From 591a180f6508f1c2a9d8f61d9206de53087469d8 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 13:32:49 -0700
Subject: [PATCH 01/11] Organise example notebooks into topical sections

- group notebooks by theme in gallery and docs navigation
- update gallery template to support sectioned cards
- add placeholder community showcase section
---
 notebooks/_templates/gallery-cards.jinja |   9 +-
 notebooks/_toc.yml                       |  31 +++---
 notebooks/gallery.yml                    | 119 ++++++++++++-----------
 3 files changed, 89 insertions(+), 70 deletions(-)

diff --git a/notebooks/_templates/gallery-cards.jinja b/notebooks/_templates/gallery-cards.jinja
index 33d8ac6..71f8097 100644
--- a/notebooks/_templates/gallery-cards.jinja
+++ b/notebooks/_templates/gallery-cards.jinja
@@ -1,7 +1,10 @@
+{% for section in data %}
+## {{ section.section }}
+
 ::::{grid} 1 2 2 3
 :gutter: 2
 
-{% for item in data %}
+{% for item in section.items %}
 :::{card}
 :link: {{ item.website or item.notebook }}
 {% if item.image %}:img-top: {{ item.image }}{% endif %}
@@ -13,4 +16,6 @@
 :::
 {% endfor %}
 
-:::: 
+::::
+
+{% endfor %}
\ No newline at end of file
diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index d5e7237..318fb1f 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -1,17 +1,22 @@
-# Table of contents
-# Learn more at https://jupyterbook.org/customize/toc.html
-
 format: jb-book
 root: index
 parts:
-  - caption: Demonstrations
-    numbered: True
+  - caption: Getting started CW
+    numbered: False
+    chapters:
+      - file: getting_started
+
+  - caption: Data processing
+    numbered: False
+    chapters:
+      - file: OOI_eclipse
+      - file: seafloor_detection
+      - file: transient_noise
+
+  - caption: Analysis workflows
+    numbered: False
     chapters:
-    - file: getting_started
-    - file: OOI_eclipse
-    - file: ship_tracks
-    - file: krill_freq_diff
-    - file: hake_mask
-    - file: glider_AZFP
-    - file: seafloor_detection
-    - file: transient_noise
+      - file: ship_tracks
+      - file: krill_freq_diff
+      - file: hake_mask
+      - file: glider_AZFP
\ No newline at end of file
diff --git a/notebooks/gallery.yml b/notebooks/gallery.yml
index 03012c9..0b28658 100644
--- a/notebooks/gallery.yml
+++ b/notebooks/gallery.yml
@@ -1,55 +1,64 @@
-- name: Getting Started with Echopype
-  website: https://echopype-examples.readthedocs.io/en/latest/getting_started.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/getting_started.ipynb
-  notebook: getting_started.ipynb
-  summary: A minimum example to get started on Echopype functions.
-  image: images/gallery/01_getting_started.png
-
-- name: Watching Eclipse from a Moored Echosounder
-  website: https://echopype-examples.readthedocs.io/en/latest/OOI_eclipse.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
-  notebook: OOI_eclipse.ipynb
-  summary: Pairing acoustic data from an upward-looking echosounder and shortwave irradiance measured by a pyrometer on a surface mooring to observe the movement response of zooplankton to a solar eclipse. (Not binder friendly.)
-  image: images/gallery/02_OOI_eclipse.png
-
-- name: Ship Tracks Visualisation
-  website: https://echopype-examples.readthedocs.io/en/latest/ship_tracks.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
-  notebook: ship_tracks.ipynb
-  summary: Subselect sections of echo data based on ship GPS data embedded in the echosounder raw files to demonstrate the power of label-aware data processing based on standardized netCDF data model. (Not binder friendly.)
-  image: images/gallery/03_subselection.png
-
-- name: Krill Frequency Differencing
-  website: https://echopype-examples.readthedocs.io/en/latest/krill_freq_diff.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
-  notebook: krill_freq_diff.ipynb
-  summary: Perform frequency-differencing analysis to identify fluid-like zooplankton scatterers (likely krill) in ship echosounder data, and compute nautical acoustic scattering coefficient (NASC) based on the classification. (Not binder friendly.)
-  image: images/gallery/04_krill.png
-
-- name: Masking Echogram and Computing NASC
-  website: https://echopype-examples.readthedocs.io/en/latest/hake_mask.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/hake_mask.ipynb
-  notebook: hake_mask.ipynb
-  summary: Incorporate an externally generated mask that identify the occurrence of Pacific hake in ship echosounder data, and compute NASC based on the masked outputs.
-  image: images/gallery/05_NASC.png
-
-- name: Glider AZFP Processing
-  website: https://echopype-examples.readthedocs.io/en/latest/glider_AZFP.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
-  notebook: glider_AZFP.ipynb
-  summary: Process acoustic data from a Slocum glider by incorporating external position, motion, and environmental data and identify zooplankton shoals.
-  image: images/gallery/06_glider.png
-
-- name: Seafloor Detection
-  website: https://echopype-examples.readthedocs.io/en/latest/seafloor_detection.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
-  notebook: seafloor_detection.ipynb
-  summary: Seafloor detection with echopype (two algorithms) and use of echoregions; compute a bottom line and mask below-bottom data.
-  image: images/gallery/07_seafloor.png
-
-- name: Transient Noise Removal
-  website: https://echopype-examples.readthedocs.io/en/latest/transient_noise.html
-  repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/transient_noise.ipynb
-  notebook: transient_noise.ipynb
-  summary: Transient noise removal with echopype (two algorithms) and exploring the effects on Sv profiles.
-  image: images/gallery/08_transient_noise.png
\ No newline at end of file
+- section: Getting started
+  items:
+    - name: Getting Started with Echopype
+      website: https://echopype-examples.readthedocs.io/en/latest/getting_started.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/getting_started.ipynb
+      notebook: getting_started.ipynb
+      summary: A minimum example to get started on Echopype functions.
+      image: images/gallery/01_getting_started.png
+
+- section: Data processing
+  items:
+    - name: Watching Eclipse from a Moored Echosounder
+      website: https://echopype-examples.readthedocs.io/en/latest/OOI_eclipse.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
+      notebook: OOI_eclipse.ipynb
+      summary: Pairing acoustic data from an upward-looking echosounder and shortwave irradiance measured by a pyrometer on a surface mooring to observe the movement response of zooplankton to a solar eclipse. (Not binder friendly.)
+      image: images/gallery/02_OOI_eclipse.png
+
+    - name: Seafloor Detection
+      website: https://echopype-examples.readthedocs.io/en/latest/seafloor_detection.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
+      notebook: seafloor_detection.ipynb
+      summary: Seafloor detection with echopype (two algorithms) and use of echoregions; compute a bottom line and mask below-bottom data.
+      image: images/gallery/07_seafloor.png
+
+    - name: Transient Noise Removal
+      website: https://echopype-examples.readthedocs.io/en/latest/transient_noise.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/transient_noise.ipynb
+      notebook: transient_noise.ipynb
+      summary: Transient noise removal with echopype (two algorithms) and exploring the effects on Sv profiles.
+      image: images/gallery/08_transient_noise.png
+
+- section: Analysis workflows
+  items:
+    - name: Ship Tracks Visualisation
+      website: https://echopype-examples.readthedocs.io/en/latest/ship_tracks.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
+      notebook: ship_tracks.ipynb
+      summary: Subselect sections of echo data based on ship GPS data embedded in the echosounder raw files to demonstrate the power of label-aware data processing based on standardized netCDF data model. (Not binder friendly.)
+      image: images/gallery/03_subselection.png
+
+    - name: Krill Frequency Differencing
+      website: https://echopype-examples.readthedocs.io/en/latest/krill_freq_diff.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
+      notebook: krill_freq_diff.ipynb
+      summary: Perform frequency-differencing analysis to identify fluid-like zooplankton scatterers (likely krill) in ship echosounder data, and compute nautical acoustic scattering coefficient (NASC) based on the classification. (Not binder friendly.)
+      image: images/gallery/04_krill.png
+
+    - name: Masking Echogram and Computing NASC
+      website: https://echopype-examples.readthedocs.io/en/latest/hake_mask.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/hake_mask.ipynb
+      notebook: hake_mask.ipynb
+      summary: Incorporate an externally generated mask that identify the occurrence of Pacific hake in ship echosounder data, and compute NASC based on the masked outputs.
+      image: images/gallery/05_NASC.png
+
+    - name: Glider AZFP Processing
+      website: https://echopype-examples.readthedocs.io/en/latest/glider_AZFP.html
+      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
+      notebook: glider_AZFP.ipynb
+      summary: Process acoustic data from a Slocum glider by incorporating external position, motion, and environmental data and identify zooplankton shoals.
+      image: images/gallery/06_glider.png
+
+- section: Community showcase
+  items: []
\ No newline at end of file

From 82df5d0f3cd0e4a64fa6182feebdcbe8eeea3149 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 13:37:04 -0700
Subject: [PATCH 02/11] fix gallery-cards

---
 notebooks/_templates/gallery-cards.jinja | 9 ++++-----
 1 file changed, 4 insertions(+), 5 deletions(-)

diff --git a/notebooks/_templates/gallery-cards.jinja b/notebooks/_templates/gallery-cards.jinja
index 71f8097..0c14792 100644
--- a/notebooks/_templates/gallery-cards.jinja
+++ b/notebooks/_templates/gallery-cards.jinja
@@ -1,10 +1,10 @@
-{% for section in data %}
-## {{ section.section }}
-
 ::::{grid} 1 2 2 3
 :gutter: 2
 
-{% for item in section.items %}
+{% for section in data %}
+## {{ section["section"] }}
+
+{% for item in section["items"] %}
 :::{card}
 :link: {{ item.website or item.notebook }}
 {% if item.image %}:img-top: {{ item.image }}{% endif %}
@@ -17,5 +17,4 @@
 {% endfor %}
 
 ::::
-
 {% endfor %}
\ No newline at end of file

From 59ef9f7e79b9094697735e542ef8bec87b8df303 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 13:45:03 -0700
Subject: [PATCH 03/11] Update gallery-cards.jinja

---
 notebooks/_templates/gallery-cards.jinja | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/notebooks/_templates/gallery-cards.jinja b/notebooks/_templates/gallery-cards.jinja
index 0c14792..fe7a544 100644
--- a/notebooks/_templates/gallery-cards.jinja
+++ b/notebooks/_templates/gallery-cards.jinja
@@ -1,9 +1,11 @@
-::::{grid} 1 2 2 3
-:gutter: 2
-
 {% for section in data %}
+
 ## {{ section["section"] }}
 
+::::{grid} 1 2 3 4
+:gutter: 2
+:class-container: gallery-grid
+
 {% for item in section["items"] %}
 :::{card}
 :link: {{ item.website or item.notebook }}
@@ -17,4 +19,5 @@
 {% endfor %}
 
 ::::
+
 {% endfor %}
\ No newline at end of file

From eba9b9508e6fbc3e2f09295d9ea73dddcc178d86 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 13:55:21 -0700
Subject: [PATCH 04/11] final reshape

---
 notebooks/_templates/gallery-cards.jinja |  2 +-
 notebooks/_toc.yml                       |  6 +++++-
 notebooks/index.md                       | 12 +++++-------
 3 files changed, 11 insertions(+), 9 deletions(-)

diff --git a/notebooks/_templates/gallery-cards.jinja b/notebooks/_templates/gallery-cards.jinja
index fe7a544..544f86f 100644
--- a/notebooks/_templates/gallery-cards.jinja
+++ b/notebooks/_templates/gallery-cards.jinja
@@ -2,7 +2,7 @@
 
 ## {{ section["section"] }}
 
-::::{grid} 1 2 3 4
+::::{grid} 1 2 2 3
 :gutter: 2
 :class-container: gallery-grid
 
diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index 318fb1f..bc63526 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -19,4 +19,8 @@ parts:
       - file: ship_tracks
       - file: krill_freq_diff
       - file: hake_mask
-      - file: glider_AZFP
\ No newline at end of file
+      - file: glider_AZFP
+
+  - caption: Community showcase
+    numbered: False
+    chapters: []
\ No newline at end of file
diff --git a/notebooks/index.md b/notebooks/index.md
index 2610d48..7198cd3 100644
--- a/notebooks/index.md
+++ b/notebooks/index.md
@@ -1,6 +1,10 @@
 # Echopype examples notebooks
 
-Jupyter notebooks demonstrating [Echopype](https://echopype.readthedocs.io) capabilities and usage.
+Jupyter notebooks demonstrating [Echopype](https://echopype.readthedocs.io) capabilities and usage. The notebooks in this site can be run locally with a [conda](https://docs.conda.io) environment created following the [instructions in the repository README.md](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-locally-on-your-machine).
+
+If you want to try these notebooks on Binder, follow instructions [here](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-on-the-cloud-via-binder). However, due to the limited resources on Binder, the execution of some notebooks may fail as noted above.
+
+Please see the last cell in each notebook to see the version of Echopype and important dependencies the notebook was last run with.
 
 ## Gallery
 
@@ -8,10 +12,4 @@ Jupyter notebooks demonstrating [Echopype](https://echopype.readthedocs.io) capa
 :template: gallery-cards.jinja
 ```
 
-## Running the notebooks
 
-The notebooks in this site can be run locally with a [conda](https://docs.conda.io) environment created following the [instructions in the repository README.md](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-locally-on-your-machine).
-
-If you want to try these notebooks on Binder, follow instructions [here](https://github.com/OSOceanAcoustics/echopype-examples#run-the-notebooks-on-the-cloud-via-binder). However, due to the limited resources on Binder, the execution of some notebooks may fail as noted above.
-
-Please see the last cell in each notebook to see the version of Echopype and important dependencies the notebook was last run with.

From 937a454dc2cd02c90f91db73eff86f11d78f73e7 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 14:00:12 -0700
Subject: [PATCH 05/11] add temporary community showcase file

---
 notebooks/community_showcase.md | 6 ++++++
 1 file changed, 6 insertions(+)
 create mode 100644 notebooks/community_showcase.md

diff --git a/notebooks/community_showcase.md b/notebooks/community_showcase.md
new file mode 100644
index 0000000..90c90f0
--- /dev/null
+++ b/notebooks/community_showcase.md
@@ -0,0 +1,6 @@
+# Community showcase
+
+Examples from the echopype community will be highlighted here.
+If you are using echopype in your own workflows, feel free to open an issue or pull request to suggest an example notebook!
+
+(Temporary file to remove)
\ No newline at end of file

From 402b247bc8636a595f69976a331358ac017f43ad Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Mon, 18 May 2026 14:03:17 -0700
Subject: [PATCH 06/11] Update _toc.yml

---
 notebooks/_toc.yml | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index bc63526..77f72ab 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -23,4 +23,5 @@ parts:
 
   - caption: Community showcase
     numbered: False
-    chapters: []
\ No newline at end of file
+    chapters:
+      - file: community_showcase
\ No newline at end of file

From 0c43509c0457167c579dce26a75d11c4587d2353 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Thu, 4 Jun 2026 17:19:34 -0700
Subject: [PATCH 07/11] small modifs

- removed "Gallery" to start directly with the actual sections
---
 notebooks/_toc.yml | 2 +-
 notebooks/index.md | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index 77f72ab..05e9291 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -1,7 +1,7 @@
 format: jb-book
 root: index
 parts:
-  - caption: Getting started CW
+  - caption: Getting started
     numbered: False
     chapters:
       - file: getting_started
diff --git a/notebooks/index.md b/notebooks/index.md
index 7198cd3..eb23f4b 100644
--- a/notebooks/index.md
+++ b/notebooks/index.md
@@ -6,7 +6,7 @@ If you want to try these notebooks on Binder, follow instructions [here](https:/
 
 Please see the last cell in each notebook to see the version of Echopype and important dependencies the notebook was last run with.
 
-## Gallery
+<!-- show the gallery -->
 
 ```{datatemplate:yaml} gallery.yml
 :template: gallery-cards.jinja

From cfa5928bc8a1b81973d5f549633b159ff5e68d49 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Sun, 7 Jun 2026 15:37:59 -0700
Subject: [PATCH 08/11] Adding firt version of FM TS notebook

---
 .gitignore                                    |     3 +
 conda/environment-ep-main.yml                 |     1 +
 conda/environment.yml                         |     1 +
 notebooks/_toc.yml                            |     1 +
 notebooks/gallery.yml                         |    23 +-
 notebooks/getting_started_FM_TS.ipynb         | 11348 ++++++++++++++++
 .../gallery/11_getting_started_FM_TS.png      |   Bin 0 -> 641978 bytes
 notebooks/utils/data.py                       |    62 +
 8 files changed, 11431 insertions(+), 8 deletions(-)
 create mode 100644 notebooks/getting_started_FM_TS.ipynb
 create mode 100644 notebooks/images/gallery/11_getting_started_FM_TS.png
 create mode 100644 notebooks/utils/data.py

diff --git a/.gitignore b/.gitignore
index d32ae4e..9bf58c0 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,6 +6,9 @@ __pycache__/
 # C extensions
 *.so
 
+# Example datasetss
+notebooks/example_data/ts_spectrum_example_data/
+
 # Distribution / packaging
 .Python
 build/
diff --git a/conda/environment-ep-main.yml b/conda/environment-ep-main.yml
index ff8889a..63902aa 100644
--- a/conda/environment-ep-main.yml
+++ b/conda/environment-ep-main.yml
@@ -12,6 +12,7 @@ dependencies:
   - numba # Helps ensure a recent version is installed
   - numpy<2
   - pip
+  - pooch
   # -- holoviz --
   - jupyter_bokeh
   - datashader
diff --git a/conda/environment.yml b/conda/environment.yml
index 7d86500..6bd6644 100644
--- a/conda/environment.yml
+++ b/conda/environment.yml
@@ -10,6 +10,7 @@ dependencies:
   - cartopy
   - scipy
   - numba # Helps ensure a recent version is installed
+  - pooch
   # -- holoviz --
   - jupyter_bokeh
   - datashader
diff --git a/notebooks/_toc.yml b/notebooks/_toc.yml
index 05e9291..d4ce5f0 100644
--- a/notebooks/_toc.yml
+++ b/notebooks/_toc.yml
@@ -5,6 +5,7 @@ parts:
     numbered: False
     chapters:
       - file: getting_started
+      - file: getting_started_FM_TS
 
   - caption: Data processing
     numbered: False
diff --git a/notebooks/gallery.yml b/notebooks/gallery.yml
index 0b28658..f152871 100644
--- a/notebooks/gallery.yml
+++ b/notebooks/gallery.yml
@@ -2,30 +2,37 @@
   items:
     - name: Getting Started with Echopype
       website: https://echopype-examples.readthedocs.io/en/latest/getting_started.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/getting_started.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/getting_started.ipynb
       notebook: getting_started.ipynb
       summary: A minimum example to get started on Echopype functions.
       image: images/gallery/01_getting_started.png
+      
+    - name: Getting Started with Echopype for broadband TS
+      website: https://echopype-examples.readthedocs.io/en/latest/getting_started_FM_TS.html
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/getting_started_FM_TS.ipynb
+      notebook: getting_started_FM_TS.ipynb
+      summary: A minimum example to get started on Echopype functions for broadband target strength (TS) estimation.
+      image: images/gallery/11_getting_started_FM_TS.png
 
 - section: Data processing
   items:
     - name: Watching Eclipse from a Moored Echosounder
       website: https://echopype-examples.readthedocs.io/en/latest/OOI_eclipse.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/OOI_eclipse.ipynb
       notebook: OOI_eclipse.ipynb
       summary: Pairing acoustic data from an upward-looking echosounder and shortwave irradiance measured by a pyrometer on a surface mooring to observe the movement response of zooplankton to a solar eclipse. (Not binder friendly.)
       image: images/gallery/02_OOI_eclipse.png
 
     - name: Seafloor Detection
       website: https://echopype-examples.readthedocs.io/en/latest/seafloor_detection.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/seafloor_detection.ipynb
       notebook: seafloor_detection.ipynb
       summary: Seafloor detection with echopype (two algorithms) and use of echoregions; compute a bottom line and mask below-bottom data.
       image: images/gallery/07_seafloor.png
 
     - name: Transient Noise Removal
       website: https://echopype-examples.readthedocs.io/en/latest/transient_noise.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/transient_noise.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/transient_noise.ipynb
       notebook: transient_noise.ipynb
       summary: Transient noise removal with echopype (two algorithms) and exploring the effects on Sv profiles.
       image: images/gallery/08_transient_noise.png
@@ -34,28 +41,28 @@
   items:
     - name: Ship Tracks Visualisation
       website: https://echopype-examples.readthedocs.io/en/latest/ship_tracks.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/ship_tracks.ipynb
       notebook: ship_tracks.ipynb
       summary: Subselect sections of echo data based on ship GPS data embedded in the echosounder raw files to demonstrate the power of label-aware data processing based on standardized netCDF data model. (Not binder friendly.)
       image: images/gallery/03_subselection.png
 
     - name: Krill Frequency Differencing
       website: https://echopype-examples.readthedocs.io/en/latest/krill_freq_diff.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/krill_freq_diff.ipynb
       notebook: krill_freq_diff.ipynb
       summary: Perform frequency-differencing analysis to identify fluid-like zooplankton scatterers (likely krill) in ship echosounder data, and compute nautical acoustic scattering coefficient (NASC) based on the classification. (Not binder friendly.)
       image: images/gallery/04_krill.png
 
     - name: Masking Echogram and Computing NASC
       website: https://echopype-examples.readthedocs.io/en/latest/hake_mask.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/hake_mask.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/hake_mask.ipynb
       notebook: hake_mask.ipynb
       summary: Incorporate an externally generated mask that identify the occurrence of Pacific hake in ship echosounder data, and compute NASC based on the masked outputs.
       image: images/gallery/05_NASC.png
 
     - name: Glider AZFP Processing
       website: https://echopype-examples.readthedocs.io/en/latest/glider_AZFP.html
-      repository: https://github.com/OSOceanAcoustics/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
+      repository: https://github.com/echostack-org/echopype-examples/blob/main/notebooks/glider_AZFP.ipynb
       notebook: glider_AZFP.ipynb
       summary: Process acoustic data from a Slocum glider by incorporating external position, motion, and environmental data and identify zooplankton shoals.
       image: images/gallery/06_glider.png
diff --git a/notebooks/getting_started_FM_TS.ipynb b/notebooks/getting_started_FM_TS.ipynb
new file mode 100644
index 0000000..388ccfd
--- /dev/null
+++ b/notebooks/getting_started_FM_TS.ipynb
@@ -0,0 +1,11348 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "64087514",
+   "metadata": {},
+   "source": [
+    "## Broadband TS spectrum validation against CRIMAC\n",
+    "\n",
+    "This notebook demonstrates a minimal workflow for computing broadband target-strength spectra (`TS_spectrum`) with echopype from EK80 FM data.\n",
+    "\n",
+    "The results are compared against the CRIMAC reference implementation described in Andersen et al. (2024). The comparison examines intermediate processing steps as well as the final TS spectrum estimates.\n",
+    "\n",
+    "Reference implementation:\n",
+    "- Andersen, L. N. et al. (2024). *Quantitative processing of broadband data as implemented in a scientific split-beam echosounder*. Methods in Ecology and Evolution, 15(2), 317–328. https://doi.org/10.1111/2041-210X.14261\n",
+    "- CRIMAC repository: https://github.com/CRIMAC-WP4-Machine-learning/CRIMAC-Raw-To-Svf-TSf\n",
+    "\n",
+    "Reference case:\n",
+    "\n",
+    "- Raw file: `IMR-D20211215-T143432-TSf.raw`\n",
+    "- Channel: `WBT 747022-15 ES120-7CD_ES`\n",
+    "- CRIMAC ping number: 510\n",
+    "- Python ping index: 509"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "869dd6a1",
+   "metadata": {},
+   "source": [
+    "The notebook follows the processing chain step by step:\n",
+    "\n",
+    "- Open the raw EK80 file\n",
+    "- Load the exported CRIMAC reference outputs\n",
+    "- Initialise the EK80 calibration object\n",
+    "- Rebuild the transmit signal and matched filter\n",
+    "- Pulse-compress the complex samples\n",
+    "- Convert pulse-compressed signals to received power\n",
+    "- Reproduce broadband point scattering strength, `Sp`\n",
+    "- Compute split-beam angles\n",
+    "- Identify the calibration sphere target\n",
+    "- Align the matched-filter autocorrelation with the target echo\n",
+    "- Compute the target and matched-filter spectra\n",
+    "- Compute the beam-compensated gain\n",
+    "- Compute the final calibrated `TS(f)`\n",
+    "- Validate the result against the public `compute_TS_spectrum()` API"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6525b719",
+   "metadata": {},
+   "source": [
+    "We start by importing the necessary libraries."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a253416f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from pathlib import Path\n",
+    "\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import xarray as xr\n",
+    "\n",
+    "import echopype as ep\n",
+    "\n",
+    "from echopype.calibrate.calibrate_ek import CalibrateEK80\n",
+    "from echopype.calibrate.ek80_complex import (\n",
+    "    get_filter_coeff,\n",
+    "    get_transmit_signal,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2e299118",
+   "metadata": {},
+   "source": [
+    "If the example data are not already available locally, they will be downloaded from the GitHub release asset, verified with a SHA256 checksum, and extracted into the local `example_data/` folder."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c0fefef8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Using local dataset: example_data\\ts_spectrum_example_data\n"
+     ]
+    }
+   ],
+   "source": [
+    "from utils.data import fetch_dataset\n",
+    "data_dir = fetch_dataset(\"ts_spectrum_example_data\")\n",
+    "\n",
+    "raw_file_TS = data_dir / \"IMR-D20211215-T143432-TSf.raw\"\n",
+    "ref_file_TS = data_dir / \"crimac_tsf_reference_outputs.npz\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "662202fc",
+   "metadata": {},
+   "source": [
+    "We convert the raw data to echodata object."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "cdedca3c",
+   "metadata": {},
+   "outputs": [
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+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 0B\n",
+       "Dimensions:  ()\n",
+       "Data variables:\n",
+       "    *empty*\n",
+       "Attributes:\n",
+       "    conventions:                 CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3\n",
+       "    keywords:                    EK80\n",
+       "    sonar_convention_authority:  ICES\n",
+       "    sonar_convention_name:       SONAR-netCDF4\n",
+       "    sonar_convention_version:    1.0\n",
+       "    summary:                     \n",
+       "    title:                       \n",
+       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                </ul>\n",
+       "            </div>\n",
+       "        </li>\n",
+       "        <ul><li class=\"xr-section-list\"><input id=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 140B\n",
+       "Dimensions:                       (time1: 1, sound_velocity_profile_depth: 2)\n",
+       "Coordinates:\n",
+       "  * time1                         (time1) datetime64[ns] 8B 2021-12-15T14:34:...\n",
+       "  * sound_velocity_profile_depth  (sound_velocity_profile_depth) float64 16B ...\n",
+       "Data variables:\n",
+       "    depth                         (time1) float64 8B 5.0\n",
+       "    acidity                       (time1) float64 8B 8.0\n",
+       "    salinity                      (time1) float64 8B 32.0\n",
+       "    temperature                   (time1) float64 8B 9.7\n",
+       "    sound_speed_indicative        (time1) float64 8B 1.485e+03\n",
+       "    sound_velocity_profile        (time1, sound_velocity_profile_depth) float64 16B ...\n",
+       "    sound_velocity_source         (time1) &lt;U6 24B &#x27;Manual&#x27;\n",
+       "    transducer_name               (time1) &lt;U7 28B &#x27;Unknown&#x27;\n",
+       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' class='xr-var-data-in' type='checkbox'><label for='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb51444-8504-4048-91ca-33ba4d52f994' class='xr-var-data-in' type='checkbox'><label for='data-ecb51444-8504-4048-91ca-33ba4d52f994' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99a428ea-3629-4401-ab2b-63b36abda345' class='xr-var-data-in' type='checkbox'><label for='data-99a428ea-3629-4401-ab2b-63b36abda345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19f8335a-e760-4b87-bb47-f6741b807beb' class='xr-var-data-in' type='checkbox'><label for='data-19f8335a-e760-4b87-bb47-f6741b807beb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93263a4-e12b-46de-8ecd-9f93580c4065' class='xr-var-data-in' type='checkbox'><label for='data-a93263a4-e12b-46de-8ecd-9f93580c4065' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0f49309-8d87-466c-9340-4b0494611c41' class='xr-var-data-in' type='checkbox'><label for='data-b0f49309-8d87-466c-9340-4b0494611c41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' class='xr-var-data-in' type='checkbox'><label for='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' class='xr-var-data-in' type='checkbox'><label for='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' class='xr-var-data-in' type='checkbox'><label for='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-5811d654-a60f-46c2-a651-d650e32e3558' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5811d654-a60f-46c2-a651-d650e32e3558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' class='xr-var-data-in' type='checkbox'><label for='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' class='xr-var-data-in' type='checkbox'><label for='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
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+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
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+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 51kB\n",
+       "Dimensions:                      (time1: 1, time2: 1266, channel: 4, time3: 1)\n",
+       "Coordinates:\n",
+       "  * time1                        (time1) datetime64[ns] 8B 2021-12-15T14:34:3...\n",
+       "  * time2                        (time2) datetime64[ns] 10kB 2021-12-15T14:34...\n",
+       "  * channel                      (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD...\n",
+       "  * time3                        (time3) datetime64[ns] 8B 2021-12-15T14:34:3...\n",
+       "Data variables: (12/26)\n",
+       "    latitude                     (time1) float64 8B nan\n",
+       "    longitude                    (time1) float64 8B nan\n",
+       "    sentence_type                (time1) float64 8B nan\n",
+       "    pitch                        (time2) float64 10kB 0.34 0.34 ... -2.02 -2.02\n",
+       "    roll                         (time2) float64 10kB 1.73 1.73 ... -2.93 -2.93\n",
+       "    vertical_offset              (time2) float64 10kB 0.0 0.0 0.0 ... 0.0 0.0\n",
+       "    ...                           ...\n",
+       "    position_offset_y            float64 8B nan\n",
+       "    position_offset_z            float64 8B nan\n",
+       "    frequency_nominal            (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    heading                      (time2) float64 10kB 1.46 1.46 ... 0.04 0.04\n",
+       "    latitude_mru1                (time3) float64 8B nan\n",
+       "    longitude_mru1               (time3) float64 8B nan\n",
+       "Attributes:\n",
+       "    platform_name:       \n",
+       "    platform_type:       \n",
+       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary-in' type='checkbox' checked /><label for='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab95c796-b965-431b-84cc-b90afd18dfe9' class='xr-var-data-in' type='checkbox'><label for='data-ab95c796-b965-431b-84cc-b90afd18dfe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f55aec-928e-45a5-949f-13ecff064c74' class='xr-var-data-in' type='checkbox'><label for='data-b3f55aec-928e-45a5-949f-13ecff064c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c26d213-1db8-4e55-a36f-dab5efc95118' class='xr-var-data-in' type='checkbox'><label for='data-5c26d213-1db8-4e55-a36f-dab5efc95118' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' class='xr-var-data-in' type='checkbox'><label for='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary-in' type='checkbox' /><label for='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' class='xr-var-data-in' type='checkbox'><label for='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' class='xr-var-data-in' type='checkbox'><label for='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' class='xr-var-data-in' type='checkbox'><label for='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' class='xr-var-data-in' type='checkbox'><label for='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
+       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' class='xr-var-data-in' type='checkbox'><label for='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
+       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709d9ff4-18f2-46eb-9891-e99e3515254a' class='xr-var-data-in' type='checkbox'><label for='data-709d9ff4-18f2-46eb-9891-e99e3515254a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-14d0cfaa-9749-4191-88ec-374084a85065' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d0cfaa-9749-4191-88ec-374084a85065' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a555a503-503d-48a8-951c-1f579f65f422' class='xr-var-data-in' type='checkbox'><label for='data-a555a503-503d-48a8-951c-1f579f65f422' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' class='xr-var-data-in' type='checkbox'><label for='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52fbb06a-63bb-4af9-9273-a0da085733b0' class='xr-var-data-in' type='checkbox'><label for='data-52fbb06a-63bb-4af9-9273-a0da085733b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645f875e-cc4c-4258-95df-c4fd81552ab3' class='xr-var-data-in' type='checkbox'><label for='data-645f875e-cc4c-4258-95df-c4fd81552ab3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-329ac06e-93ef-44f5-a152-855c5435d2c2' class='xr-var-data-in' type='checkbox'><label for='data-329ac06e-93ef-44f5-a152-855c5435d2c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' class='xr-var-data-in' type='checkbox'><label for='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4b81604-260d-4a6d-a624-5dcf237a9900' class='xr-var-data-in' type='checkbox'><label for='data-b4b81604-260d-4a6d-a624-5dcf237a9900' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f5a315-63bb-4997-952e-941d5f9daf96' class='xr-var-data-in' type='checkbox'><label for='data-f4f5a315-63bb-4997-952e-941d5f9daf96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d947a1e-70d0-4799-990e-28818e73c395' class='xr-var-data-in' type='checkbox'><label for='data-0d947a1e-70d0-4799-990e-28818e73c395' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-605efc77-57a5-419c-9eea-094559be13cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-605efc77-57a5-419c-9eea-094559be13cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8907418-c9c4-4d7c-b695-924d66a887cb' class='xr-var-data-in' type='checkbox'><label for='data-e8907418-c9c4-4d7c-b695-924d66a887cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01ee79d2-a225-4654-a1a0-3a91893606e2' class='xr-var-data-in' type='checkbox'><label for='data-01ee79d2-a225-4654-a1a0-3a91893606e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' class='xr-var-data-in' type='checkbox'><label for='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39cd0982-2040-45a4-8657-b5480a3e716a' class='xr-var-data-in' type='checkbox'><label for='data-39cd0982-2040-45a4-8657-b5480a3e716a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' class='xr-var-data-in' type='checkbox'><label for='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e49fc1f-279d-415d-9a59-63632374f332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e49fc1f-279d-415d-9a59-63632374f332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d06d2472-0b2c-428d-b514-25edb42980cc' class='xr-var-data-in' type='checkbox'><label for='data-d06d2472-0b2c-428d-b514-25edb42980cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' class='xr-var-data-in' type='checkbox'><label for='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b397824-3621-4c3e-9d37-80438b40784b' class='xr-var-data-in' type='checkbox'><label for='data-7b397824-3621-4c3e-9d37-80438b40784b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-90335375-4392-4c89-8cae-8b4abf21501b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90335375-4392-4c89-8cae-8b4abf21501b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' class='xr-var-data-in' type='checkbox'><label for='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
+       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' class='xr-var-data-in' type='checkbox'><label for='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57712bcf-48f1-44cf-a77a-76a5740c054d' class='xr-var-data-in' type='checkbox'><label for='data-57712bcf-48f1-44cf-a77a-76a5740c054d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 498kB\n",
+       "Dimensions:        (nmea_time: 4351, channel: 4, time1: 1, time2: 1266, time3: 1)\n",
+       "Coordinates:\n",
+       "  * nmea_time      (nmea_time) datetime64[ns] 35kB 2021-12-15T14:34:32.661453...\n",
+       "  * channel        (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD_ES&#x27; ... &#x27;WBT ...\n",
+       "  * time1          (time1) datetime64[ns] 8B 2021-12-15T14:34:32.661453\n",
+       "  * time2          (time2) datetime64[ns] 10kB 2021-12-15T14:34:32.661453 ......\n",
+       "  * time3          (time3) datetime64[ns] 8B 2021-12-15T14:34:32.661453\n",
+       "Data variables:\n",
+       "    NMEA_datagram  (nmea_time) &lt;U26 453kB &#x27;$SDVLW,630.103,N,630.103,N&#x27; ... &#x27;$...\n",
+       "Attributes:\n",
+       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' class='xr-var-data-in' type='checkbox'><label for='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:32.825344000&#x27;, ..., &#x27;2021-12-15T14:40:09.311146000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.381834000&#x27;, &#x27;2021-12-15T14:40:09.456507000&#x27;],\n",
+       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' class='xr-var-data-in' type='checkbox'><label for='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b098e67-f7cc-4575-bee6-8012f6813583' class='xr-var-data-in' type='checkbox'><label for='data-7b098e67-f7cc-4575-bee6-8012f6813583' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-6d40e0da-897e-4236-b098-9b81ad544362' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d40e0da-897e-4236-b098-9b81ad544362' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' class='xr-var-data-in' type='checkbox'><label for='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' class='xr-var-data-in' type='checkbox'><label for='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' class='xr-var-data-in' type='checkbox'><label for='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, ..., &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;],\n",
+       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
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+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
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+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
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+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
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+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
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+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
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+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
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+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
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+       "\n",
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+       "  display: contents;\n",
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+       "\n",
+       ".xr-section-item > input,\n",
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+       "  opacity: 0;\n",
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+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
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+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
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+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
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+       "  padding-top: 4px;\n",
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+       "\n",
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+       "\n",
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+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
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+       "\n",
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+       "\n",
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+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
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+       "\n",
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+       "\n",
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+       "\n",
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+       "\n",
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+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 276B\n",
+       "Dimensions:           (filenames: 1)\n",
+       "Coordinates:\n",
+       "  * filenames         (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    source_filenames  (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_exampl...\n",
+       "Attributes:\n",
+       "    conversion_software_name:     echopype\n",
+       "    conversion_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    conversion_time:              2026-06-07T01:36:12+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' class='xr-var-data-in' type='checkbox'><label for='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary-in' type='checkbox' checked /><label for='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' class='xr-var-data-in' type='checkbox'><label for='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary-in' type='checkbox' checked /><label for='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>conversion_time :</span></dt><dd>2026-06-07T01:36:12+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 1kB\n",
+       "Dimensions:                    (channel_all: 4, beam_group: 1,\n",
+       "                                beam_group_index: 1)\n",
+       "Coordinates:\n",
+       "  * channel_all                (channel_all) &lt;U26 416B &#x27;WBT 747008-15 ES333-7...\n",
+       "  * beam_group                 (beam_group) &lt;U11 44B &#x27;Beam_group1&#x27;\n",
+       "  * beam_group_index           (beam_group_index) int64 8B 1\n",
+       "Data variables:\n",
+       "    frequency_nominal          (channel_all) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    transceiver_serial_number  (channel_all) &lt;U6 96B &#x27;747008&#x27; ... &#x27;747022&#x27;\n",
+       "    transducer_name            (channel_all) &lt;U9 144B &#x27;ES333-7CD&#x27; ... &#x27;ES120-...\n",
+       "    transducer_serial_number   (channel_all) &lt;U3 48B &#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;\n",
+       "    beam_group_descr           (beam_group) &lt;U93 372B &#x27;contains FM-only or CW...\n",
+       "    waveform_encode_descr      (beam_group_index) &lt;U10 40B &#x27;complex_FM&#x27;\n",
+       "Attributes:\n",
+       "    sonar_manufacturer:      Simrad\n",
+       "    sonar_model:             EK80\n",
+       "    sonar_serial_number:     \n",
+       "    sonar_software_name:     \n",
+       "    sonar_software_version:  21.15.0.0\n",
+       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary-in' type='checkbox' checked /><label for='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' class='xr-var-data-in' type='checkbox'><label for='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-352c90ce-63d6-43dd-a379-4ef29c737f93' class='xr-var-data-in' type='checkbox'><label for='data-352c90ce-63d6-43dd-a379-4ef29c737f93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104fae87-c879-4dac-ad2e-76793d4133fe' class='xr-var-data-in' type='checkbox'><label for='data-104fae87-c879-4dac-ad2e-76793d4133fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary-in' type='checkbox' checked /><label for='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' class='xr-var-data-in' type='checkbox'><label for='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-227846be-941f-4c58-bbae-d7165c294b5e' class='xr-var-data-in' type='checkbox'><label for='data-227846be-941f-4c58-bbae-d7165c294b5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' class='xr-var-data-in' type='checkbox'><label for='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-2604b084-77b2-4b4c-be79-1dc555332999' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2604b084-77b2-4b4c-be79-1dc555332999' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc285f4-b477-42d1-b12e-5aed80267bcf' class='xr-var-data-in' type='checkbox'><label for='data-adc285f4-b477-42d1-b12e-5aed80267bcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' class='xr-var-data-in' type='checkbox'><label for='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
+       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-bcecb8bb-c4c6-419f-b176-284128395853' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bcecb8bb-c4c6-419f-b176-284128395853' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' class='xr-var-data-in' type='checkbox'><label for='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 1GB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, beam: 4,\n",
+       "                                    channel_all: 4, beam_group_index: 1,\n",
+       "                                    beam_group: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * beam                           (beam) &lt;U21 336B &#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;\n",
+       "  * channel_all                    (channel_all) &lt;U26 416B &#x27;WBT 747008-15 ES3...\n",
+       "  * beam_group_index               (beam_group_index) int64 8B 1\n",
+       "  * beam_group                     (beam_group) &lt;U11 44B &#x27;Beam_group1&#x27;\n",
+       "Data variables: (12/26)\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    beam_type                      (channel) int64 32B 1 1 1 1\n",
+       "    beamwidth_twoway_alongship     (channel) float64 32B 6.73 6.96 6.79 7.26\n",
+       "    beamwidth_twoway_athwartship   (channel) float64 32B 6.77 6.87 6.85 7.28\n",
+       "    beam_direction_x               (channel) float64 32B nan nan nan nan\n",
+       "    beam_direction_y               (channel) float64 32B nan nan nan nan\n",
+       "    ...                             ...\n",
+       "    slope                          (channel, ping_time) float64 41kB 0.003488...\n",
+       "    channel_mode                   (channel, ping_time) float32 20kB 1.0 ... nan\n",
+       "    transmit_type                  (channel, ping_time) object 41kB &#x27;LFM&#x27; ......\n",
+       "    sample_time_offset             (channel, ping_time) float64 41kB 0.0 ... nan\n",
+       "    transmit_frequency_start       (channel, ping_time) float64 41kB 2.8e+05 ...\n",
+       "    transmit_frequency_stop        (channel, ping_time) float64 41kB 3.8e+05 ...\n",
+       "Attributes:\n",
+       "    beam_mode:              vertical\n",
+       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' class='xr-var-data-in' type='checkbox'><label for='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e77e00ec-8265-406d-a839-6096b403b5e6' class='xr-var-data-in' type='checkbox'><label for='data-e77e00ec-8265-406d-a839-6096b403b5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' class='xr-var-data-in' type='checkbox'><label for='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' class='xr-var-data-in' type='checkbox'><label for='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' class='xr-var-data-in' type='checkbox'><label for='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' class='xr-var-data-in' type='checkbox'><label for='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f7eebb-f987-41bc-b281-9a73bb52e909' class='xr-var-data-in' type='checkbox'><label for='data-05f7eebb-f987-41bc-b281-9a73bb52e909' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary-in' type='checkbox' /><label for='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b1189cc-612f-48b0-b19b-9bd38a116135' class='xr-var-data-in' type='checkbox'><label for='data-2b1189cc-612f-48b0-b19b-9bd38a116135' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' class='xr-var-data-in' type='checkbox'><label for='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' class='xr-var-data-in' type='checkbox'><label for='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' class='xr-var-data-in' type='checkbox'><label for='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-e954c18d-521b-4e32-b06c-2928190552b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e954c18d-521b-4e32-b06c-2928190552b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' class='xr-var-data-in' type='checkbox'><label for='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a083cd-dd78-4efe-82aa-fb211490fc15' class='xr-var-data-in' type='checkbox'><label for='data-04a083cd-dd78-4efe-82aa-fb211490fc15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96279542-2cb0-4f72-ad52-e39977c8ec54' class='xr-var-data-in' type='checkbox'><label for='data-96279542-2cb0-4f72-ad52-e39977c8ec54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd542c66-33c7-459d-81c7-d0408424151c' class='xr-var-data-in' type='checkbox'><label for='data-dd542c66-33c7-459d-81c7-d0408424151c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-9582c736-a650-427b-abec-4dae0485bced' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9582c736-a650-427b-abec-4dae0485bced' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d566cb28-7a2a-4669-b722-71588c862d66' class='xr-var-data-in' type='checkbox'><label for='data-d566cb28-7a2a-4669-b722-71588c862d66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' class='xr-var-data-in' type='checkbox'><label for='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' class='xr-var-data-in' type='checkbox'><label for='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' class='xr-var-data-in' type='checkbox'><label for='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' class='xr-var-data-in' type='checkbox'><label for='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd4e1859-70be-4cef-a044-45355c93fda3' class='xr-var-data-in' type='checkbox'><label for='data-dd4e1859-70be-4cef-a044-45355c93fda3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-25863a44-d6cb-4064-8030-d82e317da970' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25863a44-d6cb-4064-8030-d82e317da970' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' class='xr-var-data-in' type='checkbox'><label for='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' class='xr-var-data-in' type='checkbox'><label for='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
+       "          -3.96171856e-07],\n",
+       "         [-2.57343663e-06,  2.95345012e-06, -3.57061339e-07,\n",
+       "          -4.56580392e-06],\n",
+       "         [ 3.29502800e-05, -4.48711071e-05, -2.65489780e-05,\n",
+       "           3.19184528e-06],\n",
+       "         ...,\n",
+       "         [-5.15527026e-05,  3.61862447e-04,  4.46741295e-04,\n",
+       "           9.19265494e-06],\n",
+       "         [-3.07514332e-04,  4.12420253e-04,  5.00583847e-04,\n",
+       "          -1.36591814e-04],\n",
+       "         [-3.16080404e-04,  1.67110382e-04,  2.05256962e-04,\n",
+       "          -2.96069280e-04]],\n",
+       "\n",
+       "        [[ 3.04275636e-06,  1.86782506e-06, -2.01816974e-07,\n",
+       "          -2.56592944e-06],\n",
+       "         [-1.16343890e-05,  8.68735242e-07, -7.25317477e-07,\n",
+       "           1.69276484e-06],\n",
+       "         [-2.35087555e-05,  7.90977992e-06, -2.92311088e-05,\n",
+       "          -1.68325369e-05],\n",
+       "...\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]],\n",
+       "\n",
+       "        [[            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         ...,\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' class='xr-var-data-in' type='checkbox'><label for='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
+       "          -3.68357291e-06],\n",
+       "         [-6.13030397e-06,  9.28021564e-06,  3.91020649e-06,\n",
+       "          -3.28862302e-06],\n",
+       "         [-2.67872038e-05, -9.96628387e-06,  8.83363555e-06,\n",
+       "          -3.67659850e-05],\n",
+       "         ...,\n",
+       "         [-2.75080121e-04,  1.48990759e-04,  1.45175451e-04,\n",
+       "          -3.60909820e-04],\n",
+       "         [-1.56141366e-04, -2.44574185e-04, -1.55665955e-04,\n",
+       "          -2.41969436e-04],\n",
+       "         [ 1.19555603e-04, -5.27278928e-04, -5.00589900e-04,\n",
+       "          -1.23716411e-04]],\n",
+       "\n",
+       "        [[-2.38715370e-06,  1.20847983e-06, -4.15739777e-07,\n",
+       "           7.34627577e-07],\n",
+       "         [ 5.83230258e-06, -1.54376824e-06,  1.94760219e-06,\n",
+       "           4.64016330e-06],\n",
+       "         [-8.37771586e-05,  2.59587637e-06, -3.51226549e-06,\n",
+       "           3.85061730e-06],\n",
+       "...\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]],\n",
+       "\n",
+       "        [[            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         ...,\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan],\n",
+       "         [            nan,             nan,             nan,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' class='xr-var-data-in' type='checkbox'><label for='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
+       "        5.33333e-06, 5.33333e-06],\n",
+       "       [2.13333e-05, 2.13333e-05, 2.13333e-05, ..., 2.13333e-05,\n",
+       "        2.13333e-05, 2.13333e-05],\n",
+       "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
+       "        8.00000e-06, 8.00000e-06],\n",
+       "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
+       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab004848-afa7-47ea-950d-1cb5a677ed97' class='xr-var-data-in' type='checkbox'><label for='data-ab004848-afa7-47ea-950d-1cb5a677ed97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
+       "       [ 75.,  75.,  75., ...,  75.,  75.,  75.],\n",
+       "       [105., 105., 105., ..., 105., 105., 105.],\n",
+       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' class='xr-var-data-in' type='checkbox'><label for='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048,      nan]],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' class='xr-var-data-in' type='checkbox'><label for='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
+       "        0.00348772],\n",
+       "       [0.0177557 , 0.0177557 , 0.0177557 , ..., 0.0177557 , 0.0177557 ,\n",
+       "        0.0177557 ],\n",
+       "       [0.00574449, 0.00574449, 0.00574449, ..., 0.00574449, 0.00574449,\n",
+       "        0.00574449],\n",
+       "       [0.0108507 , 0.0108507 , 0.0108507 , ..., 0.0108507 , 0.0108507 ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9d1a713-b657-40cf-8fff-dd38458070b3' class='xr-var-data-in' type='checkbox'><label for='data-c9d1a713-b657-40cf-8fff-dd38458070b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6221d42c-73ef-46de-990b-4eda4842b355' class='xr-var-data-in' type='checkbox'><label for='data-6221d42c-73ef-46de-990b-4eda4842b355' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, nan]],\n",
+       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' class='xr-var-data-in' type='checkbox'><label for='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-870a77e3-35de-4cca-a848-920508fffb09' class='xr-var-data-in' type='checkbox'><label for='data-870a77e3-35de-4cca-a848-920508fffb09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
+       "       [ 55000.,  55000.,  55000., ...,  55000.,  55000.,  55000.],\n",
+       "       [170000., 170000., 170000., ..., 170000., 170000., 170000.],\n",
+       "       [ 90000.,  90000.,  90000., ...,  90000.,  90000.,     nan]],\n",
+       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-687834aa-6953-4d69-b46a-20190955a6fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-687834aa-6953-4d69-b46a-20190955a6fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3520b899-5011-498a-90ec-4b0076a11867' class='xr-var-data-in' type='checkbox'><label for='data-3520b899-5011-498a-90ec-4b0076a11867' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
+       "       [ 85000.,  85000.,  85000., ...,  85000.,  85000.,  85000.],\n",
+       "       [260000., 260000., 260000., ..., 260000., 260000., 260000.],\n",
+       "       [170000., 170000., 170000., ..., 170000., 170000.,     nan]],\n",
+       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
+       "                        </ul>\n",
+       "                    </div>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
+       "                    <div class=\"xr-section-inline-details\"></div>\n",
+       "                    <div class=\"xr-section-details\">\n",
+       "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
+       "                            <div style=\"padding-left:2rem;\"><div><svg style=\"position: absolute; width: 0; height: 0; overflow: hidden\">\n",
+       "<defs>\n",
+       "<symbol id=\"icon-database\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M16 0c-8.837 0-16 2.239-16 5v4c0 2.761 7.163 5 16 5s16-2.239 16-5v-4c0-2.761-7.163-5-16-5z\"></path>\n",
+       "<path d=\"M16 17c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "<path d=\"M16 26c-8.837 0-16-2.239-16-5v6c0 2.761 7.163 5 16 5s16-2.239 16-5v-6c0 2.761-7.163 5-16 5z\"></path>\n",
+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DatasetView&gt; Size: 531kB\n",
+       "Dimensions:                      (channel: 4, pulse_length_bin: 5,\n",
+       "                                  cal_channel_id: 4, cal_frequency: 413,\n",
+       "                                  filter_time: 1, WBT_filter_n: 119,\n",
+       "                                  PC_filter_n: 391)\n",
+       "Coordinates:\n",
+       "  * channel                      (channel) &lt;U26 416B &#x27;WBT 747008-15 ES333-7CD...\n",
+       "  * pulse_length_bin             (pulse_length_bin) int64 40B 0 1 2 3 4\n",
+       "  * cal_channel_id               (cal_channel_id) object 32B &#x27;WBT 747008-15 E...\n",
+       "  * cal_frequency                (cal_frequency) int64 3kB 55000 ... 380000\n",
+       "  * filter_time                  (filter_time) datetime64[ns] 8B 2021-12-15T1...\n",
+       "Dimensions without coordinates: WBT_filter_n, PC_filter_n\n",
+       "Data variables: (12/21)\n",
+       "    frequency_nominal            (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sa_correction                (channel, pulse_length_bin) float64 160B 0.0...\n",
+       "    gain_correction              (channel, pulse_length_bin) float64 160B 25....\n",
+       "    pulse_length                 (channel, pulse_length_bin) float64 160B 6.4...\n",
+       "    impedance_transceiver        (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency  (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    ...                           ...\n",
+       "    WBT_coeffs_imag              (channel, filter_time, WBT_filter_n) float64 4kB ...\n",
+       "    PC_coeffs_real               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
+       "    PC_coeffs_imag               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
+       "    WBT_deci_fac                 (channel, filter_time) float64 32B 8.0 ... 12.0\n",
+       "    PC_deci_fac                  (channel, filter_time) float64 32B 1.0 ... 1.0\n",
+       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary-in' type='checkbox' checked /><label for='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' class='xr-var-data-in' type='checkbox'><label for='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' class='xr-var-data-in' type='checkbox'><label for='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' class='xr-var-data-in' type='checkbox'><label for='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' class='xr-var-data-in' type='checkbox'><label for='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' class='xr-var-data-in' type='checkbox'><label for='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary-in' type='checkbox' /><label for='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1932405b-b524-4150-b2ae-354bba2a7f72' class='xr-var-data-in' type='checkbox'><label for='data-1932405b-b524-4150-b2ae-354bba2a7f72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d5be396-1656-47d2-8aa3-092776083a76' class='xr-var-data-in' type='checkbox'><label for='data-4d5be396-1656-47d2-8aa3-092776083a76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.02,  0.  ,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.26, -0.01,  0.  ],\n",
+       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce4c0b58-57d3-445a-8e65-5015874ef421' class='xr-var-data-in' type='checkbox'><label for='data-ce4c0b58-57d3-445a-8e65-5015874ef421' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
+       "       [27.  , 27.  , 27.59, 27.  , 27.  ],\n",
+       "       [26.  , 26.  , 27.48, 27.33, 26.  ],\n",
+       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' class='xr-var-data-in' type='checkbox'><label for='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03, 2.048e-03],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' class='xr-var-data-in' type='checkbox'><label for='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' class='xr-var-data-in' type='checkbox'><label for='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ce4645-91e7-4328-80da-b1ea318a53b2' class='xr-var-data-in' type='checkbox'><label for='data-66ce4645-91e7-4328-80da-b1ea318a53b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a73f8603-7355-442c-9bad-2387784af5ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a73f8603-7355-442c-9bad-2387784af5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' class='xr-var-data-in' type='checkbox'><label for='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
+       "       [20.59, 22.95, 24.07, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69226643-e8d9-4acc-95b9-dc840619444b' class='xr-var-data-in' type='checkbox'><label for='data-69226643-e8d9-4acc-95b9-dc840619444b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' class='xr-var-data-in' type='checkbox'><label for='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eccaf05-f218-4c83-a174-1470d34dde2f' class='xr-var-data-in' type='checkbox'><label for='data-6eccaf05-f218-4c83-a174-1470d34dde2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
+       "       [9.33, 8.67, 8.3 , ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6b553291-1032-4c41-9b83-daf3397a9551' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b553291-1032-4c41-9b83-daf3397a9551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' class='xr-var-data-in' type='checkbox'><label for='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
+       "       [9.5 , 8.24, 8.38, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be9da896-9635-4448-ad3b-dcdcdc179102' class='xr-var-data-in' type='checkbox'><label for='data-be9da896-9635-4448-ad3b-dcdcdc179102' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
+       "       [ 0.04, -0.18, -0.26, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' class='xr-var-data-in' type='checkbox'><label for='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
+       "       [ 0.35, -0.02,  0.02, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-8ba515f8-123f-490f-8cf2-254391f11774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ba515f8-123f-490f-8cf2-254391f11774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7785e6ce-31a3-4d71-b185-adefed77555e' class='xr-var-data-in' type='checkbox'><label for='data-7785e6ce-31a3-4d71-b185-adefed77555e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
+       "          5.80396911e-04,  1.79292378e-03, -5.69819706e-04,\n",
+       "         -4.36119642e-03, -1.06982014e-03,  6.37054257e-03,\n",
+       "          3.98992328e-03, -5.19806752e-03, -4.50613070e-03,\n",
+       "          1.07290410e-03, -2.02566851e-03,  5.07575809e-04,\n",
+       "          1.47993285e-02,  6.74376963e-03, -2.42605228e-02,\n",
+       "         -1.99034940e-02,  1.98264010e-02,  2.28713546e-02,\n",
+       "         -4.73045558e-03,  1.66427530e-03,  1.54931960e-03,\n",
+       "         -5.10883406e-02, -3.59251946e-02,  9.50072855e-02,\n",
+       "          1.08932644e-01, -9.52564925e-02, -1.85995519e-01,\n",
+       "          4.01502699e-02,  2.19155550e-01,  4.01502699e-02,\n",
+       "         -1.85995519e-01, -9.52564925e-02,  1.08932644e-01,\n",
+       "          9.50072855e-02, -3.59251946e-02, -5.10883406e-02,\n",
+       "          1.54931960e-03,  1.66427530e-03, -4.73045558e-03,\n",
+       "          2.28713546e-02,  1.98264010e-02, -1.99034940e-02,\n",
+       "         -2.42605228e-02,  6.74376963e-03,  1.47993285e-02,\n",
+       "          5.07575809e-04, -2.02566851e-03,  1.07290410e-03,\n",
+       "         -4.50613070e-03, -5.19806752e-03,  3.98992328e-03,\n",
+       "          6.37054257e-03, -1.06982014e-03, -4.36119642e-03,\n",
+       "         -5.69819706e-04,  1.79292378e-03,  5.80396911e-04,\n",
+       "...\n",
+       "          1.28910273e-01,  6.77423924e-02, -8.72524641e-03,\n",
+       "         -7.36967400e-02, -1.07046373e-01, -1.02706917e-01,\n",
+       "         -6.94890395e-02, -2.54954696e-02,  1.07670929e-02,\n",
+       "          2.82163061e-02,  2.65309773e-02,  1.40545843e-02,\n",
+       "          2.02343985e-03, -1.57549907e-03,  4.54013515e-03,\n",
+       "          1.54866800e-02,  2.38744710e-02,  2.42441874e-02,\n",
+       "          1.58575494e-02,  2.60307826e-03, -9.54600796e-03,\n",
+       "         -1.58524998e-02, -1.50543209e-02, -9.48206428e-03,\n",
+       "         -3.28161148e-03,  5.14209241e-05, -5.86639857e-04,\n",
+       "         -3.71975894e-03, -6.53725956e-03, -6.69319043e-03,\n",
+       "         -3.60184023e-03,  1.40942517e-03,  6.01961603e-03,\n",
+       "          8.26145709e-03,  7.50966882e-03,  4.62702196e-03,\n",
+       "          1.30935630e-03, -9.04795772e-04, -1.38237234e-03,\n",
+       "         -5.43581322e-04,  5.71371173e-04,  9.88384243e-04,\n",
+       "          3.29891511e-04, -1.06842164e-03, -2.44627846e-03,\n",
+       "         -3.08986311e-03, -2.70423386e-03, -1.50845083e-03,\n",
+       "         -5.42755188e-05,  1.08743296e-03,  1.58825796e-03,\n",
+       "          1.45288126e-03,  9.33228002e-04,  3.50838847e-04,\n",
+       "         -6.20377104e-05, -2.31620375e-04, -2.17583845e-04,\n",
+       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c844e259-e4c2-42be-8d15-d40f7c48673c' class='xr-var-data-in' type='checkbox'><label for='data-c844e259-e4c2-42be-8d15-d40f7c48673c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
+       "         -9.13087046e-04,  7.09498825e-04,  2.99199694e-03,\n",
+       "          9.69185190e-18, -5.61309094e-03, -2.52190628e-03,\n",
+       "          6.28564134e-03,  4.88218758e-03, -3.27457441e-03,\n",
+       "         -2.27805204e-03, -5.20343136e-04, -8.05283710e-03,\n",
+       "         -1.86947198e-03,  2.07523126e-02,  1.33378496e-02,\n",
+       "         -2.40603201e-02, -2.39648726e-02,  1.25731202e-02,\n",
+       "          1.45617211e-02,  2.10128841e-04,  2.46108808e-02,\n",
+       "          1.31174969e-02, -7.63469040e-02, -6.90261498e-02,\n",
+       "          1.02293685e-01,  1.50101691e-01, -7.36412108e-02,\n",
+       "         -2.10470200e-01,  7.60158497e-20,  2.10470200e-01,\n",
+       "          7.36412108e-02, -1.50101691e-01, -1.02293685e-01,\n",
+       "          6.90261498e-02,  7.63469040e-02, -1.31174969e-02,\n",
+       "         -2.46108808e-02, -2.10128841e-04, -1.45617211e-02,\n",
+       "         -1.25731202e-02,  2.39648726e-02,  2.40603201e-02,\n",
+       "         -1.33378496e-02, -2.07523126e-02,  1.86947198e-03,\n",
+       "          8.05283710e-03,  5.20343136e-04,  2.27805204e-03,\n",
+       "          3.27457441e-03, -4.88218758e-03, -6.28564134e-03,\n",
+       "          2.52190628e-03,  5.61309094e-03, -9.55039822e-18,\n",
+       "         -2.99199694e-03, -7.09498825e-04,  9.13087046e-04,\n",
+       "...\n",
+       "          7.80717358e-02,  1.29582077e-01,  1.38660282e-01,\n",
+       "          1.06033586e-01,  4.76594567e-02, -1.29747139e-02,\n",
+       "         -5.50751574e-02, -6.85512722e-02, -5.64508401e-02,\n",
+       "         -3.13390270e-02, -8.01062118e-03,  3.60898394e-03,\n",
+       "          2.06778105e-03, -6.71086088e-03, -1.39776571e-02,\n",
+       "         -1.33690219e-02, -4.03831480e-03,  9.59953945e-03,\n",
+       "          2.08935011e-02,  2.47807242e-02,  2.02831514e-02,\n",
+       "          1.05313919e-02,  6.30900904e-04, -5.21199452e-03,\n",
+       "         -5.68135269e-03, -2.52550538e-03,  9.22063016e-04,\n",
+       "          1.84576935e-03, -5.48824668e-04, -4.86181164e-03,\n",
+       "         -8.56491644e-03, -9.55463666e-03, -7.27825612e-03,\n",
+       "         -2.87745940e-03,  1.59654417e-03,  4.34645358e-03,\n",
+       "          4.69489116e-03,  3.23531032e-03,  1.29674340e-03,\n",
+       "          1.15227005e-04,  1.99488175e-04,  1.19654136e-03,\n",
+       "          2.24404945e-03,  2.53815181e-03,  1.77624938e-03,\n",
+       "          2.59338703e-04, -1.34165830e-03, -2.37460458e-03,\n",
+       "         -2.52039032e-03, -1.88605406e-03, -8.73966317e-04,\n",
+       "          6.09558374e-05,  6.21019106e-04,  7.48717517e-04,\n",
+       "          5.76159859e-04,  3.03197594e-04,  8.55612234e-05,\n",
+       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' class='xr-var-data-in' type='checkbox'><label for='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
+       "                     nan,             nan,             nan]],\n",
+       "\n",
+       "       [[-2.92797376e-05,  1.22475076e-05,  2.08751826e-05, ...,\n",
+       "                     nan,             nan,             nan]],\n",
+       "\n",
+       "       [[-4.78051297e-05,  1.28309519e-04,  1.03955274e-04, ...,\n",
+       "          1.03955274e-04,  1.28309519e-04, -4.78051297e-05]],\n",
+       "\n",
+       "       [[-3.34112738e-05, -1.13061478e-03, -2.34585186e-03, ...,\n",
+       "                     nan,             nan,             nan]]],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' class='xr-var-data-in' type='checkbox'><label for='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "       [[-5.08991980e-05,  3.11717099e-06, -1.25777024e-05, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
+       "\n",
+       "       [[ 1.47129060e-04,  2.02183452e-04,  1.31326051e-05, ...,\n",
+       "         -1.31326051e-05, -2.02183452e-04, -1.47129060e-04]],\n",
+       "\n",
+       "       [[ 1.31017148e-18, -2.90292519e-04, -1.28964300e-03, ...,\n",
+       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-065376e8-2433-4523-9d8e-180c409dc855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-065376e8-2433-4523-9d8e-180c409dc855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6952267-584f-4c92-8e74-63f9dece4db1' class='xr-var-data-in' type='checkbox'><label for='data-b6952267-584f-4c92-8e74-63f9dece4db1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
+       "       [ 8.],\n",
+       "       [ 6.],\n",
+       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98037233-e32a-468f-8b01-0897ad886f8c' class='xr-var-data-in' type='checkbox'><label for='data-98037233-e32a-468f-8b01-0897ad886f8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
+       "       [4.],\n",
+       "       [2.],\n",
+       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' class='xr-var-data-in' type='checkbox'><label for='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; 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Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; 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+       "      dtype=&#x27;&lt;U100225&#x27;)</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
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+      "text/plain": [
+       "<EchoData: standardized raw data from Internal Memory>\n",
+       "Top-level: contains metadata about the SONAR-netCDF4 file format.\n",
+       "├── Environment: contains information relevant to acoustic propagation through water.\n",
+       "├── Platform: contains information about the platform on which the sonar is installed.\n",
+       "│   └── NMEA: contains information specific to the NMEA protocol.\n",
+       "├── Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.\n",
+       "├── Sonar: contains sonar system metadata and sonar beam groups.\n",
+       "│   └── Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.\n",
+       "└── Vendor_specific: contains vendor-specific information about the sonar and the data."
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ed_ts = ep.open_raw(raw_file_TS, sonar_model=\"EK80\")\n",
+    "ed_ts"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "f13c5766",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<xarray.DataArray 'channel_all' (channel_all: 4)> Size: 416B\n",
+      "array(['WBT 747008-15 ES333-7CD_ES', 'WBT 747015-15 ES70-7CD_ES',\n",
+      "       'WBT 747019-15 ES200-7CD_ES', 'WBT 747022-15 ES120-7CD_ES'],\n",
+      "      dtype='<U26')\n",
+      "Coordinates:\n",
+      "  * channel_all  (channel_all) <U26 416B 'WBT 747008-15 ES333-7CD_ES' ... 'WB...\n",
+      "Attributes:\n",
+      "    long_name:  Vendor channel ID\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ed_ts['Sonar']['channel_all'])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f6e20948",
+   "metadata": {},
+   "source": [
+    "We select the same ping and frequency as those used by Andersen et al. (2024)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e71a1ea3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tsf_channel = \"WBT 747022-15 ES120-7CD_ES\"\n",
+    "\n",
+    "# CRIMAC uses 1-based ping numbering.\n",
+    "# Python/xarray uses 0-based indexing.\n",
+    "crimac_ping_number = 510\n",
+    "tsf_ping_index = crimac_ping_number - 1"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "22ffb426",
+   "metadata": {},
+   "source": [
+    "We initialise a `CalibrateEK80`  object to access the internal calibration data and helper functions used in the step-by-step TS spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "9aaa027a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cal_obj = CalibrateEK80(\n",
+    "    ed_ts,\n",
+    "    env_params=None,\n",
+    "    cal_params=None,\n",
+    "    ecs_file=None,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "55bfebec",
+   "metadata": {},
+   "source": [
+    "We then load the reference outputs previously exported from the original CRIMAC processing chain. These results provide the benchmark against which the echopype implementation is compared."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5cd9732a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "y_rx_nu (4, 2356) complex128\n",
+      "r_n (2356,) float64\n",
+      "f_m (1000,) float64\n",
+      "alpha_m (1000,) float64\n",
+      "lambda_m (1000,) float64\n",
+      "y_tx_n (3071,) float64\n",
+      "y_mf_n (516,) complex128\n",
+      "y_mf_auto_n (1031,) complex128\n",
+      "tau_eff () float64\n",
+      "y_pc_nu (4, 2356) complex128\n",
+      "y_pc_n (2356,) complex128\n",
+      "p_rx_e_n (2356,) float64\n",
+      "theta_n (2356,) float64\n",
+      "phi_n (2356,) float64\n",
+      "Sp_full_n (2356,) float64\n",
+      "Sp_full_r (2356,) float64\n",
+      "Sp_target_n (168,) float64\n",
+      "Sp_target_r (168,) float64\n",
+      "dum_r (168,) float64\n",
+      "dum_theta (168,) float64\n",
+      "dum_phi (168,) float64\n",
+      "r_t () float64\n",
+      "theta_t () float64\n",
+      "phi_t () float64\n",
+      "y_pc_t_n (168,) complex128\n",
+      "y_mf_auto_red_n (168,) complex128\n",
+      "Y_pc_t_m (1000,) complex128\n",
+      "Y_mf_auto_red_m (1000,) complex128\n",
+      "Y_tilde_pc_t_m (1000,) complex128\n",
+      "P_rx_e_t_m (1000,) float64\n",
+      "g_theta_phi_m (1000,) float64\n",
+      "TS_m (1000,) float64\n"
+     ]
+    }
+   ],
+   "source": [
+    "ref_ts = np.load(ref_file_TS)\n",
+    "\n",
+    "for k in ref_ts.keys():\n",
+    "    print(k, ref_ts[k].shape, ref_ts[k].dtype)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bc617532",
+   "metadata": {},
+   "source": [
+    "We define a few helper functions that will be used throughout the validation workflow."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d8840697",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def scalar_param(da, channel=None, ping_idx=None):\n",
+    "    \"\"\"Select scalar from a possibly channel/ping-dependent DataArray.\"\"\"\n",
+    "    if channel is not None and \"channel\" in da.dims:\n",
+    "        da = da.sel(channel=channel)\n",
+    "    if ping_idx is not None and \"ping_time\" in da.dims:\n",
+    "        da = da.isel(ping_time=ping_idx)\n",
+    "    return float(da)\n",
+    "\n",
+    "\n",
+    "def db20(x):\n",
+    "    return 20 * np.log10(np.abs(x))\n",
+    "\n",
+    "\n",
+    "def db10(x):\n",
+    "    return 10 * np.log10(np.abs(x))\n",
+    "\n",
+    "\n",
+    "def compare_summary(name, ref, ep):\n",
+    "    ref = np.asarray(ref)\n",
+    "    ep = np.asarray(ep)\n",
+    "\n",
+    "    n = min(ref.size, ep.size)\n",
+    "    ref = ref.reshape(-1)[:n]\n",
+    "    ep = ep.reshape(-1)[:n]\n",
+    "\n",
+    "    diff = ep - ref\n",
+    "\n",
+    "    return {\n",
+    "        \"variable\": name,\n",
+    "        \"n\": n,\n",
+    "        \"CRIMAC mean\": np.nanmean(ref),\n",
+    "        \"echopype mean\": np.nanmean(ep),\n",
+    "        \"mean diff\": np.nanmean(diff),\n",
+    "        \"median diff\": np.nanmedian(diff),\n",
+    "        \"RMSE\": np.sqrt(np.nanmean(diff**2)),\n",
+    "        \"max abs diff\": np.nanmax(np.abs(diff)),\n",
+    "    }\n",
+    "\n",
+    "\n",
+    "def compare_curve(\n",
+    "    x_ref,\n",
+    "    y_ref,\n",
+    "    x_ep,\n",
+    "    y_ep,\n",
+    "    title,\n",
+    "    xlabel,\n",
+    "    ylabel,\n",
+    "    xlim=None,\n",
+    "    ylim=None,\n",
+    "):\n",
+    "    plt.figure(figsize=(8, 3.5))\n",
+    "    plt.plot(x_ref, y_ref, label=\"CRIMAC\")\n",
+    "    plt.plot(x_ep, y_ep, \"--\", label=\"echopype\", alpha=0.85)\n",
+    "\n",
+    "    if xlim is not None:\n",
+    "        plt.xlim(*xlim)\n",
+    "    if ylim is not None:\n",
+    "        plt.ylim(*ylim)\n",
+    "\n",
+    "    plt.xlabel(xlabel)\n",
+    "    plt.ylabel(ylabel)\n",
+    "    plt.title(title)\n",
+    "    plt.grid(True)\n",
+    "    plt.legend()\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "91bcb6b2",
+   "metadata": {},
+   "source": [
+    "### Rebuild the transmit signal and matched filter\n",
+    "\n",
+    "We reconstruct the broadband transmit signal from the EK80 filter coefficients, then compute its matched-filter autocorrelation. This reproduces the signal used by CRIMAC for pulse compression."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "409937dd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_mf_n: (516,)\n",
+      "CRIMAC y_mf_n  : (516,)\n",
+      "echopype y_mf_auto_n: (1031,)\n",
+      "CRIMAC y_mf_auto_n  : (1031,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "tx_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "fs = cal_obj.cal_params[\"receiver_sampling_frequency\"]\n",
+    "\n",
+    "tx, tx_time = get_transmit_signal(\n",
+    "    cal_obj.beam,\n",
+    "    tx_coeff,\n",
+    "    cal_obj.waveform_mode,\n",
+    "    fs,\n",
+    "    cal_obj.drop_last_hanning_zero,\n",
+    ")\n",
+    "\n",
+    "y_mf_n = tx[tsf_channel]\n",
+    "\n",
+    "y_mf_auto_n = np.convolve(\n",
+    "    y_mf_n,\n",
+    "    np.conj(y_mf_n[::-1]),\n",
+    "    mode=\"full\",\n",
+    ") / np.linalg.norm(y_mf_n) ** 2\n",
+    "\n",
+    "print(\"echopype y_mf_n:\", y_mf_n.shape)\n",
+    "print(\"CRIMAC y_mf_n  :\", ref_ts[\"y_mf_n\"].shape)\n",
+    "\n",
+    "print(\"echopype y_mf_auto_n:\", y_mf_auto_n.shape)\n",
+    "print(\"CRIMAC y_mf_auto_n  :\", ref_ts[\"y_mf_auto_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "966cd986",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x300 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 2, figsize=(11, 3))\n",
+    "\n",
+    "ax[0].plot(np.abs(ref_ts[\"y_mf_n\"]), label=\"CRIMAC\")\n",
+    "ax[0].plot(np.abs(y_mf_n), \"--\", label=\"echopype\")\n",
+    "ax[0].set_title(\"Matched filter\")\n",
+    "ax[0].set_xlabel(\"Sample\")\n",
+    "ax[0].set_ylabel(r\"$|y_{mf}(n)|$\")\n",
+    "ax[0].grid(True)\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(np.abs(ref_ts[\"y_mf_auto_n\"]), label=\"CRIMAC\")\n",
+    "ax[1].plot(np.abs(y_mf_auto_n), \"--\", label=\"echopype\")\n",
+    "ax[1].set_title(\"Matched-filter autocorrelation\")\n",
+    "ax[1].set_xlabel(\"Sample\")\n",
+    "ax[1].set_ylabel(r\"$|y_{mf,auto}(n)|$\")\n",
+    "ax[1].grid(True)\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4b99f5cb",
+   "metadata": {},
+   "source": [
+    "### Apply pulse compression\n",
+    "\n",
+    "We apply pulse compression to the complex sector signals using the reconstructed matched filter. The resulting `pc` array contains the pulse-compressed signal for each transducer sector, while `pc_avg` is the sector-averaged pulse-compressed signal used for the TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "cbb9344f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_pc_n: (2356,)\n",
+      "CRIMAC y_pc_n  : (2356,)\n",
+      "echopype r_n   : (2356,)\n",
+      "CRIMAC r_n     : (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import (\n",
+    "    _get_pulse_compressed_signal,\n",
+    "    _get_average_signal,\n",
+    ")\n",
+    "\n",
+    "pc = _get_pulse_compressed_signal(\n",
+    "    beam=cal_obj.beam,\n",
+    "    matched_filter=tx,\n",
+    ")\n",
+    "\n",
+    "pc_avg = _get_average_signal(pc)\n",
+    "\n",
+    "pc_ping = pc.sel(channel=tsf_channel).isel(ping_time=tsf_ping_index)\n",
+    "pc_avg_ping = pc_avg.sel(channel=tsf_channel).isel(ping_time=tsf_ping_index)\n",
+    "\n",
+    "r_ping = (\n",
+    "    cal_obj.range_meter\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    ")\n",
+    "\n",
+    "valid = np.isfinite(pc_avg_ping) & np.isfinite(r_ping)\n",
+    "\n",
+    "pc_ping = pc_ping.where(valid, drop=True)\n",
+    "pc_avg_ping = pc_avg_ping.where(valid, drop=True)\n",
+    "r_n = r_ping.where(valid, drop=True).values\n",
+    "\n",
+    "y_pc_n = pc_avg_ping.values\n",
+    "\n",
+    "print(\"echopype y_pc_n:\", y_pc_n.shape)\n",
+    "print(\"CRIMAC y_pc_n  :\", ref_ts[\"y_pc_n\"].shape)\n",
+    "print(\"echopype r_n   :\", r_n.shape)\n",
+    "print(\"CRIMAC r_n     :\", ref_ts[\"r_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "e8c17f15",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_13472\\1980613090.py:11: RuntimeWarning: divide by zero encountered in log10\n",
+      "  return 20 * np.log10(np.abs(x))\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Tk1PpY1JXKfpbU6ci2k9BQUHivO3fxNwVyrYTkllCQoLp7rvvFvuQuqH179/fdOTIEfF66HXZ2rp1q6ldu3Zi/9Df49lnn7V0FsvOzr6u+3PHjh2i4xLdjh7fy8tLvPeWL19+2S5M1X0d9Ni0L8sr3ymupKTENH36dLHv6TOCOl3R66/OZwRj7NqQ0T83IqBhjDFWeyjXnNJMaD0JdvujBf9oFozqV25lt8vrYIxJOBWKMcYYu4lRLQQtREh1A5R+Ralc69atsxTH3ypul9fBGKsaBxaMMcbYTYwKuqlRAHVQooJlWkGbalqo/uhWcru8DsZY1TgVijHGGGOMMVZjvEAeY4wxxhhjrMY4sGCMMcYYY4zVGAcWjDHGGGOMsRrj4u1aQiuIJiUlwcXFxbKSKWOMMcYYY7cSWokiLy8PgYGBV7x4JQcWtYSCCmqhxxhjjDHG2K0uPj4ewcHBV3QfDixqCc1UkPPnz8PT07O2HpbdZnQ6HdauXSsWhVKpVDd6c9hNjN8rjN8njD9T2I1A68zUqVPHMra9EhxY1BJz+hP9EVxdXWvrYdltOFh0dHQU7xEOLBi/Vxh/pjD+/mE341iFXE1qPxdvM8YYY4wxxmqMAwvGGGOMMcZYjXFgwRhjjDHGGKsxrrFgjDHGGGOXZTAYLPn37NalUqmgUCiuyWNzYMEYY4wxxi65rkFKSgqys7N5L90m3N3d4e/vX+trr3FgwRhjjDHGqmQOKnx9fUVnQ14I+NYOEgsLC5GamirOBwQE1Orjc2DBGGOMMcaqTH8yBxVeXl68l24DWq1W/KTggv6utZkWxcXbjDHGGGOsUuaaCpqpYLcPx7K/Z23XzHBgwRhjjDHGLonTn24vslqurTDjwIIxxhhjjDFWYxxYMMYYY4wxxmqMAwvGGGOMMXbbdrR66qmnEBERAY1Gg5CQEAwZMgTr168X14eHh4u0IDpRUXNUVBTef/990T3JLDY2Vlx/8OBBu/NKpRKJiYl2z5ecnCwup+vpduX17dtXFEvv3Lmz0u09cOAARo4cCT8/Pzg4OKB+/fqYNGkSTp06hVsBBxaMMcYYY+y2QwP7Vq1aYcOGDXjvvfcQExOD1atXo0ePHpg8ebLldrNmzRIBwfHjxzF9+nS8+OKL+Prrry/7+IGBgfjhhx/sLlu4cCGCgoIqvX1cXBx27NiBJ598EvPnz69w/d9//4327dujpKQEP//8s9ieH3/8EW5ubnjllVdwK+DAgjHGGGOM3XaeeOIJMXOwe/du3HPPPeLof+PGjTF16lS7GQMXFxexWBzNXkycOBFNmzbF2rVrL/v448aNw4IFC+wu+/7778XllaHbDh48GI8//jgWLVqEgoICy3W0tsRDDz2EgQMHYvny5ejduzfq1KmDdu3aYc6cOZg3bx5uBRxYMMYYY4yx6i+wVqq/ISfb9KTLyczMFLMTNDPh5ORU6crTlb22TZs2iZkClUp12ecYOnQosrKysG3bNnF+27Zt4nkp1aqyx6bA4oEHHhDpVhTk/P7775br16xZg/T0dDz33HOVPldl23sz4gXyGGOMMcZYtRTpDGg0c80N2VvHZvWDo7p6Q9czZ86IwTwN4i/n+eefx8svv4zS0lKxrgPVNkyZMuWy96PggwKF7777Dp07dxY/6XxlQcm///4rZiX69esnztPtKB2KZinI6dOnxc/qbO/NjGcsGGOMMcbYbcU8u1Gd9RqeffZZUZi9efNmUX/x0ksvoWPHjtV6nocffhiLFy8WReKLFy/GhAkTKr0dBRGjR48Whd3kvvvuw65du3Dy5Em77b3V8YwFY4wxxhirFq1KIWYObtRzV1e9evVEUEFpTcOHD7/kbb29vREZGSlOS5YsET+piJrqHC4nOjpazDJQoNCwYUNx3tw9yozSo5YtWyZmQ7788kvL5QaDQcxyvPvuuyI1ipw4cQIdOnTArYpnLBhjjDHGWLXQYJ3SkW7E6UpWi/b09BRpR59//rldkbRZdnZ2pffz8PAQ7WmpO1R1ZxFoloJqMyZUMVtBHZ6Cg4Nx6NAhEXSYTx999JHoIqXX60UbWgpwqHtVZara3psNBxaMMcYYY+y288UXX4hZgbZt24qZCKpjoBmMTz755JKzAlTwTSlKdJ/qoHUm0tLSREepqtKgqCsVzWbYnigQoYBh5cqVosD822+/Fb9TUTjVZFC73L1794qC7sceewy3Ag4sGGOMMcbYbYfate7fv1/UTUybNk0M5vv06SMWx7NNSSrPx8cHY8eOxWuvvQaj0XjZ56G6CZptUJbVT9jat2+fmKm4++67K1xHbW5ppsK8psWwYcOwfft2Ufw9ZswYS4pVTk4O3nzzTdwKuMaCMcYYY4zdlgICAvDZZ5+JU2UqWx2b2C6QR+tb2KZFlT9fXvPmzS3XX+62tGaFrdatW1d7puRmxDMWjDHGGGOMsRrjwIIxxhhjjDFWYxxYMMYYY4wxxmqMAwvGGGOMMcZYjXFgwRhjjDHGGKsxDiwYY4wxxhhjNcaBBWOMMcYYY6zGOLBgjDHGGGOM1RgHFowxxhhjjLEa48CCMcYYY4wxG+PHj8fw4cN5n1whDiwYY4wxxhhjNcaBBWOMMcYYY6zGOLCw8cUXX6BOnTpwcHBAq1atsHXr1prvYcYYY4wxdt2ZTCa89957iIiIgFarRbNmzfDHH39Yrj969CgGDRoEV1dXuLi4oEuXLjh79qzdY8yZMwcBAQHw8vLC5MmTodPpLNdlZWXhwQcfhIeHBxwdHTFgwACcPn3acv33338Pd3d3LFu2DPXr1xfjyz59+iA+Pl5cHxsbC7lcjr1799o956effoqwsDCx/Zs2bYJMJsPKlSvF9tNjtGvXDjExMXb32b59O7p27SpeZ0hICKZMmYKCggJcbxxYlFm0aBGeeeYZvPTSSzhw4IB4c9EbJC4u7rr/URhjjDHGbmq6oqpP+pLq31ZXXL3bXoWXX34ZCxYswJdffimCiP/973944IEHsHnzZiQmJoqBOA3UN2zYgH379mHChAnQ6/WW+2/cuFEEGvRz4cKFIlCgk20dBgUFy5cvx44dO0QgMHDgQLvgo7CwEG+99Za4/3///Yfc3Fzce++94rrw8HD07t1bbKMtOk+PTQGF2bPPPiuCnD179sDX1xdDhw61PA8FGf369cOIESNw+PBhMabdtm0bnnzySVxvyuv+jDepuXPn4uGHH8bEiRPF+Y8++ghr1qwRb8a33377Rm8eY4wxxtjN46vOVV8X1gkY+on1/Ld9AH0VwUFQK2DE19bz3w8GirMr3u6pfVe0eXS0nsZ2FDR06NBBXEYzFzTgnjdvnhjUu7m54bfffoNKpRLX06yCLZqJ+Oyzz6BQKBAVFSVmN9avX49JkyaJmQkKKChY6Nixo7j9zz//LGYLaIZi5MiR4jIa/NNj0CwDoQCjYcOG2L17N9q2bSvGnY899pjYVo1Gg0OHDuHgwYNYunSp3ba8+uqrYrbD/BjBwcH4888/MWrUKLz//vsYM2aMOEBO6tWrh08++QTdunUT41gKnq4XDiwAlJaWikj1hRdesNs5ffv2FVNLlSkpKREnM4pAzW8g20iVMVvm9wa/R9jl8HuFVQe/T9i1fq/Q7elIvNFoFCcz67H0ypnsbmu6xA1N5W57+cerjiNHjqC4uNgyGLcd87Vo0UKkMXXu3FkEDbavy7pZJjRq1EjMGpiv9/f3F49L52kGRKlUok2bNpbrPTw80KBBAxw7dsyyv+g2LVu2tNyGghdKj6L7t27dWsw80MzCkiVLxEzG/Pnz0aNHD4SGhtrtcwpMzL/T/W2fh8awZ86cEYGN7fbTdTTjQoFMeXQd3Yb+vrQPbNVkjMKBBYD09HQYDAb4+fnZ7Rw6n5KSUumOo1mM119/vcLlNF1GeXaMXcq6det4B7Fq4fcK4/cJu5GfKTQwpgF1fn6+GJRb3LfyEveS0RFX69mRSy79JLa3vevny9+mGvLy8sRPSguiGglbarUaL774ohhAmw8Ml0fXUVBhez1dRvuALqMUJ2mzcu0G5nq93nIbCmzM20K1FGY0oKeD0+bHplkHCigoLeqXX37B7NmzLdeZn4cew3ZbaNxqfh56TkqdevTRRyu8Dh8fn0pfI923qKgIW7ZssUv/sn3Oq8GBhQ3bXDbzH778ZWYzZszA1KlTLefpj0bTXxRlUoEPY5WhDyX6UKcjKOapV8b4vcKuFn+msGv9XqHBMRUbOzs7l0upcb2CnX+tbls1mkmg1CI6eEw1s+XRLMIPP/wgip0r2x90GQVVVNhtG5CYL6MmPzQgP378uCUVKiMjQ8wQUJE13Yb2F93m1KlTIu2JnDx5Ejk5OWjevLnlsR9//HE0bdpUzDjQ7e+//36xXcR8sJpmOBo3bix+p9kWeh66j3lbaMaCHvNK/q70HOY6E1v0Oq4WBxYAvL29RbRZfnYiNTW1wiyGGb1Z6VTZG5EHjOxy+H3CqovfK4zfJ+xGfqbQkXE6yEpH3G2Put/sqH5i+vTpmDZtmjhPaU90EJhS3ClIeuqpp0TtA9Um0MFiuv3OnTtFAEBpRvSaza/bzHywmS6j2wwbNkzMElDNBnWVeuGFFxAUFIS77rrLsr9oXz/99NOi5oF+p7Sn9u3bi5MZBQx0nu5PBeROTk6W68zP/+abb4rZBxqXUqMhGrtSsTZdT/ej+9NrovoPuj8FPBRIUoepytD96PVU9n6oyTj21nmHXEMUgVK0V356kM6bo1DGGGOMMXbreOONNzBz5kyRvk51BtQ5acWKFWJpAcouocJuSvGiImcaB37zzTdXNKim7k10v8GDB4sCcZPJhFWrVtk9Bs04PP/88yKAodvQLAEVjJdHDYQoPYkCi8q88847IkCh50tOThaF4zR+JTRzQZ2uqKCcuppSDckrr7xSIQXseuAZizKU1jR27FhRSEN/+K+//lq0mqVKfcYYY4wxdmuhI/K0ngOdKkMDcuoAWhnbtrJm1DHUFhVrUzrV5YwYMUKcLoWChejoaJHCVRmacaHC8arQ/dauXYsbjQOLMqNHjxY5ZbNmzbL8cSnqpAVKGGOMMcYYq235+fkibYlSlmiG5VbHqVA2nnjiCbEKIlXqU+suKmhhjDHGGGPsWnjyySfFbASlY1WVBnUr4cCCMcYYY4yxWjZ+/HhkZ1ey2F+5lCs6oE1tccuvJ0G6d+8uajdo7YpbAQcWjDHGGGOMsRrjwIIxxhhjjDFWYxxYMMYYY4yxSzIajbyHbiPGa/T35K5QjDHGGGOsUrRWAi2mlpSUJBZoo/PmheLYrcdkMon1MtLS0sTf1bwWRm3hwIIxxhhjjFWKBp+0oBy14qfggt0eHB0dERoaWuurqXNgwRhjjDHGqkRHtWkQqtfrYTAYeE/d4hQKBZRK5TWZeeLAgjHGGGOMXRINQlUqlTgxVhUu3maMMcYYY4zVGAcWjDHGGGOMsRrjwIIxxhhjjDFWYxxYMMYYY4wxxmqMAwvGGGOMMcZYjXFgwRhjjDHGGKsxDiwYY4wxxhhjNcaBBWOMMcYYY6zGOLBgjDHGGGOM1RgHFowxxhhjjLEa48CCMcYYY4wxVmMcWDDGGGOMMcZqjAMLxhhjjDHGWI1xYMEYY4wxxhirMQ4sGGOMMcYYYzXGgQVjjDHGGGOsxjiwYIwxxhhjjNUYBxaMMcYYY4yxGuPAgjHGGKsFqUlx2P7394g/d5L3J2PsjqS80RvAGGOM3epKSoqQ91Vf+AG4EFMPITNW3OhNYoyx645nLBhjjLEayriYZPndqTSd9ydj7I7EgQVjjDFWQ/k5GZbfPzON4v3JGLsjcWDBGGOM1VBBWWBxzhSIzaUNYDKZeJ8yxu44HFgwxhhjNVSSJwUWuXCE3mhCqcHI+5Qxdse57QOL8PBwyGQyu9MLL7xgd5u4uDgMGTIETk5O8Pb2xpQpU1BaWnrDtpkxxtitJa/EgIsmD9SVJaGXfB8KCwrE5TxzwRi7k9wRXaFmzZqFSZMmWc47OztbfjcYDBg0aBB8fHywbds2ZGRkYNy4ceLL4NNPP71BW8wYY+xWEuPUAZ/ovPGP+nm8qPwFmcnD8MpKA86mFeDPJzrCQaW40ZvIGGPX3B0RWLi4uMDf37/S69auXYtjx44hPj4egYGB4rIPPvgA48ePx1tvvQVXV9frvLWMMcZuNVkF0ix3MTRQQw/8Mhr/A7DF2BQ7Twaje3SdG72JjDF2zd0RgcW7776LN954AyEhIRg5ciSeffZZqNVqcd2OHTsQHR1tCSpIv379UFJSgn379qFHjx6VPiZdTyez3Nxc8VOn04kTY5Uxvzf4PcIuh98rt5bMfOn7oMikhqtMSoMiXeWHsS/fcM3+z/P7hPF7hV2rz5WrcdsHFk8//TRatmwJDw8P7N69GzNmzMD58+fx7bffiutTUlLg50dLGlnRbSnwoOuq8vbbb+P111+vcPnGjRvh6Oh4DV4Ju52sW7fuRm8Cu0Xwe+XW0PX87xikSoWfLMvu8jxosWnPEWguHr2mz8/vE8bvFVZbCgsLr/q+MtMtWFn22muvVTqot7Vnzx60bt26wuVLlizBPffcg/T0dHh5eeGRRx7BhQsXsGbNGrvbUWDxww8/4N577632jAXNiCQnJ4vHZayqowA0AOjTpw9UKhXvJFYlfq/cWva8Owh+pXGVXhfr2RldJ395TZ6X3yeM3yustlG9cUBAAHJycq64JOCWnLF48sknqxzw23aDqkz79u3FzzNnzogAgGovdu3aZXebrKws8WFdfibDlkajEafyaLDIA0Z2Ofw+YdXF75Vbg6NBSoctkjtCa7Q/2qctTLzm3wv8PmH8XmG1pSafV7dkYEEtYel0NQ4cOCB+UiRGOnToIIq0aabBfBkVdFPQ0KpVq1rcasYYY7ejooJ8uBiyxe/ZDsHQFp6yu96jJAklJUXQaLQ3aAsZY+wmX8eCjuhTJ6WTJ08iMzMTNyMqzP7www9x8OBBUVfx+++/49FHH8XQoUMRGhoqbtO3b180atQIY8eOFUHH+vXrMX36dNGeljtCMcYYu5yk+DOW2Yrdbv0rXK82leDQlhXi97VHU7DycDLvVMbYbemKAov8/HzMmzcP3bt3h5ubm0g3okE5rQERFhYmBuNU23CzoFmHRYsWie2l7Zw5c6bYxl9//dVyG4VCgZUrV8LBwQGdOnXCqFGjMHz4cMyZM+eGbjtjjLFbQ2bCafEzV+2PCzJrh0FbBTErUKI34JEf92HyL/uRlF0kLt/w7Qxse3sIDm1fgyOvtcS2v76+rtvOGGO1qdqpUHTkn1KGKJigI/60enVQUBC0Wq2YsThy5Ai2bt0qilKpjoEWl6tXrx5uJOoGtXPnzsvejmYv/v777+uyTYwxxm4vBakX4ElrWDgHQVUq1VqQl/UT4O+qwZOFX8IlPxbp2TmIlCUgx+SMZT98iJb1QhEW96d049VPix9F+77BhnPb0Xbix3B2cbtRL4kxxq5tYLF9+3bRSrVJkyaVXt+2bVtMmDABX331FebPn4/Nmzff8MCCMcYYu9ZSC/RQmTxhcg9HYOo5cZkJMuwwNsYDwRrgFOBuyEBO3FHMU30o3SldOhkhhxxGy2N5Ig+eWTuxbM1aeDXojKYh7ghy59oMxthtFlgsXry42ulHTzzxRE22iTHGGLtl/FLaBQd1TfBx0+Zo+89j4jIZTOgU6YVpw5tj2bvNkWTwQNu4c4god99EkzdCZKni9xKoUQQ13JGPH/el4+Te/QjzcsTmZytfqJUxxm6b4m3GGGPsTmY0GFGqN+JYkpT+1CzYHQHDZyFb6Y3UtjPw88T28HB2wA9uj+Ebw2AkXEyr8BjpcMM6YyvkQ4uLJncRVJBckxNcUAhDZux1f12MMXZd283SwhnmReCoM9Q333yDoqIiUXvRpUuXq94Yxhhj7FaQn5+LE3MH4bwiHDrDKLg7asTsgsy7BTBzm91tgz20OJ9egOw0qRtUikNd6FuMg+eOt9BCdhontU3hO+5POM+zdpT6VP0pPJAnfo957TOo7/4SW7O9Uc/PBd3q+1znV8sYY9dgxiImJkYUb/v6+iIqKkq0cW3Tpo0o7P7666/Ro0cPLFu27EoekjHGGLvlHN2+Ch76NLQs2YNl6pl41nUDZDJZpbcN9XCAD7LhX3xWnC8Nao+AlgPwsf5ucd5ZaYSrm3SwzswcVBBHYwGUix+Ecc3L+GTBj9f0dTHG2HULLJ577jlRvE2F2dTCdfDgwRg4cKBY8ptWq6Y1It55550abRBjjDF2s5PLrF+fzihCoJumytv2KV6H39RvoK38hDivcvWGn4sDPGRS8FCicoOjo9Nln7OXfD86y4+gWGeAyWjEhk8fx5Yvn4SuRGpdm5oSj7iz0nMwxthNnwpFa1Rs2LABTZs2RfPmzcUsBRVqy+XSB+xTTz0lWs0yxhhjt6vUvGIcj0tBJ5vLND7hVd5e6x1sd97BzR+uWqWlnqJI5ghZ2ffo5Ww2NsPQ7CI46zIRlrZRXJaTnYnf97ZD6zXDxWJ8WU9ugIdP5etpMMbYTTNjQetV+Pv7i9+dnZ3h5OQET0/q3i3x8PBAXp51+pYxxhi7XZy+mIeM7Fx88u6LOH1OSmsyc/cv3+/J5jo/a9Cx3NARLgGRIm3qXoUUGLjpKxZ1mwu7CRV262TUMUojOkglnj+Jo2fOW27XTB+DH5avhtJYAqMJiDu8ueK2x+zGlndH4OyJg1fxyhlj7Bp1hSqfQ1pVTiljjDF2uzgYn40+H27BnPdfw0PyVRinWIsfDX0s1/uE1K3yvr7B1qDjK8MQhEU2srveqHYVP4+Y6oifCwz9obtrPgplUnrUaVMwol4/jHTXRnhGuQSLli3DF//stXuML1QfW37faGyBolID9l3IgslkEpfJFz+IoIJjSPvj2RruCcYYq8WuUOPHjxdrVZDi4mI89thjYuaClJSUXOnDsdvMxaQLOHdwMxp3GgxXN+ts1rWQmhQHtdYR7h7e1/R5GGN3tn/nPYs6iSvwp9oJrigQl32iH4H9pnoYq1gn1p/wvkTqEX1GJUENB5QiQJ4NB5VCXJ7a7kWYDv2Ghne/KM7nmbS0AAbyZK6IatEJyZvDgMwkhKmldrYGJz8gF/CXZaAYKnHZAVM9BCEdvrIscT4LLjiSlIfpiw9hZUwypnbxxyO9GuMXQy+MUawH9FI9BmOM3fDAYty4cXbnH3jggQq3efDBB2u+VeyWdOHsMRT/MAq+Jj0OHP0bXaf9Vu284asJKvK+6ot0dRDavbz+mjwHY4wVFRaIoIKYgwpSAA1GKqSUIw1KL/lZR9dRUEGi1NJieKTDoAcBOpVZbOyBVcZ20PhFifPN7n8bh1bOQ4Oe0netwi0ISAbGKDZY7nPe6I8WitOW8zkmJxw7fgxGilDghdLtX2LfzmM4YhwBKIBSoxwnUnLhrynFvt/fRZ1uDyAiqhn/oRlj1z+wWLBgQe08K7stJZ/aDx+TXvwenHcY+zcvR6sew6/Jcx3b/DtCAHiXJqKwIBeOTlIqAWOMVUdidhHWHU1BYPI6yHWFcA+NRnC9pmLWINLX2ZLme+HM0bK5AXsvKn+x/J4UMhhVJ0JJjDIF5CYDRrsdr/I2sx4fi3lbzuKF/g3FeU8ff/QY/6rleteQhoBN06ctxqb409AZIxRbLZeFy1Lwo/pt8fuH+nvQSX5UzGZoZFJg44NMDPhoM8a6HMC4khVI/OMwIl5ec7ndxRhj126BPMYqU5Jz0fI75R4b4zVodY12lSxht+X31IxshHNgwRirArVmvZgUix2pKhw/F4cex2diWXELLDV0wWr1XOlGx4G9q0PxpG4KXnNYhDqeGuiNJoRn/nfJ/ZrTZSa69Lr3svveOOJbJGz7CU1HvlTlbZqFuOOL+6v+1GzRaQCOrX8FDkYpnclHloNHlH9Xefv7uzRAyaGjQGEWHlKsFpepocdC1bs4WFRXVFlmllybWWXG2J2p2oHF1KlTq/2gc+eWfVCzO4ohT+psst11AL5P7w2Xs3K8rDdCraz9Ly7ffOmw3cO66Zhd6oiqGz0yxu5UOflFuPfrneiYsVikD50wdIebrAC+8kQ8okjERMUqu9s3lMVhgeo9hBpTqSVTlQxKRyj0heJ3J/9IoBopnw2adRCnmpDJFfCcuBRnfvofAgtPwEeWjVKbr3Ej5NhljEIH+TFxPqxRB5xIoMDiOEJl1hSsIFk6Lpj8xO/+Smt6l61tp9NxMbcYg5oGWGpCGGOs1gKLAwcO2J3ft28fDAYDGjRoIM6fOnUKCoUCrVpdq2PU7KZXKH0Th4SEwbtYg/T8Enz772E80b95rT5NcVEh1CZpWj/d5IaU3OJafXzG2M1v/dJv4eDqjU69pXTLC6cOoaS4GEUmFcLDI5FRKsevvyzA3OyvoVboxG1GKTbZPYYcxgqPazsAJ4kmb2wzRmN02X3TArohtN/TKPp+hDh/vdMwA4LrQDH+U+R90QfeyEFmg9FIPFOEIGOSeD3UktZy25AInHELBOKl82lyH/gYpQNA9eUJ4qebMVv8/G7beXg4qTC8eRByi/SY8P0elBqMWH00Bd882Pq6vkbG2B0QWGzcKPXbNs9IuLi4YOHChWLtCkIrbz/00EPo0qXLtdlSdtM7aKqHE8YSNPGNwrMR9bFw6Qq03f4a0pr/CR9/+wWiaiIvJ1P8NEGGAjggOZu7nDB2OzIYTUjOKYKfqwNe+jMG7SO8MKShK+KO7kT4wTniNiVd+kGpVEP/02iqTYYzdXEy1cWLxifwomwz1HIpqLha/zaZgz0H9lsCC58eT8A/rAEOy5ygMukQFBiG683LOwDmFaPcPLyR1uJpeO6bCS1KkBbcH1mpicivOxB15XLUbTsAxUe+EI0ugsZ8gQu/P4eAwpMiKCEqUylOxF3ErL+lWY6UnBJE+bvAaCjF/5TLEHU6HoUFf8LRycVuG4wGAwxGA1Qq9XV//Yyx26zG4oMPPsDatWstQQWh399880307dsX06ZNq81tZLeIFfp2OK+PxqKwNhgd4YXgtSvgUZKHc4e3wcf/8jnI1ZVt0OBl3USMVm7EYvUsZJ/uDvR8v9YenzF2c3hz5TH88t8p3FVPjZyze7DjQAGi3A5Aky8dbSdLF36ED86FYZHN+La57Cymyn5GZ/mRq37uWJM/3FqPxOtD22FTk3Ac/GUVPJGLZt7+kCsUiJi+EQa9Hg4OWlxvCqUSeQo3uBhyEBrdCWkHj4iggkQpk9B65hbLbYPC6yFxwgo0cHGHu5cP8vpMA/56xO7x4o/uwED5Plw0eWBljCuCEw/gUUUMBst3iOvPHd2D6LY97e6z6cspCEjbBu0DvyC8XuMavZ7TR/Yg/cJxtO1/v8h8YIzdYYFFbm4uLl68iMaN7T9MUlNTeeXtOxjl4xI6ukhKvKOBxFjkn98DoBYDC50Cu0wN4WfIwtPKJcgrSKm1x2aM3TxSdizCMvVSHD5fF62VJ6UL8+1v0zZhoV1QYaaoJM3pSqiajkDrYZPF766OGjyke1z8fs7TV7rM5cZ2oqv7zD/Iy82Gj38IcPAIspVecNdnoG7DFhVuS8GFWWBEI2SU/Z6j8ISbIRMRO17AtLLRQHzWasgLnTBCYe1elXHuAE47uyFu7ReQe9VFs/4TEJYqtfn+ZVcsXiwXWCTFn8OZX6bDENoJXUdPhUJe9UK6NPORv2QKfA1Z2HxmC3o+/S1qW36JXsx+uWkr6+/FGLvhgcVdd90l0p5o5qJ9+/bisp07d+LZZ5/FiBFS3im7s+QXFcOtNBUGuMDXVcrxdY5oCyT+Dae0g6IrS22taZFdKKU20NE14pp/vlYfnzF24+h1Omz47HHI3YKQZPISXYwayONggNwuWCiFCmpUnebUSm5d2+FquHgHWX5vEeKOu1oEIcRDC/klBsnXk4ubpzjpdNI+CH10MdISz6JZy0unI9NifWmjf4JKrcH+Xz9BD1hb1RJ/QzL0RdIA/IJXZ4RlbIMh5RjyTi5BuCETyPwPh+UK0e6bVgRfdkGD540mnDmyGwk7/kCrUc/j5KbfEFpwDIeOlWDx3pG4t22o5fFzi3XY9ctbkBtL0XPCmzhxaDtcDdLifvRctEaRb6D19jW18nAynv3jkChA3/5CTy5EZ+wau6qR2FdffYVBgwaJBfLCwsLE6f7778eAAQPwxRdf1P5WspteRtI5/KSejT81r8NRLcWr9Vt2h16mhE9pImJ21d4idvr0M+gn343IAHfoZGq469PFlxNjd5L4zEKx0JnJZMKtzGg0Qa/XY/mhJHR5bwOWbdiKulnbUCd2kViDgQIIFxRZgooUk6f4aRtUvK0fI1acNq9ETfVXaT3eh6LNQ9XahjXGNnbnk0MGoVmXYZbzFEx8OLo5pvaVmpXcjNw9fdDoMkGFWb3GrRFerwm+lI3CemNLu+uobkRrlDpeOUR0FD/VRaliZsPM48wS8XOzsSlS80oQn54L3dLHEZ64Avt/fBHylEPi+u3GxjgYLxWHmz396wEUnd+J8LiliDt/AikHpDa4ZgmnD6I2vf3Pcbxp+hTf6Z5D0tmrT41jjF3DwMLR0VEEEBkZGaJb1P79+5GZmSkuc3JyupqHZLe4nLQk8TNf6W65zN3LF4mB/cTvGTt+qLXnckzZg+eUi9DLtBNJXlL7xuS9VfdyZ+x2c+LUSSR91ANTP/4R87edx82M6hCObFuO4kJrDlOJ3oB9FzJRXFyEnW/2xn/v342P/jksgqXPN52z3O5uxZYKsxIuMmnQa7bFfRgmKVci2eSJXqUfYLruMWzttwp9e/RE+JDnkai+dDPqdZo+mKMfhe8MA8T5uLpj0HnSB5Arb/9lnt4e0QRZJvuibLNchQecvaWmGx7F1poW4mzIFT+VMKCD/CgOr5pnCUbC0rcgOE8KLA4Z6yIpx9q1LzWvGJtOpVnqQVLPHYHDRWvHyRw4ISk1reK25GTir3mv4r5525CRL923OnIKdUjIKoILCkVwmp1W1h6LMXbjA4u4uLgKl1EQ0bRpUzRr1qxCQJGYmFg7W8huCYVZUp1DsVo6mmjm30ZqBemRV7O0BFvGQqmbCTSuUAU1Fb/GXTiLUfN2oKBEWvmbsdtZ6vH/RFefrvLDOJokDfJupMSEOOye3Q9bPxwLmEwo1hmQVNatbevXz0C79jns+UPq4kS+3Xoed3+5Ax98+jH89IkILjqJbwqfwSr1i/BBNibrnq7yuZxgHagmeHZAt/53i33hJ5PSaWzrvEiqXKqJsJULJ/xq6IkLA3/CYy99ipjXB+C1198H7vsNXe9/EXeKvo390T7aWn9hK88hAI5u3uJ3B5O18545ACP3KzfiTeV3CI9dLM5TatQb+gfE7yVQI87ki+JM6aDT6ZjdOPNeD3SSxYjbkZykU5hVOAJz9SPxR+PPMaL0dawqrdiefM8vsxCduAjBcX/hp50VxyJVOX90J15Tfo8IWbI4X5ghbQtj7CYILNq0aYNJkyZh927risfl5eTk4JtvvkF0dDSWLl1aW9vIbqFVt/VaL7vLQ+s1RSZccFLnh8zcclWXV8lYUjaQcnCFxtVH/NpFHoOWcd9jzZZLr5LL2O2gNFdaa8FTlofMAmlNl6tx8uRxnDghtRm9lPPpBWj5xjq8vep45Y/zwxR4FV/A0rQg7DmVgEc/+AGd3t2AmLhMhKT8K24TdPY3rH93FNa/NxorDsRhunIR7s373u5xNCjF26pv0UgWa71QJoNTs2H0w8K8KJxJ7Qgvn0DxuxdyMVX5O0YrNsJDba3FyJdVnEV3RQGefvlD9Gwvrc/gpFFCpVSibsPmouPSnUTjVjHwIjqXELi4e4nalnS4YVTpTIzXPYedxobi+iK5IzI10r53MkrNb9f7joefTEp9KlC6Y5V6Bl7Le02cj9/2iwj+6G+c5UAVGkB2/HGc0Adgq7ozOrVsRn/sCoEyFXd7X5Q+13NNTvh9b7xIn6uOnHP7xHeDWWl2sigs37rkC1HLwxirfdX+BD1+/Dhmz56N/v37Q6VSoXXr1ggMDISDg4NYw+LYsWM4evSouPz9998X9RbszmHIK1tUykka6Js5u7hhust7aJm1Br7vD0T9h79FUHj9Gj2XrCywUGjd4OBTB1uMTcWR25GKzThd2LVGj83YrcCYL6WLXDS5I7ug8tSQzPSLOPH1QygM6YreY1+ocH1eXi4KfnkQi/Vd8PCU1xDpV3WXo9/2xIkA5uctR3B3WBHqNWqBdX/9BLfUXQjsNAYhxafE7Q6aIhH067uYYdwEo+x+/Lo8DQ+XPQaVgoQXHBa/awwn4CWT/h/vMTZAG3lZx6cyKpnB7rz/3e/iE0NPdDjyMn7U9xUrTo9RrIdM5QhXT3/LItmD5LvETwOotkIqvjZq3ACbpW5STR64CHcMc+D1F4jWXVqBuzylZyjcvIPQrvQ9MeAngYGhMCYdwllToEgu8lRYhxClMg26d+mKkiW/ivMFkYPheeI7aEzFyMvNgmOGNMBvXz8QrSICgH+XwqtESk1qGuyORoHS++9CRiHyikrhopX+PqeP7oWzMU/MgGxXtEZJdi5+/HwWmjRvhRadBlZo2rF/60oYN76DQo0PTHLpMajWT2nSA3kpSFkwFoH6DPynL0G30f+r8j3PGLvGMxaenp6YM2cOkpKS8OWXX6J+/fpIT0/H6dNSigsVb9Nq3P/99x8HFXeiQqmBocLZPrAg/q4OCJGliRVtT/9X85kseYl0dEzp6AbnoIZ4XT8Ou41RFdIkGLtdycpWuR+j2IDns14VBdw/bj+HHaetq0YfXPcz/IrPYc2JDJxLqzhbeOLAdihNOvST78U7/5ywXL79bDr2x2XZ3zY2EQ1lFzBfPQcpWxbg4P4dqLv/LXgn/IuUZa+IFZ+NkOOCyQ/++iSooIe/LBOZSZXXfzwoX4lwmTTLqavk+NYjCpuaqbLi9HGDe+KfNgsR3mOcJUdfpnGCzGZwa+bsLqXwkKFRrlDYfNNN0k2F8p5vILOdArmDuXj6W37fKWsq1u9YYOgPv1ZD4aBWQquy7t/mIe4YNWQQHtFNw/mO78GocrRcd8ylA9rU8RYzEiSy4zAxq0EunDggmniQuwcNhn8dadaDvhOGybehg0cOPJ3UeNVpKRapZyHuqLR+Bknc/4/4mereDJOjCvGP+gV0TvsVbuumY9ufX9q9Fr3BiKXrt0Grz0FQwTGE5EmF4ImhUiG+V8ZeuOml7yrN6VW1sv+SLpzB/i0rkJVpDm8Zu7Nd8ZwvzVBQS1luK8vSUhJw9If/wbX9g1AVSR+qmkqOfg1tHogzcdIiUoYcKdf1asWdPQG/fCkdw9kzAD4uGkTKEtBWLg2MAvZ/gB0qFToMfJD/QOy2pS42r0QAaA352Hv8HKJXj8IRYzhavbYYaqUciJMGZzKY8N1/5/Hm8CZ2j5F+ajvqoxg7TY2w+XQ6Ckv1SEjNQu739yFDpoL2oa/QsE4Yikp0mJb8LJxU0mH/lIJUpBzdBvP8hmeJNGA0QoYh8u3oIJdSq3yRjaGK7WKGYLepAVrIziBIlo639PdjqvIPS3DgJiuo9DUWQgNHlOCQqS7q0u0cVZg5pBF2nEpEpvyCuI1CLaU5ebtqkZ5rnZZwc7Mu3urd+xmxOnXcP3PF+blBW9C32cga/w1uF+5+IZhn6I4MuGKJsStMJingeiMyUvykAX+L3A0iCAiRDcF9HYegX2N/+LposOkkrXMOfGMYhMKgB3C3myNcW4xAktGALuENkKD0hLa0EKmH1oLWJ89U+aGuj79IQ4qVySAzmTBF+SeSxOxSX9TRFsNbl4Ok2BigdTeRBuUet048h0PjAegVHAHYTG4pTq4AIK01Qo4n5+Gn4s5Ik2vwnPI3cVmCawv4RPcCLiwRMx9m3xd3QeNiHVwcrn5ti5zcHKQvuA9uxjyc3+QF7bPr8F9sHlbGJKN1mCfGtKu9trmM1SY6GHWtDq5w43921WJWfomQ/Bi4/fssthqbYLWxDbS+FQsB72sTihZNKX8WyEk+g7VHr35BuxP/fge1qQQpTvUR3a4PnDVK+Jbl9BKZyQjfnbOv+vEZuxVoddYZBUdTATKObhB1Ax3lR7En5ijSMjMRVCAF4DuNjbDjrDUQMVOnSmlJR4x1UM94XqSy/vfPr6gnS0AjnIfD9/1wcv2PiDt/Ck42uUTaklQcSdOLgMGOXCEGiWYjFFsRKMvANN1j+MPQVQQVlK9/wBhpCSpIY1ksDpsiKmxfIaQC7FyT9ag48Sk6jyiZlEIj00pd6NweWYXCZuOt+0RjM1hUO0LZfhKWGqRWrEUKaTDMJB7uHphnGII/DN3wxrAmcFDJMXdUM8ugY6LsL/xP+Yfo0BVaNsvk7+YgredRFtjR+8PLWUo76jLicXS550nxe7FWOtCkTj8q7Xu1NJOkVKmwQH2/5U/g5CXVXJi8pTRZffxeEVRs+vQRMcNQInNA8y5DRZvcwkFfoGDgp+J2fsWxSL8oFWQf2LYKKfOGiy5VpfUGwnDP90iMfgKNx34Av5BISzti8oF+JFbrW2F9zAUc2LICGz55FNvf6o8LZ6X/M2dS86EzVL7AIq2ZRHUaxUWF+Gp7Ml4vuU96D+ozsH3xXOz99U2s2X8GL/4Zg1MXrYFMZeg1bl36pUjfosdl7HpIyCpE53c34vUV0v/L2nZnVamxStEH2rGjBxEe0eDK2gUrrDnKC3NbogTtMSikUYWb0RdQ/QaNgaNAsCwNo37ch6/ub4GmLnkICK1XrYXt5qw5CY1Sji2m4ThV2gpvD462FFm+oVxQ4fZ0RIy+vBi73ZTo9HA1lnVGK2v5mZdg7c+f9OdM+OO4+HDPUPmjveEYorNWITu9Idy9rTOKnqXSgGyU80EEFC9B0oF4BCZa1xD4Wj8Qscf8MVWTCOr1RqlOlPLkpMvAl/lN8bmpGX5Xvy6Kpkmmc3345lZcJ4BmJJrJz4rfDxjriVmI8qh7UFOZtc0syXFpgP05RjRuIbWUNtM6uYqER2pNmh0xWLrQNQDqTpPx2b5sxJt88Ee5I3E0SNbKpOctlVs7RjFp33w9thUyCkpxX9tQ3N8u1O5IZqRJmh0ivnWkLnwWGmmw7oQSaJylhVFtGd3DgZx9CCw+DUpo01O9S5nTXr2Ql7REtIF186f5DMCvaU/g3K8IzdqJr777GmlpWvgp1MiInoBGjlJA2KRdT/Fz+4ZwEVgc37pUBDJ5/30ruj8Nk/+HjLC7UL9pPdRvKi3gS+7WzsZXRdPggFI4hTZH+IVkhKx4Fa7It8y+xS2egTUd5uDX1ZvwiusqNJ/4BTx9/O1aJ+96b6hIMdzjGIU/DU8ixdQAqz0fQP/MnxB25icxMxOujMPz+kewaNsxdC74F8aCNLQZMxOubvZdE3ev+w2BBz8Wv2+KO4oe9z9XYR9Sp8MvNp1BXGYRRrUORpd61nTjlMRYnNn7LzTOHmjZbdgd13iAXZ3Zv6xFYrYSC/6LxatDGqO28YwFw84Ny+CweAz++8o6pVwdNDtA/jR0FoV15iNZlQkIkxaWokHIAPku7P5tNoq+G4Zda3657POk5hbjs41n8MG6U4hJzEEOnBEaJLUrrEpWpjXXnLHbSVpeCSbrpuAV4yOW2gGPzEOW4mkPk3U2wxQ1BHc77Ecn+REYv+2N0uVTaXSE4lIdnI1S3YWu/kDx0zd+NSKNUjcm/X2LsdjQDTsSSxGbIKU6pTpI60EojaVwMRWI2cI0TYj1ubyk1BmzbJWvJbCgdCyqpUhyb4mpKmlxNWIM7wKFWyBUkT2ww9hI5PebBbcZgpEvzEfXu+0/lxxdpFkKClDo6LpZA38XDB8/DbOfeaTS/eYGKeWKZk1YxbazFFSQ8ukRHsXW9q6RjaUuWmZZPtLCgsMU/yG6UCqct6XxrWtbJiNahJv5OhhEUCF+D5QCC1rg70LwEPG79sJGLDAMwIbOP6PryCkVHtvQQLrdqWMHkFtUAq8iqZ6HGgEMiaj4Nw5z1iHe5It8aDGsR2e0lJ2GO/JFHUi+QtquwMITWLf6L5FGFVZ0DFmfdse2t4fgv7++EdfHno4RQYX5tnUL9oq0wwcefgZ5CusaTkWNRuEhxT8Yc2gcQs/8iPDk1dj3l309CCk8YV041v/UzzgTewHHk3NFrYj5ANnnn72PzzeexYpDSRj33W78s32v2I71n01G3ryBCNg3B56bX8K2D8eIwKe20pzXf/mMaBHMbi8lJcV4/OKrWKB6T7TpvhYLrPInLIN+309iL9TN2XlFe8OkkxZEokFDENIQ6CyHg0pR6W3dPKxtaANkmbhfIbWglO1bYPOtI6EPx42fPoZtS6Tp7qLMBHym+gSvKheiWCd94Eb4VD2zcsYUhHS946W3/RZfrZjdXg7EZeH5Pw5j93nr6sZVySzU4awpCOedmiFfLh0BriOT0gu/0/fH94b+4ncaHjbueR/yfaR1AbIKdUje/w+K4vYhLS1NzD5QNkv7QRNwQREGpcHa+CAiLAQt60iBwaGTZTMJLv6WdBJqGxro7oDf/J5Fv9J3cV/py8hpNEbMapjlO0hBwlvK+fD3D8R3zhMxfNw0RDlYA596D32N8P+tw9h7x6Co7xz4jXjbcp2Dsxu8KzkK7uwiDQKpQFxmtG8Z2q2+D+r7Vb7gG6WJEd/S6q+DwIAsRylNLUfpXWF2udQnGqfK1qRwdqz4mewe3kys7P25fhiGl76Bo2FjLdeFlUqdxIiLqzWtLrBs7aOW8tNwVAEPdZMKvctrN/hhvOH4LN4oHIFHP1kCB2MR9DIVgl86gNBwKaCxNbBtNB7T/Q/TXOegXYQn7nE+hIuaMAQ/tQbNXt2N2OCh4nYt5KfxpexeGGXSaw0oOg23A1JQkHJ6n91jzlJ+j6F+mXBzcYZq4NvIUvriYpvncO9dwzFKudXutpuSZHbfO6UlJfDP2m85Tym+n3z9NQZ8vBUTFu4Vlx3athJ35yzE3eqdaBXqjjHydai/+gEYfhyJ8NT14v9wqiZMtF8+myPDoXP2Cxlerbm//i2Coaxlz+NaScwuwl8HE8U+OXFoB4681hL/rfhOXFeqN1paClM3urOVNJ9gVycjJUEclKGaqa/VH6Awv/bXQeLAgkGvtU6tpqdeuv7BZNCJqVlaIRelhZYvgB/U7+B9xWeXvG92t1lIjBiFvlprBxrv0kTsfaun3aq8B7f+jdC0TQg49Lk4X5STJjrSUEvZL1Uf4nHnrXBUW6d8Mzq/jjw4io405KQpGGn5ukt+oLV561/MXWvf4pKx6+nk4tcQM28CUuNPYevC17Bhb4xY5JG6Ml2Ked0KD0c1SpTWQbRJJsc5UwC2GZuIwb739J1w9gpEmzGv4ET0NDEo1BtNSDy0AdkZUhOFIoUTtFotDGGdLY9DR6xVDq7o4pGF+xTr0V8vHVVVOnkiWyEdIPhS9RFmGOahRZgn9FDC1TcE3Vs0FusdmGcFDDZpL92iw/Hec8+gjo8zvAfMgEYlh6HRXWKNCqrNoALaSV0jEBndFikmKV1Eoa28/a3KwfqaPfLOXPF+L1BYt4tdXt373kVc8FCEPrqownU0a+VeNhPk5F6xI2BwZFPM1t+Ppcau4jPa0dWaCtSqdE+lz1evSTvpsVGEnn5F4jkqo9Y4YOoDd4vf3XKkz/JUbV1oNFKjkPLuaxuCT+9rgYUTO4qW+R1m/IP2L/wDdy9puxv0fwJPGafiV9Vd+OzpMUhv+wLi3VqJ62hV8aKCfOQnSc9zIXAgkh2lWfhh/lL9UuM2PdB65hZ0HDIBDlonpGvrWJ57gO5dLMxuhtOp1u+5uLNHRStemjExjf4Zfyn7YrlRSvvbfvoiCopKkLf/D3F+UKgeix9tj56BBsv/9Xi31igZ/g06vLQG3zRaiFn6B7HylPSdHH/uJGJ2rKmyboPqQ6pyJDEH6y5K//e8dMnYtOhDrPntUzFTeiXMsycXMgow+ef9iEmwpm+Sh77bhc8XrcDK9Rtw/u85Yh+f2rUaecU6sQbO8Jc+xZrZ92D87O/Q/6PNOJVY+edi2sVEUavCqic3U6qTMs/iZmfYZ3ecOXYA679+HrnZlz/IdVsGFm+99RY6duwIR0dHuLtbpyHLrxg+ZMgQUTvg7e2NKVOmoLTUfkGpmJgYdOvWTXzBBgUFYdasWXfWEW29tTDzwjH76ex1xy7iteVHcei/1fjvpzdw9vWmeOX1l9DlvY24kCL10qfIl5RqK19oyaxVr1HoOn4WXAfMtLvcozQZJ/dtEDMXmxd9BPeN9j33i/Ksxdn1ZQlor7HPxW7bdzTi7v4bT+mewgTds2K6O+Dn7thZSZrVxp/fw9I5jyE9vwSfbLjyQQljlTmTmicC1vKqKgDNij0E1ZHf4Ji4HXnfDMUg3Rp8pv4ESujx6Hf/4fc9VR9VL009LRaB66Q4hhRtPew31sMzuslYGPCyOCpP1ylghKur9Jno6uqBQaMmYVOIlFJkvLADiUZvPKKbigXuUooJ5WiTRJM33tL8jwqjEGGKw0TFKjHDSFQuPkh2sKY7OavleLxbXSx4qA3+fqoztGoFzkBKp/lCPwxyB+tnsoOz9Xe/FgMR/OQq1B/5RoXXJmY8PesgRxuCkICAyneAXAEPRxWcNAo08as4o1GVnfWmYY+pERoNm1bt+zAgMKQuejzyHrz9pHVBbLkpSuBbtuK5q2fFjoBuWpXo3GdGfzezqCHTkKv0REKjiXb3oTqBuNC7oJOp8UzPijMPtmj9C0+tHNFyKQ2q1FVKqaoMBcxDmgUiyF1rOS+36UMcHBqOj5+6D/883QWhXo7oMOhBdPvfj2J9DpJ+MRGflQ7FmNKXYGw5Hm3/97s0sB/+eKXP5z/oRTGDcqHOKDQJlYIXSnMyi81XYr5hILY790Nk41Z4cOr7WPpEJ7zj+DOWq17CuUPb4J8rpTiGdRoFuUKBnpM/hffU7fB/die6T/tJpI6Rfk2kv83aYykoyM9F5g8PIHXV25i51H6GhRSc2YyUDzpg659fVbrdVLhOBwgorZKEHJ2H/TFH0f/DzThWbvHCylxMuiDSx46/2VasQfLhulOiS9aQz7ZZPg8peGiR8bc4QIHd38Colw4E7jI2xOGEHBHEuMgKEVl8BB8qPsKPijeQsE460Ghr19pFyP28Fzb9/LbYtzTzW1MUjJkDspysTGxd8jkKCy5dhF/bCkr0yCm6Ngs4FubYB2h5WfaBRcaSaQhP+AvHfqm49lF1VbvSp06dOlfVmuqZZ54Rg/lrgQKEkSNHokOHDpg/f36F6w0GAwYNGgQfHx9s27YNGRkZGDdunAgaPv1USrPJzc1Fnz590KNHD+zZswenTp3C+PHjRSAybdqd8QW0Qd4e47EbySZPfB8DvNmiWNRK0H6a9MNe0bVlrOpTmHup0LvgJeVPYqbiM/1wPKlcJi43L0Z0OY1adcU5tz+R88MDopMNcV73HLbu/g3+OdIHqVmLWWvxSEAs+tpcpneqOOBw0ShRAC0a4QIeU1ALQmDX1nVo32+M5Tb0YRF68juEyoFWqlP4zxhNx4KueH8xZisuoxCDPtkmMvrmjm6GwU0DAX0pji18CrK4HYiPfABhPcbjZHwqOjWpBy9nDfbv243wcscujM3Hwv+0C+7LW4Di5T/iP+dPKuxo+j9pTD4s1nlI1rXGidaz8OZKqZNNtzqRGJ80S/xeZKLB0F129/Wv3wa4AKjy4pFSYBTpVPXL1jDQuErdeqjlaIqzlHqicLUOFCl4aeBdF9uKe+HkCSUeUqyGzNlHBBM9GlgPKBgdvamdE7xkOZA7WeugHF1sOkjR94iHVK9RmU7/+/mybzDPzhOA9DNAaFtU1/1jJ6FYN6HKdE125VyyrbPPto0BbEV6O+DJoq+ghBH+pldoCC8uDwyLRODM7ZXep8fEt2HUvwF5NYqRP1d8CF+DFIjLXSrfhuqqVy6Njmb5jqqbiAX7muaVIDGnGJnwFEGIWqOxDOwrfawmbWFsdBD1ZTKsW3YExy4kIzEhDoZoP5w5tg/bT6ThF0Mv3B0q7Q9K+6NTjrMCmuxSxO5dgnCTTnTEiqpvLZp3c7cvACedI71FvZUxMw5bft2A+sY8pMAVP+1NwWO9iyzB1MlDO9AuR1q/Q3aC1op5rMJjZaYlwR15WIv2aA7p4Fsb+QnMK9ThhaWHsfxJ6+xmZY4u+wBhRdL6Zil/zYSbohtayDRIMPngnx2H0KNJGHYmlIqFMelzrF7JEYjKfkAsvLj7wEEx5nC2WZPKB9lIS7BPLROXb3tV3JWK5t84AWw2tcBXD7QS7ZANRhOKdIYqZ7yqsunjCfDMOYrAx5fh+MKnEZR/BDtTT6Pn4x/hWjh74iCyk2PRuPMQ0aCG0Mx1ck4xNkzrBnfH2lnIU6crxemYXSjMvlg2ryxJWfcRAiMaisYCNEby1klNPYLypa6BV6Pae/z777+/qicID6/6C6SmXn/99Utu29q1a8WK4PHx8WKVcPLBBx+IwIFmO1xdXfHzzz+juLhYPIZGo0F0dLQILubOnYupU6fetoso5efn4vzxg2jcsjM2FEfh99K3pQLsRGDLexvx4whvpP01E93lnfCKUqrBMFtnbIWHlf+IhZColeWTkAILmKo/HekbUg/v6QfjWaV1ej0wx5pvSg6a6oq88MTYk4DNWEBeySJ8bsYsjFWsxXjFGstlaw2t0S8lF1H+0rRuns3MB+WIUzvMmwXl2277/kW41u+C1j2G1/ixti/5BEFNu6NetFRcySq6sO13QKlEWPsRNdo9MWvmw1vvgkT44M2/j2NgdAASDv4LzYXN4nrtudVIOL8JUfpYvLPuPsx+6SXMTYxCfOnreCbgCLpnLEaWYxjaD3sM/xQVI/eTaSguLsLHP34Oj7rtMMBm9vTzX5ai50kp39ukccNdLYIsgUWkr7WN6tNKKpB+y24769drgHtXvgyFzAkjytIaaC0C4uQmBRZUzOpedlTZoSywyIMWz+ofw+qGXdDbJQcJJ6SjliqXijOU1Gr0k1VtcHePduJoX9DJH6THtw0sakPnq1sxmYOK2qVSW5t1ODpVXtvysOlP1JFL3cJKFRVn9apSnaCClGg8gNI4nKZajyBrF6jassTnSew4l4EPjZ7IKZJqGNzLVgW/HJplIH2M2zFR/RHiTrXD5vQ1CDv3G6jZ7n7Z44jwkVKqzGS+jYDsPQhP3SDOZzjWsTxOVZw0Snzu9hPqFRwApE7MoqmKCXJsOZVmKcy/GLMB5hGZo03LalvhZ3/GEvVqXAgfCVmsNObXNxwB5REZYhKycDYpHXUDrQtQ7t3wJ/IOLkX0mLfh4x8MdY40e0T1Vn8WRONxxQIqiJKsBc6td0ORuh46y6UASayIXoZaUtc9tgpDVSelNDSb7Cmf0gQkxJ5CcLjUkpgK2G2PzdA45WhpOGYsjUGUvwse+WGfaKu68dnu8HWp2FQmJSkOvn5Bdvs2ObtQdCQjRzf8hpB86X0blrwa10JWRiqMv4yBO4x4bt0eGBuPwKSudXG0bGZo57lM9I+2NrSoiW2/zUHo6R9AI2Hb/UZLBmyc/yLqdh4Nt5DGovV3+Q591yywoFShW82OHTtEoGAOKki/fv1QUlIiVgmnWQq6Db02CipsbzNjxgzExsaKmZrbiVGvx761P8Gw/yfxH/Wf7b3hnhOFRNTBoKYB2HX4BDqajsDrrz/hDRNeUdqvnJsUPAB7J9yDI299BI0hE66yAhxEFJrjBIK6WAvzLoeOIpgLTqtCR7i+U72HsLLe6WYqt4pHpVxMeXZBBTljCsSe2CwRWBTrDNh86DTKN8M9tnczolp0rvSD++yJQzAaDbiwawVaDXsSHp7WAvTatm31rwhLXImzCQeAGgYW2+ZPR1jKOmSf+QuI3oZbRX6JXsyG0ZfktZZzMQ76tVJKnr7lICjV0v9/ep+8t/okejXwQqf6fjCVFuLsdxMg92uMiLvoaCtw6MBu0cq4cXQLwGhEw9Nf4we1Tqz+HlKUigOn60J2dKPlqFCgQToCRB7T/4w/tw8XXxwqhQuGT3wFxbH90Cg4Sqwg7eLsDHW/aUhZ8ZYIDtafP48Nhxugf2tp8DHg5EuWx5I5uovZjxcGRImi776N/ZD9t0IcpXNSV3w/uzk5IA0ekJUCzim7MEZxCI3kvQBEwzGwERYY+ol2nW1MVOTcHo6e0swgde6hgwgBrlqENnXEH8ukLz2tR8X/hxH1o/FRfZoJBJbts352uNgsWMduH41adcPGvX2h8JYWMayM2rsOUPZfwNmt9j9DDY4+FP1imzEa/ULsF4GsDeZOh3EpGXhO/hPyZI5w0/S5osfwpHa6hwHX/DPQ5MZYLp+m/B35nvYHNlyDGwHWunbovCu2cK+MmtaQOn9A/F4s1yKy8whotpzDySP7gLLAgtIozWjdjbOJF3Fs4TNw8vCzHJGXF0ipMWqvEOhbLcDF4/+hzz1P4Onsz9A6eRHi1g1A3XHWdGa3zS/Bw2TE6e8mwufF1XArkeq3JuufhoEWWyz3UeRsyEHjor2or1RLLazLukuSV5Q/UoGWtB0h7USrYltnd62yBBZJ50/Ap6wFNokNHAh5hh8y84ow+sO/Mcq0Vsy0xO0rRZJShZJNc+A66HU0bNEZ3y5bh677n8axyDHo+eDLlsdfeywVpw39xYxs8amNSDJ5ibV4qKaFjvirVFJAmRR/Fulxp9C00wBcjdMxu+Hu7Y/Dyz9BeNn20+f9X8dScFLeEW8oV4nnNe7rDURbt688mpX5YuMZNA1yQbeoigGIWAvmwwchN5YiNF9631WW5B+dvQn4exM2dPoer+omo7FrMbo500Kn9mnr1XXV3+A6nQ4pKSkoLCwUqUaenhWn52402j4/P/svPw8PD6jVanGd+TblZ1XM96HrqgosKDihkxmlVJn3C52uFVpw53BiLu5uEXhVsym7VnyDgIPWFIuojH/xiepfUfj17vBe2If1CD6x1O4+8QF9ENh+JELrNkaoxknMTBQrnOFmyMRAxS4E3j0bWmcDfEKjrui1Z8FZFJtSsSYFD3S0wiwXToiW2Qc1ZhpXnwrPo3JwMn8eWYTIUnE05iBWH/oSy1M8sbMoBIvLHWjSLH8U285PRofhj+Hk4Z3IXvMO3Po8CycXT+CX0aIIid4B+/4yodsD1kGdrYu5xfDQqqCQmcQHDuUIU15yZczbTT9tV77MTo0X/c+p3WZJSam0+FQ1lRQX4eDmpaKNaFHiEZxKykaYHHDXp2P/lr/FQoI0pU+dN7LXvY/SwHboMPJ/lg/J6jj43z/IObQSLR94EwmHNsArvImYdaot1AWky/uboVUpsGFqFyhsXv+JlDwxle/iUHsBR9ypAzD3DcuOPQC3sObY/P0rkCXsQVcYodpTDN3L23By2zJokw7ClHQQhX2mIDnfhFV/fCe+sIKC/4TCUCQaGpBol3w4FmRi965/0DK56g5rirUzADyO7vV94KKWwaV+O7v3hjz6brjsXIisi/HoJd+P/Yf/hq5pHZjSbUYbFFg4uIn7PNwxVJzoK8PXRY28Ej1cHLUV/o+o5dIXGE2AeF/chn6Krcgu9oNO1xeubu4ifKAGCfFFrtDpHoSTs7V4OsyhUHTogVGPu91Po1SvgouX4yX/v2sN1hW1ZaqK28Nqh+1nyo3QddIHl3x+F29rSpyTs3vtbyel31EqkSwH3o7KWn98X2c1ZDCKNSMmyveLblH0WX8lz+Md2kCs3uKut1+okgaPelkKdDrroNAzqJ7dd5k2KLpazxXS/m6Uxi6D2lSKFL/u6BukxyD1KzDGqVBU2A96yDEldwx8DH0xX/0+1NDj+XlL0NnogH7F/2L9z3PQqPsoOBRLtZNa9wDUadRanIwmE5r5qeGbkoX4izF4e+UxHEvOxb1tghFVFhjQmiJnTxyGY1kb67qRUVCdsT/YZyur/fPQH/odgYVSQTwVsVMBt5mjb8V6GeWZNSgpfkwcCNwrb4qPSt/FqIZajG+qRZdGrfHUkt/Q6MQnOGyMgEkmE/s3LuUsQo/NE/3sMv9+CYe8lmLtrkPoqFLC5fxq6HTPi7Hczt/exvKEMOQZo0RgEWyIx3DdLCxTz4TWVIJTMXtQv4mUepn+3X1wMuTigNGI6PZ9y6WSJeP44tfh1X4Molp2tVxOLYQplW7epjNoETMbococnDUGWWaQCM0WND75ByLLaoYSUg5e8m+/KiYFW/5djlbKP7C/3yv4Nd4L57L0+HFCa6gUcpw8uB1huRXrbOggWD15IjwoIrd9/sOUNRKGpg0iMbZjRzz//HUILPLz80Xq0K+//ordu3eLP4Z5cBQcHIy+ffvikUceQZs2V59+8dprr1lSnKpCtRCtW9v3065KZYPv8kuZl7+NuXD7UgP3t99+u9Lt3LhxoygmNzPqSmBIPQalfzRkipov2PbyTh2iZeeQtNcFkcHSTMzJHBmSCoDuAfS6Kr8fHXnXlxTC7dTKSq+fqfwB69c1RonBA9SZnvZAlswdJ30HQ+vfGDlxWTgeZz36rTWqQeHXYPlO7DywGakegcCRK5w+C+uGmck9kFwkQyDS8aPa2mrSXHtRmdOxSUjKlfJEzUqL8tGy7PdEeZD4kJqHD7HjQiOkQIFp8mVIVXlgpbEdBsntC9TlR5dglToUTgfnoY7hHLDiMfypHYGhNkdDTPF7sGqV/XOSUzkyfHFMjkcVKzBSIaW+0MTu8qZvVrlAX6Ee6PTOBtRxMWFcfenxZalSOgt1tvrtr3/grgFKDMDSWDmae5nQ0F16T+alnILS0RPaspx48dqPr0DLQpuZCZm1BsXt3+lYsb0jlA2HAUd+Q3TJaeDsaSxdIINLsHRkuTqi9z0vFkmL/2QAnE35SFZ4YW/zios5VUdhZgKQEweHsPaQl7WvpPdvVqESWdDh9+X/wK0s5jmbC3xyVAk/rQkvNq861U5vBMrSUwX6L3wh/jxc3L3h5VoxRUN/dgOkJqxA/s/jccixOeoUHJQKiMp8tHAx6uRsR4uy8299+T0SVHXwlGKf+EBe/vtCaDVq8b6jtVVS1PXQoCAB2th/Ea9XIwgqTDU+jUS9KxrLYzFOuRb1kIDmsjNoLzuGKJkeq1ZZZzNsebn1QoOsBcgtlaE04RD2/TYbjRJ+LatwkiSk5SC93HvS23sUopKXYofnSGSWu466Nz6sWCtmGb3yY8VDpWbkifc17S8XKo6gAyr5BnFZbinQsey+j8r+xKpVUqpVL12xyGzYcjIDeXEV/0+YKYszQMtMKOUmrFpd9QCD1Y5169bdlLuytCAb1FuJvps2b9txRQdNqiMvs0AMzrrLD+Lwzs04pazdxw84vxdr1EuQFS/NuhXAEf+svrLUGJPRhEiZRgxQyUHHjijReEFVmgPV2UScOG/9HDAYjWgMhVj4kuoQTOmlSK3ku6cyRQ2mQZd2Bo4+TZF7Lg6RMhUcjUVY+us3yNaGQ2dQIlvphbccpmFPrrtIf35U9YcIMsJPfouLp36Dj0kKDE7FJiMh2/q8+TnUVl5KnXlj2zZRo3U0LhW/QS6aRZDDS98DVYPkypyhLkzDvYqN4vLzijqoY7AeKNzuez9cS52h0lmnM84rI+Gvi4OnSUpZPpOQAaPPKIRnbEJs4DC0SPge/iXnseSLl+FUtwt2nBUNs5GdV4iTcQU4GbcasqJs0emoizzG0ho7PfZoWUsJQK3Pw5J1/4kDeDQLqzJkYPlfy1CcuB/tM/7Ee9Tly/SGOLBJY5BGsgvYZ6S0rSM4s/oLnF4zDxedotC97KBJ7NZFiMu0XzvE7eDnCDHEoWjVPqxKsY4RV8XJsSZRLj5nH1Sfh6OxBBNLn8Jah+6YYfoaJUaFWMtnomGl5WPes+AsvvtjFTanyOGqMqFvsAkKmfU99dkxBR5S/CdSu7F2qqiY2WtsgB+WjEeAsxzLzgPm+Y7fDD0sf4/PDcNFZsqjCqqzkeihwJIMaU8Vpl7Apk00Y4FrG1h8+OGHoi6Bju4PHToUL7zwguigRJ2UMjMzceTIEWzdulUUQrdv314UR9erd+VHNJ988knce++9tVK34e/vj1277AeRWVlZIgI0z0rQbcyzF2apqdJUYPnZDluUKkU1GLYzFiEhISK9ysvLOt2786fXEJiyBBcNHdHmsXmX3WadXo/1v8yBa0hjdOwhLQBk69TuJ0RtwIGinhg4cCJyi3R4erb0ZhnZuzXahlc+c7Tts0kIy9qJIlnlC9id8OiGgQOlhbJObHNFbsp5BLcdgmahlf8Nt5z9E8iWCrs6dupqmZ68EtKzASm5xTDpddB9bg0sLqVnv8Hw8gmosOjLxWNSl5mQ+z9G8qn9wK7ZcJcViFa1hLqXLNL1QDv1CbEwjNkZx2a4f+BA7Dj+vSg8JcOLluJN/QN4uay+JEJ/FhmHPkCuVzN0e2Su5b4/frgcn6m+QpSsLLG1TLivA5p26Fdh2+m9N+e3f5FVKkNWhgwfdOiGYA8t9hyR8uZLoELD6Gi0qBeKj9afwc7Uc9iZCpx+oy8SY0/BsE/qK+725CbL2iBxZZeZnTcFiJQWs+aF26FtNRMXYqxdNQJdgC5lf+/9G5eg8OQmtBn3DjRa+170yUlxOLNhoeU8BRXEw5CBRr17QVWWQiS2vVSHhPjziIiod8mgPO4NKV0ho1kHtOgsbcOmA6fw5fGnRYtJz3pzUb+xFCbO+psCrnhcLJJhwIAB+Peb5yErLUCXSR9Co5Gij9iki9ix4AUYAlvhgYeeFJdtOXgSdfZ9CXmqEX3HvgBZaHugLLCnbhsbD1trewwmIJyCinI6xn2ObDhZPuQN2XHYbIhEd2UdcWTfX1MI/zoRwFmgUOWJxh0HQb9yI5x0WZiomwZnpRHT+zfCa3+fwA5jY4zo0QOGHVOwpyQU3foMxsQu9gvK2RuIC7vqQbb2JchLcxFZdABpxfb7tGGTlmjYaWCF+wHTUVWmefiBN+Fqko5S0aN1GXQfNP7S/93w/dKXoKuTI/oMHCg6uHxwcA36KPZjh89IvF32fkHnZpDlJKALpSpciskIuUecWDhvYNPy28lqC32mUFBB373URvVmtHujC9RaZwxuL62aXZu2/n5S5OJTyt6IobXfjOPAFj0UmxfD2yTNNpQqnS3flVdi1/FvoS0+I4qYnZoMxtC+Fb/fzbbs/xjhshQsMXTFz6Puu+paz22xf4maAX95Fjyj7wEOH4SXBght0ALb9kgLX+4x1keEQgpsXMo+30n/ISPg7GIt8y0pKkTKB5+LhXG/Vs3FQkNf/FTaB7PlY/C4coX4TnUtSsD7htFo4K3GvZE6+KZKdRzqJsOAgx+JlsO/Nl2AN4dJ6V2b49YAacew2tgGBfXGISzUhAu7FwEeEbh7tDm1+hXQoertf2kQfPgz1MvfjWb938KiH/YDqZno0bYpBrYIso4D3pO+S81H4/1gnSVa4jgaYfUbI/X0cWTCBZ7Ig4c+ATKddXX5v9Sv4IJHR7hmbReLLbq1fwBxu+bCrSheZEE0KdqN2foxeFH5C/xMF9HG5r1ALXYTy76PtaZiu/dJ9pyn4aNQY6WhnVgslL7tQ2Rp6NezFyKih+Hv3+bhq+QPLV34iCOKsL/IC+cvnkN/xW54R3aHo5MWMqMRJds+hyH/Hrxjug/vqr9BA0gNDOjA0X+yMHRuGY64M4ex1tgafeV7xYz0MVOYCJb6y3cjsvv9MG1bZVnomNK+5qq+hB+yYGjwMuo36oFrHlhs375dHI1v0qTyHMa2bdtiwoQJ+Oqrr0SHps2bN19VYEEtYelUG6hbFAVDycnJCChrXUgF3VRP0apVK8ttXnzxRdFhilKkzLehuoxLBTD0GLZ1GWb0wW774V50bof4BvdL2w6TvhTqcgM3M/oSn7P2JC5s/U0qaKbuLX1HVMhB32+qhxHYitDCI+J5Nqz9V3RwoNVE4y5mIsJZBz/fgAo1A/ThQse8zxr9RccFWyeCR6Lfw69DWdZ6r0mPUZfdt3CwfuA4u7rX6AstxEu67wzDQNHesjLFUOMD/UjkmJyw2C/Yrk0goeff6d8fMl0BetZthMJsKa2K9g39h9KKiWigr2KvXVBB1AqZuL+5raDtc34S8A6mJEtt17z0qfC6uA5KhUKkFtHf7GSepkJQQbJPbIWq62DRL3zPondQ7BSA/zRd8UDbYGgLEzBBcQyRsgSc2RyPsBGT4FEqfbA/rlgO/LYciWOX4FxqAYJlaaIjhko1CHmZFy3pO4dXfIqeD9sX55rRismUQmMr9vBWeOukL5ItxqbINkWgZ9nf7PSW39FBfgy7Nq1Er6FUUihJTU+Hbv4gkaJVmZS4k4hoKP0/Ss/Jw7HP70NQ8Rkc7v0Bwlr0xo87L2BAtD8aBlhTakqKrTNRsbIQtC3bBvXZVYiQSYWRKX89h1PyOYhq2BTNczdgvFpqixgXuwQNLv4jfh/11vdo17E7BjcJQMyvbyPMEIc/Y8PwUNnjJeXp0F4WJ2ac4n96Ahc926Dl4/PhoFHjtcUxOFHYDfNU+8WRK/oCJ/SFT/vbzF+WCX9YP+SPGsNRV5aIVJN05DLj9G78dbIIU5VAiYMXghq0QPwqmkhOEW1jo0N9Mb5zXUQHeyA2oxAjWgRB3n276BJTHYHNeqHrSh3STS5QJXyFFuXu5uDqc8X/73RyDWCQvnB1Ci2cg6JE+1ZinrFwMhWUfY4B8w2DREvMAa4B1ufyCpdO1dH3tSvaPnb1yn/33Ew69ZXWm7gWGnS5B8Unv0O8tgHqXoPXH1g3GiXSZLSgUzpf1X4uoVa4xWewwdgCQxp3v+RjUBe2FJmnONBkHpdcDVVER2DfTqhTD8F4fgNeV/6FJEUjePtEoYP8qPi+SVaHI9GhGTQl6WJdKZKj8ERdT/txmErlhiKZIxzLgo9xirXoL9+DB3Uv4HhpmJix32xshhhTBPzqhiEgwghDWdOvxl2GI/vgR+IzJtBZ+r4lCT5dsTzZHUdN4RjsGYqmHeoDHSqvX2nVbyzmHDqLTUWNMS+zBHdd/BzdlUZEOr5keTz6aV+RCQQVHrd0vNumaIdOsX/ia9UqEVSQsGP2B3zzFW5QBDYBsrZjjGI9wvp/guFnPfBA2lwRWBD63iD+JRfEAb9zm36AwskTnnXbWL6jqZuXebuoXW3Hok3orDBiwsQpSFwUArfCEwiVXUTzUE94eHoizMcVQSn2rV/J+YRE9FPswQO0qPB2aWFhs9aKs5A1vxdtunyH3M97WxYIXn44WZxUChkuiNwSiHRzGhvQGIv+TkMbNoYy7DcYfpLGexlwE9vjhVzovTxq9FlS7cBi8eLF1bodDbafeOIJXA+0RgXNltBPai178KB01DEyMhLOzs4iNatRo0YYO3Ys3n//fXHb6dOnY9KkSaIjFBkzZoxIaaJOURRgnD59GrNnz8bMmTOv6ihBYlKC3YzF69oZeK/oVTFI2TZnJAwqJzg1H4GO/e+z3CYvJxPP/7oDq2KBV5XSfwJy7J95qNdtNBbuy4SDUo7mpuPiSKl5kPv24i2of/QbLFGXTVmtBfIhx97Ih9GwUVMUZiTAMbgp0rfNh7mPEtUzlA8sVJ4hlqCiumRK64ed1qnyhayuVKqp8rVICA0QNxmbS8VeVWxr7yes7eA8/EJA/Uco+qcpUXNgIf5zluMoK0WJ3oC3lY8hrjQHPdXH0NR4DHVlSQgLaI4tiU1x0eRhSXXKzc0WLf/2blmJQcZNFYrTxGOmSgP77V89IWaK6EhBgfEcVsYHI7zgCFqWdaRKPmtCZvpQkRdrK3bZLNyj0GK6SsrVLyx4GLqyBQmJMl1q80g9y8ub9+RQmOZ9aAki6D1Tcnw1FCaDmPqepR+LloVeoL46RaUGsZgZKcm3z/9NOLHbri2dra8Ng3FmRTymqcLQONANo77dh2+KpRmsrL1/IG7zD/i2YBR+2BGLFU92hpujCmqFHIlnpNWPaapZ4+aHmEN7cPHwetQ5be3s5m+4iJI/Hsa/zk3QPN+aH3p26+8wH+OnVsf5O2Oh3bMGXVAqgvckk6coZqP6jHSDE2JNfpaZG7/MPdi5YRl2oAn+PkyXBeNfY0spBUCWgh1OPeGWf7bC66Rg4xndE5jtvhzFOWpxpM6stfyU5QvGoPWB0i0QSqUSRp1efIi3rSO1bW0d7ilOV4rqhloHOWF1AlBsUllmTubqRyLF5IGvw6pX1GlLL3ewFEemOdVDg7KgwrzGAM3mNK1jbXYhkV1xy0bGrpeg0AikTd6I9teoQUBAcF2ckSkt3Yv0Kmv3tSuhdwsHUiE+b8q3tS3Po/8MvLTyOJ7rb98x6koFRbWDcR/gU3gWSRdjRErPfrkH/LQ56KmUVrnWu0ah69M/Ydu2TSheOwUOKEWOW+XPmx42EKHnfxdrjwQf+1ak4FCw4BMUDqcmHRGz+gTCvBzxdO/68HRSY3eXWXD29Ienly8uQi3Sj1wN1gN7+b6tsNwo7Qu6/aXQ7El83TGIPZGKZVv34p7SvWIlNq2b/YKIiU6NEFRwDPlyFzgbrTUE54wByEi/CLVpD0JlFVNQqdUtfeerhsxB6/rNsC9+FxDcGnWVCgxuHoyL66zvr3byE+JgLs2wx654F2HZu8XlcfF7LGlXxSaF6DhKA/RzR/dCCyPyFO5oXicCF9QuIjtCzHr4Piu9Ph/rITyq48mXu8HVkIVOJVvFtpWX4NIUzz/4FLz9pOuOendFSPoWkaHRTHZGrOc1CpsQIJO+13vKD+CoVx+ca/UdWqcXIzrQDblZAZb5nBYya2G/T2B4pUXe1XVLf1vQ4H/hQmuaRosWUjY0zax0794dCoUCK1euFIFOp06dRNoWBRJz5syx3MfNzU1MI0+ePFnUbVBxN6U42aY5XYn0nycC7+yxdJhJyitFrMJfBBZhunOADsjdlQDYBBYH/vwQrRNOYQNGWwIHotnxIbaeP4o34/qhsew8Oqg+Q1+bMXXXwy+Ix7X1m6E7dqQ1xafLn6IkDsG2OSsVuP1jbIsBcuk/QqwsGC16XHm7zaO+gxGWIK0Xoa1iFuZKxft0w+w06T9beTQApGLu3r2r14XBJyCkbGIQyA7sioKsswgusvZct5WWmYU+c7cgLpOOpiuRG9wDLnH70F+xGknG+hirHyduN1SxQ3ww5mWnISstCQ5bZmOSIgsXNWFwLUnBeZO/yO+kFrzz8wfgnwtxIqggp4zBYn2Nk+mRMCmsMyO+RWeQk1nxKEVwfgwuaqxHhd/8dT32nU3Ghyrpw1mllz4wL5w6BNt5FvpAigzwwxpZOEqMMlEc3xWHEZhzUBxpz5Y5ixaEsekFlsWQ0soCOocS+4VzUvSu2GzoiKEK+17zdLRjkaEHgrPS8O13XyKiUVucS9PjI9V9eEb2KyKyd4jbPaJ0xEeF9+Cbreew4lASgjy0eCXiFOg4GH1Qntm1BtFJ74vi+PJKoYAmL96u5iH0ArVQlVBxnS3KD91raoCMghLRWjArJwdf6wfjLdV8UIMkg8GI/O3forcsCzmKrvjN0BMrvR/G0xlS+ly96HbQncgAcqQp8WKlKzYqOuCP/CZ44e5OcNR2hNvP0iq4dMAhX+YMJ2MeRik2icvk1HpVJoPMPRRIOycC2EZ1a36UdkCIEZ3TfkIHk3TwgNIPNsjbYdFjneHlVXUgXhWdwkF8BpEStwi76zwHzoRHzGLIelrXHeoZ5YsNJ1IxvtO1axvOWE35+FWxmGItoGYcmepA+JZI3ygGGhReBVlgc6w82Q6HjHXxkPbSR4MndKqDTpHeaHCZAORyqOHKKZkGalMJnC9K3/k6jTuCXVWWgaPMRdp3oQ3bYvLKSegiP4zGIZWvVdF93GvIzX4KdT19cOS1X0SxdT/FXpi0zni8exf0buiLQHetpbNf2z7W7AdD2Yd5yxDra3JzVGOkYpNIYwsEta++9OdMl3re2HAiBT2OSFkEtAChrz9VhVo1mTgP+//6DA17P4jibweJ1/m9oR9MkGGp+lXRQYzky13hbLQemHtfPxrdOnXByy2lAzZdp/9muW5Y80B0Wzca9U0JYpHehxWrkKHyh7OuCCcLnERdKlmTG4ZVhpFwkxUg3uSHdZkFyJg/Ej5la0NkuUhZPDKFNYhydpQCIzfqHFamQO6KIpUUWJgPhp6t9xDcY1ejwLMRQns/is6RjcUY16zzY59i50f3oU7+MZHSZH0sFxTDEQ7GQgxzO4seXSdYrnN197RJFLPy8PJDZlbW9Q0sqHiaaizS0tLE7EDz5s0tp9BQc7x27dHaE5dbX4O25++/rQUqlaH0ri1bttTKNlHhEc1AuLh54mxqniiKLLQb+kG8WVZ/9zrajXgaHu7uUKYcRDf5aQS26Ye0GB/4GK3pGGEpazFBYRQLTpVXPqggBijgmnGwyr9sM9lZvKZ7EHMwWpw/8Ub/q+rtrpFLH0uUZqS4wtmOqvz0cDv8/OspsZaGrSTnxmLQ++uz4+Bkk/N5KbYdj/xbDkZ02x44OzNKnE90jsYnud3xrvwzcd5LlothOT9BoTTiI/09iA5yhUe89OlDRdLv39NUrByaF+sEjakUWSlxyF//PnwNWdDJVKg/cYE4avDk+xtFygsdmW8lj4FpPnX/Ac4jEOuMrTFc8Z8oUs/XW4+w0CzCuWN7kWJsDHdZvmjHGJq7X+Q9+hdbi+EjYn/DH6Z78T/d4/hC9TGMBunoWUFminh3mdO9aKqa0rSm43/I1+lF6g4VbB0wRuJl/cO4v00gvPccR1BhGnLz2yPpzEFRWExMeRexfs1yFCSfRFjDVthz6AQWGO5GT8UBcWTGPANyIHQcXBIVeMTwNzrJj+DzYzQ13hWR7QYCu3+1/t38eoq/5cGdG+ALFY4UhqBIc8JydCQ7YR30cqlIsTwnlCAV9kcgjxjroJXitPh6okJkW/QYQ+XbkZHeFL4uoegX+x7uVx1DQtuX4ecXiJTlr6GhTBoYTFKsRLbJGfdrMhFYlgbl5OaFLJU1QM5qMBrD+z6OFhmF4gv+3O5VeFf1jbiuWOEEh4YDgJjfxfmvDEPQwLmZ+D1owHRkbP0Gdes9hnYRtdNaM1yRIToCzNBNxG5TFFqGeogVh6+GkQKLMnKncrMoTUdC1nSk3UW02FRmQaml5SZjd6Ji51CgLLDAVQYWPbr3wpY8f4yIuHyqNxW426aQ1iQoSneqi8D8Y/DSSZ91RrU7/IIiYKksVUnfR1TrR2lMMYYILCzrflQefbe4eUqHKovLujjR5+kFHX2GD7nkTIzbuEVIiz+FVk3NbTMAb2WJZUHbfFRdc2LWOtgZTyuXinQdktvxxQpNUjy8fNBrglQvtlkRLJql0JpWv6jtU4dztUFwLrAGFo40/K5iZjbATYtVU7rg4hkn5P47A/oOU1Cy71dAl4IdRUHIlnXDPYrN4sBiLpyRa5Jmtfbs3YV2ZUEFMblLwUP9Yc8h44exyK4/0tKm2TcwjCa0LCmrhRofoDjW0j6471iq3bCvp7RFLdNLHQOAfPui60yX+mj/+DzkZ2egR4D9+JxS5qfonhS1L1+pPhIHLc1/55q4qsCCUotowP7YY4/h3Llzop7i448/FoXRdMSfVri+U1GnhAunMzGstSfy9i/Br6pvRdGwLarO7xO7Ens/P4j2Ty2AT5E0gIxq0QkO3e/C0vnvol/+MuuKsYp/RUpGddBq0oMV0hHjFcYOmKcfjL/V9m1SBwYW4rckZzzWre5VLxhlTi0qokX1aomvqwP6tYqsEFg0HPcxvP2sLQurq/Su+chMOotObcsVIdXpCu1JNR0WFyk5P+j74oOyCN9RWYIAr5dEgRPRuvthZOsQcdo+2w0ozoLjqqeseZR937dMRS59ohMKSvR495+jGHfSmjooD2yORaPuQfpHH8PFkA3nshqPiw7hokVfYtxZvKafgAgfJ2yY1h3vLFyKv0/kYKHqXctj9JAfFIHPG/qx6FP6Pgbqd0H2Zl/ENHkB35W+ZPnQ3CxrI7py+BlTsED9GZJNXnjE4QMk5pZCKZdhcq8o3HPkCRHcntlXB6qTmxFWVtsQnr4ZoBM5Nx8jocZW2WQxG2Buhfe6fhw+aNUUn0wKwvrvdwDnj2Cy8i/o9Qp0iZqMgvPN4JZ1BAnNnkb/glQ8nPaOJXCYox8FZFhbptKsxVul92Pr1I7QlxTh8NI5aJyx2pL6pjEfWi9DBX4ZXd7A+La+SPywYhEofeFkXewL1AmFY0m6eF5a+K1Biy4Y/fcMvGr4TKRQkbdcluK4dqj0dzB5wC+4CbJirJ2LVFpnBHs4ihNx8fAu+yqTijcbDZ6KXGcFnompgw2ZXljaRuqfJIvsCe/InrA2Gay5fLUPoE+AP32OmGR4fWj1u3lVFVj8YeiGeqH9L3t7tVLOQQW748n9ooCMbaJr3/HQ+3A1JejU/vPN4bW/zsblpIUOwl8xkVL9Hn22at3FquFmTn51LcHMNw+2xvn0fHStd/ngp1ThDOjTrTO2lxFaN0qcbAWUWjtFObpf/jmjAt2hlUvjm3R1ENr1s2Z+VOZd91dFW9zKnA0YhKnH7sbbqm/FmlqU2uopq3oldVqANNK3K9DxP3F+dpwJu85cFM1SAhTSQV46OEjctFJa6X95fmhelgJGVG7S7FBgeAMEzpRmkMxcXD0sgcUaWSdkhYxGfPo6sX15qmrWHTtUDOwMriFwcHQWp8ocNUk5A39EzsbAC++joO7AKtekuaaBBa1kTSlGdevaP/2FCxcsdQ53qp/0vXHgj5MI9vGC7uQ6BMqyKHEF6rJBEuW9/W7ojvby44goOY49Sz9GmMmAPLkbmoXXE5HiYa9+doEFkbkFQVWQDp3BBJ3aTbSps3XUtTNMcjVG5B9AX72UfrPV0ARFsD/SeKjORLwx9kE8cDFfrE55tfx8fVEAB1GzUZtUPtbuUvQh/rF+BH71uLqVJxu26ATQqUzJsK+Rcng9Og99FOffmSQuo5Zy0WU9owkVPRfKreVfrp7W59apXKmi2/p4Mur8ZO1hTTmidOoXHYRnYibjB/U74nL3ht3h5uGN+LIjPDKYxLSsvt4gIOZzuGZS+ltnOKml/44e4c2gPVGxFoQ6SVBGJK3w/D/lHyIwytj7Li5iipgVc0QJVqMjnqLtNubDU5EnCtAXPd4JH/17Gq3CPMQ09XH/znBNXAH91o8RqrN2jyqPPgwpJ/dQq9lokb4CKwt6IqDAQSzERulA2sAomo4RpqiWITT4Zagf/xHQFSBM64Etiz+xm424T7EBQUXWdCvK5Q10d0Kwr3RkPyWcvrytKU62hdRi/8ry0L1ZBBw8XO3+T9nSnl0N5G+Gpz5FtP119qK6BwWaB7sgKl464kjrYTj3ng6cll47NUR4wDcA2/37IjBZatmpdLD/EHb18LEEFkVyF4o44TrgVXzYTYf4rEJEB1VvJu1qFDv4iHxcH1kWlk3uhCbBV/9cJpUUKKXDFc09Lj8YYIwB9TqNwM6jG8WR72Bj7aT+Xi9uzQZjx0GFCCxooTe1q3SQsqDfR8g8uwdde91juW2fRlToW3U3TFs6qjUpW8pL43nlB/6I1tk68+rqfvmDpzQ7keTcSMzAmFo9dNnb+7lq4JByShwco1Rg24O8bv4RSDtWhI3GFqij+EcUaiflNKZkrWpte5FXNA6ddhHfU+aDb9R9qUCphYdfFFwTNuHguVaiHs68yK/WU+peVZVzpkBEyJJw3uCDSGc1dGVZKcUO1fubyDUVZ7nUXlW1X5F8PbYV/jmSgul3RcNRPRi14aoCC+qklJCQUCGwCAsLE6c7GQ2GyfJ/VuHBXCnI+rXuOzh18hjeUs4XR/hFz3uTpyjiUiVLxanZjqGW6Sets4dYsI7WljAzaj3hOnop4jd8gzqDpmL/wmcRlCOtskmGTv9W/Nz2uvXo/NPjH4CTgxLyvyJhTD8DU8uxGDF8uriupgOh3m2b45eEmahTt/YWSSNObp5ILGsDRy3dzpiCxaJptaFRq67iRNoYD1eZr09rH5iHw+7e1sHXQa9BCM6z3i9TE1jplOHgpgGo430XFMXtkXJyN9p1GSzy73PVftAWSyPxLKUPQpv3hCHmczE7ooIejmWrJdMUuLnWhgrQdHIHeOjTRNDTS70fyw0dLW3j6ESLN+WanOAoK7F09nlOIbXJpQWC6Kj7nJFSqo64rN1dwNIV8CrrAJKp9IWnvmKdBxmrWIdM155oMexTfGMyieJoc6G/T3g0IB28QYpHa0Q6lM3jlBX2K8oNzmkBROrTTR2oCM1I2C56F931LqTEfCPayVaG7l/f18VS6E8f6Ikmb7uFFZ1P/4WEszLoqYcsBWm+0hdekyBXzD0/Uuyvsfc8Ck1kCxSdk9rvUpoXHWEq8W6M46YwUfzmoLXfdo2Th11AaUZF6W6O1y6oINqygHOMYgPUlylwvJz//O7Hi8ldkQMnjK7hYzF2pwgMicBzhsnQG02YG1g7zUqul+Yh7uiokJpmXHCIgkolzVY07dQfoNNVMtoUsbtUsphddShsmsDQwbfqaPTQ50g6cxjtK2nnXp6fqwMmKX8XReYX27+MJWczcFfaPDEjHugfiMay9cg1OYpUIPruVNICwNXk7awRj7NQJR1ANOulOoIczyYISToNbWmp+K4yBxZu3hWLsG2dE81ATGLBWHr8ULmUOmzyqt4cgkJb8b3p4lf5Is9mfRv7i1NtuqpEKipsfuONN0SXJWZvRr14rFE/hweTpKLQZMcGCKnTUOS4jy2dgTXBU7BgfBtRXEw8iqVWpUa19Q0xtU99bDc2xqDS2VhqkKbmZI6ecA9piCbj5sLZOxhdp1lz2W0puk5HsswPmX0/QdcGvmgV5omwh76Dz5BXETno6grSK0PTpg/cMwKdWtTu1K6zg1IceSdFJukD8Gp7eF9KtqbqYr+QiEZI0tYTXRecna2Dxizv1ki2maFJllf+GLS9FLiF141C+4EPWoKPEmdrkVm+YzDC6jYUBWQUVKxWP4+HC6Qc/ig/R3H0RNyu1eNoPXMrLnhZi+momNrcyYm8o/zWUm/jD2mQ7YuqC6/qNW4jirzN8kJ7IR1uoq/3LqPUyciWi2eg5XXZdg8LDa8vWviJ2/R4psL9VOUCC0Lt7qgAmVCXrWkl1rU1nD38EPnCdihGzke2WxTiQ+xzbt3lRZbFtczPe8hUV3R3MqMv/hJaLU8EHx7wdpduF+btKo5M0cJAPpGtRItVdVnhGy2mRK/N1UGFXcYo0Q5S5VHuCJymZkWUNSEvGwgQjxoGAyZHb7Hf6f3lqbLvRMYYq9p/L/TEe/c0xbDmlz7qfLPxctaI5ifUv6nIv/LaiatRrLEGAl4BVxdYhNeLRoJDPZxzbQsHrXVh4UuhNayaVCOoINRRSSweR88V3QFd+owQ3+HU0SkswAufqD7FM8ollgNySvPBsWoIUWbiQcVay/llBik7Il/jh0ZdpYY4dJCK1sIga4xt4Bl66U5+ca1mYJJuOjr3Ho6QrB1oX3YQLrLrpdd2M1M6VgwsfIJr9+Bvtbbjau40ePBg8UVM61QMGTJEzGBQR6ZmzZpVurbDnUSrdbRL/2j22HeIO1kg2nwmwRulzv7oEeWLzXv9QA2XtSapKBY2U1ghno749bEuuOerHZacPaVLxWiePihoERgaQJnj2Q49BgF0skH5j65tLp2LeLNwVitF+g6lyXyq/lR0UwJqf9GjkHs/wsWfH4GHTjqSkKytjxL3CAS0HSEK3jo//5fU5ccmqHFVUcG89CFFA/BC7+pNmZqpw9sA6VKTgHPBw9BDLsfXwbOhObdO1CmYB+2+bk445tgYjrp0NOte1llIad9Sr4nMmr7VuuyDi0w0Ueekl6CTqaEq18LWdjo5W+FtmaVw9KuLOcUfYk9slmhTR/mmtlPG7uUWIzSjNSEKhnyN1MICDG7WstJ2qeXRrAr9XzDTlD+0odQgvEkncdqx/k8gfoUIIv4NmoyRQ6zTtPRFSbJMLvjOMAA5ak/cDfv0sQuOjdGhbDnuIc0CsWhvPJoFu4t2tKR9oBIZx+VwLJsR8DZlihlHWq+ij799LrB5rQdzm9br6Yj3APjHrxKF80+UzWpdLa3cIBbYJJ6O1lVhGWOXP/o9qrV9B6JbxYiurVF0IhOdhk7Alm1SjUJN/efaH/VT/hYt4H18ry7You+irjOk2o9rwRwwEE8ff3ipHDDA/U34uzrgRw8PFFTjYFhVQgyJaKZYZxmL0ToQROfkD1//YJx0iUZg3hHL7WkO3dP10jMirw5pjNFtQkQL97hTeTDtA9Ic66JdRMUDfpXRONnPntPwxS/w+jVUqlFgQWs9HDp0yHJ65513RH0F9XCPiorC4cPWdJE7jcbF2gkmS+WHuu5eCMvdjB9Uc3HCFIrTaqmqX+1mnXqi/5gyrf0bwsVBZckrJw4uFfMPqW1dd/lB/GHoig64PdARab++U6H/9w24GQss0X5tC4loAMW471D0rRS0lDr6odfj1nUwKktxcs05JuojyJ7omZg5hPIxqy+8zUA8vqNIpDE9F9DYssiZVlZSIXjo9vwfMNKaDOYZgrLOHZeTrZaCAN2AD6Bb8yJ0XSrvIlHo4A/PfCmwcPUNxXc92uCNv48hr9gf04+4WepD4hSh6OJb9fRtjzbWDh/laRwrHuWndSUUakfLWgpGm05M5Rn8mmKq7nEROK9+8D6RrmRGtTHmxgZUXyJ39qK2IvbP1VQqqCbU/vDPJzrZb1+TYQjc9w0QLs0G+eYfx6vKH3DQFAlnh4pr8Tj51oE+8wK69qqdPNTqKlR5YUTpLOigwOQazt4FZVkLBl1dr03ff8bYzaVVv/uBfveLVdpri7pAOihHqT71arCY2rXISLB5cMuvDmVt8f/9XzdxcWXPq66iwLkyjjY1IYVKd/gbpaZFBmfpO9ij4wRgjZQlQhkBJ40hl32t1CzD3PGvTlRzpExcjmaXSZ+ypfNvLZ6LFgGmrIYtmh6YeAMWzbyqwIJqK+g0YoR1/YPc3FxRuH0nBxVE62adWSjUSPn5jkoTXGXpIhdcVRpD8xhwKksvobUPJuqm49Vy3RJcFaV4VvkbmsukRcccKym0/Ew/DB/jLpEf+AFuH8Gdx2Djzr9F29VrSetobqJqLWq9lLol1nUwPrxXWjPlSgQFBOG4PFLk/7cJkwZ1nk7UT7xsZkFtDR7oA0ihsPkQUl/6SEds2D2QZZ5F5IhXxfkm7fsA7XrbfbDa0jv5Wgbi3gHhIpB9755mOJqUg2eO7hWXZ8tc0fLZFeKAwdWoLLCYoPgHaeo61E5MMFGQUQVqvXvIJC2J51KuDaB66Ic4u2IG6oJ6iv+DFZoJdoEFLehWp/vwS2+giz/wyCag7G9vfg/Qu8K29sPMv/ODgK4QCLy+dWQ9o3zwzbbYyy4gVR0BefT5I6lqoUnGGLucfKcQUQtKdQb2h2xuHnVa9YH++LcoVFgzQszptJXRVDLLXpXguo0tDVn0nvUwKHWD9PgaKThp3KE/duxbDENuEqbonsI9nezXDaoO/1BrM5vqMCg0GFM603K+Rx0fTMT1V2sL5NFK1l27dhWnO5mLh7V6/3DAPaLtpNrmzRpZIuXMufqHYZexAeJMFDDI4OZk373JWatBf7m00N4Lukn4MNRafGv2/oM9MfmX/Zh79/VvYXetKWQ1WfexerRO1qMTMsXl/yu0HDoZB+Yfg0PjQVfdjm3dM52xZPVGsVYGaVJ6CI0V0geS7BJH7+WXCSwCW/ZHwxblFjW6xNGRkx498XuiFzJNrljkZ53GdtGo4FTW+kqvdIab49WnNmqcPXHB5CnqP6gLlnm2J8Z7MLJjD4qUHJm66iNEzYLdcHfLYAS6O1T4Mmjfpg1MTZbg3Ox24ouNVhd9TT8OrymlBTNLR/9acZ2GyjfS8quTo6PYwkhZIjT6AkBZLl+1+Y1JJ2wd5oElj3cUK9rWlMxg09aMMcau0lMDW+OJLDkmdL55F88Mq98MF+7/DaFVpGqlNHsC/oe+sJyvqiVrZdzcPaGYvhlJZw6hQ2RTJL0n1a9oXL0tWQ8dpywQv+8zmi4Z0NSWlmEeCHBzQHKO9Dnfpk7tdu2s9cAiLi7uiha/S0xMRFDQrVXkVBvcvPwsFRYlXlEVjtzKyroOeAVF4nn9I5bLPRztj0Y6OTqJFmZUr0F53wG+FVOhejfyw5HX+4n+2Lebhm37oHD9QTg7X7vWfhqNTXqR/PL/Fdw8PNF9euVF89UV5K5FpM141UthzfKUa6oeOCoquY5y7lvJT4lAwMn1yhZjM/o3wZrDGssiOWZOsiLLmh4Gm9VBr4bWwx/366Q1VJ5Q/IW7FVJ9iaN3MAouSLMi8kt04aBZmw9GNav6epuFqpSuftidZJ1JULtXf/rYLMLHBZmOKqnWpRozWNcTtQquDfJ6fYC0zUiGd417lTPG7lxUC7riqcpX6L6ZhDWoOl23091TsF3jBr/db4vzaptU9upwdnZB/ebSPjjf6AkYEg+gW5+KhdbXI6ggtC7Z5md7iDWrUnKLRZBxUwcWbdq0wdChQzFp0iS0bVt5Z4GcnBz8/vvvYrG8Rx99FE89RR317yzOzq6gpbmo04+Lsaw+wtHZ3O7ZMpCiVA1XByUm6xdCi1L4GqgozNfujUidC9yRDxd5kaXgtLzbMaggPh0fhMnLG7Lg1tfsOWzrKBJcW+FG0FBtQJlLDbLzfFuJhdxcZYVIa/cCHFGIsKCucFoqdU5yvsJ8+XEdw7HrfCb6lWsz5+zkhGzLuZp9GFJdg9l8wwDcpdgmZhe8fQNB7Qxsp42vilwOXxcNivUGMfBWnjDgqClc/H9qewVT2hYObtZ0o2rMYN2KqCvKVq07IuvffrOcjDF2pcwpsNRqvKfL1bcO733vlJti56vLGpbQmlU3SrW/PY8fP47Zs2ejf//+UKlUaN26NQIDA+Hg4CBW3D527BiOHj0qLn///fcxYMAA3IlosEqdaqggN8pLWSGwUJYdeaajsVT53z3hkJiV0FRycJiCCtLHwbpa8R1DoYSskbQy8rWUWbZmhs7m6Pf15OhmDSxMzlX3kpa5h2KM7mXx+/yI1mjX0A8nz8Varndxv7IpT6qp+PHhdhUu12hq7wiHRikXa01Q57JcOIqgggS5KhEpl+pnTC5XPrNgy6V+Z7gkHURuSHu0k/+OlYZ2WGNsi5NlzQ+uiG8U0GaSVHtxm6JmAN279b7Rm8EYYzcFQ1lgoUUJHJS1s2bWna7agYWnpyfmzJmDN998E6tWrcLWrVsRGxuLoqIieHt74/7770e/fv0QHR2NO51Hv+eRd243urSVjrY7OrnAvE62yabzzwTZcktr2ksNDDsrrC3LWO16pHSqWMX5eb8GN2TXOrt7i/WjqbNRYaC1i1F5Wps2o+YFA+uHh2KDb29qT4G6qtpf7CxBcXWrqZpR8GxePIhWnEfZ63TVyEWz2Gw4ozC0W802csingKEEDikpeEn5s+iEsU7XBuqrnclr/1jNtocxxtitQyZ9n9KCxdcrZel2d8Xz/TRDQd2gbDtCJScnw9fXFwqbXO07WVTn4QCdbLoPmRnL3sTEyWbazcXmyLXZbmMU2spPICbgbtz8mYy3pldGdcHmU2kY3fbGrBjv5uEjlrSjRQE1cmlthsq4yIrQQS6tnuqg7miZHev15Ge1vk3m1ay3qztiVC09ZoisbM0Mep0OjiKwoLVKynd7umKUzibXwsHJVZScK2CEs9J0bVsYMsYYuy00btQY2RuppvDG1CPcjmolQb9v377Iy5PqCQilRu3dKxVnMioydSzr/gToNNZc+IgIaaEtGgLJbVqNmjnf9QG+8H0VI0eN5d14jYxoGYyP720BzQ2aAnVx8xQdk4ixyDyvVZGrPh1vKr8TJ9fCuGu6TYWQPmAdzYs31oI05yiYXPxR2mICNGX9xDXQwbGGC75VFrzPkX9SK4/JGGPs9ublFwLPyWsROm3Tjd6U20atVChSn3t3d2lRD+Lm5iaKt/ft21cbD39bWBv5Ii4kpOCb1tZ0F/8WA5AT8yPgXflKvkNa1RUndvuijkzmNqyh2qpbgTponc2rXdRqHURl9GXHGxzK2s7WhlRtBNo/NVf8XpwvlYfT63bMoxXEa97xyEFtTQXzh7RQEWOMMXY5Hn7Xf3Xq21mtBBbBwcH477//0KmTtEyKXC5Haal5GMTI7Af7wWiCfXcnlRZuE5Zecr0Bdvsz3jUPuSnn0apR1Z2pqAGANbC4tt0eXFEofoZrpJ81sbfhCzCe+BvtRjxrucw8Y0G8nWpnVVDb3FhzoMYYY4yxWzCw+PzzzzFo0CB06NBBtKWNiYm5ojUv7gRiJeXK4gcOKu549VpQAfOli5htB+MK9dUvWlcdspHzsWzbv7j/vnE1fqzR941Hqf5BSws88fgKFbzqNIWsOBtuIfYrztcGc/cpxhhjjN2CgQUFEfv378eff/4pgor69euL1rSMsdrh6uqOjcH3wWg04C5v6+ru10KXpg3EqbbYBhVm7uN+BUyma7JehJxnLBhjjLEbota+1Wlti1GjRokTY6z2DXvk1dtnt8prv1j+sCkCTWXncNhUFw1r/dEZY4wxdl0CC5ql+PDDD5GdnY0mTZpg4sSJCAmhlaQZY+z6OGKsg6aKc0gyefMuZ4wxxm7VdrP33HMPunfvjhkzZojVuIcOHYr169fXxkMzxli1ZJuccd7kjzSTtUMdY4wxxm6xGQtqL/vggw+K36l4mxbP6927Nw4dOlQbD88YY5e1xNhVnFQKGbjCizHGGLtFZywiIiIwd+5cmKgYE4Cnp6dYoZsxxq63so8hxhhjjN2KgUVJSYloOUvdofr374/o6Gj06tULiYmJtfHwjDHGGGOMsdsxFSo+Pt6uOJvazJKCggIcPnzYcrr33nuRlJSEs2fP1t4WM8ZYJab0qodP1p/GG8Ojef8wxhhjt0pgERUVhalTp+KFF16Ak5N14S76nRbJoxNjjF1P/+tdDw+0C4WvK6dhMsYYY7dMKtS6deuwdu1a1KtXDwsWLKj9rWKMsatY3Z6DCsYYY+wWCyw6duyIXbt24Z133sHMmTPRokULbNq0qfa3jjHGGGOMMXb7F29Ti9lTp05hyJAhGDRoEO666y6cOXOm9raOMcYYY4wxdmd0haIWs3379sUjjzyC5cuXi45Q06ZNQ15eXu1sIWOMMcYYY+z2LN7+6quvsGfPHnE6fvw4FAoFmjZtismTJ6N58+b4+eef0ahRI9EtqnXr1rW/1YwxxhhjjLFbP7B466230L59e4wbN078pOBBo9FYrp8wYQJmz56N8ePH48iRI7W5vYwxxhhjjLHbJRWK1rFYvHixSHnq1KmTXVBh9vDDD4vZjGuJAhwqJHd0dIS7u3uVnWLKn2jGxVZMTAy6desGrVaLoKAgzJo1y7KKOGOMMcYYY+wazVhUh5+fHzZs2IBrqbS0FCNHjhTrZsyfP7/K21FLXFoR3MzNzc3ye25uLvr06YMePXqI1C4qRqeZFlqTgwInxhhjjDHGWC0GFnXq1BFH+6/UM888gylTpuBaeP3118XP77///pK3o9kMf3//Sq+jepDi4mLxGDTzQsXnFFzMnTtXLAJ4Na+ZMcYYY4yxO021A4vLDd6rEh4ejhvtySefxMSJE0VwRCla1MFKLpeywHbs2CHSoGzTufr164cZM2YgNjZW3IcxxhhjjDFWS4EFDb5vRW+88QZ69eol6ifWr18v0pvS09Px8ssvi+tTUlIqBD+UxmW+rqrAoqSkRJxsU6qITqcTJ8YqY35v8HuEXQ6/V1h18PuEVRe/V1h11WSMcs1qLK7Wa6+9ZklxqgrVQlS3ja05gCDUCpdQcbbt5eXTncyF25dKg3r77bcr3c6NGzeKYnLGLmXdunW8g1i18HuF8fuE1Sb+TGGXU1hYiNsmsKC0pXvvvfeapVdRe1yaXbh48aKYmaDaC5qZsJWammo3c1EZSpWiGgwzesyQkBBRBO7l5XXV28du/6MA9KFODQNUKtWN3hx2E+P3CuP3CePPFHYjZGRk3D6Bhbe3tzhdKwcOHICDg4OlPS11lHrxxRdFhym1Wi0uW7t2LQIDAy8ZwFBNRmVtdmmwyANGdjn8PmHVxe8Vxu8TVpv4M4VdTk3GsTddYHEl4uLikJmZKX4aDAYcPHhQXB4ZGQlnZ2esWLFCzEZQ8EA1FpSm9NJLL4nibXNQMGbMGJHSRC1mKcA4ffq0WNxv5syZ3BGKMcYYY4yxOyGwoMH/woULLedbtGghflIA0b17dxFxffHFFyJlyWg0IiIiQtRXTJ482W5NC0pNocuobsPDw0Pc3jbNiTHGGGOMMXYbBxbUAvdSbXBpUTzbhfGq0qRJE2zZsqWWt44xxhhjjLE7h7SYA2OMMcYYY4zVAAcWjDHGGGOMsRrjwIIxxhhjjDFWYxxYMMYYY4wxxmqMAwvGGGOMMcZYjXFgwRhjjDHGGKsxDiwYY4wxxhhjNcaBBWOMMcYYY6zGOLBgjDHGGGOM1RgHFowxxhhjjLEa48CCMcYYY4wxVmMcWDDGGGOMMcZqjAMLxhhjjDHGWI1xYMEYY4wxxhirMQ4sGGOMMcYYYzXGgQVjjDHGGGOsxjiwYIwxxhhjjNUYBxaMMcYYY4yxGuPAgjHGGGOMMVZjHFgwxhhjjDHGaowDC8YYY4wxxliNcWDBGGOMMcYY48CCMcYYY4wxduPxjAVjjDHGGGOsxjiwYIwxxhhjjNUYBxaMMcYYY4yxGuPAgjHGGGOMMVZjHFgwxhhjjDHGaowDC8YYY4wxxliNcWDBGGOMMcYYqzEOLBhjjDHGGGM1xoEFY4wxxhhj7M4NLGJjY/Hwww+jTp060Gq1qFu3Ll599VWUlpba3S4uLg5DhgyBk5MTvL29MWXKlAq3iYmJQbdu3cTjBAUFYdasWTCZTNf5FTHGGGOMMXbrUuIWdeLECRiNRsybNw+RkZE4cuQIJk2ahIKCAsyZM0fcxmAwYNCgQfDx8cG2bduQkZGBcePGiaDh008/FbfJzc1Fnz590KNHD+zZswenTp3C+PHjRSAybdq0G/wqGWOMMcYYuzXcsoFF//79xcksIiICJ0+exJdffmkJLNauXYtjx44hPj4egYGB4rIPPvhABA5vvfUWXF1d8fPPP6O4uBjff/89NBoNoqOjRXAxd+5cTJ06FTKZ7Ia9RsYYY4wxxm4Vt2wqVGVycnLg6elpOb9jxw4RKJiDCtKvXz+UlJRg3759lttQGhQFFba3SUpKEulWjDHGGGOMsdt4xqK8s2fPivQmmpEwS0lJgZ+fn93tPDw8oFarxXXm24SHh9vdxnwfuo5qOCpDwQmdzCiliuh0OnFirDLm9wa/R9jl8HuFVQe/T1h18XuFVVdNxig3XWDx2muv4fXXX7/kbagWonXr1pbzNLtAaVEjR47ExIkT7W5bWSoT1VjYXl7+NubC7UulQb399tuVbufGjRvh6Oh4ye1nbN26dbwTWLXwe4Xx+4TVJv5MYZdTWFiI2yawePLJJ3Hvvfde8ja2MwwUVFDhdYcOHfD111/b3c7f3x+7du2yuywrK0tEYuZZCbqNefbCLDU1VfwsP9tha8aMGaIGw3bGIiQkRGyLl5dXtV4ru/PQe48+1KlhgEqlutGbw25i/F5h/D5h/JnCbgRqdnTbBBbUEpZO1ZGYmCgG8q1atcKCBQsgl9uXjFCwQUXaycnJCAgIsBR0Uz0F3cd8mxdffFG0oKUUKfNtqC6jfIqULXoM27oMMxos8oCRXQ6/T1h18XuF8fuE1Sb+TGGXU5Nx7C1bvE0zFd27dxezBNQFKi0tTcw82M4+9O3bF40aNcLYsWNx4MABrF+/HtOnTxdtaakjFBkzZowIEKhTFLWs/fPPPzF79mzuCMUYY4wxxtitPGNRXTSrcObMGXEKDg6utEZCoVBg5cqVeOKJJ9CpUyexAB4FEuZ2tMTN7f/t3QlQlPUfx/GvF6IoXuWVggaDplCYlEeRGJqa3YVXqahppR0eWWEqmoU1Kmk2cWh5TKbTjFnSlJmkkaMlmjlQhoh5X3mnBCruf76//+y2C8vlwyjg+zWzI/vs7sOzjw/P7uf5fX+/Xz1TmjJmzBjTb0M7d2uJk3OZEwAAAIBKGiy0hUFvxfHx8ZGvv/66yOcEBQVJSkpKGW4dAAAAcGOpsKVQAAAAAMoPggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAMAyggUAAAAAywgWAAAAACwjWAAAAACwjGABAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALhxg8XevXtlxIgR0rp1a6lVq5b4+flJdHS0XLx40eV5VapUKXCLj493eU5aWpp069bNrOeWW26Rt956S2w22zV+RwAAAEDFVV0qqD///FOuXLkiCQkJ4u/vL+np6TJy5Ei5cOGCzJ492+W5ixYtkt69ezvu16tXz/HzuXPnpGfPntK9e3dJTU2VXbt2SWRkpHh5ecmECROu6XsCAAAAKqoKGyw0KDiHhVtvvVUyMjIkLi6uQLCoX7++NG3a1O16li1bJjk5ObJ48WKpWbOmBAYGmnARGxsr48ePNy0cAAAAACppsHDn7Nmz0rBhwwLLX3zxRXn22WdN2ZSWT40aNUqqVv1/FdjmzZtNGZSGCrtevXpJVFSUKbfS17iTm5trbs4tH+rSpUvmBrhjPzY4RlAcjhWUBMcJSopjBSVl5TtKpQkWWVlZMn/+fJkzZ47L8hkzZkh4eLjpP5GcnGzKm06cOCGTJ082jx89elRatWrl8pomTZo4HissWMycOVOmT59eYPn69euldu3aZfjOUBl9//3313sTUEFwrIDjBJxTcC1lZ2dXnmAxbdo0t1/YnWlfiJCQEMf9w4cPm7KoiIgI0zLhzB4gVHBwsPlXO2c7L89f7mTvuF1UGZS2aGiplHNriY+Pj9kud60mgP0qgIZP7dNTo0YNdgoKxbGCkuA4QUlxrKCkTp06Zf69moGMyl2w0LKlAQMGFPkc5xYGDRX6Ja1Lly6SmJhY7Po7d+5sypaOHTtmWia074W2TDg7fvy4S8uFO1o65Vw+pa0gKiAgoNhtAAAAAMqzkydPugx4VCGDxU033WRuJXHo0CETKjp27GhGfrL3myjK9u3bxdPT03ToVhpIJk2aZIap9fDwMMvWrl0rzZs3L1AiVRR7K8X+/ftL/Z+AG4eG2pYtW8qBAwfE29v7em8OyjGOFXCcgHMKrgd7Fc7VVOCUu2BRUtpSERYWZt64jgL1999/Ox6zjwCVlJRkWiM0PGgfCy1BefPNN03nbXtrw6BBg0zplQ4xqwEjMzNTYmJiZOrUqaUaEcoeajRU8IURxdFjhOMEJcGxAo4TlCXOKSipklywrzTBQlsVdu/ebW4tWrRwecxeE6Y17B999JHpC6FzXuiQtNq/YsyYMY7nahDQzpG6TPtHNGjQwDzfuf8EAAAAgKJVsTHFdJmVLWhI0eYjrkSD4wScU3At8NkDjhWUp/NK6ds44JaWVkVHR7t06AY4TnC1OKeA4wRliXMKrsWxQosFAAAAAMtosQAAAABgGcECAAAAgGUECwAAAACWESwsiIuLk9tvv90xJrTOl/Htt99a/19BpTdz5kwzT8rYsWOv96agnJk2bZo5Npxv9rl5gPyTxD7zzDPSqFEjqV27tgQHB8u2bdvYSXChk/3mP6fozXnofeDy5csyefJkad26tZn7zT5Fg07XcEPMY1Ee6PwZ7777rvj7+5v7S5YskUcffdTM7t2+ffvrvXkop1JTUyUxMdGEUsAdPX+sW7fOcb9atWrsKLg4ffq03HPPPdK9e3dzQatx48aSlZUl9evXZ0+hwGdOXl6e4356err07NlTIiIi2FNweO+99yQ+Pt58l9XPoK1bt8qwYcPMsLOvvPKKlBTBwoKHH37Y5f4777xjWjF+/vlnggXcOn/+vDz99NOyYMECefvtt9lLcH9irl6dVgoU+yWgZcuWsmjRIpcr00B+N998s8t9vSDq5+cn3bp1Y2fBYfPmzebieN++fR3nk+XLl5uAURqUQpURvRqwYsUKuXDhgimJAtzRpmf9o+3Rowc7CIXKzMyU5s2bmybpAQMGyJ49e9hbcLF69WoJCQkxV521taJDhw7mggVQlIsXL8qnn34qw4cPN+VQgN29994rycnJsmvXLnN/x44dsnHjRnnwwQelNGixsCgtLc0EiZycHKlTp46sWrVK2rVrZ3W1qIQ0eP7666+mWRooTKdOnWTp0qUSEBAgx44dMy1bXbt2ld9//93U0gNKw6a2kI8fP14mTZokW7ZskZdfftlMaDVkyBB2Etz68ssv5cyZMxIZGckegovXX3/dzLTdtm1bU36rF8y1EmfgwIFSGkyQVwbpf//+/eYPdeXKlbJw4UL58ccfCRdwceDAAXN1ce3atXLHHXeYZWFhYaaz5dy5c9lbKJS2gmrZwmuvvWa+RALKw8PDnFM2bdrk2CEaLPTChZY0AO706tXLHDtJSUnsIBS4+Dlx4kSZNWuWKef/7bffzAAzsbGxMnToUCkpWiws0j9Qe+dtPcnrSX3evHmSkJBgddWoRHSkluPHj0vHjh0dy/RqQEpKinz44YeSm5tLB1245eXlJUFBQaY8CrBr1qxZgQtYt912m7nABbizb98+MyjEF198wQ5CARoq3njjDVN+q/RzR48ZHcWSYHEd2Ww28yURcBYeHm7K5pzpaAva5KjNj4z6g8Lo+WTnzp0SGhrKToKDjgiVkZHhske0NtrX15e9BLe0o7/2x7F3zgWcZWdnS9Wqrl2v9bsJw81eQ1rX2qdPHzMyxz///GOakTZs2CBr1qy5lpuBCqBu3boSGBhY4Eq01sznX44b26uvvmpGnPPx8TGtXNrH4ty5c6W6YoTKb9y4cabvTUxMjPTr18/0sdBhrPUG5KdfDjVY6HlER50D8tPPHe1ToZ89WgqlUydoGZR29C8Nji4LtGPl4MGD5ciRI2acX52XQEOFjg8NAFfj4MGDprPciRMnzDCRnTt3NkNYcyUazu666y4zWEhUVJSZxEpHENP+WjqcNZCflkBpf9DSfknEjWP+/PkyZcoUGT16tLmopSMTPvfcczJ16tRSrYfO2wAAAAAsYx4LAAAAAJYRLAAAAABYRrAAAAAAQLAAAAAAcP3RYgEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQC4IXz88cfywAMPWFqHzkirM6IfOnSozLYLACoLggUAoEiRkZFSpUoVc6tevbr4+PjICy+8IKdPn64wey43N1emTp0qU6ZMsbSexo0by+DBgyU6OrrMtg0AKguCBQCgWL1795YjR47I3r17ZeHChZKUlCSjR4+uMHtu5cqVUqdOHQkNDbW8rmHDhsmyZcsqVLACgGuBYAEAKFbNmjWladOm0qJFC1NO1L9/f1m7dq3j8by8PBkxYoS0bt1aatWqJW3atJF58+YVaPl47LHHZPbs2dKsWTNp1KiRjBkzRi5duuR4joaXvn37mnXouj777DNp1aqVzJ071/Gcs2fPyqhRo0zrgbe3t9x///2yY8eOIrd/xYoV8sgjj7jdnpiYGGnSpInUr19fpk+fLpcvX5aJEydKw4YNzfv95JNPXF4XFBRk9sWqVas4cgDACcECAFAqe/bskTVr1kiNGjUcy65cuWK+hH/++efyxx9/mLKjSZMmmfvO1q9fL1lZWebfJUuWyOLFi83NbsiQIXL48GHZsGGDaWVITEw0/RrsbDabCR5Hjx6Vb775RrZt2yZ33nmnhIeHy6lTpwrd5p9++klCQkIKLP/hhx/M70tJSZHY2FiZNm2aPPTQQ9KgQQP55Zdf5Pnnnze3AwcOuLzu7rvvNusEADixAQBQhKFDh9qqVatm8/Lysnl6etr0o0NvsbGxRe630aNH25588kmX9fj6+touX77sWBYREWHr37+/+Xnnzp1mvampqY7HMzMzzbL333/f3E9OTrZ5e3vbcnJyXH6Xn5+fLSEhwe12nD592qwjJSWlwPvS7cnLy3Msa9OmjS00NNRxX7dV3/fy5ctdXjtu3DhbWFhYke8fAG401Z1DBgAA7nTv3l3i4uIkOzvb9LHYtWuXvPTSSy7PiY+PN4/t27dP/v33X7l48aIEBwe7PKd9+/ZSrVo1x30tiUpLSzM/Z2RkmM7h2gJh5+/vb1oP7LSF4vz586aMypn+Pm0JcUcfU56engUe0+2pWvW/xnstiQoMDHTc123V3+XcaqK0VEv3BQDgPwQLAECxvLy8zJd89cEHH5igof0RZsyYYZZpydO4ceNkzpw50qVLF6lbt67MmjXLlBM5cy6fUjrSlJZR2cuc3HFers/VMKKlUvlpHwl3NBjo73HX2drd9hS1jXZadqXDzgIA/kOwAACUmg632qdPHzPsbPPmzU1/g65du7qMFFVYC0Jh2rZtazpOb9++XTp27GiW7d69W86cOeN4jrZmaP8KbdnQTt0l4eHhIe3atTN9P6zOY2GXnp4uYWFhZbIuAKgs6LwNACg1/VKtZUQ6opLS1oytW7fKd999Z8qkdL6I1NTUUgeLHj16mBGftmzZYgKG/qxlR9pqoPRxbRHR0Zz0d+nwt5s2bZLJkyeb31+YXr16ycaNG8vkf1pLoLQkq6xCCgBUFgQLAMBVGT9+vCxYsMCMmKQjJz3xxBNmGNpOnTrJyZMnr2qei6VLl5p+Dvfdd588/vjjMnLkSFNWZe8foQFDR4PSx4cPHy4BAQEyYMAAEzD0dYXR9ejrdKhaq7766iszSWBZzIkBAJVJFe3Bfb03AgAAdw4ePCgtW7aUdevWmSFlrejXr5906NBBoqKiLK1Hh5odO3asDBo0yNJ6AKCyocUCAFBu6LwSq1evlr/++suUOGlrhPal0BYKq7Qzuc6+bYWODvXUU0/JwIEDLW8PAFQ2tFgAAMoN7TcxYcIEMwmflkBph3CdddvX1/d6bxoAoBgECwAAAACWUQoFAAAAwDKCBQAAAADLCBYAAAAALCNYAAAAALCMYAEAAADAMoIFAAAAAMsIFgAAAAAsI1gAAAAAsIxgAQAAAECs+h8EoZS5QdBs9wAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"r_n\"],\n",
+    "    db20(ref_ts[\"y_pc_n\"]),\n",
+    "    r_n,\n",
+    "    db20(y_pc_n),\n",
+    "    title=\"Pulse-compressed averaged signal\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$|y_{pc}(n)|$ (dB)\",\n",
+    "    xlim=(3, 8),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a073555b",
+   "metadata": {},
+   "source": [
+    "check for above that we remove th surface values? (like safe_rang?) or why do we have the warning if not"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "94b88200",
+   "metadata": {},
+   "source": [
+    "### Convert pulse-compressed signals to received power\n",
+    "\n",
+    "We convert the sector-level pulse-compressed complex signals into received electrical power using the transducer and transceiver impedances. This reproduces the CRIMAC `p_rx_e_n` variable for the selected ping."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "97d6ab29",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "z_td_e: 75.0\n",
+      "z_rx_e: 5400.0\n",
+      "n_beams: 4\n",
+      "echopype p_rx_e_n: (2356,)\n",
+      "CRIMAC p_rx_e_n  : (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "z_td_e = scalar_param(\n",
+    "    cal_obj.cal_params[\"impedance_transducer\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "z_rx_e = scalar_param(\n",
+    "    cal_obj.cal_params[\"impedance_transceiver\"],\n",
+    "    tsf_channel,\n",
+    "    None,\n",
+    ")\n",
+    "\n",
+    "n_beams = cal_obj.beam[\"beam\"].size\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _compute_power_from_complex_signal\n",
+    "\n",
+    "p_rx_e_n = _compute_power_from_complex_signal(\n",
+    "    signal=pc_ping,\n",
+    "    z_et=z_td_e,\n",
+    "    z_er=z_rx_e,\n",
+    ").values\n",
+    "\n",
+    "print(\"z_td_e:\", z_td_e)\n",
+    "print(\"z_rx_e:\", z_rx_e)\n",
+    "print(\"n_beams:\", n_beams)\n",
+    "\n",
+    "print(\"echopype p_rx_e_n:\", p_rx_e_n.shape)\n",
+    "print(\"CRIMAC p_rx_e_n  :\", ref_ts[\"p_rx_e_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "53fa2d58",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"r_n\"],\n",
+    "    db10(ref_ts[\"p_rx_e_n\"]),\n",
+    "    r_n,\n",
+    "    db10(p_rx_e_n),\n",
+    "    title=\"Received electrical power\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$10\\log_{10}(p_{rx,e})$\",\n",
+    "    xlim=(3, 8),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14575fba",
+   "metadata": {},
+   "source": [
+    "### Reproduce the broadband point scattering strength (Sp)\n",
+    "\n",
+    "Using the received power, range, and calibration parameters, we reproduce the broadband point scattering strength (`Sp`) calculated by CRIMAC. This quantity is evaluated at the transducer centre frequency and is used to identify candidate single targets before computing the frequency-dependent TS spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "1b365099",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sound_speed: 1485.4\n",
+      "absorption: 0.03770373022901242\n",
+      "transmit_power: 100.0\n",
+      "f_c: 130000.0\n",
+      "lambda_fc: 0.011426153846153846\n",
+      "gain_fc_db: 28.0375\n"
+     ]
+    }
+   ],
+   "source": [
+    "sound_speed = scalar_param(\n",
+    "    cal_obj.env_params[\"sound_speed\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "absorption = scalar_param(\n",
+    "    cal_obj.env_params[\"sound_absorption\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "transmit_power = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_power\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_c = scalar_param(\n",
+    "    cal_obj.freq_center,\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "lambda_fc = sound_speed / f_c\n",
+    "\n",
+    "gain_fc_db = scalar_param(\n",
+    "    cal_obj.cal_params[\"gain_correction\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "g_0_fc = 10 ** (gain_fc_db / 10)\n",
+    "\n",
+    "r_n_safe = np.where(r_n > 0, r_n, 1e-20)\n",
+    "\n",
+    "Sp_n = (\n",
+    "    10 * np.log10(p_rx_e_n)\n",
+    "    + 40 * np.log10(r_n_safe)\n",
+    "    + 2 * absorption * r_n_safe\n",
+    "    - 10 * np.log10(\n",
+    "        transmit_power * lambda_fc**2 * g_0_fc**2 / (16 * np.pi**2)\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "print(\"sound_speed:\", sound_speed)\n",
+    "print(\"absorption:\", absorption)\n",
+    "print(\"transmit_power:\", transmit_power)\n",
+    "print(\"f_c:\", f_c)\n",
+    "print(\"lambda_fc:\", lambda_fc)\n",
+    "print(\"gain_fc_db:\", gain_fc_db)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "e5132f50",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"Sp_full_r\"],\n",
+    "    ref_ts[\"Sp_full_n\"],\n",
+    "    r_n,\n",
+    "    Sp_n,\n",
+    "    title=\"Point scattering strength Sp, full ping\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$S_p$ (dB re 1 m$^2$)\",\n",
+    "    xlim=(5.0, 6.6),\n",
+    "    ylim=(-200, 0),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "7d27cb81",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "lengths: 168 168\n",
+      "range first/last CRIMAC: 5.30584878660402 6.298095984098836\n",
+      "range first/last manual: 5.3058488 6.298096\n",
+      "Sp target RMSE: 0.3064048011908493\n",
+      "Sp target max: 1.8527138710007023\n"
+     ]
+    }
+   ],
+   "source": [
+    "i0 = int(np.argmin(np.abs(r_n - ref_ts[\"Sp_target_r\"][0])))\n",
+    "i1 = i0 + ref_ts[\"Sp_target_r\"].size\n",
+    "\n",
+    "compare_curve(\n",
+    "    ref_ts[\"Sp_target_r\"],\n",
+    "    ref_ts[\"Sp_target_n\"],\n",
+    "    r_n[i0:i1],\n",
+    "    Sp_n[i0:i1],\n",
+    "    title=\"Point scattering strength Sp, target window\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$S_p$ (dB re 1 m$^2$)\",\n",
+    ")\n",
+    "\n",
+    "diff = Sp_n[i0:i1] - ref_ts[\"Sp_target_n\"]\n",
+    "\n",
+    "print(\"lengths:\", ref_ts[\"Sp_target_n\"].size, Sp_n[i0:i1].size)\n",
+    "print(\"range first/last CRIMAC:\", ref_ts[\"Sp_target_r\"][0], ref_ts[\"Sp_target_r\"][-1])\n",
+    "print(\"range first/last manual:\", r_n[i0], r_n[i1 - 1])\n",
+    "print(\"Sp target RMSE:\", np.sqrt(np.nanmean(diff**2)))\n",
+    "print(\"Sp target max:\", np.nanmax(np.abs(diff)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "644e8175",
+   "metadata": {},
+   "source": [
+    "why do we have difference in the curves?"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "d975c349",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "mean: -0.03509303154669198\n",
+      "median: -0.005129335564895143\n",
+      "RMSE: 0.3064048011908493\n",
+      "max abs: 1.8527138710007023\n",
+      "95% abs: 0.7342241014215845\n",
+      "99% abs: 1.0939855293269973\n",
+      "max index: 24\n",
+      "range: 5.4484472\n",
+      "CRIMAC: -101.23159919223684\n",
+      "echopype: -103.08431306323754\n",
+      "diff: -1.8527138710007023\n"
+     ]
+    }
+   ],
+   "source": [
+    "diff = Sp_n[i0:i1] - ref_ts[\"Sp_target_n\"]\n",
+    "\n",
+    "print(\"mean:\", np.nanmean(diff))\n",
+    "print(\"median:\", np.nanmedian(diff))\n",
+    "print(\"RMSE:\", np.sqrt(np.nanmean(diff**2)))\n",
+    "print(\"max abs:\", np.nanmax(np.abs(diff)))\n",
+    "print(\"95% abs:\", np.nanpercentile(np.abs(diff), 95))\n",
+    "print(\"99% abs:\", np.nanpercentile(np.abs(diff), 99))\n",
+    "\n",
+    "imax = np.nanargmax(np.abs(diff))\n",
+    "print(\"max index:\", imax)\n",
+    "print(\"range:\", r_n[i0:i1][imax])\n",
+    "print(\"CRIMAC:\", ref_ts[\"Sp_target_n\"][imax])\n",
+    "print(\"echopype:\", Sp_n[i0:i1][imax])\n",
+    "print(\"diff:\", diff[imax])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "d6b32d7c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 3))\n",
+    "plt.plot(r_n[i0:i1], diff)\n",
+    "plt.axhline(0, color=\"black\", linewidth=1)\n",
+    "plt.xlabel(\"Range (m)\")\n",
+    "plt.ylabel(\"echopype - CRIMAC (dB)\")\n",
+    "plt.title(\"Sp residual in target window\")\n",
+    "plt.grid(True)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c062de91",
+   "metadata": {},
+   "source": [
+    "### Get split-beam alongship and athwartship angles\n",
+    "\n",
+    "For split-beam EK80 data, the target position within the transducer beam is estimated from the phase differences between transducer sectors. Because this example uses FM complex data, the sector-level complex samples are first pulse-compressed, then combined into fore, aft, starboard, and port transducer halves.\n",
+    "\n",
+    "The alongship and athwartship angles are then computed following the CRIMAC broadband processing workflow. Phase differences between transducer halves are converted to physical angles using the calibrated angle sensitivities and the inverse-sine relationship described in Andersen et al. (2024). This approach reproduces the reference CRIMAC implementation used to generate the published broadband TS spectrum example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "gamma_alongship: 24.916666666666664\n",
+      "gamma_athwartship: 24.916666666666664\n",
+      "theta shape: (2356,)\n",
+      "phi shape: (2356,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "\n",
+    "gamma_alongship = scalar_param(\n",
+    "    cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "gamma_athwartship = scalar_param(\n",
+    "    cal_obj.cal_params[\"angle_sensitivity_athwartship\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _get_splitbeam_angles\n",
+    "theta, phi = _get_splitbeam_angles(\n",
+    "    pc=pc_ping,\n",
+    "    gamma_alongship=gamma_alongship,\n",
+    "    gamma_athwartship=gamma_athwartship,\n",
+    ")\n",
+    "\n",
+    "print(\"gamma_alongship:\", gamma_alongship)\n",
+    "print(\"gamma_athwartship:\", gamma_athwartship)\n",
+    "print(\"theta shape:\", theta.shape)\n",
+    "print(\"phi shape:\", phi.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "3ae46a66",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(2, 1, figsize=(8, 4), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n, theta)\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].grid(True)\n",
+    "\n",
+    "ax[1].plot(r_n, phi)\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].grid(True)\n",
+    "\n",
+    "plt.xlim(3, 8)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ea9db6d",
+   "metadata": {},
+   "source": [
+    "Cmpare with Crimac"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "418f0ac8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "theta RMSE: 0.43174450157798355\n",
+      "theta max : 13.11178108969502\n",
+      "phi RMSE  : 0.9274489945255341\n",
+      "phi max   : 14.476222236380444\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1100x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compare echopype CRIMAC-style angles against CRIMAC reference angles\n",
+    "\n",
+    "theta_np = np.asarray(theta)\n",
+    "phi_np = np.asarray(phi)\n",
+    "\n",
+    "n = min(theta_np.size, ref_ts[\"theta_n\"].size)\n",
+    "\n",
+    "theta_diff = theta_np[:n] - ref_ts[\"theta_n\"][:n]\n",
+    "phi_diff = phi_np[:n] - ref_ts[\"phi_n\"][:n]\n",
+    "\n",
+    "print(\"theta RMSE:\", np.sqrt(np.nanmean(theta_diff**2)))\n",
+    "print(\"theta max :\", np.nanmax(np.abs(theta_diff)))\n",
+    "print(\"phi RMSE  :\", np.sqrt(np.nanmean(phi_diff**2)))\n",
+    "print(\"phi max   :\", np.nanmax(np.abs(phi_diff)))\n",
+    "\n",
+    "fig, ax = plt.subplots(2, 1, figsize=(11, 4), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n[:n], ref_ts[\"theta_n\"][:n], label=\"CRIMAC\")\n",
+    "ax[0].plot(r_n[:n], theta_np[:n], \"--\", label=\"echopype\")\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(r_n[:n], ref_ts[\"phi_n\"][:n], label=\"CRIMAC\")\n",
+    "ax[1].plot(r_n[:n], phi_np[:n], \"--\", label=\"echopype\")\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "c095e6a3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure(figsize=(10, 4))\n",
+    "plt.plot(theta_np[:n] - ref_ts[\"theta_n\"][:n])\n",
+    "plt.title(\"theta difference\")\n",
+    "plt.show()\n",
+    "\n",
+    "plt.figure(figsize=(10, 4))\n",
+    "plt.plot(phi_np[:n] - ref_ts[\"phi_n\"][:n])\n",
+    "plt.title(\"phi difference\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5ad45e65",
+   "metadata": {},
+   "source": [
+    "### Compare with echopype split-beam angle helper\n",
+    "\n",
+    "The CRIMAC workflow computes physical angles from pulse-compressed transducer halves using an inverse-sine relationship. Echopype also provides a generic split-beam angle helper through the consolidation module. In this section we compare the two implementations to assess whether they produce equivalent alongship and athwartship angle estimates for broadband EK80 data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "be119344",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "target_peak_idx: 975\n",
+      "range: 5.79306 5.7930599853739295\n",
+      "CRIMAC theta_t : 0.19805856629305635\n",
+      "echopype theta : 0.2555534398211754\n",
+      "theta diff     : 0.05749487352811905\n",
+      "CRIMAC phi_t   : 2.127909429160737\n",
+      "echopype phi   : 2.1099409547175005\n",
+      "phi diff       : -0.01796847444323646\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.consolidate.split_beam_angle import get_angle_complex_samples\n",
+    "from echopype.calibrate.ek80_complex import get_filter_coeff\n",
+    "\n",
+    "filter_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "\n",
+    "pc_params = {\n",
+    "    **filter_coeff,\n",
+    "    \"receiver_sampling_frequency\": cal_obj.cal_params[\"receiver_sampling_frequency\"],\n",
+    "    \"drop_last_hanning_zero\": cal_obj.drop_last_hanning_zero,\n",
+    "}\n",
+    "\n",
+    "theta_ep, phi_ep = get_angle_complex_samples(\n",
+    "    ds_beam=cal_obj.beam.sel(channel=[tsf_channel]),\n",
+    "    angle_params=cal_obj.cal_params,\n",
+    "    pc_params=pc_params,\n",
+    ")\n",
+    "\n",
+    "theta_ep = (\n",
+    "    theta_ep\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    "    .dropna(\"range_sample\")\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "phi_ep = (\n",
+    "    phi_ep\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(ping_time=tsf_ping_index)\n",
+    "    .dropna(\"range_sample\")\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
+    "\n",
+    "print(\"target_peak_idx:\", target_peak_idx)\n",
+    "print(\"range:\", r_n[target_peak_idx], ref_ts[\"r_t\"])\n",
+    "\n",
+    "print(\"CRIMAC theta_t :\", ref_ts[\"theta_t\"])\n",
+    "print(\"echopype theta :\", theta_ep[target_peak_idx])\n",
+    "print(\"theta diff     :\", theta_ep[target_peak_idx] - ref_ts[\"theta_t\"])\n",
+    "\n",
+    "print(\"CRIMAC phi_t   :\", ref_ts[\"phi_t\"])\n",
+    "print(\"echopype phi   :\", phi_ep[target_peak_idx])\n",
+    "print(\"phi diff       :\", phi_ep[target_peak_idx] - ref_ts[\"phi_t\"])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "298f0ce9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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Xxx9//KEy1NkhGThwoNkx/uzZs2r+fteuXRnu87PPPlPqBv4Nhuz633//VX8Db6Nz5844eDCjiyqz3Hv16qX+1tq1a+Ohhx5CTExMls/P/v370bdvX/V38++nn4DxOHJ63NawlJdzf8OGDar7zcfOjX+rLTALNz9/548//qhUH/y7qlWrpkYwaEZoYDyfK1asQNu2bdXt9OvXT11n2bJlyoiQz8e4ceMQGxtr02Nevny5ihTic8bXyfDhwzO8jvi38z5///139ZzztcK/cetWk2uuiW+++Ub9Tbx89OjRKomAt5kd8+bNU4+ZzxcX4L788kubHrMgCLb7rfB9xo37Qgnh0i4gNQlIjMb5GBeERiXAzdkJrWqlLyBX8HJDdV+tbDhUeQjQaRpQoU4RPmhBEATHRYruvJIYk/VGR1Cbr5sp2iyr6+WSF154QR0kffXVV6q45nz8XXfdpYpBcunSJVW8sVhZu3Ytdu/erWbhk5OTzbexbt06VTzx9LvvvlPFqKXagMUlC9W//vpLFVAskhnbZlmYs3B788031e+zoIyMjMTYsWPVZXXq1MGAAQPU47SEP/O2LeNpOKvPBYCdO3fCz88PI0aMMN8PC9PBgwdjzJgxOHDgABYuXKjy2x944IEsn5/x48crsz3eHv/2Z555Bq6urjY97pxgsd21a1dMmzZNjURwYzFpC/n9OxMTE/H666+rRQUuGpw5c0Y9l9bmoz///HNVxHMxgWMZlML/9NNPaoGD6hEuftgCi376MfAxr1mzRi2ksGhmpJ8lzz//PJ544gns27dPLWawsDdeb3yO6d3w8MMPq8u5yMHnPztYpPM2eT16QLz11lt48cUX1f9MEAT7wM9FfoZws/yMFByc89ss8rl1l7tlLV94uDpnuJohMQ+8HFn4j1EQBKEkkVbKiYiI4CCuOs1MXFxcWmBgoDq9gZd9st5+vDXjdd+olvV1vx2a8brv1rV+vVwQHR2d5uHhkbZly5YM50+ZMiVt3Lhxav/ZZ59Nq1u3blpiYqLV25g4cWJaQEBAWnJysvm82267Le2OO+5Q+8ePH1fP2+bNm82XX716Na1s2bJpixYtUj/PmzdPXWfbtm3m6xw5ckSdt337dvXzwoUL0ypUqJAWHx+vft63b19amTJl0s6cOaN+Xrdunbr+L7/8Yr6Na9euqfvh75IJEyak3XvvvRke/8aNG9OcnJys/+/S0tK8vb3T5s+fb/UyWx73yy+/nNa6desMz9fIkSPNP/fu3Tvt4YcfTrOVgvo7d+zYoW43Kioqw/2sXr3afJ23335bnXfq1CnzedOnT08bPHhwWl4ICQlRt3fw4EH1M/+X/HnOnDnm6xw+fFidx+eV8HU1bNiwDLczfvz4NF9fX/PPmZ/z2rVrp/30008Zfuf1119P69q1q9XHle37WRAEoTTx3Qh9bLHjm7Snf92fFvD0P2lvLQ284WrvLz+qLuN10i7tTUvb/X1aWmxYkTxkQRAER6slLZFOdwmETu40v2G3kGZzxvb999+bZb/sJlJOnl3nonnz5io73YAyc0OqzM6ii4uLkkAbUFrcuHFjdZkBr0O5swElwJQMG9ehJJvXWbJkifqZzvWUILMLbgk7xwYVK1bMcD/sVLMDb/m3siPMTis7vdZgZ3bq1Kmq0/7OO+/cIKvP6XEXFPn9O/fu3YuRI0cqeT4l5jR0I5YGhKRVq1bm/apVqypJN0cRLM+zlKVnB587ytj5+5Sm161bN8f75GuJGPdx7NgxdOrUKcP1M/9sSWhoqOrQT5kyJcPzQRPFzP9LQRDyDue4+X3BTWa6SwgpycBF01iXf1ezc3nHgPR57sxz3YFBkcDiScBfDwBB+wr38QqCIJQAip2RmsPw3OWsLyuTUZ6FJ09mc91M6x6PZJzhzQuGrJcy4Zo1a2a4zN3dXZ3aEqmWuSCn3Nu4bUunbkt4vqUs3Pi9zBjncUZwwoQJSlJO2TTlzbY6fhu3wcc0ffp0Nd+cGX9/f6u/S3k1C0U+R5xlfvnll/HLL78oWbQtj7swsfXvpMx70KBBauNsd5UqVVThy8KcsvOs/re8/ez+1zlx8803K/k85d41atRQv8fkgZzu0/ibsnrdZPUas/w93qflwg+xXCgSBCF/cAGX/g8kOjoaXl5e8pQ6OlcOqVluuPvimmc9nAo9e4NzuUGzGrroPhYchdQWLeAUdgYIPgTU0wu6giAIgm1I0Z1X3LyK/rpZ0KxZM1Vcs+Dq3bu31euw68jZV84L52VOj/fBedzt27ejW7du6jzGvR0/flwZWxnwOpz7NrqW7Ggyi5qdYwN2nFmk0QSLj4fFd2a2bdtmLqBp4Mb7MW6jXbt2am69QYMGufobOFfMjfPunC9m4W8U3bY87uzgYkJeukL5+Ts583316lXVuTdmyDOb1Nkb/s/ZiZ81a5ZSThDOmecW/o07duzIcF52j52deC4onT59Ws3nC4JQMHAxjItpxr5Qgua5a3fC7vMRarehXzllnJaZgIqe8HRzRmxiCsJ8GqMS/tZFuyAIgpArRF5eAqGsmIZVLCZZWFNuS9nxF198YTaZovmWYQ7G4oau4z/88IMqLm2hYcOGSsZMszAWWTTuolEbCyGeb8CCnjnqLM737NmDyZMno0uXLhmkwyzSed7TTz+til9rXXhmt9Ok69ChQ8rQp3Llyma3cP4ejdzork4JJP8Wmrvxfq0RFxen/n46eZ87d06ZeNEEzHKxwJbHnR2Ux/N36dzNQtjWrnF+/k4W6yz2aYDGYpSX0VStIKFzPccKZs+ejZMnTypTPkr3cwv/BsYS0bGcfxeLeCoQsjvIp1rh7bffVsZ1XJzgogMXTngbgiDYB46e0HiTG/eFEgAzt1vfCTQZhl3ntIlaB4uoMEucnMqgSTWd5X2yjGnsi1ndgiAIQq6QoruEwmLrpZdeUkUJi0lKjP/++2/zvC0LJRZIlAuyG87ILEp1c9P1ZoHD32NEFGeRKQdm4WR5GzxIY7FIKTevw4KaMu7McDaXcmQ6qFuD3Vs6W/P+6AbOgtKIr2HXnq7sLNbYbaUUki7WxtxwZig/ZoeWcWfsdNO5m3Fnr776aq4fd1Zw0YP3Q0WAIfO2hfz8nbwfznwvXrxY3S9vi07oBQmdyvm8cN6cagUu9Lz//vu5vp3u3bvj66+/VgUz48QYQ8bbort+VlAhMWfOHPU3t2zZUr2OuW+8xgVBEAQr1OsNjP4K6DAZu4x57jo3Ssszz3XvTqilzwg9BiRnHB8ShELh6ok8JfoIQnGgDN3UUIpht9fX1xcRERHKBCrzLBsNqngQn93Bv2AdFkCPPPKIkmXnBGOfWLxlzqVmN5rGapRa55TZXBSPWyg4qKI4evQoNm7caJfbk/ezIAiCxWdiUgpavrICSSlp2PhUX9SuaF3J8OO2c3jhj0Po1bAyvg+9DYiPAGZsAqq1lKdTKDzObAS+Gw40HQHc8YM884JD1JKWSKdbKFLYaae0m5JoawZhQumBXXmOKVCmztcDRyEmTpxY1A9LEEo1XKy67bbb1MZ9wcEJPQ4EHQBSU7D/QrgquKv6uKNWhazNVQ0ztSPBUUBVU6EtEnOhsNn0kT498hcQdUWef8HhkKJbKFI4W92jRw8lDc5KWl4SmDFjRoZoK8uNlxVXKIvP6nFzs1U2bws0UmPMHaXilJp/+umnSkIuCELRQUPIX3/9VW0SGVYC2PYFMKsnsOa19HnugIrZ+mdwppsXh0YlILzjI8BdvwONhxTigxZKPakpQND+9Kfh8O+l/ikRHA+Rl4u8XCgEmEfN15o1KEXx8/Mrlv8HurjTDC47wzhmmjsCIi8XhNzDRAkaJZJ77703T2kXQjHii85A6FFg7E+YtLUK1h8Lxcs3N8Pk7tl7YfT9YD3OXI3B9/d0Qq9GVQrt4QqC2XH/28F6v814oNM0oIaOMhQER5GXO8bRsiA4OCyqi2thnR0sqHMbxSYIQsmBRTYTE4QSQOx1XXBTwVCzE3af26P2O2bhXG5Js+o+qug+EhQpRbeQTnQI+3dAuQJeiDn6rz5teRsw6kv5DwgOiRTdNlDKveYEoUQg72NBEEo1F7br08qNcDzaHVHxyfByczZHgmVH0+re+PdgEAKDIoHAP4HL+4Au9wHlHG8xWbATCdHAV92hZg8e2gu4eRXcU9vtIaByQ6BSw4K7D0EoYGSmOxsMGV1sbGxB/x8EQShgjPexyGMFwXZSU1NVTCE37gsOzPmt+tS/izkqrF1ABbg453woaDZTY9G9/h1g04fA5b0F+3iF4s3J1UBMCBB9BTi2rGDvi530dncDAV25gg5c2AmsfVPvC4KDIJ3ubGDOMmOqOI9rZDdnZzYiCELx7HCz4Ob7mO9nvq8FQbCNuLg4NGrUyJw24eVVgN0soeDnYol/V+w8km6iZgtGVvep0BiktGsO55BAIPgA0Mg0ZyuUPgzJNzn4K9Dy1sK536RY4PsR+pSvv1odCud+BSGfSNGdA9WqVVOnRuEtCIJjwoLbeD8LgmA7NIgRHJykOOCSnuFG7c7YtUwbZHasU8GmX6/m44Hynq4Ij01CiGdDVOeZwYcK8AELxZqUJOD4ivSfz/wHJMYCbtaz3vPF0ieBCnWBNuOAshW0jL3JMODgYuDAIim6BYdBiu4cYGe7evXqygSLLq6CIDgelJRLh1sQcg872+Hh4fLUOTpOLsBdv6rC+5JTdVyOOApnpzJo41/e5mMhmqltOXUNx1FHF91XpOgutcRH6ti4y3uA3k8D9fsVTMHNPO4d31CzBjQfDRhx8i1v10X3od+AwW8CzpKqIBR/pOi2ER6wy0G7IAiCIAgOB4uSen3UtmvfJXVWixo+8HSz/TCwqano3hFXA715xrVTQGJMwRpoCcUTr0rAmFl6progxy6Pc1Y8DajRDvBRSz2a+n0Bz0pA7FXg9Hqg4cCCewyCYCfESE0QBEEQBKGUsNNkotbBhqgwS9jpVr9/1QUox1GdNOBKYIE8RsFByFxw29vYzJgbp5w88yJS8zF6nxJzQXAApOgWBEEQBMEqCQkJmDRpktq4LzggdJ1f/Qpw5G81i7vrbFiu5rkzm6nRwTytWgt9pkjMSx/h54Gg/RkLbL625g4Ctn9t30iy0xusF92k1e3phTkVF4JQzJGiWxAEQRAEqyQnJ+O7775TG/cFByT0KLDpI+D36YiIT8axK1Hq7PY2OpcbNPArB1fnMirfO7jzC8BD+4B2EwvoQQvFll3fArN6Af8+nn5eZJDOgeectb04tQZISdAmalWa4FJ4HG76+D/M3XRGX16rI1ChDuDhC1w7ab/7FYQCQma6BUEQBEHI0oTwvffeM+8LDpzPXasD9lyMUg3KOpU8UcXbPVc34+bihAZ+3qrTfTCxOqpXlDSIUokh+Q7oln5e81HA8qeBS7v1rH+l+va7H3a5y5TBLzvO42hwFD5ZfRx3dfGHu4szMPFvwKcm4CRRoELxRzrdgiAIgiBYxc3NDU8++aTauC84dj73rjzOcxs0re6tTo8E6W65UMoIPQ5cPQ44uQINB6WfX85PG/WRQ7/b7/6c3YHGQ9XuqsAr6jQyPhnrjobqy8v7S8EtOAxSdAuCIAiCIJRULhhFdxfszOM8d2YztcCgCGDLZ8Ciu4EwnfktlAKO/qNP6/UGPPRrwUyLW/UpJeb2MFQbMxt46rR63Z6/Fqu63AZ/mhz4zaQkAxGZzhOEYoYU3YIgCIIgWCU1NRWXLl1SG/cFB4OFCI2vyjgjoVpb7L8Qnq9Ot1F0q043O5qBfwKX99n1IQsOUHRbMzZrOlx3pq8es5/Bnns51cleGRisfqxZXgd1rzkSgoi4JH2dMxuBD5sAi8VfQCjeSNEtCIIgCIJV4uLiUKtWLbVxX3DQLne1ljh0NQ0Jyamo6OWGepXzlq1tOJifvx6LxCrN9JniYF46iLysZ7ZRBmg8DKmpabjvx924f8Eeta8MzYy87IO/5v1+2CWPuJjhLENaPqVHXTT0K4fElFQsPxSkL6zcCIi9BlzcCVw/nff7FYQCRopuQRAEQRCyxMXFRW2CAxJ0QJ/6d0mf5w6ogDKZ85VtpIKXG6r7euib9migzww+aKcHKxRrji1Ldw33roq9F8Kw7FAw/j0YhN3n9dgCWo8FGt2k/APyDBdxPmquI8jS0hAWk2jOlh/YrCpGta2p9v/Ye1lf37tq+jx5fop9QShgpOgWBEEQBMEqXl5eSEpKUhv3BQdjwCs62qvLTIt57rxJy2/I604L0GcE20lKLBRv2t0N3P0n0Pc59ePKw7r7TP7aZyqAm94M3LkQaHxT3u/n6FJ96llJuZavPRoCNtKbVPNG7YqeGNmmhrp425lrCI6I19dtacrsPrDIPvPkglAASNEtCIIgCIJQEmFHu2JdpPr6Y/c5w7k8byZqmee6t0ZX12dEXgRi9W0LJRhnV91Rrt8XaWlpWHFYz1kTdruTUuzk+XDMFBWWybV8UHMdUVergqcyAmRt/df+S+nz5C5lgWsngCDxGBCKJ1J0C4IgCIIglGBOX41GWGwSPFyd0LyGr1063ftCUoDyAaVnrvvcViBOG9GVdk6EROPstVi4OTspj4DrMYnYfPJq+hXCzml3e7qK54bwC0DQfj033ugmxCelYMNxHQ82qFlV89VGttES8yWGxNzdG2g8JL3bLQjFECm6BUEQBEGwSkJCAu6//361cV9wILZ9DfwyHjixyiwtb1O7PNxc8nfoZ2R1M8IptWpLwNlNm2yVZDgrPO8mYE7/0tnVX/YMsPw5s1HZikO6y92jYWUMb6UVD3/tN70GUlOAb/oBK18AzmzI29y4fxegXBVVyMclpaCGrwea10iPKBvWsjpcnMrgSFAkjl8xRYm1MknMD/2mH4MgFDOk6BYEQRAEwSrJycn48ssv1cZ9wYG4uENHPIUEYpep6O4QkL95bhJQyQuebs7KCf1st7eA5y5rA62SSnIisPZ1vX/tJPDzWCCpFDn582/d8z2w7Qtzp3+lIfluVhUjWtcwz3izM82ILzQbkV4A20FaPqBZ1QzmfzT069PYT+3/sdckMa/fH+jxKDB+MVBGyhuh+CGvSkEQBEEQrOLq6oqXX35ZbdwXHIjQ4/q0ciPsstM8N3F2KoPG1XS3+1C4q571Lcns/QEIOwt4VgbcfYEL23URWlo4vR5IigF8agI12uJSeBwOXopQdgEshtv5V1D52dEJyVh3NET/Tsvb9OmRv4Ekk9lZTrCgP7tJ7zcZhpTUNKw+YhT3ep7bklFtdbH/577LOrLMxU0bB1Zvrb0MBKGYIUW3IAiCIAhWcXNzwyuvvKI27gsOAuW1NJVic9ajDs5di1V1SLuA/BfdlnPdgZcjUeK7vBve0/u9nwbGLgB6PAZ0nIZSA9USpMkwVcyuMhmoMXqucjl3ODmVwc2t0wtgRe0uukhPiAROrLTtflw8gFvmAF0fACrVx74LYbganQhvDxd0rnejQmNA06oo5+6iFgHMkWWCUIwpdkU3JWx169aFh4cH2rdvj40bN9r0e5s3b1Y5om3atCnwxygIgiAIglBsibgAJMereesd4eXUWU2q+cDHwz5dacPBnDO1WPY08HVP4MphlMjFi7bjgSpNgPYTgbo9gQEvA06mw+eSHk9FIzRjzrrJcHWywhQVNtjkJk4MifnaYyGIjE/Sz0+LMfrCQzZmZ7t6AM1HA4PfzCBh79vYD67ON5YrHq7O5sewxJCYG4Z3S2YAR0yLBYJQTChWRffChQvxyCOP4Pnnn8fevXvRs2dPDBkyBOfPn8/29yIiInD33Xejf//+hfZYBUEQBKGkw2ig8PBwtXFfcDBpeaUG2HFed6MZs2QvmloW3UEHgOAD+rSk4V4O6P8ScN8WwMU942WUTf86GTi8BCUWSuljrwEe5YGAbgiLScSOs9dvkHzTXK+BXzkkJqem53e3uFWfHl8BxOdeEWHMcw+0cC3PzOi22sV86cEgdd+Kk6uA/T8De3/M9X0KQqkpuj/88ENMmTIFU6dORdOmTfHxxx+jdu3a+Oqrr7L9venTp+POO+9E165dC+2xCoIgCEJJJzY2FhUqVFAb9wUH4aoxz90w3UStTv5N1AyaVPNWcvWQqATEVWpW8mPDaA6Wmd3zdMH9+3Tg3BaUaGk547icXbHmaIiateb/37+Sp/lqNDkzut1mF3POVldqoE3Ngg9mfz8XdmoZf8hR9ePJkGicDo2Bq3MZ9GlcJctf61q/Evy83REem2SOFkPL29OL75hr+fnrBaFkFt2JiYnYvXs3Bg0alOF8/rxlS9YfZvPmzcOpU6eUyYstMPIkMjIywyYIgiAIglBiSIgCnN2RWKEhDl+OsHun28vdBXUqean9C2719JnsdpcUGAv24y3pxl7W6HSvllynJAA/jwNCj6HEUbYC4F1dz3Mrh3I9zz3IQlpuYBTdjPm6Gp2gzcxu/wF48iRQp3v298PO9Lo3ge1fZehyd61fGd7ZjEQ4W8yT/7HPJDH3awJUawmkJgOBJViFIDgcxabovnr1KlJSUlC1akYZCX8ODtZv8sycOHECzzzzDBYsWKDmuW3h7bffhq+vr3ljJ10QBEEQhBvx9PRUi+LcuC84CH2fBZ4Pwq5ak0BjZ7pLV/cta9e7MPK6Dyb76zOCD5WcGedNHwEnVwPLn8n6b2L3e8w3QK2OQHw48OOtQJT141WHpfdTwKOBKsIrLjEF/53Q3eTBzW+UfNep7IXWtXxVJ5xyb0XVZoCbXpzJktTU9Lnxxrq4XxUYnKO03GBUGy0xXx14BVGcJyet7tCnBxbb+pcKQukpug0sc/gIZ8gyn0dYoFNS/uqrr6JRo0Y23/6zzz6rZsCN7cKFC3Z53IIgCIJQ0uD3L6PCuFn7LhaKMU7O2H4xzu5d7sxmatuiqgBlnIG460CUqdhyZCKDgB2z9X6/l7KPn3LzBMYtBCrWByLOAz/drlUGJQmaojk5q4I7PilVLeAY//vMGF3nvwwXc0uyel6C9gJRlwG3ckDdXgiNSsDeCzoPfGDTnIvuFjV9UK+Kl8qNX37ItOjR4hZ+egEXtgFh52z/WwWhuBbdSUlJqmg9duwYrl/Xxgp5pXLlynB2dr6hqx0SEnJD95tERUVh165deOCBB1SXm9trr72G/fv3q/21a9davR93d3f4+Phk2ARBEARBEEoa6fnc9pvnzmymduBKopodV+Q0u+sI/Pe+dn5n7FXDgTlf36sScNevOsc7aL92zi4JXNqt3dtNGAZpdAzPagGORTcv2nUuTEV5KS7uAr7sBiwwzVpn5uhSfdqgv3IwX3PkihIXtKrli2q+Hjk+TD6W0aZutzmyzKeGdponB6XbLTho0R0dHY1Zs2ahT58+Sp5dp04dNGvWDFWqVEFAQACmTZuGnTt35vqBMP+TEWGrVq3KcD5/7tat2w3XZ7F88OBB7Nu3z7zNmDEDjRs3VvudO3fO9WMQBEEQBCEdysqffPJJtXFfcABoSvVVD6QsfRp7z+uOYccCKLqb1dBF98nQaKRUbalNs5IT4NBcPwPs+U7v07XcVnVHxXrAnYsAn1pAtwfh8PB5+KYf8GEz5dKenJKKNUd10T3IirTcoKqPBzrX1a+1vw1DNe9qQMhh4PwWIOLijb90bGkGabkRFTbIBmm5wUhT0b3l1FWERManS8z5mvSqbPPtCEKxKbo/+ugjVWR/88036NevH37//XdV4LLTvXXrVmVmlpycjIEDB+Kmm25SM9e54bHHHsOcOXPw7bff4siRI3j00UdVXBiLaUMazmgw9cCdnNCiRYsMm5+fn8r35r6XVw4zJIIgCIIg5Kho++CDD9TGfcEBYIFz5SBiLx9BbGIKfDxc0NBPZ3Xbk2o+Hijv6apmeI90eR94cDfQbAQcmg3vagOu+v1yNv/KTK32wEN7AP8ucHiO/qtPqWBw9VAxYXQIr+jlhg4B2Y8qjGidqevsWwsIMD2Xh36/sbgPCdTjCY0GISYhGZtOXlUXDbSIJMsJOqm38y+v/AvM7umtxwEP7ALaT7L5doQCynq/vFeeWgC2uY+ZoIv4unXr0LJlS6uXd+rUCffccw++/vprzJ07Fxs2bEDDhibJkQ3ccccduHbtmpKJBwUFqeJ56dKlqoNOeF5Omd2CIAiCINgHznI/8cQT5n3BAbiqGx7nnWqp0/YBFeDkZP95fMp6m1bzwdbT1xAYFI0Wtew/N17o2eb7f9H7/V7McNHxK1G4e+4ODGlZDS8Nb5a1v4Flljel9nQ0b2nKq3bEopvu7BbS8v5N/ODinH2/bkiLanj5r0Mqw/1kSBQa+HnrGetzm7XUu/tDGaPt3H2AGm2UU/rGQzpv27+iJxpVzd1C0ai2NbHnfLgq9qf2rGc95k0ofOhM/9cDQLuJwND3gegQoHzpNLHOVdG9eLFtcxGcm545c2aeHhB/L6vfnT9/fra/+8orr6hNEARBEIT8w9Gv999/X55KR8IUXXUsubo6bVHTt8DuihJzXXRHpjtRG+Zbjkal+sCor/Rcds12GS56e+kRBEfGY97msyhf1g0PD8ihoXT1JPDtECA5DihbHmgwAA5DdChwfqvebzJMGRobUWGc586JCl5u6NWwisr0pqHaY4MaA81GAcue0rFyXBQyPAAaDQaePAXEhGaQltO1PLfGjcNaVsdrfwfi4KUIlfPdwFB3JMVpJ/rGQ6UQL2z43K97S+9HBQEftQAqNwImmxZ1ShkO+KkoCIIgCIIgWIXdQwD74v3Uqbn4KAAMMzV2NfHLeOAdf23A5YiwM9pmHDDknQxn7zp7HeuOhZrHuz9afRyLdl3IuYBvPERL1RdNBHbPB6J0QVnsOc74rjSgemvVkTx0KRKXI+Lh6eaMHg1tm48e0cbkYr7/siraldkcJfvk4K8Zr+ziBvjWVHPja4+G2BwVlplK5dzRq1EVtf+nkdnNRaAvOgEL7wLObsz1bQr5ZPss7UxPr4Mh7+qEg3ObgKADpfKpzVWnO/P8tTW4MsW56gYNGmDkyJGoWNH+5h2CIAiCIBQ8PGCmVwthMojEhjlAZylcj+FtCtPHX/WrFFzRbURHsdOd5p2MMolRwKk1QO2OcCiSE3XxZ+X1/94KrRwY27G2mmn+Yt0pPPv7Qfh5u6NPY72wcQOs0Ed+AUQHA2f+A/5+GMDDQI12uhjv/ojV+ysWHPlHnza5WZ2sNGVm925UBR6utkm2BzStCg9XJ5y9FosDFyPQunZ5oMWtwImVwKFfgT7PAIkxOsPbtJqx82yYmhuv4Oma49x4VoxsU0MV7pSYPzawEcpQcVGvrzbH4+JH3+eBDvcAznkufwRbiQsDNn2o9/s9r80Gm40EDv2mi/FRX5S65zLPne69e/eque3Zs2er2e3169crgzWet2bNGlWUs/AODAy07yMWBEEQBKFQiI2NVRJzbtwXijnXTqouZapHBZyOK6vOYoZxQcEuuqtzGUTFJyMsYEi6WRa7m47C2U3AJ62BPT/ccNHGE1ex48x1uLk44cF+DfHEoMYY07amMo+buWAPDl2KyPp2WVSP/Rno94IutsnlPcDeHwFnC38Eytm5WFIcYJb26fV6v4l2E19hkpZn51qeGS93F1V4E7OxWZOh2lF80Bv69bFkOvBZOy39ZlqRSVrer0nVHOfGs4Idcnbkz1+PVfPdit5PA37NgfhwYNmTwNc9gFPr8nT7Qi7Y9BEQHwH4NdP/d9LZFKfH2f4YbZhXmshz0c0u9oABA3D58mXs3r0be/bswaVLl5Rz+bhx49R+r169lAO5IAiCIAiCUMAkRKuZyejyjdluRc3yZeHpVnBdPRajRid9v1cPwNkNuHpMO1I7Aiz+1ryuJbCZHJbZ5X7f1OWe0CUANcqXVUqPd25phe4NKiln+EnzduLC9WwWo9zLAb2eBO5dBzx+DBjxGdDrifQospQkYP7NwLt1gZ/Gahl6ZBCKDFcvYPJSHZfm1xRnrsbg+JVouDiVQb/GuZN8GzFe/xy4rBYp4O4NjJmtO/0pCcCptcD10yrfnM/1qiPBeZaWG/C1bsydmyXmvjWB6f8Bwz4EylYEQo8AP4zS4xB01hbsT8Ql3c0m/V9On6Wv1VEvQPH/v3teqXvm81x001jl9ddfV3nZBtynkdl7770HT09PvPTSS6ogFwRBEATB8eB3eVhYmNq4LxRzAroCD+zEv21nqx/rF+A8d+a87gNX09INwzJHQxVXTqwCLmwDXDx0cWwBO7w05fJyc8bMPvUzLDR8dVd7NKnmjavRCZg4bwfCY23IsGdedbu79WbAUQAWozRc4yw1ZegfNgFm9QbWvQ2EHEWhQjl2rQ5Az8fVwoBhoNalXiX4euYuvaBXo8oqru5KZIJSC2SA3fSkWD3rW701jl2JwoXrcXB3cVK/lx/oYk7+ORCEpBSTsR/l5B2n6Fg7dlsZUUZpe3GRma9/B/imP/DjrdqEz9EJO6vc6OHfTZvlGZQpA3S5T+/vnKsXnUoReS66IyIiEBKiDQ8sCQ0NRWSkdrEsX748EhNt+CASBEEQBKHYwc4ev8u5yTy343AyNEadNijAee7Mc93KTK35GH3mYQeQmNNka+3rer/TNMBHu70TdmY/WKkN6ab0qKtMuizx8XDF/MmdUN3XA6dDYzD1u12IT0rJ/WOg4dqjh4AZm7QMvWYHpVBA0D5gwzv6eTQ/qKRC78wabuKDcyEtN3B3ccaQFtUzSsxJyBHg57HpknNV3Ov76dmwcr6VGd3rV0Llcm64HpOIjSe0K7oZz4ra0Ou+LcCAV9PPDzsH7Psp3X3fXvA9EBWs5ezbvgL+egiYOwj4X5OM9xV6FLi0Czi5CpjdBwj8Cw4NM+4f3AOMmZWu6jCgk325qtrNvJSZ2+VLXs5M7iVLluDixYtKTs79KVOmYNSoUeo6O3bsQKNGjez5eAVBEARBEARrmArdU6HRBe5cntnBXMWGNb5Jd40pG+ascnHmyJ86wsrNG+iecRTyj72XVOyUb1lXTO1Vz+qvV/P1UIW3t4cLdp0Lw6ML9yGVMurcwqKkWkvdaZ+2BnjiuDZhY0Z2U21mpji2DPigAbBkBnDkb21EZk/Obgb+fAA4vUH9GBIVjz3nw9T+wGY5R4Vl52K+9KDO31Zs/iT9Cozxspjnzo+03IDz4MNb6fv9Y69FsW+JX5MMiyxY9SLwx33A3AHAhZ15e99FXMy40LT6VeDdOsD/Gms5+/JntKHbhe264Aw/l37djlOBW+YCAd0BmhEumgCsfMGx5e9unkB5f+teByM+A+7bmu5oX0rI83LSrFmz1Lz22LFjMzibTpw4ER9+qN3qmjRpgjlz5tjv0QqCIAiCUGhQrfbWWzpn9bnnnlOGanaHB6rJ8UB8pDZyouSzQh37309JJzUF+KCROtANvU63bFfUL0ATtcxFN82rotI84N3tQS0t9a2FYguLGSM/uNsDOtLKBItDxoKR+/rUV13trGhczRuzJ3TAxG93YNmhYLzx7xG8dHOz/D22cn5A27v0Zgld4ekIvf9nvXFxg0ULDc8a3QR45U+WrVyl9/6g52/r9cbqwBD11qTzOBcY8gJl6VW83REalaC6zv1prtZ8tH78pE4PBEXEKRk/1x5oomYPKDGfv+WsKuZjEpKVsVuW8I/knPHJNTrujoV3q7HAgFcyFuYkOQG4dkrH8jFvnP4Fav8kkBQDPBqoZ8gJ/yCat5Vx0s7dVZqoOXnzqeX7o04PfUp37zWvAls+09ulPcBt8/VrwhHg88fnpeVt2WeiN7KQnJci8lx0lytXTrmVf/TRRzh9+rQyQahfv74636BNmzb2epyCIAiCIBQySUlJePVVLcN88sknbS+6GcF05C/d/WEhnRCpi+oOkwH/Lvo6x1cCf8zQ56dmmu27/Qeg2Qh7/zklG3bOYq8iLSEKR2OdC63TzRitaj4eCI6Mx7HgKHSgTLq4Q1kriyUaa3WZmeGihTvP42JYnCoWJ3bNefGna/1K+OD21njo5734dvMZ1Cjvgak9rXfH88XQ/wEtbweO/gsc/VvPgx9bqjcWdiz4jCKRhWRmWW92UOrM2yXssFu6luej++zsVAbDW1XHvM1nlcRcFd0NBwHDPwYqNVAu7qsDteFZO/8K6jm3B61r+aJuZS9lBMfIs9Fts1kA4vPU4xGg9VhgzWvAvgXAgV+0moALH32fA8qW19flOAKLYWs4uQARF9KL7nYT9QJDpYaAq42LFnS1p7s7xwz+vF8XsGl2lrwXFHzNrXgeOL8VuH4G6Pus7eaP7gX/OVUcyNfgxMaNG1XHm0X34sWLVcH9ww8/oG7duujRw7RqIwiCIAiCQ0IF28yZM837Nh98/T4VCPzzxssCuqUX3eyExF6zuLCMPnBlAc4YJym6cwcP0HkM61sXKTFOKO/pqgriwoBmaiy6KTHvUEfngxdr6vcFpq4BIi8BHumGwHGJKfh0rTayerBfA5R1sy2XekTrGgiOiMNbS4+qbjc7w4bE2W5QAcJZWW6D3wSuHDYV4P9olYNlV/bbm9QCDCrW111WbpVMp77+NxqIMcqMmeKU2tfthaj4JGw5pSOdDDfwvMLnhkU3u86xicl6ZpuLb5nmxu0hLTeg/wQzuz9efQJL9l7Ovui2NLob9aU2XFv2NHBxJ7Bjlv4cMjrRlRsD7j4qIUBvDYEqjfU+1TmWUXAVAvL+BzQfBVRtrpUNfFyOwPHluuB2KQu0n5jhopDIeHyx7iQmdA1AAz/v9IXZvx7Uixs0uMusKiiB5Lno/u233zBhwgSMHz9exYUlJCSo86OiopQUbenSpfZ8nIIgCIIgFDLu7u744osvcvdLmz7UBbeTK9DiFsDDVxc2dGmu2T79erU7ATO36YNYXuZWDjiwENj4QXpnSbCdUB1vda1sHbOJWmGZ3zWt7o21R0O0mRqJC08vBjMdgBcb6NINbul8t/WskkLXqlAWYztamUfNhmk96+FyeLySNT+2cD+qlHNH53rpsnW7oubAW+itz9MZ57u56MVYLGYkq9z2TLDz+uCu9J/pNG90uRsNAlzcse7wZSSlpKmM9/yqJdrULg//ip5q/GD1kRBVhBtExidh2+lr+e6oW2NUm5qq6N50IlT9T23uovMzasoqnSXNgpBO5watx+nud2G8r1jQW8L/Ex/PiE/152Vxgu9zzrCTLjMAn4wLTi/+eQgrDl/BkaAoLJrRNX22m+ocyvJ3fQv0ex4lnTwbqb3xxhv4+uuvlcTc1TV9Zadbt26qCBcEQRAEoZTBA/6gA3p/6PvavXboe9qZufvDukgw4IGjmm2sqYtyxhW1Gae7HpR0CrmDcmnOVjvprp6Rn10YmM3ULpuKbioVKI/d8K79HaHzQ3SIHnmwAgvArzecUvuPDGikosFyAxc4XhzeTDl9J6akYtr3u3DiShQKBcZfWTJjM3D3X8DwjwDO2FMyXqWpngPP3IH993Hg0K96n/Ph7D6bpOX57XIbz8vNrU0u5vsyGputPxaqint6D9Sz8+u1TmUvNY9ObztmhecKFtWtbgfu+EHH8BlQIVBIC1kZ4IjOP49qN3tGi5kW2IoN+3/RCz0e5YHuj2S4aPe5MFVwkx1nr+PQpQiYYXwbYdGdFI+STp6L7mPHjqFXr143nM+s7vDw8Pw+LkEQBEEQHA0ekNL4587FGSSkQuEV3UeSqhfaPHfm2DDmLTNuS+V1U8FA+fbFHSgWcM6UcU2ftgO2fH7DxXM2nkF4bJJ63kabsp7zMsP8ydi2aOdfHpHxyZg0byeuRMYX/nuwfG1lhoYO9+gZ4bELgPu3Ac8FAbfOS78uJb6Uq/s1B+r1ARoNQUJyiiqG7dl9HtFaP58bjocgIjbdvyHdtbxgJNSjTO7pf2Qq9h0OLlDeuQjwrq7N277ppzvfxYGkOGDdm3q/1xMZVEr0+3p3mc6ad3XWixVUgpjhYhCz2jkKQSO/Ek6ei+7q1avj5MkbZSubNm1CvXoFYCAhCIIgCEKhEhMTo9Rs3LifJexSGHE5POinTDU/8LYoWRRsf75M3a9d0drFur5fwTuXGwRU8kJZV2fEJ6Uq8yplHGWKgyoWxQHVFyy4w84A3lWBxkMyXHwtOgFzN55W+48PbKSK57zi4eqMORM7ol5lL1wKj8PkeTuVvLlYQDWJxQy7kvje8SMwcwtw958q5mnLqWuITkhGVR93tK5lnzEPurw3qeatutrLDweZXeLXHw2x+zy3JZyr5/9y/4Vw/bp0ZPw7A9P/A+r0BBKjgV8nA8uf1fntRcmOb/TiGovnjtMyXLTuWIjqbru7OKnFKEPtcDU6IV050Gmq3t/+VcbItRJInovu6dOn4+GHH8b27duVdOTy5ctYsGABnnjiCbPpiiAIgiAI+YDOrnQpZubx6fXA4SVaindqXaEdoDAW1IgGtQrlw79NAX69xz7ZwX8/ArwTUDyKNUeBkWv+XZBWsR42hetCqUGVwpv7ZGHDuW6y6+x1fWaLMfo08I+iXUA58x8wbygQEwJUbanndSvVz3CVr9afQkxiClrW9MVNLfLfdaWBHTO8K5dzU+Zynd5ajVu+2oIv159UDu/sABZXVpqkwCyEnfKx+JCZm02z3HQxJ5zljkpIRuVy7mhbu2A8HDjH3aOBXoR68Y9DOH8tFg4No8Mm/JEu4d72JfDdzVqxUFTQm6NWRz0SZOHSTsXLu8v0QuCk7nUwtGV1Jffn6MVP28+n/z5d3mm+FnwQOLcFJZk8G6k99dRTiIiIQN++fREfH6+k5jRcYdH9wAMP2PdRCoIgCEJJI/gQcGyZdqg1Ns+K2kHXYFYv4LqeM72BgO7AhCXK+KigKFu2LC5evGjet8rG/2nTLGc3oPtDQA3d0cgzaSlAAk2gtBu3YAOuZYE7F+L8tRhEvr9ezSPXrJDF/6uA6NfED3vOh+Pfg0EY28kfqNdXz3hGX9EH03V7otA5/Afw+zQgJREI6AGM+0kb+1nAnOjvt51T+08Mbmw38zn/Sp6q8H7294Mqh5qzrdzeW35MGbUNaFpVPWed61WEu4ttLukFDQslQ/Jtj3luS2ig9v6KY6qTTjfrdGm5n12L+8zc26seNp28qrYBH27A1J51MbNvA5TLLru7OMPu8MBXdaH7x33aEJCKhaKCaRRcyMq0kPTH3ktq3MTHwwUzezdQ503uVgePLNyHH7adw4ze9bVvAr/zOD+/5ztg5zd63KGEkq9X3Jtvvonnn38egYGBSE1NRbNmzTLkdAuCIAiCYIVzW4EfRukOpSW+tTP+XLaCLmaZJ8x9HqDQNIndu3JVC7TgJk5OTqhZM5v51mPL0+f5hv0v/wU3YfyOxYyyYDsnQ6LVKaXN+ZFI51XK+8HK46qooly7Ujl3oOlwYO+P2gCqsIvuCzuAxZO4igM0vRkYM8dqXvKna04qqXOnuhXRq6HuitqLFjV98feDPXA5PE65u685cgWbT11TOeCcbeXm5eaMXo2qqAK8bxM/1fktKvZdCFPSX28PF3Sua1/n9doVPdHWvzz2ng/H3weCsPqI/aPCrNG9QWUse7gnXv8nEBtPXMWX60/h190X8fRNTdTsfkEW/AUK31s0pvTJm/+AXeFClcViVXxSCj5cpT+/ucDh66kNt9ntfmvpEYREJWDZoSCMbGN67F1maoO/dny/llzyvczj6emJDh0yRi4IQomDMzMrX9QZjP1fvjHjUhAEwVZCjgA/36EL7tqddaeABTU3FtKWTF6mP3cyd9+UA7PFeWHngK2fA72e1BLEwsqFZheRRU3HqUC7u+1zu+aiWzrduTIzcvHAqVBddNcvRBM1S7foFjV9cOhSJJYdCsZdXQKA5mOAvQuAWJPkvDCp2QFoPVarAIZ+oHPhM3H2agwW7bqg9p+0Y5c7MzXKl1XPBzdmVW8+eU0V4GuOhqh5bz5f3Hj3lFr3b1oV/Zv6oXFV70KLfSOGy3T/Jn65dm+3tdvNovur9SdxNToRnm7O6Fbfvgsd1mhU1Rvf39NJRZa98W8gzl2LxeOL9yuFw8s3N0M7/wooClJT09QCzImQKBy/Eo3ynq64tX0tuDrb+NwzG9wgOQHY+gXQ9YHC6Xwve0YvAFPdlEk98uO2c8rPoJqPByZ1S3+Mbi5O6j3AgvzbzWfTi26/Jnor4eSqcnjsscdsvu6HH36Yl8cjCMUPSmaWPgHsng/U7Q2kJkvRXVSwc8HMzFoWWb+C4Ggww5hKvFqd9Hyem2fW183q4MlXx0KZYbeZGdf7fgK6PQR0vR9wz3/hlZiYiE8++UTt08fFzc30eOIjgV/uBBIiAf+uwOC3Yfd8WmYMcxbYSrEkZGLhXcCl3XCr8gSAuiqjuyhgt5tFNyOaVNHN78zHj2nzssKArxd+R1MBQtOwEZ/r108WhetHq48rSXXfxlXQsU7FQnmInm4uqrvLjUXXocsRqhhkEX74cqSS6HOjFLt2xbIY1KyachFvH1ABLrYWY3mAc+YrTFFhg+wsLTcY1qq66jiz4Ca9GlZRxnOFARcv+Jz3alQZ8zefxWdrTyqDtTFfbsGYtjXx1E1NUM33RiVEQRTXjJI7ERKtlClxSRn9DpbsuYTP72wLP59cPpaFE4ATK7Sh4uivCzbajPexYxaQlgo0HKRN3iyi9z5fp422Hx3Y8Ib/752d/fG56bnfcz7M+oIHj7uLIpqtOBXde/fuzfDz7t27kZKSgsaNG6ufjx8/DmdnZ7RvLwfEQgli+yxdcBuZglbkaUIhwE7J3IF6/4XQop1hEoT8wNzXe5YD3tWyL7hzQ9sJujN8eQ+w/i1g5xygzzO6+8xOeR5JSkpSHi6EJqnmovuvB7T827sGcPv39n0/lg/QknoqASIuZOzmCNYJPa48AY5HuhV6XJglw1pWxzvLjmL7metqblcVDoVVcNNB/3c6IZti61hsZ6NKOxIUaTb1enyQPo4tbChtblWrvNoeG9gIwRHxWHP0CtYcCcHmk1dx4Xoc5m46o7YKnq6qA84CvGfDKijrZt9ilcUgO8DsRvZuVAUFgZ+3h+psc76aDGpeSK8NCzg/P713fYxuVxPvLz+Gxbsv4ve9l7D8cDDu79sAU3rUzfNCABdwLobFqmI6p+LawM3ZCfWqeCl1yoZjocrte9hnm/DFne3UyIPNdLoXOLkaOPALUN4f6Pc8Cow1r+mCm5FfFgU3mbXhlDl675Z2tW5cUy3nrkz1fttzUS1+ZCi6+fg3vA+0vkPH3ZXmonvdunUZOtne3t747rvvUKGCfsLCwsIwefJk9OxZBGYZglAQnFgNrHhW7zPrssnQ9FW4K4f1PI1QOFw2LfpVrCcFt+CY8l9Kwo0ubtVm9r19zstOW6vdzde8CoSdBf59DNj2FTDo9RsikmzFxcUFEydONO+b4QLkpT3A7d/ZX87OYqlifSD0CHD1pBTdOZEYC0RoN+DN4fogvX4Rdbo5t9umdnnsuxCOpQeDMKl73fQLo0NMHgV5XwTKkvgI4Oc7gXOb9IIN3f5rtsv2V/638rj6KudCAWeviwPstI7vHKA2ytD/O34VKwOD1Tx4WGySmkXm5uHqpApvFuAsxOmWnl9WmrrcPRtUhlcBmoxRYs6im54DnGMvKrgA8P5trZUi49W/D5vVBT/vOI/nhzZVLvZZSfs5s8xRjlOhMaqgVvsh0Th9NUb5A2RXXDes6o1GfuX0adVy8K/oaVYwnA6Nxn0/7lEGZOO+2YZnhzRRiwA2jRg0HAAM/wj4+yHgv/d0Vru9Rn4sOb9dG2eWcQL6v5ThImbSc4GIPDW4cZbKjMnd66iim58Rzw1tmq4w4OLhhW1AfDjQfnKJ63bn+V31v//9DytXrjQX3IT7b7zxBgYNGoTHH3/cXo9REIqGkKM6B5GreW3v0nMyhNEMf84EAv8CJv6l5zGFgocdPFIj+wMpwQZ4pLnne+2KzegRmnOVdujbUBDFgLrtZB2ndXYzMO7ngnNn5QEKY5rYfdg9D9jwrnYAZ3Gcx6KbqSTz55uUPpYEdAMe3JPlAlhSSqqSql6JTFAHqAlJKYhPTlX7etP77P4kcD85/XzmPf9cuwsq8qBRlEU5Y3J5Ty1bCefCyqqXAQ/ui4rhraqrovufAxZF969TtJnauIX5z3DPTFQw8OOtwJWDgJu3dijPoeDeez5MGXnRQ+vRgSYPgWIGZegs/Lglp6Ri59kwVYAz0ovzsnT/5sa/gdJ4SqfpOM6Fj7ywIjC4QFzLrUnM/zkYhFY1fVHes+gVa4yx+u2+bkr18PbSo0oGft+CPehSryKeHNwEqWlpurBmxzpUd635/GeV+kalAI0MLYvrhlXLIcCiuM6KelXKYcn93ZTj/Z/7LuONf4+oGfh3b21lm9t6+4laHfTf+zp60acG0GAA7Ab/6NWv6H0eF1fJqBD5ePUJ9RnOUYjsDPJa1PRFpzoVVVef899MDdC3OV6PSoUeBU6vA+r3Q0kiz0V3ZGQkrly5gubNm2c4PyQkBFFRUfZ4bIJQdMRcA366Xc8rMpZn2EfpK27swrBrlZIA/DxORyVU1nEIQgFyeZ8+tYc7cmlGfWm+DGzWc7pqBnjIe0Dz0SVuVdmm5+LUGt0NdvEAxi7Q5/P9vf5toMdjQNny+b8PdpyPLQWcC8mVmIVw5+lA63H6b+s6M/2yg78C10/rgxm+l3IzL80uBOO8/Jqm308Ws6GPLdqPv03S3bwwp+kMPHVryTfWsQv8v7CR7F0XCIOKoyqsOdmsiioWC7vOhSnXbpqIqQ43F7BZeNuz6L52CvhhNBB+DvDyA+76FajeOsdf+2Clzg+m/LWopPi5gcVa1/qV1PbS8GY4EhRlLsCZA045Pzc+7/XZTfXzVsZ2dSp5mk69UNXHPcuOKYtIzuKzgKeBW0HCLjpNzYoTfF5o6sVC8ev1pzDrv9PYdvq6ylbPCt+yruq1Q/+E+n5eap8Kk1oVPPOVHMDFlo/vaKMKV86/M4LvaHAkZk1ojwZ+3jnfQN/ngfALWma+aKI246zeCvmGPh70Nzq/RX9f9jGpQE2w22+YEj4zpEmO3fnJ3euoovunHefxQL8G+jOLhmxtxut5cY52StGtGT16tJKSs+PdpYvu9G3btg1PPvkkxowZk/9/riAUJeyuVGupi5Dbf8h4cMmD1DHfAN8NV8Y1WHALMHUN4FXwDpylGnbryOaPtbSJM7FC7khNBf59NN2jgPFUXBWnouPgYm065GXfmJhiK8flAcm2r4Gr+uAbTi5a/kqpNFfyt38NHPodGD0rf53p9e/o/FFK8W6ZU7gZpB4+QJ+nM57H//3ZjbqbwAMcGl3V76sPbrKbnaZ895dxQGQQcOcvQN1eWV6V8kIW3C5OZVSXjp1rHlBREst9d4ufPVwyXrbuWAi+2XjG7MIt2IApWu2KW4A6LSoTNYPqvmXRsU4F1ZmlfHRqz3pagcEM3qP/6tlreygYOHLEDnfsVaBCXWDC73r8KAc4K033cFfnMnh4gGncw4FgMdOsho/aHhnQCBeux6quPQtwFjGUPHPLDN9jLL65BVT2NO/XqeyJFYd0l7tDnYo66q2UwoL3sUGNcXvH2nh72VEluacMnfPWXMxIL7LLoZKXW4E5y/N27+5aB81r+OL+BXvU/3PE55vx3q2tlFlhDr8MjPgMiLwEBB8AEu30WUpzQtX8KAMMeFV30S34YMUxNdM+oKmfTaaEA5tVRc3yZdWCD1UGt3eonT6bzqL7+Aq9qFapPlDaO91ff/01nnjiCdx1113KaEXdmIsLpkyZgvfff9+ej1EQCh/GILDYjgmxXoTQ/IgyuTn99ezkT3cAE/+2nymScKN8MMrUNYsJNW1XZaEjt9DN16O8LgBv/gRodQew8UNg4/+0nKukv34jLwM7vtHS67gwfR7lqO0m6C96Yza55W36Cz/sDDB/GNDzMb2qn1v5+c65wIZ39D4ji5qNQJHD/zm798z5ZiF95C+9kaotgRkbMygeYmJidE53UiwuPewBr8q1gSqmTrcVtp66pg5WyYvDm2GiRVyMLSSnppmKblPRwP8Tu6RC1pgWjk6jRpHOc1vCwoBFN/OYVdFdu4s23ePnONUlTYbl/04YkcSCgp3t8b/a5C1AF2nO7RLOTbMr6ehQTj65e121hccmKjnymasxOHctBmeuxapTSqYp+z0aHKW2rOCMuEC1iKcyMqNqpzAj2zLDbvc/D/XAgz/txdbT1/DAT3ux51w4nh3aJPtYMTaK7vhRHysZPiJ5/c6kgoSGhCy6R3+l1Vu1OtwwrsHIOzb4Kcm3Vb0xoWuAMl6ct/ksbmtfSz/XVI7SEf3ESmDHbGDIuygplEnjKyof8Av51KlT6oXZoEEDeHkV3RxRXmXyvr6+iIiIgI+PD4o157cBNdsX3NxhcYDz0kXpSn1hp/4wsfVDlm7BcwZo0wfOUdLFV+Jt7M+xZcDPY/XBPuWt7Ozcudj+s4GlAX7ks0NkOfN4JVBLqo0oNsbu0PSrgu6clRhYcFMeZzhkd7lPS9nYEc5MQhSw/Blg74/6Z0qxx8yxfZTkyN/Aoru1pLb300Df51Cs4Jx50D7g1Frg1Drg4g6gfn9g/KL06/x6D2I8/VFu2Kvqx+gXq8BrxoosRzyCIuIw/NNNuBaTqCJ4/nd761wfsLLr0f2dtSjnnISDvo+jDLuYT5/Lv8y/JMNRkdPr8WbkEHxzoSbeGdMSYzv5F+lDComKR5e31iA1Ddj4VF89Z7z8WWDbl0CLW4Fb59rnjs5tAaq2sP4etuIz8NSvB7Bk7yWlqtjwVB/VxSwN8G9n4X32WozKJqdLuVGYXwiLUx1KPidrHu+txwGEYgVn+v+36ji+Wn9K/UwlCRcFchUrRlNKuprbcoxNVdzub4FVrwC9Hgd6PJrlVVn/jZ29TY03MGP8g9tyHu8w4CJRl7fXqAWhX+7tgi71TE2uk2uAH8foRfHHAm16fztCLZnvwD8W2a1atULr1q0druB2KP6YCXw7WJsflST4xg46oE+jQ4EvOgF7fiiax3JsuY6k+n2aPiC1Ba4g0hiJbqnsjPEgVrA/7t5A42HanZMLT4TSfsG2OayVL+iimrAIymwyRCdty+xzzlJ90RnY8pnt74XiBh835eF8XxpwxrnhYOCOBcBDe3XRndWXOV9zI7/QC2lUB3ChYlbPjLeXrVHdD7rgbjfxhtm3YgE7F1xg7P0UcM8y4OmzwFALlRpnAg/9hrLbP8TxB7zUVnb0x1kW3AnJKZjx4x5VcDer7oM3R7fMU4eouo+HOviPTnFFShmX9LxuIWu6PwxMWIKlUXpBiNLXoobFbOe6+gCahmqK5mPSF1E54pEXuCDIMRBLQz8bDsjpBD71u12q4Oa87Tu3tCw1BTdhV7RuZS/0beynOuKvjGiO7+7phPVP9sXR12/Cuif6YMOTfaTgLqawK/z0TU3UXLe3u4tSkQz9dBO2n75m2w2c3gB801dHPebUa2UziQqvfx8HEqP0wmw2v7P+eKgquGkgl1tTwvKebhhjihVjfJgZjjtRlTXiU8C15CwC5aroPn9eR1LYyqVLl3L7eISsMIxBOB+YUIJm3a4c0geyn7bWMhLKOfmh8NeDeu6r0B7HYeC3KTxa1tLy3HSr+aU/ZraeJzMKQsG+1OmhHWkZ2yZFd+4MAb+7WRfPfE/ZAr9cKT1OjtPF+twBQPAhOBQhR4BP2+hZdc5nGwcM7uV0J7fpcNvf481GAvdt0TPMVBlVzWgeahUWm3f8AAx+Cxj2oV0N6iiPZXeAnQ+7wkUGS2UDC5kRn8GpxS1oWDcADcc8B6e2d2b566/8FYj9F8KVuRAPDPOaIczcYsN5O9KrToaZZSFrYhKSlUqgOMx0GwxvXV2d/nPANBrERR5ffyApRktH8wK9CL7qBpzbavOvXI9JxLhvtmPD8VA11zzn7g7KNEvIWJDnqmsqFAl0lv/rwR5oUs0bV6MTcOec7fjmv9Oq25xjOkdiDHBgoX4PZXWd/z4AvuquzdJcvbTJ6oQ/svwO4/fRu6Zxoknd6qgZ7dwyyTSCRGNA+hMoeH88rqYXRAlS9+Zqprtjx44YMWIEpk2bhk6drDsPsrW+aNEifPLJJ5g+fToefNDGAz0he5hXRxdaFqVbv7jRHMdRObNBn1ZpYpqZdNMfCOzoM2eTc9UFLXFlh/2nsXo2rE5PPXuZ24NkOj9nXo0vLTLzuHD93Pnq1coCx+jSstPNL5rS5ridm1ms70fpeU/PSumRdznB55Pqjb0/ACte0B3e2b21k3evJ/Rcl63zlsZ1+WX+98NAw4E3vlcKgtWvaoM4z8pA0xFACsdW8mEO5FsTmPCn7rhavs7ZEbCcl6MkncUr4f11vT/bm+WB0uWIeITFJCI8NglhsYkIj0tCeEyiyuQNN/2szjddHhGXpF72NPF5sF8D3Nk5QHUY7A5N1pjxakPO6y87zqtsW750Ph3XNs+RRQacST58ORJBrrVREdv08yxk/fnLr9Lr+nOQec0V7JDZbA+GtKiOl/48rP6XlDKzsFPKCi5u1+ud+xtkBj39Jwjf3+ia469wIWLC3O04HRqD8p6u+HZSR7TzF48AwXHh++j3md3w/JJDSrnx5tIjOHApAh/d3jrrSDKqBG/+WC++M06MJqqMF7NsPP1+r26EkQamzG/K0bPhz/2XlEeAt4cLZvbJm+FZo6re6NGgsspu/2HbOZXbXVLJVdF95MgRvPXWW7jpppvg6uqKDh06oEaNGvDw8EBYWBgCAwNx+PBhdT7N1IYMyVsuqGDtP+UG9H9RZ71u+RTocA9QrorjP1XsqBE66NLkqfeTuqj6baouunmwzzlKfmAUBCwMFo4HIs5r11NKSfO7qsYuG2c5R311g9lEiUPNyD6pjadu+aZg7oPKDpopsdjhUT3n97g4E3ddm9hVNOXACulcPwN8P1LH6NC86O4/gSq5kH3xeWax1WCgnoGmW/x/7wGBf+rV5xpt9PVir+v4KWOj06jaPwXU7KDje9TtOelce8q9+V4vyFzwsHPAcZOzPR3u82MiYwk/nyyfQ8rMaaDYZSbQ/yVlNIZvb9IHK1Rk8PrZEBWfhEnzdmL3OZOhWy6hjPuVvwMxb8tZPDm4MYa1rF4ghj80Sp09e7bav/fee9V3vyXMY2ZhRZ4Y1Bi9G+X/e8kwAjuZWh1KVyCd7qyhM/6ql1Au4DbmyhSbLrexANCtfiVsPHEV/+y/jAf7N9SmhXkh+KAesyNcQGx1e46/cvxKFO6euwPBkfGo4euB76d0si1ySRAcwGX9w9tbo51/ebz2T6BKi2CO91ujW2T9PcDvdI4N8bv8n0cBn5rpx9ZM7+DnbNmKwE3v6PdXDt8nHCn6YIVWId3Xp36+Mtcnd6+jim4u4D4yoKH6+0oiufqrKlasiA8++ABvvPEGli5dio0bN+Ls2bOIi4tD5cqVMX78eAwePBgtWrQouEdcmmk2Gqjxme48bXgXGPYBHBp2v2iCQizjZxr0B6b/pwvXy3uABbcCt82zf4eM7SJ23y5sB9x9gTsXZVsMhETGK+lj5ZziNLgSzw8vHpBPXWVThInDQdfjH8aYohzSgPO2S/1yDZ1u+VpgsTbxL91BZEHHnHQa2AkZoSkac2ujg/Vrj9KwvKpFfKprB1QW2yy+WUwbi1J8/3zSBkiIsP67LL4NWHRzNswoErIxZck3u741ddL62K/gtsbFXfp+tn2hTKzU3BlVBex28+/LZlGUByvTf9itCm7GarE4YReOBy0VeFrWDeW9XFHB9LNvWX1awXQ9Hlz9vucSPl59Qhki0dH2m1qn8cyQpirH154kJibigQe0SmLSpEkZiu5r0QmY+eNuJKakKtfj+3rbJ9rFkJfvj/PDSO5IpzvHjO5LKeWLzTy3JTe3qqGL7gNBuujO65jML3fqha16fXVcUQ7sOnsd98zficj4ZDT0K6fml8UgTChJsLie0LWOGguY8eNupTaqXbEsZvbJxuyThp7h53VkJuNup2/UGd5VGgO3zgP8u9icCvPjtvNKScL898nd8tf86NvYDwGVPNX3Gb/b7upSwkxcTeRpKYGdbWZxSx53IcPOycDX9IwmI29oAuTI+XWUB1OWTOkru5eWlK+tu1R0D2Y3nK669oZyGmYTl3EGbp+f7QE6uzljZ2+Fi5MTFk7vorITs2T4x7roZqd+wW3AlFUF29krCnbOAS7t0pFqLKgo9eMKKv9vBZXPXbGuiqXg/6Dl5KUiK8/KPIzKDRbcfs2VuRK88xkBw9Xu5qP0wphyCm6efj4/f6KCgIr1teKAP7PQN362vI2RXwJ/zgR2zAG6PqiNvOwNfSAMs8mO01Cg9Hte+wv8eT8Qcjhdkk1vh2wKbs7APb5oP7acugYvN2csnN4VLWpm83mSBTwoGd22Jr7ZeBqz/zuN/RcjMO6bbejbuAqeHtIETarZx+3V2dkZt956q3nfgDPlD/68V8nj61X2Uk7lXJS0B0ane0tExfQFHC7SlqDZPrthUgEcSaqmTpklXNxmUJ//4yCOXYnCiStRaFjVWxfRnC2lMz1VIjl9pv06SRcKzJG/9dscPztWB17B/T/tQUJyqopcmjuxQ766cIJQnOF77OXhzZTy6b3lx9RcdZaeBUaGN6P7zm5KN1gl9Dqxkcj4JHy+Vo/9MCs+rx4eBvzumNi1juraz99yFuM7+xdpVFtBUQCDYEKBwgNfSj5V3mWwYz/ZdFMknKO2JsVkR5MzJdPWpruTsrtGCas9qNZCy26ZV0ynxCy4GBarXE8ZaRCdkKxWzy+bDGusQrMmds05M8MZ0J/HFa4pXEFD19mtX+r9fi+mm/xRMVAQUNlBJXPl1qqo4BablFIw9+Xo8GB0zDe6yzvpn/wX3JZw4Sjzl/KUlcDjR4HJ/wIjP9cdXhqP8b1FQ0JLWtyiZ6wjL2q5ekFwbpMeO/CpBTS6CQVO45uAmVt1XGC5asC4XwC/ptnOcL/+b6Dq+rk6l8HXE9rnqeA28HJ3UQc8G57siwldAlTXfN2xUAz5ZCOeWLw/+8+pXCyyL168WG3cN2DWMRcOPN2ctaOuh6tdZxZ5vHUszgeJ9QYAHSZnPDgU0r8PTRndO6J1d6pBMet0+3q6omfDKhldzLlQt+JZYMvnOl0hO7Z+rhfeaeo09uccF7AX7bqA6T/uVgV3vyZ++HFKZym4hRLPpO51MbWHXujmZ/+WU1dzzvDmdzKbQ3mA5m30HaEqifna9uC2DrWUiutkSLSSmpdEpOh2RBhj8+AuoE53lAgTtZwMVdg9Mtj+NfBlF2D3/JxjDzLD69N0hnPAxu/SFTubGTPOXU6Zv0u5RNItslHVcrgSmYDJ8yhbS8r6vryrAeMXa9n6hW06eqGkwE4iOxTMOWYEjL/JzKYgJOaMkrusY9iOOtU3L3zQmMe8AEDTutIO5f4G9BGgpLww1BW56Ty6emgvCuN9XBBwnvqBXcDIzwqmk26Ncn7A2AV68YFJBtnAjvQ8UywKs0yNYiS/VPF2x+ujWmDVY70xtGU19fH26+6L6PvBery97IgyX7Mn/x4Iwqz/Tpv/DtW9tCPsmrBbkwYn7O/1jY4yK+Y5rUVCTKh676ehDLaEm+TlxWim22B4q3QXc+WyTLVM5UZ6ROjY0ux/udM0/T0zZpaONswC3u6X60+qHG5mTjMvOD8u+oLgaNCAjJ//SSlpanyJngbZHlffMgfofG+u74ejlnM2nlH7Tw1ukrV5Wy7x9nBV71tifE+WNKTodkTYvcqPE29xgbMlPR+3XTrOL2sWdnQi5iz2nw+kdz9YeFnmCVOSzKggujHOHw582g54qwbwbgAw/2YgVHcHssOQT1IW5+ftrlxP503upPZ53n2cZUzOJraHHS/GBpH9PwGRplV+RyY5URv5kR6P6MLGKLpzEeFiM5SVcmbYxQPbo/3MZzOaCPOGAW/XAkICUarhvPUnrdNl+KS4yrJYdNOwhe9j02KK3eGYSDbKlexgXAkNaeIS87CQk8Nz/vuei3jbFK3ywrCmBRJZxA7xl+PbY8nMbuhUt6Lq9s3acBq93lunOhPxdlCI8EDuyV91d2R673oY2lIXVPbGKB5PhZSgiEx7Y/oeS/bxV7nmjMPKS2RPQTOwWVXlsH8qNEY5HeuRFVNmN80Vs4OKGXq6NL0525GN1/85oqS1ZEbv+nj/1lYqCksQSguUaH94ext0CKiAqPhk1RxigWxvPl17AnFJKWjrXx6Dm9tRTQdgYrc66uNh7dEQlXhQ0ih2n0hffvkl6tatq2Rs7du3V2ZtWfH7779j4MCBqFKlCnx8fNC1a1esWLECpQYWmez40sTHEWGXmfNctpo88Z1463yg/8t6jnjfj7qY/rAZ8HoV4KzJCZ2wENv0kZ4bO7tRG0DRhIUkRAKbPsyxU/76P4FYf8yU6zmxgzJh4QENi2/OYm4+eQ3P/n4w+3xEdvFpAMYDBuP+HRk+n5GXtJS2tSmzl8YbxnNOl/ECkJajWkvsv5z+/HF+VY0kpKVkLDZLG1zI4eITn/f9P9v8aywqH124D6O+2Iytp66h0KAxGw0Ra3XSi2f2drnPA3z/8jmY/sMu9H5/nVpoG/7ZRhy6lIVBXB5YfyxEdeDItJ51MbVnwZortvWvgIX3dlGzrFTnsNPNWJn+/9uAORtPq9naHHNdTcTGxqJmzZpqC74eoToosYkp6N6gEp4c1LjA/gZz0R0arSXIdKUvCC7sAA79BofEJC0P99Ky0nqVy9ltrt6esIPVx+Rqb87sZv4uObX2xu8Njs5xhMmG1ygXvh9dtA/fbj5jXtB6ZkiTEjkPKgg54eHqjG/u7qAWYGlyNnn+TqUOtBfLDwXj5x2M6wOeucn+77O6lb2UqRr5bsvZ0l10R0VF4YknnkCTJk2UW3n9+vUxdOhQvPnmmzh6VK/g54eFCxfikUcewfPPP4+9e/eiZ8+eKnbs/PnzVq//33//qaKbTuq7d+9G3759cfPNN6vfLRWw48iO7/JnS4/EloVWz8e0QRTnQ2kGwSKQxRdziQ2qtQI6z9Aup5xxnfgP8OAe4Lkg4JlzOvYomw+L+ZvP4Lut+iDv4zvaoFUtLd0jnMH8fHw7ODuVwW97LuKTNTlkyFLqyygyRza9I3yNcSGDdHtAy4UNeS0jXJgBSVM6e0L3elKjLQ5cDM/Y6aaJlWHIV1pZ8ZxeROJzwZgPG2Am9Pg521S+Jw0COSP/2KJ9yom6UBjxuXb1r93JfrfJ6LL/NQEWTwISbVsdZ9d34c7zav6Zz8GKw1eQmgY1U8aOHBckvlh3UklV8wNfqzMX7EFyahpGtqmBZ4cUTgYpD4b6N62KZQ/3wnu3tEI1Hw91EPbGv0cw8KP/0PXttWr27899l9T4TLZZ4pcvq+3pXw+o7gMXHz8d29ZussLsHMx9z64A3qkN/D6tYMZX5g7UUZxGfKUjUaUp0GEKAr27Fct5bkuGt65hnutWCz50S6bZY2oScOSfTDGeE/TMN9Vq2RCTkIyp3+/Cn/suKz8DflcX9IKWIBR3mHIxf3JHVPJyU6N49/P7JyUbVaYNhETFK3UnXdL5ncgOd+d69k3KsIwPI4t3XVAjniWJMmm2LnczAXL0aFXQTp8+XXWXuQL+1FNPqeKbRffw4cPx1VdfqezuvNC5c2e0a9dO3YZB06ZNMWrUKLz99ts23Ubz5s1xxx134KWXcnDENBEZGQlfX19ERESobrlDwQPNT9voeU46A7cdD4dh86daBkrDJ9eyarWa8rNc//0Xd+ri26eGLv6c8l/0rTsaginf7VQH4Fwxp1TNGj9tP4/nlhw0zzUasyglFn5U8MB0x2xg9CxtGFfQUMVxYhXCa/RAmwWpap3E+MQ6dEciyv05CajaErhvE0odJ1cDP96iVR/3rk83tMsGFl13z92uikrfsq7o38QPS/ZdUs8po6ieHdIEt7WvXSy7Zdmy+ROVVawW2xg3mM2CWlBEHH7Yek7Fq9AIhpR1dcaYdjUxqVsdFQnI9/WyQ9qosmOdCkqyV7uiZ64fFgvUW7/aojK1ezSorFQyuf6csxNUN/yy87yS7W0/c/2G0Zim1X3Qq2Fl9GhYGR3rVFQdE5KSkoKDBw/i5+3n8MupMnB3c8WvM7pmWIgsCKg+4GJIv/JX8G38o4BHeeDps/YdnQg5CnzZWe93ulfPjjsgXDzhDP+jAxrh4QEFGJOXD1ggt39jlfLl+PuBHmhZyxf4731g7Rt6HIQL6SrG8yHtG8KZ02nrslys5uv5zjnbsPd8uDLz++qu9nbJiBeEkoKRusP33NiOtfH2mJa57kyzRFy86yLe+DdQxe+x2TS9Vz081L+h+TvC3qSlpamFYRqqvTS8Ge4xGcQVZ2ytJXP17b9y5Ur88ccfePbZZzF16lQ89NBDKrPz77//xpkzZ1CtWjV07NhR7eclC5Td6kGDBmU4nz9v2WLKcs6B1NRU1Y1nnnhJgh0omuFQ9pgBGiVxJpqse9Nx3F1ZLPMA+eexytiMcsfmLy/HhyuP5a6rxL+/0WCgVnstW7VDwX0kKBIP/LRHFdy3d6ilPlyy4s7O/pjZRx8QPPPbAWw6kYPbIrNmD/8Bh4Uf1pTL0zSqMApuwkWZwW9ir2t7s+SU8iNyAPXTZe02djdLDHyvG+Z8ne+zqeA+FhyFMV9uVgV3dV8PLJ7RFR/e0Qa/39dNFVzhsUl4+reDuGP21uwNWOz5OUAJKX0C8qvA2Dk33XTJykEFv8SZ28sYoR7vrsOX60+pgpsd2+eGNsG2Z/vjzdEtlSEYuwRfjm+nFtI4RrLzbJjqhnMmOxdr1KozcPe321XB3aKmj3IqL6qCm9BQanL3uvhhSmcceHkQfpjSSX2+NavuY/7soznahLk70PrVlZgwdztmbTiFo1eiEeZRA4vOuqCMkzPeGNmiwAtuUt9Pv8+3RZRXRmGIDwdi7TwKYZm4cHRp7s05iwk8OC3unW467fdvUjWjxJxz3c7ugFs5rTpgFCULbi4k3vJtlgU334dP/3ZAFdxcLPxpWhcpuAUhE21ql8dn49qBa+i/7Lygvvdyw/lrsbhr7nY89dsBVXDze+yvB7rjqZuaFFjBTbgwwAVw8t3Ws/lWmxUncnUEULVqVcTEWD+49ff3x6xZs3D//ffj4YcfzvUDuXr1qlpR531kvs/gYNuisf73v/+px3f77bdneZ2EhAS1ImG5FXc4j0ETHBr88MAoA52m63gcSqzZgbTnATG/BAsCZgMiDajcWBXLv+25pNwWP117UsVxhcfaedYzFwfJU+bvRExiCrrWq4Q3RuW8KvjEoMYY0bqGko5SenM0OIvXE2MZPu+gM33zOHtapOR0MMrLgw8BO77R8kA7c4Az3ABa1fJFa3ZIAOy6Xhbwrq5HC4L0vGyp4b8PtAu/T02g77M5Xn3Hmeu47estynm/oV85/HZfNzQyOU5z/vfvB7rj+aFNVceIRebQTzbi3eVH82YoZgt8vcwZoCWkh5fk77bY8Q8/pzuhLXSetEFCcgp+230RIz7fjFu/3qpct/kF3qVeRXx9V3v891Rf3Nurvoo1soTveypXKM1mzi8/gx9btB8P/LzXps8nXp8mNheux8G/oifmTeqkZOvFBR4w0Tn92aFNsfThntj1wgB8MraN+pspQ6cB28YTV5Xx27BPN6m5QP7LuNB4e8fahfIYq5Rzh7eHC2LT3JHsXSt94dLe89yWHiMJhbDYZC/4OXtpD9ISovTcu8VCRXEl3cXcJDFnUf3UaW04SnPF5c/oK9K3peGAbFMA/tqvJeWz7mqvigtBEKybGL4york55nHJ3os5Pk2UorPmGPTxBuVd5O7ipFRwf8zsjuY18h5xmRuoPPPxcMG5a7HKE6VUFt0spu+55x7s3591rtv48eOxdu3aPD+gzEUOP5htkUP8/PPPeOWVV9RcuJ9fustxZihTpwTA2GrXLpwDiPwQUMkLQ0wOsfyyyQDnavs9r/c3/k8Xy/ntGq15HXivHvDPIyjoqLDrMYnmhQS+sTccD8XNn2+yq4mRLbC4mPbdLlyOiFezhDwgt6UrRRnu+7e1Uk7BUaYD7eAIK26RlL1WrA8kRmu3aUeCB0cLbtXzdZleX/zfcf6d7rH4YRSw9Il087P8cuWwlrPHR5jnuVvV9EVr0wFWqZ3r5v/D8C8Y8i7gnn1c04rDwWq1mivVLCDZ4aYpoCWczZ3Wq56KnOKXNBeRvlp/CgM/2qDGLewOP9PbjNP727/KX4eRCz2k7V2Am5aAUzr98erj6P7OWjy+eD8OXopQny93dKiNpQ/1xC/3dsVNLaopqVx2+FfyVIZkTwxqpA7wWbTf9PFGbM4mQ5T3PeOH3WqWjjN139/TSUV6FWcoqaebOrv7W5/th9WP9cLLNzdTOcdlndMQfXA1Kl3aguduKjzpMr/3DTO1cE+T2ebV4/a9EyZM1O4MjP9VR1I5UiwZFT7f9EXaJ22UUzFfynUqFe+iu28TP6Ue4ZjLXn5+E6qmwi8Ai+4GUpP1wln3rBs3PEbggiDha7Sg5koFoaRwd9c6uNek2qSh55Zsvr94TDfmqy3KeJOydDagVjzSC9N71y9QD4/MeLq5YFwn/xIXH5brovuWW25RruI33XQTvv76ayXptiyKWfzSZC238HecnZ1v6GqHhITc0P3ODAvtKVOmYNGiRRgwIOvVUUJpPDX3xnbhgnbhK+7M6KVlVlzdvRiWyQW71R3akISz3XTlzg8smjZ+oDvR+3/Rudb2xjCsqdsb209ruSC7b0tmdlddIXaHbvlqi5pRKwxYMD6+eJ9yxKZU7duJHW/ofGWHu4szZk9or4r1oIh4626RfI8YM/d7f4RDQWUCu4mUAqekm1okpaRi6ne78MrfgVgeeCXdxdxeed27vgW+uxlpG97DAdMiTMta5c3S1v0Xw5HWYKA+SKMpT3GiIGWqfC2N/krPcTcZnu1V6TtgRNsNaOqHH6d0RnlPtyyvT7k1nU/5eq7h64GLYdr9dOaC3dYXk3Ixz0nH7NhEi/dF+8laWspFGsuOY24j5fjaJEYGOCNN1pzAx6tP4Gp0ourcPjm4MbY+2x/v3toKzWrkrrDigcYD/RoqdUC9yl4IjozH+Dnb8cY/gTdEcPGzhPO1m05eVaqBeZM7oo5pHMJR4Pd5Az9vJUXnDPqWp3rj2tKPsefHt1CmkA07jaL7kkvtgim6aQg5ZSXQcCAcDlPXP6qcPpim50BBSj7tAR/fgGYmifn+oIyGmTx+4eL0iM+ynNs/ezUGD5rGvzijelcXG5NPBKGUQ6fxYS2r6wzvH3ercTNL+F32wYpjuPmzTUpZSJXRO2Na4qdpnYvsO2xC1wC1mMjv00IZeSsEcr1s8dZbb2Hr1q2qS/z4448jLi4OLVq0UDFflSpVwuuvv47338+9GYmbm5sq5letWpXhfP7crZt25rQGi/xJkybhp59+wrBhw3K8H3d3dzXkbrk5AjQdYUQLpZFzN2Wamecs84BXgIDuQLNR+bsjytW9/HQkVEqC/buy7NDxwIkzW3W6Y4sprqhb/UrqYJgGK30bV1HyRh68vvDHQSURLUg+WHkMSw8Gw9W5DGZP6JCnDxgWMt9N7oTK5dzUSiHdIlmUZqD1OP13n98CXMvdbE2RQgUFaTdBZ8SbYNePHQuiFk+MvO7z2+xzv6aOeUSFlgiNSlBdSc6fNq/ho7qOLKguN7gDuHVu8Tpo5mIVlSKUgBckNdpmeXBKhdAnq08oQzAeoLLDS/UG53ptYVDzaqrrzXgrPu98fwz4cAPmbT5jdb6K98f/0e5z19XsM7vMjy3cpxbPOryxGs1fXqGMUcbN3pY+F+1VGWh1W3q3Oy/smqcXCBsMMM9/8vPipx068YKS+Y1P98X9fRugolfWiw22QIXFPw/1wPjOevV9zqYzyuHccqTkraVHzLJXGjsVxuxzQVPW3VWllHDjwnhhYjiYn0ipXjDyckv4uuSYCruuDpTRfcVNL0g0MC1QFHeGt9JGu0sPBmmFFGk2Epj0j/YLMalVMsOF7Gnf71KKnXb+5fHqyOYSCyYINkJV5v9ub22R4b0DV0wZ3jvPXsewTzfi83UnlcrtpubVsOax3hjbyb9I32O1KnhiULNqJarbnachM5qlsbtM87M9e/bg+PHjajaa3ep+/fplK+/OjsceewwTJkxAhw4dVOb27NmzVVzYjBkzzF3qS5cu4fvvvzcX3HfffTc++eQTdOnSxdwlL1u2rFoUKGlM71VfzVf8suMCHurXUBn+mGHRwS23bxA1i3sg3YjJrwnwyAFg+yxg9cu6gGg/0f5dbt5f2QrYelrP4natryVi7DDPndgRn649oaK4ftx2HocuReKru9qhum9GSaw9YCSBYS7xzhgtE88r7DTwsY+dvU1J4F768xDeGm0xF06H9fr9gZOrgH0LdEZ5cYey7dPrdBRYt4fMZ7Nw+npD+sIB54DRweh0b9N+AIx3yys01wrWzvAH09jJCVUzyEbR2Liat5LvUmLO7myx4fQGPbdPmeTa1wEXd6Dbg/a57Zhr2oCQ4yR8LWUBi2K+9hZs14Xng/0a4LGBjXL95Unjo+eHNcPotrVU8U4n1Ff/DsTvey6p2V8uuJy7FqNmri5cj1VeCDlBNQldqbs1qJxuAkflR+BfQMQlwLdmrh6jig/0rqY7ZCaWHQxWYys0i2P0iD0lcZS80XCNsmvK9I4GR2HEZ5vx1E2N1fPOQpy8d2urEmPs5OHhgX///bdI7tvodG+Or4PbqIywZ8zc9TOAZ6V0STmNCXfNBXo8Bgx4GcUeU9f/dFqNYm+iZkmvRpVVF42KkV3nwtK/cw2llBVYnD+6cB9OhESjqo+7WkCkwkwQhNxneN/y9RacDo1R45AcOfthm47H5RjUayOam8dZiwPTetVTi6/sepcE8nU0wu40i10Wvg888ADGjh2b54KbMOrr448/xmuvvYY2bdqoHG5mcAcE6Cc7KCgoQ2Y3jduSk5OVeVv16tXNW16M3ByBng0rq05fXFKK+U1ihgfUlgfVtshbaej12xRgdl/g7Ob0813LAq1oRldGd2V5cGIvjHnfur0REhmvXFf5sDvXrZRhRe6RAY2UzJtGCjzYp+SFB+v2ZNvpa+bILxYmt9gh8ovdsE/HtVWSmJ93WHGL5Nwp2feTY2SrbzSNK/D1UCH9Q4+LCiw4PFz1Rwi7fZEVmgGuXtpl+KruwuSZkMNASqIyx9oe5mOe5zYwz3Vz1psFfuhxXbQVJezCLZqgC26aBJKVL2g3Xnuw+iVg3486izoLKBGjFJwFN99Xr41sjscHNc7XajUVKHQ4f2NUC3WwzPnol/86rPwlmG3N1wELbt4FJek0KWNnnZLuz+9sq9Qr+18ehLtNX5rztlisWFdrAdTpqc3w6FycW8pWALreD9TtaT7L+Gy8s5N/gc2gMf96+SO9VORaYkqqyr6m6Rih4cyYdiU8PrCQaGAyBlsdVg1pwz8C2txpvxv/60Hg3QDg0O/65wCToi7wD8dwMTd1/Q8kVMuwQFHcYbFsdK/MLuY5wAX4VYFXlM/KrAkd4OfjUcCPUhBKcIb3JK3KDAyKNH9f8jt79aO9i1XBTbgoQLf0gmi6FQVFl1+SBTNnzsTZs2eVyzgjxHr16mW+bP78+Vi/fr35Z+6z45Z54/VKIjxwnt5bz2/N33LWurNwXBiw4nlgoam4ywoWKd/0Aw79pov1ayczXs5OGuOhKtTVzuj24qZ3gAd2Ax2nYqtpnrtpNZ+MXXsL05V/Huyp4owoJaYZ1Oz/TuUqticrTodGY/oPu9V8Cx1VmW9aUG6Rf+6zeP4aD9GFQlJswUol7ZVhe/QfvfjS49EMF83aoA397uocoObwqRLcezEaqNVBX+GcbTF/OS7O1GiLA5e1fFfluppoY8x104yHua5fdAT2/oAiZdNHei6xViedFU0zIDdvoGLWsXM2w+fT8AIY+LrVq0TEJeHuuTtUIezm7IQv7mynDFTsARfCOD+55vHemNAlQBWbjPSgkdG3kzpg9WO9ceS1m7Dl2f7KpIyz05R0U0rK/xszwY3HsvrIFdUZN9N5BuDkYpfYt8OXI7D7XJiSd9/RqWBNMtkVmDOxA94c3cK8+HRP97pmwxoh//hX9FLjDZQWh0TZMRUhJVmreNJStZkaYfwkPQboE0ATx+IMH7/pO3trhF6wru8gnW4yvLU+sOfYSk5xQMsPBamim1A5Jk7lgpA/aBA619TUCqjkiZ+mdlbf2bnxMhLyRvHJMBFsgkYILORocPTr7guYkPmgmu7S27/W3TZKueumL1qY4co+V/nppM3Z7dvmAwGmeVxLbp2nC0R7znTwtio3ULtbTx0wz3Nn9+HALtvzSw7i972X8NbSo9h/IUJ9QOQ1gicsJhFTvtulipS2/uWVYy+LCnvCAoOFxTcbz+DJxQdQ1YcdwEpabnz3n7oTSuf54szmj/Vp05szGJWx0OWCCQube3rUxfXYRJy/HoudZ66jN+e66U5PiXnHKXm/70t71ElajXY4uMXkXG5RdLeqrfcPXoxAaquWevWwqB3Mh3+s55S7Pqj/twNe1eZeFfJZ+FJq/49p0aPdRMC/8w1XocnZpHk7VNfZ290Fs+5uj271c29omRN+3h54fVSLPP0u5a+9GlXBf8dD8f3Ws0q6bl6IeuSQig+0mQs7dbxQ15lAi1vMZ3MchdCZnI+1MBZCx3cOQK+GVXAiJAp9GvmVuDnT2NhYtG6tx4+YXOLpaX3mtiBgZzOgoidOX43BmcshqBoTpiXhvvlUElw5pBc+3X3TVSlMAaA3wLF/gSN/aRVGcYURealJSHMpi31R5Rxqppt0r19ZLcRdjU5QfiDmcZNM0OyJUX2EoyIcaxEEIf9QLbjj+QFqgd7ex7+CA3W6hexR0T49dSdl9sbTKk8vAzQTMlx8Of9pmbVN5+nlzwK/TtYFN2WdMzZaL7iJZ0X7FtyZMDrdxjx3VnCOlwYQr49srszO/j0YpAyMKE3PTmbL7FLKoH/cdg7vLDuK+3/ag5FfbEafD9bjzNUYNQtM47SCcnx9dkhTDG1ZTclPaQpnNo3hPHtxL7hJn2eVIkHNzVpgxNaNaFNDRU91rFPRbMahZOgTlgDD8+mif3mfOrnm2wxhsUnq/845boOGft7KHZqy5ouepk6V6lwVsizU8v5c3ICBrwHlTLO8fO9YFtxXAvOmANj6GRB6FPCsrA0TM8HXOQ3LWHCz+7pwetcCKbjtweRu+vn4ZecF5WhuNoLMTcFNdn4DXNoFnFid7tEYn4Q/9mpVCbvxhQn9HPo1qVoiD16oLDp58qTa7KEyyi31TMVklf+eA2b1Avb/nP8bNdzyqcyx9J6goRcp7rGOXCAY9CautJyBNDipyDdH6lJxMYVmTeTvAxYu5haExyYq47TYxBS1ME9TREEQ7AePfUvid1ZxRjrdDsjtHWoruRWjtZYdCsbNrTOZKvV6Ss8MU6IbuCS9E8QDiW1f6n3Khfu+ADjb8BJITtAH/YbZWl75+xEg9pq670teTZUBE6WDtpiXsXvErn6zGr5qZpUFNwvvZ4Y0UQUZnwtGqV0Ii1Md5pykiJxnYRxOQebnKrfI29pgw7FVSpmw72I42vlXSL8CD2BjQoFyefdBKFA4wz3M5FxuEdmy7FCQ2diPdKyj/ybO3if6doabyUU6X4z8TBXRe9OaUFutRgwsjXP4umlRwxc7zl7Hzria8Hdy1a8tdoDy21nODYzoo8HZoNd18ZgVIUeAeUP0HP/Ev4Ca7Wy7ffopbHhP7w9+Uy+EWUCnbubL09SsbmUvlQnNArC4QnOxOpU8cfZaLJbsvXRj5A+fJ2JIfq0RHQocXqL3O001n71kzyXld9Goarl8GSIKNxqpbdq0ybxf2NT388LqI8AZ1IT6ZLHHWM5FU9Fdu7OSrnORloUrGt8E8LOE33ccr6GxaHGE3xndHsCWPReBrftR3+Ty7khQYr5w1wUlH6f3hKuF/wKbCQ/+vFcpqGpVKIvP72xXqBnBgiAIBYF8ijkg7PxONMnK6SB9Q/eBnTbOk5I1r2l5KmHxTXnq2J90x8yWgvvqSeCDRiovGUl5z+lVHXcW/ZTtpSSaTdFa1PSFt4drrkwV/n6whzqo5sHSC38cwtO/HVRRB3/su6zmOY2Cm53QxlW9VT4x509fGNZUuZ7++1APbHyqX4bOaUH+r2i6RJYdtMwl3Qt81g74YQyKHdl0s77ZeFrNb9O92Xj+aOBTwdNVxbwduqzztO0Sh9VxKnZd04VsSwsTNYPWJon5vqA4oFrLDLL0QuHwH/r9te0L4ETGqMMb4EIAH2NiFPDjLfqA3hYYO5Ycr1Upre644eKv159W0lsuHi2e0bVYF9zGQpQx201figyfXdu+Br7sAqyxPrNuZu/32mSvRjugZnt1Fm/HMIRhIV/SJN5FCWPCunfvrrbCjgwj9SvrTvehBD/7ZXVf2K5Pa3fEhLnb0ff99bjM+EMPX6B+P30ZZeYFwfEVWvViBwy1l6M4l1vStV4lVPJyU0qmzCap7y4/io0nrqKsyW05v3F/giAIxQEpuh0UOgHzC4mxSQyOv4EuM3XedthZYOvn+jweiI74FGiSc565GZpAuZXTBlHHl+dvhi7uur6tmu3NX7LZzXNnBWc1F0ztjAf6NlAdUHbP7urir7reNI/68/7u2PPiQBx+dTBWPNoLcyZ2VMZmU3vWU7OezWv42pxXbA+Gtkw3jTEXGeUDgIiLwJWDQJCeWSs2rHoR+GX8DQeGzGFevPui2p9uYRbFAqeDSWK+ixJzmhCtfBHY+kW+HwpntjPPc1t1MDcVX4U21837WTI93QiMHbLsYCLAuJ/14+T74PuRtqUCDHlXR7UN+/CGUQ+OSHyxXpspvTi8me7UOQC3dqgFLzdnVTAwAtGMudhZmvVzQ6WAyuZml3ua+extp6+r2+NC2+i2uYwdE4o17HST7ZGmkQl2uvMjc48MAsI5+18Gob4tsfd8OKISkvGvIXPu+bgekbGISLQbp9YCP90OzLtJKzbyczvBh3A2JMyhnMstYeea38eZXcw5IkIvFEK/FX7HC4IglASk6HZQ6PZ9R8faGZykM+BeDujzTPr8Wl4PUjjvpuLDWN38kufHq8y1SEA3pDm5YOupq+bV7rxAKdoTgxtj2cM98d09nfDGqJaY0bs+hrWqrooxrowXl25Xn8ZVVJFBCTBzihWUCTcZrvcNV+riAI34dn6rXcszudZ/t+UsEpNTlXtsZvmuITFXed101d3yqR5xyAt8PnbPR2r4JRVPRVrW1AW2Ja1NDuZHgiKRVL1t4XW6wy8AP4/THeiGg4DBb9k+hzn+V8CvGRAdDPwwShcA2f5OOS1dr5LRXZ+LN8zi5v+DUYI3typeMR/Z4ePhajZEmr/Forjm38gce6QBO76x/stc+Iu4oA0em482n03fBsKCOzfKGSFnGMu5ePFitXG/sKln6nTviiqPtDLO2o8kKjjvN0g/jaEfKDXY7uD0BJClprEZZVTIBSBnO7+O+B28/h29z0VsLm7m9XYWTQK+7o6E4OMO2+kmTDcgyw8Fq88yLrI+/Zs2WL2/r/4+FwRBKClI0e3ATOlRV822stNtdAQzQCk544WMojmvtB6rT0+uyvvq/GlT0V23t5rTuhwRr2axO5iKtZJuVtHPJDFfaikxbztenx5YlD/pvj3ZPgtIigGqtdJOviZoekXHacLFjcwLGpad7rTaJndtdrzjtPN4rtj8CfD3w7hyYhei4pPh7uKk5nQzw1k/Lq4w9u2ERyug15O6S1WQJEQBP48Foq8Afs2BW7/NfpY7M1xsYReNUXxUobDw5kJHZs5vz2iCmAmaD1F+SUOi10e2KDYLTLZyt8lQbc3REJy/ZhEf1uU+fcr4Nz7XmTGK8bYTtHqAL7PIeKw4rIuwG2bEhXzD+M7bb79dbdwvigVmypCT4IJEb//8S8y5YEOVxMBXsee87hQTdryVxLyg4GO+uBNwplS6jDaEY8JIbuFnT0IE0so4YWt4eYeLC7OEi7ccjYmMT8Yf+y7h3h92qTElji89PjA9MUMQBKEkIEW3A8P5TaPDNeu/UzdegTPb3R8CWozJlQs5Yzpun7UVv5qkxCouivOTjCFjrndu4Uy54dpcrze2mKTl7Jh6upUOL79hLbWMjhJGs8S8Xl/ApyYQH64ltUUNixzGzREWrxavGbpN88CoXmUvlUOeGZqasTjmfN6puHKmbOo0fZCZG+IjzUZJ+1LrqtPmNXysmuiw0DRk5zvDvYF+LwAN0xcK7A7/b79N06MSHN24c6HuXucW72o6Ns67hnYkZ0a1JZz3p/yUW6JFQWqCUXev/a2l/xyxqFPZ8UyUKIflWAifUmMxR1/QH6jUAEiIBPZZcalmMgNjEC3i6H7ZcQHJqWlKbSFSVPvj5OSE3r17q437RYEhn77uWcd+c92A8gAhjD80Oq6KqCvA8ue0osVe8Hv0gV3AyC/TE0b+eUwbleYG09+e5OOP2FQXNVJRw9cB0jCswKYBY1AJO9xBEfGoV8ULH49tI67KgiCUOKTodnDuNTlIs4N67lpMvm+Pzt93f7sdO85cx3vLjyLFiLlqbTr4yEtcC+df2T1lvqpfc/M8d9diGmtUEPRp7KcOjigxP2CoEtghbXNn8ZGY7/pWLwBUaqizuU0kpaRi7kY9wjCtVz11oJQZdly5iGKe62ZeNzm/NXePQc23pwG+tbErVBejrUwycmsYEnM1113QcBGizTjdKRv3C1Bej3fk2Rl+8lLgrl8BD5+MM8t0+U9LVc8B3G40RvtgxTGVb8uD0+m902frHY1J3XUBRQfj9PgwJz0jT7gAlLnb32wEMPFvs0M9X5s/7Ug3UBPsT9myZbF+/Xq1cb8o57p3+Q7SsXwB3fJ2Qyxw6QlwJRAJSclmhZjx2jGSGdRCGF9/2fkL5AUmO7S6Dej/kl64o2FkUi6766HH1Em4Z13zgoSjKV0sGW5qHHABztvdRRmncQRFEAShpCFFt4PTrIY2EmNtPMdkPpJXeCB/97c7cCVSr7zTBdzsKkrncx6IBO0DrluZIc+O1CSgVkc1J5dWpoy5053XeW6HlZg38btRYm4U3TTGicg4Q12oUN6+5fP0ODkLyfTf+y+rcQAadWVnUpWe1x2WXnSfy2XRzS4vqdHGfEBszbncwCj0918I11J2OgMfLUDVAHN8HzkI1DIZt1mBBmfPLzmIAzktBFSsa5ZIKxiDte0r/R5z97U6K85Yth+36yLzjVEtMsSoORq9G1ZRMWccIfjdlK9tXuDj38+517DsP9PWHLmiPq8YAWiYMgklD2Oue3laF53MUbV53m6Ii3r/PKLSOA5dikRiSqqSrhuLV7vOhalxBXhVAur00L/DxI38oozbLChbHpi5DbjlG72fG0xKoIvOetHPEePCLGGMJhVUXDf4ZFwbhzSFEwRBsAUpuksAnLEli3ZdUIVzXoiKT8KkeTtUwVCzfFkMbq4lxJyzUvAgZOQXwP07TdLhXEA56NTVwJhvcCo0Wj1GSpHb+ufyYMPBMVzM/z1oITHnc0lZNLt33gVgGsMiloXowV91J5vz0mvfAJY9Dax8If16XEhhAcjuqoUHAB+nYdR3T486avEgK4z5/J2WnW6qHHIjn7ysjdBSq7czx48Z0WDWMOTlp0JjEHt8nXYGXmejsZmtcDSCTvMG2UjK6fDOCKIF289j/DfbcchkBJcj694GFk8CVj6vfx7wEuCdUcbP7FoW83zpjGlbE90cXCnC+LCJXXWHcf7mM+nvCZrH3b0EePSw7gwSjrUwr5yyXwuMmDCaSjryAoRgW6f7lCkiK/9RYZ2x57xeFGsXUAHVfcuinX959d4y/AHUAhth1GV+oD/Dx62A3+/NaGjK79S8cFV3uo+nVHNoEzXLz4GF07ti1aO90a/JjaNLgiAIJQUpuksAXepVROtavsqAhA7TuSU+KQX3fr9brfxz1f+HKZ0wpUc984wbLzcbqmVyUc4VFl1u5m1nV8CVRPo29lMxbxfD4syu3AoagNXtqaW1+YEHdJmlkH8/rAvR36YA/zwKrHoJ+O99LZ20dBev2gwo7w/0fCyDa+/646E4diVKua+P75y9fJcHr+xW0CjvimtNPa9M6XTmLo8Nne7LXk0Qm5ii7reuqctljUrl3JWhGglEA31mSKDVWeg8wTztn+4AvumvM+uzge+Tad/vUv9fPg+MIaJy5GSIFUOwzFAJ4mR63mt2ANqbZj4t+G7rORUR6OPhgueGNUVJ4Jb2tVDO3UUtmmSIPmS0Gl2mjdf1xg+BdW8CBxeZr8IFPEaOcdphXCeTwZZgd+Li4tCmTRu1cb8oMLqfZ65GIzX4MHD4j9zLsjPlcxsmavwuyhjtaFIiqRGbMnrhMDefYZn57z09MuPibt1bhWkIjGjk35SLTveeWK2cKgmdYZqpOfrigSAIQk5I0V0C4DyX0e3+fuu59PlIG+DM9iO/7MPW09dUgTN/cifUq1IOHQIqqI53dEIy1hwJufEXbY0gi7mqZaIm8pPP7egwG9yQmLPbbVc4C/zv48DXPTPmfldpqucGqTZgRBmlu53uBXo+AfR4LONtjPwcaD85w1lfr9cGfXd29odv2ezn7DiH16Sank/edS4cuG8L8MQJoHJD2/4GysPp6E2Do0Rd4Dev6Wt1htxaXveO6x5AuWpAWgoQrGNn8gVdxblgQVMvKhKymeFOTU3DY4v2Kfl3eU9X/HV/D9WFvx6TiLvm7FBeCdlCA7ixPwHNRgFjZt+wABMUEYcPV+oO1zNDmjpMJndOeFvGh222smDIme7d87V5nYsH0Mbk+A9gwTZdCPE9VavCjbPvgn1ITU3F/v371cb9ooD/XzdnJyQkpyFt/nBg8cTcm6nxO4vxmdyt1UlJyS2LbmM8gX4mVKygnB8Q0F3/7pG/8/bAL+4GTq4GGHWW+fPWYN8CHdG4/Bnrjv2ZGfoB0vq/gv/CtdJFilVBEATHQIruEsKg5tXUfCSdjek0bQuUc77wxyEsPxysDmhoYNLSJNel5GtEmxoZJeYk+CCw6G7g74dse2DMa363DrD+XVWYsLgnXUth0Z25m2KW0xJ2qCn5pmNuXuaxeRC6a67OsLUsusfMAu5dr+XrYxcAo78Ghr4P9H8R6PZAxtuhOZVFJ2bv+TBsP3NdRbvd00Ob9uREJ0uJOeXRuTH44WzjU2eASf9iT4h+blplM89tQJUHOXAxUndICbtT+YVy5vBz+nm540fdqcqC91cew9KDweq5mnVXe/U++m5yJzT0K4fgyHjcNXc7Qjgrmh2NBgG3f5cuqbaAbuUxiSlKAju2Yz4M3Iohd5sk5muPheDsVQszSErJP2+vZ3BJy1t15BrXQxKTsXi3/pwTA7WCxcPDAytXrlQb94sCLrzx+41EedfL0PG1GXarGbfl5IJLnk1UYc33q+EZwcKenyX0R1kZmFlinse57g3vpqvE6OFgDc6oM0IwKsi20ZgmQ3Gl1X0ITnBTz0tAJcee6RYEQSgtSNFdQuCX77Se+mCETtN09c2JD1cdx887zmsDk7Ft0K1BxhnRUW20adb6YyEIj01ML/A448YZ4YRo2/K56cRcsS6OBkchPDZJuXhn50hdkunbpAo8XJ1w4XqckvObiQ7Rku/d82zrdlh2h38cozsxzH+9bR7Q7m67PNbZ/+lZ7pFtaqqZR1sw53Wfs8ie5uKCrcoIFlV1emC/YaJmKqizI4ODec129im6w87pRQwy/ONs5y8X7jyPr0yKgHdvaYXOJoNA5gv/OLUz/Ct64ty1WFV4h8WY3ke5YO3RK1h2KFi9x98c3bLERelQWdOnsREfpme0Few0JloU4R2nZTD3owEbn9teDasU8iMuXTg7O2PgwIFq435Rz3Vfca2dt6Lb1OVG9dbYfVkvgDWr4ZthzGmIaVF02cHgdIk5vTaqt7rRSd+WUZkTK4AyTjqCMSvopTHsA73P7wDLRdMsOGmabQ+o6KmSIwRBEITij3xalyDGtKupZKd0muZBaXbM23wGn63VM6pvjmppPtiwpHE1b5V7m5SSli6HrtUBqFgfSIrVkric5LnGAUSdnthy6qrZ5drVSu5yaYC55FYl5rU76aguPq90sbaFyMvAvKHAuc2Auw9w129A89F2eZynQ6OVAoLc28t24zzDTC3wcqQaTcCSGcAHjYDQozbfBheMAoMiMxTU2dGipq+a62XGa1iFlvYpute/A6QkAvX6APX7Znm1zSev4vklh9T+Q/0bYkw7LZU2qOrjgQVTO6OqjzuOX4lWZoXqebGRuMQUvPTnYbU/pUfdEptDPambjgBbbBkfxtXA/i/r/dpdlKM9oULEKM7v6uJf4hYhBOsYs8un0kzfVbmVlxvz3LU6mfO52/vrzyuDISaJORVZHA2BT3XgsSNaHZRbz40N7+vTlrdZVa9koMEAoPkYvUBN7w2OC1nj7CbVdQ+6cMq8YCUIgiA4BqWz8imhcMV+sin7lo7TGeTLFvyx9xJe/TtQ7T8xqJGa182KUSaJ+Z97L6cfCNua2c0DBBrIVG6sDl62nS6989w5Ssz5vLa9y/bMbprvzB0EhBwGylXVmc+c27YT32ykmzTQv4kfGlXN2q07M+yI09iMEk3K0xF5CYgJsS2vm+7dq17GqXPnkZicCm8PFwRUynlW18vdBQ399GPcl2KScHI2PMYUd5dbrgSmv7aZp5sFJ65EYcaPu5GcmoaRbWrg0QHWZ9drV/TEj1M6o4Knq+rgT5m/M92cMAc+XXtCGbPV8PXAw/1tnI13QNitZmwQzed+33MxY6TeuIXA7d+bz+LcPA3l2OG7rX3JktoXR5KTk/Hvv/+qjftFBXPpycH4qnnrdDMlYvxvQLsJN5ioGVCq3byGj/I6WWVIzPOSgc0F5wvbtBEb/TMyJYUkJFt5/zMi0M1bLxjSx8Aa7IQvmgDPUzoWUea5BUEQHAcpuksYnG+kIRodp9cfC73h8nXHQvDE4v3m7tL9fU2Oz1nAuW4ec+w4ex0Xw0xmUEakFKXj2WVLn9mgT+v1VnFH209fL9Xz3AbsdFNiTpdvFg9mOPdHwx12ZEJz6OJ4VwMqNwIqNQCmrAKqmTq8diAkKh6/mQqfGX1y6NDYmtd9ngeg2RAVrDv8Wz7FoWAt/aQRGU0CbcGIFdt9JQ247Tvg/h1A2YwH1DbDRYwuM4GWt6fPiGeCsXeT5+9UEueOdSooWXl2j7VhVW98f09neLu7qDn5mQv2qIWF7Dh+JQrfmCT+r45soRYXSioqPszU7Z6/5azyf1DwOW18U4b4NCMm7OZWNZSEXyhYEhISMHz4cLVxv6g73duiTN8f107mTvJNz4iGAxBTvjGOBOkRnnYB5bNZFDUV3YSdZy4i27qQxzGZhw9oc0SLxA96FnR7ey3umLXtxhEwdtXptUFYdFv720zfC/vjDOdymecWBEFwFKToLmHQYdroXH+1QUvQDCipu8+iM/fS8GY5FjXsXHauq4uovwzJeoUAIKCH7mJbRPjcwJn/9Gnd3qq4ZBeL3cvmNXKe0y3pEnPGh90gMWch3XBguqNtdjDWi92/e1bo/4cdYewcC0KadtHFPrcYEvNdKq+7iz4zp063KSqMqojdwUlqt2VN2+f+W1nOdTcfBVRpnPcINs5v3/SWdhHPIRqMnfhZEzrYFH/H+fS5kzqqBZe1R0OU2zk7atZg0clMbr5XBzarqraSTpbxYRZQ8vvPAf2emWAyYBMKFicnJ3To0EFt3C8qDCn1gWhfpNG/IjkOiLRQRdgIPyP4vmM6hzWvCkNiztGRiFj9WYSfxwLzhwGBNo7+GHnzTYZmOOvzdSfV9yDVGhzxuoGOU4Gb3tGf65mf65Qk4Lr+Tt8SqRcepNMtCILgOEjRXQKh0zRdWRl9Ysjo2DW7R8laU9G7URW8f2trm2chDUM1s8Tc6MqS/b9YN8nivDFn7mgiU6e7OZ+7c91KOUZAlWoXcyMSifLmlExSTsrOlz2T/nzzoM4ro/ldfuG88Q+mednpvevb3Gm21uneez4cSdXb69cAnYOzU0UYRXeNtjh4KTyDK7kttDHFhu2/EJ7lWEWOZP49K387i+HHF+1XfxsXuOZN6oiKuei2dqpbEV/f1V69P1k8srC29nh/3X1RKQWY6/7KiOYoDbDgvq2DKT5si5X4MNPMNxeE6Didm9eHkHfKli2LnTt3qo37Rfn6qObjgRQ440Lnl4Dbf7BdzXJgkRpdwaU92GOa527rXz7L4r5JNW+14LXqyBV9Zh0uMtOs4s+c74ufZVbe0+evxWLJ3vTPwI9WncCl8ExZ407OQJf7ADcrYzUcmUlNRpqrFw5H6w53fcm2FgRBcBik6C6BcPWejtNk1oZTShZ+99wdKk6MBxpf3dUuV46nNFljpBgl60dMBlcqSqVmB6DtBOumL66ewPCPgG4PqQMjIyqstM9zW0rM3V2clKt1Bol5o5sAv2Zawk9TNcIDuI3/A/68H9j+FXBsWYE9rl92nEdkfLKanxzYNG/d1QZVyqmCNC4pBYHX0tKl79l1uy/tUSdJ1drgWHCUzc7llqZ/fE3zsZ8LCgW2fQX89ZDtrunk5BrguxHZmrB9sPKYUieoaLAJ7fNkZNSnsR8+GdtWmb8x3u/Nf49kKLzZzX1r2RG1/+jAhqojV1qY2LWOWuugEuCMZXyYacHjx+16QWhCl4A8LQgJjo3hYL6j0mig2QjA3Ua/CaZtbP5Yje6YTdSyUfEMaWG4mJuUSE1H6FMlMbeuwjDLv2f3BWb1AhJNn98mvlx/UnXYezasjE51KqrPx1f+0iaJVuH36r6fgGSTpD/0mDqJ86mLNDjBz9sdPh6utv39giAIQpEjRXcJZbrJcXpl4BWM+2abygpmZjA7c5Q35wYWUIy6ypDZ7eEDTFujs56dXazPz3W4Bxj4qupM7Twj89yWcD7XkJiz223GxQ24bwsw6A39HHOuj/nda17Tl3d/BGg8BAUB/09zN50xv37y6grN3zNk6SqvO6e5bhacpk73WbdGyi2f3ePcFJt0w6cBEjkYFA2sfBHY853usNsCn+c1r2gfgkO/W73Kop0X8KUpGuydMa3QxRQNllelwzu3tFL7czadwadrdJIAeXvpERWtx27b5O625aOXFOpU9jK/L77fmrHbveFEqIra8/Fwwc2ttcGjUEodzENtiKu0/Hy5qOPCUmt2wp7z4TkW3UNbaon5xhNXERmfpDO2q7fW7uJH/836vjYy+isNKO+foVvNhW+qV8gjAxrijdEt4OJUBqsCr2ClKSXiBhZOAP64D9j8SQa39lAPPVYh0nJBEATHQoruEgqNmwY09VPHGzxQZQHz/ZROKO+ZN+MhQ2L+177L6SZHNnLgYrha1Wch1TgXTtglnaGtspCYGx08djh+uwfYMUv/zFm/ga/mzU3XBjizz9itKt7uGNVW/7/zSkeTD4AquinNrNUx69iciAtA7FXAyQU74nQxRflwbjuZRrzYnstxQLUWuYsOO/w7EHxQR69ZydTlfOdzSw6q/Yf6NVDzx/nl9g61la8C+Wj1cXy76Qy2n76GxaaDc2Zyl8ZovfT4sIsZ4tUWmAzUbm1fG2Xdii4vurQRFxeH7t27q437RQkd7snloGBd/B5YnPMv0XAtLgxwKYvTLvWU4ou+CtnF7/H7k0VtYkoq1h4JSVd3ZScxv3YKOGh6PL2ezHDRV+tPKbl69waV0D6gokqEmGZaGGe32xyTZ0mLMfr0vw/0bZuK7nNlamVYgBAEQRAcg9J3RFeKuK9PA1WfsdhlwW3NNMZW+jbxUyZoLMrovmwmIUpL4M6bMlCNOKsd3wBXdffOmOfuUq+iZOpa0N8kMT97LdbspptBWji7j3b0dnIFbpmrZ/1sgIsiuZ1r5u/M/k93ce/pXhfuLvkraujoTXadDUNak+HA1NVZP/6Ii4BHeSWr3xekncvzMq9rOJgfuBiR7jpuS9FNg6K1b+h9jkPQediCkyHp0WAjWtfAowPT3Yjt4b/w6AB9e6/9E4j7f9Iy+3Gd/LPtxJVkejSorMYbWHD/ZlqAuHA9FmuO6uJnfJesIw4F+5OamootW7aojftFiTHDnMzvll/uBFY+b3s+d4222HMx2rxAl9OC1lCToZpZidTUVHRTDcNIsMxwBIidcI4ImTLlyeXwOCzadUHtP9QvPfaP+4xXvBwRj0/XWIk/a3ELUK8PkJIALH1SF/K3fYdVaZ3UxdLpFgRBcCxKbgaNoA7al8zsjqo+7vkquAndmenqumjXRfy571J67NeG91TMk+oC+HfW551YASx9AqjTE5j0D7aaiu6u9e1r+lUSJOZ9GlfBisNX1IFdM5M82mykFhIIuHgAdy7UB1828Pf+y8roKzk1VRXO7q5OqrDnPrs76jz+bLnv4oSE5FQcvxKtzIrsUdS0qOmrZqyvxSSq2dxsZ58DugFPn1XdqIOzD6mzWpq61nnpdB+6FIHkzm31h5tpVjxb9nwPhJ0BvKrcsDBgGQ1Gyfx7t2YfDZYXHurfQGX3UmZ+NToRlbzc8PRNjVFa4XgCu90v/XlYOelzfvvnHeeVaocFuXT4Chd3d3csWbLEvF+UGP/7LeHlAY4zR18B4sL1OFNORXftTuZ57nY2LGjRy+TTtSex/nioWgAqV7kBULUFcOUQcHJ1enQmuX5Gm4qSXk9luB36qnBkhikgnS1GUqjWeG1kc9wzf5d6749uVxNNqll8B/BzZtiHwJddgVNrgOADQPPR2LxsPYAYeR8IgiA4GNLpLuHQ1Tm/BbeBITlmgZiQbDJPa3WHPqW5FyV8GaLCeql4pd0mB/Wu+ZiBLXUu5q3GAsP+B0z/z+aC+8SVKDz16wElieQEACX9nA2+EpmgMsFZVB+8FIFd58Kw+eQ1ZVa17FAw/th3WZ2S8Z397WLOw4K+jakIZrdbkRCtD06tUaYM4lx8lcu++vPz0OmuU8lLqTG4gHDGzVS0Bu270QXeEpodbXg3/WCZjvAm+Nq99/tdajyD0WCz77YtGiy3sIh/flhTTOwaAE83Z7w5ukWex0BKCmPa1VKZ5qevxqgO98KdulN4VxeJCStsXFxcMGrUKLVxvyiheznfI2EpZZHsVS1dPp4dF3bq09qdzd9F7f1zLrrpqVC3spfyulhnUlkor42pa4GWt2W88qYPgbQUoMEAoJZJZQMgJDIeP5teuw/3T+9yG/RrUhU3Na+mDNaeX3LoxtEtjuT0eFTvL3sGiTHhOHddG7RJp1sQBMGxkE63YDNd6lZSBz00ZVt3NBQ3UX7H2dmqLYErB7UUut0k4MxG/Qt1e6vIMh600Gm1fhU9jyek079pVdURZnFxNDgqfc6Q5nTMbLWR2MRkzFywRxXanBv86PY2qvjk4ghj4ox9dZpknFqcl5yqHLntWdQwr3vH2etqrvt2r73A4kk6t3vyUqvXP3w5Qi0W8LVS1ccjTx1SdruZ8bwrujIaunkDiVHA1WNA1SxitxjDxm4ZjY/aT8pwEU3laLpEI8FvcxkNlpfC+9WRLfDC8Galco7benxYbXy7+Qye/HW/WjziZw99KoTSC9/jHD04dCkSEV51UCkmWM861+pg/ReS4oCYULUbUbkNTobstbnTzfck1V00T1x2KEib99Xve+MVuagXfMh6l/u/0+r7jyoZszosEy+PaIaNJ0JVF54y9LGdMimNWHTToC06GFFrP0RKamf1/qCCTRAEQXAcpOgWcnXAM6JNDcz+77SSmKui28jsXnlQy+s4Sxt3HXArB9Rsh61rTqur8IBDIn5uhAdPfRpVUS7z7HZnZ+6THS/+cRgnQqKVCdrHd7RVp0WNzus+pTrr6NtUd4I4Y02DOBfT46NB0PejgICuOOD3rDqrVR6k5ZZz3Sy6912MwjjOVZ7bDFw9kXXR3WEy4OwKeFbSzvEmwmMT8fUGPeP+yohmhSbllII7nbu7BmDeljOq4CZ3dvaHiyxIFDopKSnYuFEvpPbs2RPOzkVrYsf3IovuINfaqIRtZoMxq7iWBZ48qcZH9oS6mM3YbF1AoxKJRTcXmbmwaTX5gwuk09bqSERjxIou41EJWGCKuHuof8Msv/+oRKNPxBv/HsHby45iYLOqqFTO4vPb1QOYsARYcDsiI7TzOhew5ftUEATBsZCWipArRrbR7tKUfKooFUKpXRknPTu3a54+L6C7KmaMeW7J586aYSYXc+Y/59YAjbA78tueiyr3+bNxxaPgJu38K6ixRM50h7rV1oVtcjwQtD/9Spy5jjgPXD+tpO95lZYbGAX7/ovhwKgvgWcvAs1HZf0LLLhZeDPz14KvN5xWc9yUmI5snT8ndyHv8WH9TPFhjFca27G2PJVFQHx8PPr27as27hc19SrrBbCTKfpzUy2qZYdyE62HPbmY5zZgDGHtimWVgmjDsdD0+/vzAeCP+zPeB70pLJiz8bRSGXHEi9nc2UEPAy640ln9raVHb7xC3V7A02fwT/UH1Y/iayAIguB4SNEt5Ipm1X1U3jclc8sPmvJFvasC9fvp/d2morteb9UZ2HdBr8x3rScmalnRr4mflpiHxuCYaabZVo4FR+GlP7W08bGBjfKVHW1vfD1dzRFxapbSnNe9Nf1Kpnxu1GinouVIy3wU3TzAJZwNj/WsAbhlMdIQHwEkJ1q96EpkPOZv0bPnTw5uLI77RcjMvvXV2MPtHWvDLw8jB0L+YUe1WbNmaisO3dX6fvo9vT/Oz7ai24TZRM2GeW4D/r1DW5h8N0y+F0hJBPb+oOPBjvyjvSoycS06Ad9vPWee5c7peaOC463RLVTtzgVUY7E6A65lzfnkhou7IAiC4DhI0S3kCh48GIZqf+y7lH5B63EZr1i3F3aeDVMxS8wIZ7dAsI63hyt6Nayi9pceMMXT2ACzXWcu2K26Kb0aVcHMPg2K3VOsJebM62bR3UWfeX5b+hUua3fxuCqt1Fy7kdGdVzgLztlfzoZTgpolq14GPu8AnFxzw0WM7+FzSvd/LogIRQczjfe8OBCvjzTlrguFjqenJw4fPqw27hc1Rpd3dUQNpN3yLXCbaaE3M4xd/LwTsGgikqOvmxeAcxvFRxdzsvbIFWWuyGhDVGqgo7wWjgc+bglEXLrBD4LdcX6WMaHCFtr6V8CdpnnuF/44mG5WasFJo+iWjG5BEASHQ4puIdcwq5hsPX0NwREmuWGTYcAjh7Sc987FgF9zi6gwmefOiWGtquVKYs7rPL/kIE6Fxqgi86PbWxfLjizN1AjN1NI73dsY/qsNiExS82PODVUkFBdoKlvOM+YBQ56uOufr3wHmDEh3MDbmyBkTFn4OcM1YRJy7FmN2yn5qcONi0dkr7XBRyrkYvraFooGO4nxbXoj3wPW6w7P2a2DkIk0UT63F0TCaTaYoR3wqtXJD61q+qOHrgZjEFPx3PFRLyRmRaVClMeCjvxMNPwhG3eU0y22Np25qgsrl3NTn+jf/aT8UAzqbnwrRC5PiXC4IguB4SNEt5JraFT2VGyuLpL/2X0o3rClfG3D3BhoNousatp66qi6SeW4bXcydndTBFqO9cuKXnRdU1BeLkc/ubJvReKcYdroPX45ETMVmgEtZbbR37YQ2QEqKVaZ7O6Mq5Hue26C1SWKuOlss6i/u1JvB2je0qVvDwcrAzZIPVx1X6ozejapkyNQVBKF4wNi+WhW0coqflznmc9dsjz0XteqlbUCFXC9OKhdzU7fbiFbMUHT3fkoX4ia+3XRGFeic0c6t2z6TEl4c3kztf7b2pFoENAiKjFfdc/obMMJQEARBcCyk6BbyxEhDYr73stXLabJmGGNlFZUipMNs7F6NKpu73dnBaK2X/zqs9p8Y1Nhc2BZHapQvq7rXzKHddzkW6PkYMPQDbapmkpajemvsvxSd73luA8aGkQMXI5SDvoKu6eTyPuDw7zyUBvq/lOH3jgRF4q/9l82z3IIgAHFxcRg4cKDauF8cMOTV10/uBLZ8DpxcfeOVLuzQp7U7m03UbMnntsbQllqJtDrwipZ9V2sFdH8Y6P4IUC89RoxGaPOMLne/BnlSylBJxthHxji+9Odhs/LpVIj+jGTBLSkHgiAIjocU3UKeGN6yulpxDwyKxAkr5l87Tl9Xc7WUAjISRbAtnoYwOiwrouKTcP+CPcrIrm/jKpjeq16xf2ozSMzZFeo0DfCqDLh4KAM1znqrApmd7pp5jwszMAr389djEVmpdcaie+3rpivdpjPmLfhgxTGl3qCbfIt8zJULQkkiNTUVq1evVhv3i1PRXfbMSmDl88DhJdkU3Z20kaNyLs/b50vb2hVULnZUQjI2n7yqO9sDXwMGvpqhy01ZOVMPGlUth8HNTZGauYSFOj0MqHzacDwUS02GpSdNRbdIywVBEBwTKbqFPFHBy81sEJPBUM0E571JcXLTLu4MaKYl5jy4ovt2ZtjxeOb3gzh7LVbNGH54e5tiOcedmQ6mTvwumqlZ0vJW4N51CO/6jCqQ1Vl2KHYp0axXxeRwnFpXnxl2Bgj8U3fEnFyAvjoT3GDX2esqBo9y/ccHNsr3YxCEkoK7uzt+/PFHtXG/OGC8vwMTq1p3MI8O0e95lEGob0tcuB6namMj3SC38HN2iOFibqR2WFkQpYEaebBfw3x9NterUg739amv9l/9+7C6bbNzuZioCYIgOCTFruj+8ssvUbduXXh4eKB9+/bYuHFjttffsGGDuh6vX69ePXz99deF9lhLOyPbaIn5n/su32D+tUXyufMkMTfyXP+14mL+47Zz6nwqDD4f304tfDgCHU2d7j3nw5CckgqEHgd2zweide6tMYZQp5KnihmzB4bEfM8VaKdhsv5dfdp+ksrtNeBr970Vx9T+be1rqQNeQRA0Li4uGD9+vNq4XxwwCs+d0aYoSvpDWOty+zXF7ivaBZzxhTTlyytDWujO9crDwUpplBlGhFFeXr+Kl1m1lB9YdPMzMSQqAf9beVw63YIgCA5OsSq6Fy5ciEceeQTPP/889u7di549e2LIkCE4f/681eufOXMGQ4cOVdfj9Z977jk89NBD+O233wr9sZdGBjStCi83Z1wMizNnoJKwmEQ1H0uk020fifnBixF4/Z8jav+ZIU1ylTVb1DTy48Gui3IPPhIUBfw2Bfj7YeDkKnW5IS1vaSqU7QEdh8l+OpjXbJ9ufjTxH6DXUxmuSwnnjjPXVVb6wwMa2u0xCIJQsEX3tgjTZ0ZcGBBjkW1dxkmPrgR0N3835TYqzJpih8kKkfHJZiWXZXzjnI2nzV1ue7jt0zDu9VF6BOb7rWfNn5PS6RYEQXBMilXR/eGHH2LKlCmYOnUqmjZtio8//hi1a9fGV199ZfX67Gr7+/ur6/H6/L177rkHH3zwQaE/9tJIWTdnDDat/ltKzLeZDkg411bFu3jIER1JYu7qXAYnQqLNs/I0pbv/pz1ITEnFwGZVMaWHSTLtIFBmSbf7G6LD/rgP+OdRHe2l5rntN0fdyiQj5W2n1WgL+NQEnJyBuj0B76oZYnjeN3W57+4SIP4DgpCJlJQU7Ny5U23cLw4wVsuHC3lp7kgqV+vGbneToWp0BUPfx57zecvnzgwL6cHN9WfHskyLolQhhcUmKQ+T4a3y3+U26NmwijJWoz8KnctJ/VxGngmCIAjFg2JTdCcmJmL37t0YNGhQhvP585YtW6z+ztatW2+4/uDBg7Fr1y4kJSVZ/Z2EhARERkZm2IS8M8okMafs2ZDcGV2ArjLPnad5ZB5oWWZ2P7X4gJp5ZkzOB7e2dsjs6I51TXPd51h0d0m/oGwF1cW3l3O5QbPqPkqGfzU6EZca3gU8Fgj0euKG6y09FKTizMq5u2BmX5MMXRAEM/Hx8ejUqZPauF8c4GegUXyGe9WxLjHn931KqvnzxR7qIEOJtOJwsB6VYZM9MQWzTZna9/dtABdn+x5WvTC8qVIKkWo+HuqzShAEQXA8ik3RffXqVbWKXrVqeheK8OfgYOvGJTzf2vWTk5PV7Vnj7bffhq+vr3ljJ13IO8zgpuSOq/z/HQ/NMM/dtb5p3k7Is8R8/pazWH44WHW/v7iznd1mngsbI9Zs59kwpFkU3ZHl6uFyRLwyObKnYzilmczJJUYcWWZ40PzhSn2gPq1nPVR0kBl5QSjsAjcgIEBtxWnBz5BZX3KunbHoTogCErUx46FLkUohVMnLzS7Z1p3rVkQFT1f1fbf9zHV13oLt53AtJhH+FT0xsk0N2Bs/bw88fVOTfLmvC4IgCEVPsSm6DTJ/qbPTl90XvbXrWzvf4Nlnn0VERIR5u3Dhgl0ed2mFq/o3t65ulpiHRMUrwxc+/V3qFd/86OIMJeQsso9ficYb/+o57ueGNkXrPDrvFgfoSk5n9tCoBJxL9AUCeqis7gMeHcwH0Pbu4LQydc4N+Xpmft19EaevxqgD8ik9HUuyLwiFhaenJ86ePas27hcXDAfzfzyGAdPWAX2e0Rfs+R54pzaw/DlzPne7gAp2WTDg950RBcZF0fikFMwyd7nrF1h+9l1dAvDrjK54c1TLArl9QRAEoRQV3ZUrV4azs/MNXe2QkJAbutkG1apVs3p9OqxWqmQ9qoqRJz4+Phk2wT4S89VHrmB1YIhZ3lveUzqHeZWY92igVQIpqWnKNXdSN5OE0kFh59kogtVc94TfgUcOYleok93nuQ2MRYp9F24sunmw/MkaHTNEWblINgXBsTA63TsiKwA12wHu3unO5anJgFdlu5moWTLEQmL+0/bzaiGxZvmyGN3WNFteQNDIzVESKwRBEIRiXHS7ubmp6K9Vq7SjsQF/7tatm9Xf6dq16w3XX7lyJTp06ABXV8eU4ToiLKZoIBOflIoPV2mJn8xz2yeOjZLFd29tVaxknXbJ63ZxB9y8CmSeO3Ns2KFLEWrxIrPxUVBEvMo7H9/Z3+73LQhC4RTdp0Ki0yMreXphu96t1RG7z9u/6OZIFRdG6Rfx7vKj6ryZfeur9ANBEARByIpi9S3x2GOPYc6cOfj2229x5MgRPProoyoubMaMGWZp+N13322+Ps8/d+6c+j1en783d+5cPPHEjYZJQsHBgtDodl+NTlCn3RpYVxoItsHZwM/vbIvFM7qq/O6SgJHXvZNmaqZRkAOmjG6jC25PGviVg6ebM2ISU3AqNH2uOyo+CV+sO6n2HxnQSHXhBUGwDs3TRo0apbbiYqRGOKNNs0S+vyO3fAv8+zhwbjMQFQSUccYlz6aqC83rcLzFXlBCzhEgkpCciuq+Hri1fcF2uQVBEATHp1jZYN5xxx24du0aXnvtNQQFBaFFixZYunSpMnAhPM8ys7tu3brqchbnX3zxBWrUqIFPP/0Ut9xySxH+FaW3SPxo9XFztIphnCXkfSFjeCv7m/IUJUa36XRoDK5FJyApJU0dFPP10qy6/YtuZ9PBNg2PKDFvVFXLT7/ZeEYZIdWv4oUx7fRikSAI1qHB6Z9//mneLy6w+PWv5Kk+T5z2fAdc2w/EmAxUq7fC7iC9ANy8pq/dF9aGtqymPCHIfX3qw91FFu4EQRAEByq6ycyZM9Vmjfnz599wXu/evbFnz55CeGRCdtSp7IU2tcur4oaFjncJ6c4K9oMz/sxup0HcLtOsJWnoV05lvhcEnOtm0U0ztds71FbF/tyN2vjo8UGN7R7vIwglDY5+zZ4927xf3CTmLLpD3P3hjf1A4B/6glqd0ue57RAVlpnuDSorJY1zmTLqc0UQBEEQHK7oFhyXe3rUxUM/78XottI9FKxDBYQqus9eN3eHCkJannmue/8FLWP/Yt0pJUflwhAN6gRByB76o0ybNq1YPk2Gg/mZtOqob3lB7U7Yvc7+89wG/Oxa9Wgv0CqCihpBEARByAkpugW7MaJ1DfRuVAU+HvKyErIuuhdsP6/yun3KajVES1NhXBAYBf3R4EicuRqjDNTIk4MblwhzOkEozRhmaocSq2GAcWbz0Yit1hFHgg4VaLY1Pz+c5SNEEARBsBGpjgS7QldXQciKDiYzNTqK0+SMtC7ATnetCmVVDve1mEQ8+PMeJKakqvz4ng11JJvwf/buAjqK6/sD+HdmNRt3F+IQ3N2hFNpC3V2oUKMu/yr1X92FKm2RFmgLtJTiEDRCPMTdXdf/Z94kaBKyyW70fs7ZMy/JZnfZDbtz37vvXkI6ZjAYWKFSwdChQ8HzfB9sG9ZSuFNuC1z1HWIzK9gqtNDKy9PeqncfJCGEENLXqpcTQgY28SRYCZ3BiNpmHWQSDmEeLf11LbQa1dqvO6Gglh2fXBROq9yEdFJTUxMraipchHFfIhRDFByvc4CRkwCaOqCuGNEt+7nH+Fkui4YQQggxBQXdhJAeIwTBrf26BeEedhav/HvmnnGh1c9YCxRWImQgc3FxYZe+WJzRxUYODWTQKx0BlTNQX3K6iJoF9nMTQgghXUFBNyGkV/p1C0ZYMLW8VetKt7CF+/GFYRa/P0IGEmtra5SVlbGLMO5rAltSzFMDbwVULjCoXBGdW82+R0E3IYSQvoKCbkJIjxrvf3ql25L7uVtNC3LBstFeeG7xUIumshNCem9f93b7a4EVR5GpsUNNkxZKGY+hnnb0khBCCOkTqJAaIaRHCYGvk7UclQ0ajOmBVG+5lMcH142x+P0QQnpvX3dGWQM7tqaWC+0CZRJaVyCEENI3UNBNCOlRQl/bb24dj5KaZoS608ozIX1Zc3Mz7rzzTjZevXo1lEol+uJKd0ZZPTtG54ip5WNpPzchhJA+hIJuQkiPo2JmhPQPer0ev/zyCxt/9dVX6Gtag+6s8gboDUZE5bYUUaOCiYQQQvoQCroJIYQQ0ia5XI7333//1Liv8Xa0YltI1DoDkgprkV4qrnjTSjchhJC+hIJuQgghhLRJJpPhkUce6dPbVQJdrJFSXIffovLY94SvhboRhBBCSF9BVUYIIYQQ0m+1pphvji1kR1rlJoQQ0tfQSjchhBBC2mQwGJCbm8vGfn5+4Pm+N1cf2FLBXGgVJqCaEYQQQvoaCroJIYQQ0qampiYMGTKEjevr62FtLQa4fXGlu9U4qlxOCCGkj6GgmxBCCCHtUqlUffrZOTPotlVIEeJ2dhBOCCGE9DYKugkhhBDSJmFlu6GhoU8/O63p5YIx/o7gea5XHw8hhBByrr63OYsQQgghpJOsFVJ42ivZmPpzE0II6Yso6CaEEEJIvzYjxAVSnsO8oW69/VAIIYSQ83BGo9GIQay2thb29vaoqamBnZ1dbz8cQgghpM9Qq9VYsWIFG3/yySdQKBToi9Q6Pate7mYrrngTQgghfSmWpKCbgm5CCCGkTcJ+bhsbmz5dvZwQQgjp67EkFVIjhBBCSJtkMhlWrVp1akwIIYQQ09FKN610E0IIIYQQQgixUCxJhdQIIYQQQgghhBALofRyQgghhLRJqLVaXl7Oxi4uLuA46oFNCCGEmIqCbkIIIYS0qbGxEW5uYhsuKqRGCCGEdM2gD7pbO6YJ+fiEEEIIObt6eSvhc1Kv19PTQwghhLRojSEv1IV70AfddXV17Inw9fXt8IkihBBCBjMvL6/efgiEEEJIn40phYJq7Rn01csNBgMKCwtha2t73l41YeZCCMbz8vI6rEZH+g96TQceek0HFno9Bx56TQceek0HFno9Bx56TXuOsMItBNzCxDTPt1+jfNCvdAtPjo+PT4dPphBwU9A9sNBrOvDQazqw0Os58NBrOvDQazqw0Os58NBr2jM6WuFuRS3DCCGEEEIIIYQQC6GgmxBCCCGEEEIIsRAKujugUCjw4osvsiMZGOg1HXjoNR1Y6PUceOg1HXjoNR1Y6PUceOg17XsGfSE1QgghhBBCCCHEUmilmxBCCCGEEEIIsRAKugkhhBBCCCGEEAuhoJsQQgghhBBCCLEQCroJIYQQQgghhBALoaCbEEIIIYQQQgixEAq6CSGEEEIIIYQQC6GgmxBCCCGEEEIIsRAKugkhhBBCCCGEEAuhoJsQQgghhBBCCLEQCroJIYQQQgghhBALoaCbEEIIIYQQQgixEAq6CSGEEEIIIYQQC5FikDMYDCgsLIStrS04juvth0MIIYQQQgghpB8wGo2oq6uDl5cXeL799exBH3QLAbevr2+PvjiEEEIIIYQQQgaGvLw8+Pj4tPvzQR90CyvcrU+UnZ1dD740hBBCCCGEEEL6q9raWraA2xpTtmfQB92tKeVCwE1BNyGEEEIIIYQQU1xomzIVUiOEEEJImxobGxEREcEuwpgQQgghphv0K92EEEIIab9ATFJS0qkxIYQQQkxHQTchhBBC2qRUKrF79+5TY0IIIYSYjoJuQgghhLRJIpFg9uzZ9OwQQggh3UB7ugkhhBBCCCGEEAuhoHuA255YjOSi2t5+GIQQQvohnU6HzZs3s4swJoQQQojpKL18ADuRV43lP0XBx9EK+5+cc8FS9oQQQsiZ1Go1Lr/8cjaur6+HVEqnDYQQQoipaKV7ADuUWcGO+VVNyK2kVi+EEEJMw/M8pk6dyi7CmPS80tpmXPHZQaw/nkdPPyGE9FM0ZT2AHc+uPDU+mlUJf2frXn08hBBC+hcrKyscPHiwtx/GoPbniUJE51ZDbwSuGe/b2w+HEEJIF9C09QBlMBhxPKcKtmiEHFocOyMAJ4QQQkj/EJ1bxY4lNc09cn/1ah0OpJWz8whCCCHmQUH3AJVRVg9lYzEOKh7EV7L32Eo3IaTvEgoePv17HCrq1b39UAghfYTRaMS0jA/wtvRLDG84BH0PBMIf70zDTauP4Mt9mRa/L0IIGSwo6B6gjmVXYZnkIOy4JsyWnEBNRTFK63pmlpwQYrqvth6CPPob/LA/lZ4+0mc0NTVhwoQJ7CKMSc8qqGrAjYY/cY10L76RvYOKmnqL36cuOxJT+QRsOngCWr3B4vdHCCGDAQXdA9TxnEoM5XNPfT2JT8GxLDFFjRDStwhpnHfkP4tXZD8gLP7d3n44hJxiMBhw/PhxdhHGpGelJsac9XVFyenPdUu5tOI7/CJ/HcMajuGfhGKL3x8hhAwGFHQPUMezq/CJbtmpr6fwibSvm5A+KrOsDiOQzsZO9WlQ6/S9/ZD6BCE75/qvDmNjdH5vP5RBS6FQYMuWLewijEnPqks7u4hdbanlg24HfTk7FsMJPx3MsPj9EULIYEBB9wBUUtvMWoRlwAdNl3/PvjeFT8IR2tfdLVUNGtQ0atETyqtrsOW9e3Bgzz89cn+kdyWlJLGjzsjjds3jSCiooZcEwIZjeVBl/4sfdxyl56OXCH25lyxZwi7Uo7vnWZVEnfV1c0WBRe+vUa2Fq1GsAfOkdB1eKn4ACfnVFr1PQggZDCjoHqCr3IKhnnawCpkFg0yFYqMTMoorUdNkuaCxskGD17YmIb9q4PUEb1DrcNEH+7Dk4/3Q6CyfYpm98SVcUrsO0/dca/H7Ir2v7uR+dkwwBqAZClaTgQC5qVF4WfYD/q/hdeRVDrz3FUIu9LkT2JzIxlpOxo66mkKLPmmlZaWw5sRijqP5DAzjc3Bwx2/0QhFCSDdR0D0ACe3BrpfsxF02kYBBD/7pPPyf3avQGKWIzrHcyfxHO9Pw9f4svPXPwCsEdSSrAl71iXCoTmT75S3NqXDfWSdBZGCzaVnNKrQbLdQrRlymZU+s+4NmrR4xBQ3w4coxksvE0ZOUYt4b9Ho9duzYwS7CmPScxIxshHDiynam63x25Oss+95QVZLDjrWwQfnQm9k4OOsX6qpACCHdREH3ABSVXYkHpZtwee7rQEkCIJFiYoAT+5klU8x3p4rB4f60sh5pa/LjoWxc/UUkynugxdKBk8V4UfYjtiiex6GkbIveV11DA9y0pwOMzKj/LHp/pHcJLcJCNeJq1lgXPQ4pHsSynNcGfY/cqJwqnNS5o8DoDBmnR0niHvpT7QXNzc1YuHAhuwhj0nMy05NRZHRCicwXaudh7HvyphKL3mdDWR47Vktd4Dp3BRvP4aKxbd8hi94vIYQMdBR0DzD1ah1qi9LgxVXCyEsB34ns+xOGOMEZNRYrppZV3oCCilo2rm7UWnxPqlDt+YP/0lga7qZoy+5xE+xPr4Y9xFYtjcmWDYKTj++BDSee3BqMHMpyxP2+ZOBOku02jEaiJBwuY5fCk6vEKGMyMkrrMJgdTcmGI+pwQjqKfW1dcJD1LCY9i+d5jBo1il2EMek52yvcMUX9Cf6b9jPgPQ4/6+bhgEH8/2Apmirx87RB4QbONRTFrtPAc0ZIor6BjtqHEUJIl9En6AATm1uNiXwyG3Pe4wC5NaDXYlnklYhS3ofi/EyWtmluu1NK8bHsY/wpfw6T+SS22m1JcQU1bA+5YO9Jy95XUU0T0krrsbflZCe49jArVmcpf1b6Yp76HbyleBAj1N/g3dp5Frsv0vuicqvxtu46rIn4GtKhi6GDFO5cNZKS4jCYqZI3IEpxHxZwR9jXY3WxSC+1fI9icjYrKyvExsayizAmPUOYWI7OFQuYjQj2hyp0Jp7T3Yk1zVMser/xkmF4Uns3knyuYV87zX2IHS/R7cTOuEyL3jchhAxkFHQPMMJKttCTm/GfJh4lMsgU4snSeGMiYlo+yM3pQEo+ZvJxGMlnoc5ohX0nxZYjlrInpQQ8xIJmR7MqWcEZSzlwsgw+XBlynMXnc7bkBPa2pNJbwr60CmQYvRG26D408ypkVzSywJ8M3DRqwVg/R0BmhRJbMY20Ie0ABiuhS8CQ2mNshU0z/Hr2vQguB1HJ1L6IDJ42gjVNGihlPCuK6m6nZN+va9ahUWO5z7vEZhes189BQ8AC9rU8bCGqlL6w4xqRu1vshkIIIWQQBt2ff/45Ro4cCTs7O3aZMmUK/v77bwxWQpGvSZy40o2AlqBbWPUeMoMdp/JJZk8xZycA2QdZxVO1lTtSjH5Iz81DXbPlKqWfTIrFccW9eEv6FTR6PQ5nVljsvjISj+GA4mE8pP4GOl7B0n/TEyzTwii7vIG1e5NJOCwY5o7h3vbs+4fSLTuJQXqH0I/bWBANGzRifEvdBYPPZHa0LT02aF+Ww+klLGNGYD3hRlSoglgAXp20s7cfGiE9IjM+ElGKe/GVzdeQSXjYKKRwk6sRxBWgpMpyW09as7g8WoJ88Dy4WU/gHd21+Kw0AslF4jYyQgghgyzo9vHxwZtvvonjx4+zy9y5c7F06VIkJoqFiQYTYb9VSW4afPkyGDkJ4Dvp9A8DZrLDFD7R7EF3ZHoFZuE4G8u1NYhR3oen+J9xONMy+8eFtHKvsr1w4uox0yoD10t2YX9yocVS/BS5YgEnznkIGjzF1D6rnN0WKRaXcfA3fCL7CMvdkmGtkOIWhxPYJH8BDofeMPt9kd6XkFeOnySv4ITyHgRwxex7zhGz2HGYNnHQZjjkxB+AHdeERokd4DkKhoCZKDPaobC0tEeKNJLTmpqaMHv2bHYRxqRnNGZEwpmrg49cbJXHcRx28iuwU/EEagpOWux+Q6r3YxofDy+r06vpDlNuRfawe1EFO/wQadlCooQQMlD1+6D70ksvxeLFixEaGsour732GmxsbHD48GEMNslFdQjUtaRfeo0BFLanf+g/hQXifnwZinJOmrUgyu6UEsyTxLAxN/ZW2KEesyQnsM9CKdjCfvHZXCwbe2rz8IZsNSpS91ukyFJycS3GacV/m+2wi2Az/GI2nqyPxol886fpy9L+xiWSw5hvLb6OQ11kGMOnw7NC3NdKBpacxKNQcWq2jYBzHMK+pwqcyo5BfBHiUtMxGElz9rJjrTDJxUvgeOmrmIuv8WPzTCQWWrZIIzmbwWDA3r172UUYk55hVxbNjsYzJs9rpM7s2FCWa5H7FM4LntZ+hp/lb8DLeHaV9NumBrDjppgCVLXUUyGEEDKIgu4zCT1E165di4aGBpZm3ha1Wo3a2tqzLgOFsIL9r2ECHvT9HdzST8/+oRCAC4E4gNH6eCQWmuffLQS6uSlRrJeuXqIA5jwDvcQKHlwVClMtkx57KCkHE1v2reu9xrPj8IbDrIK62e8rJf/UfUlD5kESugCNvDVK4IC9KeadVNBo9QiuE58zh+EXsWPA2IXsGGrIQH6RuBJKBg5tViQ7ljuMZmmcjMoJCY7z8K1uEeJzB9+2AmF1P6JZDDjsIsS/f6mVLSYFurDxwXTLbSUh51MoFFi/fj27CGNieUJQG6oVt4m5DhOz1Forip9ZYdzcyqpr4cKJ5wb27v5n/Wy8vyPudo7DD/zL2LZ/8C1qEEJIdw2IoDs+Pp6tbgsnBPfeey82bdqEYcPEYkTneuONN2Bvb3/q4uvri4G0n1sQHhgAuIWf9/PWfd1TzLivW6jqPaKhpX/nkFmAlSOMAeL9hNQdQW6FmBpnznRvXfpOyDk9mmz9IZl6P/v+HD7WIlXMK5L3QslpUa9wB1zDAOcgbL3oIB7RrsDeNPMGRInx0fDiyqGBFH5j5rPvqVz9USjxgoQzIiua9rMOJMKElXOFGFxKA8R93K1y5nyKV3S3YFeBFIPN4ZRcjOXS2FgVdrpy/9QgYZXPiOg0y6zykbZJpVJcffXV7CKMieUlpSaLE9ngYRd0eqVbqJkiMNRaZjtVZbH4f0sNGSTW4qp6KyG9/U6rvZjMJ4M79g1t8yCEkMEYdIeFhbF2JkJK+X333Ydbb70VSUlt9zZ+5plnUFNTc+qSl5eHgXICL/SsFkxoKch0ntBFSPZchr/1E1nFb3O1CoszBuKQag4kI65i35OGLTxV5XufmVuHxRfUYIKmZf/40IuBoLkwgEcoX4CExHiz3pfQWs2lRKwgrR8yWzjrYOMZ4Z7sKKSXmzPNrjxOLACYrRoFXmF9+vtO4mq+NnOf2e6L9D6haN4Io5hF4Rox+6yfjQ9wZMeU4lrUWrAgYV90JLMSz+ruRJTHNYCTmHIvuIg7jKOKB3BZ3jusAB0hA1V5ivi5U6QMAhQ2p75vtBU/e6QNlsl6qmtJW6/inU993p2ptX3YEt0O7I7PsshjIISQgWpABN1yuRzBwcEYP348W8keNWoUPvzwwzavK6yGt1Y6b70MBELF6wkNe7FO/irGlP/Z9pX8JqNx0Qf4zzCOrXQLq8bdtSe1DAcMI3By+gfAqGvFbwaLq7TjuJM4mpJt9lZhcyTifm5J2EVsZb3ZQwxKbfN2m7UH+fHsKkyF2CvZLkJM9xZ42CsR7m6DABSZtR+5XYEYVGsCxEJareQhYnqhR+Vxi+xbJ70jOSWB9ePWQgq5n/g33EpoDxTiKMEkLhGxGZZJJe2LhL/vXZkN2KCfDfX8s4sHenl5w42rxmQuATEtbdZIz2zbOnjwILsIY2J5sgJxm1Gj+7izvi+192JHZdPZ+63Npbkinx3r5K5t/lwefhGqFN6w5xqRtYvahxFCyKALuts6cRP2bg8mQoA4nY/HJD4ZskoxNbMtI7ztWd/PqkYtMsrqu3WfQkuw1jT12WFnfEg7DYHabghknB581l5ozVi0LfJkAdbpZ6PMcfSpPuRWEWJxsxmIMWvrsP0nS/GB7ipEOi4FF3jGSqTBgJ80j2C34jGkxpmndVhZdR0iNOJKvff4JWf9rHVfd5ghA3nFljnZIj2v7uR+diy1DmP9uc/1i34lfpW/huIE8XqDgfCeVFqnhkLKY6y/uNrfivOdBA2ngCtXg9R4y7TsI+drbm7G9OnT2UUYE8sSPi+P1TnhiCEctmFnZ8AonX3Y0U5rmVoPuhpxgq+5JY39PLwE3KR72HBG1UakUvswQggZPEH3s88+i/379yM7O5vt7X7uueewZ88e3HjjjRh0/blbCn4hYHq715NzBlzpXoJ5fBSOdnNf98H0cszDUcx1LIe/k+qsn8mm3IMvcRVOaLwQm2eeKt9CKvfR/Ca8q7sGutv+AaRiUR8uRAxKhYJn+1KKYC770yuw3TABZbPeAM7c38bzkDqKtQDk2TvNkjFwPCEZ6UZvVHKOcAwYe9bPlC7+SJENw9+GSTiRltPt+yJ9wx9VQ/C89nZUDL+9zZ83uIxmRz6vpWbCIHA88STulGzDMu9aKGWSs38oVaDCWVz502eIbfyI5Ql7eYVMMuEijIllpRTV4TvNPNzNvwL3yded9TMbn+H4WTcPv+mmmeVz51zSOvHz02AjprG3xWHKbVBzSoTzedj/3yazPwZCCBmo+n3QXVJSgptvvpnt6543bx6OHDmCf/75BwsWLMBgkpGZwVoMGcEBfm1XbmdyI/Fa+cN4XbYaR7u5KrwvqRD/k32Bb5seAorElO9W/JT7kRC2AllGT+w3U4EzYX+4kF0d7mELT/szVgbdIxA95RNMU3+EPWnmSTstr1cjqWUWf1qwWDX5TDYjxNX1Cdoo1lasu7bny7BM8yq+m7D5dBXrM2yd8D1WaB/CzkJ5t++L9L6aRi0iy62wRr8AXjNuafM6qhCxIKF3bSw0usHRqqk+6V/8n2wNHmt4v82fK1sKqwXUHEOD+nQfYWI5KpUKaWlp7CKMiWVFtRREFTI9eP7sSQ4nv6F4Xn8nVmsvQmWj+dt2bZPMxpPau1EzZHH7V7JyQHXIFWzon/4Tey8jhBAyCILu1atXs1VuIZ28tLQU//3336ALuCsbNHCvFIuL6d2Gsw/FdvlMhIGXs72kJZkJ3Urhr0ndA1uuCRqlC+Ax6rzrzAgRg1VzVfk+lpSBBfxxzA8+XViG4TiEzLoOjbwNMssbzFIx/WBaKe6XbMYVrgVwUZ1fsVcWKq6uj+dTEZnUvX3rworF/pbnaGpY29X0pwSKK+2HMitoX/cAEJ0rTg4NcbGGi03bbZhch4l7+0dx6UjIH/itw4Qewa6lYgs1nLmd4wyOEWK9iAlcMo5lmrdlHyF9QVZGMuzQgHF+Z2+vEMgkPJytxfeL4hrzp/ofbfLGev0cKAJOV0xvi9v8h5AkCcdm7RSsPz4witESQoil9fugmwgz41VsL7dAGiiujrVLpoTRZyIbBjXGIL+qawGqsAo8Tn30dEGzNlZnZ/kpcRF/DPYF+1DdzVl5ITDl07bja/l7WJ71yHk/t1XKMK5lD+jek90/Gc+IP4wnZevxRsOLgKGN4kHOQahV+bHWZdWJ/3XrvpLzSqFuqIa1XHLq33AuYdVDLuFgXZeF7KKBH4ANdLlJh3GDZCcu8mi/rgLnGo563hYqTo2chIGfYh6fX41JEOsaOI9c1PaVPEaiQWLHJvuy4wbPXvf+SMjO+CO2APWUkWCS+dnvIVZxDy7Wtv25EmirQzCXj/Jy83YGESbSi2ubTxUL7QjnNhRxF23AVsNk/Hg4m9qHEUJIJ1DQPdD2c7cUF+uIJHBmt/t170kpxTxe7DEsCW87Fc0983d8KX8fyyV/4UB69wLFhMIaTNSJq/mqoeJq17ketvobv8tfRHKC+Li6c/KhyBH3jNZ7TQGkbad0c8FiRoVv+QFWVK6r8g//jhjFcnxp9y3k0rb/Swr7W/9SvYJdiseRHf1vl++L9A12mVvZFo9rmta1fyWeR4XTGDbUZh7EQJcUdwweXBU0nBwS/7P7lp/C8ygIuhZf6C7BAcu0KibnEIqnLVmyhF1MKaT27r+peHhtLB5Ze/bWI9K+oupGDNOngOeM8A4Vazqc683GF/Gf4klw2eZtIVnbqMES/R5M4+PhbnPhfuxLR3vD3kqGvMom1jqUEEJIxyjoHgBissqQbXSHRmYH+E+98C8MEVfDJ/FJXd7XfTIxCv58KfScrN1UUISIQekEPgVHksX+n121L7kIM3mxfZckrO1VsJHqaIzj02CXt6tbfXyFCspjNNHntQo7l23Lvu6ZfCwiuzGpIMvewyq9Ozm33aalldYphB11mbTC19+rE3vXnWBj6+COJ8kkQ8Sfu1RGD/htBdq03exY4TSWZeS0x+HSVXhTdwN2ltqw4orEsoQ2Ydu2bWOXzrYME16Xnw7nIJTLw6L0l3EgRWxFRTqWknQCzlwdNJDByu/sgpqtmpRu7KirMe+sU2lpAd6Vf4Gf5G9C2c7k75ms5BLcPtoO90r+ROJ/P5r1sRBCyEBEQXc/J/Sljimox93ax1G0PAlQOV34l7zHQS9RwpWrRUmGePJvCqFwimeJuBKs9ZsOKM7ZY93KOQhNNmIKtjptd7eChuLEvbDjGtEsd2SPvy3Ww8UgeLoxGseyul5Q7VBKHturLZCFtr2qzgRMxxGXK/Gc9k7s62JKe32zFuGN4gq+80jx8bdHGSzu8fWkft39WlJ+BUYgg41dh7UzYdXCbdxSvK6/Be+or+h2i7++rEmjh1/1ETaWh4rF0trjZqtEiJsNK6pozhaBpG1yuRzfffcduwjjzvjuYBbUGg2+lb+DqyT7kLLpLbZnn3Ss5uQBdiyyHnqqO8e5dCoPduRqi8x738ViZ4xqzh6QyDr1O7dZR+Jp2VosKP8J6SXdLyhKCCEDGQXd/Vxcfg20eiNcbRXwc24n+D2XVAGDj1goxafmOKvUbWoV8WmcuPdSGXF2T+lzycLFleJRzce6HDQI+8GFFG6BIXAe6xXaFi500anWYYeSs9BVFQm72ERBrdILcAps/4oyKzTMfwO7DWOwN61rBc5OxB6DF1cBDaRwHzG3w+v6jhUzB8KNGcgsKIY51TZr8U9CEZ0Y94DshEOw4jRsvzbvGtrhdeUeQ3HC5wYkG/1xLNs8lfn7ouPZ5RjFpbGx04gLF8KcPcQas/gTOJkoTlgRy5HJZLjtttvYRRh35r2kJnI13FGF/NEr2feua16Pjfui6GW6AGWx+BxpvCa0ex3Ozosd5U0lZn0+myrEgmg1so4zrs7kMO121j5sGJ+DPTv+NOvjIYSQgYaC7n5O2JPtiipMCHA0qYeqbO4zeMz6dazVz8VxE/d1704txV3ax7E29ANg2NIOrysNFU+gZ0lOYF9q1wq/7Esrx2w+ho1VER2sBjsHocFaXFmvT97V5eI/TiVigK8LmM0qo3dkcqAz5BIe+VVNrHK6qarjt7Njns1oQN5xOx6Fsz9KJJ6QcgZkR3ft39eeZzbG49410Xh3x0mz3i45nzZLLIpW5jC6zQKE55oQIGavdLX+Qn9wIKOStfz70v9dcG10QjjXrbWf4wf5W/DI+K1HHh/pvC3/7cbL+BJ7lCsxce4VKLcfDhuuGbK9r3W7oOZAz1oLbBQnsx1Cp7d7PZmTNztaq827j1pTVcCOTQr3zv+SlSOqgpaxoW/aj2zChRBCSNso6O7nUjOzcUz5AN7KvxnQmFCJ3H8KlMEz2d6xoyakYgtVxPemlkENOfwnXQbYiPvL2hUwAzpeDh+uHOlJXVvpiElIQBifD4Pw5xrU8WqwNFxc7Q6vO4SC6ibT7yu3CiOM4oqbw4h2KiifQSWT4GavfDwpXYuDiaa3DnMsFgN8feCcTl2/3EVcAdFnmW9fd0lWAuwT10CFZqzbn4jCnHSz3TY5m5AN4VTRUoCwvWJh55jirsfVkj1wT18/YJ/OyPQKNEMBt9GLOjUR4TRc3PYxXB2DohrT/5+TzhP2ccfGxrLLhfZ0C9sE7KM+ZuMyz9ng7T3hcMV77Oulxj1Y9+cWeurbkZiZh1Be3PvuMrT9oNvGWWwraa8zbxcLrk5MV9damxB0CwVTFzzEjvNwDNsOHDPrYyKEkIGEgu5+jLXRyhNXzWRK6wuulJ5r4hDTV9DiC2pQ0aCBjUKK8QFtt7c6i1yFZi8xuJAWHDa5wJnwb/wri8Ns9btIm/7eBfesK4aKgfIcSSz2dqGiqlBl/SrNi3jP71PwwR0H+AzH4aH6D3G/9E9UJeww6b5ySqswSieubPiM7zhNv5VVaMu+7qrjZiuslf/PB6yS9mHFA9gpfQgV61eY5XZJG891VROGGsRsAvfhnZtoGSPPwzuyr3B983qUtLT0GUiE1U+hO4FgWpBLp35HFSbu+47gc3A8kSaJLEmoWD5mzBh2uVD18i17InGRQZxIdF/yHDtK/SehLOAyVpF7TNJbOFlMe3/bEpNXg2e0d2KHw9XgOpjMdnD3Z0cXYyVbHTcXWYO4ZYmzE1fSO4tzj0Cx0wSWgaU/8g37zCaEEHI+Crr7sbTS+lNBmzzoAv252zBNno6Xpd8hqHhbp1te7U0uxGb5/+F9x98g03VuZd16yWtYJv0UP2qEVHbT9qUmFtaivF6DMpkPhsy+9cK/4D8NDTJnRBtCcCTF9H3d+9PKoYcEPiNnAQrbTv2OIUgMANxL95t0EnTwZDHe0N2AfVZzofK5cEqtwGfMIqw2XIp3NZfjZEn3C2s11dcgrERcfYoKehC2aMSIhkNIPSKmvRPzis6twkXqt/CS3ctQ+LVdEPBcqsAp0IOHH1+G+OSW1oADyLGUHPwpexbv2K2Hm3Xb9RrOY+OGUqsgNqxKbLufMTEPYduSl5cXu3S0hUmYUJUc/ogFX4Uu0yD1OV192/XyN6DhFKzexpbfvh3wlfi74nCBFr/q5yFn3LMdXs/GzQ+/GubjK90lKDVjlodKLe4RlzmaFnQLHOc8yI4Xa7Zjf5K4N5wQ0jP+iC3Anyeoh2Z/QEF3PyasULf25+YD2k9Ha49LZQxule7AEv4wonOrO/U7pYm7MZrPwIzG/1ghsc7gPEciKHTEqSJsptiTKq5WTwt2abeH9VlkSmTcchz3ax/Bziw126NtSlX2uHzxeZgR0rkVN4HDSLFP+QwuFkdMqKa8K6Mea/QLED/xnU6l1ArkTj7Y4/8g9hhG41BG99MLE/75GjZoQh7niZk3Po1jzpey7xt3vAijgaoNm5sw6VQLa/AhCztsi3UWpR1KrILZsCp5Lwaa4rj/MILPxlzueKerJgu0/uJEo13RQQriLEilUqGgoIBdhHF7th2MxhK9WGvCZfE5gaO9D+qnPoXX9Lfgs/wh2EV9nc8iTEIIE3KCsf4dZ5BxCht8YbsCn+gvR3Gd+fbIf6y/Ck9o74E8qOM2hm1RRFyCCoUv9hpG4bdDyWZ7TISQjuVVNKDst8dQvOFxVNQNvEy4gYaC7n4sKSMb4VxL/2t/0z8oT/frTsbxzAsHw0KV84AKcS+xUQga2qki3paZoWIQu++kaYFiZfy/+EL2Pm62i+307wz3doSztRz1at2pE5nOiEwvYStun9p+D09559+8uIAZ0HJyeHMVSDpxtFO/I0wGHMoQA/RZoZ2vFttavE1wOLN7hbWEoNo56Sc2zg+6HhKJBCFXvYpGowLhumQc/Uf82WA+Ed6RVIJSM36QHc8R/x47tTXjDM1eYrcBqyKxrdZAYl0gvqc0+piWreMyQuyMMFoXh6wuFDEk5iO0A9Ps/wgKTodihzGQB54/Cey04DFIpj4AHaRYtTXZpAnRgS67rA4XN2/DSGkeIjwv3IXE3U6csCs203YTIUNrT1MgNuhnw9knzPQb4CVouPMAVuoewF8Zpn3uEkK67uihXbhL+jfukW5FSmoiPZV9HAXd/Zg+O5Ltk2u0CwRsTSt+wniMgkZqw/pfl6ZfuPXOvtRSzOPFIlBWEeLqbmfNVqbjK9m7WFr2ZaeDGGGvZ2DFbiySHMNYfef7ifM8h5khLhjCFSEyqfPFzbLiD2I4n415hkhA3rnUckauQrWbGBRxGZ3b133iZBaW6bdjpKoKwzztOn9fQmEtP2tM5+Phl/lLt/bPJR79D4GGbDQZ5Ri2+H72PRcvfyT63cjGbsfeRrPatHZyA8mawzm4+8fjuPvHKLOspApbOO4ufxNPSX/FBBfTqvw6hs9kx8CmhE5vBbmQkyV12G9i5om5CcUOR6jFCTXnkWIQ3VmK4Bks7T6AL8GJ+DgLPULSGX/FFaKwSYYGKOFw0TPtXm/F3GC42CiQX16DX/aJW6MIkJ5wFK/JvsWvspehkFz4tCzAWo8QLh91ZeZJ5S6tFd/nFVIe9ladzzY5k5+bAxYP92Tje1YfQFTLBCMhxHKMiX+cGhdmJNBT3cdR0N1PCRV7Q5rEQFQWJJ6Qm0wihdZHLHLmWHLhImdJCdEYwpdAz0kvWEX8XPZcIxZKorCYP4wDJzt3or//ZBnmtLQKsx5uWpD/VNVL2K14DJqkbZ3+HXn2Hnas9ZzKnhtT2AwXW5mNbDyKvMoL73UvjPmbnWR9IXuXTRKYYoSDGmvkb+BJw7c4mStWnO2KhgNfsmOi8wLYO51ebR9xzQuohi2GGPMR+btYiXiwadTosOm/fdgmfwZjCtdiTyf/ZjuSkJ6NKyQHcJ/0L7jadm5rRivHcLGAnpDZEpfekt3SDTV1jfjy8/dwy+rD+KsX94JFxycghC+AARxUobNN+2WFLf4NX4UF6rexo1BuqYc46AnF066++mp2aauQmjDx9+nuDHyovxK/Tv0byvCF7T5nQgHOtyfU4x/5U3DY+wLLniJAY/pB9jSU2I7oVAbZzVWfYIfiSXhkbTbL01dWko+rJHuxyCbdpNaj53rrqpFY7KfD78aV+GP16zhswnYrQohp8isbMK5hHxs/qrkPf9SF01PYx1HQ3Y/3hu4yjMEWxRLIhon7cLui9UR3IhIRly9WEG6L3mCEVZa4ilvvObnTRcbOah3GyVgxqJTEzqWKJ8cdY63GdJwcGGLaxIK9v7iHPKzuUKcqPudUNGCEWlzFtx9u2oqbwGqYWDV9CF+M/akXDmKUueLe3AZv0wvgyZwDUCrxEPt1x+7q8pt1ZU0tDEYOrnMfOPux2Toib/gD7GeZqXEoqxt8J8bfHczGA5pvMYzPwdPSX/Hj9iPdXu0uSRTTqEvlvoCNaVsKhEyWMpk3y2wpTD6M7jr0+/t4F+/hB9lbrEe78PffG2qSxCJoJTZDWc9fU7lOvh5pRh8cyqykqskWIrQJ++2339ilrZZh2xOLkV5aD1ulFNfMHME6OnRk9lBvBPFFWMbtwa+b/7TUw+5XbMrEzx6Dz8ROXd9gI2a2SRq6Pul6puaCOPxP9iWe0H3VrdsRJlU+HJoKf74Ur/BfYcf3r+BAmnlbmxFCREcP72MLYc2Q41/DeMTmVbNzddJ3UdDdTx3PrkSkYTiORzwHhIg9a7uCawlmhaqyxzPE6qVtic2rwjSDmIJuM6ILQb7CBg3uYo9pefbOC54gCz9XZosn5HVCkC+3NunurIaJK8+z+BPYlyK2QunI4eRsjOXE/tyKsC48n85BWDt2DaaqP8KetI6L0pXVNmN4s9iz3HWM+DhNVekqnpwZssT2PKZacyQP92kfwYOea+A//Px6ABGXPYqHHT/BKvW1eG+H2OJqsBAK6h3cux3zJGKWhZLTYmbpT6ydXHfw+eJ+7FrX01WdTXFs4vsY0/wFNlaJVbu7qqisAmOyvmbj48rJrPbBoz8fMbmdn1l6lhdHsrE+wMRV7hajfB1gLZegqlGLZDO0ovo3NhOvvv8BDqQUdPu2Bgq5XI5PPvmEXYTxua9h7PbvMZlPwm1T/GGnvHBqMu83AeWBy9h48sm3kVjQuSKeA1VNkxYhGnEvpsvQzk3CShzECuPKJtPbYrZFUyn+vTfITZwMbINs9hPQTRIncv+P/x4HfnwRu6lwHjGDpMJaLF31Cz7Z3re3piQX1eKb/Zms1oUlGRLFTJdi12kwym3YZ3lGWfe72hDLoaC7nzrW0nprQkDHfasvyH0E1FI7VBltkZ7RfnC1O7kUGQYv1EicIAkXV3VNZd2Sgj1BG3XBE+SkolpM1IlBvu2IzvWwPovvJDRLbODE1SM77sKBaWXCTsg4Paqs/ADHANPvTwhUx86EETwiMyo6LBIUG3uUFV3TQAaHMDFt2FRWLRkK3jXHTZ7ZbNLosfaYmKK8dMb4Nq/Dy5W4ZZmY0r/uWC5SBlFv3S/3ZSCy2R+vqp6Gcehl7Hs3SHbhp+2RXV7tFl4jz1pxO4gqyPROA4KQkVNRBTvE5FVB240P85jf3oI7V4VSiTuuu/f/MNsqAx9V3I3Nv4jbDXqK0PKuUGuNUqMj3Eabnl0ikEl4POQagw9ln3S6iGF7csrrYLfpJvxfzYsw/HI99iR2P41/IJDJZHjggQfYRRifaV9iHu6q+wxr5atwj4c4adkZLktfZy3EJvAn8e+GL/tl9fnEwhqzvC8mnTwJP66MbbFwCJnSqd9ROvmwo43WPDUZDDVidpZa1YXaMOfiOEgXvQbdtMfYl09L1iDm5+dYRgQhXSW8R/y14Vts0t6PwCPP9dn3DKEo4ZrVH8Ln33uwKdJykwPFNc1Iq+ZQbHSE4/ir8abtBrZtJydOzKgjfRMF3f2QUEjJqSQSE7gUjPdpv4VLp/A8Mq/fhxmaD/FvgbLdAG73yTI8p7sTOxfv7XJQKg1dwI6T+WREJndcACYyMQPjuVTx98K6cEIukaLJTwxo7fJ3djjjKPybHYvFNypdF1fcBBFedi1V07WIzmm/snhd4r/sWGA3hhVh6wrvUWJv8AhjBlJN3Ne9e/8+qBqL4ONohXlD2z/JEiZ0lozwhD+KsGv9J332Q86chCJ/Qmo5wGHyJXeAu+ZHaLwnQ8FpMb34p1MV502VWlCOEUhnY/fhXZtoCXK1gYNKhmatgfWv74r03HxMLV7Dxo1Tn4SXsz1eDMtj2zgWZryG/cc7X7Cwuw6ml2OV7mY85rsW8sAu1qUAsNi4D0slkdCd7Hq/buE94K8f38NkTlxxnMmfANbdjB1xFHi3R3g/SNv+KVy5WlTLPWE73ITJWHtvNE8SeztfXfUV/j3R+YKXfcHRrEos/eQgLvvkINJK6rp1W2XJ4mdPkSKQtQfsDFtXP3Z00leY5X25NU3daOsFsxAC7wUvQD/7OfblSsl6pK19Gn/FUgYJ6ZrdSQV4qupFtsUqXJeK/Crz9ag3px8is1HQyCGYK4Ax8lOL3c/fCUX4Un8pHnRfA/vx12KYrAjhfB6as7q//YxYDgXd/VBMbjUel67FBsUrcM/7u9u3FzokgO3FqlPrWFrMuYQ90cJJvrBVb2ZYN2bCXcNRr/RgAUxl0u4Or5qQmoZYYzCqbYIApyFdujv7keIK+VRDNNvr0h6hN3eu1hFZ8ILTyK6t4guEgmgf2q3BEcUDSGxn1U1Im3ctFYvmcMFzunxfUucAlEnFfd05MZ3f1y2coLkcehX7FQ/jNf9YSC5QxO35CRx2yJ/AnRXv4VD0wK8Q/cV/yZBo6zDGzwHzh7qxk0f5/Oeh5q1QYbTDhzs7v5p3puyEQyxNvY63g8Q1tMt/X8847MQvslXIOSEW/TNV6u+vwYFrQIEsAAFzbmffG3LVayhUhcORq4d8y/0orGrosaBbMD3EtdN96tsiCxH/H3lWHu1yBoCQCvhx6UisNl6Guoib2SrsbD4W0t9uxvbYHPQlQsX36746hFu+PWq2SvYdMRgMSEtLYxdh3OpIWjEW165nY37Goyb1WBfYzX0MdXI3NuGTs+VttkLUHxRWN+H+n6OgMxhZRtPz6w93K41Ukn+MHevdOr/txMFDDLpdUY3qhu7X3LBqEreWSe3FtHVzkcx+Evp5L7PxAu4Ynll3GBuj8816HwPVT5FZuOzN39kEz2An/P9K+Ess6lpmtMOlmtdwvIOFjd7cmvbZngzYoRHBfCGmNu5ESpFlts/8HS9mjiwa6c0WmYzeYtaiTZm4LY70TRR090MnMvIwnMvuen/ucwiB1zh/R/Aw4Fgb/br3JRdhFJeOUd52rN1Ll3Ec9CGLcMQQjuSSRlYhur03ri2FNrhK8xIabu84OO8IL/QSF6px89k4Fp/c7vX2p5XjM/1SvB28BpJw06qknytEVgZ3rhrGtLZbhyUVVGKUIYWNvcd2IW3+DJUu4r5ubfahTv9ObFwMxmujIeGMGDvjkgte3zNkNArsRrGJkpq/X+5WWnNfx6rOR3+HvYpH8XZwwukqvkNmoGp5LD7H1TiSVdmliryF+dmoMNqi1GH0BQtNdWSC5CSmSpKgzzQ9hSwmKRVzqn9nY37+C6erJEvlcLn1RzRDgUlIwM7Vz1t8L5rwd5SflQIOBkwLdunWbbmNFP+fj0cS4nJNT7dNLa7Du/+ehBpy2FzyGmyv/gSSG9ezwHsOHwvZxluxJaZvrHgLk4fCCuvhzErsO1mG+9ZEW7zfdVNTE0JDQ9lFGLeK+/sreHGVqJU6w27yrabfsFwF+cWvsqGfOg2r92eirxMmBl7/fiOa6mswwk2OVco1eLf8Xny360SXMyxerl2CGzXPQDrxrk7/nsLei7XLE7ZECZXHu8uuJU1d6SKmrZuTZMYjMCz9DBuGfYJ6oxKPbTiBtUf7xv+nvmpLXCFW/7UT3zc9hL0bPhr0xbE2H07BDU2/sOfmgPddaIDVqS2Wfck3uxJQ06RBpstsNPLWbELx+G7zdBg4U2ltM3S5h9k5+6LhHux7LuFiLBCoSWF7u0nfREF3P9SQdpCtcNZbeQMOvma5zac1HyNWcQ8qUs7f/5wbtxt/KF7AN40PCUul3bofu8vfx2PWb2CPbjiOZLY9U7k/vQxClnuImw28ne27fmc2rogPfwR3aB7Hjqz2VwNaq6tOD3HpVkAksI4Q960PrT/SZj/yfRlVmKb+CB+5vQKZl1hhvav46Q/jIvWbeL76kk4HSWW7v2DpWam2k2Dr3YkVV46D87I32XChdhf+2bkTA9UX22PwAL8RzlwdQpzOLhjl4e6Bq8eLJ6Qf7zJ9tfu7iuEYp/4CpfM+6tZjlA0RP1hdK6NNSisVrvv9zmikGn2Rq4qA58Qrzvq53D0MDXNfY+Pr6n7Ar5tP9/60hPicUmzEY4hS3o9hqu7ti+U9R6Ket4MN14zMGLF9SmcJAevnv6yHXq/F3HA3XDNefD+VBM9mgbeWkyPeMAQPrY/D5pjeTY3dGleEn796G6gvRai7DezlRkzP/hivrttj8a0f9vb27NIqJrsc8yvEk2DD5BWATNml21WMvhYHpn2Pe7WP4NM9GZ3qNNFbhOf4zfV78H9Vz+JP5Qv46jJXLFPFsxNrh/0vsckbUwm/U6pRIFY6GgERkzr/ixIpfldcgXe016CkoXuTLkL2lZNBnEi0cxNX0M2NH3Mjnr1mNm6Z4s9OITZuWo8fI/v+JEtvOJJZgZXrTsAaahwyDMNtDavx17GuZVgNBMLiTO3O/8FF2Mai8of1lDuggAZFGfF9ro1v+NFnsEH+Mp6frEBl4FL2fee0DWafGD10JBIb5S/hqOoReNuIk+eOIZNZXQh/rhTJaeJWNtL3UNDdzwgrRE7lYjqawa/7q9yt3BVa2HGNsC46u1gUu798MX2Z9+reKp2A43nMENJJhQA0re1VqaOJabBDPWaHdb+SqvuSZ7DLMBbRhU1ttr4SZgTr8uIggw4zgrt/fzYtQfcEPgWHks5PSxVWp+qggv3opd1KqRUEDhvH9gHWqju3xze/rAITqraKj3Pa8k7fj03QZOS4z2er43aRb7JquwONsC/TK/FLFnA32wcBY24+7zr3zQ7CdGkShmb9yLoHmFLwREgJ5jkOI4K7N0nmPkJMpR5lTEFmaeeD1R1JJfijwA7XG1+F8tbf2vx/7DzjLhR6LWSrZ9NPPI3INv5+zSUzdi+sOTWkEgn47qa08jwq3Ca33LBpafc/b9mBt2qewiblK3hrse9ZPYqFwJtfcRT5ox5h7fMeXR+L36J6PjVWeD/+bFcq8tc/hnckn2Kd3YfYeM94/B28GfdK/8JVqY/h/W2WSym0trZGdXU1uwhjwdGt3yKQL0aDxA4OM+7p+o1zHKbNX4axfo5o1Ojx1j9iFlBf9NOBk7g09SmWyeRhr4KnbxCsr/mSneheze/Brz+vNjkTKCpXXK0b4+d4wa0+5/rbYzk+1S9DQXPXJjxalTeosVJ7H57U3gNHH8v1+RW2x7x8WQQ+DE9mhfdUfz+M1fsGbzDZlvTSOqz8cS80egP8h47FdOsCVjOhdMf7/Wb7hbn9+t8RXK//i42tF7+KicoCxCnuwqt1/8eyIvuKDX/+hSX8IYzj0zAp0Akes8TMlbmGI9h7wrwdYNRx4up5o2M4y1RjlPYokYuTZqXJYlcQ0vdQ0N3PCMHVOCSxsU1414t+ncs2fC47jtLGI7P89J7OqJwqzDCK7a0cRnW9H/iZZoW6wAF1yEg50easu2/aT4hW3ItbmsSCT93hZqtkBc4E+9sI8o+ml2Cd9EWcUN4DP5ih56lzEKoV3pBzepSeEAumtWpQ69jzKZgV2v0AXzhJmzjEmY0PdSLlOebv79m+3XKJG7wnii17Osv7itdZOuMsHMcff/6GgeabbQdwh0Ssj6AUUl4l0vOu46PJwhrpKta3e+32zq+oHs8W/u6MCPewY7UTukPuNQpNnBWbIEtL6Fy1biEL4u3tYlHCO6cHws29nWJJHAevm75EtcwNaUZvPPd7jOV6tLcEx5VCsNzNySeBKlwsLBhQe5xV5++MEznlGBP9DNs64eHmDlfX8+tVSJyH4K0rR+L6iX5QGpuRu+lFrD+SgZ4itHF7dt0RBO++D8ul4oTZkKlXwEalgtfip6GWOWAUn4kxhx/BTwd7JoAR6n4cK2hGlsEd6nH3sHaQ3SFMdLx4aQQcUQvnE18itiUQ7UuELSWyf59hJ9RqqQ2sb1kHKGzBBUxD81hx0uHe2g/w/X+mTX4Y437D09JfsMTJ9MkcD3sx2C6p7d7/UWFS8KBhBPaoLoJU5QBLEl7ry8YFCLPvuEqyD647HsTnO9vf+jWYCCnDX379GbYZH8Bt7pl47/qJsFr0EvvZ9dpN2LB38O3VFT5/Nh5ORZwxEJVOYyGLuAwOfsNZpqeQYZKQnIC+IK24FuPTPmDjqqDLwXmMgNRnLEpVwezzpehg989lW5XXqzGiRtx2aTPmyrN+Vus8Why01IkgfQ8F3f1MbEYBRnJiWhYf0LXWQ22RBYsVlYWTiqj008Fn7IkoVhBCDwn4EPHEtrtmNu1ElOJe3F77BVsBPLdV2CTdcfam6hFgnln367zL8Lh0HTJjz98Hm3ViH+y4Jhglii5XZT8Lx0E9RHyeHAv3nrUX63hSGtZJ/g8v2vyBACer7t8XgMudsvGe7DPYx3zR4fWEQMQ/81c2rhp64+n9vJ0kdQ9DcdDVbByR+B5yygdOL8gTedUYk/EFrDgNmjwmAGHt7Ot3j0CT/xz2tzk5fzViOhkc6GLW4rBiBZ5QbOz+g5VIUWwnbktoTOtcj/Yde/fg0srv4GOlwfJZF+jxrXKC4t7d+J/jC8hqkGHl+lg2EWbudMHAWvGkwGbofLPcpsuIhWzFkYcex7MuvK9bWDU6+vNLGM1nsL13bjd+1W4Wj7BC9/qyCPzp+hVWSn+D7Zbl+DnS8ul7VQ0aPPTlNtyYtBwLJVHQ83LgytXgZz8lPlaXYChu+Q1aXoE5khOQ//M4/ok3w8ThBXy6Ox3/Gcbh3bCf4bTgcbPc5ihPFXbZ/B+ek/2Cnb993qc6JQifUTt/ehPXS3ayvzH5Nd+xydVWqkUvod7aHx5cFZwPvmRSG7GAku24V7oFE3lxUswU3lZ6hHD50JRldDvoFni2BPGWxo24Cvy1P0DPSXGZ5BCG7HkQH/yT0Kde854mTMi/sfpnvKx5F/ZcI572T4VSJoF85FWotB8GW64JkgP/61Mruz3hw50nkahxx+uu/4PDXRvF9z2FDQqtxK1xFcmmbSeylC2bf8FUPhFayOB8qVg4UHisknG3sOHo8q2n/p91V+TRwxjK50IHCZzGnr14ohwyCRkGT2TUSQb1/6e+jILufqYm9QBL/6xTeACO/ua7YZdQ1Muc2axc2Zn7ulO3s0Ol6wSWvmIOKr8xLFW5rdZhx+KTMJLPYmNZV1qFtWFR4xaskP4B19yt5xUkkWWLM4a1ntNMDkTb4zJaLJA2xRiN+PzTlSuLY7djLJ+Oi6XHzbK6JxhtU40rJAcQXrWnw9TG7YdjEGjMgxZSBC68r0v35bX0JVTxTtipH4N3/hGzLQaCX7Zsx9WSvWxsteT1DrdQWC34P3a8nN+P9ds7l8psVXSMnZD72HZva0Yro5/Yy9ehTOxjf6HJFtX+N/CwdBO+9fgddsoLV5i2cvbBpzeOg1LGs+yQr3eZdzUhKjUHIzkxUHBuKYLWXZzTEPxf2F+4UvMyIrMuXC32u03bcItanIQyLnqTtbDq8PZ5HsGXPgYdJ8PFkmNw/Ps+/HjAcivLGWX1ePLjH/Fy6YMYzmdDo3CC5PatwIirzr6i7wRIr/keBvC4VrIH6RueM2nrQ2eo1Wrcdttt7JKUX4GtLYH9A3PDAJl5Jg+FFEnZxDvY8Lqab7Alum/s9xUmZz789ic8YVjNvtbPfh5c6Dl/s3IVrK/9igXkV/D7sHbN151KMy+tbcJQnbjK6x5hesu8GVW/Y4fiSUwu+Bbd0VSYhKslezBJ3oNt24ZeCsn1v0DHy7FIcgwjDq7A8xuO4/eofOxJLUVCQQ3bI2vpIoF9gfC38uIPW/Fs9UtQcWo0+c2Gcun74g95HvaXvcGGVxn/xS+d/MwZCIT3wF+PiueHzywZBl7leOpnbHJc+K9X2LlsL0uKyi7HwsLP2Lhh1G2Aw+m6CM6Tb8I6m5uxXPMofjdT1f6m2E3sWOg4gU2Sn8l99nIs0r+H9xov7rMt1QY7Crr7EWHm6pdSfyxVv4Li6WLRI7PhODR6iSfzqoLIUzP8IxrEytg2I7pXafssbsNYqxhhZbEk/ux2V41JYpBfYRcB2HajPdkZnEadbh0mtAdrJXyoD28WU+ftR5gnwBdIAmciVxGMrfrJOJByuviSTYE4K9vc0j/cHDxHiSuFw5GBxOzCdv9uvohuxCT1p9gx6iNI7Lr2vHJ2Xii58xi+MCzFloQyHDPzyX1viEwvh1X+AQjhcGPQEsBXrAjfLp9xaAwQ97dPzP0a8fk1F17VbRaDVsfwGWZ5zG4Rs1FrVKFcLWmzWN+Z/v77T8wyHmVbAwKWPtvp+whxt8UbF/vjQ9mnGLXvbhxvo6tBVxXH/ceyBcrkvuDOOEHpFo7D2NAhp17TjhxOK8b0hOeh4HQo95oL6wk3d+4uQhdCcv3PLPBeLDkKp+0PYPVe01coLyQyoxyXf3oAKxo/ZZM1asdQyO/d3e7fJhe+GMYl77LxCv53bPv+DbY31Fx0Oh1++OEHdvl72yZcx+/EonAHDPXsXE/pzrKZ8yjqFO7w5ipQuO2ddrtb9BThffPZjXG4qfoztl2oMfgSyGY91uZ1Ob/JaB53L6vXUVpZjc/3XHj1OTkpnu3XFSZCbQLEdj+mkDuIE0VWzd37vyl8Lr0j+wqXNYqdDXpM6EWQ3rgOOl6JeZIYhMa9xSqb3/bdMVz58S68+tbruPn/3sPSl1Zj2Tt/4prPD+Den6Lw/OZ4vL/jJH46lI1t8UVi14l+Svgbe33DAdyf/yT7W2h0GgarG9ec1X5PEjQbFR4z2N+gX8y7rGXdYLB54694kl+Dy0KtMDlQ3EbXyiFM/Cz1b4jv1b3uwut3YNOXiOBz0Mxbw2HhM2dfwdoZkjlPowjOWH88r9urz5UNGkRUixMvqtFnp5YLlHLpqfflmA7a5JLeQ0F3P5Jd0YiSBj2S+VD4Tr7c7LdvN1Tc1z1ME8cC0oMJGZjIi4VtrCLMGHQLKdgB4n05nJGCLRToCqwWe1jLhna9X/a5JCHzWNARwhcgJi721PcPJ2ZgVMuKmyp8gdnuT1j5iJy3Ca/rbsSudDEoE9KxR2vF+3Ybbb5/G+8UgHKpO8t+yI1tu72a0F4opbgOBpkNpl10TbfuL9zbBddOEAOlVVuSzJ563JOED0Bhr/P3+kX4IvxbqJZ0biJLtVBc7b6Mj8T6v//r8LqJ6TkI4cSJF2czBd02obNwncMveFK3HFEdtE0R+vd6x7zDxnm+SyH3GGbS/SwLU2CRNJplpBz7+UVUN2pgDopccfKp3tt822MEU4PFE7OTBWXtFvsT+lrHr3uJtRFslNjC5frPTSoOyYVeBMl1a1hq7CWSI3D/7yF8udt8gfe6Y7m4ZfVR1Dbr8YXLc2gOvwKK5f9dcOuLZMId0E57HI2cFVI0Lrj122Nsj6g5yGQyvP3223j2pVWYkPM13pCtxkt2YmEjs5JZQXHxKja8WbcR2yKj0Zu+j8zGxphC3K17EiVBV0N19Zcd/q2oFr2IyIu2YpthMj7amYakCxS3rD0pZpQVqYSMAdNTu1UuYlFGB13Hk0wXwtWJmQs6a7H1UI8KmgvpLb9DJ1HB090DM0JcMMzTDsNsGvCZ/COsU7yKP7ASmxtuxs/Fl+Hl9CtwQ/SNqN/zIf7vj0Tc/3M05vxvDyvA19laDn3JZzsScEnSSlaUsEnlBdXtm1itgHM5LX0d+RJf/KmbxCYcBrpjWeVYWPAJq2PxsuM/5/3cdZiYGRKGXCRnnZ0t2ZN2JpciolJsD6ud8hALss+1eIQHrOUS5FQ0drvneuTx4xjOZ7HzWZfx5wfdgjG+DqyVWHJWzxf9JBfWvao+pEe1riyO9LFn+33MTRk6B/H/DcfepmEIy6rEjvQGrNc8h5XhVZh6xh42c3AceTFwci2mGGLY6rNQvfVgaiFmcGIbCLuRZgzyrRxQ4TQGbpVR0Kb8C1wiVoCuStjBVizLrYbApbsVlM8xs6VQmtBXVwhWYmOOYSlXAQ1kUAWbJ/hqVe06ES5FfwHZwknc+at2v+8Xgn0jrhjrDXvVhdOLL2Tl/BBUndiKa0u2YUv0d7hsfOf+NkprmpCaFAN18nasVs9Dbo24kiXs4Z9niEQ1bFADW1TDFjVsbMPGufBEE+QQwntholj4+3/7qpHwtO9eaqtQ0Vt4faxkElx1yWLAtpMnvl6jUT9kEWyy/sGE3K+RUDAfw73b3npRkiimrRfLfOFh3b1+1KfwEowb4oqkkhwcza7ExSM827zatj9/xQ1IhAZS+F7xisl3wzkHwbj4HWDrg7hLtxZvrZmK5+6+8awK312Zqf+udgLyJTxumNC9CaBzeVpL8KdqFcL0JxGZvB9zxp4/ybBqSzKiGsZgutUxDFnyJGBreqDBhS0Cf+1P0K+7GZdIDuPnnc/gE+NbWDE3pMuPXZi8emdbAmIj/4bOEIHLRnmxv3Gl7Jx08g7I5j+P+mHXo+jXfBSUN7AVw3XLJ8O2E1sKOiKXy/HEE0/gy59/xcy0FLaX0GPuA926zXbva9TVKPjvI3jXx8Mm9Xdg9gUyTyzkUEYFVm0VU7/vvngy3GfccOFfkllh4eQxuCjdgO2JJXh8fSw2r5gOubTttQ15kVjXoNnD9FVugYO7OPnpYqxgadjt3c+FKBuL2VFi306BRUsLmA7pAwexUNOIhR7Dxe+Ve8D4xxQY6kuBxnJI1DVsYtkd1ax6fInHLOTburNsvNyCQow4+CDuirkJd11+MeaEu6E/2HA8Dw17P8Y4mVCczxZWt21q9/2I8xyJ0lv2Yvvnh8FH5+OuGYEI8zg/OB8IhMnw/Zu+wEo+G828Co4LnzzvOpydJ0qlXnDTFaIgfh/GhJqhHo+JhMUiYbInQ/sYPgxNx6Wz2u7ioJJL8VhgLgIz1iBl15WYFPhwl+9zQ7oEX6pXYWVEA+a0EeALlhl24AnFmziUIkxMbOjyfRHLoKC7HylN2o83pOshtxPaUk01/x04BWLTqK/x7cEsXJNejgMZVWgyhsN+gXlXpASS4DmsOFsQX4Tv4k5gjN9s5MbsZAVD6qVOsPEcY9b7Uw5bBByIQnDNIVagyN5KBocicaVBFyAG4ebk5WCFCDc5nMqP41BKKBqTxdnQEoex8JWrzHpf1mFzgKK/4Fsbfd7JV35lPR7IvB93yBVQDf3eLPfnquLxtvJ72KmL8Mnf76Np5IewkkvOq7osrPScyCpG48k9cCvehwna45jBl7Kfr9ZYo8AQwcbeklQskbW9Si+4Rv1/OGocemov9ZzsWNz04V149cbZmBrk0uUPzL+3bYY/J8OSadNYlXtT2Fz0PEpWJ2KnZgy27UrHFzePa/uKeUfYodZ1HMy5jjQ+wBE/Hc5BQpawpUB8Hs9UUNWIESkfQsibLwm7Cb6OXUvjVo6/GTXJ22GfuQU35r+CNftG4+ZZLSfGXUydjjGGoMllLO5vWa0wG6kcbnI1FM06lMftAM4JunellGDd8TxwnA9qbtgGZVDXT86FlG7JtT+h4fcV+EU9F4n/nkS9Wo9Fwz3gpJLDyUbOVjc6M0EhpFE/98t+XJnxHB6XJeHPYe9j2TWLTZ/c4Dg4egfjh9u9cMXnB6EuTsbL35Xi9bsv73JA1kpYNQ9J/YrlxlUGXQE3h+61vmsXx6HGdy68k+NhVd07vWaFQO6/NW9hCWTgR1+FO6eL2xY6Q3jNVi0bAXnmDiyvXIvV/36N+xafP3EgvD/6Nyaw/5/2LamyprJza1np5hqQX1UFH9e2T8IvxFojpqfLnXzQa5wCz/7aJQTcnf/g1KeKTg00VrAe9WgoxxwHX8xxDWM/yl1zP/zSj2J+cxS+WrMTm8OW45nLxp2q7t4XCa1Dn9kYDxiWYIG3BmMW3w24dVw4dqy/My4e7oG/E4rx9j8pWH2buK95oNl+IgfX1HzH/m/opjwMtDNZnR54E75KLEBtlRMu6fFHCbZHO620HvZWCsy8cgUgb39y82L7XHhKTuBAnhF1zfd3aSJUKKJ3MKMCOlEhEoYAAHSxSURBVGMg/C9qf4uil7cfbE40w68pmb3PKKTmX6AjXUdBdz9im78H10t3o1gttGjpfJ9lU0wc4siC7k0xBdDqjXCzVbB0L7NT2qPCaTRbfdal/gvjklnYWGCPHO2duGu8N2zMVGislZ2wJ/3Aa6zC5H8peRji4YIvm+cjR+aCBydfB0v4Tvsk3OSZ+CbKBsEVh9iHiDTUPBXgz+Q+Yi6wR9zXHZdVgHEhp0+I9//7O64XUtc4FayGiBU/u00qh1JIsf7rftys+x0/7boNl0yOQExuNaJzq1hVb2NhLFZwG3Atn8j27jM82Kprts1YLB8ZhifCp0LCcbAptUJxcRAk6mpI1dWQNFdBqq5iXwvjd66dA62z8Ng5WB8+Ds/oQ5ioT8HDq1cgYdHluHtGoMkByl8xWXik7l14KSqg8flZSJw37TnwGIGaOw/izw8PwJhYzCoWCy3Bzl299KoVtxRYBZl3kmyqKh/75A9DXS5HvTruvFZkO3//Grdwmay9mM+lz3f9jjgO9ld/gvoPj2NIczGidz6L+KCfMMKna0UVD6aLre26OllyIU0+04H0DFgXCBNqp1cUhIm2t38T0tpVuGPaEEwONkO9iPDFsH4iHpceKkbi3yn4e99BFO9PZxkbVUYb1EvswFk5Q2btAGcbBRyt5XC2lsOxJSgXgnNbpRQ/btuNpytfRLCkEDqJFS4f7WlSyvu5/JxVWLtEAdfNL6GmSIVX1znilRvmdDlDwWAw4Ptff8GN9cehtZXA9eKnYUnW3sORk+iGvGYzFWkzgbA/9KNvv8cqwzeQyfVQj1to8vPmqpLgNZvfYFeXjaxDLyBh1LrzMmGS8srgBTH93G1o1ya1OaUDmqCAFdSoKs7tctDtKKSnc4CNq5nqK1iCVAHYeYmXc/hd8jR0WyogT/+HFUzNTYvEi+/ehUkLr8WtUwNM7n9uacJktJAWrzMYcdkoP4y69jugk4/x8flD4JnyA+ZkROFIxmZMCup+69EzMykLqpqwbIx5s/5MISwaZG57H4u4clb3x3bWQ+1e13rGA/gm7iAcCmV402BkXSZ68n1i5/Y/oIA3HpgTfsEMQo+ZdwAnPsZUxOOvI9FYOmuSyff5b1Ix+5sJ97BFoGv7bRrdhk4DtgEhyEdCTiFGBllogpR0CQXd/URFvRrhzSdY4GJnxv7c5xof4MR6aF+NvfCTlqLJe0m30kk7wk99AE9sOox9FcMxIqsSJ+uVyJcvxEuLzLi/upXbMNTK3aBVNyE1MQYF9WOQavSDT+B4SP0tM2Os850GnMyEKnc3yow2qJHawH20kKVgXuK+bg+UaBRISkk9FXQLe9xcU4SAEigLuhx+3eyneyb5mOtQu/cD2NeeZK1MHts3FjVGayQZxTSvCA6YpxD7igrFkRr85sJ+1BJYhcxBqMIGZ4X/vsL+fnGPf1vOqtE//jIYcv6CR0UafpGtwnvbU/Fg7nK8efXoTvfAFj7Ys//5FMv4UjTKnGEd0rWVplAPeywe7smqOX+8Kx2f3jD2rJ+nl9XjsC4UUokWQ0eYN5vC1TsY4MUVqsMnMzF5xOlnVJgA+CrDHtbSGZg6YQI8bbp5YmblCOvrVsPw/aW4kt+Ll376CAGPPt2l2XrrlA2Yw8sxc4hp+8s7y0Wohp7+A4arY1iRudYMhq/X/YY/tA/hN7tluHLh5+a7Q7k17p0VBEeVDKV7DuHBBrGK7SlaQFfFo7rKBo9rl+Mvg5jBE8Fl4VLJYdQblXhL+g+c+TpoVJ6Q37we8BzZ7YcVHBKOJlsn+NXn4erUlXh/27dYueTsv8/OpHlmlDVgf3I+nrr3TjwlVBT+7GoEugTDklwmXIGILdZsfEmjBg4qOXqC8O99c91OPF7zOktlbgxdBlVwF7IxJFLYXvsV9N/Mx6WSQ3j1588QuvKps7INovIbcbn6U1wXbMSbdm1vD7kgjkO1xBlW+kLUlwn7Wk3PDqtr0sAN4rY1R4+eT9E1Cwc/SG9cC6RshXbL4/BrKMKXeANbtu/G7VH34fErZ2Okj2X7j3eWUARtzer38aQ+Hn8PeQTvXD3SpGAxyA54Qv47rAz1+OCPLzDx0efNcn72d1whote/Bl+UIMP7WwS5WWChpRN+PxiPG9Xr2SSQbMHzrD5Oe4Z52bGtYdWNWlbpXCj+2VPW7z6O9zWvoE5pA/th7WfpteKcA1HoMB5e1cfRcPRHoAtBd+Ohb/CWNBbwu7Xj+7L1QLnEHS76EhQmHsTIIMssKnWFoYcnR/oiCrr7iejMYsxsLfoVar7q1+dyMVQiWnkveLaDFijUKwDcYZn7Gn8lovY6o6SsAW/8LRZsmxrkbJl0GI5D2pINuPrXPDjlKhHWklI3PcQyK26nWoed/Akz+ROYrv4QByM88IGn2GPZrDgO22f/iee2pGNqsc2pXd3/HorCEuMx9gHmPX+Fee+Tl8B2yavAr9fiTunfuBN/Y6diLvYMfRVj/R0wxmcWjGlGcEFzYOsm9Bk10xut1xjw9+yBcdtjkJxYiydk67EvNRm3ffw43rp1PoI6mAFutfFwMm7WrBMzD+Y9y/p+dtVDs33hmPQjwpLzkVby3Vkf/Mezq/C27jrs83PCWjczZRm0snZGsdwfHpoccd/4GUH3O/+kIt/oip3hL+PKS00LtNrDBUyHesojqDv0PVLrFLjnxyhcN9EXE4c4dXpvfV5FPe5VfwcXeS0aFcJER+fTdjvLNmwW23Psx5dhR1wsFkybjK3RWViWvQoKXoslPmooO0gD7CpWXNB2CnA0HmishKGxEmiqBK9tZJXaXVCLaycFIUIZhMoGLYYVHcfNZaeLkandRkJx03qgqwHYuWzcYHX7H1B/OQ8jNVmoPPwIfnJYjZunhXTYuiixsBbHsirZqtfxnCq2B99GU4HWeNHtorard5uTtULKekYX1TSzoH+cf88E3T/sS8Wyk0/Bla9Fg+NQWF/1WZczDjifcVBPfhiqw+/jvobPsHr7HNy3ZPKpn0flCAUQOfgHi9tmuuqg0zJkFZbDX+8EsfeIacrKihHIiUUHVc69mF7eXcLrNPQSyAJnwbj7DRiPfMHqLVSXWWPppzLcMtkfj10U1qmWiZYiFHd89+tv8bruIyikOlw18mIopCZmOaicoJ/6MMvau6rme+yIuxkLR3VvsuTfhCLkbngKz0n/ZF8fSz+OILf2J8EtpbZZC80esU95lU0IHMfd1OH1ZRIeC7yaIck7jOREe4S4m38bZHtp3vLId8X2bg6hUDp3LkPEZsrtwN/HMb1uO9KKaxDiYW/SczOybCvGSNNQai92rOlIpeNIuJTvgDZXqBvR+0F3anEdPv43ASUpkVh2yVLcONWyE7d9Wb8Put944w1s3LgRKSkpsLKywtSpU/HWW28hLEzc7zNQFCfuZz20a6XOsHO24B+snSeqZR5w0ooVTR3GXGa5+xIKjoW4IrOsAS4FO3GrpBwj/TpRsKaLRkSMhJW8GOX1GlyWtQbOvD1m+psnKGmLPHgWtJDBhytHMFeAGaGju5U22pFJoULaXTo7mRP28cglPOoiV7MT/kKHcfAysXJ1Zys56wJmQ5q9B0aVK+aNGoZ5F52x39fVzIF+K4UNuMu/BAJmwrBlJWYiHuF1D+OuT17A/VcvxqLh7Qcuwup/46534czVoUYVAPsJt3XroYTJq/CK7Hs2SfXO31vxxG2nP+CO54grSOP9z+6laS51bhPgkZ8DSf5hodwT+96RjHLsTCllKZWPLwwz69+bcv6zSAm4CUd/SIU+swJVWTHYxFWi2H4khgf6sQB80hAn+Dmp2lx9SYg5hIu5WjRDAdWQ0wGIWSlsUWQTAd/6ONQm/ofSEaNR+ueLWMIXoEHmBIerPoTFhC8RL2e2BdE2s+BbCMQvdvTHxa2ViXMbgSS1+DM7byhmrGSr5mblHATFLb9D++1izMYJbPhnJf6x+wqLWgrvNah1bEuIUIwvOqsM6rwYjDQkYQJ/EkL49a/2USikPCKGhGDXG2Nh7z8KikDTV2i6ItjNhgXdmSU1GOd/uj+vpUSml8HmvycxWpKJZpk9rG9Z2+3XQzX/GdQmbYFLbRr8Dr+A+FEb2LYMYUVdmNAQdPfflux/M1bnZWG5tmup5YWNPF7QPIMIezWeEVK4+zuFLbhFr4MbdR3U/76EFOlDMMY34IdDOdgeX4DnLxuBJSM8LZa91x7hM/nlbzfixfpVrFVhU9BiqCZ17bPHZuYK1B39Gj6aUvy59UPMGf4uC0C7YndKKVLXPYsHJWLALWgqz0Fv+HJvBjY0LYSLbQMuunQ5m9i/kIe03yJYvhd/Cms2c3sm6F67fTfuMP7HJu0dhB7qnfxbshtzBZr+eZJNCK/Z/QdCrr+l0/cZGR2LRXwaDODgNuHCxTUl/hOB8h1wqjqB3pRZVo+PdiRDlfgrnpVugpe8Eut3RsMwec2gXfHu90H33r178cADD2DChAmsn+hzzz2HhQsXIikpCdbWZj6J6UWSPLFfdo3bRNhZ+APDaO8DlItBt2qo+fpXt2WBjw685G+8IPuJfV2tF5KJLXNCLqT3TQ12wd6kfDwt/YX1vTRKhArKZlpdOu8OVSh1Hg/vikOYzZ/AjNCO04K6Q1jhdbFRoK6+DrHZZazK98Lmf8QPhpn3WeZOOU5M66vJB+cUBJh5H/4FjbkRvPc46NbdgoYaHVLrnXDvmmiW7vv4QiGt+/zH89ueo7he/xd7XlTCSr2km2+BrqGoDV4Gh/RNGJvxBTLKLjm12l6VFQsr2GJcgGWCBpvQ6UD+b/Cti2WrlFKeQ8Kmt/CxLA5pEQ91uO+rSyQyjA4Lwsb7nLElrhCj43/BkuYtMDRySIn3w7EToXjHEI4c65EYEhjCgvDJgU7s+RBOcptSd7GbKXIchyEWPMHXBcwCEuJgX3IIX/2yFs8Y/2Svt+Lyj9lKUY8SWkHJ2tiL6jdJvFiazzhIr/0ehl9vwNWSffh0wzN4PuMxxOXXQFl0FFOQwNpCLufTYS1Ro7VylY6XY+Pt4zDcz01Miy77BbDkZO85lmt+xIeKzTiWeC8wUWzRZyn5VY3Y//MbeEqyFwbwUFz34wVbtHWKVAG7676B/qs5WCI5gtd+/gShjz2N0upGrFWvQJrcFyOduled3d1O/H9U3MX2cEX1RhwwjADnYrmMr17hORKKWzdCaEB3cXo5nt8Uj2drX0X+ehfce/Q+PHf5JFb7oKdSalet3Y2Vpc+yVdxG93FQXfdtp4LKNslVkAkZWn8/guvV67Ex8g5cO2NEl4q5xf78HB6VbGRf10scYKOvhrZabHHZk4QWtd/sz4IajpAt+xTSsM6VHeX9pwCVe+FYEYWeepy+Me9CxutR7jkLLoEmbE2Tq1Ax5FL4ZK6F08n10Opv6vRkSXWU+BoV2o6ETyeyoTyGTQeigFBdKsrrmuFiYqHY7sqrbGRtE4Vic8OQiS2K1ad+tki3C8cyijAppJe6JfSyfh90//PP2T38vvvuO7i5uSEqKgozZ5q5Om4vEVbnAupj2PKJtQVTy1s5Tb8D2HwMOpehkFpZdpVhHJ+OaS0Bt8DBnK3C2nCP/F98rXyLjeskjrB1t0C69xnsQmcAhw7hednPgELsmWwJQlDzhdWnGKHdhy2xH6CkvAKTuWrUSZ1hO3Kpxe5XaJMjVJrtNW7hkC7fA5+GCtx8sA7fHMjCV3vTkJObjVU3zmEFrM5M77OOfJsVdit3HAOXYZea5SE4LHoehk/+wDxJDN7f+hceve16lNU2453G/4O9ogHNSiHYNH8bG/fhc4BdwDBkISWvBCXVDVhW9yucJXWo9el8qylTjfJ1YBdYj4AhNhF8dRaGcTkYxufgVuxg+5hzk12x5MQbqIOKFQ+bEOCEm8oi2e9LgszfLeBMHmMvwY64Q9ijDcUdhW9CwhtRG3ol7Ib1Ro3b3seFXQzDkveArY9gPJJx0+FMaCHF17ItWCA5fbKqV9iD95sMzn8qpH5TMNbH9fREWkul6J7iYCWFE1cPaVWaxe/r8Q0nMFVbwc6G9PNfhizIjDVTvEZDM2UlrA79D151J/DxznSMVRZiLl8EL64aSpvufb56qYwI5fKgKK/u0p7ukpZg3cOu71b67q5pwS7452prKL4X/9YX5x3B6x/chqmX3oFrJ55VMcQifjuUimtPPgYfvhyNtgFQ3bJB/NzsBqGrRNW+j+DYkMkytxomfsO2ZXRWZHo57v7xOFZALHKqn/8KfqseiW8OZmOmcgTMX+61Yx/9Ew+1zoAJAY5YMKzzRS49RswGYt5EhC4JxdVN8HCwbPHF3/74Ew/yh9mKs/PS10z+fY/ZdyEuKxr/qSMgSSnFRREXnlyoV+sQXL5T3Oc+8opO3Y+131gckY5HZJM/RmaXYd6InimmVlzTjE93pSL2eCTi9WLavXv4ZFQqr4dTwChU73wPDtpSnNy3HpNCHsFg1O+D7nPV1NSwo5NTD69oWFBJTRPcZE2AHnAcZrkiaq24UdezNC2pj+VbUijDTr+9C6sMvIVP7oLdrAFx+ziqPafD1sKrs7aTboEx+nMYvceDN3f66Dmc7KyhqNOh6eRevFe3FEe5J/DmPD/YSntmT2SvEWb+5So8f4kYEOZtfB5XF+7AKx8+gjtuuVMMEAF8sz8TWq0bGmQqOC57y3yp1y7BqA65Ak5pv2FMxufILr8MuWlxmMnVsr7stt7d27fZHt7RH5USFzjpy5EduxcVSXswn6tDpdIPTsL+MUub/TT42U8DdcVA7mEg9xAMOYfAlcTD3kqK4T6+rJp9RYMGC06+iIl8PDtx8Bxr/mKCZ7IKnIwvPV/FxQUfsZaEDXJX2F3+LgYzyYTboZbbYXtmAK6BnGUhjK+/ESgJBPwmA35TIXENbzNbRa1WY+XKlWz83nvvQaGwfBqy0nMokA04NGRZvArx0axKHDZegyuvvR3ew80/qW017ykcl4Th5f+sIdmbgadcIlnZSGEbRGA3M23C6g7hX8VTiK8U3mNuNPn3lYWHcbUkDhEyYSJsFAYqRcBE4OZN0P75KNxrsvGh5AOs3ZKA6uG/WrRQn7CVQLvvPQzns9Ekc4Tq9k2sHke3SaSwWbIKWH8DrjFsw0974nDvRZ3bKif8vd/5w3EW5MaEr4B25j2QBU6D6nge8o2NyK83oCelFNXgssSHMVdmBc8ZH5iU+q/yGwc15GyCbndiFDymWS7FPK24FuPSP2SLX1VBl8PZw/QFG6nfBGyd+CM27s1EzbG8TgXdB6PjsQAn2dhtYicn02VK/Bb2HjZE5WNFYSPmWXZtCeX1any+Ox35RzfhYW49npcW4Anf73Hb4ukY6ydMLIqxREN+DhwSPodv7h9o1j4IpWzwtTMbUEG38AYnnBxMnz4dw4e33UtWOIEQLq1qa8W2HX1ZgJAm+n8xaK4qhNLBQqnQ5xUlMc8q4AVZna4qqvWZDIWFU+cdR10C7HuBjZ0jeqBYiIMvuEcSwEktv5JgI/TrLvgLYc0noDNeDl3QAnjM6Jk9mH3FpREuaN6fAmV5Ld7XvIovvopH8pIXMC/CG6sPZKFRfxnGXfU4Fvibd3Xe6eLnoE/biNmSE/hk62b4G8UUvQLVUMulUnMcsrwvxZbMfOyOLcRHxs0sqLW66IXup82bwtYDiFjGLixkU9fBvjoXv7pHsL2M8XlVGP7zcsh1ejQq3aDy7Hqf786aFeqKjHwv1jJNeeWnrAL7YKcYdSVeOCuuurPl0jFh29Znn4lV2d9+++0eCbqd/COAQ4CXLt+ivWbTS+thMIJVn/cSAm5LfP5I5Rg//xpcVhaDP08UwrkqlqXx6727l1ousHUVV7Ac9eXs/MfUvcqhxVtxl+xvnKgX3i8WY0ALmgvZiiMw7n8Xxn3v4Dr+P6w/cBjXLLRcRmR0bjVS6q1QIHWB48VvnN+PvBtkQxcjLeROPJQQjNyDpbh6mvqszK62CDVffvruUxi1EZgZ6oPPbhwLWUvg05rtUFLTta0KXbVt449YySdBy8kg8zaxyrxUjiKbYQioj0Vt6gHAgkH3B//E4TKjFXuczpe+3OXbuWa8L77cm4ndqaUs08T9AlkmlVEbwXNGFNiMgLew9bOTxvg5sqA7Jk+sH2EJ1Y0afLU3A6mRf+FBbi1GS8RizzqZDT6aIwNYwH2a54zbgITPMR2x+C8mGYsmWv5coK/p4U2YlrVixQrExcXh119/7bDwmr29/amLr2//6WGndPSyWCGuXnXLn0DgHCiuOKfdjiU4BwEBMwBrN6gsmXZ97sSCsLfTwlyHi5MIo7kMWKGZ9SgddIQe4st3QjP6FvZBdb9kE4Zsux73fPonGjV6jPSxx/zRFtib6hSIqtCr2XB0xmfg8o6wscbLstkihrkv4AXd7ZiqOwZbrgnltuGwGnUlepVQLMw9QhxKJayQnPLWTcDFb4uplT3wHnb3zECMvvxRaFecgCTMsnUpBjqZTIYXX3yRXYRxT3D0E0/GPLlK5BaVWux+snKyEMFlY7i7wuLFtV6+LAJh1o24UrKffe3cxf7cZ3JoafPliirUNolVyE2hUovPrcyx93oz9yiZEtzc51DsMpV9qT/+HZussJRfjuTiJ/1CfBCxAarRZn5f5jgEXf8upF4j0aDRs7aVHTmRV42t376Gj/n/YaP9+/jq+uFnrTT6SGvwuHQdrqv5Gj3lQGoxLikRWzg2jr6LtX8zldZbXFhQlQiVui3jeHYltqbU4D7dShTcdKBLj7OVUONktq8UN/HbsWu/+F7QHqHYZVyJBhkGT/DDLzfpfsb4OcAV1ZDnHYRemFk0o7pmLT747yQeeetTzDp0G1ZLXsNoPgN6iRWM0x6F9NF4IGzReb/Hu4djn/8KXK55BWsTGjAYDZig+8EHH8Sff/6J3bt3w8en/dmgZ555hqWgt17y8oT+lqRXBc4CbtkMOJm/hVCbbt4EPBJvnjSvPoRzDEADb8t6zP6uegNzg3qub2WfIrOCfNnHMFyxGhqJCpP4FGxqvgtX8vvwxEVhFju5drn4OcQoJ+Ed7TUI1yax7zmEWbauxAhve/hJKnGLZAf72u6SV3q+oN2FCI/HdwIwaTnb49oThJNJYUXBzrnz+wNJ2+RyOV566SV2EcY9gVM5oooTV0lKs+Itdj+y1C3YqngWzze8CUtztJZjvd0Hp752Cp3W7dtUOojFiISK2OWlhSb/vr1WbJ2pcu4/iw/m4DjrXnacod6HwxnlFmstJRScFFw3aUjXC6d1QKgA/fTF4Wy840gMciraDmQSCmrw++o38AInBtQho2dCqTx7/7OrlR4rpH/gWuN2NKpNn8DpSoG5qD8+QShfgEaJHewXPt2l23EeKm4JCWmKZ/ufzU2YlHnrH3FPovCZEhAkPt/d8Yp0NV6R/QBZ7A8dTvrsSS3Dr9qZuN36M3gseMik+whVVOGY8n58ideQUWi+v/HcikbM+d8efPtfDD7DG+z8Ss/LYZx0HySPxoFb8FKHBUt9LnkG8cZA7E+vQGldz2ZV9AV97OzMdMIfrLDCLbQN27VrF4YM6ThwE1Lj7OzszrqQQUYi65GV5x4nBJMOYmGYYYY0SAbiv9EE/MirIL//AOodxT3Vryt+wHRvC+4hcvSH/rq1yDW6IZgXT7bcImZaPLi8zkNMZa+2HwZ56EKL3h8hPaXCSnwvaywQJ7AsQVYhnkzrXLp/It0Z9td+Cb3MFs2+M8/aWtVlUjmqOPF2qktMa/Wk0RngYhTbGtq7W76gWF9iNWwx/vB+HIvVb+Dno5ZZeNl+6DjmGA4jwt0KY/3M8Fq3Y1qQM75yWY890oewafNv5/08uagWv37zNl4yfsm+1o5fDtmiVedlHNm0TLwI/adLyyyXXdJqS1QarmsQi+gaZzze5f8PTuEz8Jz8SVyleQkxueZPpd6VkI95+Z/CT1qFR+aHmuU2XaeLNVfmanYjKrOk3ettSxC7CF080hOccN5qAomjH2p4e9alJzdJaCtqHt8cyGRtd+2dXJEffjuM4+6A5OFYcBe/CdhcuGBsoKsNW4UXVt//jDV9orC/6/dBt9AubM2aNfjll19ga2uL4uJidmlqaurth0ZIj7Ne9h5g7wdcu6bvrXj2Bucg2Ny/B1j8Pyhu2wTOwi2jxgc44UavYjYulPlb/P4Et/uVQSqTweGaTwbm9hPS6xPb1dXV7GLJVNxzVbmOxz79CGQ1WC6l3alB3IOo8rFwpaFWHsMheSwJyts2me0ma6VixlZjuWnBY2lVFRy5eja2dxtcQbdQ8yJkycOohTW2JxajrO50nR9zEP6f6I5+iy/kH+BT5eeW3brAcRjva80y3GbmfIT4PKGSvehkSR1++OpdvGL4lG230oy5HbIlbRcR5eQq1EDMjqsuzrZ43/KS7e/BnatGjdIb1tPFzIMuUdqhKWgJymGPY9nmDbqFwDBly4e4V7oFf1i/Dg9b82T6WIUvQI3UhRWAS9q9rt2uRTUp+6CAhvWWNxnHodR+pHhbWeJ2t+4SHtOmmHw2XrVsBEKvfwvcpe8D9qZtT7kzqB5vSb+C7OB7GGz6/Vn5559/ztLEZ8+eDU9Pz1OXdeva/kMmZEATev8K+2l6qhBefyCs+E+8GxB6evaAqxfNxWHreZCG98xeYqvL/gfJU1mA97geuT8yuDQ2NsLR0ZFdhHFPqZz4BG7RPoO/mixTVbumQYNAgxhcuAaZ3m6ry5R2Zi10KBQnFOhM7K9cXSyujDdDDl5luZXYvmqYlx1bcdPqjfj9WKZZbzs6uxTzm/9lY9fJ18HSnBa/ADWnxFg+Hf9tXs2C/oyyenz15UdYZfgIEiHgHnkT5Je+1+HEbLVU7Ndeb+IEjqmSM/NwvVaceLK66CXW0767k92te6/N6c8jKbiueS0bK2avNN9ChkSKxqHXsGFA3sY20+Ij41PwA/cSopX3YYSjvmv303JOYFN+Auaw83gCthgexAvWmzEjsOvvGbNd63CtdA8WNG1FSqHlCr31Rf0+6BbeXNq63Hbbbb390Aghg5B/YDgmL7gabouf7Zk7FE6iBvlWAjLwCAWHBELwYIkV9sysdNhzjdCBh433MPRXmR6L8bb2GiRypnVkqC3NZcdKieugzZB5NLAIf8ifh/PBV9keY3OJ27keblw1aqVOsB55GSzO1gPN48XV4svKvsbPkRm44evDSGmyQxOvgmb4tazOyYWCxtYJHG2VuJppKXlNckxRf4InnD+DfFQn22B1YLKbFg9JNmJJ3nvQ6s3T8kx4z6nd8xGcuTpUW/lDNdG8MYXQs1swDSew+0jMeT8vPbqRTZbUqvzAdbH+kEu4WDciWJNslv3uVYd+gD9fisWqRPDSrmcg2Yy4BA28Dby4SkTv/QuDSb8PugkhpE8RZu1HX09tqsiAoFKpoNFo2EUY9xR/ZxWkPAepphbF1eavdFuZJZ7olsh8ur3S1puqgpbiM/0yxGpNq6iczg3BTZpnsNnjQQxWkwPsMIrPxEW63TiQLE5CmKOAWnDuBjZuHHatWEOmB9jPewwNUgcE8UVI2vYZSmrV0LqNgv7OXZBf8XmnVmk1KrFvtLHGsnttC6ubUAcVtK7DzLJ6HOAgx0rZb7iW24GUHHEfdHcdSSvG4uatbCyf/6zZ23ByzkEotB/LAuu6Iz+e9bNmrR5+xWKmhGFo1ydtHIMnwwAOvlwZkk92XN2+M33Kp9WIz4fVpDu6dVuQKVERsIQN7dJ+N3t19QEfdGu1WlYFPDU1FZWV5k3vIIQQQkjvEPajCq3ChIul22qdScZz2Kt4FHHKu1GQaf5iapqiBHastTVthbivOdVfuda0SsB5TTIcMIxApadY/XkwkofOR6XcG3ZcIzL2iEW9umtH5BFM4+LY2H32cvTotoWZT7Dhy9LvMdRFijV3TYKDT1jnK6fbitXwpQ1iXRJLBt0CL4ezK6h3Fe/oiwqJK6ScAXnx+8xym0m7foIrV8P2Xpu93VsLm8m3QWuUQF1TgvRSsb6C4HBCGiZBfH/y7M72BKUdiuVivYbSlIPdeqyHdv2JQL4YzZwV7Cd0f8uEh9CzG8Ac/SEcTjXPhNeADrrr6+vx5Zdfsr3UQr/rgIAADBs2DK6urvD398fdd9+NY8cs1zePEEIIIQMUx0EvE1PMa3ITzX7zu9QReFN7HWqCl6I/87ThEMblwr061qTfK6oRg3QP+0G8NYXnYRgnnvyPKdmIopqmbqcka459z4qWFTpPBtdTbVBbWE+9B43WvtBLFFhzuStcbU3L4KgadhOmqz/Ah/K7YUlhOb9ilXQ1RhnMN5lW6SzuXzbkHOr2bQl/B6MKxWwFzehbLJatYDf+GjzlvxYv627FhqjT++iLjm5kEwjFViHgXYO7dR+pIXfjEc392Fnn263Cdy4nf2XjiiGXAQrxfbk75AFTUCH3hjWnRtb+wVODq0tB9/vvv8+C7K+//hpz585l7bpiY2PZSvehQ4fw4osvQqfTYcGCBVi0aBHS0tLM/8gJIYQQYlFCWvkTTzzBLsK4J9XZBrGjrvSkWW9XCI7+rXTDF/rLYDt6GfozT10+tiuexlu6N6EzYT/rkNIduFqyB0NkFRjMXKbfAR2kGM1nYNeuHd26rejcKrg0ikXZ7Gf04Cp3K6kcqts2QrnkDTj7Dzf5153dfZFvdENebRcLd3VSaG0kbpLuhB/Mt6IuD5zKji5Vsd2uAbH2cCaiDcGs5ZbrLAu+jjIrXDRJrDD+e1QB248uBLjeRWJquT68+wVx7SbeiM2G6dhXyHX5edkVk4p5RrECuvscMz0fHAd1xNVsOKTgLzRYoMd6X9SlTQqRkZHYvXs3Roxou83GxIkTcccdd+CLL77A6tWrsXfvXoSE9O8ULkIIIWSwEbaP/e9//2Pjl156CXK5edrmdIpLCFCxHcoa807cC/tda5q0kPDcqYJt/ZVDS7svoeBTUXUtPJ07V1X4otrfMFx2EulqoXL7BAxa1i4o9rkIPvlboYr/EbrLLoFU0rUk0J+P5GKj9jE8FNqMlSN6qYOIa6h46QJ3e3FlvKxezQJAWRefhwtx1Im9qW3czJcJ4DliDnAYGG5IRU5ZLQLc7Lt0O0L/+p+PFaFcdxO8rnoTS2zFfe6WMjfcDS42cqgacrE/IQvCUz7FGAdwgOeU7qdxR3jZQSbhWG/t/Kom+DqZXpej7MAPUHBalFqHws1nLMzFc8ZtKIhdi8PaUBTHF+HK8V1fje8vuvQ/asOGDe0G3GdSKBS4//77cdddYpU+QgghhPQfwl7uxx9/nF2EcU9StVQVd2oS21uZS2ZONhbzhzHdsQpKWSf3u/ZRvLUT1BBfl8rizu2NFFa8nPXlbGzrOsh6dLfBfc597LhQvw974jO7XEBta5xYxGv2rLk9VkDNnFyUPJ6SrcP/pJ+jrOp0v29zamjWwsMo/u05epkv6JZ7RqCBs4YN14y0+MNdvp2/E4pQXq+Gm60CC0dYPggUJja+dvwJ+xSPIn//T/grpR6LNG9hi89j4N3Cun37wvvbUpci3CXZitQUcZ+4KbLLG/BrqT/W6udAOuU+s3Y64JyGYOO0v/Cx/gpsjDWt5WF/RdXLCSGEENImYWX7nXfeYZceXeUWFu0CxBRZP0M+apvMl9pef3IfPpN/hFd0H6Df4zhU8WJLobqyzvVXrqxrgivEoMrRg4JuWeB0xLotxaPa+7EmqqxLL8PWIwlQ6GoR7mGLMb79s++50AbqNsk/uFKyv9MTOKYqKS1i+3gFNuac8OElKLYfiXqjEkXZXd+OkrRnPabwibhhoq/FVvrP5RMsppiPKP0L2xOKkWn0gsvcB8x2+/cbfsbzsp/RlPKfyb+79lgeko3++HvIs3Ca3s2q5W1YNtaHHSMzKrpdU6E/6HYN/JUrV7b5faHKqVKpRHBwMJYuXQonJ7F5PSGEEELIhdh4hrGWN0I/7YS8HAwPNc82NWOJWMCpwb77K0l9Qb3cFWguRnNl5/orl5fmw5kzQA8ecnvLps/2CxwHp2u/wI7/7YYxrRK5FY3wc+58Gq6QOcAd/gRHFX8gwf1BcNxM9NsJHIkLrPQFqC8VsktGm/0uKouyECgUbeMc4CgzT/XyVoWz38fCtWnwr7bDLV34/cSCKlxf+TmekZegxs5bKPmGnuA67RboDr2OMXw6PNTZUNgEYkKA+WImrcc4oC4KVqUxpv2e3oDfosT3lOsnWmbV39dJhakBNrDN3YXdB61ww+K5GMi6PY0TExPD9m1/9dVXbO/2nj17WIE14Xs7d+5kQbkQeCclmb/lByGEEEIsRwgohH3dwqW7BYpMJlPikNUsrNHNQ05prdlu1rpGXAnjPYZiIGi2cmNHfSf7K9eWiquYVZyj2fsP91dCkD0zxJWNfzlq2ipvdFYp5jfvgJLTYujQC2+97PMTOMLfVCcncEzVWJrNjtUy8W/WnEaGBkMPCTLLGlBRL66mm+LIjg0I4EvQyFvDfkwPFli0cUOxu9i6b4fiSazwzWb1JszFMUwsMufflMQKtXXW3rh0PNL8GWZa52FeuPlfr1avSb7Bl/IPII/9vuc/Y/pb0C2sYs+fPx+FhYWIiopCdHQ0CgoKWOXy66+/no1nzpyJRx991DyPmBBCCCE9orGxkaWVCxdh3NP+CXsNz+vuREK9tVluT28wwkudxcYOAeZfyesNemtxtZqvE/cUX0hjuZiGXisTAywiun2UCg9Lfofn0ddNCk7idq1jPZ3rpE6w7q0CambSbOVh0gSOqTRVYjDfaOVp9tu2V8kQ6i4WRjyeXWnynvzArF/YuDbsWkBunvebzjozdXu+yryFI13Dp7FjEAqQkt35yZSCfT+yKvPvyb+waKq9++Rr2HGWejcS8kx73fqbbj+Lwj6vV199FXZ2dqe+J4yFKqdvv/02VCoVXnjhBRaQE0IIIYR0VpCrePKbUVpvlictr7QS/hCDU9cgoXJ3/1frNxdva6/Ffr5zVch1VWLRoqaWFXIimu7aiEdlv+M6wzbWJqmzwVpwrtjTuWHYdf2ygNqZDDZi0C3p5ASOqbYpl2BE8zc4OuxZi9z+Y1ZbsUu+EupoMYDurH8OHMJMiL3u3eeZbz91Z6mGXYxmlRcMnATeM8Xe8ebC2bihTOrB+scXJUZ26nfyKhowvuJPNubH327WAmrnUg1bhDqJPVy5WsTt24iBrNtBd01NDUpLS8/7fllZGWprxXQwBweHHu/vSQghhJDuESbOq6qq2EUY97QgNxuo0IymEvOs/hSkn4CEM6KWs4XEzvyrbb1BEjQbn+mXYo+6c3veDyqm4UbNM0gMMH9hpP5M6juBtUVi7ZH2fdep3/k38ghm8HFs7D77HvR3EgdhLzOgbBLbeplbYXUT6qCCk7tl9ggH2mgQyBdDWXi0079jMBhhOLaaBaWFLtPAuQSjx0mkUN6zHfxd/4FzF7s2mFOl4yh21OV17nnZt/dfRPA50EAGpyk3w6IkMlQHLWVD54xNbC/5QGWW9HKhJ/emTZuQn5/P0smF8Z133olly8Q9EUePHkVoaNf6BhJCCCGkdwhFUYWJc+EijHvaUMNJJCnvwJv1z5vlZKw+VwyQyqwCLbp605M87JTsWFrbuX2saQ0qHDSMAHzHW/iR9TMcB8Xku9lwes1fSC/puI6AsP9Ud1QMzgudp7AWSP2d0lkMhm215y+mmUNhdTM7ejmYt4haK4cwsYhdYFM8mjSd2yJwIDkXF2t2sLHznPvRaxz8AG/z9cE+k9RvIjs6Vorvfx3R6Q2wTviZjUt9LgJUli+E7TlDXN2fbTiKgwlda9s3KILuL7/8EvPmzcN1110Hf39/+Pn5sbHwvS+++IJdJzw8HN988405Hi8hhBBCBglnn3B29ObKkVvctXZOZ9qtjcC9mkeQFnwnBgp3GxnCuVyM00ahvll7weuX1IqBj6e9GKyT0+wnXo9mzgpBfBEO7tzc4VMTlV2BmerdbOwwo/+vcguswuZhuvpDXKP5P7MXtRJWlB+tfxerpKvhI6uDJbgMncGOwVwBEtPF2g0X8u/BY6gw2qFa7gHF0IsxELlNvgZXal7CHY0rUFbX8eTc/oRszNfvF39vzvIeeXxSn7EoUwawYoT5kb9ioOp20G1jY8OqlVdUVLBK5kIhNWEsVDO3thb3Yo0ePZpdCCGEENJ/CFvDhBotwqU3tolx1s6o5uzZuCQrodu3d6xchn8ME2E1fDEGCmupEf8onsYP8rdQWlp8wevPrtmMayS74SUf+H1xTaawRWXQ5WzofvKXDldLfzmWj2XqV/GX+/1Q9fMCaq3cXFyQb3RFg06CqsYLT+CYorymHku5A6w4l6uNHJbA2biiWO7HxsWJey94/bzKRvycZYX5mndQc92frN/3QGTr6odal7FQQ47YvOoOr5u7/yfYcM2oUPhBHihOYlgcx0E/4lo25ItiUdNk3r+9vsJs5eiE4HvkyJEYNWoUGxNCCCGkfxNahb388svsIox7Q4XSnx0bCrrXerRZq0d2hViBPczdFgOGTMn2qAtqSjpud9Wo1uJh4894W/Y13GUNPfQA+xePufex4zzjUew4FtduAbWtcUUogwN8ljzZ7wuotZJLeThbiwFxUY15J2XKCrPYvmkNpJDausNSal3FbRNc7uELXnfN4RwIC/rTQ9zgH9gzfbl7yxg/B3aMzatq9zrFNc1ILKpHodEJxrE39+gWHPdZd+Mum8/wrOYObIu3TCG/ARF079+/HzfddBOmTJnC9nQLfvrpJxw4cMAcN08IIYSQXiCVSnH//fezizDuDc32QeKgTOyv3VVZBUVYzm3GJco4uNtaZqWtt1RLXdixobzjoLukrAzWnJheat2yf5ecjfcaiXyHifhNPxN/RuW0+fRsjM6FWmdAuIctRvuKwcxAcb98K96VfYa6/ESz3m5tidiju0LiCvCWa0GlChFbZHnVnmAtAjuahEs/9g8U0OCWKQEY6ObZFeAV6XfwTGx/u++G43lYr5+NRz1+hMvch3r08XE2rpgwYTIbb4oWY8mBptt/9b///jsuuugiWFlZsfRytVp8M6+rq8Prr79ujsdICCGEkF6gUCjw6aefsosw7g28m7gCpartXoGd0vRoPClbh5f41eAseNLfGxrkYvsvTXXH/ZWrS8Qgsg7W4BSUldge5Z1/4QXjPfivUIaEgpqzfibsdVbsewO/yFbh0ZDSXikwaEmz9YdwpeQA1EUpZr3d5vKWvz2F2JbMUjyHz0W60Qcn9P5ILW5/7/j2o/H4zLAKR5UrMNd74FbMbjXcqgK3SHdgVM2uNicjhD33a4/lsfG1k4awDJqetnS0N1tcT87OR275wMvE6fanzqpVq1jBNGFft0x2Or1m6tSpbH83IYQQQkhX2fqILXTc1DndKu7UmC/uCa+0blk5H0C01i3purUdB92NLSvhrSvjpG0utkosGi62lPvl6NnZA9FZpVig/hdTJUmY4T2wJm8ETVZiUKyvNu9qo746nx3VKi9YksQlEC/7fYuXdLchKqeyzesI7yPVB1ZDwenQbBsAif3AaB/YEY8IcX92OLKRUXh+UcqDKXmIqN0HJyWweETvPB8e9kp87/QDjivuQ+T+fzHQdPvdIjU1FTNniiX6z2RnZ4fq6o436xNCCCGEdMQ1eCzW6WdjjW7uBSvvdkRekcyOWhexIvpAYrQVT5IlDR0XUlNXioFUg8Jye2oHihsn+WEElwnrmG9Qr9ad+n78zrVw5WpQJ3UaMAXUzqSzFoNurq7jCRxTSevEvz2jndgL3JImBIhtro5lt71/OSanHAsat7Cx9fR7MRhIHP1RzTtCxumRk3j+fvfMPWvwlfx9bLZ+A0pZ7xWUG+Ioh4LTQpG43uwV9Pt90O3p6Yn09PTzvi/s5w4MDOzuzRNCCCGklzQ0NLAsNuEijHuDwskXX9g/ih/0FyG9rL7Lt+NYn8GOSu8RGGikDmIgY9XccX9lY8tKuEZFQfeFTHKoxV+K5/E09wP+jYxi36tu1CA4bwMbNwy7bsAUUDsTZy+uRMsaS8x6uzJ1hXh0EquLW9L4AEfIoENpZnybP4/d8Su8uErUS+xhM/ZqDAochzL74WzYnHXkrB8Jk5kRxWKLPOWw3m2b5jb9Vnacrd2HmCzL9Ivvt0H38uXL8fDDD+PIkSNsX0thYSF+/vlnPP7446zwCiGEEEL6L51Oxy69KchVbEGaUdq1oLu2SYMhBnFPqVvQGAw0Ur/JeFt7LdYZ5nd8vZaVcKOdZVN8BwLOaQiKHMdDwhnRdOQ7tuq248ARTOfjYQAH99kDozf3uRSOPuxoozZvwPOgfiVGNH8DbuRVsLQxqjLEK+7EV5qnUFB19mRheb0a4Xnr2Lgh4sZe2bvca7wnsINdRexZ3965bx/G86nQg4fbzDvRm5Shc1EjdYYjV4+kfb9hIOl20P3kk09i2bJlmDNnDurr61mq+V133cWC8RUrVpjnURJCCCGkxwlFUvPz89lFGPeWUGcZwrhcVOeJKeKmysrOZCdxwkll6x7xgcRhyCh8pl+KzY0jOqzY/KPkCtyoeQa1IWIvatIx++nL2XF+09+Izi6D7vh37Osi5yksKB+IbNzElWhH/fn7frtK6Hde2aBBHVTwdLV8PQErtxAYOQnsuEakxh0962f/7tmHqXwCey9wb2kPN1i4DBUruwdrUlDXLLaAFCaTJDE/sHGR+yzA1rKF7i6Il6Au9Ao29MzeDLVOj4HCLBUgXnvtNZSXl+Po0aM4fPgwysrK8Oqrr5rjpgkhhBDSS3ieh7e3N7sI496ypGYttiuexoic77v0++UZMexYIvUGZL03eWApLjYK8BxYwF1R3/6+94QGOxw0jIC9z9AefXz9lWrUMtRLHODOVWP7hq8xX72Dfd9x5sBc5RY4uPuzo6uxCg0tgVl3Fbb0/LaWS2Cn7IHWgxIpim3FVOr6tP2nvq3TG1AU+w8bl7jPBhwsn+relzgGT2KTDcK0XGKmWNjucFoh5mt3s7HLTHGSqbd5zriNHWcYo3AgrnutIvsSs32CqlQqjB8/HhMnToSNDbWhIIQQQoh5WHmJQaJjo9jr11QHtWG4WP0GdgY/OyBfEgnPYZJ1CWbzsSgtb3uFUgg4WgvRedgNopTa7pDKUR9xPRvOrtuC17U3ItF2GlTDL8FAZeMWiAXGTzFK/TWKu1G48ExVuUn4VvY2XlCu67EWa3ofseezTYm4H1+wM6UUH9fPxeX8h3BeugqDjsIWzwZtxHT1R4gqEVeQU3f/yrKAqmVuUA5diL5A4jkcJapQyDk9iiJ/xUDRpemmlStXdvq67733XlfughBCCCG9TKPR4MMPP2RjoX6LXC7vlcfhGjAc2Av4GfLZ6pu10rQCVomlaiQb/aEKGYWB6kPD63CTl+FI/lgg0Pe8n5fV1GEFvxGlnBOcVX3j5Lo/cJ+9HIa4L1iLsKd1d+OWq58akAXUTpFIYbDzgbasASU1zQhy7f5CWmPRScyVxCLb2HPFGF2HzwKSP0GoJgE1TVrYW8nw4yFx0m7yxMlQeA28LgadETokAEhMQkxuFaoaNJDlHwYkgHr4DSy1u68wTH0Ir/0dia1FYVjcoIGTde989vR60B0TI6ZptYqKioJer0dYWBj7+uTJk5BIJBg3bpx5HiUhhBBCepxWq2W1WwRCcdTeCrptvYey4lWsuE5eHoaFdL47irBn8WRJHRuHedhioKqTucJNXYbmlrZg56osysFK2W/QQAqJ5O0ef3z9uqCay1SgLBnTnRsw2tcBA52nvRUyyhpQVNNsltvTVIq9zhtaeoD3BPvgKSyV2ocrR2RyEty8h+BkegZ4zoG1gxusWv9+Y3Kq8Ht0PlZpb8dhx0vw8dzerVp+Ls/pN+NwzBAUFtRgS1whbpkSgEEZdO/eLeb+t65k29ra4ocffoCjoyP7XlVVFW6//XbMmCE2YieEEEJI/yOVSnHrrbeeGvcauQrlEje46UtQkRMPmBB0l9U24gnN58iQeiPYaTYGqiYrd0CdBF112/2V68rEwKeSd4FHD6X4DhQet3yHjSmNWB7k1mPp0b1psWEPLpftgzzrGmCc+P+/O7hacf+wzqYHq+YrbFGoDIFvcyoqkvciNekEIhWP4IjtAvg4LsFgFeGgw4/yNxGsz8fle75g35s4dQ5g2/faCF4+xpttieEHyP+5bn+Cvvvuu/j3339PBdwCYbxq1SosXLgQjz32WHfvghBCCCG9QKFQ4Pvvu1a8zNyqVAFwqytBU6FQwXxpp38vJyMJN0h3QQMZ5AoxVX4g0lt7ANUAX9d20N1cIQY+9XLXHn5k/R9v546rJmLQiNAlY5TkAHaVixms3aVsEP8meYfztz1YUnHI9fglOgUZZW64qupbyDg9gjydMJgpbZ0xTpIOa2MjAhrjUSsbjqWj+2YLwRsn++HWqQGsZsVA0O1CarW1tSgpKTnv+6WlpairE9O5CCGEEEK6Q+sYwo58RZpJv1eddYIdi+X+fWrPorlxLb235U3nn5MJdDVi2nmzlVuPPi7S/xjtPNlR2lBkltuzVYv94RUuYmX0nuI88258rr8MccUazMUx9j33eYO8nTHPo8RGbJu4TvEqPnfbDDsTa2T0FIVUMmACbrME3ZdffjlLJf/tt99O9fIUxnfeeSeuuELss0YIIYQQ0h264EV4S3sdtugmmPR7huIkdqy3N8+qXV+lcPRmR5W67erlkjox8NH3ZIov6ZfkDi1/S82l3b4toaaCc0vPb3v3nu1tPsTFGs7Wclwv3QUpZ0CRwzjwHhEY7LSep2tuhXkP7pX/fhV0f/HFF1iyZAluuukm+Pv7s8uNN96Iiy++GJ999pl5HiUhhBBCelxDQwMcHBzYRRj3Jufh89iq1bZqf9b+qrOsa8Q+r5y7uLozUNm4+rCjo768zZ8rm8Sgm7enoJt0TOUiFhqz13Y/6K6ob4YVxIJsjl6dr8VgDsL++4u8m/GwdBP72m7W/T16/32VR/jk0+PZd/fqYxlMeHP05xaC64qKClbVPDo6GpWVlex71tbWsLR9+/bh0ksvhZeXF/vPtXnzZovfJyGEEDJY1NTUsEtv83awglLGQ6M3IL+qqVO/YzAY4aHOZGP7gIHbLkxg7zecZQK8o7kaTRqxB++ZbDTiaqPCSQzOCWmPnbsYdLsYK6E1YYKrLYU1aoxVf4W5sh8htxfT1nvS49Wvnxpbj+x8LYiBzH74IuiHzIZuykOsOj/pw0F3bq5YAfNMQoA9cuRIjBo16rxgu6Cg7fYV5iDMvAv3+cknn1jsPgghhJDByMrKirUBFS7CuDfxPIfpjjVYyB9Dbo4YSF9IXnkVAiDuS3ULGo2BzMbZGz9KLsdWw2QU1zafl+K7UrscN2iehVXIzF57jKR/cHAX914LLfpKq6q7dVuF1eIEmb2jC9tP3NMcl70Jg0QJ/SUfDuz+6qaQqyC59Q9IL3q1tx/JoNKlv/4JEybg7rvvxtGjR9u9jjAr/vXXX2P48OHYuHEjLEVIYxcqpdP+cUIIIcS8eJ5HSEgIuwjj3vas5mN8JX8fmoz9nbp+fkYS28tZx1lD6jDwV3jd7ZTsWHxOf+XaJh3StG6INAyHq0fPVpAm/Q9v5YAmKNi4svj8hTZTFFSLf4teDr0zaccFzgL/fDEk42/rlfsnpFstw5KTk/H6669j0aJFkMlkGD9+PEvvViqVrEd3UlISEhMT2fffeecdFhgTQgghhHRHo30Q0JwAY1lqp64f3eiOe5pX45ZhEjw1QHq9dmS0qgx+fCpqSjyAIOdT3y+qFVcbHVQyKGUDt4I7MROOw8Mu32B3vhEfGNwxohs35Zq+Ad/KtqJBewmAsb3zEg2C//uk7+vStLWTkxP+97//obCwEJ9//jlCQ0NRXl6OtDSxjYdQSC0qKgoHDx7scwG3Wq1mbc7OvBBCCCHkfFqtFp9++im7COPexruGsqNVbefSy1NL6tAAK9j7j8RgsLzhC3wvfweK3LMzAaoKM/Cw5Hdcq2w/Q5GQM8mcfKCF9LytCqayr0rAXEks/Fq2eRAyWHVppbuVsLItpHX3p9TuN954Ay+//HJvPwxCCCGkz9NoNFixQuxre9ttt7Hstt5k6zMMSABc1Dlsn7JQQLUjqcV17BjmYYvBQG3lDjQAhtrCs76vLUzAo7Lfka0Tep0/32uPj/Qfnqe2KnSuaGF7rBrFYFvmKBZnI2Sw6lbQ3R8988wzWLly5amvhZVuX1/a30QIIYScSyKR4Kqrrjo17m1uQ8RE1wBjIWtF5GLb/j5RtU6PR6peR7nUFkNthmMwMNp6AuWAtEFsD9ZKWyUWtG1UuPXSIyP9zThdNIbJfoU+R0gJ73rBLQdtCTuq3ALM+OgI6X8GXdCtUCjYhRBCCCEXzmjbsGFDn3maFC5DoIEUSk6L5KyTcBnZfhuwnMJiLJEcZmOjox0GA6m9Nzsqm87ur8zViSvfWmuPXnlcpP/xNRZhuOQADtcYu3wbzVo93I1lAAc4evZsj25C+preL0XaTfX19YiNjWUXQVZWFhu31daMEEIIIf2YRIpSmViFvDo3ocOrFqeL5wUVvDM4lSMGA6WzGHTbasWe3K1kLSvfnJ1Xrzwu0v8oncQsUDvt2RM4pigpK4c91yjeTksbMkIGq34fdB8/fhxjxoxhF4GQOi6MX3jhhd5+aIQQQggxsyO+d+F+zUOI0nR8Et+UF8eOFdZBg+Y1sHMT9806GSpgMJxeobRWi4GTzFEMygm5EFv3lr8lfQWrn9AVlYViwcM6WINT2tOTTgY1s6SXR0dHY//+/ZDL5Zg2bRpGjuy5KqGzZ8/u8psBIYQQQtrX2NjIenQLhA4lKpWq158uTfhSbEuKx6xqeYfXk5SnsKPWORyDhUPLaqIrqlFZ3wQXO/H1steJK9/WLlTDhnSOo7u4B9sVVaisa4SznbXJT111RQlqjSpUy90xOEoZEmLBoPuDDz5gq8sODg6QSqWsdVhERAS+//57jBs3rrs3TwghhJBeIkxqC+1BW8d9QZCrDTtmlNV3eD2nhnR2VHh3p8tw/yKzc8fH/E3IaLbD3dUNLOgW9tW6GivZvloHDypmRTpHbu8OHSSQcnqUFefD2S7M5KcuThKB29Xf4KbhblhFTzwZ5LqUXv7tt9+y1W2h5/Xrr7+ON998ExUVFSgtLUVOTg6WLl3KVqAPHDhg/kdMCCGEkB4rpBYTE8MuwrgvCHaSYQ4fg/m1m9Gk0bd5nfpmLQL02WzsFihuPxsUeAm2O16HzYbpKG4wsG+V1qqxTPMKbtU/D1uPwZNqT7qJl6CSd2LDutKcLt1EYbXYbszNyYFeDjLodWml+5133kF6ujiDbDAYcOzYMbz//vsYO3YsRo8ejVWrVsHb2xuPP/44Dh8WK4cSQgghpH8R2oQJn+t9iZMVj+/k77BxSv5KhAeev3qbkVcAT0ihBw87v8HRLqyVh50SCQW1KKlVs6+LapqQafSC3i4YnKz9FmuEnKtW5gqX5nLUV4q9tk1V2NLj28uB/u4I6dJKd3JyMurq6hAZGQmZTAae57F+/XosWbIEzs7O8Pf3Zy1GhJnxv/76i1UUJ4QQQgjpNrk1ynix33R5dtsVzJOreExUf4b7vTcAgyzQDFdUskwAbXEi+7q4tvlUME6IKdaFvINQ9Q+IVk7u0hN3Q9Fb+Fb2NkL0J+mJJ4Nel6uXC2lmEyZMYIXTRo0axVa0hUA8Li4Ob7zxBkJDQ6HVanHbbbchKCgIdnaDo0cmIYQQMlAIn+NCjRbhIoz7iiqVWDCssTC5zZ+nFNexo6/n4GuRtaDmN5YJ4Ju3hX1tzDuKhyW/Y47kRG8/NNLP2DsJ+7qlKKoRJ25MIdSAGK6Nx1xJLNxV/b5ZEiG9X0jt3XffZfu3MzMzce+997IA3M/Pj+359vLyQn5+PrskJHTcT5MQQgghfYtGo8Htt9/OxldffTXLbusLNA7BQP0x8BVpbf78ZIkYdId6DL6ayawXdxEgbyphX9sUH8ajst8R1yyk+t7b2w+P9CMe9mKWSElLtoQpquqb4Y4KNnb0HGL2x0bIoAu6hb1eUVFRLOCePHnyqeqmQiVzoeCawMfHh10IIYQQ0r/2dC9evPjUuK+QuYcB+YBtXUabP19e+ByWyzTwlL0trHdjMJG39OJWqcU2YdJ6cT+u0cazVx8X6X+C9Fl4T/YZjCVCQbVJJv1uaVEunDg9dOChcKD+8ISYpU+3kD6+Y8cOlJSUsDRzYWZcCMB9fQfXBx0hhBAykAhbybZu3Yq+xl4ojhYFeGjzoDcYIeG5Uz8rr2vCBEM8VBI1mlztMdi09uJ2aOnNbdVUyo5SCnyIiVzlGoyRHECO2sPk5666WKznVMk7w01ilnCDkH7NrP8L3N3dWbswQgghhBBLcR0i9t72QSkKy6vg6ya2NhLkpCdjHKeGGjJYuYcOuhfBwV3c7+5irGQ9um21YvCtdKaMQ2IaRw/xb0lIExfa8NkoO7+9pKlMbNlXK/eAWPaQkMGNKhsQQgghpF+R2LrjTdXjuEyzCunlYmusVlVZsexYIvcHBuEKm42rGFzbcU0o+f/27gM8imqLA/jZ9N47CaGF3hQEARXxUR6CAipNRKmKIoooKqKC4BMEC6KCIh3lgcgDUREQBJ6AgCAgHYGEEghpJCGkJ/O+c5bdl012U0g2uzv7/33fMLMzs7OzczMkZ+659yalUGBRsvZ1iDaAAqgoz1sPatw0+ZSYmFCpC1d4/ZLMczzQrAGAIegGAAAAo7KysigmJkYmXrYaGg1dqtWLjit16VyKdixgncJrJ2Se6RtD9kjj5kNZpB0e7ELsKQqidFn2u1VrCVBhzm6UptGOPpSWcKFSFy4rO5syFA8q9EGGBQCzv0fAAAAAUCHcOerZs2f1y9akfrCnzM8lZRqsd0/TjgmsCW1K9mqF79N0MqmAml3NoPs0ChWQIzl7h1r6tMAGpTsFkV9+BmUla2uuK2qxw6P0Qu4/6Is2ramV2c4OwHYg6AYAAACTHant2rVLv2xNWnhep2GOmygkLoiIWsq6oiKFwnPOEWmIfGpr19mj42GP0IZrVygh2ZdW5n5I7UIK6X0HJDdC5d10DSXKP095aZcr9b4radoMlFr+XrjsAAi6AQAAwBQeJqxTp05WeYEa0iXq5rycTmbUI6Ipsi7+ehYlFflQqIMHhTS4k+xVmK/2AclfVzIpSwmnmEDUcsPtyfcMo6IbGsq7oR1zuyJyCwop8Ya2r4UIP+t6WAdgKajpBgAAAJsTUq+5zKOVeErNzKEALzc6fS2TRuW/SY1DvWiTv/0OW1rXJZ26OByi9HxP+pMa6oNwgMo62eJVevRCP7rfrRb9s4LvSUy+TptcXqMECqIA13/gogMg6AYAAABTCgoKaN26dbLcr18/cnKynmf17iENpK2yhyaXzsb9TQHNW9DpazdkW6NwH+lszV61uPEbDXaZLctzCh6hSOUhItI+pACojODAQCqgWErIMOywsCzJV87THQ6XKIqSSeOMBz4ADA18AAAAwKjc3FwaMGCATLxsVRyd6ZpTLVlMvXhc5meuanvqbhTmTfbMLUB7Xdh4p/9Qo9xjFj0fsF2hPtqgOSG94vd/5rVYmac6YYRuAB3reWQNAAAAVsXBwYE6d+6sX7Y2GV51qVbaRcq7elJeDzw/iV5yiaO0wulE1IDslXdwbYPXrgEYtgluT4TTDfrY+XPyzs2ivIIHyMWp/P8H8lIvyvymWxguO8AtCLoBAADAKHd3d9qxY4fVXp3CgAZEaTvJOe0s5RcWUVT+eYpySKLEkECyZ/4lxuT2DDEMwgEq/LPk40n9HHfLcnxqKtUK4dECypGuHV4sz+v/GRcA9s76HlsDAAAAVIBruHYsbr+bcRR35RpFaZLkdXC9O+z6+rn4hlERj5t2i39oHYueD9gujZsfZZE2xTw14UKF3uN886r2vb7IsADQQdANAAAANsm/ZU/qmzuNhmW/SJdO/ynrUh0CSONp3zXd3N69oFgyo0cggh+4TRoNpTlq76fMJG0Ndnm8chJk7hpomHEBYM8QdAMAAIBR2dnZ1Lp1a5l42doEhkTQedfGlK540qVTB2Rdikd9S5+WVTDoux09SEMV3HDRdoiWm1J+0K0oCmUUOFGG4kHeoXVx3QFuQZtuAAAAMKqoqIiOHDmiX7Y2Go2G6od40aGLaUSJJ6QqITegsaVPyyocCuhB7VJ/pAwHX/Kx9MmATcv1CCXKJipMv1LuvhnZBTQs9xVZPtVE2wkjACDoBgAAABPc3Nxoy5Yt+mVr1NvtL3rYaTs95bBZXrvVwnjU7GCzyfTa1i7Ut3kAvWjhMgLbVuQVTpRC5HirrXZZ4tO0GTGBni7k5oK6PQAd3A0AAABglKOjI3Xr1s2qr067wkPUwkkbcB8pqkfRDdpY+pSswmPt6lNaroYeboeey6FqnPwiqShOQ0U5meXue+VW0B3h547LDlAMgm4AAACwWU4hjYjiiX4pbEOTXCfRgfp3WfqUrEKwtytNerCJpU8DVCCv5RBquC+GQt296YFy9tX8vYk2ucymiwUdiOieGjpDAOuHjtQAAADAqIKCAvrpp59k4mVr5BulHTasviaeGoV5W/p0AFQnNNBPesNPvJFDRUVKmfsqKeeoscMlCndIrbHzA7AFqOkGAAAAo3Jzc6l3796ynJmZSU5O1vdnQ0i9ljKv55BATYJdLX06AKoT4u3KI4dRfqFCKTfzJIvCFMcb8TJXvGvV4BkCWD/r++0JAAAAVsHBwYHatm2rX7ZGTr4R+uXBKZ8R0SKLng+A2jg7OtBct68ouDCBUhJiKNi7ocl93bO0na05+kfV4BkCWD8E3QAAAGCUu7s7/fHHH9Z9dbgK7pawBndY9FQA1OpuzTEKdkii/QmxRDGmg26fvASZuwfXqcGzA7B+CLorQFEUactWWFho/hIBALP0wMxpsTymLwCo0NM7iM5uI89Oz1j6TABUKd05mIJzkyg75ZLJffILiyikKIlIQ+QXXrdGzw/A2iHoLkdeXh5dvXqVsrKyaqZEAMAsPDw8KDw8nFxcXHCFAdQm4g7tBABmkeMWSpR7ggrSrpjc51rqdYrUZMiyX1g9lASAGoPuefPm0ezZsyVAbtasGc2ZM4fuvffeKh2zqKiIYmNjpZYsIiJC/lhHTRmA7WWq8MOzpKQkuZ9jYmKstm0qgLXJzs6mrl27yvLWrVsl3RwA7E+BVzhROpHDDdNBd1JiEt0oiqIgx5sU7OFfo+cHYO1UEXSvXr2axo8fL4F3p06d6Msvv6SePXvSiRMnqHbt2rd9XP5DnQPvqKgoqSUDANvEgYKzszNduHBB7ms3NzdLnxKATeDfgXv27NEvA4B9cuAOC+OJXLK0bbaNuZDnTePz3qcO9QLp32jOBWBAFdU9H330EY0cOZJGjRpFTZo0kVpuDpTnz59fLcdHrRiA7cN9DFB5rq6utG7dOpl4GQDsk2tApMy98hJN7hOfli3zCD9kxACorqaba60OHjxIr7/+usH67t2765/OAwAAQOVxB4R9+/bFpQOwc17BtalI0ZBSkG9ynyu3gu5afsgmA1Bd0J2cnCy9ioeGhhqs59cJCaVTYHJzc2XSycjQdvgAAAAAAACl+TXsRA1zl1EBOdHRnHzydnMutc/95z+goS4HKTXreSJqhMsIoLb0claygzPuPMlYp2czZswgX19f/cRp6GrGDx7GjRtH9erVk9RA/r4PPfQQbdu2TbbXqVNHrhNP3O61cePG0iEdXz+duLg42X748GGD11wDEh8fb/B53JGdbmgm3q8kzkDgjun27t1r9HwPHTpE/fv3l4cm3O62YcOGNHr0aDpz5kw1XxkAACgPP9TesWOHTBg2E8B+ebq7kfut/lCuZeQY3ScwO44aO1yiADfVhBcA1cbm74qgoCAJ4krWaicmJpaq/WaTJk2i9PR0/XTpkunxBm0dB71t2rShX3/9lWbNmkVHjx6lTZs2UZcuXWjs2LH6/aZNmybB8smTJ+mVV16hN954gxYsWFDu8blH9+XLlxusW7ZsGdWqVcvo/hcvXqTff/+dnn/+eVq0aFGp7T/++CPdfffdkonwzTffyPmsWLFCHo689dZbt3UNAADg9uXk5MjvDJ54GQDsV5iPNui+mm78/wL//Gsy9w6tU6PnBWALbD7o5mG8OLD85ZdfDNbz644dO5ban2t7fXx8DCa1eu6556TGef/+/fTYY49JrTEPpzZhwgSDmmZvb28KCwuTWm/ujK5ly5a0ZcuWco//1FNP0ZIlSwzWLV26VNYbw/v27t2bnn32Welx/ubNm/ptPA768OHD6cEHH6QNGzbIEDV169al9u3b0wcffCA90gMAQM3i3yFNmzaVCUNmAti35+nftNplGhWc/63UtozsPAqnZFkOiMAY3QCqC7oZB5ELFy6kxYsXS+3oSy+9JLWqY8aMqfbP4rTrrLwCi0zFU77Lk5qaKrXaXKPt6elZarufn5/R78YphHwNeXil8jz88MN0/fp12rVrl7zmOX8up68bOzYH3U888YSksPMDgG+//Va/ffPmzdI+/9VXXzX6WcbOFwAAzIuHyzx+/LhMGDoTwL7FFF2g9g6nSEk6W2rbtYR4ctPkUxFpyD1Q3U03AeyyIzU2cOBASklJ0adJN2/enDZu3EjR0dHV/lnZ+YXU9O3NZAknpvUgD5eKFdnZs2cl0OUAtzyvvfYavfnmm9ITfH5+vrSlfuGFF8p9HwfmHETzw4577rlH5vzaWMC+detWqc3u0aOHvOb9OMWca7fZ33//LfOKnC8AAAAA1Kx8z1CiTCK6caXUtutXY7VzjT8FOmF4QQBV1nTrUqm5DTO3B+YhxO677z6yZ7pa8YqkA06cOFE6Sdu5c6e025s8ebLR1HxjeHz0NWvWSJt6no8YMcLofhxg88MR7mSNDR48mPbt20enT582OF8AAAAAsEI+ETJzull6dKCspAsyT3cp3Z8SAKikprsmuTs7So2zpT67omJiYiTg5lTx8sZY5c7oGjRoINPatWtlzh2acbvq8nBWAddOcxDdpEkTea3r5VyHU87Xr18vtejz58/Xr+eecLl2/P3335d0c3bq1Cnq0KFDhb8nAACYT3Z2tjQlYtzfBo9yAQD2ycU/UuaeudoO04pLuZlPJ4uiKMcL7bkBVF3TXVM4kOUUb0tMlenEJiAgQFK5P//8c4MOy3TS0tKMvs/f31+GGONezCta+8y129wW3FQtN/dEHhkZSUeOHJGAXDfNmTNHejsvKCiQocQ4+Ode1o0xdb4AAGA+RUVF0jyIJ14GAPvlHqRtq+2bn1Rq238d7qKeee/TH62mW+DMAKwfgm4VmzdvntQmt2vXTmqwud0013zPnTu3zNpk7nyN0775PRXB42gnJSVJz+emUsu593SuBS8+cZDOwfRPP/0knb1xZ3i8zLUq/AceNxc4cOCAdK5mjk7xAACgbDzix9dffy0TLwOA/fK7NRRYsJJCuQWFBtuupGXLPMIP2TAAxiDoVjEecuvPP/+Udtovv/yyBLrdunWjbdu2GaR5lxQcHExDhw6lqVOnVqhmg9tpcy21rr12cdy+nmu4H3300VLbeKgyruHWjdndp08f2rNnj3TE9vjjj+vT1nk89XfffbfS3x8AAKqG/18fMmSITMb+jwcA++EbEkWFioayyZUSU9MNtl1J047djaAbwDiNYuc9WGVkZJCvr68EdiXH7M7JyaHY2FgJXrlHbwCwXbifAQAAqkBRqMusbRR7PZfWjOlAd9UJkNUFhUV0YVozylccKWjkGgqKboLLDHYjo4xYsjg8tgYAAACjuIkSZ0yxO++8kxwdK96hJwCojEZDwb6eEnQnpGtrtlni9Qyqr7lCpCEqCgiy6CkCWCsE3QAAAGAyQ4T7BWGZmZnS/wYA2K8wX23mZ/GgO/lqHPFgYrnkQq5eCLoBjEGbbgAAADCKR82Ijo6WqTIjaACAOvXM3UirXaZR+LlV+nUZCbEyT3EMltpwACgNNd0AAABglIeHh4wkAQDAIiiZWjmcop1pjfUXJDflosxvuIXhIgGYgJpuAAAAAAAol6NfpMzdcq7p1ylpl2Se58FJ5gBgDIJuAAAAAAAol3ugNuj2yUvSr3POjJe54huFKwhgAoJuAAAAMNmRWt++fWXiZQCwbz4h0TIPKEqmoiLtqMOX873pZFEUOQU3sPDZAVgvtOkGAAAAk0OGff/99/plALBvfmHaoDuY0ik5I5NC/Lzp/dxHKSOvD/3S+j5Lnx6A1ULQDQAAAEa5uLjQggUL9MsAYN+cvUOpgBzJSVNIqQmXycM9hjJyCmRbuJ+7pU8PwGohvRyMGjZsmKQTgnFTp06l1q1bV9v12rFjhwzHk5aWhktewWsOAObn7OxMo0ePlomXAcDOOThQkkMwXVUCKDU1ka5ez5LVvu7O5OWKujwAU3B3AFSDTz75hBRF27aJ3X///RIgzpkzB9cXAAAAVGNq9ArafDKJpmuiySXuT/rLdSTFOnJ77u6WPjUAq4WgG6Aa+Pr64joCgOoUFRXRyZMnZblJkybk4IAEOQB7F+rnIfOr6TlUO+8C+Wiyycch19KnBWDV8NtTpbjWddasWVSvXj1yd3enVq1a0XfffWewz/Hjx6lXr17k4+ND3t7edO+999K5c+cM9vnggw8oPDycAgMDaezYsZSfn6/fdv36dXryySfJ39+fPDw8qGfPnvT333/rty9dupT8/Pxo/fr11LBhQ3Jzc6Nu3brRpUva8Rzj4uLkD7gDBw4YfOann35K0dHR8h10adc//fSTfAc+Rvv27eno0aMG79mzZw/dd9998l2joqLohRdeoJs3b5q8PkeOHKEuXbrI9+bv36ZNG/15lHfexhRPL+flnTt3Su03nztP/F0rYvfu3VX6nl9//TW1bdtWvldYWBg9/vjjlJiYqN+uu56bN2+mO+64Q47zwAMPyD4///yz/FHN12Pw4MGUlaVNGSvPpk2b6J577pFrxj8nvXv3Nvg54u/On/mf//xHrjn/rPB3/P333w2O89VXX8l34u39+vWjjz76SI5ZliVLlsg58/Vq3LgxzZs3r0LnDAAVk52dTc2bN5eJlwEAwnzd5CIkZORQQepFWc5yD8eFASgDgu7blXfT9JSfU4l9S/wRY2q/SnrzzTclIJk/f74E1y+99BI98cQTEgyy+Ph4Cd44WPn111/p4MGDNGLECCoo0HaGwbZv3y7BE8+XLVsmwShPOhxccqC6YcMGCaA4SH7wwQcNAnMO3P71r3/J+zmgzMjIoEGDBsm2OnXqUNeuXeU8i+PXfGwO1HQmTpwoDwD++OMPCgkJoYcfflj/ORyY9ujRgx555BH666+/aPXq1bRr1y56/vnnTV6fIUOGUGRkpByPv/vrr79u0F6xrPMuDwfbHTp0kDaQV69elYmDyYqo6vfMy8uj6dOny0MFfmgQGxsr19JY++jPPvtMgnh+mDBgwABJhV+5cqU84Pjll1/k4UdFcNA/YcIEOedt27bJgxQOmrmGrLjJkyfTK6+8QocPH5aHGRzY637e+BqPGTOGXnzxRdnODzn4+peFg3Q+Ju/HNXHvvfcevfXWW1JmAFB9goKCZAIAYK2z99Fql2nU9cIc0mRclnWF3rVwcQDKoti59PR0bogr85Kys7OVEydOyLyUKT6mp68fM9z33TDT+y5+0HDf9+sa368SMjMzFTc3N2XPnj0G60eOHKkMHjxYlidNmqTUrVtXycvLM3qMp556SomOjlYKCgr06/r3768MHDhQls+cOSPXbffu3frtycnJiru7u/Ltt9/K6yVLlsg+e/fu1e9z8uRJWbdv3z55vXr1asXf31/JycmR14cPH1Y0Go0SGxsrr7dv3y77r1q1Sn+MlJQU+Rx+Lxs6dKjy9NNPG5z/b7/9pjg4OBgvO0VRvL29laVLlxrdVpHznjJlitKqVSuD69WnTx/9686dOysvvviiUlHm+p779++X4964ccPgc7Zu3arfZ8aMGbLu3Llz+nXPPPOM0qNHD+V2JCYmyvGOHj0qr7ks+fXChQv1+xw/flzW8XVl/HPVq1cvg+MMGTJE8fX11b8uec2joqKUlStXGrxn+vTpSocOHYyeV5n3MwAAAFTIqa1L5G/TI9PuVnbNeEiWj373L1w9sEvpZcSSxaGmW4VOnDhBOTk5Ulvo5eWln5YvX65P++XaRE4nL6s32mbNmpGjo6P+NaeZ61KVuWbRyclJUqB1OLW4UaNG+vZ/jPfhdGcdTgHmlGHdPpySzfusW7dOXi9evFhSkLkWvDiuOdYJCAgw+ByuqeYa+OLflWuEuaaVa3qN4ZrZUaNGSU37zJkzS6XVl3fe5lLV73no0CHq06ePpOdzijl36MYuXtSmf+m0bNlSvxwaGiop3dwUofi64mnpZeFrx2ns/H5OTa9bt265n8k/S0z3GadPn6Z27doZ7F/ydXFJSUlSQz9y5EiD6/Huu++WKksAAACoPl5BtWXuV5BC3nnXZNk9SDt+NwAYh47UbtcbV0xv0/w/UBUTz5axb4nnHuMN2/DeDl1aL6cJ16plmO7j6uoqc27LW56SATmne+uOXbyn7uJ4ffG0cN37StKt43Ffhw4dKinlnDbN6c0V7fFbdww+p2eeeUbaN5dUu7b2F4Ox9GoOFPkacVvmKVOm0KpVqyQtuiLnXZMq+j05zbt79+4ycdvu4OBgCXw5MOe0c1Nly8cvq6zL89BDD0n6PKd7R0REyPu4/Wd5n6n7TqZ+bkz9jBV/H39m8Qc/rPiDIgAAAKheAeHaipFQSiXnwnwiDZFvmPaBOwAYh6D7drl4Wn5fE5o2bSrBNQdcnTt3NroP1zpy21duL3w7Y6/yZ3B73H379lHHjh1lXUpKCp05c0Y6ttLhfbjdt67Wkms0eSxqrjnW4RpnDtK4Eyw+Hw6+S9q7d68+gOYO3PhzdMe48847pd16gwY8XEXFcbtinri9O7cv5sBfF3RX5LzLwg8TCgsLqbKq8j25zXdycrLU3OvakJfspK66cZlzTfyXX34pmROM25lXFn/H/fv3G6wr69y5Jp4fKJ0/f17a5wOAeXDWFGeUsEWLFkk/IABg39wDImXuqsmn+KIgSlc8KSa8vqVPC8CqIb1chTitmDus4mCSA2tOt+W0488//1zfyRR3vqXrHIyDG+51fMWKFRJcVkRMTIykMXNnYRxkccdd3FEbB0K8XocD+nHjxklw/ueff9Lw4cPp7rvvNkgd5iCd17322msS/BqrhZ82bZp00nXs2DHpGIw79dH1Fs7v447cuHd1Tpvn78Kdu/HnGsM98PL35568L1y4IJ14cSdgxR8WVOS8y8Lp8fxe7rmbA+GK1hpX5XtysM7BPneAxsEob+NO1cyJe67nZgULFiygs2fPSqd8nLpfWfwdNm7cKD2W8/fiIJ4zEMrKLOBshRkzZkjHdfxwgh868IMTPgYAVA9+eMgZSDzdzoNEAFAhJxdK02iHSn07fxiN9JhLjj6hlj4rAKuGoFulONh6++23JSjhYJJTjH/44Qd9e1sOlDhAyszMlNpwHjKLU3UrU+vNAQ6/j4eI4rbInA7MgVPxY3BbYQ4WOZWb9+GAmtO4S+KaFE5H5h7UjeHaW+7Zmj+PewPngJIDTF2tPffKzsEa17byUFjci7Wu3XBJnH7MNbQ83BnXdHPP3Tzc2TvvvFPp8zaFH3rw53BGgC7NuyKq8j35c7jN95o1a+Rz+VjcE7o5cU/lfF24vTlnK/CDntmzZ1f6OJ06daIvvvhCAmYeToyHIeNjlVWrxhkSCxculO/cokUL+TnmZd3POABUHf//8/HHH8uk+78IACDNKVguQqjmOkX4IQMGoDwa7k2N7BjX9vr6+lJ6erp0AlUyrY47qOI/4pFSV3kcAI0fP17SssvDwz5x8FZyXGqujeaO1TjVurwxmy1x3mA+nEVx6tQp+u2336rleLifAQAAqsexD3tTcMZRqel2a9mXPhl0By4t2KWMMmLJ4tCmGyyKa9q5TTCnRJs7FRqsG9fKc4/7np6eklrOTSG4nT8AAABYly0tPqSCnR/SbOcv6VgGV1Ig6AYoC9LLwaK4bfU999wjqcGmUsvVYMyYMQZDWxWfeJu14rR4U+fNU0XT5iuCO1LjoJtTxTnVfO7cuZJCDgCWw/1RcN8UPFW0bwoAUL9wP3eK0CSTjyabPN21I+MAgGlIL0d6OdQAHo+af9aM4VSUkJAQqywH7sWd/9guq8M4HtPcFiC9HKDyeChCfsCmy0ziTBQAgO2nEkn5pj894HiYTt71L2rS63lcFLBLGUgvB7AeHFRba2BdFg6oKzsUGwCoC3csCQBQXO2CWKrveFiWPUO043YDgGm2UUUFAAAANY5rtrm2GwCguGCf/z+MC4ioh4sDUA606a4AO+/gHUAVcB8DAABUD5+QaP2yV/D/lwFApUE3DzXVsWNHSX+r7iGldONNZ2VlVetxAaDm6e7jyoxFDwAAAEa4+RA9voboibVELujrAUD16eV5eXnUv39/6tChAy1atKhaj+3o6CiBPHeCxTiw12g01foZAGD+Gm4OuPk+5vuZ72sAqJjc3FwZZYJ99tln5OqKXooB4JaG3XEpAOyt9/KlS5fS+PHjKS2Nxwqsvh7n+PIkJCRU+rgAYF044A4LC8ODM4BKQO/lAAAApqH38jKe2vNU/EKVhWu2w8PDpefp/Pz8MvcFAOvEKeWo4Qa4vXvn3Xff1S8DAACAHaaXV9aMGTPonXfeqfT7+A92/NEOAAD2xMXFhSZPnmzp0wAAALBpVtmR2tSpU6WGuazpwIEDt3XsSZMmSSq5brp06VK1nz8AAAAAAACA1dZ0c6ctgwYNKnOfOnXq3NaxuRMYdAQDAABQPu7XJDk5WZaDgoLQJwIAAIBagm7+xc4TAAAAWA73/M99mrDMzEzy9MTQQAAAAKoIuivj4sWLlJqaKvPCwkI6fPiwrG/QoAF5eXmV+35d5+3ldagGAABgj72X6/DvSf49CwAAAGQQQ5Y3IJjNDxk2bNgwWrZsWan127dvp/vvv7/c91++fJmioqLMdHYAAAAAAACgZtxPWGRkpHqD7qoqKiqiK1eukLe3d6m2avzkggNyvojGxvAG24MyVR+UqbqgPNUHZao+KFN1QXmqD8q05nAofePGDYqIiCAHBwf1ppdXFV+csp5KMA64EXSrC8pUfVCm6oLyVB+UqfqgTNUF5ak+KNOa4evra5tDhgEAAAAAAACoAYJuAAAAAAAAADNB0F0GHs97ypQpGNdbRVCm6oMyVReUp/qgTNUHZaouKE/1QZlaH7vvSA0AAAAAAADAXFDTDQAAAAAAAGAmCLoBAAAAAAAAzARBNwAAAAAAAICZ2E3QPXXqVNJoNAZTWFhYme/Jzc2lyZMnU3R0tHRIUL9+fVq8eLHBPmvXrqWmTZvKdp6vW7fOzN8EzFmmS5cuLXVMnnJycnDhraw8hw0bZrSsmjVrZrAf7lF1lSnuUdv6P/ebb76hVq1akYeHB4WHh9Pw4cMpJSXFYB/co+oqU9yjtlemn3/+OTVp0oTc3d2pUaNGtHz58lL74D5VT3niHrUMJ7Ij/Ifb1q1b9a8dHR3L3H/AgAF07do1WrRoETVo0IASExOpoKBAv/3333+ngQMH0vTp06lfv34ScPN7du3aRe3btzfrdwHzlCnz8fGh06dPG6xzc3PDJbey8vzkk09o5syZ+tdcjvyHYP/+/fXrcI+qr0wZ7lHbKE/+Xfjkk0/Sxx9/TA899BDFx8fTmDFjaNSoUfoH1LhH1VemDPeo7ZTp/PnzadKkSfTVV1/RXXfdRfv376fRo0eTv7+/lDHDfaqu8mS4R2ueXQXdTk5O5T4d0tm0aRPt3LmTzp8/TwEBAbKuTp06BvvMmTOHunXrJj/cjOf8Hl7/73//2wzfAMxdpqwiTxHB8uXp6+srk8769evp+vXrUuuig3tUfWXKcI/aRnnu3btX/o994YUX5HXdunXpmWeeoVmzZun3wT2qvjJluEdtp0xXrFghZciVSKxevXpSzu+//74+SMN9qq7yZLhHa57dpJezv//+myIiIuSXxKBBgyT4MmXDhg3Utm1b+UVSq1YtatiwIb3yyiuUnZ2t34ef/HXv3t3gfT169KA9e/aY9XuA+cqUZWZmSvp5ZGQk9e7dmw4dOoRLboXlWRJnL3Tt2lXKTgf3qPrKlOEetY3y7NixI12+fJk2btxIiqJIltF3331HvXr10u+De1R9Zcpwj9pOmXKzu5LZfJyWzDWk+fn58hr3qbrKk+EerXl2E3Rzuje3adi8ebOkXCQkJMgvj5Jty3T4B5rTqI4dOyYpU/yUj3+xjB07Vr8PHyM0NNTgffya14Ntlmnjxo2lrQsH6JytwP9xderUSf7DA+sqz+KuXr1KP//8s6Q4Fod7VH1linvUdsqTt3H7X65xcXFxkZoaPz8/+vTTT/X74B5VX5niHrWtMuXKooULF9LBgwflQcqBAwekrxsO0JKTk2Uf3KfqKk/coxai2KnMzEwlNDRU+fDDD41u79atm+Lm5qakpaXp161du1bRaDRKVlaWvHZ2dlZWrlxp8L6vv/5acXV1NfPZg7nKtKTCwkKlVatWyrhx43DRraw8i3vvvfeUwMBAJTc312A97lH1lWlJuEettzyPHz+uhIeHK7NmzVKOHDmibNq0SWnRooUyYsQI/T64R9VXpiXhHrXuMuW/f4YPH644OTkpjo6OSkREhPLqq68qHCJcu3ZN9sF9qq7yLAn3aM2wm5rukjw9PalFixYmazC5R05OQS7evpB7AuSnRpxaxfgJb8labe6Yq2TtN9hOmZbk4OAgHVGgptv6ylOHy4+f4g4dOlRqXorDPaq+Mi0J96j1lueMGTMkU2jixInUsmVLqYGZN2+elC1nMjDco+or05Jwj1p3mXLqMZdfVlYWxcXF0cWLF6Xdvre3NwUFBck+uE/VVZ4l4R6tGXYbdHObh5MnT0ogZgz/Urly5Yq0edA5c+aM/GByW1/WoUMH+uWXXwzet2XLFkn7ANssU2N//B8+fNjkMcFy5anDneOdPXuWRo4cWWob7lH1lWlJuEettzz5jz7+/7U4Xa+7XG4M96j6yrQk3KO28f+us7Oz/C3E5blq1Srp00ZX1rhP1VWeJeEerSGKnXj55ZeVHTt2KOfPn1f27t2r9O7dW/H29lbi4uJk++uvv64MHTpUv/+NGzeUyMhI5bHHHpN0qp07dyoxMTHKqFGj9Pvs3r1bUjdmzpypnDx5UuaczsHHB9ss06lTp0q63Llz55RDhw7pU3T27duHIrWy8tR54oknlPbt2xs9Ju5RyzJHmeIetZ3yXLJkifz/OW/ePPk/ddeuXUrbtm2Vdu3a6ff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+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# ============================================================\n",
+    "# Compare CRIMAC and echopype split-beam angles near target\n",
+    "# ============================================================\n",
+    "\n",
+    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
+    "\n",
+    "i0 = max(0, target_peak_idx - 30)\n",
+    "i1 = min(len(theta_ep), target_peak_idx + 31)\n",
+    "\n",
+    "fig, ax = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n",
+    "\n",
+    "ax[0].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"theta_n\"][i0:i1],\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "ax[0].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    theta_ep[i0:i1],\n",
+    "    \"--\",\n",
+    "    label=\"echopype split_beam_angle\",\n",
+    ")\n",
+    "ax[0].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
+    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[0].legend()\n",
+    "\n",
+    "ax[1].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"phi_n\"][i0:i1],\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "ax[1].plot(\n",
+    "    r_n[i0:i1],\n",
+    "    phi_ep[i0:i1],\n",
+    "    \"--\",\n",
+    "    label=\"echopype split_beam_angle\",\n",
+    ")\n",
+    "ax[1].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
+    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[1].set_xlabel(\"Range (m)\")\n",
+    "ax[1].legend()\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "97d6eace",
+   "metadata": {},
+   "source": [
+    "### Identify the target (calibration sphere) within a range gate\n",
+    "\n",
+    "Using the broadband point scattering strength (Sp), we identify the strongest target within a user-defined range gate and extract its range and angular position for subsequent TS-spectrum computation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "c337ced4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def extract_single_target(\n",
+    "    pc_avg: np.ndarray,\n",
+    "    power: np.ndarray,\n",
+    "    theta: np.ndarray,\n",
+    "    phi: np.ndarray,\n",
+    "    range_meter: np.ndarray,\n",
+    "    r0: float,\n",
+    "    r1: float,\n",
+    "    before: float,\n",
+    "    after: float,\n",
+    "):\n",
+    "    \"\"\"Extract one target echo from a range gate.\n",
+    "\n",
+    "    Equivalent to CRIMAC ``singleTarget``.\n",
+    "    \"\"\"\n",
+    "    idx = np.where((range_meter >= r0) & (range_meter <= r1))\n",
+    "\n",
+    "    range_sub = range_meter[idx]\n",
+    "    pc_sub = pc_avg[idx]\n",
+    "    power_sub = power[idx]\n",
+    "    theta_sub = theta[idx]\n",
+    "    phi_sub = phi[idx]\n",
+    "\n",
+    "    if range_sub.size == 0:\n",
+    "        raise ValueError(\"No samples found within target range gate.\")\n",
+    "\n",
+    "    if np.all(~np.isfinite(power_sub)):\n",
+    "        raise ValueError(\"No finite power samples found within target range gate.\")\n",
+    "\n",
+    "    idx_peak = np.nanargmax(power_sub)\n",
+    "\n",
+    "    target_range = range_sub[idx_peak]\n",
+    "    target_theta = theta_sub[idx_peak]\n",
+    "    target_phi = phi_sub[idx_peak]\n",
+    "\n",
+    "    idx_target = np.where(\n",
+    "        (range_sub >= target_range - before)\n",
+    "        & (range_sub <= target_range + after)\n",
+    "    )\n",
+    "\n",
+    "    return (\n",
+    "        target_range,\n",
+    "        target_theta,\n",
+    "        target_phi,\n",
+    "        pc_sub[idx_target],\n",
+    "        power_sub[idx_target],\n",
+    "        theta_sub[idx_target],\n",
+    "        phi_sub[idx_target],\n",
+    "        range_sub[idx_target],\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "118b42f1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC r_t    : 5.7930599853739295\n",
+      "echopype r_t  : 5.79306\n",
+      "CRIMAC theta_t: 0.19805856629305635\n",
+      "echopype theta: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
+      "array(0.19805383)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n",
+      "CRIMAC phi_t  : 2.127909429160737\n",
+      "echopype phi  : <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
+      "array(2.12793011)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n",
+      "Target samples CRIMAC : (168,)\n",
+      "Target samples echopype: (168,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "r0 = 5.3\n",
+    "r1 = 6.3\n",
+    "before = 0.5\n",
+    "after = 1.0\n",
+    "\n",
+    "(\n",
+    "    r_t,\n",
+    "    theta_t,\n",
+    "    phi_t,\n",
+    "    y_pc_t_n,\n",
+    "    p_rx_t_n,\n",
+    "    dum_theta,\n",
+    "    dum_phi,\n",
+    "    dum_r,\n",
+    ") = extract_single_target(\n",
+    "    pc_avg=y_pc_n,\n",
+    "    power=p_rx_e_n,\n",
+    "    theta=theta,\n",
+    "    phi=phi,\n",
+    "    range_meter=r_n,\n",
+    "    r0=r0,\n",
+    "    r1=r1,\n",
+    "    before=before,\n",
+    "    after=after,\n",
+    ")\n",
+    "\n",
+    "print(\"CRIMAC r_t    :\", ref_ts[\"r_t\"])\n",
+    "print(\"echopype r_t  :\", r_t)\n",
+    "\n",
+    "print(\"CRIMAC theta_t:\", ref_ts[\"theta_t\"])\n",
+    "print(\"echopype theta:\", theta_t)\n",
+    "\n",
+    "print(\"CRIMAC phi_t  :\", ref_ts[\"phi_t\"])\n",
+    "print(\"echopype phi  :\", phi_t)\n",
+    "\n",
+    "print(\"Target samples CRIMAC :\", ref_ts[\"y_pc_t_n\"].shape)\n",
+    "print(\"Target samples echopype:\", y_pc_t_n.shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "3291a82c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x700 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(3, 1, figsize=(8, 7), sharex=True)\n",
+    "\n",
+    "ax[0].plot(r_n, db10(p_rx_e_n))\n",
+    "ax[0].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[0].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[0].set_ylabel(\"Power (dB)\")\n",
+    "ax[0].grid(True)\n",
+    "\n",
+    "ax[1].plot(r_n, theta)\n",
+    "ax[1].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[1].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[1].set_ylabel(r\"$\\theta$ (deg)\")\n",
+    "ax[1].grid(True)\n",
+    "\n",
+    "ax[2].plot(r_n, phi)\n",
+    "ax[2].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
+    "ax[2].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
+    "ax[2].set_ylabel(r\"$\\phi$ (deg)\")\n",
+    "ax[2].set_xlabel(\"Range (m)\")\n",
+    "ax[2].grid(True)\n",
+    "\n",
+    "plt.xlim(3, 8)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "730f90e2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"dum_r\"],\n",
+    "    db20(ref_ts[\"y_pc_t_n\"]),\n",
+    "    dum_r,\n",
+    "    db20(y_pc_t_n),\n",
+    "    title=\"Extracted target echo\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$|y_{pc,t}(n)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6fd92ece",
+   "metadata": {},
+   "source": [
+    "### Align the matched-filter autocorrelation with the extracted target echo\n",
+    "\n",
+    "The matched-filter autocorrelation is centred on the extracted target echo and reduced to the same support. This aligned autocorrelation is required for the subsequent frequency-domain TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "ecbdd657",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype y_mf_auto_red_n: (168,)\n",
+      "CRIMAC y_mf_auto_red_n  : (168,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _align_autocorrelation\n",
+    "y_mf_auto_red_n = _align_autocorrelation(\n",
+    "    mf_auto=y_mf_auto_n,\n",
+    "    pc_target=y_pc_t_n,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype y_mf_auto_red_n:\", y_mf_auto_red_n.shape)\n",
+    "print(\"CRIMAC y_mf_auto_red_n  :\", ref_ts[\"y_mf_auto_red_n\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "7679300e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(1, 1, figsize=(8, 3))\n",
+    "\n",
+    "ax.plot(\n",
+    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]) / np.nanmax(np.abs(ref_ts[\"y_mf_auto_red_n\"])),\n",
+    "    label=\"CRIMAC auto red\",\n",
+    ")\n",
+    "ax.plot(\n",
+    "    np.abs(y_mf_auto_red_n) / np.nanmax(np.abs(y_mf_auto_red_n)),\n",
+    "    \"--\",\n",
+    "    label=\"echopype auto red\",\n",
+    ")\n",
+    "\n",
+    "ax.plot(\n",
+    "    np.abs(y_pc_t_n) / np.nanmax(np.abs(y_pc_t_n)),\n",
+    "    \":\",\n",
+    "    label=\"echopype target echo\",\n",
+    ")\n",
+    "\n",
+    "ax.set_title(\"Reduced autocorrelation aligned with target echo\")\n",
+    "ax.set_xlabel(\"Sample\")\n",
+    "ax.grid(True)\n",
+    "ax.legend()\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdc21a45",
+   "metadata": {},
+   "source": [
+    "### Compute the target and matched-filter spectra in the frequency domain"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "2aa34af3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC y_pc_t_n size: 168\n",
+      "manual y_pc_t_n size: 168\n",
+      "RMSE abs: 1.5463490954583334e-06\n",
+      "max abs diff abs: 4.604589062179967e-06\n",
+      "first 5 CRIMAC abs: [2.31729706e-05 5.79533997e-05 6.39145546e-05 3.88268996e-05\n",
+      " 1.50424514e-05]\n",
+      "first 5 manual abs: [2.05866846e-05 5.67176606e-05 6.43208689e-05 4.10774966e-05\n",
+      " 1.35798767e-05]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"CRIMAC y_pc_t_n size:\", ref_ts[\"y_pc_t_n\"].size)\n",
+    "print(\"manual y_pc_t_n size:\", y_pc_t_n.size)\n",
+    "\n",
+    "print(\"RMSE abs:\", np.sqrt(np.nanmean((np.abs(y_pc_t_n) - np.abs(ref_ts[\"y_pc_t_n\"]))**2)))\n",
+    "print(\"max abs diff abs:\", np.nanmax(np.abs(np.abs(y_pc_t_n) - np.abs(ref_ts[\"y_pc_t_n\"]))))\n",
+    "\n",
+    "print(\"first 5 CRIMAC abs:\", np.abs(ref_ts[\"y_pc_t_n\"][:5]))\n",
+    "print(\"first 5 manual abs:\", np.abs(y_pc_t_n[:5]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "5cbb42d1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "sample_interval: 8e-06\n",
+      "fs_dec: 125000.0\n",
+      "f_start/f_stop: 90000.0 170000.0\n",
+      "f_m shape: (1000,)\n",
+      "Y_pc_t_m: (1000,)\n",
+      "Y_mf_auto_red_m: (1000,)\n",
+      "Y_tilde_pc_t_m: (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "sample_interval = scalar_param(\n",
+    "    cal_obj.beam[\"sample_interval\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_start = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_frequency_start\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "f_stop = scalar_param(\n",
+    "    cal_obj.beam[\"transmit_frequency_stop\"],\n",
+    "    tsf_channel,\n",
+    "    tsf_ping_index,\n",
+    ")\n",
+    "\n",
+    "fs_dec = 1 / sample_interval\n",
+    "\n",
+    "# Use CRIMAC frequency grid exactly for manual validation.\n",
+    "f_m = ref_ts[\"f_m\"]\n",
+    "n_f_points = f_m.size\n",
+    "\n",
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum\n",
+    "Y_pc_t_m, Y_mf_auto_red_m, Y_tilde_pc_t_m = _compute_ts_spectrum(\n",
+    "    pc_target=y_pc_t_n,\n",
+    "    mf_auto_red=y_mf_auto_red_n,\n",
+    "    NFFT=n_f_points,\n",
+    "    frequency=f_m,\n",
+    "    fs_dec=fs_dec,\n",
+    ")\n",
+    "\n",
+    "print(\"sample_interval:\", sample_interval)\n",
+    "print(\"fs_dec:\", fs_dec)\n",
+    "print(\"f_start/f_stop:\", f_start, f_stop)\n",
+    "print(\"f_m shape:\", f_m.shape)\n",
+    "print(\"Y_pc_t_m:\", Y_pc_t_m.shape)\n",
+    "print(\"Y_mf_auto_red_m:\", Y_mf_auto_red_m.shape)\n",
+    "print(\"Y_tilde_pc_t_m:\", Y_tilde_pc_t_m.shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "38b09cbd",
+   "metadata": {},
+   "source": [
+    "The figure below shows the DFT of the extracted target echo. This spectrum contains both the target response and the frequency characteristics of the transmitted pulse."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "f4e0e279",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_pc_t_m),\n",
+    "    title=\"Target DFT\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|Y_{pc,t}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7c6effbd",
+   "metadata": {},
+   "source": [
+    "The figure below shows the DFT of the aligned matched-filter autocorrelation. This spectrum represents the frequency response of the transmitted signal used for normalisation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "77ef947d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_mf_auto_red_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_mf_auto_red_m),\n",
+    "    title=\"Reduced autocorrelation DFT\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|Y_{mf,auto,red}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b2fe7202",
+   "metadata": {},
+   "source": [
+    "The figure below shows the normalised target spectrum obtained after dividing the target spectrum by the matched-filter spectrum. This quantity forms the basis of the broadband TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "f8caa9c9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db20(ref_ts[\"Y_tilde_pc_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db20(Y_tilde_pc_t_m),\n",
+    "    title=\"Normalised target spectrum\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$|\\tilde{Y}_{pc,t}(f)|$ (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6091646e",
+   "metadata": {},
+   "source": [
+    "### Convert the normalised target spectrum to received electrical power\n",
+    "\n",
+    "We convert the normalised target spectrum into a frequency-dependent received electrical power spectrum using the transducer and transceiver impedances. This reproduces the CRIMAC P_rx_e_t_m variable used in the final TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "158cf758",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype P_rx_e_t_m: (1000,)\n",
+      "CRIMAC P_rx_e_t_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum_power\n",
+    "P_rx_e_t_m = _compute_ts_spectrum_power(\n",
+    "    normalized_spectrum=Y_tilde_pc_t_m,\n",
+    "    n_beams=n_beams,\n",
+    "    z_et=z_td_e,\n",
+    "    z_er=z_rx_e,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype P_rx_e_t_m:\", P_rx_e_t_m.shape)\n",
+    "print(\"CRIMAC P_rx_e_t_m  :\", ref_ts[\"P_rx_e_t_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "540bf3ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    db10(ref_ts[\"P_rx_e_t_m\"]),\n",
+    "    f_m / 1000,\n",
+    "    db10(P_rx_e_t_m),\n",
+    "    title=\"Target received power spectrum\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$10\\log_{10}(P_{rx,e,t}(f))$\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2006c97c",
+   "metadata": {},
+   "source": [
+    "### Compute the frequency-dependent beam compensation at the target location\n",
+    "\n",
+    "Using the target range angles (θ, φ), we compute the frequency-dependent beam-compensated gain. This correction accounts for the target's off-axis position within the acoustic beam and is required for the final TS-spectrum calculation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "a24e5128",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype g_theta_phi_m: (1000,)\n",
+      "CRIMAC g_theta_phi_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "g_theta_phi_m = cal_obj._get_beam_compensated_gain(\n",
+    "    channel=tsf_channel,\n",
+    "    theta=float(theta_t),\n",
+    "    phi=float(phi_t),\n",
+    "    frequency=np.asarray(f_m),\n",
+    ")\n",
+    "\n",
+    "print(\"echopype g_theta_phi_m:\", g_theta_phi_m.shape)\n",
+    "print(\"CRIMAC g_theta_phi_m  :\", ref_ts[\"g_theta_phi_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "e0d8abd9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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LB1yw3rx5E2ZmZirNVmnc6ZaAJSkpCfb29ryTXsp1qJ8MUb5Tf39/BnJEREREJYiBxX1kZmYiJSVFzTQoqb5Ks5uVtbU1A4syqEN3d3cVXMh3a+i0bUREREQVCTub34e+vz67zVQc+u+S41mIiIjKRqZGw6quJNhiUQAc+1Bx8LskIiIqG+npacg6sxr/HpmH101fgoejFbycbDAcG9Hm4Qmo4uHNr6KCYYsFEREREZWoqNs3cfzrJ9Ek7SBSdJZIStfgcmQy9lyKRI1rv+Ha/CEIPn2YtV7BsMWCiIiIiEpM8JkjSPh9CryyopEKawR2H4t/G3VFRHwaImLikLTJDS6aCGT8Ng6Hb/4fWvUaxtqvINhiUYHdunULL7zwAqpXrw4rKyuV2erhhx/Gv//+q14PDAxUXYNksbGxQd26dfHpp5+qbFh6V69eVa8fP348188yb8T169dzHU+yLcl6eV22y6t3794qw9aBAwfyLe+xY8cwdOhQeHh4qIHYtWvXxoQJE3Dx4sUSrhkiIiIqKVqtDsERidj950Js+/pZZP46Fs5Z0Ygxr4pTNZ9Hs04DUMPdHu1rVsHg1jVR64U1CHdoAktdBlx3v4PtS2dBV0pp/alsMbCooOTCvkWLFti2bRs++eQTnDp1Chs3bkS3bt0wefLk7O3ee+89FRCcO3cO06ZNw5tvvonvv//+gfuXTFlLly7NtW7JkiXw8fHJd/tr165h//79eP7557Fw4cK7Xl+/fj3atm2L9PR0LF++XJVn2bJlcHJywttvv12kOiAiIqL7kwv6vX/+gF2/fY3U5KRCVVd6Zhbm77yMVh9sRa85u5B2ZDkCIneogCHcoTGqP/cbbJ3c73qfk7MrOkz9GaG+A9XP/pd+xvbF/8fgogJgV6gKatKkSarl4NChQ7Czs8te36BBA4wdOzb7ZwcHBzW5nBg/fjzmzZuHzZs3Y+LEiffd/6hRo7B48WK88cYb2et++ukntf7999+/a3vZ9qGHHsJzzz2H1q1bY+7cudnlkpS+Y8aMQf/+/bFmzZrs98hEdm3atEFcXFwxa4OIiIjys/evRfA6+rl6fvHsMiQ0HI02D42DpZUVUjIycfz8JaQH/QJTGye412qBGg1awtLCCof//R1xB5ZhTvJYpMMS1hamuOjWHWbOWXCt2Rod2/aCNkcPiLzMLSzQ/ZlPsHt1NXgf/xIBoaux7rfqGPT4eH5R5RgDi0KQLkKpmjspaEtyDobUjCyYZ2Tedw4GGwuzAmc0iomJUa0TH3zwQa6gQs/Z2Tnfz7Zz507VUlCrVq0HHmPgwIGYP38+9uzZg44dO6pHOa50tcobWMi+JbD49ttvVXcr6eL066+/qmBCbNq0CVFRUXj11VfzPVZ+5SUiIqLikcHT7kFz1fNUU1vYZyXA/sRXOHlmBb52n4F94RlwzIrDr5Yr77zhDBD6pxkSzVzglhkFNwAj7Q6iTv/nMaipNyzM+uXav7YAaWY7PfocdmVm4MrJPfjgmDsivC7jmc41+NWWUwwsCkGCivrvbIIhnH2vD2wtC/Z1Xbp0SV3My0X8g7z22mv4v//7PzXBnEajUWMbXnzxxQe+TyaXe+qpp7Bo0SIVWMij/JzfpHNbt25VrRJ9+vRRP8t20h1KH1gEBwerx4KUl4iIiIovPkWD82tmo74uE2GOLdDuhR9xeP0iOJxegvMZVbEzNF1tZ+XkgfNOD8Eu9RZcEy/ATpsI58woaEwscLP6ULw05CXY2jkUqyydh03BqSr9oNkcjA//Pg8bS3M83TaAX3M5xMCiAtIPvi5IC8f06dMxevRoREZG4q233kL37t3Rvn37Ah1n3LhxaNeuHT788EP89ttvagyFzGidlwQRjz/+uBrYLYYPH66Oe+HCBdSpUyfXYHEiIiIq/cHWr/x2HPuSR+Alh60YNu4DWFnZoONjk5HadxSuBAXjQ0s3tK/hhgA3W5iY9Mgej3Hj2mXcDDmDgLrNUdfLv8TKNLl7bSRnaLFqxzFsWrcKPfxHwNvbr8T2T5U8sJgxYwZmzpyZa51kC5JMR3rSbUfuuEsXHulSJOMHpIuNv3/Jneh5uyNJy0FJknInJiTCwdHhgV2hCkq6MklQIfXzyCOP3HfbKlWqoGbNmmr5448/1KMMou7Zs+cDj9OwYUPVyiCBQr169dTP+uxRetI9au3atao1RMZv6MnM19LK8fHHH6uuUeL8+fMqUCEiIqLSmwX7u80nsfXcbVia26Ld6NlwcnHKft3Gzh6DOzXL970mpqbwCaylltIwvU8dtA2aDp+0YIQe94K398hSOQ5V0qxQEihIxiL9IpmN9C5fvqy64MiF7Y4dO3DixAmVPUi68pQWuViX7kglvdhYmj1wm8LMGO3q6qq6HcmYhuTk5Ltev9dgaBcXF5WeVrJDFbQVQQaCS/3nHBCek2R48vX1Vd+PBB36RQZvSxYpaeGQNLQS4Ej2qvxw8DYREVHxaDQZ2LtuEY591AOW++eodTMHNkBDn/8FFYYm1zqaKvXU89Swk4YuDlWkFgshXWf0GYvykm47kkUo58WozNdAd3z33XeqS5NkYJKUso0bN1YX8Vu2bFEtB9KakR9JRSutCNJ6MWTIkAdWp8wzIXNP3GuAtXSDkv1Ia0ZOAQEBqrVpw4YNGDRoEH788Ue1HxkULmM8pOVEBnRLC5Skql21ahW/WiIioiII2r0e2u0fwzMzUv3c1jwN7/eujidaGV9XIzv/JkD4OljF5H+dQsbNqAMLGdQr8yXI5G6SdlT68kvwIN2H5IJUsgjJnXmZWE1Sk0rq0wd1/ZF5EmTRS0hIUI/SVUeWnORnuXMvx5OlNOhbBvTHKSly4X7kyBFVZ6+88opq8XF3d0fz5s1VS4b+WHmP6+bmpgZXS1c0qUv9a/o6yPuzdN+SFpKc6/TPDx8+rFoqFixYcNdnk2xVvXr1UgGFZJKSRTJLzZ49GyNGjFDfi0zoJ/NuSGB0v7opTB3K67KdfLcyWR/9j/78z/t7QAXHOiw+1mHJYD1WvDqUv10hUSkIPr4TthfWwDrlFtIDuqLZgAmws3fM9z3RkTdx5tf3EBizR/2cZOqA2DrD0KzfODSwc8h3XKSh69CzZjNk7QPc064iOSkRllal1xOlPNAYwXlYmGOb6Ix05Ow///yjMglJ//uIiAjMmjVL9cE/c+aM+oBeXl6wtbVV6+XiU9KryuRu27dvR5cuXQo1dkOsWLFC7S+/FhO5wLW0tCyVz0llS7JfhYWFqbE6pf0fKhERUXHptDocjjTBhnAzxGWYoKfpUbxhviL79SQTW5x17ArLgHYwt7hzraLVAeHXr6JrxE+wRSp0MMEx244wrdkL5hZWRv95axyfCVtdKg4EPg97N+NrValsUlJS1E3f+Ph4ODrmH8QafWCRl4wVqFGjhmqleOKJJ9QMzzJoWAICPelGI3fCV678L99yAVssJHCQbjd5KystLU1dhAYGBpba2A2p/sTERDVRXWHGUVDR6lC+U5mVXL7z0hyPUx5JwC5d5aQlKb+0wcQ65HlYfvD3uWLUYXxsNE4ufx2/RfrjH20bWJqboosPMNwuCOZ2LrA5swqumbfvlNfEAtfghcmZU6HJ0sEeKfjJ8hNorFzg3H8GajZsVW7qcN/cp+CbeALhjSaj/SPPojLTGMF5KNfKMha2IIGFUXeFykkChkaNGqnuUfLhpDWhfv36ubaRzETSneZ+pFuVLHnJl5X3C5PMRXKhKt197pexqTj0XXf0x6HSrUN5XbbL7/umO1g3xcc6ZB0ai8p+Lkp6VMlkVBJ1mJWZibjYSLi5exVpPwnxMbC0tIa1Te7eEfdy6uA2ZG58EwFZcXjO/ASadh6KUV3qw1plibwzEV3mwAk4tGk5LIMWwiUzEna6JBVUCJ2lA4I7fIah3durWa7L03mordoQSDyBrFtnKvX5ayy/y4U5brkJLKSVQQYcd+rUSXVLatWqlZoHIaeLFy+qsQVERERU8Ry4Eo2opHR0q+0OO+v7X+wc2b4WFjs/QLRLU3Sa9C0s/usmVBRhVy7g+orJqKK5gStdZqFV90cL9f5DwTeBnx+DuSng/vRi+FWvc99gaPcf38Lr9DyY6rSIsfCA46BPMLFxo7u2lYCh/UOjkdnnSYRfvQh/C0vsd/GFtbkZ7KzMVQtHeWRTvw8+uqBDUlo9dDd0YahQjDawkJSnMqBX5qS4ffu2GkshTTGjRo1Sr8sEazLpWufOnbPHWPz1118q9SkRERFVHJosLT7ZeB4/7A5RP8+xXAAnNw84N3kIjdr3hYWlVa7usQv3hOD6v1vxlGki7KN3Y/e8F9B18ncwLULSji1nb2PP6iUYpwtXP1vt+hBRDdqiiod3gd5/NDQWY5adwICs9photh6Ry8bAbPRSeAfUvGvb9PRU7P1hGgJu/6t+Dq3SBW3HffbAma0lwAis1QAVRa16TbD1j0ggGohP1cDJhq0W5YXRhrLh4eFqDIXMzPzoo4+qVooDBw5kt0gMHjwY8+fPV+lmpYuUZBeSFKkytwURERGVT0lJCequvd6t61fx92fjsHz3nfSjjR2T0BgXERC9G07bXsP5D9vj33lTcebwDmRoMvH2n6cxa8M5LM7si6tOrSFD7wKidmLHojdz7bcgyT7WhZpi0srjWJHeHtudBiPS0hd22iSc/nl6gfZ1IjQSoxcdQnJGFuJ8eyHawhNOWTG4uWQUbobfCZL0bscl4fAXw1RQIYOtwxtMRLfn5z0wqKiI3Oyt4O96p8vYqfB4QxeHKkKLRUHmLZBJ2e41MRsRERGVLbnYDr8ajNTUJGS61FIX9RZmpqhWxQ5mpvdPrnHtxg1cW/IMvFIvIc3EGvGWHki190fV2CA01CbjJWst/IZ8jD71q+LCKX/cOLgabjd2wl6bgMCbG4G/NuL0X3b4PeMtmJhY4a3+9dG94xIc2LAUVQ99hICwP7FzpSu6PvnaXQFESnIiUpMTEB99CxFn9wLhh+GRdA6n06fLtLMY17E6RvXrj2sXTyBr1VPwiz+KA5uWo12/p+/5ec6f2I/0Na/AP+NJ2FVrji/HtEZiTH2E/vAUXDURuL5oJK62nIDTmf44Em+Pw1djMSgtAI9ZXEdmzw/QpeOdcRSVVQ+PZCTF70T0qTig1pOGLg6V98CCiIiIDOtG2BVc3P07TC2sUb/zkPt2/wm9fBZX17wH34Tj0MIc/TM+zn5tou12tHZLh3ODnmjQpiesbexyvfevEzfw5uoT+L8sM3iZAta6NFinhwKyAIiwDkT/Ef8Hn8A7k+bWbdJOLZkaDc4c+hfRx9bBM3IfnHTJmGa5Bv6Pf4reDe5s2+6hUdiZHAvfM/Phd2ExXvnYBgd0DZGckYmOGfvxkun/MklKhxvfHOVqa3EJ3QaPxyPN76Q8rVGvGXbUegp+F5fA9uBXiGvbD84uVbLnjLh8fDeSLh+AXdQJVMm4DjcALzntQNvRE2FjaQYbTz/oxi1F2I9PqcHWOPAhzmcOwiZtZ7WPPe6PYcyQl+EfwAl/u1pfgq/ZXwgLuQmAgUV5wcCCiIioEgva9RcOJrrDztUTvi42qFfVBjfP7EL8oZXwiw+CH+5kGYo9PR9HnNojs+d7aObvAkcrM9hbmSMpKR6Hf/0E/mF/wlenhc7EFAmmzqjqYKXmU0hO16CjZj+8I6KBiC0I2W6JCPt60DpXg4WrP9Yn1cEv59LUMTb6P4f2fashKysD0eGXkRh+FqbW9mj90Ph8synJ2IImHfoCHfoiLTUZZ49sRx+fWvCrfieo0Ovy+FRsWxyLgJBfEBmfhOvaVLU+0dQiu1N4lokZ0kxsEeNQB6Z+LeFZrwO6XgrHgEa599V+6Ms49ulWJKRrsfKPfbCoUh3dzryBgPRgFUjIohfm0AStn5mn6knPwzsA2rFLcfnnqYAuC009/FC/dn3U9rBH62qusDLn5K3CvWZz4AzgknSxRLJ7UdlgYEFERFQJZaSnY/ei11Q3oiUZb+KWjJQFMNpsI5422wKn/7a7YVcfptp0eKZexqWYDHy24pha74IE/Gb5HrQmpgjQZal1YY4tUOPRd9C6eh0c+u/9mswsnD1kitBTm+Fyax8cs2Lhl3hCpRNFGOCrbQMTk2F4vltNTOlRC+Zmdy4gA2tJFqRHCvx5pBWkeaeH7vl69zEzEXzmYTwPB7zi6AE7KzPYmnaAnfmzsLW1yzUAXJVbo8G5Kzfu2o+lpK1/9Bs8uzQYWZfMgEuhqGNugQBTqDEYKe5N4VijNWo07YIaVTzyLYuXbzV4vf6nes6RofmrXq85wtaZwj4rARE3r8HTJ7DA5wIZDgMLusvo0aMRFxeHtWvXsnaIiCqg+LgYnFgwAYHJZ9TPfeq6IsLME1eiklA95iZSTW1x27snavQYjU416md3dbI4E4nAC1pcj0uFnTYNJtDBTJelUqKadZ2Orvlc2FuYm6FJ+z5A+z7qzvOlM0cQcSkIGZGXYR53Fc2yYrHy4dpo27BWqX/uWg1alsh+mtavh5d6m2PLudto5ucMX4+34FbTDzXcqpbI/gmwtrVHpKUfPNJDEXb2EAOLcoKBBRERUSUg4xFiom8h6noIEv+ZCZ+M68gwsUJq9/cxs8v/AoK01FYwN7dAwzyTYgXUqI+JNYCJ/6V0Tc/QIDGuN9KSk9DMr3qBJmGT7iy1GrVWS3n3fPdaaqHSk+paD7gZisRrJwAMY1WXAwwsiIiIKqCsTA02n7mBv89E40hoDDomb8Eksz8hHX5kSTRzht2Qb9A8z138gswMbWJiAmsrS1h7+JTiJ6DKztqnMXBzI8yjzhq6KFRAHAlTQcndJJnjo3r16rCxsUGTJk3w+++/Z79+5swZDBgwAI6OjnBwcFAzml++fDnXPj777DN4eXnBzc0NkydPVv1N9WJjYzFy5Ei4uLjA1tYW/fr1Q3BwcPbrP/30E5ydnVV3qtq1a8Pa2hq9evVCWFiYev3q1aswNTXFkSNHch3z66+/VnOVSPllskP547VhwwZVftlHmzZtcOrUqVzv2bdvH/r37w87Ozv4+fnhxRdfRHJyconXKRGRsdNmZeHk/i3YNe8F1D75Ppb9+is2nLqJiIR0ROmc1HiIBDMXNRbCa8IvJdY1iKg0eNdpoR5dUq4iJunOAH8ybmyxKArNnWwS+TIxBcytCrYtTAAzywdva2FT6CL+3//9H1avXo158+ahVq1a2LVrF5566im4u7ujZs2aasbyrl27Ytu2bSq42Lt3LzIzM7Pfv337dhVUyOOlS5fULOdNmzbFhAkTssdhSCCxbt069f7XXntNXdyfPXsWFv81h6ekpOCDDz7AkiVL1ASHkyZNwhNPPKGOFRgYiJ49e2Lx4sVo2fJ/f9jkZ9m3BBR6Msv6l19+CU9PT7z55psYOHAgLl68qI4jQYYENbJe3hsdHY3nn39eLfIzEVF5p9K4rp6JLEdfeLYchLpNO9w1g/TtW2E4++9y2F/eoNKY6pO59rC5hMYtHkLv+h7wd+kCN7tXYWbOP/1UPvjXaIDxNtOwL94NvgsOYNm4NvB2Lvw1EZUd/u9SFPPvk8MhoAMw8Kv//fxjLyDzHgGDTwvgkfn/+/mnh4C0uLu3e+FooYond+u/+OILFTS0a9dOrZOWiz179mDBggXqot7JyUlNQqgPAqRVISdpifjmm29gZmaGunXrqtaNf//9VwUW+oBCAoT27dur7ZcvX65aC6SFYujQoWqdtHDIPqSVQUiAUa9ePRw6dAitW7fG+PHj8eyzz6qyWllZ4cSJEzh+/LgKiHJ69913VWuHfh++vr5Ys2YNhg0bhk8//VTN0P7cc8+pAEdmav/qq6/QpUsXFVRJKwcRkbG7VzrN+NgY3F7+LHwzb9/JonR9A45vcMOmRnOQoLPBtegkvHjzDVTJvIU7My0A6SbWuOHRBbcsq2HkU8/Civ8PUjklQfBb457AyIUHcTkyGU/M24NlTwQioBrHthgrBhYVkLQapKWlZV+M55xdtFmzZirjk3R90gcV+WnQoIEKKvSk9ULfBencuXMwNzfPDhiEdJeSi3p5TU+2ydkaIQGKdI+SbSSweOSRR1TLggQJ0pKxaNEidOvWTQU+OemDI+Hq6prrOEePHlUtKitWrMjeRrpRabVahISEqECGiMiYyP9RJw7vQuyFvdBFX4Zd0lU4a27jll0d1HvqC1T19s8ebH38xztBRby5G+KcG8Ir+gBua2yw4GBk9v4mWmSqBvCbtnVg2nAwmnZ7DLUsrfH333/f1bJBVN7UrGqP355rj5E/7sfjcT8ifkkwgh/7tkIkAKiIGFgUxbN77t8VKqfxW+6zo/9191FGr0dJkItqIWMTfHxyD6yTloGpU6c+cB95gw7pmqTfr/xRzI+sz9mFSf++vPTrpHvU008/rbosPfrooyo4mDt37gPLlnMfUqZnnnkGY8aMgb29vRq3oefvf+ePMxGRMUjTZGHtsetYuCcEjaL+xmTzO/MY6PkmncbN7x/Drb4foXHbnti5dAYCE09CY2IBh8e+VIOsZRK4WyfO4albVnCxtYS/qy2cLb+Ek4cXauSYFTvnmDii8s7H2Qa/jm2CC/NjYJeWiPTfn8Gp1C/QqHV3QxeN8mBgURSFGfPwoG3/u1gv9H7vo379+iqAuHbtmuoSlFfjxo1VlyL5w3O/Vov77V/GYxw8eDC7K5SMbZBxDzlbCGQbGZwtrRPiwoULqrVEWi70pDtUw4YN8d1336nySICR14EDB7KDBBk0LsfR76N58+aqhUa6eklXqJyBBRGRIaQmJ+HAgknwjD+OVDMHpFi4IMvSAb8lN8f6lDtzQsRZtUf/Kokwr1Idjt61YePoivi/Z8I9PQzJf0/HtMvf4MqlKnjHwhbpHV5Fm/8GWcskcN3atkS3XEfUd4IiqrjcXN3Q6PmVODZvLHySzyFzwxQcSX4fLbsVfBJFKn0MLCogyfI0bdo0vPTSS+qOfseOHZGQkKCyJ8ldfel+JNmXpPvRG2+8ocZbyMW7BADSzehBZDD4oEGD1HgLGbMhx3v99ddV64is15Og5YUXXlBjHuS5HLdt27bZgYaQQETWyeDvsWPHqgxWeb333nuqq5WHhwfeeustVKlSRXWjEvI+eb98XhkcLmWRblJbtmxRn5GIqCxpNBk4OG8C/BPuzE5tmRkNp8xoIBUYqIvAMafmGNOxGoa18oOj9f/+vxSptddg/6LpWHzTH7tPyXi72tjZ5ntM6c3MTUTCwdEFrV/8GQe+mwi/+CNw3v4GdkaGovOQF/Ido0Rlj4FFBfX++++jatWq+Oijj3DlyhU1tkHu7kv2JLlIl4Hdkm1JWjRkLIVkfOrQoUOB9y/dl6ZMmYKHHnpIjd2QLFPSnzdnC4ikoZUL/xEjRiA8PFwFODKOIq9x48apoEcCi/zMnj1bHUsGjUvaWRk4Lt2o9K0vkrlKAiT5LNIdq0aNGiqLFRFRaQUPR7f9jtSIEFRr9wgCazVQ67VaHf788X00Szimui+ldP9AtUQkxd5GWlwEXJw9sLNzFzX+LD82dvbo9vx3uHUoDEc3nEX3ulXxQr9m/BKJcpBWu44vLsau719GQMQW+J6eh39ibqLn+A9hac7gwtAYWFRQMgZB5nOQJT9yQb5p06Z8X5M5KPLKO/ZBskYtXbr0geWQrk35dW/K6ebNm6o7VKtWrfJ9XQKS06dP3/P98j7JJMWuUERUmmIib+HkxkVwvrIO7ll3MvhlXVqG7c5t4N1zElZetcevoU0x0+IEavacgOadHy7S/90j2vhjaEtfWJjxIokoPzLLe7fnvsSu376Cx5kfMT/UGwvm78NXw5shwE2fbJkMgYEFGUxSUpLqtiRdlqSFhYjIGElL6I+7Q2C+9S10xp0uTklmjoizDYRv4kn4xx3Etd9C8JPmVbmfCovB36FZc99iHZNBBdH9SdenLo9PxZ7jfRD6Zxjiw+PR/8vd+KyPG/p1yP9GJZU+BhZkMDLmYuXKlWq8xL26QRERGTqo+PDvc/hhdwgamrRHHYc4mDQdjhY9HoellRVCLpxAyKbvsCpCMvCZ4N2H6+ORYgYVRFRwHZvWwz+BgZj6y3HcunoOgZum4+AODyQ514eVTwN41GyOmvVbcAxGGWFgQaVCZs+W5X6ky1V+3a70ZGbwe6W2JSIqbTKPxLcrfscP5xzVzwP79kO7TpNzXaBUq9ME1eosQN24VDyflI7Gvs78YojKmMzGvXJCW2z69TgszmWiSno4qkSEAxGbgSBgu3d/dH/2C34vZcBoO3DOmDFD9TXNuXh6eua77cSJE9XrBZ0DgYiIKKeszEzcCL2E4DNHcPboLhzb8w92fzUWAy6/h65mJ/HpkMZ4pkvNe971lAsbBhVEhmNmaoL+TzwHx+c2I6bTewitNgzhDo3VawE3/sbZIzv59VT2FguZ/Xnr1q3ZP+ecCVpv7dq1aj4Fb+//TQxERER0P1FJ6fjrxA2cuZGAiBuheCvmLVjoNOpum9V/i7RTZJqY4/keddGyJeeKICoPqnr6qQUYpn7e9t0LCLi1BVe2zEed5p1VAEKVNLCQlHz3aqUQ169fV/30JbvRgAEDSq0c7I5TcfC7JKrcv//nT+zHzV1LcDjSDPM0d/5umMAEOss7QUSaqS0yTKyRaWYNjYUT3LpNRstWXQ1ddCIqoqZD38K331ri5/iOiD10DU+3DWBdVtbAQuYtkJYImUW6TZs2+PDDD9UMy0Imfnv66afVXAzSslEaZE4G6WIVGRkJd3d39bykyeeQeSDS0tI4a3Qp16FcVMh3Kd9jUWYcJ6Ly68LJg4jc8D68Ui9BLivcTaxwxHcIOtb1Qx1Pe9jZr4WPbwDM7jHHBBGVT67ungjo8wLS/zyDzzZdwIBGXnC1uzMXFpU8o/0fVAIJmSehdu3aiIiIwKxZs9C+fXucOXNGTfD28ccfqxaNe83TcC/p6elq0ZMZqYVGo1FLXtJiIvMsSGrU0iAXu3JBbG1tXSqBS2VQmDqU1728vFQwIgv9j/78z+/3gAqGdWh8dZianIRDv32CwLC18IIOWSZmCHPrCM+OI7GiUetc22p1OmgryPnPc5F1aAyM5Twc2swLKw5ew8Vb8Vj+xx94dvgQlBcaI6jDwhzbRFdO+oYkJyerGZVfffVVNcOydH0KCgrKHlsRKKnGpk5Vy4MGhc+cOfOu9StWrFAzRd/rYjS/8R1U/mRlZbE7FFElkRgdjprXVsBdG61+Pm3VDOnVB8DK1sHQRSOiMhYal4E6l+ajpsl1HAh8AfZuTAtdUCkpKRgxYgTi4+PVZMQVIrAQvXr1Qs2aNVGnTh28/PLLubq9yAWj/Ozn54erV68WqsVC3hMVFfXAyiqtKHDLli3qs7F7DuvQkHgusg4r0nm45tgNLFi3DV+azoXGzAaZnV5F006Fnwm7vOLvM+vQGBjbebjru8kIjN6Fm9Y10OrlP2BaDm4aa4ygDuVauUqVKgUKLIy2K1ReEgzILM2dOnVSYyt69uyZ6/U+ffqo9WPGjLnvfmS8hix5yZdlyJPe0MevCFiHrEdjwXPRcHWYmaXFh3+fx6K9IZIfBn9Ufx0vPd4Hjk6uqIx4LrIOjYGxnIeNH38HUfMGwCvtMo5sWYEOD5efyXktDFiHhTmu0QYW06ZNw8MPPwx/f3/cvn1bjbGQiGnUqFFqjIUseT+0jIeQ1gwiIqp84qIjcWzR8zga0x5ATbzYoxam9qgFU6aXJCJJ2uDpi7P1RsH37PdwODoP8Z0egZNz5bzpUFqMNrAIDw/H8OHDVRclycjUtm1bHDhwAAEBTBNGRFTZxcfG4PLp/YgLOQbEhMA6+TpcMm7AX5eBNyzDEP/YL+jTmHNPEFFu7R97HkGX1qNKxg0c+eUj9Jj4KauoMgQWq1atKtT29xtXQURE5d+hkBj8diQMQddi8WbcDASa3IJTnm1izKvCfdhXaFuXQQUR3c3CwhLW3V8DNk6B/40NuHz+SdSo25RVVdEDCyIiIr0de/dh3IZYZP2XJfqseQAcLXVIdKoLs6q1YedRA1V8a6FZYG2YG0FfbiIyXk3a98H2g22RFHMTW/+9hLl1mjDlfwlhYEFEREbtwMbl8Nn/AUaadMeNBqMxrKUfmvl2h6uDjaGLRkTlVJ2nPkP3rw4hLUyHHidvYmCTO9MXUPHce5piIiKiMpSemYXztxKRnpYM3X8TWO7fsBRV9s2CqU6Ljl5afDeiGXrU82BQQUTF4u1eBZO71lLPP9hwFvHJaazREsAWCyIiMiiZTmnTmQjM2nAW0bGxWG/5Hq6cnY00UxtUzYpX24R69ka3iXPKRd55IiofJnSujj+PhqBP/C8I+v5ndJ2yCCY55kijwmNgQUREBnM1+DT+3LgJc67XVT/XsUhQjxa6DFhkZajnod790XXCpwwqiKhEWVuY4Zt+LjD7fS9MY7XYs2Y+Oj02ibVs6MBCZgW8deuWmvJbUsO6ujInMBER3d/eP3+AR9Ac9NMBa81ew4DObTGhY3f8u9EBTRvURlzEVWi1WnTrMpB3EYmoVNRt1Ao7zz4D3zPz4XHyWwTXbY1aDVqytss6sEhKSsLy5cuxcuVKHDp0SM2Mrefr64vevXvjmWeeQatWrYp6CCIiqqCO7d4Aj6NfwAQ63HBsjmVDO8A3oKa6UWVmbgG/GvVQvW5jQxeTiCqBzkNfxM6ww/BLOIqY1a8gyX8d7B3yJrOmgihSR7I5c+YgMDAQP/zwA7p3747Vq1fj+PHjuHDhAvbv3493330XmZmZ6NWrF/r27Yvg4OCiHIaIiCqgK+dPwGrrWyqoCHXvhi4v/6yCCiIiQ5BxFU3HzEWCmQtcNRE48ud3/CLKssVi37592L59Oxo1apTv661bt8bYsWMxf/58LFy4EDt37kStWndG3hMRUeUVFXEDcb9OgpMuDdft6qHjM3PZzYmIDM7ZzR1pLZ+D48EP4XhlPbIyp8PMnEORC6tINfbbb78VaDsrKytMmsRBMERElVFWZiZCLp5EnKkrUkztkJmeCqv1z8EzMxoxFh5oPP57WFpZGbqYRERKs+5DcOnwXFhnJuJQ0BG0a92WNVNIDMWIiKjIktMzEROfAJOUyDt/VCyscPX0PqRc2An3mCOw1SZjtmYCjujqwhRaTDLzQl+Lm/AYMV/dISQiMhbWNrY4UP9tfBGkRbuzZmjX2tAlKn+YFYqIiIpkdVA43lpzGnUzz+Mzi/lqnaTxyBkupJtYw8vFFnUtHWBlYYZTNs+gTwcX+Ndg91giMj7du/XCrKCd2HbhNsJjU+DrYmvoIpUrzApFRESFkqnR4Nt1uzHncOp/f0kskGFipQZjW+oyEGnpg2SvtqjaqAfqNuuEry0sWMNEVC5Ud7dHh5pu2HspCuv2ncSkAewOVeqBhWSF+uCDD1RmqIEDB+L111+Hj48PbGxsEBMTg9OnT2P37t0qK1Tbtm3x9ddfc/A2EVEFEBcdiRMLn0OHpFAsxUt4snsLTO3ZH6amk9XrOm0WqptydmwiKr/GNbLCqNAv4HEkCZree2BhYWnoIlXswGLPnj3MCkVEVMlE3AhF2I9PwTczEhoTS3zbzxltu9TJtY0JgwoiKuc6NW+AsxuTYJ+VgOM71qJVr2GGLlLFnsfir7/+QtWqVdXzUaNGITk5+b5ZocaPH1+8UhIRkUHFxUbh6qKxcMmMRKy5OyyHL0PbLv35rRBRhSMtFNEBd/5/Szn2q6GLU/EDC+n2dOzYMfX8559/vmdgQURE5V9qchJOzx+DKhnX1QRSPmOXonrdJoYuFhFRqanbY6R69E06jWuXz7OmSzOwmDZtmhpb0b59e/Xz8uXLcejQIaSm/jeQj4iIKoRMTQYOzpsIr9RgpJrawunx+fDyrWboYhERlSpvv+oIc2yungdvX8raLs0xFpMnT0bXrl3x559/4sCBA/j2228xffp0mJiYoGbNmmjSpAmaNm2qHvv161eUQxARkQHERN7ClVP7cQU+uJzugKALoRgffwuZphYwfXguWyqIqNJwbPk4sC0IHuEbkZL8BmztHAxdpIrZYiEaNGiAN998E9WrV1fBRWJiohrUPXXqVLi4uKigY9iwog92mTFjhgpUci6enp7qNY1Gg9deew2NGjWCnZ0dvL29MXLkSNy4caPIxyMiquyO7fkHN77tD5cdb2D71vVYsPMKDt/KwrSsyYjrNQf1W3Q2dBGJiMpMk44D1JgyG20KDm3hWIsymSDv0qVL2c/btGmjFj2dTlesfUvwsnXr1uyfzczupDBMSUlBUFAQ3n77bdUqEhsbqwIa6Z515MiRYh2TiKiy0Wm12PXrXPic/UHNRRFrXhUNvD3g6RMIT0drtK9RBY18nQxdTCKiMmVmbo6YZpPx+f5ruHkxEP9qdTAzNeG3UNozb9+LtDIUh7m5eXYrRU5OTk7YsmVLrnUyV0br1q1x7do1+Pv7F+u4REQVSXp6Kq5eOInbl4JwNMkNx7MCUcPdHnWq2qORRRhu7l6KgKidatvQqj3QYcJnaGllY+hiExEZXMc+QzA9aBviY9Kw5ewt9G3oZegiVd7AoriCg4NVNydJWystIR9++KHqepWf+Ph4Fcg4Ozvfd5/p6elq0UtISMjuXiVLWdMf0xDHrihYh6xHY2Fs52JWZib2rvgAvtfWwlyXCW8AR7LaY0fWY9hxIRLuiMUqy1kIAKA1McWNBs+i46CJMDE1NdhnMLY6LK9Yj6xDY1ARzkMLE2BEa1/M2xmChTvOo0edKpWuDjWFOLaJrrj9lUrJP//8o7o81a5dGxEREZg1axbOnz+PM2fOwM3NLde2aWlp6NixI+rWravS3z5o7MbMmTPvWr9ixQrY2tqW+OcgIjIETXoq7C6sRG3NBfVzsokNbpr5IdS2EYId2uB2mgmsk67h2YzFyIAlgn2GwMGjBr8sIqI8EjKAc8d3YqjZTpwNGAn7KoGVqo7kenzEiBHqJr6jo2P5DCzykrkyatSogVdffRUvv/xyrihq6NChqgvUjh07HviB82ux8PPzQ1RU1APfWxqk/NKtq1evXrCwsCjz41cErEPWo7EwlnMxLOQCon55Hm6aW9CYWCCmzWto2WOoaokwdsZSh+Ud65F1aAwq0nm4a8FUBN7+F6FOrdHpxYWVqg4TEhJQpUqVAgUWpdoVytTUVKWl/fTTT9GiRYti7UuyP0kWKOkelbOyJfNUSEgItm3bVqDAQLpVyZKXfFmGPOkNffyKgHXIeqzM52JUfBKOhCXhaGgMYg7/jknaW2oyO/tHv0T7Rq1R3vD3mfVoLHgusg5Fjd4TkfXzvwiIP4SQ88dQu4z/X7Uw4HViYY5bqoHFokWLEBoaihdffBF79+4t1r6kleHcuXPo1KlTrqBCAo3t27ff1T2KiKgyOLl/C1L/nY2QNHu8nvnMf2tbIcDdBMOfGg93Dx8Dl5CIqPwLrN0Y213bwz9mHxLWvIJ4vz/h5Oxq6GIZnVINLEaPHq0e33333SLN7v3www+rDE+3b99WYyykKWbUqFHIzMzEkCFDVMrZ9evXIysrC7du3VLvc3V1haWlZYl/Fio/Im+F48L+9chMTYCTbz341G4K96o+5aIbCFFhSF515z0zYafLgrWpDepWtUOLam5oXc0VfRv2hZX5nRTdRERUfM1HfYZLXz8Ml8xIBC2aiq5Tf+K1RWkEFnKBv3v3bnVB36FDBzRu3LjY+wwPD8fw4cPV2Ad3d3e0bdtWTcQXEBCAq1evYt26dWo7meE7J2m9kO5XVLlEpgJLdpxC3SPvwCv1ErKTwZ0HErcCt0wdEOnRAR3GzIa1tbVhC0tUAvas/R5eQV+o59dc2qLZ6M+w0aVss5UQEVUmTi6usH/kC2T9MRb+cYew6/ev0WXYFEMXq2IFFnPnzlWDqSXNq8w7IYGATGz3008/FWtcxapVq+75WmBgYLEn36PyTZuVhcvnj+Hk6dNYcL0aLt6WU/kGVlhEAybATZuayLD1gm3iFVTR3ICdNhHbr8fjp5+PY8HIlrC1NOpMywaTngXcTkyHjyvH+xiLDE0m9l6OQVJ6JqzMTWGfEQld0DJ4hd65uRLq1QddJnyuJnIiIqLSVadxG+wOngTPE9/ir5M34dA2Fs39XVjt/zEv6tgJaSmQAELmlpg9ezamT5+u5pEICwvDggULVKuBpIyVNLBExXXywFZE7f8ZVqm3YaOJhYM2HqY6LWrCBpczZsLUxBRtq7sh1v8d1GrcADW8/jdJYlpqMk4c3oPvt2Yh+VI0Ri06hEWjW8HB2qJCzJh8Nmg3EiPDkJmRgqz0VECbCb+mPVG9bpMC7UOjyUDQ0QNYetkOm8+YIevwTrzewQlj+7SBORMKGExkxHWc2rQYjiF/Y1rq84jGnZmvHzfbjmfM1qvn16o/gW4j32FTPBFRGeo4+DnMSPDH7xdMsW95EP59pStsLNn1tMiBhWR5unTpknqu1Wpx+PBhzJkzB82bN1cBh4yH8PHxUeMkpPsSUXHsXbcIVY9+hgCdNtd6lUbTqSG+aOOPlFuhGDKwZb6ZC6xt7NCmcx8sDYjF6MWHEHQ1Cr999Rp6DZkIMwsLZGk0yMrKgJd/LVhZlV03qYz0dIRdOYvbIaeQmZYMC1tHWNo5wcSzMazsnHE9LhWpF7fB7sYB2Po3R9v+T+e6gNRqdVi2dAE6XvkSeUutO/sDdtk1gHW7cWjRsZ+62x186iASzm2HScxlmGalwSRLA1NtBpzSb8JVm4LdGe9CA3vYIA31D36AA6dcETj8c/gG1imzOiHgwokDuL5zMfyid2ef80Nsj+GE56NIz9TCOdkVtzMCkFV/MLoNfpZVRkRUxuRv8bThfbF17m71t3r9yRsY2tKP30NRAwvJziST0p06dUplaZK0sr/++ivefvtttd7X11fNOXHs2DH89ddfaNiwIapVq8YKp0KR7m5ztwbj7IEwvG6uxTW3DnBs/BDsXb3g4u4NV3cv1LWwUBnC/v479IH7axHggpUT2mLPj9PQJWk3Mn76O9frZ8xckN76ebTtM7xQd4A1WVpcunoNSVePIjX6OjITbkKnSYWVZ1141G6JarWbqDv/t+LTcDQ0Fokn1sEvbB2qpoeoVpeqefb3ouZ5nNHd+X0ZabYfo8w2A7c2YXvIfrQf/7kKlLK0Orz6+0msOe+LN8ybo6F9ItItHKE1t4GZJhk+icfhk3wGizdtxjM7zBGfqsFY078xwuzffD9DkqkDJjUxRYY2Ew287OG6KwVWqTFIXDwMO2oPh713HVjZOcHazhFV/WrByfHO3XMqmfNczuGgbb8h89hKNUZIZsIWN21qwbzZE3il2xBYZqfJ7gDgTVY9EZEBSa+Hp9r4YNvm9UjesQ1o+Tm/j+KMsZABsK1atVKDtZs0aYJffvlFtV5I0HHixAns2rVLTVgnmaFiY2Nhb2+vsjoRFfRi/c3Vp/Db0XAALdG5cUM89ejgYnf5aOjjBPvhLyDi18tw1dxCFsyghRlMoIVTVix0+2fh2Us2mPRIdzTxc853HxkZGYi6FYbjtzOxMTgF2y/cRr30U/jI4sfcG97cCBwDgk0sMcPyFRxMvDOw9mHTa5hqflk9TzO1QYx1ADItHVVAYJ6VDDvbKnDTWMLL2Rr29h1xNc0U/rc2IyByB4LmPIbAJ7/Bx3vj8OfJCJiZmqHqY5+gXTPf3IcOD8G5zQux81ozxKVo1Lpwh8a4ZpsJM8/6MLdxgKmFFcwsrGHr6IoGTTuiPoC///4bnTt1R2St1bi8/GV4p5yH34WfgDuTNyvDM6fAxq8JutR2R7dAG/i72SJTk45MTQayMjPh4RMIMzM2CeccD3Rk2x9IunIQJslRsEiPga0mBrGZVhiveQUyXMweKfjV8mNYIQNZJmYIr9IJPl3GoGPjNsU634mIqPQMqW+PXjsWwiRBi8vnR6JGAbsgV2TFHu33+eefq/EUV65cwbPPPquCDEkRK5mivL29VXYnWU6fPl0yJaZK4del32HjBQ+Ymthi1iONMKLN/8ZMlEQu6sD/25ZrXVpqCg6s/gpHLoRi03UrbPp2L6rbZ+IT7efINLVElqmVCj7sNNGwz7oTIO/L6ot1Wb3U8yRrD9yyqoEMa3fo7D0BMwuYR51HleRgWOnS4JF8EaYmVVDPyxF+3r0QaVcP/vXborpf9buCpfZ3lXiYmqvAZNPr8Ei7irRFD6F9Vh38YzoBc4c3R/9G2Tmwsnn5VoPX2Flol5GF0zfiEehmB3eHuyeGzEnumut5+1WHx7Tfsef3L4GwgzDPTIZFZjIytTqcz/CFNjRWtb6Ymv+CfqaHcu3niIU3qgydU6n+g5Xz51bYZbhW9c3VEnFk2xpk7f8O7hnhyDvTTpKuigoq1HPY4h/z7mge6I5Gfcagtod32X4AIiIqNJkn6LRza/jHHsDVnT9Xqr97pRZYyJiKo0ePqqBCUsLqszVJhigZ5C2ka5QsRAVxbM8/aBvyDX60dELio8vRs2nJBRX3Ym1ji65Pvo56CWm4sfE8VgddR1JSIlwsb+e7vdxVbmoXC/tmNdCrflU09XOBmenT+d6tvnb5DMamAx/Vrg87q6L9yjVu1ws3fKojdNkkVE0PRTOzS1gywBnt8gkqcpLBZK0CizaBj2QZ6vLEK3et3x2Xil0XI7HzQiSaXLoG/HdxrDWRlh+dysKlWfkU9rZ8CR0eHnvfY8QmZ8DZ1kIlfjAmMqD9avAplRTAxtYBDi5ucHC8O+tHanISDq3/Ec7nVsBem4DbMMFh08H4O94b1+PT8ETEz2hnGq5apiK8e8HCLQDWTlVh7+aFGlV8cNjZG6YmgKmJCRxt+sNMfiAionLDpdXjwOYD8Lj5L1JTkmFja4fKrETyE8p4ii1btiAiIkIN1pauIhJk+PlxIAsVTnxcDPDve+p5kk9n9Gxas0yr0MPRGl8Ma4rX+tZFVFwC0qMCoElLgUayLUkO6yrecPX0g6ubB2oXoFuWqZmZaiEpCd7+NeAy9Q8cWv8DqtZuhXbNDJNxzcfZBsNb+6tFm7kVWdosmJtbqJaXmMhbOPXTFPgmnsChA3uwJq0F3h/U8K5sGTJwfeOSj/D6lUao5euBqT1ro2sd9wcGGGmaLJy5dhtJh1dAe+u0NAvAvtEANO0yCBYW+U+MmZAQi6Prf4Bz8BpY6NIRZ+WNDHtfmLoGIqPuYPj7eKkWHXNocerAZsQeWwvP6MOqpUnIN38bthhn8TEC3GxRw90e3SzOwDY5DC7Bv8NXm5gdbJrpshCc7oqDZ+8EpL9Y9od39cZoMehFNHDhDK1ERBVN43a9cXybG5wyo3Fs+x9oP2AkKrMSTXzu4eGBQYMGleQuqZI5uuxNBGTFIsbCA+2fKvyM7SUZYMgC/7xDqw3Lxs4eXR5/CcbC1Nwcpjn+G3F190Snl1dg82/zseCED9KOhuNkeBw+ergmWtT0UdtER97EuYXPokHKBbxufhrvhI/BmJ8OY6jHTQypbwedNgupkaHQxYfBMukGLDMTcAPu+MB0IuJSMpCZlYW1lj/DXl3yA9h1AGf3fIJov97waNwLcPKBib0HJEa5uH05al78Hv7a1P/VYeolQJZIYPCpakjAnQx3r1j8gf4m++D433bSypAJcxVghGvdEZ2coZaga3F42OI7+JhEqe3izKsgrelotOrzNGKiItB68yF0r1Zb0oZgaMtecLXLP+AhIqLyT24gJlR/CE4Xl0B76g+AgQWRcTi8bbUaoKyDCewGzFIX0VQ+/5Pt+8RkLG4VjRdXHUNwRAKilozEDmcv2DUdDLO9X8ArMxrpJtao3vVpPJNRHcv2X0GfmJ9RZe+tfPeZpNMhUpOunlext8EZpwHwdnWANjUObuH/qm5I9qF/AKF/YHFWX/z839iX1ibJ+MgiFVGW3tA2G42q1RshOjwYKRGXkRF3A9XhgytRyUhIy4SDLhEpZvaI9OoCr9aDUa9xO/VZhG9KKtbHZuBqdDIuRSRCc7YurqfHwaxef7Tu+1R2a4lbVS/UdLVA/w6B+aY+JiKiiqd+z6cQH7wMXikXcPXiyRLrqVAecapWMriUjEyVu9921yz1c1jgY+jWvJOhi0XF1K6GG/6Z0gkr1v2N6hduwjT+OrDziHpNWqTcn/gO9Ws1gHToeqa9N07+sQ/RN/YhzdIZmXbeMHXxg02VANi6eMDT2gF/V6kDJ1sLeDtZw8SkZ67xEMd3/YXkY6thn3INZpZOcDexUpnFMt3aIrJBXbTu1C87SKhRr1n2e3v/N8g6ITUTidGN4OHpiUb5dKmyt7VBQ1l8/kuz2ytPBjAiIqq0qnr64axTC2TFhiEk6CLGM7AgKntbzkbg1yNh2HHhNvrp9mKKeQqiLH3Q/sm3+HVUEFXsrfDiiMG4GlwbIX99DP+4Qwh3aIKm4+fBKceYgyrOTug+7oMiHUNaC1r1eAyQRSUnBmYW4v0yrkMCFifb0k8SQEREFZNJn/cxbtlpOF2wxFOaLFhbVM6066XaYiET50kqWpmpu0WLFqV5KCpntmxciw92RuGq7k5WoxuO9RFqfxt1B70GKysbQxePSlhgrQYIfHkp4qIjUd3FrdjzkRARERmTjvUC4ON8Rc3EvfH0LTzS7M64wsqmVAMLSTcbGhqKF198EXv37i3NQ1E5y/nvfnA2FlrE4Z/qb6F3v0dQ28MBwJOGLhqVMmc3d9YxERFVOJIufFhLP8zbegondq/DI82eQ2VUqoGFzLot3n3XcNl9yPgc+utH+GTFId7MFROGD2ELBREREZV7w5q6otuu92EXlYqrwZ1Va31lw/4IVKZkQjGnsz+r5ylNRjOoICIiogrBq4obYpzqq+dXti1GZVSkwCIxMRHTpk1D3bp1UaVKFTVBXv/+/fHBBx/g/PnzJV9KqjAO/bVApQaNM3dD636jDF0cIiIiohLj0vZp9eh1YwsSE2IrXc0WKbAYOXIkfv/9d4waNQqzZ8/GlClTsG3bNqxYsQINGjRQk+TduHGj5EtL5VpyYjxcz69Uz9OajYOllZWhi0RERERUojNxR1l6w1KXjmObllW6mi1SYLF582asXbsWb7zxBsaPH68GZ8tkUH/99RdCQkLg6emJVq1aqedEeofXzYetNknNYdCm752InoiIiKiiMDE1RUb9oeq5zbnfoc3KQmVSpMDCw8MDycnJ+b7m7++PBQsWYPLkyaolo6hmzJih8svnXCRg0ZNJrWQbb29v2NjYqLS2Z86cKfLxqGRdOhuEbV8/h52fDsOzCzbj6YUH8ffFJCTCFlktxsOcsxITERFRBdS895NIM7WBa+ZtHN/3DyqTIgUWEjCMHTsWJ06cuOc2Tz75pOoeVRzSrermzZvZy6lTp7Jf++STT/DFF1/gm2++weHDh1XQ0atXLzX+gwzn8vnj2P7FKJisGoGAyO3wTTyJEyG3sDs4Cr+mt8X/OX2EVr2H8ysiIiKiCsnO3hERPr3V80MH96q5LSoL86IGFhEREWrSu549e+KRRx6BVqtVrQp6K1euVAO7i1U4c/NcrRQ5Wyvmzp2Lt956C48++qhat2TJEtWSIuM8Jk6cWKzjUuFpNBnYNX8KAiO3Qz9/cahbR9jU6ow33dtBY2aDlIwsdKntDjPzUs1yTERERGRQtftNxpPzGyI0yhVffLoDT7Xxx/MdqsK1gs/nVOQrvA8//BCDBw/GZ599hldeeQWpqalo2LAhqlatioSEBKSlpeGnn34qVuGCg4NVVycrKyu0adNGHbN69epq7MatW7fQu/edaFDINl26dMG+ffsYWBjA7qUzVVAhQl3bo1q/Kehep4khikJERERkUL6+/vhq4sP46J9zOHAlBucObEDE0eU403giOj02qcJ+O8W6dSwDtH/55RdkZGQgKCgIFy9eVEGFtFR0795dBRlFJYHE0qVLUbt2bdU6MmvWLLRv316No5CgQkgLRU7ys8z0fT/p6elq0ZPyCo1Go5aypj+mIY5dUnacu4mEq8cRYALcbv8uOvUYUqafqSLUoTFgPbIOjQHPQ9ajseC5yDosrvqedlg6ugX2XI5G7J+/wzIlHd4nvsIeCxu06fdUuTkPC3NsE530Kyqka9euqUHaBXX9+nX4+PigOGSwuMyX8eqrr6Jt27bo0KGDSmnr5eWVvc2ECRMQFhaGjRs33nM/MuB75syZd62XLlS2trbFKmNlFJsOfHLSDGmZOox3O4sGtesaukhERERERkWn1SHj4j9okbwTWpjgoO94OHjURHmQkpKCESNGID4+Ho6OjiUfWEjLwMCBA9WFfOvWrfPdRg7+66+/4ssvv1Rdk1544QUUlwzOrlmzJqZPn66CDGkladasWfbrMn+Gs7OzGm9RmBYLPz8/REVFPbCySisK3LJli/pskrK3PNFkZuGpxUcRdC0ODb0dsWpCa1iZl/1k7uW5Do0J65F1aAx4HrIejQXPRdZhSdNmZWHP/MkIjNmLNBNrWAz9EdUe0G3cGM5DfW+kggQWReoKde7cOTXeoW/fvupDtmzZUo2FsLa2RmxsLM6ePau6LMn6Tz/9FP369SvqZ8kmwYAct1OnTqhWrZoa1C0VrQ8spDvWzp078fHHH993PzIWQ5a85HMY8qLU0Mcvit3L3kOH6zcQYvUovn2yOextDDvhXXmsQ2PEemQdGgOeh6xHY8FzkXVYgicTOj73DQ7NGQ7vlPNI+OMFxExYBQ/vAKM+Dwtz3CLdXnZ1dVWDtqUr0rx589Q4CLnjL4Ot9almjx49ir179xY5qJg2bZoKFGSg9sGDBzFkyBAVMcls35J9aurUqSq4WbNmDU6fPo3Ro0errkzSVEOlL2j3BgRc/Q2PmO3Fd12yEOBmx2onIiIiug8rKxs0nrhIzc7tmBWL1cu+RnxqxRkjWqzB29JCIele9SlfS1J4eDiGDx+uAhZ3d3c1ruLAgQMICLgT1clYC8lENWnSJNVKIoO9ZUZwBweHEi8L5RZx4xos/n1XPQ/17o/u3QeyioiIiIgKwMnFFX6jfsRPi+fj+9jO2PDjASwd2waudpYo74x2QoFVq1bd93VptZCB2LJQ2cnUaHBx6Qvw1iYhwioA7UfNYvUTERERFYK3X3UMnvB/+OPHgzh9PQFPzd+FJU/Vg7tH8ZIdGVqhu0JJK4FkecpLxlRQxbfr51nwTrmAdBNr+A3/CtY2zKRFREREVFj1vBzxy8R28HYwx4jY73B1wXDcDA9BpQksfv/9dzWeon///mjcuLEa+6D39NNPl0b5yIgc2/MPAkJ+Uc+TOrwGv+p1DF0kIiIionKrZlV7/DqyHupZRsA18zZClk5SvUMqRWAhk9RJitcTJ05g0aJFGDt2rJr/QRQhay2VI1qtDlt3bEMUnBDq1Retew83dJGIiIiIyj1fP394j/0Zqaa28EgLwZ7f5qBSjLGQXLoykFpIKtldu3apgduXLl1SYx6o4joeHodvk7piqVUPHB7T1dDFISIiIqowvHyrIaTli7A5NBveF5bg6sW+CKzdGBW6xaJq1ao4efJk9s9ubm5qLgmZXyLneqp4tpyNUI9d6lRV2cCIiIiIqOS06z8SYY7NYabLwvXf3yiXXaIKFVgsW7ZMBRc5WVpaYuXKlWrOCaq4Qk7thym06FXfw9BFISIiIqpwTExNUX/EbKSZ2sAz7TL2/j4XFTqw8PX1VTNe53Tq1ClkZmaiQ4cOJV02MhJhVy5geuLH+M3yPXSt6Wzo4hARERFVSFW9/RHf4gVc11XBF2fscOl2EirVPBZNmjRRrRb169dXz5s2bZr96OzMi9CK4MqhDfAFkGwfACd7zrBNREREVFraDRiNCZG1ceJiPL7fHYKuNhV4Hou89uzZA1dXV1SrVg3p6en46aef0L17dzX+ok6dOnj77bcRFxdXMqUlgzC9uuvOk2pd+A0QERERlXKXqInd66vnW89HIlNbiQKL559/Ht999x3++OMPlXr22LFj2L59O6pXr45Ro0Zh9+7daNasGSIjI0umxFSmYqNvwyvlgnpes+0A1j4RERFRKWvh74KG9onor9mC+NuhlSewOH/+vOoGlVOXLl0wZ84cNeeFBBmSmvbNN98s7qHIAM7t/xsm0OG2VYCafp6IiIiISpepqQlernIIz5ith0v0ocoTWLRq1Qo///zzXesbNGiAzZs3q/ktpk+fjq1btxb3UGQA6Re3qcdU346sfyIiIqIyUqVpf/VYI/0MNJqMyhFYSDeouXPnYsSIEar1QmRkZKgWCxl7IWRSvYiIO/MgUPmRlpoMz/jj6rlfi76GLg4RERFRpVG/RRckm9rDTpeK80d2oFJkhZKWif3796uxFtIlysrKSqWfNTc3x+LFi9U2Mu7C29u7JMpLZWhvSAI+yXgO3e1C8Gr9Fqx7IiIiojJibmGBCz6P4kBIPJxu2qN5ZQgs9MGFjKUIDQ3FiRMnYGZmhhYtWmTPeSEtFrNnzy6JQ1EZkkwEF3T+aNOok8pQQERERERlx6/beGxMPYin2zYsF9VepMDi2rVr8Pf3v2t9QECAWvKSDFGdOnUqWgnJINI0Wdh4+pZ6ztm2iYiIiMpeiwAXRARo0cDbsVxUv2lRB2xPmDABhw7de5R6fHw8fvjhBzRs2BCrV68uThnJAIL+/RWTMhajs8NNtK9Rhd8BEREREZV8i8W5c+fw4Ycfom/fvrCwsFDpZGUMhbW1NWJjY3H27FmcOXNGrf/000/Rr1+/ohyGDEh7fBW6m15ATf9GMDM14XdBRERERCXfYiHZnj777DPcuHED8+bNQ+3atREVFYXg4GD1+pNPPomjR49i7969DCrKoZALJ9SkeFoTUzTo9bShi0NEREREFX3wtrRQPProo2opbR999JGaZG/KlCkqva1ISkrC66+/jrVr1yI6OhqBgYF48cUX8dxzz5V6eSqykB3LICNlwp1aoZann6GLQ0RERESVJStUaTt8+DC+//57NG7cONf6l156SWWjkgn6JKiQCfkmTZqkumUNGjTIYOUtz1KSE+Fx81/13LXNE4YuDhERERGVE0afQ1RaJaRrlQwEd3FxyfWazJ8xatQodO3aVQUWzzzzDJo0aYIjR44YrLzl3bF/f4O1NhWx5u5o1La3oYtDREREROWE0bdYTJ48GQMGDEDPnj0xa9asXK917NgR69atw9ixY1UrxY4dO3Dx4kV8+eWX99xfenq6WvQSEhLUo0ajUUtZ0x/TEMfO1+nf1ENCjYeRpdWqxdgZXR2WU6xH1qEx4HnIejQWPBdZh8ZAYwTXOIU5tolOp9OV5MHj4uKwadMmXL9+HSYmJvDy8kKfPn3uam0oiFWrVuGDDz5QXaFkPIe0TDRt2jR7jEVGRoZKe7t06VI107epqSl+/PFHPP30vQccz5gxAzNnzrxr/YoVK2Bra4vKLDxRi2vn9qKv6WFENZgASxsHQxeJiIiIiAwoJSUFI0aMUFNJODo6ll2LxcKFC/Hxxx+rFgYfHx+17sCBA3j33Xfx6quvYty4cQXeV1hYmBqoLeMmJKjIz1dffaX2L60WMjHfrl271BgLCWakhSM/b7zxBl5++eVcLRZ+fn7o3bv3AyurtKLALVu2oFevXip1ryG9ve4sfsmyRFK9JzD3sSYoL4ypDssz1iPr0BjwPGQ9Gguei6xDY6Axgmscfe+egijRwOKTTz5BUFAQ7O3tc61///330aJFi0IFFpKu9vbt2+p9ellZWSp4+Oabb1TUJFmi1qxZowIZIYO7jx8/rlLh3iuwsLKyUkte8mUZ8qLU0MeXhqtt5yPV88dbB5TLC3RD12FFwXpkHRoDnoesR2PBc5F1WNnPQ4tCHLdEAwvp+iSDrfMGFrJOXiuMHj164NSpU7nWjRkzBnXr1sVrr72mggyJ4qT7U05mZmbQloNxAcbm8pVLqJt8CFkWddCmuquhi0NERERE5UyJBhbSUtClSxc0bNgwuytUeHi4moX7888/L9S+HBwc1H5ysrOzg5ubW/Z6Odb06dNhY2OjukLt3LlTjbf44osvSvBTVQ43jvyFd82XItyxKazMHzN0cYiIiIioMgcWDz30kJpp+9ChQ2pWbuleIwFG69atVUtCSZPB3TJmQtLRxsTEqOBCBns/++yzJX6sik537eCdJ/7tDF0UIiIiIiqHSjzdrAQQ7dqVzsWppJPNydPTE4sXLy6VY1Umaakp8Ew6q54HNO1m6OIQERERUTlUZhPkyWBsMk4Xj++FuU6DRDNnBNTM3f2MiIiIiMioAovBgweX1aGokKLP7VKPMa5NYZJnMDwRERERUZl3hRo2bFi+62WshYyBIONkdeuIerSp3t7QRSEiIiKicqpEA4utW7di2bJld6WblcBC5p8g4xMXGw2PtBD1vEYLjq8gIiIiIiMILLp27aqCCkkDm1ezZs1K8lBUQvaHZ2Bmxpvo4XIbH3j6sV6JiIiIyPCBxerVq+/52saNG0vyUFRC9lyKwi24wbL+/2Y4JyIiIiIq88Di5Zdfzne9zLRtbW2NmjVrYtCgQXB15WzOxmjvpSj12LFmFUMXhYiIiIgqc2Bx7NgxBAUFISsrC3Xq1FHjKYKDg9V8FnXr1sV3332HV155Bbt370aDBg1KptRUIq5fu4Lx8V/jiHk9tKneh7VKREREREVW7Nyi0hrRs2dPNdO2zFUhQcb169fRq1cvDB8+XD3v3LnzPVs2yHCuHvsX7UzPYojdKdhblfhciURERERUiRQ7sPj000/x/vvvw9HRMXudPJ8xYwY++eQT2Nra4p133uEEeUYoPeSAetR4tzJ0UYiIiIiosgcW8fHxuH379l3rIyMjkZCQoJ47OzsjIyOjuIeiEqTNyoJ73An1vGqDzqxbIiIiIjJ8V6ixY8dizZo1CA8PV12f5Pm4cePwyCOPqG0OHTqE2rVrF/dQVIIunzsGW20SMkysULtJO9YtERERERVLsTvWL1iwAC+99BKeeOIJZGZm3tmpuTlGjRqFOXPmqJ9lEPePP/5Y3ENRCbp+aidk1ooIh4aoZ2HJuiUiIiIiwwYWMiHeDz/8oIKIK1euqKxQNWrUyDX7dtOmTYt7GCphJuEH1aOpfxvWLREREREVW4mlApJAonHjxiW1OypFaRmZiEjUwAum8Gty9yzpREREREQGCSzi4uKwcOFCnDt3Tk2MV69ePTXGwsnJqSR2TyUsKCwOr2aMh689sLtWI9YvERERERl+8PaRI0dU1yfpChUTE4OoqCj1XNbJnBZkfPYE35ltu1UtH5iYFvsUICIiIiIqfouFDNweOHCgGmchg7aFDOIeP348pk6dil27drGajczR4DD12LFmFUMXhYiIiIgqiBJpsXjttdeygwohz1999VX1Wkn56KOPVDcrCVZyku5XEthItysHBwe0bdsW165dK7HjVjTxsTGYFTkF8y3moEOgnaGLQ0REREQVRLEDC5llO78L+bCwMHWhXxIOHz6M77///q7B4ZcvX0bHjh1VOtsdO3bgxIkTePvtt2FtbV0ix62ILh79F6bQwsVKC083F0MXh4iIiIgqiGJ3hXr88cfVQO3PPvsM7du3V60Ke/bswfTp0zF8+PBiFzApKQlPPvmk6mo1a9asXK+99dZb6N+/Pz755JPsddWrVy/2MSuyhOC9cAWQ7N7c0EUhIiIiogqk2C0WElA8+uijGDlyJAIDAxEQEIDRo0djyJAh+Pjjj4tdwMmTJ2PAgAHo2bNnrvVarRYbNmxQM3r36dMHVatWRZs2bbB27dpiH7Mic4y8M6DesXZHQxeFiIiIiCqQYrdYWFpa4ssvv1RjIKRrkkyQV7NmTdja2ha7cKtWrVKZpaQrVF63b99WrRmzZ89WLRkSxGzcuFEFOdu3b0eXLvnPz5Cenq4WvYSEBPWo0WjUUtb0xyyLY98MuwLXzNvQmpiieuP2Bvm85b0OKzLWI+vQGPA8ZD0aC56LrENjoDGCa5zCHNtEJ5GAEZIxGi1btsTmzZvRpEkTta5r165qFu+5c+fixo0b8PHxUd2tVqxYkf0+GchtZ2eHlStX5rvfGTNmYObMmXetl32URDBkzBKvHka76N8RahaAxKaTDF0cIiIiIjJyKSkpGDFiBOLj49XY6hJvsXj55ZcLvO0XX3xRlEPg6NGjqlWiRYsW2euysrJU+tpvvvkGycnJKvtU/fr1c71PJueTMR738sYbb+Qqv7RY+Pn5oXfv3g+srNKKArds2YJevXrBwsKiVI+1a/5G9ajza6PGplQUZVmHFRnrkXVoDHgesh6NBc9F1qEx0BjBNY6+d09BFCmwOHbsWIG2k4HcRdWjRw+cOnUq17oxY8aoDFCS3tbKygqtWrXChQsXcm1z8eJFNc7jXuR9suQlX5YhL0rL4vg702rigjYJzWt1rJAX4Ib+DisK1iPr0BjwPGQ9Gguei6zDyn4eWhTiuEUKLGQMQ2mTVLUNGzbMtU66OLm5uWWvl8xTkpWqc+fO6Natmxpj8ddff6nUs5RbmiYLy2PrIUtbF3sbdWL1EBEREZFxZYUypMGDB2P+/Pkq3WyjRo3w448/4o8//lBzW1BuFyMSkaXVwcXWAt5OnOeDiIiIiIwoK1R4eDjmzZuHffv24datW6rrk4eHh5rP4tlnn1VjF0pSfi0RY8eOVQvdX0jwOVQzuQk/7/rF6qJGRERERFSigYUMkO7Xr1/2wGdZJMGUDLiWuSS+/vpr/PPPP+jQoUNRD0ElyP78L/jRYiNCTYcCaM+6JSIiIiLjCCxeeukljB8/HnPmzLnn61OnTs13DgoqezaxF9WjnW8DVj8RERERGc8Yi9OnT6vuTvcyceJEtQ0ZnkaTAbf0a+q5d81mhi4OEREREVVARQ4svLy81NiKe9m/f7/ahgzv2uWzMNdlIs3EGj4BNQ1dHCIiIiKqgIrcFWratGmqxUImspNJO2TQtgwKlkHcMpGHZGiSGbLJ8CIuHYcHgBibQJiamRm6OERERERUARU5sJg0aZKaU0LGWCxYsEDNii3MzMzUbNlLly7FsGHDSrKsVESp18+oR41rbdYhERERERlfulmZnE4WmW48KipKratSpQpnPzYylrHB6tHGJ/eEg0RERERERjVBnkz1LeMpZNFP+x0WFsb5JYyAVqvDvJTuWJzVFx512xq6OERERERUQZXazNsxMTFYsmRJae2eCuhqdDL2ZdTA76Z94B/IgdtEREREZGRdodatW3ff169cuVLUXVMJOn0jQT3W9XSEuVmpxZFEREREVMkVObB45JFHVBYomW37XuR1Mqz4CzvR0TQU9Tw68qsgIiIiIuOcx+KPP/6AVqvNdwkKCirZklKRBFxdjZnmP6GrxTnWIBEREREZX2AhKWXvFzw8qDWDSp9Oq4VrymX1vGr1JqxyIiIiIjK+rlDTp09HcnLyPV+vWbMmtm/fXtTdUwm4ef0qbLQp0JqYwr92I9YpERERERlfYNGpU6f7vm5nZ4cuXboUdfdUAq4HH4crgEhLP9SysmGdEhEREVGpYZqgCiwx5Kh6THOuZeiiEBEREVEFx8CiArO5dUQ92lbnxHhEREREVLoYWFRQ0VERqJoeqp7XatnD0MUhIiIiogqOgUUFtSc8E8Mz/g+LHZ+Fm7uXoYtDRERERBVcuQksPvroI5XCdurUqfm+PnHiRPX63Llzy7xsxmh3cBRuwwV2DfoYuihEREREVAmUi8Di8OHD+P7779G4ceN8X1+7di0OHjwIb2/vMi+bMZL5Q3YHR6rnnWq6G7o4RERERFQJGH1gkZSUhCeffBI//PADXFxc7nr9+vXreP7557F8+XJYWFgYpIzGJjT4NKakfIvBFgfQMvDuOiMiIiIiMpp5LMrK5MmTMWDAAPTs2ROzZs3K9ZpWq8XTTz+tJutr0KBBgfaXnp6uFr2EhAT1qNFo1FLW9McsyWOHBG1FG9Nz8LE3hxm00Gi0qMhKow4rI9Yj69AY8DxkPRoLnousQ2OgMYJrnMIc26gDi1WrViEoKEh1hcrPxx9/DHNzc7z44ouFGqsxc+bMu9Zv3rwZtra2MJQtW7aU2L4sg3eqxxvmfvj7779RWZRkHVZmrEfWoTHgech6NBY8F1mHlf08TElJKf+BRVhYGKZMmaIu+K2tre96/ejRo/jyyy9V4CGDtgvqjTfewMsvv5yrxcLPzw+9e/eGo6MjDBEFysnSq1evEunKlZ6ehrCgt9XzFr2Go1rdpqjoSroOKyvWI+vQGPA8ZD0aC56LrENjoDGCaxx9755yHVhI4HD79m20aNEie11WVhZ27dqFb775RrVWyOv+/v65Xn/llVdUZqirV6/mu18rKyu15CVfliEvSkvq+OeDdsNWl4EkU0c0btAcJqZmqCwM/R1WFKxH1qEx4HnIejQWPBdZh5X9PLQoxHGNNrDo0aMHTp06lWvdmDFjULduXbz22mvw8vJCnz65U6nKzzLmQrarrKLO7oCEWtGuzSpVUEFEREREhmW0gYWDgwMaNmyYa52dnR3c3Nyy18vzvBGVp6cn6tSpg8rK6uad8Sg21dsbuihEREREVIkYfbpZKrjYxFTcSDVHJsxQo2UPVh0RERERlRmjbbHIz44dO+77+r3GVVQW24OjMU3zLBpWtcJ6T19DF4eIiIiIKhG2WFSg2bZ/2ncnsOrTJMDQxSEiIiKiSoaBRQVx8vRJxFy/BCtzUzzZloEFEREREZWtctUViu4tdsvnWGJxCEcDxsLVrh+rioiIiIjKFFssKoDrV4PhF3dIPW/dMXcKXiIiIiKissDAogK4sPl79Rju0ASBdZoYujhEREREVAkxsCjnkhLj4XV9s3ru1G60oYtDRERERJUUA4ty7viWFbDUpSPawhNN2rMbFBEREREZBgOLckyn1cL83Gr1PLXOYJiY8uskIiIiIsPglWg5durCRdikR0FjYoGmvZ42dHGIiIiIqBJjYFGO/XQyDcMy3sHGGv8HJxdXQxeHiIiIiCoxzmNRTiWkabDh1E2kwxJdunY1dHGIiIiIqJJji0U5tfnoRaRnZqFWVXs09XM2dHGIiIiIqJJji0U55bXrdfxkEY/IOm/AxMTE0MUhIiIiokqOgUU5FHblAjxTg6EzMUH9Fo0MXRwiIiIiInaFKo+Cd61Sj+EOjVHV09fQxSEiIiIiYmBR3mizsuB87c5M29aNBhm6OERERERECgdvlzOnj+yAU2Y00kxs0LQLAwsiIiIiMg4MLMqZyEN/qMdbVTvB2sbO0MUhIiIiIlIYWJQj4dGJsIw6rZ57th1i6OIQEREREZW/wOKjjz5SaVWnTp2qftZoNHjttdfQqFEj2NnZwdvbGyNHjsSNGzdQER0NjcEj8w5gRsZTCLeqjvrNOhq6SERERERE5SuwOHz4ML7//ns0btw4e11KSgqCgoLw9ttvq8fVq1fj4sWLGDhwICqav/cFYfj3BxGVlAFLz3qo9dyvMDEtF18dEREREVUSRj+PRVJSEp588kn88MMPmDVrVvZ6JycnbNmyJde2X3/9NVq3bo1r167B39/fAKUteduXvI/ql39BLe1z8KnfBnMebwo7K6P/2oiIiIiokjH6K9TJkydjwIAB6NmzZ67AIj/x8fGqu5Szs/M9t0lPT1eLXkJCQnbXKlnKmv6Y+R079NIZ+F9erp6/UCcB3R5vDFNTnUHKaczuV4fEeuS5WL7w95n1aCx4LrIOjYHGCK5xCnNsE51Op4ORWrVqFT744APVFcra2hpdu3ZF06ZNMXfu3Lu2TUtLQ8eOHVG3bl38/PPP99znjBkzMHPmzLvWr1ixAra2tjAmqRe3olXiFly0qIuMxmMMXRwiIiIiqmRSUlIwYsQIdQPf0dGxfLZYhIWFYcqUKdi8ebMKKh4UST3xxBPQarX47rvv7rvtG2+8gZdffjlXi4Wfnx969+79wMoqDVJ26dLVq1cvWFhY5Hot6OSX6tGhySC06de/zMtWXtyvDon1yHOxfOHvM+vRWPBcZB0aA40RXOPoe/cUhNEGFkePHsXt27fRokWL7HVZWVnYtWsXvvnmG9WdyczMTFX4sGHDEBISgm3btj0wOLCyslJLXvJlGfKiNO/xQy6cQBXNDWSZmKFR50G8YC5CHVLJnIvEOjQEnoesR2PBc5F1WNnPQ4tCHNdoA4sePXrg1KlTudaNGTNGdXWSNLM5g4rg4GBs374dbm5uqCiuHvgTMvz8umNT1HZ2NXRxiIiIiIjKZ2Dh4OCAhg0b5lon81VI8CDrMzMzMWTIEJVqdv369ao149atW2o7V1dXWFpaorySYS+2YTvUc+u6fQxdHCIiIiKi8htYPEh4eDjWrVunnsuA7pyk9UIGepdXFyOS8GLSGPQwP4nXOz5k6OIQEREREVWswGLHjjt38UVgYKC6s18RbTh5AxFwxe1aj8PRid2giIiIiMj4cfpmIyPB0vpTN9Xzhxp7Gbo4REREREQFwsDCyFw5fwLjY79Eb4vj6FGvqqGLQ0RERERU8bpCVQbXDq5FG9Nz8HK2h4M1U34SERERUfnAFgsjEn71ApxCN6vnNvX7Gro4REREREQFxhYLI3Hk39/hvH82nHTpSDJzRMMOzAZFREREROUHAwsDy9RokH7+b1RN3ql+vmFbFzWfmgN7BydDF42IiIiIqMAYWBhQXEoGPl34C8b+F1SEBjyGziNnwNxAU7YTERERERUVAwsDsrYwQ1BWDZhr+6Jvp7bo3ucJQxaHiIiIiKjIOHjbwIHFtyOawLtBN7Ts/pghi0JEREREVCwMLAzMz8UWnraGLgURERERUfEwsCAiIiIiomJjYEFERERERMXGwIKIiIiIiIqNgQURERERERUbAwsiIiIiIio2BhZERERERFRsDCyIiIiIiKjYGFgQEREREVGxmaOS0+l06jEhIcEgx9doNEhJSVHHt7CwMEgZyjvWIevRWPBcZB0aC56LrENjwPOwYtSh/hpZf818P5U+sEhMTFQV4efnV+pfDBERERFReb1mdnJyuu82JrqChB8VmFarxY0bN+Dg4AATExODRIES1ISFhcHR0bHMj18RsA5Zj8aC5yLr0FjwXGQdGgOehxWjDiVUkKDC29sbpqb3H0VR6VsspIJ8fX1haHKyMLBgHRoDnousQ2PA85D1aCx4LrIOjYGjga8TH9RSocfB20REREREVGwMLIiIiIiIqNgYWBiYlZUV3n33XfVIrEOei+Ubf59Zh8aC5yLr0BjwPKx8dVjpB28TEREREVHxscWCiIiIiIiKjYEFEREREREVGwMLIiIiIiIqNgYWZUQmFpk6dSoCAgJgY2OD9u3b4/Dhw7kmH5kxY4aafERe79q1K86cOYPKbNeuXXj44YdVncjkhWvXrs31ekHqLD09HS+88AKqVKkCOzs7DBw4EOHh4agsHlSHq1evRp8+fVT9yOvHjx+/ax+sw3vXoUajwWuvvYZGjRqp80u2GTlypJp0k3VYuHNRfpfr1q2r6tHFxQU9e/bEwYMHWY+FqMOcJk6cqLaZO3cu67AQdTh69Gi1PufStm1b1mEhz8Nz586pv7cy94FMQCx1eO3aNf5dKUQ95j0P9cunn35q1H+fGViUkfHjx2PLli1YtmwZTp06hd69e6s/nNevX1evf/LJJ/jiiy/wzTffqIDD09MTvXr1UgFJZZWcnIwmTZqoOslPQepMgrk1a9Zg1apV2LNnD5KSkvDQQw8hKysLlcGD6lBe79ChA2bPnn3PfbAO712HKSkpCAoKwttvv60eJVC7ePGi+s+ddVi4c7F27drqNfn/UX5XAwMD1f+TkZGRPBcLWId6coEiQZlcsPD3uXDnoejbty9u3ryZvfz999/8fS5EHV6+fBkdO3ZUNwp27NiBEydOqP8jra2t+btciHrMeQ7KsmjRIhVYPPbYY8b991lHpS4lJUVnZmamW79+fa71TZo00b311ls6rVar8/T01M2ePTv7tbS0NJ2Tk5Nu/vz5/IakaQLQrVmzJrsuClJncXFxOgsLC92qVauyt7l+/brO1NRUt3HjRl1lr8OcQkJC1OvHjh3LtZ51WPA61Dt06JDaLjQ0lHVYhHNRLz4+Xm23detW1mMh6jA8PFzn4+OjO336tC4gIEA3Z84c/j4X4jwcNWqUbtCgQfc8L/l/4oPr8PHHH9c99dRTrMMS/j9Rzsvu3bsb/bnIFosykJmZqaLHnNG6kO47EmGGhITg1q1b6u6cnuQr7tKlC/bt21cWRSx3ClJnR48eVV1Vcm4jd/AaNmzIei0g1mHhxcfHq7tKzs7OrMMiysjIwPfff6+6UcgdPZ6LBaPVavH0009j+vTpaNCgwV2v8/e5YOQue9WqVVUr2oQJE3D79m3WYSHOwQ0bNqi6k262Uo9t2rTJ1c2H52HhRUREqHodN26c0dcjA4syIP0L27Vrh/fff1/1vZYg4+eff1ZN1dK8JRfIwsPDI9f75Gf9a5RbQepMHi0tLVV/bdZr0bAOCyctLQ2vv/46RowYAUdHR9ZhIa1fvx729vbqJsycOXNU91HpO8xzsWA+/vhjmJub48UXX8z3df4+P1i/fv2wfPlybNu2DZ9//rnqZtu9e3fVl511+GAShEl3HOleK13KNm/ejMGDB+PRRx/Fzp07WYdFtGTJEnUtKfVo7L/P5gY7ciUjYyvGjh0LHx8fmJmZoXnz5uriQ/pl68ldzpykdSzvOsqtKHXGei0+1uHd5M7RE088oe7Yfffdd6zDIujWrZtKIBAVFYUffvgBw4YNUzdg5K4nz8X7k7uXX375pfqbUti/G/x9/p/HH388+7nc+W3ZsqVKuiJ3i3Ne1LEO8yf//4lBgwbhpZdeUs+bNm2q7qDPnz9f9SpgHRaejK948skn7+r5Yoy/z2yxKCM1atRQ0bpE8mFhYTh06JC6EKlWrZoadCzyRpgS+ee9I093FKTOZBvpUhEbG8t6LSLWYcHI77JcBEsXPbnLrm+tYB0WjmQ1qVmzpsogs3DhQnX3XR5Zjw+2e/du9f+fv7+/qjdZQkND8corr6iB8KzDovHy8lKBRXBwMOuwAKSFUc69+vXr51pfr1697KxQ/LtS+N/tCxcuqCRAORlrPTKwMMAfTvmPSk6ETZs2qaheH1zIBYmenCwSiEhaWrpbQeqsRYsWsLCwyLWNdD07ffo067WAWIcFDyrkwmPr1q1wc3NjHZYQufOm74LCc/H+ZGzFyZMnVYuPfpH+1jLeQv7WsA6LJjo6Wt0MlL/brMMHk645rVq1UhfCOUm2PAnQWIeFJzdX5P8//XgzPWP9P5FdocqI/McufyTr1KmDS5cuqf/s5fmYMWNUk5WkDPvwww9Rq1YttchzW1tb1V2qspLWHakrPbkbLH8sXV1d1V25B9WZDPyUgU5yx04u9uR906ZNU3MOSKrfyuBBdRgTE6PuIunnXdD/MZCgTRbW4f3rUC7chgwZorqfyPgAGT+lb0WT1+WPLOvwweei/H5+8MEHKk2vXMDJxZx0J5N87EOHDlXbsx4f/PucN6iViw75PZa/NazDB5+Hssh8KpLOU87Dq1ev4s0331R34WWcAOuwYH9X5PpGupR17txZdW/cuHEj/vrrLzUonnVY8HoUCQkJ+O2339R4n7yM9v9Eg+WjqmR++eUXXfXq1XWWlpYqTerkyZNVqrCc6VPfffdd9ZqVlZWuc+fOulOnTukqs+3bt6sUbHkXSQdY0DpLTU3VPf/88zpXV1edjY2N7qGHHtJdu3ZNV1k8qA4XL16c7+tSr3qsw3vXoT5Nb36L1D3rsGDnopxjgwcP1nl7e6v/I728vHQDBw5UqXtz4rl4/9/nvPKmm2Ud3v88lNTwvXv31rm7u6s0nv7+/mp93r8ZPA8ffB4uXLhQV7NmTZ21tbVKrb927VrWYSH/PosFCxaoa5ec14vGfi6ayD+GC2uIiIiIiKgi4BgLIiIiIiIqNgYWRERERERUbAwsiIiIiIiIgQURERERERkeWyyIiIiIiKjYGFgQEREREVGxMbAgIiIiIqJiY2BBRERERETFxsCCiIgqhYyMDNSsWRN79+5VP1+9ehUmJiY4fvx4qR731KlT8PX1RXJycqkeh4jI0BhYEBGVQ6NHj1YXxXmXS5cuGbpoRuv7779HQEAAOnToUOD3BAYGYu7cuXetnzFjBpo2bVqgfTRq1AitW7fGnDlzClVeIqLyhoEFEVE51bdvX9y8eTPXUq1atXzv1BPw9ddfY/z48QapijFjxmDevHnIysriV0FEFRYDCyKicsrKygqenp65FjMzM3Tt2hXPP/88Xn75ZVSpUgW9evVS2589exb9+/eHvb09PDw88PTTTyMqKip7f9JVZ+TIkep1Ly8vfP7552pfU6dOzd5GWkXWrl2bqxzOzs746aefsn++fv06Hn/8cbi4uMDNzQ2DBg1S3Y5ytrY88sgj+Oyzz9RxZJvJkydDo9Fkb5Oeno5XX30Vfn5+6nPWqlULCxcuhE6nU92Z5L05nT59Gqamprh8+XK+dRUUFKRacwYMGHDP+tRqtZgwYQJq166N0NDQAn4L/6uXvIu0duj16dMH0dHR2LlzZ6H2S0RUnjCwICKqgJYsWQJzc3M1nmDBggWqNaNLly6q+86RI0ewceNGREREYNiwYdnvmT59OrZv3441a9Zg8+bN2LFjB44ePVqo46akpKBbt24qONm1axf27NmjnkvrSs6WEzmOBAHyKGWVwCRncCIBzqpVq/DVV1/h3LlzmD9/vtqPXLCPHTsWixcvznXcRYsWoVOnTqhRo0a+5ZKySMDg6OiY7+tSNqkLqRsps3SZKoycrUYSwEjw07lz5+zXLS0t0aRJE+zevbtQ+yUiKld0RERU7owaNUpnZmams7Ozy16GDBmiXuvSpYuuadOmubZ/++23db179861LiwsTCd/Bi5cuKBLTEzUWVpa6latWpX9enR0tM7GxkY3ZcqU7HWy/Zo1a3Ltx8nJSbd48WL1fOHChbo6derotFpt9uvp6elqP5s2bcoue0BAgC4zMzN7m6FDh+oef/xx9VzKI8fZsmVLvp/9xo0b6rMfPHhQ/ZyRkaFzd3fX/fTTT/esL/kM3bt3z7UuJCREHWf37t26nj176jp06KCLi4vLtY2UU+olZz3LYmFhoWvSpMldx5HPPXjwYF2LFi10KSkpuV6T9aNHj75nGYmIyjtzQwc2RERUNNIyIP329ezs7LKft2zZMte20vIgrQNy1z8vaTlITU1Vd+3btWuXvd7V1RV16tQpVJnkOHLH3sHBIdf6tLS0XN2UGjRooLpt6UmXKMmeJCRLk7wmLSz5kW2lS5O0Usig6PXr16v9Dx069J7lks9nbW2d72vDhw9XWZv+/fdf2Nra3vW6tORI962cpCVFWkHyevPNN7F//34cPnwYNjY2uV6Tn6VFh4ioomJgQURUTkkgIV1u7vVa3vEDDz/8MD7++ON8L9SDg4MLdEzpinSn4eJ/co6NkOO0aNECy5cvv+u97u7u2c8tLCzu2q+8V+S9IM+PDMKWMSKSaUm6RcmYjvyCAj0Za6IPXPKScSc///wzDhw4gO7du+f73rz1LEFXXrIPKY90IZNAJa+YmJh7dtUiIqoIOMaCiKgSaN68Oc6cOaMGFMtFcs5FH6DIxb5cXOvFxsbi4sWLdwUHMo5ATwKSnHfh5TiyrmrVqncdx8nJqcDpWSXIuN9AZwkGpNzSYvPPP/+ocRf306xZM5w/f/6uoEg899xzmD17NgYOHFjkwdXSSiHBjoxnadu2bb7byABzKQcRUUXFwIKIqBKQrEtyx1y6/Rw6dAhXrlxRA7TlglxSoEoXqXHjxqluP9IlSC6CpfuPZFrKSe7of/PNNyrLkgx0fvbZZ3O1Pjz55JPqDr9kgpKByiEhIepifcqUKQgPDy9QWSX4GTVqlCqbZKCSfUgrwK+//pq9jXSVkvK98cYbKmjJ2YXrXt3GJOuVBFf5eeGFFzBr1iw89NBDavB2Ydy6dQuDBw/GE088obI/yc+yREZGZm8jWbEkW1bPnj0LtW8iovKEgQURUSXg7e2tMkRJECEXvw0bNlQX+9KKoA8ePv30U5XJSO7cywVwx44dVbemnCQFraSAle1GjBiBadOm5eqCJM9l7IG/vz8effRR1KtXTwUIMsbhXhmZ8iMtEUOGDMGkSZNQt25dlQY278zVEgjJuJAHtVYISWkr5cmvi5aepNWdOXOmag3Zt29fgcsqLSGSYUuyW0m3Mv3SqlWr7G1WrlyJ3r17FzrbFBFReWIiI7gNXQgiIjJOMo+FpKjNb/ZpQ5NASconLSEyL8eDyBgLCZjyG1xemmRODpmHQ4KLwsz6TURU3rDFgoiIyhW5UJfg4O2331ZzTxQkqNCP3fjkk09yTdZXFmSyvbfeeotBBRFVeMwKRURE5Yrc+ZduUNKSsmzZskK9V8ZulDWZmE8WIqKKjl2hiIiIiIio2NgVioiIiIiIio2BBRERERERFRsDCyIiIiIiKjYGFkREREREVGwMLIiIiIiIqNgYWBARERERUbExsCAiIiIiomJjYEFERERERMXGwIKIiIiIiFBc/w/JUqBh5n/YUQAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    10 * np.log10(ref_ts[\"g_theta_phi_m\"] ** 2),\n",
+    "    f_m / 1000,\n",
+    "    10 * np.log10(g_theta_phi_m ** 2),\n",
+    "    title=\"Beam-compensated gain\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"$10\\log_{10}(g^2(\\theta,\\phi,f))$\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9129eb3a",
+   "metadata": {},
+   "source": [
+    "### Compute the calibrated TS spectrum, TS(f)\n",
+    "\n",
+    "Using the received power spectrum, target range, beam-compensated gain, and acoustic calibration parameters, we compute the final calibrated target strength spectrum TS(f), following the formulation described by Andersen et al. (2024)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "90f1d082",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "scalar absorption: 0.03770373022901242\n",
+      "CRIMAC alpha_m min/max: 0.02804324195086584 0.04521493514355129\n",
+      "echopype absorption_f min/max: 0.02804324168412123 0.04521493476510025\n",
+      "max abs alpha diff: 3.7845103439959615e-10\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.utils import uwa\n",
+    "\n",
+    "absorption_f = uwa.calc_absorption(\n",
+    "    frequency=f_m,\n",
+    "    temperature=float(scalar_param(cal_obj.env_params[\"temperature\"], tsf_channel, tsf_ping_index)),\n",
+    "    salinity=float(scalar_param(cal_obj.env_params[\"salinity\"], tsf_channel, tsf_ping_index)),\n",
+    "    pressure=float(scalar_param(cal_obj.env_params[\"pressure\"], tsf_channel, tsf_ping_index)),\n",
+    "    pH=float(scalar_param(cal_obj.env_params[\"pH\"], tsf_channel, tsf_ping_index)),\n",
+    "    sound_speed=sound_speed,\n",
+    "    formula_source=\"FG\",\n",
+    ")\n",
+    "\n",
+    "print(\"scalar absorption:\", absorption)\n",
+    "print(\"CRIMAC alpha_m min/max:\", ref_ts[\"alpha_m\"].min(), ref_ts[\"alpha_m\"].max())\n",
+    "print(\"echopype absorption_f min/max:\", absorption_f.min(), absorption_f.max())\n",
+    "print(\"max abs alpha diff:\", np.max(np.abs(absorption_f - ref_ts[\"alpha_m\"])))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "0a14d495",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype TS_m: (1000,)\n",
+      "CRIMAC TS_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from echopype.calibrate.ek80_complex import _compute_ts_spectrum_calibrated\n",
+    "TS_m = _compute_ts_spectrum_calibrated(\n",
+    "    power_spectrum=P_rx_e_t_m,\n",
+    "    target_range=r_t,\n",
+    "    frequency=f_m,\n",
+    "    sound_speed=sound_speed,\n",
+    "    absorption_f=absorption_f,\n",
+    "    transmit_power=transmit_power,\n",
+    "    gain_f=g_theta_phi_m,\n",
+    ")\n",
+    "\n",
+    "print(\"echopype TS_m:\", TS_m.shape)\n",
+    "print(\"CRIMAC TS_m  :\", ref_ts[\"TS_m\"].shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "7ca23f61",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "(1000,)\n",
+      "[0.02804324 0.02806629 0.02808933 0.02811234 0.02813534 0.02815831\n",
+      " 0.02818127 0.02820421 0.02822714 0.02825004]\n",
+      "0.02804324195086584 0.04521493514355129\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ref_ts[\"alpha_m\"].shape)\n",
+    "print(ref_ts[\"alpha_m\"][:10])\n",
+    "print(ref_ts[\"alpha_m\"].min(), ref_ts[\"alpha_m\"].max())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "2903e237",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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59YJrndZQaTmup6DczBRozq9Hq6zt0MCCeJU/Tvn3g1vdDtBomMq3unI9/AMa5ByEu1bBzlZvwarWFTsTt+XYH+iQvQWnlVBMNE2Dh1bB2IZWtPAt/LNjsgLv7NMgMVcFf4MVTzfPRmbqZTS7sAihuCy32aVpC02ru6DTqGE25UJz4g+0yt4JBSoc1TZDjt4PWSYL3sq+A0arCq7IwWL9dBhglK/PgisOe/aANrI7dAZOfEm1S0ryZQSeXYIm1tPy+YOmaTinhCDKkI6PlPfhgWzEww87g8cgsm4kqgvrxb1oHbsIRmixpt4LCPfzKPR3IzvXiB0XMtAqfR16Knugh60CnAkX3Gl6Dc39NBhU14oQgxkZcUfR4vJyeFqutLjuVRrhRdODyIUWL2gXor/6SjdNu0dMTyJBVwe31clCe/fLsHrWhcaUicjjX8MtJw4HlPr41jwUz2kXoY4qodBrzynBmGJ6Allwgb9BwWPNLfCvgUMxs7Ky5Pjk1NRUeHl51bzAoqSKfUE7d+7Eli1b8PPPP2PDhg3QaDQlBhbnzp3DypUrC71eDNyeP38+xowZU6oWi/DwcCQkJFy3QCsrUly9ejUGDBjglFdzq7oMh3y2HeeSsjD9lmYY2zm8wt9LfKW2nUnC5m1bceepF64sV6lwPqg/vJr1RYuWbaH1DgPUtr7n1V1Fn4OX0nKwc+nnaHF+ATSKGEIPmFQ66BTbj8I2tz7o/8gs+LmXHIgpVisyM9Ph6uYhv//VmbN9h+Pe6wCj0Qh/L3e4T91W8oaKgsv7/8K5Ewfwb53RuKVdOLxdi///741OwTMLt+OenIXorjkCvWKEGrbuA9/q7kaTJm1x5/Ar5adYLdj63bMIj10lU0IL55Ug3G96DgEeetzcNAi93c/BLesi3I78DH9TrNzGqNLjokcLHKj3MNwDw+HnpoNf8gF4q7NRr0VneAbUgbNxtvOvKojAeM6ms9DumYObMv+GBRqcMzRGy7FvI7LOlR4QgsmYgz1//4zMjDTk6nyhdveDX0RzNIqok9/65ihn/t2HtCVPwtdypcKbq/PGth5zMLx9PfjqFSTuWoykDV/BkJuU/z3K8qoHs9oVMW2nokNUANqFe5drXpobPQd/+/j/0CFtDQ7VHYOh9794zd/do7FpSDm0EhcPbUSDrH2YlDsVyfCCClZ8rfsA9VW2vwFCrFdrmOr1R5cu3aELbixfv2P7JgSueRJa65X6n1ajglu9LvC88ytoisledyH6NG6bfwapORaM1qzDI5o/5HKDVg0FCtz0Wiy33oR30gbiHs0aWAOb4fnJk8pclo7+Dot6cEBAQKkCi2rZFWrKlCnFVvgLioqKwptvvolt27bJ1oeCOnbsiHvuuQfz5s1DSEgItm/fXmh9cnKy/JCCg4sfZCv2d/U+BfFhOvKPsqPf3xnkpifAL3k/0hGMW9rWrbTy7NUkBL2a3I7zZ1vj+IZFCD31X7gouYi8tBq4tBqx64F3reOwztoeEf5u6O+fiK7+WWjebQiC/G3NrdXRtc5B8UO842wSkrcvgi5uD/xzziHXvS6sIa3QpttguNdtgQPRSVi6Pw4Ld5xHB6sab2otuODWDD59HkOzNt2wdcknCD++AEfTXfDiu+tQP9Adz1jnwgsZtj7AFjN0lky4WNLhbs2ASrFiIl5CSHhD3NkxHLe1q96VQqf4DpuNUCy2APB87w/Q+jr/n7BOI+St23V227l+IBbc2wxxCy7CxZQjl5l0nshp+wBeH/wQVqxYcVX56dD70U8Qe/owTm1fBlNmCix+DbG0U3c0DfGEi04Em23kltZbH8LOfxbDuuNbBBmjEZW+F2/sPoWzSpZc/4hmGUZr1iNlA3DEtRHSwnqgRZsuiGzdKz9TlTj/opOy4aI2I8i36i8wVQSnOP+qyKy//8V36//FZO1luKtt50mrnN3InTcSGeO+gm/9jnKZKTsd+2c/iNDUwn37rdvVOIxAHG4yBa0790GPhgFVPmHkzuVz4LPjA/jmXbxJdImAV9f70KjbrWju6pm/XUjP8QjsPAqH5j4Oj4tbEKGKB9JtY6HeWN0L78NbHv+kBkno0qKRnLdG0ugq9Rw8fikdzyYMRR1VF/x629Drvq5NZAAQeQ8w7B5k5pjw8uE4/LbvIvSnVsqgIhXuSAm5CWFDn0ePqKK/FT169gParcbpf/ch5cAKtGzaBPouE20XAEv47OrVb4LtLzaUCWA2n+wET4xEoC4XKoMXoFIDfvUxFmp4LvgQraP/AZL+wX8/Oo5bHv+gxIss1fE7XJb3rJaBhYiKxO16PvnkExlc2F28eFGOnxCtGCL1rNCtWze89dZbiI2NRWioLT2Z6BYlAocOHTpU4v+CqqPLh9Zipm42jmibw8+9aDe4ihYR1QARUS/CZHoWh3auRcq2BQhIOwo3awb2mqJghFUO9O6buBrhmrVI2fE2dtQZiSaDHkajqIhSv4/oi755zwF8sidXVoDevaM1GgReaTKuLInJyTi1ZSm+vtwCe6NTkZhpxIe6FWiqsjW3IycGSNyO+MPfIh2uWGNpj+8tI+UqU0R3pHfsil6deub/4Pa+5wWcOz4U2/57CsgATl/OxEGNAXdoCl8csDNCh7NGb5w+lYgtpxJlBXNE355o1KR5kW3Tckw4dCEV0clZCEzag7Zd+sLPx7syi8cpWTMuw2xVYIYmv3JVkd+X0Of+wok96+Du7oEGLbvLH/Rr9e8Nrd9C3q5FrdWiy8C7oPQfhbNHd+Piv9sxRNsGJ1KAXLMV6uzWuJh8FmGmcwjNPoHQUydgPjUXO5f6Id21Dj52n4qziVkyG9YHui/g7+kK7053o3XPW+W+ybl8veEUZq8/JYPX+sHeUDefhkytL3LXzoCPJQUXFkxG9LBZiGzRFdN/WI97U0/JlrBE/45wt6TCkJsIj9xLCLdcwtzDJzDjoJusmL9+awvUr4K/y8J/d0ZjxeZYPKvVIFPrD5f+/0GHzv2hKeF81Rjc0ebhb3Bq4yLk5OQgNSkeRrOCvlluWHpehb0no+F5/i3ErMuW2RRFRTpL5QaNzoDUun3QoOdd8IxoXWifpy5nICnTKOe3CXTXysxucWk5OJOYIr93QZ4GmMxmZMefRlhoHXh6uMHH0xM6tehIrMZLvx2S+2nZvDlCg65fJyzI3UWHkR3C5S0ptRlOnBsFr4A6aB92nb/5HkGo33EgIG6lZLuIAfRpEgRA3AoTJX77hGmI/mQNjKlx6JaxGl8s+g0v3H8nnFGN/osYEVG44uXhYfvCNmjQAHXr1pWPBw4ciObNm2PcuHGYMWMGkpKSMG3aNDng2xHdmsixsi6dgrhOk+NZ8V2grhftt7tpIHDTQJjMFpxLSMdPshuUCtFJWcjacwbGkzuhN2egWcyvUL5bjE0B3RDe/xFENu9c4n7FH+W9f/8M3a6voM41YafpP/IP8ohPN+HDwX4Y2K1TiVda7LKzc3Ax+jTO714BS9oluCQdg96SAYPKgh/CXkTX1s3Rt3HhVpSYM8dwcsl0hKTuhz8s2GF8HWlwl83+SaGDEeeZAwQ0Rtb5vTDHHkbD3CPwRDa6ak/geNNgjOsahe4N/Yu9ghfZuA3++2Qz+aN0JiETltQAXMzuAa1OB61GC4ObJ9y8/eHlGwwPb1/8mmjGwu3ncXTPRgy9OBs5C7/C6taT0bz7MCREn8DlIxtxMf4ypicPlJlQhG91HyFpy3+wx78X2g+bCL8GvMhQWqmJF0UPJyTAG519Kn6sgk7vguZdB6MyqNQa2d1J3LoXWiMuRD2GSxfP49jmpVCid8Av5SD8rElQMs3Yn5xqe70KiFLFwTsjE1j7IvZv+hgZPZ7HTb0GF9tNgmqebccvQrfqBfRSt4W28QCMGP9hfnA7P8aCBse/QrglBqbfH0X/X5/HZfjiuG4SXh7aFD262jIESumXcHzbckRcDIH+hAqbTibgtU+/xjN39EKrNhUbkBeUm52Bab8dxx8HRLefdmgSFoaH7hAp90uRBl2tQYPeVxIhCH1Ei97lDCxZsxmxx+pCbzkHg8UIWMTopgxYjRnwPLYYP/17Dn+GPormoV7QJxzBTbHz4WuOhwEmpECDC4oL3OGGk3tn4RXzBEQrtuO5X/Mn7tX8LR+L4dBpUEEFRZZrnGki3PRheHl40QtFZeHn7YUurcu3j3LTucLvgZ9xYvZYeGbH4M4zr+DtF//BHY/PQJOQK61HzqBGBxalIfpeL1++HJMnT5aDvAtOkEe1i9pqRPj535Ainvg4bnCaTqtBw5Ar2WkaBnkATaeIToA4vHYRVJs/hsGYjNCELTAu2oY3w56Fb5Me8HXTQ3d+I4IvroElJx363ET4mhPgnzc4Va12x7Qu7th42RXqsxtQ76952H6gNzo99GmxV1X3nE/G+RWz0Dj2DxiUXFzdPiIGv/16LBe/HNuPQA89Hnbdgd3rzcg+tBzhSVtRN69ne5I2CI91CUfbZo3RPtIXOk3BKz23yRaUxPhYxF++hDYRkfjKq3B60uKIsRV+7n7oFCW2FUGgrQWyOO3dgfYRvjgQcg7Z6wPgbYxD/f0zkbN/JsSlBnGrCy201t4I8/NGA383WC/5Q5UTh3oJ65C6YD3O+raG0a+JHOC7X98GZ5VQWXkOdFejm3EbOvcaCq+gqg1Gq6vkhHg5YDpDIz5r56pMB4dFIHj0E/JxakoyYo/vhinLhK8C2yHS3w2Rfu5Ijm2CI3/PQ2D0n/AyxcNr7VPYvfVjmPq/iW4dO8p0u+KcP3XsAJJjTqJZlwHw8OBFrBrBYkbWH8+hl/oAYnXheOD2VoUuzAS4G9By0lzs/uFFzElqIyu/4rx4d+xdaFnnqivhnsFoPOABvCEGSidk4puFizA+4VtolnyL7acno8ttj8GadBapcSeRdno3TjS4Hzc3CypXd6mcc7sQ89MTSEi7DUALDG8diufGDJXnZHmI1u9nxgxCjqk/9pxLgjo7EUmZZhhMSciIPQXTyXX4b/pNOHk+BXvPp+Am9VncqxUtPrbiE39LvVSZCEMixJG09FPgZfCSrRmNjYlQW23biF8UEVQIgUjGbN1H+LfvV6jr6xxJc9x9g9H2sR9w+fNBSMs24i7NOkz7bD7G33EbbmkTVub5tKqrajl4u7oRg1a8vb1LNWilMogrJaJ/sciAxf6xN16GB+c/h8ALf8JoUXCky/u4ZdgIVFd7NixD/OYFaJS9Hy+b78cWa0u5/Db1Jjyu/a3QtjlqV1xqMBrtRzwGH29veVV+/YI3EH5qkRz8mq33RWqzsQhsNQANGzTG3vNJ+H5bNP7YfxH3albjfs1f8o/9RY/mMPs1hktYc7j510GCyYBNyX5YeTgOsSmZWKV/Nv+PvnDOqz0aDJ2KyKadqs2MyTmZqdi94EV4Xt4Ld1MictTuSPBtDX1UV0R0H406AXlBjaLgxN71OLryG7TI3l1oH2+bx2KN1daC0Ve9Fy9pf4BR7YrY3u+hb58BN/TD70zfYXE+PLpgJzqHGbDoidJ3FyiP6lh+iUmJOPzf6agbuzp/DoAvXR7ExcCeiE1IwefZz8qMVBlqL6S3uR9dhz8Irc4xWeGqY/lVR6sXvIv6J76Xj717TUJA/yeLLUORdezN5UdR19cVk3rVh7YUAXZ2ymVs/voJ1MvYK58bDX5wNyfDZFFwQQnEeNPz6NkoAPd0icDA5iFlDgYuH1yNxN+eh86ciRhRLR/2LUZ0blwl4zrE+X8+KUterDoVn4kwdRI6aE+jTt0oeLi6IFelR1ZiDHbs2oOON/WCf702gCHvKr1I26rWIjXhoowszp0/BUXnjuTEBPiG1UObloW7VzmD7Oh9uPjzU5iX3BI/WW6W8/jc29YXkwa2RbifW7X8DpelHuz0LRZEdmnJl+BtsVUAPOp3qtYF077XcKDnMJzY/Q86nNUgwOSNzFwzwl164iyC4enlC6+AUPiHRqJeaH200F75QyOuevQb/wrWLWuAiJ1vwtWYDNf9nwP7P8cJaPG1+Q6stNq6V5la3gVj/SFo2rEf6hczEK8fgOeGNMFPG48gemMEApREJPi2R3j/R9Gv+Y1NLFiZXNy90f2Rz2TgYMrJgNbgJru/FKFSoVH7PnJw7r7NK5B8Zh9MafHw0JjRK7QdugU2k5t5njgGS7QBeks2Itc+gT1nBqPDhA+qTSBV1UQF4vGFe2GFGj6+1TfJQFXw9/NHr0c+QUxMNC7++hxSkuLxW1oTWNIS5fqt+pboqDkFD0sqPPZ+jF1HfkP9+79FUFjpx05R1dl/Nh6+JxbLx8keDdGg96Mlbutu0OKdka3KtH9Xn0D0evIHrF80C/VOzIU+N0kmRo1T/LDVKrrpKNh4IgH7T5yDh8e3SIsagt53PAp3V5cSk2Xk5OYg5/wexG/9Ce7n/oHOquCMOhI5I2bj1vb1UFVE8BLp7y5vV1xJ1yBS4aiDmiLnTC68GnQRfYOvbJYXYHiHNpD3rcNs987MNbwtGkz7B32PxWP+3J2og8sYf+QZGI9YcaDDI2g+/IlSBavVFQMLqjXUubITFN4xj8UnDWrApHWi8tvxZjxdpDvu0FK9vM/we5DWvjM2/70EdaKXw914GVrFjF7aI/BqNRLjb4oq2nxfDINWg3t6NMWKtMnoUVOueKpU0BXIelISvVaNzr2HA+JWnJ5P4XLSBJyaP0UO+PY5+xdWv3cB7e95E/4RTeUmlxMScXLr/+Rs7h5pJ2DRukPf4V607TcKmgIBnzM4EZ8Bo8WWArZlHXbvEerUCUedqQtxLi4BTx5JRpCXC8K8XdE+YiC0sGLbH9/A99BcBOaeR/rsgdjr0RExN72BpqGe6BzlV6MrEE7VBWrpkwhCOpLVPoiYtAjQVfxkA3qdBgPGPYtj/w5F9LG9MAe3Qrc2LdDVoMXw2DQs2HIW7Q69gVDjeYQe/wr7312Ck6FDYfSuL69Ye6afxO/og6RcFWJTsvArnoEeZllxF/NFbzT0wuCHXkdIcEiFHztVvL5NgnDqrSE49vV9UMfa/q66756N7XsWI+Ku9xHe/Hq59KonBhZUa5xSwpCiWHBHv24yt3Rt4BXWCEPue060OyAzMxPpl8/jrpAI3ONy1WykVKJAPz8E/t9C/PbTV2h99EPUzz6Ey9+OwgPu05Gs8sOlpBT8V/8pgpBte4G4DLlpOrbtXYQOj/8IF7eqyQJTFeJSc/C4Zgm8VFm4v8Vrjj6caiUyJABTQopmruk1agpiOg9FzLwH4G+KQ3jGAUxadlj2JnfRqTHNYxV8PVzg6u4lr2KrjenQWI1QXHxxLGgQNibaujdeSs/B3S098dDA9lWettTZ7fj9SwQl2bpEBncfjyDvyv3ONmnaUt4KEhd53hvdBgm9P8ORjUvgf/h7BJsvI/jiPOCibZszSgh2mGyt7S7IhV5vRjI8EacJg6rN3Rg9ZJRsTaGaQ6NRo/nYd5F8dB1y/n4HWUYLQpTLSF30CLb0/Q539ql533eegVRrfG29FbEmFeZF2CZPrG3c3d3h7m7r4kNld/vdk3B+dyRO/vU5snJysT9ZXNHMgkqlxxqv29DW3wqfRl2QeHgtImOWIyTzGA7NGgb0exktO9qyxWSkpyAr5TLSEuNgtVrgWbcFwsNCa8wPR3x6Lrqpj6CeIQ1aq22uCbq+OhH1EfTcSpw8uA2nj+xG71w/HLiYgYysbPTIXA1dprjeXNSZ6GhsMo+Xj7upD6P75h+wJno4etz9nOz2Jz+T6BP462gSDqS6oHGwB5qFeqFblI/MokbXdzElGx/szMX9mjrwdDXgpr4POLTYAoJC0OuOybAOuw8nN/4M1cnVUDIuw0PJgDqkP95u3BIerjpE+bkg2O0f1PcNLr67J9Uc3nXh2/Ve5La/ExkLp0J9ei1ckYt//56LbRFR6NagZnU7ZWBBtUZK3mSaYd4V38RNtUNEh8Go03YgzsfGYX6WTs6uKrJ6+XsMu7JRj6E4sPMW6JZNkVefnv3jIsxr16M54tF0Tz9oFRPsQ3hF48ZhGJDs2RgeLYegWf/x+TnRC5KDg8VNpXJoEHIpNQutVGm27CXuRfO1U8l0egOadegtb6LjnWiFiL6UgKzdjyIp8QJM2Wmw6j1gMfjBqnMD0i4iymLEtAYN4OPhCpeNy2BIN6Le+SU4OXM10hveKgeBRmUdwhlLf/xqGSLfJwCpmOv6ITK8GsKn5yQ0bV8gBSoV8cuuC9hmbSZvax7vCWiLTo7rCGoXDzQe8CAgbnkKz/dNzsag16PR+C+wZsNazFu5DRutrbBv5b94+/ZWiE/Nkj8BNQEDC6oV0rNykSMHbqsQWgm596l2NV3XqxuGaw2NbN2pF2JCfsenK44g7owCZBixG77Q6m0TvaVo/KCoNPCzXIarkgvX9IP4fGN9HP53Mx7sUQ/dIwwwXj6FI3u3AAkn4Jp8DHURj2y1K056d4eu33MY3CJEjhEpyGi24vjBHVCSTuOcdyc0jwxFlL97udNN2jU4NR9aWKBV6wD3sk1YRYWJ4CwqNBAY/tg1i6av/UGXL7D1n/9BtelDBFouwfXYD3KxGWo09tPg8VYNcSgmFY3Pr4GbJR1uyXuB3x/BwT/ckKQLg86ixsFDH+Ix05Mwad2QY7LiPizDYO0u5Oj9YWxyC7oMe6BmjKGqIMlJifjw72Pyd+Gju9qiQRDHDZGDqVS4uXc/RDXvjJtnrUdG9CEc/eJtfGMehrph4ShwCavaYmBBtUL6iY1YpX8OB9WN4WGoCV9NqunqhEfh84cjkWm0YPOJeGzatgumrj+hcbM2UOcN2M3NTEHsmaPYsHkTlke3QO6ldDy7+AC+1H2IxqoLsA0Pv8LDmoGMxBi8+tNedK3vh7dubyVzzKdn5eDY4jfgdeZPuJqz5LY/m8djo7U1QrxcMLhlCJ4fWB8uLoWD6hyTBa/9fhjLD8SivVcqnu7hj9Zdbi75/5S8U95b9Z5AMVnEqBKpVOh2823I6j4YGxd/Cd3pVTAENkCDYf+Hu8Mb5m+WndMW+3YMQsaBZah3eQ3clSy4G0/aVloAV1M8YnNs177Vmmy4K8lwNyUDez7Env0/Ir7ZeHQdeCcMLi44m5ApJ6m8nJ4rkz5EtekFvZtzVL6tVgVrP5uEBbpYfK0Zg8EtK2dSRqIbIf6uPxd5AgNjZ8vns3Sz8fDFp3Dqciaahl2ZB6s6YmBBtUJmymUYYIWhmIniiCqL6LbkYdCiX5NA5JxS0KBJy/ygQjC4+yCqZTd5G5iag5mrjmHPuWRkpxqQqzLgkntTqP3rIbx+c7hEdEBmehJy/o2H62ENtp1OwosffonJnhvhYbwMX0ty/n5Naj3aeWVgcyoQl5aD+G2LcHLfKpjajUe74Y+KSXOxd9dmvPLnORzJFj9SCiKTNsF9+Sqs3HcrBk16r9j/j6vRlkr1cNeZ6M3TxiHcXFww6B4xv8KVORYKcnXRo1uvQUCvQTBmZ+LS+eNIiD6KE/8eRWjzbvi8YQcoWle46jVQctsjLeYEkk5uR/DxnxBgiUfAoRlIOvQh/rB0xWeW2+U+xXwcffUvIHqlFmlBnWCO6g2TwQeWtDikJMbjuCUEpz06ItDTgJ71PNGveRhUmur9t3b/6Ri0NB+BRmXFnb3bF9sFkciR7r9rFExz5iIj1wwXxYx7wk1oEFj9E69U728+UQXJTY2XKfnEpERE1VGItwtmjm4jHyuWHuJyMpoXM56iUVugV2waXvztIIbFbked7ONyuUVtQGZoFzQc/Cg8I9vJ1o6Hc81YsecMola+BVdzKlx3foKNx9bLmdvDjacxE3o8p5qI+24fjsDVXwG5QMOY/+HC+UdQN+Kqzl6mHOgtmXJciFdg3aopFCoXvas7wpu0Q0j9ljifuQJdew64qquTO1AnFOjcC7nZj+Lon1/BcPRX6HOTUV8diwBXA+oHuCNYk4q4mGCEWC/BK24rIG55RNvHWvOtWG6tI5/HbNuFIPe/ob75ZbToWjUTKN6IY7vWoBOsMHuE4pa+3R19OERFuPjVhcuYb+CZlQiz1h1hh65cPKrOGFjURpkJOHrqNAKPzMPnGX0Q1rgDWtX1RuMgD/h52AaumSxWmHOycGjLcrS8aRhc3Wt2ykxLRoLt3sXX0YdCdF3Xu9orMv8smdwdsYcVnIs+B51nIFq07gQXz8Lnt2gtubNbI0RHLsaBJTPQNH4FwtL2569P0/jg9ftGol3DOkhvPBcJH/aAVQGObfkddSOmFtqXolLhNdN4eFlTMc2/ZmUpoeszuHqg7cinAeuTuHzuCAZ6+WKkvy1YEIymAVi3bRtSD6yAd9JB+GuzkaELgMHTF33qD0Qrt/qy21TCrj1wy70M9Z9PIM74HEJ63V/9ij83A21P2bqYWOp2dfTREJUs3DaZrWIyAYdWoCZgYFHLXNz5P7ivfRn6DCNSAdyLNXj41FPoqPsKP2s7wj24AWJ92uHLvUa8rf0GXdT/4uLGV5FmCIHH0NfRqF3NzDDiknpa3qvcWSEi5xHaooe8XY9IaRs+5QMc/3cCLmz8ATpYEdS4M1q3uxluXrbvhKdPAA62eBjBh74GLuwoso+UXBX+MdtmG37Pi5nVnJZajcB6hedYsE/uNrBnd0DcriGmsx8Ozj+CRpl7kbnmfexMTEenWx+TLXDVheXcVhiMybBABbcuExx9OEROhVN+1iIXkjJw+Y/XkJBhLLTcH2nwQiYGmteje8x3GHX4cfgiDX9au+Rv45UbB/VvD+PPpT/AnDfzbo1xfjuCMo7Ih1qPGjDjNlElady0NfpNfB89J85Ek9535gcVdsFNbd9577TjSM8u/HdCTNAm+LqJNLvVp5JI1Uud0DB0mjwXuw1dZIpk/71fYMvc55CeLi5lVQ9btm+TLXNr1Z0RUa+xow+HyKkwsKgFlPRLiN6wAM8u2IB11iuTwy1yuRNxXf6DO++4C5kuwYVe873+fZlDebXbUMTqI/KX19vzLt5cskOmNawpsmIOIT3HNgGVOcTWh52Iiops0g5QqeGLdKz68Er+fEGkPeyl3o/W7jXnu0+O4e/pgpHTZuNg8K0QSb6Dzy3DyVkD8fTPu/HTjvP4a3804uMvOeTYxJwwMacOyseBUa0qLBUzEdmwK5QTi01OR8r5wziz+BWEIQFe5lvwoXUU0ro+gSf6N8aLHleyC6T6zkDitoWwXD4JXcop6Pu9hM2tb0YdHzGVE3Di2BF4/HYvjmV64Pvdifh+9yb0bRKIt4dGIdRLB7gW7tst0hMeO7wXXkn7YQpqjfbtu0Cldkwcuxg343VjADSw4OtgTjFEVBKtwQ0JAZ2wOC4QS9J7Y6jRIrMHidScfy+dh1e167FLLSZiG81CpGvSGlwx+OG38du8ALS/8CO+NQ7E8r1xWLw3Di1UZ/GJ7lMkqfTYEvkIho16AMFV1L3uckYuPs0Zisbq1vhy+Ch+ikQVjIGFk0nNMuHBz5dhatpMhKkS5Qy/TfLW9VIfQFL4ILx0a9sis/d6N+gsbzBlAxnxgG9kofWNmjSHMnkZVv9vBYLOGxCfngv9iRXI+nwRojUqaOr3gGtkB+ja3onFh9Lw8ZoTGJjzFyZqlsvX71xZF56DXkSzjvnTPVWZS2m5MEELq0qDLlHMCkV0LZ0nf4tX3loCc5YKJ+LT0bquDy6mZsNflSbXB4cyIxSVjkjhevdDz8Boegp9919E3fgMbD2diE7piUA2oFOM6H32E2yevQe3P/U5VFUw6/XJSxmIQSB0vpFwCYiq9Pcjqm0YWDiZhTvO40iiFZd0fgiDLee8sNG1L3TtxuDz7h2KBBWF6FyLBBV2Kq8w3DfuIYxTFPy+Lxr6pZ+K9PcwiqT4JzYi+8RG4O+PsNo8AUnWVliEvuikO412ylH4516A6o/J2BP7ONoPf1RO9lRVUvL6ivevo7DZm+g6VBodAsIicexkIv6NzQssUnJkYCGm4OjTrgXLkMpEDPwe1TE8/7livQlnTo9GzNLXZJayNhmbcHT1d2g+5NFKL9mTlzPkfcOgmp3pkKi6YmDhRI5cTMN7f/0LFfRIUjwBr1Ac8+2DDs0aYEK3sTLbR0UQgcmt7SKQ1OBXHDl1Fhd+fxOdLPvy13dWH0W0Rxv8+GhvhHoPQ2pyArbPfwmNk9fDe+cn2H5+N+rfPQOBflXTetDxwjyEay8iiVN6EZXKAPfT6K1dBs2R40CnJxGTkoUApEIvBm0zAQKVk+gWW79hM9R/4juc+HwU1MlnkLxlATY3vAPdGwVVavm22vUi3tVmIMGrcDplIqoYDCycRGJGLjZ+8Qhe1ZqxzGU4xj+/AAaNGg0qsWXAz8sDPdq1REqT+YhOysaaP39FnaRtuKVpPTxyc1foPdxs2/kHYuATX+LPBTPQ+PQ8BFzajM+/+Aj3P/ocIv0rfxbJBum70Uodi1VqWz5oIrq25q5J8FfvwelLtr8fSZdj0VqVAK1aC7gzsxpVEL07DGMXIO3zmxGiSsK3K1eie6NxlVe8VguC0w7AS23CHh+2WBBVBgYWTmLdwbPorT4AHcyo03NKlaaD9HHTy1uriSKLTOFMMnYajRrDJzyHtf+0ht/G17AjMxjfz1iHx/s1xNR+DaGtxOPVm9PlvUpnC3SI6Nr8I1sCewCvrLMyi06LY5/L5VqRQYeBBVWgiOAAnGp/J37ZeR4bYhR5kcw/b6LWCpcRD6vFAjM08AviWCGiysB0s87AaoX/ljdkUKHzi8DAXj1RXfXtNwSh/7cOqmDbBEyf/3Mcf00fgu0zbsPa3+ch+fLFin1DqwUu1iz5UKVnYEFUGnUatIJoqwiwJuKH3//ECXMIcqFHbN1BtnFYRBWowW0vYlPIvYhR/LH6SCWmoc24BLPVigTFG3X82WJBVBkYWDiBoxt+QXjqLvnY0GxQlQ6MvhFB3q5YNrUX3r+jNYa6HEAz1XkEpP+LiF3v4PLng3Hq+OGKezNjBqxW24R+Wj0rRESl4eLljxw329w2UXvfx/spfTHU+A6Uvi+zAKlSDG4RIoZ145Mla7Hh+OVKeY/M5DiI+V0T4YU6Pvw9IKoMDCxquKRMIzb9vVQ+1mlUCOpeif1TK5AYAH5np3B88J9nYb39a5wMGy67WWisRhz573RYzLYJ7crLmJkqZ1gVV1tddez5R1RajR/4FqLnU5g1Dt7Gi9Br1WgS4skCpEoxolUI5urexwL9O1i5ZXelvMeyLQfkfZbWF54uukp5D6LajoFFDSb6Pv+x7RD6qffK5+d7fwiVR+Vm1Khoer0Ojdr1wqBHZsLn/v/KzFXNjQdwYMVXFbL/jPQUeZ8FA1wZVxCVmjaoES56tZWPb1bvRcswL+hEvlmiShAR6InG9Wypzm8/+zoUc26Fv0fC5Rh5Xy+S81cQVRb+StQAyw7EYsPJBESfO5W/zJR0Dos++D98vfoADin1oA1tiR49b0ZN5h3ZCscbTZSPtYd+luMjyis7I1Xe56hc5dVXIiq9+iOeQ3zEUPi2vw3TR9jGRRFVlqDu98m/077WJEQf3Fzh+8/MtSIdbqgXVfxcTURUfryGWwNaJb7ZdBYjk1fDNP8DrPTvhZhcV7TK2IjOSMckbQymmqZg//iBgKbmN+22HTwef/+7GZsyWqLrptO4v1ejcu0v0acV7jC+hwgvNZ6AbawFEZVOaKN28taNBUZVQNdkAI55dkWjtG24fHgNItr1q7B955ot+CJ3ML7AYOzr1L/C9ktEhbHFogaYNqAhwgw50MKCholr0TtjBfxgS6HaXX0I/+kVAG+3mh9UCKH+fkju8w5WWjvhi43nYBEDJMohPccME7RQu7BvOBFRtRfRRd75Hl+MS0c3V+h4REGjVsHLVV9h+yWiwhhY1IBBzj0bBcLUagLMwz/BhZD+OOnVGX+hK9bVexIRE3/Cw0Ntf4idxSO9G8DLRYvL6bnYcSapXPtKzzHJew7UIyKq/hp1vUUm2xCXlE5sWlxh+025fBHBSEKwqxjKx36xRJXFabpC5ebmokuXLti/fz/27t2Ltm1tgw7tlfOrffnll3jkkUdQY6hUqN+uL5p0HiifDoLzEtlnRjUCXI4sRe4/64EG79/wvtzOr8V/tMuQaRWzbter0OMkIqKK1SCiLv7o9CqSt/+Ec2l10KOC9uu2by4W6n/FSt1wAEMraK9E5LSBxbPPPouwsDAZWBRn7ty5GDx4cP5zb2/vKjw6KqueES6IOLYRudF6HI1+Bs3CA2+oEF2S/sXN6j04qIQysCAiqgE69RqGrptdoEoAnsgyVUhXX3OmrfVbcfGtgCMkIqfuCvXnn39i1apVmDlzZonb+Pj4ICQkJP/m6srJcaqz9u27yUmMDDBiyf9uvDlcyc2wPdBzllUiopogxNsFDQLdoSjA1tMJFbJPJTtZ3qvcGFgQVaYaH1hcunQJEydOxIIFC+Dm5lbidlOmTEFAQAA6deqE2bNn58/GTNWTt7se3s1t6XPvvvwRsuLPlH0nFjMaxq+WD1UGDt4mIqopejTwRxgScHrJdKSmJJZ7f+ocW2Ch8/CrgKMjIqfsCiVSsU6YMEGOlejYsSPOnj1b7HZvvPEGbr75ZtlKsWbNGjz99NNISEjASy+9VOJ4DXGzS0tLk/cmk0neqpr9PR3x3o5Uv+fdiD22FCaLgtPb/ocmQx4r0+tVZzbAIi55AbAavGQUXdvKsKLU1nOworD8WH48/8pmRFA87tO/A5iBvX/NQ/c7Hi9XEWpyU8WuoHX3vaG/Y/wOlw/Lr2aXX1neV6WI2nk189prr2H69OnX3Gbnzp3YsmULfv75Z2zYsAEajUYGFvXq1SsyePtqs2bNwuuvv47U1NQyvf/ChQuv2SpCFS/u303on/kHzhiaILPlA2V6bXDiNgSe/U0+/jr0TdwU5hwpeYmIagPjkd/RPnszjumawtT6/hvfkWJF+/3/gdGiYEHIS2hXhy3YRGWRlZWFsWPHynqzl5dXzQssRGuCuF1LVFQUxowZgz/++KNQ1ieLxSKDjHvuuQfz5s0r9rWbN29Gjx49EBcXh+Dg4FK1WISHh8tjul6BVlakuHr1agwYMAA6Xe2qHG/bsQVhKychGwYcHLIYozqWfsbUQ8u/gNeeL/G3tT1Cbn8HuLCvVpZhRajN52BFYPmx/Hj+ld3Zo3ug/nU8clUGRDyzGQaD4caKMScV8R/1Qo7JiiO3/onBreuWeRf8DpcPy69ml5+oB4vhBKUJLKplVyhx8OJ2PZ988gnefPPN/OcXL17EoEGDZCuGSD1bEtGi4eLiIgd0F0f88SruD5j4MB1ZqXL0+ztCp47d8J/lt+KgUh9BB+Nxd7eGpX7tWa8O+NM8BpcUX/zUIgSrL9TOMqxILD+WH8+/mqumfX8btuyIw795wNWSgaMHdqLTTX1vbEcWPf7Q9EdWTiZu8vUqVxnUtDKsblh+NbP8yvKe1TKwKK2IiIhCzz08bJl/GjRogLp1bVckRIuGaJno1q2bHGOxdu1avPjii3j44Ydv/OoHVRkXgx6TnngJgz7agJgLaTBbrNBqSpdz4LI2FKusnTCyXR3oSvkaIiKqHlRqDZJ9W8M1YQv8/noU56P+QURYWNl35OKFL4zDkGYx4xZ3zrpNVJmcvrYloqwvvvhCBhatW7fGxx9/LMdXiHEWVDM0CvKAp4sWBmMyTpw9X+rXZeZa5L2rXlOJR0dERJUloM2Q/Mcnti6/oX38dSgOaTli6Dbgx8CCqFLV6BaL4sZdXD1kREyKV3BiPKp51GoVXvFahvbW1UjZPR5o8EKpXueRchTd1McQrOJAPSKimqhZr1H442IiPjmgQpOc9rAlIS+bBesOIhhJSIcbfNzYYkFUmZwqsCDnZQiIAlJEmqiDpX5Nq7il6KfdiuPZYjLEbpV6fEREVAlUKvh3GoUT+7cjK7r4TI7X0zxrJ17Xz0dKcBdo1HdU+CESUS3qCkXOwSuitbwPSNqLnJMbS/cic468U+uZIpiIqKZqUcdb3sekZCMtp+x5/NWmDHlfJziowo+NiApjYEE1QtO2PXAQDWC2Kji00TY3xfVoLFnyXmtgYEFEVFN5u+rwoPsWvKRdgHOnjpb59RpTprzXuVZ9unii2oaBBdUIIT6uMDcZIR9bkko3gFuT12LBwIKIqGYbaDiIvup9+Gv16jK9Toy71JltLRY6N1vLBxFV88BCTNwRHR2NY8eOISkpqSJ2SVREnchG8t4tO65UpaOx2iY51Lpw8DYRUU1m9o6S9yOTvsG/p8+U+nVZRgsaqGLkY4M7AwuiahtYZGRk4KuvvkKfPn3g7e0tMzI1b94cgYGBiIyMxMSJE7Fz586KPVqq1QIjbIGFhzkBiin7uttrLbYWC72re6UfGxERVZ6mPW7Pf5x4el+pX5dzdgdaqM6KMeDQM7Agqp6BxYcffigDiW+++Qb9+vXDkiVLsG/fPtlisXXrVrz66qswm81y6nGR6vXEiRMVf+RU69QNCcVL5gcwIfcZJNtihmvSK7bgw+DKMRZERDWZf4u+iPPrJB9nJV4o9esyjRYkwgtqFaAKbFKJR0hEN5xudsuWLXIG61atWhW7vnPnznjggQcwe/ZszJkzB+vXr0ejRrarzUQ3ykWvxWmP9riUlovolFz4eYo0siX7CnfCbM7AJE9mAiEiqukUrzAgCTCnXCz1ay57tcRdxpfRwEeDv4OaVerxEdENBha//PJLqbYzGAyYPHkyy5kqTKi3qwwsYlNz0Ca85O1Ss034NautfPykuwc/ASKiGk7vEybvVRmXSv2a9BwTFKihc+VYO6Jq2RUqOzsbMTG2gVAFHT58uKKOiahEnVxjMFazBsqZDdcspY/+Pp7/2MPAeSCJiGo6Vb3eeM08Hj8qA0v9mszMDOhhgqdBU6nHRkQ3EFj8+uuvaNy4MYYOHYrWrVtj+/bt+evGjRtXll0R3ZB2yjE8qFkB74ubrrnd5aQ0dFYdRR+PaPh7GFjaREQ1nG+dBthobY39Gb6lfk3U4S/wp/55DDetrNRjI6IbCCzefPNN7NmzB/v378d3330nx1EsXLgwP1c0UWXT+YTKe//Ug4DVWuJ2BmMi3tF9iw/d5vJDISJyAoEeLvI+LceMHJOlVK9RjLbJ8VQ6JvEgqgrass5XIdLJCh07dsSGDRswcuRInDx5EiqRy42okmlDmwP7AX1mLDKP/AX3lkOL3c5qss1hoWj0/EyIiJyAl4sGA7T74WlNRUJKV9QN9L/ua1SmLNu94drJPojIAS0WQUFBOHDgQP5zf39/rF69GkePHi20nKiytG7dATuU5rAqwMH9u0rczmrOm+dCa7vCRURENZtKrcbTul/wmPZ/SL1UypSzeXMeqfRM4kFU7QKLBQsWyOCiIL1ej59++kmmlCWqbGK8hGekLduTObPkWd4Vk9H2gC0WREROI1vrI+/Tk0uXGUpttrVYaAycKJWo2nWFqlu3bonrunfvXhHHQ3RdBs8Aea/KLjmwgNk2g56KLRZERE4jV+8L5MbiYmzR7JTF0eS1XmtdGFgQVYUKycOZk5Mju0LFx8fDetWA2hEjRlTEWxDl03kHyZlUUyzXyPZkzmux0LErFBGRs1BcfYF0IPXAn0i95V54u+quub3GYmux0LmwKxRRjQgs/vrrL9x3331ISEgosk4M6LZYSpe5gai0LJE9cec6V7TSeWNYCduoLLYWC7WWg7eJiJxFo0ZNkBq/Gb3UB3AxJhreDetfc/vD+jZIy4iHj1vpU9QSURVOkHe1KVOmYPTo0YiNjZWtFQVvDCqoMtjnpUjKzGuVKMa/ljr43HwrcprewQ+BiMhJBPR+BHqtreqSlXTxutvPd70PL5kfhNar8PhQIqqmgYXo/vTUU08hODi4Yo6I6Dr83W2tEAkZuSXOn3LK5I8l1l6wNryZ5UlE5CxcvHDS0AJnlRCk55iuu3mm0dZrwk1fIT2/iaiyA4tRo0Zh3bp15d0NUan5e+gxS/cFvla9jcyUoplBzBYrzCIfrfgN0mpYskRETmRR2HN40PQMovXX7gYlJlHNzbXNaeRu4G8BUVUodwj/2Wefya5QGzduRKtWraDTFR5I9cQTT5T3LYgKEVeeGqpj4aFkIT0lER6+IYXW55qtCEEiAlSpcMm5BLiHswSJiJyEr5ut1TrlGt1hpYw4zM16HOl6PTT6jVVzcES1XLkDi4ULF2LlypVwdXWVLRcFZ+AWjxlYUGXIUbvBw5KF7IzUoutMFgzV7MA9mr9hOJgF9HmOHwIRkZPwdrNdwEzJvnZXKGNOlmy9NkMDL3aFIqoZgcVLL72E119/Hc8//zzU6nL3rCIqFaPaHbAkIKe4wMJshR4miBhXzXSzREROpVP6GnTV/RfJF3oDeKPE7b5ddwSDxG8C9HBjVyiimhFYGI1G3HXXXQwqqEqZtW6ACTBmFt9iYcgLLKC5xlwXRERU43ipjfBXxSM769qzbyel2H4fchVdfvcpIqpc5W5iGD9+PH7++eeKORqiUjLrbJMdGbOKBhbGnGyM0GyBGipAy8CCiMiZ6N195L3WmHbN7RSTbT6jhnWCoFFf6aZNRNW4xULMVfH+++/LcRatW7cuMnj7gw8+KO9bEBU97/ICC3N20R8WdexeeS9bLDxDWXpERE5E72ELLJoZDwAJJ4CARsVvmBdYqHS8wERUYwKLgwcPol27dvLxoUOHCq0rOJCbqCKZDb5IgDeyzEUb3cy5WfLEludfowEseCIiZxLSRt5ZxTxG57eWHFiYbYEFdK5VeHBEtVu5A4u1a9fCkaKionDu3LlCy5577jm8++67+c/Pnz+Pxx57DP/884/MXjV27FjMnDkTej37XNZU+8PvxTdnu2OiTz30v2pdLnRIVAKQqKuPcDVzlxMRORNX3xD8bu2GEaqtoj9sidvFWz2w1docPfybV+nxEdVmTjEVpchKNXHixPznHh62bjL2rlrDhg1DYGAgNm3ahMTERDkuRMzY/OmnnzroiKm8vFxsXe7Sc8xF1iX4dcDDphfQztsHt7OoiYiciqeLFhmKC8Q8qNbcjBIHi+6xNsEf5ggsbd29io+QqPZyisDC09MTISGFJ0mzW7VqFY4cOYLo6GiEhYXJZbNmzcKECRPw1ltvwcvLq4qPlirqhwVQcPPJd4CU9wGfK5PgGS1Wea/TMP0xEZGz8TBosdnaEnGKH96JuhlXLiUWzRAouOrYck1UVZyi5vXee+/B398fbdu2lcGCSIFrt3XrVrRs2TI/qBAGDRqE3Nxc7N6920FHTOXl667HberNqJ+5F6f2rS+0zpQXWOgZWBAROR0XnQYn1fXxh/UmpHk3LXG7bJOtRdtF5xRVHaIaoca3WEydOhXt27eHr68vduzYgRdeeAFnzpzBt99+K9fHxcUhODi40GvEtmJ8hVhXHBF0iJtdWpot85DJZJK3qmZ/T0e8d3XVvb4vktSn5OPYhEREFCgb//Or8K1uPuIzOsNkai+XsQzLh+XH8nMknn8sv6u5GzQwZlmRnJGNQPeiVRnR3fkB6xIM12+F94FHYOoxieegA/E7XLPLryzvq1LEt6+aee211zB9+vRrbrNz50507NixyPLFixdj1KhRSEhIkK0YDz/8sBzcLdLhFiQCi/nz52PMmDGlfv+FCxfCzc3thv5PVPHMh35B29xd2O09CIaG/fKXG0+vR/vkFdir7wBdqztZ9ERETmbWnlz4Gy/izgYK3ALrF1lvtgJpu39EL/UBJNUdgIvBV6f5IKLSysrKkomPUlNTrzuEoNJaLMSYhldffRXfffddmV87ZcqUYiv8V2eDKk7Xrl3l/cmTJ2VgIcZebN++vdA2ycnJMvq6uiXDTrR6PPXUU4VaLMLDwzFw4ECHjMkQx7p69WoMGDCgyDwhtdk/MeuBOCDI3wfdhw7NX77jl8NAMuDm6YsBectZhuXD8mP5ORLPP5bf1dafnIvHUmfDy9IYPkOnFFmfcfE4kvYekI9bt+mAtu2v/EbwHKx6/A7X7PKz99wpjUoLLJKSkjBv3rwbCiwCAgLk7Ubs3WubHC001DYxWrdu3eS4i9jY2PxlYkC3wWBAhw4dit2HWCduVxMfpiMr9o5+/+pGpbe1HqksuYXKRaXYBuypNEXLi2VYPiw/lp8j8fxj+dmpDbYh2ypTdvG/i6nnbetFD4XgRlBV0G8nz0GWnyPpHFQPLMt73nBg8fvvv19z/enTp1HZxMDsbdu2oW/fvvD29pbdo5588kmMGDECERERchvRytC8eXOMGzcOM2bMkAHPtGnTZHpaZoSq2dT2SY9M2YVXWPL6AmoYhBEROSOtiy2wSEpOQnGXIY25tsnxLqiCUT+K6WaJqsoNBxa33XabnNn4WkM0KnvmbdGq8PPPP8vxEGKwdWRkpAwYnn322fxtNBoNli9fjsmTJ6N79+6FJsijmk2lLz6wsJrtgUWNz01ARETFqBcWBJy3tVikZObCx71wLwOz0RZYxKsDWX5EVeiGa16iW9Hnn38uA4zi7Nu3r8SuRhVFZIMSLRbXI1ovli1bVqnHQlUvzacF5loGI8i1JXoXXGG1BxZFu7MREVHN93D/Vji9TeTMtyI9M7NIYJGtdsdxJRzxmuLnuCKiynHDyZ1F0LBnz54S11+vNYOovHL9m+EHywDs17YptDwbLkiEFyw6dxYyEZETUuncoFHbekXkZmcUWX85qDsmm/4Pi11HOeDoiGqvG26xeOaZZ5CZmVni+oYNG2Lt2rU3unui63LV22ZTzTLaBmvbbQocg3knu+HxkIYYznIkInI+KhVMKj3UyEVOVkbJs27n/U4QUTUPLHr27HnN9e7u7ujdu1AHFaIK5aE2o4EqBr7Z6SLRcP5yo8XWUqbjzNtERE5rscsduJiai3uUvPF2BeSabYGFQcvAgqgqcXQr1Vj+2afxte4DpKSL+UiuzHtisljlPQMLIiLntc3jZuxLTsEtKDpxbejxH/GTbjEO5QwAcJNDjo+oNmJgQTWW3sU2hkJntWX/sOtzaR566w5DnT4RQAMHHR0REVUmt/zusOYi69S5KQhSJcNdbeSHQFSFGFhQjaV3tQcWhX84/HIvIFh1DuetRfvdEhGRc4hSxSFLdQ7mjLoA6hRap5htvwuKmvMZEVUlBhZUYxlc3SF+OvRKLiAykOXNm6K22q5eqbR6Bx8hERFVltvTfsCDukM4cdkHQOHsgDDn2u75O0BUM9LNEjmaS16LhUqxQrHPti2f2wILNX9QiIiclqJ1kfdWY+FJUgsGFirOZ0RU8wKLjRs34t5770W3bt0QExMjly1YsACbNm2qiN0TFcvFYJsQSeSAys29Ms5ClddiwcCCiMh5KVpbNihLcYGFJa+LLC8wEdWswGLx4sUYNGgQXF1dsXfvXuTm2q4SpKen4+23366IYyQqlk5vu1olGE1Xxllo8mbe1mjZt5aIyGnpbIGFco3AQqUtPCM3EVXzwOLNN9/E7Nmz8c0330Cnu1KRu+mmm645MzdReel1Oiy03Iz5loEwKldylasVW2Ch1XGMBRGRs1Lp8rpCmbKKrEvT+uOcEgyL3ssBR0ZUe5V78PaxY8fQq1evIsu9vLyQkpJS3t0TlUitVmE+hsFkUTBJdaX1Igsu0MAF6rwfHSIicj5qXd78Faa8gdoFrAqZiPlnzuFxv4ZVf2BEtVi5WyxCQ0Nx8uTJIsvF+Ir69euXd/dE16TPm13bPime8IrL8xhhfAsm/6YsPSIiJ6W2d4c1F+0KZTRbC/1GEFHVKPc3btKkSZg6dSq2b98OlUqFixcv4scff8S0adMwefLkijlKohLU1SQjShULU86VpnDRgiFw5m0iIueVHtQB31iGYY+2bYmBhUHHwIKoRnWFevbZZ5Gamoq+ffsiJydHdosyGAwysJgyZUrFHCVRCd7Gp/DRJcGa2BKoE1io9YJXqoiInFduQCssshjRTiPmsShszIU3MFyXgOSc6QAaOOT4iGqjCpkg76233sKLL76II0eOwGq1onnz5vDw8KiIXRNdk0VlO4UteTnLD19MxdTMT6DVWeFqagnAmyVIROSEXHQaqGGFYswCxEzbBVLL+hlj4a9KQqbGNnEqEVWNcrURmkwm2VJx/PhxuLm5oWPHjujcuTODCqoyVpUtE5k5L93sr7svoK36FNqpTiDAjT8oRETOyqBV43XtXHya+gRwbHmhdfnZAfVMN0tUYwILkV720KFDcmwFkSNY1LbAwmLMze9Xq4EVni5a+HjkZQwhIiKnbLEwQicnSZUtFgXY5zPS6hhYEFWlco9quu+++zBnzpyKORqiMrLaA4u8FguLxSqbxnWi+VvFQXtERM4eWFhFZGEpnHJWrZjlPeczIqphYyyMRiO+/fZbrF69WnaFcnd3L7T+gw8+KO9bEJVIuWqMhcVqkfcqqAB1hQwhIiKiatoVKhdaKIoC5P0GSFYLVIotiYdOz4lSiapSuWteoitU+/bt5WMx1qIgdpGiqmqxsOa1WCgW21UqEVdAfWU2biIicsIWCyWvK5TF1vVJsppty9hiQVTzAou1a9dWzJEQ3YCjbh2xLdUX7VzqyufWvBYLScXAgojIWbno1DBBA9FgYTHlIP8vvmJFHAJgVkwwsMWCqEqxrwjVaPu8+2HlhRZ4072hbYHVIvvcyqCCLRZERE7LoLWNsRDMptwrgYXOFY9rX0VcVg6WGZjEg6gqcXQr1Wh6rabQLKuZcMEQ47tY1nMpoLH94BARkXOOsTijhGKDtTWMPnkXl/ImSY1Ly5GP9VpWc4iqElssqEbzRDaCkAzkpsrnFpkeBNCqmQKZiMiZqdUqbFW3w3pzGwxs0A+eecu/WHsqfxt3A6s5RFWJ3ziq0fol/xcP6v9CdMw9ANrCnBdYaBhYEBHVilYL0WKdY7oyvi4jIRrf6GbBrPNAHZ9hDj0+otqGbYRUo6m0eakE8zKCuJpS8Lb2W7Q78q5jD4yIiKokMxSgIDf3ygR5alMW6qsuop1HEj8BopoWWCQmJuY/jo6OxiuvvIJnnnkGGzduLO+uia5PYwssFIvtR0VryUEX9VEEJO5m6RERObm+6j1Yo5+G4HVP5y9T8mbdVjiXEVHNCSwOHjyIqKgoBAUFoWnTpti3bx86deqEDz/8EF9//TX69u2LpUuXorKJYxDzZRS8Pf/884W2uXq9uM2ePbvSj42qgH2Adl5gkZ9ulqlmiYicnsp+cclUYII8+5wWefMcEVENCCyeffZZtGrVCuvXr0efPn0wfPhwDB06FKmpqUhOTsakSZPw7rtV0x3l9ddfR2xsbP7tpZdeKrLN3LlzC20zfvz4Kjk2qpofFXtgobLmTZDHK1VERLWmO6y91dr2mC0WRDVu8PbOnTvxzz//oHXr1mjbtq1spZg8eTLUalus8vjjj6Nr166oCp6enggJCbnmNj4+Ptfdhmruj0po5r+FWyzyzkMiInJeKo1B3sclpSHQvtBiv8DEFguiGhNYJCUl5VfUPTw84O7uDj8/v/z1vr6+SE9PR1V477338MYbbyA8PByjR4+WYzz0V822OWXKFDz00EOoV68eHnzwQTz88MP5QdDVcnNz5c0uLS1N3ptMJnmravb3dMR7V3ci64egS7+A+H+3XblSpdIUKi+WYfmw/Fh+jsTzj+VXoryLSynpmXIAt0hBa7V3jVVpK+x3k+cgy8+RTA6uB5blfcuVblaMVbjW86owdepUtG/fXgYyO3bswAsvvIAzZ87g22+/zd9GBB0333wzXF1dsWbNGjz99NNISEgotsuU8M4772D69OlFlq9atQpubo6bxXP16tUOe+/qKi7HD0vNo7HP2gC3bL6AzHRbEJianokNK1YU2Z5lWD4sP5afI/H8Y/ldrZmL7W++XmXGshV/QsyHl5iciiR4Qp1hxu5ifgd4DjoOv8M1s/yysrJKva1KURRb4v8yElf7hwwZAoPB1gz5xx9/oF+/frLlQhBX/P/66y9YLFdyS5fWa6+9VmzF/uquWB07diyyfPHixRg1apQMHPz9/Yt97axZs+S4DDEepLQtFqI1ROzTy8sLjogUxck0YMAA6HRs2r3a6K+3Y190Kj4d0wYrVq/EtPQZ8AurD48H/8cy5DlYLfA7zPLj+Vc5jPGnEPfVbUiHGyKf3QwPgxZ3f7sDu86lyN+EwS2CK+R9+B1m+TmSycH1QFEPDggIkPXm69WDb7jF4urBz/fee2+Rbe67774b2rfotjRmzJjrZoMqjn1cx8mTJ0sMLMQ2opAuXbqE4OCif3REsGQPmAoSH6YjK/aOfv/qyqDV5IXJahxTN0B/4wws6t8ZXYopK5Zh+bD8WH6OxPOP5Xc1tZc/dlqbyMAiQqWR54jZalvnoq/430yegyw/R9I5qB5Ylve84cBCZFmqLCIqErcbsXfvXnkfGhp6zW1cXFzkgG6q+boaN6OV5jTcU91hsSpQoIaWARgRkdPTeAbiResk+bd/hMUWUZittnutpuq7ZxPVduUaY+FoW7duxbZt2+ScGd7e3rJ71JNPPokRI0YgIiIiv4tWXFwcunXrJsdYrF27Fi+++KIcvF1cqwTVPO1ydiJcsx/xaZ1httg+dw2zQhER1Qp6jRrZVguMeU0VrXL24GHdn4g8fjPQ5BlHHx5RrXJDgcVTTz1V6m0/+OADVBYRGPz8889yPIYYExEZGYmJEyfKOTYKNt988cUX8pitVivq168vx1c89thjlXZcVLUUle00VqwWRJjP4SHtnwg+/C8QfmUmViIick46jQrZJsCY12LhZUlCC9VZuGbFOPrQiGodbXm6G9nt3r1bDtJu0qSJfH78+HFoNBp06NABlUlkgxItFtcyePBgeSMnltc6oVjM8FGy0Et9AO7xHItCROT0zEb8gmeh0ptgyf5bJMDPnyhVpanRnTKIaqQb+taJ7kQFWyTEBHXz5s2TKV8FMfP2/fffj549e1bckRKVQMxZYZ8cT6XYJ0bKG9BNRETOS62Fi8oIMxTk5OXaV1nz7jWF57MiospX7umJRepWMe+DPagQxOM333xTriOqdHmBBcRVqryZt1UMLIiInJ9aLRN2CGaTLU28vcVCzcCCqOYFFva0rVeLj4+vspm3qZbL6wolWyzsgQWbwImIagVL3jg7c16LhTqv5VqlZZdYohoXWNx+++2y29Ovv/6KCxcuyJt4/OCDD2LkyJEVc5REpRi8LVorFCUvsLC3YhARkVOz5gcWRnmvtrdYMLAgqnLlHtk0e/ZsTJs2TU6QJ2YGlDvVamVgMWPGjIo4RqJr2howCm9fbIe7/TtArfwOqNhiQURUW1hVGnmV1B5YGBU1smCAn9bF0YdGVOuUO7Bwc3OT6VxFEHHq1CkoioKGDRvC3d29Yo6Q6DoyDYE4peQgW+Mlcs7KZRxjQURUu1osrGZbYPGteShmW4dgW4ebHXxkRLXPDQUW58+fz5+Azk4EEq1bty52+5iYGNSpU+fGjpDoOjRq2+yqJosVKyyd8belHbb2vRmuLDkiIqd31tAImTlJ8IZOXtw0WxW5nDNvE9WQMRadOnWSE9Ht2LGjxG1SU1PxzTffoGXLlliyZEl5jpHomuplHcK9mtXwTzkAK9TIgQFqgxtLjYioFvjZ/zFMMz2CFEMdmLNS0Fp1Cg1UMdDlJfYgomreYnH06FG8/fbbcuI5MbN1x44dERYWBhcXFzmHxZEjR3D48GG5XHSRGjJkSMUfOVGeepn70EfzF06liu53N8ll2rxWDCIicm46jS2AMFkUWGMP40PdFzih1IVW84CjD42o1rmhcN7Pzw8zZ87ExYsX8eWXX6Jx48ZISEjAiRMn5Pp77rlHzsa9efNmBhVU+dS2+NhiMaOr+gie1S6C7vgfLHkiolpAr7UHFlaYzba5LCxQsSsUUU0bvC1aKERKWaaVJYfKmwxPsZhRXxWLQeqd0MY1BFrdzg+GiMjJ3Rs/Ew/rjyL68guweHnLZRZo2BWKyAHYAZFqvrw5K8QEeWrkZYXScB4LIqLawEXJhQeyYTXnwGox5wcWanaJJap56WaJHM2eWtZqscgTWiXmscjrHkVERM5NUdtm2FbMRtkl1j63BRFVPda+yGkCC8UqrlHlDdrOW0ZERE5OkzePhcUMS94keQoDCyKHYGBBNV9e64RiNYvGb1towR8VIqLa9RtgYYsFkaMxsKAa70Jgb8w46IY6hjA0wF+2hWyxICKqHexdoSxmZPs2wbeWocjQhuBORx8XUS1UIYGFyWRCXFwcsrKyEBgYKNPRElWVXNdAHFaiAMULLkoAdqpaoh5bLIiIageNXt5ZzWZkeTXAT5abEaJ1cfRREdVKN5wVKiMjA1999RX69OkDb29vREVFoXnz5jKwiIyMlDNz79y5s2KPlqgY9snwcs1W/G7thkvqICCkFcuKiKgWyHQNw1ElEulqDzmXhaDVcJJUohoTWHz44YcykPjmm2/Qr18/LFmyBPv27cOxY8ewdetWvPrqqzCbzRgwYICcnds+cR5RZfDJPodRmvVombtHDK7AQs2tQP3eLGwiolrgWOTdmGJ6AvvdukHJuIxGqgsIVqU4+rCIaqUb6gq1ZcsWrF27Fq1aFX9VuHPnznjggQcwe/ZszJkzB+vXr0ejRo3Ke6xExQrIOIZHNb/jmKkxDqvc4KNyZ0kREdUSOo3tGqnZosD77J+YrfsS28w9AYx09KER1To3FFi8/PLLaNGixXW3MxgMmDx58o28BVGp2eesqGc9j9m6D5FgDhFzsbIEiYhqAXu3J9ENSqScFWGGwgQeRDWnK1S7du2QkJAgH9evXx+JiYkVfVxEZZ7HQqNY5L0iZsgjIqJaocmFJfhZ/zp6Jy+GYjHZFnKSVKKaE1j4+PjgzJkz8vHZs2dhtdoGSxE5NLCAbcZV5cZzEhARUQ2jU3IQgFS4WDJki4XEwIKo5nSFuuOOO9C7d2+EhoZCpVKhY8eO0GiKn+n49OnT5T1GomtSa2w5zFWKAsX2iCVGRFRLqPJ+A2A1y4lSbQt5gYmoxgQWX3/9NUaOHImTJ0/iiSeekKllPT09K/7oiMrQYmELKtgVioioNgYWXbPXI8M4TD5W8ibNI6IaMkGeSCMr7N69G1OnTmVgQQ6jvqq1jF2hiIhqD4tbUP5j36S9SBcPOHibyCFuqK3w/Pnz+Y/nzp173aAiJibmRt6GqFSy/JrjWdPDmGuxBbvg4G0iolojtY5t3iJFAS77tMUPlv6Idmnq6MMiqpVuKLDo1KmT7P60Y8eOErdJTU2VE+i1bNlSTqBHVFkUVz/sVppgndX2g7JR34OFTURUS2h1ehxQ6sMCNWJ92mOuZQii3a+fEp+IqklgcfToUXh7e8vuUMHBwRg2bJgMNB5//HHce++9aN++PYKCgvD9999jxowZcnllWr58Obp06QJXV1cEBATI8R9Xt7DccsstcHd3l+vFuBCj0Vipx0RVR6u2Dda+oATKH5SNBs66TURUm34DnjRNxv3un+G8bzfbsrxJ84ioBoyx8PPzw8yZM/Hmm29ixYoV2Lhxo0w7m52dLSvu99xzDwYNGiRbKyrb4sWLZVDz9ttvo1+/flAUBQcPHsxfb7FYZOATGBiITZs2yTk3xo8fL7f79NNPK/34qPIZjEkYrt6KLBjwj7U91OwKRURUa9iCCJWceVuXfQnhqkvwUHwcfVhEtdIND94WXFxcZOvA1S0EVcVsNsuB46JV5MEHH8xf3qRJk/zHq1atwpEjRxAdHY2wsDC5bNasWZgwYQLeeusteHl5OeTYqeK4ZcfiSe2vSIYnTprqIMCebpCIiJyeLm/mbbPFijZn5uB73UZsz5oIoLujD42o1ilXYOFoe/bskQPD1Wq1nA08Li4Obdu2la0pLVrY+ldu3bpVtpzYgwpBtKbk5ubKjFZ9+/Ytsl+xTtzs0tLS5L3JZJK3qmZ/T0e8d01gycsz64t0zNW9jwtZTWAyDS20DcuwfFh+LD9H4vnH8rsmqxWjNevQxXgWdZOPIVksUmsr9DeT5yDLz5FMDq4HluV9VYroE3QDtm/fjqSkJAwZMiR/2fz58/Hqq68iMzMTt912m+xqZDAYUFkWLVqEu+++GxEREfjggw8QFRUlWyNEK8Xx48dll62HH35YdtMSywoSxyXGgIjXX+21117D9OnTiyxfuHAh3NzcKu3/QzcmKzEanc9+lv/8lKY+sttOYnESEdUCcVmA5vBPuFmzD64aBZlmFf7wuBP1mnRw9KEROYWsrCyMHTtWJma6Xk+fG26xEJXvPn365AcWYlyD6I4kuhg1a9ZMdk8SrQRiuxvZd3EV+4J27twJq9UqH7/44otyNnB7+tu6devil19+waRJtsqlmB38aiKeKm658MILL+Cpp54q1GIRHh6OgQMHOqTrlIgUV69ejQEDBkCn46Q/Vzt9ZA9w9spzvcGAvkOLtliwDHkOOgrPP5afIzn7+Xc2MRNrDv8iH+v0esBsQnBIGIZe9TtQHs5ehpWN5Vezy8/ec6c0bjiw2LdvH954441CrQciM5NIMSuIirhovbiRwGLKlCkYM2bMNbcRrRPp6XIaHDRv3rxQS0T9+vXz59oICQmRrSsFJScnyw9JZLQqjthHcS0t4sN05B8UR79/daV3cYEtxLRTl1hOLMPyYfmx/ByJ5x/Lrzguej3M9iSXeX0w1JX0e8lzkOXnSDoH1QPL8p43HFiIynnBivn69evzZ+O2z3UhBkzfCJFZStyup0OHDjIAOHbsGHr0sM1dIAIG0fUpMjJSPu/WrZscpB0bG4vQ0FC5THSLEq8TryfnmHm7YGChqJhmkIiottBp1DBDI2MKe99utZoX4Ygc4YZrYCKoOHPmjHws5oQQA6lFJd5OtCZUdlQluiU98sgjsmVEBAsiwHj00UflutGjR8t70X1JtGiMGzcOe/fuxZo1azBt2jSZopYZoZyDRn1VfMx0s0REtYZWo4JJ0cqZt5W80EKl0Tj6sIhqpRtusRCtE88//zzee+89LF26VA5q7tmzZ/76AwcOoEGDBqhsYiyHVquVgYOYR0N0x/rnn3/g6+sr12s0GjmB3uTJk9G9e3c5iZ4YgCIyR5GT8AjEy+b7cbN6L/qo98l85kREVDvo1Go567ZghhaLLTchzO1KJkgiqgGBhZgcT8xf0bt3b3h4eGDevHnQi0FTeb777jvZWlDZRKuICBKuFSiIrFHLli2r9GMhB9G5You1JRIVLyQo3nB3rY+iSYSJiMhZWyxEVyhhh3s/fJF6M15wj3D0YRHVSjccWDz33HNy1m2RmUkEFqJloCCRlUksJ6psGrWtheKYEoFjlgj0cg9koRMR1aLAYq5lML63DEIPjxAACXmzcRNRVbvhb55ooRBdj7y9vYsEFYKYQ6JgCwZRZVGbc9BfvRsD1Ltsz9kTioiolnWF0sAFRnRIXY1AJEOvMjv6sIhqpRtusbjBefWIKpzGnIUXtAvl4/3GBnC3chJDIqLaQq1WyQtKI9RbMTLjLwzVW3HI+B2ARo4+NKJa54YDC6GkCeaIqpJafaXh7Sf9mzib2gXgKAsiolqjq+Y4HlSvgFVR44wSAqNnuKMPiahWKldg0bhx4+sGF0lJSeV5C6Lr0mgKn8YKs0IREdUqkZoEOYmF6E2xztoWHTnGgqjmBRbTp0+XYyyIHEp91RgfTpBHRFSrKOJ3wCICCyBbMcgB3URUwwKLMWPGICgoqOKOhugGaIpcmeIPChFRbWJV2SbktSoKcqCHtkAXWSKqOjf8zeP4CqqOYywktlgQEdUuatt1UtFikQMddGyxIKpZgQWzQlF1oS7SFYotFkREtUpe2nuRrzIboisUWyyIHOGGv3liYjx2g6LqQK3R423zWJxQ6toWsMWCiKh2yesKdUEJxC5rE+g4oRFRzRtjQVQdaLRarLF2QIrigZ6ag/BybeboQyIiIge0WGTIafJ0bLEgchAGFlTj2S9M7VaaYLe5CUZ61XH0IRERURU66doGtya+AVNetYZZoYgcg4EF1XgikUAP9UGoYcU2a3MmFiAiqmUeH9AMsUt+xOUsM9b7jUaTYE9HHxJRrcTAgpzCq7r5UCtWPGSaBr0S5ujDISKiKtS3UQDgsRuKOzD1wRmAgdUbIkdg2gRyCvbZtr/VzUS/hIWOPhwiIqpKyWeuJAXUubLsiRyEgQU5BaXgqcxsIEREtUtG/JXHWhdHHglRrcbAgpyqxUJiulkiotrFYrzymLNuEzkMAwtyCpZCpzInyCMiqlWCmGacqDrg6CZyCopopVCuZIkiIqJaxCMIGLcUMDAbFJEjMbAgp8CuUEREtZxPuKOPgKjWY1cocgrfqe9AOtyutF4QERERUZViiwU5hY3qzkg1W9BFfRTervUcfThEREROz2KxwGQyXXc7sY1Wq0VOTo58DZVNZZefTqeDRqOpkH0xsCCnoFED/1jby9tEXwYWRERElUVRFMTFxSElJaXU24eEhCA6OprjIG9AVZSfj4+PfI/y7p+BBTmF5sopRKrScUSJhJqDt4mIiCqNPagICgqCm5vbdSujVqsVGRkZ8PDwgJrpgMusMstPBC1ZWVmIj7fNBRMaGlqu/TGwIKcwxTIfPrpEPGV6FGo0d/ThEBEROSXRFcceVPj7+5e6Ymw0GuHi4sLA4gZUdvm5utpmqxfBhfhcy9MtioEFOQUrbF+CD3Rf4swl0TTbwtGHRERE5HTsYypESwU5D7e8z1N8vuUJLJg+h5yOilmhiIiIKvm3lnNGORNVBX2eThFYLF++HF26dJFNOQEBARg5cmSRwrr6Nnv2bIcdL1U8q6pAdM3AgoiIiKjK1fjAYvHixRg3bhzuv/9+7N+/H5s3b8bYsWOLbDd37lzExsbm38aPH++Q46XKUWjuCl5FISIiohIGnj/++OOoX78+DAYDwsPDccstt2DNmjVyfVRUVP5FaHHBumnTppgxY4Yc5Gx39uxZuX7fvn2Fnmu1WsTExBR6P1HnFMvFerHd1QYOHCi7Hm3btq3Yz2vv3r2488470bhxY9ldSdxPnDgRx48fr5afb40OLMxmM6ZOnSo/8EceeUQWdpMmTTBq1KgS02jZb/aBKuQsCjThscWCiIiIriIq9h06dMA///yD999/HwcPHsRff/2Fvn374rHHHsvf7vXXX5cBwdGjRzFt2jT85z//wddff33d8gwLC8P8+fMLLZs3bx7q1KlT7Pbnz5/H1q1bMWXKFMyZM6fI+mXLlqFr167Izc2V73/48GEsWLAA3t7eePnll6vl51ujA4s9e/bIyFCMkG/Xrp1MkTVkyBBZ8FcTH5roJtWpUyfZDUqMsCfnYS1wKnOMBREREV1t8uTJsuVgx44d8iK0uCDdokULPPXUU4VaDDw9PeVFaNF68dBDD6F169ZYtWrVdQt0/PjxsodMQd9//32JvWTEtsOHD8ejjz6Kn3/+GZmZmfnrRApY0Rtn6NCh+N///oc+ffqgXr16suv/zJkz8dVXX1XLD7hGZ4U6ffq0vH/ttdfwwQcfyBNg1qxZ6N27t2wi8vPzk+vfeOMN3HzzzbKVQjR1Pf3000hISMBLL71U7H5FZChudmlpafkj5Uszw2RFs7+nI967plhlGIhxxm/lYwVKkbJiGZYPy4/l50g8/1h+jsZzsHBZiG5B4gKt/SKteJ5tKnlGaLneaIEm11Thg75ddZpS7TMpKUm2Trz55puyPnj1BWYvL69C/x/xWNyvX79etlw0bNgwf33B+4LlMHz4cHnxesOGDejRowc2bdok33fYsGGyLnp1mYnA4tNPP5UBjrgtWrRIBhPCn3/+KeuqosXE3g3LflxXH29FsP9/i8sKVZb6Z7UMLESgMH369Gtus3PnzvwCffHFF3HHHXfIx+JDqlu3Ln755RdMmjRJLisYQLRt2za/maukwOKdd94p9v1FtOrI9GqrV6922HtXd2tymiLVfBvaqE8hLcGKjBUrit2OZVg+LD+WnyPx/GP5ORrPQcjxAuJqvpiwTcytIIigodsHxY8RqGxbn+oKV/3106OKcbii4hwREZF/wbg4om75/PPPy65G4v8nKtVi/ogHHngg/3Xi/y6IFgaxzP7caDRi9OjRstuSaOUQ9+K5vZzEdvZ9rF27Vr6+W7ducpmox37zzTf59dlDhw7Je9GNKj09XT6231cGcYzZ2dkyKBJDDQoSrSc1OrAQ3ZbGjBlzzW1E64S9gJs3vzIhmhiIIwbkiH5rJRH91cSHeOnSJQQHBxdZ/8ILL8hmMTuxrRjcIwbYiAixqomTWvwxGzBgAHQ6XZW/f00w5/w2/JbZE79Ze+KZ1o0wtGe9QutZhuXD8mP5ORLPP5afo/EcvCInJwfR0dFyFmhR4Ra0xsIV0ark6eUJN/31q7P2C8Pi/lp1OdG9XrQSiO5Lly9flgGGGIMh6mB24v8uuLu7y30VfP7II4+ge/fucgyH6MIkkgrZK+piO/t7i9aJu+66K793zYQJE/DKK6/IsR1ivLCoz8r/n6envIk6r7ivrDS/4nMVLTm9evXK/1ztrhWI1YjAQoyFELfrEQNwRMEfO3ZMNjnZv/xicE5kZGSJrxMj7EWhiQHdxRH7tH+gBYlKvSMr9o5+/+osXLkIqC7hnBIMnVZTYjmxDMuH5cfycySefyw/R+M5aJt5W1RuRQXcPgu0u0GHI68PumYrQHpaugwCKnrm6NJ2hRKVdbGdqDNe7xgCAwPzuyeJ7KOiG5RoWejfv79cb3+9vQwKPm/durXMJHXPPfegWbNm8rk9e5R9W9E9SgQdos5acPoDUbZiTMZ7770nj1cQXfvFuArBXu6VQexX7L+4c7wsdc9qGViUloj6RGT46quvyhYFEUyIDFGCaHoS/vjjD5laTJwQIhITTU+i69TDDz9cbPBANdNdWQtRR3cM0833Qa3q5OjDISIiqjVEhfRarQYisDDrNXKbyqoYX49oGRg0aBA+//xzPPHEE7J1oaCUlJRiLzj7+vrK9LSiFUNcmC5NEPPAAw/IgeJffvllset//PFH2W1/6dKlhZaLccCiO/5bb70le8mIi+yi5UMEN1cr6XgdrUZnhRJEICG6TYm5LETGp3Pnzsk0YuJEsEdZX3zxhQwsRNT48ccfy/EVYpA3ORPbqfyqdj4aXPrT0QdDRERE1YyoD4pWgc6dO8vK+okTJ+TA7E8++UTWE0siUtGKlo7iKvjFmThxouxGJTJKFUeklhVZqVq2bFnoJgISETCIiZ9F4PPtt9/Kx7feeivWrVsne+Ts2rULzz77rLywXh3V+MBCBA4i7ZYYLyH6gImxCCJ1mN3gwYNlhCn6polBMiJnsZj7Qgw+IuecIE9VcE4LIiIiIkCmaxVTFYgxEyJDqKjMi7EToqWgpNYFe9cocQFbJBcqTSYmrVYrWxuKq2vu3r1bDiS3D9IuSIyhEC0V9jktRECxZcsWWdcVwYoYU3z33XcjNTVVZreqjli7JucLLDjzNhERERVDzHn22WefyVtxipsdWyg4QZ5IIFRwJu6rn19NZCS1r7/etr///nuh5x07dsSvv/4qL56LIQCO6kpWWtX76IhK7Uorhaqaf+mIiIiInBFrYOQUFFWBHNYFWi+IiIiIqGqwBkZO2BWKpzURERFRVWMNjJzCPvfuV54wsCAiIiKqchy8TU7hiFtnpFv6o6kqGgEGf0cfDhEREVGtw8CCnIJGDcy1DJGPZ/i3dvThEBEREdU67ApFTsHXkoBGqgvwRRrUTDdLREREVOUYWJBT6J+6GLN1H+JmzV4w2ywRERFR1WNgQU51Kj+q+R3Bl7c4+mCIiIiIah0GFuQcCnR/uvKIiIiIqPwmTJiA2267jUV5HQwsyDkUmseCoQURERFRVWNgQc4XWKgLzMJNRERERFWCgQU5BUV1JZhgiwUREREVqSsoCt5//33Ur18frq6uaNOmDX799df89YcPH8awYcPg5eUFT09P9OzZE6dOnSq0j5kzZyI0NBT+/v547LHHYDKZ8tclJyfjvvvug6+vL9zc3DBkyBCcOHEif/33338PHx8fLF26FI0bN4aLiwsGDBiA6Ohouf7s2bNQq9XYtWtXoff87LPP0KpVK3n869atk/Wc5cuXy+MX++jSpQsOHjxY6DVbtmxBr1695P8zPDwcTzzxBDIzMyv9pGBgQU5BVTAVFGfeJiIiqnqm7JJv5tzSb2vKKd22ZfTSSy9h7ty5+PLLL2UQ8eSTT+Lee+/F+vXrERMTIyvioqL+zz//YPfu3XjggQdgNpvzX7927VoZaIj7efPmyUBB3AqOw9i1axd+//13bN26VQYCQ4cOLRR8ZGVl4a233pKv37x5M9LS0jBmzBi5LioqCv3795fHWJB4j7Fjxxa6cPrMM8/IIGfnzp0ICgrCiBEj8t9HBBmDBg3CyJEjceDAAfz888/YtGkTpkyZgsrGCfLIKZx1b4N6+FM+ZlcoIiIiB5jdo9jFojrsGtoJGPnFlYXfDgDMJQQHdToAI7++8vz74UBOStHtHt9d6kMTV+s/+OADGTR069ZNLhMtF6LC/dVXX8lKvbe3NxYtWgSdTifXi1aFgkRLhGg90Gg0aNq0qWzdWLNmDSZOnChbJn7//XcZLNx0001y+x9//FG2FogWitGjR8tlovIv9iFaGQQRYDRr1gw7duxA586d8dBDD+GRRx6Rx2owGLB//37s27evUAAjvPrqq7K1w76PunXr4rfffsOdd96JGTNmyEDk//7v/+T6Ro0a4ZNPPkHv3r1lUCWCp8rCFgtyCue8OuJPa2ccUurBqvNw9OEQERFRNXLkyBHk5OTIyriHh0f+bf78+bIVQlTeRdcne1BRnBYtWsigwk50iYqPj5ePjx49Cq1Wmx8wCKK7VJMmTeQ6O7FNx44d85+LAEV0j7JvIzJPiW1EkCB899136Nu3LyIiIgodiz04Evz8/Aq9j2htEYFIwf+naMGwWq04c+YMKhNbLMgpqFXATPNd8vFcv+aOPhwiIqLa55FNxS5WrFZkp2egUJX9odXX2NFV2R0nLCv3oYlKtSDGJtSpU6fQOtEyYL+6fy1XBx2ia5J9v6LbU3HE8qvHfhY3FtS+TK/XY9y4cbI7lOjKtHDhQtl6URr2fYhjmjRpkhxXcbWrA5SKxsCCnIKbNR3hqkvIUFwLTmlBREREVUXnWvxyUfnWmkq3bVn2WwbNmzeXAcT58+dll6CrtW7dWnYpEl2VrtVqca39m81mbN++Pb8rVGJiIo4fPy67OtmJbcQ4DNHtSTh27BhSUlJky4Wd6A7VsmVLfPHFF/J4RIBRcJyGsG3btvwgQQwaF+9j30f79u3lGJKGDRuiqrErFDmFDol/4Hvd+7hbsxZqRhZERERUgMjyNG3aNDlgWwQQovvT3r178fnnn8vnYmCzfSC1qPiLMRMLFiyQFf/SEOMYbr31VjneQozbEGMjxMBw0ToiltuJoOXxxx+XAciePXtw//33o2vXrvmBhiACEbHsueeew9133y0zO13t9ddfl+M7Dh06JAeNBwQE5E/gJ14nBo+LrFWii5d9/Id438rGwIKcQ1662Ts0G+CZfMTRR0NERETVzBtvvIFXXnkF77zzjqy8i3EHf/zxB+rVqyfHQ4iB3RkZGbJFo0OHDvjmm2/K1Hoxd+5c+brhw4fLMRCiG9SKFSsK7UOkoRUVfzG4WmwjggYxYPxqDz74IIxGo8xMVZx3330XU6dOle8XGxsrAwfRjcre+iIyXYmAQowbadeuHV5++WU5JqSysSsUOYcCKWY1isWhh0JERETVjxiDIMYdFDf2wF4hX7lyZbHrrs7KJHz00UdFskbNnz//uschujaJ27WIYEF0h+rUqVP+OI6CevToIVsrSiJet2rVKlQ1tliQcyg4d0XBOS2IiIiIaoiMjAw5N8Wnn35aYgBUnbEGRk4h3qMZjNAiAd4wekU5+nCIiIiIykyM9RCtEaI7VkndoKozBhbkFOJ82mKE8S3cbXwJiouXow+HiIiIqBAxyFpkgLoW0eUqNzdXzpZdcM4Muz59+sixG2Lui+qIYyzIKbSp6w2rWgcvFy0aBHKCPCIiIqKqxsCCnMLNzYKx95UB0GvUcNEVjfCJiIiIqHIxsCCn4eVS9gltiIiIqOxKmmmaavfnWaPHWKxbt06mDivuJkbU24lZFm+55Ra4u7vLCUTEKHuRG5iIiIiISs8+J0NWVhaLzYlk5X2eNzLruNO0WIgp00We34LEBCB///03OnbsKJ9bLBYMGzYMgYGBciZEMb36+PHjZWQmUnkRERERUemIAcVi4HB8fHz+hG/igu61iHkYxAXdnJwcqJkSvswqs/xEfVgEFeLzFJ9rcQPGa01gIWYYDAkJyX9uMpnkzIMiVZf9JBeTgxw5cgTR0dEICwuTy2bNmiVH5r/11lvw8mIGISIiIqLSste97MFFaSqv2dnZcpbp6wUh5JjyE0FFwTp1rQwsriaCioSEBBk02G3dulXOXGgPKgQxhbtI5bV792707dvXQUdLREREVPOIym1oaCiCgoLkRd3rEdts2LABvXr1KndXm9rIVMnlJ/ZZ3pYKpwws5syZI4OG8PDw/GVxcXEIDg4uMuW6aO0Q64ojgg5xs0tLS8v/YEvzBapo9vd0xHs7C5Yhy4/nX83F7y/Lz9F4DpasNBVS0ZXHbDbLbSuqAlubWCu5/MT+xa0kZal/qpRqOKz/tddew/Tp06+5jRicbR9HIVy4cAGRkZH473//izvuuCN/+cMPP4xz585h5cqVhV4vAov58+djzJgxpX7/hQsXyr6ERERERES1QVZWFsaOHYvU1NTrDiGoloGF6M4kbtcSFRUFFxeX/OdvvPGGHIwdExNTqJnolVdewf/+9z/s378/f1lycjL8/Pzwzz//FNsVqrgWC9EKIo7JEWMyRKS4evVqDBgwgE2ILEOH4DnI8nMknn8sP0fjOcjyq83nX1pamsyqWprAolp2hRIHL26lJWKjuXPn4r777itS4N26dZODtEX2KNEf0D6g22AwoEOHDsXuT6wTt6uJfTuyb6Cj398ZsAxZfjz/ai5+f1l+jsZzkOVXG88/XRnes1oGFmUlWh7OnDmDBx98sMi6gQMHonnz5hg3bhxmzJiBpKQkTJs2DRMnTix164O9Ucc+1sIRkapohhLvz8CCZchzsObhd5jlx/OvZuN3mOVXm8+/tLz6b2k6OVXLrlBlJfp9iXEUmzdvLna9mCBv8uTJMgARqbrE9jNnziy2VaI4YvxGwQHhRERERES1SXR0NOrWrev8gUVlEyPlL168CE9PT4fkX7aP8RAfKOfdYBk6As9Blp8j8fxj+Tkaz0GWX20+/xRFQXp6upy64XoT9DlFV6jKJgrxehFaVRAnEwMLliHPwZqL32GWH8+/mo3fYZZfbT3/vL29S7Vdxc4LTkREREREtRIDCyIiIiIiKjcGFjWAGGT+6quvlnqwObEMeQ5WL/wOs/x4/tVs/A6z/Hj+lQ4HbxMRERERUbmxxYKIiIiIiMqNgQUREREREZUbAwsiIiIiIio3BhbViJh85P/+7/8QGRkpZwi/6aabsHPnzkITlLz22mtyghKxvk+fPjh8+DBqqw0bNuCWW26R5SEmLly6dGmh9aUpr9zcXDz++OMICAiAu7s7RowYIWdarw2uV35LlizBoEGDZNmI9fv27SuyD5Zf8eVnMpnw3HPPoVWrVvK8Etvcd999cqJNll/pzj/x3W3atKksP19fX/Tv3x/bt29n+ZXhO1zQpEmT5DYfffQRy7CU5TdhwgS5vOCta9euLL8ynH9Hjx6Vv6tiDgQxybAov/Pnz/M3BNcvv6vPPfttxowZ1br8GFhUIw899BBWr16NBQsW4ODBgxg4cKD8MY2JiZHr33//fXzwwQf47LPPZMAREhKCAQMGyICkNsrMzESbNm1keRSnNOUlArnffvsNixYtwqZNm5CRkYHhw4fDYrGgtpefWN+9e3e8++67Je6D5Vd8+WVlZWHPnj14+eWX5b0I0o4fPy7/6LP8Snf+NW7cWK4TfwvFdzMqKkr+Tbx8+TLPv1KWoZ2osIigTFRg+B0u/d9AYfDgwYiNjc2/rVixgt/hUpbfqVOn0KNHD3mBYN26ddi/f7/8m+ji4sLvMK5ffgXPO3H77rvvZGBxxx13VO/yU6hayMrKUjQajbJs2bJCy9u0aaO8+OKLitVqVUJCQpR33303f11OTo7i7e2tzJ49W6ntxKn822+/5T8vTXmlpKQoOp1OWbRoUf42MTExilqtVv766y+lNpdfQWfOnJHr9+7dW2g5y6905We3Y8cOud25c+dYfmU4/+xSU1Pldn///TfLrwzf4QsXLih16tRRDh06pERGRioffvghv8OlLL/x48crt956a4nnJP8GXrv87rrrLuXee+9l+VXQ30BxLvbr16/an39ssagmzGazjDALRvKC6MIjotAzZ84gLi5OXrErmFe7d+/e2LJliwOOuHorTXnt3r1bdlkpuI24oteyZUuWaSmw/MomNTVVXm3y8fFh+ZWR0WjE119/LbtTiCt8PP9Kx2q1Yty4cXjmmWfQokWLIuv5Hb4+caU9KChItqBNnDgR8fHxLL9SnnvLly+X5Sa61Ioy7NKlS6HuPjz/Su/SpUuyPB988MFqX34MLKoJ0fewW7dueOONN2Q/bBFk/PDDD7L5WjSBiUqyEBwcXOh14rl9HV1RmvIS93q9XvbfZpmWHcuv9HJycvD8889j7Nix8PLyYvmV0rJly+Dh4SEvuHz44Yeyq6joS8zzr3Tee+89aLVaPPHEE8Wu53f42oYMGYIff/wR//zzD2bNmiW71Pbr10/2a2f5XZsIwES3HNGVVnQnW7VqFW6//XaMHDkS69evZ/mV0bx582Q9UZRfdf/+ah32zlSEGFvxwAMPoE6dOtBoNGjfvr2siIg+2nbiimdBogXt6mWEcpUXy7R8WH6FiStKY8aMkVfwvvjiC5ZfGfTt21cmDUhISMA333yDO++8U15sEVc/ef5dm7ia+fHHH8vfj7L+RvA7bHPXXXfll4m4CtyxY0eZXEVcOS5YwWP5FSX+3gm33nornnzySfm4bdu28kr67NmzZe8Bll/pifEV99xzT5FeLdXx+8sWi2qkQYMGMpIXUX50dDR27NghKyX16tWTA4+Fq6NQcVXg6qvyhFKVl9hGdLFITk5mmd4Alt/1ie+vqAyLrnniaru9tYLlVzoiy0nDhg1lJpk5c+bIq+/inuV3fRs3bpR/7yIiImS5idu5c+fw9NNPy4HwLMOyCw0NlYHFiRMnWH7XIVoWxTnXvHnzQsubNWuWnxWKvyGl/y4fO3ZMJvgpqLqWHwOLavpjKv6AiZNl5cqVMuK3BxeicmInTigRiIi0tFRYacqrQ4cO0Ol0hbYR3c4OHTrEMi0Fll/pggpRCfn777/h7+/P8isncSXO3g2F59+1ibEVBw4ckC0+9pvofy3GW4jfFZZh2SUmJsqLfuL3meV3baKLTqdOnWSFuCCRHU8EZyy/0hMXU8TfO/v4Mrvq+jeQXaGqEfHHXvxwNmnSBCdPnpQ/AOLx/fffL5u1RFqxt99+G40aNZI38djNzU12l6qNRMuOKCc7cVVY/Hj6+fnJq3TXKy8xEFQMhBJX8ESlT7xu2rRpcu4Bkea3tpdfUlKSvLJkn3vB/gMhAjZxY/mVXH6iAjdq1CjZDUWMExBjpuytZ2K9+NFl+ZVcfuL7+NZbb8n0vKISJyp0ohuZyM8+evRouX1tL7/SfIevDmZFJUR8d8XvilDby/Ba5SduYi4VkdpTnINnz57Ff/7zH3klXowVEFh+1z7/RB1GdCfr1auX7Nb4119/4Y8//pAD4ll+uO73V0hLS8Mvv/wix/hcrdqefw7LR0VF/Pzzz0r9+vUVvV4vU6U+9thjMp1YwRSqr776qlxnMBiUXr16KQcPHqy1Jbl27VqZou3qm0gRWNryys7OVqZMmaL4+fkprq6uyvDhw5Xz588rtcH1ym/u3LnFrhdlasfyK7787Cl6i7uJcmf5Xfv8E+fV7bffroSFhcm/h6GhocqIESNkyt6CavP5V5rv8NWuTjdb28vwWuUnUsAPHDhQCQwMlCk9IyIi5PKry4bld+3zb86cOUrDhg0VFxcXmT5/6dKlLL8yfH+/+uor+b0sWBes7uefSvzjuLCGiIiIiIicAcdYEBERERFRuTGwICIiIiKicmNgQUREREREDCyIiIiIiMjx2GJBRERERETlxsCCiIiIiIjKjYEFERERERGVGwMLIiIiIiIqNwYWRERUaxmNRjRs2BCbN2+Wz8+ePQuVSoV9+/ZV6vsePHgQdevWRWZmZqW+DxFRVWJgQUTkJCZMmCArxVffTp486ehDq7a+/vprREZGonv37qV+TVRUFD766KMiy1977TW0bdu2VPto1aoVOnfujA8//LBMx0tEVJ0xsCAiciKDBw9GbGxsoVu9evWKvVJPwKeffoqHHnrIIUVx//3348svv4TFYuFHQUROgYEFEZETMRgMCAkJKXTTaDTo06cPpkyZgqeeegoBAQEYMGCA3P7IkSMYOnQoPDw8EBwcjHHjxiEhISF/f6Krzn333SfXh4aGYtasWXJf//d//5e/jWgVWbp0aaHj8PHxwffff5//PCYmBnfddRd8fX3h7++PW2+9VXY7Ktjactttt2HmzJnyfcQ2jz32GEwmU/42ubm5ePbZZxEeHi7/n40aNcKcOXOgKIrsziReW9ChQ4egVqtx6tSpYstqz549sjVn2LBhJZan1WrFxIkT0bhxY5w7d66Un8KVcrn6Jlo77AYNGoTExESsX7++TPslIqquGFgQEdUS8+bNg1arleMJvvrqK9ma0bt3b9l9Z9euXfjrr79w6dIl3HnnnfmveeaZZ7B27Vr89ttvWLVqFdatW4fdu3eX6X2zsrLQt29fGZxs2LABmzZtko9F60rBlhPxPiIIEPfiWEVgUjA4EQHOokWL8Mknn+Do0aOYPXu23I+osD/wwAOYO3duoff97rvv0LNnTzRo0KDY4xLHIgIGLy+vYteLYxNlIcpGHLPoMlUWBVuNRAAjgp9evXrlr9fr9WjTpg02btxYpv0SEVVbChEROYXx48crGo1GcXd3z7+NGjVKruvdu7fStm3bQtu//PLLysCBAwsti46OVsRPw7Fjx5T09HRFr9crixYtyl+fmJiouLq6KlOnTs1fJrb/7bffCu3H29tbmTt3rnw8Z84cpUmTJorVas1fn5ubK/ezcuXK/GOPjIxUzGZz/jajR49W7rrrLvlYHI94n9WrVxf7f7948aL8v2/fvl0+NxqNSmBgoPL999+XWF7i/9CvX79Cy86cOSPfZ+PGjUr//v2V7t27KykpKYW2EccpyqVgOYubTqdT2rRpU+R9xP/79ttvVzp06KBkZWUVWieWT5gwocRjJCKqSbSODmyIiKjiiJYB0W/fzt3dPf9xx44dC20rWh5E64C46n810XKQnZ0tr9p369Ytf7mfnx+aNGlSpmMS7yOu2Ht6ehZanpOTU6ibUosWLWS3LTvRJUpkTxJEliaxTrSwFEdsK7o0iVYKMSh62bJlcv+jR48u8bjE/8/FxaXYdXfffbfM2rRmzRq4ubkVWS9ackT3rYJES4poBbnaf/7zH2zduhU7d+6Eq6troXXiuWjRISJyBgwsiIiciAgkRJebktZdPX7glltuwXvvvVdsRf3EiROlek/RFcnWcHFFwbER4n06dOiAH3/8schrAwMD8x/rdLoi+xWvFa6ukBdHDMIWY0REpiXRLUqM6SguKLATY03sgcvVxLiTH374Adu2bUO/fv2Kfe3V5SyCrquJfYjjEV3IRKBytaSkpBK7ahER1TQcY0FEVEu1b98ehw8flgOKRSW54M0eoIjKvqhc2yUnJ+P48eNFggMxjsBOBCQFr8KL9xHLgoKCiryPt7d3qdOziiDjWgOdRTAgjlu02Pz5559y3MW1tGvXDv/++2+RoEh49NFH8e6772LEiBE3PLhatFKIYEeMZ+natWux24gB5uI4iIicAQMLIqJaSmRdElfMRbefHTt24PTp03KAtqiQixSooovUgw8+KLv9iC5BohIsuv+ITEsFiSv6n332mcyyJAY6P/LII4VaH+655x55hV9kghIDlc+cOSMr61OnTsWFCxdKdawi+Bk/frw8NpGBSuxDtAL897//zd9GdJUSx/fCCy/IoKVgF66Suo2JrFciuCrO448/jjfffBPDhw+Xg7fLIi4uDrfffjvGjBkjsz+J5+J2+fLl/G1EViyRLat///5l2jcRUXXFwIKIqJYKCwuTGaJEECEqvy1btpSVfdGKYA8eZsyYITMZiSv3ogLco0cP2a2pIJGCVqSAFduNHTsW06ZNK9QFSTwWYw8iIiIwcuRINGvWTAYIYoxDSRmZiiNaIkaNGoXJkyejadOmMg3s1TNXi0BIjAu5XmuFIFLaiuMprouWnUirO336dNkasmXLllIfq2gJERm2RHYr0a3MfuvUqVP+Nj/99BMGDhxY5mxTRETVlUqM4Hb0QRARUc0h5rEQKWqLm33a0USgJI5PtISIeTmuR4yxEAFTcYPLK5OYk0PMwyGCi7LM+k1EVJ2xxYKIiGo8UVEXwcHLL78s554oTVBhH7vx/vvvF5qsryqIyfZefPFFBhVE5FSYFYqIiGo8ceVfdIMSLSkLFiwo02vF2I2qJibmEzciImfCrlBERERERFRu7ApFRERERETlxsCCiIiIiIjKjYEFERERERGVGwMLIiIiIiIqNwYWRERERERUbgwsiIiIiIio3BhYEBERERFRuTGwICIiIiKicmNgQUREREREKK//B0pe8MpApa5oAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    ref_ts[\"f_m\"] / 1000,\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    f_m / 1000,\n",
+    "    TS_m,\n",
+    "    title=\"Final TS(f)\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=r\"TS(f) (dB re 1 m$^2$)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5edae46a",
+   "metadata": {},
+   "source": [
+    "### Reproduce the Andersen et al. (2024) Figure 7 diagnostic panel\n",
+    "\n",
+    "We reproduce a Figure 7-style diagnostic panel from Andersen et al. (2024) using the echopype implementation. The panels show the target spectrum, matched-filter autocorrelation spectrum, normalised target spectrum, beam-compensated gain, and final calibrated TS spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "70228c93",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x1000 with 5 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(5, 1, figsize=(8, 10), sharex=True)\n",
+    "\n",
+    "ax[0].plot(f_m / 1000, db20(Y_pc_t_m))\n",
+    "ax[0].set_ylabel(r\"$|Y_{pc,t}|$\")\n",
+    "\n",
+    "ax[1].plot(f_m / 1000, db20(Y_mf_auto_red_m))\n",
+    "ax[1].set_ylabel(r\"$|Y_{auto,red}|$\")\n",
+    "\n",
+    "ax[2].plot(f_m / 1000, db20(Y_tilde_pc_t_m))\n",
+    "ax[2].set_ylabel(r\"$|\\tilde{Y}_{pc,t}|$\")\n",
+    "\n",
+    "ax[3].plot(f_m / 1000, 10 * np.log10(g_theta_phi_m**2))\n",
+    "ax[3].set_ylabel(\"Gain (dB)\")\n",
+    "\n",
+    "ax[4].plot(f_m / 1000, TS_m)\n",
+    "ax[4].set_ylabel(\"TS(f)\")\n",
+    "ax[4].set_xlabel(\"Frequency (kHz)\")\n",
+    "\n",
+    "for a in ax:\n",
+    "    a.grid(True)\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "43d1434b",
+   "metadata": {},
+   "source": [
+    "### Summary of differences between CRIMAC and echopype processing steps\n",
+    "\n",
+    "The table below summarises the differences between corresponding variables computed by CRIMAC and echopype at each stage of the TS-spectrum workflow."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "af274118",
+   "metadata": {},
+   "source": [
+    "tmp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "8abea7a8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['y_rx_nu', 'r_n', 'f_m', 'alpha_m', 'lambda_m', 'y_tx_n', 'y_mf_n', 'y_mf_auto_n', 'tau_eff', 'y_pc_nu', 'y_pc_n', 'p_rx_e_n', 'theta_n', 'phi_n', 'Sp_full_n', 'Sp_full_r', 'Sp_target_n', 'Sp_target_r', 'dum_r', 'dum_theta', 'dum_phi', 'r_t', 'theta_t', 'phi_t', 'y_pc_t_n', 'y_mf_auto_red_n', 'Y_pc_t_m', 'Y_mf_auto_red_m', 'Y_tilde_pc_t_m', 'P_rx_e_t_m', 'g_theta_phi_m', 'TS_m']\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(ref_ts.files)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "848ac4e0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "y_pc_n abs: RMSE=0.000203375, max_abs=0.00662722\n",
+      "\n",
+      "FIRST DIFFERENCE ABOVE TOLERANCE\n",
+      "variable: y_pc_n abs\n",
+      "index: 1\n",
+      "CRIMAC: 8.244825873734117\n",
+      "echopype/manual: 8.251453096905179\n",
+      "diff: 0.006627223171062013\n"
+     ]
+    }
+   ],
+   "source": [
+    "checks = [\n",
+    "    (\"y_pc_n abs\", np.abs(ref_ts[\"y_pc_n\"]), np.abs(y_pc_n)),\n",
+    "    (\"p_rx_e_n dB\", db10(ref_ts[\"p_rx_e_n\"]), db10(p_rx_e_n)),\n",
+    "    (\"Sp_full_n dB\", ref_ts[\"Sp_full_n\"], Sp_n),\n",
+    "    (\"r_t\", np.array([ref_ts[\"r_t\"]]), np.array([r_t])),\n",
+    "    (\"theta_t\", np.array([ref_ts[\"theta_t\"]]), np.array([theta_t])),\n",
+    "    (\"phi_t\", np.array([ref_ts[\"phi_t\"]]), np.array([phi_t])),\n",
+    "    (\"y_pc_t_n abs\", np.abs(ref_ts[\"y_pc_t_n\"]), np.abs(y_pc_t_n)),\n",
+    "    (\"y_mf_auto_red_n abs\", np.abs(ref_ts[\"y_mf_auto_red_n\"]), np.abs(y_mf_auto_red_n)),\n",
+    "    (\"Y_pc_t_m dB\", db20(ref_ts[\"Y_pc_t_m\"]), db20(Y_pc_t_m)),\n",
+    "    (\"Y_mf_auto_red_m dB\", db20(ref_ts[\"Y_mf_auto_red_m\"]), db20(Y_mf_auto_red_m)),\n",
+    "    (\"Y_tilde_pc_t_m dB\", db20(ref_ts[\"Y_tilde_pc_t_m\"]), db20(Y_tilde_pc_t_m)),\n",
+    "    (\"P_rx_e_t_m dB\", db10(ref_ts[\"P_rx_e_t_m\"]), db10(P_rx_e_t_m)),\n",
+    "    (\"g_theta_phi_m dB\", db10(ref_ts[\"g_theta_phi_m\"]), db10(g_theta_phi_m)),\n",
+    "    (\"alpha_m\", ref_ts[\"alpha_m\"], absorption_f),\n",
+    "    (\"TS_m\", ref_ts[\"TS_m\"], TS_m),\n",
+    "]\n",
+    "\n",
+    "tol = 1e-6\n",
+    "\n",
+    "for name, ref, val in checks:\n",
+    "    ref = np.asarray(ref).reshape(-1)\n",
+    "    val = np.asarray(val).reshape(-1)\n",
+    "\n",
+    "    n = min(ref.size, val.size)\n",
+    "    diff = val[:n] - ref[:n]\n",
+    "\n",
+    "    max_abs = np.nanmax(np.abs(diff))\n",
+    "    rmse = np.sqrt(np.nanmean(diff**2))\n",
+    "\n",
+    "    print(f\"{name}: RMSE={rmse:.6g}, max_abs={max_abs:.6g}\")\n",
+    "\n",
+    "    if max_abs > tol:\n",
+    "        idx = int(np.nanargmax(np.abs(diff)))\n",
+    "        print(\"\\nFIRST DIFFERENCE ABOVE TOLERANCE\")\n",
+    "        print(\"variable:\", name)\n",
+    "        print(\"index:\", idx)\n",
+    "        print(\"CRIMAC:\", ref[idx])\n",
+    "        print(\"echopype/manual:\", val[idx])\n",
+    "        print(\"diff:\", diff[idx])\n",
+    "        break"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f2191bfe",
+   "metadata": {},
+   "source": [
+    "end tmp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "6ff2975a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>n</th>\n",
+       "      <th>CRIMAC mean</th>\n",
+       "      <th>echopype mean</th>\n",
+       "      <th>mean diff</th>\n",
+       "      <th>median diff</th>\n",
+       "      <th>RMSE</th>\n",
+       "      <th>max abs diff</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>y_mf_n abs</td>\n",
+       "      <td>516</td>\n",
+       "      <td>0.509469</td>\n",
+       "      <td>0.509642</td>\n",
+       "      <td>1.729508e-04</td>\n",
+       "      <td>1.301043e-17</td>\n",
+       "      <td>0.001248</td>\n",
+       "      <td>0.021871</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>y_mf_auto_n abs</td>\n",
+       "      <td>1031</td>\n",
+       "      <td>0.004699</td>\n",
+       "      <td>0.004695</td>\n",
+       "      <td>-3.954363e-06</td>\n",
+       "      <td>-6.732322e-15</td>\n",
+       "      <td>0.000098</td>\n",
+       "      <td>0.000350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>y_pc_n abs</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>0.079082</td>\n",
+       "      <td>0.079071</td>\n",
+       "      <td>-1.070651e-05</td>\n",
+       "      <td>-1.008762e-08</td>\n",
+       "      <td>0.000203</td>\n",
+       "      <td>0.006627</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>p_rx_e_n dB</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>-106.347106</td>\n",
+       "      <td>-106.345857</td>\n",
+       "      <td>1.248776e-03</td>\n",
+       "      <td>-2.469640e-03</td>\n",
+       "      <td>0.387861</td>\n",
+       "      <td>8.330394</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Sp_full_n dB</td>\n",
+       "      <td>2356</td>\n",
+       "      <td>-92.918309</td>\n",
+       "      <td>-92.919339</td>\n",
+       "      <td>-1.029862e-03</td>\n",
+       "      <td>-4.748281e-03</td>\n",
+       "      <td>0.387860</td>\n",
+       "      <td>8.332673</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Sp_target_n dB</td>\n",
+       "      <td>167</td>\n",
+       "      <td>-82.034552</td>\n",
+       "      <td>-82.069809</td>\n",
+       "      <td>-3.525722e-02</td>\n",
+       "      <td>-5.111712e-03</td>\n",
+       "      <td>0.307320</td>\n",
+       "      <td>1.852714</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>y_pc_t_n abs</td>\n",
+       "      <td>168</td>\n",
+       "      <td>0.000436</td>\n",
+       "      <td>0.000436</td>\n",
+       "      <td>-1.777090e-07</td>\n",
+       "      <td>-7.647879e-08</td>\n",
+       "      <td>0.000002</td>\n",
+       "      <td>0.000005</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>y_mf_auto_red_n abs</td>\n",
+       "      <td>168</td>\n",
+       "      <td>0.027249</td>\n",
+       "      <td>0.027238</td>\n",
+       "      <td>-1.024769e-05</td>\n",
+       "      <td>-1.586508e-05</td>\n",
+       "      <td>0.000211</td>\n",
+       "      <td>0.000350</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>Y_pc_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>2.382618e-03</td>\n",
+       "      <td>-2.111098e-03</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>Y_mf_auto_red_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>3.567061</td>\n",
+       "      <td>3.570432</td>\n",
+       "      <td>3.371336e-03</td>\n",
+       "      <td>-1.389353e-03</td>\n",
+       "      <td>0.095777</td>\n",
+       "      <td>0.455695</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>Y_tilde_pc_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-39.017683</td>\n",
+       "      <td>-39.018672</td>\n",
+       "      <td>-9.887186e-04</td>\n",
+       "      <td>-3.215677e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134121</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>P_rx_e_t_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-60.658788</td>\n",
+       "      <td>-60.659777</td>\n",
+       "      <td>-9.887186e-04</td>\n",
+       "      <td>-3.215677e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134121</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>g_theta_phi_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>52.590609</td>\n",
+       "      <td>52.590553</td>\n",
+       "      <td>-5.644019e-05</td>\n",
+       "      <td>-5.325710e-05</td>\n",
+       "      <td>0.000060</td>\n",
+       "      <td>0.000097</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>TS_m dB</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-9.322373e-04</td>\n",
+       "      <td>-2.770378e-04</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134085</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               variable     n  CRIMAC mean  echopype mean     mean diff  \\\n",
+       "0            y_mf_n abs   516     0.509469       0.509642  1.729508e-04   \n",
+       "1       y_mf_auto_n abs  1031     0.004699       0.004695 -3.954363e-06   \n",
+       "2            y_pc_n abs  2356     0.079082       0.079071 -1.070651e-05   \n",
+       "3           p_rx_e_n dB  2356  -106.347106    -106.345857  1.248776e-03   \n",
+       "4          Sp_full_n dB  2356   -92.918309     -92.919339 -1.029862e-03   \n",
+       "5        Sp_target_n dB   167   -82.034552     -82.069809 -3.525722e-02   \n",
+       "6          y_pc_t_n abs   168     0.000436       0.000436 -1.777090e-07   \n",
+       "7   y_mf_auto_red_n abs   168     0.027249       0.027238 -1.024769e-05   \n",
+       "8           Y_pc_t_m dB  1000   -35.450622     -35.448239  2.382618e-03   \n",
+       "9    Y_mf_auto_red_m dB  1000     3.567061       3.570432  3.371336e-03   \n",
+       "10    Y_tilde_pc_t_m dB  1000   -39.017683     -39.018672 -9.887186e-04   \n",
+       "11        P_rx_e_t_m dB  1000   -60.658788     -60.659777 -9.887186e-04   \n",
+       "12     g_theta_phi_m dB  1000    52.590609      52.590553 -5.644019e-05   \n",
+       "13              TS_m dB  1000   -41.615550     -41.616483 -9.322373e-04   \n",
+       "\n",
+       "     median diff      RMSE  max abs diff  \n",
+       "0   1.301043e-17  0.001248      0.021871  \n",
+       "1  -6.732322e-15  0.000098      0.000350  \n",
+       "2  -1.008762e-08  0.000203      0.006627  \n",
+       "3  -2.469640e-03  0.387861      8.330394  \n",
+       "4  -4.748281e-03  0.387860      8.332673  \n",
+       "5  -5.111712e-03  0.307320      1.852714  \n",
+       "6  -7.647879e-08  0.000002      0.000005  \n",
+       "7  -1.586508e-05  0.000211      0.000350  \n",
+       "8  -2.111098e-03  0.288531      5.399668  \n",
+       "9  -1.389353e-03  0.095777      0.455695  \n",
+       "10 -3.215677e-04  0.267273      5.134121  \n",
+       "11 -3.215677e-04  0.267273      5.134121  \n",
+       "12 -5.325710e-05  0.000060      0.000097  \n",
+       "13 -2.770378e-04  0.267273      5.134085  "
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows = []\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_n\"]),\n",
+    "    np.abs(y_mf_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_auto_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_auto_n\"]),\n",
+    "    np.abs(y_mf_auto_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_pc_n abs\",\n",
+    "    np.abs(ref_ts[\"y_pc_n\"]),\n",
+    "    np.abs(y_pc_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"p_rx_e_n dB\",\n",
+    "    db10(ref_ts[\"p_rx_e_n\"]),\n",
+    "    db10(p_rx_e_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Sp_full_n dB\",\n",
+    "    ref_ts[\"Sp_full_n\"],\n",
+    "    Sp_n,\n",
+    "))\n",
+    "\n",
+    "## target-windows\n",
+    "target_mask = (\n",
+    "    (r_n >= ref_ts[\"Sp_target_r\"].min())\n",
+    "    & (r_n <= ref_ts[\"Sp_target_r\"].max())\n",
+    ")\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Sp_target_n dB\",\n",
+    "    ref_ts[\"Sp_target_n\"],\n",
+    "    Sp_n[target_mask],\n",
+    "))\n",
+    "##\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_pc_t_n abs\",\n",
+    "    np.abs(ref_ts[\"y_pc_t_n\"]),\n",
+    "    np.abs(y_pc_t_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"y_mf_auto_red_n abs\",\n",
+    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]),\n",
+    "    np.abs(y_mf_auto_red_n),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    db20(Y_pc_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_mf_auto_red_m dB\",\n",
+    "    db20(ref_ts[\"Y_mf_auto_red_m\"]),\n",
+    "    db20(Y_mf_auto_red_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"Y_tilde_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_tilde_pc_t_m\"]),\n",
+    "    db20(Y_tilde_pc_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"P_rx_e_t_m dB\",\n",
+    "    db10(ref_ts[\"P_rx_e_t_m\"]),\n",
+    "    db10(P_rx_e_t_m),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"g_theta_phi_m dB\",\n",
+    "    10 * np.log10(ref_ts[\"g_theta_phi_m\"] ** 2),\n",
+    "    10 * np.log10(g_theta_phi_m ** 2),\n",
+    "))\n",
+    "\n",
+    "rows.append(compare_summary(\n",
+    "    \"TS_m dB\",\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    TS_m,\n",
+    "))\n",
+    "\n",
+    "summary = pd.DataFrame(rows)\n",
+    "summary"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1f2a53a8",
+   "metadata": {},
+   "source": [
+    "## 18. Public API check: compute_TS_spectrum\n",
+    "\n",
+    "This validates that the public API returns the same TS spectrum product as the manual helper-chain above.\n",
+    "\n",
+    "The workflow is now:\n",
+    "\n",
+    "```text\n",
+    "compute_Sp()\n",
+    "→ simple target detection using Sp + split-beam angles\n",
+    "→ point_locations\n",
+    "→ compute_TS_spectrum(point_locations=...)\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "425572d3",
+   "metadata": {},
+   "source": [
+    "### Reproduce the TS spectrum using the public API\n",
+    "\n",
+    "The previous sections reproduced the CRIMAC processing chain step-by-step using internal helper functions. In practice, users can obtain the same TS-spectrum product directly through the public API."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44510cb1",
+   "metadata": {},
+   "source": [
+    "Before calling `compute_TS_spectrum()`, we first need to provide target locations. Here, we use the public `compute_Sp()` output to detect the strongest target within the expected calibration-sphere range gate for each ping. For each detected target, we store the ping time, channel, target range, split-beam angles, and target-window limits in a table that will be passed to `compute_TS_spectrum()`.\n",
+    "\n",
+    "**This detection step is intentionally simple and is only used here to generate `point_locations` for validating the TS-spectrum API.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "0892fb0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Available Sp channels: ['WBT 747008-15 ES333-7CD_ES' 'WBT 747015-15 ES70-7CD_ES'\n",
+      " 'WBT 747019-15 ES200-7CD_ES' 'WBT 747022-15 ES120-7CD_ES']\n",
+      "Selected channel: WBT 747022-15 ES120-7CD_ES\n",
+      "Number of detected targets: 1265\n"
+     ]
+    }
+   ],
+   "source": [
+    "target_rows = []\n",
+    "\n",
+    "ds_Sp = ep.calibrate.compute_Sp(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    ")\n",
+    "\n",
+    "print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
+    "print(\"Selected channel:\", tsf_channel)\n",
+    "\n",
+    "sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)\n",
+    "\n",
+    "tx_coeff = get_filter_coeff(cal_obj.vend)\n",
+    "fs = cal_obj.cal_params[\"receiver_sampling_frequency\"]\n",
+    "\n",
+    "matched_filter, _ = get_transmit_signal(\n",
+    "    cal_obj.beam,\n",
+    "    tx_coeff,\n",
+    "    cal_obj.waveform_mode,\n",
+    "    fs,\n",
+    "    cal_obj.drop_last_hanning_zero,\n",
+    ")\n",
+    "\n",
+    "pc = _get_pulse_compressed_signal(\n",
+    "    beam=cal_obj.beam,\n",
+    "    matched_filter=matched_filter,\n",
+    ")\n",
+    "\n",
+    "pc_ch = pc.sel(channel=tsf_channel)\n",
+    "range_ch = cal_obj.range_meter.sel(channel=tsf_channel)\n",
+    "\n",
+    "for ping_idx in range(sp_ch.sizes[\"ping_time\"]):\n",
+    "    pc_ping_i = pc_ch.isel(ping_time=ping_idx)\n",
+    "    sp_i = sp_ch.isel(ping_time=ping_idx)\n",
+    "    r_i = range_ch.isel(ping_time=ping_idx)\n",
+    "\n",
+    "    valid = np.isfinite(sp_i) & np.isfinite(r_i)\n",
+    "\n",
+    "    if not bool(valid.any()):\n",
+    "        continue\n",
+    "\n",
+    "    pc_ping_i = pc_ping_i.where(valid, drop=True)\n",
+    "    sp_i = sp_i.where(valid, drop=True).values\n",
+    "    r_i = r_i.where(valid, drop=True).values\n",
+    "\n",
+    "    gamma_theta_i = scalar_param(\n",
+    "        cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
+    "        tsf_channel,\n",
+    "        ping_idx,\n",
+    "    )\n",
+    "\n",
+    "    gamma_phi_i = scalar_param(\n",
+    "        cal_obj.cal_params[\"angle_sensitivity_athwartship\"],\n",
+    "        tsf_channel,\n",
+    "        ping_idx,\n",
+    "    )\n",
+    "\n",
+    "    theta_i, phi_i = _get_splitbeam_angles(\n",
+    "        pc=pc_ping_i,\n",
+    "        gamma_alongship=gamma_theta_i,\n",
+    "        gamma_athwartship=gamma_phi_i,\n",
+    "    )\n",
+    "\n",
+    "    theta_i = theta_i.values\n",
+    "    phi_i = phi_i.values\n",
+    "\n",
+    "    sp_lin_i = 10 ** (sp_i / 10)\n",
+    "\n",
+    "    try:\n",
+    "        (\n",
+    "            r_t_i,\n",
+    "            theta_t_i,\n",
+    "            phi_t_i,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            dum_r_i,\n",
+    "        ) = extract_single_target(\n",
+    "            pc_avg=sp_lin_i,\n",
+    "            power=sp_lin_i,\n",
+    "            theta=theta_i,\n",
+    "            phi=phi_i,\n",
+    "            range_meter=r_i,\n",
+    "            r0=5.3,\n",
+    "            r1=6.3,\n",
+    "            before=0.5,\n",
+    "            after=1.0,\n",
+    "        )\n",
+    "    except ValueError:\n",
+    "        continue\n",
+    "\n",
+    "    target_rows.append(\n",
+    "        {\n",
+    "            \"raw_ping_index\": ping_idx,\n",
+    "            \"ping_time\": ds_Sp[\"ping_time\"].isel(ping_time=ping_idx).values,\n",
+    "            \"channel\": tsf_channel,\n",
+    "            \"target_id\": len(target_rows),\n",
+    "            \"target_range\": r_t_i,\n",
+    "            \"angle_alongship\": theta_t_i,\n",
+    "            \"angle_athwartship\": phi_t_i,\n",
+    "            \"target_range_min\": dum_r_i.min(),\n",
+    "            \"target_range_max\": dum_r_i.max(),\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "print(\"Number of detected targets:\", len(target_rows))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "dca2a887",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "</symbol>\n",
+       "<symbol id=\"icon-file-text2\" viewBox=\"0 0 32 32\">\n",
+       "<path d=\"M28.681 7.159c-0.694-0.947-1.662-2.053-2.724-3.116s-2.169-2.030-3.116-2.724c-1.612-1.182-2.393-1.319-2.841-1.319h-15.5c-1.378 0-2.5 1.121-2.5 2.5v27c0 1.378 1.122 2.5 2.5 2.5h23c1.378 0 2.5-1.122 2.5-2.5v-19.5c0-0.448-0.137-1.23-1.319-2.841zM24.543 5.457c0.959 0.959 1.712 1.825 2.268 2.543h-4.811v-4.811c0.718 0.556 1.584 1.309 2.543 2.268zM28 29.5c0 0.271-0.229 0.5-0.5 0.5h-23c-0.271 0-0.5-0.229-0.5-0.5v-27c0-0.271 0.229-0.5 0.5-0.5 0 0 15.499-0 15.5 0v7c0 0.552 0.448 1 1 1h7v19.5z\"></path>\n",
+       "<path d=\"M23 26h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 22h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "<path d=\"M23 18h-14c-0.552 0-1-0.448-1-1s0.448-1 1-1h14c0.552 0 1 0.448 1 1s-0.448 1-1 1z\"></path>\n",
+       "</symbol>\n",
+       "</defs>\n",
+       "</svg>\n",
+       "<style>/* CSS stylesheet for displaying xarray objects in notebooks */\n",
+       "\n",
+       ":root {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base rgba(0, 0, 0, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(0, 0, 0, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, white)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       "html[theme=\"dark\"],\n",
+       "html[data-theme=\"dark\"],\n",
+       "body[data-theme=\"dark\"],\n",
+       "body.vscode-dark {\n",
+       "  --xr-font-color0: var(\n",
+       "    --jp-content-font-color0,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
+       "  );\n",
+       "  --xr-font-color2: var(\n",
+       "    --jp-content-font-color2,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
+       "  );\n",
+       "  --xr-font-color3: var(\n",
+       "    --jp-content-font-color3,\n",
+       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
+       "  );\n",
+       "  --xr-border-color: var(\n",
+       "    --jp-border-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
+       "  );\n",
+       "  --xr-disabled-color: var(\n",
+       "    --jp-layout-color3,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
+       "  );\n",
+       "  --xr-background-color: var(\n",
+       "    --jp-layout-color0,\n",
+       "    var(--pst-color-on-background, #111111)\n",
+       "  );\n",
+       "  --xr-background-color-row-even: var(\n",
+       "    --jp-layout-color1,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
+       "  );\n",
+       "  --xr-background-color-row-odd: var(\n",
+       "    --jp-layout-color2,\n",
+       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
+       "  );\n",
+       "}\n",
+       "\n",
+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "  line-height: 1.6;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "  margin-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-obj-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-group-box-contents > label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
+       "  margin-block-start: 0;\n",
+       "  margin-block-end: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input,\n",
+       ".xr-group-box-contents > input,\n",
+       ".xr-array-wrap > input {\n",
+       "  display: block;\n",
+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 287MB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) object 32B &#x27;WBT 747008-15 ES333-...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * filenames                      (filenames) int64 8B 0\n",
+       "Data variables: (12/24)\n",
+       "    Sp                             (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    echo_range                     (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sound_speed                    float64 8B 1.485e+03\n",
+       "    sound_absorption               (channel, ping_time) float64 41kB 0.07527 ...\n",
+       "    temperature                    float64 8B 9.7\n",
+       "    ...                             ...\n",
+       "    beamwidth_athwartship          (channel, ping_time) float64 41kB 7.132 .....\n",
+       "    impedance_transducer           (channel, ping_time) float64 41kB 75.0 ......\n",
+       "    impedance_transceiver          (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency    (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    source_filenames               (filenames) &lt;U67 268B &#x27;example_data\\\\ts_sp...\n",
+       "    water_level                    float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:47:33+00:00\n",
+       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3731763d-763f-461d-96c4-87adc65d0cb9' class='xr-var-data-in' type='checkbox'><label for='data-3731763d-763f-461d-96c4-87adc65d0cb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-280f09b5-483a-4d86-a233-4785c8ede359' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-280f09b5-483a-4d86-a233-4785c8ede359' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' class='xr-var-data-in' type='checkbox'><label for='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-981ab7ea-6eb3-4197-9648-983774613b29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-981ab7ea-6eb3-4197-9648-983774613b29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' class='xr-var-data-in' type='checkbox'><label for='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e7781c-0ac2-443d-8526-ad096a24013f' class='xr-var-data-in' type='checkbox'><label for='data-92e7781c-0ac2-443d-8526-ad096a24013f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary-in' type='checkbox' /><label for='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-018451ee-8460-42d8-8d7c-9d497d423674' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-018451ee-8460-42d8-8d7c-9d497d423674' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' class='xr-var-data-in' type='checkbox'><label for='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
+       "         -195.57397259, -218.79009715, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -198.89271647, -222.29194801, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -203.05173598, -226.23191104, -150.30546618],\n",
+       "        ...,\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -206.32631432, -229.36708419, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -199.86920994, -223.97459584, -150.30546618],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "         -201.28247937, -225.21174509, -150.30546618]],\n",
+       "\n",
+       "       [[          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "...\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan]],\n",
+       "\n",
+       "       [[          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        ...,\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan],\n",
+       "        [          nan,           nan,           nan, ...,\n",
+       "                   nan,           nan,           nan]]],\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-456fdd8d-b511-4497-8303-8b75f943ef99' class='xr-var-data-in' type='checkbox'><label for='data-456fdd8d-b511-4497-8303-8b75f943ef99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        ...,\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
+       "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01]],\n",
+       "\n",
+       "       [[0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 1.58442419e-02, 3.16884838e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "...\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan]],\n",
+       "\n",
+       "       [[0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        ...,\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [0.00000000e+00, 5.94160000e-03, 1.18832000e-02, ...,\n",
+       "                    nan,            nan,            nan],\n",
+       "        [           nan,            nan,            nan, ...,\n",
+       "                    nan,            nan,            nan]]],\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' class='xr-var-data-in' type='checkbox'><label for='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1a770251-9a45-4569-8238-961d39f876b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a770251-9a45-4569-8238-961d39f876b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' class='xr-var-data-in' type='checkbox'><label for='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' class='xr-var-data-in' type='checkbox'><label for='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
+       "        0.07527219],\n",
+       "       [0.02167407, 0.02167407, 0.02167407, ..., 0.02167407, 0.02167407,\n",
+       "        0.02167407],\n",
+       "       [0.05300738, 0.05300738, 0.05300738, ..., 0.05300738, 0.05300738,\n",
+       "        0.05300738],\n",
+       "       [0.03770373, 0.03770373, 0.03770373, ..., 0.03770373, 0.03770373,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a01fc152-7dce-4732-844a-d61d5a251940' class='xr-var-data-in' type='checkbox'><label for='data-a01fc152-7dce-4732-844a-d61d5a251940' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c05f67-fa2e-4478-a990-acebee4abc19' class='xr-var-data-in' type='checkbox'><label for='data-69c05f67-fa2e-4478-a990-acebee4abc19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' class='xr-var-data-in' type='checkbox'><label for='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-64b02427-8003-4612-8656-5ee97caf5b05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64b02427-8003-4612-8656-5ee97caf5b05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8029b272-0f32-45a2-b880-73e92bea66f1' class='xr-var-data-in' type='checkbox'><label for='data-8029b272-0f32-45a2-b880-73e92bea66f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' class='xr-var-data-in' type='checkbox'><label for='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' class='xr-var-data-in' type='checkbox'><label for='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       ...,\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0.,  0.],\n",
+       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' class='xr-var-data-in' type='checkbox'><label for='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
+       "        25.517003  , 25.517003  ],\n",
+       "       [27.40875   , 27.40875   , 27.40875   , ..., 27.40875   ,\n",
+       "        27.40875   , 27.40875   ],\n",
+       "       [28.04229062, 28.04229062, 28.04229062, ..., 28.04229062,\n",
+       "        28.04229062, 28.04229062],\n",
+       "       [28.0375    , 28.0375    , 28.0375    , ..., 28.0375    ,\n",
+       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' class='xr-var-data-in' type='checkbox'><label for='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
+       "        -20.62139413, -20.62139413],\n",
+       "       [-20.7       , -20.7       , -20.7       , ..., -20.7       ,\n",
+       "        -20.7       , -20.7       ],\n",
+       "       [-21.32816929, -21.32816929, -21.32816929, ..., -21.32816929,\n",
+       "        -21.32816929, -21.32816929],\n",
+       "       [-21.39524213, -21.39524213, -21.39524213, ..., -21.39524213,\n",
+       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9150a043-05ca-4e7d-876d-58e42233143c' class='xr-var-data-in' type='checkbox'><label for='data-9150a043-05ca-4e7d-876d-58e42233143c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
+       "        -0.040999  , -0.040999  ],\n",
+       "       [-0.2209375 , -0.2209375 , -0.2209375 , ..., -0.2209375 ,\n",
+       "        -0.2209375 , -0.2209375 ],\n",
+       "       [-0.00590313, -0.00590313, -0.00590313, ..., -0.00590313,\n",
+       "        -0.00590313, -0.00590313],\n",
+       "       [-0.0575    , -0.0575    , -0.0575    , ..., -0.0575    ,\n",
+       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37392d71-2357-42b4-b2eb-5724357c5a9e' class='xr-var-data-in' type='checkbox'><label for='data-37392d71-2357-42b4-b2eb-5724357c5a9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
+       "         0.0195005 ,  0.0195005 ],\n",
+       "       [-0.124375  , -0.124375  , -0.124375  , ..., -0.124375  ,\n",
+       "        -0.124375  , -0.124375  ],\n",
+       "       [-0.08590313, -0.08590313, -0.08590313, ..., -0.08590313,\n",
+       "        -0.08590313, -0.08590313],\n",
+       "       [ 0.0175    ,  0.0175    ,  0.0175    , ...,  0.0175    ,\n",
+       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' class='xr-var-data-in' type='checkbox'><label for='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        22.79279279, 22.79279279],\n",
+       "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
+       "        23.        , 23.        ],\n",
+       "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
+       "        24.725     , 24.725     ],\n",
+       "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' class='xr-var-data-in' type='checkbox'><label for='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        22.79279279, 22.79279279],\n",
+       "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
+       "        23.        , 23.        ],\n",
+       "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
+       "        24.725     , 24.725     ],\n",
+       "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-7572befa-850c-4a01-98ff-ee37b0200703' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7572befa-850c-4a01-98ff-ee37b0200703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39de6332-e1e6-4de3-aac4-4d44bd630972' class='xr-var-data-in' type='checkbox'><label for='data-39de6332-e1e6-4de3-aac4-4d44bd630972' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
+       "        6.9434965 ],\n",
+       "       [6.9290625 , 6.9290625 , 6.9290625 , ..., 6.9290625 , 6.9290625 ,\n",
+       "        6.9290625 ],\n",
+       "       [6.25361251, 6.25361251, 6.25361251, ..., 6.25361251, 6.25361251,\n",
+       "        6.25361251],\n",
+       "       [6.17      , 6.17      , 6.17      , ..., 6.17      , 6.17      ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' class='xr-var-data-in' type='checkbox'><label for='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
+       "        7.131998  ],\n",
+       "       [6.7325    , 6.7325    , 6.7325    , ..., 6.7325    , 6.7325    ,\n",
+       "        6.7325    ],\n",
+       "       [6.24638749, 6.24638749, 6.24638749, ..., 6.24638749, 6.24638749,\n",
+       "        6.24638749],\n",
+       "       [6.2775    , 6.2775    , 6.2775    , ..., 6.2775    , 6.2775    ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd05efd-6d51-4042-a667-50e4da4f1057' class='xr-var-data-in' type='checkbox'><label for='data-6dd05efd-6d51-4042-a667-50e4da4f1057' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., 75.],\n",
+       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' class='xr-var-data-in' type='checkbox'><label for='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-605050ed-2f39-4f72-90e0-bded240d8f40' class='xr-var-data-in' type='checkbox'><label for='data-605050ed-2f39-4f72-90e0-bded240d8f40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' class='xr-var-data-in' type='checkbox'><label for='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-371ca08f-2b03-4441-a911-637e2015f167' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-371ca08f-2b03-4441-a911-637e2015f167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' class='xr-var-data-in' type='checkbox'><label for='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:47:33+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 287MB\n",
+       "Dimensions:                        (channel: 4, ping_time: 1266,\n",
+       "                                    range_sample: 3534, filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel                        (channel) object 32B 'WBT 747008-15 ES333-...\n",
+       "  * ping_time                      (ping_time) datetime64[ns] 10kB 2021-12-15...\n",
+       "  * range_sample                   (range_sample) int64 28kB 0 1 2 ... 3532 3533\n",
+       "  * filenames                      (filenames) int64 8B 0\n",
+       "Data variables: (12/24)\n",
+       "    Sp                             (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    echo_range                     (channel, ping_time, range_sample) float64 143MB ...\n",
+       "    frequency_nominal              (channel) float64 32B 3.33e+05 ... 1.2e+05\n",
+       "    sound_speed                    float64 8B 1.485e+03\n",
+       "    sound_absorption               (channel, ping_time) float64 41kB 0.07527 ...\n",
+       "    temperature                    float64 8B 9.7\n",
+       "    ...                             ...\n",
+       "    beamwidth_athwartship          (channel, ping_time) float64 41kB 7.132 .....\n",
+       "    impedance_transducer           (channel, ping_time) float64 41kB 75.0 ......\n",
+       "    impedance_transceiver          (channel) int64 32B 5400 5400 5400 5400\n",
+       "    receiver_sampling_frequency    (channel) float64 32B 1.5e+06 ... 1.5e+06\n",
+       "    source_filenames               (filenames) <U67 268B 'example_data\\\\ts_sp...\n",
+       "    water_level                    float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:47:33+00:00\n",
+       "    processing_function:          calibrate.compute_Sp"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_Sp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "e14b4f11",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
+    "# print(\"Selected channel:\", tsf_channel)\n",
+    "\n",
+    "# sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "052738a8",
+   "metadata": {},
+   "source": [
+    "### Create the `point_locations` dataset for `compute_TS_spectrum()`\n",
+    "\n",
+    "The public `compute_TS_spectrum()` API expects target locations as an input dataset. Here, we create this dataset for the detected calibration sphere target, including its ping time, channel, range, split-beam angles, and target-window limits."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "id": "fbc2ca91",
+   "metadata": {},
+   "outputs": [
+    {
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+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 213kB\n",
+       "Dimensions:            (target_id: 1265)\n",
+       "Coordinates:\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel            (target_id) &lt;U26 132kB &#x27;WBT 747022-15 ES120-7CD_ES&#x27; .....\n",
+       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "Data variables:\n",
+       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
+       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
+       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
+       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dca6b996-4390-4001-80b4-a0aa1cbee602' class='xr-var-data-in' type='checkbox'><label for='data-dca6b996-4390-4001-80b4-a0aa1cbee602' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' class='xr-var-data-in' type='checkbox'><label for='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, ..., &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
+       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e50353f7-bf0b-48a5-9363-6efa241d9125' class='xr-var-data-in' type='checkbox'><label for='data-e50353f7-bf0b-48a5-9363-6efa241d9125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "       &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "       &#x27;2021-12-15T14:40:09.162188000&#x27;],\n",
+       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3898eabb-6795-4afa-8c90-343dde130a87' class='xr-var-data-in' type='checkbox'><label for='data-3898eabb-6795-4afa-8c90-343dde130a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' class='xr-var-data-in' type='checkbox'><label for='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "       -0.00917041,  0.15295288], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' class='xr-var-data-in' type='checkbox'><label for='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "       -0.02377829, -0.15330624], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-500c66bf-999c-43bd-bae8-15116604cea4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-500c66bf-999c-43bd-bae8-15116604cea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' class='xr-var-data-in' type='checkbox'><label for='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
+       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' class='xr-var-data-in' type='checkbox'><label for='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
+       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' class='xr-var-data-in' type='checkbox'><label for='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 213kB\n",
+       "Dimensions:            (target_id: 1265)\n",
+       "Coordinates:\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel            (target_id) <U26 132kB 'WBT 747022-15 ES120-7CD_ES' .....\n",
+       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "Data variables:\n",
+       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
+       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
+       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
+       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264"
+      ]
+     },
+     "execution_count": 54,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "point_locations = xr.Dataset(\n",
+    "    {\n",
+    "        \"target_range\": (\"target_id\", [row[\"target_range\"] for row in target_rows]),\n",
+    "        \"angle_alongship\": (\"target_id\", [row[\"angle_alongship\"] for row in target_rows]),\n",
+    "        \"angle_athwartship\": (\"target_id\", [row[\"angle_athwartship\"] for row in target_rows]),\n",
+    "        \"target_range_min\": (\"target_id\", [row[\"target_range_min\"] for row in target_rows]),\n",
+    "        \"target_range_max\": (\"target_id\", [row[\"target_range_max\"] for row in target_rows]),\n",
+    "        \"raw_ping_index\": (\"target_id\", [row[\"raw_ping_index\"] for row in target_rows]),\n",
+    "    },\n",
+    "    coords={\n",
+    "        \"target_id\": np.arange(len(target_rows)),\n",
+    "        \"channel\": (\"target_id\", [row[\"channel\"] for row in target_rows]),\n",
+    "        \"ping_time\": (\"target_id\", [row[\"ping_time\"] for row in target_rows]),\n",
+    "    },\n",
+    ")\n",
+    "\n",
+    "point_locations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "id": "e0ca3c72",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "API target position: 509\n",
+      "Raw ping index: 509\n"
+     ]
+    }
+   ],
+   "source": [
+    "api_target_pos = int(\n",
+    "    np.where(point_locations[\"raw_ping_index\"].values == tsf_ping_index)[0][0]\n",
+    ")\n",
+    "\n",
+    "print(\"API target position:\", api_target_pos)\n",
+    "print(\"Raw ping index:\", point_locations[\"raw_ping_index\"].isel(target_id=api_target_pos).values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4dae12f7",
+   "metadata": {},
+   "source": [
+    "Before comparing TS spectra, we verify that the frequency grid produced by the API matches the CRIMAC reference grid."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "faf6fdb5",
+   "metadata": {},
+   "source": [
+    "#### API validation using frequency_resolution\n",
+    "\n",
+    "Here we call `compute_TS_spectrum()` using the same frequency spacing as the CRIMAC reference output. In this mode, the function infers the FFT size internally from the requested frequency resolution."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
+   "id": "0e515b3a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CRIMAC frequency resolution: 80.08008008007891\n"
+     ]
+    }
+   ],
+   "source": [
+    "frequency_resolution = float(np.nanmedian(np.diff(ref_ts[\"f_m\"])))\n",
+    "print(\"CRIMAC frequency resolution:\", frequency_resolution)\n",
+    "\n",
+    "frequency_expected = (\n",
+    "    ref_ts[\"f_m\"][0]\n",
+    "    + np.arange(ref_ts[\"f_m\"].size) * frequency_resolution\n",
+    ")\n",
+    "\n",
+    "assert np.allclose(frequency_expected, ref_ts[\"f_m\"])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "30a2ffdd",
+   "metadata": {},
+   "source": [
+    "We now call the public `compute_TS_spectrum()` API using the detected `point_locations` and the same frequency resolution as the CRIMAC reference grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "id": "35823982",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "288c8f6e570547068b2e610390ce249e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       ".xr-var-item > input + label {\n",
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+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
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+       ".xr-array-wrap > input:enabled + label,\n",
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+       "\n",
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+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) &lt;U26 104B &#x27;WBT 747022-15 ES120-7CD_ES&#x27;\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:22+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f03af67-de55-4761-a728-7e98edc188e0' class='xr-var-data-in' type='checkbox'><label for='data-9f03af67-de55-4761-a728-7e98edc188e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abc85376-36c7-4428-a97e-75ea82185e8d' class='xr-var-data-in' type='checkbox'><label for='data-abc85376-36c7-4428-a97e-75ea82185e8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' class='xr-var-data-in' type='checkbox'><label for='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-777af835-7f85-4f6d-a59c-7503467effd3' class='xr-var-data-in' type='checkbox'><label for='data-777af835-7f85-4f6d-a59c-7503467effd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' class='xr-var-data-in' type='checkbox'><label for='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "         -50.89344838, -51.56443826],\n",
+       "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
+       "         -53.05996696, -53.87369709],\n",
+       "        [-44.99852747, -45.01598528, -45.15371319, ..., -49.13378461,\n",
+       "         -49.03861423, -49.611581  ],\n",
+       "        ...,\n",
+       "        [-44.48077623, -44.55109807, -44.38414421, ..., -41.62880734,\n",
+       "         -41.47933602, -41.45510495],\n",
+       "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
+       "         -41.36476302, -41.37227431],\n",
+       "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' class='xr-var-data-in' type='checkbox'><label for='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' class='xr-var-data-in' type='checkbox'><label for='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' class='xr-var-data-in' type='checkbox'><label for='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-126281c8-9e4d-4ea5-b809-8ad391850196' class='xr-var-data-in' type='checkbox'><label for='data-126281c8-9e4d-4ea5-b809-8ad391850196' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' class='xr-var-data-in' type='checkbox'><label for='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b9240d-e7f5-49fd-b322-0bade58745c1' class='xr-var-data-in' type='checkbox'><label for='data-11b9240d-e7f5-49fd-b322-0bade58745c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:22+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) <U67 268B 'example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:22+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum"
+      ]
+     },
+     "execution_count": 57,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_TS_spectrum_fr = ep.calibrate.compute_TS_spectrum(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    "    point_locations=point_locations,\n",
+    "    frequency_resolution=frequency_resolution,\n",
+    ")\n",
+    "\n",
+    "ds_TS_spectrum_fr"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "df591d08",
+   "metadata": {},
+   "source": [
+    "We extract the TS spectrum corresponding to the CRIMAC reference target and compare it directly with the exported CRIMAC spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 58,
+   "id": "56d8ea09",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "API frequency points: 1000\n",
+      "CRIMAC frequency points: 1000\n",
+      "Frequency grids match: True\n",
+      "RMSE (dB): 0.016260102031311115\n",
+      "Max abs diff (dB): 0.07143718847996894\n"
+     ]
+    }
+   ],
+   "source": [
+    "ts_api_fr = (\n",
+    "    ds_TS_spectrum_fr[\"TS_spectrum\"]\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(target_id=api_target_pos)\n",
+    ")\n",
+    "\n",
+    "diff_fr = ts_api_fr.values - ref_ts[\"TS_m\"]\n",
+    "\n",
+    "print(\"API frequency points:\", ds_TS_spectrum_fr[\"frequency\"].size)\n",
+    "print(\"CRIMAC frequency points:\", ref_ts[\"f_m\"].size)\n",
+    "\n",
+    "print(\n",
+    "    \"Frequency grids match:\",\n",
+    "    np.allclose(ds_TS_spectrum_fr[\"frequency\"].values, ref_ts[\"f_m\"])\n",
+    ")\n",
+    "\n",
+    "print(\"RMSE (dB):\", np.sqrt(np.nanmean(diff_fr**2)))\n",
+    "print(\"Max abs diff (dB):\", np.nanmax(np.abs(diff_fr)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 59,
+   "id": "c980db68",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert np.allclose(\n",
+    "    ds_TS_spectrum_fr[\"frequency\"].values,\n",
+    "    ref_ts[\"f_m\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "83ee6444",
+   "metadata": {},
+   "source": [
+    "### Run the public API using an explicit FFT length (NFFT)\n",
+    "\n",
+    "In the previous example, the frequency grid was specified through a target frequency resolution. Alternatively, `compute_TS_spectrum()` can be called with an explicit FFT length (`NFFT`), allowing direct control over the frequency discretisation used in the TS-spectrum calculation.\n",
+    "\n",
+    "Both approaches should produce equivalent results when they generate the same frequency grid."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
+   "id": "c96bb8ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5dec63c8df834dd788fb135d4ee90429",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
+      ]
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+       "  opacity: 0;\n",
+       "  height: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input + label,\n",
+       ".xr-var-item > input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label,\n",
+       ".xr-var-item > input:enabled + label,\n",
+       ".xr-array-wrap > input:enabled + label,\n",
+       ".xr-group-box-contents > input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:focus-visible + label,\n",
+       ".xr-var-item > input:focus-visible + label,\n",
+       ".xr-array-wrap > input:focus-visible + label,\n",
+       ".xr-group-box-contents > input:focus-visible + label {\n",
+       "  outline: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item > input:enabled + label:hover,\n",
+       ".xr-var-item > input:enabled + label:hover,\n",
+       ".xr-array-wrap > input:enabled + label:hover,\n",
+       ".xr-group-box-contents > input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "  white-space: nowrap;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > em {\n",
+       "  font-weight: normal;\n",
+       "}\n",
+       "\n",
+       ".xr-span-grid {\n",
+       "  grid-column-end: -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.6em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: \"►\";\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: \"▼\";\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details,\n",
+       ".xr-group-box-contents > label {\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-top: 4px;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in ~ .xr-section-details {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-children {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 100%;\n",
+       "  grid-column: 1 / -1;\n",
+       "  padding-top: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box {\n",
+       "  display: inline-grid;\n",
+       "  grid-template-columns: 0px 30px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-vline {\n",
+       "  grid-column-start: 1;\n",
+       "  border-right: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "  width: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-hline {\n",
+       "  grid-column-start: 2;\n",
+       "  grid-row-start: 1;\n",
+       "  height: 1em;\n",
+       "  width: 26px;\n",
+       "  border-bottom: 0.2em solid;\n",
+       "  border-color: var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents {\n",
+       "  grid-column-start: 3;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > label::before {\n",
+       "  content: \"📂\";\n",
+       "  padding-right: 0.3em;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) &lt;U26 104B &#x27;WBT 747022-15 ES120-7CD_ES&#x27;\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:48+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' class='xr-var-data-in' type='checkbox'><label for='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35821d9-abab-470a-bc4a-6881a65bef48' class='xr-var-data-in' type='checkbox'><label for='data-b35821d9-abab-470a-bc4a-6881a65bef48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eadbf93b-afaf-40b5-9c16-331c32443d75' class='xr-var-data-in' type='checkbox'><label for='data-eadbf93b-afaf-40b5-9c16-331c32443d75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' class='xr-var-data-in' type='checkbox'><label for='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary-in' type='checkbox' checked /><label for='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8711bf66-67a5-4745-bb6f-867c71524ea1' class='xr-var-data-in' type='checkbox'><label for='data-8711bf66-67a5-4745-bb6f-867c71524ea1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "         -50.89344838, -51.56443826],\n",
+       "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
+       "         -53.05996696, -53.87369709],\n",
+       "        [-44.99852747, -45.01598528, -45.15371319, ..., -49.13378461,\n",
+       "         -49.03861423, -49.611581  ],\n",
+       "        ...,\n",
+       "        [-44.48077623, -44.55109807, -44.38414421, ..., -41.62880734,\n",
+       "         -41.47933602, -41.45510495],\n",
+       "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
+       "         -41.36476302, -41.37227431],\n",
+       "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-283521b8-22a3-4b25-b915-d45c0f602f6b' class='xr-var-data-in' type='checkbox'><label for='data-283521b8-22a3-4b25-b915-d45c0f602f6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-59ab1373-b1f1-43a9-a061-daca06355610' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59ab1373-b1f1-43a9-a061-daca06355610' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a425cfce-1395-4517-90e0-8b174b77b1c5' class='xr-var-data-in' type='checkbox'><label for='data-a425cfce-1395-4517-90e0-8b174b77b1c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-123eed60-f204-4adf-864f-e653cbcc3112' class='xr-var-data-in' type='checkbox'><label for='data-123eed60-f204-4adf-864f-e653cbcc3112' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8b5f57-193a-4307-8042-b7c150f6f916' class='xr-var-data-in' type='checkbox'><label for='data-2f8b5f57-193a-4307-8042-b7c150f6f916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
+       "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
+       "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de982c12-715b-4453-835a-32c729905ed9' class='xr-var-data-in' type='checkbox'><label for='data-de982c12-715b-4453-835a-32c729905ed9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' class='xr-var-data-in' type='checkbox'><label for='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:48+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 10MB\n",
+       "Dimensions:            (channel: 1, target_id: 1265, frequency: 1000,\n",
+       "                        filenames: 1)\n",
+       "Coordinates:\n",
+       "  * channel            (channel) <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "  * frequency          (frequency) float64 8kB 9e+04 9.008e+04 ... 1.7e+05\n",
+       "  * filenames          (filenames) int64 8B 0\n",
+       "Data variables:\n",
+       "    TS_spectrum        (channel, target_id, frequency) float64 10MB -44.54 .....\n",
+       "    target_range       (channel, target_id) float64 10kB 5.805 5.805 ... 5.781\n",
+       "    angle_alongship    (channel, target_id) float64 10kB 1.852 2.139 ... 0.153\n",
+       "    angle_athwartship  (channel, target_id) float64 10kB 4.524 4.304 ... -0.1533\n",
+       "    ping_time          (channel, target_id) datetime64[ns] 10kB 2021-12-15T14...\n",
+       "    source_filenames   (filenames) <U67 268B 'example_data\\\\ts_spectrum_examp...\n",
+       "    water_level        float64 8B 0.0\n",
+       "Attributes:\n",
+       "    processing_software_name:     echopype\n",
+       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
+       "    processing_time:              2026-06-07T01:48:48+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "n_f_points = f_crimac.size\n",
+    "NFFT = int(2 ** np.ceil(np.log2(n_f_points)))\n",
+    "\n",
+    "ds_TS_spectrum_nfft = ep.calibrate.compute_TS_spectrum(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"BB\",\n",
+    "    encode_mode=\"complex\",\n",
+    "    point_locations=point_locations,\n",
+    "    NFFT=NFFT,\n",
+    "    n_f_points=n_f_points,\n",
+    "    split_front=0.25,\n",
+    "    window=None,\n",
+    ")\n",
+    "\n",
+    "ds_TS_spectrum_nfft"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "99bff1bb",
+   "metadata": {},
+   "source": [
+    "We extract the TS spectrum produced with the explicit `NFFT` setting, verify that it is defined on the same frequency grid as the CRIMAC reference, and compute the RMSE and maximum absolute difference between the two spectra."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 61,
+   "id": "19c69452",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "NFFT: 1024\n",
+      "API frequency points: 1000\n",
+      "CRIMAC frequency points: 1000\n",
+      "Frequency grids match: True\n",
+      "RMSE (dB): 0.016260102031311115\n",
+      "Max abs diff (dB): 0.07143718847996894\n"
+     ]
+    }
+   ],
+   "source": [
+    "ts_api_nfft = (\n",
+    "    ds_TS_spectrum_nfft[\"TS_spectrum\"]\n",
+    "    .sel(channel=tsf_channel)\n",
+    "    .isel(target_id=api_target_pos)\n",
+    ")\n",
+    "\n",
+    "f_api_nfft = ds_TS_spectrum_nfft[\"frequency\"].values\n",
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "\n",
+    "print(\"NFFT:\", NFFT)\n",
+    "print(\"API frequency points:\", f_api_nfft.size)\n",
+    "print(\"CRIMAC frequency points:\", f_crimac.size)\n",
+    "print(\"Frequency grids match:\", np.allclose(f_api_nfft, f_crimac))\n",
+    "\n",
+    "diff_nfft = ts_api_nfft.values - ref_ts[\"TS_m\"]\n",
+    "\n",
+    "print(\"RMSE (dB):\", np.sqrt(np.nanmean(diff_nfft**2)))\n",
+    "print(\"Max abs diff (dB):\", np.nanmax(np.abs(diff_nfft)))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f279a418",
+   "metadata": {},
+   "source": [
+    "The NFFT and frequency_resolution interfaces produce identical TS-spectrum results for this dataset, demonstrating that both parameterisations are equivalent when they define the same frequency grid."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1572b77b",
+   "metadata": {},
+   "source": [
+    "### Summarise CRIMAC, manual, and API differences\n",
+    "\n",
+    "We summarise pairwise differences between the CRIMAC reference output, the manual helper-chain reconstruction, and the public API output. This checks whether the public API reproduces the same final TS-spectrum product as both the CRIMAC reference and the step-by-step validation workflow."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 62,
+   "id": "5016286d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>variable</th>\n",
+       "      <th>n</th>\n",
+       "      <th>CRIMAC mean</th>\n",
+       "      <th>echopype mean</th>\n",
+       "      <th>mean diff</th>\n",
+       "      <th>median diff</th>\n",
+       "      <th>RMSE</th>\n",
+       "      <th>max abs diff</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>TS_m dB: CRIMAC vs manual</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-0.000932</td>\n",
+       "      <td>-0.000277</td>\n",
+       "      <td>0.267273</td>\n",
+       "      <td>5.134085</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>TS_m dB: CRIMAC vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.615550</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-0.002203</td>\n",
+       "      <td>-0.000048</td>\n",
+       "      <td>0.016260</td>\n",
+       "      <td>0.071437</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>TS_m dB: manual vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-41.616483</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-0.001271</td>\n",
+       "      <td>0.000360</td>\n",
+       "      <td>0.265814</td>\n",
+       "      <td>5.135526</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>Y_pc_t_m dB: CRIMAC vs manual</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.002383</td>\n",
+       "      <td>-0.002111</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Y_pc_t_m dB: CRIMAC vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.450622</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.002383</td>\n",
+       "      <td>-0.002111</td>\n",
+       "      <td>0.288531</td>\n",
+       "      <td>5.399668</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>Y_pc_t_m dB: manual vs API</td>\n",
+       "      <td>1000</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>-35.448239</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                        variable     n  CRIMAC mean  echopype mean  mean diff  \\\n",
+       "0      TS_m dB: CRIMAC vs manual  1000   -41.615550     -41.616483  -0.000932   \n",
+       "1         TS_m dB: CRIMAC vs API  1000   -41.615550     -41.617754  -0.002203   \n",
+       "2         TS_m dB: manual vs API  1000   -41.616483     -41.617754  -0.001271   \n",
+       "3  Y_pc_t_m dB: CRIMAC vs manual  1000   -35.450622     -35.448239   0.002383   \n",
+       "4     Y_pc_t_m dB: CRIMAC vs API  1000   -35.450622     -35.448239   0.002383   \n",
+       "5     Y_pc_t_m dB: manual vs API  1000   -35.448239     -35.448239   0.000000   \n",
+       "\n",
+       "   median diff      RMSE  max abs diff  \n",
+       "0    -0.000277  0.267273      5.134085  \n",
+       "1    -0.000048  0.016260      0.071437  \n",
+       "2     0.000360  0.265814      5.135526  \n",
+       "3    -0.002111  0.288531      5.399668  \n",
+       "4    -0.002111  0.288531      5.399668  \n",
+       "5     0.000000  0.000000      0.000000  "
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows_api = []\n",
+    "\n",
+    "def add_three_way(name, crimac, manual, api):\n",
+    "    rows_api.append(compare_summary(f\"{name}: CRIMAC vs manual\", crimac, manual))\n",
+    "    rows_api.append(compare_summary(f\"{name}: CRIMAC vs API\", crimac, api))\n",
+    "    rows_api.append(compare_summary(f\"{name}: manual vs API\", manual, api))\n",
+    "\n",
+    "add_three_way(\n",
+    "    \"TS_m dB\",\n",
+    "    ref_ts[\"TS_m\"],\n",
+    "    TS_m,\n",
+    "    ts_api_fr.values,\n",
+    ")\n",
+    "\n",
+    "add_three_way(\n",
+    "    \"Y_pc_t_m dB\",\n",
+    "    db20(ref_ts[\"Y_pc_t_m\"]),\n",
+    "    db20(Y_pc_t_m),\n",
+    "    db20(\n",
+    "        _compute_ts_spectrum(\n",
+    "            pc_target=y_pc_t_n,\n",
+    "            mf_auto_red=y_mf_auto_red_n,\n",
+    "            NFFT=n_f_points,\n",
+    "            frequency=f_m,\n",
+    "            fs_dec=fs_dec,\n",
+    "        )[0]\n",
+    "    ),\n",
+    ")\n",
+    "\n",
+    "summary_api = pd.DataFrame(rows_api)\n",
+    "summary_api"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5de90b9a",
+   "metadata": {},
+   "source": [
+    "** NOTE ** - ware we using als th NFFT or freq here?\n",
+    "\n",
+    "\n",
+    " ** NOTE ** to remove Llod - The API and manual workflows produce identical target spectra (Y_pc_t_m), while the final API TS spectrum agrees more closely with the CRIMAC reference. This suggests that the API implementation reproduces the calibration and correction steps more faithfully than the simplified manual reconstruction used in this notebook.\n",
+    "\n",
+    "The key observation is really:\n",
+    "\n",
+    "Y_pc_t_m: manual vs API\n",
+    "RMSE = 0\n",
+    "\n",
+    "but\n",
+    "\n",
+    "TS_m: manual vs API\n",
+    "RMSE = 0.266 dB"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "24167859",
+   "metadata": {},
+   "source": [
+    "We inspect one detected target from the public API output and compare it with the CRIMAC reference target. The diagnostic panel shows the target position in the pulse-compressed echogram, the corresponding TS spectrum, and the split-beam angle location."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 63,
+   "id": "a8ee9fe9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "target_to_plot: 509\n",
+      "api target_id: 509\n",
+      "api ping index: 509\n",
+      "api target range: 5.79306\n",
+      "api theta/phi: 0.1980538342357811 2.1279301087201414\n",
+      "CRIMAC ping index: 509\n",
+      "CRIMAC range: 5.79306\n",
+      "CRIMAC theta/phi: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
+      "array(0.19805383)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975 <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
+      "array(2.12793011)\n",
+      "Coordinates:\n",
+      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
+      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
+      "    range_sample  int64 8B 975\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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Q7KYxDMMwDMMwDMMwzYiJEydS165do34PBoOybPzWrVvps88+kyXuX3nlFbr88suT0k6mYbT4cJiCggK6/fbb6fTTT092UxiGYRiGYRiGYZhmgIgouOyyy6S4MXToUPrhhx+kV0h42mGHHUbLly+vE0mEEHLqqafSunXrZFQCk7q02MSoQp176aWXpDonwmKcXJzEJ0woFKLi4mJq3769dHtiGIZhGIZhGIZJJmLcevPmzdLg9nqbtzN/RUVFwsJGxHHRbbaMjAz5iYe1a9fSmWeeSa+99ppM+K0zf/58GjZsmOIlMnr0aGlXfvfdd7TffvvFtX2mcWlxIsgvv/wiRQ9xc+Xk5NCrr75KQ4YMMc4/bdo0uv7665u0jQzDMAzDMAzDMA1FeB4053Ljwkbr0yuH1qwLJmR9wt7bsmWL8tuUKVNo6tSpcQkrwqPjnHPOoV122UVWO9NZs2YNderUSfktPz+f0tPT5TQmtWlxIsigQYNk0pqSkhLpujR+/Hj65JNPjELI5MmTpZtTmNLSUlnOb0/6F/kprQlbzjAMw8y57T/UIb+CNmzMpNMnjuYDwjAMwzBEFKBq+ozeprZt2zbr4yE8QIQAsvS73pTbNj6Plk2bQ9Rr5yVSGMLwE5MXiBBG6hv8/uabb+iLL76gTZs2STvRCbuoATvPFCb1aHEiiFDf+vfvL/8Wyp24kO+++2568MEHbec3uUsJAcTvYRGEYRimKWmb5aHcNkSVFR5+BjMMwzBMmNosji3FwM5p65GfeAhRzfLhyqD1ccEFF9AJJ5zgOE/v3r3ppptuoi+//DLKRhS25UknnURPPPEEde7cmb766itl+saNG6m6ujrKQ4RJPVqcCGKnxmHOD4ZhGCZ1WVtqUaVFVLKpRefsZhiGYZhWTdAKUdCKfx0NQZSxFZ/6mDVrlhRCwqxatUrm+3jhhRdo+PDh8jeRfuHmm2+m1atXU5cuXeRv7733nhROdt555wbvC9O0tCgR5KqrrqJDDjmEevToIRMHiQy9H3/8Mb377rvJbhrDMAzjglEzKmh1CVGXdhU0lI8YwzAMwzBNjEiNoOcdEfTr168uH8uoUaNkuoVx48bJSqSisMaECRNkMlWuDJP6tCgRRGTxFReiUOTy8vJou+22kwLIQQcdlOymMQzDMAzDMAzDMDKUxZKfeIh3+Xjw+Xw0b948Ou+882jkyJGUlZVFY8eOpRkzZiStTUwrFUHmzJmT7CYwDMMwDMM0C9LbpFNuh+wWk2OAYZpz+P6mDVupqiwxZWObAyH5X/zraApEnhBxjuw8Rt56660maQOTWFqUCMIwDMMwDMM4IzSPfU8bQbsevj35030sgjBMkhEGdqAqSN+8+RN9/NgXZGNvtziCliU/8a6DYWKBRRCGYRiGYZhWhBBA9jphNypoV0Be8iW7OQzDSK+GIO11Qk01ko8e/YKPCcM0IiyCMAzDMAzDtBIystOlB4gQQNIoPdnNYRimFh/55H0p7s/Pn/+2xYfGNPecIEzzhkUQhmEYhmGYVkLb9tkyBIY9QBgm9RD3pbg/Ra6eDctavggSZBGESRLeZG2YYRiGYRiGaVpEElROhMowqQvfowzT+LAnCMMwDMMwDMMwDNNkcDgMk0zYE4RhGIZhGIZhmhmDdu1PH3z8fqNuY8WqFXI7v/2xMK71zH7objpy7OEJaxfTcqrDxPthmFhgEYRhGIZJGV65IIN+nV7zL8MwjM76DevpxtuvpwOO3I+GjdiG9jl0Tzrn0jNp/teRahr7H7GPNNzFZ7s9h9LBx46iR556WJYhNRn34e9Ddh9Ea9etUba5bsM6+buYLubT+fcF42mb4QPpx19+sD1hC/9YQBdNuoBGjB5O244cQqOPOZCuuekqWrx0cVwn+LN35tPeI/amxqRLpy5yOwP6DaTmCF4L4c+M2bcp86xas0peQzvstS0NP3BXumnGDVRVrebjePv9eVLE2X7PYbTf4XvL64lhmOYLh8MwDMMwKUP/Tl4qLCBaX8waPcMwKkKAOPGM4yk3py1dcdFEGtR/MAUC1fTZl5/S9bdNpXdffq9u3ovOvoSOO+p4qqyqpPlff05Tb51COdk5dMLRJzoe1o4dOtJr816ls087t+63196aS50KO0ljWUf89sMvP9JJY8bRy6+/RDtsu6My/aNPP6QLrzyf9tx9L5pxwx3Uo3tPKt5YRO9+8A7d/cCddNe0WTGf5sIOhdTY+Hy+JtlOYxK+FsK0adOm7u9gMEhnX3IG5ecX0LOPPE8lJSV05fUTpWB27RVT5DyffP4JXXHt5XTNFdfRnsP3pH+W/CNFrMyMDDr5uFOSsk8tgVDtJ951MEwscC+TYRiGYRiGSXmunz6FPB6il56YSwcfcAj16dVHeiicdtLp9OJjLyvzZrfJlsZ7967dacxRx9OgAYPo8y8/q3cbRx16NM196xXlt7lvzZW/2zH3zZdpvz33oxOPHUtvfzCPysrL6qaVV5TT5BuupH1G7ksP3PEQjRg+knp060HbD9uBrrxkMt1w1U2OHgz3PnIPXX7NpbTj3tvRnoeMoKdeeNIYDhP2ZHnvw//QuHNOkh4LR4w9jH74+XtlmRdffV56z4jp519xLj32zBzaZT9VuEF0j5mvvvtSfheeN0efcpRczwn/HkOLlixSlnvo8Qek58uO+2xPV904iSorK6PW/cobL9MhY0ZL7xjhrfPMS0/XTZt8wyQ6/MRDqaqqZrnqQDUdPe5Iuvyay6ihhK+F8Ed8D/PZl5/R34v/pttvmElDBg2V52jSJZPpxddeoC1bNst53njnNTpg3wPpxGPGShFr3z33ozNOOYsefuIhxbuIaRiiMkwiPgwTCyyCMAzDMAzDMClNSWkJfTr/f3TSsSdTm6zISH6Y3La5tssJI1UY7v8s/of8/vodoPff+wAq3VRK3/74rfwu/i3dVEL77bW/7brnvvkKHXHIkdSvdz/q3bMPvfP+23XTP5v/KW0s2UhnjDvTdlumNoeZ8/TDNKj/IJr71Ot09qnn0LQ7b6bPv3IWcu68/w46/eQz6LVn3qTePXtLESUQCMhp3/30HU259To65YRT5fQRu42kBx67v95jYr+dmTTp4sn0ypOvks/vl0IHho7MeuhuuvTcy+iVJ16lwg4d6dlXnokSY0RbxTxvv/gfuuy8y2nWg3fRq2/NldOvmXAtlZeX0Yx7bpff777/Tnksp066vm4d484eS5OmTqy3rY88+RANP3AXGc5y/6P3KaEuIoRJCGnC0yeM8NqpqqqiX3//VX4Xf2ekqyGamZmZtGbdGlq5emUMR48RBK3EfBgmFjgchmEYhkkZXvk2QP40okB1TaedYZimoefSo8gXXN+khzvoK6RlvV5zNe+yFUul6NC3dz9X88+45zYZblJdXS29CDIyMmjc8ePrXS7N75eihvBS2GWHXeS/4rv4XeeLrz+X3h7CaBYccfCR9PIbL9ExRxwrvy9ZvkT+67bNOjtttzOddeo58m/h9fL9T9/R488+RiOH72lc5t8nny49FQQXnXUxHXr8IbR0xVIp0jz9wpO094h96PRxZ9StU3iKfPzZRw1u26XnXk677Txc/n3W+LPprEvOkN4e4jg/+dzjdMwRY6QHTs28l8mQpMrKiPhw35x7pcfFqP1Hy+/CQ0Z4ZLww9zn6v8OOlt4awjtj3NknUXabHHrsmUfp8fuepLY5bevW0aVz13pDdU45Ybz08MjNzaNfFvxEM++dQStWLaebr5kmp28oWk8dCtory+Tl5lFaWhptKNogv4vzKwQo4f0yfJfdaenypfTEc4/Laes3rJPeRgzDNC9YBGEYhmFShhter6bVJURd2lXT0GQ3hmFaEUIASQuspVQlHHbgEfEwLjh93Jl09GFHU/HGYulxsPsue9BO2+/katljjziOjj99jPROePe/79ALc16iYDBamBU5QP510KF1HiaHjT6cbp81XYaG9O3dN+5QCT2/iPj+xPM1xrcJkScljPDAEBQXF0kRZPHSRXTgvqOU+bcbun1MIogIL4psp0aIKNpYRF07d5U5M044ZmxU27/69qua9mwsotVrV9PVN06ma2++um6eQDCgiBw7breTFHXum3MPnXnKWbTrTrsp67zt+hn1tvPUsf+u+3vwgMFSDLnoygtowgUTKb9dvvmasiK/H/d/x9Oylcvo7MvOlF41IreMEFdmPzRL5kxhYoNzgjDJhEUQhmEYhmGYVo7wykjlbfbq0Vsapf8s/psO3PegeufPz8uXy4jP7On30qijD6Adhu0gcz7Ux8D+A6lvr7502TWXSPFAfNdLxIrwnA8+eV8axc+98mxkn4JBeuXNl+mKCydSn5595G+LlvwjDfpE4CFnEQg9VsJGfMiqSR8pNBnd4I9VqPELlz2tTaGQuzSVoVDNNm+8+mbaftj2yjSvNyIqiPUJ7xchNAjvi0QgroGwZ5EQQTq0L6SfFvykzCPCoYT3UPtaDxFxzMT5FKKY8BwRSVTnfz1fTuvWhb1AYiVEHgrWcz27WQfDxAKLIAzDMAzDMK0ct2EpyaJdXjsZlvDMy0/TuBPGR+UF2bR5kzHHhghvOPm4cTT97lvptWfecOVNIkJaRCLWqZNusJ3+5rtvUOeOnene2x9Qfp//zRcyKagIARm5+57S0BblVO+9PTr3hlObBT/9+mPUd+FhEitiWRESgvz62y+UaIRwJHJtHHXo/9nuS4f2HahTx060fOVyGWpkQhw34VXy1IPP0hkXniZDk8KhRrGysFbMCnvJCA+VBx67T5ZBFpWBBCKBbnp6Og0bPExZVogxnTp2ln/Pe+9N2nHbHeuEEoZhmhecGJVhGIZhGIZJeaZceT2FgiEaM/5o+s+H79KSZUukZ8iTzz9Bx/97jOOyJ405mRYvWySXc4MoqTr//a9pzJHH2U4XoTCj9z9YeongRxjpm7Zsoo8//0gKNTddcwt98tnHdM5lZ9EXX30uq638svAXum3WdJoy7VrHNggviIeffIgWL11Mz7z4lAzNEWEYsXLy8afQJ198IivCiGP3/Nzn6H9f/M91iJFbROJV4Q0j8qOItouEp38t+kuZ58IzL5JikcitIeb54+8/pMgh2iYQnjdiOZG7Y+ftd6arLr+Gbr7jRlq+YlndOiZOmUAzaxOn2iHynTz+7KNyXUJwEQlbr5t2rUx+K8J2BHvuvif179OfJl43gRb+sUDm/Zh+9zR5/nNqQ3OKS4qlt48QZMS6bppxozwXok1M7AiHoER8GCYW2BOESTk8WnylFQxSyuPR9MRa11OGYRiGYRKDSJ459+nX6YFH76Ppd02To/cF+QU0dPAwpWqIHQX57enIQ46iex6aRaP2q0nG6YTI81HQrsB22q+//Uq///WbDOfQEfkiROJSIZIcuM9B8vPcnBelwX/5tZfSlq1bqEunLjJHySXnXurYBlH6d8Fvv9K9D8+WiUKvvHgy7bXH3hQrQky4ftINdM8js+mu+++kPffYi04de5oUWBLJv0YdSstWLqUZs2+jyqoqGr3faDrxmJNktZwwImlqZmYWzXnqYbp99nQpGA3sN5DGn3iaTLA64drL6OjDjpGChZz/yOOkmHTFlAn0zEPPSa+M1WtWkVfvfwHCm0MIH/c8PFtWhOnauRsdd9RxsrxtGLGeB+96RHr9nHi6aFOmzO1y5cWRajeC1+bNpdvuvlWGDwnvkaceeEbmU2FiJ5iAcJh4l2daLx6LC1wrbNq0ifLy8uiAvHHk96STVV0dOVjeyIPW0ioXeNIjsZFWbSky+XtGpKSWVRXJih0qrzAa/lYgsk2mdeJNT498wRe8N/Kw9+ZGkocJQiWbIotkZdqLSrB8zXdYdwZsE6V1PSN+CEQpiN1VqKyM/J2mLQ/XvnIfgdjlwf0X+KCdmVCmLhBZxtq8JfI3bl80Ge49JrVZkPdybWJUoqGl8bk9MwwTTWGvAjrr/pOoU4fO5CNO6piq7H/EPtKjQogUjck1N11Fi5Yuomcffr5Rt8O4I0hBWrthDT107jO0fmmxMi1gVdPH9DqVlpZSbq5zeeXmYGt9taAz5bSNLyhhy+YQDR+6ptkfE6bpYU8QA8HSTeTxRISNeqlURY06ystdLW4F2HOAaZjRHnK6tkzXYxPhzci0FQglIMoo4h8KNCjIiGkVkf3x4K5hAjgUTlDcEZvMyoqsC46t8ndz8DjS8OXluZrPg0KWdmxlprz6AGGXdIHKhMM1jMfa2lquXSviOrAUMVA/N83xXDEMw6QCc556hEYOH0lZWVkyFOa1ea/SlCunJrtZTCuEPUGYZMIiCMMwCSeEIoyTIINeLhBC5MvJUWYLbtliK5zg363R2yMExyVKCEKhAY6zBwUNuZLIcbeqqu29b4KReTzoiaMvD+t2FOlMiGslz2rV55RhGKYx+XnhT/TIUw/R1rKt1KNrD7p6wrUyNIVhmpqQ5ZGfeNfBMLHAIgjDJIlmmfsk0Rhyp+jhZso0NO4Nxww9UXRRRp9mN09zIcpDwo3woAkLXghXciU66MfJIGQxDMMwsfPhG580yuG7e9rsRlkvwzBMc4JFkPrgDn7LIoXOZ0qIHnA8vDjCD5ni9ZF/a8tW25w3mPsjOsQhQqisrF7PBV2QULw/cJuG9ToJGo0ldnj86n5GhQHZ5RYCL4qo+ZQ8QQH73zWxyLRvyjLadRe3t0WC76OObT3k9VjUIcdDVJrQVTMMwzAMkyJwOAyTTFgEqQ8e2WxRqIZlqMmTnKacez9c38bwBRAXdLyG0BRFOMGwCrEM5OfA/CCIT887gYICGP4ooqAIkgwcExrDcfa0aWPMx4E5Sjx5kQRfHpwPj7O2GV92fmRdWvLlut8r1KSxHsjFkgrC3PsTM6mwoJzWF2fS2IuS3RqGYRiGYRqDIHnlJ751MExssAjSXCuGuAwLYFSSUnkHvS3wHGpVV5JtxMcLGvDetpDTQ/d2yIVwFDTuwfskCqwwg3kr4Hd/RpfI73qYyNbIsQ3C340pcpquteDmza6WDxZvrF9U0zxB/Bn5ttcXVqNSPH60427FeQ06eZwwDMMwDMPU9RMSkBNErINhYoFFEAPerEzyelTRAUed9dh7ZRoYfej6jsaXWL8CJB705kYMyMD6DbARVS31pPts14eVIKxKKMuLxp9upBnCRBKetyKFwlHiBvbFl69W6fCkpdmeA+V4ah4SKAhgiVsMP7GgdK03J1tZPFhSEpkG16O3XV69nhdy3e2gtJjPY6y0YsE0TxUY4SH7eSxtm97KansRBO4BK1MLLQGvHSsn4kniCcLyFVDpZUORvnv1X3fa/RV1j9q0WRF7dO8VKK8dVZHFVH4Y7y8o/6tcK3hucR4BiBimezWkeYIk8j5k4YNhGEXQdlN9qiXvvy7uO4RAulpfazyeDMMwjQCLIAZElQQhLiqdeqekgy7CHLzgBq8YploJUALjy1cQGdn1aEZaCHMzoPCB1R/QW0Qbmfa3bx+ZVhkxjDzZkXZaZZrYUxhZJtQW3PrR6PVH2hnK0LwdYJoXDFtPNVQG2axu00qPrMO7KTItlAthFdhGLczFg+sDY9KCEAsrU22nt8xwPkGEIAw3QINXO26e9gX229cMfS+EPxCEKHjy20V+V86tup9+vKawPdiBgvOsE/ztT4oH5VrNBFEOvTjkD17jcaubRTfuQ0H7cq+4b3jMUJwQh231GtvtKJ45mliD3hN+uO7x/iTwqrDSfGbhBq57FJWilqkO2i8DHV+8H/Rrndq3jUwDUciDOV4qqs3PLri+rdJNkWXw2tSFGxRoSjYpZcaT6oHlAHusMIwDyjNWuXPgb8vBUDcY/cZ1ORj3TgMv+MzG5VHYjUUzcCs6mOZzEkHw2OqVukzguhVB3WP7jow6tqZz4HRslH0w/K4cczK/FxThx2UDcN3Y74pFRGJSFs4JwiQTFkEM+Pr1Jp8vQzE4yntEDAxLG8T3BKCsY1rkIR9MB4MH39c40i6Wh4d8CKaFwE7WPb48+F7DdxG+uyzz+8YbdLOMuhBO8wQNbcEXlr5NOE6eAIol4DHTQxM3cJsWGGOG9QbT1QMVSsu397ZwODaKJ4PJ0w77H5qDRcjvsb9WvA7n03AOTfNE9R+sGJZBDaF6QL3nWT/W3mrL9nd/ubmj4q0C8QuNbgePxhB4PWGb8b7DdXk0gcjTu1Nk+5UBW6HBW6F2SH2mw4bXEAhsHkgGGyVAFhVH/lbuD7WdVgO9riwHoTUEYUNKCIwmEIWgbR7wLvLkRp53wTXrzB4yKOqAUKzkiNGFMNg3RRAOhmjC89VUVk3UJq2a/F0hxAkB7ypj7hjd+MDvfoPxhF4y2jWEIptSStgJ2E8s88y0LDApsh5uhp5XeO/gwAMaxsrvDoKdF8qIB0tLXeWhCq9L/ivuByFIi49uWLo1zt3gJHwgRhHBYXmcL5Hhd269LUzzORnqDt6YrsD3B/YtsCl6igVjqCm+i3RRC2czHGen/Yz3EjKJLeiZGnUsDX1P5drQ9tMH76ZgoOHiGbYBt8PeO64IWl75iQd0CGaYhsAiiIHinduTL13t7KPBh0Z/lNGL/WvDSypKRMGXjEloIHdGM4obqjGrPim8hpcUzqcIGtq6Tcassh1dBAGPDzwGVjkIImlaWAKMduvT7PBraQ1CIETpYoUJCw0erynMAxfQRC14aQdBFFPEJn2jcE15YxjsUNsJq/UaBBHtOsa4TEWs0hpamQvHEwalQn7D4dAH/Fy87/T7y7S88V5z2oZJLHLotCn3EQp+hnstavlgX/t2Rs0Y+dNbZb8dHzyH/BXa/Qm2ua8SvKsq4O9K1VjwdSywF25wvRCiF+Wlgx2/jIjY5MEOsi4ooNgA95pIevv+giCtLiHq0i5I22fWrlvbpsmAJNhnJXeMZoyiZ4oiHDXzvDxMcsDrKbjFLJCFyuD9h/eNgyepSQwNbjLnFjIl4A6vS/4r3lFChBUPay3kUQntUwYEHF5g2IVxyu9kWh7b6WLgIRr7qmGOxGs8udjNqH0xOEKY3jHR7zlPQvbzqgkX0eZNpTT7ocejtu92XY7L1O7DKScfTdsMHkpXXX2D8rsdSn8T3h8rli2hAw7di157fh5tM2CbyDz6vWES0pxErXgFP5P4xmFLDJPysAhiIHN9gPxpAeUhjx4eToaMceQdDRzsrEe9AGF0HQwWb5X6sPVuRkMAwzzsT6veMVHc7ZXG2P9csxBsH1z3ldFxDHPBnBG6MWR4meshAsZpsD8hDBHQK26AW6YHjyF640SNgthPs7CzaHIRlQ1Cbwn7kZNgtponorptmq1wY7rW9M5VCDxg0GhWOlC6IIFeR3jYceBHq/SKAokPo25CBsFQF8Kq7L1HTO2SbcjAe89TrzCpHzNcHvdH2X/ttkGREI+b4p1lEn60/dbXHZlJ+44pUrBiMf6eFVmoqq12TyuCF1xDaLvoDg4B+7AyZV1BB8+goL0XlioSuntGymWeCc9EtPqY/rZtQzEWO9VOnXLjMxuPjcNgsuL1pBwPszhuEq8Qf1nQViSW3yvw+R+wfQ7qz1jMwaM8Cw2dcg/m6NHDpSAkLLSxxJiPSDGiIR+SKReOlZVuXB6f5V4I6YpqP3pI4LsME/3qHpdwrvB9GMq0XxeGb+rrw+sJ+wY4IKJPc3c9ml/A2H5lOy7t4vD12SY/i6zsDArlZRH50hw9BI04ib6Gfo9bjPcx3B4/fP8NnTz2KBoxcm96eM5zyjIrVi6nA/ffre57bm4eDRw4mC66eCLtttse8rdJky6RIsC99z1mu6m5c1+gabdMoW++/V2dYNw3w3n2uN1Pp4dXzUpeFW26+Tr6+vs/ojfp8piHZ7vqmhvJsqy6Z5TDq0hrdFSz7Km9je9+YA6l+dMi94FjO/EH8A5uW/MyDOSkU6DA/n3lGJJF7o6z/l665+4ZdN+smco87TsU0qdf/RyZzbLo3lkz6aXnn6ZNpaW03fY70jVTp9HAgYPq5lm2ZAndNv16+v7br6mqqor22ns/uvq6m6lDh0J7z+lQNdHmdArtOoRCvbYqbbMCFURfvE4thRB5KBRndZhQ3Gom01phEcRA5oZy8vs0V3XoeOqCgqmziTH+2NHzbq00J5tETwpDmcsoNzxYnafKPmeCLo5Y1bhN+3ZGdSKhw+2BsALFLRIf6tqIlJIrQylXC+vFBJ0amHBU+R1yj+geL6EscFUur65fBJIr8dSbp8EkyETlasDrAQwM78ZITheBPwdcpfHY4HYUw1Tdz0B2mq2XjpVmPp/YyceQJMXbwmHkSfEACtmLfLoo5dsaOdc+7T4IE8xWR/WCWXDtYnoN2E9vuX2Yi6CqXcToCmbaH49AprqfvkowmNBjFgx9o7jhgONoqslLBe8pJ6Pd03CPFRSllFW57FegkBWKYcRSEZK0ZTI2WbYeXIoIYuhUxx1uFtVQMnrI2W1fLgLtDuAzHp1kIFRIF0o8bfECg/wzHvMxU68VezHXadQZQ8zw/iLqCvuliW9KTqgGGv3yGWvvfeirQsVRXQaFYrynlfXqIqvJADN4/kV7Mtqfd8VDUhOyrCrTxQZ/Onn+YcggXkNOIgTsN56P8HM5w0qT7w9x73rrHbE2eDJGLRanIWI1bJ65Lz1HJ590Gr38ynO0Zvly6tqlW6Rttf2Rxx99nvr3G0RFxRvozrtupbPPOpnefO1D6tG9Z811ZtnkVapZQ937NWq66RoyGeAe4SwQJH/YY82YR8PBOK9ddzjMs+7dbxJBoncn6s+8Nm0dYwk8LtQrJ4/PMPlta8ORw/eIkwhi2IfwgIT4F70do7eZOGNYXB/iM2DAIHr0sRfqfvf5fMo77+GH7qEn5jxI0269i3r37ksP3H8XnTH+eHrnnU8pJyeHysrK6IzTTqDBg4fQ44+/JJeZNes2Ou+sU+iF598ir53oKU6zZZF/cxX5S2v7SLX3vhVMrfxa8cI5QZhkwiKIASFSeH1azoDNDoIEYooxx86qFtNuTPaIIoIe/4iDaTgNtwnrjfLKRK8Mw3YwoWLUutGNEN3VYT8xeav8jssbqlL4Ma4/amK1rbu7B5fR3BuVnAOYTFbx6tD2U3PRj8wGndA2WfY5BpyMXiVZmFbtZ22R/XHHc4v7qVX5SMdcD+gqDaO2Vhuzy3CgXZa9YaV7EGECUvSSwWOD11ZUbobIn6EM+3ONBk70RDIYBWA8rVNj5P2RlBbKMcTlg23VESYfJMfF0elgTmT5QBYKVC6Nfhcdx6j53HiakYMxi947WjiMIh5B7hXlHKK3g240oZGAx7MNHGeHY4P5XqQBGl69RZRRGrQdXVc8iAzu2VFGt+JxUr84oKOISmhkooefU3CySTdxOraG+ZTV6sfWTW6FUP3eWPp8TgaXSfgwtlMXjbE94K2nDCJoy4RAHPaVewwhl+btKNNMh0BbHvMJ4faVbeieiKb9Nh1bHVPbFDE05MrjJexZky5WKuapFp4AIeftK5eQ/X3jtIyb9jvOZ7MdYVi+8+6b9PKzb9KGdeto7svP0wXnXRqZoXb/2+XmU2F+B/m54ZpptPdBu9Hnn31MJ4w5uTYcSByH6H7IV9/Mp8nXXCb/HjS0u/z3gnMuoQvPvYxef2suPfHMHFq8ZBG1yWpDu+82gq6aOJXad+hQt+wp/z6OHnngKbpz1m3055+/0yMPPk3Dhm5PU26YRP/96D+Uk92WzjjtHPrvR+/R4EFD6eorp8plq6qr6K7Zt9Obb79KmzdvogH9B9GES6+i4buOoK+++YImX13TpsGDawTJC869lC48//Ko4zT7vjvogw//Qycefwrd/+DdVFK6kfbZ+wC6aeptlJtX0x+adNWltGnzJrpv9hz5fdz4Y2nQwG0oPSNDCktpael0wvEnR9ZPRP8s+puuue4K+nXBz1JIuuaqG+i0M06ke2fNoQMPPNj2/I475VgpAFw9uSYcZv8Dh9NxY06ipcuW0Lv/eYvy8vLo3HMupuOPE+ekZpmff/6Brpt6pdyeECHOPfsi+bs3GKq7v//++0+aPuNG+vbbLymrTRsaOWJvmjz5eirIL6Cvvv6CTj9jLD3+6Iu0yy7D5fyPPvYAPfjQbHrz9Q+pY8dO9ecRESJI0CKf10cd82vOrf7OE14gTz7xCJ1z1oU0er+D5T5Pv/lOGrH3jjTvjbl0wnEn0w/ffEUrVy6n1156l3JyaoSnaTfMpN1GDqOvvviURuw2IvqgWUF5X3qKSskb7stk1PTdvCFzcnuGYRoGiyAmSjeLHo/Znbj2gVSvwIEGLL5r9YRSIEKYYoCtEtWww/kwMVuoMiLW+Nq2ta12IZsMVWBM1WX0hGuJLHGLbcaYaqUssEt8mCROT0C4odi2zY7LYDvxHBrK4upt9mZFDOqQIVmkfp79HQsjXwweL0qHTUtwSVgCuaCdvViE3jua0esvMuRD0EZ9FaMRDTMQi1Bs0isMESbJRIEJEnFaK1epTYBzpYgYmHQQqtPobvhWNnrZoLs8usGr+xlsk26b3wJDFDJAQNBRqsMoVWxgJqf4aEyCuMVeTLXWF7krzQzHHI9ZVOWXbAdX47oFtOsBc2/AubEfYbXBIWQj+/ei+g0uJ285MjxzUUzE6xaFUf0Zjc91FD2V9WphHoroadn/jufDKWkiVFJSnv3wrIkStFFcd5u0D54x+OzCZ5ouDijtMT278Nhqzz7lWsV3EcwX2qzmwPDCOxhL1Cv3h3ZtmN5zSngPCiWaJ6MHq0EVb3T1XPdBzhlcXtkO5LixHJJNKvc3tM2LFcicznXtOfBke2v7NiInSMhWCLBd3uRlFPXdNB9ed7oLkoMLTpjadr799uvUp1df6turDx1x6FF0461T6PyzLowMHoTPrfi39lhkpteGVIhKfOLYieMsRZBg1CZ3HLo9XXX5tTTrgTvp3bn/lb+1EecxEKDqygq6+JxLqW+vvlRUUkzTZtxIk665lB6e/ZgyIHT7zJvpyosnUY9efalt21y6dfpU+uGHb+n+ux6h9u0LadZ9M2nBb7/S4IHb1CTkDIZo8jWX0spVK+jOabOpY2Enev+j/9AZ55xMb77wDu04ZLuaNj14F737+oc1bcrOiTx/lLAKi5YtW0LvvPsGPTBrDm3ZupWunnoFXX/T1TTz1ll188gPDGC9+sbLdNq4M+jFp9+gH3/6jiZddznttO3OUmAIhUJ0/oWnU9fOXemlp1+nLVu30PSZN0XOCwqWeN7FNkTb4Dn72OMP0kXnT6BzTj2X/vPB2zT1+sm0y7Y7U79+A6TAdfa546W4dPtNd9GKVcvp5ttqRCK5jUCA1q1fSyefegwdd/SJNOnyq6myooJm3HUrXXLx2fTknOdp+I7D6ZSTTqeJV15Ir7/0HylC3HnXdLrj1tnUMb+9bMvc11+iyddeTn/8uDTSZrz3xD1tWbR06WLac5+dKD09nbYftgNdduFEKQAJVqxYRus3rKM9dxtZs3+WRenkpV132o1++P5rOuGo46mqrExel+ni9NQ+5zJC4lb00ndff0EjdtjV7kInKxiSIYjB9cVKHzlgtTBPkIQkRuVwGCY2WAQxYFVX14zg4IsFPQy0pHseMLrQ6DMJGti5TATGShI4Uq/NgwKHSZCIXl/iypMlsmymY+UFQ5vdVmtQjxuExqDxpINeEdhBNrnRi8tr3foGiU1Ykla2DDrlfrg+lVLKmpGrGCwgiinXveatoeRFMY06w/1gNIoE2PkHEQevR/kdBR+90kgtgRUrjZvBagmKZxC02acbkwiW8gUPIMxtEJWbQQljwhgemEk/tYZpFhrd6P2ildrG7Xgyoc1bIsc2qBmTBN9RNFVyLmDCUK1ELiYT9dWOMsrtoxDlZGQp+6aJAOFrV/8dBQFFRMDyy+r5QBFYMXpR1HNos5uSv4pgqt/veB8nUEwmitz3jUmqJY1Vrsk42+b2fewzvE8VEUgvtQ1t82Apenje6GIL4gERBa9BpUqTVlHG1B/whK+7iowasUV6gQSV5/1jTz9Cjz3zKNXHkMHD6IG7H8Gt0jkXn0ELf/u13mWFoX3a2H+rP+JjxSQE1RrsL7/6PB1x8BHyHt9r15FUVraV5n/+PxoxfKQyn/w3EKCy8jKaefetMpRBGKg1AkDtvV93n0eOQbrPT22zc6TxWlgA5dFDITr28GPrvvbo1oOunnAdjRn/f7R1y2bKbpNd1/aLzr6YRg7fUz67hGDw2puv0Ixb7qI9dt5dTp923XTa6+A9ao59IEjLViylef95kz6Z9xl16lRTFev0k8+gTz//WBrsl50/oaZNRFSYVxB53oXPtZZUtLKqkqZPvZ06i3V5vXTNxKl09kX/pkmXXkWFHTpGxInwsbIsGjRgEF1wVo3XRe/uPenp5x+n+V99RiN335M++/xjWr5iKT31yHM1yxPRpedPoNPOFR4coehzpnha1QoutYd57z33o5OOGyeXOfPUc+jxZ+bQ199+Sf36DqA3571GoVCQbplyG2VlZdGAfgNozZpVNPWWa+ra/NwLT9PQwUPlMQlzy5TptM8hI2jx4n+oT+++dMkFl9P8Lz+la6+/kv7+50868tD/o4P2G1W3v22zsuV8Sh9GCQv30HbDtqfpN91Bvbv3oqKiDXT/nHvphFOPprdeeJfy2+XT+nVr5KzthbAC+9+hoAOtWr1Crm+HodtRVmYW3T5rumyv8B6ZMWu6FJXWb4A+XxSWfM+kWnn5xskJ4ol7HQwTCyyCmJCjBCFl5ChQUmLu7Na6bacaSviJAy39QdsYOHZcMdFfLKX7XBhGKHroBIpUD4E6wEtIBz1RlBwtmWqVJGXUFcUBk9ihJ0fEaxI68p7syD0VNS6AwoeIU7MxJHx5IaMHE1ZLCKHYFCf+Lp2NYVh4nDxonDtVTsAOGR5nU4lABywQa3CLfmyLOB7C6y0MPNdw5N1tJQtl+yAGB9FLSU4EzxrYTykaZEOOkVqjD73WaibYd1yFeB35osds2OfpUTrvHnMon5rDqLrecqQ6roVmpnmjeDToAgnZXqtKGVtdAMbnClzDirii90dwkAaWsWrbZpWl1xqUYppHuR+2bNlMa2uNOye6dOqsPvO8XtpYXORq2S2bSqONZsy34jCyu2jJIvplwc90z233ye8i18a/DjqUXnnz5YgIUssJpx8nR9zLK8ql4S6Eh0H9Iwkr69uWHQv/WECzH5pFv//5G5VsKq3z3Fm9eiX17yvKzNesb9tttq1ZIBSiFcuXUnWgmrYbsl3d9oSg0adXn7r1Lvh9gTSQDz7mIGV7IpFmu9x29m1GoVbzqOvSqSt1LuxUc5xDIendIgzvxf/8RYXtCmqfoeFroFYE6TdI8QwpbF8ojX9xnhcv+ps6d+xSI8DUCszbDR4aaYdeZQVzoGhi06ABg+vaK4SmDmI7xUWyLf8s+osGDdiGskS/o3Ye0faa7QjBLkQLFv5MX33zJe04snb7gPCA6dOzD6X70qQnyRHHH0xdO3ejqy67umb52nUetM+B8mOsDhMI0j677x3Zh34DaYdtd6CD/m9/eu2tV+i0k0+vm9WjCT0110TNu6Qgvz3dfetsmnrrdfTU80/I6/HQUYdJEUf83doRSVGDnBiVSRIsghgQIy4ej3kEWx9p8WZk2oajJBvubCdnZNStl0kiMYXguF1G8V7BcC8tf40yCg+dbaVkYwI9hiQgQMYC7icKm4qHid4hcSPwoFeEbqijK/5WOB84gqt5VUi3aDuxCEWczVuM5xk9OaI8PtwQ57MrKnzOLtRL83pSwjm0/akTkvR8EOVlttegIk5onj3GUqN4nOBv3Rg1PUudhA83yzPNBzfPdafzrFwrKHwYBLaabdbvddTQez1UVQlGmyoC5GTnUCclZ4I9+cKQVlYakqPjbpYV24jCpRjx8hsvUSAYoL0PjQgeQjwQYkjpplLKy414o915y93Uv29/apuTK9sWL8Kj5N8XnEojh+9Ft98wk/LzC2j1mlV0+oWnUTW+L8RjPqv2fWBZdUJJVL4Y9CwKWdJT5ZUnXyOfJlS3ydKqMUVW4LrtHlOeN8CvC3AeT03bxb/hZd2UPxaExYWw1w2IXn4hxonp4fAsuZ2gFClqjhWEKemEQlLM2W+v/WnChVdETZZeKrXb/uGHr+W/pZtKqLRkI7XJrCfc0ykcUp6HNjSw3yBasnypbGJhQU2ukA0b1lHH9pF3XNHGIurQPpJHZM/d96IPXvuIikuKye/zU27bXBo5enfqPqqHc3sYhmlUWARJFNpLi2FS1evHtIwXcnIo6Ilq0UsEDH8/xLsH1kYykfrbgzux6LCDoGEM49LAMAv0wMGQJEfjwyQKgfGAI/q6cR4q2mi7HX+nGrfgmi9a9SXMBYMiCnauNDd2Y64KMHgwnMeDgopct5WSngdKqFd9wgn0U+tyOug5JAzChzIK79BZxxAaNCZNuZUYpjFx+xyMdxk3nHbS6fITCw/c8RA1JoFAgF6f9ypNumSyFCKQC688n95893U6+bhT6n7r0qkL9ezeK6ZtpaWlUVAzhIUXysaSjTThggnUpXNNctJfF/5S77pEDglRJvbnhT/XLSc8bpYuX0q77lSTuHObQUNkFZnijUW0y467um6TidVrV9Ha9Wupk/AGEYLALz9Iz4PePSPeJ66xLJl/RQg+GzasrzPwf3Gx787rjfZk6d+nP73xzmtUUVFBmbVeqD/++qOymPCi+M+H/6FuXbpHqu5oiPCiW+68hW686mZ654O3aeLUK+iJ+55y9r6oR1Sqqqqkf5b8TTvvsIv83r1bD+kt8/lXn9OQQUPrktt+8/3XNOHCiVHLF9QKh/O/mS+Fkv33OoBaO5wThEkmLIK00HhpO/SR0UTnJWGo3qSrbl3nYyIW7wt0lYaQBRQXlPwJAlNoBxj6ijigXXdeQ+JdJfmp5t6t5GrAagf5ETdhkUQsnms76ny4OT/YadKEUEX4wISIkJ9Df24oITRYfQiOmeJerydoxgSu0LYQhqNo10ljGVOx8n87+6kyGKAMn4/+/LBGiPBoIo45B5J9uEAUcK4sqJaTaseCYZgIH3/2EZVuLqVjjzyO2tZW2ghz8AEH08uvv6SIIPEgDGyZa+TrL2jQwMEyr0PXzl2kEPHUi0/RiUefSH/+8yfdN+deV54vRx36f3Tb3dOlp4rIITH7obvJ4/XUvc5EaMzhBx8hjfVJF0+WoogQXL78dr4M4dln5L62bRIfOzLSM2jS1IkyOavISXLTjBvpkAP/RYUdVK88t4j8JkLMuXLqFXTFRVfS1rKtdOf9M2smNjQlgye8THTS3MMOPlyu9+qbJtO5/z6PVq5eSY8+jblniMaOOZlefO0FuuyaS+iMcWdSfl4+LRU5Vd6bRzddfbOcZ+J1E2jP4XvSMUccS3uP2IcOP/Ff9Ogzc+T8gvc/eo9m3juD3n35PaMIMv2uadLjRAhXQpwSOUHEsfy/w46uabHHQ6eceCo9+Nj91LtHb+rVozc9+Pj9lJmZRYeNPrxuPa+88TL169NPVq754ecf6JY7bqJTTzyN+oqcJK0cEQ4jPvGtgxOjMrHBIkgK4tpQhlFPJUkaJvozqORRq3LIbt9QEm3oeyExXCqJTdguJQZbN05RBIFKHB7dcwNGKFAcwFArHPVOtMHmNoTH2yni5mlpeRPCeFA40SssoPdIO6hMgsdQ93DA5K5Y+QYrPHSJuGF7irXwGbgnTCEbsYBVLUirgoN5MHzgZeO4fRBv0CVaCRkxlD+OypcCIowPQ3W0GGilgga62EMSRqWqEnjlyO2A90oslZ10ph6VRoUFAVpfnEZjP2ycaz2VniMMw7jj5ddfpBG7jYwSQASj9h9NDzx2Py34/VfK03NoxMBO2+9EJxwzli656mJZYvaCMy+kC8+6mG6dchvdcd9MeuqFJ2jooKFSZDj38rPrXZ9ISDpl2nV0zqVnSVHkjFPOpNVr10ixIsy0KdOloX3r3dNo3bq11C6vHe2w7Y5SAHFqkx3CA0YkAj3zkjNkOMg+I/alKVdeH/PxEKE69864n6656So6dvz/UY9uPWniRVfSOZedpeyDs+hRSzgKy0Y8EcllhUeROFZHnXyE9AyZcMFE6ekTRni3PPfIizRj9m0yFEnkTenapRvttcde0tPj3kfuoRWrV9L9tZ5JQvi56Zpb6JLJF9HI3UZKgWnzls20eOkix2avWbeGLrvmUiop2ShDn3YYtgO9+OjL1K1Lt7p5zjzlLKqsrKDrp0+RAt32Q7enR2c/roR8ie3cce8MGa7VrWs3Oue0c+lUPTEwwzBNjsfCoESGNm3aJOuW759xHPk96eqIIZYadQoRAMMEk1cm25hXRtqTlbciRQWNePEXqnXklVwZbqvwYPlduIbwOHlN5RYF4DkQXBEpMevD8om6KIYJRzHJGs6H1Tt0Yz83x3Z5q6jYPu+GTCK82TY0xmnfPFgJB3JiYDsDUFYXhaOostGwLkUk1MOBcDvogoylfKE6DGG5YAew3K6OUnkHHW6wtDEmVFynlWaGY60kJm2qe91Q9cTXTjVK8LzrPDtrHhUWlNP6jW1o3FXH1/youTDHK2QlUvSNl1QKW2JaB4W9Cuis+0+iTh06k48cyjIziccTyS+y9yEj6cpLJtOYI49L6CaEl8kHH39Arz/7JjUm3/30HY0943h6/9X/Us8evc0zspnRIIIUpLUb1tBD5z5D65dG+lLhErkf0+tUWlpKubkwiNRMba2nftiW2rSN7xlUtjlI43b8pdkfE6bpYU8QE6K8l8djNNQdO6vF9t4PSilJB0FCyaGAI+U6aMDiKDpWTsgEIw2yfsvtBNrbu8jjfHquE1OcPYwmK2KRXsITDGov/I3lRD2btVAGHLmGHAqhTeBhgd4BDscptCaSq8KLwoW+n4bqEyg0oGFmZZhvJW+/7radAa9mNHsq4RzCvvny4RiC94jufRJcurzub3+3rpH5wIsi6JCbQal0opQa1cIn2kNOitIt9qVj+0RGSjxbVY8XzGPh6xHZpqcM5tMztoNwYHWInGtPRbXtPoc0jwQ0NE1VdbwoejiE1Pgx70ZagdETRBGSMLwHPWP0PCTwXAnlwPGE+9hbCs+kIf3UbW4Br47CiNjjWw2JSLUkr5i/JV6hwIv3Guynk+hhxLKMCR/deJs5CWHoqYXVN0xlTxsTFj6Y5BBOcqlWh2lx6B4ITU3tc3Th7wto0ZJ/aLtthkkvBOGtIDhAVChJBE65LkzTXOYXCSNCSNq0aSPDPpYtX0o3z7yRdtp+55q8K/o28PmJ70JM/u3T+k2mcrVMiyWYgOowQQ6HYWKERRAD3uxs8nrTlWSRoc4QBpBhVi6DWREjozo3cogteBkH2qg3va8S4vf9kRmDGR7b5eV3aILH8C6znHJAwfo8lv269PV6wHD34rusKvK7rzzy8vJVqivwgAFpYR15INTJJnN8LcFMCBnJgDK0Tlcylqv3dK93+zXT7JfH7YR8MMFrPra4jNOxxWNIVqHtuVGe9VrzfWALBrRokrpmatqCB/oZaWUh+7ZpHWScFvJHBBFvAMQB3BWvVjUFrzUUgry5Db5ulfwgsH0KRkQYgQ+FHDwH4L3i3aIZ05mR+9hbjslYg7YijNVW3U/FewPbD+KGnvsEO35eFMW2gnHeJmLAe4tUkcDKAuO+OBLOYnUHgQsEkSjPGBRIUAxFkVErd4seJ1hWF72jEhEmowCdai94nyhCh+6th9NwP1GIAjHXqwnVeG7ceta48vIweM8wTKzhpe48Lu2rw7ipktGkYFv0QRj8bnqdK+WwtX01lMdWltG3idPQS1Jft/6M93rp0acepsVLFsm8IkO3GUbPPP4KFYhSw3K9hvbr7TQdD6UOur9mIC884KD0IQwDXvp+auWPBVvLy+j22dNp9drVstrOiF1rPFnqFS2MZWi13/GZjetT3ktY/llbn+kcNhfBjGGYJoVFEAPVA7qS5c8kXxmMzH6/wHaUVM/14AOXdG/XAtsHdKCNeui9ARjpBuMaDXVdBPFWo9EJf8O60Mj0bVarHaABp7w8MEeAVvbNNGqMBk9wIyS7bK+VpYOXWQhG5DH8Qc8zgR0/kWE9HtdxUylj/XwqISQYJgKeOaFce68QQSAb8iS0hX2GzeB51lHEAcOLXRFHNHHCX2bfOVKEAmloRxZKLwVDHzxB9Gs1lAbXJAhR1SDYBbLwGlbbGciMTAulGcQiy0GwU0QY3Bkyiyh4CE3zebSSqsrpaVNvR0lvs9rx1KY1cD8VkRL7rQH1/sJp3lDknvQpzjjqMr6KyMrTtlq258ZJvDMJhhnFkQ6uv6y7us2tUB4URaVAiEbcVElrS4k65VVQ//BzRbu/MIlv0GDkRXmRgNjggedSYNGSSDu7d7N/Dor5YgjBcfWMYuGj1RBT6BOOorsUQVD4wHezVTuQ4+2cU2Nwiveu10+W3/zAVJ6X0Xks6wefXfiz0/Iun5fKNBQhrPp/j/4hBhFE6Z8ZBInav7fZcQd65bX31PlUTd6M4bibBrLOmzBRfoJ2yyjhT5HrMfp0ROf5OHzcSXTYKSdF/R5o4Lkyge8vapNu2x/y4Esf+2ayIcH6BS4nsYaFjyYnZHnlJ751NN6J6927Ny1dulT57corr6Rbb7217vuyZcvo/PPPpw8//JCysrJo7NixNGPGDErXPH2Z1INFEANpi9eR35tOIUiwiNVVdFd5a2u5rUGNnX2lckNlmoMboGUbJqJ7G6DxgHg3lduvF5M4ytwMm2w7WjG5rsPy2LkLbihSZvN17mQ/QuUyPwgmgA1ubrgIYip7qbu+G0t6gnDj79YFGqZ2IdKqIx5E/tKIBRrMBbFH63WE0iEkyJBfAsUuXUTxlQVs1+VFLwjdqwOmeSvAMN0MnWg9zAOTvmIFEghTqS6wz1gvqMrz2woqwXTw6tD33yACoKcUGu06ps6iaR79+GJH2guXnQ+ESL0DhWKBIj6ZOujaNtO2gEdVBXghgBdaeUd1p4OYogTFKhTf9MivnMh8VXlKb9l2Xxy9dGDa1s7YAdA6A5a9qCS2s/VJi4ReKxxmVo0bGNUWvT1eRRQiV9cQHg/aF+5jtG+CZi8qf3nI9tx60ZtLO7/pxRAyCEanrxhEX907bcNG2+eyr0d3o1CtiMhoCECokhIShp4ocgWNM/KvhychUV47NkJWVAlrzCEEoXihEkgqreUjwvcRvqe9Pe1DFpWcP/K6gQsH7tVgdrrxuYzfg2kQQgn3pzK/dg2gZ6hpdDvKExTvKexP1K67Tfs2sl3iOgz5fMogjH5NebSwS2N+KfSKUPJLGbxm9d03hdq6Hd3HaSYBWl9e8bBA902DcqP/AC8NUSnEDcp8uE1T+/U2wPLKsxifXfqjT7nFDSq+/ox1ao9JhEAw8TteA7r3I4IhxpiPDwcG4X6wojrFLkwa/TQZrhVlNod3tiscBkjU41z7dygg85X5evckf3qtYB/ur4eqiMxRzc2O5hAOc8MNN9CZZ9ZUFRLkYPXHYJAOPfRQKiwspM8++4yKiopo/PjxJNJtzp49u1HbxcQPiyAGAmvWCp9p9WB1hBCFqA4ZGH34N47co2ihG6NV4O6OeTPAMNVzelhFkY6shfH3kDcj0XHtJk8KC7aptFHbPo7gGnHolOP6sFNsYZhNDB4iOELnuA5oS2DFSuP6vOuzbPMPpGGpV71kcV4kGaqVWf+tiZ0EgW9L5Bx4YBRF6VRrHTU0xtCDSOncaDkkQiAQeTtE8spYC/6q+zujW2djRym9IOJNE8yJHJtQOlQ7grKluliD91EgP3I9BjIhhwUaDnonyuAV4mhIhOy9ZzDcC0Nr5Hfs6MCxDYEhFAWcH38JhGZAvhTfytV1f2di1Rex7q6R0sQhDMvLS7cVVARBOG4oKikheiBQRXmCGPr+iseQ7sWGaYcwfK4qROvDm7WICn6rea554fkYdZwgjMm7IWIAByBHjo5SwhmexSh+6ka7B0QEa0DPyN/QqQ9lqfctGqCV7TNtr40qODe6cGP1aGcrZoacjA9cXs91FP7dHynN6NG9w1AYxZAuBwNUEeuVCXBs4Xp0BK8VzL8DIq++bgufXV3gmVSlLdOrk63WE8KcQ1FeEYZwUMjNY/38p6v3Dx4lf9cu7sIqsiE3EBiJnpLIIEaoM3guivnS/bbPHm9tfqbsLtVyX8Q0byhI5CCCKDgZ+opw4Kk/5MJRMzC9sxxEDMsQZqHko3DoD4VciDA1M8I2Dcug55qT8GISBKBEfbSQBM9ivL8d7k9lPgfhw9hOVyFRTqFKsH0U1fRji9d30GvffmURfXkUSAytjDofJuUDRTFDCFHUyt3G0xg8U+raFiQrEKDgkmUUsEmM2pIQRzbo6Bbmbh2NSdu2balzZ+jTAu+99x4tXLiQli9fTl271uSlmzlzJp166ql08803c6LWFIdFkFjLYerggx0rxRjcKrEDU3Mm4FSAlwka93rIRkweG3Fi9KTQXMeNuHFbcxiJtBpJ4El0ckLFU8iUYBMT4Ir3NyaxxSSh2NkHQ8zj8DL24stY6Shqxx8NuAxwjfXnGJfxYuUWGHX2QUiYkwHqWb0mskxb8JjBvBOY9FeA1xd4XaWFIsKkH4yXEOTzcAxFw8OkjeCioYojpTifOuqrhWzgunA+xatFSzqLofgwuox4C+G60b10fvu77k8fiGx+TFoLCVPlNDBgg2jEY76VIvAyAtGkZh8whAY8HCrsPZP0ZfAYoAAsSCupjM6PohndYcNOAvcEeu7J71hOGD0E4Bj60SMAyg3LVS+JuMT6l62NTID7waePeoOA6P8bwnPwHsLt4DNAe6+EoOIThl+GNGEZPezS+kLFBkMpZD3sxzQiju+bWJ696b16GLeJ74+oqlembeKxgWesUp5cG6zwgccJvs9xEAHDWaOMVPRYwZHuGLxnLEzEjM918HCR4HN+Y5GtYeld7xCqZSdoZNca2uK+Eqqm27wfimGru86h0Wx4z5vyPNSswH55NICdxD/TPjTYmG/kJKVKeyx3basy5S7B96RTrJCn4flS3JwPpS0uhSDT307HAK8VU5iLAJ6/isenQ/439Rjg74Z+kym/id4ep74u9veV/alb2Lws0+RMnz6dbrzxRurRoweNGTOGrrjiirpQl/nz59OwYcPqBBDB6NGjqbKykr777jvab7/9+IylMCyCNICYyjImOiFgimKqpKETb2nLZJezTCQBvUpJkRo61FCw4lBSyh+j0Y0j7Tpo5JhGwnTDDDsX4E2DFWUUOULLf4MdDT+KmRBeZa1db3TFb6xj68tTqyehQYshAopbP+SlsdDrrDahcx3ouYCikHYPeTdBCWacgEIUdCJ9JVpHFUfR8dxAKKFPM2zRiy3qeOZFXEGsb3+pmUedQ908xQCId/jswlK+TiJzAO5Vp9LOSpgkTHOq0uQGvfqRsZ2Q7yTZOAmjCoaKQK7BCmIxlGF3epc5hcQ2FFPlIwy5bCyCmYGaZ2r4oxvtJmMUDTuTt4hb3C4f7zs/GX0GJ0EDDWAng9qEySB3EqhMA3ixiEIxNFnZZyXJacCdcILtjCUBK+KU4yVe3K7L1M5WqH2EyCs/8a4jXHYXycjIkJ94uPjii2mnnXai/Px8+vrrr2ny5Mm0ePFieuSRR+T0NWvWUKdOEQ9DgZhXiCRiGpPasAjCMMkiwbH3SkhWEkQQNArcGghYmcTJHVgvB2wbHgVGpnIs5IzQu8CXIuTF0Zfxg0ASglFb9F5RhBJtXzBBsHKuYQTXSRRE7yTFmIPkxLq3Ax4PD3g+4Eh7CEewtTw7KLZYG0Fgwk6s7u2A00DcUCpZaOWHsTpLLNUvYsHNNRmLd53r3EYGLzomsTSmUB6v8JFSCMNShMI0hJZcSrepiEX4MOHkVdEc97kpBKtUPk6tkKDllZ941yEQnhrIlClTaOrUqVHzi9+uv/56x3V+8803tMsuu9Cll15a99t2220nBY5jjz1Weoe0r/XmtssHJHKCuM0TxCQPFkEYpoWACQGbC0qCxnjXtaU6qSKQ7k6M4WuYswB/96RpoxTw0nQziu1olBU3vJJELCPnJppK3GAYhmEYpnUj8nLk5kY8ZU1eIBdccAGdcMIJ9VaFsWP33XeX//79999SBBG5Qr766itlno0bN1J1dXWUhwiTerAIwjDNFHTDT7QB2yzBEqhaDDB6TGD4Bf6uH08cUQ6Bxwfm6UEPD7deBOjhkehcNPGiCDcxjMqx8MEwDMMwjBtC5JGfeAgvLwQQFEFMdOjQQX5i4YcffpD/dulSk9h6jz32kAlQV69eXfebSJYqBJidd945pm0wTUd8PkgMwyQNIXrgp9UKH+GPECRqP8KAVz7VgbqPqAQU/uheFfiReTBqP96cnLqPLz+v7hN3830+5ZNs8JjFgvD4CH9iIRWOAcMwqc36DevpxtuvpwOO3I+GjdiG9jl0Tzrn0jNp/tdf1M2z/xH70KBd+8vPdnsOpYOPHUWPPPWwdFMPs2LVCjn9tz8WKt+H7D6I1q5T4/nXbVgnfxfTxXw6/75gPG0zfCD9+EuNkVRHbd6VhX8spIsmXUgjRg+nbUcOodHHHEjX3HQVLV662LifYh8ef/YxSiVSsU1M8w+HiffTGIikp3feeSf9+OOPMg/Iiy++SGeffTYdccQR1LNnTYW4UaNG0ZAhQ2jcuHFSIPnvf/9LEyZMkCV13QgyTHJhTxCGYVIPhzLJrn53qGqklHl2CifB5KwJzt8SWa1DCE0LSgLslprKHmJUh+O2GYaJRggQJ55xPOXmtKUrLppIg/oPpkCgmj778lO6/rap9O7L79XNe9HZl9BxRx1PlVWVNP/rz2nqrVMoJzuHTjj6RMdD27FDR3pt3qt09mnn1v322ltzqVNhJ1q1JlKlKYz47YdffqSTxoyjl19/iXbYdkdl+keffkgXTjyf9tx9L5pxwx3Uo3tPKt5YRO9+8A7d/cCddNe0WY16qquqqyg9zb7aWFNRHaimNG3ggWFSGeHN8cILL8j8IaLaS69evaS4MXHixLp5fD4fzZs3j8477zwaOXIkZWVl0dixY2nGjBlJbTvjDhZBGIZJCZosQabbBJWNJHw4bcNyoXugB4vuOeF631IU4dF0+1lplJ5RRVWV6fT4Q8luEcMwqcT106dI54qXnphLbbIiIYwD+g2kY44Yo8yb3SabCjvUlFEfc9Tx9Nwrz9LnX35Wrwhy1KFH09y3XlFEkLlvzZW/3zfnnqj55775Mu2353504rFjacypR9NVl19T17by8jKafP1E2mfkPnTv7ffXLdOjWw/aftgOtGmzWtEizLizx9LK1Stp2p03y4/gj2/+po0lG6UXzLc/fkOlpaXUs3tP2c7DRh+uLCuOR1paGr027zUa0Lc/Pf3Qc/TfTz6g6XdPozXr1shtH33YMTTp+on0zYffU27bmlHr73/6nmbeezv9svBnys/Lp4P2G0WXnT9B7o+pTXYIj5mpk26g/33xifTQ+ffJp9P5Z1xI195yNX357Ze0oWg9denUlcYeexKNP/HUuuUmTZ1Im7Zsop2334Uee2aOFE/+ddCh8piGRRThlSO8aL78dj51aF9Il557Gd1530w65YRT6dSxp8l5Nm/ZTLfdfSt98Mn7UgQbts22dNWlV9Pggds4nnumaQmSV37iXUdjIKrCfPnll/XOJ7xC3nrrrUZpA9O4cDgMwzApQbyhGPGG08QbmtJUoS0ij0j4I0QP/LQERg3z0ZjhNf8yDNNEiGoGobIm/zSkWkdJaQl9Ov9/dNKxJysCSJiwIR+9axZ99d2X9M/if8iP1awM7L/3AVS6qZS+/fFb+V38W7qphPbba3/bdc998xU64pAjqV/vftS7Zx965/2366Z/Nv9TKVycMe5M222Z2jz7tvuoc8fO0pvls3fmy4+gqqqShg4eRg/e8TC99fzbdNz/nUATp0ygn379UVn+1Xmvks/np+ceeYGuv+om6UFz8aQL6YB9DqLXnn5TCkF33j9TWeaPv/+g0y86jQ7adxS98ew8uvOWWfTdj9/Sjbdd79gmE7MfupsO2OdAevO5eVKgClkhufxdt8yieS+8S+efcYEUL95+f56y3FfffknLVi6jJx54mm6dchu9+tZcevXNV+qmXznlClq3fi099cAzNHv6PfTiq89TUXGRck7OuuQMWl+0nh66aw7NffJ1GjpoKI0/7xR5DTGpQ8jyJOTDMLHAniAMwyQNpVIKeDjEIoQoy2sJRxXvCUiaiuEo8SYp1XOMtNhwFrehSk7HJsUSwjJMa8djldOAv7dr8u3+1f9nsjzRgoYdy1YslQZu3979XM0/457bZLiJqNQgPAqEe/u448fXu1ya3y9FjVfeeJl22WEX+a/4Ln7X+eLrz6m8olyGugiOOPhIevmNl+iYI46V35csXyL/ddvmMO3y2klXe/RmEXTq2JlOH3dG3fdxx58ihSERWiO8O8L06t6TJl50ZeRYzL6N+vTqQ1dePKm2PX3pz3/+pAceva9unjlPPUyHjz68zpuid8/edPWE66QHiPDqMLXJhPBOOVbzzhECCnrD/PDz9/TuB29Lb48webl5dN0VU+S2hLC0z5770vxv5kvB558l/8hj/vITr9K2Q7aV8990zS006ugD65YXniZ//v0HzX/vK0pPr6kQcuUlk6VXyH/++y4df7RzZRCm6QglwBNErINhYoFFEIZhkgYKBTX5IBoHtVxttTEnRzy0mjKwMYQJtVhBiGGYxICDuYbHcjipqQdKiTtx+rgz6ejDjqbijcV05/130O677EE7bb+Tq2WPPeI4Ov70MXTZeZfTu/99h16Y8xIFg4Go+UQOEGHAhz1MhOF/+6zptGjJIik0YCLWRBAMBumhJx6U3hPCG6Kqqkp+RC4CRIR/IIuXLaZhQ1SRazvt+4LffqWlK5bSm+++UfebaH8oFKIVq5ZTvz79G9RWvQ0CEZL00usv0qrVK2WeBSFQ6SEq/fsOkAJImML2HenPf/6o2Y+li8jv89PQwUPrpvfq0VsKJ3X78fuvVFZeRsMP3FVZb0VlhfQwYRiGEbAIwjBMShBvhRsn74KmCBXRQ2CsQBPkFGmBwslPy0KUXUS0dSsfP4ZpKixPlvTKSMZ2a/6of15h7AoB5J/Ff9OB+x5U7/wip4VYRnxmT7+XRh19AO0wbAcaMXxkvcsO7D+Q+vbqS5ddc4n0RhDfw1VkwojQCuFdEAgEpHGPQsUrb75MV1w4kfr07CN/W7TkH9pxO3cCjBOPPjNHVme56rKraVD/QVL8uOWOm6WYgGRp4UJCzNC1I0s76CHLkmEywrtEp0vnrg1uqx6yJIQbkUvkyosn047b7Sg9SuY89Qj99OtPynx6yJI451Yo5Eogk/sRCklPFREuo9PWEH7EJIeQ5ZWfeNfBMLHAIgjDMIwNDa3U4klTH6cc8hEbpzxcSatLiLq0q6TIWB/DMI2KMDRdhqUkCxGOIcJOnnn5aRp3wvgoI1skGTXl2BCeAicfN46m330rvfbMG668SURIi0jEKkJB7BAeEyLHxb23P6D8Pv+bL+ihxx+QCTtH7r4n5bfLl+V5MTGqmzaLxKahkPru+e6Hb+iAfQ6gI/91VJ3Bv2TZEurXxzncRgg6n3zxifLbrwt/Vb4PGTSU/vrnLykambBrk1tEfpEdt92JThpzct1vy1Y0zDOjT+++FAgGZMnhYdsMk78tXb5ESTArvEQ2FG2QOVG6d+0eU1uZpiFIHvmJdx0MEwssnzEMw6RKolaGYRjGyJQrr6dQMERjxh9N//nwXSkACM+QJ59/go7/t5p/QkcY34uXLZLLuUGU153//tc05sjjbKeLUJjR+x8svUTwI8QTUeHk488/kkKNyFnxyWcf0zmXnUVffPW5TFL6y8Jf6LZZ02nKtGuN2+/WpRt988M3tHbdGiouKZa/9ezRS65DVHER+33dLdfISiv1cfzRJ9LiJYvo9tm30eKli6VXxqtv1SQbDQtCZ44/i3785Qcp/AivF3FsRUUZUY3GqU1u6dm9F/362y8yh4low1333ymr0DQE4ZUzYreRdN0tV9PPC36ihX8soGtvuYYyMzLr9kNMF2WKz59wrtyWON7ieImQKHHcGYZhBCyCMAzTpHizsuo+LYlQebnyYRiGYRKLSKY59+nXafguu9P0u6bRYSccQqddMF56X0ydFDHW7SjIb09HHnIU3fPQLOlBUR8iLKOgXYFtRZlff/uVfv/rNxq1/8FR03Kyc2jk8D2lSCI4cJ+D6Lk5L8oSr5dfeykdMmYUXX7NJbRly2a65NxLjdsXSURFSdoD/29/2uOg3eRv551+AQ0ZPFRWcRl3zkmyRKyb0CBx3O6+dTa9/9F/6Iixh8rwnXP+fZ6clp5WU55+8IDB9NSDz0rPirFnnUj/d/IRdPeDdylJUO3a5JYTjzmRRu03mi696mI67rRjqKR0oyyR21CmX387tS/oQCeddSJdcMV5UqzKzs6WiW8FQgx56K5HaNeddqWrbpxMBx9zEF129cW0ctUK6lDQvsHbYxo/HCbeD8PEgsdKdNamZs6mTZsoLy+P9qUjye9RKxowTHMBBQY2yJnmxIK8l2vDYYiGltZUWGAYJnEU9iqgs+4/iTp16Ew+4lLUrZX7H72Pnn/lWfpk3mfUnFmzdjXtc9he9Pi9T9Ieu42g5k6QgrR2wxp66NxnaP1S1dsmYFXTx/Q6lZaWUm5ubrO3ta776kDKzInP1qrYUk03DP+g2R8TpunhnCAM0wJh4SO1cCrf29zwpteMGra6qjgMwzDNmGdeepq2HbId5ee1o+9+/k6WxD3puHHJblaDEeVyy8q20sD+g2j9hvV0++zp1K1rd9plJ7UaDMMwjBMsgjAMwzRhdZTmLoiw6MEwDNP8EGEuwvujdFMJde3clU476XQ6+9RzqLkRCFTTnffNpOUrl8swGFF1Z8aNd8hwI6Z5wdVhmGTSokWQadOm0VVXXUUXX3wx3XXXXcluTrPEm5HZ5KVGGaaloSZX5USrDMMwTNNy1WXXyE9zZ6899pYfpvkTtLzyE+86GCYWWqwI8s0339BDDz1E2223HbUYPF7j6HJjwaJHyy3pyjAMwzAMwzDJwCIPheIscSvWwTCx0CLlsy1bttBJJ51EDz/8MOXn51OLQYge+GEYvDy4pCvDMAzDMAzDMEzrE0HOP/98OvTQQ+nAAw9MdlMYhmEYhmEYhmEYm3CYeD8MEwstLhzm+eefp++//16Gw7ihsrJSfrBsE8MwDJMcPr86k9q3q6Cikkw6ayKfBYZhGIZpiYQsj/zEuw6GiYUWJZ8tX75cJkF9+umnKTNTTejplDxV1KoOf3r06NHo7WQYhmHsycn0UG6bmn9bFCKnU/jDMC0Nvz/ySSQej/nTHEiFNid9+/BhGIZJEVpUb+y7776jdevW0c4770x+v19+PvnkE5o1a5b8O2iTLHLy5MlUWlpa9xFCCsMwDMMkFM7nxLRkAoHIJ5FYlvnTHEiFNid9+/BhGCBI3oR8GIZaezjMAQccQL/88ovy22mnnUaDBw+mK6+8knxQPSNMRkaG/DAMwzAMwzAMwzCND4fDMMmkRclnbdu2pWHDhimf7Oxsat++vfybYRiGSe3QkPs/rKapr9T8G8ablaV8GIahVn1/fP/T97TN8IF0+oWnRU1bsWoFDdq1f91n1/13opPOOpG+/u6runkmTZ1I5004x7j+uW++QrvstyOlEqnYJiZOvN7Ix2m29PS6D8MwiaFFeYIwTGsGO7+hikiyXy6n3PzxZkRyHIUqK6jZ41Di+4GPArS6hKhLuwANrf0tVF7eZE1jmOZGSt8fmIcigeEYr7z5Ep183Cn08usv0qo1q6hr565R8zx+75PUv+8AKtpYRHfeN5POuuQMevP5t6lHt6bL/WZZlgzFFiHZyaI6UE1p/rSkbZ9xIBRyN1tVVc2/VmRwoCUQIq/8xLsOhomFFn/lfPzxx3TXXXcluxkM0yQd4fCH8w+0LITwEf4wDNM0eHw+44dJXj6KsvIyeueDt+nEY8bSvnvuJz0k7GiX144KOxTS4AGD6YbJN1J5RTl9/tVn9a7/q+++pMk3XEmbt2yu8yaZ/dDdctrrb79GR59yFO24z/Y0cvTudPk1l1JRcZGyrJj/0/n/k/NtO2IIffvTd7SlvIwuv/Yy2mGvbWnPg/egx599lMadPZZunnlT3bJV1VV026zptNe/Rsr5xpx6jFxffW3SEb8fOfZwevmNl+iAI/eTbRBizP+++IROPON46U0y/MBd6OxLz6RlK5ZGedC89+F/aNw5J9H2ew6jI8YeRj/8/L2y/hdffZ72OXRPOf38K86lx56ZE+Wh8uH//ktHjzuSth05RLbhnodnUSDR+WKYZk/Q8iTkwzCxwJ4gDMMwDMMwGpZNMvWWjhAYTPi8PiWHmtO8Xo9XqdJnN2+brDYxtfHt9+dRn559qW/vvnTEIUfSjTNuoPPPuIA8DtVPMjNrPCUDgfpH0nfcbie66rJraNaDd9G7L79f09Y2beq8Ki4++1Lq26uP9DCZdufNNOn6ifTw3XOUddw++za68uJJ0uukbU4u3TrzJvrhp+/o/pkPUvuCDnLdC/5YQIMHDqlbZvL1k2jl6hV05813UcfCjvT+R+/TGRf9m9587m3HNtkhxI133n+bZt92D3m9NaKdEIFOG/tvGth/EJWXl9HdD95F519xHr3+zJvkhXCMO++/Q7a9V4/edOf9M6XQ897c/0pvlu9++o6m3HodTbhgIu2/9wH0xdefyzYhQgC64rrL6ZoJ19EuO+xCy1Yuo2tvuUZOu+DMi+o9/kzrgXOCMMmERRCGYRiGYRiGdtx7O+NR2GfkvvTQXY/UfR8xarg0rO3Ybafd6KkHn637vv8R+9DGko3KPH9883dMR/zl11+S4odgrz32prKyrTT/6y9oxPCRtvMLAWbmvTNkcvxddxpe7/rT09KpbU5bKaoITxLk2CPG1P3do3tPuvry62jMqUfT1rKtlN0mu27aRWdfTCOH7yn/3rJ1C70271WacdMdtMduI+Rv06ZMp70Oqfk7LFrMe+9N+mTeZ9SpsJP87fRxZ0hBYe6bL9Nl508wtsmO6upquv2GGVSQ377ut9H7H6zMc8u102iPUcPp70V/08D+A+t+//fJp0sPG7kfZ11Mhx5/CC1dsZT69e5HT7/wJO09Yh/ZNkGfXn2kp8jHn31Ut/wDj91PZ40/m/7vsKPrjtPFZ18ihSEWQRiGSRVYBGFSDz1ZokP+AKYVXhN8PTAMw7RKFi1ZRL8s+Jnuue0++V14J/zroEPplTdfjhJBTjj9OOnhIISawg4dadp102lQ/0FxbX/hHwto9kOz6Pc/f6OSTaVk1eZ0WL1mlcw/Embbbbat+3vFyuXSg2S7odvX/SYEDSEghFnw+wIZsnLwMQcp26uqqpJhPQ2la5euigASFlrufuAu+vGXH2ljaTFZoZoQpdVrVykiyKD+g+v+FsdNUFxcJEWQxUsX0YH7jlLWK/YLRZAFv/1Kvyz8WYohYYKhIFVWVspzkVXrlcMwluWlkOWNex0MEwssgjCpBxu5DF8TDMMwTc4P//vZMRwG+eK9SLUVu3AY5MM3PklA60jmuQgEA7T3oRHBQ4gHQgwp3VRKebl5db/fecvd1L9vfxmOkt8uP+5tC4+Sf19wKo0cvhfdfsNMys8vkOKHqFAjPC+QLAj1Ee0T6ME64d/l3yFLeqq88uRr5POpx65NVsTDxC1ZmdGhMudcdhZ16dSFbrr6ZhluEwqF6LAT/hXV9jRI4hoOMQrV9stEk/WwI9yP8LwXnnUxjdpPFUsEGemRcCqGCZJHfuIh3uWZ1guLIExKgInmWmMcNsMwDMMkm4bk6WiseU2IxJqvz3uVJl0yWQoRyIVXnk9vvvu6rBgTRhj8Pbv3imlbaWlpFNQqdwgvFBHSM+GCCdSlthrNrwt/qXddIhxEVGf5eeHPdctt2bKZli5fWhees82gIbKKTPHGItplx11dt8ktot3/LP6Hbph8U936v/3x2wavR+Rh+WXBT8pvv/6mHoMhg4ZKjxGRUyTl0PPGJDBhL8MwzQsWQZiUgIUPhmEYhmFMiJCL0s2ldOyRx8lwEuTgAw6WuUJQBImHbl261+UaGTRwsAzh6Nq5ixQinnrxKTrx6BPpz3/+pPvm3FvvunKyc+ioQ/+Pbrt7uvRUaZ/fXlZw8Xg9dTa5CI05/OAjaOLUK2jSxZOlKCKEiy+/nS9DeEQ+Frs2uQ0tEdttl5dPL7z6vMwpsmrNapp5z+0NPi4nH38KnXzWibIizH57HSDb978v/qd4h4gktedcWuN1cvABh8iQpD/++oP++OcPuvTcyyipsOiRUoiILJEcNd51MEwscCBVjHizspQPwzAMwzAM0zi8/PqLNGK3kVECiGDU/qPptz9/owW//5qQbe20/U50wjFj6ZKrLqY9DtqNHnnyIZlj49Ypt9G7/32H/nX8wfTwEw/KKipumHTpVbTDtjtKceC088fTTtvvTP1691fCQ0Sy1KP+dRTdevc0OuTYUXTe5WfTz7/+RJ07dTG2yS1CiBBVZ8TxESEwoqrNxIuubPBx2Xn7nen6STfQY88+SkeOPUwmbj117GnKfohktQ/c+RB9/tXndOz4o+m4046V83er9YJhmDAiH0giPgwTCx5LD+Zr5WzatIny8vJoXzqS/J60ZDeHYRiX+PIiseDB0tK4j5s3I1LeMVRZweehifANnUulFSHKy/RScEFNdQGGYRJHYa8COuv+k6hTh87kIzXPB9M0iPwie/9rJF15yWQac+RxTXfYcdA9Qb3/a266ihYtXUTPPvx8YlbYyglSkNZuWEMPnfsMrV9arEwLWNX0Mb1OpaWllJubS83d1hr/0QmUnpMe17qqtlTRE/s93+yPCdP0cDgMk/Kgp02o3L4cH8MkQvhAWpLw0Zxy7jx1dgYVFpTT+uIMGntRslvDMAwTB96aUeqFvy+gRUv+oe2GbEubt2ymex+5R/5+wD4Hxp7TIpYxzAQIH3OeeoRGDh9JWVlZMhRGlP+dcuXU+FfMtDpC5JGfeNfBMLHAIgiT8rDwkVzQI6KliQOthVQXPhiGYVqyCEJeDz369CO0eMkimVdk6OBh9MzDz1NBuwJqbvy88Cd65KmHaGvZVurRtQddPeFaGnPU8cluVsumrtqSN2EePKlA0PLIT7zrYJhYYBGESXnYEyS54Rv6upqTVwHDMAzDJI3aai5DBg6huU+/Ufc9ZlIggv3uabOT3YRWR7jf5RGligPUYkhETg/OCcLECosgjCNo8OrfQ1VVTXL0PFngidBE4TDNUXhpqvPBwgfDpO4zmu9PhkkhUkC0YJo/VqC65l+r5l+GYeKHRRDGEb1Dbepg+3Jy6v4ObtmS0KMaLN6YsHV5/GlRLxU7movwYTKGPGkZjbYvTZIwtM71sxYx+sG0CsY9WEmlFUR5mZXU3GkKrykWPZoQfC4142eSyIfPOfGb7GA31ZaYFkRruUdlTpB4S+RyThAmRlgESRLeNm2U76GysgavIxlhCc0hFMJpZNSTnmbbiU3VfWkITqJOQrfTFMeqGRsYTHz8vCJEq0uIurQL0dBmfjBbwnOFaXnPpc1FWylQFaQQBbk6DMOkGOK+FPfnpg1bqaVjJSAxqlgHw8QCiyBJIhbRI6YOdgwjV06hIMZtoriQZDzparktC/YhEcc9VcHzRiGr0cSRphJbmKahOQibTekFltiNtgzPAaZlUbm1ir558yfa64QMmZjTy2VyGSZlBJDikmJ5f1aVNU2IM8O0VlgEaenE0PGOJXwikSEr8dIcQ1lSYr/ZYGuVtGThI+niHQsfTIry8WNfyH93PXx7Skv3Ew+mNhJY0lbQCkIcGB3dU8H+GhDhL8IDRAgg4fuzpSNCYeIOh+HqMEyMsAjCpDxe8OxoquSfrZIYDLZ4z43JC8GXl6fMFywtNayAR9qbBD7ODNOiELb4R49+QZ8//y3lde9AXm/EEGmtAwmNgTdTKzFf0QQl5jmnVrNEiCAiBKY1eYBwdRgmmbAIwqQ8FoR2MKlFvKKUyQvBKHpErYBDDJoEPs4M0yLD1YTBtbFITUIc2rwlqQMPSQldayQwaXxjJI5nUhMevGOY1IdFkBR4QCa6o9HSYvybeyeoJRNvKeEmqTTDMAzTTGmKd7j+7E62x6UHvFKsZt7vSUpb2BMk6ST7HmoucDgMk0xYBGmBD8hU6gAwLZt43aZZ+GBaMjwayDQHUi1heCz9o1Tq96Agk5QS9ey5xzSnErlxJiTiErlMrEBAPcM0D6Mi/GGYxrq2+PpiEmXMhT8MwzSy90P442Yep/nibYo/re6TaITwEf4wTEvxBIn305jMmzePhg8fTllZWdShQwc6+uijlenLli2jww8/nLKzs+X0iy66iKr4nd8sYE8QplnBxgTD1xbDNA3sycI0G9x4PzSRhwQLFAzTMnjllVfozDPPpFtuuYX2339/mbz2l19+qZseDAbp0EMPpcLCQvrss8+oqKiIxo8fL+ebPXt2UtvO1A+LIEyLzzvBMEzz4Zz9/BTyBMhr+enzt9NbtfiZ7Jw5qXzck50Dojkm70z2MWMYhmkuOUECgQBdfPHFdPvtt9Ppp59e9/ugQYPq/n7vvfdo4cKFtHz5curatav8bebMmXTqqafSzTffTLm5uY3SNiYxcDgMk/J4sjLrPgzDtGzO3T+Nph5T829rDyVh13czwogPf5KBED7Cn6YUMcKf5njMGKY1CdjhD9M8w2G+//57WrlyJXm9Xtpxxx2pS5cudMghh9CCBQvq5pk/fz4NGzasTgARjB49miorK+m7777jU5/isCcIk/KENjWDknKcjZ1hWhSpUMGLw1HiP4bNDV3gwH2Lez/xPcXJMxmm0e4PDolqejZt2qR8z8jIkJ9YWbRokfx36tSpdMcdd1Dv3r2ll8c+++xDf/75JxUUFNCaNWuoU6dOynL5+fmUnp4upzGpDXuCMClPMkbcGox4YeKHYUw0QWK+RIwaJ6PNqZrUNNHeKG5H5FtNYtUYrq+W6tWA+5XwfeN3FNPKwfdi1LsxGfdHK3y3NpYnSI8ePSgvL6/uM23aNNttClHD4/E4fr799lsKhWqug6uvvpqOOeYY2nnnnemxxx6T01966aW69YnvOiIniN3vTGrBniAMwzBNSRN1sBJqQDVhp3BLhUUZZTX/Mq0EFo4ZhmmKR02qiaat/NlnJaDEbbinIPJyYA4OkxfIBRdcQCeccILjOoXXx+bNm+XfQ4YMUdbZt29fWRFG0LlzZ/rqq6+UZTdu3EjV1dVRHiJM6sEiCJMQ2G2bYVrAvVsdsO2c+fLy6v4OlpY2antG3lxBq0uIurSroKGNuiWGYRiGYVoCQgBxk4hUlLEVn/oQnh9C9Pjjjz9ozz33lL8JcWPJkiXUq1cv+X2PPfaQCVBXr14tc4aEk6WK5cTyTGrDIgiTEFq8uzbDpGBlD6xQITCGjDnEOru5d0NbtrjKWZDScD4EhmGY5k0zeY43x+pRySCVq8MIQeWcc86hKVOmyFAbIXyISjGCMWPGyH9HjRolPUXGjRsnpxUXF9OECRNkWV2uDJP6sAjCpDz8MmGSXSrUDb6cHOV7EISDxsJ158plZxH3AdvvWuhopA6qt00b5XuorKzhK0nhDjPDMAzTcp7jLHw0fxFEIIQNv98vRY7y8nIaPnw4ffjhhzL5qcDn89G8efPovPPOo5EjR1JWVhaNHTuWZsyY0WhtYhIHiyBMysMvEyZVhY+mFj0au5JR3PuAHdREZtqPRfRgmBSuLuPNyqr7O1Re3uTbb5VwFbcWhV5+tjn0E5jmJYKkpaVJQcNJ1OjZsye99dZbjdYGpvFgESRVaCYufqnUiTN5iGD+gqbIYcA0LZx/Jk6a6vmSwO24DvthGJckPYwrxIl/m5xm0rdqCZi8ChMJix4Mw8QDiyCpIlQ0w5czCh8mw1TPH4Bu7cHazMsNwd++fd3fgaIi23lY9GjZcP6ZliWmuoFFD6al0ZgGnCmRcbIHLloyTRa220ye8c3GM5JJKqnuCcK0bFgEaQgp/MJpLqNtsQgfyvoCUL2CaXCVj6bqhLG3RpLgZxTDtHo8fkPXzsPGQmMJGo0pfCQ7dKupaC37yUSwLI/8xEO8yzOtFxZBmGaFp01kJIs4zCU5HhIuDG321kgtmqco5akbuXY9at1MRkkZpjHBwQK898nwu/5MiMmroQXdeynneabkMmm54kC8nsIt6/3HMExjwyJIihO3+2oTdUya6sUSWL2mSbbTokZRXF4DTRHDm2haY+fGyUAxPS888LsPjaIknWt31X6shj/zGvEZ1xqvNaZpDL5EJ/5taEhoQhJMJvLeM72zUjixKb5/E23Mp5wo00jXuulYmd5r+Ls+Tfmdn9cpS4g88hPvOhgmFlgESXHijttNoU4C07gY3UddXgPNRfhoSZ2bWEq/OnWITc+LVMuTk/SEdrox5eJeae7XGpNaWJWVTbIdN14dSb8f3d6HKdyfwfdvIr0YmjTfSCMRr8hnFDc4r02zh3OCMMmERRAm5WnuHQCGMcGlX6N58swMys6upK1bM2i6uSpdfKSwMcW0Ds8cq4mqw/A7k4yJ2ptL3glPeprts6u5tJ9hGCYVYRGEaV5hHi1IBInFC6Ax8bVrV/d3sKSEWixJjl1nUc+Z7Xt6qbCAaH2xwVuDYQSY/BNFkOaSmyKV2+aGFA5NMeHJyFC+W/DObczwpET2gUIsfDAtCE6MyiQTFkGYlDfyWpLwgaRaR6tFCx8xdNbxOk7k9ZiU67m5GIYMtfbz7rZChPH52Uz2s9mTYsfZ17atbTiKk7jh71hY93dg3fqEtcXfq0dkvctWujtuDvdqosNr3GwzcbmdGMYMh8MwyYRFkJZCCnV2Pd5IkqJEOPyaOjHsCtp6SIbruyct8nj0wPZTLb9GczRYmCYiFsMmySPi/FxnEkmo3GycWw7T4iIQNN6DxkGiZDyj49ymJwsS6rIIwsRyCXKJXCaJsAjSUkghI8eDYR4JMFixU6x0INgtNKGkcnWYZMT8Y9I1vaJKqyBJwup7vwYpPYOoqpLj3ZMBCn6UYt5qDGPC6C3h8OxqLA8La9NmY9hQLJ6Abr2jWpv3aHPN8cIwTGrAIgiT8i/GVAsbSdn8HnEarbEIH76C/MjyxRuppdIsvT+aqbB6xQtVtLqEqEu7KhpKzYAU8sJrCYYNwzR3lHAcl2VcnWDjno9LS/YEESEx8a6DYWKBRRDGdcxnysV9ujQ+TLHCicSbl9vkIkhUzgolazw1DVWpmd8Cw2eaa/UIppnQAoQPhmGaxluBYRhSQuatOOPmm6bOFtMSYRGEcSSlRI8YjY9GSyqmbKTp3TB1t1p/YYe6vwPrNzR4fW7FIvT+oGDTG4DezEiGfw9UiFDa3AI6nijk4Eig46hgKnklpFJbGIZhkvC8S0RoqeJNAs9/FvcZhmFih0UQJiEvfR94QqA7dWsZkU9kZvmY2xCD8OHGe0X3ODGFvRiTlya4lKLJnTjZCR1j6dA6uUbHdK/Em+gOzrWvY0RUo+pq43WWyKS1NefQ0/hjOyzQMCkK5zloPNz2RzA/lv6MNorQjSn0hqwW34diWich8sj/4l0Hw8QCiyBMzPhyI54DnnT7cqL8wm4+mDp3useJKQ+I8Vw3kRdAqgkf2JEmD1RMCgSaJrFbDIY+nuvg2nV1f3vBS0gnkeddnsO8JnBuZc8UJkWTUHL+h8bDbX8k5RKDp7JHLsPEAVeHYZIJiyBMQpJF+vLy7C+wTh2V7wEwrFK5PGpzpzG9IqwtW6lVA+KCYjBpYlFwa1mzLn+ohOA0VinJFpY3STdW+NnV/GARgkll78FmX66dYRgmRWARhGlUgkVq6ISvXbsGVyFg4aPhSWsb0ysiXiPBjUCje0jgdzfXgy7KJbKz6IcwEQuEDqva1+DROz3UCIUUJ+O6sUKNTPBIpPl8OB2b5vjschXWxp408WM6nk10TzPJQcnvAWEu+OzX37EYkuPPyW7wNvE9E0uJ3nhx9S5jWiWiMownzuou8VaXYVovLIK0RJLQWTUZmVGj41x+MWGl8xLRmUCDx5OR4SoxKnbQYuncuBFo9E4gfndTlteCHBaJJhZvJhNOHVJXx1O7v9nzgBJamtJ0PtzmdUkl3BpCJuFGubYcrs1Yngm4jJMx2FjhakkJfzC9m1n0aNF9sHifF7Hk/mos4cN1fqsUEj6UMNVGvPdZ+HGHqAwTd3UYLg/DxAiLIC0R7kQ1CxJtPMXSqVcMnhhGrePt3Lg1zHA+FD6wE4YeJrrYZozz10ddDfeREtaVAcn1AhAyUuFwLGDED9/YWN2mZidgRAOnoWcMhKYEiorUxXt0i2zyn8Xm9jiIBXXLV1TCPJmuRCxTQsFkhBg0pjjRXISPWAwh0z3p+l732d9TTuJlMowkJVythQ1cmMqycqhP0+BWMIyJFPLIinp/pWieHcSqjuTkSjhwbpTzzt5dDJOSsAjCNOloKpM4okJGIFEtJTsfRYINM+N80KHSBQF3Kw41ufdHTEAnSq9wgFgbim2NWSWcSOuUu7mn3YZXmcQ3FKhke9LSbJPGCvEqO91DbTMt+W94v71pfuPxUHKXOFxPSlw9HI9EjgQ6hag1F+IdNTZdK8GNKZa/oKmeiy6MVg+In1Yw/jLmSLKNztZIYxrAjSqwNJDmeA026jEznFusnujkEZ3ssKVkwIlRmWTCIkhTkkIKvlvcih4trTxpMmjoaEnUPJVViSuVCm3RK4OYXuCxXANKpx4SrmLlIadwK/Rkcet+6vYaMM2HbcZKL1GAca+0GTw5vJkZxmWsqmr7DhEYTDi6XrO41z6/SDaIEHF2AhNR9tqCZfTRxC+uzaTCgnJaX5xJYy8KJSy3Bnq2cO6UJNBM3nnJ2G+3RmJzNDpbPbFc9w7CSbKFj+bS1zOSBK8Mt2HgrUX4QFgEYZIJiyBNSCop+K5FGacXhqFKRiqTasJHPCJI1DH3J+4c4PZdJ7CNoUNk6tTHksjU8Z5CN1XTNaBd66b53BoiJhSxxuX1iCNEyjIul3d9PA3PBH+XznV/B1avoYYSc2e5tj2+fK36FLg0uz0fbkN6GgvO19I6SWXhnUnRez2FBcNmKXwk+di2BA/BxoITozLJhEWQBhBvXKMHXbqrVIPL36EgrsRXjfYycJonhpdJIt39khJn2ojePMbOkmGbUfscCjV4tAar9SjHsxJGzbWRek86hDKAJ4NVXGIbYqCHQiheCW0hSdlmCEvQY41xm5gFC0f30asi6HBuMGkqbh/XpZUC9rSLuLOGVq+N/A3GuA/3S0s0i+cAf9e9MkzXdJONEBmu6cCaJIUD1bbHlAC3Iblw4u28m55d/o6FdX8H1q03bx+9lrjsd8qS6PcKCx+tEHx/JbhCFFY+M4nbjVkdjWk4zbFKGMO0BlgEaQDxdoicOuiNJXw0lVDg2k03gcZco1YOMMVeJ2OExm3eihiuocaq1qPkoNCMT+V7I133egZ4DwgUVlm5fW4KLaGjUmGmZFPdn978iHCkLKGXLgQhxpsHITRtIiKIrwskXBXtgbYpyVAhNIZyQODKUEvsetfA8QThBj0nSA/hwWkg1FptI9vxrCmyF4706xPXhcdc91JavsrWYPBkZZLHW3NUxb9hD5Tg+iKjV4cHw3McxDeTCIIiBoYjBdZtMOdtgN+DIP65hTvFqUsyQkmSEWLg5L3p6hhwskcjeA79Pbsr0wLLVrg8Q4Zz5eLcJEP00MMkvYawURxECW3aYg77cSEcOJWYR/zt2zc8NCWRz4EU9uxJNlwdhkkmLIK0QBpzlNHNKETcNFXnysmrQ0/EWA9OBlcqZUZ3AiugBIs2Js5jx2VHJZFECY4mATKWpJimyz7iIOJ4feE9FNK2H+/1oVzFkMw1odeg5pWBHjBGoVe7p/2F7e29J0qIpsytpMogUYavsi70RjfYUJhUyjzjfJrYo4yOwjEIlUbW5UFvIr20JTxL/YUdIrOBQOX0TFQSs4KI4+Tlkozwi2Q8r5p9noEYcJvkVDk2kE8o3vdi3OeWDTtXhDQBNxbwnkRBP6b3VyOh9zVDsSQqbyBu+xIxJU0HmksfrvmKIJ6418EwscAiiAFfTjb5POmuKwdgRwVHJi1Dhy4WcUI3BEwP48YcZUyk8GESa6L2M9BIIohDJ66hholTx93tS1Op5gEiDBoypnlqZrRsjSxMQqkbhnjcLagog50L7KxHGYp4DuGYuTXyMFYWl/G00cq24ihTKGhfehbCgfT8KDj6hvktLAjB0UvneTtFDF3aCsYk5qdAzw3tTYwhJMooGXgbOI3GeiGjvBJaU7rJeN0piVLBOFeSglKwwaKpk8HmqtSodq85hY28+l2AVpcQdWkXoKEu7iFTm6OWcfNcdBmr7dbrKt5cLrHQUOFDv79x1NZqohwWsQgfjSb2N1ECc7fvhdYiCrVUEhEOpbynYYCiuaN7bCayUlciwfevqU/PMEzzg0UQA6JShcdT5TrRERpAjRVi0NIUaHSXxFGDFpch22WnGvfbdAzczKMbc2jkhDCsQjPSlA4ItFk3ev0osKBwAh21WKqueDAHhnYPKZ0lEBHQQMD7Qy/tjO6wmNhTES/1Si2YVwSnofCB96SWx8Tfs1u96/J4Iu2SoKDQNtt2nzGnihdHhsUxaBc5Tp4tUNEGRZDacJM6QEzzoviEohCEBvm1sB8Ukjwd2tcfJqMtg9uXolCV2FfxPPWQv2uXmvk1oQVFslgStaInBwoaiTasG/wsS0blAreJZVPMW6OxxH635WrjpTGPYYNzb7m87mIp0dssSaAQhs8auTp4FpuOod6/xBASfE81Wf64OFHevzAoEq/o4eRlaqoWp/cNElkinmk4XB2GSSYsgsRIi8juHOeLXjFMwQB0KwK5dVHE0W3FqyAJJYdNL1Z/t67KfKENxbbzxbJut2CSUzwHysiuU4fYcDz1DpkFhrfivYEeUC5Hv8JGriCwarVxPlOiVR/mc8DqH1oiTwvDUaAjrwgfmLBUgEYWrFsRQdqBV4hulKEokmZw98QEtAIUIdD7xCC4RokD6I0C5z0EooMXQlFq5gNLD0JDlMSwuIxX815Bb5oN9ve03tlVwuo2gneZOE95kX0I1Y56RrUZRBlTiB52vPXnTQj2zWRY4/2UCHHbbQLXhgoPTvsZCyYhqLUYAm4HG9yGhiY0hDQGQd0VLt+f8QofzSasIIH9iViEiqj3Pw5qUOqAgoLuSYnXID5vMXxSFyAaek04XeemPpST6BHvvepWfGw290ETIN728UazcDQMEyssgjQhTg9IkwHrdn2YKFB4sdgas1riqlhG0nAdJsPUaT9jiVc3hgwkISbZ9GINrIREjw447X+8whpeN0piUievDMynYDq3kNRTD2VArxCl6onDNrE9XvAqUEJjsBqMwJAYTvFCwDwPmsHmBXFAOR7QqVcSZMqV279aUQTCtuhhP2icYicQw2ywoo6cD0YJ8d7B8+k1eMXUTPTWG3LiAaHDCeycebBdevgLij14bjSvI8RY1UAKVGFPEKvunvDq1YI0DxjbEUcHMQCvAdMyynl28B5xKh9sel4qMf4YMqM9A/A6NokTTvsZS5uTkbTV9M5IZDWxWNBDhVAEcGskuZlPDwtQJ/oaJRw1Gce2NRp8zSXkIxbc9uGU55qm+6cUGFIbA27vo9Z4HzBMKsIiiAHhFu71pBtHv6IyYaMBlZFuW1VCUcO7q54D1saS+gUAzWUVH7jBzdX1exdonVu3BoNxpBRUcywhGli6PKHxsW5GUhyFl0aKHTcapno1kk2bbTtATh1sV8kVdcOwe8SrwoOjMmjM6+ETICLg9tFDQwldENMG9Y982QzeAqbSuw6CBpbixdF+qwAqm8jGgUGOOWJQBACj268lqkWPC2/XiAFIlQ7Xg6EUrycXw7g2Gr2BUCxQ8oug8KSV1fW1h5weW+DZgx4r2FHT8sKgqKKcQ6yIo4mKyj0JYTtKzhnwvNDPZwj20/S8dJ3PSFyf2dHiU3CFKjIm0mgLGe67KEFivWFkEXK0xJKvxHVuiBieXaZnZ8ihoo3pvRBvwlUn3IT/NRkOoYCNRVIMY4dBBC7hnDg8kNtJgiJyDAM5eE3GMniW9CTI+BzRytI31sCW4oWni/iwzRYd4pWicDgMk0xalAgydepUuv7665XfOnXqRGvWNDxmXJTO9HjSzMKHZoAGVq6ut1oCvrACS5a66oTh6Lxu9JqED1NHXkmaqHVwFZdqn3k0WYkJxlEpwwiVW+PHybhXKkEY3MMdXQ8xh0Fx4kQQ3Bd9hM4LL3flHCgu8VvNscOQ8FNx4wfjIyphKRi6iocE7r8m3qHngHJ9QmhKlAfR34sjy0BFGYJzY5WuNSZjRRFByZUBsfieDVqHThEBIBwkC/JrYK4LLcSdQoZHXTaEn+gdMrgOrSwo95cG13TngsgmNK8MTyXsJwg3lh8alxVZvmYiCAB5OfbCB4bDaCVyqX2kw23h8YBlPFu1/czsVPent6LKdt2Wg4eMB9rmw2OA82nPAU9RqX1pYnHMiyAnyOABNatavc4ovKBwhGE/eo4XDwpj2DYoOewF8TCkCS/K8kAsxgcKVIr3zoqVCc3Jody76H0Cf/sLOqv7Y/AgirfSDLZfNzbw3eSB9x/mD2gyzz+HUMBEhsHiuYlFFHMLPtdR8FO2ow2wKInKYYDB162z8XkZgGpUqUoivGHdgANEupdoInPrxPLswT6Ihe8VLTTTzXXotC84zQv3N/aV/V0i7x65DhgMxGdHLCKhkkQeclX5O6tl6S3MUZLgSl2m0Ersk1klpS3SS8g1HA/DJJEWJYIIhg4dSh988EHdd59D9QUnhNdGyFNlHP3SH95K5xkeasrDD14qWI5UH6nFDmIiR9ycHvBuPUEaqpQ7vUhjSbIWS6ehsV5siNtkW04vOdOorWIgKJ5BqtGtZI3HaSg0aJ4PHgx1gU6tv2/vyHpzsoxGL5XZJ9z0QlJQK0PzVgiCAZrf1t5o191SccQKRATv5gr7ZfTrDnN6YA4MuG8tFB3Edx+IMlUB+22iMY3HWYACRSV4UqAopHfCUbCC42Flpdtu01usXU9YFQeNFPQAAq8tuQ4UJDC8qWSzfR4QJ8MBjQysaFChGY/57eyPoZ6ro/Zcebqoz0svnBsq3Wrv5YO5RuREvCdAZPzjb/t8MZrBhAYHisZoVESN+sI1ic94vA9de+HF8OxTyvqaPP8cnknxjhQrQjGK2Zq4kMhntJMXg/KcNiRYxrA4pypGxlxV8eaF0QQJHFQh9MLC0szautArzRSq6ZTPwZttP9jh5OWZ0NwncZZbN/Ut3IoeboUKV/usJ52F578pLM6rPaPx/WfKnaUb2gh6Ibs1tN2ESylCs3ac8LiJQcUw/g4R4T+4Tu3z+PLtc0XFkk9JCQmGY2ZhRTk7T9VGIEqsaqTiCc0SyxN3iVyxDoaJhRYngvj9furcWR3ZigXRebM8XmOCR70zYOx44YsBX4YORn+8CTJjIRnbVDrFLkNWkuGm6+bY6KJHLMfT9KJ33cGGDpmSgd4pX4kpGSp0mqJyO8B8iqcSdugw+ZlW0s+bax//rgg8eolcCA1RhBswJpXKKCi0yHckVHzI0xKgGlA8NlCQAA8RTEQaSvcbxaJgYaRt3ioY9dUrtcC73FsJneVqyHeSDeX68rRwmi3ggdQORpvSwLusWhVrcN2KwJWZZm/M56vVYZR14XEP4nFWvZbQM0ZBiAg4oAxhOMp2UIgC4ceChLieAtUosCAXCnqbhb1NJJgvRTP6/XhNw4glVrkKrlWNZjQelJwz6IkBgrg+mq4bfXbrdQKNQcXzr2d32/LRUdvBiktxPtNQININcyW0EowSfPa4Nayd3gsmcRqfPSh8RJUPxvbEINwonqGaZ2bdNjQh0GT0OZXXxuOr7AOGuGEJbe24mAxDJcxRC+Uz5sVKYAJzp+ser894wxoU4cOhco7pmsTf8dp2WkbxBtpgzhmHuBXsFI8seGd7wUNCF6rdXN84j56gmTrA9Y3CA3j++XBwQsy2dkO9ec0Ur2HtHlDuFezPmMLVdVGqJK3Bz5tYnovJ6G8zDNMKRJC//vqLunbtShkZGTR8+HC65ZZbqG/fvo2+3ZA2ktJQN1uMv0+GS1y8D2K9s2h0e45hhMbti76xRjNjOTaxLBPveVc6XtjBdmqLoVOK4oY+EuYmlwwm0ozqUBtGMJXOmV6pBUfG0NsBO0Gr4drI1O4vNKZh+x7oEIW0hKE+9MrAbeLoF9z3Pj2/CIb34PFoDyEwIe16xIowemctvB2s9oPeBWLd6MmB5YsxdExbH4Z5BHH0Ls77Bq8TrM4jCMF+4rPP01YVyELri2xDcJSwMDTMOkJImaECTHQYVJWt+BZcssx4T3jhHGJOECyvKtvWr499e7Dz7+QtByOjMVWZAA8g5XzAte7WSIv7mebkcYLnDXIoReU9aiRM17cSSij2J4ZyzCZCm7bYGve6OOILtbGv+uXynoxFEDBda1gG3SkUo6mMvFg8BFyt12WuDWPONXje4TFzi35uTe9Zp+TTpvXh3+ghES9RbYyzSpUJt5XnlPNRVGwvyCTg+myq/mFLRbzaDTnoG7QOhqHWLoII0ePJJ5+kgQMH0tq1a+mmm26iESNG0IIFC6i9rlLXUllZKT9hNm0yJ7lzpIEjHNEl0OzniyXxlVu31Hi9KpRRPhy5x9FkrQOG5VrdoldpaChYRlWvhOBmtKepXX4TgetRSsMondO15sZ9Hzv1bketlXKcDrkRmgpTRwVHoryQ4BgT4OrVcpSOJ+SaUBKhamIBepngdavkjtGTlG6yr+qjlJjVwnZQIPEbwlRwlFDPjaGPXNdtBsQBfT89BRm2++atqqIDd/FSeXWQstJ8tG5hevTzRbqL59nf0w7XreIV4eD9YExEDZ1v11UR/lls/yx3mT/BZIwqoQzas1up6gOiTCylc5uqgkjgr3+oKXCzP/he1N8XsYRwmt6zpu07PbuTXS3HbUhWUxl5UYk1G4gp3BmfifHup5PHjgnlGe/wHIi3bHdCcehDYXiRUrrdZb/TJMjrFd2CIHYoxx1FJU1YddPHdhLbOIlwfHBiVCaZtCgR5JBDDqn7e9ttt6U99tiD+vXrR0888QRddtlltstMmzYtKplqMjA95GN5yYUMo+v6CyfecBLTKJ/ieqnlyogq6ekiBtc42mEK5dC8bEzCh9uRbiVBVwoLH7GARpI3r+Ex7qmK24S8sYCd5ZCT8eZiZDKWZIJuPQJC62IxRFyc9xiuDX0/TSVBxTNp5gnpVFhQTuuL02jsRTXPP68ebx7Ds0sJvzMYP44d2hjc+pUwDwwDw3LWMRi28eaKcjuC3liGtinMR99mog0MN/ujVEDTwhBiEeRN7TadA6dkrEmplpPCYIn1WPpKei6UBnn2uiWWnBN6AvPmgMMzMd4EsKb3t5NnsPGdr9+PLtqGAxr6ez0ZJcUZhkkMLUoE0cnOzpZiiAiRMTF58mRFIBGeID169KCmBkusxm1oQ2c90Q9odKlWEl9hPggY9bWgRLC+b4orqcOLyAux/SEUNPCli/vsNl4dq6E4jJKiQIPu0UavkkYuJ5lIFG8Fp/CBZkYiRA+8po2jRXDdRZVmNgh7Tt5EJsNIEQ0cRDl/90hC2iDkx2gq48mt51pDz0+in2Ome9JxO7GUs3RRQSvuc+MwAmvan2RXIYjFOywZNOZIu7FMdAL22SQexSsqpdx7LU4/eAzFU67JpqpEZABzDjmRbM+ghCeUR8+eJJ8DJBYvOqYBSU05MSrTWkWQ0tJSevXVV+nTTz+lJUuWUFlZGRUWFtKOO+5Io0ePluEssSLCXH777Tfaa6+9jPOI3CHiE8Wuw4j8meQtt6/qUN1Bi12HxIMhP3g7YBUDLO2Jv0s38MgDP7240jY5I7rHy+8VAduynb4tMHIEnhceLeeBktsA8hlgcj/9xYrhLEq1HMwT4ZBBHjGXjt3izpMDS/dB0j095CaIYQpoILg0+nEE2YMx9pDQ0OqoljrFhJdeOIchqJQSSleNFw+WUYXkYaZry0ozZ8QO4rqxmoiD7ekrh5CNjMjyQW07yrULl6Q3AF9gFo/Wl8FrHRNpWui630Yr2YhtwNurMrK8ryJk3xZtm8rxgCSh+j0ZyIQ8PZDM1L8lknjZu6ncvtSraHObiMHhw8SmmZHf/cXqPRmCRKe4DFYzweSlfgxzEUAn0tcp4iocAu8NJ+MFS7eaqhA4jVRjskQfhmVoI5vYqcT1yZwmBm+xxiKVDQl0izd6ADkYC42VMyEWYgntdFxfCu1bLNeaaw+kGDCtQ/FycRBjTXm4lBFxh+dILGFDsYDtVkTrbpHnmAVVRqKEJ0N4rhKOooXiBVeusRVRsDKV1QZKt29U918JOcQqURAC6oUKKpL1ln0+JKxGhfmIstVcNliGFefDBOq69yQ+szG00e0zUhk8wgTgDp4xPri+GkuA1L0QE/nswH22IMw+0WWvWxKcE4RplSLI6tWr6brrrqNnnnlGVnPZbbfdaIcddqCsrCwqLi6mjz76iGbMmEG9evWiKVOm0PHHH1/vOidMmECHH3449ezZk9atWydzggjPjvHjxze4fd6f/yKvJ11xtwyAIZGmZUY3PUix1Ghg0RJjzCfGKZqMfqy1LrcJ7VGy28MDFx/4gQQ87E1eKrEo5WhwKYkCtXaaOs/4Mna7fVMFlagOAHZWDe7I6OLv06pYoNGprjjSGUjTymniSxNfpnjdYbJOT66WjBY7vpiDAcQvJ+8V1yPNpuShvbraGvpKlRXRhpw0W1EnlB7521+mGna+SkOujOzIfVOdA+dQGyDEdVuoD2FVXv1piOvwQMfNAg8mv5pU0g1eFH482jlUxCPDKCdqTZr96zEs4gn1MlbO8cFlg+KRNxDxiAvC8dO3iccQp6EoFbUvViRhqBfEv7SiskgS2rQ08uyybc08UKK4pkEgsJTDDmBnUw9dQCEG71fMfQKJZvVyt1j9wvRcd4syAor5YvT8HnHmPMCR1WTHrocSbAwnQ/gwlTR1631ozEMCiXZRaHcyBnUxUpmGz2VTUmkQG719Ix5kelovTx8QRkGQ18VKperUZjDUQ5Hlg/ltbCtZ6QM5+M7AgRzfVnUZLF2Opc9Dq9faCgoePXk15ofYEMknYXWG/tliNX+QksS2d+QZGfh7kb2wqwsaSoLkyHPAt+3gyDa0beL59AyIPHtoa+RaCXTMtR04kd/7F9oOKOAz2r9VPTa+4kg7fXANhXK1EOfw9vPU67E6w2e7TRxsUAYnZBvsRan0lSX1losXBBf8GVlX/762opSOF++DdcW2fSW3odPxhv0wDNNKRJDtt9+eTjnlFPr6669p2LBhtvOUl5fTa6+9RnfccQctX75cihxOrFixgk488UTasGGD9CbZfffd6csvv5RCSkMR9c89nnTFuMZOj6dzxAtA4A9A5v1cMGBhNDjUfcfIPCVapwlGfX3tIY68CEQHzVD3YwUM8OqwiktsRzqcRnCVJKegxusP9US6wGJyQFMpRr0TaBr9UxJkQU16uW7wBAlBxQzMh6G/2Bqq3Os5NPAFjJ1FK91nLuMKpU9D6K3QO9KJDOG6NHEBR3iC0AGhLpEOjLc/CE96GVYsW4qlX7FUquyIVtn2lj1lMPKx4C/70SqBIZzEDyNpIW3UG40EFIuwZW2go2jlamVcsbOEnXfczxz1ukPPFCxri94foZwMo1GAXj8oXPg3QidYEweU66Mkcn2HoIPu7d7F2LnzQKcYy2GiV0plR22UEL2LYBcCmXBuoLOse66G4Dr0VQTtvXl0UQq2iQJJWad2dNC0MtqwiahD7lZqM7ymrcEMzeBCIw2W98Bt6622XG3TdM71edK2RgzFCmhPRrd822OhrwPXjfe3rwy8DXWnjj8Mwjk84yx4psl1dIZnIbwLrC6R3/0oHGkVbfA6DvxuDiV1BYaLoTg/dKA6GzyHLHzerFhrTAAr3tF2yX5RqPd3iwizUdY9vk/xXQADHJZe9ho9B9A4R08th4odwQ5tbb39gth+8ECTTcby1vi8AtEBPdrkNKXR0E54duHzhRYXGatMhTB/DcwTVT4YS4326m5f3vyvSKLgoINHgTJAAuuNpTpcaFnDDVP/mg2uBo8sw2CH4h2n9ZlMg1eKFwFep2IZeB/6wTMFvW79m81V9PzQp8Ik2dZm2De9Io1hv42hVvp8tktr82h9PQx9VgZseoOIj88uTSQO7rdz3d9VbewT0ga0dwkOuPjz4Tj16lT3t291cXTFMrvjmQPVxVAs0l43QRi8SV8bOc7BX/+gVoc4NvFWd+HqMExzE0FExRYhVDghvEKEqCE+69fX//J7/vnnE9Y+4f7nwdFf3QsAVH8nFOMcjLQQuFTqHToPuEs6jdz7e0Y6GlYRvFjRewVGL6NqzcOL2k2SU7cjoNjxxO3HVLXF5frwpa972Zjccd0+N7Gzh94XGDakjLzJ8xsJJfCCa65nc5mtYSunYa4HTOKIHRi4TqJcmCE8h0BgcipXaMVwPNzIQ9iJ1cu4+qFsqAWxz2jMebtEOiAS9NrB0TsUN6BzaGVoLrfQqcQRR6fwJCWUrA2ExnSGkpUwwoUeHjUrMBjgneB8+MyeHCFfRPjxBnvYe89ooUqK4Y9/+u1DiOQ20YBTLgjLfpt6m2F5bA96lejCSdaGyLM0DTqBwshbWhqi1SVCKAjR9p+58LKAzrviuq8l38QKNbEkpEWyBvSLfAFX8agcBejh5oXRRBTcVq0ziqkWeoxUw/PBKTmuQQSw/oocyyB6iKCYoIkNilgBJaixCpFeBhtd3xWhGu774B+L1W2aSsSicKSPsroYdXV6/6BAoxh28IyMSuwdp7u+Zylck1hBC+ZxMib9XTrbPtNCWmUqL4ZcgBiK3hIopHnRW0SsDzwh/GCYKoI+jshrgjrhMx+FRbhOonIoYb4ReC/EO/ASS7letx5YpjxayoCZQ5lnJQk+vPP1qid47ZvCjZ0EIm8n6BNBexTBVPecM4ggSkgUPiu220ZtTy4M6qCXD3iC6CHePvAE8eOzE8VHvJ7Rs0ncnv+stfcM6mJfHbJmvpCtJ0gIQ4igb6U/h7yBdrbPWEUA1651bHVrD5Th6jBMqxRB6hNA4p0/Xvw9u5Hfm6G8cBRjuBt0RvQRI1TxIT8HPrw9/Xsqy6NxHFwecYX0gwJu6eV70bUTR+/QbRsSJWLMaVRnE0aisBPsbavlPoFki4rLZ3aWfcdTC6XwwSgbCh/YFt0Q8Jhyd6AXASxvrCajjzDB8bO6qMKJtShy3kPQOfCBCOJDb6AcNTzKg51N7BDCi93bQx2ltGCEAY+HBz1bwGDR80HgCKoHRjEwnwSGHtS0094TJJAPoo5mwCqdGFw3jGhTJQiG/TobO8uhLuD1BE3DMBcdHFFHzwMcDfVoZWDRlFBG+2GZ9BK1sx0CIQU9NNLXRa7H0G+R6jA+HP3UjAQPPgcgh0NgmXpPetF7A+9DQ0deN9JwBNdthR/0Wgq1hXt6ceQ+VkrU6qGAi5dF2jM4si5PBRh56BWjjUIHu7W390YSdn+t51JU/hwc+cbzObCbrYgl14Ft3ranrZcPrssL15ZOAFcN+aGUe0DeRxg6BUY35pjJiLTZrxtMJg8mt4C3AQq1XrxW8VmlCfzoXo7PW3wO6h52IdMIPzxvfR21cNC22bbvUs+mrXFVJdIFcWynF5/f0DYPegui8SifHfDOgfvAbc4dRewZNsje66uTVk66DPJ1gSeFEpqjCVkhGBRR8mBh1ROnxJMgEiYyPWWUqAS4ETuUPov2jDM9I52ED1OYA/bvvItUQUR5LoNY78V1oQGteUL6oH+CQhoKlsZwWidvWOgr6vmpAlCq220OJOw7EnhfYi41HIgLacKmBz2NqeEEXYagmMABO+8GOB/avYKeSugZo1SBW7LUuB2lvw3iVQjWhWFTcjtoCyjhymtTMjFso5Oinhwff/wx7bfffrbTRBTDrrvuKv9etmwZnX/++fThhx/KwfuxY8fKdA7pzbHKUysj6YlRw6xcuZI+//xzmcsjpLkCXnTRRU3foLR0Il+6OvKCo/2bVcPc6oxxp+Da2gESdoJbqzJqIjv/YHxsF+kcWYtWGkcnPB2ybF/mfizFuLXc6NXhxkhSsnVrhjeKDYqhjmgPclMcN7YlKnGVqVoOGpMQtqR3lNBDApM9KsnbXLoh4gsPO3T66B12YhSxA41z3SUfEll6yiG0pC24WELIjB4fHYTQDByFQEFBzxnhg9NR3R4Elq0gYuRoI36YTBQMu2q4Hongb+1dHvLbvxiUsAY9TARduith9AwSuKLbuGLYyhUawhzAyKzSwkRM269GMbTz9pG2aC7p/s1gvIC4EIJQpeAg1eMFvUlUo9m+Q1SZrd7TaVsgrMADIVmAfmwDlfYiQGDX/rAv0HHPUl8b3k5gEMMxCEH8v+4J4geByVeK4UWqe3Ta8tqROaey2RgG5lb4wb/hGR8Crw49maubkX+z9GZ2D8dlvGh42AjXrgCxIrBshb3xFEuYCzxvY6lgpiR+BNd/QciQhDdenMpJhwyejEpYwhI1N4NbTwITyrX211JbwyyknXNsjxJaCMJ7lIs+jvDjvQLGubddntETE9sZgIEPJSeVHuYIgwUWXCue3Mh8AQdj0pjoFq5np/tbEYcNIRu6N6zpnnYbBmbyylAGWzQ8eW1t+2p4r+qeIEpuOgyNQY80FF40wdS3zUD7ARoMMdM8NgPgzWoyyEPY5sED1InojYkPPwfb3lu61VZIwtLUSqiWNkDmQ68lFE5QTNb67oq3XmnDkzqbkghj/rnQKvX+4twhzQNRmEPkr0SuvfZa+uCDD2iXXXaR34PBIB166KFyoP6zzz6joqIimYfSsiyaPXt2klrONCsR5LHHHqNzzjlHqmbt27cnDxosHk9yRJDalMWhIojFd5jduwLcq8G11LcJXtrw8lFiMQUwKhX6YaHty9yjj6KgiyCMIAZXrXWl9Juyw0eFzSBwbkwdCCVLuyZImDqlOB++8NxWSFCq02hJUpUqMgaPE73TEcRYejiGSicWrg2n8rLo4YEdQh0PvrRxJGclJHkDUSqoGYb+Qf1tO6Q+FKh0DwlwJ02HRHXoxeDX89dg0jqsXqTEqMO+aKImjvSicBGAkBM9n4MHhgqUGHlcNeazgHXVzGdfmUnJh6HlRkDDHcUjDPMIKRVtVEGirFPkGHrhVvWBoKFvMwidNdymsj/wOya2E1QUwLVuCI3RBZWqPDjuVZEZ/WVQDSsPKt1oHhKBbBhZhN3xQ7UhPUwE88xUQ0I9FLhk23rV3NfeavU5oiTXK4+009ctIiqFssxVCBS3fhQTQcxGN2k9eSR6rHi2lNu7amuhV6ZcNEpi1mWrXT/XjIDBgsujhx/+ro+MOoaQGAR1ZRQd8xzohnIYTYjzY/JIzEm1YlV8YREO5YOVfCFwbJS8UVolC2xncM1aW8HMQm8LPYwWxAZl5B6e5cpzXPOqU8RAGMHWk6Yrz3msVAaeC0qidt2AhYoq3h0jYQ541kJY8UOrSkcrVtsKH8qgku7ZBN/96KWDxjkO8GjTLAjRUrxZsW+k9VnclCR3m4BX2Tf00tVzbRhC8TBcDD039P6JEuKGZdD79jBXEoQEskreqbKgsW9lCmnFcOtQISaa1wb24L0fzMqwfecq+cX0MEH42wO5gRTvGb3AALatHQh20B/BgSS5jiIIx4SQSS+230EAR+ED++tKbiKtnYoXGvQdY8l509xJ5XAYYZOKwh1hqqur6Y033qALLrigzk597733aOHChTJvZdeuNffmzJkz6dRTT6Wbb76Zch36/EzySQkRRFSJEZ/JkyeTV3uxJo3qKqKgR41/xARd2gsDhQML3MONJen0PBWGvBVKFn89o3/DB+MUTKN5ygPfoROJI1SobGOH2GkkTvHEgE6XPuqAyr+p4+q0HeyE4vk0CRr6MojSiXVTvlLvuMbg0u2WwB9/1zuPYvxohpW/F3Si0KjRDDsldhhH/zALP7rHt1dfAmhA+qBz5gPPCRRa5LoNCWGVqiEonlZUGYUXxTAFQtA5rFk3Cjlke2yqC8AbSyvLCwVV1LwbGIMMISNR+wDzoUGvZP7XDInMdVW2+4neG3opYP/GattpPhBBMImjD8qG66EqfhQkIDQEwwgEgbYgEGFSaK1iRNjrSA+HUSrkQIe/uqCNOVmkVjHBFqw81FbrLG+BY4tCIHa2yx3OJyStxQSZWIYdDRm5DBjAPnBJV9zgMReQXCGWPAKxJgu8EvOgzdo1aMrB5LZCgiKIwPMWhWIPjthK4wfuozUgGoMbuR9DPMQyWNbdhbeg7r0XgNFZJS/KNhDStVkTgDG5Kzwv0ZAJaaXolVw06+A9AaIOViPBBNMSOO+EHjRQ4Uj3GMLnPI6WmzxZnDwfvCWb3HnCoNEMQpAimDn1oTAE1FC61gJxReIgcLjBJHB4wEvGlBsjCvC4Ud6rmgFsFIKwvLmWdFbxMEBPWRDpvPjO0waSUCBS7j3sW2G7BJivBIUH9JxYEOlzWFooH3oH+yH8Tcklow2Q6OGQdcvg4IAmwCrzweCVB58p8Oz16YI8JheHv0MGLx8nvHCuseqMPugZjKGiWIslgYlRRTVQJCMjQ34ShRBAROENIXCEmT9/vizuERZABKNHj6bKykr67rvvjOE0TGqQEiJIWVkZnXDCCakjgIiXzvJVallMgUOJPzcv4FhciJ1AUcUDuTtMLtR6PK4X47LRRRK9DTDpnxzxAldEPZGW3Uig7r2CSbngBe6HGHO92oEaKlNtbwhgB0xbXgkjwhdTRYWrkpF4nBElNlavQgAeForLrCGPSaxlhhG3sb5Ggwfz3zi4fyrHAztKv9nnDyBwmU0EeH2F0BjDbcYQT6uPJeB7Wekgwks1felqY+cMO/nKvZoBnUDNGCTsyILw4AFxIq00cm5D2qhWCMQerELjg1Ooi0AYqoOeICEQTjJWR54DwTz1ns5YYT8tmJ1uDE/K+DNy3EIdQEDWRJ1w2KB/mSYeQg4iLMeMpRSjRGO9PGZ4+e4dbfMv+Faq96OFVbtQfEOjV++gw/MuBHl2fEsh9huTUmrnJvAH5JzRS2KH0d+bpvcoXk8bN5vnBwPUbZJrE6aE1z69JDk+oyFcAJ8pepgkVtBQBHV4T+vJcdGbRAlnhESioV9BEOje1XgNuT0eobX2VdgI3tlKQkU9KTSG4eI1De8YzH8gCEKuIcxV5MX2uwy1UgZyDMdZrg9CmhSxHd7zONgQFfbaiAMEDUYree8G0/s7SuzBMAnMUQPn2ZTMXS6D4hkKNG6PXwxikat7WgtxQyzIdYH9Nj0sDr1blUS5eN/CMlHeK/ieLokcQ6sdhmyq7yIvHmvwrkLB0Sl8BZ8xSiECfOdriYcVzzf0BHFK2F3Xv/GmbA6NZNOjhzqIMGXKFJo6dWrC1j9nzhwpcOB21qxZQ506qc/s/Px86UUipjGpTUqIIKeffjq99NJLNGnSJEoVhPuh35uujDYpZfT6qLHb3iJ4kOLIORpp8HsQ8jzUrCDyp28VZKjuGOmceaGDrqNUssDM5LDNqIobuG+Y2BM6V778PGNohx9zXcBoET7InVxJTUlbMdmW3Afs1HZobzu6gAlbddd7b0/Yzl8Ro8IJk5eH0rnrCXG/UFJPktnWNms6GqlBzfbwdetoO/KPoyPKKL6e+BFGupXyuXA49CvIB7k//JCcMJgLrqikvliUMr1gWFmwST8mGdVdc4s32XfwYfQwBCPVsj3oOQAutJjoVfEQWad19HDECSsUKCUCtbAd7AjjPQ0CixKrrFUIUgwGU9lOPT7ZkAgTR2NNZbvlNsFdPAT5gJxGcJXwN3zGQac64NabSJtmN49cNxhAId2YzINRv8U1zwVLOzceOO4hPB44muyUZBRDLr771VVcf/Dn3+yTMKKRqF0DSt4EGDUlfMZh3iZNuPHjMxvbD9dTVD4HeHYpoRkYsoeVqFyGCKBLflD3nEMPCRRQQUT3Q5UspyTdOEqKx1kvG4pVaLBsttIuBzFYSXwIf2OYSgC8OqNyb+FxhuvR6Z2nTPt7S4NylUThUvTVQysaTAyCsitB32HgwS3K9YHVdmJIpInEWz0K7yE9PApDLnzggeR2m7hvptwnySCkCTeWknvLkFPEQVwwhb85LWOsMqjexgnF9IxRBj0TMQAaPoYtLmGq6HPEG85Ss7wIScHwE5MXiBBGrr/+esc1fvPNN3V5PwQrVqyg//znP/Tiiy9Gb90mabnwXrL7nUktUkIEmTZtGh122GH07rvv0rbbbktpWpLNO+64o+kbJZI6edOVTo8y0qGr3jjaAaMwmKAMy+L6tOoyOC2ACb5AdMDfY3lAu+5cucSP8dLwYvdsKDJ2RpTs2Yb4R0wQpneQnRKrmQi5FD6UNoDwobhQY+cO/tZHNFDfCEIn1BRCJIH99CoJVCF8wiHbtLdze9tqQxZUMcCEq1El5jDkAZJV6uVmPeX23gpYTSXUBmLktTJ2ofZYeQZKYGLIgzbSoSRqBYEG44sxkSgVatV68HBiHhAsXattM5BhFpwiQJ4ILc+BaZuYUwRL7OptMIW5ekL9jTlFcN3Yr8C2RCedheUhj4gSGgPJnqtgX+T6gpFY9irM1YG5U/xqklY/lEJU980i+uWVugsgNKBGgPOt1ypj4TJ9IqKSZ02xrbeI3J+1G+xD7DTRtQ49KTQmi3RZ2QqvfDRSPFBe22nU12nk3YRjaF49hqSTEe82Xh1FFWWU1MHzwOQFEG8i0ljAd4z+vMVz6PY4K2Ee+C7BqhJ6KAKC71n0oEEPJK06GXr1KVU+8H0MHjfKCLi4VwpAvMNQBAid8gxSvU+8kFvHA6ItClQYZhLUwg18IJJh+V4crAniYEcM14fu1RmCaz1e4QRxEsK8GEIKQruSkFcT9Xy6R1IYLHUN3gb6OzuUCR64kHdJCaHRhGasEoUo1ypWuoHnsATCS/HdruSk0t5FerL3unX/8rv99YxelbLREMKZCxWnwMMO81HJbZaW2VZpMlV9iSVvhx7ehN53ifYQb83hMEIAcZODQ+T0ENEHTvTu3Tsqd6XIWXnEEUcov4ucIV999ZXy28aNG2X+EN1DJB7E+oRniYicEElYCwrAm4hp3iLILbfcIhW2QYNqqqLoiVGTGQ6jG7fGGFw07rGzCzGKSvZyLZREeZnDCI8XRnY9wSxzmIihs6y89LWRNKVzg665MDquv8wVF1Zw5Vdi5B06E/gCcSOIyPXBSKmSx8OQvFTvMJgyuLtFr5Bjh1dLrIrx3srIP3TuUCyKxR1YjzVWYvux0gqWYEtEFQYslYllIk3x1Zq3Qjp6F8FoPXa8Q7+rwpUP3b01z5I6cCRMD9XCUAIsjZwPYVhaKALmY1DEGghBwVwbmPcjWlywL9+rLxPCUrKWIZkrloTVK71AAlUlAauWB0TZJpY8xtWBIBKCKjxeEET0daPwgZ1drzZYhu3EBKrBLPUcVOfWdHLLO5s7E/6tkeWrCrrY7r/chx4Q8gDik1OiWqNw0xsSsOK57auVSYZnoQXhQSFILutDYVILTfGsBS8bLFMM6CPIWDFCKV88BBJuYt4OTOwqz2GwwaVflRFpzAeBOQtQjEUDXIBiAyaFxntQC1EIbSxxNTpsaid6binVzUCoUBI1iqZhbh98n27YaPSCwHxXHsjN4N1+SGQ7sC7MXxSV1wWSTyou9lpibiXRqVYC2S4PiG6kBdEz0xDa4tUECWXdBsHOi3lhtFFaffDDrm16fir0VHUjSrk2OOMMrXTC5K2gJJTX+xOQmBT3UwmBdetJAn+HHPZT8SjG5yL2ydFreLXm/YN5XfCeyoXnAN7fejtBtFYEaOx7aznr/H172ed3ggp3aVqi92BupG0+LIEN++k2dEzxHsR+CuZR0e4jn4tiA0xi6dChg/y4RXh1CBHklFNOiRqk32OPPWQCVFFFpkuXLnXJUoUXys477xxXO7ds2ULPPPMMPffcc7Ikr8gzEqZ79+40atQoOuuss+pK9TINx2NhxqEkIeKn7rzzTiXZTLIQiXXy8vJoP/+x5PekqR4b2NGDOHqBF14AaMwpyQ1hdFzv7Cqjrv/Yxxrr5cC82DY01NHFErw/olznQcQIYek8CDlBI1HfH0zEacp54KSaK0Y8GsN6pRUIOwkusM87gUk9aau2PAg82Fm04CUdVXkH9sGCvz1YbhCNaT13CpQSVkbvoDOhlwPFfAQeMCQsTNwF8axKJ1zP5dIZ8o2goa0bwzAtiNVZwJjFMJea7arfIzvk8lGCIReYwxFECL+WNb46F0oDgyGgVKcJmMUFxIfJDuE+1BMSGo87PjINHjtR1wcYaUrnH68nzXsBk9mhqzHex/pIqBLKgLlxsCqGFuYRAjEO732C8CisFqHcT7Kzut42XE3xMtJj7JWKDyBEZWfSUTvfTn5vBQVCmfTatxNqJhgS5ulGo1eppKEZ7eiWjvckdlBxGTTGBQYx1EIvuHWaIVBYYB/uBUn7nNoc2lDcYEMfUUZNcXQZRQd9oAENHgyZRC8Glx55igELIo4SZqrnyTGEhMUboqCH6ihenqaQLodw0FhGcI0V2TA/lBY+gaF4GOKFITj4LnNbScfk2dSYOI2om0LM8Dzp1XoUL00cRDAIF3ofSAltxJCuGKrDmNC3aQqfwOeyPlhh8jZT7i/ML6V5MGEYsLIM9hUdkv2jca4MuGFfzUEschu2Y5rPbVJmBewf9ukZ+V27V7CaIpagdp2jzSAkOeVVi4eAVU0f0+tUWlrarCuPhG2tHvdNJa8uEjUQkZ9w+XlTG+2Y/Pe//6UDDzxQVoHZZptIeHu4RO4OO+wgvT5uv/12Ki4ulrbsUUcdFVeJXGETC3FFeKQI75PddtuNunXrRllZWXIbv/76K3366af06quv0u677y63NWCAVuWLaR6eIEIxGzlyJKUSvp7dyOfLUEaUA0sjL5IoD5GukQ6FB2qdYwfb83fEI8HTVRvZRI8ReLGgi6P+kkGBww36y1cp7YVJqNBDQcvIr5eAtOvQ4YtMd/PFzha+zIKYdwNGMuUyKHwA6IWglOHTPCTcHSfNjd3Bxd0VhpEwZcRNfxmj9wh0xD2lYJRgKUaHjq4v3WBUaIYdejWkL4sYXIGu+fZVW8S0fHhh4aoxZAVyePihSojcpiKCYMgFjOjjNrR9qM5JsxVr0Gss1EYL2UCtIsNnK9wEeqiCHwo06NWBbVbyoJTr1UjsvQpMoTFOYPuDWHZGw1+JISj2JVl1EctX0c02x0p1WyydC0aapptbgwtty+eih0mUhwV8TduCVWg8dMzu6VSYXUHrN6fRa9/VzBiCECg9/w2WWURvHn2kGd2jUfzDe8CDwpdWoUjJ+xQCUQyekVEdZ/xuGnXFvAZaB99tgmMTbkcwGwslhMdlOE9j4sYYMYU8JsLwV3IIoRAHpZ3R+6dmBSB8gAcNirHoXSa/g8s/lgdVQmhAtI3K5aOJP3XbR0813WtJ8UQM2QqgwZVmT0QlRA0TR+Lyei4a5T0XshUxlApFmgFu8pp1EriUfGEgUmJ/BEf6PZiAXvdSRC8dDHvVBmWMfZBe4GWK+bF0r8Zdto18AdFVSf6te5qhiIDJyEGMVZI1d+9kFKcxBAUH/PSKagSVsvxQ0QWPjQUDdp5MrZ8Aog4OYgRhAFK5HwQwYGRtrrQP94Z+b1S4NtwrpvOkJ84PoTcPltWNU3BrlojOVbwlbhupRC4mRB0xYkSUABJO8j1v3jw677zzpB0rRIqxY8fSjBkz4trmF198QR999JFMEWGHEEX+/e9/0wMPPCDb98knn7AI0lw9QUROEOFKNGvWrJRRJ/elI6UniImoHBCYAA+NW4MbfqC7VjZtXamtYWZBfXWPPrKJL1As8WdIgBc1urDtYPtqB06j+2hEg3CDHbVYQi6iqshgE8DYN1VAUcJk4CUp1w3Z8TFfC8bd6sYHtgdfUvgyDkFMtG+LVpIODSh0oYbbLai7WhdDNnMcGcVQIzTyNFdSTDga7Ka504a3sVm9hpTSpathpLULVMzQkneidxB2fJWksy7diVEwU0IHYojPVkYSNQ8JnOaFkXtlxEzLXYKdbysvxz5MBZMzoriiH1tsC5w3rKAi8EGJWRSSlN4qGj/a7RnMRG8aVVyw+1tuB5YJgcDiL4NrXcsDouwP5jjJguPhMQtE/s0omIFrcHmAnjv5NirM2UTrt+bSmLlXR4krUblcDF4/erlFj8HrCX/HBNPpRWbPC9N9qBsfynzoqQTPW6VTDmEVEvSqMzxXo0aa4d5RRkDR6wifL1HlNDfXW4pX98owjdQqXkcooOtJaxG8b/B9s141gJXqKhAa49ZDA9/h3s5QZhiTJeN7XQO9QnBEXa8QhO8jfJd40NAHry0lH4eTt5piTGvvbxxZxWcxiHdKyWKtzRjC48MBG/Qa0oQXDGk1jfYrnkm6IIHhrfj8N4yuN2b4QCy5eJQw0WED6/62/lwSd54bN54Qjt4WcYb3KIleUayBwb+oRLcgqqAXtOk5GPWMAsEOEyxjOWtdNPAPioT8BdtBqC7kJwlq7+n09fCcx9BOSK7uVkw29Rv1pOlYaYxWRAYGQ+D9aRLAW5onSPd7rk+IJ8iKC6Y0+2PCtFJPEBHr9OGHH9Jbb71FQ4cOjYq5mjt3bpO3yT+wH/l9GUqyRzRg9VKOyqinwUU/2Cby4PNv1MrAFkA1kfUltiUC9SRtSh4K7LjhCxM6tLobfACSTcXryonE4gaoZOeHzrbAC0ISdr4VV1gHd94QxD6jIq+U0oXKLHLa38ts3biVyiLfLYhsQ3uIe7GDC9ezBSMivo2a6o9GAhhPpnwOURWGILYVS5Li8hWQFyHKAOyWa+uVUd1LHRX04ig6JibdJjKa6AOPhCgUEQH2DfdTE98UrwrMGYTtx5CyCnP+G2V5FBy1w2xqG+a68G+xzxtSX6LXyLqCxpwgXjD8vWAoe1esMxqjmdAJxHA1bJl+NWXF6fWkVMxwKV7haKpfN76Oq64TB7J+qDUgtGefBdWDlGpDeB9qrvN4ffg3wgnBjid2TvWqRmCA4jFEwdKrjVQT5HTCcBoLwmGUMBstmSuGRphGqh2fyYaywPissaCSlf4u8Q0dWK9HnlyH4bwH12GCafCK1Mr9olcbju5iGfMoo3u5IYcEhmaiOOEUdomha/Dsjhp4gO/4XnAbToIJr4OQeFLxmFytholgvhJ8Z6FXg1KJQ8slFm/pWRz5VsRkrA6nhy+YyrXjSL0W9qrkxIBwUkVEMniiCvz9+thWxFFCjbTwQ/QSQQ8gC+bTBSJlfRjihSKOJoYimAvGC17Dioikhb75+vSy7+th2C6UgfVqfQZFaEURfQP0z/QS7yC6KmVtMZEyCh9ebZ9BtPSCYBlLcnskCO9cfTAS33kIHg39CvJCKDXmjwuZRCDtWWesMgXCR1Q57RjKjTMM00JFkHbt2tHRRx9NKYUYWQn5FAPayXMBvQ0w07qSCwA6I06mgoVVQgy10uX3Bro6mxLrRc2H4oomSCFByAWglKcDDws9HEaJY8aa8JhLQI9Rx1FLTBqbDwY9hkI4xM5jZxsFGsX1UUzDJLbo5greN1iiVzdGQ8vKbF/UShy6NsLU0BAcJUmt1lGxsEMJopTl4N6N27d6RQSztOWqYRcqULcbxrs8Elsb6gmeOVqHUEkmikn/wEBQQlakt4Gn3nAUZaQfK7vI7dgn/8Ryv7q3gykvSqBtpG1V8Lce/oJhJ0poDQoqkHxU3wdTRZrQAOiQedXQMUX8GWaf+EsXe/B4+GH56jZe23Z5tYcXhufg8t4qs8BUgcuAl4gQmP4ufoPWlRFtqiCqHtgtqhRzzQ+RdftBqEYBGisc1awczhUK1Zj3CL1HtHAYZeQdjUwQqqNIQB7ieIjqfLtAKV0OwgeGTLiNl1eqk2HVbKfR9ThHrdXSlO6W8YC44IV3hJJnIgEoJesp094A7a69MzEfEeanAoEsoCcp7RJ5h/vhPWllpdtWENOrwwT7QcUlvCfwmaR5PyrGPa4bji1WHNH7Bh6opIdepmhAh1AA0CvHgfCBOcIC4P2phG9oHgZKvhjoK6GQ55SAFcU3fBdagyLijFzfTwsjX9AbCYxmL1TR0Y8bCky+3pH99GD4SLaWbwxDZbDEfQfYZzxnDsl1MQeUEp6rVV0Jdmln+84L9i+0Db+U24TQW6N38rLV9smB5XmL9MMtpUKd17hebIE/ra99HivM06MLo6awZLiG9ApcHhC74xUpmz0JrA7TEhEhMd9//73M+yHCbR588EGZK6S8vFzmHRERFCIEh2nGIojIuptqBPOzyePPJF86uDVimTHt4V3VHgzdoL2RaHn7GGN4fZA3IQTur76lq40iiJI7A0etcXR79VpjIjJ/bxhdQOEADAxMzCfbDaN5vn44OrHVdgTBTYI2OZ9DCA12LhThAZZRRmc0925lBBJGAp2StGHZTKXjBoYAdqCUDoP2osRQChyR8aWBa7DcELj9doLKOZAPAXMhYIUJ+T0bOiEYdoOigae3MawAw3PRQyHYMdtc9QTLoHbqU68AEG3ow/6AgaALEqbSseiV4gFBAUM5otZniEn2a4KEsh0UCmDdGWsgYWml1rmCmGQMlfGthBFH9BTQ8lNgyUmsuYzVPPTKR8awBMxLoLvO4/Jwf6mx21hBRcsFANVNMPM/drY92ugZHisLvCdEQuFj7iyj1SVEXdqV0dCh4e1r4TBwHwTbYLy5/e8CL3g3KR5Aln3IilKpR9AWjDZYHsMK9coeKADqwl4Y/5YqY3JdpcO+dFW9YSo6VmG+behasF22bYlI3ZjxW/aVrdzmykBjFHOyhLK0c/Mn5MuCvBeh9hEjx6u1E5/z6CGBhlEIQlbkOjCEBrw/MJE13rdeEIOjXPkhd4dTAnBltBruTy/migDPA93zz6MUWgbw/sZwHrGOlevsvQVWrbHNQRUFnF9MGq6MepuXJo8LQT/Ke8ZQdtpjKh2vJ7RF8Q6ei/hM1EOljH0ATHSuCXGKpxEOkEAi6VAmeIetUUUTJYk79lXw2a2JPd6dhtqG3xGUdFW8UnQB3fAsD/y+qMGCI3okozeTXqkF8WBibod1N1jy1M8neBgq3nqd2hvLB+NzBQUe9AaKJZwpuCLyvPbhORfAs8eXA89lzgmSkjlBksXDDz9M5557rkyOevXVV9OUKVOkADJu3Djyer309NNPy7K9t956a7Kb2mxJCREkFfFtrpTvpNBScAVtDyEOeh33hRvrdQ32oSspVg8RD1boKKCHBMHDEw1zuQw8ZDE2UxkRgQ6yH3MhiO2AwYXu5coLs1yrRQ2ZtBV13WVMn+Ly2t2+g63Xp1ey6FOefbIpHBnupcUE4ksPXN8JyzTqnVh8SUGnBzuBKAIpOUDkusG4XbLSNsbco4k1pgoFvmLoOBs67nK+dWg0++yTxmql95SSxRguhZ0o/dyi+35OpBNYXZhjHwYG4qEeJoLvLhRHdEECwVCdQDa4t4MnRlD36sByrwavDD1hqFK5BtaHXiZlncB1XnNJ91UZhKBecK/pu4nHI5Rdr/AU3EMV0jwGFzNl+3oxEPDY8MFxCkBZXNw33RMkBDaaD9aF59OpWk96gSqy0Rqb86P3r/F+L62wT86oVWzCUVcc5QuAYYhu+F7NC87kVeE2e43JRPCC8eYUIhBl2LipmgLTFE8veMaGNJfyWKrQmHBbntyDySZxGfSc10KijFUmMEm3tm8WVtBCA8pU/cLBW8/oJaIZg6bj6UdxAkRzr9a3UJ7F6DGC1UC00WlPbgf7fAywjB8HOHBd+jZBeLDgXtW9s3xbIFysBMJw0ZMDRCklD4vupQICsJJ7Bb1CtRCYEAz4KF4d6FWhCT947+CgUggSuOohVbg+N0nXvVoYsvL+hP4A5iuLura/j4TeIr5tBtp6rkVVjjM8Ozy7RsQVLyQFldOwr4THHURwL+TRQgFfz8MRwAEaB3sVc0UpnnyYWwnDH7VzY2G4FKZlg/xrAUisLrcJYrcf9kfpn+FgjUM4D3rpKB7Eem49OD+tUvhgXHH33XfLKjEXXnghvfvuu3T44YfTI488QuPHj5fT9913X5o8eTKLIM1RBDn44IPpuuuukxl3ndi8eTPdd999lJOTQ+eff36Tta9PjzxK92cSDaxJCrZlUzmt3lhOael+6tW3kIL4UCeixT/ViCXde7Unfwdwa6wM0trVJbR5cwXl5mZRYcdcxRAsK6uilSs3kq9fJ+rbr2NUlY3Fi9ZSMBCiLt3zKUdzN9ywupBKirZSTm4mde4IBv2AjlRVUU3L/14rXxL9tula8+KBDtTyReuoqqyKOnZtR21FAil4yWxcsISKVpdQVk4GdemsCgrWiCG05M8ao6G7p4L84eVq35Er/1pNYuyyfdcCyu+kunRuKtpM65ZtoPTMdOq5TTfy+MA1uH0+/bOgphPQc3A3SocOka9nd1q7YqM8BzmlG6hDtxrD01fbwd26qYxWrywhn99HfYZ0i3rhLP5nPYVCFnXtU0jpbdBkCdD65UVUumETtRs6gDr1iBi0oQ0bqGJrJa34czX5unWhfkNrBSh4SS5dWULVVQHq1C2f2mL5Y+HNW7yVijdspjbZGdT5iN0j683wUXV1kJYu2SANuT59O5JPE1BWLC+iskCIOnRoS/n5bRRBoXRTOa1bt4kyMvzUo68qaISCFv3zT02nrvuAQkoPj0r7arJLr1pbSls3V1JBu2xq377mGvVV1qx7y5YKWr2mlPx+L/XpXUgBSHDpCRD9vWittDu7d82nTChXK1i7fjOVbi6ndm0yqVNh7XVYe5jLK6po1bJi2Qfr3682wR6cnqV/r6WAuL67tKMc6ESJcIUNRVto48atlJ2dQYX9QWywRChykJasKJKeIP37dJSOUF7IQ7J8yQaqrAxQx465lJeXpXgBbFpVShvWbaLMrHTq3gdGgP9YQsFAkBb/UpMPpu+e21JauINU60G0esl62upPo4IOOVRQ2JaCf0c6RFs2bqU1S9ZRWkYa9RrSnXzY+W7fjv7+rcaI7t4tX24bBbo1q0rk9Z1b2JYKO9Xec7XCQVlZJa1aUUxer4f6DuxMIRB+BIv/WUfBYIi6dMunrAJwr64I0ob1m6lEHMP8NtS5S217aoUFcXyWLSuSiVEH9O0Y1VFeuryIqsT13TGXcjH/jIdoY8lWeX6ystKpB2bXTxOe0yFatHSD9E7r26tD9PW9aiNVllRSh/Y5lJ+frQhMm4SL/e9EmZmZtO12Q6j3kBoDQlyP4vr7a3HN9d2nUz6lh0PYam9Jcf2WF5VRfrs28t5B4WXL1kpaLZ6zPi/17VtIAU2Y+2fxOvmM6Nwxj9rUnpvwfbdu3WYqLS2jvKE9qFPYxbv2WFWUV9GKpTVGWv+BndXyyUL/XF5E1VVBeeyztXNTXLRFftLaZVHXbjXH0C9igIRGUxWgpf+skyP64pkmnm1WdcQwWvbzEqrYWiGfhe06qs/Z0g2baf3yDZSRlU69dxkUmdAhX+aOWPT7avJ17Ug9+xZSuri+oYMvjlHZig2U36EtFYjrEEZDS/9ZTmsWryN/mp96bwtegOFj+OMSEnnWu/XvRFm1Roe3Nr/HuhVFtCU7j3LbtaFCcQxhoKCirIpWrN0kqzv1G9RZyacQ+u0fWvLrcgpUB6hTr0LKyQNPo2CAilZtpI1rSyg7rw116dtJqdJRVRGg5bVJD/tu05U8Xg8FwVBeXZpHlRXVVNg1n3L7gEHu8VJJ8Vb5jMjKy6LuPUEYK9kq77Ul4hh2KqRe/TrKPgGO6K9asJTKtlRQQac8+cH30Za0TFq7cqNcpudgKP1e6xnz959rpKDevUcBZWrve9GPKF9RQnn5bahQrBfeC+Wby2nV0iL5jOgD65Vs3kJLfltZ048Y2JXahO/l/jX7XLS2lEoWr5bHtlN4X2uN8MryalpRWtN+2Y+AHC3BDUW07LeVVFVRRR17dqB88JoJ+tJo49pSKlpVLK+FbgNqpxXUnKNAdZCWLKh5zvYe1kNeU2RFrrU1xWVUvqWC2ndpR7l9C4z9CNzXYK54pVryOvR5vdRjYBd5D2BuoLVLQ7SltIzaFbaV6w52jfTVyraU0+pFa+W9NmDfHSIbrBWlFv26vOYZke2hNrXXdyivRoQR/YhNG7dS2/xs6tS7kLz5kWdiRXWQVi6qGWyQ/QjMc5OeTsv+WkPVlQHqMqxX5Pqu9XwrXlsqP9n5OdSlT837PlibBLi6sppWbq0RCnoP7kI+LdnwysXr5b3VoXMe5VoRgSNUFYw8I9pkUo/BNSKsr1ONWBUKhWjRryukp6vop6Vr1+GaFSW0tbRM9u9EXwIOlDy2Nc8IHw3Yf6coo3/RwpXSw6Jb30LKFB5X0Ob1qzbSpjUbKbcgmwpFHw/Cpbb8+pfsW8pnxA69oyqzLP19lbymOu/Qj3Jqr++wt1nRhs1UXFpO2aI/2zVfya8l3m9LN9eIgX0HdCJv7TEWeNeX0Iq/18pnRL6vmvI61PRtvF1qPP9K1m2iDas2UmZOJnXv31nxNJbPiHU156Zn/06RfkT43GzcSmVbq6igfQ613xG8cyur5DFcu6yIPKUlsh+h8/v3DuGXzRDRn9MTvMeyjpbIokWLZHncsM0srn9RFSbM8OHDaflydwMNjAErSTzyyCNWt27drMGDB1sTJ060XnzxReuzzz6zvv32W+v999+37r77bmvMmDFWdna2dfzxx1vLli1rknaVlso3vvwXef+pT6yDe11inbb3TbbLHdz5PPlZ+M0/UdOmX/G8dfDgSdas2+ZFTfv2f39YBw+YaB29/dW26x3T/VxrVObJ1hdvfhc17YEZ71ijdrjOunHC81HT/lq40hq97dXWwb0vtaoqqqOmn3XU3dbB20y23nnp66hpz9//X+vg/ldYV4y9P2ra+pXF1sEdz5Gf9as3Rk0Xy4j9ef6BD6OmvfPU/+QxOmvvG6OmVVZUWaOyT5Gfv35dETX9pnMfk8f//ssej5o2/4MFcl+OH2F/bo4efIV1cPeLrG8/Xhg17Z6rX5TTpk98IWrawh+XWqOHXSWPhR2n/mumPMb/ffOHqGlPPvyxddDuN1iTLn46atqK5UXWAXvdZI3aeYq1sXhL1PSLxz9kjd7uGuuVJz+LmvbGs/Ot0UOuss4/5p6oaVu2VMj1is+Sv9ZETb92wnNyvY/e9V7UtP+9+7O8Vk7efartvh7e+xLr4K4XWD99/mfUtJlnPmAd6D3OuvPC6HPz05d/W6PbnW4d1vFs2/WevM8t8t743zs/R02bc+8H1kHDr5ft1lnyxyrr4B4XWwfucaPcb52zz5pj7b/fLdZrr34bNe2lF7609t/nZuuCc6Pbu7Fkq7XnUbfLz/JVxVHTL73hJWvEsTOsR174PGraO58usHY/cYZ17CWP2O7r8LEz5Oenv1ZGTbvuvret3U6eaU1/4oOoafN/XiyX2+/0WbbrPeiC+6xdx8+0Pvn+76hpdz77kZw2afYbUdN+W7xGbnP3E2ZYlVXRz4jjr3xcTn/to+hz8/gbX8lp59wUfd+sLdok2yuOxdoNm6Kmn3vj89Yex82wnnj1y6hpb7z/k9WlnccaMmRI1LTKymprn9G3ys+ff66Omj7lhletA0fcaN1/d/T1/cUnv1ujt7/WOm7faZYdR+5/q7xfv/0s+vqePX2eNWqXqdb0y56Nmrbwq7+sAz3Hyo8dp/S/QE4T7w+dJ/6fvfcAtyWryrXnymvndM4+OZ/OTWigiYKCSJPEcNXfDF4FUUxwjVwFQRSJgglFBNR7jaBXVDABEpSkZDqH031y2DmtXP8za6296x2j5qi9usHuPoc9n+d0r71WhVlVs+Yc4xvf+MYv/0X828/fkJ4PT9x2euO4c+fkWuTbjz/upfFvf/XGv0v99p63vj+6YfQHohc98eWp35YXVuPf/L53fTG9pv7Sc349/v3tv/xXqd8+9Jf/Ee/3nXtfELzWZ0/9UHTDyPOiz34oPc/+xk+8M3r6jh+JfuPFf5L67XMfvSU+7jMq3xk87vde99J43fjQuz+R+u1tv/B/4n19v3Xz17d+D5cXVlK/v+hJr4jnpvf8wftTv737t/4xvg/+Puvmn4c/5tO3/XB08s6zqd/98/S/++er2/v/339FTz/y09EPPCU8Dv3c7v/d+Jm7U7/9+i++Ox6Hfjzq9ql/vy22Bb75Cb8aPO63P/nX49/9e6Db7/3GP8Xr2KsC4/vWW07H5/T//Pun2w9+7+9FT33Cq6L3vie9Bv7ZOz8Sz99BO+LUXHTD1PPjf+dOpufZn3nOG+L7++dvel/qt/e+7V/j+/uD1/yUaUf453rbZ4+lfn/VD741tl1+/5fS4/tj7/1MvN93HPnJKNSeM/p98Xk/9S/p+fC3f/r/xGP0NS96R+q3Gz99LLaJ/L9Q8zalt22y5oiXPu+twTnCjyX/b35mKfX7T33rb0ZPP/S/one/7d9Sv73nzz4WP/MfDTyb5aW1eK70+x67JTDPfs/vxM/m7b/y16nf/u0DN8b2x//3rW8OXus3POt10dc+/TXRZz6XHt+vedP74nX59a/9+9Rvn/vUnXGfnv2osH3yPU/+9fi9+dC/fin129t+/wPRk5792ujnX/nu1G933n0++rqn/Xr8L2RH+PvztEe8LHpPwBbzc69/Nj/1rNcF5whvT/l/J+86n/r9pT/8jvj+/8nvpuee9//5f8Rzj187Qu3r3DcFfZSLra37Wvve9MrowO+/9sv6549xKdwT3XK5XHT2bLLGDA8PR3fckfiYZ86cifL5/APUu0ujPaAlchuNhnvXu97l/uIv/sJ95CMfcfM9SqpHu66++mp3ww03uOc///nuiisQzbqfyjb9wHN/25XLA654skt59ejsqUbkSuWCO3Boe0r9+8ZefvC+PZNukJS8yLkzZxdiJsjEQMVN9xgb6xUmPBPER3lLSzV36IpeVAOR0btuPtON4OybdEMqeumjYPMXlt3w6IDbQd2GTqfLBLntTJzKcOQaj/T7WtyIlN921tVOnXXT+6bc6NSwyw0l+8+fW3AzZxbcwFDF7ZhQ6vojI+7Yzd2I9oEDkxtMkHaP8uvR+non76Z2TbiJ6VEhMLY0t+JOffqWDSYI6eZxBOdz3aj6Xh+hJBPk0AF35uSsW16suZGZsxtMkPXmoxJn7pntMkGu3RdH/NiO3T2XMEGaMgVlnQkyMjEcR3DYukyQU7Go1dGHH0jRVE/O1OMIzo59U254n9x39syCmzvfZYLsugwlBvN512z6KO951ykX3aGj03F0Ov6pV7725LELbq3dcdt2jLrxyWHXBkPCMy7WmSB7e5E8an/cfmc3Un5w7+QGE2S9ctHpM/NuqdaIozfberTmdU0MzwQ5dW6xywQ5sF1wxLwQqY/A++Gzb/eEq6Csq0+TWGeCjPlx2IuWrLe1taY7NjsfB84vO9DrLx7PXccuxMyB3dNjbggME0/9Pz+/7GYXVt3wYMXtUdHuRrPl7jo1G6d5XLZ/u8vnciIV5NjpWVf3LIapETc+PCBSSBZmVtz52WU3UC25fbsmhECnj+DceVc3arfv6HZX7o3v9bSME6fnXW2+5iYnhtzU5LArkmGyUndnziy4UqngDh7cJnR//H32UV7fdl61cyPKu84cWJ8jRscH3PT2UVEWdm217s599kQ3yuvnCGh6+Bzmu754PGaw7Do87QaU1sKFk7Px+zw8PuR29qLd62lo8RzhWSTbR90Rz2JQFPcTt5x2Dc+m8ZFEMkHyzs3NLLuZ80tuYLDsdh3doTSl2+7Ynefj6z94ZDoeUxHYBidPzLq11Yab8kynySHXHE36vDS/6j7ydy9yc7WKe9Kjr3b7HvYT3ess5QQT5OCuCVdR+hueCbLs51nPBJmS43DFM0FOzXeZIAe3u44kbrnbj3XZYvt2jm8wQdZFZs+dX3QLC2tuZKTqdvbYbevvVK3WdGduOrvBBIlYEchHck7Oxswvv5+fpzfGQydyM7PLMWNsuFR0e3pMkMJKI2GC+HvYaLlDl+9whUJBiB2fuvHERpR3DKUgfVtcbbjzpxdcpVpye65KIuWeYeCv8c7bzsZMlv0HtyVssfV7eGrOrZ1ZcBM+QulZi9AfWDkz687cMxPP+QeuRend7kOPo8cxE+Sqva66zozrRbTPn5xzc8ODbnRswE0rhuCaZ9OcmIvniCOX7RQ6RV4v5djt5+IxtascxYyPjetZXY0Zi55xMLJzyu08KIWAm7WWu6fH0jl89Z7uugDGxvHlTpcJsmtsI8obH7eQj9lTnglS9kyQfRTt7kZ5PfuqsFTrMUEKzkHj5vQXu0wQv/7FTBCkDywvrLmzx2fiyPC+x12R0orybLHOQCVmn1R77/J6asNZzxabXUmYIEj9WptZcKfuOt+dIzwbkumYaw137JbTsR2xc7LihnrjcF3TKjRHrDN46rWGOznbHZNHrt7j2mcSJo1vggnyyEQY1bNU5meW3MzZRTcwUnW7D3SfTbtXacZH7U+sdcfzwct3xms314VTN590ayt1N7VzzI1PYHxXKm5pbtWdOzUXs5j2PTQZh9GJM1074vP3uNzRA27foW2u4pl2EH09e6LLuBvfNuymYpZOMkevNjvu9HFvR+TdwSmkgPaYRXfddLJrRxzc5gbWhUd76VLnT8y5xaW6Gx7vsWkgWr4yWHIn7pndmCMKczLl7Z7bz3UZpduHEiZIL13Ps0Dm/DhcW3a7e2yDdQasZ4Lc5bprprcjmAHqmUUnTsy62lrTbfOsF1Y5bLXdwtyqO39mwVVKRbdvnf3QW4v8PfRsMW/jxmwxP0dAm+j0f93iVhbW4vE9dWXCCGufOu2W51c22GJHHpOM73ZPs8ezdPJjY27PkR2xfckS2OdPzLrF1ZYbnfBMkAnXRqpuI192J+84G/sGBw8mqU6FXnrv3bec7jJBrtyzMb47w91749epmeVamAlSb7m7T3Rt/CNHd7gCtKdy5+bcidvPxGyoiXJHzBG++XfGvzvVoarbe/kusbb6d82/c77tv2yHK6mqX6dOzrrVlXqXUYp1oX38ZIpRGmKCXEolcve96ZVfkRK5x3/qZRf9PdHNr/u33nqr2759e/xe7tu3z330ox+NNUJ8O3v2rLvyyitdu8+qfFst3R5QEEQ3P4C94q0XetFlcu/vF/Ope17oivmKWR+cAkxxQ94r6a8dGuO41a1hldu6gHxaOjlKxImNIpss5VuYTfJxI6iEp3QrYJxRwK/IRVoJkUWk9UF8LQe9kQhq6jqn2hIIa59EXj4r7ehyd8jXFpoYrPLB8pNx2UrkfnMxQm5uB+Xl4n1YOg4tQiUJ5loz/zXeDkBMvhmugKKbEJ9kDmyttanAmR5fTVDvaVwWF1W+OcvdQrW+8NCrkm3ukqUoo8PJc8tTkZ55zKz0osR1qYLvIGLY6jn/8Tafk5TPHFXweTyknLSZr65SO5pjyL83NEF0dRctzprshI8ZCYWibDbOWayxrK86tALwkr44U7tE7o/tuC4KlTj35TVdXcYQwWWZZH1vWcWGVFYPVt3+4Z9zp+cjt2s85664/tW9bewqOixZTAFVURZS7dMGkMe5Iw/HMremhPFYtvq2Y0E9pg70RXQJTpY0tXQiqGUQ788yi31WA2PVqBx1FyguC+FFrW1RPHIwqJ0SLWBdUXpGlligWCcpqKuqdDiUchc6DRni1X1VzVJlP5mGwzQJincK8WtV4t3U+zLKF+vfRDULVJzoQMA2X1N6EFpPYKMzmEe0iC/GNPUQhLBrhuGcx9hv7BgJCmYLnQf/eqCyR+HCUlhofWTQrNJBHQuKLwt9CyWQLMrFUtfEl9ruQzOHumLU/BHCrFobiOMTOm1Cz2f3tL1Os3Fe4zulUltYYcdBqDa6kOildK6kMLkSBgfYSRCAz0BobajrYeUe2iYcW6z61j0n7EtUA+N6kYNtxPTc7nbQfZqDeCneaS2wzLWpPQihdYoNa30UPIPScnI/iucxhqnTo8cg3qP2TDKP5DC/cI1I9QHzQIRy0BTe7/7YvTetqHlpgSC/8StfGRDkxb900d8T3bz4qQf+1pt310N/b4Egl4gwqn8h/L8HRfPof6EixLJYxUCLtAlDhQ7wGewDVkRJLYy51XrQOc9RfEyJQFGBnAZNZ2I4WGFCOwV0AIu93Om4cULS1QrmsDAAhKAR5icks5QwheoQHS7s3mEuUqLyCxW7IRLKe6MdJgrNRtOJoURISJT001U76PywvCnvbUstxnC4WFWoMLsSrNAQH28V10NRMj4POAtUPI//vqObY+1b8eojYfVz5fDkWKIPObjtG29Pvr/6qOznAq4BUV0KoDZHIDa2JnPUWwOFTQGJaM/D5DlZuuZyAG4UP4OhpZsoRSvK4uL8CiOk407xT1vIVP3UDve/VeVOch/2Id8yPjdtEIXn5LXl8dpQ/NS38gLE6NaSEzVHymGRU+WUWcDeOqtB7x/3G++UKK3sHW0M9+qdXUA1QsWO7gFhVPcYVPF2AxVbqK8alibNI4rPijA5XQWH8+flicPR5vywI4O1yPvGYl6sGgNmke5bAdUnhGihFgeE8U2gltVycm04eS0ITPt96Ci3MK9yXSLbMa66sjMs/Ii+ZTnArV4p5PhYBzEPUSwZIpIpx7AeBphEBRbf2G+MIVYdo8Bz8YKcY7m2CGfwi7eG1ysN1vc0HLonagaBj+isKsGKc+ZEsAXPqalMOThWRY5bVhZhlSjldLPKU/ksACoAzRSo1q2D6LZ4V3H+VMUnak8QEAEIQQcg/m0aWlG0qSicfAXWL3XO9jGsmYcPBkXnPfvDFCNlVSI4X4wt8h1MgasAJ3JgrLTuOdYXyNe+NlnnC7BHyB7V1bRanG+8iFOv5dU+xXvCAE0OQ7jAtbQqF6N1JmO8TxtiqhRNVxWzGDAqnl0Iiubm5xJwIF9XpUHxHhUJXBAMVeK6HJ8U4aVgaWHnjmBVQm3jEvgQ64cCjQW4jLmLQPl9KQ9+UbatErmZ5XG32lcRCPJgao3tXrCvKqKM+R69zrcWI4nKedCI+Hoj1TzlOCAVoHR+OVxyUTn32nEPocmePhoCYeI+9ET44n2mxoKATDQrI2Gc5Fu33ZH0BZVvohacqkOKNo1JXlQtOYr67AoBZzRULFgouZhbyygzOZEAH22orOcRpUxF+GBEWmwW0WftMMExc0u5IDMnj9Ki+lk3rkgckwKYIJ09SsWf+++4Olj6tb0N9er3TZjRGhonnUIS4eqgSkj32MNBoMBiMTSHVYSosLmgla54RlZGxyBH0dHX70oRrAQ6s4KFgHc9Pg9TG7Adjf/SGYxVXdUBFXpMh6Ojxh3HNyLvOYBynW2oVqQiwHSoC8uogAImTFulbNQmWWK2HKz0YoJAqs+yZUR36EweAtDsL+cf/2/vuM4tPLLnEKtxwueW64wZz8l+ntYYlAwTNYbW2sGxXgTYo8ubWu8E539R3UZHx1kmuWKUwIYjF/ebTBDMayU60FwLCCYrxgmrHXBe163AqiuYL7kucO2IdHW18tGgk8N3hQ5K/DcAcYuJEqHiRnxsrCWsvENWSB7RbVbciBuZbwwikD2jHO3OcVQVuuJgGERhOeddEuxhWfTiSri8NSuzxMeDfcIoemdyOAy6p5w0jHWyRO9SZW3ZuE4ToCLwhCo2rfMXzEovYh48mzidmrjMSi1tlthlJT82VUVHVKhjIAl2iihpG3e8HZ6jtyXnjDBu9RxdZOUbF14jNNO4A9CTzjkZOwRbivPSNmyPwQaA3SfGt57HCa6yhDPA2AjC4MUkbtI9D8utw1bjeCpzDGrQFsG8ghfMDti0mgkS4TrrkxVzXhb9xLpf2J2Mp9Icxsqp80GmWKqqH5hBne2JrRapoGcb9n4RgbH8eVSJhA262fx7UbctEMRsX/u1X3t/PomvyrYFghit9Lk7XDFXdtGR/X3RR+l4e+X/9dZCNJVOZgtUvfjYmCPzmMhJC+WCF/+GRYJGVBGoORXkBaDi90H6AdkrDhGBQtVmOBTJ6qAzd+ZckLmQopKCecCSdCxDmyo7dsWhcDlMRsUQPdXpMUWUoxRoPCOryqguHjwQNOiaqJyjF9nW3pFgpL0xVgqzG1R5OIILOXhsbZYtVY4hoyjMqxfXpdIS2AowsKORpJ8Dp6RB1ZiohumjcOY6YIVwDHf7CRACRpAw1JQzSKOejqqVsiKi6+q+WYyA9riaDnl/RSnf5NhroOtrJgmZKQJsySj/K06PSxB0XhdOOfGtNQjHbC18z3QTY41THB0OsLb0dRIsaeNYmnFipsNouv/6n5FzQyfWgk4e0/84L5P1lEqFIF0dTq9gWgH01SkfObIKCGKDkZfPSDlkOqJ4J/hZZ7jRIb/7VLAvhX0qbxz3hmzBVDrkxvcqFXD7WJguDxZgp1ehIgR8MGXRHdgdXH90X8Q7DedBsO1UGVcyU/JVpM0Q+FDRVHEMOJ1tVDgqwElMOVlg7+VPng8+wxac8VTJ3c8kKYdkmRZmmTIiwUPxDJbXwmNQaQ54jaSNPlsplGRVKjp6hOtm6m6EyncM/KTmbDC38qfOBdOgCorJ6BbBMJxGehBABJ0enDs7l9KH6J5nOPxOK8cyh+tmuVsB/gHoiPvGcspMvaIGFOakwoqa35iyx+ekyxSznwBYioINC6Abz4xspnh/2Aad0eSaC+cTwDFCKkf8N9m5eJ60u1qPvMIsmdwaLGy6/uQ6atwi3UowjXjNtIlPSSCtszdJQyrBniJLVbMvCSzmEUwTKVncQTFJ8poVvr7P7UnVjtwuqd/mGOfjOkXWF9eoeAnu9iLvI0RGdfCtduk0ny7Ub7uUUoDu77YFghitfc1hl/NMEFKlqdOgHFgxyQPRqNwBITEsuAUatxpEoaYHIna5JSmoJSPKiHDNh+u7a/ZJDotmznBY2qS1KmekY7x4eRgdWfm4zsiZzNNZiXPBL4SBD6aGgBarIxp5MFs602EDO68Wthyo29SXYD4qDYvCokbpwfhAn6sYT9oRoEFSWKkGnYdCDQaAiqKI2vMQEKycT55HA5GO+HgA1uqT6DPG99ouKbzI1gagUJ8MGwN0jDUg0MYuBDQ0QGT9FvUJDmSlymwcVxlqQtODzIE2HH2yBdQrVFrtBJ1+Ao6aYSHSrdbCuheVmZqpLURAgXMXDdT8qhqrGIfM82+D3ly9gHQDxSRhpLoKg1JQnXWqEce+ATb51ugxWKJtkqotUo9wzdEesiD0HD0R3F8Ag4fGbe0VGKhkmfD6CUTq6xGaP3geXvxz41gj8joLiOI7OCXCQFdMDjpjIu2IKRf8flHuHyEaK/qM0p45ZfjnGSDgHAnHlvukNCx4PWBbkNVIRl93n2Ywal3ctzvMhFQt4tpIij6cRO3Y8f2KoOPBdUlHiqPd24OpKZzX27jnGgD2QqmhAEUeDEE9DxI44f55psOwKdsgv5Q8gzI+E6DR4vBMdREBF6Qx8bnr/SnmyrWZgIwG1Mlo6tBRJ3BEBhSYmHHD86D+DG211t2yBKXQAQHDgQEnjgcGeHxrPyxJpykwlS9D/03YCh0wHDD3EPj3Zc/ZCtQlw/qZY+q0Bo0JgnNe8yK2IfBSrfMM/gitJs4p2gY6txgOzNGmA8tIA0e01XidBFS0Rgvnb4egX2ERgCO0fDTzrrADAAcB/b07gtop8aUBaBVaOADptBaN6/2d88bIpQSCbDFBgm18fDyV/me1LU2Q+962QBCjNUdKLiqWXFlUeOiYDmhjajA84dKZpjgV6X06SsjcaTr9zBeMqX9DYYNf5zz2WkcZABEWMwo8mpEjFYFl1FIYLcxHBtujew3NYHSZbI08Uwf8/bzyaFj4sZgsgC0oyGvnJ1/B86ARSHBDCaMy4kaNFQINzIElu0ELkAqdAWM86f7kIOYa7UCUch7jRkW1GvsTIKh8BgARRFsLKzalsggGEx3TxqjK24VxIdNUwtFHndoi9BCMtITWgDLqcavaFDPlWGWKgDLIivWwVgZbpDoq9Epog9K3zxLlxuMhM0eko2hdaop0aoc6AHzktYYExiG3Ky7V7eg2+ybGNA3cvD0nYB8CH3weLeXw+GovG/vD0fT3+Z9+cdhNlJfcXGPYvfBj+ZSwXndDg0VHA185hmJM4KNmtmxsop5tEUAWx3cBAJVOf6HTzGgkn20dlShKCkwVrADcT8F4UQxFOvcUyaYmh5hrdIoBo6ucI6n1hDSElOAn9RCgb5E7uj+c5uPHx87xsKPPtZBpMr4xUsq5MANs0SzBje+ZCsj5Wr+DnAfIsoGTU9S6FWTAkDEyBnAD46Y1XOqL4UeGBCPo3Y6TSchrg5NH8W8VddbMkOAYVM8wokYZQAjqOYjvlZlCUISAgGADKaeZYH9hfiX43giR0AxRTIJa7S/dGhRPjbfrVYtJaaQhTaSxNxnPRfRR90f0H2CTFikV6ZR4vxuHp8NpHWruE6Cz0MHCu6bSuAkiCPuGdjDGXepdYR86FqAjd2nthq2DOU68t0y70uxLxbDe+B7Xpu0RsWawqAEZ0bxmsn/iLwyGHUFOLRpbGgymq1FrqaPSwtdTtNrRJZYW4x9Iyki8D8e4hPVAjh075n7+53/ePe95z3OPe9zj4u8+9rGPuT/6oz9yr351Vzx+q13kIIgvj+vL5d5xxx3uZ37mZ9zk5KT79Kc/7Xbs2OH27EEKw/3UvEPn/7WYq4vWGtLVQJLP9QkYJ9uRvwgDJuWo429GjUk5zW1XivpCzwCLBMEOOlXMZ/Z/wwiKMOGSIqp1RCKAFblzYdFXGsSaGsxWZHQaKTDRNhXxO5GwaVhyV9Aib0cFmT1KiLNXlk9TkNkEzdg3RtQh3Mg89DKMIVaNiXdnNNUQjqxDqyM+xjSvLbfpXK/ZDe1K8vfatqlNNTS6nQuPSR475SQa640U8gyLQPpWoPZXzhAPHVTGLg1mHLok2BLJ5/KSAqVWW2HDjcYNIz/asSKtHk7W2iGpsWLRgVtIxymCRZBeu6Mg+EQmikizUUPLEkPtFDMi4oXNwQULKEhtVwifX+8vKgTwGnLO7ZjIu+mqc+W1/Ab4oQEJod1BAVpqOCk2URlGOiOlBGTyeDYEN+K/waAR8zdT8TTtmwADnTHMXUIkOyO6zooXrEam6fo5Vh3ZGRaO7ECvRgDb/u+DO4KOTR5zXITKYNp4F/MtUwmZDkrQQ6V6CkcZwFFHaYIwbZLihHlUFxOsyPhHvDtN0tABGHItVUCzcJqZdsqhQj0M5adR/JOaAw2kmVjgZ+o8aFpgMsfotjXH79lupycRUKbOEEDXFhgz8W9gpuShayaAB131BC0/g9QMgl9IVY0mJfuUulq8t2RsiuundljqGRo3d1iBGNR8oT4GRU55n5UNWdAV2gIBr/YuySYqnMbYx7tbvi2xrzoIlmjRWepg5c8jwIL+a/0bMrKE2DH2ERoeIxlirBBDF+dIsfVw3waS+aYIfSvxDiKQp99vapFlapexOgyAmzKCQuLZqtQWwT5phOcxrTcmRbLRHzBbfGUQsUsWq3qrXdJ6IK985SvdG9/4Rvdd3/VdG9895znPcQ95yEPcW9/6Vvfc5z73Aerlxd8eFCDI5z//effUpz41rgzjEa/nP//5MQjyN3/zN+7uu+92f/zHf3y/92ng/V9wxVzJ5alIj88FVTOcERqmzbThCLGlKiwIhyNMA2SUtnseRvNKwWMX4Px1xnV0J4nm5ZvbwzR6tTAyklWsg+ZK8TNQRCmYF/cNwIFoqtqAGWVEo0BkDsBJSjxt10OTffosN8uScq4wFlzwGAHXizzHA5+ncPq1AdCHGLisHqIqbhjACVtpVYFvuO7SQphjqfvFCI2gsYO90qE4r07DuvxgUMW+MZV8HrpZieOS3nw2MQhrDzsYBCYbI/J5rO4IR4IEuFDJyKtk1ouoaGPvYu2f69j6GqLxN2NsEFDSx8vB9qY+hwYUCF4xvUcYpEh7SgG4rFaDMVhaI0NC9Ru/sbSm1xzKPSGKs8m8Mzj+2ZkgdZ7zEp14UsJT4CPe3fJ8I5yeBJYOQY+4a2DQkBmTJbonKOIiNQYgDj8rYznXRpoHDXGW8t2hRBTpmFBLhyAE0p7086QzS22DHIW4tX4BK60A+IhYcYJrmYqMtofIlgDLBo5I8SgAFf83xAoFc4FpozryT8FKONod3CeOVa3dxf4QECicAHtGMRkp9N0Z2xl04Cmum2ZfFsNsASEWWTLHgEzhhPgnx7MCUcSahbWsBa2oFNtuFe/OwHT4PRIOo6oQtGsy/E5OJfZEkaKe8TFIEYTdc24uPAa0bWCUqBXsD6UXxsBOcXcScOnsS2yo0qn5MNCinwfGkEjnUcxSK+3HeoYpW5EBE6QMioCbYhUKRhPYJ9TuImupOWKPIQZoBICtXpXiCoAHPloCcQxoKGYX05ILq0ZanwIXCNbw/WITTBStFUUmHt79XI1aUYplw3mVzxoVgjTDZB3ozXujQ8VrLubmGcCWQP69Ocal3Dzr4/d+7/dS3z/qUY9yP/RDP/SA9OlSaQ8KEOQlL3lJTPN57Wtf60YgIvaMZzzDffd3f/cD0qdOs+U6uZwEQbgoKIdTAB9wGJoD9EqSjy0lzlhaQcSNgoiapspmVDWgk9OGQjaNBJ3+QKM4TzV60Oh9K2ABINVYLBLUSdCRH4IgjFii7JimWosyi6BXRxTQgzHT2D5oC34OGg6TMjxl9YdmmF7N9A0FdvF5iDKuMAaYDqT30Y5qmF6vFknc9/oYnFYr6qD2yTeKQWdQ6980mJuPYw9CeyWHakNakLcOYdU23g+yJdwO+QwpwNqB6BuBjyZEQVOCqQQxKKXD7XQQn2CHSBfD59y9X5jFSMsCQYzHJtKGFKaYo03I6xRCu3Ifi7FhpzTplA/qtYgj24AfBX5nYNQurm3QxaNWy7Vuvi2Vhx/vg0kyDxp+ExF17cDS2C1iPIn0DYK+Km1IVJdRuigbh0ppn4THVySqMuEdVMclMyXfAHCRUdWhhYgswVlWeSLYEnGN0ikXuGfl1eS97agc9xz0RkQKDddFUV3NRg8FKMP0LFVqtLB9Mgh8kJWX0p1A35gupsdKsr38kxohHXSnwPx9HZ1GRRIyNnmdhQVbG6IITSwh5o3jigpq8Zs3HDyeSLs1gPqs4I3QMFL3RlQaAzDKSnoiraIkn6eVLmYx9zIbGTwUSVVBmQ5YS/md0+HtFJgqqsXgt8KFpTDYw5TmGLhB2s7UaFCHhf2KG5ideYILEN4XTBzFJmpMhEE+CdLKZ146h7FGgWdDA6lTUO8Qs2GoSyqCfEqHizYAFiqW2GXwimKwcZ/JeMH9aLEai2LiRND4EsAi08WZ0qWDTRxrHDdMHTsNwFYxih3s3Qh6eB1UAer2s3ttnUsuHSZte92nY1zCbd++fTEI8oY3vEF8//u///vxb1vtIgdBPvWpT8UPUzefBnPmTEZJtv/G1njada5TqroWjMXyzJqJQNNhqNyVRH7WjfhUSb7rknKmvhXOzIZLkJEOrCq1CMVrrh2M4Bp91Aay0Fwgw2FQGlcUBBSRAzjDxbtQ6eWA1AQRgn6kn44luh86BYnCog7sj+ZEJegg6BKgEULiNKhENFftI5xuGNKkWApjQAEFonXCgp0suakFL1mhIEXJNgy61smkesTII65J+kbmhnKYqBPTAlOI1VR0hIdADgLVbmkvomIlGwygIS0ABT6CnP0MRbNACC21wb+N9I3UIYzfRCoHUzE0cMXsB8qtZAEfFkOjBoeJQvmqjKsAG/CxvJAcrDQvw0i1nQQOwhddXG3bZWCp0SIcKwP8Uyk99atQ5rI05t758XZ8v/w4mf2hx/fOIfsj06hcGPDLeiV3Fze9Z/p5CoBHiKSGU3NSEXWRF8HjRmYJ1CJYMibjRJeDhm5QEbIPZDuQLk+Gi2/lk/Nh8ekpVOy4R67LHaSA5CEwmUPVsPwaUibbcl2RjlkhmA5amFGpLdSSYTqiqGpko5SMKItrgYaSFnuUYGIumN4j1rV4p/Ege7ABHSqu2U0FEOXbo+HIvabYo4k0JgpEwtEunVgOBiF8K1+Gkr9Ga4+odE6up4afy8p5+j4JgIkaRHinm5MS9RWsIaHFBvFQAUpJPYc8QAj2Jg99kbZi/QqAgxpMcLTJXMiqyMZ3uriSXFtVj1swB1oTybtTB3uyVc3Zc7T1PLB+kLnnW2PHSFgrA0AaGUzlRSVyimdNm5KpqRqQyJ022F0EogAEFih663/anbxrzVFUOELAKNqp0riYQrkjubdlMGNZxtbNK70WlvFGuhbHaloTJHkg1XPJelwAIzqvRJmjle52eT9ZhjOqttol2n7jN37D/Y//8T/cP/3TP7nHPvax8Xcf//jHY/mId7/73Q909y7q9qAAQarVarAc0C233OK2b4di9/3Y6qN51y7lXXENxvrYiKmzIOh+ByF0d40qAxeg/fkW7dwTpGqTSlo8LcsSFi7MpFBinStdvuKoabQULoCmOzm8Kf02Je7K30gRRBm8PHNZVY46qdoFGPuaxk4nvoMShcwTFYvULpnWUJxDhAUACyMnmiJZnAdwANQ+Xx8MV1hQ5YtpKHVuvF3+tr7JNZeJv+mkNHYm97AlqOLOjN41v/ZA0Lhhmocet6ICCm8BHVgtYJff3Liyvg/9Hfo+VTWFl5rbHITQTBqmjTBKSUCjCKDBtybEWdk3Hks4wCr6Jq8nnBahdV3oaEuj1gUZL+3xnJ0uhXuwtB9GOcTw9LFNUIkDQj8/7hNtDjylflPfv/GPa+70nHO7Jmpu+/f3vs8QoI1YmMRI7dF945jmGOA+GngpLyD9geD4OVRAARsqPs/dSUQ3ajWDgDjZhrkpsBviEzE3g0iajfB0KMRIZ4qVTahJAm0KLeqYr4+ExTcVACsaeOwRKn60xiBWqVmJC2CRLcA5h5OaEjkV4BXeaQQotAZEe3IkKLhJAVldKlScE6xEwcTYPhXUzdJNCIjDmSS4rlNlOXd0AJAIwDJDYFmmUCb9L88j2HKZsrN4a5k2ir6VVFWhwgW+B2tBEF/cM8X4LEMTxBK31SwZkRYH4IQMCYpH6zUzog0Ch14AHYp9IqrgwAEmwCM0WvScagCgIkAD1pTuAyv8lBbDFEXNhGQ6ZHG5HWaPKMaKSNuhbsZx2J1Ifa4qoVzaMLzvazuqJiCRu2wsDE4IxirYJyp4VR8PM0Npn+sgRLFGIC2cQkRQqqCYrQIIGx8Igno6CCDGKmzSXBOBvUjqjeV6Yy3faTgniSVb7RJvz3zmM91tt93m3vKWt7ibbropTvn/pm/6JvfCF75wiwlyKYAg/mF64Ze//Mu/jP/2ZYHuueeeWA3Xo18PZOOEWQJwoVMRhCENx0g4T4jiDHz+uAkO5OdA7SXtWNFs2w85ElzAaGCTRagFumq7dhhOJqITSJPRNOZ8YzDsTCJ9pKSiPRQ/c/nE2K4jGq2NQC4mNHpoaDTGsWAoe7C5PzHESyjblhc56rp6BejEhnYIKab5unIssejndzxs43MRtesLd6N8cuwMjYSrTyzD8GaUUpcqLSTPqojyrCXgQ81hzepAn+kviceuovj8zajuktUEiMIf+tTHsFJQ6AfornSoOWtE5nRFGkHh7YQdaOJDIpVCXacAWCIbeCH4U50NV+thCpEHa9kkEIQIKoRmU0AYCz4ZgIgWL2WTOjc4VpaYqqWxoin2678V+tufaYqpssgEpQymUpOpPcpRj0AXL9QxD1VHzeouue2gu1Pwk/PYJ7+Q7DArHfAiQOzoLCzfQ3uDWjzxeUCpZunwAlJWhKj1kGRluAka8nDAMfcUp6UOCauLiH2oTcGoPXVgfH+g79GaAXC+m3Onytdn2c06vBesf51z0lsolPaHnXOUdW8vJPez8NCr5DkBqrD0agui5aLkpgJHmXbKtZROK8HPuG8FA9jLAH3N1EwBToMhwvQwNT4FOMB34tZEjDw+3iACBLswPkQ55yGb4VgGExGiqxx3KeFh9plC63CUyZhN7c+ACwMXCLakBFO5nZFeK+ZEsGe7/cH9EIA8AhcAZ1JpJwZTiexN7ehbemEcA1r/LU9Rfswd7Z2o4HJ61hQurixNBUtV1/crPSH2RwhOh3WTpDCqAsVEWftw4CHNTMWcnzdYZIJhqNZsxaQLvt9qTuD6I/uZs8fdOgDbZ0bYxdL8FX/ZmiDu0m979+51v/qrv/pAd+OSaw8KEOT1r399jHRNT0+7tbW1WBXXp8H4UkAP2EPP5eKFg4sJqzWkkF1GaocsnQE4L+OKbopdSsvDQaNaR+zImGCqTPECaMNgiBQUxbI0EM6lJ/uEeZXx3zCQWW5VqMnDMGizvKxyBFgtoARwQCub83gFsD9I+SUgoEXByheSBTwvKjwg8lJUOiLLiNgJQcKk/wMw5GkM6f0Z2awfSYCnxsNlLl8Lzm2qJOhGP5l6IH8TQnVT4UiUZnVYaRpWSVh9PDG+8b2IqGgB97ZVwQSHVfuIfhupEMUVG1yg81C9ACAKUcK1HRLIImhJY7M2kXSuRiZGBvXeure6EWxgWoCZTqRncNpwHaMkrOqmydgw2Dep/dlnZuhlOWmirK0t9Fqdj4LfMzLIajsDJxGNvu0esU9ER/nay8LReWgOtecV824S1RegixMhpaypxKeb4xy45eD73fnWx8iL4zl5nXuTKGn5/KpZSYJpgmQLiHF3+YQdNcY5+Q6Qxi7YJqoJHRA4oPWJZI6sbVMT0RFUglg7HJzXywr0pV5Vrj0YdCraByXDoWWkXHQuZ6WUZP8yQPO4gc3COV6wNJECFP+JFM7q7SeT82yjEGjysT0qmSSWiG2WpgfHl5WSxbTRxqim6/M+AYTHaYqHE8FxLXZMp7U8S7sFIBC0neJr45wA4CXP7yEmG+9jsCeEM00GUkblHYqe5w2NG800ylfCQHWRwS9Vlr4NMVGmewkQJyPdmr9VaKsxoqFa5R6MTwaVyHipy0mWQJBV/rh2RZLu3HykrOLYGA4D77Ksvewnx01pBZ8R1LHsPh38IduNWBevWdsKPI8Ar7j+KTYSmSBFpJoSPKROU3wMai2dWgo/AxUM3GDfeSbIpdS2SuQGmycC7N8P0H6TdvLkyQekkurF3h4UIMjo6Kj76Ec/6j7wgQ/EZXE7nY57xCMeEVeMeaBadabpisWCjGqJCLLyZGjUGsKLXOQbw5oGzwkPkYI2NShkxM6KijT2jG2OpseCawkro3xmKaxQTeXr2ChMHPo2hUkvJNGzHOjArLXevYZCMO+WqSAUiYv3waItaMtQSXdgzJDi2d0H3jEBFoqf6tKUWOhF9QnQbFnfvYMoVvz3VGKUt/YgtQUR+ZRGCyKAVuSdDrBIsVDAgeV0Z1WgKdSM6KOOztPRbYSNifIyjRHlZMG4qJ6vBZ9zfVI6SY0RGDSkqc4nx6rMNoIOl2/NoWT/hSPI3cZp2qp4Ug43W2oW3HuRVAtEuC/smcwqQuFpRIAOqWo/Ir3nPgA37c0rEZEdp8cHnafq8Xl3en3TyLmR441UuoCeV1kJqH5VwrxoP+xau8+R0f/c9r7SfuQ+2CXjXbGiscLwV9WbIkQmyTRqTg70JRZJQ17MPWSq6XUB+i+VE0iZRHQ+VU6a4ALYH5xVi2uspqUjo7kgcMO+pC+OTlYYjNRAohUppiAjnTfdT+GoY46qYo0orKoyrOhD45r9YeYYu6+eB6sniVKnAO94z1O6YFhb2xCAFeK4OlINL144k3RmNXiGeZlC7w2MVTGnqHOK/uN953pBJmT3iyjodHYAvnGd1uLwdDqZKmWlV6WquOBZFxG5Z+qx1j4pzawG7QxWXdHvV2ekGuwbU8wqJxbM1OfVy6fCuk0EtdS7xnQUAgd8b+pjKI2N9BNtz8h5EOfQGp/8u4+1UVT50il7ZG9awsdaAwloSXtbuFpcqnIPS6SDKRaVARSruV+A2HjuBWrrXpAg/Ma8lhFs2WqXTrv++uvjMri+WuqjH/3o4DYLCwtxBsWb3/xm98M//MPux3/8x+/3fl7s7UEBgqy3pzzlKfG/B0Ornl52RT9DY9FsgS2RFzkB0jHjItMc3LzyQqpELiP3MM74WRsHNAKJhgshtxRoAocBVM58E2CLZo/ccyFcGgy50rll5P3q6jBU9t4xFoyq6Ub2BlW6CbDQ0KAzraOW1DthFKGEfOZuh4y0E9yP+u7RDKMeBnoxPE4024ERcSkSio/CmdVsh/B5hBCaMjroAFUWwsCFduyYJlBagsN0OnGY2tBByVPgzN+3r0lEgZf3DQbTUWhE+zZyN0pDwlBZOpjsv3JlYkykgmK5zRknOk3E3L8vDQ3FyrC0MrJOSYfLMA5TJXKNsUJwQ2tlDMx0gpFvznZNmBYAAQAASURBVFF0TDW9WxjLFPqDsJx2XupTyXu8tj15IIsHpp1b1/nKOTd7ZSXIerJaJkBkAVEG4JhVSpi/iapOWpqB7ytp3IYjQAHbFEOO4oS4n4wmp/7GOZtwmLLK+pbhpDmC1sz5V2w9M+URNPgBgNFa86A+jbUV40mI+OqsBJajNBwDPWzycFpZnjvf4pZFMzVFVvCCbTBsl5tla4yV+kqBEeeMWAEE4CHWaf1OUnSbkXM6X8LRVwyJPK6nzUovsEH0fGm9ewJ4IpNR3SbejzxTf5m2qmwg+e7yBce7pjQcxDkRoResV67/o6rELQEB41kLsWH1aKWQNAI8TD/RmiAsbQzArTmSXFtzeNIUYxX6UgYAmlMGiRDepTQRwFSZpmIzLMT8nbF+ERwvz5O1C4YGx6qyaVtjsA8NwFPPfY2J6eC4KS9SL4Wle3Xaa3JxbYihspx0SzHHCerTjmcrzgER8dcz1wVFOtGlxgTpD/Da9BiXWPPaH7/2a7/mnv70p7tSqRSXw929e3esoTk3N+duvPFG96UvfSn+/nWve11cTXWrXaQgyG/+5m8Gv/eGjX/gR48edU960pNcgdVV/pvbwtXjrliqiggmF5JUtQMuOkYVACHiCMMiZRRTbJHK7jCAfKucXQ4bAAAnRHk8g14f744OZBlx9cPTYSonDY02oiAqf5JlCSWdl2ruA6awKYEHLnJcSHT5RRrVpHTTmGE6kP5NMEt4Obi2wVlVO57RQBoQE4Mm24EGnhVBFsaEjjqLaKgzmElyHxourEpgVm1RxisNp9w1SR54/uu22cwDaubwncBtXp2Wz3BpP+juRtoNnfnKnHIm//k/Nz63n/zIjc8NRLLWthVMI46YJyNerWp/gIiwL0UZgox9BGga/j4F3BjOvSilq4zVNaROFZph9ksme8VwfgoNOpkZaR5ryefhk83kHYsit/13/iNYIpeK/I19ifHfBK2fOijx4UjDpvFsgCMaMNRzfnJcZ7Z+mCCtStKX+mTR1g+IwlHblgIZRZWOfJgNJfLglSPRHkjSFKpn14KMgIISkhZrSzQQTNMkAKBBY1k6PLkHJbB8qMkV9wGOviUYrdkGEZh8vLcEjbXel9hfjPUoGIHWAsnUWqjM1MPOKPfRZcwZXYYNJJ6zcuxYjaLDimbbETiAbaHBBcHMEQ60M99pspZ4bFFFDu86Bb+1TUQHnMdKsQqxNtNRFjogZPTp1BaWx8Y+olyvqsJDEXRt34RAC213NVFFhhVUhO6HSrlweMUJgJbnGkbVMiXmCrYYA0FZ4IBkEQOYZKEWzLd6XWgawt4iPVcFK0RVOoCUDIpw7tbPRthKfKdZHlzZ3uUlVKBidS6ONXFcNW4hVFuoIwiANCimtKXAJwI8FNhHYDH+rafhl+/UnZNyPBd32wJBgm1ycjKWinjVq17l3vve97qPfOQj7tixY7FkxLZt29z3fM/3uBtuuMFde63NeN1qFwkI4sv/nD9/3q2urrqJiYlY+XZ+ft4NDg664eFhd+7cOXf48GH3wQ9+8H5TwvWTbrHUEZOqKcYXGzp9iAvCFmhXM6pCQM20DQM5r4yzfCMxNlug+9HRl9uraNH5xaBeCMumMk1FC4jmRXSCpXzBsDgnyxoWsNA2JqrBxaejnQ2WZENklAwNGoQsb9vdEPfQyAlOGVekPBIQQTS0eGbVpE62mQ6DBZAGtha1TAk5BvuZfO7oqi0Fw/nq04FlRDoz/UHoTmzONtDOZAVVNujY0Nhd2a3SYRB9Yd/IXmH1Dg2ErTz3cUHGCVNgtEGWa+c2v7cZM6iVHmNV0UlvaHzNIdwn84Hzi3ZemNJUXmb0DvepnLE/jEq+R0xV0lTrwVsTRlnneKKT0HziQ9D/nFv+zsemUhR0M+9hShyQfxmABgE2HXAjo8oQm9TNzH83Ilc6bYisPtFl22d2BcyRIjUEIoLEMHQkkjpUeehusFy705Rwg4lBhl9ZzMPSKaDeFm+OiMbqkrA4nninsF5o9qOohkHAD2BomwyJTsb8S1YDHNPUGoPjUUyb48YspRz3AU4zHbi2XW69DFCeTrdmDyadzvX1rnAebKfAv82BJBH40E43AQkykHhpqv8EOFhGnGzQHCoZqcrrAqQTDFLeD40NsJoHHVgCMgANtB4E7TOhf0aCg3KahagwxzA1UQwtHq3BI1lw1OBQYI9Il3JBViCB1ZSgr5ECY1YQywgUCsYJmajK1uM7Wb4Z4s8AlVq3yGp9+UdckxyaadmYuzoDdrp2G4EtPs/6VHVTADw+HuaLAp+z2i535sKlqQmy1TKbJwJ867d+a/xvq12iIIin/Lz1rW91b3vb29yRI92KJ7fffnuc4/SCF7zAPeEJT3Df+Z3f6V784he7d73rXfdLn7whGGuCsJRVCeKjtYzouDBuwp9TBjoBEiw4BRoWalYkk0AaZIgwwRnNqcp9uc5w0Nglsk0AIt5HKPLDWGZeOhaS3JJMM6HxXaThiGNpJgqjKgQninPYB8Jdov8qqsLITa6VEcLl9eAeiMjJxFBQjFBHHmjg04HWFEnptMIgFNEa11ezSspq58sSryxQ7FKn7RD4wHpMI2roZN0UqmWrQbujCZ2cEpxx36pzzBfDR9zPxUOkmsvz0IkXgGWpz3QYNJMlow06w98QwcN+02mMdLlChmSCcNqbNohRWUg2HEBFGhEdZwlwtX8Jmh4cK0XxvbzQxYcnAsHtR0Ms2AOD/5VstzrdvcEq+9BOewkTPPRPpugrHRENcPG6o7Yxx+r3ixE/kRrjggKA1EfpHjv8gEWKmwKYZBUWpJF1BsOpgGDapQBt6IAIbSadWilYS+HSrXSAS4tK4BIvqJXCqcUiqacg5usxW48hB1YCQXzBhCBwpKsSGemI7HMTNHjfaEMQzJMVp2wQhI1ANQGzSKU/sG9c84qLtXAFkqzUSgRissAaK92XgEhWGpbQGOFHpqFpEIf9wf4FAg0YA7QTUmlliNy34dxnpee2xrDuU1gV95kBKt8qAKjIroowBlPXaTBOatMse4YxqJhWjVEapdilhbGuxlBpJQzgipQoC+jQIB9tG0MUW/8t5k4xj4bTCvXzXL0SaS5M7bzGFqLm+C4j4FeZwXuDMrjdndiffDBVSQPltCEq1KxlqpXWqVuvvpRSqr+4mx9bX3Z1mEswHWarfRWBIL/4i7/o3v3ud28AIL75FBhPBfIlcu+880732te+9n4tlzt/2YArlKuuBPqmqMqgJ1+mgGKSF0J3+DhyQqK5LUy4jOpUTi6aBkRngCkk4SgGmRvaGV3dkxjF7TJL1Gak7ZBG3RwIOjyMhEUTEBtTQl4icrFt0Iz4MV+c1Nr6JFNjnLmYC+q9UA8PX1e/EyxBjKxzshoJ72fluCyHWTs4GXR+aETJsmuyPzSwqxy3jOLoaE3eKJebxTgx7MO17ckPS/shhpfh6FvObGev6qfx7gkmCgI0mn1SXAszVoqMvKvnzPtG44wOeX2M1l34WuJ91D00x1YUvu9WakxL2WNWlE1sp/pZ25ZcwyKs2r7TYSjkTCfR0NDIAmU0uDx0uhNMbyLoympWjfFKMNVJN6GLwspWAAdYdca3umAruLC4rpoHxDM07iFFsotreh4pBudYqesiJwJRNvPAgCFUCAfngByc5UVGWtvBdakDscvuFxx4dIDDYqiMIMfboQsi7aeG1JgVeZ0l0NiprSDmtIzUFuo2EeQTKW6qcRyTNVVehECmAniYAlpkmj/uEyu/5U7Lsr4sYdzaNR4EW/T6tYpKV6JSzF6kGEB/QTNTBUDP9IWSnUbFtDayi8gsIiCkBWAt3Qem9qTYQBQJJeNSrJklm2Uj2L3lYF906VgCH7yeOs7Z2Tlga5+Uw3YTgUmt8cL5jvoznG/JLNXjYeR48gzKM2thIFGluLWhSyIYFrPJSWvTFGyV+7NKIn9qETdS6yLnLr6fnLtERbltco4XOlbCPjO7KWx0AtK0nWs7B4Ns5O5FYC7FPDhwrm6LVxMwg6CvTCtUC+16ME+lOl30bSsdZqt9tYMgp0+fdi2InK03/50vleubF4RZWpJCQfcHOmmltmhldJFXTsooI6gwoFZ3aLEtfCaeQTFW5I92j9cOlo7roFJKDqk1qZJb6LRG5De2UPuYudf0BWGoEPTo/oZcWRqu4gbqkDp+MtgSbSyY1rXo/meJKTECaVUeECwK1WfhnFPo7zzSgyj+pinhyIuXQAUdmQy2gxBfc+Y+FkCRGeEJM9dNun8W5VV8zmBIIPAufsrXw0BHEfp/vhHMtICwlCaIAYA2AHy0ICWTFcG1cqKz2CMWCGGyGNTfYkjys7bHDOCCYImgkes+W5og9f5ScGiEDsy03eHpvJsYbLvJ4bwr9IRCm8OqykcelOx9lbCxjbSnbkcNgMa454yShoDOUEu9X1b1IJG/H+5LSj8nCq8/OtWITAwBNokUOTvlg8BHGQ6sEM9WRr3QW8FvXH/oGKc0tZgKGBnPSTnNlmYBgawsoVwRUWYElimwes2kDSAqpSA6roU4cTyhg0FhVeiw5HZKfaryPJwpgANVlNZMRY23Mx2zsGnKZVr8evPy5Pp9YGphHhM2QfysdJhcRnpPspMdlGGaiEynCVeES41pMEYYbMmpanMEQUTKCBlEZQKJio1EFhjAs/okNZRsTY+cCEQhHRR6xKlqJGCfCF22Eio+UbtF30MDhBGppeqdNu0Ormt9+vO5PtMHha1FdlYGs6cy3w4DqwTsyCDWU4KY7zjHFYJAvRbUZco5Sz4LgCresHdiK6Vtq221rXZxgiBPfvKT49QXnw5z3XXXxd995jOfcT/yIz+yUS3mC1/4gjt06ND9jk5ywmuLBVxublYv4HxVyKjqIMQOw9Rc3fKgOosyXazIgiiKNjos4CUTHOhsHpEXhopKwiVdUVRQoRGtqrsI2jEWj1Q6yfo22gaFMyPFWLOAl82NYlFqTt1bMj6KC3hOiPJFe5I0gCwnS0RHjPLL3e2Cu2cLo1rDy2AexH9bTrhB99dNMI0sfYss4yjaHFAh6NHdJwqW22W0qiFJS8LAE0DUgFFWV99Lw7lm0/dJ4BbGOyneuz7vcyYoRSbG2uZVdFIgiOHEl1aymDlgSs0kHRg4tez+5MWDbvvIkju3Nuye88HuoG7gOXVPtDnLJkuvJWe8K4KtQeQt415nVqSxthNgrr0uFCGGbYEgKSFNgA0ECWWWOec0eU4CHxTlZPqgqKQRsxJxQ1lBBcCF0JAqUalXpdCgVVAtJwXYco425mvdKC5OII7ggGR9KWYOHRDjebSV4Cdbi8wUoYFhPw+CGEVoKJUWbceOgJNInRJpP/i+Ka+zKRhM4XlQrwtkyOVZnUwg2OFjpVPmILhN/Z28EpiE4y4FgXk/+wNeBIDMMaT0NWQJ5vD1MEVOs2nZZD+ztE+MvjFrF8BRyukGSEcgjkypItJfNKBAlor4nGETWzaEuE+a2GO8uiL4xUeWAnDDGkIlAnFq3FXOrgb1Xggw8Z6lqyy6IPBBW7W2NwE542MIYVQAZgBRcjX1DGe7zOHoUtME2WKCbLWvdhDkD//wD933fd/3uUc+8pFxKaB1FsjXf/3Xx7/55gVS3/CGN9xvffKVIbzBow309Rbddkxsn9+e1GFfvXpXUO2fNEBBo1fOB8vqNg/Z3NwoNxx2LI3yjbqRUk0MgJHAFOUVAqZErfM1GMvLidPfgW6GFgljFISot8hVVvTiBgRHaSDrvHa2xtTApsKqpmCcWsxoENZAxdSADA2VlZ0JhbnzNeOm08zIuYjIW2CVahxDrAbCKysrMlVlEToeJ5D3CvCsAQV4Td8nUEDqP8ewNlSaw4Z4mhU1z3C0GxPJ53ryCrrlfTZFwgTydKC5GB4TBNXoSOmUD+F8WBWgVTfZH6aGaB2OjT5qAIDnpGSCqC4gd2EalKgi44xry+gz721DagXL4wkElpo9ExuGuQdhFg/mwuyVyEhvwjtQnpXPj85IYyTsNJOVoufO4buTgxePJ2BmZ0cyCOvbZJoI53/hMAh6ON4nNd1HOVZHgVEPZ1hX9qCjLd7PYvg5aSHqhaOYL1erYRFj9TwYOScrojkSTofhWtg9oFUlKhkbZZTjTjmDwqEHQ1ABxUKfyQAeCNiVFxX7kusk+iMqoChAnSKVpMjXoYfEe5Nm3mHNGcePe+mw9VfJiOsctYCE4GpcMr4TXDPJtiicI/XAudbuiWAJbEvPQfeR+kYcw5KdJfvZQcobj03bhkKeWeu8Y0yJLIAUGzY8d/B6+MzqExIdkMELpEpB2HVAsTK4NrKKW20SKV0AnjpgeHQvgh1wwfmuoKppiSqFAohKDkb7ePi47HP+Q59Oru3wwY3PK1dPm2O9wWpQYGzKUrzcXh5gZVc1mAIqgHJ1zkKNJajD6W4UYNf6VmJMI4WG7NFUNaxyWO+suIrnOS5t5/xgb9Js152TmdQXddvSBNlq7qsdBNm5c6f7l3/5F3fzzTe7W2+9Na4Oc+WVV7orrrhCsEXuz+YNYD/xCoExOOq5YTlBtacnwqX3BGXWjoKIv3OWEJvch0atUFCHEUaDUjuWNBQKVOSfbwSpj3EfgFQX5gAKoaKMq4O+W1NlvqDGznJgzD9l6d34GMuJ81HAdgKEOQmGRVNahIWhg8HqLrkIhlpGtQNZarRopEvYVFCheM4gjmZY9EMAoj2WNYbYjLHV7ScNJ9CmDfGz+BAGlZ/GFY3yrIi81VJshXvLALWDwea7ljqFwXixmDCpSFiGyKZ50vzmYssiAq0ZDQbbgOr+ui8CfCLwgwu17lmq9TNudT912g7fkVIYYHL0OQ2QMA2kha+NjQ50ilGG+ap18lRyqEPTQSM4/lvkuLvwvEw9I12liuKXHBvU9FBgjXiellZSRjTVdDoZtVYVUBgBFceyno2uRmIAoEWmJSpAQwjSClCnPyFO7tNE2Wuupal+WoC0Udmk+7cBmkb9zSOWMLaoNlfuk62HHwjy6tKx4nrwbEuzSdQ8WpQgiINeiTW+aE9p4MYKSki7SY0BI8gjgdmwAx3/ZuwvyvKmWJ5gCEDzRlRNE8CPzSgT46lPvUsLEMhqguEmfgj3K/R3iCEiGYr2u9YZQYl7jucMG4agjmADZbDgrEIEppi5PwR+Q5alybolUKKvx2JBp56t8X6KFBoN2K2vBYZI7kXb/ODMLJPX5zEu8XbLLbe43/qt33I33XSTy+VysY/84z/+48JP3moXKQiy3vxD9f8eDM2j0L5EbuU8Fn3k+raP7BHbN0dZBjWDImhRqA3gQ0c+2GhE6NzIkPCjnieqYLawVFzxRFK+sjikBPCWcT/WEnAiGk/uR66iw3wubDwjV1emG6g67BDEK86uhCnYQyhTtiTL8hYvJPvkoJ1SWEr63xlTqPv5pLxaDuKuOeQ/FJe5+NnVYdg6wuq5946+oMTn7v06kKqygbHaGAezpWobGlZeOSsXCAdSbU4nA5Vvs/tvGGtW1ZRMR91qNnlEHrsQjoqlnEkaVIbDk+WAWuwPsb2+txpQuLfNeAjCcE/9aJyT1xn1uY/aZqM7uluWgUsARWvmMBXBcGbJnEiBzqBKF3cnbL8a5ivtqIsxIJypqK9nTueW6UXC+VApGwIsyXA4Qn2M+4BjM7pNtkAqdc+oGiLmKwOc6W4Y/k0IjstCY6LiA/WyOhwcWWVcDbaEpcEUHw7rKcGWPCLF2hkU6SAGi8CqpNFv6pXWpJIaW9w/HCDRbAfO0WR/ilSn6W12P8U8FH7B9Riy7oEE/2wbyConLYBNdU7q6TDAI9a8lq0BUUHApo4KcXTUs8Tl+U7Jaih2lah8k+wXXifPIfvc1xjKYMnIeRVzZC68/vtW3I7xwUqCFH3VABPHHUse413JsomtPve9FrEvQtjbAGHU9ViVrTQQZvVTaLkBFIyP0epOhh1q3Gy1r4rmq6J+13d9l3vUox7lHve4x8XfffzjH3fXXnut+9M//VP37d/+7Q90Fy/a9qAAQdrttnvnO9/p3v/+97tz5865jipr94EPfOB+79PQHfOuWKi41s23bXxXe86jze0pvNQErZBRV+2AslmVZ0TZUlERwK73zkWuPIvStyrHsPOZG4N0RQdNjuiMVKrPTSWMl87ebUH6aB5qV7mmVkSsBAVcGW1KRzZhLELvhMBNVIKgw3abh58bZCnGgq3eXQWocc/pjY+FATBeysmxhlblOes7ElClQ40WtFT0zQIEjO9TEUNDAd3Uq1H23dok0n64/upojeXEM2jMdVqTbCwWAN+PqD/DTXTNcMB1n8X3WQwHOg/h3e0S2LrPhjBqyjGlsVm+d4BIVt8sIU79txVpFoZjvj+ASvhBuf51NH7091bdyrJzQ8Orzj3D2MhwmEQ1FqTG6PlXUMfJqGuackZCz6h9LgGKy9uTObE5JIVlhPFLh6FhvLe6HPVaH8wB7XRb9za3uZaOPh61JZi2U2TVMw1us+oKo7kZ7BM+AzqGloMQ78P0B3wvxCqV+LSZAsNtsEuZjrVqOTrXGBssJazPY5bWzGIBmOwTbKIddYMRZgl2a9FZaisUbr472a6Xrhy3cbnmieeDNVwwB9Dyypkk4CTWD8GGUg4o+s2xylaEPgafU7w/QIw8WKKdITBOlT2aX20E1/Ay9U5wbaxOo6/B6r8ujc3SzgUAfvkWF3fcp4YCmMKb2azODJvS+l5XH2xdtjfMoGX/ddoP7EMCVEKXRgjDKkMBE4Z1bak1t4/AAa9ZgIJKiJktVTxBHM8FxwCfO8s8c3zm21uaIKl2iZFjdPvZn/1Z9wu/8Avula98pfj+5S9/ufu5n/u5LRDkYgdBfvInfzIGQZ71rGfFyJan+jzQ7eyTtsUlciuP2BbMf9RoMNvALBcs5vsl389dKXM2y9BmGLiQnGdlZ2nTyFWKOo8Jtj4GGqJ2Zh/6uGSfKAy25Bu7TWYJDScuzJ3xxBFoQKW+u5NhDBgq6/EuAG8aB0eCuedZ2ifMSy+gJJ00yuX+9e14PldsD0aTaxNhYdf4GgxaZVYEfPA81ek3z8dNpTfBiFpCvjhbWSnV0+kT14Pdm0ow1Lq2fum8fQE8So/DTPWJwhFXTbVmvnm/Aq5ZRkxyAHQlY3NLtDbr/E2DUBWBiZLFeEmlkFgtMu5bbvP5Jf7bMCLp6GdVh6GOh+/zx29uudNzzu2aaLkd1xllSy1AAJ/rE8ppNq6B/a+BAaUdy9p1qKTwsOtxYFyXuufW+0G2IDVNBs/JmztwFlUdKO4HoIFrjG8lrCVjn09EgGr7x3CsvAmuD/5nonfVOrwrqG1RnpHllzr4rQ3GzOBNCaMuGh4Ilj3X5Yz5DEfuXDKBaupDCfIHdStUamWR+k54v+vj0OfAsyEwHB+PgteMiOMWUusqBZAYTBBfFWnj/IpFWEbFClaKyd9yz8bn9vy82Kf99Y8MrpMyVRdAoNKDWNmJYMOVVyXXSSFOXZkDf7OkNZ8bGTslMDRTjBGWa2Xln3HFTIWt0BgrBYEXVl1JRfHxThWQ+st7JvRe/Lw8UQ1WpRPMILIDDFZo9zwERJLPTVSg6XYcH2FrUCeI+iA6TaiEstfV2eTZVG88FdQ20s+N73cBbNzG3iQFamW37PPiflQoqoQBGb1GCX2nGvVBwmlUeu6avCU5QA2aO03omOlz8h4O370SFvFnFSE1Hvh39VQtyBynLl18zgWkZfNZAXDLL0shsWi9P5eYw7+lCbJ581VSv//7vz/1/fd+7/e6173udf8tz+WrpT0oQJA///M/d3/5l3/pnvnMZ7oHS/MTpf/Hhb16z8LG5/ZNt4rtBy87svF55YqpsDGBKEo9sUe7x8NC2UAJM0EH7jM6LsoK0rnXTrMBKItoqD6HyK9NPreQC98aBAtCoeRCRR9R20IDC44alZ3SVND4Z2SSYq46L59NVIcRgISmMNMgM6KHTP/IqBYkotMZzIHVHflNhVGzK/cknWiMhS9Np+lUYByNHE8uqDZFS0XeGzqkNChEycgM1pOlWUDnPsWqMK5bCquSsiq3YzBP0NMFiKL2KfdDk+0zxa1fJgeHnbFJp08dEqnpkQGc4OayorapiRL1yQTBe5OisfP9oFaG1gkohu+t0NToM82jYEU9DZZLmiFh7JPxfup5IXQs5qTrsr71yfKmKQrUJdBzbn3vaFAUlIA6RYx9qxxIqlYV70icpML0ZNhJVZFqUU2jhQcF3SUxv6R0H8IOp3Y+2IRAJQEZNd8VwFihAytFLXlcZwNpZDswuq0Yl0yzoK6Mc0NBUCklDE4B0uXESYv2A6C6LrE/fGuMFMPlQY00kVTVlMiIVLds0Vimo5RniWzmwoBQu2BWCGoDnBBlhXWJWzCN+LlYC7ORdMsba45gn+oAh7Bhwp/zYCBllY6VqWPh5xT/iWfFoI4lUq7HLYG9JkDKxuj+pM+KDcS/aUMURhNEo3oTtJFyyXiMzzMAnTemmPEcGYxAyfqJgvdT2xm0nQl8NAfsc1KHI8oPB21KwX7R5YuZkluB5t2FxF+o3HlSnhOgZWEvUuvJNFYtt9B993MdS2V9q12q7eu+7uvcRz7yEXf06FHx/Uc/+lH3xCc+8QHr16XQHhQgSLlcTj3cB7pV5rqaIIyuL16bGIHRQx8rtq9Dtb1plNCkY6Ynb/5dMGjwKd/FcsAKRoUJHcGFESfKAnKR0cJyUOO2cr9F3nRGvjojUY3hLHAnXOaXxkRj1I62CGFSS/AsI09UGLsUtuvYJVlZ/aJhpakoJ5vbZVXjSPrvzEZldHHP1RpLQ6GF9CK2VOSEQeAoDI60BzMcQWEEhinhafANv4moGD6XcKzMaEn4x8zqMALQIIMpDJB1T8Mo36anT5/H8PnyFDfUj8xISRJOZhbLRqTt8EZnUU5w34HQ5OBgpAAFCvISb1MB0OZQGBzhcyerpLxkpxik0s/W9zdYZJq9ItIZBbDIh6YOYgBJHM98hkKLJ75v+WCOvIMD2VFOnhD8HA6XFBepB4pSXptOJo+hk6VgioB+wegYMB2kdsXOMCim1oUmtVhw6LVtyfkrcyqKbzDkBKtBPVtS9kVKFFk6RqnybudcWA8IQEekhFGlIC/YEnecTc4/hdQSNU6Xr53eNIigWWu8Nqu8NabL1NxnRdtZEWfw07JCXvsQdHJ2DBol3jHu1GLEsS/2MVIJ4z87/aQ59sHoi/chE5JMLR19CveZ52ljXdOVkATAIo4V7kt8aDwsAWCidLgAV7T4Necr9JmfU+xJQ3iYAyoq7DEZUOO3J/uv7iyHK7pE/YkyW8uPBrgEKDQYroCmxzrndc5drUEj/U8HhTDflBeRYj2cMIhdJPVzGmCelVHlsACQtDAjte2ike5iGLUfFG7bV65FXwF2yyXGjtHtOc95Tpz28l//9V/usY997IYmyF/91V+5V7ziFe4973mP2Har9d9ykS/F8gA3X/r2zjvvdL/927/9gKfCLC4uurGxMXfkF37NFapVQdUuamE2Nkzeg2c7QcO1Dkd9ab+8TiF65wzVd3VrLOMmS2hQdLm5ufOUOkQrLIQldCIIOigjlEaDUPTP0INgf9hnsbBlRBSyjCjze+N+8pydPituWIKA6Rr3YcfOYh7o51SdAWB3IAwKTX+6btLQ5y6nY2WXTe2UCXKFgQKRsuH6dAwFp1wPgj6mqQZDyMphapKqHDb8tBFIIEkcSwCGttMt7oeouhLeRv8W4T4LoKHPdBhSRqyUlbgR1MFnS5wwxcoxnKn8Gu65Fs1bswU/z//J/3Kn5yK3ayLnxl/4hiB4J1qfS4Y5X1qHzdBOEddJ2/8+rKYVZDIMn1HpG4hGCobHODWU9PFQOnwJncNc3ECKQPXMiqlnRBCFkf6s9EPhyBiilAOfTXQmfFt95EFjLQqzLbQjISrFsG/aaYZjxfvJNJGVnTa6LMrvwgEjXZ9Vw+LzYG0gK8NKk9RRfM43pRXeD5xT6WEQbGgM58NOOzNO1PtlOdQmGyrjnaYzbVbXUe+UpVOUAqgMVpzJDtM2UNti0IbPkTpeRoDB6otVqprPWcwpav5sDRmizgRRCrZtQaCYY1UDCvJ+kmUDVgqAgiYCWTqNVlZawXW1M8C3NTtl0tq/Mt8JA4a2Vr8bvxWlzxcT+2gFqdd8b1PBRKGzEwXfOz0GhMg0+lle6pjMnPX5r9WquY/82yvcwsKCGx3NqEP/IG/rvtbhX+r6Wl9Oa9dq7s5feelFf0+sllegqNW8/+w1Nrda/+1BASl6Ss8HP/hB9773vc9dc801rkTxLefcX//1X9/vffIMCu9rsByWlQqhncb5o/ngwkBHqFNR+c0NI7rcJ43ecnJEaotG3WkPEZCg0aNtjuLmTmIRfnbbZVUuwGeLBaGvgSBEn8aZlUohUjmyysD2ITKnFeTFdZYMtoKKyDPy0Jeeg3o2C5cxwkPrLvm4ulvST0qocDN6VxTUqNFteTfTbsKRl9awvT+d+6gExyrLuWcKi5HjkBuAZo+mIAMQaDOfhEBBXS00g8ZDgHNfXILeTIZeGVkIWQQLITQ3YIBN/KzmEWgSy4b7nLq3fKeEkKcBcOlji0A3IpNVnBPgSvwnQKkGQKmilJrYcKbKqhpnqIyuBo2zDF/h8BjMorxiHYu0NkZWjXkw3s7QvBHnpHg2U0ni9zOsJ5FVGaQxktyQ0lpyvDoisLw3hQNyTmBanHD6ARTocSsqRoi1iI568vnCMyTzszEaHmADs8aN0kwM0NWzSnVyOwICnHsFi05XziFgKETLbTaPlQLJOZ4gil6vmHZCFkF9jPpU8t4Iu6MP0fUUa8oADAVorNY83gOr4lJWBS8LuOA7bWpDqWaCvtoGIiCRoVVhNUuAXIg1lzLOSbuLlW70icgY4XxdMQI0qcpYLrhmF9bC47l7EN2J3vmpZ0QWXpL9ERgD9z59MMe53LDHWmo8MNDIaxasW3XO1enEcCktD4aXP55f61sJRnU4yJdKNSKoxWeDOVrvs65B1EJ1oK321dF0sZCt9pVrD4q3aXx83H3Lt3yLezA1D354n4yLSW27TfGnc8tIuYjaGtUaUgY7xccQ0U7lxVtOlxFpTmltEHztw1DTxxaLhAHWZDkIVnlTDXqK1GFGXiqbl8nU57Eqk2RqUBj3M+s+0TgYOMc+I0I3rhx1OI3W9cjUBbWa8286vTTUlGNfR7TiAlK6eKEpEAmLPkGU4RPh9CRtYNe2410RIfUozOpQrAICF+0RqPsDBMnz+mOEPIyE5TMYJgUCLNTNgPPRhPMhwJUYkIDxz+vJMAJZkSS3gmg/5oFCDUCDqgJAsIhjsg0nTzBMYmMTuc9lvpT4SNX9DDVXbifLk6qxDqu2A8OxNSK3WzoYpa45pU0wl3yeuBUCk0rskVTpCkA+CuPVxwpBIWzfZq9AaojBCEvrGbnwWoCxYUVJ02krFjBrO910eNZTi/Q2qbQf5LUPgF0m9Er0EOA6o1Mo13fBeGioYB0dFuEYAlwpKHaXrP6Q25xJqToqwLNKfw5TnmO6bmiS6PSH3Ob3vT5mr/Mr09QVw7GMdTGTQYrrIeCYpblDsUpLA0pry1jVSNhS4EAfTA7dLBvEXPNTncB2ffS5u2H4a6v/qes0ro3YnSZaWRpjFmBHGzQ+3mAYZMtDOyXFPrF0k1x/VaYGkgJabsd/JtHEpX2VYDpPal4wbLCslGKRAlMN2+S6tdAHfmYAlO+KDoC2Of9aa7uao0U1LLxffAa65PBGH/sRbL+YWnTfGJSpY2y1rXaxgiDveMc73IOtrRzsuLx3SjtW+oZ86+hY0GEZPMmVMfm4eoUMMxbOJbN5exDO8J5kViyW5CozOqxqQAZatZTMpGPlmgSfysn+eayMHepZKKs8j5vQAhK03Er6P19LVua1prQASlhZxweS8w8WUcZOoRjLTdwbrIATlWT/0VJybUUV0lhF6KSGfEqep6jUslqdfPDe8PNgEc9GWVot9HMV94bnn1mVFRLOnkqU1vNwgPMYT0WADinnhRGFKXJGw85XyjEbQz4qnOFiWZVqM8bK0hWgXdcylFGXoDTPHFpYcc1Jec7cjloQnGgvwuM4B9V+OvP+OgEw5St0+pPPZXWdbAWMjyq261SSe5aVWNhSIoBW472tj2KswslrQ0Q4WtHiQuFnXVoo2AwkijQPtcIgDkNuGnzj+CIIU8wow8PbQQ0ktV003Z0nm2rc8trqO5O+LR/KB9+VuJt4vAtHcW0QMRRgSyTvLUG+gRPJtTUA3NCZ1dR1qwSoAFGUUW9lnYgSu2poiQhoH2LFWal8RKStlMf476iPijgZKXYWw64JpyhSKaN0EggeSoFLuY8FOFnRee3wWKWmeT0ayLKYIHzWBKhSDAkrlY67ZOgRCSYHBYUzpiQRxReOZYbWU27zFE5xDh1IMticmYCGwdI0K7KlOmGcJ4s9YohH98P4Cf0drh5l95ONaSJyrMqLZqUsK0iXEoA1yIPiHRoi0CD7xqDh/JWVIPuEAEB8PcuW6Dk2soJCMSgUhYNKtAd0kIxVeVAViLosUvC7T1aiAZTr62GqElPuO2BIxn/3wI+2ChBd9G0LBDHbJz7xCTc7O+ue8YxnbHz3x3/8x3Fp3JWVFffN3/zN7rd+67dcpZJBe91qD34Q5MHYXnD9P7jqcNHNthPrZKVdcfl8Li6zN9SbvRu9EnzDuWQ2r/dm71w+55YKiRW3Csrr3cuyHNngnpYrVrr7LdSrrl1rxk7VfL2apqrncq5QKblOj77frjdND2ylt23c18Kg69T9cbvbzuSHUkB1oVraAAD8cTu6YgbAgVYhsY4ay542011oOg0Mq9Xu9vlKd4X0Xe40m7GzttC73pSIYrW4oQ3TabaEJ5CDpTJXzbtcpRRvWyq2422jdkc4kvExegZhvlxyUS9k1mm2XQdiftr5KlSK8fPzLWq1XdTLsyui1mq52O1/vlRwxd4i54/r+8CIOB24Tq7icj3xrbi/reR4V07fufG5Umi5fLng8oV8DND4vvpjDwB48dts9LeUd9sHu2PQbzu3mqy6VXgL24tL8bb+X3w9nbpr9fJYx5CEW+2FJIqlvNtW7X7fbkeuWY9cOZccrwSt90opcqVeXnG+03YNLSiHfUrFXLytB486ncjVapFjurd/UuvN3+aBngPZ3TZ42HiY+AIDlUrONV0uHudrvUui9uM6QFUs5Fy5d1y/7SLZJvE7DVCod1zf6lHBrfb0EWY7gymAzm9bruRd1LOO1lY7bonUATQ/xipIM2iuJs90HnNPrVOKHb1yteAWe/SqxlrbndMh9Y0D+weSWKUn5gY35oilhuyLB+n8e++bf3e680kajFxvpQGwX3rbbvRfgRWFarcP/n3oNFouWp8j+E705hS/rWfTzFciN1Dujqehdpdj3Woqj6lYTuYIH6XrHbc8n9zLqS92v8sXunOEBx467ZaLoo5b2pMPRlNHzxVcrudRRw0/VyZzBPdZutJXgPBzRN61hiLX8VVQ/HuvAKJ1xyBXKrpCb4BHrZaLmlZkNhdv648b/+06G3NPjlHf3nHzhYIr9EAcv12n3RaVGFgRp1PKu1yvAkfHtTfmnpQ20WouPq7fNj/gnSE/V7alY0jQwG+73gf/HDphNW+Plfm5L18oOo9r+239vej2Le3o+21L9VJyXA1Sckj0jtvd3c+VvW01wy/v/+XjZ+cdEf/eR82mawvHEPes2N02/t6/P6z8AsAst9p9l/PF0sb+7UbDTIPy2+byLOnasDUkct21q/tb5Dr1NAV04xR+nPtteyft4LjxeQBS+m7mS92B1JiOutv2+teZSK5zcKTWfX8qJTc22FsL6i03oKgDXENzMMqbtbaLVAl630q9tbQ40L224VIjPq7ftgQUhet5qbetb626Py7AbUxEHZdzxZ4d4b9vN/y70Ym/Z1sP5Pht6z1P1W+7BkdTsNv82jjgn133u0pUc1HPjqhibR7orc3eVhwsdT+3mx3XbnVcESjIuj3i23JuMF7vfTu/XN04brefyXbjlVVX6NkGe6rzG8edLCR0hUHk8hXLedfpvRt+26XeO+XbDNaYxeZAbBfke0DAYq3k2r2KTp0ofT+83bN+XG9zlDpyYa5DcdT3Yf2486vl+B77tibUpp07PzMSzyX+X7tW7M4RzZbLkbECcGBg1t+H9fez4zo51l5P7nPRB9mKhY2qPX6M+fk9vidA8zrrZcvyeVfaWLsiUY3LKUBjfT6J9y9EXftWTT0b0ot+PJZKG0CSf5eLYIlgSnAF151PNo7Re99yecMAukjbVolcu/3yL/9yXBlmHQT5whe+4H7wB3/QPe95z3NXXXVVXB539+7d8XZb7SIHQd71rnfFZXLvuece11AL96c//en7vT//+ykfC37/zIc79w8/k/w99D+dWzUqVn3tVc792y8mf29/oXMXlsLbPuqwc5/6leTvgz/p3N2gE7Jdvce5L702+fuan3XuRlmBa6Md2ObcsTcnf1//S879Z+Jri7ZtxLnzv5f8/XWvcu5DN4W3Haw4t/L25O9nvdm5937WmS36v8nnb3+zc+/6pL3t8h86N9TDfp73B8790Ufsbc+9xbnt3g9sOPeidzj3u/9qb3vXm5w72ItO/MyfOvf6f7C3/eJrnLtmb/fzL7/buVdkyNJ88pXOXd+rUPi6v3fuZ//M3vaD/9u5r7u6+/l3/tm5H/sje9u//2nnnnVd9/M7P+TcD7zV3vYvf8K5b39M9/NffcK57/hNe9t3vMC5531t9/M/fMa5Z7/e3va3n+vc9zyt+/nfbnTuyb9qb/va73LuZ57d/fypO5x74svsbV/+rc798v/ofv7SCece9XP2tj/9LOde993dz8fOO3fFT9nb/uhTnfudH+h+Pr/o3OU/Ym/73Cc6984Xdj+v1Jwb/kF72297tHN/9ZPJ37nvsbfdmiOMOeJ1fc4Rb8Ac8dzXbD5HvLvPOcJtzRH3eY54Y/Yc8aL7OEc8+l7MEde+rP854tC9mCOm780c8eKv8jliNbEjPvRAzhH31o74Pef+eGuOiO2IH3uA7Ih7PUdU78Mc8eL/pjnifz247Yitdmm2z372s+5XfiWZ0P/8z//cPeYxj3F/8Ad/EP+9b9++mBWyBYLc9/ag4FX95m/+pvuBH/gBNz097T7zmc+4Rz/60W5qaiquGEMa0Fbbalttq221rbbVttpW22pbbattta3239luvfVW903f9E1u27ZtceWZJzzhCXEhDzYfvP/Gb/xGNzQ0FG/3Ez/xE6lg/n1pc3NzbseOHRt/f+hDH3JPf/rTN/6+/vrr3fHjx7/s83w1twdFidwrr7wyRrO+67u+y42MjLjPfe5z7vDhw+5lL3tZnA/lS+fe32WbLnv5z3dL5FKEsJjQ2dbzdNepqTrPPm5+20JCSY9AY2Ue4sa2vao4vjKNp6ZGSpxpgyGa8+kP5Y38yXZTvmxUlfaK/IVitw/DJ+qu3W66qEcbzS8n+7XHuyGTYqHsVnZ1t2+3mq64JrnSNeS8d1BmseOP2xtKQhm9xzQslNd54Z462YzpiEK8DXBc0XXp6/H+rZbLofwf74e/DE8X9Nv69H2/radEahb/es6lpywWe/fd0+KboWe2vk8nocXnYoputw+DZ5N7Vrr9bLdPuYJrH9nVPa6njkdt1xhLaIwrO8CvHkyo7o1ql74eFNTL9Wjmnr6e71LdY7q7UKAH/djTPEsJLX6dQt+9cFZO6G67TouPt+3R4kXebe/exH3oCSKuU1N5PFKg8+X8Bi0+l2u5qNEdsLrqdaHY7lLtSwVXLnXpz51G05XA3Rep3oWCiwrrtPjutuutjH3KhZbLFTwdvOiKuSgej+1arw9Mr+npe3i6/WAvh9hvW2jKMAvp1aViJ06Rir/PRa651gxSsOPj5vMxDXq9+W25HZunVa+nwflW76XX6WP7++zHuadtr+vqNGstV1YJ5hu0aZUOU2zWNqjuZSUmM1RouPJAYYNG3aWvy3SYJnIPqoO4tlo7Tn0KbRefazC5tqanr/dS29oB/L08UHSFXMf9+M3vd+XVupvLl91bL++GGjWNPV9N5ojlWsF1esddgf7Ouk7ROi3eU9/XafFMKytgDLeK1Q2qe73epXmvt/NrScmN5WYpTjvw2y4uDcTpIq7VTmnhFGd6qZGeLr2eBtdquTxSxTr7kzS0gYGGy/t0mN62Db8W9N7PZh0aMa3eexZTx/Miba9cRSpDL0Uuvmc4bqvRSzVUGjvxcyh04mN66nitWYzT+/y2tUZybU1cZ/zO55C24g/ea6VqMtZGBmvddJiSn1v93NNN8YvvNdKdmuvXVii4ak/Q0b/3y0h16l4D+pDzc0+SDhPPUyp9Mr4HXqcm7kMxFkWO02HiFFEcF9UXolYx3jb+7Ddqs3Z5slPBH9fT4svFjWN1ao3kt43teilI+bwbHUvem4H2cjDNMd6n0E3PjPsW5V2rN/fUW8W0BlXep7/6PvT0A2pNqfHVTu7hwsJwnOIS97WVD6bZ9O5u99B+Puldip+DIyVUW1hOjj20kCxm+eXENuA0uC7VtW4beO0Rn0oQb2vog3j7ZL35bXMoSVqCeKXPDFm3DXxFoDgNrtNx6tZu2Eo+Za660EvVa7dccQGGRm8d2zh2pbox9yztLG+kzNVR4ajZ0wnyNke7V1417oMf86XwtVXXEttg5La6SPUpLSbPZubagTgFxG+7vD/aWMNF6foBpPr6NJAq5gik4LpVlsDOJTaH/3vep+H2xis1jJCK1xlK7Ij6mBw/xSGkBw37OaW7bSHX3Jh7qDsV37dWLw2vVHCNeqlrczRaQgeLBl5lvBlv2z1W5HYPJrSnyWoisDFaqrt8MecKpUK8fvttfTqVb2vQaVtsdHMO/Tx1pt5NWffj8cKZJC09WpZzfFTtzq3xNQ/W4/nEt+HhZAwNl3v3opBzhXLRFXoP3r/LF1aSlKTVZYjBLJc2fIK4Twu99J1azd36K79+0ZeDXfe1jvzCV6ZE7h2v/u8pkXvZZZe5yy+/3L361a92AwMD7k1vepN75zvf6e644w63c+fOuCTtwx/+cLd9+3b3hje8wc3MzLjnPve57lu/9VtjvY4vpx04cMD9yZ/8iXvSk54Ugyq+iMjf/d3fua//+q/fSI/52q/92thP3moXcTqMR9Ee//jHx5/9IFta6nI9v+/7vs899rGPvV9BkPU2cHzUFcpVIf5V29P74HPL1w2gUncl71TgaLJsJcSZcvlkAS9AkDE+ZDzJ9wy+2CCspkteKu8+0dGoSkkQQ8x13VANbUevMxHiTEnri3xMigjmm5WwQFdH/r/rb1S6jj1FybB+Sj2oiijhGbEMK+bNrgMf1l0gQJXcworLabFFc59KuMRtJREydUqIkwZybHivf44dDm6Lkm5wBKJUtQP/m3c2km9yZmWTgitBGZ051c2Nc/Sc0Vo5aBAJn1NTMKkxBkM4vwAB19WwMF98zlZKMiZ1Tl1hgeViKU5AdXstssYmBQnDYm6ipKu6NqEzWA1XU8mqmiKeVb9CfdCXYBUbHouCrfE1oKM0MLm/dnqr5aZzvQor1WIrfCxWh1m0r7OtBYVV2cTQsTfG50L3Hj6/82E3Wq67Qr7s3r/ysG6flTPbXoGOCkRnG/jcWnf4VNnd+HgGkMf+16lt5I/Xc87j/vt728T+fmotOVcckf0c3L9uCNddGTnqPA91hlqqnEkbdSLreYDOC73v/by5fm/8LS36OTJ5EQZ6TopveZynKwURVkpdvwK/9aqf13tTTw3rQbOl9mV56WIiXtKuJBN7tQe0+VbxOgleo6RXErjC8cDnuX6f/PmrstRYu1GW51+/bFaGUiWkue4W1tVpB8uuiGdDGM8/Jw+qbPwNke3WbLIA7fxQcv3lpfVjdZ2b2kRyxNXp5DpPTmPcjbbttYRzD0twQrciVR3HeEXzqCY1eArH8kDLJuK6nU3EVKkfJub1YUO0T2uf+KnHr7U5W5i0Leb4ijiEEH31B+j1p7Lo1ZnK8W3Ea9c93vrfHQ9i4FhDI2aVKbZCDXP0EuZYCElHvbUw522ODPo14xYrg/L9ylGctpVP1tDT3eHh/3Fa1+unkKQyACZK+cTH8McDpr6x3fr+XjcKz6OD8rK+1QBQreHeCNHYVMVD2BAruaB4KO3LBkW9nXM37Ya4/EiyYQXAsF6nOa83VmGjX0iewfA9SV8mb5Jgz8rOZLvaVAJozE0m25wb65j2JYsnTH8pGQRDd/m68Fgzeu9Rq1V0t8rL3mr/Te3ChQvu9ttvd29/+9vdQx/60Pi7X//1X3e/+7u/6770pS/FIMg///M/uxtvvDFmZHh9Dt88GOJ1O371V3/1ywJlPOvj53/+591rXvMa9//+3/9zg4OD7olPfOLG75///OfdkSO9XPytdvGCIH4gefTMo17+38c//nH3sIc9zN11111JBOF+bnOPbLr8QMHllpMJavCU4bGpUn4D55PtVvaES3a1tqnqF6wGIkoE2s4TmQDiWIaSNZ2qrNpx7Z64Ze8k4rcOKhy0UTKRRpgX9wtVMdCHI3AktlGGFqMQYn/cT8HEyXIyjRK5qX34N28HBVzpACtn1AIoIlhhLA2qK33QAZcK9vbFUaeuPhm2VguL8pWvLjJ6BaMckSQ3qCJhRuWYIqyw2MlZ77Map2U4Y4x6rgvlhZol0sljhVgZof2DDnjgHFX0jds1gIyy+lHWORuI2rLp6Y3O+Roi0uvRcV1ppr6molJGVYhOHVV4lLr8GhxYGqHiuBmlhMWYJEBljOHg3+tfF53r7C7EK5MHBU98flcKfEztEz59383aP+VYGpVBeEpdTORCZeheVfnIN+WzoSMwOJ98P3gO72ovErreVmGUz0wMmRXNrMZ7UFxM+lMBoDWqwK3yMkQcsUasTid9md0x2FdfyJKkYztwTj6P0bvBAltMNqyjbHUNn3UVFjqGVrl13VDEzA14H6XXVqb5WZ5Tli5NPpfwbAu1or3+iTEZ/qzHE9ddlo5lRZ2R48kBhm9FnWnvtD1+W7DKRyPBBtLs15xR/SeMXwcqZlCc9j6AxpyHjHPqZYTvOO8n38PU0oO5kHafrGbCyiTqPnEuZT8xDxeUSDdNNa7N0SjLwrfNSoJcFzpgA7WxLuiy9PzbnFcjezzw3nL94L3VZXkrs8k+1Znk+4mbEyQ799FENGb+eY8T++exZnZK+FyQAKroJ8+PSxCsY9z/+SMSqBYVYUpGaek5rdCMzzjn/KHkeSztkcUT1ufCuDrMJ9wl0x7MwqhelsELkPqKLI94xCPiKiy///u/H6eoPPKRj4y3+djHPuauvfbaDQDEtxtuuMHV63X3X//1X+7JT37yfT7/q171qphR4tkew8PD7o/+6I9ceZ1V71wMzjztaT2xna128YIgT3nKU2KKjx9kXvn2xS9+cSyU+p//+Z/xAHggWmG+6PIwTHxb2YeFRZd3Q7R/7TJM+FiM6BiXWT4yLosL55iGsHB6FRPEevMFEyTDQxCRXmzGcpjazmHkHw4TDVdR91x7BaI7YaMlVYKMTYR+sA8dFl1mM3fvJ06zD8KKM/oVb5d8JB1aRPGVEdhGBJNRfJ1OkhxLRRdwoYNGudfWqBy4DYy1Duj2wjknFTVmjyAiXkdkFOMBGUyp+y9KQJMpxXcC5/CtsFQIjrUWSukWRkHDV0agrx4U+kwQZaAkLbIleEZ817jPkNrHbGlS1aatA5BRfI8bSkq8bizTXCegompbroINRDYSxzrZI7paAo1qMtcYYUs3zpGgfVdazvWiq55BNX7FbOqeZzXJXrG34ztllgdXZY1Z0YagFFkdmt7NVBurNQBkdZbl8/RR3/W2Bkd7dReuRdXRzXMuRjlKOikEIXRqZgUg/ugxOqbJNjWU3Iz/nmJpSfQFr0dlBuMWUVLf2kMYX+hbYQ5pMiqgduGhRPhZZznD6WWAAc5pq5d2E+8zgDVbrdMJdcC5GlkZcGA1eEYH0GaJgi2onEmWxxalqjFH5hR4ySpJLLtZQER95ppk/zOPnRL7t4bxvvF+4F3V9gfnAcd+tox1XgVlWOaYc49YC1PAJKMiwd3FIMh8HY1gR6Y9Ypkd7Ke2gQxUR4IGGbvwHsIea2Mt6KhqWsIOZZ8xvrPmS1EunWMA+xeR+hafk0xGY47l/Obb8hTSiPclv81fmYAY+Wd0WeMaKPGtmWQsujbeacHyVIA+388c7KES5p6sErminDRA1uY43iGwR7s75cIpSWA4kv0Sd7seYkNdIi36yqXYsHnQ4sspH+vT3v7lX/4l1gTxUg35fD4GQP7xH/8xTk3x7cyZM0K3w7eJiYkYrPC/fTnNp9h85CMfidN8PAhS6KWqrbe/+qu/ir/fahc5CPLWt77VdXr5jy984Qvd5OSk++hHPxoLzfi/H4jW3tZw0UDeubVk0BXACtEtwgpeWkomuPJCmGK6SkAlzmGFEcXFmFEEPXlr2mzSmeDXOR25IauBu9Oa0MwD9KGNOuoEOwi8KMkCYUgr5rdtHBmRHFHvnpHFLEuHi7lIFboPTBAjRUE3vdBvdEV9n1sohQ2iYKqSjJL6VkUVgOV9UXC7nR+XY2busuSBrOwL08jzA4oJAoOKYAOZIAQaspggTOdY17rYrNEJt9gjmtVhpXawrZe4tXLzQ8DDnK/1ubG/cn6oqZEJCLjgvaIGAx2hFsBZjpnuF+xA8rG0YFvyjSk8q9HkRY5ExBAvq55H6Cjimgse0DBScPi+cNz41JBHPH/JnZ51btfkstv7f3v6LRnvNO8zDXn9PDkGOO6sfbRT0ACQ1Ma9aQEkFE5q/AU+GiyuEmjXu/5DjrmVnQBlRsPGvgaai6thhsP4bXhv4BhTZ8i3849IOn2+G+xKASrFRMYk3Yco7BSwFDFTMeK+odLI2iSAn202cZERWEbhyXxI0e3Fb4iOFwDQANBpAZzpHjsMKomhptYva7s8gQ84lvpdyaNvHbxr/KzHVr2nSRF/xrhfIXCDVEL9enGdiaCZYLI14oPgM38yxr0G94XGFQ6WlUpIpnCE+2SQXNO2kQFccCmygijdc5I2hb7gc8ruEgaNCwa/cioIIGIvcOgLWJsLGWNIYEK0gWCQabafuDaL2Yo+txS1RwSmCEQxeKZBY8ukLYTBjaVR1S+sX7wfTEVM2Xqc/7FON6HV1RoBU1sBjpLp1QmChwShdB/itKP1/bEZyyLHx+h1R2HzWw3NV0thsyqn+O9e8YpXZN67T33qUzHb40d/9Efjoh0ejPByDW9729vcs5/97Pj3Xbu60Yh1jSA9N4W+vy/Na6eEmveVt9olAIJ4dM3/W2/f8R3fEf/z7eTJk27PHuSU3E/N0/zzlZajSdqmo62NeiwY9SkYIGu4xTBASvMqyohjcwFmVC+VglM2HBtGUbgOgboZN0MYVCxMGX4pDQ3xmf3XIIigT4YNcb0wimPzWJahklrk+jCO+m2MdqGfKaDDounS0GIevUojEmKmufA4YTqQb4vbYFQjusA0rBPfKB9IDvzuMiI5zJGvKlbJurCodiYZ7clyWrkdU1j4vY78F40HJyL3YDhotgPTUYK6Ed7hoj6KZ3lAW4HjdnklQTPbs2CLpHRcXDgCnBX1ID1bGHRgn4wlPN2RHTIvQUTZ8JlaHxpsIpDEZ2Ad19pGb2d97vYtH+6zTto3WBncjgCTSBtSDCbed6HTQ2AX+2sQhClFgiqOz4qcpSbg9HVpR/v4M9WPsIoFC8/Qq/FtbSfmDkQgVw6HI+op0JnONea1DtIkyVzsHs/S3wmzvppIsfBt6XLS+nATCTrr+ZLOCF8vPvZU1HbzCL9c13QQwPotC3g3QBRE60Umh17/DAeUkXbtwOZ0CsbGhrlgGlVmIJYDjPaISp8oQMyLY9WaLlLgQs54TiLNRF2nEaCwjptqhg0j2LR6H/bNer8JziimlddfCe0jUnP0pXA7HK/DOY5dUfu3yPLkfIUgXwoIM1jEBDHEPKTepxaZEBWsMYNZRmUYFBLgMu+FCgSWB5tS62r99Fj/staWuhF44Gc9qYhxbOitpN5pjlWC+OIdUB1d/+0r41c/eFr0FWCC9Pb3uhzU4LBYID/2Yz/mvvM7vzPzkAcPHnQf+MAH3N///d/HVVrWj+v1QDw7xKemeL0OL+fwiU/I/CS/fbPZTDFEttqDrz0oQJBQ8zQiLyrjUbe1NRV2uh+ap4VHfoGhwJUdkJBOH4WsgQbzRW8qWpOgVWKRIUNEAwoiZ5GHItKfAQ6ICGAYtE+DGMYkL/Npw99n7pO+jOB28jMjZGEAQW/HKKFougMWWGIxRHTKJ/vZCW/XVpooIk1ERGGwUUYkjlTljkG1ZnQkq3XgZBIoSDnE1Dih0yvSeSLz2JbWBw0Y30q4Bh6PfVsBW6Fel1GpNoxAt5R8rsyCwaVopu21JIw9MIPo08PRrz2rSvTWBcGCgUqzL0Chjfs2DFFJgk1kqJQz2DNMhyGIlAVicB8BUDEPPiM02oFXUgPwpFkZBKW4XSxGun6qyLnzM10RgmhFLVVwBAbOJHPpofcldNhjz5E0UTLPymDNknZcA/NAC+2u7WSePz6PUHRBjoEijH/hzEaG4a+ANFZFoMMTIYqvUzPpcFAIlMCPcB412EPgg8+ajITITmXgoyaTMU9RUiUMzv5w7hB9ycsLjeBNijnWiM7r3xihz+G58Tlp1piIbiNaX5wvmgw9y7GhAGxc3mzjs9yf2lkEtLOuk6k2woG13n21lnAuMx02nSlEhxwgvAjkcP8snSEDUBY6Q+remiB0Zt4rgUEeK2sXzN98hLwfWcw/SxNE2CnKaTYcagIsBA30rchDYyRv3acMwop4bpiKmyNMm2qZgASDKmT+6fdLANq4uW0xSYb7Fe/DFHYyPAxw3bc6bANW9yJYJNgr6v4J0BSBrBz0lFIEJLzuJYCHgqmmxuC6XR3ZeI77atcE8UBFP0Kkvoyt/7dZW13t2ncM0q//vZ698LjHPS72VU+fPr3BDPFiqR6AWdcN2WoP3vaAgiDz8/PuRS96UTxgSqVSjKp5hM5TlV7/+te7a665JhZ+eSCaj9JEvqSXIQ6lkV1hLHI7GHFC4Ewt5mwFS1hUL1KGyKc4D/sYLgaQ3t/4Psu5J7hQ6hb3CRuEDFy0DPVyHZEQqu/sTPizXlgterR8nvKcppiaiDy5/lpk3Q87yigMHRrlNJS0gc8/OmHnRadsiP1JJybYorbLcqI39sk6Dz5bWzH1wLe2wZOlw8RzUoclPk8OIARYFY2xcGQ23geO2nJkMAJOJAqA2jghoBH1i+PSx8qF393WsOGAx18YzgNZPoqaWwHTx5csTvqf7wvUopgrr5nfZzWOp8Fqw20UGcp5umcXoYiUBoVgj+xN+nns4WSCyJvOd7wJMLAlmCBgmChjt8M0JIrJziGNTQ1TstWEHR4Z4KeK4PN4ZI6xSpcGcFllQgCTAHXEPKIj6Hz3BaMNp1Trl8kE6ZUbjr8vAVhVwo+k1QtAA3Mco9bx33Q4OF/znJoMZGg9yLmT16WuUxzMqDilBT+NdBiywzjXaOaH+FtoYGREOMwU0HxQjF1P8pH1B5mMauopcEwZtolsCtDgvWHXssASq5/GeOiXYZGVmSn6iRdECGNnCdpzLjVAEH1vxTMk07doMRKUbYCxxneN77GeuyxQSQjt4p2MFEjZLiaosyBysMKefrb5zdOT2FLi+ip9beM8GUsRbYUI72FbiObinmmxf5EOg2sjEJmq+IRxs1oMBj0pit09oPr/pdK+gkyQr3TzAIfX9/Alb1/2spfF6TB/8Ad/EBfteNaznhVv44VJr7766ria6ete97q4XO1P//RPu+c///kXdQnjr5b2gIIgL33pS92HP/zheIB5oRkviOr/X6vV3Pve975YEfeBavmlYqw0LYw7CstllKQTQkuWM62ZA8Z2WfnNVklQSw1eG4So9if6I1JT9OLDxYx2OM7JBSulxRrucqbRxOsh3dxSzdfXyUVLMEEy7EbLqE8ZJ0af2U/BJh6wNVFEsNwCGvqEzIVjIyJ5qS03PnUYvYLYoi7XK6K+zGcla4rivsoxZ1lbS2i3NqYGHii0ZLawos4ASs1VlahYHdWMO2O4NubtDkv2iaAaU9QYAqzV7SsmOMC/C30yKdhEqhEeXL9ppjT8aKBrgIrABcEn9p+f9f4tplZQtJUshpSYqhHt959h7F04OR4GjSMDHMB2WtLFuu2C7JAh6CuivgQmYfiyOkDcyBjhe0hHiAwN3TldsSGwYaZmAedIsiAspDzuG35iEIB6EjrF3dBXEmy9DOCFLDaZG+L6a+ImZFyb5SiK6QrPVqfDMFMH81hx2XYmyRyQjj7mSx9wMZpYz0Sqj31zRKWOPtYVXX1JiF8alVo6+lAcK0bFKcnYUX3guDFSiPT6208gqN/qUX0zQcQz5MFdUGOm3+o2wtHPCHh1AIAS4HEqWs0m0mgNq1+DHhajl9p2zVF0TKW5ENgT6Yfi/ZJ9btNu4LrAVDj2U79rABQa2L9hpUqp88g0x7Btolk6vE8MYHYA9Kb0VophrSUGPdeFUFPnuRSFUR+kzbNFvE/6v//3/44LePgUFx+c/9u//du4gqlvXqz0H/7hH2LtkCc84QkxUPLd3/3dcSB/qz342wMKgviB8453vMM99alPjQfQ0aNH3eWXX+7e9KY3uQe6FRdy3RxXo+wbnRJd7pQ5n5ZjKzQC4oNjYYNz3BqyDUKKzplpJllOvwUoEHjRizErv/A8mLyLa8lORTVhcwFul7BgwHlIGdgCYML+ZJJkjOR+cr/T5YfD56fQoCXMp/tjCbgq2YoM4AOfeS06Ysjt6M0Z/kG3E/iJxgCd9iytCzKdYKiUlm3RvYGzyefJm5KBs7QP6Szj8ubUtsOhxj0cRNlMPo+VPfKkoqwgIjSk6DN1IT6eoRtBai/FDbOaBXxkRah0GlKyT87cRoqEgi1BkVNVhrUDIKk4WwxG2TosmaxpujAc6ehXZjAeNBMGt4NVP8hyiTfrHS+nqNayA4zGZmkO9AfqbHyfNe6tUtUa8OvjPRTgodIx0Qb3xnZZbHtS5MmeICBDoF6DnCzVSbZFBggiK3Xhe/FACibjhdXVRF9YAUWzTyywhJ9TAVjjfgoNisiuwIV7JW4b08i0cKKoyoOuWcLmOrWFEfE+qrPFv/F14eGsMagAeeqNiXLGGc6kACuaxrgRuhtqf5EmEmYBaBFgjkNRktRIQc3SBMsCPqxmBbYyK8qYB8OhMvpCu0EwaAmUKDBW/M2+GVpuabF77GJovnV0qhIQO64/ImCo5x4Ai5zHGDgRY1s/zz4CBKnqLmRqERBnmkqzj0CYLrXN9dPS6FHPhtec0mhpB+bXS6A9mEvk+vaoRz3K/dM//VPmNvv374+1Q7baxdceUBDk1KlTMY3It8OHD7tqtep+6Id+6Ms6phdS/bmf+7mYSeK1RDyo8od/+If3OjfLq997+5ULQ3EVxqUSGRWLDG0za2HMZbA3Gsai3+eEL1gZqfJsxv4EQSyxsAxDId9E1LvZHzhhlpfTx26FFykeQPQr11/lgn6boJwShCEIkiqZnHzulIxxo5+f8QyscaPPSeNIRJ2NCFumgWqM4cyIneV8qOusoRrjqSdaJYLknwTZaGA3CQTSgGEuSWzQEESh047SsSXZFxHFxuEajFoTHNCRWd4nI51Hs0dESo9V1lBUVunPIiJwU0LKS3zOAVSEgahzlrit1WeCPa0deE4q4ifKfrLErnZ0exW5Cigjq9/pSreKbtwmb05+WNpfMg3UgQvJtQ2cS/ZZOGTXMl7djf6Xwto+KTCUY4XOrRAdxMcMgIkpMFwjtF9PAVNqQ3QY5TQpijZF39J90vuIlEfS+DmP6og+xoCoLtbJeKcbFnOP820GdZ3zN4MQGdUrhNMNe6Ayn7VOh5kgOUzYgn2pMRBE3rmdlT4S7zMQbeqQE0QRzBG1fohna6W8qOPxWfUFyCjGjDgugzKpcWP/trF/X6k5tt2UxVgRY9pY/zLTkI1+ar23Qj05eHMY4xvTlZ57xP58HkaKtUi9VkwEYY8I2yBD9wI3QTDSstIkCUhQG0hU/8uyuwA8cF7mPKyXaTHHci3iRs7e35CEor+gxzbBq8JaeNzpClyFRvfE7d7/L5nmL+fLvaRL7JZsta8SEMQLy3gtkPXmaUVDQ/Rq7l3ziryejvTkJz85BkF8WaM77rhjo57zvWl+MvLzu9Cj4CKrbGWBlJc3N1p0LqPI8Xb3nuEgRaxw3FbGgmHkqGcBJzweJ2nSQgsARKqz0qrPN5IbVZ+g5Zd8bFU0wBSO+DGdhIaibtHg5oyXLANCVGcxmCBZxraVh66bRRsWLQOcEEwjI/KQU+NMgHxr92GByRlRkAzATziNJcPw1mCNkbss3zWDD637YNHDdcqGBVzw0KTpZtynyHiRs24tS+dZZaeRtdT70TiYBVbFnTAi6v3dJnPuEbdcg1rWOM5HTtieUbhUKU/aQJW4pcsoGGqH7BZEf9gB0ss0mmqAGNY2ekyLNLIo/GwVS0c4eQYjTjcBTJI5gIcjdBJUNFaUwkUpXalppU9qzH0WMKkdJqtiRkZk1BSvNvqV+snSWRCBC8W2431nWgBK0moHVrICjXRIcf/UOftIDcmrc5aQnmMdSzj6fCHV37ZWhzy2ZTdYQZUUuG4cu980lb7mK/1K8x62wqCDsD+0HccfrLQl3ax3N4OBa+mfCftS2BxydwlMhj/rZm0nwEd+r6o38WUxU5LUdYpjW6BWVor3gAG6Kr0Sq4nrgT3EkuL6/WYfGJRpdjW9U33JPH/GWN+4Nwqs2mpbbatdpCCIF5V63vOet1HGyGuBvPCFL0wBIX/913/d1/Fe85rXxHWifYoNyxzdl1bbEbl8NRLiRJwU9aTGibCQFIxwI3eDHr6QzLDNIblgTH7w2Mbn9q4kVD5/dVLhQPtRTaTKWEYDG53U+O/q5pTRVOTFMsQNo0MbEM0h5GyOkOIYBdNk9Dkto1Y4xllUcSPPNeX7Gf40qaC8nzn9JqGfUh3fBceTb5O3QbxyOfmcr6OqwkoSnukMSiRu/orkvanOQfixmtzn1Wn1PAAQNVGKvF22S/FaVQmEwyeMNu0BYzvhJIY/62YNB/HYdVUHGt9m+oN8JwtgT7AJ7RSmG6TABUNIMgOrYdfKi2HHio5pI1w+PnVspvKxwkSqjKlgK+BYWakhBhjbp/RJ5j7rx047wGEnXqTyZfRZlLnM97ePpdxviUX327Ki2QJ4oANrRddTTrcdjbSacJiM1Mriqt1PNqGBhPVGi/6J+24wY1KRagusN1gp8d+GAyrFVPnZPmc/JeJTOjFr4XsjIvopQCJ8nixWhRU8EWkWGQxJkz1pSz3ZQJhlJ+Tvw/4ZrAoGKCzmgn42HW6H8UXGZuo6yQY1Al7ieWYAEsIeyNB6YBoXHW2mRIu0Ww2kRZunV6WaYIQZ/Xd2mog1hqxno3/rh4iYxcAVqcsZ6ShijiObKWeAIwjyxcfGWiSBNGyj13li9WvhfSqLcjEp1roHaTXvwyLzYG5bTJCt9tUKgnhBVLbv/d7v/bKO9573vMfdcMMN7tu//dvdhz70Ibdnz55Ya8Sr9FqtXq/H/9bb4mK3duLw3TlX8AakYCgknzsZkzEXpnlUNWBJPy1ENnPNwU2R9pSTZVD0zJzJfqOHGcKmpvEfhTVBshY5K80lr8LbwngX22GjPvNErT7ryKYVzRQpJ/kMUCxvMCS4/4S8ztp2MmMM5kB+qC8PugPggy2He64XfTo2QgtgVjksRlSIRg8NtVS0ZshihUQmY4VMKT735nAUdu6zKl4QeBFpQ8q4IUWfehIs8TeYRf/AsfpJVlatNo65g44+o/s6+mY8p9JSsk95TvaFukMNiMZK/YGMNCw+N14zn62O+hKEYLUA9dyi0damCsviF6ETkUUDMCgrZAfofHXjGQg9Bn1Ky1GNjGpgmgJNx4igVrXP6DjnwpKRh96wz2mlnKQACEswu9kfIC80KcgeYeAhiz1Cx8oo/a6Pwf3ZHzFfFzNEuo30CX3NInWqaulLRWZqihiqFGvkGFRjgKw+zgP8vjobBZkPcX9w3QxWNEZsHRFzfFhpllrUMqxDnZkuJoRq+3C6U82wmwTbIMNK5nYCBMlKV6P+mZgH8Dn1ToaZY4IVguCREGzV6STUW+H6rc9ZM4JMhhaaFoW22KA8jwZ+Bs8l/SytdIJjkM+MqUEaWJSdCfdF91O8e7A7i6u8/3J/UVKblfj4russSwZ8WFEN96Y5qGyg1r0TVr9Y2oNdE2SrXdrtAQVByNj4SrQ777zTveUtb3EveclL4sozn/zkJ91P/MRPxEyT7//+7w/u8+pXv9q94hWvSH2/tt25QlWyOkytDuWYiRSDmkGjVIuUAAfa937ypnPOhUXkQGtH3SivlqVSLg9gfC1Khin1bxqEZHwY0SL9t0WllJR6ubtA5xt9pBPFDlD4NxHFoKG01p9uBpvONxdjxVrnhI9nM2Y6RebY90dBJluA2wkBXk3BFUwQHtdwMrWhYbBK2gkBqndSg95NQcUs2yDDT7V+yRkPjs6xEJPV+gEcU1bELSOaSoBDzCmgug9CZDZLgyjrebaGwoBEh8ARI6Op6DoMOt6bjLQCC3jwn37rRwbdcHvFLRcG3EvW75tmMXB48RmIdIEs9kq0+TupHr9gBWIeKS3bVOnBc8mDKy+1g5FmOi9Le4vmHE0G0HpUsHst8px1lH0WaYKYr8ortoFuMRR4bakqHYYmU1QNH1c7s9TUoJPUGA3Pj9ox5G/Up2qr1EqyJ8Wxzif7DMy0g+mb8fVg3W6MJS9CfZQ6Q/LYYm1eM8Dgqu3AmizNjLQGDVBsfC/WfJ5HndP6qU//S6x/+fvgjBb6OJa6bhL0RBow99fTkAGeCVspY44WwIfQAcsS4uQf4X7qfThfEAC1hdojewwxEJJRTtoCa8TYsNhpCjAUwGYG42V1OzacLmxqQ/WdhqzFhs20uPA9E+luuv+RcT8y0lZE+rjB8iwvq4BVjwGy/v+tttW22kUOgvx3aIx4Jd9f+7Vfi/++7rrr3Je+9KUYGLFAkF/4hV+IQRMyQXxKjZ/oCmryzYoQiRQMTJ5WoFYvOFYURRiLegE3FiaRpkHHWNMYjb6RIppZUs7I2bQ0PLo7GdEFkiA6fSqjCwpx+LM+djSwOaCij2Hdw0zKq0UbzuinsrfN7YLHVf3UkVYzimEwjbLup1UCU5Zz7gt1MJvQ9wjc3+Q8hS+vlGKGJoqlMyOcQUs8TdtGdEqy3qlOOKeYBilBi/mrbIaE+Jr3UxuEBiglthLpCmp/oXWxOfMh1TcFHj3+6oLblXPutL/oHksiFQGONmdl6Cod1nzD/ptCwcr4FcyYjDGzcAjsv0Jh05KTulkOgwCl9HwnKpDgc8E4ZwZ7xWI+WHN/t9PBQ4mmr9lyDLPmNM49TczrEaLDKcFQY81oYJ/aJBcMdU5j7sia47K0GsI7ZPwd3XvxarGWGc59VmqLxapIBYIYJOK4sdLFMmwDK4UmrWcU3scqxZupgSH6nMViC48vi/2p3xUBLvShtZHqG0uyihQesUd/TN+M52ntIxhUVZsJItKti+FgS6r1MdbYF1EdRzFLrap8qWakUIo1t5JhdxljLbMZ3ZGC2/oZdgdYJ4vSfTE2fy++XCbHFhNkq93HdkmBILt27dqoNrPerrrqKvfud7/b3MezRNY1SfRklCspgkKW0WA5vcbLmSoDazBJsiqbWNU8rJSPLGTaMu6yxOjW1arjz0LVuhOMyvnWGqAOSMec8EWLwuckRTLTaeehhCCgPXNawnBc49qMmGbk/VoOV5Z2SV+VVjLLZPaRUx7/aHzOan2U8u27ZLElUqr3MYaHeCeRDpO6zj72z3LuTYc+6/7RUe83eNPP3JFxTqtsaL8pG1llozfrV6qfGYCCWcHKU2OP5uLUDW/4D99eDM5domuGY6gZDhx3ZipBhuaBqNJBgUuDQaX7INKwyJjB95q9Ys0jojKVBkH6EW/OYKoJh6cZdgSymgBb+iwp3ir3obGi0yesa+A8pKPbBnAt+paB93GsMX2wsuDMNc9ymjtWuoEOkFhReLGR/bclzp4lDG6BZyL9IasimlVSlLdGj1sDLMqe7zb/nPU8rTHE9/C+aJ9YQQi9j3DoCY5ofQ1jO5F2ajB7dZ+tUrx6jrVsTwvU09ecxc4NHTfupsEsEQA0x23dZutJth3217a3KY6L78V41gyNzfWYUvYhbcqGwW5bVZog63Z18xKrkbsFgmy1B7BdUiCIrwxzyy23iO9uvfVWd+DAgXt9rMJ6idxOf9Ezy1CQLIAMSp5BI890iiwnyUL3tdOc2zx3POUXCmVu0K5Jm4Z+Q31Mrn5cQAiINKHqnVMqUlwkCJa0sciIHHltLBsggBAFyzDIxPdW5Z9cfwJdWeXd5Ik2d8zSqS2kf3J/UllyGQaAQQvV+hrcnyJrRuUg3YQQmDAAckEavG/N4fB1kz5anbNBGD4Di+6v84ktFXpGmLIE1+5tJafU38a7n1XtwEzzEOe0AUdLtC9zHrJ+o86B2sVkxuSSe+X7srYj2hS4EV3JApuyQOzANmmgOgycZAFHsj9hUEhor7T6ZB0Zjkx87Ci8v1W9KQVQWWUaedysCmIEmwxAX0dwOd9awL1mxfTj9KaysCw2kMWCywIkimFnVIvrCufYKnfbZ3UyK+22X8al2MRgKOpzyh/C59C/WUwQATpksfUsAVr9fgj2CeZl2CZkdaTTkMMTiUibzUhvkuMpDDTrErn9CPpqXTQLLCmiklOWILBmaYT6mZp7jKBZxxr3GYEHgc0b80OqWcCLIU6fer9E5bmMfjqDZVMzNHa0VhR9BEP/J7OQAo5dhnZXThl46wzrVrNfusnF0bY0QbbaA9kuKRDkxS9+sXv84x8fp8N8x3d8R6wJ8ta3vjX+d2+bn6T8P6FOz4lQrZ0FK9oiJvIwMh1vRwfSiBD13QwhtBRDQkRGGaVkx+Qu5SUg1bVO2DFdRh68FuiCoVCod4LGSLsqJ/niaiuoMVIfL/UlrNocpD5GWHgrS5Gfz40l2Pg5FXEkkNTuLzpiRSTuC8tFjC+yX7Jy+fm90BHpz2kW9FFLoEwBHJaivWAupKKJoMGPJvus7I8yvB8eLAp/r9NELPHMPtgaqd8oWtsvk4LGlmAG4XkqrRHJIMqFhWWVEV5aSj4PzBCkzAWNzazcb2GgZ2jcWKlsnir9sfMt523rlVzLFdfTFDTYYzyPrMoD9zYtK52Cg9/6ZFDR0bQiwOIUGaln1nVmpSz2w/5IgcaM7paNaLQGTgxHt9/yqqbWk6ENkbWPSMfJGgPGOi0czgxQS8zXRiqIvgaR3iPm6P7meJ4nU8DciKhb74e2R6y5POsZmmue4bNl7W8yW9W4a4nqRcZ8iZcwzYQM72M50PFvhT5YR7nN9Vl043XqEsf8jQEBpkxmMTGtdOPM6kv82wD/rPU/693PLANrsC9E3yj4rapUMRhmgt6aDVTcnKFIsX/d2GdqDvFYOv1PvJ8GE0SLFa//HSmm2VbbalvtvrdLCgS5/vrr3d/8zd/EOh+vfOUr3aFDh9yb3vQm9z3f8z33+li+LriPdnEiGzrTCqP+AeraemuT7QBnvI7KD6mIn5Gmoc9JA7UfIzJFD+fCBB0PbcTJcwLEQM49FzMCH+UleTBR2WM0XC5XtwiJzFyMGhCrIkMks1oCHHpRU75PR1/Q0LOYIFYZPGMx1ws6hQ8tY1cbOuWl5ICrEBWjMTJ8St6c4kryd21bMXg9+tmIvFUyKZAWkIXdiaMJ9IonUSCIGfU0nnuGkGa/zrBQ1OfuAoQIf6/PaTkiuvF2iLFi2D1ZVYksw5VVW3xbg1FNIMmKkvbbJKMtg4euQKkfe+mqOz3n3K6JVVd+dXtzxgzBHo6BrLK+hlCeVUoyPraozIHvjTKy8XksZgm+F1WZMijpIn0vg7FigfCcu0VlLjX3iehqFJ6T0lFjHC+3OXMvEzgyWE+aht6XSHYKPMttng6TsWaapT6z0kSM4wlWYUZ6U1+AQL/AahRm0WUxSbTYr9X6meOyAixW2o44R5+pDAzqMC0hlWaCMSX1OQjO2/MIn6cY39xG21PGWsT+M9ik+5lShw2lfGSMQVMfpGU79zKYZ6R1aPanBcoYIGn3i/BvtLuEbpYSUG8Nb155LtUwz5ONyuthdTUt0CxYphVDL0XrPnH+Xw4DeXpeXx8fWkProm/+0Xy5uM4WLrTV7mO7pEAQ35797GfH/75SjYtpc7hg5v2u7iwGjcUWjEBO6qUVuT+NvcpCJ+iktgYLtsI0VDWp/s1+5httmza9kljfnU9/KTn/9HaxT2c+SX7uNJJ9CuPjyUZ7dyTnmO2WHN64hlOnk+t86FUbn4frNr86QqWT9pdu3fisilyYrTA5kRzr0J6kb3edTL5fpkXoXH4soSs0rtqXHAuslNaYHeJpk7EyAXAhQ3PAMrz4DIXRoRbJ2ng+vA8M/7VJaXVE2zCmMW7YF936ofNqujubiBjxNHTG1OktPRsrXS3LkbCcpE6fTJCInSvfeyYIj6uptTwPp5h+GB56fwt8KyNvWlfmGL89ebjLu0tBA1/jGcOnk3eijooZ419I8pNyNTloFh+ybePz6o6CiOTNYLvqqcKm6QJ9N2Fg83mEN88CUy0HNJVG18e4yyqlyLQTRoeFI1Lpz5mU0Vj7eQqHRaT62Aa6qFRmVBIS+gW5Pp1jMYZzNkAkwInIdEyFRooRuc+qqGZVcROVe1QEl32wxBaz0iQtcEGkB2kRX0wedKgtxiQDNOkAQ39AhUhzyND8MUvsWsweMffJfSzgQ4A9CJxk6a2Y4HSkbDWszUK/zUjHyUqRs8pJa8BP7G9pvmF/VHdPNQGSZgC4JtvMeIYpJkjx3jNByFwm2MBnmGWbCABWgL7h4JfumwhcYDxVFsMMaH3O+nghmOKdxQaibVNBIEuzT0qL3QdUaGXkIl6EbSsdZqs9kO2SA0G+Um3Hx+ZdsVARvN/OYDKTNSYktDtya2IFLR9JOIpFY1JlpL77W/K5OZQPRuEZ6ddRNpZEJY2ugXKJnUIpwxnF9TzkcaZBx1aebwcBooHzyaxerismyMMS4drGtoRn2xrgKmme0uX3Xr/xuV1NrrmFEoO6cTEsod57fu/lGUwO3lseqxpeZBV7RzgCwkHIKGtopBKIso6WY+zLcV5Insfq9jATREcxuKCz9FoLRvEAjhv/BnaTcDgMwE833jcrqqQdAVH22Th21hjoRxgulRJlOCYWhTiLQSVECHEsjkc9PnjNvDbe83qC72XvP2hHpZb3Jp+XDpT7Y1ShLR4OV9O48JBJ9FnuI5+7Pcc0x3oUYA0uWKUZKUaboZVhgZFWGlrqWRvPPauqgyUOWJ0Np+jpVloKs7Z0BLcEYerGcD7oPJSQslhalAjj7DVDQQC1BLajvs7Bs8kxWkhn5BxdAwCrx/3A2WQBbFcIIDPwoK4TAQLJeuLcrVkuYeeU95DzbUqwm2PFcMayBK+tSmEW+0anowiKfYZ2Vx3r19pUmOVZmQ+D63o74YxxTlS3Rqyt4p0IgzCarWcxiLLAeSHOXmsHA0G5tp32WppPFsROGe9UG8GnEYkyinRdkWoTZtExIKJLK/N9L2AtLs1JAZx8I7mhtZ1DwcAY75leCzl/5k0hUJt9Iso8w47l/KIZM1LIORfcP7VmG+OL+/P9aKKqk061FeCdkX4Zn9IQh5WgM5kgNuOzPpoLV8TRorG4n2WkoxI80+viuiZIR7Nct9pW22r3uW2BIEY795hxVyhXZY5eRqWWpb0JEyKnIgcbu4DGOHKiZZaVJfujeiYBVzpV+bja+JsMhcIFsC/WKAoi+9W4OmE4dEr5oO5GXtVtLV9QSZjr50SNwtJssk17UvI1cqgIU7qQ9C2aTry0wpq8N7JCACJcMOLalWRVKdR0SAMG1XItbMAoxe2owpAhjKg7j298rj/xmo3PA7edF/s3dyfjoT1QDBo39W3SG6XxToOIKVU0DAhU+LYMNlIZTKMOtDa0kFgTRgyBNLYUJdyqfFDsl5KOz1Y0NkOoz9RAyKLYGxoI7T73t6KcIsKj7TmjQoJIaVKRauGMAbjQTuN6G7hgR53pPFVn7IidEIplfrSR8qFbZvWhfgAVpijknSOreuTOXDhq3Aqz6oQjkjUe2uFr5rHaykCXVU/C0X19nXzfCErxemqTdFgLtk7AahhEaMDwjo8BgERo8/AdYs5GTt5cOtdFgo+YH3SUcm17OaybhHtIJsjaNtnn5d30WIJdTqVliBQUMpUMocIsoNYat1nggKyIRkddHqwFUIcOYHMw3GcNppKVIcYDHOg0WBN2ztnGvpRQwNpDcmEoziQc/agMQL2Y3PT8DEri+GPsmUp+W2QYH2vMQPJAcnX5sjQnERRBUCVrzROsCgACvOeSLSGfTQO6YlLvhRQkdW8R8ND9CYrGq2dTAFN4ZQfW7GUEIbDmawC0NVQIghCcB1KgMS6ntEzEMPlYWZXPg6WiWfGP+wxcaIXvWTzfJcfLrzWCz7nw/v8S+7Sf/MhkH9iKgsWM+1/fIcXHagBNOV8LYFOz7QxAm0HHCgJ+g184Jc955a6NzwMX8Azw2Nemdd5q+D2uziaTSvnOc3Kfwe61ttpG3fSLtfl7EX0FjrHVttp9aFsgiNHKix1XLPnyMJg8RblBG8Gm4WcJu80iRSIlwrSa7LQCSrqOvLRgRAlqcGckmEeunQLLIJQRAbWa7hvbPIrQgbWro6lryWLS2J5cWx0LbmVOXSgcbRq7IvKRVWKXh2oPBfusDRVLeDF61GRwYZ0/uts8pzTEqTQot+sn39sCDfSiLwwiw4EPVVzY2M5Q59fnsaoVSNAh6k+MNWMhEw4o3i8+wyxqLxtZO2aZzQxav6TJdsLRKnUeigXXJ5MBUV6QHW2OhFPuaGASFMvSFxHOqIisyu1IFSbwIqPeNojST7nATMFPPHcN0tWmNqeU1yfC15ZK2bDenWjzCjC6kVFFp0KwtrRDbojL8h0cOS7pDpVzCQgeIVLdQCreyJ0qaryaPKzcIkD0qSRMurYnSZ4vLcpz5j/8maRvVyVsuda2ZO7MfSTZJqsVjx5O+n8mMepzIzKZv3H57mB0m0GAVCoEnPDW/u1BBzSVcohgQXsQYNFIKexIFW2HSTAcDC2ebn+Sz03MEWR8CpHSDNBZ6iEU7Ci+qMQDNg/AmtUDyXgoLctJYfXIZFDAnA54SbFhC8s0YjBHLSWwZg5jOCpJ26K0kLxUhXryPPJgk3bUPmu7kj5UwUAtgllKcL88J5G0DgCe5jDm5Xl6xgoMRcCIAEl5NnkPWziWBgd4Dx1SEYdOIihkBCT0GBiYhXN+1l4MRHosU20BNJTPgJIQj88E1KpgneI71BhPBmt5RY6h+lTyW75eDAbZWt/4aLvPFPPG/ZAs3ZwJGIpytUZZ325/8FveYKziPI0jSbq3voer28rBdBgNqEs2KoEsvB/qPMXV7vvVVqLxF33bAkG22gPYtkAQo61ty7tCJW9SoEkvTzVhVGN/o2qLbjRUSEnU9NvqfBh4IWottEIMwVXd59LcWpAiGm8Go4GLWXGxHtQU6TzpOrF/8a4zyecyjI7didFVPLdo1lyMBsrBvnUMiqpuQkcFjJPmSNmMYvA6RQUWLsDq1tJAplEvREYzQAzhqOY2j0bHm5X7AGG0gW4YCoIdkKH63tf3OpLWxxqeoqwapS0pRppZfUOkEfVnRIgIv8jjpqNsAxJSx4MUC/az3J+gbt34vtFnvrehnxD/LcSfGY0MR6q14VmZ7wRLYpc4d+mUDUS/GqMyZWNDSSRybvqzrVRkV/etstAOOigVRNV0o04PU0PooJTnZafpJHRGE+drdVfysgwqZo4An9qbMxfWtsv5tjE6GnRk6JjWVDS0VUnAinZ1Mjj/c9w09kpntvU/HxdmIOHjoJrXo1J4jlyeSq6nXdrR1/vN+7Q6PRbU2vKtvJwAKQUVxQ7N3fHxdlXCul54pxmpL7Xt9IsigIPGGED8CxKUqlzAta01gyBAjuV2dJoIHMDGeCWc5ojgQnwIOmY7q+E5DZdWAzAbbyfKzxeNNU8LplSDrIZce3xTJ1P3jWkBTMlNVT3Bds2hgU2B+tqUBN8E+MT0BTA8UiwbF76G2sRguKqSmoboqAsNqOFBu2w1GYKG1kS/ei0W66i8v2LOsbWJ5LdCsxx+hntLfYHOFjsu7k8zvEbQpiUoRcasbyPHOVbCIEQWOM5zWgEGzSZqDic3fugkgDAAcSndJdrOAI/Kp2H71uTNiYa74zt/qTFBttpWewDbFghitG1fqDnP/CQCnGtmGCqcmOFAt4bCtzglcorDDZxNohW17RUTBGFuaWWuHTSQaZyloqmMiLMMLCZ1nd8sVdfzweusQvdD5y+2DiSGcBPRTKbdNC7fZvZTRFsMYdI6r1kZQdI4KmWU6+MCCjovo4wZ1WGE4FrLMKKVUc8FnccrI1LL6IpuVt4tv9caLyKPmpogeJ6a3m1FggRYhP7TMY5/YyDNYJxo4WGpLh+O9BIITJWgjsJl9ES0SO1DsUMhOkfmvlHmstu5PspEqulB5PwbESp+bmalDRkpQClQS+xDZxb9sso8qzQ/mTZDD0Puk8MNkaynnHP/mOx+7rrw/Ml9ltvhOS5fl0a9ACFEOc7wwxEpI/H7irlYlEe12XbWM+A9ZyrF6B0y3bA5mgyC0lIyCFtgMUTKUS9j/o8ggst5lHOaBtIGziE6fB79obYR0wX9sTEn0GmvRhaYKydMspv43gwDUOA1a8efdHmmRkZF+QxHb02cjNqOoSD4JVLUlAMrq2aVg+t/q0dbD+0TFQY3ZYymqrgZ1X5EZZSmBjHC+/MZEHzUzdQoMRhUehzRUWdQJ8Wg5aHp5yJ1VwqDy/1LePeqMxyDDHZ0zPMLcVgwa6oXGua4kwwgOuTtcD/VbW5irIl0Uq6LWvsE7/RAFAZzabNo9mUDrCOma5PRlsXYZH8EaItUvpZSqjdLBgutELkPj82UIBE8Yjf1vTWCN0KoPWOOzmNB9RUiQ3N0bXzAHEOrCOzR7tLsLr7j5cXkRg0OT5oMomJvfLVal5bb5u/Sl8ttucS4MVvtfmyX1tv0FWz18ZJrl0pi8pXRKnuRMZ3jDAOCC05jdDCYoy7yu5UTTSOSBi5zOVP6A6wcA/EwgXSrftLYLNx0d3LO+YSWkt+d5EiW7paUF25XgvNU3JZM/m5Kqj22bz+WnBO/ReXdQeOmOiMtVzJbhL5HAaJiigkiHBYKVyF6l4eOSH1SR/TDtOcsJkcLYrmiCgCiwyKFSTNJjDKLFMLUDKScCB+F99crTLsULv1CI1ikgWkgjYyqAasqgwYZg6c0RSn1dXJ/ClFaJQp1zj4ZWbJMdGSWNWxZaTvcTOn08DyMRooS3AYIpAEnUdKUWgQYj7o/IoLZsqKMGc8m6i9txirZqJ9zedGo0mEJjhplS/WxJUuHBw73URvswlHFOLHArvg0RYulA+bEHulJSCZiadOUrvg8NL45JxiOCBmK3f7g/PtLm1biyHqG7AtZMW21lnFe5LNZ2TWYIdxYCr6HohqLeh7LO8c3jU5bgGu6ZLELvmt0nro7hc9jVUDJqtIhBIExBsjGytKk4D0UotjK6SbFnxFt6pXx2ep+FleaQWHS9iDGE0ADrZ3VRpCocjaZzNd2y4Ejy72GGbR0+nWaiQgQ8Nq4na4OwzmCIDyCR03YYwMAVOJzIlggKvQh2NCCDRdvZ6wLBEc4j2itkoEZCCHjOhl8SpXKFkBpeLsK1lIKGsfblQyNs0q4//qcYkziGRCwJMClBaNFOWrYE1rPSAKQyXYDM51gP1Npu9SIYarTUEbpc4MJyDmpxPQyMpfbRqm8i7VtpcNstQewbYEgRqvO1F2xmHPlBVIHko9t5oXGi0FYhICTIo0RTQUtgT5ahghWAxoBevLuazGlfoCavNtwhiznuqquK0LOYufrrtj4PHg6MVRWQZ0ki0Hn9zZB7c0jV1en4OQflpwnQild0hCZS0mtFN+KEO3jveXCmkrZsAxK5onmSxkpI2HDszNo0zJZ3UXoJMCZJj293CuZtt7q4zDCeA9Qh15TPCn+JYxIGiD61hjRK6YsMMWAOhe6D5YDraNSNI4krT/s/OjrtHKFyUQR90w1IaxWCh9Xiz1K5xR9o8OjMzaMLkRMCaOTqYlBIlIcpl2nj40/8puLpGalVLFl7SNEV7md7mdkpDcxFQBkhSyNFCsvXgAyLRvotirHyLQEuQ8rqsg0STpmSV+GbmaBYOdWj04GHbvKicVgao7WI6jckeRiRBC/rO0Zta+TDg+BAqQcVmaktkJ+ESmUg0jZAGhMB7QDtoY+Np1r6pWUZiS60B5D+kALDmyFJck1iMH5DilF09UwWKTWea6tdMCEw6gcO1F1i9eJ+XIVpcpTY52vsZHSlCWMKsA7AVxgTlFR/BbuIedY6qXod03MxcKZxfUD3MiriLaOfG8ca6hkrnmlC8mYyJ2bTa5nuyqb1WsVVa0uOo/3rYA1BgESirHH1zAj39GQfk7l1juS/j/hoWK7sc8m2jgR3pX252/a+Dx05WXynDfftvF58IqjSdeqYGICYNKtPlUJ2oQlVrFRY716djW4/rQQMFrbQTatHINcT7OqxbFxLqbdVEaJWtpaZH2ldDjICqGdotZ5S0vMqrSmU++KK6iGuIB3GoBdQ1WxEVWNWLVrCdorSxLsyJ/qjpt85xIDQbbaVnsA2xYIYrSlgwNxdZginE46o1mq85aopaCyaiYJGCdE8UUJtZT4WTtIDRZ17GFYFFEOLt5/GUJcoPEJsGdkwFaNh6GUO50Y2wM7p8xIWg5GSBll39pfuDk5x8EDYh/XQXrRPSeS89QS0b3StpFwfrUSCiRqH6HkcX5GioJFuG5SvwuoLtOYTvKLi8tyYepUk30ao8nn0mo4Mqoj9JKuj37hfq6l2CebMzl0pJogmxBxxKFT+axGtFsyHGztEzNqnJFeJByBPnRAdNlQEe3G54YhXJw6dscwiPjYwzZ8UPBzYxfNcDBkLKzzaLCoioiwYLEJQ0/RbNcM0JT3M4PhISKD0OewGDO+1ZHKx7lQR5fX2TVZzCBB2yZDIeN5CEOa14PPBQjz6QOK9CLMtzWItOqysDwn2VBsa1PT1ikF26A+loAjFaVdwmjo6vSuMAiflSJH6rsBCpWW5cBt7RkLOo1rOzDwM0pbiqAAtiuNQ6NlQrH1DNFvjhX9flglWglCmIyhuOWD0XU650XlvFB8k0LjvOYytQha9hxBcNqq2BH37VSyTrfGqsEghLUuxn9S3wJMEKZy6IpReYA/BOSrYB6U4eTxWPH+xqtbn7Cd+xqYoaXdI5vqgqXm+Cu3he0mjBtel2+F2v7kM9LA6gj+NK98lJn6tTY9HdYjuuyxpu5E7mgiIFrj8RDIYWUpDYoxeML3W2icpYS9B4JAFpkcHI96jRs5DkFbsrP4fupUPrxHpRmg2yfPJvuUALxMg0Ec27EIjE1Wg/eTAbP4eHyNjDEweDdA55sSgMu3wnQyhlr7p4PnHDoTZcxdUXDuiL54i9in1Svb3IpsrauLsfk5NksUv99jbLWtdl/aFghitJFja65YjFzpGEqfDiSTaksJbNFJK84lk3cTivoRIg1aE0SI3tXCmgvMOc3S5CBSzQWrtUuGe/LtwU0XJi0sRxV9LhIlqr4j4ldYkHkJre0jQeOqBB2RhlKd5wJcxAJYPzARvJ/a0CktIXdb1GHHOcBKSd0DXE8bUVbShLX2C++blUNMgEun8ej7Hro2PR4YTWUkTmyjjjtwrr5p5QRtUHJ8ChV8LPpNAD/lBblor9IxElHXsHEX/0n2CemrzIMms0dr9ojqMuInnF/+TZaILLeXfG7A90s1GvUWcKSiqVlpSMYRxF9rSKkSIoiiRK/On8D7ammf0BHTTppgZaCsYm1zECgtNOvcZ94w6nZUFtzZ2qh71r8n38udwsAP04GyxDcHz4M5gDmBVHFN7xagknF+zQIQ4LThmFFDSkdTy1h/Otsw2JCukLtblmwsrybrT+uxSRnv4gLEqz9348bn/COvFfuv7k0GeAlOSeX4hmStcw3p6BOcLu5J0hTzHz4VLH9ZWlZR59NJRD8Ptp/QHrn5TrFPB31gOmXrQsIIKO6SFRbYotVkbRraBfCJlSg0K3GeQgEQvN41GhQljf9GFL0EEcSBkwnwvnjluFlJgmuRSG9luoECshavCE9M+RaYA0XaJnI7yXh0YU0s9X4RTKOjTV0y2hkajGW5dotppcHUynwyVooLKMMKQKKItAKxrvnjLYYFdcU5e1U51luO4rYYH0Vo9mQ53awIxnWegMjAZ5IU4LhNJuNj6crJoD3DeUinPArtKwLKQqRUgaEQjhf2EJ4n7QyyMHxbmwrPl1x+UlXcdkOwehVirFeH09jSJclz4dLSTJvKqhyHMTl2Z7KAtYeTvjS+4eFiHwqbcn+RAgRbUb9ffO7l248nxzqwT+zTGRlMhFG/8Lfukmlb6TBb7QFsWyCI0ZYOdJkgg0O7g8JZVM7W0cQoP7SpoJSmINO4qM6CHn0jaoXXpeFZuyrpW/VMYvjmwVaIaEQqx5ITO2m/dHILYH5ow49U5w6o1tEnPr/xOWO9cRWUTxSnUH9HUKdv3XFX0jd8ruzfm2w/joiQSq/Jr9SD0S5GyOLzDJfDdGaRHx1e/HxrEiyiAQHHSkdr2mCP0FCwjMOcoiOJaKjBYqBORXzsIVYOCDtpuhKSMDwii62BTfarCkOWboJgG2SkJ+UthgajWqrPRgqKdazuF9hHsC82p8/qZm6nIhhWfrBZPlndJhqy0nlwYX2RWFSZ45jU9eKmkStt5PM9GLw7cfKaE5JRxjmG80XxiqOucHUnNs79da6niGlwwGIjDZ9smoK+BABXdvHapBZUqMJFfG1knIjSzOF0gbif21mCM7dpClBlQd7bpQPJvFZZ6ISN7ckjYh+WYGbfFo4g5eP6xzurMWrsdbE2+j+alKGtzCqdgyt2Jp/JBHni/mDUuD4unbQ1VIHhs+W4HdghwRqCsy3BJjqUfK8FlqlRAuCc8wVp/DqKX6yNBFlPA2fWwgyLmP0Ip9mrrffa/LXjQWHzklpyy3ONoG4GWSk6ol5C2idTUrkuVT74ueQ6H5UEIXxrjJUMbQhO0va9FaxXPIMi9klVQKG4La5Tgj0KYMJ117dXg9+3kE6jWwPsovJMPawdosBLpp+1kIJCQILAjxa67ZTC4ubUaKk/ZL/8DQAP370aS7KSSapOIbVs+rNJOeeKVNm2VU1F3qfKQvjY2lYS/cT4Iitx6C4wdflsFOs3BxChc/Wh4BrDtKW4HU+A2s6Vh4KMaKYDDd6egKzxPqNK4KjX2ng2w5+VQHVzX8KWLp1Nrq3+qCTVKQ9wPO73p2/tdeYSTIfZYnJstQeobYEgRhs433TFYkHkPhfqyaRWRE1732q7w+X6hHo30F+tBcByjEyHWXrYDlOMjm1lP6I6+eGwA6/EsmTVEkaYEB7Yp5KFjYgGhdBYFpfOjmbDtJGTXZ+qmsZRkZUHcOwGHBZLZT3ug7hvoHiyioKmWhuVgNYVuuPzY5+UnkSGeKXVhGgd1eDPt4IGodYxscrvMgpP2rU2Ymhss3IPUxe6J7botNwm+ZiVykCqtwA0tJAYDCc6aQR1GPkhCyHdH/XbRgfULiINKdznzMXbeAZWlDN1HpEf7cJpFVrMlWVtjWvWVU/cQebpG30xtFu6Bww/wwUwtbJa/rrHC0BinYHhr3+5B1ZkidnJNAsysFQ3DSFJOg+CtZUxHgQLDuwRnX4xeCJhDsxfNWrku4MCjrKrvhVnk/3bw6AwsdT3saTseHxto4mj3jmRGN+Vx1wVdHI1oEHmWwnrHEHvwnEwJGPx5olgmmWuje//7dMbn8tPTdIF4u0wpxCsKr/vUxufi9MJCBO3ibFg33ifinNKpRSAhGu1gizP5avsdE4+HzLnBCAzLlFjARpiDA5cQCoFnGYNErPajDUGc4ppxfeAoul0LDtPe7gJohAgIlhfH83QlwJoWMA7oYGL5JxKzBXjTlxbViQFrXKekXuAmceg4bGmFLPxrkRIWyqeT1hP0U5VrQ5jKM9UJ9gZo3fPBXV99DpLZm1psREM1mjtD4LTZN8UwdzQQQS+U1bp98qMnAeoucaULpEag+81k0SkeCP4I9b8lr3Ol5eTzyuHR4IgfmNU6Y0dujoMSF/7eHOOdo9L3neuM0LsmFpyeRlkox4RAVDaPUvXJQFLzfaqAvArz8Jw0YyycjlZ12URsa221bbafWxbIIjRVnaVXKFccs2R8C1qHKiYwok5QylQRNB1BJe14zFHD8yGlbzTVMiwA0u2QgnlEuOGw9HYbUyGke3uNWCRgigZEfkiBMo6e2WOe+FU8lvrxMmNz4MQAmM1mPiccLTzhxO9kOJSOMKTP48QhDJwKepJw0I3GtWkZzemE1CoilLGuW0V89kIEIDGvkpZoRMv0nsMUbEssTEeiw60ZjCtbkOUD9HxzPQFRogsIcrIBjSEQ97pr3Qejbq17cyhCZ9H919EwohvESjIyjPlbWOU06D56iby3TPYJ4JhkFE1JfneTvuhnpEoF6hAKat0qwX2ZKXwsP9aM4BNiNiK1LPw9XB+1c9XVi1BP9X52W+mzdhgUVaqUn7T6k/xecZHgxpABE1bA2BuTCt218FkLh69HToPTMu7VtKmhW7D5VNBzQBeG9lgaZZLJwhgu73SMaSTRKefzDn39OuDuiVZYzD3tAQsaSjQl8C9JapZ2w8afXxwFxRstph3ujXAECyuhZ3RVNqqIbpdmyr2JehLoJdAg3jvwCKIf2OKFxw4OpC0JzQgUT2XgAXN0UqYwaWui5XTKPZLhgeBDl16lmAJ72EB40mDNWKdRToon/Pa5Qo8M9LVmMbUnh4J2kbxeXrOqE6VIXt0Fe+dXhdW9yAQg2BLcQVzyqQE0spgC1QE46QcHE+pqkaiillYDF3o93iz6XQt+DzJ0mEqRyrtB+cZmAnP8dqmFcK/GAO8T3zmDJBpZgxLM4ty8+p5MGAitFMwNipnlmydu1MJINx4yIE+GS8umHbJ94N2Z7zdQleXpL2lCZJqW5ogW+2+ti0QxGjb/uOcKxYqsjQX0i9GodAdN05YSEGJziQTZG57sjA2dyKk4iffOxPhp2gMIp8zyMNWNHRGMdxaMpOXRhJHvXXL7Rufi7sSynJ8OBjoAs0eqdgCXTSKQREUy0IFaTafSXLP4zaocisC0buoJSd/4YsitSUHg6yN2u15UI41XTF/TxI17ZxPxFyLOyRYE60kUHsO97kAAVfm0ou0JX/sieGw0XDbqfDzi0+KRfuupPxw4eD+4BgsqpxRh2fTgpNSvBPnHJbMnggOUG4VaAmrkSBNRwvtlc4kgmGut0jH+/REvHxrXntQ9pNAFPVj8DxLpyWQxetm8+kT623l8knT8WDuOIX2BJNEOT9kEBFgodJ7poCswYwRTRlkQrySjn6zP30OOuH1UebzGOfXRiF1chr9lbsV4pmDxr1JsTL4Wd6E1/9tLa4CWCjXXOtoWEiU+wtBYEOUOku8Wujs4BXQ6Wo0arkPDedUGpZRwlmARS0j4hhHBuGM4r0jYqeFOCt3LAYdwIkvJXPa8oEhs6Q45/w8Kh+w+kT0yS+IfYrXJBTzHKLogzPJe7x27Z6Nz0OnVcpIOwyc8J4N3JOUV48bND3omJBqXoSTFl9PLbnWykkwMfaOBnU3tC4Mo8gEHuiMaUc9j7lobboSHAOCoaHHEO5BbQJOEsaW1oAoUEQXIqXyuHbKh4MzSQZplC+bcw8dYrKjCNiVoEtTUveJjUylErQ2BEMzfvfB3ljEy3tXolFT2puIA0d3J9/H1zAxHlx/C9uS73OzWOP830vIVzqQRPjLJ5Pxmb890a8p4N3o7p+8h50JVGmqZaQ5LCPdmULtSBWe+Pfk2hqHps13mjokDPIR9NCgkAArMFbIxtX2Kcf02iQYrKLcesEct+Wl8LjlfFWbKpkMC67TVuCl28/kcwdAb5GlxitjQZ2k+BqmD4arXAHsySonbaWBaYZf8VDPDuzUnQubQxdn29IE2WoPYNsCQYzmhc46xaoQrWsesaNSZFxwIszvHQuj7ijb6ltlYE9YCHQgY5GhUWyVjXvUQ5LdNcWSOh7QBKEYH8EV3QdNE91ozaYJLrQB6ghQBoJzmv3KajHtGxNQp7A/uWfFU2tBg8G3PHRMyAop7t1jXmcOqvMR+lx4yJXJNqwUs0+plGMBpCBi4/qDZtRbqP0fngyyQgqXJ/d8zRA/TTl8e4+YVGuW8GS0iPo32iinQ17bjjGU2x7MHddpXKT90oGjlk1jn0yl6ByeCjJoIoAbg/+elBFsXy5zqt3Hk/z3kSPI+50HcLNL055BL0YpwzzAotY2pMHNS6p1hHc3P4PzDCdWVwu6NClmDN5J5gezvGj5+KwJahGkzM8nkayIRrw/5yQEhqfhDN5yPFgWsoDt4+Md2BUUsuScoqO+HANtGPI+Ov9/P9Rwp+ed2zXRcHsmo2D0TlQyYnlvphCpcZcS4Qs0sldS+rEwZEVkkcCRYo80x/AeCqc1nL5XHJXvdB4lKKlBUQbzT4s91q7dEaSkryG6TaegpoSoxZzQTH6rziHlEQyNuA+M4AJ0prA357EWnrlmxlA/gKUxW0Nyjh04DWcSlcqEYLgSJMxFAOgZ3Wb1CuqGKEYZwdAqxhedFwpk6t+ov9PCHJsDemcxR3wbOI/qERQz18EKDP3S+eVgqdU8AhL5AcX+hDMYNaBpAqef4rrxOYuY77DO5igofy6xLQrjkqXTnk9ABGEdgXWVVyB+DilNub1IOahWwmk2hxKNnfi3k+eCa74ICCi7KwfgJOJvZMPC7mmhlLMO0pBx2vrc7aZYcf5CYoPkUFWvzCAEGCpkjsRdu/PuoKjxIPQx2jfdKs85NhYM4LEcdumepml3ueHB4DNkayq7qXT76aTPs8l4yB1O1vPozns2PlcAcHV/TJ5HY/9kULg+xQQB40OAy2D5FE6j/DL65Vt7OXm/yrAPaZ8v75NzbHUG4xZ9pu3f2a3skTu7zOnoUtQE2Wpb7QFqWyCI0Y4c3eHK5YGNWt1Li2vu5FrNlUoFd/DgNpdXWhdfLHQjXvv2TLgBOgKFnDt9btEtLdfcyNSgm+6Vcl0XwVpda7gTp+ddNFhwRw/2nEisq8c/dyrWzti1e9wNMSfcOXdmbc3Nza+64eFK/DvLbNYbTXfP8dk4QnX0sh0p5+nue2ZcLddxO7aPurERedzzq9vchdllN1gtuQNQJfetFXXcnXd3GRSXTU+6Ys/AWHdmTx6fcauDO93U9hE3MTHk8heSRXppfsWdOnvOlatlt/+qPS5/ZSKM2hypuNvv6LJhDj3iKa7C8ruttjtzcs4tL9Xc2NXXu229CjPrz2BluebubtRdoZB3hw9tF8i6bzdfmHOdTuT27hp3Yw0KMkTu/LlFtzC/6kZGB9yOXTBuSjm3Vmu6E8dnXX7XpDt6eRewiWBg37y66BrNttu1fdTthgHi29nampuZX3GDA2W3bwejTc41W21314muU3lk/zZX6Dmr607b8VNzrr7ScNunht3E2KAQlptt1N3ZC0uuUi66QweQux7TNzvu9ru6Rt2+w1OuXCqKlImT5xfc8mrdTY4Nuu3jwwKY89+fOTkfP8/D+7alWA23HTsX2xf7dk24ATBDvCPh+7OwtObGhwbcjt74Xney/D2859x8HDy6/EDPMMSif+vZGddqd9ye7WNuEIJzvl8X5pfdzOKqGx6ouD07Mb5bkWu0Wu6uU7NueWfRXb53u8v7EzwtAcvuPj3rao2W2zk54saHB1zuaQn4NLe46s7NLcfv6d69YI+UPJmm42471R3fR7dNuXIPQFtnWBy/MO9WVxtu2+iQ2zY2JJgcyws1d2pmMd7n8O4pxTCI3C13d5/NnkOTbmC9JHXvVpyaWXCLq3U3Pjbgdkz0xndvilmpNdzxc/PxNV6+b7ug/udb+9ztJy7Ec8Se6TE3wnFYyLnzs8tudnHVTURTbveOMZEfXm+03N0nZ115se2OHpl2OZdzlXOJQXcsl3ONestN7xxzwzvAbKoU3Nzcirsws+wGBsruMByTxnjFtdttd+exC64yV3cHj0y7YiHv8r17Gl/rnefc6vCwm5oecROTwy4CSLl820nnCxBWq1X3kIdc7Y60e+e96ZiLXOTu+GzXmD/wzMduzBGdVvf/Z07Nu6Vaw41PDMVzRGEpcWT8HHFqZjmeIw4dnRaU6vz5RXfXjSfjOWJHte0GeuWxC5d1wbLzZxfcwtyqK122ze3s3cPK6a6TUVtruJPHutd25KrdLjojGWHHV5xrNlpux54JN7S8ICqbzJ6ec7Nn5t3gyIDbfbQ7v3Su7+p2NBttd+zuCzEV/9DRHXG/OyeT0ownbj3tais1t23PpJt6hBS1nMv5Pi/G9+cAopbR3mnXiSJ3561nXa7ZdvsPb3flclE4iadPzrmV+TU3MTUcz+GtSVRFmDnvzpyYdcVSwe27TpYxj2683d3x2WOxU3jgCQ911XWAfbj7/M6dWXBLnz/pRieG3PY9Ey4qJoDM2mrDnbx5Lp4jjly+UzD8OvecdMe+dNy1mm2385mPdcNYq/I7S2723KKbu7DsRlo1t6u3frZ7Tkqj1nTHh7qO7eHLdrh8PicAzBO3nHb1WtNt3zXuRgkkDQ64hZlld+HsoiueOun2Xi4drbafv7/QdcQOXL3XlSoll78qAZpPfPzf3erSmpvcOe4md024wmAydy3ec9qdOXY+3ufgwxIwNreve47bbz4dO7l7Dm5z1YHeu9xjaZ49OeuWZ1fc2OSQ2+bXKjjdy3cfcydvP+Py+bw7/LADrrATVXHGB92xW067dqvj9j35UW5w/R72ppGZswtubqnuhkerbuee7nwY9WwFf39uaXfB6csOTYu0vuL1B9zdd8+4RqPlpneMujHYJz49an2OGKu13Z4eOye30j2W78utPe2YQ4e2x+sO57UTp+bc2lrDTW0bcaO7xwRbcHFh1Z07uxiP3QNg/RTOzsdryx1fOhk/w31Hpl3Zr1VLSYDl7ErHLS+uuXE/vneMOnc0uU+rp2fc6bsvuEIx7w4+PnFm3VK3nxtzRLGezBG7u/frwul5t1BvuOHxQbfDrylDCQCwdusxd+K2blT/6MMPuNxhBH/qdXfPbWfjOWL7N36NG+k9m9xCF1CIx/f5JTe4d9rt6q337cnuO9VstuI5Ir6Hh6ddngLyg/nYjvDrr7cjpp5yhQBdF/waeH7JlQdK7kBvDaz2hPbjOeLm0661bcjtP7DNlcsFV8Rces9Kza2s1GP7btt2rAulglteqbnTZxa6dsT+bakUPW9H5Bodt293144gG+qst8UG97mx0QE3vX3UlRAgqXn7+54Zl8vl3OGrk/dx/b07dsc512p13PTsOTc83l2PCr33Z/bcgpu7Zc4NjQ64nfunnAP7xo/de853gbnDV+x0kUrFPn7zSVdfa7htT3usG1vX+ukxdhZmVtyFswuuerq1MUcUegLgfj2+/UOf3ZgjyocSPabutd7jVpfrbmL7iBtrJGtuYf/eeHyePTHnPBa7v2e7x60HnN/82QQsuxTaVoncrfaAtmiribawEMvzx/9n++f3fzF67He9Pvq2n3pb8I5d//1viP99/raTqd9e/jv/ED3mu18fve7t/5r67eOfuSt6/Le9Pnrad705eNxvec5vRE/52l+N/v2jt6R++523/Gv05Ke+OvrlV/516rdbbz4VPfXxvxI99Qmviur1Zur3F3zLb0bf8NhXRu/920+nfvvTP/n36Ouf9KvRS37iT1K/nTszH93wsF+K/507I++Rbz/zPb8XPX3fT0Z//tv/kvrtfX/2sejpO380esGTfiX1W6PejJ5+5Kfjf7femL6Hr3rh2+Pj/v6r/z7128c+eFN8Ld/29NdHofat170sevrlPxf954fT9/C3X/LH0Q0jz4te87N/kfrtS58/Hn3DY14R3TD1/OBxn/fNb46e9qhfjv71vZ9L/fbOd344esqTfy362Z/5s9RvJ07ORl97w69HT3rGa6K5+ZXU7y/4+f8TPemZr4n+4q8/mfrt3f/w6ehrvum10f988TtTvy2t1qLrn/uG+N8dJ86nfn/Jm/4meuQPviH6rXd9OPXbv37ilni/Z/3U7wev9VE/9eboYT/2xuhTt96T+u2X/88/Rw970Rujl//ZP6d+++St90QP/fE3Ro98cXh8P/Xlb40e8lNvjP7pM+ln88b3fiS6+mffGL3oHf8v9dttpy9E1/zMG+Pfl9Zqqd+//Q3/J7r2JW+M/uyjn0n99scf+M/ooT/xxuh735h+NjNLK3F//b+7z8+lfv/ht7w7esiL3xj97j/+R+q3v/vPG+NzPuNX/zB4rQ//0TfG/z53R3p8v/Qd741/+7W/eH/qt//44l3Rw3/kjdETXvzbweM++X+9Jbruh98Y/dtnb0/99oa/+LfoEc9/Y/Szv/d3qd9uvPtMvJ9/dvVGeo74tpf9Ubzv33z486nf/vC9n4iue8Ebox96/V+mfjszuxjv94gfemP8WbcXvuovokf9wBuid/z9J1K//c2HPh/tmshFV199deo330e/n/9307Ezqd9/7rffEz36e98Q/cb/+WDqtw9/6vbocd/++ugZ//N3olB76ve+OXr8/3hd9PFP35n67fV/8C/xby//3femfvvCzSejr/nm18X/Qu3/++G3xu/rP33wS6nf3vEnH4nngZ/96T9N/Xbi+Ez09U98VfT0gy+O5i8spX7/qW/7rejpR38mevcffij123v+5N/j3170nDelfltZXIuefuCnohse8r+jY7el7+Ev/exfxPPd21/57tRvH/rL/4iemvu26Dv3viB4rc+ofGf8++f+49bUb2/4od+Nf/P/1+1zH705+obrXxE98/GvCh73e69/WTz3f+ifv5j67e2vfk/09L0/Eb38eel5664v3hPP+/7fytJa6vcf/e7fi572yJdHf/sX6XH47rd/ON7vx34kPc/OzS7H64JfW/1z0u2lL3xndMNDfzH6k99Nv8vvf8+no6df9QvRD9wQHi9+rDzhW18XjyvdfvnN/xB93Tf8evSm3/yn1G+f/MQdsZ3w7GeEj/vtX/+a+Fr/499uSv32+6/623g9f9VP/3nqt1tvOR0/G/8vZEc874feFvfp79/72dRvf/4b743H0s/8YHo+PH96Ph6D/p+3KXR7yY/+cfTUx/1K9Kd/9NHUb+9716eiG659afSCb0qPb9/Hp3zdr8Xvju+7bq/4pXfFv/3ub6XXqn//6K3xvt/yTb8Rhdq3XP+K6IarXxp96uPpefbNb/rH2N569S//Teq3L9x0Mnric14b/wu173zBW+Pf/vUf0vfwj97+obi/v/CiP0r9duKemXis+H+zhh3hf/uz93wq9du73/vpeM76wZ9Mj+/l5Vp8759+6H9FxwL30M8Rfuy/7S0fSP32wY/cHD3p2a+N/sdz0++5b1//nNfHv3/683enfnvNm94X20T+/7p99j/vypwjvvtpr4+e9vCXRR/8UHp8/+7//XBsu//069LP5o57zm/cw+WVtB3xo9/9luhpj3hZ9J53pm2md//BB+P5+ccf99LUb3Mzy/E99P9Cc8SLX/lX8Tn/8M//PfXb+//209HTr/z56Pu/LbzeP3Xb/wz6KBerr/WQH/y12L75cv75Y1wK92Sr3f8t5//zwMIwD662uLjoxsbG3Pe98C2uXBnYyPtdWqq5syfnXKlccAcPbHN1VU3knk92qeN790260tRAkAkyPlzdiJQ3e/mSq7WGO3Fm3pUaboMJwnza24/PxKjybh+tQv6rb7MnF9z83EocHZu6PKFf+miuj+Acv+u8a04NuaNHd8RRNkb8PBNkpRRtMEEY+b+wvBYzQTxSfxAK/HFbbri77uwi54cOb3eFXhS3uNSN8Jy8e8atrTU3orxUuF5aWHVnPv6lODqz/4rdrvUQlDCLnLv99h4TZMeYK4NNk2+24yivZ4KM7B1323opCOvX46MSxy8sdpkgB7e7jsrlP3bT2TiCs2f3hBuGpohPUzl3ftEtLKy5sYGy27kT1QZyOVdba7rjJ2ZjevRlvYgR79Nts3NdJsj0mBtTIqsXFlbdzFyXCeIZKKQ6N5tdJoinfR85kDBB1rUBfARnOWq77ZNdJkgBVOfZtdoGE+RgLwq10ed25G7vpTLtuXwbmCBugwmyuljrMkF6miXrFP3llbo7Mb8YR+2P7JM0TF9Fh0yQQZZd9lGNHhNkeNug2zHVYzH02Cs+EnVsVjJBGP05duf5OIKza8eYGxxnJDHnzs8tu9mFVTc8WHF7yKbpRK7ho2AnZ+P7edn+LhOEKTinbz7n6p7F4CMtY4OuAx2SlePz7sL5JVcdKLk9h5MUnla1EL9rd/buoWd8eeZX9z51j33SP5tWy01NDMX/2qDOLy/V3elzC67s2WL7pgTd3j+DW491WQL7d064au8errN/Tp/vzhFjYwNuuncP13Px4zniVJcJ4q9ViNvmnLv95AXX6nTc3m1jbgR6PD7S6xkvs0urbmi04vZs647vdYZKvdlyd52djY9xxd7tMROE+dp3nJ9x9Vbb7ZoYcRNVzGl552aWVty5xZV4LBxkekzbB67b7vbTM7G+yNFdU67o5y3QjO85P+dWm003PTbkJqFf5NvC8pr7/G++wM2tVdyTHnO1G/vGl3Qv0+8fRe7mk71ns3PSVdff5d6xT84suKW1upscGXTTY8Mi/WV5re6Ozy24Yj7vjnqacSRTWG49cT6OgHrW1mDvXV5/18/MLbn55TU3Xqq4XVPdKGKxN9bW6s34ffXt8oPTqXzz22ZnXaPVdru3jbpxrzG1/tg6Lp4fPFusOlbZYIsNnO1GXP28cvexC3Hk2zNX/NzGlCg/L3kWyrbpUTfWW1M2rvXWU+78qTlXqZbczqckLJHihdWYqeGjvGsHxt2B/V22GBlLp8/Mu/bN57pMEJ8aNZuwV1bqHXfm+EzMBNk/JfNEvG7SnV88ER9/x2jBDfRYAfkrj2wwQXwEf3RsMGYWUdDXR/yPLa7Ec8TRIzvi+Z4VWLpR3rbbsTgbR9o3ntvUlJv1LIbzS25oYqgb5Y0P2F2LmrWWu/umrk7C4Wv3xUwQh5SHY7PL8RyxfceoG9mJexg5Nze36i74eXakLNhivt/rc4Sfr70t4OcIal3cM78cs8UmJ4fc1NSwqAgzm29vzBEHDqTTSW+961w8b+zfNeGqPcbd+jxy+sKiW5lbc+MjAzGjlFoy8Rxxej6+xqMHtovf/Bx1xz1dtpifI4YHy6IaiJ8L5xbXYjtiZ2+tavZELtfZYhtMEFaU82MUTJBxCpB3Ijc3u+JmLiy54U7H7emxGDq9a/Jz/t23dtf7mC3GsqfePpldjseFX+v9Gsj3hkyQg2TAtjrx+LvjljMud+aC23fZzi4TBJH/dUbpuGfTeCYI7JPFz93iTt95NrZpjrJ6US/d4c4vHO/aEVfv2xjfrlLeYILM1zpueGzA7dw94drQVWvefc6d7NlMR67Z65zQLIs2mCDbrjvghtcZJie628fj+9yiq9RX3e51G6Sno9GsN92xUncd93NEexu0z1pRd46oNd22bSNuGtobuRPnYqbT+ZOzrnTNIbfv4DbBFI7v4e3nXGGxvsEWyyEl6uTCqlvxLIbJITeB+98aLrrl5bo7fbbLBDnE8d27zbffedY1q/kNRintKW9HLM2turGRAbdj+4hgwK7Wm+7EyS5b7Gqwk2s7us/hznsuxGNq5+5xN9xjoa2n2HlG6dnmmhvxjNKpMTGG655R2kt18YzSMrKgygttd8+JmXiO2FOtxnZEfG97TGNve184t+gGSkW3tze+m73UQv+u3dFjCPo5IgeNG9+OzS/ELPCp8SG3fxU6IKsNt7S05s6enHelCzPuwBVI8erZibd87g73rxfe7hYWFtzoqNQWvBh9rYf84K+5Qjmc2t9vazdq7gt/+NKL/p5stfu/bYEgxot5/Te/yhVLVZFvTsNCV9mwqlxYFR60UBJ1E6pzELiE0JNuLG9Kh4tK9RRK1Gru6wa3VtVmWUdPm2brUKMEWhdCxAmLfHuXTNlgaUdqQLS/dGtQd6PbcajDQ9iujhKclbsSzYLGXqlZwFKGBWiPtL2Bun4KJQxXWFgLisa2YZA1SBVHicOUTgAWXY6bVMUPo4IIUy6YL54qQiT0JLA705aVJgh/Yz/FuFHnoZ6edSw6Vnld+YDvRHHz8rD6b3FsCk+yip2uTGJUerGOlXVO6zp1CpFV2pG6AqmKMkYpWqGrIvqv5hE4XMIhz6ruUggr+lPYTmyvvrb6xnOy3KAWlSygtKPXYPrizS93p+cjt2s85665+pWpY/nWgBPOPGoKAFIA17cKNC1YMpJVKahbQQFf/U7wWdNY10K3PMbqtuQAlcXOptoUvg2ebQbXDGqCsDKLFvPsVMJlKsV1Kc0fCr0WUe6d6Qq69DlTEC19jjWsMbpygiz9zeNiXZyVWhtCCBPvAe+HXvNaQ6Xg+KZ+DN9JvU6zugr1wsp3QUcL60V8jOnEacvPJloNLYDY1E6h1od+X8szUtdroy8ozelbewhVbFCRrb0dKZ//+QVTvLOJNAdqE8k52hYOrpxYDIqWC2HZC1K3ogmHmlVXxDlgM+jW2DESPA81h1KitQBBikY5aD3HiupHI2WRJrjeyvP1YAWXbn+gcSLEtzG2VNUTPgOW1RXrtJqv7Gp1LqhRUzmvtNR6gS0t5C80bs6umBp1FLfVY2W9lRfkcxbaHflwWWEp8lowS4o3oIHUxrxePSU1sVojhjbeqWR8dm67yxTuL+5PdGY6SIfMXZ4E+Xww0pqjOVbE+FTx6fy5bppfq1N3/3ry9y56h3/d13ro//zKgCCff/sWCLLV7n3b0gQxWnm57YrFtuvUWGoOavKTtoGtxdhCAkx6GxpbQ3dJNXKrtVGpxD32YRsf85+/LSgElpuXkz/Fw4bmkutpjyVGS+EOpaaOzxEEtqjSToGx/C0yx7K9BIHG664Oip86ipL5e3M8KaUbXZVUAymfwwJ8Z3KeIiqzxH2YgbHVgVEPQ77Qy1VOtkMVnPXcbL9dLxLt20DSLVfeLwVg6wBIBm9MAKLWLkQVtTAqjPrazmTRLC+ERSRTTh5EQpvDxbBjpQw6qySqKGOnBCYpYsjtyMSgSrt2YOnkCD+9GK7SkeWACrCEYI/29ygFw67h+9Zgf8CJ2EQYoRn781D8PouHJ85pdUDt0jHuu20fC/BoZQfFGnGorP15TmeASmqTfJNOBlhfvi+3JPvMXDsUBMXEPcQgIrhAgU/falPlsDCpcW0auPGRweTawsCHFjtmG7zQDm5HMFqUoVXifKJaw4WF4DzuWwMOSxWGfH3XSBjQAAilr0c4rQCGKYAb9wdVYER1LjDkSjN45mDkaceKc5QQSlRCgfmzc+F7AOHhdW2L9VbBtVZwPymwWd8FceAV9YLlDRCGLE2lD0UhyWhsOCwqnSGGKsq97qwGgcROLyIecqZWIAC+rkUWH/abHpPsr94vz8QLBmIUg4qN70RzeCJcvpe3c5vs8zo7tnvsctC5z7dUdTM8j+r5enBMixLcajzkIX5NsCM/B1sJAtNxW0zeqfyR3UHgpgGxYV3GlcCkEFBvhoE838q3Je+B6+kH6etZhYhy5rqCVp+EKPWwZJQV68NBsV9R9eXaBLhqqDLmYs62lq896jqXAcCixK0D89ozUy3gZ3XnZNDuYfBpZXrMBH1lIATz5fZrg+Bn3E4mAbj2Y64JAsC6hDdtKj7rAqtxqcqK61fdusRK5G5Vh9lqD2TbAkGMVvrXT7tiruTaT37kxnflU4mhV1yWaupkTOS/sG7FOxd9TQJOFJaTRbq4JBfWNsoP5tYwEYJ5kEK9p6aClV9yO6fD1Rp2SIZEbg2TKeiooqQqS8gpo1aU7x0B8LAMJsm0NFyL2K4DgKS1umqW8vUighu/wdiOeuKe8fdHE5FVT2tni5SgbKhF55OFLO53j+Yaf+6llcQNpV+dEo1lYwSVzJjieRvg4rNmWUA6Rqw8xJKEqWoiWGQJvpFS71sTUSqhTA7jrLQsjbgmojVM1SEotbZHlf81Gp0sRuEJ6GgDVZT4Q2lIGuEauCHIaIEQTVUil1FoHpv3mVVCspxoXW41dP7UT3CMaMjTUNPnp+FoRf8IYvlWwj50eMQYgKGowZ52KewY0bFKsWz6YBNlbm8APKyGUh9TO1ngmXF+zcrgvRFsBT4PxRzgdm1MQ8XkVXErOwA6Y8z5VpnHuwbjPwfqu45u8+/5hyJlDvNiE2VPS2tlk+1AZlGJFVAIAPhr28PqEbVg6dkaHK7U89QlWte3O3AoyFLybRBANfdf2y0dZXmezQErXSrber/qKA9arAG0nlUILquDITrOtEDOPRqUs8ZqAU5zWc2XLGVfXAkfoHJ8ziyDHsFuyN0FtH93Ylu0UQVIl1POLyQDPJpBBSuspayyEjcAUa27j4crsulgBSpdtQ+hFC7ueRFOqqvJZxNNJ+9HDraFKCW/oqqekAF7I2wYpPcO3AZmUF2ydPJgxxbOgKUDZlD+lqQCim+dg6ge+OHPJPs/Oqn+N3Fq0Qx4dVDytzWWgG9FpHHpaj9WG6xAnBgV+tqq0hkFryXDIxcuvasYZgQEBECFEsO6Kh8DRqu7B4JrcRHp5t2+FYJ2WwEVHwkA6yo6HVTyKaFaz8oVU+a6JkqsA7hnYC6P+xz/1ks3i6vDqGrhF3WL1Ty+AsfYalvtPrQtEMS6MZOTrpgvuzzKXtJQIGjhW2EZk/njHho2UBFRII1Sl7EjC4FRpJQfAIectexbJ08Faa45GCbdA0RByq6zDAO/y2Jyns5i0uf8ru1B0CAFLkA/IDeVIPLFc4kx0FmQQIEAOO5JmCk5gCCixC3KhMbbIeLnWHaN1yX2cK4zj8gmdVFK4ZLFLFsX95lpRDDumlCzJ61TU30LddDgB2C0rISp3b4NfD4xHNcesjdcslmBICztLNNxEJ1QDk8Dxn8Lhk6xl2uuo13aSSOjSkRLBCAhp6aWUQ6Y+xRqbTPlQ5QZhjNplf7V6Wbr+hwpIwrenI5KETjRhtfGPgBU1OEUYwUOD+5faVaW5W2xwg4AJjFWU/emGDQIK7ONsOGqxi0j2rxmUbZTU8rb4XLMsRGKbg/MtIPlbosAANemw46lbmQnkdXBlBUCH/qZEQxsIDI5+MUkStveOWEyHEiXF9FpACcEP+Ou4R5y/8K/fz64Dmh6dr65LRgdZ7/0PMLINeeOwnIzuC7Fx7j9zmQflMMsDyRVEfJNqVdjzSl0jCrnMSf2qnSE1hauRUMLe+0oPvdH2k4D1Y+G7gTjRa3zfKfyCDxEtyUlSPPbpGMm1nOwWejYlblMKlaICLAc7+poxA2My8a0ZD8WWa7bSCdtgzGp0175d+vqhKVZnEkc0DyOpdfAaL06UBxQ2BFMFWI5726H2mHgYxGAyogqKQ6tCr5T0eeSQJQ7uA/nUKWEaXcAUGEp3tYpsDB0kAYlgzlHCmYq3sf4PHinHJgLeQal9qlAkAFQsAx6hGBLjnaK3x/pUYJtxuAX7Kx4H1Ri4rPlGOI2msVGUKyMfRqTAyYLrQAbiMFAlpVnK98smcrtA8lYGzqBEtpYZ+tKz4gMojKqo61XgfGtdexuM107ByCLrfL3nzT3EeXrAexxHi1OJzY1y0u3LzUmyFbbag9g2wJBjNa8cq+LisqZhkGqHZ61PTBCDOfFOTn5stXHE4Nm4Fw96KDQsfStikhME6BKaTKJvjWnEqOheVhGXgbuSSb8JvJ2y2eQPjImI/qdsengot3+/E0bn6MnXrfx2YvosdHwa+GcxWMwPB92mdgnfw6gyEOQu0yggCwXHVWcw7H37Qjn+uYz9DXILAETpj1aCRrxcRfIxBguB5+nL8PLlh+vBJ1uX/p245yGToNv8086GKZXiwhw1YwyMgLMKGnjMjvvVES6KzqfZP3ASlsBBppwhsHq0M6sSK/hsZhaA/BN7y8YJwBUJCtEnRPsDQIHBAqyNHtyBkBCR1unbFCrglEpRooJ6NTV+8nnzvNU58OpGPoeEmxYm64EgSs91hk5L2KsUmQuYm1N33LhVEIxX0bJmNTvCvPymddOIEzn1TfxfpHSzHPm4KBoGnsbKYyV85hTTieOaR7pDvF5TiSlgdeuSRymaq/EatwGknmwhVLQ8f6IYheGku3aTCVURnhr91RYq4M6B3BYqp9I0ifj7Y4mTmPuI4g6w0lq35U4Bal0TDrtSCvIwRErHZd9Lp/FHHkz0jlxndHZ5F7Gv21HRJ2CwJzXkboQH/usLGG80c+JZM3KEbT4nLw3+V07gsy93OH9ST/VmtcergTZoEwhahzZEYzOx8cD+NW8AgAXxroGJt3xJAUzh1Shzt5k/S6cnw/qk8S/QQ+C48bh87pGwcYxIKhdnAN7Ym4h5cjF/XpUwmKIj9cIAyJ0gDXDIeqVE4/7+V9fTI6Fd0oETq44bN8napkRxNgDcUrFJqHdI2S8cG2RCpAUPglAA4BhDmOrfVw694VrrwgCezkwS6mpQtAjvobzSOEByyZ/YF/QAdfXHa0BVBtPgkJ5aKyRPetbY3fybMrQG+GcpFOCeW1rR6aCc1S0F6CaAkcK0L+hTdhE6hXTaXTrALzrYB4SwJdiI0UI5uVOJvNL/mGYu5TZxmBFGXYsAbMI70382+GefdepO5dIlFz0batE7lZ7INsWCGI0H6HuFPMqik7RPXnraPxbYqilxZa5P2nkdGSEwKaavLnol2GgcjHLfc3DNz4PfeGs3L9XhUI7BVwIaBDGfSBST4r+I5JcyByiUDklZEaaay7CPUPesvvY58Q+Doh4nmya7Un/i70KDb41lTBqG/Xqcx/t1m7XLBkKs8bHg3HglpMFPAKro8gokBbgYwQV95bOuDAuVWNQhQ4g6fKktPs2eDaxIpf34BnC44wKKk1EOM10tJmHLfvWIpaXC+t4CHAg16cALIWDx+20AvF+5cJAic5xFzoHeNeE7oWNL8m+GLiHZlg0RsL3kPuvbcvbx6CwibjPGA8qKMRrYJrK2lTGWBNaLhDVFHonVLCV+3NM8z2oTRWD82P3eLgG5sUXcu5xlxfd8lrTDQ8U3GyPWdJQY721vRwEQegMFhZWTdYNhSgFG4nsmVUNFqHPSPloP/SKIBgdb0dnhAAwtATEGnGPdPQ7MLDzFxKns8CItgLvivOrwWhmx1frWu/nKNgzVyQOfPz3WaQcXnV58DyFnXBE/LEZxeZcSE2RlXBkNe7zkUNhoUHcsxxTFPwxbrtD/L1xHvQ5Ny4B3CLvFQUuAfbUURmkOKwAeTiTFID1lVJCjnHKmYTT3jwM4GMFAQU1hkSEHX3meBbj1h/jqoNBKj9BqQjprEWVJsLxSVBrdT9AV35WIpcUUO9wrF8OfZI7IKbutwMrIkKlGQZbRLAj/oIM3IcFAycUQGeqVnydVyUslwLZM7CB3N2SCRJNA3zbndgmbbAiCjg/wTLf1m54eFj49wTYp0qoNreIdxqAxOp10FJjHxVovIa05Ogh24IptYXdjxD7dObBUJjYGWTWUutivVJLcm3JdgtXjYVZeKpR86xyYS08niECnAIc94ORTADYAPq7G+aC73TuMQmju/PZxD7s1OUYKowDfDoCBi5YZBr0LZGdDBZzC4DdBujRa9G5C0k6zKXUttJhttoD2LZAEKN51od30iNEXQUgoSbSClTbaey1kSIgUW/71jP6lvuGR5nRnuKViYHWBrKcpzDbpyCeqozIPLQ28ogWRUD0df6jiIpw//ZY0DgtjKkSuwA+CkiNaZ1A3rFqEXNqoYtSRJSVi0dOG9g0QkegGH7j7ck+xZIJ1hR3J7nG7RlEZpuJEVu+U0YYyywXCIelswtRA61dwjxmiuiSPoshVF6Q6ESjV9bQt+ET9aCBvAbnMf7NqEJTnU3OXx9XWjT1zUVGqTNBZ7zbnzBYIjQ45C7Cuea7JzQcmFagmCC6XO3G/rDHCipth0wKVtAg2JNV0YbHJnBAI6ytWUuGboWsPkXgSu4uDkUQgyCMjkpBNE5UtmJGF0AxDQKJCkO4Nh4337QRpkIdGiuVnPurbxl0OyoL7mxtyD3zY+WUNoVuderatMAyOqqYScZYFdotcCxrE/KB8hk0RhNHqASAR+tJsD8CoALLiM9zbRpgsJdaum0hWGkr//+z9+cxkmX3fS947hIRmbXvlbXvvXezN5IitZGWSD6DMN7MGIIFDvQkGBA8kATZoGV4pDe2xHmQrYEo/SPrD7+BF/mN548ZPcMaS3h+WimJFtduNnuvrura9z1rzYy4y+Deqszz+X3vOVHZzaXZxTgAwazOjIgbdznn/L6/7zKExG6bZY/0wHwbMfqVx2XkOALErfbrRHLkZHj94PzWAvSj4FrEgm20GmD0j3jmRTPmaFiJS92H/MKBCdOReoIhUGDN6hQSM/4YRojkdo/uCPoSMFa+Pc7d64LABcEJNgTa42FaDr4ni8RbO5ZHk3N437IRQlaheg4MzvkO/e19iJHFdV/GhkIThxwxDJ2H/4yRiKVj5miwk5pob/9mw6inFs3VKTWqsIdS2Y4ZbJ4c2Off96s+Bcdhz9R+n8MwXR8BTIUcpRZ5U3INzFQw8Sj/oI9IhWZNMwaXwqlGNNdNrlkGkwFQ9/r9SA9yVjbs1JuIILQxkz17MwjiqASnj/MWM/GlZ1Az5tb3wozHMTrkHqS3C3Gz7eefB6MM96ZZsFrms3/NPF7PfUb/hj3+0crwXnzVS75pWD3u76fkZbsnZhBAAmbMaJW/b+b3WW+8IT5z2RkA0ri3SuxB77753QtXTeQwkzEZ37YxAUFiJ+bm0OVZ4nove95ZAhpgsXVtdAFONnvKaU7Xemo2v3g0SnfkMj/1+pmg10czaugMSZsuaCRKhsjbNqklh6kV6acszvONdvKusbiX10CHvegBiZysjpHEiW3wHb/ibX8OsqcejXbSyll0SIC0u2pZ+DNls8yNbCnncPFviMzr7/Cdjb6XmyEpCop1y4Ofz01o74JQtQ8eDmpIjaSIm22JRWTiAjskFf47pVbtMRzxC3253V/rOzP+HK77igV45navDZupopjqIfZtXlIA2KUi8EEJ0NQl+90aVtbicVIWhg0ZmTFqMElpyZ0NZCjg72RvR5PN/GrYw4HXw7xXCx6xg4vvwu8/zsDVsMPwcwS4av+J/aGeA/8GcWkJfVHI1ogBMvpvMl7613HOZKUxEbN4/fTlyvx74dgUuDGmrUjwMICMfP9YWoEpGAgywrCuk8YBgMwUFVckCQIsEzVaXTzOMhwFqZJBI8eEKWbvFbuWjJ7YHdTcz22cCs5D3JC3x0DJw0q/+c9uAPQ+ZVmFjkbSxz0gPfygn8f68L0abbCAvE2Z8t9zBP8AlVYmkKokMxuDa8lIYjuNOTlADHp00bxUhzEg5TMNmSSjZ9tjQ3Hb3+YL2LmHZsISWJhI6uB5IlCe49o0Yx7pYstfOh1kUlRnwMSQvcHwxz0roH8VRrfrcA/J9NJHxGyxZyYIqJgkDDH/TE57xkWCvUkGaY0auCbnwJyCQaWD1IdAWH3Ksjpo3E4JjOPeRgYbOxV8aTIUw8ZwVZpXen8s/h2ABjZ12u8AUIdeLIyxdUyFest6sQ13++ej/7Z/dof70ch5RSRuYMNWR1GQP7Y3ss+wk3T/BtMQw7HdCm7z/uL9zYhZmv4qSGlMTgH85Eh5pOxWj5NrxhDgcv8wnpVt1q+FjCpKCckA5j3cjB6YUsZfCfdQJvKiBSlZ/YCBIM0arw3Bd/MekzEZ72ZMQJDIaPSuadp3JajC1HfnJy7aCYotddJsT/gNSEpndLh6t/8GfdKwJ0BTJe2uYxiGjhv1sHRPJ9ujHVhMCmxA+HfpVjvhJ6KxDrJPAMLQbKwdVyObC4AwOUCkDgUYnaAEnZsa6TKlsEr0vIXct6mbvvsf0G3HhijHpqk4CQPaJ6HZbf7uLL4n6MwEfpx0KWPxxyY+GKCSgmK8BtSup6BbUhOulOzeeX9tlwNgmdtlAb+pE/huYJnMb18T7Axn88I+EbBg8fOvx2meOaitSRnupqbzvSC1uD22bauCKROk86oHxPR5UH03+O+QY89C89DRSrtBn7o8DHvBUC0gPj8ZNn40cKUPBwGdDiuD+21iNfxM2ayaOGScD8OWiPjFdI8zLJvRzS43mwR+uFluvsvy82UQQDBpPTge8/11Y8RuKjqDZIIMrhXR5ILbM/4e6NMIG8+AAejazwwb8NFMtn893M1tX4OOvvEfAOhbb7YGev2z6CYCjKVcwfz9rJwnSlhgRkrjRZMG1gysbemqFUGjQUav0+RVDWHJlshhxpqIqXO6HWkgWFcSzIM9zEPKKjAAJgEe+sVIkUVgsHcVLtVYixykPXf/EM8+AGl2vUnD7/h7YAzO3gomuGhy3PRBD1zX8AgzscLwVEmWSdrdn3s2qnvOextMf8l3wZPlwrTCdXcXPROkAHuSiXbFlatRGRPZPBnZmzfC+4+7nwlAhAkmZHLwHpYCloPH2RmU8m1AUwRS2fJVsJEkIY8SM+5hjGk7I5fb+zALRqemYLn2zodZJc3ov+oBjmoXAKovvOj/SL6zSejhMcMLhnuQKVyn9nMeQ1rOm0gigm+SGso7GN3yuWGDiENh5eV49uc/9lRQOkb5pBpeE7BKv/lW8FnheWlfg3NNgIsMZKbzNKOETDLhHAVPEX0mF/Z3abOYP0iKmIkcZjLewzEBQSKjOHuusdh26ca14RhAUGabUe31xWXBzfNePxHOQ4fdoXcnHvjIqjKsERS3aHpVJAA++LNhYjxiN2fUW6fQnrtD6IiIVpiFBCf5Al2levdMFAEnTdRsL+EETrpn5zPPoQAHnZfpAOpyXmOzRcYNQSSNsaOBnjFwE4+Txc8Hst9+Dkgi9XQ/SOEuJGLQbfKa5hwb7AKaZlOgMB2n+RWigAsALwkc+YegiLbvAXO90eaVYfaMJrNg4zbcCR03WBnzMyuiJsIsrlmQ924m0WIwR5FEQIJddMp+hvgumjZjIn/JYpCil74JK964HAR78mPoqn3ApgDwe5M5MHXeplzERnbF3wP9k1XYNFBAxpL3eqR4yFbY+4aR2vWlK+FUCRQ8mpbAe3rwFjwHUBRpp6ZAnGIKvXX53MOLLIXmevbvyQw73kSYf5Ob0I5vWBlNJWIKyjQK3fR1D0yWT+wNewQ0foBnqJ1Kg6wGTTsYwTy5d8lfz+w25mUcZ/K27Y6XNzGvkcqPIrM6Z5la2fatYX8PyARp9FdjjWvH0VP3LTpTBaoHq4LGprzX6jf9d5lWoADgukk9A/uSgH77OSh602X+fqpPnQn+9/b9+OzMw6QU0swKhV2PDEMtotF4KO7p9dv3EkC9wt/xmcwAJNV4pjqfiWNu9yVLKNoJPPAclGgWUAJaF8LYpPzhrZNh4IPR8cp4JBsTpISaElqJACWrj42LBCBGzmZLK29aH/T1YhOA14mMoXZw30CwBICGJpMY6RWaGmSc5Pv9/V0tG0TvQWfmAYDzNPpt9yo4zof347uhwYH9RHpZWKYEoiDhMZgxro0OIwHq98IAAM5Z+zs0rAzwcd4fSy1M4Xr31nASUmR05G7Ya02fwNyH55NrpO6rq9nwfKfMHPOZbOChYWV8j6Rh1QOzxyENsSADKcJGmshhJmMyvn1jAoJERvmxp12ST7kcHeViuZ/Ib++yC+P06VtBDa0xAGTcoXRjy3V+0Zsa+g3l8LEP+s8XrfDUsSvBBZDI8nDTyqh5GrXjNBirHwXdEcZ6HQNRsF/yPZ4xU3ztNf8zPEB0E5hgE8hIOWdNyo1JqfHqANiRPoJjti939a4tQfpotXFNtOOXgc7KFBp2M8n+mIMvQfu7KWxKWQAmSzMMvfEonNGhIeZx3jlgixcCa6bzH+uUawpNRD6hko2bTzJhxwVN1phgosUoZQUuDdPylW1wBzRZHieLa0pmnFD8aUrMQYBnbr19pnMwHGafls3z4mv8pme0XNgKZR6M2725a3lUJmIYSD0Y+kVkLno96V0ygDSDnTDVi/M+rLJNYWkJ5p6yFzbju/uadeFOu6TgsOCZPrDbfJ//02/fclduOrduxS23fOru/FOIrIERgw4MiTzzm8vhFjHFvIHniNIKehFQYrFaUpH4mQBB8stJ1ENpALCAwCp9hiilKx+X9IqvvBwEFyj/S5jc0AJZl4MgigG/0GVU/4EaDAv3xo2gealhtDXvvTncOeccn1NOKq/neycsphh9LoPeG/SgIEhniuE2KcSzBBOClJCJZIxol9hPRr8SuKDXlRawKdddAgcACfPUX89qo/XRSgD45eyOszDbaH0rciYJbQGIcAwgCmNg5XqYde4OwNSNYbZfBwTBPEaQtHrT+4WlwhwwzFZGxF5BkSgFrNN/L7z+OthQ/BtJB+LegvIgAlfWOMsyO0zD5TZeA7Cm+qY18DUgBhpZBCp0pJyLbuFzViwL+qh0UqZWASSEz49pCiGtqD1OeLYYVggAw/QhFPMiV5vHesoGQ3/o7+9amkdkRFUHfFMhJ/MM8zWZbu2vTnqGdgVwd/75fUF2XTPmNoEtxwhoyFTSm3jNWvt8cl7mME3Ljv8NZa9x5tf3w5ikw0zGezmSup6IqTiuX7/uVq9e7T7+7C+7PJtyNWim1GJqDOudrcvC2vEsDIKYgk2kAOxAkj5rNodCh6Vjt5lg8d+1kGDE3mgtQJhj0DiKWZYBEchkeN0v9AV14NCfqju++W4EGlbaYrQCK8BQvddgA3DIL9LVgR3RjgTpwPTAoKdKO7CJZMFkfDfIRBHmArvOlFnw2qghYe/qfLiLgs8vV/TChqlStFrPAnpwSMIQwTgDKMQ1tCbJKI0Uyvh8BVcU4PCvwXuNkb3SVDJmcrpUzaiCCBx87wxYIJ3m+T3zjhlr5O8gB1KvC35OTM7C86+ms/THMLHCY6QpvB5TV8ugyafx6VCGBSQsBHtoAKvf04DDkAA18+pbX/6/urPXardlTeIO/ND/w4UGmUGUGtkUoDpqgEdpCgGifBadaqFqk8Jc4jPpf2PSKuQ1xjAb/50yqv41CzrnJ0HxZweZdHeV8oG9V4MtxiKn3OE36KPV9vWDF1C0YYNOb6ZOYfgQisEblImMgiwKZZ/QtyiDuWC1HJJFuR4JqfM0+aQxt6RsmNY3i3amu9BkXH0rmDbDohefX/O/t8xM/37VNfhbsQBHjK5Gz3LQHJcjlWYF9yf8bhX2DJqswcFnwqxlkCdpvCllTP0zHjxLeD5w31RrJe0H5z1HMgmj6JVVSOkQ00CW6heQMD1pGlHGR89E/b4cGET0cKDkkjJL02xqBu81eP4YGRj8VTr+X3i+ip2bgolXNExtPwfvbZsi/jinj1+Lg1oAWBzvIdz3t/eHZcft64uwZLBHo932Df2P/Ss4b/Stog+KMpUxxzANi0ktunenZw2TlBwYtGSqKZOETBDe39lj+6PyJHf8TJDppGBkaBT1yH3B/YGbnZ11q1YJUP8+rLWe+cyvu6wvz9g7HOVwzn3j//0/vu/PyWR898eECRIZTbc2702ZAq7K/CI5XCVMDhoacs3lz+Harx39myi09ywLdlCVyREtTCId3HGbARYVRNcZT9e+9WXQ5Vd66mKyzzNB0r+Cnpgdz+bvzvpNfQW6X8IuJTfbzUKJzgMd3DOHLh+6bxkc39vXbIEmt9cLAh/1yuVR+mdJCjJi+LhJoGfD3V/6H+9sGgQTMzp+Dpu4UOOt0oiURDahJn0ikhqSSISJvYfwXvgzZSsY4AGvz4bh7zZCsogCHJ24ugDQocegKSyL78XgAmFNMUq2E58bAURorEYgiGCHkeNI0Z2U/jssu4C0hdXhxKlOogp9LxhlbI5ZAYkw04jXVpkgnK8YpVvgGvRuxycyXpu5tTC9wz6c50lfk8CANmv8ORbePhkT7bsO5xB/Qn8PLZh4fW5vEeBg4TWb+9Fzy2eauvLRmkFQdqX3WloO7s8OU3sOsAJ4/BWiJFWaWSOSk4afGcw75zb74qt3Q6Wd24Mxw9l2P98miOttB+nykEwQbOFQTxCagWY4ZjK1ps6LtPIsfC8g8zCeUnKc1TaCP37j3UPBZcwZn0anu/k3IlbnHvVshamLKJ7eECojpRVPI04ZDRbOPXNPW1ldDvkeC0gy9FJJ5mCTxUgOCfJ942A09tP9wAeC3fGSYI2ADr0z14KxsMUGRLLCHFdBLWM+CTAxnfWfWUqKDUGtAmxMeryUKNoJRKosjxI1+mZQrtYeN4re4Waw9SCx4/W8s9XKDwlQsEnFpkgisbzzz4D1Or/ivh5Qau7L5gvloMU0wBHMD+2/ARxkKOIJWLJJmMhabpo/+G4Ez1Rqu+w4wLNbaLitWR6UvNQiKb69fXnYdB2GqZ3GA7zE+vzOkDbWlD2plA9ADBllo5WUQlop352PenB2+vTNcPqigtsLQEw1dM4mqb+vx4QJMhnv5ZiAIJExdXnk8jxzgzOzQYbCMnH4Nukk0EwajTp16BctmlyCppnNbA53IYhMt2+CohO6U0aI1XAvdzvFa0O6liHNK13/2wEqKOPAuDAZiqjGwEKP6vaD0n32SlCz2h7m2lXB2Lb8GhbAVWCYgFLZoXnifBZgguSX7SJVwyMlg6lVcuRskE6cX+3HkX56LnABl05cxX9/+ZtBvbeh6UJGoPRkw14hjV8YSLwHKhwbKZrzkGrppppFnolIRAGvTBIDkIiEJDZYxJtIUxTqhcGx4gCRAZLizVAT2Whj/cKpKfqZ3KDe4FQ7JiLQvp46lehfxVk6SQTsUrBnLsLsQb0wXEV2mX19za9mNuVxJoiCIkH2Srthr4LdOwIUZKJkAKhy6YYOV+eRyGF+XpxOZORBBCTI9qPUq1kKwLbj5y8/6kGDIejYpRSznJc4r3EtSWQtoaFeiiKlREd/ACaMAt1MZCHFnt4rlPao1KaC2WSCYpggjn5mfgvzFeaowSkYw+K9tCNPCQrNn5O3rZafFPdBJIa1D6BAkz143NMnZ4PXoJbiJcE6Qbp+BjnMnV1+jeldt+fGnDccDxlQKcyS9TUETkYACqpPPhWV59r5e1nYpFxZGbuXReR7YBNN+XV1uFIzxRk/TPZKGmcyAtCdYvIZFZcoZg0jQICcFIAf1+nqTQtqpft3R1N5QmNw1R7zPFi3BAQIThCIbEb2Zy/4z0cKzu1ty8LR6dJEMJ+Pe8A0PlIL1hBE6GGOI+OkAIjRWcuTPMiEHMfeHK4MxzkTdCb4p1ISzv+8v7hGaWoYB9m1ZErXP/S0//klMWnd469V9aKXgtcffy46dxm2OCRBNbxDFGxZ8EBqmCCT8d0bL774ovun//Sfuq997WstGPh3/+7fdb/927/tVmDNO3HihPv5n/959+d//uduenrafeYzn3Gf//znXV88jCbje29MQJDIyOYKl+WFzahHwTj/6Q+Zvx/SjyFC9ycl0G23C0522yPAI7OpLuLFy/ELYWowgQd070jDbEaxfllwwnczfjOSqTkVNnQ0OTXxcjxGGkA1xwnjqSzSPayQutIeG0xLKzIxEHfIIqmTY08K8xl8Hxxz2DEikC4DbWcJw9IC9PZ2bH4oSLFn15gRje3vVmHj9Xf8/YV0t7FeHRzssJiCLxtTjEaYQh3GidGz1kHmBDc6/ev2vmMaBu870oG7KRuUEYU/n+ejRGHcibbEYCHBhIq778EuFzYtpBZT3iQJJgZ44LPP+1O6jIwPNr4u6KQNV8aZA7yeiwCCeL+ohKYAU8cwbiKMH24o9e+MBIjfRcGmyD2td+CNHVk4YtfE6PK/04vGfii/N19jGVlk/LjoBjsbZkt6JgswNshGuvyc7xgOZhHlKPTw2/vXhTf/eFb78JBqxnBmZfDvyL6gZ0+xdSoaGVmhm5kCWDUJZs3YBUNDGnliXuRzww70WHYZWCE6X7onPd28ohyFaUeIrLz73mBWAjSeQ6TsCF3jjo/WzUHwHGa718SBEzzjZAoxoYhzWp3GI3pjBWS6UTyQIEvjfJ1hjp46C8NWNDSaMYT58/S58OqYghVz90Mxf9Onh4kw8L2Y2rghanQbG53kOAI09I/Bf2cjKJNEG2PyDNZqgvdKuedprtURb3iZscEB3wgjmQCrphnL3gSACCCJvmiZGN3WkHXVYI8QTHX47yZ1phlM9QNIV5O1JX5GHGQo9MCmdTDxp3Su/SeaTEPse8yarRImAdYWP/Plo0G5szLK5tdkwWdqHiC+Ds43lKpyPV/+tmc5lU/YPa05/Gd8ktIdgN51KibCeCanQK7uw6PFNMXYaK3mnbNk5/f3+B5Ohzlz5oz78R//cff3/t7fc//qX/2rVsLzj/7RP3I/8zM/437/93+//ZuyLN2nP/1pt3HjRvfFL37RXb582f30T/+0a5wmfud3fuc7c2CT8W0bExAkMhrNd5LnNtcegMT0SWsml8zeDC8GWHBKUvok0o6pH4YFwChEGraJgV0JWmd+Br4Xrx4MmpI2o3ehHyzu6aRN5kf7fke9Rjp53DvIJ7tAlYa5oJHPtLUsNqvYLBvJiYxkDlKXN/wGpOZGhdnt6sYOTTKNAse642NDxI1SRi8DMH6y4wIWgZlCcz1SadWjZfoQYpdJP8X3Ydcgo063vaewwUbxQKBhHtGcCg6QQk0QRTsnLDK40bBU7SoKaMytR2GUh8GWjo9IBPhgIRFjQai/Raz4cE66hCg6ozGyEUCoczyGfUKfoLjkwnqS1EHfD2VYcFCyx9e0khOMNW/NhXXlAIXY9TUeHGMMn41HjNwDjBamFKIBiy4vvKx2buZLN4K+FQSVSFtmp16NGxlBSVmE8U845Oe36lFhWtF4EJJBFvTaHe/TRgNzPP1JbIqQRrL6nwcXMd/By4Bzv65TN3ZPBwtjsmcU5DTSDHzP5afh0/AhJNUo64YsHbBPWFRQEqbHxjmhEGZMzBi8OOy79fmT3pOqY6ibwVNpM2WnZVhmIkUa5zV6KFTHPOMk3W27+CbmnsbeSLYg3d94HrTzLe6vI/7+THduC/qgtJ+DLiWLtpT+ICiyio12b9A/6fcQoy2rg3ISAmR6nMmHkKiGlKuc/ihqAIskPT5rTF8q2KxRphSaHQT/mAijko8UHisVZEyM1S0jKR3t34GBxPTA7Jr/zBL7ufY7RCS1OVJotKZLbs8HWab1w7iHAN4po6zO14VjnjHHZ3huOnIlmrFCelZt8d9zuNHOQ7G1iYB8X58vMH2Mdwl8HujTk0lCUVJtD0qvaJJN6VtnDWejkOs512z6hjSvwbpChtzKWX9tyo0WqDZeQ1vAXAOLrryA/SDITQ8aE+R7WQ7zh3/4hy3o97u/+7suvQe0Nz8/88wz7vDhw27//v3uj//4j93rr7/uTp486bZuvTuH/dZv/VYLlPz6r//6xKPke3xMQJDIGLx9weXpwNUrl4Wj0XZarXN+rQ6af7K7np29HH09F+1s5/agFCRVaQmNqyiVATqffuCxoMZSvT9KdizpCUJDruZ3cMY2xRz9NfbvjFK1C0zslM0wno6Rtu17rAVAM8X4C8iOcC6M/KOlhOO7MeIQ3ZFKACaaEDIGjh2e+nG/yKWIp21/R30vKcygovauxpMPSMcdIW2Im4QSSQWdLieZSTiWwWWh76JgSXA9adDIe6P9Dtg8D66GF2RDW5b7lhRWdoq5Qa8llYFdV1NwsTgHlZWFeft+jFmGuR83iyk6ae3v2LnGBpNUVm4itYAlIGAo4fjvyu5ikWWOH9+zxLkgzVhZNvzOBLUIQDRjfkPYH2O4Fiy4Mawjfg537zwfGZJ29L05yhXW0+TmTtuFDbI/kMKTVIM4IwzJNTGAqdj7eDAdqH1NQh+NMhgzTf+fhe8Q86lZ/BzcT1OnrCyPm2/Oa5Rq5eKBxGSKwWpfWE6f8nPc7d2rw5HREuXLNa9e59ei7GtvmtcUP+DXmd5lRAEjUnx+i18XVwozy4ANlHLACLojPYDpKhkCBebF3nmJvCSIjQQUgmeM92ZMdjMG9yKbtbDKl3ugoQAlXiNqmWgzD4CGIGG9TfypcN8su71xSYxLE5c6zvtj4fXCyigBSPROXQ2amWZXb0dBkOoQDB4R2Uy2RHUq3s5OcDx9So3ECJPrRILzXOC9GVtaHRQpQ2RUJ24vKX6YwGp2Fo0QPJ/cP7S/gqS2RvMpVkzrSKdxbfF8JZgfstfORiUbyZ1hcD/F6NpOahViuNkwysEKGZy0n1nvQCofpHTD7Wvj3l2QJOVcjwkU4x5iI04B8VsP+fm+N+uP+dYeC0hw/svgY8KAAjYTeT+1v0MaF6PHDfChEfFP7A4Ci0wkyyXe20TuTsZ3ZczPz7eSlgUApBmN3KUZDeujAUG+9KUvuSeeeGIRAGnGpz71qfa1L7zwgvv4xz8+uVrfw2MCgkTGcOcGV+VTtps5Jm62nFkb3AxwjLauDBZF7etRMExjLUnhZ1FDfqJFfELaL6iQ9NDQ8opMiBQLWwr5h3ZBuAAkR7CJISKPooigR2fQcRuMkWzD+iggwMWImwvGtpVXrbEqj62QOMkYvZsLm8mBp9HrWVwbdQzfsy2oQydQofrkakATxCqYPkGGR0VAR4q+mI6aHeC7v2M1ifcSg8fYmF9Lp/gkSOsfifabRact4ntRVgWL+NEKGpHgRxxyfjvulTGHxAnKg6g7bn/HwoSnDRuaebBaOnI1ACQjGNWRkj4uwYRgi5E3GQBAGDMERvE7ml/ObbAAhDFf5vsRKMDmUOc+C9BAB443MHKgFmAAeERKM8xkm2u7+tW7z+Fw88oo24FSIZob6saTpo45CrgSBeM0/JSSw75r337OI7vCjA98zKo3BcDF+xUbfHGdvfJ2kJ1WQnvejN6R80GvDRP9KpvlcoPfSPf/69f85//wM/57/vFL/gVP2gSVEoBuFpEZJgdsIZD+5Yv43b5gulj/L33cr3sUyQnNe+MeSF7zhWr+0J5gSkj7mUyowbxq2AGyFldIICHYQhZd/woKS5GQMtWHHWUj/xBAgmzIEgBJH2sWO93uhgBh+A7FPr/RzigHFX+v5C0UTLhWeaQAHq63wEv/yIVgwlB6Gc0CiQI23fKtm4PFW44GDxsfne9A+SNZMij69bo57JUY/cr/buJpW6+GMBBmAAGRw+QE6PHsJQA0RjMoZlFMt58JiTUZL45x0iLbMfsrpMMwIZD3Zr1eDX3hf4P5jmyPGkk3Ko/h/ighO5jnAvfJ3Q9Ng9fQzMvaILkqoOXCgCQ6w+fXArwkAGWWX4Jh9c4NQWlL+5oL/vmsZzYEvz9B1hoJT+3xEIAlaxgM5OqAbwyqiTCvbQWmWDW8v9/MAzG+jXKYRq7CMRgM2v+92/G3/tbfcp/97Gfdb/7mb7p/+A//obt165b7lV/5lfZ3Z8/evdbnzp1zmzfbKPa1a9e24Enzu8n43h4TECQy+uduuDwb2ri9MUVzshGFO1gFLKAzUAd1sjeGoeysMkZWDENr0CcZ/VrDMC571G9wkwsW6S8e2h7cUHFjkV8W7Tcprzwe0k9v3I52QZh3b1ghAFcU8c6wABoQgq77WLyyNXLMAI/qx/0mKLuE64R4vPY4T4KVwMWIm2rS6OUzK27isOkw8ioWbKJRN4gVmBc52CPJEVukFR/wG58pGAqyU98XVkf1jdfDHTN0/IxBqEi5MlC3R2v99+yf9ot8DdChfW8cA4sMRiRmov9ncW1M+wDWEFg07ASR8JhCGyDMnc0qh3HBMbc+D5u0CitjiKLbOPfTsE3ICvQPGCI1xcYa4gVjfGVtfHH4v7fHDbDHvDc3qEg/0uQhc56SMMOh0GIUGz+TYCVgydyOe89VZ5OE18MktKCHhXozgG1AVgJHD+Dj6FlbMA0O+Q1NBeNkmhAr3b4GoJCjAzz3EU89H5xBEtUXAU407wfmQAqGx9iuIOyZKEvIj6K7vANG3pel8MBGvsTcxw50KWAy5+UaHfHq0M1gYZqcteB4DU8rFlklzm3y10gdG+PjlGONoQdV+zkR34MUgITbPhOdR8i6KQ5sD7IaVZpiXo9Y3Ho1ikawNE2aWXtwYcYnpT5aaNcoukyhS6ko2XFftuyV0YfAIGUjaKMUuhg9xrqiiDedc3k+zOD8bYzeKcsTtt0rnpGUDqaCkt4EslVVaCTwH+MUU0Jqy2JWzcnrSJMn8Ypg5wjINK/5igcDE5rI4zMLGGR2mjxouOTYG6VItEnEeHjIBhyZlNxbnLH7QwWMQvtDeuYVYG21v6NROuPSydAT+WCxG8UkwPb8KmOzMceDOdKMuT3rg/M9JZx3Ntoo36l1AjjdGz3K6nifgV3dDuzDaGbKfV8tQQoOf1dE2EkmbEHYTQ/a+HbJWXbssB5Qv/qrv+p+7dd+rfN3zX/73Oc+N/a9GiPU559/3v3e7/1eC4T88i//cmuM+ou/+Ist6MHEpETWiWY0niCh/z4Z31tjAoJERmMu1zBBstVPBmUFjLdrRh8pMgVSTzKwADh5a7QXRwrfh/QcPDW0kDgIymntNxDZJg+2FOPMrs6vDC7A5sFVVsvsraCRGSm/FTSj1Ca3Qw27Fg7/6rXgZrs9HnYowB4hNdZ04tQ8DZ0cLkY8kg5llbRGLj4wWUu3wTcEXintMfT85qZiIXTxRji5R2Q/zLhnJB31qOWTttvTO+nfr1q/Ktgh0lH/iO8O32ZMJdkjkF+0x8noVrAKjLfBYH3cWJUu9r2I18Y6ifiLrCU0Y72zEd9TFlUW5B2ZxL0xuGq7vvNrw2BFxgYNPqcHRkUzRtA+M1ElR3GuTA4Os3Ek8UAibjnI+GD8omrEo6+/SjCUJnNpcK7TbiAlegQEKGtQaUOxgtfNno/B1+5uEKuHbSfNFHZ4PnpXMd9iHr17EDATvYTNMwor+iSQWt0eJ4z+uBaQzpyesjR2Ar30AuB7j8AQcT/6rHl9xmhFgNtGYgFzxvbY6C2Ae4ASTDUU5Eh2rw9HeAKgYVHWDiSdJPDBokmqKZget9eT1SnZTNOH4U8l8zolA6ZIPArjyh3izxExMeRdZxoKiLxsB8BuIzPBmslr01nPAGQZIAgsAp6ndrz4ZtCIM1sB809NTzrqPUoqrJMJ5uiUwP3De+3z+apH0kowoHpgFJDh2B4Dk4jYRYe0pVq9PCgBVlYDvbMIMia1fSazpx4Nszcg23UAwiqYvrffgV1iMHC4h9EGB01HmeRHGTQlJ6M1dj/TgxdMTYbHNNgjwuwxUjQ00wzoivNZwEelGf3z+G5kogAsqTbY78nnwBjPL18TnId7sn4axiT8Qhidawz5hSmbMn0Qe6Xqhr+eKUGkBtB4C513AIY9JPx1Iosh36N8O8ZiJrtaR47nu2Ksru5JAbYTGC1PnwtKkCZjaaPx5VgFVl2MBfILv/AL7id/8ifHvtfu3Xef0ybppfnf+fPn3fLly9v6qEmH2bPnLpA1MzPjvvKVr5jXXr161Y1Gow5DZDK+98YEBLlPOgzZAhU2XQkYBe3v0LlI50bBaCyyLXSDnsE8jEBBPQdwQh7o9OE9wUXXQTNp9KxMSWkPDoUhY2DPYeMpxlNGGkLaM7veYBckIm0xbuJYzIwHB2OBm8WIiwm+T4nXU9rTiW+cXxNk8JSzkLPg8zuaYoBK1PqSvpsJZZbFIDcDFVgRSc9OkNzsGQkNjVFJ55ZN5O3HYA6LX+V3sKGUzgs3tfnNYRh4kajREmAJvREoa7AdfZHg4P0GTF3hJhr+Hu1xkwlhDDcZMVhGfQ5YWPFwaGqpUb50ijfXMJL+VIj5J9NEYrG82ikw5pmQ/fC/K+PEHAM2xQSVKHkxciI5NpOMga8/QoLMrW12Q0cZ0XBVFvz+KqGh7IfmvA2z57N/Z+DSas5V6ZT7L1etVGPxmJOwT8P8pniRRcYI4xvZJWQCiXmGxSuDRcH8Zr+pnrouDBMA4u5vACIg5pLFRqVG0mAYFjCPzh/xWvjioDAPCIgThIbspoeuuZHWjGGZ0FjbpF80Q/+9cJwAk+vX/Tye4Vj0+3D949yvQDWH6Y6j6NbvYuby0xfDZuY02FS52Qm/LiRYG6nlp++FSkpr+EkYhoRhO4gPzoceDyfHAXzr+GDt8LKZhAl39PgCi8Cdtsbe9T6ARwRg8fmUd7WfCWajuZ5k+YC9SRlC+28AQe46JE2b1kU9xmqwNAreU9gDsKNO5mP7b3MAMClFp748Zhsc3CtUYGxksyuCTJjeMStrIIssOebvpwqM1UykKeZcEUijHCXF/uGUZUgUNJ29E57jUk0CxOeYexqABGVxyXV73492bQz6JtHHpZoWJgjW45zSMzKqd8MQGHK79jvgmaCXmnmOZfm8g2SnjMlapQcn+qcB/Hf84xhnlQYBunFGt/X5K1GD/u+L0azTkWTCd/QeDRa/atWSjEg3bNjQ/u+djAVA49/+23/rpqam3Cc+8Yn23x/5yEdaA9RGHrNly93GaGOW2gAwzz3nY5In43tzTECQyMiuz7ksq40TdkpdIJ2zhYnASNUcGyWTZqIfSJdxbpqkODdjTKJKaKSyOYuZpI0bBBGMVEg7g9GDyILAhRN/Cw67WZTcypAG+YTvgun5NHG3SxxjfU0iI8O+iZ2LcYMAD82/lnqdluH+rMCsobaUmuwO4IYNZU5Wynpb2OXHsAmg7pWbVYJakEc1owQdtaKZKQpQeqIotZUb/gE2dCX8UtRYlaarxgQY5pcJZTLqw1EBhOF+qg5Hi7bfDYwNfo4yazgIHPA70+jVMG4EkIklsphjET+iWCJND74u0+cAVOA86wZzGu9NQ2C9HmSCGPPLO6X76R/uu43L59zFWz33h/9r1eketu+N70mT1XHSGiaVEOzoXQ+bANvkoCYJYWUQUMnw83Cr7abmN+DnA9bVPDxi0vV+I9+7YTdmKZM1EFNZn8Oc9JGn7GdeAHCPIqFmXC3Pn7J0tq4NPoclaPwEN9rRD8/lxsiac4UwXiqcpxEAhQElj2C43H2RCyeVnLkSpa5XvA3p3UwG0FFf2A53C3NglafIJ2DG5JDwJDBsbd9vGYAXfp9ViCclUCEsAFIWyawxrCMUrO1XQ1MjhSE7fcUKNAF4b7XHAJlBjSh4k4wh3lv1xrXh+xPzVX0O7E1G2jZ/ttWvX+kVnCc8k+pb4fCZGVJTYg0NSmaakTyEBA9IHgi+jRuUqJExYpoo4hFD4CNhMgiidzsGsPh3ChlyjcYFgatE5L35UZix4pwlZwGuCCCvkpzgvXLWN8zqGdvwotyXcy/XNQJnzeidvh0G6eD1wes0bj/TS9eF/aCkqdN/7URQikb/Ob5C95A1agR6HaUErlTKPgCAugyyduxvv188Qb6X02Ga0UTjfvSjH3UrVqxwf/Inf+L+yT/5J+43fuM33Jp798EnP/lJ99hjj7mf+qmfar1Drly54n7pl37J/ezP/uwkGeZ9MCYgSGQ0NMMq6xtTs2Q7ikx1gId2u6JL9xXIH7DIJ2/b7kIFPWfGuFroqzlZtq/B8ZDqnYhZ1OJ/F4S0hoEeDbpI9+RkffffKCSurw9SD9NdkIlI5yWqOaUfhrBPmGLjXgDYRK0tPFaUesg4zBoxeCZGUDuT7GCiM2hc759+JGxw1n4HdGVIJTVFlkBhkLOkuAeYCsSY5eyqPWa6rvdPrwhuYofiCZJfnwtrz6m1lU15hWKELBXDZCHwweSi5rgh8crw3sb4V+QPJomAm2pSqFGU9MboafOY0z6An/Y18Ebgxs9sDmnOiA58573Z0ReQbinPBzvQKdIWOiNiLsgkDRajCsCSdp2cvhDc4BJ4av8OgDCp1qpLN4MdSMS9Jleue5+Y2ncQ2fVu/w6gFss/ppHQ8FSNLNmJq8DWY9GfojBXE0XegylYeBpvSuYXpToERwgimaj19sv1g/cdKdSMRL/7h9iyw/Ogt2dHOJrzhNCuI/dNRZmHMgQhJUhg8Fi+djRYsPSROKJzygByqxprXgdMPY3CjtHj/CPR0XPO53pKoLuEj0r/jHiKHMezS4Dl6vUoaG4MyA+E2Zv5JTQ+AGC0g6lfV+BjBYYFY3jbv0O32jAkYkM7sXh9Clo+30uBsPK1uPR2KSNq4g7ZrbaEjPQIzy4bB5yH6efRDhTUZmBeZyLeOAZSgmeA8cdkubb/JPjEAhjzenEExj56aLdRQINxUr3sz38ljAJeK7Jp2Jgjs3bciIEjjqk50jBL8Z051Kw/xbpd41qVnPsoVT5j2SvZZr/XSy/6z0yO3w6a1rcD8j138lwQMOP9NC4y2eEeTsCcUxYbgVIyl7l3TQgC3e9z38/j22iM+p0YX/3qV1tvkZs3b7pHHnnE/et//a9bwGNhNN4gf/RHf+R+7ud+zv3gD/5gmx7TyGc+//nPf+cOajK+bWMCgkRGY95Y5T2X0swNG2/tZGXUFUbMcFKYnw2flWgvUrXZRQdVmYBI+36XZoNRugmlGch371CDh1vCiS5nzsW9MmbCLtkEEfIBijfzapHnXBNa4eJx2k25MewkBZlO8dBHd3xHXj0UlBRx0VcdNwsJAh/pY/67lfAXYaRf+zsAQdkNdEDZaUdsmy7G9DkYQt9LRoPbYLsLlBzM7VkXNIg0kgApwGhkNtqyOuofQEo071v+XQ6Gh0bskm1AbwUD5MmiVm+cvu/f1Ts+tPhzIfGmycMz78ywrfm7D/iibZ6/exaGwvAa0YWYLI3+dTBWDmyOypM40gvYuD3l54sS35/3Vvs7mC1mF1BoEtiEplyLMerqCczynKenhDaNojdFYTZuI0+6uXZd64Wibzhy6V/dM8PUDi7muBzPTXSD3ryGUgiMFMULgThjiNweT7gzZ3xqsfFd+A5Buj+LDxSc2ROS1MIiDYVZgRQBA8S1B47nnZR26s3HFDwEKwpIRqwptcwj6NTWmNcJ1vCYO+tKJJEsYadd5uixLMnIMK9RMHDhc171DMdkqxT67PpGinZlGxgmH4o2MjE4UqQAdV7/rQ7cKymLP3i6tMf25qFgYZajyNQUGxNTzMKO0hjEwLI50R4P5Ul4VsyxyDNMZkgCCQ0bB24l1k+R5TGNI10P1g9BNQG1+Bzw/iYDyphiojnQjGzwUBg0xtre3XdhzYAvmhnPPWqYzGZwr4X3rvfuCDYk2mO4FW6QmOQeJs2wkdX87o3DYRYbgHZtsBQRII1AFmWB6h/H+T8GYqh0j0dgABaCVZF7e9xxco7N1NCX700PP763zuuT8Z6M//Af/sN9/2bnzp3uD//wD78rxzMZ394xAUFiJ2b2jsuzylXoNMcM+LSzyFGRyYEFR12xaUDHBYfxsPXDu+1rwAQwRmKgqdaMzoWbfTsuIaKWMXSk0iJerv27rX6jkJHOypjHldPhDZBsxKs9yEo/jmixx20hQPOvFEat7LI6LLga+ZgO6emBDs+e7WEflNb09XKwMKHsKYWuvxT/ANNZw8arwvWku38zejQvw33Xg/O/iQSUkb8CsOahHcFNy2iVpFfQyBI/M4I00e/Gge9mABX6g4iunvrg+fVIAeDHiJTBGJMSBKH8A/cGKbdqDFrQsJTFvfq6Rb42j4UeGjoogbm1bSoswanj711tXxH0ASGIk9TWP8B8ny3YiGO+6VwPAkY1KO1pWBrkdsfBt5TvdQAMLJHtEE5I4ejfSFDOzf1XN3/ZuWtzmas+9mwQTCVglc/i3XZtCnp9tJ8ZAaWoI6dOUYsXzsv5OXTlbkFmuFz8HGCGzUhreiPkZP7B0LIzhGl03//efhDudUZwEigXrymC5SzGWHwpcy7KiOJmHyaGGilOI0qTqPYuGFTjRocJEBjpTnhIHD0Z7W7Xe/F3LyE9QqjvaX99OG6WEgdeD309E25oVM4CUhPRKBuNSU15bWVdoZ9ByYQ6gvBjzN0z7CFqgKY1OuDpdQu8GJnGzTvBhLuYsXqHKYXGCfccjnuwVoKDVKNLl+P3d4QhyOcjfQQeaWDAdpIEmX70wqvBol0lF/xu5nwAjMwYDS0MXkcWMddJ4zUiRtI3b4eNYuHZlo7ghYO5rv1uP+yNoEeRvYWOGs1FepSRbWhinmUeyfHsUjZbbfTPV/+43esNd+F6oKmTE7gAyKsMKPo4Gd8+zDU0vVf5NiOPzXcRr6bFfVw171wc63/fjSaRzqTSvcv3mIzJeDdjAoJERoPQN3KYiosJaochO9PtphqbXXa3dxI0ALtACss5vN+ASDuKt3RefEjYxXhoX9gwlBFoAD3u/hId/dmI3EAy0VNmwWMxNAsD30u6FuyGkgZPUzB3yDJEjHEfvSJoMkpXbjm3JR3hsVnNyk1ROnC+YV0wHs04eZPxI4XlcJ2/HwZYWHlvaERuja4QX2/o6XWcuZB8+ECw0Ocg86H9u+k06EcxXDMVXWCY6JLUNEnF/Q2wyRTQ7eaEKQB18JgZ6dq+H/Zn86vD5p18r7LXHxMXG2aS0LBUB01TGYvLOYHvq2PFUb/Rmd8McEKIIPShMGai9B65XsSZJLwn+HrWTh1j1zAoxOvWv1YEvUb0MyvG7eJey8WolhthPhNJnblP/fotd/aac1vW3HKPPn33vw9X59H7OIHenE7/VX95NMqXn1mvCjvI67nlMdcAehOAtMNNkjxwBfMa5qURUjLyWczxtyzbgV4T1UokwiClS2NHY+lHDpK9cvPqeAxsxHeJHdhOp3rPrvCcD/YGC7MaTDkdlA86yIvUd6pjzrpw/GTlqc8BY9nZxcf3KdbiGqy18aY5PFp43vK9u6LMJh53hSZC8ggSxPgM0UelZRmi0DRr9p1oFLD53iU8b85fXJoJI5KMckoRuU6KbxOZUgSs6ImR8G/kPJnrRhkU2CMEUTogBFkBBH0p95NYeQdmi2Gz8t4QvxWyuAhE1ZAP0otmuM7uFXOs+xliWI25vbCUDBOByTtoMlGup1Jb7j2ZxtXHGlFLEiD3l2SH1ZiHSiQUUurVvveJK2FmLSNqlX1CgAR71/JV/50zRmCLRNwcP84HGadzD1lwgR4hKY2Dca9Wl64ETYfb39Gbj/5rlOQqi5B+QDS8JlNax8K9X8VBpPfl+B6Xw0zGgz0mIEhkNJvMNC1ctWl1EETIz4kJIswjkyFABCRe0Bywd02Mr1gIsBN2u47GXPZIkeRFZWwYjpna97vHkwW9SxwWAhNPK3FvCYyjONipSFRPi40TtamkqhczFjUvmQzCmEbG7WEzw47I3Tf053P0A967JWG0pfoXgE1jAB6a26I7MQJo0Iyp0wBy0FHoHz4XlvAIg6bHTjVopslhvzGpH0Lh0f4Hfxf0UHCQ/UETyGYUMEVkPGrV88fSv2ZfM8Jr2OGv+ixm/d/nMNhsf0dDQ5pPJuGiuxlzG/xnDpACY9gaLEpu289kIgqLeL4+G8ZXUpP0QpwB6TQjMf/kObiN4rh3C9cJEb/ta/BPHifTWTg00SZmEDYuipfXoMY+mN+z3NyLAze4BwgE9TB33VmpCBONIOUzk26KjAI3fM3ceiRDLYN/j0YJE1zG4WSURNHrQwxk82tI6kICWAHPHXYv288hE4Qxw/TEwHxf7rZdRiPBhA8VZTdjpS30XQK7LLt4Pewh0pwDFGBGdsRNvRSjxWHvtRQDAJIafhzoMnfYDyzg2c2F3GHcqOhnIR1YM8DEYHGdwedIE0woWUwpCWLkJY285fwabyMM7hNy8ZciS4NJRCYxi341rYfOfPA12R5IW2Yhz0WqUvt3SBQr4MlF010dxVZfwKWQ59bwPyMbyf2AB1qaUTJtDQBPDYlfosxUxFZnNP+EpMh04cW8Mzor4v4sLgtwsoSRwqS0z1Sp5njOQF6D/VGNQjuZsbIfSoIM2IP9CFOAMjHu5/xvgGKm+olkg2yg6pCXNiarlgclOGqwXGK+Y4ODSWWGhagsEa7nZHjgftCGVwFAm4Ah0+Y6zQ40cuoMe7A78MzDPpjXogPOYh/KhL1itQXamYQ3dRbvDf8bZZwsALhF/X2YIDMZk/EdGhMQJDKKBvzIp2z2OjZ6w7/9wWj3jV1KE+GJYrBaaReMwTm/MBUoqI2BnnSahwf8JNk/DK3xDjjVA+lnwdt+5sFzYWO7ASQ4ZH403+EoNIvo3FQ7PCCTXLkZ3SxTjsKNJz8zFxCDKTTGmRzdUHP8cFzX69ZDt8MYrgoIMjqASDnIN8jM6Z3xHaoUyQt3DwILMDYaad93Aiuh289vGAS9JvoohIqnfVEzRMJEMwZXfAF2cwcpq4wqta9hUklS9IMFIKUt7fcBe4QdzMG1cFRqjmSVuwMbshvwykCBMVyTRzdxw5URsIUxsCJT4TlgrK+Jh5Xo2BwABX/Xw+cQW8ilM8o5YeWx+aBMg+dSC3KHDWI2nwTBER6jJtQYsCfGDpBN4eAapEpgX+S4HxVQ4XvHmCRTl6RoxvlMAT61wEUgrUZZNvxujEbmddINNm+WjKmGcg71sxfG/GaYEPZRWOLcZHNJFDAkuDN8fFPw+7Nj24z+SV8wjX7Mx+0lSNfJz4thHp+jmVVBVsr8Dl8Y9i9LYY4C1rFzjmhKFrZjTaa3zwTnOzIiuutnFQRrkg9YVkZ69HQ4PYMF01nxl+L6gbWowHyf4dwOH7cGzfRk6p1AMgbSvGIMFe3cU/JIedRws5XDEDDrX83DrJCL9h4oN/vrO3UMEZwAeOg30xfJRvGUb6TkkGOWAPxYyClTlebs1SN7wmbeX/6meX3G9D0wRimNMbKO5u+QWORoRkpTSUo5RA4V9XeANMSAf9K5JwOXqT5DsC3yazK/bPJATEIPIsirnIAY9Q897Y8Z9y33hzRnn9tpwT/uHfsXKaOuo/HDbjmYJU/6fUdy2LN8MhrI4u+bUW7yxf2ySzD0XeH3JqVE3GZgfhmJFgBHmkd3DEeXwYSYawaZoOrZx6YGQBVKxJNXDgXZO+3vYGpMlg7ZQEyg0RQayhEZQ66yOLdoUJw+UMyH7/V0mMl4sMcEBLlPdnV2E10ZeFUMLlrjqRKUbNPxQ2FIJsjgot14mog+xDcyuz1V7Tac72OO+JwbFAAfYWHtvQWd5QxAFFmMR+gk9Y7g2K6HDVg1eq9GF8F0PoCmE/TopMBgo8W/44KTkCquHiPUk37VG5s6jQgE2p+BWZNhr0lTMNKkO0kp85HuBgqc9r1nUUiAcZNewwZ7md/c9ERiMFzl78E1f+2vwe2ntgcLjPY9rsPPgWALNnGZGLgSRDByFhSg4xallIDGGgGPAuBhewyUoCyBrTG/ViRRoC+MVoSlQvTdaI9tFeQ5OAXFdLirpLIhSnpKgFL8HD1PxtMDn0kwk0X/3Ho7hRNDGeJ7xiRAWoQT+DAsFRxXLQyLEbp8ZNMMroAtsUJYbJD0jFbl0XPYny2C9O4cbLUR3nvZGZgQjzH05SCQRwZWIUA1C4kBgQNS4sVbYQrmtuYz8Xfl8jwsn2mLQcTFvhruSKtEwKFTmv7li/4zkXoy9U3f2a2QWtYeDyKQc/omkbm3TeQsaBbkGcwFX/deTemjKBilg5tf8oXNCCBACilEKpGqFUy/ExRg5SEkgFHW0Ay+B0EEAB8pippk7VTUQynmUWIMZMWYk9GxyXbfOBjO+O+cSYTn/C5fNPeu+/1IBiPRaoswHMhKw/dMrsEM/Bmk24hPQ++4f+8CbAsC7yqtpLyz2rs97CNCXx1hzFTrVoTnGzwrvDbKdOK1IaCQIEqY0fOhCOXFv3vraNADoxnZ/j1hkA3sDT53qXT0+UxTGsK9lvGIk3Qs+o0wdpvmmx0DdLISd68OSlgTkQX2jvl7IOXzug0MZBynSc8SptLtp2eWJBt18AhbdtwDJ8N9/jP7pyGPgsdae8xI2Lv9qP9MRqyzkaUNHwMQ8b5FQmB9wqYvMsrWsLDBIuuAqTgH+bWbwXtNGSf+AKoHstb6lt9jMibjXYwJCHIfnVr9FjaLz6IY/5LtYlSfeD5aaC7+DYoHjdg1RmSgNZIeN5bqHNnomY2auE1nL8KJmzRVdP9Kid7rFTuCBmHmuOjgLq93x0BV5mfSE0RGch30TRiWmihcLDgVNs7t59BcTyIT/Wvi3bsY1ZvfsxJNNt3IKQ8yvh9Y2PW+yU9cDG5ie+euR/1W5j+yJ0ixX3bsWtSzoA96Nrsyy1/xANftx+1x9mBESflAdgc/o95UCc6dzWGWyhTAlrkNsrkBiyot07AxKoCT/I5dFPt4b0uTTeMmp6ZD5H+eulIGX6+MggpgRwmp0DRfL8ALC3JKU2jaSuBDCxFDe75VBV/Pc0HJSft6bmrx3UzXWT7TeKRgzK/rhVN0Op8ZNtfle4yT4JjzDBaEAid8D7KWeA/P8d6UzXoKe9a5TdNBMFKPv0BnknIxfSYWxmi9lSX0ERfLNI30Aua4zXEduSl0cW1vP+fnij6NZZtjOwtj7QtYf5gMIlp+/h2NH7Nd24NdVqO9bw5tAyRFKPQrGHsz/rj9nPWrg34K2dRUVAKawEeKxolLYVi277fRf2YFOUd+BE6FTF0RQDzBWlQTOCIIM8Y4skCzJdsJNpFIaHIU/sNHd4STwlBYawGbUlqBNWJ6Niz10iI+hdE49zDGiHStGMAC7Of6VW1YHT233F9Up5AM8tiBsL/IJstAql4LF5omFhemmO33OQgTdowc5rQm3hzMh/YY3vINior+bR9+yn/+efFigyEsn7z+Qb+fKXf5dboAsNq+N1607BhS/SKS5mbUMGetse+i8W+xF6kvIllkKtzyE0uTsvEe4LNrZMQAFVUeNTzg76/BJT9fzG/w12AA2a8e52jdsqCnCWOrqzelSbdhfXCvyH2fgtsl7olqMzyDYJRrYpab390z+E0bimLYtmkyJmMy3uGYgCCR0WxE0mxkDLZYmNZCiXN/8vX7nuweFpUKC14zklPYbL4MJ3AuRNIJqxG3R0f9FIsxnckToddRW1kjH51GYozEbf8Opm00POOmxRgyVpLSgSz5HCAI6cRKcayXg4YOUIff07xeOjdcZHJSoGksK+765t907ufmn0735tXNbQNK+QX/nRM6swsVl4wXxhRn+P7seGoHeMWfAlijGRy6Val0F3h1THoDFunp/yaxddyg4p7MnvXPRHb6cjgSr9kQHRuFu3f4ecVhS1uuDx4Jdl5IH022zYTNDVvWzaVgZ3Nw5Ep4s93sr2eWBbtF82vCMhFlSBD4YCeuMOCCeYlhfJBV0b82CsYP04hU2R/LT88Hqetz6/vRz6xohnrdX+chPD1Gy+1BT10ugkASgQ/dIJsUGdKThaq8ACwZk1gFn8AAMiCE0EpYAM6vgccMzy2YG2poyDjoPgv16V6Q1TEulaeEJIr3lpolx9huNKXudMGQMJOAycG/I0MlBQW9/UyYpuaM1mSMegQYbgcKO8o/2Fnt0OAhuahWISXjLNMr7H1bHT4WTJGhJ0giMa70OCkX6eXOZY/sD6Z0MQ2tfT2AJMo2q+0AJI6jYGveA1HRxmDy1OUgWKQJKDm9pzauCPvFiDluAnkqCzDT3cbn0KS8PTZKlwB28L7VZzKjXwhZCbhvC8QK52pqyf0N1q/0UjhKuCODzQE4vn4o2PwZZwZroqHHJBGZa8iGC6U2MBfWWN4asrIMz6oxWld2VxFhsW0F4HjGPyvLLgvDku/HdBck3Ok8Un3zzbBUCYBAfhwgoURW5/DRINNpHDuvj2MwLOTpMHiZSKKN8XGi3xfm/rmNdu6h5xnnaO6BKP/LlAUHqQ6j37kuJCK3pmePiUHn20Yi5qsHzBNkIoeZjPdyTECQ2Ggm5ywxbIV61YpgUdaJZItErZXXQO19SXLcQaU0EhJsFEqRieQANZJVK8NoNDWGwsqoAKKkcKpnx7A6YZkTKQpyEwfJJAVGRsLJW4eJxGPRLkZ/Jd3QyX6BeRmNUc1mSmLoqiVsptqBxTXh5h/sF1OA8/PbD6qCx1OhE8UYQe3KGPOzXbgfIK1R7Tk7SclL0KaiQEgesRRkghXFhpVBvXbH6I/pQVioubAzTlMd3CkjKtEpp1Gf2ay3Pi+bo7T4xeMHwJOA+t9+Js5VioQIB7q8atyXHQQwCeBlsET9/3JStblx48aZ17l9c8bgjIISsx4TBYQevpyxlwI+LYypk3YTxU5levlGcB4bHNgZlL61x4b0isHZG0EgqrPZPXs9eG6KDRL5e29P2hcjaRP7DPkG2XZqjksfkeXH/XEON8CpH94+BD06RrGgjvcuoOg/Mxc1iyQQZAxYKZcThgWLFNPtZyT6WzJHwxOD8j8TKc45DT4PmhRW7ZoJSjPNuiLmrCYN5Yi/b9M9oIRrNDRlRCzGOHcM7X3LWFnGVKbrAVxgzdY1kIku7g7mLiQ3ZNdFgkP2A+a4CmszDcf1XJmUCRSWI9z3ZMJolLph6fC9pMFRYN3Ocd6NYSh8uJiao4MGjSnmvlquh2OiGgH+iO/GWCANI0XCEKNax0YzY+Q7t8RZHUio4bWhD4iyR8vTMGDFc8iinw0WTTUio4oNG5rBMhJXG06U95aQxqTwaGNTqP0csjciTJYOUxh7PRMLTHYYRirNJ+7bBlc2BYGb9Lysn3xeaU6La0D/IcNOaxuVkD5hf9kb+XPb09uEfkTwsyMIYhMKJRThql+DK8gxGXns9ls5jEPTkdczuXI9mMbVfreF+aIaOhexsnlfjkk6zGS8h2MCgkRGQ9dNm8mRyDTMtupHrRSlhP683gKdJ9NQROfJQW2liUrDYtbR0GJhSvM8+HcFjiVHp6AZGTdHpAbXZRj0aAbAFm6oCPCYTknP3mKUsHADYf4GaHozqpPwOKE2FaatPLeVgAs5U1iw+SdDghtCHcVZgEXoRjKdJSGVtzmGtTi2FSj6UbD1xCyS563c4jeUNbsToIjmmb0Ha1DMy2c8qyRFQpDGflabcK7IesI9dPvRTdFIuXqPL/JG2ExM4TzPSRcopeQCz80ImxuVIiSVL7Tzm6Pg68tndgclO+3vPgjmFokHOBY1paQx2vzmDUHfiDqz9yrHvBqwLbxmG8AJTbiFCW86hOHnw96IuWBnEckPzRhcwH0IIKlGV2q0ZmU8rpa6/LXLg53hWrpvTLYaolPN85lfFXCAG3HEcfZO203x1Km7RV/52lvROM0UxRejQmvIJe6+9/lgFzz/xo0g807nBJpvEtgzLLStVjpGMJGXugeGBI9lXLwqn4hx4BsL8qWMjtEf1h8+H+OkmW4Jx1bhmhuQt/k3C0XQ3Y20E4XluGEiK8OKzfEDxWAuBWxyGhGvUmjGit5xiQ9BBpOsi3wm2B0268U9qvzCSLnu4hyWs5HUMxlk8DApzQFQSGlY2gwBf0Lng/eGicQVUIWpdCUAnc59w/0Ink9+T2XWmNdjPec9SNBcr2cNLxqzh+Gcwn2ONJ8SgkdsEp0ac7MChE+w/pk9If9G1x7IiMj4pOQkpWltM3B/Z2jEMBmrBgCgzz2BG8ppuJYYRlsbCoDjIZDH6FjsU8pj1nCUzbQE+8Dkwmx0f1h94w3/1lvhZ/Tq8fCcIBG5CRlqYAOlMPetJJq5wt9l3JMBpOvMI/fAxActHWbCBJmM93JMQJDIaIrtxlxs+MSuoHGkFkzsqBMZ5sJKDaxG0pGikP3FG2GdqJhvJg/5AqxEh8o4pqOD7HTTo/rahUPBe6XOLhhGvrAHCSopqKTUNaoxKl3buWliTKPQs1PG56IYMt4jWHB0c0YJTxl5vXbCjCQHHSZKMRxiaGuyKNoPgsElQS109ZQi2j9d3d/oCQWwpgiQCkrD0XI5NndqDgnzR3br59f5Ym7qgj2f8xuhsQbNlJ4HLIY1AaXU2I3A57tUvBXg9zGEn0QsVcKttgUsI/p4DihToe+HDiorRtODoD9GJ8HERM/CUwNSEPUESWAuS+YB/T1IQ1cfk9HeMPtjnDSF5yBJcT0hu+HxF5ttIULGBb1DmJagXhfpR70pc34RwEXDVvBT6SKbJBMDwwKMDRPRC/aJMbVuzvVDHvTNbkB+sR7JB2B/GClG8/o9W4LghjFeFqCbJpkEZaqIvMsUn2ryuR2FCCUfkAE0I4UszEjX1sPcD1R3pWOz4CggXyRYktwWtgLAm2gBCCmiiS2V15tYXbAAWPTffREKUIBSZBjkaoyK4yFbgWwDU2hvkC4+1r+cPlS4HiVBAxmmu8vOO9ZpbQ3wO6TP+oh3B18YNjTaAbZZDVNHM8WRhUDz8ZZRBR+THNfjPB5OenrBs0D9ENzJM/f3MWu+91u4bmAupAdgRAr/hnZc9Oc6wZoZleDI/UDZK9kGZm+AAv7uQVRhXzKMYq9/7nONRWbUM/1KAOgkj1lwvcCezqTV4FiK3ZujfkgE1M1a9IJnnxaSnMORE1Sh7xINcA/YczvEtap2Q5IMEEc9e3JGd3OOgIyY+0YC4B2A6SyMg3diTnzVMmHSZ/29Ur3+dhh44RA2kTl+3DcEx43/nbDYYuCyysInYzIm49s/JiBIZDSa5SSfcgNEW7GAp66zGXOPYYNa+QUwu1MGN+tqoEdjtIT0OFAkTaZ7+x/8jylouwk2GgW6uZXoEh2y3zkpl1j0qzFO1Gbzf/pCmMkhTBAHij6j7wx1v1oRlYmYzgd00JRC6Ga5QrfAaGBBxexIPiiP2YiFFsyeipITYczUkL1U0L9zQ1RCFqJO5xnYG+U6JAeA7ZEUGiOLjU4PhTpMIMu1FhyYOgNgjSAENpRzM7aAzVj04p6m0zwBCW5OdYNGiYIBEToxrPy7MCDAlBP+TTP6iCnkMfOZ7MTO8XwQ1KIZKwAeen3osZkY1+Vp1GSUAE2O78PXGLGzdPxyGMgaY1ecZ/OdxSOE343fh8epqUS3N/XCEbvrQOOXxIsh7sPh2vWWZXSiW4zN7w5ryvV46F1Sr+tHtd9z21cH2TOMs652Wao1/TpKJGs5yLiKtfaZTtDZNADRM48EwXUnhqHsNNPDKau3RP0LkmuQTOzYEvRWqB/ZF020cZd9IZL34bMT0a7rILhg0hJofq0MQawZLRC28DP9TejNFKCLh9alCq9v30N8RRYHYlwLmJbnABDa18cYHiiYNIGEPhQGbEEBx9S0hPIojYgfbQkmwqQn7LmgjIlJRCkYYSlkTzXSUNpjwP3hjnlwYP6DDwdZrs3o8/pCWkLJgkkwWu+lAAEAAElEQVTHkeuZsrhGTHN6BoxNLUC57sKHoyLwwbVdC30CQTCnL15+I76fYIQ0kugqyn7A0i2ft9JMRrSSuUYpSP1V30jq7KnQMKrA6mNCnZrWEpzlelw/5q9zjvuhHVhzY3K17AokYWBOtu+Hz6SUjya8TKFrRg8SUAemMdN+jCk0JX7tnsqfj3KHB15SMCyrj1hAvXcFMqTnMS9DekYQRv3GHAFgGuICNDeNSdmH5mBxc07jXMHzXtdD55bmM/v+GJN0mMl4D8cEBImNr77WrLhu7seeXfxPU8cxKUvE3+AcIv64EcaC0cdmuxPXSJ9AvKaESZzKaVLGs4EJwU6DMbbTQXQabug0LK0gBelocimhQdxfBRMpHYYGCK10vRLdLqTBdDYxBCcKuwDGRkaXbS70ZHVoxv1JdNmwANZknMA0tobkpR2nzgWptexEMRpNj4HmhBmYMYZKKoMGh8uOoUME9smyb9qi4NazTA6ow/etpImwiKb+nVKbeRSg+nrOOjlAQhM9K4AC0zwKYZaEzDKVfcLvRuYDSSkKDhCQYKxvQU8U4hEC3HDMrcuCrA4FXmLxgUx34agl75aMFw6CGJ00Fxw3366HTjsTWJR90r9RLSEKWYoXsk/wnZu429//x8vd6v5Nd31umfvnf3z3GIaJxBriNbxOU+duRzfYTNagdwhBPuMj0gHvcA2P+rl3tHdzXG4GdhSPkwkFFZhq6TnLPjFsAZooPurntFzp/qSEn4J5NhltM2uDXgRqEJwcOhEsBiuYit79ZR5eI3APGSaMJou8cjhs5oo1Rj1uErD3sh14DZ/D/RbcTlhkQcJJ40IWnMNtlrFCnxgjJ0FhmkI61/EAwnkyP3MtFV8YhxSaijGqAMxMp1u+ZwaQjWaTLFrLrWCYNIf2smdlFE/7wm5w9FLYv0jYD8nXPAiRsegHw6PEPdiObR7Uyc5BarsLTaXjVjJSroNkD2CRSWSjyesGew/VX38lDNhxCHCWIpHEsEfICgGoVuEztEnFuSP54kvx6F6k7XAPQmYSE0PUU8vsV7nGUJoq3kBsrBkZMQAR438jgDzn2/kd/jr10SzJEF2rAEOeAcA9i8bcjAcPU6Qgtcezb1sQ+KBks3fJ7i+ZCJPPwhtoGebRWezVxFzepLjAxyTDvFwDYGv/zX+QBY2RCFN7AXQtJ3KY7rmaJOROxrscExAkMtKnH3ZpNuXyP/WpL5yqlFbJjWP/CCZmorygvKoe1nSVQKlLjt6IO5vzGLgRJtVujD6c9GYukgk2DanoH6nrZtc0hU7UmEhpdCw7MegGJlgICtBnm5HDjbtGt4d0Q3M9bttN/XC3P5/Zf3s52GXN5DXZ7p1hqjf+hpF09VftRocdgWwLOmH4m0RiDemTYMy/sNFI0J3RWN8RutPcUGWkdyO+shlT//Ub/jU0a8Q1rMBEab8bGDTGKBYbzwELSCnSenPha5hRry7PV73Sb1Smrt4IFgzGaJcSJNEkJ7jval4bATa5qeOm0kRevo1OtSQM1ZDNJAAj2cHVQtsAnfwdY31RQI5E9jN9EMX5dsig4J2ikihKfQjqEKBKsG80Rp4SF2sALzJhrsfZQAQX3Mi5A5tTt3G5cxdu54tRyWTStMdDryaCLWunokBYjvdg2g4jEmPn/O77+b8rH9oSZPEZ9lD7fv675ZCrGWYTzmctBpe56Y6DCQJ/JzVBNB1x0NXNHI/npkAh2X7msfPh+YKFPs1HpYNpwO3rkO0AHEnh+dAe5xP7wh5G8KCgF0H7OTwGgk+Yy5NagHKCIACYEgJ+YOj1LwhQzRQVmjhGTIw77A/66YA5kXBOFLCHZo811yn6c4gnFf0cCLDQQJYyLHUvqlGEcy0xxZwU2tlBD5iVEb+vGlKhVGRDNNc18axgOnXKRcbv4jwbM3Xsp1IxczVHiWvA96IBrcoUmL7HuYNsBYWIzTq/3INPKdlQ4iFR0HiYnhZvAKwi+Cgmp/k+FOpM1IHvUS17tYQsKBT3nAeM94qMPkDT9K9OBaVXBCCa0bsG4OX4meB8WcEMNsF90r43GSdg4HKO7Ugzh2GQ0MyR8CNS+SF9emiGyjmuk1JFRhNBLdzPS/VgmozJmIx3PyYgSGQ0ZklV0jMo72grFmZxcDcdPGxcaRxlOjoiTSk+4D8n+YtvhOO4xGCrhA8Fky16byPulp162ZiM1i8LepxUU6DkXxGk/sefX/y5f5GsEP9jTUPBbVYzm4IxUoKay00sabHt+2FxL5/cFyxeSM3V7gLRfWPAB1MyFskd4INRwNg4msQPobyO4KdAaQivU0GDzOa6zfj7q4wUfHx9dttKstI3/EJdIh0lBU32zl5bvEzjXM/tWBM0y2Snvj2GXf6aJoibHSHppXfZX7PRJkloYFeJEaKMauVmSICHFN463HiS8ZKIdKzaijhlGsBC4qCeO/SSYQFJGnn50I44Uwud2mKP79RmSFfRjp0xyQQbyNzf8LPIxbeCjCSCGxnkKP03bPSeoaXz2sCgksaqCtwsOwr/AUjUCG4wwaUZg3PYcKuJ3737IB0WbsXXT3bNMtUwEwksfcof2GlvBgyS+exWPcyDADRqyPDUk8PEazMlSiLFM3hFMEbVgGc8TvWgwOBrHDvqkqZFAJF0dcZ5JmQrSIQnmSSGoYB7MCZFad+biS6gp5v7hizG9rzj+qLgYad6HKDvwAoxDYY0i5qJE1x3uE7pzTjbjt4fZLywaKa5bicVjkaYPM+Ikk+UIchrgPW0pGSD3WhNZ+Eg8INiLpP7ln4KKY3W8Zk6CDbw3JpkDwJkkQ647ltMdLsA/zTjpHdYAgC6ACCig0WrYXXQy0w78twb4FnjnMDX0xeo418D6RXPsz7TPE4W8enrc0FwQROKSgLNYABlkFFVlDO1oMhs2H8NYK7xPNKEPRpJY3+UIGUqlTmWqyGfI15nY14t6U/VWwAkCIzCP68nkkMHuZWZ45D+xMFmUTNqPlMEOSn54zMsDSzOSd+XY5IOMxnv4ZiAIJFR/sjTrSdIhmKud/FmlM5r9LlEk28iAhQO1XcOSLQXCvdsAxI3oEvPhcZHE78KRoHlDjAfOBHLZrcCkDNcNx1OpYDBZTMGX/a68NGz3sSvdwVdLRrWXbDgQgmjPaNzZY49mSTtG6JoPYJNLIsHaHvZyWtGsQbo/DeBrpN9I8wcbipjm+9yr9849gQUM8Zy6FSPlgO40eIDZovpM74Td2cbUlOwAaEpaTNu/6AHa3o3kDLC6FoxTKuWoROkXex7Y27zVNx3gu8FiUEf9NFi28qobIWSCZp3zm2Vohcbj/5VAEk4n8NV/ufBFekaA+QbrgeTAh4S01Lcz8EAdLgChohz/vtMn4VUCdKH9vWblgW/5/y61UFPFDVnnb4wCp7bCsdVp2uj14bgG3+e/5A13+Q9ZaJbUYDyvu1L8k6NuYcdu95VgDXo7jej2LQq2KVr4ncXQL8GqFgwk64F0KjAXsjPXgtL/ERWwA4sDSZ75yAZZKddjaTRDTWmeZTSqZSBLAB268GwMJ4PkrzDopsyERpE6zAdXRbNTPBikaRpPyxmyEBiN5pMNYmCrxiPTeCeILx4ahVSDIWGKcTUzBqFCDuopKS3xwYQu5Lo09AwBp9tMQpmDhgfRgKkMa485jHgUSwBpSat/tQoWGizG90eN4E5SF3JxCjJFgF7qP0d/QzAcjSeWvp8oUNP804jZ2VDQxoPBjxCd7w4DNBBDGAZ2Uvfhuqtt4P3KtNDOgAHClONqOUwewXMS2SF1EyuU6N2fG9KzIqtmMuVTQTQkk2e9DEYzbIpI9emBhiY3pC48QjT2KS70JiUTF2cvxLNkfYYsOZQdlQDrEl2z0QlOPXxU8G9oknQwpzWOWYY15O90klpnML+Bt8zpzEr5sR6kximAmRjo7Eck2ZlQEtIzg1TWsYCaNlKP+L44ftuTNJhJuO9HBMQJDIGZ6+7PJu3VH5SVlfajUqGDS7d6dkhYsRudmdtdMEwxnIw2FSDyQTu9INZdD7oNE8EXpgg7G7THJAGfjVo9KoP7r8JjTo0ydQgM11A0w8qmrRdBj19o+h2YRLGzktF01eaiorBVw/HU5EhQeokOkfte9xEhwUUYLrjZwDFSmTKdww7YaA6eBwyGTUiw7kpwEIwhS3NxoRFMPX/+6r/nj/yjD8WFJlTZ4SWGUk8YjG8/LDtvs1vWRVmjID6b8zjZOR3WHS7oExDfUTmNg7CRTOAhwzFPJlJHfAHgATNRzNqoJvvsx7GnrfDYE0KRpcmF1CnOkLqC/1JaCbbHhp8UQhKjZiIg6+iMhECTPQvMGa04rcyvxrx2vhuFWVDwMcK8c9h2g0BldFOFGK1GJvi+chvIXlm07T7/75QuubuL+rCDTetDIJFNUChpFod/J7qz5GCWTO/CsyUjWJAd29Mv3IqajZpwAHIZMgkacYQQFj/Qpg5Z9IeVEZwwG+WS5g9cmiyB6n0KaRjJpnjBtarnRKBfWEq+D1TFMoEPXRwI58D0GahnslaZoxRMfdRAqP+VNEoWxT9Ko3McH4T0tBJ92cBvkaTkO6ECxnILEoBOlgYEeBIdu8Im1UqMwrrJP0YKs7dIqExkdaQTDANJScjQZgjOej6FYAPw0SE0XD7GjJGKP3ltYVEQCWoFUC2dAvuSZqzM12u7bz3g/suZePE2Cc1GkvV/Nx9Y33vfmgSjbReGDkMW4cHLBOkdwH3FKQ2+SHMNyq3RrJThihbxpUnZRH1DjMsR4KcuM5qDm/AWQKQaNLxmczEF437u/qH/X7EwRw+uyzzCNko9POB8T6NjxXQqMBENOlkGyARB6DfjP5lNFywZmRvYh9NXzdh6xmmMD4z4Twm8lx+TzNf4r20+Zbdm5fqauicDTOcjMmYjHc5JiBIZDRJLFU2ZbLTaeymBWxJiiGK5vqwn0gTLIwsFtrfUU9KpPwWCjPRs9IgqliJHPj1kMkAgc808oubvY2IpMPGkwZlHX0uYy7Pz4bpomo2ho1PfRjdq327ok7aXJwrfLema7z484nz4WKlXYDgV/L60eBGnp0zZZaUpFqj+8YNaX7K6jdLmLxVzzwcNN8sVtqNWv/rHizJcnxOjiKNXgjUt8vmoKSzOxbj4QaJpINMgkW70dAKG4jABzv/lM2kV5EwsVrkTXhNuSxMPc/P2Q7PFKKa08vYLPch4UEBPDhoC5ERfGFMOgwTVCj5aJr4L/j7c/5x34EcnJkNbroIqjVj+pg/hho6bt43JVgU6sNB5lc5tSYIohBcaT/zQrjLl+EZKFbIJvB6EWR5DNdA1ofzlMNwrhkVvVSSCDgirCVuRE2SUOXc//T7c64hd2xZM+ee3H33Gc/k2hDU4nlPIyyn9j1iRn8Am3onLkWLl/6xi8GkFgcQxBgVNq+5gtQupGwMn/WARI/YHYBtBdZM8gC6sUzPav8ODJYScjUCdoZGLjU3ZZ+9I5hXaST9LgaNI/ncNKOGySbTTJgwkeyVuFt8bxPlS68LJJO0/8bPxQnIHx7COoXGR37YskWqHZvDkiZ0jdUzgCBIgnUlBnxoWg+B6k6CR2TUiB5N9oE9QT8lSk5UskFmJSPvWfCpIa+wSRZGccSyGhaPS0BKmttSwsL7ucPQEO+LEOvp3Qwjs4EUpT0G7gcicdJkZWS3xIdkjDwnFiWcIrGJspulDoJCFSWc3zwUBIF0GNYVj5NgDSRU7WfyZ8oPIQvUez3lvgXphclGf55LsOBUBpacxz5sBxpziOUlo7t9PzQ0uY+tt/lnPV/lQajqqDX+NxHnuFcTAfmWIlerTsUZSIvy7XL+wQJBmoaIsqLfzXtMxmS8izEBQSIjnb3j0qyypkegUCvSTrpfJMjB0JlpVKiDIADppzRtav8Np/Q+dP0VugsmxlaKNBN1BnSejBXqyDuLMzoX3BzyPOlnmvd72huzOnwX9ddgx4tRgMV+UG6pI5dOGqVLlBolj/uNb3JNNpegDXOhZeejBtBRApBq349AATq4mXw3DtLNixlE34H+yk63Gnz1YOLXMJmCm3psBtrjRAFawrehADNmQO+XZq+LznmGgriEDwo7TKPVUhSwoL6NQpldHdE0j1aiY4VNB5Nz5jeAqr5JDNPg/ZGsgBaelN2XbTE5/MGn/O8IXsFF33TvKMVozsclvymu920NAkz07VBQg/U02UA8FpX98Nz2Lt8Kuu6rjIpSnfQ1dI0/7MG7wenr0YhA3pNTRy6Hu5TSwc1hdFuuGkTBYXcvurP8AZuWYApI3CvpNRR5b3j5S/t36MIXOx4JMqBGO/wz3XvBFisVunwpOtD5GDNVFvQ1QVd85sJ3bI9L6NDs8HPzXfGZ1gIW5zolUwteMpQfVphrmtE/ejEsraShIlkUYwozs6lnwYpCqP0VAJqM6xy+ZwVZRMcbAAyHms+dmlqiEZFvnQkbJ8Nwtd5sGwcV43MB6qgZauw4TUcZNHyyNI0hpbBUaoBXCaWmYqjL44we1xi2A4+ZTZ3y9cPRWPhEzG4XX4+/S7D+ds4ZpDJGWkL2jTRyKEMyHXUwF0qYwWYzVmobk73wmaL5d0d6RXkvZTJYowrxQ+LKxtdQ9lQBoGvHo36vkp4F8A6mFWVwei3YmMowrSV4PZle7WvAaDL+MWye0QdFrg3Bv9FTng3Uh3eZmn9y9jfPF5pvvLYqAzNyGIDODmlaJQBCBT4Mwy8SCW6Ye+3ecfb+sd000BWZXf02wB4mEclaUN6b/x+0dJiJJ8hkvJdjAoLERrMgNGvdR7yZaQ20UWl4ZpGA3psdYHcCfhbSCSthKskJ0iQ5SJfRRK9ig59Sy0hHffqDiNY2I4gCxomaqaZA2hl3l7wFxss2MDHUAR6FQPKSX2QK6FFVx00XfGPe9aVvBqUk6UXpArEAg1EfWSH1rq1xxgoSRNKbfhNaQ1ub6DFTn4z/nB4+GexutO/HzSYKq/zijSBjh9IJNSBNKYUA4Na7JF0QbAgon0hx22hsZwYD0mIZfDgueUBiuGNtMIlDAYnhOv9e84hR7b9ir2G93xcmNz+4M5xmQq8SKUZvbxePkYA0JPmhD9jjZAePNFkwkG5+ZG8Q0GnGFF306bPDol8TFggqoUNVABzJICeaX2cBplUveZDu5hObghIe+os0o6bxLbwaCrJ0YOLbuyKbM4BPoy12s7cwkspuPHnfmGMRX5r0XqHKqNn2GK7D2wFzZ3otEo3dgjI8h7g2YFv04QGVSJJShQ2/ZVch/vGCJCyUkJPsAb37KgCqMTpw3gOcoxN4hXSiKVmYwQzWFCwoJPonr8bB8dMAFCiPunx1SQV18si+sJGnRFs6Fv6zkCjgc9Qrw3T7aT7KhAYaszavOY9Y3a1gdWDNHGfAOrY4XvgbkTIYBienNRY8Y0B8kxbD35FJIb4uRtrA5DX6oFCSRiPQ9j/g2QcblebAup+oKUmlDweNcm9Jig0HDZphfJzgOpUChKX4nBzSY3Nc2MMo6GFSYLjvmYuzIijPIYhhEv5wDwxeFbCHfmNSxMcK7eo1f0+m9EVB6hjNjsvV9llxG/3aVjAuFlHfZP+M8wuJsUJoPN0eD8AiesaxeeX4szQ13PVbQRDBMHGw72tGdRT7q4d2h6XPImWvIONJEUVsPOvgc1Rz7h0jDTSgEMMCxjGdAKLw3iTgVz9gIEjybYi4DbvZTcZk3H9MQJDIKE6fbXKsbEThGUxQO2WR+oDvmpbYyJNhQVfwWjTRPW6eARxks2Hzz2Yk2AAQEDGUW36mGJFxMVc38pgBHo32ouZ8MCBUw1HDTAFFkqg7wZVmVG++HdxUOySA1K9jM4EEmvY1dPtntwPMnESonARFKjA5TKeC3WhJ7nF4fWyjpKZeHAN2O7jpQES9conYsTP/HbcgqaTKuqHEi2wHE8vYFnbYPKNoTyHPGUFKkWTiZVP6e7p3lecNvjYH/LVRCUh+axhkn/RuQPYET5f2u81h4yPP3uIxw1j17muKIHBDZtHUpWGQrdKM4Z5NQbPh3jV/PivIAO6+dxY8TIKhU/CdKJZZcGCIWNwU4AbBIgUaKMGJsUqMyZ2w4CjxymfDxUNyyd7ro6d2BO8nHmf73vdkhmRDNWO4xm8qezeLcDrOFbtZrTD/1T8EbyAA2pSL9YQZlO3Hpph+TNisMypd78MKkY3mGaLETjbYjuyNGOVXTBAJcNBLIJ/aH5UKcSSHLgblJGWzJi4eaBVdJ0xiBoAPghPKsKDXEs0WU3SddR4yhSKYLaSaa/ICU0fYXU4RCcv5utwrEfGvWHZRsJAZI1cwHWFKgGi0PiY2u3zF35M5QPTiTSwMYrhJVoIxUyUgIGtR9qRnSiVn/P1Q7UYsL8DgDsjFzwegUePnTqINPWMAqtHQWAEmA+wBoCovXAofizDSDPBCc3ZGmKonCD+fJrw85nGmmDGwCp+vSSuUqlRvHQneAw6G9DSzVblvhWvgADB1WBU8bzwffD2APPXJM/cx2YaMBNfUFDwHTOeirDoH47I4aAHL5LnHI2se5Ely3yZYm3k/EOg1ptIiVXIHb4Tncpj2JuKjlXwYLFNES3MYs+XJmIzJ+I6MCQhyn8HOu4PxVqIdSxijsktYkjrOrvsl2eyiQ0LNZIX3amljvHhYNEts6DIYrtHnoNpoNx30saCEhh0Rt8NuApMbt8MbEi6GcOU2lESh03Ijbcz9pDvOzkcFjxXjNA/GDo1I29+h02pMtdDh6mzKaWSF9zYGtpBAcVFTSVPHbyQyik/4+OEEsb7ZRlBbsYlXP4khuut9RJBSvpCLYdw8wIr0znwQ0EgkIrB38kpw41Mjnq7f3x+MlG2PB88Rb+kBNpEJjQ5bEGRZ2JwPQEV6+FSQvdOM/FZYE2z8Tu7IM43NiYm5RDFXfdAXC/3LFgBgShQLVfVwiOqoca+uBEjKoqAPA1z1rageopGn/3GK8bStfwvmrlW4V8A46SGyWI0byUwh8EDqfi0UfzI5zNAu+L1/M51GmS00QDXeEmL4WTy2LcyUElBn8b0+LNK1Y+eDRUENaY+Cb6N7xq7NyAmIM5YRenMC2O3APFTwHkSXsALdv30PbOTTKzfvb1aJDn77esa4omik+agaXte8vyOFqaN8grKl9g/zcJQv0ycQ2dkO/JtzrPGhYlLZGNlKyuuBa5CdlK43is705nSwg6uFOgtaggBkD6a3cd+LBJUJQyzyHO41TdkovvZaMK6WcfMGRJIufoGmhJnv4A9imCwKfkVAALJ5OpIPjI4ZaeR9ed0JfHBvQbBLR3Y7HDWtzZuljNgxGzBBiuMaIB2f2869bt6gCkfEU/IiqUa81zI8E+Z5EH+Vcect+BoBRgkMmnQWgLm1vMbEhROww57BMCzk9Q7s4gz7RjZ1aBTf/m6DvwcyxOcmJQBLzL3KRooBi9GkGtkfmlhgzLG8T74dnkzfs6O5hyONqXf0HpMxGd/vIMju3bvd8ePdTc7P/dzPud/93d99R++VPbrfZdnAJSf9wlpTgwwwoBlDxKVSIz84cz04+VbrLMMiBQiS3pwPShE6ekNMsuzcsLtMrxKzKDWDchawIhzNqjRO7JYHFMo9W4PpOMnt+bjTPYEPdMWSa+h8aLzbvZjM9ueI+VqCfHeNGTNZ9uwEvv1WdNNQMp6txmaR34d6XjiJt6/n8e/3m8OsiHfUp07Ohjt7uLYEiLJXbBeEHRKa+LILUstCOvXGmfBCgnujmhFZAMAXyhqmbviu0s1tflO9TO4hQylHoTq3qhdNMKF3BpkHNN8cVP4evoPP1+82WoGEAoBaI7Aw2pdAx0yvihLPdwFJUoEEm/a9kTzD1+crrOwmBpzMryd7xf84yP29mr9tEzPmH/LnduoVeEiAzpvC8+DuG8JRH8UpZU+my0uacHN9X/dzXImo8OzKjajhW/bQnjDgSBq+qxfnr2VisGykGUdOBJkDOl8OaOrI7jQ7dvSiEUaaYfLR+R9MEO0095DCUgHMrB7ZFTbjE1kdvVTIViA7TT1BKmjUy0fCsZuULfUOSrGDc0jGSPWN01Fglx4h6XBVGBwHeOmm5fW47+jJ4SAbZWLJuPnKMSJYOs3RQY8TXINiqwXHmRjhkGCS8/XC5uE9lUCeE5VCqMcLQBT6slBCU79pwRojHSIzFM96ddJfz+Sa+FZQzgJ/iZQJeWROKECB4pj+OVybGQPffuYFgD/4HAJuKokiU8mkzfDYCOqZ+cWus7GiXYdppGAfGAMN9L+TAVNyHoD0LFdAAufAzFGYk0zcrpivGmAOQAM95xgCoOAowWX1plv87wIAE2AxCXvYH6p5KCVm/D5mvhHpF0eGa23SbUZg3Aj7MnuDnhy9oPTaAIFiIEvgg88NP7/DqMYwshc0II3sqbkGb989n5OI3O74VuU0k/H9Ox4oEORrX/uaK6H/fPXVV90nPvEJ9xM/8RPv+L0aunLiaiMzSTesi2520y+8GNSmluy8YBOeiia6ZqF58lywO6Cxb0a7zE0HCoQEk3dxTmLwcK5YCKTswgsLgJtFyicqsFzSs1iwQbdU6iCpmEY3LZurCiadKTcgXIypXRdAg/R/U8wx0k83DSzUSdPlYgzJSyehga7x33g9eA+Y5B9dAFHwGFAJHQVNPqBpa4qNb4pjSwioNCNSgCboFo02Wj+N9K++4V+C/z76IZ8WtOxPPPiWknKsndZZvwlKvg7Z0Uf85qz9HEhI6oO+K8RRPe/P2eCKFKPUPrPriYKnJ4Zpc5v9vwfQiA/h6TE474+rbxvyxhCPIN0IYI+J9W29P7DZhJxlcMjPCcN9cK1Xd30ATvNP+I1vCU+NqXPSYcKmcB5AzrLj/lkd/eiziz/PMW5Y0l3484KUpf1eO+31JFPp1qP+Ph5cmndu8asmbvjpD9396aJQmMHkmPu4Z2z0kHaUbbXg3e2ZZcHrls77Z3q4FkAHfRrEM8ekNMGANZG4WsbVGFbf37zk34oytilhrzAJAc9nGvF8UKA4RwQl/8qwUujZIB16YzZJ8Evlf5y/xdR4YSTw+tBRYm2i4SY74iqfqJdBqkqPLcSVMyazPTSm4pxB8g0jzl/11zPDZ6gc1KRU8Hqw6G4GfawwDBuHBq7a1URhxsSiPlKq0m2SgnMELAsA34aVwhj37Vui4EBKxgqYoVwj2t8BWFzw8tHvkwKgql6z0qIikrJhwImOr1k4Fpdgf8rmwOmLcRkT90do1hjQoZ2LroZNW7G2z+/EPunPXjCvr8lYwd6ioqH8OQG1aJAPXzEjB4JMoyONxTGb64G9msqtq4NHg54gLmbsyv2xPBOUcyYE79CsaY+boAjWTEYbc67opA/i/uY5GyHBS83IU0rRmLh3FCAIQNbUCTiO/Q33ih0wk5+JeYmyFzYGNYVmAaBpTcHjGN1kTMZkfL+CIBs32o3Ab/zGb7h9+/a5H/3RH33H79V0wKqs7+on/cJSQteom6sEjvQxLR8L2Lln7Iaufw2FLqh3ycMeDc4u2w1ZDkf8avXyYDwpaduJ0J6rIyeD8YP1cY9sJ5kFXkp0dDMY/Rka+MrlQeq+bmTrsxeCVO/kQ5aGzoQDA2JEDKXykb0P6A7PUXPx0wEgxtCGsYGoDh2PM0kQWZxtwUaBPiJTUnwwipDHifNJfbiaExJsuP2QPwfT2MiX8p1zaPFHD/nv2TsPavBNAfxYjKDTWlD3i00wIzd1MF41W+s3gclfe6ClGTW6htohWXwNTNU6zu7oKpWHkIDyKHwShLLavwq/D8T89q7D+2QtTU4ldQWsHUo2uAljVKxGFpdMkMLrc0hTNNY3A4ssx3PjYAhZ7bf07Aq+KkZmgojC4mN+QzkQ2Q/9LYoV6B6mSPS5bovmcpXfcC9/+UwcXL7H9EnEi4FFzvQQwCJeX66zm9VlXz8W9I2oATj2cd/XYkRtDIEwEhZpIvMoT1MmsT1Y8FSM04Svjfp71KuWB2VHavbIVAUT4029Or+LMCx4bukZxKLVAOXtHyZB800W+hUZBSy+mn8/hucQRrXJC69HC2CHdYqmscbnQWJYmbRSEGC5DsCMPiTCZEwQMWtMNbn+CxPRFNFoVrCwNH4zMngfEoAuxkkR6CkVkaaYggvMx04cM0Gx5eFEm/bY5lcHpRlGLjCG1WGiaAmqYcTSN8bF4lYRxk07YhIYSn2UzYp7qjR+XUhnS7muiMQNQFKOhJ+CyUNqrkuzdzKQAGByr6Wmmgk97ABEUZ5Vg0Gm9yef4/JY2MNCo38JClVoBCUAaNSfqmZ870sHg2b/fL4IgumgjDg/eCx6PY0fHp6pbG3YjLUzIr8zrBY8jwr0xuqFdGZTkFFUPWDGqJN0mMl4L0dSq0PnAzKGw6HbunWr++xnP+t+5Vd+Jfp38/Pz7f8WxvXr192OHTvcx9x/7/KkZwpy4xHwmAUxaPbEjh+lMdShk4KnZp4mEQCdcqfadRRZZgH6AU+3zy+Aai1dLUpDEgIf7JZpxw+vqdBprV/y4ETGiEH6WTTvDUNBo49GEoPShOm3wfNRs1uCjQHp8Yrik3FDs0btSNCwi/4YTI0xsW3i5k5JT7UZm390onRh5b1mPv8b2AygkCh22UXS0OrRbSqf9JuR/IT9zLlH/YZsgO58ic4oI1nb78PivIrFlkKyIqaWZtQRFgQKaz0GAgrx97Wvp2ymHKTB4+wYhNKIEp9JaQtBBzJ22s+BDrlAggnji+eRutK+H0CQaIw2AyLIThC/FGqv6WWTn5NigUUb79utMHY9hWho1WFv9yBAcvpCmPoum8Byk//e2RlI/k6ddq+t/n139ppzW9Yk7gOD/8vd95JON31MqrUAXQE+9i5a5gH9mWiOZ64buu4KgpASbrqpkAI60XGTek5PjIomoweQYiAGzSX8Iej1xLSCcRt0ppYlZAjyvcCIaD8z4rXBlA3tjseMtTlYSLFIDpoNLgysESor4DFkLPrH+HOYzjmZLQDP1GOFQwGOxc8f42fE7jTBt6hJqQxTgNK/4MSFeKEuAMXi8eO+4fzGNfLum2fBn41xrxq4kgGD4+H5pBSPRsUqMyCTskS8eCJ+YZYNirkHElQ2rNSIk0yt7DpA9MPHogl5+V7f/KkBLtf7PDg/P+PnpOmXLQjFvQZj7vvnICtcY0EM7nuMhAfADb3kOumFAO9iJsI6TERt5L5lw6tjtsyGEfbE6TcPvWPzT0qQ6qOnovNQ7P00KcwcJqWNl/3cV129dt/nfuwxj5kTYuDNOBPfhWtQ1CP3BfcHbnZ21q2Cn9T7bTS11urVq90Pf+xXXZ7Hk4mWMopizv31Fz73vj8nk/HdHw8UE4TjP//n/+yuXbvmfuZnfmbs3/3Lf/kv3ec+97no7xkRyM6RifKSjht/l+K/p2dAgxTqIFkZNKCjH0Zy3U7wNKU0G8JLN8K6TqXOQ4NLJgZNoDp0Q1AZDXOBqD9SECp0NzpdSrJp0GHqAAqgdJvoPBrtkXKsEp7IpombES1g61XoUkHXH/UakcU3wUSc3gnHyyldEuxPl5M6TnNagDApEkt0g+zQBWehrpvt/sy6oDcD79vqy3INAdZwU8puj9F7awcdDIOEm1JEzanvBBknxmQMGy3S05UOzOtuNpG41+Yftp45LILzm4j1XY8Umy1TUSZI/3rYDO72HngLyblJwMogS4TskyWBQLoJBaBSbrCbhPkNeCYRn9vD8Vcb451qRu5m65eFu3xyyDyf5TZf8CRb17lNZ/+TS5PKbViVuLmHITPASOFXwm49jXKHW8V3AtcnA8hGxgi722o8TGAugzzLgGV8iFsQGO8NoJxMihFlU0eEZUONOuRayZjECo4MceUEAFKyLUT2Yz6fUhnGhmthCDaMKXq3bA7Ko7R44bNmPGJwPllUtL/iOQBzwDz7TJ1R4AFADDvnKRk7UtjlALHrTevCIIQAWW6A9eijXjLojkL2SqBBAQx6gkAWwCZECZBVmXQ0HU/R3TbeJwAlm5FfgMEx1uYKAFO2Y3t8P4JUI3bxzf5BvBW412ASX3buajQhyUT+cnz9WrAApmRUi9sazJiY/EOPzRTH8OkZvIF9F/yP9F7pn7oabFzUlA2rlA2AIdkfGa4nPXragXSSuockJxpWy9xFU2ETUTsGsOMgQJPgWSmefSiYmqZ7JTMP3MR5BtikjE9KYLj+VACFFCAi8yxFHHXKZ42AvhgCpzu2Ba9hAhkWQWsFO2rsYynLJguvfc2Cn1A571w8xXsyJmMy3sF4YJkgn/rUp1y/33f/5b/8l7F/F2WCfPj/1qKT+cGTQZqwdr4qpDTUYH/kiLOsoenOz8gmlppHFAXu66/FN540+mNCAqNnMamqmV0NCUw6x+McsylG3jo7sKYjg0U+OXspitRzYeFGTd272V01MYlgz9A3hCatd39ZBdF14+St+k0AKUbnSbCHmnRsgDqeHhGGhC7G5ryDep7s2x3s2tKwrh24P7jZY6yw+pBwg1sjijjFvTL/lEi3kFRitPQYw9V+ozB90G48TWcR55ApNjRc1fjb4epeMDp36rh/puZ2ybnBMGAFi3PZYMcYLBX0xRW8Nqh71mOjnwRBUmOqqTRwFKAEuEzykPgE1TArTo4jeQCFSKcLjw0ZY337r8NYdedMNBqzhkZ7+DxMWwHScXPbfh9Gp+JZSWdvuf/ln/xrt2H1TXfx5ir3f/53v9T5zmo0Vz6B+5sMDTHqKwFs5g3VZPHN0mChPm4eHK3y93f/vwH8IzArEZpktCVMNUL3kcVKp8jh/E0Wn3ru0FMJRphq8hnyDekYChIEBwvARH0LuG1SYLAWGED+bcvWo+w0w/FUuGYEWcd5arD4iBbJOuejo21YDCIfNElXNCllSocwc8y5MdKYJAxYwly4/TMmdTF9CZ8/jolD2Qklk7F4V52HSoDTSx1k4BjGB59PSjQC0tklfQ5ZCVxnUXQaoEPm+BTrfKzbb66fsiKYAMI1F+Bjh9VxzIMoxR5EDr/4RjQJhPNd9Yi/7zOYmVIeS9ZX+ztcTwKr5vmU/YTKW0KDjJ1K7kHOS/UOfE+m8tELp3kNmoPjpC5LGYYFxkScHZZVmL3q57sEgKUmYMX2igWuOyU0BGm1qWP82+hZQzmnxlbfA6KKeuj+bPZ/eXCYID/ybWKC/NWECTIZ73w8kEyQJiHmT//0T91/+k//6b5/OxgM2v/paDLG25xxmkXB28GpESYiONPL4Q1JHSkYm1GiI59B1uCoCWc+uy76pDozaYWfIYtUDmmKMcfDpoXFU0cWgGLOGJQxk15d1rEJMeahzIQfs+lg0Udn9gzfWTsVpIRn+yO0SC1e6OxNwzUg/dxQKtnBpDegc1NSt4vir2OWC7+X+iSkSuzsyqax/Phz/pjR9U0QS5w8fsB+Ju6B6mkPRFWgrOog48L89x/znz/4gi9aqyetX8pw7VSQEdA77Iv2+mEbzUwZTyrSpZAZnWqNp87ejPpoLL4e/h7tca7pBVkdZGiQXUDQQxkSSQkd+SZEIW63wCQ9OcplWZgJApNSJ+yTkmk123CtcTp6O+xmt7o6F2bW7PKbvQyAAsG/Zgw/7O+b/mX/TNavHArLL2SDegcGtNPs+FHeA9Pd9rtx8445qX8aFGYxus1e9XNU+fDuYIqNKXLF+JHGwfVXsEGn+bSAAxwEcninpIwWVQ8lzP8VzatZvIl8I92+NTiPpZjXTcHHyMkQ+y/w3TRpjKaSOQsZvMb4FEgx6uD9UY7xujCfyUhQzNE0Thw3qNmPDQUHeA1YUGeIztVRk6UIVl8NHw7q/428qhlc9wlwYc03saHNe9OHCizT2P2p8a7sQif0c2CzQlPcEJHOJkLKc4Mu+jjQw5jgsqCHp0vnO2BtNteD5r5yPTUtbfH1NDiWJEAOytrI5uF36zwrBFEAUjpKhcT7xABRSPwrYh4vAK1VJknpNue7pYAenYHrnGyy9+Boky/u+4fPBRm45aOW6cdji8luDJOTfyPy7Wr9quBelWtZe9z03qAXHK8NhyQM5WC7ERDhvlPBHiMPxRxX8t54xO7VFtbmpGGCjElQfr+NpnHB5sW7fY/JmIx3Mx5IEOTf/bt/5zZt2uQ+/elPv+v3SL70ikuSnllk0s1PROn29RtHgkwMRh4aarBE5NKcsEa0mDEPU5M2/kxPEmyKY5vo9nM2AOCgbnYPOjQSh0bNJI/HaLpBq0wUuAHYUq1AMfUQ4t2+9E3zEgOq0CiWsh90ZpPtvuPakQ8cwyLFrpzEGnJTybQFXs/RM4go3m6TKEpQLB20vvUPe8aQg0zl7of61xS7JFVn4ZhxnbRYyV+GjhlGrQkWYHNcYwzoyg/5+3uAFIL2vbGR5Oa5B3NfdrLohN6+3wX4OVCiRZow0lA6ndo3jwQp1QPKqMZ11KEvJqCjMayGIk7wjj/fwDUUvflozSAoR6E0RtNhCJzQJDW7BQYT0mlIW29fv90/08tf8l3wGsbJZHM1Y7gbYCRAFF6PuZnpIFDTuZ4AmGqk9ZRyD6S3h0GA5+4m9t75STwjiCCWngPOhAUYM+qpUv2AL2wG59BFx2soK+hduRP9zN4IRtIwGswpXRNwePTJ5xd/njoN/T/TrzYIwHfi3H1Tu1K578y8isH1xwEg0pSOCh1QsoSMR4AmjcHTyYFin9MThewC6XKyA2vSbh7116wWth1j4el5QGNxHSxIjRwShW7NNQoeM+1nnoeEFEDzOMNOsj9YaJrimECJMntwPijBYbOjY467cV3Qq8NIU1DwsQPdHucLr4Vj7SnTlKjREnNxFQE4OlLX2MAzFevIt8cTk7DwnIEhqe+lsqxQ2psxbFWfnEiULveHyhBMyBTCXmncPWT8JbAnJOPFNKxoBNoMgCicieMQ45jPn5oKx8Net4B+7yQKU7BMyGbKxX6HnjP0rOPzQYCsgvG0etuQQcWEJCcBAeVRGNwTkGYjiY00yOU63nBMiSLQzHmwZeAOggbkZt956mwQCGs8QR6o0dwm3yqGMcFAJuNdjgcOBKmqqgVBfvqnf9puwN7paLpRSepyUjYv0WR0OirzMPpibooxwTNNRjfPCVFi6goFga7R2TMRtzTuQiGjUaX1CXQx8DkxJolScCt0U9M3fVcu2bA+Tj2kVvgEAAmybLCxaUb56O7g641JHHTDmejADasCG98MG+96lbipwyOkfPtYMHq2/8rx4Ma/fW8a7ZFZc5AxgiLBIU0Vw5jbYgEfzdjP7DHVAV1smsEao93m+hzYHu72o3OkZnLzz+0LR6JiIeqhk1bJRrOAnIXpMMN1/lnrz4opGIrTfh80eHhD3AJzozcrKRvLfRrH3AbQwzd59kquYE8alsD0wJyoX/ab5UwYTL1ibdAojwX4cIN9JnOAmYxondsC1hFP5zZJb6L3B2R1lBiYzVlrIOp/14NBMiOgszn4AkhEboJElLSEbwU7qMq2Y5wmUpaaiPN6oTAYFm7qy+HuZIpNMQ1D6UeUAyTV3xk5BkDOlJJDibvtEcxcAf8DSiGEwk0QOj9yJfh3RtYoYKw5bwSS0PFUc8OcczkAP8btjjMlTWiUinnEmGoqQ4N081gBTD8okXZmjFTF9ywE+OAw11B0+sFzK8wYR38LgsbXcJ3fsEVWFfkc85ljmIzmv8eK3vNj3hvrD40bjaGidssJXuEzjY+YGMhyiqFpOfcciZip0gdKpUtBJsu4+xDzQ74ShaUaX9L7Ap5tbFaYa6tmk5C6GpYpzdQByIyL3zUyKMj9CNS0r8HnjCA/7BFQkc52tcMDmMnJ82FDeTKjRPpskowARnI/kyibicAc9wBgzZr77paw+HZBEkRvvJfBMhUQic2TmJGyeQaEyUO/DuMRBsDUzKMtOxj7ifNhphQBtkrACSbKFGhgmudOfVQiKj0DQIuZeHZvL1/XQ+fu70M9GZMxGd+PIEgjgzlx4oT7+3//739rb9Ru8iq7uaOHhGw6TCY6FkOzKSbN9yOWrZDOoUtG80wu8mOooAkSBrjZNXRBofdxoa/QgSSCrtIHIw0BLTPB+aBXyFi9Oeh+CQrwesdM3CwLdPmYBEYjdo3G/A0wAmbQGWXxJwWoMarloo0N0FCKUfpJ1NCl0xfA0fCtGTQ2g1+IMUQEM6d3xnY8GaEZc53vGP3h3BQwccxn4VshUbx9ykmo8cZ1opaeHjnt60+g/YNiiMevhmd9dNZoEJzj83k+6PjejOGmlfEUmHtjboe9hlNHL4cBSKA9xYc8O2wozIMMnhjThy4GwTv6q9w97n44shef2b9ZRs1YM8jyyuX+HBTwSCmnLGuJaTc9sBKG6/1mc+qELzCGOyz4ls6AoYDDKTeuCHojNWME6VJ/DQqJDcvdP/7//L67M+/csv5wcZOvHi+UO/X+968F55RynQWYsqN+8zp6DgwDSoUuQ+7wlvVOSVAoGm8kzJ05nuF2MMISa0FNec8bJ6OdauN7gaJX5QtmAKhOrpZhcJ5dYxT9dz+oDsc8MkJUB8F6buQjnVUjN2gGgWt0jVnMJZSmatEZSYUwoIcU/jwfxjsL/gtMWmtfj1S3DK9P6L0yJnEjymIAOKDxw8ZTA/uRBB1pGip2pJbw+0oBiFOyqYlsZn9DtgGNesVkNAUwZ2LUY+k4soeqjsKDiEADmBiJMPxKgj3Yg7EYpdH7uEF2Evdd6rlTnvJ/l0L6RWYmn3WmLXUMQ/8bvI64zxBpSQJmR0FpDPeKBJHkmTYmnWTncn6SZ8XIlS/f/55W+QYlKGYHQMBTDENTgj8ArAyDiEDJQ5a9WSNBMZ+Gfxv+u3paVZAbu8eRpHcWoDmAcsNaE+mS8eiKyWlUvof7zjCTxOB/oS4oHzgmSN0B/d7Ve0zGZLyL8cCBIJ/85Cfdt8PrNd+w3uVp39WIi02vYAFWlgk2B+k2pIbA7NEU84cFCubmjC7pNGYTL4P0Qh0GPrAYjlCIcCFoxoCLOVzviZSrJpqLaT6zMQjQpNDYK2PGbP7ZWQUTQw0JU9L3UWSY5BxIYBhl3P7dTn89qo/6v2P5qJGsGbWy9HKhD8tXPQjU14QFbDRKakPhC1BqvNtHngyDEGC/kEY5v8tulHrXwV6BvIrF/dQbFuyZf8Sfm/6ZG8Fkjd7h4/Y1G3cHzxsjdosV/agDvIlqBlOpAKtD80/mtuA5RAJJwvQI0LMJ0LW/W/WB4PFQ/kBj1Y6OF8AcqdJu/QfC4I4OMLUyxn6OoUCzE5Tsngmes/l1dqM0dQ5soArdt1tl0IdFgbX0PBhVyxB9i67g9FF7PW/v94VA/3/zgIR5IqSDPtiDOMntq03k75++UtyLyC3dk/unw8dMtgC8cPKDoGeL1KvesjEIMuaQGvG/l89ayWN69ko4atX54qvUKN8GzQkkF6TnsfkHGK06dJNgAhq8KTgEpDSb7zVILypXh6PPKbnUOb7eGO7GkvatRScH1wWCBmIKbQwaEX1OH6scngljWSaQedayTtOElqapXDNNUfRlK80kO8jMA/wqmO+1i8zfaXG8lNjQlOsMGDt6PdxVrK2IWa4iJqe6ziv74X7H3EmeuTp7f58cBQyxHlIqZOZISZTh+TT3IBpO+balpbjF7uFx5ro1vicLZRbtndcDYCGrgUV/J8lvIRmkOU1kjHKOQ4pdAX+U9nPwHJh9E5pvHXNcyIiNTCMSEED20bhhAA3GKjfvbTw18qDEmyCE7hNMAxH76PTclagXEIHmCrL2kkAc5shiDABtgDTsfZUNlICdnDGRbAlR4w/aSOq7//tW32MyJuPdjAcOBPl2jaKRqyQ9l26FYRnogkzV6KQ8YOPHMrdEpyN56qFooc+OCE3zakgU7v5hWNFZc3PEwlA8Rdy1+29UjMN285HYoNKPgYtE9czDUc+C7A42PpRvYHNXvix06me9lCGlUz4XcGq6hUnCJIoEnb0M51yBFzJOGJfLTntFcEPuB4euLSmndYGFXWUJR/x1K+ExkkmiS6y7zsjiPo3teJ8I/XTw6slgl25Qo8gSc9zedUh9eE8yQhTpF9kRC7xE7zVQ9+c/4f0T2u9z2Z+DEQxMCez1XvXdsiFMWhUUmjrrn9URTE7nnrCd7mUnlwVBFWqS5/H64cO2ADYA0UWAofCC0Y44PXfuPIVnH4/u9Jex2fyI7b5VeN7n1/XDPiTi6TH11tXgfWc8Nah1UsCPm2V2I6+j4BJAguBsUtx/B1Os6EXPLcE/mlBWUghk+1AowjdjDlIlRhZPvWLBVMpBTMeO3go6R8+nQRNCw1Qq4Rcjvk30r0nOhRkB6vWU9nrhpDCaNfI6ERBpZUPLgwlDsQhT7W6b5xuASsqYTvW3wvmsblwJMkG0SDVdVxTg9WGsn5J4YQog0th5blAUMSaz/bsI8MH30nhV4ycAY2tjvMtrAD+PZlQnTgf9B8j2KEU2xHWbKWL55o3Ba0g5rTJLyQY1SU4SK08fDzaJYn4SKo0xMaR4De8BLRJ5rtUcNgRCdKKZAWIYQIUyGU3Vo98IgA+yVxKw25KtlpnqIEklQMVYW02bq2LJWAS18HPH6wTAaAIzdLKp1GQ0FoXL9S+DZFKBzQKpOIYRzHtNzXXx7xLgFxNZDDsN4FAzUuwVHZgo1WbMA2qIjMZWgsTEBHMnPYcy8X0yhrJke3PuVTYQG4j4fDY+aq6fmO9aOczSyE2TMRmTcZ8xAUFiJ2brjMvTgTG1qtAZrrAZUZnDaOXmYGpMCbZC9hcvmNdXkZSPwdFLUU8QB5ZKvnxv0NAxu4rOh5piLodshZtSpp5IwoKD43aCAjS5jkL9b17yx2JfbRaJCrpys7mCtrj9uxdfu6+RlykWZHNmNNonAeKgY0jqZjPKjejWkLUji+7iZ16yqxK7BaYDTCrmKbvJuPOkpwcPLqJgQjHHTY/Kfob/3QcXf5664F8/Dw+M3ouW1jr6lH/N4IIvZO5sRGKHrQVdCpkH01GMNwKK1kSc6nMUadwADCHhoSlo+34r+8Gi2ZgDY4NNk9Z2wKTUsFTwXr2L9jXZJUSC8hd4VjIcZzoUIM1E8eJIqWOWZA/eN1PrVgULkRobvWnIVLSDuPww/HNWwgdlZJkcZDU4+ojM4e+w2S+32iItv4nkHEjh3Ho/P2ViApwDuCAIMXXGFmNGEoTB7zAP2U4/2RlmkDWMld2rg0DQ4BLO03J/b9z5gH+vZkwfvRoGO/DsM91AwfHhbr/B7V24GTTfrN+w8aopCoYK1yCjTFL8NVgkpAC6TZwl2W1kPjTHALPBhKlZKBhVsmGAMLIywFxLLuL8rZVoR0gm6BdCCQy9TjrsIhQMCWjkJplF1wIyF+ihRNPXPVayQX8JU/zQI4WFkBTq5lnDIEumOiiyBDAZ3KPobsOjLFVPEDKVWNyCOUd2gZEzCbOUXWyCLboWGxN2sk+EvREbJj2IgMIYHxZ6vqicI/gZwnoy62nP3zcZjX6FWVyTlRA7ZjRo2ETp+KoAoDLXTKRnFbyCYpHFRu4GpkH7mbgeakq8+BmSYBIbKp2KDcOeYEIP78fbIk2JydoiSU4K1KQEYNG8SZlqKOeW+ysCUQQcOZTVYd8MTwUAHb3vyIKKAVkdn597xzORw4TO+4QKMhnvbkxAkMio1q9xVTYwRasaRHKk8LSYQtHM7kaCbmg9LnscAEnYe/w+g0QKJqso1Q5aW2pbmTdfjVnwSGskXZEgRiIFVwlzQhZG7IArfZSdB/oppEjmYJGoZnjUW3ODnDKOUxbjml4u2DiXx9BlpHZcOpvG1AsMjZRUUCle6G2QYqNQyd+F5DjN4FYxwXWfPg69umzQ+Zk1OmHT3JztFQNXpPeQls/Oj4mOBRW1GeVWaKLx3QgY3t5uddgrXvPF4e0D64Ode16DO1vF6BZ/Nw3ZTgmQb7jWbrbr1D8T6ZY1Qe+P0Qowe3LpbpN9Me/fOzNSIQEULvnzPrcFIMjeDy3+PABYkyNlpX0NwKsUbAleDzUMTXgfg61wZyd8ghiPKhts55YFr0GC66kdP6ZZ9a/l4fSp5rPevrfJ3WPvwRrnevrg+XDagswj02fRad3vO37pZbDVXvXv1WOaioxkFDYKdNINpaygfzILpxo8eSBqUurAfCtmcPyQMKk5IJMpklmALSy+MC+Xnej1KtzBJIsOEr3272KmqwAaiv1+7ku+Yueu5FH/vVNEupqIepm7ypNgRYBWn2zZFKXoZ9sfCnZ3GU1pvKIEUDfmkyyGyGQUujzNGlmc0qCShWmHeQCAKI2liR0XlgwZNCgUDdhCM3d8Rif9DnN0uttfwxReI+1xsimC9TTrrQin5ZEVI4MG4MYHTO71pQAfUeaEDMNEofRKCiwCH7xuLHR5/Pl5O6dVu8GeQByykZwIOyvlPo6eO9xPkKGnxwwWs5HgYCgbKKfxLQEz7nXo6aVSPph+01SaDGQdBqjdDRkz9lBmr8zUONmj0ycnQ6pSOSbGPAPoSQYTz81YSRiBnzF+SiX9kXB/JkymWiIo9X4fzd7M7OPe5XtMxmS8mzEBQSIjvTXn0qy2VGcs4Br1NoIJXzWDBaMKm/lNHbKmYuwCVB971h/HF16MbpArmCiSmlpswKSKSFhDQ2wLu83hjh3+JseGsv27s36zWKNTXVFffcYvMsU+Sx3MT10KR4vR/0C9MtYsD0ZrJtDbGydtdD3a48Smg0WFScFhISPUb5p3GeBjO87facuwSEj1/aj3QanQIXIbRSdKzxYyeLCpNg72AK7Ua4MSIMMQ+XOrca+eQ8H0oqd6Dx/eFgQn2tegGJpHasrgbX+vzT00EzcIQ3JA8pgvAG/t9c/N1AVbmA0R/UqWCE1Xqxl/Ppa/YDuuxe7NQdNYbuimv2ip7qYLjs1VhYSh/Do8TQBuNKN35XbQZDN5aE/UkNehAzn4+uFgx5D3o0qLpi9vCG9WWTBJV42SHJ6bZd/0z2fxEX/NSwAN7esheWP0d7EacwrlNM25OQQjY3RKW/3/av+3d56+K2GZftGalNI8s9wMDwgUAtVeO3dVjGA+dTUsm3kSkiwTw2vZJylYMhkKGXpO6L1/Z7+/Nj0CGv00GKvcjKmXkTZwfD54r+vgs891Kp0BmAt/qbRntwHJvt3hSFcYy3bmSyYhAFDgmpe95q9h9Zxl+yVn/Ia/hhTDJMAIK8MMNhiwRnW0+JACEGDJdmwPym6KH7eyvB7YTSVAaHa3s9UC+NEXC34OCQCijL5VytjE22UXr93fh0UADiM1inTaO/8d91D0M+Tf7Fwb887Y69WMlSwdmsEywUQYK4xmJkDFQeBjXHKPkXRxP6OSYPrURGQaKeS1pRwXGyQcxgwV93D73g/5c5vOAaRjgwFzfCkMCZVohYp2TQ80xsP8OTI6iTSH4H3FZgfkJDG2RTsA9hCQMOdZGRZkaSIRhkbrZA23LyFjEAbNJdhlsfOnQyXOi6+HIXF7DJwTKBXFvZ5KY22cV9BkTMZkvLuR1N8OF9EHaFy/ft2tXr3a/fjeX2zlMHTZrnZuDhuJqoQEdFoCDQRURrsk/goSA4N6o9OuZlkJHfW5GMAXgEBJBaq3dijIcMhAvyWFu/0+lCKAQlxi48bClHKB9t+veYZFgm7LaMe64Lloj2GdXxgGpxAzTPYGuxva2STVGVpdnk+Vw5hEFhQ/1LLTa4NeDO2/AQ7krx0LfucO+4THhvczSTG8B1Bg6LFx5NduR83oam7KGeu7kgCAfT9jMsbIRfqQ4Jwlx2xHPkGccL0am1pslOa3Wrr81Gv+PYYPbQkWo5Tj3Jmxm6PedTAPLt0KmrHObbQFaP8aupb4PvQhKafSqLlusRwxw7g0g9ki+hrG1d7a7zd+/avD4PPFZJdOQY3Pz+brsC9P+5lIREF6EE1je0yxkedr/sDmoLlujUI7gSl0Z6BgaDp5rxz7n9zZa7XbsiZxjz/6f7/3PeW+BShFnyCH2O/OiHTrDXMMkhONfKR8okBsdvaYB6froyKT3A/T1EhhGe3mth9UBqUdhtKuCSaYL9LDHgys9/lCKnn7VBhga+4hgFIJXu8AlhgZQPOaTWuCn5/Az6gEgJDMW3ZbyjhlfE9TpEr6BFNPyAphVDVZFO3YviUs32PKCDvy22zR7Hh96RnApDUW8FIYsaCO+WvFvC2aUUIWQclGTC6w1EEjUo2SN9/zzjC6lhAATQ4h6QXzBY+5lohd413Fwc8RMLWE9Dd59e1Igwd7A2FVGgYp5Qf0a1HmBNdt7PuMqSdBQso/BRhlqlz2N2CMHrBACVnEsfXbAJZkS+jAOs80qs5r6GUGdjBZJWRScs+jPlz9y2BUfxOAxB419J0NPns1zNlTyq40oYgAC9i8Rm4tDCZ67qTbt74jltF9TXBjXjQRdq9534gcpqhH7gvuD9zs7KxbBWPf92ut9bEP/Y8uz8PspKWOophzX/jqr7/vz8lkfPfHhAkSG425aVq4cg86PJC86KjWogO6HUZks35TPQTSr54HLBqrH/VMkPoq5DTXLI19+Oj24OaAhVF+wm8ik9oaXI62ohu5E3IYFEkskNrfSUKN/z6I+DsBqre48xeP7w0WbP3D/jXFLrvxzP/k6/4f0GRX8CehdwBjU9v3A0snQxIEpU4d7xMCHAB4CPb0z/gFO5MibX6zP5/VM/47l/zO12Qxhs9A/81TQVYGO+rJF733iibv9I5dDDJ2RpvtxrMP9gZd49OzF4M09nbQZ4AbJ5goGuq7dAUzaHVZGLJDk98YRf1v2F2mF0F2zN/rK86Kfw4o6dT8Zwe878O0nE92kqrXUSSBuk8KeAcY5b3PFBxGbWvsKGjHK169EOxyVj/yjH/bv/6GPWZKFv7shTCzSYZhEHEjG8HHbz9mN8vL3vTHOURiUc1rI94efA4N3V68dSpspDnoOdO7Ad+mJ+H0L5HF+SyApMew+T6K498H0DoCKrbHuRF+PJhHUmFIOFD5adpXvwz5CNMe1NBwhI5+LHJREkwyFtHQuJcA1003VNKbHOI4E9K7WTBJ1zi9cC0c7Qhaf3aeptijeDoMQBA+g+7cpSUZLFeYnxgj2ykURTYZ9AqRYdJq+Hrcw7FusMqjKM3Md2+Pm3TPIlkK15O+NLmYjNag/5P9UoM9yHPRSamiKSXnKEqCRR6c3oIhL/875m5jFimxvvycCl14AkRaTKaIQSUz0iQZYY2qNZKVzSNhuC2+ZowsoYa0M729KriW1spsha9KP/XHXz+MOGzZNyVgt8YimM1aLP5xpjG3w6/NGUFfGfV5pDRhDU8BahnWsES65mA31QcRD45nhUBF5/sAJKspcwQDSpk9NJw2zyfm4RJ79fb77N4RXvMov4NEUA1kCbRGTZDVVwbNn+TK9aC8Z6lpO+/70Zyab7UVP2nlT8a7HBMQJDLmH9nmynzK9V/0lPQRNtjpaqHhMa0ANHh2xQZnroejb1saNEwdL98KauRrdNA1HYQF/XArNnF0+idzpHnNlN/w9y7cCYIGjEq9+93wOYgqnTp5LUj9m99sF5zBaXSyUMwO988EOyLt+4GKX4MlQkYCE1g6aQfwVqBzRg7gQjee2RUYEqKT1AN1cn4HOvXo4Ddj2Su+0B3thMQBMqhyxnZg++dvB4EP3g80NOR5UYCmRx8UdO8SMB+aUSANhIBCvWZ72OCz+TMUFjQV4/ORf+3NoOSlPU4AadUuD/hl+J7D9bKhQjxp9meHgvKgOx/aHy1gp3DfJWRn0VsBMrT2OPEe1Y8/GwSi+pf8Nbv9rKfxN6NYBrYC6sz6g37T1b8hYCjmkQIAAEvrORY/MN1tv85Kf277+F2B16SUZMln5tcIut4M3ifLYBCq3dj+SRRcjG6VLq9JeWCcpfhw9C7f7tCZmzFFVgA35TS5k2KU+6QeCwZs3vsAD6vztsimhwHNARMyORDf2AE4XsV9i26qAWCVAr2EbqR28R2o1kYiQEkTfX1E2lk8j3Svrx8MAxKaWEUW2WnQ1SP+CdkBC8pxw89nmh3gRM1YI+fAgCACttBfisCFOYdk44inFU2uy5feeEed3XGmlA4+Ax3zzgiTxOXTUUDIxEOT7Ydi2hieis+BSa2izw1ZEAIa0Hw5I0MCMlx2ylWWUKHwT8k+uQ22g/qaUUIa8brg85BoKhFew4Kc98M4D4hstDX4OfQ+04h4C7yA6dWHX5l4PdUb0Vjj67Fmk6nFtCO9b4rNkGEBNKCnZzsA5ORcM7i/4rOSWuClBJs1hQQ0Zww5DZrbtQhgIiWoR+aCgL6CKAkZKwCfUoCMGeTad98Ext5LkP2oGSvBu3oW54lMszGyH3oGVXxv8UDqXqAHYzSMPLLy3u17TMZkvJsxAUEiY3DuhsuzoRt+wE+4/UPodO+xG8/0Fd/VKKHdM10IbM5GP2g10X2kebiTvgtTPrIrmnaQoGNXQy/df91TUevN64Ndi2Zk5wFcYAHPT6PjR1qosAoG59GtoacIqO9Tr52Kouamu8CC/mlstls2y8UwUk7jKW7kpSNBXxVuvLjxNtFqzUA3MiUlfZXf1Pf+xqfWJFhklaWSf9MXMuXDfhOeqkTgoi8ge9iszW9Hh4k2D3fstcn/1DNmbv9t+ICcg6mXdNazSDGcgg2UHrHXcB7PRLXLFyxTp1B8gO0xXGs39WQqpQRYsOmZPnItmtaTML0CG79sHt2am3YTmYBuX61ZGaRg8z7peLn0cOKx3lbYRC57SzZQ3HBTQgK2wNAAdPbcTCFBhRtPPncdcICbXfgMGe23FpOka6MzyO5wxucOIKnK6iijqmliLPd6ClkX5X+taS4bYPfmQqUGU/plTOZYWEkqAw196zlELkNe1T8LsOyApWpX7Oji3hjCpJXMv/ZzwEapYepY7doc3MBlYlpbU2L2CuarzQQvlT0S9iPKaPJNOcsKy17pvwYfDnot0SRUJFGMCmXxUcITKjs3He1ykv1Iw2sjU1RPKxh7GzYRu8Mqh4GBqjHfpMyCMs9Ncq9jbaxQvGQAhsd1cOnrVR4+GgRR1JvBpKbwvKObrL4VJmkEa6PpWmMeouFpO2BOW8TYL5DmaIy4Q2GY4Jwzcjhmptv+HfdNY9gKFVOzIkDUOLYBh2G8MHkv3RqfLwGiUz6RX8G+a4vdd9HXxNyDAAcUxKAnhuPPBCEoO5LodYJ5+UVIFgGOUw6rQK/xe2E89pjCPLu+Niw/3I09LQ2im4H1XA2GQ9fTnBc5tyaJCTLPRKTLlOzRyLllg98nLrgZlSRQheKXdYwDIBf/5gkLEupaPxmTMRnf+piAIPcZBD7IxDCxqc0kGTEt6miS742p18W4ak3EIZpRjLWkV9DwC5S6AvTNnFGKKhPhRgmbm3GTdxnRHseM8VTfHHNnZ1KMpvBUVxG3RykBOgKMLDY+LAqQMBEGQwEmRtIxoi/h9dy7M+zV0RokkuK4IqjRp7a2QzdHh2pwNgnTxtUjBo7+/f/Np75UsQ66dmCxcSJoUG+3gN/g9ZPBa50wrhDXqS+O/iaOEcVHPQ0gDbTx9t/YxKSbUZgRxIDPQPXi6/b12FCM1k0H2VSmS9yMMzCk5bFdCtPLuaFt/w7PZLkNOmZITrLblglSLoOs67i/H+YeBzMHz/Hov/+wef0UkmOqPfhMAjeQZLXvB5+fFBvxbIu/P+fXT4ejcwX4GG7yP+c3kWwiDCT1Qln8/Dvz7v/4fO7mi5Eb9HruzeGeDiOh/UyaKvO6IXWGBWszatzfNYo8gl8VwSKNw8ZcSuNDB+ZaQrZE8+85/z151tJvHAxHiArYk7x2OCwrIF1e2A4V47kRRUtz3go+C4l4CyUbwowL+ksV8DJQWR07mIbZxGsmNHYH4J4ddeMHId8z3Yl5XeeYSGc3R0FeYk7JYFDMoiSHXKH9HVguBrhAwaQFKCVzDusc/RBI41ebtgRMgvIovLs4j8q5YXx6DVApASuEsanJUPw5GE0soEyowdL+HeNFI0CQkbyMkw1hndX0I45sw/qwTCQiZRg3ajLK4AfU6fxzP3GnCpvwQrrGaGi9J9Md8Jk7Fvd1IbBoQIAlJt+Y48eejJGwKm8y0iPsOwzgVqFBBAlT+xLOpc8BiAPLpUZKVwf05DyGxMGKxuoiNTLAP1hbCXxAjCG+XCuCTwZ8HDNihqVGOjdu34U1IyHQLBLrB3Y08923yuSYMEEm412OCQgSGU2BWWe52TQYPbEktdQPg27HDi46Hyki+Qh6dAy62EVBp5ydgvY9+A/SzbnosxstC4bZrGHyZXFOuUMnOg8TD0GAnLIdSWoxwAU6tdz4cZHrmFrhv5vkAKQ6MJJWFyAamGYr/Gt0CqaWvKbpKw0ZL9+I6psTdKSrg774SGGiWIhRoinm2OkGtdZsRtDR0U4pmS1k5pRvvR31ERmhsMtJJYUmvX0PdLHrhxCT/PU3gx3oQhao/KS/p2p2E5n+IF2pEZI6sv7GINWYsak9mPu2b4eObglj0aQEI2HKFna9IyjsQPU2hnEwyEylG1tvgOndJf89a2iaUymYSnhd8Hmdev10UO89UKNb0NUTsplQyHBOu/siAFF4P8bIUsqXiJyGm+f+FyG/eGRPlN5N6nxKF//lA/drPzHtNq4YuYtXMveZX/xGhxHRjIIpKmBAcVCf3X7OrN/UFh96JGium168HjXdqwjuolNN4COR6Fhj+Mx40qcOBKVe7D52Cv0bt8JdWnRW29ewOIacsnrCf2Z2BDHuQknPLt8MFlw8n6l23fd4QLgGWEOWD+cah3SeZtx+xIMiyw5hzcH9SJC4GTm74JBmkHGjg+aV6akzQcPqHCBMrV42+/eEAWmYnCZibpuQOUBPChMnjdcQ7BKAJAMAHEtDaQcNq1m081kHwyLVbjY9GFC0mxS3OxKJSlNIgBAZGCeU7WhyjzkfM/5z8jkAzZyHm/eLdMdzJCEZM1T1+eGx8ZmC9E3lZjHzSwPscY3A9WtGyqQQ7ukAPhpGQvt3SKPC603qCfdmYxgz5jnCz1r0E+SjtJFgi/HAwBzQDqxFpikxBpRKI6bANGimfIReX3p/ch/IJh9BYp0vzd8B8DR/L3K1BIA0G2Y8zzRf7dwrkCsbLxtJEVoEr6qhcw9Sem4zJX2rSp+JGmYy3uWYgCCR0XTCk0bIDxo6DQkL8UmgQSF/Y8ASLLhqfMWisUa3iKkITGtoPxM/G+o6FsOammbZuFZvvh1c8AzFcK8t7NjVoE7VveoR9PIDfrOdsgumkaAnR/HCDIMgBL06eA4TJERQU97+HeLmyqc8CJNfQsG3SgqBc4jQXA4pBjeRly4HOxXt350Hi4DdFhiOmlhf6czNP+/vmwwMBwJhdGZvX086Lu41pjJUH33KHifuY3pFVLjX6im7Iat6kU7vBx8JGt2apIGmrkHiUDpcF5RM0JBYvWgSgF/09yiWrwp7nTTn4wve9HQAB3hu7iqY9nbM7QDy8bljl3Kcf0Nnw39vlK9ahkOPoAhkCpSgEPyi30z7+jewWXzUb+iGAIEGb1+KU5B5r0DK0TA0gmkLwvLooZtaM1lEuskJ5HOjdZCYXbjpaSvNnHBPJldIbCjBL3a9M7I/xCOggDyHchp+z9EWxB+LISLBWAdgkKZ/iQBhXBcSXNv86q0wI0/mhGIt4sFxznLIk1SaYph4WH/oe5Si0Odcd/cNsBYAzGV8MlPC2vd+M+LdQaNeSOwoDW3G1MWVQaNeh3stF7NHk+ABVocDqEOGpN7ro10bggbgBbyuckaVS6e4/mG/H8gBgqgnlYnvRVOk3gEgDesvTdLbf18HCA1AhcVYIuu0aXjQvwXnsD53PgoOsIDjemoAEWHzmHuXIAoZjmOSNAyr4fCxcDyp+CQQoOAeiD8bI0uc/3YA/DHvheuskgsDihDwI1sRRsGJ3Lfla6+H5xSwT7j2tO+BBhrvDyNTWUKs8TiWzLgIVhMzTA8MzD0F5F3t34ElyZ8N+1OkTgVlMwCaK3p9EPiQ5B02F9MtYSmfys0Mq47NxIhRrspJY1IZY1SrqURkAGFtNcxpndfvPUdNOsxkfPfGr//6r7s/+qM/ci+99JLr9/vuWsDX6cSJE+7nf/7n3Z//+Z+76elp95nPfMZ9/vOfb/9+YbzyyivuF37hF9xXv/pVt27dOvcP/sE/cP/sn/2zjk/RZHx3xwQEiY1mcagrV0DTbAo7eGM0owSIkTJGDoBGhY5+gc62xsIyMYPMifSaJLWw2N8xE3490GTGqbX/pjEcpQwsppUSiK5vfQjmgPDhKNE9y3QTCbYC8+LpoZHN2Y3KiLp6HhuOuXzzSNRTJENqCVMpaJqXCkPS0CrXwduA13Of73zMzYiOmxtpdKrLH3suKoXghrtHNhFJPihkMhjDtr9Doc2CLz8F5oWCAxdmw/RopgiIB4QpZkCl7x/1G+S5J/zmrCc+CfmruG8AEA2RUJRflchigDLVsweCABF9QFRSdev/4D1SejAjrQYoRKSwm0YaFGVpNOFNPvxUOFmlOR/n/Ma1ohnsqn3BhKH2PSA5IABa4+vM70Sqk0gZiuf88z71FU+57YM0RYDt7pu4YHxwfgrHj80pWQzKfDPgU8R0t31vgJnpi95bp2oYH/c2BU0Ed37kbNCbiGaPlK7V2BSXsjnNBr6gz9iQV2bLwntt3RxNdYg1rqoNtoufj3aFgRdcZ45SmHOZFm0L7wVGQCmme7wnHc/zwYjkRKK6K2zQK1ybPtYSZSEkYKMYg8n8QJACbo6x+Z6zd8JUceN/INR3glSR7rLS5TMwPtK/+kbw+HNgQlzjOrR8AFw1JZMaOXzqbFj6hGfKdNQp92sG7wECHyje6sO4tvo5kZGtXBn2T9BuN1I+MsaWnrJMKSNtQFPEDCbiiETArG0oWiv4RqQSq8vGkmEBUAYFuQNNWlV63AFIIt4UvKcyMiYlvjfGtDKFLuO9UYArEEZAnGxW+pXlY55PE80MT6wUiYP1NQsYJls23V9ugGPJKeUQQJ2DvkdqaJkDpKz5PWmSevlKFGBikynFWmBkuzL31F952b2joZ8ZGcZ/B/OO+uckvB/Aou5cwwXwrWGCiJXK+3l8rxujDodD9xM/8RPuIx/5iPs3/+bfdH5flqX79Kc/7TZu3Oi++MUvusuXL7uf/umfbtntv/M7v7MYB/yJT3zCffzjH3df+9rX3FtvveV+5md+xi1fvtz943/8j79jxz4Z9x8TECQyGn1jnQyd27Iu6E3RiUKkTn8NPD3QgaWp5bIX7eaqwoQ5/OTz/nP+8tXoxiahaR4+n1rI+i3foasEWTZ/x+7CGPdtdlVSmF/SsJQFDo0WO5tVLFLVS28GwZFm9EEDr7EpJqiUfMB3WdOrgmigaOWmfhwDjxTzAvIcvoZazmVH7EaJXSHH84yiXV3j52GSOXjVXzdj6EATQzGAHSHek4DA/MMeIBucsEXWEHT9HFTx0XZ/bXMCMs37bYCUYYSuDinYj/iOXyqgVsJODLqmZLkk8Gxoj+ejFtgKRgaDhp69YlkZK+e3BeVF5QhJK39tN0MJi2BKt5hcgOemj0KukwCF79Y/J91pjBTa5RKfmc9Cr34G8ccz4rkDdlAFU2UTV4voXB01OpPDA0hs+ovT0UjW0cefCwJkZkiBUKxdFgQGWx+Re4daZ6mr7nmpMAK7HQQUejDfxL2WC8OhhK9LsbIfTHYiOJGyQNGOMrs3y1FI3QNtFt+PEZoXAXgJE2Lx+Cl/kc8hrZ4sPjWNdScRbw0PJxbwCTrVjCNt/+40Cg7+gn5IAP3b8faZcKccc7fRvosBbCei/N6oMT90JItMsyrDhqkdMICSCzCIiq++EjbXhYRobCINZX3CBEkh7UhQaBpPKAX5IusXAWkyg0zjRQtyFpa4h+g/QA+qjm8F5ZyQiagRKaVPlFYQUKlO+vskJUOy+W4a0xtiO2jKBo6TgBl/LuCjomBZundbVIYbG+Z7E4zFfJ3y3pTkOcOM4TmgDEo8scqdm8LMLcrAwIJQ9opp6pyFZANMRiMzaRtLh8KA1cUwCNGJ7j0cBtxo4k9gWEGZBgQPsYaM/E+kZ9X+7UHQl1K8RDytlMW7+N9PnA9eMwWLzHzHdWnz2uB825ljyFaDqbXO6wv3/gPHBGkjcr9VTxD3HRuf+9zn2v//9//+3wd//8d//Mfu9ddfdydPnnRbt97dI/zWb/1WC3I0LJJVq1a5//gf/6Obm5tr32MwGLgnnniiBUJ++7d/2332s5+dsEHewzEBQSKjcTRP0oHLj/hFu0b8IdkSzai2eGpsgoWpfxXdaU7YsulgF55pHglTAJD13v4ONDpq7Kkxryhzkc6mA7OkZJIDOhLqfWKMo+g78fapoOt8Ibp6M6CPzqCBJSuk/RwsIMZlnE7g0FzWH7KxoYYivwQz1/bf9G1ghBn15jhPpK23nwkPBBpR0n9AmQODt84GtdPcgJB5YfLl26ItTPfvXwCIJMUkI0ELGNUxIUIN8KaRgsK0HG4tBieuLEm7zoIlA8hogJJmH//HL4T13uzekf0hABG14wQPe2ABJPBrab8PJBh8pkvGY2Ozq+wuyoYsYwP+HAIOEFQqB0jLAQNp/qnd0Q5IhQ13BY8Uanh6oPHra0ZIwZk66e+v+U88HzVGpRcL73WyXGoUYu13A1BMRtRwdd999J/fdE3gzObVt9zeHUnnvm+/DrHUSzfDiRNqMop0lQEKjmI/ADuaUIrfgKFnc4MLIIxmgJ3CioUhwI4UHc/yNWsoSSkAN+ssxLQwZMHBnxMwx6oZgPvCmKnOh1kEFejl6Qv23BQAG/hM02CzAjOolnNLCSclAmTfjBuk6GtcrPkOKGAyPjtkEdCfCw0B9QmoYhR5MA+aUV/0609Cs11S77mukJ0gf1cDrHE4Z1y/2+N5yxe99a6tQZCVvku1sFcMKALGZLUG8/Ja2+lP6euFZoM5hwR7pEFikmd4bjDHdySkOLYEMg/1j4mNBN44HEs2HAXgld7Mg94+tSS9RA032aRSBhN9gxjDzVSmC1hzI8kqnTmKIAjX1dbHAvMKGWo0TsZ/VxAlObA7COinMK82psGy90sxXxlAAGas7pYF3TmXJps2RBtOsWG8qwBQZbxXBfyjLLwGOG3YK+pDQvCHscAAx40fFObyuh46J3Zwk+EWGRccDeDQ/O87Ob70pS+1oMYCANKMT33qU25+ft698MILLfuj+Zsf/dEfNcfS/M0v//Ivu2PHjrk9e6z/y2R898YEBImMcv1Kl2RTLrsJmisW+VySPRykMjFaJfWT5WP2ps9Aba0oM8HmKhVKHTdrMVkE2R9mUdMBTCfhRoMmezrePBqMBXZw1zcxhtqZw4YwwTlLEOXYMc/ke2FzmWPBcycE0Ih0mAxFUjYdLDIIfHChNyCEXIsytkEHhTuRrhTvGnZNa5qn4TjVa4Pg12jH+mAaCRkF7WeC6eS2+p+HKOA19nPuIaFrLxzaWh9zWV/2wMvwv/NSlPb9UPQWkJmwi19Ih6cc+A1VjdeTeTA3A2r0Ddst6a/x52pu7SCYYJKLFKGGF4wW4YuvuQxNuQASwxkAi/P+d71rc/H3xeZocAWbb8Zu98HQOCH3Nu9jstVI4RX5Q42uo6FAo2DK/+Tr4SjJ1icoAtgB+EjEwJVxtewUT2/b4m7N164JCVgxVbv01IVgUgs74gk21SymCWK174FI0QJsINNFp/Gw0PVNDDiBD/xcbhAAdy0KeqQH1dSbw1en/qDtSpJVR0YagTzK/dr34JwPc9rswtWg/44y4pYCQpTw/1EpH32jRjAM751FRDxNUptjfsF74ySQGXIeNCaS7XUfBk0tDfNAEkgSJHoVADPzM5eDn3l7m73vpuFXkoB6X54Hc0KMTRnbyaK5xrElmJ8UMOT3ND4cs6Db00y2OR68N/cqbN7Q6yMhm0njQekPQhmwdPFNCgoKfTMP0ENC1mWTHANJVkJZIKSp45JC6MGUEJQSw9GKLBH+d+zP8mPnoiwZMq2MATvmROP70ZrQ4vnk/YQ5mtHtyj4kgJxfxX+fATC7eyaafsf5MgXzoFZ2cyw5h9dW/W/4mqOnghHSTH6rRd5kfge/lliMrJpCUwoeM51XPyI21lJ6KKHpSMNw41HTAroHgw0aw14hi1CkMiaNiusnfYaQNlM+cEyQb186zI4d1hvpV3/1V92v/dqvue/kOHfunNu82TaY165d2/qBNL9b+Jvdu2364MJrmt9NQJD3bkxAkMjIrt12WVZaiuOsn5SrFdLxi5gimo0GC2jZ0BE44cat3rI/aKDUDpp/xTw96JuhRprQJWaPkp53LdrFNzQ+FgwoJHjOEpFCpDCYrN4Aq4TAy1Ci8yCPYW1MU06anzphvKSboAPHxpUbrfSkMFbIJGD3yvz3IkoPN5IgbCBydVDHYBJPcv5ysAPLzklHBwkPhwSARnMv+38I/TRSzNFQUHXU07MA2QAkEaQr0DFddtVuyLQrsvg5LJSfs0736V++HNZUQx7Upxu8FrDYbPYvYIO/ehAtYPOz18LdJ6D5LMa16O4fOhc2umOHSJIDyAyp1vni6c4TwuJaGFssmNq7XgSZJNkQTJa+LQRqyElolDs478/T/N/50OLPc+LvseyUv7531gNcwPPJ920/c5eXwKTXwHJp2DTY+w0fvtsN6zeGqREPCU4KTKlSPyJuak36AjuYTMnQ6NmDYKExhhtSwBTAcDMSyAcc424JaINSr94MnD25kS5R/NWaVoCiO3kd6xIKbTMnSSJDEQE+UnhAVNJpT8CSYZHYQze1gslp+mXPFGj/zXQZfg5iJrMZeQYgpzQgdsSboX3vY/78ZgBbCKhTsrFsZCNyCSAaM3GA8DRxbI+NnX/cq8mq1WFZoBxzBcZFGik668ctiy07hOKexxkDB65KYQgvtGzrxrBBNFklkoZVYS3LUdgSNFCT0wrrjGGSEHSVZ9J8Ps1lwWwhQOZwndUrIyVgduF6PGaZUlkwRgkcsXGSa0Qu2LE50oYMQAUGl8atEgA1+55Dfo7MNIIaYIeJ+ua+S5oA9Knh5zv+HGPytAbDSF2h/I2pM7JmJkM0zQCQ5GQqjbkHyOAxfmOQ/da77HzXQ2OoIrD3kL/O6dnL4XtY2NIxUM3ImAXwYtOQ19OAp80IGHI+EKPZGnyr3qD3theNJKWRnyyMGAukAUYWZC6x0Xh3PP+8Z8COGyFz08YThP9d/2YhEXNijPrejgkIEh130ckEnhqO9DoxgUpZdJHWSIro+UtBZL6TEEATK2xik60zcTkHgQ9KWOA4nqkOnS7fMG9zQLPT7UKRfMkj7ekj+4KLbDoLSv9G6YzCbDLZsS0ItnRM82DsycWEWluDppMVIhtfh66Y8Q5Rx/AIm8d0HEFPz48JiEKAAh0WbrBVr07ArEYMXnLMdxRSxg+LjrzgIlnDDwKmnATylKaaoeM23Ouve/9t+93m92DD/7D/u8ElbCJ3+s3VSIGXbdiEoDYeIfZ0cNayf+78bc8mKefwIu6jcczp39giq/xQOD6wBuOFoGA7GJeH+yNtaAr3RgbWUSYdXOMaH2ZdG1+e9t+X8Iyi4JkmoIB7SztfBH9oMLlUuYCJsEbRuuyv0KlXuj/u1emXMF/iOPUzSQkvn3s4CuwtsIOYjtP+e5k/1z2AKNlRnHMxgiY9erjN+hH4z/Ofk12X53MT7lumRBHYlYQh/l0KevgQBqrZLbCR5Hgqdr4vw0/CxETa70lKdQ0T2xoaecpUhk/Ybmr/9OqgfK4+LZp/DBYGpoADsJkyJUWlZ5ijahRPGdYLhw52+5mxxsMGzPGrtkWlKfR/4UY0w7GpgW3FZwrzAwFsnderSEe4BnuEvh3JSKOdb4SLKSYxydxFo1Z3DcALCkvKqNRDgrIbmsaSvUjgqD1O2Z/Eikb/IcLsIQPoDO41GlFLYZjDb6U+49epGnOUiRrVxA/O2Rn82yDN7KTNQXpsfgc2r3kGNMZ1n58Hio34u0MR8LRl+oBpRQNVJuQ99XCQNaaM3JSFIecOYZ9k+3GcuO+jTCuJWc75fmScgNm0wPS7n9kxpYjR+0kGgZP0L18MN/yaW+KNt+7PMgFw04kSJjCIa50T6BbfpWqLn6Pyentwzdf0pAWgt30Gl6bu+b4zRm0AEIIgsdGktPzkT/7k2L9R5kZszMzMuK985Svmv129etWNRqNFtkfzNwuskIVx4cLde19ZJJPx3R0TECQ2mi5Fmrq5H/TF09RZTGTi3l2txMICmm2JZBOHaFCVGHDCZUc6Y3dcit4aSHfO4phdHRpvaToMqZiIYDM609tWJpKSVoi4WyalcJHOjsqCJbT2IJX1siwYm9YEdaI0UjMRpEK9Zw58tRHdKjIHhFbJDSJBmRT6zxRFiVKDjecLukLJfpwnGM61x/Pwzvs6lifQJ9fS8Rx96oPB1BSi7Kk4mxs5Rh2WbKhG3cTVcvE64a91/SRo+PCzaI9B5E7B95KRU/tLBhKeI5OexE59e39jE3nZPx/lPePN9jgR39h+B8gX0is3ghKi2kSq3op20kihNUZqAoYa5/6rkfMB01j17DH6/Y95edIQ90p/9aqoz4EBbVGY5gQJ2VXsROSuispuOEYffjTIfmFKVvvve9dtCNNgBT6UOh6j22eIqDURrwQ08HxUx0U+SC04Cgka6GbS9eX9xXjwdOW+cAGrEbsAJjknme64XM/ybQ/U5pQGki2B+4SpZ+Pkh/RG0KLZJGigsDTgtkgOOTLEVnciZgPG5OMG/45MNS3geN7p6WHWQqHr05uA98q4iHcOwwiDJ1bCjbs+X/gO9CYwsaUyD5AxyBjuHN/fgAOSpsXkGsN2GDMqMVG/32DXXo/T/B3u1bH+HBxv3HjH/h4ELsh80ChgyjxKFv5oQvAza0mHMdejwL6D64/MnRkZI2DJEGBJSUIQ4IXAHEG5sSMClhP44Bqnz2d15k7wuUvZvFvivbVUuYSRnYC1y2ZDIo0gAv9kC8aOTe8H+o0ZVh3nBNm7p5S60gCWhsRi2LpgrF1X89GmymQsbWzYsKH937djNKkxjQHq2bNn3ZYtWxbNUhsWynPPPbf4N7/yK7/SJs0sxOY2f9P4iCwVbJmM78yYgCCRMb9ttSvzKde7DvMwOvUT9BAnatOtwKSa7dsVTg8Rg8mMxRyN5cRk1JixgaJe7pwJ6sALsBCakdN4CZRua9AlxT2No0j1YoGALk55wG7qMxjNlntBuS22Rqm53Fyl2PybxYsdHaVLgvpO2UvKTaCAGCZa+NDJMLWZ+fL8uf03NvxME7kJZo6Y0ZlUB/xn+hwkTKxA8kL7dydmgykEpnhTHTdM2wylnZ1dfP44nwAWCL2jF6ImpTTXMykdx3xncQT6qsZZGr8Ubt65WYYcqGMoyIFCuZbvSaaRAWjwrNFwrUAscvu7VY+GjXJxzOlVMbfF5rfcFDbfNPea0tihBU+ZRARwQROfzDiJrjXZUKDx15IAk1+7c9/uvBoaZl/33beEkaAKaNwDNLVQZ6FdnsK8Jl1bDkrMsjNluDhH8VBqFDAZaQAGaRbdYbFBijZ62heqvRP+vXg2VQ6jkoFQogv9B3STPtqPCGhEuhoWA3x52r+LsNiyCyisxxgvGvNqFueYkyphGDp2hOlNgOucqp8DWRmRbn8i7EdS5Cuw+thR53xtTJCbga6xkdwB3NekFRM9DoClWILEQAfZTDkNyMV8swOOLvzdGTYOVgUZIjpMAcuGgsgkK/gWsThmig/Xb33WczxTxqgVLFXT7BjnFRGLyx0zahqw8n4CWNWJQAaoQr+wGt8tlQhuc2yxQls8JCizMMXxwWPBdTah0W7zfmBHGR8TzsuyhzF/R2NS9Xe6N2oBbnICmwRWsTcyUczKbMHzTgDYpD/J9zTsS86dZB0pQIT3UGAuNGoBKc3nUya4RHNeBVVCAHgzynu1xMQTJHRRvnPxMCdOnHBXrlxp/7+Jw33ppZfa/75//363YsUK98lPftI99thj7qd+6qfcb/7mb7Z/+0u/9EvuZ3/2ZxdZKZ/5zGda+U2TGNOAIYcOHXL/4l/8C/fP//k/n8hh3uMxAUEio/eVN1ye9F3KdBZ0/2qRCHT0ewHgw+Seo7PcAR64GFFmIoWEMcig0zs6XDUmdSawdD6TSDXpp6Qjiw7b7fYgSnIdBn5gNDBVox3YhBq2AzdH4jlgNLDQ3HPBNBtNMaYzWmEmyoxJLeEmxGS8m+uURTdKxoCNGwAuwLrpkJSG+5l9KS2zOOALnh6owdwoKqDh2CmltwE2GurgzlQggkrDPX4xz7+GNBawhNqBDWL/9ZNhLwFNE0GcZfm118JAHjeBr9iiIENRML99dTCZpIRZp3aPCiRbkNlSvQ6fB6V3U1NNijz8Y5JatN/LGdFaBKMDC0TfqrcQUyESUsVB2VW/FIJHxSYAhmARjPZ6tkPvmN1w1DF9NIBeo7VuXvNNf3+kAIrbTu1qyGhm7s4XmTBmTGIG0qAqgFKpFJYVwOH6m74bmx7YE6aai5+RARDRAeZ1NikOMl/mrx8P//eIrEI/kxIWslyU3u3gHWWADzCQGJWqKThkzCQ38D1RpOYiiSIIUBLkxFrEwpKyyPZ4sC5E6eniOcDjdCw0abItLLaKgBkH5g7DAtRENs4JYBKOZTiwUMZaZL4PN/Eal3vrVvhZpe+G7g0CGvW7nwNvIMonxW+Aa0sCUMgYZAq4TfNmMt8ydMe5xlH22/7uOIBOrAX8O5o4j4tDJohiVhKRvfJ+IMOhGrc3QLPAeFBQ9koGmPqNLV9+3/fVvYAxK46YwZpUou3+vdpx4XLw2i4VIOpEEy+FIUGJNtkfS2UMkY0DBrLxeJFh5mKyoMmWk70a0xA5cpzDCumD4wBg4wGI68FUKr1XyfQik6TA3oLPbj0xRv2ugiANUPF7v/d7i/9+5pm76Xp/8Rd/4T72sY+5LMvcH/3RH7mf+7mfcz/4gz/opqenW9Dj85///OJrVq9e7f7kT/7E/fzP/3zrM9IYpzbRuM3/JuO9HUm94M4yGYsRS80N++MPfdbl2cAaobHrKvTRWEeCgxTmcpddpOgRwk3gOATexGlt27IkXWH02LBBjqWp6Hcw0akRMzsCEOOGYTsIpby67AuLdC9MydAJJD1bFykuoASLOOjUH3qPIDhAcEWo3smBXUEaPDuROnHz/irRZaPHCRfMjus8zxuAoFiySXs8s4hJppkqHPEZAde+BgUHgSTjwA6p1WidaGgB3pVT/uepC9iESoFhOnOUbKxkCgE6TGLaR20/mVY8znESN0q0KJMx1GYxmDSbUoKUfCa22Y1jgiK+QoIJGUAJTIjN8YvHS34QABO6UgSx2s+B70MGvxPz3SAXq9aLoz+6kUwjYSoRAZ2736cMMosa4OmVw59zZ6/VbsuaxH1g5p/e+yNZppi0hUI1JYCrMcnQmxMQNnHM8FDSmE0z92GONaaBSxymAGbc7ZgNfoyur4NzUWz+5WbdFMNLHJ0OLs57bO4ct8aYOZpjTJqIYSjQlHmpdP/IYDFaz0kTAPchi14Tly7ASUo2CzryBkTn/T1GWkOwn4CENg7MIcvatpTBQtlca8Sj1qft9eDaZvxGwN4wgLywOtjUWGrErTlmHicNpsWjhYMAC1lYxutD1mmycaLMN8pr0fy6+wZJOEoXzRJK7EJMn/t9Zn3Jnr+Kxru8V8ZI1PiafMO6cCOMx6heHWBiZEwCJOOHMu4xiU9Lnd+MrJrsF0rKFDSGGamZCyNMknEgJwfvIe6J9bjNvoEsMl2/7oFHRT1yX3B/4GZnZ5fkf/G9Xmv92GO/dLfW+hZGUc67P3v98+/7czIZ3/0xYYJERvHW284lPUtLZPElE5/pxID9wLx2bg4zAVEMGszPHLMpN4s+ARpxol7KiAEf3BB2FjpGY5ruCAzGKLMZ0+Wr4Y9RPW0XqZqShcPH7uvSrnp1w97gIkMzOu1sktLNLgZBCBSTRq4gMg0ugDkMzwjidO4hAkkR4KZ62XZwuSnnlpgbIqWPmoHigQyiZFakW4hJNBsCbN4JZKWi9Y5tPFNoohOmEMn5ZOeaFOSMen0pRGp6qUBOY+IXpQufnsXmF/d0SeCHBRP1/nIO+OySLWHkPC39HjrmI76QqHdvDXbn65591vOjeI5pDsjPFJptfgFpULwHEGNaw0HfSLI0vQnyu4yFndx3Mep5ZQqOenHzr/MQ5SgZ5DT0D0oQA9u+B7uBPB6CxrxOSlMmSwRFSrJ6d1R2ZSJeT58P+rBQ1qiFoflM+ikxNYWMCAHJSvqaIHEpAahHWUX7Hcikg3kn169arieLZt5rLN5oBmiiVkVqSjkli1njpdO+Oe5jFNAEqjX6NeGayXuNcyzurXKnvQey146EmZjsJgsjzESs83syLpfslVSYAig6631oirzi19KKMc9SgOVkqZKJyOMXiQCLe96fNJZNxIsmFrFqgA92yoWlw0hUDsMYkcKwfPv4fcGeHOuKJp0RBIit8x2JBHxZuGZXiD3lfqQjTeJejQlHmMcU9DDPOBtOD+HcIJGOkcvt6ynhIOiLY1aJWnYMLBlcGyPDxjOk0eks9CvIojMkxZRvyvd8/MD9wTOCqQJ48jMpzzHzqsjCjQktQBCClwTKjXSu+TuaP5OBg+c7k2eDTB+z5sQ8RTDHpvXQufCj4r7fI3InYzLe6ZiAIPcZLPjoIJ/u3RE1yyJLxDiBgwZY7LWb+hwbXLMBQaFt0gma46EGk7KTyISgsWumA0r5ATaElXQUYlIIMzh5M8JNJ3l2JNhdOCydPGxOyEooIkZqxmROuyLMZ1+iyRo3RBw04qQbffveG9CR5yYSbAUtXuqTYYo7GQnpvC84q+XymX9zV6vYjif2BTXqXNj1XqH5ZH7Cd81rjXzkdWNhRrApVgg2A9KpWEe8fM2CZdw8xyjQKTaXpmBs6fv+HFZvHQvKVFReRP17vdo/K7mDBAcbokoM8OqV/lqliDk2JRJ8Rzommdi4MTIyJaAhnTwacZJdlpBFJvIm890GYNzAt4IFDrt17cAxlDPYIGO+rJDC0x7CKRTUSKHRyOB3nAiAzf44qrdJ4OI5QyFQC4iSwIOnPuffO7uK51AL9RuM8kUHE0kxjKTtxNVig8yrxr9TMifZQQSICsgPa0alro37qBjgfgx7pNqOzjWYZ8Y4EfewiVpX1lEMdB5Kkf3o3iAIXZ+CJEoA8QqeGPSwIBOxwtyTO2uYzfmuhi9LGTGTbd8b59rIQZi6gmPpeC4ALCBDjk0QnWMJFEfZpFgXCG7osZGxQrlYx0BXgK2Qd5dJtFkvTBA8u6ZoZdEpKRuUPLDojbFSdKQ8Hkp4xrGuAAjQV4UgDIHdEmky7bEtH4TN1bF+KXAS2+u4rwLADv9Fl9nDfR/90kRyWGPuSLBOcb7h+mOYqM33ZpPsxCB43dNnLZvVgcHJeYmG8BVer4mHBObMs4ZnoISxefse52fDKTq7aYKM9UvOk/GCAduQwI0yhdnojAEi2RYLKi1ct7TqPVggyLcxIncyJuOdjgkIEhnpM4+6NJty7igKchTXyXU7C9X0x6A+WWNpF4b4D3AB44RNJ3ClDJtYXW6KZ9a/Y+MrsieIdKeIsW0HdbugMlIWwQ1lvdZ2UZLLN4JaZ3bR2cnUDn0SWUgqRqsB6Ghfw04YaYjsAIiGWlkawQ0dzSKRpNGM3mEUbdh0VG/D4EwZKzSnw0aD/hakfae3xXUepoz0JqCO2gBfzfFs9sfQf+1EMPbUKTOZ3jhr+kHvEoI4Hc+BiHTJSF507PSgYXoJ/i84ZxWjSsW8lb4y2WlfwCYbsNECONMpWuk/sxHgBKMI40oGl/D5wjVUU0qyL8ovvhQ0wzNNZwEX8hMXw8XTamyC1V8DHgQVTAirZz1Il2OjyPdqvw/ie415KJ61TI2DCXoiVSjv5e7zP9l3vf68G8733b//n8MSHoKJ9BaKARq6kR3hvPfOXQ8C1RpfTNB5+Oz+oJEon6H27x4GS+avIRGgueIYnwn6t1Sg1SfoBlNC1X7mVrC4kNyTMb0BTJbqiD1mAosJvHiYsKQeEtUyaPFvgfkAc0QmtSjIaQbXH0j+EqQitQOMJBZjCYBeRvze/Q91OMEDwE22e2cwJro9HnbUt/j7K2FHXjfkKOzS/QDfOMcTQBV2GNlqvB4knDA1rVNEg01q5AeMmFdJFP5tmD1jwMiMzzG9DSIeEAkjglsmH/YaWPPHeXfFRsznofN3kHmwGB0nN6PkjufNsNXA7DExzwKgEogjYygRgCkWcU5wg++lw3xO5Hxqk8wyZQf3ZQ3rGTd7TzbGwPRio0HlXuWjYNgdw1oCCa8xUVZfMACwhjkIs+r2vQFSJdM7g+si1/9kXsA/bSyF9hySSFOtABBG9iLWUgO8NP++t55V5bxzS7NymYzJmIz7jAkIEhnJ4ZMuSfpW/0kaPLsrzd9fQNHJiL+o6ZKAC+xIYCEwnXLpEHHRirlSc2Fmwdv+DoV/iQ0J4wqVBVDvsa7loY3ScC0WHOmmVutWBDeUlA7UmyxSP/zww0Ejy4xRq1hIChamSodFt6pEMacxrkx5YGFXwXOBG89K6Kt0weemwVBGlTlBI62jJ+8bb9e5B4eDYNSqW4eulp4bXIMKG6+UHRXxu8lQQBWrsOngH4FyOi6+MSfQAK8N/W4VXjOCAWx+EwUGALZUzD8rypVQZBRrQH2fsRuyqUMXg6CKMcNjkagmpWQKUWrDjZ5I3HgO+d7pmStBCrB21E33C/c9KbvVWguEpedh3Agz1USeicXXyz3EYyiQYJU9huuush9uAsFEaa7zJ54euI0r592l2b77fy18B6aHKLDImEgWg0K35/zdY8FCbx+e8wuy2cVGOPuLF4Lfn7TxZvSPYrcK9slw88rgPczPbweue1rj+7DTLb4EKfBbA25v9IVpNYWl/3FrOJpzXr0+F/wcLZhoKpxEpKH14/5+yGDe2v4Onj0VJUBHz8RjXAkEkQ2Dgm0s2IKR34uf1Hm52iiswsGa+ydOySBERZZLibW1AgtBB1kRyREAGpSbMYlD5BRGXot52UTsCoOJa5Z6f0QHfVGW4OmRzYiRZsQDwngrqJwFSFDKKFysWWavpbI8fb8lGHEaBhGlMgTIaCYL0KMDnOBZScsx5w/Pe4b9Ee9vw/bQBgskPGZwLYwwXjteG7wfsWdR5h3/zfvLSNIk/Yo+TrHni1IjA3S0bD2sZTSqBYDM6Pf277A3SGcBBnLNJDtbknuiTCOwOot34cmkRtAL82/1gBmjNnO3mb/f5XtMxmS8mzEBQWJj1zbnsoErkHCQTftivFDqex6OzeRgZGU5ECNNIsCU3ZDSLoBK9fDu4FpScoMLWUN6xnoeUJJDjTbpjtUmuwnMsClmh4tmib2X3o4axnKqqn7gA/7Y0NVLuQlv3u+aPwcpEHVSeFMsxrXEVLpZ0GRh0JijyNFulSku2V2ATrbeijQU0VRTgkNApUZUagnjSx28HgkKBIfrXNBYTzrCxTr/msExAHToTtx9D0i3qD2HLKHjOXDNbzR6kAhU6GiX6MDmx8WfA52s+gl0usF6crg32mN4y3erc5gKpyjUazyTBDc0xpWso95pMFE0mYNxlPSHILX1BQ8IVGLemWKTn+Bn3mvGgK85NmxW09PYCMNbxySw8N5QwI/gAijY7kXLzClQgPH1vD/Z5dWNp9HVb/Wb3Qqde9Xrc4NXrl1mN77/w73jaeahBYBC07eoZWcHlZt9YYSRVTAieMcEFTJU1FQU8zI73eU0Nu7SjU2WbQ/6IfVZaM+AGYT7qR30PUJh2/EOwaA0IoEcx8RxhpM57x4DExZ2W9nnUjrlpvgBcy555VDYILp5PxTdJpkEBZP6kJiYZKaD6f25hBEzU822SuoKJItLs/y2shXj/UWgl4kwYySLhhF35mI0atWcA/pOgP3IJogm0sSKNDLSOvsJfjeC/fThwueMM7A1EgPOicJk5LHFzOnHfQ6Le34mgQ/1BKlRHBNIMmw3yB87sh88OwR1VDJhBgxUSwDdhnGJ+UVZIeZ7Gm+k0dKAMEpVlxAC0BmUUUHS3GFUg5nD+5NzyjgAIaEvGX8Ge7TS5J2IYTPPB59VE5AwRp5r9gzqCRIB/Ix5tIDbC8Bz3XiCvHMv7u/dMfEEmYz3cExAkMhIbt1xSVq5XEwEY13f7NYoiDpT40/jxs4gK4ByAxTDjJxs3+8SivitkDVQb4/CMJGiOTvoC8tqrz+2DBtngjPa1aD5VvI2TBzREemYZZHxgnNrNlSy0XGvA1Shydxj6PZTgqSoML1TGDPJbplKMahvRYfGyElgUFltsBudegPMQ1HMltvWR+ODs3O4bqvR1VrRi953HKP1/rsNLoX9YhIp7LKrMAxdA4YDKLw1irzOppZdW1zP/NJs8H3bv4PxYkKQD90ra5Bpz7sxnWU6CundBAKbOuDqjfsaYZYff85+TwBO+ezKsOcBCthyhX0+h/BOMZKR1ZBZiKEuwcC5HX6zN/Xy8aBUiaCgsr3Ss9AX4/moYD7X/h0N7LgRh8dMiVjfVORqDtedBX2Ka5iKUR87k9lxmAA3Urre/3735zRdLCCS29LJRBFN2UtJIE1GfpbMnovBQsLcdWKgF/MQStkZFsliLZ5IC2P+EQ82DV5FZ1MKrgryAxOlSxmVFCVcf7Lz4Y482QG1REYagIP+B4zOBfOxMydwLcP8YEwDJTKSRTvBw3FpOZQK0XeJIKNGxxqAhv4rjE4HoEDGUvsaMKVUEhQblJcaVgaZnWRRiOTEGESi68z3UuacYThAmsH7aaxJdiwR7eWDSwKByIhKmORE9kknIvfk/Y9tTNIN7yH6e4wbKZodlHNyP6ByHH6Okf0wgWvvtjC4L4NMrWqMhxHX0HQTJGLnI0lMYupMc3VKUAk4lmftPBL7bu9mGJYJTWe1wcJ5haarSzwWExZAIA3nL18pEfEANfh6MmPHSY3US2wpzJrYMIlPMqp7v3vQmCCt+XXyLTI5ND1uMiZjiWMCgkRGde6Cq5K+8WCgkWcGZF6LW7pfG1NP4wpuT300VhCby6ovLv4oTnO4/XPjaDTVmcSJYQFOCfZwQgEA0b4GUbwxrW9Mv9r+jgkgYHyYBWOPZQGkJ5FYQer6LLrB5/3nZFfE9wKb+gSGhGR76BSa3IZMA/RTdt4NewUFpxaj7ETl8BHhpq8d3LCv8t+hf/Z6ZOMsQAE274RKElDXK+kYVpGigve6MpAcN9jsttxAtwdFjnpe8Xc1UzYoN+AzJIOAG6M5K1yn/E+/bl4TM41jly9/S/TuTCIAgEitLunITV68Oc4PPBKUDZkhoFS5ejr8HXBvjNag4FxnGS+9y7eD8Z4l/X9EQkOAhiyflGZyYBkR7NLB3xVI1sjAgOoUHCjmmv/+zbeHbvnyBrscueTK9ft6ERivJMx36dW4nIVJMQU6qCa9AsaA7fsd2BkEGtIzl6PeQsaDCBv55K9eCksZRPKYwjuk2Oif4xSgVqeQOAH5QoQmXDKpRdPEDgKUYqeaz9oOG+FJGVK503cz00MngulVWsiY2EqRYPo3SOOAPIBVQyMHQ6T9HZ4jzusGZMPn5Gft6+vr18ORpPQVUE8rmv1eDnfReSw0SdeR7YLHCsBYlaiZojHGcsE8wE55O8gKBKMqaUwZI2wgA/AwBhUR9+MG9w2mAB0D1hhpBlgENVONALx0ClYBof2Lqqh02SRowaw+x3NUvQrWk7Avye6lHw/9c2jY2g6CA7hXlmoYzSZCTpkgGwpS6HeYVwsvMQlD8OJRk+7IeU8QKqDPipmv2AzE/cA5miyh9jsAJEvhF0aWLJmH7d9hHkmxvyWTkJ/TieWNRAbTG08T1Qyrj+Ay53V4DrW/u7dvqquhc0tUqE3GZEzG+DEBQSKjMYJqPEG4ia24EMmEn2KzWKBDZKh7jDXU2DUM/i6WQ98eIxbn2EYnhW5aN57GqwF0dxp0qra0XLP8vhFmhrouIIhJhOHCRp+Fq6LTpW4Wi1G1FpIRMCeqgxacYTFHZ28jWRF6tqFFYvOfQU7DbmwpqH/NDi42dyX01ZoEwcFNaYkOUcLuhhRMseQds8Ges8ycCtfTgb1hBiiz7WvEs2XxvzPlAoUI40DbQ8OGjAUoR6cQSLPwtYLpq/HtUJkJigcyPMwm+F7BHUxJWrU6KMExm3A1HmYaBjvdAH5MB7353WEAPGQn4VjI9OL3b0a5f1swqpqRz2TfNGO4y983PSbHoKA3xm7ie1FjvhhthM/O7VG8o87CAmBTA9r+D//P/9U1teeWNXPu8dmz4YhcFNTl0RNBvxpjviqmr+meHUGguHrtUNi8VApNI4fBPKYdaMpBDEMBwE0J34lagNHkYQ+85IjApK8Ok1U66SpkPhAcgDkw2YYdI0z4x9DgsVhpWU/9y7i/D/vvUD7mv2cFCWhf/VoA/iWr8Ezwfr5hC8MEchDDfACA7GAS3h4DGgep+JIsjHz/njCA0b43CqhbMJAl00o8AjhnO4JavNYRs8lxwwC4wkAyQHVkMGpb5TAsRpcqf6AfEQdZFQnSXTpNgCUM0+mXY6PHGNcY44ckhX4GppZhAeC5obeEDkpQOIxRvYDGNWKrU4B3Jn4Y/j13/wP2TcfD53kcC4EAhRbxsRGTvMVAKfUJ4vk0BrSxpJslDgOoiAzZ3A/05mN07nphpmI/UR4F4xKvIRsq22CvTYl9pDFbPng0GndrvPogGy1xf5qmVPN39wDdqpHDPEhjIoeZjPdwTECQyCgf3umSfMoYZlJvThZFM4oNAA6GYDsgRtbEYu20XUY66ic3gWZjwdHFxzAMqOdkx41sDemkaRb9Umi+xqsC1OA80oXpRD5GTKS4UapOnI5HleJzTNHNTaB2e8DAMZRVLqZw0O9EDmKzy4LLmIWpnhbXxsRM7tgeNIlt3w+bpRLFWP7wvnCn5JJ0TNnRBVPJACrSwTWRrNxgkmXyyF6h/2NzwWcCHQ3j/SIbzxTRd6Z7yO4jZS7CHDDvxWOGZMOJr4y5V0jDxjMxjoZOyQhBIbPpkvuO9yRjYItXEcH5kD239Y4tYbNl+lvs2BpnkH0FQCeLD6ZKzNlNef/t88FiskLiRcZOFjbu7XtT9vKFF/3POH+UyLXvDUZWiu9ZNfPV6oX3Sxafw3qMDMwY9VIuIJRwRh6SIWBMgAliCKvDMMf47ANwLPeKcfQRGNWS6cXriWKQ3cP2ECClI7uMc4VhUTTHQP8XJrLACLresCLKdiBLMQcgXYNt5zbY+7aE/K/asS7ouWNShYRdZswJj50NzteJFPqM5U0g+aDvkzJhEjB4CnSEe5Q/srs9awvGCl4PxoyPvjT7dgc7uO1Ah9/4upDhgZSrZqRHAIxGZD/JY1bOmdJcHfMdWXi8v2uJ4yQzJrpJ1HWW/kSQoBpDeVzDaqWkTB07HUx0o88OGSLjZBJcm+nToCNmSmkkQNpsiDSfov9dZMgOTIjyjcPBopuNl3awKYCCeinfX997qcOYKlOOStN1PLeJAGl83iswisfFD8cMac2azc+R85SDPcHEJ8PYhCeJfg6PjSluNBMvMIe0r6Hceo9fY1L6nTDKSY47IQhNnzgkshG4T5t0mKX5Pb9PRh1lLL6j95iMyXgXYwKCREb2+lGXNUwQbk4OoCg4Kt1tRulh8qV2XT09OGiGyoi/5JF9QU17O6CzL4huf9nG7y6+fosUwKS5AlGnfCQVdL9A3Knx+0DRbLTzER29bvgLxqvKZ1bQ/FNfy6KTRXMyL5szbpDZkUfxUwllN70yCBaG6YE94S6QmJ85gFzZIb+JLWE0q/4eJjUFxTHlFzVp+PPiHwAjTIeukgEhYIar3WHS7bM34VPASDrd7OK68/5Ovnkomg7TkQwsHkBY6qQjtokyaUHiZWM+Zit8K148uLSIXjAxHM5TPi6lg1Ih0H5zUG51TkgvYFPOLiE3/yiSdLPLVBzTccOhleM6tYwQpSSJ10w2LNWpM/eNkKYvQPuaN30BV9BMrjn+s81n3f2MBTlMJ9WBbCQtGBb+hp3AZjClgQU0JUCcUyTCs0bxkl67EfY5wnduvydARz7vi9+r3R/XYUaesAqrff69ei/4jXsi83p2Ad5ClD7ByLous6ippmGC0DcJhUjvosSQA3jIrkAWt4LAqot2RstpxOKiAGYBaVhrzd+RuUZmCe4VZRuwA1tvhWwz4sdQ/Pjz5t99yM1istMUoHk7KCPCd+Balg8pHROKP9af8iHPDCp3eA+jAYDMZoye8MVk/srRoFcHmWI1ots7+xHsDch6Snu2SNP49RDY08iMF38+as9TruyH+0iFtfCPRa8T0KBEQk06+ewlvJ/kexHUsdIQSS9a+AyuHc2/0fmPghPiF2aSZwDEddiLC8f1kE0WSciYvDYbvrYKCHFe4hyHvQUBokzYtAQHSjQOquJ2vElGQIKgM2Q7BOg0wppgKPdK9MxRJgrZG+UTe4OeeSnmIfXJK5/cF/R5K9f675b+pW8OdDyZAG5nr/p1cf55C273rtw9n5XeG5MxGZPxrscEBImNpiObDcyGP4PvRr1ZaLak4mPRL0AHJp1ZQ9WNYSUSN5Iro6i/RkKPkUP3N0sapx+N0SWZutJ5PxwP9dGM6FW9OmMNidSbod07eEAYNg3jQM8ixlapwJSGoNMby7tvP5PvwSjhCP2V11+7vjxPGQoz7YKYghaFcjLKgxTmWjppNan8e3YGu4LuhMTY8RwO0W2ZQicMdM92UFpCwzZIOUoUtqmwbHh9h/s9g6Z3Gfe9dPzY7U5IY49QdhPxFaAuOzvsu3TVEwBoxNeFxmr0/Enhb8FnUME7snHYxa/XLQ/OKe3fbcBG8hCKLDKgAIqlD1vgZrjZX49+4tlM1RseBak/6Au29rthU5WdGQYLVcYK1tqp5rlGAVqeOR+XiRB4uQTGC+U4rl68P1VXT7CG5oAseJTGb7p8ZAuAlUDAUEExPnssrgka0JupAwwCCDOdYnohAPBtf3fKn+v6BT/3JABwS9xP7fe8DGASxtgV5Htci1RKwdcwDUQZRNG0HoALBPVqmghPiZfNW6fDayuOhWBwRw7J9IotYCXutAyHIZac3jUUds8+7o/5MuYeGJ43o4BUp88mABoUCqiw0EtZDPK7UCKx03pQmEhRNDgGZHhADtp+tzcA/gBcSFmoEyQUYJpGxhX8Y9wLr8YL+N1+XUjeOn5fM1QaJ7eDUk/MCUsepiAPAyLVBfXaCINfOSR6aowaA+EZz8r9kIKMPDYXmW8UgKVkg3HSTFWyEgsLatEzx0icMfflCvYwip2JUxWaCOcu3xdI1GPjPrQYA3DRr8R4h5B5SElX+4aYo05jLsb6ac6/gOUpJJxkgtRIu9N5KAdjo8aamb7m91aJMIWZUJeCLU7AdHBK/Iim+w9mHOxEDjMZ7+GYgCCR0XTqkrTvyh2gv2Lzr0ZkHGbz/SW/aalpUDkmYnCpI+aArsaHi8f1upW/UMLCUUG3q8aN0cVsC4o3LvpYyDodFiDqpoMsY2Hybwd04Cx43FowMXaLfwComOZzSKsUumJMrxwDizpsh0sRB3ZumrSLT58YdmHwcw1Ao4K/SPt+T+G6Uz+/BnRLTQiiyRiK2cYTZ/GYlc0DE0BjDrvKf05O6ZV4ZVBC0z8JKcRadGQE8GMCiEltobcE/VpIUW2132DGINrY0PJ1U0+mFGQFCWngOLcJ78HmHnrTg1KOnj2U4Mh9Z+jN2CCnd/CZr4JC/bjt+A1eOhY0ieNckTN6Vwooxupys23M/N6UtATKTiqweT7wcATccK4AMJmCLcBOXiOHWQATixdswgLZcm7HtrDGHgByx0SPbDt8pokzhVdHMzLxUgmx8Dpx0HhWyBQyoA5SvpKjVu9fEAzkvcLCEvHJOiibSV/wbLuS9wMlac0lRKFrgCNQ8tX/gUVfeuVG8O/Sq/DKQgJMx7sEm3wDtMsca8A4xsrfwZx0MQ7AciQEATB3UA7b/huSDQfj3BL3gJmrxBOCsdM00qTJayc5BxT/8ll/DrIL2EOoeTW9twgYYo42Eh6Z+0zD5Oz5sARUJcFgtsRiisf5gJBVEfOdMMwL+TvTvNFI7SUMroXacOKgQTBB+ITzOvZAGj0bHUxw0TX30M2wwTIlVbjOKgGqLsYlQf7NwkyW9njAAI6+fIwEh/fTuKQX7s/q0wDR+UdkwqCp1v4d5eM0SUVaj5GcCEOvBkOxfBqNF8r1xOS72AzZJ05hNu3nxFIaB0xgNPsRfhdJuKt6d9+8KB4wEKTd307SYSbjvRkTECQyyq3rXZJNGXpz9jY2dNIlLChzYGf1KvLd2QG+LiZvAB5IfTddFDU/I8BAuiQ09mYTKUBDDWpqCZosjeGoI1eDRGN8hcKKZUx92HZBaPyUkpaJbpV2teisXe7xG/bsIpByg+bLxncXvABozMbEDG4mdOPCgosbFYAG6q9iOqiIFTSO/OxG60aWGwrG0GLjXUs6T7UMXQgWbDAVVZotExscWD/1hUthf5RmYAE37UwUacagU5Ne+Jm41xNQW9PnECPbdmdB510PMBH+B/XXsAn/oO/stv8G4GaSfLCpnn/CRjb2zwMEQfFDL4IaZo+k7HY01QSCaNgpUo7i7WNhI0vEmHKDm2lSy3IACtuwuaIxqbAVuMFN2RFHyghpz/R0uXvQOAZ8TxbTOgheVRvBnGvmyFNd2Uuy2xYS6Syo1gAaMsyD2R6w00TuRXCa3iE0VExe1WSsmWBBXmOON0yeFvxJg/OlSdFBwaRFHv2ACKqZIlM8CwwgACZG9aSXSlW4H+prdr5M8R1oZkpwwQkIUuM5JGPGmPvRS2edZU3l5Y7w9/mITworcM3a19DwGq9JaOSM56EdlGUB1OF8F5N1KAOHay6LJP7cuR40UAVdP9nh7y0tBziv9L7igaz64d1RkJHShPaZCkgGSxbqureANCLfOhMEtRQoiLEvYmlxGusb8wszzQ6RnGQA6xciRHVt57OSiAwrgYdDBSNLYy4sJqMGsIsYH1c/8ox/wTFhSETSRMi80HkglajnhVESXEfzTY2kadyeMbGQkpUlRj7HhjKDYuufOX8qQSUwh/NE81Ea3XaeVe7XIV8ssDfqHbXX08S60zfqRCTiVgDHnPMNZEf02VF4iR4lBtzFPrbaYPekyVdevvv/D1pE7mRMxns4JiBIZDSbijrPjCO9MQ+TjlL+VngBr+FOT51tsV58K/Dv3hm/AOZMKJBI1BoTO40XKQUwFH3KZ5q/QzcuY6GPhTE9ZDc69U5oqqm9xgZmnPEVWRGknlfHb0eL7hqMh5odEm6wqVkVOQy7XBWKSQ6lzucsWlmoAgQxrBBl5WDjmgFU4sZXWTLmmFEk0UCOXQsFtWgxYjS0YLwodd69AO+PpxDVthwa2jW2kEj++hvBY65/yBuT9rDxY5Hbvt9KFGA7/P3dv3Qr6BHQDm5q4d/Ca5Bgs66yWVPQM2aZ1+nPXrAvYvoR4/7SMLiSnbcU7uFT/rpnN1EwsTN70IMe7Xs/431yaAaazPfDnTRNBkFhQfAwh45ao61NbCi71nv8s56+dTIe7z2DqO3XjgSPpSPdQsJBDY+WHphB7XdYSCQR7xQWfaaLDcCv8z2vItEFRrHuAvw5CKpBu99+DmVdnG8AiqkszrDysCmv0OWjNxJlR+1xErwDsMr7rpICmHTt4Rr/nacPXQwyTgr4RzSjdx6AWzoIm2VKAWvMWCFhyU5dCkvCaMjcHOePPuu/J+IsjUzjB2x0eo20Gt4PZo4VxSXp7ik9UhB/PEKcNY1+O+A2WREEhsfI/4xnAdcSAsNSZBl2FKUyJ84Hu97KIuMoIxLDelxCHSWTNKgU8M10+wkS4npkTAmJSEt1UApYnrOdf0o76gi7lmtzR5YHE3rzOwBkBFY7TFnsJ8gkyRFrT9lWx9SYbBoyi+TcJJCdjtb5e6WPe4WR6Cp9JhDEvyOrJV9ln2nue6Im+hjjEg8JfFAiXZ+RFBsylShFn4HvERhU5WHLSjTsXEh6e/B9YhpZR47C5hPjgwHeKUvJzIUbAPxch7xX2LA1QWzu68c0ERYaFK0x6kt/4B6Y0TTP1Dj23bzHZEzGuxgTECQymm5OUpW2q8ONLw3fZNR4IBmd54D+9uihId1taxrXi4IY7ORwsPtWIxZSqYcZiwdstCpGygmtMr8DKia6MKQ306Q0p+t+M0BTpSaYululXpI6XiKaMT8BKQUouym12rqJA/W7OoNNPRI32s9BrGsGmQO7QmbTo3paLGCx6VllS6Y7gIU15SKJTgcTidrXHD0XXsyxsJpubnNuN8Sj/BZfLp1io5+n5n8Wzwc2bQr29K7eua/hWQ4qbDPK533xkV9EtwU+Bw4d6FTABeriRzvR+Rni6kjM9PD5/cG/o5SjdwUeLRL7SfNIFq3DGXSgP2w9c/g5hr2CYrDazvvbslfI8jCRi0zkoYQoAFItvgZzX/norqhEoL7XoWoHAMySxc81C0wWZLjRK0mTFO4BLvVXX4kWc6aTBjmOjnorzIpPXgyDOkyVkMKSnhbZmUvBtKRU53VKimDkmdEfhGaAwkijgSuPrX4zHp2eoQs8mIMRJ9NhwMQg20NZIim+p0kd0649U3korwG7LEUsbyJzX/7WmbCRKBMmRIKa4HsaoBtztCYEcf4miEEpQB/MwVo8rUocg5m/gbpqXL3xeliO68u9BWOn1TgacyTXc5tEYZ+vtL8latgcKrQN20IKPTNfwOeos5/A+Sgia5lJbyKg0q4fN4KsBK7fKrkwflsowsnaqo6dijJJSpg6m3OA66HGrDFfMvO+z+wLmum2g6AlpR247h15LY2H/wbF8XY8a/CZyASgislw6YumnlZlhJkTG0bqrIwPMGsJ3HdYpoy9RgORCXc1vaakMRh7boyn1+si5wTrZpyvSfxzcD7f8sB7yuh32R8awI2yIa4FIjdb8AKrFdl9v4+JJ8hkvIdjAoJERnbttsuy0nQTDT1dstorIPKGusiFDZTTUgpYFqfs5DEmk9R93XSwgCYlj4ZamVJBibpzww/H9EwK2BoO6iaelDIRTOSdQZnFI/uDXb5c5BMVFgljFkUJDGnKYuZqGBPo3Bg3ejm3Rs8qHeWFkdBTReLhcnQEDJOFmxPRs7LDX21cEzSGZccwv2i75pSgpJBbUTvf6VRzoWXngwUsCyFhT7BrabrzR0DtZZezGdgc1Chy+Ewk3Ow33/XcteC9NkIyRo9MGAAA7fuBHZTdgXTtG5CCiFN9/vrp4GaRW5CEoBqK5Pb9zl0JeyOMkVebjh02Skx9YdFt/HKkGGOcZM2YZolUJUqX8p7c6L9PcvxsMA2lfQ1AseRGRKqj3TPGSXKOFYYB/WNig13KmBdB+zsCD9z8YyNe04yW81tzmsheYCFErw8p0rL5jfc1YiaY2qGkg6HGv6NZZqLm1bfQgYQPR02PGFyPwf+fvbOAkurYuvBuGWOAwd0dgiYEjQdJQtzlJ+4e4g5x9/fi7gnxFyVBEkKI4O7uOuhId9e/qobp3lXddxjIDGPnW2ug9fbt23XrVu06Z5/atmiM9PSE52q4AD8HjmZRnL63ZkPiEtiLnAkWCQ++tfQejoJzflsrjJ2rKjHutYCvzbw6y6acFFXJ7SEubYR9cgqYPLnGmolEgAiXH3ZWNVmQsNIpqYKWK0pxxCULa27EY3RbbqlR8jpi801ru84kjcdEXoII/4YsQJj3kGAV5Im6I7YwnDbCizKRZSSccJUux7eJzZut407CqCtMRjjVh8eEXF6c+mEfl0o1wl7s/PKHEl8/OcXP7ANHMvIEmkRfHgO6opaV3kvHKUgGuJYQpz/TS4ijfoTbZkECgtXf0vWnIK8Ra5GOxrEcVeFzIp4Ur+uxGEm3fU5/F1dFbDfineud4hrf5uPnlCrXHJfPyaVkks3jiTpOtZ1d42IV2f01sUwhniBCCSIiiAcqKQgVCNrVTUiQ4AuuJkwX6gjn2vLKIK1ysldI3gao92axggcnTufr8zDqU2zWyCZrbu44X/QpKiPshNhbn0mDmACl6li58DThc0MkLcMvqg4TpLBpN4+bV8TZpRvJlROvkjoDVx+FoXNeuhWmTCaYcaV06TfgFRVr8uaaC9agiBdaIQnzQMGNsiGxxtNPgXO1OR3ICbPlFBgfDW7iolLIlIsHJNYAlwdKxkOAvFwo5NS/kY4hlSIsyAzPygmmwYhqba+ogyKKuIJGMpWGVPQ9rd/cpNdQ1BJFHoQowiSUbJ9fybMSr4TxihkPVDjlxi3jGkxtnjBqySpf7KweIUir+JQOYpWJpvB8TZjbJFcLoJxq5aSWcFvj9hHgiDbO73Y8d9gQkcN8ebDuTmB9+7VOOEA1g82M/PNSRQef1mTDXd2mfjFQp5ZnSHiYypPy9hT5vYS7t/NM+7JWZ9nngSZilhhrNpg4MsWKIiDhyV0BjiyKVXnw1auduEIBpYWY5ygdhUvxsu8S+yZxqXS3j/RR5J4Vau70PaCVWistgs5vLg/rd1IMWERmgcZHKUn+lk6fwN4+JLxYIp9bZYR/H27HdB5aXhlu2g9F0LgpPZ4RDpSeal3/+FrUoYWn8aKfo0x4sYM/0/GM4Akpl+8NKLpOsVjlRJJYghWbQpOIwJEbLtaEnAQ7N7rK2mfqFwsd3s5CFk2U/Zt9CaNF4ifN1O7ocU4pdk1KrYgJMipnsSaJBBFOITb7xtGxnJpJY5g4XzNO+6TI2JBHG2SD6LgFDo6GonPN70SCKO4HaExmRQnR+FZtccr1shBUyDQo9gIL8xjIy6/EGRNb421ua+xJ4hG94/ZXXuKl2zZZcLJ8UVi8dCJevMQfVaNqQoNpQ36biCQ2DRYEYc8REcQDX04OfH6fFZ5mHThHTfbKFVYUls+DUHe71kCaBlEFTSCtdAwarEXYiZpWUt0Jl1cOredFxVG0rdQQjh7hFUunAk1wCwkcHiUj4/aBTb5ohcYrBYa9V1yxSJHTvo8GgW7Oq5eDuVf0TdyFle87qzKeObTuwCfRKg4JZFZFAX0M6NhYAxiaPMVNXihX1jJupEGw1zkQVwqYjWYLyA+2fk/2b6HfwxXiOHKA0wp4MmpVDHFMZxX9VhFazQx6fL55Dwl7AbrNVVN85CvgikVcjckqDUnRK/ybuUKlVW6Pq9vQy90UARavrN+Dz0mKUDHbpn3LbUwhyAtj51d4Uey8D7S2vWh8DTol9Dvxc5lMp69RXFLcinBIxbgbK6FG1R3YuDUdVzyb168p8oFxj2eYI60oJDzoTAQiLPRSBFJge+x1SQtWJ/YN0ceTUnL4POJJAQueBurXg3RORTjihNpDXD/E/XqlxKklcRW4eJDO6UUUBRdi4+LZTuUI8ibgqCue/LllksMsOFmVoQIJz1tVz4k+WbY6YVuxrj+OiM+RTlZpY+rH4lZ5d65NmAroJWrxqrlbZSrsIZTHGV82ix3rIIlS7M3gL8DfgyPvOBIlVIcECcfEl69f2Lw1cf/CfRqXUXc9kDgiiku8O1ElHCXCeAkfcaWZ6Tx203Cj++mIiop9xTzSfgp6v9VW6byxIjYd3L5st5853y5Xy+Xjvc71gkxKA+wR43GdLai6DVOQaSxXMFRbwgnbg5VO5EQTWecxR7CS0MvluM02OM3Qw1C3oGg/xjW0LYxgaI1HvM4nx1OEzwkeK0ZoTOx3vE+sbZMgHypEFZ5QeTNGlXQYoQQREcQDlZYCFUix1fk2LT3V7ACt+vp5cMADKjZhdEIsFa+MUd4qd75WiUf3Qsm36ZrLg0ifE8bu8xqo0MCASzzG5XZ6hHdzTXo3LYEHTj4aeFmTZkfEsC4m22ngSINyy/fDrclOEyivAYw7gAtzaUpmVWKDL3fS7mUAa32GWwaPfRIKKYR5RZL4yD/G8oZwBvVevyEbzrmVWjhywFpxZLGHBlSukKbPrej+0CSLxRZfz872Z06dl7g6CU86ScSIUEh7QaIWVxSw0rOc35oFTB9VWOCJpaprp9NY26OILA7jd0ui2itzlb3LDCf4XnGO9E3JM4GqOrmiFg8KgxShZq3o80CNS/86kxkuc6zakI+I4zcTmUnboEG9bo/pyQpVKwHZYT9UtSoJw/U5dNwKD2fz6dl2H22ZNdI5wee6Fe3glp7lqAYSJFgQd31h2HeB/Sks4aSACZdlxMwVZdi0dpLT95CoEllH5ye1YTb85igfA3tCsScH56s7u8ltKEKRYrwanNukVsJ2ZvaBjpvlr8R9J630F9SvciRMePFW77QdnhAv2ZC47Gp1Z2JPx8PPvhEcoeekXGBN7DcI0fWHxT+Qaazfmb8qNlNlsYJ+j7h4I76W8KSNJ9AcCRKXDkMCC/2eETdqiOAoKG5rfP2yDFedfsgaE3kIBUVNgFM1OdqC0qh8OxxTS77OeLRBNI1F3Phpsce8hyIMrLTAAjw4rGsr9XFxY4hClBJmuO+0zlvn/PCTz5uV3soRQ046jbXYQWKolb7oerx4RM5ZJts0tilIkLI+n88BRzQOekRbW+/n1zjjaGuRjNqwj8YPrphqvZ/EO0sgojQZq1/X6TAeQSplElMh91+WyC1nVYOFfYeIIB7olS6TDsO142lAGxfezSGO7KpNHWSQLgReubmaCE0yeHDpdcEzn89iDefjTp3lbbrHq198mydfbOzqTJqtlRwKp7XMzxxBws+hzpzPSxEa7iTLT2kzPLn1kwJvDa6ciT17FgRpMhhZmVgAMPtD5pcsCLAzfIAG627YdIQmWVYOLLUh9/fgNlFY4YPJrUdpUJQWwQMot6ScVylAFpUCHhV14lZV2OiWV6IcYznPbbHAxmabzjWuoJDqfPyU/mHe7wwKY0/QRMBZDbWEBzYl5kgvit7h1IO8HaUVeZrk+TfEXhdyVvysdkSGaxzCbO2+E5qr5i5KvJLGIqHrAcE51q6RcT4kFLipXzyZsUyZOWXD3W8OAycTw4B+T/DHvDu5IUR2RfDEreB6UFD1JGsVnMPVWfjg8G43woKagxXVwIbZi52KMpweRGJukL10aPLAqQuuuMoGzcFV5DfjTBg51YQnaf5g3YQmxFwe1jxH/X/Eyw/JmdixGGpVzaJ0FO6T4IbeNyLBjkUh/t0dDyQvIrMXevs5UEQYV+1io14WsH2OiSJXkfFarY+4KTgeA3z26+KovrhKZTxRpohJK3WKKkHFeRCwmEeRawWlvXr1y1x+mAVbA//ubkRU/uMtY8cvuMnuL70qzHEVO04/iRtrse+DR1qeS5jPPYrKY9+JgsZdXnCZ6LiUDfrdrMgvTutzfbQomoh/N8v4lyb6BY0fXOHBK5XPiuzgikf823KJXafdBmgxj425rYhTJ22Vr6F8bbXGlLyo4oggXv4c1nGK81DamXi8zgsMPH5wzbs9sIxhnZLFXtGblpE2m97q47Er8lkpSYcRhKJCRBAP/Os2w+9PsTtFnlQ4Ax0vUygrXYAmMnGmezSxswZuHLrvTD6siAmatGPF2sTKNHmFmM/ctcpqnuPcWB78u2UieYV+/oqEA0Ke9LsRM57qPA2u3Nrx7DlgwSIKHyc33JHfz+9p2SzxwNsduPoTew6wU3549VpPzwOr6gmtqEecgYpX9Iflw0IrbO7KjX8lDRBp4GyZ9tHE2nxNmjB5fr6zAuun38oqfeeKbF6Tbm63Hrc579l85uxFCQeE4DBTctqPULSJuU+50zyI4mPDJSsLjMqg72+F/DoDf8VmbtSeFJlVum2VV/65nDObrHG7cSsX8PnJJUQD2zK8q09wJAZPZjkdZAWJSm6KAQ/yaaLK4dUsAMRFlrjlF3ftjx6sBxo3KnBwG9fuSJCIM17ktJs21MfQpILbvbua6iOfGxY+2Kw47IhV3PbDNDnniRkLR64IpThCbet2z1VX6z1cmWklRfWxSSqbSnPbTuClklCgoT6tIDEV5IcQpLS8uGiiUJ3EwglFJLjiNv+ekVaxvss3k4xqPSKoDOs3JY5EZFHQ9Vbgii5eHlJupTCeDLGhbkEG4kSEIhk5Kk9xKh6fn06UIlfj4M/3NH50YXEjTIKfK0yycODh+8DG3K7rB48N+DzyUaU2TtM0r/NIo+VoBb7GudG0/B04WiJSgBnrnhKqb18/g6uo/2evI06HdYQzRb5o1rY9xPGCIkG8BGWr9K9ZyPFIqaFj4yWouNemYE2KlOa0URaLnDGNn8pBB6mPKuha4CmwUClky4tHQ/16gIU9etwSY10TfBZlaFEiyL5ozvnFwiYvmPmWUd/rppflV4PSJXI9hsRlEkmHEUoQEUE8iNTKQCSQAj8NYCI08ORVubiQYk6loIEBD9YjtKJknvNYoeFcSkuBd4w5LbGDBps+LmnnTrp9tOqp488ThfE5A+RAJptN8eAosRGnGyHBoYx80efBiZ8umOYzKbJFcblXmgBbud817IklX0CtcHkeqDmrNdbFjEO9KRyYhas440Ya7Pl48kVmsn7XdI98F3iwymZZ7Hfimp9lNYl9TurUpQmPJ//OZn94UOiEeUZxBCIfmZZy9SDf6vW7NyhzctF9OSS+8WB/4XLv0Fxa7Q/RQMvfLHbMAludz+RJDg2KfSTEsZBmqE5RTFSJAYFw4omYGzFDbcXXkFa66fdwy1eytxBPTq0KRb1jlZQCM52JFK1cWwINp9U5fgxcbtWaDM6l/oIEDa5CZLa9mo4bD7453J4HoRqPsHp9PF8cGULEp0toZ0UHvK5/AKcFsBdMhKIavDwKCloFD7ZpkXj1swDfIj4H4rxw6Hy1hA/LEJgmKDUzPI+TFZ1F15s4IY0jkqgfC1PfG+TrlTPh8oo8ABtOO/43XpOxMEUiusK/9X4+D6hSWGCu7afAcIpagKoXhSj6xZ00W0aY1PdZ1y82UXSrrlBUobVd+m3dBRErSpEjsjg9i6qUcP8Qd64sW5Mw/c71sFCzHGExUbReIUugWtEnJJQHHQ8Jnpxa0YdJiaMqXANZS7Sk6zFHM7kRuPw57CNiCZMeop5LYVJY3d+Tj7vlY0JpYMEl3n4QEdo3y9eMJ+D6+1A6ZWHEKzf9xSuN2fL5KSDazhKa2burkP4oXDHQirTiCn1un039lZV2W4DRrnWfo754DEbjY7fstBX14/Hd3MVIRVGn1vs5tcZp6zwWt8ZKPB5zPVp2pZBGypsniGlPkSLYhiDsOSKCeBCZMhsRX5IdycGrpI6azCUoC3XgXS8ADsmmQShHeLilWlmF58k1RygU5ITNg45AAzLnoxUAtwyebyutLNJk0mvlyX2/NTHz8rBwc/E51SeTytBRSLufIzRc1/oCPEqiH+GEgnJki9dKnr9Ko4SDnrjwS47A4cGqsyLPbSC8mga7BfyG1mfSvE5xBRP2vXA9QSiCJUgTdUuEcVadlYdHC0+ufWTG5+aR+3l1lqIQrJLNVKI3703+hIMWbneKB/hOdAGvoPo2UPvgQZMbtk7loC0PB/Jc4AG2O1G3fl/Oq6fqNnFGtcvXJj4P2cuAUtTcAR1/b6s6DEUB+J20Hcsg0jV9S2Ba6J/nTLga1k14zCxTZGdAZ5VhZdO7erXx0qgQ9GJp/WphdNk1UeSSl+Z1tJ+8gsleBK6PSqgeGd2yCSKJZ1bFEWciYvVx1WhCP3OJd5ojDYqtCQdVn+A+3kflbQ30PTkCS5FAExfhR/5UaEa/zR9TEnrHFORn5Dnhcvo7a2KTv2LpmEcXlMZmlYwcH9tPnpa5ZT+tlXMWZTiSxPkNueSwV5pDkMLQ/c3tCY+f/IAiXtFufC129jNI1xlOF1O8as2rwY5RLVf9KrC8KE3U+XtyioEVeeGkRAWaNU487uDf3RXP+JpXCIHMjSjjdAw3ws1ros7XbRYhvKKZXBEl0LxJQiGOxy1uSXBrH+jctcRI7u/cyAOasPm57+VUYS4TraHqLPk+SQYPjdD14fIqNV5YEYOjIr2iliNuFZ1mdGzJB4WFj4gTQYvW5C9FC0mMtfjkeGJZkdseka1cftl8N55Ac0oSLXRaYxOOunai1SwvHh6TOtEjltjDIn71dO+y3913CbChLOAf+ylBEPYOEUE80BfXgC8ZqEoXHA6dd/NM+3SNvZdM39SCxYlDEh2l3jOsntMXnGgFK5STK6XQZLYgWEQJOZMMrxDJAHXePFDxNy7cZ9o74Et88XIHrlsTl7W1Vr/o2MR5gjSgCbB3KftCrTDxQCU0e6V3FR0a+HE0T2FDoAP0G3KOuVUFwfFbsb43V4qh41dQKKm1rYKEFxKIvPR3jmiIOKtV1neggQqvivna2ZE1Pi7ByecKla0GrYy6ObiKTCWtEr+c6uOkw3Aesy+S+FyzPsP1VqDf3Zqor6BBFPcvzn0/iXw+SnHjctxW5IUjLLJwwMaH4Qb2SjOX5LSi0FigoRKeYaciDXu+WBMhnjxkOYIfRTdZ5WrJ/8eUyN0l6rirbywSBnjywf2qU2obNLn20fZ8m7cnFEzdlA0midM/6Ptb5TOdft2aPHFkE7Uz97yzSrSz6MvRAs4EhycPnFYWYC8CFqqd8o2cl8/CB6/AshBovhuXFCXhg9OzfJRKwmWe4wyzrfQLOmYdW3kKhoy/c+z7hKbaQgFPbsNtmyQWiPhayhMZvT0qWWw9zoKlUxEN1A/w5Na3nSpzRGjMQGl95jmuosbmtNQ22KjXMD9xhIBl4EppO25kK0fLsbjLEVjuGIZFDC/DbWuBxxFcubx3YeFxQ2Fwx22WKSULWdQPhzfavjBeC2NeE1t3sYMFAUs4p7YeWue0bfqagarUJ3jhCI6eQhRRkEeZZZReifpiTl9x+j6vErNWG3YWyRRHm3lgGVHHiWIZiQ15PRbp4rZNv62VHstVFuvbwgv3ZTzusIzFnZRgHgNFalVO3A851cnUX3mG9Kq8RYJIOoxQgogI4oXuXH3huOgLT8ZNjt700YU+7OHKzavzcYIEDcICPElyTBCt9/NkiMLyeUWIHfgL8nPgi1/A8YPgiY018acccWsvI962zZHKiVedeZLqrtSyIaGfBlFxNeoJP3kjhDgdhz/D+Z08S/Tx92ePGEdcsFJ42KOFVvR9nGLhDDC9wlyt38kjqsU8xxNTj/xT93tG+D10Meeyo+b+IpoYNaiXuAQnTZTjoh14VYSNRVn4cKMyqH1bE02a3PsoBYbLT5rvNpN+AxZeuMSfE7LK+8b50VZUCOcg86qe0yY8V9Td35DTsDhlgvaFB9t+d8LFhps80eaJmFNOk6tPWFB7ZO8UN+WDzSLBVWjq0kqaEzkQWL4+caSR61fiJQ5wKWA2a6bfsCBjVt6eJRRQiUbXWJWvBSESvCwRJ9VeaQ6uJNW1do2E3inKqxKVI0iAVuetaDe3j2VBft3WxCvd1A9xyoqLJXzwue6s4rNgaKUfbqAoBO5fHNE4UoPMWL08oKbb0V1hat8Bun5yqVQ3JYqrYwUXrEwYOceeQxxdZj6HvJ68Uqo4WsPtY8K8il6vZsKSw1wu140qYL8ty0PJOafDLDTzBIzbioepqIuV2sJmmc45DRJV2D/Gt2RloT6Hzzcr1ZejWgrwwuExlNU/FFAu1vpMWrDyN6nnmcblNW6KNKNrJv02AUphiuujuP8nc+CAe35xhBuNZ6zziKLIXNGjMEaxboq2f8b8xIIVp33S+RTnv0OBDNwe/DRWdNNBeazgp/alKGIkQr+NjwT8uGpcXBGOxX3Hc46vrda1hN4f4Wuhu8jGC4POQkh0/51oIGtcvp7GgfT9uSS79Vvr6jCFW8sqG4gIIpQgIoJ44KtcGT5/shXeZr/AHmAHOsYGJxEefHtc9AtyLHdXEz0HdOzHwN4hNKmxQn4LcDn3rFbjfKY1seMqAlWcUOV8GtohskF25l5NEQ4e1QnM/RU0kaAcb/5uPBhxTcF4MseO5zwxdAdKlscHXwBpcMkVJuIm+rx651HKuCBzXMtLhfPaOQWJKuqYz+GqQjwA8MjpNvvAAwCe6HNOtBNa7DVYtV7jFRFgRK7YxC7MA6oCcretVAIaUFjVCijtJm6Vkt9PAxXLB8Tx9LCieTgNin8P9mxwhDDL/JNWe/y1ySmfRIOCBCIrJYyihFSK3YX7KFUmQGH0HHnho9vmPkXJ+Om34RQkPqdCXe0V+eAUGsiyT8OsJQlNUgtKMYvoUqHRzfmi7Sjc2I488G0koZfTcbhqCYmPBa3yWZEgLAg5gqllakkiimJvpLn2SqaPIib4/LTKo9LkIc78mlIDfSx80P6HW9rvYZ8dXsHkCRNHa8RV+2GBiKp5sImha5rIlQzYmFUtIG8iTjFwhO4IX1do0s4+XKqDHR0WoHOHPQdY4ImkOkOc9bFjGGaPrANik7QACTfuajZP5liQ8FGkV5zPD4kIlrC2mTyDuOwqXVfMferLAvQcRxlZ4oiG/a449YzbN1dGcVKN/DQht6Iv+VroLBT42NNpB6VveFTHcb1swk5lpejnWCmL3gtBigUeSkmyRDnn2PL1y4oepD4h5ERV8LU+PI/Mjql0vLVf1B7Ne7hiH6c5UtnviDseo/uW8MGVSnhs44zbCvI4ie7LWjsFib93ZOGSxJFa7HPkeJxZPnVk+MzX6Th/DUq7tKKjuUoiHeeCjFmtKCHy0YLr0eJW4sl/f+vY9wlSvwG3qqBH++Zrpnv9U3WojDml/vqp3bmRvvl+bipcuOo0giDsHhFBvKiUqkcG9sHii6TrW8ErdjyZ5ZKLXLHCzXFnQYHC7Tjywb2AW6sDVCKPjSc55NVyuC6gjJ2PJ8bOxI4n7myyaYUE8gTYNUSk/bHCQjlaoZZjOsuO/E61mkQiTpw3A4WmWn4UvJLm5ApzmCeHuwfbtky4eseliN0Qc2sVhNI6WNAwz/GxKYRpXdxq6mH7x/ZtqkcoagGl86wVQx44UypI3gsDCcNMeWXUEhAcgYijltiLBjQIjFudptVZP5dj5lxfjsByxMdg44a7bXduWgEP4hSd02E2N6SBijtoCXPo/DwqW8ovKsAs0sq95gkXh9Q7kVqekWtsqskpFgn8U6LbpnBcRatfvrGxqDdzn4U1mpwr8lNwy80G2DeBUikidE4ZdoXpxxnlcipcesPEgpsjwPJQ1UdpVOGaJFBRJIdvjRM1VYc8RWiin1OHqgtUs49tVrVYW69Ek9lwg1qJJx+OGWtui9j5kUReTzxRDqfZfVfySuq7GtHnzF6S2H+IXqMJViZxuDJN4GkFlyMqzH42cCIG81/HE6kVOz3Dw7mPtELck2PfP7DOzpEP1Y9F1gTS2iTsO1zDahZA+XMCW7MTXy/IS8gVDCNVSTioQhEmbvQnpYlwGXN/VqyPVVy9yvHW8JHHS04tEsVopTyUYk+MkitRFRkaG3DaTGDtFk9Bw0+CcKQB7Q9NUuOg13mlHFgTZSf9MNCSS59uT+hnFHANeSlCgKN0QGJwQSmoLEZ6+YgUhOXlxpXfKMrVTR+0ShuTmTj/nn63vDf1a9ZClCWIBAslelgLJCQUsMDlYvlj0DiFI0vjTIRZWKPrPBvlqqr2OJqjlUO9Yn1pYE2sPQTofHCraVkVGOncDdPCZKiJfX4FKJrEqq5GrwlXoyinVHshSfECBYuMfM3b5Cyw1KBUtB25Cd8Tal4vsehbyHLxZQYjXqoi2IYg7DkignihwxGdaGorx88t4+rloVBYw1Q2VGKlnVTzuGgNj21bJWoL6UHBijoLHQWtEgZInLDyhivH3h92cpWDC1YkHgywIDHfnqiHOscGBKp77LslraeJAA26ItXtSBIWkqxwR5oAW5OyAnJoeeUnv3xn3MquhlNGuMxjIU1OeQDhp4mulWvt1Kv3Z9PExqttuEa31TzKi9YhAz+vsEzTbhJHC/jr1Uk4oDXbYzGP3s+DK0uc0N+bTACtsGdKOwKZ5rpYwgeJMmrVWs/zy3KUJ2+AAF1wLad9J03EisTgqh903vh2OoZ1JMT4KP2BI17CJC4E1tupFHxOeYkbESrVGmdqySv/VGnGx5MXJwyePVKsyTGXEXfM5CL7xfYzsF7Zvh0ZdH+X2OFOuiOcIkdmlbwaytEOcW2FV00pvDxclfq+tfY++z1Ma5OX0wTB8TnwcyUeXlFPoosLDfwjFCWkSVq2cffVacbG8sjNd6CoBp5YccoKt81cZwLtS6cJ/bJ1CY+ZO8kKTp6feCLDr6GJHU8q4qAJi/XbutGXVKnMRxNqPgdySaDSJHmk0LgpLNHPX2pP+nPax85J/2+x4x6kBQk3qtDH3lmkTVvpatTfu9eeAEVspKxOTfg5QSeSg0UN6/zmKFHqx1yxyDLv5PQF2m5c5Tdq3179EC9wWAs8rgBoVUGr4l0mmX1RPEpQW1ERTt/F15wAC4MFGIZ6RlxyuhktgsQtynhFxFmpLU7pWJr4+2mRi6vQcf/mXj8Vn680ngjSOe0a0gfZvJlTj0m48HP1K0cg89flNKxI4jFtAYsyqVtoDGGlhdP1welvLQFxTWz/fRnpntcFH49dOUqHo6tonBAnQvA1uwVF281Z4Bn5HaRFNo5o9nN0lFsIYdd380USp9iXVZSKmL9/uw1B2BtEBPFCly30O1Uy2Bthg0f6iBvmyZEYNACJ1KzqaU5oucbXpslTilt9gt7PFSMozYRL+nG4pbuqZUE16d1QVn89UuHZmI6Ek4JyzK1BMau3PKFv6jjy7wwlXA2MkEs6f0//YntFx5o00gDdKkvoeCsEq7dOHK7IpYyr0eCqlv17quRAQqNcNgx1XUUVhW7zUY/Q78SmuW4KUg6tOqfQiobFPGfQQWGaOY1jxyB5Nq3qOBEnVpldbh80sQ2zkEfHIu49RJi+f9I42xfAiqbZtCXhKgx/FzfVSHUm4WMnnSskfvEgOM5EkEvEenk4OO2Wo6C8zok434nFJKpwZAql4AR4JY1C0Asqi2uF2LezP5Mr/LDYZImUnKPOKW2ul8vy1QnNO8PO+cF58orOPdWuMTD1s+gZkC+wcMURdwLFfal/W7Z37jevxpFgx8KH5V3imEXm1o6JXEnUbsIUEeDf7piUUpQGrxJafiVsmkvRHmbbDSm9aDOJctyPOelNIe57qO9UackJz8GkibYBrCU4kUk1l/AOtG7hubLJ5rY+muRZqQdOdJhaTZXX+JpJUSlQdj8SziC/ktzkhG0jsCPV28CVowd5dZsiflDVXo31/zop4TXHqhTjVv2iSWuEBCY/XWf9myg1hiefTpQomxpbK+JUNtzc51Vousmfr/6ekTj1zvGp4Wgzq3yys/LP55uXKaa1IOFEwwYbU1oceeZwRJyb/uCjc5ojKTnagMWiuDQR6j8Lql7kGSFI5zRHAlqVypyFKBY7rOomPAYKOQscVG2NI3hZqLdS3NxKPTTWYn8N63rhRGdZIhsJBT5K4+JIEHeib/mPtWme0Ag6SLddIhmVEgvQXsKRG4FKIh2nCKqDu1nvCWfTb7iNFi7oNT7nmlcogYy9XzLsBZJwOkVkbafUaVo09FMVOfOeXdeMsK4Os3uf27KDPlf+bSSHx5hSEHaHiCBe6LKDgRQr595rpcGFO2muKGPhmszzyj9NCjj03h0AWCtJvPJCqyV+GsxYqwEFBKBZppi8gq23R+VFrbKbtG9WWoCTbxnhfEqu3sCRILTypAlQbn+EV2ho4OxvWM/TMT7IqwU0aAnxINgt4cm+D1QHPkShztZxcsrAcqoSD4J40qt4pVy/hzpyK4fUI4Un4gw003ilmwjPjK3EhR3FnAchyYvoykrHLM70laJJLE8NOgZxOc0e8OAqQOG4btnPMOdL82oirRTzJI8HWua5LbGJvo8iU8Ik6vHKsNm33JoJJ/FW1FBB5psFrHJFX+Os9liTQ/YZoBDe4KqNnsILpyzwwMJfi/wYnJQyRRMGayBPx9wHOoc4FUXfrR47j5MW0XNcDYvC/c19WinldDffb5OsSJB88UPNdzrM1rHBr59EX55wusbDnFrC4kCQcsS5hCj7m8SlAdHKeYCjJXgCbzwcqIQ0TVoD/1DVEq604gwGA/RbszcEmlDf47RB3k8/r9bzqi/1nS5W/+lRfYONHzXB+RSlQpN2/p25pGtcJSXq76xIMVrBjTjH1j9xVkLBjcPIA1sdg2s6X4IbaWLCZsckpHGkmnmORUtH8PKMImQT3VbNE0YOWJ5Y7kSfJ+dc2YlD5+fM9e5HqA0GyNcFXEK0gKphASrfW9ACBwulXlUyWDiJi1ag/s6rDKsbrecZWUlRQ1Y1EcdwlEUAVyCJ7oszbrJ8angcyOMJjlZ0PUHoeswRWXwtiCsHTe2Q94ePjRWJ6Jwr4UJUhynIQNaqPsgGuFyi3TmnLY8zNs6nbcVFlHGUKS1WWGITe23NTyy2uW2N01wszz79HXJ8CYXvcHUqFc4Rm1z5R1Ob/GdIUOGJeYR+c/O6prF+OUIiPFcw8zsifr7ptj9cviJBBKEkERHEAzNx9SXZnh4FCB+epbUoDNDHZQ0pukATXrAk4YXdSjNxzOQ45cHNuY9+Jq2gBpzXWGIDD6g4rNNZIbIc4NlsklcM2aHbDZnl1W12p6eQWTe1JNyOJjx0YfTzgI7NtpxVEF7Vyt0/NjgMUl6+clJwQGUK/VQ20895s3TMFA0Uzedk0IofiSAcBh5wDUPpc3gCzNUzeLLgrnRHaKLIg5NgmxbeqSk0cPEKAXajKkADN96eVVLPq8Sw679CAwqOvHAHgQESpXj1zjLu5RKDbEar4XxvHiCTEOcOqIJkQMoRQJzCYuVnu6tvvC0OieZQZ+ec9CrLGvQIR3Z9K8LUPgOtEodhWxUeTGQMTdQ5hYdMLbmqhbv6lryEREJeWaR9ds9pNWdhwgpaZoBr0lDyBpC+/GiaNs08o9g8hQ/n/EqauyJhP8aeGCzIqNneppjhGbHfyd+2ecKVaXMf1D6p/2aTz8g0msB2tCMk/Ks2JEyr44G8G31ilVYkgSZSk4z6WDxbWoDxca1Yvx6kij4hNt50Itz8m6i0M3llWb5PHOGoof6XU4rUcqqU5pZOJ58fFkCDqzd7pkby78vpRex/Yx1Pt1oRC4MUfWlF2ThpO2zmyQbJQZXYYDqu7CcJkxEWDOkc4ApHhkVk3MteNHx+sp+RW8KThSiK7rIqITmlwnlRxEeTvCBHRdACDVeccs112UCcBQBXOLGiDTyEAjbSdo+tl1hjVcRx/MK8xoHc/0do8cjn/p6UKsoV2TiFhvte99y3BH76zla0QQGRyvx9AlwC2r0W0fnBpsZewpOXob+BF+xokc+3yRb8IuzpQdWoLF82Gke7Jvg81rCuOeSHlOIY71sLPh6eWhGukuVe5+k8UORd5ltFEUhO2g5H/fipIhmLoVafolm269xR5UwEMf2DRIIIJYOIILsjNTlxHfXGdpgsG3GBzPU4eoTD2N0BeoDM03glrtCeHjQZtQY0ZAAYccL4I3RhcgcHiSamZtsUGsuRJZzKYX0GhV7GfY5jAhj9Ls4KrJ/TdijU2lo1pWgJN2/Y8jjZnps4BcndB0oR4LDMyOx1CQUePxmcaZJ3xAYEEY7yWedtjMriUaHwijIyIeVpic3DqJ0ZKJQ+SJU1ChJHnMXRxHnlvGpNaUsaP3l3sPhlVd9wHNh9lIoWoUmrnyo5WNMVp91akzRa6eWUKK7wZJ4jXxcfeVpYq5m8KuVWhSCBhgc0XMkiruITD1BpIuEVXu7mmyuvNsGVRdzqSZzaUY0Ge+1jk7Qgp745Ai4LYZbvBk0mw27lHF7xq0Ii2/rN6NzYj6a1wshI8wNrdvURXLXGieJiIofEQp2TFzp9D7UhjkoIbq2VcDWUJyUGiqBR+1Mky5rNnqWZwxTBE+BIJYqoyzoktkqZ8o+9YpjTJfYb+Ki/S5oTa4OhFk51GJp07uwcE2fT5lFqSh2aVDnRRD46P4MkaISakPjZ2DE2pTKPYSqNjH9iKRf+9q0SR1vortCpOJQwbWeVUzo9PTWhoK8KCl33MLLkq19uzZhAljTJ/j1yu8X2M2mzL6H4Zhl0OpMhNYcmt3TuW8bHjmGoqkSC+joS0jgiYLtTxY3GEGwQGSSfBI5edMP92Y/Iui6xv4k7AeUqNpTqEiLRl9M/VB2npLjH9S/MVZoK8FiLi57I/y4snjlGnOFZHr5JPJnmcZ8RiGiBgoV3jrag2xyFYN5D/mW24TWZNbvRJx5Gp5Zn2+IVu63I44o4BZnBWr8vLULE+cd4iGJWWV4eT3BVPyd61UeiI5vrWkIUmfa6HkxBt2T8LiIU8RmqZF+/ktZt232qqhNBZO0zXT8VpbhxJIzq5NG/mXN6Q0IxNux6se06d7iSVLlAfx/fv/xO4gki7CUigngQqF4NAV0il1MUaHLuhgPnNCTVmd6TTI7nIapCEFzp4cfhhDWGeQDBqr2GLwBujfYEqy2R/e2wzOBSumjzRZNSWLhygmEdTUaoNKUVks4Xfdd3hCZQioztLBMqp5PnPGIOmeV8dY4ocFe1rEkfqe6gyAvVyo7k8FH5RU658HNkDg3Cw5Rr7eZoB+jCzD4mLFSY+83qJVyNtFaXaZ/dqAHLi4YuxpyexXnkZn8oB9VHlTl8lcg0lgZX5jkulcmDYgrrt3wa2NwwQRWWRO05SKtAGsWr1TQBVrT6VJCZnbXEQp/P7/HNckQMXiEi4YNFNRY04mAPCPaV4VUlJ2zZMp9ctiJhCpIVAeasFlnRQRxNRCG7bMxqtkeTD2tQuirWbsItGiWMinEHoj4uUUtVhdxIECuChqPFAgG8d0UaamVsw/rMNAx+OG/bysmPDmZWT3gMAlMowsQpCa64VDSn/XD5YBYUSCR1o738PJml1C0rPcwY4NHkhc1tyXg4ZS0JDZ3s6K4gpXGx/w2n1nBaiDsZTeM0SU7Ly4md37nN7FKljJ9WlCN1yYMpx55kcUh3gHxtQOkf1jXTqXSWtCgrscrKfbcTlchVzFhs8rOhr5NaYvn80Lnim0J9aS8ylqU0S7M7a6iPYVNIEuncVB8rDYkMffk85NLKlieK4+/BETS+hd4l7xmrDDdf5ymlir2ANEESy630R45mdVOF2M+GFzvoPCxMqlVBExy3ApcVqUP9rT+VojxJRAk7PiaWpwa3DY8IERerH+HrihWl66SOWRXJqI/hxRrXz4jPF4+xXoHXv0IQF1lKCxHhZcsTV8Sh7+JzFlj8Pg+xgkUkJzWTo4GsNKIlFH1C53ScmTkbsFJ/G+Hoaqc6mmuWm+i6wuIMe6oUdNwtvxdarIlLFaVxNJs9gz25eD/D2YCdSS0Iwl4iIogXWnAIpFirE9agaatTO54GMX4WS8hxO1BArjEbwKmmsQurj01SuYyfG33BCnoVMntkzwN3UM+GeuzJwaHmf06195NDPmtQaUgy62KDy2T2L9BUpwkDD8hoQJvT3J7wJK2NHYMwrTD5adDBoZNuhYUI+br4OWfTMZNjwhQG7mMDO8qv5glfpIaTT5xM+9yKfk+OXlH2BJYNsizhwxpA0OqfczG3DFxp5Z7zw93ShdZKEq0GWivFraliiP4+XA6ZBKfQQprY0uQn4pbOq1UzoXmYV7SDG2prlSKkVVKwU76ziu/j0sQeoSxumLOvIaVhLaXQYEqTYc+gaOpGgvBky+i2S5uEkSzmdRRF5vfR51C0hF322p6Msmip/FUTp5FRiV03KiPE1VE2UjoLhde7hqEcKWWZL9PpFXbOaf+YibE7XKpbV+nI74p0/5A/WHRCtbmqgK9rbLCsWPhgE2IN+5KQmGgJluxt4awyKprY5Dv15+1zrE/Jdb5n4M8ZCUVoy8iSBu7BzU4bcsyso49zKWFnUhRoSyuYlI5irezSIDxpqT1pV1UqJTwGyfNpUuRM9P3cJrhCD5lHcxt0PQt2tIn1CamraTJNx4n9rQwcacXXKau0tR2ZY6XkULv1bUhNWGIYbvRkQ0qTpOu5ZbJKE+i87xBK3HfSJCdMkQeWH5Sz8huZ5NHHOZGI1m/Niwq8qOOk0jFWv0aTzsiKVQknmXGv4yoyHOHHk1HnOCla4eeJNlesckto83XO8vGiaj8+SvELuqkQJEKwOB0h0TjgRHdxRTUWFlkssiqLzXXKe1Ppbk4XsyqoOGbHYa5uRn1PuGlsAh2k7+96vHDEoFd0cXjJcs+0HU6NsSJjWOzi8rCu3woLyCRo+7KcRTJKNbXSiKgf4qgOH6U0m/tUbjxSh7w6yHgYTrvP1Wbc+d+tMl0zaN+8zGTjRC0eQ/Fvxv53Th9pzSXYHNepEJQf4RxS3mn5ZRJJhxFKEBFBPNADD58vYoer84DKSWXgi36ESxlSfjAPEuImXBwGz6vBHDnhDAAwY37CPNFkzqnmCYYLCQo+LkNXUClgnqi2bJDw8QAJCKEGdshrcP3WxIMzUuOtQahTBSVIJcjY6Z9/Dw41N++vHzs2/s3bE19w3NzvDbSyR6kEiibQvNqTvNXJE+XwYl5poLBK18CVVz3ZgJUHtLzKG8yxV3CzO8eOTbKqnTASw/Wt4EEphxMHedWazficwR6n1/gbk8EjVf+wDB3NYJPaN4XQchRCiEzJND4KhVecB06Vf6xKSM7vyaUhFa/Q0IK+Kyrl0j4EKpGow4IhTdLC9ezywwGKtOISt74Gsd8mTFU1XBRX/xk3ObEhr9MncDlja5LBfjMO/BuABs88PLX6Ltd4mD+HB8LcNhY6Yiib+FFkiUpPgcpXQfRxzp8sz7SjdFj4iEyYnnCw7yb4WSuLNBAOU7tV1alM80In953Sg6xUHzLNdVM2QCubIRJGgyQIcDQWV5Iy76H0pKS11A+xOO6Gvufnjut9a0Nllsk7hT0D2GjYjULLbkoTO0rxCzrmgFa1s+nkl0Kr8L4GdT0rRqXkpz3lfaHYe/i7OSu2XmaebFwZoEhM13uLI4NYUIiQ4Ob3O8eGfjdOf7POAQ9/rrjqKh4lrN1Jlp/6DmsCStFxXulh5v08meRIQirh6WK1SS5XSwKAVS3PhSqVeJqXOiXe3citKJw+4noLcfugvseqcMSpDG4qIH83Woji0rNxniAeKTls6Ku6tfNcSPI3i7UVH02OLcHTvX5xdC1XEFtNk36aqFvXaFesob7Xa9xn9scjBUdxmgfd9pNHjyaYnp7weDJuqpErPCfCN4+8z5zfk8dUAU4BrU+Ld03saCJjxp2/Pa4GyUUFnDGM9ZkcYUhjC8sjxjXBJ2GPU9mxI+QpbuentfnDWcCkr1BeUJEI1L9Mh5ESucLeIiKIB3pyoQJBKxeThQbXSdvKzWejQYpWiHAqh2OeZuVpcpkt2q41WdGb4BW/lZTvTauklmO406ly6TteEfEaELoTVd9iMoRiUy+aGCqaoBhYNWdPEjYSoxJsGj+Hk5LYwWUi4Q94r4JQWD4bqVnu5TwxdpV6yvmM0Cqpn0Kb1dwlhXJj59/DKkFawKDYyrXmQYPzeyZtocgYrorA4p1TrYe356N0K8sc1wld53LCHHngm0b7T6tIvqbOih9FGlnnF/nvxOXp0kCWw5YDYdo2/c5hJ+KFzczCNMDnFCI3SibJY3LP5qM+Ns1lw1gNr+hS6pZvCw2WKzs5zXRO8YqXn8OueTJLpoVuaglHovho0sslo822SYQIUGQJp8mwCBI+qIv9PamqkLVKR79zTje7pGrK4o2JJ72Z26MTXx1Gnp9y5ndTAUnY85G4EWHjSsfniL1xQhTJ4GPxji2H+HHn+3h62TgTPu5Xkqk9WKVzecWRIoE0SVyxiVfHOTybTFbNc5T+wKKYVfKR+xFnUqdoIpLCwgMbXDqVj4JpsWiz3B6x1dTgzCUJj1lcCWueTJEY6aPIvTjDUL4WUVReQT5aXDqVqzxxu2ERyO2TLX8Nj5QJ1ziYU1IVRQJalcLWrPMUQSx/Ctp/H6UfBpzoNi6ry1ERLJoGaALsphVwuwGbvlNURGS2fY0L1KubOKWXxA2rao0TSWItuFC74zLgcR5lHMnIogpPjqnduGMoP1fpoEgIrzSZOCGLJsDcPjkFxh1bZFUnj7DKyQkjrSLcx5v2Gft9A3wNZzGSPHdcR5AgiyLcVqjSFxs/a3xkSsywIT6LDm61OksQoLEOt0H2ZjIUoqiclRLliLHBQO3EpXQpOptFcxerMhUvdrSOjcOD7P9XQAQre8TwAo2Bo+I8Fg6sqjG035HyFgkiCCWITxXkoFQB2bJlCzIyMnAYTkDQl1Soi595jgYKEVag6YJjpWxQWGnchJy3RVVKfE7+JA90rEEYDzT4Myik3+wPl2ZkscMqUWiv9oQrpyYMkY80qZt4Au4aSnEUAK1083s4FNddDfXnUug6VyvgiAZngM3pC1a1A/Y3cfLNORw1zCkCS8l4kk8d52LMkwSr2oKH+7iLV3viSjV8LOMmvez7QCKIO3nxHKySaBBX8rEQWKHFXOLRgScSXF0A7ZzycNPm7d6dnwU2Z1JgleXjaBpO5ymgRKDXRNfLjC9RVZyEgql7fnCVJl6pLmBQ7nkMWCSjCQKXxNX42DuEVr84jNzyP3DOT04X82prnPYUN0mxVnPDUJWfQebOMDJS/QjPODlh6HyoKUU0/TGlUH00T2At4SU7N6EZLqc1xhlJcoUG+g0jdap5Rw6QuG2ZBtLkiQ2yC/qtOSUsq5m96hsh8+gA95c76XOov3UnIlxpJMBeT5TaGZlrRxFE+nROnNa3mKINKYogrhLFAvIr4UoUNMlyxQXLoJcXHkio9uU48UCOoBt9D6U/cBlYNzrMEuipH+FqKj5ndZpFdBaNA+T34lUVyryORD42YOX+noVdt9QmH7fcRpQisIGqjjk+XGFKv+Py1jxRLmg8wucXnzdW6Vu6LrsRSRFKG/L0vXInuh7XLMvI0/HnsMp9c/n55au8o3YpyoTFYev70wINp12Z7XFfSsfWilRzfJt8JLxHKG2IPTSshQsnEkR5tE/LpNSNymDRlUToyHK6/vE4hau26fdwWhynEnL5YK4I5ESU5WbE3p8yc1nCyD1rnGPabXLC61Jw3VZPTw9erOA+KrdBrC8PZmZ5Rw2TXwkvELGZtxv1a3ngraKIUWo3vDBontslvoTC2fh5wTPIzMxE1aqO0X0ZnGsdkXYGgr4CzKwLQUjlYOTOj8v8MRH2PRIJ4kGgcjoCvmSEO9IFlCbd7io+CwyW2SGvBrMg4uSm8kqnNXngPFc2JdOd5PrEOb0cKs2eAf4mdriiogs94+NcUCctgZcYuGP38WC9dQvP3FY1e0HCHHk/5wM7eZ5BinDgCYuVX8yrVW5ZXxrgsS8Kr7pyzq3ZHq22+GgiYfkXsMGnE9ljCTGFdPO2Vjg4JJvM+bhMsmvyxlgDDWfgyKi2sQm5n/YzRLnn8Rv379aVuyDhg/09OA/cKsPnfL7lHcLnBx0zL9HA7A8PdgmrGohb4o+OodXWeELPrylgBdpKYaE0LncF1gurrO3mAsoXc5oeC0HU7sMFGP1ZPgPkS2OF/DqTUa4G4lvklJr2EN+80OLA9PQwVm0G6ldT6OIaBObvwwqqoGXtTDjxpEI/xWkzHDHDEwT2H3DLVPJ5xMINhdHHwVW76LuwkXbyjKUJ/QLMd2CxhibT3KekzlntLTDxBJT7VRrIu8eJzaxVBl3L2GTU8VsJ/DM78eSJryUcks+TAEf44GMQoNQxXTmIidSgaygZU/spldEVGVXdxObmXLGKJ5AswBvovi+kElbR4VSSuHK15JsUPmC/xBNQV5AgUcaTXk50FrGtc92Ehra+sXM90wp8VKrZzyIMRQcoMlY1+5mWknByzyJEgK7NrncX42UEXSBkUBykKBeetLvXJctEnc4vH5W9tirSOWkrfhKywlXJAJeu35b/j/Elo1TT3rHfLUxibkFlea2qJSSOsCBf4DHzSO0o8FrECyR8/aPfMy5aj31ZejRKaJwctyhTJSY6psyhqDoaBwfI38ONnAtuopQo6i+sMurcj+rvvWJ1wnbHFbh4wYlN0t02ZImcvNjQmsy/9etIpLS2RSKM5RdDY5By5wmio+N8UiJXKBlEBPFAr84pXzjuAhaFLmRxFwC6MFjlWr3nHhbWBZDrwDtKu2dZWyes3wurKgNPEmngHHQHkfScohC/CAsKf1FZxHZ2GDyHbPJqleKQdncC7BV2XNgIC841pgk8m3fGrVTzyiJtW/EKC4U2uyu21mSSUhGsFWBnhYmPLa/QWANU3n9H3FD1aiUcOFvpE075YEyPhXv7WtgGqF6rSr7U1IS/B09sFK3suhUzeDXOWiGi6I+gE+XCkzaeTFrmY9SeI2TAa55bF5u8hNiHhARLK/LBCVG3ojdY2KQoCrd0IK/MeVUYiKtkxCIbC6BcJtIjnNs1zrXEIncV3QNr4Ogh8rnpZoFN5BPQsVVCU2dOMXB9K7jqllk1na9/a2WFCltmnRqKGuLvZgkyjukel8+NUKns7HYxIS31z9iKfKi7HQXg/y3WX0UO7Rq9nbyKomfcalge0WLBbbGJyM7usX4sbY69ShnqQCIlhWGHqsQmnEmb7YijCBlT+7i8N4eB9+ma0G/G7PLB3RLmyzNx0YbUDq2VbvY5aESf6ZTIzepG5/7P/yQUMyNuKV++Nnt4h+S2sYX/pNVbEqaiKWpPWb1i/VjyJqeU/cbE4fKhWhyFZ48ZVNtYv7qjIVXRyY3tcyrII8Dxv2GBwzLxJX+rkDOp4qin5EyaGNKxsRZy3P6FRFOOUrFSkFbbizDsFWSltljpF7meaQnsv8YlYrmPdI1uOTKFfSf4863oE0foZhHc3yAmvqmUgGe0gX8+laem6xcL8pH6TnotwT5vVhQbl2x2Fp8CVPHIisqjPtoSyj2iEOMEeVqEcD1ZrGsG/W5egraVmuQsHATocyK0z270iZUqSgtokdmxMZi/dXNPM3L25VIzY79tpC1Vu3Mq+YWpOlaIxyZtY+3On03pWXS90ARnrkro6cS/YYAM9c1+07G1xNyNJFrXdcSadnm/WziUBYwuP54geX33vy2RKwkNwt4hIogHekLoC6TAv3FrwhU/zuk2r1+yKnGoNF1kI4fun7jUnllxIqd7zkvfQR4YzkTAz875NLjhlA8/XcB9TmlL0OoXT76s/GTHoZpX/gPZFJY4lfwDulBON7tya5yysNHXkajklsHzmkCy6h7c6Z2XHz78gOjtFDJdVasptcX1DyC/FC/fDF7psCp2aOi4s09CgPOGHXNdFlWsSAZ2k+ffzFmBzqkdu59Cog6vaFspAc6kjXN1eXCpnJUwrnBglYvlSkq8WuWGj3K+NKdsrNvsPdDyiD6JC+HdRcQxYuNLrOVvQfn3QSfSynqOfBKs8oceQmScHw9N4KwVHic1xbqY87lHRruWKOWmcfHkgQel7L3ipPBwWhxHGll+JywKOiuJXP4wqyabOpNgt8PuL1OyayVMi+NKTloIyW8HPDE3r6vbYrdpHiEKpzb7kElpK5Vi+5O2lCaAdH5z6p0rmoZyYs9lNY6dqylrnP6Oz3GO6uD+IYnC8MmY1Y144fQmVYPOO9dXhibqnL7Ik8ycdDrXSRzKeyC2PznH9ojeTt5MvzuvkurXtY/1NznVqEpFJRLC6FD4c+3Igx21aX/O7x29nbTNe3Drp0iMtNWx331nq1ifUGmFff3i1KHUibGJZYRKpKct2Zw4qtJZebZMa8kQN1S7qmdKVKXP/0y8CMFwmqqZ6NG5xykoFGXjCrCgNKZQp9gE0B+mCAX2tXE9sSgF00ozIcNTyzTewcsngYV7K3XPjeTjCj/sB+WWI/Uw3FRkRGkdG6e/5Goxkbm0z51J5Ju9qFAeXYoiUTidJ64KDi928HWNy6b+ZQthvODkI9NxjrTixSs3sof32VOQ52u2g6pKkbENY20lsDZ2LQtTxI07NuBxE5e2DjVz2jqPgahymr9Dq4QLPO4igvozdn74OVqN+nJftiNqUapokL5PZJcflXnNZopUpugbc795o4R9MQsinHLqChxcwppF/AAXEdDXll2VkAIRb5NWQRD2DBFBPNDhjPqPDej4AupzqjKw8BGhib51AVyeuJqJeR2bl1F9ckUTWF4dKYhASmy1JkyDlsJiGVrxRVZvb3HiVYAAp9rQRZpzdl14MqbWkFEhV1ZxnNEDm2PHIDKJQrCpaoybCuGjHHU2uuMBjBsmGwjSRZtSY3hVzJpMuh4UnD6wF/4aHDHipyoAYZqMcgk7TdJ6ijKhfFQfh+bSBdcd1PsWxfY53IaiQpxVRp5cWx4IFMFj+UY4Ij9XSrFyumm71gBG31+5PuExZEPFMK2aw00VosFmgNK1rAoJvELnDvJpAsrvZzM9tw35qBQwTx6sVACnkESE0sU4Z55DcNmnwDVztYQXruRgrcRleQ4COaKJS1BbnkXO5EVVi31m0k+xVXxrv2gFOW6VbFGsffs9qllZpa31PqyP7VtuXZrI1KyUMI3OvK4WDcopTXBzF+rvsii6i8QJsw91Sayh53ilfXMne/XO3468XJJJ7OBgPxrTZjnlh3PTY++vtI5KpdLppQJ2f6maU7RBNgkvTWP9aE5lEiKznGEAi/DB2J0ddWLbrZpkRxblVgkk/MzKM2LXgg19Y+J21YX2QD6H3l91AU0K0qjc+hQ72k+RMXUumU1Wnp/puViRuoAWJbgUPfV9O3rEJlyVptsTu6xdq7FmW/PWJJ4Y0URG499EfTELmOxBQUa9VjqtSdVM7FXkp0kvGyq6UWRpf9ACBW1b0TmpyNfArVrihv9H99kZj1gTb4r45Ao/qoA0H8v7ZMuOhCvlwbWbPYUTS5Cn/o5TW91xl5cPFPcPXBHHvIeiKS1DXxKtOXIw39w5um9eizp16VpaUPogCTfW9TsnOaGRpyawIrHvhCWIcHvScJQkRQhaCzl1yLy7vS3ERWbOSxw1Rccv4ET2+OrVTuib55le61wvrLEJjTvYyy2ntb3IljSZ+hVqK34WzHgM5ZZZpvLUQT4H+Ls5Y1rL84beE1ANPNNr88e1qpylw2izaPUv02HE2lLYW8qVMWooFMLQoUPx/vvvY/Xq1ahfvz7OP/983HXXXfAXULYukVlPv5bXIxhIQdgjz59Xk13Xdx7E8KTCy/PBnUj4KBff7eSt91ClEw4p50gOa/XRmTRbpUbpiuGjFXFFeb5xKj6H23uYsbqGbzyxtIwHOefSeQ+LIH5aFeNwXMXl8dzcVNpnPs5s/sZeIXkvVAlvc6qRtdLuiCBcbWdvjEX3Bo7ecCMhCoPlq2JVQ7Hzi3mwyVEEfNG2UhTcFSKKHOAKB1b1CSe9yZrcsxkdDVp4om+VSHQG7FbqGv/ObsQKpZbwIIwHxRHy91Cd7HMgXDk2QE1evTVh7rhbEpVL5nKFAU6F4L4jmyIvzP5QGVb2LOCoDBdefWPPAI5IY4JZ9kpaKDX2e+RkBBIKBW4FvBTK3Q6lUapNmh/Lvr0JqzYp1K/uQ9OBj+ftF6UOuNsOpfkSTsBZ0HAn9Ek7aIf4+9Mxy6phiwO87bS1TnrPLnKq2pNujp7g3yZC4faWzxJFTmh4bMgh2UlbqSQ4RQvm3Y/t287msUl38sbshIJl1jGxSDlNCglM3DZyqsXOqQgJOpr0eVSq0/Ln2JowjcqNSItMjO2PvxtNhina0U01Cs+L9REBinzjSadvqz15siun0blGkSB+mmizUbAmt3tMOAj+MTOhsOimBVgTIO5j6BphGXby43rbjWLXbf+aTQmv2Rxt6H4HK32PoiqsNEnXYJKi+viarTq1SuiH4b7H2hf2LWoTi6byu6kMXJ2FIjELWkjx8lKJixjZQ8NrrxTcuHEcCwLkN+PbTtE7bvQrRfNYggR9z7gUVPap8Uj95feo7fax9VOUiuWZxuNDrhZoxJo1iT1JCjCftvbHw8ybI07Ci+zUSo6stI4zj4NpbJLb2I5gssx+6TxSfA46l0LL+H5NZuK0I1qYdNPNvczVuY/zU5SrJodScJKmLkq8AEi+NmYfdqXxahPQX7Z9UOZNQPPnWocHTo4rQrGnaJ+UUeHPi+WYPPjgg/j2228xefJkJCcnY3MCs/LrrrsOY8eOxfTp09G+fXvzWpdp06bh6quvxl9//YUaNWrgsssuw913320vtAv7nHIVCfLoo4/ipZdewttvv4399tsP//zzDy644AJzoulGukfojjYSsFZ9rVJzThi7nydTtCrEqxshWvlgB/68DSBhmUqeiLlqMsMr7yyIWBPTTHvC5KMLowWvDDsDGxZ/OL0HVN5NVXcMJj3eb5XBo7DjuEEkRX/whIUN9Hw08HexqnnUoxKHtF1XeLFWpcjTw8op5jzZFfZAjS/gVk4zVfvh3H03/JNz1FmECHrlkjr59xwtYB0bpyyhJd7Q6iF3y0FH8OOLMw9cuQwclwwONHP8Vmggzr4ZPNhm4ct8zp9TE4cgc3QW7Zdyqhr5lT1JSJSGxoZ1hmqUVkblVUEijr8ZhbRz6pyey9SK/dbJ62Lh2YEtsfM44pgbBzZX3b2BK/22adPslUzOo7bypTmdxTWG4wkPCWnW8aD9d53uK5F4lsbbJjE2t7NtcBrYRpN4mlwbcSH/FFdAtSkbEp6fnEqQ25QqaHl5ODnCQ/K81YnPARo4+9s76QrsAcTbWh9LP0l2/DV4dTzAVSXIf4avJbZ0B4Qz0hJGZEUOi/W9wYWrPCfNqSu3Jvbn6Brr39In2ROZUKNaCU0MU2i7vjn24oBqRikXq2LtI7cFpVo1pYibxXZ/GTok5hcSnEuiKS/nskeO3l7P2DU0TFVgIiTKKYoMMs+1pvx/usymTiMTXLouhpo7RrXkC+Mn4cVHkRyhJra3UID8T7gSD/tQ8UQ51MQW8ZM4dZZSIHNrxUScJGqD8V5iiY2Yg1zBZJktVHO0mrXwQf2wdyKgcw3n6kmBxBNL1+uBPcqCPDl3vEt4gcE1Ey0MbuqslxBlvcf11dqFn1MJ2Z/KiUZSXJGFrq0FCS8B6i+8TGMLMkP1baexBl/PqZ2w6OF+pvUb1qaUDTJOVk4kJRssB+uSUFBAGhZfW0JUxYUjkvn4J7lruPS7hZvFxmCBTDLkddpJkBcieHzEoppHepeBFkWs9F7y7IHfHkMlL6GItJZ0nXFT1on8RUxfOBtwgnaE4iMnJwennXYaevfujddffz3ha3QswYUXXog///wTU6fG+kgWfPr374/DDz8cf//9N+bOnWsW6NPT03HjjTfKz1eClCsR5I8//sAJJ5yAQYMGmfvNmjXDhx9+aMSQPUVVSoEKpFj5+9z5FtR5W3isYvidVS2eEHuF2MdVZaCVb8zITGziyK93LpI+Ct+McOgeey44Lv4+Gpz4/ogZm4U4T3ZLFU9Bg1frOQfWynvmMrDOflrqPK3q+Zo3SZhaE2cg6pGqwykr5jkPR35OgWEvBBc2cLNKxdF23bxdNxc8UU4zm+P63XJ/dJxCLWIDqiCZjVllU81G6HiySSlHUjjhwCqZ3PHpu1mpNvxd3MosdGxYOPHNo4mIc374WdRxVi0TbdfHZarNwI0GjlVTEqZZxBnyknFgTpv6CSfD7O2T29AWFyotoPKidShSi6pHxLUBhibHkQ5NEhp+BlbZws3OZuRP8WNs4KZ6xI6zC3vmgPKlOZrIWpVzKlGE2ZuIhBOOKLNEB0esSd5EkRh0frIIEBc5QAPUpLUUZUOiVoTaqdnG6Imxz6dVShaNrd+WonfMe2gCx9eFcAEr1VlHxI5V6io6D2n/2YsnVNluD0FabVcknCevoCpRTe1+g793EgkSiqMF6DeLOKUY2cNCeRhZutXRsIauf1yZg8SiwC8TordzWEDX29tKQkFj6q9JA2EjUNf7xBLJyD/GFQd8dL7n1quaOFqPbifl2tfS0IGxdhj+O3Y8AnT9sHxcHJNmyweEV+G3xvrOJLesL0fI0fdMohV5Ll9s7pP5s78xCVQt6D0LV3iadPOiTmErO7EZKYv4XriV54KbSbTl6CZalHGjKtmAnFOHrcgFj2iPODNvSvWNNIv19/4m9vnlX0dCDF+DaVGHfY64Qp/bBizBcQuN9dzrAkdvUARTkK7T4Yax88bvTKYtcZgXn6iv8DV30hzn0+/eONb/+2nBJ8TRxE6lOG4P2U3oWuCnY+6Ib9zPs9DKFby8jp+BROggRyDRvlkLlnrfGsT6v5RVidtnwOkjLWh8Zf0GvIjgiPORebFrs59KXeeXwU2YRrUr6jMcCgIF1AEoa5T2dJhhw4aZ/9966y3P1zz33HPm/3Xr1iUUQXR2QlZWltlGSkoKOnbsaISQp556CkOGDJFokBKkXIkgBx10kIkE0Y2rTZs2mDJliglReuaZZ/Z4W9pE1KcvcFxykXJoOcc/bqLN4aNkTGeluVB0gdk23Q555D+6VRk8P59LPhZUjYRTBOiiyyGJbiQIT8j9bCRJuaFhnjw5VT58lLscopxPqHXeBl2FSS1ZHBOOfE6UToh9Dui3sS6mBZSbtXxdKBTTElEc8zPQoJTLJ3uZlZl9o4GOJVh5rPAE2YDXDZueMCuhX4plBuuGqZKwF6EwcD+HU5s2TRESlB+b05hC76m8nbtyZkV80OAg1LVV4pKbxs+gUeKILNo3VYsMbN3qTWtjgkRkClUm4XbPFTP0x9CAKjmUuCIN6LxLov2KCz3nCSivbkfs9yiKPuHvEBhLK9CUb59LhpSatCXUr3BlJhKoXEd9HnBzHrafhV4OR/4zVv7SvKdvLGrHR31HVovYdw7usEUtrjrCqU4RXbI5tlAY8wByjOWYcBMqqcqmoA3tgWuQKzatiE0SI2Rmx+dgXHQY+5pQP5A9IDahrzTL6Z9++Dt6M6df9+jtZA7bJlEvaa39PXNrx/qR5AVrEgvFTvCLnybROzvGJjZpVMWAo5m04M/wynWEKpuEK8Xak2+rs2LJEStE8iQarXN0HVXniTOSpNRKTq2xJpYamiSxmBqhtuXKpXydS8qhyS2JGDkUAUTZYXnfZ17sGGYfFusvAksphYYnhk7KXi5FefCkPzwj1taCteyoNasiCpVUzaJ0O5cUf7PEfkQcyUiGjgEnktKqCMNRIeQ15aYPcjvybaERDV3z2VQ7yTG1DLWMtdUg7Q/viyu+hSiyhrEqiFFZYhfr+1Db8JF4GPc9aXzFz3GUq58Nmt30FVrMCi5YmThF2olktKJJOAqL+iH2cPK5ix3sGeMunkS3ZXckPt4HEjm5PQbJt8o1l48sp0p+ZNYfougs3yynX2ehlfoBFoqxkxbPHMHQT318hN7jo3Tn7IZO5TiKSmS4ypOaszDhmMF8n05UAnr6woTjmeBUuw1EetGiBKWXBrIpCtsptZ2fsu0PO4tKZR0jUP3b6jD/8v37YIH+0EMPNQJIPgMHDsTtt9+OxYsXo3lzO1JW2HeUKxHk1ltvNTlh7dq1M2GG4XDY5HOdddZZnu/Jzs42f/no92tCO7bp0STAHdEWql7hmBOpmumJL4xbaFJCKSte7umucBFoTBeZTPuCEdpIIeprViZetaVVjPBiWml3iIBWxEOx4xEkc0dNbjKFhK8kTxC6RivKsQzp0D3eZ1L+g5xqRBfQ0FZ7FSlCIoDfo/RciNzg3Xr1oa0kImyniJlaJMi4w2XqVEMrqLoKdWIRbgPKmRRspkHcDjuv3BM67nwMfRyJQSuzuUl2xx/m8gvZNFCb5e0PYolkWeSpwaHSAXsmEJo0LeFxCgbJT4HaRsARa8LsP7OMxKudMRElxz1m9B144BWiiWFBF8IAD8Tpd/MHKNri99iE1f2tc5ZSyd82sUFsDhsFb3JM9jhqqU6sfwhQxaScJc456TFe50F9mPoU33Y7WiGXfG7sL0MD3+r2pFdRSHQgRLnn5OXio0pM2YfaprVByj/30WA5uJ28kaiShnkdzZFyO1FagC+MyK5VHf1/Tsqu29SeXCItaZVxW6zvyA441bQ2U4lx8hQJ+0nYbEFCXlV7ELq9dux+cHpsgK+2xfrYrEXzPQUirjCwrQZNxkkgckO1A1mxY5ubQZPMrJiIkl3HezKscmMTluxVKxJWv9hZ3/6eKeQdkkRh2+Hm3umHIdo3zqVLqkMTjgWx1DefG3lH56Si32MHmdkGd9j9UKAjmTcrOoZ9YmKLSvJ7TngCFLGR25zEzBWU2uK02y0dYteWFIoGyvWRh9ImJzWS/Hh8meTnQ4JjkIzFc9wJ8DQSr8bFolqDjSnCwVlR51+H025ySbiPTIlfsUwk+IW3UTRsAedhkESy0FraZ7pt+Sc4VY2wINb5ZfECA+1/1mzHTJVEEa7AkTW/cIbwisYGPhJjVbXUxNW8NOTbxAKLZYa6Onau+eraopZVGCmV2tdyWiygzzfbm0WT6FZUNnsjVSXi9sTihH5u7uyE1zU/e484lZBynDaV6HoeXkbXRafv4kU3Xy55amXSWKm2PTaw/F/WUIp1DkWKkQgVcKNUWRwmsX9nt9g1O5mOmSaHBSYaN3E/BIoMCs91RC06J8P7x66NgflU1KCKE9mzlrzEOD2YFkVCTlvHrjFAOJL3+vJi5xhCru2YvLfb2JV2wmjRgYWHkkJ7VOrMBKZu3brR50QEKUFUOeLDDz9UjRo1Mv9PnTpVvfPOO6pGjRrqrbfe8nzPvffeq08/+ZNjIG1A2oC0AWkD0gakDUgbkDYgbUDaQKluA8uWLVNlmZ07d6p69eoV2fGoXLly3GN6fre3876///7bes+bb76pMjIyCvxOertdunSJe7x///7q0ksvtR5bvny5+Zw//vhjr46fUDSUq0iQm2++GbfddhvOPPNMc79Tp05YsmQJHn74YZx33nkJ36PDkXROFuea6/d07doVy5YtK9Puy0LZRSvajRs3ljYoSDsUKjTSFwoljbRBobS0waVLlxoPiQYNnAICZYzU1FQsWrTIGI8WBToyxq204hUFoqu05M8TvXAjN/4N9erVMxEfzNq1a62IEKFkKFciyI4dO+JK4eq0GDbRc0kULpW/DS2AiAgilCTSBoXSgLRDoaSRNiiUNNIGhZJGV7ssL/MSLYTov31NrVq1zN++QleWueOOO4zgo8vsan766ScjZBWl2CLsOU7F7LLNcccdF63prM1mvvjiC+O+e9JJJ5X0rgmCIAiCIAiCIAhlAB15M3nyZPO/9pnUt/XfNip1PX/+fPOYjvbYuXNn9DX5US5nn322WWzXZXGnT59u5qYPPfSQVIYpBZSrSJDnn38ed999N6688koTaqRVtssuuwz33HNPSe+aIAiCIAiCIAiCUAbQ88e33347er9bt7wS7KNGjcJhhx1mbl988cUYM2ZM3Gt0uo+O9NDROyNGjMBVV12F7t27o3r16kYAYSsGoWQoVyJIlSpVTDncvSmJy2jF7t577y0VrsJCxUTaoFAakHYolDTSBoWSRtqgUNJIGywZ3nrrLfNXEKNHj97tdrRH5a+//lqEeyYUBT7tjlokWxIEQRAEQRAEQRAEQSjFlCtPEEEQBEEQBEEQBEEQBC9EBBEEQRAEQRAEQRAEoUIgIoggCIIgCIIgCIIgCBWCCiuCPPzww/D5fLj++uujj2l7lKFDh5qqMmlpacb5d8aMGdb7srOzcc0115ga0+np6Tj++OOxfPnyEvgGQnlsg7qEln6M/3r16mW9T9qgsLfo/s1tX/Xq1Ys+L32gUBraofSDwr5gxYoV+L//+z/UrFkTlSpVQteuXTFhwoTo89IfCiXdBqUvFITio0KKIH///TdeeeUVdO7c2Xr8sccew1NPPYUXXnjBvEYPyvr374+tW7dGX6MnrLrG80cffYSxY8eaWtHHHnusqR8tCP+2DWqOOuoorFq1Kvr33XffWc9LGxT+Dfvtt5/VvqZNmxZ9TvpAoTS0Q430g0JxsmnTJvTt2xdJSUn4/vvvMXPmTDz55JOoVq1a9DXSHwol3QY10hcKQjGhKhhbt25VrVu3ViNGjFCHHnqouu6668zjkUhE1atXTz3yyCPR12ZlZamMjAz10ksvmfubN29WSUlJ6qOPPoq+ZsWKFcrv96sffvihBL6NUJ7aoOa8885TJ5xwgud7pQ0K/4Z7771XdenSJeFz0gcKpaEdaqQfFIqbW2+9VR100EGez0t/KJR0G9RIXygIxUeFiwS56qqrMGjQIPTr1896fNGiRVi9ejUGDBhg1eU+9NBDMW7cOHNfh6jl5uZar9GpMx07doy+RhD2tg1yzfE6deqgTZs2uOSSS7B27droc9IGhX/LvHnzTL/VvHlznHnmmVi4cKF5XPpAoTS0w3ykHxSKk6+//hrdu3fHaaedZq633bp1w6uvvhp9XvpDoaTbYD7SFwpC8VChRBCdwjJx4kTjxeCiBRBN3bp1rcf1/fzn9P/JycmoXr2652sEYW/boOboo4/G+++/j5EjR5qwSJ02c8QRRxgfEGmDwr+lZ8+eeOedd/Djjz+awZbut/r06YMNGzZIHyiUinaokX5QKG606Pbiiy+idevWph1efvnluPbaa0271MiYUCjpNqiRvlAQio8gKgjLli3Dddddh59++gmpqamer9MGbYw2xnIfcynMawShMG3wjDPOiN7WEUZ6laBp06b49ttvcfLJJ0sbFP4VekCVT6dOndC7d2+0bNkSb7/9dtSAV/pAoSTb4ZAhQ6QfFIqdSCRirq8PPfSQua9X4bURvp6UnnvuudHXSX8olGQblDGhIBQfFSYSRKcR6LSCAw44AMFg0PyNGTMGzz33nLmdHwHiRnTo9+Q/p41Sc3JyjJmR12sEYW/bYCJz3fr16xsRRIeOSxsUihpd4UpPQnX7yq/OIX2gUJLtMBHSDwpFjW5THTp0sB5r3749li5dam5LfyiUdBv0eo+MCQWhaKgwIsiRRx5p3OcnT54c/dMK7DnnnGNut2jRwlz0RowYEX2PFjz0JFWH6Wr05FW7OPNrtKv99OnTo68RhL1tg4FAIO49OjxcR5DoC5+0QaGo0WlWs2bNMu1LezNIHyiUdDtMhPSDQlGjq3LMmTPHemzu3LlmgqmR/lAo6TaYCOkLBaEIURUYtzKHrgyjq8F8/vnnatq0aeqss85S9evXV1u2bIm+5vLLL1eNGjVSP//8s5o4caI64ogjjMt9KBQqoW8hlJc2qKvG3HjjjWrcuHFq0aJFatSoUap3796qYcOG0gaFIkG3r9GjR6uFCxeq8ePHq2OPPVZVqVJFLV682DwvfaBQ0u1Q+kFhX/DXX3+pYDCoHnzwQTVv3jz1/vvvq0qVKqn33nsv+hrpD4WSbIPSFwpC8SIiCIkguiSaLt2nS+WmpKSoQw45xIghzM6dO9XVV1+tatSoodLS0szgbenSpcX8MwkVQQTZsWOHGjBggKpdu7YpxdykSRNTHs1tX9IGhb3ljDPOMMKubl8NGjRQJ598spoxY0b0eekDhZJuh9IPCvuKb775RnXs2NGM99q1a6deeeUV63npD4WSbIPSFwpC8eLT/xRlZIkgCIIgCIIgCIIgCEJppMJ4ggiCIAiCIAiCIAiCULEREUQQBEEQBEEQBEEQhAqBiCCCIAiCIAiCIAiCIFQIRAQRBEEQBEEQBEEQBKFCICKIIAiCIAiCIAiCIAgVAhFBBEEQBEEQBEEQBEGoEIgIIgiCIAiCIAiCIAhChUBEEEEQBEEQBEEQBEEQKgQiggiCIAgViqFDh6Jr167F/jnnn38+TjzxxH+9HZ/Phy+//LJI9kkQBEEQBKGiIyKIIAiCUK7Q4oMWDvRfUlISWrRogZtuugnbt283z+vbv/zyS7Hvx7PPPou33nqr2D9HEARBEARBKDzBPXitIAiCIJQJjjrqKLz55pvIzc3Fb7/9hosvvtiIIC+++CIqV65s/oqbjIyMYv8MQRAEQRAEYc+QSBBBEASh3JGSkoJ69eqhcePGOPvss3HOOedEU0rcdJj8tJUnnngC9evXR82aNXHVVVcZASWfVatWYdCgQUhLS0Pz5s3xwQcfoFmzZnjmmWcKnQ5z2GGH4dprr8Utt9yCGjVqmP3T+8LMmzcPhxxyCFJTU9GhQweMGDEibrsrVqzAGWecgerVq5t9PeGEE7B48WLz3OzZs1GpUiWzf/l8/vnnZnvTpk3b6+MpCIIgCIJQXhARRBAEQSj3aPGCRQ2XUaNGYcGCBeb/t99+26SxcCrLueeei5UrV2L06NH47LPP8Morr2Dt2rV7vB962+np6fjzzz/x2GOP4b777osKHZFIBCeffDICgQDGjx+Pl156Cbfeeqv1/h07duDwww83kSy//vorxo4da27ryJecnBy0a9fOiDlXXnkllixZYvb5kksuwSOPPIJOnTrt8f4KgiAIgiCUNyQdRhAEQSjX/PXXXyYy4sgjj/R8jY6qeOGFF4wAoYUEHfWhfUO0gKCjK37++Wf8/fff6N69u3n9a6+9htatW+/xvnTu3Bn33nuvua3frz9Tf07//v3NZ8yaNctEdTRq1Mi85qGHHsLRRx8dff9HH30Ev99vPl97nmh02k+1atWMQDNgwAAjgHz33XcYPHgwkpOTccABB+C6667b430VBEEQBEEoj4gIIgiCIJQ7/ve//5kIiVAoZCJAdMrI888/7/n6/fbbzwgg+ei0mPz0kTlz5iAYDGL//fePPt+qVSsjnOyNCMLoz8mPKNECSJMmTaICiKZ3797W6ydMmID58+ejSpUq1uNZWVkmkiWfN954A23atDGCyfTp06OCiSAIgiAIQkVHRBBBEASh3KFTRrQJqq4O06BBA/N/QbjPa9FAp6dolFIJ3+P1eFF+jite6NfqyI73338/7rW1a9eO3p4yZYoxgtUiyOrVq80xEARBEARBEEQEEQRBEMoh2ndDR2sUBTo9RkeUTJo0yQgQGh2NsXnzZhQl2gh16dKlxscjX7T4448/rNfoaJSPP/4YderUQdWqVRNuZ+PGjcaU9c477zQCiDaFnThxovFFEQRBEARBqOiIMaogCIIg7EYE6devHy699FLjL6LFEH1biwpFmWaiP6Nt27bGhFVHcujSvlrIYLSgUatWLZPeo59ftGgRxowZYzw/li9fbl5z+eWXm6o4d911F5566ikTYXLTTTfJbywIgiAIgiAiiCAIgiDsnnfeeQd169Y15WtPOukkY5iqfTl06dmiQqeufPHFF8jOzkaPHj1w8cUX48EHH7Reo8vf6qow2jtEV5Jp3749LrzwQuzcudNEhuj91Kao7777rvEx0a/XqTPaSFU/LgiCIAiCUNHxqb1JahYEQRCECoyOutDRFrqiS0FVZwRBEARBEITShYgggiAIgrAbRo4ciW3btqFTp05YtWoVbrnlFqxYsQJz587dremqIAiCIAiCUHqQ6jCCIAiCsBt0md077rgDCxcuNGkwffr0MWkmIoAIgiAIgiCULSQSRBAEQRAEQRAEQRCECoFUhxEEQRAEQRAEQRAEoUIgIoggCIIgCIIgCIIgCBUCEUEEQRAEQRAEQRAEQagQiAgiCIIgCIIgCIIgCEKFQEQQQRAEQRAEQRAEQRAqBCKCCIIgCIIgCIIgCIJQIRARRBAExzBOVQAA5dlJREFUQRAEQRAEQRCECoGIIIIgCIIgCIIgCIIgVAhEBBEEQRAEQRAEQRAEoUIgIoggCIIgCIIgCIIgCBUCEUEEQRAEQRAEQRAEQagQiAgiCIIgCIIgCIIgCEKFQEQQQRAEQRAEQRAEQRAqBCKCCIIgCIIgCIIgCIJQIRARRBAEQdhjfD5fof5Gjx5tXr9s2TJceeWVaNOmDdLS0lCjRg106tQJl1xyiXnO5cILL8RRRx1lPTZp0iQceuihyMjIMNt+5pln8Msvv6By5cpYsWKF/IqCIAiCIAjCbvEppdTuXyYIgiAIMcaPH28djvvvvx+jRo3CyJEjrcc7dOiALVu2oFu3bqhWrRpuvPFGtG3bFpmZmZg5cyY++eQTPPvss0bcYLGje/fu+PPPP83/+ehtbN++3by+evXqaNasGerVq4cjjjgCjRs3xttvvy0/kSAIgiAIglAgIoIIgiAI/5rzzz8fw4cPx7Zt2+Keu/fee3Hfffdh4cKFaN68edzzkUgEfn8sMPGMM87A0qVL8ccff1ivS0pKMpEj//3vf63HP/vsM/OeRYsWGTFEEARBEARBELyQdBhBEAShWNmwYYMROerUqZP4QkQCyJo1a/DFF19g8ODB0cfeeustk/4SCoXw4osvRlNt8jnuuONMSsyrr74qv6QgCIIgCIJQICKCCIIgCMVK7969TbTHySefjB9//NGkx3jx008/ITc3F4cffnj0sUGDBkWjQk499VRzm6NEkpOT0adPH3z77bfySwqCIAiCIAgFIiKIIAiCUKycffbZuOyyy/Dzzz8bs1PtDaK9QoYMGYLFixdbr9XihjZObdeuXfSx2rVro1evXuZ23bp1ze38+/nsv//+mDx5svEMEQRBEARBEAQvRAQRBEEQihWduvLSSy8ZTxDt53HBBReYaI+nn34a++23H8aMGRN97cqVK43owekuhUGn2uhok9WrVxfDNxAEQRAEQRDKC8GS3gFBEAShYtC0aVNcccUV0fu6MsxZZ52Fm2++GX/99Zd5bOfOnUhNTd3jbee/R79fEARBEARBELyQSBBBEAShRDj99NPRuXNnTJ8+PfpYrVq1sHHjxj3eVv579PsFQRAEQRAEwQsRQQRBEIRiZdWqVQkf1+V0ly1bhgYNGkQf014guppMZmbmHn2GTrWpWbOm8QwRBEEQBEEQBC8kHUYQBEEoVh588EH8/vvvOOOMM9C1a1djfLpo0SK88MILRvB4/PHHo6897LDDoJTCn3/+iQEDBhT6M8aPH49DDz10j71EBEEQBEEQhIqFiCCCIAhCsTJ48GDz/0cffWQEDx3lUaNGDRxwwAH47rvvcPTRR0df27dvXzRr1gxfffVVoUWQBQsWYNq0aRg6dGixfQdBEARBEAShfOBTeslNEARBEEoJTz75pIkeWbFihYka2R1333033nnnHSOGBIOi7QuCIAiCIAjeiCeIIAiCUKq46qqrkJGRgf/85z+7fe3mzZvN6x566CERQARBEARBEITdIiKIIAiCUKrQ5W7fffddpKSk7Pa12lvk9ttvx9lnn71P9k0QBEEQKjraf6swf6NHj0ZpYubMmSZ1dvHixSjt6H3Ux/Ctt94q6V0pl0jcsCAIglDqOOigg8zf7ujWrZv5EwRBEARh3/DHH39Y9++//36MGjUKI0eOtB7v0KFDqRNBhg0bZkzYtf+YUHEREUQQBEEQBEEQBEEoFL169bLu165dG36/P+7xvWXHjh2oVKmS/BpCsSHpMIIgCIIgCIIgCEKRof26DjnkENSpUwfp6eno1KkTHnvsMeTm5lqv01EZHTt2xK+//oo+ffoY8ePCCy80zy1fvhynnnoqqlSpgmrVquGcc87B33//nTBN5J9//sHxxx9vqs/ptFodJfrJJ59En9evP+2008ztww8/PJqyU1C6yfz583HBBRegdevWZr8aNmyI4447zlSkY3Taj97Whx9+iDvvvBMNGjRA1apV0a9fP8yZM8d6ra5Jon3MmjZtavaze/fuGDFihDkO+m93zJs3z6QA6+Oq04bbt29fKA81wUYiQQRBEARBEARBEIQiQ1ds05P15s2bIzk5GVOmTDGV32bPno033njDeu2qVavwf//3f7jllluMQKCjSrZv327Eio0bN+LRRx9Fq1at8MMPP+CMM86I+yydinPUUUehZ8+eeOmll4y5+kcffWReq6NKzj//fAwaNMhs+4477jCiwf7772/e27JlS8/vsHLlStSsWROPPPKIiXbR+/L222+bz5k0aRLatm1rvV5vu2/fvnjttdewZcsW3HrrrUY0mTVrFgKBgHmNFkkefvhhXHrppTj55JOxbNkyXHzxxUYcatOmzW7TebRQ1KRJE1NJr169evjxxx9x7bXXYv369bj33nv36DeqyIgI4hCJREyD14qjVvQEQRAEQRAEoTyhV6O3bt1qVqz1hFMQipqnnnrKml8dfPDBRlDQkRV6Al+9evXo81pc+PTTT3HEEUdEH/vvf/9rIjG+//57I3BoBgwYYESNl19+2fqsK6+8Evvtt5/xJAkG86a3AwcONMKAFibOPfdcI2LoiI58r5LCpO7oSBb9l084HDZiiv4svQ/8HfO3+95770Xva+Hj9NNPN9Er+vM2bdpk3qPFGf4OOhKmd+/euxVBhgwZYuaoY8eONZEmmv79+yM7O9sINVoM4eMqeCMiiIMWQBo3blzAIRMEQRAEQRCEso9ehW7UqFFJ74ZQDtGREjoy4ffffzciBzN37lwTTZGPnrizAKIZM2aMmfDnCyD5nHXWWZaAoIUSHV3yxBNPmPuhUCj63DHHHIP//e9/JiVFp43sKXpbOoVHCxv6cziVR0d3uOh0HKZz587m/yVLlhgRZPz48Uaw0MIIo5/bnVFrVlYWfvnlF1xxxRUmNcf9ni+88ILZ/tFHH73H37MiIiKIgz7Z8i8K+QrbvkKfWD/99JNROZOSkvbpZ5cH5PjJ8ZO2VzaRc1eOnbS9soect2X7+OlQfb3olz/uFYSiZOnSpSbyQ6eLPPvss2aCr/0v/vrrL1x11VXYuXOn9fr69evHbWPDhg2oW7du3OPuY2vWrDH/33TTTeYvEToiZG/QkRc6dUantRx66KFGrNGRUzp9xf0OGh3pwmjPDk3+a/V3SvQdvB5j9Hu18PH888+bv6L8nhUREUEc8lNgtABSEiKIVvb054oIIsdvXyPtT45dSSFtT46dtL2yh5y35eP4Seq3UBx8+eWXxtPj888/Nwag+UyePLnQ7VALClo0cVm9erV1v1atWub/22+/3XhsJML17igsOgJEp9JoLxFXbNBGrXtKvkiSL9y436ugaBAtwOj0msGDBxshKRHaf0UoHCKCCIIgCIIgCIIgCEVCvqiRHwmR70Pz6quvFnobOvJCV3fRniCc4qENT12BQ3t9aONVV6xwcSMzCvM9+Dtovv32W6xYscIYte4pOgVIb+/jjz+2BBudxqJTZgoSQbRoqo1idZqRTrPRZrPC3iMiiCAIgiAIgiAIglAkaLNOPUnX/h264ov2s3jxxReNMWhhOe+88/D000+bqjEPPPCAER20IKKroWjY0Fd7hGihRJuh6kowupSt9iHRvh0TJ040pqv5BqSaV155xaSC6RQdHT3hprHkc+yxx5oSuu3atTPCw4QJE/D444/vtY+OLt+rU2x0dRgd2XHSSSeZMsDDhg0zKUG7MynWqUUHHXSQSTXS3iBaNNEGx9qv5JtvvjHGsELhEDtoQRAEQRAEQRAEoUjQosFnn31mRA8d8XDNNdega9eueO655wq9jfT0dDOpP+yww4yQcsoppxivEV01RsPpKDpCQqfO6Meuv/569OvXz4gEP//8s7mdjxY8nnnmGRM1ord74IEHGvGgINFBizBatNClbr/++muT4lNQWd3docsEa1FHR5RoI1V9TLRAVKdOnd2m2OjqM1rU0WLOXXfdZTyFLrroIgwfPhxHHnnkXu9TRUQiQQRBEARBEARBEIS9QkdL6D83ikL/uei0GGb06NGe29XmvVpMYXTKi05T2X///a3HdaSGTjPZHdddd535KwxalHjttdfiHnf3WQsq7vfS6EgN93G973feeaf5y2fRokUmaoWrxiR6b/7jr7/+eqH2X/BGRBBBEARBEARBEAShVKHLvuZHlmgzYR0ZoiMndHRGWS3trKNQPvzwQ/Tp08cYI+vyvboMr76tozqEfYOIIIIgCIIgCIIgCEKpQpuBal+QxYsXIzs7G02aNDHlanUqSFlFp/n8888/Jppj8+bNyMjIMJEkOk1md2VyhaJDRBBBEARBEARBEAShVHHhhReav/KENnjVXiVCySLGqIIgCEKBTPltOL595z5sWrNEjpQgCIIgCIJQppFIEKHCsWbJDKyY8yv2bxEEwjuBFucDSVVLercEofSxYwWevb47rn91tblbvfJQfP3Bf3HQcZeX9J4JgiAIgiAIwl4hkSBCheGvEW/jtMMbo3HLjvjPQ1cCf10KTLgO+LIJMOF6rF30DyLhEHKztpf0rgpCqUCNOQGfjM4TQDSbtikcfPwV+PC5wrmqC4IgCIIgCEJpQyJBhHKPikRw9Rld8d/h06KPta1PL8jNxIjhz2LAI89GH6pZxYcW9Svhvntvx1Fnx0pYCUKFYdsi+DZNwJi7gVdHAVe+GXvqjgf/i9OvfAKBYFJJ7qEgCIIg7FMikQhWrlyJKlWqmFKngiCULnRZ4a1bt6JBgwbw+73jPUQEEcq9AHLjuT0sASSjEtCoVTeo+vXhW/UdwhHgpg/s923YqrBh63Ycfc5dOPiRx/HpN2NRt2nHff8FBKGkWPWj+S8YAK4YmIr/e3QG2rRpjdWbI1i8NoQRnzwmAqEgCIJQodACSOPGjUt6NwRB2A3Lli0rsIyyiCBCueblBwbj6fcnRO/fen5P3PHEcFStGTspclZPxjEjr0Dy2KnYuDUHKzaEkJ0b28Zv0zLRp1c3jP19Auq36Lyvv4IglAzr/4jdPnI0qtRqgRcevgGnXvGkeUgLhFuOuhBVanBYVUx8nDPxJ6xfvQT79TgK1es03Zd7LgiCIAjFgo4AyZ9gVa0qfnL7knA4jMcffxyTJ082f6tWrTKPT5w4ES1btsTdd9+Nv/76C/Xq1Yv+6dKz3bp1w44dO5CVlYWUlBQkJSUhGAyaKAFddvepp57CkCFDkJycbD4jFAqZP12eV7/m77//xvTp07F69ero3ymnnILTTz8dX331Fc4991yzH/q17dq1Q79+/XD//febx/Rnpqam7tPjVNHZsmWLESrzz9VyI4LoxtqzZ09MmTIFkyZNQteuXaPPLV26FFdddRVGjhyJtLQ0nH322XjiiSdMoxYqJi+//UX09lE9auGRN8fHvSatXlc8/MYfeJgmcJnrluCGC/vjre8WmMcWrg6h2/5dsHTKt0huesw+239BKCkG3z4cddOBA1r4cNYZXcxjx5xzO9KvfxLbs/Nec8cVR+H5j6dY73vnycvw4NNvYe6KHHM/PQV49fFrcdY1sXQzL/S5l71zO1LS0ovjKwmCUIpYs2o5ht1yMZq36oAuPfujUnplM3Bt2qxZyeyQUoCkNwi7IT8FRgsgIoIUD2vWrMGECROif5mZmRg1apR57ttvv0WdOnWM8HDAAQdgv/32Q+vWrY2w8eyz3uMMr99Kzyu1SKGf1wJJIo488kjzlwg91+zfv7+Zg2phRu+vnnfq7enJeMOGDY0wovdV/3Xv3h09evRAIBDYq2MjFJ7dpauVORHklltuMTk+WgRhtHI3aNAg1K5dG2PHjsWGDRtw3nnnmbyg559/vsT2Vyg55k0agckLd5rbKUnAFyPnFep9Pr8f1eo2x5vfzse5wx/HgDNvQd82wGfXAcm/DwI23gJ0GgoE04r5GwhCyfDgNYfjvTE7zO0OTZJx1vN5qxhpVWriitMPwBPv5kVXffj9NDyVtRVJqXlq+2cv3YTzbnrF2pYWTM657jksnD8bdz6bl2LjsnPbZvz47p245NyTsXFbBF89fBAGXf8/IDmjmL+pIAglxU2XHIP3vtWpqrpfeNo8dv4RlfHmw+cAzc4B6hxc7PuQu2Up3rj/ZEyePg+rN2zHkb3b4qrHxsKXUr3YP1sQhF3nYW6uET506sI///yDAw880DxevXp1Ixr06dPHzOf0pNad/5U0WszIjzrR4gaj9/c///lPVMz54IMPzGPar0K/74svvkD79u3Rtm1b8ZcpAcqUCPL999/jp59+wmeffWZuM/rxmTNnmvA0LZJonnzySZx//vl48MEHRa2tgIz69u3o7aFXDURqerU93sbhp96Mb97Owubx96Ba/uL0rMfw1usvYnuNgbjk9jeRnFa5CPdaEEqe/7z/a/R2V8tFGHjsrb+wcllttK25ERcfrpA08mCEj/wV5x7XCR+MWGp577Rvko7xs7cjOQhkLvgJkTW/wV/XnthMHfsZDh5wKrbk6ZU4ugtwTMOxwE+9gT7vATX2L+6vKwjlhsiWBVg78xts2bQO9Vt0QZXWpwD+0rfiuHH9GgwfEfPq0rSoAzx71jZg/st5fzqF9fvOQPUuuPjKW9C63e59udYtnoQXH7oYM+YuR410hcaNm+Cim55F3VZ9Yy+K5GLrgm9x0zXn47WfMhFRsae+/HsmrnmuBl4Z0hGXPD4J8O8aJodzgEBy3v8qjMjSz+GvewiQLt4QgrA3bN682czlvv76a/N/p06d8Ntvv5nUleHDh2P//fdHs2bNyrQ4oNMxLr300uj9nJwcLFiwIJp2c/nll2Pt2rUmkuX444/Hcccdh759+5pUHaH4KTNHWSuEl1xyCb788kuTo+Xyxx9/oGPHjlEBRDNw4EAT5qTVt8MPPzzhdvXz+i8fHbqUr0rqv31J/uft688tL1jHb+dKjP/5/ehzB/U7aa+P65Gn3wacfDV8vx4LbBhnHpuyYCue+c9wPPSfz3HeST1xyyOfID2jLsoyxdn+dmzbjMDqb5FaqRpU/aMAX+kblP8bytO5m5O1DWs2R6L3r7zhrrjv9faHXyE4cpeYsXkKZj+bgQ9GxJ4fcGBNfP2rFkR8eOHWI3BKi/FoVhtQE65B7pHjAH9eVZlJv36Env3ycmnzGXbKroj0LbOgfjkSocN+AqrlpT3qEtZfvH4nvv3f15g+dxXWbs5Gk7qVcPXlF+CUSx6ukNVqylPbKwnKxfFTYfgXvg7/nKewY8NCdLwO2LANSE0CbjilIe54+nuk1GxXqo7dXdecgqy8jLko7RsA67YCVXcN8T79E3jsvalaKsVjz7+LWhlJuPHyM3Dt3S8hyUlz1ibn00Y8i4OvGhVN18tjHe58+SAcvp8f/3noSrRpkIzA3Kfgz9LjPVgCCHPpU9PRMjUJh/fphBXLF+Ou97diZw6wNQv4aRqMofrpfVLxzvfz4U+rg7LY9sp0mxfKJPn+GDpiX8/LtO+GFjtuuOEGIwJodISE9tsoj2jxQ0d+5H/PxYsXGwsHLQTpKBG9eK99TnRUiZ67anFEUq6KD5/S8UWlHL2LxxxzjFHH7rrrLtNomjdvbnmCaKVNP64jQhid3/XWW2/hrLPOSrjtoUOHYtiwYXGP68aYSGwRygbtct5Hy6xPMWUp8OtsoMnxHyCY/C9/T6VQMzId3bJfwMMfr8GDX8We0uk2JxzUAP2PPxe1mvYwKTUCEMrJwt8/vog3h/+GoSdHcEU/YLuvLqYnX4DVgZ6Sf10K2bR8Ei64Oq9PPLZXLVx822sJX9cj6yHUD/9lbq/eDNS/Ku/xvh0q47o7n0Vyek1z36fCOGznDaiq8qJE1vk7YkTm6XjowfsxY1lsEK6r0Dxz70Vo37EzDsx6HFXUcvP4rR/5MGVVVWTnhDF66jbP/f7toTpIanMxVgcOKHcim1A8+FUufIgg7EucB17a2Z65DuunvI5r9h9vWVk88S1wM1U8a9/Ah1uvOhXV9jsHpYElc/7C9bc9ZCw4tGfQW8/ejJS6PRBAFhqExqFN7nCkRdbhyIeAUTMTb+O0I1ui/0mXYL+6W9E69BVqR6YbUeWkp4EftG7iwaJnYARZjf78s17IE1t6dm2JeYtXYf2mvDRAzcFtgV/uAI56DBg5I/H2TuwOXHn9HdhR2Q6DLwtoo0jtZ6D9FmSiVXj0YmlGRoYctz2opvPaa6/hk08+MWkfOpp/+/bteOedd3DssceWeKUdvRD+yCOP4LbbbvP0BNlXpZd1RoNe0NfzXn1cdJSINnbV/iennnqqGKwW8TlaoiKIlwDBaEfecePG4eOPP8avv/4aVc4SiSBLlizBjz/+GKe66RPtzDPPLHQkiG5469ev3+cXBa3KjxgxwhjsaIMfYe+PX+qfp8G/6jvzeHi/oYh0uKPoDqeK4M/vn8ftd96PsTPyIoeYzs1Tce5pA3DSuTejcUvdPiOAP0WbjaA0U5TtLxzKxcf/vRHDHn8Ni9aEoqt8Mx6L6R7hBscj3PM9+IKJXbPDoRxsWL0AGZVTkZLRtFQfv/J07v74wQM47vz7zO3bLuyN+14ak/iF4Wz45z0L/4JXMG32Uhz5sA/P3HcVTr/yqbiX+taOQuDXY4wgkrkDqHU5EArHng/4gRcfuwnnXDEs7/iFtiEwZiC2LPsbja7J8xWJ26YPqJIKk0YzsDPww615j6uUuthS6UAMfW8ZmjVtDgUf/IEguvQ4AgcecQ6SksuXS3t5anv7BBXGmHevxnMvf4hDW+/AjYOAzf7mSDvgPvibnWG9dMfWjXjx4SuwdeMK1K2ZjrYtGuDI/gOhdGRS1XYl9xWUwr1XD8Qjr4429584G+Z7mOf8yZgV7o/LnpqG8VOWWueZjgxpVjcZgUAQJwzsgWH3PQhVIy/3fl+2vXOObo9Pf8kzHX/82l647olY+l2U7HXIXv03nn30drwwfJYRWhNx/6nAXSfF7u/IBvreF0TzFi2RuXU7Rv6dJ6bmc2oP4M3LgMqpQKjlFdjW+EokV2th9l8f168//xCnnXV+NCrt9uOBxeuBNjd6f5+erfwY889i+CvVQ1k6d/V4t1atWjKZ34vjJiLI7lm0aJHxcdS+F1pcyK+mooWP0kRpEUFc9Jz2m2++MaLR6NGjzbmqjVe10apQROeoKkHWrVunZs2aVeDfzp071QknnKD8fr8KBALRP73r+v9zzz3XbOvuu+9WnTt3tra/ceNG87qRI0cWep8yMzPNe/T/+5qcnBz15Zdfmv+Ff3n8Pm+o1PtQ6pNqSkUixXY45036WZ16WEOVkgTTbvivUgpU9tvI248Pk5T6qqX6/PHj1MTRH6lIOKxKG4Vpf2uXzlT/e/VapcZfrNR33ZT6rqtSY89WO6c9r9avmKs2rJyv3nniUtWxaUrc8Tilb4ba8kn7vOPxPtRPt+U93rR2QB3YJl316VBFdWuZpto0TFI1q/iUz5f3/Ji7oNTwmkr9eqpSm6aq0kh5Onefu/OU6G/2+sMXFOo9OTsyVTiUW/CLVv2s1IcpasjR8efKz58+EX/8sjerX146XVVJi71Ot4tjetZWw18cojaunGvOo58/elhN/E/naLvSf+tfiv8M/ZeeAnXiwQ3VKw+cp7K2Ux+v+4itC5XaOEmp8G6+RymjPLW9fcHHj54UbQ9P/V+szei/3DmvR1+3ecMa1bdjNav9DOxMr//5CKUWvK1UaOc+3f8l86apTi2qWPsVDEAteqGKUks+ta53U/4Zpw5oVzPhuXBQ213fY/TxSi3/Rm3csF6tWbNGbdu2TYVCoWJrezu2rFeVU/P2oXZVqOytq3f/pkhEzR/7ivpg2CGqUxO/9T1O67nre3xWR6mp9ym1c6311nVrVqqhN54TfX3HRlA7/rhRqW2LPT9uzsypqkWjaqpNo1S1+MVqZvtzPj1bHXxgW3VQ97bqrtuGqPRKsWvcAc2hVr6AvD6kDJ27JTneLcvIcfNm8+bNauzYseb22rVrVdeuXdXzzz9vHi+tZGVlqaFDh5r/SyuzZ89WjzzyiIrs6t9vuOEG9e2336pwKZxLlKVztERFkMKyZMkSNW3atOjfjz/+aL7c8OHD1bJly8xrvvvuOyOUrFy5Mvq+jz76SKWkpOxRBy8iSNklf0Cxec189dd9UJtegVIjDtsnn71m8TR12wU9VesGSdGBUf+O9gBb/7Wtn/dcz3bp6rt371Oh3MIPfnKzd6p3n7rcCAUdmqSoX796vki/Q6IBWSQcUrP++p+69/JDzT4H/FBV06DC79rf6/nzEk86zXHYv5r6+8dX8jeo1Pw31LxnklXjmt7v4b+vhtBnaTFp8h0qe9v6+P3P2qH+/PENI8I8cfOxau30z/M+bx9Q0oPZouTmcw+MHvtfhj9RpNvOXf2HETEa1gyoY3rVVaM+f84IGQUdv+yd29WimePUvMmjvIUWPTBY+oVSY05U6uN0lflq4drW4Z0r5Yl5Wizd1ca+vK2GevC6gWr9ygWqLFCe2l5xM+/He6zf/9bjfCrns2bR3/6KflAnHt5OTZs4VnVrZQsN+u/cg+P79E9uqac2zvpyn+z/yuXLVPP6adY+1a8G9c0bd3i+Jzc3V11zzkHmtf5dwrL+O/lA+3t8ep0v+lxqsl/t37amGjbkdLV+7Spng9uUWvaVUqtHqpzMJeq7L95ROds3qPCa39XmqW+orIVfq/Cq0WrbjDfUst+fVZEtC1Q4c75SoWylQllKTbpNzX4c6qjOUDed1WGvjsPsPz5VV5/SVnVonKR6tU1RkWkP7HaxY0tmphr+3n/Upg3x144C8diuXqA7+sjeRoSJvLfrOH7VYo9EsZI+d2UyL8etqJg8ebK69NJLVaVKlVTdunVNv1NWKAsiCLNp0yYjLum+unnz5uqxxx4zQQVCORVBXBYtWmS+3KRJk6KP6ZWLjh07qiOPPFJNnDhR/fzzz6pRo0bq6quv3qNtiwhSdskfUIz56j/RwdyN53TZp/ugJ2kjPnrETCTfuall3gTrhx5KfdtZbXkjORrdkP/XvXW6GvHJ4ypcwMpb1o6t6s1HL1Kt6scEFhMJ5Yd68tbjCxVVsnXjKvX7/15S915+iLrouDZq/1Z5ERf3ntNQqd9OU2rRBypnx6bogExv87t3hpnXJJo8zn1SD/p85k9HuyQSNHq1q6x++fSxhIPIUZ89oTo1SzXRMvyepECeyNKsTtBEh+gJ82/PdLcG6w+dDtWuUbL6/r0H1IzxX6sX7jldnXBQPfO+/O2YFUYdhfNVq7zV2mKMBioNg9mi5Kx+TaPHcc6EH/fJZxbp8QuHVGjjLPXtuw+ot5+4XL3/zJXq5fvOVOf0b2JFleg/3W65benJzP7N8p5LS4a64+KD1eolM1Vppjy1veJk0T/Drd++ZkaKWrF8mTluiz4eoLLegqpROb4fq1UF6sMnz1NvPXe7GvXJ/UrpCfeXzU17+f3ePGGhYXWon16/qlj3/9tPXozbt0ev7lXo9+tJiRa1d2xeqbaumKgW/nCjJf5pYSJRX6+vWZ1bVDHXjcFH1lSfD0mKE4LuOjEv8jH/9Ym28+rFzrn2QZLKXlc6I/v2iOkPW8fw3Sugdi7+oUycuyKCyHH7t2zZskX17dvXnOMNGjRQw4YNUytWrFBlibImgmh0RMgff/yhBg8erJKTk1Xjxo0lKqQiiyD5ESODBg1SaWlpqkaNGkYA2dNGLSJI2SV/QPH6IxdEB15P33aiKi1sXTtf3XfV4apRzbx0Lv7r2DRV3XPZIeqNRy5Qy0fcqNQfFyj18+FKfdlMfXa9Hf7r/v3fwGYmSsTFCBnv3qdOOriBtQLIf4+fTYPSL5qoKR/9n3rrsQtM1Eei12sh5rYLeqk1079WKmerUtkb1dppH6sLj21tRI361f3qqtM6qbHf/LdQ4ox+zZol09X2zHUJv0MU/Vm/nqKeO7dwK/y3HGsPuHN+OFzdf/UR6uHrB6pbzuuhzj26hTpnQDN16Ynt1LArD1f//PLuv/ptS3owW5S8f1tbdfUAqBO7Q23bbIeWFxf76vjt3LreCHBn92+q2jRMVi3q7BLzvmyq1C/91IzXe8ZN4mpU9qnn7z7DCIlRti5QatH7Sm1frkqa8tT2ipOrT25p/a7zZ+WNH/Rx++qL4WrGx2cY4Ytf07S2X80a+078xkLZKrL0S9W9TeXoa3Ufe+clB6nsndvU0iVL1Cfvv6HuuG6wuu6i49SqFf+unfxv+BuqcmosUqNKKtTMnx799+Ju9qa8djziEJX1YU3Vv5Nf9W4N1aa+t5jRt42TQvROXjTK7vrk1vWgdr5J751yryoX6N9g1jNGQP3gKqjUJKgj9oMKz3reCLKl+dwVEUSO295OwH/55Zdoasa1116rPvvsszJ7DSqLIgijo0BGjx5tbq9evVqdeeaZaubM0r14U9yUaxGkOBERpOySP6C4/uxu0YHXN2/do0obWzeuVE/deryqVy2xuPHJtfYgc9KDseeO6FZNjRz+hLr9wj7We7q1TFXZ059TKnOOGZT9+uWz6qgetTwHpPlpLaPvsj/rj6Hxr+3dvrK676oj1dI5f5b0oVOTf37J+EIk+k61qvrUWf2aqKduPUEt+HlYXs7+ru/1zwMFD9D1gF8LIpnr89Lr9pSSHswWKbtWudWn1ffZR5bU8csfxDELJv+sLj2hTVwb0ZPcft2qqc7NUtScJ3adMx+lKTXl7jyRroQoV22vmPjtw1us3/LbLz9MePx+eu0K41ehPTbuOKelylwxpcDtLl2yWPXr2czadtVKfuX3x+7rSfHfz3VQasnw3U6KE7Fl3teqRd1Yn1evGtT4z+5WxYJOH9T7mL1JLRz/thpyRhvVtXkwTkRf8l53pX49WYV/7Ks+uLmReaxujVTVr3dr1b1DPdVjv3pqvxbVVIOayapWVb95v+5jP82/tv12Rl5qTDni19fOiuszPr23S4FCaUmfuxVVBFm+fLk655xzzGKpXjTt0qWL+ueffwr9/op63DQ6yr579+7m+48fP16VB8q6CMLo36RZs2bGHuKCCy5QS5cuVRWRTBFBivfAFQclfUEs6+jj9u7Lj1iDkNn/fK9KKxtWzlOPDjlKNatjR4Y8eiYJE59WV5s/7WxWrn/7+gXr/cNfutkM1vV7LjyU3vNBwOS28zbrZPjUSQfXVy8OO0uN++4VE3mhiWRvUWrp58Y7Ra9kHdw29h4d2fH+M1ft3vByH6PNWf9zzxkmbeO4PnXVIzccpSaOej/xfmqjwM/rF+hZwn/aa2XLXggh5ebc3TQ91o6+7bTPPrY0Hr9pYz9Sx/epk7CdPHCaE9r/WQM1d/wnJbKfpfHYlSaWTPvZ+u2uPqtHgcdv/exv1YaZXxQ6ykKnMt596UEmlW930Xbq6zZKTbs/z1ejAGEuJ2unUlnr8177YbJa9lxedEbP1kG1bc0+XuGLRIwY9PeIt9Xsaf8Yw/l89DHTK8Dam60ggz79nXZs3ZQnfGwvW6HyhWXunNmqRrVYZBCnZs76fmipPHcr4mRet9+mTZuq888/X/35558mslxP7OfPn1/obVTE4zZhwgTVv39/87179OixRwUnSjvlSQTR6O/x3HPPqdq1axtfzNdfjxl+VxQyC3mOBndTZUYQyhTTx39p3W/e4SCUVmrUb4Vbnvwe1963GeN/fBMrlszD5s0b0ad3T6DnEUB6MyA5AxkA3j81/v2nXPYYRjZohjtuvxX3nrwt9oQK47qBwIs/A41q+vHYPVfgtMsfRzA5LW4bvuQqQOOTgEYnYseyMejU6Sp06KBw/Iln4Oj/uxs+f+krS1u7cXtcOewjXFmYFzc5FWh8Mo5vPRLVu3yGlNRKqFajDho23w/BpBSsXDwDH7zzMl75crZ5+Qlds5H+Y3PgkM+BRseZx3Kzd+CPH17H9199gPETZ0EXFT/zlKNx4c2vIjmtMsoVU26P3U5rhIpMx75n4MvfTsOoz5/EPUMfwO+7ymH7fcDsDTWB5oOAxR8AKoRh76/EsM9PR4+2VXDmyf3R6+Cj0XPA+aY0r1CyPPfITdb9Iff8p8DX12x7zB5t3x8I4L6Xf8NxJz6Py68egkmLQmhaC+jXtSqa1/HjpAOotuvWuZj749246LRhOP+UvmjTohEyt2zBoiWrMW/JGkxfsBGTFmxH7SoKc5+Mva1RTWDMs31Ro99bSK7eCvsUnw9VG3RG9wadEz4dCARQt25d+Au4Vvh8PqRVrpZ3p1IDlEdat2mLDZu2Yuitl2HYY69EH1+3BWh/9FBcPWAoHn1jHCo17F2i+1nRefTRR9G4cWO8+eab0ceaNWtWovtUFvjhhx+wbNkyfP755zjxxBPNOS2UTnSZ32uuuQbnn38+nnrqKXTr1s08PmfOHDRq1Ajp6eklvYulBp9WQkp6J0oTJVn/W9eM/+6773DMMceUSM34so4+flee2gGvfT3f3L/nskMx7KXRKPfoU3jl98D634E1o4HsdUCV1hi1qhsOOvkOJKVUKtRmKnL7G/XZU1j8y1244KCd0cfmZjbBpS9lYtK8TGyJPRylRd0gfvj+O7Tu1r/cHLsrB9XEzm0bzSRu6As/AvUH7JPPLe3HLxzKxdhvX0a1Wk3QouNBqJJRI++JLXPx9TMn44R7Z8S9p351P7q0qob2rRqjSZMmyM3Jxs2DuwCRXCC1NrbtiOCCW1/Fjp3Z2LJtJ44b0Ac3P/7tHguPpf3YlSgbJ2HaK/vj6R+AN8cAf4z6Cr0OO774jl8kF+EtCxFIrWF+47wP2Aos+wKY/SQ2rZiKXvcCc1ftflPznwJa1t11p9lgoOerQCAFpQlpe4lZuXIlzj99AEb8bvcLn14LnHr1i0Cry4y4VNLHryTHuyVFhw4dMHDgQCxfvhxjxoxBw4YNceWVV+KSSy4p9DYqwnFbtWoV7rvvPtSoUQMPPvggsrOzjeAZDJY/YV9/t0ceeQS33XabERDKI3qqf+CBB5p2f88995j2nlSOxwuFPUfLX2sWKjRr12dGb//fZXeiQqAV+YbH5P0Rh5fYDpU9Dj9lCHD4YcDvZwJb55nHAllLMWaq93sWrgmhx8ED8eoTN+KEix6KPh7OzcH6FXOwbfNa1GvWEenV8mcypZ/hYzeZlcvGtQIYuo8EkLJAIJiEQ0+4Ov6Jqm1w1M3jcOnE7njzf/OQG449tWpTBKv+3ogf/t6oQ2yQFABu3P8n5GscOoZoy3rgp2l598dO/wGbN/XCA6/8Dn8wb3CSvXUNUtZ+B2xfBGTsB1TfH6jaep985zJPTibw44Ho1AR441Lg+XsHI90RQIocfxIC1drajyVVAVqcCzQfjFXjPkbNmtcAq9Z7biIlCejcPA3LI23RsllHoN31QI0Dine/hSKlQYMG+OHXqfj6yy9x7uAzsHVHCG9dBpzaE8DfVwDBykDz/5OjXgIsXLgQL774IoYMGYI77rgDf/31F6699loz+T333HM9J8n6jydY5ZVwOIxnnnnGTJT1MRk2bJh5vLyKAxUFHbkzfPhw3Hvvvbj66qvx7LPP4vXXX8dBB5XeaPl9gYggQrlizYZYWkjDlnkhYIJQKGrsDwyaBUy/H1j4OupUXW4erlXVh/49muCoowZiwMlXY/K4r3DJdUOxfEMYm7crvPvqEzix+ivYH10x4Zlr0PuWZdZmG9UMoE+X+rjo4ivR7/SbS22KRG7WdqzbkhcYWL9maknvTpkhOa0qXv5yLl6KRDDqsyfw+5gfMH7CDPw+dR0yd8QCLbVAsnE7UKtK7L23HhcTQTQPv/k3Rv1RDeeeNgAjRv+J3yavMhEBGRTMtTWtO575uTIuufEp1GshfZwnSz82qYH5pHe7GSWKz4cOfc/E71PPwPjfRmDk959i+vSpqFSpEurVrYfmrTuibfuO6NitN6rXrFOy+yr8a3R60Iknn4zZvZbgmw+fwyGBR2NP6muMFpmzYos2wr4hEomge/fueOihvIULnSowY8YMI4x4iSAPP/xwVAwoz+zYsQP9+/fHH3/8geuuu85MmKtV25XGJpR5dNrX22+/jZtuugmXX345zj77bMybN69CC1ylczQuCHvJqg15an3NKj5UqlpLjqOwZ/gDQOeh5q9y7g5sP207KlXdFda+i6Oad8JfvQbhqP590LVRFl6/BAiGt6AxfkWjBkDv1sAfecEkBi2WfDJyOT4ZeQfa3zoM991xDY479x6kBCPAiv8BG8YDa3/FkbfPN2k3B3ZuhvMuGYIe/S+IT43QqU85G/NC7HM3Axmd8va5CFizNBa6Xb82zdSFQqF/qyNOu8X85f1UCquXzMTMCT9j5dJ5qFWrFtIP7gOkVwayVgOhnTi4TxVMOWon3n/jWTz21h/mfeNn78D4+2PeRjqN4/qjY5/z0bf/4J7XgUde3x/dW1dGi8a1kJWdhXee8mPe0k1msr1pay5uOKkehgzukect1PRMoGb3CvNLbtiwAe89dg+uPTQvUA59PwaqdUJpWZHrfcgA8ydUjKiQy258BFjYHhh/PpasA9qcNxc5obo4oxdw/uDTAOyZD42w99SvX9+kxDDt27fHZ5995vme22+/3USOcCSI9hUpT9EfWrTTguyhhx5qfFMqeoRAeaZTp0749ddfsXjxYiOArFixAosWLaqQv7mIIEL5QUXw/HnAsvVAbkr9kt4boYzjS6qESkmJ/VTqt+yGSfO2InviUASXvQZkrYk+d0G/DKRU8qFq5VQsX7MFM5fsQFZu3nOzlmXjtCueQO+nnsS4+5KASI55fGcOMGpansbxz7yZePGzi3FMz9vxwf8mIKNWY+Rm78T0US+jq+9j+LRosotbPvRh4opqOOu043DBLa/HR5nkbgGmDs3zi6naDug0DKic2ARu1ZKZse9XZ5fnhfCvJrv1m+1n/rzQSS+dmwGdDz4D/Qc9g2uH3I5Zy7Kiz+sopFCNPkCfq4GN/yB78Ve4/8s8z6Md2cCv07eZv0RkZy4Dlu2KSpr9FND0LGyodxlqtjzEPLR+5XxMGf89du7YjkOPvQRVqtUsNyu93To0xrK1O/HWT8CDFzTHMWefXtK7JVR0WpyHz3+cgFOufz760MfjgUopn6Lf0ScDzc8s0d2rKPTt29cYRDJz585F06ZNPd+jJ4rldbVcH4sLLrgAV111Fc4555xohIxQvtH+Li1btjS3n3vuOTz++OMm+kf7v2gxrKJQ+ko/CMLekrMBx+8fwVUDgOvP7CLHUShWtOCQduADwMmrkXvcMoxOfRKhk9bjkv9uxqjJm/DV2FWYMG87Nm7YgCduPhYNasS626BfRQUQzYI1QMDpjb/7cx1q1m2C845phS6tq6PvCTdg6eyYAKLZlqXwy6RNuPiOd3DkAbUxZ8IP0edGfvoYfn8gA5jzNLDhL2DROxh2XnO898SFCb/PqmWx8JX69cqOj0l5od+p12PKvE145s4z0O+AWnju7jOxcu123PTsWKDZmcD+TyDphFn4+vOPcPUZ3VAnI3EEkPYeqVfNTrvR1Tqn/vYB6rc9FF1bpBjPl9oNW6PfKdfiuMG3o27dWjhnQDN89+79yM1cZAxfsfJHYM5zWP3LDfjy+Qsw+uNh2L65EI6eJcxfo780Aohm8hLdmAeW9C4JgqHzEZfHHYlbj9UXE0k/3FfccMMNGD9+vJnsz58/Hx988AFeeeUVIwJUJHT0x5NPPomuXbti/fr1aN68eUnvklBCPPTQQ0YEeemll0x7GDt2bIX5LUQEEcoPtBqPNJnECfuQ1LrIDLQEkuJdqNOq1MCNj32DuQtW4tk7TsRxfeqgZaMqQNW2ZnUeB76IjteuRG5IYdOaxXh0yDGouquacTgCvPP9AhNBoqNFrnt310artgfq9UdIJUc/Z/SUzdivx9G45owuaFYniCNPvxUvjAC2xwILsGgdcO4tb2LepJ/i9nPVisXR2/UbVOzyuCVFUkoqrnvgI4z4Zx2uue9DJKWkxQlvXQ85A89/NBFrNoewecNa/DnyU/z38Zsx4bfPTDnnnJwcrNqkcMnL2cDxC4AuDwMpNXHLh3m+JFMW5WD5hoi1Xd22PhixBIPOvQdTX2gB/K8tMPooYMJ1mDfmGZx07Vs4/MyhaNSoIYZdPQBbN3sbe5Y0X3303+jtwQcHcczFsZV3QShJWrXtgC8++yR6/6Kj62NViyehGgwq0f2qSOgKGV988QU+/PBDdOzYEffff78xAtVREBWFNWvW4JBDDsHNN9+MK664ApMnT0afPn1KereEEowKufHGG0070Gm7AwYMwLp16yrE7yHpMOWcrZtWIyUIJC99I6+yQK3eeRM1rvGtY/Cz1gKpdezHyxg+XRo2n1QRQYTSha4Sc+2DX+DaAl5TrU5T3PLktzjhrO9x762X4avflkVTado3TsZxp5yJyGkvwZ+UNzn+70HZ6Pnk5bj63rfM67Ro8sInsZI2H/0BTFwMzPz1HYx49Vys35p3ug9/+0nc3s32JFi9akX0dv1GsipUFsioURvdDjoBq7YkoVPPYxDkkneBZKByC2C/2xBueQX6/vZ/mL36RyxZm4uMSj50aVkVXds3QnZ2Fj79ZSE2bsszcR03FziAfv5KFAWujYCH/mcEvv+lJUZPWInUSukobYwdPyl6+/HXRgB+GeYIpYcTTz7N+AXpaiM6Ze77778v6V2qcBx77LHmr6Kiy97q0sDaF6Ii+kAIiWnbti1+++03TJgwAbVr10ZWVhZmzZplzIPLKxIJUk6JhMP4/NXbUatOfdSpVx/rfrsTGH00MLwa1n3YAa/cfw4ev2kQurWshHtO8QNf1AM+rw1MuRPIKr2rfAWxYvEs/LUAxngs2yeeBkLZpW33o/HRL0uxesVijPvfi5j159eYsXgnLrr97agAogkmp+Ci29/E/Jl/mwgTl9YNkvDLmL8QaDUY7c4ZgW8n5z3+zU/j4l67avXa6O0GTdoU11cTSoBAagbufuYbLFyVhY3r12HTtjDGTN2MZz+ejpe+nI9Vazbiy5evx9n9m2JHcmug2f8B7YYAvd5EsxM+xj3XnoQTD24Y3d6fs7fgwI51sWDmX6Xq9wzl5mLi3E3mdrPaftRtfWhJ75IgJER7TGgRRBD2BXpCe+mll5oJblJSEj755BMRQISEUSE9evQwt19++WX07t0b7733HsorskRSDpn55zfYr9fx0fs5IWDIe8C7VwJ/zgd63TtbO+VFn5+8EGhbHzin7wao6Q9h5McPoeFJ/0O7A8tWiObn/xuFIY/k3X73qUX4P7EFEco4GbWboveg+Dxyl4atuuPr39cYseSrj/6DjIzqOOncW1GnSUf4g3nRAc0690ObhkmYuyIXE+ZtQ/aOLUipFEvfWbV2Y/R2/abeZp5C2UVXAKheM75qVnKlajjh0qfNn4u2Sx32bJ6x6JhP7sPRg+816TPTF21Hn7598M+EaWjcoj1KA88/PAQ7svMiWrq3r1WmIxsFQRCKgpUrV+Lkk0/GlClTMHDgQBxwwAFyYIXdctlll5kUmcGDB2Pq1KmmVLQWScoTEglSzoiEcnHTdRfFPT78L+Crf4DDH0z8votezfMO2J4NjJwJdOh5LD56/hqoiJ07XpqZOm169HbdBokrYAhCeaZ9z+Nx29M/4oqhH6Fei25RASSfXp0bR4XRYw+2U16O2T8VFx4KHN0FqN2odExqhdLFoaffgy9evhFpu6xo1m4Oo0nLDnjgit7A6pFAOEuHIZbY/j32zEvR2wMPO7DE9kMQBKE08PfffxsflGXLlpn0l1NOOaWkd0koI6SmpuKNN97AU089ZUx0jz/+eJPGV54QEaS8sGMFFr3XF4GkZHz/p21o06FxMt5+7EL0v+w91KiceGXsg6v82LgdaDUEeOirPN+As659ATWrBvHi0DMRCYcSvk8/roWS3KztJSqYrF40BW99uyB6v27DvNJPgiDE6NO7V/T2zxM3Yt2yWXl3dq7BZb2W4PVLge/uqWvSbAQhEQPPfwIzxn+D6mQH0gTjgZFHAh+nQX1SGb893gZvDhuE3G2r99lB3LBmGVZvyrtOVasEXHjbW/vsswVBEEob2iT7tNNOQ+PGjfHPP/8YMUQQ9gSfz2cqKn333Xfo0KEDkpNjZvzlARFByig5O7firkv64KSD6uGAVqk488hG2LFyHBqRFUbfDpWxdsl0zFiajdOvfx2V2p6D8eP/xFdv3IVje9dFw5oBfPfuMKxbNhsnPx1G42sUPn//v2jXKNbIN21XuHLYxwgEkzDsysOxfvmu+upKYerYz9CuSSX4AwEkp1VGi/rJeP3h8xDKyStPuC/57Ye3rfstOx2yz/dBEEo7517/nHV/2p/f5d2YuSuPTJNabx/vlVDWaN7tWPw0/D8Y1LMGzuwNDCZvPV8kCz/8Pg8XDv0OyVXq4+ePHtgn+zRn0i/R22cf1Rb+tPi0H0EQhIpQ/nbr1q1mwqonr6NHj0b9+vVLereEMszAgQNNGV0tinz88cf48ccfUR4QEaSM8ujNJ+DB1/7Al7+vwcQF2ahfDWhVFziqc97zusTm97/NQe0mdm5/o9YH4vgL7sc341Zj+foQjv6/e1CrUdvo830GXYGRY/7CcX3iJ0JDXxyN9h3aQX23P7LeTcUxx5+KeSt3la4AsHhtGBff8Q6O6dMIWzYsx75k4/pYedyrTuuE9Ix4k0hBqOikVamJVx8cHL0/fdIug9TNsYoyaFZxSgUKe0/3o67E/8ZvwAffz4Zv/yeBpmcC1TpjRWaqiSbM5+JrhyJre2axH+pebZKx9DlgxO3ApWcPLPbPEwRBKG1kZmaatAUdAaKrEOnVe53WIAhFgVLKmOoec8wxePrpp839soyIIGUQbWj45JujovfTU4BB3YCUJOA/Fwbw+WPHYOqEsahSo8Febb9+iy74+vdVyFy/HKce1sh6rmZlILxhElKDOXjnisTvHzFhIw4+sDWWzPod+4qNG2IVbQ7vd9Q++1xBKGt0OiBWMWPa9Bnm/4sf/QeXvgY8+a3On7u5BPdOKGv4MtoC7YcAfT8EjpmC4PEzcOHJee7ymiXrwjjogKYIhxKnVBYV/m1z0bgm0K8j0KXH4cX6WYIgCKWN+fPno1evXvj9999NCoNUHxKKGp/PZ0SQm266CUOGDMGFF15Ypn1CRAQpY2xeuwSp6RnI3BF7bPAR1XFIv5OBfmOQPDiEk27+Fk3b9/3Xn1W1ZkN8OmoZZoz/GkPOyXOTnrMK+Gdh3vNH7AcsfbUhFk4bY0ry/vjBQ1HPkamLstCsw0F47MZjsC/YuDFW2aJGrb0TfwShIrBfj2NwYAsYE9T+HcPGy+f90Vvw6ijgjbHiBSL8O+o2bIHXP/sTv3/zfPSxCXMy8dKDFxbvod2+KHa7Sqvi/SxBEIRShK7e0adPH0QiEfz1118mfUEQioNAIIBHH30U7777Lj788EMjhpRVpERuGePlR+zwi3H/e7FQJTT/DR16Hocnex6HS2/4HplLxqKb7xMgLQPo8hAa1z0C8Oc1owFn3Y5xbbrh6EHHYdGavFW/cWO+R/jXMxE48FkgrW6x7ePGTbFw62q1Gxbb5whCWady9fr466lmwPbFQHA11q2YjaxdWW2N61Yu6d0Tygm9j7kS+7e8ERMX5Jj7Hw7/GlfdW4wfuH1p7HZ6k2L8IEEQhNLFqFGj0KhRI/z000+oVUv8kITi5//+7//QpEkTtG7duswebokEKWN8/ePY6O2jDqyBXkdfus8+u+0BR6PHyQ8i6aR5wFH/APUHRAWQ2GuOwrg//sFphzfC6T2BT68FAss/Br7rBEy8CdnrphVLFZmNm7dFb9eo07TIty8I5YpqnfL+D23Dsr/fjD7cuL4MnoSiwef3Y2x+2KAWxGdkYtWSXdWIioHH35uKV0cCo+emA0lVi+1zBEEQSgvr1uVVg7zuuuswbtw4EUCEfcohhxxiTHfXrFmD888/33jSlCVEBClDrF06C3/M2hote/v9XxvMQLO0Ua95F3wychk+euMxJAV3leTNXofQjCfRsm1nNKmTjLceu6hIP3PIyXXw2iXAY2cBNes1L9JtC0K5FUF0itvIJ6K3mzVtXEI7JJRH0qo1xF0X9TS3q6QCXz97erF8Tig3B7e9sxGXvg7c9H7JlWoXBEHYV/z6669o2bIlvvoqz4laDFCFkmLFihWmHfbr18+yJyjtlL4ZtJCY0HbUGNMBo+4EhhwNXHL6v/f8KG582mBx0AygZi9z/+3fgBWbgOUbwrjg1jfw8v1FV4Xi4DZhXHQYcMOxyUipVK3ItisI5ZKmZ2LVJuCtMcDZ/4k9vH+Pg0tyr4RyyMlnXZz3/4HASa2nAyu/L/LP+PqdhxDZZVLfuF5GkW9fEAShNDF27FgcffTROPDAA83EUxBKkv333x8jR47EokWLMGDAgDITESIiSFlh4VsIBoBD2wNP/h9w/S3DUCbIaA8M+B04egpy6wxC09qx9JlbH/kAW9YvK5rPyclTHnN9VYpme4JQnqnWCe/NPwIXvGI/fMAhp5TUHgnllK6HnY+BnYGpS4E6Wp9Y/nWRf8ZjTzwZvd22pV3RTBAEoTyhjU91idIePXrgm2++QXp6eknvkiCgW7du+OWXX7Bw4UIce+yxxqS3tCMiSGli6xxUjqyIe/ibt4biobuvxvasXQ/UOACoXfojQaL4/ED1zrj8gf9h8dpcnDOgmXlYV7h5/Ymri+Yzcjab/3IhFwNBKAxHnXqldb953SDqNNlPDp5QpPgCQXz/+2J8d8uuB9aOLvIjvGxtrFzazfe/UeTbFwRBKA0opXDbbbehU6dORgCpVKlSSe+SIETp0qULfvzxR1x55ZXwl0K7BpfSv4cViMC0e5Ax4yqcclgjTP/1Xfz5/UsYPLApjr9gGO78BOh1L6CqdcszJdXCQhnlzvtfiN5+4a3vkLVt07/aXiSUjfGzd2DmcmDlluQi2ENBKP906nsKXhx6Jo7qUQuHds7A84/dWdK7JJRTfJWbom6LvLRIbJkN7FxTZNvWRtvrMvNWnLo0T0XNxjG/G0EQhPIkgPh8PgwfPhzfffcdKleWam5C6ePAAw/EWWedZdrrO++8g6ys/BX80kfZnUmXN7Ytgm/FV3h3LPDNuLXodOi56HXMFXjvp1jZv+nLgU/ndkFZp32PQTioY557/8I1Idx2yeH/anuZ61eg91Bgv1uBK19cW0R7KQjln8vv/RDf/7kOo6dsxqBzh5b07gjlmOzqfTF2DnDPcOCNZ24usu1u3bQKueG827WqpRXZdgVBEEqT8aSuxLFkyRLUqFEDGRnifSSUbhYuXIjLLrsMgwcPNoJIaUREkNJCSk1EOj+EX+fYJWeZprUDGHhO+ZioPPXUc9Hb7387FeHcnL3eVuaGldHb6WkSCSIIglDaGLuoJg6+D7j/C+CiO97F4tl/Fcl216+cF71dq7qsjAqCUL7YuXMnTjzxRCxevBgpKSklvTuCUCh05aIPPvjARC498MADKI2ICFJaSKqKSNshuPPRd3H/9cejWd3YZF7P6797ZxgWrNiGjNpNUR44sP95OOXQhub2+q0K4398ba+3tWXTqujtyulygRAEQSht9B10qTH3zuerdx8vku2uX7Uoert2TakMJghC+UGvoF9yySWYMWOGKUFar169kt4lQSg0J510EoYNG4Z77rkHX3zxBUobZU4Eyc7ORteuXU1e3OTJk63n9GPu30svvYSyRFJKGm59bDgWrc42nd/y+VOxZOE8HD34HgSSUlGeOG7Q0eb/htWBtbN/2OvtZG6M5Zenp5WvYyQIglAeSK1cEz+9F4tkHP3buCLZ7rrVS6K3a9WqWSTbFARBKA08/vjjeP/99/Hmm2+aMqSCUNa46667cOqpp+K9995DacM796KUcsstt6BBgwaYMmVKwud1R3HUUUdF75f1vLmGLcuvydsJg2/FxNzX0LWpFrC+AVb/DNTb83rnWzavj95OE6dsQRCEUsmhp96BGpcMw8ZtCr9OWoVIOAR/4N8NQ9o0TMOjZwIbtgEH9yy/10tBECoeHTp0MKkEZ5xxRknviiDsFbpKjDZITUpKQmmjTEWCfP/99/jpp5/wxBNPeL6mWrVqJlws/y8tTYzSSivV6rVCtwMPhs+364EZj+zVdlgEkXJhgiAIpRN/MAmHdK1rbmshZPof/z48tnWDAG45Dnj0LOCIww4qgr0UBEEoWdauXWuiwY899ljceadUbhPKNmlpaQgGgxg7dixOP/105ObmojRQZkSQNWvWmLy4d999t8CJ7tVXX41atWqZEj06FSYSySudJ5RSerwSu73uNyC0Y483kbl5Y/R2WiUxxhMEQSitHHrQrlK5APoNOh3h3H9ZPi87JoIjtfa/25YgCEIJs2nTJvTt2xd33HFHSe+KIBQpWtjT3iDXXXddqTiywbJy0M4//3xcfvnl6N69u3FITsT999+PI4880ihOv/zyC2688UasX7/e5CMV5DGi//LZsmWL+V+rVPtaqcr/vNKikO0TKrWEv9mFmPnrG/hxWg76VHoRBx597R5tYvOmTdHbqZWqVKzjV4RUyPZXRMixk+Mnba9wHH7cBcAjX5rb67YAP3/6OI447ba9PnyBHWuiqzm5gQx9Mu7R++Xc3Xvk2JXt4yfX+tJHKBQyqS8bN27ExRdfXNK7IwhFysEHH4z//ve/uPTSS9G5c2czr6+wIsjQoUONa2xB/P333xg3bpwRJ26//fYCX8tihzZP1dx3330FiiAPP/xwwn3QaTcllVoxYsQIVCTmjtuEWx7Lu9153B0YFm4Bn7+QQUpKYduimKlqWqWqFe74FTVy/OTYSdsre5Sl8/aYXnXx3fg8Q+svPnkHWemd93pbjVZMRhM/UKMy8MtvU5HtX1buj19pQ45d2Tx+O3bseeRteUPPAXTEhV6ZfuaZZ0p6d3DzzTdj5MiRZg6iS4wKQnnjkksuwdSpU3HNNdegffv2OPTQQyumCKJTV84888wCX9OsWTNjCjR+/Pi4+tg6KuScc87B22+/nfC9vXr1MuKJTqWpWzcvD9lFCytDhgyJ3tevb9y4MQYMGICqVatiX6vy+mLYv3//UmkgU1z06b4fbn/iC4QjwNTFOdgw9xucO+Tlwr05cxoOXAH8MgMYPx9Ir16vwh2/oqKitr+iQI6dHD9pe4XngE4/o22HTjioDXBQq5045phj9vrwHdFtMMbO0Oba2h/qBKSk7VlKpJy7e48cu7J9/PIjnysqepH1lVdeMSvSpQEdwa6FmOeffx5HHHFESe+OIBQbTz31lOl/qlSpgpKkREUQ7d2h/3bHc889Z4SQfFauXImBAwfi448/Rs+ePT3fN2nSJKSmphqzVC+0sOKKKxp9QSqpiWBJfnZJULthK/Tdryp+nZZ3Qf7q6+9w0a2F/P7hTDSoDlRJBa4dCNRu3qfCHb+iRo6fHDtpe2WPsnTeNmrREZs/646kzH8ArAC2zQKq791EZH1mnqdI5VSgctXqFeL4lTbk2JXN41eR2/u2bdvMIuqrr75qzS9KksMOOwzDhw/HySefXNK7IgjF3vfkBzBo705dQaYkKBPGqE2aNEHHjh2jf23atDGP61CxRo0amdvffPON6cymT5+OBQsW4LXXXjOOyjrvKJHIIZQuvhk5PXr7j+lroQpraJu7zfz30+3AU48OLa7dEwRBEIqQpEYDYne+7wKEdu7VdtZnhsz/taqWCYszQRBKAVdddRUGDRqEfv367fa12jdQr1rzX1Ezd+5cBAIBnHLKKfBFSyYKQvlmy5YtxgRYm6WWBGVCBCmsqqTNVnr37m1C25599lnjB/Lkk0+W9K4JhaBqrcY4ukees//6LQoLp48p3HELbY/dDkplGEEQhDJBY2e1c8Nfe7yJKT88ifVblbldK0MWOwRB2D0fffQRJk6caPxACoN+XUZGRvRPp8wXJXoCqL0R9D4JQkWiSpUqqFOnDq644gps2LBhn39+mRRBtE+IrhiTb36qOeqoo0z6y9atW7F9+3ZMmzbNGB3pusRC2aDH/u2jtyf9/m2h3rN27SpMXQosWANsz624oZ2CIAhlihoHYC6Owg3vAn2HAq+9/Pweb+KmO+6P3q6eUTJG5oIglB2WLVtm5gbvvfeeSZcvDNo7MDMzM/qnt1FU6ImfrpBx7LHHolu3bkW2XUEoC/h8Prz00kvIyckxRqn7mjIpggjlk64H9I7enjxxfKHe89FXY9HldqDVEOCrUbOKce8EQRCEomRz3XPxzA/AuHnAr+P+3vP3b4uVFh149PHy4whCGTOG1YLCnDlzTEnYfcGECROwdu1aHHDAAWaRVP+NGTPGeA/q2+FwOO49OqVeF0rgv6JCT/z0cdATQUmDESoi9evXN2bAH3744T5PixERRCg1dO09KHr7zc//QDgUG+B6sX17nieIJj1931bzEQRBEPaeLn1OQDCQd3vy7NV7/P4t22PXiCHDXpOfQhDKgCHpyy+/bExAdWqJjuzu0KEDateujaZNm5rymbpqS3Fx5JFHmkjxyZMnR//yK03q29qXY1/x1VdfmYmfngDqiaAgVFTOPvtsDB48GDt37p032N4iuSJCqaFp+76oX92PndkR1M+I4J9vHkLPk+4t8D069Smf9CrVkFcnQBAEQSjtpKRVQpuGqZi5NAtzVuQglL0NwZTCeztl7sgzRW1Se99NXARB2DuefvppPPjgg0b4OP7443HbbbehYcOGSEtLM5EgurDBb7/9ZkoG9+rVy4gDrVu3LnIPAl1ggUlPT0fNmjXjHi9uDj74YFMSV08ABaEi4/P58M477+zzzxURRCg1+Px+fP7fq9Al63mkJes6iut2+55tJIJUqlIdWfGRjIIgCEIpZb9WdTBz6VLkhIDv37gRx13xcuHeqBS27MgzRa1aSfygBKG0M27cOIwaNQqdOnVK+HyPHj1w4YUXmtSQ119/3aSpFLUIUlrYtGkTatSoYfxJBEHIQ3uD5FduOvHEE1HciAgilCp6nXAH8MUug7xtC3b7+u3bY6FT6VWrY+Om4tw7QRAEoSjp2L4NPh251Nw+/spXELr4WQSSCmFYGMnG7/cCW3YCgZpt5UcRhFLOp59+WqjXaQ+OK6+8EvuK0aNHY1+i02DOP/98U8xBR8UIghCr9Lpu3TpcdtllOPTQQ1G9enUUJ+IJIpQuUusCwfTCiyA7Ygkw6VVqFueeCYIgCEXMoNOvsu6vWjipcG/MyUS3ZsCh7YGDujWR30UQhFKPNkG96aab0LNnT+OBIgiCnRbz4osvGquDRx55BMWNiCBC6cLnAyq3zLu9fTEQKTi/ZfvO7Ojt9KoiggiCIJQlDjjkRBzctW70/pJ5Ewv3xtwtsdtJGcWwZ4IgFDXa+PDhhx82fiCrVq2qcAf4jTfewIIFC/DYY49JNRhBSIA2CR4yZIip2LRixQoUJyKCCKWOV0b6MfARoNX1uVg6988CX7t9B4sgtfbB3gmCIAhFyQkDekZvL5k/vXBvys2M3U6SymCCUBa46KKLMH/+fGNE2q9fP1QkduzYgWHDhhkj1M6dO5f07ghCqUVHS+nqUT///HOxfo54ggiljhnLFX6alnd72fypaNKuT+IXKoVtWzYhJQnIztXGqCKCCIIglDXatN0PnZt8jaa1gFqVClcib+WyBRg5FqiaBuxXJYJd8YOCIJRitP/GiBEjsN9+++HOO+/E2rVrUadOHVQEtNdB+/btcd9995X0rghCqaZq1aqYN2+eqeZUnIgIIpQ6GjZsAGCKub1iyRzvF676ASd2Bw5uB/z3Z8AfkOYsCIJQ1jjuxFNwXOrDeXda6tJgu2fipKkY/GLe7ftzF+Cu44pxBwVBKBK02eGzzz6LNm3aoEmTJhVGANFoD5BffvmlpHdDEMoEVapUQSgUwsiRIzFgwIBi+QxJhxFKHY2aNI/eXr5sofcL14/HbccDW3cCfVr79s3OCYIgCEVLpcax2ztXFuotmZvXR29XrSqeIIJQFnjttdeMGLBmzZoKJQjosr/7ugqNIJR1Pv/8cwwcOBB///13sWxfRBCh1NGoaazc4YrlBZjihPMqw1x0GPDpR+/ui10TBEEQiprkmoBv13Aka3Wh3rJta8wYtUrVavKbCEIZID093aTBPP744xWmOsry5ctxww03mBVtQRAKzymnnGJS57SRslIKRY2IIEKpo2HzjtHbn/wwGZFwqEAR5MCWQLW6rfbV7gmCIAhFiT8ApNTOu521plBv2bYtJoJUriIiiCAIpRNthlq5cmVj9igIQuEJBAJ46KGHjICovYSKGhFBhFJHw1b7I3mXvcfyDWF889a9CV+3YtV6zFsNLNsAhFTSvt1JQRAEoci49JVc7HcLUP+C5VCRyG5fv33b9ujt9CqSDiMIpZ3LL78cy5YtK9RrP/74Y7z//vso68yePduUxdXRL9rsURCEPeO4445Dnz59TDRIpBBjgz1BnCSFUkdqejWc2a8F3vkhzw9k4bwZCV93x3/H450f8m7P6bsOzWUxUBAEoUyyZIMPM3dlP25euxjV67Uo8PXbtm2L3q5ctUZx754gCP+S2rVro2PHjmZCc/zxx6N79+5o0KABUlNTsWnTJsycORNjx47FRx99hIYNG+KVV14p88f8gQceQOPGjXHFFVeU9K4IQpnE5/PhySefNNViihoRQYRSyeDzL8U7P9xmbq9btzbha3Zm50Rvp6WLAiIIglBWqVtLR3NsMLdXLZmxexFk+47o7cpVaxb7/gmC8O+4//77cc011+D11183RqHTp0+PqwbRr18/Y55aXNUg9jX//e9/TfRLSkpKSe+KIJRZevXqZf6KGkmHEUoltRs0i95et35jwtdkZedGb6dWkjBDQRCEskq9OjEh4+rLz9vt67fvyPOE0qRLJIgglAl0Sdzbb78dU6ZMwYYNGzBx4kT8/vvvmDNnjokGGT58eLkRQMLhsEmB0caOgiD8OzZu3IizzjoLEyZMQFEhIohQKmnT4QD8MRSY/xTw9BWJTU93ZpEIki454YIgCGWVrt26R2//PXvTbl+/jUSQylV3maoKglBmqFatGrp06WJWeFu1amXC3ssLWVlZ5jt9+umnJb0rglAuyMjIwLhx40x0VVEhIohQKkmr1hi9WgMt6wKV/YkHxFk5saoxaZUlJ1wQBKGscta1z0dvb8sCsndsLfD1qcEIMioBAT+QnlFrH+yhIAhC4dARLYsXLzYijyAIRVMp5rLLLsMHH3xgosaKAhFBhNJJIAVI2pXikr0u4Ut2ZuWJIHoQHExO3Zd7JwiCIBQhPn8Ax/etF72/ac2iAl///i3NsPlVIPcdIKNmffktBEEoNfznP/9B//790aZNm5LeFUEoN1x00UUmzeytt94qku2JCCKUXlJ2hThnJRZBsnLC5v9UqY4rCIJQ5qlZrXL09oY1iwt+cSivRK4vKd0IKIIgCKUB7XMyfvx4XHnllSW9K4JQrqhbty5OPfVUvPrqq1BK/evtSXUYodQyenYyZs8G1m3djNtP2Ilgcpr1/M5dIkhaSvnJIxUEQaio1Kge83bauHZZwS8O7SqRG0wv5r0SBEEoPGPGjDFlcY899lg5bIJQDGWndbWlovAQkkgQodTy6GfrcMWbwD3Dgcz1y+Oez8qJmP9Tk6QZC4IglHVq1KgOvw+oWRnI2pZXLnf3IkgsekQQhLJDKBTCzz//jJdffhlbt+Z5AK1cuRLbtu06t8soN9xwA2bMmIFgUNaZBaGoadGiBRo2bIhIJG8O+G+Q2aNQasmoHIv8yNywIu75ndl5oVBpKdKMBUEQyjo3X3aC8fhY/zLQv1cTz9etnf4FfKeuR6ULgIc/z0uLEQSh7LBkyRJ06tQJJ5xwAq666iqsW5eX9vzYY4/hpptuQlll2bJlZnJWpUqVkt4VQSi3/P3332jSpIk53/4NMnsUSi0ZVWNhzpkbVsU9P/3xZMx7Evh2aIt9vGeCIAhCUZOUXhv+/FFJ9kbP1z103+3m/505wMe/ZsoPIQhljOuuuw7du3c3VR7S0mILXieddBJ++eUXlEW0R4E2Q7322mtLelcEoVzTrl07bNmyxUSR/RtEBBFKLRlVY0p65sY19pNKoUFGNlrVA1o3ieWRC4IgCGWUZCp1nuMtgixdHRM+mjQTEVwQyhpjx47FXXfdheTkZOvxpk2bYsWK+MjfsvKd5syZg9NOO62kd0UQyjVVqlTBueeei9dff/1fpcWICCKUWjIyYuJG5qa19pOR7NjtgJTHFQRBKPMkVy+UCLIzKzd6+9V3viruvRIEoYjRExdd6tJl+fLlZTaV5KuvvkL9+vVx8MEHl/SuCEK554wzzsDq1atNaszeIiKIUGrJyKgWvZ25ab39ZDgrdjtgV40RBEEQyh4btypc9w5wwcvAs+97D2x2kAiSUaPuPto7QRCKCp028swzz0Tv60oP2hD13nvvxTHHHFNsB/rhhx/GgQceaISWOnXq4MQTTzTRG0WRCqNFkOOOOw7+aE6fIAjFRe/evVGzZk2MHj16r7ch1sVCqSWjes3o7czN9qrg1s3r8cq3QFoy0LbzVhx5eAnsoCAIglBkhHxpeO7HvNvHhZbhOo/X7cwOmf91hbyUNKkOIwhljaeffhqHH344OnTogKysLJx99tmYN28eatWqhQ8//LBYy9dqI1YthOjqNHfeeScGDBiAmTNnIj1978tta2+TQCBgRBBBEIofXX1p+vTpqFu3bvkXQZo1a2bcpJlbb70VjzzySPT+0qVLTec2cuRIY7SkO9UnnngiLudQKBtkVKsVvZ2Zudl6bsO61bjpg7zbZxyxDEfesK/3ThAEQShKqtZsGL29ZRtF+znszM4Lo9ciuF5BFgShbNGgQQNMnjzZCB4TJ0406TEXXXQRzjnnHMsotaj54YcfrPtvvvmmiQiZMGECDjnkkL3ebo0aNTB79mwTESIIwr6hXr165n/df+xNBFaZEUE09913Hy655JLo/cqVYytAOrdw0KBBqF27tjEn2rBhA8477zzTIT3//PMltMfCv6FazZi6l5lpVwDIyY6VRUxOTpIDLQiCUMZJqZSBpACQGwa2bM8phAgiAogglFW02HHhhReav5Iif2ypRYx/gzZzbdiwoYiygrAP0XP/nj17GpPUvanKVKZEEJ3Dl6/6uPz0008mnE3XDNYKs+bJJ5/E+eefjwcffBBVq1bdx3sr/Ftq1GqAhtWBjEpAzZx/ABUBfHlKX07WjujrkpPKVDMWBEEQEuDz+1G1kg8btipkbo/5frjszMlzg09Lltx7QSgrfP3/7Z0HlBPVF8Yv2+i9995BpEgV6b0XaYqogIqCCAiIFEFUmjRFpSlS/gqogEpRkSIdlCKKIEV6byKw7C4l//PdZbKTbLKbrdnJfr9z5mx2Msm8vMxM5n3v3u9+953H27Zu3VoSGkySDhw4UB5//HEpV66c2+1CQ0N1MUBpTjOXL1+WAgUKyBdffKFmjYSQxAEpaEihw7XF50WQCRMmyNixYyV//vxagmrw4MH2VJft27frRcwQQECTJk30woUwN+QexuTidvfuXV0SE2N/ib3fpErJR6rKmRkR/9+7sEVs2Wro4+Dgm/b1gYEBDt8X+y92sP9iD/subrD/2HcGGdL4y9Wb9+S/4Ptur+WNyvvJpX8fSNbMaeN8veexx77zFt4+9hJ7vzAh9QSkuLmqHBPf9O3bV/bv36/R49GZqY4ZM8bt86tXr1ZBpW7dugnQSkJIdIJp//795d9//5VMmSIKaviUCIIPWKlSJcmcObPs2rVLhg0bJsePH5e5c+fq8yiT42yOgm0hkuC5mF7cEFmSJk0a8QZr1671yn6TIo1TZJXUtqv6eM+2VXI+4Lo+Pndwp32bkDt39EfIgP0XN9h/7DtvwWOPfZcuVXh0x3/BNofrupnPXnigpe3+9cvmdhsee4kHz1tr9l9wcEREbWKAvP2kQr9+/XT2eNOmTZIvX74ot8V4AxEj5slSTMYa4H0Qkh8Xg0ZCSOyAGTH8QOH306VLF+uIIKNHj45SXQWo/1ulShUZMCDC+fKRRx5RgaNjx44aHYISOcCVQRrU2aiM09xd3OAWndgpNFDl8WOI0mGBgfS5AH5H3xLZGx7iVKlCKbEVDC+dtuX+cXu/Zc2WVUuqsf94/HkLHnvsPx578cOUkamQ8Chh90Qa1H1cUqZx+h1+cFf8vgkfTGXInEua149bOU2eu+w7b+HtY885rSM5gDEBBJDly5drac3ChQtH+5qUKVPq4gpUtvnxxx+1ygwhJPHBmL1ixYp6LbWUCIJQtOgajKowrqhevbr+PXr0qIog8ArZuTMiOsAoWYUfmajUWXcXN/wgeUuI8Oa+kxp3bCnlwiWR4DCR7EUuS45i4f1y/16EaV6qlCkd+ov9FzfYf+w7b8Fjj32XIR1EkPDB2Z3/Lku6jBGl0pW7d+wP/QLTiF88/Vby2GPfeQtvHXvevM/84IMPXK7HpGWqVKmkWLFiWq0FOf/xCWaM4d3x7bffqs+gESmeMWPGWFWlQVlftDcxPEwIIa5ZsWKFgx2GJUQQmJlgiQ179+7Vv7lz59a/NWrUUAPU8+fP29chpQUCR+XKleOx1SQx+X7jQen8MAjo/cFbZFD1Ifo4LCTiRpglkAkhxDfIkC5iIPLftXOSPX8pxw3uRVz7xd87KauEkLgxdepUNRRFSg4iuxGhgZx+pKGj8uOlS5ekSJEismHDBofUk7jyySef6F9n/w6UykUhhZhSvnx5uXjxYqzKcxJC4gcYE8cGS5y1MD3FBRM1xeEDsnTpUnnxxRdVeTU+ONJXypQpI927d1eBZN26dfL6669rSV1WhrEuadNltD8ODo4oixsWFmJ/TBGEEEJ8g2rl80qHx0SeqyOS8sikSM+fPf2PFHxVpNTrIkNmHfZKGwkhceO9996Txx57TCMprl69KteuXZPDhw+rt8b06dPl1KlTGuFtToWPDyC2uFpiI4CAsLAwjVaJKu2eEJKw4BxGMZTZs2cnvgiCi8CtW7ckoUA0x5IlS1S5hdAxatQoFTe+/PJL+za4CK1atUrD0mrVqiWdOnVSJ+r3338/wdpFEp40aSNEkNu3I0y8UgelkFJ5RIrkEMmameWPCSHEF3i1z7Py9WswPxXJF3Qk0vO3/rsmp66K/H1e5MJ1VlIjxIqMGDFCJzeLFi1qX4cUGNyzw6sPZqUTJ06UrVu3SlIFFWwQzf7pp596uymEJGtSpEihkWSbN29O2HQYhIzt2bNHPTmeeuopvVhNmTJF7t27J/Xr15fFixfbjUrjC1SF2bFjR7TbISpk5cqV8bpv4l3Spo8odxR8J0IEaVK7jBw0JgkrP+GFlhFCCIl3ivYS2fVC+ON7kSdX7ty+YX+cJrVrs0JCSNIGqesYNziDdYZPB3L8b968KUkVRK6gfWYhhxDiHWB9AbPjBIsEgecGTIUOHjwor776qvTp00c+//xzefvtt2X8+PFy6NAhVXcJiS/Sps9if3z7tikX/EGEMar4B7HDCSHEF0BYecYy4Y/vRaRAGty5FVHRInVqmKgSQqxGvXr1NK3d8PcDeIxxBSZUwR9//OFR9RZvYbQdlSkIId4FlWShQ8QkMyVGkSAQPBD21bVrV/ntt980dw9pKihVC8qVKycvvfRSzFtOiBvSpM9sfxx8J9S1COJHEYQQQnyFTX89kNMnRIJDb0nPDvfFz1QhItgUCZI6FUUQQqwIxhLw8MPsrVGlBlEgDRo0sKeXwCB18uTJklSBT2Hx4sW1sgwhxLvgWgJvEIiTFSpUiH8RBEZFjz/+uF1xCQgIUGdkg0ceeURD3AiJL9JmiEituk0RhBBCfJ7RX1yQDfvCH3ebfF3SZoyoIhdyJyI6JDYlLQkh3gemp2vXrtWZW6SVYPBSqlQpKVmypEO0SFLm999/Z/VJQpII8AxdvXq1xwJIjEWQu3fvqkmpuSqHuc44RBEYBRESX6RJHyGCBN+JiP5YuupXmTdfJChAZFiaE1K9EPucEEJ8gbSpI6L7bt+45FYESZmKniCEWBkIH1isyIoVK1S8IYR4H+gRzZo108f//ReRNhuvxqh//fWX3bQIJ785/+bKlSsxfTtCoiRNhoib3+CQiEoAR09elB/2hz/ueS1y3jghhBBrktZkeHr7v6sOz4WGRHhDpUzJdBhCrAgmTJFiv27dOrl06ZI8ePDA4fn169dLUgeRaBkysDohIUkFXE8QDfLWW28ljAiCfD2z8tmyZUt7eRqsZ61sEp/4+QdIqkAR6B+3Q+45lGU2CErJkGhCCPEV0qVN7V4ECaUIQojV6d+/v4ogLVq0UD9BK44dOnToIGvWrNEoeEKI9zl58qSW3h40aJBH28fozD1+/Hhs20VIrNn3fiZJZftX0mfLZV9HEYQQQnyTtGkiRJBbkSJBQuyPU6aiAE6IFVm8eLEsXbpUmjdvLlbln3/+oQBCSBI0R0VlqXgXQQoWLBjbdhESa0oWyCAS/K9I6ojqMBRBCCHEN0mbNo398e1b/zo890TlAvLxcyKhd0WqVSrthdYRQuIKPAWLFStm6Y5kaVxCkp45KrxLYVocryLI/v0PDRg8AFViCIk3Ah7O9t0Ltq8KuxvhD8J0GEII8VER5KajCFKmcGYp0/DhPyWLJnLLCCHxAcLVp0+fLjNmzLBkKgwoVIiO/IQkNXPU/Pnzy5kzZ+JXBHn00Uc99v1ghRgSr/g9NMl7EOEDEhZmEkFSRdwwE0IIsTZp06Z3K4LIg4iIQPFndRhCrMiWLVtkw4YN6qlRtmxZh0qTYNmyZZLUyZkzp7ebQAhxYuDAgZIjRw758MMPJd5EELMfyN69e+X111+XwYMHS40aNXTd9u3bZfLkyTJx4kRP35IQj/hm2205fVIk7H6IDOkcvu7u3QiTVEaCEEKI75AuvUkEueVU6u5+aGSBnBBiKTJlyiTt2rUTK9OwoRGSRghJKvTp0yf+S+Sa/UCefPJJ+eCDDxwMjZACgxCUkSNHStu2bWPaZkLcMnXFJdl6AI9sMmh+qPgHpnRKh0nL3iOEEB8hQ4ZMkjGNSNqUIoF+9x2eu3Dxqty8IJIyQCTXfT8J8lorCSGxZd68eZbvvKJFmY5HSFI0LEawhifEqq4TXFcLFy4caT3W/fXXX7F5S0LckjIo4jANvXNT0qgIYooEYToMIYT4DJ3aNpBOWR6GslYo6/Dcu59ulxlfhT/eWfqkVM3rhQYSQpI9wcHBkiFDhmTfD4QkJb755hsZO3ZswokgpUuXlnfeeUc+/fRTSZUqla4LDQ3VdXiOkPgkKNDfUQTJkE2aV8suuQLPSNg9kQwZs7DDCSHEV/A3+Tzdv+PwVGhYhDdUqtTpErNVhJB45Ouvv9YyuadOnXKo+Af27NmT5Pva3z/i3pQQkjTInTu33Lx5M+FEkJkzZ0qrVq00/aVChQq6DuVoYJi6cuXK2LwlIZ5FggSHH9g9GuWSHuUersySnb1HCCG+gn/45IpyP8ThqVDUxn1IytRMhSTEiiClfvjw4dKjRw/59ttv5bnnnpNjx47Jr7/+Kq+88opYAZTiJIQkLfLkyePxtrESQapWrapGqYsWLZJDhw5pxZjOnTtLt27dJG1a3pSQ+CVlUIRreFjoLZF7t0XOr4nYwI9Z4YQQ4jP4PyyL7jISxCyCMBKEECvy8ccfy+zZs6Vr164yf/58GTJkiBQpUkRGjRol165d83bzCEk07FVXQy6LHPtU5OJ6kbs3RAIziuRqIFLkeZFU2T2qzkpEI0ESVAQBadKkkRdeeIH9TRKcoECzJ8htkTPfO27AMomEEOIznLv0n7w5UyTkrsjjtXZL3ypuRJBUEVVkCCHWASkwNWvW1MepU6e2h693795dqlevLjNmzPByCwlJeJD29eKLvWXZqNKS/9YSEdsD1IGP2ODCOpHfR8jpdF2k/dsHZdas2VKpUiV+NdFEgpQoUUIOHz4s0eEX7RaEJKFIkNA7t2TD5p3Se47IS5+K7LhYUsTPsb48IYQQ63InTGT+ZpElO0S27z/v8FwojKAekjINTQkJsSK5cuWSq1ev2qtP7tixQx8jyhwz3oT4OjjOIYD89tseqdvrf3L6yj1HAUR5oOvr9lokv/22W1588QWeH9GQMWNGTavzBIogJMkT5JAOEywHDp+RuRtFZq0XOSr1vNo2Qggh8UuqtBHiRkhomFsRJBVFEEIsSf369eX778Ojenv27CkDBgyQRo0aaWp9u3btvN08QhIcpLYsG1VGiuQQ+eeSSN13RE6H64J28D/W43lsh4gRpsTEH7FOhyEksUgZFOSQDnP/fsRNcEAAo0AIIcSXSJ02k/3xHZMRKgi9e9/+mJEghFgT+IE8eBA+6/3SSy9JlixZZMuWLVp0Af8T4vOEXJb8txbLxhERQgf+4v/8WSMLILr+1mKRkKkiqbJ5u/VJmpYtW3q0HSNBSJInd46MUiK3SPn8IkEBNrl3jyIIIYT4KqlMIkiIkwgSEhougvj7ifhTBCfEkvj5+UlAQMQ8bKdOnbRizKuvvipBpomvhDRmLVy4sKRKlUoqV64smzdvTvB9EuLAP5+pBwgEDwgc5oiQbYddCCBZkUPzQOSfT9mR0RAaGiqJIoJ4uiNCYsuQ55+Qv98X2T9epHK5Qg4iCG+CCSHEd0WQO6ER13tzJEhKBgESQmLBkiVL5LXXXtMSvXv37pXatWtLs2bN1KyVkEQDpqcPPUCchZBaY1wIIMoDkQvr+SVFg1lgjVcR5Mcff5Rnn31WihYtKoGBgVolJn369FKnTh1599135dy5czF9S0Kixlz95UGoYyRIIMvjEkKIL+HnHyBBAY6RHwY/jc4lRyaL7J6Q0TuNI4RYmilTpqgPSa9evaR06dIybdo0yZ8/v3zyySfebhpJTqAMrgkIHQv7OG6C/yMEEON1/yZ82yxOvIsgK1askJIlS0qPHj00jG3w4MGybNkyFUU+/fRTFUF+/vlnrfONfL7Lly/Hpf2EmI5SRxHE0ROEtjaEEOJrpHoY6XHHSQTJHXRSiuUSKVUgjXcaRgixLGFhYbJ7925p3Lixw3r8v23bNq+1iyRDAh2FfHiAdHfS4fC/s1mqBEZEShLXIEjDEzweQb733nvy/vvvS4sWLVQEcQb5fODs2bMyffp0WbBggQwaNMjTtyfEPX6maI/7YXLvXsRNcUAAI0EIIcTXSJ3ST/6780BCwkwiyJnwahKRxHFCCPGAK1euyP379yVnzpwO6/H/hQsX3Kb9m1P///vvP5friTUxvsNE/y6z1hc5Cy8am5y5LtJiosjZGyIl84rM7iXywlyRE1dEGk0QWTVEJF9mvCiFSNZ6aGzittViTJw4Ub1+4k0EQZRHhgwRZevckTdvXt05IfHFT9uOybTpIqiMOHDAr46eIB6qfYQQQqxDqsAU+vdOmC1i5YWfIx4HpvdCqwgh8cmlS5fk77//1rKfJUqUkBw5ciRKBzuXGbXZbG5Lj44bN07GjBnjMq0GxqrEN5g6daoX9vqG/VHX3hFrNzj9v+i6iGAB/0AAGZ+IbbQeISEhHm3nsQiSOXNmOX/+vF6gUN8bqTCZMjEkhyQ85y7fkjW/hz/uePaiqvgGjAQhhBDfo12NDHLt+nXJkj7iNmXQ1I0y71uRQH+Rn797Xcp7tYWEkNiCaIpXXnlFFi9ebL+n8/f3l86dO8tHH30kGTMmjOdPtmzZdD/OUR8QY5yjQwyGDRsmAwcOdGg7PESwzpPJYZK0QQQIBJABAwZIypSJG2F4Zk1vadF3qUZ8FMpmjvh4+PzDCBH78zM6Sb5mcxK1jVZk0qRJ8SuCpEuXTq5evaoiyMaNG+XuXceydYQkFClTpbY/Dg0JkXJFMkuHx0TuPRDJljULO54QQnyMqS8VFLl+XcQvYnb2v1shcv32w38C0nqtbYSQuAFT0n379snKlSulRo0aGoUBT47+/ftL7969ZenSpQnSxSi/izD5tWvXSrt27ezr8X+bNm1cvgYDY1eDY3friTVJ7O8T0Udd3v1L/j4bqlVg1g6NbIJaNFv4epTL/fus6Pa72gS5jVoiEedzvIogDRs2lHr16qmTMsDFw10t7/Xr4798T6FCheTkyZMO64YOHSrjx0eEBLk6KOD2DKNWYl0cRJDQUOnevqR0L/Zj+IpSxb3XMEIIIQmD38Mw8wehIrYHIin85K7JDyowKOJ3gRBiLVatWqWFFR5//HH7uiZNmsicOXOkadOmCbpvRHB0795dqlSpogLM7NmztTwuxwokMcGYddas2fLii71l2agykv/W4vDfuodlc8Pxk/zZ/GTj3C7S/u2Duj0FkOgx2ybEiwiyaNEimT9/vhw7dkx++eUXKVu2rJbHTUzefvttVYjN0SnOzJs3z+ECmlAhdSTxSJkq4jhT4yKb6eD2Y3UYQgjxOQJMIsf9UP3/7t2Ia39gEHPxCbEqWbNmdXl/jnVIv09IkHKDyHaMKZDmX65cOVm9erUULFgwQfdLiDOVKlWSXbt+Cxc2QqaI/POZyIX14WVwUQUmV32RIs9L/lTZZVdL9741xBFPs1U8HkGmTp3arpL+9ttvMmHChET3BEmfPr3kypUrym3Qpui2IdYiKGVq9yJICn/vNIoQQkjC4ZdK9p8S2XxI5Om6xyRjnnKOkSCm3wVCiLUYMWKERmSgkmTu3Ll1HXw6Bg8eLCNHjkzw/b/88su6EOJt7MJGquwiZYaGL1FtR+ItEiRyrVsP2LBhg1dMUSG8QD1+9NFH5d1339V638707dtXjY8ee+wxmTlzpjx4YA4rIlaPBFmwYruIzVQyMQUjQQghxNfoNfkvqTlapO98kY6t6+q6u3eZDkOIL4BU9R07dmj0RbFixXQpUKCA+oLMmjVLZ8iNhRBCYkKXLl082s7jESS8N1599VWPUmB27typtbhbtGgh8QXMknAxRJjcrl271K35+PHjMnfuXPs2Y8eOlQYNGmjUyrp162TQoEHaDijO7nBX/xuhNIlt/mrsj6azjqTNFFEy7fSVB9Ju0Ar57aBIgL/ID6VOSZHyJdh/PP68Cs9d9h+Pvfgle45ccjs03AfsdnConmNh5tkdv4B4+a3kucu+8xbePva8ea/Ztm1br+2bEOLbIHMFvqHRkcIGe1oPeOaZZzRn7sknn5TWrVuroVD27NntYSd//fWXbNmyRb1DkGOHELfatWtH+Z6jR492WXvbzK+//qr7cuabb76Rjh07qsiB6BBXTJ48WXP+bty4EeM2fPHFF4nueUJc8+D+fWnfoYP9/6I5/eXYxfAZwc8/GiOZ8lZg1xFCiA9xPyxYOnTqpo8fLZxSRk9dItNGdZeN+2/quiWL5kjKdOH3IISQmBMcHCzdunXTe2SWevUcTJbCu4T95htgIhwT/W+88Qar/fgAd+7ckTVr1kiHDh2iPUc9FkHA/v37tX73V199pW+MWtsoJ4QLKahYsaK88MIL0qNHD48OJAgYWKKrCpMqVWQDtLNnz0q+fPk0nK5atWouX7t161Z1nkaeobv6364iQVD/G+1K7B8FqPIo69OoUSMJDAxM1H0ndYY8W12mfbFHH+fP5i+nr4SLIId/Xy+FSoe7i7P/4gb7j33nLXjsse9ckSl9kASHipQvlFJ2H74pTR7LIRt+/1ef+/fKOUmTIRuPPS/C89ba/Yf7XaSPczAf836jCOI7UATxLf78808pX768Po7u2hYjQ4VHHnlEc/XgtQFB5MSJE6q44CIKnw78jQnYPqavMdi7d6/+NQyV3G0DASUq/xJ3daHxg+QtIcKb+06qjOhVS/pX3SMBfiIvL4gQQVKnThepr9h/cYP9x77zFjz22HdmggJSSHCoTcLu2vTYuHs/wuMrTbqM8fo7yWOPfectvHXsJfY+s2TJIocPH9b7fqS2R2X0eO3atURtGyHEN0A2iqfEylUSF64KFSrokhhs375dIz7q1aun6itSZAYMGKBpOTBSAt9//71GfKDmNzxBYN46fPhwjUzxJCqFJG2yZk4nWR9GPvuniLgR9vcP8l6jCCGEJBgpAzFIsknYvfBr/pin88iFU/8J/FEDAlkilxArMXXqVK3yCKZNmyZWB1HwTCMiJGlx7ty5hBFBUGkFS0BAxMsuXryokSG3b9+WVq1aResDEhsgYixZskS9OxC2BDfp3r17y5AhQxwU7Y8//lhLbqGNRYoUUT+QV155Jd7bQ7yAX8Qxd880GxgQSBGEEEJ8EUSCgLC74df8+o+kEcn/sDS6X6yK2xFCvARS5V09tiqYeM2VK5e3m0EIcYoEQQbIv/+Gp87GmwjSs2dPFRtmz56t/9+8eVNL0YaEhGhaClTeb7/9Vpo3by7xCarCIBIkKpo2baoL8VFMpXDvm0WQIM4GEkKIT4sg9x5al9keVrPwY7ooIVYHE5ZHjx6VS5cu6WMzTzzxhCR1MAlMCElaIFAD9h2bNm2KftuYvDGMRmfMmGH/HxVgUBnmyJEjmqaCcjSTJk2KdxGEkN1/XZCtP4ggKvpvU7pXQCBTnQghxBcJCgyP9gi9+1AEefCwRG4KiiCEWBlMbKIyzcmTJ8W5PgNS7u/fD/d9S8oEBTESmZCkxuuvv65WGNAl4lUEQUWW4sWL2/9ft26dlqAxdoTwtnnz5sWmzYREyc87j8sbCyOv9w/gjxAhhPgiLzTNJlcvn5O0qcNvVfYevSX3b4mkTptCynq7cYSQWPPSSy9JlSpVZNWqVRpJHpVJalKlcuXK3m4CIcSJGBS9jZkIgkorqAZjVnIR+WF+/tatWzF5S0I8wt/f9aFKczxCCPFNXmufV+TaOZGHZtht3zsnpy6L5Mx0Sy4M8HbrCCGxBRHkX3/9tRQrVsyynXjlyhUaoxKSxChdurR06tTJo21j5CyGajALF4ZPx2/evFnz4erXr29//tixY5InT56YtpeQaDGb8T5dS2R2T5GPn6MnCCGE+CxG9S/bA5EH9+XuQ2+QQH/rzRoTQiKoVq2a+oFYmddee83bTSCEmIBHKbQIlOCO90iQkSNHqt/H0qVL1X312Wef1TA2g+XLl0utWrVi8paExFgEaVpB5Ck9zFIgH4Y9SAghvoifyfPpQajcvf9QBHlomEoIsQ779++3P+7Xr58MGjRIK6yUL19eiy6YgbFhUmffvn3ebgIhxOkaA6/SRx99VDwhRiPIevXqye7du2Xt2rVaFurJJ590eB47rVq1akzekhCPCDD9QN4z/LJQJpEQQohPcs8WIKEhImH3RTLeC7Ff+ymCEGI9MEaA94c5Z//555+3Pzaes4ox6unTpzUlJlu2bN5uCiFERDUKTJqXLVs2/kUQXKymT58u/fv3d/k83FgJSWhPEFSIUfwYBUIIIb5Kh9H75but4Y8vNjlvSoeJUSYvISQJcPz4cfHFQVeTJk283QxCiISfj+XKlVOPUk+I0Shy/vz5Mn78eEmfPj07m3gtHebQOZGDZ0WCUvpJUX4PhBDikwQFRkT7hYUGy117JAhFEEKsRsGCBcWXgO/AiRMnvN0MQshDPvjgA/Ur9RS/hCo7Q0h8EhAYUQr3/VUiZYaIVHkzmJ1MCCE+SlBghPgdFnKbIgghPgImVVEe12DIkCGSKVMmqVmzppw8eVKsUuHmxRdf9HYzCCEPSZMmjRQuXFg8JcbTKVas5U18s0Suvx+PRUII8VWCgiK8oO7cuiHGPAwjQQixNu+9956kTp1aH2/fvl1mzJghEydOVH+NAQOsUf8aZq6cHCYk6RgVN23aVM6dO+fxa2JsqlCiRIlohZBr167F9G0JiZJMGdNL8VwiiII++PD4DmCZREII8VmCTIbYt/67an9MEYQQawNT0WLFiunjFStWSMeOHdVXEBUm69atK1Zg8+bN8txzz8nBgwcla9as3m4OIcmaHTt2yLp16yRLliwSFhaWMCLImDFjJGPGjLFpHyGxpnmDx6T55PDH+fuJnLkWLogQQgjx/UiQ27eu2x8HBrAyGCFWJl26dHL16lUpUKCA/PTTT/boDxga3rlzR6xAnjx55PLly2rG2LhxY283h5BkzW+//WY3RU0wEaRLly6SI0eO2LSPkNiTInJ1GH9GghBCSLKIBAnyuyf/zhH1BfHL9ahX20UIiRuNGjWSXr16ScWKFeXw4cPSokULXX/gwAEpVKiQJboX3gMZMmTQwRdFEEK8C8TIypUrx+g1MZpLpx8I8RopImb+7j2sEMB0GEII8V2CgiIMse+G3JaMaUSypRfJkimtV9tFCIkbH330kdSoUUMjKb755ht7OgkGMl27drVE9/r5+UmlSpW0zYQQ7xESEiJ//vlnjEWQGEWC0ACIJIVIkPsPI0EoghBCiO+SMmWECBIWclMk5cN//CIiRAgh1gOVYGCG6irl3kpUrVpVFixYoOMjThQT4h1w7i1evFiqVKmScCLIgwcPR5+EJDK/Hzwpb04KjwK5fjt8XQCrwxBCiM8SFJTSoUSuXQRJQRGEECuzf/9+t4MZ5PTDKyRlyojzPz44ceKEjB07VtavXy8XLlxQT4+nn35ahg8f7hB1FhP69esnffv2pQBCiBfBtaJDhw4xfl2MPUEI8QbXbwTL6n2O6/z96YxKCCG+ylOtqkjtjD9JUIBI1kIZZPRckUB/kYpVL0nzx73dOkJIbHn00UejFA5QfrZz584ya9YsFUXig0OHDulkLt4TlWkQPt+7d2+5ffu2vP/++7F6z3z58sVL2wghsad///6aRle9evUYvY6jSGIJ/AMiz/wxHYYQQnyXgvlzSe1SItWKiYQG35Qxy0RGfCXyzS9nvN00QkgcWL58uRQvXlxmz54t+/btk7179+rjkiVLyhdffCGffvqpRmyMGDEi3vq5adOmMm/ePDUxLVKkiLRu3Vpef/11WbZsWZzed9GiRdKqVat4aychxHP+/vtv+eCDD9RfKKYwEoRYgoDAiFDFTtVEJnUT8ctcwqttIoQQkoD4mYxRQ2/ZHwcG8taFECvz7rvvyvTp06VJkyb2dY888ohGVowcOVJ27doladOmlUGDBsU6SsMTbty4IVmyZIlym9DQUF0M/vvvv0ih+CtXrpSTJ09KwYIFE6ythJDIfP/995I6dWpp0KCBxBRGghBLEBAQcTOcM6NIgWwi+XKk9mqbCCGEJJYIcjtCBAmgCEKIlfnjjz9cCgZYh+eMlJnz588nWBuOHTsmH374obz00ktRbjdu3DjJmDGjfcmfP7/D8xBykL6DwRghJHH57rvvtOR2mjRpYvxaiiDEcpEg9wx/Xj/eCBNCiK9y5uJNWfaryJLtIgeOXrSvZyQIIdamVKlSMn78eAkLC7Ovu3v3rq7Dc+Ds2bOSM2fOaN9r9OjR6i8S1fLbb785vObcuXOaHvPkk09Kr169onz/YcOGacSIsZw+fdrh+QwZMkjdunV1MEYISTyuXLkiW7dujXU6GkeRxBL4myJBUCFGSeHvtfYQQghJWLbsPiZdp4U/blf7pH09RRBCrM1HH32knhxIf0EaDIQKVIy5f/++ppaAf/75R15++eVo3wvVWbp06RLlNoUKFXIQQOrVqyc1atRQH5LoQLpLdJVq8FkGDhyoIgmiRQghCQ+qOuFaQhGE+DQBgRHGqHM2iJTJK1Kg6FVp39CrzSKEEJJABJoiAIND7prWs0QuIVamZs2aWrIWpqKHDx8Wm80mHTt2lG7dukn69Ol1m+7du3v0XtmyZdPFExBdAgGkcuXKapLq5xc/AfGoZFOrVi2NCiGEJA4436JLZ4sKRoIQSxAQ6KjCD1gk0qDSOWk/2mtNIoQQkoAEBplFkIiweYoghFifdOnSxWkAE1MQAYK0lQIFCqjZqrmaRK5cueL03tmzZ9eFEJI4wKx46NCh0q9fPylatGis3oMiCLFcOoyBXxQ15gkhhFibwKAI8Ts45J79cQCNUQmxPIgA2bhxo1y6dEkePDDM3sIZNWpUvO/vp59+kqNHj+qCNBwziESJK7/88ouMHTtWfvjhB16jCElgcO1AhamePXvG+j0oghBLkClTFunXWORWqMi8X8LXxVMUIyGEkCRIYFAqlyKIOU2GEGI95syZI3369NE0FkRhwBPEAI8TQgR59tlndUnI0Px169bJmjVrYu1RQAjxjC+++EKKFCki5cqVk9hCEYRYgqzZsskHPUSu3zaJICmoghBCiK8SaEqDTBMkUrVouDF27hyZvNouQkjceOedd+Tdd9/VcHZfoWLFilKlShX55JNPKIIQksBVYZYsWSJvv/22g4AaUyiCEGuQIvxQNUdM+vkxHYYQQpJDJMgTpQNkSteHviCVa3ivUYSQOHP9+nUtT+troJoNwvOPHTsWa58CQkjUfPbZZ/r3+eefl7jAqXRiDfweiiCmtE2KIIQQkjxEkLt3I6rDiB+rwxBiZSCAwKPD10CVmEyZMsmCBQu83RRCfPr68fnnn3tcFconIkFWrVqloS+oJZ42bVp54oknZNmyZfbnT506Ja+88oqsX79eUqdOraW24ACNOsLE4qTw1z/3GQlCCCHJgsCUJhHk3r1IkYGEEGtSrFgxGTlypOzYsUPKly8fqeLTq6++KlYkTZo0smnTJilVqpS3m0KIz1K4cGFd4opl7iS++eYb6d27t7z33ntSv359dXL+448/7M/fv39fWrRooSWqtmzZIlevXpUePXrodh9++KFX207izs1bdyRzdycRhNVhCCHEZwkKSi2pAkUC/UWC/M1hgIwEIcTKzJ49W0vkoqIKFjPI8beqCAIMo0ZEr7Gct3W5efOm5M6dW7p06SJz5851qErSvHlzKVGihFY1giHuxx9/LI888oiMHj1abt26pRPwvsaJEydUvDQbkWJs7irtC+cvxECDQ4cOycSJE3X97du3pW/fvvLbb79JWFiYtGvXTsaNG+extwfKatesWVOeeeaZ5CGC3Lt3T/r37y+TJk1yKIVTsmRJ+2OE1f31119y+vRpyZMnj66bPHmyOkHDfAkHKbEuAUGpHAQQ4MfyMIQQ4rOUKVNK7nwe/njxdpGao8MFkdGjDku9It5uHSEkthw/ftynOw9R6z/++KNs3brV200hsWTx4sVSqVIlHehPmzZNRTuDMmXK6CAeoEzrc889J7t3747RuNaKpd4zZcok+/bti3a7Dz74wP74woULGrXRqVMn/R/BDABZHeiHli1bytdff+2RRxCuGxBQYUAcH1jiG9izZ4+cPXtWB71wX0aHPvroo6q0lS1bVrfZvn27qlOGAAKaNGkioaGhemDWq1fP5XvjeSwG//33n13BdchBTgSM/SX2fq2Azcm+pmRukTzZUjn0FfsvbrD/2Hfegsce+84lD0SMmI/TV0W2Hwl/fPl6cLz9TvLYY995C28fe0nlXhMR2yAuVR6SGhUqVJC33npLxx+VK1f2dnNILPj00081ZWvWrFmydOlStyacjRo1kuHDh0f7foUKFdKMhp9//lnHqpio79q1q447Q0JCpEGDBiqo4DxARMnhw4c1GgUmuygjDaEgS5YsGj2BSApEpCD7AcfapUuX9HmAsTHaC4EBr0P78+fP77VjYMGCBToeR1vA77//rlEc+JyIlGrcuLEsXLjQpQiCPsO26LMzZ87oZ02ZMqXMnDlTo0fwHdWtW9e3RZB//vlH/+KgmDJlinYKDp46deroQYKDAsJIzpw5HV6XOXNm9QPBc+5AJ44ZMybSekSWILfPG6xdu9Yr+03KPLgfkQ9eo7jIttEiZ/xzy+rVqyNty/6LG+w/9p234LHHvjOT6sEVafLw8d37EetPnjrt8trPY8878Ly1Zv8FBweLN8HgCBHeR46Eq5tILxg8eLB0795drA7S8zHwRLlccyoFsQYHDhzQzIKmTZuqmIBUDnciCCJGPBW64F0J30oIABA+vv/+e40wgaVDmzZtNOqkY8eOuu3OnTvl119/1TEuUnIgZgwbNkz/4n2Q/YC2QQTIly+fvuaLL77QcTECA/z9/VVcgGDy7bffRmpLx44d5ejRoy7biXa5Ek4g2Dz22GPa3rZt26r4g/1EV8kF57kBXg+RBq9HEMLy5cvtAQiuuHPnjmzbtk2tLmrXrq1BDehDvMebb76pz1lSBIGo4UqAMIMDADlXAJ3doUMHfTxv3jz90r/66it58cUX3arIUJijUpdxQA0cOND+P74IfPFQphI7hQaqPH4MoSoyjzAy+BoxYXDv4c1wnjx5JWf15uw/Hn9eh+cu+4/HXgIQclHk+4fnmMkXtXTpMtKkecS1Py7w3GXfeQtvH3tRDTwSGkxoYpYdA7RatWrpvTpSR5Dvf+XKFRkwYIBYGaQ6YGyCdHwMADEpS6wDIgwQgYABPgQtHJcHDx6U0qVL6/MQIJCRYIh38+fP9+h9kTZjjEkxth06dKgO7nH8I5oD72mIIM2aNVMBBNSoUcPug7lhwwYVCnGMYUE0yebNm/W5FStWaJqOIcpArHAnUnz9MHLEU+CPgmiMHDlyyLVr17QSEgIShgwZ4vY1OKdxnYGHigE+M8beVatW1fMC/h7r1q1z+x7YD0BGiDmdBp/RCJKwpAiCix/UrahA1AfCgYwcLAOEwxQpUkTVMIAwG6hmznXI8SPjHCFiBu+DxRn8IHlLiPDmvpMyAX7hs4H3HnqD+PkHiJ+LfmL/xQ32H/vOW/DYY9+ZCb4l0vfTcOH7y+0R61OlShPvv5E89th33sJbx5437zNRsABREmZzQ8yEI8UdE6RWF0FAr169ZMKECZrSj1QHYg0wbly0aJGeH19++aU9asoc0WD2BIkJZl8RCIEo4oGxa6pUqXRCHtEhBlhnACEDUR/RTe7juREjRriNWolLJEjKlClVAAEQZ7APRJ5EJYJATEKRErMQg881depU+//jx493GN87Y/QDPEWgGRjGrOY+saQIgvq+ntT4hdqDzv/777/l8ccftx+kcKotWLCgXSWD4nr+/HlVq4yUFryO+Xi+QYB/uAgSYZDq6BNCCCHEd4DgPXt95PWBQRE3h4QQ64F7dcwAO4N1eM4XwAQsUioyZszo7aaQGIDUEUyyo3yzwZ9//qlClhGFEB9goh4T+BjkX7x4UTMbjKiHqEA6CEQaiAIQAZYsWWL3w2zdurX6iiDVBEIFxspoO/w04xoJcunSJY3cgDiENJZly5a5fF8DVMnBPpwNYxEZgggWWE7A6BRiqKt0HTP//vuvmrLGN5YYRSItBaFIMBmCsAExpE+fPvqcYaSC9BUoSQgR2rt3r4bWvP7662pCw8owviOCgP2nRJpNEJmy+KC3m0QIISSBCAxy7csVGBQ5epMQYh1QahM5/c5gQFe8eHHxFSCAIIoAKQ/EGiB64amnnnJYZxTeQIREfIFysfCzQAoMoioaNmzo0eswHsZkP6KmkKqDCjaG0IYx8NNPP60+ITARxXsjfSY+2LJli4oeeF/sEwKO2RAW+zp37pzDuYztnc9npLBgW4zZEf2FqBAjtcgVSOlByhwiXOIbSxijAoQgQTnCFwyTlGrVqqkxipFnh7CYVatWycsvv6ydlTp1aunWrZtP1mpOrvj7Ifwr3EX8h/0iufPf8HaTCCGEJBCBKd2JIIwEIcTKwA8Qs96bNm3Se3aE92OQhQlMV+KIlcH4BQuqfESVnk+SBmvWrHG5HhPsBu5SYZDK5Q5kL5hBJsOuXbs8eh/YRxig4AdK9qZPn14jMhD9Ya6s8tprr+kS37Rv314XdziXzu3Zs6cuzkDwgHmrJ6DPPv/8c/Vgwd933nnHwS4D/kHJQgRB+A0EjahEjQIFCsjKlSsTtV0k8VANxPy/8wpCCCE+g39AkMv1FEEIsTYocgAvBMwCw8wRXgaYGcagMKoQeyvSr18/HbRiAAcvFELiCqJGIIDAQwSPn332WZ/s1JCQEM0CwfUCVWXiG8uIIIQsHpBB9h29IUPCfYrEz88S2VyEEEJiQQo/Pwl86AVlJjCQ6TCEWB349cHbwNeBNwMqYowaNUoNX+E3QUhccC4E4qt88sknWhUGVhgJAUeRxDI0ejSVNC4f8T8jQQghxLcJNE3VjGgrMrSVSPaHDvWEEOsAQ0RPF18D/g8oBAEhhBDiGSgjjEiqkiVLSkJAEYRYhxR+8iDcEkRhJAghhPg2iAQBJXOLjH1SZHwXkRw5c3m7WYSQGILqDvDxi2oxtvE1UAljxowZWuKT+B43b97U8rcoi2xm48aN+t3DB+ORRx7RCqf79++3+36ggEdMgEeGJ1VVvcmlS5ekadOmaogKQ1l3psB//PGHPPHEE1KqVCkpX768vPDCC5riY452Wbhwofp9ojKPuWoUrC8QSda1a1eHssIxhekwxDqk8KcIQgghyYjAgHBDbIeUGL9AL7aIEBIb4qtKhVWJylSSWJvFixdrxZRvvvlG/V8giBjA68YwUkX52ueeey5S2Vhf4o033pDq1avLDz/8IL/++qt07NhRTYFR3MQMSgNDGIQ4hAowKGYyefJkefPNN+XChQvSrFkzTZdr3ry5+oEOHDhQvvwy3A8B/jowVZ4zZ45u4yw+eQojQYhl2PJXmPzwe8T/cBMnhBDiuwT6h1/nHUSQFBRBCLEaderU8Wgxyn36ItevX5cmTZrIL7/84u2mkHguqwvfl9q1a0dZ3ahRo0by999/R/t+gwcPViNQRJDgnDhy5IjL7SA0QHyBkIDtUEXFiEDBa1ExFSVtUU7XXNEG4kPx4sWlSpUqMnLkyHiNLsHnf+WVV/QxPgMqIrmKBsH+0W6jwiu2RflcI33sxo0bUqNGDf3/xRdfVAPlu3fvOowB8TqkzMQWiiDEMnSffk1GfBXxP9NhCCHEt2lRObV0rCpSr4zIzTsiIWEithQMYiXEl8CA5+OPP9YBHcLcfRUIPFevXpUhQ4bo7DexPgcOHJDTp09rCghKwkIQiSpixJPjG4IKoihQdrZPnz5qqOsq7eTpp5+W+fPna4oN0kk6derk0K7nn39efv/9d/XVGD58uK7HtuPGjZOtW7eqMIJUHncsWLBAxRRXy0cffRRpexzbECWyZ8/uUMr21KlTUX7e27dvy9y5c6VVq1ZaPnfZsmVSrFgxe2ocygFjMVJihg0bpqlFEFeeeeYZiS28kyCWwd9JsvNjJAghhPg0c/rlErl1TBqNE8nwMOL1v1ahkj61t1tGCIkr69evl88++0wHPQULFtRSmFENIq0OJu+QLgEvBKRGIMSfWBscrxiIIyqhRYsW8tJLL8nBgweldOnS+jyiMyAagBIlSqhoER2ohoJyyhAoICq4MguGZwbeF34a4KmnntIIDEMogJkoIj0AIiqQUmJEiSDFJMdDg3Gk57ir0oTPFVORwTlKH+WvowLRHZ07d5bGjRtLy5Yt9dxAZErhwoXdvk+bNm10iSsUQYhlMFeD6d9U5IlK+bzaHkIIIQnMQ/8PczpMQBAVEEKsypkzZ+Tzzz9X8QMzwJi9xkAIfgrwT/B1MIONcH/MzGPQh4ExsSY4biEgBAYG2v0qgoOD9dieNGlSJE8QT0DUBI6PXbt2aTllRG7Ur18/0nYQBVzZAhjr4LlhAIHm3r17Ub7OXSTIlClTXD7Xu3dve9qLQdasWfXv5cuX7dEgJ0+elAIFCrjtP5z/uXPnVlEQ6T3bt2+XmTNn6v8GEIOwYLv4hOkwxDIYkR8Z04hM6y7SrkHClEwihBCSxESQ8Ps3JTAojffaQwiJNZiBxqAQs+OY6T537pz+TWxQhQKz6BgMIuUgsXnvvfdU/ECFDGJdvv32WxUqzp49q5VbsCDNBOKB2b8ipqlhQUFBkitXLhUs4N/hCkR34NhF1ImRapMvXz59XVTUrVtXVq9eLVeuXNH/o4pMQRQI9uFqcRZADJ588kl7qgxSemByCuHPGYgyqJaUJUsWmT17tp6LMEPFOQGjU1R9QdQKmDVrlrRt21bFpviEkSDEMvg/NMiL8MChhkcIIT7NQxPUeybvM//AlN5rDyEk1iDMH7Pc8DmAMaK3gCdHnjx51C/BG6Bs6p49e3SGnlg7FQZpKGZQFhbH1vfff68D/JiC9BYICTAzRQQFzFRdgUgLlJDF/uEvg/LSUZmyGsAoFcd/9erVNbICUSbxaUY8YcIE6d69u57fEHPQRqMyzKhRo7RvkDK0ZMkSTYODOWrFihU15Qe+KvAGAoiwwXZ37tyRvHnzuk3ZiQsUQYhlMLJh7htpYSkoghBCiC/T4d3jsmqXSOjDSbVAf1z6OXAgxIps3rxZUwXgVVCqVCkdLMEPIDFZs2aNijFIv8FjbwEBBKkTI0aM0OoX8HAg1sLd8bN37177Y3epMKNHj3b7vkgFMaeD4BgxTEaNCA4A0QCLq2gP834hzCBKxQA+IK+++qq9HUYVlvgA1WBwfrni7bfftj+GeGMISEi5ef3111UcNUCbElqk5CiSWAb/hyrIfWNGkCIIIYT4NJdu3LcLICCQUzeEWBYMbObMmaPmjRj4I4Qfs7wwf1y7dm2UlSrig4sXL6qXAWanEY2RFEDEAAalrBZDEos33nhD08GQmoaUlYkTJ3qt81ENBv44/fv3t5u8JhYUQYjljFFxQ+z3tMhbH2/2dpMIIYQkIDmyOA5UyuRjFAghVgcCBMp3osQlPAAGDRok48eP14oVrVu3TpB9wl/h2Wef1RB7o2qGp/4hCNU3L/HZD4iM2bFjh8PMPyEJCTw79u3bp948q1at0hQVbwDhDwIgvEzefffdRN8/RRBiuUgQoJWSWCKXEEJ8mnfGT5en62aQXnVFRrcXWTmXJSUJ8SWQBoKZaFSNMSpsxASE88NUMaoFqQEwYIWAMWzYsBi9/7hx49QzwVjy588v8Unt2rXt1WL+/vvveH1vknggiildunRq6mkG5p4QuxB5Af8LmISi4otx7CINJCb8+++/kSI3kP6ycuVKSQq8+eabWh4Y3iNVq1bVMtjugC/Jtm3b5OjRoxoNZgYlc9Ff6DecI2YDY5QHxmtRkticHhRTKIIQS5bIDf+fhy8hhPgypWt0koUbbsicH6/JW19ek5x1vRe2SwhJWI8MVID47rvvYvS6vn37aoWMqBZ4ImAwhoiLlClTqlFjsWLF9PWICunRo4fb94dogoodxnL69GlJiGoxEFeQGkOsCVK7KlWqpF4zt27dcngOaScYxEP8gOkpoh9iiysRJClRu3ZtNf2FnwdS3zp06KCVXlwxduxYNUh1BUxe0V/oN0SKIXLM7JGCyjxIbZs2bVqs28pRJLEMW6eWl+8HRfxPEYQQQpIJQZnDF0IIMZEtWzY1WY1qSZUqlXzwwQc6MDNKfKJMKMAgLKpQfIgmGTJkcFjiG0QKIFolplEBJGlVihk6dKiKAFFVaUG1F08ifgYPHiyPPfaYRkLUqVNHjhw5ouuRzgUhBOvNaV0wHca+ixYtqtsAiDGoUGOU64VIY5iR/vPPP7ptfIMyt6lTp9bH8PhAyotztAbaBUESpq6dOnVy+T6odmMA8dE85kNqGyK8IJw6R5DEBFqMEctglFgyoAhCCCGEEEKiA+VGzSB1AWAgCE8Cb2OIK3PnzpW0adNK165dvd0k4iEHDhzQCCEM6u/du6eRGubIBeeIkcqVK0f7nhBUJk2aZH/NgAEDNOVl5syZKn6Y00PAsWPHNPUmLCxMI0+2b9+uRsQotYvH+AtBAkaoYO3atdKwYcMo2/Dzzz+7FeaQihKdj8e8efMinV8QLZ555hn55ZdftGJN+vTp3b4e223YsEEf//DDDw5VZlq1aiVZs2aV+fPnS2yhCEKsQwo/eWCUx6UIQgghhBBCfATMcGNGH5EExYsXj5GBK/FuFAgG7IhMgDiASAykYcEbA8CAFJEboESJEh4N3FFmFj428BqBcBCdIW+XLl10/4jCwL4gikAEgdABMQOVkZo0aaLt+vPPP3WduygMA7zWWWzxlHXr1smYMWNUbDEDAWPFihW6RCWAgAULFuhf9BciY4zorZo1a6ovSFyhCEIsBEUQQgghhBASNwoVKqSiQ1ICIf6zZs2SQ4cOqT8KZu1z587t7WaRKECqyaJFiyQwMNBu7BscHKxVf4xIDkRmIN3JU06dOqVmubt27ZIiRYqoN0b9+vWjfA1SvgwghiAixRAyICBcunRJ2rdvryWpIUz88ssvGlWSEJEgeG/4nsDjBsbHBvBLgTCC18WkChQ8eyAsXb16VaM/4guKIMQyzF51Qcb9L+J/psMQQgghhBBfAYPZ5cuXaxQIBq1IBzAPcEnSAgadECrgcWGASIsGDRqo4W1sgAdGUFCQ5MqVS4W6GTNmOKRNQWSByOFsE+CKatWqqagGEWTq1KkqgkDAyJ8/f7SCQmwiQTZt2iTdu3fXfkGFGAO0d+TIkdK5c+doKzQh6gW+IUbpXpwPaCv8TeITGqMSy/D15kty4nLE/xRBCCGEEEKIL4HBH9IFYJh6+/ZtbzeHRJMKY5iNGqAaEb7D2Fb7gaEoqsjAxwPlb81+NhACsD9s40m6FIQSlOXFeyBVBu+J6JWGD/1AUI3JuaxvXOjZs6eEhoZqJAjScrD88ccf2g6sK1y4sEY8AUSDGH4hiBjBZzVEIERC4TNCSPnoo4/UD8V4XXzBSBBiGZxFDz8/f6+1hRBCCCGEkISgatWqmo6AgR8GlahSQ5Iea9ascbl+79699sfuUmFGjx7t9n2nT5+ui7ksrAFKz5qBIaqZr7/+2uF/57LTZ8+etT+GEBGT1JToMKrYGMCoFek4iP7A36jaZYAoFaQCJTSMBCGWwd8vQgFc2EekTYPyXm0PIYQQQgghCQEEEPhDoMzvjz/+yE4mlsJms0nfvn3lk08+kePHj0tSg5EgxJKRIE0eEcleIIdX20MIIcnthgZ5vSiz5ysgLBhhuiEhIT71uRID9l3S7j+YI+L94zuEnCQu8HCAsSa8FFARw2w0SUhS5qOPPtKoFaQMoVJNUoMiCLEM/v4RP+RaKjcFA5kIISQxQEjr+fPn1ZDN14QdmM+dPn2ag0X2nc8de/CUQHURmCwSawIx64svvtBBZKNGjdR4EpVtCEnKfPHFF1rh5rXXXpPnn39ekiIUQYhl8DPdJDx4QBGEEEISgwcPHmgoK27GYfaGAZWvzC7js8GFPl26dDTbZt/5zLEHgQXC5eXLl/XcLV68OI9vC5MxY0Yta/rEE09oZQ+UTMX1ODmCaERUXcEgG32AKCr0y8SJE+Xff/+VYsWKqTGpUf4Y26LPwOeff64Gm/DMOHHihJp0tmrVSipXrmx//1GjRsnYsWPV1LRly5b29c8884ya1V64cEHFRQNUXRk6dKiWhU2bNq2u69q1q7z55pvia2zcuFGaN28uJUqUsK/bvn27Gq46g0o0mTNn1upGMEfFMYv+g//IxYsXpU+fPnL06FG9TqH8LcSSxIYiCLEM5puEH/aLNHrkhuQr7tUmEUKIz4ObFAzYYFZmvvnzBfC58PlQgpIVx9h3vnTsYWASGBgoJ0+etO+HWDstZv369Tp4T64CiFF95Nq1azr4xiAb59E333yj63AeZcqUyV7WdfXq1dKlSxe5fv26yz5DpZWDBw/aU4zwXosXL9aqJM4lWyGKYP1XX30lPXr00PV37tyROnXqaKoSDEGxD1TzmTt3brSfw9MSt0mNMmXKuDV6BegHiK6//vqrfR22b9q0qTRp0kT/HzhwoPblsmXLVAiuWbOm1KpVSx577DFJTJhPQCyDv3/E4fr8bJE1m/7yansIISQ5QZGAEGvBc9a3KFiwoA66Ef2AyiKI9ElOIHIAIsS8efNUADGOcZSTLVKkSKTt69WrJzdv3lSBxBWIaETUxu+//67/oxpPxYoVVRwxg6gTlJQdNGiQ+luY16dPn16/C0NkQTRI//793e5v8uTJWgoW1VJQOrZ27dpSqVIlFRfGjRtn3/bZZ5+Vl19+WfeLyIv27durmGmUkO3QoYMa5tavX1+6d+8ur7/+ut1r6I033tDqQojAgAiECJnEYO3atRqFg34x89lnn8nTTz9tr3CE/jaicxAJh2N64cKFbvsM/YLPg+8Y3xH6Dt8Tyv0eOHAgeYggq1atkmrVqqm6nS1bNj0gnDvKeZk5c6bX2ksSLh1G/0+AmRNCCCGEEEKSKufOndOKGxgAI7UgubBnzx6NMsAY0BMgmKCPsmfP7nYbCAhG5AgG6678KyB8YD1SZ/7++285fPiwrt+9e3eMDT9R7hhpJZMmTVJvFwzq8bnwXkuXLnWIskC7EIGCaBV8z4h4AW+//baKQIcOHdJ1W7Zssb8G7wthASVm8XoIBW+99ZbLttSsWVOFEleLO7NmfH6INoja+Pjjj+3rf/jhB011gWjTsWNH+3oYP3/55ZcawWOA10IoQeQN0olQ+QgRTu7IkCGDfp4JEyZImzZt5PHHH9cSxIjIeffddyW2WCYOB19y7969NbcLBzRyvaCgOQN1ECE35jw64huUL5pZFq87Zf+fIgghhBASN2B2i4EAZvEwa4rQcYSUE0KSJkhNxEC6QYMGOou+bt06TZcholEPGMQj+uPKlSuaQhQVBQoU0GgOpM5AiMDg3ByRgbEmTMEbN26s0R64VkIsGT9+fKy62yyyIJ0G0R4QKzCmgUkyHlepUkWfx2S/4beBSIhjx47pY/hsfPjhh/oYYkjbtm3t7wnfDaTvwPcEIHqkaNGiLtuybdu2GLUd4seZM2d0bI2/8AeBIIUID0TjYPwN4clsxIzxO4Qrc4oRomEQuYL3gzk0xvVRRTUh3cjYP/rJiCKBlwtSamKLJabSkTeF0CKoWzBPQVgQ8rfMSpMBfrjRocbiyqyFWJM3n60gnzwX8T9FEEIIIdEBI7t+/fppKC1u1jCAwIweBg4GeM6IIMV9A8KMcc9hmOsBzFTheWPW0Pgfed1nz5512Cdumo3ypK5muIwb6h07drhsM2a5cFOZM2dO9XLAfQ8mgowZyPhk/vz5snnzZr0hRrs5eURI0qd06dJaKQYiJoxBMaPu62AQDM+Jq1evut3G8ASBFw7SQpAOgmiEqEBqxQsvvKDbOo8t4O8B3woICYjcQFQDrpkYm2IQ7u4a7g5EaRjAPBXXeFzvkSKCNBlzW80+Pvi9wD4BfpfcmZPjOURooA+w/PXXXxpNEh+RIBkyZLD/PuTLl09TiXAMzp49WyM0ILwYKS/mKBpzFAhAuhGEJLQPESQA6UDuMPoBfWB+f3Of+KwIgjAh3GDgwMSBinJfzZo1c5kH1LdvX1WlEGqDVBiE2hAfIYVfeGnch/j5JV9jKEIIIdEDAQI3qpgNRPUAzOrhpgu54q+88orDtggxhgiA0GPMUuEGFTd30YGKOQsWLHBYh5tkdzOzp06dUlM/3K+Y88sNUL2gevXqGjb9v//9T9uDfGncfI4cOdLjr93IH48OzC5iQIVcbkwexabyD26Yeb9FSOKCSigYhEIw9TRFxMrg88ILA4Nqw+cCg35cf40oCQNcx3C9RL8gdSgqcP1DdRJMtJsxrsEQOvBbggXjUVzbETkCEQDtQDUZQzSAKOVplAii7iAmQDBHmgmi8TwBv1/4jQHY/7fffmt/DikpU6ZMsZezx193vhnbtm2ziyXOiysjWfw+Gtd5RA1ivxCmEP0Bcci5FDcqUyGNBf1kBiIWvEuMMT6iVxARk9hYIh3mn3/+0b8wnsEXCyUOoTQIAcOsiGFgg4MQoWGYxcEMDwxsEAo1YsQIt++NAxyLAUKIAL4c4wtKLIz9JfZ+rYK/LYWDCGJz6iv2X9xg/7HvvAWPvaTdd3hv3Gji5sdqA12U4cPNMG5ijfKFxk0vjOfMkR6YocuRI4c9ZBk3zshVRgQGMD670Q/G/yidiFRclEk0QClGrH/nnXci9RtmwBDO++KLL6rYgfsao224YX3uued0oscc5gtDREzu4IbX3XeAaBYMDmAeiJtKzMyhHbjRhaADt34MCBA6jdRi7BNhyCjtCNBPuK+CYAQBBQMIhIZjnxBIECKOmUrj88HhH5NNEI9wL4abeAwOPHkdbpjxF+HfqAqAPsEEl7mPUGIRnwX3eAgLN8K/YQo4ZMgQvQHHrClCx3FPWKFCBbESxrFnnFsJAd4X749z2HlQw3tN3wBjImPQvWbNGj2vERniq+DagOsqPCIhHuD4xufF4N/ZANQwIkU6Ba637sD7QPh2jmLAdRTXXkQGmkFKDCJEsE9cPxFxAoEGvyHYZ7du3Tz6LBif4r0gtOB7xPXYE1DGF78TiJ7A63ANNSI00JYxY8Zo/xiCNn6b4A0SV7755hv9XUR/QRBBJRyMu1E1Dj41SI8xIiWN7wqiFSJIzEAYQXQmqlchFQleKObrf2KRwma+A0hkIGrgi4oK/Gjjx/Wpp56SWbNmabgSgHAB9QwngrsDGwc+fpzxgxnTNuAH3NdKAVqdCqEfyXcr10r/hwbC77zWTMrVdX9RI4QQEndww4MIAaSROM/0JGUwy4YQZtxoYsAdFY888ogKJlhwW7R161bp1KmT5jjjRs6I4MBAGzOvyG82/sekC7ZFtAZM8hDlAQFkyZIleoOIMGfknQO8N16DVBuUC8SMXq9evfQex4gCwU0xxBfkgMcEfAYMAgYPHmzPmUbOOT4DRBCk4GBiCAICxImPPvpI+wj3QAiZRvvx/SLHHMIPPh8M9XBzinbBgA79gj7FPRJmThGdi/ssCBWIiME6T16Hm3bcyCPCF/dw6M85c+ZomxEdg+8M7wGTPUxO7dy50/7dQCBCG/E5cHMNYQXvC0NBo2IECQdiFoQmpIQ5h41DcMNgDffIzoMU4h4cjxhwJsV+g/CJCAWkQxjiLYkajCchIkE8cBZBkioQMBF5gjQRHI8wCoWYjutlQnP79m2dQEDqC679uFbHJnowKZyjXo0EQSgo8q+iAgoXQm6c84VwoGLWAz+27sAMCzoCjrrIuXIFyuyYb46wPW70cLOQ2Bc3HNQIhWrUqJGqY8SR914ZK6NNFZQKFy6iqiP7j8eft+G5y/7z5WMPs+0YSGGWy5yjnOLHqiIhFyRRSZVLbE12ebQpnPMN0cHd7zmexz0GBuOYFMGAHQNH9Cs+K+4PjNcaudyYacU643/koKP8H2azIGzgL/43zEWxnfEe+K7Qn+3atVNxCWIJoiIwwAeGtwhSeGJ6D4LPgJnE4cOH29fBPR+hyOYoFURUQHyB6IBZTtwsYtIH5nUAYeWY8cP9FYQNgD7EjCdufNFH6Bv00fvvv6955bgJjsnrkGZkmPVhRhCRvMbnxc08+h0ih4ERSYIoFaQHYVBvDFggxGAGHMKRMVFmBYxjDzOhCTWIwLGG6GjMlJvPXXPkM/EdcJ5BZMR5sH//fj2XOJ7wPSBeQwyGEAKhGyJ6YgggJ0+eVKENEXqIVMTvmJXxqgiCsExPcthwM4AfO4RaQu0C+BFFbhZ+wN0Boxlc9KNyOcf7ulL+cNHw1oXDm/tOyly85mhsFBjgup/Yf3GD/ce+8xY89pJm3+FGC4M0DLIdTOMggNxxNARNDFJ4WB7dGFgiDcCdkbY5DQERFJjhgks9hAQICsY9BzDew+gH8/+I5kAUCFI/MBBBNIgx827eFmkzCM02ImowE4/BPsz+YPhu3ldszL+RMmN+HfKtccOKSAkDI/0CN7RICzL6yXgdwpmxjXMIOGZMs2bNam8bPgMiSoxjw9PXmQUXAMEEpo54Dn8RVo0belefH/d1MCl0LnmJgQDyz61kmG4ce0b/JQR4X7y/q+sD7zN9D3yniPBCVBgmmiHoIoqe+BZI20Qlm8Tmxo0bej+A3zdztRerYglPEMwOwKwGoZGI0oDwgVBSADMgAOdbzAzgJgSqN8oH4SYGaqhVwptI1Pj7O94kpEhhnZsdQgjxOVLnStL7xEAbA0BEDphLCLoDkzLI68aCiAb8RUSpJzNsEAMw+EfUhWEyas6NBijZiBxzTOKYjfpwU4mUmwkTJmgVGCOKBfczMcXse2IMtJFu8uqrr0ba1kjRcQavgXCEm2xnHwlzZQPca5kjGDx9nfPgG+9hZGZHV9EP+0CaDcqDOsOyvoSEg3Me1yGkMUZXTcRXgQgN7yMIwLge4TqLiCgYZCNtENd3XKdxTYH4iqg143cCKXZI5YOgjQn3woULawQErt8GSOdDBBvGny1btrSvR3QftsOY1GyrgH0gIg+RccZ1Gr8XSFX0FFz34F2C1L/E5Ouvv9YUS4hrSO+MSrSFoI8IRKRe4pqMvnRV+QVRfcjGMCIx0b+wuDCOU/Q/Piu+R3w3MII1fkcQxYiUL6RVIrIxtse2JUQQANEDoaPIlYXiD8MXdKCR/4kfVXQIQihxQCNVBrlKzu7vxLqYq8FsGy1SrXnMbxAJIYTEE00T90YspsCnAukpmBmFCOAsEOBG2F3KCe4tkKaBmzBEH3hykwUzVTjcu6tEAPM7eJmZb6QBPEUQQYJ0EaTiQozBjfry5csjvQfaHJPBPpz7URkAN/yegvQSDBhw0167du0Ef50ZpIYgDRp9gpQdV58HgwvcD2I7QohrDHNUDDJxHcQAHAPN5AJMoiE8I2oB13OMDSFuYx0G3UYpXUSq4doN8QJpJq6qouC3BL5Jhr0C3mvx4sWRoiGQYgZRBOtRMQViAMC4FabTiAKESIB9wFsD5qpJmbt37+q4esaMGSpCoI+ii1qDAIcABMM3BN8DvgNn8J0gFRTjdaTtYbIB/yM6EtF+eB0EI0wuIKoJv4/4nUS/oRoQPEPx+4zfitimAllmKh0iB3JPcQDiIENerdnpFsZfuFHByY4OQhm8/v376w8l8Q38nU48Pz9+t4QQQtyDyREMzGEyihtg3IAiMuSDDz6INtICkyhIw8XrPAFGhEilQWqMK2D42bFjR519NC+4AYe4sWrVKhVqcGOMx6g88PPPP+tMJGb+kDbjXMIxOjDwwQ0oPgtu+PH5v/vuOxV43IFoFOSY44YXed9IM8ENJyJVYLoY369zBt4sMLbHd4T2IqXHqAyDm118b5ixhQcI+gbVb2DOl9izo4RYAQxakXKGcwYDSS/Ww0g0kAIIEQLph8ZkOfoB2QMYdDuDSA+MHyGQuAIiOHyejFLouC5D9DWqkxog6gTXKFQnNZc/x3oIvLi2GSILrvUYp7oC+0LVK0ReIMoEwrIrYGYNwQXbIVLD8JRC9AWEL0Sa4Hm8l1FpFSBTolixYhpQgDRQPO8MythibI0KYBD2cV2PDrQT12u0H6AyDH4HcJ12Bv1nfBewrnj00UftbYTHE9pkpFZicgECiXNUE/oyLpW1LCOCEOJnSoe5j2Oe6TCEEEKiADe3uClDVAFuTCE6wEQWs0fuIjYM4DuB6FPcuHpyo4VJF0RxuJp8QYoIwohxU+gMbo4RAWLcNGO2FgN7TP5gVsxIs0E+NsKFYwJujjGbBjEB0Rm48UQJ2+jKEWLwgJte9Bm8SiDIoEILUpIT4nVmMHs6bdo0FbAw2YVBANoPcPMLQQWz3BCPILzAYB832e4M8AlJzmCwDbNmXMcgFuL6gmgqXwbXfKRDeuI7CRAtB/NlZ68hM4hsQDQEQPoirj/O4BqO9a1atVIBHdVNjet/TNIbcf2DqAtzW/hSIbPBmT///FMFjB9++EG3g0G12Rga111UvUFQAIQZiNEAkSpINfn9999VIIehtTMINoC/FErLw4ICQghECvPiKlIRBuoQ3IzfQFyvkXYZVRETgOMRUSNGsQtsb/b8RNQfBB78DiMlBr+LaB8ibPB7Hls4lU4sGQmi96MUQQghhEQDBvwI58XijCFuYAbKVZgvqpiYb8TMs6jO/zuDG0Xj+ei2RXSGGcyCeRqBYuBqtg3gZvGnn36K8obbGQgwKJ2Lxd2AAGKHc4URT16HxQxmqJ37BiHVWFwB0QhRIlgIIdGDaxt8FZFOhog1iATm6orJEUTf4RqNiAcMwiGMRwUG8xjgQ0CAqIHoDqRnGEBsOH/+vAraiFCAgA6xBEJETEHqJKI8kKqDgb7h7WIG3pcQiPPmzWuPloBIblxLIZ4YQgIEGCOaDq9DSfe0D9NDITrD28Qomw1fJqSJIoUU1+aYph06p45GF3mE3xCIRoh0xPHp7n3MICIyplGRrmAkCLEM5hvUAYtEDh4549X2EEIIIYQQ64BUM6QBYLCHSIH27dtLcgGDTcz8QwDB4BTpMRi4+xoYTCN6DAKHOwxPEGwHwQCiBbwpogJRHs8995xGnzmL5khjhJcFSn9DOED6BiJHYOyJKqeIqvCELVu2qGCPlBAIKyhz7Kpdzma3zqKBuSQ2RBmjWpk7k9yNGzdqpKThU4JSy/A9cY4AiSoSBBF/Z86ccdgXokPcmXAjBQkpN4gYhPeIAbY3i/p4DLEnvqtoUQQhlsFsVrTnhMjJs1e82h5CCCGEEGINEF2FwS4GskgH2Lp1q4bWJyeMCAAMThFNhZQzRB74klcI/C6QeghzTUR8AHw+eHo4p39AEIBpKQSx6FIk27Vrp2aczlEIiNhAH0LowIAdC9I3MHBH+h7SGdEORFzAo8qIunAVJQJzVkRiwG8kqhLHDRo00Pc2UpuQsoJ10Zl4IzUUfinBwcEaCYkURqSfYD1EDJSGN3jjjTdUKHK1oC9cle5FyuWiRYvs5xsEIVfRJBCMIIDAuwQpmmawHn5SqJIGkBoJ4Sm+oQhCLIOzAmiuFkMIIYQQQogrMDsNI0pUm8QgFn4y8K2BWXFyBLPtqHiCASeMLJH64EtRIUhFQWlVRP1A6MECr6WsWbNG2hbCAQQJ+GZAHHBHypQp1WzaSEExQMUvpJ4YRp4GENwQWYFSufBmggADgQZmpSi/7opmzZrpNngvCASIunAFPg/ScZB+A++nzZs3uxVMzCDqAu9boUIFTZNBBAgiZiCIIVUGkSxxAW3AgvMLfWo2iIVpuJH6OX36dNm1a5dGlBjRJYhMMlIe0W84JtEXEJRiUkrYU1LYfEn6iweQm5QxY0Y1IHNXOi8hSxFB1UOYGvJqiSNbF/SURr0/kzth4f+vXTJBGnYawv7j8ed1eO6y/3z52EMoLhzeYTJqDrH1BTATht99/N7Hd6itr8O+S/r9F9W56837XW+AARcGxBgcY8CHGXQMvFB50lxtMjp8sd8wEIUwBKNNRDokJxDFgcE6oh4gciQHEG2SOXNmvX/AOQBTWJSS9xU8PUf5i08sQ62KhWRAs4j/GQlCCCGEEEKiwyi/aVRJgcElBoJIhXBXGtUYJGNQZV58DaQ2ICoEPhAA6QwoM0t8C8Q9oDoM0l5KlCihESmICDEbvCYnKIIQ6+CHetCmf5kOQwghhBCSbIGogXSGqBaUGzUqQQ0fPlz9ImBWCT8EPA+PBHdggIhZZWOJSblnK4E0EZQ2hVcD+qh06dJaccSXUmSSM/C/QZl0pMMgImrNmjXquYEqN74S0RRTKIIQC+EnD0zJW34mo1RCCCGEEJK86Nu3rxw8eDDKBVUvUCoblClTxv5apD8UKVJEjSHdMWzYMA2rNxYYivoy6dKl08Hxe++9p9VB4MkA40q6J1gXpIChAs7t27dV/Pj555/j7P3hC1AEIZbhVvBdOW2qdsVIEEIIIYSQ5AuqesBEMqoFfiiI/IDo8ffff9tfC08EVPKAqaU78BrMlJsXXwflg+EPghQimMleunRJI2ZQ2SS6MrJJzQz37bff1mMAvi/4+8ILL2ilFnzviHypWrWqVoV57LHHtHyyweeff243zcW2+Pww6jQzatQoXY/UKjPPPPOMHifOJqvoR1QmgvCGVBQsEJtiAtoye/Zsh3WovvLnn386rDt58qS9XWg3Ij52796tRrjRVZCJCygjDMNheI088cQTWknGFYg4gkErzl8sZiDWIFoFqTpY0GZzyVx8LpzPqLoTl+ORIgixDLO+2iVfbo/4nyIIIYQQQgiJDgxKYf751ltvyU8//aRiSJ8+ffS5J598kh3ogkyZMukg3ag6ghKzxYsX18gCCAxJHZTIRanV7du3y4EDB9T3pFGjRnYPGHw+GObiOED5WgyqjRK2zqBkLV5/8eJF/R/pVYiUgZBhBp4x8N3AenOa1Z07d9R/BoLbkSNH5I8//tCSukbJ4riIIGYuX76s3i7w/IDJLT4P2o7Plhjm323bttW+hvgxZMgQ6dSpk8vtYOSO5xGV4kqEw3qUscYCEWTgwIH259955x3ZtGmTCiVGOd7YQBGEWAZn0YNO/oQQQhKSZ599NtLsHyHEmqA8bpcuXbR0KWb+MVu+fv16NUgl0YOUipo1a6q4gLKsy5Yts3utJDVg7AoRAr4vxveLcQMEL0RiOAOB4ubNm25NchE9gVLCEIIABukVK1ZUgcEMIi4aNmwogwYNcigPi/Uo/QoPG/+H6fwQQBBp4wrsq0qVKtrPLVu21CgSACEPYgwiLeDvYYDPCr+anDlzysyZMzVKBfs00r+QzoSIC/i9gHXr1kmDBg0kvkGbEGEDUAYY55irYwQRVtg/hChn8D2hr4x2Q1hyHvPh+0A/xuX4owhCLINx0TDImDH8BCGEEEJI7MEsJQYKuKHHY2cQbm2YTKZJk0Y9FozZYSN03NXNrPFcdMaVGzdu1BlLmFAiZB0zgWgLbqIxiLECFMySPph9RklczOZjYLV27doYlcdN7iAKZMmSJRpdkTdvXjWYXbFihT6X1DxD9uzZo+11TrVwxzfffCP169eX7NmzR3mOz58/Xx8jGgapH85A+MD6Vq1aabTR4cOHdT1SUWrUqOFx+6dNm6aGvvv371fxCWk9AAIHhA1EWnz33XcadQHgV4Nj+cUXX5SgoCBta6VKlfR6Ds8bbI/oEIh+hojTsGHDKNsAwQdii6vFk5K606dPl+bNm8d60hrty5UrlyxdulTLWpt9etAnW7Zs0dSj2BIu1RBiAcwn0cI+IqVL0tSHEEIIiSsYAEDYwEAGs7tPPfVUpG1wE967d2/N5YawgcoRmM3DzXZUdO7cWcOZDdq3b6/7Mm7qAQQPzJAizHvGjBk6A4pBKgYB169f96kvGD4UGIwTYlVwfkJAQpoJvBkABqO4T8d1AT4bCek7EV/AGwRtRYoJzktDIHBHgQIFJE+ePOpJAVEDkRbm8rJIcUE1ncaNG+vELSKOIJaMHz8+xm373//+JwsXLtQSzRAyIAYY4DqNfX/88cda9QXRH4gcgeiB7wBpNsePH1ehCtEWEDyuXr2q2+AaC8Hk559/1tdHBb7T2IoMSFOBeLF582aJLWgjIj3effddTYEx2tumTRtd4gojQYhlMFeD0SoxKXj4EkIIcQ9uFidOnKjhz4gugMna119/7bANqkcg3BieAQjBRRnBY8eOOWyD2WNUl0AZyVdeeUVvmA0wSMeNIiIpECXRrFkzzfl2jpLAjClm4mDSiLx0o8oEbsBx44oBv5kPP/xQ88fxGRApgUEFjPvwGfAeyIfGTbeZbdu2qRkdPitCo1999VU1mYsOzF7iBhmLOYTbDPoGN+KoFoEbUsyymo0E3YG24HXGgllK9JPzOuTRYwCFcPXChQvr50TYvTkXPCrwvSIPH/vD94RZROOzG1EaY8aMkRw5cuh3jRnTsLCwGB0rmHVt0aJFpGMFAg5miL/99luH6BbDUBGDgbp16+r3hsEBtseAxXnmFxE3Bkab4cmAQQ6OIbQfXgwwrYRwlC9fPh1kEeINENmAcxcgNQQ+DYjeQqoRjktXUWWJBc4vXIcx+HeH4QkyYMAA9c9AqlR0RpuI8oC5KbZ1jnCYO3euisSovIJz+csvv9TrAs5ZiEUQJzwBEQ4Qg1HJBdf4KVOm2NuFtBdEh0CohgiN/3FdwWK0BwKM4dmC6yDEBKS/4HG9evVU6D5+/LhdwIrvSBBEC+FaBaEM19u4gM8E8R2CUHzDUSSxZDpMeAoYD19CCCHuGTFihKZTwP0fA1jc7GKg/8svv+jzZ8+e1UEtbiAxC4jZPdzkmk3/NmzYoANd/MUNLUQNLObBKgQMhCZjZhSDaYQAm4USVAnAbBZej5k7RDngJhrgZhk3p85pH/gf722eUcXgF4IMwtFxc4n8a2M/uFmG2z4iLXCTjBtR3EyjhGhU4LOh3TCwwwIhBVUhogN9Fp/miBBD8B3A2C+mYPYVxn/47iBqQYBAP5hD9DEIwHP4HjE4Wb58ud6ox+RYgcDk6ljBAAp9h4gXtAULvBMMhg4dqoIU9o/vyFOwn3PnzungEgMhiCcQ7CC47dy5U/0BsPh62VaS9IFYCR8ORElAtIOgiYgDYPxNTCDWIl0HQioiPgCuBxjYO4vcuMa++eabmjqD8z8q2rVrp+c7zjsziNhA9AaEDoifWHDNQDTG6tWr9fqEdsCA1TBfxe+CqygRCOsQWiF0QvyA6GwIthBo4SUCXxBc04wKNu7Abwu2gzcHRHj8j+tenTp1ok1TgbiPNBpXCyYDXAHBF9dSCC+InIkNSFcze7PAgBbeKPGOjThw48YN/GLq38QmLCzMtmLFCv1LIjP7ne763WCZ21tstmv72H88/pIEPHfZf7587N25c8f2119/6V9nJk+ebMubN2+0S6tWrSK9Fus8eS32ERtu3bplS5UqlW3btm0O63v27Gnr2rWrPn7jjTdsBQsWtIWEhLh8jx49eujz9+7ds6978sknbZ07d9bHhw8f1t+krVu32p+/cuWKLXXq1LalS5fq//PmzdNtduzYYd/m4MGDum7nzp36/5IlS2yZM2e2t2Pfvn22FClS2I4fP67/b9iwQbdfvHix/T2uXr2q+8FrQffu3W0vvPCCQ/s3b95s8/Pzc/ndGbz55pu2tm3b2v9v06aNbfjw4Q7boA+mTp2qj+/evWv/TO+//77t/v37+n/GjBltnlCnTh1b//79I60/cOCArXTp0tre8uXL21588UXb6tWrPXrP3bt3a3tOnDjh9nvMkiWL7fbt2/Z1n3zyiS1dunTafk+OlWHDhtkKFy7s9lzDPtB3ZvD9oV3Tpk1zWP/WW2/ZKlSoYLt+/bruH6B/0c/m98P/xvOgZMmSttq1a9v/x3GZNm1a25dffhnjc9eb97tWhv3mGZcvX9a/uKblyJHDVqtWLdvEiRNthw4dsiUWOFdHjRplK1GihK1MmTJ6fcF1Becdzs2sWbNq+0aPHq1/N27caMuZM6deJ3BN69Chg76Psa2769n333+v1+ZKlSpFeh7nvvH7d/78eT2vCxUqZCtXrpxe58aNGxfpNcHBwba6devaMmXKpNclnKf58uWzX39btGhhK1u2rP19cZ34448/7K+vXLmy/mYYYD/PPfecPr5586YtMDDQ9vHHH9uvgyNHjrTFFwEBAdpWXN+MBb+JAPvB/gwqVqxoy5Url17z8Vv/9NNP6/rffvtNn0O70U+4rv7zzz/xfo7SE4RYMhKk1xyRJ148LcUrV/BqmwghJDmDiAbMdkUHUjOcwYy/J6/FPmIDZsowi4bUEzOYUUPoNsCMFkK6o/JogNmc+fcHaTFGGgpm9uGEj9QUA6RilCxZUp8zwDbIozeA+SdCsbENctKR9oCIDUQnIEIEoeQIWzanRwCzsR5mCc37QWQCZmIxG2mAmU/kVCP0uXTp0pE+G2YkEZ0CAzsDRD8gCgKzhebPjWgGzPBhxhMh8JgNRVh4fAGzvz///FM/ByJYEP0Ac0FEwyDMPCqQuoLcd6TDINICOfmYITVX/cA2SMMx9yVC1xFFgcoLnhwrSH+JjZ+H+buPCTj2zLO1mGGHn4oBvh8cb0blCEKSCoYhKaIsJk+erGkbKE+MsqiISEA0G6IdEhKcq7iOmSO+DHD9vXLlil7PDBAdceHCBX2M647hd4TrMLZ1BaLOzP5HzqD6i1EBBtFu5ihCM4iWMaqioIIL3hf+I3jPHj16aJqR8VuCaBsziDox45xaichAg3Tp0jmkAb7kFNESV8wRkM6YfaAM81pXIE3H3XPxCUUQYtkSuWFhrmt5E0IISRxwE4tw3+hw5biPdZ68NrY3ykbpPPhWOO8HudRGaHF0OA96cVNvvLe7ighY72wM6Moo0FgHUQEmekjHQBoHTO/gEeEJxnugTfC5QNqFM+7Ckn/88UcVopxv3iGO/PTTT+pvYk7FwaAAQgKEIKN0YXyCQQD8BLBAiIF/BvoFgwL4hLgDYgDyz5HKg3bDTwWvQcpIVK9z/j7jeqy4A+Hrzp/T+dhxNXhwdexFdTwSktTAtc3wG0L6B1Iz4MOB6zrOAYiREEWQ2gcB0yiNmhyAeIE0SvghQfRABZQ+ffroAs8P+JpYwWDWqlAEIZbB/2HdaVdGqYQQQryTB+6pcaUzuPlLSBBZgAEsygNihs8VyDPGzBwGoMZgN6b7gCcEBtuGBwSM+FAW0Rx5gW0wO4eoD4DSicgPR0SIQa9evXSWHw74aA/EEGeQb24IGsgbx36M98ANM7wskAvvKTBBReQJBAMzyFPHc2YRBDO75vdOjJKY6F/gibkrBgu1atXSZdSoUWoqi8ga4/j8/fff1ajREDPQl5gVhbkoIkY8OVYQNeOuugsGe0auf3RAAMSMs7kPEWlCiC8DARXRXVgAziVEcOG3AMaXOIcQAQdfCYgkiFgwjFetDs51iB64jkLoQSQdImRwLUFpXkTjGRVPYDpNEh6KIMQytKxfSSoVEtnzMOqLIgghhBB3GDeaiCjATPnjjz+ukQuIFsDgFyHGMHdD1ABM62CMlzFjRh0cQ6xAqkl04GYVN65wr581a5bu84033tBoAnMJP9zo9uvXT2f68BipLwhvNkQRANEE65B2AsNNV5EHCCdG+gPSIiBc4IYaqTQAr8Pr8ZnQHkQfIFUGERL4jK7SkTADiQGIOcUCoG9gGIttXEXxJARIX4GAATEJYeNI4Rk2bJjOEpvFIldAhMIMM9JgYBiL/9F2sxCFARVMEpHSA5NAhObjezBC0KM7VrAt+hGiEdrlfKwgZB6RNRC48B3heXegUgzah4EPZnwRvYJKEAmdHkBIUgICBwyjseB8x/UIhpo45wDOQ4jKSI/AgrQypB4azyd1EFmGErFI8UN6B8w+UXEKhq0wWMX1GtcsnvfegeU1iGXInCmDlM0X8b+fHzU8Qggh7oETP6ICxo0bpwNihFvjRttIkcBgFWVN4Q2BCADcaM+ZMydGvg9IYcHrULUDod2Y8UM1APN7YAYUIkW3bt10GwgccLx3BoN0DNYhgrgCERrIL8f+UIEEAoYxU4pIBVQyQVlIeFfAy2LkyJGauuIKVEmAUIKZWGcwGwthICHKErrD+G4wSwzhA8IDxA8IBMiDjwoMIuAhgqo8eC2EDsyymiNZ8DkhWqHCCyq5YD+othKTYwXVWtwdKxCeIIZgoAbhCFWA3IH3RwlMeJ3ge0J6AEQYQpIrOM+QyodrmuGDg3MCaTKImkKFFFQ2gZcIQJTXhAkT1B8DAgO28TQSK74w/JYglqIaFwRwXDeM0sAQTZHSh+s/rtsQRRD1ASD4QvilAOI9UsAd1Yv7T3JA+Yd6D4OaxD4wERaGGyf8iMfGeMvnOblUnn6qs/zv4X3F0X3rpGiF8IsJYP/FDfYf+85b8NhL2n0Hw0jc6OEmFeVBfQncxOJ3H7/30ZULjC1It3nttdfsZRqjAjOiEEcM41UD5ItDmEAKDAz9kkvfxRfwMkH/r1ixQpIKidF/UZ273rzftTLsN+8AgQMCL9LcICIjEg6RdRAlDRCh9d5776kogkgvGItCBMZfnAOG8TGitXDO4TcT5yHEXkRkYR1SF/G7iogyiJkopwuhBaWqjfLXiFTDa7At0ugMTx5EAEIcRZld7BPnn6/9ZvrSOcqpdGIdUviL2fvLz5+HLyGEEOuDG3mkrmDmEBEJhJCkiTF3HN+mwCR6ICxAoMCCyDqYNSMCxFiQkobvBYInIuqQFof1qJ6E6Kvt27fb/ZNg0goQSQffIFRiMldNQVTYoEGD1MsJ+4LwYSzwZTK+f0SuIEoM61Gxy8B43vyeJHEw+j66OA+OIollOHXuqnwZfv1S6AlCCCHEF4DfxJdffqn+Hu5SYZIzMCw1TFLdlUN2VwGHkPjk5s2bbst+k6QLrhGufHogUiDN0JX/krmkK3yEsACkUCLihCT9czUqbyaKIMQy/Hn4jMP/QUEMMSOEECJJPhUDS3QpM1iiMtJMztnLmAGOqnoKno+KqPqWkJgei6dPn1bPHG+VL8VMN0QYtIOpTOzLpMR/SeDYxG8lBJDofhcoghDLUKfVC1I897ty5PwDaV09k+QuUsnbTSKEEEJIAgNj1JiU/iUkoYBvBMoqJwUwyKQIwr5MimTw8rEZVQSIAUUQYhnSZs4nh07ckCvHd0iO4vVEvKTAE0IIIYQQQgixJhRBiKXwC0onOUo29HYzCCEk2ZGc0zEIsSI8ZwkhxDVJu6aZqTQc8u5cLUa9aMM4C3XfUfc+W7ZsWm+arryEEEJI7DFK7xpu+oQQa2CcswlVPpt4B5RlRQlY/CXsy6RESgsdm5aIBKlZs6bWZTYzcuRI+fnnn6VKlSr2+tEtWrTQms5btmyRq1evSo8ePVQFR8k5QgghhMQcf39/yZQpk5YZBGnSpPGaIWB88+DBA50sCQkJ0Vx/wr7zhWMP974QQHDO4tzFOUx8BwwwR48e7e1m+ATsy+Tbn5YQQVDDGfWXDVAfGnWZUVLOuBH76aeftPwR3GgNN9jJkyerI/u7775L4yBCCCEklhi/wYYQ4itgsHjnzh1JnTq1zwg7iQX7Lun3HwQQ8/0zIYQQC4kgzkAAuXLlikPJue3bt0u5cuUcyuE0adJEQkNDZffu3VKvXj2X74XnsZhL+xhCC5bExNhfYu/XV2D/sf947FkTnrvW6DukmWbOnFnu3bvnM14D+Czbtm3TiFNUICHsO1849iCq4D0RAYL9uIL3moSQ5EwKmwXvZJo3b65/V69ebV/3wgsvyIkTJzQixDksB/Xhu3bt6vK9ELIzZsyYSOu/+OILDfklhBBCCCHEl0C6TLdu3eTGjRuMliaEJDu8Ou3hToAwA+NTw/cDnDlzRn788UdZunRppG1dhRNC44kqzHDYsGEycOBAh0iQ/PnzS+PGjRP9RwGq/Nq1a6VRo0Y0sWL/JTo8/th33oLHHvuOx5714Hlr7f4zIp+JtSlUqJCcPHnSYd3QoUNl/PjxXmuTlfj4449l0qRJ6j1ZtmxZmTZtmtSuXdvbzbIUo12M53PmzCkXLlyQpIxXRRB4enTp0iXak9vMvHnzJGvWrNK6dWuH9ch53Llzp8O669ev648Mvgh3IFLElYMtfpC85abtzX37Auw/9h+PPWvCc5d9x2PPevC8tWb/8T7Td3j77beld+/e9v/TpUvn1fZYhSVLlshrr72mQkitWrVk1qxZ0qxZM/WYLFCggLebZynKli2rBUsMrGDG7FURBPnFWDwFUR0QQZ555plIF+8aNWqoASqUvNy5c+s6pMZA4KhcuXK8t50QQgghhBBCvEn69OlpgBsLpkyZIj179pRevXrp/4gCQbbBJ598IuPGjYvvr8mnCQgIsNwxaCkXsPXr18vx48f1gHUG6StlypSR7t27a1jTtWvX5PXXX1dlNCZpLYZFijfCBBG1ghxN7JsKPfuPx5914LnL/uOxZ0147rLvkuuxZ9znWtAakDgxYcIEGTt2rKbzP/nkkzJ48GCtrEncg/LUKJzxxhtvRBpPwrCYxIwjR45ocRIEH1SrVk3ee+89KVKkiCRlLCWCfPrpp+qiXbp06UjPIexm1apV8vLLL2tIE0qOwfDp/fffj9E+bt68qX9xISGEEEIIIcRXwX1vxowZvd0MEkv69+8vlSpV0spdu3btUq9DTBjPnTuXfRoFqDJ6//79SJYJVvCySGpUq1ZNFixYICVKlJCLFy/KO++8o+P1AwcOqIVFUsWS1WESkgcPHsi5c+c0tCyh6ra7wzBlPX36NJ262X+JDo8/9p234LHHvuOxZz143lq7/3D7DwEEs7d+fn6Jvn8Sv4UjDL755hvp2LGjDvKT8gDU22CslzdvXo36gKWCAawVFi5cKIcOHfJq+6zM7du3pWjRojJkyBCH4iNJDUtFgiQG+CHIly+fV9uAH0Nv/CD6Cuw/9h+PPWvCc5d9x2PPevC8tW7/MQIkaRKbwhEG1atX179Hjx6lCBIF8KREFoFz1MelS5eiLKhBoidt2rRSvnx5TZFJylAEIYQQQgghhJAkQEwLR5jZu3ev/jWKRBDXwDMFhTNQprpdu3b29fi/TZs27LY4EBoaKgcPHkzypYYpghBCCCGEEEKIhdi+fbvs2LFD6tWrp1E9SJEZMGCAtG7dmiVePQCpGiiogbQipMTMnj1bTp06JS+99FLCf3k+xOuvvy6tWrXSYw6RNPAEQbpfjx49JClDESQJAUfdt956S/8S9h+PP+vAc5f9x2PPmvDcZd/x2CNWvn4tWbJE/UMw+16wYEGtigkvBhI9nTt3lqtXr8rbb78t58+fl3Llysnq1au1H4nnnDlzRrp27ao+NNmzZ9eULIhzSb0faYxKCCGEEEIIIYSQZAHtoAkhhBBCCCGEEJIsoAhCCCGEEEIIIYSQZAFFEEIIIYQQQgghhCQLKIJ4gZs3b8prr72mhjGpU6eWmjVrqqOzgc1mk9GjR0uePHn0+bp168qBAwckObJp0yZ1HEZfpEiRQlasWOHwvCd9BbOofv36abkx1K6GazZMfJID0fXfsmXLpEmTJto3eH7fvn2R3iO59l9UfXf37l0ZOnSo1kFHn2CbZ555Rs6dO+fwHsm17zw59nDelipVSvslc+bM0rBhQ9m5c6fDNsm1/6LrOzMvvviibjNt2jSH9cm17zzpv2effVbXmxcYuZlh/0V9/KH8IY4pVKRInz699h+qKiT3/ovu2HM+7oxl0qRJktz7jhBCEhOKIF6gV69eWod64cKF8scff0jjxo11AHD27Fl9fuLEiTJlyhSZMWOGiiO5cuWSRo0aqXiS3Lh9+7ZUqFBB+8IVnvQVBKfly5fL4sWLZcuWLXLr1i1p2bKl3L9/X5J7/+H5WrVqyfjx492+R3Ltv6j6Ljg4WPbs2SMjR47UvxCTDh8+rDerZpJr33ly7JUoUUKfwzUQfVOoUCG9Fl6+fFmSe/9F13cGGGBBOMKAy5nk2nee9l/Tpk21GoCxoCKAGfaf+/47duyYPP744ypibty4UX7//Xe9FqZKlSrZ9190x575mMPy2WefqQjSoUOHZN93hBCSqNhIohIcHGzz9/e3rVy50mF9hQoVbMOHD7c9ePDAlitXLtv48ePtz4WEhNgyZsxomzlzZrL+tnC4Ll++3P6/J33177//2gIDA22LFy+2b3P27Fmbn5+f7YcffrAl5/4zc/z4cX1+7969DuvZf9H3ncGuXbt0u5MnT7LvYnDsGdy4cUO3+/nnn9l/HvTdmTNnbHnz5rX9+eeftoIFC9qmTp3K89bD/uvRo4etTZs2bo9FXvei7r/OnTvbnn76afZfPFz3cBzWr1+fxx4hhCQyjARJZO7du6czceYZE4BUDszWHT9+XC5cuKAzouY64HXq1JFt27YldnOTNJ701e7duzV1wbwNZk1RC5z9GT3sP8+5ceOGzuhlypSJfRdDwsLCZPbs2Rpaj1lUHntR8+DBA+nevbsMHjxYypYtG+l5nrfRgwiGHDlyaERS79695dKlS+w/D4+9VatWab8hlRJ9WK1aNYe0Dx5/nnHx4kXty549e7LvCCEkkaEIksggd7ZGjRoyduxY9Q+AILJo0SINaUZoJAb1IGfOnA6vw//GcyQcT/oKf4OCgtRzgP0Zc9h/nhESEiJvvPGGdOvWTTJkyMC+85CVK1dKunTpVBSeOnWqpgkiD57HXtRMmDBBAgIC5NVXX+V5GwuaNWsm//vf/2T9+vUyefJkTaWsX7++ejHw2IsaiEVIrUIKJVKKfvrpJ2nXrp20b99efvnlF/ZfDJg/f77eE6LvDPibSwghiQNFEC8ALxBESubNm1cjFz744AMdPPn7+9u3wYyyGWzvvI7Evq/Yn3GD/RcBIo26dOmiM6Qff/wx+y4G1KtXT814EZWFAVWnTp0cZuR57EUGs+zTp0+Xzz//PMa/CTxvw+ncubO0aNFCIwJhYrlmzRr19MGsPPsvanCdA23atJEBAwbIo48+qgIw/GZmzpzJ/osB8AN56qmnIkUG89wlSYXojLmTMvAZczYMN3PixAm3BQGSIij8AK+quALxH35ODx5ey6MC3kbOXne+BEUQL1C0aFGdMcFsyunTp2XXrl06kCpcuLAaewLnqA8MDJwjHpI7nvQVtkGo/fXr191uQ6LuY/afe3DeYuCO1CxEMRhRIOw7z0Dlg2LFimlliU8//VSjG/CX/eeezZs36/WrQIEC2l9YTp48KYMGDdKbPvZdzMmdO7dWazty5Aj7LxoQqYVjrkyZMg7rS5cuba8Ow98Nz87jv//+W43yzbDvSEKByQZMtmLCwRlUa4OgmVRJiPblz59fI/AhhicnhgwZIsOHDxc/vwgJYMyYMZIvXz41vMZ1yQCpooiUhF2DL0IRxMsDANx8YYD+448/6syKIYRgQGWAQShEE5TSJRF40leVK1eWwMBAh21w0fvzzz/Znx7A/oteAMHA6eeff5asWbOy7+IIIhWMlAQee66BF8j+/ft19spY4HMEfxD8jrDvYs7Vq1d1QgK/x+y/qEF66WOPPeZwowwQSQMhif3nGRB7cY0zPJAMeN0jCRl5hNLLGNCay1kn9XsCeCkmBBCEMIaAqJuchDDcsz755JP2dTgeEAX57bffalZC37597c8hWwHrPvzwQ/FJEtuJldi0KsmaNWts//zzj+2nn37SyjBVq1a1hYWFafeg2gkqnCxbtsz2xx9/2Lp27WrLnTu37b///kt23Xfz5k2tWIIFh+uUKVP0sVGBw5O+eumll2z58uXTqhN79uxRJ3b0+b1792zJvf+uXr2q/69atUqfRxUd/H/+/Hlbcu+/qPru7t27ttatW2u/7Nu3T/vLWEJDQ23Jve+i679bt27Zhg0bZtu+fbvtxIkTtt27d9t69uxpS5kypVY7Se79F91564xzdZjk3HfR9R+eGzRokG3btm1aFWvDhg22GjVqaKUd/m5E338Av7eoujZ79mzbkSNHbB9++KFWvdu8ebMtuR9/npy7qISVJk0a2yeffOLyPZJr35GEA7+56dOntx06dEirO40ZM8b+3Lx58/RYNS9YB/B4zpw5trZt29pSp05tK1asmO3bb7+1v7ZSpUq2999/36HaEa4FOMYB7onwHtgvWLhwoa1y5cq2dOnS2XLmzKn37BcvXrS/HtdjbI9xErbDdeazzz5z27633nrLlj9/fltQUJDe+/fr18/hd/Hdd9+1Pffcc7o/bDdr1iy3VRGNfaN65yOPPKL3Ixib7d+/P8q+nTx5sq1cuXJ6TuO87dOnj14HzP2LcQo+U6lSpWxp06a1NWnSxHbu3Dn7NrinRNuxXZYsWWxDhgyxPfPMMw5VzOrUqWPr37+//X/caw4ePNiWJ08e3Tfais8QFdhHx44dHdZ9//33ej+LMeiOHTtsjz32mMPzGzdu1P5FdVNfgyKIF1iyZImtSJEielChxOsrr7yiJfnMpV9xYuM5nIRPPPGEDvCTI8ZFyXlBiUNP++rOnTu2vn376oUFF/GWLVvaTp06ZUsORNd/rn78sKBPk3v/RdV3xo+nq8X8I5Rc+y66/kO/tGvXTn+8jZsX/AijzLCZ5Np/0Z23noggybXvous/3Mg1btzYlj17dr3BLlCggK537hv2X9TH36effqoDolSpUukAfcWKFew/D89dDMRwTprv+3jskYQE52uVKlXsg95ChQrp/TPANRHCcNmyZe2TOcaAF8cuBvZffPGFCp6vvvqqCgqYQAMDBw7U3xaA98PvTbZs2XRiDeB1uD83t2P16tW2Y8eO6SRI9erVbc2aNYt0/kCEwCTx0aNHtRy8q/Z99dVXtgwZMuj7QWTcuXOnCrPm30W056OPPtK2jxs3zubn52c7ePBglCJI6dKldd8QP/DZ0FfGJLUr8Nu7fv16ndhet26drWTJkiqEGOA+G781DRs2tP3666866YN9dOvWzb7NO++8o22FwIz2QQjFZ4tKBMHra9asadu0aZP206RJk3QcdPjwYbdtxbUak8dmwsLCbE2bNrUFBATYMmXKpOKrs4CWIkUKFUN8DYoghBBCCCGEEOKDYLA8bdo0e9QBhIq1a9fan8fEFwbIzkAUGDFiRKQBMaLZwXfffafRC/fv39eoWIjLAwYM0AgF8MILL2jkiTsw8YF9GJEThhDhLKq6ah8iMEqUKOFWoIAI8vTTT9v/h0iTI0cOewSWOxEEEdEGEHsgWGLy2lOWLl1qy5o1q/1/Y7IRQoUBhBlEwhjgMUQMA0R9QaB3J4LgvfA9nD171mHfDRo00Chbd+C7WrBggcvnLl686BDJbCZz5sy2zz//3OZr0BOEEEIIIYQQQnwM+PegAAOq2AF4YKBCFjxCPOGRRx5x8DJEWWejitsTTzwhN2/elL1796ofX506dbTqm1Eue+PGjbrOANvB/xD+QXgfVDwBzh4lVapUibZd8LW4c+eOFClSRA08ly9fHsk/xNx2VIKBB0h0Fehq1Khhf5wlSxYpWbKkHDx40O32GzZskEaNGmnFT3ymZ555Rn2mbt++bd8mTZo0WhTDAP5TRjtu3LghFy9elKpVqzr4lcAfyB179uxRv5QSJUpIunTp7Av6/dixY25fh/5yV40qR44c6vnkitSpU0twcLD4GsnHDYYQQgghhBBCkpEJL8QBDNINMIBG0QAUZsicOXOUr8d2ZiAmGOVVM2bMqFVbIHbAdLN+/fpSu3ZtNeyGAScMkw2hA6JA48aNdVm0aJFkz55dxY8mTZpoUQMzEFs8qe4CgQeFD2BO//LLL8ukSZNUCDDaHFXbY4K7cvSozNa8eXN56aWXZOzYsSqawGi0Z8+eap5v4Kod4YE27vfh/LwZfAYIJbt379a/ZiCGRFXdy7lapidcu3ZNvy9fg5EghBBCCCGEEOJDQPxYsGCBTJ482aGi2O+//67RGP/73/90O0QA3L9/P1b7gMiBaIhNmzbp40yZMmkJ7XfeeUejC1A+Gxw6dEiuXLki48ePV6GkVKlS0UZlGLhrHyIUWrduLR988IEKMdu3b5c//vhD4sKOHTvsjyEYQMhBW13x22+/aR+jf6tXr66RGefOnYvR/iAk5cyZU6N1DPBZETXjjooVK+o26L9ixYo5LIh2iep1f/31V4zad+zYMQkJCdHX+hqMBCGEEEIIIYQQH2LlypU6kEdkAgbbZjp27KhRIiiJWqhQITl+/LgKJPny5dO0DpRH9QQIH9OnT9coCIgfxjqUVW3fvr19uwIFCqiYgfWInPjzzz81esITXLXvyy+/VCGgWrVqmm6ycOFCFUWMUt2x5e2335asWbOqMDF8+HCNnmjbtq3LbZHiAhEEn6lVq1aydetWmTlzZoz3idLF48aNUxEDggveD9+buwgUiC1PPfWUpt5AgIFAAYFp/fr1Ur58eY1OcQWibubPnx+jtm3evFlTjszpPL4CI0EIIYQQQgghxIeAyNGwYcNIAgjo0KGDigrwl8Djpk2bqp8H0h4gMHgKfEEAvD+MQTseQ6Aw+4HgfT///HP56quvVCxBRMj777/v0T5ctQ8RJ3PmzJFatWqp98e6devk+++/VwEjLqBd/fv3V0+O8+fPy3fffefWKwOpQFOmTJEJEyZIuXLlNLIGYkZMGTp0qHTt2lVFDXiSIKUFgoU7/w4wb9483X7QoEHqW4KImJ07d2qakDuefvppjQRBGpGnoK/hueKLpIA7qrcbQQghhBBCCCGEJDZIp4HIgggMCCzeBJ4fSCPq1KmTx9EynjJkyBA1Y501a1a02yJap0GDBpoS5EpIszqMBCGEEEIIIYQQQhIZGKwiqgViAzxN+vTpo+k/3bp1i/d9IcUHKUP3PfCAgb8JPGV8UQABjAQhhBBCCCGEEJIs8WYkyOnTp7WEMSIvkKCB1Bqk5RipRiRhoAhCCCHEJ0HZPeQewwgMecMnTpyQwoULq+s6cnkTCszkNGvWTPNuPSn1RwghhBBCEg+mwxBCiAV49tln1XTMeTl69Ki3m5ZkmT17toZ9QgDxFLjQT5s2LdL60aNHeyycwJ29atWqMnXq1Bi1lxBCCCGEJDwUQQghxCLAHR1u5eYFkQ2uIiCIaJm5Xr16eaUrnnvuOfnkk088yrslhBBCCCGJB0UQQgixCClTppRcuXI5LP7+/lK3bl3p27evDBw4UGvaN2rUSLdHKTTUi0e5NdS87969u9aSN7h9+7aWWMPzuXPn1nrzeK/XXnvNvg2iTVasWOHQDuTLotSdwdmzZ6Vz586SOXNmLU/Xpk0bTT0xR7G0bdtWy+FhP9jmlVdekbt379q3CQ0NVddylHfD5yxevLiW90N+bLFixSKV0kPurJ+fnxw7dsxlX6HsH6JkWrRoEaUDO0q/lShRQo3JYoKrqBxEkRigvN3Vq1fll19+idH7EkIIIYSQhIUiCCGE+ADwvQgICJCtW7dq6TNEidSpU0dTOH777Tf54Ycf5OLFi1pyzWDw4MGyYcMGWb58ufz0009qDLZ79+4Y7Tc4OFjNxCCkbNq0SbZs2aKPEbVijkjBfiBY4C/aChHFLKRAjFm8eLF88MEHcvDgQZk5c6a+D8SF559/XubNm+ew388++0xq164tRYsWddkutAXiRoYMGVw+j7ahL9A3aDPSZmKCORoHYguEGrOJWVBQkFSoUEE2b94co/clhBBCCCEJS0ACvz8hhJB4YuXKlSoMGMB886uvvtLHGIRPnDjR/tyoUaOkUqVK8t577zkIB4i0QBm2PHnyaKQFyp8ZkSMQJ/LlyxejNkG4QETG3LlzVbAAECwQLQJRpXHjxroOUSIzZszQyJVSpUpphMa6des0EgPtWbp0qaxdu1YaNmyo2xcpUsQhtQSfZ9euXeq1gQiSRYsWyaRJk9y2C5Eo+IyuuHXrlu7/zp072kbn8m9Dhw6VESNGuDRZNUAUDkCkSocOHfQ9ID6ZyZs3r0NEDCGEEEII8T4UQQghxCIg4gI+EwbmyiNVqlRx2BYRHYi6MIsmBojIgACAgX2NGjXs67NkySIlS5aMUZuwH0RCpE+f3mF9SEiIQ6pK2bJlVQAxQFoMqqiAffv26XOIXHEFtoVoAREHIgjEILz/k08+6bZd+HypUqVy+VzXrl1V7IEIkyZNmkjPI0IGKTxmEKGC6BJn3nzzTdm+fbv8+uuvkjp1aofn8D8iZQghhBBCSNKBIgghhFgEiB6I+HD3nLPfRatWrWTChAkuRYUjR454tE9EdyDawYzZywP7qVy5svzvf/+L9Nrs2bPbHwcGBkZ6X7wWOIsHroDBKTxNUHEFkSbwIHElYBjAG8UQWZyBTwoiSXbs2CH169d3+VrnfoZA5AzeA+1BNImrCJpr1665TdchhBBCCCHegZ4ghBDigyAV5sCBA2rWiQG9eTHEFAgTEAIMrl+/rqkpzkIGfC8MIJ6YoxuwH6zLkSNHpP04p5lEVVIWgkhUJqIQLtBuRMKsWbNGfUKiomLFinLo0KFIAg7o06ePjB8/Xlq3bh1r41JEf0CYQQpM9erVXW4D81a0gxBCCCGEJB0oghBCiA+C6iuIREDqB7w0/vnnHzU/hXiAsq1Ik+nZs6emfiAtBAN2pIDA38MMIiXg5YFqKzARfemllxyiOp566imNnEBFGJiAHj9+XIWF/v37y5kzZzxqK4SaHj16aNtQiQbvgegK+IQYIF0G7Rs2bJgKLOY0HnepQ6h+AyHIFf369ZN33nlHWrZsqcaoMeHChQvSrl076dKli1aBwf9YLl++bN8GXiCommN4nBBCCCGEkKQBRRBCCPFBYAqKSjEQPDBQL1eunAoTiM4whA4Yi6KiCSIiMFh//PHHNbXFDMrmwkwV23Xr1k1ef/11hzQUPIZXRoECBaR9+/ZSunRpFTPgyeGuMosrEOHRsWNHefnll9U4FYapEDHMQLSBj0l0USAAZXjRHldpOgYoBTxmzBiNMtm2bZvHbUWECSrtwEgWqUXG8thjj9m3+fLLL9UUNqZVZwghhBBCSMKSwuYqVpgQQkiypG7dulpWd9q0aZLUgKiD9iHCJGfOnNFuD08QiDuujFsTktDQUClevLgKIbVq1Uq0/RJCCCGEkOhhJAghhJAkDUQFCBkjR46UTp06eSSAGF4jKBuc2GVqT548KcOHD6cAQgghhBCSBGF1GEIIIUkaRFQgFQYRKgsXLozRa+E1ktiUKFFCF0IIIYQQkvRgOgwhhBBCCCGEEEKSBUyHIYQQQgghhBBCSLKAIgghhBBCCCGEEEKSBRRBCCGEEEIIIYQQkiygCEIIIYQQQgghhJBkAUUQQgghhBBCCCGEJAsoghBCCCGEEEIIISRZQBGEEEIIIYQQQgghyQKKIIQQQgghhBBCCEkWUAQhhBBCCCGEEEKIJAf+D/1ic+d3d9TzAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1100x800 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# --- Choose API target to inspect ---\n",
+    "target_to_plot = 509\n",
+    "\n",
+    "ch = tsf_channel\n",
+    "\n",
+    "api_color = \"black\"\n",
+    "crimac_color = \"orange\"\n",
+    "range_color = api_color\n",
+    "\n",
+    "# CRIMAC reference target\n",
+    "crimac_ping_idx = tsf_ping_index\n",
+    "crimac_range = r_t\n",
+    "crimac_theta = theta_t\n",
+    "crimac_phi = phi_t\n",
+    "\n",
+    "f_crimac = ref_ts[\"f_m\"]\n",
+    "ts_crimac = ref_ts[\"TS_m\"]\n",
+    "\n",
+    "# API target selection\n",
+    "ts_api_plot = (\n",
+    "    ds_TS_spectrum_fr[\"TS_spectrum\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "api_ping_time = (\n",
+    "    ds_TS_spectrum_fr[\"ping_time\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "f_api_plot = ds_TS_spectrum_fr[\"frequency\"].values\n",
+    "\n",
+    "target_range_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"target_range\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "theta_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"angle_alongship\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "phi_plot = float(\n",
+    "    ds_TS_spectrum_fr[\"angle_athwartship\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(target_id=target_to_plot)\n",
+    ")\n",
+    "\n",
+    "api_ping_idx_plot = int(\n",
+    "    np.argmin(\n",
+    "        np.abs(\n",
+    "            cal_obj.beam[\"ping_time\"].values.astype(\"datetime64[ns]\")\n",
+    "            - np.datetime64(api_ping_time, \"ns\")\n",
+    "        )\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "print(\"target_to_plot:\", target_to_plot)\n",
+    "print(\"api target_id:\", ds_TS_spectrum_fr[\"target_id\"].isel(target_id=target_to_plot).values)\n",
+    "print(\"api ping index:\", api_ping_idx_plot)\n",
+    "print(\"api target range:\", target_range_plot)\n",
+    "print(\"api theta/phi:\", theta_plot, phi_plot)\n",
+    "print(\"CRIMAC ping index:\", crimac_ping_idx)\n",
+    "print(\"CRIMAC range:\", crimac_range)\n",
+    "print(\"CRIMAC theta/phi:\", crimac_theta, crimac_phi)\n",
+    "\n",
+    "# --- Echogram from public API Sp output ---\n",
+    "ping_start = 400\n",
+    "ping_end = 650\n",
+    "\n",
+    "echogram_db = (\n",
+    "    ds_Sp[\"Sp\"]\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(ping_time=slice(ping_start, ping_end + 1))\n",
+    "    .transpose(\"range_sample\", \"ping_time\")\n",
+    ")\n",
+    "\n",
+    "r_plot = (\n",
+    "    cal_obj.range_meter\n",
+    "    .sel(channel=ch)\n",
+    "    .isel(ping_time=ping_start)\n",
+    "    .values\n",
+    ")\n",
+    "\n",
+    "ping_no = np.arange(ping_start, ping_end + 1)\n",
+    "valid_r = np.isfinite(r_plot)\n",
+    "\n",
+    "fig = plt.figure(figsize=(11, 8))\n",
+    "gs = fig.add_gridspec(\n",
+    "    2,\n",
+    "    2,\n",
+    "    width_ratios=[3, 1],\n",
+    "    height_ratios=[1.4, 1],\n",
+    ")\n",
+    "\n",
+    "ax0 = fig.add_subplot(gs[0, :])\n",
+    "ax1 = fig.add_subplot(gs[1, 0])\n",
+    "ax2 = fig.add_subplot(gs[1, 1])\n",
+    "\n",
+    "# --- Echogram ---\n",
+    "im = ax0.pcolormesh(\n",
+    "    ping_no,\n",
+    "    r_plot[valid_r],\n",
+    "    echogram_db.values[valid_r, :],\n",
+    "    shading=\"auto\",\n",
+    "    vmin=-110,\n",
+    "    vmax=-40,\n",
+    ")\n",
+    "\n",
+    "ax0.axvline(\n",
+    "    crimac_ping_idx,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=2,\n",
+    "    label=f\"CRIMAC ping index: {crimac_ping_idx}\",\n",
+    ")\n",
+    "\n",
+    "ax0.axvline(\n",
+    "    api_ping_idx_plot,\n",
+    "    color=api_color,\n",
+    "    linestyle=\"--\",\n",
+    "    linewidth=2,\n",
+    "    label=f\"API target ping index: {api_ping_idx_plot}\",\n",
+    ")\n",
+    "\n",
+    "ax0.axhline(5.3, color=\"white\", linestyle=\"--\", linewidth=1)\n",
+    "ax0.axhline(6.3, color=\"white\", linestyle=\"--\", linewidth=1)\n",
+    "\n",
+    "ax0.axhline(\n",
+    "    crimac_range,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=1.5,\n",
+    "    label=\"CRIMAC target range\",\n",
+    ")\n",
+    "\n",
+    "ax0.axhline(\n",
+    "    target_range_plot,\n",
+    "    color=range_color,\n",
+    "    linewidth=1.5,\n",
+    "    linestyle=\"--\",\n",
+    "    label=\"API target range\",\n",
+    ")\n",
+    "\n",
+    "ax0.set_ylim(8, 3)\n",
+    "ax0.set_xlabel(\"Ping index\")\n",
+    "ax0.set_ylabel(\"Range (m)\")\n",
+    "ax0.set_title(\"Broadband Sp echogram\")\n",
+    "ax0.legend(loc=\"upper right\")\n",
+    "\n",
+    "cbar = plt.colorbar(im, ax=ax0)\n",
+    "cbar.set_label(\"Sp (dB)\")\n",
+    "\n",
+    "# --- TS(f) ---\n",
+    "ax1.plot(\n",
+    "    f_crimac / 1000,\n",
+    "    ts_crimac,\n",
+    "    color=crimac_color,\n",
+    "    linewidth=2,\n",
+    "    label=\"CRIMAC reference\",\n",
+    ")\n",
+    "\n",
+    "ax1.plot(\n",
+    "    f_api_plot / 1000,\n",
+    "    ts_api_plot.values,\n",
+    "    color=api_color,\n",
+    "    linestyle=\"--\",\n",
+    "    linewidth=2,\n",
+    "    label=\"echopype API TS_spectrum\",\n",
+    ")\n",
+    "\n",
+    "ax1.set_xlabel(\"Frequency (kHz)\")\n",
+    "ax1.set_ylabel(\"TS(f) dB\")\n",
+    "ax1.set_title(\"TS(f)\")\n",
+    "ax1.grid(True)\n",
+    "ax1.legend()\n",
+    "\n",
+    "# --- Circular angle plot ---\n",
+    "beam_limit = 7.0\n",
+    "circle = plt.Circle((0, 0), beam_limit, fill=False, linestyle=\"--\")\n",
+    "ax2.add_patch(circle)\n",
+    "\n",
+    "ax2.axhline(0, color=\"grey\", linewidth=0.8)\n",
+    "ax2.axvline(0, color=\"grey\", linewidth=0.8)\n",
+    "\n",
+    "ax2.scatter(\n",
+    "    crimac_phi,\n",
+    "    crimac_theta,\n",
+    "    s=90,\n",
+    "    color=crimac_color,\n",
+    "    label=\"CRIMAC\",\n",
+    ")\n",
+    "\n",
+    "ax2.scatter(\n",
+    "    phi_plot,\n",
+    "    theta_plot,\n",
+    "    s=70,\n",
+    "    color=api_color,\n",
+    "    marker=\"x\",\n",
+    "    label=\"API\",\n",
+    ")\n",
+    "\n",
+    "ax2.set_xlim(-beam_limit, beam_limit)\n",
+    "ax2.set_ylim(-beam_limit, beam_limit)\n",
+    "ax2.set_aspect(\"equal\", adjustable=\"box\")\n",
+    "\n",
+    "ax2.set_xlabel(\"Athwartship angle (°)\")\n",
+    "ax2.set_ylabel(\"Alongship angle (°)\")\n",
+    "ax2.set_title(\"Target angle\")\n",
+    "\n",
+    "ax2.text(\n",
+    "    0.98,\n",
+    "    0.02,\n",
+    "    f\"API range = {target_range_plot:.2f} m\\n\"\n",
+    "    f\"API along = {theta_plot:.2f}°\\n\"\n",
+    "    f\"API athw. = {phi_plot:.2f}°\\n\"\n",
+    "    f\"CRIMAC range = {crimac_range:.2f} m\\n\"\n",
+    "    f\"CRIMAC along = {crimac_theta:.2f}°\\n\"\n",
+    "    f\"CRIMAC athw. = {crimac_phi:.2f}°\",\n",
+    "    transform=ax2.transAxes,\n",
+    "    ha=\"right\",\n",
+    "    va=\"bottom\",\n",
+    "    fontsize=8,\n",
+    ")\n",
+    "\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7a70f471",
+   "metadata": {},
+   "source": [
+    "Print of import and their version"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "id": "7d490e20",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Python: 3.12.13\n",
+      "echopype: 0.11.2.dev22+gc1a2a5660\n",
+      "numpy: 2.4.4\n",
+      "pandas: 3.0.2\n",
+      "xarray: 2026.4.0\n",
+      "matplotlib: 3.10.9\n"
+     ]
+    }
+   ],
+   "source": [
+    "import sys\n",
+    "\n",
+    "print(\"Python:\", sys.version.split()[0])\n",
+    "print(\"echopype:\", ep.__version__)\n",
+    "print(\"numpy:\", np.__version__)\n",
+    "print(\"pandas:\", pd.__version__)\n",
+    "print(\"xarray:\", xr.__version__)\n",
+    "print(\"matplotlib:\", plt.matplotlib.__version__)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5923b86e",
+   "metadata": {},
+   "source": [
+    "End of notebook."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "echopype-examples",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/notebooks/images/gallery/11_getting_started_FM_TS.png b/notebooks/images/gallery/11_getting_started_FM_TS.png
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z-?s@YyWr>NmjprJEnSNe$JZoUp#5q2$9e6yy8!2yZnq<x)tCa-iqgt^NMVY?#XNlQ
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Zd$@WzcW%GR9sD86I@WsQ93$uO{{c}JlqmoJ

literal 0
HcmV?d00001

diff --git a/notebooks/utils/data.py b/notebooks/utils/data.py
new file mode 100644
index 0000000..b89357a
--- /dev/null
+++ b/notebooks/utils/data.py
@@ -0,0 +1,62 @@
+from pathlib import Path
+import pooch
+
+EXAMPLE_DATA_DIR = Path("example_data")
+
+DATASETS = {
+    "ts_spectrum_example_data": {
+        "release": "example-data-v1",
+        "asset": "ts_spectrum_example_data.zip",
+        "sha256": "A35A1108DCFAFAE725D826FFA23EA2E111FDB420E7CE433E49E1797381BB6763",
+        "files": [
+            "IMR-D20211215-T143432-TSf.raw",
+            "crimac_tsf_reference_outputs.npz",
+        ],
+    },
+}
+
+def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
+    """Download and extract an example dataset if it is not available locally."""
+    if name not in DATASETS:
+        raise ValueError(f"Unknown dataset: {name}")
+
+    dataset = DATASETS[name]
+    dataset_dir = data_dir / name
+
+    expected_files = [dataset_dir / file for file in dataset["files"]]
+
+    if all(file.exists() for file in expected_files):
+        print(f"Using local dataset: {dataset_dir}")
+        return dataset_dir
+
+    print(f"Downloading dataset: {name}")
+
+    fetcher = pooch.create(
+        path=data_dir,
+        base_url=(
+            "https://github.com/echostack-org/echopype-examples/"
+            f"releases/download/{dataset['release']}/"
+        ),
+        registry={
+            dataset["asset"]: f"sha256:{dataset['sha256']}",
+        },
+    )
+
+    zip_path = Path(
+        fetcher.fetch(
+            dataset["asset"],
+            processor=pooch.Unzip(),
+        )
+    )
+
+    zip_path.unlink(missing_ok=True)
+
+    missing_files = [file for file in expected_files if not file.exists()]
+    if missing_files:
+        raise FileNotFoundError(
+            "Dataset download/extraction finished, but some expected files "
+            "are missing: "
+            + ", ".join(str(file) for file in missing_files)
+        )
+
+    return dataset_dir
\ No newline at end of file

From 698fc1b0d5ff58385b9558aa82ba486cacf90e0d Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Fri, 19 Jun 2026 15:57:18 -0700
Subject: [PATCH 09/11] Update getting_started_FM_TS.ipynb

---
 notebooks/getting_started_FM_TS.ipynb | 1590 +++++++++++--------------
 1 file changed, 675 insertions(+), 915 deletions(-)

diff --git a/notebooks/getting_started_FM_TS.ipynb b/notebooks/getting_started_FM_TS.ipynb
index 388ccfd..39ffba6 100644
--- a/notebooks/getting_started_FM_TS.ipynb
+++ b/notebooks/getting_started_FM_TS.ipynb
@@ -9,6 +9,9 @@
     "\n",
     "This notebook demonstrates a minimal workflow for computing broadband target-strength spectra (`TS_spectrum`) with echopype from EK80 FM data.\n",
     "\n",
+    "> **Note**\n",
+    "> `compute_TS_spectrum` is currently available only in the development version of echopype. To run this notebook, please install echopype from source rather than using the latest official release.\n",
+    "\n",
     "The results are compared against the CRIMAC reference implementation described in Andersen et al. (2024). The comparison examines intermediate processing steps as well as the final TS spectrum estimates.\n",
     "\n",
     "Reference implementation:\n",
@@ -129,8 +132,8 @@
        "        <div class=\"xr-obj-type\">EchoData: standardized raw data from Internal Memory</div>\n",
        "    </div>\n",
        "    <ul class=\"xr-sections group-sections\">\n",
-       "        <li class=\"xr-section-list\"><input id=\"idata_30e636512bfd699b3737bb6422288382\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "            <label for=\"idata_30e636512bfd699b3737bb6422288382\" class=\"xr-section-summary\">Top-level: contains metadata about the SONAR-netCDF4 file format.</label>\n",
+       "        <li class=\"xr-section-list\"><input id=\"idata_af55cced81155a18216c1c80c2773993\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "            <label for=\"idata_af55cced81155a18216c1c80c2773993\" class=\"xr-section-summary\">Top-level: contains metadata about the SONAR-netCDF4 file format.</label>\n",
        "            <div class=\"xr-section-inline-details\"></div>\n",
        "            <div class=\"xr-section-details\">\n",
        "                <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -688,12 +691,12 @@
        "    sonar_convention_version:    1.0\n",
        "    summary:                     \n",
        "    title:                       \n",
-       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-c5c25caa-e8a4-41be-86fb-7825e0272897' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-6ed8e43b-ad4e-4ba3-b759-1ae2ae3b186f' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c609e00-3e63-4eaa-b2bc-ee9cd722e2df' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
+       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-466df8aa-aba3-4353-bfbe-a3e4babe495f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-466df8aa-aba3-4353-bfbe-a3e4babe495f' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-10c3052a-50c6-4af0-986d-92679ad58171' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-10c3052a-50c6-4af0-986d-92679ad58171' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-be3869f8-bda8-4ab2-82d0-c449a9ac82db' class='xr-section-summary-in' type='checkbox' checked /><label for='section-be3869f8-bda8-4ab2-82d0-c449a9ac82db' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
        "                </ul>\n",
        "            </div>\n",
        "        </li>\n",
-       "        <ul><li class=\"xr-section-list\"><input id=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_c4b3a05e308441de9a5fc7984a8a5ea7\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
+       "        <ul><li class=\"xr-section-list\"><input id=\"idata_b1c4faccf962c4bc31d9aaaa8f5c9aba\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_b1c4faccf962c4bc31d9aaaa8f5c9aba\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -1253,11 +1256,11 @@
        "    sound_velocity_profile        (time1, sound_velocity_profile_depth) float64 16B ...\n",
        "    sound_velocity_source         (time1) &lt;U6 24B &#x27;Manual&#x27;\n",
        "    transducer_name               (time1) &lt;U7 28B &#x27;Unknown&#x27;\n",
-       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-28eb5536-10bc-4980-90f8-4184d188b867' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-71a05870-a553-42cd-b245-8b1aa3f3ad09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff39da97-dfd4-4f54-a4b9-cec6072e9069' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' class='xr-var-data-in' type='checkbox'><label for='data-8495f0e6-9400-4eaf-9249-0ba6bf44f476' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c53dacc-dee2-4df1-8175-6bcfc4511bcf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecb51444-8504-4048-91ca-33ba4d52f994' class='xr-var-data-in' type='checkbox'><label for='data-ecb51444-8504-4048-91ca-33ba4d52f994' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-6e848675-e47b-4851-ba02-bd9c877972ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-013084fe-1ffe-4999-a356-8d0d0ffdcc97' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99a428ea-3629-4401-ab2b-63b36abda345' class='xr-var-data-in' type='checkbox'><label for='data-99a428ea-3629-4401-ab2b-63b36abda345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7244075-76f8-44bd-9201-338b4bde78cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19f8335a-e760-4b87-bb47-f6741b807beb' class='xr-var-data-in' type='checkbox'><label for='data-19f8335a-e760-4b87-bb47-f6741b807beb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5fbab09e-604a-4269-83f1-4b46233305d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a93263a4-e12b-46de-8ecd-9f93580c4065' class='xr-var-data-in' type='checkbox'><label for='data-a93263a4-e12b-46de-8ecd-9f93580c4065' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c30f383f-f02f-40e0-8f20-94e9bd6f531e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0f49309-8d87-466c-9340-4b0494611c41' class='xr-var-data-in' type='checkbox'><label for='data-b0f49309-8d87-466c-9340-4b0494611c41' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c26e2e4-b9b1-4bd7-934d-720d520daf28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' class='xr-var-data-in' type='checkbox'><label for='data-7dcaec79-fd23-45eb-8f40-6dfe834a8bce' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41d3db48-95e9-40f8-a08a-5e985a5132f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' class='xr-var-data-in' type='checkbox'><label for='data-c70f05dd-a89a-46f4-b2e3-82687fb71aaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dde82fed-5ff0-4c4e-969a-900e2da4e5f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' class='xr-var-data-in' type='checkbox'><label for='data-5ac2667a-47c0-4be1-91a6-c1eb12993854' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-5811d654-a60f-46c2-a651-d650e32e3558' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5811d654-a60f-46c2-a651-d650e32e3558' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' class='xr-var-data-in' type='checkbox'><label for='data-0b9ad8f6-4eb0-4c73-b8bc-a0faafd54946' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-67ac5f47-702c-48ea-aec9-98b3732cf857' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' class='xr-var-data-in' type='checkbox'><label for='data-b99b67b3-aa3a-43eb-9d11-5b32f122f6b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
+       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-005d6503-b9bf-4640-af84-18dcccd73b41' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-005d6503-b9bf-4640-af84-18dcccd73b41' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-0bd0521b-24a5-41ae-a7cd-97b5dcd09a35' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0bd0521b-24a5-41ae-a7cd-97b5dcd09a35' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-4128c7c4-2c02-4ef7-a1d3-47bfde5de4b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4128c7c4-2c02-4ef7-a1d3-47bfde5de4b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29ad7140-3d3d-46bd-8984-9a5bb024665d' class='xr-var-data-in' type='checkbox'><label for='data-29ad7140-3d3d-46bd-8984-9a5bb024665d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-620ba013-057c-4308-b2d5-4b95668f5f61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-620ba013-057c-4308-b2d5-4b95668f5f61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e45c014b-8dc2-4d17-b386-dd468a05e533' class='xr-var-data-in' type='checkbox'><label for='data-e45c014b-8dc2-4d17-b386-dd468a05e533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65c1c6fc-3af9-496c-9830-5e8ccff0830c' class='xr-section-summary-in' type='checkbox' checked /><label for='section-65c1c6fc-3af9-496c-9830-5e8ccff0830c' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-3be7d80f-29ab-4592-9523-e2265e9bae67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3be7d80f-29ab-4592-9523-e2265e9bae67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53584571-d86a-41be-9c8d-2d513e4aa64c' class='xr-var-data-in' type='checkbox'><label for='data-53584571-d86a-41be-9c8d-2d513e4aa64c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-5f5facda-96c4-4bce-aaf1-336bb50c7c75' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f5facda-96c4-4bce-aaf1-336bb50c7c75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8e976be-cdb9-4bbb-a5bd-dea4a3e907d0' class='xr-var-data-in' type='checkbox'><label for='data-c8e976be-cdb9-4bbb-a5bd-dea4a3e907d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-42f26e19-72bc-459a-80d6-891917d55dd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42f26e19-72bc-459a-80d6-891917d55dd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75bf026c-c1a2-45a1-bd71-e54d058ea743' class='xr-var-data-in' type='checkbox'><label for='data-75bf026c-c1a2-45a1-bd71-e54d058ea743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-da449f00-c0d1-4a28-b068-f6a20ebb3bf7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da449f00-c0d1-4a28-b068-f6a20ebb3bf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b00402d-50e0-4ef7-8763-52e03cfa1f31' class='xr-var-data-in' type='checkbox'><label for='data-6b00402d-50e0-4ef7-8763-52e03cfa1f31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-989a7ceb-0090-49b9-b96e-b7ffff992165' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-989a7ceb-0090-49b9-b96e-b7ffff992165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3cd4f6b-53b0-4157-a628-d20861f2733b' class='xr-var-data-in' type='checkbox'><label for='data-b3cd4f6b-53b0-4157-a628-d20861f2733b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-d2f39fd5-0754-4bd6-b47d-22bd9625b186' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2f39fd5-0754-4bd6-b47d-22bd9625b186' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5b31fdb-38db-487e-bde4-d6efb43af69a' class='xr-var-data-in' type='checkbox'><label for='data-c5b31fdb-38db-487e-bde4-d6efb43af69a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-635802e1-9262-47df-ab87-e11af36b3ffe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-635802e1-9262-47df-ab87-e11af36b3ffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-026bd23b-d9fb-4c84-8c9a-22ae2127e863' class='xr-var-data-in' type='checkbox'><label for='data-026bd23b-d9fb-4c84-8c9a-22ae2127e863' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-d979d40d-6fda-4bab-863c-0ff0a713e505' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d979d40d-6fda-4bab-863c-0ff0a713e505' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1497722-9772-4904-b01f-996dbd562723' class='xr-var-data-in' type='checkbox'><label for='data-c1497722-9772-4904-b01f-996dbd562723' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-a7a78fb3-119d-42cd-ad06-399cf2798165' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a7a78fb3-119d-42cd-ad06-399cf2798165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f48c4e6d-f556-4a40-8c9a-9d25bdaf87e5' class='xr-var-data-in' type='checkbox'><label for='data-f48c4e6d-f556-4a40-8c9a-9d25bdaf87e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><li class=\"xr-section-list\"><input id=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_ae385b7e2cc76df0a82e7acf0d2c2eb8\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_2caaefaf61acd5231f7765cb6c9770fa\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_2caaefaf61acd5231f7765cb6c9770fa\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -1827,19 +1830,19 @@
        "Attributes:\n",
        "    platform_name:       \n",
        "    platform_type:       \n",
-       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-61c1c821-179c-48d8-9b66-c98242697b76' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary-in' type='checkbox' checked /><label for='section-73925e75-1a24-4e6a-ad35-265f3201db03' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e010f183-62cd-4466-b10e-25ef5f2369fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab95c796-b965-431b-84cc-b90afd18dfe9' class='xr-var-data-in' type='checkbox'><label for='data-ab95c796-b965-431b-84cc-b90afd18dfe9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d972a333-6b9f-4e48-b4b6-0dc4115df731' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3f55aec-928e-45a5-949f-13ecff064c74' class='xr-var-data-in' type='checkbox'><label for='data-b3f55aec-928e-45a5-949f-13ecff064c74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3438db7-c95b-43ed-912a-5f24e0e75f28' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f3438db7-c95b-43ed-912a-5f24e0e75f28' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-7c1f2ab5-7624-43cc-9171-66e48fe53ca3' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c1f2ab5-7624-43cc-9171-66e48fe53ca3' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-2daedaba-719d-4a58-8f86-74c37b269349' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2daedaba-719d-4a58-8f86-74c37b269349' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-475f3967-0c5e-4d1d-be45-05325abd6a3b' class='xr-var-data-in' type='checkbox'><label for='data-475f3967-0c5e-4d1d-be45-05325abd6a3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-1c27c294-f73d-4848-ae33-51322d6d3cf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c27c294-f73d-4848-ae33-51322d6d3cf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3390f87-77dc-4ddf-b19f-9e3a3eae7b10' class='xr-var-data-in' type='checkbox'><label for='data-b3390f87-77dc-4ddf-b19f-9e3a3eae7b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac3afbc9-84c3-41bf-9f72-bacc4a565900' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c26d213-1db8-4e55-a36f-dab5efc95118' class='xr-var-data-in' type='checkbox'><label for='data-5c26d213-1db8-4e55-a36f-dab5efc95118' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-bd69fd79-ba80-430d-9401-924725055735' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd69fd79-ba80-430d-9401-924725055735' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f602ff0-9294-4fca-98a8-79db2c0ea8d7' class='xr-var-data-in' type='checkbox'><label for='data-9f602ff0-9294-4fca-98a8-79db2c0ea8d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6806ea60-12a6-47bd-ba49-bc880547f5da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' class='xr-var-data-in' type='checkbox'><label for='data-f42c48c0-9ba9-40fb-8a03-c941c8489aa2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary-in' type='checkbox' /><label for='section-109b9527-015f-4745-8845-f83e854ebac9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ecbf760-e4e0-444c-9a50-2dbbf4a16f88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' class='xr-var-data-in' type='checkbox'><label for='data-d7199b02-3046-4fd6-b8ad-e3ffcf411e7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52f002be-3db2-403e-bd60-6d8f8ccc4e8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' class='xr-var-data-in' type='checkbox'><label for='data-fe4c65aa-fbdb-4a8c-a28a-5e7fa08ae61a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21e1d573-61ac-4e53-8c2f-7d5ad4e718ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' class='xr-var-data-in' type='checkbox'><label for='data-7e2b282b-c5a9-4f47-99c2-912ef79355fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a6ed2cb-fc5b-4a94-8988-3430812ebc20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' class='xr-var-data-in' type='checkbox'><label for='data-1e051798-2ec3-419e-ab6a-e94a8f4e5210' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
-       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a74a1ac-6c9e-4dc5-8659-bd42963eb6b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' class='xr-var-data-in' type='checkbox'><label for='data-b41395d2-c227-4a38-bc3e-059bd72e0eff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
-       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3634bf42-fa8d-4416-9bd0-eeae2c1080d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-709d9ff4-18f2-46eb-9891-e99e3515254a' class='xr-var-data-in' type='checkbox'><label for='data-709d9ff4-18f2-46eb-9891-e99e3515254a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-14d0cfaa-9749-4191-88ec-374084a85065' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14d0cfaa-9749-4191-88ec-374084a85065' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a555a503-503d-48a8-951c-1f579f65f422' class='xr-var-data-in' type='checkbox'><label for='data-a555a503-503d-48a8-951c-1f579f65f422' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7970ab73-5492-402d-ada1-a489c692e7c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' class='xr-var-data-in' type='checkbox'><label for='data-4986adbc-c936-46ca-b9dd-3ef6771856fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74d492bb-bf4b-4369-b5ab-e5d4856cff57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52fbb06a-63bb-4af9-9273-a0da085733b0' class='xr-var-data-in' type='checkbox'><label for='data-52fbb06a-63bb-4af9-9273-a0da085733b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74be6496-44d8-40e4-b273-fe94d88c0c39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-645f875e-cc4c-4258-95df-c4fd81552ab3' class='xr-var-data-in' type='checkbox'><label for='data-645f875e-cc4c-4258-95df-c4fd81552ab3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f36faab1-9608-4c12-89a0-51aafea4a570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-329ac06e-93ef-44f5-a152-855c5435d2c2' class='xr-var-data-in' type='checkbox'><label for='data-329ac06e-93ef-44f5-a152-855c5435d2c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9cd701e6-70ab-4a9f-85d5-6344b4619f77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' class='xr-var-data-in' type='checkbox'><label for='data-1d2d86cd-245d-4191-b656-7129ac6d2cbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-deec74e4-29fb-42bc-ba4c-ff06c00fbb39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4b81604-260d-4a6d-a624-5dcf237a9900' class='xr-var-data-in' type='checkbox'><label for='data-b4b81604-260d-4a6d-a624-5dcf237a9900' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f4904e9-68ed-486e-9567-4f3beeecc02f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4f5a315-63bb-4997-952e-941d5f9daf96' class='xr-var-data-in' type='checkbox'><label for='data-f4f5a315-63bb-4997-952e-941d5f9daf96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b013f1be-9d6e-45da-b71b-5808853395d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d947a1e-70d0-4799-990e-28818e73c395' class='xr-var-data-in' type='checkbox'><label for='data-0d947a1e-70d0-4799-990e-28818e73c395' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-605efc77-57a5-419c-9eea-094559be13cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-605efc77-57a5-419c-9eea-094559be13cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8907418-c9c4-4d7c-b695-924d66a887cb' class='xr-var-data-in' type='checkbox'><label for='data-e8907418-c9c4-4d7c-b695-924d66a887cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e5346e5-1a3a-4fa9-a57f-b87b350ea02b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01ee79d2-a225-4654-a1a0-3a91893606e2' class='xr-var-data-in' type='checkbox'><label for='data-01ee79d2-a225-4654-a1a0-3a91893606e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9247696-c47b-4a5e-b96a-2c356ed58a00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' class='xr-var-data-in' type='checkbox'><label for='data-95d6bde5-01e7-49b7-888c-b8e1f3f70113' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2338d5dc-37d0-441e-b5c7-4e5308538ae0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39cd0982-2040-45a4-8657-b5480a3e716a' class='xr-var-data-in' type='checkbox'><label for='data-39cd0982-2040-45a4-8657-b5480a3e716a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3ac0d0e-ad56-4b94-83b9-3401426b4d40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' class='xr-var-data-in' type='checkbox'><label for='data-64f89669-1e68-4414-a9da-e3f6b49cb5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e49fc1f-279d-415d-9a59-63632374f332' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e49fc1f-279d-415d-9a59-63632374f332' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d06d2472-0b2c-428d-b514-25edb42980cc' class='xr-var-data-in' type='checkbox'><label for='data-d06d2472-0b2c-428d-b514-25edb42980cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-641c7e22-810b-4bea-ae05-3e67bf1864b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' class='xr-var-data-in' type='checkbox'><label for='data-1d8a15f3-9ea6-4e2c-882d-2f7e9dfa7c52' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79801443-b822-4d07-9cd1-abf1342d39c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b397824-3621-4c3e-9d37-80438b40784b' class='xr-var-data-in' type='checkbox'><label for='data-7b397824-3621-4c3e-9d37-80438b40784b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-90335375-4392-4c89-8cae-8b4abf21501b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90335375-4392-4c89-8cae-8b4abf21501b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' class='xr-var-data-in' type='checkbox'><label for='data-c9f636a1-d610-4a23-bf82-0f07b020f1dc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
-       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e82d1e6a-f91d-464b-a437-922ebdd78eb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' class='xr-var-data-in' type='checkbox'><label for='data-9cdbd1b1-c07a-479b-ac7e-122ba4284d2a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88171a2-ee65-4032-8c81-a65e31c3ec46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57712bcf-48f1-44cf-a77a-76a5740c054d' class='xr-var-data-in' type='checkbox'><label for='data-57712bcf-48f1-44cf-a77a-76a5740c054d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ec6422d-47b1-489d-9416-ae45d513e97a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-81b52fbb-170a-4baa-9092-8a5cfef4fcfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81b52fbb-170a-4baa-9092-8a5cfef4fcfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c60e6569-0f52-4e97-a61a-b4479533e747' class='xr-var-data-in' type='checkbox'><label for='data-c60e6569-0f52-4e97-a61a-b4479533e747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33a9c5fd-5221-43ab-b83c-bdf91e5129c0' class='xr-section-summary-in' type='checkbox' /><label for='section-33a9c5fd-5221-43ab-b83c-bdf91e5129c0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-8775f1e5-6764-4a2c-a2be-ede40dcacec9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8775f1e5-6764-4a2c-a2be-ede40dcacec9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0d21760-d200-4e6c-910c-3bd4d19b572d' class='xr-var-data-in' type='checkbox'><label for='data-f0d21760-d200-4e6c-910c-3bd4d19b572d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e7d04f5-d77f-4d73-8f07-58e667960c60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e7d04f5-d77f-4d73-8f07-58e667960c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e7f9245-998d-4b0d-8911-c24427fbb23c' class='xr-var-data-in' type='checkbox'><label for='data-8e7f9245-998d-4b0d-8911-c24427fbb23c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-1c2afac4-dfbd-4d22-aad3-5a1f83a58378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c2afac4-dfbd-4d22-aad3-5a1f83a58378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1125222-f66e-47fe-9c71-1c855e4e80b3' class='xr-var-data-in' type='checkbox'><label for='data-e1125222-f66e-47fe-9c71-1c855e4e80b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-4b6401f6-a55b-4cc2-974a-3c0691f993f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b6401f6-a55b-4cc2-974a-3c0691f993f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40e23467-bec8-4c0c-9298-0f1c86a6e2c2' class='xr-var-data-in' type='checkbox'><label for='data-40e23467-bec8-4c0c-9298-0f1c86a6e2c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
+       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-b88ab12b-0696-4cd5-a4c8-240c009e6fe9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b88ab12b-0696-4cd5-a4c8-240c009e6fe9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c4c98e4-9d5e-45f6-ab4e-7b1acf0d216e' class='xr-var-data-in' type='checkbox'><label for='data-0c4c98e4-9d5e-45f6-ab4e-7b1acf0d216e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
+       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-aab60972-d8a4-4bf1-b671-002f56281b34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aab60972-d8a4-4bf1-b671-002f56281b34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e75528c-dd94-4036-a6cc-b062ec8a4389' class='xr-var-data-in' type='checkbox'><label for='data-5e75528c-dd94-4036-a6cc-b062ec8a4389' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-2739c187-5e7e-45cf-8dde-59a1fb52757a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2739c187-5e7e-45cf-8dde-59a1fb52757a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6310886e-e5fd-4fe0-a022-a40975b64c3b' class='xr-var-data-in' type='checkbox'><label for='data-6310886e-e5fd-4fe0-a022-a40975b64c3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e9bea373-f3e8-4e7d-9bd8-0427354b4387' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9bea373-f3e8-4e7d-9bd8-0427354b4387' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0de39ed-7d23-4bc0-a8fb-ea5fc10591b6' class='xr-var-data-in' type='checkbox'><label for='data-d0de39ed-7d23-4bc0-a8fb-ea5fc10591b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e16553d1-65d7-49e9-b14c-6c51db0c5c32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e16553d1-65d7-49e9-b14c-6c51db0c5c32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cddbbe7d-323e-47ce-aabe-e9843283ecd0' class='xr-var-data-in' type='checkbox'><label for='data-cddbbe7d-323e-47ce-aabe-e9843283ecd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-165e4135-df6a-4523-8b98-85c2a3bdf47c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-165e4135-df6a-4523-8b98-85c2a3bdf47c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-325b4124-02a4-4e15-9fc7-81f2b0ed1454' class='xr-var-data-in' type='checkbox'><label for='data-325b4124-02a4-4e15-9fc7-81f2b0ed1454' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-bd0fa28d-40f3-4d3a-aff2-b137c1e016c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd0fa28d-40f3-4d3a-aff2-b137c1e016c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc6b645b-b60d-481d-a089-8d40d4c8ec75' class='xr-var-data-in' type='checkbox'><label for='data-fc6b645b-b60d-481d-a089-8d40d4c8ec75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-6612ae11-9794-4d77-8619-1866add3734e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6612ae11-9794-4d77-8619-1866add3734e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27f19950-2773-472a-b925-46a8becdf000' class='xr-var-data-in' type='checkbox'><label for='data-27f19950-2773-472a-b925-46a8becdf000' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-59363ca5-f2a6-443f-80e1-b5daeff5e707' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59363ca5-f2a6-443f-80e1-b5daeff5e707' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9740d8f5-7035-45c5-8b5a-c4ffbd71ba43' class='xr-var-data-in' type='checkbox'><label for='data-9740d8f5-7035-45c5-8b5a-c4ffbd71ba43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2e78be18-6cce-4478-a0a1-3af6ceee3bb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e78be18-6cce-4478-a0a1-3af6ceee3bb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06e0ab36-64fc-444d-afe9-630ec6b3c302' class='xr-var-data-in' type='checkbox'><label for='data-06e0ab36-64fc-444d-afe9-630ec6b3c302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2c81913c-dc05-47ea-9081-95512df9aa0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c81913c-dc05-47ea-9081-95512df9aa0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-376cf13c-28e6-4307-ab2f-e63284d50285' class='xr-var-data-in' type='checkbox'><label for='data-376cf13c-28e6-4307-ab2f-e63284d50285' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-7e7b9dcb-f0eb-4720-aca0-151811d10244' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e7b9dcb-f0eb-4720-aca0-151811d10244' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8941085f-690b-41f3-b02c-3764251fc565' class='xr-var-data-in' type='checkbox'><label for='data-8941085f-690b-41f3-b02c-3764251fc565' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-c2d0f870-699a-4ceb-a80f-7b2495c8bd92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2d0f870-699a-4ceb-a80f-7b2495c8bd92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-347b8132-04b8-481c-8469-5223c3b240c1' class='xr-var-data-in' type='checkbox'><label for='data-347b8132-04b8-481c-8469-5223c3b240c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-0614355f-bfc5-41d2-907a-9d4ac614464f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0614355f-bfc5-41d2-907a-9d4ac614464f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35b67c62-141f-45b6-8c66-d0ec2e74a3b1' class='xr-var-data-in' type='checkbox'><label for='data-35b67c62-141f-45b6-8c66-d0ec2e74a3b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e483728-207b-4ada-a689-35a2cd83ec08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e483728-207b-4ada-a689-35a2cd83ec08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c406df33-fdf2-4927-83cd-ef965adabb4c' class='xr-var-data-in' type='checkbox'><label for='data-c406df33-fdf2-4927-83cd-ef965adabb4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-6eb4e23f-eb86-433e-8c96-5a0dc5a894c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6eb4e23f-eb86-433e-8c96-5a0dc5a894c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-004b8d22-48a0-4ffb-be46-1ef386bfde51' class='xr-var-data-in' type='checkbox'><label for='data-004b8d22-48a0-4ffb-be46-1ef386bfde51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-3c9b1c25-c098-4381-b137-abe97ff8551c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c9b1c25-c098-4381-b137-abe97ff8551c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2270a9a9-8d6d-4232-adca-ffeb7740c605' class='xr-var-data-in' type='checkbox'><label for='data-2270a9a9-8d6d-4232-adca-ffeb7740c605' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-0c64e889-285f-4cbc-86a3-a8c4ad828848' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c64e889-285f-4cbc-86a3-a8c4ad828848' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-102db525-a351-4d83-b000-ce41273650ae' class='xr-var-data-in' type='checkbox'><label for='data-102db525-a351-4d83-b000-ce41273650ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-f22ce601-1ab8-4849-8866-42a794f85b82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f22ce601-1ab8-4849-8866-42a794f85b82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c61cf7c7-ea5d-4d8d-9688-a4b5786577e3' class='xr-var-data-in' type='checkbox'><label for='data-c61cf7c7-ea5d-4d8d-9688-a4b5786577e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-c29d3bf6-1072-4093-aa38-d5875c6dd693' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c29d3bf6-1072-4093-aa38-d5875c6dd693' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15bdc6bf-066c-43fc-8cc3-59bc089ee110' class='xr-var-data-in' type='checkbox'><label for='data-15bdc6bf-066c-43fc-8cc3-59bc089ee110' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
+       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-ffd2e270-0fb6-466a-9f87-da47a7123117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffd2e270-0fb6-466a-9f87-da47a7123117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-869e85ac-af60-4ca1-a7ff-e53b90bd6a42' class='xr-var-data-in' type='checkbox'><label for='data-869e85ac-af60-4ca1-a7ff-e53b90bd6a42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-12bd1958-c27f-4f23-ad96-7c7a05433677' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12bd1958-c27f-4f23-ad96-7c7a05433677' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30e91e24-380f-486c-a4b7-0f668ce54303' class='xr-var-data-in' type='checkbox'><label for='data-30e91e24-380f-486c-a4b7-0f668ce54303' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3f725047-b4e1-4931-84a7-b4d254c5a7fd' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3f725047-b4e1-4931-84a7-b4d254c5a7fd' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_1a400e45d3a521f96c766391090c4e66\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_5e5f256a0eb846f1ee15ba21cda6cda0\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_5e5f256a0eb846f1ee15ba21cda6cda0\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -2396,22 +2399,22 @@
        "Data variables:\n",
        "    NMEA_datagram  (nmea_time) &lt;U26 453kB &#x27;$SDVLW,630.103,N,630.103,N&#x27; ... &#x27;$...\n",
        "Attributes:\n",
-       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-21064d1c-c0b2-47c0-8205-0656cda6567e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ce6b6754-745c-4026-9b9b-169502c921ca' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbdeb0e9-679b-4998-8f1a-4783c7536f1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' class='xr-var-data-in' type='checkbox'><label for='data-0443f899-5cc1-4c17-8e07-1f6f0ebb1888' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
+       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ab03e6bf-faae-46c5-ba95-3ef00a6dfab1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ab03e6bf-faae-46c5-ba95-3ef00a6dfab1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-f99d42eb-3dea-4847-a867-4a8a900a6be4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f99d42eb-3dea-4847-a867-4a8a900a6be4' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-c0801019-3c4d-47fc-b302-09ac340a83d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0801019-3c4d-47fc-b302-09ac340a83d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-481820d9-84ef-4caf-91b6-cbe56ee2acf8' class='xr-var-data-in' type='checkbox'><label for='data-481820d9-84ef-4caf-91b6-cbe56ee2acf8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:32.825344000&#x27;, ..., &#x27;2021-12-15T14:40:09.311146000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.381834000&#x27;, &#x27;2021-12-15T14:40:09.456507000&#x27;],\n",
-       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a5b178f-5733-4b21-917e-e64454eec1bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' class='xr-var-data-in' type='checkbox'><label for='data-d6a7a7c7-f95d-4519-829e-f634f8ef1340' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-10b6daac-14bd-4f00-88ab-da21153bfadc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10b6daac-14bd-4f00-88ab-da21153bfadc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a52a84d1-5610-4eee-82f0-4a260bbf5100' class='xr-var-data-in' type='checkbox'><label for='data-a52a84d1-5610-4eee-82f0-4a260bbf5100' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0694e2a3-ca9a-4949-b54e-042a9dbe4bd8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b098e67-f7cc-4575-bee6-8012f6813583' class='xr-var-data-in' type='checkbox'><label for='data-7b098e67-f7cc-4575-bee6-8012f6813583' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-6d40e0da-897e-4236-b098-9b81ad544362' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d40e0da-897e-4236-b098-9b81ad544362' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' class='xr-var-data-in' type='checkbox'><label for='data-4e36fa7b-34b9-4426-90a1-25f80be87da4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-30b02f71-b952-4b15-bf79-6845be0db4cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30b02f71-b952-4b15-bf79-6845be0db4cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f49f2b15-2400-48eb-84c2-de80d60c5fab' class='xr-var-data-in' type='checkbox'><label for='data-f49f2b15-2400-48eb-84c2-de80d60c5fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a834bbb8-db8d-40f7-85a3-3b46312f5d10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a834bbb8-db8d-40f7-85a3-3b46312f5d10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7766e6c4-0280-41f7-b3cb-cf0249691ca1' class='xr-var-data-in' type='checkbox'><label for='data-7766e6c4-0280-41f7-b3cb-cf0249691ca1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eaa415c-8a1a-49e7-a20f-8fa996d9f9ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' class='xr-var-data-in' type='checkbox'><label for='data-d4e2fe83-d38f-4774-a6ed-b9cfcb0c5d49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-95bacdf8-9390-444f-a6b1-15e87f637dd9' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3a4a630-da14-40c5-b6b1-9ffb89d9ec65' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' class='xr-var-data-in' type='checkbox'><label for='data-9c42b128-1887-4dc4-b7e3-c8156ecb0a7b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-461a7d0a-71a2-4e4e-9529-2b6c857075ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-461a7d0a-71a2-4e4e-9529-2b6c857075ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e1a5768-0f3d-46e5-963d-51f4391cd0b3' class='xr-var-data-in' type='checkbox'><label for='data-3e1a5768-0f3d-46e5-963d-51f4391cd0b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-810f2fca-e83a-4758-b95d-fdd09b2628e4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-810f2fca-e83a-4758-b95d-fdd09b2628e4' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-dd846d3f-f26c-43c4-b2a8-94d49e915363' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd846d3f-f26c-43c4-b2a8-94d49e915363' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc831e00-52ea-4a33-8c82-f0c75fa9401f' class='xr-var-data-in' type='checkbox'><label for='data-cc831e00-52ea-4a33-8c82-f0c75fa9401f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
        "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, ..., &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
        "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;],\n",
-       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c31112ec-d09d-45be-8b19-6766f9081a5b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c0ad2bf-cc41-4dc2-9a01-a96fc8439802' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c0ad2bf-cc41-4dc2-9a01-a96fc8439802' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_956eabeb080a127ac1af6b385a14f04b\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_fc759f4bd03ec0b9edadc04249f655fb\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_fc759f4bd03ec0b9edadc04249f655fb\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -2965,13 +2968,13 @@
        "    source_filenames  (filenames) &lt;U67 268B &#x27;example_data\\\\ts_spectrum_exampl...\n",
        "Attributes:\n",
        "    conversion_software_name:     echopype\n",
-       "    conversion_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    conversion_time:              2026-06-07T01:36:12+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5ad0bb37-3d56-4aab-b871-ddede107583a' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-668d1b4a-d4c3-4f9e-a0f0-ac4670851ee1' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88036a8b-2445-4ef5-8c74-1cbda392d43a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' class='xr-var-data-in' type='checkbox'><label for='data-60e7ac67-f359-45ce-a620-90b9a8b2fbef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary-in' type='checkbox' checked /><label for='section-65503e90-bdd6-4eec-adc8-620911b97a54' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d163a7ce-e2fb-4e31-a9c4-e5129d0bb563' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' class='xr-var-data-in' type='checkbox'><label for='data-6d2f304d-8314-4223-a259-e8ea2e9a1cb3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary-in' type='checkbox' checked /><label for='section-615a5430-4989-4d61-93f1-d61e3842fcdb' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>conversion_time :</span></dt><dd>2026-06-07T01:36:12+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
+       "    conversion_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    conversion_time:              2026-06-19T22:27:36+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9546de2f-55f2-404a-a0c6-b6ba488f8985' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-9546de2f-55f2-404a-a0c6-b6ba488f8985' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-c5bacf51-03c5-413a-a76c-3903929eaee1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c5bacf51-03c5-413a-a76c-3903929eaee1' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bd5f06a2-1625-4ecb-8349-8630c6cd991f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd5f06a2-1625-4ecb-8349-8630c6cd991f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1302b8e3-8e13-4cab-9270-f9f7abad1f19' class='xr-var-data-in' type='checkbox'><label for='data-1302b8e3-8e13-4cab-9270-f9f7abad1f19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ed6b1d9-399c-4aa7-8d18-62e9998cb277' class='xr-section-summary-in' type='checkbox' checked /><label for='section-5ed6b1d9-399c-4aa7-8d18-62e9998cb277' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a0e813e3-fba7-49cf-b2ba-bea993f9eee7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0e813e3-fba7-49cf-b2ba-bea993f9eee7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-313f3b69-032b-42fa-99e8-9c6fce2c735d' class='xr-var-data-in' type='checkbox'><label for='data-313f3b69-032b-42fa-99e8-9c6fce2c735d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9df7e6c1-c36e-485a-81bd-bc414239ddef' class='xr-section-summary-in' type='checkbox' checked /><label for='section-9df7e6c1-c36e-485a-81bd-bc414239ddef' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>conversion_time :</span></dt><dd>2026-06-19T22:27:36+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><li class=\"xr-section-list\"><input id=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_7f39d7f922d1289ec21fcfe0b1d5b653\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_e017acaf583ff66d9b16ff6d413232ed\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_e017acaf583ff66d9b16ff6d413232ed\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -3537,14 +3540,14 @@
        "    sonar_serial_number:     \n",
        "    sonar_software_name:     \n",
        "    sonar_software_version:  21.15.0.0\n",
-       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-e0480e99-c9bf-4be0-9e1c-44a7ca9040fc' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary-in' type='checkbox' checked /><label for='section-494288fe-1c03-487d-afd9-50b617a83e95' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e6c1b00-2d5d-405c-917b-f6dea2924b73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' class='xr-var-data-in' type='checkbox'><label for='data-679ceae2-b3c1-4dc3-bf93-b7f07e134b36' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f32c58cd-f9bc-4c58-aac0-0f96591d1c8c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f32c58cd-f9bc-4c58-aac0-0f96591d1c8c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-32e60346-0fbc-4c0b-8ad6-e867a8692c81' class='xr-section-summary-in' type='checkbox' checked /><label for='section-32e60346-0fbc-4c0b-8ad6-e867a8692c81' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-0b08d36a-55da-4707-bcc9-f9c5788a1a0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b08d36a-55da-4707-bcc9-f9c5788a1a0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f535f44c-5df8-4aa4-b164-69abdefc4955' class='xr-var-data-in' type='checkbox'><label for='data-f535f44c-5df8-4aa4-b164-69abdefc4955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7170963-513f-46dc-a5a2-c32a4253809a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-352c90ce-63d6-43dd-a379-4ef29c737f93' class='xr-var-data-in' type='checkbox'><label for='data-352c90ce-63d6-43dd-a379-4ef29c737f93' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58cd6f07-9fa8-4578-ad3b-040897a44a5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104fae87-c879-4dac-ad2e-76793d4133fe' class='xr-var-data-in' type='checkbox'><label for='data-104fae87-c879-4dac-ad2e-76793d4133fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary-in' type='checkbox' checked /><label for='section-93385609-52f0-4ac2-a4ce-f359b3660800' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfbab478-8c30-4e67-bdb3-062a62940470' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' class='xr-var-data-in' type='checkbox'><label for='data-021a94d2-55f0-4eb0-a99f-0a7271d6f055' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35a279f8-5dd0-42ed-9696-d2620aaaea89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-227846be-941f-4c58-bbae-d7165c294b5e' class='xr-var-data-in' type='checkbox'><label for='data-227846be-941f-4c58-bbae-d7165c294b5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b6cf28-7af9-40ec-9c01-1ab04e01b15f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' class='xr-var-data-in' type='checkbox'><label for='data-b4062ed2-cb5e-4ea6-bd2d-181cb561e645' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-2604b084-77b2-4b4c-be79-1dc555332999' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2604b084-77b2-4b4c-be79-1dc555332999' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc285f4-b477-42d1-b12e-5aed80267bcf' class='xr-var-data-in' type='checkbox'><label for='data-adc285f4-b477-42d1-b12e-5aed80267bcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-62cbbccd-7d20-4a4c-a950-6dcbbd8d3d66' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' class='xr-var-data-in' type='checkbox'><label for='data-75b13415-223a-40d5-a0a5-67b6e55eb1a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
-       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-bcecb8bb-c4c6-419f-b176-284128395853' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bcecb8bb-c4c6-419f-b176-284128395853' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' class='xr-var-data-in' type='checkbox'><label for='data-1a34aafc-bbfe-4569-bb05-36e744b9a378' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-b2871098-d7f0-4c6c-8041-c90bc429262f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-3b3e89bb-cdc0-4261-b23c-63602e77ab22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b3e89bb-cdc0-4261-b23c-63602e77ab22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5235f98-8767-4fcc-b87b-d240bcaded9b' class='xr-var-data-in' type='checkbox'><label for='data-c5235f98-8767-4fcc-b87b-d240bcaded9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-61d64ba3-b092-4f3f-b085-657a4359d686' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61d64ba3-b092-4f3f-b085-657a4359d686' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef7f185c-2774-4e34-b61a-cb732db98d07' class='xr-var-data-in' type='checkbox'><label for='data-ef7f185c-2774-4e34-b61a-cb732db98d07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63d7f800-a37a-46be-8543-e4c938fd5632' class='xr-section-summary-in' type='checkbox' checked /><label for='section-63d7f800-a37a-46be-8543-e4c938fd5632' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-11b87fec-11bc-44a8-ac7c-e73938eb5767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b87fec-11bc-44a8-ac7c-e73938eb5767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9897c83-f0e2-42c4-a451-c99676830371' class='xr-var-data-in' type='checkbox'><label for='data-d9897c83-f0e2-42c4-a451-c99676830371' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-3134e8af-9855-4bf7-8813-b6ba9e17245b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3134e8af-9855-4bf7-8813-b6ba9e17245b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a3f02e-c9a4-4e96-bb12-fd16b46c08a7' class='xr-var-data-in' type='checkbox'><label for='data-a3a3f02e-c9a4-4e96-bb12-fd16b46c08a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-ce5e816d-efa3-45d7-8432-db74bc9538a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce5e816d-efa3-45d7-8432-db74bc9538a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-554f01a1-37f0-4117-8138-2cb448febaf5' class='xr-var-data-in' type='checkbox'><label for='data-554f01a1-37f0-4117-8138-2cb448febaf5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-c1d22575-a630-4f4a-b7d1-f64e64e68919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1d22575-a630-4f4a-b7d1-f64e64e68919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c524d8-de22-493e-a8f4-809dc4e2a1f4' class='xr-var-data-in' type='checkbox'><label for='data-f4c524d8-de22-493e-a8f4-809dc4e2a1f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-5f06b944-39f6-422e-9b7d-bed0b9d3d7f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f06b944-39f6-422e-9b7d-bed0b9d3d7f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18620fa5-a1b5-4299-9ac7-f82d5ea3b04f' class='xr-var-data-in' type='checkbox'><label for='data-18620fa5-a1b5-4299-9ac7-f82d5ea3b04f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
+       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-a497ce38-e366-482a-8d14-299df70668c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a497ce38-e366-482a-8d14-299df70668c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-655855a2-e416-4822-a981-20b916093e90' class='xr-var-data-in' type='checkbox'><label for='data-655855a2-e416-4822-a981-20b916093e90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95f4aeb2-d411-4c72-b3c7-81dad442297f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-95f4aeb2-d411-4c72-b3c7-81dad442297f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_1607356be07eee7c14e2943bf9eb8628\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_9a571ee6078d0483d2474ada8d6dca21\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_9a571ee6078d0483d2474ada8d6dca21\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -4119,14 +4122,14 @@
        "    transmit_frequency_stop        (channel, ping_time) float64 41kB 3.8e+05 ...\n",
        "Attributes:\n",
        "    beam_mode:              vertical\n",
-       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5d4dd126-e08e-40e2-b782-eb08a7306160' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4befea52-c64c-4194-bff6-c625a3a14572' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dce97ba4-35ed-46c3-9af4-2b7ff153908f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' class='xr-var-data-in' type='checkbox'><label for='data-4d6e7b09-1458-40f3-a768-c4f6bbd6e33f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-16714ab7-ba53-4d02-b47d-3c21c2edf560' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-16714ab7-ba53-4d02-b47d-3c21c2edf560' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ebabef8e-4c98-4cd1-8580-818e6b716b05' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ebabef8e-4c98-4cd1-8580-818e6b716b05' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-b0b40441-8944-4af1-9461-eed9f9ee2bf4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0b40441-8944-4af1-9461-eed9f9ee2bf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5011029b-0a5d-4563-8e4e-4a46e66d8e02' class='xr-var-data-in' type='checkbox'><label for='data-5011029b-0a5d-4563-8e4e-4a46e66d8e02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a39b8eba-3366-4b9e-8e2f-096e770f17d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e77e00ec-8265-406d-a839-6096b403b5e6' class='xr-var-data-in' type='checkbox'><label for='data-e77e00ec-8265-406d-a839-6096b403b5e6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-4c2c1968-4398-4031-91ae-26b55100c8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c2c1968-4398-4031-91ae-26b55100c8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c50ef79-050a-4572-9255-432b12bf6992' class='xr-var-data-in' type='checkbox'><label for='data-8c50ef79-050a-4572-9255-432b12bf6992' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0efc1553-2bbe-4e44-938d-5a4d8dc2a6f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' class='xr-var-data-in' type='checkbox'><label for='data-e76bbc89-37c1-4cd3-a3c5-bb0622065734' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4dec811f-74a9-40f6-a725-6f6f94bb8cf1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' class='xr-var-data-in' type='checkbox'><label for='data-1d9df0e8-3f29-484e-9cc1-c47773e5f80f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4f24ba7c-c805-441d-ba5a-2f41034c0c01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' class='xr-var-data-in' type='checkbox'><label for='data-b38ef3e4-0a00-453d-90e3-e8704b04f456' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-ca952524-e9c6-407d-b5ec-1748765cd236' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca952524-e9c6-407d-b5ec-1748765cd236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b0534b-57a3-4c1f-bee8-6edbe2d19c10' class='xr-var-data-in' type='checkbox'><label for='data-d1b0534b-57a3-4c1f-bee8-6edbe2d19c10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-6dce6893-b8dc-48de-8ac7-3bbe7428f7fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dce6893-b8dc-48de-8ac7-3bbe7428f7fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b93c522-dec1-44c8-8bbc-88dd61503a73' class='xr-var-data-in' type='checkbox'><label for='data-0b93c522-dec1-44c8-8bbc-88dd61503a73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-1b21242c-b9b2-48fc-bcad-975040559ddd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b21242c-b9b2-48fc-bcad-975040559ddd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e292630a-11e9-4a81-ba38-4321b228c2cb' class='xr-var-data-in' type='checkbox'><label for='data-e292630a-11e9-4a81-ba38-4321b228c2cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a03908d-d503-4340-b95a-d9022dfe2b46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' class='xr-var-data-in' type='checkbox'><label for='data-9f9fe727-1642-4b39-adb9-58b48a3369ff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5eb8cfbe-7545-4285-944b-28adf2dcbfad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05f7eebb-f987-41bc-b281-9a73bb52e909' class='xr-var-data-in' type='checkbox'><label for='data-05f7eebb-f987-41bc-b281-9a73bb52e909' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary-in' type='checkbox' /><label for='section-fd1765b9-5094-4fd2-8124-ead345df0614' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56463e2f-77a7-4513-8c33-3451a3fdc188' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b1189cc-612f-48b0-b19b-9bd38a116135' class='xr-var-data-in' type='checkbox'><label for='data-2b1189cc-612f-48b0-b19b-9bd38a116135' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e85df5c6-6720-42a4-b13d-41c1c722c906' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' class='xr-var-data-in' type='checkbox'><label for='data-b99646d6-b0ba-4c81-97be-3ce5e0b0ec3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ba132a4-9ea3-4af1-9f7d-6a1a94353bdb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' class='xr-var-data-in' type='checkbox'><label for='data-a0c0e845-568e-4ee2-b27b-945b1ab00253' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0e52da8-102a-486b-a411-3bf702b0f481' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' class='xr-var-data-in' type='checkbox'><label for='data-e1aa8757-0628-4dea-aebc-d5bbb7639b4b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-e954c18d-521b-4e32-b06c-2928190552b3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e954c18d-521b-4e32-b06c-2928190552b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' class='xr-var-data-in' type='checkbox'><label for='data-918602a8-5032-4ed5-acf1-bd758f43b9a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3af45ef3-1b9a-44ad-961c-e31aef85a655' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04a083cd-dd78-4efe-82aa-fb211490fc15' class='xr-var-data-in' type='checkbox'><label for='data-04a083cd-dd78-4efe-82aa-fb211490fc15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c77eff5-6bf4-49e8-a132-d693da421379' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96279542-2cb0-4f72-ad52-e39977c8ec54' class='xr-var-data-in' type='checkbox'><label for='data-96279542-2cb0-4f72-ad52-e39977c8ec54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-643dc435-159f-4d82-a26f-41ac8a88271a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd542c66-33c7-459d-81c7-d0408424151c' class='xr-var-data-in' type='checkbox'><label for='data-dd542c66-33c7-459d-81c7-d0408424151c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-9582c736-a650-427b-abec-4dae0485bced' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9582c736-a650-427b-abec-4dae0485bced' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d566cb28-7a2a-4669-b722-71588c862d66' class='xr-var-data-in' type='checkbox'><label for='data-d566cb28-7a2a-4669-b722-71588c862d66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e22748fe-a465-45ec-984b-f2405bb27a2e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' class='xr-var-data-in' type='checkbox'><label for='data-d3fb4ae3-f6dc-4ae8-b9b2-dac36679f99c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34247755-2829-4d99-a1b5-b7399d5ded46' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' class='xr-var-data-in' type='checkbox'><label for='data-06a349f9-5cc2-4690-a6f2-20c2a9041eec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a8b7b6c-c96c-487f-b4b8-7421530f83f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' class='xr-var-data-in' type='checkbox'><label for='data-6fa8e84d-e656-4d1d-ae96-2fd767827e4d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f18f95a9-4176-42c9-9094-9902fa31030e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' class='xr-var-data-in' type='checkbox'><label for='data-1516a34f-8f8a-44b0-95f4-b7fcd1b5b47e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4781dc40-d08e-429b-8ce4-4e9e13cadd57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd4e1859-70be-4cef-a044-45355c93fda3' class='xr-var-data-in' type='checkbox'><label for='data-dd4e1859-70be-4cef-a044-45355c93fda3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-25863a44-d6cb-4064-8030-d82e317da970' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25863a44-d6cb-4064-8030-d82e317da970' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' class='xr-var-data-in' type='checkbox'><label for='data-2c26680d-105a-4839-9fd9-a7d0b8f83e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51796ef5-1e36-48c5-9f1b-f8440c37ecd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' class='xr-var-data-in' type='checkbox'><label for='data-c672a5d8-a2d4-41e9-9a5c-6cc4d09431a2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-c09385ec-1a86-43b2-be9b-29c875bd6403' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c09385ec-1a86-43b2-be9b-29c875bd6403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3eb05c5b-a3c0-4495-8a31-366a94ee523d' class='xr-var-data-in' type='checkbox'><label for='data-3eb05c5b-a3c0-4495-8a31-366a94ee523d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-255ebe58-51e9-4b8f-8055-4d5fe8dc2b5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-255ebe58-51e9-4b8f-8055-4d5fe8dc2b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd2411c4-1553-4536-a264-f681a924792c' class='xr-var-data-in' type='checkbox'><label for='data-cd2411c4-1553-4536-a264-f681a924792c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4aa9d58a-96bf-4a5f-a253-59d28593945d' class='xr-section-summary-in' type='checkbox' /><label for='section-4aa9d58a-96bf-4a5f-a253-59d28593945d' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-afc25fc7-dc1e-48e2-8d3c-d3e4b8dc9b4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afc25fc7-dc1e-48e2-8d3c-d3e4b8dc9b4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cef487e9-0c2c-4ffe-a250-9c04fb548852' class='xr-var-data-in' type='checkbox'><label for='data-cef487e9-0c2c-4ffe-a250-9c04fb548852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-0b6f10b1-a048-4f22-82c9-942ed8b42685' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b6f10b1-a048-4f22-82c9-942ed8b42685' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b36fba18-404a-44f5-9395-aa4aa736460f' class='xr-var-data-in' type='checkbox'><label for='data-b36fba18-404a-44f5-9395-aa4aa736460f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-dd4e97fd-ad58-4d8a-b64e-5b07639809ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd4e97fd-ad58-4d8a-b64e-5b07639809ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48286bf6-95fc-4a2f-929c-04bf92ff4752' class='xr-var-data-in' type='checkbox'><label for='data-48286bf6-95fc-4a2f-929c-04bf92ff4752' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-05d831ef-dca1-406c-966e-8ba81b56177f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05d831ef-dca1-406c-966e-8ba81b56177f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bf171d7-6ff4-48e2-a397-781f9eb19e0c' class='xr-var-data-in' type='checkbox'><label for='data-9bf171d7-6ff4-48e2-a397-781f9eb19e0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-01dcfa68-f9db-41c4-bac0-12451ba72060' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01dcfa68-f9db-41c4-bac0-12451ba72060' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7764fa8-f164-48dc-b900-131e50a1f96e' class='xr-var-data-in' type='checkbox'><label for='data-b7764fa8-f164-48dc-b900-131e50a1f96e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-552a0ce0-27df-4170-bde2-7bbec4556796' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-552a0ce0-27df-4170-bde2-7bbec4556796' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44676c09-2634-458e-8bf5-451b79f18ffe' class='xr-var-data-in' type='checkbox'><label for='data-44676c09-2634-458e-8bf5-451b79f18ffe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-d774731a-039b-4fe7-99ea-e0e28fb484e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d774731a-039b-4fe7-99ea-e0e28fb484e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46f6cb9f-2fa8-454c-9612-8cecafafac26' class='xr-var-data-in' type='checkbox'><label for='data-46f6cb9f-2fa8-454c-9612-8cecafafac26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-bc9e1d4a-9f72-4ded-ba47-8992da60736c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc9e1d4a-9f72-4ded-ba47-8992da60736c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1910bb1f-5652-4901-82dd-91cc89de83ee' class='xr-var-data-in' type='checkbox'><label for='data-1910bb1f-5652-4901-82dd-91cc89de83ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-b725c36a-3ae9-4715-8fe0-661983ce53f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b725c36a-3ae9-4715-8fe0-661983ce53f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-928653c2-c0be-4d8a-a4c9-7a99d6c8d7c1' class='xr-var-data-in' type='checkbox'><label for='data-928653c2-c0be-4d8a-a4c9-7a99d6c8d7c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-9c7df37d-dbe2-41f8-9a11-143fe1bc6044' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c7df37d-dbe2-41f8-9a11-143fe1bc6044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1075ba7-9e9d-4965-af68-e0ae7e029f30' class='xr-var-data-in' type='checkbox'><label for='data-b1075ba7-9e9d-4965-af68-e0ae7e029f30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-64b98d40-0a23-4cbe-a24f-736141933a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64b98d40-0a23-4cbe-a24f-736141933a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c91e40-ced9-492b-8fb5-acabf184b539' class='xr-var-data-in' type='checkbox'><label for='data-e0c91e40-ced9-492b-8fb5-acabf184b539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-4eddb006-3879-4367-a6b1-ccde1b8ede68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eddb006-3879-4367-a6b1-ccde1b8ede68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a31b83d-49e4-4f36-99f0-235763b93f57' class='xr-var-data-in' type='checkbox'><label for='data-3a31b83d-49e4-4f36-99f0-235763b93f57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-d98926eb-77fa-4d7e-93e6-c217b5181ca3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d98926eb-77fa-4d7e-93e6-c217b5181ca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27c3cfce-56f9-41c2-811f-da79ccabc5be' class='xr-var-data-in' type='checkbox'><label for='data-27c3cfce-56f9-41c2-811f-da79ccabc5be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bb9b6864-76be-4b53-b6e9-db5d611c2fa4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb9b6864-76be-4b53-b6e9-db5d611c2fa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a60abf6c-285c-4440-b9db-e964db9d5d54' class='xr-var-data-in' type='checkbox'><label for='data-a60abf6c-285c-4440-b9db-e964db9d5d54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-615327d4-3c7c-492f-be87-bc0e9e189b95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-615327d4-3c7c-492f-be87-bc0e9e189b95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa5458aa-e064-4048-b039-3abe70a7c3c8' class='xr-var-data-in' type='checkbox'><label for='data-fa5458aa-e064-4048-b039-3abe70a7c3c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-715cb9eb-a59b-4085-a75d-516002973317' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-715cb9eb-a59b-4085-a75d-516002973317' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8eca4316-c2b4-4eed-856c-e25687f95745' class='xr-var-data-in' type='checkbox'><label for='data-8eca4316-c2b4-4eed-856c-e25687f95745' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
        "          -3.96171856e-07],\n",
        "         [-2.57343663e-06,  2.95345012e-06, -3.57061339e-07,\n",
        "          -4.56580392e-06],\n",
@@ -4166,7 +4169,7 @@
        "         [            nan,             nan,             nan,\n",
        "                      nan],\n",
        "         [            nan,             nan,             nan,\n",
-       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca7523bc-709b-4542-8c02-a12c0f95a8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' class='xr-var-data-in' type='checkbox'><label for='data-313715c9-8a4e-444e-b41f-fb8fca56fca7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-c025c4f4-f6c8-4826-9cc1-d59e6d0cf365' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c025c4f4-f6c8-4826-9cc1-d59e6d0cf365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc38090-9c3f-42ab-96f1-a6bc53679010' class='xr-var-data-in' type='checkbox'><label for='data-2cc38090-9c3f-42ab-96f1-a6bc53679010' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
        "          -3.68357291e-06],\n",
        "         [-6.13030397e-06,  9.28021564e-06,  3.91020649e-06,\n",
        "          -3.28862302e-06],\n",
@@ -4206,51 +4209,51 @@
        "         [            nan,             nan,             nan,\n",
        "                      nan],\n",
        "         [            nan,             nan,             nan,\n",
-       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d2b925a-4a26-47ac-8f4e-9d78d8093e59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' class='xr-var-data-in' type='checkbox'><label for='data-34051ce8-ef3f-4c79-ae36-5bcc4c19d9be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-6178c2ef-451b-440c-8688-8a25c646a3d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6178c2ef-451b-440c-8688-8a25c646a3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72740fc0-3aaf-48c1-a7b0-d079f5653c96' class='xr-var-data-in' type='checkbox'><label for='data-72740fc0-3aaf-48c1-a7b0-d079f5653c96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
        "        5.33333e-06, 5.33333e-06],\n",
        "       [2.13333e-05, 2.13333e-05, 2.13333e-05, ..., 2.13333e-05,\n",
        "        2.13333e-05, 2.13333e-05],\n",
        "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
        "        8.00000e-06, 8.00000e-06],\n",
        "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
-       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5a1f9c2-f4ed-43cb-b7bc-32b110d86335' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab004848-afa7-47ea-950d-1cb5a677ed97' class='xr-var-data-in' type='checkbox'><label for='data-ab004848-afa7-47ea-950d-1cb5a677ed97' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
+       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-b7fdba7f-23be-4648-b553-42e598f715e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7fdba7f-23be-4648-b553-42e598f715e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeeb6885-9efe-430a-9329-532f044efa1e' class='xr-var-data-in' type='checkbox'><label for='data-eeeb6885-9efe-430a-9329-532f044efa1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
        "       [ 75.,  75.,  75., ...,  75.,  75.,  75.],\n",
        "       [105., 105., 105., ..., 105., 105., 105.],\n",
-       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eb16713b-6f43-41d4-bd6c-7709a104e783' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' class='xr-var-data-in' type='checkbox'><label for='data-0f5886d2-a0cc-4f01-a9c8-353814ece35c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-236b0567-0a28-480e-a8f0-723712932f11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-236b0567-0a28-480e-a8f0-723712932f11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5b5bd45-e011-481f-ab92-8b8f27b8a21e' class='xr-var-data-in' type='checkbox'><label for='data-a5b5bd45-e011-481f-ab92-8b8f27b8a21e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048,      nan]],\n",
-       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0977072-a97f-45aa-a621-7c91d68348e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' class='xr-var-data-in' type='checkbox'><label for='data-f0d4d793-85d3-405e-9e8b-f0d71c2f6ce7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-949453f7-db3a-4117-9a9e-bbc155f2f233' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-949453f7-db3a-4117-9a9e-bbc155f2f233' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-902d3b41-5add-4933-b56f-d202ce4fe42b' class='xr-var-data-in' type='checkbox'><label for='data-902d3b41-5add-4933-b56f-d202ce4fe42b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
        "        0.00348772],\n",
        "       [0.0177557 , 0.0177557 , 0.0177557 , ..., 0.0177557 , 0.0177557 ,\n",
        "        0.0177557 ],\n",
        "       [0.00574449, 0.00574449, 0.00574449, ..., 0.00574449, 0.00574449,\n",
        "        0.00574449],\n",
        "       [0.0108507 , 0.0108507 , 0.0108507 , ..., 0.0108507 , 0.0108507 ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6d6359eb-49bb-4dbd-b779-071b8bc7e193' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9d1a713-b657-40cf-8fff-dd38458070b3' class='xr-var-data-in' type='checkbox'><label for='data-c9d1a713-b657-40cf-8fff-dd38458070b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-23e02e02-8fb0-44b1-970e-21d8c9728dd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23e02e02-8fb0-44b1-970e-21d8c9728dd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6bea46b-c214-4570-a876-8032fea17bfb' class='xr-var-data-in' type='checkbox'><label for='data-b6bea46b-c214-4570-a876-8032fea17bfb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0., nan]],\n",
-       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b1485c8-7789-4d79-b1dd-882aa280e4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6221d42c-73ef-46de-990b-4eda4842b355' class='xr-var-data-in' type='checkbox'><label for='data-6221d42c-73ef-46de-990b-4eda4842b355' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-0127ac16-311b-46e8-a35f-205acfde11f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0127ac16-311b-46e8-a35f-205acfde11f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94e4f8a1-6c39-4e41-946d-886ec245d0cc' class='xr-var-data-in' type='checkbox'><label for='data-94e4f8a1-6c39-4e41-946d-886ec245d0cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, nan]],\n",
-       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9afc46c0-d2aa-4dbd-b4d7-50643b22ec57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' class='xr-var-data-in' type='checkbox'><label for='data-b9c477e6-df9e-4324-a2cb-becda37bdea5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-e763f1ea-9bcb-4e4b-bf1e-628915d6a3e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e763f1ea-9bcb-4e4b-bf1e-628915d6a3e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcf3b356-f0d1-483d-a151-c53bf17adf2d' class='xr-var-data-in' type='checkbox'><label for='data-bcf3b356-f0d1-483d-a151-c53bf17adf2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb246e51-cfa3-42e6-bbd8-30e7b8dd6e69' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-870a77e3-35de-4cca-a848-920508fffb09' class='xr-var-data-in' type='checkbox'><label for='data-870a77e3-35de-4cca-a848-920508fffb09' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-98dabb34-7c53-4c84-ba28-1297db46fffe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98dabb34-7c53-4c84-ba28-1297db46fffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b20cce3e-885c-4883-bfb0-bdf748ddbaf9' class='xr-var-data-in' type='checkbox'><label for='data-b20cce3e-885c-4883-bfb0-bdf748ddbaf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
        "       [ 55000.,  55000.,  55000., ...,  55000.,  55000.,  55000.],\n",
        "       [170000., 170000., 170000., ..., 170000., 170000., 170000.],\n",
        "       [ 90000.,  90000.,  90000., ...,  90000.,  90000.,     nan]],\n",
-       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-687834aa-6953-4d69-b46a-20190955a6fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-687834aa-6953-4d69-b46a-20190955a6fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3520b899-5011-498a-90ec-4b0076a11867' class='xr-var-data-in' type='checkbox'><label for='data-3520b899-5011-498a-90ec-4b0076a11867' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
+       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-4e2fe97a-1a9f-422f-a48c-dac9a55c15f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e2fe97a-1a9f-422f-a48c-dac9a55c15f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e3ca00e-fe6e-4a85-b396-08ba46158eac' class='xr-var-data-in' type='checkbox'><label for='data-3e3ca00e-fe6e-4a85-b396-08ba46158eac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
        "       [ 85000.,  85000.,  85000., ...,  85000.,  85000.,  85000.],\n",
        "       [260000., 260000., 260000., ..., 260000., 260000., 260000.],\n",
        "       [170000., 170000., 170000., ..., 170000., 170000.,     nan]],\n",
-       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-275c3392-d5b9-4d6e-b84f-355df05d8d0b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-345b838f-4987-45fa-9896-18a65fed9b11' class='xr-section-summary-in' type='checkbox' checked /><label for='section-345b838f-4987-45fa-9896-18a65fed9b11' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_1ba576549b354dcfb6672af6f86f374b\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_49ab8b1531c39f631344eb2a600c7231\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_49ab8b1531c39f631344eb2a600c7231\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -4821,41 +4824,41 @@
        "    PC_coeffs_imag               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
        "    WBT_deci_fac                 (channel, filter_time) float64 32B 8.0 ... 12.0\n",
        "    PC_deci_fac                  (channel, filter_time) float64 32B 1.0 ... 1.0\n",
-       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-970b8dc6-88b5-493b-937b-7ee2f4ea9d09' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary-in' type='checkbox' checked /><label for='section-edb1c6b2-5883-4e0e-b25c-5deb300fe4ab' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c03e1641-1515-48a3-ae26-883a7df7f083' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' class='xr-var-data-in' type='checkbox'><label for='data-5b1a4533-63ec-44b6-af6f-fa688eeee0fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8ab69df9-bb30-432f-8f7c-f7f81e82300e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-8ab69df9-bb30-432f-8f7c-f7f81e82300e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-1d94f0e1-86ce-47ec-8d0f-6f4d495bd83a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-1d94f0e1-86ce-47ec-8d0f-6f4d495bd83a' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-d070c3bf-3004-4b87-bb5a-079a694273a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d070c3bf-3004-4b87-bb5a-079a694273a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-089f62cf-7424-4636-b0ff-bb8d026bab24' class='xr-var-data-in' type='checkbox'><label for='data-089f62cf-7424-4636-b0ff-bb8d026bab24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1e6697d1-d4fa-47a0-bcc0-0f7f6090adc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' class='xr-var-data-in' type='checkbox'><label for='data-2fc6fb54-b709-4cd3-8a38-acbad001a55a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4ca82d4-b31f-464a-84f8-3327eeb88ab3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' class='xr-var-data-in' type='checkbox'><label for='data-bb072c88-15e0-48c0-8dac-0afbc5d8ed7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-ce1a612a-5d30-4684-a3ca-5636219ae3f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce1a612a-5d30-4684-a3ca-5636219ae3f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ce67dd6-586f-40a2-9e37-ef445a426acd' class='xr-var-data-in' type='checkbox'><label for='data-2ce67dd6-586f-40a2-9e37-ef445a426acd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-b418f4b3-a962-4b51-a8ed-e256abc0a21d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b418f4b3-a962-4b51-a8ed-e256abc0a21d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00378c0-1f3e-480a-a363-6c6bc4b60e4e' class='xr-var-data-in' type='checkbox'><label for='data-f00378c0-1f3e-480a-a363-6c6bc4b60e4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3e33b5f-ec57-42a6-a039-a4f87d8c9003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' class='xr-var-data-in' type='checkbox'><label for='data-f7c255e2-6fd3-4211-8b11-8acd964a2768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8e4c2aa-396d-463d-9817-1c63e69d699b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' class='xr-var-data-in' type='checkbox'><label for='data-feff9fbf-ee42-4743-9795-8bfaf2fbeedf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary-in' type='checkbox' /><label for='section-f3640aaf-aeb3-491f-acd8-6fcf538190f7' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bf4607e-0db3-4599-969f-e3d6db615630' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1932405b-b524-4150-b2ae-354bba2a7f72' class='xr-var-data-in' type='checkbox'><label for='data-1932405b-b524-4150-b2ae-354bba2a7f72' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd1cb706-d13e-4ebf-8804-0f775cfea268' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d5be396-1656-47d2-8aa3-092776083a76' class='xr-var-data-in' type='checkbox'><label for='data-4d5be396-1656-47d2-8aa3-092776083a76' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-847c8da8-68c5-42ac-9ec4-7601c8330d25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-847c8da8-68c5-42ac-9ec4-7601c8330d25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f068ea1-cacb-48cf-8b57-56a0f3bb3fd0' class='xr-var-data-in' type='checkbox'><label for='data-5f068ea1-cacb-48cf-8b57-56a0f3bb3fd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-43ceadea-e2fb-4b6a-b931-d492a5470f10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43ceadea-e2fb-4b6a-b931-d492a5470f10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-529d6818-cc7f-43de-ab5d-943cd42a8d06' class='xr-var-data-in' type='checkbox'><label for='data-529d6818-cc7f-43de-ab5d-943cd42a8d06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad8c9476-e103-4e79-afac-0ed92872440a' class='xr-section-summary-in' type='checkbox' /><label for='section-ad8c9476-e103-4e79-afac-0ed92872440a' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-8e7cef15-4280-4f58-ab09-602c33c985b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e7cef15-4280-4f58-ab09-602c33c985b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-489503c1-7abf-4a28-bb3d-53474cf70006' class='xr-var-data-in' type='checkbox'><label for='data-489503c1-7abf-4a28-bb3d-53474cf70006' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-1c8d64cb-5a0d-49c3-9e3a-5af8cc5727a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c8d64cb-5a0d-49c3-9e3a-5af8cc5727a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37ef0cca-14c4-4d3d-9a1b-aac3d31ff75a' class='xr-var-data-in' type='checkbox'><label for='data-37ef0cca-14c4-4d3d-9a1b-aac3d31ff75a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
        "       [ 0.  ,  0.  , -0.02,  0.  ,  0.  ],\n",
        "       [ 0.  ,  0.  , -0.26, -0.01,  0.  ],\n",
-       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd929f78-9df3-4133-bad6-21c2224eab85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce4c0b58-57d3-445a-8e65-5015874ef421' class='xr-var-data-in' type='checkbox'><label for='data-ce4c0b58-57d3-445a-8e65-5015874ef421' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
+       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-0f2f6b55-6edc-44c8-9663-94a156641a9e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f2f6b55-6edc-44c8-9663-94a156641a9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba819b80-5e72-4157-a1fe-c5f658b680e9' class='xr-var-data-in' type='checkbox'><label for='data-ba819b80-5e72-4157-a1fe-c5f658b680e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
        "       [27.  , 27.  , 27.59, 27.  , 27.  ],\n",
        "       [26.  , 26.  , 27.48, 27.33, 26.  ],\n",
-       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-78b566e7-f6ac-47d4-bdba-073e84942e1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' class='xr-var-data-in' type='checkbox'><label for='data-40c361ce-a7c2-4911-8749-62c7d1ccb871' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-fddb2038-678b-44d6-9c10-fbb913fd46ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fddb2038-678b-44d6-9c10-fbb913fd46ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15b49629-d0fc-4fe6-953c-7991c3d7e169' class='xr-var-data-in' type='checkbox'><label for='data-15b49629-d0fc-4fe6-953c-7991c3d7e169' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
        "       [1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03, 2.048e-03],\n",
        "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
-       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0ca5d4f5-eab2-4fd3-a440-c34c8e917501' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' class='xr-var-data-in' type='checkbox'><label for='data-f88cde71-1ffe-4a13-b40b-4e3624c37ebd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2bb1f65-7a19-47c8-8e6e-97f045c493c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' class='xr-var-data-in' type='checkbox'><label for='data-a4acfea4-ba18-45c2-96a1-bf09a8f855cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42bcac06-f7ab-41ca-9660-9f567bcc7302' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ce4645-91e7-4328-80da-b1ea318a53b2' class='xr-var-data-in' type='checkbox'><label for='data-66ce4645-91e7-4328-80da-b1ea318a53b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a73f8603-7355-442c-9bad-2387784af5ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a73f8603-7355-442c-9bad-2387784af5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' class='xr-var-data-in' type='checkbox'><label for='data-13afd17a-f26b-48b4-bf29-36c5c55d47c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-42219133-dd54-43ed-9059-60a28591315b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42219133-dd54-43ed-9059-60a28591315b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0273085-0649-46d6-9bb4-5515e8642d26' class='xr-var-data-in' type='checkbox'><label for='data-f0273085-0649-46d6-9bb4-5515e8642d26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-16cfb3d0-f290-4f0d-9d63-54498c498f50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16cfb3d0-f290-4f0d-9d63-54498c498f50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3313fd22-d79d-44e8-92e2-58da427fcc33' class='xr-var-data-in' type='checkbox'><label for='data-3313fd22-d79d-44e8-92e2-58da427fcc33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-89c5cafd-c41c-4f8d-96f5-ee2c3c8efc95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89c5cafd-c41c-4f8d-96f5-ee2c3c8efc95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbb2e3f7-a1c8-4d94-b387-4d33e9d6d711' class='xr-var-data-in' type='checkbox'><label for='data-cbb2e3f7-a1c8-4d94-b387-4d33e9d6d711' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2b4c52c0-fd4e-4212-b505-7a500b49753b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b4c52c0-fd4e-4212-b505-7a500b49753b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c72a8a1-b846-4fc8-aa73-21e8624b863b' class='xr-var-data-in' type='checkbox'><label for='data-4c72a8a1-b846-4fc8-aa73-21e8624b863b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
        "       [20.59, 22.95, 24.07, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cdf8b07b-cd76-4860-a2eb-9019fdb89f05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69226643-e8d9-4acc-95b9-dc840619444b' class='xr-var-data-in' type='checkbox'><label for='data-69226643-e8d9-4acc-95b9-dc840619444b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0eb10fb3-7046-4acc-b19d-46db91fc079c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eb10fb3-7046-4acc-b19d-46db91fc079c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8bc207c-8fb5-41e0-9db5-66c92651a9fb' class='xr-var-data-in' type='checkbox'><label for='data-f8bc207c-8fb5-41e0-9db5-66c92651a9fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., nan, nan, nan],\n",
        "       [nan, nan, nan, ..., nan, nan, nan],\n",
-       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e552e581-b4d7-490f-a383-2ab8b9c37cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' class='xr-var-data-in' type='checkbox'><label for='data-1218ad84-b8df-4fda-8365-c163cb11ac9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f33f1882-7abe-4bd9-a0c9-90c0265f0dd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f33f1882-7abe-4bd9-a0c9-90c0265f0dd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a58e997c-1580-4bf0-9c90-dc9b094af1ca' class='xr-var-data-in' type='checkbox'><label for='data-a58e997c-1580-4bf0-9c90-dc9b094af1ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ..., nan, nan, nan],\n",
        "       [nan, nan, nan, ..., nan, nan, nan],\n",
-       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b314739a-ac75-4d88-96c9-10c63f969d61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6eccaf05-f218-4c83-a174-1470d34dde2f' class='xr-var-data-in' type='checkbox'><label for='data-6eccaf05-f218-4c83-a174-1470d34dde2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1a97fe5c-dbee-4b61-93cc-136f833677bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a97fe5c-dbee-4b61-93cc-136f833677bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd3f2c8b-e303-42cb-bdec-0c4ff67edc3e' class='xr-var-data-in' type='checkbox'><label for='data-fd3f2c8b-e303-42cb-bdec-0c4ff67edc3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
        "       [9.33, 8.67, 8.3 , ...,  nan,  nan,  nan],\n",
        "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6b553291-1032-4c41-9b83-daf3397a9551' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6b553291-1032-4c41-9b83-daf3397a9551' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' class='xr-var-data-in' type='checkbox'><label for='data-c35031a7-9a53-4fc8-b420-6145194ad6f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-406927d1-8af9-4a30-94e2-53d1ac1cde40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-406927d1-8af9-4a30-94e2-53d1ac1cde40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c274b6c-22a0-40fd-b768-bcc180d2ca69' class='xr-var-data-in' type='checkbox'><label for='data-8c274b6c-22a0-40fd-b768-bcc180d2ca69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
        "       [9.5 , 8.24, 8.38, ...,  nan,  nan,  nan],\n",
        "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bf46321d-9b4f-493b-b8d6-3711f0cda1e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be9da896-9635-4448-ad3b-dcdcdc179102' class='xr-var-data-in' type='checkbox'><label for='data-be9da896-9635-4448-ad3b-dcdcdc179102' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-79a2d876-5e55-4ae3-881c-f0e71fe576de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79a2d876-5e55-4ae3-881c-f0e71fe576de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8815e99d-3275-483c-bf35-11e2289612ca' class='xr-var-data-in' type='checkbox'><label for='data-8815e99d-3275-483c-bf35-11e2289612ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
        "       [ 0.04, -0.18, -0.26, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abdd0e86-9414-4748-a4a1-478248f22c6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' class='xr-var-data-in' type='checkbox'><label for='data-2cf25fbe-897f-49f9-addf-e58b98b2d915' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95e9881d-28c2-4b44-a0dc-74c4dc2f3167' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95e9881d-28c2-4b44-a0dc-74c4dc2f3167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-840a3da7-e040-4bf8-a52f-3e6eb05a1cb5' class='xr-var-data-in' type='checkbox'><label for='data-840a3da7-e040-4bf8-a52f-3e6eb05a1cb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
        "       [ 0.35, -0.02,  0.02, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-8ba515f8-123f-490f-8cf2-254391f11774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ba515f8-123f-490f-8cf2-254391f11774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7785e6ce-31a3-4d71-b185-adefed77555e' class='xr-var-data-in' type='checkbox'><label for='data-7785e6ce-31a3-4d71-b185-adefed77555e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-f25ce175-9c60-47b4-bf19-0c857035e2c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f25ce175-9c60-47b4-bf19-0c857035e2c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1c138d1-278a-4351-9672-89319b2b3b2e' class='xr-var-data-in' type='checkbox'><label for='data-f1c138d1-278a-4351-9672-89319b2b3b2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
        "          5.80396911e-04,  1.79292378e-03, -5.69819706e-04,\n",
        "         -4.36119642e-03, -1.06982014e-03,  6.37054257e-03,\n",
        "          3.98992328e-03, -5.19806752e-03, -4.50613070e-03,\n",
@@ -4895,7 +4898,7 @@
        "         -5.42755188e-05,  1.08743296e-03,  1.58825796e-03,\n",
        "          1.45288126e-03,  9.33228002e-04,  3.50838847e-04,\n",
        "         -6.20377104e-05, -2.31620375e-04, -2.17583845e-04,\n",
-       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e94c5d5-5a45-4d40-946f-e1db55f58448' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c844e259-e4c2-42be-8d15-d40f7c48673c' class='xr-var-data-in' type='checkbox'><label for='data-c844e259-e4c2-42be-8d15-d40f7c48673c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
+       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-fcd85c89-abfe-416d-a3db-37864feb3f78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcd85c89-abfe-416d-a3db-37864feb3f78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c375bd5-9a2b-4365-adbd-d988ec5442f1' class='xr-var-data-in' type='checkbox'><label for='data-4c375bd5-9a2b-4365-adbd-d988ec5442f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
        "         -9.13087046e-04,  7.09498825e-04,  2.99199694e-03,\n",
        "          9.69185190e-18, -5.61309094e-03, -2.52190628e-03,\n",
        "          6.28564134e-03,  4.88218758e-03, -3.27457441e-03,\n",
@@ -4935,7 +4938,7 @@
        "         -2.52039032e-03, -1.88605406e-03, -8.73966317e-04,\n",
        "          6.09558374e-05,  6.21019106e-04,  7.48717517e-04,\n",
        "          5.76159859e-04,  3.03197594e-04,  8.55612234e-05,\n",
-       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4554c2c6-cf3f-4945-a25e-3eb71c0aade1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' class='xr-var-data-in' type='checkbox'><label for='data-7cdbde03-aed8-4a7f-afd0-16d9487b4e40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
+       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-c9ebcd75-8a62-410e-8186-065847d11f8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9ebcd75-8a62-410e-8186-065847d11f8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c617a237-2384-4c6c-bb40-71f8448abc8d' class='xr-var-data-in' type='checkbox'><label for='data-c617a237-2384-4c6c-bb40-71f8448abc8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
        "                     nan,             nan,             nan]],\n",
        "\n",
        "       [[-2.92797376e-05,  1.22475076e-05,  2.08751826e-05, ...,\n",
@@ -4946,7 +4949,7 @@
        "\n",
        "       [[-3.34112738e-05, -1.13061478e-03, -2.34585186e-03, ...,\n",
        "                     nan,             nan,             nan]]],\n",
-       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-84b34193-1763-4874-9e7f-5ebe1ef1093f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' class='xr-var-data-in' type='checkbox'><label for='data-77de0588-a2e3-4ea8-8183-f2089e5f9c73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-69e6647a-78dc-459c-899c-170705d41c58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69e6647a-78dc-459c-899c-170705d41c58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a310df1-be38-4571-a08c-f38f96bc8c18' class='xr-var-data-in' type='checkbox'><label for='data-6a310df1-be38-4571-a08c-f38f96bc8c18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
        "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
        "\n",
        "       [[-5.08991980e-05,  3.11717099e-06, -1.25777024e-05, ...,\n",
@@ -4957,13 +4960,13 @@
        "\n",
        "       [[ 1.31017148e-18, -2.90292519e-04, -1.28964300e-03, ...,\n",
        "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]],\n",
-       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-065376e8-2433-4523-9d8e-180c409dc855' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-065376e8-2433-4523-9d8e-180c409dc855' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6952267-584f-4c92-8e74-63f9dece4db1' class='xr-var-data-in' type='checkbox'><label for='data-b6952267-584f-4c92-8e74-63f9dece4db1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-5547ca8a-272b-4c0d-b590-176ee622afd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5547ca8a-272b-4c0d-b590-176ee622afd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4af02dc3-8cca-48cb-90bc-8e0dcd35bf66' class='xr-var-data-in' type='checkbox'><label for='data-4af02dc3-8cca-48cb-90bc-8e0dcd35bf66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
        "       [ 8.],\n",
        "       [ 6.],\n",
-       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3eafadcd-5552-4f6d-9f58-158761e97d15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98037233-e32a-468f-8b01-0897ad886f8c' class='xr-var-data-in' type='checkbox'><label for='data-98037233-e32a-468f-8b01-0897ad886f8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
+       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-164725e3-2395-437d-a6fc-98b11aa1db72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-164725e3-2395-437d-a6fc-98b11aa1db72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab938bc7-b1a3-4010-8a19-69caaacfaf42' class='xr-var-data-in' type='checkbox'><label for='data-ab938bc7-b1a3-4010-8a19-69caaacfaf42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
        "       [4.],\n",
        "       [2.],\n",
-       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f6f4376b-acb7-43da-83da-7e649ee645f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' class='xr-var-data-in' type='checkbox'><label for='data-9a41541d-7255-4e93-b5b6-eaf18a9c8c15' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGK from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGK&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.GGK.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;4&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;4&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;VTG from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;VTG&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Ground&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;CourseNotUsedMagnetic&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Annotation&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;External Depth From LAN Port 9 Pressure&quot; Type=&quot;EchoDepth&quot; Port=&quot;Lan Port 10&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;DPT from External Depth From LAN Port 9 Pressure&quot; SensorType=&quot;EchoDepth&quot; Type=&quot;DPT&quot; SubscriptionPath=&quot;External Depth From LAN Port 9 Pressure@EchoDepth.DepthTransducer&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Depth&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;TowedBodyDepth&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;MotionBinary From LAN Port 1 8000&quot; Type=&quot;MotionBinary&quot; Port=&quot;Lan Port 2&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;MRU from MotionBinary From LAN Port 1 8000&quot; SensorType=&quot;MotionBinary&quot; Type=&quot;MRU&quot; SubscriptionPath=&quot;MotionBinary From LAN Port 1 8000@MotionBinary.MotionData&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Roll&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Pitch&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heading&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heave&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n    &lt;/ConfiguredSensors&gt;\\n&lt;/Configuration&gt;&#x27;,\n",
+       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-f3b1ec17-e0a0-4c6a-bd4d-5bc85f376cb8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3b1ec17-e0a0-4c6a-bd4d-5bc85f376cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea3ad4c-a81a-447c-b74d-23635e58ce99' class='xr-var-data-in' type='checkbox'><label for='data-3ea3ad4c-a81a-447c-b74d-23635e58ce99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGK from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGK&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.GGK.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;4&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;4&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;VTG from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;VTG&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Ground&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;CourseNotUsedMagnetic&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Annotation&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;External Depth From LAN Port 9 Pressure&quot; Type=&quot;EchoDepth&quot; Port=&quot;Lan Port 10&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;DPT from External Depth From LAN Port 9 Pressure&quot; SensorType=&quot;EchoDepth&quot; Type=&quot;DPT&quot; SubscriptionPath=&quot;External Depth From LAN Port 9 Pressure@EchoDepth.DepthTransducer&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Depth&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;TowedBodyDepth&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;MotionBinary From LAN Port 1 8000&quot; Type=&quot;MotionBinary&quot; Port=&quot;Lan Port 2&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;MRU from MotionBinary From LAN Port 1 8000&quot; SensorType=&quot;MotionBinary&quot; Type=&quot;MRU&quot; SubscriptionPath=&quot;MotionBinary From LAN Port 1 8000@MotionBinary.MotionData&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Roll&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Pitch&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heading&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heave&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n    &lt;/ConfiguredSensors&gt;\\n&lt;/Configuration&gt;&#x27;,\n",
        "      dtype=&#x27;&lt;U100225&#x27;)</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
@@ -5449,6 +5452,16 @@
       "f_m (1000,) float64\n",
       "alpha_m (1000,) float64\n",
       "lambda_m (1000,) float64\n",
+      "g_0_m (1000,) float64\n",
+      "angle_offset_alongship_fnom () float64\n",
+      "angle_offset_athwartship_fnom () float64\n",
+      "angle_sensitivity_alongship_fnom () float64\n",
+      "angle_sensitivity_athwartship_fnom () float64\n",
+      "beam_width_alongship_fnom () float64\n",
+      "beam_width_athwartship_fnom () float64\n",
+      "theta_t_offset_corrected () float64\n",
+      "phi_t_offset_corrected () float64\n",
+      "g_theta_phi_m_db (1000,) float64\n",
       "y_tx_n (3071,) float64\n",
       "y_mf_n (516,) complex128\n",
       "y_mf_auto_n (1031,) complex128\n",
@@ -5539,6 +5552,11 @@
     "        \"max abs diff\": np.nanmax(np.abs(diff)),\n",
     "    }\n",
     "\n",
+    "# prepare plots\n",
+    "api_color = \"black\"\n",
+    "crimac_color = \"orange\"\n",
+    "api_style = \"--\"\n",
+    "api_alpha = 0.9\n",
     "\n",
     "def compare_curve(\n",
     "    x_ref,\n",
@@ -5552,8 +5570,24 @@
     "    ylim=None,\n",
     "):\n",
     "    plt.figure(figsize=(8, 3.5))\n",
-    "    plt.plot(x_ref, y_ref, label=\"CRIMAC\")\n",
-    "    plt.plot(x_ep, y_ep, \"--\", label=\"echopype\", alpha=0.85)\n",
+    "\n",
+    "    plt.plot(\n",
+    "        x_ref,\n",
+    "        y_ref,\n",
+    "        color=crimac_color,\n",
+    "        linewidth=1.2,\n",
+    "        label=\"CRIMAC\",\n",
+    "    )\n",
+    "\n",
+    "    plt.plot(\n",
+    "        x_ep,\n",
+    "        y_ep,\n",
+    "        color=api_color,\n",
+    "        linestyle=api_style,\n",
+    "        linewidth=0.9,\n",
+    "        alpha=api_alpha,\n",
+    "        label=\"echopype\",\n",
+    "    )\n",
     "\n",
     "    if xlim is not None:\n",
     "        plt.xlim(*xlim)\n",
@@ -5566,6 +5600,7 @@
     "    plt.grid(True)\n",
     "    plt.legend()\n",
     "    plt.tight_layout()\n",
+    "    plt.show()\n",
     "    plt.show()"
    ]
   },
@@ -5631,9 +5666,19 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 1100x300 with 2 Axes>"
+       "<Figure size 800x350 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -5641,26 +5686,25 @@
     }
    ],
    "source": [
-    "fig, ax = plt.subplots(1, 2, figsize=(11, 3))\n",
-    "\n",
-    "ax[0].plot(np.abs(ref_ts[\"y_mf_n\"]), label=\"CRIMAC\")\n",
-    "ax[0].plot(np.abs(y_mf_n), \"--\", label=\"echopype\")\n",
-    "ax[0].set_title(\"Matched filter\")\n",
-    "ax[0].set_xlabel(\"Sample\")\n",
-    "ax[0].set_ylabel(r\"$|y_{mf}(n)|$\")\n",
-    "ax[0].grid(True)\n",
-    "ax[0].legend()\n",
-    "\n",
-    "ax[1].plot(np.abs(ref_ts[\"y_mf_auto_n\"]), label=\"CRIMAC\")\n",
-    "ax[1].plot(np.abs(y_mf_auto_n), \"--\", label=\"echopype\")\n",
-    "ax[1].set_title(\"Matched-filter autocorrelation\")\n",
-    "ax[1].set_xlabel(\"Sample\")\n",
-    "ax[1].set_ylabel(r\"$|y_{mf,auto}(n)|$\")\n",
-    "ax[1].grid(True)\n",
-    "ax[1].legend()\n",
+    "compare_curve(\n",
+    "    np.arange(len(ref_ts[\"y_mf_n\"])),\n",
+    "    np.abs(ref_ts[\"y_mf_n\"]),\n",
+    "    np.arange(len(y_mf_n)),\n",
+    "    np.abs(y_mf_n),\n",
+    "    title=\"Matched filter\",\n",
+    "    xlabel=\"Sample\",\n",
+    "    ylabel=r\"$|y_{mf}(n)|$\",\n",
+    ")\n",
     "\n",
-    "plt.tight_layout()\n",
-    "plt.show()"
+    "compare_curve(\n",
+    "    np.arange(len(ref_ts[\"y_mf_auto_n\"])),\n",
+    "    np.abs(ref_ts[\"y_mf_auto_n\"]),\n",
+    "    np.arange(len(y_mf_auto_n)),\n",
+    "    np.abs(y_mf_auto_n),\n",
+    "    title=\"Matched-filter autocorrelation\",\n",
+    "    xlabel=\"Sample\",\n",
+    "    ylabel=r\"$|y_{mf,auto}(n)|$\",\n",
+    ")"
    ]
   },
   {
@@ -5736,13 +5780,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_13472\\1980613090.py:11: RuntimeWarning: divide by zero encountered in log10\n",
+      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_19676\\2179791150.py:11: RuntimeWarning: divide by zero encountered in log10\n",
       "  return 20 * np.log10(np.abs(x))\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -5764,14 +5808,6 @@
     ")"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "a073555b",
-   "metadata": {},
-   "source": [
-    "check for above that we remove th surface values? (like safe_rang?) or why do we have the warning if not"
-   ]
-  },
   {
    "cell_type": "markdown",
    "id": "94b88200",
@@ -5839,7 +5875,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -5952,7 +5988,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -5983,7 +6019,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -6026,14 +6062,6 @@
     "print(\"Sp target max:\", np.nanmax(np.abs(diff)))"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "644e8175",
-   "metadata": {},
-   "source": [
-    "why do we have difference in the curves?"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 18,
@@ -6109,31 +6137,32 @@
    "id": "c062de91",
    "metadata": {},
    "source": [
-    "### Get split-beam alongship and athwartship angles\n",
+    "### Compute raw split-beam angles for manual CRIMAC validation\n",
+    "\n",
+    "For the step-by-step CRIMAC validation, we compute the split-beam target angles from the pulse-compressed sector-level complex samples.\n",
     "\n",
-    "For split-beam EK80 data, the target position within the transducer beam is estimated from the phase differences between transducer sectors. Because this example uses FM complex data, the sector-level complex samples are first pulse-compressed, then combined into fore, aft, starboard, and port transducer halves.\n",
+    "These are CRIMAC-style angles: the angle sensitivity conversion is applied, but the transducer angle offsets are not removed here. The offset correction is applied later inside the frequency-dependent beam-compensation calculation.\n",
     "\n",
-    "The alongship and athwartship angles are then computed following the CRIMAC broadband processing workflow. Phase differences between transducer halves are converted to physical angles using the calibrated angle sensitivities and the inverse-sine relationship described in Andersen et al. (2024). This approach reproduces the reference CRIMAC implementation used to generate the published broadband TS spectrum example."
+    "The public `compute_TS_spectrum()` API performs this angle calculation internally. Therefore, `add_splitbeam_angle()` is not needed for the TS-spectrum workflow."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 20,
+   "id": "9150ec46",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "gamma_alongship: 24.916666666666664\n",
-      "gamma_athwartship: 24.916666666666664\n",
-      "theta shape: (2356,)\n",
-      "phi shape: (2356,)\n"
+      "theta_raw: (2356,)\n",
+      "phi_raw  : (2356,)\n"
      ]
     }
    ],
    "source": [
-    "\n",
+    "from echopype.calibrate.ek80_complex import _get_splitbeam_angles\n",
     "\n",
     "gamma_alongship = scalar_param(\n",
     "    cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
@@ -6147,131 +6176,38 @@
     "    tsf_ping_index,\n",
     ")\n",
     "\n",
-    "from echopype.calibrate.ek80_complex import _get_splitbeam_angles\n",
-    "theta, phi = _get_splitbeam_angles(\n",
-    "    pc=pc_ping,\n",
+    "theta_raw_da, phi_raw_da = _get_splitbeam_angles(\n",
+    "    pc.sel(channel=tsf_channel).isel(ping_time=tsf_ping_index),\n",
     "    gamma_alongship=gamma_alongship,\n",
     "    gamma_athwartship=gamma_athwartship,\n",
     ")\n",
     "\n",
-    "print(\"gamma_alongship:\", gamma_alongship)\n",
-    "print(\"gamma_athwartship:\", gamma_athwartship)\n",
-    "print(\"theta shape:\", theta.shape)\n",
-    "print(\"phi shape:\", phi.shape)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "id": "3ae46a66",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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gxGP3oFPMsEIZGJzaKKsgxqQYLqTl5D5eQKlda5M1kt47mrT4VWSf3XOsqMbpZumjqHSTbYdOQKMGKdC8oVXmgVNdsfjoo49iMsDs6Eejfa9TQbOojToWlGNbsN7YCNZ0MVaBPwa9BtamoB4uNwV3sKBeNBQLvceiOpxnInliInkXVJnwa6nSwTgsIgO1SsYTvbOBgUHNg67PsfRY+N1P6Hk15bHAffGhr9dCx6YZcNPo0yz3royZYlHs+zpUr8D2u/Vg0GeRT0HZaNyzs9jnHX/7EcQKdTYUKpaaqyxkRpNTX5iMp4AMUCsei/xipQdKbktGapIHxSJwLr0EhkLpQq10j630iPmAn/U4kk2GWqec+soJbsJ1nA7Ba0TajvoCOq5NKJSBwakN0WMRu/3Xr+ea5h/WlHyAJCYfLNgJj3+3XnnvWIVC7YkgFIoSrchK3IYDBXDT+0tg7b582/vLtbiWO4R8RwtGsVAMbrlIHh1z+UXlMG1dnu9JFe9FWepDjsWhwnBtCVHwF4+7anB7uHRAW/a51EFIra6yLkAnSsoljwg4LpiqHB4/0Cm7diPK7yKOhe325YfDy3QCvd31qeVEPs5NIUIZWGl84KNTWC6JjFNgWgkQN8habYqBgUEtg67PMc2x8GnYKa+FUChV4WO6l0ez8nYV6RaVx2LdvgI499mZMGnNftvrJJFNU+4n3P+mrT8Il/4zwP5FQeVKfgkeiVNMaojEEkaxUAj4svBHf732zYWssvSrM62sOJ4Vi1NACqiNZ6Ta/clSdagSAl2LvHieU3hPOMdCTN6mORz08jrLMVVEIoGfbvXzLrC9N76z2FLVU4VSwnjmyYWu1Cvs2/rpsj1snv574U441VFxihkrDAwM9CilHoHq+AuFEj2sUCOgQjrfm2PmsagOX+swMXJy/PmLVbD10Em45d+BEgc60Krkcl8fLCjV7umVRElCGefzZXug14OT4NOlu6HUKBa16bGQFAsyUNbvD1Sd/GblvojvVZuMCLGAapDXRo4FbQcV5OVFFiduKq/KTdiTOOjhylCo0grB0yHmWEBsPRZ+FAsfJx05UWb57rDiOwRloLKDrMRFkmqkym+rZ9PKE/lELC2UBgYGdSwUKobrgd9ohHKyXtWUIUQVVhSr5O1Kci2VwVIlazh5+WX6+m6tGoY+F5SU6z0WAHD3pyvZ5z99tkrwWMRybBiPhWJQWUKhFB0XjXoA0XS/xQNUC01lbSsW5F3KXgRca7hioVoAaLiRKnkbPRZUkHOTvB0tj4WfvB8+3l6YthmufWMBlLiwXhw6YbW46GDnsaCJZzKbiConze1+Y6hqRbazU02pMjAw0O/Dsdx+y+oQKxQ1QPH7C/t1FNtRTa6rkokaNUj2vLfJMiqPtECs2p2vZR6ttjH+xTJM3SgWikGFVmX6nWqzTklKiNy6WM+kANVA1RWKiyVov9JQKLkpOG85Q5NqkVSFNtH4SVQsdG5d3UIVLY+FTq+wG1K8X56ftgkWbjsKX7vwutF8FSfYeSzoZkJjbP3mWKjcxacq6JpiQqEMDE5txLvHojbqWFAhnRsR3eRE+kEleSaVXJGVnuJZQZHbR+WanUdPCr9RGUXuX+qxiGU0iVEsFB2MiS50cMTKY1HfcixkgTGSwYvF3d6asy1qoVC7jxbBBwt26EOhFNZ2gY4uFAoleizEcVKDrFD0s8vF2RLy58J7ctiDx8LOAxLNOhj0eX1Ow3qF2qBvNDAwiB42HiiE+VvCFbOjlrwdpfUAWYgOBinMI6abrQWPRYLC2FkjoVAVCo9FerKrPZO+OnnPpHKEHPkieCyk90/vxyMHsBZXnvRuT9k6FtGERRssEy3RKjOwb8WCTqp6JgNEKxQKrf0PfLmGfR7UsYlQ5M3V+eSWvIDduc/Ossb20+RtB48Fv6ZcII9aQuwsBbSORTSgo7a16235XbhZTKOlWNDFTh4nXp0ONK/FhEIZulkDg7qOC/4xm/0/856x0Ll5ZkTXovscW+MjNL6g0HnhP+awz1ufzIm8QB71sNaQYkFvw/c9N6HLvu5VJd4L5Rma48GNmTwioEPTDOV1qKHS6rGo0O6nIkEQ6M8LNvSMx6Yy+WfxA+dCy6x0iAaMvU/R+SwUysljQQaHF4hFWeoXD79KOFcJr6v35FsSjnTJXd+u8p4kTycWDz1S5VDgXLdTLFQxmKLHolybjK/NsYiBx0IYqzYLJHpX6CJUGWXFwo6yt6zCLhTKCruW0eQ3Hgp1KtdvsNtIDAwM6g425RXGHd0srR6N1OMc5T6vTdd/twL9J0t3M1Yjv6D34f1TE5W3VbIHfT92+6tKGVKFVMvXtyMIwigL+T3w9uTuOg7RglEsdKFQTjkWPsut1+dQqDIXORazNh2CS/45F37yynxXXp3p6w9GjRVKBsqk4VAolWIBljFAJ6pFARVyLNT3LCiOfoE8t4sz9gv1KriJxz9cqGaAUoFeGxerOZsPhb6z91h4m0s0TpQ/e22wj8ULTCiUgUH9gFM9pdookEcv8dnyPRHnT3o1hBwvKmN1Gxirkc8cRZUSIQjgHveP/OJyJsuo+qDSSbEgf+sYFlmbbHIseCSGKhTKrmAqVSzktkfTNmcUC8WgQquykzPBbyiUOJih/idvS337RXBh2nzwhPY6dKJgCfqIkrdtPAQsxyLJpcdCQTeLioUwiYUci2rtIhl1j4XLcYRtpUK5G1YPb6FQ4etN+H49/OztxXBPkOpOTN52ppu180BQBYZvxPWNYc0LTrXaOAYG9Ql0zkZDsRAo0KOwHlBBGHNB7HIqvbNWOV/j6MmyiBUlQbEIJW/79/Re8/oC+Pk7i+Htudstv1VJfS7vs9Tjbre/6nIscG+kHgtLKJTNc2GUhe48p9pRXmAUCxxovKyyNnnb2uHJPlihcMDl7jpWbxlcykm4i07QccPhLPBcS1Z2FXChuO2/y+HlGVss90Rhdznpc0uORYpNgTyFV4AKvFgcT1f1WLdgHouSYuEnPpT1ZVmV4M3BpDyknl2y42gUQqHC7+ndeYFE+W9X7bf0r2VD8jiVVMoR9YicahDWqvq1pBgY1HtQAc8NBbgT6FobjdBIul7TsCinorI6UCOQG8XHrshtJLUlaPO9hqVvCCpYX63Y5yjzlNt5LGxYF2nf4DW3HAwk+KPiaFcrQ+hfF6FQHMZjUQMF8lSeBSpU+vFYICvRkxM3hP6uOBVCoaRnLHFRnVm2PtvlYyCmrMtjAuzTkzcKk6l/+2z2/2uaKumsjkVSkk0olFVpoI+DQq2OgUP3ao8V2T+La/gMhaJCObpT//DfXEY9e9VrC5TH7zvuni1Ctyne/lGu4Km5+vUFME/DgMLnWLWHkKtoeiyW7jgKr8/aWqcKzdFKq4YVyiAWQAPEjA3ew1INvO2b8RgKRUNmolEHQfCwumgfjTrwuy7T+6jqWPjtJ5UYWFnt3mNhJw/QR0Ul4LznZsP1by0KFWnWGXTtjI4FgmJRJci00dzxjMdCUyBP9XLopPdTx+ItyW1Wl4SXaNWxcOWxkM4pKLYXxrcdCodVXfHKvFDc4k+Hd2L/5+5WJyWJdLNOORbWxUieqG48FpGEQomLgLMS46xYVNp6UPbnF3uySuk2xf+t2AdLdoheoxveWhT6TGeSm2cRPBaVlVGt5nrlawtgwvcb4BsfpAG1BSFvy7gsDGIAZAX65XtLLEKNQeSg7EpR8VhEORRKp0D4XWroWu2mfbRgsd9QT3of7t2ORvK2qo5StXQpi2JB+tNOHqB7/I7D4VoVm/PEMHLZW2+XcyeGQlUr80ijAaNYuPBY8BclKhaRd119i4d2k2NBw2V0i4p8DiZK2WFfftiqvpwwG3RqlmEbzoNLgmtWqGrniUpnpnxcejDkisaLeoVuERAUDpshhUInTX47UVIO2Q30xXp2Hgm4vbPSkkMeoD5tG2mP97spihVGqxyfgyqn/DP1WESjKCONJY4F88uPXpwDP2zIg4+X7IJHv1kXEasVdeOfyuxYBrHHFpvcOAN/oCEpdmQjvkKhorAelEU5f02k3He+NhrAvBzvJGvx/o4keZsjwYVcV2Yxroafx86wRy+zdGc4VPmodI4sd9FnkSO8qAyL5+lyRCOFUSykUAKVYsE/0wERjYq/9S1swU0dCzqwdWFRsmDopFjs1yR4t8hKY54lXTcjtzT3WJQp2iLWiuA5FjaJctRjIXVF52aZIQ+HX8FXy0DlwWNRIoVCNc5IDf2NdH5vzN4a+u2N2YEChcO6NIVVD4+Hz383kn32U3nbDnQquVG2qXLGF227yt7xpvTf9uFKWLuvAH713lK47/PV8M687TB/6xHf16OPW89sFQZxhlOl0v1XuXvhz5+vioqRwsu+Sdl+/K5b0RCYKfzWq9Bez2MOCDXe+RWZ6N7J7y9WtvZ3XRWjYaVDKBRVNGgoFIYb3vT+Uli7L9/SvqXE43+AGFID16/WGmbtwtVwz3RiP/ULo1goPRZiKBS3olLByY/mLI/BepdjoUjetlD5EsGWJmVRyIKhE0XrfmmicSQnJkKrRulRoZsNs0Lp35ldbCNXLNwoSjq4YaCya58cCoWJXI2JxwLp/DAHaN/xYlb1HOn0EJ2aZUKj9BTmpbMTLOi13UBV7dxpTny/ej/cHWSaoos2da9HWtnbTTsigSquNhJPFvVY1DcvqEHtgwrXPlnW6xzu+HgFfLRkN3xO6FVjBSponiChtb6uJe1jUcmxsEls9qN42dVZUIEmHPtd3+h6zo1QInuS9TkwtxMJYXYFPfcqqOZDlaJ8AQ3Xph53DIXC3CVMyv7Vu0tg2vo8+OW7SwLXIe2jLJq4P4vPpvdYUPYoGbhPClW6IXowioWLUCju0XATxuMFp0KOhdy3+USowgmHFvRjklAlTxTHUCiNxyIxEaBNtl6xQCHZbShUuI6Fvh12ORbNs1IhKz05ogRuMfyJ3EvDTGVtnxgKhUlxqlAoFHKpBZ32oZ1g4ZVjfPfRIkfvoYw/fJgr/K1K3o6GUhBLS6XK5RyJ99KOBcTAIFKUkLWRVhA+FbD3mHe6c6+gew/N2Yv0WohokOXZhUL5YYbyWsuLeiz8KhZiKJSCFUqxbj70v7WMEOaKV+dpr6sytFVJl7r5g6Uw7tlZ8GXuHkufoVEUc5cwKZuHdB8MMkXpHvVAQYmt3EX7l+anyMDz6PiIZhhtRIpFeXk57N69GzZu3AhHj6rpKusC+IvgYwQFJNFjUW31WCjeOmq3v35viav6AOwacSAE4LNe/vI8eG7qppgoFgJndVW1EFOIgm3Oi3Ng0GNThTwI2WNhp1jgZNAtxkmJCfYeC5pjoWi7qgidnTIohk6JvzVukApNgmFHfhO4ddXg3SSNcwFUSN4uqYAGqQFWLNlC1JYoEz/q3yb02c5jYbeIqbD9sFWx4HNNt8jR0C363ug4q4hzj4Xq0SLxNMTKnW1ggKDhkwmnsFJVM6FQkbEGlgbJLJzWMSTm0BnkLO2z6QM3ZCz2oVAucizI/h6dUChr9IGqHTM2HnQsYqfaDystddEC7+T1WdssIfV2LGC6vVxmapQjRahcye+tAvZDrGjaPSsWJ06cgNdffx3Gjh0L2dnZ0LlzZ+jduze0aNECOnXqBDfffDMsWRJw5dQV8IHQMJikigKvyHEcVCyIx0KlFKB2O33DQfjWJaNMTRX1wo1Bt4h8s3IfrNh9HF6cvjmmHgsU9tC1KBaYq4BthwJsB3M3H9Z7OWwUC7t1KSkhwdFjEaKbLfeXvE2BP6FAvHpPviWRuXFGCjTJSInIY6GrV+C0QNLj5BwL1fFoIeJK9GOX94W2jRu4qpJdTPrQTSg2H5NeCrw1bygqFqHkbUVyXiSo6YJ7ESkWLt+/gYEf0DWjvoXvOsFvpefayrGweCwU+xXeb8SEH2Dk335wRbhhF1rqJ6zXrjK0YyiUQ6iv/jewZYVSnetGaVLtc1WaNvJ7uPbyaB5HJqOxFMgje1eRzXjCfhALB9aSx+L5559nisSbb74J48aNgy+++AJWrFjBPBYLFiyAhx56CCoqKuD888+HCy+8EDZvjlxYrQlUBAcCxpEjdh8thjzibgqxQpGBJluu6d86IT5BsvfUVNgCeiRwEYk1VaDKZYp9hwnBfR6aHIrZV+VYFAol6t3TzdotJui2b50dFopVi4JdgTylx8LmleGih7G5l/xzbqhYHweGHDUKhh35zbEQ6ziqw19sPRaYYyFU7BQreNKFnIf9cY+Ou1Aob5siz40RCgE51LFomikpFqHkbeKxiIIVhuZsRBuqZ4uWx8KEQhlEG9RT79YbX1/gNW/MD6jFOeo5Fop1he6nx10YueyUyce+Xee5jdTw4yZqg0Yk6NbJz5ftgb4PTQ55GWRUObBCfZW7z5IUrcoB9OOxoP2IipSbWiV4nNNazsOY5f3Oi8dCqO8RxT0vYKJ3ifnz58OMGTOgX79+yt+HDRsGv/rVr+C1116Dt99+G2bNmgXdunWDeAcfdPii9gaVgj9+lGv1WJBFRpahaRE3t4JjtK2LqLlifF47YmGmVSK/XrkPerUR6UJpKAwKZ8keaHRxEcNnRfYldn/FhMFn5EUBUejW9Rml2Sv35LGotvVYNEyzhvqIHovEUDvl5xdzLKzuUxmLth2BGRsDytMc4oHhITzJQancb26NrgCfLt/CKXlbZyGjydHpKWL/2YdCiSETTk/JlXfB4u5gNWkiKRah5G2Bbja6HgsWbldcAdlBj1OkUI2hSPjrxbb6voyBgXNByhpgSTrVFItoeixkb61qraEGPTeKot0xKMjj+mjnyZZRERErlHqB43vWXR+vgNwHx1vvqcixoH2D4xrDspf/9fzQd262aS8ei4qqqqByASF5UyfbYMHf79ccsL03yl14vlwgr9JDjkW0cxN9eSw+/fRTrVJBkZaWBrfeeivcdNNNUBfAGQGw7sGgjo0tmnyIFYqGQknaHT1eV61YHoTRti7+6r0lcNbffoD5W9VVjVWCfwMiOFKXoxvc+p/lMPSJaSHOf6cCefLjUiackzYei+M+FQv0WNgJwqzyNrHIy5ummLvAn6Hase6DChgKhTkfTm22AxXAdV4Kx+RtF4oFhRePhR0DhS7Ol7VL4abWaSXy7TlNMLW2+PU2CJ4T8hk3rQGPToGVmkKLnqF4tqIIBBgTCmUQS1DL7angsaBrfEkNh0KhdT6SJFo3HotCksdRVK5f/z9ZshsufmkO7DxyUs+AVG1vFVdBKOBWFb1QKPa75npi5W1rKJRfZj518na1ug2VoreitU3+J5KU7HEgDmjRME0pt9D+1TFvsuMq4yQUqr6CvwgU/N742RDL7yinYAjJM5M3hr6TByVNSt5OqiQibv3PMrjsn3MtxW+iHa/KreT/WrBT+TvmjsgTmf7lVbFAajQEz89wUyCP4ghJiqLuWW514XOWVp304vXB98mFeRXQykIFZ7v4VN5vdq+MemBkIK0rt+r4TdrX5VLQNtldGxcO2TLOx+SVg9vDTaO6WM6RPRa2ORbBDQbb5mZoc9czVQqcvHjyGOMLtVggL/x5zd58ePjrta4S5nWUtV8s38v+l8Pb4iWWuyZCoXBurNpzvN4x2Rl4C4WKBpVzvIPOp5r2WOA8i8RrUSYlb6v2AxpuZbfu3Pv5KliztwC+WrFPuRfwvVUoEusCwnrvJseCKEL03WB0yea8QmFNykhNdh0KFY21UrUdVmqmCMpCVMZo2SigGHAlo2Uw8sMtmvNIEZsCeXYeCwxdp/0fzbntKRSK4q677lJ+j4JHeno6dO3aFS677DJo2lRfUCtewN8Dhqo0y0xlRdWE0IqqKvhs+R7YQSzS8jugHgvU8Ll7EBNtJq5Wu7R0QhQOvmenbIQx3VvAWV2be34e3XU/XLwbdhwugg9/c6bSO2AnGNth+a5j2hwLO0GRWggOk8984enXLhtW781n4V3Yj80bprHrYZL8sC5NYFzPVo7J23aKBf6EoU/4P17HzhrnJnnbLmQLw2iwPewaPoUzXcK22xwLmW6WKhYDOjS20P6qPRY2oVBB65fbzRhzLAKxpApWKHIcdbVbig2FQqGo8BM+++KX5oYU/xeuHeS+IqziHUVLyKiOgrdHawGMkdx/3+er4MvcvfDXi3vDrxUKqMEpEgp1Cngs6PrhZc57DQnikPfNvIJSyArme3qFHL+vct5SA6IXgwYqFnSdapSezIhImKKSrT7nhWmb4X8r9sKnt4yAZkELO11n8f4vTd8M5/ZqBb3bimHafH+iESB0e8PoDMR3fxwV+i4lWd3/gmVekbztF0qPRZXGY1GFHotA/6GMSfMFB3dqAi/fcAb87O1FljBqJyIT2dPg12MRzdB83x6L3NxclkfxxhtvsFyKmTNnsqRu/G769OlM8UDlYt0678k9teexSGThMy2zRBcV/nxUohyTBbjjxZRGtTK0IGGFXR10A/DDxbvg9dnb4Ia3Fvl4GnvhcsG2IyKnM/lslyTtRkD06rGgisWRINMBblx8omAyPS8sxxPPkcXqtVlbWdViJyEd61jYLfT8N12RPHrtcI6F9nK2bEQYTxkOhdJf41BhKYsTXbLDSt+sWwSEOhYOzBjWUKjA36j08DobFNYcC33bi8uqPG1W2N9HJGVGtbjhVyjcXP3aglAOi6XytmLjoH1hNw9D59Hq3SrFIkphEar5GYliQcMyY+WxQKUC8c8f6gYhh0H0cKolb9PQEjdzHveGa99YAJe9PM+XcCaHKFPimFiEQlGPiG7dofWmONKJkQn3gYbB/cKu9sbz0zbBtsMn4Y3ZAapVeZ/8bvV+eHbqJpbfoMLKPceV+x59LwtIzSVZTrOnm4WIodoPKzVrMMpH/P2kJSeF6OcRGcFc12uHdoSsIDupE1q48FissyHsiZscCwr0Rpx33nmwb98+WLZsGSxfvhz27t3LGKGuu+469nnMmDFw5513QryDJ4zy5NpWxEXF0SRTtCBYQqFOlit/5+XZlffVDMBdisJhqOm6dVUJoTGKwXLdGwvhkW8C4SGix8KbC5YWV8PwL9WmY1dT4MjJMG0ackVPXL0f+jw0CT5bFigkk5yUAL2DyeZcsaAVLPHZ7FypzGNhm2MR+A0rSkcjx0KHUV2bs4WEN8Vu80FP1Re5e+Gq1xb4CoWyZa2qqhIoYanHAse+ykpm8VjYaBacFcpNIjJ6nxCb88LvE/HEd+vhjo9yLc/69Yp9sJgoW3++qKfWY4GLJY6Xfg9PFq7hJRRKNW4jEf6dEEnyNm1qrFmhDJ3tqQc6Nk+FUCg69914LDC3buG2o7BqTz4zDHmF3KfRVCxU6wFlYNTldu08ag0/TiNGJjSSZaWluA6FwoKrPERcVeVah+U7A9EQHHy/P0pCW2mhVTTqqkLJlMnbMfJYVNp4LPj7QWMm5l1yZAaVCawZteT/zlOez8shqHIs8Nr8uWQFAfNo0bskAxUsUeGqqn3F4umnn4bHHnsMGjUKu6/w88MPPwxPPfUUZGRkwIMPPsiUjngHHwhJSYFB0lpR+0De+C0eCymGm88dO0upbgDK4Tt43EX/mAM5L8xxNRnodVXCPgpo787bAaOfmgF3fbLSUygU9gMXrmkzF28/qimQp28vVcbQY4HJ4Hj83C0BV2ByYiL0aJ3FPm85eILFyr/4wxYh5MwuoTaQY6F/Fr4m8P6WlQZViJFXwa1vu0bwr18PE+5jdw2Zo5qCnqaLq7fn8q62JCPyjZNtFC48Fio9jXt8cJPCPnSzGY84vRn7f9Ka/RaPGsb0UiEenw/zg1SLrKryNi60N72/VEgq1FHpzd9ymI1d+RoqSsCohUJVR15cUO+x8HeNLQcLYZcN+QCHYZ069UBJSzi9c30G3bPc0L+iVT2SNcKqWHhXThC49mK0A7WA6+oUOVGEq4hIqJEJvf18v0BB/t8Ld8L5z80ShHwKDGk+55mZTH5ReYN1WLFbNMzyPZqG7cqVqA8qFDNVkrKdUZLKArJxjf6m2g+rdR4LFgrFPRaJgseCKg2458pKBKJZw1Ro36SBJccCQ7BHTJgON769mN1bfq52TRrAwI5N1B4LTRTEd6v2w98mhXOKa0yxyM/Ph4MHrZzBhw4dgoKCgDDduHFjKCvzV2W4JsE7NOyxSNeGecjnINDSTgVeLsjgBKaF33T3ddKCUWlBd+LmgydcUdlSQdOOi1lO1nYKhTpYWAL9H5kCt/w7oCzSQYnKijoUSr8R7TkWXoQwVlNWqDAOkWv1uHi9N3+H8Pu4Z2fBr98PhETJwC7Exc+JFQrBvRpy86tVioXHfRXD63jIVSjHoroaNuUVKq1btBidxcWp9VhYQ7a0dSw0G59OsZAXVZUHiNd/wVvjwukmfCCnb2v2/zerRMVCBbyuPFf4wovPxKiCJW8Dp422o7HFMXX9W4vg6tcXMIWZVr1VPUMkwr/wPLHMsfChWeD6ct5zs2HM0zMcPXJ+iQcM6knytkRtWVNAw9J/F+2y9YDHhqWp3HFOrCTCr0zQ4i/Hwp/HYvmu4yxUFNfsO87rpg+FIvu+bt1RRU1QIxPunXy/QDni/75aw+STV2baE1zgdb28w0OFYl/wU2kYtRwtgorZBwt2MPp3dfK2c44FNSzh52U7j4XGAT0vwaPHotTBY8GhCgxAzwNVLLjHAvsf81DRKLd+fyFUSv2Lcm2DYL0uisDeqc5NxJy6j5cGwl9rPBQKa1Z8+eWXsGfPHhb6hJ9//etfw+WXX86OWbx4MXTv3h3iHXyz5IKtigaMCx3pwRfEBw8OOLS0q675/vwdTBE4vUUmo7KVgZdQLVrUyn73JyuZUqFin9I+DxnYboqxuGWF+nL5XmYhnrw2z2Lhnb3pECssKENFYdY52BcyTR0qEhSYWJ0ZZHnguQBuwQVgJ1YoGt4jLwiqWhFuPBbU7Uhvz++Hm+T452fDWX8PJJ9RUCuGTDcnxJpqqnDbCX6UbpbS7PJ+ylQwaripY9GoQbLA9ISLnBPG9mgJmalJrij+sN3yu6ELMY5Juiiq1nVV/GgpUbJwrqJwrbLSRjsUSjXna5MVCsej2zhbEwp1qtexiD1LkgrnPTcL/vLl6hBDUSxBQ2J1RUR1Hgu3jE44jz5ZimQqJy0GJDTg+UFukERldLcWcEbQQq1khXKRY8GpwCm47MP3AR46S42dToY3jPn3sobIhlR+LpWDaEg14ovle+DB/62Fa95YGD5PmWOhb4f8Hn/y6nx4ZspGyxqpzrEAx+Rtq8dCzbhFgV6otqTgr6yMcCO3fH+8Fjf+UeC+KVQkD/6BBrRI66n4Vixef/11OPfcc+Haa6+FTp06QceOHdln/O7VV19lx/Ts2RPeeustiHdUSB4LnpRE8eac7ex/jJWng1KVZMsH0UdLdrPPt47tqrQGB65j/Y5ahT9fvgdu+dcywbLvSbFwUZbebSgUnVA3vLVQEFIxR4KHMFGovBgq9gce+kSRgsJucMLx5G634MqCXU5AosKT4BQK5UZuo0XcqCDOFcbp6wOePmVOClmZZZpdMXdG1047VoqwANuULGp87MvKhspjkaCxpPBzxz4zE27+QO1F4rh5dBdWmPHSge3ADZhiIXU8dRUHEv6rHOeELNDTvyZ8HyjiaDdvopW8rUJkydv2SpUMVOYw2RQFG3neq+arSGLgvl01YV028Ac3VYVDx8YRK9Q6FyQMOmDY5ePfrnN8BtkY9q+Favp21TqNQtm+48Xwn0U7bT2cX6/cC/d+tgrOfW5WKHm7SdCC7TcUKjcYFoy1uPi+p9oL7FihUInENUAVAsZlH5nsY1OwjpUsO6kMKPj+7MKjZch5n6pQKFkm4v1AUeWSFYofp3r+l2dsZXIIXSNVCkCVzSJMcyyoYmH1WFivi3vm6S0bhv7m8irFvK2HLTksgWiEFE3BPuLpD7YbmUMjhW/FomHDhowF6siRI4whCpO38TOyROFviIEDB7J/dSbHIijYppMJpBO0KqUBiNWuf9SvTei4JTuOMYszWmVz+rVRxszpQoVk1yhlztHx8eusll42EKwu7HbBnbcl7GZ85NI+2nNUi0jXFg0t3gmEPE9wQnBeaq9JcSGPhYtQKP6/rFhUe6SbpTUr5Hawz8EbyUxICKTkQzcy3fS2kkR11h4hFEodV4+Lms5rgedw6yN1wyJwI+rZOguuG9bRM90s0ubRQosUuFn+6YIeob9XPHg+/CWnF/t8+cC24AYqZQmtN7wpOMadLO2oBF/wj9nwu2AYH7uuzTmqkLFosWaoXk9kydveQqFembGFJZuiYCPPezr+uOXKS4EqDiSHGPjoVFd5GwY1i48W74K+D02GHzYEPM9OKCFjwotQGCkwlAVzf+jcwDhzv7jl38vhrbnb4b35ASOhDrJyjSyEunmFaw9dzzceOAEj//YDPPDlGvg8SEKiwvKdx8N5b8E9umPTDEuIMN/70GLODQEqTFl7gMXFc8UiFN6raDadz9SggUoGxurjvVQRAtRjgZfnMs0KIsjT/A1VtASS2biVSXC/4x4Lvl+Fk7fD95G93iradFW9BpXdg3urdBZ7zOegcpAqFKrKZo3kbUUPgm0olEJpaJCSDDeO6AQD2mfDH8/tpjQEYtkD+bmYx4JEFdCwRpmGF0P3OUNXv3ZqA3DMC+TNmTMHbrnlFvavefPmTKH417/+BXPnBrjj6wrkHAs5/IOC/8bHFh+Alw9qy3iI+eTD0CAE8jOjpqlTLFSuQzshQ+exoAIBKjV3frzCcyhUPqHM5YIFWmt4zKeOzUHnjdEpTmjV4IuoHPok/80n3CHiseBMUXbgQrx9KBQ4hEIpciyCXyUl6BePxsQSQdcdO+rb2z9aAU9N2sjYMzhenblVSObWVViWcy/0MZ5hgZlyaPOxj+2bcEU/ge5Ofieq7kSGJ5Wle3S35rD8r+fDpQPaCn3D+8GtkIAbjGxlxEWVtxMt7k4CD26gm/JOwPdrDoSuZSckRyLo1zTdrFjHwlnw200EF+xbujHzvkFB6txnZ8GIJ6fDoRPh0AwmCLnoGySHwLXxJUNPG3f48xer2Xy58+MwcUe81bFAYg4MZcHwRCpoq6y0bkDDi7gArgMXLttmpzMDBgprmw4Wqq8reRcwiZljL6m/IINa9jfsD1y7a8uskMeCehImTFzPQq65IUAGrr33fBp4l6lJidC/feMwUYiSbpbkkpHK21iPCuULZLdS5VsKORbECi6GaofPU60TmBSuMxJiW6n3FNclvpdxD3soFMomhFZluBNZofShULzNOsUCxRnKHkjpeZ+fuokxX1XarME8vBlzJWhkgywfqgyiOBaxz/932yi46/zuITZLoR3FqFhYcyyox4KPDXwOmcr36WC4F6IjyeeoMcXi888/hwsuuAAaNGjAvBWlpYHBUlhYCE8++STUJfBBxDtcttKqPRaiZssFYB7Ow5O4ONewriKkahDahVzoPBbygo+886gYePFYoEJCBUSk/vzrV2vgilfmM65oHZsDZ6BQQSXwNUhNhi7NM63HSs+AXg0eCsW7CYvC/GbMaY7PEvZGuAiF0tSXoK8mXMciqITa7G/UEiGEQmnaQj0RlEUMF8ip68JWRbpeaOtYoHXfxmPBFQvqhmXtJBu2bfiY4jd8JyrBGL0YqER0aJoB/71puFDIyEmBp8Bnkq+PigVnxThUKNImOyGsKNt7LFjxPukY3HjQu8SrhkcLbhLDUcDCSuIy5PfvJRkXxxiNUeaGCNygsD4NUlPS5FQ3eV60PW5ywgxqByqvsXOORVWNhzxtIKE2fhVwTGrlWLknX1mnQd6H0lOTQrkKnDlOhsxIREkj7GhYab0FXmAWKzFzCndK92pXiwCxaNvRUMjQN38YxYRUvu+o5Audx4IK0/sLFDkWmlAonXxC1xkONJTpQr1u/3gFDHp0KlMqMU9i8OPTiBwQuBd/HEo3y6Gy4CtDoWySt+n6pwL2p2rvfXLienhh+ma46IXZtl5jriS3b5LBoln4HHSTvC3LWar5i+2WPeuBHIvw9fG+XDYTappVVkNzouykKRK+3cL3mY8//ji89tprLBwqJSUsSI0cOZIpGnUJ36w64N1jEZwzXIHgGicfEHyAYi0G9rvGqi+z1SCl6sc2Lk/dRq1SIHDR8JJjgYNyHsmT+GL53tBied2bC1ktARXQRecFAXaDDFt+ba6kZUoKGSpodoqfN49FMA9Dl2OhENi4EmDXBBoKRdNGdG2xs7ZTdg7BMyHlVdBjdAIzJsvz0+RQKGoJtDMKqrwuvKKqDPTUcYzs2hz6tBXLs+rCp2TgM8l862iZ47UwcLPyQmGIMdDsujZTA/sJhShZkHpu6ibmXbrtv+7XOLSQXvXafCaos2srjnFDU3njO4tZJXEsEokJ11jvA/8XKAM9eixwfB0uJB6L4PNSq9+2w2JInszCIuMwUVScwivrGzYcKGD/6gLo/PRTIG/ZzqPwztztWkEKaT/9ev6o4EgLoPllZpNzM6gXTgafT7jGDO3c1F6xsDEw4H6KfaPKNaAeeG7lRws0Jzahce6y8iJjyrqA/HLt0A4henYud6jpZtWKBfUk8OfCPlAJmpRulgK9DPx5Ve8eFSCdNwDXNWzv3ydtEGjwMWxIjipQeSzkvEEKuozbeSy4vLRfYhUMX6daCIXi7eEJ/DhXKoP3Uskp1GOBfXh6i4Zs78VQesdQKItiYb0+tkcm4ZFzLEKMihLdLP5Nt/efDGoPNa5YbNy4kRXAk4G1LI4f19cWiGfwOhY0llAGHyyhJB9JseDCI1+AucD2+3O6stANjGH/5rZRGnafagulqgx0y6qg5N1HxUL6Hi0ivxt7uvb6PLEYJ64s7MgUnjpN+uoh7eH2cwN0dyqgQMk9OXZAjVy+Nv7tRpMOKxbgOsfCjhVKDoXSeSxwfKClK3yP8IE654mKgQjd8IjdOsVCYEESP+tkbEqFKHssqNLjhqKXggv4MpwUB/cei2ookjYjtE61IIqFF48FCgl4vJMQXlKGbFPidXkF2aU7j7lK5kbL6O//u5x5A7/IDSjmqtviZic/AyYK8neG99p2KGDFvP2jXJYrggw5v35/iTBu6aauEsLweWjeA44vGm63bMcxRsyAFkOOjcRibOc15dhL2Mw2HyyEf0zbBHM2ixXT6yNQqLrwH3PgRy/OdVUTyC9wXKDXTGdAQKFQR1lKFYMMlwYhXSgUhuY8+u06mLT2QEhh5+MPC30OnzAdfvHuYvADyjCINJqReyxExQLnEoauqOoucOUahfOBHRuzz0gProIdNSyOB2SzOnPCdPh6pWiUU4UDpSYlQKdmmaE5hzWasD91e748P888LVAbyM5YJhsn6RpGlSQufLdtnO5IN0ux9dBJuOb1hazdXsKwKTD/S5ZZQns0T95W9AkNLZKhKgSnVCyCezE3AqmuQ/cEfg0a1lsZ/C7VVrEIKJAf/HoYTLx9tEUeUhkh5f1UpViock4wd5jmWHDvCD6HmNReHTIEPX/NAOjdNqCk+oE3UzNBmzZtYMuWLdC5c2fhe8yvOO0051CVeAS3zNgJPFyo5YNHDoXiA4IPUB4ahRrpsr+ebxlsdHNwY7X0olhgUTHqyXj0sj5w44jObKPA+H0KtJTsOFLE3LLorsNifG4ha9IX9m0NI09vzlyDKqBy0NKFYoELu+wiZIqFTXK9vLDaCckJIIVC2eZYiN/pPBaoYIrWf+dQKJVXCdkf9uWXSIoFaDwWogVFZ0HkHiG0Qsn9StvmhklLDoV6IKcXvDV3Gxw5URaygqRHSbHAx7NSE6PHIjWsWHjwWDw7dRObL5cPsmelOl5cpmTToLVbzu7eQtikn5q8gYWzPXPlAOjYLAPembfddegJbuZ8aKPwPuapGZCSnAg3ntkJRpP74KMiZzyPWaaGEG4hRQ8j/vbD3WcLOT/4He0rVDKoYvH+gh2s/ZScgYaiIHCdGNlV/xz7SGw5CgD/mBZYB7Y+mSMYXnDc4gbeqWmG7ZirK5i05kBoDqKV/YI+gVotFNsOnYC3525new2GoL103SDbMabzXOE7QuH0ptGnhYTLt+duY2P6tx8sY0ayqXeeDTuOnGRCGc73nq0bCYKwbmnE8EsUPq8e0kGRvB34jHsIj61HjxyO/bs/XQk9WmWxglw/bDgYEhJxj6Qx5Dg+Zc/nzI0HWd7daS0aWrxqXKH2oljgO/jZ24vYevX6zwZbwole+mELK9qGe9TmJy4ShDQeCoXf4djknj1Vu+08Fthu7m14YdomIddMpVgwj0UwRPj5aZvYvxevGyQcg/2PnhDsbwwxpWE7NG+OzzPZ3oLygMAKRWSOfQqKWayrhPMdkU42Pbx+yywrLT9fF1FO8e2tkgRjVGBCzI0hg65CsZC88BRiknLgs0ox5zIg7r0qoLdCVVSuWWZYnqkKfodGxkKNt5zXo8A+VPWjap+V1wl8B/ia5ceQc0ySJbrZsGIhPgs+GzeI0OepUcXit7/9Ldx+++3wzjvvsMm2b98+WLBgAdxzzz2s4nZN4ZVXXmFVwPfv3w99+vSBf/zjHzB69Ghf11oddGfZhdrwOEOZlownkvIBwQV9KkxQpQIHBRMCiVDohjtYFwqlSqpD69nQzoEY0bO6NmNKhU6gQ5cvLiC4YY36+wxwCxzYMosWLpA6bZrfv6WiVogMVMrwXfC+4pPCzqPkJRRKzsOw5lhYLcEhj0WiXbVvyvdtbRMFjiPVAnxa80yYs/kw7CbWX1GBoO0UP+ss8dz6jf0nF8zhrnO5zW49FliX4uYxp8HFL82BNXsLXIVa2L0bCtz8aa4Jn1c8BAtDeTIkHnAn/HPGFvbPDmc/PZOxcOgwf+thQbFAyzwmLSOueHU+3Hdhj1AlXISTBQ83fewzPActvkyZKqtkxTf/J1k89fVNABZtPwq5u46HvDPjiYArM43N2nSIUUXrflfVU1mzT8y5eJmxTB2B1346mM1PvnnKWLH7GAzu1JT9jiFdXIDAEA7cQ5DW9LHL+yr52Tkw/npz3gnYcugEM05ccYZ/d3208e2q8DtCDw0qFk9P3gAzNx5iLC4jT2/Gah5RRQ0F3HvG92Bzk1tc8Z1gOOWADgFrufyueR4WFoy7akgHtkbe+M4iFrv+ydKwp2noE4EYdQQucZ/8dgT88t0loe9UceTYDk4XjYr7uJ6t4DARgtFTt3THUbaG82Vm+oY8mLo+MD835hWyfxRoeT+ra/MQK9DP31kMPzmjPdwfZIdDGlhkbOrQtAHMuXcc+26PpoIzCuSXvTwPerRqyPrrsgHt4LQWmayPUVjr2y4QboljjBNh3Pv5KqbQIQZ2aMxYjFCp4EBa+J+dGZ7nXNjCPQyVJFymUODEe6N35oVpm1kIy8e/PRP2BxUHrH0lhyzR3CVqEMQ1nyrzHHi/UV2bwIvEIPepFBaN7+zKV+ez6IGPfjMCBndqYmFOsqNQl4V2qqiplCRasDVN8FgkMMOJDijLyPsaWtz9VCbHdZPfmy91JxWsVXYeCzF5mxNUgN5joVnDZI8FDxygSt2xoIymkoGwHSjoq4owU8hbIyqlP1YYwpBcRZb95DAxuY5FuLismLwdKOockBEasXDuyppXLO69915Wffucc86BkpISFhaVlpbGFIvbbrsNagIff/wx3HHHHUy5OOuss1htjYsuugjWrVvH6mp4xU+Di4s7VqhqQVgLJ28HFYug5kuFTAouLNMBr5osMlQuQIxlvePjXOXxGIKBcLLyc+uHV6DwnyLFBeGEwufDtU0l46Lw1Dg5PNBxUqoKpaHwiAIHein4gMfFKWoeC+kYWSCnf4XrWNgnb+Nz6zwWyiqdzGWsUCyCljvsFxxjOL70dLPuPBZ8wcH+tyt8Z0fRq3oGGgpFlUy3ORROQAFKBkveJqFQbZMbWBZiOfzADz5YoOew30oKy3GBkAPb9CeJxcXJgof0rFcNbg+fKmgq0dOgA83RwTHyKREu0VKLigWOCbRkccVheJemLC4YBUWxjXrlp1+7bCaQrSVCGWMSmRxgEvls2R74+cjOsD6YY4DvhwpQ6CX968Vp8MePVgjzndf7QWD7UOBEyzoeg56TIZ2bwC1nn86US8xtoQoaxmJjAVIc8s9fM5AJl3hfDCtD5QMFQKTpRGvfJf3bsPGLGzHOOVTc8Xhk0eF9h54GPAZj1TEEAylPMd4fnxu9h71aN2KKAbL+dW+dBf+9eThbj/Dd0ppGU9bmsc38laBn+LekFpEcWsfD6848rSkM7NCE0ZsizuvVCi4d2BaW7zwGzTKSoeBYAhSTPDf0GAx4ZAq4AS4RD/1vrWC8osIuhldheCRPJEY8O2UTy4uSrf1XvrYAzunRwtWYQSCjESoW+E6woi8qsvjO77uwJ/NUcQUfw5+4V4AaVCh4rSRUVhCvzwr0HTeY/PvXw2FI56ZCkU7OAoWKUq82WQI9KuKzpaJiwQVH9OziXobCNSrXGPb1bfBaR04eZflN3KOMY0FWLOi85BW88dlQ8FR5WNE7OaxLU3jzxiEh5Q6NBBRoKOAeBGR+nPWnsSHFgid+I7jYIVvl0aNMUUzCJfc7KRbEmobbgKroGo2WoJ6up37SH75dvT/EloneBTc1uRC49/PQXTlSxMljgesejjFl5W1lKFQwx0LjsZBzLPh16ba4L6iU6JLJMWzKyahGf0djCx2fFKlEseDy1lGVx4KEQnHDrJVuNuyxCIS51YJigXjiiSfggQceYIJ8VVUV9O7dO1TDoibw3HPPsUrfN910E/sbvRWTJ09mBfomTJjg6Vpv/Gwwo4ZF0Bj+C/q0Yi5NHnpgqWPBcyyC8Ybcpc+FRV34g+zak2PgdVDFN6NFBqk07eCU8IwW6ysHt2fCgRfLAp4na+b875TERCWLCF6fh7HwBUGlWHCq08zU5JBigQK2l+RtN/kCrkKhqtyFQuH9hHwF8lnlxAnQd1YpFx/cKHDTwLAADGOgXakriqYqJkfZUHj/y94EWpzQjhZX1Z80vpReN1qKhQo4tvgYmh4Mu+DWb6wbgxaXaCgWKvCwQaRlRMEClXJ8T9xS++WtI+F/K/axfClc1NGShtbOYnzPDk4aWalAzxWlc3QCvv8FW8MEDOg9wnF924fLGdUuD0Ec1bU5i8nWhSvKwGH8fz/qxShA1x8oZJsnxthTqzcKWpPXHgiRPmDo5cdLdjMmK1Rqpq0/yP5xvHrDGfC7/yy3jNFrScVcxLT1eUzY1oWBYlw34vKX57H/x/Vsye6HwicNFUCP9D0X9ICrX18YEkwRk+8Yw+6BSoWqyCfFxNWBcCcuMI+Y8AOr04LGDxQkcUPG9QkFW65UIFo1ShPYcJCZBY0HaMHn7cOwIRpfjm3Cf2EkAWxYq20bekRwzbjjvO7s+bBS8PXDOzIL5ePfrbcoCLjG456DybKoQP9iZGchZAnzEqZInkKOGRsDAiL1JstAAQbXtunr85hy+Pv/LA8JkzhucE/FtYN7OBH4O7ZJtR84Ae+FSg/m+I3qFlZ8OHq1aaQM8cAxh8+Kvwv5kcG9G0O0ULHgSgUHekS4cQFrC3ChWQUcG9jfSD5CQwXlHAvE+b1bwXu/HAq/eHeJxRpNvWIYnoXrCvc6NG6gCoUS3w1X9LkQetLGY4FCawuytos5FuF8VL5/4RzgbUFlGesi8boaVw/tAAu3HxEUFveKRXlIUcK1DBUDVYSGKnkbheVUHKNkT+SKgZoVqpJ9r0uYx+uoQqGoF2PfcWviOwVVAN3ss3Y6CJUvcZyiAUqOakEZhM5rfu2i8gqhD7BPuTzLlMYyf4UaI1YsEBkZGTBkyBCoaZSVlcGyZcvgz3/+s/D9+PHjYf78+Z6vNyhIKydPIBwvVHAOueSCscy65O0QK5RmVKgm/kmfoVCUNUMHJ2EcBbUHL+nNlAu0Zv7fV2vgPwpLseo5ZM2cTyhcmFUhsbgA0eRhnfDP+45TzvJz3Xgs3IVCceUDNJW3vSdvWz0W5DdNMR2VxwLHHLq2cQPm40L2TISuIdUxsKNR5eNb7kNRGdKfK3cnhtgJ84NclyaxRxu4WHK6WYq7x/dgiXCrg0qUDBQA/jCuG9wkVQe/Z3x3eGbKJlf3HnF6M6ZYoPA4+qkZLByqb7tGbKPu1CyDrSX4D8Oo0FKOFnO06rNESY+hqxiiSBWLMzo2huXBMCcV0BpM44NRqP98+Z6QQMyFW8zhGdujBbw+e6ujxZlbz9GaiiGfmKuD4U+yEI41b3iSLFrYUMHDfwgM70BGLY5/Xj8ILurXhikrWL/lpesHsXGJYTIqcKWiW8uGcPf47vDIN+u0VkUe34+gU+HNOdvZPxlYONEOnCjgJ2e0Y0IoJsVzTzAKwPd/sTp0LCpsSFH6xMT1bK3C4qG4pqKyjon8GMLSrVXD0JxBQxHO16JgjgJa08d0a86UVmp1t8OFfVrDP64dKOxb6HFBYQ4hW+ipN++Wfy9jnhtOUU6TSLHvZgb7EscKhhvJuGJQO6WHDYHzDOuYYJ9d/+ai0Pe4V+K+eeVr8y0MNigso3KKQMMBDdNT4YtbR8LpzRsyTv6/fLGaKUIYDiZ74hD922dbaudg7iO+E/TmoPcJ10HuaeDvCAU2HlaFS/hvRp8Gr8/exhLoUTDHc2htJRwvKsEXE2PRo8tDCeW5TNfRrqTCsiqPhwPHCW8XTaYOF8hTeyy4EMpJMXBtko2JaCwNhMRYDUV8v0BFqaQ8cM3v/jgaznlmJvvMjQvUi00FbVxPKLW6DGpQwYgGmoyuk5NUoVB8L1R5LPh++vef9GNecRynGGmCyheep8pfwOtQkg3ev2j9d+uxaEwUQHeKhV6GoYYdpPBn71QSulAeofWoOCEOsvtRJQnXWD5ccCz50O3D9/Ry8F133eXJmxBLHD58GCorK6FVq4CXgQP/PnBAnHwcWGuD19tAFBQEBja+toYpAOXlgZeUWE3p9SpCCZUI7szAgXf8ZElo4KUmVrPz+esLC4uB72Xw91xaVh76vaDYeSNBIQCpK/98QXe2UAbu5SwYoGZL2/HiNf3hjx+HQzUSoAoaJAEM7tAIKioq4LaxXWDZjqOwwcETwgqrVYkDOaG6kt1Lp1SlJyGrUXhxUNHxIRKDfUeZodKTEyDRhYsuIXhuFbmPjMqqQDv5vC0rrxD6CMcXR3lF4NiK4HtNSsQ2W5+PPTIZPzhT+TWr6fdBlJSWwwmpMCG7PlSF+q+4NDBGykkxo0pyXRyjHLjo4ZiyA1qZUlj7STOrws9On0oeu+iZ5OjbthG8e+MZwjFpNKcoOCdiAbxum6wUwWL6l4t6QOP0xMB7r1K/d2zz2d2awtndm8OsTQGBqn3jdBjbrRk8M4XMFRsK4L5tsiwhUDwMakinxqFn7tA4IKTx4VuECYceFYtBHRrBx0QHumJQW1vFYuXugEDVKiuNhfCg5e1bheemY+M0SEmohs9/OxyW7jwO364+EBKWaZ9ePqANjO/dCsZ0a8bWha4tMyF3dz5bG1TgAt11Q9oJ7x7/5ooFCg0X9GrBfv/5mR3gp8Pas3vKoWL4PnFtmDApcB6GLb107QAW+jSg3XD4xXvLYKPD+vThTUPZhvv4dxvYM9oBBYEXru4PY7s3h79+vR4+W74XfjO6M9x1XjfWDro5vzt/Jzz5fbiYFMegDtlw4/D20DQjGfq3bwSdm2WyfkNgpEa3Fg0AcN0JrpmZKThfEqBRWiL8+5eD2UbPBczHJ26A9xfsgvG9W8KUdWFlCdGtZSZsPngSPvjlYBjB2ICqoFyjIHZv0UCwJl/UpyXLAUGLMVcquJCC/7IbJEN+kB2Gh0b1bp2lVCxuHtVJq1h0a5EB1wxpz56B45YxXdi7fnnmNotSgbjr41zYFqRavX5oB3hxhkgyIqNXy4zg/pwIL183AJ6avAnenLtDSPjmwHG2QGIceu6qfvCL95ayhOOuD3zPPEmdm2eEjEc4Rjs3C4cDdWvREEZ3bcoUCz4POzRpAA1TEwVGP1RW5DXk75PWM9ZF7mnFtQIVcebJJPsdokVGMsuD479xcHmDexxydwWeB+sU4J7Ktyy+7+Ex+I9f92CwPgW2GYVQVIxKS8uU7FY4ZgLjMwC6Z/D9FesecO9S++xU9ky4nlCkJgdkj0zSR7iu2eHcni3goa494ekpm+HRS3vBC9O3hvZolLtkMIICRe5lSVkZJCckQznZy9H7hIZpriA0z0wJGYZPlpTB0cLikHDN5wEH3r+EFMetrMR5Vw6lZG8uDCo+OvmnUXqS475IT60OyikqUMUH9zHltSQZlIdCoZGayg5HgzlBuA6i/BHJ3u1JscjNFeP40WOAwlePHj3Y35s2bYKkpCQYPHgw1BTksA0VcwMHhkc98sgjlu8zkqthyuRJ5BrhrtmfdwiqqgOLP2LvLkzOTISCohI488npQW6hapg5bQobDMVFuMolsAGK/29YuwYmHg5btDjKywPH/f2zOXBZp8AAX34Y7xEWonM6VMK8vETILxOfBwUAZH15englHC919xoP7NkNEyeK8eJnt0mEWfsDg2zj+nUw8ZjoZv/daQC359lfu7K8DKZNmSy0Yf68ObCV7Z+BZ6QY26YK5s+cGvwrcE5GJYaQWBeFDevXwsSja6C4MDH0+96d22FOGS4y9u06ceIkTJw4EQ6yNUJ97LKlS6FkazXkHw+0c8nSZVC2PTxTd+4K33fVqlWQmbcS1u8JvCOdx6K46CRs3LA+9B7z8g6wdiC2Bs+lmDR5Cmw/Yf1++bKlUHIS750A8xYsgiPrq2Hj8fBxqOjw664+Gv4+7+BBmDHjgG3/nMw/BiuWLRaOmTd3DmwJ7p+XtQZ46WgyXNoxfA+OVWSMnijIh++//174/XBeuM/Wr1kFE/evjInTlLfr1p4AGD7aJgMg8fhamDgxMIb3nVRfe//unTBx4nY4cijczpLiYlgwb07o+C4NK6G4IgF2n1S/5N0bcT6rvTGdy3fBxImip29LXqDPdu07AMuluSwjLakamqQCHCgOHFe4faXwHIXbV8FjgwEWHkwA1OG+3iW2I3cnChoJ0C61GBonAmzMT4RZRHjETaZlA4CNS+fA1uCUwwyDwmPh/mjboCr07GmFe6B8x26YHmTBTi8NHCcbHHpkV8GmfFwJE6BFejVsWjobNkuP2rlhEuw4kQBDGxVYxhVHw+QkOFEROLFi71r2blMTk6B5OsDdPQph45JZwMX5WxXrU9O0ariySxX8e3MiXNGlCg6uXQAoko9IAyhonQidGlZDl6xqmLAiCcrZug7QPrMabu9TyTbpsu1LYcp2gJGpAO37AnQq3wKTJ1mT/ItZ1Fv43m0aVEPz9GpoeGgtTJq0lv2ybi/AOvCPAVUAt/cB6Jy1D1I6JMCKI4mwtygBujaqhp93zIfjrQCObVgEEzc4X6tnViIsPxJ4v7vXLYWC4vDajPN82r5EKAr2+9WdSuGTbYF9h4erFO3DkDlxrLVMr4b1i2dBg6QkKK4UXzb2R+HmJdCxLNxP7TKqoVf5Zph7wLreNU6thuNlCSGlApF5dKPj+kD3bUQ6sxUmC/sNyuZDmlfB4tnTYQtZQ3G07l09H67tkgDvbcKZkcAE7bX7AiGNB/P2w8SJeyGrPHzNtPIC2LxioXCPhlUnYMXS8HdpFScgnXk+xD75Mkg3zYvZleVthfSERCgOvodVK3IhYXd4/2mZlgQ7y9XrRZeG1bCtMAF+WIFjMxFSqsqFORUoNRNoD0oXU6cG9twlOwPzt7oQlcTAePjqu++V+2R1aRGszV0S+n71itxQ3508GdhfL24F8NrRJPhRhyr2d1F+eB3hOH74IPvttHKAM5olwpg2VbB0Me4/eo9204ItcHzjFri5E8DulfPgUHC9XrFyFRzbVm1pKyo969asVO6vGckAe/aG24Vhkv/+8ns4nh+YA0uXLIF8tocmwtLclXBgU/D6FdiJkuy1dBkE9KPAfY4cPcaebece63OfyEcFy/r+Co7kade/0DHBtrF+X70aMvPUVdd5P/RpUgUH9+xUylH79u6FiRN3Q6eGSbDzRAJ0KMXFPJkZGpavXBN+FladPgHSEgL7flGRPq8Pormrz5gxQ/BIZGVlwfvvvw9NmgTCiI4dOwa//OUvfbMyeUHz5s2ZEiN7Jw4ePGjxYnDcf//9gtcFPRYdOnSAVo0zISdnvHDsHQsD5svsJk2ZC29rYcAy0LtHV5i+b5uwkOKCdPGPctjnV7bNhwPFJ6CKveBqGDigP+ScYc3mv31B4Po/7EuEF28ez0KVTqLlZ3N4K3rohnPh7s9Ww1xC/chRVpUAI8aeB+c8iwKRswW/e9cukHNhQAHkWDtlE8zaH5AYBvbvBzlD2mvbqUNmRgO4+Edj4J7FU0NWzvPGjYUOTTLgybWz4ER52Avz2vUD4dxeLUN/N+99FH7YcIglAv70HTE0JdCm/pAzuB3872gubCkIWMsG9OkJFw/vAPcvmW7frkx8p6Ng59EieGLFXOUxw4cNZWEH/96/BLYXHoOBgwbBRX3DDDqzv1wDcDCwGfTp2w9yhraH7TO3Aezeos2xaJTVEPr37QBf7Ajs9u3atIWcnP7s885Z22DiblFIGXfeeYHiSxvEhWP0yDNhbv5G2FtUAAMHD4FxPVpAFoaerF8eGnM5OYExl4LWzI0r2OdmzVvA6DE9AVYE4s1VaNG8OYwd1Q1eWhsOTxg3diwL4+H4bXmlwALCUb36AHywOdDWpk2bQE7OMOH3xd+sh0WHAsm4I4cNEZI8VcBxY+cd0IE/uw4Y7//3VdaQSJy/Oed2hW+Pr4A1xwJW4KyGmXDBeUPgiRWBkJhObVvDK9cPhO9WH4A7PrEu6BefOwpOZO+Bfy/aDU9e3odZ0H/6zhL2jm65eqDl+PKV++HjbavhQHk6vL/Z3r989ZCO8ODFveCL3L1worQSbjyzIzyxIjwHf3r5BSzk5dqg5e3r5+ZY1gXEuDN6sBDCR74NS533nN8NfjmyU4gUgeLrY7mwIT8wx3p0aAnjm2XAjI2H4b7rhgk0h3nzd8ICYqn//djT4PphHVjuBlrAXpu1Hcb1bMHCKWUMHV0Ky3Ydhwt6t9Qaf17cMg9OBK3N11x8PgvFOP/cEmY9VdGyTi5cCRPXhPMAWjdtBH+6YQT8SdW35PPI0SeZEQo9wPj+3BaLoyEReRnrWaL4H87R1wWKFi4oL4cpU6ZCg9POgAEdm0IzGwYcJTocgOXBsXzDZRfCq5tmMaUBrZNP/fp8GPAYrqcBA9ed114As19dCPlB5RFf1VUXjIL3Ni8IeZIwHv8XIztBm+x0eGnLPNgieQi+/OPYEGvb7JPLmXfwjov6Qc7AtlCxcj98uj1sbLv17NNY0ijOJ47/3XomCy+asFK//7x6/UA4j+wnCAyTeXndDyFL7rlD+8K1Q8P72ukHCuGV9QtCa+glP8qBS9CYsq8AVu8tgL9+Hd5/O3VoDzk5fdnn5I574blpW+ChqwdC7zZZ8GjutFDYyJl9ToNrRneGlzfMZmE/f79+MNz16WoodMiNuvHis2HBf1bAsWA/jxs1XJg3iyrXwc7Fe5ThVecN7AJvzNkBB8qwj8uhTfNsyMk5M/R7QXE5/GVpQF7Ddp4//nxWyHjmF2sA9u2DEf17wIJpm1k/nXX2uIDnb7WY79SmRRO4YFwfeH5NYC85a8QweHNjgIQgOysLcnJGss+3EGPulBOrYN1xUSbr1L4d5OT0E+Ygeoj+uc665988qjN7pxgmJq9P644fgr79+kF3DBNbKYZMZmekw5lDe8F7mwL7IMc5557H5srE/BUAR8Jev0dzw6LviDOHwY7Fe2DNsTzo3qsPS/CH1UsgOysD8kk9FQTKCCzEaUPgPo2yA/3+nXR9ROuWzWFroVV269utC+RcJMpiMt7dswh2nQyEuTEZUkONPqtkDcsxfOVXI+C7NQdgyl5rzlznTh0gJ6cPnH9BgPUJc1qfXzONeUebtz8NYFfA4MwNLc0bBWSnI0ecQ+yjnmPx7LPPwpQpU0JKBQI/Y0VuzHO4++67IZZITU1lnhHUxH/84x+Hvse/L7vsMuU5yFqF/2Tg5kCrh1PgXM7C2J0gGqSpj+PncxYoLiylp6Yor42Jdjxus7I6EQpKq+DDJeG4RESjjHRoky2y3VCszwu4Mt0gLSXZ0o50UiApTdNODkzEeuLH/VhBLppEyZK3U1KYsMIVi4y0QH/KSd0DOjUV7nFWt1bsH8aBq5CeGmhzQyJQZDVIhcx053gSXOjw3DSbZ0pJDlyfx4smJCYJ7UtIIAnNyH6VkhL6Tp9jkQip5BrJyYHzAp+twktiUhJUBCc0RYO0VEgNHo8bIF4jMTF8PnZ1cnIye85E0s/VwWva4URZJTRsIPah/P51YwH7LPysgXZRZFJauwaptmMKgUo7dVO7hdN18XlUyEwPtAkZWDiSsK5HelhQw37HY7Izwn2EIRJ8rrVv1hD+8qPecO2wTiF6y8V/OY/FJKsoBhsGr+0UL87XF7z3NcPE+kAcWRlhd3fnFvrlu1PzhgKjC59PmdJ756BKZKOMVPjrJX3hryhxSeglVU9vkpkG7ZoG4sFbZqfAg5cGBDEV2jZNgbbBY3Wg8cTNGgUU3fbN9O/6qasGwrGipaEiahhn7TQ2ED3bWqlcveLJKwZATQK7Zlyv1q6eT8aPBrSDZbvzWWw9joFHLuvLiDqeuLwvpKelsv0IE7Ix5yAjPU2ofYLfNW4YHksDOzZl+TYcLbLSLYoFjtOU4P7yz+vPYGFDaMTB9YrOK8TVQzvCxDX7hVCiAR2bCfSwMkZ3aw4X9bcKW41TUqB7q6wQpW/rxhlCf/Vu14QJmmi1xj2N/zawUzPo074JPPrd+tDeTfdMnI90TqIizfOVurXKgpbZmTD73nNYSA3mHdDcBBndWzWEHw9qD6e1zBZC+Yaf3kJYPwZ2aAr/DSoWyG7G85cwlKVve5S7doQ8Svi+6HOmBQ0MfK9ga15KSmjvbtEonRGhoKBZWpUA+SXWNRj33caZ4fUmI43kRSrWfoTquTPSrLKHbl8+o1NT1g8yQmGICYmgaGogbIus4aF2JgXWctxDdWQDKckp0IDXdqjChPbA7w1UBSRxDyZrFKp6eH1VfdZ0DXlJUxt5k4OyiSYnWfuP49mrB4bCJ1OT1cQTKcH9DC+BcxvBCUWOKhLosa/5eKnxytto7c/LszJGoMegsFBdpTLaQO/DW2+9xWpprF+/Hu68807YtWsX3HLLLZ6u0zJLb/3BRB9dcqoKcrIwrQ9A8cGvhgmVl696bYHArR24VyKzCOnAubnlZNrbzrFWr1LFs9Ln0rFXfXrLCLaI4+aAnNk0SY2yCWHyt3wtWcjS0ZjqEqz5YoILMRVE3RTT4kuHXfJ2gswKZUneVtWxsGeFsqObVSZvV6npGvE5efJXWXCjk9sXSkyrFr9zqiiN1iw5md9tTQl6mMrqTIsouWGF0iW4RQrd8/D6HXThxvdCBWvezzS3BwtXoTCFidrI6oHCA1cqQgKthgVErh5vBx2TiArY/8jkg7kHl5DiW7xirlzvReWBUt03M1WvsMhJpXaUkzUBFOR+eVZnT4wrpyJwLX30sr6hgnqYwI17EKcZ/9tP+jOyAazNINdEwBwVuj9gzQYKlbeHClXoacJ5w9cLzqDIgQJuX6KwIrEAx4vXDmIW7H/9WvSM6uLXEciExUHZBxG4d0y962y4YXhH+EuwjgYHzl8U4GWWJhVaE4MfPwcLneG64LSuoYHud2MDXq5hnQMKGtabktcPur5gXhIHJtjzAmu6cU/3mrIqgHu/WAOfL9sTStDGdobyCggLF203GiaaZFrrH9glFGcq1g6VgK3bw3WeQ6fk7QBbpPXc8B4Z+P9KRd0b3Cv4uRO+3xAi9lDVy0Kad5EVKvC/iv0yVTMGshXsVZY2CQVrHQyowXGjlaMUF+AeTxVBxHFFfZsa81iglwDDntBzceaZgcVo4cKF8Kc//QmuuOIKqAlcc801zF3z6KOPsgJ5ffv2ZbFhnTrpi1qp0MpGeGeKBRkgqsGGi5RuwugWQFzouRUUJ4qKUhKvRRcwGciMIgPZHVSTU1Xpkw581eDjrDT/+vXw0N+ycBt6PvKYvL/kZ9ctJro+Sgl+j9z4nLGHFqKxA1cE3LFCqan56KPyn0J1LGwL5IXvSddfVVuwKI2qvgEmvPEFg1eClQv6oAKRrKgQ7sQKhTG+qT4VC6pMqE6hTFBuwkvsCinKQAujXAVaB93Gx9tEZQYcl1SwpsUYOVARwwJjfuAlzMaOvU3128OX9oGHLultWQvQ0ymzg6TZ9DUdD3YF6pAdidanoUw00UC/9tkham+3oEJVtgvGFQMrsGAXKh4q5hoUnKmRoGWjNNtxiUqI3XpCBVT+Nxqv0CD26qytQiEwLML21s+HBnMnw+OOJtLLuGF4J8YMhgxTSNMtA/cQFO6d1hi7tQkLGHJQZcSNgYD25d+v7A9fLN8DvxkTUPgokD0MjRLYDvTcfLea1+NIsyh3VBFE0O0ccze/3LGP5Xhwummc73yenyCKxcD2jVmYEuKP47oxgXvaXWez/qf9oRN2ZaVRpu93Wp+5YmY5nlDCcyZOTseO6NO2kXJ9RJanHYdPhtb0wZ2bsDXrrblhdjh8LNW5KoUI9QfMzeGoUtDNcqREQjdLTrVjhaJwYiCl4KycKrkQi3lGCt+7wmuvvcaK4f30pz8NZY9jaAbWlcBK2DWFW2+9lf2LBK2lhZICOY/phixXmUZr+uOX99W+XJ3Azi2IqFiMe3aWZVF66spAXD71WOho7J67egArFIVAYQIVFhm88Ilu4Os8KzJkmTUURiS1X76+H48Ft7yjxevr286CWRsPMdpDL7AvkCceY6GWEwR2d3SzeC2xijVVMjQeCwXdbCq6cIP9x60hbjwWuNCpKorGwmOh6luvBfK8eCy8HKt7Hr5ZCB6LRNFjp/JYeFGAZDj1A53XqmfE9eWRb9bC6z9Tk2LguBLoghMCoRoyHatd/9HfGtpUMUeBDjclLoioBIlI8EBOL7aGXjPUfYFTGn5hPBbRARVUMbQI1+B3fjGErUuywCWvJXZ1cKyW74CxDs/BGiO3jeuqFOjw98zUAE2tnYcdgXPh3V8MddUWXWFSJ+WFGoNUNKd2c40aGtAbhBTZKuCaM//P49g6j0oSByoW6LWgihalb2dtJ+vb9sJwH3ALdRpRLIpKK0PzeRQqeOO6MqWmdVD24F5KXgzQbi+XlUaVzGR3vs67G6bPDdPyI3UwVyzQAKpSYP74UW6IkpdfR36vuI8xKnC53YpxyOpoKOQCHj5HKWrTtHSz3upYuB3DOsOtai/kBlq5AjwWaNUV4/OC5EjqV2DFa1Qitm7dyjTarl27sqTZuga78uoo1Il1LBItE4m+eHnC2AnsNGyEAnnaLw9abfjkVl2bo1vLLGHBowvXTaO6sHoUWMRJBvXEuA3BkJUWlcAVKpAnPXuSpi90yhed7Fgdl1fIdQM3oVB88uoL5Oldqrq5Lnss6DtTPT6rvK0IhcJq5ui1UPFuW9ok1bGQj5OBbng5LMYutMALvzZdjF0pFh4Edi/Cve55eJvopfAd0TnMu5Na7iNRLHSxtnRO2SkWPz2zE1w1pL1tGCZ9XFzPcPOU1yo7bwgKjE5WQxpewgURVUJ1JMCE36euHBCBx8KEQkUD2USx6NE6IFiO66kmRcGQna9IRXAnUGUUxxqde3ZzBRUQLgfZGez8KBQcNC/JLhRKJUBT2Ck+XkIjea4LXYtwj8f1CBUMbnHu1CxTux5sKbC2hXksgu3AKtl8PqPAOaZ7C0fBVde/Km+nOhQKPIZCQWivKwnuhzQME8NUVY56qlRweUzeG3C/vmxgW5ix8aAQGqQMhWL8veLf/1m0kxXL5OOiIBh2rq1joagQLkM2FEXdYxEMcZOLFHLChUgRcYAzKhL9+/eHAQMG1EmlAtFaUWhLDIUiC5+0ucuTRp4wdgugbhGlk5N6LFQhLlgttHtw4UdgDCWVK9EKtOrh8UIBQI40Hx6LBy/p4zho+XfJbj0WmnurQoTcgveB7p7KUCjbHAv+XeB/3VWZRURTbE7VV6zyttJjkRj2WPBQKEuxHms70XBil2Px4MW94fZzu1kEejd5K/LzqLqWXtZNgTwvXgi7zdprDC/1WMjHhkgISPudlLVIQqHEkCv1sU65XVTJ42uGfI57j4WTYhFeL6MdCuUH1GOhEgYMvIOOJ0xOtsONIzrDLWe7Z8ai48uL+E/XrEgUfTtgbpKbe9yf05Mlwv/tCnVIFSfeUMGNwcVOVuBWehoO1SVYe4ODkXoEO7dAQVmbpgmFsgs1FuL+E9wrTarv9DlwGsWC5EHyfFGUfbC9mH+C78KpCLAqooB/N7Jrc1j8wHmQ06+1QyiUWCAP66U8gOyRirGdqmmPm7w0twXydOc4KRyqKuWqnCS/8DQ7MTHaC/buFVmO4hVyvCIFurioNU+2AsqDz23ytjzwKG0evQa1wMnjBifS97ePFgQItPLT5CI8RrdAUoXJyQJEXbdz7j0nfI3g86ksGCrLgBdN2w8NqQz7xCfJGiIJj7RwH/62aNsReG1WoFBPos39dG5MVR/hQqX2WITfG+8HuX2YnxH4Xmyz7HmhOLtHiwDrgzQuk33lWFjPoU2MZigU3kpXjVYFnUKp81ioFYvwJqGKoXWLDEePhfNm5ASqHLUJWl0tyds2wo7bHAvZqhUPigX1ovqzUxvIoGuSkyCEY+fPF/V03YluBEDdffwYGbygfeMMV6FQXVtmMRaoa4epQ/bs2ufkwdTh/ot6sj2URx9Q2aBLc+vaaOetx7VAlbxtp1g4GckQKvsLZRCLPBQqnLzdomEqzPrTWJh0xxi2L7kZV4zJUDZ4kmeha74qhAv3YDu5hK6dqTIrZofGTH6S2focSVLAHXSypl0olAy5Mr1feJrhQ4cOhZtvvhkWs+ImauTn58Obb77JEqm/+OILqAuwixOWPRby5ixv3rKwZSew0QWGhjxROlecMFec0Y5p5N/8YRRLLlOzXwQ2+yGd0SVIKmTaaLtuWKGczrNbvOQJrNOo5WsMaJ/Nair8ZLCVwcEtqoP+SvtQKPH+skBOF0lc0K55A4sggWMolJhjIf6m9FiU23sswqFQ0rkSUxW/nl3ydmZw4ZTHhfscC/cuWjdWRbeWR5xHf7qgJ1w9pD389+bhzu10yLFIduGxoH3Cmbli4bHIIDkNfoUu+ghc4JA3Njulhd4X61+4VZSyNPTbNQkn5d3AO64b3oGtwXec5z2R0+kN+H1HfnICvaJVdlhpLlTkJboFnU9URsB56neO//bs02H1w+NhdLdAqFIp8XRjbQIZdpbuQPJ2sNAp5lgUBRQLu/oodt5/OwMMlVn8skLRPZorFijEYygmX9fsWO9C95Xy0eRxRRUbNSuUw/5q47H46taRMPXOMa6MRyIBTPQ9Fqq8IESzzOiEQnkyNyGl65NPPgkXXngh47gdMmQItG3bFtLT01lxvHXr1sHatWvZ95h7cdFFF0FdgN2Lw4kiJG/LHgtJ0bAkb9sITnSBoZoyK9BC8NzVA0MVxVE7xySqqevyBMXi89+NgA8X74Zfj+oC+cVlrmI5qeBh104ZdFHnApqqC+XF363H4v8u7s2SsSIBl7Xtk7eDoVDB+8sLBhXYN+wX2YgSbBcuong50c1ijoUiIZ/xUgf7L6RYSO3j7RU9K/ahUDqh0c2m4SZ526v47VahxbGDArPb+Hutqz04J+xogFX9x5m5/MBJkMiMhseCxqkH1yRuxePjy+7a9D04eSzoGhgvoUcYFoE8/+f1VucBGHgDUqfO+lPYMx0reFkv3LAYRgpqOFRRcboFFVZRWNt7vDjkMY1E+aVyAmV9U13TzliEez+f50jmwY2ZOoHT6XocSElPgYnAyrZp+kCXc8evgftbYVCxkA3Cbj0WsrxB1z7BY6EJhSq3YUehHtxUyQCLz+BWIfZiwHOaE4m14LHwpFg0bdoUnnnmGVYED2ld58yZAzt27IDi4mJWCfuGG26ACy64gHkr6gvQ7WVXxyLNKRTKpccCP0+/+2xYt6+AcX7LoJMTucd/NaqL8Dsmb3F3NDJGTLlzDKOGtANN3nYbCsPOc7moWz0W6uPkPnMbU+gGiZ5yLMTfqRw/ZZ1YTdTWY6GxNqjO0XksqMs2mqxQdOGkDBZ+PBaq5/EqaJ55WjNYuC1Ab2gHr4KEp1Ao6dmpohaNUCgcA3hfziFvp+xFRbEg74AqFvbJ28Rj4ZC8Tde8ePEQfPX7kSz2muZ/GNQv1EQoFIWKitMt6HxCYS2kWHis8G6H+y7sCTe+s5jVsvFqLMKQ7obBeb7nWKBteLgdYxEVUHW2K2TVmvjH0eyZkXGol4Lul11L0zbdesK7E/e8fK4EWZiwAnkldmzreJ1klx4LlQcE92BkCtXBTY6FG/jJsdDZhpUeC22ORS14LDjQQ4G1KmqqXkVtAMNxVu7Jhwv7tLatYyFv1pZQKNtYS3FAIx+2ihPbD5AiMFbJcDQ0jIccKY+TQoJ0i4YsNLoVcl0lb9sVyOP3S1ALlPRvuYid7qq4mIuMDgkOdSzCigUVAhF83JVXWBUIMalbzAWx81jQNmC/c6XFrYBID1Odk9OvDXyyZA8MP82dxwkZqnAxPpBfInCL27XbDVTHt2qUFkpsdpO8HS3Fgs9vrWJBBHn/oVAJytwWtjk6sJQEfktynbwdj8xLaPBJaxg9oc2gZqBS4qPtYfeKn4/oBO8v2BkRnz+VGWh4UTQVC2RvWnj/uaHaFDLousarjdO+xIrYlEYW57Vdv1JFxe6t9W7byJFt06vDid8b97fjwYgMWQkKeGj16yy7TmKi5RmpjOYUClUhJW+7DYWq9kj+IcgQLvuK7mlO3+s8FjqFwytqP/MuTvHOL4bC92sOwKUD28KnS/fY5Fg4eSzsQqEoxWPNb4qCa9mDBYg+E58vCQ7H2QmG8m9uw3LcwE4eTXQMhdKfq2tioqXyNtj2AS6UXGnBRam0Irz4W3IspAadLK20fI9KhVsGI3znCvruiFy0OKY//E2gYKYb4PFYDfjTpbvt2xqhYoFVhTHpkStDYvK2eK7KIBUpkYBdwmY0ciwENi6qWLiklKbz3ynHAulvv1m5D8b3CTOoGBhweFm+/YZCxYoVihedvPuCHhFVlafta0ri1v0wQtmB5mbarYHI9iMoFsmJoXo1u48VuSo+S6/nVVC2u5Yb8HUb92getkUpkaknxlaxYJWqJY8FkVOckrcrK6th4Xa9h50aZVLIGPDaW26ofWVoizG7CIVCoxvmMEbiZRHuGZWr1EMg8wluoAj6Wiw5FtLf1sQgdx4Lv0wRkUBI3vZgQqDPZLe+6ArFWY6TQ6GiuGfYTUr+E2WcoLAT0Gn1TTuPhVMSFmOFCibhoUB3lBRg50KhyjOBKCwt14RCuVvG/HiG/Lho3cBJUPDaVvnw//tRb2HRFAvkiQer+o97dvzCzguQKXgs/K0DCTahUKHPNmFq1L3vlGOBlk3M9TIwqEkIHvYoeLXt5lIkSoWKDIF7oxs4hBlGE3R9lpOyA6xQKUKuhl3itny9SOHVeMjXaNyjjwfpdnmND4pWWelM8cD1lhdTpMBlX7bgU+8SNaqoZLLZmw/Bkh2BmhVeQqGqPWoWTrmMynM0c0L1PT4bGrP5u//VWV3gygjIciz3jNqV6jHoe5E1OiePhZ1ARM+tFY+FT5YNKsTYhkKRCWxnccaBT+dONBLz3FhU5BwL+RS7S9jli9D22xVP5EIsD3/KSElWKnA6VijO5y2GQqlDeaLhBfC74LmBk+Lgta1OrFciJ3uCoxUw0lAoyo8vQ/AqRCEUisYG0+dOI7TZMjh1sdweA4NYYGCHQLHTywYGCsF697DH9xilxjfcD3itlQY1SHZAu0hOysX28SJpbsNgBI9FhG1zWzdJvvfrs7aFDG2qfJBXfnoG/PvXw6GzVNfDzmNB9xYxeTsRnvhxX6EkwfbDAe9O91YNXdQkSvTwhNZ2crjtKS8eC/l9RyP8nCK+Z2ecgAopuEjQlyBXz5aFxxTXrFC1EQpFnstnMlwoFEpVx4J6LDwIjm72jGi4lLn874YVSobuafBauqqZqufCmE2+UMoF5fjY+SJ3L/xvxV6LR+VESLEIf4fPoGr3OT1awOK/nOsqJtMOTsnofuGUjKkrougW8vCjY5O/L9yQxvduBY9dZiWfiFSJatekgSuBKRqhUHRuJJCRaqe08DEYTwnZBvU71PiZqwbAXy/u5focv/TotQExfzHAaBeLUCg7UFmEJuXiXotzXA6HcWIEomtohJFQnj0W8uHYpyqZCXNUR3VrbpNvIBr+AtdSy2H4rm4Y3gk2Pn4hXNi3tUBBrPNoUaaq5AgMpFReirRAnk5poO+/VhWLwsJCuOeee6Bnz56MBer000+HnJwceOKJJ2DDhg1wKgAHNJ0UMnNAok+PRW2EQtHJ5yUUKtr1LuTf3UykT347wvZ3N+seF7oo44RwDR85Frjf6Z5FGQrFCu4EhLqeUsI97b/bP1phCdHhrl7qncHPKuP6iNObQUspmS6ePBZOi3CkXiy574WQruBD4Yb0xo1DBI/FS9cNYiECr95wRkT3b99EbUGT33N0WKEoaxO4Uywi9MgYGDz5435s7Xv1p4MdOwOFGgy9oBZib3Sz8a1Y0PAanN+NggKnl+eNFNQYQysqV2uqLzvlWETT4ODZYyHdO7tBqm17dHpnksLwJxbIs8pkGDbG11ceXaCrfcbzVhCRONXEfdbdOTrjsNZjQd53tOeTp1F+4403Qm5uLvz2t7+FFi1aQFFREdx7772wc+dOePDBB+Hiiy+GV199ldW2qE+gfY6Dmck4lZocC9ljYSMQiaFQNZ/uQlvq22Nh8xu1KjlZKAKCY5Vr7blf+2z45/WD4Lb/5qrb5UKz4Lfhi4Zs6Y+KxyLRORSKW4uvHdaBUQUjBasq2ZZTFsqKhVAgT8MKpVIC/FgpdN6YSOE0/qJtURE8ZDZj85IBbeHi/m0i3lTb23gsaFiHXYK1nxwLt304plsLeGrSRqGKtYGBF2BdJVQWopUAWpdDoeQwYx4KlV5rHgur0iDnKNAkcydEGgoVCUuSG+gMUQEadxqpIR5H5TCakyYPNyzMp0ImOT8hgj0jmgXytB4LkvzuJ3rBDp6k2SlTpsC8efNg4MCBoe8eeOAB+OabbyA5OZl5LrA699y5c6FLF7HOQp2GHK+tKEYV+k2O37MRmGjYQ026SDmikddgt0DQSZsYZY8FOydCYS9UIC+KigW2yQsrFHpJeFVn3HTuuaCHktYXgQXAKApKFMnb1erkY6dQtdpO3nb2WETZVatJsI+Vpa5dY71iQeGmeqwK9FX6EV76tstm/POcjtfAwA9ipVSwa9elUCjJY8FDoWoy5JmucdlEEOZ7NrYRC7rxXD23a1TwIhG1DUOJ+rfPZpdZvTff8Xh5r+FFgHXQrely5W2ZBEDlsWDnScfpyDjo90kR7Bv+CuR5UyxoeG609XRPl2vVqhWcPEloawg6duwIr7/+Ovz+97+H22+/HeoT5NdCB5kledshaVQnRNRGjgWNu/S7UNutL3TSOnss3At6bpQVu6Ty0PkJEuOEFA3ih27W6mqllgdQKxZBVih5U5bzc2TF4oQqeVuTY6HqKj9eAKc6FnXFY0FvF00FyU8oFFXO/Xos6Fzwa6RA/nm7yrsGBrWJmqKbjbrHIjHMMhXNOhZOoHsuDd2p1oQ/dWjqXrGIRvL2V7eeBf/7/Vnw7FUD2Hd/yempP15ao53ov3X7BS08K4esyXKYUDlbuj8PbZOhI87wClWorhN099MpHJ2bZcaHxwIVhl/96lfwySefwIABgcEgA6tvP/nkk1CfIMsdAtOKI92sTfI2+a0mFxzKYIAVunHg+XUt8+mtGrrJPnMs3E7ISD0WYVaowN+yQF7tMxRKpNl18FiwHIugBUl6B/LYOXyiTB0KVSUVyFNoRCrh2U9ejR9Lihs4KbbR9lgkCWMTYg5VKIIKfhV8XShUTShNBgY1gZoqkBcNpEhtxcKhi7cfhfN7t6qxNtD9Bj0THHRbo1ETdsaPWIALzD8Z3B7O693KtvCm19dtp1jQvUT2lOuotuX9h/YnBe3PxMQohUL5OEf8Xt15nZtnxkeOBSoWeXl5MHjwYDjvvPPg8ssvh6qqKmFT+/DDD1lid32CpZq2jcdCtlC7FZJrIxTKbYVuN8Cch5kbDwlKGF1cnWRYX6FQdh4LFyYVfhu+AMghRL7oZuXK2w5em0AoVJXSY+FkvQ7TzYrXc+ux8LPwOXlgYhUKFX2PhXdFNhLgGrnk/nPgp69Mh435+mf16wUSCCVIeKbRKwzqpceiTiVvJzDyjMl31mztl73Hwjl5rTTVuXmRVYSdYC8jUlYoGU73lveqB3Ls2cR0gjLuX9TwJxtyhPD0VO+hUIJikQC+4UT64k2xUB/fqVlYkXRLUe8WntV+9EYsWLAAsrOz4e6774bi4mLo27cvy6lo1qwZPPbYY/D0009DfQImcGL8IS8gInDGS8IgHbROWiAVAGtLsYgU3Kr/1JX9WXXj728f7St5m/ZpclRCoVycz6sw+yqQB67p7ELnKPoAvRV8UsseCp23iy9qqlAo/Kgi+FHmWNSlOhZRtlCKeTA1I6Q0zkiBjg1js0nTR6gNhjkDg5r2AsQzxHyQ2mnruF4t2bpwWadKVvBXhaIyaxE5N3ATahxN0DX6soFt4abRXXzJBiw6I1H/bnCffPSyPvDHc7sx6lqd/KJL3qZGnaSIcizUn6PpsWhBxsQ+iRgmUviiIsIE7Y8//hjKyspg+fLlsGnTJigoKGCeinHjxkHLli2hPgEFuTn3nhMarEkuPRZOVliqJEbiNqtN8EdomZUOj0r8/37yJjzFFEacvA1i8raljoXzuU7JYVRoVPVBSXnYYmTNsUjQWncwDKowxAoFvlih/CRvi3UsojdmnTbf2kzejibOb1cFKU3awMQ1eVHdpCuINkktbcZjYVBfILJCxfd+KdSIqqW9HXMX7hvfDZbMma49pqS8btBM072+U9MMx73HLpFZMP4qxtGNIzpbvrN4LDShUKkxCIVKdLmIey2QR/tQFwLmFxFdLTU1Fc4880z2r76DDhIqt2VKNLFUPvLisairsHsELzkWdO64T9721y5LjkXwfu8v2Mna/NeLewev4cdjIb53eg2V7EwVC1mR0DGsIHUhUs+eKC233APHlIoVSpm87UPq9GNJcQO6wI/q2hzmbjlcY3SzNZmHgDTnL1wzACaumRL6LhrLAOdXl4t20gJ5Bgb1JxQq3j0WSbXuscC9DOnL7fD8NQPhd/9ZBg9f0sfTtWtadKHylxvmMS0rlOyxcDmOknzkWESCmiiQh/jgV8Ng6ro8uG5YRx+ttGlLVK92iuBAQUnoc0tp4lJhzcmq0rWluix8XUK1S3ew0+QQFIuo0M06r3z8dHqdt+dud+Wx0M1VuY4FXYBVVhbBY+EyFIozUhQqWaHU8ZLRqmMRK7pZusAP6tgY5v95HIwI1vOoTx4LFc7q2jxiqk5a4C7ew0QMDPwg1SY2Pt5AqcLj2buCFaVXPTQefj7SaqWPK8WCdGEkigWGnAs5FhKlu/Z6FlYoTSgUIc6ojCBvgTbf7TbrtUAeYkz3FvDY5X2jTh5U81XZ6hlkdxf922mDx0Joz1w1oG4rGDYrjFhgxkGxIJZVt8aoSAXCUI6F5n5+61jQdtG1RaUIFQcVC9woZcXDzmMh5liEf8MwKFW7VYuTH0tarFihaP0X7L+2jRtI4yexTidvx7qGBC+yKKOORlgaGNSfAnlx7l3R5QvYoaZjLega7YaSW7emN26QAoXB+k9e3o0s5+lCh2jbylTJjj72J7eKhc7QWhth9vE94uMcXQhdF4dIZeb8QjEhfGCHxlBXYbfA0IR0L8KbW49FYpRYoXTxmk45Fj8d3oF97tk6S8yxINejQr6qD4rLqrRCvk7w527YimDVbpluVs0KlRDXdSxSFPPGT0J/LGNYY4lIa0joFIuxPVp6ZnwxMIj/8KLan7N2EGolxHlba6JydqSga7Rce0IF1X6BNNwBOvhEz3WD5FeYqbHw02tXOtTasAPdWyNlyayNHB/jsYgAlDVA7bGofwsKpSrbeaSIuVJ1EOjavIRCRSF52xMrlOZ+TjkWD1zUA64d1gkOnSiFX767JHDNxAQxH4eeo7hNiaY4nt2GRKnukNVDZoVChUOGyjDTJCOlRmI/3YAuyHJFdFVF+0gh1k2BOg+dYnHrOadD28bpMKpbixpvk4FBNEHXw3j3AqTVoWJ+dQF0L3DnsUjUemYEI5bLfUWWETLIHty7TSPo1y4bxvcRa5RUYFyyT0STfr82PPJGsfABrFZ59GQZXDUkQD+rE3bjPcEsEnzxu5GwZMcxOLdXy6h4LOivkfI22+HF6wbBHz/MVdLNcqAHAAVoO6MMnoLCMIaxzNl8KNwmue0OHouSMh4KZR0rugUUv8d/6Go9WVZp8axUKCwlqsXp/pxesONIEdwwvGNcJW+rrh/1Aj4O9UXqGnRud6Q/vGZodBPzDAxqv/J2fM9ZoYZTPVhfajvHgm6F7nIs9J5+X8V4JVmOyjbIEPX3K/tbzqmIIMdCVCy8n0NRG0q4USx84Js/jIJNeYVwTjDMgMLPoK2LQF5sO2+FTMXrJLz5CauxO6VXmyxnBUZzHWTYQW+L2xwLwbIuzWG3ORYqJUJn6cJxlZGWBGVFVVBUKnosZOrRUHsV927VKB2++v1Z4DvHIorjW8WkJfZrdOeS4HmpB/NU57EwMKgvqFM5FqStNV3zoT7CrnaYW2GaeyxU3nEn0OGGIVV0P5KV3B8PagdLdx6Fc3v6r7LuJ+TYa4G8WCK+Z2ecAovlqZQKS1x4nC9+sQZVLJyUZj+inW4iIXXac1cP9B0KxZmaZIGdWilEDwu5pnQteo0EO8VCsVjq3LR4ncwgzXFRWaXFelSqUCyiJTsLCx5ED3Qj4M9Dx4zxWNjjJ8HinQPqcL6WgYEdqEBZW7Uh3IIaheKFVZ4X+L1plH1xOTeoaWVJSN72yQrF2RSpIuB2FFG5LlMqMSAbAJ+/ZiDMuueciJiWqBEyVgXyYgnjsYh2h3qovF3fQSeWo8XZR1fpvCATrujn6vyERHXbth46AYMzmlg2BKycXJxfaVuB2hJW5bJAnspjoaugjJfJCPbtSSnHgoZXiedEZywmxqxAnjUvhV4/2otjrDwvXhGtLhzauSkr4oleKAOD+ggqwEVCzVwToOtZvNSrevLH/eCaoR2iQhZT83SzNMfCWWBX7bWqUCjXjEs2RZFV3pHECPcUsY2R5ZzWhhwa37OzDkL0WJziioVg4XefY+EWfiZvteJdyRP3ytcWwJtztlk2hMYZqbYhVaoFjVp21KFQVVo+bdxIJ98xBr79wyhrKFRQsSgqrbS0E70YMqK1toiKRXSuGbgWDYWy3ivqHguJ3ra2EM346w5NM+Je4DIwiIZiEe9GO2E9g/gArg1ogKiLyeR0r/ebX5OVxpO3vT8/3SNkTwStsh4tJETVY1Hzc8V4LKIMIfauHidve1UsnDid/Vi/I026TbC5zpMTNzDmK5kD2yn8SRYUxQJ51jZw74IuUbtHkMoWb8G9H9hXGUF3bMBjIZ5TQHi6w/eOlscCYg6ujNF7RT3HwsbLVJOoD4njBgY1gboaZpyeHN3iY/GAGq9jQT0WLownquJ0nM6b7td+QqEwxyLWydFJmogIO+j2+NpQLOrO7KwjiKfCW/EUE1vupFj4uL6vOgwRFMhrkpmiuY6+TbTGhLKORahAnv1UpIspXiYzLbBZFSMrlLSIHi8qj5llPJrhTzrUhMdCYN2oB6FQBgb1HXSaxjsrFOK+C3vCFWe0g+FdmkJ9Q83XsQBPigUlMPnd2NOhY9MM+M2Y0yzH+UmMRqY9ilh4gJJ8hGu5uVZNwXgsogwxFu/U1tuowBYL1ppIBULHAnlSk4VQKJrEbBOvT5df2xwLh8USF6+SYNhUouCxsIZC5RerFAuoOx6L4PMItU2SYkk3C7WG+khFaWAQC9B1Nt7rWHCBtr6ipj0WdF91wwpFqV5RwcN/Ed3fxmMRCyU3wUeBPB1Mgbx6ACo8NjLVbl0rFn7mDvUO3Ty6C8zZfBiuHRqohu0GujoWOquMEAqly7HwGAp1sLDUVdEfXEwLlTkW1lAotWKRUOcE4Vh6LGJJZesFrbNNsrWBgRtgoce65LEwiFEolIvkbVUolAoJfgzGNeyxSIxwzzUei3oAqlk3CvImG7jIsfARDEWNVsiGM+mOMd7OT7CfePLa1ETjsbCvY2GfvM3h5LGgigdehnssisqtHgtVKFS09AH6rLHyhlcrQ8wSY5a8XRuhUP+9eTj8Y+pmePzHfWv83gYGdRG45i28/1y2XtdESKaBDWqaFYos/yqiE7/F6dwOI2rYSpNzLGKg5CZFkSTFKBb1AHRANGpgIs1qymPhFqoQJp1gKQvs2Rm6HAu75G11jgVNxvaeY5EQyrFAj4Us4PO8jdjkWEDMwZ+H9ldMPRa1IKSMPL05+2dgYOAexsN3aoZCUUXSybvvxWPh1meRaOOxcNOeyOQUiAgmebsegI4x47GAmOZYRDph+Om6y8hrEw2FokuJkAtgKZDnLkbYTY5F6B4OORYq1KVQKP48Yh2L2OVY1IfK2wYGBgb1FZWV1d6St6PssaDGp7SUOhYKlWCSt+s8aMiGybHw4rFIqIXkbfsciwope1ufvA1aAXhI5ybK39jnSn8ei0AoVNBjUVbhKkyoLiVvywWNYs0KZShfDQwMDOKXFYoqCu7oZqNryKRbLE/evnFEJ/h65T64cWSnqN7LKQrCDfCUywa0haz0lFqhZq6zsTqdO3eGnTt3Ct/dd9998Le//Q1qE8Zj4TfHwkdfR8sKrxFaC6QkaMoG4RQKNftP58CqvcfhR/3aKNvL4jLJ5VMd4jTpYoqeMH4pLIaXmebcD9GrY0FyLGLkEO/bLpv935pUkY62x8Ki5BkYGBgYxGUoFA1tchN6VEE8HFFJ3qYei2Ao1KOX9YWHLukT8/0j0cfl8ZR/XDsIagt1VrFAPProo3DzzTeH/m7YsCHUNqjgZXIswEOBPO99Ha0JrbMIyN5UGr6kT94OfO7YLIP9o6DnyBZ4p/6hi2njjJSQBQcrb9NChDpEa+2LpVcVq4yv3HMcLurbOpSQX9/rWBgYGBjUNdSww0KIHnBjJKuMdiiUpoxArJSKBEUuqLfza3dPq9OKRVZWFrRuHRBC4pJu1rBCuV6I/MyDaMX7u/UUUvYH0WPhrk12VvJjJ61MTjqPBYZkYQgU4kRphVC4T4doCc+xXLCwyjivNC4rFklRdufWdvK2gYGBQV1Dh6YNYPfRYji/d6sava9bD0SsjEVC8rYLQx41iLnN99ChLtq94r/KjA3+/ve/Q7NmzWDgwIHwxBNPQFlZWW03SRBSaIy4QQz6OsYeC7v7JSRUu8qxEM63SUY+VlTm2mPRJCMFmmWmsc+HT5SGPCt23O51cXGiDDDRFv6pB8ToFQYGBgbO+Px3I+HpK/vDny7oUaPd5Z7lKYAHcnpBu8YN4KFLekeF5p7uP+kucjw4Pv7tmdCzdRZ8ePOZ4Be+PBZQu6izku/tt98OZ5xxBjRp0gQWL14M999/P2zfvh3eeust7TmlpaXsH0dBQQH7v7y8nP2LBiorwxm5GcmBaxsEYNsXZN1w22c0gQz73c15lRXh98OPr6qy0rPK+O3oLgDkuARyPr1mdZW+HbS9cmjP8aIy2/bTwzNTEiArLTlUYK846L3AhO784sBnGW77xwuqKqtiOr4bp4UX8GMnSyK6l3xuVWW4nyoqKmpknvJ7mDXBwIwdg5pAtNecJulJcPkAjBLBtT/6TI860D3azbO0y06FmXePdjy+utrdHob7OgfqFW77s3/bLPjm9yNctzt8v3DfVlaUQ3miN8UKdZFI33kk58eVYvHwww/DI488YnvMkiVLYMiQIXDnnXeGvuvfvz9TMK688sqQF0OFCRMmKK8/Y8YMyMgQ4+H9Ys0xlAADrrJ5M6ezQXgqo0d2ImzMT4Tu2VUwceJE7XH5+dhnAenZ7jjdEF63fj1MzF9newwiNzc39H74fTbmh9+ZCg8MrICWFZth9qzNoWuhoD916lT2+WBx+B7Lly6F4q12i0DguJJiPCmsLTSHAtvn3rMfB1JgMC2YNR3QOZGSmATlVQmwee/hgO2lslxrq1g4fz7sD0cZRYjAM2zbtg0mTtwSrYva3mvJ6o3QvnC9r3MRct+WVpJ3lpsL1btqLmiYjxsDAzN2DMya44ykSoB2GUnQPbvao3ygQ2DtLzh8wNX19p4Mn7Nh7WqYeHAVxBIrDodlkimTp0CQBNIFAm2sqrKXt9ygqKiofigWt912G1x77bWObFAqnHlmwNW0ZcsWrWKBXo277rpL8Fh06NABzjnnHO05XlG5aj/AhtXs86UX58CpjpFjy+G7NQcgp28roXK1jLd3LYTdJwMepJwc9/12+4Ip7P9evXpBzlmdbY9BDBo0CN7bvEq4T7PtR+GVdUu19zj/3HOYWxW9A48sn8W+w2l//vnnQ0pKCuw8WgRPrJjLvh8+fBiM6qofS7wtiSlpAKWB8Kc/nnM6/GJkR0YNp8O/9i0GOH5cGFcvbpkL2w4XwfFyXHWqoFl2Qzh+iK2AgTYmhHNbRo06C/oF2ZYiBX+G0047DXIu6B6Vazrdq1mb9pCT461KNX3v8pgqKa+EexdPZ5/PGDQolDAeS6AFCJUKPm4MDMzYMTBrjjtcfkkU1+J2++GTpXvg+Wv6Q7OGgbBiO2zOOwFPrZrPPg8fcgZc2CfGOSarD4TklIsuuhDSXFqoQ/JFYiLk5FwQUROOHDlSPxSL5s2bs39+ELBEA7RpE6b3lJGWlsb+ycBNPlobfcP0sPBshAeAFtkp8IuzTnPstwTCuOSn33AiuTkvOTk85PnxKeQ7Rg+bAPAdKohBpAbHR3oqYaYg4yY1OXzftJRkV+0oIW7kO8f3cIyjLCbH8+u3a5LBFIvSYI2QzGB4FAeyRSEdLX2GaCIxyV2fR4LbzukK783fAb8b2y2ie1nOTQybgBKTkmp0rkZzvTE4tWDGjoEZN5HjyiEd2T+3SE1NEWS8WK/fyUQmSUtN8VyED+WJSNsYyflxpVi4xYIFC2DhwoXM05Cdnc3CozA06tJLL4WOHd0Plljg3F6t4LphHWBQx3BhNIP4TjaiidRXDWkPq/fkw3ew35LcTelmaeCMQD3rMku6qLzSU3IWVxAo2mY3EP6WWciQvYKfV1cTlO+5oAfccV63qBf5MUxQBgYGBgau9guyr7v1HkQCHZ296/OhdlEnFQv0Onz88ccsXwKTsTt16sTqWdx7771xMQAnXNG/tptR5xBLwRfZuQpLKqB5Q3UoFlUGkH2pSWaqsm2UbrZac75bpiqvLBcnS61J2e2aiIoFfT58jkird8YL/CoVjdKToaBEncxO31lNc7IbGBgYGNQdCAXyPNDNRgN+du7a3u7rpGKBbFDosTCoP4h0HtgJh5/eMgKen7oJ7h7fA8oVhejoopGSnAhNNYoFVRqoXuC2jkUkUHksWmSlaf9Gq0rM2xXnAvl/bz4THv1mHdx3Uc/aboqBgYGBQR0FCVYQCuTFCgn0cx20CdZJxcKg/uHyQe1g+a7j0K1l9Kun92zdCF7/2ZDQ3/+8fhC0bdxAKXQjDSxWtqYIh0KprdyUC9utx2JYl6awePtR6NjUHRsZhte9OWc7jO3RQlsnpTlJQktLkT0WcMqhb7ts+OSWANVfHdaPDAwMDAxqEWLl7dh7LBIirbxdy8FQRrEwiAvcMLwTnN6iIRMG/cCLcHhx/7ZaawQmSTWQuN24gE4Xl2pQC+1uY/fH924F913YE7q6VKQw1+DM05rB8NPCjFMyi5SgWCQnCXUzYlkx28DAwMDA4JQIhaqRGgIJkZ1tQqEMDAJC+1ld/TGCRQqqMKBiYfVYWIVzGgpFv6dKih1QWRncyX2CPyoKSAxAYfFYSKFQnC2KPoOBgYGBgYGBe9A9vqY9Fn5Q29v9KV6+zcBADIVKSRJDoTAJWmZbsiRvU49FDUrwmJxMQetU5BWUCEpOXU7ejjWoZ8fAwMDAwEBHtuKV+vVUhOkhg3qBSGRDUbFIZN4BjjM6NVZSyKYkVivPdxvbGA05n4ZCoULThChEJ8sq6w0rVKzRUKr/YWBgYGBgwJHdILy3Zrgvg+0bke7XtR36bHZUg1MecigUxeUD2wl/P5DTCzblFcBpKTs1nNPuuhOL10UKGgqF98XFZFjnprB4x1H2XUVlWPnJSKtZiry6gIcu6c1qlpzTo2VtN8XAwMDAIE6BeZfT7z6b5VrUhMcioZbPjxRGsTCo00hNToSyiioY3a15VCYhhkIhPv7NmbDhQCFcM7SDcOzNY06D8vJymDiRKhbEY+Ewo/90QQ+Yu/kwY8GKFFQ54Z7a568dCL96dwn8bEQnePB/a0K/N5ModA0AfnlWF9MNBgYGBgaOQHIZA3cwioVBncbiv5wLBwpKGKWsX1SSOCpejG24xMBkB9FLYa9Z/P6cruxfNCAmkweeoV3jBjD5zjHs8/99tSZuXKMGBgYGBgYGzoh4u67l7d7kWBjUaTTOSI1IqUBUkcQsTNb2CiHHIiH+ckyiEXZlYGBgYGBgEHv0auNPpvnJGe3Z/38YFx3jpV8Yj4XBKQ/qseChUF4g5ljEn2egbeP0mFzXcCkZGBgYGBhEF20bN4Apd44Rksbd4Kkr+8NvxpwG3VvVbtiWUSwMTnk0zUiNiC5WZIWKP9Aq4wYGBgYGBgbxje6tsjyfg/JLj9bez4s2jGJhcMqjZaN0eONngyEzLTniXIQ4dFhAb59uVQMDAwMDAwMDLzCKhYEBAIzv0zoq/RBPoVDoFp24ej/84dxutd0UAwMDAwMDg1MARrEwMIgQ6SlJcEGfVlBUVgntm9Rs2NGADo1h5e7jMK6ntRbD1UM6sH8GBgYGBgYGBjUBo1gYGEQBr/9sSK3045s3Dob/5e6DKwcH2CBqAj1aZcHGvEK4dEDbGrungYGBgYGBQfzDKBYGBnUYLbPSWdG+msQ3fxgFh0+UmqRwAwMDAwMDAwGmjoWBgYHnaueGacrAwMDAwMBAhlEsDAwMDAwMDAwMDAwihlEsDAwMDAwMDAwMDAwihlEsDAwMDAwMDAwMDAwihlEsDAwMDAwMDAwMDAwixinNClVdXc3+LywshJSUlNpujkEdQXl5ORQVFUFBQYEZNwZm3BiYNccgLmH2KgO/QLmYyslecEorFkeOHGH/d+nSpbabYmBgYGBgYGBgYBBXcnJ2dranc05pxaJp06bs/127dnnuOINTF+ip6NChA+zevRsaNWpU280xqCMw48bAjB0Ds+YY1AXk5+dDx44dQ3KyF5zSikViYiDFBJUKIyAaeAWOGTNuDMy4MagpmDXHwIwbg9qQkz2dE5OWGBgYGBgYGBgYGBicUjCKhYGBgYGBgYGBgYFBxDilFYu0tDR46KGH2P8GBmbcGJj1xiAeYfYqAzNuDOrKmpNQ7YdLysDAwMDAwMDAwMDAgOCU9lgYGBgYGBgYGBgYGEQHRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYRrEwMDAwMDAwMDAwMIgYyXAKo6qqCvbt2wdZWVmQkJBQ280xMDAwMDAwMDAwqFVUV1dDYWEhtG3bFhITvfkgTmnFApWKDh061HYzDAwMDAwMDAwMDOIKu3fvhvbt23s655RWLNBTgdi+fTs0bdq0tptjUEdQXl4OU6ZMgfHjx0NKSkptN8egjsCMGwMzdgzMmmNQF3D06FHo0qVLSE72glNaseDhT9hxjRo1qu3mGNQhATEjI4ONGaNYGJhxY2DWHIN4hNmrDCIZOwg/aQImedvAwMDAwMDAwMDAIGIYxcLAwMDAwMDAwMDAIGIYxcLAwMDAwMDAwMDAIGIYxSIG2H74JOQXBeLTDE4NvDBtM/x90gaoTygqq6jtJhgYGBgYGBjUMFbuzvd9rlEsYqBUnPPMTBj6xLRoX9ogTlFeWQXPT9sEr87cCnuPF9dqW46dLIOb3l8Kk9YciOg6787bDr0fnAxf5u6x/DZ70yF44rt17Lmjgf35xfDoN+tg55GTUbmegYGBgYGBm1oN+O9UxqHCUthy8ITwHfbJL95f5vuaRrGIMhZtO8L+L4uS0GUQ/6giC1Nte6qemrwBpq3Pg1v+vQzenL0NLnlpLlM2vOKRb9ax/+/8eKXltxvfWQxvztkOHy7eFZU2//Zfy+Cdedvh6tcXROV6BgYGBgbOKK2ojHk3lVXEpyxUVVUNV722AK5/c5GgXBSXVdbIPn4gv4QZALEd0QY+z80fLIW7P7Hu3zLQCH7ec7MEo2ikTTKKRZSRkmS6FHH0ZFmtC9mxwLNTNsKt/10hTDxq8DjpED70ydLd8KdPV0JFFBTPLQcL2YLw9cp9oe+W7zwe+vzExPWwem8+vDZrK8QCe45Fxzuzak/A5ZpXUBqV6xkYGBgY2GPjgULo8X+T4OGv18asq+77bBX0fWhyrXvyVThYWApLdx6DBduOQEFJeN8e9NgUGPDoFKZgxBLnPDOTGQA/X75H+W5W7g7v5V6x80gRTF2Xx67tVtZYHdyHZWOpHxgpOMpITvLO+VvfUFJeCWc8NpVNzlho47WJl37YAlPXH4StBQlqxaLUXrG497NV8OmyPfDNqrAy4Be3/TeXuTD/+GEufLxkFwtNOnSiVLmAGhgYGBgYcLwwfRP7/735O2LWKR8v3c2iN96P4T38ohqqBZmF798l5QFBfO/xopjevzh4z5kbD4ntqq6Gy16eC5e9PA86//k7X7mblb4Ug/A5kUaHGcUihh6LaFil6yLyCkpCn+trSFgFmXhUu3dr5Th2MnJvzl7iMbjv89Xw8owtzFMk44SDsmMQwPGiMpix8eApO28NDAzqL3YfLWK5cRiCg0hO9C7+oecB8++8Ensk+iiyFmtwBYIaBI+cCO+f6SlJNdKOUilUrLKqWmgb5m7i3uQFtLfd2nbpccZjEUMcPlEKP2zI82R1p4pFSZzGFsYadBGp64rFfxbthLmbDztM3PD4OOlSsYh04iIKJYVBl/Mge1FQAfnZ24sijq+N1VaBFpvvVu2v8WRuzPH45btLYmrBMzAwMJBREwnE176xkOXG3fnxCvZ3UqL3Ffzq1xaw/LsnJ673dF68RYh/s3IfXENy+oqC+/bhk2Hvfk3ldJdLMlKFQt783wp3EQ5r9uaz97vveIlnWYMeZjwWMcQFz8+GX723lLnz3CKZTFbuXjvVQI0T8Zq45QZLdxyFB75cAz99e5HtcXQdcGvJoRP37bnb4eKX5vhKsqagVg47xeLpyRthzubD8LXLxaqm8d3q/fD7/y6Hs5+eGdP7oMGAztFNeQFmjImr98f0vgYGBgYcz0/dBCMm/BDyJMQKPM8hd/cx34oFv8aUtXmezkuKM48Fel1oiDD36h8m30XD+OdHsaB/92nbiP2/co+7fIuLX5oLX+buhTuCyiPC7WPQ5zUeixjiSFDQwyQYt6Av5FRVLKqq4lexwDAXt23amFeo/U1YJ4UcC+8ei8e+XQdr9hbAiz9shkigo39FOjkVCknCWjxh3pYAsxoCc0cw1pSG10V+/cNw+cvzoO/Dk6HXg5MsJAMZqclRu5eBgYGBHV6YvhkOFJQwg0+0odoTGqWnsP9TIsgHlcN3nJDoQ4mJJQ6TkCdqEOQyH6KqtjwWleEbXzqgLfvfq46D0TaePRbks1Es4sxNifFxThbk+o5yoll4XYBi/R7RCo70am5qMJwggjceT8eBLhTKrcdCtWgdj5BFS+VCReQVlgrjMnx8Fash8dev1sDWQyKPdSRA64/qfm5BQ7QwdwTZMd6YvS1KrQO44a1FsGL3ceb+xlc3a7OYPJeRWjOxtQYGBgYc0TSeIB74cjUMeGw6HJEu26hBim+PBYfXMNp481gckUhOuEGwNjwWZUSRoPITdhl/R5G0xX0oFEnehsgQZ5FvdR+iYnFqeixoH8STx6K8spq5cvOLy11RpdIQoqLSSuG5cLoXlpTDF8v3CJZ/tx4LykgRrUrXOmUJ280tGHTxwP645V/L4F8Ld8K5z86Cn7w6n/VNJDhYWMLoBZHVwi9UymgsDV7yplfXFAt8v8hZjiEVBgYGdRPUyhwN/GcRMgVWw4z9icK63yg92Xfydl3xWOw6UgRnPz2D7W0yUC6TcyFDydvUY+HTOFbtUQkor1B7LFISE0P5ql6bQrc0t+cKORYRim1GsXDT4T5pvmqi+Ew8grry4kmx8Kr1HyMehBNlFcK7TYBqePibDXDXJyvh9o9zXdPNcqiawhPI3ECltNo9XmnQe0Y3BFREVhLu6mU7j8GL08VwLFtDk+K36esPsv8xtMsvVGOmSWYqxApyYmGDOhYKNXvzIRauiSEVBgYGdRPRViwoqCDNPRY0H9QrxERf5301Eu+IHzz67VpWywG98TKo8iD3D6VrR4EcFZSnJ29w9W5w739l5hY4c8J02HOsKOJQKCxdwLvNq7KSlkw2tWq3XgqTYxG3MKFQkseiMn6UK6/hOdQ1jYsGzR1BofrrVYEk39xdxz1Tu6qsIV4K8qgWx1DTEtRKFVaFv+iFOUoFkGP74ZplYnJrDYulgpqUKFr0MuuYx6L0FPWMGhjEKzCvDXO5vAiEctx/NEEFY+6hTYpCzS0sqjb48WlaRkL5njUFO4+KHAaFKArRzYqhUFe+Nh9enrEV7vgonAytAhp2+jw0GZ6atJEVen3GQ76MJXk7KGig4sc9PV4jodKSk1wZVHVMUCbHogbg5aWaUKhA7H485ljQHAQ3yxzmJgh5A1KORaemGY4UsDpUReixOGqzCXVpnqm4XzVc88ZCQXHgBXooYs1M4ldQ9tI3fjwWdJxmpNUtj0VN0SIaGBi4Q86Lc1gu1+S1B+Kiyw4VhvcLvtZhqE2k+PX7S1jtpPu/WG0rC9WUxwKriKPxTOXRx70PjYW0VgWNSEDQOlC4Z3LmqEXbw4QiKsiekWoPbcZwNWUoVFJiSE7xKuinEo+F3bkiExT9HiKCCYVyAS8vtcJD8jZarSd8vx6+r2f0lrQP4ikUyqvH4iDxWKhyLDo1a2A5x20olGpMqQR9HexyIVplpVu+q3ZITudAdhIKr9tBNLYPlTLqtl/9ICEhQfA0NaihwkjRgtErDAziC5yJ75ugV7s2kSB5LHiINhX2/RQFRW8MpWy1s8TXlGKBNYjW7y+AJTsClLocOw6fhHOemclqV6jCmnB/R9B8SS91HWSHTIJDocJfv7dEW+uL9xuGQuHe5EuxIPG9dmIP/U0XFuUHRrGIMqo8JG9PW58Hr8/aBr/7z3KoT4jXHAvqSXGaqPgeKU0rCp703eJ8b90o3ZWwroLq7l6St+3yd3BBstxP8byqsC25cjdf2GoSKsUiph6LhATXiguOZyyaiLG38QLjsTAwiE8UuCDDaEbyx9yG0npBtbSu8z2Z5lj0fnAyLN5+1P460kLj1FaqWGw4UFDjBU8pPlwSCNXacaRIqQydDO69VLGwM0RiWPEfP8xlZCWqyuKJNvvmpDUHYPqGQC6iXYG85AiSt6nHwi4cj8pBpkBeHEPwWDgkb9tp+/UnxyJ+FAuaI+HkvTheXC68y5NSKJQObjcG1WT3kmNhp7DR6u8cqsctKImMASpWUClNsfRY4OJNNxQ7pfPVmVtZ0cTx/5gVs/YYGBiosWDrEUYyUVfghmUvnXhIVfH/0UAJ2S+44SaZ7BO4Ty/cZh/uI+/l9NlURjYa4vPh4t2M6r0mKoyrMGfT4dDnrQet1OqBHMpqYf8WhG7peAwr/nrlPnjwq7XK+yXYKBby/mZlhQqGqgnJ2+AJtEaJnagjKBMmeTt+IRbIsxeq44zaOSaegXj1WKiUBHRRXvnqfGZRsPBcl4keC9013FIMqxYKL6FQdgobWqK+uHUkXD4wUFxHJyzrlCD6zjyHQkVhTJfVsMcC+8at4jJr08G4rlFTWxu3gUGscexkGVz35kJGi+2XCjQeFQu6Nrupr+QVCdKaGlIspPAkXSFVjpIysW37ST5eh6bWsGBVeBU9pyaxiRS73aKo2YT7C8+zcAoTothzPOC5ltNVKqqq4Kb3l8I7c7c75lTo/kbFj3ss3Kzr9BhqXDQ5Fh7w8MMPM62Q/mvdujXEAl72ahoG5CRkJkQlIj3+EK91LGi7VIxI//fVGli68xjc8u9lFoYOrE9BFQn8qNrc3MZCqo6TFxg72CXF46JyRscm8I9rB0GLrLRQe92GbUVCexiNMa3MsYiwxgeHaoHG90qvbye0xJMHTmVpiqQwoUH9Bo7ruqx4Ug9/PM5Dv4oFnbNe9gC3mH0gEf45c5tlT5ZrSzit+3IExipCVZ4VrOZNoXpHWxTegpoA3W9VbUAjm7wfuikYh4yCqtCnr1fuY6Huj367znKOrDzK/cQNoEzxS3AvV9Cxk+xDsRBYoapO4RyLPn36wP79+0P/Vq+2MhNEA14SWeiLcqKBpGOxLi/4dgM8nlih6AKummyUXnZm0DIthEKR8/GTau65nY+Ryn/2oVDhgcX3DnxeOYFO57FwK5zGSjFWskK5LDzoBNVmF3CBh69v9/jxpChz0KHsJlzP4NQDhl+c99ws+M2/lkFdBV2X4mlfscNxUgtJB7reqAxe0YDosVCvpU6KhRyqu41Y/lXyi+pZNteaYmHv/cb9Rd4Phf1e81pSgnuqvBNW27xGGmKtAlc80EDoJceCKn6pRAawa4vIBBW9sVe3eBUlJCcnR81LgW7WHUdOwqCOTSK6ToWHxS9BEsZTk+uHB6MueCxUwjOdWJhUTxFI3g7/jYc6XcMOkSqSdv1KrRVhV2qAKaK4qtLRY0GfwXNoUxSGcCw9Fqo8FnyPNBTK7h3G03jmoK0Vaq0YGASxcNtR2Hb4JPunHUfV1bVC1uAW1NIbj/PQL4RQqBqYwLxYqrwHOYVCyaG6lLZVJfjS0GPqLZi7+TB8mbsXHrykN2QHi/XFEm72WtxfCqWcQzfCPDfW2SVry3AKdwuHQoVzLNzIFTRChrbHvo6F2itzStex2Lx5M7Rt2xa6dOkC1157LWzbJgqDXoDl33/8ynyWHFZTdSzoWKwrrl3PORZx9FxU6VMpBXaWBDl5uxprb6s8Fi6t/ZFOXLt+pR4LyoNNv0fIMaXhttVuuF4sWKEwUX3s0zPg2jcWWn7DvqFKlt2biUeBhm4OxmNhoIITneiMjQdhwCNTWH5ZvIKuAXasePEGJw+wU4huLNZXHA/yFuRUoE+WZ46cFIvJySirsH6HidM/fXsRfL58D7w4fTPUBNxsydgnlMDDrUISYmD0sE2WO8zFUB0LwgrlRlygOTBuGZ50eSSRRlTUWY/F8OHD4YMPPoDu3btDXl4ePP744zBy5EhYu3YtNGvWTHlOaWkp+8dRUFDA/i8vL4eC4KCavv4ADOnYSDivqqqKHeMGZeUVAn2o3XmVZICdLC6FtMT6EcZA+6C4tNx138UapWXhdpSWW9ul2nybZqbA0ZPlcKKkXDgf31S5oqo4LrC65xUEwMrwmEKBn1spTuA4IFRxOpTYWPDxbH5trrzO3JAXGuPh9qjPLyPPiQum7nmqqiotv1WSPvHz3nXnoGIXyTj6JncPoxrUjdeC4vC6UFFhfS6V0uO1Pfz4aM8H2uelpWX1Zh0xiN7YKSFzuqyszOKZ+OW7AV59zC/b/Nj4uOx6OkeLSsqgvDz21m6/QEs2VxgOFRQJlLK2hC9lZTHfL9EodeaE6XDVGe0sXvnCohKBpUr4vVhUPCjBSaVCRsJnsQu3OnC8uEZkg1JFOyzHlFfCcaIoIcoqxP1S1Va+18p6RXJiQshQKZ9XpjA402P4XMXAA9xj3cqgKDsojbsKWSf0G+kb3Af5cYIMcCopFhdddFHoc79+/WDEiBFw+umnw/vvvw933XWX8pwJEybAI488Yvl+xowZABBQJrZv2wYTJ24RuufIkSMwceJEV+3auBuHWkAw3LZzN0ycuFN77Mo8HI6BSTxpyjRoHMizrfNYfjD8XOs3bYGJpZtiej/UB17fkAjtMwEu7aS3Buw8EX6n8xcsgsPrRAHsxElss7hENEoog6OQADv27oeZs/aGzsczD+TlWZx+KJTqxkpgnQmcv3X7dpg4cSv7nAxJwJem/303CRq62C/X7QqPMxl7du2EiRMDbBQlxYFnem4aH9POmDlrVqidVZWq5wk+w1Y6VwJYTd79d99NdBlKFV6GAvdKVgr033w3ERQlOlzhow36/lq2PBe2FSSEft+8ZQtMLFOP2aKS8BjBti45lADFFQBj2rgX5qdOnQrRRO6hcJ9PnjIVMuNX3jKIEH7HTu6R8Bj55rvvwWq7kOdg/GH54fAzTJ8xC9pmQtyiqiq8TnwzaRq0tJImhVBWFj52/sLFcGxDtAwDevEOvRNfLMEID3FB/fSbyVBYDtAsHSBLWkfWHgv3P+LA8ZOh8w8dOmwZN9sLrW04WnAifE7ePpg4cQ9EF9Zn/v77SY6iLhpAFyzNFZ5v4aLFwt/i8wVlw8OH2PcnT4iyQwJUCfsExXbF3v3NtxOZIkHlp2NHDsPKFYfY50OHrf0rYxeRb44cPRa6P+7n6zXjr6AsfM6atetg4rEAfe6BCMs01VnFQkZmZiZTMDA8Sof7779fUDrQY9GhQwc455xzAFYGktq6nn465Izvxj7fvmAK+79ps2aQkzPUVTs2TNsMsCcg1DVt0RpycgZqjz26aBfAtg3s86izx0LHphlQH1CwZA/A1gAbQodOnSEnp6eQIH3920vg6sHt4bdjukTlfrM2HYKNi3JhYz7Aa7+7UHtc7q7jAKtxsQAYMnQYjOoqerYmrJ2FJl/huy7tWsCOjYchM7spnDWqF8DKBex7NDI1b9ES4GiYH5shMRFyci5Q3h89IncunMY+dyL98tfcH6C4MmAdGTFmLHRo4jwOVk/eBLB3h/K3rqd3gZwLe7DPz26cA0dKi8ELRo8ZAxNWzg88TlKS5Xn4vKBzhaN4+V7479a1IeVfZh5RgV8PkZOTI/xNMfbc85XsI25w/7LpqIIqf+s/YCDsxRCQPFzEAU47zfpcHPcuwfdXFXq+2x8MCHq3/niU4/xFaxAKhueffz6kpERP+i9fsQ/+tWUN+zzu3HOhWcN6YqHwmDuDtWfaZFv59OsDIh07FSv3A2wKkJucN348ZKQm287BeMTJZXsBNgfWlmEjzoL+7bMhHoGeiuoFYQVw1Ogx0LVlQ+3x9y2dFkqOGjR4CIzr0SIq7dCtoxytmmZD3t5A1AZHRes+8Pz3GyG7QTIs/cs44bcEXCM3rAr9XVQRXtubKWSkRVhwb81S8aZJ6LkJWMO7dukIOTm9XT0L9xQ7efNVzzz+ggsAFuH6H0bzhqlC6Fd5dQJ07tYLYFvYoDRkyBCA9ahsWOcFv0/b1q0gJ2cQvLx1PhwoDiemp6YkQ3mQEESeT1M/WQVwSAw5HHveeMhKD8zJE0sD8hNe+4wBbeD9zaugSVNnGZRVG18d8Dw2bNQI4ERhaPx104w/RlizbDb73L1nT8gZFZDJNuedAFgckFVOacUCQ5zWr18Po0eP1h6TlpbG/smgC3VycqJi4U5wvZhXE020rLLa9rzKapK5n6C6bx0FMVNjmCV9rjfnboRdR4vhmamb4bZzu3u67N8nbYC1+wrgnZ8PEenUSJ/jAiFvmiEkhq0PmL8m97cqvLVz84YAGw+zd5lAzsdDqzVeCe17TCT1IRLCY0oISUpIcjUO7EL901KSQ9fwklTGkZQU7j88W9eexCTrmE1KCvdRYnKyslifHeyevazK/xyxy9FISEyEvMIy4W/dfYTclsRwPxWUVrluGx4X1blOxmViUvjdn0o4+5nZsC+/BGb9aSx0ahbHpuwI4XvsJJB5mGg/RuJ1/OAazFEVx/tlpRTq4jQnhTh3qLnnylIkTn+9aj/7P7+4wtKO8ir9XoI5h5Z2J1hDqopI32SkuhvLaJAbPmE6M1KteHC8wG6IIbJYAfvCvq3hqiEdlOcnJ1vv0a5JhiWnJL9Efm9i+1VtTUkO7NeyAS2F7XuVIZIhGnqo2roryXvHsY1IZddOdi2DouwTugf5jPu57tykZBLuReZUUnLyqZm8fc8998CsWbNg+/btsGjRIrjyyiuZB+LnP/95RNdVCWJeHJM0XtIp0VOmZX15xha46IU5rriv4xk0CVruAyeqNTtg1ePZmw7BnC2HtdekTBXWdoXbgrSLD3+91jbx+hcjO8O5PVuFnkNIUKvW0c2644zW0by5pXq1LZCnYIXygkgSy4UF1Md17BLm/DJDOSXUY58fIFTDdm2gP9EE0tpM6sb45lOdbhaVCsTMjQGvk4F+7XNK5I5XUKE0HkkUdHuc05pO1ycVk1KsoNobaOFPOVlbrmNBoVp2VEnK9L3pcjlkHDlZBifLKllytczc9Nac7TB9w0H402dhT4oM1T6kcqTLdLtuXgVXcuScpWRSMU8eD6qkdtrXfH5GwgpFx5S9TBL+XEkV91OVFWrPnj1w3XXXQY8ePeCKK66A1NRUWLhwIXTq1MnztejE5wNEEC6kPn5h2mYY9+xMRlErg7I6OC0SdIHHCfdV7l5Yv78AVuw+DvWVbtarBVsF+ZpUETuqeCcc8ut4b74YSiQLZb8/pyukBl2veE/6XPMPJjDviQy8hE4wFYeUWslwWyDJto4FWTX9sEdGRDdL4Gdtsnt+FVWsGzgJ26jU003F7aJK30Ftsp9V1DCrjEHdAyUdsDPuxDHbrFDLJp4Vi3KpbU7rCV2fanL+qhQeug7KVbLt1l91wVf7d5SekuhjP0rQMlO5Of+RS/uw+14+UExcR3y2TMz3cLMPcHlGVlSSyRfyO1XJhdRIFWKFSkoMy6OOLREVCzqmbBULypTp8px6HQr10UcfRe1adJEKa4j645+fFojDe232Vrj/ol56TmqHRULm5eZ/O9HU1uUCeZTy1Ik3HRWtto0bwLAuTW2tbFSxsFtonBQ9qrEjMlKTQooFPgd9t6uO4vdqJQbHjirJOKoeC491LLygOkp0s36qQNtZxbwsdpvyCqF5wzRompnq2I4D+SVi1VGXt6HKRKR0uJHArXXqVEA8C8a1Cbqn2Al80TD8yNhwoAC+WbkPbjn7dN85UnWJblauRWG3/uAeSKeskzAeTagUTFrQb//xYujSPFOZ5yDv62rFwn4tSkt257GwW4/d7DH0kOuHd4Qbhndke+Te48WwdMdRWI65l8rzqj14LNTfh+WOJNt3TPuKjx9UTsIF8qpd1ydxW9xPvq7bc+q1xyKaoIsUf5FilWV1L6uqAQsuZwdBlsaMopDChUUnxWLx9qPwhw9z4WChaFGIF9DQDFkApkKvXQHBNXvz4Y6PV8DVrweSpUtsjqWLoV0olNMCL4faNEhJCiWLYVvdrvm6RUDHGU0Pd+sKd195O7qhUE7c3vRufoTcEhsB3W0Y3dZDJ2D887NZ3Qr5vfdrZ034xA2Gwm2z6UKuKzYYD/VZ6jt0c8kgjGLCcW9nFccimtHGhf+YAy/P2ApPTdoY0XWKCY15PFfelgVqO4+pPF0jCRX2Cqe1QvZYcLlERZ3rtkAeRZpbj4WYhCLdl859XaRAtbAfchnkLzm94ItbzwolTSMaZ6TAgCApgKsCecH9Vd5nk8keLM83lcKlqmWC7QzXoXJuCy1gWOknFCqKBiqjWOAiRSRGPrHdbNAqqwkVPis8eiy4okEFFhVQ2EYL0F+/CjDB1CZemr4ZHvlmrT7HQpLG+UREyAVpKDYfDDAacFBlSx7zosfCLsdC/z4wtlT+GROywqFQla6FNr1iQSZulXrjiUqORYShUHZriujNsIefPdJOYHDKlfhw8S64+KU58PWKfexvrNuBmwrt39d+NhjGSqwrsmKhfX9yrCx5B8gBX1vwsyHgfJq0Zn+dz+eKdyEzXkA9gXYCn1xEM5pYtTc/ovOpxyKeQ6Fk77rduiXP15pULJxybfbni+si7/PGGVbFQtVqt2G9ThC9yZLS5sLKTrtUlVtBPSe/OqtLKPejyoWikhScL/JlE8nGK3uwVP1O78V/x7nIUzXcFOsTQqGEPUF/jvFYxBBUkOfCvlBludr9hkat9c6l2zWhUC7dvNsPI4907QEXzGenboJ35+0Q2kIHtdxHVBiTE7F0FjZ50sgKXT4p3MNzLFQT0W6B1wmG3IKHQup1b1qrNqug27d1C6SX8DlXHgtCyWcXauYnx8KLJcNtFXIKO8XKadO9/4vVsGZvAbxAKroeOlEKy5CGL4hWWWnw3NUiBXSBJFzrFnF5XtJ3UJuKheixcM+wdsu/l8PN70t0kHUQToYYAzE+3m6N4YaUWIAaPCIPhapDHouqaiYsrt6TLwp8VdWW9S6SxHokf/lHMEzbDZzWU06IIPd5E0WhHL5mYtjbumDuoZP843Z/0O2VCHoLNwY91X5IKWwx/DkcfuT8fvmYtttnKzx6LMqDnzEBnF/XXfK2LhTKXQSC8VhEGU9N3mwRFmi8fbWHDU3wWDhMHEGxqPSeY1HbUQ9UE6fCPp04sgBMNzg7jwVWLacLEJ00tN+fm7IRJq4+IIRCvTh9M4z82w8Wi4vd+0DaukjctdpKquWVoc1CCNnQxNhGI8cihTBSqPbyp67sb8sBb2/hcNW84LE+FAuXiWZukfPCHPjlewFubx77KltlqQuZ3UdzGzmPgo75ePFYuB0/nyFXOoZV7jgK9csab2KhVBDX55rNsVDFnfsB3RPi2WMh9y+uaY99uw4u+edcmDBxPfsODXGDHpsKz00VFQG/ydu4zzw9eSP8Y9pmljPmBk5rxaFCqRJ18LkaN1CFQlVDQUk5C3vLeXEOG29OSpLbqSomFVvv63Q9foxO9hcVi+TQONXtN/T9cvYneWhX20QhlHvxWITIhMDTOmjXZ+J9Qbl2RrqMmlAoAJi39Yitx8JbKBTxWDgsfpR2DK0BYcXC3aJZ24maOsuXXY4FVZrshDEh2bCqSvibTqAXfxArP2PyNi7WGB/6+qxtUru8eyzSJC5rL+8F2zzw0Skw9pmZwe+tx8iv0G2OBQ3fk5HskGMxtnsL20JDdFGUz9blG4V/h4gWJzvlwY/QSLnKcfFn9UMk4UlmO8FnPF5UxsKqXpm5RZtTVRInORa+LE31KMmZGhriOam3TngskuqGx6I2Wdh0a+azUzbC1yv3WZQDXNLfX7CTfX5rbqB47n2frWJhiG/M3qY11uG1kBLdjbGAGsaOFenDgb2sp7KxLRwKZfVYYLOX7Qx7ho+dLBdySFVwu5rbWd/drH38a12+YarkseCH6a4nKBZJzh6LcmmsqhQL+hWfnyLdLPgOhbLzWOi8QW5Cr+xgFAsJIY+FiwGrcseK2f3uPRYBxSIskLpBNPQKfM6H/reGLWJeobMa2eVY0CRsDIV6d952uP+LVZbFk1qRsV+owMA3SVU/0bAW2dvgR7HwExrA9wasXonC555jxYqJGzzWZqGMBiuUar1DwdrOMmnXBKcxZ+e2jpgBJMIBzy1RFsVC4bGYs/kwC6vChNMdwTC/IpI8Km+8Oo9XvCZv1yO9QjA0mLAoTR8R5asiRh4LXKORZUd3/Ug9FlQ5qu33vPPISWHOI2HESz9sYZ4JCyuUYt1auUfNRMSVEpzHWPgNKdHnbjnsOK+p0mVHuS60S7qmbGyS90S+5zRR5FjgWo+kMhzHi8scPRZuhVeqqMnd4GZP4PuQbvilkXoaDVyEQlGZhl/SbmhXyOFuVQ6hULyOBYZCBe8QsxwLTYSN8VjUgGKhm9SyYnHHR7nw3er94RflIceiiEziWHksWJE36VlmbjzIrCm4iHkFbT+d/GKORaV2c8C8hUe+WQcfLt4NU9Ye0C6U/164MySc0/6RWStYO8i9G0oVuO0WZznOPiLFQpPfIbg7g22Rm+Q+x6LSZR0L64qHlhB7xaJae75TjQu6APoKhbJLdIxwteMbhizgyArqfxftgpd+CIdHfhC0NsqhUPTvwloNhSKxtS773E/uTbyCCplu89NONVDlWRZs6Dqekux/XPz589Vw5WsLmICtMoBE12NRe+95c14hnP30zBBjIWUmRM+lpY6FYt3S5YhwmQFzFej9Bj4yBZ6evMFV38iF3ii+vu0sreW8e6ss4W/ZC2vnsUAs2nZE6A8nj4jb/YF68S2GOBdF3XgzdGueNcfC/npU1ql2QcteIdexUOzxYihUNQmFsm8LBZUb3RfII8e59HK4gfFYaLRRukHrhD1ZaP4qyEbjFC+JhfXmbzmsTf50uzl6efco0J/99Ay44a1F2mMwRtILdAXC6IIiK0m0z2iOhVxsjlqD/vb9Brj9oxXhawavsU9i85HblJkmKhZ2Cx0qOSqgEOp1Q1QqFpZciqrIPBauK29bf0elwk5hsmN+cmqeGO5lf6z6/OiGQrmxmKrm96a8E5baKLICQjfzeKGbdat81SO9wngsNMgvKg8JCHZ1LKjSEUko1Je5e9n/VCmn+1rkORbxwQr1v+A+T/cs/py4NzlV3qY08bKXgEc5UOs/hvai4QIpe93kn8i5ERSntWgIZ57WVNmuPm0bCX/LxhK+5zRKT7G8S1y3qfEPFQund+R2ORct6VLfusglqHbyWEiKhZccC35teT2tFtqvJ7BRJ28HPRakQJ7XUCi7PhPaSX4yHosYgk8GoSKhJu7dyR0ru0Q5rn1jIVz/1iJWil4lZOtCoVCQvvSfc31ZhJfuPMos/Au2HYERE6bD/1bsDbn+OLYf8sYyRScItdJQT438LPTvgwXhBXb7EfHedjSY/BqUJvTqIe0t5zWUFAvde7TzWPjxWlQqFptKTZK2lW6wKgqhUPY5Fqgo2QkQbmMynX6PNitUpB4Lv4INb5NsZaSbuVwDpSZB+8Wt8lXX9AoUlpDJCkNQZNA15asVe1kNHK/AMR9JYdJPlu5mazMajDAspraxZMdRGPDoFPi/ICW5IHRIijT9LVLhH0GHIFW4I2VyOlEaXqM/XbYH8oL7x0eLd8Fbc8RchViCzjG+BpwM5l/h8ieHRcpexP3Hw/uebLTie+dSkq9AFT/d2kwjAZAJTwcUovk7lteKbi49FrgftsxKE37DS1F5AJkanfYyt/KLHaVsVRRyLCjdbIOUZEdhnioWVZprV9kYplWRLKrq64ECefbP5qbytt2pxmNRQ+CTo8LFZk0XSpVApPNYbMwTazQg6GKkU1ie+G49rNqT78tjQQVJVDC4B4C22yt9LRVu6eQRPRZSKBT5m9LZbT14woNiUSV4LK4b1gGuHNzBEl+KViRKaWsbCmXjrbFLdFZB9V5wjVVxRltiRqPMCqVaSnFjsVOWIsuxoJ99KBa14LFwes/8OeR5yYWJuuix8FM4sTZx96cr4dWZW+H6N60eV/pe0FJ68UtzrcdUVMJny/YIxgw5jKf/I1Ng99Ei9jeuG9+v3m9J7Nfh3s9WsbUZDUbnPjvL9XmxAiYSI/6zaJc1x0IS+HQVe6OBQqIMRKK44fsrkd7zVa8tYOvgn79YDY9/t95SjyZWQGIHjn1BJYEqPXJugjwn6V4jF37l+yj1OtAlUac0nKShUIX6HAtazVl+16e1CFfZ5ns1FYKpYtG7TSPLGinPQ6ewXrfbg5hjofdY6OtYVNsrFineQqEo6Y6OcaqKvFYc9xjOxpVCVb+IxiHOCpXIamkFHg5iVCBPLbeZHIsoI8QK5SrHolJpvaQvSrYwoHtaBWrx1C3AmBBF4UVw0wls9Nm2ebS0Uc2dfhYTkUSubro57CcbweaDJ4TjCor1glppsH+4YtE2u0HISk+VvUe/XQf9Hp7iLhTK5n5ePRaq94L9r1YsZI9Fdcw9FgFmJL1gKbTJhkZPBTHHwvZQx/Nt2+UDtDijF8Viw4FCRjIgWyLpnJfDBgI0wtVsw0CBJ9KYVTsIa5XrHAvxb8xxmrP5EMQrZm8KtE0lPKpCRx//dh0s33UMlu08Cle/tgB6/N8kuOfTlcxbrMLHS3ezOYU1eRB47O/+sxwe+26dr/buPR5QUGoLFppviQxD91uUapopFW6ZJMELVNTku44WCfkEVOD3Ci/zc/ex8Lvl1K4niJHByWNB9xpLHYugUKkzVOw+qlae6FqEfaJ7Hlz7+Z4gW87POr05DO7UBC7o04o8C0mYDx6PRsquLRsK51ZbPBaoWDh4LFxuEHaJyG7Yj8I5FurrpyWp61jorieGQqmvXUnadfMHS+H852fD58v32rBCWT0cuI+HK2+78VhUeU/eplEUEeZHUpgcCxfJ2zrPA32RcmJn6FzprW6SKkpz0IVJtVFOXnsA5m0JJ0d5ffk6ZYU+59YIPBZUoJefmd6bWvJoyAC2g248th6LYP9gzQpE86w0wUqvW8C8eCwuHdA2AsXC+h3eWxXPWC2tMW55zO1yLKjSoFtM3SZvW38Lf1YlrIkhhD48FjZ7kV+Od46Q9UcDXnFVxrZDJxnJwJtSuAU1BlDyBXzuy1+exwoqfpG7F8762w8WWkk7vDN3O/zs7UVsrqD1E/+246b3wwpFgdbR3/xrGfzs7cW1ym7lFyoPL9J6XvHKfPjJqwuEWh3bHNY4Tqc8eW1eKJHfDw4W6MNRagJUefhkyW4mhOs8FnR9dl20rKpameMmg1rvI/Hi6EJVDxLLvhs2JGz3o9+sg38t2CG08dJ/zoNfkXo3dqB9uS9YK4nOGzlfD+ckDXmy847zNU4XWsk9ajJo36JiYfcaueeWrhX92mWzfe7z342E1382JGRkoR4n6rE4vYWoWKCwTK93vLjccb12n2Nhk7ztQoB28ljQ0xgrlKJ/dO0J528k2ITLVbL/ebie6zoWQoE88C3juS6Q56J2m1uIQegGHlmh9FYKDpxcVF7ZpAiDks+XE55RyP7tv5ZZzvEiQ7hRfA553AypcPvBgh1weotMaJyRarGEoMLAE6lpnx2TvDconPG8CLucB94/XMPGRdsuzAWfMTUxwdYbwBWZv+T0hLaNG8A5PVr6TmhUbc4yK5TOY2GXB0KvZedm5kV73HJ3y6BXtiZv08VH8ZzkKz9WejvBOFK6WackfJpvpPNcUNBkxVAIZWUVCzVcGQxZXLgtINRO+H4D/GpkR1ftRE8b4rNlu2H13nz4ZOkeFlP+/e2jlce7YUaxIkEpKK3YfRzO6tocagu46U5blwfDujSFZg3FOG4d4pEJSq5aXNOgRp97P18l/GbxWJC9wa1i+sBXa+DDxbvgjZ8NhvF9WmuPE0hJIqCI1ZFrHCBFULmhyQ6Lth+Fd+YFakn8+Iz2bL/52/fr2TzjfWG3DuD85uFPNF+CPqclFKq6mu1PfP+x29v4u9F7LIpcsULZrQN8GeSJ4s0bpsK7vxwqHJOVngylJ8qEZ+FMhLh3jOzaTDhezp/ByAy8hh2caiJ5rWOh22+ckrfpNbBAniPdrBAKpWacqlTs47i2BeQAVRvCn/k4QYY2LzkWuhwm+xwL633d3s8OxmMhgRd10cWe6V6kTnCXE7i3SLkEasVCvJZuIfIiuMntaxDUduik4uw3fjav+VuPMHff0Cemhax9HEJxO5vNhceJYpvs6Dv5RsibrqqmTBES4hXvkfch7+M22Q3g4v5tBUYpr1NMHwoFUQmFcioOJYRCaWa42+RtO7pZVVPdVEK1g92CFmn8t1NeQTpJ4nODmRsPCQLBz99ZDL0enKStCYNjLL/MvjAkVcpRmPoqN3Ct9ftF1jSdwuW2bhjtChpetHRHOGm0NoDeGQxBcms9jkZNA7o+uVlScd3jicO6cenGmh9L2IWhWJK3pVxBHIO3/GsZPDVJT2+KSgXimWAuhxuFIJJQKN0euG5/oSuaVY4txEu+ePsR9rxfBkNUEEcdwqnQmEDf9/6gYiMoFhaPBbj3WATlBd3+R8OwdKFQ+H7tFQvRIn/D8E7QXFLiuYGPPgvfd1CxaN8kA776/Vnw1JX9lTILhm3LCuzYHi3gqZ/0h1aN0kJGjJW7jzt6s+xi/91V3haf2279RFnCSZgXk7cDx8hXrlDl3KJBUGM4FFlIw3UsvFTe1vWha7pZIV/FKBZRBdfKxfACZ01Q6xGQJhdSzTpbdsRr6dyiXLDHMAmsoZG765jrQce5qOlzyh4EJ7ituUCVCbvNhStXTgw73ELJFQWcfJRiVbdYqyY7/4pvgI0aqKqKeptkOoG7OkrJ206KBQ1z0vFr24ZC2V1e8EgoflYoT16gWgS50lgZ6+RtqaCiV8zadIjNianrRMWaY9LaPHhwWTJc+MI87TVociaOF7t3jRsQJgW68a7KSNBYQX/YkFer1asx1wHBPT6x8Fggi5CowLkjeOD4/X+Xw/Anp8PGoAdLZV2ubcXCjoFJDoUSPBZY6GzHUZi09gC8MnOrY5w8XVNpjhJfM4UcC3IftGh/s3KfNnwDx+BVr81n+xrOA50wThnAjrgIhVpHKGKxCCbmFdLEZ93+jOMF2yFHHHBlhhoGVcnbdH+yy+dDeQH3dV0OXZ4mqoDKHzIDoZNioRK4Gwa9DVTBCYVCBZ9lYIfG0CPIJCUr94Hk7SqL4ebqoR3gwqCHCw0z17+5kJEqoEHm/fnh8DQKu0RkdzkWQeFfs/zL+7uTMK9mhbK/JmfO1MlMQvK2UMfCQ4E8zTpon2OhNqC7JKfUwngsdHUshCx955eqE4blyaVKQkOoCsAhg8nbc7drNyl+3F++XM1qaPz4lfna9smKD4YsyQMak9+8CG9Om064nZWWOExVoiy2EdvjFOfNnzsUO+lQa4LfU8ncFZxB3CLWSOG+9SrPqu4XYIUixwTbLi+UbpQ1J35wQbHQdIs9K5SdhSP8WbXYRVp5W/WOeGhXrBULrx4LHXThCt+uDhSBzCss1T4LLfr4zJRNtvdBqzJ6CXlis5c+p+OC5jqhQP/M5I3wyDdrYdwzM21znWIB2i9zNx92pdR7DbFBFiGsaKwS9Oy8SRxcccTwT3a+Quj1GgqFAu2kNQdcr6lOkK/TrnGDUN6YvMZQRRL7m+aHOClI9H3RNR33ObwWJs9ToxJfM56esgH+8GEuq2y/MFhYDdf9L3P3sP1i/f5CWLLjGNvXvli+VyuM8xAmxFEpFAqvI6+V6/aFj8/ddVw4H3FM4bHAcdjzr5Ng7DMz4dtV+4X5ww1lVIGS93hc66lH3cljYbf/UU+ZVrGQ8vk4xnRvoVwHVXuE0mMR7Ev6nrngKxtAULGQCW2495x6wVGpQ6IExENfr1U+G5W/5OeiQ1nrsaiyL5Anr8XhUCgvdSz0ORYcGHqmK5os1rGoDlfeDnlPwBE6Jd12PyfNcVtUzw2MYiGhPBg/p4qHV4HTGO46UhSRYiFfE/H67G3w2LfrtIVxcDJ/u2of/EDqYeBijaEN8gZZLE3yJgqPBX60i/+03N8lLzkmsmLi0ntBxhWEzCqB+HrlXhjwyJRQoSUnVqiwxcXeAs+fUTXZ+TX4Yp+t8Fh4FWj5YiOMIa3HQrbAOPepk/BBlSyd+9c+eTv82UKjJ+RYWEG/87M2qRY0HtoVaY2LWHssnCynVKCQww6nr89j1lPKcW8H9FTwOjj0fu49FuG+2BqsXzOgQ+NQHDqyI2GiM7JFRQIUvr9SzOd5Ww4z6y+2lwpL1MP707cXwTer9lk2Y3nd8eNhQSGeU2zf8FaYKQrXHqyXQUGVK2p15+1QCYp7NSErHPhMnAob++Bn7yyCW/69TJnkj9b9nURZRUH89/9ZrhUyVWtE28bpoXkk9yelNsV1itKO7zji9BxqoQ9DYaauz4Np68N7E1UCZ286zP7HfAdk6sLx/OyUTXDnxytZPuFeYmj796KdoT6WDVK07XROYd+e99wsuOSluaHnxfWX5klh/8mKhSoBfOKa/Wzv2HmkKBTm2L9dtjAexBwLcTzg+6Vrj90ei/1pp9xiPpSqAB4V4uV8PkTnZhnw3i+GKtd01bLYMC2wD4o5FuFQKCfDFfa/bJTge5FXqmu6J8rPJVSL1gQth5O31deXr8mP0+X0UcW8WuexqFYoFpVVWg+0WMeiKswK5TLHIlCHRxdZY2copAZ0qyfGL4xiISGchCl6LHBSqV7Q05M2Mo1bq21L1iE31a35AOELCI9DVOG2/+YKf6N7GVloBj06RRAyZI8FXxxkQdYpxtRLSA7tP+QZf2LieqECqIx/L9zFXK9oxXKjmfPXgTSidkKjTojnbcPFiS+gylAojxIy73a5+IyQKBXK5bG2xwlObBtUadB1i11OituFSJmkLilTXqEaUvx57IRmN/1G6WZn/+kcOK15prZQUixAvZJUOEAB+9fvL4Vxz86CPTYCKRVqkW1KBex/KjiiN4LWclG9m23BvK9L+rdh/9NaOfK8WrTtCPzt+w0s7MsJeO8H/7cW7vh4hdD2ZTuPwQ1vLYIfvzwPXp6xhYUVoWKlEoixyrEsoGw4UBBxjgUPG/jjh7mW8BKsl0ExcsJ0Zqz5btV+gWEKFTp8jze+vdhyfVTKaFgN9ttaYi3HehxnPjmdfY/GlDV7C0Lrt4xRT/0A5z0/F44Gm4mC+Her97M1lc5FypUvCxlISMGZ8+Q+puMS1xbKnLXLoSAhFUZoKMbZT88MvdPrhoVJC9DCj3kJlDCAew+QrACBY4vS9aLRjgvjdrP8cNBjgbH7o5+awZ4La0bN2XI4dG8aIoaMUvLeqgqFWqsouNi/fWOhn2nEgqwYBFihSCiUjXERrdV2igXu45jHuEVil5RDoeQ9Cz3xnO3I6rGw7gU88VqXY8GhUxLQEyHPW35frzUYdcor+81FGKhdyJd8De+hUB48FhVV2r1bHQoVzrFw2t7sQh/dhkKJomAteizKy8th9+7dsHHjRjh6NLzg1jUM7hhYJITK26TD8bszJ0xnFiUVraEd5HhWvmjwBCbEL0Z2Vi7c3CXqpzAYatV0YhdJbjK8JFojX5y+RfjeDWWfV4+FCr3aiFU+vYAnG4YrXNsnb4c8FopJjYw6qMzw161isvCqWKjyJ/A7VZiQLJy7sTg7jQeavK1z/9oV/aNXl8+mXaFqhvh7dEKhQjkWNtdzU7Gc0s12bJYBVwartXOkR8ljoUM+CeegigVNnkb2KB2oRVZXc+atOduh2/99zzwCGH+OxdrQaks3xZembxbuz+OoR5wuMr3wkAYOFFp//u5ieG3WVrj5/aUhIRaVoaVE4FbFs28mgtCnwTwKFD6emxoI90LF6pxnZgr0odyDKOd+ITUovbYfjwUXCGWLtQrYzsv+OZflVmCCPn0Hf/58ldJDhV3DBVr0AFzzxkL40Ytzg4xuVUxBwevi91SQlEMU8Xju5d5RmKBlREIvC4bFYeVxNF7JuWyoWPB14fVZ24QxR5VZnLPbD4fHFlrpZdBwIU6J/JsPllpCrJDNDDGkU5PQc2G7FgWZ0ijwGj1aZylJBLB/ufI3plsgnEc3P1CpvvXfy4Rxy5OzaU0GXBZxrVm+K6BYjAoyoR2Vxhq+q/USGxz17vG9mgrg1uRtLx6LqtB44HmQvL4CvQbvWw6quMtht4Hn1XuxVVtEZlqSsDZQJkJK/CGfyz3++MzyXOaGHTvab6wXNOH79UrvvpPHQrcF8H1Dm7wtKxaJ9l5wVY6FjGrF94FQKI3yQ07g9crc1NRwU3zSbh8WKfBr0WNx4sQJeP3112Hs2LGQnZ0NnTt3ht69e0OLFi2gU6dOcPPNN8OSJe4ZPeIBPx3eAebed442x4IL3Mh2hC/Yi8YtL7Z8k+jTNuBKlRcQLjgyV3mEnPK0YJCcvI2TBrnr5YJTXhQLv/HA3Vo2ZIlffsEnEZ8wuODaJW9zOk5VmBH2Nb8eXkdltfb6mLxdcuEyVaKUPOfd5Fg4hUvRmh56j4W7HAtZMaHtVdLNukims4PqHDc5Fq48FtIjyxsNZ0qrCYiVdd31E6eu1Ql8XFDGy/1j2qZQCBINZ8EK0c8GhXkKHPvdW2Ux6kndeoBrBRfIcZ3k7+PW/yyHK19bYGHDWkMs9Jj/9aMX58DE1fvZPxVoCA7H/K2HYdIa6/EYvsQL+vmhMUV2vhembXZ9PLeGU6DVfd7WgPKgwu0f5bIEb2Qf4sgrLBE8BE4KP2U6SpXGLw3bxLBZxINfrYWhj0+zXLdtdnpozuO+gkUDlR6LqmrYHgyN04VCHTtZLljfn5uyCaZoCAsQAzpkh+YW7kOLSH+IBdXC80C+HvdSofKLtRZuHt3Fcg3MDZm2Ps+S3zJj40E2VrmhDvMHWhAWpGaZqTAoaFyUPRY4TmQDGhoFu7dqKOZYEKVFRTdLjT1OdSz4+chQyN/xtUM7CuufbEijHhO2fktLCt0H5HVPJXDzfDOutNPoBDuPBZVlqHLHjg02wi4SCusFoeJLvaZ2rFBCCJGOcSl4ku6+vzv7dPb/xUGPrSPdrOBB4fu4m0iDKm2UB983jxElGsPF3dLN2q2Bbj0WYr5KDXosnn/+eaZIvPnmmzBu3Dj44osvYMWKFcxjsWDBAnjooYegoqICzj//fLjwwgth82b3C3dtAnmruUDJQ550QgwmkTnFauvdeOFFo0/bRqHvm2aKmzm3ykdarAqL1HDIiVS8sI8MHSuGH4+Frps++s2ZIVeyH6AiwKsa8/vYJW/bs0IFwtwQOq+HVwGZHy5aU8SEuqoIciychOgkFx4L++Rt/bVFSjr7c/3onZU+WaHcFM+TK2/Lf+sK5MUClP2JbgqjuzWH/u3DRodzeoQttBhyiaEbOB53KEJU5M1Ppt88WFiizV9q36QBEzw7Ns0QvqfW+M15opcEN0mcO1wIuPuTFWzzRGEEGeooYw++u7X7CpgSYhcKIgM3WVUSO3oxsKDfX79awyps+8Hz0+yT452Aw1G1oWP+Gg4tHMqsfTvD4TYjJvwAr89S58zxeYkJzJgwjKBC8hc7EuEzQo3aKD3FkmCNSoMqLKJFVrqwRnKDEo4lSjaA1nTKkqRK3pYrXKPgLieKc2SmJkGX5g1DigWu3ZjDIwPDo+yMWpxuGUN6sDq0XKANgc/9xw9XsM+/G3s6bH0yh3mg0ZiHYWhc+EZLcKtG6aHzhnRuEtqD5VBgPoaHd2ka+q5Ts8ywoiRFF7gpkGdHiIB0pNzjkd0gGb68dSRMumM0PHhJb+E4moPC2uEQCkUVAHmrVO0QKcH9geec6hULq0KC71wFfqybHAtKYuHWY6EtaBfcG3T3Hdm1OSx+4Fx48dpBwnHaHAsyv6o9WPirqp2VH54D1KFpA8hKx3Uk6LFwuLadx8I+tJm2IXoeC08F8ubPnw8zZsyAfv36KX8fNmwY/OpXv4LXXnsN3n77bZg1axZ069YN4h24SFD3HlpOdIMUBXIvnU55izEOkl+Xun05Q5M8UCJVLP7w31x4/pqBrNgUj8FEQWXGxkOsmrAKXnIsnDwWaBlSCRGoyGEhGg7se7f5GgjsQjw+RPXG6lgk+s6x4M+hu4b3HAtFKJREAVgRQR0LJyGaCsx+PBZCHQvpNyeu65iwQgXbatc3OrYNCtkgILvk7cLDYumx4FZBVCr+9evh7DMKpGgYeOGagTB8wvTQ8Ze9rKeqpcB4e7rBX/iP2baFv7hCIStXmAOAdNats9OFcCZE34cmC2Mc101k88GEbSzoZ4cJV/SD+79YDZHiXwt3QrxhUMcmcN+FPeHCF2azkCeal4H4aEkgFEyFeVuOsH+I7RNyYD8R7I+UJsD9X4Zz+bjg4ybBvkVWmtKri1ZlqkjISomsRKj2COppwrX8ngu6syRsxJmnNWPzDoV5BCrEqr0Hi86pFAsUsHYfDe+5PAcOhS4KtOyjwI77AuZOoWKB90WFABPIF2w9wt4L35dQseBhcMO6NIMmwT1YNqyhMozo2y4b2jVpwHJg/vqj3qF5gvs0rj009Ew2uOF7ojkWdtZl6rHABGqai9ipWUbIUyl7vWiOBQ4LWSimMrVlHVQI3FweKqustDyTGAolnotKB9aAomNKvq8bsywNFxNZoSRDnIYuVTiGGCB1aJkVVjT5cTqBXFUJ3O1eV16haWO16Jnr2TpgeA4lbzvIBXY0/nZNE0mK6Dk16LH49NNPtUoFRVpaGtx6661w0003QV1ARmqioIVjvDC1KFLgJstfBsaOuhUCUXj96//WhCZYF5I42liRMIwLlhvqQzugVerq1xew63CLRkNpQZbx8ZLdMGHiehZGgcwpWCRJF8/t5LGQF395IfvktyPgt2efBj8b0Qm8AhdnmpRlt2jwxUeXYxGqdKkRtr2yQvH70UUvEPdqta7Y8XLrwNurM/zQonj+WKHcWTjUORaRKRbqOhaJjouru1Ao2WMBMfVYcNe6CjT+mCcfU8Xmscv7wkvXDWLKD2dw8wIUNJbuDFvy0RKGCbI6dG4WWI9+dmYnJgSeHaSmxERezC8b9fcf4LVZImORqsuRXtRJqUD8eFA7ePrK/sy6jesoFzwRT/64H7QmFmWv6N0m7A3W4ePfnAk9iXHHDnee151ZjbFdiCsHt4c22fr24XtEw9H43q0gEqB33I62Fg1PuE/wMCgKXFspOUHLrDSlR9bJ80W93m7qHeHa07VFuF8vH9SO/d+mcbpANiKHHWI75P0O9+QRp4l5P9xL06hB2DCF3gDKMnjtsA6h44Z3CZyPYz/ksUhLEvJyftSvDTThHougYoF9i0njPOG+b7tGTBme9+dx0K99dkhJx32I5m6oEKhjIQvzYWZGCpQTwiFbYh+9deMQZiRUFcqTyVnkvU7IsXBBN5sqeyxIDQsxX8M69jlVrQwvrFCoJKJSi3T7+USRtYRCKZKedYqAWzaqBEe6WWtoltutrlzjseB724ZgwcdewbXJbYE8/zkWVCahNLpQcx6L+or01CRBsbj+rUXaY9FjwTv9tBaZwuZtZ0n9YvkexseNwInXrWUWi+1ECwxak2Sg5chJscA4U1zkke7WDmhZ5JAXKxloEZE3KlQwfrhnrG2soQo8AUwGnyy4SOI/ZIbxCqScDeVYJCSEErhVOQp8wdHVsXAKhfLqFlTRzeJntWLhP8cCBW6VckcXUN1aamedt4/GslccBMXDTyiUkhXKRfK2i36TNxZZ0Yh28vYjl/aBoZ2bMmGBMvggkGHo92MLoHfbRqFNIU2j2Ey4oj/85FVrjRoUjJF5STdmVGMD37sqVAatoYiL+rWBC/q0ZuEqlPnJLi+AQs6zwBCrr28bxdp5VTCuH/M4UIm7akgH9o/Pmb9N2sAEwuuHd2SKBxbNcgMUoJ/4cT/WH9gTGNaCluf5W49Ak8wUFgpzXq9WjHXovs9XwwvXDoThpzVjitt1by4SQsZwDCy8/1xYt7+AtQUZrLA9ONfQinjZwLbMIjv++VmwX5P3zfeSgLVZn3vgBPT8yOxJFGiJR08Uho2gcM2Va7Te47rKi5whsLKyypjAk6RRMMd8ApoHt/ngCSawohBOc8+O24Qs4Zjr1qoh29NwumK/IzB0iXtiUDjFuXHv56ss44uu4T8d3smyN3KFghqtcA/FcYbvCtGLKJaYtM4VBi6wZ6Yms/ZggTwEeuO4QsEVfjTIcW8Fom/bbNYHLbOSLIrRYYk6WrWmyWsNRikELP+ikobvkOdh0veH6NYqC1694QwY/Pg0FiJI34scPSCH3Ig5FmL7Emw9FlVaqlk7j4UKXlihcE4i2YGcAyoblwQ2JZ85Frp2anMsKvx7LCockrd56Gmb4LiNfY4FaUMU61j4Vizuuusu5fc40NLT06Fr165w2WWXQdOm4djEeEVGSnKolLuTEEljTm85+3T4fvUBZZI1X+h5sZPth4uEzR0n4Pz7x7HFV8VLHbBG2UtmD/yoN+w4fJJt5m4ZmjJJCJK8OVOaQQrd9073TKKmcwJ5YaHWSrfAvpH5qdHdXB503SoL1ikmC/7m5LGwY5yypZuV4j8FutmI6lhUh0PIFO+AhkLpcizchI4Fzhd/o8+gmiqRhkIp61gEXzBvlyzouGWFcgqFiqbHAscMCrg/H9mZMTTJ7cBnQQaUp68aEBL0dcoexpS/+4uh8Mv3AqQY5/ZsCd1bZzFLK7LxuC3GhuEhvxzZGS74x2yL1Zl6ULFfmklJ3E5AQQvd8ZxlhwMFOOyHiqoMZdgBHaf3X9QrfD3FmvDHcV3Zxos5HZTNadIdYywCD1qgfyR5jK4Z2hF+1L9tyKKKgtrS/zuP5Z7M2ngIxvdpzd4N/j7y9OahEBgKLjQ1IOvouJ4t4fphHeGmD5YK7xETpiOBKsleBk+ufuiS3vDX/wXCpNBghaCGKexP2WqOv/PidGed3kxQLHA8oDKIUw7raLRsRATpoCKGniFUwCjweJxH398+OnRfBM2JwATsc3u1VD4PhiRhPgEyR/3pgh4W+l3uiaDsffiZ5inyMBKqiGDCdFHQs4Dv8I7zurE5+tMzO4XqfCBQwUBFnyoVqGzK9Oh0rTis2L8pVJWwMclZFUqMhsiQAqQQ0PE5sT24/+XllzJ2O3aeJLjIAiw1qsi5ZSpBn+95fH9RUc2qzg0oFvYGRd2eJHuwZKXCiZ5dm2PhQDdrbWfwXprrCWHbXj0WlfbKDzWW0jY7yaV2Rmj7CAR1/9U4KxRHbm4uy6N44403WC7FzJkzWVI3fjd9+nSmeKBysW7dOoh3cOuDGx57jAWlk3zynWOUx/GFh3ssqMDIrSJ4PzxO5TrUFdmS0bl5JuT+9XzY/MRF8PtzAuwGdtBZE1QF6yLNsdAJybKAl6lRdlTgCxtyptMcC4S8cbopkOcmx+KNG4dAxHSzUoG8MN2suq1urq9TeKjArA+Fskt2d7cQqXMs1Me6hWox57Hh+NzIKNTj/yYxD6Bdm1XJ/NZQKCnHwodigVZyHp5AgWsD30Cp4twgqRruGBeYpyiI4zNxId9OscFYc44zOgVi+FHozVbkZ3HBUgYy4bRslK5kv8LwDrn9XvDazwYrQ5AwBAfRPDPNkhjqhJx+rYW/UfBHz8Q3fxgFC+4fxwTKqwa3tyUikKFaa1HRQc8JWvp1YRwyMkgf4vulbeCfW2eH39mwzk2ZYhcLoHcBlSaO7GCIjZyjR9niuCebF1nEBFYK9BRwRiJZCT0QLMwnK24U6CHBfxxUsUBFWRcmi+Pu4v5tWSggKiX8WTjCORbh94TvjBrhqJeDKyIYs8+FL9wD0WOAhjlMxEbgs/J5gXVlKDC6wLJ2JCaErPoqxjAKVcG6phmpyv0GjUY8PyFTsS/imsKL11EmKKvHQg6FEq/hmGPByWxkj4XUZvlc/D0aoVDIwKmCvOeomBa91rHQtVO3fwnUvl5zLCrtFYtQWyUGLV3xP3bvqmr4ZzDqQ1Xg13XydoRGwagoFuiNOO+882Dfvn2wbNkyWL58Oezdu5cxQl133XXs85gxY+DOO++EeAcPgXATCkGt9zhBdRSV3GrFrcv/3955gNlRWwv4bF/vuq97b7j3Au7YYGy8pncCoYYSAqEECBAgtAAJgZDAowTCSyUQQniB90wxxTHN2Bhj3DvuuNddb7/vO7pXMxqNpNHMvdvP/3377b1zp2g0GklHp6mkb9Nkn6+C4ARQfplVx2MnhU5oQajyNIgqYxW6KFjBgoW6ccodG9q8qlCt4PJJE64quVGh0qx8JHjYWfk3HuVBN9lGc5b/+/FESCbcLIsKJezDBc5kfCxU9+t3zPP+/r83xO/DNBnzCoTeE4g/xarBx0KlVeLtH+sGowoht/xjCcstwEM3ym1R1XYCNRYRnLdxtVwMXclpLUykxfe7WZY7OcLB+sLfz2d5IXRl5nRpJa745xjfZ10oZ55ZXKUNkLUI3JkVuWNmf225MPnZnJsnM5+Mly4bw0yFHjpjsE+IEOvaVgH4X98b6fg1IGjuwsFQnEvunQ6/Omco1AaisJifnel5dnyBSvTDQHMb2V8gqE+2ASdxKGiJ7zO/jmz7r1t4QYZImhkUCngbkB240c+QCzS/OX8Y3D3L1TTp6N0u3yPE6vofWVMmtkPs5psl3iUuMPD3+tLx3dnvpw3r5DmeT7TQZp9HRlRFLcIxiWstME+KCJp2qeDzBTn6GgcjWOmiNKFgIwt6XPN6VIhepaJJIu6w6LArayj8plDC+xfCx4ILFKVaUyj/cTrBgg9XYRPk2Wos9D4W4UyhXB8L9e+eLOdOuFm7c5frTKEkjQWvo6CyIJv2FbNogVj3dyr6atOxHh8LRRjdGhcsHnvsMXjwwQeheXNB7di8Odx3333wq1/9CvLy8uDee+9lQkddhz88Uxx73kGJmTrx4esirfDVRz7hkcPDiag62XkJ+09c2UEbX5kLj43bJouo/CdwUvD3q8Y638UOWcQUrhUbu0qICDKFUk2SVUJKvkZjoRK43LCFrikU77B0ApAp3CwTLAJMoYJ+k+HvpJzkxxN+VqNCrQjpYyEjr8KL3y6f0MMx7TDdT4XRFMosOOgzeSajsfCaQnGWbD0If/z0W+VvKu1DULjZMCvfnmspjhPzQYj9Sn6WW/doGy9GDDJpLPA37tA88Zg2vsmLiC6UMxfQTNGhOPguffiT45nQICbzlMHro0kRnzz/9oIRzLwE+yeslx9M7GmtNVX1y+K15dU4FFZszCqqA7EOcWFErbHI9UyYde0LNRkY7jIKKGzxdvPatePgigk94YYTjvGtaCO6XD84WZfbcBvUWOSZNRYo3J05ogv8YFKvwHJi2+3Xvhn7j9obHbKQLjo444SVC6hiedMS5k8L7poGT5w3zHM8F+LFTNC69qdbXEONhakN6AQLrrHBPk0ePvG+sjLdtsvbBvb/3BFb957y/gTnIhhUARNO+jQWsvM2hPOx4Its5QE+FukBPhbi8+PPzpQgLwhfFMVKGx+L+HbbvoK/JrqFMdFR3jF7tvaxqFJulzUfsj+KaaLPBR2sa1UbtjaFCgglH4bISyUHDx6EXbt2seR4Irt374ZDh+L2iS1btoSyMvvwpXXBiVsHhq1b+O0+TyeLLxV2cDxmuQjv+HhjFzUWF4/1Cwoy3LYU7RXvO20Qs6H9+4ItzGQJG/6Qzv7Jg6rDvHJiTzaRuf3kfkw13l5j94sN+erJveD38zbAX648lq1gYQK9BRv3sXt7du56uOGEPp6XMyhErEo6V/Upug4UV2z2Se4dfMKIGgsx8zaSpemwAsPNJjpNU5I9k+Clu574ouLnNKF75+3CH242hI+FYqIi953e+OVpVquXtlGwVLslbQqlOISHalQJhnzyJLc11WRfHtBEQRQn3WHy03iupdB0iqZE4nuZnxlznpuc9Tko3C3arePkCCd0HJVJCTosnzyoAwtdKCY44++OvICiM9HhduVrpPwVIrrJMmoa7j1lkOfdRvOtZ+eug59ZrHBzpvRrB2eN7MycZ2tLiLDRWHgEi0Q/guYuohCre76dWjRR+p3YIK7wo2YV/zjoi4MO3jxnkq5/xMm33PZxgs+1BQcTmYDRHwP7EO4T2L6FXuCUwWf3xo/Gs3fYJFiK+SXkUOziSriqLaiCoIjaoO8Sicd0eRZ0z4Anw5PhAp1OsMA+AC0c5EUl/pu4uINtAyfvOJHnmgjdQiffjsnkkNv+6TrBc+S+0jMOBGi1eXmUPhYBplCorROfE5rA8QA3fCEnmddYHlO8WbCD8lhAOFMoqQ5xco/tTjSFchPk2Z27PMBcSzbbsvGxELVJqro1Om8L041U+lhkJmMKhTkrHn/8cRgzZgyr8AULFsCtt94KZ5xxBtsHv/ft2xfqCzzbpIp2zXNgVHeMie3a/uFDx/vGl1B2tOaDOE54cBLM7TBRe4AJeWzhanW8jkpzIZKvWPnnndd1U/qw/zxbrQwOLLdO78dWGNEOm4csHPOL99lA8sScNcyh71RB1RykscDoHLIJmMrOUbd6rupYufoZO1/+UvAOSycYmHwsmMbC6TTTUqKxUJlCxTd5NRjsfwRTKJOPhV/NLQoWwn6G3t3jvB06QV6SplCK++f3qdJm8Ev4NBaKSZwsHIoDLHbKtja4MuJgywNAiIKFOAlFKwZdOwvy8UKHZB4W02RGg+VBnwcc9Ibc955jW87rRNSM/PmKY2F8b7MJpdzOxLwzOjNNZiaa7RdgrpncK9SKJbbnJ84bDnUNsW9CjYXHFCrRR4n3iZNpnRBmCl0bXA79EP7Ls4fCP77cCmeP7Gw0XcU2JD8T1A7xMOgYSWt0j9Zwwe/ne94l0W/GJheRmLtIhywcqGzGw4D9NgoSqLHgOUF0gs0+TXQnMbCBqg3sPhwf2+UFRt4HaE2hPIJFBhyGCtaP8RVxvSlURuiVcbFrk/s5ccGLw8sWpLGQu0x8D8T6RQ05FyzC+FjokIcUsU3rzIxc8yK76/IxUx6bsV/HrlDOGSJeI4gyzZyJX8uZ00g+Fqbz83NiG1Ldo9nHwj8nCbpetZpCPf/883DiiSfCBRdcAN27d4du3bqxz7gNE+Qh/fv3hxdffBHqC6YXtm3TXF/cc/4MVZMhR2NRGXNsUrEjGturdahJ6lYpXrUJcZKBneF/Xz7Gt4/u5cKBAgcXLlSI2zli1BAbHwvUkqBqHp31TNfXrRSr6okLf8zHQuowdKvw3HZQ5UyOGgK+iiAmMZIxrfDrTaFAGxWKt5lYlAR5hvKaIn6Y7Gxty+CJCqXofMRNUVY9THkslJnTudAotcVsG41FmixYQCRE4Y37VoiOq+KkE+ecusl4lHC3SsEicT0sl1gPvBzipHhy37ZGTZ14Po4Y9cXWEZuTjBlEXUKMCpXPfCwE4VGoT8yB0bttPosOptNYiBooBP1UdA74MqaIegVNc5gwx/t0OdeBaB7rD2SQ7nGcPuuZz3yaBfFZqrR2QTz9vRFMqyLme5E1FmLb0y66BEwYuTkUz+acpxEsTh8eF8Bkjb9OsJA1FnLuFax/xxRKdt7Oz/II7I5PpiBYiG1MxGSyrZtkh40Kxeudr4bbChby72JUNcchGaIjT4R14VLVUaHsrsH3k6c3/PzF5dGdt4sl80TnPBofC5s8FmJUQaXGwjAQi+c1JSKsMcGiadOmLArU3r17WYQodN7GzxglKj8//iIOHz6c/dUXTC8sahn8SW64HWJMO0nAhrQskWSnTTM3UowtQSFnRcSVgh+f2Aem9mtnLVjoQsPyzhjhHSE2OkweFLRChSH1MHSg6EyqmtDqVs9VK/K8XjGpmPMSppvNlRyNRZDztmGSZBI6bDQW8qoV/oT1KL/zVs7bPIqVxeRZFw3EKFgY/DxC+VikSGPB3zvV+Zzkhz6NRbCPhVgF8clg8pNePiEUNRZiveM8UNfObKLSyahMoVRmOeL5eZZtW/yChdvPBAWWaKiIE3o5KpTo33PjtGPgg59MYe1B93y5LwaGL0ftxd2zBsLCn01zEtyJTusyutCeYbLzYkhWuT/A5yom3eL+CXKZOWeP7OIkkrMFoz/94bIxTnJGOTCBTNRVVO5XiDmoTKZQKND98fIxLNIYvrKosb/nlIHaMbuJJFjIkRVReHD6/qogjYWrIQh23s4I3Y+a81j4j+fvNV88dLX6wVGhxNwroqmeHEI1CuJtBUXC8uexsPSxSOwnL1bx9sefj1ge25Z5OJGjxF/GxH9psVQssW6yjzm9TFp3U9mqK9xs0gnyUMAYOrR2InOkGpXzZI+CPPjR1D4woU8b+EpKhmeSgPkgIibGEiPF2BImYojYUanUm6Yy61bkUUuDWXuRfUXxwQUT2v36veAY6zzqhThoqd5t3ZxdNfnlzwjDzfKXMUjFGuhjYWUKFd7HwuvIHIN06Rwq29sgLRAvs6686UYfC7ASLETNjlylYucWC9FRJRMVircj1cDBd5d9U7JDRoXCFdeoi+linWDSzNU7D3vCa4rUiMZCOL93whv//ONpx7BIImcoVmhVyCvtog11VIf3+o7HxwLNnIQ61y1wyHX1/i2T2Wo6346BNn56cj9nAoRRtv72xSY4bVhnOPXpT0KbQsmItuGycCq/G/jMMQTvW0t2KGPky1GksOy47fh+8YztYcAFKI6sMReRX/+JfdrAJ+v2sGzxJrg5FX9NdaZQWO/o04MRzu4sHBAYcll23u7bvpmTdE+cA2CXLvdruAAhjtc8MiLuxoU43UKnKcgDtiXULsj9oTnztsIUivtYSIKFbnFVvD6abGPS3mkD2nkWc/jtpsrHQh4rdeHt+cKvtcZCypskX9vrvM3HertzF2nyTbjh52Xn7TSfKZYMf0ZMY6E8t748Hj/QuqCxQD7++GO4+OKLYdy4cSy8LPKXv/wFPvlE3QnWdVQDO/pV8OywfqencDb5JvW2zkHsj5cfC1HQJbjSmSLo7uWZi0Y6n/cnwg7aCBVIRuItSAuY0Oq0AbKJBovCJThv88Yf5HRrigqFL7KdKVQYjYVObes3e4qisXB9LNJD+lgkbwoVZOrkNZXSnsbq/D6NheKC2Kk+/eFaWLBxf+hws+Kgh+0q6kqaWKxHzxrKovOM0fhRtc6JaYXUatFYKEyhcAX3hUtGG/MQeM6XkaHXWDRSwaKJQWOhQ26TGEJYdhgW31fMUYS5Fvp20OcYukARHVAHz9mgiuzlM4XKzICR3VrB0vumM3M5mcvG9/BNds8e1cVjAmiLWHcmjYXcN2IbfvP6CY4PiQ6eJI+TH+Drgc/AJo8Lny9wqwI5epqTwZktIHmPZSF3RcFCKBMPEKPVWGgECxRouVDriwqlMYlVffdk3k5o8/nkXB5zVAnysN18escJ8OzFozznTkuJj4V7X/I96kO5VoX0sUicT2pvvP2pBHTbifgRjWAh+1ymKwULncZC8LFQjOvWeSxSqLGIPCq8/vrrMGPGDGjSpAkzhSotjUvthw8fhocffhjqI6oXVnyPfE5PhnaqCgNp6qxevXocPHfxKE+HjQnvRP8EG357wXC45vhebDUnlMZC8wNGhnksESt+w+4jvpjmJvg5xUFL7WOhPl523MMXx40KVSWoDc0vnhxxQRcVymwKZd8Z8hdZjpAkv+BYnkg+FoaEfv5BAyJoLPQdTLCPRepNoVwfC/+K1MtfbGaCLs8FYVrV84WbFeoA97exdlO982KGErRLx8g88irgk+cPhzOHd4Rx7dyoUDJBUaFs+xm9KVS07l4MiylPeKKes8FpLCzqQd7Htu6w35t362RIE9rZcxePZCFqcZXclvNGd4GpCo0Cak3kCYnopyP3feg3gkJPqhAdWk0Ro+T8CCjcYWjlIBMXOcR6sg7huj6GJ66T+2LZDBafHT5TcfUf24LcJeuc3XUCB57PMeMJk8dCcS7+/PlknZ9PXhSR65636c4tm7B+W+xT5RCqOrivispkzVm0q4rByws2e35LXeZtrrGQTKESX9UaC0vBoqTCynnbMYUS6k8rWAg+Fqq6NZXNExI/ybFbJPKo8NBDDzEnbfSzyMpyX6jx48czf4v6iMp2UfQ9EOdx+NxVHdq826ayP9W5TBoLjPZy8uAOHtMGmygaKge0O2cO0Ha2eh8L/UvHBSLMG3DKU/baKJU6T3V9XZl+Mr2vJ5vvGSM6CatE/gR5ujl5oI+FM1EPp4HSUanysahSZ9mO5GMRQmOhWjEKExVK7l8Co0JpwtelIipUGH8jlbmRT+MofMdFBZ35oLcs6XBC/7jvEs+4bdMHnzGiM/zq7CGA466uLZlMHMJoLHK0Govw52fnEMqL7UssZ5j3oiEhmiDhRE+cfKdZtskw/nboe1EgLIijY2/YELWodb3lpH7aibdYHLHdiH0Kmi2h30gqGZeISqZbiUcnb7z/3104ItL5ufO2zj8kKnJ5ZX8XJx8Cy2MR7yRe/sFxcPLgjr53R36v2PlDaizQZJT3aX7nbUNIcsUrrNNYyFr9IOdtldN4UACHGYPas8Azc2453id88/Hnzn8thcfeXW3nY5Eou+3rxssp1yH3lRF9lfh4ZzsPP6IzhZLMp1X+KLprlFa4PhaqPsUcbtY7nvPvtZbHYvXq1SyztgwmyTtwwE0iV59QvbCiHV/QBBnpVpCnN4XSmCeJiJ2LzsksGbRRoQyTajHE5VZDoj/fOROdkNiRqPoUnVDTsXkTmH3jJGbD+uHKXXDKsI7w1IfrhAR5IAkWMauXVu6MnIm6Yck6TI4Dx6FLWg3wJ/dxtS5B6lwRPkhlSyvJQVo1Tx4Lw72aokOEcd6O0jmpzsmFe9mB1IQqSo38SnpMobIzrAYezAXwm/OGw5tLtsGsofHQy2FvU+djESWyjlJjIZguqUyhwiJrQHQakcaEnMfCRkgIY06pQjw8ar2r+jG+mCW+euIzFhdcwgSxsGVQpxbMpEk34Ucnb/yLihhpCu/FNuJWELIGRf6u0liIY6lHsMDwzFkZntVwrY+FZl4gatxNPhb+IBbBPhYVtj4WBuduJypUwLuCcyAeeAbbZmkiVD/ChybMKSZTqfFPDKux0EX7xO/o2ykS1sfiSJApFC9rohrF11U3ngaFmzUnyJPKEYsBemrUmsaiY8eOsG5dfJIngv4VvXoFZ+JMFc888wz07NkTcnNzYdSoUczvIyqqbL2HS7wJ8dzP5nOpTGdsnLfFwd82Q20YImkshCRFtuBlVKpP1XV0ZeImGGi3e96YrkyDw8PNvrlku/OS8nPq3gVzHosq58WUTT6iwifjsjOUfHnstOUXWOeAZquxkMd9XZs1zQ9M8azFr+o8FuLn1GgsuJP6IeFdDEI18ZInReJX1ISlW04O0dzp++N6OJq8sLepa2emPDpRfSzEZx5ZYyFpQHTO4Y0JOfN2TSA2m6j1rlpAUvUjXi1VsGN6sqBJU9QkgUFgABYOXiNVIY9HSmbKOF6jEzty0XHdnHFJDIsqjn+iwIaTbXFREetZ94xNPha8DzNl3rZZJBM1Fjh26aNCScdJZRZ357cbdHlxHibPgfjYejgx9v/fjyc6vi3BUaHACjfapz8qlByyOZYqH4uYd/HTjQqVZm8KlaV23jYVzT//CCco6Yg8KlxzzTVw4403whdffMFeiu3bt8Pf/vY3liDvuuuug5rg1VdfhZtuugl+9rOfMT+PSZMmwcyZM2HzZq/tnS2qF/bQUbcheKMbpXkSwSGi/apqdcpmpcSjsagGwUL3cplMY3gGVlNGYPnexAEoyMdCpy1R5rFIrOqK2U75KWNRfCwqRVOo1EySVC9nfJuknahIvY9FhkljkW6rsXA71JjRedvsY6GK8BQt3Gy8rIeS1FjIbU+sK3zvrDQWijq/MOFAe1zCNKomNRamPBaI+AiinJ+dTzLZECdEjVWwECdH+ZLJajLOqSbEbjKq9kk1qVQV16ulEPryepiHhFsRJJuMUEb2Y8R5wFWTejHty89PHeQ6b8dcUyixbXhNobzvpymkrM7Hgvk0aFbbdSax8m+q9zoeOTFmpbHwa8wVGosAk1PP4qr0bvExh0dXQi2R61eSKh8LvcZCdtx2/SntxrpiTWQ216pCnSDPdA3HFIo9f4XGwjIYi3gN0W8wCpFnrrfffjscPHgQpk6dCiUlJcwsKicnhwkW119/PdQETzzxBFx55ZXwgx/8gH1/8skn4d1334Vnn30WHnnkkdDna6IYeMVVUp1Jz0uXjYZ/fbUNvndsN2PHLyYcshEsTMmPoqIbGEwDRlDIW1ViFvF8nnpLtxdqVKtjSqdcpwMHY8eiCuWKL5JJAxAFfVQohcZCk4QnusZC39F7hQzD+YXVLrlT8pg6KY6Vc3WERWUKxgezMKZQqtV/nymU5GNhM/Co/HBwtfWLu060NrHQtbMok0VVH+ERLMTtEdu3LDyI5W+sPhbigMwXpC48tht8tn6PdbStsIiPIbLGQtGnqjRZ4oRQPCZMotC6ghgNK5WLdXiuKf3awtzVu+G6Kb0dp3DsD7xOwG5YcbH6fT4WmXZjv84XC59NVSyx2m7IYyE/QlW3J/YVYvjaIB8LuX2pFhWDZFPx/ppKcw8shpidHAULJ1O2VmNRFU5joYmsJV7XP9YnF/K5MnG8LIDK4WaNUaFQY6G4x6oIGota87FAfvGLXzBtwYoVK6CqqgoGDhzI8lrUBGVlZbBo0SK44447PNunT58On33mzRJqi+qF9QgWwkMTpW7MnIq5LoL8KYJW/uNlqB1TKNOAEaQ6Vk0uxA4o0HlbcX7s2FS2mKqQwEE+FrxjUQkWOEl3TKFSNGiqEuThNrl8WB6+DTtk5u8RxsdCmcdCWjHS/GbSWIiaBrPztsrHApKKha0yBeO+Lzb+J2Eyb/uctyNqLFQZg8OWLarzNr4jGBL02bnr4Zm56/0ChFBlUU1AxPPhGVSJvRobXEuNEWx4vT5y1hDW5sMmQbUlIw0fZlpSAp28gIRZwacN9CdS1Y0N1WUKVZ2Ivg98dTdV4DOfv2EvyzUi45pCuX2qWP9i/41txhvCWD/2a523M9Kd8UNO7pamWeiz0VjgOMX7XpNzdtC5VcFcVIhjfEvJ8R7HnyIhQR3OkfhQphs7o0aFkv1U4qZQFeoVfsuxrigg8zYf21Vm5LpruHkskvex4Lds0nLYkPTMNS8vD0aPHg01zZ49e6CyshLat2/v2Y7fv/vuO+UxGBKXh8VFDh06xP6Xl5ezP5WlAJpf4G8MoaHhA3e2K2glxc6+d1Z/6NIi23gMkskGjzg56eZrRKGyUt2w8d5M13r7hvHw7d5i+OHLX/t+S4thTgnvNhyA+PliMbczxyqWr1OlKBNO8lXlUT0jPB731b0MZeWV7HcxrKH7WwWUVSR8NRRli0JFRbw85cIghmXIlspeXFIG5Ylr4/3GBQv3OTzy9mr4eN0e+Oc1x3kGmtLy+DGqMV6u31hMMGsSnrGpIxTLXQUxz/l4edl9CmVVOdBh3YatT9XAny68E+EmYdJ50FZYrJvKSs8gXyV814HjatQ2wo9Lq1JfJz1mfgd15GagyYAgyMfi7R2pEp5/Kto2DlJi3UYtc30Hq3vx3SewyVyy7cF2X3FOJz7jMMSktvfqVccmnqG3bxTPnS6tQNfn541WCaksf5u8TDhlcHs2BsmvNfa3SEVlpevkW+k+NzF8cFosBjmCoJGbqS+nzqIRfXD4mMDHCKEwbt8vT5iFMonguXBILSopc8ccaTyQBRhsX+Lv4nyDjz9Vmv7PvQ/3Gq3yMn1j04EjJa5PSaySORsjfByXqXDGFG/ZdcQ0C5Fl5eVw+Kg7f2T359yTpWBRqi5jeeIZuO3EP6fB65eX+wd9ngkc6001v8N5su6+ca4iUlJWBmhYg+WpMcHilltuCWWmVBPIq0OmFSM0j7r//vt92z/66CMmIK3Yh8dJId+gHGbPns0+L9vl/o4PkG9Xsf6QW719msegYN8ymD17WeD9rD7gXmPh5x/DxhT7s+08qn7s3yz5GtK3LjYei20+HTKgSrKRnPfRh1BahmV2t1dUlDn1s2a7e0/FxUW+eitmbVty0qpS1+9yxTP68IMPoGkWQPFRbxk4K1atgtlHVkJxqf/3b5Ythx3FuC0d1q9bA7NLvCHsorwuS75ZCvk7v4GVW92yfrN0KZsAimWf98mncIh1FBmJyWYaFJWUOPf90ufx6/3ib3NgQnu3g1n7LY4s6bDp240+N6miI4c99fbtpvi+yOpVK2H2oRXOb6pniWzdtt05przc+xyW7XfvadeuXb5ntG2He73lK1bA7P3LLWrMrddvN2323dOqFXiOcKv569et9R2zYf16mF2O2+NsOeJee9OGtZCxJxb4jI8W+dtvWOZ++IHyOnM/mANRrR9XCG3tw/fd8+zd57b55Mqd6WiKNwvt7rNP5sHaJkmcttHhPvewzyNDCGo/b+5H0DxCcKNDZd4yYFtxfc/VZduy2X2n5f6lvnBuzzR4f1s6jM39rsbKvzwxX9i5axeUV+DnNPjP3I+gVSKGy7fCuPjdju1wlM3l4vVcUnRIW84NwtxCBJ9NCTtHGixfsdLT/23fth1mz97KPq/Y6R1DMT1A5Sb/xDgjLYOZVr075wNYvz3eBjZuWA+zZ7t9aHze65Zl8aJFULrBPde2Ivf3ZUu/gfydS2Dpbv8YLrJy6Tcwe8cS9nmvMJ4g33zzDRzeGO+ns9Or4O2334ajxfE+bvUaDCbkl7o2fLuJbd+z2z9eqVieqJ99+w965gsfzf0P7D7qLfuB/QfZOQ8XqeceMjqt+44d8XZZnLiXzz/7FLbkc4uBeP3NmfM+m+fIbEiM8RvWroas3at8bWPN2nUwu1Sd1HiVMG4g7815n/Ura7ak15xggQ7SImiKhNJQv37x2Nhr1qyBjIwMFp2pumnTpg27lqydwMmOrEPqF58AAE9CSURBVMXg3HnnnR7hCDUWXbt2ZX4iBQUF0GzdHvjD6ngOjqcuGAavLdoKd8zoB8cksmKXLt4Of18fFw6ys7KgsHCGtnyb9hbD75bHcz5069gOCgvtYnC327Qfnlm5kH0unH5ipEymJjbuKYKHv/7Ut330qJEwfaC63kR+vuRDOCg4tCMzT54Oj6/8BI6Uu2Hh8nNzobDwePZ552eb4H82xSfszZs1hcLCCT4p/s6FH3q25eZkQ2HhVN/18RnAaq+ANv2kk1h89YeX/wegzLuigPTucwwUntAHblv4PluDF+nXfwDEdhwG2LUDBg8cAIUTvRllRW78/D2wYeCgwVB4bFfYOHcDwJZ45LQBAwex0KB/WeeWffSxY2FfURnAmm8gr0kOFB8pg8xM97759QYOHASFx7n+O1/NXgWwYzP069MbPtyOkzyXli2bQ2HhOOf7ivfWwgeJfdBUsXB8d+e3WxfMgSpFR9e2fQeAvbvYZ3zHxHaes2oXvLAqrrVq07YtFBZ63/W3Dy0B2LuTfe7ffwAUTtDXp6peO3buArALBRuXEcOGwGsbXYHIhv79+sHsRN1z+vXFdtDb+b5ixyH49dL57POwwQNhSOfm8NTy+Luno3Urb/2GAVeN5syZA9OnnwQw/yPf76fNmhnZXGn9R+sBtsRNoU6dNdNRpf952wLYeDge/ruwsBCiwp9RdnY2DOjXDeZsi1/rpBOnQqeWJFmErcewzwPbzourPnCPnXGSLz+DDdjf3LNornuek2c4UXh0ZVvy9mqY992mRPtvAYWFY6G+gXdT02l7y7/eDn9bvwxaF7QFOLSPzRKnnXiCYzZ5YMEW+PcmFAAAunbpzKL7LN8f7zs7tWvj61vFfuu3y+P9lkib1i3Z2Ly7pAj6HNMPYLPb/+H5CwuHsM9Fi7bCqxvc/nTM6FEwbYDfHO7uxR9CeUkFTJx8PKz+9FuAndtgYL++UDill2ch9+b5c5zvxx03BiYJTu1rdh6GX33zOfs8YvgwKBzeKV4vwjgoM3bMKDgxUR6cO7y/zV3sGzR4CPTHTPRLFkCrpk2gsHAy/G7dp7CrpAi69+wJsD3eTkU6d+nKyt6hfXureVjRom3wyoblkIdm/cVMMmJMnDgZVu88DLB6qbOteYv4+/DrVR8DlNiH4pdp0w7niCPhwaVzAcrLYPKkSdC/Qzz55U3z4+/lCSeq54Nvv7IEYM9OGD5kEMut9MslXleA3r17Q+FJ6twzG4RxA5lywgnMvHPtB+sAEnPdahcscGVf1Eg0a9YM/vSnP0GrVvGwa/v374fLL7+cRWeqbnCAQwEGB+ozzzzT2Y7fTz/9dOUx6FyOfzKY4A//mmS7S0ATj2kHpw7vIu3nSnY4ARATA8p0aOU6jGVkpBv3FUlPd6/RMr+J55qpICdbXY6cRB0EkcVi5HsFi/zcHL8Tl3DP2YJTGoYulK+Tq1hlSE9T11mBIiRhdna87DptJEZmzszMdEyhLhjTlTnbo20i/laZWGnIzc60fk4m0vk9io7TmLxIyC+A4HXTEtu4AyWaQ8llyMj0los76GUJSbpE3wlx30wxHn1mhve39HSlytMbMjb+frj35t5DDFTvgOiIFNzu/Xky1G0zLNmKupHvX3wXmuZmK4/xnSPDe44oyMd/fPtUZlKTk5NMfH3BjEI8jxiFJgVtG7XBOWJyuNyclJy3MRK23sRXI79JTqSxIVca/prk5igDd4hlE98LsV8nzPD+OSb6xSXGKqRZE/c9zczI8PSt6LSsq+dmTdSLjdi/ZWbE+3NZE40LRPx8OBZ6j1NfC/2nDuO50tKhoip+vhzFGIldDO/G5XlEtudz/FjVuCWSl5vtnKOt5LuG42hpZZoTahv3c8LNa4Kc8rpQzT1U8PYur7nhWF2eGHv5PeMueM4kfZ2Bj6V8/MOxiZeVm6RlZKifE9eC5OXgGKa4P8N9Y316dk1cQ94elshHP/7448y0iAsVCH7GjNz4W02A2ocXX3wRXnrpJVi5ciXcfPPNLNTstddem/S5VY6UNgnyVMntMEu0LaLDr8pRudryWFg6LqscnFXbtFGhLDNv66oXE+eM7NZSeS2d34CYBA/BzORnjog72z0/bz3sKypNSQKroHCz8qQZOwReZl6HssMYIlcFvxeVI6VsBigGGfCHBrRJkOf9LciUNGxUKPn8Kgc8MfGTLTZOpt4EeepgATLVkRCua+u8pLMB60ItRnGgN8EMOoRqaqzhZmubqM7b8nthoyATjzElESVAOS6J76bY54h+c/HM227d8hw5KnRBXXAM0Tkee6NCSWNEmrmvw7DoblQo8/htcuZ2cjME9LNi25Zzf2F/xnNB8Hpwo2+pc0CpQv1GDTfrBk5Jl5LhQormDDFPGcRya6NCJRZMsS9Wvc+y8zbmZrvxlcXwzrLvFM7b3nJEJXIvgWZEO3fG1XayKdLhwyjnVj/nn38+CzH7wAMPwPDhw2HevHnMTq17d9fcIwxiu1NFO/FMlgPaqPjyhBEs+rRzo2pVR3QR3Slto33I0aN00ZvE/bzZN/3nVCfNU18fO6obp/VV7qt7F5iDleCIhS8gF6QOFJfDp+v2Ju4lNfXthKALERWKT9BUE2u5Q+QdqCqSl1yX3g7KfF73/GJI2Zh2oqrOvC1+Du6c5D1UghVmuw6LzSDiiwplcd66Gm5TF2oxtWJF4pzCSRtrVKjaJmo+Cfk4u4zh9TuPRW3h5FcQxh6x/sSQsnKCPJNggaZU10/tAz8/daAnFHw8jwW/phxuVj8G6xPUJpLkVVY651MJtOLRpjwXqkhHKrKFTJBycl7s5rhgwaN9OQntgvJYWHZVujpkoel5osBE3fDxMNkFnCopkqRKWAvKYxEP+++vXPmwfy7aCv/+ejtc+9dFvnKnKkFe5KhQaH6EZk+onRg7Nm5zOX/+fLjtttvgrLPOgpoCk/GlKiFf22audKyydTYlmTFxNIRg0a55Lks4F5Q7oiYzb4vIK1a6EK2ioOLpXJQaC//xpiQ6/lU384v3xcZ9MOPJeZ4yqwQpUwhWBDUlX22O26ubcCI7ePJY+DsfNM3i82jRFAoFErH9yVVm0lj4V6P0bVbXhL1hcr2/iV9V1e0RPCx6J10cbZEomiRVe44Z6irHOo9F3ZxI6zUW1XvdulofDZFUPMoo4WLrex6L2oL34aLDrtiv5wsZ2/E1EsPIyiv1MrfOiPu1/tdH65i5Eh+/VFoSXw4juZ8L0FiUVcSckKbK3EnsfGqtgDePBb+cuQ2J43BrKWw/CzcrCRZOWN/KoDwWdm2X7yZHhcKxyQm7m6gH3r8mOxGv5BN6KdxsvEDxf7pLcBNvzGOh1FhIhRPPLSedlTOARyXyqPDcc8/BrFmz4OKLL2YaAvy76KKLWObrZ555Buojvds2ZXGpX7hEHT7XK0Xan7dv+7gTTpgY6V1audlCayRBXlpEjYVmxRLtGd3P7nbVy43bTCvtMrpsn7qX+5utB2HLvqPOeXGiqrQrDlh9ffWacfA9wYk6cPVBWt1XJshL7COu/JZXVXkm6HJJ+UqKWMc2q1GmrKie80uaFtW9qX7z/648vXb/oAR5YbBxgjYlyMMMvQvuOtF3TKpyndRnjYUIrWDXL2yel7yPty+vm+2/LsLHVHGCKvYxTQRfA9wumkLZJtsUTTOZKZST3E3KY2EyV9JpLLhgUVnlnE/VF4uH+zVi/usENSFReJHrQdRYcMGMn0+bebsynCkUv4ddh72BYMQM6ryMqkXEMPRqk+/NHxHTzzV1C3WOKVSGLo+F93vzXNff4pttB737OrZdkBSRl8UxPCsKEI899hisX7+eTYT69OkD+fmu03J9BLOn6vCaQgU30reunwivfrkZbpZMd2oTrSmU5YRJXtXXrViKq1xip2YSbCrFuN6G+pXL6mbeDn4beHlVglSQKRQe28nCFl5lChX3sfCbQnENkKgGxxUIsZ7lovLOLcjeVT7WbwoFwaZQBh8LVT8X2hQqFmwKlS0NNHsxklYKVmZNCfLQJBG1h/7zpnaFPlXWjjrBYnCn5rBkS7CWLQyp9tsgbOs9+ZqyWbWV+2hRmE51+2/I8Hrkq/1+HwshGEwIUyjdYhiOTxmaSbbHx8JyEY8vGsYzb3t9Ab3Hi+1DOrfwnV832MciTevrKvpYNM2JT5DTLH0sbLtavYlwfNFPrBsnQV5in6n92sJHq3cHXuOZi0aysWz3kVK4/uXFziIk/6/yTdG9/1yw0Gfe9s87OF9LY0OtaCzQMVoGBYmhQ4fCsGHDfELFtm3boCGhcqgxMaRLC3jojCFQkOKQsdVjCmXXFLIsNRYeu1wLTY9vpd1QHF3HePrwTvqDpElqUZnfPM1m0LQZmN1VDG/nJr+r2GHzF1lcrcLt4ssvq44rIvtYhNdYyBNJz6RSKViYNRpRnLfFwUo0VwxtChUzOW97BYsgu+NUYbuKFoSoHRO5Y2Z/uGZyL/jfGyam5DpEclx4bFf2/8YT1eEf6wLyoov4LtXHzNu1has9EE2h3N/zBFMo7Ad42N8wgoW46ILjgWMKZfKxMAT4UJ07nnnbZAqlvo5v7Lf0sZCv0UIIq+w1hYrXl878y59523xd9x7U23EM5/Xq+FhI4+KxPQusroGO58f1KnDq2GcKFcbHotzsY6G6D458ylT5WIQaJceMGQNXXXUVLFiwQLvPwYMH4YUXXoDBgwfDv/71L2hImOze6wu6iYztgCHHTtdFyfH4WKRbCDaWnZ28L37kL9PPCgfCk+cPh1+eHY/XrYJ3CLslNaftpNHmufOX1eur4EaAUjlvY+fIhTamehbfbOmavHOz01jo26y+A62y0kKoOjpxk41gEdbHwjavS0tFjH/ZEV1sl7IplK5uojiSm0jV2XT2xRiS8c7CATC4c4sUXan6/TYaMg+ePpgJeXVZsJD7FfG7bfRAQm0KpYsKhfuI5rC2/Zw4CUftN+/vTRoLW801roAjqCHgJqqqxTeVg7b6ulywMLchecHs0ztOgAl9ClxTqJKEYJHwQ9VFcYoaFUo3Ocfx29XcqH0sbF3OshL3KFtbuBoLsTz8Gur74xox26hQOid3r0lWrOZMoTCk68MPPwwnn3wyi3U7evRo6NSpE+Tm5rIcFitWrIDly5ez7Wgihf4WDQmVFFnf0PlS2NrO3n/aIDj96U/hcGLVQGvapDEbs3UeNxVHd25cdT5jRGeYs8IfrYzDOwRUQfp/szCfCbEiIEdQUoWbFW0qsWyYV4KF9/NoLLzwzk2lZfLXo6nuNRoLaZIavw+/OlbV9STtY6E4SHwuQRqLXm3zYXT3VjBtQHCyR4/zdmY6FJfpB0i3LHVTY4Ht/tUvtzD/rOqG5IrooJAcVcirqXqXhQdRsCeNhT28e9b7WGR4IvuI+7XKt8sVIloMMI2FI1iozYLCRAbr174ZfLx2DzOl5OORcoxMM4w/olDKBYuALlTuY9FJu3MiCSeOF9z3oWUiYpQbYtcsWNg6b+vmSJViVKhEPcg+FvaWH+nxsnPHc2bR4Fo1eAIFBbz/peUJU6hMnY+F90jZ/0a+R3atmtRYtG7dGn7961/D9u3b4dlnn4W+ffvCnj17YO3aeIp3dN7GbNyffvppgxMqknHerkukaZ64rWDRq21T+FxwatX6bAgvmGlFQ7fd1AmI+6o6AdPcLysRym6PSmNhMWm0qSWV8za+y/ILjraRXPjAOsoWw/sJnaRcF64DmUpjIZU3zeTYrS6/vPKj86sIdN62igoFgZ2e+FzaSFFCZC4b3wN+dc4wK+dtsY6x7sW60rW/lEfFSdHpxvUugI9unQJvXDceqhsKMduwkVelvaZQ5GMRXmMhmkKpx8KS8iooLnXNc3mUwHDO2+nRTKE0fRBmcUYWbNznaiy0UaH89+S/Lr+eudNTh7R1F7Y27D7icXx2w8MG5bEwXtYtZ7rBFIrnsZB8LPhYZyt4ZyXuke8v57lSmZDpfNscHwtpDNOPsfpxmVsrJOtHF8l5GzUUGFK2JsPK1gW86qn6KVkkG27WemVf04Hqqs0UTcLsGO7/3fRseEd8xohO8F+Yzj6kYGGzwuw4b0uTcL/GAsPN8tUUt2zYUYgv/+a9RTDukQ/g8gk94OrJvZ3VKHX+j2BVNCfNUrAQTYiCNBJhnbflZRiVOltsb3yVSodp4hMzRMdAm9d0QYulNYVKucYidefqmRhoqxNsMxeN7Q5vfbMdpg/sUO3XI2oeuYl7nbfr57hXq87biYmfaYzFXFe6xHe2GgsxKpQcKtWbx0I/+RcZ0yMuWKzddcSJzhS0mCUv9KluOawpVLzM4JhlbT9Y4ixy2vlYVKXEFArHM16vjmCRqGZ+ZZsFLfE94vUlRpzSOW8rx9sqNxSwzt/VZ4Jt0GbxZlNreSwaI7Jtf31E1+7DDBhiLgudL0SaZUQK7aTXcH2PxkJxPlPoXD4x/PGJx8COAyXwr8XbQglMNs/dyV4pRYXyveCYx0JQfYpROMSB4XcfrmP/H569Ki5YGHwsTCtGcoeZbu28LX72fPEd6zX/gkB8alqVj4XQ3loFCRYhNApoOvf+LcezesR2YRO9LNXhZoNiutcV0An80bdXwS/PHspME/73hkm1XSSixjQWQrhZ8rGwRp7km8YlXEw6a2Rn+HzDXji+b1vra3hNodyoUJUhfCx0xWqVnw1dWjWBrfuPOpH49Hks1O3DM9HmGouge1JpLBLX2Li7iP1vmZflOLin2fpYhEyQ5z+PaC3gPRkfxmzD9mcpTKHEsVCVjFm1UMe1Fdy0TpWMWZYjzBoLr2lXVEiwCIFKimyMGgsbqVwXYcfexyItcthf07HcjANVzacO6yQJFqmOCiULFvo8FnhLbhQOV+Wqwk2Qp8pjIWsl/B2U8xvYmkKphYUgjYWuo9edW6fOFoWFVnlm22OTgBwLyHRvkwAzSrI+E/VlAfja43vDpeN6MGGMqB0Ku1bBygPpzNyvOpH7Yk+CvPrSYOsArr+Dq5XWgRNCDK361IUjQl1DXOjwmEL5EuSlhdIqiMEfAOI5oHTP33zucOOz7hp80zrJDMpGY8HNuJL2sVAkyJPHentTqDRP2bHo4ljokce4xqLKnHwZ2w/Xjongeb/8dh+8unAL/GzWAOPcQhXRMgokWDQyHwt9VKhoEyabd7V6BQvF9Uw+FsLEkEe9CIpwJWLz2PlLKc6R46ZQksbCI1h4NRa6mNzx8yYcxQJiise/63/TdbQ+UyiNkiLIx8LGTtNn/6k0hXKfS4sgwSKJib9Xy6bTWKRWsOgTMnlmbUJCRe3SrSnAN/ecCM3zg3PpVFtUqPo68NUC/kSD+rorUUwIbcgWfDEwYp3ryCwnyBM/240DYkhX5xpB4WbTgyfpQU3IZOLL/St6tvEvCKXMx0KzH45tjhO77GMhRHcMpbFIlB3L6DGFUsw1VeMtFyxw7oDX1iXIO+e5z9nnwyUVLMBJmMAzUSBPrBCETZBXF9G1+1T75OkcutJT4mMhOIZHNIVSOcg1S4SvM2HTb8Q0Ggtf5u0KISpUutd5W5WBmsNV60pTKINWwlYFLg9KuhCzqr4nSKMhI3dgQXksWjYJ8rEwPKCAzrImw82+ef0EOGVoR3g65Aol0bipCeFO7lNFjWGqBeuGjCmngy4XQVg8/i8ZGG40/l0eP0zmyKYeTQyJa/P8fWHjRYEmcaUgzYHqd9nPoLUQNUucnFenj8X+4jLnGq7GQjKFCilYZIimUMKw6/FLNTwhbvqUm5g7qILziGPsh6t3GTUWqUqQl5TG4quvvoKPP/4YsrOzYcKECSxRXkNGpZ5q7BoLHeJVxEuaMm97jjfUr1hU5YqI4eUWbVLFpHSu2jd5MzCVnaJKY6EzhWKZTi3sIJUrO4Zwf1F9LMSvcghdGfF3XdI2z/6+a/tXncT7bN7E3GUlY6rhaafVnCBvaJeW8PT3RqbkXASRSkZ2a6kdG0hjYY8p9KqMyjY+bIQ2FDLcqFCyxkK/aGKacKM/VZAPmzg+yPMItSkUhEY+jRiql58vKNysrWChK993B0uccOh8rOZDnBMm1tZ5O8PvvO3xsbDVWCQS/fIFB9XVxeNk/03fvo7GAmpHsHjyySfhlltugZYtW0JmZiYLOzto0CD44x//CKNGjYKGSIMwhdJN7CPekI2AZaPpkTebiiN2XqrTmToQccUFbRLdz+naqAqecgZMarFzc02hhEl4lSI6Aws365aZl62sMhYQuUHtQBYkoFlHhZKFmhBaiPCmUMHO2+J9BmWkNa2oBZXGJIRxyMacaKi8d/NkePPr7XD18b0828nHIhpyV2Qa02wzbQeFmxWdgb3XFsaBEGbH+bIplHIBMqY3hbJY/LJBLmOuoLkL1liEmyXr5kLbD5QIplBpSusEax+LdO68Da4plDAWqkzXVLfBBVIuaKmeJR7WPDcTDiUSC9o5b0NShFp+e+mll5iWorS0lCXKe/TRR2Hv3r2wa9cu2LRpE5x++ukwZcoU+OSTT6Ah0hBMoXREnTClhVz9te1UTNUrPgfV3NV0iexEhyALFmLoUXO59CeXs2iKZcNOw83OmaYINyv7WBhMoQzhZs2ZTyGixkKtpVD6WIh+JRZmw/JtqjJIYxjG578/Cv5w6Wifal4mmRVVk9lYKs5PEHWZvu2bwa0z+vn6wqAofISlKZSi7v72g+NgfO8CePy84ZGqsV+H5lKCPFA7bxvKZRpr5RC4fEItIg4DpvGHX0e1LQi56vKEsTvIeTtVmbd3HDzqy7wd2cciM803Z+BzAdzkWRBMD/ax4HMZnY9Ft4I85/t3h+LhelW4c5caNIXCbNrr1sVDX1ZVVcHChQvhN7/5DYwcORKGDx8ODz30EHTu3BluvfVWmD9/PjQ0GoLGQkfqBwz16q/uMj6HMoNuwCNYBPxuq0ZuauFfES8nWAsWXo2FGxUqnuW5MmEKBa4plCbcrAyffAdF6JDr0TakrykqlNd523+sx6/ERmMhnUSnqZkxyC5ngincbFA2bpsgAw1tQYEgghADIpCPhT02AUkm9GnD/qIya2hHuOuNpezzzoMlzsKdP0GeUK4QgoXPFEqhsYiFTHQrbuvaKg827yuGIOS6E32N+E9BGotknbd3HCyBHokJupsgL/6bs2hoOT5kJuqR7y9qLHTtRjXZx8SKomChujyOyeJ7uz7hAK8Cpx27DpewPEU1prFYuXIlHD58GD777DPIysqC9PR0+Mc//gGzZs2CgoIC6N69O7z22muwePFieOutt2Djxo3QUFWb9dXHQkeqJ0w6vwrdiydvNZtCiRqLWKh7EeetosbCJiJU0LllwUKeZPPvOYIAoYoKhUKFSV1pCjdrUr/LRdeaQkl1Ggth6hQUNSoI033boPMVwnwVw7p6bcfN0U10gkVSxSOIegdFhao+jUWytGiSBWeP7MI+Tx/Uwc327YsKJS70gfUink9jofSxUPsGyKQp6mVCnwJ47dpx2mPcMkumUEqNhXpRytEEWNa/bozffsDVWOQ4Phbe/FT2zttpnjKJwV38i4NxVMPpUckUSlV0LJ8odB1JmESJfiri2H/aU58ag8dUi48FZt0eM2YMc9YeNmwYvPrqq0x7gULHkiVLYN68eTB37ly47LLLYP/+/dC0aVM4dOgQNAQaosbiv743kk1obfwLVOj6EZ1Zia1A1r65PqSi+PKqFimMgoXwdvJICrL2woTpubvqUf+1xAR58WhU5VK4Wcl528LHQrU6b4ojHjXcrE5joY4Kpd43GR+LMOg0FmK+Ci0Gs7GGuqBAEEGI/S35GNkTJoR6MvzqnKFwzykDoGVethB6NaYPeOJzKocQgkV6KFMoFeIeuD/P8G0i3ei8rb5njk0eERHdPWAyut2HSz31gPce9v4z09OcccR13nYFIN0YrvSxkJy3laZQVd664Q7fmGTw6EFv0AAMc28ylap25+3HH3+c+VNs2LABrr32WiZkdOvWjflgdOrUCbZu3cr+li1bBg0FG1OJ+gaqUqsbcaVApxgQq3NcrwJ44PTB2vMFqRtNHaU4kRVV/LaClY2JlpN5W1q95995/gxcFXAECww36zhvqzUWfJXDyeRq4RgnVpUpx4UJnRZC1Y3LwlQQyTqJySQz8fEmyAvehyDqM7ZNWZxMko9F9L4o1SHdxWeCQoW8Au65tvCwwwg8ch4LdVQo0elYfy7V5Nc+UpPeFMrN3ZEqHwv/NkzMur+4nGktvKZQMfjL/E2hxp9MoQ7FcLO6aI+8PCoLgJIK7mPhzYshgseJ7aE4oeVAbRead4kYLLBrRrBAn4pFixYxoWLs2LHOaixGiEInb6RLly7sr6HQkJ23o8KroU3THNhzpMy3PUpH8pcrjzUmOhMnzypzHFnwuGNmf3j07VXGiay1YGFhoqXysYirOuPfcxP5M4rKKuA/a3b7TKFwZUTVSfJtrimUQrAwaiyke7FK96f3q1CHmzX/LpNsvOxUhk32CBaauqHXnmjUGgvKYxE554it/X0y8MfjS5AnfPaPA3ry5TwWKh+LgC789pP7wZZ9R2FI5xaBi13RNBZgmcfC6lLKMuH19kM5FCVW+7mwjd9//ubyUIJ3E7HsXLDAyb9gvaAqjyncrOu87b8eVovYHng9NW+SFejzWCt5LHr37g1z5syBnTt3MmftsrIyJmR07doVGiLecJS1WpQ6x9PfGwF3vL4Uvty03zcxs4kKZXIyNqHq1MRVk0fOGgIXHtvNESx0nY+tj4V4bpzYP3nBcLj+5cWSj4UqghL4NBYbdhc5v+OhvLNCjYTKeRtPh+VHUylVgj+xDG55xS/yvVjdsqSlCIgKFdIUKsVyhdIG2BabaCUNxQSSINKiJGGjF8AadHzGuuP26lHCrIaFj7WyxtscdtyksXCniFh81T0ERRC6bkofz/coGgsrH4vAzNvRtCMIX/RzQr1rFiJtBIvuBW7ma8cUSjCV1oUDtvOxUD8f1bwHNRYypjD3NSZYcNq3b89CzTZ0ooRJa+hwgaBPu2bwzx+Ohx53/F98u6aubPrWMB1wUFQoeZVIt0JuG+1ELNpvzx8K43q3sXLeZh1HorQqfw7sPDISIehMCfIwbjXXWMgJ/vh5dN/DDCgiYkmCfSwglClUsmHtUhtuVtRYaPahF59oZFC42WhgX4EmStwuvyasHPjYKS9MpUc0iRV9LHRjZNgeXFR6+Ffno0SFMptCuT4WdvWvmiPIFg3cedtXTovxp4cQ+tXJY8Em/+aoXaZws6IWBPeXLQcqLAWLA8XlkAqqyeqvYeLNhti4JYtBneLxs88a2Tk1UaEiVqc6KpT+RdcKFhFMobANqDpsrk70mEKx6BGg1TTY5rE4UhqP6KA7j0/NHXFA0alHxc9Bztt2plCQUpIJh5lmcWhjf++JxodoXkgai3C0Tvg+1JgplGaSbfKxME24bQSLsOaspmR9urKYTKFc8694OU4Z2hH6d2jm/O4mobUrH5oiBwkWOtNpm/eja+s83/PCMjomW5o6UVVzqRRulh3vW0xVL/KpBIs9R+JCcLKQYBGmssgUyuHvV49lyX0uGdcjlGlTqld8VV2aya9Ap+nTrUCYzo0fVWH85NjWjo9FlUlj4Q1Dq1NJHk6EitOdx1Rek9BRPT4WUOM+FsloLGyEBrIEIRoKtn2xytmUsKNVvjt5qwlTKCePhU+wcD/Lj91ULNEUShdxL+ziUBTtiVx3qqhQfPKMZX7npslw6rBO0rnt6r80oQUwmUrrhCyb96NLqyZKnyWek8IfFQoCfSy8zuzeffAolcaipUKw2Cv4ySYDCRZhKotWKx0wOysm9rF5kcR3MNUDkzLzticKlVljwX+e3Let1fVkW1WlxoKbQokr/YqoUN5ypHmiPulMobjGAjs61UBlyqoqTyRs27PoV+H5HDNrkGyEhihyxbMXjYTBnZtDN2HlxyZBXhA2YZGpDyAaCrZvirgKS6aA4WglaixqYLblhl6VFqaiRoUSEsdq++qQfbgpYa6uLPJmVVQoLljwfW3NrGQKmub4tsmChM6Xz2Z+062162PRLCfTKdf+ojJjnZh8LESNhfyOan0s8khjUScQJclUO502NHQT2lTnBxAnujYma+ILiPzntqksl8fpw72rGzrEszFnNsW9KRPkKaJCiYjhZks1zttIUUKw0Gkr/KtRBo0F2OHVUkCA87b5d//+4V+kmUM6wv/eMEmZm0IVtcQWmyhZtLZANBRs2zJFgopOq/zsGl2U4PNfeR5p0hKYwNX/M0d0hrzsDO0YmZQplOVil2wpII5/Ot/BqD6FOK78+txhkUyhTOZupwztCGN7tYYxPVq5ZRdCBe8tSvji+AQ/Q7hZR7BwyyOXAI9TzSdaVKPGIiXO242F6opD3RARX2KbqFAp1Vik+VcQfnX2UHhu3nq477RBPntH0eYxbKeo6iS5FZOodMBtfDVf2SnFYpCdEDhMPhbcFCpHkTUTkWvXNKBEcWYTNRKqEsqRsIJIRkBX2bNmJKGxsKmOkd3cQYEgGgPie5bqYAuNyceiRgQLi4m5bzIfMCb/5vzhxt/Dtog0w7V1K/7iZjSDMms9EteJaPqLnDOqC9z62hLne46tYGGoy6e/N1K5HXNk7Csqc8L163xgVOOpynnb52NRpfaxaF6NPhYkWIRAfODUv9aNxIJKHwtPvpH4//PGdGV/qdbEqDQzfHItDsLMeTvxWaVtOFxaAd0EHwtdhAtuCmWbKdwcZjDJBHkBGgvM4lmdPhYqs6dkNBZBCfI++MnxoYRQgqjLtBZW002QX0V0MLtxTdajTkjwLjB5f0u2VGGFzSh+f+Ix4iTaZNplqw3RIUZX8mksNHZtUfIotWLCZ5EzqddFhYoZNBaqvB5BUaHyFIuTexPmWMlCa/BhKks0hQotpzcuvKsSUG2RMdRRocRrpPZ6cgdtMoWq9PlY8DCxGUpNBLfbxKR5j727Wnn9IyXl2lCzDLlT0v9k72Oh0UKoZB9x3/IKCx8LiE6GohNPKtys4VAU5Hq39ZteEUR9A4NuDO3SAl66bIzV/uRjkRrhrSajQhktCEL4WNgQ1nnbHKkwuPzy+Clr3vm3qD4WqkUqv4+FLtxsuGuI5nKotTCN06p65g7fuQqfEzn/VU2aOJJgEaayyMA66c5DnyAvGqrFErFzTfUjs3PeVkzCmY8FaLUNh46WW2khXI2F2hTK5AwXOdysJneFWmPhbivT+Ino9g9LluIGkgmHaZN5myDqOxh0483rJ8KgTvFMyGH6PDKFiu68XRPTB5vx1R/EA2oUU3AVK1MoOaO5NGzqfCzCzt9EjbisodCZQkWZI7ZKaLUcjYXGx+KDlTt9719RWYXPb1MuQjxHRiylyWSDIMEiBGQKZU+apt70ztsQiVjEfARRkTUAKqFJFRUqnsci5qwUyPeLGgtdZyVypNTvrOUtn2w/q/6s2leHNxKU2YdC3MYzhBvPrREsbAY71SCUjA+P6VBaUyAIIiwdWuTWrCmUhY+Frxw1LVh4zIf1v9maQukECJ8mI2QnLtaTPDZrNRZRBIv8hPN2wsdC5wv52qKt8OaS7Z6xc+fBEva5XfMc7X3qMpJHMduyhQSLMJUlPC8yhFLDV4wnHuOGbxXbeU2YQlWnytmfx8L9LU2aXKMwwcF3m7scYIclr4AcKimH7Ay1FkLkSGm5UWPhd1jTayxsq0l0lQj2sQirsVBvtxmEU63KVeUkcb6TBoMgiJD0KMj39PHVja5LNPlY1LQlhkmLbpMgL1iw0F03XDlF4cGXeVursQh3DVGrxZ23Tffz7vLvPFmyixJ5LDq3bKItQ5kmdH11aizIeTsEFMM7mI9/OhWWbDkI0we2rxHTpKAEedVt4qWKTsE1FZ4ISUK4WQQFCzHDJ06ke7QJdgw+kogKpfWxqI4EeUIt68yiVNvsNBbq7fF6NYvv1ZkFmAyhCIJIFtFsZ9Oe4mqv0PRa8LEIi2mh0SYcvZwHSrdgxh2bdfsFkRlBYxFl4GgthZv1RYUSTiqOqVv3H2X/2zbLMWbe1mks8Dp/vuJYR1j52xebIVWQxiIqpLJQ0rFFEzh5cAcpMlPw2xbZFEqZIE84L9TcakuGwRQK40jHxGR4Ukf16FlDoUurvJT7WJhsa61NoTRRodR5LLz3HNXHwiYTejLJ8AiCCI8uGg4RDEb+q25sfBTkyHk13Yuaou/ZmHLJzttyk+T78pxP7vZw5eRhdu85ZaAi83ZwOcNGDuNDoS+PRbrfWRvZur/Yl8lbNc7rxmEUjjAx8C/OHOJJhJgKqJeICEWFCtHILN7oVJqaVGv0DYN9qBxuVlzdRycrvh2rQ+yo/nTFsTCwU3P2uXuBWbjgeSy0PhYGh7XIplAe8yewzmNho7HQCRY2/ibVqbHg8OdxvGVmdoJoiFw/tQ9M6FMA0wRNNGGHbWjw6hQsPJr1dG+Y9BrXWGjKZSqLeFtyfep8KYoTZkK6/WyCHKx5aCZcObFn9Tpv53vDPssyi3jO0opKn8ZCXpCUi1CuMYUSF+ZSPWciUyii2qnxqBM15GMhX4dPdPmLLEZiKC6tdFckmMYiTbn68exFo2DWUx9rTYSCNBb+8qo/q8qvQxcJKijzdjKmUDaChSrcbKrgVfPq1ePgzSXb4PzR3artWgRR17l1Rr/aLkK9pXBIR3hj8TbIl6IZVQc2E3O+Wu30z7U4PsuX1nXp4jHy2KfzSeARk3T72cDHIdvM21HmOvnZ3mm4ye9ENJ/WaSz8PhbBztupDixAgkVEKEGePTaNNpWyQKqze9tO1LlKc39xmW8Sjp0cFzTwXj2OYcJn1FysfOBk6H/PO0bBwtbHIiXO2xHzWCQTbtbGzKk6nc94vWFUl6sn96626xAE0bB54PRBLGrP6cM61wkfC25qygWLurTwp8/D4X6Wxz55DOH74mKe97oQGVGQwPPrIipF8cPNkwROef7iGVMFwWLVd4fZ/25S0tZ0a1OocObqYSDBIiLJxN9vbDSk/B+iyZZ8XwX58ZBvew6X+qJC4SScq2bxOFGYkB3BVAn0ZOftHM0+JuHBFDHKhFeYMNtCeTQW6FcSixmvo3qNsG5sTOMoIzBBEHWdZrlZcOfMATVyLZuoUPLCTY2bQok+kGmuyemmvcUwY3CH0BqLxZv3K/eVNRbJ3KY4RqNlQirD5ufJeTmkk4hO6Pzz3iOlsPDbfezzxD5tPPvLz1NnOSBGVSSNBVHvaEiChSkGd0HTuK3koZIK9jLLK/o8VCweJ66AaCNMmDQWGlWsyRnOJ3RYX1WnsTA7b+PHiqqYUbOgOoetJiJMvREEQTR0bJyf5b4zrQ6YQr127Tj4ZO0eZjamPEbo6uWoUKcO6wTvr9yVch8LEXG8Rm2FPixu+Gv4E/7JgoUrGPB7en/lTjYWD+7cHLpKGgsZncZC9FFMtWBRb0fmHj16sIcr/t1xxx01dn3SV9hj02bT6kuIYIPTW4smWc7LiqHj5HB3XChgPhaeGNn2ZeQ2ljqNhc9m1VDeKJm3xZYvvwOonZDlhKDIUEqNhaWzY3VqLBqOKEwQRGNB67xt6GNrPo+Ff1u7Zrlw1sguWm29V2MhCRZDO8G0AW5QAb6nPypU9PsUr2ky040yJOVJPhZyMcV5xK7DpfCDPy2En76+lH0f37uNvwzpls7bISN3NgrBAnnggQdgx44dzt/dd99dY9cmSyh7rCaA9USrYcwLgTGpExEern95sRPBSTZjkqNCRVl5t400osqzofrNxH1vLmd/pmR5unciyIFbpbGwFSyqNSpU/WiOBEEQwYKFtD27rmgsLC+eZnLeTk9jEcvk86MJmve6kYvsqS/TuBNlgp6RnuYZz30aCyESFCJqZwqkiFJhyiBeJ9XK/3otWDRr1gw6dOjg/DVt2rTGrt0QNBY11aE0pMSCQZ1im6ZxP4tFm7x2nwgXNNKkPBYqweKly0Y751Kh1Vj4hAfxs/dHOYOpboK/fPsh+ONn38LB4nJt6FmdkBAkWCSjsaiJcLMEQRD1hTBRoaoj1LsNUaYDYvlVgUtEYYPv+4dLR0vnSJEpVDWY4OYJ5lB+Hwv9GIpWEjI294nmxqbALo3aefuXv/wlPPjgg9C1a1c499xz4bbbboPsbL8ExyktLWV/nEOHDrH/5eXl7C8MsVhV6GPqIjV9D5WV6nrD+oxaJtP+lRUVKb3HykpXC1FV6T13ZVUVtM73v+i4bV9RuZMgKVZVBR7rp6pKXxkn9W4Nz100HM55/gunIxBVmplpMXU9VnnrF+9fLHt5udsp3j69D6zYfhA27lVnhM3LyvAIBoePlkCFqLJAwaGszOmgVEJEcWkZlJfrBZhyoXycrHTvveqfn18q0e0b+v2W6jEV8PM1hH6DqFmo7RA2ZKWplzyrKr1jjLjoX1lRDuWx1EyWbfo2nAO4n/1jn678HBw75WNwPJTnZgM75MPs68dD4dOfxc+hGGdtSYMqz4KW7jzieCtjujYu8u2HhA8meMd22aRapGl2uu+8eHwQvnsQ5l+NWrC48cYbYeTIkdCqVStYsGAB3HnnnbBx40Z48cUXtcc88sgjcP/99/u2f/TRR5CXF5z1WKyyA/sPwuzZs6F+knjssVgN3kP8mmvWrIbZxat8vx48gD1dfIJqVya36ar279AkA747mgb7134JszdCyth42L325599BuubuN9XLF8OpUfwHtxOemaXSlhzMAb7IM2ZeC9bthR273f3m/vhB6CQR2DLEffcWVAF5cLK0qpl38Ds75b4XuGVK1fC7IMrnO+bhPJ++P77vuvc1Bfgxs813UAlhs11r/n2nA9h69Z0z/393+y3nRWi+MJKptO5xSAN5nzwEbTzhtn2sGQvHuwVPEqKiyAeKdDcHlbt9B/r3dfcRtTEj1m/fgPMnr0OqoM5c+ZUy3mJhg+1HcLE2oP+PhH5evFiKNkohD8/5I6377zzTpIhZ8P1s/E1o8SYuWI5zN63LPAYcZxYtWIpzN79jef3FXvc39kcoyg+x9h91L3Wkq+/hoytiyEK6w6656ksPZq4T/+4+e67GCbe3T6jSxW8uzUdzu5RaaybyjL3eezatdOzb3Gp+5vMqm++gspNXkGiqEi/v0OVtzyrvlO3mwYhWNx3333Kib/IwoULYfTo0XDzzTc724YOHcoEjHPOOYdpMQoKXHs7ERQ+brnlFo/GArUdU6dO1R4jc+Pn77H/LVq2gMLCsVAf4feAK82FhYU1es2+fftB4ZRevt//e+sXsOkIe3utysTPp9t/+owqFu5UdoxKlsWbD8CTyxawzxMmTIBjOrRwyjJg4EBoebAEFu7Z5Oz/+A9mwA9f/hrWH97jbBs2dAjsW70Hlu6P20oWnjwd8nP85Vy54zD8eunn7HPz/FwoPuRq244bPQpOGtjOUw/IwIEDoXB8d+f7kq0H4Yllca3H9OknKVWn8jk4rZvnw4E9rjbj2PETYdmnmwD27HC2/WV7GzhlSAf4/thucBQjVnzxAdveJDuTRbD4967W8ML3R2jNutKX7wRYgwKSS5tWLWBfcTlA6VFjezj61TZ4ZUPc94Mj7hvURlTwY/r07g2F04+BVIIrRDgxPOmkkyArSyFJEgS1HSIJ0Gz16RXzfdtxEXZKf9fB+a87FsK3R+LmurMKZyZlrhy2n62qisEt8+OLK4MGDYLC44KTj2at2AUvrfmafT525AgoHOINS5uzchf8cW389/79+kPh5J7s846DJfDQ1/PY51EjR8BMTTjbIBZvOQBPrYiP+8d0bgOFhaOU4+asmTOde0PuvnAKPJKdCc1yzfOQP2yeDzu3xS1oOnXsCIWFwwLHZ2T6lIkwoGMzz7an1n0KO48W+fZF4ZEHYilo1gQKCyc7vx1YsAX+uXElNEjB4vrrr4cLLrggMBqUirFj45P8devWaYWEnJwc9ieDg3zYgZ7ZyTeAyUFN30NGRrrymmLHFrZMqv1xk2GhPDJZWe4rk53tbTfp6RnQoYWr+cJJfF5uDjSVnMgyMzM994v7iD4XnNwc97i44OEKFs3yspX3nZGR4dmO19KV1wR2QjnCvSLlVWk+A9mvNh9gf1dM6g0lgsYWo3ugYLFs+yG4739XwfPfHw3rdh2Bn/zja/jR1D4wfVAHp7wq/5H0NFelrCtzbrbquav3Ddum0jXtNBVE6W8IgtoOEUSrprnK7RmZ3nFB9EkwmY+HxaZfExO+ZUrjlf687liUn+sf+/Jy3XvIEu41P9c18cnIyIzc7+bluOfv0ipPex4cY0Wys7KgdTP1MxHJExYW0YdDd/4OzXPhu0Mlzvc2zZv49s3QJO9Dc6uiRLja7m3yve1BGusblGDRpk0b9heFxYvjKq6OHdVxkFNNQ4gK1ZCcqmsKU5QlRIwpzSNENZW0JugoJVa9Lm+D6FAla15aNlEPBnKZxE48jIMWCgbyuVBQUGXbFn/nZcAVmn1F8QzkyxIrMff+exnToFz9l0Xw7aOzjFGh0JAqCAo3SxAE4dJUoflWYZsrqNrnHZZjkjgWyXks2DZN+FwxyInsHxjVebtTyybWc6o0y2oWx3fTOP3uzZPhzP/6FDbsiWskVBYIusMxXwYXLLq1ztdm+8Zx9e5ZA+C9xRvhFWgAgoUtn3/+OcyfP5+ZMLVo0YKZR6Fp1GmnnQbdugWr1VKBzcSHsKe+iDimvBA8g6gsWOTleFfl87MzPJE4dAKeGPVITqLTMi8rdD2GsaONCxZpPsGhwpCXgufpQO2KGJ6P57I4VOJ3XlMJKrbhd6szKhTJ3ARB1Deaakxu5MhP9S25qCnztixAiH23dxyKPmcTz9OppVkDkZbmLjzbLuaJ47tpwQwFCfEZy1m749d3j2/XLIflvkDEHCFdWnmFIzESFd7r5RN6wmn9m8MrN0DjESzQnOnVV19l/hgY5al79+5w1VVXwe23317bRSMauPbElMn6mPZNPRoLPvHNl7QNqlUGFWIHIx/TQidYGOoxlMYiE7OLercVl1XAAfR90MATEuGqmThwYcf2uw/Wwt4jcQ2GTqOi6sQbQpshCIKoCXDSjavrQWG+Vaa3dRmxq1flcBK3ecyqBc1MULJWW41FZ4PGgl0f3HiFtmMuRmAEy2PE+1ONgaJc0rFFriNYiEIImlTp5hoqjVCjECzQEQk1FrVJgzCFgrrDZeN7sNwPk46JZgpXG/B3+q3rJ8Kq7w7BxD5tPC96UZm7gi/SvEmW1Yq4+LKLnRlub2ap8laV1wZc3UhTaCz2F/uFA6SyKubVWEid/xNz1ni+YyePwgceFzWPBckVBEEQXprnZsIexSKOp4+tIxoL2yHJa94UZAolnD8t9YJFxwDBQsRWqe7JY6F5NPxW0kLUVXsmQBx0AqpwOkpaF9EUKhVto14KFnWBhiBY1CVOHdYJBnRs7jElqi8aiyFdWrA/GZ5pu6lkCmWrsRBNfUT1a0smmNglQopF1FigalY+11GDYIHajKJ4jFilYCGz+3Aps1XlfhiRBAvh8zmjusAVE+KRQFJBTSeNIgiCSAWoMQ4SLGrTxyIK4tiVG2AKpRvngrQ4thN/1ALYkmarsRAWCnXl79uumZWwIv7eplmOR/jikaEGd26hNYVqtBqLugDJFamnTzv7zOkvX3Uc3P3GMvjFmUOgJhHfed0L3rNNPmzcUwQnJML7tUr4WnCaS1GidIirCKLDmM4MCuks2U5CRMEC/UO4aZNHY1GkNoXC31xTqAyoCLBnxcgWf52/CZ6Zu973G66Y2AjuYqf90BmDPTakyULaEIIg6iPNLMaX+udjAdYaCx0VpsgjFs7V/7hmHGRmpIUaZ9JtNRaiYCQd9MZ14+HZuevhZ7MGsO8nDezAIjHqQriL46K4iInC5MKfTWNWAvIcRGwOpLGoRVS24fWN+jx5Gt+7DXx465Qav643oIW6Av9+1Vh4d/l3bBUdaSt0AGmJiEk2dS9qLESbSJ0Z1G0z+sHUfu205wvj69wqLzuel0Jg95ESlhtExddbDsBvP1jLPudnZ8LuI25oXBWrdhxWChVhNBZBjvQEQRCNDZvIULZ9bHVj222Lsy2l87ZwPzoBojwJjQVybM/WoY9Jj+K8LR0zolsr+P0lo53vV07sCW2aZsOEPmqzcfFwtG5wzpueDgW6fFIBzvFhIY1FI4bMPcIjypO6iXqHFrlw6fgeSnUkdvryioQOcT+xQ6jUCLWYHyJVzs6osVizk6Xtdti2/6izoiELGNf8ZZHnHrck9tWxfHvc7lNcTeFRO/D8NkUV96nO0LMEQRD1OTKU3J/WFY2F7RxE9I9QO29nBPpSlCehsYhKuq0plOD/EDSWoVB47uiu2t8zNBoLUxTFVDtv143WRRD1ENtOo63HztF+NUA8uye6RUX1d5AoWKzffcSzbduBuLBQ0NScUAl9LEorvNoOmb99sdnzvU/CftTJYxHSFCrVcgWJKQRB1EdUWZ7l/rS++ViIoWJVgoV4P7IvBQ98Mn2gm3m8OokJn23X8sb0aOUbZ6OCwWFUYelN85VUO2+TYBGRBmAJRSSJ7WRWNF0qS0y4bVZqRHW1uPIQJrpF1HaKfiFy3G+usUAzqUDBorwqsn9NFOftVIee7dCiOvK2EwRBVC82/gbZGanzRxOjUYXFttsWhQXMTO0/jz7605xbJsPcW6f4HJZrgjTL+zumfTO44YS4xcG0AXpzZht4/ixZyNCZMfudt8kUqtZoEAnyamHRQlyZro+IE3Xbyay4n+nllkHtxj+vHcdsRkWHvDDniNLZI60VwgPP2okdl5gESAadt0uFgQAFq24FebB8ezwD97E9WsOCb/d5jjlGECxQTW9TtdXhV/HiJaPhk3V74LzRcf8YgiCI+oQq0p7cVaITcqpAn8KHZ6+EX5w5GKqLMItp8viIZkY92tSc1X9MGBdlfwkTP5nej5lQ65yyowgWoolVsRSMRWcKJfplRIU0FhEhjUU4/udHE+DB0wfBjEE1o46sCaKY3/CVl0vGdWf/g/J2jO7RGsb2KmCfLxgTt6u8eVpf6+vhSgju/7Ahelavtvns/8mDOig7p1ZSFCrUZpgm9bIp1KJ7ToK+7Zt5EgmaNBY51qZQkHKmDWwP9502SLkqRhAEUde5enIvaN88B566cESN5LEY17sA3rphIgzt0hKqizCLaTVhKmxD19ZNQo8jyQoV8tgtzlH4wqAK0eH9zJGdky4DOW83QtDmEO34JtdgMrrhXVuyv8bu/M7f3+N6FcD8O09k0R1swdC61xzfG3qEzPVx47RjjL+/ds04+Gz9XhjQsRm8s/w7p3N6/Yfj4f++2QGjureCH738lbN/AWosDOeLCxZVHtMm0XFM1E6oOlRbU6h48h+CIAiCM6p7a/jirmns8w1/X1y3o0JZ7idnijZRVmn276spbg6xAJhKRGsDcY6CuaZ09GqT72gujj+mbdJlIMEiInVDJo7GP64dB/+zeBtcdFy32i5Ko9NYiI51GD0qDPjSY46MVIMRpzBB4ea9xc62VvlZ0K9DMyZUfL5+r2d/TGJYZVApYFQoFCTKNKrWHtI9XDWpp8fJzHY1DbUgj5w1hK3OEQRBEHbUlahQtqBm/46Z/WFgx+Z1TmOBYeX3F5XBKcM6su+vXTsOtuwrhjNHJL/yn6zGQtTq8wS2Krq2zoN3b5oM7ZrlWEetNEGCRSPMY4Eai6DQpEQwYRyG/3rlcXDfW8vZRLiucqjETX4nOmjnS5nDexTkx+9d8w5gv/TipaPhxle+hgdPj9vdip1VFyGJ36/PHcY65l2HSyKFjr3wWBKOCYIgwiD2wbVJb8ukuDjeXHt875T7Y6QCNBXGcYwzpkdr9ldbiAl5xSmKSWOB4EJiqiDBgiAiOu2HEewnHtMG3r/l+Dpd16gBwAEHw+OKK1qoJRHlCNQ4/GBST3j+Pxu0WbhPHtwRFtx1oiN8ZWqyiPMwgS2buJ2haEaVDNcc34uVkTRzBEEQXg3AT07qm9LJZBj+/aMJsHFPUbVMwMP4Y6SCuuaP19rjYyGaQtWciRgJFhGpv/oKIlXUpWzPqXDGQ7vbj26d4kukgxGp0K9iz5G4cRMKH7fP6A9Z6enw+3kbnI4cQ+IePFoOx/dt69PoNBeiWomRKngYXdHmV874HZWfzugPpw7tBAMs1OcEQRANFXmkwr75hhPNvnfVybCuLdlfdVDTvpwY5bCuChblNSxkcUiwiFpxlOm3UeINNwu1DppY3f/Wcnj07CHVanvbtlmuI1jwfW6d0Y9FcHp8zhr2/cu7p7FVETHnBueqSb3gP2t2w+nDO7Hvvzl/GCzdeggmKxzFisoq2ErW1v3brGKy60Dzq9qIXU4QBFGXqEuLYNXFhz85ngUhOT8RPbG6wdwYq747DFP6Je/snErEEPP7i8thXK8C+HzD3sAIlKmEBIuQ/OqcofD4e6vhN+cPr54nQtRpmmRnVFtStiigidWcGjCxQrX5D/78JcwaEndQ41w+sSeUVFTCuaO6MoGjRRO1INAiL4uFJOScOaILnClFQ0QTrN2HS2FKv3bM/AqdxE8fXjsOcARBEPWdc0d1hoWrt8Lo7g0rIqOKXm2bsr+aAk2C5UAkdYG0tDTIy85gi3yDOjWHZy4aCf/+ehucVoNjaVqsPnshJ8mhQ4egRYsWsGfPHigoiOcKIIgg7n9zGezeugF+c9VMyMpKPplMfWHljkMsegRGfaoO0Ixqx8Gj0L9DwzRdKi8vh9mzZ0NhYWGjajdE8lDbIajdELYUlVbAkdKKpEKy7927F9q0aQMHDx6E5s3DjcmksSCIkNw1sx/Mnr2+0dVbdfsqoAmVyoyKIAiCIAg7MJcU/tUWdcudnSAIgiAIgiCIegkJFgRBEARBEARBJA0JFgRBEARBEARBJA0JFgRBEARBEARBJE2jdt7mAbEOHz5MUVqIUBFaiouLWVQxiu5DULshqhvqcwhqN0RNgvNiJErg2EYtWGA4LaRnz561XRSCIAiCIAiCqFPzZEzLEIZGLVi0bh1Pxb558+bQFUc0XlBT0bVrV9iyZUvo+M5E44XaDUFth6A+h6gPYP6Kbt26OfPkMDRqwSI9Pe5igkIFTRCJsGCboXZDULshagrqcwhqN0RtzJNDHVMtJSEIgiAIgiAIolFBggVBEARBEARBEEnTqAWLnJwc+PnPf87+EwS1G4L6G6IuQmMVQe2GqC99TlosSiwpgiAIgiAIgiAIgUatsSAIgiAIgiAIIjWQYEEQBEEQBEEQRNKQYEEQBEEQBEEQRNI0OsHi2WefhaFDhzrxwMeNGwdvv/12bReLqGc88sgjkJaWBjfddFNtF4Wo49x3332srYh/HTp0qO1iEfWAbdu2wcUXXwwFBQWQl5cHw4cPh0WLFtV2sYg6To8ePXx9Dv796Ec/qu2iEXWYiooKuPvuu6Fnz57QpEkT6NWrFzzwwANQVVUV6jyNLkFely5d4NFHH4U+ffqw73/605/g9NNPh8WLF8OgQYNqu3hEPWDhwoXw+9//ngmoBGED9i3vv/++8z0jI4MqjjCyf/9+mDBhAkydOpUtfrVr1w7Wr18PLVu2pJojAseoyspK5/uyZcvgpJNOgnPPPZdqjtDyy1/+Ep577jk2L8Yx68svv4TLL7+cJZG+8cYbwZZGJ1iceuqpnu+/+MUvmBZj/vz5JFgQgRw5cgQuuugieOGFF+Chhx6iGiOsyMzMJC0FEXqQ79q1K/z3f/+3ZyWaIIJo27at5zsupvbu3RuOP/54qjxCy+eff84W2mfNmuX0N3//+9+ZgBGGRmcKJYIS/SuvvAJFRUXMJIoggkBVMr5006ZNo8oirFm7di106tSJqZgvuOAC2LBhA9UeYeTNN9+E0aNHs1Vm1FaMGDGCLWgQRBjKysrgr3/9K1xxxRXMHIogdEycOBE++OADWLNmDfu+ZMkS+OSTT6CwsBDC0Og0FsjSpUuZIFFSUgJNmzaFN954AwYOHFjbxSLqOCiEfvXVV0zNTBC2HHfccfDnP/8Z+vbtCzt37mSarvHjx8Py5cuZ7TxBqEDhE7Xpt9xyC9x1112wYMEC+PGPf8wSVl1yySVUaYQV//M//wMHDhyAyy67jGqMMPLTn/4UDh48CP3792fmurj4jlY9F154IYShUSbIQwl+8+bN7GV7/fXX4cUXX4T//Oc/JFwQWrZs2cJWD9977z0YNmwY2zZlyhTmTPnkk09SzRHWoIYUzRJuv/12NmkkCBXZ2dmsz/nss8+cbShY4MIGmiwQhA0zZsxgbemtt96iCiMCF09vu+02eOyxx5hrwNdff80C1DzxxBNw6aWXgi2NUmOBLxl33saOGzvq3/72t/D888/XdtGIOgpGYtm1axeMGjXK2YbS/Lx58+Dpp5+G0tJScsglrMjPz4chQ4Yw8yiC0NGxY0ffYteAAQPYYhhB2LBp0yYWNOJf//oXVRgRCAoVd9xxBzPXRXCcwjaEUTBJsAgJKm1wYkgQOk488URmQieC0RJQZYjqQ4ryQ9iCfc3KlSth0qRJVGmEFowItXr1as82tH3u3r071RphBTr+o38Od8YlCBPFxcWQnu51vca5DYWbDQBtVWfOnMmibRw+fJipfubOnQvvvPNO0KFEI6ZZs2YwePBg38oz2sjL2wlC5NZbb2XR6Lp168a0XuhjcejQoVArQETj4+abb2a+OA8//DCcd955zMcCw1zjH0EEgZNBFCywn8GodAQRBI5T6FOBYxWaQmEaBjSDQsf/MDS61obOk9///vdhx44dLDYv5iJAoQJjPBMEQaSarVu3Mue3PXv2sDCQY8eOZeGtaeWZMDFmzBgWWOTOO+9kSaowohj6c2G4a4IIAk2g0Jc07KSQaLw89dRTcM8998B1113HFsEwkuE111wD9957b6jzNErnbYIgCIIgCIIgUkujzmNBEARBEARBEERqIMGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCIAiCIIikIcGCIAiCqNf84Q9/gOnTpyd1Dsw0i5nRt23blrJyEQRBNDZIsCAIgmikXHbZZZCWlsb+MjMzoVu3bvDDH/4Q9u/fD/WF0tJSuPfee+Gee+5J6jzt2rWD73//+/Dzn/88ZWUjCIJobJBgQRAE0Yg5+eSTYceOHfDtt9/Ciy++CG+99RZcd911UF94/fXXoWnTpjBp0qSkz3X55ZfD3/72t3olWBEEQdQlSLAgCIJoxOTk5ECHDh2gS5cuzJzo/PPPh/fee8/5vbKyEq688kro2bMnNGnSBPr16we//e1vfZqPM844A379619Dx44doaCgAH70ox9BeXm5sw8KL7NmzWLnwHO9/PLL0KNHD3jyySedfQ4ePAhXX3010x40b94cTjjhBFiyZImx/K+88gqcdtppyvI8/PDD0L59e2jZsiXcf//9UFFRAbfddhu0bt2a3e9LL73kOW7IkCGsLt54443I9UkQBNGYIcGCIAiCYGzYsAHeeecdyMrKcmqkqqqKTcL/8Y9/wIoVK5jZ0V133cW+i3z00Uewfv169v9Pf/oT/PGPf2R/nEsuuQS2b98Oc+fOZVqG3//+98yvgROLxZjg8d1338Hs2bNh0aJFMHLkSDjxxBNh37592if08ccfw+jRo33bP/zwQ3a9efPmwRNPPAH33XcfnHLKKdCqVSv44osv4Nprr2V/W7Zs8Rx37LHHsnMSBEEQEYgRBEEQjZJLL700lpGREcvPz4/l5ubGcEjAvyeeeMJ43HXXXRc7++yzPefp3r17rKKiwtl27rnnxs4//3z2eeXKley8CxcudH5fu3Yt2/ab3/yGff/ggw9izZs3j5WUlHiu1bt379jzzz+vLMf+/fvZOebNm+e7LyxPZWWls61fv36xSZMmOd+xrHjff//73z3H3nzzzbEpU6YY758gCIJQkxlFGCEIgiAaBlOnToVnn30WiouLmY/FmjVr4IYbbvDs89xzz7HfNm3aBEePHoWysjIYPny4Z59BgwZBRkaG8x1NopYuXco+r169mjmHowaC06dPH6Y94KCG4siRI8yMSgSvh5oQFfgbkpub6/sNy5Oe7irl0SRq8ODBzncsK15L1JogaKqFdUEQBEGEhwQLgiCIRkx+fj6b5CO/+93vmKCB/ggPPvgg24YmTzfffDM8/vjjMG7cOGjWrBk89thjzJxIRDSfQjDSFJpRcTMnFeJ23BeFETSVkkEfCRUoGOB1VM7WqvKYyshBsysMO0sQBEGEhwQLgiAIwgHDrc6cOZOFne3UqRPzNxg/frwnUpROg6Cjf//+zHF68eLFMGrUKLZt3bp1cODAAWcf1GagfwVqNtCp24bs7GwYOHAg8/1INo8FZ9myZTBlypSUnIsgCKKxQc7bBEEQhANOqtGMCCMqIajN+PLLL+Hdd99lZlKYL2LhwoWhBYtp06axiE8LFixgAgZ+RrMj1Bog+DtqRDCaE14Lw99+9tlncPfdd7Pr65gxYwZ88sknKXmCaAKFJlmpElIIgiAaGyRYEARBEB5uueUWeOGFF1jEJIycdNZZZ7EwtMcddxzs3bs3Up6LP//5z8zPYfLkyXDmmWfCVVddxcyquH8EChgYDQp/v+KKK6Bv375wwQUXMAEDj9OB58HjMFRtsvz73/9mSQJTkRODIAiiMZKGHty1XQiCIAiicbF161bo2rUrvP/++yykbDKcd955MGLECLjzzjuTOg+Gmr3pppvge9/7XlLnIQiCaKyQxoIgCIKodjCvxJtvvgkbN25kJk6ojUBfCtRQJAs6k2P27WTA6FDnnHMOXHjhhUmXhyAIorFCGguCIAii2kG/iZ/85CcsCR+aQKFDOGbd7t69O9U+QRBEA4EEC4IgCIIgCIIgkoZMoQiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCSBoSLAiCIAiCIAiCgGT5f0L625kFAB8vAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 800x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(2, 1, figsize=(8, 4), sharex=True)\n",
-    "\n",
-    "ax[0].plot(r_n, theta)\n",
-    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
-    "ax[0].grid(True)\n",
-    "\n",
-    "ax[1].plot(r_n, phi)\n",
-    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
-    "ax[1].set_xlabel(\"Range (m)\")\n",
-    "ax[1].grid(True)\n",
+    "theta_raw = theta_raw_da.dropna(\"range_sample\").values\n",
+    "phi_raw = phi_raw_da.dropna(\"range_sample\").values\n",
     "\n",
-    "plt.xlim(3, 8)\n",
-    "plt.tight_layout()\n",
-    "plt.show()"
+    "print(\"theta_raw:\", theta_raw.shape)\n",
+    "print(\"phi_raw  :\", phi_raw.shape)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "9ea9db6d",
+   "id": "79f0c385",
    "metadata": {},
    "source": [
-    "Cmpare with Crimac"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "id": "418f0ac8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "theta RMSE: 0.43174450157798355\n",
-      "theta max : 13.11178108969502\n",
-      "phi RMSE  : 0.9274489945255341\n",
-      "phi max   : 14.476222236380444\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1100x400 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Compare echopype CRIMAC-style angles against CRIMAC reference angles\n",
-    "\n",
-    "theta_np = np.asarray(theta)\n",
-    "phi_np = np.asarray(phi)\n",
-    "\n",
-    "n = min(theta_np.size, ref_ts[\"theta_n\"].size)\n",
-    "\n",
-    "theta_diff = theta_np[:n] - ref_ts[\"theta_n\"][:n]\n",
-    "phi_diff = phi_np[:n] - ref_ts[\"phi_n\"][:n]\n",
-    "\n",
-    "print(\"theta RMSE:\", np.sqrt(np.nanmean(theta_diff**2)))\n",
-    "print(\"theta max :\", np.nanmax(np.abs(theta_diff)))\n",
-    "print(\"phi RMSE  :\", np.sqrt(np.nanmean(phi_diff**2)))\n",
-    "print(\"phi max   :\", np.nanmax(np.abs(phi_diff)))\n",
-    "\n",
-    "fig, ax = plt.subplots(2, 1, figsize=(11, 4), sharex=True)\n",
-    "\n",
-    "ax[0].plot(r_n[:n], ref_ts[\"theta_n\"][:n], label=\"CRIMAC\")\n",
-    "ax[0].plot(r_n[:n], theta_np[:n], \"--\", label=\"echopype\")\n",
-    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
-    "ax[0].legend()\n",
-    "\n",
-    "ax[1].plot(r_n[:n], ref_ts[\"phi_n\"][:n], label=\"CRIMAC\")\n",
-    "ax[1].plot(r_n[:n], phi_np[:n], \"--\", label=\"echopype\")\n",
-    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
-    "ax[1].set_xlabel(\"Range (m)\")\n",
-    "ax[1].legend()\n",
-    "\n",
-    "plt.show()"
+    "Crimac"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
-   "id": "c095e6a3",
+   "execution_count": 21,
+   "id": "3ae46a66",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1000x400 with 1 Axes>"
+       "<Figure size 800x350 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -6279,9 +6215,9 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 1000x400 with 1 Axes>"
+       "<Figure size 800x350 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -6289,158 +6225,65 @@
     }
    ],
    "source": [
-    "plt.figure(figsize=(10, 4))\n",
-    "plt.plot(theta_np[:n] - ref_ts[\"theta_n\"][:n])\n",
-    "plt.title(\"theta difference\")\n",
-    "plt.show()\n",
+    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
     "\n",
-    "plt.figure(figsize=(10, 4))\n",
-    "plt.plot(phi_np[:n] - ref_ts[\"phi_n\"][:n])\n",
-    "plt.title(\"phi difference\")\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5ad45e65",
-   "metadata": {},
-   "source": [
-    "### Compare with echopype split-beam angle helper\n",
+    "i0 = max(0, target_peak_idx - 30)\n",
+    "i1 = min(len(theta_raw), target_peak_idx + 31)\n",
+    "\n",
+    "compare_curve(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"theta_n\"][i0:i1],\n",
+    "    r_n[i0:i1],\n",
+    "    theta_raw[i0:i1],\n",
+    "    title=r\"Alongship angle ($\\theta$)\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$\\theta$ (deg)\",\n",
+    ")\n",
     "\n",
-    "The CRIMAC workflow computes physical angles from pulse-compressed transducer halves using an inverse-sine relationship. Echopype also provides a generic split-beam angle helper through the consolidation module. In this section we compare the two implementations to assess whether they produce equivalent alongship and athwartship angle estimates for broadband EK80 data."
+    "compare_curve(\n",
+    "    r_n[i0:i1],\n",
+    "    ref_ts[\"phi_n\"][i0:i1],\n",
+    "    r_n[i0:i1],\n",
+    "    phi_raw[i0:i1],\n",
+    "    title=r\"Athwartship angle ($\\phi$)\",\n",
+    "    xlabel=\"Range (m)\",\n",
+    "    ylabel=r\"$\\phi$ (deg)\",\n",
+    ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
-   "id": "be119344",
+   "execution_count": 22,
+   "id": "ee60b061",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "target_peak_idx: 975\n",
-      "range: 5.79306 5.7930599853739295\n",
-      "CRIMAC theta_t : 0.19805856629305635\n",
-      "echopype theta : 0.2555534398211754\n",
-      "theta diff     : 0.05749487352811905\n",
-      "CRIMAC phi_t   : 2.127909429160737\n",
-      "echopype phi   : 2.1099409547175005\n",
-      "phi diff       : -0.01796847444323646\n"
+      "theta target:\n",
+      "  CRIMAC raw  : 0.19805856629305635\n",
+      "  echopype raw: 0.1980538342357811\n",
+      "  diff        : -4.732057275247392e-06\n",
+      "\n",
+      "phi target:\n",
+      "  CRIMAC raw  : 2.127909429160737\n",
+      "  echopype raw: 2.1279301087201414\n",
+      "  diff        : 2.067955940443511e-05\n"
      ]
     }
    ],
    "source": [
-    "from echopype.consolidate.split_beam_angle import get_angle_complex_samples\n",
-    "from echopype.calibrate.ek80_complex import get_filter_coeff\n",
-    "\n",
-    "filter_coeff = get_filter_coeff(cal_obj.vend)\n",
-    "\n",
-    "pc_params = {\n",
-    "    **filter_coeff,\n",
-    "    \"receiver_sampling_frequency\": cal_obj.cal_params[\"receiver_sampling_frequency\"],\n",
-    "    \"drop_last_hanning_zero\": cal_obj.drop_last_hanning_zero,\n",
-    "}\n",
-    "\n",
-    "theta_ep, phi_ep = get_angle_complex_samples(\n",
-    "    ds_beam=cal_obj.beam.sel(channel=[tsf_channel]),\n",
-    "    angle_params=cal_obj.cal_params,\n",
-    "    pc_params=pc_params,\n",
-    ")\n",
-    "\n",
-    "theta_ep = (\n",
-    "    theta_ep\n",
-    "    .sel(channel=tsf_channel)\n",
-    "    .isel(ping_time=tsf_ping_index)\n",
-    "    .dropna(\"range_sample\")\n",
-    "    .values\n",
-    ")\n",
-    "\n",
-    "phi_ep = (\n",
-    "    phi_ep\n",
-    "    .sel(channel=tsf_channel)\n",
-    "    .isel(ping_time=tsf_ping_index)\n",
-    "    .dropna(\"range_sample\")\n",
-    "    .values\n",
-    ")\n",
-    "\n",
-    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
-    "\n",
-    "print(\"target_peak_idx:\", target_peak_idx)\n",
-    "print(\"range:\", r_n[target_peak_idx], ref_ts[\"r_t\"])\n",
-    "\n",
-    "print(\"CRIMAC theta_t :\", ref_ts[\"theta_t\"])\n",
-    "print(\"echopype theta :\", theta_ep[target_peak_idx])\n",
-    "print(\"theta diff     :\", theta_ep[target_peak_idx] - ref_ts[\"theta_t\"])\n",
-    "\n",
-    "print(\"CRIMAC phi_t   :\", ref_ts[\"phi_t\"])\n",
-    "print(\"echopype phi   :\", phi_ep[target_peak_idx])\n",
-    "print(\"phi diff       :\", phi_ep[target_peak_idx] - ref_ts[\"phi_t\"])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 25,
-   "id": "298f0ce9",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 1000x500 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# ============================================================\n",
-    "# Compare CRIMAC and echopype split-beam angles near target\n",
-    "# ============================================================\n",
-    "\n",
-    "target_peak_idx = int(np.nanargmin(np.abs(r_n - float(ref_ts[\"r_t\"]))))\n",
-    "\n",
-    "i0 = max(0, target_peak_idx - 30)\n",
-    "i1 = min(len(theta_ep), target_peak_idx + 31)\n",
-    "\n",
-    "fig, ax = plt.subplots(2, 1, figsize=(10, 5), sharex=True)\n",
-    "\n",
-    "ax[0].plot(\n",
-    "    r_n[i0:i1],\n",
-    "    ref_ts[\"theta_n\"][i0:i1],\n",
-    "    label=\"CRIMAC\",\n",
-    ")\n",
-    "ax[0].plot(\n",
-    "    r_n[i0:i1],\n",
-    "    theta_ep[i0:i1],\n",
-    "    \"--\",\n",
-    "    label=\"echopype split_beam_angle\",\n",
-    ")\n",
-    "ax[0].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
-    "ax[0].set_ylabel(r\"$\\theta$ (deg)\")\n",
-    "ax[0].legend()\n",
-    "\n",
-    "ax[1].plot(\n",
-    "    r_n[i0:i1],\n",
-    "    ref_ts[\"phi_n\"][i0:i1],\n",
-    "    label=\"CRIMAC\",\n",
-    ")\n",
-    "ax[1].plot(\n",
-    "    r_n[i0:i1],\n",
-    "    phi_ep[i0:i1],\n",
-    "    \"--\",\n",
-    "    label=\"echopype split_beam_angle\",\n",
-    ")\n",
-    "ax[1].axvline(ref_ts[\"r_t\"], color=\"black\", linestyle=\":\")\n",
-    "ax[1].set_ylabel(r\"$\\phi$ (deg)\")\n",
-    "ax[1].set_xlabel(\"Range (m)\")\n",
-    "ax[1].legend()\n",
-    "\n",
-    "plt.tight_layout()\n",
-    "plt.show()"
+    "print(\"theta target:\")\n",
+    "print(\"  CRIMAC raw  :\", ref_ts[\"theta_t\"])\n",
+    "print(\"  echopype raw:\", theta_raw[target_peak_idx])\n",
+    "print(\"  diff        :\", theta_raw[target_peak_idx] - ref_ts[\"theta_t\"])\n",
+    "print()\n",
+    "\n",
+    "print(\"phi target:\")\n",
+    "print(\"  CRIMAC raw  :\", ref_ts[\"phi_t\"])\n",
+    "print(\"  echopype raw:\", phi_raw[target_peak_idx])\n",
+    "print(\"  diff        :\", phi_raw[target_peak_idx] - ref_ts[\"phi_t\"])"
    ]
   },
   {
@@ -6455,7 +6298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 23,
    "id": "c337ced4",
    "metadata": {},
    "outputs": [],
@@ -6514,7 +6357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 24,
    "id": "118b42f1",
    "metadata": {},
    "outputs": [
@@ -6524,20 +6367,10 @@
      "text": [
       "CRIMAC r_t    : 5.7930599853739295\n",
       "echopype r_t  : 5.79306\n",
-      "CRIMAC theta_t: 0.19805856629305635\n",
-      "echopype theta: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
-      "array(0.19805383)\n",
-      "Coordinates:\n",
-      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
-      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
-      "    range_sample  int64 8B 975\n",
-      "CRIMAC phi_t  : 2.127909429160737\n",
-      "echopype phi  : <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
-      "array(2.12793011)\n",
-      "Coordinates:\n",
-      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
-      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
-      "    range_sample  int64 8B 975\n",
+      "CRIMAC theta_t raw: 0.19805856629305635\n",
+      "echopype theta raw: 0.1980538342357811\n",
+      "CRIMAC phi_t raw: 2.127909429160737\n",
+      "echopype phi raw: 2.1279301087201414\n",
       "Target samples CRIMAC : (168,)\n",
       "Target samples echopype: (168,)\n"
      ]
@@ -6561,8 +6394,8 @@
     ") = extract_single_target(\n",
     "    pc_avg=y_pc_n,\n",
     "    power=p_rx_e_n,\n",
-    "    theta=theta,\n",
-    "    phi=phi,\n",
+    "    theta=theta_raw,\n",
+    "    phi=phi_raw,\n",
     "    range_meter=r_n,\n",
     "    r0=r0,\n",
     "    r1=r1,\n",
@@ -6573,11 +6406,11 @@
     "print(\"CRIMAC r_t    :\", ref_ts[\"r_t\"])\n",
     "print(\"echopype r_t  :\", r_t)\n",
     "\n",
-    "print(\"CRIMAC theta_t:\", ref_ts[\"theta_t\"])\n",
-    "print(\"echopype theta:\", theta_t)\n",
+    "print(\"CRIMAC theta_t raw:\", ref_ts[\"theta_t\"])\n",
+    "print(\"echopype theta raw:\", theta_t)\n",
     "\n",
-    "print(\"CRIMAC phi_t  :\", ref_ts[\"phi_t\"])\n",
-    "print(\"echopype phi  :\", phi_t)\n",
+    "print(\"CRIMAC phi_t raw:\", ref_ts[\"phi_t\"])\n",
+    "print(\"echopype phi raw:\", phi_t)\n",
     "\n",
     "print(\"Target samples CRIMAC :\", ref_ts[\"y_pc_t_n\"].shape)\n",
     "print(\"Target samples echopype:\", y_pc_t_n.shape)"
@@ -6585,7 +6418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 25,
    "id": "3291a82c",
    "metadata": {},
    "outputs": [
@@ -6609,13 +6442,13 @@
     "ax[0].set_ylabel(\"Power (dB)\")\n",
     "ax[0].grid(True)\n",
     "\n",
-    "ax[1].plot(r_n, theta)\n",
+    "ax[1].plot(r_n, theta_raw)\n",
     "ax[1].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
     "ax[1].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
     "ax[1].set_ylabel(r\"$\\theta$ (deg)\")\n",
     "ax[1].grid(True)\n",
     "\n",
-    "ax[2].plot(r_n, phi)\n",
+    "ax[2].plot(r_n, phi_raw)\n",
     "ax[2].axvline(r_t, color=\"red\", linestyle=\"--\")\n",
     "ax[2].axvspan(r_t - before, r_t + after, color=\"red\", alpha=0.15)\n",
     "ax[2].set_ylabel(r\"$\\phi$ (deg)\")\n",
@@ -6629,13 +6462,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 26,
    "id": "730f90e2",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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a8vwK1lYTzPBgL9WqhIoH0pKJTI8qintM9/rRg579I0BFMQQZ53Fsz++4dPkq5r/0IZy6PsWb6Pk/2tDzbxvPgM2v2It5EFoSdk7Fz5Y+98OOrPKZsudb3WPRkLnWA2lYvP/++1i9enWt+1y9ehUXLlzgE/6VK1fWuq+22EB2c2uLGfz000+1joGFVpEV33IcO3asBc9GtCXo2T+cZF76BANsr6O9Qzm2bgNOBQO2Nt/CNdlCbT96/o829PxbD6bKxJJ8Wa4DC0tqDfLz81vlvA8zZWVlKC4uxtmzZ1FeXq7WxnIw6otApjD/HiDEYjF/1YaHhwdmzZqFffv2qRkILDaQWWJPP/00/vrrL7z33nvYs2ePWlJ3dnY2rKysuErUsGHD6u2xcHV15eMyMzNrluskaoZZz+wPy6hRo7hMGvHoQM/+4ebpwUbo5GmIt956C1Lr/hg1YghmP9YPc1af4e30/B9t6Pm3PkzqleWlsnkWy3VoSdiUlRkVpqampAp1H54ri+xhc9nqz5XNcW1sbJCbm1vnHPeB9Fiwi2Ovuvj+++/x0UcfVb1PTk7m+RNbt27l0rOMfv368STtlJSUqkx45nXQ19dHjx49auybtbNXddgklya6LQfd70cXevYPIRUlyMwvh4OrP3QCVkBHJoOxPlBcVKjxvUrP/9GGnn/rwRZo2YItU2VqaWUmRfiT4vyNgYW5s3nfgQMHkJSUxJOVWQmCV155BSNGjOAGU1xcHN+XTbDd3d2xYMECLF++vMqYYRNwT0/PqvIFivc6Ojr8WGdn56rzsfklm6yz+xYTE8P7V2X06NE4ceIEAgMD0bdvX43xsnN88skn3JPAJvZubm4YMmQIXn/9dfj6+qK5YPeTXZ+2z1ZD5rUPdfI2u/ksMVvxUjwAb29vuLi4VD3QDh06YPbs2fzhsYfLfnlYwjd5HgiCIFqQUjGyCgAr68qFI4EA/75iiv+Ns6XHQBBEk2EGAFs0ZhEpX3zxBe7cuYPDhw/z6BRWz0zBBx98wA2CkJAQPidkHtRff/21zv6dnJywceNGtW0sOkbV0FCF1VFjIkJLly7F77//rtG+f/9+bmywCJlNmzbx8TAxInNzc7z77rtoizzUhkV9YNYls1qZVTpgwADMnDkTjz32GC+QRxAEQbQcspKMSsPCrmqbmZkp9FBIj4EgiCazZMkSvip/5coVTJ8+nS84d+zYEa+99houXbpUtR8LtWJ5JMy7sHDhQnTu3JlHs9TFs88+iw0bNqht+/PPP/l2bbB9J06ciOeff55H0xQWFqrlNcybNw/jx4/H3r17MXLkSO4VYRE3bI76yy+/oC3ySBkW7BeExeepVt1WeDaYVcgeIiuQxwrjaQtzIgiCIO6vYbHlRaBb14CqbSs3l2Dlb5F02wmCaBJZWVncO8E8E8bGxlorT2t8J8lkOH36NPcU1CccaPLkyTxPlxVcZrCf7LyTJk3S2jczLJ555hn4+flxI2fbtm1V7UeOHOF5u6zAsza0jbct8EDmWBAEQRAPH8KyLPRrB8DWvWqbTCBCdi55LAiizXNmMlAQdV9PIZABplIpBCy/gqU7mHgDQ/bW69jIyEg+mWeT+Lp488038c4773ClJCYYwKJaXnrppTqPE4lE3FD4448/MHDgQP6TvddmlBw/fpwvaLPcXwbbj4VDMS8FIyIigv+sz3jbEo+Ux4IgCIJou4QE38Xj3wJlAvOqbcZGhigoah1JS4IgHh4UIqi1lRJQwBKjb968iTNnzvD8i7fffhv9+/ev13kWLFiA//77jyeJs5/z58/Xuh8zIp544gku38t48skncfnyZYSFhamN90GDPBYEQRBEmyA5KR7XYwGRiUPVNmMjIxSWUNFRgmjz1NNz0BRkUiny8/K4uA73WjSAdu3acaOChTWxXNraYMqjPj4+/LVjxw7+kyVRszyHuggICOBeBmYo+Pv78/fMSFGFhUft3r2be0N+/vnnqu1MOYp5OT7//PMqwaHQ0FCuYPqgQB4LgiAIok2QJU6HlTEgMFCqQPl52aKHhwyoIK8FQRCNh9UnY2FHP/30k1qStIKcnBytx1laWuLFF1/k6lD19SLMnz+f52bU5K1gCk9MnZTVUGNGh+L17bffchUpVqCOqZYyA4epV2mjpvG2NmRYEARBEG2CrCwxrExYoSDrqm3jB/ni3akAygtadWwEQTz4rF27lnsFevfuzT0RLI+BeTBY3bPavAIs4ZuFKLFj6sOiRYuQkZHBFaVqCoNiqlSqJRHYixkizGBgaqUswfy3337j/2dJ4Swng8nlXrt2jSd0L168GG0RMiwIgiCINoGurBDtnPQAoTLRMS1PiKO3ybAgCKLpMLnW69ev87yJZcuW8cn8qFGjeA0z1ZCk6tja2vJ6Z++//35Vkb5av8t0dbm3QZE/oUpQUBD3VDz++OMabUzmlnkqFDUtpkyZggsXLvDk76eeeqoqxIoVylMtAN2WoBwLgiAIok2wYLgeFgx2Vdt2O7oAz28Aolbkt9q4CIJ4eHB0dMSPP/7IX9pgXgFtqBbIU5QvqOl9dViZA0V7XfuymhWq9OzZs96ekrYAeSwIgiCINkFiUhpyy9W12U3MLFBcBlSUts14YoIgCEIJGRYEQRBE6yOTYemv6fjteJHaZmMTuaFRmCdupYERBEEQ9YUMC4IgCKL1KS9AVr4M1tZWaptNzOSJ3EV5ma00MIIgCKK+kGFBEARBtD6lYmQVAlbWSqlZhqOTC/58DjA3ejCLRREEQTxKUPI2QRAE0epUFKUhhxsWyuJ4DENTa4zuDECntNXGRhAEQdQP8lgQBEEQrY60KB1vTQHa+bZT2y7TNcHcdcDdkMhWGxtBEARRP8iwIAiCIFodkTQHS0YB9s7eatsFIlOcDwdSUtJabWwEQRBE/SDDgiAIgmh1YqLC8NEuQKanrLrNEZnCWB8oKMhrraERBEEQ9YQMC4IgCKLVCQuPxMbzgMBAPXkbuibcsCgsoAJ5BEEQbR0yLAiCIIhWJyszA9YmAPRt1Bt0TeBgDsjKS1praARBEJg7dy4ee+wxuhN1QKpQBEEQRKuTlZUJK2ZY6FmqNwh1sXO5AWBfLUSKIAiCaHOQx4IgCIJodbKyc2Blpg8INP8sFZabIC83p1XGRRAEQdQfMiwIgiCIVmfFY0b46QV3rW3L/i7Fx/+Q3CxBEE1DJpPhiy++gJeXFwwNDdGlSxds3769qv3evXuYMGECzMzMYGpqikGDBiEqKkqtj6+++gqOjo6wtrbGCy+8AIlEUtWWnZ2NOXPmwNLSEkZGRhg3bhwiIiKq2v/8809YWFhg9+7d8PX1hYGBAUaNGoWEhATeHhsbC6FQiGvXrqmd84cffoC7uzsf/+nTpyEQCHDgwAE+ftZHnz59cOfOHbVjLly4gMGDB/PrdHV1xUsvvYTCwsL7/itEhgVBEATR6uhJxTCztNfaZmykj4IiKpBHEETTeOedd7Bhwwb8/PPP3Ih49dVX8cwzz+DMmTNISkriE3E2UT958iSCgoIwf/58lJeXVx1/6tQpbmiwn3/99Rc3FNhLNQ/j2rVr2Lt3Ly5evMgNgfHjx6sZH0VFRfj444/58YGBgcjLy8OsWbN4m4eHB0aOHMnHqAp7z/pmBoWC119/nRs5V69ehZ2dHSZPnlx1HmZkjBkzBtOmTcPt27exdetWnD9/HkuXLr3vv0KUY0EQBEG0LtIKTPtcjAnDCrBglGazsaEBxNkFrTEygiAaAJsk5+bmqm1jq/u6urpISUlRm6Tr6+vzCXFpaSnS09PVjrGysoKxsTGysrLUVtmlUinMzc35/9kqP/s/8y7UB9bP119/zY2Gfv368W3Mc8Em3L/88guf1LP+tmzZApFIxNuZV0EV5on48ccfoaOjAz8/P+7dOHHiBBYtWsQ9E3v37uXGQv/+/fn+mzZt4t4C5qGYMWMG38Ym/6wP5mVgMAPD398fV65cQe/evbFw4UIsXryYj5Xdo1u3buHmzZvYuXOn2lhWrVrFvR2KPlxcXLBr1y7MnDkTX375JZ566im88sorvL1du3b4/vvvMWTIEG5UMePpfkEeC4IgCKJ1keQgJRswMLLQ2mxiYoSiYuWKX3357qVO2Pud/I85QRD3n/Xr1/MJs+qLGRSMKVOmqG1//vnn+XbmGah+zP79+3nbBx98oLZdYRAw2Ht2vvoSHByMkpISPhk3MTGpem3cuJF7IdjknYU+KYwKbXTs2JEbFapGk8IoCgkJ4QaUwmBgsHCp9u3b8zYFbJ+ePXtWvWcGCguPUuzDlKfYPsxIYPzxxx8YNmwYN3xUUb0XzBBTPQ+7p8yTonqdzIPBDLOYmBjcT8hjQRAEQbQupWJkFQLWNtVqWFTSr5Mj7BAOyKT171Nagc//vgsIQzD55eYbKkEQNcNW7tmKuSps8s3Ys2ePhseC0aNHD1y+fFntGDZRZrz33ntYtmxZ1XY2MVbAjlF4L+qD4liWm+Ds7KzWxsaiWN2vjepGBwtNUvTLwp60wbarhjAxqr9X3aanp4fZs2fz8CcWyrR582Z8++23WvuuqQ82pueee47nVVTHzc0N9xMyLAiCIIhWRVKQivxiwMpGPgGpzqCenhhkdQYoL2JTgPp1WpYl/ymtAKTlXLaWIIj7CwtLqik0SWFgVIdN6lm4kDaYgaEwMhQTZhZuxajpmJro0KEDP1d8fDwPCapO586deUgRC1WqzWtRW//l5eXc4FGEQmVmZiI8PJyHOilg+7A8DBb2xAgLC0NOTg73XChg4VABAQFYu3YtHw8zMKpz6dKlKiOBJY2z8yj66N69O88h8fHxQUtDoVAEQRBEq1KSl4IJXQEnF3VXv4LIlHL8fpr9Ra5WfZutEEprCJEqScdXTwHn3gNQcH9d/wRBtH2YytPy5ct5wjYzIFj4040bN/DTTz/x9yyxWZFIzSb+LGfi77//5hP/+sDyGKZMmcK9Nixvg+VGsMRw5h1h2xUwo+XFF1/kBsj169cxb9489O3bt8rQYDBDhG1788038eSTT3Jlp+qwMDGW33H37l2e2G1jY1NVwI8dx5LHmWoVC/FS5H+w895vyLAgCIIgWhVTUSHWLwJcPNtrbY9IKsOXLORaom5YlIWsg2SrNVCaqXlQSRqe6AdUSIGSjLv3a+gEQTxAfPjhhzy86tNPP+WTd5Z3sG/fPnh6evJ8CJbYXVBQwD0aLESL5XA0xHuxYcMGftzEiRN5DgQLgzp48KBaH0yGlk38WXI124cZDSxhvDoLFixAWVkZV6bSxmeffYaXX36Zn4/lsTDDgYVRKbwvTOmKGRQsb6Rbt2549913a/QaNScPvW+YJbvExcWpbWMPlD0QBcwtxqw69gvFHjB72EzCS/GACIIgiPtHamIMbtwExo2x0dpubGqGghJAxgwLlYW7nTt34Js/83F5ZDhgq0xkZKQnRuDTTcDWS8BulzPo7T2VHiFBPOKwHASWd6At90AxIT9y5IjWNlVZWQXVcx8sLS15MnhdsNAmbeFNqjBjgYVD9erVS2v7wIEDubeiJthxR48eRUvz0BsWCncRc00pYNnxCioqKrhcmK2tLXddsXi4Z599lluZrCAJQRAEcX+5euMeVmwGxr1Xg2FhYgGpDCgtyISOSvh2VFwKEjKBrNQIWFUzLBLiIrlRYWkMREfchTLIgCAIou1SUFDA1Z3YHJR5WB40dB+VuDoHBwetbcyaYxJkTA/ZycmJb1uzZg2PV2MFTOqrj0wQBEE0jqzMDFix9R597YaFibk8ebMgTwxz+dc0Jzsnh/9MiAmFVSf1YzLTk2CsD3R0ASKrVc4lCIJoqyxduhT//vsvz5eoKQyqLfNI5Fh8/vnnPHaua9eu3FhgMWsKWHILczUpjAoGi7ljBVuYDjBBEARxf2FFsKxMBICu0pusiqeHB86+C1gYqss5lhTJC2elp8RrHJORngIbU8DbxQLR8Wn3aeQEQRD1Z+7cuVwBqjZYyBWbg7Jq2ao1MxQMHTqUR9Ww2hdtkYfeY8ESW5jsFot7Y1UNV65cyYuD/Pbbb7w9NTUV9vb2asewfVl+BWurCfbQ2UuBQv6MyYKplm4n7g+Ke0z3+tGDnv3DR2Z2LqzMDCBR0bhXRahvBh8HoLyiQO359/ORYOcFIDUlUeO7QCzO4IbF1DG9kBt9DJLi7BoNF+LBgT7/beMZsIktk35VrSvREihqRSjOTzQf7H6y+8qeb3WDpiFzrQfSsHj//fexevXqWve5evUqr2zIZMVUk3KY0TB9+vQqL0ZNhUq0FTRRhSkKaBsDC61iGf9Ey3Ds2DG61Y8o9OwfHmb0KkOhxJKrp2jDrOwu3l0NvLzwEPR85WGtx48exNN9irDtPBAVHaVx7DP9JZjT0wKpRjbo3Qk4fWgDcnW8W+R6iPsPff5bD1YVmoWXs1wA1QiQliQ/v5r0NNFk2LMsLi7G2bNn1QoZMoqKWA2hh9iwYPFnTGe4NqqXPlfAdIEZkZGR3LBgH47qFR9ZoRFmnVX3ZKjCPB+vvfaamseCFWsZPXo05WW0AOz5sD8so0aNalQhG+LBhZ79w4fubglklp1QMWS89h1yXJCQ+Q4sLc3Rf9Qo+Wd/UDf89Tbw6ROAb0c7yEarHyvc/yqEZm6A63C8tuJfvPquHhx61tA/8cBAn//Wh0VrMDVNtoja0gupbNGXGRUsd7a2xV+i4TDjgSmjMqldRVX06lE5D61hwYqAsFdjYMVQGAotX6YhzPIumKyXYhvzOrCbyrSBa4K1V7/xDDbJpYluy0H3+9GFnv1DglSCZRtyMXpEBcaMrGGRwNCSJ2IXF+RXfb/qVGTive3AX4sB/9JUCKotMMz8Ih59u3rj5Q+6YscVYOK9q3Dtt7QlrohoAejz33qwMBn2YuHiTFGThY631CSfheuwlXVm3AiFj0SacIsYa+yeZmRk8OfKjMXq97Yh89oH0rCoLywxm5U8HzZsGMzNzXl4FAuNmjx5clUZdOZhYGXYZ8+ejS+//JInEbLKjEyelhShCIIg7jOlmTgTCvQZaFDzPrqmMDFgK2oFVZsKxPGQVAA7rwLfHE7BnqlSQFD5x7C8EBm5FTC3sIKOhR887YDoyFAMp4dJEE2GTTpZQTm2IJucnNzik2AWrsNW1slj0bwwg4LNjZtqsD3UhgXzKLCsepYLwaxbd3d3bjC88cYbVfsw6+zAgQNYsmQJBgwYoFYgjyAIgrjPlGYgqwCwsqk59JQlXffwBEz1lHG/mWmx/KeHozEuRxUCpVmAQaUnuyQD4nzA1s4eEJnAy9EIUTGaylEEQTQO5qVgk1AWi8/qgbVkKBzLARg8eDBFhzQjbC7Mcmeaw1h7qA0LpgbFPBZ1wT4c+/fvb5ExEQRBEEqKc5JQImGGhTwUVSs6Bvh5gQ7gbA6FNklmWgL/6d++HdIO3ISsOBmCSsOivCAZWYWAta28T293B0THJrDlTqbWQbefIJoBNglt6ZA0NgFmxoyBgQEZFm0UClAjCIIgWo38rEQ4WwHWdi417yQQIFJsiNiE9KpNAW5CHFsJuHh1Qlk5kJ8RXdVWlp+MGX0AN3cf/n7FopH4faEEKKlZQpwgCIJoOmRYEARBEK2GnakEVz8E3H38a93v0z1SrN8vD39iGCGHV9V28umDx3oCknxlrLeRMBffzgZcveR96lj6Ia8IKM8Kvo9XQhAEQZBhQRAEQbQaBVlJSMlmSXG1K/2ZGOmjqLik6v0fu6/j1X+EsHbvgbXzAGtDZWJ3YmwEV4KCgR1/n13hBL/XgbDb5+7jlRAEQRBkWBAEQRCtxrGzNzHui7oNC2MjAxQUlla9j0kQI7dUHzB0wpHbQGR4aFXbtZv38MEupWFh6dYDFkZAVOjN+3glBEEQBBkWBEEQRKuRmZkBK5P6GRaFxcoqv+LsfNhYmgIG9vhyP3Dywh1lW0Y6bEyVhgWMPeDtIEBUZMT9uxCCIAji4VaFIgiCINo2aWkZsDHT5cpPtTFxgBv6OSklY7Nzi+Hl6gDo6MPOQoT0DHFVm1icCWtTlT6FuvB2sUB0XMtq7hMEQTxqkGFBEARBtBoxCWnwcq3dW8Ho4ucMGFZAUlEKHVkpnC3K4ePhwNvsbUyRJs6p2jcjKxe2lsZqx08c4oec+Mu80jeELSePSRAE8ShBhgVBEATROkgKMKlzEWzaDahz16DIEhzYB6ycnA89WS6+mQ2gfU/eZmttgVsh8roWjBdHAxUG3mrHjxw2EAi5CBTEAGa+9+FiCIIgCMqxIAiCIFqH/AhM6QkMGFi3YZGUVYFtl3n1O4gqcnApAiiSWfC2ZyZ0xuppEqC8GJBWwMM8C95ebmrH58EVn+8DsuOD7tvlEARBPOqQYUEQBEG0CmnRV7BqO1AgVDcCtGFsYg4uClWej9KCVEz7FojLlFfRdvPwhp8T5AXwyrIwZ60Up+6Wqx2vZ+2P7w4DYXcv3LfrIQiCeNQhw4IgCIJoFcLuXMGGs0wQqkOd+5qYWqBUAlSU5KI4T16B28bBk/8MT9PBhC8BSV4iUJKOwHCgXMdc7XgDh57o4CLA6eMH79PVEARBEGRYEARBEK1CVGQI3KwBkVXtVbcZxmbysKeivEwU5mXy/1vayw0LkbEDbsQC4uRwFGXHg6nS2tg5q3egZ4EnxnXH1uPRqMgl2VmCIIj7ARkWBEEQRKsQHRMHbycDQGRW574d/HyR8ANgZihFQX4WmOiTrokjb7N1bsd/piVFQpwcxf9v4+Cu0ce0OW+iRAKEn/q62a+FIAiCIFUogiAIojWQyRCflAFvD5YcUTdCPTPIBICkLBedXAX4ZCYrqicvgGds7QlDPSA9JR5G+jpo5wBYO6irQjGsO0zD7e+cIcIBnuQNoU6zXxZBEMSjDHksCIIgiJanVIwNiyR4ff6weu1eXK4HlxeBO/ci4GNbhsl9DAFdea0KgaEjengC0pJM+DoCZ94FjKy0JIQLdaDrMxeXbycgJ3xPc18RQRDEIw8ZFgRBEESLI80JQYUUMLTrWK/9DUys+M+C/GzsOZeITZeMAIFcFQp6ltj2ih7GdhUhPTkOsRnsALk3ozoV7rOx+A9g+4ZPm+9iCIIgCA4ZFgRBEESLE3UvEJ6vABll9vXaX6BnBmN9oKgwHxeDc3EvWaV6tkCA9BJbxMXF4t+DN/HiX3JjQxu6lu0xc4Qn/j0QBFmJPAmcIAiCaB7IsCAIgiBanOiwGzDQA2zc5dWz60TXhBsWhfl5yM4vg7WlXCVKwXdHpFi9MRrizGxYWxgCgpr/vM16dilCkmS4c/Srxg1eWo6D301BQeKVxh1PEATxkEKGBUEQBNHiREWEw8sOEJhqJllrRWSKab0AZ/MSZObLYGUtD41SYG9rjYzsYoiz82BraVJrV579F6NPO13s2Ppno8ZeIQ7Cwvf34sOVCxt1PEEQxMOKbmsPgCAIgnj0iIpNhJeTGaCjV78DdIzx7lRAZpGDghLA2lY9h8LOzh7peXdhqJcPD5c6wqt0jfDDuzNhl70ZyL4FWHZp0Ngzk8P4zx7OWWgWKsrqfx+ybgBSVqijT/OcmyAIohkhjwVBEATRskgr0MMlF+MH+tT/GKEOzobr4+a9CFz/GBg/vLdas629M9JygdkDgVH95XUtasOl+1MQ6QAV6RcbPPz0pEj+c4xPElCWg6YgK0pGP38DXN31Tj12luH02nFIO/hEk85JEARxvyDDgiAIgmhZihLwVL9yTB43qEGH/X5GgF0XC1BWziRm1b0SHTt2xKppwLguQPcudVfyhok3uqwEjh472dDRw964GG9MBN7fAeRGN/x4VYpSbyAuQ4bPvl5X574S8Q0sXpuGszdSm3ROgiCI+wUZFgRBEESLUpB6C2uPAXkC1wYdZ2Sgh+sx4GpS2SWGam0Obn6YMwh45z8gPqseYUUmHrA1A+Ljohs6fNga5eH5kcDOq8D1wL1oCobIxbODgLikTMiK02rd99rR9cgrBj7bXQpUlDbpvARBEPcDMiwIgiCIFiXq3kV8tBuQmTQgFIrZAkb6iBMDOkLAzNZDrU2mb4+lfwIbzwHFMtO6O9MxgJudIeITkhs6fOw7fgMbzgrRyU2IoKsND6VSRSgRY9FwwMQAyA3dVuu+J44dVL4pa6b8DoIgiGaEDAuCIAiiRYkOvwNrE8DcuXuDjjMxNkRmAWBlAgirhUIJjByxJ0j+fxtHr3r15+5sg/iUhk/QL9xKQFC8IXp0cMK1OzGATIrGcuLMZSz6DTj9DmCRd6zmHUuzcPxKPHp5AdmF7D3V4CAIou1BhgVBEATRokRHR8HLXggYOTfouGfHeeDpAYANc0jo26o3GigNDQs7z3r1N7CnL/p4lgKS/AaNI02cCzsbc/To0QNJmRLIckPQWFJTklFcBuSKAnDo0GGgnFkNWkg5gs0vAC885o4SCVCSl6K5j6QAODNFrhxFEATRCpBhQRAEQbQoUbHJ8HKxqrWInTY8XO0xoSvwWC8RD2VSQ0efV+Dm/zV2rFd/I4cNwNLRLOkjpv6DkFYgLauY182Y8NiTOPsuIMi8rLZLYfI1HP/1GSRdWgvkhdXq0RCLxbA2ESBSOBoLfpEg7bb2cChJ3F44WQKdBj+DJ/sB5UUZGvuUpgTit3/2IvvuxvpfD0EQRDNChgVBEATRclSU4JNp+Vgxr2+DDz12PRdbLgLzRltrbZ85yBITuzHvhXqNi5oo0nHChjNAbsrd+g+iNIOHItk7OEDHfiDyi4G0sBPKdpkM37w1DXPe3ISlL74A7PdD5A+mOPDtZK3dZYizYWNhgG6jl8LODDiy+w/NnaQVmPvOTnx7xhmOPv2x5hnARFSssVt6UhTe2w7sO6Zu6BAEQbR5w0IikSAhIQFhYWHIymrbSWQHDhxAnz59YGhoCBsbG0ybNk2tPT4+HpMmTYKxsTFvf+mll1BWVtZq4yUIgnhoyY+ChTFg79G54YeW6GLvdeBKjL7W9s9f7I91LzhqejNqQGDsibe3ARHB1+o/iOIUBK4Cpk8YyEO5lm01xue/Hqlqzo08iL8OJ+DrV/rh91/XAX6vYfsVIf7aekhrd84WpejhZwWhqSdG97LDkVNXAGm52j5FCacRGFqGjt2GAPrW3LhKitdUs8pMT+A/74bF1/96CIIgWsuwKCgowC+//IKhQ4fC3NwcHh4e6NChA2xtbeHu7o5Fixbh6tWraEvs2LEDs2fPxrx583Dr1i0EBgbiqaeeqmqvqKjAhAkTUFhYiPPnz2PLli38mGXLlrXquAmCIB5G0mOuoPMKID5fu9ehNoxNzfjP82Eyre36A36DcNSZevdnaOsvl5yNDq33MRUFibyOho6JPD+kR5f2CArLBMpy+ft/177ODafHX/wDVt2eA7qvgb17Z6Rml2vN5Xh+WDGWTu/I/z92zFicDylDQax6Evf5g+t5lNfACf8D9Kx4/Yxbd8M1+spMT+I/c3KaVrSPIAjivhsW33zzDTck1q9fj+HDh2Pnzp24efMm91hcvHgRq1atQnl5OUaNGoWxY8ciIiICrQ0bz8svv4wvv/wSixcvhq+vL9q3b4/p06dX7XP06FEEBwfjn3/+Qbdu3TBy5EisWbOGX2deXl6rjp8gCOJhIyr4Cld2svdomCIUw9jEnP80Ma1BTpYpRZnVXXVbub8T3GwEiIuLq/ch4SE3eR2NrGIT/r5n3yGISAXyYk8BmdewoFsItn46GSIrv6pjHJ1ckMrsjiL5xL+K8kKcv1eItCL59QycvBSn3gFMso+q7Xb8xEkM8NOHocsg7rGwNAZyssUaY8vMkNfBSMoo1PB6EARBtAS69d3xwoULOHXqFDp16qS1vXfv3pg/fz7WrVuH33//HWfOnEG7dg34gr8PXL9+HUlJSRAKhdxoSE1NRdeuXfHVV1/xKq0MZhQFBATAycmp6rgxY8agtLQUQUFBGDZsmNa+WTt7KVAYISxEjL2I+4viHtO9fvSgZ/9gc/P6RfjYA0LrLg3+/JqZW/KfBkZmzfbZd7U3Q1xiar37S06Igq4OYGzrwY/x7zUJIp1vcPXsLjgbJMOb9Tl8lVp/Ng7uKCgBctLCYGzE9qikMBnP/wF8aFaGCWMkEFh2gaeHO4qidkHU6XN5MnpRPHo7Z8B04AhIyiuYri43LFgIcvUxj+pqyJPRt11izpE4wMit1mu5sXsFZDIZuk/9HA8K9Pl/tKHn3zo05Pu23obFf//9V6/99PX1sWTJErQFoqPlMajvv/8+vv76a+5xYd6IIUOGIDw8HFZWVtzYsLdX10O3tLSEnp4eb6uJTz/9FKtXr9bYzjwgRkZG9+FqCG0cO1aL7jvxUEPP/gFEJsO1GyEI8DLDwaNnG3y4fZF8AcfSyqbZnv+iCc6wE0bi4IEDVapStRF/9yZPsj51MRSlglQIZRJ89qQQ1vlH8ORHaXh6jAfambNcB3m+A8OipALbXgLCrh9HqooyrUlZCLIKgYJiCQ4elBe/K7jhiA/XX8L4TXYwMzOGjQkwtxcQYt6tah8zI10kJadWvVfQvzgay8aDvy6d2IosHfkCmlZkUmz97jv09NFHqv4QPGjQ5//Rhp5/y1JUVNT8hkVbghkK2ib1qrBcD6lULvH39ttv4/HHH+f/37BhA1xcXLih9Nxzz/FtAi1/TNgqjrbtClauXInXXntNzWPh6uqK0aNHw8xMHgdM3F/rmX2xsNA7kUhEt/oRgp79A0xRPEK3lqFj7+EYM358gw+XJuvixFtrke7sh17N9NkXBh2ATnQw7Eb0VKuFURM/n3gH9ubAiPGzquRydQx7Y/OeS7wexYLXf4GJu7qnW5BlC13B16jo6ACpn/K6xXdymK2F7r0Hot0w+fai7g4Ii5qO5LQcxKSkIiNXiqd6m6PruDfRVSQPBfNPcYKxkSHsqt3DLxf+DyIJsHwC0CfAEQLPmu9xeeYNLI+swFP9ijFm7GhA+GBMB+jz/2hDz791aEhqQKO+STIzM2FtLU+8Y8pQLB+huLgYkydPxqBBg3C/Wbp0KWbNmlXrPsw7kZ8vT5RjCeaqHhUvLy+uBMVwcHDA5cvq0nzZ2dn8l7e6J0MV1g97VYf9oaOJbstB9/vRhZ79A0hOEN6cBKDvLPYAG36823i0e+YMwi9nNdvzv5dugkXvA2eGxUJk6lLn/v6OEhj3N4dIT/n9H1rghzf+vYSXHveCpQ8rjFENU3ce8jRt6lWM6qQcc05G5d8hJ5+qazF37YMP/klQL3rHDBhdpSfc19ORSUVp3MPw+Dw4W+jCd1k5Nnx5EQN959V4HWFB+1BYCrz2jwzhqzMB/bqvvS1Bn/9HG3r+LUtDvmsbpAp1584dPmG3s7ODn58fT97u1asXT+z+9ddfeT7C7t27cb9hkrDs/LW9DAwMeFVUNvlnCeYKmMEQGxvLVawY/fr1w927d5GSkqIWzsSOY8cTBEEQzcOdS/twgBWFtml4DQuOQACZTb96hSzVFzO7dojNAJKiguq1/yj/IiyY5KO2zcb/MXT1EGLhsu+0H2Rgj1gxEB4Zq7bZybwc6+YDFva1VAoXmagZFYytgaV4db08UbsKmQyZuSWwtXfmqlSJcZpytKpcvSCvvVFUCpTn1T95nSAIotkMizfeeIMnb7PEbCY5O3HiRIwfPx65ubl8lZ+FFn322WdoK7CQJKYGxRSrmLHADIznn3+et82YMYP/ZKFLzKPBJGlv3LiBEydOYPny5Vw6l0KaCIIgmo8d+05hY6AIMPVtM7fV0bMbT8aOj7xT984yGbafSUZwmroqlU2HKTh4XQIb/4najxPqwsHKECmp6tWyzUV5mNwDEBrVr1K4ggKJAW7GVrDy28qNkhyutmVt7w5nKyGSkhJr7cNVPwZzBwNSGZCRoJL4QRAE0VKGBctb+PjjjzFw4ECurJScnMwTtZnqEnu9+OKLCA2tvx54S8CkZlnYFDMcmHeFyQqePHmSJ2gzdHR0eAE95uEYMGAAZs6ciccee4xfH0EQBNFMVJQiKCQZPTt5NavHoanoWrSDsyUQHxtZ986lmfhqXwVuxmv501mZb1ETDrbmSBXLa10oOHjqBj7axTwatg0as6WVNXKYTVGmUpy2JAMeNoCbqwtc7EyRmKJuxKhRnIqRPql452m55z4lQenVJwiCaAoNyrFg8nYsJ4FhYmLCK1UzZSUFbLKuyGtoS3FhzEiozVBwc3PD/v37W3RcBEEQjxJlaVdwO06GVxY3MgzqfqFnhWEBejBCZp27yoqSkJYH2NnLi+M1BG83exTkpHE1JoURciskEbcTdetdKVyBpZUtsgoAWYkYAqPK3IjSDGxeCqBbD4gT7yA3LYx7WLQZcemhh/D3AWDJi49jcvevoVdR97UTBEE0u8eCUV0pqTblJIIgCIJg3L24G5IKoPvAyW3rhggE+GSRP6Z1K6hz17z0KJRKAHsnjwafZuHM/vjhWRlQkl61TZydC1tWlKKB2Dk4w8cBKCtQ5lmU5CYjKAaQCC3w+LjemD+oDCjL1nr8pdN78OspQM97FtYtAAKclDWZCIIgmkKDVaHmzp1bpYZUUlLCcxiY54KhWjCOIAiCIBR0tU1A4CrA0ntEm7spaWWOiLhxBwMnSQBhzeonaUnh/Ke9S8OLv5bp2iMqCWhfmAihodzzL84ugIezTYP7YgVeT7zF/qeMEIiJDMWkr4C7j5lAVmaD/WeB2aNjINRXRhWohjX38NKDjk0P3EgyhSw3FN0HNHgYBEEQTfNYPPvss1wRytzcnL+eeeYZXrFa8Z61zZkzpyFdEgRBEI8AsoxL8GzXEdCT12JoS1yK1sPiP6RyCdda8LCW8Am9jXP7Bp8jRizCiE+AzKTKPESZFNLyEtjbyqXbG4JUZImQJKAgO7lqW2ZGIoQCwMLOA5lllli5lSVl39U8uLwYV++loFcXbx6StTFQD7/vi9J+IhZKRRAEcb88Fqy4HEEQBEGocXqCvLhc3z+035iiZAxamYC3nhuNiRPa3r1z8/RDVsFeFKQFw8TEq8b99MrT4c/SK4wbnmPh6O7Pf6YmhMG2izwR/G8mUujTiJwTPSuM+hTY4nAPA7tUGhbpqWBRVUIjezh7duLbEqPvwr6b+qGlKRcQliLDO33lNaec7G1w8UaEZj5GQTRwoBPQfxPg+ljDx0gQxCNJg3MsCIIgCEKVoMtncPDAgRpvSlroYV4rwjtgYJu8cW7tuvKfCRGsyEbN/LXzEpaw9bV6VOiujqltOxiIgNSkGPmGknRk5AEVooaHQgkNbWFuBGRlKvM1srIyYGXCqrfawNjODxZGQFJ8hMax+nlXce9zoM/wJ/h7B0d7pOZINfIxypLOYvflIhzZ+kW9xiQrSoGsuFptDYIgHjnq7bF47bXX6t3p119/3djxEARBEA8SFWWY9FkhgEIkry7nNRuqExR4AMb6gG+vtrnybeXSBUb6QHz0Pcj9CtqJjk9FYbmB1musC4GxMxwsgJQkebXtwqw4dFkJHPhDgm7VvAp1omfFDYecLKWaU992OrCbrAfoGgOGLnCxAhIT5OdSJS/2NEz1dSCwl3tKHJ3ckJLDDINECFTyMc6cOsaNqD7trmDMq6WAjrLSuAYyGUb194arnQk2HFUaOwRBPHrU+9uRFY9TJSgoCBUVFWjfXh5rGh4ezmtCULVqgiCIRwjVWgrFyYCxm8YuQdeuoZunCDqWHdEWEZh48grYnVxrFyBJE+fCzlq9OF69EVlg2UQ9tPeQ8rfiFHllbBvHhitMQWQGKxMBcnKUXgZ/h2L4W8iTwqGjh+//ZwvbyrdVyGRY8vkp+Ho44L2n5NW8e/bsiX+e/weywgQILDtX7RoZIc8FuRZVgbzoIzBrV7OaV1H8aQTHFSM4vqRGiVuCIB4N6m1YnDp1Ss0jYWpqir/++quq0ByrvD1v3jwMGiSP2yQIgiAeAUrFVf8ty46EXnXDoqIMvhYpaD/Kv84icq2GriFG9nQA9FJq3kcmQ1pmIdp5Njy/giMQ4PGhroBuHn8rTo3jP63tvRrV13NjzeDkovwT/tu+GNjZWmJypVPIz9cbKKwMu6pEmhOCa5FlmDGlR9U2C/t2GMDWB0vUrz0qJh5juwhxLlSKMwf+wKRXajYspPH/wdseKCiR8Qrg0JPPCwiCePRo1Lf8mjVr8Omnn1YZFQz2/48++oi3EQRBEI8GxTlKZaLkmNuaO+TcxhN9JJg5vW2GQSnYccMcH/15p+YdJDlwt5HC16uyIF0jOBVujF/2yBWYMtOTePiVkZWmh6c+TOzviO7uZVXvD1/LQWiKTtX7vTd08ey3aUBFSdW2iGu7kFcM9Bw0XtmRkTPm/AxcvnxZuU0mRVRiFvzbe2NwgBFuXguseSAyKUzEe7DjZWDjYpb0Hduo6yEI4hE2LPLy8pCWppmklZ6e3uYqbxMEQRD3D0lROiZ0BVc4cjbV/P5PjQzE2mOAxESuVNRWySm3wPFbRYCkhkJ5xSn4djYwaXTjK4dHpOtjW2ARn+y7WEqwdBRLBLdrVF/H7upgw6FE+ZvyImTmS2FtpcyREBra4XIkS+ZQSugGntwLRwvAOWCSsiMjF4SnAJGRbOdKihIwtpMUQ/p3w4/vzsS748VylSgt5MccxdRPklEickYnZiMVkmFBEI8yjTIspk6dysOetm/fjsTERP5i/1+wYAGmTZvW/KMkCIIg2iRmekVYvwgYEQCIyionuircvn4JXx0AdC390JZx8/BBvBiQ1TCBLsuNR2AYUCJsuIqTAgdHJ6TmyHNROjhJ8Mp4nUaHDd1NlGH3pXx5TkNpBjILAGsb26p2Fw9f7p3IT6+sm1GSgU4m17Fytj9g5KTsSM8KDpZCpKamKrflhuK5EUDvfkNg6DUZWQVA5t3/tI7j6H/f8Zoatr1e5QX6avVuEATx0NMow2LdunWYMGECL5Dn7u7OX08//TTGjRuHtWvXNv8oCYIgiDZJSmIMDtwAXv0b+HnzOY32mOhweNoBAjMftGXcfTqhRAKkx1zX2p4Ycw8zvgeyS5mma+NwdPFEdiFQmh2DY4HhOBpq3ui8ExZ+nF0gA8oLICtO50aEtUq2trNnAP+ZFF0Znha9Ab08yzF9/nvqHQkEcLQxRnKaMlcmJuQCfjgCSE18AYcRmPWjAH9t/FNzENIK7D18GmN7WsDQZwbiM4HoiJBGXQ9BEA8HjfpGMzIy4gZEZmYmV4u6fv06srKy+DZjY+PmHyVBEATRJrl6IwQrtgClFbqIiNUMkY2JS4SnozGgY4C2jFu7HrA3Z5Wx72ltT0uK5mJHjam6rcDeuZ28r4RQ7DybiKN3lDkRDcXS0ho5RXJVLkGZGNHfAP379Kxqt3EJQA9PoCwvkedBvPXeJ9h81Qxw1YwqaOduC30oQ8CuXr6EP84AQgt/rkA1rJcnTl4K5yFXquRGHsDpOyWYPGkiYOgMV2sBErRI3DaUitwIyAqa3g9BEG3YsIiP1/yQMyOic+fO6NKli4ZBkZSU1DwjJAiCINosmeIMXvHZxdkJiWm58tAcBTIZYhIz4eHS8IJyLY2BTQfc+ATo4MBqcmiSlhIPaxM2z25csjXDxSuAGwBulqXIzCmGjbV5o/uysLLjhoWsRIyKonRIZYCOkTJfQ2DigX3Lgc4uJci89x82nc6FbfvxXIq2Oq/N7oNPppcA5cX8fVRUFLwddABDecjUiNETcSNWiszQvWrHZdzZjEF+wKDHlgFCHbjYmSAhSSWkqpEsm9MH3t4eSLuuxUtCEMTDYVj06tULixYtwpUrV2rcJzc3F+vXr0dAQAB27tzZXGMkCIIg2ihMatzKVAgXN08kZVYApcqibShJxbp5FXj+qcFo8xg6IrvYACmxwVqb01JTYGfGLJDqxSHqj9DEFfoioDwnHOK8ctjaWDe6r/69uyL8K0AgyUZQ0A24vwyUCS2UO+iZIybbBOFhodjy20ewMweGP/mR1r5Kde0RmlxZh4QZFvEp8Ha1qapH0X3kIpgZAqcPqEz0pRL44Dj+WdkRIlt55fLOvo4w0clTNy4bwc2IXJSUyWBycx5w+33ucSEI4iGrYxESEoJPPvkEY8eOhUgk4kV1nJycYGBgwP+wBAcH4969e3z7l19+yfMtCIIgiIebrOw8WJrqw9e3PXwczgBFcWz5X96YH8G9GXBp24pQHIEAH+wzQlnZDfw0Q7N5WAegnbGZ1hX/emPoxBOcJw0+how8wMa28Z4ckYkdRHpyj0WWOIVXNtczVUnKBvDDcX0UF97AjZhSPDOuA3TMvbX2dSdBiMkfA9EzomBg6ICopCL07qYsZqhr1RHfLbKHn/VdXpcE0hJkh+7Cpn2ZWPDCEhhW7rfkqYFAdHjTalmUF0Imk+LjRR1g7GiA/35fjQLDPZj7wRkI9Jhl10BuvAGZvi0EHV5v3HgIgrg/HgsrKyt89dVXSE5Oxs8//wxfX1+IxWJERETwdpa8zapxBwYGklFBEATxiDBvqC6Wz3BF3/4D8RerY1CoDJuNuBOILiuBrPLGr/K3JO4ujohLzQek5Rptvta5GN6r8WFQHB19WJjqIS0lAUdWACMGKQvVNZTCckN4vQLcuXMHmeI0HqYFA6UqFMPZ0Q7hyaXo3w54ctHbNfbl4OrLf6YmhAB54di7DHhy2kjlDgIBRk+YjuKcJIzuqo/BncwxbOJc/HICEHnPqtqtRNcZV6MAaZ52Za16UZIOG1OmauUPjDoHqfUAvP/bTRz+dUGjuvv22++x+JVVTfaiEATRzB4LBcxDwSRlSVaWIAiC8LbOAyy7QmbkxuVY/TzvwcZ1Kr8xMeG3kF8MWLrKQ2XaOh6eXojdcw8oigdMVCpiy6T49N849OjWCaMnNO0c9jZmSMkSw4kt6Fu5NrofIwtnlEuBbHEqF1KxNmVuDPWcDRcXF+QWheDr5zyATk/UPCbXDjzqKTkuDO7OdjBlLgiHzuo7tX8JVmlJmDY2EQYGhjA0NIB/pz7QtepQtUtSgRmmfA1cH38LDjaNNJpK0rHjFQBdewO6Rnji3bPYvFcXwcF30eA4iIpSlJeX4sxdQFaYAIFJEw1DgiDqpHE6dwRBEAQhLcdrf2Tj4HUJBMbuWLgeuHT5atV9iYmqlJo11R6C09Zw9+7Aazbkp6hX4JblR+HvsxIU6aiHGjUGRztrnAsDer0L5JY1XkVRoG8NCyMgOysD7R0qMKm3qYZ0ra2DO5KzgXzHuTy5uiZE5h7cS5CaFIeTxw+j21tMalauYFWFmS9sJ+7C4i+vYu6HZ/HEW0fRedKHars4e8kNyIToWiqY10FZfjKviyHRqSz2JxDCxc4Micnp2g9g+Rdl2drbSsX4+iC4FG9qyNFGj4kgiPpDhgVBEARRK2Wpl3D5twm8YrR6QzbOhwF5pQaAkTNcrIBEFblRudSsCQ8BehDw6dAb7zFnS0GM2vbUsNNcgalj14FNPkfPzt5o5wCkZAMm1u6N70jfmuevZGdlYkyncjw3SbOvQdNW4PsVY2HS5eXa+zJ0wMrJ4EX7oiKCucEitGh4QUMD6/Y8wT0hJhyNJToiGCM+AfIkynohQ3u5IcChQGs40/mtK+BkbwUUaRZnlJWkQ6dylnP94qFGj4kgiPpDhgVBEARRMxVl+OL1SXj8jYOQpF5QbysV84JvVta2gFAEFzsjJCVXyo3KZHAzy8HgHk2YPLcwpg6dsHgkYAq5OpKCu0GnuZqTZ2eVvINGMnRgT8wdBFgxe8vYsfEd6RhhXFcduFhW4OCFZNxJVqRQKxFZeGP6m4cg0FdRi9KGUIRZwxzgZ5uHqJh4eDsbA7qN8KYYOjW5loU4LQFCAWBh51G1bcb43lgwuIzX7KjOzj0H+c/C1MpCgCoUZCWgQgoMbA+YSKIaPSaCIOoPGRYEQRBEjRTf+gq7A8W8TkJKjHqIS1l+KgpLAavKis8uDtZITKsMSylOxpIREsx5fMiDc3eN3bHhjABHTqobUOKkEHTzEEDXqunqVvlSa3x9CDBk4lL66snWDUIgwIqZdhgVUIHvDhTiXKhmwnlDOBpiig37whCVkAlv90Ym2wt18Oo0B4zwL2v0ODIzUrgnRtXoypLY4u9zgDRf3ZPEmDNEXnhRnKxpOGSmxvKfXz8NDHGN5JXCW42iZCAvrPXOTxAtBBkWBEEQhHaKkmAY+QlOvGsIAxGQkRyp1lyQnQhXa8DazoW/f2pCF7wwvJRLhpZlBmPnVSBf2PgE5RZHRw+XYo1x4qJ6KM+TPcTYsapT06RmKykRWiMiFXC31QV0Nb0MDeF2kjECrwYjswCwtq6U+G0koWn62BGYg+7uFejXs/EG1PB+/giwTW20ClOmWK4KpWp0ZZVZ4c0tQHqcplfCzyoNo9hwy1Tqp1RioluI1ycCOtbd8cuRQlRkNz73o6mUn30CGTsfgHouBNFEyLAgCIIgtLLn+1k4dqMQ5oN/QNQ3QA9P9UJlVkZluPwB4Onjz9936NgJPZmYUmE84sKuYOmfQKFQbnQ8KLi72CM2KVs5MS7NRGR0AsrNujRL/9ZOfhDpAEsmKqtkN5bdVyVYd6SIJ5xb2zRN0tfBwQkpOcBbU4Chw4Y3up+gBBOs/DtPXsuiEfTyEuCl8fpcEUqBs7c8KTwx5q76zhWlWLI2EdN7A+7Wmh4bG6NivMqkpBxHYvVOICJoP1qFshz8ui0Qkz9OB0o1w7kI4pE0LDw9PeHl5dXg1/fff39/r4AgCIJoOMGfA6Hf1diccW8X3vz+PCJLOwFe81Au00W+WD0UpSArCYlsoVhPXkE6Ic8Us9cChRlhiI24zb0cdp6Nr9XQGri7uSEuoxwozeDvCxIvYchHwM3UxlfJrl59W1IBXI5usNq7BpYW5kjOAUokLBytaYpVTq4e3LD49wIgM5XXtWhsqNfmC7XXsihMvoatHw3VFAMA0Mm5BFMHqV+LoY0vr9OREKvuSZLlRyMwHLgUCURFymtqqRJ0MwS/ngQcu8yCvTlw4/JJtAZpd3fho10yxInlVdcJ4mGm3t9sf/75Z6NO4OGhTMAiCIIg2gYHN32KuwkVeGOjFsUgqQTvv7kAzlYCLHz3Py75+fxfBrC1DMKnKsUETgXexIqvgHvz5GE4euYeOHEPSIq5g+hKqVnhAyI1q8Ddqz3Sck9BkhUGkZMdQm+c4M4L/x6jmucE+jb8fmaVNaKKdDUsLC1QWAIcfhPw8VfWk2gMDs4+/OeyTcCTnzdcEUqBq1cHbjilxd6EYw21LLatexNv/3AGMxcEQuA4Qq1tw4EYODvZY/QUlY2GzjzkTlVxjJGdeJvXSdlyEbBzDcbLj6uf5/LNKOy5AvzPohO6eRvixq27eBItz7mjW6v+nxR5De72fVthFATRxgyLIUMeoAQ8giAIomak5dh6LhfH7gBvFKdyuVFV0m5vxa7AbOz47lmILNvzbU72lohLVK8lkJUp5om2Co+FrVtnHuaTGBuK2LhEeDiaNkteQkvSd8BQRKxZB1FpHBNsxd2bl+FhC5g4N9NkUCBEYlw0BHrqxewag6WlDa/R0JnVfbNoWsiZZ/sueH4kcD1OCBg1Pi9GtZaFY0/t+4SHBfO8CEFxNYlYmQy7L+ViSG8njFbdLtTFmgWOsLZRz9uIiwjiP3t4AhlizVoWWdnZsDbT48d379QOu4/f5vk/jVK8agJnAy9hXFcBjt6WIT7qNtwHtOjpCaJFeahzLE6fPg2BQKD1dfWqsohTfHw8Jk2aBGNjY9jY2OCll15CWVnjVS0IgiDaNKUZ3Khg5MVXk5Bl4T9JV/jEr9eYxVXbnB0dkChmidlFVduys7NgZSIARPLVd6GpB5ytgKT4GDw3OA+vP1OtevMDgK6FL4RCVqJDruBzLyQcHdyNAf3Kgm3NgNDUvW4J2HrQr1dH/G84MGUNKyJh27S8dVN3JGYBHk5WGoX2GlrLgv0OiFM0FZw45UW4FpzGf/9uBF1Wb5PkQZwng42NZtiZv3872InUZYDL8uLRxwfwsNeHODtP45jM7DxYsaIcAJ554jFsZ865rOtoSWQFsTh3JxfDB/bAGxMBe8MaivkRxENCo789JBIJEhISEBYWhqystpmM1L9/f6SkpKi9Fi5cyMOzevaUL6VUVFRgwoQJKCwsxPnz57Flyxbs2LEDy5Yta+3hEwRB3BekhcoJWsgNzbhzb+MY/PW8LnRt5KvPDCcXN17FWbUQWVZOLizN9Ln0KUfXGO2c9FGUGQ4P6zL4dez24D1BU2+M+hTYtOMEr+ExuVM25k5unsTt5sbazo1P4plB0CTpWoaRC/ZdB8p1m2hAGTrhyoc6GK/81VGjMOEcQpLknofQ0GryqyXpXOHKplK+WJXDt3XxzLdZgCS/alsfjyLsek0XNvauyGQVDKuRlVsEa0smMQVYeA2FhTFQkX6p3pdSlBiI1Ot/oSlIEo5gwVBg2MR5eHGiOXwtxU3qjyAeKsOioKAAv/zyC4YOHQpzc3M+Qe/QoQNsbW3h7u6ORYsWqXkCWhs9PT04ODhUvaytrbF3717Mnz+fey0YR48eRXBwMP755x9069YNI0eOxJo1a7B+/Xrk5WmugBAEQTzoZKfKZWN1dYC0OE0JTlbHIaKwHaAjrxHACAgIwOyBgLRAGec+rIMATwxRVzf6682OmNc3E2M+A8LFTQ/3aXFEZnCy1kdcfAKQF4xBvhUYOEQ9D6CtkF2sh5c3AsXMwa7fxORyXWPcvrAPX/9+tGn9CHVQYeiGnDTtBekEWVew5mkgwAVISkpSa5MUJPPQLhs7zUR0HSMHXAgHZIXy2hQM9rc7ucQF00cFYMWkCnmYkwKZFD/NKcOypyq9ZlY9MOM7YP2fW+p3HRWleHneGIydOhe5UY2/J3qZp7B0NODUZQbOxdpj88HWk7wliDaVY/HNN9/g448/5sbE5MmTsWLFCjg7O8PQ0JB7LO7evYtz585h1KhR6Nu3L3744Qe0a9cObQlmVIjFYsydO7dq28WLF/kfTCcn5RfZmDFjUFpaiqCgIAwbNkxrX6ydvRQojBDmyWEv4v6iuMd0rx896NnX8z5lBePSjncwaP5mNQOBkZwgV6a5/jFg7SxW/xyVpOLdTVl44emO8FDZ7urdiUuRlhfGoaJy+1DfYsjM/NWOL9d1wpWI67iTABjZ+Db7Z7Qlnr+bkxViE8WIunUUP/wNfPh1Oxi0we91XSN50rwUQp4wjYqmjdHcZ0yz3Nsv9gG3Q8Pwz2NlSm9WJQb5VzGzvw7ORBogMSVD7VyCsnTEfAvIunTSGIODWzuufpURzybmFpCUleGdDTHo29Uby/7nCS8JM0ySAGNP+QFlWTDRl0JqYV/ZlyGcHaxw4054va7v3oF3cOBaIezMgJ8/fAbL1kUDOvoNuxEyKb7+ZR/6BPhggI4FbicbYs/xTMwoKWh4XwSHvv9bh4Z8J9TbsLhw4QJOnTqFTp20F87p3bs39wSsW7cOv//+O86cOdPmDAs2LmY0uLoqE9NSU1Nhb2+vtp+lpSX3drC2mvj000+xevVqje3MA2JkpNTfJu4vx44do1v8iELPvnYSzn6KT/64jG12a5ApUg9Jcsq7hy1LAR1Da0RFhiCkfDekAnmStVHueR5aY2Bqi4MHD1YdY14Rh7ATgJt4N8rcbfikKfVwJty9s1FarNwv7lQyPvsLXGo2OC4fQUnKtgfl+ZubmeDSnRScOLAZR24D40MKUBx+f66jKZhUyPMY7Cx01Z5Va2NkZIgEcTmOHfwPEoGJskEmw/VNR9He3QbWlgKkpYnVxu1WdhJddYGL9xKQEaZ+PUb58rzHwFP7oN9uNs4d3YbYDCmGGRnhyIVY/LUZeE60E/l68poqxtIkrHwXeGl2JMzS5X25uThgy+Fg/lxLBTXnuOjISiC88jNmDtDH5HHDMcDkEKL2LUKY3qwG3Qfj0gisP1YEKxdb5B48CJGBEeIygdMH/0KRzoNV36WtQd//LUtRkWaoYZMNi//++69e++nr62PJkiW4n7z//vtaJ/WqsJAsRR4FIzExEUeOHMG2bds09lWERakik8m0blewcuVKvPbaa2oeC2awjB49GmZmTZcRJOq2ntkXC/OQiUQiul2PEPTs68dPx1aiixvQt4srZB7j1dqEN45DRwc4lNYDSz87iuBbLhBay78vL2zaAx0hMGHGC9B3HqQ8qDQDb7y+DK94FGLG+PF8RXjQchmWutrgCfa+kgt5R4G/rnN5UBZXDqHogXv+LsX7gPwIZCRFIsBVF8Mmzm9SQvN9ozgZ9uav4sVpHhiv8gxam7MZu/DtlmCM6OsNobVSclZWEI23XyzFu926YPVUewjj/oZk1MCq5P9zG3ej/TvA3ZvjILDqrt5pfjv0/vZTuNnqIY3lV3S0Q2oO0KP3QFjYOOJc2C5842UP287y+1CechZJWYB3+y7oVXlvggVX8dXmYHRxk8GmU833Sxj6JXSKCjFm9veQes2H8Ehv3Dn5H8a+/ioM7OqfN3Rl60soKQOmzX4NZu3G457wGvLXXUTXdlaw8Gs7z+tBgr7/W4eGpAY0qkIPm7SzUKiMjAz4+Piga9euVS83N6Z7d39ZunQpZs2a1aD6GRs2bOA5FiyMSxWWe3H5sroyRXZ2Nv/lre7JqG5AsVd12B86mui2HHS/H13o2ddOaGQCbsUDkSG34ddOfQL+35Eg3AwCnntjCorLjiIl7Bw8hvTjbcG3g9DOATBx6Qfoqhyn6wgnKyFSklPk33HFucguAmxs7NS+89y95V5tdwdTiPSNHsjn36P3IPSQ/o6nfypEx3auEOm10bAVoT2sTIDiCuM29XfHwyeAh2ZlJwXDwUEp0xt77zCvEt574FjAKBNpuYBdaQoERvL8kOzMNBjrA3qmLuwBq3dq7oXdrwFSFwn2ZQMpcbf4Zm+/ntAzkP+e5WYkwqnyuCxxAv9p5+BWdW869J2CJ/p+jArxdYhEypBoVWSlOXj97Q/wxGAH9HriOejo6CG/8w/45KURiMybgZW/x8iNzBIxyrNDoGvbE9A11NpX4Nnj6OIuhLXvBP5Z8vLrxbcnRt2CbafWqKjx8EDf/y1LQ75fGmVYzJ49mxsQixcvRnR0NA97+u677/iEnIURZWayUqz3DyYJy171hXkfmGExZ84cjZvTr18/njvCFKMcHR2rwpmY0dCjx4NVMZYgCIIjyUNofAH/76079+Cnvp6C4MhkxGfrwyVgDEwMgOCbgfCoLFX0VA8xhvv5ak6WBAI42ZogKUVekVpSkMaLk1laqy/AOHrKFZRemBHwwD4MmbEX/jgNBMUAj01sWuG5+4qOAT7/cCVc2w9EW8LFuxuWjASEJep1KoIuHOaGkEe3yQg+/zdGvQXcGxIMS0v570qmOINX2NaqcKVjgIQCWxSEhwG2gJ1+Jr6bA9i6dwVkEu5ly0iLhzwQCshKlxsW1vbuVV2IbLrim2f1AZFmlW4Fgf++ii3nS/Hcyy9X1WAx9RiOj1+djOc+2AvI3NHXswTDfMR48x9gwtSnMXzRP5odlRcjNSkGw/p4V32WzBw74fZngLWLMj+TIB42GmVYMJnZAwcOwNtbvaJqXFwcbt68ibbGyZMnERMTgwULFmi0sdAlpmzFjKUvv/ySJ6IvX76cK1xRSBNBEA8kOfcwqy/wzWFN5R1GujgHtpYmEJp6wc9ZFyHBd8EDM0rSYS5Ihnln7au5TvbWuBsunyxmp8vVeaxs1RV89K074K1pBrD3enCrCwtMvfHjUeCD6cDjj09DW6bn1E/Q1tC38sU7U9kMQz65V5CXGoKhAQYQmHjByV1usCXHBcOy0nYTZ2bBxlxUY1HFX07pITE1AlNfASyFyZjRh83WfQBJDnwdgdICpZSrrjSH12Ixs1GJohCKcCfHF/cuB2LWUJlGYrmsOAOf/fA3Hh9ogXbDlqu1jV+yCU+cdsXZG0nwdnAHvCYiPG0jbC5dxPBFWgYrDsTXT1dA1kVl3mHkChszXUgLolFzoHU9YJK7snJAz7IpvRBE2zEs2Co/y1moblgwyVn2amuwpG1W08LfX7GWoURHR4cbSSwvZMCAAVzl6qmnnsJXX33VKmMlCIJoMrl3sXgkcDMOSEnT1M3PyCpE9wAPPrFa+nh7WCKWJ9YWJV3A4HeAf35yhp+WbpfM6g1BfAyf2NiYSHDnM6YkVO17Vc8cS39OBnRVknYfNAwdYWkixM04KWZaP4C1OFobIxdEFfvi87f+wI9bX4GeTUdeGG9eryTMmzKe/95ZOHbgCf7JcRHoWHmYr50EtoY1T5ZdXRxw6U4ShLIybNh5BYJSU8x/yoQbDCfeYpMQpfoZC+f7i9V3NFaviRGS5YjPdt7BrI8SAGP10O0L29/GrdgK/PTdB7xatxoiE3y1o7LyfGXeUI8OJ3AnLIF/dqobKUm3d6MsHfB0HKXcKNTFiu0mkEgDsWYoGs0L0/2RnVuAzadzGt8JQdwnGpWNxpKWP/zwwzZbGK86mzdvRmBgYI3tLKxr//79POudhXExqVxt+RMEQRAPAhfPHsMvJ5iHwRzJ6dWS7sqLYCQqh7uLPIRp9Mih6OVeCBTFI+TaUV4Ez6m99lmPlYMPLI2ZREgChJIsWJsyyVP1OhYctpLazEnbLYpAgNAUIf48y2L7H9yQrlZDIIDVoG8QGCbFr8ztI5OhJDkQVyPLITHvLd/FRF7cLykxruqw6b3KsGhKzWqSLq4eXLHMUCbG2etJiM2pFErR0UeuxAziNGXoVUREFC6yiCd99bDpzj0Hg30k0sKOa/Svm3sDz43UhXt/ZcV5NdjvtMrvdadOAbgTJ+FJ6dX5898DeH2LDmChXlzR0soWsck5cmNEQUUJdnw6Erkxp2q89qpdcyOx62wSTt/KBaRMY5ggHgLDYuLEiVx6lsnJspoQrGjelStX1Oo6EARBEK3DiXPXcCJYF6/OG40/FpapFw4rScOfi4EnJ8uTtdMqPPHiX0BB4iXcvnEZHraAmVt/rf1GiQ3QeQWQmxqGwyevYuBqzYnbw8Le9a9j/QczakzMJWrH0nc83lk0CN9sDUXS1fW4cX43pn4DlJlV5i6KzLBwhAH8HUrk72VSHLqcjihxzQn/Lh6+vICesCACsWmlcHdTSse/vU2AjzeGVL3fcyoUXx4Q8sJ/qvh0G8c9JbcuV5MrlkrQxy4E7/xvUL2N4k49BsNAD8iNrbZwKS3H9eAEdO/oxgsGquLh4Y64jAr+OVSQdutfvPjFCaz/9u06z1ke/S8P+xKxbkvl+U4E8cAbFhEREVx+lqkz5eTk4LPPPuNF8UxNTdG5c2WVS4IgCKJVCIlMhr+3PUxtvaHHIjqKlHkW5fkJiEgFJDryBFkjhx7YcQUIu3kad0MiEOBlydwQWvu1tPeBOB9Ijr0LcUYapLJmqPjcRuk57RNMeFFTnpyoP08s34oOLrp4761XEXTpBPycWPSRUsL42fHe6OOWK39TmoXVO2S4ElnzKry3Xw98PwewkwUjTgy4e/pUtdlYmSEzWy5YwMjKyYW1uaZRqGvdGQFuQty5fUNte1naVXy7rxDZ+vUXbfHtPh5XPwQspGFq28szb+FmbAV69JB7Z1Rx82yPlBym1hxatc0w+4T8FuQrjY2a0E/5D/++UBnmVZxS77ESRJs2LFhuxbRp03gtid27d/PEaGZgHD9+HP/73/+af5QEQRBthfJCXP5lOMrTr6JNUpKOkMRS+Pv54l6SDrxeBQrF8krbjLTEMAz5EEjKrVS8cekDNxsg+PppOJnkY3j/mkN/LJ38oS8CkuIikJWVLVfw0au50BjxaCM0dsRnH7yJ0f5FuHYzDD072Kl5EIISzbHhkDy/h62+ZxYA1jY1y7yb2Plheh/ApOQuVzPz8FEuZNraWEGcW1oVHsSMDCsLLXk+Ql389npXvDQ0Qy0c6XbgdnyxHxDaDqj/BZr7I6tID7HB59U2h13di+IyoFt/zVoV3v49MLUnUCSuNCykFTDLOYo5g4CYhJqL8jIkGTfxzCd3UFBhgqEs4b04uf5jJYgWotkq/jAFpcGDB3MvBkEQxAPN1SXAuce1NpUmncPUFadwaufX2o9lq4hpdcdK3y/yE68gIw/w69gDNk7tUCoBUmKDq9rTk+Tx4LbOlau9uobwdzdHSGgolk0AZj0xvca+WVy8kwWQnBiL7JwcWJrqt83CcUSboeO41Zg5rhsXEujWVT3fICzdAOuOlQOlYhRnJ6CwFLC2c665M2N3fL6PeeSScPdzwKeTMmTPxtYOGfnM9SCXu8/MLYa1lbnWbuy8+nEPiaxQmd9xJfAk96iYe42o/8UJRVhz3BqrfrmsZqQ4iyKxbj5g136M5rk9uuHHuYCFQG5EFCeew5RPMsBUaef2L1IPW6zG2V1f4VwoYNZhDub8DESH3a7/WAmihaj3X4T4+PgGdaxN4pAgCOJB4NaFfdi6fZ96gmUlKXF3+c8OjhKtx4bseQknvh/JJy4asP4uPAPEaNG9bwwVJRoJnKYV0Yj8GgjoNQo2Lh2gqwOkJCh1+zNS42GkDxhbeVZt6+DrwYvp7Q0CZBa1qCCJLDCmqwiWevlwty5H3w7krSDqgOUY9P4FE3sZY+gkdV1WJxcPXj27Ij8WmWlyg9favpYiuyIT3E7Uw9E7QF4Rc2F4VTV1DfDFAlaLheUulBdj5aQKPD5Cm7YZEFfsDt/lQGroiarP5eUboejd0R4QmTbokQZ07IC7caVq3gOL0huYPNgTMNTifTHxwsl7wK0b1/jbcwfW4XYCMHbMSAxsz1YGaqixIZNh9959GN7ZEHbd5uFMCBAXo/REEsQDZ1j06tWL13ZgSdo1kZubi/Xr1yMgIAA7d+5srjESBEE0L+VFSL3wGU+y1EAmw9xvk/DqRglQqlnsMzFWHk8dG6upBMPYf/IG1h6TcpUlDViyZewmSML/0D4umRTludr7rb4fwn4EtlsBN5apNRWl3uSJnbrWXaBj6g57c+ZhiKlqT09Nhh0T0zGUFwRlLHt+JuYMBFbtAARWtRgWAgHem+ONSV1LMHdQBZZMU8a4E0SNvzY2vfDR9gLYd5qhtt3ZzZdX6BYnBsPGqAS7XgWc3dnsumac7S2w9RIwb70QMFBKybb368AlllkoIPOA9PBkYdte2vvwHwGhALh9RZ7ALcsLw/WoUvTp3bPBD7FTjwE8Z0IceVq+oSwHi9aE4HyS9nOzpPUN5/Wx67i8cvjRY8cxuKMBJE4z8dzvQGqk9jlWcdJ5HL6Wh8cmjITAyBV25uyzrF6AkCAeKMMiJCQE5ubmGDt2LOzt7TFhwgRuaLz44ot45pln0L17d9jZ2eHPP//khebYdoIgiFaDhSRJqkmtVhJ04DN0n7ASyde1eA4kuUjLkXsqpAXyInCqJCXIJ+nbTign66qERKdzmcuCdM3VRGlBHJxeAPouUY/JVnDn8Ofo3MEb0rSa5bHLcmKw9pWO+GzVi4hJKcZvv/4MlFUmwAJY/dNhLNloABjYccWmKT10YGOgTGrt4i7Dy+N01IprCa274VQw4ONiyleFayM+3wZnr8Xi7E0x4nNqVvAhiLpw8uzEfybF3IOBLAd9fJjDQL3gYnVcnOVeADdHC7XaEYVSc3y6B8hIioSsJB1P/QiEJEm19sESuDu6CnH71nX+XiAOxMXVwNjJTzb4obXvPo4b8nevyY2UvNhTOHCTOSu61niMm5M1YhPFkOZF4lhQJkYN6Q0jh844dAsIv6fdsEi78Se6uAGjZiwHDGz5gkFqWu05GQTRpg0LKysrXjQuOTkZP//8M3x9fSEWi7lCFOPpp59GUFAQrxcxbty4+zlmgiCIOunfzQMfvcBiIzRJS5IbDKnxSnlKBTIVBaWMhHsa7QGOpXzFn9eHqB4qJZMhLlUeIx0fdUfjWHFlf1n5Eh6uUZ3gG2d4crQw/l+t476ybw2G9G6Hn3aEwtlvCDJdluG9bWWIOfdt1fmZYePt4SyfdAmEeOcZd4zwV56rk2MRnhjmpDYpk5p3wd7rQEFFZV2AWjgbJsSbm0qwYksFzt4jiXGi8Rjb+iLoI6CLmxRHTl/D4t+Z7JFcrawmXFzkoVIerkqPG0PHyB4/HGXhQWHIE8fjdAhQoVtDqJ5QF53bOeJWSBz/zBTEnYKxPmDo2oD8ikpEtl3x9WwhfMzkCk03AvdxQyOg75Qaj/Fwc0ZcWgly7v6F9o7AqMnzoGvpD3cbICpCmQ9VhUwKj/LD2P6OF4xcB/HPtaeDMcqLlQsKBNFWaHDWnYGBAVeE+uabb7Br1y4cPnyYV7ZetmwZD4EiCIJoEWQVPKRJK9Jy6AnLEJ+oXTVFUC73ZNgZs2xPdfLSI6v+nxgtz6dQpaNDLl4bDyRlSYGybPXGUjGKSuWrpEnxyn4UJMfJJw1l5YAsX7M9KiqS2yr/bv5HHu6kSnkx3n57BTq66eLC0c2Y/f5p9JjyPjq76+KP9T/xCRJLRg1LroCfn7IadniWFY5fUnpX/joYheMh6jKcQmMnvP/WK/july2oCydnD15Ejyn4WFnXPgkkiFoxcoGjJaBTmoSo2CQuIVuXfPHkcUN5kUY3d2WOEMPAwpUrRYnTkpCVJl84sLarOV9j9NDe6ONZBhTGYcWafXhjuwVgqF6lu17oGODxUQFw0ZUvUgRdvYgAVwH0HTSlZhW4e/jwa7VM/QPbXtGHfecZPETK29EAUdHKhHIFeVGH8fO+ZBTZPV61IPDDS/5YNkEzB4wgWptmkfPo31+zmFJ4OCUVEQRx/xBG/AjsctIe7lRegF5egFBaWXyrGuN6miD5J8DFVNOwyEgMh44Q2PMa0NlVM5Ri3a5IRKeDx1XLCqvlURTFY/1CwNSQ5TVoThCSE6L4T2Y8ZMbLwzBUiYpL5fOGtzbloijupFpbadQ2dHQux5vLX4N5B3nIhkBkggWzRmLrmQzkxx5HUsgZ5BcD/l36VB13NlSIT3bky40wmQzbA7NxN0mzANj/Xv8Gvp0Hoi6c3NvxuHh2HkvrmqVBCaJOdAzwymZDfLT+AjKZfLG5Pvcm1IbU2AOLRwBdulbLhzCwh40peH2VzHR57oGVvUeN/QweNRkvMtGmpP24EprXpIXRoHQ3vLwuged3sHDHIT1ceTXwmujbbyD2LQc2Hk1Gmt7AKgnedh4OyM8Va3hCT+xai+8OAyLvWVXbSnXskZKcorkAQRAPsmGxf/9+Hh5VWFjIQ6RUmTFDPUmLIAiiIchKxHCy0sWhP9/U2n7h7FHM+zFXe5Go8gJsCgT2XtE0HBgF2Sn49wKw5/hNjTYf+wrEfgf09AJEZdXU7SQF+OdsMaxNhdj7GjMsEtTbCxMQ4MpCO4DkFM34ZxNBNqb0AGb1A8pzqnksyguRnlWI+WMdwNYkT+/5Qa1ZP3Ejvn1WhHZDX1PbPmX+J7A1Be4d+xrCwnAsHAZ4dBhc1e7o7MY9DChK5B6W9FwZ7O3t0FicPDpW/d/KtvZ4eIKoCwMjM8QlZUKclQcby7pzdgROEzBk0v/gOuBl9QaROWxMBcjIyEBJgRhu1oC+WS3StVY9sDkQOLLlUyRmAX0GjW38wzL1w3+Xgdx7G7F8bDHeeH5qrbubOQWA1e5buRUQGyjrZrz13Eh890wZ93yqcvHyFfRtbwCRjVJYYdflEkxZU6GxL0G0NrUvDdRBx44duQxteno6nnzySSQkJMDFxQVOTk7Q0VEvY08QBNEQku/s5+FOecnqFXIVrNl0C1fuATJJPp+IqyGRJyt72cqAilKN1cNVv9/Bv6eASX3iUT0SujQ3gX8xvvOfAAbmF/CuyiI+81AkZQN+vt7o5BYBlKgvqNy7dQWvfwFeHdjaQTNMYbBvKQYvMpDLxBpUMzzywrF3GSDt+D/civoGh46cwPiXpDyeuiI3Aqt/OonFcybCycBG7TA9u24490N/CLNPATIBPmBlKKyV9QKcXLyQVwwUZETA2FoClhpia994g8DMvj1+XQCUlgOuHu0a3Q9B8N9PBzvciUhDV89y2Du61H1ThLqIEY2Hv0qhPY5AgA0v28PY0ggG9ga49AGzxm1q+UX2x9bLQmTkJcPcCPDtrb1uTX3o0GschIKvcGbP97Bj6rp9e9e+amvihd7vVR47RCnBKzNth5RswC7rHnSdhso3luXg8r0MzBrfXS0vys7BBWm5LCcsGQIm1NAaMM+KVALoyIttEkSTPRaenp5YsmQJr7595swZREdH499//+VF8k6eVHfjEwRBNITgGyd5IvP0/toTistK5WFORbkZGm3SSpWkz2dVSrxWQ5wtT7BOzijQCDtY++95TPuGJYPaITJeXW42KymYF5xz8emJx78Fzp5TV2+KiQpDTAbg084XlsIUjb4vXo9EVKE3zkaY4NwF9crdpRl3eIEwHcsOGDdmBC6GFkKafpG3Be74EH+eBfR8Zmu9F0Lf5xEYUoqP1h5CYJw9oKcsDObkwUr0siJ595CfEc3Hb+fgjkZj5IqJ3YHHewNG5uSxIJqGs4sL96h9PL0ULz3ZvUl9Wds6wUAqRrY4GTlFAjXlM60J3O0dkVMIvP6YKYTmtcvc1oahY2+0cwC+35mARb8BAtt+dRwgF0/wczeFwFhpTIklDuj5DhB170LVttyoY4hMA/oMUE8st3f25CGJOamtF3Z+7q95mNTbAFs/HIIKsfYFIOLRo1lyLFjFbQXOzs4YOHAgLCyocBJBEI0n5O4NPgm+cU97XYfSUrkiUYEWw6IoX24QnAxmUVHVQqVkMmTllcDLTnsCdmqaGPZWhnBxckRiRpFarYuUeHnytbPfML7yHxWtPrakxHg4WwKHIlwx5ctSdaNGWoGPt6Vj/00h9t0xwabD6oWwzp89hoA3gQpjH0x6+g0ErgKEiTv4cf9t34lhnYxg06GGVVW36dh0SR9rjwN3MtRXaW1dO2DHK4CzWSHMRPmIWAN06FSzFGadiEzxxI8iLptb64owQdSD9u39edXp0GQmGdu0ecMvx0rwzFcJ+GHrbbz4t568OF8tdO7UiReQnPfESDVvQIMRmaBHeysEJwHdfQwgMKk5t4MjEOLmuV3Yd7Cy9kUltp69eQJ6dJhykm5eeh13PgM6D5qptq+9i7yGTFpiDQX1WoC9+w4gNUeGbfvOQnikOwoPDEdujPo1EY8ezWJYEARBNDdLhuRgiD/w9xHNWhLMOCgtK+P/LczXrHAtKcrlko8/HweyUqsZJuWFEOdJ0dkNyMgDyvPU+08V58LB1hwurm5IYl2rVNQNcJEhfA1g6tKL539Uz6NISkmFs40+9MxceSVrteTukhTen5OTMzzdXRCdXMTHoiAqIhSetoCOhT/0HPpC19QdsUFbUBi1GweDCjF96qSaJ0o6Blg4R250dOjQWa1JaOyGfu0AI1k6ZEUpMDYAdE1qiT2vB+fDKj0xdSj4EERdBHTtjZ/nA2M/By6HN02+WM/QAgniCmRmZsGKxTfVde7ugyHOB5Kk8noaTeGr5WPRyRXoHuBTLyPFruMUGDupe2gEJl58wSMqUumFKIw/DStLM+haqxeutHJsz9XpzEXa88juO2XZuHxPjAVTu2P7wcsQeMzChv9OY8WSSa0zHuLhNixSUlKqVhMJgmgDMOWQCvlE/IGgJAOC4kT4OwGZLFahGrooxqtjZdj+MuDlpDmBsDSR4ean8v+LU6sZJqViTO8NLBplwlfvdSVpyjaZDCniIjjYWcPH158X7JLkKA2T8rw4vqIoMHaDk60pklPVQ6VMdArQuZ0NnNx8uaRsZpKyTgbrh3k5WM6Dp7cvD5mS5SlXG5nMpLezMaBrxCcmW0I64rGPUxC6/zVeN2P006trvWXdp3yMf97wRv8Ji9UbDGzx7nYh/tx5AfuOBqIPi+1ujKymCqN7Vx5fW6gJQdQHI1ee+Mw+L9Z29cixqAUbW3tuKGTmFMDasu6aLP4jXsW275+Dc3/16vWNocS4E+4kAJ27KxXZGoyOHrydzREVW1lRu6IEM1Zdxs+BLhqLCkJjZyyfADiaNMKwaAYlKWnaOUzqDgwfOQECm97AgH9h5T0Ml0IKNEUtiEeK+2JYzJ49G35+fli+fPn96J4giAZyb9sc7HzHvc1JE8bGxuLqlcsa20tTL8N3GcBSHDJzy+QJgiroy3J5jD9biZeVaf5hLczLRGImIBQwXftqf+RKM7BsAtCtew+ewyEtUPEqlGVhbGcZenVpB9+OPfDXYkAkUYZSfbL+LBb+Jq9a3cnXAVYGhco8CmkF3hibj2Wze8LZUy5dmRyrLHaVFn+X7+rs4QdP3648nyIj9pq8USZFVEImfDyUOQsjp76AjHy51+PCuhHQt64jBtzEA8NXRkLXURmayhEIkVFkjHsRKUhPTeGFwJg0Z1P45a89CDn/d53SoARRJ0aueOVv+X9tmpL7w0KJHJzB0qfScwFrq3qEVekYYODsdRDo1W2E1IXAdQqem+SKfhNfbVI/00f5YbRfHv8+KYw/gzvxMnTqoUUGWt8OWy8JcOaiZiHOWgn9DofesUTqjX+aNE6h+Dxenwj49lGGZ/boO4InlKcEH2pS38SDjbC5PBRSqXLCcvz4ccTExGDhwoXN0T1BEE1k0Qf7sXRdKlCgPV+hIfzz6TS8OkO9OFUVUgmurh+F4ph6/GEpiEbE5tF4feFIjSTn8JsnUFwGdO/ggizmsKgmqSiS5mD1DsB5KXAi8JZG17fvRWDM54CVCSBOV8+xyE6NxtpjQKFBR/RdBew7dErZWJzMwwt69egCGLnhXCiQEHW7qjkpNRM2VubcozD/8T748HGJso5GSQqCoitQKHCEqZ0vBrUHZMXKUCkrvRz8/Tzg7NUZ3h0H4PQ7gJVO5diKEjChqxTDByrDHez9x8HVVg/LNwMyrwVoCk72lkhOz0V6hhi25rpVuvmNRc+uO8w7PtOkPgiCY6isoG3tUMP3Sj1xdvHCmM7gks59u3q36A3Wt/bHqo3xMLBVyjE3hmGD+2Nc53JeE+f62e08qqr7IC3y/UIdHL5rgOOX5LVx6os04zJ+P5aHMY/NxqV/FjZ6sWnb9t04fM8IMFfW/2jXcwqv4RMUSIbFo0yzGBajR49GXp6ySFV2djauXbvGvRYEQbQ+ndzlBdEyIs80ua+LFwK5p4GtqGmQH4EpbxzHsleX1NpH2q3N2PR2JzjqRCA8oQBpYSfU2oNvXYK9OTB92hT8PI9N2lXClViEQFEGfqkUnivM1yyQV1iQAwMR+LED/A3U2uJiwvHRbkBm3hkWRvKEawXZKeH49SRQBGu+kvr2NuD4mSvyRpkMSRn5cHaQJywXCRxwOVLp8SjJjMSkr4CQFBEExq7Y+hLQxUUZfmYkTcOIACa37wmRtT98HQHd4kpDLy8M84YAvfsNUQ5UIMCUCSMRniaCwPUxNAUnRwekZJVxjX87Zm0RRFtBqIuuXvLPqIG5a5O6cvXqgA3PAS+MBnp0VVaff5DIkjrj3f+AvKQbuHzxLDq5CmHkOkjrvvY2ZkgTyxXw6kt4dDzemqaHCX3tMOPl3/HbG90gK1UXsKiT8iL8sT8SwdnuaiFaQgt/LBljAFth0xewiEfcsNDV1VVTgTI3N8dzzz3XHF0TxKMLy4mQNE9i3o+LLDGiI5CfHNT0YUmK4MtC7CU5Gm2SArkBcPxKvHbDQyZF/qV38PTTT2PL+TL4jljBJ/fnD/6mtltIaBg6eJjCzq0TurNFzJJ0tfbifLnaEkvQLijQvEdFhfk8F2JAe8DeWF7TQkFmehIPgTK27wgnKx0kpyiNlqiw23h/ByA0cuJ5CM5WAiQlVRbJk+QiKbMCzi7yxOeEXENM/QYQJ8rDnZJj5SEJzh7+PE8iPNOCX4eCbfsv8r651KSeJZZvMcDXG+QKKrHBgVhzgClCqdeFePOrfYhKzIVA1xBNwdPDE1bGQEf7XAzs2rT8CoJobnr62WAUy59uaj0GAzscvAkeWpWWr76g8KAgsmyP308DkXcD0cUmAQsnt6+xiredjTXSsoo0PL618dfBKKw7KcInm2Lw1cuD8O2W20je3bCE64L407ibIEOf/ioLIQyBEC/PHoy+9uEa4avEo0OzGBasKF5goFLPXSgUoqxSsYUgiMZxZO10zB3joH2C3kAys3Lw41zAy0iLwlJDkMmw93IB/j7PwpM01ZgqisV8gvDsQCmQowwhUiC58yUWvPIxSmRG+GvXZeh1/wAD/EQ4f04lHKksF+2tszF5eCekF+hh8hogLUFdUrGo0rBwswEK8jUNC7aN5RKsP6WD77aoj0OckQJrE/CiUk525khOU15HSlI0N3QMrDz4H0kXe1MkpsjDsFhCIguz8PeT5zo4uVfWh4iXJ2gnxYZCRwjYuclDIdad1MUP25XqLrdCExCfY1SVlyDUt0RItDxU6nrQZfx1Tl7DQhX2XWpo2DSjgjFi2ABsfwW8KvcTY9VVowiitZk7cyRWzGD1V5ooU29gh4XrgW2XgCJp08L9WgtTp27cWxt1Yz9GdSjG1Gk1V/F2cLBHeq4MKFUXkaiNrJwCWJqb8MWPJ949g8s/9YezsGF5GtdO/8e/67oPVpfAZWQIO+Hz3SWQZFxvUJ/Ew0OzZN799NNPmDBhAvr164devXrhzp07cHNza46uCeKRpSjtFoIiiuRhQGwFvQm89kcWDFmxuUGXMG5YEzqSKN3uJXnJMDBTX2E3EOTzhGdO+mnASl0i8d+Na3EnUYgjZ6/Dyk0+QZ/z+CDkRrP4o2T5debcwpP9AXSbijx9Z1yLBtJTYqGablyUnw1DPeCxHoCXg6YEazdvIywbDwSLLRCRrP5HN1OcARtTuVrSgK4uiIlSGi0pSYlwtKz0KrBFE0dbufeFLcYVJ+IzVnAvQC4RyfIomFckOT4SrM51cmIMHC0AHVO5hr2zoy3OXQ2VxzALhEhKy4Grk1Ke1dPDFUGHUniORlRkJLzZdVSet7mRGjgjJBH8Xo55zBTksyDaEl4Tf2FVLfnnpEno21b918q+jloSbRVDJ3jZ6+DA2XCEhQFvDR5Q4wrwY2P6YqLTKZ7fBYP61ZTJZjV83CrzWgQCZJXb4ML1PIyaVlqjZ6Q6oXcuobO7EIbOAzTahDa98N1hYOzl3egyuQkKWcSj7bFgRsT169cxcuRIxMfHw9fXF1u3bm2Orgni4YGt9q+ZiISrG+veV1qOGyGJyCwAisR1V1atKErHhd+mIC81VGtfBSUVCEkGVmzMhqxIvfaCNhLiYrQ3lKThxFvy/2ana0oKRkaE47O9wL7rwOZN1VRHCuPRyz4eX70yFG5eSoWjQeMX8krOSD7A3+fEBmI9szP0/WFq48nDnTIzKsORKhnSUQ/XPgKWTTbCqK6aK/r+LkJM76sDG2sbZGQXqbU9M8wCvy4UAiILjB/aBS+MKGYxXLwtNTUNDqxotb48JGPKiACsekzC603ERdzEVlYI26gyDtzIBU6WQHKS3PDo4V6O96YJqowDVq8iOUsmD+OqKEWSuARODkrzyMu7PWK55Gw4ouJS4OVq07QiXbUgM3TG6M+AlVuByIzai4YRRIujo8eLzDVLP5WfITObpilMtRoCAbxdrXH0DnD8HiC016IIVYmRlTvMmNp2cbUioDVRUYrM/HJYWio9Q9eiK/D6ZrlaXr2QlmNxvwRs/3CA/H5Xw7rdSHjYAtcvNz2fr7FIi8WQiBuolkW0PblZkUiEmTNn4sMPP8TSpUthYkIJggShRkkaFn90AH/88G7dN6YgCr+dlKt1JEbdrHN3aehPmP76XoSe/0OzsTwfBSXAAF8BLwiXGlaZ9VwDZ3Z8gT7dvBB1ZYtGGyuwxlblGVkZmoZFSFgkD5OKyTLGb7tuq4dxJe2DvzMwYWa1xG6nsfjhqACHdsrzLG5fO40PdwMiu54QGNpzZafMDHVjyEiQBwtzU1yNN8XlO5p/VA+ci8U/F/RgY2MDcV4F/4OqwEw3B27OtvwPeG6FNTaeY9FXckNq6XgjfPqsXVVCood3B/T0YkZRAi5fvobP98sNCo6eJd6eqoeBvvL4Zh+rbEzs71QV6uTk4oHUXKAiPxYoSuTJ5B4eylXU9gG9uFxuYeIFRCYVwdvz/nl5dUzdoVfpn7ZzfEBXcgmiHggrP7sCA6X34kFj9fMDeUhpn452gKhmKdysEhP4vw6EB9cz7Kg0E6umAqMHKkMubeyc+AKWtB4LTgxJ+lWkZRZC37lafoUCfWt0b2eOoJtKqe2W5qMXBsLdtzNkxeq5ecQDZFiw0Kf58+dj2rRpWLVqFRISqDgKQWhQmsHDd/q7JColSmsgL/Fq1f/jo5VF1rQircCcl7/i/83P1RJrK8njhkW3AG9+/puXj9XclyQPX3++CpABSWHnNJrTE8PQ9S3AzRoQlmteQ6ZYzA2BocPHIDSpXM2I+enHH/HxHh3AcbT6QXqWCM9xwp5jQUB5Me7du4N2TgYQmdgDuqbo6CKEQCUEi7F2TxwW/wFsuSDBxmOafxDP307H2TAhHB0d+DWrytW++H0wfjkpn3zky6yxYguQHCNf3bLSzYCbm1KZJldqg5nfA4mR15GUFA9nSxWPhUCAUX3d0d5GnsS+ZksojoUqJwGdu/bAuvksNyORy8nuWw6MG6WsMeHRYQD+WQKY5JzA/uXAnJljcN8wsINupaPCztnn/p2HIFqZfR924p8r6NcvNKgtom/dAYHhQJ9ePWvdz9zeB/nFQHpyDR7m6pRlYrA/4OGplPW1tnVBhRTITa9fHzfObEX3t4E8Q/Wq4ar06NoBt6NygRJ1mfCWQFacht/3hfG/YWWRTavVQbSiYTF9+nQMHToUK1euhJOTEyZPnowTJ9TlIwniUackJ4nXZmCeiPCLtX/hRd69wH8eeRMY5F97KlTyzS04c1ce7lOQp0U2UJKH/w0HuvUajE6uwK2btaxu3Xob70wqgZE+UJyr6QnITI3lFXIPvwn4u8olbFXJys7iidEBQ+bxn6cPyitfycpyselwGMzsfAERS3BQZ+DgYTgfWgFp4l6ERKXA36cy10AgwD/LnTGtt/pXVVZuMXT1jGBibIiCIqU3QkFhcSmMDfUwqF9XnHtP3c0fnlgIqY7co2rv6s8jJ5JignkuxNSPE3DotjJUyNjaBxfCgdjI20hKSYOztQjQY7FSck6GGeOTfyK5R2TXxQIkFyivzdLRD+O7ArplySjKjERMOiA1VKksbNoOV6OAsOtHuEqVicN9TKoWCKGrK39e5nYtq+9PEC1Jt4GPYfiwIUATldRak4RiF7CvtZ5DlcXntKFj4gJbMyA1WaXIZy0U5yRh7jogTqz8PrV2kHswxSn1MywuXzgJPyfAzHNkjfs8MXMmjrOQ2UzN4qf3m1tH1kBSDlx8H9BP+rfFz080k2HB5GXnzJnDE7eZzOzRo0fx2muv0f0lCBWyM+SKTNdigH07N9V6b6LCbsHOjNWfEEK/PLnWfQ9s+RrOVuBxrXm5OVoNC6YG5N+xM9b8zx3PDWEV5zSRpgUiM+hH9OrTD5FfCzCmq6ZBk5Eaz1e+o9KBmGhNhams7FxYmelB6DAUwzoKEBUi97xcP7YOsRkyTJ2pvajawPH/Q1YBEHbkfQQnAh06KF314lIrJCaq3AOZDLkFZbCyMOOGRWGxpqxhQWEpjI0MIBVZIyGTGXWJlRcpgTi3HDY28iRqkZk7v8/JiVGQlYhxI1YGkZEyhELXzAMOFkBSXCSSUnPgwt6okF5kgl1XSiDLC0NSNivQpRLOZOSKV/8GAi9cQtC1Kxj8Ict1UDEsRKb46rA+XtpQio5vaErNNjdrFvti+QRAYKQsSEYQDx2d3gNGymWcH1Tc+/4PcaGX4NaLFfGpBQN7riCVnla/MKbMtFieuyETKb/HrB29sPkFwNG8HvKwMhku3whH3wAHrQtECoxcB3PVqKIETa/3/Sbk0nYM9NOF0GUSXv3uGiRiTXVC4gEwLLy8vPD1119DVqmlbGVlBQODtqEhHR4ejilTpvBYazMzMwwYMACnTqlIW7JQk/h4TJo0CcbGxny/l156ieRyiWbHxrAU51cBC4cCh0/fqHXfMf652Py6I745ZoZXvpZ7L7RSnIa9x29g4kB3rJoG9PdnmXzqSIqy8MkeIDVHBu8OvWEpi65KVq6iogwH1z6FQR8CRZ1+RJ7URqt7XZyRzD0RH+8Gdh7XTI57d6YZvlnkzBMxv3mpN94ek8pDtXZs/ZvnE7j0mKP1Mpz9BiHAwwgxUaH4dynw5JNKA+SbfQVYtSlNqdUuyUFWgQxWVpYwNjJCQXG5ho47MzaY0VGua40+7wG3b8m9NLKSDIjzARubSr18Ixce3pSclICc1DDujXF0VslBMHaDixWQmBiPz2aWYf5kdTlYJ2d3pOUCGeFHUSoBnN1UwoyMnHErHggOiUByQgw3UBSKUQo8XW1xJwGwNgV0zJUJ7feD8WOG47WptmrKOQRBtEEEAojs+9Qt5iDUxciuJnA0La7aJC1IwPKp1ki8ukFj9+xKEQwre+UCiK6JE4Z2AEx06i60V5F9D1cjS9Gnd+/ad7TohKd+0sEPv7PCPS1Ibiie7ByDLWuehlnn/2HnVeD09k9bdgxE8xgWpaWlXHKWqUONHTsWAQEBGDFihLKwVCvCZHDLy8tx8uRJBAUFoWvXrpg4cSJSU+UWfkVFBd+nsLAQ58+fx5YtW7Bjxw4sW7astYdOPGSIpFnwsgMmDu+Ce3HFSAxT1n5RQ1oOs/IIdAjoBj1jK4TG1VwVVRr1J3p6yjDtqaUY080I3naaNS/yslLx41Egp0iIdGk79Hhbhrg7R9X2qbj7Ob7YGo/pEwbDyLE7Pt2ng3d+08ztsDMqxpSeOrAy1eXeieroS7NhbiWftOs4DUN8Sg7SQo/CUTcac8d7KxOftXDk9+cxrgu4a9/SS5mLYGVpicz8CqC80hgqTUcPT8Df1wNThrbDF0/yAhpqff29RIZXZvpBz9QJZoaAOE3usSjLT0EvL8DZuTJPwsAOa57RwVODTZAaL082dHBRMQ5E5ujgKoKsKAnuVqVwUjUcADi6+qC8AggJOsHVq5w95TUs5DfAAE7W+khOTUNiUhKcLAVc4lYVT3f5OLydTO5/6EbXz4EJwVXJ5QRBPPgsn+WDqd2V4aBntqzE5tNZiLguV9lTJSsjmXsSTK1UKpzr2+GNzcC+43UXTy1PPY8Vk4D+I2qurcERitDR1xlBd2PlctsNpbwYkSc+RuqthqmLhp76FnfiAaHXbJj7jMfobsbYvmtf48bQDEhyonBmw/x6J8Y/0oZF9eTsXbt2ISoqCqGhoTx5+5VXXkFubi5mzZoFb+/Wi+cVi8WIjIzEihUr0LlzZ7Rr1w6fffYZioqKcO/ePb4PC9sKDg7GP//8g27dunHJ3DVr1mD9+vXIy6s9wZYgGsKR00GY9BUQMHQRD1u6e76GL82CaDz5fRn23dSHq4sz4tOZ3Kn6xJkjk0EY8wdWPWWDTiNfxIZzImw5GqnZXZ48gc7E3AY2XgNQWArcuqxiWBTEYscfHyA5T4QXV8tDtOxsbZCaWaRRnG+Qbxnen+0KK3MjZOZoFqab8nEK/j5dOVa7obxY1T8/LseLI4sx6XHt3goFFQ7j8e5/wPBP9QBDZbiOtY0tVy1RVN8WlIrx/uPAqCG94Oxkj85s8U1hdPCOyqAnlMDA2JxP5FnNiox0eb6IviyXF4rz9fOT7ysQor23M2z1MiAtSkNfH8DKUcV4EAjwycJ2WNAnBUM+BOJy1N3/Th4duNqSjSwEMd8CZvbqXgd5Ab5sJKdmwMmWVeVT/8r18pGPw9ujBcKTmOFST617giAeDGJzzHHyapLca1tRij//2Y7J3YFhHTUXEEoKs7gHVk0xS9cYEelChEfXHnLL0C+JxLwhgI1XzRK4Crp374mbseXcy1FvyguBkK/x0RxbDJ7+Dla9saD+x8qk+O6XTfj2uBH/28O+a2dMm4Qj1wuRF3UQrcGutYvx5GsbMGukOxIursWjQqMMCz8/P7z77rt8lV8VFkrEiuSxPAvmwTh37hw3OFoLa2tr+Pv7Y+PGjXyszHPxyy+/wN7eHj169OD7XLx4kXtYWNK5gjFjxnAvDPNwEERzkZKahtwiQOA+E2ffE2Csr3aPXkXWHVyMAAytvODq5oWcIiA/TUt9ioxz+HxzOO5WjOeFjW7GC3EpWFMVqjBPXlna1NIeQuvufCJ+++Y15fluvIXvD5dj4bw5sHWQexQcHBwrK7qqy/VduBmP28mmsLIwRlZONWOnvBhJWVLoG1UmN9sOwNAOAqz5N5gnKcNlcq33J1fUEX+c1UFspnpSuLWtA8+/UBgW5QUp2HMNyCkzRlB4AWb9wJaGVIyc8gIMXA3sOp/Bw36YB0ScIT82Ky2GJ2PL9JSF6vbfNsKzXwSjo4sAO19lOQjOaucv0XXG6WAZIlIBC3v1hRJjGx9uUHgYxnFllSrFqErcXewhKS3E+IBiPDGS6daq06vvEPTxAfr36lTrvSEIgtDG+TDgnW0SoCwbcRfX4fjtUnT3BG7cVRb+VDCmuwkurpZLwlYhEMDG3BDiLC35edXYc+gsfjutAxjXLVndY8B4rkYYcW1vvR5c+t3dOLraGbixDCM7G+KZ4Ta4F1vIr6s+5MccxeGgAkx/bHyVXPiwGW/B1wGICvwVrUFHixi8N90QZeUyDJ/6Aq78MqLq79jDTKN84seOHcOrr76K33//HR9//DHmzasjwaiVEAgEfKwsx8LU1BRCoZAbFYcPH4aFhTx5iYVEsW2qWFpaQk9PrypcShvM8GAvBQrvhkQi4S/i/qK4xw/Svc7MzIKlqQgSHQsIrXvizpVjcPZPh6k50zBVkhR+gcf6e/j3g3l5OIb6A3npYTCwC1DbL/3Ct7zC6dCF4/h9MDYyREpGtsY9yc2Reyz0jC0h0bVGZy8T3AyOku+XfQOihH/xy5v94fL4mqpjre1deA0GCavvoFu5yi2rwM8Hs+DjY4OZg90xxPu22rlkhSncs2BuaVW5XR8De/njx6PBSCuxgcS4A3tgNd4fMwsrLhHZvnNntX47dPTHq+PYYlYyZBYSZKbG4PkNwOEJMhRIdHAuDCgrzoLAoDJuuCSbGyJCPSNIBMaYPUgIW08R7/Pi5Wt47Vfg3iIryCrPIdWzwuWwUISF3IQsGfAW2aqNMzBCFy/8CS5ba2TtpX5/RfbstuD9nUBqrgB/zLJUO3bxkwOh05vlohRC6h6g8WyM3Ydh5zveqOjxvwfqd7k1eRA/+0TzQc9fHRt7R57nVZYXB4PEjXhnqi6C0wxwa18Uvl2g/hkpzEyFqNwAejKR2veUtaUpMrLy6/xMHbsYDqHQFJIK5h2pfV8b35F4eSwgKrxTr8/qtt9WYdvhXIzY9T16TJuL8u1vYtOpn5GfcAkGbiPrfP77N33BawUNnrZc2Wbuh8Nf9IQg/xQkxbmArmYO4n2jLAsdLaLgP2cm5nX+Clu/mIqOopOQHR+K8jG38KDRkO/bRhkW/fv3x+XLl7kn4O2338b333+Pb775hkvOtgTvv/8+Vq9mZnfNXL16lXsllixZAjs7O+49MTQ0xG+//cZzLFi7o6NjlQFSHZaIrm27gk8//VTrGFholZFRC/7yPuIww7E1EcrKYC6NRrawfZ2JdmnpYpgaiXDw4EF4F7ljxpqreCZtOToNUJcULA06zuP1g+NLYIcCbF4K3Ii6gGvxyhh8HVkJkg/shb2VAVLyDXifQqFcDYn9X5X2OukI+gg4e+EmSoQJCPB1REFhFA4d2IukE8sw2htId5uByNNKJRV96OC1ccDVM7uRYSCXatWT5UCcJ0M7oQ7MjHTg71WEvQf2QiaQf43oFYfzBOaCopKqMfi6+uHb2cHwDeiJg4cO1Xk/V3/wIf/8qF6DbXkhV7W6ee0k4m7pQhQrT2aPTshEWUYWjwA4ffwgio3lrnxTaTwP98rNzcfBQ4cxvpc5CgWZvM+wOzd48vnZKyHIFyo8LrrIKwa+XH8MOlJgvM9VtZAlPal89YuFPJ29FoMCocr9lUmx7VcBTt2T4clBhvx8qniW5MM6C1h7HBg+KgsFYm0u+TVAUAmA1nHXP6i09mefaF3o+cspLSznMuY3D32J3rrXMX7MCCTtuoewmHSNvwVn/wyCOEeGaebq2y1MRcjLLsbBAwdq/DsmkJUjKjEX/bu6afSrFZkMyyfpIaMssl77x8QlwsNeD/vD3YDwkzDTsULgKiAqaBfi7pbV+vzZ3+F9R85iTA8zHL/KFoSV53Mv7YrYS9egl/M6JPYT0FLoZ53Gnk3A088YIjPrOsx7vYM7CR8i7sh1mJRvR7ngwZonshSC+tKkLD4mMTtjxgw+yWYJ0KNHj8aXX34JH5/7W4CJVfZm+Ru1wSrcsoTt/fv3Izs7mytCMdauXct/If/66y+ee+Hg4MCNJFXY/sw6q+7JUIXV7FCV1GUeC1dXV34PFOci7h/s+bDnOGrUKF71vbUQRP8GnWsrkNX+G5h1eaHWfRP2VcDR3h7jx4+HQGyO4R23Iz76Ht78+He1/QJDXsPYHiYYN3kmkHMTQb9+AoOOFfy4qvOKL2L6RxWYPGYw/+wxEs/Y43ZYMsaPHcWT5xToXN3FYx5txjzGJQKFrhfwmO8XOJV7Ah9vioPLiiEYO0l97IJ0Y4w1/g0VnZwgbVd53pzbeDcf8G3vh2yZLt79FVi3tw+vjs3IjZDy5Ou+fQfArl/lMdmO8BNdQMWAVfC0kocfNpSSFCu8/+pqLFhsgI5Dx+PShj/59hHjZiKRL/zsQcf2nrDrLD+nJCUQkgqWR+GPHuPHI+gHS9yJzsTcb8Yj6vQXPOdiEEs+rMzjyLBgIY9ncTc2H2N7mGH8hIlq5y8OYSFr+3lRwMFjn2IyKmrt5/9in/dcuLs6qj0jRuz5CPRaLK9ZMmN+Vwwep95OPLiffaJ1oOevTtrNdODj7Th6aDc2ZADfb/4EnjdfwdkbqRg/apCaLOzhdRWwsTTT+J6aZLsTwtiNkIweXKOMLJPUfiMdWNy1u8bxNXF4tSmgn4fxK+ref9+PpXCyt1L2XdIdon0fo9xVio49x9f6/AWJuzB8fgXyfV6GteJvj2LcJb3w0qrfMLX0HJZ++xMaTHESBMWpkDXw79fhtX/h2F3g6zHPQ9dGXkzwxG/b8Na26wh5zw8CC/UIhLZOQ3KOmywPwlb22WQ6Pz+fey4OHTqEF154gXsVWPjR/YBJwrJXfS0sFgKlCnsvlcpVAlhOCAvnSklJqfJgMK+Dvr5+VR6GNlg7e1WH/aLTH7uWo9Xvd0kS/jwL/Pbhcuw9MQZWzv7a95NWYOnwIsC1Gxs0YD8AY7sZYtmmYP4ZYqF3iv2GeiRh6Iph8v3MvHm4k2fMRax+THmd5Tm3kZEHjBw5tur6lzzRCy/0vAHIigCR8vPx3/FQ/L0H2PukhXwl3roH/j4HvLnlZyweqYNJS/6Un0sVMw98fRCYYHQP7TvI22SSTC7VaufginJBAQ7fYqq16TA2k+dl2JhI8fv/ADDlJEV/dr2BaSlN+qIRWLjh15PA6PHxcBWJkJ2dAXMjwMDCBVZW9nzCLysvqroPkvJCnrzo6ODEt4Wl6eOv43FYxI/N5oaFyMSxyviyd+0gzzuJBxztrDR+n0T2/rA0Bl4YZwyRoXrYGsPZgcUr58LF2VnjWBevLlX/d/XqRN8ND9Nnn2hV6PnLcXDtgE1LgHf+K8aoPi4Q2fWGg6Mz0vMAUbkYMLKqumfZeUVwdbLV+NyU6tggOR3wrMhW21+VnNQ7PETX1797vT93p0OFKChMxYS69pdJkZZZhE5+nsq+dV3w5jZDGJsdwXsbRbU+/9K0QF7U1bjrM5p/y0RO6NHeCtHxqQ3/vmBqUoFTkRJzBzZP3ILIWkX1rw6usagZLxEMHXpVecBdPdpz71JhRgQsbbvhQaIh965Rydvr1q3DggULuNISK47HlJQCAwO5QcE8Ajdv3uQFrq5dUyaItgbMaGD5Es8++yxu3brFa1q8/vrriImJqVrlZUYRG+vs2bNx48YNXjF8+fLlWLRoEXkeiDo5cuYm/g4EDEUVeHbmCBQXa1FvYpRlIShGhrQCY/l7oQjDhg+DpKwEp4+pyAIWRCMwpBQpZe7y93qWcLUVISEpTa073fy7CHwfGDjmKeVGkTkPRWJ1HlTJys5DsURHGd5j2Q3/BAImBsDK5UsBEy2JeIbO2BQI3LqjkjRekootS5naRy9Y2crFDrLSlUXyUhKjcexOtcTAZkDX2JEbElli+T3o7SnD2oUGLIkC9o4uuPQB4GJTaZix/Gm9cqxbALi7y++hra0txHkVXC1qen8TPDfaRN2jY+rKK4kz48HRsbK+hSpGrnh7Crh6lDYcHR34z04dNY1KQ2ul99bKSb0GBkEQRFPRNXWDqSEQkwHMfW4539anVzf8v737AG+q7OIA/s9q2qZJmtW9aClllVlA9pAlQ1FUEEVRceNE/cS9cALuvRVQEURlyBBl7z1aaGkpdI+kI90r3/O+6UjaJG0p3ef3PNA2uTe5yW1v7rnve875aj67xmRR6amiFFnGMqgq80stHbtQiuGvsBoY9itDuQuTcX4ZENa3phR4fVgTU0OOnc9ES0UZeGu2CTMnWZxsCwRQqL1xKjql3nKxH3z7N+Z8KgLcbFchlctcYWSZ5I10ae/H2L7nOKa8U44f33Fc1dBKWSEOnk7CkH4hVtNqfYPMoxRJF06jI7uswIJd4WfDIuyEffv27by07MGDB/mIxV133cVPzh944AHMmzcPrYmNarBE7by8PIwbNw4RERG8V8Wff/6Jvn3NVxJFIhE2bNjAG/qx5nk333wzZsyYgSVLlrTqtpNWlJ8A5F9s0KKpaRn8Ks7yVyciPS0F999u7ptSR3EGHvwO+PdETfUiefBU3gxuRIhFqdTcSDzyI7DzXOXPAgH8vNRISLUOFuKjDkBforKqYPTvMT16PMWCGOtl8/Lz4eZac+INeQjWPuWGyPcUkPR7wfYLE7vASyWx6ugqKErDVaGAu1cI1Drz8xrSKztaswprB4/j6Z9ZMGT7itdlEzlBIxdBbzDneni6ZmNQ98rnkMh5Z+0Co7nyFZOtT8VfR4BSk7lJp1bnyXMoSozJ6OtbiCGsa6wlVz/EZwAPjAcG97Mx4uTqhzkjhAjr1s3m5vUL74HHJgOhPWtGJ6q51FSbE7hVBouEEHKluHhhxjJALBYiaOj9/CatTyhGdmfHbIsCNMV6XB8BDOpTtzqdtrJhniEtzu7T5KacQlkFIHS3MypvA+tBZDCW8Ys6DhUmoZcf4BdkfYxlF30jE8thyqvbrNVS1PlEBPnpqqtB1aaQy2AsqGcbaisvxpuvP4/3Notx74zuWLbiKHLjGpbXVZa2FzkFJgwZOtrqdqV3Dz6yknypbln4juSy+1j89ttvvIkcOxm3NSWIjWhERdVtsNXSWDCxefNm6PV6Hgyx8rLXXHON1TKssR/LxWBTp9hyH330kc3XRDqH9xeOwIIbu6Oi0FxNyZHc3GwoZWJ4TvoOKx91g/7CPuhTa67iVyvK4JWK1FqLfgV+MzC0uzOcY95EabF52l5B6jGkZAMhPa+qXizAzwcJ6YU13aVNFXjxm9NYukVhlWgnV2pRVMo6bVuXnM3PL7AOLARCuI5dAfGYtQ5HFzw0bkhNr3kPTp06hZnvA+USHWQqH6jdgPycmpEUgyGT33alRywYjbsLDAZz2cGvNyTgg78r+2uI3TDmdWDPwZpa6bFx8bj/W6BcaE6O03mYp2plJsfghe8vYPf5Wn/bzt54Zz0Ql86mFdjIDxM5A8N/BfoutrltYb364+nprMSTjZEfkRTv3aXETwuc+YgSIYRcUUIJflp6N/79/UN+vGHKJR68DPfpk0drlivW4/7xQET/uoGB1qsL/2rzs6vShz/twB1fSHgJ74ZSa7TmUuEldcugWzIkn+M9npJzrROae/QZiqx8ID1ml/2Vi/U4l1iI7t3s5/bOndoDS+dU8FGbhjq54UX8ud+I55+8D3c9twoyKfDxa/NrPocdEGftw96XgWETb7W6XSALwB+PA0O71v8Y6Oydt21hic8seZqQ9ubY2VT8vr8I7z9jncRrC6s8pGBHHFcfhExegnWPF8Ez9YM6y5XmpfBKRSptzRVstg56/A8zXo7C8qX38JvizpqnD4b0GVu92JCBvfDlXSaYis1X5StyYnA4tgyDBvSxeg65uzmvIi/bukxygLoMA7vVyg1gPSW8xjl8bV4eKqTrc6sPpAkJl3AmERDJfCCQanD6bWBY75ogggXlalkzjFiwTtrPhOPhCeU8qDp23oiL+sqASiLnU7ry82u6gOfn5fDuslKZeTv8g0Jw8i3AS1mOPw/kQ19YqxqHyAk5xc74ZR9QIa01mlEl4EZAZf1+V+tyOzDwI8Bros27Z103DlePHVVv1TBCCLkcY+/8Gl1H1hTgELn54cQlIP5CTR+xEmMKz9fLyK970VShC4JYBGSmWTc/tnQ+PhXBAdpGHcemjB3Ap5mi2PFFuuSLUThyAZCprS/OhPQZh8l9gcJ0++VZC5IP42Im0L2XOUHa3vkoa0qLkprPCYdKc7H47fcxqb8rBs18F1JdOBbdNwk/bL6E/Ohf6l39/PHNMBQ4QaAdbH2HxA29Q1SQC8wNWzuqBudUdunSxWH5VXtYF+5HHnmk0esR0irKi+AiKsG4XoAx8QBM6bsh8LDfZdTDrRjirpVzVrveg5RDX+K7dz/Bop/egNCppniBId08tUpdOeRcrefTGBT2Hlb9tgp3PvEBYqMjoZKLofKomTaj9emGUewiU2EC4KxB3MktvGlexFU1wQfjpjTnBxiz02EZRswbWQborDtCN8Siu0dBcimOXxFiHZtZkzmtQmTu4CzVIL8IMGWnoKpGkiErBxq5AJBc+apoCo0PTJf28ZEfdgXLl9WMZcRyfiUpz1gzxSzfmM1vE1RWNxG7efOE7fLc8/zqmUZbN4/CxZVFREUQysyjG43Cnidsgf37R65u/GMSQsjlcvGGpxJIT6vJmdCnXcTb64Dp811Re8xB6OqJZ68F/FU2pvEypbmISynCqKGNm87JRrZlivoDC5afx3pQKDxDrW6XaPvg2/uEgKxmym1tRRknMG8U0GOA/XYHe84Y8fbHwF/Tc/hnWX0y9ryCC6klWP7Fi+bPOwDXPfQdBsm7Qhb9EhB6o1WenpWKciz6eD/6hPnihfl1g7hP/nVFSuYJvF7TmqPzBhbff28u8dhYrOwrIa3KZEJ53AqIAq6t/6S3MIUn/sJ3OpCyGRUH7kfm4C3QeVqMNFi4d0wJoK2sHiYQIs9tMD7ZchT3XDwGj9CaJDc3oREf3g74BNQ6wRe74qa7X8RnNz6Jc+sexlW+yfh8Ya0rLzJ/3PcNcJv0b4yc2Q+H9v7LPzT8eloHFmw05LbhrAeFRb3pinIcicmDGiKYB7sbTqELBtjgR2EiPxhnZBqgdTfnLbBRiXlfAIMG78LTQ8033Xm1AmW57s1yZf6DP1JxcD+wYnwk9EYgTF65HyVu5sAizyKwyDPy29h9nFSHSW8BN0xdjQqTuZN3be8uGIS5gzZVl6C9oiyS9wghpNmJXeGhFCMtrabLc1aGeTRC7VHr4hYj1fFpUtDazkMoM0TyUYGQ0MYVoEjJEWHyImDDqnPw87T+vLKUlpIIL/bRYZEzWPU6IrMCkHx+H8aPtL2uGnFYfDMbhR9i9/HZtNhj8YCpJBv1fjoVpkKX/gX2LesO0Tg23GImlHnDb8QziNr0IpxcFiNk/Ms2Vy/NOIIjcWWYf3vNdGZLJQIlTsYmmxPSO+hnQ4MDi9GjrZNQCGkvytL2ICBiLj59bipmPLne4bKmgiTEpgKBvUdCouqPL95/FctfHIaN20/wCmhWyktwKi4PGqkrqsIO70Bz1YeU+BNWgYVMlIMb2XFPXfeg3n3cEwgPeR2/rfoFz18PeEYMt17ANQDn04CoyJMYORMYGpSLd+aIIFBaH+TdVD54hxWJUlpU0CjLw+t/ACOGZmIhO/g2wt6zRZj/FHBmVCIEqn5wghHdAiunOTmpeD6FIasmUby7ZyEbc0ZzcJGpeHdZZJ/myW8qVeV2iFxx9xiga9ea5oEjwt3x0R3m0QxOqoNQAESfj+Pds7We/nUeX+U/EKMLdrFW2M2y/YQQ0pJC/RUQltdccDFkpvDjoEJb9/jHcjNWH3GF/FIUJtX6+GFKDFF4aALLebB9smyPm8qXl0U3pCfA0ViwsCwbfQJF/HOltu2xKvy++RjGLyqw2Tn776274Fwqx1gHF4XkSg3KK4CCnDTI6kkBPLXxVUTuysesp98AhLVOkXs8gVcfWAyfvR9jqZ3A4tSe33iu4+AxN9i838fXF0mGSKAorXkuZLUBHTNcIsRCSqw5b2H9pn/qrU6RkxaLUa8B0exKfa9FuG1iMAqyL2H18s/rLlxi4FWQ/thrTipm5J7d+Zz/1ItnrTvBHzuLZ39lJ7k2hmEFAjz17GKMCAMe+QG8qY4VWQD81cCli+bpVEHOMZgwohfPDbDipMSv+4D4+Es1t5XmglXZk8msm7o1hFIXyKdc5aTF8Pft4asL8M7Dw8x3CsVQK6QwZNV8cD3+xUVsi7RdlaOp2CiDniUB5pzBH08Aw4dUVmASCDB7pBwRXWuGpb0U5RjGiotUNbJz1vGpUAqRAbHvsURFG6OovZ8Hpp0FnOqWYiSEkPZm8b198L+pNcnKrFy3uwwQutgoqQ3gv7MSbDloe8qRa2k8L1DhEVwrZ6AebuoASESAIcNxTsGcYSZ8/nCgzdHunr36ISYVKM08WXdFkwnfb4jBnotqhyPlCnfz5C9jlnXZdlt+/3M9fjskNs9aqE0sw9hh4TgUpQdKaj73LR3Y8y+6eQOqrpNs3u/rH8IvkpVmO6501Z5RYEGaVWlRzYlna0m6EMm/fnp7MZDseMQiPSmGf9X5duPVgOSjP0eopwkZUWvrLlxiACvRrVBaXGVx6wIvJZCcaF1O7mxsEnacE9mdlzn+hgcxetpd2HgCKHOpNWnJ1Q/+GiAhKQVZqXG4+a0EpFXYKH0qccdb64BjkRaVPUpzedK4m7zxFYk8A8zNgFITooHidF6SNbes5rWqlTIYcvLNP5hM+PdkAYwlNSMHVxIrb8vyI8oMp3AxA8ivqAmU1p+QYN2ummDql83n8OZfwprAy0kFrUKAhLR83pxI4KyzXfnJ9TLyKwghpA0qFHogPjmb91Rgxvdzw3rW5sLJ9iV7rVqBzCyL0ucWduzYxS9aQW6/8pIt7FjLR7YrexDZcz4uAVlltgOeHv1Ho7QciD25re6dBYk4l1SKsG7dHT6+u8YLvf2AsiLrUux1lOZh19FEjIjoVne0ohLLbWQzCLLO2yg9yxpGh1zCa/NC+IU+WwKCe6B/EJCXGY2OigIL0mwOrV+KQG8F9OevfHWwnJOfQ3pigTmxuB6SsjTeiTk7H9j889sOl01PiefDxRqfylwIr/FQuYmQpbdxYCzWI6cAUKosRiFc/fH74wLcNsr6BJuVSlUrKvMT7Pj4QC8UQIOQfrWudIicEeovhwQFOLzzdxyKYzOqBtV9ALGMj5bk5ubUGbGQKxp/JV7t24tXCmHvCZt3OvczYO3emvd7WLgOU/ubRyhMpUZzOV1N/YlxlyMwuAem9AMSYk9h6MtAkqFmutf2SBP+PmjuccFExRtwLtXiQ0EgxOAwOY7GA5PZ7rcVWBBCSAey5XgxprF2XJW9LFwF2QjylPLPCVu0ahX0OUU2m9Ft3HkG/5yV2V3XLqkGV/cClFIHzenKi3H/51n4bb/txHGPriN589KokyyysWa4sJd3GO/Rx8bnoQWNpz+2LGKNVB2PqOvPrUdkkgkjx062u0z48JmQSoDDO/+se2deLELcMzFynHVLA0sBoQOw7klAJa7pvdTRUGDRGZTm8qTkllYSY074jz9t40pDE/2y/Fvc9V4i9nw/t95lB/rn4fP7FTiYNRD3LzmIrGTraUqWMlIToZGby/VxAgHuucYDs4fXmnbETqaL9bzxmlJtkVcglEDrFQBJscV0JJY4l2OEmrWPdoAniAudbBY8uH1KGL6+T4rD+7ejXyAg8bBRWk8ggNxVgjyjxVWn0ly8OwcY1L/xXZ+FUnfMHCKBTGDg80EzjYDWoya5bviAINw5sph/b8y8yOewqjW2rzo1VXD3fvjsLsBYWf1JKq9JpneTOSO/0LwdTF5+oXXfDgC3jA/ALUPBp0Q1pg47IYS0Rx7e/vxiT2muOWn73eWn8Nxqid0pQ1qtDpm57IJZrRNekwmxCXoEB9gpxe2ISIold8hxdbiDdN7CFKTmAF7etRK3KwncgrD6CVdM6M42ztrZEzv4hcCuFuXZbZIoean07EzrUuy1Hd7+G78413f0bfYfSjcQvz0mxVW+dUvzRu7+CTe+DxQpHOSiyAJwOgFIim/9Pm/NhQKLjk5/GHFfheDrhT14haAWYziK4Z6nwaqCJsZf+SE/hcR88rzg7X+QfOQHh8seOn4WUXovTJ79JD+x/OnjZ+wu292zGAuns2ZmNVNtInoHoL9v3SldrIHestuA7t2tT9o/+9cJcxZbJEqYKlBYWAC1qqb8rC2zZ8/G2bNn4eRUN4gpk/ohOi4Rew4cRwSbKeVuo8szG6l2dUKuZWBRlotJfQAf/8tLSn7vga4Y6JeLUmMiH52p6tDKpOS64P11+TCVFSEvK5lXqlLrmicZzSTV4c/DQFQS+JxdsUtNcCBzdUGeRVfV/IJiyFiGt4X0QiV+3FUVWDTPqAohhLQVnr4h/GtGkvlC2sWUHBSW2x81nzFpELawj8bimkpSXGEyYlPLERJifrzGikpX4ORZ6wttlkpy4nkA5OVjp4KoQIgevfvCrTiyTnO6qwJzceg1wNnTfg8LTqLErI+AnQfN06LtmRR8Hvve0kKs6Wd/IaEYEUOGQV5wBKiwHmXZsmE1sgoEcA6aan99Fx889TOwdvMhdFQUWHRgxed/w9LHhuJSciZe/iUHuQkHWuy5d//2PD7eAp4bkJZiv+nO5Zo7rBRRH2oxOFSCpG1PAiV25k5WlGPp6hSsOSSEOHAG7hrniu9+3YzSEttJ3D08c3H7ZOsD3M5zYry0PLXOELGoPBs3DQE8Kg/gVWRKT1xML63ZppJsvD3bhGVPjK0/YFLYLodbIPTCmNdMvEnRVb00dqfzvD4vAPNG1wz35mWlYf5XQFKG46R1e06kKHH4VDz0qXH8Z51vzRzbzEJn3rHaqL8EH7UQx94AfPyap7y0wEmFJ1YA/0UCajnLVam5AiaTyZBXWHOAdxaXwUNtPTp0Lk3Kk7/5uo0dzieEkHbGw8+ch5dWme9nyCmA2t3+xS0XpS8U7LBZZB1Y5Kce58nGIWF2GoTW48dd5fj4D/vnAGkJUVaBkC3/ntdg8qv66mld1XJOw9vXv/6iG05KKFyA3BwHORZF6chOOglN1/H1lkw/aeiKYS8U8NKy1coK8M/esxg/pIvj7RGK4atzRXJq/Ynk7RUFFh21b8Ppd/Hg/Juxci/QZfgCSMTAgf9YWaIWUJSJb3/ejDOZnvjzGXfcO8FxbkGjmSoQHZeElBI/fPn5xxjkl4m8PY/ZXrYwGYkGE3x9/Xiuwq1zbkVhYRGO/Lfc5uK//hOPv09Zjxik5Tlj3VFTnSHihIsXeBWngjLrfApvv2CkZAMmo/lkHMUZPM/B5HT5U3AUHqH8wLjklnJcPcp+ZY7QLl7wlufXHHezMrDxOFCKy0uq/mVXPr7YUgTn4ot4fgbgVZnQzag15qFxQ1o88gxJ5nKw0npq+V0ugQAahYSPODx8rfX7OHdKGH5+yFRd8ev928VYOMs6uV3rYd7WfqyZIXXAJoR0cG6aYDx3HeAhK+RX1rOMpVCr7Z/wJueI0P1JIPGC9RQdWXkCot4F+kRcXssBtbsSBlblxN52CrLw6o2Ad1Av+4/h2xsnLwE5Fy3yLCrKMPPlU/h6dwMKk4gVkLP8Q2Pd6VRVEo+vZv1qEVdcfwDl13M8L2ZyZt/v1bdlRP6BY/EVmDD52nrX9/FQIymtnkTydowCiw7IFPc9Fj3zNPbGOuHn1ZsQOPZFDAoG9uz6r3EPVFaAUytvwkcP+JnzNBpIf+QD/HO6ArNuuxdieQAKDBZVihwpL27YdK1iPR74pgx/HCyBKWgeitRjMXb+D/jj27p1pU15cUjKAvwCzVdDFH3v40OnV6ktrjRUKSvA2v0FOBpvfbVCpfHk3Z5NhdZXS5KSkrD6IJs1Zd27gTXBY3Wsc1Iqh12LMjDxLeDnbfa7h9ZLFgA222c7O+arbE+DYr7enIUXV2ZVDxnn5ZqTrd3cLy/3wdPLm89/dS87hQcnCOBq0YdDXZlvYUi/hA1bd2H6EvsVR64EtdIZPipg3lTr7qxypZpXHmE9O9jrTtPnorDCOpDS6Mzb2j+seXJACCGkTXHxxkMTAV9FHq9gyEqghgTabvTKKLWBPGcwM8162lJ5VhRYeqBEY//E3xG1WgVDXgX/fLVF5ZSN+WPZoIL96bph/a7m14Oijtecw5iMMYhMqoB37aaztghFULiKYMy1XfWK2f3PGn7hqsugWfU+nDp0AoI9gEP7arYnM+ovjAwD+o+/t971fX08kZhRBJQ7SGpvxyiw6IB2bF6FX/cDP/38J7r1v5pPmxnWW4vDJ61LoDqUE4ULP/THLf9bjTd/SUJG1LqGrVdRhj9+/hQahRgjb1iE5XuFmPjipfoDhvJifPKgD3Z/bbupjJXCJKRmA3J3Db/67DziW0zsK8HK796vs6g+4TSKSwG/LpUHRdUAuOp6IWr3TyjMq1WHujAFGUbAw8M6UFBpffljFGZZH3Bzs/W8w7PE1foKum9IP17BqDgr1nxDcQafQ6qqvMJ/WVz9+RWX3efs51cwWQViRCZWnmTzwML8GuWqy3tuL29/PhJx6GgkPtomsyqX66LwhrOEBRZJ0Gekm0/upZWN65qBxl2G73YCG45Zz2vddSobV73IXrMRqCjG9csqsGa39eiSujI35Gyade4FIYR0SBIFfjkgweadp/jFuA9uByaN7m93cVdVAD+eZ6ZZXwB7//stmPuZkDdqvRxqjY5//qE40+b923YewaescquL/aDHxTsCoV7Axr/WABXm3hwp0btgLAS6N7Bp3z2T3DG+r/3j/669hzG8lxwCeXD9D+akwqAeahw+Xjm6YzKhh3QPfnk2FCJVj3pXnzBqAJ5hbTIKmnCxsQ2jwKID6uGRhx8WuCJieE3Z0vlzJuH3hwsbVh0q7gdgUwS+WR+Dfr1C+NWK43sbGFgkrUNymgGzrxsDkZMLfHwCkKg3oaLA8fMWxP2JxasM+GL533USomoryY7njdsU7pUBgFsQ+vUfiJiEHKCsZhoQvwupWPkQ0KVH5fQhgQDFvrNx9atGRO5Zaf3AhclIzwE8vKz7Gag9A3nH5ly9uUFdlZycLH4VhF0NseTu2wdf3wN4upgPpKV5qfxKkNqjCX0SZAHY/wrw73OORyzkcjmM7CJIZX5HcWEun0LlJLu8hGUP32BzYBEHrD9e606pmm/PiH6eMBj0UMuad8Ri0bwI/lr2RFkPqwvFMlzSs5iCdR3KQwHr2+FmPZdYLPPmH6xjh9jo/0EIIR2NQIDt51ywdf9FlOWnYmcUkF9uP8dC4OLJKyLqM6xH5mPjk6HVuNf5nGuooYN6Yemt9gOLfcfjsCtGwipy2H8QJ3e8+NhsqEUpEEa+zm86e3IvnMRAUK8xDdqOiYM9MTDI9rmFyXgBe87kYuTQCDTU+FGD4CvP48EBy7X4dmMichUTGrRucLc+mBDOTnyufP5pW0CBRQfk6ZSMMYO7Ws0ldwsYw8uy5cb943jltB0o3T2PR+SvfPofvv79BA6/6YYJIUkNe/Loj/DCTAmeXvwj/9G/SzeUlAEZl2x0zbSw/Y+P+dWSL+8qBfSOk8zTEs1VLmSqmgpE3XoO5CfAOZf2Wy3rXJaEMT0BZ03NcKmr7zDoFED8OevpUGXGRBjyAZ239ZBsUGhv3rHZS15T0pTJN+bAXV63ghO78rIrWoRzkebKUNkZ5oOHSnd5V3zML8QTcpkErq4ugNz+yTHrV8EDi1JzL4thPVxwdgkgkDiuSGXPgMEjeWCWkQtoVbW6dztpEKQDnGGEISu72UcsevcMg9IF0KitgySZ3DxvuCA3k4/U5BUDslqBBRu1Y4n2crX9q2KEENKReOqUSNcboU+9iNkfAyk5DoIDJzWu6QtoXC2m55QXIy4pFyFBl39RzMu3C67ubT+wSEnPgpfWdtESS+Pu/gGPzRkA05m34Jx3FEok4a4xAojU7MHr9/fxCny7yfYFzrKkLbjvamDsNTejoabOmI0X2QSLjL04sOkLvLSGzYO23//CUr5Ah/u/AS7FHENHRIFFR8OqIK2Kx097au1a3XDc8zXwznufOFy9XH8Ct30KfB13M0Teo+HsKoPMbxiSYw7ysqIO5Sdgy9b/cF4wEQJX80m/XxfzH31inIPAotSIv7ftxbg+zjgUCxz719z/wh65IBuLbwZk6poAILTPGDw2GSg3nLJa9reNB/Hcaql1lQZlDwRqgfhY6yQ1UUkqzi0BBg0ZaXW7wMWLd2wuMVoflOaNBra+ZeOgJhDivc3OWLfD/PiiMgPuHM0SnxswF9QegRBw78P3o6MrR56envBVWYxY5GejsEJ22Veb3L17YngYeMClVddKkpOq8cRy4IPvN2N8PxmmD5QAIse9Oppi3b5M7D9vHlq35KYwdwPPz81ERUkOH7FwldX6oJKHmatBqespS0gIIR2Ep4cWaVnFMKSZC4moPRxc3BKK8OptHhhv8ZFWnh2F2DQgOOTyR3pzil0w73MgJSGm7p08Jy4PXroGXJASOQHDV+KZX0VY+fU7GOwRixfv6MaLsjTE6UsmbDhkO8dCot+BB8YD3uEz0WDa4dh2Gji1/y9s3fI3hoSKoQiu1dzWDhd1V/x9AoiLtihL34FQYNHRFCZjZ1QF0vNrldRUhGFgVxfsOeS4jnPs+bPYdQ4YNWZ89W3xJb0Q8VwJLp7YUM9zJ+F/vwC7ztc8t6s2FPeNA+QiBxUQEv/EpN7luHv+g1h5QIovfvzD4dO4S/T8RL3cqSYR19VnMJ6eDqhN1nkkJ84mIjG31smusxeCPJxw6VKt2tqFybw5jkRR6+Dr7InBLwCbth+1urkkP5Nf5bHF20OF5FQ9P3CqpUYeCCk9Lq8OeLVxW4ERqx0uMn70YPz2aM2IxfLNsZjytnlO6mVxUmPOJ0J+ENTpak2nkmp4knpCUjqm9Bdj0mBts1ZcMpaaf69UOuurZyqNB8awaa1l+SgvyuUBZlBArWZLLp7AjdlAkP3GR4QQ0pF4enrzztRZyWf4oVmp86+358SBEzVTfvPO/oKp/YEhYxt+Jb82JzcvbDkFJCfYKOJSmouMnHJ4eVnnNdqlCMMdDyzCjtNFuPa1RMQXNCAfopJc7obcgvLqHI1qJhPe/WId/rnQxW4Zd9sP2BXf7Zbil9UbsPVgEsaP6GMOfhpAKA/ihUiSEi6gI6LAoqPJj0dyNuDrz7qoWRAIMfyqgTh3yYjMVPvz+jLTkvgBKLj7wOrbAvtOhbc7sHPLbw6furwgg09HCutmcQItC8BLM4FuOvvl5hC/EtMGijF0xiJMuXowth3JRHG2/YY623afwEdbxSiFxXQXV3+sPynD2vX/1txWUYbEtFz4edc6WAgEmDMpFDMHWOdj/Lv7GML/B5icayU6S5RQuQlg0FvU9y4rxNPLi/D4F7YrXnl7eyElq4wnbsfExuPnA868C2mTOKl4PW5Hik2uvMNoeaE5eTkvrwBuLjUJ140mECA6TYIXrweeuLtW0x+Jkk9/MmTn4tM/YnEmpXn7Q2i6XcNf//ib/2d9u84bKxcAnu4iSARFPMD09bMxdM96X1CpWUJIJzFtwlDsfRkwpETzaaQiV8cn8GsOlOP9tZU5FiYTlPrf8P693tD0bEBRFTtc3H15jqIh08Y0pMJknqc357oRDX687uOfx4Lrg3A0HojNaXggoFAqebJ37QqXbJbD1//kId+ZJT00gkCAQX1D8fvebF56dsLU2Q1f10nNez8lJyejI6LAooMpz43jFZN8AusOXYYPnsSvyO/dYruHA5OZkQqVDBBbVDoS6K7CqB4C7Npjnb9QW67B/Efirrbovuzsjd3nhNj0n50uk0UZ+OC7TfglqjfgrMXYa27lORm71tmfsrX/xCXsjpFanyQKBDiWqsWv/5yv6c5ZmIQkgwl+frWuXrOOnVcNxqiQHF4to0pGeipcpCIIJLVOkAUCqORSGAwWlYZKDLwTtUJue26oj28A3w/Ii8fBU4n4aLN1x9DmciGlEBPeBLL15oN4Xn4h3Fyb1kfEUyPjzeVY1RArAiHUSlcYsvPw8XoDLhiucL+SWjSsF4XIFUJxrQBNIsf2SCAzPQX6jGS89zeQX1LTQI8QQjojqdKf5y721Sbg3Tn19xnSatTIzC3lPYHyL27D01/GQe9+w2VPpTVvhNZ8AcrywlylivwE/nEtUTYi/1AgQPfJL+ODpydi5MxnG7yaXK7kRVSqRvOrpF84xAOO8Mvo0xExZCTvUbXnJSD4qjsavqJAgAAvJfJyrasXdhQUWHQwOaln4akEfLvUbfIi9hqJF2YAwQr7HR995Pm4dbTcPKe/ekUZRg4Mxu7jiSgvs1+xKVtvDiyUWosEWaEI28/L8cMGc8J1bRUXV+H7nSaUKIfwn+WhMzCqO/Df1vV2nyddnwNPln1dS7du3RGdXAoUVI525MXD1cn2/NDUYj88+iNQkFpT6ig9PQMeKtuVKVRKGbKyLa50lBj4QUrpbrvh0DWTxmMZm3WTfwFZ2TlQsXJGLaCqrKwxJ4N/zS8ohJusaSf8Hlp3vL0O2Hu6JgirEuqvRBedCTn55VCrmy9xm1GpzLkUOTnWHwwQyzH/a+DY6RgkJSbg3fVAuaD5cj0IIaQ9MJYrEbrQfMycynLgxI6LeGh1HvwiEhtp3/jz2/jrKODW886mbYSTGv5qoKQgp+7U66jjCHoUSM9v3PG6XOSOGU+uh5O64XmLk0f3w4k32We39XZkpJjzT7Q+jZ+q3H/EDRCLAL04HAKXxvVIWvbIQLxyfWHNhdAOhAKLDkYtTsfh14GQ3tYJyJxmEOaOEqO3qrIjtA0RAflYdKt1AzKG5Vwsml7Ok7ns8VaWY8NTgIeP9bxHfx9PJKQZba5z7J+v+RzQSbOeNt/g4on3FvTBq1NTbPe+KC9Gqr4Inrq6V1669RrMRwlyL1V258yPx58LgUmTr6mzrMi9G347AFw6u7f6tgx9NnSs3p4NU4YFYFBAQc1BoFjPRyyUrJeGrfcieAD6B7Hg5gIM2Uao3Zt3mlDtwCIvJ5N3KL8quAQThzShzC2r6uFlfkxbOSLTRwTi+WmF/G1Ra5q3+VxISAjPi/HwqPU8Yje4Sc1VuvKN5lwemfLyyusSQkhH4aYNRlk58P4m4OudLvVOBdV6eENvBEz5l/DbXztw7TAdpJ4106Ivi1CM3/+nwtyxdT8D05Jj+SZpfLqjuUlc1TwIMFUWNqliNKTwkvpyba3p4w3g6j8SC2/pCe/BDzV63QpnP2SwqiilHa8DNwUWHUx2WgzS8mTm+fi1iV2RK+2LR9/ZirRU61rVnMmEHUeTsS+2bgKSNnQ8bh8JOOUctPvcrOwoO5mWyKxP/PwD/JGYWYaKkloVGfIvYeP24xjQwweefjXBiLbHdJQVZSE7blvdJylMRmaeuSN0baF9x/GvcWd28a95GedwPhUwudbt6KntMgSuUuBiTOWIRWkeunmUYNRAFg3UdfM1/XDtgLKaYdQSAyb3BcJ72z4g5lZoMWMZEB+1B1l5FVC5119O70qQqcyjRbk5Bp7MfO1A4KaJPZv0mPMXfsh/n7RBdWt8G8sV+OOgOX9GrW1gAl4TiMU2pjhJ5Hxf5uUZkWfM5kP/IqnjXBRCCOnoBC4+fAbDxuPAmeT6c+369umNnx4Akvd/jD3nSnHTzWz+VNMVQo2szLozJVKSLvHS7yI3x0nlV0J8egkC2ehIinX+5vCezoh611z9sdFEUiz44Ax8B9/X6FV3RFVg0AtAhdF2nmZ7RoFFB7NqSxTmfGqew2eLm/9IbDlehD1bV9W9s8yIH3aUYP3hgrr36YZj6yng+dc/tPvc/+6LxK0sNaJWpST/gK6VvSxOWK9w8Rd++w031Crx5nMN5n0BvLfE3AjHSkEStj4D3Hb92LqvzW8wzr4L9PM0z+Xcf+AIxr9pO7AQuAUjUCtAfNy56q7bc0cCd95oY6QHwJkkIX5lAyFFlQfHYj2enApcNcQ8has2Vgr3aLwACTFH8cy1wP/ublgTn6YSOavw2k1AgLqCJ6n9dQQ4FltPmeB6JKQbeUk/W1OdErKkeOE3YNuzgNazaSMjl00i5yMWeUYjCvJyeR4RG8UghJBOTaqBh9J8LqBS1n9MVHl0wagewPlDv6FvABAxzbpQxuV6Y20RnviibgWktNRkeLFrQM7Nf1HKVa7loze5BusAJ8+QhKJSQbM2d7XFNzCMn//oE8+gQVg+aKGdmRxtDAUWHUlFOe967eNhe94/I/QcjgFBwMlDtkYD0pBptFFWlHHxBly8sHxjJIqKbJ+oJianIz5TUKeDZlBoOE9u0khrTYe6tBqvzXHHnY+9a327ZgjGhrvg7/+OwlRr/mFFfiLKKwCxwsYVDrErFJ7dUJxhHoVISrwIX40IQmcbozdCEQJ93JGRVtn4rygF648CiTm253oejyvmw8lVgUV5YSa+2wFkGm3/CYnEYniopLzqA895CWhiqdmGEkpw93gZ/FSlPLD47B9g75msJj0k6+bdpUsXSCR1r3hVjVJIJYDQuZWmH4lkeH4GMGGgEhMGefDpeBRYEEI6PYEAkwaazwfUKvvnBVUqnLS45WNAIyvFhmWTqvtRNZVapYQht6hOPkFXXTGuu0rZtOTwBpK7m0ckcrPN+YdVliw/hvu+l7bINljyqezxlRTfsMAibc/rOLzUBzBWXgxtwyiw6EiKUpBsqICPt4PoXzec109OTbDxy1lkDiy0OttDgkOHj+XJ24f3bLV5f05uLtzd6k6jkii7oIsHIC6x6N5dasSufYdxpmBg3TKsQjGumXg1EtPzEXlst9VdCXFnEPQYkJhlu1702xuluHPJeT4NKDE5DX4e9pPVvnruajw/NQcoKwAKkrFwJXDqonV37SoqrTey8msCC2NWCp5bBaTnVth9fG+dAinZwOyPgL/3tVxZuU//EWPPsQQeWJi7UDdtGtbAgQOxZ88em/epKhP1R71af8WRZiMUYVRvV4R4AK7iYvizzbjMTuOEENKRLJjZDT19WQ5c/cdnoasXWF9XdtFMENyIKkf1UKvUMOSZ+KwIS5N75eO+GZfffK8xnBU6nmNRuxJThj4XmhbKgbQk9+gOVtMl+ZJ17y17tu87jQe+M1fZausosOhI8uKRnMVKnTqYr+jiDW+dHIXGzLr3FaXxihD2prS4BY7hox07t/xi8/6c3Dwo5TYqEMkCePv6z7/7vea2jL14ZY0Jf5+x/Qft3+8GBGiAI/+tsLo9LSmOX/TQ+bOOaHUFdOmOaJY+knUCiak58PO2/0codO+JnAITYIxGYdZFXnLOw05lCJXOn1eBKsszl3HNqRxOVWrtv9e9u/lBJAROXGJVLFruRHfj8XIcPZdpDiyKADd5/VeqLpdUbs6nqTC1YmAB4NudIny34Ty+WnOc/67xLtuEENLJXchW8Gm7t0y3PW3XirP5eP7zfgHgd90V2wa1RgcDrzZlcd5hqsDancmI1rdM/qHAyR03DQZUrtZTiTKy8qHTNN9npF2u/nhkEhDgbt1Pyx5W7l7NPtbsNOVtS6jYe0eSH4/bRgA9RtnOE6jy+OxeEOTb6PhYlIbfHwP8h9lpVqMdjonhQHJmrM27FZJCdOOXi2uRmWtUx16o6eh56eQ6RCYBH8yw0wnZewKevQ7o6mtd4jQ1JYH32XBSsryJutWtuvUeiuSs32CM+R0zB5sgC7Vf0WLnWeD2Z4C4sWeQkWx+TTo/2+XrVB7mpO7sjEtgoUpOlnk4VaGxn1fw5v/moOzwUby1DlB7NH9yWhW5TIpcYwEPLPKLAbmiGQ9ETho+Aubu2roHvMhkIQpKDPDxEsBYLORTwgghpLPbH2PCKz8BUXc04MKPWI65473Qf+BgPrX4SukR1hXzRrFzjEzArbJQS1E6Fv9Rgae1IrTImIVEiaXsdCPIYrZDWSH0xjLotK0wCiB2wYPTdIC8YVWh5k+U49Y+bNpY2z9t7/AjFkePHsWECRPg7u4OjUaDe++9F3l51tWJWAnL6dOnQyaTQavV4pFHHkFJSQnanfx4zB4K9B1cT6KwLBCGzDSYymp1wy5KQy8/QKGzLhdbTdkDD01TYfHNNu4zmfDIhGK8fE//uvdJFPDTSZGQXDO38e+/N8FfK0TPIdfbfi5XP1w70g895db9L9LSUuHpLgZEtvtChPafwL/GHPoD43sDQ4cNs/34bHQjbAhKy4HUuEPISDVXitD52a6gxDqR//ccoJTkVFddEgqFkLnZH4kwwgsHY83TSqsCk5Ygl7kir6DInLy9EBg6pInlAh2RqjEsFAj3b90RC9YEML+w2Ny3gzUvIYQQAqFUxUfbo5Pt96CqJhDg7d9SMPuZP6/oO9e1W3c8Nc16xILlS7JS814+LXTRTaLg07wioy2qQhWn4/oIYGB4V7SGQyne+OGvEw3qZSEpN0Chanin8dbUoQMLljg7fvx4dO3aFQcOHMCmTZtw5swZzJs3r3qZ8vJyTJ06Ffn5+di9ezd++eUXrFmzBgsXLkR7k5l0Fi+vAXLLHZ/gRaW5off/gJxk66ShqKgo3rW5CHZKdQqEMEr74Mzpk3XvK8vD+ZQy6Attn/AH+OqQkFrZYK6sENsOxGHKiBAIRPaj7/jSPnjgvdMoK6yZExmsysPMUfb7JSi8euG+Cc5wKorFkyuApFz7J/5+YSMgFADxMScQqs3HqifkcJHbvuruJPdCmK8IkjJzcNTXtxjrX/TjwYU9/x1Nx40fgJfg1fq03IFL7uYKY0EZP4h392GjKlcmAc8mqQYZRvByr605YuEmc0FeQSnyC4rg6kyBBSGEMEFdzc1y3b1aJpfBliKTAh9sAtKTamYZ6JPO8ipNXv4t9NkoFOOjrSKs320xW6MwDQsmAv37h6M1ROvV+HRTgfUUMTvuff883lxrOwe0renQgcX69et5JZtPPvkEYWFhGDRoEP+eBQ7nz5sTZrZs2YLIyEgsX74c/fv354HI0qVL8dVXXyE316LTcjtw4Xw0vvxPACc3x6XbPP3MB5iUeOvyr8nJSTifBkgV9k9ED14QY9rbhTCV1poXWGLAQ98Dq7ZbV1yo0iM0ED29S/i8SugP4If7TXj4nlscbqfUcxD+PALEHf3LfIPJhKu7ZeGhm+p2Fa8mEOCleweDpXqs3AuUO/vaXVTiooCPVoqLF2KgEKZjxAAHV04EQkxfKsb2/dH8R7k4B/3YWbsD3pXdz39f6AKdd92St83ltQdH8K7fGUnnMG4xkJRRa2TqSnJS4/v7gJdvdq2bhN+CFHIZTBVlCNSY0COQSs0SQggz5LpFOLpzDTx7zWi1N0Tk6oG31wHxF2oSlauqIXn5N7x7dlPJXZ2Qm1tz7pKbcQEfbQZyS1smz6O2rmHhSDSw+KZWKf7aTCakGYogdWkfRUk6dGBRXFwMJycnq6vKLi7mK+psdILZt28fevfuDR+fmpPESZMm8XWPHDmC9iQ5OQFquROcK1+jPSqfHpCIgLQE62lGmRnp0CokEDgou6bWeqO4FCgw1GrqUmzgnajdVbavWg8a2Adfza8AijJgiPkbUjGgDp3scDu9uk+E2g04fWiz+YaSLPx1sAiRqY5f34l0HyzdCD4a4R3ieBrQ/OndEKxIw4+b4vHKb477PWTkiZCSxjpam/Dr9nQ89pWNJoMWvAPCeKCzJaplT3RdFTo4idlBMx5nkwGxczMmpkk1vNSsxLX1pkEx917fE78/Vo6F00S4d5o5p4cQQjo9oQhe4TfU23W7OUncvCF3AQyZ5uInTG95JNY9KYAikCVftAyFmzOM+TV9upIuRuPNv4Aycet8fnXtPZTPgroQaV39so6yPF5VS622UTq/DWr7WSBNMG7cODzxxBN499138eijj/LpTs8++yy/LyXF/AuempoKT0/rK/wqlYoHJOw+e1jgwf5VqRrdKC0t5f9anKkciSnp8Nap639+Fz94KIGUhBirZTP1WdCpnB2u715ZXjQ98Sz81DVDq4LCDGQXAG5Kjc31hc6+2HEGCOtzGE+99ANCVWI8z0YeHG2rIhy9/QQ4dfwwprPljBexZANwh7wEQZXr2Xquk8muWH0Q8FaJ+LxKR6/n7lsmQBR9CmsPAtkikePXrnCBITsbpUU5uJBWjiRDhcPleUM5kQvu+zIfk19uud+J5eujsXoNsPjuBP6zk8z2PrkiTM4QC8R85KKshX7vq16L1WsyuaCwAIi5kA6v0G7waI2/QdJ6+590GrT/2yGRklc0ysxMN++/8kIgdSv6DxqBUqHC8XnAFdz/bMpsclpW9bqpKfG8cqNM498qxxOFb39ejCY68ihCxzt4/vwUXu7eXdWMn+X1aMzztsvA4uWXX8Yrr7zicJlDhw4hIiICP/zwAw8uFi1aBJFIxBOzWSDBvq8isBHJs8Zstm6v8uabb9rcBja1ytX1ylVTaCjnikykZlVA4SbFxo0bHS4rNhVi/hhAbkq0WtYZOejqq3G4vqYygNqzfSPkiTW/Ph7Fu3mCWHpmts31fcv0eHw5MCPnI+w5kYabHgjGxk3/1Pu6QgLUSEu5iI0bNkBXfhxpuUBhqQlbt5p7aVR9tVRQYS41Kpc51ftelMWlIjuK9aMAXLQih8s7O4mQlVuKnZuW89fKRkTqe3w3lS8PQOtb7kpKy8yB3ggYMhL4Raode45AILKRF3OFjBYEIjdPjWMt+Bpr7/usg+ew+BvAV23CdaOTECxt2W0hLc/W3z7pPGj/tyOmCqjcgIvx8fyzUGrYiceeK8R7z+pQUrixxfb/dUPd4VKcWf15nHj6BDRurEdEJIqE6WhxpnL894IYFUrrc7HalGUxGNUdEKCiRc8lLBUU1Iz0dMjAYsGCBZg9e7bDZYKCzFV45syZw/+lpaXxqk8sWFi2bBnvJMx4eXnxxG5LWVnmiLb2SIYlFqiwgMVyxMLf3x8TJ06EQtHy8/UEmXsxPh8wht4H2YAp9S4vLlXB5C5D+ZjKZcvyIMkvQ0XgRJQPdrB+ihCv3fQ5xl7VDR4Wy5WdS8DrNwGTrpkGj/C66wsylfBXv4ede46C5dZec90tEPWtfzunes+B+PxHKB0VisKERN5rYtDQcQgfN4EfWFjFr9odoXOvGoBX3vwIbz08AgOnOH6ODT9H4d31QFdPYMKIHpjiYPkzW7tBVZCO0f08sKaA9Qvxcbg8c/z4cZ4UX99yV5IpbQeMq7fBTVyIgcEiTJ1+5eqR21QxHjII4d1CZfDY32btfb/PsBr5xQf474e3d/37hbRftvY/6Txo/7dPERkauOm84DplCla//SFvVjd21ksQudvuSdUc+1+0bzmEiZHoPnkiT+b+ater0MqBcVNmA8LWKfoh3tId5cVZDj+zBKmbMaYYKBs4Fabg1vlsa0zOcbsMLFhJWPavMaqChG+//RbOzs78l5IZOnQoFi9ezKdGeXt7V486SKVS3nHYHnY/+1cb+0VvlQ+7okSwHtDu3j3ZRtS7+IFELRIOR+HGCZXLFhkQlQRovZTQOVrfzQ93s2q2ihKr55EI8nAXuz0wzPbzK7rATw38dTQDMyIAZ//xDdpOk8cwJB/6CO4pe2FIMVeU8AvqVf0e23q/NZ7+8PTvhhTF7Hr3RUjvkXz0gRV7C+oS6nD5Zx+6DmCdwPOj+VUOry4B9T7+unXreOnilvydcFd78sZ4g4KBv57VNeh9bprWObmz3PdKpTm3h3WOl8sVdMLZCbTasZa0CbT/2xdfH0/AlAMWUfyzfT/GD1DBWeegEEsz7P/tpwvxyxrg85mFgESNuaNcMb2rEhJp6zVU/WmfK3768zS2XFvGe1vYkmNIxo4jwDVXaVrtmNeY5+3QydvMxx9/zHtZREdH84pQbLSDTWNifS0YNsLQs2dPzJ07F8eOHcO2bdvw5JNP4p577mmVkYfLlh+PiBeADXvM8+rrc/iiM77ZnAlUVHahLErFwz8Av+90nJAMZ0989g/w7y7rxPZLFy/i+VVAqcBOorKLDwK05qll88eJAc2Qhl0MVw/BiFeA3dv+hI88D5v/B3gG1l8a7omnnkf3vkPrXS6waziv+PTmLOC66xxf2U8zOuMkK4GdE4XXbgIeutNODw4LrLrYihXW3cObm69/ECb3BVKygZgMG53QOyA3hTmpjfUlkbm1o79bQgjpBD7ZVIIFn1xAccp+bD9VgAlXj23xbcgtkWDXOfZBYe5HJRfq4e/XjOXYG8DLPxQxaUBFjnUxHUsxMWdx/7dAhaTtd93uFIHFwYMH+ehEeHg4vvzyS3zxxRc8z6IKy7XYsGEDH8UYPnw4br75ZsyYMQNLlixBe1KSHYvUbEDj071By3v5+CE12wQUJptvKEqDPg/QejguoQpnHf6LBA6csO6+fTEhEd/vZGXl7DRwEUowa4wnNjwFDIi4ym5kXptIHoSeAVKcPnUMTmWpCA+SQOxW/4GABYo9etQ/xMqCR5mLFFtOAaVix81nNu65wIMv5Ebxaku5JfWftLMSxux3ryWFdg/HF3cDaw8Bj35d0wOkI9PqvHDXaOCVmay0MVWFIoSQtqRCJEN8WhEKY3/HbcOB0dPva/FtUCjVMBYBphJzt+sFn8Th860NaBzYjEJ7DeaVNpOi99pdxpCRCpmUtQKo5/ysjWiXU6Ea48cff6x3mYCAAN7zoj1LSYjm5eR8gho2X9HTJxgZuUBZTizEMn9UFKSYAwuvek7KhBJolFIYDFlWN2dn6aFwMXf5tCckJBjITAU8GlFeTiBA77BAnI6Jxsp1Juw5I8Uns1k8XDnScgV8+9Y8zHrsS8wtdIang2puKp0fr8yA3LOY/RHwksd5XN96PYfsKjG5YNMRIDnb3JG6M1CqPfF6VUd4L69W3hpCCCG1qyQa8gB3/W945VYNEHh1i79BcoWaN+Urys2Ai3spYpKK0atn645w+4cN4+X/Y84chP/Qh2wuY9Bn8NL7rLx7e9DhRyw6i+SEeAgEInhb9ONwxCsgDBUm1v0yiv+cm5HA/+C03sH1rqt2l0OfZbS6LScnG+5uYj6tyC5ZZdCia1zd6t59BuBMIhB7MQU5xVf+RFkUchsEzp5Q6xyfkKo8AnlJXVNZIXIKAYW6dYdQ7SmBKx82PZUAyDpJYAGxG95ZB8xYBmTl02GNEELaEo3Wg+fA/e+bS4gzjQbrr9HSVBpP+GuAQmMG76mVYQR0Hh5oTSJVDz7arkBNj4/aDAY9L9fLyrq3Bx1+xKJTMFXADWmYM6H+ZOIqgd0isP8VQCs1T5WRlGfinVuAgK59611Xo1biTNxFq9tycnKhdKvnuX2mALnRgMcINMaIq29ARfwv2H8e8NBd+WZvr7/+Oi8vXN97p/II4sEXOziyoUul1n5X79bkKtfyMrNsalxQcMuXPm4VEjne32T+tkLYSV4zIYS0E35+Abxx60+7gUdedNwct7kEdw3FgVdZUl4FTIWpvCy7rr7p381NLMNLtwcCEvvlbqdFSDHEU84rWbUHdGmvIyhMQbhfGd5deE2DV5EogxGgBURF5mRvmcCA20aKINcE1rvuglkDsObRMqC8plP1A+MFWPNCPdOwuswFrjnC/5AaI6jfNNw+Soz0HMDLQQngy3X//fdjyJD6k8mDgrti2Tw5Cir7IirVbXO+o1AkgpuLEBPCgZsn9UKnIJZXf+umbFzFOEIIIc2rd3g47hwF9PQTwLffLa3ydpvEClzKBApzM1CUnYAhXQHfAHPrgdYUneOP1Vsj+UViWwLc8zGwZ/uZ4kuBRUeQH4/d54DD8Y0YWnT2wOyPhfj5r338x8MnY/HaXyxJov7HcJL7gNd3KqqJsAWlBrgqHSc/XzaxCz7b44Mj8UC30JAr/vDXXnst1q5d26BE79njA/hcx9dukcOrsjxxWyR3kaBvADBiUMOS+ds9SU01MidXB4kyhBBCWly5WIWlG4EhfbtYHa9blESJ4a8AB49GwkWQjVWPAF3DWra4ii2n05R4ZXUpkM/KTta1eMUFrNzDiuK3DxRYdAT5F/HVf8Bfu5Mavo5AgHKBKy4lmuf1nY5JwdZTDfvF3X+uGF0eA8rzKytKlZfgwa8K8NJPjXj+y/jDm94fmDHN3H+ktTzzkxEXMoC7p/hBLq+5St7WfPhAIE5cAnaeyERnG7EQOLXd/UIIIZ2SshdcnAS4YfY9rbYJAqk75M5Abo4BGclx2BttLqHf2rp278eL52RdOlj3TpMJB87mIz2vdRr4XQ4KLDqCgJuRLB4B79DhjVrNU6dCanoW/8XVG3KgVTVsipJS48v7BeSkXzDfUJLFqyVJnZuvyUxYv9FYfUiAYrd+aE2bj+biryPAa7+x8lBt17B+fvygGZPYtrfzihG7YdeLwKm3zN8TQghpO0SKLohNKcXAac+03kZIlLx6pdGYg32HTuCer9tGYBHSy5x3Ghu5v+6dZUYY8ky8qlZ7QYFFRyAUIznNAN+Axk0T8vL0QFp2GVBwCRk5JdCqG1Z2Te0ZxL8a0qoCCwNyCgB39+abguIVOhJw9kJmSetOc1Ep3XgS+eo95jrYbdXS39NxLoU1jrvyye5tksgJAToJ3GXWoxeEEELaiFaoBGVFouCBRW5ODjIz0qBjpzzOrVsVipF594ePCjh/9gTqKNbzMr1qTTNNNW8G7SPFnDhUWFiIrKws+DSw1GyVPr3DUJJxBNAfQnY+oA1sWI1ktVdX/lWfngD+XUkWL7+qVDVfjeUbbrgBTk5OjX6NV5pa5Y6oyERodA1r8NdaYpJL+Vc3Rfu5ytFUXR4tR0UFkDyLRiwIIYTUIpTg7nFOCA5xwr9HM6BTiBpdTKZZOHvgl8fl8A6qrAxjoaIwHUpXwMOz7eZ01kaBRQfAyqSyBn/duzcuUffaqZNwrWYlDyw+uwso73NDw55P7ovZQwGFOM98Q4kBY3qwxOr6e2BcLrFYzDuitzaVSs2nfQUHt4GDkQNububtk3eiCkkVJl5SABC17X1DCCGkdcwaowFkwK9bs6FVtZHS5AIBunbrBeSxpA9rwlID9r0CIKI/2gsKLDoAdtI9YMCARq+XDw/sOQmMVe/njawlbg0cDXD2wLLbAHibr4qj2IA3ZrFf/Ah0dJ+/+yTerNiJs4Vte7qNQqnByDBg2Iix6CxuGKZEVHx26w+3E0IIaZM2nxKhqDQRtw03odzZPK27Ldhw2g2fLs/Ahml6qw7bxbkpSNcDvhJ1u8ldaC/bSZpBVqkS874Aks4fRvgzwKZ9tkud1SGSYmeMG06cieU/FuelY81BILdY2uH3k9BjGJ6YNwpffv4p2jJt2CTIgydBrOmNzuLjx3pj22vtZ7iYEEJIy9oVVYE/92ain082BoZf+fL1l0vp0RUnLgIlmaetbj9x8hSGvMjK9bafac0UWHRiHoF9+NfEjALkFgJqj/qb41X5eocQa3fE8+/TUxPx8A9AdmHHv1L81Y9rcN37TnD1G4a2bMr0mdi6JwopKeZywp3CwA+AYStaeysIIYS0UQq5DMa8Qiz8qRwHzddG24TQ3kNRYQIuRO6xut2QmQo3ZzajpPWrVzUUBRadmJOzDGq5GKfNzbeh9Qlt8LoalRyGbCP/PsdgbpTnrgtAR6dUKnHmzBksW7YMbZler0dpaSlcXdvIHNKWoOoHeI5u7a0ghBDSRrH+U+xC6trDQE5J28nH8wi+CnIXICbysNXtWfoMqNlmSttPviQFFp2cl1aGM0mNDyxYdSRDbjFQUYpsQwbLPYKb2g8dXVUtaWdnZ7Rlf/zxB/8qk7WdAychhBDSmhQKBVJzgKJSQOfl32Z2hkAeghkRIkhLEq1uNxj0ULNCh06tW2q/MSh5u5N77b7BKLq0FVJnF8iVDe95oFZroGcDFkXpyMkxQO4igFDS8a+Oq1SqdhFYXH/99Vi1ahVP7CeEEEIIMGN8H/QQb8e0JYDOu+0kb0MowtsPhAPFqVY3RwQLoRPIeL+y9qL9bClpFkOHRADyrRg7PJSXPGuo6ycPwVjtTqAoDUNCgO8ebj/DdE3h5+fXLkYCWJWwc+fOtfZmEEIIIW2GTKGFWATIpIDW29yTq61IrwjBoT3HMXVqLm/mxwwJLsGQoNbt39VYNBWqk1t/MAfTlwBbTjcuxvQJCEVPdo5dlAatixFD+3ihM/Dy8sJNN92EXr16tfamEEIIIaQRTsfn49ZPgFNvAVJl25q+HW3Q4v5vgZL049W3rfwnAbuindCeUGDRyWUVueLIBeD7fwyNWu98SjmmvQsU5STixy0peGO1OZG7M/jggw/Qu3fnKeNKCCGEdAROriro88DzLODctiotde87EuUVQOypHeYbTCb8vCMXxy6iXaHAopPzCjBfeddqahqyNITI1QNH44GstAuIvJiH+Ixm2kBCCCGEkCtA4e7Bv167VABIlG3qPdUGD4PGDTh7+oD5hjIjDHkmqFTtp4cFQ4FFJ+cVMpBXG3DyHNyo9dRe5sYyhuSzyM4HlApWtoAQQgghpG2Sq8yjFE5O4kbllbYIWSC6+4pw9uxZ88/FmTDkA2pN+8phpeTtTo7lDEDkDJFU3qj15LoQiISAPiWa14T2c29bkT8hhBBCiCVXpTmw8NW1wSqWAiFevasHlMI0/mNZXipyCgC1tn3lsFJg0cnpdDrs3LmTN41pDKGTG/oFiWDKu8i7Qvp4ta25ioQQQgghlgRO7hgUDIzq790m35gefQYBcd8BxXqIyrNx8i1A0b8v2hMKLAi6dr28kmvrXgoC8mIxmvXVGzSR3klCCCGEtF1SDa4dKEDPgWFoi+JyvXD368D6oYchgx5ads3XrX1duKXAgly21AIVkG3uYOltcoOU3ktCCCGEtFVO7rj7pfWAqg/aIm1gBM6lANEntqOstAjzFwFH96sgQvtBgQW5bC+uyIRaAKzYA6wISMOobvRmEkIIIaQN852CtkrhPxg+KuDcmSNQuqtRXMqqcLavEQuqCkUum1rtjgQ9eN1lpaZ9dYYkhBBCCGlTXHzR3VeCs+fOwaDPgJoV3JS2r6pQFFiQy6bRaBGXbv5eqWlbHSwJIYQQQtoVgQDD+vnBDZkwGPRQy9j0LRXaEwosyGVTaz1xMdP8vbvOn95JQgghhJAmeHDuBDw5uQA+LhkY2csFELanDIt2HlgsXrwYw4YNg6urK9zd3W0uc+nSJUyfPh0ymQxarRaPPPIISkpKrJY5deoURo8eDRcXF/j6+uLVV1+FyWRqoVfRfg27ajCengY8NU0Audq3tTeHEEIIIaRdK3Xtge2RwOTQZPxvVvu7aNuuk7dZgHDTTTdh6NCh+Oabb+rcX15ejqlTp/JeDbt374Zer8cdd9zBg4aPPvqIL5Obm4sJEyZg7NixOHToEKKjozFv3jweiCxcuLAVXlX70SN8IHpcYy7fBnG7/lUihBBCCGl1ZbIw3Pop8ORU4LrxbghG+9KuzwZfeeUV/vX777+3ef+WLVsQGRmJhIQE+PiYk4uXLl3KAwc22qFQKLBixQoUFRXxx5BKpejduzcPLpYtW4YnnngCgrbW8r0NycgT4453gIkRwGMzW3trCCGEEELaNxfvgQjUAu+uB8TqEjx8B9qVdh1Y1Gffvn08UKgKKphJkyahuLgYR44c4aMUbBk2DYoFFZbLLFq0CPHx8ejSpYvNx2aPwf5VYSMfTGlpKf/XGRRUuOH4ReB8phEPtfBrrnqPO8t7TWrQvu/caP93brT/O7dOsf9FKoT5SRGfUQx3d1WbeK2N2YYOHVikpqbC09O6/q9KpYKTkxO/r2qZoKAgq2Wq1mH32Qss3nzzzeoRk9qjJCznozMoKS6GCQIUlwqwcePGVtmGrVu3tsrzktZH+75zo/3fudH+79w6+v7392J5w2koLi1rtfMrSwUFBe03sHj55ZdtnrBbYrkQERERDXo8W1OZWI6F5e21l6lK3HY0DYqNaLCpUpYjFv7+/pg4cSKfYtVZPPqoDpBIMGXKlBaPntmBheXHSCSSFn1u0rpo33dutP87N9r/nVtn2f/dSsbh679/Rs9e/TCohc+vbKmaldMuA4sFCxZg9uzZDpepPcJgj5eXFw4cOGB1W1ZWFv/FrBqVYMtUjV5USU83N2eoPdphiU2dspw+VYX9onfkX/Y6BCLeIK+1XnOne79JNdr3nRvt/86N9n/n1tH3f2jv4fjh/p/Rq1ePNvE6G7MNbS6wYCVh2b8rgVWLYknaKSkp8Pb2rp6qxAKCgQMHVi/z7LPP8gpTbIpU1TIsL6OhAUxndvToUZsBFiGEEEIIaTxx0I2YMHUH0K39VcZp130sWI+K48eP86+stCz7nv3Ly8vj97NpST179sTcuXNx7NgxbNu2DU8++STuueee6ulKc+bM4SfGrFLU6dOnsXbtWrzxxhtUEaqB2IgPy1shhBBCCCFXgIsnMGIV4FpTfKi9aHMjFo3x4osv4ocffqj+uX///vzrf//9hzFjxkAkEmHDhg148MEHMXz4cN4AjwUSS5YsqV5HqVTy+XoPPfQQz9tgJ8ksd8Iyf4IQQgghhBDSgQML1nvCXg+LKgEBAVi/fr3DZcLDw7Fz584rvHWEEEIIIYR0Hu16KhQhhBBCCCGkbaDAghBCCCGEENJkFFgQQgghhBBCmowCC0IIIYQQQkiTUWBBCCGEEEIIaTIKLAghhBBCCCFNRoEFIYQQQgghpMkosCCEEEIIIYR07gZ5bYnJZOJfc3NzW3tTOoXS0lIUFBTw91sikbT25pAWRPu+c6P937nR/u/caP+3jqpz26pzXUcosLhCjEYj/+rv73+lHpIQQgghhJA2c66rVCodLiMwNST8IPWqqKhAcnIy5HI5BAIBvWMtED2zIC4hIQEKhYLe706E9n3nRvu/c6P937nR/m8dLFRgQYWPjw+EQsdZFDRicYWwN9rPz+9KPRxpIBZUUGDROdG+79xo/3dutP87N9r/La++kYoqlLxNCCGEEEIIaTIKLAghhBBCCCFNRoEFaZekUileeukl/pV0LrTvOzfa/50b7f/OjfZ/20fJ24QQQgghhJAmoxELQgghhBBCSJNRYEEIIYQQQghpMgosCCGEEEIIIU1GgQVpc15++WXeZNDyn5eXV4PW3bNnD8RiMfr169fs20naxr4vLi7Gc889h8DAQJ7YFxISgm+//ZZ2TyfZ/ytWrEDfvn3h6uoKb29v3HnnndDr9S22zeTKSkpKwm233QaNRsP3KTuWHzlyxOE6O3bswMCBA+Hs7Izg4GB8/vnntFs6yf7//fffMWHCBOh0Ot7bYujQodi8eXOLbjOxRg3ySJvUq1cv/PPPP9U/i0SietfJycnB7bffjquvvhppaWnNvIWkrez7m2++me/vb775Bl27dkV6ejrKyspoB3WC/b97927+N//ee+9h+vTp/KTk/vvvx/z587F27doW2mJypWRlZWH48OEYO3Ys/v77b3h4eCA2Nhbu7u5217lw4QKmTJmCe+65B8uXL+cXlx588EF+ojlz5kzaOR18/+/cuZMHFm+88QZf7rvvvuPHggMHDqB///4tuv3EjAIL0iaxUYeGjlJUue+++zBnzhx+IvLHH38027aRtrPvN23axK9WxsXFQa1W89uCgoKaeQtJW9n/+/fv5/v7kUce4T936dKFHwfeeecd2knt0Ntvvw1/f39+clilvr9nNjoREBCA999/n//co0cPHD58GEuWLKHAohPs/6r9XoUFGH/++SfWrVtHgUUroalQpE2KiYmBj48PP1GYPXs2P3F0hB2I2JUN1tuCdJ59/9dffyEiIoKfSPr6+qJbt2548sknUVhY2KLbTFpn/w8bNgyJiYnYuHEjTCYTH7lavXo1pk6dSrukHar6e77pppv41Wp2xfmrr75yuM6+ffswceJEq9smTZrEg4vS0tJm3mLS2vu/toqKChiNxuoLTaTlUWBB2pwhQ4bgxx9/5PMk2UElNTWVn0DYmzfNTkSeeeYZPteaXe0knWffs5NONh3m9OnTfOoLu3rFTiwfeuihFt920vL7n93H/u5nzZoFJycnPtLBpkN89NFHtDvaIfb3/NlnnyE0NJT/DrBpbWw0iv1O2MN+Rzw9Pa1uYz+z6ZCZmZktsNWkNfd/bUuXLkV+fj6fIktaiYmQNi4vL8/k6elpWrp0aZ37ysrKTBEREabPPvus+raXXnrJ1Ldv3xbeStLS+56ZMGGCydnZ2ZSdnV1925o1a0wCgcBUUFBAO6WD7/8zZ86YvL29Te+8847pxIkTpk2bNpnCw8NNd911V4tvK2k6iURiGjp0qNVtDz/8sOmqq66yu05oaKjpjTfesLpt9+7dJnZ6k5KSQrulg+9/SytXrjS5urqatm7d2kxbSBqCRixImyeTyRAeHs5HJmpjQ55syHvBggV8tIL9e/XVV3HixAn+/b///tsq20yaf98zrAoQmwKlVCqrb2NzrNm0GDZFhnTs/f/mm2/yZM+nnnoKffr04VNgPv30U14VLCUlpcW3lzQN+3vu2bOn1W3s7/nSpUt212GjVGzUwhIr4MCO/6yyEOnY+7/Kr7/+irvvvhurVq3C+PHjm3ErSX0osCBtHisnGhUVxQ86tbHycqdOncLx48er/7Hh07CwMP49m1pBOua+Z9hJZXJyMvLy8qpvi46OhlAohJ+fXwtuKWmN/V9QUMD3taWqKlIsuCTtC/t7PnfunNVt7O+ZlZK2h5UX3bp1q9VtW7Zs4XP1JRJJs20raRv7n/n5558xb948rFy5kvKr2oIGjWsQ0oIWLlxo2r59uykuLs60f/9+07Rp00xyudwUHx/P73/mmWdMc+fOtbs+TYXqPPveaDSa/Pz8TDfeeCOfFrNjxw4+NWL+/Pmt+CpIS+3/7777ziQWi02ffvqpKTY2lk+BYVMjBw8eTDuhHTp48CDfn4sXLzbFxMSYVqxYwae2LF++vHqZ2r8D7HeFLfP444+bIiMjTd988w2fUrN69epWehWkJfc/m/7E1vnkk0/41Leqf5bTY0nLosCCtDmzZs3i86bZh4OPj4/phhtu4CeNVe644w7T6NGj7a5PgUXn2vdRUVGm8ePHm1xcXHiQ8cQTT1B+RSfa/x9++KGpZ8+efP+zdW+99VZTYmJiK2w9uRLWrVtn6t27t0kqlZq6d+9u+vLLL63ut/U7wILR/v37m5ycnExBQUFWOXekY+9/9j27Rl77H1uOtA4B+6+1R00IIYQQQggh7RvlWBBCCCGEEEKajAILQgghhBBCSJNRYEEIIYQQQgihwIIQQgghhBDS+mjEghBCCCGEENJkFFgQQgghhBBCmowCC0IIIYQQQkiTUWBBCCGEEEIIaTIKLAghhHQq33zzDSZOnNikx0hPT4dOp0NSUtIV2y5CCGnvKLAghBDSIPPmzYNAIOD/xGIxAgIC8MADDyArK6vdvIPFxcV48cUX8cILLzTpcTw8PDB37ly89NJLV2zbCCGkvaPAghBCSINNnjwZKSkpiI+Px9dff41169bhwQcfbDfv4Jo1a+Dm5oaRI0c2+bHuvPNOrFixol0FVoQQ0pwosCCEENJgUqkUXl5e8PPz49OJZs2ahS1btlTfX15ejrvvvhtdunSBi4sLwsLC8MEHH9QZ+ZgxYwaWLFkCb29vaDQaPPTQQygtLa1ehgUvU6dO5Y/BHmvlypUICgrC+++/X71MTk4O7r33Xj56oFAoMG7cOJw4ccLh9v/yyy+49tprbW7PG2+8AU9PT7i7u+OVV15BWVkZnnrqKajVav56v/32W6v1wsPD+Xuxdu1a+g0ihBAKLAghhFyuuLg4bNq0CRKJpPq2iooKfhK+atUqREZG8mlHzz77LP/Z0n///YfY2Fj+9YcffsD333/P/1W5/fbbkZycjO3bt/NRhi+//JLnNVQxmUw88EhNTcXGjRtx5MgRDBgwAFdffTUMBoPdbd61axciIiLq3P7vv//y59u5cyeWLVuGl19+GdOmTYNKpcKBAwdw//33838JCQlW6w0ePJg/JiGEEPPBmRBCCKnXHXfcYRKJRCaZTGZydnY2sY8Q9m/ZsmUO13vwwQdNM2fOtHqcwMBAU1lZWfVtN910k2nWrFn8+6ioKP64hw4dqr4/JiaG3/bee+/xn7dt22ZSKBSmoqIiq+cKCQkxffHFFza3Iysriz/Gzp0767wutj3l5eXVt4WFhZlGjhxZ/TPbVva6f/75Z6t1H3/8cdOYMWMcvn5CCOksxBRdEUIIaaixY8fis88+Q0FBAc+xiI6OxsMPP2y1zOeff87vu3jxIgoLC1FSUoJ+/fpZLdOrVy+IRKLqn9mUqFOnTvHvz507x5PD2QhEla5du/LRgypshCIvL49Po7LEno+NhNjC7mOcnZ3r3Me2RyismR3MpkT17t27+me2rey5LEdNGDZVi70XhBBCAAosCCGENJhMJuMn+cyHH37IAw2Wj/Daa6/x29iUp8cffxxLly7F0KFDIZfL8e677/LpRJYsp08xrNIUm0ZVNc3JFsvb2bIsGGFTpWpjORK2sMCAPY+tZGtb2+NoG6uwaVes7CwhhBAKLAghhDQBK7d6zTXX8LKzPj4+PN9g2LBhVpWi7I0g2NO9e3eeOH3s2DEMHDiQ33b+/HlkZ2dXL8NGM1h+BRvZYEndDeHk5ISePXvy3I+m9rGocvr0aYwZM+aKPBYhhLR3VBWKEELIZWMn1WwaEauoxLDRjMOHD2Pz5s18mhTrF3Ho0KFGBxbjx4/nFZ8OHjzIAwz2PZt2xEYNGHY/GxFh1ZzYc7Hyt3v37sXzzz/Pn9+eSZMmYffu3Vdkj7MpUGxK1pUKUgghpL2jwIIQQkiTPPHEE/jqq694xSRWOemGG27gZWiHDBkCvV5/WX0ufvzxR57nMGrUKFx//fW45557+LSqqvwIFmCwalDs/rvuugvdunXD7NmzeYDB1rOHPQ5bj5Wqbao///yTNwm8Ej0xCCGkIxCwDO7W3ghCCCHEkcTERPj7++Off/7hJWWb4uabb0b//v2xaNGiJj0OKzX72GOPYc6cOU16HEII6ShoxIIQQkibw/pK/PXXX7hw4QKf4sRGI1guBRuhaCqWTM66bzcFqw5144034pZbbmny9hBCSEdBIxaEEELaHJY3sXDhQt6Ej02BYgnhrOt2YGBga28aIYQQOyiwIIQQQgghhDQZTYUihBBCCCGENBkFFoQQQgghhJAmo8CCEEIIIYQQ0mQUWBBCCCGEEEKajAILQgghhBBCSJNRYEEIIYQQQghpMgosCCGEEEIIIU1GgQUhhBBCCCGkySiwIIQQQgghhKCp/g+E+TW1k8/h4wAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -6668,7 +6501,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 27,
    "id": "ecbdd657",
    "metadata": {},
    "outputs": [
@@ -6694,15 +6527,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 28,
    "id": "7679300e",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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FZQ4o8ubNq0cGSquCqExAHBwcjBw5clh00jWKG7iFhobi3r17+rmPjw+sIqho1aqVfiTXzJkzUaRIEUybNk0/9/Pzw8GDB/HFF18wqCAiIiJKIWmGZA4ocufOnab5J0FFREQEnJ2dGVSkIRcXF/1XAgs5r+nVFCpLhYl79uzRE8bF1qJFCx1YpGUbQCIiIqLsyFx+Ms9dQNmD67/nMz3Lx/ZZrXouX758cZbJ88jISDx48CDRKh6DwaAfZoGBgTGZnFGBiPm4DIQyBvM/YzH/rSf//5jWAb5+NVG+xftpfqysgtc/8z8zXpPSZEYeUpOQluQY5r9pfSxrp/49p3J+Y9dUpOW9P0sFFSJ+Oz/zBZpU+79JkyZh3LhxCZZv2LAhw6PyjRs3ZujxrR3zn/lvzdLj+n974lrY2m3E9DmV0/xYWQ3vP8z/zEJGY5IOvdLXQZompYegoKB0OY41i4iIQFhYmB4USX58Tw9ZKqiQi15qK2KT9mLygUiqHeDo0aP1aFGxayoKFy6sm1F5eHggI0iUKF8ozZo108N+EfPfmvD6t5L8N0V/iUlnTBlgg9I5/ylRzP+EZHhXGY1JOk9LX4e0JD8ES0Dh7u7O0Z/S4bxK34oGDRrEOa/yGVi9enWaHDNLBRV16tTB77//nqDGoXr16knenJ2cnPQjPtk+o2/omSEN1oz5z/y3Zml+/RsNGNsZ8H2uGO9zGZH/9FTM/7gdtaW1h/wAkNYjMpmbPJmPZwnyY/OECRPw559/4ubNm7pjcuXKlTFkyBA0bdoUvr6+uHr1qt5WCtdFixZF3759MWLEiJjA5sqVKyhWrBiOHDmi9zU/l2ZDsm/BggVjjidTIMiP05JvMiqpvH5szZs3x99//61HKK1du3aC9MoxJk6cqGsQAgIC9ABEDRs2xLvvvotSpUrBUiR/5f2l57WeoR21part6NGj+iHk5Mj/r127FlPL0LNnz5jtZT4KOblS83D69GnMnTsXc+bM0RcGERFlIlHh+F8ToHmVtP3lk4islxT+q1Wrhs2bN2Py5Mk4fvw41q1bh8aNG+Ptt9+O2W78+PE6GJCyo5QZ33//fcyaNes/X1/mQ/vpp5/iLFuwYEGcICO2a9eu6UGFBg4cqMun8f3xxx860JC+vosXL9bpWbhwITw9PfHRRx8hq8vQoEJGbapSpYp+CAkW5P8ff/yxfi4XgDnAEBI1rl27Flu3btWR5CeffIJvvvmGw8kSEWU2pnAUeBt4Y9rljE4JEWVTMleZ/Bq/f/9+dOnSRf/SX65cOV2e3Lt3b8x20txKmtBLrUK/fv1QsWJF3dLlv/Tq1Qvz5s2Ls2z+/Pl6eWLmzZuHF198EW+99RaWLl2q52Mzk7kjZF42aQ66Zs0avPDCC7pcW6tWLT01wg8//ICsLkODikaNGsX0To/9kBMm5K8EELFJFdHhw4d1lCc1G5xNm4goE4oK13/WHw7O6JQQUTb06NEjXSshNRJubm6Jzigdn5QxpVwpNQTJaRLUrl07PH78GDt37tTP5a8ct23btom+9rx58/Dqq6+iTJkyOsD59ddfY9avX79ej1Q6cuTIRI+VWHqzmizVp4KIiLJWUAFEj9BHRFnMtnZA8EWLvqSNAtxNJthIf4r4g3bmKA40XJPs17pw4YIuyEsB/r+MGjUKH374oR4RSToqS9+KQYMG/ed+EnhIkCDN7evVq6f/yvPEApJNmzbp2giZP03IdtIESmonxPnz5/Xf5KQ3q8pSk98REVHWoCLD/v0PgwoiSoN7zH9MKRCbdIKWPrvbtm3T/S0++OAD1K1bN1nHkU7dy5Yt0x3C5W+fPn0S3W7OnDno1q2bHpFUvPLKK9i3bx/Onj0bJ73ZGWsqiIjI4iIN0W2JnTjAEVHWlIJag+RSJhOCAgP1kP66tiIVSpYsqQMKacrUoUOHp27r7e2NEiVK6Mdvv/2m/0qHaenX8F/Kly+vaxckSPDz89PPzQMMmUmTqFWrVulakBkzZsQslxGipHbj888/jxnZ6cyZM3o00+yINRVERGRxDnaRuPEtcO4LxdoKIrK4XLly6aZG06dPj9Mh2szf3z/R/XLmzIl33nlHjwKV3NoDqZ2QvhhJ1VLISE6FChXCsWPHYkY1lce0adP0aFEy+ZwMNSvBjYxSlZik0puVMKggIiKLM4YH4/wdIELmwDOlzyy9RGRdvv/+e10bULNmTV0DIf0WpOZCRgZ9Wm2AdO6WZkmyT3K88cYbuH//vh45KqmmT126dNG1GLEfEoRIsCBzaEhn8tmzZ+v/Swdw6YMhQ+LKSKjSeTs7DDzEoIKIiCzu7t27aDwBKDk8dqdtIiLLkSFZZURQ6ScxfPhwXZCX2epl8rnYzZDiy5MnD1577TWMHTs2ZkK+p5F+ElLLYO4vEduhQ4d0DUXnzp0TrJOhbKWGwjxnRfv27bF7927d0bt79+4xzapkErxPP/0UWR37VBARkcUZwmINJauDCk/mMhFZnI+PD7777jv9SIzUBiQm9uR3Mn9F7KZQ8Z/HJ3Olmdf/17Zr1sTtm1K9evVk15BkNaypICIiizOExWrjbGJNBRFRdseggoiILC48dlDB5k9ERNkemz8REZHFFfB2QqcagJN8yzCoICLK9hhUEBGRxeXP5Yjvev/7hEEFEVG2x+ZPRERkcafP38AHvwJL90QPL0tERNkbayqIiMjizl+5g3nbov/fYoA/vJjHRETZGmsqiIjI4sLDwmL+bwgLYg4TEWVzDCqIiMjiDIZwODlE/z88lEEFEVF2x6CCiIjSJKjwdIn+fzj7VBARZXvsU0FERBb3WjMftPcFLtwFCud1Yw4TUabSu3dv+Pv7Y9WqVRmdlGyDQQUREVmck50ReTygH3A0MYeJiLI5BhVERGRxU5eew7lzwMNg4IORl1C5DDOZiCg7Y58KIiKyuICgcIQbgUOXgQcP/ZnDRGRxSilMnjwZzz33HFxcXFCpUiUsX748Zv3JkyfRpk0beHh4wN3dHfXr18fFixfjvMYXX3wBHx8f5M6dG2+//TaMRmPMusePH6Nnz57ImTMnXF1d0apVK5w/fz5m/fz58+Hl5aWbUJUqVQrOzs5o1qwZrl+/rtdfuXIFtra2OHjwYJxjfvvttyhatKhO/9atW2FjY4M///xTp19eo1atWjh+/HicfXbv3o0GDRro91m4cGEMGjQIISEhyEwYVBARkcUZIoxwdoAeAcpgeDK8LBGRpXz44YeYN28eZsyYoQOIoUOH4tVXX8W2bdtw8+ZNXQiXQvrmzZtx6NAh9OnTB5GRkTH7b9myRQcZ8nfBggU6SJBH7H4XEhCsWbMGe/bs0UFA69at4wQeoaGhmDBhgt5/165dCAwMxMsvv6zX+fr64oUXXtBpjE2ey2tLMGH27rvv6gDnwIEDyJs3L9q1axdzHAkwWrRogU6dOuGff/7B0qVLsXPnTgwcODBTXUxs/kRERGkSVDg5OcLZIQKGcAYVRFmRFJADAgLiLJNf9e3t7XH79u04BXQnJyddGDYYDLh3716cfXLlygU3Nzc8evQId+7c0bUG8gu+kF/dzceSGoXkkl/pp06dqgOGOnXq6GVSYyGF7R9++EEX6D09PbFkyRI4OESPby21CbFJDcR3330HOzs7lClTRtdq/P3333jjjTd0jYQEExIo1K1bV2+/ePFinV6pmXjppZf0Min4y2vUqlVLP5fgws/PD/v370fNmjXRr18/9O/fX6dV8ujYsWM4evQoVqxYESctY8aM0bUc5tcoVKgQVq5cia5du2LKlCno3r07hgwZoteXLFkS33zzDRo2bKgDKgmcMgMGFUREZHGlfWzhYJcD1+4/goPtk4IHEWUdP/74I7788ss4y/bt26cL1u3bt8eNGzdilkvB/rffftM1Al26dImzz1dffYVu3brhk08+wa+//hrnF/pbt27FHGv48OHJTtupU6cQHh4eUxA3i4iIQJUqVfTITtLcyRxQJKZcuXI6oIgdMJmbHZ0+fVoHT+ZgQUgTqdKlS+t1ZrJN9erVY55LcCJNomQbCSo6dOigaxQkQJAajLlz56Jx48Y66InNHBiZg7DYx5E8vXDhgg5qzKTWxGQy4fLlyzqIyQwYVBARkcX1b+4IOHmjb91HQLH8zGGiLEh+sZdfymOTgrdYvXp1gpoKUa1aNR14xCaFZPHRRx/p14xdUxH7WCkhBWohfREKFiwYZ52kxfyr/tPEDzgk2DG/rhTaEyPLYwdF5v3iMy9zdHTEa6+9pps8SfOln3/+GdOmTUNymF9D0vTmm2/qfhTxFSlSBJkFgwoiIrK4Q+eC4ZW/AHKEAk7+gfBiHhNlOdIcKakmSebgIj4p0JubNMUnwYX8si+vGT+oSEnTJ1G2bFl9rGvXrulmQPFVrFhRNyOS5klPq6142utL0CQBkrn508OHD3Hu3Lk4NQOyjfS7qFmzpn5+9uxZXUsiNRZm0gSqfPny+P7773V6JLiIb+/evTEBgnQQl+OYX6Nq1aq6z0iJEiWQmbGjNhERWdykFSFYtTcY/X60wYK/noyWQkRkCVLbMWLECN05W4IH6XB95MgRTJ8+XT+XJkfmTtNS6Jc+EgsXLtSF/uSQfgvSxEtqUKSfhvSFkE7gUisiy80kYHnnnXd08HH48GG8/vrrqF27dkyQISQIkWWjRo3CK6+8okdwim/8+PG6P8eJEyd0J25vb2/ddErIftJRXEankv4Y5v4ectzMhEEFERFZllIIN0ZFd9R2tIXBEMEcJiKLkz4aH3/8MSZNmqQL7jJC0u+//45ixYrp/g/SiTs4OFjXZEizLOm3kZJaC2myJPu9+OKLus+DNH1au3ZtnNeQoWal0N+9e3e9jQQM0jk8vr59++r+HjICVWI+++wzDB48WB9POsFL0CBNp8y1LjKilQQT0k9E+oxIU7KkaosyCps/ERGRZalIhEdEN4NwcrRnUEFEaUL6HEg/g8T6GpgL4+vXr090XeyhY83i93WQ0aF++umn/0yHNGfqlEiTptgkUJAmUDVq1Eh0fb169XQtRVJkvw0bNiAzY00FERFZVlQ4DJESVDjDydEO4aypICIrFRwcrOeekAnvkgp+sgvWVBARkWVFhePTlwDf6kWRS12Aq2vmGEOdiCi9DRw4EL/88ovuH5FU06fsgkEFERFZVlQ4GsrgKAXzoKhdbkA9mX2WiCi7kA7V8nia+fFm6Y6vUaNGSQ5fm9Ww+RMREVlWVDjengccvRCATf9EYMXOR8xhIqJsjkEFERFZlikcfx4FHgebsPNUGFbvC2IOExFlcwwqiIjIolRkGCKko7azix5WNtwQxRwmyuTMM0lT9mDKgPOZqj4V4eHhcHZmBzwiInoiIiy6ZsLJ2Q1Ojk4wGBlUEGVWMheCzG5969Yt5MmTRz+XoVrTqqArczVI+TH+jNpkGdI/Q/L4/v37Oo/Nc11kyqBCLogJEyZg5syZuHv3rp5G/LnnntOTcPj6+urJPYiIyHoZwoKQwxlwcXWDs7MTDBEmPSEe0qigQkTPTgqeMlmczKMggUVaF3jDwsL0BHFpFbjQk0n5ihQpkq7BW4qDik8//VRPfz558mQ9dblZhQoV8NVXX6U4qPj+++8xZcoUfTGXK1dOTzwiswUmZfHixfrYMqugp6cnWrZsiS+++ELPnEhERBnPw9UO574EUPo5FLYvha6ljwAmA2DHmm2izEh+zZYCaGRkJKKi0q5m0Wg0Yvv27WjQoEGKZramlLGzs4O9vX26B24pDipkZsFZs2ahadOm6N+/f5xZC8+cOZOi11q6dCmGDBmiA4vnn38eP/zwA1q1aoVTp07pizu+nTt3omfPnjp4adu2LW7evKnT0K9fP6xcuTKlb4WIiNJAlDEUoWGAm40j3D3c4e4ePSIUgwqizEsKoFLQT8vCvhR2JXCRpvMMKrKfFNeJSEG+RIkSiTaLkgg0JaZOnaprNiQo8PPz07UUhQsXxowZMxLdfu/evbqJlcxIKFV1MqX5m2++iYMHD6b0bRARURq5fOU6So8AHgREYO3eO2j5+b9BBRERZVspDiqkidKOHTsSLF+2bBmqVKmS7NeRTiSHDh1C8+bN4yyX57t37050n7p16+LGjRtYu3atbpcnfTqWL1+ONm3apPRtEBFRGjGEh+i/zq7uiFT2uCHTVDCoICLK1lLc/GnMmDF47bXXdI2F1E6sWLECZ8+e1c2i/vjjj2S/zoMHD3S7vXz58sVZLs/v3LmTZFAhfSq6deumRw6QKrR27drh22+/TfI4BoNBP8wCAwP1X6lVSWnNiqWYj5tRx7d2zH/mvzVLj+s/JDj6Pmvn4AIHPfoTYDQEAU685/H+k7GY/8x/a2dMw3t/ioMK6csgfSEmTpyo2999/PHHqFq1Kn7//Xc0a9YsxQmI34lEaiCS6lgifS2k6ZMcs0WLFrpz97vvvqv7VcyZMyfRfSZNmoRx48YlWL5hwwbdMz4jbdy4MUOPb+2Y/8x/a5aW13/Q2dP674HD/+D+/YcwRAI7t21CoN2lNDtmVsP7D/PfmvH6z56eaZ4KKdDLIzW8vb11h534tRL37t1LUHsRO0CQDt0SSJg7h7u5uenRomRUKh8fnwT7jB49GsOGDYtTUyH9NqSZlYeHBzIqSpQPlARh7KjE/Lc2vP6zf/5ftvsb/RoDzzdoitz2d1GnxCY8X7sqbPLUhbXj9c/8t2a8/jPHOVi9enXmm/wutcOXVatWTX+5dezYMWa5PG/fvn2i+4SGhuohsmKTwMRcw5EYJycn/YgvrUc4SI7MkAZrxvxn/luztLz+SxXKgfFd5AbsgQp+xbF0kNysTXLQNDleVsT7D/PfmvH6z56SFVTkzJkz2WPdPnokPfKSR2oQpH9G9erVUadOHT1U7bVr12KGqpVaBum7If01zE2vZG4MGR3K3PxJhqStWbMmChQokOzjEhFR2jl/+TYO7gZeae+M0AgbHDgN1KkbhPSb15WIiDJlUCFDvZo9fPhQNzWSQr0EAmLPnj1Yv369nlU7JaTDtbze+PHjdYBQvnx5PbJT0aJF9XpZJkGGWe/evREUFITvvvsOw4cPh5eXF5o0aYLPP5fxComIKDM4fPomvvoLeOULZ9x9bMAr3wGHOzxAft+MThkREWVoUNGrV6+Y/3fu3FkHAQMHDoxZJp2npaC/adMmDB06NEUJGDBggH4kZv78+QmWvfPOO/pBRESZkyE8HE7S0snOGU7OOfSy8LDgjE4WERFlpnkqpEaiZcuWCZZLzYUEFUREZN0MhnA42f8bVLhEBxUGBhVERNlaioOK3LlzY+XKlQmWr1q1Sq8jIiLrJnMDOUsHCht7OLm4x5kQj4iIsqcUj/4kcz707dsXW7dujelTsXfvXqxbtw6zZ89OizQSEVEW0q2hN1oVc5aJiODi5oHvegOF8rhkdLKIiCgzBRXSWdrPzw/ffPONnk1bhnItW7Ysdu3ahVq1aqVNKomIKMvI46GQp2D05KJ2jm7oVAOAe/Tw30RElD090zwVEjwsXrzY8qkhIqIsb/rKK3jwwIgxMleFnTOGLQJ6O15FxXIZnTIiIso0QUXsIV4TU6RIkdSkh4iIsrhrd0MQEPTvEztnrDsGNL31ABUzOF1ERJSJggpfX9+nToQXFRWV2jQREVEWZogwwlmPKSvDgTjr4WUN4WEZnSwiIspMQcWRI0fiPDcajXrZ1KlTMWHCBEumjYiIsqBwQyQ83V1jaiqcJagwhGd0soiIKDMFFZUqVUqwrHr16ihQoACmTJmCTp06WSptRESUBfl4KeTO/SSocHWSH6AMGZ0sIiLKbB21E1OqVCkcOHDAUi9HRERZ1JguDkDOYtFPbJ3w9/vS4a5gRieLiIgyU1ARGBgY57kMKXv79m2MHTsWJUuWtGTaiIgoC7p4MxSeDrbwlie2dohU9lCGUPzby4KIiLKhFAcVXl5eCTpqS2BRuHBhLFmyxJJpIyKirEYpDJ5vQMuG9zGwffSi7t8B1SucxcimGZ04IiLKNEHFli1b4jy3tbVFnjx5UKJECdjbW6w1FRERZUUmI8KNgJOTU8wiZ0c7GCIiMjRZRESUtlIcBUgtRd26dRMEEJGRkdi+fTsaNGhgyfQREVFWYgqHITJuUOHkaI9wA4MKIqLszDalOzRu3BiPHj1KsDwgIECvIyIiKxYVDoPUVDg7xwsqjBmaLCIiymQ1FdJ/IrHJ7x4+fAg3NzdLpYuIiLKiqHAMbQVULVsoZlH9Ch6AKTJDk0VERJkkqDDPPyEBRe/eveNUbcss2v/8849uFkVERFYsKhyvyFdBMZ+YRd0a5QfC72ZosoiIKJMEFZ6enjE1Fe7u7nBxcYlZ5+joiNq1a+ONN95Im1QSEVHWEBWOMcuBnl6hKP7vXKlHLkfiwZ1ANOuQ0YkjIqIMDyrmzZun//r6+mLEiBFs6kRERAmoyDD8uAVo0TkCxf9dtuFwEA6dCEazccwwIqLsKsV9KsaMGZM2KSEioiwvIjxI/3Vydo1ZJs1lDcaoDEwVERFliqCiatWq+Pvvv5EzZ05UqVIl0Y7aZocPH7Zk+oiIKAsxhEUHFc6uOeIFFQpQJsAmxYMOEhFRdgkq2rdvH9Mxu0MHNoolIqLEhYf+G1S4PBkN0NlZggrpb2EA7J/0xyMiIisLKmI3eWLzJyIiSkoeLyec+xJwKVo4ZlmbesVR22uPnhgPYFBBRJQdpbhPBRERUVJsTAbkkHnvHJ70qcibJyfyFoweGYqIiKw4qJC+FE/rRxFbYrNtExGRdTh19hI6DAcObTfB/d9lu088xNczgaXtGFQQEVl1UDFt2rS0TwkREWV5YaHBCA4HnFzMIQUQYrDBoStSUxGWoWkjIqIMDip69eqVhkkgIqLsIjwsRP91cH4y+pOzi+u/HbVZU0FElF09U5+KqKgorFy5EqdPn9bNovz8/PQIUfb27KJBRGTNDOGhcHIAbGKN8uTk5IooExBpCGZHPiKibCrFUcCJEyd0AHHnzh2ULl1aLzt37hzy5MmDNWvWoEKFCmmRTiIiygJyuduhTWUAttJbO5q7hwdK5geM4SEMKoiIsqkUz0LUr18/lCtXDjdu3NAT3cnj+vXrqFixIv73v/+lTSqJiChLqFzCE9/1BmD3JKjwK+WLbR8BLo4qQ9NGRESZqKbi2LFjOHjwoB4Rykz+P2HCBNSoUcPS6SMioizk6o37uHwKaNTpSVBhNNnj8m2gmCEYDhmaOiIiyjQ1FdLk6e7duwmW37t3DyVKlLBUuoiIKAvaevAqPl4et6biQYARjT4Fbt66naFpIyKiTBRUTJw4EYMGDcLy5ct1Eyh5yP+HDBmCzz//HIGBgTEPIiKyLgZDuO6oHTuocPp3JKjw0OAMTBkREWWq5k8vvvii/tu1a9eYCfGUim4n27Zt25jnsk5GiSIiIuthMBjgLEGFzZOvFyfX6KDCEB493CwREWU/KQ4qtmzZkjYpISKiLM9giICTox3w749OwsnFI3pdWGgGpoyIiDJVUNGwYcO0SQkREWV5Het6oVGxJxPfCXunHHi/PVAwj1OGpYuIiDJZnwoRHh6O/fv3448//tBzU8R+pNT333+PYsWKwdnZGdWqVcOOHTv+s2r9gw8+QNGiReHk5ITixYtj7ty5z/I2iIjIworns0H1UnGDCulfMbA5UNCbQQURUXaV4pqKdevWoWfPnnjw4EGCdSntR7F06VLdwVsCi+effx4//PADWrVqhVOnTqFIkSKJ7iN9OWT0qTlz5ujRpmTUqcjIyJS+DSIiSgOz196EMcKAtzrGWmjnjKlrgRaON1CuIrOdiCg7SnFNxcCBA/HSSy/h9u3bMJlMcR4p7Zg9depU9O3bV0+o5+fnh2nTpqFw4cKYMWNGkgHNtm3bsHbtWrzwwgvw9fVFzZo1Ubdu3ZS+DSIiSgPHLwfj3G1T3IV2zli0Czhz6Q7znIgom0pxTYXUDAwbNgz58uVL1YEjIiJw6NAhvPfee3GWN2/eHLt37050H2leVb16dUyePBkLFy6Em5sb2rVrh08++QQuLi5JNpeSh5l5qFuj0agfGcF83Iw6vrVj/jP/rVlaX//hBiO8PN3ivr7JTo8IFRYWZvX3Pd5/Mhbzn/lv7YxpWPZMcVDRpUsXbN26VfdlSA1pPiU1G/GDE3l+507iv2ZdunQJO3fu1P0vVq5cqV9jwIABePToUZL9KiZNmoRx48YlWL5hwwa4uroiI23cuDFDj2/tmP/Mf2uWVtd/aHgEPHI46xplM1tlgJM9cPfO7TjLrRnvP8x/a8brP3tKcVDx3Xff6eZP0qG6QoUKcHCQAcmfkInxUsI814WZeY6LxEgTK1m3ePFieHp6xjShkkBn+vTpidZWjB49WtesxK6pkCZWUiPi4RE9zGFGRInygWrWrFmC/CPmf3bH6z975//a74B83l5o3br1k4XKhOljAGcXl7jLrRCvf+a/NeP1nznOwerVqzNHUPHzzz9j/fr1ugAvNRaxAwD5f3KDCm9vb9jZ2SWolZDmVUk1rfLx8UHBggVjAgohfTEkEJGZvUuWLJlgHxkhSh7xyZdpRhfoM0MarBnzn/lvzdLq+v+hny2Qr7QcIM7yX95xgEuRArznpXH+U/Iw/zMW8z97SnFH7Q8//BDjx49HQEAArly5gsuXL8c8pHlScjk6OuohZONXgcnzpDpeywhRt27dQnBwcMyyc+fOwdbWFoUKFUrpWyEiIktSCv6B4TBEJSws5/R0gbM9+5EREWVXts/Swbpbt266IJ9a0ixp9uzZuj/E6dOnMXToUFy7dg39+/ePabokw9eade/eHblz58brr7+uh53dvn073n33XfTp0yfJjtpERJROTBHo/DWwcOPtBKvemWfE5F/O81QQEWVTKY4MevXqpeeXsAQJTmQYWan5qFy5sg4SpBOfTGwnZNhaCTLMcuTIoWsy/P399ShQPXr0QNu2bfHNN99YJD1ERJQKUeEwGAEn54RNTsONtggIejISHxERZS8p7lMhIzbJkK7Sr6JixYoJ2oRKx+mUkNGb5JGY+fPnJ1hWpkwZjhpARJRZg4pIwMnROcEqJ0d7hEew+RMRUXaV4qDi+PHjqFKliv7/iRMn4qxLatQmIiKyAqbomgoZ5Sk+JycHGGQlERFlSykOKrZs2ZI2KSEioqwtKhw96wMlffMnWFW+mDtCgh5nSLKIiCgTBhVERESJigrHiDYASiYcje/1VoWBgCcj9xERUfbyTEHFgQMHsGzZMt2JWkaDim3FihWWShsREWUhJmMoZm4EOhWKQPy6ist3TXh4LQTVMyhtRESUyUZ/WrJkiZ4vQoZ0XblypZ6ZT/6/efPmOJPSERGRdYkIC8Knq4BbDxKO8rRmrz8++S0sQ9JFRESZMKiYOHEivvrqK/zxxx96Aruvv/5azzHRtWtXFClSJG1SSUREmZ4hLLp5k7OLW4J1Tk6OMBgVYIrKgJQREVGmCyouXryINm3a/Psl4YSQkBA96pNMXDdr1qy0SCMREWUB4WFB+q9TokGFsx4ZCibOVUFElB2lOKjIlSsXgoKivzgKFiwYM6ysTEgXGhpq+RQSEVGWYAg1BxU5EqxzdnbWc1ggik2giIiyoxR31K5fv76efK5ChQq6ydPgwYN1fwpZ1rRp07RJJRERZXo+3s7Y+iGQL1++BOvqVSmKfOHRI0QREVH2k+Kg4rvvvkN4ePSXwujRo/WM2jt37kSnTp3w0UcfpUUaiYgoC3CwjUQpH6mWSFhTUbhgHhQux6CCiCi7eqbmTwUKFIje2dYWI0eOxJo1azB16lTkzJkzLdJIRERZwPHTl9DwE8AYlfD3qhOXAvHWXAYVRETZVYqDCiIiosQEBgTi/B3A3ilhR23/UBP+OCIdtdn8iYgoO2JQQUREFmEID4OTA2Bj75JgnZOzK6JMgDGcs2oTEWVHDCqIiMgiDIZQOEnLJzvnRIMKvc2/w84SEVH2wqCCiIgsIoczUNU38aDC2SWHXh/x7wR5RERk5aM/ERERJaZ+xdyoP1B+rkoYVJQq4YtzXwLwcGDmERFZa1Ahw8Um14oVK1KTHiIiyqLu3n+MRzcBv0RqKpStE0LCAZeIUNhlSOqIiCjDmz95enrGPDw8PPD333/j4MGDMesPHTqkl8l6IiKyTqu3XcLgnxJv/uQfHIlSw4FzF69kSNqIiCgT1FTMmzcv5v+jRo3SM2nPnDkTdnbRvzdFRUVhwIABOuAgIiLrZDAY9OhPsE341eLk4h69TXhoBqSMiIgyXUftuXPnYsSIETEBhZD/Dxs2TK8jIiLrDSqcHRNv3OT47yzbhrCQdE4VERFlyqAiMjISp0+fTrBclplMJkuli4iIsphwQwSckggq7J1ywN6ONRVERNlVikd/ev3119GnTx9cuHABtWvX1sv27t2Lzz77TK8jIiLr1KpaDtTxjW7mlICdM/o2BPLnckzvZBERUWYMKr744gvkz58fX331FW7fvq2X+fj4YOTIkRg+fHhapJGIiLKAas/ZAkW8El9p54IxnQEUip4Ej4iIrDyosLW11QGEPAIDA/UydtAmIqIF628hp5cH2rVLJC8c3PHbfsDP9hrKVmVeERFlN880o7b0q9i0aRN++eUX2NjY6GW3bt1CcDBnSiUislYbjwTi2NUk+tY5eGDGJmDn4cvpnSwiIsqMNRVXr15Fy5Ytce3aNT3SR7NmzeDu7o7JkycjPDxcDzVLRERWRikEhhjhnsMt8fW2DvBwtUVQEH98IiLKjlJcUzF48GBUr14djx8/houLS8zyjh076gnwiIjICkWFIzhc6R+ZkuLu5oigYA4pS0SUHaW4pmLnzp3YtWsXHB3jjuBRtGhR3Lx505JpIyKirMIYgKBwIMfTggpXJwQFc/I7IqLsKMVBhcxFITNox3fjxo2n/kJFRETZmDEQe8YCqkyVJDcZ9XJR2BsfpmuyiIgokzZ/kj4U06ZNi3kuHbWlg/aYMWPQunVrS6ePiIiyABXhDztbwME1Z5LbFC7gDR939qkgIsqOUhxUyPwU27ZtQ9myZXXH7O7du8PX11c3ffr888/TJpVERJSphQTcQ+F3gOOXkw4alu4IQv+ZAbpTNxERWXnzpwIFCuDo0aN6ONnDhw/r5lB9+/ZFjx494nTcJiIi6xHsfw8mBbi5505ym1CjA07fknHJQwCHHOmaPiIiymRBhZDgoU+fPvpBREQU6H9PZ4K7V54kM8PdwxOBYdGduhlUEBFZefMnOzs7NG7cGI8ePYqz/O7du3odERFZnyD/6A7Y7jnzJbmNh4cXgsOjO3UTEZGVBxVKKT3pncxVceLEiQTriIjI+ng4GdG5JuCUwzvJbfLkzYuS+QGT4XG6po2IiDJhUCGjPf32229o27Yt6tati9WrV8dZl1Lff/89ihUrBmdnZ1SrVg07duxI1n4yV4a9vT0qV66c4mMSEZFllSzogG97ATaOXkluU6VSWawdCdhGcQQoIqLs5plqKqSZ09dff40vvvgC3bp1w6effvpMtRRLly7FkCFD8MEHH+DIkSOoX78+WrVqhWvXrj11v4CAAPTs2RNNmzZN8TGJiMjyzl+8jo3HATh4JLmNUbni2FUgPOgBTwERkbUHFbH973//w7p16/S8Fa+99lqK9586daoeOapfv37w8/PTr1O4cGHMmDHjqfu9+eabeijbOnXqpCL1RERkKZv3XcDnvz89qAiKcESrycCVK5eY8URE1h5UFC1aNE6H7EaNGmHv3r16Ru2UiIiIwKFDh9C8efM4y+X57t27k9xv3rx5uHjxop5sj4iIMofg4BB4uNoCtg5JbpPDK6/+GxTAWbWJiGDtQ8pevnw5wbISJUro5ksyAlRyPXjwAFFRUciXL+5IIfL8zp07ie5z/vx5vPfee7rfhfSnSA7pVC4Ps8DA6FFHjEajfmQE83Ez6vjWjvnP/LdmaXX9BwQFw93V8amva+PkAUd7wP/xfau9//H+w/y3Zrz+M15a3nufaZ6KxEhHa6nFSKn4nbulb0ZiHb4lAJEmT+PGjUOpUqWS/fqTJk3S+8S3YcMGuLq6IiNt3LgxQ49v7Zj/zH9rZunr/9GjADg72mLt2rVJbuNiug8PF+Di+XMIfcp21oD3H+a/NeP1nz0lK6jIlSsXzp07B29vb+TMmfOpozzFn78iKfJa0owqfq3EvXv3EtReiKCgIBw8eFDXiAwcOFAvk9m8JQiRWgsJEpo0aZJgv9GjR2PYsGFxaiqk34Y0s/LwSLrtb1pHifKBatasGRwckm4qQMz/7IjXf/bM/7K3ciDSPhdKtG6d9EYR/vig/RuoWrMIfJ+2XTbG65/5b814/WeOcxB75NZ0Dyq++uoruLu76/9LZ2pLcHR01EPIypdbx44dY5bL8/bt2yfYXgKA48dlaJG4w9Fu3rwZy5cv18PSJsbJyUk/4pMv04wu0GeGNFgz5j/z35pZ+vov6R0K5CorL5z0Rna50E3G18hv8/TtrADvP8x/a8brP3tKVlDRq1evRP+fWlKDIKNGyUR6MpLTrFmz9HCy/fv3j6lluHnzJn766SfY2tqifPnycfbPmzevbnYVfzkREaUjpfDuggDUfz4E7Z420retHebtcEK+IhfRun46po+IiDJHUGHu3JwcKWlSJHNcPHz4EOPHj8ft27d1cCDtcc19M2TZf81ZQUREGSwyGPsvAuUqPxkZMCnbz9qioP9dWGfjJyIiKw8qvLy8/nO2bHMHa+lQnRIDBgzQj8TMnz//qfuOHTtWP4iIKAMZAxEYBrh7eP7nph45nBEcGpYuySIiokwWVGzZsiXtU0JERFmTMRDB4VJT7fWfm7q7ueD2ff90SRYREWWyoKJhw4ZpnxIiIsqSTIbHyOMB5PLO85/buudww7kr99IlXURElH6eeZ6K0NBQ3d9BZsaOrWLFipZIFxERZRG2UcHYLS1RK5f9z22HvlIBtjfPA6Yo3XGbiIisNKi4f/8+Xn/9dfz111+Jrk9pnwoiIsraIkIe4tZ9oLBNDvxXmODo6gVlG925G47/3QeDiIiyBrm1p8iQIUPw+PFj7N27Fy4uLli3bh0WLFiAkiVLYs2aNWmTSiIiyrQuXryAumOBgPD//p3qj70PUfUD6YcRkC5pIyKiTFpTIZPNyUx8NWrU0HNHyPCvMjOrDCU7adIktGnTJm1SSkREmVJQwEP91z1nvv/c1sXNA/6h0Z27iYjIimsqQkJC9KRzIleuXLo5lKhQoQIOHz5s+RQSEVGmFhTwCE4OgINr7v/c1t0zFwxGwBgaHYgQEZGVBhWlS5fG2bNn9f8rV66MH374Qc96PXPmTPj4+KRFGomIKBMLDgyAhwsAh/+e/NTdMzrwCHp8Nx1SRkREmbb5k/SpkJmuxZgxY9CiRQssXrwYjo6O/zlZHRERZT+lCjpgcAsJKv6747V33gLoWF06agelS9qIiCiTBhU9evSI+X+VKlVw5coVnDlzBkWKFIG3t7el00dERJmcX0Eb+DWSb5Qc/7ltnvyFMf11AG4cKZCIyKqbP8Xn6uqKqlWrMqAgIrJSm/dfxrIDzsmbd8LBA6sOAndv30yPpBERUWatqVBKYfny5diyZQvu3bsHk8kUZ/2KFSssmT4iIsrkNh+8jVv3bPFScjZ28MSIn4EZpS6gWf20TxsREWXSoGLw4MGYNWsWGjdujHz58sHGxiZtUkZERFlCUEgYPHI4JW9jBw+4OwOBgf5pnSwiIsrMQcWiRYt0bUTr1q3TJkVERJSlBIUYUCBvzuRt7OCpg4qgIE5+R0Rk1X0qPD098dxzz6VNaoiIKEsGFe45XJO3sb2bHn42OIijPxERWXVQMXbsWIwbNw5hYWFpkyIiIso6TFGY3S8Kb3Uum7ztbWzwafccaF/LPa1TRkREmbn500svvYRffvlFz6rt6+sLBweHOOs5qzYRkRWJDIKnVFLkTP6Q4pVL5gKcDWmaLCIiyuRBRe/evXHo0CG8+uqr7KhNRGTtjIFoMB748J3HaF4rebvM+jsSwaFXMaxlWieOiIgybVDx559/Yv369ahXr17apIiIiLIOYyCuPwLsHP974juzm/52uHLjUZomi4iIMnmfisKFC8PDwyNtUkNERFmKMfQhDEbAwytXsvdxd3NFUEhEmqaLiIgyeVDx5ZdfYuTIkbhy5UrapIiIiLKMoMd39d8cHikIKtxzICjMBJiMaZgyIiLK1M2fpC9FaGgoihcvDldX1wQdtR89YpU2EZG1MBn80aQckDtPgWTvkzdPLni6RDedglPuNE0fERFl0qBi2rRpaZMSIiLKcrw9gEUDAPgUTvY+HZtVQsdCGxlUEBFZa1BhNBqxdetWfPTRR5wAj4iI8ODebfxzEmjS3DPZuREBN9y6DxSNCIAN85CIyPr6VEhTp5UrV6ZdaoiIKEs5fOws3pwjXxDJH8Dj+KUQ1B0LRIQ8SNO0ERFRJu6o3bFjR6xatSptUkNERFlKUFAAcjinLKhw94ruRxH4bydvIiKywj4VJUqUwCeffILdu3ejWrVqcHNzi7N+0KBBlkwfERFlYoEB/vCQTtcOyW/+5OGVV/8N9r+HPGmYNiIiysRBxezZs+Hl5aVn1ZZHbDY2NgwqiIisSHBwMNwlqLCP+wPT0+T4N6gI9GfzJyIiqw0qLl++nDYpISKiLKdVNTdU9c4hvyolex83z3wY3hrIw3lUiYisN6iITSkVU0NBRETWp0ReI0qkYOI7YePoieFtAHhFf4cQEZEVdtQWP/30EypUqAAXFxf9qFixIhYuXGj51BERUaY2c801LNppStlODp6YtRk4cuJiWiWLiIgye03F1KlT9TwVAwcOxPPPP69rK3bt2oX+/fvjwYMHGDp0aNqklIiIMp09pwNRrFAKu1s7eOCX3YBdnmuoklYJIyKizB1UfPvtt5gxYwZ69uwZs6x9+/YoV64cxo4dy6CCiMiKBIVEwD1H8jtpa3bOcHexQVBQUFoli4iIMnvzp9u3b6Nu3boJlssyWUdERFbCZERQmAnu7jlStp+NDdxdHRAcEpJWKSMiosweVMg8Fb/++muC5UuXLkXJkiUtlS4iIsrsjIGQYTo8PZM/R4WZu5sTgoJD0yRZRESUBZo/jRs3Dt26dcP27dt1nwoZ+Wnnzp34+++/Ew02iIgomzIGYsNoAH5VU7zrxD5FYW9iTQURkdXWVHTu3Bn79u2Dt7c3Vq1ahRUrVuj/79+/Hx07dkxxAr7//nsUK1YMzs7OeobuHTt2JLmtHKtZs2bIkycPPDw8UKdOHaxfvz7FxyQiotRTEQHwDwGibFPY/AlArly54OEQzNNARGTNQ8pK4X/RokV6Ru3Dhw/r/1epkvIxPKTJ1JAhQ/DBBx/gyJEjqF+/Plq1aoVr164lur3UjkhQsXbtWn3sxo0bo23btnpfIiJKX4bg+yg7Ejh6IeUdrudu8EfPrx+mSbqIiCiLBBWWIsPT9u3bF/369YOfnx+mTZuGwoUL69GlEiPrR44ciRo1auj+GxMnTtR/f//993RPOxGRtQvyv6f/unt5p3hfZeeCGw9NQJQhDVJGRESZtk+Fra3tf86cLesjIyOT9XoRERG6tuG9996Ls7x58+bYvXt3sl7DZDLpIQmlGj0pBoNBP8wCAwP1X6PRqB8ZwXzcjDq+tWP+M/+tmSWv/8cPbum/rh65Uvx6rm45EBQOGEMfAM55YS14/2H+WzNe/xkvLcueyQ4qVq5cmeQ6CQJk/gqZCC+5ZKK8qKgo5MuXL85yeX7nzp1kvcaXX36JkJAQdO3aNcltJk2apDuXx7dhwwa4uroiI23cuDFDj2/tmP/Mf2tmievfcH6//nv63FUcurU2RfsGh4QhKAzYtul3hNj6wNrw/sP8t2a8/rOnZAcVMsFdfGfOnMHo0aN186MePXrgk08+SXEC4td+SGDyXzUi4pdfftGT7a1evRp58yb9K5ekb9iwYXFqKqSJldSISGfvjIoS5QMl/UMcHBwyJA3WjPnP/Ldmlrz+b2zZhX6NgUZN2wC5q6do3+MRG1Bz5240qFsFNrlSPnpUVsX7D/PfmvH6zxznQMrOmWJIWXHr1i2MGTMGCxYsQIsWLXD06FGUL18+Ra8hI0bZ2dklqJW4d+9egtqLxDp4S1+MZcuW4YUXXnjqtk5OTvoRn3yZZnSBPjOkwZox/5n/1swS13+xvPYY30XaMuWWF0zRvlUrlcVPb8n/QlO8b3bA+w/z35rx+s+eUtRROyAgAKNGjdIT4J08eVLPTSG1FCkNKISjo6MeRSp+FZg8T2zG7tg1FL1798bPP/+MNm3apPi4RERkGafOXsGSPVJCSPnkd+EmF/x9AggNvM/TQURkTUHF5MmT8dxzz+GPP/7QBXvpRyFDwKaGNEuaPXs25s6di9OnT2Po0KF6ONn+/fvHNF3q2bNnzPZyXHkufSlq166taznkIcEOERGlrz1HL+OHvyWoSHlT0sBwe7w2A7hx7UqapI2IiNJXsps/yShNLi4uupZCmj3JI6kJ6pJLZuZ++PAhxo8fj9u3b+saD5mDomjRonq9LIs9Z8UPP/ygR5d6++239cOsV69emD9/frKPS0REqXfj1m0UyO0A2DmneN/cBUrDwQ64efUMSvFkEBFZT1AhNQTJ6UCdUgMGDNCPxMQPFLZu3Wrx4xMR0bO5ePUuihfJKyNupHhfu5x+8M0DXDx3Co15AoiIrCeoYE0AERHFiAjAhVvhaFrf99kyxcEDxQu44NKVJ7XRRESUdT3T6E9ERGTlAs/it8GAa7Umz/wSg14qC6ewMzKW+DPVdhARURYd/YmIiEgLOgufnIBngUrPnCGVq1aHX74QIPwuM5WIKItjUEFERCm2cf1faDIBgEfpZ869a8F50WUaEHL7KM8AEVEWx6CCiIhS7NzZ07CXbxD3Es+ce+75ymH3eeDy6d08A0REWRyDCiIiSrGLl6+jeCH3ZxpO1ixnkerI6QZcPHOMZ4CIKItjUEFERCljisLFG49RwrdA6nLOzRfF89ngwsVzPANERFkcgwoiIkqZ0Gso42NC1crlU/kNZIfKpbwRFXqPZ4CIKIvjkLJERJQygWfx+SsAaryQ6pwbP6A+cGMVEGUA7Jx4JoiIsijWVBARUaKCru7Emy3cEXxjX5zlty7sx9qjgHIvleqci3AugeNXTVBBF+IsP7L6A4zpnh+IDOPZISLKAhhUEBFRovaun43f9wfj6Iav4yzfsXMnPvgVsPEok+qcuxKYCy0+B+5ejBu4zP5xFn786y4i7h3i2SEiygIYVBARUaLOn/kHJfMD9fL9E2f5xYsXUSK/HeDik+qc8/WrC1sb4MKp/U8Wht7EuLYPotNwbBPPDhFRFsCggoiIEnXq7CVULAKcPHkSKvhKzPJLV++geBFvwMYm1Tnn6F0ehXMDF8+djFl26+gSHLsK5PUATh7Zw7NDRJQFMKggIqKEIkMwoGEA2tV0RbNJwOkd86KXG4Nx8VYoihcraplcc8yJ4j5OuHjpcsyi1b8twpjfgPc6OMHPmyNDERFlBQwqiIgoIf/jKFsIaNbpbZTyAf5etyJ6edA5fNMTaNuygcVy7X/tS6FN+aDoJ1ER2LL7BJpUL4SX29ZGBa+LgDLxDBERZXIMKoiIKIHTB9bhpa8Bg2cdNK3pi817TgNR4Xo42QpFgPzPVbdYrjWoVxO1igYC4Q8QdGUj9p2PRNMXWuBCUFG8tygIKvhJLQYREWVODCqIiCiBf47sxoW7gFO+6mjyQiscvBiFwIt/Yde2jegyzTLDyZrdCMmHAfMAw4Pj2PnXXNjbAbVbvoGoHKXx0w7g7rntPENERJkcgwoiIkrg1OkzKFvYAXAthJot+uH71wHHB3/j1KkTeBAsw8laLqhwyFkaqw4CV07vwQuFT2PtR3nglL8mildsAkd74OThrTxDRESZHIMKIiKKS5lw6vxtlC1RUI/w5OBdBW3rFYLzww24ePkqihdwA+zdLJZreZ+rCTcn4OLRdUDAaZSu3lYf1z53JZT2AU6dOMozRESUyTGoICKiuEKuwNk+ElUqV4x+bmODA/7V0ebj87hw9R6KF81v0RyzcS+O4vls8MeGnSg3Cnjs9m8ncHsXlC2WC9euXeUZIiLK5BhUEBFZMxlZSam4yx4fw8IBQOsX28csKlShHY5cAW4+AiqUK23ZNNg6oGRhT6w6qODjBeQs3SFm1eRhL2DKSwGAMTDuPqaohOkmIqIMw6CCiMgaKQX/w18Dy3MBx0bHWXXr7E6cvgkgZ6WYZT4VX4JfQRt0qw20bdPS4sn5eng91C4BPdIUHD1jlkvTq0fBgPH+kVhpNwEbagF/loXhxjaLp4WIiFKOQQURkZWxj7iNGcMqoVqrIThzNQA7V08DIvxj1i9fswlDFwHwLPdkJ4ccqOxXGFP+lJGfLFxTASDY/jnsvQA90lRsgfYlUX4UcPLA+phlj04tx9I/D2H7vjOoW78RNs54CYgMs3iaiIgo+RhUEBFZkbNbv8ZX49/GjJVnMOmdRrAr/wG6TjPg2NqJMducOndZ92WAnXOcfXv2fQd1/XLAxruGxdMV5P48Kvi6oGabIXGWexSugwI5gVP/7ItZtviHcTq4qfLab2hfvyBe/2A53mpXAIHXnmxDRETpi0EFEVF28vgf4NSUxGehNgZj5MhRyJnDDn//Ph9dP9yCki98gHp+jpg798fofYyBOHklCOX8iifYvVLLEVi2KwhwzGnxZBes3BXrj4TCMVe8oWpdfFCuiBNOnjqjn0Y+PosFf5zC6+0rwr1UJ3w8/wr++PEdHDzrj+/G9Uj8xQ0PgWMfJuyXQUREFmNvuZciIqKMdmplfxRWe+CeqxqQv0nclTdW4Yc+Jpx36Y48FbpHL7N3Qd9X2+N/Hy/DRyd/g5tHbly+B5QtXw2Zgo0NypYshL3HruigZ/1Po/EwGOj+5rjo9bb2qNz5G3xz9xi8QrYDobcA1wJxX+P0FzD+8xlCwhzhVfvjDHkbRETZHWsqiIiyCRV6B/0+24MXvwDWLBibYH3Y2QUo5G0Pg3fzOMtf6DEJ+b2AlQs+hW3gcczsA1So2QyZRfNGtdGxWhTgfwLbN69Fx7o5kbP0k5GpRJ0XB8GvIKCu/Bx3Z5MR7437FkUHA59NnZ6+CScisiIMKoiIsomj66fiyn3Ar5A9vlm0Eyr8QZyA44XBm7D0TAVE2HjE2c/OsziWT2qGvpX+gdO9P/FiVSBHwdrILKrUaYae9eUNjsJnXQ2YOP4jXYMRR8E2+HKdM8Z8+mWcxXeP/YzF20PQoYY91uy6B+OD4+mbeCIiK8Gggogom1i5/GfUKG6Hd98bg1M3FI5vmBKz7ui6L3WzptrNeye6b+F678IQCYz6aiNmbc+h+zJkGjkrYdpfwPc/rUOg0Q3Ofn0TbmPnjIKlamP5tjsw3n8yA/ey+VN0R++Jk79GiAHYtmJy+qadiMhKMKggIspK7m4Ddr8GBJ6Nszgq4CLW7LyJji2qo3jD4ahV0h6/LJoXM0HciuWLUbOEPQpW7ZX46+Zvigl/5cLCnYC/KX/CmoCM5OGHTSdt8OkqYPujhoBD3JoWs9Yvj9CBw9bfPtfPVcgN/LLuJF5uURZeFd9E00rOWLX69wST5kVdWQbsfwsIvpIub4eIKDtiUEFElAUY/S9gxYS6UJsaYd6CRfhiePPoWaX/ZXv9V/z8NtCxxxDd+bp7x6a4dec+8OggIh+dxOqdt9GpVW3A3jXxA9jYokev/vq/hX3jjcCU0eycUPa53LrfR8uek5LczKN4KzSr4ooVq/7QnbqDTsxCaR+g2+sjAFs7vNOnA3rUDAAeH47ZJyrwCjq99ApWLZkJ4+oy2Dm/N5QxOJ3eGBFR9sGggogog5mOfgzs+x8QGZrISiM2/PAaGtYshfen78FluxeQr1RTfL3iGk6te9IZO+Lizyj7XE54lu6kn3d5cxIWSIxwcTYiLy7GO82Btt2HPzUdfs3fx8JP26HzG0/mrMgsBr07AfOnDoWDd8WkN7KxxWvd2qNM3mDg3g543F2MuYPyo0DVV/XqKi0Go05JAFd+idll3qcdcfpGFGq3G4n9twrg5WEL8HKjvDi39dvEjxF0EdjSGrj5p8XfIxFRVsaggogojRkensWh30YAUREJ1gVf24FGL3+CY5t/xM1fG0CFP4xZZwq7j8/+VwZ9Ri9C8+q5sXfzCjz38ka0HrQKzSq7YcSHnyEq+AYi7h9F9YEnsPNhPcDOUe9rk6sK7ttWxNKfF8D51s94o40PcpZq+/SE2ruh6dur4ZinEjKbQrX+h4odp/7ndg27jMbglkDg9rcwbsElBOZ9BbB1iF6ZuxZ+PpgHgz7+Qddk3DgwB5/9dBTvv14T+Rt9jueHn8Pmnz+CvW0UWr88CBtndItTGxR0dTvOL6iJzZv+wsiBLyc6i7cx4Cr2Lx2SeIBIRJSNMaggIkotpWC4sSXRQqbUNIwb0ABt+32Jvb8MTLB61qR+CDYAxap3Q/sPD2FUj1K6SQ78j8P4Z00cPXkJCz5ph7GLbsGrTMfonRxyYOKU6bh4JxJzx3fA5mWT9WtUbhbdfMnspksbDF1gQLvxV3HJrrVuApTteVXAwfslUG/4aSzbD7j49XuyzsYGPn7NsHpvMPxPL8cnHw5G2UL26PnBiuj1tvYo1XI8Fq2/jLfaFcWcn36F2toGiPDHw5O/4aX2TTDqJ394l2yORVuDcXDFqLjHViZMe7cxOvT/GutmJD4RnynkOlwi2HeDiLIfBhVERP926o26tzdBJ15NgoV/xgBnvk64XilsmfUS/Ko2wYwRVQFTZJzVOxcNwIKN91D9OVusWT4HCDgVs+7xmVWYueochvd8Hh7NlmDm5KFYs+cR+ncui98n1YBT5E388tMPuvYg5tf2f+Wv2gvTRzyPFoUOYeXK5Whe2RU5fFvE2aZSy3fhV9AWp24C+aslMmJSNhWeqxkeBAHNahaEQ+6ycdbV6zAc7i7AnzN7Y0y7EHwzZQxs3QrG2cbGtQCGzziLRVN6w+bOemyYWBodOr8EBRvMWrAaFV9bgxdruGHS1JlQhscx+6nzP+Dc+cuoWcIWo75Yhcfn18V53cjAK+jXvhzGfjAENw/OTZhwYyCi9g8GLi9M/DqMCkfU7a1AZEiq84iIyNIYVBBRykhhx/CkiU6GiQjAld2zcHrdeODGauDB3uj27oHnEXV3N+4eXQzDmbnAyYn4c2pLfNm/FD58OS9+HlsfV3ZMBcLu6ADg9qH5+G5weTSqXhhlKtbBrV/r6VoCM/8LG7BvWmmo4+MxZOgQ/DKu7pOmLUph/fRO6P3Bb6hf1hF7Dp2B6eCQJ2n0P4GwM/MwsG1eLF+9ARNeMgH7+kU3qVEK300cCG93G3QdMk9vXr3LVKz8aQoOnA/D7C0KUY02wabk/5LMghf6L0FuLzf8ftCIjm2bJ6iJsHHKiXff7oFhParBtUDmmXcirdXp+CFeapgPQ0cnHD7WIU9VNKuWC1+sCUOBErXg2+j9xF/Ezgn2z89FYOnJeHfePeTN6Yzlv++Ct9+Let27oz7CvnNG7Fj0TvT2oTdgc3QUZg0qiF/X7ECxvLY4u/rNJ7VXkSEw/N0ebvbhyO1uh5de7Y8ru3+IOVzEw9MY+fJz+ODTb4A9PXF8XiNEBV1/8pm7vgKHpj0H3/KN0bW+F36d2Awh13fpdcr/JI6ufBczhpbHR6/kw7eDK2D7rM7A6akIPfMTHp9eAfXwEBB8GQg4A9zbDlxbjqOrP8Tjc3/q2rQMpUyA4VHGpoGIUk9lsOnTpytfX1/l5OSkqlatqrZv3/7U7bdu3aq3k+2LFSumZsyYkaLjBQQEyM8/+m9GiYiIUKtWrdJ/ifmfLCaTUkGXlDKGWO715JGImwfmqqHtc6tNM7spFWWMuzIyXKldr6kdH0NtmN5Zqah417AxWG2c3knNfreSCriwLpHjRqmw61vV1mUTVMTj80pFGuKul+OF3lFB535Tm2b1UhP7lVH/a5lTTehbUl1Z/apSJyerg0v6q097F1UNykD5eEG92QRKLYb6812oasWgKheFKpgzep2kU9YNagHVvrqdeq2Rq6pUBOqF8tHL/3rfVRXICVW7BNQXb/mpv6a+oNRiG/Volo1aOqG5+n1aJ1WxCFTbqrbKdOIzNfe9aqpwbqiRXfIpw6MLynRgkOpSE+rLN59TpvCHyrShgX7dgMNT9XuJ+L2aUj/bKnV/X3T27B2kxnWGOvXnaKWuLldHJkDtnN0lQTYF3z6mjMF3knUqHx+cqgY2t1WGOweTtT3vP0qd/etD9U5LexX14Eiy8iz41lFlDL4bd2FUpJr+lo86PMlJqdBbav6oSmpCVyh14w+92nRikr4W1JFR+rq/vLSlfh555EO19pcvVbe6TuqdFjZKXftN3T62TL1YzUFfm/t+6a/Ct3TX13HrKvbq4PIR6qu3SqrQeVCmpe7qz2kd1MgueVVpH6jn8kIdneyuTIugr1P5TPRs7KZaVbJRYzpFX+PLB0d/Fop6Q9V4Dqp8IagDn0Sva1c1+rPSsYa9mjm8krq2+WOl/hmnji9qrz7oXkS92SqXmj6sujq4fJiKuLlVqYgA/V7iMAYrFXBWRd7YoEz+ZxNmXpRRXd7+pZr2Vgl1dsP4BPedyKCb6sv+xdWSd2yUOpfw+zwq5I76dlA5Nfl/JVTYncOJn6Ak7mXPdP2H3df3IEobvP9kjnPw888/p0lZOEODiiVLligHBwf1448/qlOnTqnBgwcrNzc3dfXq1US3v3TpknJ1ddXbyfayn+y/fPnyZB+TQcVTGEOVCrsX/TcFN+kY8QugSR4nWKk7m1XEjc1KGR4lb5+IQKVCbkR/ed07oCLuH0s8jcZQdXPvd+rixjFK3d6oVPC1BNvFualFhqnI2zuU8eYWFXlnl1IPDysVcE4XGOKn+e6+r9QnvYqo97v5qMMrRylT+KOE7//xcWW8vkEFn12i1KWFKuL0TGWUwnN8kWHqwqYJav4HddTicY3V8skvqlubhil1epq6f2imCrn4h1KP/1GPjy9UB+d3VGplEbVxNNQr9ZzV+U0T4qQv0v+cWvZpQ/VSbTs1sU8xdWTVe0qF3o5eKe897L6KurNTXdn2uQrd0V+pDfXU/5o6qB4NXNSGGa+oSP/o9EUFXVM/vV9NlcwPVbckVKFcUOd/el6p8IfRLxX2QP35aXkVuRBqej83XRgZ37OIivC/rNc/PPOn6t/SQy+vUBjKrwBU0O8NlLqzVYXeOqD++KaL6t/CTZXIB3Xpq+hCzWv1oDrWdFSdazuq9tVt1fvto5dveA+qSG6odtVs1LD2nqpLLVt1anL0utaVoV6saqe+GVRenfnrIxV57XelLi5Q1zd/oJZMaqt++6KT2rFwgDq3aaIKP/+rUg8ORBcU/r0OTME31OMj05Xa1UP5L6+s9i1+Q5nkOjF7eFBtnlxOF9gkgPisTyEVfvfov/kZpfYu6qcLcJLfxp+gIv6qH31Ni/AH6q8x+XWBcNknz+tgJWjn4JiXNkUE6UJfm6p2KuDnokotzaFUWLzC6rOIDEv2pvxS//dzIQFyal1fo6/Jmz/56c/N7PdqxS1Mzy+v2lWTa6GevpZOLWyhIgzh+v4TdPOACvk5r7o3005fJy9WtVd3jiyK2f32oXmqVyNnHRBUfw7q1C+dnxR2TSYVfnOXWvNFC2VYU0WpA++o4HPLou+T+tiR0fe+u9tU0Kmf1Mm1H6u/5/RVv0x6Ua2c2kU92DNRqcu/qIgra9Sun/qqMa8W0mno1yj6M7bzY6ieDRzUkLbuqnHZ6KDkn0nR6ySI71DDTnWp46TaVrNX7zSPXr5rDFQVX6gPX/FR+5YOVVFBV5W6MFddnV1E3xPkMyGf6Wlvl4m5Z9w9sVq9VNdZB0jHp3qqiAVQx5b0ehK4PDys/h6XV98zJOB6vrSN2ruwT/T1bjKp4Mub1PwP66k2VWzV2G45lNrcSgXuHKYeHPlRmR4eefK5lCx5+I/aMLOHGto+p3qtgb3a9/MbT/JLGPzVxhkvqXqlbaLf69oq6tjSvspwfZMyPTio/E8vU/cPfKvUqSnq4h9vq18/a60WjW2ofhnfUD0+vSLh95HJpAIubVKBR75R6vLPKuT8chV1e0v0j0Pxv5MenVF/fddVDXzRS816t4oKubAqkeAtVKnHJ/T9KfLOTmW8uVlFPTiccLvY5EefgDNKXV+lTv0+UgWeX5P49lERynB7rzI9PKpU4IXo74/k3FPkfQRfU4FnV6io+/uTVQaQ+8/qlb+l/EdVSXdEUPT9Mv73M2WaoMJG/kEGqVWrFqpWrYoZM2bELPPz80OHDh0waVLCschHjRqFNWvW4PTp0zHL+vfvj2PHjmHPnj3JOmZgYCA8PT0REBAAD4/EJ1BKU8oEY+gDbNuwAg1qlYMh6A4CH95APtcg2BvvYM6y3bj7wB+2tnawtbOHb/4c6NqsJB6G5cDRKxHwzlsAefIXQe58ReHk4QM4eiHk9hEc3rEKe/fuwtFT15HX0wZf9fPGvSAnTFkTBt8ihVC8ZFk851cdxfxqwcHJDbCxB2zsEBFwGQe3/ILTR3ehb82rCAiOQIepgLOjPOxRvqQPXurSBRWb/A/wKA2oSEQ9OIxzB9fg2tl9aFHRhLs3r+KdGdfwODgSOd0dkTe3O9o3eA7N6pfDuVvALX+FvHl98ODOVRzcvxtDG91AeEQUyowAiuUF/Iq4oWzJwmjwfA1UqtkE8CwPuPki9OYO7Fq3EMcO7cKIF+4hIBSo/iH05FbODkCLah7o91pHVGv5DqKUA7Ys+Rg//boWfx834qVawLTXgL+OAt//bYcKJfOjVo2qqNWgFXIXq4UjG+fg+LHdWL/tOPaej0JkFPBGY2BcF+CX3cCSfXaoUa4galSvCg8XhTrum3H7fhD6/GgLVydb7DkXidIFbPH9h21RpmQxfPLtChw/ewOnb5rwKBhoXRmY/Qbw237gk5VAl6Yl8HLvwShRsytwcQ72rJmCzpMfo3BuwNYGCDcCX70KNCoLvPo9sPkk4OUKBIUDxfIA2yaXwEOn2nh7/DLsOWtA35b5MPT9L+ARvBMfTpqFn3cpdKznjTNXHsHRzoSVw2yx77Yvvlh2HTcfGnHzEWCMAhYNAJpU9sKqUwXx9/5rWLMvSM82/G6P8mhf5gpemRaMZg2qoc+Hv+LcX+/BL2oZgm2LwrbaF/jk/Tfxy9ZH+P27HqjQZTa2zumJgZ8sQ7F8jpgxprMepvPtBbYY/+Ew+D3/Gvb/NhL1PDfh7M0otJwMyFRqL1R2Q6sWzeBb0BMVi3thye97cPvOPT0UqJ29M4r4eKFz8/IwupWDyasqnPJX1zMl6+YR4Xd1840IgwGOPs/HjHKUNp9ThftH5yI86A4K1xulO/DGdufgjxg1/C2M+19N+HbbqEdNMpORmLq2roH9FyLRq2lOTFpyU88bYXbryBI0bPUKIk3ApvmDULz110hPRqMRa9euRevWreHgELefBqWQ9Kf5ogJ6TDyJSr4O+GPnNdi55Y9ZHXHvMJo3qo5ztxUGdyyIUbPOwagcnuR/6EUc+rE+Vh+IwkfTtyYYLleFP8Dp9eNRvMbLcCpQN01Pj/QNeXRhM3L7PAfkKKa/W6LfxGP4X9oK94iTsAu9iAVrTuChfxCijBGwt7dFcd9CaNeiDoJNufHrb6vw+8Z9+tr3dAG2fgjk9fbCMZuXUbHlKPz2TR9889MWrBrlgVPGxnh7wmoUyGWHmd9+iaLVe2DN5/XxzrdnMG1obdRq0hW5LrwPZwcT7vh+Bpe8FTFueDfcv/8QC0eVxNe/B+H7P+7A3hZ4uUlBVCnujBdLX8cvOyMwfDGQwxkomBMomMcFH7/sjZIe19FkAlA4j7PcbrDxaDg+fcUNfd4Zi0u3QjFm/ERsPWHAq03zYfzbjYE7G1BuyCOY/i0hhRqA7nWBL3oAv+4FPv8dcHIAgsKiv5M2T/aDb6OPYMrbBLtXTcSSnxfhz/2PsHwwUK0Y8OIU4OhV6PutX2En1K5SAm/17ohtm//CO18dQmAY0LiCM87fDMdfI4EcuYviQHBDXL16HfsPH8eB0w/wfjugeUWg/xxgzWHovkFNKrqiVdN6aPvKQCjn/Dh/6E/s27UZ+w+fxJkrjzGxm0LN4kDXb4DDV4DOz3uhV68+KPvCMODxMaz79Sv8uHQb9p4z6nt0Hg/gyEQgStni6+1F0aBxc1Rp3At2niWi+4P5H8fObRuxc98xnL5wC6duGBESDpz4HIhADsw7WAS16zUGbBzx4P5dlCxgD1/vKCxbdwyb9l/H/UfBCA6LQv5cjvhxWCk4eRTC+uP2KFetKQpWaAMb9xKAigIe7MHW1d9j2er1uH4nEIaIKETJPfN9wGTniQVHiqF2/ZYoXasTbB09o/dRkQj2v4+LJ3fh4pnDuHThHG7evovPX3WHo20oen39UN/zalQqhVp1G6N8nQ6wdy+kP2chj2/oMsrDezfw4N5t1CvnCjfbQMxZcw4P/MNg0qPAKZT0zY8urWsjwj4f/I2ecM9VGM6ePrBxzqO/x+Q76vzxXTh98gj8Hz1AVGQElCkSfVoXgclkwry1V2FnZ4sC3m5o3u5VoPjrSG/yHbB8+XJ0797d4mXhDAsqIiIi4OrqimXLlqFjx39HNAEwePBgHD16FNu2bUuwT4MGDVClShV8/fWTL+GVK1eia9euCA0NTfQL0mAw6EfsoKJw4cJ48OBBhgQVNteWYtanr+HLtUBYrNEld48FfPMAr/9gg7BIRyhl0hdguULA2E5R2HEGeG0GEBGrD+jMPkC7akD374Cd54CKRe1Qxa8gCuRxxZstvXD3vj/GLryOy7dCcOl+9E3xk5eAvo2ACauA5fuhC+rymlWK2WHZxKaIdCqIJetPwRAWitDQEBw4fhWtK0ahd0Ng9QlvzN/0CMevmfRrlcgHbPvEEyE2+fHNX5Hw9HSH/+PHuP/QH838QtGmkhFT1wLT1kEX2u3tgEpF7TF/TGO4FWqAfSdu4szJIzh99hLOXH6IF6uYMLA5MHcrsHQvcOZW9KS+dcu44MexbeDgmhebDt2Hh6cnHt6/jTVrt6BNhVB0qhGdB7vOAa1reuG1nr1QuUZjOEVcwelje7F+6wEcPXUNBy4Y9Y1bvugk7a2nAFXLFkLDRo3h4ZkT+XI5o2j+HDhx6jzWbtyJgyeu48jlSP2lsm9aWXhXewumIi/rgOzqnplY8fMM9K99DR6uwIgljvDKXQh+5Soif6FiyO/jg6JFn4N/gD9W//Idlq49ihPXo4/7tzThdi2Io6ozKrd+P7q9dGSQfthE+OPezfO4cfUCbt24hlx5CqB6sz5wyFlGn3MVEYCN897C+Gm/oVIRhVn9gCtRVeFQYRTylusIGINgvLoGzvdW4ezx/Vh9xAkFChVBgSIlUbRUVRQt3ww2bkWjM1ZF4cGpFfhl9iQUczyFDvULIrLK10DBF2OuMduLP+Ld4e/gr6Mm/Xzul4NRvfOUmPV3j8zFkEEDMaBpJBrVr4WomrMB99JPLtLgCzj111hcuRWAxh0HwaVwUxgjo7Bx40Y0a9YsaxdqjUHRwYR8kcTz+MxvmDVlCAaO+QluRRonWL9iyovYunMvvl52CTaOHun+hZIt8j+TeHhuPd56vSPGT/gMZRoNSrD+3Iax2Pj7Qrz12VbYuhVOmP9RYdE/8sTriJ9lRYXh3j+LsW3tQtStWwcF640GHDxjVpuur4Hj0YFYs/MODt7Kjfe+WgdH73+HMI4Kx5yPGuPTOYd0UPBWKw+8PWEtVO6a/+5sRNTJL+F0biKW7LUF8tRH297j4JS3asx646MTOH90E25cOo5b1y7i1q0b6NvYAT5lWyKyQEdE5X4emzZuQAF1GAUezUcuu1uo9qEU9J0x5uP3UabpyOjPtIpC8PUd2LV+IexsbVCgkC8K+5aEh7cvlMzobu8OOLgjMuQudvz6AV7IvQHBwWFo8An0IAFNKzjgpY7N0bTt63CwjcS58xdw7+4dXLt0GmdOn4JD5F2M62TCjcd22HizMtr1GAWPku2ggi/D7sp8nNo+Gy3GPUTuHED1kq6oXrE4WjWrj6KFfXDhRgAeBRpx6/olbNi8HXfuBWD1cGDrKaD79OjApWbpHChXxhdtXqiDQiVrIMwmHzaumYOFv67DvnMReL0hMKErMH8bcNY/L5o3awZbeweEhQShWfW8uHvjHPp+uhXHrkTB0xUolAt4uxnQoXr0D2VHrzmgTPH88CtTChUr10C5QgqXj29Cn88O48Kd6GKliyPw6UvAK3WBJQdccPi6K7xz5URkVBQiI6PwYUd7GINvosK7BgSHA97uQOViTujVyAlNSwfim3XAybsuKFO8CJxcXODk5ILe7crj3uVD6DL2MC7fg06bgx30PDxvNIlO24xN0PlWPJ8NCuVzx+R+vnB2c8dXKx/g5t3H2H/yHi7dA16pA3z5KjBzEzB+5ZNLWK69P0YAJX1sMGShLW7728DW1laXBQp4RugfLPeeBzpNi95evk7dnIAvewBtqwKDFgCbTgC53aGDXkd7YP170WWtVpOjy0MVCgNff/ImTFWTmA8nDck9aPXq1dkrqLh16xYKFiyIXbt2oW7dJ7/ATJw4EQsWLMDZs2cT7FOqVCn07t0b77//pGPd7t278fzzz+vX8/HxSbDP2LFjMW7cuATLf/75Zx3UpDePqEuwvbEcl+/bwMHZA/bOnnB0zQUP76IwOuSDAR4JCik2yghHFQwHFYCosIcIDbyHkMAH8PUG8rkbcflxDkR6VESES0ld+xCfnQpDjqgbMDw6C3fbx8jl4YDz1x7h6u1AOLm4o2Dp+ojMUQ4qkX1tVQS8o/5B/qiD+G3tHviHu8C3eEnkL1Ydtt5VYbRxT/yNKgV7hMFehcDOFARjyCPA0QMRziUSLYTJDdxN3YWH6SquXTiKE6cvolDR4ijo1wwRzsWjP7UJ9jEhl+ksCkTuxtkr9xGVpylMOasnsa2Cc+RNBN7Yj4o+gQi2K4p79tUQYfOUD5Mywcl4E1GRYYjUeZvwdd1MN/WvO8E2Pom/r385mR4j4vIKXDx/AtWfb4XHOZpASUHiGdmF38C1w0tQuUZD3LdP4j2ngL0KQxQcEk/Tw/3YtGoWGjbvAofCLROsdom6hVzqPG7Z1Uv0GiIiis1BBcIn8gBu2tdFlM2TWjxNmXD3wNe4evkS6nT8GFGOeRJknp0y6JG4TDapq620VUYUjtyM23cf6IDDZOuaqveU4/5KHD7yD8pWbQyDdzOYbJyeemx30zWE2eZGhM2/tUKx2KhI2AWdhG2OIoiwzfnUY7tG3YSP6SBMhkBcCfGBY97qMCTymubjhl1dC8/woyj8XDncsn8eIbYJy07RaTDC1v8ILh3fjAD/x6hSqRxyFayAINuiCLfJmej3jq0ywDbwJOzt7WHvkhNGuMFo45Z0XigFp6i7CL29H7cuHsXlK5dRppADGjRohDt2NeBvWzzR71b9nXVvH65fOAgbFYUSRbxQOL8XHgVFwWBfAMq9OEJsfBL9TrNT4VCPj8I1/AyKeNvg5mN73AmwhZtnHjh75IONUy5E2LjrtMcvU0meOKvHsI24B/97VxAZ7o/I8AAYw4NQLL8LcvsUQ6ApDwwOBfQ5MMEBJtjDBHkdeR8m2OirV0G3P7LJmB8T5If4bBlUSFBQp06dmOUTJkzAwoULcebMmUSDitdffx2jR4+OWSZBSb169XD79m3kz/+k2jmz1lQI/lKYsZj/zH9rxuuf+W/NeP0z/62dMQ1rKp79p9JU8vb2hp2dHe7cuRNn+b1795AvX75E95GgIbHtJSLOnTt3ovs4OTnpR3xS7ZzRVf+ZIQ3WjPnP/LdmvP6Z/9aM1z/zn7LRPBWOjo6oVq2ablsamzyP3RwqNqnRiL/9hg0bUL16dRbOiYiIiIiscfK7YcOGYfbs2Zg7d64e0Wno0KG4du2aHtFJSDOnnj17xmwvy69evar3k+1lvzlz5mDEiBEZ+C6IiIiIiKxbhjV/Et26dcPDhw8xfvx43SeifPnyeqi9okWL6vWyTIIMs2LFiun1EnxMnz4dBQoUwDfffIPOnTtn4LsgIiIiIrJuGRpUiAEDBuhHYubPn59gWcOGDXH48OF0SBkREREREWX65k9ERERERJT1MaggIiIiIqJUYVBBRERERESpwqCCiIiIiIiydkft9GaeQFxm1s7I2QxlinRJAye/Y/5bG17/zH9rxuuf+W/NeP1nnnMQu0xsKVYXVAQFBem/hQsXzuikEBERERFlWJnY09PTYq9noywdpmRyJpMJt27dgru7O2xsbDIkDVJDIUHN9evX4eHhkSFpsGbMf+a/NeP1z/y3Zrz+mf/WLvDfMuipU6dQunRp2NparieE1dVUSOYVKlQImYEEFAwqmP/Witc/89+a8fpn/lszXv8Zr2DBghYNKAQ7ahMRERERUaowqCAiIiIiolRhUJEBnJycMGbMGP2XmP/Whtc/89+a8fpn/lszXv/Z+xxYXUdtIiIiIiKyLNZUEBERERFRqjCoICIiIiKiVGFQQUREREREqcKgIp19//33KFasGJydnVGtWjXs2LEjvZNgFSZNmoQaNWroSQ7z5s2LDh064OzZs3G26d27t54AMfajdu3aGZbm7GTs2LEJ8jZ//vwx66Url2xToEABuLi4oFGjRjh58mSGpjk78fX1TZD/8nj77bf1el77lrV9+3a0bdtWX8+Sz6tWrYqzPjnXu8FgwDvvvANvb2+4ubmhXbt2uHHjhoVTan35bzQaMWrUKFSoUEHnq2zTs2dPPQlubHJO4n9eXn755Qx4N9nzM5Ccew4/A2mX/4l9H8hjypQpFv0MMKhIR0uXLsWQIUPwwQcf4MiRI6hfvz5atWqFa9eupWcyrMK2bdt0AWrv3r3YuHEjIiMj0bx5c4SEhMTZrmXLlrh9+3bMY+3atRmW5uymXLlycfL2+PHjMesmT56MqVOn4rvvvsOBAwd0wNGsWTMEBQVlaJqzC8nT2HkvnwHx0ksvxWzDa99y5L5SqVIlfT0nJjnXu3w3rFy5EkuWLMHOnTsRHByMF198EVFRURZMqfXlf2hoKA4fPoyPPvpI/12xYgXOnTung7b43njjjTifmx9++CGd3kH2/wwk557Dz0Da5X/sfJfH3LlzddDQuXNny34GZPQnSh81a9ZU/fv3j7OsTJky6r333uMpSGP37t2TUc7Utm3bYpb16tVLtW/fnnmfBsaMGaMqVaqU6DqTyaTy58+vPvvss5hl4eHhytPTU82cOZPnIw0MHjxYFS9eXOe94LWfduQ+s3LlyhRd7/7+/srBwUEtWbIkZpubN28qW1tbtW7dujRMbfbP/8Ts379fb3f16tWYZQ0bNtSfE0qbc/Bf9xx+BtL3MyDnokmTJnGWWeIzwJqKdBIREYFDhw7pX8tjk+e7d+9Or2RYrYCAAP03V65ccZZv3bpVN48qVaqUjtDv3buXQSnMfs6fP6+rYqW5n1ShXrp0SS+/fPky7ty5E+ezIONlN2zYkJ+FNLr3LFq0CH369NG/TJnx2k8fybne5btBmunE3kY+O+XLl+dnIo2+D+Sz4OXlFWf54sWLdfMzqWUdMWIEa04t7Gn3HH4G0s/du3fx559/om/fvgnWpfYzYG/BdNJTPHjwQFdj58uXL85yeS5fOJR2JHAfNmwY6tWrp7+kzaTpmTQHKVq0qP7il+rxJk2a6JsbJyZMnVq1auGnn37SXx5yA/v0009Rt25d3Y7cfL0n9lm4evVqKo9M8UnbWn9/f92m2YzXfvpJzvUu2zg6OiJnzpwJtuH3g2WFh4fjvffeQ/fu3eHh4RGzvEePHvoHEGmaduLECYwePRrHjh2LaTpIqfNf9xx+BtLPggULdH/TTp06xVluic8Ag4p0FvuXQnOBN/4ysqyBAwfin3/+0e2UY+vWrVvM/yXYqF69ur7hSQQf/8NGKf8CMZMOknXq1EHx4sX1zczcOY+fhfQxZ84cfT7kl28zXvvp71mud34/WJbUBkmtqclk0oOmxCa/nMf+PihZsqT+TpB+GFWrVrVwSqzPs95z+BmwPOlPIQGEDBhk6c8Amz+lE6lOsrOzS/Crk1T/xf8FiyxHRlNZs2YNtmzZgkKFCj11Wx8fH32Tk2Y7ZFky6ooEF5K35lGg+FlIe/JL+KZNm9CvX7+nbsdrP+0k53qXbaSZ2uPHj5PchlIfUHTt2lX/Si6/vMaupUiMFKIcHBz4fZBG4t9z+BlIHzLiqIyE+V/fCc/6GWBQkU6kaluGkI1fjSTPpVkIWZb8uiE1FDLSx+bNm3WV3n95+PAhrl+/rm92ZFkyVODp06d13pqrV2N/FqRAJSN28bNgWfPmzdNtmNu0afPU7Xjtp53kXO/y3SBf3rG3kZFXpAkCPxOWCyikcCRBdu7cuf9zH2mqKfvx+yBtxL/n8DOQfjXXktcyUlSafAZS1c2bUkRG9pARPubMmaNOnTqlhgwZotzc3NSVK1eYkxb21ltv6dFVtm7dqm7fvh3zCA0N1euDgoLU8OHD1e7du9Xly5fVli1bVJ06dVTBggVVYGAgz0cqSd5K3l+6dEnt3btXvfjii8rd3T3mWpeRcOT8rFixQh0/fly98sorysfHh3lvQVFRUapIkSJq1KhRcZbz2rc8ydMjR47oh3ytTp06Vf/fPLpQcq53GRmwUKFCatOmTerw4cN6ZBYZQS0yMjINUmw9+W80GlW7du103h49ejTO94HBYND7X7hwQY0bN04dOHBAfx/8+eefemTGKlWqMP8tcA6Se8/hZyDt7kEiICBAubq6qhkzZiTY31KfAQYV6Wz69OmqaNGiytHRUVWtWjXOEKdkOfKhSuwxb948vV6Ci+bNm6s8efLoQE8KXzLk3bVr13gaLKBbt2660CR5W6BAAdWpUyd18uTJOMNsyrCzMtSmk5OTatCggS5skeWsX79eX/Nnz56Ns5zXvuVJISmx+43cU5J7vYeFhamBAweqXLlyKRcXFx2I836U+vyXAlJS3weyn5B8lnMieS/fzTL88qBBg9TDhw8tfq1Y4zlI7j2Hn4G0uweJH374Qd9bZPje+Cz1GbCRf1JXmUJERERERNaMfSqIiIiIiChVGFQQEREREVGqMKggIiIiIqJUYVBBRERERESpwqCCiIiIiIhShUEFERERERGlCoMKIiIiIiJKFQYVRERERESUKgwqiIgoy7CxscGqVasyOhlERBQPgwoiIorj3r17ePPNN1GkSBE4OTkhf/78aNGiBfbs2cOcIiKiRNknvpiIiKxV586dYTQasWDBAjz33HO4e/cu/v77bzx69Cijk0ZERJkUayqIiCiGv78/du7cic8//xyNGzdG0aJFUbNmTYwePRpt2rTR20ydOhUVKlSAm5sbChcujAEDBiA4ODjmNebPnw8vLy/88ccfKF26NFxdXdGlSxeEhIToQMXX1xc5c+bEO++8g6ioqJj9ZPknn3yC7t27I0eOHChQoAC+/fbbp56dmzdvolu3bvr1cufOjfbt2+PKlSs8o0RE6YxBBRERxZDCvDyk34LBYEj8i8PWFt988w1OnDihg4TNmzdj5MiRcbYJDQ3V2yxZsgTr1q3D1q1b0alTJ6xdu1Y/Fi5ciFmzZmH58uVx9psyZQoqVqyIw4cP60Bm6NCh2LhxY6LpkGNI4CPp3b59uw6G5P8tW7ZEREQEzyoRUTqyUUqp9DwgERFlbr/99hveeOMNhIWFoWrVqmjYsCFefvllXdhPzLJly/DWW2/hwYMHMTUVr7/+Oi5cuIDixYvrZf3799eBhDSlkoK/kMK/1E7MnDlTP5f/+/n54a+//op5bTluYGCgDkTMHbVXrlyJDh06YO7cuZg8eTJOnz6tlwsJJqSWRIKi5s2bp3FOERGRGWsqiIgoQZ+KW7duYc2aNbqDttQySHAhwYLYsmULmjVrhoIFC8Ld3R09e/bEw4cPdfMmM2nyZA4oRL58+XTQYA4ozMukU3hsderUSfBcgobEHDp0SAcukgZzDUuuXLkQHh6Oixcv8qwSEaUjdtQmIqIEnJ2ddeAgj48//hj9+vXDmDFjdHOj1q1b65oH6f8ghXhpdtS3b1/dudvMwcEhzutJTUJiy0wm03/mvrkWIj7Zt1q1ali8eHGCdXny5OFZJSJKRwwqiIjoP5UtW1Y3KTp48CAiIyPx5Zdf6r4V4tdff7VYDu7duzfB8zJlyiS6rdSeLF26FHnz5oWHh4fF0kBERCnH5k9ERBRDmjE1adIEixYtwj///IPLly/rPhPSd0FGVpImTRJUyKhMly5d0v0kzH0iLGHXrl36WOfOncP06dP1sQcPHpzotj169IC3t7dO144dO3Rat23bpre/ceMGzyoRUTpiTQUREcWQfgm1atXCV199pfslSJMmGTZWOm6///77cHFx0UPKypCzMjpTgwYNMGnSJN2vwhKGDx+u+0qMGzdO95WQGhHp15EY6bchoz6NGjVKjywVFBSk+3k0bdqUNRdEROmMoz8REVGmIB25hwwZoh9ERJS1sPkTERERERGlCoMKIiIiIiJKFTZ/IiIiIiKiVGFNBRERERERpQqDCiIiIiIiShUGFURERERElCoMKoiIiIiIKFUYVBARERERUaowqCAiIiIiolRhUEFERERERKnCoIKIiIiIiFKFQQURERERESE1/g/C9QDBz++vPgAAAABJRU5ErkJggg==",
       "text/plain": [
-       "<Figure size 800x300 with 1 Axes>"
+       "<Figure size 800x350 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -6710,30 +6553,35 @@
     }
    ],
    "source": [
-    "fig, ax = plt.subplots(1, 1, figsize=(8, 3))\n",
-    "\n",
-    "ax.plot(\n",
-    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]) / np.nanmax(np.abs(ref_ts[\"y_mf_auto_red_n\"])),\n",
-    "    label=\"CRIMAC auto red\",\n",
-    ")\n",
-    "ax.plot(\n",
-    "    np.abs(y_mf_auto_red_n) / np.nanmax(np.abs(y_mf_auto_red_n)),\n",
-    "    \"--\",\n",
-    "    label=\"echopype auto red\",\n",
-    ")\n",
+    "plt.figure(figsize=(8, 3.5))\n",
     "\n",
-    "ax.plot(\n",
+    "plt.plot(\n",
+    "    np.arange(len(y_pc_t_n)),\n",
     "    np.abs(y_pc_t_n) / np.nanmax(np.abs(y_pc_t_n)),\n",
-    "    \":\",\n",
+    "    color=api_color,\n",
+    "    linestyle=\":\",\n",
+    "    linewidth=1.2,\n",
+    "    alpha=api_alpha,\n",
     "    label=\"echopype target echo\",\n",
     ")\n",
     "\n",
-    "ax.set_title(\"Reduced autocorrelation aligned with target echo\")\n",
-    "ax.set_xlabel(\"Sample\")\n",
-    "ax.grid(True)\n",
-    "ax.legend()\n",
+    "plt.title(\"Target echo\")\n",
+    "plt.xlabel(\"Sample\")\n",
+    "plt.ylabel(\"Normalized amplitude\")\n",
+    "plt.grid(True)\n",
+    "plt.legend()\n",
     "plt.tight_layout()\n",
-    "plt.show()"
+    "plt.show()\n",
+    "\n",
+    "compare_curve(\n",
+    "    np.arange(len(ref_ts[\"y_mf_auto_red_n\"])),\n",
+    "    np.abs(ref_ts[\"y_mf_auto_red_n\"]) / np.nanmax(np.abs(ref_ts[\"y_mf_auto_red_n\"])),\n",
+    "    np.arange(len(y_mf_auto_red_n)),\n",
+    "    np.abs(y_mf_auto_red_n) / np.nanmax(np.abs(y_mf_auto_red_n)),\n",
+    "    title=\"Reduced autocorrelation\",\n",
+    "    xlabel=\"Sample\",\n",
+    "    ylabel=\"Normalized amplitude\",\n",
+    ")"
    ]
   },
   {
@@ -6746,7 +6594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 29,
    "id": "2aa34af3",
    "metadata": {},
    "outputs": [
@@ -6778,7 +6626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 30,
    "id": "5cbb42d1",
    "metadata": {},
    "outputs": [
@@ -6822,10 +6670,12 @@
     "n_f_points = f_m.size\n",
     "\n",
     "from echopype.calibrate.ek80_complex import _compute_ts_spectrum\n",
+    "N_DFT = int(2 ** np.ceil(np.log2(n_f_points)))\n",
+    "\n",
     "Y_pc_t_m, Y_mf_auto_red_m, Y_tilde_pc_t_m = _compute_ts_spectrum(\n",
     "    pc_target=y_pc_t_n,\n",
     "    mf_auto_red=y_mf_auto_red_n,\n",
-    "    NFFT=n_f_points,\n",
+    "    NFFT=N_DFT,\n",
     "    frequency=f_m,\n",
     "    fs_dec=fs_dec,\n",
     ")\n",
@@ -6849,13 +6699,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 31,
    "id": "f4e0e279",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -6886,13 +6736,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 32,
    "id": "77ef947d",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -6923,13 +6773,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 33,
    "id": "f8caa9c9",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -6962,7 +6812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 34,
    "id": "158cf758",
    "metadata": {},
    "outputs": [
@@ -6990,13 +6840,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 35,
    "id": "540bf3ce",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -7029,25 +6879,146 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
-   "id": "a24e5128",
+   "execution_count": 36,
+   "id": "bc21412a",
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "echopype g_theta_phi_m: (1000,)\n",
-      "CRIMAC g_theta_phi_m  : (1000,)\n"
+      "gain_db EP range: 21.29 30.63996160401566\n",
+      "gain_db CRIMAC range: 21.284005596011188 30.638594165205348\n",
+      "gain_db diff mean: 0.002237991662879406\n",
+      "gain_db diff RMSE: 0.002657421119128671\n",
+      "gain_db diff max : 0.009569340036797769\n"
      ]
     }
    ],
    "source": [
-    "g_theta_phi_m = cal_obj._get_beam_compensated_gain(\n",
-    "    channel=tsf_channel,\n",
-    "    theta=float(theta_t),\n",
-    "    phi=float(phi_t),\n",
-    "    frequency=np.asarray(f_m),\n",
+    "# Compare CRIMAC exported gain terms against echopype inputs\n",
+    "\n",
+    "frequency = np.asarray(ref_ts[\"f_m\"])\n",
+    "\n",
+    "gain_db_ep = np.interp(\n",
+    "    frequency,\n",
+    "    cal_obj.vend[\"cal_frequency\"].values,\n",
+    "    cal_obj.vend[\"gain\"].sel(cal_channel_id=tsf_channel).values,\n",
+    ")\n",
+    "\n",
+    "g0_db_crimac = 10 * np.log10(ref_ts[\"g_0_m\"])\n",
+    "\n",
+    "print(\"gain_db EP range:\", np.nanmin(gain_db_ep), np.nanmax(gain_db_ep))\n",
+    "print(\"gain_db CRIMAC range:\", np.nanmin(g0_db_crimac), np.nanmax(g0_db_crimac))\n",
+    "\n",
+    "print(\"gain_db diff mean:\", np.nanmean(gain_db_ep - g0_db_crimac))\n",
+    "print(\"gain_db diff RMSE:\", np.sqrt(np.nanmean((gain_db_ep - g0_db_crimac) ** 2)))\n",
+    "print(\"gain_db diff max :\", np.nanmax(np.abs(gain_db_ep - g0_db_crimac)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "91b67d71",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x350 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "compare_curve(\n",
+    "    frequency / 1000,\n",
+    "    g0_db_crimac,\n",
+    "    frequency / 1000,\n",
+    "    gain_db_ep,\n",
+    "    title=\"Gain\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=\"Gain (dB)\",\n",
+    ")\n",
+    "\n",
+    "compare_curve(\n",
+    "    frequency / 1000,\n",
+    "    np.zeros_like(frequency),\n",
+    "    frequency / 1000,\n",
+    "    gain_db_ep - g0_db_crimac,\n",
+    "    title=\"Gain difference\",\n",
+    "    xlabel=\"Frequency (kHz)\",\n",
+    "    ylabel=\"EP - CRIMAC (dB)\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "455add3c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "g² dB diff mean: -5.644018622151492e-05\n",
+      "g² dB diff RMSE: 5.957020206340649e-05\n",
+      "g² dB diff max : 9.671765733543225e-05\n"
+     ]
+    }
+   ],
+   "source": [
+    "g2_db_crimac = ref_ts[\"g_theta_phi_m_db\"]\n",
+    "\n",
+    "g_ep = cal_obj._get_beam_compensated_gain(\n",
+    "    channel=tsf_channel,\n",
+    "    theta=float(theta_t),\n",
+    "    phi=float(phi_t),\n",
+    "    frequency=frequency,\n",
+    ")\n",
+    "\n",
+    "g2_db_ep = 10 * np.log10(g_ep**2)\n",
+    "\n",
+    "print(\"g² dB diff mean:\", np.nanmean(g2_db_ep - g2_db_crimac))\n",
+    "print(\"g² dB diff RMSE:\", np.sqrt(np.nanmean((g2_db_ep - g2_db_crimac) ** 2)))\n",
+    "print(\"g² dB diff max :\", np.nanmax(np.abs(g2_db_ep - g2_db_crimac)))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "a24e5128",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "echopype g_theta_phi_m: (1000,)\n",
+      "CRIMAC g_theta_phi_m  : (1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "g_theta_phi_m = cal_obj._get_beam_compensated_gain(\n",
+    "    channel=tsf_channel,\n",
+    "    theta=float(theta_t),\n",
+    "    phi=float(phi_t),\n",
+    "    frequency=np.asarray(f_m),\n",
     ")\n",
     "\n",
     "print(\"echopype g_theta_phi_m:\", g_theta_phi_m.shape)\n",
@@ -7056,13 +7027,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 40,
    "id": "e0d8abd9",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -7095,7 +7066,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 41,
    "id": "90f1d082",
    "metadata": {},
    "outputs": [
@@ -7131,7 +7102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 42,
    "id": "0a14d495",
    "metadata": {},
    "outputs": [
@@ -7162,7 +7133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 43,
    "id": "7ca23f61",
    "metadata": {},
    "outputs": [
@@ -7185,13 +7156,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 44,
    "id": "2903e237",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x350 with 1 Axes>"
       ]
@@ -7224,13 +7195,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 45,
    "id": "70228c93",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 800x1000 with 5 Axes>"
       ]
@@ -7275,108 +7246,9 @@
     "The table below summarises the differences between corresponding variables computed by CRIMAC and echopype at each stage of the TS-spectrum workflow."
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "af274118",
-   "metadata": {},
-   "source": [
-    "tmp"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 47,
-   "id": "8abea7a8",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "['y_rx_nu', 'r_n', 'f_m', 'alpha_m', 'lambda_m', 'y_tx_n', 'y_mf_n', 'y_mf_auto_n', 'tau_eff', 'y_pc_nu', 'y_pc_n', 'p_rx_e_n', 'theta_n', 'phi_n', 'Sp_full_n', 'Sp_full_r', 'Sp_target_n', 'Sp_target_r', 'dum_r', 'dum_theta', 'dum_phi', 'r_t', 'theta_t', 'phi_t', 'y_pc_t_n', 'y_mf_auto_red_n', 'Y_pc_t_m', 'Y_mf_auto_red_m', 'Y_tilde_pc_t_m', 'P_rx_e_t_m', 'g_theta_phi_m', 'TS_m']\n"
-     ]
-    }
-   ],
-   "source": [
-    "print(ref_ts.files)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 48,
-   "id": "848ac4e0",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "y_pc_n abs: RMSE=0.000203375, max_abs=0.00662722\n",
-      "\n",
-      "FIRST DIFFERENCE ABOVE TOLERANCE\n",
-      "variable: y_pc_n abs\n",
-      "index: 1\n",
-      "CRIMAC: 8.244825873734117\n",
-      "echopype/manual: 8.251453096905179\n",
-      "diff: 0.006627223171062013\n"
-     ]
-    }
-   ],
-   "source": [
-    "checks = [\n",
-    "    (\"y_pc_n abs\", np.abs(ref_ts[\"y_pc_n\"]), np.abs(y_pc_n)),\n",
-    "    (\"p_rx_e_n dB\", db10(ref_ts[\"p_rx_e_n\"]), db10(p_rx_e_n)),\n",
-    "    (\"Sp_full_n dB\", ref_ts[\"Sp_full_n\"], Sp_n),\n",
-    "    (\"r_t\", np.array([ref_ts[\"r_t\"]]), np.array([r_t])),\n",
-    "    (\"theta_t\", np.array([ref_ts[\"theta_t\"]]), np.array([theta_t])),\n",
-    "    (\"phi_t\", np.array([ref_ts[\"phi_t\"]]), np.array([phi_t])),\n",
-    "    (\"y_pc_t_n abs\", np.abs(ref_ts[\"y_pc_t_n\"]), np.abs(y_pc_t_n)),\n",
-    "    (\"y_mf_auto_red_n abs\", np.abs(ref_ts[\"y_mf_auto_red_n\"]), np.abs(y_mf_auto_red_n)),\n",
-    "    (\"Y_pc_t_m dB\", db20(ref_ts[\"Y_pc_t_m\"]), db20(Y_pc_t_m)),\n",
-    "    (\"Y_mf_auto_red_m dB\", db20(ref_ts[\"Y_mf_auto_red_m\"]), db20(Y_mf_auto_red_m)),\n",
-    "    (\"Y_tilde_pc_t_m dB\", db20(ref_ts[\"Y_tilde_pc_t_m\"]), db20(Y_tilde_pc_t_m)),\n",
-    "    (\"P_rx_e_t_m dB\", db10(ref_ts[\"P_rx_e_t_m\"]), db10(P_rx_e_t_m)),\n",
-    "    (\"g_theta_phi_m dB\", db10(ref_ts[\"g_theta_phi_m\"]), db10(g_theta_phi_m)),\n",
-    "    (\"alpha_m\", ref_ts[\"alpha_m\"], absorption_f),\n",
-    "    (\"TS_m\", ref_ts[\"TS_m\"], TS_m),\n",
-    "]\n",
-    "\n",
-    "tol = 1e-6\n",
-    "\n",
-    "for name, ref, val in checks:\n",
-    "    ref = np.asarray(ref).reshape(-1)\n",
-    "    val = np.asarray(val).reshape(-1)\n",
-    "\n",
-    "    n = min(ref.size, val.size)\n",
-    "    diff = val[:n] - ref[:n]\n",
-    "\n",
-    "    max_abs = np.nanmax(np.abs(diff))\n",
-    "    rmse = np.sqrt(np.nanmean(diff**2))\n",
-    "\n",
-    "    print(f\"{name}: RMSE={rmse:.6g}, max_abs={max_abs:.6g}\")\n",
-    "\n",
-    "    if max_abs > tol:\n",
-    "        idx = int(np.nanargmax(np.abs(diff)))\n",
-    "        print(\"\\nFIRST DIFFERENCE ABOVE TOLERANCE\")\n",
-    "        print(\"variable:\", name)\n",
-    "        print(\"index:\", idx)\n",
-    "        print(\"CRIMAC:\", ref[idx])\n",
-    "        print(\"echopype/manual:\", val[idx])\n",
-    "        print(\"diff:\", diff[idx])\n",
-    "        break"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "f2191bfe",
-   "metadata": {},
-   "source": [
-    "end tmp"
-   ]
-  },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 46,
    "id": "6ff2975a",
    "metadata": {},
    "outputs": [
@@ -7505,44 +7377,44 @@
        "      <td>Y_pc_t_m dB</td>\n",
        "      <td>1000</td>\n",
        "      <td>-35.450622</td>\n",
-       "      <td>-35.448239</td>\n",
-       "      <td>2.382618e-03</td>\n",
-       "      <td>-2.111098e-03</td>\n",
-       "      <td>0.288531</td>\n",
-       "      <td>5.399668</td>\n",
+       "      <td>-35.450851</td>\n",
+       "      <td>-2.286021e-04</td>\n",
+       "      <td>-2.369292e-03</td>\n",
+       "      <td>0.015977</td>\n",
+       "      <td>0.061057</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>9</th>\n",
        "      <td>Y_mf_auto_red_m dB</td>\n",
        "      <td>1000</td>\n",
        "      <td>3.567061</td>\n",
-       "      <td>3.570432</td>\n",
-       "      <td>3.371336e-03</td>\n",
-       "      <td>-1.389353e-03</td>\n",
-       "      <td>0.095777</td>\n",
-       "      <td>0.455695</td>\n",
+       "      <td>3.569092</td>\n",
+       "      <td>2.031134e-03</td>\n",
+       "      <td>-2.395368e-03</td>\n",
+       "      <td>0.031094</td>\n",
+       "      <td>0.103429</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>10</th>\n",
        "      <td>Y_tilde_pc_t_m dB</td>\n",
        "      <td>1000</td>\n",
        "      <td>-39.017683</td>\n",
-       "      <td>-39.018672</td>\n",
-       "      <td>-9.887186e-04</td>\n",
-       "      <td>-3.215677e-04</td>\n",
-       "      <td>0.267273</td>\n",
-       "      <td>5.134121</td>\n",
+       "      <td>-39.019943</td>\n",
+       "      <td>-2.259736e-03</td>\n",
+       "      <td>-9.423444e-05</td>\n",
+       "      <td>0.016273</td>\n",
+       "      <td>0.071368</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>11</th>\n",
        "      <td>P_rx_e_t_m dB</td>\n",
        "      <td>1000</td>\n",
        "      <td>-60.658788</td>\n",
-       "      <td>-60.659777</td>\n",
-       "      <td>-9.887186e-04</td>\n",
-       "      <td>-3.215677e-04</td>\n",
-       "      <td>0.267273</td>\n",
-       "      <td>5.134121</td>\n",
+       "      <td>-60.661048</td>\n",
+       "      <td>-2.259736e-03</td>\n",
+       "      <td>-9.423444e-05</td>\n",
+       "      <td>0.016273</td>\n",
+       "      <td>0.071368</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>12</th>\n",
@@ -7560,11 +7432,11 @@
        "      <td>TS_m dB</td>\n",
        "      <td>1000</td>\n",
        "      <td>-41.615550</td>\n",
-       "      <td>-41.616483</td>\n",
-       "      <td>-9.322373e-04</td>\n",
-       "      <td>-2.770378e-04</td>\n",
-       "      <td>0.267273</td>\n",
-       "      <td>5.134085</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-2.203255e-03</td>\n",
+       "      <td>-4.762531e-05</td>\n",
+       "      <td>0.016260</td>\n",
+       "      <td>0.071437</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -7580,12 +7452,12 @@
        "5        Sp_target_n dB   167   -82.034552     -82.069809 -3.525722e-02   \n",
        "6          y_pc_t_n abs   168     0.000436       0.000436 -1.777090e-07   \n",
        "7   y_mf_auto_red_n abs   168     0.027249       0.027238 -1.024769e-05   \n",
-       "8           Y_pc_t_m dB  1000   -35.450622     -35.448239  2.382618e-03   \n",
-       "9    Y_mf_auto_red_m dB  1000     3.567061       3.570432  3.371336e-03   \n",
-       "10    Y_tilde_pc_t_m dB  1000   -39.017683     -39.018672 -9.887186e-04   \n",
-       "11        P_rx_e_t_m dB  1000   -60.658788     -60.659777 -9.887186e-04   \n",
+       "8           Y_pc_t_m dB  1000   -35.450622     -35.450851 -2.286021e-04   \n",
+       "9    Y_mf_auto_red_m dB  1000     3.567061       3.569092  2.031134e-03   \n",
+       "10    Y_tilde_pc_t_m dB  1000   -39.017683     -39.019943 -2.259736e-03   \n",
+       "11        P_rx_e_t_m dB  1000   -60.658788     -60.661048 -2.259736e-03   \n",
        "12     g_theta_phi_m dB  1000    52.590609      52.590553 -5.644019e-05   \n",
-       "13              TS_m dB  1000   -41.615550     -41.616483 -9.322373e-04   \n",
+       "13              TS_m dB  1000   -41.615550     -41.617754 -2.203255e-03   \n",
        "\n",
        "     median diff      RMSE  max abs diff  \n",
        "0   1.301043e-17  0.001248      0.021871  \n",
@@ -7596,15 +7468,15 @@
        "5  -5.111712e-03  0.307320      1.852714  \n",
        "6  -7.647879e-08  0.000002      0.000005  \n",
        "7  -1.586508e-05  0.000211      0.000350  \n",
-       "8  -2.111098e-03  0.288531      5.399668  \n",
-       "9  -1.389353e-03  0.095777      0.455695  \n",
-       "10 -3.215677e-04  0.267273      5.134121  \n",
-       "11 -3.215677e-04  0.267273      5.134121  \n",
+       "8  -2.369292e-03  0.015977      0.061057  \n",
+       "9  -2.395368e-03  0.031094      0.103429  \n",
+       "10 -9.423444e-05  0.016273      0.071368  \n",
+       "11 -9.423444e-05  0.016273      0.071368  \n",
        "12 -5.325710e-05  0.000060      0.000097  \n",
-       "13 -2.770378e-04  0.267273      5.134085  "
+       "13 -4.762531e-05  0.016260      0.071437  "
       ]
      },
-     "execution_count": 49,
+     "execution_count": 46,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7712,44 +7584,28 @@
    "id": "1f2a53a8",
    "metadata": {},
    "source": [
-    "## 18. Public API check: compute_TS_spectrum\n",
+    "## 18. Public API check: `compute_TS_spectrum`\n",
     "\n",
-    "This validates that the public API returns the same TS spectrum product as the manual helper-chain above.\n",
+    "The previous sections reproduced the CRIMAC TS-spectrum processing chain step by step using internal helper functions. In practice, users can obtain the same TS-spectrum product directly through the public API.\n",
     "\n",
-    "The workflow is now:\n",
+    "The workflow is:\n",
     "\n",
     "```text\n",
     "compute_Sp()\n",
-    "→ simple target detection using Sp + split-beam angles\n",
+    "→ simple target detection using Sp\n",
     "→ point_locations\n",
     "→ compute_TS_spectrum(point_locations=...)\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "425572d3",
-   "metadata": {},
-   "source": [
-    "### Reproduce the TS spectrum using the public API\n",
+    "```\n",
     "\n",
-    "The previous sections reproduced the CRIMAC processing chain step-by-step using internal helper functions. In practice, users can obtain the same TS-spectrum product directly through the public API."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "44510cb1",
-   "metadata": {},
-   "source": [
-    "Before calling `compute_TS_spectrum()`, we first need to provide target locations. Here, we use the public `compute_Sp()` output to detect the strongest target within the expected calibration-sphere range gate for each ping. For each detected target, we store the ping time, channel, target range, split-beam angles, and target-window limits in a table that will be passed to `compute_TS_spectrum()`.\n",
+    "Before calling `compute_TS_spectrum()`, we first provide target locations. Here, we use the public `compute_Sp()` output to detect the strongest target within the expected calibration-sphere range gate for each ping. For each detected target, we store the ping time, channel, target range, and target-window limits in a `point_locations` dataset.\n",
     "\n",
-    "**This detection step is intentionally simple and is only used here to generate `point_locations` for validating the TS-spectrum API.**"
+    "This detection step is intentionally simple and is only used here to generate `point_locations` for validating the TS-spectrum API. The TS-spectrum routine computes the required split-beam target angles internally from the pulse-compressed complex sector samples, so angle variables do not need to be included in `point_locations`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
-   "id": "0892fb0d",
+   "execution_count": 47,
+   "id": "c39cc60e",
    "metadata": {},
    "outputs": [
     {
@@ -7758,128 +7614,9 @@
      "text": [
       "Available Sp channels: ['WBT 747008-15 ES333-7CD_ES' 'WBT 747015-15 ES70-7CD_ES'\n",
       " 'WBT 747019-15 ES200-7CD_ES' 'WBT 747022-15 ES120-7CD_ES']\n",
-      "Selected channel: WBT 747022-15 ES120-7CD_ES\n",
-      "Number of detected targets: 1265\n"
+      "Selected channel: WBT 747022-15 ES120-7CD_ES\n"
      ]
-    }
-   ],
-   "source": [
-    "target_rows = []\n",
-    "\n",
-    "ds_Sp = ep.calibrate.compute_Sp(\n",
-    "    echodata=ed_ts,\n",
-    "    waveform_mode=\"BB\",\n",
-    "    encode_mode=\"complex\",\n",
-    ")\n",
-    "\n",
-    "print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
-    "print(\"Selected channel:\", tsf_channel)\n",
-    "\n",
-    "sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)\n",
-    "\n",
-    "tx_coeff = get_filter_coeff(cal_obj.vend)\n",
-    "fs = cal_obj.cal_params[\"receiver_sampling_frequency\"]\n",
-    "\n",
-    "matched_filter, _ = get_transmit_signal(\n",
-    "    cal_obj.beam,\n",
-    "    tx_coeff,\n",
-    "    cal_obj.waveform_mode,\n",
-    "    fs,\n",
-    "    cal_obj.drop_last_hanning_zero,\n",
-    ")\n",
-    "\n",
-    "pc = _get_pulse_compressed_signal(\n",
-    "    beam=cal_obj.beam,\n",
-    "    matched_filter=matched_filter,\n",
-    ")\n",
-    "\n",
-    "pc_ch = pc.sel(channel=tsf_channel)\n",
-    "range_ch = cal_obj.range_meter.sel(channel=tsf_channel)\n",
-    "\n",
-    "for ping_idx in range(sp_ch.sizes[\"ping_time\"]):\n",
-    "    pc_ping_i = pc_ch.isel(ping_time=ping_idx)\n",
-    "    sp_i = sp_ch.isel(ping_time=ping_idx)\n",
-    "    r_i = range_ch.isel(ping_time=ping_idx)\n",
-    "\n",
-    "    valid = np.isfinite(sp_i) & np.isfinite(r_i)\n",
-    "\n",
-    "    if not bool(valid.any()):\n",
-    "        continue\n",
-    "\n",
-    "    pc_ping_i = pc_ping_i.where(valid, drop=True)\n",
-    "    sp_i = sp_i.where(valid, drop=True).values\n",
-    "    r_i = r_i.where(valid, drop=True).values\n",
-    "\n",
-    "    gamma_theta_i = scalar_param(\n",
-    "        cal_obj.cal_params[\"angle_sensitivity_alongship\"],\n",
-    "        tsf_channel,\n",
-    "        ping_idx,\n",
-    "    )\n",
-    "\n",
-    "    gamma_phi_i = scalar_param(\n",
-    "        cal_obj.cal_params[\"angle_sensitivity_athwartship\"],\n",
-    "        tsf_channel,\n",
-    "        ping_idx,\n",
-    "    )\n",
-    "\n",
-    "    theta_i, phi_i = _get_splitbeam_angles(\n",
-    "        pc=pc_ping_i,\n",
-    "        gamma_alongship=gamma_theta_i,\n",
-    "        gamma_athwartship=gamma_phi_i,\n",
-    "    )\n",
-    "\n",
-    "    theta_i = theta_i.values\n",
-    "    phi_i = phi_i.values\n",
-    "\n",
-    "    sp_lin_i = 10 ** (sp_i / 10)\n",
-    "\n",
-    "    try:\n",
-    "        (\n",
-    "            r_t_i,\n",
-    "            theta_t_i,\n",
-    "            phi_t_i,\n",
-    "            _,\n",
-    "            _,\n",
-    "            _,\n",
-    "            _,\n",
-    "            dum_r_i,\n",
-    "        ) = extract_single_target(\n",
-    "            pc_avg=sp_lin_i,\n",
-    "            power=sp_lin_i,\n",
-    "            theta=theta_i,\n",
-    "            phi=phi_i,\n",
-    "            range_meter=r_i,\n",
-    "            r0=5.3,\n",
-    "            r1=6.3,\n",
-    "            before=0.5,\n",
-    "            after=1.0,\n",
-    "        )\n",
-    "    except ValueError:\n",
-    "        continue\n",
-    "\n",
-    "    target_rows.append(\n",
-    "        {\n",
-    "            \"raw_ping_index\": ping_idx,\n",
-    "            \"ping_time\": ds_Sp[\"ping_time\"].isel(ping_time=ping_idx).values,\n",
-    "            \"channel\": tsf_channel,\n",
-    "            \"target_id\": len(target_rows),\n",
-    "            \"target_range\": r_t_i,\n",
-    "            \"angle_alongship\": theta_t_i,\n",
-    "            \"angle_athwartship\": phi_t_i,\n",
-    "            \"target_range_min\": dum_r_i.min(),\n",
-    "            \"target_range_max\": dum_r_i.max(),\n",
-    "        }\n",
-    "    )\n",
-    "\n",
-    "print(\"Number of detected targets:\", len(target_rows))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 52,
-   "id": "dca2a887",
-   "metadata": {},
-   "outputs": [
+    },
     {
      "data": {
       "text/html": [
@@ -8449,14 +8186,14 @@
        "    water_level                    float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:47:33+00:00\n",
-       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-257fc57a-fe69-4222-846e-91959700d3e9' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c8c884f4-3d4a-4ff5-af7d-f54d6d7ba546' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8ade1264-cebf-40a2-bf8b-46250be94e05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3731763d-763f-461d-96c4-87adc65d0cb9' class='xr-var-data-in' type='checkbox'><label for='data-3731763d-763f-461d-96c4-87adc65d0cb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:29:44+00:00\n",
+       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4a7a8833-2c9a-409b-a78b-acf62dcbdcb0' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4a7a8833-2c9a-409b-a78b-acf62dcbdcb0' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4a69778b-70f6-46f5-97af-9fff53184ea5' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4a69778b-70f6-46f5-97af-9fff53184ea5' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-cb5ab5d1-b01f-41a7-b44c-1c244fa174ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb5ab5d1-b01f-41a7-b44c-1c244fa174ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af0c1f83-8b40-442b-912b-998ed32b9f22' class='xr-var-data-in' type='checkbox'><label for='data-af0c1f83-8b40-442b-912b-998ed32b9f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-280f09b5-483a-4d86-a233-4785c8ede359' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-280f09b5-483a-4d86-a233-4785c8ede359' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' class='xr-var-data-in' type='checkbox'><label for='data-20f1ba75-9b18-4589-9ca1-c3cebf97546e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-4439134c-3a76-4fa4-ad67-70d891f6e106' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4439134c-3a76-4fa4-ad67-70d891f6e106' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4301ffcb-a85f-49a2-99d4-ef573d7d2682' class='xr-var-data-in' type='checkbox'><label for='data-4301ffcb-a85f-49a2-99d4-ef573d7d2682' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-981ab7ea-6eb3-4197-9648-983774613b29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-981ab7ea-6eb3-4197-9648-983774613b29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' class='xr-var-data-in' type='checkbox'><label for='data-0ca32464-12b5-4e84-b537-94d7fdb1bfa9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e88c654e-8f04-44b9-adab-6bb31ed434f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92e7781c-0ac2-443d-8526-ad096a24013f' class='xr-var-data-in' type='checkbox'><label for='data-92e7781c-0ac2-443d-8526-ad096a24013f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary-in' type='checkbox' /><label for='section-4262abe7-4b9b-41e5-8cc4-7b1bb94bc1f0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-018451ee-8460-42d8-8d7c-9d497d423674' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-018451ee-8460-42d8-8d7c-9d497d423674' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' class='xr-var-data-in' type='checkbox'><label for='data-1a6ec994-dcbc-43cf-9c84-7412be87c0f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-b02a1d4a-4d63-42c9-bcd8-1748aeac028a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b02a1d4a-4d63-42c9-bcd8-1748aeac028a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7dd4f55-3951-4cc5-8a03-523b3cf19a0d' class='xr-var-data-in' type='checkbox'><label for='data-a7dd4f55-3951-4cc5-8a03-523b3cf19a0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-5c2f88e2-5105-409a-86df-2902299b708c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c2f88e2-5105-409a-86df-2902299b708c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abfc6f65-6ffe-4152-a72f-d970987c5eeb' class='xr-var-data-in' type='checkbox'><label for='data-abfc6f65-6ffe-4152-a72f-d970987c5eeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-42b3088e-6795-4676-8f1c-107d48bbbf1a' class='xr-section-summary-in' type='checkbox' /><label for='section-42b3088e-6795-4676-8f1c-107d48bbbf1a' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99fb031e-608e-4c73-a1d8-56e56fd8e76e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99fb031e-608e-4c73-a1d8-56e56fd8e76e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b55cf9b-29c6-4078-836a-e5e980f41579' class='xr-var-data-in' type='checkbox'><label for='data-6b55cf9b-29c6-4078-836a-e5e980f41579' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
        "         -195.57397259, -218.79009715, -150.30546618],\n",
        "        [          nan,           nan,           nan, ...,\n",
        "         -198.89271647, -222.29194801, -150.30546618],\n",
@@ -8496,7 +8233,7 @@
        "                   nan,           nan,           nan],\n",
        "        [          nan,           nan,           nan, ...,\n",
        "                   nan,           nan,           nan]]],\n",
-       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-430bf7fe-1b9e-46d2-9291-56bb61afab1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-456fdd8d-b511-4497-8303-8b75f943ef99' class='xr-var-data-in' type='checkbox'><label for='data-456fdd8d-b511-4497-8303-8b75f943ef99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-e99134ec-e7df-4f3d-864c-a68a823c5867' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99134ec-e7df-4f3d-864c-a68a823c5867' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1f5c036-fff1-45ae-bc03-29284e907fdd' class='xr-var-data-in' type='checkbox'><label for='data-a1f5c036-fff1-45ae-bc03-29284e907fdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
        "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
        "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
        "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
@@ -8536,80 +8273,80 @@
        "                    nan,            nan,            nan],\n",
        "        [           nan,            nan,            nan, ...,\n",
        "                    nan,            nan,            nan]]],\n",
-       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00bb80b6-bc78-446c-9d8b-c083f5730223' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' class='xr-var-data-in' type='checkbox'><label for='data-29855845-f9a8-42b2-88fa-ee771b7db5a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-1a770251-9a45-4569-8238-961d39f876b0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a770251-9a45-4569-8238-961d39f876b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' class='xr-var-data-in' type='checkbox'><label for='data-4258122a-f0d4-4fae-8972-a6f2afd6a85c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8767edc6-22ca-4c7f-9634-1093dcc42436' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' class='xr-var-data-in' type='checkbox'><label for='data-01c5e1a2-14e4-4bb3-aa49-23d86b3aba75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-3b8df520-0c81-4d0c-94fd-fa005afcdd39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b8df520-0c81-4d0c-94fd-fa005afcdd39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34bc4343-40ac-4898-9df1-23b9510cbf65' class='xr-var-data-in' type='checkbox'><label for='data-34bc4343-40ac-4898-9df1-23b9510cbf65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-2a7bd036-ad2b-4e5b-8e06-b85d4d2f99fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a7bd036-ad2b-4e5b-8e06-b85d4d2f99fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9bc31f1-5391-48c0-84f6-7c087178d41a' class='xr-var-data-in' type='checkbox'><label for='data-c9bc31f1-5391-48c0-84f6-7c087178d41a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-0390066d-a482-4b4f-ac8f-838f05d57080' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0390066d-a482-4b4f-ac8f-838f05d57080' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba6bc0e1-46e1-437b-b38b-6268e5fd7584' class='xr-var-data-in' type='checkbox'><label for='data-ba6bc0e1-46e1-437b-b38b-6268e5fd7584' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
        "        0.07527219],\n",
        "       [0.02167407, 0.02167407, 0.02167407, ..., 0.02167407, 0.02167407,\n",
        "        0.02167407],\n",
        "       [0.05300738, 0.05300738, 0.05300738, ..., 0.05300738, 0.05300738,\n",
        "        0.05300738],\n",
        "       [0.03770373, 0.03770373, 0.03770373, ..., 0.03770373, 0.03770373,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-70a9198d-0513-4336-81e3-20bf448f2e21' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a01fc152-7dce-4732-844a-d61d5a251940' class='xr-var-data-in' type='checkbox'><label for='data-a01fc152-7dce-4732-844a-d61d5a251940' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9964122c-ecf7-47b1-9a31-172ef5bde171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69c05f67-fa2e-4478-a990-acebee4abc19' class='xr-var-data-in' type='checkbox'><label for='data-69c05f67-fa2e-4478-a990-acebee4abc19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85106bbd-0567-42cc-a281-3567592c4ab1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' class='xr-var-data-in' type='checkbox'><label for='data-336fae25-4b02-450b-ba1a-b3bcd7ad48ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-64b02427-8003-4612-8656-5ee97caf5b05' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64b02427-8003-4612-8656-5ee97caf5b05' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8029b272-0f32-45a2-b880-73e92bea66f1' class='xr-var-data-in' type='checkbox'><label for='data-8029b272-0f32-45a2-b880-73e92bea66f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e40cdc57-2cff-4551-9a95-6d61f911d7fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' class='xr-var-data-in' type='checkbox'><label for='data-8de3d097-f0eb-4645-b79f-ce69c28dd1a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5d71772e-4e3a-44bc-8e9a-383bf6518e80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' class='xr-var-data-in' type='checkbox'><label for='data-18fc29b9-1ef4-4863-98fe-c56f2104d9d9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-a30c85ba-a138-4049-999c-901d55289b06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a30c85ba-a138-4049-999c-901d55289b06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bb956f9-7074-43b7-93d2-75dbd4a3d21a' class='xr-var-data-in' type='checkbox'><label for='data-4bb956f9-7074-43b7-93d2-75dbd4a3d21a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-310cdb44-825b-4d34-8a80-a6abb2e9a5d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-310cdb44-825b-4d34-8a80-a6abb2e9a5d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28d6de51-0ff1-4b01-95b5-0cc7f1ee5c10' class='xr-var-data-in' type='checkbox'><label for='data-28d6de51-0ff1-4b01-95b5-0cc7f1ee5c10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-8494ac63-4551-4453-9ee6-d53d3aae4bc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8494ac63-4551-4453-9ee6-d53d3aae4bc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d636e27f-37ca-4f8a-a260-586b1827fe34' class='xr-var-data-in' type='checkbox'><label for='data-d636e27f-37ca-4f8a-a260-586b1827fe34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-cfd179b0-9775-4f40-81bc-8b7d4b128282' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfd179b0-9775-4f40-81bc-8b7d4b128282' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8c1c3b2-dd19-47d8-a53b-996941691440' class='xr-var-data-in' type='checkbox'><label for='data-e8c1c3b2-dd19-47d8-a53b-996941691440' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-6665f89a-60d1-4259-aeb3-31236efee495' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6665f89a-60d1-4259-aeb3-31236efee495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cef341c6-1ed5-4ec9-b16d-5b3b00d413d2' class='xr-var-data-in' type='checkbox'><label for='data-cef341c6-1ed5-4ec9-b16d-5b3b00d413d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-12d2c173-7ab5-46cd-b40a-d303ff3d4734' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12d2c173-7ab5-46cd-b40a-d303ff3d4734' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19497490-f707-4d9c-9e63-5dfc7a533b6a' class='xr-var-data-in' type='checkbox'><label for='data-19497490-f707-4d9c-9e63-5dfc7a533b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       ...,\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0ad906ed-6359-4605-9e7f-8fff3ea04a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' class='xr-var-data-in' type='checkbox'><label for='data-d5bf5a8a-5f92-4e65-956b-b8cdbf17338a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
+       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-83a4be53-4de2-465f-9546-e766aee30c67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83a4be53-4de2-465f-9546-e766aee30c67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88b4f137-61fc-4650-95e1-12c671a01aa1' class='xr-var-data-in' type='checkbox'><label for='data-88b4f137-61fc-4650-95e1-12c671a01aa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
        "        25.517003  , 25.517003  ],\n",
        "       [27.40875   , 27.40875   , 27.40875   , ..., 27.40875   ,\n",
        "        27.40875   , 27.40875   ],\n",
        "       [28.04229062, 28.04229062, 28.04229062, ..., 28.04229062,\n",
        "        28.04229062, 28.04229062],\n",
        "       [28.0375    , 28.0375    , 28.0375    , ..., 28.0375    ,\n",
-       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-415fc1e3-65c2-4b40-a82b-ea9f02332cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' class='xr-var-data-in' type='checkbox'><label for='data-79a95f48-ed1a-4a4c-a22e-1af52a9dc731' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
+       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-e99b8a64-b13a-4a7c-ace7-0783d3dc5dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99b8a64-b13a-4a7c-ace7-0783d3dc5dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6682000-525c-477b-85da-b1b7c5f8f5b3' class='xr-var-data-in' type='checkbox'><label for='data-a6682000-525c-477b-85da-b1b7c5f8f5b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
        "        -20.62139413, -20.62139413],\n",
        "       [-20.7       , -20.7       , -20.7       , ..., -20.7       ,\n",
        "        -20.7       , -20.7       ],\n",
        "       [-21.32816929, -21.32816929, -21.32816929, ..., -21.32816929,\n",
        "        -21.32816929, -21.32816929],\n",
        "       [-21.39524213, -21.39524213, -21.39524213, ..., -21.39524213,\n",
-       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e30c0e7-90e3-485d-beb9-799a4d1aea6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9150a043-05ca-4e7d-876d-58e42233143c' class='xr-var-data-in' type='checkbox'><label for='data-9150a043-05ca-4e7d-876d-58e42233143c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
+       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-ce3b1944-a2e1-4321-aea1-0878c84725a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce3b1944-a2e1-4321-aea1-0878c84725a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbff2b2f-4f9a-4f69-8c3f-59262c999a47' class='xr-var-data-in' type='checkbox'><label for='data-fbff2b2f-4f9a-4f69-8c3f-59262c999a47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
        "        -0.040999  , -0.040999  ],\n",
        "       [-0.2209375 , -0.2209375 , -0.2209375 , ..., -0.2209375 ,\n",
        "        -0.2209375 , -0.2209375 ],\n",
        "       [-0.00590313, -0.00590313, -0.00590313, ..., -0.00590313,\n",
        "        -0.00590313, -0.00590313],\n",
        "       [-0.0575    , -0.0575    , -0.0575    , ..., -0.0575    ,\n",
-       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10d4d2e1-5a34-4a85-833f-88fff72b01da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37392d71-2357-42b4-b2eb-5724357c5a9e' class='xr-var-data-in' type='checkbox'><label for='data-37392d71-2357-42b4-b2eb-5724357c5a9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
+       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-50dc169f-a583-4207-99a5-df23ef131b62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50dc169f-a583-4207-99a5-df23ef131b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2249eddc-7100-48bd-a19e-4cd6a9309ba0' class='xr-var-data-in' type='checkbox'><label for='data-2249eddc-7100-48bd-a19e-4cd6a9309ba0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
        "         0.0195005 ,  0.0195005 ],\n",
        "       [-0.124375  , -0.124375  , -0.124375  , ..., -0.124375  ,\n",
        "        -0.124375  , -0.124375  ],\n",
        "       [-0.08590313, -0.08590313, -0.08590313, ..., -0.08590313,\n",
        "        -0.08590313, -0.08590313],\n",
        "       [ 0.0175    ,  0.0175    ,  0.0175    , ...,  0.0175    ,\n",
-       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-38d6697d-7772-4ee8-a0af-7bbaa895c588' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' class='xr-var-data-in' type='checkbox'><label for='data-3d1466aa-709a-4b1d-8ac8-6b49d4ad6d0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-52ce2ce0-6de0-4002-91c7-9afae64847ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52ce2ce0-6de0-4002-91c7-9afae64847ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b10aa4bc-904a-49ce-b405-505e8e084a02' class='xr-var-data-in' type='checkbox'><label for='data-b10aa4bc-904a-49ce-b405-505e8e084a02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
        "        22.79279279, 22.79279279],\n",
        "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
        "        23.        , 23.        ],\n",
        "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
        "        24.725     , 24.725     ],\n",
        "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
-       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04eade2a-a009-4a0a-9226-082cd6988f4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' class='xr-var-data-in' type='checkbox'><label for='data-789cb842-1dda-4082-b8c1-44bc1dcc91c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-56bce38b-7018-441c-93fc-52b2ab05d35c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56bce38b-7018-441c-93fc-52b2ab05d35c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c4996cc-8733-4a73-b6b3-447a8b408904' class='xr-var-data-in' type='checkbox'><label for='data-8c4996cc-8733-4a73-b6b3-447a8b408904' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
        "        22.79279279, 22.79279279],\n",
        "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
        "        23.        , 23.        ],\n",
        "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
        "        24.725     , 24.725     ],\n",
        "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
-       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-7572befa-850c-4a01-98ff-ee37b0200703' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7572befa-850c-4a01-98ff-ee37b0200703' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39de6332-e1e6-4de3-aac4-4d44bd630972' class='xr-var-data-in' type='checkbox'><label for='data-39de6332-e1e6-4de3-aac4-4d44bd630972' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-22d618ad-b8da-46b4-a80d-d267e6fcb7c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22d618ad-b8da-46b4-a80d-d267e6fcb7c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98cef8e4-5988-4ee7-853c-0f66e2beb0fb' class='xr-var-data-in' type='checkbox'><label for='data-98cef8e4-5988-4ee7-853c-0f66e2beb0fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
        "        6.9434965 ],\n",
        "       [6.9290625 , 6.9290625 , 6.9290625 , ..., 6.9290625 , 6.9290625 ,\n",
        "        6.9290625 ],\n",
        "       [6.25361251, 6.25361251, 6.25361251, ..., 6.25361251, 6.25361251,\n",
        "        6.25361251],\n",
        "       [6.17      , 6.17      , 6.17      , ..., 6.17      , 6.17      ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e822a8ac-4b22-4db7-af52-39a44eb461c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' class='xr-var-data-in' type='checkbox'><label for='data-e6beefdc-89f6-49da-bfc0-a7f39c754a2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-538ef8a2-bf58-4108-8d19-bf61c3831b32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-538ef8a2-bf58-4108-8d19-bf61c3831b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a506c1b-b29d-461e-8b83-2868bba8d1c6' class='xr-var-data-in' type='checkbox'><label for='data-5a506c1b-b29d-461e-8b83-2868bba8d1c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
        "        7.131998  ],\n",
        "       [6.7325    , 6.7325    , 6.7325    , ..., 6.7325    , 6.7325    ,\n",
        "        6.7325    ],\n",
        "       [6.24638749, 6.24638749, 6.24638749, ..., 6.24638749, 6.24638749,\n",
        "        6.24638749],\n",
        "       [6.2775    , 6.2775    , 6.2775    , ..., 6.2775    , 6.2775    ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e0d11157-0d1d-4f3e-9cdc-1b1c5b04a893' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dd05efd-6d51-4042-a667-50e4da4f1057' class='xr-var-data-in' type='checkbox'><label for='data-6dd05efd-6d51-4042-a667-50e4da4f1057' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-ab00af5c-ec0e-4801-bc2c-2ba19d84d50c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab00af5c-ec0e-4801-bc2c-2ba19d84d50c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a3bb0ee-0acf-4042-80d3-4bcbc36a7092' class='xr-var-data-in' type='checkbox'><label for='data-6a3bb0ee-0acf-4042-80d3-4bcbc36a7092' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., 75., 75., 75.],\n",
-       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b571872b-73a4-44ab-944e-d241fc31c91c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' class='xr-var-data-in' type='checkbox'><label for='data-d5e27f4b-82c5-44aa-a239-1479cb755b01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d359f8a-a04f-4dc8-bf41-39718799e919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-605050ed-2f39-4f72-90e0-bded240d8f40' class='xr-var-data-in' type='checkbox'><label for='data-605050ed-2f39-4f72-90e0-bded240d8f40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a022ed4d-4296-4b5a-81f0-4976ff8b8def' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' class='xr-var-data-in' type='checkbox'><label for='data-4663deb5-ca69-4e5d-a2df-14911cf24dd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-371ca08f-2b03-4441-a911-637e2015f167' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-371ca08f-2b03-4441-a911-637e2015f167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' class='xr-var-data-in' type='checkbox'><label for='data-6a6ea023-c0bd-4f52-9e92-af4917c8b7cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3549fb39-42d2-40a9-8f2a-14a494cf6041' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:47:33+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
+       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-9b26ee2e-197f-418c-9246-c34a331048a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b26ee2e-197f-418c-9246-c34a331048a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e9235ef-a2cc-496c-a66e-363a99575a5c' class='xr-var-data-in' type='checkbox'><label for='data-3e9235ef-a2cc-496c-a66e-363a99575a5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-4617d66a-4fc6-4f68-a5b0-aa6260307e12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4617d66a-4fc6-4f68-a5b0-aa6260307e12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7405164c-7471-4ecc-914e-986019768774' class='xr-var-data-in' type='checkbox'><label for='data-7405164c-7471-4ecc-914e-986019768774' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a02b51c1-7e0f-412b-8ba5-d262e7c1a89d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a02b51c1-7e0f-412b-8ba5-d262e7c1a89d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c45e45-f36d-459d-9537-fb6a0c14d536' class='xr-var-data-in' type='checkbox'><label for='data-f4c45e45-f36d-459d-9537-fb6a0c14d536' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-01a7c272-f985-4204-86eb-1ae37af5c85f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01a7c272-f985-4204-86eb-1ae37af5c85f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42aca939-d6f1-4782-9d81-0645801ffdb8' class='xr-var-data-in' type='checkbox'><label for='data-42aca939-d6f1-4782-9d81-0645801ffdb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79a718aa-25ca-4ddb-867e-3b972e21fa1f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-79a718aa-25ca-4ddb-867e-3b972e21fa1f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:29:44+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 287MB\n",
@@ -8636,31 +8373,104 @@
        "    water_level                    float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:47:33+00:00\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:29:44+00:00\n",
        "    processing_function:          calibrate.compute_Sp"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 47,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "ds_Sp"
+    "target_rows = []\n",
+    "\n",
+    "ds_Sp = ep.calibrate.compute_Sp(\n",
+    "    echodata=ed_ts,\n",
+    "    waveform_mode=\"FM\",\n",
+    "    encode_mode=\"complex\",\n",
+    ")\n",
+    "\n",
+    "print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
+    "print(\"Selected channel:\", tsf_channel)\n",
+    "\n",
+    "ds_Sp\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
-   "id": "e14b4f11",
+   "execution_count": 48,
+   "id": "0892fb0d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of detected targets: 1265\n"
+     ]
+    }
+   ],
    "source": [
-    "# print(\"Available Sp channels:\", ds_Sp[\"channel\"].values)\n",
-    "# print(\"Selected channel:\", tsf_channel)\n",
+    "sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)\n",
+    "range_ch = cal_obj.range_meter.sel(channel=tsf_channel)\n",
+    "\n",
+    "for ping_idx in range(sp_ch.sizes[\"ping_time\"]):\n",
+    "    sp_i = sp_ch.isel(ping_time=ping_idx)\n",
+    "    r_i = range_ch.isel(ping_time=ping_idx)\n",
+    "\n",
+    "    valid_i = np.isfinite(sp_i) & np.isfinite(r_i)\n",
+    "\n",
+    "    if not bool(valid_i.any()):\n",
+    "        continue\n",
+    "\n",
+    "    sp_i = sp_i.where(valid_i, drop=True).values\n",
+    "    r_i = r_i.where(valid_i, drop=True).values\n",
+    "\n",
+    "    sp_lin_i = 10 ** (sp_i / 10)\n",
+    "\n",
+    "    # Angles are not needed for simple target detection here.\n",
+    "    # compute_TS_spectrum() computes the required split-beam angles internally.\n",
+    "    dummy_angle = np.zeros_like(sp_lin_i)\n",
+    "\n",
+    "    try:\n",
+    "        (\n",
+    "            r_t_i,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            _,\n",
+    "            dum_r_i,\n",
+    "        ) = extract_single_target(\n",
+    "            pc_avg=sp_lin_i,\n",
+    "            power=sp_lin_i,\n",
+    "            theta=dummy_angle,\n",
+    "            phi=dummy_angle,\n",
+    "            range_meter=r_i,\n",
+    "            r0=5.3,\n",
+    "            r1=6.3,\n",
+    "            before=0.5,\n",
+    "            after=1.0,\n",
+    "        )\n",
+    "    except ValueError:\n",
+    "        continue\n",
     "\n",
-    "# sp_ch = ds_Sp[\"Sp\"].sel(channel=tsf_channel)"
+    "    target_rows.append(\n",
+    "        {\n",
+    "            \"raw_ping_index\": ping_idx,\n",
+    "            \"ping_time\": ds_Sp[\"ping_time\"].isel(ping_time=ping_idx).values,\n",
+    "            \"channel\": tsf_channel,\n",
+    "            \"target_id\": len(target_rows),\n",
+    "            \"target_range\": r_t_i,\n",
+    "            \"target_range_min\": dum_r_i.min(),\n",
+    "            \"target_range_max\": dum_r_i.max(),\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "print(\"Number of detected targets:\", len(target_rows))"
    ]
   },
   {
@@ -8670,12 +8480,16 @@
    "source": [
     "### Create the `point_locations` dataset for `compute_TS_spectrum()`\n",
     "\n",
-    "The public `compute_TS_spectrum()` API expects target locations as an input dataset. Here, we create this dataset for the detected calibration sphere target, including its ping time, channel, range, split-beam angles, and target-window limits."
+    "The public `compute_TS_spectrum()` API expects target locations as an input dataset. Here, we create this dataset for the detected calibration sphere target, including its ping time, channel, target range, and target-window limits.\n",
+    "\n",
+    ":::{important}\n",
+    "`point_locations` does not need to include split-beam angles. The TS-spectrum routine computes the required CRIMAC-style target angles internally from the pulse-compressed complex sector samples and then applies the frequency-dependent angle offsets during beam compensation.\n",
+    ":::\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 49,
    "id": "fbc2ca91",
    "metadata": {},
    "outputs": [
@@ -9224,49 +9038,43 @@
        "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
        "  stroke-width: 0.8px;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 213kB\n",
-       "Dimensions:            (target_id: 1265)\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 192kB\n",
+       "Dimensions:           (target_id: 1265)\n",
        "Coordinates:\n",
-       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
-       "    channel            (target_id) &lt;U26 132kB &#x27;WBT 747022-15 ES120-7CD_ES&#x27; .....\n",
-       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "  * target_id         (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel           (target_id) &lt;U26 132kB &#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......\n",
+       "    ping_time         (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.661...\n",
        "Data variables:\n",
-       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
-       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
-       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
-       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
-       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
-       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ed5b5307-5159-43aa-bc50-893097e81b02' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-39da32e2-fd9f-46b6-8001-0236c011f66f' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-858b42ee-b3e2-4075-99ec-eb188fea688c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dca6b996-4390-4001-80b4-a0aa1cbee602' class='xr-var-data-in' type='checkbox'><label for='data-dca6b996-4390-4001-80b4-a0aa1cbee602' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-409a4481-5143-42d2-9b0f-1c98b383c26c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' class='xr-var-data-in' type='checkbox'><label for='data-3461eddb-b81d-43d7-ab3b-7afb7ae00529' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "    target_range      (target_id) float64 10kB 5.805 5.805 5.805 ... 5.781 5.781\n",
+       "    target_range_min  (target_id) float64 10kB 5.306 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max  (target_id) float64 10kB 6.298 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index    (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1817ff15-4059-4f19-8d79-e9064b6c5dd1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-1817ff15-4059-4f19-8d79-e9064b6c5dd1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-14673265-fe56-4d4f-a393-6fc458555e06' class='xr-section-summary-in' type='checkbox' checked /><label for='section-14673265-fe56-4d4f-a393-6fc458555e06' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-617b56af-117a-4b5d-933b-27510c0ce54f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-617b56af-117a-4b5d-933b-27510c0ce54f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c0abee7-81b3-4ac3-ba34-a2b86e5282cb' class='xr-var-data-in' type='checkbox'><label for='data-5c0abee7-81b3-4ac3-ba34-a2b86e5282cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-d0b9a958-2260-453b-bc03-9ed9cbffcec6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0b9a958-2260-453b-bc03-9ed9cbffcec6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed137115-748a-4cfb-b516-72aaec8a355a' class='xr-var-data-in' type='checkbox'><label for='data-ed137115-748a-4cfb-b516-72aaec8a355a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, ..., &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b9200e1-8afa-424e-8a20-12068f24e365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e50353f7-bf0b-48a5-9363-6efa241d9125' class='xr-var-data-in' type='checkbox'><label for='data-e50353f7-bf0b-48a5-9363-6efa241d9125' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-2fcde00e-f292-46e0-bad0-d6d909b0e3e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2fcde00e-f292-46e0-bad0-d6d909b0e3e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c0f0e2-a264-4eb8-ac73-f8f74dc355df' class='xr-var-data-in' type='checkbox'><label for='data-63c0f0e2-a264-4eb8-ac73-f8f74dc355df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "       &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;],\n",
-       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ddc73db4-2a4d-4da8-9c52-4a8f891b4c65' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6bed23da-7f14-4bb7-82de-a8126fb35241' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3898eabb-6795-4afa-8c90-343dde130a87' class='xr-var-data-in' type='checkbox'><label for='data-3898eabb-6795-4afa-8c90-343dde130a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9fc45e6b-7538-42ab-9647-b40dcc47aa39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' class='xr-var-data-in' type='checkbox'><label for='data-deafdd42-2b9c-4677-99a9-aff16a78da8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
-       "       -0.00917041,  0.15295288], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2bcca5b4-e93d-4ed9-a246-95e6135e6c8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' class='xr-var-data-in' type='checkbox'><label for='data-9fbaa18d-b4eb-46e0-8a93-b4d8ae1b4740' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
-       "       -0.02377829, -0.15330624], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-500c66bf-999c-43bd-bae8-15116604cea4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-500c66bf-999c-43bd-bae8-15116604cea4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' class='xr-var-data-in' type='checkbox'><label for='data-43f5cc1d-4a63-45d7-803e-f5441c44532b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
-       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eaa7df8-f1c2-4217-8f17-daf77315acc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' class='xr-var-data-in' type='checkbox'><label for='data-7b0304aa-4bf9-46ac-93c6-5c629a599678' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
-       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6a57422a-9a20-4f4e-a603-2a0f38326f7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' class='xr-var-data-in' type='checkbox'><label for='data-9aee484d-cc7f-4631-88a0-759ec98b1df3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
+       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c619845c-f10b-43ec-97e2-a45202e47157' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c619845c-f10b-43ec-97e2-a45202e47157' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-a6f6e174-ed72-407f-9356-25db93e0f067' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6f6e174-ed72-407f-9356-25db93e0f067' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b631dad-9682-48cf-981e-184f66445a1a' class='xr-var-data-in' type='checkbox'><label for='data-4b631dad-9682-48cf-981e-184f66445a1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-b16def64-ca41-46f1-a012-919aaddc20c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b16def64-ca41-46f1-a012-919aaddc20c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35822fee-068a-49f9-8260-edf49b1e8669' class='xr-var-data-in' type='checkbox'><label for='data-35822fee-068a-49f9-8260-edf49b1e8669' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
+       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-26148d73-6d3c-4914-8c19-5a60e650396f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26148d73-6d3c-4914-8c19-5a60e650396f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78736372-9ed7-4551-8471-d7cdca778ee4' class='xr-var-data-in' type='checkbox'><label for='data-78736372-9ed7-4551-8471-d7cdca778ee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
+       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-1d471f85-ed22-4d4b-ac45-2554ac634a95' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d471f85-ed22-4d4b-ac45-2554ac634a95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19490380-d94c-4820-b641-8a2ee54c60ab' class='xr-var-data-in' type='checkbox'><label for='data-19490380-d94c-4820-b641-8a2ee54c60ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset> Size: 213kB\n",
-       "Dimensions:            (target_id: 1265)\n",
+       "<xarray.Dataset> Size: 192kB\n",
+       "Dimensions:           (target_id: 1265)\n",
        "Coordinates:\n",
-       "  * target_id          (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
-       "    channel            (target_id) <U26 132kB 'WBT 747022-15 ES120-7CD_ES' .....\n",
-       "    ping_time          (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.66...\n",
+       "  * target_id         (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264\n",
+       "    channel           (target_id) <U26 132kB 'WBT 747022-15 ES120-7CD_ES' ......\n",
+       "    ping_time         (target_id) datetime64[ns] 10kB 2021-12-15T14:34:32.661...\n",
        "Data variables:\n",
-       "    target_range       (target_id) float64 10kB 5.805 5.805 ... 5.781 5.781\n",
-       "    angle_alongship    (target_id) float64 10kB 1.852 2.139 ... -0.00917 0.153\n",
-       "    angle_athwartship  (target_id) float64 10kB 4.524 4.304 ... -0.02378 -0.1533\n",
-       "    target_range_min   (target_id) float64 10kB 5.306 5.306 ... 5.306 5.306\n",
-       "    target_range_max   (target_id) float64 10kB 6.298 6.298 ... 6.298 6.298\n",
-       "    raw_ping_index     (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264"
+       "    target_range      (target_id) float64 10kB 5.805 5.805 5.805 ... 5.781 5.781\n",
+       "    target_range_min  (target_id) float64 10kB 5.306 5.306 5.306 ... 5.306 5.306\n",
+       "    target_range_max  (target_id) float64 10kB 6.298 6.298 6.298 ... 6.298 6.298\n",
+       "    raw_ping_index    (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264"
       ]
      },
-     "execution_count": 54,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -9275,8 +9083,6 @@
     "point_locations = xr.Dataset(\n",
     "    {\n",
     "        \"target_range\": (\"target_id\", [row[\"target_range\"] for row in target_rows]),\n",
-    "        \"angle_alongship\": (\"target_id\", [row[\"angle_alongship\"] for row in target_rows]),\n",
-    "        \"angle_athwartship\": (\"target_id\", [row[\"angle_athwartship\"] for row in target_rows]),\n",
     "        \"target_range_min\": (\"target_id\", [row[\"target_range_min\"] for row in target_rows]),\n",
     "        \"target_range_max\": (\"target_id\", [row[\"target_range_max\"] for row in target_rows]),\n",
     "        \"raw_ping_index\": (\"target_id\", [row[\"raw_ping_index\"] for row in target_rows]),\n",
@@ -9293,7 +9099,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 50,
    "id": "e0ca3c72",
    "metadata": {},
    "outputs": [
@@ -9335,7 +9141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 51,
    "id": "0e515b3a",
    "metadata": {},
    "outputs": [
@@ -9369,24 +9175,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 52,
    "id": "35823982",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "288c8f6e570547068b2e610390ce249e",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/html": [
@@ -9950,10 +9742,10 @@
        "    water_level        float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:48:22+00:00\n",
-       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-a577f8c6-d6f0-40b6-a146-74ba6cf37d4c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0ba12740-d1ce-40da-997d-3da1469b3a09' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9da823e5-62fd-4a15-9328-ef90ec138ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f03af67-de55-4761-a728-7e98edc188e0' class='xr-var-data-in' type='checkbox'><label for='data-9f03af67-de55-4761-a728-7e98edc188e0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83f25625-cd7c-49b8-9fd7-06f920564fed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abc85376-36c7-4428-a97e-75ea82185e8d' class='xr-var-data-in' type='checkbox'><label for='data-abc85376-36c7-4428-a97e-75ea82185e8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9594d9f1-4214-4e78-aff4-36a68cde1690' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' class='xr-var-data-in' type='checkbox'><label for='data-aa7cb116-0e97-4d7c-a7a3-6e6a97f9abfa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
-       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-396171c0-37ef-496b-a746-3dfed2186e7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-777af835-7f85-4f6d-a59c-7503467effd3' class='xr-var-data-in' type='checkbox'><label for='data-777af835-7f85-4f6d-a59c-7503467effd3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary-in' type='checkbox' checked /><label for='section-5577afeb-6e1d-4a3e-9722-e713d1ef83ac' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b94b868-71b4-4f51-bb13-1d44430c8f71' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' class='xr-var-data-in' type='checkbox'><label for='data-da9c00ae-a9e4-45ca-b468-663e6f202cf1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:32:44+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4b7617aa-3c8c-40e7-9c4a-369fa002dd31' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4b7617aa-3c8c-40e7-9c4a-369fa002dd31' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-bfcfcaa7-a11c-4f38-b591-4373a92013a6' class='xr-section-summary-in' type='checkbox' checked /><label for='section-bfcfcaa7-a11c-4f38-b591-4373a92013a6' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-8c8e44ca-1796-48c9-ae32-33739007040f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c8e44ca-1796-48c9-ae32-33739007040f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1712598-76c8-41c8-aeb4-5a82959ef54c' class='xr-var-data-in' type='checkbox'><label for='data-c1712598-76c8-41c8-aeb4-5a82959ef54c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-8f29476a-92d5-49c5-9efb-c7bcad8e9897' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f29476a-92d5-49c5-9efb-c7bcad8e9897' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3abd539f-d3f7-4532-9b30-b91672b62307' class='xr-var-data-in' type='checkbox'><label for='data-3abd539f-d3f7-4532-9b30-b91672b62307' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-8d2e3a9f-e18f-4059-bf3d-b9850dafdb6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d2e3a9f-e18f-4059-bf3d-b9850dafdb6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65fd6ad2-f9aa-4e73-9910-d15a9067d0f7' class='xr-var-data-in' type='checkbox'><label for='data-65fd6ad2-f9aa-4e73-9910-d15a9067d0f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-16a6ac73-9d7a-4ee8-a16c-171476165066' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16a6ac73-9d7a-4ee8-a16c-171476165066' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edb540ff-6bd0-4b69-9aab-ca05fc19adcb' class='xr-var-data-in' type='checkbox'><label for='data-edb540ff-6bd0-4b69-9aab-ca05fc19adcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-976c3fd4-d598-48ac-a9b5-49894c1bf125' class='xr-section-summary-in' type='checkbox' checked /><label for='section-976c3fd4-d598-48ac-a9b5-49894c1bf125' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-ea6931cb-ff67-471b-b470-347974ddd7d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea6931cb-ff67-471b-b470-347974ddd7d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88772d63-506d-4f4e-abf6-52f1be70e35b' class='xr-var-data-in' type='checkbox'><label for='data-88772d63-506d-4f4e-abf6-52f1be70e35b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
        "         -50.89344838, -51.56443826],\n",
        "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
        "         -53.05996696, -53.87369709],\n",
@@ -9965,15 +9757,15 @@
        "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
        "         -41.36476302, -41.37227431],\n",
        "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
-       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-adee60d9-a479-4c80-be26-ba9fe72cf471' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' class='xr-var-data-in' type='checkbox'><label for='data-3155626b-9e62-4baf-8b0b-992ddf95a4c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3fa2d7d0-e4f6-47e8-8d74-16d2cb2e6224' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' class='xr-var-data-in' type='checkbox'><label for='data-cffa51f0-84b1-439f-9c0f-c2078f8470bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
-       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb2b8e2a-4c31-4284-b464-c5dc1352aeca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' class='xr-var-data-in' type='checkbox'><label for='data-ee2142c6-eedc-42bb-9fb0-f1b30d9352c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
-       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2cd90cd-2c6d-4c4e-96ea-78623fc50042' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-126281c8-9e4d-4ea5-b809-8ad391850196' class='xr-var-data-in' type='checkbox'><label for='data-126281c8-9e4d-4ea5-b809-8ad391850196' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-0d9ece50-38f3-4ceb-9b1a-0cd8019f2bb2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d9ece50-38f3-4ceb-9b1a-0cd8019f2bb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab9b5104-1406-4dbe-af52-3695a5d2a273' class='xr-var-data-in' type='checkbox'><label for='data-ab9b5104-1406-4dbe-af52-3695a5d2a273' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-998266aa-c355-4800-9433-2fed87160d86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-998266aa-c355-4800-9433-2fed87160d86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d434e36-ef2b-4b3f-bb0e-ad80e53a4b69' class='xr-var-data-in' type='checkbox'><label for='data-6d434e36-ef2b-4b3f-bb0e-ad80e53a4b69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-3e12bfbd-dfc3-40ce-9916-38def277e131' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e12bfbd-dfc3-40ce-9916-38def277e131' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50366880-56ec-4cda-9fd6-838e1bbbc2da' class='xr-var-data-in' type='checkbox'><label for='data-50366880-56ec-4cda-9fd6-838e1bbbc2da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-5b5e2ab7-1a9e-4c5c-8ec6-93eeb7342147' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b5e2ab7-1a9e-4c5c-8ec6-93eeb7342147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb56b03a-42ad-4092-bcaa-87410fb200f5' class='xr-var-data-in' type='checkbox'><label for='data-eb56b03a-42ad-4092-bcaa-87410fb200f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
-       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1496af1d-a1c2-434d-a4d7-d14c2a20f758' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' class='xr-var-data-in' type='checkbox'><label for='data-e6985299-43ad-498c-9d3e-1cf15f43b2bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2928165-5c94-4910-b17f-3b92a04a08eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11b9240d-e7f5-49fd-b322-0bade58745c1' class='xr-var-data-in' type='checkbox'><label for='data-11b9240d-e7f5-49fd-b322-0bade58745c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-fa7a2b1d-059f-4236-b5cf-b0acf3c7c52e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:22+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-bc9db149-38fa-43cb-875f-2de9ad84e1c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc9db149-38fa-43cb-875f-2de9ad84e1c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-074b1161-3845-448d-bcea-6ad2f211a995' class='xr-var-data-in' type='checkbox'><label for='data-074b1161-3845-448d-bcea-6ad2f211a995' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-7232b93a-4fc8-460b-9393-58464f04c15c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7232b93a-4fc8-460b-9393-58464f04c15c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3807545-7afd-4855-a0e1-8d7e1029e9fb' class='xr-var-data-in' type='checkbox'><label for='data-e3807545-7afd-4855-a0e1-8d7e1029e9fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c4c1a8e8-dccf-464a-9589-ab8f6bc480f9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c4c1a8e8-dccf-464a-9589-ab8f6bc480f9' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:32:44+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 10MB\n",
@@ -9994,12 +9786,12 @@
        "    water_level        float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:48:22+00:00\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:32:44+00:00\n",
        "    processing_function:          calibrate.compute_TS_spectrum"
       ]
      },
-     "execution_count": 57,
+     "execution_count": 52,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10026,7 +9818,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 53,
    "id": "56d8ea09",
    "metadata": {},
    "outputs": [
@@ -10065,7 +9857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 54,
    "id": "c980db68",
    "metadata": {},
    "outputs": [],
@@ -10090,24 +9882,10 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 60,
+   "execution_count": 55,
    "id": "c96bb8ce",
    "metadata": {},
    "outputs": [
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5dec63c8df834dd788fb135d4ee90429",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "WBT 747022-15 ES120-7CD_ES:   0%|          | 0/1265 [00:00<?, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
       "text/html": [
@@ -10671,10 +10449,10 @@
        "    water_level        float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:48:48+00:00\n",
-       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4145e14c-9b49-4081-b726-de55f7550c22' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-df60d1b1-c4b3-4445-b71e-c6e1fc3a2a5e' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8dd22c23-9327-472f-b36b-fa312e2fbd0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' class='xr-var-data-in' type='checkbox'><label for='data-e438593c-62b5-4b4e-821b-bc1dfc97beea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e8055df-c129-4ed6-979d-12ed199422b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35821d9-abab-470a-bc4a-6881a65bef48' class='xr-var-data-in' type='checkbox'><label for='data-b35821d9-abab-470a-bc4a-6881a65bef48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2f04f2f-0b9b-46d0-a7f2-bdc0edb76d5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eadbf93b-afaf-40b5-9c16-331c32443d75' class='xr-var-data-in' type='checkbox'><label for='data-eadbf93b-afaf-40b5-9c16-331c32443d75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
-       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6b88e88-3663-4f6e-be49-81d5bc8ea65a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' class='xr-var-data-in' type='checkbox'><label for='data-be6bfcc1-6178-4737-925c-6b08fe4ca72d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary-in' type='checkbox' checked /><label for='section-043498cb-e5ee-4657-a5cb-a6a1c79ad995' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a550c822-08d1-4fb7-bc7b-2532cf6279ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8711bf66-67a5-4745-bb6f-867c71524ea1' class='xr-var-data-in' type='checkbox'><label for='data-8711bf66-67a5-4745-bb6f-867c71524ea1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:35:32+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d42c7f64-c3a5-47f4-baf6-c26f1f2bf0d3' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d42c7f64-c3a5-47f4-baf6-c26f1f2bf0d3' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-a57763c8-9b55-4a2a-9e15-9c15c6baa481' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a57763c8-9b55-4a2a-9e15-9c15c6baa481' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-617ea556-592d-44c2-8676-84165dfd7e8b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-617ea556-592d-44c2-8676-84165dfd7e8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90f28064-8cd0-425c-b17e-6a205ff0eef7' class='xr-var-data-in' type='checkbox'><label for='data-90f28064-8cd0-425c-b17e-6a205ff0eef7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-483e2f35-e0b7-41cd-b210-fff7cb5b731e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-483e2f35-e0b7-41cd-b210-fff7cb5b731e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1d066a9-1bc2-4627-ba96-5600678e3fa1' class='xr-var-data-in' type='checkbox'><label for='data-c1d066a9-1bc2-4627-ba96-5600678e3fa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-4a655da4-19b8-4acb-8440-31db7b7931a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a655da4-19b8-4acb-8440-31db7b7931a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce9e1ef7-821b-4bd5-af7f-de64d4a205e7' class='xr-var-data-in' type='checkbox'><label for='data-ce9e1ef7-821b-4bd5-af7f-de64d4a205e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a5ace771-b9cf-4867-ab13-e253c82ba143' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5ace771-b9cf-4867-ab13-e253c82ba143' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a009e095-3aa5-4437-aca8-2bf1439cf513' class='xr-var-data-in' type='checkbox'><label for='data-a009e095-3aa5-4437-aca8-2bf1439cf513' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5d01d24-ec31-4c60-9e0d-c70cbbee3213' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f5d01d24-ec31-4c60-9e0d-c70cbbee3213' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-8aa1c98b-c790-4d3d-8afd-82c033a417db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aa1c98b-c790-4d3d-8afd-82c033a417db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cf45bf3-06f6-48b0-adf8-dfb6c0ad0a84' class='xr-var-data-in' type='checkbox'><label for='data-7cf45bf3-06f6-48b0-adf8-dfb6c0ad0a84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
        "         -50.89344838, -51.56443826],\n",
        "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
        "         -53.05996696, -53.87369709],\n",
@@ -10686,15 +10464,15 @@
        "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
        "         -41.36476302, -41.37227431],\n",
        "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
-       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da786fe7-f92a-4ce6-8295-42f918ac04ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-283521b8-22a3-4b25-b915-d45c0f602f6b' class='xr-var-data-in' type='checkbox'><label for='data-283521b8-22a3-4b25-b915-d45c0f602f6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-59ab1373-b1f1-43a9-a061-daca06355610' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-59ab1373-b1f1-43a9-a061-daca06355610' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a425cfce-1395-4517-90e0-8b174b77b1c5' class='xr-var-data-in' type='checkbox'><label for='data-a425cfce-1395-4517-90e0-8b174b77b1c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
-       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46bd61c2-9143-4f8c-b8e1-737c71499d8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-123eed60-f204-4adf-864f-e653cbcc3112' class='xr-var-data-in' type='checkbox'><label for='data-123eed60-f204-4adf-864f-e653cbcc3112' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
-       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6eae573-18ff-4e87-aebd-776d803e68e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f8b5f57-193a-4307-8042-b7c150f6f916' class='xr-var-data-in' type='checkbox'><label for='data-2f8b5f57-193a-4307-8042-b7c150f6f916' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-05dbb1dc-c053-4ddb-b6a5-c6322f6c2b4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-05dbb1dc-c053-4ddb-b6a5-c6322f6c2b4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2435ba6a-6cbb-4126-9d5f-d9c0930e38fd' class='xr-var-data-in' type='checkbox'><label for='data-2435ba6a-6cbb-4126-9d5f-d9c0930e38fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-9a3bcf42-b605-40df-8bd8-eac50f54f1bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a3bcf42-b605-40df-8bd8-eac50f54f1bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc5d31f-ea66-42bb-aa50-ebe25b088fdc' class='xr-var-data-in' type='checkbox'><label for='data-2cc5d31f-ea66-42bb-aa50-ebe25b088fdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-7a4afd91-5957-4906-9cb1-598a9bc641da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7a4afd91-5957-4906-9cb1-598a9bc641da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a91be634-31af-45f7-a91a-2ac7a10ba45e' class='xr-var-data-in' type='checkbox'><label for='data-a91be634-31af-45f7-a91a-2ac7a10ba45e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-718e12a6-be37-402f-9cfb-195324fed9ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-718e12a6-be37-402f-9cfb-195324fed9ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-686277da-7bb8-414c-b778-87917358375d' class='xr-var-data-in' type='checkbox'><label for='data-686277da-7bb8-414c-b778-87917358375d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
-       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca8be6dd-b610-4ae9-b950-0f0c548b4285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de982c12-715b-4453-835a-32c729905ed9' class='xr-var-data-in' type='checkbox'><label for='data-de982c12-715b-4453-835a-32c729905ed9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94862f3a-17db-4df1-9a23-fb77436b7e55' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' class='xr-var-data-in' type='checkbox'><label for='data-5eb0b7c5-a01d-4ea7-bc35-4ed7adfd7657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f064f7a9-6886-41b2-814b-cd5a5d850087' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev22+gc1a2a5660</dd><dt><span>processing_time :</span></dt><dd>2026-06-07T01:48:48+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-33c389f7-8681-4c37-b237-5861e9b0a44d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33c389f7-8681-4c37-b237-5861e9b0a44d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebd9b8aa-5efc-4f19-bab0-caaea0890ab1' class='xr-var-data-in' type='checkbox'><label for='data-ebd9b8aa-5efc-4f19-bab0-caaea0890ab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-29e56c80-c8b1-479b-9c23-38730ea20713' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29e56c80-c8b1-479b-9c23-38730ea20713' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0799c5ca-d2e9-4dc3-9bd4-42123de790c0' class='xr-var-data-in' type='checkbox'><label for='data-0799c5ca-d2e9-4dc3-9bd4-42123de790c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e9cb365-b2f7-405f-9467-43f5980f839a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-2e9cb365-b2f7-405f-9467-43f5980f839a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:35:32+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 10MB\n",
@@ -10715,12 +10493,12 @@
        "    water_level        float64 8B 0.0\n",
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
-       "    processing_software_version:  0.11.2.dev22+gc1a2a5660\n",
-       "    processing_time:              2026-06-07T01:48:48+00:00\n",
+       "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
+       "    processing_time:              2026-06-19T22:35:32+00:00\n",
        "    processing_function:          calibrate.compute_TS_spectrum"
       ]
      },
-     "execution_count": 60,
+     "execution_count": 55,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10738,7 +10516,6 @@
     "    NFFT=NFFT,\n",
     "    n_f_points=n_f_points,\n",
     "    split_front=0.25,\n",
-    "    window=None,\n",
     ")\n",
     "\n",
     "ds_TS_spectrum_nfft"
@@ -10754,7 +10531,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 56,
    "id": "19c69452",
    "metadata": {},
    "outputs": [
@@ -10812,7 +10589,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 57,
    "id": "5016286d",
    "metadata": {},
    "outputs": [
@@ -10853,11 +10630,11 @@
        "      <td>TS_m dB: CRIMAC vs manual</td>\n",
        "      <td>1000</td>\n",
        "      <td>-41.615550</td>\n",
-       "      <td>-41.616483</td>\n",
-       "      <td>-0.000932</td>\n",
-       "      <td>-0.000277</td>\n",
-       "      <td>0.267273</td>\n",
-       "      <td>5.134085</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>-0.002203</td>\n",
+       "      <td>-0.000048</td>\n",
+       "      <td>0.016260</td>\n",
+       "      <td>0.071437</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
@@ -10874,41 +10651,41 @@
        "      <th>2</th>\n",
        "      <td>TS_m dB: manual vs API</td>\n",
        "      <td>1000</td>\n",
-       "      <td>-41.616483</td>\n",
        "      <td>-41.617754</td>\n",
-       "      <td>-0.001271</td>\n",
-       "      <td>0.000360</td>\n",
-       "      <td>0.265814</td>\n",
-       "      <td>5.135526</td>\n",
+       "      <td>-41.617754</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
+       "      <td>0.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>Y_pc_t_m dB: CRIMAC vs manual</td>\n",
        "      <td>1000</td>\n",
        "      <td>-35.450622</td>\n",
-       "      <td>-35.448239</td>\n",
-       "      <td>0.002383</td>\n",
-       "      <td>-0.002111</td>\n",
-       "      <td>0.288531</td>\n",
-       "      <td>5.399668</td>\n",
+       "      <td>-35.450851</td>\n",
+       "      <td>-0.000229</td>\n",
+       "      <td>-0.002369</td>\n",
+       "      <td>0.015977</td>\n",
+       "      <td>0.061057</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>Y_pc_t_m dB: CRIMAC vs API</td>\n",
        "      <td>1000</td>\n",
        "      <td>-35.450622</td>\n",
-       "      <td>-35.448239</td>\n",
-       "      <td>0.002383</td>\n",
-       "      <td>-0.002111</td>\n",
-       "      <td>0.288531</td>\n",
-       "      <td>5.399668</td>\n",
+       "      <td>-35.450851</td>\n",
+       "      <td>-0.000229</td>\n",
+       "      <td>-0.002369</td>\n",
+       "      <td>0.015977</td>\n",
+       "      <td>0.061057</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>5</th>\n",
        "      <td>Y_pc_t_m dB: manual vs API</td>\n",
        "      <td>1000</td>\n",
-       "      <td>-35.448239</td>\n",
-       "      <td>-35.448239</td>\n",
+       "      <td>-35.450851</td>\n",
+       "      <td>-35.450851</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
        "      <td>0.000000</td>\n",
@@ -10920,23 +10697,23 @@
       ],
       "text/plain": [
        "                        variable     n  CRIMAC mean  echopype mean  mean diff  \\\n",
-       "0      TS_m dB: CRIMAC vs manual  1000   -41.615550     -41.616483  -0.000932   \n",
+       "0      TS_m dB: CRIMAC vs manual  1000   -41.615550     -41.617754  -0.002203   \n",
        "1         TS_m dB: CRIMAC vs API  1000   -41.615550     -41.617754  -0.002203   \n",
-       "2         TS_m dB: manual vs API  1000   -41.616483     -41.617754  -0.001271   \n",
-       "3  Y_pc_t_m dB: CRIMAC vs manual  1000   -35.450622     -35.448239   0.002383   \n",
-       "4     Y_pc_t_m dB: CRIMAC vs API  1000   -35.450622     -35.448239   0.002383   \n",
-       "5     Y_pc_t_m dB: manual vs API  1000   -35.448239     -35.448239   0.000000   \n",
+       "2         TS_m dB: manual vs API  1000   -41.617754     -41.617754   0.000000   \n",
+       "3  Y_pc_t_m dB: CRIMAC vs manual  1000   -35.450622     -35.450851  -0.000229   \n",
+       "4     Y_pc_t_m dB: CRIMAC vs API  1000   -35.450622     -35.450851  -0.000229   \n",
+       "5     Y_pc_t_m dB: manual vs API  1000   -35.450851     -35.450851   0.000000   \n",
        "\n",
        "   median diff      RMSE  max abs diff  \n",
-       "0    -0.000277  0.267273      5.134085  \n",
+       "0    -0.000048  0.016260      0.071437  \n",
        "1    -0.000048  0.016260      0.071437  \n",
-       "2     0.000360  0.265814      5.135526  \n",
-       "3    -0.002111  0.288531      5.399668  \n",
-       "4    -0.002111  0.288531      5.399668  \n",
+       "2     0.000000  0.000000      0.000000  \n",
+       "3    -0.002369  0.015977      0.061057  \n",
+       "4    -0.002369  0.015977      0.061057  \n",
        "5     0.000000  0.000000      0.000000  "
       ]
      },
-     "execution_count": 62,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10964,7 +10741,7 @@
     "        _compute_ts_spectrum(\n",
     "            pc_target=y_pc_t_n,\n",
     "            mf_auto_red=y_mf_auto_red_n,\n",
-    "            NFFT=n_f_points,\n",
+    "            NFFT=NFFT,\n",
     "            frequency=f_m,\n",
     "            fs_dec=fs_dec,\n",
     "        )[0]\n",
@@ -10980,20 +10757,9 @@
    "id": "5de90b9a",
    "metadata": {},
    "source": [
-    "** NOTE ** - ware we using als th NFFT or freq here?\n",
+    "The manual and API workflows produce the same target spectrum (`Y_pc_t_m`), confirming that the target-window extraction and FFT step are equivalent.\n",
     "\n",
-    "\n",
-    " ** NOTE ** to remove Llod - The API and manual workflows produce identical target spectra (Y_pc_t_m), while the final API TS spectrum agrees more closely with the CRIMAC reference. This suggests that the API implementation reproduces the calibration and correction steps more faithfully than the simplified manual reconstruction used in this notebook.\n",
-    "\n",
-    "The key observation is really:\n",
-    "\n",
-    "Y_pc_t_m: manual vs API\n",
-    "RMSE = 0\n",
-    "\n",
-    "but\n",
-    "\n",
-    "TS_m: manual vs API\n",
-    "RMSE = 0.266 dB"
+    "The remaining difference in `TS_m` reflects differences in the downstream calibration and beam-compensation pathway, not the extracted target spectrum itself."
    ]
   },
   {
@@ -11006,7 +10772,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 58,
    "id": "a8ee9fe9",
    "metadata": {},
    "outputs": [
@@ -11021,22 +10787,12 @@
       "api theta/phi: 0.1980538342357811 2.1279301087201414\n",
       "CRIMAC ping index: 509\n",
       "CRIMAC range: 5.79306\n",
-      "CRIMAC theta/phi: <xarray.DataArray 'angle_alongship' ()> Size: 8B\n",
-      "array(0.19805383)\n",
-      "Coordinates:\n",
-      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
-      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
-      "    range_sample  int64 8B 975 <xarray.DataArray 'angle_athwartship' ()> Size: 8B\n",
-      "array(2.12793011)\n",
-      "Coordinates:\n",
-      "    channel       <U26 104B 'WBT 747022-15 ES120-7CD_ES'\n",
-      "    ping_time     datetime64[ns] 8B 2021-12-15T14:36:42.927639\n",
-      "    range_sample  int64 8B 975\n"
+      "CRIMAC theta/phi: 0.1980538342357811 2.1279301087201414\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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Q7KYxDMMwDMMwDMMwzYiJEydS165do34PBoOybPzWrVvps88+kyXuX3nlFbr88suT0k6mYbT4cJiCggK6/fbb6fTTT092UxiGYRiGYRiGYZhmgIgouOyyy6S4MXToUPrhhx+kV0h42mGHHUbLly+vE0mEEHLqqafSunXrZFQCk7q02MSoQp176aWXpDonwmKcXJzEJ0woFKLi4mJq3769dHtiGIZhGIZhGIZJJmLcevPmzdLg9nqbtzN/RUVFwsJGxHHRbbaMjAz5iYe1a9fSmWeeSa+99ppM+K0zf/58GjZsmOIlMnr0aGlXfvfdd7TffvvFtX2mcWlxIsgvv/wiRQ9xc+Xk5NCrr75KQ4YMMc4/bdo0uv7665u0jQzDMAzDMAzDMA1FeB4053Ljwkbr0yuH1qwLJmR9wt7bsmWL8tuUKVNo6tSpcQkrwqPjnHPOoV122UVWO9NZs2YNderUSfktPz+f0tPT5TQmtWlxIsigQYNk0pqSkhLpujR+/Hj65JNPjELI5MmTpZtTmNLSUlnOb0/6F/kprQlbzjAMw8y57T/UIb+CNmzMpNMnjuYDwjAMwzBEFKBq+ozeprZt2zbr4yE8QIQAsvS73pTbNj6Plk2bQ9Rr5yVSGMLwE5MXiBBG6hv8/uabb+iLL76gTZs2STvRCbuoATvPFCb1aHEiiFDf+vfvL/8Wyp24kO+++2568MEHbec3uUsJAcTvYRGEYRimKWmb5aHcNkSVFR5+BjMMwzBMmNosji3FwM5p65GfeAhRzfLhyqD1ccEFF9AJJ5zgOE/v3r3ppptuoi+//DLKRhS25UknnURPPPEEde7cmb766itl+saNG6m6ujrKQ4RJPVqcCGKnxmHOD4ZhGCZ1WVtqUaVFVLKpRefsZhiGYZhWTdAKUdCKfx0NQZSxFZ/6mDVrlhRCwqxatUrm+3jhhRdo+PDh8jeRfuHmm2+m1atXU5cuXeRv7733nhROdt555wbvC9O0tCgR5KqrrqJDDjmEevToIRMHiQy9H3/8Mb377rvJbhrDMAzjglEzKmh1CVGXdhU0lI8YwzAMwzBNjEiNoOcdEfTr168uH8uoUaNkuoVx48bJSqSisMaECRNkMlWuDJP6tCgRRGTxFReiUOTy8vJou+22kwLIQQcdlOymMQzDMAzDMAzDMDKUxZKfeIh3+Xjw+Xw0b948Ou+882jkyJGUlZVFY8eOpRkzZiStTUwrFUHmzJmT7CYwDMMwDMM0C9LbpFNuh+wWk2OAYZpz+P6mDVupqiwxZWObAyH5X/zraApEnhBxjuw8Rt56660maQOTWFqUCMIwDMMwDMM4IzSPfU8bQbsevj35030sgjBMkhEGdqAqSN+8+RN9/NgXZGNvtziCliU/8a6DYWKBRRCGYRiGYZhWhBBA9jphNypoV0Be8iW7OQzDSK+GIO11Qk01ko8e/YKPCcM0IiyCMAzDMAzDtBIystOlB4gQQNIoPdnNYRimFh/55H0p7s/Pn/+2xYfGNPecIEzzhkUQhmEYhmGYVkLb9tkyBIY9QBgm9RD3pbg/Ra6eDctavggSZBGESRLeZG2YYRiGYRiGaVpEElROhMowqQvfowzT+LAnCMMwDMMwDMMwDNNkcDgMk0zYE4RhGIZhGIZhmhmDdu1PH3z8fqNuY8WqFXI7v/2xMK71zH7objpy7OEJaxfTcqrDxPthmFhgEYRhGIZJGV65IIN+nV7zL8MwjM76DevpxtuvpwOO3I+GjdiG9jl0Tzrn0jNp/teRahr7H7GPNNzFZ7s9h9LBx46iR556WJYhNRn34e9Ddh9Ea9etUba5bsM6+buYLubT+fcF42mb4QPpx19+sD1hC/9YQBdNuoBGjB5O244cQqOPOZCuuekqWrx0cVwn+LN35tPeI/amxqRLpy5yOwP6DaTmCF4L4c+M2bcp86xas0peQzvstS0NP3BXumnGDVRVrebjePv9eVLE2X7PYbTf4XvL64lhmOYLh8MwDMMwKUP/Tl4qLCBaX8waPcMwKkKAOPGM4yk3py1dcdFEGtR/MAUC1fTZl5/S9bdNpXdffq9u3ovOvoSOO+p4qqyqpPlff05Tb51COdk5dMLRJzoe1o4dOtJr816ls087t+63196aS50KO0ljWUf89sMvP9JJY8bRy6+/RDtsu6My/aNPP6QLrzyf9tx9L5pxwx3Uo3tPKt5YRO9+8A7d/cCddNe0WTGf5sIOhdTY+Hy+JtlOYxK+FsK0adOm7u9gMEhnX3IG5ecX0LOPPE8lJSV05fUTpWB27RVT5DyffP4JXXHt5XTNFdfRnsP3pH+W/CNFrMyMDDr5uFOSsk8tgVDtJ951MEwscC+TYRiGYRiGSXmunz6FPB6il56YSwcfcAj16dVHeiicdtLp9OJjLyvzZrfJlsZ7967dacxRx9OgAYPo8y8/q3cbRx16NM196xXlt7lvzZW/2zH3zZdpvz33oxOPHUtvfzCPysrL6qaVV5TT5BuupH1G7ksP3PEQjRg+knp060HbD9uBrrxkMt1w1U2OHgz3PnIPXX7NpbTj3tvRnoeMoKdeeNIYDhP2ZHnvw//QuHNOkh4LR4w9jH74+XtlmRdffV56z4jp519xLj32zBzaZT9VuEF0j5mvvvtSfheeN0efcpRczwn/HkOLlixSlnvo8Qek58uO+2xPV904iSorK6PW/cobL9MhY0ZL7xjhrfPMS0/XTZt8wyQ6/MRDqaqqZrnqQDUdPe5Iuvyay6ihhK+F8Ed8D/PZl5/R34v/pttvmElDBg2V52jSJZPpxddeoC1bNst53njnNTpg3wPpxGPGShFr3z33ozNOOYsefuIhxbuIaRiiMkwiPgwTCyyCMAzDMAzDMClNSWkJfTr/f3TSsSdTm6zISH6Y3La5tssJI1UY7v8s/of8/vodoPff+wAq3VRK3/74rfwu/i3dVEL77bW/7brnvvkKHXHIkdSvdz/q3bMPvfP+23XTP5v/KW0s2UhnjDvTdlumNoeZ8/TDNKj/IJr71Ot09qnn0LQ7b6bPv3IWcu68/w46/eQz6LVn3qTePXtLESUQCMhp3/30HU259To65YRT5fQRu42kBx67v95jYr+dmTTp4sn0ypOvks/vl0IHho7MeuhuuvTcy+iVJ16lwg4d6dlXnokSY0RbxTxvv/gfuuy8y2nWg3fRq2/NldOvmXAtlZeX0Yx7bpff777/Tnksp066vm4d484eS5OmTqy3rY88+RANP3AXGc5y/6P3KaEuIoRJCGnC0yeM8NqpqqqiX3//VX4Xf2ekqyGamZmZtGbdGlq5emUMR48RBK3EfBgmFjgchmEYhkkZXvk2QP40okB1TaedYZimoefSo8gXXN+khzvoK6RlvV5zNe+yFUul6NC3dz9X88+45zYZblJdXS29CDIyMmjc8ePrXS7N75eihvBS2GWHXeS/4rv4XeeLrz+X3h7CaBYccfCR9PIbL9ExRxwrvy9ZvkT+67bNOjtttzOddeo58m/h9fL9T9/R488+RiOH72lc5t8nny49FQQXnXUxHXr8IbR0xVIp0jz9wpO094h96PRxZ9StU3iKfPzZRw1u26XnXk677Txc/n3W+LPprEvOkN4e4jg/+dzjdMwRY6QHTs28l8mQpMrKiPhw35x7pcfFqP1Hy+/CQ0Z4ZLww9zn6v8OOlt4awjtj3NknUXabHHrsmUfp8fuepLY5bevW0aVz13pDdU45Ybz08MjNzaNfFvxEM++dQStWLaebr5kmp28oWk8dCtory+Tl5lFaWhptKNogv4vzKwQo4f0yfJfdaenypfTEc4/Laes3rJPeRgzDNC9YBGEYhmFShhter6bVJURd2lXT0GQ3hmFaEUIASQuspVQlHHbgEfEwLjh93Jl09GFHU/HGYulxsPsue9BO2+/katljjziOjj99jPROePe/79ALc16iYDBamBU5QP510KF1HiaHjT6cbp81XYaG9O3dN+5QCT2/iPj+xPM1xrcJkScljPDAEBQXF0kRZPHSRXTgvqOU+bcbun1MIogIL4psp0aIKNpYRF07d5U5M044ZmxU27/69qua9mwsotVrV9PVN06ma2++um6eQDCgiBw7breTFHXum3MPnXnKWbTrTrsp67zt+hn1tvPUsf+u+3vwgMFSDLnoygtowgUTKb9dvvmasiK/H/d/x9Oylcvo7MvOlF41IreMEFdmPzRL5kxhYoNzgjDJhEUQhmEYhmGYVo7wykjlbfbq0Vsapf8s/psO3PegeufPz8uXy4jP7On30qijD6Adhu0gcz7Ux8D+A6lvr7502TWXSPFAfNdLxIrwnA8+eV8axc+98mxkn4JBeuXNl+mKCydSn5595G+LlvwjDfpE4CFnEQg9VsJGfMiqSR8pNBnd4I9VqPELlz2tTaGQuzSVoVDNNm+8+mbaftj2yjSvNyIqiPUJ7xchNAjvi0QgroGwZ5EQQTq0L6SfFvykzCPCoYT3UPtaDxFxzMT5FKKY8BwRSVTnfz1fTuvWhb1AYiVEHgrWcz27WQfDxAKLIAzDMAzDMK0ct2EpyaJdXjsZlvDMy0/TuBPGR+UF2bR5kzHHhghvOPm4cTT97lvptWfecOVNIkJaRCLWqZNusJ3+5rtvUOeOnene2x9Qfp//zRcyKagIARm5+57S0BblVO+9PTr3hlObBT/9+mPUd+FhEitiWRESgvz62y+UaIRwJHJtHHXo/9nuS4f2HahTx060fOVyGWpkQhw34VXy1IPP0hkXniZDk8KhRrGysFbMCnvJCA+VBx67T5ZBFpWBBCKBbnp6Og0bPExZVogxnTp2ln/Pe+9N2nHbHeuEEoZhmhecGJVhGIZhGIZJeaZceT2FgiEaM/5o+s+H79KSZUukZ8iTzz9Bx/97jOOyJ405mRYvWySXc4MoqTr//a9pzJHH2U4XoTCj9z9YeongRxjpm7Zsoo8//0gKNTddcwt98tnHdM5lZ9EXX30uq638svAXum3WdJoy7VrHNggviIeffIgWL11Mz7z4lAzNEWEYsXLy8afQJ198IivCiGP3/Nzn6H9f/M91iJFbROJV4Q0j8qOItouEp38t+kuZ58IzL5JikcitIeb54+8/pMgh2iYQnjdiOZG7Y+ftd6arLr+Gbr7jRlq+YlndOiZOmUAzaxOn2iHynTz+7KNyXUJwEQlbr5t2rUx+K8J2BHvuvif179OfJl43gRb+sUDm/Zh+9zR5/nNqQ3OKS4qlt48QZMS6bppxozwXok1M7AiHoER8GCYW2BOESTk8WnylFQxSyuPR9MRa11OGYRiGYRKDSJ459+nX6YFH76Ppd02To/cF+QU0dPAwpWqIHQX57enIQ46iex6aRaP2q0nG6YTI81HQrsB22q+//Uq///WbDOfQEfkiROJSIZIcuM9B8vPcnBelwX/5tZfSlq1bqEunLjJHySXnXurYBlH6d8Fvv9K9D8+WiUKvvHgy7bXH3hQrQky4ftINdM8js+mu+++kPffYi04de5oUWBLJv0YdSstWLqUZs2+jyqoqGr3faDrxmJNktZwwImlqZmYWzXnqYbp99nQpGA3sN5DGn3iaTLA64drL6OjDjpGChZz/yOOkmHTFlAn0zEPPSa+M1WtWkVfvfwHCm0MIH/c8PFtWhOnauRsdd9RxsrxtGLGeB+96RHr9nHi6aFOmzO1y5cWRajeC1+bNpdvuvlWGDwnvkaceeEbmU2FiJ5iAcJh4l2daLx6LC1wrbNq0ifLy8uiAvHHk96STVV0dOVjeyIPW0ioXeNIjsZFWbSky+XtGpKSWVRXJih0qrzAa/lYgsk2mdeJNT498wRe8N/Kw9+ZGkocJQiWbIotkZdqLSrB8zXdYdwZsE6V1PSN+CEQpiN1VqKyM/J2mLQ/XvnIfgdjlwf0X+KCdmVCmLhBZxtq8JfI3bl80Ge49JrVZkPdybWJUoqGl8bk9MwwTTWGvAjrr/pOoU4fO5CNO6piq7H/EPtKjQogUjck1N11Fi5Yuomcffr5Rt8O4I0hBWrthDT107jO0fmmxMi1gVdPH9DqVlpZSbq5zeeXmYGt9taAz5bSNLyhhy+YQDR+6ptkfE6bpYU8QA8HSTeTxRISNeqlURY06ystdLW4F2HOAaZjRHnK6tkzXYxPhzci0FQglIMoo4h8KNCjIiGkVkf3x4K5hAjgUTlDcEZvMyoqsC46t8ndz8DjS8OXluZrPg0KWdmxlprz6AGGXdIHKhMM1jMfa2lquXSviOrAUMVA/N83xXDEMw6QCc556hEYOH0lZWVkyFOa1ea/SlCunJrtZTCuEPUGYZMIiCMMwCSeEIoyTIINeLhBC5MvJUWYLbtliK5zg363R2yMExyVKCEKhAY6zBwUNuZLIcbeqqu29b4KReTzoiaMvD+t2FOlMiGslz2rV55RhGKYx+XnhT/TIUw/R1rKt1KNrD7p6wrUyNIVhmpqQ5ZGfeNfBMLHAIgjDJIlmmfsk0Rhyp+jhZso0NO4Nxww9UXRRRp9mN09zIcpDwo3woAkLXghXciU66MfJIGQxDMMwsfPhG580yuG7e9rsRlkvwzBMc4JFkPrgDn7LIoXOZ0qIHnA8vDjCD5ni9ZF/a8tW25w3mPsjOsQhQqisrF7PBV2QULw/cJuG9ToJGo0ldnj86n5GhQHZ5RYCL4qo+ZQ8QQH73zWxyLRvyjLadRe3t0WC76OObT3k9VjUIcdDVJrQVTMMwzAMkyJwOAyTTFgEqQ8e2WxRqIZlqMmTnKacez9c38bwBRAXdLyG0BRFOMGwCrEM5OfA/CCIT887gYICGP4ooqAIkgwcExrDcfa0aWPMx4E5Sjx5kQRfHpwPj7O2GV92fmRdWvLlut8r1KSxHsjFkgrC3PsTM6mwoJzWF2fS2IuS3RqGYRiGYRqDIHnlJ751MExssAjSXCuGuAwLYFSSUnkHvS3wHGpVV5JtxMcLGvDetpDTQ/d2yIVwFDTuwfskCqwwg3kr4Hd/RpfI73qYyNbIsQ3C340pcpquteDmza6WDxZvrF9U0zxB/Bn5ttcXVqNSPH60427FeQ06eZwwDMMwDMPU9RMSkBNErINhYoFFEAPerEzyelTRAUed9dh7ZRoYfej6jsaXWL8CJB705kYMyMD6DbARVS31pPts14eVIKxKKMuLxp9upBnCRBKetyKFwlHiBvbFl69W6fCkpdmeA+V4ah4SKAhgiVsMP7GgdK03J1tZPFhSEpkG16O3XV69nhdy3e2gtJjPY6y0YsE0TxUY4SH7eSxtm97KansRBO4BK1MLLQGvHSsn4kniCcLyFVDpZUORvnv1X3fa/RV1j9q0WRF7dO8VKK8dVZHFVH4Y7y8o/6tcK3hucR4BiBimezWkeYIk8j5k4YNhGEXQdlN9qiXvvy7uO4RAulpfazyeDMMwjQCLIAZElQQhLiqdeqekgy7CHLzgBq8YploJUALjy1cQGdn1aEZaCHMzoPCB1R/QW0Qbmfa3bx+ZVhkxjDzZkXZaZZrYUxhZJtQW3PrR6PVH2hnK0LwdYJoXDFtPNVQG2axu00qPrMO7KTItlAthFdhGLczFg+sDY9KCEAsrU22nt8xwPkGEIAw3QINXO26e9gX229cMfS+EPxCEKHjy20V+V86tup9+vKawPdiBgvOsE/ztT4oH5VrNBFEOvTjkD17jcaubRTfuQ0H7cq+4b3jMUJwQh231GtvtKJ45mliD3hN+uO7x/iTwqrDSfGbhBq57FJWilqkO2i8DHV+8H/Rrndq3jUwDUciDOV4qqs3PLri+rdJNkWXw2tSFGxRoSjYpZcaT6oHlAHusMIwDyjNWuXPgb8vBUDcY/cZ1ORj3TgMv+MzG5VHYjUUzcCs6mOZzEkHw2OqVukzguhVB3WP7jow6tqZz4HRslH0w/K4cczK/FxThx2UDcN3Y74pFRGJSFs4JwiQTFkEM+Pr1Jp8vQzE4yntEDAxLG8T3BKCsY1rkIR9MB4MH39c40i6Wh4d8CKaFwE7WPb48+F7DdxG+uyzz+8YbdLOMuhBO8wQNbcEXlr5NOE6eAIol4DHTQxM3cJsWGGOG9QbT1QMVSsu397ZwODaKJ4PJ0w77H5qDRcjvsb9WvA7n03AOTfNE9R+sGJZBDaF6QL3nWT/W3mrL9nd/ubmj4q0C8QuNbgePxhB4PWGb8b7DdXk0gcjTu1Nk+5UBW6HBW6F2SH2mw4bXEAhsHkgGGyVAFhVH/lbuD7WdVgO9riwHoTUEYUNKCIwmEIWgbR7wLvLkRp53wTXrzB4yKOqAUKzkiNGFMNg3RRAOhmjC89VUVk3UJq2a/F0hxAkB7ypj7hjd+MDvfoPxhF4y2jWEIptSStgJ2E8s88y0LDApsh5uhp5XeO/gwAMaxsrvDoKdF8qIB0tLXeWhCq9L/ivuByFIi49uWLo1zt3gJHwgRhHBYXmcL5Hhd269LUzzORnqDt6YrsD3B/YtsCl6igVjqCm+i3RRC2czHGen/Yz3EjKJLeiZGnUsDX1P5drQ9tMH76ZgoOHiGbYBt8PeO64IWl75iQd0CGaYhsAiiIHinduTL13t7KPBh0Z/lNGL/WvDSypKRMGXjEloIHdGM4obqjGrPim8hpcUzqcIGtq6Tcassh1dBAGPDzwGVjkIImlaWAKMduvT7PBraQ1CIETpYoUJCw0erynMAxfQRC14aQdBFFPEJn2jcE15YxjsUNsJq/UaBBHtOsa4TEWs0hpamQvHEwalQn7D4dAH/Fy87/T7y7S88V5z2oZJLHLotCn3EQp+hnstavlgX/t2Rs0Y+dNbZb8dHzyH/BXa/Qm2ua8SvKsq4O9K1VjwdSywF25wvRCiF+Wlgx2/jIjY5MEOsi4ooNgA95pIevv+giCtLiHq0i5I22fWrlvbpsmAJNhnJXeMZoyiZ4oiHDXzvDxMcsDrKbjFLJCFyuD9h/eNgyepSQwNbjLnFjIl4A6vS/4r3lFChBUPay3kUQntUwYEHF5g2IVxyu9kWh7b6WLgIRr7qmGOxGs8udjNqH0xOEKY3jHR7zlPQvbzqgkX0eZNpTT7ocejtu92XY7L1O7DKScfTdsMHkpXXX2D8rsdSn8T3h8rli2hAw7di157fh5tM2CbyDz6vWES0pxErXgFP5P4xmFLDJPysAhiIHN9gPxpAeUhjx4eToaMceQdDRzsrEe9AGF0HQwWb5X6sPVuRkMAwzzsT6veMVHc7ZXG2P9csxBsH1z3ldFxDHPBnBG6MWR4meshAsZpsD8hDBHQK26AW6YHjyF640SNgthPs7CzaHIRlQ1Cbwn7kZNgtponorptmq1wY7rW9M5VCDxg0GhWOlC6IIFeR3jYceBHq/SKAokPo25CBsFQF8Kq7L1HTO2SbcjAe89TrzCpHzNcHvdH2X/ttkGREI+b4p1lEn60/dbXHZlJ+44pUrBiMf6eFVmoqq12TyuCF1xDaLvoDg4B+7AyZV1BB8+goL0XlioSuntGymWeCc9EtPqY/rZtQzEWO9VOnXLjMxuPjcNgsuL1pBwPszhuEq8Qf1nQViSW3yvw+R+wfQ7qz1jMwaM8Cw2dcg/m6NHDpSAkLLSxxJiPSDGiIR+SKReOlZVuXB6f5V4I6YpqP3pI4LsME/3qHpdwrvB9GMq0XxeGb+rrw+sJ+wY4IKJPc3c9ml/A2H5lOy7t4vD12SY/i6zsDArlZRH50hw9BI04ib6Gfo9bjPcx3B4/fP8NnTz2KBoxcm96eM5zyjIrVi6nA/ffre57bm4eDRw4mC66eCLtttse8rdJky6RIsC99z1mu6m5c1+gabdMoW++/V2dYNw3w3n2uN1Pp4dXzUpeFW26+Tr6+vs/ojfp8piHZ7vqmhvJsqy6Z5TDq0hrdFSz7Km9je9+YA6l+dMi94FjO/EH8A5uW/MyDOSkU6DA/n3lGJJF7o6z/l665+4ZdN+smco87TsU0qdf/RyZzbLo3lkz6aXnn6ZNpaW03fY70jVTp9HAgYPq5lm2ZAndNv16+v7br6mqqor22ns/uvq6m6lDh0J7z+lQNdHmdArtOoRCvbYqbbMCFURfvE4thRB5KBRndZhQ3Gom01phEcRA5oZy8vs0V3XoeOqCgqmziTH+2NHzbq00J5tETwpDmcsoNzxYnafKPmeCLo5Y1bhN+3ZGdSKhw+2BsALFLRIf6tqIlJIrQylXC+vFBJ0amHBU+R1yj+geL6EscFUur65fBJIr8dSbp8EkyETlasDrAQwM78ZITheBPwdcpfHY4HYUw1Tdz0B2mq2XjpVmPp/YyceQJMXbwmHkSfEACtmLfLoo5dsaOdc+7T4IE8xWR/WCWXDtYnoN2E9vuX2Yi6CqXcToCmbaH49AprqfvkowmNBjFgx9o7jhgONoqslLBe8pJ6Pd03CPFRSllFW57FegkBWKYcRSEZK0ZTI2WbYeXIoIYuhUxx1uFtVQMnrI2W1fLgLtDuAzHp1kIFRIF0o8bfECg/wzHvMxU68VezHXadQZQ8zw/iLqCvuliW9KTqgGGv3yGWvvfeirQsVRXQaFYrynlfXqIqvJADN4/kV7Mtqfd8VDUhOyrCrTxQZ/Onn+YcggXkNOIgTsN56P8HM5w0qT7w9x73rrHbE2eDJGLRanIWI1bJ65Lz1HJ590Gr38ynO0Zvly6tqlW6Rttf2Rxx99nvr3G0RFxRvozrtupbPPOpnefO1D6tG9Z811ZtnkVapZQ937NWq66RoyGeAe4SwQJH/YY82YR8PBOK9ddzjMs+7dbxJBoncn6s+8Nm0dYwk8LtQrJ4/PMPlta8ORw/eIkwhi2IfwgIT4F70do7eZOGNYXB/iM2DAIHr0sRfqfvf5fMo77+GH7qEn5jxI0269i3r37ksP3H8XnTH+eHrnnU8pJyeHysrK6IzTTqDBg4fQ44+/JJeZNes2Ou+sU+iF598ir53oKU6zZZF/cxX5S2v7SLX3vhVMrfxa8cI5QZhkwiKIASFSeH1azoDNDoIEYooxx86qFtNuTPaIIoIe/4iDaTgNtwnrjfLKRK8Mw3YwoWLUutGNEN3VYT8xeav8jssbqlL4Ma4/amK1rbu7B5fR3BuVnAOYTFbx6tD2U3PRj8wGndA2WfY5BpyMXiVZmFbtZ22R/XHHc4v7qVX5SMdcD+gqDaO2Vhuzy3CgXZa9YaV7EGECUvSSwWOD11ZUbobIn6EM+3ONBk70RDIYBWA8rVNj5P2RlBbKMcTlg23VESYfJMfF0elgTmT5QBYKVC6Nfhcdx6j53HiakYMxi947WjiMIh5B7hXlHKK3g240oZGAx7MNHGeHY4P5XqQBGl69RZRRGrQdXVc8iAzu2VFGt+JxUr84oKOISmhkooefU3CySTdxOraG+ZTV6sfWTW6FUP3eWPp8TgaXSfgwtlMXjbE94K2nDCJoy4RAHPaVewwhl+btKNNMh0BbHvMJ4faVbeieiKb9Nh1bHVPbFDE05MrjJexZky5WKuapFp4AIeftK5eQ/X3jtIyb9jvOZ7MdYVi+8+6b9PKzb9KGdeto7svP0wXnXRqZoXb/2+XmU2F+B/m54ZpptPdBu9Hnn31MJ4w5uTYcSByH6H7IV9/Mp8nXXCb/HjS0u/z3gnMuoQvPvYxef2suPfHMHFq8ZBG1yWpDu+82gq6aOJXad+hQt+wp/z6OHnngKbpz1m3055+/0yMPPk3Dhm5PU26YRP/96D+Uk92WzjjtHPrvR+/R4EFD6eorp8plq6qr6K7Zt9Obb79KmzdvogH9B9GES6+i4buOoK+++YImX13TpsGDawTJC869lC48//Ko4zT7vjvogw//Qycefwrd/+DdVFK6kfbZ+wC6aeptlJtX0x+adNWltGnzJrpv9hz5fdz4Y2nQwG0oPSNDCktpael0wvEnR9ZPRP8s+puuue4K+nXBz1JIuuaqG+i0M06ke2fNoQMPPNj2/I475VgpAFw9uSYcZv8Dh9NxY06ipcuW0Lv/eYvy8vLo3HMupuOPE+ekZpmff/6Brpt6pdyeECHOPfsi+bs3GKq7v//++0+aPuNG+vbbLymrTRsaOWJvmjz5eirIL6Cvvv6CTj9jLD3+6Iu0yy7D5fyPPvYAPfjQbHrz9Q+pY8dO9ecRESJI0CKf10cd82vOrf7OE14gTz7xCJ1z1oU0er+D5T5Pv/lOGrH3jjTvjbl0wnEn0w/ffEUrVy6n1156l3JyaoSnaTfMpN1GDqOvvviURuw2IvqgWUF5X3qKSskb7stk1PTdvCFzcnuGYRoGiyAmSjeLHo/Znbj2gVSvwIEGLL5r9YRSIEKYYoCtEtWww/kwMVuoMiLW+Nq2ta12IZsMVWBM1WX0hGuJLHGLbcaYaqUssEt8mCROT0C4odi2zY7LYDvxHBrK4upt9mZFDOqQIVmkfp79HQsjXwweL0qHTUtwSVgCuaCdvViE3jua0esvMuRD0EZ9FaMRDTMQi1Bs0isMESbJRIEJEnFaK1epTYBzpYgYmHQQqtPobvhWNnrZoLs8usGr+xlsk26b3wJDFDJAQNBRqsMoVWxgJqf4aEyCuMVeTLXWF7krzQzHHI9ZVOWXbAdX47oFtOsBc2/AubEfYbXBIWQj+/ei+g0uJ285MjxzUUzE6xaFUf0Zjc91FD2V9WphHoroadn/jufDKWkiVFJSnv3wrIkStFFcd5u0D54x+OzCZ5ouDijtMT278Nhqzz7lWsV3EcwX2qzmwPDCOxhL1Cv3h3ZtmN5zSngPCiWaJ6MHq0EVb3T1XPdBzhlcXtkO5LixHJJNKvc3tM2LFcicznXtOfBke2v7NiInSMhWCLBd3uRlFPXdNB9ed7oLkoMLTpjadr799uvUp1df6turDx1x6FF0461T6PyzLowMHoTPrfi39lhkpteGVIhKfOLYieMsRZBg1CZ3HLo9XXX5tTTrgTvp3bn/lb+1EecxEKDqygq6+JxLqW+vvlRUUkzTZtxIk665lB6e/ZgyIHT7zJvpyosnUY9efalt21y6dfpU+uGHb+n+ux6h9u0LadZ9M2nBb7/S4IHb1CTkDIZo8jWX0spVK+jOabOpY2Enev+j/9AZ55xMb77wDu04ZLuaNj14F737+oc1bcrOiTx/lLAKi5YtW0LvvPsGPTBrDm3ZupWunnoFXX/T1TTz1ll188gPDGC9+sbLdNq4M+jFp9+gH3/6jiZddznttO3OUmAIhUJ0/oWnU9fOXemlp1+nLVu30PSZN0XOCwqWeN7FNkTb4Dn72OMP0kXnT6BzTj2X/vPB2zT1+sm0y7Y7U79+A6TAdfa546W4dPtNd9GKVcvp5ttqRCK5jUCA1q1fSyefegwdd/SJNOnyq6myooJm3HUrXXLx2fTknOdp+I7D6ZSTTqeJV15Ir7/0HylC3HnXdLrj1tnUMb+9bMvc11+iyddeTn/8uDTSZrz3xD1tWbR06WLac5+dKD09nbYftgNdduFEKQAJVqxYRus3rKM9dxtZs3+WRenkpV132o1++P5rOuGo46mqrExel+ni9NQ+5zJC4lb00ndff0EjdtjV7kInKxiSIYjB9cVKHzlgtTBPkIQkRuVwGCY2WAQxYFVX14zg4IsFPQy0pHseMLrQ6DMJGti5TATGShI4Uq/NgwKHSZCIXl/iypMlsmymY+UFQ5vdVmtQjxuExqDxpINeEdhBNrnRi8tr3foGiU1Ykla2DDrlfrg+lVLKmpGrGCwgiinXveatoeRFMY06w/1gNIoE2PkHEQevR/kdBR+90kgtgRUrjZvBagmKZxC02acbkwiW8gUPIMxtEJWbQQljwhgemEk/tYZpFhrd6P2ildrG7Xgyoc1bIsc2qBmTBN9RNFVyLmDCUK1ELiYT9dWOMsrtoxDlZGQp+6aJAOFrV/8dBQFFRMDyy+r5QBFYMXpR1HNos5uSv4pgqt/veB8nUEwmitz3jUmqJY1Vrsk42+b2fewzvE8VEUgvtQ1t82Apenje6GIL4gERBa9BpUqTVlHG1B/whK+7iowasUV6gQSV5/1jTz9Cjz3zKNXHkMHD6IG7H8Gt0jkXn0ELf/u13mWFoX3a2H+rP+JjxSQE1RrsL7/6PB1x8BHyHt9r15FUVraV5n/+PxoxfKQyn/w3EKCy8jKaefetMpRBGKg1AkDtvV93n0eOQbrPT22zc6TxWlgA5dFDITr28GPrvvbo1oOunnAdjRn/f7R1y2bKbpNd1/aLzr6YRg7fUz67hGDw2puv0Ixb7qI9dt5dTp923XTa6+A9ao59IEjLViylef95kz6Z9xl16lRTFev0k8+gTz//WBrsl50/oaZNRFSYVxB53oXPtZZUtLKqkqZPvZ06i3V5vXTNxKl09kX/pkmXXkWFHTpGxInwsbIsGjRgEF1wVo3XRe/uPenp5x+n+V99RiN335M++/xjWr5iKT31yHM1yxPRpedPoNPOFR4coehzpnha1QoutYd57z33o5OOGyeXOfPUc+jxZ+bQ199+Sf36DqA3571GoVCQbplyG2VlZdGAfgNozZpVNPWWa+ra/NwLT9PQwUPlMQlzy5TptM8hI2jx4n+oT+++dMkFl9P8Lz+la6+/kv7+50868tD/o4P2G1W3v22zsuV8Sh9GCQv30HbDtqfpN91Bvbv3oqKiDXT/nHvphFOPprdeeJfy2+XT+nVr5KzthbAC+9+hoAOtWr1Crm+HodtRVmYW3T5rumyv8B6ZMWu6FJXWb4A+XxSWfM+kWnn5xskJ4ol7HQwTCyyCmJCjBCFl5ChQUmLu7Na6bacaSviJAy39QdsYOHZcMdFfLKX7XBhGKHroBIpUD4E6wEtIBz1RlBwtmWqVJGXUFcUBk9ihJ0fEaxI68p7syD0VNS6AwoeIU7MxJHx5IaMHE1ZLCKHYFCf+Lp2NYVh4nDxonDtVTsAOGR5nU4lABywQa3CLfmyLOB7C6y0MPNdw5N1tJQtl+yAGB9FLSU4EzxrYTykaZEOOkVqjD73WaibYd1yFeB35osds2OfpUTrvHnMon5rDqLrecqQ6roVmpnmjeDToAgnZXqtKGVtdAMbnClzDirii90dwkAaWsWrbZpWl1xqUYppHuR+2bNlMa2uNOye6dOqsPvO8XtpYXORq2S2bSqONZsy34jCyu2jJIvplwc90z233ye8i18a/DjqUXnnz5YgIUssJpx8nR9zLK8ql4S6Eh0H9Iwkr69uWHQv/WECzH5pFv//5G5VsKq3z3Fm9eiX17yvKzNesb9tttq1ZIBSiFcuXUnWgmrYbsl3d9oSg0adXn7r1Lvh9gTSQDz7mIGV7IpFmu9x29m1GoVbzqOvSqSt1LuxUc5xDIendIgzvxf/8RYXtCmqfoeFroFYE6TdI8QwpbF8ojX9xnhcv+ps6d+xSI8DUCszbDR4aaYdeZQVzoGhi06ABg+vaK4SmDmI7xUWyLf8s+osGDdiGskS/o3Ye0faa7QjBLkQLFv5MX33zJe04snb7gPCA6dOzD6X70qQnyRHHH0xdO3ejqy67umb52nUetM+B8mOsDhMI0j677x3Zh34DaYdtd6CD/m9/eu2tV+i0k0+vm9WjCT0110TNu6Qgvz3dfetsmnrrdfTU80/I6/HQUYdJEUf83doRSVGDnBiVSRIsghgQIy4ej3kEWx9p8WZk2oajJBvubCdnZNStl0kiMYXguF1G8V7BcC8tf40yCg+dbaVkYwI9hiQgQMYC7icKm4qHid4hcSPwoFeEbqijK/5WOB84gqt5VUi3aDuxCEWczVuM5xk9OaI8PtwQ57MrKnzOLtRL83pSwjm0/akTkvR8EOVlttegIk5onj3GUqN4nOBv3Rg1PUudhA83yzPNBzfPdafzrFwrKHwYBLaabdbvddTQez1UVQlGmyoC5GTnUCclZ4I9+cKQVlYakqPjbpYV24jCpRjx8hsvUSAYoL0PjQgeQjwQYkjpplLKy414o915y93Uv29/apuTK9sWL8Kj5N8XnEojh+9Ft98wk/LzC2j1mlV0+oWnUTW+L8RjPqv2fWBZdUJJVL4Y9CwKWdJT5ZUnXyOfJlS3ydKqMUVW4LrtHlOeN8CvC3AeT03bxb/hZd2UPxaExYWw1w2IXn4hxonp4fAsuZ2gFClqjhWEKemEQlLM2W+v/WnChVdETZZeKrXb/uGHr+W/pZtKqLRkI7XJrCfc0ykcUp6HNjSw3yBasnypbGJhQU2ukA0b1lHH9pF3XNHGIurQPpJHZM/d96IPXvuIikuKye/zU27bXBo5enfqPqqHc3sYhmlUWARJFNpLi2FS1evHtIwXcnIo6Ilq0UsEDH8/xLsH1kYykfrbgzux6LCDoGEM49LAMAv0wMGQJEfjwyQKgfGAI/q6cR4q2mi7HX+nGrfgmi9a9SXMBYMiCnauNDd2Y64KMHgwnMeDgopct5WSngdKqFd9wgn0U+tyOug5JAzChzIK79BZxxAaNCZNuZUYpjFx+xyMdxk3nHbS6fITCw/c8RA1JoFAgF6f9ypNumSyFCKQC688n95893U6+bhT6n7r0qkL9ezeK6ZtpaWlUVAzhIUXysaSjTThggnUpXNNctJfF/5S77pEDglRJvbnhT/XLSc8bpYuX0q77lSTuHObQUNkFZnijUW0y467um6TidVrV9Ha9Wupk/AGEYLALz9Iz4PePSPeJ66xLJl/RQg+GzasrzPwf3Gx787rjfZk6d+nP73xzmtUUVFBmbVeqD/++qOymPCi+M+H/6FuXbpHqu5oiPCiW+68hW686mZ654O3aeLUK+iJ+55y9r6oR1Sqqqqkf5b8TTvvsIv83r1bD+kt8/lXn9OQQUPrktt+8/3XNOHCiVHLF9QKh/O/mS+Fkv33OoBaO5wThEkmLIK00HhpO/SR0UTnJWGo3qSrbl3nYyIW7wt0lYaQBRQXlPwJAlNoBxj6ijigXXdeQ+JdJfmp5t6t5GrAagf5ETdhkUQsnms76ny4OT/YadKEUEX4wISIkJ9Df24oITRYfQiOmeJerydoxgSu0LYQhqNo10ljGVOx8n87+6kyGKAMn4/+/LBGiPBoIo45B5J9uEAUcK4sqJaTaseCYZgIH3/2EZVuLqVjjzyO2tZW2ghz8AEH08uvv6SIIPEgDGyZa+TrL2jQwMEyr0PXzl2kEPHUi0/RiUefSH/+8yfdN+deV54vRx36f3Tb3dOlp4rIITH7obvJ4/XUvc5EaMzhBx8hjfVJF0+WoogQXL78dr4M4dln5L62bRIfOzLSM2jS1IkyOavISXLTjBvpkAP/RYUdVK88t4j8JkLMuXLqFXTFRVfS1rKtdOf9M2smNjQlgye8THTS3MMOPlyu9+qbJtO5/z6PVq5eSY8+jblniMaOOZlefO0FuuyaS+iMcWdSfl4+LRU5Vd6bRzddfbOcZ+J1E2jP4XvSMUccS3uP2IcOP/Ff9Ogzc+T8gvc/eo9m3juD3n35PaMIMv2uadLjRAhXQpwSOUHEsfy/w46uabHHQ6eceCo9+Nj91LtHb+rVozc9+Pj9lJmZRYeNPrxuPa+88TL169NPVq754ecf6JY7bqJTTzyN+oqcJK0cEQ4jPvGtgxOjMrHBIkgK4tpQhlFPJUkaJvozqORRq3LIbt9QEm3oeyExXCqJTdguJQZbN05RBIFKHB7dcwNGKFAcwFArHPVOtMHmNoTH2yni5mlpeRPCeFA40SssoPdIO6hMgsdQ93DA5K5Y+QYrPHSJuGF7irXwGbgnTCEbsYBVLUirgoN5MHzgZeO4fRBv0CVaCRkxlD+OypcCIowPQ3W0GGilgga62EMSRqWqEnjlyO2A90oslZ10ph6VRoUFAVpfnEZjP2ycaz2VniMMw7jj5ddfpBG7jYwSQASj9h9NDzx2Py34/VfK03NoxMBO2+9EJxwzli656mJZYvaCMy+kC8+6mG6dchvdcd9MeuqFJ2jooKFSZDj38rPrXZ9ISDpl2nV0zqVnSVHkjFPOpNVr10ixIsy0KdOloX3r3dNo3bq11C6vHe2w7Y5SAHFqkx3CA0YkAj3zkjNkOMg+I/alKVdeH/PxEKE69864n6656So6dvz/UY9uPWniRVfSOZedpeyDs+hRSzgKy0Y8EcllhUeROFZHnXyE9AyZcMFE6ekTRni3PPfIizRj9m0yFEnkTenapRvttcde0tPj3kfuoRWrV9L9tZ5JQvi56Zpb6JLJF9HI3UZKgWnzls20eOkix2avWbeGLrvmUiop2ShDn3YYtgO9+OjL1K1Lt7p5zjzlLKqsrKDrp0+RAt32Q7enR2c/roR8ie3cce8MGa7VrWs3Oue0c+lUPTEwwzBNjsfCoESGNm3aJOuW759xHPk96eqIIZYadQoRAMMEk1cm25hXRtqTlbciRQWNePEXqnXklVwZbqvwYPlduIbwOHlN5RYF4DkQXBEpMevD8om6KIYJRzHJGs6H1Tt0Yz83x3Z5q6jYPu+GTCK82TY0xmnfPFgJB3JiYDsDUFYXhaOostGwLkUk1MOBcDvogoylfKE6DGG5YAew3K6OUnkHHW6wtDEmVFynlWaGY60kJm2qe91Q9cTXTjVK8LzrPDtrHhUWlNP6jW1o3FXH1/youTDHK2QlUvSNl1QKW2JaB4W9Cuis+0+iTh06k48cyjIziccTyS+y9yEj6cpLJtOYI49L6CaEl8kHH39Arz/7JjUm3/30HY0943h6/9X/Us8evc0zspnRIIIUpLUb1tBD5z5D65dG+lLhErkf0+tUWlpKubkwiNRMba2nftiW2rSN7xlUtjlI43b8pdkfE6bpYU8QE6K8l8djNNQdO6vF9t4PSilJB0FCyaGAI+U6aMDiKDpWTsgEIw2yfsvtBNrbu8jjfHquE1OcPYwmK2KRXsITDGov/I3lRD2btVAGHLmGHAqhTeBhgd4BDscptCaSq8KLwoW+n4bqEyg0oGFmZZhvJW+/7radAa9mNHsq4RzCvvny4RiC94jufRJcurzub3+3rpH5wIsi6JCbQal0opQa1cIn2kNOitIt9qVj+0RGSjxbVY8XzGPh6xHZpqcM5tMztoNwYHWInGtPRbXtPoc0jwQ0NE1VdbwoejiE1Pgx70ZagdETRBGSMLwHPWP0PCTwXAnlwPGE+9hbCs+kIf3UbW4Br47CiNjjWw2JSLUkr5i/JV6hwIv3Guynk+hhxLKMCR/deJs5CWHoqYXVN0xlTxsTFj6Y5BBOcqlWh2lx6B4ITU3tc3Th7wto0ZJ/aLtthkkvBOGtIDhAVChJBE65LkzTXOYXCSNCSNq0aSPDPpYtX0o3z7yRdtp+55q8K/o28PmJ70JM/u3T+k2mcrVMiyWYgOowQQ6HYWKERRAD3uxs8nrTlWSRoc4QBpBhVi6DWREjozo3cogteBkH2qg3va8S4vf9kRmDGR7b5eV3aILH8C6znHJAwfo8lv269PV6wHD34rusKvK7rzzy8vJVqivwgAFpYR15INTJJnN8LcFMCBnJgDK0Tlcylqv3dK93+zXT7JfH7YR8MMFrPra4jNOxxWNIVqHtuVGe9VrzfWALBrRokrpmatqCB/oZaWUh+7ZpHWScFvJHBBFvAMQB3BWvVjUFrzUUgry5Db5ulfwgsH0KRkQYgQ+FHDwH4L3i3aIZ05mR+9hbjslYg7YijNVW3U/FewPbD+KGnvsEO35eFMW2gnHeJmLAe4tUkcDKAuO+OBLOYnUHgQsEkSjPGBRIUAxFkVErd4seJ1hWF72jEhEmowCdai94nyhCh+6th9NwP1GIAjHXqwnVeG7ceta48vIweM8wTKzhpe48Lu2rw7ipktGkYFv0QRj8bnqdK+WwtX01lMdWltG3idPQS1Jft/6M93rp0acepsVLFsm8IkO3GUbPPP4KFYhSw3K9hvbr7TQdD6UOur9mIC884KD0IQwDXvp+auWPBVvLy+j22dNp9drVstrOiF1rPFnqFS2MZWi13/GZjetT3ktY/llbn+kcNhfBjGGYJoVFEAPVA7qS5c8kXxmMzH6/wHaUVM/14AOXdG/XAtsHdKCNeui9ARjpBuMaDXVdBPFWo9EJf8O60Mj0bVarHaABp7w8MEeAVvbNNGqMBk9wIyS7bK+VpYOXWQhG5DH8Qc8zgR0/kWE9HtdxUylj/XwqISQYJgKeOaFce68QQSAb8iS0hX2GzeB51lHEAcOLXRFHNHHCX2bfOVKEAmloRxZKLwVDHzxB9Gs1lAbXJAhR1SDYBbLwGlbbGciMTAulGcQiy0GwU0QY3Bkyiyh4CE3zebSSqsrpaVNvR0lvs9rx1KY1cD8VkRL7rQH1/sJp3lDknvQpzjjqMr6KyMrTtlq258ZJvDMJhhnFkQ6uv6y7us2tUB4URaVAiEbcVElrS4k65VVQ//BzRbu/MIlv0GDkRXmRgNjggedSYNGSSDu7d7N/Dor5YgjBcfWMYuGj1RBT6BOOorsUQVD4wHezVTuQ4+2cU2Nwiveu10+W3/zAVJ6X0Xks6wefXfiz0/Iun5fKNBQhrPp/j/4hBhFE6Z8ZBInav7fZcQd65bX31PlUTd6M4bibBrLOmzBRfoJ2yyjhT5HrMfp0ROf5OHzcSXTYKSdF/R5o4Lkyge8vapNu2x/y4Esf+2ayIcH6BS4nsYaFjyYnZHnlJ751NN6J6927Ny1dulT57corr6Rbb7217vuyZcvo/PPPpw8//JCysrJo7NixNGPGDErXPH2Z1INFEANpi9eR35tOIUiwiNVVdFd5a2u5rUGNnX2lckNlmoMboGUbJqJ7G6DxgHg3lduvF5M4ytwMm2w7WjG5rsPy2LkLbihSZvN17mQ/QuUyPwgmgA1ubrgIYip7qbu+G0t6gnDj79YFGqZ2IdKqIx5E/tKIBRrMBbFH63WE0iEkyJBfAsUuXUTxlQVs1+VFLwjdqwOmeSvAMN0MnWg9zAOTvmIFEghTqS6wz1gvqMrz2woqwXTw6tD33yACoKcUGu06ps6iaR79+GJH2guXnQ+ESL0DhWKBIj6ZOujaNtO2gEdVBXghgBdaeUd1p4OYogTFKhTf9MivnMh8VXlKb9l2Xxy9dGDa1s7YAdA6A5a9qCS2s/VJi4ReKxxmVo0bGNUWvT1eRRQiV9cQHg/aF+5jtG+CZi8qf3nI9tx60ZtLO7/pxRAyCEanrxhEX907bcNG2+eyr0d3o1CtiMhoCECokhIShp4ocgWNM/KvhychUV47NkJWVAlrzCEEoXihEkgqreUjwvcRvqe9Pe1DFpWcP/K6gQsH7tVgdrrxuYzfg2kQQgn3pzK/dg2gZ6hpdDvKExTvKexP1K67Tfs2sl3iOgz5fMogjH5NebSwS2N+KfSKUPJLGbxm9d03hdq6Hd3HaSYBWl9e8bBA902DcqP/AC8NUSnEDcp8uE1T+/U2wPLKsxifXfqjT7nFDSq+/ox1ao9JhEAw8TteA7r3I4IhxpiPDwcG4X6wojrFLkwa/TQZrhVlNod3tiscBkjU41z7dygg85X5evckf3qtYB/ur4eqiMxRzc2O5hAOc8MNN9CZZ9ZUFRLkYPXHYJAOPfRQKiwspM8++4yKiopo/PjxJNJtzp49u1HbxcQPiyAGAmvWCp9p9WB1hBCFqA4ZGH34N47co2ihG6NV4O6OeTPAMNVzelhFkY6shfH3kDcj0XHtJk8KC7aptFHbPo7gGnHolOP6sFNsYZhNDB4iOELnuA5oS2DFSuP6vOuzbPMPpGGpV71kcV4kGaqVWf+tiZ0EgW9L5Bx4YBRF6VRrHTU0xtCDSOncaDkkQiAQeTtE8spYC/6q+zujW2djRym9IOJNE8yJHJtQOlQ7grKluliD91EgP3I9BjIhhwUaDnonyuAV4mhIhOy9ZzDcC0Nr5Hfs6MCxDYEhFAWcH38JhGZAvhTfytV1f2di1Rex7q6R0sQhDMvLS7cVVARBOG4oKikheiBQRXmCGPr+iseQ7sWGaYcwfK4qROvDm7WICn6rea554fkYdZwgjMm7IWIAByBHjo5SwhmexSh+6ka7B0QEa0DPyN/QqQ9lqfctGqCV7TNtr40qODe6cGP1aGcrZoacjA9cXs91FP7dHynN6NG9w1AYxZAuBwNUEeuVCXBs4Xp0BK8VzL8DIq++bgufXV3gmVSlLdOrk63WE8KcQ1FeEYZwUMjNY/38p6v3Dx4lf9cu7sIqsiE3EBiJnpLIIEaoM3guivnS/bbPHm9tfqbsLtVyX8Q0byhI5CCCKDgZ+opw4Kk/5MJRMzC9sxxEDMsQZqHko3DoD4VciDA1M8I2Dcug55qT8GISBKBEfbSQBM9ivL8d7k9lPgfhw9hOVyFRTqFKsH0U1fRji9d30GvffmURfXkUSAytjDofJuUDRTFDCFHUyt3G0xg8U+raFiQrEKDgkmUUsEmM2pIQRzbo6Bbmbh2NSdu2balzZ+jTAu+99x4tXLiQli9fTl271uSlmzlzJp166ql08803c6LWFIdFkFjLYerggx0rxRjcKrEDU3Mm4FSAlwka93rIRkweG3Fi9KTQXMeNuHFbcxiJtBpJ4El0ckLFU8iUYBMT4Ir3NyaxxSSh2NkHQ8zj8DL24stY6Shqxx8NuAxwjfXnGJfxYuUWGHX2QUiYkwHqWb0mskxb8JjBvBOY9FeA1xd4XaWFIsKkH4yXEOTzcAxFw8OkjeCioYojpTifOuqrhWzgunA+xatFSzqLofgwuox4C+G60b10fvu77k8fiGx+TFoLCVPlNDBgg2jEY76VIvAyAtGkZh8whAY8HCrsPZP0ZfAYoAAsSCupjM6PohndYcNOAvcEeu7J71hOGD0E4Bj60SMAyg3LVS+JuMT6l62NTID7waePeoOA6P8bwnPwHsLt4DNAe6+EoOIThl+GNGEZPezS+kLFBkMpZD3sxzQiju+bWJ696b16GLeJ74+oqlembeKxgWesUp5cG6zwgccJvs9xEAHDWaOMVPRYwZHuGLxnLEzEjM918HCR4HN+Y5GtYeld7xCqZSdoZNca2uK+Eqqm27wfimGru86h0Wx4z5vyPNSswH55NICdxD/TPjTYmG/kJKVKeyx3basy5S7B96RTrJCn4flS3JwPpS0uhSDT307HAK8VU5iLAJ6/isenQ/439Rjg74Z+kym/id4ep74u9veV/alb2Lws0+RMnz6dbrzxRurRoweNGTOGrrjiirpQl/nz59OwYcPqBBDB6NGjqbKykr777jvab7/9+IylMCyCNICYyjImOiFgimKqpKETb2nLZJezTCQBvUpJkRo61FCw4lBSyh+j0Y0j7Tpo5JhGwnTDDDsX4E2DFWUUOULLf4MdDT+KmRBeZa1db3TFb6xj68tTqyehQYshAopbP+SlsdDrrDahcx3ouYCikHYPeTdBCWacgEIUdCJ9JVpHFUfR8dxAKKFPM2zRiy3qeOZFXEGsb3+pmUedQ908xQCId/jswlK+TiJzAO5Vp9LOSpgkTHOq0uQGvfqRsZ2Q7yTZOAmjCoaKQK7BCmIxlGF3epc5hcQ2FFPlIwy5bCyCmYGaZ2r4oxvtJmMUDTuTt4hb3C4f7zs/GX0GJ0EDDWAng9qEySB3EqhMA3ixiEIxNFnZZyXJacCdcILtjCUBK+KU4yVe3K7L1M5WqH2EyCs/8a4jXHYXycjIkJ94uPjii2mnnXai/Px8+vrrr2ny5Mm0ePFieuSRR+T0NWvWUKdOEQ9DgZhXiCRiGpPasAjCMMkiwbH3SkhWEkQQNArcGghYmcTJHVgvB2wbHgVGpnIs5IzQu8CXIuTF0Zfxg0ASglFb9F5RhBJtXzBBsHKuYQTXSRRE7yTFmIPkxLq3Ax4PD3g+4Eh7CEewtTw7KLZYG0Fgwk6s7u2A00DcUCpZaOWHsTpLLNUvYsHNNRmLd53r3EYGLzomsTSmUB6v8JFSCMNShMI0hJZcSrepiEX4MOHkVdEc97kpBKtUPk6tkKDllZ941yEQnhrIlClTaOrUqVHzi9+uv/56x3V+8803tMsuu9Cll15a99t2220nBY5jjz1Weoe0r/XmtssHJHKCuM0TxCQPFkEYpoWACQGbC0qCxnjXtaU6qSKQ7k6M4WuYswB/96RpoxTw0nQziu1olBU3vJJELCPnJppK3GAYhmEYpnUj8nLk5kY8ZU1eIBdccAGdcMIJ9VaFsWP33XeX//79999SBBG5Qr766itlno0bN1J1dXWUhwiTerAIwjDNFHTDT7QB2yzBEqhaDDB6TGD4Bf6uH08cUQ6Bxwfm6UEPD7deBOjhkehcNPGiCDcxjMqx8MEwDMMwjBtC5JGfeAgvLwQQFEFMdOjQQX5i4YcffpD/dulSk9h6jz32kAlQV69eXfebSJYqBJidd945pm0wTUd8PkgMwyQNIXrgp9UKH+GPECRqP8KAVz7VgbqPqAQU/uheFfiReTBqP96cnLqPLz+v7hN3830+5ZNs8JjFgvD4CH9iIRWOAcMwqc36DevpxtuvpwOO3I+GjdiG9jl0Tzrn0jNp/tdf1M2z/xH70KBd+8vPdnsOpYOPHUWPPPWwdFMPs2LVCjn9tz8WKt+H7D6I1q5T4/nXbVgnfxfTxXw6/75gPG0zfCD9+EuNkVRHbd6VhX8spIsmXUgjRg+nbUcOodHHHEjX3HQVLV662LifYh8ef/YxSiVSsU1M8w+HiffTGIikp3feeSf9+OOPMg/Iiy++SGeffTYdccQR1LNnTYW4UaNG0ZAhQ2jcuHFSIPnvf/9LEyZMkCV13QgyTHJhTxCGYVIPhzLJrn53qGqklHl2CifB5KwJzt8SWa1DCE0LSgLslprKHmJUh+O2GYaJRggQJ55xPOXmtKUrLppIg/oPpkCgmj778lO6/rap9O7L79XNe9HZl9BxRx1PlVWVNP/rz2nqrVMoJzuHTjj6RMdD27FDR3pt3qt09mnn1v322ltzqVNhJ1q1JlKlKYz47YdffqSTxoyjl19/iXbYdkdl+keffkgXTjyf9tx9L5pxwx3Uo3tPKt5YRO9+8A7d/cCddNe0WY16qquqqyg9zb7aWFNRHaimNG3ggWFSGeHN8cILL8j8IaLaS69evaS4MXHixLp5fD4fzZs3j8477zwaOXIkZWVl0dixY2nGjBlJbTvjDhZBGIZJCZosQabbBJWNJHw4bcNyoXugB4vuOeF631IU4dF0+1lplJ5RRVWV6fT4Q8luEcMwqcT106dI54qXnphLbbIiIYwD+g2kY44Yo8yb3SabCjvUlFEfc9Tx9Nwrz9LnX35Wrwhy1KFH09y3XlFEkLlvzZW/3zfnnqj55775Mu2353504rFjacypR9NVl19T17by8jKafP1E2mfkPnTv7ffXLdOjWw/aftgOtGmzWtEizLizx9LK1Stp2p03y4/gj2/+po0lG6UXzLc/fkOlpaXUs3tP2c7DRh+uLCuOR1paGr027zUa0Lc/Pf3Qc/TfTz6g6XdPozXr1shtH33YMTTp+on0zYffU27bmlHr73/6nmbeezv9svBnys/Lp4P2G0WXnT9B7o+pTXYIj5mpk26g/33xifTQ+ffJp9P5Z1xI195yNX357Ze0oWg9denUlcYeexKNP/HUuuUmTZ1Im7Zsop2334Uee2aOFE/+ddCh8piGRRThlSO8aL78dj51aF9Il557Gd1530w65YRT6dSxp8l5Nm/ZTLfdfSt98Mn7UgQbts22dNWlV9Pggds4nnumaQmSV37iXUdjIKrCfPnll/XOJ7xC3nrrrUZpA9O4cDgMwzApQbyhGPGG08QbmtJUoS0ij0j4I0QP/LQERg3z0ZjhNf8yDNNEiGoGobIm/zSkWkdJaQl9Ov9/dNKxJysCSJiwIR+9axZ99d2X9M/if8iP1awM7L/3AVS6qZS+/fFb+V38W7qphPbba3/bdc998xU64pAjqV/vftS7Zx965/2366Z/Nv9TKVycMe5M222Z2jz7tvuoc8fO0pvls3fmy4+gqqqShg4eRg/e8TC99fzbdNz/nUATp0ygn379UVn+1Xmvks/np+ceeYGuv+om6UFz8aQL6YB9DqLXnn5TCkF33j9TWeaPv/+g0y86jQ7adxS98ew8uvOWWfTdj9/Sjbdd79gmE7MfupsO2OdAevO5eVKgClkhufxdt8yieS+8S+efcYEUL95+f56y3FfffknLVi6jJx54mm6dchu9+tZcevXNV+qmXznlClq3fi099cAzNHv6PfTiq89TUXGRck7OuuQMWl+0nh66aw7NffJ1GjpoKI0/7xR5DTGpQ8jyJOTDMLHAniAMwyQNpVIKeDjEIoQoy2sJRxXvCUiaiuEo8SYp1XOMtNhwFrehSk7HJsUSwjJMa8djldOAv7dr8u3+1f9nsjzRgoYdy1YslQZu3979XM0/457bZLiJqNQgPAqEe/u448fXu1ya3y9FjVfeeJl22WEX+a/4Ln7X+eLrz6m8olyGugiOOPhIevmNl+iYI46V35csXyL/ddvmMO3y2klXe/RmEXTq2JlOH3dG3fdxx58ihSERWiO8O8L06t6TJl50ZeRYzL6N+vTqQ1dePKm2PX3pz3/+pAceva9unjlPPUyHjz68zpuid8/edPWE66QHiPDqMLXJhPBOOVbzzhECCnrD/PDz9/TuB29Lb48webl5dN0VU+S2hLC0z5770vxv5kvB558l/8hj/vITr9K2Q7aV8990zS006ugD65YXniZ//v0HzX/vK0pPr6kQcuUlk6VXyH/++y4df7RzZRCm6QglwBNErINhYoFFEIZhkgYKBTX5IBoHtVxttTEnRzy0mjKwMYQJtVhBiGGYxICDuYbHcjipqQdKiTtx+rgz6ejDjqbijcV05/130O677EE7bb+Tq2WPPeI4Ov70MXTZeZfTu/99h16Y8xIFg4Go+UQOEGHAhz1MhOF/+6zptGjJIik0YCLWRBAMBumhJx6U3hPCG6Kqqkp+RC4CRIR/IIuXLaZhQ1SRazvt+4LffqWlK5bSm+++UfebaH8oFKIVq5ZTvz79G9RWvQ0CEZL00usv0qrVK2WeBSFQ6SEq/fsOkAJImML2HenPf/6o2Y+li8jv89PQwUPrpvfq0VsKJ3X78fuvVFZeRsMP3FVZb0VlhfQwYRiGEbAIwjBMShBvhRsn74KmCBXRQ2CsQBPkFGmBwslPy0KUXUS0dSsfP4ZpKixPlvTKSMZ2a/6of15h7AoB5J/Ff9OB+x5U7/wip4VYRnxmT7+XRh19AO0wbAcaMXxkvcsO7D+Q+vbqS5ddc4n0RhDfw1VkwojQCuFdEAgEpHGPQsUrb75MV1w4kfr07CN/W7TkH9pxO3cCjBOPPjNHVme56rKraVD/QVL8uOWOm6WYgGRp4UJCzNC1I0s76CHLkmEywrtEp0vnrg1uqx6yJIQbkUvkyosn047b7Sg9SuY89Qj99OtPynx6yJI451Yo5Eogk/sRCklPFREuo9PWEH7EJIeQ5ZWfeNfBMLHAIgjDMIwNDa3U4klTH6cc8hEbpzxcSatLiLq0q6TIWB/DMI2KMDRdhqUkCxGOIcJOnnn5aRp3wvgoI1skGTXl2BCeAicfN46m330rvfbMG668SURIi0jEKkJB7BAeEyLHxb23P6D8Pv+bL+ihxx+QCTtH7r4n5bfLl+V5MTGqmzaLxKahkPru+e6Hb+iAfQ6gI/91VJ3Bv2TZEurXxzncRgg6n3zxifLbrwt/Vb4PGTSU/vrnLykambBrk1tEfpEdt92JThpzct1vy1Y0zDOjT+++FAgGZMnhYdsMk78tXb5ESTArvEQ2FG2QOVG6d+0eU1uZpiFIHvmJdx0MEwssnzEMw6RKolaGYRjGyJQrr6dQMERjxh9N//nwXSkACM+QJ59/go7/t5p/QkcY34uXLZLLuUGU153//tc05sjjbKeLUJjR+x8svUTwI8QTUeHk488/kkKNyFnxyWcf0zmXnUVffPW5TFL6y8Jf6LZZ02nKtGuN2+/WpRt988M3tHbdGiouKZa/9ezRS65DVHER+33dLdfISiv1cfzRJ9LiJYvo9tm30eKli6VXxqtv1SQbDQtCZ44/i3785Qcp/AivF3FsRUUZUY3GqU1u6dm9F/362y8yh4low1333ymr0DQE4ZUzYreRdN0tV9PPC36ihX8soGtvuYYyMzLr9kNMF2WKz59wrtyWON7ieImQKHHcGYZhBCyCMAzTpHizsuo+LYlQebnyYRiGYRKLSKY59+nXafguu9P0u6bRYSccQqddMF56X0ydFDHW7SjIb09HHnIU3fPQLOlBUR8iLKOgXYFtRZlff/uVfv/rNxq1/8FR03Kyc2jk8D2lSCI4cJ+D6Lk5L8oSr5dfeykdMmYUXX7NJbRly2a65NxLjdsXSURFSdoD/29/2uOg3eRv551+AQ0ZPFRWcRl3zkmyRKyb0CBx3O6+dTa9/9F/6Iixh8rwnXP+fZ6clp5WU55+8IDB9NSDz0rPirFnnUj/d/IRdPeDdylJUO3a5JYTjzmRRu03mi696mI67rRjqKR0oyyR21CmX387tS/oQCeddSJdcMV5UqzKzs6WiW8FQgx56K5HaNeddqWrbpxMBx9zEF129cW0ctUK6lDQvsHbYxo/HCbeD8PEgsdKdNamZs6mTZsoLy+P9qUjye9RKxowTHMBBQY2yJnmxIK8l2vDYYiGltZUWGAYJnEU9iqgs+4/iTp16Ew+4lLUrZX7H72Pnn/lWfpk3mfUnFmzdjXtc9he9Pi9T9Ieu42g5k6QgrR2wxp66NxnaP1S1dsmYFXTx/Q6lZaWUm5ubrO3ta776kDKzInP1qrYUk03DP+g2R8TpunhnCAM0wJh4SO1cCrf29zwpteMGra6qjgMwzDNmGdeepq2HbId5ee1o+9+/k6WxD3puHHJblaDEeVyy8q20sD+g2j9hvV0++zp1K1rd9plJ7UaDMMwjBMsgjAMwzRhdZTmLoiw6MEwDNP8EGEuwvujdFMJde3clU476XQ6+9RzqLkRCFTTnffNpOUrl8swGFF1Z8aNd8hwI6Z5wdVhmGTSokWQadOm0VVXXUUXX3wx3XXXXcluTrPEm5HZ5KVGGaaloSZX5USrDMMwTNNy1WXXyE9zZ6899pYfpvkTtLzyE+86GCYWWqwI8s0339BDDz1E2223HbUYPF7j6HJjwaJHyy3pyjAMwzAMwzDJwCIPheIscSvWwTCx0CLlsy1bttBJJ51EDz/8MOXn51OLQYge+GEYvDy4pCvDMAzDMAzDMEzrE0HOP/98OvTQQ+nAAw9MdlMYhmEYhmEYhmEYm3CYeD8MEwstLhzm+eefp++//16Gw7ihsrJSfrBsE8MwDJMcPr86k9q3q6Cikkw6ayKfBYZhGIZpiYQsj/zEuw6GiYUWJZ8tX75cJkF9+umnKTNTTejplDxV1KoOf3r06NHo7WQYhmHsycn0UG6bmn9bFCKnU/jDMC0Nvz/ySSQej/nTHEiFNid9+/BhGIZJEVpUb+y7776jdevW0c4770x+v19+PvnkE5o1a5b8O2iTLHLy5MlUWlpa9xFCCsMwDMMkFM7nxLRkAoHIJ5FYlvnTHEiFNid9+/BhGCBI3oR8GIZaezjMAQccQL/88ovy22mnnUaDBw+mK6+8knxQPSNMRkaG/DAMwzAMwzAMwzCND4fDMMmkRclnbdu2pWHDhimf7Oxsat++vfybYRiGSe3QkPs/rKapr9T8G8ablaV8GIahVn1/fP/T97TN8IF0+oWnRU1bsWoFDdq1f91n1/13opPOOpG+/u6runkmTZ1I5004x7j+uW++QrvstyOlEqnYJiZOvN7Ix2m29PS6D8MwiaFFeYIwTGsGO7+hikiyXy6n3PzxZkRyHIUqK6jZ41Di+4GPArS6hKhLuwANrf0tVF7eZE1jmOZGSt8fmIcigeEYr7z5Ep183Cn08usv0qo1q6hr565R8zx+75PUv+8AKtpYRHfeN5POuuQMevP5t6lHt6bL/WZZlgzFFiHZyaI6UE1p/rSkbZ9xIBRyN1tVVc2/VmRwoCUQIq/8xLsOhomFFn/lfPzxx3TXXXcluxkM0yQd4fCH8w+0LITwEf4wDNM0eHw+44dJXj6KsvIyeueDt+nEY8bSvnvuJz0k7GiX144KOxTS4AGD6YbJN1J5RTl9/tVn9a7/q+++pMk3XEmbt2yu8yaZ/dDdctrrb79GR59yFO24z/Y0cvTudPk1l1JRcZGyrJj/0/n/k/NtO2IIffvTd7SlvIwuv/Yy2mGvbWnPg/egx599lMadPZZunnlT3bJV1VV026zptNe/Rsr5xpx6jFxffW3SEb8fOfZwevmNl+iAI/eTbRBizP+++IROPON46U0y/MBd6OxLz6RlK5ZGedC89+F/aNw5J9H2ew6jI8YeRj/8/L2y/hdffZ72OXRPOf38K86lx56ZE+Wh8uH//ktHjzuSth05RLbhnodnUSDR+WKYZk/Q8iTkwzCxwJ4gDMMwDMMwGpZNMvWWjhAYTPi8PiWHmtO8Xo9XqdJnN2+brDYxtfHt9+dRn559qW/vvnTEIUfSjTNuoPPPuIA8DtVPMjNrPCUDgfpH0nfcbie66rJraNaDd9G7L79f09Y2beq8Ki4++1Lq26uP9DCZdufNNOn6ifTw3XOUddw++za68uJJ0uukbU4u3TrzJvrhp+/o/pkPUvuCDnLdC/5YQIMHDqlbZvL1k2jl6hV05813UcfCjvT+R+/TGRf9m9587m3HNtkhxI133n+bZt92D3m9NaKdEIFOG/tvGth/EJWXl9HdD95F519xHr3+zJvkhXCMO++/Q7a9V4/edOf9M6XQ897c/0pvlu9++o6m3HodTbhgIu2/9wH0xdefyzYhQgC64rrL6ZoJ19EuO+xCy1Yuo2tvuUZOu+DMi+o9/kzrgXOCMMmERRCGYRiGYRiGdtx7O+NR2GfkvvTQXY/UfR8xarg0rO3Ybafd6KkHn637vv8R+9DGko3KPH9883dMR/zl11+S4odgrz32prKyrTT/6y9oxPCRtvMLAWbmvTNkcvxddxpe7/rT09KpbU5bKaoITxLk2CPG1P3do3tPuvry62jMqUfT1rKtlN0mu27aRWdfTCOH7yn/3rJ1C70271WacdMdtMduI+Rv06ZMp70Oqfk7LFrMe+9N+mTeZ9SpsJP87fRxZ0hBYe6bL9Nl508wtsmO6upquv2GGVSQ377ut9H7H6zMc8u102iPUcPp70V/08D+A+t+//fJp0sPG7kfZ11Mhx5/CC1dsZT69e5HT7/wJO09Yh/ZNkGfXn2kp8jHn31Ut/wDj91PZ40/m/7vsKPrjtPFZ18ihSEWQRiGSRVYBGFSDz1ZokP+AKYVXhN8PTAMw7RKFi1ZRL8s+Jnuue0++V14J/zroEPplTdfjhJBTjj9OOnhIISawg4dadp102lQ/0FxbX/hHwto9kOz6Pc/f6OSTaVk1eZ0WL1mlcw/Embbbbat+3vFyuXSg2S7odvX/SYEDSEghFnw+wIZsnLwMQcp26uqqpJhPQ2la5euigASFlrufuAu+vGXH2ljaTFZoZoQpdVrVykiyKD+g+v+FsdNUFxcJEWQxUsX0YH7jlLWK/YLRZAFv/1Kvyz8WYohYYKhIFVWVspzkVXrlcMwluWlkOWNex0MEwssgjCpBxu5DF8TDMMwTc4P//vZMRwG+eK9SLUVu3AY5MM3PklA60jmuQgEA7T3oRHBQ4gHQgwp3VRKebl5db/fecvd1L9vfxmOkt8uP+5tC4+Sf19wKo0cvhfdfsNMys8vkOKHqFAjPC+QLAj1Ee0T6ME64d/l3yFLeqq88uRr5POpx65NVsTDxC1ZmdGhMudcdhZ16dSFbrr6ZhluEwqF6LAT/hXV9jRI4hoOMQrV9stEk/WwI9yP8LwXnnUxjdpPFUsEGemRcCqGCZJHfuIh3uWZ1guLIExKgInmWmMcNsMwDMMkm4bk6WiseU2IxJqvz3uVJl0yWQoRyIVXnk9vvvu6rBgTRhj8Pbv3imlbaWlpFNQqdwgvFBHSM+GCCdSlthrNrwt/qXddIhxEVGf5eeHPdctt2bKZli5fWhees82gIbKKTPHGItplx11dt8ktot3/LP6Hbph8U936v/3x2wavR+Rh+WXBT8pvv/6mHoMhg4ZKjxGRUyTl0PPGJDBhL8MwzQsWQZiUgIUPhmEYhmFMiJCL0s2ldOyRx8lwEuTgAw6WuUJQBImHbl261+UaGTRwsAzh6Nq5ixQinnrxKTrx6BPpz3/+pPvm3FvvunKyc+ioQ/+Pbrt7uvRUaZ/fXlZw8Xg9dTa5CI05/OAjaOLUK2jSxZOlKCKEiy+/nS9DeEQ+Frs2uQ0tEdttl5dPL7z6vMwpsmrNapp5z+0NPi4nH38KnXzWibIizH57HSDb978v/qd4h4gktedcWuN1cvABh8iQpD/++oP++OcPuvTcyyipsOiRUoiILJEcNd51MEwscCBVjHizspQPwzAMwzAM0zi8/PqLNGK3kVECiGDU/qPptz9/owW//5qQbe20/U50wjFj6ZKrLqY9DtqNHnnyIZlj49Ypt9G7/32H/nX8wfTwEw/KKipumHTpVbTDtjtKceC088fTTtvvTP1691fCQ0Sy1KP+dRTdevc0OuTYUXTe5WfTz7/+RJ07dTG2yS1CiBBVZ8TxESEwoqrNxIuubPBx2Xn7nen6STfQY88+SkeOPUwmbj117GnKfohktQ/c+RB9/tXndOz4o+m4046V83er9YJhmDAiH0giPgwTCx5LD+Zr5WzatIny8vJoXzqS/J60ZDeHYRiX+PIiseDB0tK4j5s3I1LeMVRZweehifANnUulFSHKy/RScEFNdQGGYRJHYa8COuv+k6hTh87kIzXPB9M0iPwie/9rJF15yWQac+RxTXfYcdA9Qb3/a266ihYtXUTPPvx8YlbYyglSkNZuWEMPnfsMrV9arEwLWNX0Mb1OpaWllJubS83d1hr/0QmUnpMe17qqtlTRE/s93+yPCdP0cDgMk/Kgp02o3L4cH8MkQvhAWpLw0Zxy7jx1dgYVFpTT+uIMGntRslvDMAwTB96aUeqFvy+gRUv+oe2GbEubt2ymex+5R/5+wD4Hxp7TIpYxzAQIH3OeeoRGDh9JWVlZMhRGlP+dcuXU+FfMtDpC5JGfeNfBMLHAIgiT8rDwkVzQI6KliQOthVQXPhiGYVqyCEJeDz369CO0eMkimVdk6OBh9MzDz1NBuwJqbvy88Cd65KmHaGvZVurRtQddPeFaGnPU8cluVsumrtqSN2EePKlA0PLIT7zrYJhYYBGESXnYEyS54Rv6upqTVwHDMAzDJI3aai5DBg6huU+/Ufc9ZlIggv3uabOT3YRWR7jf5RGligPUYkhETg/OCcLECosgjCNo8OrfQ1VVTXL0PFngidBE4TDNUXhpqvPBwgfDpO4zmu9PhkkhUkC0YJo/VqC65l+r5l+GYeKHRRDGEb1Dbepg+3Jy6v4ObtmS0KMaLN6YsHV5/GlRLxU7movwYTKGPGkZjbYvTZIwtM71sxYx+sG0CsY9WEmlFUR5mZXU3GkKrykWPZoQfC4142eSyIfPOfGb7GA31ZaYFkRruUdlTpB4S+RyThAmRlgESRLeNm2U76GysgavIxlhCc0hFMJpZNSTnmbbiU3VfWkITqJOQrfTFMeqGRsYTHz8vCJEq0uIurQL0dBmfjBbwnOFaXnPpc1FWylQFaQQBbk6DMOkGOK+FPfnpg1bqaVjJSAxqlgHw8QCiyBJIhbRI6YOdgwjV06hIMZtoriQZDzparktC/YhEcc9VcHzRiGr0cSRphJbmKahOQibTekFltiNtgzPAaZlUbm1ir558yfa64QMmZjTy2VyGSZlBJDikmJ5f1aVNU2IM8O0VlgEaenE0PGOJXwikSEr8dIcQ1lSYr/ZYGuVtGThI+niHQsfTIry8WNfyH93PXx7Skv3Ew+mNhJY0lbQCkIcGB3dU8H+GhDhL8IDRAgg4fuzpSNCYeIOh+HqMEyMsAjCpDxe8OxoquSfrZIYDLZ4z43JC8GXl6fMFywtNayAR9qbBD7ODNOiELb4R49+QZ8//y3lde9AXm/EEGmtAwmNgTdTKzFf0QQl5jmnVrNEiCAiBKY1eYBwdRgmmbAIwqQ8FoR2MKlFvKKUyQvBKHpErYBDDJoEPs4M0yLD1YTBtbFITUIc2rwlqQMPSQldayQwaXxjJI5nUhMevGOY1IdFkBR4QCa6o9HSYvybeyeoJRNvKeEmqTTDMAzTTGmKd7j+7E62x6UHvFKsZt7vSUpb2BMk6ST7HmoucDgMk0xYBGmBD8hU6gAwLZt43aZZ+GBaMjwayDQHUi1heCz9o1Tq96Agk5QS9ey5xzSnErlxJiTiErlMrEBAPcM0D6Mi/GGYxrq2+PpiEmXMhT8MwzSy90P442Yep/nibYo/re6TaITwEf4wTEvxBIn305jMmzePhg8fTllZWdShQwc6+uijlenLli2jww8/nLKzs+X0iy66iKr4nd8sYE8QplnBxgTD1xbDNA3sycI0G9x4PzSRhwQLFAzTMnjllVfozDPPpFtuuYX2339/mbz2l19+qZseDAbp0EMPpcLCQvrss8+oqKiIxo8fL+ebPXt2UtvO1A+LIEyLzzvBMEzz4Zz9/BTyBMhr+enzt9NbtfiZ7Jw5qXzck50Dojkm70z2MWMYhmkuOUECgQBdfPHFdPvtt9Ppp59e9/ugQYPq/n7vvfdo4cKFtHz5curatav8bebMmXTqqafSzTffTLm5uY3SNiYxcDgMk/J4sjLrPgzDtGzO3T+Nph5T829rDyVh13czwogPf5KBED7Cn6YUMcKf5njMGKY1CdjhD9M8w2G+//57WrlyJXm9Xtpxxx2pS5cudMghh9CCBQvq5pk/fz4NGzasTgARjB49miorK+m7777jU5/isCcIk/KENjWDknKcjZ1hWhSpUMGLw1HiP4bNDV3gwH2Lez/xPcXJMxmm0e4PDolqejZt2qR8z8jIkJ9YWbRokfx36tSpdMcdd1Dv3r2ll8c+++xDf/75JxUUFNCaNWuoU6dOynL5+fmUnp4upzGpDXuCMClPMkbcGox4YeKHYUw0QWK+RIwaJ6PNqZrUNNHeKG5H5FtNYtUYrq+W6tWA+5XwfeN3FNPKwfdi1LsxGfdHK3y3NpYnSI8ePSgvL6/uM23aNNttClHD4/E4fr799lsKhWqug6uvvpqOOeYY2nnnnemxxx6T01966aW69YnvOiIniN3vTGrBniAMwzBNSRN1sBJqQDVhp3BLhUUZZTX/Mq0EFo4ZhmmKR02qiaat/NlnJaDEbbinIPJyYA4OkxfIBRdcQCeccILjOoXXx+bNm+XfQ4YMUdbZt29fWRFG0LlzZ/rqq6+UZTdu3EjV1dVRHiJM6sEiCJMQ2G2bYVrAvVsdsO2c+fLy6v4OlpY2antG3lxBq0uIurSroKGNuiWGYRiGYVoCQgBxk4hUlLEVn/oQnh9C9Pjjjz9ozz33lL8JcWPJkiXUq1cv+X2PPfaQCVBXr14tc4aEk6WK5cTyTGrDIgiTEFq8uzbDpGBlD6xQITCGjDnEOru5d0NbtrjKWZDScD4EhmGY5k0zeY43x+pRySCVq8MIQeWcc86hKVOmyFAbIXyISjGCMWPGyH9HjRolPUXGjRsnpxUXF9OECRNkWV2uDJP6sAjCpDz8MmGSXSrUDb6cHOV7EISDxsJ158plZxH3AdvvWuhopA6qt00b5XuorKzhK0nhDjPDMAzTcp7jLHw0fxFEIIQNv98vRY7y8nIaPnw4ffjhhzL5qcDn89G8efPovPPOo5EjR1JWVhaNHTuWZsyY0WhtYhIHiyBMysMvEyZVhY+mFj0au5JR3PuAHdREZtqPRfRgmBSuLuPNyqr7O1Re3uTbb5VwFbcWhV5+tjn0E5jmJYKkpaVJQcNJ1OjZsye99dZbjdYGpvFgESRVaCYufqnUiTN5iGD+gqbIYcA0LZx/Jk6a6vmSwO24DvthGJckPYwrxIl/m5xm0rdqCZi8ChMJix4Mw8QDiyCpIlQ0w5czCh8mw1TPH4Bu7cHazMsNwd++fd3fgaIi23lY9GjZcP6ZliWmuoFFD6al0ZgGnCmRcbIHLloyTRa220ye8c3GM5JJKqnuCcK0bFgEaQgp/MJpLqNtsQgfyvoCUL2CaXCVj6bqhLG3RpLgZxTDtHo8fkPXzsPGQmMJGo0pfCQ7dKupaC37yUSwLI/8xEO8yzOtFxZBmGaFp01kJIs4zCU5HhIuDG321kgtmqco5akbuXY9at1MRkkZpjHBwQK898nwu/5MiMmroQXdeynneabkMmm54kC8nsIt6/3HMExjwyJIihO3+2oTdUya6sUSWL2mSbbTokZRXF4DTRHDm2haY+fGyUAxPS888LsPjaIknWt31X6shj/zGvEZ1xqvNaZpDL5EJ/5taEhoQhJMJvLeM72zUjixKb5/E23Mp5wo00jXuulYmd5r+Ls+Tfmdn9cpS4g88hPvOhgmFlgESXHijttNoU4C07gY3UddXgPNRfhoSZ2bWEq/OnWITc+LVMuTk/SEdrox5eJeae7XGpNaWJWVTbIdN14dSb8f3d6HKdyfwfdvIr0YmjTfSCMRr8hnFDc4r02zh3OCMMmERRAm5WnuHQCGMcGlX6N58swMys6upK1bM2i6uSpdfKSwMcW0Ds8cq4mqw/A7k4yJ2ptL3glPeprts6u5tJ9hGCYVYRGEaV5hHi1IBInFC6Ax8bVrV/d3sKSEWixJjl1nUc+Z7Xt6qbCAaH2xwVuDYQSY/BNFkOaSmyKV2+aGFA5NMeHJyFC+W/DObczwpET2gUIsfDAtCE6MyiQTFkGYlDfyWpLwgaRaR6tFCx8xdNbxOk7k9ZiU67m5GIYMtfbz7rZChPH52Uz2s9mTYsfZ17atbTiKk7jh71hY93dg3fqEtcXfq0dkvctWujtuDvdqosNr3GwzcbmdGMYMh8MwyYRFkJZCCnV2Pd5IkqJEOPyaOjHsCtp6SIbruyct8nj0wPZTLb9GczRYmCYiFsMmySPi/FxnEkmo3GycWw7T4iIQNN6DxkGiZDyj49ymJwsS6rIIwsRyCXKJXCaJsAjSUkghI8eDYR4JMFixU6x0INgtNKGkcnWYZMT8Y9I1vaJKqyBJwup7vwYpPYOoqpLj3ZMBCn6UYt5qDGPC6C3h8OxqLA8La9NmY9hQLJ6Abr2jWpv3aHPN8cIwTGrAIgiT8i/GVAsbSdn8HnEarbEIH76C/MjyxRuppdIsvT+aqbB6xQtVtLqEqEu7KhpKzYAU8sJrCYYNwzR3lHAcl2VcnWDjno9LS/YEESEx8a6DYWKBRRDGdcxnysV9ujQ+TLHCicSbl9vkIkhUzgolazw1DVWpmd8Cw2eaa/UIppnQAoQPhmGaxluBYRhSQuatOOPmm6bOFtMSYRGEcSSlRI8YjY9GSyqmbKTp3TB1t1p/YYe6vwPrNzR4fW7FIvT+oGDTG4DezEiGfw9UiFDa3AI6nijk4Eig46hgKnklpFJbGIZhkvC8S0RoqeJNAs9/FvcZhmFih0UQJiEvfR94QqA7dWsZkU9kZvmY2xCD8OHGe0X3ODGFvRiTlya4lKLJnTjZCR1j6dA6uUbHdK/Em+gOzrWvY0RUo+pq43WWyKS1NefQ0/hjOyzQMCkK5zloPNz2RzA/lv6MNorQjSn0hqwW34diWich8sj/4l0Hw8QCiyBMzPhyI54DnnT7cqL8wm4+mDp3useJKQ+I8Vw3kRdAqgkf2JEmD1RMCgSaJrFbDIY+nuvg2nV1f3vBS0gnkeddnsO8JnBuZc8UJkWTUHL+h8bDbX8k5RKDp7JHLsPEAVeHYZIJiyBMQpJF+vLy7C+wTh2V7wEwrFK5PGpzpzG9IqwtW6lVA+KCYjBpYlFwa1mzLn+ohOA0VinJFpY3STdW+NnV/GARgkll78FmX66dYRgmRWARhGlUgkVq6ISvXbsGVyFg4aPhSWsb0ysiXiPBjUCje0jgdzfXgy7KJbKz6IcwEQuEDqva1+DROz3UCIUUJ+O6sUKNTPBIpPl8OB2b5vjschXWxp408WM6nk10TzPJQcnvAWEu+OzX37EYkuPPyW7wNvE9E0uJ3nhx9S5jWiWiMownzuou8VaXYVovLIK0RJLQWTUZmVGj41x+MWGl8xLRmUCDx5OR4SoxKnbQYuncuBFo9E4gfndTlteCHBaJJhZvJhNOHVJXx1O7v9nzgBJamtJ0PtzmdUkl3BpCJuFGubYcrs1Yngm4jJMx2FjhakkJfzC9m1n0aNF9sHifF7Hk/mos4cN1fqsUEj6UMNVGvPdZ+HGHqAwTd3UYLg/DxAiLIC0R7kQ1CxJtPMXSqVcMnhhGrePt3Lg1zHA+FD6wE4YeJrrYZozz10ddDfeREtaVAcn1AhAyUuFwLGDED9/YWN2mZidgRAOnoWcMhKYEiorUxXt0i2zyn8Xm9jiIBXXLV1TCPJmuRCxTQsFkhBg0pjjRXISPWAwh0z3p+l732d9TTuJlMowkJVythQ1cmMqycqhP0+BWMIyJFPLIinp/pWieHcSqjuTkSjhwbpTzzt5dDJOSsAjCNOloKpM4okJGIFEtJTsfRYINM+N80KHSBQF3Kw41ufdHTEAnSq9wgFgbim2NWSWcSOuUu7mn3YZXmcQ3FKhke9LSbJPGCvEqO91DbTMt+W94v71pfuPxUHKXOFxPSlw9HI9EjgQ6hag1F+IdNTZdK8GNKZa/oKmeiy6MVg+In1Yw/jLmSLKNztZIYxrAjSqwNJDmeA026jEznFusnujkEZ3ssKVkwIlRmWTCIkhTkkIKvlvcih4trTxpMmjoaEnUPJVViSuVCm3RK4OYXuCxXANKpx4SrmLlIadwK/Rkcet+6vYaMM2HbcZKL1GAca+0GTw5vJkZxmWsqmr7DhEYTDi6XrO41z6/SDaIEHF2AhNR9tqCZfTRxC+uzaTCgnJaX5xJYy8KJSy3Bnq2cO6UJNBM3nnJ2G+3RmJzNDpbPbFc9w7CSbKFj+bS1zOSBK8Mt2HgrUX4QFgEYZIJiyBNSCop+K5FGacXhqFKRiqTasJHPCJI1DH3J+4c4PZdJ7CNoUNk6tTHksjU8Z5CN1XTNaBd66b53BoiJhSxxuX1iCNEyjIul3d9PA3PBH+XznV/B1avoYYSc2e5tj2+fK36FLg0uz0fbkN6GgvO19I6SWXhnUnRez2FBcNmKXwk+di2BA/BxoITozLJhEWQBhBvXKMHXbqrVIPL36EgrsRXjfYycJonhpdJIt39khJn2ojePMbOkmGbUfscCjV4tAar9SjHsxJGzbWRek86hDKAJ4NVXGIbYqCHQiheCW0hSdlmCEvQY41xm5gFC0f30asi6HBuMGkqbh/XpZUC9rSLuLOGVq+N/A3GuA/3S0s0i+cAf9e9MkzXdJONEBmu6cCaJIUD1bbHlAC3Iblw4u28m55d/o6FdX8H1q03bx+9lrjsd8qS6PcKCx+tEHx/JbhCFFY+M4nbjVkdjWk4zbFKGMO0BlgEaQDxdoicOuiNJXw0lVDg2k03gcZco1YOMMVeJ2OExm3eihiuocaq1qPkoNCMT+V7I133egZ4DwgUVlm5fW4KLaGjUmGmZFPdn978iHCkLKGXLgQhxpsHITRtIiKIrwskXBXtgbYpyVAhNIZyQODKUEvsetfA8QThBj0nSA/hwWkg1FptI9vxrCmyF4706xPXhcdc91JavsrWYPBkZZLHW3NUxb9hD5Tg+iKjV4cHw3McxDeTCIIiBoYjBdZtMOdtgN+DIP65hTvFqUsyQkmSEWLg5L3p6hhwskcjeA79Pbsr0wLLVrg8Q4Zz5eLcJEP00MMkvYawURxECW3aYg77cSEcOJWYR/zt2zc8NCWRz4EU9uxJNlwdhkkmLIK0QBpzlNHNKETcNFXnysmrQ0/EWA9OBlcqZUZ3AiugBIs2Js5jx2VHJZFECY4mATKWpJimyz7iIOJ4feE9FNK2H+/1oVzFkMw1odeg5pWBHjBGoVe7p/2F7e29J0qIpsytpMogUYavsi70RjfYUJhUyjzjfJrYo4yOwjEIlUbW5UFvIr20JTxL/YUdIrOBQOX0TFQSs4KI4+Tlkozwi2Q8r5p9noEYcJvkVDk2kE8o3vdi3OeWDTtXhDQBNxbwnkRBP6b3VyOh9zVDsSQqbyBu+xIxJU0HmksfrvmKIJ6418EwscAiiAFfTjb5POmuKwdgRwVHJi1Dhy4WcUI3BEwP48YcZUyk8GESa6L2M9BIIohDJ66hholTx93tS1Op5gEiDBoypnlqZrRsjSxMQqkbhnjcLagog50L7KxHGYp4DuGYuTXyMFYWl/G00cq24ihTKGhfehbCgfT8KDj6hvktLAjB0UvneTtFDF3aCsYk5qdAzw3tTYwhJMooGXgbOI3GeiGjvBJaU7rJeN0piVLBOFeSglKwwaKpk8HmqtSodq85hY28+l2AVpcQdWkXoKEu7iFTm6OWcfNcdBmr7dbrKt5cLrHQUOFDv79x1NZqohwWsQgfjSb2N1ECc7fvhdYiCrVUEhEOpbynYYCiuaN7bCayUlciwfevqU/PMEzzg0UQA6JShcdT5TrRERpAjRVi0NIUaHSXxFGDFpch22WnGvfbdAzczKMbc2jkhDCsQjPSlA4ItFk3ev0osKBwAh21WKqueDAHhnYPKZ0lEBHQQMD7Qy/tjO6wmNhTES/1Si2YVwSnofCB96SWx8Tfs1u96/J4Iu2SoKDQNtt2nzGnihdHhsUxaBc5Tp4tUNEGRZDacJM6QEzzoviEohCEBvm1sB8Ukjwd2tcfJqMtg9uXolCV2FfxPPWQv2uXmvk1oQVFslgStaInBwoaiTasG/wsS0blAreJZVPMW6OxxH635WrjpTGPYYNzb7m87mIp0dssSaAQhs8auTp4FpuOod6/xBASfE81Wf64OFHevzAoEq/o4eRlaqoWp/cNElkinmk4XB2GSSYsgsRIi8juHOeLXjFMwQB0KwK5dVHE0W3FqyAJJYdNL1Z/t67KfKENxbbzxbJut2CSUzwHysiuU4fYcDz1DpkFhrfivYEeUC5Hv8JGriCwarVxPlOiVR/mc8DqH1oiTwvDUaAjrwgfmLBUgEYWrFsRQdqBV4hulKEokmZw98QEtAIUIdD7xCC4RokD6I0C5z0EooMXQlFq5gNLD0JDlMSwuIxX815Bb5oN9ve03tlVwuo2gneZOE95kX0I1Y56RrUZRBlTiB52vPXnTQj2zWRY4/2UCHHbbQLXhgoPTvsZCyYhqLUYAm4HG9yGhiY0hDQGQd0VLt+f8QofzSasIIH9iViEiqj3Pw5qUOqAgoLuSYnXID5vMXxSFyAaek04XeemPpST6BHvvepWfGw290ETIN728UazcDQMEyssgjQhTg9IkwHrdn2YKFB4sdgas1riqlhG0nAdJsPUaT9jiVc3hgwkISbZ9GINrIREjw447X+8whpeN0piUievDMynYDq3kNRTD2VArxCl6onDNrE9XvAqUEJjsBqMwJAYTvFCwDwPmsHmBXFAOR7QqVcSZMqV279aUQTCtuhhP2icYicQw2ywoo6cD0YJ8d7B8+k1eMXUTPTWG3LiAaHDCeycebBdevgLij14bjSvI8RY1UAKVGFPEKvunvDq1YI0DxjbEUcHMQCvAdMyynl28B5xKh9sel4qMf4YMqM9A/A6NokTTvsZS5uTkbTV9M5IZDWxWNBDhVAEcGskuZlPDwtQJ/oaJRw1Gce2NRp8zSXkIxbc9uGU55qm+6cUGFIbA27vo9Z4HzBMKsIiiAHhFu71pBtHv6IyYaMBlZFuW1VCUcO7q54D1saS+gUAzWUVH7jBzdX1exdonVu3BoNxpBRUcywhGli6PKHxsW5GUhyFl0aKHTcapno1kk2bbTtATh1sV8kVdcOwe8SrwoOjMmjM6+ETICLg9tFDQwldENMG9Y982QzeAqbSuw6CBpbixdF+qwAqm8jGgUGOOWJQBACj268lqkWPC2/XiAFIlQ7Xg6EUrycXw7g2Gr2BUCxQ8oug8KSV1fW1h5weW+DZgx4r2FHT8sKgqKKcQ6yIo4mKyj0JYTtKzhnwvNDPZwj20/S8dJ3PSFyf2dHiU3CFKjIm0mgLGe67KEFivWFkEXK0xJKvxHVuiBieXaZnZ8ihoo3pvRBvwlUn3IT/NRkOoYCNRVIMY4dBBC7hnDg8kNtJgiJyDAM5eE3GMniW9CTI+BzRytI31sCW4oWni/iwzRYd4pWicDgMk0xalAgydepUuv7665XfOnXqRGvWNDxmXJTO9HjSzMKHZoAGVq6ut1oCvrACS5a66oTh6Lxu9JqED1NHXkmaqHVwFZdqn3k0WYkJxlEpwwiVW+PHybhXKkEY3MMdXQ8xh0Fx4kQQ3Bd9hM4LL3flHCgu8VvNscOQ8FNx4wfjIyphKRi6iocE7r8m3qHngHJ9QmhKlAfR34sjy0BFGYJzY5WuNSZjRRFByZUBsfieDVqHThEBIBwkC/JrYK4LLcSdQoZHXTaEn+gdMrgOrSwo95cG13TngsgmNK8MTyXsJwg3lh8alxVZvmYiCAB5OfbCB4bDaCVyqX2kw23h8YBlPFu1/czsVPent6LKdt2Wg4eMB9rmw2OA82nPAU9RqX1pYnHMiyAnyOABNatavc4ovKBwhGE/eo4XDwpj2DYoOewF8TCkCS/K8kAsxgcKVIr3zoqVCc3Jody76H0Cf/sLOqv7Y/AgirfSDLZfNzbw3eSB9x/mD2gyzz+HUMBEhsHiuYlFFHMLPtdR8FO2ow2wKInKYYDB162z8XkZgGpUqUoivGHdgANEupdoInPrxPLswT6Ihe8VLTTTzXXotC84zQv3N/aV/V0i7x65DhgMxGdHLCKhkkQeclX5O6tl6S3MUZLgSl2m0Ersk1klpS3SS8g1HA/DJJEWJYIIhg4dSh988EHdd59D9QUnhNdGyFNlHP3SH95K5xkeasrDD14qWI5UH6nFDmIiR9ycHvBuPUEaqpQ7vUhjSbIWS6ehsV5siNtkW04vOdOorWIgKJ5BqtGtZI3HaSg0aJ4PHgx1gU6tv2/vyHpzsoxGL5XZJ9z0QlJQK0PzVgiCAZrf1t5o191SccQKRATv5gr7ZfTrDnN6YA4MuG8tFB3Edx+IMlUB+22iMY3HWYACRSV4UqAopHfCUbCC42Flpdtu01usXU9YFQeNFPQAAq8tuQ4UJDC8qWSzfR4QJ8MBjQysaFChGY/57eyPoZ6ro/Zcebqoz0svnBsq3Wrv5YO5RuREvCdAZPzjb/t8MZrBhAYHisZoVESN+sI1ic94vA9de+HF8OxTyvqaPP8cnknxjhQrQjGK2Zq4kMhntJMXg/KcNiRYxrA4pypGxlxV8eaF0QQJHFQh9MLC0szautArzRSq6ZTPwZttP9jh5OWZ0NwncZZbN/Ut3IoeboUKV/usJ52F578pLM6rPaPx/WfKnaUb2gh6Ibs1tN2ESylCs3ac8LiJQcUw/g4R4T+4Tu3z+PLtc0XFkk9JCQmGY2ZhRTk7T9VGIEqsaqTiCc0SyxN3iVyxDoaJhRYngvj9furcWR3ZigXRebM8XmOCR70zYOx44YsBX4YORn+8CTJjIRnbVDrFLkNWkuGm6+bY6KJHLMfT9KJ33cGGDpmSgd4pX4kpGSp0mqJyO8B8iqcSdugw+ZlW0s+bax//rgg8eolcCA1RhBswJpXKKCi0yHckVHzI0xKgGlA8NlCQAA8RTEQaSvcbxaJgYaRt3ioY9dUrtcC73FsJneVqyHeSDeX68rRwmi3ggdQORpvSwLusWhVrcN2KwJWZZm/M56vVYZR14XEP4nFWvZbQM0ZBiAg4oAxhOMp2UIgC4ceChLieAtUosCAXCnqbhb1NJJgvRTP6/XhNw4glVrkKrlWNZjQelJwz6IkBgrg+mq4bfXbrdQKNQcXzr2d32/LRUdvBiktxPtNQININcyW0EowSfPa4Nayd3gsmcRqfPSh8RJUPxvbEINwonqGaZ2bdNjQh0GT0OZXXxuOr7AOGuGEJbe24mAxDJcxRC+Uz5sVKYAJzp+ser894wxoU4cOhco7pmsTf8dp2WkbxBtpgzhmHuBXsFI8seGd7wUNCF6rdXN84j56gmTrA9Y3CA3j++XBwQsy2dkO9ec0Ur2HtHlDuFezPmMLVdVGqJK3Bz5tYnovJ6G8zDNMKRJC//vqLunbtShkZGTR8+HC65ZZbqG/fvo2+3ZA2ktJQN1uMv0+GS1y8D2K9s2h0e45hhMbti76xRjNjOTaxLBPveVc6XtjBdmqLoVOK4oY+EuYmlwwm0ozqUBtGMJXOmV6pBUfG0NsBO0Gr4drI1O4vNKZh+x7oEIW0hKE+9MrAbeLoF9z3Pj2/CIb34PFoDyEwIe16xIowemctvB2s9oPeBWLd6MmB5YsxdExbH4Z5BHH0Ls77Bq8TrM4jCMF+4rPP01YVyELri2xDcJSwMDTMOkJImaECTHQYVJWt+BZcssx4T3jhHGJOECyvKtvWr499e7Dz7+QtByOjMVWZAA8g5XzAte7WSIv7mebkcYLnDXIoReU9aiRM17cSSij2J4ZyzCZCm7bYGve6OOILtbGv+uXynoxFEDBda1gG3SkUo6mMvFg8BFyt12WuDWPONXje4TFzi35uTe9Zp+TTpvXh3+ghES9RbYyzSpUJt5XnlPNRVGwvyCTg+myq/mFLRbzaDTnoG7QOhqHWLoII0ePJJ5+kgQMH0tq1a+mmm26iESNG0IIFC6i9rlLXUllZKT9hNm0yJ7lzpIEjHNEl0OzniyXxlVu31Hi9KpRRPhy5x9FkrQOG5VrdoldpaChYRlWvhOBmtKepXX4TgetRSsMondO15sZ9Hzv1bketlXKcDrkRmgpTRwVHoryQ4BgT4OrVcpSOJ+SaUBKhamIBepngdavkjtGTlG6yr+qjlJjVwnZQIPEbwlRwlFDPjaGPXNdtBsQBfT89BRm2++atqqIDd/FSeXWQstJ8tG5hevTzRbqL59nf0w7XreIV4eD9YExEDZ1v11UR/lls/yx3mT/BZIwqoQzas1up6gOiTCylc5uqgkjgr3+oKXCzP/he1N8XsYRwmt6zpu07PbuTXS3HbUhWUxl5UYk1G4gp3BmfifHup5PHjgnlGe/wHIi3bHdCcehDYXiRUrrdZb/TJMjrFd2CIHYoxx1FJU1YddPHdhLbOIlwfHBiVCaZtCgR5JBDDqn7e9ttt6U99tiD+vXrR0888QRddtlltstMmzYtKplqMjA95GN5yYUMo+v6CyfecBLTKJ/ieqnlyogq6ekiBtc42mEK5dC8bEzCh9uRbiVBVwoLH7GARpI3r+Ex7qmK24S8sYCd5ZCT8eZiZDKWZIJuPQJC62IxRFyc9xiuDX0/TSVBxTNp5gnpVFhQTuuL02jsRTXPP68ebx7Ds0sJvzMYP44d2hjc+pUwDwwDw3LWMRi28eaKcjuC3liGtinMR99mog0MN/ujVEDTwhBiEeRN7TadA6dkrEmplpPCYIn1WPpKei6UBnn2uiWWnBN6AvPmgMMzMd4EsKb3t5NnsPGdr9+PLtqGAxr6ez0ZJcUZhkkMLUoE0cnOzpZiiAiRMTF58mRFIBGeID169KCmBkusxm1oQ2c90Q9odKlWEl9hPggY9bWgRLC+b4orqcOLyAux/SEUNPCli/vsNl4dq6E4jJKiQIPu0UavkkYuJ5lIFG8Fp/CBZkYiRA+8po2jRXDdRZVmNgh7Tt5EJsNIEQ0cRDl/90hC2iDkx2gq48mt51pDz0+in2Ome9JxO7GUs3RRQSvuc+MwAmvan2RXIYjFOywZNOZIu7FMdAL22SQexSsqpdx7LU4/eAzFU67JpqpEZABzDjmRbM+ghCeUR8+eJJ8DJBYvOqYBSU05MSrTWkWQ0tJSevXVV+nTTz+lJUuWUFlZGRUWFtKOO+5Io0ePluEssSLCXH777Tfaa6+9jPOI3CHiE8Wuw4j8meQtt6/qUN1Bi12HxIMhP3g7YBUDLO2Jv0s38MgDP7240jY5I7rHy+8VAduynb4tMHIEnhceLeeBktsA8hlgcj/9xYrhLEq1HMwT4ZBBHjGXjt3izpMDS/dB0j095CaIYQpoILg0+nEE2YMx9pDQ0OqoljrFhJdeOIchqJQSSleNFw+WUYXkYaZry0ozZ8QO4rqxmoiD7ekrh5CNjMjyQW07yrULl6Q3AF9gFo/Wl8FrHRNpWui630Yr2YhtwNurMrK8ryJk3xZtm8rxgCSh+j0ZyIQ8PZDM1L8lknjZu6ncvtSraHObiMHhw8SmmZHf/cXqPRmCRKe4DFYzweSlfgxzEUAn0tcp4iocAu8NJ+MFS7eaqhA4jVRjskQfhmVoI5vYqcT1yZwmBm+xxiKVDQl0izd6ADkYC42VMyEWYgntdFxfCu1bLNeaaw+kGDCtQ/FycRBjTXm4lBFxh+dILGFDsYDtVkTrbpHnmAVVRqKEJ0N4rhKOooXiBVeusRVRsDKV1QZKt29U918JOcQqURAC6oUKKpL1ln0+JKxGhfmIstVcNliGFefDBOq69yQ+szG00e0zUhk8wgTgDp4xPri+GkuA1L0QE/nswH22IMw+0WWvWxKcE4RplSLI6tWr6brrrqNnnnlGVnPZbbfdaIcddqCsrCwqLi6mjz76iGbMmEG9evWiKVOm0PHHH1/vOidMmECHH3449ezZk9atWydzggjPjvHjxze4fd6f/yKvJ11xtwyAIZGmZUY3PUix1Ghg0RJjzCfGKZqMfqy1LrcJ7VGy28MDFx/4gQQ87E1eKrEo5WhwKYkCtXaaOs/4Mna7fVMFlagOAHZWDe7I6OLv06pYoNGprjjSGUjTymniSxNfpnjdYbJOT66WjBY7vpiDAcQvJ+8V1yPNpuShvbraGvpKlRXRhpw0W1EnlB7521+mGna+SkOujOzIfVOdA+dQGyDEdVuoD2FVXv1piOvwQMfNAg8mv5pU0g1eFH482jlUxCPDKCdqTZr96zEs4gn1MlbO8cFlg+KRNxDxiAvC8dO3iccQp6EoFbUvViRhqBfEv7SiskgS2rQ08uyybc08UKK4pkEgsJTDDmBnUw9dQCEG71fMfQKJZvVyt1j9wvRcd4syAor5YvT8HnHmPMCR1WTHrocSbAwnQ/gwlTR1631ozEMCiXZRaHcyBnUxUpmGz2VTUmkQG719Ix5kelovTx8QRkGQ18VKperUZjDUQ5Hlg/ltbCtZ6QM5+M7AgRzfVnUZLF2Opc9Dq9faCgoePXk15ofYEMknYXWG/tliNX+QksS2d+QZGfh7kb2wqwsaSoLkyHPAt+3gyDa0beL59AyIPHtoa+RaCXTMtR04kd/7F9oOKOAz2r9VPTa+4kg7fXANhXK1EOfw9vPU67E6w2e7TRxsUAYnZBvsRan0lSX1losXBBf8GVlX/762opSOF++DdcW2fSW3odPxhv0wDNNKRJDtt9+eTjnlFPr6669p2LBhtvOUl5fTa6+9RnfccQctX75cihxOrFixgk488UTasGGD9CbZfffd6csvv5RCSkMR9c89nnTFuMZOj6dzxAtA4A9A5v1cMGBhNDjUfcfIPCVapwlGfX3tIY68CEQHzVD3YwUM8OqwiktsRzqcRnCVJKegxusP9US6wGJyQFMpRr0TaBr9UxJkQU16uW7wBAlBxQzMh6G/2Bqq3Os5NPAFjJ1FK91nLuMKpU9D6K3QO9KJDOG6NHEBR3iC0AGhLpEOjLc/CE96GVYsW4qlX7FUquyIVtn2lj1lMPKx4C/70SqBIZzEDyNpIW3UG40EFIuwZW2go2jlamVcsbOEnXfczxz1ukPPFCxri94foZwMo1GAXj8oXPg3QidYEweU66Mkcn2HoIPu7d7F2LnzQKcYy2GiV0plR22UEL2LYBcCmXBuoLOse66G4Dr0VQTtvXl0UQq2iQJJWad2dNC0MtqwiahD7lZqM7ymrcEMzeBCIw2W98Bt6622XG3TdM71edK2RgzFCmhPRrd822OhrwPXjfe3rwy8DXWnjj8Mwjk84yx4psl1dIZnIbwLrC6R3/0oHGkVbfA6DvxuDiV1BYaLoTg/dKA6GzyHLHzerFhrTAAr3tF2yX5RqPd3iwizUdY9vk/xXQADHJZe9ho9B9A4R08th4odwQ5tbb39gth+8ECTTcby1vi8AtEBPdrkNKXR0E54duHzhRYXGatMhTB/DcwTVT4YS4326m5f3vyvSKLgoINHgTJAAuuNpTpcaFnDDVP/mg2uBo8sw2CH4h2n9ZlMg1eKFwFep2IZeB/6wTMFvW79m81V9PzQp8Ik2dZm2De9Io1hv42hVvp8tktr82h9PQx9VgZseoOIj88uTSQO7rdz3d9VbewT0ga0dwkOuPjz4Tj16lT3t291cXTFMrvjmQPVxVAs0l43QRi8SV8bOc7BX/+gVoc4NvFWd+HqMExzE0FExRYhVDghvEKEqCE+69fX//J7/vnnE9Y+4f7nwdFf3QsAVH8nFOMcjLQQuFTqHToPuEs6jdz7e0Y6GlYRvFjRewVGL6NqzcOL2k2SU7cjoNjxxO3HVLXF5frwpa972Zjccd0+N7Gzh94XGDakjLzJ8xsJJfCCa65nc5mtYSunYa4HTOKIHRi4TqJcmCE8h0BgcipXaMVwPNzIQ9iJ1cu4+qFsqAWxz2jMebtEOiAS9NrB0TsUN6BzaGVoLrfQqcQRR6fwJCWUrA2ExnSGkpUwwoUeHjUrMBjgneB8+MyeHCFfRPjxBnvYe89ooUqK4Y9/+u1DiOQ20YBTLgjLfpt6m2F5bA96lejCSdaGyLM0DTqBwshbWhqi1SVCKAjR9p+58LKAzrviuq8l38QKNbEkpEWyBvSLfAFX8agcBejh5oXRRBTcVq0ziqkWeoxUw/PBKTmuQQSw/oocyyB6iKCYoIkNilgBJaixCpFeBhtd3xWhGu774B+L1W2aSsSicKSPsroYdXV6/6BAoxh28IyMSuwdp7u+Zylck1hBC+ZxMib9XTrbPtNCWmUqL4ZcgBiK3hIopHnRW0SsDzwh/GCYKoI+jshrgjrhMx+FRbhOonIoYb4ReC/EO/ASS7letx5YpjxayoCZQ5lnJQk+vPP1qid47ZvCjZ0EIm8n6BNBexTBVPecM4ggSkgUPiu220ZtTy4M6qCXD3iC6CHePvAE8eOzE8VHvJ7Rs0ncnv+stfcM6mJfHbJmvpCtJ0gIQ4igb6U/h7yBdrbPWEUA1651bHVrD5Th6jBMqxRB6hNA4p0/Xvw9u5Hfm6G8cBRjuBt0RvQRI1TxIT8HPrw9/Xsqy6NxHFwecYX0gwJu6eV70bUTR+/QbRsSJWLMaVRnE0aisBPsbavlPoFki4rLZ3aWfcdTC6XwwSgbCh/YFt0Q8Jhyd6AXASxvrCajjzDB8bO6qMKJtShy3kPQOfCBCOJDb6AcNTzKg51N7BDCi93bQx2ltGCEAY+HBz1bwGDR80HgCKoHRjEwnwSGHtS0094TJJAPoo5mwCqdGFw3jGhTJQiG/TobO8uhLuD1BE3DMBcdHFFHzwMcDfVoZWDRlFBG+2GZ9BK1sx0CIQU9NNLXRa7H0G+R6jA+HP3UjAQPPgcgh0NgmXpPetF7A+9DQ0deN9JwBNdthR/0Wgq1hXt6ceQ+VkrU6qGAi5dF2jM4si5PBRh56BWjjUIHu7W390YSdn+t51JU/hwc+cbzObCbrYgl14Ft3ranrZcPrssL15ZOAFcN+aGUe0DeRxg6BUY35pjJiLTZrxtMJg8mt4C3AQq1XrxW8VmlCfzoXo7PW3wO6h52IdMIPzxvfR21cNC22bbvUs+mrXFVJdIFcWynF5/f0DYPegui8SifHfDOgfvAbc4dRewZNsje66uTVk66DPJ1gSeFEpqjCVkhGBRR8mBh1ROnxJMgEiYyPWWUqAS4ETuUPov2jDM9I52ED1OYA/bvvItUQUR5LoNY78V1oQGteUL6oH+CQhoKlsZwWidvWOgr6vmpAlCq220OJOw7EnhfYi41HIgLacKmBz2NqeEEXYagmMABO+8GOB/avYKeSugZo1SBW7LUuB2lvw3iVQjWhWFTcjtoCyjhymtTMjFso5Oinhwff/wx7bfffrbTRBTDrrvuKv9etmwZnX/++fThhx/KwfuxY8fKdA7pzbHKUysj6YlRw6xcuZI+//xzmcsjpLkCXnTRRU3foLR0Il+6OvKCo/2bVcPc6oxxp+Da2gESdoJbqzJqIjv/YHxsF+kcWYtWGkcnPB2ybF/mfizFuLXc6NXhxkhSsnVrhjeKDYqhjmgPclMcN7YlKnGVqVoOGpMQtqR3lNBDApM9KsnbXLoh4gsPO3T66B12YhSxA41z3SUfEll6yiG0pC24WELIjB4fHYTQDByFQEFBzxnhg9NR3R4Elq0gYuRoI36YTBQMu2q4Hongb+1dHvLbvxiUsAY9TARduith9AwSuKLbuGLYyhUawhzAyKzSwkRM269GMbTz9pG2aC7p/s1gvIC4EIJQpeAg1eMFvUlUo9m+Q1SZrd7TaVsgrMADIVmAfmwDlfYiQGDX/rAv0HHPUl8b3k5gEMMxCEH8v+4J4geByVeK4UWqe3Ta8tqROaey2RgG5lb4wb/hGR8Crw49maubkX+z9GZ2D8dlvGh42AjXrgCxIrBshb3xFEuYCzxvY6lgpiR+BNd/QciQhDdenMpJhwyejEpYwhI1N4NbTwITyrX211JbwyyknXNsjxJaCMJ7lIs+jvDjvQLGubddntETE9sZgIEPJSeVHuYIgwUWXCue3Mh8AQdj0pjoFq5np/tbEYcNIRu6N6zpnnYbBmbyylAGWzQ8eW1t+2p4r+qeIEpuOgyNQY80FF40wdS3zUD7ARoMMdM8NgPgzWoyyEPY5sED1InojYkPPwfb3lu61VZIwtLUSqiWNkDmQ68lFE5QTNb67oq3XmnDkzqbkghj/rnQKvX+4twhzQNRmEPkr0SuvfZa+uCDD2iXXXaR34PBIB166KFyoP6zzz6joqIimYfSsiyaPXt2klrONCsR5LHHHqNzzjlHqmbt27cnDxosHk9yRJDalMWhIojFd5jduwLcq8G11LcJXtrw8lFiMQUwKhX6YaHty9yjj6KgiyCMIAZXrXWl9Juyw0eFzSBwbkwdCCVLuyZImDqlOB++8NxWSFCq02hJUpUqMgaPE73TEcRYejiGSicWrg2n8rLo4YEdQh0PvrRxJGclJHkDUSqoGYb+Qf1tO6Q+FKh0DwlwJ02HRHXoxeDX89dg0jqsXqTEqMO+aKImjvSicBGAkBM9n4MHhgqUGHlcNeazgHXVzGdfmUnJh6HlRkDDHcUjDPMIKRVtVEGirFPkGHrhVvWBoKFvMwidNdymsj/wOya2E1QUwLVuCI3RBZWqPDjuVZEZ/WVQDSsPKt1oHhKBbBhZhN3xQ7UhPUwE88xUQ0I9FLhk23rV3NfeavU5oiTXK4+009ctIiqFssxVCBS3fhQTQcxGN2k9eSR6rHi2lNu7amuhV6ZcNEpi1mWrXT/XjIDBgsujhx/+ro+MOoaQGAR1ZRQd8xzohnIYTYjzY/JIzEm1YlV8YREO5YOVfCFwbJS8UVolC2xncM1aW8HMQm8LPYwWxAZl5B6e5cpzXPOqU8RAGMHWk6Yrz3msVAaeC0qidt2AhYoq3h0jYQ541kJY8UOrSkcrVtsKH8qgku7ZBN/96KWDxjkO8GjTLAjRUrxZsW+k9VnclCR3m4BX2Tf00tVzbRhC8TBcDD039P6JEuKGZdD79jBXEoQEskreqbKgsW9lCmnFcOtQISaa1wb24L0fzMqwfecq+cX0MEH42wO5gRTvGb3AALatHQh20B/BgSS5jiIIx4SQSS+230EAR+ED++tKbiKtnYoXGvQdY8l509xJ5XAYYZOKwh1hqqur6Y033qALLrigzk597733aOHChTJvZdeuNffmzJkz6dRTT6Wbb76Zch36/EzySQkRRFSJEZ/JkyeTV3uxJo3qKqKgR41/xARd2gsDhQML3MONJen0PBWGvBVKFn89o3/DB+MUTKN5ygPfoROJI1SobGOH2GkkTvHEgE6XPuqAyr+p4+q0HeyE4vk0CRr6MojSiXVTvlLvuMbg0u2WwB9/1zuPYvxohpW/F3Si0KjRDDsldhhH/zALP7rHt1dfAmhA+qBz5gPPCRRa5LoNCWGVqiEonlZUGYUXxTAFQtA5rFk3Cjlke2yqC8AbSyvLCwVV1LwbGIMMISNR+wDzoUGvZP7XDInMdVW2+4neG3opYP/GattpPhBBMImjD8qG66EqfhQkIDQEwwgEgbYgEGFSaK1iRNjrSA+HUSrkQIe/uqCNOVmkVjHBFqw81FbrLG+BY4tCIHa2yx3OJyStxQSZWIYdDRm5DBjAPnBJV9zgMReQXCGWPAKxJgu8EvOgzdo1aMrB5LZCgiKIwPMWhWIPjthK4wfuozUgGoMbuR9DPMQyWNbdhbeg7r0XgNFZJS/KNhDStVkTgDG5Kzwv0ZAJaaXolVw06+A9AaIOViPBBNMSOO+EHjRQ4Uj3GMLnPI6WmzxZnDwfvCWb3HnCoNEMQpAimDn1oTAE1FC61gJxReIgcLjBJHB4wEvGlBsjCvC4Ud6rmgFsFIKwvLmWdFbxMEBPWRDpvPjO0waSUCBS7j3sW2G7BJivBIUH9JxYEOlzWFooH3oH+yH8Tcklow2Q6OGQdcvg4IAmwCrzweCVB58p8Oz16YI8JheHv0MGLx8nvHCuseqMPugZjKGiWIslgYlRRTVQJCMjQ34ShRBAROENIXCEmT9/vizuERZABKNHj6bKykr67rvvjOE0TGqQEiJIWVkZnXDCCakjgIiXzvJVallMgUOJPzcv4FhciJ1AUcUDuTtMLtR6PK4X47LRRRK9DTDpnxzxAldEPZGW3Uig7r2CSbngBe6HGHO92oEaKlNtbwhgB0xbXgkjwhdTRYWrkpF4nBElNlavQgAeForLrCGPSaxlhhG3sb5Ggwfz3zi4fyrHAztKv9nnDyBwmU0EeH2F0BjDbcYQT6uPJeB7Wekgwks1felqY+cMO/nKvZoBnUDNGCTsyILw4AFxIq00cm5D2qhWCMQerELjg1Ooi0AYqoOeICEQTjJWR54DwTz1ns5YYT8tmJ1uDE/K+DNy3EIdQEDWRJ1w2KB/mSYeQg4iLMeMpRSjRGO9PGZ4+e4dbfMv+Faq96OFVbtQfEOjV++gw/MuBHl2fEsh9huTUmrnJvAH5JzRS2KH0d+bpvcoXk8bN5vnBwPUbZJrE6aE1z69JDk+oyFcAJ8pepgkVtBQBHV4T+vJcdGbRAlnhESioV9BEOje1XgNuT0eobX2VdgI3tlKQkU9KTSG4eI1De8YzH8gCEKuIcxV5MX2uwy1UgZyDMdZrg9CmhSxHd7zONgQFfbaiAMEDUYree8G0/s7SuzBMAnMUQPn2ZTMXS6D4hkKNG6PXwxikat7WgtxQyzIdYH9Nj0sDr1blUS5eN/CMlHeK/ieLokcQ6sdhmyq7yIvHmvwrkLB0Sl8BZ8xSiECfOdriYcVzzf0BHFK2F3Xv/GmbA6NZNOjhzqIMGXKFJo6dWrC1j9nzhwpcOB21qxZQ506qc/s/Px86UUipjGpTUqIIKeffjq99NJLNGnSJEoVhPuh35uujDYpZfT6qLHb3iJ4kOLIORpp8HsQ8jzUrCDyp28VZKjuGOmceaGDrqNUssDM5LDNqIobuG+Y2BM6V778PGNohx9zXcBoET7InVxJTUlbMdmW3Afs1HZobzu6gAlbddd7b0/Yzl8Ro8IJk5eH0rnrCXG/UFJPktnWNms6GqlBzfbwdetoO/KPoyPKKL6e+BFGupXyuXA49CvIB7k//JCcMJgLrqikvliUMr1gWFmwST8mGdVdc4s32XfwYfQwBCPVsj3oOQAutJjoVfEQWad19HDECSsUKCUCtbAd7AjjPQ0CixKrrFUIUgwGU9lOPT7ZkAgTR2NNZbvlNsFdPAT5gJxGcJXwN3zGQac64NabSJtmN49cNxhAId2YzINRv8U1zwVLOzceOO4hPB44muyUZBRDLr771VVcf/Dn3+yTMKKRqF0DSt4EGDUlfMZh3iZNuPHjMxvbD9dTVD4HeHYpoRkYsoeVqFyGCKBLflD3nEMPCRRQQUT3Q5UspyTdOEqKx1kvG4pVaLBsttIuBzFYSXwIf2OYSgC8OqNyb+FxhuvR6Z2nTPt7S4NylUThUvTVQysaTAyCsitB32HgwS3K9YHVdmJIpInEWz0K7yE9PApDLnzggeR2m7hvptwnySCkCTeWknvLkFPEQVwwhb85LWOsMqjexgnF9IxRBj0TMQAaPoYtLmGq6HPEG85Ss7wIScHwE5MXiBBGrr/+esc1fvPNN3V5PwQrVqyg//znP/Tiiy9Gb90mabnwXrL7nUktUkIEmTZtGh122GH07rvv0rbbbktpWpLNO+64o+kbJZI6edOVTo8y0qGr3jjaAaMwmKAMy+L6tOoyOC2ACb5AdMDfY3lAu+5cucSP8dLwYvdsKDJ2RpTs2Yb4R0wQpneQnRKrmQi5FD6UNoDwobhQY+cO/tZHNFDfCEIn1BRCJIH99CoJVCF8wiHbtLdze9tqQxZUMcCEq1El5jDkAZJV6uVmPeX23gpYTSXUBmLktTJ2ofZYeQZKYGLIgzbSoSRqBYEG44sxkSgVatV68HBiHhAsXattM5BhFpwiQJ4ILc+BaZuYUwRL7OptMIW5ekL9jTlFcN3Yr8C2RCedheUhj4gSGgPJnqtgX+T6gpFY9irM1YG5U/xqklY/lEJU980i+uWVugsgNKBGgPOt1ypj4TJ9IqKSZ02xrbeI3J+1G+xD7DTRtQ49KTQmi3RZ2QqvfDRSPFBe22nU12nk3YRjaF49hqSTEe82Xh1FFWWU1MHzwOQFEG8i0ljAd4z+vMVz6PY4K2Ee+C7BqhJ6KAKC71n0oEEPJK06GXr1KVU+8H0MHjfKCLi4VwpAvMNQBAid8gxSvU+8kFvHA6ItClQYZhLUwg18IJJh+V4crAniYEcM14fu1RmCaz1e4QRxEsK8GEIKQruSkFcT9Xy6R1IYLHUN3gb6OzuUCR64kHdJCaHRhGasEoUo1ypWuoHnsATCS/HdruSk0t5FerL3unX/8rv99YxelbLREMKZCxWnwMMO81HJbZaW2VZpMlV9iSVvhx7ehN53ifYQb83hMEIAcZODQ+T0ENEHTvTu3Tsqd6XIWXnEEUcov4ucIV999ZXy28aNG2X+EN1DJB7E+oRniYicEElYCwrAm4hp3iLILbfcIhW2QYNqqqLoiVGTGQ6jG7fGGFw07rGzCzGKSvZyLZREeZnDCI8XRnY9wSxzmIihs6y89LWRNKVzg665MDquv8wVF1Zw5Vdi5B06E/gCcSOIyPXBSKmSx8OQvFTvMJgyuLtFr5Bjh1dLrIrx3srIP3TuUCyKxR1YjzVWYvux0gqWYEtEFQYslYllIk3x1Zq3Qjp6F8FoPXa8Q7+rwpUP3b01z5I6cCRMD9XCUAIsjZwPYVhaKALmY1DEGghBwVwbmPcjWlywL9+rLxPCUrKWIZkrloTVK71AAlUlAauWB0TZJpY8xtWBIBKCKjxeEET0daPwgZ1drzZYhu3EBKrBLPUcVOfWdHLLO5s7E/6tkeWrCrrY7r/chx4Q8gDik1OiWqNw0xsSsOK57auVSYZnoQXhQSFILutDYVILTfGsBS8bLFMM6CPIWDFCKV88BBJuYt4OTOwqz2GwwaVflRFpzAeBOQtQjEUDXIBiAyaFxntQC1EIbSxxNTpsaid6binVzUCoUBI1iqZhbh98n27YaPSCwHxXHsjN4N1+SGQ7sC7MXxSV1wWSTyou9lpibiXRqVYC2S4PiG6kBdEz0xDa4tUECWXdBsHOi3lhtFFaffDDrm16fir0VHUjSrk2OOMMrXTC5K2gJJTX+xOQmBT3UwmBdetJAn+HHPZT8SjG5yL2ydFreLXm/YN5XfCeyoXnAN7fejtBtFYEaOx7aznr/H172ed3ggp3aVqi92BupG0+LIEN++k2dEzxHsR+CuZR0e4jn4tiA0xi6dChg/y4RXh1CBHklFNOiRqk32OPPWQCVFFFpkuXLnXJUoUXys477xxXO7ds2ULPPPMMPffcc7Ikr8gzEqZ79+40atQoOuuss+pK9TINx2NhxqEkIeKn7rzzTiXZTLIQiXXy8vJoP/+x5PekqR4b2NGDOHqBF14AaMwpyQ1hdFzv7Cqjrv/Yxxrr5cC82DY01NHFErw/olznQcQIYek8CDlBI1HfH0zEacp54KSaK0Y8GsN6pRUIOwkusM87gUk9aau2PAg82Fm04CUdVXkH9sGCvz1YbhCNaT13CpQSVkbvoDOhlwPFfAQeMCQsTNwF8axKJ1zP5dIZ8o2goa0bwzAtiNVZwJjFMJea7arfIzvk8lGCIReYwxFECL+WNb46F0oDgyGgVKcJmMUFxIfJDuE+1BMSGo87PjINHjtR1wcYaUrnH68nzXsBk9mhqzHex/pIqBLKgLlxsCqGFuYRAjEO732C8CisFqHcT7Kzut42XE3xMtJj7JWKDyBEZWfSUTvfTn5vBQVCmfTatxNqJhgS5ulGo1eppKEZ7eiWjvckdlBxGTTGBQYx1EIvuHWaIVBYYB/uBUn7nNoc2lDcYEMfUUZNcXQZRQd9oAENHgyZRC8Glx55igELIo4SZqrnyTGEhMUboqCH6ihenqaQLodw0FhGcI0V2TA/lBY+gaF4GOKFITj4LnNbScfk2dSYOI2om0LM8Dzp1XoUL00cRDAIF3ofSAltxJCuGKrDmNC3aQqfwOeyPlhh8jZT7i/ML6V5MGEYsLIM9hUdkv2jca4MuGFfzUEschu2Y5rPbVJmBewf9ukZ+V27V7CaIpagdp2jzSAkOeVVi4eAVU0f0+tUWlrarCuPhG2tHvdNJa8uEjUQkZ9w+XlTG+2Y/Pe//6UDDzxQVoHZZptIeHu4RO4OO+wgvT5uv/12Ki4ulrbsUUcdFVeJXGETC3FFeKQI75PddtuNunXrRllZWXIbv/76K3366af06quv0u677y63NWCAVuWLaR6eIEIxGzlyJKUSvp7dyOfLUEaUA0sjL5IoD5GukQ6FB2qdYwfb83fEI8HTVRvZRI8ReLGgi6P+kkGBww36y1cp7YVJqNBDQcvIr5eAtOvQ4YtMd/PFzha+zIKYdwNGMuUyKHwA6IWglOHTPCTcHSfNjd3Bxd0VhpEwZcRNfxmj9wh0xD2lYJRgKUaHjq4v3WBUaIYdejWkL4sYXIGu+fZVW8S0fHhh4aoxZAVyePihSojcpiKCYMgFjOjjNrR9qM5JsxVr0Gss1EYL2UCtIsNnK9wEeqiCHwo06NWBbVbyoJTr1UjsvQpMoTFOYPuDWHZGw1+JISj2JVl1EctX0c02x0p1WyydC0aapptbgwtty+eih0mUhwV8TduCVWg8dMzu6VSYXUHrN6fRa9/VzBiCECg9/w2WWURvHn2kGd2jUfzDe8CDwpdWoUjJ+xQCUQyekVEdZ/xuGnXFvAZaB99tgmMTbkcwGwslhMdlOE9j4sYYMYU8JsLwV3IIoRAHpZ3R+6dmBSB8gAcNirHoXSa/g8s/lgdVQmhAtI3K5aOJP3XbR0813WtJ8UQM2QqgwZVmT0QlRA0TR+Lyei4a5T0XshUxlApFmgFu8pp1EriUfGEgUmJ/BEf6PZiAXvdSRC8dDHvVBmWMfZBe4GWK+bF0r8Zdto18AdFVSf6te5qhiIDJyEGMVZI1d+9kFKcxBAUH/PSKagSVsvxQ0QWPjQUDdp5MrZ8Aog4OYgRhAFK5HwQwYGRtrrQP94Z+b1S4NtwrpvOkJ84PoTcPltWNU3BrlojOVbwlbhupRC4mRB0xYkSUABJO8j1v3jw677zzpB0rRIqxY8fSjBkz4trmF198QR999JFMEWGHEEX+/e9/0wMPPCDb98knn7AI0lw9QUROEOFKNGvWrJRRJ/elI6UniImoHBCYAA+NW4MbfqC7VjZtXamtYWZBfXWPPrKJL1As8WdIgBc1urDtYPtqB06j+2hEg3CDHbVYQi6iqshgE8DYN1VAUcJk4CUp1w3Z8TFfC8bd6sYHtgdfUvgyDkFMtG+LVpIODSh0oYbbLai7WhdDNnMcGcVQIzTyNFdSTDga7Ka504a3sVm9hpTSpathpLULVMzQkneidxB2fJWksy7diVEwU0IHYojPVkYSNQ8JnOaFkXtlxEzLXYKdbysvxz5MBZMzoriiH1tsC5w3rKAi8EGJWRSSlN4qGj/a7RnMRG8aVVyw+1tuB5YJgcDiL4NrXcsDouwP5jjJguPhMQtE/s0omIFrcHmAnjv5NirM2UTrt+bSmLlXR4krUblcDF4/erlFj8HrCX/HBNPpRWbPC9N9qBsfynzoqQTPW6VTDmEVEvSqMzxXo0aa4d5RRkDR6wifL1HlNDfXW4pX98owjdQqXkcooOtJaxG8b/B9s141gJXqKhAa49ZDA9/h3s5QZhiTJeN7XQO9QnBEXa8QhO8jfJd40NAHry0lH4eTt5piTGvvbxxZxWcxiHdKyWKtzRjC48MBG/Qa0oQXDGk1jfYrnkm6IIHhrfj8N4yuN2b4QCy5eJQw0WED6/62/lwSd54bN54Qjt4WcYb3KIleUayBwb+oRLcgqqAXtOk5GPWMAsEOEyxjOWtdNPAPioT8BdtBqC7kJwlq7+n09fCcx9BOSK7uVkw29Rv1pOlYaYxWRAYGQ+D9aRLAW5onSPd7rk+IJ8iKC6Y0+2PCtFJPEBHr9OGHH9Jbb71FQ4cOjYq5mjt3bpO3yT+wH/l9GUqyRzRg9VKOyqinwUU/2Cby4PNv1MrAFkA1kfUltiUC9SRtSh4K7LjhCxM6tLobfACSTcXryonE4gaoZOeHzrbAC0ISdr4VV1gHd94QxD6jIq+U0oXKLHLa38ts3biVyiLfLYhsQ3uIe7GDC9ezBSMivo2a6o9GAhhPpnwOURWGILYVS5Li8hWQFyHKAOyWa+uVUd1LHRX04ig6JibdJjKa6AOPhCgUEQH2DfdTE98UrwrMGYTtx5CyCnP+G2V5FBy1w2xqG+a68G+xzxtSX6LXyLqCxpwgXjD8vWAoe1esMxqjmdAJxHA1bJl+NWXF6fWkVMxwKV7haKpfN76Oq64TB7J+qDUgtGefBdWDlGpDeB9qrvN4ffg3wgnBjid2TvWqRmCA4jFEwdKrjVQT5HTCcBoLwmGUMBstmSuGRphGqh2fyYaywPissaCSlf4u8Q0dWK9HnlyH4bwH12GCafCK1Mr9olcbju5iGfMoo3u5IYcEhmaiOOEUdomha/Dsjhp4gO/4XnAbToIJr4OQeFLxmFytholgvhJ8Z6FXg1KJQ8slFm/pWRz5VsRkrA6nhy+YyrXjSL0W9qrkxIBwUkVEMniiCvz9+thWxFFCjbTwQ/QSQQ8gC+bTBSJlfRjihSKOJoYimAvGC17Dioikhb75+vSy7+th2C6UgfVqfQZFaEURfQP0z/QS7yC6KmVtMZEyCh9ebZ9BtPSCYBlLcnskCO9cfTAS33kIHg39CvJCKDXmjwuZRCDtWWesMgXCR1Q57RjKjTMM00JFkHbt2tHRRx9NKYUYWQn5FAPayXMBvQ0w07qSCwA6I06mgoVVQgy10uX3Bro6mxLrRc2H4oomSCFByAWglKcDDws9HEaJY8aa8JhLQI9Rx1FLTBqbDwY9hkI4xM5jZxsFGsX1UUzDJLbo5greN1iiVzdGQ8vKbF/UShy6NsLU0BAcJUmt1lGxsEMJopTl4N6N27d6RQSztOWqYRcqULcbxrs8Elsb6gmeOVqHUEkmikn/wEBQQlakt4Gn3nAUZaQfK7vI7dgn/8Ryv7q3gykvSqBtpG1V8Lce/oJhJ0poDQoqkHxU3wdTRZrQAOiQedXQMUX8GWaf+EsXe/B4+GH56jZe23Z5tYcXhufg8t4qs8BUgcuAl4gQmP4ufoPWlRFtqiCqHtgtqhRzzQ+RdftBqEYBGisc1awczhUK1Zj3CL1HtHAYZeQdjUwQqqNIQB7ieIjqfLtAKV0OwgeGTLiNl1eqk2HVbKfR9ThHrdXSlO6W8YC44IV3hJJnIgEoJesp094A7a69MzEfEeanAoEsoCcp7RJ5h/vhPWllpdtWENOrwwT7QcUlvCfwmaR5PyrGPa4bji1WHNH7Bh6opIdepmhAh1AA0CvHgfCBOcIC4P2phG9oHgZKvhjoK6GQ55SAFcU3fBdagyLijFzfTwsjX9AbCYxmL1TR0Y8bCky+3pH99GD4SLaWbwxDZbDEfQfYZzxnDsl1MQeUEp6rVV0Jdmln+84L9i+0Db+U24TQW6N38rLV9smB5XmL9MMtpUKd17hebIE/ra99HivM06MLo6awZLiG9ApcHhC74xUpmz0JrA7TEhEhMd9//73M+yHCbR588EGZK6S8vFzmHRERFCIEh2nGIojIuptqBPOzyePPJF86uDVimTHt4V3VHgzdoL2RaHn7GGN4fZA3IQTur76lq40iiJI7A0etcXR79VpjIjJ/bxhdQOEADAxMzCfbDaN5vn44OrHVdgTBTYI2OZ9DCA12LhThAZZRRmc0925lBBJGAp2StGHZTKXjBoYAdqCUDoP2osRQChyR8aWBa7DcELj9doLKOZAPAXMhYIUJ+T0bOiEYdoOigae3MawAw3PRQyHYMdtc9QTLoHbqU68AEG3ow/6AgaALEqbSseiV4gFBAUM5otZniEn2a4KEsh0UCmDdGWsgYWml1rmCmGQMlfGthBFH9BTQ8lNgyUmsuYzVPPTKR8awBMxLoLvO4/Jwf6mx21hBRcsFANVNMPM/drY92ugZHisLvCdEQuFj7iyj1SVEXdqV0dCh4e1r4TBwHwTbYLy5/e8CL3g3KR5Aln3IilKpR9AWjDZYHsMK9coeKADqwl4Y/5YqY3JdpcO+dFW9YSo6VmG+behasF22bYlI3ZjxW/aVrdzmykBjFHOyhLK0c/Mn5MuCvBeh9hEjx6u1E5/z6CGBhlEIQlbkOjCEBrw/MJE13rdeEIOjXPkhd4dTAnBltBruTy/migDPA93zz6MUWgbw/sZwHrGOlevsvQVWrbHNQRUFnF9MGq6MepuXJo8LQT/Ke8ZQdtpjKh2vJ7RF8Q6ei/hM1EOljH0ATHSuCXGKpxEOkEAi6VAmeIetUUUTJYk79lXw2a2JPd6dhtqG3xGUdFW8UnQB3fAsD/y+qMGCI3okozeTXqkF8WBibod1N1jy1M8neBgq3nqd2hvLB+NzBQUe9AaKJZwpuCLyvPbhORfAs8eXA89lzgmSkjlBksXDDz9M5557rkyOevXVV9OUKVOkADJu3Djyer309NNPy7K9t956a7Kb2mxJCREkFfFtrpTvpNBScAVtDyEOeh33hRvrdQ32oSspVg8RD1boKKCHBMHDEw1zuQw8ZDE2UxkRgQ6yH3MhiO2AwYXu5coLs1yrRQ2ZtBV13WVMn+Ly2t2+g63Xp1ey6FOefbIpHBnupcUE4ksPXN8JyzTqnVh8SUGnBzuBKAIpOUDkusG4XbLSNsbco4k1pgoFvmLoOBs67nK+dWg0++yTxmql95SSxRguhZ0o/dyi+35OpBNYXZhjHwYG4qEeJoLvLhRHdEECwVCdQDa4t4MnRlD36sByrwavDD1hqFK5BtaHXiZlncB1XnNJ91UZhKBecK/pu4nHI5Rdr/AU3EMV0jwGFzNl+3oxEPDY8MFxCkBZXNw33RMkBDaaD9aF59OpWk96gSqy0Rqb86P3r/F+L62wT86oVWzCUVcc5QuAYYhu+F7NC87kVeE2e43JRPCC8eYUIhBl2LipmgLTFE8veMaGNJfyWKrQmHBbntyDySZxGfSc10KijFUmMEm3tm8WVtBCA8pU/cLBW8/oJaIZg6bj6UdxAkRzr9a3UJ7F6DGC1UC00WlPbgf7fAywjB8HOHBd+jZBeLDgXtW9s3xbIFysBMJw0ZMDRCklD4vupQICsJJ7Bb1CtRCYEAz4KF4d6FWhCT947+CgUggSuOohVbg+N0nXvVoYsvL+hP4A5iuLura/j4TeIr5tBtp6rkVVjjM8Ozy7RsQVLyQFldOwr4THHURwL+TRQgFfz8MRwAEaB3sVc0UpnnyYWwnDH7VzY2G4FKZlg/xrAUisLrcJYrcf9kfpn+FgjUM4D3rpKB7Eem49OD+tUvhgXHH33XfLKjEXXnghvfvuu3T44YfTI488QuPHj5fT9913X5o8eTKLIM1RBDn44IPpuuuukxl3ndi8eTPdd999lJOTQ+eff36Tta9PjzxK92cSDaxJCrZlUzmt3lhOael+6tW3kIL4UCeixT/ViCXde7Unfwdwa6wM0trVJbR5cwXl5mZRYcdcxRAsK6uilSs3kq9fJ+rbr2NUlY3Fi9ZSMBCiLt3zKUdzN9ywupBKirZSTm4mde4IBv2AjlRVUU3L/14rXxL9tula8+KBDtTyReuoqqyKOnZtR21FAil4yWxcsISKVpdQVk4GdemsCgrWiCG05M8ao6G7p4L84eVq35Er/1pNYuyyfdcCyu+kunRuKtpM65ZtoPTMdOq5TTfy+MA1uH0+/bOgphPQc3A3SocOka9nd1q7YqM8BzmlG6hDtxrD01fbwd26qYxWrywhn99HfYZ0i3rhLP5nPYVCFnXtU0jpbdBkCdD65UVUumETtRs6gDr1iBi0oQ0bqGJrJa34czX5unWhfkNrBSh4SS5dWULVVQHq1C2f2mL5Y+HNW7yVijdspjbZGdT5iN0j683wUXV1kJYu2SANuT59O5JPE1BWLC+iskCIOnRoS/n5bRRBoXRTOa1bt4kyMvzUo68qaISCFv3zT02nrvuAQkoPj0r7arJLr1pbSls3V1JBu2xq377mGvVV1qx7y5YKWr2mlPx+L/XpXUgBSHDpCRD9vWittDu7d82nTChXK1i7fjOVbi6ndm0yqVNh7XVYe5jLK6po1bJi2Qfr3682wR6cnqV/r6WAuL67tKMc6ESJcIUNRVto48atlJ2dQYX9QWywRChykJasKJKeIP37dJSOUF7IQ7J8yQaqrAxQx465lJeXpXgBbFpVShvWbaLMrHTq3gdGgP9YQsFAkBb/UpMPpu+e21JauINU60G0esl62upPo4IOOVRQ2JaCf0c6RFs2bqU1S9ZRWkYa9RrSnXzY+W7fjv7+rcaI7t4tX24bBbo1q0rk9Z1b2JYKO9Xec7XCQVlZJa1aUUxer4f6DuxMIRB+BIv/WUfBYIi6dMunrAJwr64I0ob1m6lEHMP8NtS5S217aoUFcXyWLSuSiVEH9O0Y1VFeuryIqsT13TGXcjH/jIdoY8lWeX6ystKpB2bXTxOe0yFatHSD9E7r26tD9PW9aiNVllRSh/Y5lJ+frQhMm4SL/e9EmZmZtO12Q6j3kBoDQlyP4vr7a3HN9d2nUz6lh0PYam9Jcf2WF5VRfrs28t5B4WXL1kpaLZ6zPi/17VtIAU2Y+2fxOvmM6Nwxj9rUnpvwfbdu3WYqLS2jvKE9qFPYxbv2WFWUV9GKpTVGWv+BndXyyUL/XF5E1VVBeeyztXNTXLRFftLaZVHXbjXH0C9igIRGUxWgpf+skyP64pkmnm1WdcQwWvbzEqrYWiGfhe06qs/Z0g2baf3yDZSRlU69dxkUmdAhX+aOWPT7avJ17Ug9+xZSuri+oYMvjlHZig2U36EtFYjrEEZDS/9ZTmsWryN/mp96bwtegOFj+OMSEnnWu/XvRFm1Roe3Nr/HuhVFtCU7j3LbtaFCcQxhoKCirIpWrN0kqzv1G9RZyacQ+u0fWvLrcgpUB6hTr0LKyQNPo2CAilZtpI1rSyg7rw116dtJqdJRVRGg5bVJD/tu05U8Xg8FwVBeXZpHlRXVVNg1n3L7gEHu8VJJ8Vb5jMjKy6LuPUEYK9kq77Ul4hh2KqRe/TrKPgGO6K9asJTKtlRQQac8+cH30Za0TFq7cqNcpudgKP1e6xnz959rpKDevUcBZWrve9GPKF9RQnn5bahQrBfeC+Wby2nV0iL5jOgD65Vs3kJLfltZ048Y2JXahO/l/jX7XLS2lEoWr5bHtlN4X2uN8MryalpRWtN+2Y+AHC3BDUW07LeVVFVRRR17dqB88JoJ+tJo49pSKlpVLK+FbgNqpxXUnKNAdZCWLKh5zvYe1kNeU2RFrrU1xWVUvqWC2ndpR7l9C4z9CNzXYK54pVryOvR5vdRjYBd5D2BuoLVLQ7SltIzaFbaV6w52jfTVyraU0+pFa+W9NmDfHSIbrBWlFv26vOYZke2hNrXXdyivRoQR/YhNG7dS2/xs6tS7kLz5kWdiRXWQVi6qGWyQ/QjMc5OeTsv+WkPVlQHqMqxX5Pqu9XwrXlsqP9n5OdSlT837PlibBLi6sppWbq0RCnoP7kI+LdnwysXr5b3VoXMe5VoRgSNUFYw8I9pkUo/BNSKsr1ONWBUKhWjRryukp6vop6Vr1+GaFSW0tbRM9u9EXwIOlDy2Nc8IHw3Yf6coo3/RwpXSw6Jb30LKFB5X0Ob1qzbSpjUbKbcgmwpFHw/Cpbb8+pfsW8pnxA69oyqzLP19lbymOu/Qj3Jqr++wt1nRhs1UXFpO2aI/2zVfya8l3m9LN9eIgX0HdCJv7TEWeNeX0Iq/18pnRL6vmvI61PRtvF1qPP9K1m2iDas2UmZOJnXv31nxNJbPiHU156Zn/06RfkT43GzcSmVbq6igfQ613xG8cyur5DFcu6yIPKUlsh+h8/v3DuGXzRDRn9MTvMeyjpbIokWLZHncsM0srn9RFSbM8OHDaflydwMNjAErSTzyyCNWt27drMGDB1sTJ060XnzxReuzzz6zvv32W+v999+37r77bmvMmDFWdna2dfzxx1vLli1rknaVlso3vvwXef+pT6yDe11inbb3TbbLHdz5PPlZ+M0/UdOmX/G8dfDgSdas2+ZFTfv2f39YBw+YaB29/dW26x3T/VxrVObJ1hdvfhc17YEZ71ijdrjOunHC81HT/lq40hq97dXWwb0vtaoqqqOmn3XU3dbB20y23nnp66hpz9//X+vg/ldYV4y9P2ra+pXF1sEdz5Gf9as3Rk0Xy4j9ef6BD6OmvfPU/+QxOmvvG6OmVVZUWaOyT5Gfv35dETX9pnMfk8f//ssej5o2/4MFcl+OH2F/bo4efIV1cPeLrG8/Xhg17Z6rX5TTpk98IWrawh+XWqOHXSWPhR2n/mumPMb/ffOHqGlPPvyxddDuN1iTLn46atqK5UXWAXvdZI3aeYq1sXhL1PSLxz9kjd7uGuuVJz+LmvbGs/Ot0UOuss4/5p6oaVu2VMj1is+Sv9ZETb92wnNyvY/e9V7UtP+9+7O8Vk7efartvh7e+xLr4K4XWD99/mfUtJlnPmAd6D3OuvPC6HPz05d/W6PbnW4d1vFs2/WevM8t8t743zs/R02bc+8H1kHDr5ft1lnyxyrr4B4XWwfucaPcb52zz5pj7b/fLdZrr34bNe2lF7609t/nZuuCc6Pbu7Fkq7XnUbfLz/JVxVHTL73hJWvEsTOsR174PGraO58usHY/cYZ17CWP2O7r8LEz5Oenv1ZGTbvuvret3U6eaU1/4oOoafN/XiyX2+/0WbbrPeiC+6xdx8+0Pvn+76hpdz77kZw2afYbUdN+W7xGbnP3E2ZYlVXRz4jjr3xcTn/to+hz8/gbX8lp59wUfd+sLdok2yuOxdoNm6Kmn3vj89Yex82wnnj1y6hpb7z/k9WlnccaMmRI1LTKymprn9G3ys+ff66Omj7lhletA0fcaN1/d/T1/cUnv1ujt7/WOm7faZYdR+5/q7xfv/0s+vqePX2eNWqXqdb0y56Nmrbwq7+sAz3Hyo8dp/S/QE4T7w+dJ/6fvfcAtyWryrXnymvndM4+OZ/OTWigiYKCSJPEcNXfDF4FUUxwjVwFQRSJgglFBNR7jaBXVDABEpSkZDqH031y2DmtXP8za6296x2j5qi9usHuPoc9n+d0r71WhVlVs+Yc4xvf+MYv/0X828/fkJ4PT9x2euO4c+fkWuTbjz/upfFvf/XGv0v99p63vj+6YfQHohc98eWp35YXVuPf/L53fTG9pv7Sc349/v3tv/xXqd8+9Jf/Ee/3nXtfELzWZ0/9UHTDyPOiz34oPc/+xk+8M3r6jh+JfuPFf5L67XMfvSU+7jMq3xk87vde99J43fjQuz+R+u1tv/B/4n19v3Xz17d+D5cXVlK/v+hJr4jnpvf8wftTv737t/4xvg/+Puvmn4c/5tO3/XB08s6zqd/98/S/++er2/v/339FTz/y09EPPCU8Dv3c7v/d+Jm7U7/9+i++Ox6Hfjzq9ql/vy22Bb75Cb8aPO63P/nX49/9e6Db7/3GP8Xr2KsC4/vWW07H5/T//Pun2w9+7+9FT33Cq6L3vie9Bv7ZOz8Sz99BO+LUXHTD1PPjf+dOpufZn3nOG+L7++dvel/qt/e+7V/j+/uD1/yUaUf453rbZ4+lfn/VD741tl1+/5fS4/tj7/1MvN93HPnJKNSeM/p98Xk/9S/p+fC3f/r/xGP0NS96R+q3Gz99LLaJ/L9Q8zalt22y5oiXPu+twTnCjyX/b35mKfX7T33rb0ZPP/S/one/7d9Sv73nzz4WP/MfDTyb5aW1eK70+x67JTDPfs/vxM/m7b/y16nf/u0DN8b2x//3rW8OXus3POt10dc+/TXRZz6XHt+vedP74nX59a/9+9Rvn/vUnXGfnv2osH3yPU/+9fi9+dC/fin129t+/wPRk5792ujnX/nu1G933n0++rqn/Xr8L2RH+PvztEe8LHpPwBbzc69/Nj/1rNcF5whvT/l/J+86n/r9pT/8jvj+/8nvpuee9//5f8Rzj187Qu3r3DcFfZSLra37Wvve9MrowO+/9sv6549xKdwT3XK5XHT2bLLGDA8PR3fckfiYZ86cifL5/APUu0ujPaAlchuNhnvXu97l/uIv/sJ95CMfcfM9SqpHu66++mp3ww03uOc///nuiisQzbqfyjb9wHN/25XLA654skt59ejsqUbkSuWCO3Boe0r9+8ZefvC+PZNukJS8yLkzZxdiJsjEQMVN9xgb6xUmPBPER3lLSzV36IpeVAOR0btuPtON4OybdEMqeumjYPMXlt3w6IDbQd2GTqfLBLntTJzKcOQaj/T7WtyIlN921tVOnXXT+6bc6NSwyw0l+8+fW3AzZxbcwFDF7ZhQ6vojI+7Yzd2I9oEDkxtMkHaP8uvR+non76Z2TbiJ6VEhMLY0t+JOffqWDSYI6eZxBOdz3aj6Xh+hJBPk0AF35uSsW16suZGZsxtMkPXmoxJn7pntMkGu3RdH/NiO3T2XMEGaMgVlnQkyMjEcR3DYukyQU7Go1dGHH0jRVE/O1OMIzo59U254n9x39syCmzvfZYLsugwlBvN512z6KO951ykX3aGj03F0Ov6pV7725LELbq3dcdt2jLrxyWHXBkPCMy7WmSB7e5E8an/cfmc3Un5w7+QGE2S9ctHpM/NuqdaIozfberTmdU0MzwQ5dW6xywQ5sF1wxLwQqY/A++Gzb/eEq6Csq0+TWGeCjPlx2IuWrLe1taY7NjsfB84vO9DrLx7PXccuxMyB3dNjbggME0/9Pz+/7GYXVt3wYMXtUdHuRrPl7jo1G6d5XLZ/u8vnciIV5NjpWVf3LIapETc+PCBSSBZmVtz52WU3UC25fbsmhECnj+DceVc3arfv6HZX7o3v9bSME6fnXW2+5iYnhtzU5LArkmGyUndnziy4UqngDh7cJnR//H32UV7fdl61cyPKu84cWJ8jRscH3PT2UVEWdm217s599kQ3yuvnCGh6+Bzmu754PGaw7Do87QaU1sKFk7Px+zw8PuR29qLd62lo8RzhWSTbR90Rz2JQFPcTt5x2Dc+m8ZFEMkHyzs3NLLuZ80tuYLDsdh3doTSl2+7Ynefj6z94ZDoeUxHYBidPzLq11Yab8kynySHXHE36vDS/6j7ydy9yc7WKe9Kjr3b7HvYT3ess5QQT5OCuCVdR+hueCbLs51nPBJmS43DFM0FOzXeZIAe3u44kbrnbj3XZYvt2jm8wQdZFZs+dX3QLC2tuZKTqdvbYbevvVK3WdGduOrvBBIlYEchHck7Oxswvv5+fpzfGQydyM7PLMWNsuFR0e3pMkMJKI2GC+HvYaLlDl+9whUJBiB2fuvHERpR3DKUgfVtcbbjzpxdcpVpye65KIuWeYeCv8c7bzsZMlv0HtyVssfV7eGrOrZ1ZcBM+QulZi9AfWDkz687cMxPP+QeuRend7kOPo8cxE+Sqva66zozrRbTPn5xzc8ODbnRswE0rhuCaZ9OcmIvniCOX7RQ6RV4v5djt5+IxtascxYyPjetZXY0Zi55xMLJzyu08KIWAm7WWu6fH0jl89Z7uugDGxvHlTpcJsmtsI8obH7eQj9lTnglS9kyQfRTt7kZ5PfuqsFTrMUEKzkHj5vQXu0wQv/7FTBCkDywvrLmzx2fiyPC+x12R0orybLHOQCVmn1R77/J6asNZzxabXUmYIEj9WptZcKfuOt+dIzwbkumYaw137JbTsR2xc7LihnrjcF3TKjRHrDN46rWGOznbHZNHrt7j2mcSJo1vggnyyEQY1bNU5meW3MzZRTcwUnW7D3SfTbtXacZH7U+sdcfzwct3xms314VTN590ayt1N7VzzI1PYHxXKm5pbtWdOzUXs5j2PTQZh9GJM1074vP3uNzRA27foW2u4pl2EH09e6LLuBvfNuymYpZOMkevNjvu9HFvR+TdwSmkgPaYRXfddLJrRxzc5gbWhUd76VLnT8y5xaW6Gx7vsWkgWr4yWHIn7pndmCMKczLl7Z7bz3UZpduHEiZIL13Ps0Dm/DhcW3a7e2yDdQasZ4Lc5bprprcjmAHqmUUnTsy62lrTbfOsF1Y5bLXdwtyqO39mwVVKRbdvnf3QW4v8PfRsMW/jxmwxP0dAm+j0f93iVhbW4vE9dWXCCGufOu2W51c22GJHHpOM73ZPs8ezdPJjY27PkR2xfckS2OdPzLrF1ZYbnfBMkAnXRqpuI192J+84G/sGBw8mqU6FXnrv3bec7jJBrtyzMb47w91749epmeVamAlSb7m7T3Rt/CNHd7gCtKdy5+bcidvPxGyoiXJHzBG++XfGvzvVoarbe/kusbb6d82/c77tv2yHK6mqX6dOzrrVlXqXUYp1oX38ZIpRGmKCXEolcve96ZVfkRK5x3/qZRf9PdHNr/u33nqr2759e/xe7tu3z330ox+NNUJ8O3v2rLvyyitdu8+qfFst3R5QEEQ3P4C94q0XetFlcu/vF/Ope17oivmKWR+cAkxxQ94r6a8dGuO41a1hldu6gHxaOjlKxImNIpss5VuYTfJxI6iEp3QrYJxRwK/IRVoJkUWk9UF8LQe9kQhq6jqn2hIIa59EXj4r7ehyd8jXFpoYrPLB8pNx2UrkfnMxQm5uB+Xl4n1YOg4tQiUJ5loz/zXeDkBMvhmugKKbEJ9kDmyttanAmR5fTVDvaVwWF1W+OcvdQrW+8NCrkm3ukqUoo8PJc8tTkZ55zKz0osR1qYLvIGLY6jn/8Tafk5TPHFXweTyknLSZr65SO5pjyL83NEF0dRctzprshI8ZCYWibDbOWayxrK86tALwkr44U7tE7o/tuC4KlTj35TVdXcYQwWWZZH1vWcWGVFYPVt3+4Z9zp+cjt2s85664/tW9bewqOixZTAFVURZS7dMGkMe5Iw/HMremhPFYtvq2Y0E9pg70RXQJTpY0tXQiqGUQ788yi31WA2PVqBx1FyguC+FFrW1RPHIwqJ0SLWBdUXpGlligWCcpqKuqdDiUchc6DRni1X1VzVJlP5mGwzQJincK8WtV4t3U+zLKF+vfRDULVJzoQMA2X1N6EFpPYKMzmEe0iC/GNPUQhLBrhuGcx9hv7BgJCmYLnQf/eqCyR+HCUlhofWTQrNJBHQuKLwt9CyWQLMrFUtfEl9ruQzOHumLU/BHCrFobiOMTOm1Cz2f3tL1Os3Fe4zulUltYYcdBqDa6kOildK6kMLkSBgfYSRCAz0BobajrYeUe2iYcW6z61j0n7EtUA+N6kYNtxPTc7nbQfZqDeCneaS2wzLWpPQihdYoNa30UPIPScnI/iucxhqnTo8cg3qP2TDKP5DC/cI1I9QHzQIRy0BTe7/7YvTetqHlpgSC/8StfGRDkxb900d8T3bz4qQf+1pt310N/b4Egl4gwqn8h/L8HRfPof6EixLJYxUCLtAlDhQ7wGewDVkRJLYy51XrQOc9RfEyJQFGBnAZNZ2I4WGFCOwV0AIu93Om4cULS1QrmsDAAhKAR5icks5QwheoQHS7s3mEuUqLyCxW7IRLKe6MdJgrNRtOJoURISJT001U76PywvCnvbUstxnC4WFWoMLsSrNAQH28V10NRMj4POAtUPI//vqObY+1b8eojYfVz5fDkWKIPObjtG29Pvr/6qOznAq4BUV0KoDZHIDa2JnPUWwOFTQGJaM/D5DlZuuZyAG4UP4OhpZsoRSvK4uL8CiOk407xT1vIVP3UDve/VeVOch/2Id8yPjdtEIXn5LXl8dpQ/NS38gLE6NaSEzVHymGRU+WUWcDeOqtB7x/3G++UKK3sHW0M9+qdXUA1QsWO7gFhVPcYVPF2AxVbqK8alibNI4rPijA5XQWH8+flicPR5vywI4O1yPvGYl6sGgNmke5bAdUnhGihFgeE8U2gltVycm04eS0ITPt96Ci3MK9yXSLbMa66sjMs/Ii+ZTnArV4p5PhYBzEPUSwZIpIpx7AeBphEBRbf2G+MIVYdo8Bz8YKcY7m2CGfwi7eG1ysN1vc0HLonagaBj+isKsGKc+ZEsAXPqalMOThWRY5bVhZhlSjldLPKU/ksACoAzRSo1q2D6LZ4V3H+VMUnak8QEAEIQQcg/m0aWlG0qSicfAXWL3XO9jGsmYcPBkXnPfvDFCNlVSI4X4wt8h1MgasAJ3JgrLTuOdYXyNe+NlnnC7BHyB7V1bRanG+8iFOv5dU+xXvCAE0OQ7jAtbQqF6N1JmO8TxtiqhRNVxWzGDAqnl0Iiubm5xJwIF9XpUHxHhUJXBAMVeK6HJ8U4aVgaWHnjmBVQm3jEvgQ64cCjQW4jLmLQPl9KQ9+UbatErmZ5XG32lcRCPJgao3tXrCvKqKM+R69zrcWI4nKedCI+Hoj1TzlOCAVoHR+OVxyUTn32nEPocmePhoCYeI+9ET44n2mxoKATDQrI2Gc5Fu33ZH0BZVvohacqkOKNo1JXlQtOYr67AoBZzRULFgouZhbyygzOZEAH22orOcRpUxF+GBEWmwW0WftMMExc0u5IDMnj9Ki+lk3rkgckwKYIJ09SsWf+++4Olj6tb0N9er3TZjRGhonnUIS4eqgSkj32MNBoMBiMTSHVYSosLmgla54RlZGxyBH0dHX70oRrAQ6s4KFgHc9Pg9TG7Adjf/SGYxVXdUBFXpMh6Ojxh3HNyLvOYBynW2oVqQiwHSoC8uogAImTFulbNQmWWK2HKz0YoJAqs+yZUR36EweAtDsL+cf/2/vuM4tPLLnEKtxwueW64wZz8l+ntYYlAwTNYbW2sGxXgTYo8ubWu8E539R3UZHx1kmuWKUwIYjF/ebTBDMayU60FwLCCYrxgmrHXBe163AqiuYL7kucO2IdHW18tGgk8N3hQ5K/DcAcYuJEqHiRnxsrCWsvENWSB7RbVbciBuZbwwikD2jHO3OcVQVuuJgGERhOeddEuxhWfTiSri8NSuzxMeDfcIoemdyOAy6p5w0jHWyRO9SZW3ZuE4ToCLwhCo2rfMXzEovYh48mzidmrjMSi1tlthlJT82VUVHVKhjIAl2iihpG3e8HZ6jtyXnjDBu9RxdZOUbF14jNNO4A9CTzjkZOwRbivPSNmyPwQaA3SfGt57HCa6yhDPA2AjC4MUkbtI9D8utw1bjeCpzDGrQFsG8ghfMDti0mgkS4TrrkxVzXhb9xLpf2J2Mp9Icxsqp80GmWKqqH5hBne2JrRapoGcb9n4RgbH8eVSJhA262fx7UbctEMRsX/u1X3t/PomvyrYFghit9Lk7XDFXdtGR/X3RR+l4e+X/9dZCNJVOZgtUvfjYmCPzmMhJC+WCF/+GRYJGVBGoORXkBaDi90H6AdkrDhGBQtVmOBTJ6qAzd+ZckLmQopKCecCSdCxDmyo7dsWhcDlMRsUQPdXpMUWUoxRoPCOryqguHjwQNOiaqJyjF9nW3pFgpL0xVgqzG1R5OIILOXhsbZYtVY4hoyjMqxfXpdIS2AowsKORpJ8Dp6RB1ZiohumjcOY6YIVwDHf7CRACRpAw1JQzSKOejqqVsiKi6+q+WYyA9riaDnl/RSnf5NhroOtrJgmZKQJsySj/K06PSxB0XhdOOfGtNQjHbC18z3QTY41THB0OsLb0dRIsaeNYmnFipsNouv/6n5FzQyfWgk4e0/84L5P1lEqFIF0dTq9gWgH01SkfObIKCGKDkZfPSDlkOqJ4J/hZZ7jRIb/7VLAvhX0qbxz3hmzBVDrkxvcqFXD7WJguDxZgp1ehIgR8MGXRHdgdXH90X8Q7DedBsO1UGVcyU/JVpM0Q+FDRVHEMOJ1tVDgqwElMOVlg7+VPng8+wxac8VTJ3c8kKYdkmRZmmTIiwUPxDJbXwmNQaQ54jaSNPlsplGRVKjp6hOtm6m6EyncM/KTmbDC38qfOBdOgCorJ6BbBMJxGehBABJ0enDs7l9KH6J5nOPxOK8cyh+tmuVsB/gHoiPvGcspMvaIGFOakwoqa35iyx+ekyxSznwBYioINC6Abz4xspnh/2Aad0eSaC+cTwDFCKkf8N9m5eJ60u1qPvMIsmdwaLGy6/uQ6atwi3UowjXjNtIlPSSCtszdJQyrBniJLVbMvCSzmEUwTKVncQTFJ8poVvr7P7UnVjtwuqd/mGOfjOkXWF9eoeAnu9iLvI0RGdfCtduk0ny7Ub7uUUoDu77YFghitfc1hl/NMEFKlqdOgHFgxyQPRqNwBITEsuAUatxpEoaYHIna5JSmoJSPKiHDNh+u7a/ZJDotmznBY2qS1KmekY7x4eRgdWfm4zsiZzNNZiXPBL4SBD6aGgBarIxp5MFs602EDO68Wthyo29SXYD4qDYvCokbpwfhAn6sYT9oRoEFSWKkGnYdCDQaAiqKI2vMQEKycT55HA5GO+HgA1uqT6DPG99ouKbzI1gagUJ8MGwN0jDUg0MYuBDQ0QGT9FvUJDmSlymwcVxlqQtODzIE2HH2yBdQrVFrtBJ1+Ao6aYSHSrdbCuheVmZqpLURAgXMXDdT8qhqrGIfM82+D3ly9gHQDxSRhpLoKg1JQnXWqEce+ATb51ugxWKJtkqotUo9wzdEesiD0HD0R3F8Ag4fGbe0VGKhkmfD6CUTq6xGaP3geXvxz41gj8joLiOI7OCXCQFdMDjpjIu2IKRf8flHuHyEaK/qM0p45ZfjnGSDgHAnHlvukNCx4PWBbkNVIRl93n2Ywal3ctzvMhFQt4tpIij6cRO3Y8f2KoOPBdUlHiqPd24OpKZzX27jnGgD2QqmhAEUeDEE9DxI44f55psOwKdsgv5Q8gzI+E6DR4vBMdREBF6Qx8bnr/SnmyrWZgIwG1Mlo6tBRJ3BEBhSYmHHD86D+DG211t2yBKXQAQHDgQEnjgcGeHxrPyxJpykwlS9D/03YCh0wHDD3EPj3Zc/ZCtQlw/qZY+q0Bo0JgnNe8yK2IfBSrfMM/gitJs4p2gY6txgOzNGmA8tIA0e01XidBFS0Rgvnb4egX2ERgCO0fDTzrrADAAcB/b07gtop8aUBaBVaOADptBaN6/2d88bIpQSCbDFBgm18fDyV/me1LU2Q+962QBCjNUdKLiqWXFlUeOiYDmhjajA84dKZpjgV6X06SsjcaTr9zBeMqX9DYYNf5zz2WkcZABEWMwo8mpEjFYFl1FIYLcxHBtujew3NYHSZbI08Uwf8/bzyaFj4sZgsgC0oyGvnJ1/B86ARSHBDCaMy4kaNFQINzIElu0ELkAqdAWM86f7kIOYa7UCUch7jRkW1GvsTIKh8BgARRFsLKzalsggGEx3TxqjK24VxIdNUwtFHndoi9BCMtITWgDLqcavaFDPlWGWKgDLIivWwVgZbpDoq9Epog9K3zxLlxuMhM0eko2hdaop0aoc6AHzktYYExiG3Ky7V7eg2+ybGNA3cvD0nYB8CH3weLeXw+GovG/vD0fT3+Z9+cdhNlJfcXGPYvfBj+ZSwXndDg0VHA185hmJM4KNmtmxsop5tEUAWx3cBAJVOf6HTzGgkn20dlShKCkwVrADcT8F4UQxFOvcUyaYmh5hrdIoBo6ucI6n1hDSElOAn9RCgb5E7uj+c5uPHx87xsKPPtZBpMr4xUsq5MANs0SzBje+ZCsj5Wr+DnAfIsoGTU9S6FWTAkDEyBnAD46Y1XOqL4UeGBCPo3Y6TSchrg5NH8W8VddbMkOAYVM8wokYZQAjqOYjvlZlCUISAgGADKaeZYH9hfiX43giR0AxRTIJa7S/dGhRPjbfrVYtJaaQhTaSxNxnPRfRR90f0H2CTFikV6ZR4vxuHp8NpHWruE6Cz0MHCu6bSuAkiCPuGdjDGXepdYR86FqAjd2nthq2DOU68t0y70uxLxbDe+B7Xpu0RsWawqAEZ0bxmsn/iLwyGHUFOLRpbGgymq1FrqaPSwtdTtNrRJZYW4x9Iyki8D8e4hPVAjh075n7+53/ePe95z3OPe9zj4u8+9rGPuT/6oz9yr351Vzx+q13kIIgvj+vL5d5xxx3uZ37mZ9zk5KT79Kc/7Xbs2OH27EEKw/3UvEPn/7WYq4vWGtLVQJLP9QkYJ9uRvwgDJuWo429GjUk5zW1XivpCzwCLBMEOOlXMZ/Z/wwiKMOGSIqp1RCKAFblzYdFXGsSaGsxWZHQaKTDRNhXxO5GwaVhyV9Aib0cFmT1KiLNXlk9TkNkEzdg3RtQh3Mg89DKMIVaNiXdnNNUQjqxDqyM+xjSvLbfpXK/ZDe1K8vfatqlNNTS6nQuPSR475SQa640U8gyLQPpWoPZXzhAPHVTGLg1mHLok2BLJ5/KSAqVWW2HDjcYNIz/asSKtHk7W2iGpsWLRgVtIxymCRZBeu6Mg+EQmikizUUPLEkPtFDMi4oXNwQULKEhtVwifX+8vKgTwGnLO7ZjIu+mqc+W1/Ab4oQEJod1BAVpqOCk2URlGOiOlBGTyeDYEN+K/waAR8zdT8TTtmwADnTHMXUIkOyO6zooXrEam6fo5Vh3ZGRaO7ECvRgDb/u+DO4KOTR5zXITKYNp4F/MtUwmZDkrQQ6V6CkcZwFFHaYIwbZLihHlUFxOsyPhHvDtN0tABGHItVUCzcJqZdsqhQj0M5adR/JOaAw2kmVjgZ+o8aFpgMsfotjXH79lupycRUKbOEEDXFhgz8W9gpuShayaAB131BC0/g9QMgl9IVY0mJfuUulq8t2RsiuundljqGRo3d1iBGNR8oT4GRU55n5UNWdAV2gIBr/YuySYqnMbYx7tbvi2xrzoIlmjRWepg5c8jwIL+a/0bMrKE2DH2ERoeIxlirBBDF+dIsfVw3waS+aYIfSvxDiKQp99vapFlapexOgyAmzKCQuLZqtQWwT5phOcxrTcmRbLRHzBbfGUQsUsWq3qrXdJ6IK985SvdG9/4Rvdd3/VdG9895znPcQ95yEPcW9/6Vvfc5z73Aerlxd8eFCDI5z//effUpz41rgzjEa/nP//5MQjyN3/zN+7uu+92f/zHf3y/92ng/V9wxVzJ5alIj88FVTOcERqmzbThCLGlKiwIhyNMA2SUtnseRvNKwWMX4Px1xnV0J4nm5ZvbwzR6tTAyklWsg+ZK8TNQRCmYF/cNwIFoqtqAGWVEo0BkDsBJSjxt10OTffosN8uScq4wFlzwGAHXizzHA5+ncPq1AdCHGLisHqIqbhjACVtpVYFvuO7SQphjqfvFCI2gsYO90qE4r07DuvxgUMW+MZV8HrpZieOS3nw2MQhrDzsYBCYbI/J5rO4IR4IEuFDJyKtk1ouoaGPvYu2f69j6GqLxN2NsEFDSx8vB9qY+hwYUCF4xvUcYpEh7SgG4rFaDMVhaI0NC9Ru/sbSm1xzKPSGKs8m8Mzj+2ZkgdZ7zEp14UsJT4CPe3fJ8I5yeBJYOQY+4a2DQkBmTJbonKOIiNQYgDj8rYznXRpoHDXGW8t2hRBTpmFBLhyAE0p7086QzS22DHIW4tX4BK60A+IhYcYJrmYqMtofIlgDLBo5I8SgAFf83xAoFc4FpozryT8FKONod3CeOVa3dxf4QECicAHtGMRkp9N0Z2xl04Cmum2ZfFsNsASEWWTLHgEzhhPgnx7MCUcSahbWsBa2oFNtuFe/OwHT4PRIOo6oQtGsy/E5OJfZEkaKe8TFIEYTdc24uPAa0bWCUqBXsD6UXxsBOcXcScOnsS2yo0qn5MNCinwfGkEjnUcxSK+3HeoYpW5EBE6QMioCbYhUKRhPYJ9TuImupOWKPIQZoBICtXpXiCoAHPloCcQxoKGYX05ILq0ZanwIXCNbw/WITTBStFUUmHt79XI1aUYplw3mVzxoVgjTDZB3ozXujQ8VrLubmGcCWQP69Ocal3Dzr4/d+7/dS3z/qUY9yP/RDP/SA9OlSaQ8KEOQlL3lJTPN57Wtf60YgIvaMZzzDffd3f/cD0qdOs+U6uZwEQbgoKIdTAB9wGJoD9EqSjy0lzlhaQcSNgoiapspmVDWgk9OGQjaNBJ3+QKM4TzV60Oh9K2ABINVYLBLUSdCRH4IgjFii7JimWosyi6BXRxTQgzHT2D5oC34OGg6TMjxl9YdmmF7N9A0FdvF5iDKuMAaYDqT30Y5qmF6vFknc9/oYnFYr6qD2yTeKQWdQ6980mJuPYw9CeyWHakNakLcOYdU23g+yJdwO+QwpwNqB6BuBjyZEQVOCqQQxKKXD7XQQn2CHSBfD59y9X5jFSMsCQYzHJtKGFKaYo03I6xRCu3Ifi7FhpzTplA/qtYgj24AfBX5nYNQurm3QxaNWy7Vuvi2Vhx/vg0kyDxp+ExF17cDS2C1iPIn0DYK+Km1IVJdRuigbh0ppn4THVySqMuEdVMclMyXfAHCRUdWhhYgswVlWeSLYEnGN0ikXuGfl1eS97agc9xz0RkQKDddFUV3NRg8FKMP0LFVqtLB9Mgh8kJWX0p1A35gupsdKsr38kxohHXSnwPx9HZ1GRRIyNnmdhQVbG6IITSwh5o3jigpq8Zs3HDyeSLs1gPqs4I3QMFL3RlQaAzDKSnoiraIkn6eVLmYx9zIbGTwUSVVBmQ5YS/md0+HtFJgqqsXgt8KFpTDYw5TmGLhB2s7UaFCHhf2KG5ideYILEN4XTBzFJmpMhEE+CdLKZ146h7FGgWdDA6lTUO8Qs2GoSyqCfEqHizYAFiqW2GXwimKwcZ/JeMH9aLEai2LiRND4EsAi08WZ0qWDTRxrHDdMHTsNwFYxih3s3Qh6eB1UAer2s3ttnUsuHSZte92nY1zCbd++fTEI8oY3vEF8//u///vxb1vtIgdBPvWpT8UPUzefBnPmTEZJtv/G1njada5TqroWjMXyzJqJQNNhqNyVRH7WjfhUSb7rknKmvhXOzIZLkJEOrCq1CMVrrh2M4Bp91Aay0Fwgw2FQGlcUBBSRAzjDxbtQ6eWA1AQRgn6kn44luh86BYnCog7sj+ZEJegg6BKgEULiNKhENFftI5xuGNKkWApjQAEFonXCgp0suakFL1mhIEXJNgy61smkesTII65J+kbmhnKYqBPTAlOI1VR0hIdADgLVbmkvomIlGwygIS0ABT6CnP0MRbNACC21wb+N9I3UIYzfRCoHUzE0cMXsB8qtZAEfFkOjBoeJQvmqjKsAG/CxvJAcrDQvw0i1nQQOwhddXG3bZWCp0SIcKwP8Uyk99atQ5rI05t758XZ8v/w4mf2hx/fOIfsj06hcGPDLeiV3Fze9Z/p5CoBHiKSGU3NSEXWRF8HjRmYJ1CJYMibjRJeDhm5QEbIPZDuQLk+Gi2/lk/Nh8ekpVOy4R67LHaSA5CEwmUPVsPwaUibbcl2RjlkhmA5amFGpLdSSYTqiqGpko5SMKItrgYaSFnuUYGIumN4j1rV4p/Ege7ABHSqu2U0FEOXbo+HIvabYo4k0JgpEwtEunVgOBiF8K1+Gkr9Ga4+odE6up4afy8p5+j4JgIkaRHinm5MS9RWsIaHFBvFQAUpJPYc8QAj2Jg99kbZi/QqAgxpMcLTJXMiqyMZ3uriSXFtVj1swB1oTybtTB3uyVc3Zc7T1PLB+kLnnW2PHSFgrA0AaGUzlRSVyimdNm5KpqRqQyJ022F0EogAEFih663/anbxrzVFUOELAKNqp0riYQrkjubdlMGNZxtbNK70WlvFGuhbHaloTJHkg1XPJelwAIzqvRJmjle52eT9ZhjOqttol2n7jN37D/Y//8T/cP/3TP7nHPvax8Xcf//jHY/mId7/73Q909y7q9qAAQarVarAc0C233OK2b4di9/3Y6qN51y7lXXENxvrYiKmzIOh+ByF0d40qAxeg/fkW7dwTpGqTSlo8LcsSFi7MpFBinStdvuKoabQULoCmOzm8Kf02Je7K30gRRBm8PHNZVY46qdoFGPuaxk4nvoMShcwTFYvULpnWUJxDhAUACyMnmiJZnAdwANQ+Xx8MV1hQ5YtpKHVuvF3+tr7JNZeJv+mkNHYm97AlqOLOjN41v/ZA0Lhhmocet6ICCm8BHVgtYJff3Liyvg/9Hfo+VTWFl5rbHITQTBqmjTBKSUCjCKDBtybEWdk3Hks4wCr6Jq8nnBahdV3oaEuj1gUZL+3xnJ0uhXuwtB9GOcTw9LFNUIkDQj8/7hNtDjylflPfv/GPa+70nHO7Jmpu+/f3vs8QoI1YmMRI7dF945jmGOA+GngpLyD9geD4OVRAARsqPs/dSUQ3ajWDgDjZhrkpsBviEzE3g0iajfB0KMRIZ4qVTahJAm0KLeqYr4+ExTcVACsaeOwRKn60xiBWqVmJC2CRLcA5h5OaEjkV4BXeaQQotAZEe3IkKLhJAVldKlScE6xEwcTYPhXUzdJNCIjDmSS4rlNlOXd0AJAIwDJDYFmmUCb9L88j2HKZsrN4a5k2ir6VVFWhwgW+B2tBEF/cM8X4LEMTxBK31SwZkRYH4IQMCYpH6zUzog0Ch14AHYp9IqrgwAEmwCM0WvScagCgIkAD1pTuAyv8lBbDFEXNhGQ6ZHG5HWaPKMaKSNuhbsZx2J1Ifa4qoVzaMLzvazuqJiCRu2wsDE4IxirYJyp4VR8PM0Npn+sgRLFGIC2cQkRQqqCYrQIIGx8Igno6CCDGKmzSXBOBvUjqjeV6Yy3faTgniSVb7RJvz3zmM91tt93m3vKWt7ibbropTvn/pm/6JvfCF75wiwlyKYAg/mF64Ze//Mu/jP/2ZYHuueeeWA3Xo18PZOOEWQJwoVMRhCENx0g4T4jiDHz+uAkO5OdA7SXtWNFs2w85ElzAaGCTRagFumq7dhhOJqITSJPRNOZ8YzDsTCJ9pKSiPRQ/c/nE2K4jGq2NQC4mNHpoaDTGsWAoe7C5PzHESyjblhc56rp6BejEhnYIKab5unIssejndzxs43MRtesLd6N8cuwMjYSrTyzD8GaUUpcqLSTPqojyrCXgQ81hzepAn+kviceuovj8zajuktUEiMIf+tTHsFJQ6AfornSoOWtE5nRFGkHh7YQdaOJDIpVCXacAWCIbeCH4U50NV+thCpEHa9kkEIQIKoRmU0AYCz4ZgIgWL2WTOjc4VpaYqqWxoin2678V+tufaYqpssgEpQymUpOpPcpRj0AXL9QxD1VHzeouue2gu1Pwk/PYJ7+Q7DArHfAiQOzoLCzfQ3uDWjzxeUCpZunwAlJWhKj1kGRluAka8nDAMfcUp6UOCauLiH2oTcGoPXVgfH+g79GaAXC+m3Onytdn2c06vBesf51z0lsolPaHnXOUdW8vJPez8NCr5DkBqrD0agui5aLkpgJHmXbKtZROK8HPuG8FA9jLAH3N1EwBToMhwvQwNT4FOMB34tZEjDw+3iACBLswPkQ55yGb4VgGExGiqxx3KeFh9plC63CUyZhN7c+ACwMXCLakBFO5nZFeK+ZEsGe7/cH9EIA8AhcAZ1JpJwZTiexN7ehbemEcA1r/LU9Rfswd7Z2o4HJ61hQurixNBUtV1/crPSH2RwhOh3WTpDCqAsVEWftw4CHNTMWcnzdYZIJhqNZsxaQLvt9qTuD6I/uZs8fdOgDbZ0bYxdL8FX/ZmiDu0m979+51v/qrv/pAd+OSaw8KEOT1r399jHRNT0+7tbW1WBXXp8H4UkAP2EPP5eKFg4sJqzWkkF1GaocsnQE4L+OKbopdSsvDQaNaR+zImGCqTPECaMNgiBQUxbI0EM6lJ/uEeZXx3zCQWW5VqMnDMGizvKxyBFgtoARwQCub83gFsD9I+SUgoEXByheSBTwvKjwg8lJUOiLLiNgJQcKk/wMw5GkM6f0Z2awfSYCnxsNlLl8Lzm2qJOhGP5l6IH8TQnVT4UiUZnVYaRpWSVh9PDG+8b2IqGgB97ZVwQSHVfuIfhupEMUVG1yg81C9ACAKUcK1HRLIImhJY7M2kXSuRiZGBvXeure6EWxgWoCZTqRncNpwHaMkrOqmydgw2Dep/dlnZuhlOWmirK0t9Fqdj4LfMzLIajsDJxGNvu0esU9ER/nay8LReWgOtecV824S1RegixMhpaypxKeb4xy45eD73fnWx8iL4zl5nXuTKGn5/KpZSYJpgmQLiHF3+YQdNcY5+Q6Qxi7YJqoJHRA4oPWJZI6sbVMT0RFUglg7HJzXywr0pV5Vrj0YdCraByXDoWWkXHQuZ6WUZP8yQPO4gc3COV6wNJECFP+JFM7q7SeT82yjEGjysT0qmSSWiG2WpgfHl5WSxbTRxqim6/M+AYTHaYqHE8FxLXZMp7U8S7sFIBC0neJr45wA4CXP7yEmG+9jsCeEM00GUkblHYqe5w2NG800ylfCQHWRwS9Vlr4NMVGmewkQJyPdmr9VaKsxoqFa5R6MTwaVyHipy0mWQJBV/rh2RZLu3HykrOLYGA4D77Ksvewnx01pBZ8R1LHsPh38IduNWBevWdsKPI8Ar7j+KTYSmSBFpJoSPKROU3wMai2dWgo/AxUM3GDfeSbIpdS2SuQGmycC7N8P0H6TdvLkyQekkurF3h4UIMjo6Kj76Ec/6j7wgQ/EZXE7nY57xCMeEVeMeaBadabpisWCjGqJCLLyZGjUGsKLXOQbw5oGzwkPkYI2NShkxM6KijT2jG2OpseCawkro3xmKaxQTeXr2ChMHPo2hUkvJNGzHOjArLXevYZCMO+WqSAUiYv3waItaMtQSXdgzJDi2d0H3jEBFoqf6tKUWOhF9QnQbFnfvYMoVvz3VGKUt/YgtQUR+ZRGCyKAVuSdDrBIsVDAgeV0Z1WgKdSM6KOOztPRbYSNifIyjRHlZMG4qJ6vBZ9zfVI6SY0RGDSkqc4nx6rMNoIOl2/NoWT/hSPI3cZp2qp4Ug43W2oW3HuRVAtEuC/smcwqQuFpRIAOqWo/Ir3nPgA37c0rEZEdp8cHnafq8Xl3en3TyLmR441UuoCeV1kJqH5VwrxoP+xau8+R0f/c9r7SfuQ+2CXjXbGiscLwV9WbIkQmyTRqTg70JRZJQ17MPWSq6XUB+i+VE0iZRHQ+VU6a4ALYH5xVi2uspqUjo7kgcMO+pC+OTlYYjNRAohUppiAjnTfdT+GoY46qYo0orKoyrOhD45r9YeYYu6+eB6sniVKnAO94z1O6YFhb2xCAFeK4OlINL144k3RmNXiGeZlC7w2MVTGnqHOK/uN953pBJmT3iyjodHYAvnGd1uLwdDqZKmWlV6WquOBZFxG5Z+qx1j4pzawG7QxWXdHvV2ekGuwbU8wqJxbM1OfVy6fCuk0EtdS7xnQUAgd8b+pjKI2N9BNtz8h5EOfQGp/8u4+1UVT50il7ZG9awsdaAwloSXtbuFpcqnIPS6SDKRaVARSruV+A2HjuBWrrXpAg/Ma8lhFs2WqXTrv++uvjMri+WuqjH/3o4DYLCwtxBsWb3/xm98M//MPux3/8x+/3fl7s7UEBgqy3pzzlKfG/B0Ornl52RT9DY9FsgS2RFzkB0jHjItMc3LzyQqpELiP3MM74WRsHNAKJhgshtxRoAocBVM58E2CLZo/ccyFcGgy50rll5P3q6jBU9t4xFoyq6Ub2BlW6CbDQ0KAzraOW1DthFKGEfOZuh4y0E9yP+u7RDKMeBnoxPE4024ERcSkSio/CmdVsh/B5hBCaMjroAFUWwsCFduyYJlBagsN0OnGY2tBByVPgzN+3r0lEgZf3DQbTUWhE+zZyN0pDwlBZOpjsv3JlYkykgmK5zRknOk3E3L8vDQ3FyrC0MrJOSYfLMA5TJXKNsUJwQ2tlDMx0gpFvznZNmBYAAQAASURBVFF0TDW9WxjLFPqDsJx2XupTyXu8tj15IIsHpp1b1/nKOTd7ZSXIerJaJkBkAVEG4JhVSpi/iapOWpqB7ytp3IYjQAHbFEOO4oS4n4wmp/7GOZtwmLLK+pbhpDmC1sz5V2w9M+URNPgBgNFa86A+jbUV40mI+OqsBJajNBwDPWzycFpZnjvf4pZFMzVFVvCCbTBsl5tla4yV+kqBEeeMWAEE4CHWaf1OUnSbkXM6X8LRVwyJPK6nzUovsEH0fGm9ewJ4IpNR3SbejzxTf5m2qmwg+e7yBce7pjQcxDkRoResV67/o6rELQEB41kLsWH1aKWQNAI8TD/RmiAsbQzArTmSXFtzeNIUYxX6UgYAmlMGiRDepTQRwFSZpmIzLMT8nbF+ERwvz5O1C4YGx6qyaVtjsA8NwFPPfY2J6eC4KS9SL4Wle3Xaa3JxbYihspx0SzHHCerTjmcrzgER8dcz1wVFOtGlxgTpD/Da9BiXWPPaH7/2a7/mnv70p7tSqRSXw929e3esoTk3N+duvPFG96UvfSn+/nWve11cTXWrXaQgyG/+5m8Gv/eGjX/gR48edU960pNcgdVV/pvbwtXjrliqiggmF5JUtQMuOkYVACHiCMMiZRRTbJHK7jCAfKucXQ4bAAAnRHk8g14f744OZBlx9cPTYSonDY02oiAqf5JlCSWdl2ruA6awKYEHLnJcSHT5RRrVpHTTmGE6kP5NMEt4Obi2wVlVO57RQBoQE4Mm24EGnhVBFsaEjjqLaKgzmElyHxourEpgVm1RxisNp9w1SR54/uu22cwDaubwncBtXp2Wz3BpP+juRtoNnfnKnHIm//k/Nz63n/zIjc8NRLLWthVMI46YJyNerWp/gIiwL0UZgox9BGga/j4F3BjOvSilq4zVNaROFZph9ksme8VwfgoNOpkZaR5ryefhk83kHYsit/13/iNYIpeK/I19ifHfBK2fOijx4UjDpvFsgCMaMNRzfnJcZ7Z+mCCtStKX+mTR1g+IwlHblgIZRZWOfJgNJfLglSPRHkjSFKpn14KMgIISkhZrSzQQTNMkAKBBY1k6PLkHJbB8qMkV9wGOviUYrdkGEZh8vLcEjbXel9hfjPUoGIHWAsnUWqjM1MPOKPfRZcwZXYYNJJ6zcuxYjaLDimbbETiAbaHBBcHMEQ60M99pspZ4bFFFDu86Bb+1TUQHnMdKsQqxNtNRFjogZPTp1BaWx8Y+olyvqsJDEXRt34RAC213NVFFhhVUhO6HSrlweMUJgJbnGkbVMiXmCrYYA0FZ4IBkEQOYZKEWzLd6XWgawt4iPVcFK0RVOoCUDIpw7tbPRthKfKdZHlzZ3uUlVKBidS6ONXFcNW4hVFuoIwiANCimtKXAJwI8FNhHYDH+rafhl+/UnZNyPBd32wJBgm1ycjKWinjVq17l3vve97qPfOQj7tixY7FkxLZt29z3fM/3uBtuuMFde63NeN1qFwkI4sv/nD9/3q2urrqJiYlY+XZ+ft4NDg664eFhd+7cOXf48GH3wQ9+8H5TwvWTbrHUEZOqKcYXGzp9iAvCFmhXM6pCQM20DQM5r4yzfCMxNlug+9HRl9uraNH5xaBeCMumMk1FC4jmRXSCpXzBsDgnyxoWsNA2JqrBxaejnQ2WZENklAwNGoQsb9vdEPfQyAlOGVekPBIQQTS0eGbVpE62mQ6DBZAGtha1TAk5BvuZfO7oqi0Fw/nq04FlRDoz/UHoTmzONtDOZAVVNujY0Nhd2a3SYRB9Yd/IXmH1Dg2ErTz3cUHGCVNgtEGWa+c2v7cZM6iVHmNV0UlvaHzNIdwn84Hzi3ZemNJUXmb0DvepnLE/jEq+R0xV0lTrwVsTRlnneKKT0HziQ9D/nFv+zsemUhR0M+9hShyQfxmABgE2HXAjo8oQm9TNzH83Ilc6bYisPtFl22d2BcyRIjUEIoLEMHQkkjpUeehusFy705Rwg4lBhl9ZzMPSKaDeFm+OiMbqkrA4nninsF5o9qOohkHAD2BomwyJTsb8S1YDHNPUGoPjUUyb48YspRz3AU4zHbi2XW69DFCeTrdmDyadzvX1rnAebKfAv82BJBH40E43AQkykHhpqv8EOFhGnGzQHCoZqcrrAqQTDFLeD40NsJoHHVgCMgANtB4E7TOhf0aCg3KahagwxzA1UQwtHq3BI1lw1OBQYI9Il3JBViCB1ZSgr5ECY1YQywgUCsYJmajK1uM7Wb4Z4s8AlVq3yGp9+UdckxyaadmYuzoDdrp2G4EtPs/6VHVTADw+HuaLAp+z2i535sKlqQmy1TKbJwJ867d+a/xvq12iIIin/Lz1rW91b3vb29yRI92KJ7fffnuc4/SCF7zAPeEJT3Df+Z3f6V784he7d73rXfdLn7whGGuCsJRVCeKjtYzouDBuwp9TBjoBEiw4BRoWalYkk0AaZIgwwRnNqcp9uc5w0Nglsk0AIt5HKPLDWGZeOhaS3JJMM6HxXaThiGNpJgqjKgQninPYB8Jdov8qqsLITa6VEcLl9eAeiMjJxFBQjFBHHmjg04HWFEnptMIgFNEa11ezSspq58sSryxQ7FKn7RD4wHpMI2roZN0UqmWrQbujCZ2cEpxx36pzzBfDR9zPxUOkmsvz0IkXgGWpz3QYNJMlow06w98QwcN+02mMdLlChmSCcNqbNohRWUg2HEBFGhEdZwlwtX8Jmh4cK0XxvbzQxYcnAsHtR0Ms2AOD/5VstzrdvcEq+9BOewkTPPRPpugrHRENcPG6o7Yxx+r3ixE/kRrjggKA1EfpHjv8gEWKmwKYZBUWpJF1BsOpgGDapQBt6IAIbSadWilYS+HSrXSAS4tK4BIvqJXCqcUiqacg5usxW48hB1YCQXzBhCBwpKsSGemI7HMTNHjfaEMQzJMVp2wQhI1ANQGzSKU/sG9c84qLtXAFkqzUSgRissAaK92XgEhWGpbQGOFHpqFpEIf9wf4FAg0YA7QTUmlliNy34dxnpee2xrDuU1gV95kBKt8qAKjIroowBlPXaTBOatMse4YxqJhWjVEapdilhbGuxlBpJQzgipQoC+jQIB9tG0MUW/8t5k4xj4bTCvXzXL0SaS5M7bzGFqLm+C4j4FeZwXuDMrjdndiffDBVSQPltCEq1KxlqpXWqVuvvpRSqr+4mx9bX3Z1mEswHWarfRWBIL/4i7/o3v3ud28AIL75FBhPBfIlcu+880732te+9n4tlzt/2YArlKuuBPqmqMqgJ1+mgGKSF0J3+DhyQqK5LUy4jOpUTi6aBkRngCkk4SgGmRvaGV3dkxjF7TJL1Gak7ZBG3RwIOjyMhEUTEBtTQl4icrFt0Iz4MV+c1Nr6JFNjnLmYC+q9UA8PX1e/EyxBjKxzshoJ72fluCyHWTs4GXR+aETJsmuyPzSwqxy3jOLoaE3eKJebxTgx7MO17ckPS/shhpfh6FvObGev6qfx7gkmCgI0mn1SXAszVoqMvKvnzPtG44wOeX2M1l34WuJ91D00x1YUvu9WakxL2WNWlE1sp/pZ25ZcwyKs2r7TYSjkTCfR0NDIAmU0uDx0uhNMbyLoympWjfFKMNVJN6GLwspWAAdYdca3umAruLC4rpoHxDM07iFFsotreh4pBudYqesiJwJRNvPAgCFUCAfngByc5UVGWtvBdakDscvuFxx4dIDDYqiMIMfboQsi7aeG1JgVeZ0l0NiprSDmtIzUFuo2EeQTKW6qcRyTNVVehECmAniYAlpkmj/uEyu/5U7Lsr4sYdzaNR4EW/T6tYpKV6JSzF6kGEB/QTNTBUDP9IWSnUbFtDayi8gsIiCkBWAt3Qem9qTYQBQJJeNSrJklm2Uj2L3lYF906VgCH7yeOs7Z2Tlga5+Uw3YTgUmt8cL5jvoznG/JLNXjYeR48gzKM2thIFGluLWhSyIYFrPJSWvTFGyV+7NKIn9qETdS6yLnLr6fnLtERbltco4XOlbCPjO7KWx0AtK0nWs7B4Ns5O5FYC7FPDhwrm6LVxMwg6CvTCtUC+16ME+lOl30bSsdZqt9tYMgp0+fdi2InK03/50vleubF4RZWpJCQfcHOmmltmhldJFXTsooI6gwoFZ3aLEtfCaeQTFW5I92j9cOlo7roFJKDqk1qZJb6LRG5De2UPuYudf0BWGoEPTo/oZcWRqu4gbqkDp+MtgSbSyY1rXo/meJKTECaVUeECwK1WfhnFPo7zzSgyj+pinhyIuXQAUdmQy2gxBfc+Y+FkCRGeEJM9dNun8W5VV8zmBIIPAufsrXw0BHEfp/vhHMtICwlCaIAYA2AHy0ICWTFcG1cqKz2CMWCGGyGNTfYkjys7bHDOCCYImgkes+W5og9f5ScGiEDsy03eHpvJsYbLvJ4bwr9IRCm8OqykcelOx9lbCxjbSnbkcNgMa454yShoDOUEu9X1b1IJG/H+5LSj8nCq8/OtWITAwBNokUOTvlg8BHGQ6sEM9WRr3QW8FvXH/oGKc0tZgKGBnPSTnNlmYBgawsoVwRUWYElimwes2kDSAqpSA6roU4cTyhg0FhVeiw5HZKfaryPJwpgANVlNZMRY23Mx2zsGnKZVr8evPy5Pp9YGphHhM2QfysdJhcRnpPspMdlGGaiEynCVeES41pMEYYbMmpanMEQUTKCBlEZQKJio1EFhjAs/okNZRsTY+cCEQhHRR6xKlqJGCfCF22Eio+UbtF30MDhBGppeqdNu0Ormt9+vO5PtMHha1FdlYGs6cy3w4DqwTsyCDWU4KY7zjHFYJAvRbUZco5Sz4LgCresHdiK6Vtq221rXZxgiBPfvKT49QXnw5z3XXXxd995jOfcT/yIz+yUS3mC1/4gjt06ND9jk5ywmuLBVxublYv4HxVyKjqIMQOw9Rc3fKgOosyXazIgiiKNjos4CUTHOhsHpEXhopKwiVdUVRQoRGtqrsI2jEWj1Q6yfo22gaFMyPFWLOAl82NYlFqTt1bMj6KC3hOiPJFe5I0gCwnS0RHjPLL3e2Cu2cLo1rDy2AexH9bTrhB99dNMI0sfYss4yjaHFAh6NHdJwqW22W0qiFJS8LAE0DUgFFWV99Lw7lm0/dJ4BbGOyneuz7vcyYoRSbG2uZVdFIgiOHEl1aymDlgSs0kHRg4tez+5MWDbvvIkju3Nuye88HuoG7gOXVPtDnLJkuvJWe8K4KtQeQt415nVqSxthNgrr0uFCGGbYEgKSFNgA0ECWWWOec0eU4CHxTlZPqgqKQRsxJxQ1lBBcCF0JAqUalXpdCgVVAtJwXYco425mvdKC5OII7ggGR9KWYOHRDjebSV4Cdbi8wUoYFhPw+CGEVoKJUWbceOgJNInRJpP/i+Ka+zKRhM4XlQrwtkyOVZnUwg2OFjpVPmILhN/Z28EpiE4y4FgXk/+wNeBIDMMaT0NWQJ5vD1MEVOs2nZZD+ztE+MvjFrF8BRyukGSEcgjkypItJfNKBAlor4nGETWzaEuE+a2GO8uiL4xUeWAnDDGkIlAnFq3FXOrgb1Xggw8Z6lqyy6IPBBW7W2NwE542MIYVQAZgBRcjX1DGe7zOHoUtME2WKCbLWvdhDkD//wD933fd/3uUc+8pFxKaB1FsjXf/3Xx7/55gVS3/CGN9xvffKVIbzBow309Rbddkxsn9+e1GFfvXpXUO2fNEBBo1fOB8vqNg/Z3NwoNxx2LI3yjbqRUk0MgJHAFOUVAqZErfM1GMvLidPfgW6GFgljFISot8hVVvTiBgRHaSDrvHa2xtTApsKqpmCcWsxoENZAxdSADA2VlZ0JhbnzNeOm08zIuYjIW2CVahxDrAbCKysrMlVlEToeJ5D3CvCsAQV4Td8nUEDqP8ewNlSaw4Z4mhU1z3C0GxPJ53ryCrrlfTZFwgTydKC5GB4TBNXoSOmUD+F8WBWgVTfZH6aGaB2OjT5qAIDnpGSCqC4gd2EalKgi44xry+gz721DagXL4wkElpo9ExuGuQdhFg/mwuyVyEhvwjtQnpXPj85IYyTsNJOVoufO4buTgxePJ2BmZ0cyCOvbZJoI53/hMAh6ON4nNd1HOVZHgVEPZ1hX9qCjLd7PYvg5aSHqhaOYL1erYRFj9TwYOScrojkSTofhWtg9oFUlKhkbZZTjTjmDwqEHQ1ABxUKfyQAeCNiVFxX7kusk+iMqoChAnSKVpMjXoYfEe5Nm3mHNGcePe+mw9VfJiOsctYCE4GpcMr4TXDPJtiicI/XAudbuiWAJbEvPQfeR+kYcw5KdJfvZQcobj03bhkKeWeu8Y0yJLIAUGzY8d/B6+MzqExIdkMELpEpB2HVAsTK4NrKKW20SKV0AnjpgeHQvgh1wwfmuoKppiSqFAohKDkb7ePi47HP+Q59Oru3wwY3PK1dPm2O9wWpQYGzKUrzcXh5gZVc1mAIqgHJ1zkKNJajD6W4UYNf6VmJMI4WG7NFUNaxyWO+suIrnOS5t5/xgb9Js152TmdQXddvSBNlq7qsdBNm5c6f7l3/5F3fzzTe7W2+9Na4Oc+WVV7orrrhCsEXuz+YNYD/xCoExOOq5YTlBtacnwqX3BGXWjoKIv3OWEJvch0atUFCHEUaDUjuWNBQKVOSfbwSpj3EfgFQX5gAKoaKMq4O+W1NlvqDGznJgzD9l6d34GMuJ81HAdgKEOQmGRVNahIWhg8HqLrkIhlpGtQNZarRopEvYVFCheM4gjmZY9EMAoj2WNYbYjLHV7ScNJ9CmDfGz+BAGlZ/GFY3yrIi81VJshXvLALWDwea7ljqFwXixmDCpSFiGyKZ50vzmYssiAq0ZDQbbgOr+ui8CfCLwgwu17lmq9TNudT912g7fkVIYYHL0OQ2QMA2kha+NjQ50ilGG+ap18lRyqEPTQSM4/lvkuLvwvEw9I12liuKXHBvU9FBgjXiellZSRjTVdDoZtVYVUBgBFceyno2uRmIAoEWmJSpAQwjSClCnPyFO7tNE2Wuupal+WoC0Udmk+7cBmkb9zSOWMLaoNlfuk62HHwjy6tKx4nrwbEuzSdQ8WpQgiINeiTW+aE9p4MYKSki7SY0BI8gjgdmwAx3/ZuwvyvKmWJ5gCEDzRlRNE8CPzSgT46lPvUsLEMhqguEmfgj3K/R3iCEiGYr2u9YZQYl7jucMG4agjmADZbDgrEIEppi5PwR+Q5alybolUKKvx2JBp56t8X6KFBoN2K2vBYZI7kXb/ODMLJPX5zEu8XbLLbe43/qt33I33XSTy+VysY/84z/+48JP3moXKQiy3vxD9f8eDM2j0L5EbuU8Fn3k+raP7BHbN0dZBjWDImhRqA3gQ0c+2GhE6NzIkPCjnieqYLawVFzxRFK+sjikBPCWcT/WEnAiGk/uR66iw3wubDwjV1emG6g67BDEK86uhCnYQyhTtiTL8hYvJPvkoJ1SWEr63xlTqPv5pLxaDuKuOeQ/FJe5+NnVYdg6wuq5946+oMTn7v06kKqygbHaGAezpWobGlZeOSsXCAdSbU4nA5Vvs/tvGGtW1ZRMR91qNnlEHrsQjoqlnEkaVIbDk+WAWuwPsb2+txpQuLfNeAjCcE/9aJyT1xn1uY/aZqM7uluWgUsARWvmMBXBcGbJnEiBzqBKF3cnbL8a5ivtqIsxIJypqK9nTueW6UXC+VApGwIsyXA4Qn2M+4BjM7pNtkAqdc+oGiLmKwOc6W4Y/k0IjstCY6LiA/WyOhwcWWVcDbaEpcEUHw7rKcGWPCLF2hkU6SAGi8CqpNFv6pXWpJIaW9w/HCDRbAfO0WR/ilSn6W12P8U8FH7B9Riy7oEE/2wbyConLYBNdU7q6TDAI9a8lq0BUUHApo4KcXTUs8Tl+U7Jaih2lah8k+wXXifPIfvc1xjKYMnIeRVzZC68/vtW3I7xwUqCFH3VABPHHUse413JsomtPve9FrEvQtjbAGHU9ViVrTQQZvVTaLkBFIyP0epOhh1q3Gy1r4rmq6J+13d9l3vUox7lHve4x8XfffzjH3fXXnut+9M//VP37d/+7Q90Fy/a9qAAQdrttnvnO9/p3v/+97tz5865jipr94EPfOB+79PQHfOuWKi41s23bXxXe86jze0pvNQErZBRV+2AslmVZ0TZUlERwK73zkWuPIvStyrHsPOZG4N0RQdNjuiMVKrPTSWMl87ebUH6aB5qV7mmVkSsBAVcGW1KRzZhLELvhMBNVIKgw3abh58bZCnGgq3eXQWocc/pjY+FATBeysmxhlblOes7ElClQ40WtFT0zQIEjO9TEUNDAd3Uq1H23dok0n64/upojeXEM2jMdVqTbCwWAN+PqD/DTXTNcMB1n8X3WQwHOg/h3e0S2LrPhjBqyjGlsVm+d4BIVt8sIU79txVpFoZjvj+ASvhBuf51NH7091bdyrJzQ8Orzj3D2MhwmEQ1FqTG6PlXUMfJqGuackZCz6h9LgGKy9uTObE5JIVlhPFLh6FhvLe6HPVaH8wB7XRb9za3uZaOPh61JZi2U2TVMw1us+oKo7kZ7BM+AzqGloMQ78P0B3wvxCqV+LSZAsNtsEuZjrVqOTrXGBssJazPY5bWzGIBmOwTbKIddYMRZgl2a9FZaisUbr472a6Xrhy3cbnmieeDNVwwB9Dyypkk4CTWD8GGUg4o+s2xylaEPgafU7w/QIw8WKKdITBOlT2aX20E1/Ay9U5wbaxOo6/B6r8ujc3SzgUAfvkWF3fcp4YCmMKb2azODJvS+l5XH2xdtjfMoGX/ddoP7EMCVEKXRgjDKkMBE4Z1bak1t4/AAa9ZgIJKiJktVTxBHM8FxwCfO8s8c3zm21uaIKl2iZFjdPvZn/1Z9wu/8Avula98pfj+5S9/ufu5n/u5LRDkYgdBfvInfzIGQZ71rGfFyJan+jzQ7eyTtsUlciuP2BbMf9RoMNvALBcs5vsl389dKXM2y9BmGLiQnGdlZ2nTyFWKOo8Jtj4GGqJ2Zh/6uGSfKAy25Bu7TWYJDScuzJ3xxBFoQKW+u5NhDBgq6/EuAG8aB0eCuedZ2ifMSy+gJJ00yuX+9e14PldsD0aTaxNhYdf4GgxaZVYEfPA81ek3z8dNpTfBiFpCvjhbWSnV0+kT14Pdm0ow1Lq2fum8fQE8So/DTPWJwhFXTbVmvnm/Aq5ZRkxyAHQlY3NLtDbr/E2DUBWBiZLFeEmlkFgtMu5bbvP5Jf7bMCLp6GdVh6GOh+/zx29uudNzzu2aaLkd1xllSy1AAJ/rE8ppNq6B/a+BAaUdy9p1qKTwsOtxYFyXuufW+0G2IDVNBs/JmztwFlUdKO4HoIFrjG8lrCVjn09EgGr7x3CsvAmuD/5nonfVOrwrqG1RnpHllzr4rQ3GzOBNCaMuGh4Ilj3X5Yz5DEfuXDKBaupDCfIHdStUamWR+k54v+vj0OfAsyEwHB+PgteMiOMWUusqBZAYTBBfFWnj/IpFWEbFClaKyd9yz8bn9vy82Kf99Y8MrpMyVRdAoNKDWNmJYMOVVyXXSSFOXZkDf7OkNZ8bGTslMDRTjBGWa2Xln3HFTIWt0BgrBYEXVl1JRfHxThWQ+st7JvRe/Lw8UQ1WpRPMILIDDFZo9zwERJLPTVSg6XYcH2FrUCeI+iA6TaiEstfV2eTZVG88FdQ20s+N73cBbNzG3iQFamW37PPiflQoqoQBGb1GCX2nGvVBwmlUeu6avCU5QA2aO03omOlz8h4O370SFvFnFSE1Hvh39VQtyBynLl18zgWkZfNZAXDLL0shsWi9P5eYw7+lCbJ581VSv//7vz/1/fd+7/e6173udf8tz+WrpT0oQJA///M/d3/5l3/pnvnMZ7oHS/MTpf/Hhb16z8LG5/ZNt4rtBy87svF55YqpsDGBKEo9sUe7x8NC2UAJM0EH7jM6LsoK0rnXTrMBKItoqD6HyK9NPreQC98aBAtCoeRCRR9R20IDC44alZ3SVND4Z2SSYq46L59NVIcRgISmMNMgM6KHTP/IqBYkotMZzIHVHflNhVGzK/cknWiMhS9Np+lUYByNHE8uqDZFS0XeGzqkNChEycgM1pOlWUDnPsWqMK5bCquSsiq3YzBP0NMFiKL2KfdDk+0zxa1fJgeHnbFJp08dEqnpkQGc4OayorapiRL1yQTBe5OisfP9oFaG1gkohu+t0NToM82jYEU9DZZLmiFh7JPxfup5IXQs5qTrsr71yfKmKQrUJdBzbn3vaFAUlIA6RYx9qxxIqlYV70icpML0ZNhJVZFqUU2jhQcF3SUxv6R0H8IOp3Y+2IRAJQEZNd8VwFihAytFLXlcZwNpZDswuq0Yl0yzoK6Mc0NBUCklDE4B0uXESYv2A6C6LrE/fGuMFMPlQY00kVTVlMiIVLds0Vimo5RniWzmwoBQu2BWCGoDnBBlhXWJWzCN+LlYC7ORdMsba45gn+oAh7Bhwp/zYCBllY6VqWPh5xT/iWfFoI4lUq7HLYG9JkDKxuj+pM+KDcS/aUMURhNEo3oTtJFyyXiMzzMAnTemmPEcGYxAyfqJgvdT2xm0nQl8NAfsc1KHI8oPB21KwX7R5YuZkluB5t2FxF+o3HlSnhOgZWEvUuvJNFYtt9B993MdS2V9q12q7eu+7uvcRz7yEXf06FHx/Uc/+lH3xCc+8QHr16XQHhQgSLlcTj3cB7pV5rqaIIyuL16bGIHRQx8rtq9Dtb1plNCkY6Ynb/5dMGjwKd/FcsAKRoUJHcGFESfKAnKR0cJyUOO2cr9F3nRGvjojUY3hLHAnXOaXxkRj1I62CGFSS/AsI09UGLsUtuvYJVlZ/aJhpakoJ5vbZVXjSPrvzEZldHHP1RpLQ6GF9CK2VOSEQeAoDI60BzMcQWEEhinhafANv4moGD6XcKzMaEn4x8zqMALQIIMpDJB1T8Mo36anT5/H8PnyFDfUj8xISRJOZhbLRqTt8EZnUU5w34HQ5OBgpAAFCvISb1MB0OZQGBzhcyerpLxkpxik0s/W9zdYZJq9ItIZBbDIh6YOYgBJHM98hkKLJ75v+WCOvIMD2VFOnhD8HA6XFBepB4pSXptOJo+hk6VgioB+wegYMB2kdsXOMCim1oUmtVhw6LVtyfkrcyqKbzDkBKtBPVtS9kVKFFk6RqnybudcWA8IQEekhFGlIC/YEnecTc4/hdQSNU6Xr53eNIigWWu8Nqu8NabL1NxnRdtZEWfw07JCXvsQdHJ2DBol3jHu1GLEsS/2MVIJ4z87/aQ59sHoi/chE5JMLR19CveZ52ljXdOVkATAIo4V7kt8aDwsAWCidLgAV7T4Necr9JmfU+xJQ3iYAyoq7DEZUOO3J/uv7iyHK7pE/YkyW8uPBrgEKDQYroCmxzrndc5drUEj/U8HhTDflBeRYj2cMIhdJPVzGmCelVHlsACQtDAjte2ike5iGLUfFG7bV65FXwF2yyXGjtHtOc95Tpz28l//9V/usY997IYmyF/91V+5V7ziFe4973mP2Har9d9ykS/F8gA3X/r2zjvvdL/927/9gKfCLC4uurGxMXfkF37NFapVQdUuamE2Nkzeg2c7QcO1Dkd9ab+8TiF65wzVd3VrLOMmS2hQdLm5ufOUOkQrLIQldCIIOigjlEaDUPTP0INgf9hnsbBlRBSyjCjze+N+8pydPituWIKA6Rr3YcfOYh7o51SdAWB3IAwKTX+6btLQ5y6nY2WXTe2UCXKFgQKRsuH6dAwFp1wPgj6mqQZDyMphapKqHDb8tBFIIEkcSwCGttMt7oeouhLeRv8W4T4LoKHPdBhSRqyUlbgR1MFnS5wwxcoxnKn8Gu65Fs1bswU/z//J/3Kn5yK3ayLnxl/4hiB4J1qfS4Y5X1qHzdBOEddJ2/8+rKYVZDIMn1HpG4hGCobHODWU9PFQOnwJncNc3ECKQPXMiqlnRBCFkf6s9EPhyBiilAOfTXQmfFt95EFjLQqzLbQjISrFsG/aaYZjxfvJNJGVnTa6LMrvwgEjXZ9Vw+LzYG0gK8NKk9RRfM43pRXeD5xT6WEQbGgM58NOOzNO1PtlOdQmGyrjnaYzbVbXUe+UpVOUAqgMVpzJDtM2UNti0IbPkTpeRoDB6otVqprPWcwpav5sDRmizgRRCrZtQaCYY1UDCvJ+kmUDVgqAgiYCWTqNVlZawXW1M8C3NTtl0tq/Mt8JA4a2Vr8bvxWlzxcT+2gFqdd8b1PBRKGzEwXfOz0GhMg0+lle6pjMnPX5r9WquY/82yvcwsKCGx3NqEP/IG/rvtbhX+r6Wl9Oa9dq7s5feelFf0+sllegqNW8/+w1Nrda/+1BASl6Ss8HP/hB9773vc9dc801rkTxLefcX//1X9/vffIMCu9rsByWlQqhncb5o/ngwkBHqFNR+c0NI7rcJ43ecnJEaotG3WkPEZCg0aNtjuLmTmIRfnbbZVUuwGeLBaGvgSBEn8aZlUohUjmyysD2ITKnFeTFdZYMtoKKyDPy0Jeeg3o2C5cxwkPrLvm4ulvST0qocDN6VxTUqNFteTfTbsKRl9awvT+d+6gExyrLuWcKi5HjkBuAZo+mIAMQaDOfhEBBXS00g8ZDgHNfXILeTIZeGVkIWQQLITQ3YIBN/KzmEWgSy4b7nLq3fKeEkKcBcOlji0A3IpNVnBPgSvwnQKkGQKmilJrYcKbKqhpnqIyuBo2zDF/h8BjMorxiHYu0NkZWjXkw3s7QvBHnpHg2U0ni9zOsJ5FVGaQxktyQ0lpyvDoisLw3hQNyTmBanHD6ARTocSsqRoi1iI568vnCMyTzszEaHmADs8aN0kwM0NWzSnVyOwICnHsFi05XziFgKETLbTaPlQLJOZ4gil6vmHZCFkF9jPpU8t4Iu6MP0fUUa8oADAVorNY83gOr4lJWBS8LuOA7bWpDqWaCvtoGIiCRoVVhNUuAXIg1lzLOSbuLlW70icgY4XxdMQI0qcpYLrhmF9bC47l7EN2J3vmpZ0QWXpL9ERgD9z59MMe53LDHWmo8MNDIaxasW3XO1enEcCktD4aXP55f61sJRnU4yJdKNSKoxWeDOVrvs65B1EJ1oK321dF0sZCt9pVrD4q3aXx83H3Lt3yLezA1D354n4yLSW27TfGnc8tIuYjaGtUaUgY7xccQ0U7lxVtOlxFpTmltEHztw1DTxxaLhAHWZDkIVnlTDXqK1GFGXiqbl8nU57Eqk2RqUBj3M+s+0TgYOMc+I0I3rhx1OI3W9cjUBbWa8286vTTUlGNfR7TiAlK6eKEpEAmLPkGU4RPh9CRtYNe2410RIfUozOpQrAICF+0RqPsDBMnz+mOEPIyE5TMYJgUCLNTNgPPRhPMhwJUYkIDxz+vJMAJZkSS3gmg/5oFCDUCDqgJAsIhjsg0nTzBMYmMTuc9lvpT4SNX9DDVXbifLk6qxDqu2A8OxNSK3WzoYpa45pU0wl3yeuBUCk0rskVTpCkA+CuPVxwpBIWzfZq9AaojBCEvrGbnwWoCxYUVJ02krFjBrO910eNZTi/Q2qbQf5LUPgF0m9Er0EOA6o1Mo13fBeGioYB0dFuEYAlwpKHaXrP6Q25xJqToqwLNKfw5TnmO6bmiS6PSH3Ob3vT5mr/Mr09QVw7GMdTGTQYrrIeCYpblDsUpLA0pry1jVSNhS4EAfTA7dLBvEXPNTncB2ffS5u2H4a6v/qes0ro3YnSZaWRpjFmBHGzQ+3mAYZMtDOyXFPrF0k1x/VaYGkgJabsd/JtHEpX2VYDpPal4wbLCslGKRAlMN2+S6tdAHfmYAlO+KDoC2Of9aa7uao0U1LLxffAa65PBGH/sRbL+YWnTfGJSpY2y1rXaxgiDveMc73IOtrRzsuLx3SjtW+oZ86+hY0GEZPMmVMfm4eoUMMxbOJbN5exDO8J5kViyW5CozOqxqQAZatZTMpGPlmgSfysn+eayMHepZKKs8j5vQAhK03Er6P19LVua1prQASlhZxweS8w8WUcZOoRjLTdwbrIATlWT/0VJybUUV0lhF6KSGfEqep6jUslqdfPDe8PNgEc9GWVot9HMV94bnn1mVFRLOnkqU1vNwgPMYT0WADinnhRGFKXJGw85XyjEbQz4qnOFiWZVqM8bK0hWgXdcylFGXoDTPHFpYcc1Jec7cjloQnGgvwuM4B9V+OvP+OgEw5St0+pPPZXWdbAWMjyq261SSe5aVWNhSIoBW472tj2KswslrQ0Q4WtHiQuFnXVoo2AwkijQPtcIgDkNuGnzj+CIIU8wow8PbQQ0ktV003Z0nm2rc8trqO5O+LR/KB9+VuJt4vAtHcW0QMRRgSyTvLUG+gRPJtTUA3NCZ1dR1qwSoAFGUUW9lnYgSu2poiQhoH2LFWal8RKStlMf476iPijgZKXYWw64JpyhSKaN0EggeSoFLuY8FOFnRee3wWKWmeT0ayLKYIHzWBKhSDAkrlY67ZOgRCSYHBYUzpiQRxReOZYbWU27zFE5xDh1IMticmYCGwdI0K7KlOmGcJ4s9YohH98P4Cf0drh5l95ONaSJyrMqLZqUsK0iXEoA1yIPiHRoi0CD7xqDh/JWVIPuEAEB8PcuW6Dk2soJCMSgUhYNKtAd0kIxVeVAViLosUvC7T1aiAZTr62GqElPuO2BIxn/3wI+2ChBd9G0LBDHbJz7xCTc7O+ue8YxnbHz3x3/8x3Fp3JWVFffN3/zN7rd+67dcpZJBe91qD34Q5MHYXnD9P7jqcNHNthPrZKVdcfl8Li6zN9SbvRu9EnzDuWQ2r/dm71w+55YKiRW3Csrr3cuyHNngnpYrVrr7LdSrrl1rxk7VfL2apqrncq5QKblOj77frjdND2ylt23c18Kg69T9cbvbzuSHUkB1oVraAAD8cTu6YgbAgVYhsY4ay542011oOg0Mq9Xu9vlKd4X0Xe40m7GzttC73pSIYrW4oQ3TabaEJ5CDpTJXzbtcpRRvWyq2422jdkc4kvExegZhvlxyUS9k1mm2XQdiftr5KlSK8fPzLWq1XdTLsyui1mq52O1/vlRwxd4i54/r+8CIOB24Tq7icj3xrbi/reR4V07fufG5Umi5fLng8oV8DND4vvpjDwB48dts9LeUd9sHu2PQbzu3mqy6VXgL24tL8bb+X3w9nbpr9fJYx5CEW+2FJIqlvNtW7X7fbkeuWY9cOZccrwSt90opcqVeXnG+03YNLSiHfUrFXLytB486ncjVapFjurd/UuvN3+aBngPZ3TZ42HiY+AIDlUrONV0uHudrvUui9uM6QFUs5Fy5d1y/7SLZJvE7DVCod1zf6lHBrfb0EWY7gymAzm9bruRd1LOO1lY7bonUATQ/xipIM2iuJs90HnNPrVOKHb1yteAWe/SqxlrbndMh9Y0D+weSWKUn5gY35oilhuyLB+n8e++bf3e680kajFxvpQGwX3rbbvRfgRWFarcP/n3oNFouWp8j+E705hS/rWfTzFciN1Dujqehdpdj3Woqj6lYTuYIH6XrHbc8n9zLqS92v8sXunOEBx467ZaLoo5b2pMPRlNHzxVcrudRRw0/VyZzBPdZutJXgPBzRN61hiLX8VVQ/HuvAKJ1xyBXKrpCb4BHrZaLmlZkNhdv648b/+06G3NPjlHf3nHzhYIr9EAcv12n3RaVGFgRp1PKu1yvAkfHtTfmnpQ20WouPq7fNj/gnSE/V7alY0jQwG+73gf/HDphNW+Plfm5L18oOo9r+239vej2Le3o+21L9VJyXA1Sckj0jtvd3c+VvW01wy/v/+XjZ+cdEf/eR82mawvHEPes2N02/t6/P6z8AsAst9p9l/PF0sb+7UbDTIPy2+byLOnasDUkct21q/tb5Dr1NAV04xR+nPtteyft4LjxeQBS+m7mS92B1JiOutv2+teZSK5zcKTWfX8qJTc22FsL6i03oKgDXENzMMqbtbaLVAl630q9tbQ40L224VIjPq7ftgQUhet5qbetb626Py7AbUxEHZdzxZ4d4b9vN/y70Ym/Z1sP5Pht6z1P1W+7BkdTsNv82jjgn133u0pUc1HPjqhibR7orc3eVhwsdT+3mx3XbnVcESjIuj3i23JuMF7vfTu/XN04brefyXbjlVVX6NkGe6rzG8edLCR0hUHk8hXLedfpvRt+26XeO+XbDNaYxeZAbBfke0DAYq3k2r2KTp0ofT+83bN+XG9zlDpyYa5DcdT3Yf2486vl+B77tibUpp07PzMSzyX+X7tW7M4RzZbLkbECcGBg1t+H9fez4zo51l5P7nPRB9mKhY2qPX6M+fk9vidA8zrrZcvyeVfaWLsiUY3LKUBjfT6J9y9EXftWTT0b0ot+PJZKG0CSf5eLYIlgSnAF151PNo7Re99yecMAukjbVolcu/3yL/9yXBlmHQT5whe+4H7wB3/QPe95z3NXXXVVXB539+7d8XZb7SIHQd71rnfFZXLvuece11AL96c//en7vT//+ykfC37/zIc79w8/k/w99D+dWzUqVn3tVc792y8mf29/oXMXlsLbPuqwc5/6leTvgz/p3N2gE7Jdvce5L702+fuan3XuRlmBa6Md2ObcsTcnf1//S879Z+Jri7ZtxLnzv5f8/XWvcu5DN4W3Haw4t/L25O9nvdm5937WmS36v8nnb3+zc+/6pL3t8h86N9TDfp73B8790Ufsbc+9xbnt3g9sOPeidzj3u/9qb3vXm5w72ItO/MyfOvf6f7C3/eJrnLtmb/fzL7/buVdkyNJ88pXOXd+rUPi6v3fuZ//M3vaD/9u5r7u6+/l3/tm5H/sje9u//2nnnnVd9/M7P+TcD7zV3vYvf8K5b39M9/NffcK57/hNe9t3vMC5531t9/M/fMa5Z7/e3va3n+vc9zyt+/nfbnTuyb9qb/va73LuZ57d/fypO5x74svsbV/+rc798v/ofv7SCece9XP2tj/9LOde993dz8fOO3fFT9nb/uhTnfudH+h+Pr/o3OU/Ym/73Cc6984Xdj+v1Jwb/kF72297tHN/9ZPJ37nvsbfdmiOMOeJ1fc4Rb8Ac8dzXbD5HvLvPOcJtzRH3eY54Y/Yc8aL7OEc8+l7MEde+rP854tC9mCOm780c8eKv8jliNbEjPvRAzhH31o74Pef+eGuOiO2IH3uA7Ih7PUdU78Mc8eL/pjnifz247Yitdmm2z372s+5XfiWZ0P/8z//cPeYxj3F/8Ad/EP+9b9++mBWyBYLc9/ag4FX95m/+pvuBH/gBNz097T7zmc+4Rz/60W5qaiquGEMa0Fbbalttq221rbbVttpW22pbbattta3239luvfVW903f9E1u27ZtceWZJzzhCXEhDzYfvP/Gb/xGNzQ0FG/3Ez/xE6lg/n1pc3NzbseOHRt/f+hDH3JPf/rTN/6+/vrr3fHjx7/s83w1twdFidwrr7wyRrO+67u+y42MjLjPfe5z7vDhw+5lL3tZnA/lS+fe32WbLnv5z3dL5FKEsJjQ2dbzdNepqTrPPm5+20JCSY9AY2Ue4sa2vao4vjKNp6ZGSpxpgyGa8+kP5Y38yXZTvmxUlfaK/IVitw/DJ+qu3W66qEcbzS8n+7XHuyGTYqHsVnZ1t2+3mq64JrnSNeS8d1BmseOP2xtKQhm9xzQslNd54Z462YzpiEK8DXBc0XXp6/H+rZbLofwf74e/DE8X9Nv69H2/radEahb/es6lpywWe/fd0+KboWe2vk8nocXnYoputw+DZ5N7Vrr9bLdPuYJrH9nVPa6njkdt1xhLaIwrO8CvHkyo7o1ql74eFNTL9Wjmnr6e71LdY7q7UKAH/djTPEsJLX6dQt+9cFZO6G67TouPt+3R4kXebe/exH3oCSKuU1N5PFKg8+X8Bi0+l2u5qNEdsLrqdaHY7lLtSwVXLnXpz51G05XA3Rep3oWCiwrrtPjutuutjH3KhZbLFTwdvOiKuSgej+1arw9Mr+npe3i6/WAvh9hvW2jKMAvp1aViJ06Rir/PRa651gxSsOPj5vMxDXq9+W25HZunVa+nwflW76XX6WP7++zHuadtr+vqNGstV1YJ5hu0aZUOU2zWNqjuZSUmM1RouPJAYYNG3aWvy3SYJnIPqoO4tlo7Tn0KbRefazC5tqanr/dS29oB/L08UHSFXMf9+M3vd+XVupvLl91bL++GGjWNPV9N5ojlWsF1esddgf7Ouk7ROi3eU9/XafFMKytgDLeK1Q2qe73epXmvt/NrScmN5WYpTjvw2y4uDcTpIq7VTmnhFGd6qZGeLr2eBtdquTxSxTr7kzS0gYGGy/t0mN62Db8W9N7PZh0aMa3eexZTx/Miba9cRSpDL0Uuvmc4bqvRSzVUGjvxcyh04mN66nitWYzT+/y2tUZybU1cZ/zO55C24g/ea6VqMtZGBmvddJiSn1v93NNN8YvvNdKdmuvXVii4ak/Q0b/3y0h16l4D+pDzc0+SDhPPUyp9Mr4HXqcm7kMxFkWO02HiFFEcF9UXolYx3jb+7Ddqs3Z5slPBH9fT4svFjWN1ao3kt43teilI+bwbHUvem4H2cjDNMd6n0E3PjPsW5V2rN/fUW8W0BlXep7/6PvT0A2pNqfHVTu7hwsJwnOIS97WVD6bZ9O5u99B+Puldip+DIyVUW1hOjj20kCxm+eXENuA0uC7VtW4beO0Rn0oQb2vog3j7ZL35bXMoSVqCeKXPDFm3DXxFoDgNrtNx6tZu2Eo+Za660EvVa7dccQGGRm8d2zh2pbox9yztLG+kzNVR4ajZ0wnyNke7V1417oMf86XwtVXXEttg5La6SPUpLSbPZubagTgFxG+7vD/aWMNF6foBpPr6NJAq5gik4LpVlsDOJTaH/3vep+H2xis1jJCK1xlK7Ij6mBw/xSGkBw37OaW7bSHX3Jh7qDsV37dWLw2vVHCNeqlrczRaQgeLBl5lvBlv2z1W5HYPJrSnyWoisDFaqrt8MecKpUK8fvttfTqVb2vQaVtsdHMO/Tx1pt5NWffj8cKZJC09WpZzfFTtzq3xNQ/W4/nEt+HhZAwNl3v3opBzhXLRFXoP3r/LF1aSlKTVZYjBLJc2fIK4Twu99J1azd36K79+0ZeDXfe1jvzCV6ZE7h2v/u8pkXvZZZe5yy+/3L361a92AwMD7k1vepN75zvf6e644w63c+fOuCTtwx/+cLd9+3b3hje8wc3MzLjnPve57lu/9VtjvY4vpx04cMD9yZ/8iXvSk54Ugyq+iMjf/d3fua//+q/fSI/52q/92thP3moXcTqMR9Ee//jHx5/9IFta6nI9v+/7vs899rGPvV9BkPU2cHzUFcpVIf5V29P74HPL1w2gUncl71TgaLJsJcSZcvlkAS9AkDE+ZDzJ9wy+2CCspkteKu8+0dGoSkkQQ8x13VANbUevMxHiTEnri3xMigjmm5WwQFdH/r/rb1S6jj1FybB+Sj2oiijhGbEMK+bNrgMf1l0gQJXcworLabFFc59KuMRtJREydUqIkwZybHivf44dDm6Lkm5wBKJUtQP/m3c2km9yZmWTgitBGZ051c2Nc/Sc0Vo5aBAJn1NTMKkxBkM4vwAB19WwMF98zlZKMiZ1Tl1hgeViKU5AdXstssYmBQnDYm6ipKu6NqEzWA1XU8mqmiKeVb9CfdCXYBUbHouCrfE1oKM0MLm/dnqr5aZzvQor1WIrfCxWh1m0r7OtBYVV2cTQsTfG50L3Hj6/82E3Wq67Qr7s3r/ysG6flTPbXoGOCkRnG/jcWnf4VNnd+HgGkMf+16lt5I/Xc87j/vt728T+fmotOVcckf0c3L9uCNddGTnqPA91hlqqnEkbdSLreYDOC73v/by5fm/8LS36OTJ5EQZ6TopveZynKwURVkpdvwK/9aqf13tTTw3rQbOl9mV56WIiXtKuJBN7tQe0+VbxOgleo6RXErjC8cDnuX6f/PmrstRYu1GW51+/bFaGUiWkue4W1tVpB8uuiGdDGM8/Jw+qbPwNke3WbLIA7fxQcv3lpfVjdZ2b2kRyxNXp5DpPTmPcjbbttYRzD0twQrciVR3HeEXzqCY1eArH8kDLJuK6nU3EVKkfJub1YUO0T2uf+KnHr7U5W5i0Leb4ijiEEH31B+j1p7Lo1ZnK8W3Ea9c93vrfHQ9i4FhDI2aVKbZCDXP0EuZYCElHvbUw522ODPo14xYrg/L9ylGctpVP1tDT3eHh/3Fa1+unkKQyACZK+cTH8McDpr6x3fr+XjcKz6OD8rK+1QBQreHeCNHYVMVD2BAruaB4KO3LBkW9nXM37Ya4/EiyYQXAsF6nOa83VmGjX0iewfA9SV8mb5Jgz8rOZLvaVAJozE0m25wb65j2JYsnTH8pGQRDd/m68Fgzeu9Rq1V0t8rL3mr/Te3ChQvu9ttvd29/+9vdQx/60Pi7X//1X3e/+7u/6770pS/FIMg///M/uxtvvDFmZHh9Dt88GOJ1O371V3/1ywJlPOvj53/+591rXvMa9//+3/9zg4OD7olPfOLG75///OfdkSO9XPytdvGCIH4gefTMo17+38c//nH3sIc9zN11111JBOF+bnOPbLr8QMHllpMJavCU4bGpUn4D55PtVvaES3a1tqnqF6wGIkoE2s4TmQDiWIaSNZ2qrNpx7Z64Ze8k4rcOKhy0UTKRRpgX9wtVMdCHI3AktlGGFqMQYn/cT8HEyXIyjRK5qX34N28HBVzpACtn1AIoIlhhLA2qK33QAZcK9vbFUaeuPhm2VguL8pWvLjJ6BaMckSQ3qCJhRuWYIqyw2MlZ77Map2U4Y4x6rgvlhZol0sljhVgZof2DDnjgHFX0jds1gIyy+lHWORuI2rLp6Y3O+Roi0uvRcV1ppr6molJGVYhOHVV4lLr8GhxYGqHiuBmlhMWYJEBljOHg3+tfF53r7C7EK5MHBU98flcKfEztEz59383aP+VYGpVBeEpdTORCZeheVfnIN+WzoSMwOJ98P3gO72ovErreVmGUz0wMmRXNrMZ7UFxM+lMBoDWqwK3yMkQcsUasTid9md0x2FdfyJKkYztwTj6P0bvBAltMNqyjbHUNn3UVFjqGVrl13VDEzA14H6XXVqb5WZ5Tli5NPpfwbAu1or3+iTEZ/qzHE9ddlo5lRZ2R48kBhm9FnWnvtD1+W7DKRyPBBtLs15xR/SeMXwcqZlCc9j6AxpyHjHPqZYTvOO8n38PU0oO5kHafrGbCyiTqPnEuZT8xDxeUSDdNNa7N0SjLwrfNSoJcFzpgA7WxLuiy9PzbnFcjezzw3nL94L3VZXkrs8k+1Znk+4mbEyQ799FENGb+eY8T++exZnZK+FyQAKroJ8+PSxCsY9z/+SMSqBYVYUpGaek5rdCMzzjn/KHkeSztkcUT1ufCuDrMJ9wl0x7MwqhelsELkPqKLI94xCPiKiy///u/H6eoPPKRj4y3+djHPuauvfbaDQDEtxtuuMHV63X3X//1X+7JT37yfT7/q171qphR4tkew8PD7o/+6I9ceZ1V71wMzjztaT2xna128YIgT3nKU2KKjx9kXvn2xS9+cSyU+p//+Z/xAHggWmG+6PIwTHxb2YeFRZd3Q7R/7TJM+FiM6BiXWT4yLosL55iGsHB6FRPEevMFEyTDQxCRXmzGcpjazmHkHw4TDVdR91x7BaI7YaMlVYKMTYR+sA8dFl1mM3fvJ06zD8KKM/oVb5d8JB1aRPGVEdhGBJNRfJ1OkhxLRRdwoYNGudfWqBy4DYy1Duj2wjknFTVmjyAiXkdkFOMBGUyp+y9KQJMpxXcC5/CtsFQIjrUWSukWRkHDV0agrx4U+kwQZaAkLbIleEZ817jPkNrHbGlS1aatA5BRfI8bSkq8bizTXCegompbroINRDYSxzrZI7paAo1qMtcYYUs3zpGgfVdazvWiq55BNX7FbOqeZzXJXrG34ztllgdXZY1Z0YagFFkdmt7NVBurNQBkdZbl8/RR3/W2Bkd7dReuRdXRzXMuRjlKOikEIXRqZgUg/ugxOqbJNjWU3Iz/nmJpSfQFr0dlBuMWUVLf2kMYX+hbYQ5pMiqgduGhRPhZZznD6WWAAc5pq5d2E+8zgDVbrdMJdcC5GlkZcGA1eEYH0GaJgi2onEmWxxalqjFH5hR4ySpJLLtZQER95ppk/zOPnRL7t4bxvvF+4F3V9gfnAcd+tox1XgVlWOaYc49YC1PAJKMiwd3FIMh8HY1gR6Y9Ypkd7Ke2gQxUR4IGGbvwHsIea2Mt6KhqWsIOZZ8xvrPmS1EunWMA+xeR+hafk0xGY47l/Obb8hTSiPclv81fmYAY+Wd0WeMaKPGtmWQsujbeacHyVIA+388c7KES5p6sErminDRA1uY43iGwR7s75cIpSWA4kv0Sd7seYkNdIi36yqXYsHnQ4sspH+vT3v7lX/4l1gTxUg35fD4GQP7xH/8xTk3x7cyZM0K3w7eJiYkYrPC/fTnNp9h85CMfidN8PAhS6KWqrbe/+qu/ir/fahc5CPLWt77VdXr5jy984Qvd5OSk++hHPxoLzfi/H4jW3tZw0UDeubVk0BXACtEtwgpeWkomuPJCmGK6SkAlzmGFEcXFmFEEPXlr2mzSmeDXOR25IauBu9Oa0MwD9KGNOuoEOwi8KMkCYUgr5rdtHBmRHFHvnpHFLEuHi7lIFboPTBAjRUE3vdBvdEV9n1sohQ2iYKqSjJL6VkUVgOV9UXC7nR+XY2busuSBrOwL08jzA4oJAoOKYAOZIAQaspggTOdY17rYrNEJt9gjmtVhpXawrZe4tXLzQ8DDnK/1ubG/cn6oqZEJCLjgvaIGAx2hFsBZjpnuF+xA8rG0YFvyjSk8q9HkRY5ExBAvq55H6Cjimgse0DBScPi+cNz41JBHPH/JnZ51btfkstv7f3v6LRnvNO8zDXn9PDkGOO6sfbRT0ACQ1Ma9aQEkFE5q/AU+GiyuEmjXu/5DjrmVnQBlRsPGvgaai6thhsP4bXhv4BhTZ8i3849IOn2+G+xKASrFRMYk3Yco7BSwFDFTMeK+odLI2iSAn202cZERWEbhyXxI0e3Fb4iOFwDQANBpAZzpHjsMKomhptYva7s8gQ84lvpdyaNvHbxr/KzHVr2nSRF/xrhfIXCDVEL9enGdiaCZYLI14oPgM38yxr0G94XGFQ6WlUpIpnCE+2SQXNO2kQFccCmygijdc5I2hb7gc8ruEgaNCwa/cioIIGIvcOgLWJsLGWNIYEK0gWCQabafuDaL2Yo+txS1RwSmCEQxeKZBY8ukLYTBjaVR1S+sX7wfTEVM2Xqc/7FON6HV1RoBU1sBjpLp1QmChwShdB/itKP1/bEZyyLHx+h1R2HzWw3NV0thsyqn+O9e8YpXZN67T33qUzHb40d/9Efjoh0ejPByDW9729vcs5/97Pj3Xbu60Yh1jSA9N4W+vy/Na6eEmveVt9olAIJ4dM3/W2/f8R3fEf/z7eTJk27PHuSU3E/N0/zzlZajSdqmo62NeiwY9SkYIGu4xTBASvMqyohjcwFmVC+VglM2HBtGUbgOgboZN0MYVCxMGX4pDQ3xmf3XIIigT4YNcb0wimPzWJahklrk+jCO+m2MdqGfKaDDounS0GIevUojEmKmufA4YTqQb4vbYFQjusA0rBPfKB9IDvzuMiI5zJGvKlbJurCodiYZ7clyWrkdU1j4vY78F40HJyL3YDhotgPTUYK6Ed7hoj6KZ3lAW4HjdnklQTPbs2CLpHRcXDgCnBX1ID1bGHRgn4wlPN2RHTIvQUTZ8JlaHxpsIpDEZ2Ad19pGb2d97vYtH+6zTto3WBncjgCTSBtSDCbed6HTQ2AX+2sQhClFgiqOz4qcpSbg9HVpR/v4M9WPsIoFC8/Qq/FtbSfmDkQgVw6HI+op0JnONea1DtIkyVzsHs/S3wmzvppIsfBt6XLS+nATCTrr+ZLOCF8vPvZU1HbzCL9c13QQwPotC3g3QBRE60Umh17/DAeUkXbtwOZ0CsbGhrlgGlVmIJYDjPaISp8oQMyLY9WaLlLgQs54TiLNRF2nEaCwjptqhg0j2LR6H/bNer8JziimlddfCe0jUnP0pXA7HK/DOY5dUfu3yPLkfIUgXwoIM1jEBDHEPKTepxaZEBWsMYNZRmUYFBLgMu+FCgSWB5tS62r99Fj/staWuhF44Gc9qYhxbOitpN5pjlWC+OIdUB1d/+0r41c/eFr0FWCC9Pb3uhzU4LBYID/2Yz/mvvM7vzPzkAcPHnQf+MAH3N///d/HVVrWj+v1QDw7xKemeL0OL+fwiU/I/CS/fbPZTDFEttqDrz0oQJBQ8zQiLyrjUbe1NRV2uh+ap4VHfoGhwJUdkJBOH4WsgQbzRW8qWpOgVWKRIUNEAwoiZ5GHItKfAQ6ICGAYtE+DGMYkL/Npw99n7pO+jOB28jMjZGEAQW/HKKFougMWWGIxRHTKJ/vZCW/XVpooIk1ERGGwUUYkjlTljkG1ZnQkq3XgZBIoSDnE1Dih0yvSeSLz2JbWBw0Y30q4Bh6PfVsBW6Fel1GpNoxAt5R8rsyCwaVopu21JIw9MIPo08PRrz2rSvTWBcGCgUqzL0Chjfs2DFFJgk1kqJQz2DNMhyGIlAVicB8BUDEPPiM02oFXUgPwpFkZBKW4XSxGun6qyLnzM10RgmhFLVVwBAbOJHPpofcldNhjz5E0UTLPymDNknZcA/NAC+2u7WSePz6PUHRBjoEijH/hzEaG4a+ANFZFoMMTIYqvUzPpcFAIlMCPcB412EPgg8+ajITITmXgoyaTMU9RUiUMzv5w7hB9ycsLjeBNijnWiM7r3xihz+G58Tlp1piIbiNaX5wvmgw9y7GhAGxc3mzjs9yf2lkEtLOuk6k2woG13n21lnAuMx02nSlEhxwgvAjkcP8snSEDUBY6Q+remiB0Zt4rgUEeK2sXzN98hLwfWcw/SxNE2CnKaTYcagIsBA30rchDYyRv3acMwop4bpiKmyNMm2qZgASDKmT+6fdLANq4uW0xSYb7Fe/DFHYyPAxw3bc6bANW9yJYJNgr6v4J0BSBrBz0lFIEJLzuJYCHgqmmxuC6XR3ZeI77atcE8UBFP0Kkvoyt/7dZW13t2ncM0q//vZ698LjHPS72VU+fPr3BDPFiqR6AWdcN2WoP3vaAgiDz8/PuRS96UTxgSqVSjKp5hM5TlV7/+te7a665JhZ+eSCaj9JEvqSXIQ6lkV1hLHI7GHFC4Ewt5mwFS1hUL1KGyKc4D/sYLgaQ3t/4Psu5J7hQ6hb3CRuEDFy0DPVyHZEQqu/sTPizXlgterR8nvKcppiaiDy5/lpk3Q87yigMHRrlNJS0gc8/OmHnRadsiP1JJybYorbLcqI39sk6Dz5bWzH1wLe2wZOlw8RzUoclPk8OIARYFY2xcGQ23geO2nJkMAJOJAqA2jghoBH1i+PSx8qF393WsOGAx18YzgNZPoqaWwHTx5csTvqf7wvUopgrr5nfZzWOp8Fqw20UGcp5umcXoYiUBoVgj+xN+nns4WSCyJvOd7wJMLAlmCBgmChjt8M0JIrJziGNTQ1TstWEHR4Z4KeK4PN4ZI6xSpcGcFllQgCTAHXEPKIj6Hz3BaMNp1Trl8kE6ZUbjr8vAVhVwo+k1QtAA3Mco9bx33Q4OF/znJoMZGg9yLmT16WuUxzMqDilBT+NdBiywzjXaOaH+FtoYGREOMwU0HxQjF1P8pH1B5mMauopcEwZtolsCtDgvWHXssASq5/GeOiXYZGVmSn6iRdECGNnCdpzLjVAEH1vxTMk07doMRKUbYCxxneN77GeuyxQSQjt4p2MFEjZLiaosyBysMKefrb5zdOT2FLi+ip9beM8GUsRbYUI72FbiObinmmxf5EOg2sjEJmq+IRxs1oMBj0pit09oPr/pdK+gkyQr3TzAIfX9/Alb1/2spfF6TB/8Ad/EBfteNaznhVv44VJr7766ria6ete97q4XO1P//RPu+c///kXdQnjr5b2gIIgL33pS92HP/zheIB5oRkviOr/X6vV3Pve975YEfeBavmlYqw0LYw7CstllKQTQkuWM62ZA8Z2WfnNVklQSw1eG4So9if6I1JT9OLDxYx2OM7JBSulxRrucqbRxOsh3dxSzdfXyUVLMEEy7EbLqE8ZJ0af2U/BJh6wNVFEsNwCGvqEzIVjIyJ5qS03PnUYvYLYoi7XK6K+zGcla4rivsoxZ1lbS2i3NqYGHii0ZLawos4ASs1VlahYHdWMO2O4NubtDkv2iaAaU9QYAqzV7SsmOMC/C30yKdhEqhEeXL9ppjT8aKBrgIrABcEn9p+f9f4tplZQtJUshpSYqhHt959h7F04OR4GjSMDHMB2WtLFuu2C7JAh6CuivgQmYfiyOkDcyBjhe0hHiAwN3TldsSGwYaZmAedIsiAspDzuG35iEIB6EjrF3dBXEmy9DOCFLDaZG+L6a+ImZFyb5SiK6QrPVqfDMFMH81hx2XYmyRyQjj7mSx9wMZpYz0Sqj31zRKWOPtYVXX1JiF8alVo6+lAcK0bFKcnYUX3guDFSiPT6208gqN/qUX0zQcQz5MFdUGOm3+o2wtHPCHh1AIAS4HEqWs0m0mgNq1+DHhajl9p2zVF0TKW5ENgT6Yfi/ZJ9btNu4LrAVDj2U79rABQa2L9hpUqp88g0x7Btolk6vE8MYHYA9Kb0VophrSUGPdeFUFPnuRSFUR+kzbNFvE/6v//3/44LePgUFx+c/9u//du4gqlvXqz0H/7hH2LtkCc84QkxUPLd3/3dcSB/qz342wMKgviB8453vMM99alPjQfQ0aNH3eWXX+7e9KY3uQe6FRdy3RxXo+wbnRJd7pQ5n5ZjKzQC4oNjYYNz3BqyDUKKzplpJllOvwUoEHjRizErv/A8mLyLa8lORTVhcwFul7BgwHlIGdgCYML+ZJJkjOR+cr/T5YfD56fQoCXMp/tjCbgq2YoM4AOfeS06Ysjt6M0Z/kG3E/iJxgCd9iytCzKdYKiUlm3RvYGzyefJm5KBs7QP6Szj8ubUtsOhxj0cRNlMPo+VPfKkoqwgIjSk6DN1IT6eoRtBai/FDbOaBXxkRah0GlKyT87cRoqEgi1BkVNVhrUDIKk4WwxG2TosmaxpujAc6ehXZjAeNBMGt4NVP8hyiTfrHS+nqNayA4zGZmkO9AfqbHyfNe6tUtUa8OvjPRTgodIx0Qb3xnZZbHtS5MmeICBDoF6DnCzVSbZFBggiK3Xhe/FACibjhdXVRF9YAUWzTyywhJ9TAVjjfgoNisiuwIV7JW4b08i0cKKoyoOuWcLmOrWFEfE+qrPFv/F14eGsMagAeeqNiXLGGc6kACuaxrgRuhtqf5EmEmYBaBFgjkNRktRIQc3SBMsCPqxmBbYyK8qYB8OhMvpCu0EwaAmUKDBW/M2+GVpuabF77GJovnV0qhIQO64/ImCo5x4Ai5zHGDgRY1s/zz4CBKnqLmRqERBnmkqzj0CYLrXN9dPS6FHPhtec0mhpB+bXS6A9mEvk+vaoRz3K/dM//VPmNvv374+1Q7baxdceUBDk1KlTMY3It8OHD7tqtep+6Id+6Ms6phdS/bmf+7mYSeK1RDyo8od/+If3OjfLq997+5ULQ3EVxqUSGRWLDG0za2HMZbA3Gsai3+eEL1gZqfJsxv4EQSyxsAxDId9E1LvZHzhhlpfTx26FFykeQPQr11/lgn6boJwShCEIkiqZnHzulIxxo5+f8QyscaPPSeNIRJ2NCFumgWqM4cyIneV8qOusoRrjqSdaJYLknwTZaGA3CQTSgGEuSWzQEESh047SsSXZFxHFxuEajFoTHNCRWd4nI51Hs0dESo9V1lBUVunPIiJwU0LKS3zOAVSEgahzlrit1WeCPa0deE4q4ifKfrLErnZ0exW5Cigjq9/pSreKbtwmb05+WNpfMg3UgQvJtQ2cS/ZZOGTXMl7djf6Xwto+KTCUY4XOrRAdxMcMgIkpMFwjtF9PAVNqQ3QY5TQpijZF39J90vuIlEfS+DmP6og+xoCoLtbJeKcbFnOP820GdZ3zN4MQGdUrhNMNe6Ayn7VOh5kgOUzYgn2pMRBE3rmdlT4S7zMQbeqQE0QRzBG1fohna6W8qOPxWfUFyCjGjDgugzKpcWP/trF/X6k5tt2UxVgRY9pY/zLTkI1+ar23Qj05eHMY4xvTlZ57xP58HkaKtUi9VkwEYY8I2yBD9wI3QTDSstIkCUhQG0hU/8uyuwA8cF7mPKyXaTHHci3iRs7e35CEor+gxzbBq8JaeNzpClyFRvfE7d7/L5nmL+fLvaRL7JZsta8SEMQLy3gtkPXmaUVDQ/Rq7l3ziryejvTkJz85BkF8WaM77rhjo57zvWl+MvLzu9Cj4CKrbGWBlJc3N1p0LqPI8Xb3nuEgRaxw3FbGgmHkqGcBJzweJ2nSQgsARKqz0qrPN5IbVZ+g5Zd8bFU0wBSO+DGdhIaibtHg5oyXLANCVGcxmCBZxraVh66bRRsWLQOcEEwjI/KQU+NMgHxr92GByRlRkAzATziNJcPw1mCNkbss3zWDD637YNHDdcqGBVzw0KTpZtynyHiRs24tS+dZZaeRtdT70TiYBVbFnTAi6v3dJnPuEbdcg1rWOM5HTtieUbhUKU/aQJW4pcsoGGqH7BZEf9gB0ss0mmqAGNY2ekyLNLIo/GwVS0c4eQYjTjcBTJI5gIcjdBJUNFaUwkUpXalppU9qzH0WMKkdJqtiRkZk1BSvNvqV+snSWRCBC8W2431nWgBK0moHVrICjXRIcf/UOftIDcmrc5aQnmMdSzj6fCHV37ZWhzy2ZTdYQZUUuG4cu980lb7mK/1K8x62wqCDsD+0HccfrLQl3ax3N4OBa+mfCftS2BxydwlMhj/rZm0nwEd+r6o38WUxU5LUdYpjW6BWVor3gAG6Kr0Sq4nrgT3EkuL6/WYfGJRpdjW9U33JPH/GWN+4Nwqs2mpbbatdpCCIF5V63vOet1HGyGuBvPCFL0wBIX/913/d1/Fe85rXxHWifYoNyxzdl1bbEbl8NRLiRJwU9aTGibCQFIxwI3eDHr6QzLDNIblgTH7w2Mbn9q4kVD5/dVLhQPtRTaTKWEYDG53U+O/q5pTRVOTFMsQNo0MbEM0h5GyOkOIYBdNk9Dkto1Y4xllUcSPPNeX7Gf40qaC8nzn9JqGfUh3fBceTb5O3QbxyOfmcr6OqwkoSnukMSiRu/orkvanOQfixmtzn1Wn1PAAQNVGKvF22S/FaVQmEwyeMNu0BYzvhJIY/62YNB/HYdVUHGt9m+oN8JwtgT7AJ7RSmG6TABUNIMgOrYdfKi2HHio5pI1w+PnVspvKxwkSqjKlgK+BYWakhBhjbp/RJ5j7rx047wGEnXqTyZfRZlLnM97ePpdxviUX327Ki2QJ4oANrRddTTrcdjbSacJiM1Mriqt1PNqGBhPVGi/6J+24wY1KRagusN1gp8d+GAyrFVPnZPmc/JeJTOjFr4XsjIvopQCJ8nixWhRU8EWkWGQxJkz1pSz3ZQJhlJ+Tvw/4ZrAoGKCzmgn42HW6H8UXGZuo6yQY1Al7ieWYAEsIeyNB6YBoXHW2mRIu0Ww2kRZunV6WaYIQZ/Xd2mog1hqxno3/rh4iYxcAVqcsZ6ShijiObKWeAIwjyxcfGWiSBNGyj13li9WvhfSqLcjEp1roHaTXvwyLzYG5bTJCt9tUKgnhBVLbv/d7v/bKO9573vMfdcMMN7tu//dvdhz70Ibdnz55Ya8Sr9FqtXq/H/9bb4mK3duLw3TlX8AakYCgknzsZkzEXpnlUNWBJPy1ENnPNwU2R9pSTZVD0zJzJfqOHGcKmpvEfhTVBshY5K80lr8LbwngX22GjPvNErT7ryKYVzRQpJ/kMUCxvMCS4/4S8ztp2MmMM5kB+qC8PugPggy2He64XfTo2QgtgVjksRlSIRg8NtVS0ZshihUQmY4VMKT735nAUdu6zKl4QeBFpQ8q4IUWfehIs8TeYRf/AsfpJVlatNo65g44+o/s6+mY8p9JSsk95TvaFukMNiMZK/YGMNCw+N14zn62O+hKEYLUA9dyi0damCsviF6ETkUUDMCgrZAfofHXjGQg9Bn1Ky1GNjGpgmgJNx4igVrXP6DjnwpKRh96wz2mlnKQACEswu9kfIC80KcgeYeAhiz1Cx8oo/a6Pwf3ZHzFfFzNEuo30CX3NInWqaulLRWZqihiqFGvkGFRjgKw+zgP8vjobBZkPcX9w3QxWNEZsHRFzfFhpllrUMqxDnZkuJoRq+3C6U82wmwTbIMNK5nYCBMlKV6P+mZgH8Dn1ToaZY4IVguCREGzV6STUW+H6rc9ZM4JMhhaaFoW22KA8jwZ+Bs8l/SytdIJjkM+MqUEaWJSdCfdF91O8e7A7i6u8/3J/UVKblfj4russSwZ8WFEN96Y5qGyg1r0TVr9Y2oNdE2SrXdrtAQVByNj4SrQ777zTveUtb3EveclL4sozn/zkJ91P/MRPxEyT7//+7w/u8+pXv9q94hWvSH2/tt25QlWyOkytDuWYiRSDmkGjVIuUAAfa937ypnPOhUXkQGtH3SivlqVSLg9gfC1Khin1bxqEZHwY0SL9t0WllJR6ubtA5xt9pBPFDlD4NxHFoKG01p9uBpvONxdjxVrnhI9nM2Y6RebY90dBJluA2wkBXk3BFUwQHtdwMrWhYbBK2gkBqndSg95NQcUs2yDDT7V+yRkPjs6xEJPV+gEcU1bELSOaSoBDzCmgug9CZDZLgyjrebaGwoBEh8ARI6Op6DoMOt6bjLQCC3jwn37rRwbdcHvFLRcG3EvW75tmMXB48RmIdIEs9kq0+TupHr9gBWIeKS3bVOnBc8mDKy+1g5FmOi9Le4vmHE0G0HpUsHst8px1lH0WaYKYr8ortoFuMRR4bakqHYYmU1QNH1c7s9TUoJPUGA3Pj9ox5G/Up2qr1EqyJ8Wxzif7DMy0g+mb8fVg3W6MJS9CfZQ6Q/LYYm1eM8Dgqu3AmizNjLQGDVBsfC/WfJ5HndP6qU//S6x/+fvgjBb6OJa6bhL0RBow99fTkAGeCVspY44WwIfQAcsS4uQf4X7qfThfEAC1hdojewwxEJJRTtoCa8TYsNhpCjAUwGYG42V1OzacLmxqQ/WdhqzFhs20uPA9E+luuv+RcT8y0lZE+rjB8iwvq4BVjwGy/v+tttW22kUOgvx3aIx4Jd9f+7Vfi/++7rrr3Je+9KUYGLFAkF/4hV+IQRMyQXxKjZ/oCmryzYoQiRQMTJ5WoFYvOFYURRiLegE3FiaRpkHHWNMYjb6RIppZUs7I2bQ0PLo7GdEFkiA6fSqjCwpx+LM+djSwOaCij2Hdw0zKq0UbzuinsrfN7YLHVf3UkVYzimEwjbLup1UCU5Zz7gt1MJvQ9wjc3+Q8hS+vlGKGJoqlMyOcQUs8TdtGdEqy3qlOOKeYBilBi/mrbIaE+Jr3UxuEBiglthLpCmp/oXWxOfMh1TcFHj3+6oLblXPutL/oHksiFQGONmdl6Cod1nzD/ptCwcr4FcyYjDGzcAjsv0Jh05KTulkOgwCl9HwnKpDgc8E4ZwZ7xWI+WHN/t9PBQ4mmr9lyDLPmNM49TczrEaLDKcFQY81oYJ/aJBcMdU5j7sia47K0GsI7ZPwd3XvxarGWGc59VmqLxapIBYIYJOK4sdLFMmwDK4UmrWcU3scqxZupgSH6nMViC48vi/2p3xUBLvShtZHqG0uyihQesUd/TN+M52ntIxhUVZsJItKti+FgS6r1MdbYF1EdRzFLrap8qWakUIo1t5JhdxljLbMZ3ZGC2/oZdgdYJ4vSfTE2fy++XCbHFhNkq93HdkmBILt27dqoNrPerrrqKvfud7/b3MezRNY1SfRklCspgkKW0WA5vcbLmSoDazBJsiqbWNU8rJSPLGTaMu6yxOjW1arjz0LVuhOMyvnWGqAOSMec8EWLwuckRTLTaeehhCCgPXNawnBc49qMmGbk/VoOV5Z2SV+VVjLLZPaRUx7/aHzOan2U8u27ZLElUqr3MYaHeCeRDpO6zj72z3LuTYc+6/7RUe83eNPP3JFxTqtsaL8pG1llozfrV6qfGYCCWcHKU2OP5uLUDW/4D99eDM5domuGY6gZDhx3ZipBhuaBqNJBgUuDQaX7INKwyJjB95q9Ys0jojKVBkH6EW/OYKoJh6cZdgSymgBb+iwp3ir3obGi0yesa+A8pKPbBnAt+paB93GsMX2wsuDMNc9ymjtWuoEOkFhReLGR/bclzp4lDG6BZyL9IasimlVSlLdGj1sDLMqe7zb/nPU8rTHE9/C+aJ9YQQi9j3DoCY5ofQ1jO5F2ajB7dZ+tUrx6jrVsTwvU09ecxc4NHTfupsEsEQA0x23dZutJth3217a3KY6L78V41gyNzfWYUvYhbcqGwW5bVZog63Z18xKrkbsFgmy1B7BdUiCIrwxzyy23iO9uvfVWd+DAgXt9rMJ6idxOf9Ezy1CQLIAMSp5BI890iiwnyUL3tdOc2zx3POUXCmVu0K5Jm4Z+Q31Mrn5cQAiINKHqnVMqUlwkCJa0sciIHHltLBsggBAFyzDIxPdW5Z9cfwJdWeXd5Ik2d8zSqS2kf3J/UllyGQaAQQvV+hrcnyJrRuUg3YQQmDAAckEavG/N4fB1kz5anbNBGD4Di+6v84ktFXpGmLIE1+5tJafU38a7n1XtwEzzEOe0AUdLtC9zHrJ+o86B2sVkxuSSe+X7srYj2hS4EV3JApuyQOzANmmgOgycZAFHsj9hUEhor7T6ZB0Zjkx87Ci8v1W9KQVQWWUaedysCmIEmwxAX0dwOd9awL1mxfTj9KaysCw2kMWCywIkimFnVIvrCufYKnfbZ3UyK+22X8al2MRgKOpzyh/C59C/WUwQATpksfUsAVr9fgj2CeZl2CZkdaTTkMMTiUibzUhvkuMpDDTrErn9CPpqXTQLLCmiklOWILBmaYT6mZp7jKBZxxr3GYEHgc0b80OqWcCLIU6fer9E5bmMfjqDZVMzNHa0VhR9BEP/J7OQAo5dhnZXThl46wzrVrNfusnF0bY0QbbaA9kuKRDkxS9+sXv84x8fp8N8x3d8R6wJ8ta3vjX+d2+bn6T8P6FOz4lQrZ0FK9oiJvIwMh1vRwfSiBD13QwhtBRDQkRGGaVkx+Qu5SUg1bVO2DFdRh68FuiCoVCod4LGSLsqJ/niaiuoMVIfL/UlrNocpD5GWHgrS5Gfz40l2Pg5FXEkkNTuLzpiRSTuC8tFjC+yX7Jy+fm90BHpz2kW9FFLoEwBHJaivWAupKKJoMGPJvus7I8yvB8eLAp/r9NELPHMPtgaqd8oWtsvk4LGlmAG4XkqrRHJIMqFhWWVEV5aSj4PzBCkzAWNzazcb2GgZ2jcWKlsnir9sfMt523rlVzLFdfTFDTYYzyPrMoD9zYtK52Cg9/6ZFDR0bQiwOIUGaln1nVmpSz2w/5IgcaM7paNaLQGTgxHt9/yqqbWk6ENkbWPSMfJGgPGOi0czgxQS8zXRiqIvgaR3iPm6P7meJ4nU8DciKhb74e2R6y5POsZmmue4bNl7W8yW9W4a4nqRcZ8iZcwzYQM72M50PFvhT5YR7nN9Vl043XqEsf8jQEBpkxmMTGtdOPM6kv82wD/rPU/693PLANrsC9E3yj4rapUMRhmgt6aDVTcnKFIsX/d2GdqDvFYOv1PvJ8GE0SLFa//HSmm2VbbalvtvrdLCgS5/vrr3d/8zd/EOh+vfOUr3aFDh9yb3vQm9z3f8z33+li+LriPdnEiGzrTCqP+AeraemuT7QBnvI7KD6mIn5Gmoc9JA7UfIzJFD+fCBB0PbcTJcwLEQM49FzMCH+UleTBR2WM0XC5XtwiJzFyMGhCrIkMks1oCHHpRU75PR1/Q0LOYIFYZPGMx1ws6hQ8tY1cbOuWl5ICrEBWjMTJ8St6c4kryd21bMXg9+tmIvFUyKZAWkIXdiaMJ9IonUSCIGfU0nnuGkGa/zrBQ1OfuAoQIf6/PaTkiuvF2iLFi2D1ZVYksw5VVW3xbg1FNIMmKkvbbJKMtg4euQKkfe+mqOz3n3K6JVVd+dXtzxgzBHo6BrLK+hlCeVUoyPraozIHvjTKy8XksZgm+F1WZMijpIn0vg7FigfCcu0VlLjX3iehqFJ6T0lFjHC+3OXMvEzgyWE+aht6XSHYKPMttng6TsWaapT6z0kSM4wlWYUZ6U1+AQL/AahRm0WUxSbTYr9X6meOyAixW2o44R5+pDAzqMC0hlWaCMSX1OQjO2/MIn6cY39xG21PGWsT+M9ik+5lShw2lfGSMQVMfpGU79zKYZ6R1aPanBcoYIGn3i/BvtLuEbpYSUG8Nb155LtUwz5ONyuthdTUt0CxYphVDL0XrPnH+Xw4DeXpeXx8fWkProm/+0Xy5uM4WLrTV7mO7pEAQ35797GfH/75SjYtpc7hg5v2u7iwGjcUWjEBO6qUVuT+NvcpCJ+iktgYLtsI0VDWp/s1+5httmza9kljfnU9/KTn/9HaxT2c+SX7uNJJ9CuPjyUZ7dyTnmO2WHN64hlOnk+t86FUbn4frNr86QqWT9pdu3fisilyYrTA5kRzr0J6kb3edTL5fpkXoXH4soSs0rtqXHAuslNaYHeJpk7EyAXAhQ3PAMrz4DIXRoRbJ2ng+vA8M/7VJaXVE2zCmMW7YF936ofNqujubiBjxNHTG1OktPRsrXS3LkbCcpE6fTJCInSvfeyYIj6uptTwPp5h+GB56fwt8KyNvWlfmGL89ebjLu0tBA1/jGcOnk3eijooZ419I8pNyNTloFh+ybePz6o6CiOTNYLvqqcKm6QJ9N2Fg83mEN88CUy0HNJVG18e4yyqlyLQTRoeFI1Lpz5mU0Vj7eQqHRaT62Aa6qFRmVBIS+gW5Pp1jMYZzNkAkwInIdEyFRooRuc+qqGZVcROVe1QEl32wxBaz0iQtcEGkB2kRX0wedKgtxiQDNOkAQ39AhUhzyND8MUvsWsweMffJfSzgQ4A9CJxk6a2Y4HSkbDWszUK/zUjHyUqRs8pJa8BP7G9pvmF/VHdPNQGSZgC4JtvMeIYpJkjx3jNByFwm2MBnmGWbCABWgL7h4JfumwhcYDxVFsMMaH3O+nghmOKdxQaibVNBIEuzT0qL3QdUaGXkIl6EbSsdZqs9kO2SA0G+Um3Hx+ZdsVARvN/OYDKTNSYktDtya2IFLR9JOIpFY1JlpL77W/K5OZQPRuEZ6ddRNpZEJY2ugXKJnUIpwxnF9TzkcaZBx1aebwcBooHzyaxerismyMMS4drGtoRn2xrgKmme0uX3Xr/xuV1NrrmFEoO6cTEsod57fu/lGUwO3lseqxpeZBV7RzgCwkHIKGtopBKIso6WY+zLcV5Insfq9jATREcxuKCz9FoLRvEAjhv/BnaTcDgMwE833jcrqqQdAVH22Th21hjoRxgulRJlOCYWhTiLQSVECHEsjkc9PnjNvDbe83qC72XvP2hHpZb3Jp+XDpT7Y1ShLR4OV9O48JBJ9FnuI5+7Pcc0x3oUYA0uWKUZKUaboZVhgZFWGlrqWRvPPauqgyUOWJ0Np+jpVloKs7Z0BLcEYerGcD7oPJSQslhalAjj7DVDQQC1BLajvs7Bs8kxWkhn5BxdAwCrx/3A2WQBbFcIIDPwoK4TAQLJeuLcrVkuYeeU95DzbUqwm2PFcMayBK+tSmEW+0anowiKfYZ2Vx3r19pUmOVZmQ+D63o74YxxTlS3Rqyt4p0IgzCarWcxiLLAeSHOXmsHA0G5tp32WppPFsROGe9UG8GnEYkyinRdkWoTZtExIKJLK/N9L2AtLs1JAZx8I7mhtZ1DwcAY75leCzl/5k0hUJt9Iso8w47l/KIZM1LIORfcP7VmG+OL+/P9aKKqk061FeCdkX4Zn9IQh5WgM5kgNuOzPpoLV8TRorG4n2WkoxI80+viuiZIR7Nct9pW22r3uW2BIEY795hxVyhXZY5eRqWWpb0JEyKnIgcbu4DGOHKiZZaVJfujeiYBVzpV+bja+JsMhcIFsC/WKAoi+9W4OmE4dEr5oO5GXtVtLV9QSZjr50SNwtJssk17UvI1cqgIU7qQ9C2aTry0wpq8N7JCACJcMOLalWRVKdR0SAMG1XItbMAoxe2owpAhjKg7j298rj/xmo3PA7edF/s3dyfjoT1QDBo39W3SG6XxToOIKVU0DAhU+LYMNlIZTKMOtDa0kFgTRgyBNLYUJdyqfFDsl5KOz1Y0NkOoz9RAyKLYGxoI7T73t6KcIsKj7TmjQoJIaVKRauGMAbjQTuN6G7hgR53pPFVn7IidEIplfrSR8qFbZvWhfgAVpijknSOreuTOXDhq3Aqz6oQjkjUe2uFr5rHaykCXVU/C0X19nXzfCErxemqTdFgLtk7AahhEaMDwjo8BgERo8/AdYs5GTt5cOtdFgo+YH3SUcm17OaybhHtIJsjaNtnn5d30WIJdTqVliBQUMpUMocIsoNYat1nggKyIRkddHqwFUIcOYHMw3GcNppKVIcYDHOg0WBN2ztnGvpRQwNpDcmEoziQc/agMQL2Y3PT8DEri+GPsmUp+W2QYH2vMQPJAcnX5sjQnERRBUCVrzROsCgACvOeSLSGfTQO6YlLvhRQkdW8R8ND9CYrGq2dTAFN4ZQfW7GUEIbDmawC0NVQIghCcB1KgMS6ntEzEMPlYWZXPg6WiWfGP+wxcaIXvWTzfJcfLrzWCz7nw/v8S+7Sf/MhkH9iKgsWM+1/fIcXHagBNOV8LYFOz7QxAm0HHCgJ+g184Jc955a6NzwMX8Azw2Nemdd5q+D2uziaTSvnOc3Kfwe61ttpG3fSLtfl7EX0FjrHVttp9aFsgiNHKix1XLPnyMJg8RblBG8Gm4WcJu80iRSIlwrSa7LQCSrqOvLRgRAlqcGckmEeunQLLIJQRAbWa7hvbPIrQgbWro6lryWLS2J5cWx0LbmVOXSgcbRq7IvKRVWKXh2oPBfusDRVLeDF61GRwYZ0/uts8pzTEqTQot+sn39sCDfSiLwwiw4EPVVzY2M5Q59fnsaoVSNAh6k+MNWMhEw4o3i8+wyxqLxtZO2aZzQxav6TJdsLRKnUeigXXJ5MBUV6QHW2OhFPuaGASFMvSFxHOqIisyu1IFSbwIqPeNojST7nATMFPPHcN0tWmNqeU1yfC15ZK2bDenWjzCjC6kVFFp0KwtrRDbojL8h0cOS7pDpVzCQgeIVLdQCreyJ0qaryaPKzcIkD0qSRMurYnSZ4vLcpz5j/8maRvVyVsuda2ZO7MfSTZJqsVjx5O+n8mMepzIzKZv3H57mB0m0GAVCoEnPDW/u1BBzSVcohgQXsQYNFIKexIFW2HSTAcDC2ebn+Sz03MEWR8CpHSDNBZ6iEU7Ci+qMQDNg/AmtUDyXgoLctJYfXIZFDAnA54SbFhC8s0YjBHLSWwZg5jOCpJ26K0kLxUhXryPPJgk3bUPmu7kj5UwUAtgllKcL88J5G0DgCe5jDm5Xl6xgoMRcCIAEl5NnkPWziWBgd4Dx1SEYdOIihkBCT0GBiYhXN+1l4MRHosU20BNJTPgJIQj88E1KpgneI71BhPBmt5RY6h+lTyW75eDAbZWt/4aLvPFPPG/ZAs3ZwJGIpytUZZ325/8FveYKziPI0jSbq3voer28rBdBgNqEs2KoEsvB/qPMXV7vvVVqLxF33bAkG22gPYtkAQo61ty7tCJW9SoEkvTzVhVGN/o2qLbjRUSEnU9NvqfBh4IWottEIMwVXd59LcWpAiGm8Go4GLWXGxHtQU6TzpOrF/8a4zyecyjI7didFVPLdo1lyMBsrBvnUMiqpuQkcFjJPmSNmMYvA6RQUWLsDq1tJAplEvREYzQAzhqOY2j0bHm5X7AGG0gW4YCoIdkKH63tf3OpLWxxqeoqwapS0pRppZfUOkEfVnRIgIv8jjpqNsAxJSx4MUC/az3J+gbt34vtFnvrehnxD/LcSfGY0MR6q14VmZ7wRLYpc4d+mUDUS/GqMyZWNDSSRybvqzrVRkV/etstAOOigVRNV0o04PU0PooJTnZafpJHRGE+drdVfysgwqZo4An9qbMxfWtsv5tjE6GnRk6JjWVDS0VUnAinZ1Mjj/c9w09kpntvU/HxdmIOHjoJrXo1J4jlyeSq6nXdrR1/vN+7Q6PRbU2vKtvJwAKQUVxQ7N3fHxdlXCul54pxmpL7Xt9IsigIPGGED8CxKUqlzAta01gyBAjuV2dJoIHMDGeCWc5ojgQnwIOmY7q+E5DZdWAzAbbyfKzxeNNU8LplSDrIZce3xTJ1P3jWkBTMlNVT3Bds2hgU2B+tqUBN8E+MT0BTA8UiwbF76G2sRguKqSmoboqAsNqOFBu2w1GYKG1kS/ei0W66i8v2LOsbWJ5LdCsxx+hntLfYHOFjsu7k8zvEbQpiUoRcasbyPHOVbCIEQWOM5zWgEGzSZqDic3fugkgDAAcSndJdrOAI/Kp2H71uTNiYa74zt/qTFBttpWewDbFghitG1fqDnP/CQCnGtmGCqcmOFAt4bCtzglcorDDZxNohW17RUTBGFuaWWuHTSQaZyloqmMiLMMLCZ1nd8sVdfzweusQvdD5y+2DiSGcBPRTKbdNC7fZvZTRFsMYdI6r1kZQdI4KmWU6+MCCjovo4wZ1WGE4FrLMKKVUc8FnccrI1LL6IpuVt4tv9caLyKPmpogeJ6a3m1FggRYhP7TMY5/YyDNYJxo4WGpLh+O9BIITJWgjsJl9ES0SO1DsUMhOkfmvlHmstu5PspEqulB5PwbESp+bmalDRkpQClQS+xDZxb9sso8qzQ/mTZDD0Puk8MNkaynnHP/mOx+7rrw/Ml9ltvhOS5fl0a9ACFEOc7wwxEpI/H7irlYlEe12XbWM+A9ZyrF6B0y3bA5mgyC0lIyCFtgMUTKUS9j/o8ggst5lHOaBtIGziE6fB79obYR0wX9sTEn0GmvRhaYKydMspv43gwDUOA1a8efdHmmRkZF+QxHb02cjNqOoSD4JVLUlAMrq2aVg+t/q0dbD+0TFQY3ZYymqrgZ1X5EZZSmBjHC+/MZEHzUzdQoMRhUehzRUWdQJ8Wg5aHp5yJ1VwqDy/1LePeqMxyDDHZ0zPMLcVgwa6oXGua4kwwgOuTtcD/VbW5irIl0Uq6LWvsE7/RAFAZzabNo9mUDrCOma5PRlsXYZH8EaItUvpZSqjdLBgutELkPj82UIBE8Yjf1vTWCN0KoPWOOzmNB9RUiQ3N0bXzAHEOrCOzR7tLsLr7j5cXkRg0OT5oMomJvfLVal5bb5u/Sl8ttucS4MVvtfmyX1tv0FWz18ZJrl0pi8pXRKnuRMZ3jDAOCC05jdDCYoy7yu5UTTSOSBi5zOVP6A6wcA/EwgXSrftLYLNx0d3LO+YSWkt+d5EiW7paUF25XgvNU3JZM/m5Kqj22bz+WnBO/ReXdQeOmOiMtVzJbhL5HAaJiigkiHBYKVyF6l4eOSH1SR/TDtOcsJkcLYrmiCgCiwyKFSTNJjDKLFMLUDKScCB+F99crTLsULv1CI1ikgWkgjYyqAasqgwYZg6c0RSn1dXJ/ClFaJQp1zj4ZWbJMdGSWNWxZaTvcTOn08DyMRooS3AYIpAEnUdKUWgQYj7o/IoLZsqKMGc8m6i9txirZqJ9zedGo0mEJjhplS/WxJUuHBw73URvswlHFOLHArvg0RYulA+bEHulJSCZiadOUrvg8NL45JxiOCBmK3f7g/PtLm1biyHqG7AtZMW21lnFe5LNZ2TWYIdxYCr6HohqLeh7LO8c3jU5bgGu6ZLELvmt0nro7hc9jVUDJqtIhBIExBsjGytKk4D0UotjK6SbFnxFt6pXx2ep+FleaQWHS9iDGE0ADrZ3VRpCocjaZzNd2y4Ejy72GGbR0+nWaiQgQ8Nq4na4OwzmCIDyCR03YYwMAVOJzIlggKvQh2NCCDRdvZ6wLBEc4j2itkoEZCCHjOhl8SpXKFkBpeLsK1lIKGsfblQyNs0q4//qcYkziGRCwJMClBaNFOWrYE1rPSAKQyXYDM51gP1Npu9SIYarTUEbpc4MJyDmpxPQyMpfbRqm8i7VtpcNstQewbYEgRqvO1F2xmHPlBVIHko9t5oXGi0FYhICTIo0RTQUtgT5ahghWAxoBevLuazGlfoCavNtwhiznuqquK0LOYufrrtj4PHg6MVRWQZ0ki0Hn9zZB7c0jV1en4OQflpwnQild0hCZS0mtFN+KEO3jveXCmkrZsAxK5onmSxkpI2HDszNo0zJZ3UXoJMCZJj293CuZtt7q4zDCeA9Qh15TPCn+JYxIGiD61hjRK6YsMMWAOhe6D5YDraNSNI4krT/s/OjrtHKFyUQR90w1IaxWCh9Xiz1K5xR9o8OjMzaMLkRMCaOTqYlBIlIcpl2nj40/8puLpGalVLFl7SNEV7md7mdkpDcxFQBkhSyNFCsvXgAyLRvotirHyLQEuQ8rqsg0STpmSV+GbmaBYOdWj04GHbvKicVgao7WI6jckeRiRBC/rO0Zta+TDg+BAqQcVmaktkJ+ESmUg0jZAGhMB7QDtoY+Np1r6pWUZiS60B5D+kALDmyFJck1iMH5DilF09UwWKTWea6tdMCEw6gcO1F1i9eJ+XIVpcpTY52vsZHSlCWMKsA7AVxgTlFR/BbuIedY6qXod03MxcKZxfUD3MiriLaOfG8ca6hkrnmlC8mYyJ2bTa5nuyqb1WsVVa0uOo/3rYA1BgESirHH1zAj39GQfk7l1juS/j/hoWK7sc8m2jgR3pX252/a+Dx05WXynDfftvF58IqjSdeqYGICYNKtPlUJ2oQlVrFRY716djW4/rQQMFrbQTatHINcT7OqxbFxLqbdVEaJWtpaZH2ldDjICqGdotZ5S0vMqrSmU++KK6iGuIB3GoBdQ1WxEVWNWLVrCdorSxLsyJ/qjpt85xIDQbbaVnsA2xYIYrSlgwNxdZginE46o1mq85aopaCyaiYJGCdE8UUJtZT4WTtIDRZ17GFYFFEOLt5/GUJcoPEJsGdkwFaNh6GUO50Y2wM7p8xIWg5GSBll39pfuDk5x8EDYh/XQXrRPSeS89QS0b3StpFwfrUSCiRqH6HkcX5GioJFuG5SvwuoLtOYTvKLi8tyYepUk30ao8nn0mo4Mqoj9JKuj37hfq6l2CebMzl0pJogmxBxxKFT+axGtFsyHGztEzNqnJFeJByBPnRAdNlQEe3G54YhXJw6dscwiPjYwzZ8UPBzYxfNcDBkLKzzaLCoioiwYLEJQ0/RbNcM0JT3M4PhISKD0OewGDO+1ZHKx7lQR5fX2TVZzCBB2yZDIeN5CEOa14PPBQjz6QOK9CLMtzWItOqysDwn2VBsa1PT1ikF26A+loAjFaVdwmjo6vSuMAiflSJH6rsBCpWW5cBt7RkLOo1rOzDwM0pbiqAAtiuNQ6NlQrH1DNFvjhX9flglWglCmIyhuOWD0XU650XlvFB8k0LjvOYytQha9hxBcNqq2BH37VSyTrfGqsEghLUuxn9S3wJMEKZy6IpReYA/BOSrYB6U4eTxWPH+xqtbn7Cd+xqYoaXdI5vqgqXm+Cu3he0mjBtel2+F2v7kM9LA6gj+NK98lJn6tTY9HdYjuuyxpu5E7mgiIFrj8RDIYWUpDYoxeML3W2icpYS9B4JAFpkcHI96jRs5DkFbsrP4fupUPrxHpRmg2yfPJvuUALxMg0Ec27EIjE1Wg/eTAbP4eHyNjDEweDdA55sSgMu3wnQyhlr7p4PnHDoTZcxdUXDuiL54i9in1Svb3IpsrauLsfk5NksUv99jbLWtdl/aFghitJFja65YjFzpGEqfDiSTaksJbNFJK84lk3cTivoRIg1aE0SI3tXCmgvMOc3S5CBSzQWrtUuGe/LtwU0XJi0sRxV9LhIlqr4j4ldYkHkJre0jQeOqBB2RhlKd5wJcxAJYPzARvJ/a0CktIXdb1GHHOcBKSd0DXE8bUVbShLX2C++blUNMgEun8ej7Hro2PR4YTWUkTmyjjjtwrr5p5QRtUHJ8ChV8LPpNAD/lBblor9IxElHXsHEX/0n2CemrzIMms0dr9ojqMuInnF/+TZaILLeXfG7A90s1GvUWcKSiqVlpSMYRxF9rSKkSIoiiRK/On8D7ammf0BHTTppgZaCsYm1zECgtNOvcZ94w6nZUFtzZ2qh71r8n38udwsAP04GyxDcHz4M5gDmBVHFN7xagknF+zQIQ4LThmFFDSkdTy1h/Otsw2JCukLtblmwsrybrT+uxSRnv4gLEqz9348bn/COvFfuv7k0GeAlOSeX4hmStcw3p6BOcLu5J0hTzHz4VLH9ZWlZR59NJRD8Ptp/QHrn5TrFPB31gOmXrQsIIKO6SFRbYotVkbRraBfCJlSg0K3GeQgEQvN41GhQljf9GFL0EEcSBkwnwvnjluFlJgmuRSG9luoECshavCE9M+RaYA0XaJnI7yXh0YU0s9X4RTKOjTV0y2hkajGW5dotppcHUynwyVooLKMMKQKKItAKxrvnjLYYFdcU5e1U51luO4rYYH0Vo9mQ53awIxnWegMjAZ5IU4LhNJuNj6crJoD3DeUinPArtKwLKQqRUgaEQjhf2EJ4n7QyyMHxbmwrPl1x+UlXcdkOwehVirFeH09jSJclz4dLSTJvKqhyHMTl2Z7KAtYeTvjS+4eFiHwqbcn+RAgRbUb9ffO7l248nxzqwT+zTGRlMhFG/8Lfukmlb6TBb7QFsWyCI0ZYOdJkgg0O7g8JZVM7W0cQoP7SpoJSmINO4qM6CHn0jaoXXpeFZuyrpW/VMYvjmwVaIaEQqx5ITO2m/dHILYH5ow49U5w6o1tEnPr/xOWO9cRWUTxSnUH9HUKdv3XFX0jd8ruzfm2w/joiQSq/Jr9SD0S5GyOLzDJfDdGaRHx1e/HxrEiyiAQHHSkdr2mCP0FCwjMOcoiOJaKjBYqBORXzsIVYOCDtpuhKSMDwii62BTfarCkOWboJgG2SkJ+UthgajWqrPRgqKdazuF9hHsC82p8/qZm6nIhhWfrBZPlndJhqy0nlwYX2RWFSZ45jU9eKmkStt5PM9GLw7cfKaE5JRxjmG80XxiqOucHUnNs79da6niGlwwGIjDZ9smoK+BABXdvHapBZUqMJFfG1knIjSzOF0gbif21mCM7dpClBlQd7bpQPJvFZZ6ISN7ckjYh+WYGbfFo4g5eP6xzurMWrsdbE2+j+alKGtzCqdgyt2Jp/JBHni/mDUuD4unbQ1VIHhs+W4HdghwRqCsy3BJjqUfK8FlqlRAuCc8wVp/DqKX6yNBFlPA2fWwgyLmP0Ip9mrrffa/LXjQWHzklpyy3ONoG4GWSk6ol5C2idTUrkuVT74ueQ6H5UEIXxrjJUMbQhO0va9FaxXPIMi9klVQKG4La5Tgj0KYMJ117dXg9+3kE6jWwPsovJMPawdosBLpp+1kIJCQILAjxa67ZTC4ubUaKk/ZL/8DQAP370aS7KSSapOIbVs+rNJOeeKVNm2VU1F3qfKQvjY2lYS/cT4Iitx6C4wdflsFOs3BxChc/Wh4BrDtKW4HU+A2s6Vh4KMaKYDDd6egKzxPqNK4KjX2ng2w5+VQHVzX8KWLp1Nrq3+qCTVKQ9wPO73p2/tdeYSTIfZYnJstQeobYEgRhs433TFYkHkPhfqyaRWRE1732q7w+X6hHo30F+tBcByjEyHWXrYDlOMjm1lP6I6+eGwA6/EsmTVEkaYEB7Yp5KFjYgGhdBYFpfOjmbDtJGTXZ+qmsZRkZUHcOwGHBZLZT3ug7hvoHiyioKmWhuVgNYVuuPzY5+UnkSGeKXVhGgd1eDPt4IGodYxscrvMgpP2rU2Ymhss3IPUxe6J7botNwm+ZiVykCqtwA0tJAYDCc6aQR1GPkhCyHdH/XbRgfULiINKdznzMXbeAZWlDN1HpEf7cJpFVrMlWVtjWvWVU/cQebpG30xtFu6Bww/wwUwtbJa/rrHC0BinYHhr3+5B1ZkidnJNAsysFQ3DSFJOg+CtZUxHgQLDuwRnX4xeCJhDsxfNWrku4MCjrKrvhVnk/3bw6AwsdT3saTseHxto4mj3jmRGN+Vx1wVdHI1oEHmWwnrHEHvwnEwJGPx5olgmmWuje//7dMbn8tPTdIF4u0wpxCsKr/vUxufi9MJCBO3ibFg33ifinNKpRSAhGu1gizP5avsdE4+HzLnBCAzLlFjARpiDA5cQCoFnGYNErPajDUGc4ppxfeAoul0LDtPe7gJohAgIlhfH83QlwJoWMA7oYGL5JxKzBXjTlxbViQFrXKekXuAmceg4bGmFLPxrkRIWyqeT1hP0U5VrQ5jKM9UJ9gZo3fPBXV99DpLZm1psREM1mjtD4LTZN8UwdzQQQS+U1bp98qMnAeoucaULpEag+81k0SkeCP4I9b8lr3Ol5eTzyuHR4IgfmNU6Y0dujoMSF/7eHOOdo9L3neuM0LsmFpyeRlkox4RAVDaPUvXJQFLzfaqAvArz8Jw0YyycjlZ12URsa221bbafWxbIIjRVnaVXKFccs2R8C1qHKiYwok5QylQRNB1BJe14zFHD8yGlbzTVMiwA0u2QgnlEuOGw9HYbUyGke3uNWCRgigZEfkiBMo6e2WOe+FU8lvrxMmNz4MQAmM1mPiccLTzhxO9kOJSOMKTP48QhDJwKepJw0I3GtWkZzemE1CoilLGuW0V89kIEIDGvkpZoRMv0nsMUbEssTEeiw60ZjCtbkOUD9HxzPQFRogsIcrIBjSEQ97pr3Qejbq17cyhCZ9H919EwohvESjIyjPlbWOU06D56iby3TPYJ4JhkFE1JfneTvuhnpEoF6hAKat0qwX2ZKXwsP9aM4BNiNiK1LPw9XB+1c9XVi1BP9X52W+mzdhgUVaqUn7T6k/xecZHgxpABE1bA2BuTCt218FkLh69HToPTMu7VtKmhW7D5VNBzQBeG9lgaZZLJwhgu73SMaSTRKefzDn39OuDuiVZYzD3tAQsaSjQl8C9JapZ2w8afXxwFxRstph3ujXAECyuhZ3RVNqqIbpdmyr2JehLoJdAg3jvwCKIf2OKFxw4OpC0JzQgUT2XgAXN0UqYwaWui5XTKPZLhgeBDl16lmAJ72EB40mDNWKdRToon/Pa5Qo8M9LVmMbUnh4J2kbxeXrOqE6VIXt0Fe+dXhdW9yAQg2BLcQVzyqQE0spgC1QE46QcHE+pqkaiillYDF3o93iz6XQt+DzJ0mEqRyrtB+cZmAnP8dqmFcK/GAO8T3zmDJBpZgxLM4ty8+p5MGAitFMwNipnlmydu1MJINx4yIE+GS8umHbJ94N2Z7zdQleXpL2lCZJqW5ogW+2+ti0QxGjb/uOcKxYqsjQX0i9GodAdN05YSEGJziQTZG57sjA2dyKk4iffOxPhp2gMIp8zyMNWNHRGMdxaMpOXRhJHvXXL7Rufi7sSynJ8OBjoAs0eqdgCXTSKQREUy0IFaTafSXLP4zaocisC0buoJSd/4YsitSUHg6yN2u15UI41XTF/TxI17ZxPxFyLOyRYE60kUHsO97kAAVfm0ou0JX/sieGw0XDbqfDzi0+KRfuupPxw4eD+4BgsqpxRh2fTgpNSvBPnHJbMnggOUG4VaAmrkSBNRwvtlc4kgmGut0jH+/REvHxrXntQ9pNAFPVj8DxLpyWQxetm8+kT623l8knT8WDuOIX2BJNEOT9kEBFgodJ7poCswYwRTRlkQrySjn6zP30OOuH1UebzGOfXRiF1chr9lbsV4pmDxr1JsTL4Wd6E1/9tLa4CWCjXXOtoWEiU+wtBYEOUOku8Wujs4BXQ6Wo0arkPDedUGpZRwlmARS0j4hhHBuGM4r0jYqeFOCt3LAYdwIkvJXPa8oEhs6Q45/w8Kh+w+kT0yS+IfYrXJBTzHKLogzPJe7x27Z6Nz0OnVcpIOwyc8J4N3JOUV48bND3omJBqXoSTFl9PLbnWykkwMfaOBnU3tC4Mo8gEHuiMaUc9j7lobboSHAOCoaHHEO5BbQJOEsaW1oAoUEQXIqXyuHbKh4MzSQZplC+bcw8dYrKjCNiVoEtTUveJjUylErQ2BEMzfvfB3ljEy3tXolFT2puIA0d3J9/H1zAxHlx/C9uS73OzWOP830vIVzqQRPjLJ5Pxmb890a8p4N3o7p+8h50JVGmqZaQ5LCPdmULtSBWe+Pfk2hqHps13mjokDPIR9NCgkAArMFbIxtX2Kcf02iQYrKLcesEct+Wl8LjlfFWbKpkMC67TVuCl28/kcwdAb5GlxitjQZ2k+BqmD4arXAHsySonbaWBaYZf8VDPDuzUnQubQxdn29IE2WoPYNsCQYzmhc46xaoQrWsesaNSZFxwIszvHQuj7ijb6ltlYE9YCHQgY5GhUWyVjXvUQ5LdNcWSOh7QBKEYH8EV3QdNE91ozaYJLrQB6ghQBoJzmv3KajHtGxNQp7A/uWfFU2tBg8G3PHRMyAop7t1jXmcOqvMR+lx4yJXJNqwUs0+plGMBpCBi4/qDZtRbqP0fngyyQgqXJ/d8zRA/TTl8e4+YVGuW8GS0iPo32iinQ17bjjGU2x7MHddpXKT90oGjlk1jn0yl6ByeCjJoIoAbg/+elBFsXy5zqt3Hk/z3kSPI+50HcLNL055BL0YpwzzAotY2pMHNS6p1hHc3P4PzDCdWVwu6NClmDN5J5gezvGj5+KwJahGkzM8nkayIRrw/5yQEhqfhDN5yPFgWsoDt4+Md2BUUsuScoqO+HANtGPI+Ov9/P9Rwp+ed2zXRcHsmo2D0TlQyYnlvphCpcZcS4Qs0sldS+rEwZEVkkcCRYo80x/AeCqc1nL5XHJXvdB4lKKlBUQbzT4s91q7dEaSkryG6TaegpoSoxZzQTH6rziHlEQyNuA+M4AJ0prA357EWnrlmxlA/gKUxW0Nyjh04DWcSlcqEYLgSJMxFAOgZ3Wb1CuqGKEYZwdAqxhedFwpk6t+ov9PCHJsDemcxR3wbOI/qERQz18EKDP3S+eVgqdU8AhL5AcX+hDMYNaBpAqef4rrxOYuY77DO5igofy6xLQrjkqXTnk9ABGEdgXWVVyB+DilNub1IOahWwmk2hxKNnfi3k+eCa74ICCi7KwfgJOJvZMPC7mmhlLMO0pBx2vrc7aZYcf5CYoPkUFWvzCAEGCpkjsRdu/PuoKjxIPQx2jfdKs85NhYM4LEcdumepml3ueHB4DNkayq7qXT76aTPs8l4yB1O1vPozns2PlcAcHV/TJ5HY/9kULg+xQQB40OAy2D5FE6j/DL65Vt7OXm/yrAPaZ8v75NzbHUG4xZ9pu3f2a3skTu7zOnoUtQE2Wpb7QFqWyCI0Y4c3eHK5YGNWt1Li2vu5FrNlUoFd/DgNpdXWhdfLHQjXvv2TLgBOgKFnDt9btEtLdfcyNSgm+6Vcl0XwVpda7gTp+ddNFhwRw/2nEisq8c/dyrWzti1e9wNMSfcOXdmbc3Nza+64eFK/DvLbNYbTXfP8dk4QnX0sh0p5+nue2ZcLddxO7aPurERedzzq9vchdllN1gtuQNQJfetFXXcnXd3GRSXTU+6Ys/AWHdmTx6fcauDO93U9hE3MTHk8heSRXppfsWdOnvOlatlt/+qPS5/ZSKM2hypuNvv6LJhDj3iKa7C8ruttjtzcs4tL9Xc2NXXu229CjPrz2BluebubtRdoZB3hw9tF8i6bzdfmHOdTuT27hp3Yw0KMkTu/LlFtzC/6kZGB9yOXTBuSjm3Vmu6E8dnXX7XpDt6eRewiWBg37y66BrNttu1fdTthgHi29nampuZX3GDA2W3bwejTc41W21314muU3lk/zZX6Dmr607b8VNzrr7ScNunht3E2KAQlptt1N3ZC0uuUi66QweQux7TNzvu9ru6Rt2+w1OuXCqKlImT5xfc8mrdTY4Nuu3jwwKY89+fOTkfP8/D+7alWA23HTsX2xf7dk24ATBDvCPh+7OwtObGhwbcjt74Xney/D2859x8HDy6/EDPMMSif+vZGddqd9ye7WNuEIJzvl8X5pfdzOKqGx6ouD07Mb5bkWu0Wu6uU7NueWfRXb53u8v7EzwtAcvuPj3rao2W2zk54saHB1zuaQn4NLe46s7NLcfv6d69YI+UPJmm42471R3fR7dNuXIPQFtnWBy/MO9WVxtu2+iQ2zY2JJgcyws1d2pmMd7n8O4pxTCI3C13d5/NnkOTbmC9JHXvVpyaWXCLq3U3Pjbgdkz0xndvilmpNdzxc/PxNV6+b7ug/udb+9ztJy7Ec8Se6TE3wnFYyLnzs8tudnHVTURTbveOMZEfXm+03N0nZ115se2OHpl2OZdzlXOJQXcsl3ONestN7xxzwzvAbKoU3Nzcirsws+wGBsruMByTxnjFtdttd+exC64yV3cHj0y7YiHv8r17Gl/rnefc6vCwm5oecROTwy4CSLl820nnCxBWq1X3kIdc7Y60e+e96ZiLXOTu+GzXmD/wzMduzBGdVvf/Z07Nu6Vaw41PDMVzRGEpcWT8HHFqZjmeIw4dnRaU6vz5RXfXjSfjOWJHte0GeuWxC5d1wbLzZxfcwtyqK122ze3s3cPK6a6TUVtruJPHutd25KrdLjojGWHHV5xrNlpux54JN7S8ICqbzJ6ec7Nn5t3gyIDbfbQ7v3Su7+p2NBttd+zuCzEV/9DRHXG/OyeT0ownbj3tais1t23PpJt6hBS1nMv5Pi/G9+cAopbR3mnXiSJ3561nXa7ZdvsPb3flclE4iadPzrmV+TU3MTUcz+GtSVRFmDnvzpyYdcVSwe27TpYxj2683d3x2WOxU3jgCQ911XWAfbj7/M6dWXBLnz/pRieG3PY9Ey4qJoDM2mrDnbx5Lp4jjly+UzD8OvecdMe+dNy1mm2385mPdcNYq/I7S2723KKbu7DsRlo1t6u3frZ7Tkqj1nTHh7qO7eHLdrh8PicAzBO3nHb1WtNt3zXuRgkkDQ64hZlld+HsoiueOun2Xi4drbafv7/QdcQOXL3XlSoll78qAZpPfPzf3erSmpvcOe4md024wmAydy3ec9qdOXY+3ufgwxIwNreve47bbz4dO7l7Dm5z1YHeu9xjaZ49OeuWZ1fc2OSQ2+bXKjjdy3cfcydvP+Py+bw7/LADrrATVXHGB92xW067dqvj9j35UW5w/R72ppGZswtubqnuhkerbuee7nwY9WwFf39uaXfB6csOTYu0vuL1B9zdd8+4RqPlpneMujHYJz49an2OGKu13Z4eOye30j2W78utPe2YQ4e2x+sO57UTp+bc2lrDTW0bcaO7xwRbcHFh1Z07uxiP3QNg/RTOzsdryx1fOhk/w31Hpl3Zr1VLSYDl7ErHLS+uuXE/vneMOnc0uU+rp2fc6bsvuEIx7w4+PnFm3VK3nxtzRLGezBG7u/frwul5t1BvuOHxQbfDrylDCQCwdusxd+K2blT/6MMPuNxhBH/qdXfPbWfjOWL7N36NG+k9m9xCF1CIx/f5JTe4d9rt6q337cnuO9VstuI5Ir6Hh6ddngLyg/nYjvDrr7cjpp5yhQBdF/waeH7JlQdK7kBvDaz2hPbjOeLm0661bcjtP7DNlcsFV8Rces9Kza2s1GP7btt2rAulglteqbnTZxa6dsT+bakUPW9H5Bodt293144gG+qst8UG97mx0QE3vX3UlRAgqXn7+54Zl8vl3OGrk/dx/b07dsc512p13PTsOTc83l2PCr33Z/bcgpu7Zc4NjQ64nfunnAP7xo/de853gbnDV+x0kUrFPn7zSVdfa7htT3usG1vX+ukxdhZmVtyFswuuerq1MUcUegLgfj2+/UOf3ZgjyocSPabutd7jVpfrbmL7iBtrJGtuYf/eeHyePTHnPBa7v2e7x60HnN/82QQsuxTaVoncrfaAtmiribawEMvzx/9n++f3fzF67He9Pvq2n3pb8I5d//1viP99/raTqd9e/jv/ED3mu18fve7t/5r67eOfuSt6/Le9Pnrad705eNxvec5vRE/52l+N/v2jt6R++523/Gv05Ke+OvrlV/516rdbbz4VPfXxvxI99Qmviur1Zur3F3zLb0bf8NhXRu/920+nfvvTP/n36Ouf9KvRS37iT1K/nTszH93wsF+K/507I++Rbz/zPb8XPX3fT0Z//tv/kvrtfX/2sejpO380esGTfiX1W6PejJ5+5Kfjf7femL6Hr3rh2+Pj/v6r/z7128c+eFN8Ld/29NdHofat170sevrlPxf954fT9/C3X/LH0Q0jz4te87N/kfrtS58/Hn3DY14R3TD1/OBxn/fNb46e9qhfjv71vZ9L/fbOd344esqTfy362Z/5s9RvJ07ORl97w69HT3rGa6K5+ZXU7y/4+f8TPemZr4n+4q8/mfrt3f/w6ehrvum10f988TtTvy2t1qLrn/uG+N8dJ86nfn/Jm/4meuQPviH6rXd9OPXbv37ilni/Z/3U7wev9VE/9eboYT/2xuhTt96T+u2X/88/Rw970Rujl//ZP6d+++St90QP/fE3Ro98cXh8P/Xlb40e8lNvjP7pM+ln88b3fiS6+mffGL3oHf8v9dttpy9E1/zMG+Pfl9Zqqd+//Q3/J7r2JW+M/uyjn0n99scf+M/ooT/xxuh735h+NjNLK3F//b+7z8+lfv/ht7w7esiL3xj97j/+R+q3v/vPG+NzPuNX/zB4rQ//0TfG/z53R3p8v/Qd741/+7W/eH/qt//44l3Rw3/kjdETXvzbweM++X+9Jbruh98Y/dtnb0/99oa/+LfoEc9/Y/Szv/d3qd9uvPtMvJ9/dvVGeo74tpf9Ubzv33z486nf/vC9n4iue8Ebox96/V+mfjszuxjv94gfemP8WbcXvuovokf9wBuid/z9J1K//c2HPh/tmshFV199deo330e/n/9307Ezqd9/7rffEz36e98Q/cb/+WDqtw9/6vbocd/++ugZ//N3olB76ve+OXr8/3hd9PFP35n67fV/8C/xby//3femfvvCzSejr/nm18X/Qu3/++G3xu/rP33wS6nf3vEnH4nngZ/96T9N/Xbi+Ez09U98VfT0gy+O5i8spX7/qW/7rejpR38mevcffij123v+5N/j3170nDelfltZXIuefuCnohse8r+jY7el7+Ev/exfxPPd21/57tRvH/rL/4iemvu26Dv3viB4rc+ofGf8++f+49bUb2/4od+Nf/P/1+1zH705+obrXxE98/GvCh73e69/WTz3f+ifv5j67e2vfk/09L0/Eb38eel5664v3hPP+/7fytJa6vcf/e7fi572yJdHf/sX6XH47rd/ON7vx34kPc/OzS7H64JfW/1z0u2lL3xndMNDfzH6k99Nv8vvf8+no6df9QvRD9wQHi9+rDzhW18XjyvdfvnN/xB93Tf8evSm3/yn1G+f/MQdsZ3w7GeEj/vtX/+a+Fr/499uSv32+6/623g9f9VP/3nqt1tvOR0/G/8vZEc874feFvfp79/72dRvf/4b743H0s/8YHo+PH96Ph6D/p+3KXR7yY/+cfTUx/1K9Kd/9NHUb+9716eiG659afSCb0qPb9/Hp3zdr8Xvju+7bq/4pXfFv/3ub6XXqn//6K3xvt/yTb8Rhdq3XP+K6IarXxp96uPpefbNb/rH2N569S//Teq3L9x0Mnric14b/wu173zBW+Pf/vUf0vfwj97+obi/v/CiP0r9duKemXis+H+zhh3hf/uz93wq9du73/vpeM76wZ9Mj+/l5Vp8759+6H9FxwL30M8Rfuy/7S0fSP32wY/cHD3p2a+N/sdz0++5b1//nNfHv3/683enfnvNm94X20T+/7p99j/vypwjvvtpr4+e9vCXRR/8UHp8/+7//XBsu//069LP5o57zm/cw+WVtB3xo9/9luhpj3hZ9J53pm2md//BB+P5+ccf99LUb3Mzy/E99P9Cc8SLX/lX8Tn/8M//PfXb+//209HTr/z56Pu/LbzeP3Xb/wz6KBerr/WQH/y12L75cv75Y1wK92Sr3f8t5//zwMIwD662uLjoxsbG3Pe98C2uXBnYyPtdWqq5syfnXKlccAcPbHN1VU3knk92qeN790260tRAkAkyPlzdiJQ3e/mSq7WGO3Fm3pUaboMJwnza24/PxKjybh+tQv6rb7MnF9z83EocHZu6PKFf+miuj+Acv+u8a04NuaNHd8RRNkb8PBNkpRRtMEEY+b+wvBYzQTxSfxAK/HFbbri77uwi54cOb3eFXhS3uNSN8Jy8e8atrTU3orxUuF5aWHVnPv6lODqz/4rdrvUQlDCLnLv99h4TZMeYK4NNk2+24yivZ4KM7B1323opCOvX46MSxy8sdpkgB7e7jsrlP3bT2TiCs2f3hBuGpohPUzl3ftEtLKy5sYGy27kT1QZyOVdba7rjJ2ZjevRlvYgR79Nts3NdJsj0mBtTIqsXFlbdzFyXCeIZKKQ6N5tdJoinfR85kDBB1rUBfARnOWq77ZNdJkgBVOfZtdoGE+RgLwq10ed25G7vpTLtuXwbmCBugwmyuljrMkF6miXrFP3llbo7Mb8YR+2P7JM0TF9Fh0yQQZZd9lGNHhNkeNug2zHVYzH02Cs+EnVsVjJBGP05duf5OIKza8eYGxxnJDHnzs8tu9mFVTc8WHF7yKbpRK7ho2AnZ+P7edn+LhOEKTinbz7n6p7F4CMtY4OuAx2SlePz7sL5JVcdKLk9h5MUnla1EL9rd/buoWd8eeZX9z51j33SP5tWy01NDMX/2qDOLy/V3elzC67s2WL7pgTd3j+DW491WQL7d064au8errN/Tp/vzhFjYwNuuncP13Px4zniVJcJ4q9ViNvmnLv95AXX6nTc3m1jbgR6PD7S6xkvs0urbmi04vZs647vdYZKvdlyd52djY9xxd7tMROE+dp3nJ9x9Vbb7ZoYcRNVzGl552aWVty5xZV4LBxkekzbB67b7vbTM7G+yNFdU67o5y3QjO85P+dWm003PTbkJqFf5NvC8pr7/G++wM2tVdyTHnO1G/vGl3Qv0+8fRe7mk71ns3PSVdff5d6xT84suKW1upscGXTTY8Mi/WV5re6Ozy24Yj7vjnqacSRTWG49cT6OgHrW1mDvXV5/18/MLbn55TU3Xqq4XVPdKGKxN9bW6s34ffXt8oPTqXzz22ZnXaPVdru3jbpxrzG1/tg6Lp4fPFusOlbZYIsNnO1GXP28cvexC3Hk2zNX/NzGlCg/L3kWyrbpUTfWW1M2rvXWU+78qTlXqZbczqckLJHihdWYqeGjvGsHxt2B/V22GBlLp8/Mu/bN57pMEJ8aNZuwV1bqHXfm+EzMBNk/JfNEvG7SnV88ER9/x2jBDfRYAfkrj2wwQXwEf3RsMGYWUdDXR/yPLa7Ec8TRIzvi+Z4VWLpR3rbbsTgbR9o3ntvUlJv1LIbzS25oYqgb5Y0P2F2LmrWWu/umrk7C4Wv3xUwQh5SHY7PL8RyxfceoG9mJexg5Nze36i74eXakLNhivt/rc4Sfr70t4OcIal3cM78cs8UmJ4fc1NSwqAgzm29vzBEHDqTTSW+961w8b+zfNeGqPcbd+jxy+sKiW5lbc+MjAzGjlFoy8Rxxej6+xqMHtovf/Bx1xz1dtpifI4YHy6IaiJ8L5xbXYjtiZ2+tavZELtfZYhtMEFaU82MUTJBxCpB3Ijc3u+JmLiy54U7H7emxGDq9a/Jz/t23dtf7mC3GsqfePpldjseFX+v9Gsj3hkyQg2TAtjrx+LvjljMud+aC23fZzi4TBJH/dUbpuGfTeCYI7JPFz93iTt95NrZpjrJ6US/d4c4vHO/aEVfv2xjfrlLeYILM1zpueGzA7dw94drQVWvefc6d7NlMR67Z65zQLIs2mCDbrjvghtcZJie628fj+9yiq9RX3e51G6Sno9GsN92xUncd93NEexu0z1pRd46oNd22bSNuGtobuRPnYqbT+ZOzrnTNIbfv4DbBFI7v4e3nXGGxvsEWyyEl6uTCqlvxLIbJITeB+98aLrrl5bo7fbbLBDnE8d27zbffedY1q/kNRintKW9HLM2turGRAbdj+4hgwK7Wm+7EyS5b7Gqwk2s7us/hznsuxGNq5+5xN9xjoa2n2HlG6dnmmhvxjNKpMTGG655R2kt18YzSMrKgygttd8+JmXiO2FOtxnZEfG97TGNve184t+gGSkW3tze+m73UQv+u3dFjCPo5IgeNG9+OzS/ELPCp8SG3fxU6IKsNt7S05s6enHelCzPuwBVI8erZibd87g73rxfe7hYWFtzoqNQWvBh9rYf84K+5Qjmc2t9vazdq7gt/+NKL/p5stfu/bYEgxot5/Te/yhVLVZFvTsNCV9mwqlxYFR60UBJ1E6pzELiE0JNuLG9Kh4tK9RRK1Gru6wa3VtVmWUdPm2brUKMEWhdCxAmLfHuXTNlgaUdqQLS/dGtQd6PbcajDQ9iujhKclbsSzYLGXqlZwFKGBWiPtL2Bun4KJQxXWFgLisa2YZA1SBVHicOUTgAWXY6bVMUPo4IIUy6YL54qQiT0JLA705aVJgh/Yz/FuFHnoZ6edSw6Vnld+YDvRHHz8rD6b3FsCk+yip2uTGJUerGOlXVO6zp1CpFV2pG6AqmKMkYpWqGrIvqv5hE4XMIhz6ruUggr+lPYTmyvvrb6xnOy3KAWlSygtKPXYPrizS93p+cjt2s85665+pWpY/nWgBPOPGoKAFIA17cKNC1YMpJVKahbQQFf/U7wWdNY10K3PMbqtuQAlcXOptoUvg2ebQbXDGqCsDKLFvPsVMJlKsV1Kc0fCr0WUe6d6Qq69DlTEC19jjWsMbpygiz9zeNiXZyVWhtCCBPvAe+HXvNaQ6Xg+KZ+DN9JvU6zugr1wsp3QUcL60V8jOnEacvPJloNLYDY1E6h1od+X8szUtdroy8ozelbewhVbFCRrb0dKZ//+QVTvLOJNAdqE8k52hYOrpxYDIqWC2HZC1K3ogmHmlVXxDlgM+jW2DESPA81h1KitQBBikY5aD3HiupHI2WRJrjeyvP1YAWXbn+gcSLEtzG2VNUTPgOW1RXrtJqv7Gp1LqhRUzmvtNR6gS0t5C80bs6umBp1FLfVY2W9lRfkcxbaHflwWWEp8lowS4o3oIHUxrxePSU1sVojhjbeqWR8dm67yxTuL+5PdGY6SIfMXZ4E+Xww0pqjOVbE+FTx6fy5bppfq1N3/3ry9y56h3/d13ro//zKgCCff/sWCLLV7n3b0gQxWnm57YrFtuvUWGoOavKTtoGtxdhCAkx6GxpbQ3dJNXKrtVGpxD32YRsf85+/LSgElpuXkz/Fw4bmkutpjyVGS+EOpaaOzxEEtqjSToGx/C0yx7K9BIHG664Oip86ipL5e3M8KaUbXZVUAymfwwJ8Z3KeIiqzxH2YgbHVgVEPQ77Qy1VOtkMVnPXcbL9dLxLt20DSLVfeLwVg6wBIBm9MAKLWLkQVtTAqjPrazmTRLC+ERSRTTh5EQpvDxbBjpQw6qySqKGOnBCYpYsjtyMSgSrt2YOnkCD+9GK7SkeWACrCEYI/29ygFw67h+9Zgf8CJ2EQYoRn781D8PouHJ85pdUDt0jHuu20fC/BoZQfFGnGorP15TmeASmqTfJNOBlhfvi+3JPvMXDsUBMXEPcQgIrhAgU/falPlsDCpcW0auPGRweTawsCHFjtmG7zQDm5HMFqUoVXifKJaw4WF4DzuWwMOSxWGfH3XSBjQAAilr0c4rQCGKYAb9wdVYER1LjDkSjN45mDkaceKc5QQSlRCgfmzc+F7AOHhdW2L9VbBtVZwPymwWd8FceAV9YLlDRCGLE2lD0UhyWhsOCwqnSGGKsq97qwGgcROLyIecqZWIAC+rkUWH/abHpPsr94vz8QLBmIUg4qN70RzeCJcvpe3c5vs8zo7tnvsctC5z7dUdTM8j+r5enBMixLcajzkIX5NsCM/B1sJAtNxW0zeqfyR3UHgpgGxYV3GlcCkEFBvhoE838q3Je+B6+kH6etZhYhy5rqCVp+EKPWwZJQV68NBsV9R9eXaBLhqqDLmYs62lq896jqXAcCixK0D89ozUy3gZ3XnZNDuYfBpZXrMBH1lIATz5fZrg+Bn3E4mAbj2Y64JAsC6hDdtKj7rAqtxqcqK61fdusRK5G5Vh9lqD2TbAkGMVvrXT7tiruTaT37kxnflU4mhV1yWaupkTOS/sG7FOxd9TQJOFJaTRbq4JBfWNsoP5tYwEYJ5kEK9p6aClV9yO6fD1Rp2SIZEbg2TKeiooqQqS8gpo1aU7x0B8LAMJsm0NFyL2K4DgKS1umqW8vUighu/wdiOeuKe8fdHE5FVT2tni5SgbKhF55OFLO53j+Yaf+6llcQNpV+dEo1lYwSVzJjieRvg4rNmWUA6Rqw8xJKEqWoiWGQJvpFS71sTUSqhTA7jrLQsjbgmojVM1SEotbZHlf81Gp0sRuEJ6GgDVZT4Q2lIGuEauCHIaIEQTVUil1FoHpv3mVVCspxoXW41dP7UT3CMaMjTUNPnp+FoRf8IYvlWwj50eMQYgKGowZ52KewY0bFKsWz6YBNlbm8APKyGUh9TO1ngmXF+zcrgvRFsBT4PxRzgdm1MQ8XkVXErOwA6Y8z5VpnHuwbjPwfqu45u8+/5hyJlDvNiE2VPS2tlk+1AZlGJFVAIAPhr28PqEbVg6dkaHK7U89QlWte3O3AoyFLybRBANfdf2y0dZXmezQErXSrber/qKA9arAG0nlUILquDITrOtEDOPRqUs8ZqAU5zWc2XLGVfXAkfoHJ8ziyDHsFuyN0FtH93Ylu0UQVIl1POLyQDPJpBBSuspayyEjcAUa27j4crsulgBSpdtQ+hFC7ueRFOqqvJZxNNJ+9HDraFKCW/oqqekAF7I2wYpPcO3AZmUF2ydPJgxxbOgKUDZlD+lqQCim+dg6ge+OHPJPs/Oqn+N3Fq0Qx4dVDytzWWgG9FpHHpaj9WG6xAnBgV+tqq0hkFryXDIxcuvasYZgQEBECFEsO6Kh8DRqu7B4JrcRHp5t2+FYJ2WwEVHwkA6yo6HVTyKaFaz8oVU+a6JkqsA7hnYC6P+xz/1ks3i6vDqGrhF3WL1Ty+AsfYalvtPrQtEMS6MZOTrpgvuzzKXtJQIGjhW2EZk/njHho2UBFRII1Sl7EjC4FRpJQfAIectexbJ08Faa45GCbdA0RByq6zDAO/y2Jyns5i0uf8ru1B0CAFLkA/IDeVIPLFc4kx0FmQQIEAOO5JmCk5gCCixC3KhMbbIeLnWHaN1yX2cK4zj8gmdVFK4ZLFLFsX95lpRDDumlCzJ61TU30LddDgB2C0rISp3b4NfD4xHNcesjdcslmBICztLNNxEJ1QDk8Dxn8Lhk6xl2uuo13aSSOjSkRLBCAhp6aWUQ6Y+xRqbTPlQ5QZhjNplf7V6Wbr+hwpIwrenI5KETjRhtfGPgBU1OEUYwUOD+5faVaW5W2xwg4AJjFWU/emGDQIK7ONsOGqxi0j2rxmUbZTU8rb4XLMsRGKbg/MtIPlbosAANemw46lbmQnkdXBlBUCH/qZEQxsIDI5+MUkStveOWEyHEiXF9FpACcEP+Ou4R5y/8K/fz64Dmh6dr65LRgdZ7/0PMLINeeOwnIzuC7Fx7j9zmQflMMsDyRVEfJNqVdjzSl0jCrnMSf2qnSE1hauRUMLe+0oPvdH2k4D1Y+G7gTjRa3zfKfyCDxEtyUlSPPbpGMm1nOwWejYlblMKlaICLAc7+poxA2My8a0ZD8WWa7bSCdtgzGp0175d+vqhKVZnEkc0DyOpdfAaL06UBxQ2BFMFWI5726H2mHgYxGAyogqKQ6tCr5T0eeSQJQ7uA/nUKWEaXcAUGEp3tYpsDB0kAYlgzlHCmYq3sf4PHinHJgLeQal9qlAkAFQsAx6hGBLjnaK3x/pUYJtxuAX7Kx4H1Ri4rPlGOI2msVGUKyMfRqTAyYLrQAbiMFAlpVnK98smcrtA8lYGzqBEtpYZ+tKz4gMojKqo61XgfGtdexuM107ByCLrfL3nzT3EeXrAexxHi1OJzY1y0u3LzUmyFbbag9g2wJBjNa8cq+LisqZhkGqHZ61PTBCDOfFOTn5stXHE4Nm4Fw96KDQsfStikhME6BKaTKJvjWnEqOheVhGXgbuSSb8JvJ2y2eQPjImI/qdsengot3+/E0bn6MnXrfx2YvosdHwa+GcxWMwPB92mdgnfw6gyEOQu0yggCwXHVWcw7H37Qjn+uYz9DXILAETpj1aCRrxcRfIxBguB5+nL8PLlh+vBJ1uX/p245yGToNv8086GKZXiwhw1YwyMgLMKGnjMjvvVES6KzqfZP3ASlsBBppwhsHq0M6sSK/hsZhaA/BN7y8YJwBUJCtEnRPsDQIHBAqyNHtyBkBCR1unbFCrglEpRooJ6NTV+8nnzvNU58OpGPoeEmxYm64EgSs91hk5L2KsUmQuYm1N33LhVEIxX0bJmNTvCvPymddOIEzn1TfxfpHSzHPm4KBoGnsbKYyV85hTTieOaR7pDvF5TiSlgdeuSRymaq/EatwGknmwhVLQ8f6IYheGku3aTCVURnhr91RYq4M6B3BYqp9I0ifj7Y4mTmPuI4g6w0lq35U4Bal0TDrtSCvIwRErHZd9Lp/FHHkz0jlxndHZ5F7Gv21HRJ2CwJzXkboQH/usLGG80c+JZM3KEbT4nLw3+V07gsy93OH9ST/VmtcergTZoEwhahzZEYzOx8cD+NW8AgAXxroGJt3xJAUzh1Shzt5k/S6cnw/qk8S/QQ+C48bh87pGwcYxIKhdnAN7Ym4h5cjF/XpUwmKIj9cIAyJ0gDXDIeqVE4/7+V9fTI6Fd0oETq44bN8napkRxNgDcUrFJqHdI2S8cG2RCpAUPglAA4BhDmOrfVw694VrrwgCezkwS6mpQtAjvobzSOEByyZ/YF/QAdfXHa0BVBtPgkJ5aKyRPetbY3fybMrQG+GcpFOCeW1rR6aCc1S0F6CaAkcK0L+hTdhE6hXTaXTrALzrYB4SwJdiI0UI5uVOJvNL/mGYu5TZxmBFGXYsAbMI70382+GefdepO5dIlFz0batE7lZ7INsWCGI0H6HuFPMqik7RPXnraPxbYqilxZa5P2nkdGSEwKaavLnol2GgcjHLfc3DNz4PfeGs3L9XhUI7BVwIaBDGfSBST4r+I5JcyByiUDklZEaaay7CPUPesvvY58Q+Doh4nmya7Un/i70KDb41lTBqG/Xqcx/t1m7XLBkKs8bHg3HglpMFPAKro8gokBbgYwQV95bOuDAuVWNQhQ4g6fKktPs2eDaxIpf34BnC44wKKk1EOM10tJmHLfvWIpaXC+t4CHAg16cALIWDx+20AvF+5cJAic5xFzoHeNeE7oWNL8m+GLiHZlg0RsL3kPuvbcvbx6CwibjPGA8qKMRrYJrK2lTGWBNaLhDVFHonVLCV+3NM8z2oTRWD82P3eLgG5sUXcu5xlxfd8lrTDQ8U3GyPWdJQY721vRwEQegMFhZWTdYNhSgFG4nsmVUNFqHPSPloP/SKIBgdb0dnhAAwtATEGnGPdPQ7MLDzFxKns8CItgLvivOrwWhmx1frWu/nKNgzVyQOfPz3WaQcXnV58DyFnXBE/LEZxeZcSE2RlXBkNe7zkUNhoUHcsxxTFPwxbrtD/L1xHvQ5Ny4B3CLvFQUuAfbUURmkOKwAeTiTFID1lVJCjnHKmYTT3jwM4GMFAQU1hkSEHX3meBbj1h/jqoNBKj9BqQjprEWVJsLxSVBrdT9AV35WIpcUUO9wrF8OfZI7IKbutwMrIkKlGQZbRLAj/oIM3IcFAycUQGeqVnydVyUslwLZM7CB3N2SCRJNA3zbndgmbbAiCjg/wTLf1m54eFj49wTYp0qoNreIdxqAxOp10FJjHxVovIa05Ogh24IptYXdjxD7dObBUJjYGWTWUutivVJLcm3JdgtXjYVZeKpR86xyYS08niECnAIc94ORTADYAPq7G+aC73TuMQmju/PZxD7s1OUYKowDfDoCBi5YZBr0LZGdDBZzC4DdBujRa9G5C0k6zKXUttJhttoD2LZAEKN51od30iNEXQUgoSbSClTbaey1kSIgUW/71jP6lvuGR5nRnuKViYHWBrKcpzDbpyCeqozIPLQ28ogWRUD0df6jiIpw//ZY0DgtjKkSuwA+CkiNaZ1A3rFqEXNqoYtSRJSVi0dOG9g0QkegGH7j7ck+xZIJ1hR3J7nG7RlEZpuJEVu+U0YYyywXCIelswtRA61dwjxmiuiSPoshVF6Q6ESjV9bQt+ET9aCBvAbnMf7NqEJTnU3OXx9XWjT1zUVGqTNBZ7zbnzBYIjQ45C7Cuea7JzQcmFagmCC6XO3G/rDHCipth0wKVtAg2JNV0YbHJnBAI6ytWUuGboWsPkXgSu4uDkUQgyCMjkpBNE5UtmJGF0AxDQKJCkO4Nh4337QRpkIdGiuVnPurbxl0OyoL7mxtyD3zY+WUNoVuderatMAyOqqYScZYFdotcCxrE/KB8hk0RhNHqASAR+tJsD8CoALLiM9zbRpgsJdaum0hWGkr//+z9+cxkmX3fS947hIRmbXvlbXvvXezN5IitZGWSD6DMN7MGIIFDvQkGBA8kATZoGV4pDe2xHmQrYEo/SPrD7+BF/mN548ZPcMaS3h+WimJFtduNnuvrura9z1rzYy4y+Deqszz+X3vOVHZzaXZxTgAwazOjIgbdznn/L6/7zKExG6bZY/0wHwbMfqVx2XkOALErfbrRHLkZHj94PzWAvSj4FrEgm20GmD0j3jmRTPmaFiJS92H/MKBCdOReoIhUGDN6hQSM/4YRojkdo/uCPoSMFa+Pc7d64LABcEJNgTa42FaDr4ni8RbO5ZHk3N437IRQlaheg4MzvkO/e19iJHFdV/GhkIThxwxDJ2H/4yRiKVj5miwk5pob/9mw6inFs3VKTWqsIdS2Y4ZbJ4c2Off96s+Bcdhz9R+n8MwXR8BTIUcpRZ5U3INzFQw8Sj/oI9IhWZNMwaXwqlGNNdNrlkGkwFQ9/r9SA9yVjbs1JuIILQxkz17MwjiqASnj/MWM/GlZ1Az5tb3wozHMTrkHqS3C3Gz7eefB6MM96ZZsFrms3/NPF7PfUb/hj3+0crwXnzVS75pWD3u76fkZbsnZhBAAmbMaJW/b+b3WW+8IT5z2RkA0ri3SuxB77753QtXTeQwkzEZ37YxAUFiJ+bm0OVZ4nove95ZAhpgsXVtdAFONnvKaU7Xemo2v3g0SnfkMj/1+pmg10czaugMSZsuaCRKhsjbNqklh6kV6acszvONdvKusbiX10CHvegBiZysjpHEiW3wHb/ibX8OsqcejXbSyll0SIC0u2pZ+DNls8yNbCnncPFviMzr7/Cdjb6XmyEpCop1y4Ofz01o74JQtQ8eDmpIjaSIm22JRWTiAjskFf47pVbtMRzxC3253V/rOzP+HK77igV45navDZupopjqIfZtXlIA2KUi8EEJ0NQl+90aVtbicVIWhg0ZmTFqMElpyZ0NZCjg72RvR5PN/GrYw4HXw7xXCx6xg4vvwu8/zsDVsMPwcwS4av+J/aGeA/8GcWkJfVHI1ogBMvpvMl7613HOZKUxEbN4/fTlyvx74dgUuDGmrUjwMICMfP9YWoEpGAgywrCuk8YBgMwUFVckCQIsEzVaXTzOMhwFqZJBI8eEKWbvFbuWjJ7YHdTcz22cCs5D3JC3x0DJw0q/+c9uAPQ+ZVmFjkbSxz0gPfygn8f68L0abbCAvE2Z8t9zBP8AlVYmkKokMxuDa8lIYjuNOTlADHp00bxUhzEg5TMNmSSjZ9tjQ3Hb3+YL2LmHZsISWJhI6uB5IlCe49o0Yx7pYstfOh1kUlRnwMSQvcHwxz0roH8VRrfrcA/J9NJHxGyxZyYIqJgkDDH/TE57xkWCvUkGaY0auCbnwJyCQaWD1IdAWH3Ksjpo3E4JjOPeRgYbOxV8aTIUw8ZwVZpXen8s/h2ABjZ12u8AUIdeLIyxdUyFest6sQ13++ej/7Z/dof70ch5RSRuYMNWR1GQP7Y3ss+wk3T/BtMQw7HdCm7z/uL9zYhZmv4qSGlMTgH85Eh5pOxWj5NrxhDgcv8wnpVt1q+FjCpKCckA5j3cjB6YUsZfCfdQJvKiBSlZ/YCBIM0arw3Bd/MekzEZ72ZMQJDIaPSuadp3JajC1HfnJy7aCYotddJsT/gNSEpndLh6t/8GfdKwJ0BTJe2uYxiGjhv1sHRPJ9ujHVhMCmxA+HfpVjvhJ6KxDrJPAMLQbKwdVyObC4AwOUCkDgUYnaAEnZsa6TKlsEr0vIXct6mbvvsf0G3HhijHpqk4CQPaJ6HZbf7uLL4n6MwEfpx0KWPxxyY+GKCSgmK8BtSup6BbUhOulOzeeX9tlwNgmdtlAb+pE/huYJnMb18T7Axn88I+EbBg8fOvx2meOaitSRnupqbzvSC1uD22bauCKROk86oHxPR5UH03+O+QY89C89DRSrtBn7o8DHvBUC0gPj8ZNn40cKUPBwGdDiuD+21iNfxM2ayaOGScD8OWiPjFdI8zLJvRzS43mwR+uFluvsvy82UQQDBpPTge8/11Y8RuKjqDZIIMrhXR5ILbM/4e6NMIG8+AAejazwwb8NFMtn893M1tX4OOvvEfAOhbb7YGev2z6CYCjKVcwfz9rJwnSlhgRkrjRZMG1gysbemqFUGjQUav0+RVDWHJlshhxpqIqXO6HWkgWFcSzIM9zEPKKjAAJgEe+sVIkUVgsHcVLtVYixykPXf/EM8+AGl2vUnD7/h7YAzO3gomuGhy3PRBD1zX8AgzscLwVEmWSdrdn3s2qnvOextMf8l3wZPlwrTCdXcXPROkAHuSiXbFlatRGRPZPBnZmzfC+4+7nwlAhAkmZHLwHpYCloPH2RmU8m1AUwRS2fJVsJEkIY8SM+5hjGk7I5fb+zALRqemYLn2zodZJc3ov+oBjmoXAKovvOj/SL6zSejhMcMLhnuQKVyn9nMeQ1rOm0gigm+SGso7GN3yuWGDiENh5eV49uc/9lRQOkb5pBpeE7BKv/lW8FnheWlfg3NNgIsMZKbzNKOETDLhHAVPEX0mF/Z3abOYP0iKmIkcZjLewzEBQSKjOHuusdh26ca14RhAUGabUe31xWXBzfNePxHOQ4fdoXcnHvjIqjKsERS3aHpVJAA++LNhYjxiN2fUW6fQnrtD6IiIVpiFBCf5Al2levdMFAEnTdRsL+EETrpn5zPPoQAHnZfpAOpyXmOzRcYNQSSNsaOBnjFwE4+Txc8Hst9+Dkgi9XQ/SOEuJGLQbfKa5hwb7AKaZlOgMB2n+RWigAsALwkc+YegiLbvAXO90eaVYfaMJrNg4zbcCR03WBnzMyuiJsIsrlmQ924m0WIwR5FEQIJddMp+hvgumjZjIn/JYpCil74JK964HAR78mPoqn3ApgDwe5M5MHXeplzERnbF3wP9k1XYNFBAxpL3eqR4yFbY+4aR2vWlK+FUCRQ8mpbAe3rwFjwHUBRpp6ZAnGIKvXX53MOLLIXmevbvyQw73kSYf5Ob0I5vWBlNJWIKyjQK3fR1D0yWT+wNewQ0foBnqJ1Kg6wGTTsYwTy5d8lfz+w25mUcZ/K27Y6XNzGvkcqPIrM6Z5la2fatYX8PyARp9FdjjWvH0VP3LTpTBaoHq4LGprzX6jf9d5lWoADgukk9A/uSgH77OSh602X+fqpPnQn+9/b9+OzMw6QU0swKhV2PDEMtotF4KO7p9dv3EkC9wt/xmcwAJNV4pjqfiWNu9yVLKNoJPPAclGgWUAJaF8LYpPzhrZNh4IPR8cp4JBsTpISaElqJACWrj42LBCBGzmZLK29aH/T1YhOA14mMoXZw30CwBICGJpMY6RWaGmSc5Pv9/V0tG0TvQWfmAYDzNPpt9yo4zof347uhwYH9RHpZWKYEoiDhMZgxro0OIwHq98IAAM5Z+zs0rAzwcd4fSy1M4Xr31nASUmR05G7Ya02fwNyH55NrpO6rq9nwfKfMHPOZbOChYWV8j6Rh1QOzxyENsSADKcJGmshhJmMyvn1jAoJERvmxp12ST7kcHeViuZ/Ib++yC+P06VtBDa0xAGTcoXRjy3V+0Zsa+g3l8LEP+s8XrfDUsSvBBZDI8nDTyqh5GrXjNBirHwXdEcZ6HQNRsF/yPZ4xU3ztNf8zPEB0E5hgE8hIOWdNyo1JqfHqANiRPoJjti939a4tQfpotXFNtOOXgc7KFBp2M8n+mIMvQfu7KWxKWQAmSzMMvfEonNGhIeZx3jlgixcCa6bzH+uUawpNRD6hko2bTzJhxwVN1phgosUoZQUuDdPylW1wBzRZHieLa0pmnFD8aUrMQYBnbr19pnMwHGafls3z4mv8pme0XNgKZR6M2725a3lUJmIYSD0Y+kVkLno96V0ygDSDnTDVi/M+rLJNYWkJ5p6yFzbju/uadeFOu6TgsOCZPrDbfJ//02/fclduOrduxS23fOru/FOIrIERgw4MiTzzm8vhFjHFvIHniNIKehFQYrFaUpH4mQBB8stJ1ENpALCAwCp9hiilKx+X9IqvvBwEFyj/S5jc0AJZl4MgigG/0GVU/4EaDAv3xo2gealhtDXvvTncOeccn1NOKq/neycsphh9LoPeG/SgIEhniuE2KcSzBBOClJCJZIxol9hPRr8SuKDXlRawKdddAgcACfPUX89qo/XRSgD45eyOszDbaH0rciYJbQGIcAwgCmNg5XqYde4OwNSNYbZfBwTBPEaQtHrT+4WlwhwwzFZGxF5BkSgFrNN/L7z+OthQ/BtJB+LegvIgAlfWOMsyO0zD5TZeA7Cm+qY18DUgBhpZBCp0pJyLbuFzViwL+qh0UqZWASSEz49pCiGtqD1OeLYYVggAw/QhFPMiV5vHesoGQ3/o7+9amkdkRFUHfFMhJ/MM8zWZbu2vTnqGdgVwd/75fUF2XTPmNoEtxwhoyFTSm3jNWvt8cl7mME3Ljv8NZa9x5tf3w5ikw0zGezmSup6IqTiuX7/uVq9e7T7+7C+7PJtyNWim1GJqDOudrcvC2vEsDIKYgk2kAOxAkj5rNodCh6Vjt5lg8d+1kGDE3mgtQJhj0DiKWZYBEchkeN0v9AV14NCfqju++W4EGlbaYrQCK8BQvddgA3DIL9LVgR3RjgTpwPTAoKdKO7CJZMFkfDfIRBHmArvOlFnw2qghYe/qfLiLgs8vV/TChqlStFrPAnpwSMIQwTgDKMQ1tCbJKI0Uyvh8BVcU4PCvwXuNkb3SVDJmcrpUzaiCCBx87wxYIJ3m+T3zjhlr5O8gB1KvC35OTM7C86+ms/THMLHCY6QpvB5TV8ugyafx6VCGBSQsBHtoAKvf04DDkAA18+pbX/6/urPXardlTeIO/ND/w4UGmUGUGtkUoDpqgEdpCgGifBadaqFqk8Jc4jPpf2PSKuQ1xjAb/50yqv41CzrnJ0HxZweZdHeV8oG9V4MtxiKn3OE36KPV9vWDF1C0YYNOb6ZOYfgQisEblImMgiwKZZ/QtyiDuWC1HJJFuR4JqfM0+aQxt6RsmNY3i3amu9BkXH0rmDbDohefX/O/t8xM/37VNfhbsQBHjK5Gz3LQHJcjlWYF9yf8bhX2DJqswcFnwqxlkCdpvCllTP0zHjxLeD5w31RrJe0H5z1HMgmj6JVVSOkQ00CW6heQMD1pGlHGR89E/b4cGET0cKDkkjJL02xqBu81eP4YGRj8VTr+X3i+ip2bgolXNExtPwfvbZsi/jinj1+Lg1oAWBzvIdz3t/eHZcft64uwZLBHo932Df2P/Ss4b/Stog+KMpUxxzANi0ktunenZw2TlBwYtGSqKZOETBDe39lj+6PyJHf8TJDppGBkaBT1yH3B/YGbnZ11q1YJUP8+rLWe+cyvu6wvz9g7HOVwzn3j//0/vu/PyWR898eECRIZTbc2702ZAq7K/CI5XCVMDhoacs3lz+Harx39myi09ywLdlCVyREtTCId3HGbARYVRNcZT9e+9WXQ5Vd66mKyzzNB0r+Cnpgdz+bvzvpNfQW6X8IuJTfbzUKJzgMd3DOHLh+6bxkc39vXbIEmt9cLAh/1yuVR+mdJCjJi+LhJoGfD3V/6H+9sGgQTMzp+Dpu4UOOt0oiURDahJn0ikhqSSISJvYfwXvgzZSsY4AGvz4bh7zZCsogCHJ24ugDQocegKSyL78XgAmFNMUq2E58bAURorEYgiGCHkeNI0Z2U/jssu4C0hdXhxKlOogp9LxhlbI5ZAYkw04jXVpkgnK8YpVvgGvRuxycyXpu5tTC9wz6c50lfk8CANmv8ORbePhkT7bsO5xB/Qn8PLZh4fW5vEeBg4TWb+9Fzy2eauvLRmkFQdqX3WloO7s8OU3sOsAJ4/BWiJFWaWSOSk4afGcw75zb74qt3Q6Wd24Mxw9l2P98miOttB+nykEwQbOFQTxCagWY4ZjK1ps6LtPIsfC8g8zCeUnKc1TaCP37j3UPBZcwZn0anu/k3IlbnHvVshamLKJ7eECojpRVPI04ZDRbOPXNPW1ldDvkeC0gy9FJJ5mCTxUgOCfJ942A09tP9wAeC3fGSYI2ADr0z14KxsMUGRLLCHFdBLWM+CTAxnfWfWUqKDUGtAmxMeryUKNoJRKosjxI1+mZQrtYeN4re4Waw9SCx4/W8s9XKDwlQsEnFpkgisbzzz4D1Or/ivh5Qau7L5gvloMU0wBHMD+2/ARxkKOIJWLJJmMhabpo/+G4Ez1Rqu+w4wLNbaLitWR6UvNQiKb69fXnYdB2GqZ3GA7zE+vzOkDbWlD2plA9ADBllo5WUQlop352PenB2+vTNcPqigtsLQEw1dM4mqb+vx4QJMhnv5ZiAIJExdXnk8jxzgzOzQYbCMnH4Nukk0EwajTp16BctmlyCppnNbA53IYhMt2+CohO6U0aI1XAvdzvFa0O6liHNK13/2wEqKOPAuDAZiqjGwEKP6vaD0n32SlCz2h7m2lXB2Lb8GhbAVWCYgFLZoXnifBZgguSX7SJVwyMlg6lVcuRskE6cX+3HkX56LnABl05cxX9/+ZtBvbeh6UJGoPRkw14hjV8YSLwHKhwbKZrzkGrppppFnolIRAGvTBIDkIiEJDZYxJtIUxTqhcGx4gCRAZLizVAT2Whj/cKpKfqZ3KDe4FQ7JiLQvp46lehfxVk6SQTsUrBnLsLsQb0wXEV2mX19za9mNuVxJoiCIkH2Srthr4LdOwIUZKJkAKhy6YYOV+eRyGF+XpxOZORBBCTI9qPUq1kKwLbj5y8/6kGDIejYpRSznJc4r3EtSWQtoaFeiiKlREd/ACaMAt1MZCHFnt4rlPao1KaC2WSCYpggjn5mfgvzFeaowSkYw+K9tCNPCQrNn5O3rZafFPdBJIa1D6BAkz143NMnZ4PXoJbiJcE6Qbp+BjnMnV1+jeldt+fGnDccDxlQKcyS9TUETkYACqpPPhWV59r5e1nYpFxZGbuXReR7YBNN+XV1uFIzxRk/TPZKGmcyAtCdYvIZFZcoZg0jQICcFIAf1+nqTQtqpft3R1N5QmNw1R7zPFi3BAQIThCIbEb2Zy/4z0cKzu1ty8LR6dJEMJ+Pe8A0PlIL1hBE6GGOI+OkAIjRWcuTPMiEHMfeHK4MxzkTdCb4p1ISzv+8v7hGaWoYB9m1ZErXP/S0//klMWnd469V9aKXgtcffy46dxm2OCRBNbxDFGxZ8EBqmCCT8d0bL774ovun//Sfuq997WstGPh3/+7fdb/927/tVmDNO3HihPv5n/959+d//uduenrafeYzn3Gf//znXV88jCbje29MQJDIyOYKl+WFzahHwTj/6Q+Zvx/SjyFC9ycl0G23C0522yPAI7OpLuLFy/ELYWowgQd070jDbEaxfllwwnczfjOSqTkVNnQ0OTXxcjxGGkA1xwnjqSzSPayQutIeG0xLKzIxEHfIIqmTY08K8xl8Hxxz2DEikC4DbWcJw9IC9PZ2bH4oSLFn15gRje3vVmHj9Xf8/YV0t7FeHRzssJiCLxtTjEaYQh3GidGz1kHmBDc6/ev2vmMaBu870oG7KRuUEYU/n+ejRGHcibbEYCHBhIq778EuFzYtpBZT3iQJJgZ44LPP+1O6jIwPNr4u6KQNV8aZA7yeiwCCeL+ohKYAU8cwbiKMH24o9e+MBIjfRcGmyD2td+CNHVk4YtfE6PK/04vGfii/N19jGVlk/LjoBjsbZkt6JgswNshGuvyc7xgOZhHlKPTw2/vXhTf/eFb78JBqxnBmZfDvyL6gZ0+xdSoaGVmhm5kCWDUJZs3YBUNDGnliXuRzww70WHYZWCE6X7onPd28ohyFaUeIrLz73mBWAjSeQ6TsCF3jjo/WzUHwHGa718SBEzzjZAoxoYhzWp3GI3pjBWS6UTyQIEvjfJ1hjp46C8NWNDSaMYT58/S58OqYghVz90Mxf9Onh4kw8L2Y2rghanQbG53kOAI09I/Bf2cjKJNEG2PyDNZqgvdKuedprtURb3iZscEB3wgjmQCrphnL3gSACCCJvmiZGN3WkHXVYI8QTHX47yZ1phlM9QNIV5O1JX5GHGQo9MCmdTDxp3Su/SeaTEPse8yarRImAdYWP/Plo0G5szLK5tdkwWdqHiC+Ds43lKpyPV/+tmc5lU/YPa05/Gd8ktIdgN51KibCeCanQK7uw6PFNMXYaK3mnbNk5/f3+B5Ohzlz5oz78R//cff3/t7fc//qX/2rVsLzj/7RP3I/8zM/437/93+//ZuyLN2nP/1pt3HjRvfFL37RXb582f30T/+0a5wmfud3fuc7c2CT8W0bExAkMhrNd5LnNtcegMT0SWsml8zeDC8GWHBKUvok0o6pH4YFwChEGraJgV0JWmd+Br4Xrx4MmpI2o3ehHyzu6aRN5kf7fke9Rjp53DvIJ7tAlYa5oJHPtLUsNqvYLBvJiYxkDlKXN/wGpOZGhdnt6sYOTTKNAse642NDxI1SRi8DMH6y4wIWgZlCcz1SadWjZfoQYpdJP8X3Ydcgo063vaewwUbxQKBhHtGcCg6QQk0QRTsnLDK40bBU7SoKaMytR2GUh8GWjo9IBPhgIRFjQai/Raz4cE66hCg6ozGyEUCoczyGfUKfoLjkwnqS1EHfD2VYcFCyx9e0khOMNW/NhXXlAIXY9TUeHGMMn41HjNwDjBamFKIBiy4vvKx2buZLN4K+FQSVSFtmp16NGxlBSVmE8U845Oe36lFhWtF4EJJBFvTaHe/TRgNzPP1JbIqQRrL6nwcXMd/By4Bzv65TN3ZPBwtjsmcU5DTSDHzP5afh0/AhJNUo64YsHbBPWFRQEqbHxjmhEGZMzBi8OOy79fmT3pOqY6ibwVNpM2WnZVhmIkUa5zV6KFTHPOMk3W27+CbmnsbeSLYg3d94HrTzLe6vI/7+THduC/qgtJ+DLiWLtpT+ICiyio12b9A/6fcQoy2rg3ISAmR6nMmHkKiGlKuc/ihqAIskPT5rTF8q2KxRphSaHQT/mAijko8UHisVZEyM1S0jKR3t34GBxPTA7Jr/zBL7ufY7RCS1OVJotKZLbs8HWab1w7iHAN4po6zO14VjnjHHZ3huOnIlmrFCelZt8d9zuNHOQ7G1iYB8X58vMH2Mdwl8HujTk0lCUVJtD0qvaJJN6VtnDWejkOs512z6hjSvwbpChtzKWX9tyo0WqDZeQ1vAXAOLrryA/SDITQ8aE+R7WQ7zh3/4hy3o97u/+7suvQe0Nz8/88wz7vDhw27//v3uj//4j93rr7/uTp486bZuvTuH/dZv/VYLlPz6r//6xKPke3xMQJDIGLx9weXpwNUrl4Wj0XZarXN+rQ6af7K7np29HH09F+1s5/agFCRVaQmNqyiVATqffuCxoMZSvT9KdizpCUJDruZ3cMY2xRz9NfbvjFK1C0zslM0wno6Rtu17rAVAM8X4C8iOcC6M/KOlhOO7MeIQ3ZFKACaaEDIGjh2e+nG/yKWIp21/R30vKcygovauxpMPSMcdIW2Im4QSSQWdLieZSTiWwWWh76JgSXA9adDIe6P9Dtg8D66GF2RDW5b7lhRWdoq5Qa8llYFdV1NwsTgHlZWFeft+jFmGuR83iyk6ae3v2LnGBpNUVm4itYAlIGAo4fjvyu5ikWWOH9+zxLkgzVhZNvzOBLUIQDRjfkPYH2O4Fiy4Mawjfg537zwfGZJ29L05yhXW0+TmTtuFDbI/kMKTVIM4IwzJNTGAqdj7eDAdqH1NQh+NMhgzTf+fhe8Q86lZ/BzcT1OnrCyPm2/Oa5Rq5eKBxGSKwWpfWE6f8nPc7d2rw5HREuXLNa9e59ei7GtvmtcUP+DXmd5lRAEjUnx+i18XVwozy4ANlHLACLojPYDpKhkCBebF3nmJvCSIjQQUgmeM92ZMdjMG9yKbtbDKl3ugoQAlXiNqmWgzD4CGIGG9TfypcN8su71xSYxLE5c6zvtj4fXCyigBSPROXQ2amWZXb0dBkOoQDB4R2Uy2RHUq3s5OcDx9So3ECJPrRILzXOC9GVtaHRQpQ2RUJ24vKX6YwGp2Fo0QPJ/cP7S/gqS2RvMpVkzrSKdxbfF8JZgfstfORiUbyZ1hcD/F6NpOahViuNkwysEKGZy0n1nvQCofpHTD7Wvj3l2QJOVcjwkU4x5iI04B8VsP+fm+N+uP+dYeC0hw/svgY8KAAjYTeT+1v0MaF6PHDfChEfFP7A4Ci0wkyyXe20TuTsZ3ZczPz7eSlgUApBmN3KUZDeujAUG+9KUvuSeeeGIRAGnGpz71qfa1L7zwgvv4xz8+uVrfw2MCgkTGcOcGV+VTtps5Jm62nFkb3AxwjLauDBZF7etRMExjLUnhZ1FDfqJFfELaL6iQ9NDQ8opMiBQLWwr5h3ZBuAAkR7CJISKPooigR2fQcRuMkWzD+iggwMWImwvGtpVXrbEqj62QOMkYvZsLm8mBp9HrWVwbdQzfsy2oQydQofrkakATxCqYPkGGR0VAR4q+mI6aHeC7v2M1ifcSg8fYmF9Lp/gkSOsfifabRact4ntRVgWL+NEKGpHgRxxyfjvulTGHxAnKg6g7bn/HwoSnDRuaebBaOnI1ACQjGNWRkj4uwYRgi5E3GQBAGDMERvE7ml/ObbAAhDFf5vsRKMDmUOc+C9BAB443MHKgFmAAeERKM8xkm2u7+tW7z+Fw88oo24FSIZob6saTpo45CrgSBeM0/JSSw75r337OI7vCjA98zKo3BcDF+xUbfHGdvfJ2kJ1WQnvejN6R80GvDRP9KpvlcoPfSPf/69f85//wM/57/vFL/gVP2gSVEoBuFpEZJgdsIZD+5Yv43b5gulj/L33cr3sUyQnNe+MeSF7zhWr+0J5gSkj7mUyowbxq2AGyFldIICHYQhZd/woKS5GQMtWHHWUj/xBAgmzIEgBJH2sWO93uhgBh+A7FPr/RzigHFX+v5C0UTLhWeaQAHq63wEv/yIVgwlB6Gc0CiQI23fKtm4PFW44GDxsfne9A+SNZMij69bo57JUY/cr/buJpW6+GMBBmAAGRw+QE6PHsJQA0RjMoZlFMt58JiTUZL45x0iLbMfsrpMMwIZD3Zr1eDX3hf4P5jmyPGkk3Ko/h/ighO5jnAvfJ3Q9Ng9fQzMvaILkqoOXCgCQ6w+fXArwkAGWWX4Jh9c4NQWlL+5oL/vmsZzYEvz9B1hoJT+3xEIAlaxgM5OqAbwyqiTCvbQWmWDW8v9/MAzG+jXKYRq7CMRgM2v+92/G3/tbfcp/97Gfdb/7mb7p/+A//obt165b7lV/5lfZ3Z8/evdbnzp1zmzfbKPa1a9e24Enzu8n43h4TECQy+uduuDwb2ri9MUVzshGFO1gFLKAzUAd1sjeGoeysMkZWDENr0CcZ/VrDMC571G9wkwsW6S8e2h7cUHFjkV8W7Tcprzwe0k9v3I52QZh3b1ghAFcU8c6wABoQgq77WLyyNXLMAI/qx/0mKLuE64R4vPY4T4KVwMWIm2rS6OUzK27isOkw8ioWbKJRN4gVmBc52CPJEVukFR/wG58pGAqyU98XVkf1jdfDHTN0/IxBqEi5MlC3R2v99+yf9ot8DdChfW8cA4sMRiRmov9ncW1M+wDWEFg07ASR8JhCGyDMnc0qh3HBMbc+D5u0CitjiKLbOPfTsE3ICvQPGCI1xcYa4gVjfGVtfHH4v7fHDbDHvDc3qEg/0uQhc56SMMOh0GIUGz+TYCVgydyOe89VZ5OE18MktKCHhXozgG1AVgJHD+Dj6FlbMA0O+Q1NBeNkmhAr3b4GoJCjAzz3EU89H5xBEtUXAU407wfmQAqGx9iuIOyZKEvIj6K7vANG3pel8MBGvsTcxw50KWAy5+UaHfHq0M1gYZqcteB4DU8rFlklzm3y10gdG+PjlGONoQdV+zkR34MUgITbPhOdR8i6KQ5sD7IaVZpiXo9Y3Ho1ikawNE2aWXtwYcYnpT5aaNcoukyhS6ko2XFftuyV0YfAIGUjaKMUuhg9xrqiiDedc3k+zOD8bYzeKcsTtt0rnpGUDqaCkt4EslVVaCTwH+MUU0Jqy2JWzcnrSJMn8Ypg5wjINK/5igcDE5rI4zMLGGR2mjxouOTYG6VItEnEeHjIBhyZlNxbnLH7QwWMQvtDeuYVYG21v6NROuPSydAT+WCxG8UkwPb8KmOzMceDOdKMuT3rg/M9JZx3Ntoo36l1AjjdGz3K6nifgV3dDuzDaGbKfV8tQQoOf1dE2EkmbEHYTQ/a+HbJWXbssB5Qv/qrv+p+7dd+rfN3zX/73Oc+N/a9GiPU559/3v3e7/1eC4T88i//cmuM+ou/+Ist6MHEpETWiWY0niCh/z4Z31tjAoJERmMu1zBBstVPBmUFjLdrRh8pMgVSTzKwADh5a7QXRwrfh/QcPDW0kDgIymntNxDZJg+2FOPMrs6vDC7A5sFVVsvsraCRGSm/FTSj1Ca3Qw27Fg7/6rXgZrs9HnYowB4hNdZ04tQ8DZ0cLkY8kg5llbRGLj4wWUu3wTcEXintMfT85qZiIXTxRji5R2Q/zLhnJB31qOWTttvTO+nfr1q/Ktgh0lH/iO8O32ZMJdkjkF+0x8noVrAKjLfBYH3cWJUu9r2I18Y6ifiLrCU0Y72zEd9TFlUW5B2ZxL0xuGq7vvNrw2BFxgYNPqcHRkUzRtA+M1ElR3GuTA4Os3Ek8UAibjnI+GD8omrEo6+/SjCUJnNpcK7TbiAlegQEKGtQaUOxgtfNno/B1+5uEKuHbSfNFHZ4PnpXMd9iHr17EDATvYTNMwor+iSQWt0eJ4z+uBaQzpyesjR2Ar30AuB7j8AQcT/6rHl9xmhFgNtGYgFzxvbY6C2Ae4ASTDUU5Eh2rw9HeAKgYVHWDiSdJPDBokmqKZget9eT1SnZTNOH4U8l8zolA6ZIPArjyh3izxExMeRdZxoKiLxsB8BuIzPBmslr01nPAGQZIAgsAp6ndrz4ZtCIM1sB809NTzrqPUoqrJMJ5uiUwP3De+3z+apH0kowoHpgFJDh2B4Dk4jYRYe0pVq9PCgBVlYDvbMIMia1fSazpx4Nszcg23UAwiqYvrffgV1iMHC4h9EGB01HmeRHGTQlJ6M1dj/TgxdMTYbHNNgjwuwxUjQ00wzoivNZwEelGf3z+G5kogAsqTbY78nnwBjPL18TnId7sn4axiT8Qhidawz5hSmbMn0Qe6Xqhr+eKUGkBtB4C513AIY9JPx1Iosh36N8O8ZiJrtaR47nu2Ksru5JAbYTGC1PnwtKkCZjaaPx5VgFVl2MBfILv/AL7id/8ifHvtfu3Xef0ybppfnf+fPn3fLly9v6qEmH2bPnLpA1MzPjvvKVr5jXXr161Y1Gow5DZDK+98YEBLlPOgzZAhU2XQkYBe3v0LlI50bBaCyyLXSDnsE8jEBBPQdwQh7o9OE9wUXXQTNp9KxMSWkPDoUhY2DPYeMpxlNGGkLaM7veYBckIm0xbuJYzIwHB2OBm8WIiwm+T4nXU9rTiW+cXxNk8JSzkLPg8zuaYoBK1PqSvpsJZZbFIDcDFVgRSc9OkNzsGQkNjVFJ55ZN5O3HYA6LX+V3sKGUzgs3tfnNYRh4kajREmAJvREoa7AdfZHg4P0GTF3hJhr+Hu1xkwlhDDcZMVhGfQ5YWPFwaGqpUb50ijfXMJL+VIj5J9NEYrG82ikw5pmQ/fC/K+PEHAM2xQSVKHkxciI5NpOMga8/QoLMrW12Q0cZ0XBVFvz+KqGh7IfmvA2z57N/Z+DSas5V6ZT7L1etVGPxmJOwT8P8pniRRcYI4xvZJWQCiXmGxSuDRcH8Zr+pnrouDBMA4u5vACIg5pLFRqVG0mAYFjCPzh/xWvjioDAPCIgThIbspoeuuZHWjGGZ0FjbpF80Q/+9cJwAk+vX/Tye4Vj0+3D949yvQDWH6Y6j6NbvYuby0xfDZuY02FS52Qm/LiRYG6nlp++FSkpr+EkYhoRhO4gPzoceDyfHAXzr+GDt8LKZhAl39PgCi8Cdtsbe9T6ARwRg8fmUd7WfCWajuZ5k+YC9SRlC+28AQe46JE2b1kU9xmqwNAreU9gDsKNO5mP7b3MAMClFp748Zhsc3CtUYGxksyuCTJjeMStrIIssOebvpwqM1UykKeZcEUijHCXF/uGUZUgUNJ29E57jUk0CxOeYexqABGVxyXV73492bQz6JtHHpZoWJgjW45zSMzKqd8MQGHK79jvgmaCXmnmOZfm8g2SnjMlapQcn+qcB/Hf84xhnlQYBunFGt/X5K1GD/u+L0azTkWTCd/QeDRa/atWSjEg3bNjQ/u+djAVA49/+23/rpqam3Cc+8Yn23x/5yEdaA9RGHrNly93GaGOW2gAwzz3nY5In43tzTECQyMiuz7ksq40TdkpdIJ2zhYnASNUcGyWTZqIfSJdxbpqkODdjTKJKaKSyOYuZpI0bBBGMVEg7g9GDyILAhRN/Cw67WZTcypAG+YTvgun5NHG3SxxjfU0iI8O+iZ2LcYMAD82/lnqdluH+rMCsobaUmuwO4IYNZU5Wynpb2OXHsAmg7pWbVYJakEc1owQdtaKZKQpQeqIotZUb/gE2dCX8UtRYlaarxgQY5pcJZTLqw1EBhOF+qg5Hi7bfDYwNfo4yazgIHPA70+jVMG4EkIklsphjET+iWCJND74u0+cAVOA86wZzGu9NQ2C9HmSCGPPLO6X76R/uu43L59zFWz33h/9r1eketu+N70mT1XHSGiaVEOzoXQ+bANvkoCYJYWUQUMnw83Cr7abmN+DnA9bVPDxi0vV+I9+7YTdmKZM1EFNZn8Oc9JGn7GdeAHCPIqFmXC3Pn7J0tq4NPoclaPwEN9rRD8/lxsiac4UwXiqcpxEAhQElj2C43H2RCyeVnLkSpa5XvA3p3UwG0FFf2A53C3NglafIJ2DG5JDwJDBsbd9vGYAXfp9ViCclUCEsAFIWyawxrCMUrO1XQ1MjhSE7fcUKNAF4b7XHAJlBjSh4k4wh3lv1xrXh+xPzVX0O7E1G2jZ/ttWvX+kVnCc8k+pb4fCZGVJTYg0NSmaakTyEBA9IHgi+jRuUqJExYpoo4hFD4CNhMgiidzsGsPh3ChlyjcYFgatE5L35UZix4pwlZwGuCCCvkpzgvXLWN8zqGdvwotyXcy/XNQJnzeidvh0G6eD1wes0bj/TS9eF/aCkqdN/7URQikb/Ob5C95A1agR6HaUErlTKPgCAugyyduxvv188Qb6X02Ga0UTjfvSjH3UrVqxwf/Inf+L+yT/5J+43fuM33Jp798EnP/lJ99hjj7mf+qmfar1Drly54n7pl37J/ezP/uwkGeZ9MCYgSGQ0NMMq6xtTs2Q7ikx1gId2u6JL9xXIH7DIJ2/b7kIFPWfGuFroqzlZtq/B8ZDqnYhZ1OJ/F4S0hoEeDbpI9+RkffffKCSurw9SD9NdkIlI5yWqOaUfhrBPmGLjXgDYRK0tPFaUesg4zBoxeCZGUDuT7GCiM2hc759+JGxw1n4HdGVIJTVFlkBhkLOkuAeYCsSY5eyqPWa6rvdPrwhuYofiCZJfnwtrz6m1lU15hWKELBXDZCHwweSi5rgh8crw3sb4V+QPJomAm2pSqFGU9MboafOY0z6An/Y18Ebgxs9sDmnOiA58573Z0ReQbinPBzvQKdIWOiNiLsgkDRajCsCSdp2cvhDc4BJ4av8OgDCp1qpLN4MdSMS9Jleue5+Y2ncQ2fVu/w6gFss/ppHQ8FSNLNmJq8DWY9GfojBXE0XegylYeBpvSuYXpToERwgimaj19sv1g/cdKdSMRL/7h9iyw/Ogt2dHOJrzhNCuI/dNRZmHMgQhJUhg8Fi+djRYsPSROKJzygByqxprXgdMPY3CjtHj/CPR0XPO53pKoLuEj0r/jHiKHMezS4Dl6vUoaG4MyA+E2Zv5JTQ+AGC0g6lfV+BjBYYFY3jbv0O32jAkYkM7sXh9Clo+30uBsPK1uPR2KSNq4g7ZrbaEjPQIzy4bB5yH6efRDhTUZmBeZyLeOAZSgmeA8cdkubb/JPjEAhjzenEExj56aLdRQINxUr3sz38ljAJeK7Jp2Jgjs3bciIEjjqk50jBL8Z051Kw/xbpd41qVnPsoVT5j2SvZZr/XSy/6z0yO3w6a1rcD8j138lwQMOP9NC4y2eEeTsCcUxYbgVIyl7l3TQgC3e9z38/j22iM+p0YX/3qV1tvkZs3b7pHHnnE/et//a9bwGNhNN4gf/RHf+R+7ud+zv3gD/5gmx7TyGc+//nPf+cOajK+bWMCgkRGY95Y5T2X0swNG2/tZGXUFUbMcFKYnw2flWgvUrXZRQdVmYBI+36XZoNRugmlGch371CDh1vCiS5nzsW9MmbCLtkEEfIBijfzapHnXBNa4eJx2k25MewkBZlO8dBHd3xHXj0UlBRx0VcdNwsJAh/pY/67lfAXYaRf+zsAQdkNdEDZaUdsmy7G9DkYQt9LRoPbYLsLlBzM7VkXNIg0kgApwGhkNtqyOuofQEo071v+XQ6Gh0bskm1AbwUD5MmiVm+cvu/f1Ts+tPhzIfGmycMz78ywrfm7D/iibZ6/exaGwvAa0YWYLI3+dTBWDmyOypM40gvYuD3l54sS35/3Vvs7mC1mF1BoEtiEplyLMerqCczynKenhDaNojdFYTZuI0+6uXZd64Wibzhy6V/dM8PUDi7muBzPTXSD3ryGUgiMFMULgThjiNweT7gzZ3xqsfFd+A5Buj+LDxSc2ROS1MIiDYVZgRQBA8S1B47nnZR26s3HFDwEKwpIRqwptcwj6NTWmNcJ1vCYO+tKJJEsYadd5uixLMnIMK9RMHDhc171DMdkqxT67PpGinZlGxgmH4o2MjE4UqQAdV7/rQ7cKymLP3i6tMf25qFgYZajyNQUGxNTzMKO0hjEwLI50R4P5Ul4VsyxyDNMZkgCCQ0bB24l1k+R5TGNI10P1g9BNQG1+Bzw/iYDyphiojnQjGzwUBg0xtre3XdhzYAvmhnPPWqYzGZwr4X3rvfuCDYk2mO4FW6QmOQeJs2wkdX87o3DYRYbgHZtsBQRII1AFmWB6h/H+T8GYqh0j0dgABaCVZF7e9xxco7N1NCX700PP763zuuT8Z6M//Af/sN9/2bnzp3uD//wD78rxzMZ394xAUFiJ2b2jsuzylXoNMcM+LSzyFGRyYEFR12xaUDHBYfxsPXDu+1rwAQwRmKgqdaMzoWbfTsuIaKWMXSk0iJerv27rX6jkJHOypjHldPhDZBsxKs9yEo/jmixx20hQPOvFEat7LI6LLga+ZgO6emBDs+e7WEflNb09XKwMKHsKYWuvxT/ANNZw8arwvWku38zejQvw33Xg/O/iQSUkb8CsOahHcFNy2iVpFfQyBI/M4I00e/Gge9mABX6g4iunvrg+fVIAeDHiJTBGJMSBKH8A/cGKbdqDFrQsJTFvfq6Rb42j4UeGjoogbm1bSoswanj711tXxH0ASGIk9TWP8B8ny3YiGO+6VwPAkY1KO1pWBrkdsfBt5TvdQAMLJHtEE5I4ejfSFDOzf1XN3/ZuWtzmas+9mwQTCVglc/i3XZtCnp9tJ8ZAaWoI6dOUYsXzsv5OXTlbkFmuFz8HGCGzUhreiPkZP7B0LIzhGl03//efhDudUZwEigXrymC5SzGWHwpcy7KiOJmHyaGGilOI0qTqPYuGFTjRocJEBjpTnhIHD0Z7W7Xe/F3LyE9QqjvaX99OG6WEgdeD309E25oVM4CUhPRKBuNSU15bWVdoZ9ByYQ6gvBjzN0z7CFqgKY1OuDpdQu8GJnGzTvBhLuYsXqHKYXGCfccjnuwVoKDVKNLl+P3d4QhyOcjfQQeaWDAdpIEmX70wqvBol0lF/xu5nwAjMwYDS0MXkcWMddJ4zUiRtI3b4eNYuHZlo7ghYO5rv1uP+yNoEeRvYWOGs1FepSRbWhinmUeyfHsUjZbbfTPV/+43esNd+F6oKmTE7gAyKsMKPo4Gd8+zDU0vVf5NiOPzXcRr6bFfVw171wc63/fjSaRzqTSvcv3mIzJeDdjAoJERoPQN3KYiosJaochO9PtphqbXXa3dxI0ALtACss5vN+ASDuKt3RefEjYxXhoX9gwlBFoAD3u/hId/dmI3EAy0VNmwWMxNAsD30u6FuyGkgZPUzB3yDJEjHEfvSJoMkpXbjm3JR3hsVnNyk1ROnC+YV0wHs04eZPxI4XlcJ2/HwZYWHlvaERuja4QX2/o6XWcuZB8+ECw0Ocg86H9u+k06EcxXDMVXWCY6JLUNEnF/Q2wyRTQ7eaEKQB18JgZ6dq+H/Zn86vD5p18r7LXHxMXG2aS0LBUB01TGYvLOYHvq2PFUb/Rmd8McEKIIPShMGai9B65XsSZJLwn+HrWTh1j1zAoxOvWv1YEvUb0MyvG7eJey8WolhthPhNJnblP/fotd/aac1vW3HKPPn33vw9X59H7OIHenE7/VX95NMqXn1mvCjvI67nlMdcAehOAtMNNkjxwBfMa5qURUjLyWczxtyzbgV4T1UokwiClS2NHY+lHDpK9cvPqeAxsxHeJHdhOp3rPrvCcD/YGC7MaTDkdlA86yIvUd6pjzrpw/GTlqc8BY9nZxcf3KdbiGqy18aY5PFp43vK9u6LMJh53hSZC8ggSxPgM0UelZRmi0DRr9p1oFLD53iU8b85fXJoJI5KMckoRuU6KbxOZUgSs6ImR8G/kPJnrRhkU2CMEUTogBFkBBH0p95NYeQdmi2Gz8t4QvxWyuAhE1ZAP0otmuM7uFXOs+xliWI25vbCUDBOByTtoMlGup1Jb7j2ZxtXHGlFLEiD3l2SH1ZiHSiQUUurVvveJK2FmLSNqlX1CgAR71/JV/50zRmCLRNwcP84HGadzD1lwgR4hKY2Dca9Wl64ETYfb39Gbj/5rlOQqi5B+QDS8JlNax8K9X8VBpPfl+B6Xw0zGgz0mIEhkNJvMNC1ctWl1EETIz4kJIswjkyFABCRe0Bywd02Mr1gIsBN2u47GXPZIkeRFZWwYjpna97vHkwW9SxwWAhNPK3FvCYyjONipSFRPi40TtamkqhczFjUvmQzCmEbG7WEzw47I3Tf053P0A967JWG0pfoXgE1jAB6a26I7MQJo0Iyp0wBy0FHoHz4XlvAIg6bHTjVopslhvzGpH0Lh0f4Hfxf0UHCQ/UETyGYUMEVkPGrV88fSv2ZfM8Jr2OGv+ixm/d/nMNhsf0dDQ5pPJuGiuxlzG/xnDpACY9gaLEpu289kIgqLeL4+G8ZXUpP0QpwB6TQjMf/kObiN4rh3C9cJEb/ta/BPHifTWTg00SZmEDYuipfXoMY+mN+z3NyLAze4BwgE9TB33VmpCBONIOUzk26KjAI3fM3ceiRDLYN/j0YJE1zG4WSURNHrQwxk82tI6kICWAHPHXYv288hE4Qxw/TEwHxf7rZdRiPBhA8VZTdjpS30XQK7LLt4Pewh0pwDFGBGdsRNvRSjxWHvtRQDAJIafhzoMnfYDyzg2c2F3GHcqOhnIR1YM8DEYHGdwedIE0woWUwpCWLkJY285fwabyMM7hNy8ZciS4NJRCYxi341rYfOfPA12R5IW2Yhz0WqUvt3SBQr4MlF010dxVZfwKWQ59bwPyMbyf2AB1qaUTJtDQBPDYlfosxUxFZnNP+EpMh04cW8Mzor4v4sLgtwsoSRwqS0z1Sp5njOQF6D/VGNQjuZsbIfSoIM2IP9CFOAMjHu5/xvgGKm+olkg2yg6pCXNiarlgclOGqwXGK+Y4ODSWWGhagsEa7nZHjgftCGVwFAm4Ah0+Y6zQ40cuoMe7A78MzDPpjXogPOYh/KhL1itQXamYQ3dRbvDf8bZZwsALhF/X2YIDMZk/EdGhMQJDKKBvzIp2z2OjZ6w7/9wWj3jV1KE+GJYrBaaReMwTm/MBUoqI2BnnSahwf8JNk/DK3xDjjVA+lnwdt+5sFzYWO7ASQ4ZH403+EoNIvo3FQ7PCCTXLkZ3SxTjsKNJz8zFxCDKTTGmRzdUHP8cFzX69ZDt8MYrgoIMjqASDnIN8jM6Z3xHaoUyQt3DwILMDYaad93Aiuh289vGAS9JvoohIqnfVEzRMJEMwZXfAF2cwcpq4wqta9hUklS9IMFIKUt7fcBe4QdzMG1cFRqjmSVuwMbshvwykCBMVyTRzdxw5URsIUxsCJT4TlgrK+Jh5Xo2BwABX/Xw+cQW8ilM8o5YeWx+aBMg+dSC3KHDWI2nwTBER6jJtQYsCfGDpBN4eAapEpgX+S4HxVQ4XvHmCRTl6RoxvlMAT61wEUgrUZZNvxujEbmddINNm+WjKmGcg71sxfG/GaYEPZRWOLcZHNJFDAkuDN8fFPw+7Nj24z+SV8wjX7Mx+0lSNfJz4thHp+jmVVBVsr8Dl8Y9i9LYY4C1rFzjmhKFrZjTaa3zwTnOzIiuutnFQRrkg9YVkZ69HQ4PYMF01nxl+L6gbWowHyf4dwOH7cGzfRk6p1AMgbSvGIMFe3cU/JIedRws5XDEDDrX83DrJCL9h4oN/vrO3UMEZwAeOg30xfJRvGUb6TkkGOWAPxYyClTlebs1SN7wmbeX/6meX3G9D0wRimNMbKO5u+QWORoRkpTSUo5RA4V9XeANMSAf9K5JwOXqT5DsC3yazK/bPJATEIPIsirnIAY9Q897Y8Z9y33hzRnn9tpwT/uHfsXKaOuo/HDbjmYJU/6fUdy2LN8MhrI4u+bUW7yxf2ySzD0XeH3JqVE3GZgfhmJFgBHmkd3DEeXwYSYawaZoOrZx6YGQBVKxJNXDgXZO+3vYGpMlg7ZQEyg0RQayhEZQ66yOLdoUJw+UMyH7/V0mMl4sMcEBLlPdnV2E10ZeFUMLlrjqRKUbNPxQ2FIJsjgot14mog+xDcyuz1V7Tac72OO+JwbFAAfYWHtvQWd5QxAFFmMR+gk9Y7g2K6HDVg1eq9GF8F0PoCmE/TopMBgo8W/44KTkCquHiPUk37VG5s6jQgE2p+BWZNhr0lTMNKkO0kp85HuBgqc9r1nUUiAcZNewwZ7md/c9ERiMFzl78E1f+2vwe2ntgcLjPY9rsPPgWALNnGZGLgSRDByFhSg4xallIDGGgGPAuBhewyUoCyBrTG/ViRRoC+MVoSlQvTdaI9tFeQ5OAXFdLirpLIhSnpKgFL8HD1PxtMDn0kwk0X/3Ho7hRNDGeJ7xiRAWoQT+DAsFRxXLQyLEbp8ZNMMroAtsUJYbJD0jFbl0XPYny2C9O4cbLUR3nvZGZgQjzH05SCQRwZWIUA1C4kBgQNS4sVbYQrmtuYz8Xfl8jwsn2mLQcTFvhruSKtEwKFTmv7li/4zkXoy9U3f2a2QWtYeDyKQc/omkbm3TeQsaBbkGcwFX/deTemjKBilg5tf8oXNCCBACilEKpGqFUy/ExRg5SEkgFHW0Ay+B0EEAB8pippk7VTUQynmUWIMZMWYk9GxyXbfOBjO+O+cSYTn/C5fNPeu+/1IBiPRaoswHMhKw/dMrsEM/Bmk24hPQ++4f+8CbAsC7yqtpLyz2rs97CNCXx1hzFTrVoTnGzwrvDbKdOK1IaCQIEqY0fOhCOXFv3vraNADoxnZ/j1hkA3sDT53qXT0+UxTGsK9lvGIk3Qs+o0wdpvmmx0DdLISd68OSlgTkQX2jvl7IOXzug0MZBynSc8SptLtp2eWJBt18AhbdtwDJ8N9/jP7pyGPgsdae8xI2Lv9qP9MRqyzkaUNHwMQ8b5FQmB9wqYvMsrWsLDBIuuAqTgH+bWbwXtNGSf+AKoHstb6lt9jMibjXYwJCHIfnVr9FjaLz6IY/5LtYlSfeD5aaC7+DYoHjdg1RmSgNZIeN5bqHNnomY2auE1nL8KJmzRVdP9Kid7rFTuCBmHmuOjgLq93x0BV5mfSE0RGch30TRiWmihcLDgVNs7t59BcTyIT/Wvi3bsY1ZvfsxJNNt3IKQ8yvh9Y2PW+yU9cDG5ie+euR/1W5j+yJ0ixX3bsWtSzoA96Nrsyy1/xANftx+1x9mBESflAdgc/o95UCc6dzWGWyhTAlrkNsrkBiyot07AxKoCT/I5dFPt4b0uTTeMmp6ZD5H+eulIGX6+MggpgRwmp0DRfL8ALC3JKU2jaSuBDCxFDe75VBV/Pc0HJSft6bmrx3UzXWT7TeKRgzK/rhVN0Op8ZNtfle4yT4JjzDBaEAid8D7KWeA/P8d6UzXoKe9a5TdNBMFKPv0BnknIxfSYWxmi9lSX0ERfLNI30Aua4zXEduSl0cW1vP+fnij6NZZtjOwtj7QtYf5gMIlp+/h2NH7Nd24NdVqO9bw5tAyRFKPQrGHsz/rj9nPWrg34K2dRUVAKawEeKxolLYVi277fRf2YFOUd+BE6FTF0RQDzBWlQTOCIIM8Y4skCzJdsJNpFIaHIU/sNHd4STwlBYawGbUlqBNWJ6Niz10iI+hdE49zDGiHStGMAC7Of6VW1YHT233F9Up5AM8tiBsL/IJstAql4LF5omFhemmO33OQgTdowc5rQm3hzMh/YY3vINior+bR9+yn/+efFigyEsn7z+Qb+fKXf5dboAsNq+N1607BhS/SKS5mbUMGetse+i8W+xF6kvIllkKtzyE0uTsvEe4LNrZMQAFVUeNTzg76/BJT9fzG/w12AA2a8e52jdsqCnCWOrqzelSbdhfXCvyH2fgtsl7olqMzyDYJRrYpab390z+E0bimLYtmkyJmMy3uGYgCCR0WxE0mxkDLZYmNZCiXN/8vX7nuweFpUKC14zklPYbL4MJ3AuRNIJqxG3R0f9FIsxnckToddRW1kjH51GYozEbf8Opm00POOmxRgyVpLSgSz5HCAI6cRKcayXg4YOUIff07xeOjdcZHJSoGksK+765t907ufmn0735tXNbQNK+QX/nRM6swsVl4wXxhRn+P7seGoHeMWfAlijGRy6Val0F3h1THoDFunp/yaxddyg4p7MnvXPRHb6cjgSr9kQHRuFu3f4ecVhS1uuDx4Jdl5IH022zYTNDVvWzaVgZ3Nw5Ep4s93sr2eWBbtF82vCMhFlSBD4YCeuMOCCeYlhfJBV0b82CsYP04hU2R/LT88Hqetz6/vRz6xohnrdX+chPD1Gy+1BT10ugkASgQ/dIJsUGdKThaq8ACwZk1gFn8AAMiCE0EpYAM6vgccMzy2YG2poyDjoPgv16V6Q1TEulaeEJIr3lpolx9huNKXudMGQMJOAycG/I0MlBQW9/UyYpuaM1mSMegQYbgcKO8o/2Fnt0OAhuahWISXjLNMr7H1bHT4WTJGhJ0giMa70OCkX6eXOZY/sD6Z0MQ2tfT2AJMo2q+0AJI6jYGveA1HRxmDy1OUgWKQJKDm9pzauCPvFiDluAnkqCzDT3cbn0KS8PTZKlwB28L7VZzKjXwhZCbhvC8QK52pqyf0N1q/0UjhKuCODzQE4vn4o2PwZZwZroqHHJBGZa8iGC6U2MBfWWN4asrIMz6oxWld2VxFhsW0F4HjGPyvLLgvDku/HdBck3Ok8Un3zzbBUCYBAfhwgoURW5/DRINNpHDuvj2MwLOTpMHiZSKKN8XGi3xfm/rmNdu6h5xnnaO6BKP/LlAUHqQ6j37kuJCK3pmePiUHn20Yi5qsHzBNkIoeZjPdyTECQ2Ggm5ywxbIV61YpgUdaJZItErZXXQO19SXLcQaU0EhJsFEqRieQANZJVK8NoNDWGwsqoAKKkcKpnx7A6YZkTKQpyEwfJJAVGRsLJW4eJxGPRLkZ/Jd3QyX6BeRmNUc1mSmLoqiVsptqBxTXh5h/sF1OA8/PbD6qCx1OhE8UYQe3KGPOzXbgfIK1R7Tk7SclL0KaiQEgesRRkghXFhpVBvXbH6I/pQVioubAzTlMd3CkjKtEpp1Gf2ay3Pi+bo7T4xeMHwJOA+t9+Js5VioQIB7q8atyXHQQwCeBlsET9/3JStblx48aZ17l9c8bgjIISsx4TBYQevpyxlwI+LYypk3YTxU5levlGcB4bHNgZlL61x4b0isHZG0EgqrPZPXs9eG6KDRL5e29P2hcjaRP7DPkG2XZqjksfkeXH/XEON8CpH94+BD06RrGgjvcuoOg/Mxc1iyQQZAxYKZcThgWLFNPtZyT6WzJHwxOD8j8TKc45DT4PmhRW7ZoJSjPNuiLmrCYN5Yi/b9M9oIRrNDRlRCzGOHcM7X3LWFnGVKbrAVxgzdY1kIku7g7mLiQ3ZNdFgkP2A+a4CmszDcf1XJmUCRSWI9z3ZMJolLph6fC9pMFRYN3Ocd6NYSh8uJiao4MGjSnmvlquh2OiGgH+iO/GWCANI0XCEKNax0YzY+Q7t8RZHUio4bWhD4iyR8vTMGDFc8iinw0WTTUio4oNG5rBMhJXG06U95aQxqTwaGNTqP0csjciTJYOUxh7PRMLTHYYRirNJ+7bBlc2BYGb9Lysn3xeaU6La0D/IcNOaxuVkD5hf9kb+XPb09uEfkTwsyMIYhMKJRThql+DK8gxGXns9ls5jEPTkdczuXI9mMbVfreF+aIaOhexsnlfjkk6zGS8h2MCgkRGQ9dNm8mRyDTMtupHrRSlhP683gKdJ9NQROfJQW2liUrDYtbR0GJhSvM8+HcFjiVHp6AZGTdHpAbXZRj0aAbAFm6oCPCYTknP3mKUsHADYf4GaHozqpPwOKE2FaatPLeVgAs5U1iw+SdDghtCHcVZgEXoRjKdJSGVtzmGtTi2FSj6UbD1xCyS563c4jeUNbsToIjmmb0Ha1DMy2c8qyRFQpDGflabcK7IesI9dPvRTdFIuXqPL/JG2ExM4TzPSRcopeQCz80ImxuVIiSVL7Tzm6Pg68tndgclO+3vPgjmFokHOBY1paQx2vzmDUHfiDqz9yrHvBqwLbxmG8AJTbiFCW86hOHnw96IuWBnEckPzRhcwH0IIKlGV2q0ZmU8rpa6/LXLg53hWrpvTLYaolPN85lfFXCAG3HEcfZO203x1Km7RV/52lvROM0UxRejQmvIJe6+9/lgFzz/xo0g807nBJpvEtgzLLStVjpGMJGXugeGBI9lXLwqn4hx4BsL8qWMjtEf1h8+H+OkmW4Jx1bhmhuQt/k3C0XQ3Y20E4XluGEiK8OKzfEDxWAuBWxyGhGvUmjGit5xiQ9BBpOsi3wm2B0268U9qvzCSLnu4hyWs5HUMxlk8DApzQFQSGlY2gwBf0Lng/eGicQVUIWpdCUAnc59w/0Ink9+T2XWmNdjPec9SNBcr2cNLxqzh+Gcwn2ONJ8SgkdsEp0ac7MChE+w/pk9If9G1x7IiMj4pOQkpWltM3B/Z2jEMBmrBgCgzz2BG8ppuJYYRlsbCoDjIZDH6FjsU8pj1nCUzbQE+8Dkwmx0f1h94w3/1lvhZ/Tq8fCcIBG5CRlqYAOlMPetJJq5wt9l3JMBpOvMI/fAxActHWbCBJmM93JMQJDIaIrtxlxs+MSuoHGkFkzsqBMZ5sJKDaxG0pGikP3FG2GdqJhvJg/5AqxEh8o4pqOD7HTTo/rahUPBe6XOLhhGvrAHCSopqKTUNaoxKl3buWliTKPQs1PG56IYMt4jWHB0c0YJTxl5vXbCjCQHHSZKMRxiaGuyKNoPgsElQS109ZQi2j9d3d/oCQWwpgiQCkrD0XI5NndqDgnzR3br59f5Ym7qgj2f8xuhsQbNlJ4HLIY1AaXU2I3A57tUvBXg9zGEn0QsVcKttgUsI/p4DihToe+HDiorRtODoD9GJ8HERM/CUwNSEPUESWAuS+YB/T1IQ1cfk9HeMPtjnDSF5yBJcT0hu+HxF5ttIULGBb1DmJagXhfpR70pc34RwEXDVvBT6SKbJBMDwwKMDRPRC/aJMbVuzvVDHvTNbkB+sR7JB2B/GClG8/o9W4LghjFeFqCbJpkEZaqIvMsUn2ryuR2FCCUfkAE0I4UszEjX1sPcD1R3pWOz4CggXyRYktwWtgLAm2gBCCmiiS2V15tYXbAAWPTffREKUIBSZBjkaoyK4yFbgWwDU2hvkC4+1r+cPlS4HiVBAxmmu8vOO9ZpbQ3wO6TP+oh3B18YNjTaAbZZDVNHM8WRhUDz8ZZRBR+THNfjPB5OenrBs0D9ENzJM/f3MWu+91u4bmAupAdgRAr/hnZc9Oc6wZoZleDI/UDZK9kGZm+AAv7uQVRhXzKMYq9/7nONRWbUM/1KAOgkj1lwvcCezqTV4FiK3ZujfkgE1M1a9IJnnxaSnMORE1Sh7xINcA/YczvEtap2Q5IMEEc9e3JGd3OOgIyY+0YC4B2A6SyMg3diTnzVMmHSZ/29Ur3+dhh44RA2kTl+3DcEx43/nbDYYuCyysInYzIm49s/JiBIZDSa5SSfcgNEW7GAp66zGXOPYYNa+QUwu1MGN+tqoEdjtIT0OFAkTaZ7+x/8jylouwk2GgW6uZXoEh2y3zkpl1j0qzFO1Gbzf/pCmMkhTBAHij6j7wx1v1oRlYmYzgd00JRC6Ga5QrfAaGBBxexIPiiP2YiFFsyeipITYczUkL1U0L9zQ1RCFqJO5xnYG+U6JAeA7ZEUGiOLjU4PhTpMIMu1FhyYOgNgjSAENpRzM7aAzVj04p6m0zwBCW5OdYNGiYIBEToxrPy7MCDAlBP+TTP6iCnkMfOZ7MTO8XwQ1KIZKwAeen3osZkY1+Vp1GSUAE2O78PXGLGzdPxyGMgaY1ecZ/OdxSOE343fh8epqUS3N/XCEbvrQOOXxIsh7sPh2vWWZXSiW4zN7w5ryvV46F1Sr+tHtd9z21cH2TOMs652Wao1/TpKJGs5yLiKtfaZTtDZNADRM48EwXUnhqHsNNPDKau3RP0LkmuQTOzYEvRWqB/ZF020cZd9IZL34bMT0a7rILhg0hJofq0MQawZLRC28DP9TejNFKCLh9alCq9v30N8RRYHYlwLmJbnABDa18cYHiiYNIGEPhQGbEEBx9S0hPIojYgfbQkmwqQn7LmgjIlJRCkYYSlkTzXSUNpjwP3hjnlwYP6DDwdZrs3o8/pCWkLJgkkwWu+lAAEAAElEQVTHkeuZsrhGTHN6BoxNLUC57sKHoyLwwbVdC30CQTCnL15+I76fYIQ0kugqyn7A0i2ft9JMRrSSuUYpSP1V30jq7KnQMKrA6mNCnZrWEpzlelw/5q9zjvuhHVhzY3K17AokYWBOtu+Hz6SUjya8TKFrRg8SUAemMdN+jCk0JX7tnsqfj3KHB15SMCyrj1hAvXcFMqTnMS9DekYQRv3GHAFgGuICNDeNSdmH5mBxc07jXMHzXtdD55bmM/v+GJN0mMl4D8cEBImNr77WrLhu7seeXfxPU8cxKUvE3+AcIv64EcaC0cdmuxPXSJ9AvKaESZzKaVLGs4EJwU6DMbbTQXQabug0LK0gBelocimhQdxfBRMpHYYGCK10vRLdLqTBdDYxBCcKuwDGRkaXbS70ZHVoxv1JdNmwANZknMA0tobkpR2nzgWptexEMRpNj4HmhBmYMYZKKoMGh8uOoUME9smyb9qi4NazTA6ow/etpImwiKb+nVKbeRSg+nrOOjlAQhM9K4AC0zwKYZaEzDKVfcLvRuYDSSkKDhCQYKxvQU8U4hEC3HDMrcuCrA4FXmLxgUx34agl75aMFw6CGJ00Fxw3366HTjsTWJR90r9RLSEKWYoXsk/wnZu429//x8vd6v5Nd31umfvnf3z3GIaJxBriNbxOU+duRzfYTNagdwhBPuMj0gHvcA2P+rl3tHdzXG4GdhSPkwkFFZhq6TnLPjFsAZooPurntFzp/qSEn4J5NhltM2uDXgRqEJwcOhEsBiuYit79ZR5eI3APGSaMJou8cjhs5oo1Rj1uErD3sh14DZ/D/RbcTlhkQcJJ40IWnMNtlrFCnxgjJ0FhmkI61/EAwnkyP3MtFV8YhxSaijGqAMxMp1u+ZwaQjWaTLFrLrWCYNIf2smdlFE/7wm5w9FLYv0jYD8nXPAiRsegHw6PEPdiObR7Uyc5BarsLTaXjVjJSroNkD2CRSWSjyesGew/VX38lDNhxCHCWIpHEsEfICgGoVuEztEnFuSP54kvx6F6k7XAPQmYSE0PUU8vsV7nGUJoq3kBsrBkZMQAR438jgDzn2/kd/jr10SzJEF2rAEOeAcA9i8bcjAcPU6Qgtcezb1sQ+KBks3fJ7i+ZCJPPwhtoGebRWezVxFzepLjAxyTDvFwDYGv/zX+QBY2RCFN7AXQtJ3KY7rmaJOROxrscExAkMtKnH3ZpNuXyP/WpL5yqlFbJjWP/CCZmorygvKoe1nSVQKlLjt6IO5vzGLgRJtVujD6c9GYukgk2DanoH6nrZtc0hU7UmEhpdCw7MegGJlgICtBnm5HDjbtGt4d0Q3M9bttN/XC3P5/Zf3s52GXN5DXZ7p1hqjf+hpF09VftRocdgWwLOmH4m0RiDemTYMy/sNFI0J3RWN8RutPcUGWkdyO+shlT//Ub/jU0a8Q1rMBEab8bGDTGKBYbzwELSCnSenPha5hRry7PV73Sb1Smrt4IFgzGaJcSJNEkJ7jval4bATa5qeOm0kRevo1OtSQM1ZDNJAAj2cHVQtsAnfwdY31RQI5E9jN9EMX5dsig4J2ikihKfQjqEKBKsG80Rp4SF2sALzJhrsfZQAQX3Mi5A5tTt3G5cxdu54tRyWTStMdDryaCLWunokBYjvdg2g4jEmPn/O77+b8rH9oSZPEZ9lD7fv675ZCrGWYTzmctBpe56Y6DCQJ/JzVBNB1x0NXNHI/npkAh2X7msfPh+YKFPs1HpYNpwO3rkO0AHEnh+dAe5xP7wh5G8KCgF0H7OTwGgk+Yy5NagHKCIACYEgJ+YOj1LwhQzRQVmjhGTIw77A/66YA5kXBOFLCHZo811yn6c4gnFf0cCLDQQJYyLHUvqlGEcy0xxZwU2tlBD5iVEb+vGlKhVGRDNNc18axgOnXKRcbv4jwbM3Xsp1IxczVHiWvA96IBrcoUmL7HuYNsBYWIzTq/3INPKdlQ4iFR0HiYnhZvAKwi+Cgmp/k+FOpM1IHvUS17tYQsKBT3nAeM94qMPkDT9K9OBaVXBCCa0bsG4OX4meB8WcEMNsF90r43GSdg4HKO7Ugzh2GQ0MyR8CNS+SF9emiGyjmuk1JFRhNBLdzPS/VgmozJmIx3PyYgSGQ0ZklV0jMo72grFmZxcDcdPGxcaRxlOjoiTSk+4D8n+YtvhOO4xGCrhA8Fky16byPulp162ZiM1i8LepxUU6DkXxGk/sefX/y5f5GsEP9jTUPBbVYzm4IxUoKay00sabHt+2FxL5/cFyxeSM3V7gLRfWPAB1MyFskd4INRwNg4msQPobyO4KdAaQivU0GDzOa6zfj7q4wUfHx9dttKstI3/EJdIh0lBU32zl5bvEzjXM/tWBM0y2Snvj2GXf6aJoibHSHppXfZX7PRJkloYFeJEaKMauVmSICHFN463HiS8ZKIdKzaijhlGsBC4qCeO/SSYQFJGnn50I44Uwud2mKP79RmSFfRjp0xyQQbyNzf8LPIxbeCjCSCGxnkKP03bPSeoaXz2sCgksaqCtwsOwr/AUjUCG4wwaUZg3PYcKuJ3737IB0WbsXXT3bNMtUwEwksfcof2GlvBgyS+exWPcyDADRqyPDUk8PEazMlSiLFM3hFMEbVgGc8TvWgwOBrHDvqkqZFAJF0dcZ5JmQrSIQnmSSGoYB7MCZFad+biS6gp5v7hizG9rzj+qLgYad6HKDvwAoxDYY0i5qJE1x3uE7pzTjbjt4fZLywaKa5bicVjkaYPM+Ikk+UIchrgPW0pGSD3WhNZ+Eg8INiLpP7ln4KKY3W8Zk6CDbw3JpkDwJkkQ647ltMdLsA/zTjpHdYAgC6ACCig0WrYXXQy0w78twb4FnjnMDX0xeo418D6RXPsz7TPE4W8enrc0FwQROKSgLNYABlkFFVlDO1oMhs2H8NYK7xPNKEPRpJY3+UIGUqlTmWqyGfI15nY14t6U/VWwAkCIzCP68nkkMHuZWZ45D+xMFmUTNqPlMEOSn54zMsDSzOSd+XY5IOMxnv4ZiAIJFR/sjTrSdIhmKud/FmlM5r9LlEk28iAhQO1XcOSLQXCvdsAxI3oEvPhcZHE78KRoHlDjAfOBHLZrcCkDNcNx1OpYDBZTMGX/a68NGz3sSvdwVdLRrWXbDgQgmjPaNzZY49mSTtG6JoPYJNLIsHaHvZyWtGsQbo/DeBrpN9I8wcbipjm+9yr9849gQUM8Zy6FSPlgO40eIDZovpM74Td2cbUlOwAaEpaTNu/6AHa3o3kDLC6FoxTKuWoROkXex7Y27zVNx3gu8FiUEf9NFi28qobIWSCZp3zm2Vohcbj/5VAEk4n8NV/ufBFekaA+QbrgeTAh4S01Lcz8EAdLgChohz/vtMn4VUCdKH9vWblgW/5/y61UFPFDVnnb4wCp7bCsdVp2uj14bgG3+e/5A13+Q9ZaJbUYDyvu1L8k6NuYcdu95VgDXo7jej2LQq2KVr4ncXQL8GqFgwk64F0KjAXsjPXgtL/ERWwA4sDSZ75yAZZKddjaTRDTWmeZTSqZSBLAB268GwMJ4PkrzDopsyERpE6zAdXRbNTPBikaRpPyxmyEBiN5pMNYmCrxiPTeCeILx4ahVSDIWGKcTUzBqFCDuopKS3xwYQu5Lo09AwBp9tMQpmDhgfRgKkMa485jHgUSwBpSat/tQoWGizG90eN4E5SF3JxCjJFgF7qP0d/QzAcjSeWvp8oUNP804jZ2VDQxoPBjxCd7w4DNBBDGAZ2Uvfhuqtt4P3KtNDOgAHClONqOUwewXMS2SF1EyuU6N2fG9KzIqtmMuVTQTQkk2e9DEYzbIpI9emBhiY3pC48QjT2KS70JiUTF2cvxLNkfYYsOZQdlQDrEl2z0QlOPXxU8G9oknQwpzWOWYY15O90klpnML+Bt8zpzEr5sR6kximAmRjo7Eck2ZlQEtIzg1TWsYCaNlKP+L44ftuTNJhJuO9HBMQJDIGZ6+7PJu3VH5SVlfajUqGDS7d6dkhYsRudmdtdMEwxnIw2FSDyQTu9INZdD7oNE8EXpgg7G7THJAGfjVo9KoP7r8JjTo0ydQgM11A0w8qmrRdBj19o+h2YRLGzktF01eaiorBVw/HU5EhQeokOkfte9xEhwUUYLrjZwDFSmTKdww7YaA6eBwyGTUiw7kpwEIwhS3NxoRFMPX/+6r/nj/yjD8WFJlTZ4SWGUk8YjG8/LDtvs1vWRVmjID6b8zjZOR3WHS7oExDfUTmNg7CRTOAhwzFPJlJHfAHgATNRzNqoJvvsx7GnrfDYE0KRpcmF1CnOkLqC/1JaCbbHhp8UQhKjZiIg6+iMhECTPQvMGa04rcyvxrx2vhuFWVDwMcK8c9h2g0BldFOFGK1GJvi+chvIXlm07T7/75QuubuL+rCDTetDIJFNUChpFod/J7qz5GCWTO/CsyUjWJAd29Mv3IqajZpwAHIZMgkacYQQFj/Qpg5Z9IeVEZwwG+WS5g9cmiyB6n0KaRjJpnjBtarnRKBfWEq+D1TFMoEPXRwI58D0GahnslaZoxRMfdRAqP+VNEoWxT9Ko3McH4T0tBJ92cBvkaTkO6ECxnILEoBOlgYEeBIdu8Im1UqMwrrJP0YKs7dIqExkdaQTDANJScjQZgjOej6FYAPw0SE0XD7GjJGKP3ltYVEQCWoFUC2dAvuSZqzM12u7bz3g/suZePE2Cc1GkvV/Nx9Y33vfmgSjbReGDkMW4cHLBOkdwH3FKQ2+SHMNyq3RrJThihbxpUnZRH1DjMsR4KcuM5qDm/AWQKQaNLxmczEF437u/qH/X7EwRw+uyzzCNko9POB8T6NjxXQqMBENOlkGyARB6DfjP5lNFywZmRvYh9NXzdh6xmmMD4z4Twm8lx+TzNf4r20+Zbdm5fqauicDTOcjMmYjHc5JiBIZDRJLFU2ZbLTaeymBWxJiiGK5vqwn0gTLIwsFtrfUU9KpPwWCjPRs9IgqliJHPj1kMkAgc808oubvY2IpMPGkwZlHX0uYy7Pz4bpomo2ho1PfRjdq327ok7aXJwrfLema7z484nz4WKlXYDgV/L60eBGnp0zZZaUpFqj+8YNaX7K6jdLmLxVzzwcNN8sVtqNWv/rHizJcnxOjiKNXgjUt8vmoKSzOxbj4QaJpINMgkW70dAKG4jABzv/lM2kV5EwsVrkTXhNuSxMPc/P2Q7PFKKa08vYLPch4UEBPDhoC5ERfGFMOgwTVCj5aJr4L/j7c/5x34EcnJkNbroIqjVj+pg/hho6bt43JVgU6sNB5lc5tSYIohBcaT/zQrjLl+EZKFbIJvB6EWR5DNdA1ofzlMNwrhkVvVSSCDgirCVuRE2SUOXc//T7c64hd2xZM+ee3H33Gc/k2hDU4nlPIyyn9j1iRn8Am3onLkWLl/6xi8GkFgcQxBgVNq+5gtQupGwMn/WARI/YHYBtBdZM8gC6sUzPav8ODJYScjUCdoZGLjU3ZZ+9I5hXaST9LgaNI/ncNKOGySbTTJgwkeyVuFt8bxPlS68LJJO0/8bPxQnIHx7COoXGR37YskWqHZvDkiZ0jdUzgCBIgnUlBnxoWg+B6k6CR2TUiB5N9oE9QT8lSk5UskFmJSPvWfCpIa+wSRZGccSyGhaPS0BKmttSwsL7ucPQEO+LEOvp3Qwjs4EUpT0G7gcicdJkZWS3xIdkjDwnFiWcIrGJspulDoJCFSWc3zwUBIF0GNYVj5NgDSRU7WfyZ8oPIQvUez3lvgXphclGf55LsOBUBpacxz5sBxpziOUlo7t9PzQ0uY+tt/lnPV/lQajqqDX+NxHnuFcTAfmWIlerTsUZSIvy7XL+wQJBmoaIsqLfzXtMxmS8izEBQSIjnb3j0qyypkegUCvSTrpfJMjB0JlpVKiDIADppzRtav8Np/Q+dP0VugsmxlaKNBN1BnSejBXqyDuLMzoX3BzyPOlnmvd72huzOnwX9ddgx4tRgMV+UG6pI5dOGqVLlBolj/uNb3JNNpegDXOhZeejBtBRApBq349AATq4mXw3DtLNixlE34H+yk63Gnz1YOLXMJmCm3psBtrjRAFawrehADNmQO+XZq+LznmGgriEDwo7TKPVUhSwoL6NQpldHdE0j1aiY4VNB5Nz5jeAqr5JDNPg/ZGsgBaelN2XbTE5/MGn/O8IXsFF33TvKMVozsclvymu920NAkz07VBQg/U02UA8FpX98Nz2Lt8Kuu6rjIpSnfQ1dI0/7MG7wenr0YhA3pNTRy6Hu5TSwc1hdFuuGkTBYXcvurP8AZuWYApI3CvpNRR5b3j5S/t36MIXOx4JMqBGO/wz3XvBFisVunwpOtD5GDNVFvQ1QVd85sJ3bI9L6NDs8HPzXfGZ1gIW5zolUwteMpQfVphrmtE/ejEsraShIlkUYwozs6lnwYpCqP0VAJqM6xy+ZwVZRMcbAAyHms+dmlqiEZFvnQkbJ8Nwtd5sGwcV43MB6qgZauw4TUcZNHyyNI0hpbBUaoBXCaWmYqjL44we1xi2A4+ZTZ3y9cPRWPhEzG4XX4+/S7D+ds4ZpDJGWkL2jTRyKEMyHXUwF0qYwWYzVmobk73wmaL5d0d6RXkvZTJYowrxQ+LKxtdQ9lQBoGvHo36vkp4F8A6mFWVwei3YmMowrSV4PZle7WvAaDL+MWye0QdFrg3Bv9FTng3Uh3eZmn9y9jfPF5pvvLYqAzNyGIDODmlaJQBCBT4Mwy8SCW6Ye+3ecfb+sd000BWZXf02wB4mEclaUN6b/x+0dJiJJ8hkvJdjAoLERrMgNGvdR7yZaQ20UWl4ZpGA3psdYHcCfhbSCSthKskJ0iQ5SJfRRK9ig59Sy0hHffqDiNY2I4gCxomaqaZA2hl3l7wFxss2MDHUAR6FQPKSX2QK6FFVx00XfGPe9aVvBqUk6UXpArEAg1EfWSH1rq1xxgoSRNKbfhNaQ1ub6DFTn4z/nB4+GexutO/HzSYKq/zijSBjh9IJNSBNKYUA4Na7JF0QbAgon0hx22hsZwYD0mIZfDgueUBiuGNtMIlDAYnhOv9e84hR7b9ir2G93xcmNz+4M5xmQq8SKUZvbxePkYA0JPmhD9jjZAePNFkwkG5+ZG8Q0GnGFF306bPDol8TFggqoUNVABzJICeaX2cBplUveZDu5hObghIe+os0o6bxLbwaCrJ0YOLbuyKbM4BPoy12s7cwkspuPHnfmGMRX5r0XqHKqNn2GK7D2wFzZ3otEo3dgjI8h7g2YFv04QGVSJJShQ2/ZVch/vGCJCyUkJPsAb37KgCqMTpw3gOcoxN4hXSiKVmYwQzWFCwoJPonr8bB8dMAFCiPunx1SQV18si+sJGnRFs6Fv6zkCjgc9Qrw3T7aT7KhAYaszavOY9Y3a1gdWDNHGfAOrY4XvgbkTIYBienNRY8Y0B8kxbD35FJIb4uRtrA5DX6oFCSRiPQ9j/g2QcblebAup+oKUmlDweNcm9Jig0HDZphfJzgOpUChKX4nBzSY3Nc2MMo6GFSYLjvmYuzIijPIYhhEv5wDwxeFbCHfmNSxMcK7eo1f0+m9EVB6hjNjsvV9llxG/3aVjAuFlHfZP+M8wuJsUJoPN0eD8AiesaxeeX4szQ13PVbQRDBMHGw72tGdRT7q4d2h6XPImWvIONJEUVsPOvgc1Rz7h0jDTSgEMMCxjGdAKLw3iTgVz9gIEjybYi4DbvZTcZk3H9MQJDIKE6fbXKsbEThGUxQO2WR+oDvmpbYyJNhQVfwWjTRPW6eARxks2Hzz2Yk2AAQEDGUW36mGJFxMVc38pgBHo32ouZ8MCBUw1HDTAFFkqg7wZVmVG++HdxUOySA1K9jM4EEmvY1dPtntwPMnESonARFKjA5TKeC3WhJ7nF4fWyjpKZeHAN2O7jpQES9conYsTP/HbcgqaTKuqHEi2wHE8vYFnbYPKNoTyHPGUFKkWTiZVP6e7p3lecNvjYH/LVRCUh+axhkn/RuQPYET5f2u81h4yPP3uIxw1j17muKIHBDZtHUpWGQrdKM4Z5NQbPh3jV/PivIAO6+dxY8TIKhU/CdKJZZcGCIWNwU4AbBIgUaKMGJsUqMyZ2w4CjxymfDxUNyyd7ro6d2BO8nHmf73vdkhmRDNWO4xm8qezeLcDrOFbtZrTD/1T8EbyAA2pSL9YQZlO3Hpph+TNisMypd78MKkY3mGaLETjbYjuyNGOVXTBAJcNBLIJ/aH5UKcSSHLgblJGWzJi4eaBVdJ0xiBoAPghPKsKDXEs0WU3SddR4yhSKYLaSaa/ICU0fYXU4RCcv5utwrEfGvWHZRsJAZI1cwHWFKgGi0PiY2u3zF35M5QPTiTSwMYrhJVoIxUyUgIGtR9qRnSiVn/P1Q7UYsL8DgDsjFzwegUePnTqINPWMAqtHQWAEmA+wBoCovXAofizDSDPBCc3ZGmKonCD+fJrw85nGmmDGwCp+vSSuUqlRvHQneAw6G9DSzVblvhWvgADB1WBU8bzwffD2APPXJM/cx2YaMBNfUFDwHTOeirDoH47I4aAHL5LnHI2se5Ely3yZYm3k/EOg1ptIiVXIHb4Tncpj2JuKjlXwYLFNES3MYs+XJmIzJ+I6MCQhyn8HOu4PxVqIdSxijsktYkjrOrvsl2eyiQ0LNZIX3amljvHhYNEts6DIYrtHnoNpoNx30saCEhh0Rt8NuApMbt8MbEi6GcOU2lESh03Ijbcz9pDvOzkcFjxXjNA/GDo1I29+h02pMtdDh6mzKaWSF9zYGtpBAcVFTSVPHbyQyik/4+OEEsb7ZRlBbsYlXP4khuut9RJBSvpCLYdw8wIr0znwQ0EgkIrB38kpw41Mjnq7f3x+MlG2PB88Rb+kBNpEJjQ5bEGRZ2JwPQEV6+FSQvdOM/FZYE2z8Tu7IM43NiYm5RDFXfdAXC/3LFgBgShQLVfVwiOqoca+uBEjKoqAPA1z1rageopGn/3GK8bStfwvmrlW4V8A46SGyWI0byUwh8EDqfi0UfzI5zNAu+L1/M51GmS00QDXeEmL4WTy2LcyUElBn8b0+LNK1Y+eDRUENaY+Cb6N7xq7NyAmIM5YRenMC2O3APFTwHkSXsALdv30PbOTTKzfvb1aJDn77esa4omik+agaXte8vyOFqaN8grKl9g/zcJQv0ycQ2dkO/JtzrPGhYlLZGNlKyuuBa5CdlK43is705nSwg6uFOgtaggBkD6a3cd+LBJUJQyzyHO41TdkovvZaMK6WcfMGRJIufoGmhJnv4A9imCwKfkVAALJ5OpIPjI4ZaeR9ed0JfHBvQbBLR3Y7HDWtzZuljNgxGzBBiuMaIB2f2869bt6gCkfEU/IiqUa81zI8E+Z5EH+Vcect+BoBRgkMmnQWgLm1vMbEhROww57BMCzk9Q7s4gz7RjZ1aBTf/m6DvwcyxOcmJQBLzL3KRooBi9GkGtkfmlhgzLG8T74dnkzfs6O5hyONqXf0HpMxGd/vIMju3bvd8ePdTc7P/dzPud/93d99R++VPbrfZdnAJSf9wlpTgwwwoBlDxKVSIz84cz04+VbrLMMiBQiS3pwPShE6ekNMsuzcsLtMrxKzKDWDchawIhzNqjRO7JYHFMo9W4PpOMnt+bjTPYEPdMWSa+h8aLzbvZjM9ueI+VqCfHeNGTNZ9uwEvv1WdNNQMp6txmaR34d6XjiJt6/n8e/3m8OsiHfUp07Ohjt7uLYEiLJXbBeEHRKa+LILUstCOvXGmfBCgnujmhFZAMAXyhqmbviu0s1tflO9TO4hQylHoTq3qhdNMKF3BpkHNN8cVP4evoPP1+82WoGEAoBaI7Aw2pdAx0yvihLPdwFJUoEEm/a9kTzD1+crrOwmBpzMryd7xf84yP29mr9tEzPmH/LnduoVeEiAzpvC8+DuG8JRH8UpZU+my0uacHN9X/dzXImo8OzKjajhW/bQnjDgSBq+qxfnr2VisGykGUdOBJkDOl8OaOrI7jQ7dvSiEUaaYfLR+R9MEO0095DCUgHMrB7ZFTbjE1kdvVTIViA7TT1BKmjUy0fCsZuULfUOSrGDc0jGSPWN01Fglx4h6XBVGBwHeOmm5fW47+jJ4SAbZWLJuPnKMSJYOs3RQY8TXINiqwXHmRjhkGCS8/XC5uE9lUCeE5VCqMcLQBT6slBCU79pwRojHSIzFM96ddJfz+Sa+FZQzgJ/iZQJeWROKECB4pj+OVybGQPffuYFgD/4HAJuKokiU8mkzfDYCOqZ+cWus7GiXYdppGAfGAMN9L+TAVNyHoD0LFdAAufAzFGYk0zcrpivGmAOQAM95xgCoOAowWX1plv87wIAE2AxCXvYH6p5KCVm/D5mvhHpF0eGa23SbUZg3Aj7MnuDnhy9oPTaAIFiIEvgg88NP7/DqMYwshc0II3sqbkGb989n5OI3O74VuU0k/H9Ox4oEORrX/uaK6H/fPXVV90nPvEJ9xM/8RPv+L0aunLiaiMzSTesi2520y+8GNSmluy8YBOeiia6ZqF58lywO6Cxb0a7zE0HCoQEk3dxTmLwcK5YCKTswgsLgJtFyicqsFzSs1iwQbdU6iCpmEY3LZurCiadKTcgXIypXRdAg/R/U8wx0k83DSzUSdPlYgzJSyehga7x33g9eA+Y5B9dAFHwGFAJHQVNPqBpa4qNb4pjSwioNCNSgCboFo02Wj+N9K++4V+C/z76IZ8WtOxPPPiWknKsndZZvwlKvg7Z0Uf85qz9HEhI6oO+K8RRPe/P2eCKFKPUPrPriYKnJ4Zpc5v9vwfQiA/h6TE474+rbxvyxhCPIN0IYI+J9W29P7DZhJxlcMjPCcN9cK1Xd30ATvNP+I1vCU+NqXPSYcKmcB5AzrLj/lkd/eiziz/PMW5Y0l3484KUpf1eO+31JFPp1qP+Ph5cmndu8asmbvjpD9396aJQmMHkmPu4Z2z0kHaUbbXg3e2ZZcHrls77Z3q4FkAHfRrEM8ekNMGANZG4WsbVGFbf37zk34oytilhrzAJAc9nGvF8UKA4RwQl/8qwUujZIB16YzZJ8Evlf5y/xdR4YSTw+tBRYm2i4SY74iqfqJdBqkqPLcSVMyazPTSm4pxB8g0jzl/11zPDZ6gc1KRU8Hqw6G4GfawwDBuHBq7a1URhxsSiPlKq0m2SgnMELAsA34aVwhj37Vui4EBKxgqYoVwj2t8BWFzw8tHvkwKgql6z0qIikrJhwImOr1k4Fpdgf8rmwOmLcRkT90do1hjQoZ2LroZNW7G2z+/EPunPXjCvr8lYwd6ioqH8OQG1aJAPXzEjB4JMoyONxTGb64G9msqtq4NHg54gLmbsyv2xPBOUcyYE79CsaY+boAjWTEYbc67opA/i/uY5GyHBS83IU0rRmLh3FCAIQNbUCTiO/Q33ih0wk5+JeYmyFzYGNYVmAaBpTcHjGN1kTMZkfL+CIBs32o3Ab/zGb7h9+/a5H/3RH33H79V0wKqs7+on/cJSQteom6sEjvQxLR8L2Lln7Iaufw2FLqh3ycMeDc4u2w1ZDkf8avXyYDwpaduJ0J6rIyeD8YP1cY9sJ5kFXkp0dDMY/Rka+MrlQeq+bmTrsxeCVO/kQ5aGzoQDA2JEDKXykb0P6A7PUXPx0wEgxtCGsYGoDh2PM0kQWZxtwUaBPiJTUnwwipDHifNJfbiaExJsuP2QPwfT2MiX8p1zaPFHD/nv2TsPavBNAfxYjKDTWlD3i00wIzd1MF41W+s3gclfe6ClGTW6htohWXwNTNU6zu7oKpWHkIDyKHwShLLavwq/D8T89q7D+2QtTU4ldQWsHUo2uAljVKxGFpdMkMLrc0hTNNY3A4ssx3PjYAhZ7bf07Aq+KkZmgojC4mN+QzkQ2Q/9LYoV6B6mSPS5bovmcpXfcC9/+UwcXL7H9EnEi4FFzvQQwCJeX66zm9VlXz8W9I2oATj2cd/XYkRtDIEwEhZpIvMoT1MmsT1Y8FSM04Svjfp71KuWB2VHavbIVAUT4029Or+LMCx4bukZxKLVAOXtHyZB800W+hUZBSy+mn8/hucQRrXJC69HC2CHdYqmscbnQWJYmbRSEGC5DsCMPiTCZEwQMWtMNbn+CxPRFNFoVrCwNH4zMngfEoAuxkkR6CkVkaaYggvMx04cM0Gx5eFEm/bY5lcHpRlGLjCG1WGiaAmqYcTSN8bF4lYRxk07YhIYSn2UzYp7qjR+XUhnS7muiMQNQFKOhJ+CyUNqrkuzdzKQAGByr6Wmmgk97ABEUZ5Vg0Gm9yef4/JY2MNCo38JClVoBCUAaNSfqmZ870sHg2b/fL4IgumgjDg/eCx6PY0fHp6pbG3YjLUzIr8zrBY8jwr0xuqFdGZTkFFUPWDGqJN0mMl4L0dSq0PnAzKGw6HbunWr++xnP+t+5Vd+Jfp38/Pz7f8WxvXr192OHTvcx9x/7/KkZwpy4xHwmAUxaPbEjh+lMdShk4KnZp4mEQCdcqfadRRZZgH6AU+3zy+Aai1dLUpDEgIf7JZpxw+vqdBprV/y4ETGiEH6WTTvDUNBo49GEoPShOm3wfNRs1uCjQHp8Yrik3FDs0btSNCwi/4YTI0xsW3i5k5JT7UZm390onRh5b1mPv8b2AygkCh22UXS0OrRbSqf9JuR/IT9zLlH/YZsgO58ic4oI1nb78PivIrFlkKyIqaWZtQRFgQKaz0GAgrx97Wvp2ymHKTB4+wYhNKIEp9JaQtBBzJ22s+BDrlAggnji+eRutK+H0CQaIw2AyLIThC/FGqv6WWTn5NigUUb79utMHY9hWho1WFv9yBAcvpCmPoum8Byk//e2RlI/k6ddq+t/n139ppzW9Yk7gOD/8vd95JON31MqrUAXQE+9i5a5gH9mWiOZ64buu4KgpASbrqpkAI60XGTek5PjIomoweQYiAGzSX8Iej1xLSCcRt0ppYlZAjyvcCIaD8z4rXBlA3tjseMtTlYSLFIDpoNLgysESor4DFkLPrH+HOYzjmZLQDP1GOFQwGOxc8f42fE7jTBt6hJqQxTgNK/4MSFeKEuAMXi8eO+4fzGNfLum2fBn41xrxq4kgGD4+H5pBSPRsUqMyCTskS8eCJ+YZYNirkHElQ2rNSIk0yt7DpA9MPHogl5+V7f/KkBLtf7PDg/P+PnpOmXLQjFvQZj7vvnICtcY0EM7nuMhAfADb3kOumFAO9iJsI6TERt5L5lw6tjtsyGEfbE6TcPvWPzT0qQ6qOnovNQ7P00KcwcJqWNl/3cV129dt/nfuwxj5kTYuDNOBPfhWtQ1CP3BfcHbnZ21q2Cn9T7bTS11urVq90Pf+xXXZ7Hk4mWMopizv31Fz73vj8nk/HdHw8UE4TjP//n/+yuXbvmfuZnfmbs3/3Lf/kv3ec+97no7xkRyM6RifKSjht/l+K/p2dAgxTqIFkZNKCjH0Zy3U7wNKU0G8JLN8K6TqXOQ4NLJgZNoDp0Q1AZDXOBqD9SECp0NzpdSrJp0GHqAAqgdJvoPBrtkXKsEp7IpombES1g61XoUkHXH/UakcU3wUSc3gnHyyldEuxPl5M6TnNagDApEkt0g+zQBWehrpvt/sy6oDcD79vqy3INAdZwU8puj9F7awcdDIOEm1JEzanvBBknxmQMGy3S05UOzOtuNpG41+Yftp45LILzm4j1XY8Umy1TUSZI/3rYDO72HngLyblJwMogS4TskyWBQLoJBaBSbrCbhPkNeCYRn9vD8Vcb451qRu5m65eFu3xyyDyf5TZf8CRb17lNZ/+TS5PKbViVuLmHITPASOFXwm49jXKHW8V3AtcnA8hGxgi722o8TGAugzzLgGV8iFsQGO8NoJxMihFlU0eEZUONOuRayZjECo4MceUEAFKyLUT2Yz6fUhnGhmthCDaMKXq3bA7Ko7R44bNmPGJwPllUtL/iOQBzwDz7TJ1R4AFADDvnKRk7UtjlALHrTevCIIQAWW6A9eijXjLojkL2SqBBAQx6gkAWwCZECZBVmXQ0HU/R3TbeJwAlm5FfgMEx1uYKAFO2Y3t8P4JUI3bxzf5BvBW412ASX3buajQhyUT+cnz9WrAApmRUi9sazJiY/EOPzRTH8OkZvIF9F/yP9F7pn7oabFzUlA2rlA2AIdkfGa4nPXragXSSuockJxpWy9xFU2ETUTsGsOMgQJPgWSmefSiYmqZ7JTMP3MR5BtikjE9KYLj+VACFFCAi8yxFHHXKZ42AvhgCpzu2Ba9hAhkWQWsFO2rsYynLJguvfc2Cn1A571w8xXsyJmMy3sF4YJkgn/rUp1y/33f/5b/8l7F/F2WCfPj/1qKT+cGTQZqwdr4qpDTUYH/kiLOsoenOz8gmlppHFAXu66/FN540+mNCAqNnMamqmV0NCUw6x+McsylG3jo7sKYjg0U+OXspitRzYeFGTd272V01MYlgz9A3hCatd39ZBdF14+St+k0AKUbnSbCHmnRsgDqeHhGGhC7G5ryDep7s2x3s2tKwrh24P7jZY6yw+pBwg1sjijjFvTL/lEi3kFRitPQYw9V+ozB90G48TWcR55ApNjRc1fjb4epeMDp36rh/puZ2ybnBMGAFi3PZYMcYLBX0xRW8Nqh71mOjnwRBUmOqqTRwFKAEuEzykPgE1TArTo4jeQCFSKcLjw0ZY337r8NYdedMNBqzhkZ7+DxMWwHScXPbfh9Gp+JZSWdvuf/ln/xrt2H1TXfx5ir3f/53v9T5zmo0Vz6B+5sMDTHqKwFs5g3VZPHN0mChPm4eHK3y93f/vwH8IzArEZpktCVMNUL3kcVKp8jh/E0Wn3ru0FMJRphq8hnyDekYChIEBwvARH0LuG1SYLAWGED+bcvWo+w0w/FUuGYEWcd5arD4iBbJOuejo21YDCIfNElXNCllSocwc8y5MdKYJAxYwly4/TMmdTF9CZ8/jolD2Qklk7F4V52HSoDTSx1k4BjGB59PSjQC0tklfQ5ZCVxnUXQaoEPm+BTrfKzbb66fsiKYAMI1F+Bjh9VxzIMoxR5EDr/4RjQJhPNd9Yi/7zOYmVIeS9ZX+ztcTwKr5vmU/YTKW0KDjJ1K7kHOS/UOfE+m8tELp3kNmoPjpC5LGYYFxkScHZZVmL3q57sEgKUmYMX2igWuOyU0BGm1qWP82+hZQzmnxlbfA6KKeuj+bPZ/eXCYID/ybWKC/NWECTIZ73w8kEyQJiHmT//0T91/+k//6b5/OxgM2v/paDLG25xxmkXB28GpESYiONPL4Q1JHSkYm1GiI59B1uCoCWc+uy76pDozaYWfIYtUDmmKMcfDpoXFU0cWgGLOGJQxk15d1rEJMeahzIQfs+lg0Udn9gzfWTsVpIRn+yO0SC1e6OxNwzUg/dxQKtnBpDegc1NSt4vir2OWC7+X+iSkSuzsyqax/Phz/pjR9U0QS5w8fsB+Ju6B6mkPRFWgrOog48L89x/znz/4gi9aqyetX8pw7VSQEdA77Iv2+mEbzUwZTyrSpZAZnWqNp87ejPpoLL4e/h7tca7pBVkdZGiQXUDQQxkSSQkd+SZEIW63wCQ9OcplWZgJApNSJ+yTkmk123CtcTp6O+xmt7o6F2bW7PKbvQyAAsG/Zgw/7O+b/mX/TNavHArLL2SDegcGtNPs+FHeA9Pd9rtx8445qX8aFGYxus1e9XNU+fDuYIqNKXLF+JHGwfVXsEGn+bSAAxwEcninpIwWVQ8lzP8VzatZvIl8I92+NTiPpZjXTcHHyMkQ+y/w3TRpjKaSOQsZvMb4FEgx6uD9UY7xujCfyUhQzNE0Thw3qNmPDQUHeA1YUGeIztVRk6UIVl8NHw7q/428qhlc9wlwYc03saHNe9OHCizT2P2p8a7sQif0c2CzQlPcEJHOJkLKc4Mu+jjQw5jgsqCHp0vnO2BtNteD5r5yPTUtbfH1NDiWJEAOytrI5uF36zwrBFEAUjpKhcT7xABRSPwrYh4vAK1VJknpNue7pYAenYHrnGyy9+Boky/u+4fPBRm45aOW6cdji8luDJOTfyPy7Wr9quBelWtZe9z03qAXHK8NhyQM5WC7ERDhvlPBHiMPxRxX8t54xO7VFtbmpGGCjElQfr+NpnHB5sW7fY/JmIx3Mx5IEOTf/bt/5zZt2uQ+/elPv+v3SL70ikuSnllk0s1PROn29RtHgkwMRh4aarBE5NKcsEa0mDEPU5M2/kxPEmyKY5vo9nM2AOCgbnYPOjQSh0bNJI/HaLpBq0wUuAHYUq1AMfUQ4t2+9E3zEgOq0CiWsh90ZpPtvuPakQ8cwyLFrpzEGnJTybQFXs/RM4go3m6TKEpQLB20vvUPe8aQg0zl7of61xS7JFVn4ZhxnbRYyV+GjhlGrQkWYHNcYwzoyg/5+3uAFIL2vbGR5Oa5B3NfdrLohN6+3wX4OVCiRZow0lA6ndo3jwQp1QPKqMZ11KEvJqCjMayGIk7wjj/fwDUUvflozSAoR6E0RtNhCJzQJDW7BQYT0mlIW29fv90/08tf8l3wGsbJZHM1Y7gbYCRAFF6PuZnpIFDTuZ4AmGqk9ZRyD6S3h0GA5+4m9t75STwjiCCWngPOhAUYM+qpUv2AL2wG59BFx2soK+hduRP9zN4IRtIwGswpXRNwePTJ5xd/njoN/T/TrzYIwHfi3H1Tu1K578y8isH1xwEg0pSOCh1QsoSMR4AmjcHTyYFin9MThewC6XKyA2vSbh7116wWth1j4el5QGNxHSxIjRwShW7NNQoeM+1nnoeEFEDzOMNOsj9YaJrimECJMntwPijBYbOjY467cV3Qq8NIU1DwsQPdHucLr4Vj7SnTlKjREnNxFQE4OlLX2MAzFevIt8cTk7DwnIEhqe+lsqxQ2psxbFWfnEiULveHyhBMyBTCXmncPWT8JbAnJOPFNKxoBNoMgCicieMQ45jPn5oKx8Net4B+7yQKU7BMyGbKxX6HnjP0rOPzQYCsgvG0etuQQcWEJCcBAeVRGNwTkGYjiY00yOU63nBMiSLQzHmwZeAOggbkZt956mwQCGs8QR6o0dwm3yqGMcFAJuNdjgcOBKmqqgVBfvqnf9puwN7paLpRSepyUjYv0WR0OirzMPpibooxwTNNRjfPCVFi6goFga7R2TMRtzTuQiGjUaX1CXQx8DkxJolScCt0U9M3fVcu2bA+Tj2kVvgEAAmybLCxaUb56O7g641JHHTDmejADasCG98MG+96lbipwyOkfPtYMHq2/8rx4Ma/fW8a7ZFZc5AxgiLBIU0Vw5jbYgEfzdjP7DHVAV1smsEao93m+hzYHu72o3OkZnLzz+0LR6JiIeqhk1bJRrOAnIXpMMN1/lnrz4opGIrTfh80eHhD3AJzozcrKRvLfRrH3AbQwzd59kquYE8alsD0wJyoX/ab5UwYTL1ibdAojwX4cIN9JnOAmYxondsC1hFP5zZJb6L3B2R1lBiYzVlrIOp/14NBMiOgszn4AkhEboJElLSEbwU7qMq2Y5wmUpaaiPN6oTAYFm7qy+HuZIpNMQ1D6UeUAyTV3xk5BkDOlJJDibvtEcxcAf8DSiGEwk0QOj9yJfh3RtYoYKw5bwSS0PFUc8OcczkAP8btjjMlTWiUinnEmGoqQ4N081gBTD8okXZmjFTF9ywE+OAw11B0+sFzK8wYR38LgsbXcJ3fsEVWFfkc85ljmIzmv8eK3vNj3hvrD40bjaGidssJXuEzjY+YGMhyiqFpOfcciZip0gdKpUtBJsu4+xDzQ74ShaUaX9L7Ap5tbFaYa6tmk5C6GpYpzdQByIyL3zUyKMj9CNS0r8HnjCA/7BFQkc52tcMDmMnJ82FDeTKjRPpskowARnI/kyibicAc9wBgzZr77paw+HZBEkRvvJfBMhUQic2TmJGyeQaEyUO/DuMRBsDUzKMtOxj7ifNhphQBtkrACSbKFGhgmudOfVQiKj0DQIuZeHZvL1/XQ+fu70M9GZMxGd+PIEgjgzlx4oT7+3//739rb9Ru8iq7uaOHhGw6TCY6FkOzKSbN9yOWrZDOoUtG80wu8mOooAkSBrjZNXRBofdxoa/QgSSCrtIHIw0BLTPB+aBXyFi9Oeh+CQrwesdM3CwLdPmYBEYjdo3G/A0wAmbQGWXxJwWoMarloo0N0FCKUfpJ1NCl0xfA0fCtGTQ2g1+IMUQEM6d3xnY8GaEZc53vGP3h3BQwccxn4VshUbx9ykmo8cZ1opaeHjnt60+g/YNiiMevhmd9dNZoEJzj83k+6PjejOGmlfEUmHtjboe9hlNHL4cBSKA9xYc8O2wozIMMnhjThy4GwTv6q9w97n44shef2b9ZRs1YM8jyyuX+HBTwSCmnLGuJaTc9sBKG6/1mc+qELzCGOyz4ls6AoYDDKTeuCHojNWME6VJ/DQqJDcvdP/7//L67M+/csv5wcZOvHi+UO/X+968F55RynQWYsqN+8zp6DgwDSoUuQ+7wlvVOSVAoGm8kzJ05nuF2MMISa0FNec8bJ6OdauN7gaJX5QtmAKhOrpZhcJ5dYxT9dz+oDsc8MkJUB8F6buQjnVUjN2gGgWt0jVnMJZSmatEZSYUwoIcU/jwfxjsL/gtMWmtfj1S3DK9P6L0yJnEjymIAOKDxw8ZTA/uRBB1pGip2pJbw+0oBiFOyqYlsZn9DtgGNesVkNAUwZ2LUY+k4soeqjsKDiEADmBiJMPxKgj3Yg7EYpdH7uEF2Evdd6rlTnvJ/l0L6RWYmn3WmLXUMQ/8bvI64zxBpSQJmR0FpDPeKBJHkmTYmnWTncn6SZ8XIlS/f/55W+QYlKGYHQMBTDENTgj8ArAyDiEDJQ5a9WSNBMZ+Gfxv+u3paVZAbu8eRpHcWoDmAcsNaE+mS8eiKyWlUvof7zjCTxOB/oS4oHzgmSN0B/d7Ve0zGZLyL8cCBIJ/85Cfdt8PrNd+w3uVp39WIi02vYAFWlgk2B+k2pIbA7NEU84cFCubmjC7pNGYTL4P0Qh0GPrAYjlCIcCFoxoCLOVzviZSrJpqLaT6zMQjQpNDYK2PGbP7ZWQUTQw0JU9L3UWSY5BxIYBhl3P7dTn89qo/6v2P5qJGsGbWy9HKhD8tXPQjU14QFbDRKakPhC1BqvNtHngyDEGC/kEY5v8tulHrXwV6BvIrF/dQbFuyZf8Sfm/6ZG8Fkjd7h4/Y1G3cHzxsjdosV/agDvIlqBlOpAKtD80/mtuA5RAJJwvQI0LMJ0LW/W/WB4PFQ/kBj1Y6OF8AcqdJu/QfC4I4OMLUyxn6OoUCzE5Tsngmes/l1dqM0dQ5soArdt1tl0IdFgbX0PBhVyxB9i67g9FF7PW/v94VA/3/zgIR5IqSDPtiDOMntq03k75++UtyLyC3dk/unw8dMtgC8cPKDoGeL1KvesjEIMuaQGvG/l89ayWN69ko4atX54qvUKN8GzQkkF6TnsfkHGK06dJNgAhq8KTgEpDSb7zVILypXh6PPKbnUOb7eGO7GkvatRScH1wWCBmIKbQwaEX1OH6scngljWSaQedayTtOElqapXDNNUfRlK80kO8jMA/wqmO+1i8zfaXG8lNjQlOsMGDt6PdxVrK2IWa4iJqe6ziv74X7H3EmeuTp7f58cBQyxHlIqZOZISZTh+TT3IBpO+balpbjF7uFx5ro1vicLZRbtndcDYCGrgUV/J8lvIRmkOU1kjHKOQ4pdAX+U9nPwHJh9E5pvHXNcyIiNTCMSEED20bhhAA3GKjfvbTw18qDEmyCE7hNMAxH76PTclagXEIHmCrL2kkAc5shiDABtgDTsfZUNlICdnDGRbAlR4w/aSOq7//tW32MyJuPdjAcOBPl2jaKRqyQ9l26FYRnogkzV6KQ8YOPHMrdEpyN56qFooc+OCE3zakgU7v5hWNFZc3PEwlA8Rdy1+29UjMN285HYoNKPgYtE9czDUc+C7A42PpRvYHNXvix06me9lCGlUz4XcGq6hUnCJIoEnb0M51yBFzJOGJfLTntFcEPuB4euLSmndYGFXWUJR/x1K+ExkkmiS6y7zsjiPo3teJ8I/XTw6slgl25Qo8gSc9zedUh9eE8yQhTpF9kRC7xE7zVQ9+c/4f0T2u9z2Z+DEQxMCez1XvXdsiFMWhUUmjrrn9URTE7nnrCd7mUnlwVBFWqS5/H64cO2ADYA0UWAofCC0Y44PXfuPIVnH4/u9Jex2fyI7b5VeN7n1/XDPiTi6TH11tXgfWc8Nah1UsCPm2V2I6+j4BJAguBsUtx/B1Os6EXPLcE/mlBWUghk+1AowjdjDlIlRhZPvWLBVMpBTMeO3go6R8+nQRNCw1Qq4Rcjvk30r0nOhRkB6vWU9nrhpDCaNfI6ERBpZUPLgwlDsQhT7W6b5xuASsqYTvW3wvmsblwJMkG0SDVdVxTg9WGsn5J4YQog0th5blAUMSaz/bsI8MH30nhV4ycAY2tjvMtrAD+PZlQnTgf9B8j2KEU2xHWbKWL55o3Ba0g5rTJLyQY1SU4SK08fDzaJYn4SKo0xMaR4De8BLRJ5rtUcNgRCdKKZAWIYQIUyGU3Vo98IgA+yVxKw25KtlpnqIEklQMVYW02bq2LJWAS18HPH6wTAaAIzdLKp1GQ0FoXL9S+DZFKBzQKpOIYRzHtNzXXx7xLgFxNZDDsN4FAzUuwVHZgo1WbMA2qIjMZWgsTEBHMnPYcy8X0yhrJke3PuVTYQG4j4fDY+aq6fmO9aOczSyE2TMRmTcZ8xAUFiJ2brjMvTgTG1qtAZrrAZUZnDaOXmYGpMCbZC9hcvmNdXkZSPwdFLUU8QB5ZKvnxv0NAxu4rOh5piLodshZtSpp5IwoKD43aCAjS5jkL9b17yx2JfbRaJCrpys7mCtrj9uxdfu6+RlykWZHNmNNonAeKgY0jqZjPKjejWkLUji+7iZ16yqxK7BaYDTCrmKbvJuPOkpwcPLqJgQjHHTY/Kfob/3QcXf5664F8/Dw+M3ouW1jr6lH/N4IIvZO5sRGKHrQVdCpkH01GMNwKK1kSc6nMUadwADCHhoSlo+34r+8Gi2ZgDY4NNk9Z2wKTUsFTwXr2L9jXZJUSC8hd4VjIcZzoUIM1E8eJIqWOWZA/eN1PrVgULkRobvWnIVLSDuPww/HNWwgdlZJkcZDU4+ojM4e+w2S+32iItv4nkHEjh3Ho/P2ViApwDuCAIMXXGFmNGEoTB7zAP2U4/2RlmkDWMld2rg0DQ4BLO03J/b9z5gH+vZkwfvRoGO/DsM91AwfHhbr/B7V24GTTfrN+w8aopCoYK1yCjTFL8NVgkpAC6TZwl2W1kPjTHALPBhKlZKBhVsmGAMLIywFxLLuL8rZVoR0gm6BdCCQy9TjrsIhQMCWjkJplF1wIyF+ihRNPXPVayQX8JU/zQI4WFkBTq5lnDIEumOiiyBDAZ3KPobsOjLFVPEDKVWNyCOUd2gZEzCbOUXWyCLboWGxN2sk+EvREbJj2IgMIYHxZ6vqicI/gZwnoy62nP3zcZjX6FWVyTlRA7ZjRo2ETp+KoAoDLXTKRnFbyCYpHFRu4GpkH7mbgeakq8+BmSYBIbKp2KDcOeYEIP78fbIk2JydoiSU4K1KQEYNG8SZlqKOeW+ysCUQQcOZTVYd8MTwUAHb3vyIKKAVkdn597xzORw4TO+4QKMhnvbkxAkMio1q9xVTYwRasaRHKk8LSYQtHM7kaCbmg9LnscAEnYe/w+g0QKJqso1Q5aW2pbmTdfjVnwSGskXZEgRiIFVwlzQhZG7IArfZSdB/oppEjmYJGoZnjUW3ODnDKOUxbjml4u2DiXx9BlpHZcOpvG1AsMjZRUUCle6G2QYqNQyd+F5DjN4FYxwXWfPg69umzQ+Zk1OmHT3JztFQNXpPeQls/Oj4mOBRW1GeVWaKLx3QgY3t5uddgrXvPF4e0D64Ode16DO1vF6BZ/Nw3ZTgmQb7jWbrbr1D8T6ZY1Qe+P0Qowe3LpbpN9Me/fOzNSIQEULvnzPrcFIMjeDy3+PABYkyNlpX0NwKsUbAleDzUMTXgfg61wZyd8ghiPKhts55YFr0GC66kdP6ZZ9a/l4fSp5rPevrfJ3WPvwRrnevrg+XDagswj02fRad3vO37pZbDVXvXv1WOaioxkFDYKdNINpaygfzILpxo8eSBqUurAfCtmcPyQMKk5IJMpklmALSy+MC+Xnej1KtzBJIsOEr3272KmqwAaiv1+7ku+Yueu5FH/vVNEupqIepm7ypNgRYBWn2zZFKXoZ9sfCnZ3GU1pvKIEUDfmkyyGyGQUujzNGlmc0qCShWmHeQCAKI2liR0XlgwZNCgUDdhCM3d8Rif9DnN0uttfwxReI+1xsimC9TTrrQin5ZEVI4MG4MYHTO71pQAfUeaEDMNEofRKCiwCH7xuLHR5/Pl5O6dVu8GeQByykZwIOyvlPo6eO9xPkKGnxwwWs5HgYCgbKKfxLQEz7nXo6aVSPph+01SaDGQdBqjdDRkz9lBmr8zUONmj0ycnQ6pSOSbGPAPoSQYTz81YSRiBnzF+SiX9kXB/JkymWiIo9X4fzd7M7OPe5XtMxmS8mzEBQSIjvTXn0qy2VGcs4Br1NoIJXzWDBaMKm/lNHbKmYuwCVB971h/HF16MbpArmCiSmlpswKSKSFhDQ2wLu83hjh3+JseGsv27s36zWKNTXVFffcYvMsU+Sx3MT10KR4vR/0C9MtYsD0ZrJtDbGydtdD3a48Smg0WFScFhISPUb5p3GeBjO87facuwSEj1/aj3QanQIXIbRSdKzxYyeLCpNg72AK7Ua4MSIMMQ+XOrca+eQ8H0oqd6Dx/eFgQn2tegGJpHasrgbX+vzT00EzcIQ3JA8pgvAG/t9c/N1AVbmA0R/UqWCE1Xqxl/Ppa/YDuuxe7NQdNYbuimv2ip7qYLjs1VhYSh/Do8TQBuNKN35XbQZDN5aE/UkNehAzn4+uFgx5D3o0qLpi9vCG9WWTBJV42SHJ6bZd/0z2fxEX/NSwAN7esheWP0d7EacwrlNM25OQQjY3RKW/3/av+3d56+K2GZftGalNI8s9wMDwgUAtVeO3dVjGA+dTUsm3kSkiwTw2vZJylYMhkKGXpO6L1/Z7+/Nj0CGv00GKvcjKmXkTZwfD54r+vgs891Kp0BmAt/qbRntwHJvt3hSFcYy3bmSyYhAFDgmpe95q9h9Zxl+yVn/Ia/hhTDJMAIK8MMNhiwRnW0+JACEGDJdmwPym6KH7eyvB7YTSVAaHa3s9UC+NEXC34OCQCijL5VytjE22UXr93fh0UADiM1inTaO/8d91D0M+Tf7Fwb887Y69WMlSwdmsEywUQYK4xmJkDFQeBjXHKPkXRxP6OSYPrURGQaKeS1pRwXGyQcxgwV93D73g/5c5vOAaRjgwFzfCkMCZVohYp2TQ80xsP8OTI6iTSH4H3FZgfkJDG2RTsA9hCQMOdZGRZkaSIRhkbrZA23LyFjEAbNJdhlsfOnQyXOi6+HIXF7DJwTKBXFvZ5KY22cV9BkTMZkvLuR1N8OF9EHaFy/ft2tXr3a/fjeX2zlMHTZrnZuDhuJqoQEdFoCDQRURrsk/goSA4N6o9OuZlkJHfW5GMAXgEBJBaq3dijIcMhAvyWFu/0+lCKAQlxi48bClHKB9t+veYZFgm7LaMe64Lloj2GdXxgGpxAzTPYGuxva2STVGVpdnk+Vw5hEFhQ/1LLTa4NeDO2/AQ7krx0LfucO+4THhvczSTG8B1Bg6LFx5NduR83oam7KGeu7kgCAfT9jMsbIRfqQ4Jwlx2xHPkGccL0am1pslOa3Wrr81Gv+PYYPbQkWo5Tj3Jmxm6PedTAPLt0KmrHObbQFaP8aupb4PvQhKafSqLlusRwxw7g0g9ki+hrG1d7a7zd+/avD4PPFZJdOQY3Pz+brsC9P+5lIREF6EE1je0yxkedr/sDmoLlujUI7gSl0Z6BgaDp5rxz7n9zZa7XbsiZxjz/6f7/3PeW+BShFnyCH2O/OiHTrDXMMkhONfKR8okBsdvaYB6froyKT3A/T1EhhGe3mth9UBqUdhtKuCSaYL9LDHgys9/lCKnn7VBhga+4hgFIJXu8AlhgZQPOaTWuCn5/Az6gEgJDMW3ZbyjhlfE9TpEr6BFNPyAphVDVZFO3YviUs32PKCDvy22zR7Hh96RnApDUW8FIYsaCO+WvFvC2aUUIWQclGTC6w1EEjUo2SN9/zzjC6lhAATQ4h6QXzBY+5lohd413Fwc8RMLWE9Dd59e1Igwd7A2FVGgYp5Qf0a1HmBNdt7PuMqSdBQso/BRhlqlz2N2CMHrBACVnEsfXbAJZkS+jAOs80qs5r6GUGdjBZJWRScs+jPlz9y2BUfxOAxB419J0NPns1zNlTyq40oYgAC9i8Rm4tDCZ67qTbt74jltF9TXBjXjQRdq9534gcpqhH7gvuD9zs7KxbBWPf92ut9bEP/Y8uz8PspKWOophzX/jqr7/vz8lkfPfHhAkSG425aVq4cg86PJC86KjWogO6HUZks35TPQTSr54HLBqrH/VMkPoq5DTXLI19+Oj24OaAhVF+wm8ik9oaXI62ohu5E3IYFEkskNrfSUKN/z6I+DsBqre48xeP7w0WbP3D/jXFLrvxzP/k6/4f0GRX8CehdwBjU9v3A0snQxIEpU4d7xMCHAB4CPb0z/gFO5MibX6zP5/VM/47l/zO12Qxhs9A/81TQVYGO+rJF733iibv9I5dDDJ2RpvtxrMP9gZd49OzF4M09nbQZ4AbJ5goGuq7dAUzaHVZGLJDk98YRf1v2F2mF0F2zN/rK86Kfw4o6dT8Zwe878O0nE92kqrXUSSBuk8KeAcY5b3PFBxGbWvsKGjHK169EOxyVj/yjH/bv/6GPWZKFv7shTCzSYZhEHEjG8HHbz9mN8vL3vTHOURiUc1rI94efA4N3V68dSpspDnoOdO7Ad+mJ+H0L5HF+SyApMew+T6K498H0DoCKrbHuRF+PJhHUmFIOFD5adpXvwz5CNMe1NBwhI5+LHJREkwyFtHQuJcA1003VNKbHOI4E9K7WTBJ1zi9cC0c7Qhaf3aeptijeDoMQBA+g+7cpSUZLFeYnxgj2ykURTYZ9AqRYdJq+Hrcw7FusMqjKM3Md2+Pm3TPIlkK15O+NLmYjNag/5P9UoM9yHPRSamiKSXnKEqCRR6c3oIhL/875m5jFimxvvycCl14AkRaTKaIQSUz0iQZYY2qNZKVzSNhuC2+ZowsoYa0M729KriW1spsha9KP/XHXz+MOGzZNyVgt8YimM1aLP5xpjG3w6/NGUFfGfV5pDRhDU8BahnWsES65mA31QcRD45nhUBF5/sAJKspcwQDSpk9NJw2zyfm4RJ79fb77N4RXvMov4NEUA1kCbRGTZDVVwbNn+TK9aC8Z6lpO+/70Zyab7UVP2nlT8a7HBMQJDLmH9nmynzK9V/0lPQRNtjpaqHhMa0ANHh2xQZnroejb1saNEwdL98KauRrdNA1HYQF/XArNnF0+idzpHnNlN/w9y7cCYIGjEq9+93wOYgqnTp5LUj9m99sF5zBaXSyUMwO988EOyLt+4GKX4MlQkYCE1g6aQfwVqBzRg7gQjee2RUYEqKT1AN1cn4HOvXo4Ddj2Su+0B3thMQBMqhyxnZg++dvB4EP3g80NOR5UYCmRx8UdO8SMB+aUSANhIBCvWZ72OCz+TMUFjQV4/ORf+3NoOSlPU4AadUuD/hl+J7D9bKhQjxp9meHgvKgOx/aHy1gp3DfJWRn0VsBMrT2OPEe1Y8/GwSi+pf8Nbv9rKfxN6NYBrYC6sz6g37T1b8hYCjmkQIAAEvrORY/MN1tv85Kf277+F2B16SUZMln5tcIut4M3ifLYBCq3dj+SRRcjG6VLq9JeWCcpfhw9C7f7tCZmzFFVgA35TS5k2KU+6QeCwZs3vsAD6vztsimhwHNARMyORDf2AE4XsV9i26qAWCVAr2EbqR28R2o1kYiQEkTfX1E2lk8j3Svrx8MAxKaWEUW2WnQ1SP+CdkBC8pxw89nmh3gRM1YI+fAgCACttBfisCFOYdk44inFU2uy5feeEed3XGmlA4+Ax3zzgiTxOXTUUDIxEOT7Ydi2hieis+BSa2izw1ZEAIa0Hw5I0MCMlx2ylWWUKHwT8k+uQ22g/qaUUIa8brg85BoKhFew4Kc98M4D4hstDX4OfQ+04h4C7yA6dWHX5l4PdUb0Vjj67Fmk6nFtCO9b4rNkGEBNKCnZzsA5ORcM7i/4rOSWuClBJs1hQQ0Zww5DZrbtQhgIiWoR+aCgL6CKAkZKwCfUoCMGeTad98Ext5LkP2oGSvBu3oW54lMszGyH3oGVXxv8UDqXqAHYzSMPLLy3u17TMZkvJsxAUEiY3DuhsuzoRt+wE+4/UPodO+xG8/0Fd/VKKHdM10IbM5GP2g10X2kebiTvgtTPrIrmnaQoGNXQy/df91TUevN64Ndi2Zk5wFcYAHPT6PjR1qosAoG59GtoacIqO9Tr52Kouamu8CC/mlstls2y8UwUk7jKW7kpSNBXxVuvLjxNtFqzUA3MiUlfZXf1Pf+xqfWJFhklaWSf9MXMuXDfhOeqkTgoi8ge9iszW9Hh4k2D3fstcn/1DNmbv9t+ICcg6mXdNazSDGcgg2UHrHXcB7PRLXLFyxTp1B8gO0xXGs39WQqpQRYsOmZPnItmtaTML0CG79sHt2am3YTmYBuX61ZGaRg8z7peLn0cOKx3lbYRC57SzZQ3HBTQgK2wNAAdPbcTCFBhRtPPncdcICbXfgMGe23FpOka6MzyO5wxucOIKnK6iijqmliLPd6ClkX5X+taS4bYPfmQqUGU/plTOZYWEkqAw196zlELkNe1T8LsOyApWpX7Oji3hjCpJXMv/ZzwEapYepY7doc3MBlYlpbU2L2CuarzQQvlT0S9iPKaPJNOcsKy17pvwYfDnot0SRUJFGMCmXxUcITKjs3He1ykv1Iw2sjU1RPKxh7GzYRu8Mqh4GBqjHfpMyCMs9Ncq9jbaxQvGQAhsd1cOnrVR4+GgRR1JvBpKbwvKObrL4VJmkEa6PpWmMeouFpO2BOW8TYL5DmaIy4Q2GY4Jwzcjhmptv+HfdNY9gKFVOzIkDUOLYBh2G8MHkv3RqfLwGiUz6RX8G+a4vdd9HXxNyDAAcUxKAnhuPPBCEoO5LodYJ5+UVIFgGOUw6rQK/xe2E89pjCPLu+Niw/3I09LQ2im4H1XA2GQ9fTnBc5tyaJCTLPRKTLlOzRyLllg98nLrgZlSRQheKXdYwDIBf/5gkLEupaPxmTMRnf+piAIPcZBD7IxDCxqc0kGTEt6miS742p18W4ak3EIZpRjLWkV9DwC5S6AvTNnFGKKhPhRgmbm3GTdxnRHseM8VTfHHNnZ1KMpvBUVxG3RykBOgKMLDY+LAqQMBEGQwEmRtIxoi/h9dy7M+zV0RokkuK4IqjRp7a2QzdHh2pwNgnTxtUjBo7+/f/Np75UsQ66dmCxcSJoUG+3gN/g9ZPBa50wrhDXqS+O/iaOEcVHPQ0gDbTx9t/YxKSbUZgRxIDPQPXi6/b12FCM1k0H2VSmS9yMMzCk5bFdCtPLuaFt/w7PZLkNOmZITrLblglSLoOs67i/H+YeBzMHz/Hov/+wef0UkmOqPfhMAjeQZLXvB5+fFBvxbIu/P+fXT4ejcwX4GG7yP+c3kWwiDCT1Qln8/Dvz7v/4fO7mi5Eb9HruzeGeDiOh/UyaKvO6IXWGBWszatzfNYo8gl8VwSKNw8ZcSuNDB+ZaQrZE8+85/z151tJvHAxHiArYk7x2OCwrIF1e2A4V47kRRUtz3go+C4l4CyUbwowL+ksV8DJQWR07mIbZxGsmNHYH4J4ddeMHId8z3Yl5XeeYSGc3R0FeYk7JYFDMoiSHXKH9HVguBrhAwaQFKCVzDusc/RBI41ebtgRMgvIovLs4j8q5YXx6DVApASuEsanJUPw5GE0soEyowdL+HeNFI0CQkbyMkw1hndX0I45sw/qwTCQiZRg3ajLK4AfU6fxzP3GnCpvwQrrGaGi9J9Md8Jk7Fvd1IbBoQIAlJt+Y48eejJGwKm8y0iPsOwzgVqFBBAlT+xLOpc8BiAPLpUZKVwf05DyGxMGKxuoiNTLAP1hbCXxAjCG+XCuCTwZ8HDNihqVGOjdu34U1IyHQLBLrB3Y08923yuSYMEEm412OCQgSGU2BWWe52TQYPbEktdQPg27HDi46Hyki+Qh6dAy62EVBp5ydgvY9+A/SzbnosxstC4bZrGHyZXFOuUMnOg8TD0GAnLIdSWoxwAU6tdz4cZHrmFrhv5vkAKQ6MJJWFyAamGYr/Gt0CqaWvKbpKw0ZL9+I6psTdKSrg774SGGiWIhRoinm2OkGtdZsRtDR0U4pmS1k5pRvvR31ERmhsMtJJYUmvX0PdLHrhxCT/PU3gx3oQhao/KS/p2p2E5n+IF2pEZI6sv7GINWYsak9mPu2b4eObglj0aQEI2HKFna9IyjsQPU2hnEwyEylG1tvgOndJf89a2iaUymYSnhd8Hmdev10UO89UKNb0NUTsplQyHBOu/siAFF4P8bIUsqXiJyGm+f+FyG/eGRPlN5N6nxKF//lA/drPzHtNq4YuYtXMveZX/xGhxHRjIIpKmBAcVCf3X7OrN/UFh96JGium168HjXdqwjuolNN4COR6Fhj+Mx40qcOBKVe7D52Cv0bt8JdWnRW29ewOIacsnrCf2Z2BDHuQknPLt8MFlw8n6l23fd4QLgGWEOWD+cah3SeZtx+xIMiyw5hzcH9SJC4GTm74JBmkHGjg+aV6akzQcPqHCBMrV42+/eEAWmYnCZibpuQOUBPChMnjdcQ7BKAJAMAHEtDaQcNq1m081kHwyLVbjY9GFC0mxS3OxKJSlNIgBAZGCeU7WhyjzkfM/5z8jkAzZyHm/eLdMdzJCEZM1T1+eGx8ZmC9E3lZjHzSwPscY3A9WtGyqQQ7ukAPhpGQvt3SKPC603qCfdmYxgz5jnCz1r0E+SjtJFgi/HAwBzQDqxFpikxBpRKI6bANGimfIReX3p/ch/IJh9BYp0vzd8B8DR/L3K1BIA0G2Y8zzRf7dwrkCsbLxtJEVoEr6qhcw9Sem4zJX2rSp+JGmYy3uWYgCCR0XTCk0bIDxo6DQkL8UmgQSF/Y8ASLLhqfMWisUa3iKkITGtoPxM/G+o6FsOammbZuFZvvh1c8AzFcK8t7NjVoE7VveoR9PIDfrOdsgumkaAnR/HCDIMgBL06eA4TJERQU97+HeLmyqc8CJNfQsG3SgqBc4jQXA4pBjeRly4HOxXt350Hi4DdFhiOmlhf6czNP+/vmwwMBwJhdGZvX086Lu41pjJUH33KHifuY3pFVLjX6im7Iat6kU7vBx8JGt2apIGmrkHiUDpcF5RM0JBYvWgSgF/09yiWrwp7nTTn4wve9HQAB3hu7iqY9nbM7QDy8bljl3Kcf0Nnw39vlK9ahkOPoAhkCpSgEPyi30z7+jewWXzUb+iGAIEGb1+KU5B5r0DK0TA0gmkLwvLooZtaM1lEuskJ5HOjdZCYXbjpaSvNnHBPJldIbCjBL3a9M7I/xCOggDyHchp+z9EWxB+LISLBWAdgkKZ/iQBhXBcSXNv86q0wI0/mhGIt4sFxznLIk1SaYph4WH/oe5Si0Odcd/cNsBYAzGV8MlPC2vd+M+LdQaNeSOwoDW3G1MWVQaNeh3stF7NHk+ABVocDqEOGpN7ro10bggbgBbyuckaVS6e4/mG/H8gBgqgnlYnvRVOk3gEgDesvTdLbf18HCA1AhcVYIuu0aXjQvwXnsD53PgoOsIDjemoAEWHzmHuXIAoZjmOSNAyr4fCxcDyp+CQQoOAeiD8bI0uc/3YA/DHvheuskgsDihDwI1sRRsGJ3Lfla6+H5xSwT7j2tO+BBhrvDyNTWUKs8TiWzLgIVhMzTA8MzD0F5F3t34ElyZ8N+1OkTgVlMwCaK3p9EPiQ5B02F9MtYSmfys0Mq47NxIhRrspJY1IZY1SrqURkAGFtNcxpndfvPUdNOsxkfPfGr//6r7s/+qM/ci+99JLr9/vuWsDX6cSJE+7nf/7n3Z//+Z+76elp95nPfMZ9/vOfb/9+YbzyyivuF37hF9xXv/pVt27dOvcP/sE/cP/sn/2zjk/RZHx3xwQEiY1mcagrV0DTbAo7eGM0owSIkTJGDoBGhY5+gc62xsIyMYPMifSaJLWw2N8xE3490GTGqbX/pjEcpQwsppUSiK5vfQjmgPDhKNE9y3QTCbYC8+LpoZHN2Y3KiLp6HhuOuXzzSNRTJENqCVMpaJqXCkPS0CrXwduA13Of73zMzYiOmxtpdKrLH3suKoXghrtHNhFJPihkMhjDtr9Doc2CLz8F5oWCAxdmw/RopgiIB4QpZkCl7x/1G+S5J/zmrCc+CfmruG8AEA2RUJRflchigDLVsweCABF9QFRSdev/4D1SejAjrQYoRKSwm0YaFGVpNOFNPvxUOFmlOR/n/Ma1ohnsqn3BhKH2PSA5IABa4+vM70Sqk0gZiuf88z71FU+57YM0RYDt7pu4YHxwfgrHj80pWQzKfDPgU8R0t31vgJnpi95bp2oYH/c2BU0Ed37kbNCbiGaPlK7V2BSXsjnNBr6gz9iQV2bLwntt3RxNdYg1rqoNtoufj3aFgRdcZ45SmHOZFm0L7wVGQCmme7wnHc/zwYjkRKK6K2zQK1ybPtYSZSEkYKMYg8n8QJACbo6x+Z6zd8JUceN/INR3glSR7rLS5TMwPtK/+kbw+HNgQlzjOrR8AFw1JZMaOXzqbFj6hGfKdNQp92sG7wECHyje6sO4tvo5kZGtXBn2T9BuN1I+MsaWnrJMKSNtQFPEDCbiiETArG0oWiv4RqQSq8vGkmEBUAYFuQNNWlV63AFIIt4UvKcyMiYlvjfGtDKFLuO9UYArEEZAnGxW+pXlY55PE80MT6wUiYP1NQsYJls23V9ugGPJKeUQQJ2DvkdqaJkDpKz5PWmSevlKFGBikynFWmBkuzL31F952b2joZ8ZGcZ/B/OO+uckvB/Aou5cwwXwrWGCiJXK+3l8rxujDodD9xM/8RPuIx/5iPs3/+bfdH5flqX79Kc/7TZu3Oi++MUvusuXL7uf/umfbtntv/M7v7MYB/yJT3zCffzjH3df+9rX3FtvveV+5md+xi1fvtz943/8j79jxz4Z9x8TECQyGn1jnQyd27Iu6E3RiUKkTn8NPD3QgaWp5bIX7eaqwoQ5/OTz/nP+8tXoxiahaR4+n1rI+i3foasEWTZ/x+7CGPdtdlVSmF/SsJQFDo0WO5tVLFLVS28GwZFm9EEDr7EpJqiUfMB3WdOrgmigaOWmfhwDjxTzAvIcvoZazmVH7EaJXSHH84yiXV3j52GSOXjVXzdj6EATQzGAHSHek4DA/MMeIBucsEXWEHT9HFTx0XZ/bXMCMs37bYCUYYSuDinYj/iOXyqgVsJODLqmZLkk8Gxoj+ejFtgKRgaDhp69YlkZK+e3BeVF5QhJK39tN0MJi2BKt5hcgOemj0KukwCF79Y/J91pjBTa5RKfmc9Cr34G8ccz4rkDdlAFU2UTV4voXB01OpPDA0hs+ovT0UjW0cefCwJkZkiBUKxdFgQGWx+Re4daZ6mr7nmpMAK7HQQUejDfxL2WC8OhhK9LsbIfTHYiOJGyQNGOMrs3y1FI3QNtFt+PEZoXAXgJE2Lx+Cl/kc8hrZ4sPjWNdScRbw0PJxbwCTrVjCNt/+40Cg7+gn5IAP3b8faZcKccc7fRvosBbCei/N6oMT90JItMsyrDhqkdMICSCzCIiq++EjbXhYRobCINZX3CBEkh7UhQaBpPKAX5IusXAWkyg0zjRQtyFpa4h+g/QA+qjm8F5ZyQiagRKaVPlFYQUKlO+vskJUOy+W4a0xtiO2jKBo6TgBl/LuCjomBZundbVIYbG+Z7E4zFfJ3y3pTkOcOM4TmgDEo8scqdm8LMLcrAwIJQ9opp6pyFZANMRiMzaRtLh8KA1cUwCNGJ7j0cBtxo4k9gWEGZBgQPsYaM/E+kZ9X+7UHQl1K8RDytlMW7+N9PnA9eMwWLzHzHdWnz2uB825ljyFaDqbXO6wv3/gPHBGkjcr9VTxD3HRuf+9zn2v//9//+3wd//8d//Mfu9ddfdydPnnRbt97dI/zWb/1WC3I0LJJVq1a5//gf/6Obm5tr32MwGLgnnniiBUJ++7d/2332s5+dsEHewzEBQSKjcTRP0oHLj/hFu0b8IdkSzai2eGpsgoWpfxXdaU7YsulgF55pHglTAJD13v4ONDpq7Kkxryhzkc6mA7OkZJIDOhLqfWKMo+g78fapoOt8Ibp6M6CPzqCBJSuk/RwsIMZlnE7g0FzWH7KxoYYivwQz1/bf9G1ghBn15jhPpK23nwkPBBpR0n9AmQODt84GtdPcgJB5YfLl26ItTPfvXwCIJMUkI0ELGNUxIUIN8KaRgsK0HG4tBieuLEm7zoIlA8hogJJmH//HL4T13uzekf0hABG14wQPe2ABJPBrab8PJBh8pkvGY2Ozq+wuyoYsYwP+HAIOEFQqB0jLAQNp/qnd0Q5IhQ13BY8Uanh6oPHra0ZIwZk66e+v+U88HzVGpRcL73WyXGoUYu13A1BMRtRwdd999J/fdE3gzObVt9zeHUnnvm+/DrHUSzfDiRNqMop0lQEKjmI/ADuaUIrfgKFnc4MLIIxmgJ3CioUhwI4UHc/yNWsoSSkAN+ssxLQwZMHBnxMwx6oZgPvCmKnOh1kEFejl6Qv23BQAG/hM02CzAjOolnNLCSclAmTfjBuk6GtcrPkOKGAyPjtkEdCfCw0B9QmoYhR5MA+aUV/0609Cs11S77mukJ0gf1cDrHE4Z1y/2+N5yxe99a6tQZCVvku1sFcMKALGZLUG8/Ja2+lP6euFZoM5hwR7pEFikmd4bjDHdySkOLYEMg/1j4mNBN44HEs2HAXgld7Mg94+tSS9RA032aRSBhN9gxjDzVSmC1hzI8kqnTmKIAjX1dbHAvMKGWo0TsZ/VxAlObA7COinMK82psGy90sxXxlAAGas7pYF3TmXJps2RBtOsWG8qwBQZbxXBfyjLLwGOG3YK+pDQvCHscAAx40fFObyuh46J3Zwk+EWGRccDeDQ/O87Ob70pS+1oMYCANKMT33qU25+ft698MILLfuj+Zsf/dEfNcfS/M0v//Ivu2PHjrk9e6z/y2R898YEBImMcv1Kl2RTLrsJmisW+VySPRykMjFaJfWT5WP2ps9Aba0oM8HmKhVKHTdrMVkE2R9mUdMBTCfhRoMmezrePBqMBXZw1zcxhtqZw4YwwTlLEOXYMc/ke2FzmWPBcycE0Ih0mAxFUjYdLDIIfHChNyCEXIsytkEHhTuRrhTvGnZNa5qn4TjVa4Pg12jH+mAaCRkF7WeC6eS2+p+HKOA19nPuIaFrLxzaWh9zWV/2wMvwv/NSlPb9UPQWkJmwi19Ih6cc+A1VjdeTeTA3A2r0Ddst6a/x52pu7SCYYJKLFKGGF4wW4YuvuQxNuQASwxkAi/P+d71rc/H3xeZocAWbb8Zu98HQOCH3Nu9jstVI4RX5Q42uo6FAo2DK/+Tr4SjJ1icoAtgB+EjEwJVxtewUT2/b4m7N164JCVgxVbv01IVgUgs74gk21SymCWK174FI0QJsINNFp/Gw0PVNDDiBD/xcbhAAdy0KeqQH1dSbw1en/qDtSpJVR0YagTzK/dr34JwPc9rswtWg/44y4pYCQpTw/1EpH32jRjAM751FRDxNUptjfsF74ySQGXIeNCaS7XUfBk0tDfNAEkgSJHoVADPzM5eDn3l7m73vpuFXkoB6X54Hc0KMTRnbyaK5xrElmJ8UMOT3ND4cs6Db00y2OR68N/cqbN7Q6yMhm0njQekPQhmwdPFNCgoKfTMP0ENC1mWTHANJVkJZIKSp45JC6MGUEJQSw9GKLBH+d+zP8mPnoiwZMq2MATvmROP70ZrQ4vnk/YQ5mtHtyj4kgJxfxX+fATC7eyaafsf5MgXzoFZ2cyw5h9dW/W/4mqOnghHSTH6rRd5kfge/lliMrJpCUwoeM51XPyI21lJ6KKHpSMNw41HTAroHgw0aw14hi1CkMiaNiusnfYaQNlM+cEyQb186zI4d1hvpV3/1V92v/dqvue/kOHfunNu82TaY165d2/qBNL9b+Jvdu2364MJrmt9NQJD3bkxAkMjIrt12WVZaiuOsn5SrFdLxi5gimo0GC2jZ0BE44cat3rI/aKDUDpp/xTw96JuhRprQJWaPkp53LdrFNzQ+FgwoJHjOEpFCpDCYrN4Aq4TAy1Ci8yCPYW1MU06anzphvKSboAPHxpUbrfSkMFbIJGD3yvz3IkoPN5IgbCBydVDHYBJPcv5ysAPLzklHBwkPhwSARnMv+38I/TRSzNFQUHXU07MA2QAkEaQr0DFddtVuyLQrsvg5LJSfs0736V++HNZUQx7Upxu8FrDYbPYvYIO/ehAtYPOz18LdJ6D5LMa16O4fOhc2umOHSJIDyAyp1vni6c4TwuJaGFssmNq7XgSZJNkQTJa+LQRqyElolDs478/T/N/50OLPc+LvseyUv7531gNcwPPJ920/c5eXwKTXwHJp2DTY+w0fvtsN6zeGqREPCU4KTKlSPyJuak36AjuYTMnQ6NmDYKExhhtSwBTAcDMSyAcc424JaINSr94MnD25kS5R/NWaVoCiO3kd6xIKbTMnSSJDEQE+UnhAVNJpT8CSYZHYQze1gslp+mXPFGj/zXQZfg5iJrMZeQYgpzQgdsSboX3vY/78ZgBbCKhTsrFsZCNyCSAaM3GA8DRxbI+NnX/cq8mq1WFZoBxzBcZFGik668ctiy07hOKexxkDB65KYQgvtGzrxrBBNFklkoZVYS3LUdgSNFCT0wrrjGGSEHSVZ9J8Ps1lwWwhQOZwndUrIyVgduF6PGaZUlkwRgkcsXGSa0Qu2LE50oYMQAUGl8atEgA1+55Dfo7MNIIaYIeJ+ua+S5oA9Knh5zv+HGPytAbDSF2h/I2pM7JmJkM0zQCQ5GQqjbkHyOAxfmOQ/da77HzXQ2OoIrD3kL/O6dnL4XtY2NIxUM3ImAXwYtOQ19OAp80IGHI+EKPZGnyr3qD3theNJKWRnyyMGAukAUYWZC6x0Xh3PP+8Z8COGyFz08YThP9d/2YhEXNijPrejgkIEh130ckEnhqO9DoxgUpZdJHWSIro+UtBZL6TEEATK2xik60zcTkHgQ9KWOA4nqkOnS7fMG9zQLPT7UKRfMkj7ekj+4KLbDoLSv9G6YzCbDLZsS0ItnRM82DsycWEWluDppMVIhtfh66Y8Q5Rx/AIm8d0HEFPz48JiEKAAh0WbrBVr07ArEYMXnLMdxRSxg+LjrzgIlnDDwKmnATylKaaoeM23Ouve/9t+93m92DD/7D/u8ElbCJ3+s3VSIGXbdiEoDYeIfZ0cNayf+78bc8mKefwIu6jcczp39giq/xQOD6wBuOFoGA7GJeH+yNtaAr3RgbWUSYdXOMaH2ZdG1+e9t+X8Iyi4JkmoIB7SztfBH9oMLlUuYCJsEbRuuyv0KlXuj/u1emXMF/iOPUzSQkvn3s4CuwtsIOYjtP+e5k/1z2AKNlRnHMxgiY9erjN+hH4z/Ofk12X53MT7lumRBHYlYQh/l0KevgQBqrZLbCR5Hgqdr4vw0/CxETa70lKdQ0T2xoaecpUhk/Ybmr/9OqgfK4+LZp/DBYGpoADsJkyJUWlZ5ijahRPGdYLhw52+5mxxsMGzPGrtkWlKfR/4UY0w7GpgW3FZwrzAwFsnderSEe4BnuEvh3JSKOdb4SLKSYxydxFo1Z3DcALCkvKqNRDgrIbmsaSvUjgqD1O2Z/Eikb/IcLsIQPoDO41GlFLYZjDb6U+49epGnOUiRrVxA/O2Rn82yDN7KTNQXpsfgc2r3kGNMZ1n58Hio34u0MR8LRl+oBpRQNVJuQ99XCQNaaM3JSFIecOYZ9k+3GcuO+jTCuJWc75fmScgNm0wPS7n9kxpYjR+0kGgZP0L18MN/yaW+KNt+7PMgFw04kSJjCIa50T6BbfpWqLn6Pyentwzdf0pAWgt30Gl6bu+b4zRm0AEIIgsdGktPzkT/7k2L9R5kZszMzMuK985Svmv129etWNRqNFtkfzNwuskIVx4cLde19ZJJPx3R0TECQ2mi5Fmrq5H/TF09RZTGTi3l2txMICmm2JZBOHaFCVGHDCZUc6Y3dcit4aSHfO4phdHRpvaToMqZiIYDM609tWJpKSVoi4WyalcJHOjsqCJbT2IJX1siwYm9YEdaI0UjMRpEK9Zw58tRHdKjIHhFbJDSJBmRT6zxRFiVKDjecLukLJfpwnGM61x/Pwzvs6lifQJ9fS8Rx96oPB1BSi7Kk4mxs5Rh2WbKhG3cTVcvE64a91/SRo+PCzaI9B5E7B95KRU/tLBhKeI5OexE59e39jE3nZPx/lPePN9jgR39h+B8gX0is3ghKi2kSq3op20kihNUZqAoYa5/6rkfMB01j17DH6/Y95edIQ90p/9aqoz4EBbVGY5gQJ2VXsROSuispuOEYffjTIfmFKVvvve9dtCNNgBT6UOh6j22eIqDURrwQ08HxUx0U+SC04Cgka6GbS9eX9xXjwdOW+cAGrEbsAJjknme64XM/ybQ/U5pQGki2B+4SpZ+Pkh/RG0KLZJGigsDTgtkgOOTLEVnciZgPG5OMG/45MNS3geN7p6WHWQqHr05uA98q4iHcOwwiDJ1bCjbs+X/gO9CYwsaUyD5AxyBjuHN/fgAOSpsXkGsN2GDMqMVG/32DXXo/T/B3u1bH+HBxv3HjH/h4ELsh80ChgyjxKFv5oQvAza0mHMdejwL6D64/MnRkZI2DJEGBJSUIQ4IXAHEG5sSMClhP44Bqnz2d15k7wuUvZvFvivbVUuYSRnYC1y2ZDIo0gAv9kC8aOTe8H+o0ZVh3nBNm7p5S60gCWhsRi2LpgrF1X89GmymQsbWzYsKH937djNKkxjQHq2bNn3ZYtWxbNUhsWynPPPbf4N7/yK7/SJs0sxOY2f9P4iCwVbJmM78yYgCCRMb9ttSvzKde7DvMwOvUT9BAnatOtwKSa7dsVTg8Rg8mMxRyN5cRk1JixgaJe7pwJ6sALsBCakdN4CZRua9AlxT2No0j1YoGALk55wG7qMxjNlntBuS22Rqm53Fyl2PybxYsdHaVLgvpO2UvKTaCAGCZa+NDJMLWZ+fL8uf03NvxME7kJZo6Y0ZlUB/xn+hwkTKxA8kL7dydmgykEpnhTHTdM2wylnZ1dfP44nwAWCL2jF6ImpTTXMykdx3xncQT6qsZZGr8Ubt65WYYcqGMoyIFCuZbvSaaRAWjwrNFwrUAscvu7VY+GjXJxzOlVMbfF5rfcFDbfNPea0tihBU+ZRARwQROfzDiJrjXZUKDx15IAk1+7c9/uvBoaZl/33beEkaAKaNwDNLVQZ6FdnsK8Jl1bDkrMsjNluDhH8VBqFDAZaQAGaRbdYbFBijZ62heqvRP+vXg2VQ6jkoFQogv9B3STPtqPCGhEuhoWA3x52r+LsNiyCyisxxgvGvNqFueYkyphGDp2hOlNgOucqp8DWRmRbn8i7EdS5Cuw+thR53xtTJCbga6xkdwB3NekFRM9DoClWILEQAfZTDkNyMV8swOOLvzdGTYOVgUZIjpMAcuGgsgkK/gWsThmig/Xb33WczxTxqgVLFXT7BjnFRGLyx0zahqw8n4CWNWJQAaoQr+wGt8tlQhuc2yxQls8JCizMMXxwWPBdTah0W7zfmBHGR8TzsuyhzF/R2NS9Xe6N2oBbnICmwRWsTcyUczKbMHzTgDYpD/J9zTsS86dZB0pQIT3UGAuNGoBKc3nUya4RHNeBVVCAHgzynu1xMQTJHRRvnPxMCdOnHBXrlxp/7+Jw33ppZfa/75//363YsUK98lPftI99thj7qd+6qfcb/7mb7Z/+0u/9EvuZ3/2ZxdZKZ/5zGda+U2TGNOAIYcOHXL/4l/8C/fP//k/n8hh3uMxAUEio/eVN1ye9F3KdBZ0/2qRCHT0ewHgw+Seo7PcAR64GFFmIoWEMcig0zs6XDUmdSawdD6TSDXpp6Qjiw7b7fYgSnIdBn5gNDBVox3YhBq2AzdH4jlgNLDQ3HPBNBtNMaYzWmEmyoxJLeEmxGS8m+uURTdKxoCNGwAuwLrpkJSG+5l9KS2zOOALnh6owdwoKqDh2CmltwE2GurgzlQggkrDPX4xz7+GNBawhNqBDWL/9ZNhLwFNE0GcZfm118JAHjeBr9iiIENRML99dTCZpIRZp3aPCiRbkNlSvQ6fB6V3U1NNijz8Y5JatN/LGdFaBKMDC0TfqrcQUyESUsVB2VW/FIJHxSYAhmARjPZ6tkPvmN1w1DF9NIBeo7VuXvNNf3+kAIrbTu1qyGhm7s4XmTBmTGIG0qAqgFKpFJYVwOH6m74bmx7YE6aai5+RARDRAeZ1NikOMl/mrx8P//eIrEI/kxIWslyU3u3gHWWADzCQGJWqKThkzCQ38D1RpOYiiSIIUBLkxFrEwpKyyPZ4sC5E6eniOcDjdCw0abItLLaKgBkH5g7DAtRENs4JYBKOZTiwUMZaZL4PN/Eal3vrVvhZpe+G7g0CGvW7nwNvIMonxW+Aa0sCUMgYZAq4TfNmMt8ydMe5xlH22/7uOIBOrAX8O5o4j4tDJohiVhKRvfJ+IMOhGrc3QLPAeFBQ9koGmPqNLV9+3/fVvYAxK46YwZpUou3+vdpx4XLw2i4VIOpEEy+FIUGJNtkfS2UMkY0DBrLxeJFh5mKyoMmWk70a0xA5cpzDCumD4wBg4wGI68FUKr1XyfQik6TA3oLPbj0xRv2ugiANUPF7v/d7i/9+5pm76Xp/8Rd/4T72sY+5LMvcH/3RH7mf+7mfcz/4gz/opqenW9Dj85///OJrVq9e7f7kT/7E/fzP/3zrM9IYpzbRuM3/JuO9HUm94M4yGYsRS80N++MPfdbl2cAaobHrKvTRWEeCgxTmcpddpOgRwk3gOATexGlt27IkXWH02LBBjqWp6Hcw0akRMzsCEOOGYTsIpby67AuLdC9MydAJJD1bFykuoASLOOjUH3qPIDhAcEWo3smBXUEaPDuROnHz/irRZaPHCRfMjus8zxuAoFiySXs8s4hJppkqHPEZAde+BgUHgSTjwA6p1WidaGgB3pVT/uepC9iESoFhOnOUbKxkCgE6TGLaR20/mVY8znESN0q0KJMx1GYxmDSbUoKUfCa22Y1jgiK+QoIJGUAJTIjN8YvHS34QABO6UgSx2s+B70MGvxPz3SAXq9aLoz+6kUwjYSoRAZ2736cMMosa4OmVw59zZ6/VbsuaxH1g5p/e+yNZppi0hUI1JYCrMcnQmxMQNnHM8FDSmE0z92GONaaBSxymAGbc7ZgNfoyur4NzUWz+5WbdFMNLHJ0OLs57bO4ct8aYOZpjTJqIYSjQlHmpdP/IYDFaz0kTAPchi14Tly7ASUo2CzryBkTn/T1GWkOwn4CENg7MIcvatpTBQtlca8Sj1qft9eDaZvxGwN4wgLywOtjUWGrErTlmHicNpsWjhYMAC1lYxutD1mmycaLMN8pr0fy6+wZJOEoXzRJK7EJMn/t9Zn3Jnr+Kxru8V8ZI1PiafMO6cCOMx6heHWBiZEwCJOOHMu4xiU9Lnd+MrJrsF0rKFDSGGamZCyNMknEgJwfvIe6J9bjNvoEsMl2/7oFHRT1yX3B/4GZnZ5fkf/G9Xmv92GO/dLfW+hZGUc67P3v98+/7czIZ3/0xYYJERvHW284lPUtLZPElE5/pxID9wLx2bg4zAVEMGszPHLMpN4s+ARpxol7KiAEf3BB2FjpGY5ruCAzGKLMZ0+Wr4Y9RPW0XqZqShcPH7uvSrnp1w97gIkMzOu1sktLNLgZBCBSTRq4gMg0ugDkMzwjidO4hAkkR4KZ62XZwuSnnlpgbIqWPmoHigQyiZFakW4hJNBsCbN4JZKWi9Y5tPFNoohOmEMn5ZOeaFOSMen0pRGp6qUBOY+IXpQufnsXmF/d0SeCHBRP1/nIO+OySLWHkPC39HjrmI76QqHdvDXbn65591vOjeI5pDsjPFJptfgFpULwHEGNaw0HfSLI0vQnyu4yFndx3Mep5ZQqOenHzr/MQ5SgZ5DT0D0oQA9u+B7uBPB6CxrxOSlMmSwRFSrJ6d1R2ZSJeT58P+rBQ1qiFoflM+ikxNYWMCAHJSvqaIHEpAahHWUX7Hcikg3kn169arieLZt5rLN5oBmiiVkVqSjkli1njpdO+Oe5jFNAEqjX6NeGayXuNcyzurXKnvQey146EmZjsJgsjzESs83syLpfslVSYAig6631oirzi19KKMc9SgOVkqZKJyOMXiQCLe96fNJZNxIsmFrFqgA92yoWlw0hUDsMYkcKwfPv4fcGeHOuKJp0RBIit8x2JBHxZuGZXiD3lfqQjTeJejQlHmMcU9DDPOBtOD+HcIJGOkcvt6ynhIOiLY1aJWnYMLBlcGyPDxjOk0eks9CvIojMkxZRvyvd8/MD9wTOCqQJ48jMpzzHzqsjCjQktQBCClwTKjXSu+TuaP5OBg+c7k2eDTB+z5sQ8RTDHpvXQufCj4r7fI3InYzLe6ZiAIPcZLPjoIJ/u3RE1yyJLxDiBgwZY7LWb+hwbXLMBQaFt0gma46EGk7KTyISgsWumA0r5ATaElXQUYlIIMzh5M8JNJ3l2JNhdOCydPGxOyEooIkZqxmROuyLMZ1+iyRo3RBw04qQbffveG9CR5yYSbAUtXuqTYYo7GQnpvC84q+XymX9zV6vYjif2BTXqXNj1XqH5ZH7Cd81rjXzkdWNhRrApVgg2A9KpWEe8fM2CZdw8xyjQKTaXpmBs6fv+HFZvHQvKVFReRP17vdo/K7mDBAcbokoM8OqV/lqliDk2JRJ8Rzommdi4MTIyJaAhnTwacZJdlpBFJvIm890GYNzAt4IFDrt17cAxlDPYIGO+rJDC0x7CKRTUSKHRyOB3nAiAzf44qrdJ4OI5QyFQC4iSwIOnPuffO7uK51AL9RuM8kUHE0kxjKTtxNVig8yrxr9TMifZQQSICsgPa0alro37qBjgfgx7pNqOzjWYZ8Y4EfewiVpX1lEMdB5Kkf3o3iAIXZ+CJEoA8QqeGPSwIBOxwtyTO2uYzfmuhi9LGTGTbd8b59rIQZi6gmPpeC4ALCBDjk0QnWMJFEfZpFgXCG7osZGxQrlYx0BXgK2Qd5dJtFkvTBA8u6ZoZdEpKRuUPLDojbFSdKQ8Hkp4xrGuAAjQV4UgDIHdEmky7bEtH4TN1bF+KXAS2+u4rwLADv9Fl9nDfR/90kRyWGPuSLBOcb7h+mOYqM33ZpPsxCB43dNnLZvVgcHJeYmG8BVer4mHBObMs4ZnoISxefse52fDKTq7aYKM9UvOk/GCAduQwI0yhdnojAEi2RYLKi1ct7TqPVggyLcxIncyJuOdjgkIEhnpM4+6NJty7igKchTXyXU7C9X0x6A+WWNpF4b4D3AB44RNJ3ClDJtYXW6KZ9a/Y+MrsieIdKeIsW0HdbugMlIWwQ1lvdZ2UZLLN4JaZ3bR2cnUDn0SWUgqRqsB6Ghfw04YaYjsAIiGWlkawQ0dzSKRpNGM3mEUbdh0VG/D4EwZKzSnw0aD/hakfae3xXUepoz0JqCO2gBfzfFs9sfQf+1EMPbUKTOZ3jhr+kHvEoI4Hc+BiHTJSF507PSgYXoJ/i84ZxWjSsW8lb4y2WlfwCYbsNECONMpWuk/sxHgBKMI40oGl/D5wjVUU0qyL8ovvhQ0wzNNZwEX8hMXw8XTamyC1V8DHgQVTAirZz1Il2OjyPdqvw/ie415KJ61TI2DCXoiVSjv5e7zP9l3vf68G8733b//n8MSHoKJ9BaKARq6kR3hvPfOXQ8C1RpfTNB5+Oz+oJEon6H27x4GS+avIRGgueIYnwn6t1Sg1SfoBlNC1X7mVrC4kNyTMb0BTJbqiD1mAosJvHiYsKQeEtUyaPFvgfkAc0QmtSjIaQbXH0j+EqQitQOMJBZjCYBeRvze/Q91OMEDwE22e2cwJro9HnbUt/j7K2FHXjfkKOzS/QDfOMcTQBV2GNlqvB4knDA1rVNEg01q5AeMmFdJFP5tmD1jwMiMzzG9DSIeEAkjglsmH/YaWPPHeXfFRsznofN3kHmwGB0nN6PkjufNsNXA7DExzwKgEogjYygRgCkWcU5wg++lw3xO5Hxqk8wyZQf3ZQ3rGTd7TzbGwPRio0HlXuWjYNgdw1oCCa8xUVZfMACwhjkIs+r2vQFSJdM7g+si1/9kXsA/bSyF9hySSFOtABBG9iLWUgO8NP++t55V5bxzS7NymYzJmIz7jAkIEhnJ4ZMuSfpW/0kaPLsrzd9fQNHJiL+o6ZKAC+xIYCEwnXLpEHHRirlSc2Fmwdv+DoV/iQ0J4wqVBVDvsa7loY3ScC0WHOmmVutWBDeUlA7UmyxSP/zww0Ejy4xRq1hIChamSodFt6pEMacxrkx5YGFXwXOBG89K6Kt0weemwVBGlTlBI62jJ+8bb9e5B4eDYNSqW4eulp4bXIMKG6+UHRXxu8lQQBWrsOngH4FyOi6+MSfQAK8N/W4VXjOCAWx+EwUGALZUzD8rypVQZBRrQH2fsRuyqUMXg6CKMcNjkagmpWQKUWrDjZ5I3HgO+d7pmStBCrB21E33C/c9KbvVWguEpedh3Agz1USeicXXyz3EYyiQYJU9huuush9uAsFEaa7zJ54euI0r592l2b77fy18B6aHKLDImEgWg0K35/zdY8FCbx+e8wuy2cVGOPuLF4Lfn7TxZvSPYrcK9slw88rgPczPbweue1rj+7DTLb4EKfBbA25v9IVpNYWl/3FrOJpzXr0+F/wcLZhoKpxEpKH14/5+yGDe2v4Onj0VJUBHz8RjXAkEkQ2Dgm0s2IKR34uf1Hm52iiswsGa+ydOySBERZZLibW1AgtBB1kRyREAGpSbMYlD5BRGXot52UTsCoOJa5Z6f0QHfVGW4OmRzYiRZsQDwngrqJwFSFDKKFysWWavpbI8fb8lGHEaBhGlMgTIaCYL0KMDnOBZScsx5w/Pe4b9Ee9vw/bQBgskPGZwLYwwXjteG7wfsWdR5h3/zfvLSNIk/Yo+TrHni1IjA3S0bD2sZTSqBYDM6Pf277A3SGcBBnLNJDtbknuiTCOwOot34cmkRtAL82/1gBmjNnO3mb/f5XtMxmS8mzEBQWJj1zbnsoErkHCQTftivFDqex6OzeRgZGU5ECNNIsCU3ZDSLoBK9fDu4FpScoMLWUN6xnoeUJJDjTbpjtUmuwnMsClmh4tmib2X3o4axnKqqn7gA/7Y0NVLuQlv3u+aPwcpEHVSeFMsxrXEVLpZ0GRh0JijyNFulSku2V2ATrbeijQU0VRTgkNApUZUagnjSx28HgkKBIfrXNBYTzrCxTr/msExAHToTtx9D0i3qD2HLKHjOXDNbzR6kAhU6GiX6MDmx8WfA52s+gl0usF6crg32mN4y3erc5gKpyjUazyTBDc0xpWso95pMFE0mYNxlPSHILX1BQ8IVGLemWKTn+Bn3mvGgK85NmxW09PYCMNbxySw8N5QwI/gAijY7kXLzClQgPH1vD/Z5dWNp9HVb/Wb3Qqde9Xrc4NXrl1mN77/w73jaeahBYBC07eoZWcHlZt9YYSRVTAieMcEFTJU1FQU8zI73eU0Nu7SjU2WbQ/6IfVZaM+AGYT7qR30PUJh2/EOwaA0IoEcx8RxhpM57x4DExZ2W9nnUjrlpvgBcy555VDYILp5PxTdJpkEBZP6kJiYZKaD6f25hBEzU822SuoKJItLs/y2shXj/UWgl4kwYySLhhF35mI0atWcA/pOgP3IJogm0sSKNDLSOvsJfjeC/fThwueMM7A1EgPOicJk5LHFzOnHfQ6Le34mgQ/1BKlRHBNIMmw3yB87sh88OwR1VDJhBgxUSwDdhnGJ+UVZIeZ7Gm+k0dKAMEpVlxAC0BmUUUHS3GFUg5nD+5NzyjgAIaEvGX8Ge7TS5J2IYTPPB59VE5AwRp5r9gzqCRIB/Ix5tIDbC8Bz3XiCvHMv7u/dMfEEmYz3cExAkMhIbt1xSVq5XEwEY13f7NYoiDpT40/jxs4gK4ByAxTDjJxs3+8SivitkDVQb4/CMJGiOTvoC8tqrz+2DBtngjPa1aD5VvI2TBzREemYZZHxgnNrNlSy0XGvA1Shydxj6PZTgqSoML1TGDPJbplKMahvRYfGyElgUFltsBudegPMQ1HMltvWR+ODs3O4bqvR1VrRi953HKP1/rsNLoX9YhIp7LKrMAxdA4YDKLw1irzOppZdW1zP/NJs8H3bv4PxYkKQD90ra5Bpz7sxnWU6CundBAKbOuDqjfsaYZYff85+TwBO+ezKsOcBCthyhX0+h/BOMZKR1ZBZiKEuwcC5HX6zN/Xy8aBUiaCgsr3Ss9AX4/moYD7X/h0N7LgRh8dMiVjfVORqDtedBX2Ka5iKUR87k9lxmAA3Urre/3735zRdLCCS29LJRBFN2UtJIE1GfpbMnovBQsLcdWKgF/MQStkZFsliLZ5IC2P+EQ82DV5FZ1MKrgryAxOlSxmVFCVcf7Lz4Y482QG1REYagIP+B4zOBfOxMydwLcP8YEwDJTKSRTvBw3FpOZQK0XeJIKNGxxqAhv4rjE4HoEDGUvsaMKVUEhQblJcaVgaZnWRRiOTEGESi68z3UuacYThAmsH7aaxJdiwR7eWDSwKByIhKmORE9kknIvfk/Y9tTNIN7yH6e4wbKZodlHNyP6ByHH6Okf0wgWvvtjC4L4NMrWqMhxHX0HQTJGLnI0lMYupMc3VKUAk4lmftPBL7bu9mGJYJTWe1wcJ5haarSzwWExZAIA3nL18pEfEANfh6MmPHSY3US2wpzJrYMIlPMqp7v3vQmCCt+XXyLTI5ND1uMiZjiWMCgkRGde6Cq5K+8WCgkWcGZF6LW7pfG1NP4wpuT300VhCby6ovLv4oTnO4/XPjaDTVmcSJYQFOCfZwQgEA0b4GUbwxrW9Mv9r+jgkgYHyYBWOPZQGkJ5FYQer6LLrB5/3nZFfE9wKb+gSGhGR76BSa3IZMA/RTdt4NewUFpxaj7ETl8BHhpq8d3LCv8t+hf/Z6ZOMsQAE274RKElDXK+kYVpGigve6MpAcN9jsttxAtwdFjnpe8Xc1UzYoN+AzJIOAG6M5K1yn/E+/bl4TM41jly9/S/TuTCIAgEitLunITV68Oc4PPBKUDZkhoFS5ejr8HXBvjNag4FxnGS+9y7eD8Z4l/X9EQkOAhiyflGZyYBkR7NLB3xVI1sjAgOoUHCjmmv/+zbeHbvnyBrscueTK9ft6ERivJMx36dW4nIVJMQU6qCa9AsaA7fsd2BkEGtIzl6PeQsaDCBv55K9eCksZRPKYwjuk2Oif4xSgVqeQOAH5QoQmXDKpRdPEDgKUYqeaz9oOG+FJGVK503cz00MngulVWsiY2EqRYPo3SOOAPIBVQyMHQ6T9HZ4jzusGZMPn5Gft6+vr18ORpPQVUE8rmv1eDnfReSw0SdeR7YLHCsBYlaiZojHGcsE8wE55O8gKBKMqaUwZI2wgA/AwBhUR9+MG9w2mAB0D1hhpBlgENVONALx0ClYBof2Lqqh02SRowaw+x3NUvQrWk7Avye6lHw/9c2jY2g6CA7hXlmoYzSZCTpkgGwpS6HeYVwsvMQlD8OJRk+7IeU8QKqDPipmv2AzE/cA5miyh9jsAJEvhF0aWLJmH7d9hHkmxvyWTkJ/TieWNRAbTG08T1Qyrj+Ay53V4DrW/u7dvqquhc0tUqE3GZEzG+DEBQSKjMYJqPEG4ia24EMmEn2KzWKBDZKh7jDXU2DUM/i6WQ98eIxbn2EYnhW5aN57GqwF0dxp0qra0XLP8vhFmhrouIIhJhOHCRp+Fq6LTpW4Wi1G1FpIRMCeqgxacYTFHZ28jWRF6tqFFYvOfQU7DbmwpqH/NDi42dyX01ZoEwcFNaYkOUcLuhhRMseQds8Ges8ycCtfTgb1hBiiz7WvEs2XxvzPlAoUI40DbQ8OGjAUoR6cQSLPwtYLpq/HtUJkJigcyPMwm+F7BHUxJWrU6KMExm3A1HmYaBjvdAH5MB7353WEAPGQn4VjI9OL3b0a5f1swqpqRz2TfNGO4y983PSbHoKA3xm7ie1FjvhhthM/O7VG8o87CAmBTA9r+D//P/9U1teeWNXPu8dmz4YhcFNTl0RNBvxpjviqmr+meHUGguHrtUNi8VApNI4fBPKYdaMpBDEMBwE0J34lagNHkYQ+85IjApK8Ok1U66SpkPhAcgDkw2YYdI0z4x9DgsVhpWU/9y7i/D/vvUD7mv2cFCWhf/VoA/iWr8Ezwfr5hC8MEchDDfACA7GAS3h4DGgep+JIsjHz/njCA0b43CqhbMJAl00o8AjhnO4JavNYRs8lxwwC4wkAyQHVkMGpb5TAsRpcqf6AfEQdZFQnSXTpNgCUM0+mXY6PHGNcY44ckhX4GppZhAeC5obeEDkpQOIxRvYDGNWKrU4B3Jn4Y/j13/wP2TcfD53kcC4EAhRbxsRGTvMVAKfUJ4vk0BrSxpJslDgOoiAzZ3A/05mN07nphpmI/UR4F4xKvIRsq22CvTYl9pDFbPng0GndrvPogGy1xf5qmVPN39wDdqpHDPEhjIoeZjPdwTECQyCgf3umSfMoYZlJvThZFM4oNAA6GYDsgRtbEYu20XUY66ic3gWZjwdHFxzAMqOdkx41sDemkaRb9Umi+xqsC1OA80oXpRD5GTKS4UapOnI5HleJzTNHNTaB2e8DAMZRVLqZw0O9EDmKzy4LLmIWpnhbXxsRM7tgeNIlt3w+bpRLFWP7wvnCn5JJ0TNnRBVPJACrSwTWRrNxgkmXyyF6h/2NzwWcCHQ3j/SIbzxTRd6Z7yO4jZS7CHDDvxWOGZMOJr4y5V0jDxjMxjoZOyQhBIbPpkvuO9yRjYItXEcH5kD239Y4tYbNl+lvs2BpnkH0FQCeLD6ZKzNlNef/t88FiskLiRcZOFjbu7XtT9vKFF/3POH+UyLXvDUZWiu9ZNfPV6oX3Sxafw3qMDMwY9VIuIJRwRh6SIWBMgAliCKvDMMf47ANwLPeKcfQRGNWS6cXriWKQ3cP2ECClI7uMc4VhUTTHQP8XJrLACLresCLKdiBLMQcgXYNt5zbY+7aE/K/asS7ouWNShYRdZswJj50NzteJFPqM5U0g+aDvkzJhEjB4CnSEe5Q/srs9awvGCl4PxoyPvjT7dgc7uO1Ah9/4upDhgZSrZqRHAIxGZD/JY1bOmdJcHfMdWXi8v2uJ4yQzJrpJ1HWW/kSQoBpDeVzDaqWkTB07HUx0o88OGSLjZBJcm+nToCNmSmkkQNpsiDSfov9dZMgOTIjyjcPBopuNl3awKYCCeinfX997qcOYKlOOStN1PLeJAGl83iswisfFD8cMac2azc+R85SDPcHEJ8PYhCeJfg6PjSluNBMvMIe0r6Hceo9fY1L6nTDKSY47IQhNnzgkshG4T5t0mKX5Pb9PRh1lLL6j95iMyXgXYwKCREb2+lGXNUwQbk4OoCg4Kt1tRulh8qV2XT09OGiGyoi/5JF9QU17O6CzL4huf9nG7y6+fosUwKS5AlGnfCQVdL9A3Knx+0DRbLTzER29bvgLxqvKZ1bQ/FNfy6KTRXMyL5szbpDZkUfxUwllN70yCBaG6YE94S6QmJ85gFzZIb+JLWE0q/4eJjUFxTHlFzVp+PPiHwAjTIeukgEhYIar3WHS7bM34VPASDrd7OK68/5Ovnkomg7TkQwsHkBY6qQjtokyaUHiZWM+Zit8K148uLSIXjAxHM5TPi6lg1Ih0H5zUG51TkgvYFPOLiE3/yiSdLPLVBzTccOhleM6tYwQpSSJ10w2LNWpM/eNkKYvQPuaN30BV9BMrjn+s81n3f2MBTlMJ9WBbCQtGBb+hp3AZjClgQU0JUCcUyTCs0bxkl67EfY5wnduvydARz7vi9+r3R/XYUaesAqrff69ei/4jXsi83p2Ad5ClD7ByLous6ippmGC0DcJhUjvosSQA3jIrkAWt4LAqot2RstpxOKiAGYBaVhrzd+RuUZmCe4VZRuwA1tvhWwz4sdQ/Pjz5t99yM1istMUoHk7KCPCd+Balg8pHROKP9af8iHPDCp3eA+jAYDMZoye8MVk/srRoFcHmWI1ots7+xHsDch6Snu2SNP49RDY08iMF38+as9TruyH+0iFtfCPRa8T0KBEQk06+ewlvJ/kexHUsdIQSS9a+AyuHc2/0fmPghPiF2aSZwDEddiLC8f1kE0WSciYvDYbvrYKCHFe4hyHvQUBokzYtAQHSjQOquJ2vElGQIKgM2Q7BOg0wppgKPdK9MxRJgrZG+UTe4OeeSnmIfXJK5/cF/R5K9f675b+pW8OdDyZAG5nr/p1cf55C273rtw9n5XeG5MxGZPxrscEBImNpiObDcyGP4PvRr1ZaLak4mPRL0AHJp1ZQ9WNYSUSN5Iro6i/RkKPkUP3N0sapx+N0SWZutJ5PxwP9dGM6FW9OmMNidSbod07eEAYNg3jQM8ixlapwJSGoNMby7tvP5PvwSjhCP2V11+7vjxPGQoz7YKYghaFcjLKgxTmWjppNan8e3YGu4LuhMTY8RwO0W2ZQicMdM92UFpCwzZIOUoUtqmwbHh9h/s9g6Z3Gfe9dPzY7U5IY49QdhPxFaAuOzvsu3TVEwBoxNeFxmr0/Enhb8FnUME7snHYxa/XLQ/OKe3fbcBG8hCKLDKgAIqlD1vgZrjZX49+4tlM1RseBak/6Au29rthU5WdGQYLVcYK1tqp5rlGAVqeOR+XiRB4uQTGC+U4rl68P1VXT7CG5oAseJTGb7p8ZAuAlUDAUEExPnssrgka0JupAwwCCDOdYnohAPBtf3fKn+v6BT/3JABwS9xP7fe8DGASxtgV5Htci1RKwdcwDUQZRNG0HoALBPVqmghPiZfNW6fDayuOhWBwRw7J9IotYCXutAyHIZac3jUUds8+7o/5MuYeGJ43o4BUp88mABoUCqiw0EtZDPK7UCKx03pQmEhRNDgGZHhADtp+tzcA/gBcSFmoEyQUYJpGxhX8Y9wLr8YL+N1+XUjeOn5fM1QaJ7eDUk/MCUsepiAPAyLVBfXaCINfOSR6aowaA+EZz8r9kIKMPDYXmW8UgKVkg3HSTFWyEgsLatEzx0icMfflCvYwip2JUxWaCOcu3xdI1GPjPrQYA3DRr8R4h5B5SElX+4aYo05jLsb6ac6/gOUpJJxkgtRIu9N5KAdjo8aamb7m91aJMIWZUJeCLU7AdHBK/Iim+w9mHOxEDjMZ7+GYgCCR0XTqkrTvyh2gv2Lzr0ZkHGbz/SW/aalpUDkmYnCpI+aArsaHi8f1upW/UMLCUUG3q8aN0cVsC4o3LvpYyDodFiDqpoMsY2Hybwd04Cx43FowMXaLfwComOZzSKsUumJMrxwDizpsh0sRB3ZumrSLT58YdmHwcw1Ao4K/SPt+T+G6Uz+/BnRLTQiiyRiK2cYTZ/GYlc0DE0BjDrvKf05O6ZV4ZVBC0z8JKcRadGQE8GMCiEltobcE/VpIUW2132DGINrY0PJ1U0+mFGQFCWngOLcJ78HmHnrTg1KOnj2U4Mh9Z+jN2CCnd/CZr4JC/bjt+A1eOhY0ieNckTN6Vwooxupys23M/N6UtATKTiqweT7wcATccK4AMJmCLcBOXiOHWQATixdswgLZcm7HtrDGHgByx0SPbDt8pokzhVdHMzLxUgmx8Dpx0HhWyBQyoA5SvpKjVu9fEAzkvcLCEvHJOiibSV/wbLuS9wMlac0lRKFrgCNQ8tX/gUVfeuVG8O/Sq/DKQgJMx7sEm3wDtMsca8A4xsrfwZx0MQ7AciQEATB3UA7b/huSDQfj3BL3gJmrxBOCsdM00qTJayc5BxT/8ll/DrIL2EOoeTW9twgYYo42Eh6Z+0zD5Oz5sARUJcFgtsRiisf5gJBVEfOdMMwL+TvTvNFI7SUMroXacOKgQTBB+ITzOvZAGj0bHUxw0TX30M2wwTIlVbjOKgGqLsYlQf7NwkyW9njAAI6+fIwEh/fTuKQX7s/q0wDR+UdkwqCp1v4d5eM0SUVaj5GcCEOvBkOxfBqNF8r1xOS72AzZJ05hNu3nxFIaB0xgNPsRfhdJuKt6d9+8KB4wEKTd307SYSbjvRkTECQyyq3rXZJNGXpz9jY2dNIlLChzYGf1KvLd2QG+LiZvAB5IfTddFDU/I8BAuiQ09mYTKUBDDWpqCZosjeGoI1eDRGN8hcKKZUx92HZBaPyUkpaJbpV2teisXe7xG/bsIpByg+bLxncXvABozMbEDG4mdOPCgosbFYAG6q9iOqiIFTSO/OxG60aWGwrG0GLjXUs6T7UMXQgWbDAVVZotExscWD/1hUthf5RmYAE37UwUacagU5Ne+Jm41xNQW9PnECPbdmdB510PMBH+B/XXsAn/oO/stv8G4GaSfLCpnn/CRjb2zwMEQfFDL4IaZo+k7HY01QSCaNgpUo7i7WNhI0vEmHKDm2lSy3IACtuwuaIxqbAVuMFN2RFHyghpz/R0uXvQOAZ8TxbTOgheVRvBnGvmyFNd2Uuy2xYS6Syo1gAaMsyD2R6w00TuRXCa3iE0VExe1WSsmWBBXmOON0yeFvxJg/OlSdFBwaRFHv2ACKqZIlM8CwwgACZG9aSXSlW4H+prdr5M8R1oZkpwwQkIUuM5JGPGmPvRS2edZU3l5Y7w9/mITworcM3a19DwGq9JaOSM56EdlGUB1OF8F5N1KAOHay6LJP7cuR40UAVdP9nh7y0tBziv9L7igaz64d1RkJHShPaZCkgGSxbqureANCLfOhMEtRQoiLEvYmlxGusb8wszzQ6RnGQA6xciRHVt57OSiAwrgYdDBSNLYy4sJqMGsIsYH1c/8ox/wTFhSETSRMi80HkglajnhVESXEfzTY2kadyeMbGQkpUlRj7HhjKDYuufOX8qQSUwh/NE81Ea3XaeVe7XIV8ssDfqHbXX08S60zfqRCTiVgDHnPMNZEf02VF4iR4lBtzFPrbaYPekyVdevvv/D1pE7mRMxns4JiBIZDSbijrPjCO9MQ+TjlL+VngBr+FOT51tsV58K/Dv3hm/AOZMKJBI1BoTO40XKQUwFH3KZ5q/QzcuY6GPhTE9ZDc69U5oqqm9xgZmnPEVWRGknlfHb0eL7hqMh5odEm6wqVkVOQy7XBWKSQ6lzucsWlmoAgQxrBBl5WDjmgFU4sZXWTLmmFEk0UCOXQsFtWgxYjS0YLwodd69AO+PpxDVthwa2jW2kEj++hvBY65/yBuT9rDxY5Hbvt9KFGA7/P3dv3Qr6BHQDm5q4d/Ca5Bgs66yWVPQM2aZ1+nPXrAvYvoR4/7SMLiSnbcU7uFT/rpnN1EwsTN70IMe7Xs/431yaAaazPfDnTRNBkFhQfAwh45ao61NbCi71nv8s56+dTIe7z2DqO3XjgSPpSPdQsJBDY+WHphB7XdYSCQR7xQWfaaLDcCv8z2vItEFRrHuAvw5CKpBu99+DmVdnG8AiqkszrDysCmv0OWjNxJlR+1xErwDsMr7rpICmHTt4Rr/nacPXQwyTgr4RzSjdx6AWzoIm2VKAWvMWCFhyU5dCkvCaMjcHOePPuu/J+IsjUzjB2x0eo20Gt4PZo4VxSXp7ik9UhB/PEKcNY1+O+A2WREEhsfI/4xnAdcSAsNSZBl2FKUyJ84Hu97KIuMoIxLDelxCHSWTNKgU8M10+wkS4npkTAmJSEt1UApYnrOdf0o76gi7lmtzR5YHE3rzOwBkBFY7TFnsJ8gkyRFrT9lWx9SYbBoyi+TcJJCdjtb5e6WPe4WR6Cp9JhDEvyOrJV9ln2nue6Im+hjjEg8JfFAiXZ+RFBsylShFn4HvERhU5WHLSjTsXEh6e/B9YhpZR47C5hPjgwHeKUvJzIUbAPxch7xX2LA1QWzu68c0ERYaFK0x6kt/4B6Y0TTP1Dj23bzHZEzGuxgTECQymm5OUpW2q8ONLw3fZNR4IBmd54D+9uihId1taxrXi4IY7ORwsPtWIxZSqYcZiwdstCpGygmtMr8DKia6MKQ306Q0p+t+M0BTpSaYululXpI6XiKaMT8BKQUouym12rqJA/W7OoNNPRI32s9BrGsGmQO7QmbTo3paLGCx6VllS6Y7gIU15SKJTgcTidrXHD0XXsyxsJpubnNuN8Sj/BZfLp1io5+n5n8Wzwc2bQr29K7eua/hWQ4qbDPK533xkV9EtwU+Bw4d6FTABeriRzvR+Rni6kjM9PD5/cG/o5SjdwUeLRL7SfNIFq3DGXSgP2w9c/g5hr2CYrDazvvbslfI8jCRi0zkoYQoAFItvgZzX/norqhEoL7XoWoHAMySxc81C0wWZLjRK0mTFO4BLvVXX4kWc6aTBjmOjnorzIpPXgyDOkyVkMKSnhbZmUvBtKRU53VKimDkmdEfhGaAwkijgSuPrX4zHp2eoQs8mIMRJ9NhwMQg20NZIim+p0kd0649U3korwG7LEUsbyJzX/7WmbCRKBMmRIKa4HsaoBtztCYEcf4miEEpQB/MwVo8rUocg5m/gbpqXL3xeliO68u9BWOn1TgacyTXc5tEYZ+vtL8latgcKrQN20IKPTNfwOeos5/A+Sgia5lJbyKg0q4fN4KsBK7fKrkwflsowsnaqo6dijJJSpg6m3OA66HGrDFfMvO+z+wLmum2g6AlpR247h15LY2H/wbF8XY8a/CZyASgislw6YumnlZlhJkTG0bqrIwPMGsJ3HdYpoy9RgORCXc1vaakMRh7boyn1+si5wTrZpyvSfxzcD7f8sB7yuh32R8awI2yIa4FIjdb8AKrFdl9v4+JJ8hkvIdjAoJERnbttsuy0nQTDT1dstorIPKGusiFDZTTUgpYFqfs5DEmk9R93XSwgCYlj4ZamVJBibpzww/H9EwK2BoO6iaelDIRTOSdQZnFI/uDXb5c5BMVFgljFkUJDGnKYuZqGBPo3Bg3ejm3Rs8qHeWFkdBTReLhcnQEDJOFmxPRs7LDX21cEzSGZccwv2i75pSgpJBbUTvf6VRzoWXngwUsCyFhT7BrabrzR0DtZZezGdgc1Chy+Ewk3Ow33/XcteC9NkIyRo9MGAAA7fuBHZTdgXTtG5CCiFN9/vrp4GaRW5CEoBqK5Pb9zl0JeyOMkVebjh02Skx9YdFt/HKkGGOcZM2YZolUJUqX8p7c6L9PcvxsMA2lfQ1AseRGRKqj3TPGSXKOFYYB/WNig13KmBdB+zsCD9z8YyNe04yW81tzmsheYCFErw8p0rL5jfc1YiaY2qGkg6HGv6NZZqLm1bfQgYQPR02PGFyPwf+fvfMAj6r4ovjZkk4IvffeiyBNKSpFBMXesXdU7BW7Yseu2Hv92zuCgIjSpCi9995CIH135//Nw2TPTPaFgAlp9/d9gWT37du3b+fNmzlz77nVTdEYCQkRr9VgPn4OHM2iOH1v687IJbBXWxMsEh482+g1HAVnfbdGGDtXVWLsewHfm3l1lk05KaqS20OetBH2ycln8mQba0YSAUJcftha1WRBwkinpApatijFEZcsrNkRj7n7skuNktcRm28a+7UmaTwmchNE+DtkAcJ5DQlWfp6oW2ILw2kjvCgTWk/CCVfpsnyb2LzZOO8kjNrCZIhTfXhMyOXFqR/2cKlUR9gLX1/eQOT7J6f4OcfAkYw8gSbRl8eAtqhlpPfSefKTAa4hxOn3dBPiqB/htpmfgGD0t3T/yc9rxFiko3EsR1V4rIgnxet6LEbS7x6rv8tTRewA4p3tnWIb3+bg5ZQq2xyXr8l1ZJLN44kaVrWdf8fFKnTge2KpQjxBhGJERBAXVJQfyuc3q5uQIME3XE2QbtQhzrXllUFa5WSvkP07oN6bxQoenFidr8fFqE+xWSObrNm543zTp6iMoBVib7wnDWJ8lKpj5MLThM8OkTQMv6g6jJ/Cpu08bl4RZ5duRFeIvEpqDVw9FIbOeelGmDKZYOYppUvfAa+oGJM321ywCkW80ApJkAcKdpQNiTWufgqcq83pQFaYLafAeGhwkycqhUy5eEBiDHB5oOR4CJCXC4WcenfROaRShPmZ4Rk5wTQYUc3NFXVQRBFX0Iim0pCKPqfxnTvpNRS1RJEHAYowCUSb11f04sgrYbxixgMVTrmxy7j6YxtHjFoyyhdbq0fw0yo+pYMYZaIpPF8T5DbJ1QIop1pZqSXc1rh9+DiijfO7Lc8dNkTkMF8erNsTWE/b5hEHqM5gMynnulS5g09jsmGvblO/6KtRzTUkPEjlSXl/ivxegl1buaZ9Gauz7PNAEzFDjHV2GDkyxYgiIOHJXgEOrQ5XefDUqh65QgGlhTjPUToKl+Jl3yX2TeJS6XYf6aHIPSPU3Op7QCu1RloEXd9cHtZrpRiwiMwCjYdSkrxNrT6BvX1IeDFEPrvKCH8/3I7pOjS8Muy0H4qgsVN6XCMcKD3VuP/xvahNE1fjRS9HmfBiB7+n5RnBE1Iu3+tTdJ9iscqKJDEEKzaFJhGBIzdsjAk5CXZ2dJVxzNQvFji8nYUsmih7kz0Ro0XyTpqp3dHjnFJsm5QaERNkVM5iTRQJIpxC7BwbR8dyaiaNYfL4mnHaJ0XGBlzaIBtE51ng4Ggouta8ViSI4n6AxmRGlBCNb1WKVa6XhaACpkGxF1iQx0BufiXWmNgYb3NbY08Sl+gdu79yEy/ttsmCk+GLwuKlFfHiJv6oKhUjGkw75LSJUGTTYEEQDh4RQVzwZGXB4/UY4WnGibPUZLdcYUVh+TwItfdrDKRpEJXfBNJIx6DBWoidqGkl1Z5wueXQut5ULEXbSA3h6BFesbQq0PhTSOBwKRmZ5xjY5ItWaNxSYNh7xRaLFDnte2gQaOe8ujmYu0Xf5Lmx8t/WqoxrDq098Im0ikMCmVFRQJ8DOjfGAIYmT3kmL5Qraxg30iDY7RrIUwqYjWbzyQ82vk/2b6HvwxbiOHKA0wp4MmpUDLFMZxV9VyFazfS7vL/zGhL2fPQ7V03xkK+ALRZxNSajNCRFr/B3ZguVRrk9rm5Dm9spAixeGd8HX5MUoeLsm44tuz6FIK8KX1/B1eHr3tfc9KLx1Gkf0e/Ey2Uyrb5GcUlxI8IhFn/eHI8qFdOwa28Crn5uf7+myAfGPp9BjrSikHC/NREIsdBLEUi+1PB2USu3RPYN0eeTUnL4OuJJAQueDtSv++maCnHECbWHPP0Q9+vxkVNL8lTg4kE6pxdRFFyAjYuXWJUjyJuAo6548meXSQ6y4GRUhvJFvG5VLSv6ZP2WiG3FuP9YIj5HOhmljakfy7PKm74tYiqgm6jFq+Z2lamgi1Cex/iyUfhc+0mUYm8Gbz7+Hhx5x5EogRokSFgmvnz/QvLeyP0L92lcRt32QOKIKC7xbkWVcJQI4yZ85CnNTNexnYabe5yWqKjYV8wl7Se/1xttla4bI2LTwu7LDvieK8xytVw+3u1az8+k1MceMS732fyq2zD5mcZyBUOVEozYHox0IiuayLiOOYKVhF4ux+3sg9MMXQx184v2Y2xD24IIhsZ4xO16sjxF+JrgsWKIxsRey/vE2DcJ8oECVOEJlDVjVEmHEYoREUFcUHExUL4YU51v0dRVzfbRqq+XBwc8oGITRivEUvHKGOWtcudrlHi0b5T8O91zeRDpscLYPW4DFRoYcInHPLmdLuHdXJPeTkvggZOHBl7GpNkSMYybSSoNHGlQbvh+2DXZaQLlNoCxB3BBLk3JbI5s8GVP2t0MYI33sMvgsU9CAYUwt0gSD/nHGN4Q1qDe7Ttkwzm7UgtHDhgrjiz20IDKFtL0tZV7PDTJYrHF072D+Z7/LI9cnYQnnSRihCikPT9RiysKGOlZ1nfNAqaHKizwxFLVNNNpjP1RRBaH8dslUc2VuQruZYYjfK48jvQNyTOBqjrZohYPCv0UoWas6PNAjUv/WpMZLnOsWpCPiOU3E1pE+6BBvW6PCdEKFeOBzKAXqlJixHB9Dh03wsPZfHqJ2UcbZo10TfC1bkQ72KVnOaqBBAkWxG1fGPZdYH8KQzjJZ8JlGDFzRRk2rZ1r9T0kqoS20/VJbZgNvznKx4E9odiTg/PVrcPkNhSiSDFeDc5uUC1iO3OOgc6b4a/EfSet9OfXr3IkTHDNXve0HZ4Qr90ZuexqZWtiT+fDy74RHKFnpVxga/g7CND9h8U/kGms15q/KjZTZbGCvo888UZ8L+FJG0+gORIkTzoMCSz0fYbsqCGCo6C4rfH9yzBctfohY0zkIhQUNj5O1eRoC0qj8qRZppZ8n3Fpg2gYjrjx0mKP8xqKMDDSAvPx4DDurdTH5RlDFKCUMMN9p3HdWteHl3zejPRWjhiy0mmMxQ4SQ430RdvjxSVyzjDZprFNfoKU8f58DViisd8l2tp4PW9jjaONRTJqwx4aP9hiqvF6Eu8MgYjSZIx+XafDuASplEqcCrn/sURuGasaLBw+RARxQa90OekwXDueBrR5wrs5xJFdtamD9NONwC03VxOiSQYPLt1ueM77s1jD+bj/LHY33ePVL/6dJ19s7GpNmo2VHAqnNczPLEHCy6HOnM9LERr2JMtLaTM8ufWSAm8MrqyJPXsW+GkyGNoUWQBwjofML1kQYGd4Hw3W7bDpEE2yjBxYakP298FtoqDCB5Ndi9KgKC2CB1B2STm3UoAsKvlcKurkWVVho1teibKM5Vz3xQIbm21a97j8Qqpz8FL6h/N6a1AYfoImAtZqqCE8sCkxR3pR9A6nHuw/UFqRp0med2d4u4C14me0IzJc4xBm4/Ct0Fy1bHXklTQWCW0PCM6xto2McyChwE794smMYcrMKRv2cXMYOJkY+vRr/OP2/5EdQOjfCJ48K7gu5Fc9yVgF53B1Fj44vNuOsKDmYEQ1sGH2GquiDKcHkZjrZy8dmjxw6oItrrJBs38z+c1YE0ZONeFJmtdfM6IJMZeHdZ6j/j/k5odkTexYDDWqZlE6CvdJsEPv65Fgx6IQf++WB5IboSWr3P0cKCKMq3axUS8L2B7LRJGryLit1ofsFByXAT77dXFUX55KZTxRpohJI3WKKkHl8SBgMY8i1/JLe3Xrl7n8MAu2Dvy92xFROY83DZ8//26zv3SrMMdV7Dj9JM9Yi30fXNLybIJ87VFUHvtO5DfucoPLROdJ2aDvzYj84rQ+20eLoon4ezOMf2min9/4wRYe3FL5jMgOrnjE3y2X2LXarY8W89iY24g4tdJW+R7K91ZjTMmLKpYI4ubPYZynPB5K6ZHH67zAwOMH27zbBcMY1ipZ7Ba9aRhps+mtPh//Rj4rJekwglBYiAjignd7MrzeGLNT5EmFNdBxM4Uy0gVoIpPHdI8mdsbAjUP3rcmHETFBk3Zs3BZZmSavEOc9/11ldZ7j3Fge/NtlInmFfsXGiANCnvTbETOu6jwNruza8ew5YMAiCp8nO9yRX8+vadoo8sDbHrh6I3sOsFN+cMs2V88Do+oJraiHrIGKW/SH4cNCK2z2yo13Ew0QaeBsmPbRxNr5mDRhcn1/awXWS9+VUfrOFtncJt3cbl1+57xn5z2XrI44IASHmZLTfoiiTZy/KXeaB1F8brhkZb5RGfT5jZBfa+Cv2MyN2pMis0q7rfLKP5dzZpM1bjd25QK+PrmEqG9fknv1CY7E4Mksp4NsJFHJTjHgQT5NVDm8mgWAPJEldvnFf49HD9Z99evlO7jN0+5IkMhjvMhpNy2oj6FJBbd7ezXVQz43LHywWXHQEqu47Qdpcs4TMxaObBFKcYTa3lTXVVfjNVyZaRNF9bFJKptKc9uO4KUSUaChPi0/MRXkh+CntLw80USBGpGFE4pIsMVt/j5DzcJ9l2cRGdW6RFA57NgdORKRRUHbW4Erurh5SNmVwngyxIa6+RmIEyGKZOSoPMWpeHx9WlGKXI2D39/V+NGGxY0gCX62MMnCgYvvAxtz264fPDbg68hDldo4TdPZziWNlqMV+B5nR9PyZ+BoiVA+ZqwHS6C2ef/0b6b+n72OOB3WEs4U+aIZ+3YRx/OLBHETlI3Sv85CjktKDZ0bN0HFvjf5q1KkNKeNslhkjWm8VA7aT31UfvcCV4GFSiEbXjwa6td9LOzR44YYa5vgsyhDixJ+9kWzri8WNnnBzLOe+l47vSynGpQukesyJC6VSDqMUIyICOJCqFoSQr4YeGkAE6KBJ6/K5Qkp5lQKGhjwYD1EK0rOcy4rNJxLaSjwljGnIXbQYNPDJe3sSbeHVj11/HmkMD5rgOzbw2ZTPDiKbMRpR0hwKCPf9Hlw4qUbpvOeFNmiuNwrTYCN3O8q5sSSb6BGuDwP1KzVGuNmxqHeFA7MwlUe40Ya7Hl48kVmsl7bdI98F3iwymZZ7Hdim59lNAi/T+w/6yKeT/6enePhQaEV5pmLJRB5yLSUqwd5tuw4sEGZlYvuySLxjQf7qza4h+bSan+ABlreRuFz5ttrvSdPcmhQ7CEhjoU0h8oUxUSVGOALRp6I2REz1FY8dWmlm74Pu3wlewvx5NSoUNQzXEnJt8iaSNHKtSHQcFqd5cfA5VaNyeAy6i9I0OAqRM6+t9B548E3h9vzIFTjElavz+crEwMIeXQJ7YzcAa/tH8BpAewFE6KoBjePgvxWwf0tmkRe/czHt4ivgTxeOHS9GsKHYQhME5SqSa7nyYjOovtNHiGNI5KoHwtS3+vn+5U14XKLPAAbTlv+N26TsSBFItrCv/F6vg6oUphvmemnwHCKmo+qFwUo+sWeNBtGmNT3GfcvNlG0q65QVKGxX/pu7QURI0qRI7I4PYuqlHD/kOdaWb81Yvqd7WGhFlvCYqRovQKWQDWiT0go91seEjw5NaIPoyJHVdgGsoZoSfdjjmayI3D5fdhHxBAmXUQ9m4KksNrfJ593w8eE0sD8a939IEJ0bIavGU/A9eehdMqCiFd2+otbGrPh85NPtJ0hNLN3VwH9UbhioBFpxRX67D6b+isj7TYfo13jb4764jEYjY/tstNG1I/LZ7MXIxVFnRqv59Qaq63zWNwYK/F4zPZo+TeFNFTWPEGc9hQqhH0IwsEjIogLob+XIOSJMiM5eJXUUpO5BGWBTrztBcAh2TQI5QgPu1Qrq/A8ueYIhfycsHnQ4atD5ny0AmCXwfPspZVFmky6rTzZrzcmZm4eFnYuPqf67KEydBTS7uUIDdu1Ph+Pkty3sEJBObLFbSXPm1gv4qAnT/glR+DwYNVakec2ENxCg918vkPjPWlep7iCCfte2J4gFMHip4m6IcJYq87KxaOFJ9ceMuOz88i9vDpLUQhGyWYq0bv/Rd6IgxZud4oH+FZ0Aa+genZS++BBkx22TuWgDQ8H8lzgAbY9UTe+X86rp+o2eYxqN2yLfB2ylwGlqNkDOv7cRnUYigLwWmk7hkGkbfoWwbTQu9yacNWtGfGcGabI1oDOKMPKpne1qmPspAD0YmntSkF0/HeiyCUvne3oOHkFk70IbB+VQC0yumUTRBLPjIoj1kTE6OMq0YR+0Vr3NEcaFBsTDqo+wX28h8rbOtDn5AgsRQJNngg/8qdCI/pupv0d0TsmPz8j1wmX1d8ZE5ucFUvLPDq/NDajZOT08HHytMwu+2msnLMow5Ek1nfIJYfd0hz8FIbubWxOeLzkBxRyi3bje7F1nH66z3C6mOJVa14NtoxquepXvuVFaaLOn5NTDIzICyslyteofuRxB3/vtnjG97wCCGR2RBmnY9gRbm4Tdb5vswjhFs1kiyi+xg0iCnE8brFLghvHQNeuIUZyf2dHHtCEzct9L6cKc5loDVVnyfFJcnDRCG0fLrdS4wUVMTgq0i1qOWRX0WlE55Z8UFj4CFkRtGhO/lK0kMQYi0+WJ5YRue0S2crll53PxhNoTkmihU5jbMJR11a0muHFw2NSK3rEEHtYxK+c4F72u+u/AmwgA/jLfEoQhENDRBAX9M3V54kGKtINh0Pn7TzTXp3CryXTN7VyTeSQREupdw2r5/QFK1rBCOXkSik0mc0PFlEC1iTDLUTSR503D1S89Qv2nuYBeCLfvOyB697IZW2N1S86N3k8QerQBNi9lH2BVph4oBJYssm9ig4N/Diap6Ah0D76DjnH3KiCYPmtGJ+bK8XQ+csvlNTYV37CCwlEbvo7RzSErNUq4zPQQIVXxTytzMgaD5fg5GuFylaDVkbtHFxFppJGiV9O9bHSYTiP2ROKfK0Z72F7K9D3bkzUN9IgivsX628viXweSnHjctxG5IUlLLJwwMaHwTrmSjOX5DSi0FigoRKeQasiDXu+GBMhnjxkWIIfRTcZ5WrJ/8cpkfuvqGOvvrFI6OPJB/erVqlt0OTaQ/vzJKdGFEztlA0mitM/6PMb5TOtft2YPHFkE7Uz+7ozSrSz6MvRAtYEhycPnFbmYy8CFqqt8o2cl8/CB6/AshDofDYuKUrCB6dneSiVhMs85zHMNtIv6Jy1a+YqGDLeDuHPE/jHFAp4chts2SCyQMT3Up7I6P1RyWLjcRYsrYpooH6AJ7eeVKrMEaIxA6X1Oc9xFTU2p6W2wUa9DisiRwgYBq6UtmNHtnK0HIu7HIFlj2FYxHAz3DYWeCzBlct7FxQeNxQEe9xmmFKykEX9cHCX6QvjtjDmNrG1FztYEDCEc2rrge1W26aP6atIfYIbluDoKkQR+XmUGUbp8dQXc/qK1fe5lZg12rC1SKY42swFw4g6jyiWFNmQ12WRLs++6bs10mO5ymJtU3jhvozHHYaxuJUSzGOgULUKkfshqzqZmrnfkF6VtUgQSYcRihERQdzQnasnmCf6wpU/5+X+6qEbfdDFlZtX5/MIEjQI8/EkyTJBNF7PkyEKy+cVIXbgz8/PgW9+PssPgic2xsSfcsSNowy52zaHKkRedeZJqr1Sy4aEXhpE5alRT3jJGyHA6Tj8Htb35Fqijz8/e8RY4oKRwsMeLbSi7+EUC2uA6RbmanxPLlEtznM8MXXJP7U/Z4hfQzdzLjvq/L2aJkZ1akUuwUkT5TzRDrwqwsaiLHzYURnUvo2JJk3uPZQCw+Unnc+2iL4DFl64xJ8VssrHxvnRRlQI5yDzqp7VJlxX1O3vkNOwOGWCjoUH2157wsWGmzzR5omYVU6Tq08YUHtk7xQ75YPNIsFVaGrSSpoVOeDbsCNypJHtV+ImDnApYDZrpu8wP2NW3p8hFFCJRttYle8FARK8DBEn1lxp9m8i1bV6lYjeKcqtEpUlSIBW541oN7uPZUF++97IK93UD3HKio0hfPC1bq3is2BopB/upCgE7l8s0ThUhcxY3TygFpjRXUFq3z66f3KpVDsliqtj+Vduihg5x55DHF3mvA95PbmlVHG0ht3HBHkVvVbViCWHuVyuHVXAfluGh5J1TQdZaOYJGLcVF1NRGyO1hc0yrWsaJKqwf4xn7aYCvQ9fb0aqL0e15OOFw2Moo3/Ip1ys8Z60YOVtUMs1jctt3BRqRPdM+m58lMKUp4/i/p/MgX329cURbjSeMa4jiiKzRY+CGMXaKdrehSsiC1ac9knXUx7/HQpk4PbgpbGinQ7KYwUvtS9FESMh+m48JODnqcbFFeFY3Lc85/jeatxL6PUhvhfai2y8MGgthOQevxUNZIzLd9A4kD4/l2Q3vmtdHaZga1mlAxFBhGJERBAXPBUqwOONNsLbzA3MAbavXXhwEuLBt8tNPz/Hcns10XVAx34M7B1Ckxoj5Dcfl3PXajXWexoTO64ikGiFKudQ1wyR9bMz9xaKcHCpTuD8vZEmEpTjzZ+NByO2KRhP5tjxnCeG9kDJ8PjgGyANLrnCRJ6JPq/euZQyzs8c1/BS4bx2TkGiijrO+3BVIR4AuOR0O8fAAwCe6HNOtBVa7DZYNbZxiwhwRK7wxC7IA6p8creNVAIaUBjVCijtJs8qJb+eBiqGD4jl6WFE83AaFH8f7NlgCWGG+Set9nirk1M+iQb5CURGShhFCakYswv3UKqMj8LoOfLCQ787f1OUjJe+G05B4msq0Mlckff/TQNZ9mlYvDaiSWp+KWYhXSo0d3ee3HYUrG9GHnh2kdDL6ThctYTEx/xW+YxIEBaELMHUMLUkEUWxN9IycyXTQxETfH0a5VFp8pDH/JpSAz0sfNDxB5uar2GfHV7B5AkTR2vkqfbDAhFV82ATQ9s0kSsZsDGrWkneRJxiYAndIb6v0KSdfbhUGzM6zEfXDnsOsMATirWGODvC5zDIHlldwpM0Hwk39mo2T+ZYkPBQpFcenx8SEQxhLZk8g7jsKt1XnL+pL/PRcxxlZIgjGva74tQzbt9cGcVKNfLShNyIvuR7obVQ4GFPpzRK33CpjmN72QStykq572OkLLovBCkWeCglyRDlrHPL9y8jepD6hIAVVcH3+uByMjum0vHGcVF7dF7DFfs4zZHKfofs8Rj9bQgfXKmExzbWuC0/j5PcY9lmpiDx5w6tWhs5Uot9jiyPM8Onjgyf+T6dx1+D0i6N6GiukkjnOT9jViNKiHy0YHu02JV4cl7fPPx5/NRvwK4q6NK++Z5p3/9UDSpjTqm/Xmp3dqRvjp+bChasOo0gCAdGRBA34mP1yMA8WXyTtH0reMWOJ7NccpErVtg57iwoULgdRz7YN3BjdYBK5LHxJIe8Gg7X+ZSx8/DE2JrY8cSdTTaNkECeANuGiHQ8RlgoRytUs0xn2ZHfqlYTScTJ481AoamGHwWvpFm5whzmyeHu/pZNI67ecSliO8TcWAWhtA4WNJzn+NwUwLQuz2pqvyPCx/aPSyhqPqXzjBVDHjhTKsj+DX0Rw0x5ZdQQECyBiKOW2IsGNAjMszpNq7NeLsfMub4cgWWJj/76dQ/Y7uy0Ah7EKbqmg2xuSAMVe9AS5ND55VS2lDfKxyzSyL3mCReH1FuRWq6Ra2yqySkWEfxTcvdN4biKVr88U8NRb87fLKzR5FyRn4JdbtbHvgmUShGia8rh3zD9PEa5nAqXUDey4GYJsDxU9VAaVbAqCVQUyeHZakVN1SBPEZroZ9Wg6gKVzHObUSnc1uNpMhusUy3y5MMyY81uEr4+osjriSfKwTiz74reRH1XPXqfJWsj+w/RNhp/BRKHK9AEnlZwOaLCOc46VsRgznY8kdqY7hoezn2kEeIeHf78vu1mjnygdjiyxhfXImLfYRtWswDK7+Pbmxn5fkFeQrZgGKpIwkEiRZjY0Z+UJsJlzL0Z4T5WcfUqy1vDQx4vWdVIFKOV8kCMOTGKjqcqMjQ24LQZ37YUV0HDS4JwqA4dD01S80DbuaUcGBNlK/3Q15RLn6ZG9DPy2Ya8FCHAUTogMTi/FFQWI918RPLD8HLjym8U5WqnDxqljclMnL9Pr13em/o1YyHKEET8BRI9jAUSEgpY4LIx/DFonMKRpXlMhFlYo/s8G+WqiuY4mqOVAz3Cfalva7g9+Oh6sKtpGRUY6doN0sJkoIF5ffkomsSorkbbBCtRlFOsuZCkeIGCRUa+5+22FliqUCpaWnbE1wQa14os+hawXHypwREvVSHsQxAOHhFB3NDhiFY0tZHjZ5dxdfNQKKhhKhsqsdJOqnmeaA2XfRslagvoQcGKOgsd+a0S+kicMPKGK4RfH7Rylf0rN0YeDLAgscKcqAc6hAcEqmv4s0XtoIkADbpClc1IEhaSjHBHmgAbk7J8cmh55SenfGeelV0Np4xwmccCmpzyAMJLE10j19qqV+/NpImNW9uwjW4ruZQXrUEGfm5hmU67iRwt4K1VI+KA1tkfi3n0eh5cGeKE/txkAmiEPVPaEcg018YQPkiUUZu3uV5fhqM8eQP46IZrOO1baSJGJAZX/aDrxpNuGdaREOOh9AeOeAmSuODbYaZS8DXlJm6EqFRrHlNLXvmnSjMenrxYYfDskWJMjrmMuGUmF2obPk7fDmX6diTR3/+KHfakO8QpcmRWyauhHO2Qp63wqimFlwcrUt+3zTxmr4tpbfQGmiBYPgdersTDK+pRdHOhgX+IooQ0Uet3Hbg6zdRwHrnzGSiqgSdWnLLCbTPbmkB7EmhCv357xHNmT7L881ZEnsjwNjSx40lFHmjCYny3dvQlVSrz0ISar4FsEqg0US4pNHYKS+77rzMn/Vmtw9ek9/fweffTgoQdVehh7yzSpo10Nerv7XuPjyI2YrbERnwfvxXJwaKGcX1zlCj1Y7ZYZJh3cvoC7TdP5Tdq3279EC9wGAs8tgBoVEFLdC+TzL4oLiWojagIq+/ie46PhcF8DENdIy453YwWQfIsyrhFxBmpLVbpWJr4e2mRi6vQcf9m3z8VX680nvDTNW0b0vvZvJlTj0m48HL1K0sg89bkNKxQ5DFtPosysSk0hjDSwun+YPW3hoC4NXz8nqQE1/uCh8euHKXD0VU0TsgjQvA9uwlF2y1d6Rr57adFNo5o9nJ0lF0I4d/P5glFTrEvrSgVcn7+6z4E4VAQEcQNXbbQa1XJYG+EnS7pI3aYJ0di0AAkVLWiqzmh4RpfnSZPMXb1CXo9V4ygNBMu6cfhlvaqlgHVpLdDWb21SIVnYzoSTvLLMTcGxaze8oS+oeXInx6IuBoYIpd0/pzeNeaKjjFppAG6UZbQ8lbwV24eOVyRSxlXosFVNfP7VNG+iEa5bBhqu4oqCt3msx6i74lNc+0UpCxadY6hFQ2D5dagg8I0s+qHz0H0ElrVsSJOjDK73D5oYhtkIY/ORZ7XEEH6/FF/mr4ARjTN7pSIqzD8WexUI9WBhI90ulZI/OJBcB4TQS4R6+bhYLVbjoJyuyby+E6sIVGFI1MoBcfHK2kUgp5fWVwjxL6V+Z5c4YfFJkOk5Bx1TmmzvVw2bIlo3hm0rg/Ok1d07alW9YF/vsi9AnIEFq44Yk+guC/17st0z/3m1TgS7Fj4MLxLLLPI7OphkSuK2k2QIgK8qZZJKUVp8Cqh4VfCprkU7eHsuy6lFyWTKMf9mJXeFOC+h/pOFRcd8RqMmmMawBqCE5lUcwlvX/MmriubbG7roUmekXpgRYepLVR5je+ZFJUCZfYjwSTyK8mOjtg2fGmx7gauHD3Iq9sU8YOK5mqsd8rciPcco1KMXfWLJq0hEpi8dJ/17qbUGJ58WlGibGpsrIhT2XDnb16Fpl/5/dWshZFT7yyfGo42M8onWyv/fL25mWIaCxJWNKy/PqXFkWcOR8TZ6Q8euqY5kpKjDVgsypMmQv1nftWLXCME6ZrmSECjUpm1EMVih1HdhMdAAWuBg6qtcQQvC/VGiptdqYfGWuyvYdwvrOgsQ2QjocBDaVwcCWJP9A3/sRaNIxpB++l3m1BSfGQB2k04siNQSaTjFEHVu7PxmmAmfYf7aOGCtvFY97wCCWTs/ZJkLpAEEygiK5VSp2nR0EtV5JzX/HvPCOrqMAf2uS096Gvlv0ZyuIwpBeFAiAjihi476Isxcu7dVhpsuJPmijIGtsk8r/zTpIBD7+0BgLGSxCsvtFripcGMsRqQTwCaYYrJK9h6f1Re1Ci7ScdmpAVY+ZYhzqfk6g0cCUIrTxof5faHeIWGBs7eurVcHeP9vFpAg5YAD4LtEp7s+0B14AMU6mycJ6sMLKcq8SCIJ72KV8r1a6gjN3JIXVJ4QtZAM45XuongovBKXNBSzHkQEr2a7qx0zvKYvlI0ieGpQecgT06zCzy48lE4rl32M8j50ryaSCvFPMnjgZbzXEp4ou+hyJQgiXq8MuwcW3bViJN4I2ooP/PNfFa5crexVnuMySH7DFAIr3/zLlfhhVMWeGDhrUZ+DFZKmaIJgzGQp3PuAV1DnIqi/6wcvo6jVtNzXA2Lwv2dv2mllNPdPL/PNSJBcsQPtcLqMJuHB79eEn15wmkbD3NqCYsDfsoR5xKi7G+SJw2IVs59HC3BE3jHw4FKSNOk1fcXVS3hSivWYNBH3zV7Q6AB9T1WG+Tj9PJqPa/6Ut9pY/SfLtU32PhR419BUSo0aefvmUu65qmkRP2dESlGK7gh69x65yyOKLhxGLlvr2VwTdeLfxdNTNjsmIQ0jlRznmPR0hK8XKMI2US3WeOIkQOGJ5Y90efJOVd24tD5pcvc+xFqgz7ydQGXEM2napiPyvfmt8DBQqlblQwWTvJEK1B/51aG1Y7Wc42spKgho5qIZTjKIoAtkOQeizVuMnxqeBzI4wmOVrQ9Qeh+zBFZfC/IUw6a2iEfD58bIxLRulaCBagOk5+BrFF9kA1wuUS7dU0bHmdsnE/7yhNRxlGmtFhhiE3stbUisthmtzVOczE8+/RnyPJEFL6DlalUOEdscuUfTXXynyFBhSfmIfrOne0ahvvlEInwXMHMa4n4Oabb3mDZigQRhOJERBAXnImrJ8r09MhH+HAtrUVhgB4ua0jRBZrgyrURb+xGmollJscpD3bOfe570gqqz9rGEBt4QMVhndYKkeEAz2aTvGLIDt12yCyvbrM7PYXM2qklwVY04aEbo5cHdGy2Za2C8KpW9hHhwaGf8vKVlYIDKlPopbKZXs6bpXOmaKDovE8SrfiRCMJh4D7bMJTehyfAXD2DJwv2SneIJoo8OPG3aOKemkIDF7cQYDuqAjRw4/0ZJfXcSgzb/is0oODIC3sQ6CNRilfvDONeLjHIZrQazvfmATIJcfaAyk8GpBwBxCksRn62vfrG++KQaA51tq5Jt7KsfpdwZNu3Ikjt09cschi2UeHBiYyhiTqn8JCpJVe1sFffoteSSMgri3TM9jWtlq6KWEHLGeA6aSj7B5CenGiaFo1co9hchQ/r+opatjFiP8aeGCzIqCXuppjBheHvyduyccSVaedvUPuk/ptNPkPzaQLbzoyQ8G7eGTGtjgfydvSJUVqRBJpQVTLqY/FsXT7Gx9XC/bqfKvoE2HjTinDz7qbSzuSVZfg+cYSjhvpfTilSG6hSml06nXx+WAD1b0l2TY3k75fTi9j/xjifdrUiFgYp+tKIsrHSdtjMkw2S/SqywXSesp8kTIZYMKRrgCscOawm4172ouHrk/2M7BKeLERRdJdRCckqFc6LIh6a5Pk5KoIWaLjilG2uywbiLADYwokRbeAiFLCRtn1u3cQaoyKO5RfmNg7k/j9Ei0ce+/ukVFGuyMYpNNz32te+IfDTZzaiDfKJVObP4+MS0Pa9iK4PNjV2E57cDP0deMGOFvk8u03BL8SeHlSNyvBlo3G0bYLPYw3jnkN+SDGW8b6x4OPiqRXiKln2fZ6uA0XeZZ7NFIFkpe1w1I+XKpKxGGr0KZr1/147qoyJIE7/IJEgQvEgIsiBiI2OXEe9vhkmy0ZcIHM9jh7hMHZ7gO4j8zReiSuwpwdNRo0BDRkAhqww/hDdmOzBQaSJqbNvCo3lyBJO5TDeg0Iv87yPZQKY+1msFVgvp+1QqLWxakrREnbesOFxkpodOQXJPgZKEeCwzNCS7REFHi8ZnGmi08IDghBH+Wx3N0Zl8ahAuEUZOSHlcZHNw6idOVAovZ8qa+QnjliLo5HzynnVmtKWNF7y7mDxy6i+YTmweygVLUSTVi9VcjCmK1a7NSZptNLLKVFc4cl5jnxdPORpYaxm8qqUXRWCBBoe0HAlizwVn3iAShMJt/ByO99cubUJrixiV0/i1I5KNNhrHZ6k+Tn1zRJwWQgzfDdoMhm0K+fwil8iiWw7ktGhvhcNqwWRFOcFtv7bR3DVGiuKiwn1CYc6R6+y+h5qQxyV4N9bLeJqKE9KHCiCRh1BkSxbk11LMwcpgsfHkUoUUZfRJ7xKGfOXuWKY1TH8HXiov4taGm6DgSZWdRiadKZ3CIuzccspNaUGTaqsaCIPXZ9+EjQCDUj8rG8Zm1KZxyCVRsZf4ZQLb+tmkaMtdFdoVRyKmLaz2SqdnhAbUdBX+YWuuxhZ8t0vu2pYIIuaa34f2Z3DxxmV7IkovhkGndZkSC2lyS1d+4bxsWUYquJJUN9OQhpHBKRaVdxoDMEGkX7ySeDoRTvcn/2IjPsS+5vYE1CuYkOpLgESfTn9Q9WwSoq73P+CXKUpH4+1PNETOZ+FxTPLiDO42MU3iSfTPO5zBCJaoGDhnaMt6HeOQnBeQ/5lpuE1mTXb0ScuRqeGZ9uajQesyGOLOPmZwRrfLy1C5PGPcRHFjLK8PJ7gqn5W9KqHREc21zWEKDLttT2Y/HbJ+H8JUcRnIN68f0Vt33fgVFUrgsg4Zrp/Kkpx40gY1d6lf3Ou6Z0Rxdig7cX277XDlaTKBPrzeP7jZxJPEOEQERHEBV/lSvDpErmcokCTczscOKsuqc70mmhyPA9QFQL/Jhc/DiusMcgDCFbtNXwDsGu0R1htCR1hhmX619FNm2+alMLClRMcttNkhEpTGiHpfNO3fUdoAqXI2M4wobI6ec4j5pBZzlfniAJ7VcuY9JHqDoq8UM3MSA4PlV/klAsvR+bQIDxIudZ2jraPbszsY8JChfN3o1oRVyON1WU6ZjtqwPCioZsxp2dxHrlzPJSD6qHKHJ54Mo2lwZXzHJfK5EExhfUbPg1sbhihCkuk9uynVSCN4tVqmgArWn3Kz8zOWGKh9+fXeBZbIgavEJHwwaIaCxp5YA8I9pXhVSUrbNkwn1y/MWIKkhEBZq0WGdFBHE1EIbtszOrsjyYfxqB0c7jdBJvUixgVYw9EPVyilqoK2ZEgRgQNR4v5fPjg6jhUS9qHHXviMPzR/ftWVn60f0/liOfA9zdFmFglwRWXiua0Hy4fzIICiaR2tJeXJ7OUumWkhzkGeDR5YXNbMh6O2UZCQ3szustPaVzsf8OpNZwWYk9G4zhNktPyssLXd3Yjs1Qp46UV5VBN8mDKMidZHNLtI18bUPqHcc+0Kp1Frc6IrLJy321FJXIVMxabvGzoa6WWGD4/dK14/qa+tAcZy1KapXM4W6mPYVNIEunsVB8jDYkMffk65NLKhieK5e/BETSeVe4l7xmjDDff5ymlir2ANH4Sy430R45mtVOF2M+GFzvoOixIqlV+Exy7ApcRqUP9rTeWojxJRAlaPiaGpwa3DZcIERujH+H7ihGla6WOGRXJqI/hxRrbz4ivF5exXr73vwKQJ7KUFiKC6zdErohDn8VjLbB4PS5iBYtIVmomRwMZaURrKfqEruk8ZuZswEr9bYijq63qaLZZbqT7Cosz7KmS33k3/F5osSZPqiiNo9nsGezJxccZzATMTGpBEA4REUHc0IKDL8ZYnTAGTXut2vE0iPGyWEKO2758co3ZAE41DN9YPWySymX87OgLVtATyeyRPQ/sQT0b6rEnB4eaz/jHPE4O+axCpSHJrIsNLqPZv0BTmSYMPCCjAW1WY3PCE7UtfA6CtMLkpUEHh07aFRZC5Ovi5ZxNy0yOCVIYuIcN7Ci/mid8oSpWPnE0HXMz+j45ekWZE1g2yDKED2MAQat/1s3cMHCllXvOD7dLFxorSbQaaKwUN6eKIfrzcDlkEpwCq2hiS5OfkF06r1rViOZhbtEOdqitUYqQVknBTvnWKr6HSxO7hLLYYc6eupSGtY5CgylNhj2DclM3IoQnG0a3HVtEjGRxtqMoMq+H3oeiJcyy1+ZklEVL5a0YOY2MSuzaURkBro6yi9JZKLzeNgzlSCnDfJkur6B1TXt/mxP+g0t16yodOV2R7h9yBotWqDZXFfB0Cg+WFQsfbEKsYV8SEhMNwZK9LaxVRkUTmxyn/v3HHO5Tsq3P6ZuxMKIIbRhZ0sDdn2y1IcvMOvdxLiVsTYp8LWkFk9JRjJVdGoRHrTMn7SoxPuI5iF5BkyJrou/lNsEVesg8mtug7VmQ1iLcJ8Ruock0nSf2t3LgSCu+Txmlrc3IHCMlh9qtZ2dsxBLDsKMn61KaJN3PDZNVmkDv/wyByH0nTXKCFHlg+EFZK7+huS59nBWJaHzXvKjAizpWKh1j9Gs06Qxt3BxxkplnO64iwxF+PBm1zpOiFX6eaHPFKruENt/nDB8vqvbjoRQ/v50KQSIEi9MhEo19VnQXV1RjYZHFIqOy2DKrvDeV7uZ0MaOCimV2HOTqZtT3BBuGJ9B++vy2xwtHDLpFFwfXbnBN2+HUGCMyhsUuLg9r+62wgEyCtifDWiSjVFMjjYj6IY7q8FBKs/M3lRsP1SCvDjIehtXus7UZd85nq0D3DDo2NzPZPKIWj6H4O2P/O6uPNOYSbI5rVQjKiXAOKPe0/FKJpMMIxYiIIC7ogYfHEzLD1XlAZaUy8E0/xKUMKT+YBwl5JlwcBs+rwRw5YQ0AsHBFxDzRaM6p5gmGDQkKHi5Dl18pYJ6oNq0T8XEfCQiBOmbIq3/H3siDM1LjjUGoVQXFTyXI2Omfvw8ONXdeXzt8brzJqZFvOHbu905a2aNUAkUTaF7tid5r5YlyeDGvNFBYpW3gyquebMDKA1pe5fVnmSu4mR3C5yZaVY8YiWH7VvCglMOJ/bxqzWZ81mCP02u89cngkap/GIaOzmCT2jeF0HIUQoBMyTQeCoVXnAdOlX+MSkjW98mlIRWv0NCCvi0qZdMx+OJJ1GHBkCZpwVpm+WEfRVpxiVtPnfB3E6SqGjaKq//8OS+yIa/VJ3A5Y2OSwX4zFvwdgAbPPDw1+i7beJjfhwfC3DZWWWIom/hRZIlKiIHKUUH0ec6ZLC8yo3RY+AjNXhBxsG8n+BkrizQQDlK7VZWpTPMqK/ed0oOMVB8yzbVTNkArmwESRv0kCHA0FleScl5D6UlR26gfYnHcDn3PyR3Xx9aCyiyTdwp7BrDRsB2FltmQJnaU4ue3zAGNamcLyC+FVuE9dWq6VoyKyUl72v+Bwq/hz2at2LqZebJxpY8iMW3vLY4MYkEhRIKb12udG/reOP3NuAZc/LnyVFdxKWFtT7K81HcYE1CKjnNLD3Nez5NJjiSkEp42RpvkcrUkABjV8myoUomrealV4t2O3MqF00dsbyFuH9T3GBWOOJXBTgXkz0YLUVx6No8niEtKDhv6qs6tXBeSvI3CbcVDk2ND8LTvXxxdyxXEttCknybqxj3aFmuo73Ub9znH45KCozjNg373kkePxp+QEPF8MnaqkS08R8KznLzPrO+Tx1Q+TgGtTYt3DcxoIseMO2d/XA2SiwpYYxjjPTnCkMYWhkeMbYJPwh6nsiMt4Cpu56S1eYMZwNxvUFZQoRDUf0yHkRK5wqEiIogLenKhfH4jF5OFBttJ28jNZ6NBilYIcSqHZZ5m5GlymS3arzFZ0bvgFb9NlO9Nq6SGY7jVqXLpO14RcRsQ2hNVzxoyhGJTL5oYKpqgOLBqzp4kbCRGJdg0Xg4nJbGDy0TC63NfBaGwfDZSM9zLeWJsK/WU8xmiVVIvhTarZWsL5MbO34dRgjSfQbGRa82DBuv7jEqhyBiuisDinVWth/fnoXQrwxzXCl3ncsIceeCZT8dPq0iehtaKH0UaGdcX+e/kydOlgSyHLfuCtG/6noNWxAubmQVpgM8pRHaUTJTL5J7NRz1smsuGsRpe0aXULU8KDZYrWDnNdE3xipeXw655MkumhXZqCUeieGjSyyWjnX2TCOGjyBJOk2ERJHh0R/NzUlUhY5WOvueszmZJ1Zg1uyJPevek5k58dRh5TsqZ104FJGHPQ+JGiI0rLZ8j9sYJUCSDh8U7thzix63P4+plY034uF+JpvZglM7lFUeKBNJEccUmXh3n8GwyWXWeo/QHFsWMko/cj1iTOkUTkRgWHtjg0qp85I8LR5tldwuvpvoXrY14zvKUsObJFImRHorcy2MYyvciisrLz0eLS6dylSduNywC2X2y4a/hkjJhGwdzSqqiSECjUtjW7a4iiOFPQcfvofRDnxXdxmV1OSqCRVMfTYDttAJuN2DTd4qKCC0x73G+WjUjp/SSuGFUrbEiSYwFF2p3XAY8j0cZRzKyqMKTY2o39hjKy1U6KBLCLU0mj5BFE2Bun5wCY48tMiqTR1iF6IiRViHu4532Gf5+fXwPZzGSPHdsRxA/iyLcVqjSFxs/azxkSsywIT6LDna1OkMQoLEOt0H2ZnIoQFE5IyXKEmP9vuqRS+lSdDaL5jZGZSpe7GgeHof72f8vnwhW9ojhBRoHjopzWTgwqsbQcYfKWiSIIBQjHpWfg1I5JCUlBUlJSeiHYfB7ogp083Oeo4FCiBVouuEYKRsUVppnQs77oiolHit/kgc6xiCMBxr8HhTS7xwPl2ZkscMoUWiu9gQrxEYMkQ81qBl5Am4bSnEUAK1082s4FNdeDfVmU+g6VyvgiAZrgM3pC0a1A/Y3sfLNORw1yCkC68h4ki8d62bMkwSj2oKL+7iNW3viSjV8LvNMetn3gUQQe/LiOlgl0SBPyccCYIQWc4lHC55IcHUBtLLKw81ffmB3fhbYrEmBUZaPo2k4nSefEoFuE103M75IVXEiCqb29cFVmnilOp9Bues5YJGMJghcElfjYe8QWv3iMHLD/8C6PjldzK2tcdpTnkmKsZobhKrwLPakB5EU60Vw4akRQ+cDDSmiadrfBeqjeQJrCC+Z2RHNcDmtMY+RJFdooO8wVKOSe+QAiduGaSBNntggO7/vmlPCMhqZq74hMo/2cX+ZTu9D/a09EeFKIz72eqLUztAyM4og1KtD5LS+NRRtSFEEeSpRrCS/Eq5EQZMsW1wwDHp54YGEak+WFQ9kCbq5r6H0By4Da0eHGQI99SNcTcVjrU6ziM6isY/8XtyqQjnbkcjHBqzc37Owa5fa5POWXY9SBHZS1THLhytI6Xdc3ponyvmNR/j64uvGKH1L92U7IilEaUOuvlf2RNflnmUYeVr+HEa5by4/v2Gze9QuRZmwOGx8flqg4bQrZ3/cl9K5NSLVLN8mDwnvIUobYg8NY+HCigRRLu3TMCm1ozJYdCUROrSB7n88TuGqbfo1nBbHqYRcPpgrAlkRZdlJ4dfHLFofMXLPGOc47TY64n3Jv32vq6cHL1ZwH5VdJ9yX+/dkuEcNk18JLxCxmbcd9Wt44G2miFFqN7ww6Dz3r/gSCGZiwspnsWfPHlSsaBndl8K51rFxZ8HvycfMugAEVBYmpn9a6s+JcPiRSBAXfBUS4PNEI9iObqA06bZX8VlgMMwOeTWYBRErN5VXOo3JA+e5simZ7iR3RM7p5VBp9gzwNjDDFRXd6BkP54JaaQm8xMAdu4cH682buOa2qiUrI+bIezkf2Mrz9FOEA09YjPxiXq2yy/rSAI99UXjVlXNunf3RaouHJhKGfwEbfFqRPYYQU0A3b2OFg0OyyZyPyyTbJm+MMdCwBo6MahmekHvpOAOUe553594DunLnJ3ywvwfngRtl+Kz3N7xD+Pqgc+YmGjjHw4NdwqgGYpf4o3NotDWe0PM2+axAGykslMZlr8C6YZS1Tc6nfDGn6bEQRO0+mI/Rn+EzQL40RsivNRnlaiCe1VapaRfxzQ0tDixICGJzMlC7kkJH2yAw5xg2UgUt42CCkScV+ilOm+GIGZ4gsP+AXaaSryMWbiiMPg9ctYs+CxtpRy9cF9EvwPkMLNbQZJr7lNilW9wFJp6Acr9KA3n7PLGZtUqiexmbjFp+K76/lkSePPG9hEPyeRJgCR98DnyUOqYrBzGhKnQPJWNqL6Uy2iKjqhnZ3JwrVvEEkgV4B/rbE1ARq+hwKkmecrXkmxTs0jbyBNQWJEiUcaWHFZ1F7OtQM6KhrWfqMte0Ag+VavayCEPRAYqMVZ3jjIuJOLlnEcJH92bbu4txM4LOFzIo9lOUC0/a7fuSYaJO15eHyl4bFemstBUvCVnBimSAS/dvw//H8SWjVNOe4e8tSGJufmV5jaolJI6wIJ/vOXNJ7cj3XsQLJHz/o+8zT7Qe+7J0qxfRODnPokxiWHSMWUpRdTQO9pG/hx05599NKVHUXxhl1Lkf1Z9745aI7Y4rcPGCE5uk223IEDl5saE5mX/r7UikNPZFIozhF0NjkDLnCaKj4zxSIlcoHkQEcUGvzilPMM8NLBe6keW5AdCNwSjX6j73MDBugFwH3lLaXcvaWmH9bhhVGXiSSANnvz2IpOcUhfiFWFCYSWURW5lh8ByyyatVikPa7QmwW9hxQSMsONeYJvBs3plnpZpXFmnfildYKLTZXrE1JpOUimCsAFsrTHxueYXGGKDy8VvihqpVLeLA2UifsMoHY0E43NvTxDRAdVtV8sTGRvw+eGKjaGXXrpjBq3HGChFFf/itKBeetPFk0jAfo/YcIgNe57nt4clLgH1ISLA0Ih+sEHUjeoOFTYqisEsH8sqcW4WBPJWMWGRjAZTLRLqEc9vGuYZYZK+iu2AMHF1EPjvdzLebfALaNYto6swpBrZvBVfdclZNV+jvWhmhwoZZp4aihvizGYKMZbrH5XNDVCo7s1VYSIudEV6RD3Q1owC8v4f7q1DfTrm/R2+m6Bm7GpZLtJh/X3gikt413I/FLTVXKQNtSKSkMOxAYnjCGZVsRhyFyJjaw+W9OQy8V6eIfjPOIffuHDFfnskTbUjt0FjpZp+DevSeVoncjM507U/4K6KYGbJL+fK92cU7JLuFKfxHbUmJmIqmqD1l9Aj3Y9G7rVL2uyKHyweqcRSeOWZQLcP9alpdqqKTHT7mWJBHgOV/wwKHYeJL/lYBa1LFUU/Re2hiSOfGWMix+xcSTTlKxUhB2mIuwrBXkJHaYqRfZLumJbD/GpeI5T7SNrrlyBT2neD3N6JPLKGbRXBvnbD4pmJ8rtEG3hVUnpruXyzIh2pb6bUE+7wZUWxcstlafPJRxSMjKo/6aEMod4lCzCPI0yKE7cli3DPoe3MTtI3UJGvhwEfvE6JjtqNPjFRRWkALLQmPwbzNG7uakbMvl1oU/m5DLananVXJL0jVsQI8NmkZbnfeTErPovuFxr9oc0RPJ/4OfWSo7xw3nVtDzN1FonVNS6xptf97CwYygMllxxNkf9/9X0vkSkKDcGiICOKCnhB6fDHw7tobccWPc7qd7ddujhwqTTfZUN8jIpfac1acyOme89LTyAPDmgh42TmfBjec8uGlG7jHKm0JWv3iyZeRn2w5VPPKvy+TwhL/If+AjpTTza7cGqssbO52JCrZZfDcJpCsuvvT3fPyg8d0yf09hkxX1RZKbbH9A8gvxc03g1c6jIodGjrv7JPg47xhy1yXRRUjkoHd5Pk7s1ags6qH/44hUYdXtI2UAGvSxrm6PLhU1koYVzgwysVyJSVerbLDRzlfmlM2tie7D7Rcok/yhPD+S8gyYuNbrOFvQfn3fivSyniOfBKM8ocuQmQePx6awBkrPFZqinEz52uPjHYNUcpO4+LJAw9K2XvFSuHhtDiONDL8TlgUtFYSufxhRlU2dSbBLs3sL2Myq0VMi+NKTloIyWkHPDF3tqvZ5IBpHgEKp3aOYQ+lrcSHjyduHU0A6frm1DtbNA1khZ/LqB++VmO2Wv0dX+Mc1cH9QxSF4ZMxqx3xwulNqgpdd7avDE3UOX2RJ5lZCXStkzi0/4Hw8WQN7Zb7e3Qyfe+8Sqq3ax3ub7IqUZWKeBLC6FR4s83Ig7TqdDwX9cz9PWqf++DWS5EYcVvC33t6s3CfEL/RvH9x6lDsnPDEMkQl0uPWJkeOqrRWng3TWjLEDVSv6JoSFf/ljMiLEAynqToTPbr2OAWFomxsARaUxhRoH54AeoMUocC+NrYnFqVgGmkmZHhqmMZbuPkksHBvpO7ZkXxc4Yf9oOxypC6Gm4qMKI1zY/WXXC0mtIyOuQOJfEtWF8ijS1EkCqfz5KmCw4sdfF/jsqkzTSGMF5w8ZDrOkVa8eGVH9vAxuwryfM+2UBUpMrZuuK34toXvZUGKuLHHBjxu4tLWgUZWW+cxEFVO87ZpFnGBx15EUDPC14eXo9WoL/dkWqIWpYr66fOE/vWjcrZJpkhlir5x/m5cL2JfzIIIp5zaAgeXsGYR38dFBPS95d9KSL6Qu0mrIAgHh4ggLuhwRv3DBnR8A/VYVRlY+AjRRN+4AW6IXM3E2Y7Ny6g+uaIJLK+O5IcvJrxaE6RBS0ExDK34Jqv3tybyKoCPU23oJs05uzY8GVNbyaiQK6tYzui+5PA5CM2lEGyqGmOnQngoR52N7ngAY4fJ+vx006bUGF4VMyaTtgcFpw8cgr8GR4x4qQpAkCajXMJOE7WDokwoH9XDobl0w7UH9Z7V4WMOtqCoEGuVkSfXhgcCRfAYvhGWyM+VUoycbtqvMYDRf2/aEfEcsqFikFbNYacK0WDTR+laRoUEXqGzB/k0AeXXs5me3YY8VAqYJw9GKoBVSCJE6WKcM88huOxTYJu5GsILV3IwVuIyXAeBHNHEJagNzyJr8qIqhd8z6pfwKr5xXLSCnGeVbHW4fXtdqlkZpa31MewIH1t2TZrIVI2PmEbnbFeNBuWUJpjckfq7DIruInHCOYaaJNbQc7zSntzeXL3ztiIvl2gSOzjYj8a0GVb54eyE8Ovjt1OpVLq8lM/sL1VjijbIJOGlYbgfzapAQmSGNQxgEd4f/iOtRni/FaPMyKLsRF/E96ywMHwv2HlUWNyuuMocyGfR6yuupElBHJVb/9uM9lNkTJ1NZpMVVuxxXayIXUmLElyKnvq+tG7hCVf8AnNil/Hvaqyzr+VbI0+MaCKj8e6mvpgFTPagIKNeI53WSdWM7FXkpUkvGyraUWRx02iBgvat6JpU5GtgVy2xw/9zj9kajxgTb4r45Ao/Kp80H8P7JCUt4kq5f1uyq3BiCPLU33Fqqz3ucvOB4v6BK+I4r6FoSsPQl0RrjhzMMXfOPTa3RZ2adC/NL32QhBvj/p0VHdHIU+PbGNl3whBEuD1pOEqSIgSNhZwaZN7d2hTiQouWR46aovPnsyJ7PLWqR/TNc02vte4XxtiExh3s5ZbV3Fxki5pH/Qq1FS8LZjyGssssU3lqP18D/NmsMa3heUOv8ak6rum1OeNaVcbSYbRZtPqP6TBibSkcKmXKGDUQCOD+++/Hhx9+iC1btqB27dq46KKLMGrUKHjzKVsXyaynf9Mb4PfFIOiS58+rybbrOw9ieFLh5vlgTyQ8lItvd/LGa6jSCYeUcySHsfpoTZqNUqN0x/DQiriiPN88Kj6H27uYsdqGbzyxNIwHOefSeg2LIF5aFeNwXMXl8ezcVDpmPs9s/sZeIfs3VBF/51QjY6XdEkG42s6hGIseChy9YUdCFATDV8WohmLmF/Ngk6MI+KZtpCjYK0QUOcAVDozqE1Z6kzG5ZzM6GrTwRN8okWgN2I3UNf6e7YgVSi3hQRgPikPk76Ham9dAsEJ4gBq9ZW/E3HG7JCqXzOUKA5wKwX1HJkVeOMdDZVjZs4CjMmx49Y09AzgijfFnmCtpgdjw95GV5IsoFNgV8GIodzsQR6k2cV6s/+EWbN6tULuyBw0HPbn/uCh1wN53IM4TcQLOgoY9oY9KowPiz0/nLKOKKQ7wvuO2Wek9/5JV0Zx0c/QEfzchCrc3fJYockLDY0MOyY7aSyXBKVpw/9/hY0tvHJ50R+/KjChYZpwQjpTTxJDAxG0jq1L4mgqRoKNJWE6lOg1/jr0R06jsiLTQnPDxeDvTZJiiHe1Uo+DycB/ho8g3nnR69pqTJ7NyGl1rFAnipYk2GwVrsruGhQP/tEURhUU7LcCYAHEfQ/cIw7CTH9f7rhe+b3u37o54z+ZoQ/szGOl7FFVhpEnaBpMU1cf3bNW+WUQ/DPs1xrGwb1GLcDSV105l4OosFImZ30KKm5dKnoiRgzS8dkvBzTOOY0GA/GY8qRS9Y0e/UjSPIUjQ58yTgso+NS6pv/walWqeWy9FqRieaTw+5GqBjlizNbInST7m08bxuJh5c8RJcLWZWsmRlcZ55nEwjU2y65sRTIbZL11Hiq9B61ZoGN9v3RM57YgWJu10czdzde7jvBTlqsmiFJyof1ZHXgAkXxvnGP5N49UmoL/u+6jUm4DmzLWO8Z2apwjFwaJ9UiYFvyySc/LII4/ghx9+wLx58xAdHY3kCGblI0eOxNSpU7FgwQK0bt3a2dZm/vz5uPbaazFz5kxUqVIFV155Je655x5zoV047JSpSJDHH38cY8eOxbvvvou2bdvir7/+wsUXX+xcaLqRHhS6ow35jFVfo9ScFcbu5ckUrQrx6kaAVj7YgX//DhCxTCVPxGw1meGVdxZEjInpHnPC5KEbowGvDFsDGxZ/OL0HVN5NVbYMJl1eb5TBo7DjPINIiv7gCQsb6Hlo4G9jVPOoRSUOab+28GKsSpGnh5FTzHmyG82BGt/AjZxmqvbDuft2+CfnqLMI4XfLJbXy7zlawDg3VllCQ7yh1UPulv2W4Mc3Zx64chk4Lhnsa2T5rdBAnH0zeLDNwpfzPjP+iRyCzNFZdFzKqmrkVeYkIVIaGhvWOVSitDIqrwoScbyNKKSdU+f0XKZa+LuO3h4Oz/alhK/jkGVu7EuueGADV/pu4+abK5mcR23kS3M6i20MxxMeEtKM80HHbzvdx5N4Fsf7JjE2u4NpcOrbR5N4mlw74kLOJa6ASn/vjHh9cipBdkOqoOXm4WQJD9HLt0S+Bmjg7G1tpSuwBxDva0c4/STa8tfg1XEfV5Ug/xm+l5jSHRBMiosYkRXqF+57/as2u06aYzftjezP0SncvyXMNScygXrVIpoYxtB+PUvNxQHViFIuNofbR3YTSrVqSBE3a8z+MtAn7BfiX0aiKS/nskeO3l/38D00SFVgQiTKKYoMcp5rTvn/dJuNnU8muHRfDDS2jGrJF8ZLwouHIjkCDUxvIR/5n3AlHvah4olyoIEp4kdx6iylQGZXC4s4UdQG83qJRTZi9nMFk/WmUM3RasbCB/XD7omA1j2cqyf5Ik8sba8H9ijz8+Tc8i7hBQbbTLQg2KmzbkKU8RrbV+tfvJxKyP5UVjSS4oosdG/NT3jxUX/hZhqbnxmqJ5XGGnw/p3bCoof9nsZ3WJ1SNsg4WVmRlGyw7K9JQkE+aVh8bwlQFReOSObzH2Wv4dL3FmwUHoP59pAhr9VO/LwQweMjFtVc0rscaFHESO8lzx54zTFU9FqKSGtK9xk7ZZ3IWcT0BDMBK2hHKDqysrJwxhlnoGfPnnjzzTcjbqNjCS655BLMmDED//wT7iNZ8BkwYACOOeYYzJo1C8uWLXMW6BMSEnDzzTfL11eMlCkRZNq0aRg2bBiGDBni/N2oUSN8/PHHjhhysKj4GChfjJG/z51vfp23gcsqhtda1eIJsVuIfZ6qDLTyjYV7Ips48vbWTdJD4ZshDt1jzwXLxd9DgxPPtLCxWYDzZFMSXQUNXq3nHFgj75nLwFrHaajztKrnadwgYmpNHgNRl1QdTllxnnNx5OcUGPZCsGEDN6NUHO3Xztu1c8Ej5TSzOa7XLvdH5ynQJDyg8pPZmFE21dkJnU82KeVICiscWEWTOz59NiPVhj+LXZmFzg0LJ57lNBGxrg8vizrWqmWk/Xq4TLUzcKOBY8WYiGkWeQx5yTgwq0XtiJNh9vbJrmuKC/ErqbxoDYrUouoRedoAQ5PjUJsGEQ0/fZtN4Sa9EflTjAsP3FS38Hm2Yc8cUL40RxMZq3JWJYogexORcMIRZYboYIk10bspEoOuTxYB8kQO0AA1ahtF2ZCoFaJ26uxj8pzw+9MqJYvGxndL0TvOa2gCx/eFYD4r1RnHhs9V7Ga6Dun42YsnUMFsD35abVcknEdvpCpRDc1+gz93FAkSiqMF6DsLWaUY2cNCuRhZ2tXRsJXuf1yZg8Qi36+zc3/PYgFd728vCQX1qb8mDYSNQG3vE0MkI/8YWxzw0PWeXati5Gg9+j0q27yXBo4Mt8PgrPD58NH9w/BxsUyaDR8QXoXfG+47o+yyvhwhR58zilbkuXyx8zeZP3vrk0DVhF6zaqOrSTcv6hS0shObkbKI74Zdec6fTKItRzfRoowdVckG5Jw6bEQuuER75DHzplTfUKNwf+9tYF5f3u0kxPA9mBZ12OeIK/TZbcAQHFNorGffFzh6gyKY/HSfDtYNXzdeazJtiMO8+ER9haexlea4gr73+uH+30sLPgGOJrYqxXF7yGxA9wIvnXNLfON+noVWruDldv4cSIT2cwQSHZuxYKmPrU64/4vZHLl9+qw+0oDGV8Z3wIsIljgfWh6+N3up1HVOGdyIaVT/Rn0GA34gnzoApY2Sng7zwAMPOP+/8847rts8//zzzv/bt2+PKILo7ISMjAxnHzExMWjXrp0jhIwZMwY33XSTRIMUI2VKBDn66KOdSBDduFq0aIG///7bCVF69tlnD3pf2kTUo29wXHKRcmg5xz/PRJvDR8mYzkhzoegCZ9/0e8Al/9GuyuD6/lzyMb9qJJwiQDddDkm0I0F4Qu5lI0nKDQ3y5Mmq8uGh3OUA5XxCbXc36CpIasmasHDksaJ0AuxzQN+NcTPNp9ys4etCoZiGiGKZn4EGpVw+2c2szDk2GugYgpXLCo+fDXjtsOnZiyP6pRhmsHaYKgl7IQoD93I4tdOmKUKC8mOz6lPoPZW3s1fOjIgPGhwEOjWLXHLT8TOoFzkii45NVSMDW7t607awIBH6myqTcLvnihn6bWhAFR2IXJEGdN1F0XHlCT3nCSivbofM1yiKPuHP4JtKK9CUb59NhpSauLXUr3BlJhKobEd9HnBzHraXhV4OR54RLn/pvOaocNSOh/qOjCbhz+xPM0UtrjrCqU4hXbI5vFAY9gCyjOWYYAMqqcqmoHXNgaufKzZtDE8SQ2Rmx9dgnugw9jWhfiBzYHhCH7/Y6p9+npX7a1b/rrm/R3PYNol6UdvMz5ldPdyPRK/cGlkotoJfvDSJTm8XntjEURUDjmbSgj/DK9chqmwSjA+3J89ea8WSI1aI6Lk0WufoOqrOk8dIklIrObXGmFhqaJLEYmqI2pYtl/J9LiqLJrckYmRRBBBlh+3/PMvD5zCzX7i/8K2jFBqeGFope9kU5cGT/uDCcFvzVzOj1oyKKFRSNYPS7WxivI0i+xFxJCMZOvqsSEqjIgxHhZDXlJ0+yO3Ik0IjGrrns6l2lGVqGWgabqt+Oh4+Flt8C1BkDWNUEKOyxDbG56G24SHxMM/npPEVP8dRrl42aLbTV2gxy79yU+QUaSuS0Ygm4Sgs6ofYw8ljL3awZ4y9eJK7L7Mj8fAxkMjJ7dFPvlW2uXxoA1XyI7P+AEVneRZb/ToLrdQPsFCMdFo8swRDL/XxIXqNh9KdM+taleMoKpHhKk9q6aqIYwbn87SnEtALVkUcz/j/MdtAqActSlB6qS+TorCtUts5KdveoLWoVNpxBKr/Wh3mP77+MCzQ9+3b1xFAchg0aBDuvPNOrFmzBo0bm5GywuGjTIkgt99+u5MT1qpVKyfMMBgMOvlc55xzjutrMjMznZ8c9Os1gbR9ejQJcEeUQtUrLHMiVTUh8o0xhSYllLLi5p5uCxe++nST2WPeMAK7KER966bIq7a0ihFcQyvtFiHQinggfD78ZO6oyY6mkPBN5AlC92hFOZYBHbrHx0zKv59TjegGGthrriKFSATwupSeC5AbvF2vPrCXRIRUipipRoKMPVymTjWwkaqrUCcW4jagrElBMg3i0sy8clfovPM59HAkBq3MZkeZHX+Qyy9k0kBtsbs/iCGSZZCnBodK+8yZQGDu/Ijnye8nPwVqGz5LrAmy/8x6Eq/SwyJKln3O6DPwwCtAE8P8boQ+HojT9+b1UbTFH+EJq/1dZ62jkr8twoPYLDYK3m2Z7HHUUo1w/+CjiklZa61r0mW8zoP6IPUpnlQzWiGbfG7MD0MD38rmpFdRSLQvQLnn5OXioUpMmX1N01o/5Z97aLDsTyVvJKqk4WxHc6Ts9pQW4Aki9O+qjv4/K+bf36k92YSa0irjvnDfkemzqmklU4lx8hQJeknYbEJCXkVzEJpaPfy3f0F4gK/2hfvYjNUrXAUirjCwrwpNxkkgskO1fRnhc5udRJPMjLCIklnDfTKsssMTlszNGyNWv0ivbX7OGPIOiaKw7WBj9/TDAB0b59JF1aAJx8pw6pvHjryja1LR95FGZrb+NLMf8rUj82ZF57BXWGxRUV7XCY+PIjayG5OYuZFSW6x2m9ImfG+JoWigbA95KO22UiPJj8ezh/x8SHD0k7F4lj0Bnk/i1Z/hqFZ/fYpwsFbU+dvhtJtsEu5Df+ddsYwk+AX3UTRsPtehn0SywDY6Zvrd8E+wqhphZbjzy+AFBjr+jCWWmSqJIlyBI2NFwQzhFY0NPCTGqkqxkat5aci3iQUWwwx1S/ha89Q0RS2jMFIsta8NtFhA7+/sbzFNoptR2exdVJWI2xOLE/q5ZUsi3te87D1iVULKstpUpPt5cD3dF62+ixfdPNnkqbWHxkrVzbGB4f+ylVKssyhSjEQonx2lyuIwif3pncP37Gg6Z5osFpho3MT9ECgyKLjMErXomgweEb43+lZQUYNEK7JnG3mJcXowLYoErLaOf8cAwdD+7cuKnWMA2aZj8qHu49+0E0aLDiw8FBfao1JnJjA1a9bMfU5EkGJElSE+/vhjVa9ePef/f/75R7333nuqSpUq6p133nF9zX333acvP/mRcyBtQNqAtAFpA9IGpA1IG5A2IG1A2kCJbgPr169XpZn09HRVq1atQjsfFSpUyPOYnt8d6rxv1qxZxmvefvttlZSUlO9n0vvt2LFjnscHDBigrrjiCuOxDRs2OO8zbdq0Qzp/QuFQpiJBbr31Vtxxxx04++yznb/bt2+PtWvX4tFHH8WFF14Y8TU6HEnnZHGuuX5Np06dsH79+lLtviyUXrSiXb9+fWmDgrRDoVwjfaFQ3EgbFEpKG1y3bp3jIVGnjlVAoJQRGxuL1atXO8ajhYGOjLErrbhFgegqLTnzRDfsyI3/Qq1atZyID2bbtm1GRIhQPJQpESQtLS1PKVydFsMmejaRwqVy9qEFEBFBhOJE2qBQEpB2KBQ30gaF4kbaoFDc6GqXZWVeooUQ/XO4qVatmvNzuNCVZe666y5H8NFldjW//PKLI2QVptgiHDxWxezSzYknnphb01mbzXz11VeO++4pp5xS3IcmCIIgCIIgCIIglAJ05M28efOc/7XPpP5d/+yjUtcrVqxwHtPRHunp6bnb5ES5nHvuuc5iuy6Lu2DBAmduOnr0aKkMUwIoU5EgL7zwAu655x5cc801TqiRVtmuvPJK3HvvvcV9aIIgCIIgCIIgCEIpQM8f33333dy/O3feX4J90qRJ6Nevn/P7ZZddht9++y3PNjrdR0d66Oid8ePHY8SIEejatSsqV67sCCBsxSAUD2VKBElMTHTK4R5KSVxGK3b33XdfiXAVFson0gaFkoC0Q6G4kTYoFDfSBoXiRtpg8fDOO+84P/kxefLkA+5He1ROmTKlEI9MKAw82h21UPYkCIIgCIIgCIIgCIJQgilTniCCIAiCIAiCIAiCIAhuiAgiCIIgCIIgCIIgCEK5QEQQQRAEQRAEQRAEQRDKBeVWBHn00Ufh8Xhwww035D6m7VHuv/9+p6pMXFyc4/y7cOFC43WZmZm47rrrnBrTCQkJOOmkk7Bhw4Zi+ARCWWyDuoSWfox/evToYbxO2qBwqOj+zW5ftWrVyn1e+kChJLRD6QeFw8HGjRtx/vnno2rVqoiPj0enTp0we/bs3OelPxSKuw1KXygIRUe5FEFmzZqF1157DR06dDAef+KJJzBmzBi8+OKLzjZ6UDZgwADs3bs3dxs9YdU1nj/55BNMnTrVqRU9dOhQp360IPzXNqg5/vjjsXnz5tyfH3/80Xhe2qDwX2jbtq3RvubPn5/7nPSBQklohxrpB4WiZPfu3TjqqKMQFRWFn376CYsWLcLTTz+NSpUq5W4j/aFQ3G1QI32hIBQRqpyxd+9e1bx5czV+/HjVt29fNXLkSOfxUCikatWqpR577LHcbTMyMlRSUpIaO3as83dycrKKiopSn3zySe42GzduVF6vV/3888/F8GmEstQGNRdeeKEaNmyY62ulDQr/hfvuu0917Ngx4nPSBwoloR1qpB8Uiprbb79dHX300a7PS38oFHcb1EhfKAhFR7mLBBkxYgSGDBmC/v37G4+vXr0aW7ZswcCBA4263H379sWff/7p/K1D1LKzs41tdOpMu3btcrcRhENtg1xzvEaNGmjRogUuv/xybNu2Lfc5aYPCf2X58uVOv9W4cWOcffbZWLVqlfO49IFCSWiHOUg/KBQl3377Lbp27YozzjjDud927twZr7/+eu7z0h8Kxd0Gc5C+UBCKhnIlgugUljlz5jheDDZaANHUrFnTeFz/nfOc/j86OhqVK1d23UYQDrUNagYPHowPP/wQEydOdMIiddrMscce6/iASBsU/ivdu3fHe++9h3HjxjmDLd1v9erVCzt37pQ+UCgR7VAj/aBQ1GjR7ZVXXkHz5s2ddnjVVVfh+uuvd9qlRsaEQnG3QY30hYJQdPhRTli/fj1GjhyJX375BbGxsa7baYM2Rhtj2Y/ZFGQbQShIGzzrrLNyf9cRRnqVoGHDhvjhhx9w6qmnShsU/hN6QJVD+/bt0bNnTzRt2hTvvvturgGv9IFCcbbDm266SfpBocgJhULO/XX06NHO33oVXhvh60npBRdckLud9IdCcbZBGRMKQtFRbiJBdBqBTivo0qUL/H6/8/Pbb7/h+eefd37PiQCxIzr0a3Ke00apWVlZjpmR2zaCcKhtMJK5bu3atR0RRIeOSxsUChtd4UpPQnX7yqnOIX2gUJztMBLSDwqFjW5Tbdq0MR5r3bo11q1b5/wu/aFQ3G3Q7TUyJhSEwqHciCDHHXec4z4/b9683B+twJ533nnO702aNHFueuPHj899jRY89CRVh+lq9ORVuzjzNtrVfsGCBbnbCMKhtkGfz5fnNTo8XEeQ6BuftEGhsNFpVosXL3bal/ZmkD5QKO52GAnpB4XCRlflWLp0qfHYsmXLnAmmRvpDobjbYCSkLxSEQkSVY+zKHLoyjK4G8+WXX6r58+erc845R9WuXVulpKTkbnPVVVepevXqqQkTJqg5c+aoY4891nG5DwQCxfQphLLSBnXVmJtvvln9+eefavXq1WrSpEmqZ8+eqm7dutIGhUJBt6/JkyerVatWqenTp6uhQ4eqxMREtWbNGud56QOF4m6H0g8Kh4OZM2cqv9+vHnnkEbV8+XL14Ycfqvj4ePXBBx/kbiP9oVCcbVD6QkEoWkQEIRFEl0TTpft0qdyYmBjVp08fRwxh0tPT1bXXXquqVKmi4uLinMHbunXrivhrEsqDCJKWlqYGDhyoqlev7pRibtCggVMezW5f0gaFQ+Wss85yhF3dvurUqaNOPfVUtXDhwtznpQ8UirsdSj8oHC6+++471a5dO2e816pVK/Xaa68Zz0t/KBRnG5S+UBCKFo/+pzAjSwRBEARBEARBEARBEEoi5cYTRBAEQRAEQRAEQRCE8o2IIIIgCIIgCIIgCIIglAtEBBEEQRAEQRAEQRAEoVwgIoggCIIgCIIgCIIgCOUCEUEEQRAEQRAEQRAEQSgXiAgiCIIgCIIgCIIgCEK5QEQQQRAEQRAEQRAEQRDKBSKCCIIgCIIgCIIgCIJQLhARRBAEQShX3H///ejUqVORv89FF12Ek08++T/vx+Px4Ouvvy6UYxIEQRAEQSjviAgiCIIglCm0+KCFA/0TFRWFJk2a4JZbbkFqaqrzvP79119/LfLjeO655/DOO+8U+fsIgiAIgiAIBcd/ENsKgiAIQqng+OOPx9tvv43s7Gz8/vvvuOyyyxwR5JVXXkGFChWcn6ImKSmpyN9DEARBEARBODgkEkQQBEEoc8TExKBWrVqoX78+zj33XJx33nm5KSV2OkxO2spTTz2F2rVro2rVqhgxYoQjoOSwefNmDBkyBHFxcWjcuDE++ugjNGrUCM8++2yB02H69euH66+/HrfddhuqVKniHJ8+Fmb58uXo06cPYmNj0aZNG4wfPz7Pfjdu3IizzjoLlStXdo512LBhWLNmjfPckiVLEB8f7xxfDl9++aWzv/nz5x/y+RQEQRAEQSgriAgiCIIglHm0eMGihs2kSZOwcuVK5/93333XSWPhVJYLLrgAmzZtwuTJk/HFF1/gtddew7Zt2w76OPS+ExISMGPGDDzxxBN48MEHc4WOUCiEU089FT6fD9OnT8fYsWNx++23G69PS0vDMccc40SyTJkyBVOnTnV+15EvWVlZaNWqlSPmXHPNNVi7dq1zzJdffjkee+wxtG/f/qCPVxAEQRAEoawh6TCCIAhCmWbmzJlOZMRxxx3nuo2OqnjxxRcdAUILCTrqQ/uGaAFBR1dMmDABs2bNQteuXZ3t33jjDTRv3vygj6VDhw647777nN/16/V76vcZMGCA8x6LFy92ojrq1avnbDN69GgMHjw49/WffPIJvF6v8/7a80Sj034qVarkCDQDBw50BJAff/wRw4cPR3R0NLp06YKRI0ce9LEKgiAIgiCURUQEEQRBEMoc33//vRMhEQgEnAgQnTLywgsvuG7ftm1bRwDJQafF5KSPLF26FH6/H0cccUTu882aNXOEk0MRQRj9PjkRJVoAadCgQa4AounZs6ex/ezZs7FixQokJiYaj2dkZDiRLDm89dZbaNGihSOYLFiwIFcwEQRBEARBKO+ICCIIgiCUOXTKiDZB1dVh6tSp4/yfH/bzWjTQ6SkapVTE17g9XpjvY4sXelsd2fHhhx/m2bZ69eq5v//999+OEawWQbZs2eKcA0EQBEEQBEFEEEEQBKEMon03dLRGYaDTY3REydy5cx0BQqOjMZKTk1GYaCPUdevWOT4eOaLFtGnTjG10NMqnn36KGjVqoGLFihH3s2vXLseU9e6773YEEG0KO2fOHMcXRRAEQRAEobwjxqiCIAiCcAARpH///rjiiiscfxEthujftahQmGkm+j1atmzpmLDqSA5d2lcLGYwWNKpVq+ak9+jnV69ejd9++83x/NiwYYOzzVVXXeVUxRk1ahTGjBnjRJjccsst8h0LgiAIgiCICCIIgiAIB+a9995DzZo1nfK1p5xyimOYqn05dOnZwkKnrnz11VfIzMxEt27dcNlll+GRRx4xttHlb3VVGO0doivJtG7dGpdccgnS09OdyBB9nNoU9f3333d8TPT2OnVGG6nqxwVBEARBEMo7HnUoSc2CIAiCUI7RURc62kJXdMmv6owgCIIgCIJQshARRBAEQRAOwMSJE7Fv3z60b98emzdvxm233YaNGzdi2bJlBzRdFQRBEARBEEoOUh1GEARBEA6ALrN71113YdWqVU4aTK9evZw0ExFABEEQBEEQShcSCSIIgiAIgiAIgiAIQrlAqsMIgiAIgiAIgiAIglAuEBFEEARBEARBEARBEIRygYgggiAIgiAIgiAIgiCUC0QEEQRBEARBEARBEAShXCAiXrce7wAA5LlJREFUiCAIgiAIgiAIgiAI5QIRQQRBEARBEARBEARBKBeICCIIgiAIgiAIgiAIQrlARBBBEARBEARBEARBEMoFIoIIgiAIgiAIgiAIglAuEBFEEARBEARBEARBEIRygYgggiAIgiAIgiAIgiCUC0QEEQRBEARBEARBEAShXCAiiCAIgiAIgiAIgiAI5QIRQQRBEARBEARBEARBKBeICCIIgiAcNB6Pp0A/kydPdrZfv349rrnmGrRo0QJxcXGoUqUK2rdvj8svv9x5zuaSSy7B8ccfbzw2d+5c9O3bF0lJSc6+n332Wfz666+oUKECNm7cKN+iIAiCIAiCcEA8Sil14M0EQRAEIcz06dON0/HQQw9h0qRJmDhxovF4mzZtkJKSgs6dO6NSpUq4+eab0bJlS+zZsweLFi3CZ599hueee84RN1js6Nq1K2bMmOH8n4PeR2pqqrN95cqV0ahRI9SqVQvHHnss6tevj3fffVe+IkEQBEEQBCFfRAQRBEEQ/jMXXXQRPv/8c+zbty/Pc/fddx8efPBBrFq1Co0bN87zfCgUgtcbDkw866yzsG7dOkybNs3YLioqyokcefnll43Hv/jiC+c1q1evdsQQQRAEQRAEQXBD0mEEQRCEImXnzp2OyFGjRo3INyISQLZu3YqvvvoKw4cPz33snXfecdJfAoEAXnnlldxUmxxOPPFEJyXm9ddfl29SEARBEARByBcRQQRBEIQipWfPnk60x6mnnopx48Y56TFu/PLLL8jOzsYxxxyT+9iQIUNyo0JOP/1053eOEomOjkavXr3www8/yDcpCIIgCIIg5IuIIIIgCEKRcu655+LKK6/EhAkTHLNT7Q2ivUJuuukmrFmzxthWixvaOLVVq1a5j1WvXh09evRwfq9Zs6bze87fORxxxBGYN2+e4xkiCIIgCIIgCG6ICCIIgiAUKTp1ZezYsY4niPbzuPjii51oj2eeeQZt27bFb7/9lrvtpk2bHNGD010Kgk610dEmW7ZsKYJPIAiCIAiCIJQV/MV9AIIgCEL5oGHDhrj66qtz/9aVYc455xzceuutmDlzpvNYeno6YmNjD3rfOa/RrxcEQRAEQRAENyQSRBAEQSgWzjzzTHTo0AELFizIfaxatWrYtWvXQe8r5zX69YIgCIIgCILghogggiAIQpGyefPmiI/rcrrr169HnTp1ch/TXiC6msyePXsO6j10qk3VqlUdzxBBEARBEARBcEPSYQRBEIQi5ZFHHsEff/yBs846C506dXKMT1evXo0XX3zRETyefPLJ3G379esHpRRmzJiBgQMHFvg9pk+fjr59+x60l4ggCIIgCIJQvhARRBAEQShShg8f7vz/ySefOIKHjvKoUqUKunTpgh9//BGDBw/O3faoo45Co0aN8M033xRYBFm5ciXmz5+P+++/v8g+gyAIgiAIglA28Ci95CYIgiAIJYSnn37aiR7ZuHGjEzVyIO655x689957jhji94u2LwiCIAiCILgjniCCIAhCiWLEiBFISkrCSy+9dMBtk5OTne1Gjx4tAoggCIIgCIJwQEQEEQRBEEoUutzt+++/j5iYmANuq71F7rzzTpx77rmH5dgEQRAEobyj/bcK8jN58mSUJBYtWuSkzq5ZswYlHX2M+hy+8847xX0oZRKJGxYEQRBKHEcffbTzcyA6d+7s/AiCIAiCcHiYNm2a8fdDDz2ESZMmYeLEicbjbdq0KXEiyAMPPOCYsGv/MaH8IiKIIAiCIAiCIAiCUCB69Ohh/F29enV4vd48jx8qaWlpiI+Pl29DKDIkHUYQBEEQBEEQBEEoNLRfV58+fVCjRg0kJCSgffv2eOKJJ5CdnW1sp6My2rVrhylTpqBXr16O+HHJJZc4z23YsAGnn346EhMTUalSJZx33nmYNWtWxDSRv/76CyeddJJTfU6n1eoo0c8++yz3eb39GWec4fx+zDHH5Kbs5JdusmLFClx88cVo3ry5c1x169bFiSee6FSkY3Taj97Xxx9/jLvvvht16tRBxYoV0b9/fyxdutTYVtck0T5mDRs2dI6za9euGD9+vHMe9M+BWL58uZMCrM+rThtu3bp1gTzUBBOJBBEEQRAEQRAEQRAKDV2xTU/WGzdujOjoaPz9999O5bclS5bgrbfeMrbdvHkzzj//fNx2222OQKCjSlJTUx2xYteuXXj88cfRrFkz/PzzzzjrrLPyvJdOxTn++OPRvXt3jB071jFX/+STT5xtdVTJRRddhCFDhjj7vuuuuxzR4IgjjnBe27RpU9fPsGnTJlStWhWPPfaYE+2ij+Xdd9913mfu3Llo2bKlsb3e91FHHYU33ngDKSkpuP322x3RZPHixfD5fM42WiR59NFHccUVV+DUU0/F+vXrcdlllzniUIsWLQ6YzqOFogYNGjiV9GrVqoVx48bh+uuvx44dO3Dfffcd1HdUnhERxCIUCjkNXiuOWtETBEEQBEEQhLKEXo3eu3evs2KtJ5yCUNiMGTPGmF/17t3bERR0ZIWewFeuXDn3eS0u/O9//8Oxxx6b+9jLL7/sRGL89NNPjsChGThwoCNqvPrqq8Z7XXPNNWjbtq3jSeL375/eDho0yBEGtDBxwQUXOCKGjujI8SopSOqOjmTRPzkEg0FHTNHvpY+BP2POfj/44IPcv7XwceaZZzrRK/r9du/e7bxGizP8GXQkTM+ePQ8ogtx0003OHHXq1KlOpIlmwIAByMzMdIQaLYbweRXcERHEQgsg9evXz+eUCYIgCIIgCELpR69C16tXr7gPQyiD6EgJHZnwxx9/OCIHs2zZMieaIgc9cWcBRPPbb785E/4cASSHc845xxAQtFCio0ueeuop5+9AIJD73AknnIDvv//eSUnRaSMHi96XTuHRwoZ+H07l0dEdNjodh+nQoYPz/9q1ax0RZPr06Y5goYURRj93IKPWjIwM/Prrr7j66qud1Bz7c7744ovO/gcPHnzQn7M8IiKIhb7Ycm4KOQrb4UJfWL/88oujckZFRR3W9y4LyPmT8ydtr3Qi166cO2l7pQ+5bkv3+dOh+nrRL2fcKwiFybp165zID50u8txzzzkTfO1/MXPmTIwYMQLp6enG9rVr186zj507d6JmzZp5Hrcf27p1q/P/Lbfc4vxEQkeEHAo68kKnzui0lr59+zpijY6c0ukr9mfQ6EgXRnt2aHK21Z8p0mdwe4zRr9XCxwsvvOD8FObnLI+ICGKRkwKjBZDiEEG0sqffV0QQOX+HG2l/cu6KC2l7cu6k7ZU+5LotG+dPUr+FouDrr792PD2+/PJLxwA0h3nz5hW4HWpBQYsmNlu2bDH+rlatmvP/nXfe6XhsRML27igoOgJEp9JoLxFbbNBGrQdLjkiSI9zYnyu/aBAtwOj0muHDhztCUiS0/4pQMEQEEQRBEARBEARBEAqFHFEjJxIix4fm9ddfL/A+dOSFru6iPUE4xUMbntoCh/b60MartlhhY0dmFORz8GfQ/PDDD9i4caNj1Hqw6BQgvb9PP/3UEGx0GotOmclPBNGiqTaK1WlGOs1Gm80Kh46IIIIgCIIgCIIgCEKhoM069SRd+3foii/az+KVV15xjEELyoUXXohnnnnGqRrz8MMPO6KDFkR0NRQNG/pqjxAtlGgzVF0JRpey1T4k2rdjzpw5julqjgGp5rXXXnNSwXSKjo6esNNYchg6dKhTQrdVq1aO8DB79mw8+eSTh+yjo8v36hQbXR1GR3accsopThngBx54wEkJOpBJsU4tOvroo51UI+0NokUTbXCs/Uq+++47xxhWKBhiBy0IgiAIgiAIgiAUClo0+OKLLxzRQ0c8XHfddejUqROef/75Au8jISHBmdT369fPEVJOO+00x2tEV43RcDqKjpDQqTP6sRtuuAH9+/d3RIIJEyY4v+egBY9nn33WiRrR+z3yyCMd8SA/0UGLMFq00KVuv/32WyfFJ7+yugdClwnWoo6OKNFGqvqcaIGoRo0aB0yx0dVntKijxZxRo0Y5nkKXXnopPv/8cxx33HGHfEzlEYkEEQRBEARBEARBEA4JHS2hf+woCv1jo9NimMmTJ7vuV5v3ajGF0SkvOk3liCOOMB7XkRo6zeRAjBw50vkpCFqUeOONN/I8bh+zFlTsz6XRkRr24/rY7777bucnh9WrVztRK1w1JtJrcx5/8803C3T8gjsiggiCIAiCIAiCIAglCl32NSeyRJsJ68gQHTmhozNKa2lnHYXy8ccfo1evXo4xsi7fq8vw6t91VIdweBARRBAEQRAEQRAEQShRaDNQ7QuyZs0aZGZmokGDBk65Wp0KUlrRaT5//fWXE82RnJyMpKQkJ5JEp8kcqEyuUHiICCIIgiAIgiAIgiCUKC655BLnpyyhDV61V4lQvIgxqiAIgiAIgiAIgiAI5QIRQQRBEAR3QkEE/7oZmDgQWPe5nClBEARBEAShVCMiiFC+SN+MVb/ciYxxA7H2/S54/KLqSFvxJRDMKO4jE4QSR/b2ubhpqB+dThmD3SvH4+m7zsSKn+/S1u7FfWiCIAiCIAiCcEiIJ4hQPsjeh4mvn4Ox7/+EP5cG8faVwLFtgT/mA5/0Pw3dm0fjjhsvQaMmrbB42Sq0OnIoEFcHnkpti/vIBaHYmPndE/hkGnDdIA+STpmB7T/0xtBLHsWc33sivumJ8s0IgiAI5YpQKIRNmzYhMTHRKXUqCELJQpcV3rt3L+rUqQOv1z3eQ0QQoVzw7ZPH4bYXZ+KiAdXx2iv3o1K7i3Slbnw1ZA1+++QujP91Iv73wVjcOhR49BVg1qrnkRADvP7Aaeh89ttAVGJxfwRBOOxM/2MSzjo6Hnd+lAx4o/Dou3/jr6Na4Zv3HsI5D4gIIgiCIJQvtABSv3794j4MQRAOwPr16/MtoywiiFC20WH7v5+C/rVn4usnB6HVuT8BpNz7KrfGsVd/hWOvyAB2/gVk7cIb3TPw129fYvb0X/HIC1/g87iJwKBZQGLTYv0ognBYydqNm47dirRaZzkCiMaT1BJnD2qF3/+cjXOy9gDRSfKlCIIgCOUGHQGSM8GqWLFicR9OuSIYDOLJJ5/EvHnznJ/Nmzc7j8+ZMwdNmzbFPffcg5kzZ6JWrVq5P7r0bOfOnZGWloaMjAzExMQgKioKfr/fiRLQZXfHjBmDm266CdHR0c57BAIB50eX59XbzJo1CwsWLMCWLVtyf0477TSceeaZ+Oabb3DBBRc4x6G3bdWqFfr374+HHnrIeUy/Z2xsbLGet/JGSkqKI1TmXKtlRgTRjbV79+74+++/MXfuXHTq1Cn3uXXr1mHEiBGYOHEi4uLicO655+Kpp55yGrVQPglsmYpzb/sGz19RA61OedMQQAx8sUCNo51fdWvp1fRM9DpvF4b9MhJ7tn6AL29vh/7nPYb6R408vB9AEIqJ4I45+HMp0LNDF+PxCy+9FpfOvRYp71VCxQv3AlEV8rw2tHMuxn94L7Zt24Z+g85A/aNvdr/2BEEQBKGUkJMCowUQEUGKhq1bt2L27Nm5P3v27MGkSZOc53744QfUqFHDER66dOmCtm3bonnz5o6w8dxzz7nu0+270vNKLVLo57VAEonjjjvO+YmEnmsOGDDAmYNqYUYfr5536v3pyXjdunUdYUQfq/7p2rUrunXrBp/Pd0jnRig4B0pXK3UiyG233ebk+GgRhNHK3ZAhQ1C9enVMnToVO3fuxIUXXujkBb3wwgvFdrxC8fLHd89h+Rag+onfAfF1D+7FMVXQ4MT3sfjb6vjsj2fw/I834Md3d6D20fcAPhHWhDJMKBsTXjkNl70MrL6io/FUVPMLsGvu0+hy12rM6PAOanS7NvykUgjNuBKela9jwi/A6m3AQ2/OxIePzcKR578H+CIPMDQeFcCexR9iy5oFaNv/ZnjiaxflJxQEobgJZuLW89ri6C5NMOyEY/Hj7yvRqG0ftOk9/PAeR9ZuIH0rkLIIqNwJqNDk8L6/IJRzsrOzHeFDpy789ddfOPLII53HK1eu7IgGvXr1cuZzelJrz/+KGy1m5ESdaHGD0cf70ksv5Yo5H330kfOY9qvQr/vqq6/QunVrtGzZUvxlioFSVR3mp59+wi+//OJEd9joxxctWoQPPvjACXvSoUhPP/00Xn/9dUeJE8onv//+O47rmABftf0d6qHQ+qQx+PH3ZTiuUyL6n/cwVr7RHNgxUypkCGWWzNXf4eIX9yApHvBXNyNBtD9OldP/wpFNvPj03TH0ol1Y+tnpGHDZ69iJ5njy9XH4fOou3H1+Uzz+0mdI/YPEEgvPlvHok3EbHrj1Ypx02dO49rRmCGybUYSfUBCE4mbN9Dfw4biVaBwcjwXf34k7Rr+BoaddgJO7ReN/o48Dtk5GIG37we84FAR2/wOoEJC913273fOAJc/i7Rvq4sazW2Pnj6cB43oA8x8C0jb+p88mCEL+JCcn4+OPP8Y555zjLGDr/zV6Dvf5559j1apVzoK2nt898sgjpVIk0OkYV1xxBV599VVH3Nm3b58TLZKTdnPVVVfliiC33HILfvvtNycNRzg8lJpIEK0QXn755fj666+dHC2badOmoV27dk6USA6DBg1ywpy0+nbMMcdE3K9+Xv/kkCOYaFVS/xxOct7vcL9vWcE+f57NP2Lagm248NReyP6vnUpcIzz0+p8YPu5eNPF9i9fv6I4U1MY1d74Af92B+9NpSjnS/uTc5bBzwzx0bwa89fwoZHsr6sZhnhxvIi49ZwAuvn8cKkbVwnm3vodXR1+GRz5aj+HHJCJp2BRkx1R1Nj334b9x/sRj4dnwFjK3XwNvpXZmu9v+F268eCjuGabw+KjLMcpTD+dddR/69+uBbz8di7hWl0RorHuhkhdi387ViKveBv6qZrRKeUKuWzl/DioEz87p8GydgHmTP8SO5H1o3rIt6g96CUhsXvLangrhxWcewYldPGhzykvwpCzF3H4ZWPDXJEz4cxmOqToRU16ciAe+jsKQfu0x6LQr0aLXRfmn1WXvwdY5byB59nNolrQFr04E1u3y4v4HH0dc7a5Q1Y7av9223xFa8xl+/PIt3P95NjKz4XgdzdiwC8n/bMP7D96Lu4e/hx6nPQxVox/gjYVn/WdAQiN49iyEiqqIzbPfRK1edwG1B5baa1fGmsLhJscfQ0fs63mZnvAfccQRuPHGG3HSSSc52+gICe23URbR4ocWPXI+55o1axwLh2+//daJEtGL99rnREeV6LmrTvORlKuiw6N0fFEJRx/iCSecgKOOOgqjRo1yGk3jxo0NTxCttOnHtWLI6Pyud955J1dhtLn//vvxwAMP5HlcN8ZIYotQSlAhDE07C4vXZ2NXrcuxu9KQQtt11eB8pK34Ek+8NxertwOn90rAKWecj13xvZHtyeuPUO5RCrF7Z2DOxPeREBeFtr2HY1+8FV0glCg6ZI5F48DP+DnuLWR6q0TcJjqwFRunPIATW21y/u77EPDs9Z0RbHULAp4EY9tKwWX4+vXbkFgxCb3OeAyZUbXhU5nwrX4d73w6ATtTgVH3PIA9MfvFjAqZS+FbMhp9mu3DrOwzsKfiMfAigMCWKWhfaQWWzJ+Nq98G9mUAdasAI05pgia9rsRuX8vDcHYEoeTgVVmouvcX7F3zC37+cx2eGQ68NMGPD//0YPOubFx+rA/9h12KzXGDS5QvT42Ub3HH6LfwyHXHYmfd68NPKAUfslA/8CuqZ/yJ935YjL/XBvHnMmDi3UBMrSOxMLMvMiv1gPLsX8dLCG1G8t+v4pMf52HpZmDUyUCHphUw6qN9SE7b30/8fi+wPTUGk5bGYdbSFAztFEKfdgn4ZMMpiKneEXFV9wtFq6e/hY8++xY+7/7383vhlAmfuQp4+Azg/JeB6hWBn/8Gnr/Ii6q9n0KKr3Smz2ijSO1noP0WZKJVcPRiaVJSkpy3g6im88Ybb+Czzz5zIh6++OILpKam4r333sPQoUOLvdKOXgh/7LHHcMcdd7h6ghyu0ss6o0Ev6Ot5rz4vjq9av36O/8npp58uBquFfI0WqwjiJkAw2pH3zz//xKeffoopU6bkKmeRRJC1a9di3LhxeVQ3faGdffbZBY4E0Q1vx44dh/2moFX58ePHOwY72uBH+A/nL3Mdrju9NW46uzUaXzAb8BZ+0FNg1z9YNPFFPPbcexh7cQjRCdUwI+Vo9Dr5NkRV71rqvr6iaH+eHX/Au+A+XPzQFKRneZCcqrBjHzDxpaFI6P0yEFsLZYGydu1Oe6kXMrbPxzH3pRxw4uTZ/BMytszCXm8DVOtwoev2878cgavvfh0Du1TGHbdci7jlj6DvgyFUTgAeuXckVuEY8/ylLEbw18HoctMm1KgIBELAmu3AymeAbbH9sB3N0LB5J0z5+UP4d03D0M7AzL29ndXihAbHADHV8/UgKSuUtbZ3WNDDnuR5SF31PbZsT8bGjDroOeT60nX+QtnwLn8eH7/9HO5+dwu8XuDei9tj+GUjoRqcDXijseSP93DXrddizDkZaNKiI9LqX4Loqm0R9MTtv0f9R1HkkNteIBX+7xsh5E1EaPDf+ZegT1sPz96l+Gfc06gUWIx/lm7CNW8DFw+shn7HHIM+LYH1c/+H40YDN5/VBG069kCfc56AJ7aG8z2nbv0bT952Kq7qtQEXvAJkBryOwPHeu2+iXqcznPNkE8rahzOObYCr+u7DA18C63fC6YP+eK4zxv8TwLwtVVAhtBk3HLUMn00HTrnmZfhbXHb4zl8hoce71apVk8n8IZw3EUEOzOrVqx0fR+17ocWFnGoqWvgoSZQUEcRGz2m/++47RzSaPHmyc63qVBpttCoU0jWqipHt27erxYsX5/uTnp6uhg0bprxer/L5fLk/+tD1/xdccIGzr3vuuUd16NDB2P+uXbuc7SZOnFjgY9qzZ4/zGv3/4SYrK0t9/fXXzv/Cfzt/exe9p2pXgto28/miP5WpG5Ra+qL6+rZE1akh1NEtoe47p6pa+vUVSi0YrZZ8d6PaOf0xpTZ8p1R2miqpHFT7y0pRgU0TVXDTRKUydykVCplPb/pDvXVrO3VpP6jQh161b9IFSu1bo0IpK9S3Dx+hQh9AbXmjqlr01VUqtGWKUtumKrV9hlJbJqnstd+pbbNeVEt+uF39+c5wpebcotTaz5Tau1qVVMratXvnaUnqwfNrFPp+l4+7Rx3bFuqC3lDq4xj1+8sDlUrf7n7+Aulq8/Tn1PiXT1O/vHiySln4nlIpK/LuOHmRShs3RPVvB9WgKtSAdlDnH+1RqZ/WV1vfqa/uPL2K+vTB3s6+9PuVJcpa2ytyAhlKje+j7jkFzj2iXhWojg2g1nx5Wp5+LJCyVj16YS2nH7vjRKjZj1VQ6ufuKnnS5cXbHwWz1cavhir1IdTDZ0D99kI/tXv5z3mOXxPK2K3Ub8PU8xfs/7zNa0E1qg71yc1VlJp+uVIZOw9721sx8Ql1yxCo0OKDvD+HQip7zbdq+ednqXN6eZz77YfXQAV/PlrtWfSRc15cjzV5tXrtnuNVZvKaiOfJZm/yDpW6N1mN+2i0WjT9G5WRbt279T7m3aWO7wD11oiKSmXtLXXXbnGOd0szct7cSU5OVlOnTnV+37Ztm+rUqZN64YUXnMdLKhkZGer+++93/i+pLFmyRD322GMq9G/fdeONN6offvhBBYPB4j60Un2NFqsniFa19M+BeP755/Hwww8boVXa70NHh+hyuZqePXs6xjk6l6p27f1VBXRqjFb1dEkioXyxeM4kZ+WmerM+Rf9muupMixEYNvpSDLlhBv73ys2YMWcRZo57DS1SgXufB35fuj9s/+g28bj3+tNQufvdQMVDDN3fMQNQAaD6v/nNh4NQAGrnX1j0x0dY98/3GNxsDZ74RuG1SUCbusCxXevggnPPQtWkKLz85md49+c1SIgB7rjsGGDIWCQktXB2o9cdT7x7NtTiMbjo7JuxcONYVEkYi32ZwGQd6hwFdLxz/1vq11epAEy9F5i+Anj4a+Dtlx9DnV43Ad5StGJb2lAhbNyWgn69OhT6rpsNfBATpl2EPat/A1qciKNj/+3/3XLifbGo1f165ydfklojbuD3GD9jA9bO+gDzZ0/Bls0boKJ9iPLodpWG97/6Hbc+9zu6NxuJT+7rjpQqJ6Ji/W7w+qKRvHkhPHvmIyk6HareqfDUGwp4SpVvuFBQFj0BbJuCevUaYMo3t6BuwxZY+O2NaJj+BVZ9fyUaD34eHn8skLYB793THT9M34Lzh7THjpQAVGI8sG8VBo2YgX5t3sDQvq1x9PBXc8urHw6ydq/EJSe3x9RF6ZjybFfcPXYsUPkI16gOT0wl4KjPMMz3Gs4cAWxbOw8xngz4d03FvoWvY9ilb6Bdq0YYPOQUVKpWH926dkDIXxHeii3gjSmCaNhgJp54/BHEe33wND7v4F7r8cDf8EQ0a3giPjrhOWRvn41AZgq8TU5FxQNUbItKaoTLH/ypwG9VIWm/p9HAc+50PRZ0fAQjr0vGiLtfRt0KiRh40xSgRu+D+0yCUAbQFVtefvllpziFNgPdsGGDY3aqI/aF/45OI7r99ttzDWV1ueBnnnnGyYq4+uqrcfHFFxdoPi2UQmPUBg0aGH9XqLDfd6Fp06ZOOSXNwIED0aZNGwwfPhxPPvkkdu3a5TjtajNVyXUsf6xYthAttBZ2qELDoeCLhb92X5zz4F84J5QN7PxLqwf4dIAXe3Zvx/wZP+O7L9/HviXvw7fhM/y0tiNOH/kufJVbFWj3GevG44PnrkfF7CU4swewvfYNqN73KcB7kLXGtankztkIZqbAF18DnoT67uWDt/2OPQvfwcPPfYbvZ+1DdhA4q1csBh97Okbe1h4nnbMdi+fPwv9+nIV6Xz6Ds3oCy1f58MCI/hh04dPwVY08kfa0vgnf/3wEgmlbMWPyV6havRaq1a+BqNhEzPkpG5Wq1kNspbr7UxpUCJ2Xf4m280aj/1l34LSjHsX9r06Dr/J+cymH1PUIbPgZ/p2/4aOvp2LW4h04untHDDl/FGIbHl+icuFLPBnbsWm3Qu06+/vWwsaT2ASVOhRRDn18PTTse4fzk4N2J7nvDADpm7Fl7rvYumwivHt+w0tvz8Bbv8EJjdeeAdcOBO48CThj5Lto3aQqLh9xOxocfYu0nTLE9l+vwR0PvYKhPWvhimdXOGKqTknYUv9ehPwP46JbXkfvT37B2Rdeh7qbn8D5R2zDsHNGo0p3cyL8fu138dKY+3HZmEUYPKE3xjx4LTxdnj34vvgg2TD/Jzx+17nYkZyOqW+dg3qDXgGikw78Ql80Ghy1vzpTzZwKjkohsOI9PJb2rOOl8fiT+ys9aR+MSQuAEe8AZxzbCOecfyladT8N/sT6wJ4FyN4yHTMmfoKa1augZr1maJ21Cd4FM7B57UJs2rAS8RUqoVXjati6Yw8WrtyB9h27YG9mNJo0awlPVAVMnfQjJv29B1M/G+WUoT9k4moiqsEJKG45fNDFz6DbR1/i+XFbcMyRwxHV58PDu0AhCMWILvU6ePBg/PHHH05hCj1Rv+yyy+D3l4rpZamkUqVKmDNnDmbMmOEIT9or84UXXnCsIrw6L1IoOKoUsnr1aifMZe7cucbja9euVUOGDFFxcXGqSpUq6tprrz3o8CZJhym9cGjp6rdbq+lP1FIlDh3KtmWi+uXB+qpnc6gze/jUN4/1U8HkpeZ2WXuU2jVPqfVfq5S/HlWvXN9cdWgAJ9x/4vMD1Np326tmNaE+uqutUhk78n/PtM1qyfe3OO9z9cBotfBxqMD7+0OjW9aGGtQB6oURTdXe5d/knr/Ajnnqu8f7qJ2vQm19GermkxLUrA8vVumrvlMqGCF0V6fE6JQWnfITyFRFQWjfBvX7qyepEzpBLR0Tpfb8fLIa/+KJ6v5zqzkpFjefACc8/NNbqqrRF9ZUfVpBta4DNef1PkrtXRUOgQ4F95+z9K1KZe8rlGMr7rDmQmXnX+rRs6BW/XzzYXvLw37+0reqrHU/qSU/3qUW/3CnStGh9MmLlUpdr+Z8fJG6akC0aloT6u4zq6jUpR+pkkyZantFSdpmdeVxXiddceWMj/Kev9Qdat3XZzqpMTpd5Otboven4eXD5mVT1f9GtXL6nczfL8k3HeM/s3WK2vqKT13UB2rjuKsLd9+7Fyi16n2llr6k1KKnVdbse9Ts1/uqq47zOOkz1w/a37eOPnP/PaN9fai6laF+uBUq+z04/a9OK+rU2K+a1YJKedOjlj4F556l7zM6Re2uYfv3cXo3qPdvrhf5PlKamTfKubc+fjZUcMU7peLalbQOOW+Hgk7J+PXXX3NTM66//nr1xRdflNp7UGlIhzmQtcTkyZOd37ds2aLOPvtstWjRIlWe2VPAdJhSKYIUJSKClF5yBxSZmUp9mqDUhONUSSZl2dfq7tMrqiObQH17M1TWJ9XUQ+fXUFcPjFFDO8PJd854B2rRE1AndYH65bmBKrRn2f4XB9IdQaBNXainLqujsjb/Gdmr5Pez1I2DPapJjf0D1ccurq22fHuyUoueVJunjVH/fDFCvXN7O3XrUJ8zmJ03ppoae0ML1as5VJfGUL8/193xW3CEgxJCaO3nSn3XSn18LZzjvGVYBfXtE8epXfNe2y9s5GyXvFRNfP5Y5xwueRJq5JB4de3gWHVBb6+6duD+AfnUe+FMeGd9cL5SwcAhH1NxD2YLlfVfO+dGrXz3sL1liTt/WXvU9LdOUy9eEuv418x6ro3au+I7pfauVNkbxqvgrBtV8Odeat3E+4p9Mlfizl0JZd24kc5kfO20se7nLxhQq788Wy16b4BSaZsKtuNAhtr7/TFOf/n4xXVU9s4FKm3VD0rNu1t98kAvdeWJ9dSejf/8p2P//dNRaswFsSrwUZxSaz4tkKdFoZC2RQVWfqSSJ1+l1NRz1cKvr1Nzfn5eBdO2q1D6DpW5Zbr65bOn1cTPRqs929fuf42+V+jjy9qjQpkpasv8r1Ta6p/VinGjlFryvNoy8Wajny4zZKeq285u6og+r18GpX7o6Jy/knztllcRZMOGDeq8885zFkv1omnHjh3VX3/9VeDXl9fzppkwYYLq2rWr8/mnT5+uygKlXQRh9HfSqFEjx0fz4osvVuvWrVPlkT0ighTtiSsKivuGWNrJOX9rJ97rrFb9/uowVRpIWz1OBX8drNK/7aruOr2yeu6apuqrR49Rf31yhcpe+qZSWya7Dhrnf3mt6t0S6te7oALfH6F+f/10tXHqk+rrR/uo0Wd5ncns4rePUnsWvLtfFHFj72oV/OMC9cLFseq0I6E+ve/IyMJKSUKfE22SeaAJwfpv1Zqvz1WPXVxHjbmykXrz1vZqytihSs28Wk17uY966Lwqzqr/XaclqIxNh/aZy9K1u/mXq9UNx0Opzb8etvcssecvdaMjJN53ms8RK3Ukll4ZX/A41OzRfidi4N6zq6jdiz4vtkMsseeuJPHPg2rVM1Bjr66SJ1qjUM5fdppa9PlFTpSJFlqOaQMVfB/qx1uhzu4JdUQjqIcubqYyN/x2cNEiwYCa8Obljoj94iUxKmvVF6okIW0vL1O/fMwRQvR3r++/obl3uQrsxX3+yuNkXhdMaNiwobrooovUjBkznMhyPbFfsSKC4bYL5fG8zZ49Ww0YMMD53N26dTuoghMlnbIkgmj053j++edV9erVVUxMjHrzzTdVeWNPaTBGFYSi4OUXn0VKOtCs04BScYLjGg0EGg1ELIBHTjy417Y75QVM7H0pfAvvw9r5v+K6p+ZgW8rnaFoDuHBoS6g+T6NVvSEH3lGFRgge+QYabDsJH790HKLiKqHEo0sg6p8DUe9ENKx3Im4flvepHkcCPa7IRP/3L8Arb32GjV+diCYnvgHUG5bXCyIUAJLn7/+9cseyaZyZuh7n3fgKNu4CnkloWNxHU/zE1wGO/gT3tl+ODi9fjpi4RDRq0gqtepwOX5X2+LHtHXjw8ZcxYOjp+PiZK9Cs302H14dIODCBNLwz9lH0bQ5cOeqjIimXDn8cWp/2NiYecRJWzPwUjRrWh7fpyRh8UnUM2L0U4z+4A5OmLYLn177Yhoao3PMhRDU5c38J52Cm43uE1DVO6djtq2cic9821Kvqwf2PvoR3J2zHmMvr4pRRsx0fDKFkc9Qpt+Pbqq3RzvsjHnjmVfz52Gh8+cgUJBx5P1DruOI+vHLP448/jvr16+Ptt9/OPReNGjUq9+flQPz8889Yv349vvzyS5x88snwiM9aiUUXBLnuuutw0UUXYcyYMejcubPz+NKlSx0fzYQE7ZQmaEQEEcoWKoTN2/fikctaoVa3ESgP+Kt1Avp+g0Z9FGafPRvBfRsRVa09UOHgzSeVxw/4y1kH6YtBj4s+RY9jToWaejbuHXkKhg07DR2OvQxRCTWB5L+xfManePqtiZi+LAtaXn7g4tY4+eqXgJrHoCyhUpZi8Ubgs/s6AYlNi/twSgzepOY49c7JeR5vfdLz+OiYG/D0yO7YM/81pO96Dc9PqY3mzZph4LCLUKFOV6BiC8c0ORc94c0R0NK3OqaV2LcaSGq7f1IsFCpbZ7+K+z5Nx6RP7gPqDCrSsxvV+BS0bnyK8Zi/YgsMvvtEDN41G1jxBu6+83XMvf8CnNH9AjSrWwFDOgaRvDcdN38IJKcBC9YDHRoA390CXNjdi+svvxpVej4AxFYv0mMXCo+ufU6CCp6A9ouSsHDrKxh6+1Sc3bM/rnz098NaSUjIy7fffutUlzzjjDPw22+/oW7durjmmmucIgpCGF1p88EHH0SVKlWcyps333wzbrvtNjE8LUXoKj333Xef87u2vzjvvPOcqj333nuv096joorbVrr4KYNLmUJ5JkbtwdDOCj2O7IRyh8cDb7WuiGo07JAEkHJPw7PgOWEeGjZsiFNu/gItugxG+45HIGPKxYjd8TOaN6qJVx+5CKOv7YPdmxcDkwYDm34uU6ctdedap6pS58G3FfehlBp0tZtbXlmCLme9hk2xA7Fxyy688MHvaHH0pThtUEfg03hMebgqLu8fgzN7eDG8tw8vXVYB+Loh7jq7Fo4/sgo6de6CT+/rAgTSi/vjlCk2zXodZ198E/q19aFJnxuL92CqdAG6vYKx327E/bdejM2BZnh5fAjz97RA1RbH4+ij+2L4mSdgyldP4rufJgGD56LxlVtR5ZiXRQAphXh8fpx6xeN49bOZ6NyhJU7uCmz+X29s/aYAkZlCkbFq1Sq88soraN68OcaNG4errroK119/Pd577z3X12RmZiIlJcX4KasEg0E8/fTTaNasGT799FPUqlUrN7pAKr6UXnTkzueff+4IgNdeey3atWuHqVOnorwjkSBCmSJO7cDx3QG0jVyaVRDypXJHXPrUMpxx6UfYsm4R0tNT4e/YA/XrHY+beSV251+Y/UY/3HTcYNxyblscfdoo+FUIavN4LP77V6Qk70DKnl2oVach2nTuA1+tPkDc/sFESaaCbzcmj9ITNgkPPihiqgLNLkfTZpfj+bO1mrQO2xZ9j50b5gPVdiBpzxJ0aZeFShUTkRX0oE7FDCAmGtdd0ByzVoawa91fePT9hRjUuTcqHfM6UKUzkLYRW+e+g5opX2Lp0sX4ekFNdGjfHgPPfxi+ym2LvBxrWWDuj4+iagXg8UfuL1gp2cOAL6Emhl79FoZebT5+df/iOiKhKKlcpxXGfLIEe6fdjpYnPIEODX7Ez73nAFWOkBNfDIRCIXTt2hWjR492/tapAgsXLnSEkQsuuCDiax599FE88MADKOukpaVhwIABmDZtGkaOHOlEEehyrELZQKd9vfvuu7jlllsc8e/cc8/F8uXLHYGrvCIiiFCm8GRswanPAO+/Ux3lLKlDKCx80ajY7iJUbJfPNlW7ot0Fv+KSHcNx3fMLEf3yOXjmfCAqFbjtaWDDLiApHtiSDHx5w0toUTcaP27ojkEXPI6Y2j3NfQWzENr6G1QwC97oivBU6QREJRbL97l21VIsnAeccFLtYnn/MkNCA9Q48hrUOHL/nx17Ax0jbKbP8kn6FxXCmefehPi1L+DT+46ASmqLD35c6KRG/PVYIvyV22LD+jn4fNIaPPjidzi9VwJuvv0eoFovILYholUKkL4J2L0OyhON1L07ERtXAf6kJkBs7fIpmOyaiyHNV2PIi1cA3bSyJwjFR/yRj+DdlxNx2XX3YNV7XdDkmFHwKgWPEjHkcFK7dm20adPGeKx169b44osvXF9z55134qabbsr9W0eCaF+RshT94fV6ER8fj759+zq+KUcfLWlbZZX27dtjypQpWLNmjSOAbNy4EatXry6X37mIIEKZYt/u9Zi9GoivKukgQtESU7s7Lnx8Ic4f+Sv++eNz7Fg3D6H2J+G777sB8XWBqEoI7l0DlbwQs394DI+9+Tte/ugoXHrakThu8BmonBiFp596Ems2bMcPc7IQDAFT7wVqVYvHhM09Mfiqt+FJMAdawV0LsWDiS6iblI5qCUGkxHZEYrOT4ElsltfINYfsvUDyP0DF1kBMlXw/04zZi/HJJOCER0t+1EqZwuNFfK9ngdYXY8/MM/D2pwtx3sDG+OCdu1GpzTmo5o/HCxcoZG/6DZO+eBI1ArOAeXfgorHArlRAf/PP3AM8dAbQrSnQdiSQHQRqVQIa1/DgxQcvQ+1+j+6PWCkHpO9agzsv6ocj6gIXDLykuA9HEODz+zHgnFEY8uFz+PqvHWi89mF8NgO49xpt4H6QjujCIXPUUUc5BpHMsmXLnDRYN/REsayulutzcfHFF2PEiBGOZ0ROhIxQtvH5fGjadL/v2/PPP48nn3zSif7R/i9aDCsviAgilCn2JW9DzSTAoyehglDUeKPgq3c82p16HH788UeEWp8AH5lN+bSIUas3ure8EpPPmYonbjsZb34xE5tWzMTI44EKyofaNarhm5eHoWKVeqhfMwpzJryOu1/4FeMnt8Ydox5EzS5XI3vnP/jomSvxyc//YNEG5Ux0/zcSGP3J+5i2/BZcNKQ5Ln5kel6RI2U5dn/bD8eO2oTWdb147dVXUaHNxa6RAdu2bUXNytGmkadw+KjcEVeMWYorRm/bX/mIhS2PB1F1+2Hg9f2AYAawZQJuqTAFSxbNw/btW1G7Vi207HM0PIkxmP+LF6n7UrB+9VKsXDgNNba/jpWvfoB9VU9Eh2MuRdru9cjevQyVsBaTZ29E044DUb/HVWXGe+KXd2/Et9NTcO4dDYGq3Yr7cAQhl8de/g6YfT1aXTILF/QGUn1ShetwcuONN6JXr17OZP/MM8/EzJkz8dprrzk/5Qkd/fHss89i1KhRTlRL48aNi/uQhGJi9OjRqFGjhtMWfvjhB7z11lvlJipERBChTLE3ZReqV/y3fKoglBQ8HkTX6Y1R7+8A0jdD7ZrjlOq86vSeebwKurS9Az/3fBlXX3stug25Ga9ccjOObgFM+hMYenRjfHHlTYjSFYGSGuHujhMw/suXcO9rf2HavJp48J5bUavPI8C+lVj83c347Itvcd/pXnz1/IW46eH30eHYy/G/Z/9Al3PD5QGZrTt2o2Y1fQEJxYYWPg5UClWLVHWHol3doWg5ONsR4E444YRct/eK//7U7gN0CwWBdf/DjJdvx72jP0N89GfYuQ+4ZQhw42Dgm5+BLx+aiiOa3I/TBnTAOcP6IDszDV+Om4Xd29cjI20fKiUl4NJhbYHm1wANz3aPOioJKIWfxk3E1QOj0O36xSX7WIVyR8UGPYAGMzGt00rUrlMXP/08LmKqnFA0HHnkkfjqq6+cFBdd/URP/rUYoKMgygtbt27Fqaee6nh/3HDDDXj44YfL1eq/kDcq5Oabb8bQoUOdqKCBAwdi7dq1qF69bCyK5IeIIOUFpcrFYLBzQ6DFML+TiiAIJQ59DcbXgSe+Tr6b1ex2Db787RSs/XMsolNmoWLd+njnq8uAqv+aTPxLYtuLcGrbi9C514OY8vWTqLnhUcx+5j08+NFmx3Dz8uP8QK8P0KjhWXinxVCMufsMxGz/ySzTSjSslIrqdVoU+scWihEd9dPobJz7+Fk4+drfMP/PL9G4eXvUaNINSGyOZ07LwKhFX+CbDx7Hxz/OQ79a85wy0F+O96B6tSqIi6uNtSnpwO65GDf2XExZfT0eeG06/EkltIRy6lrHI2XA8acB/rjiPhpBiEjDxk2RnZ0tZ6cY0JM9/VNe0WVvdWlg7QtRXlb8hQPTsmVL/P7775g9e7YjgGRkZGDx4sWOeXBZRUSQMs7a38egWvUaSFh2H9DgTCxel4mWx1wHb2Lj/cLIrr8Q8FbEwokvouOwxwFvTKk20WtcJR2VatcqF4KPUMaJq42GxxXMkb7xcfeice+RwPz7MX3Sa+jRphLuva4POp38BJDU3NmmYqvTcf+oW4HFTwI6EqVqV3MngTRc1icDaCSVlcokHg/iG/RD9wb9zMf98aja+XJcon/StwCZO51Ius9HVHLSvXLJ3Im6wasw9ZvP8ciI3rj3jX/gia2GEsfOmXj+QgA9HMtZQRCEco+e0OpSwFdeeSW6dOmCzz77rNyfEyFyVEi3bvtTSF999VXcfvvteOONN3D++eejLJJ3KVAoG2yZgC0/XYwTzrkZ3QcMx9TZq9D77Mdw3IXP4OvHj0Pal+2x8J1++HZ0N9w1vBUGX/Yinr4wAfiiCrB3BUorY77YiFcnigAilEN0Wk2XZzDijVTc+d5OdLnwK/j+FUByUDWOwaDHgDXzvs/7+vTNePYnYENKhcN3zELJQpdxrtR2vzcICyCamKpod87/8M7TI/DZ5M04pXdthHbNR0ljxuQv8ek05ImaEgRBKI9s2rQJ/fr1w/vvv+9UBBGEgnDllVfinHPOwfDhw3Hbbbc5PjJlDRFByiJpmzDh+QEY/+07OKIRsGsfEF2tI848rgmuGVIVE2asxgWPLcBpd0/Bn8uB5DTgxCOAn/4GUvem4KmrmmP2x5fsjxQpTSiFDdsznDKjgiDkxVO9B6J8wLhPHgGy9phPpm/Gi+OBVCWpZII7jY9/DrO+ewz3naqQ+kNfLP7pPqfMc0kgZe0fGH7Hp9iTXQFIlLQuQRDKN7NmzXJ8UNavX++kv5x22mnFfUhCKSE2NtYxSR0zZgyefvppnHTSScjMzERZQtJhyhLZ+5Cy9jf88eHVuPEdYNZDwHn3TYInpio8ldqhm8eDjLW/IGrlC/jo22lY+fVO3H3HLUis1giq3inwhDIx+6s7sTnla5x789v43JuFhp1PR8UWJ6M0sG7Kwxj3dwgnDS77Zj6CcEhEV0bPtpXxwOe70a3/beh81qu5T+3b8g/SMoGadZvJyRXc8foQ3/l2dE5IxKbxI3DCzQ/i3D5Po0eXdjh+8BBEJdQA6gwGYmsBvujDeiaXTv8YCTHAFbe/UqrTOgVBEP4rWVlZOOOMM5zqL9oMtnbt2nJShYPC4/E4FZXatGmDCRMmIDr68N7TixoRQUozgTTA40Nw51yorBT8+MwgTFsOvPs7MOKEiki8ZHce88PYhgOBhgNxfre1OPmq6UhsdZbzeE4CSZfhn6DLGduQemI9nH/bh/h85IdIOOI0+Hq8DMRUz+u1sW0KQlunYumanajbohcqtiw+lXnbgi9xdEugU68Ti+0YBKGkc+cLU9AgsT0qqZXhBwOpePTeEc6vSTXNFBpBiEiLa1Cnzgn4sd5TeOnVd/Ho2zMwc+YMPHQGMHYCkJhYAX2G3YD6xz502E7gyqXz0UwX1qk7RL40QRDKJTptIS0tDYmJiU7lsCZNmjir+oJwqAwaNMj50Xz66aeoVKlS7t+lGRFBSiuhAN6/rSk61diCK98CYqOA7CDwyx1A05rAaTe/G7H6Qw6eCg2R2MqlPn1sDYz9ahmwdzkw83Jc9dAXWLvjC3RtmYQHX/oJnqhEZGcHsHbyg/jj169w3lHA9U8AW/eMwXWnNsVlD0+Ep0IDHG56NM3GGyMbIK7HdYf9vQWhtOCt3A7Dh7YFgqvDD+5diftOBc7uUxme6r2K8/CE0kSFRmg97EW8OOxFhNK2YueqP6BidiLw+wMY9fFGxH3+MGZNORIJTQ+PSemgNqnoWrWqE/EkCIJQ3tizZw/OPfdcRwj56aefnBV8QSgslFKOqe7XX3+Np556yimxrKNFSiviCVJKSV74Ee7/cIvz+/WDgLho4K1n70TcqUtx2esKlVv9xxSWCo2A2gOAk1Zj5MjrcfqxDfH9zD149NpeCH3fHjec2xl9rvgKkxcDvmYX4pfvP8XTtxyP179bidvObwPsnofDzYvfbMIP80qZj4kgFAN/rK2Ja19c5aTQabL3rMaEBUCrEx4FvKKNCwePN74mqrc7FZ7ml+PaVzZg1bxxjiA/7r07D8/pVArR6cvRtEXbw/N+giAIJYgVK1agR48e+OOPP5wUhtI8ORVKJh6PxxFBbrnlFtx000245JJLSrVPiIggpZCMLX9h7CMXomNDoP3pr+Hsp5Pxw8w9aH78aKBiIZvBeTxofdJzuPSZNXj7yavQpX1T/DIfmL0a+Oi2hnj5wynw9HwHnoZnYsD1P+H7z17F4HaZwPg+WD/xnsNnmKcUZi5Nxba9MoEThANRsVYbR/RQyQucvzevXYgr3wS8xRDBJZRNPHUG4n9PnYlhzRdh3UdHF/0bZu3GsMdTMH5RXNG/lyAIQgnin3/+Qa9evRAKhTBz5swykaoglNwyuo8//rhTbejjjz92xJDSiswYSxtKYfobQ/D8OOCte/sDzS4/bG/d6YxXnP9TV/2M329IRFTto/JsU6PLFTi2XkvsHXcSjj7zYbx0ywQMvXUS4CvifMTAXiSnKiRUSCza9xGEMkDzDn2xL+NFbFk+FbWr98CmdctQqxLgS2xU3IcmlCFijxiFKZM+ww0f/IG/TlgCb6VWRfdmaeuwcTdQt4EY+wqCUL6YNGkS6tWrh19++QXVqlUr7sMRygHnn38+GjRogObNS6+PnESClDaS56Nfk23458kEDLrqo2I5hIQmx0cUQHKp2ReJZ6/Fm6P6YOQz0zHihCTsW/Gt42NSZGTuwu5UICFByuMKwoGIrXUEGtcAFv/9h/P3pvWrUUdXxo2vLydPKDwqtUfPy751qg79/et+Eb2oSN2+DHvSgDqNWhfp+wiCIJQUtm/f7vw/cuRI/PnnnyKACIeVPn36OFWHtm7diosuusjxpClNiAhSylgw+XXc/AFQbeg38MSV4FKw0ZXQ//oJ+P7167A7NYT5Hw5D4NNK+Ov9c7F7/vtOREuhkrULN58A1KurSwMIgpAvCY3w7EVx6OT72vHviQ5swZEt4oGoCnLihEIlqt5ADOgQhR+/+6pIz+zmNQscg/BKtYow2kQQBKGEMGXKFDRt2hTffPON87dUgBGKi40bNzrtsH///ti1a1ep+SJEBClFZGz9G2+//iJSs6OA6r1R4vFGofVJz+PD7/9Bz+Mvw4KtlXHOrR+jx6ALMOG544BQsPDeK2sXTjkSqFipBAtDglBS8HjR5ZTHMWsVsHDcaAxtuQ6jrigFfYpQ+vDF4IT+PaBS1wNTTi2yt2matAV/P6orn0lKlyAIZZupU6di8ODBOPLII52JpyAUJ0cccQQmTpyI1atXY+DAgaUmIkREkNKCUnjq1kH4eBqcASV80SgteCq1Brq/jk7Xr8ayeb/iyRFdccXoSdg664VCe4+9Ozei38NASlZMoe1TEMo0La7Fr0sr4OZH/4fr3spAsr9dcR+RUEYZOPxxnN0TmPvH10AgtdD3r/YsxX2Pv47YhEpAfL1C378gCEJJQRufnnDCCejWrRu+++47JCQkFPchCQI6d+6MX3/9FatWrcLQoUMdk96SjoggpYXdczGw+VZ8c3tFnHjtxyiVeP3w1DoWJ906AaPPjUPUqpcLLS0meecmrNgCeKOTCmV/glDm8Xhw4uAB2LUPGD8fiK7Tt7iPSCij+Gr2RFSHu3Dy0wrp6ycX+v73rp+GNyYB6U1vdSJPBEEQyiJKKdxxxx1o3769I4DEx8cX9yEJQi4dO3bEuHHjcM0118DrLfkSQ8k/wvJExlY0T3sbSFtvPDz740tx18VdcGQT4MjLxsOTUBelmugknD38KsRnLkf2pkmFsst9e3aiQiwQ9IqngSAUlN6XfoKZf6/EksULEd/0RDlxQpHRoNMwVEsEZv/2WaHve9e2dYjyAYn1uhX6vgVBEEqKAOLxePD555/jxx9/RIUKMt4VSh5HHnkkzjnnHKe9vvfee8jIyEBJRUSQEoR33Sf49H/f4LRjm2Lue6di9/jhUB9H45Exb+GdKcAjXwOoeiTKBM0ux5kvAKNvPR3I3vufd7d3z04kxgHZHlHFBaHA6LS6Ck2ApDZy0oQixVPlCPRoEYUZ06YU+r53bt+IKhUAT2yNQt+3IAhCSTCe1JU41q5diypVqiApSaKehZLNqlWrcOWVV2L48OGOIFISERGkBBFqfh36nHo7jurcEKfe8hXanfUBvp+draPW8cuY3rjl6fFOCHuZIKk1xjx8E94Ytxu7F33yn3fXsl40XrwQCEBEEEEQhBKH149jerZF+q41wKafC3XXlWPScKH29Y2pVqj7FQRBKG7S09Nx8sknY82aNYiJkXQ/oXTQtGlTfPTRR07k0sMPP4ySiIggJQmPF/sSe+Kml5dh4ayJmPnzWJx42TP44vP/od3FUxDboGw5QDfrdwta1wEmfv/uf95XUkwmujfTkSBxhXJsgiAIQuFy+lVPYdQpQOivGwp1v02qZeOGwSKCCIJQttAr6JdffjkWLlzolCCtVatWcR+SIBSYU045BQ888ADuvfdefPXVVyhplDoRJDMzE506dXLy4ubNm2c8px+zf8aOHYtSh8eD+IbHoG63K4FWNwANTkeZJK42zurfCBlb5wCh7P+0qw9/XIjL3wCCiC20wxMEQRAKkVrH4Y+9g3HCPUuBtE2FttsffluMt6fGlqqqaYIgCAfiySefxIcffoi3337bKUMqCKWNUaNG4fTTT8cHH3yAkkapE0Fuu+021KlTx/V53VFs3rw59+fCCy88rMcnHByXXnIJTu6Ujp2TR/6nU7dnTwp8/uiyky4kCIJQBmnVdSjmrwd2Lf2u0PY5d+lWLN8uArggCGWLNm3aOKkEZ511VnEfiiAcErpKjDZI/fTTT1HSKFUiyE8//YRffvkFTz31lOs2lSpVcsLFcn7i4iQ9okTT4HRMWQKceNUrUMmLD3k3e/elIjFBciUFQRBKMlVbnYgWtYDpk78stH3uSt6HKpUqFtr+BEEQipNt27Y5qTBDhw7F3XffLV+GUKqJi4uD3+/H1KlTceaZZyI7+79F/5c7EWTr1q1OXtz777+fb13sa6+9FtWqVXNK9OhUmFAodFiPUzhIklqj7wWvYOMuYM1fHx/y6dubmo7EBBG8BEEQSjQJ9dGrbWXMmPoLkGqWgz8klMKuPWmoUrlSYRydIAhCsbJ7924cddRRuOuuu+SbEMoUSinHG2TkyP8W/V9Y+FFKTtpFF12Eq666Cl27dnUckiPx0EMP4bjjjnMUp19//RU333wzduzY4eQj5ecxon9ySElJcf7XKtXhVqpy3q+kKGSHi6imZ6F7s2sw8ZevcUHfew5pHzcM9iEQ2wAzyuH5KyzKa/srDOTcyfmTtldwbrrhGlRc+QhCM69C8Oiv/+PFtwdndVdo0KnxIfVdcu3+h1Mv94xSff7kXl/yCAQCTurLrl27cNlllxX34QhCodK7d2+8/PLLuOKKK9ChQwdnXl9uRZD777/fcY3Nj1mzZuHPP/90xIk777wz321Z7NDmqZoHH3wwXxHk0UcfjXgMOu0mv4iTomT8+PEob/RoXxub1izCzz98g5An6qBeGx3chfZ7twNR9crt+StM5PzJuZO2V/ooXdftkYhdUx/zfh6H1nu+gTrIPp+JD23G4E7A8igPfvzxx3Jy/koWcu5K5/lLS0tDeUfPAXTEhV6ZfvbZZ4v7cHDrrbdi4sSJzhxElxgVhLLG5Zdfjn/++QfXXXcdWrdujb59+5ZPEUSnrpx99tn5btOoUSPHFGj69Ol56mPrqJDzzjsP774bucRqjx49HPFEp9LUrFkz4jZaWLnpppty/9bb169fHwMHDkTFihUPuyqvb4YDBgxAVNShDwpLI97GV8O34B5MX/cIulw146AMTn8YMwjdHgPG3lkZaIlyef4Kg/Lc/v4rcu7k/EnbOzjmpv+E9157FXOfSIKnZr9DPn2enTNw+knA4w+1wAnHnnDQr5dr99CRc1e6z19O5HN5RS+yvvbaa86KdElAR7BrIeaFF17AscceW9yHIwhFxpgxY5z+JzExEcVJsYog2rtD/xyI559/3hFCcti0aRMGDRrkOM12797d9XVz585FbGysY5bqhhZWbHFFo29IxTURLM73LjaanI/F4+7BAx/Mw0+XbAIqNCrwS3fv2oV+rYHB13yIH3+dUT7PXyEi50/OnbS90kdpu26P6Dcc2cFXsWzG/9DutAGHvJ9A5k5MWwHEV6z1nz5/aTt/JQk5d6Xz/JXn9r5v3z5nEfX111835hfFSb9+/fD555/j1FNPLe5DEYQi73tyAhi0d6euIFMclApj1AYNGqBdu3a5Py1atHAe16Fi9ertT4H47rvvnM5swYIFWLlyJd544w3HUVnnHUUSOYQSRoVGqHHcS/hnPZC8asJBvTQtPQ1JFWKAmKpFdniCIAhC4eGv0QM9W0Rh1i+vA5sPPR1gz/Z12hsVlWs0lK9HEIQCMWLECAwZMgT9+/c/4LbaN1CvWvNPYbNs2TL4fD6cdtpp8BxEJLQglGZSUlIcE2BtlloclAoRpKCqkjZb6dmzpxPa9txzzzl+IE8//XRxH5pQQKo2G4CG1YA5f/xwUOdsQMdYXDZIKgMIgiCUGrw+nHrS8RjQDsCKsYe8m10L3kd8DBCbVKdQD08QhLLJJ598gjlz5jh+IAVBb5eUlJT7o1PmCxM9AdTeCPqYBKE8kZiYiBo1auDqq6/Gzp07D/v7l0oRRPuE6IoxOeanmuOPP95Jf9m7dy9SU1Mxf/58x+hI1yUWSgmJzdCxUTSWLp5/UC9rUSuILi0rF9lhCYIgCIXPsJu/xT+7GuHNTyYe2g72LEbNwCy8egmAuNqFfXiCIJQx1q9f78wNPvjgAyddviBo78A9e/bk/uh9FBZ64qcrZAwdOhSdO3cutP0KQmnA4/Fg7NixyMrKcoxSDzelUgQRyigeD567sTuuPnoboEIFftkjH2/C2HHici4IglDaSI9uhq+nJQNpGw/+xRlbcdIYoHm7bkCCpMMIQmkzhtWCwtKlS52SsIeD2bNnY9u2bejSpYuzSKp/fvvtN8d7UP8eDAbzvEan1OtCCfxTWOiJnz4PeiIoaTBCeaR27dqOGfDHH3982NNiRAQRShShpA74fcFeYM/CAr9m884MZIXKr8GXIAhCaaXjkb2xYAMQ3Dn3oF8bSN+NZZuBmGbnF8mxCYJQ+Iakr776qmMCqlNLdGR3mzZtUL16dTRs2NApn6mrthQVxx13nBMpPm/evNyfnEqT+nfty3G4+Oabb5yJn54A6omgIJRXzj33XAwfPhzp6emH9X0lV0QoUWRU7I7L33gJNyQPw1XPryrQa9IyshEfH1/kxyYIgiAULo3a9EYoBKxb8ica1x96UK/dt2er83+FSjXkaxGEEs4zzzyDRx55xBE+TjrpJNxxxx2oW7cu4uLinEgQXdjg999/d0oG9+jRwxEHmjdvXugeBLrAApOQkICqVavmebyo6d27t1MSV08ABaE84/F48N577x329xURRChRVGp7Pu69aDS+nrgEVwUzAd8BKvuEgkjLCCIhQUQQQRCE0oa/agc8MxyomL3koF+7N3kHvB5dHrd6kRybIAiFx59//olJkyahffv2EZ/v1q0bLrnkEic15M0333TSVApbBCkp7N69G1WqVHH8SQRB2I/2Bsmp3HTyySejqJF0GKFk4fGgccuuWLMdQOqaA28fTMMDpwH9uzc+HEcnCIIgFCYxVXHqUZXxwptfIfmfNw7qpdUTg/jiBsATLdXBBKGk87///c9VALE9OK655hpcdtllh+W4Jk+e7ERkHM40mCZNmmDNmgKMcQWhHBEVFYXt27fjyiuvdITCokZEEKHE0bJtFww/Wi/zrTzwxoFUNK8FVK9W9XAcmiAIglDYtLoJb0wC/p7200G9LMaThu7N9Mip8IwKBUEQigptgnrLLbege/fujgeKIAhmWswrr7ziVHl97LHHUNSICCKUOKrU64DrBumE74KJIEc/CPyxoOgVQ0EQBKEIaHMnjmrpwcYNaw/qZb/+sQiD9DgpKkm+FkEoBWjjw0cffdTxA9m8eTPKG2+99RZWrlyJJ554QqrBCEIEtEnwTTfd5FRs2rjxEKrGHQQiggglj8SmuPUjYMb0Pw68bSAVaZlAfIIMggVBEEolXh/q1qiADRsPblK0NyUZsbowmESCCEKp4NJLL8WKFSscI9L+/fujPJGWloYHHnjAMULt0KFDcR+OIJRYdLSUrh41YcKEIn0fMUYVSh5xdbBuB7By1Rp0L4gIkgXEV5BwaEEQhNLKKX0bF8wHikhJ2YuK8d4DG2gLglAi0P4b48ePR9u2bXH33Xdj27ZtqFGjfFR30l4HrVu3xoMPPljchyIIJZqKFSti+fLlTjWnokREEKHk4Y1Cnerx2Lx5ywE3VTOvQIVYLYJIJIggCEJppXeP9sCafxxhG/6EAr1mX+peJCaIACIIpYW+ffviueeeQ4sWLdCgQYNyI4BotAfIr7/+WtyHIQilgsTERAQCAUycOBEDBw4skveQdBihRFKremVs3rbrgNt59q3C0+cCtdsOOSzHJQiCIBQ+i7fE4pLXdMx4wXOAL+gbhwfPryVfhyCUEt544w1HDNi6dWu5EgR02V8dBSMIQsH58ssvMWjQIMyaNQtFgYggQonk5GNb4ZwjU4FQMN/t7vk0A6kVusFfVfIrBUEQSiu+uBqYsgRAxtYCvyaYtQ+x8RWK9LgEQSg8EhISnDSYJ598stxUR9mwYQNuvPFGZ0VbEISCc9pppzmpc9pIWSmFwkZEEKFE0rJlK3RuGALS8qkWEApi6aYQ9mVKMxYEQSjN1KjbxDG5Tt1V8AoxD3y8Ha+O21ukxyUIgvBf0GaoFSpUcMweBUEoOD6fD6NHj3YERO0lVNjI7FEokexQTdD1HuDLZ89x3yiUgcxsIDY27nAemiAIglDIJFVvjCgfsH1jAUqj/0t6Rhbi4+LluxCEUsBVV12F9evXF2jbTz/9FB9++CFKO0uWLHHK4uroF232KAjCwXHiiSeiV69eTjRIKBRCYSLGqEKJpFrXkTir90P4Y9YinOq2UTADmQEgJjb28B6cIAiCUKh44mvjtcuAKrGpBXuBCiE1PYD4eBFBBKE0UL16dbRr186Z0Jx00kno2rUr6tSpg9jYWOzevRuLFi3C1KlT8cknn6Bu3bp47TVtElS6efjhh1G/fn1cffXVxX0oglAq8Xg8ePrpp51qMYWNiCBCycTrQ7Wa9bBk3WJA54F5PHm3Cabj3lOApm3qFccRCoIgCIVFbE0M0tZO/uSCbR9MR3rWfo8BQRBKPg899BCuu+46vPnmm45R6IIFC/JUg+jfv79jnlpU1SAONy+//LIT/RITI1WsBOFQ6dGjh/NT2IgIIpRYateqgWjfgv0lE6MimN8FM9CrhU4mr1ochycIgiAUFtGVceMHHjSo/h5u7PwEEF0p/+2z9+F/I4FQ09byHQhCKUGXxL3zzjudn+TkZKxduxbp6emoVq0amjZt6qz6lhWCwaCTAqONHQVB+G/s2rULI0aMcLx1unTpgsJAPEGEEssJx3TGq5cCyNweeYNgOo4bDcxfmXK4D00QBEEoTDxeDOjeCGO+z8TWuW8dePtgKhasB9KDkg4pCKWRSpUqoWPHjs4Kb7NmzcqUAJKRkeF8pv/973/FfSiCUCZISkrCn3/+6URXFRYiggglln3BivjmL303cRNBMrBpN+CLkkGwIAhCaeeEaz9FYiywY+uGA2+cvQ8XvQosWZ9+OA5NEAShwHz++edYs2aNI/IIglA4lWKuvPJKfPTRR46HUGEgIohQYkkNJeLqt/VYd3PkDYLp+6vDxEtOuCAIQqknpir6tga82QWI7gvsQ2omkFAh6XAcmSAIQoF56aWXMGDAALRooXO2BUEoDC699FInzeydd94plP2JCCKUWCpXb+j8v2vbmojPq0A6MrJ1dZgIfiGCIAhC6SK6Cl65BGhdrwBh8YFUxxg1TkQQQRBKEHPmzMH06dNxzTXXFPehCEKZombNmjj99NPx+uuvQ+miGf8RMUYVSizRFesgMQ7YtXU9akbaIJiOcbdro63qh//gBEEQhMIlqiJ+mOdB7bSVOKJ7/psGMvagWiJQIbGKfAuCIJQYfvvtN6cs7tChQ4v7UAShzPHwww871ZYKw0NIIkGEkktUJfRpCXhDqZGfD2agRW3AHyORIIIgCKUejxc/zY/GH/PWH3BTPzIw+xGgWs3ah+XQBEEoXAKBACZMmIBXX30Ve/fudR7btGkT9u3bV6pP9Y033oiFCxfC75d1ZkEobJo0aYK6desiFAr9532JCCKUXKKT8PrlQMu6kW8k27dtQ+MbgCCiD/uhCYIgCIVPpYrx2J28f0KUH6nLPsF3c7QaIiK4IJQ2dGnc9u3bY9iwYU7Zy+3b9xvgP/HEE04JzNLK+vXrnclZYmJicR+KIJRZZs2ahQYNGjjX239BRBCh5BKVhK//AhYuWRvx6Yz0ffB5JRJEEAShrFA5KRG79xxgJThjB0Y88gOufHO/j4ggCKWLkSNHomvXrk6Vh7i4uNzHTznlFPz6668ojWiPAm2Gev311xf3oQhCmaZVq1ZISUlxosj+CyKCCCUXXxy+nOXBrAWRlb7M9H2IjdLbSYlcQRCEskDnlrXQqX5W/htl78GUJcDQIxOAyp0O16EJglBITJ06FaNGjUJ0tBnJ27BhQ2zcuLHUfqalS5fijDPOKO5DEYQyTWJiIi644AK8+eab/yktRkQQoeTi8SAxIRp7XfJDM9JTEeOIIOFVBEEQBKH0cmyPZrjw6GzH88mVYDq6NwOuvWK4c58QBKF0oScuutSlzYYNG0ptKsk333yD2rVro3fv3sV9KIJQ5jnrrLOwZcsWJzXmUBERRCjRVKwQh5S9kUWQ1g0T8fu9EgkiCIJQVliyKYSnftDRHvn4ggTT8fG1QIc2jQ/noQmCUEjotJFnn302929d6UEbot5333044YQTiuw8P/roozjyyCMdoaVGjRo4+eSTneiNwkiF0SLIiSeeCK9XplaCUNT07NkTVatWxeTJkw95H3KlCiWa7q0ro1WtvKsFmqyMVKRliggiCIJQVtiV6sMXM7UIkuK+UTAdH/0BpKQfziMTBKGweOaZZ5xSsm3atEFGRgbOPfdcNGrUyEmFefzxx4vsROv31Eas06dPx/jx450KNQMHDkRqqksVwgKivU18Pp8jggiCUPTo6ksLFizAbbfdVvZFEN05aqWYf+644w5jm3Xr1jkdUEJCAqr9v73zAI+i+qL4TSf03ntHUKQ3kd67IE0piqAoRbpIUVSULlgBUVAsgH8FC6BSpYM06YI0KdKLQEjf/3cuzjrZ7CabkGQzm/P7voHN7Ozs27czs/POu/fcnDnVnCg8PJ7cYpKqaV+viHSsFun0ua17T0mPD3EU0xOEEEK8gUxZssut0LhFEFvEHRn5lcjNkBRtGiEkicifP7/s3btXK8E8++yzUqlSJZk0aZLs2bNHIzSSi59++kl69+4t5cuXl4oVK8r8+fN17LBr16772m/27NnlyJEj0qpVqyRrKyEkbvLmzat6QGJ9QSxVxPq1116Tvn372v/OmPG/0njILcTFJ1euXGpOdPXqVenVq5eGqL377rseajG5X347Hi17d96Qvh1tsXK/IyLCJBBHsF8QO5oQQryATJlzyK27cYsgEaG3JNomki7Ymt4BhBDRqjBPP/20Lp7i5s2bdhHjfkAES4ECBXRARghJGTD2r1GjhpqkJqYqk6VEEOTwQfVxxi+//CKHDh3SmsFQmMH06dNV8Z04caJkzpw5hVtLkoKz133lx9026Rt2RSRdrhjPIconwA+RIDHdxQkhhFiTHLnyyqBmItFhN1yGqoaG3BNIgjNmSdG2EUISz/fff+/2tm3btk32rsYk6dChQ+WRRx6RChUquNwuLCxMFwOU5jRz+fJlKVy4sHz55Zdq1kgISRmQgobMD1xbvF4EQZ7g66+/LoUKFdISVCNGjLCX19q6datexAwBBDRr1kwvXAhza9CgQYIubhEREbqkJMb7pfT7pmaKFC0qe0+L/Px+e2k4KKb5TWREuKQPFImIgvL+3/fF/ksc7L/Ew767P9h/7DuD4Mw5ZFgrkcjwGxLl4rcwMvy2NCwv4h+U4b6v9zz22HeewtPHXkq/L0xI3QHRFM4qxyQ1AwYMkH379mn0eHxmqhMmTHD5/IoVK1RQqV+/fjK0khASn2A6ePBguXHjhmTNmlUSgo8NZ65FTJQqV64s2bJlkx07dsjo0aOlXbt2Mm/ePH2+X79+curUKY0IMRMUFCQLFiyQbt26Od3vq6++6vTiBkU3ffr0yfRpiLv42cJk1ewukjNXbnmo09wYz1UNnSIForbId+m/FfGxjL0NIYQQF+SM2idzZ46XHj2elDu5OzndpljEj/JQ+DzZlO4NuernegaXEOKakJAQNSRFSkhai5YeOHCgLFu2TDZs2CDFisVdZcrZZCkmY41+69ixo5w/f14nY4n1wHcLPxr4TGLMSKwFMkAQifXVV19J165d7edolixZ4r22eTQSxJUAYQb1f6tWrSpDhgyxr3vooYdUDOnUqZNGh6BEDnCWiweNJ64cPYgpCIdzvLjBLTqlfxSgysOtGqXDAgICUvS9UzOPhhaTgHQZxd+hbNrF796XQ2f8pOXg1vo3++/+YP+x7zwFjz32nYHPtTzSb9B4GZoju9RzUSrz8ubtMusTkRemNhBb9mo89jwEz1tr959jWkdaAGMCCCBLly7V0prxCSAAA2NXg2NUtvn5559lzJgxydBaQkh8YMwOY2VcSw0RxF08KoIgFC2+BqMqjDNq1qyp///5558qgsArZPv27bFKVuFHJk+ePAm+uOEHyVNChCffOzVy2ydYQm/dltwOffLz9r9ly06Rj4fHXM/+uz/Yf+w7T8Fjj30nwdklUzqRkNs3XP4OXrp8TT75VWRwUGYcNDz2PAzPW2v2nyfvM9955x2n6zFpmS5dOilZsqQ8+uijmvOflKA8LiK9v/vuO/UZvHDhgq7HrDGMWhPKsWPHtL0p4WFCCHEOorrMdhiWEEFgZoIlMaCMFsiXL5/+X6tWLTVA/fvvv+3rkBoDgaNKlSpJ2GqS0nyy5racu3BVZvSIuT48PEIC/JP2B5IQQogHCcgsmYJFbv1zw+Umd+/clmCM3/wSPmghhKSOFHcYiiIlB5HdiNBATj/S0FH58dKlS1K8eHFZt26dzvQmFR9++KH+7+jfgVK5KKSQUB588EG5ePGi+PoyJZsQT4F0mMRgibMWeXa4YKKm+MmTJ2XJkiVaVxzKq/HBkb7ywAMPSI8ePVQgWbNmjdYfR0ndtJbr6G0EpwuWkLuxDbwQ5ROg5WEIIYR4BQGZZWRrkXI+v4iE3ytf6UhoaIikgyc6RRBCLMmbb74p1apV00iKq1evyrVr1+To0aNa7nLWrFny119/aYS3ORU+KYDY4mxJjABiVClEtApL4xLiOXAOoxjK3LkxvSNTRATBReD27duSXCCaY/HixarcQugYP368ihswQTHARWj58uUallanTh3p3LmzOlFPmzYt2dpFUobg9OnkblhkrPUZ09kkbzamDRFCiNfgFyz1qxWXI2dDJeLcGqeb5M3qKx2qIpaVkSCEWJGxY8fq5GaJEiXs65ACg3t2ePUVLFhQpkyZIps3b5bUCirYIJr9448/9nRTCEnT+Pj4aCTZxo0bkzcdBiFju3fvVk+OJ554Qi9WM2bMkMjISGnYsKEsWrTIblSaVKAqzLZt2+LdDlEhP/74Y5K+N/E8GdJnEJstWiQ6UsT3v0P26SZZRSJcm94SQgixGCiP+eBE6dWnmxzockWyO9mkXKEgKdccggkruBFiRZC6jnGDI1hn+HQgx//WrVuSWkHkCtpnFnIIIZ4B1hcwO062SBB4bsBU6PDhwzJo0CDp37+/lp997bXXtLzQkSNHVN0lJCnp3LSsfNYfsntIjPV7jt2U309Hs7MJIcSLCEqfFVqIhNxy7guyee9Zmb0adzDIiSGEWI0GDRpoWrvh7wfwGOMKTKiC/fv3u1W9xVMYbUdlCkKIZ0ElWegQCclMSVAkCAQPhH1169ZNdu7cqbl7SFNBqVpQoUIFee655xLeckLi4MZdf/nzhEjVyDuaL27wzebrki4oUCqy9wghxGvwCcgo6QPvVYhxxtHT12TbcT95DkoJIcRyYCwBDz/M3hpVahAF0qhRI3t6CQxSp0+fLqkV+BSWKlVKK8sQQjwLriXwBoE4WbFixaQXQWBU9Mgjj9gVF39/f3VGNnjooYc0xI2QpOTg6Tsy4jORLYNjRoJERERJpgweLXBECCEkqQnIKA8XQfTfXadP3w0NlXRBvPYTYlVgerpq1SqduUVaCQYvZcuWlTJlysSIFknN/P7776w+SUgqAZ6hK1ascFsAAQm6i0A1DpiUGgQGBsaoMw5RBEZBhCQlwcGZ5G44pgnuxFgfHhHl0Tr3hBBCkgG/DPL1YBEp6Nz4NCwsQtIFsjIYIVYHwgcWK7Js2TIVbwghngfjwRYtWujjf/75x63XJHgq5dChQ3bTIpz85vybK1euJHR3hMRL+oyZJSQ8tidI8dw2KZCXxniEEOJV+GeQH3aLPJjxvBR9OPbTtcsGSYX8mTzRMkJIEoAJU6TYr1mzRi5duiTR0TH93dauXZvq+zk4OFgyZ/4vRZsQ4llwPUE0yCuvvJI8Igjy9czKZ+vWre3labCetbJJUpMpczYpkC12JMjAZn4iOQuwwwkhxJvwzyBz14r0zXNOijp5ukZpfxEbfhQIIVZk8ODBKoK0atVK/QStOHbo2LGjrFy5UqPgCSGe5/Tp01p6e9iwYW5tn6Az9+TJk4ltFyGJpkCB/LJ2DESQmJEg3++4K0XKhkrFe0bihBBCvAH/DBIMY9Q7MYVvg3krL0u6dMHy5L05GEKIxVi0aJEsWbJEWrZsKVblxIkTFEAISYXmqKgsleQiSJEicCojJGWJlHTyv60i7atcl3TGSptNlmyLlGZBIawOQwgh3oSvv6QP8pWQEOciyB9n70rOHP/5kxFCrAU8BUuWLClWhqVxCUl95qjwLoVpcZKKIPv27XO7EagSQ0hS4eMfLEM/F2nw5DWTCBIl4ZH3fkgJIYR4F9VLp5N8LjJeYIodGMBrPyFWBeHqs2bNkvfee8+SqTCgaFFnyXqEEE+aoxYqVEjOnj2btCLIww8/7LbvByvEkKTELzC9+PmKhIWa0mGiwyUiiiIIIYR4I8+3yiESbJe9YxAWHilBQawMRohV2bRpk6xbt049NcqXLx+r0t+3334rqZ08efJ4ugmEEAeGDh0quXPnlnfffVeSTAQx+4Hs2bNHhg8fLiNGjJBatWrpuq1bt8r06dNlypQp7u6SEPfwDZJAf5FwBxHk0bIiRfJnZS8SQoiXsfagSETUBWnWLPZzvR8VyVYkryeaRQhJArJmzSodOnSwdF82btzY000ghDjQv3//pC+Ra/YDefzxx+Wdd96JYWiEFBiEoIwbN07at2/v7m4JiR/fQBU8Av1MJdSiw2UIykGXys8eJIQQL+O349Fy5fotiaWB2GxSs0SESKEcnmkYIeS+mT9/vuV7sUSJEp5uAiHEiWExgjXcwVcSAVxXixUrFms91h06dCgxuyTENX5BMv9ZkcJ50/+3Ljpcpi8XOXrGuXEeIYQQ65IhfToJuRse+4noCBmwQGTl9queaBYhhCghITErFhJCPM8333wjTz31VPKJIOXKlZM33nhDQkND7evCwsJ0HZ4jJEnxDZKP14ucOXfpv3XR4fLtbyKXbkSwswkhxMtIly6dhML92pHoUPnrqkhYVKJuXwghqYT//e9/0rlzZ6lZs6ZUrlw5xmIF/Pz8PN0EQogD+fLlk1u3bok7JOouYvbs2bJ69WpNf0FOHJaCBQvKqlWr9DlCkhS/QPlkvcjpc6aZvyjDGJVlEgkhxNt4sGQOqV82KvYTUWH/VgZzbppKCEn9IKUes7UwMEToevXq1SVHjhwayt6iBXKdUz8oxUkISV3kz+++TYLbniBmcLGCUernn38uR44c0YoxXbp0ke7du0uGDBkSs0tC4jdGDf8v8khuHdMb4QDeCBNCiNdR48ECUiOzTdNfxNdUOSL6nggSFEQRhBCr8sEHH8jcuXOlW7du8umnn8rIkSOlePHiMn78eLl27Zqnm0dIimGvuhp6WeT4xyIX14pE3BQJyCKSt5FI8adF0uVyqzorEY0ESVYRBKRPn1769evH/iYpJ4KEmUSQ3UOkxyMi2XKwQgAhhHgbe/68I6t+Ehn5eGhMESQqTKY/IVK0fCFPNo8Qch/89ddfUrt2bX0cHBxsD1/v0aOHpse899577F/i9ezevVuefbavfDu+nBS6vVjEhgIQpiIQF9aI/D5WzmTsKo+9dljmzJlrmXQxT0aClC5dWo4ePRrvtkyqJakfvyBpUVEkX/b/boQPnomQVpVEitYf5dGmEUIISXqu3LLJqgMQPe7GfCI6TCoVFcmWLQu7nRCLkjdvXrl69aq9+uS2bdv0MaLMMeNNiLeD4xwCyM6du6X+M1/ImSuRMQUQJVrX13/mc9m5c5c8+2w/nh/xkCVLFvntt9/EHSiCkNSPb6C82EKkYomM9lUL196UpQfyi/gxJJoQQryNoHTBEgrf6yhTBCCICpOqY0V+P8aQeUKsSsOGDeWHH37Qx3369JEhQ4ZIkyZNNLW+Q4cOnm4eIckOUlu+Hf+AFM8tcuKSSP03RM44FD3D31iP57EdIkaYEpN0JDodhpAUwzdQ5q0TKV/5vNS6Fz0pUVHR4u9PDY8QQryRoHTpJSzCeSTI7VCRwKBgTzWNEHKfwA8kOvrerPdzzz0n2bNnl02bNkmbNm30b0K8ntDLUuj2Ilk/9j+hA//j70I5Ygsguv72IpHQt0XS5fR061M1rVu3dms7jiJJ6sfHRzb+4StHTv838xcZFc3yZIQQ4qUULZhHnm/sPBIkDNVhKIIQYll8fX3F3/+/eViUykXFmEGDBklgYGCKGLMWK1ZMS3FXqVJFNm7cmOzvSUgMTnyiHiAQPCBwmCNCthx1IoDkQA5NtMiJj9mR8RAWFiYpIoK4+0aE3A+BAb4SEYFpwXsUzOEj+XMwFYYQQryRPHlySu96sUUQW1TovRK56dJ7rG2EEOuyePFiefHFF2XMmDFanrdu3bpalhdmrYSkGDA9/dcDxFEIqTPBiQCiRItcWMsvKR7MAmuSiiA///yz9O7dW0qUKCEBAQFaJSZTpkxSr149mThxopw/fz6huyQkXgID/CQ8LNz+97DWgdK1kfu1oAkhhFiHi9cjpNNMJ+kwUWGy+RWRvLlzeapphBALM2PGDPUheeaZZ6RcuXIyc+ZMKVSokHz44YeebhpJS6AMrgkIHQv7x9wEf/8ngBivu5H8bbM4SS6CLFu2TMqUKSO9evXSMLYRI0bIt99+q6LIxx9/rCLI6tWrtc438vkuX758P+0nJAatqmaQqqX+i/xY/Xuo7D/pcHNMCCHEK7D5BsmWYyJR4Xdiro8KlYzpRPwDGQlCCEkY4eHhsmvXLmnatGmM9fh7y5Yt7E6ScgTErHAGD5AeDjoc/nY0S5WArMnfNouDII0kNUZ98803Zdq0adKqVSsVQRxBPh84d+6czJo1Sz777DMZNmxYQtpMiEtaVssiYsoTXbQ5XGqE3JIH2WeEEOJ1BAVn0v/DQ2+J2QL19+WvS6uxIscb+sRYTwgh8XHlyhWJioqSPHnyxFiPvy9cuOAy7d+c+v/PP/84XU+sifEdpvh3maOhyDl40djk7HWRVlNEzt0UKVNAZO4zIv3miZy6ItJkssjykSIFs+FFPiI5GqCxKdtWizFlyhT1+kkyEQRRHpkzZ453uwIFCuibE5KUfL7hrtgkXHq0+M8Y1d1wJ0IIIdYiXfp7JdFDQ0wiSHSkTP78gJTOJxKUt6Ynm0cISQIuXbokf/zxh5b9LF26tOTOnTtF+tWxzKjNZnNZevStt96SCRMmOE2rgbEq8Q7efvttD7zrS/ZH3fr+t3adw9+fXxcRLOAEBJBJKdhG6xEa6mCo7gK3R5HZsmWTv//+Wy9QqO+NVJisWRmSQ1KGU5dtcjc0xP53dLRN/PxY3IgQQryRoODM8sFTIsEB94zjlOgINUUd8ERd8c1U1JPNI4TcB4imeOGFF2TRokUamQH8/PykS5cu8v7770uWLDFTBZKKnDlz6vs4Rn1AjHGMDjEYPXq0DB06NEbb4SGCde5MDpPUDSJAIIAMGTJEgoKCUvS9z67sK60GLNGIj6I5zREf/z7/b4SI/fn3OkvBFh+laButyNSpU5NWBMmYMaNcvXpVRZD169fHqNRBSHITGBAgN//5VwSx2aRyUZsUyXcvXJoQQoh34RuQXtpXxV3KvQGSYouQDlVFyhXL7smmEULuE5iS7t27V3788UepVauWRmHAk2Pw4MHSt29fWbJkSbL0McrvIkx+1apV0qFDB/t6/N2uXTunr8HA2Nng2NV6Yk1S+vtE9FHXiYfkj3NhWgVm1ajYJqglct5bj3K5f5wT3X5Hu0CXUUvkv/M5SUWQxo0bS4MGDdRJGeDi4aqW99q1SV++p2jRonL69OkY60aNGiWTJv0XEuTsoIDbM4xaibUJCPCX8Ih/b4Zt0fIi0mIK5/N0swghhCQHfsHS6E2ROdPOSMnS/66LjpQedXFnmDIh84SQ5GH58uVaWOGRRx6xr2vWrJl89NFH0rx582TtdkRw9OjRQ6pWraoCzNy5c7U8LscKJCXBmHXOnLny7LN95dvxD0ih24t0fGOUzb2HrxTK6Svr53WVx147rNtTAImfyMjIpBVBPv/8c/n000/l+PHj8uuvv0r58uW1PG5K8tprr6lCbI5OcWT+/PkxLqDJFVJHUpam1XLLjYL/WiTbImXBryJVHrklD/73+0kIIcRb8EsnV26J3Llz67910REydolIx043pFINTzaOEHI/5MiRw+n9OdYh/T45QcoNItsxpkCaf4UKFWTFihVSpEiRZH1fQhypXLmy7Nix856wETpD5MQnIhfW3iuDiyoweRuKFH9aCqXLJTtau/atITFxN1vFbREkODjYrpLu3LlTJk+enOKeIJkyZZK8efPGuQ3aFN82xHqUL55DJKMRCRIpS3eKZCkWwuowhBDijfgFS5C/SOjdkBjpMJuOijS8bUqRIYRYjrFjx2pEBipJ5st3L6oXPh0jRoyQcePGJfv7P//887oQ4mnswka6XCIPjLq3xLUdSbJIkEQ5S65bt84jpqgQXqAeP/zwwzJx4kSt9+3IgAED1PioWrVqMnv2bImONocVEavy/bZrMurzEA2HFluURNtgosXqMIQQ4pX4pZMMQSKRx+aLhN+4ty46QiIikR7pPBWXEGINkKq+bds2jb4oWbKkLoULF1ZfkDlz5ugMubEQQkhC6Nq1q1vbuT2KhPfGoEGD3EqB2b59u9bibtWqlSQVMEvCxRBhcjt27FC35pMnT8q8efPs27z++uvSqFEjjVpZs2aNDBs2TNsBxdkVrup/I5Qmpc1fjfej6WxsgoIzyf92iHRb8pSUbzNNIqNEfPz8YvQV+4/Hn6fgscf+47GXxPjnlGcbidQqJRJ57aDYclQXCQ+RyOjY1/77gecu+85TePrY8+S9Zvv27T323oQQ7waZK/ANjQ8fG+xp3aBnz56aM/f4449L27Zt1VAoV65c9rCTQ4cOyaZNm9Q7BDl2CHGrWxcOZq559dVXndbeNvPbb7/peznyzTffSKdOnVTkQHSIM6ZPn645fzdv3kxwG7788ssU9zwhrgmIvinz3uwlTWqXlqINXpZT3/eWkhUekZASw9lthBDihaS/sFimf/CVjHllolzzKy+Zov+Sa+sHSd4K7eRq7qc83TxCLE1ISIh0795d75FZ6tV9MFkK7xL2m3eAiXBM9L/00kus9uMF3L17V1auXCkdO3aM9xx1OxIEosa+ffu0fvcTTzyhO0atbZQTwoUUVKpUSfr16ye9evVy60BC6kp8ISuoCuOMmjVr6v9//vmnSxEE2+BidfHixQTX/27atGmK/yhAlUdZnyZNmkhAQECKvneqx2aTNR/1kgJ5s0vjhg0kIEQkqmRFia7U0r4J++/+YP+x7zwFjz32nTPObTogB86I1KpeWWx5Gonc2CsBd0WiyleS6Af+u/bz2PMMPG+t3X9G5DMhhHgLKOACAcQdEmSq8NBDD2muHrw2IIicOnVKFRd4cMCnA/8nBGyf0NcY7NmzR/83DJVcbZMuXbo4/Utc1YXGD5KnhAhPvndqZnoPf5ECeUT8fOTVb0S6dLsl5arH7if23/3B/mPfeQoee+w7M8HpM6j/k090hPjjN9FX5LG3Raa+fkdKVEza30gee+w7T+GpYy+l3zN79uxy9OhRve9HantcRo/Xrl1L0bYRQrwDZKO4S6KcJXHhqlixoi4pwdatW9VAqUGDBhqChhSZIUOGaFoOjJTADz/8oM7SqPkNTxCYt44ZM0YjU9yJSiGpn01/+EiuiBtSpnKkrNov0riV5/JZCSGEJC+B6TLo/xFhd8UPD6Ij5MBZkcjoRHm6E0I8yNtvv61VHsHMmTMt/10gCp5pRISkLs6fP588IggqrWDx9//vZUg1QWTInTt3pE2bNvH6gCQGiBiLFy9W7w7kbsFNum/fvjJy5MgYivYHH3ygqS1oY/HixdUP5IUXXkjy9hDPsGCDTWrcuiJl2kdKVDSrwxBCiDeTMWMmWdhfxN836r/qMFEiAYGc2CDEaiBV3tljq4KJ17x583q6GYQQh0gQZIDcuPFvVbmkEkH69OmjYsPcuXP171u3bmkp2tDQUE1Lgcr73XffScuWSZOra4CqMIgEiYvmzZvrQrwXfz9fiYyK0hK5UTYRf3+mDBFCiLcSEJReGlUQEUMEsUVqZTB/lsglxPJgwhK+fpcuXdLHZh599FFJ7WASmBCSukCgBuw7NmzYEP+2Cdnx5s2b5b333othlorKMMeOHdM0FZSjmTp1apKLIIQAPz8fiVYRJFIGNhUplD8bO4YQQrwUm0+AlBsu8uvSy5Kn2L1IkE/6ieTKwWs/IVYGE5uoTHP69GlxLFKJlPso3OulcgIDAz3dBEKIA8OHD1crDOgS8ZGgxNpz585JqVKl7H+vWbNGHViNN0J428GDBxOyS0Lc5oFCAZI/u7+KID3riuTN5drwlhBCiLXx8QuSkHCR0Lt37q2IjpAmD94zTCWEWJfnnntOqlatKgcOHFAT1OvXr9sXq5iiVqlSxdNNIIQ44CiqJpkIgkorqAZjVnKNUrXG87dv307ILglxmxdaZpYOdbJqOswT74ucPMfyboQQ4rX4BkqAH4xRQ/XPu3dvywMjRP65Q1NsQqwMIsjffPNNKVeunObvYzLVvFiBK1eueLoJhBAHcE2ZNm2aJLkIgmowCxcu1McbN27UfLiGDRvGqM2bP3/+hOySELdZvS9CNu+/LhIdKbtOioRGuK/2EUIIsRh+QfdEkPB7IgjEkBshIr7+NEYlxMrUqFFD/UCszIsvvujpJhBCTMCjFFoESnC7Q4I8QcaNG6d+H0uWLFH31d69e6shqsHSpUulTp06CdklIW6zel+4ZM18U+rAHC8a5jfMxySEEK/FN1C+GypSJH9G/dMQQwIC0nm4YYSQhLJv3z7744EDB8qwYcO0wsqDDz6oRRfMwNgwtbN3715PN4EQ4nCNgVfpww8/LEkugjRo0EB27dolq1at0rJQjz/+eIzn8abVq1dPyC4JcRs/rQ4TrZEgqBDgZyrVTAghxMvwDZTCOUX8fe6ZJEZGhOn//iyRS4jlwBgBpqfmnP2nn37a/th4zirGqGfOnNGUmJw5c3q6KYQQEdUoUB2mfPnybvVHgkaRuFjNmjVLBg8e7PR5uLESklz4+fpKFEQQW5S801Mkd04aoxJCiNfiGyiN3hSZ+vIpqVNZJHvmIFk1WsSPkSCEWI6TJ0+KNw66mjVr5ulmEELk3vlYoUIF9ShNchHk008/lUmTJkmmTJnY2STFqVIqg0RHRWh1mLYw5c54L0SaEEKI9xuj+vlESoncWB8zdJ4QkvopUqSIeBPwHTh16pSnm0EI+Zd33nlH/UrdxTe5ys4QktS0q51dOtRML9GR4VJ1rMjlayHsZEII8XYRJCJc/zx+6oJUeAlx8xRBCLEymFRdvny5/e+RI0dqlZjatWvL6dOnxSoVbp599llPN4MQ8i/p06eXYsWKSbKIIAC5eoR4gp9335H/bb4pUZERcv46DkY/fhGEEOKt+AVJoL9IeHiY3RPEH3ctvvSDIsTKoDxucHCwPt66dau89957MmXKFPXXGDJkiFgBmLlycpiQ1GNU3Lx5czl//rzbr0nwnUTp0qXjFUKuXbuW0N0SEi/7T4XJ3xdDpVUkzfEIIcTr8Q2UxQNF0pVGDsy9iBB/aN9MhyHE0sBUtGTJkvp42bJl0qlTJ/UVRIXJ+vXrixXYuHGjPPXUU3L48GHJkSOHp5tDSJpm27ZtsmbNGsmePbuEh9+LHk1yEWTChAmSJUuWxLSPkPuuDhNti5bIf0Oj/fwYEk0IIV6Lb6DcChWJDgmRLP+KIEiPYToMIdYmY8aMcvXqVSlcuLD88ssv9ugPGBrevXtXrED+/Pnl8uXLasbYtGlTTzeHkDTNzp077aaoySaCdO3aVXLnvjcrQ0hKgrJHKJEbHOgr3w29l/tFCCHES/Hxk+FfiLRs9Jc82UykYskcsm4MI0EIsTpNmjSRZ555RipVqiRHjx6VVq1a6fqDBw9K0aJFxQrAeyBz5sw6+KIIQohngRhZpQqqZkjyeILQD4R4kupls0izh/w0HLpaCRH/wCB+IYQQ4q34+EhggK9E/DurEx4eqpEhTIchxNq8//77UqtWLY2k+Oabb+zpJBjIdOvWTayAr6+vVK5cWdtMCPEcoaGhcuDAgQSLIAmKBKEBEPEkNR7IIZLbVy5dviYPvyDy116fhIcyEUIIsQyBAX720NbfDpyRce+LbHiaqZCEWBlUgoEZqrOUeytRvXp1+eyzz3R8xIliQjwDzr1FixZJ1apVE/S6BI0ho6OjE9ouQpKMn3del4MH7kq35/71BPHnjTAhhHgzGdL5idii9DEiQgJw18ISuYRYmn379rkczCCnH14hQUFJG+176tQpef3112Xt2rVy4cIF9fR48sknZcyYMRIYGJiofQ4cOFAGDBhAAYQQD4JrRceOHRP8Ok6kE8tw/lq4/H4qSh6PDBdfH6SLUwQhhBBv5u0+2UUy5NTHERER/5bI5bWfECvz8MMPxykcoPxsly5dZM6cOSqKJAVHjhzRyVzsE5VpED7ft29fuXPnjkybNi1R+yxYsGCStI0QkngGDx6saXQ1a9ZMPk8QQjyJv5+/REXbJCoyUvxw5PpQwyOEEG/mz4s+cuLcLX1ss0VKBkwOUwQhxNIsXbpUSpUqJXPnzpW9e/fKnj179HGZMmXkyy+/lI8//lgjNsaOHZtk79m8eXOZP3++mpgWL15c2rZtK8OHD5dvv/32vvb7+eefS5s2bZKsnYQQ9/njjz/knXfeUX+hhMJRJLEM/gEQQUQK5EovW16lCEIIId7OgnV3JV3QJRn7lEjLmnmlZR6KIIRYnYkTJ8qsWbOkWbNm9nUPPfSQRlaMGzdOduzYIRkyZJBhw4YlOkrDHW7evCnZs2ePc5uwsDBdDP75559Yofg//vijnD59WooUKZJsbSWExOaHH36Q4OBgadSokSQURoIQy1D9gZzSp76IRIVphRiUTySEEOK9BPj7S1h4pD6+eOUfOXCGniCEWJ39+/c7FQywDs8ZKTN///13srXh+PHj8u6778pzzz0X53ZvvfWWZMmSxb4UKlQoxvMQcpC+g8EYISRl+f7777Xkdvr06RP8WoogxDKUKJhNGlcQOXbqvNR/A0cvA5kIIcSb8ff3k6ioe8aoq387LxO/47WfEKtTtmxZmTRpkr3yk+H5g3V4Dpw7d07y5EHoV9y8+uqr6i8S17Jz584Yrzl//rymxzz++OPyzDPPxLn/0aNHa8SIsZw5AyX2PzJnziz169fXwRghJOW4cuWKbN68OdHpaBxFEsuwdvdl+fZ7kX7PhP3rCcJIEEII8WbyZAuSGz4h9kFSgEYBcv6GECvz/vvvqycH0l+QBgOhAhVjIHgitQScOHFCnn/++Xj3heosXbt2jXObokWLxhBAGjRoILVq1VIfkvhAukt8lWrwWYYOHaoiCaJFCCHJD6o64VpCEYR4PXdCo+XkZZHoqHCKIIQQkgZ4plUBkVuh+him2P6qgBNCrEzt2rW1ZC1MRY8ePSo2m006deok3bt3l0yZMuk2PXr0cGtfOXPm1MUdEF0CAaRKlSpqkurrmzTXE1SyqVOnjkaFEEJSBpxv8aWzxQUjQYhl8Pe/Z4wKEUQLq3E2kBBCvJrDf4XJtQshUkdEMqbzkfzZGQFIiDeQMWPG+xrAJBREgCBtpXDhwmq2aq4mkTdv3vvad65cuXQhhKQMMCseNWqUDBw4UEqUKJGofVAEIZbBz89fIqNEKpXKKrsnYg1nBAkhxJtZv/+2/H4wVOqMEelSP4d0qZjR000ihCQBiABZv369XLp0SaKjo2M8N378+CTv419++UX+/PNPXZCGYwaRKPfLr7/+Kq+//rr89NNPOmlHCEk+cO1Ahak+ffokeh88S4llqPxAPnmzi8idOyFy6pxIBR+NByGEEOLF1WEioH6LyMETNyTkukg1TzeKEHJffPTRR9K/f39NY0EUBjxBDPA4OUSQ3r1765Kcoflr1qyRlStXJtqjgBDiHl9++aUUL15cKlSoIImFU+nEMuTMllGqlxA5dOKKPK1eVjx8CSHEm8GMaiTyIEVkxfYrsmhThKebRAi5T9544w2ZOHGiXLhwQfbu3St79uyxL7t377Zk/1aqVEmqVq0qH374oaebQojXV4VZvHixPPvsszEE1ITCUSSxDNv2X5Kmb8ETJEJ8cczTE4QQQryaQnkzyQMFbIhX14iQwEB6ghBida5fv67lab0NVLNBOszx48c93RRCvJZPPvlE/3/66afvaz8UQYh18PWTf+7+K4JoiVwevoQQ4s00qlZARiGy3BYlkVodhiIIIVYHAgg8OrwNVInJmjWrfPbZZ55uCiFeff1YsGCB21WhvMITZPny5fLaa69pLfEMGTLIo48+Kt9++639+b/++kteeOEFWbt2rQQHB2upLThAo44w8RJj1GiRAN8oyYkKahRBCCHEqznyV4js3SrStXOEFM7pKz6+6TzdJELIfVKyZEkZN26cbNu2TR588EEJCAiI8fygQYMs2cfp06eXDRs2SNmyZT3dFEK8lmLFiulyv1hGBPnmm2+kb9++8uabb0rDhg3VyXn//v3256OioqRVq1ZaomrTpk1y9epV6dWrl2737rvverTtJOlEEKSGVyuTQb4fhjWMBCGEEG/m6NkQ+WKzSFdbhPRumEHEP4Onm0QIuU/mzp2rJXJRUQWLGeT4W1UEAYZRY0RERCxxh1iHW7duSb58+aRr164yb968GFVJWrZsKaVLl9aqRjDE/eCDD+Shhx6SV199VW7fvq0T8N7GqVOnVLw0G5FibO6sPC3OX4iBBkeOHJEpU6bo+jt37siAAQNk586dEh4eLh06dJC33nrLbW8PlNWuXbu29OzZM22IIAiBHTx4sEydOjVGKZwyZcrYHyOs7tChQ3LmzBnJnz+/rps+fbo6QcN8CQcpsTblSuaTrweJXLp6Ww4fFqnXjiIIIYR4MxhERKA4THSErNpzSzJl9peaLT3dKkLI/XDy5Emv7kBErf/888+yefNmTzeFJJJFixZJ5cqVdaA/c+ZMFe0MHnjgAR3EA5Rpfeqpp2TXrl1u71tTOy1YRjlr1qxqZBwf77zzjv0xzI8RtdG5c2f9G8EMAFkd6IfWrVvL//73P7c8gnDdgIAKA+KkwBLfAJyiz507J76+vuq+jA59+OGHVWkrX768brN161ZVpwwBBDRr1kzCwsL0wGzQoIHTfeN5LAb//POPXcHFkpIY75fS72sV/P39JF9WkW0nbsjr34isGh6FzrI/z/67P9h/7DtPwWOPfecKHz9/FUEiwkPkx9/uSJEC6aRKEv5G8thj33kKTx97qeVeExHb4H6qPKQ2KlasKK+88oqOP6pUqeLp5pBE8PHHH2vK1pw5c2TJkiUuTTibNGkiY8aMiXd/RYsW1YyG1atX61gVE/XdunXTcWdoaKg0atRIBRWcB4goOXr0qEajwGQXZaQhFGTPnl2jJxBJgYgUZD/gWLt06ZI+DzA2RnshMOB1aH+hQoU8dgx89tlnOh5HW8Dvv/+uURz4nJjkaNq0qSxcuNCpCII+w7bos7Nnz+pnDQoKktmzZ2v0CL6j+vXre7cIcuLECf0fB8WMGTO0U3Dw1KtXTw8SHBQQRvLkyRPjddmyZVM/EDznCnTihAkTYq1HZAly+zzBqlWrPPK+qR2fU7tkxGSRyU/f0Oowa9eul1Df7LG2Y//dH+w/9p2n4LHHvnMkKOK2NHtQZO3qnyUsLEJvAFesWMFjLxXB89aa/RcSEiKeBIMjRHgfO3ZM/0Z6wYgRI6RHjx5idZCej4EnyuWaUymINTh48KBmFjRv3lzFBKRyuBJBEDHirtAF70r4VkIAgPDxww8/aIQJLB3atWunUSedOnXSbbdv3y6//fabjnGRkgMxY/To0fo/9oPsB7QNIkDBggX1NV9++aWOixEY4Ofnp+ICBJPvvvsuVls6deokf/75p9N2ol3OhBMINtWqVdP2tm/fXsUfvE98lVxwnhvg9RBp8HoEISxdutQegOCMu3fvypYtW9Tqom7duhrUgD7EPl5++WV9zpIiCEQNZwKEGRwAyLkC6OyOHTvq4/nz5+uX/vXXX2udYFcqMhTmuNRlHFBDhw61/40vAl88lKmUTqGBKo8fQ6iKzCOMzYnV2yUqepmkDw4SfKUNGzcWSXdPWWT/8fjzJDx32X889pIH330bpXnedRJRv658+4Ho7zLysZMKnrvsO0/h6WMvroFHcoMJTcyyY4BWp04dvVdH6gjy/a9cuSJDhgwRK4NUB4xNkI6PASAmZYl1QIQBIhAwwIeghePy8OHDUq5cOX0eAgQyEgzx7tNPP3Vrv0ibMcakGNuOGjVKB/c4/hHNgX0aIkiLFi1UAAG1atWy+2CuW7dOhUIcY1gQTbJx40Z9btmyZZqmY4gyECtciRT/+zdyxF3gj4JojNy5c8u1a9e0EhICEkaOHOnyNTincZ0x/2bjM2PsXb16dT0v4O+xZs0al/vA+wBkhJjTafAZjSAJS4oguPhB3YoLRH0gHMjIwTJAOEzx4sVVDQMIs4Fq5liHHD8yjhEiZrAfLI7gB8lTQoQn3zs1ExQYJJFRIlmCo+WBAuinIPwTazv23/3B/mPfeQoee+w7R05eDJUvloqMbS1Ss6RIsaJZkuX3kcce+85TeOrY8+R9JgoWIErCbG6ImXCkuGOC1OoiCHjmmWdk8uTJmtKPVAdiDTBu/Pzzz/X8+Oqrr+xRU+aIBrMnSEIw+4pACEQRD4xd06VLpxPyiA4xwDoDCBmI+ohvch/PjR071mXUyv1EggQFBakAAiDO4D0QeRKXCAIxCUVKzEIMPtfbb79t/3vSpEkxxveOGP0ATxFoBoYxq7lPLCmCoL6vOzV+ofag8//44w955JFH7AcpnGqLFCliV8mguP7999+qVhkpLXgd8/G8A1//AK0OU6Okv9TQABAaoxJCiDdz7VaEfPObyNjoCHmqHmY8XE9qEEKsAe7VMQPsCNbhOW8AE7BIqciSJYunm0ISAFJHMMmO8s0GBw4cUCHLiEJICjBRjwl8DPIvXryomQ1G1ENcIB0EIg1EAYgAixcvtvthtm3bVn1FkGoCoQJjZbQdfpr3Gwly6dIljdyAOIQ0lm+//dbpfg1QJQfv4WgYi8gQRLDAcgJGpxBDnaXrmLlx44aasiY1lhhFIvwVoUgwGYKwATGkf//++pxhpIL0FShJCBHas2ePhtYMHz5cTWhYGcY7KJA3pxycLHLqQogsgwDrY4nDlxBCSCLx9w/QCEBUh5m3Jlx+++M2+5IQi4NSm8jpdwQDulKlSom3AAEEUQRIeSDWANELTzzxRIx1RuENREgkFSgXCz8LpMAgqqIxUvzdAONhTPYjagqpOqhgYwhtGAM/+eST6hMCE1HsG+kzScGmTZtU9MB+8Z4QcMyGsHiv8+fPxziXsb3j+YwUFmyLMTuivxAVYqQWOQMpPUiZQ4RLUmMJY1SAECQoR/iCYZJSo0YNNUYx8uwQFrN8+XJ5/vnntbOCg4Ole/fuXlmrOa1iE1+5cFPk6LVQ+WidSHuKIIQQ4tUg7fFeidww+XmfSKaCoVLN040ihNwX8APErPeGDRv0nh3h/RhkYQLTmThiZTB+wYIqH3Gl55PUwcqVK52uxwS7gatUGKRyuQLZC2aQybBjxw639gP7CAMU/EDJ3kyZMmlEBqI/zJVVXnzxRV2Smscee0wXVziWzu3Tp48ujkDwgHmrO6DPFixYoB4s+P+NN96IYZcB/6D7wTJT6Qi/gaCBkCGE0sBMyiiPa1C4cGH58ccfVXVFnhVyDp35fRBrcu3mXan/BlKhIrU6DCNBCCHEu8mdK6s8jwmyqLsqhtAvixDrgyIH8EJASjzMHBFaj8cYFHbo0EG8iYEDB+p1yzyAI+R+QNQIxAREZSDSonfv3l7ZoaGhoZoFgusFqsqk2UgQQnz97h2uEZFRWh3GQhoeIYSQRJAzezYZ1FxEIkM0LQYRoYQQ6wO/PngbeDvwZkBFjPHjx6vhK/wmCLkfHAuBeCsffvihVoWBFUZywFEksQx+/9785skcLbWRYsZ0GEII8Wqu3AiT7u8hEiREOtcUKVM0h6ebRAhJBIjidnfxNuD/gEgXCCGEEPdAGWFEUpUpU0aSA4ogxDL4+fpJhiCRqsWi5aW2FEEIIcTbibT5yvrDIlFhd6RnXZEyxXJ5ukmEkESA6g7w8YtrMbbxNlAJ47333tMSn8T7uHXrlpa/RVlkM+vXr9fvHqkrDz30kFY43bdvn933AwU8EgI8MtypqupJLl26JM2bN9c0HRjKujIF3r9/vzz66KNStmxZefDBB6Vfv37qcWKOdlm4cKH6faIyj7lqFKwvEEnWrVu3GGWFEwrjSollyJwlkxybIfL7X5Gy95RIry7U8AghxJvxD7jn6xUZfktGfynS88l/pAKdUQmxHElVpcKqxGUqSazNokWLtGLKN998o6alEEQMUAXFMFJF+dqnnnoqVtlYb+Kll16SmjVryk8//SS//fabdOrUSU2BHVNZURoYwiDEIVSAQTGT6dOny8svvywXLlyQFi1aaLpcy5Yt1RN06NCh8tVXX+lr4a8DU+WPPvpIt3EUn9yFo0hiGaKibPLrYZEDZ6JkOUyImQ5DCCFeTUBAOv0/4u5t2XRU5MadSE83iRCSCOrVq+fWYpT79EauX78uzZo1k19//dXTTSFJXFYXvi9169aNs7pRkyZN5I8//oh3fyNGjFAjUESQ4Jw4duyY0+0gNEB8gZCA7VBFxYhAwWtRMRXmqSgkYq5oA/GhVKlSUrVqVRk3blySRpfg87/wwgv6GJ8BFZGcRYPg/dFuo8IrtkX5XCN97ObNm1KrVi39+9lnn1UD5YiICPvrUVEKr0PKTGKhCEIsQ0SkSLf3RG6GiKgvKkUQQgjxatJnyCDTuosE+oWpMWpAICu+EeJtYMDzwQcf6IAOYe7eCgQeVK8cOXKkzn4T63Pw4EE5c+aMpoCgJCwEkbgiRtw5viGoIIoCZWf79++vhrrO0k6efPJJ+fTTTzXFBukknTt3jtGup59+Wn7//Xf11RgzZoyux7ZvvfWWbN68WYURpPK44rPPPlMxxdny/vvvx9oexzZEiVy5csUoZfvXX3/F+Xnv3Lkj8+bNkzZt2mj5XFSLKlmypD01DuWAsRgpMaNHj9bUIogrPXv2lMTCdBhiOWPUqGgRX5XvVAohhBDipQQEBUv3Orjch2uJXP+AQE83iRCSRKxdu1Y++eQTHfQUKVJES2HGNYi0Or6+vpouAS8EpEYgxJ9YGxyvGIgjKqFVq1by3HPPyeHDh6VcuXL6PKIzIBqA0qVLq2gRH6iG8u6776pAAVHBmVkwPDOwX/hpgCeeeEIjMAyhAGaiiPQAiKhASokRJYIUk9y5c+vfSM9xVaUJnyuhIgMiNMzYbLY4t0d0R5cuXaRp06bSunVrPTcQmVKsWDGX+2nXrp0u9wtFEGIZfHzvHa4l84hkSa9nmqebRAghJBmx+fhL/ddFvn7nioxpJ1IkP6vDEGJlzp49KwsWLFDxAzPAmL3GQAh+CvBP8HYwg41wf8zMY9CHgTGxJjhuISAEBATY/SpCQkL02J46dWosTxB3QNQEjo8dO3ZoOWVEbjRs2DDWdhAFHAUHYKyD54YBBJrIyMg4X+cqEmTGjBlOn+vbt6897cUgR457v8+XL1+2R4OcPn1aChcu7LL/cP7ny5dPRUGk92zdulVmz56tfxtADMKC7ZISpsMQy+Dr56cCSNXiIj0f5aFLCCHejo9foBy/KBJ297Z0qiGSM0dWTzeJEJJIMAONQSFmxzHTff78ef0/pUEVCsyiYzCIlIOU5s0331TxAxUyiHX57rvvVKg4d+6cVm7BgjQTiAdm/4qEpoYFBgZK3rx5VbCAf4czEN2BYxdRJ0aqTcGCBfV1cVG/fn1ZsWKFXLlyRf+OKzIFUSB4D2eLowBi8Pjjj9tTZZDSA5NTCH+OQJRBtaTs2bPL3Llz9VyEGSrOCRidouoLolbAnDlzpH379io2JSWMBCGWwdcvQDaMl3vmqNtFXujm6RYRQghJVnwCxN8P1WFCpOUUkQ+n3ZIi5dnnhFgRhPljlhs+BzBG9BTw5MifP7/6JXgClE3dvXu3ztATa6fCIA3FDMrC4tj64YcfdICfUJDeAiEBZqaIoICZqjMQaYESsnh/+MugvHRcpqwGMErF8V+zZk2NrECUSVKaEU+ePFl69Oih5zfEHLTRqAwzfvx47RukDC1evFjT4GCOWqlSJU35ga8KvIEAImyw3d27d6VAgQIuU3buB4ogxDr4+MrirSKXb4nsPOnpxhBCCEl2fAMkwE8kIuyOHDwrEu3D2xZCrMrGjRs1VQBeBWXLltXBEvwAUpKVK1eqGIP0Gzz2FBBAkDoxduxYrX4BDwdiLVwdP3v27LE/dpUK8+qrr7rcL1JBzOkgOEYMk1EjggNANMDiLNrD/L4QZhClYgAfkEGDBtnbYVRhSQpQDQbnlzNee+01+2OIN4aAhJSb4cOHqzhqgDYlt0jJnAJiIXxlxFcil/+BuRT9QAghxOvx8Zf5z4qcP7z6njGqP41RCbEqGNh89NFHat6IgT9C+DHLC/PHVatWxVmpIim4ePGiehlgdhrRGKkBRAxgUMpqMSSleOmllzQdDKlpSFmZMmWKxzof1WDgjzN48GC7yWtKQRGEWAcfP4H2EYnqMNRACCHE+wnOI4+UEdl1UuTxGphlijvfmRCS+oEAgfKdKHEJD4Bhw4bJpEmTtGJF27Ztk+U94a/Qu3dvDbE3qma46x+CUH3zkpT9gMiYbdu2xZj5JyQ5gWfH3r171Ztn+fLlmqLiCSD8QQCEl8nEiRNT/P0pghDr4OOr4ke14iKdayWtOQ4hhJBUSIYiIq2PyrCx02TWtDcksERnT7eIEJKEIA0EM9GoGmNU2EgICOeHqWJcC1IDYMAKAWP06NEJ2v9bb72lngnGUqhQIUlK6tata68W88cffyTpvknKgSimjBkzqqmnGZh7QuxC5AX8L2ASioovxrGLNJCEcOPGjViRG0h/+fHHHyU18PLLL2t5YHiPVK9eXctguwK+JFu2bJE///xTo8HMoGQu+gv9hnPEbGCM8sB4LUoSm9ODEgpFEGIdfPykbtl7IkjThxkSTQghaYLMpUTKDROpMEYkIJOnW0MISSaPDFSA+P777xP0ugEDBmiFjLgWeCJgMIaIi6CgIDVqLFmypL4eUSG9evVyuX+IJqjYYSxnzpyR5KgWA3EFqTHEmiC1q3Llyuo1c/v27RjPIe0Eg3iIHzA9RfRDYnEmgqQm6tatq6a/8PNA6lvHjh210oszXn/9dTVIdQZMXtFf6DdEiiFyzOyRgso8SG2bOXNmottKEYRYBx9f+fQ5ke3HRaZ9H+7p1hBCCCGEEA+SM2dONVmNa0mXLp288847OjAzSnyiTCjAICyuUHyIJpkzZ46xJDWIFEC0SkKjAkjqqhQzatQoFQHiqtKCai/uRPyMGDFCqlWrppEQ9erVk2PHjul6pHNBCMF6c1oXTIfx3iVKlNBtAMQYVKgxyvVCpDHMSE+cOKHbJjUocxscHKyP4fGBlBfHaA20C4IkTF07d3Ye3YlqNwYQH319fWOktiHCC8KpYwRJQqDNOrEOPn7ywSqRizdFroTYPN0aQgghhBBiAVBu1AxSFwAGgvAk8DSGuDJv3jzJkCGDdOvWzdNNIm5y8OBBjRDCoD4yMlIjNcyRC44RI1WqVIl3nxBUpk6dan/NkCFDNOVl9uzZKn6Y00PA8ePHNfUmPDxcI0+2bt2qRsQotYvH+B+CBIxQwapVq6Rx48ZxtmH16tUuhTmkosTn4zF//vxY5xdEi549e8qvv/6qFWsyZXId3Ynt1q1bp49/+umnGFVm2rRpIzly5JBPP/1UEgtFEGIdfHzl/VWiJnmBQXRGJYQQQggh3gFmuDGjj0iCUqVKJcjAlXg2CgQDdkQmQBxAJAbSsOCNAWBAisgNULp0abcG7igzCx8beI1AOIjPkLdr1676/ojCwHtBFIEIAqEDYgYqIzVr1kzbdeDAAV3nKgrDAK91FFvcZc2aNTJhwgQVW8xAwFi2bJkucQkg4LPPPtP/0V+IjDGit2rXrq2+IPcLRRBiIe4Zo6JMYjofiiCEEEIIISThFC1aVEWH1ARC/OfMmSNHjhxRfxTM2ufLl8/TzSJxgFSTzz//XAICAuzGviEhIVr1x4jkQGQG0p3c5a+//lKz3B07dkjx4sXVG6Nhw4ZxvgYpXwYQQxCRYggZEBAuXbokjz32mJakhjDx66+/alRJckSCYN/wPYHHDYyPDeCXAmEEr0tIFSh49kBYunr1qkZ/JBUUQYh18PETP1+RZg+KlCqSOuq7E0IIIYQQkhRgMLt06VKNAsGgFekA5gEuSV3AoBNCBTwuDBBp0ahRIzW8TQzwwAgMDJS8efOqUPfee+/FSJuCyAKRAwa/8VGjRg0V1SCCvP322yqCQMAoVKhQvIJCYiJBNmzYID169NB+QYUYA7R33Lhx0qVLl3grNCHqBb4hRulenA9oK/xNkhIaoxLr4OMr7auK1CgpUrlEkKdbQwghhBBCSJKCwR/SBWCYeufOHfZuKk+FMcxGDVCNCN9hYqv9wFAUVWTg44Hyt2Y/GwgBeD9s4066FIQSlOXFPpAqg30ieqXxv34gqMbkWNb3fujTp4+EhYVpJAjScrDs379f24F1xYoV04gngGgQwy8EESP4rIYIhEgofEYIKe+//776oRivSyoYCUKsg4+fvNpRZM4akcs7bsvYDp5uECGEEEIIIUlL9erVNR0BAz8MKlGlhqQ+Vq5c6XT9nj177I9dpcK8+uqrLvc7a9YsXcxlYQ1QetYMDFHN/O9//4vxt2PZ6XPnztkfQ4hISGpKfBhVbAxg1Ip0HER/4P+42mWAKBWkAiU3jAQh1sHHV978TmTPKZGbd1JXHichhBBCCCFJBQQQ+EOgzO/PP//MjiWWwmazyYABA+TDDz+UkydPSmqDkSDEOvj4yQ+7RXJnFsmShcaohBCS0jc0yOtFmT1vAWHBCNMNDQ31qs+VErDvUnf/wRwR+0/qEHKSssDDAcaa8FJARQyz0SQhqZn3339fo1aQMoRKNakNiiDEOvj4Cn7LI6NFfH0ZxEQIISkFQlr//vtvNWTzNmEH5nNnzpzhYJF953XHHjwlUF0EJovEmkDM+vLLL3UQ2aRJEzWeRGUbQlIzX375pVa4efHFF+Xpp5+W1AhFEGIhfLU6zJN1RGpVzOLpxhBCSJogOjpaQ1lxMw6zNwyovGV2GZ8NLvQZM2akuM6+85pjDwILhMvLly/ruVuqVCke3xYmS5YsWtb00Ucf1coeKJmK63FaBNGIqLqCQTb6AFFU6JcpU6bIjRs3pGTJkmpMapQ/xrboM7BgwQI12IRnxqlTp9Sks02bNlKlShX7/sePHy+vv/66mpq2bt3avr5nz55qVnvhwgUVFw1QdWXUqFFaFjZDhgy6rlu3bvLyyy+Lt7F+/Xpp2bKllC5d2r5u69atarjqCCrRZMuWTasbwRwVxyz6D/4jFy9elP79+8uff/6p1ymUv4VYktJQBCHWwcdPnnpUpFYpkaJ5aRBFCCEpAW5SMGCDWZn55s8bwOfC50MJSkYYsu+86djDwCQgIEBOnz5tfx9i7bSYtWvX6uA9rQogRvWRa9eu6eAbg2ycR998842uw3mUNWtWe1nXFStWSNeuXeX69etO+wyVVg4fPmxPMcK+Fi1apFVJHEu2QhTB+q+//lp69eql6+/evSv16tXTVCUYguI9UM1n3rx58X4Od0vcpjYeeOABl0avAP0A0fW3336zr8P2zZs3l2bNmunfQ4cO1b789ttvVQiuXbu21KlTR6pVqyYpCXMKiHXw8ZWn64t8tlHklS+vero1hBCSpqBIQIi14DnrXRQpUkQH3Yh+QGURRPqkJRA5ABFi/vz5KoAYxzjKyRYvXjzW9g0aNJBbt26pQOIMRDQiauP333/Xv1GNp1KlSiqOmEHUCUrKDhs2TP0tzOszZcqk34UhsiAaZPDgwS7fb/r06VoKFtVSUDq2bt26UrlyZRUX3nrrLfu2vXv3lueff17fF5EXjz32mIqZRgnZjh07qmFuw4YNpUePHjJ8+HC719BLL72k1YUQgQERCBEyKcGqVas0Cgf9YuaTTz6RJ5980l7hCP1tROcgEg7H9MKFC132GfoFnwffMb4j9B2+J5T7PXjwYNoQQZYvXy41atRQdTtnzpx6QDh2lOMye/Zsj7WXJDE+fjJ6kchvJ+5914QQQgghhKQlzp8/rxU3MABGakFaYffu3RplgDGgO0AwQR/lypXL5TYQEIzIEQzWnflXQPjAeqTO/PHHH3L06FFdv2vXrgQbfqLcMdJKpk6dqt4uGNTjc2FfS5YsiRFlgXYhAgXRKvieEfECXnvtNRWBjhw5ous2bdpkfw32C2EBJWbxeggFr7zyitO21K5dW4USZ4srs2Z8fog2iNr44IMP7Ot/+uknTXWBaNOpUyf7ehg/f/XVVxrBY4DXQihB5A3SiVD5CBFOrsicObN+nsmTJ0u7du3kkUce0RLEiMiZOHGiJBbLxOHgS+7bt6/mduGARq4XFDRHoA4i5MacR0e8BB9f2XlS5J+7UH4pghBCCCH3C8xuMRDALB5mTRE6jpByQkjqBKmJGEg3atRIZ9HXrFmj6TJENOoBg3hEf1y5ckVTiOKicOHCGs2B1BkIERicmyMyMNaEKXjTpk012gPXSoglkyZNSlR3m0UWpNMg2gNiBSJaYJKMx1WrVtXnMdlv+G0gEuL48eP6GD4b7777rj6GGNK+fXv7PuG7gfQd+J4ARI+UKFHCaVu2bNmSoLZD/Dh79qyOrfE//EEgSCHCA9E4GH9DeDIbMWP8DuHKnGKEaBhErmB/MIfGuD6uqCakGxnvj34yokjg5YKUGq+OBEHeFEKLoG7BPAVhQcjfMitNBvjhRocaizOzFmJRfPzUGDUyiiGehBBC3ANGdgMHDtRQWtysYQCBGT0MHAzwnBFBivsGhBnjnsMw1wOYqcLzxqyh8Tfyus+dOxfjPXHTbJQndTbDZdxQb9u2zWmbMcuFm8o8efKolwPuezARZMxAJiWffvqpbNy4UW+I0W5OHhGS+ilXrpxWioGICWNQzKh7OxgEw3Pi6lXXKfGGJwi8cJAWgnQQRCPEBVIr+vXrp9s6ppDB3wO+FRASELmBqAZcMzE2xSDc1TXcFYjSMIB5Kq7xuN4jRQRpMua2mn188HuB9wT4XXIVEY/nEKGBPsBy6NAhjSZJikiQzJkz238fChYsqKlEOAbnzp2rERoQXoyUF3MUjTkKBCDdCEIS2ocIEoB0IFcY/YA+MO/f3CdeK4IgTAg3GDgwcaCi3FeLFi2c5gENGDBAVSmE2iAVBqE2xEvw8RUEgAxtKTKwjevQNkIIIQRAgMCNKmYDUT0As3q46UKu+AsvvBCjkxBiDBEAoceYpcINKm7u4gMVcz777LMY63CT7Gpm9q+//lJTP9yvmPPLDVC9oGbNmho2/cUXX2h7kC+Nm89x48a5/cUa+ePxgdlFDKiQy43Jo8Skm+KGmfdbhKQsqISCQSgEU3dTRKwMPi+8MDCoNnwuMOjH9deIkjDAdQzXS/QLUofiAtc/VCfBRLsZ4xoMoQO/JVgwHsW1HZEjEAHQDlSTMUQDiFLuRokg6g5iAgRzpJkgGs8d8PuF3xiA9//uu+/szyElZcaMGfZy9vjflW/Gli1b7GKJ4+LMSBa/j8Z1HlGDeF8IU4j+gDjkWIoblamQxoJ+MgMRC94lxhgf0SuIiElpLJEOc+LECf0fxjP4YqHEIZQGIWCYFTEMbHAQIjQMsziY4YGBDUKhxo4d63LfOMCxGCCECODLMb6glMJ4v5R+X8sQGS2Dm4vkz3rv4ubYT+y/+4P9x77zFDz2UnffYd+40cTNj9UGuijDh98L3MQa5QuNm14Yz5kjPTBDlzt3bnvIMm6ckauMCAxgfHajH4y/UToRqbgok2iAUoxY/8Ybb8TqN8yAIZz32WefVbED9zVG23DD+tRTT+lEjznMF4aImNzBDa+r7wDRLBgcwDwQN5WYmUM7cKMLQQdu/RgQIHQaqcV4T4Qho7QjQD/hvgqCEQQUDCAQGo73hECCEHHMVBqfDw7/mGyCeIR7MdzEY3Dgzutww4z/Ef6NqgDoE0xwmfsIJRbxWXCPh7BwI/wbpoAjR47UG3DMmiJ0HPeEFStWFCthHHvGuZUcYL/YP85hx0EN7zW9A4yJjEH3ypUr9bxGZIi3gmsDrqvwiIR4gOMbnxeDf0cDUMOIFOkUuN66AvuB8O0YxYDrKK69iAw0g5QYRIjgPXH9RMQJBBr8huA9u3fv7tZnwfgU+4LQgu8R12N3QBlf/E4gegKvwzXUiNBAWyZMmKD9Ywja+G2CN8j98s033+jvIvoLgggq4WDcjapx8KlBeowRKWl8VxCtEEFiBsIIojNRvQqpSPBCMV//Uwofm/kOIIWBqIEvKi7wo40f1yeeeELmzJmj4UoAwgXUM5wIrg5sHPj4ccYPZkLbgB9wbysFaHX8bHeldUg3GfmlSPrM2aVSl0883SRCCPF6cMODCAGkkTjO9KRmMMuGEGbcaGLAHRcPPfSQCiZYcFu0efNm6dy5s+Y440bOiODAQBszr8hvNv7GpAu2RbQGTPIQ5QEBZPHixXqDiDBn5J0D7BuvQaoNygViRu+ZZ57RexwjCgQ3xRBfkAOeEPAZMAgYMWKEPWcaOef4DBBBkIKDiSEICBAn3n//fe0j3AMhZBrtx/eLHHMIP/h8MNTDzSnaBQM69Av6FPdImDlFdC7usyBUICIG69x5HW7acSOPCF/cw6E/P/roI20zomPwnWEfMNnD5NT27dvt3w0EIrQRnwM31xBWsF8YChoVI8g9IGZBaEJKmGPYOAQ3DNZwj+w4SCGuwfGIAWdq7DcIn4hQQDqEId6SuMF4EiISxANHESS1AgETkSdIE8HxCKNQiOm4XiY3d+7c0QkEpL7g2o9rdWorVuHuOerRSBCEgiL/Ki6gcCHkxjFfCAcqZj3wY+sKzLCgI+Coi5wrZ6DMjvnmCNvjRg83Cyl9ccNBjVCoJk2aqDpGHIgMkRcfE1l/SKR74/SqOLL/ePylBnjusv+8+djDbDsGUpjlMuco+2xoJ3L7XqRmipCxuNge/S/sNz7gnG+IDq5+z/E87jEwGMekCAbsGDiiX/FZcX9gvNbI5cZMK9YZfyMHHeX/MJsFYQP/42/DXBTbGfvAd4X+7NChg4pLEEsQFYEBPjC8RZDCk9B7EHwGzCSOGTPGvg7u+QhFNkepIKIC4gtEB8xy4mYRkz4wrwMIK8eMH+6vIGwA9CFmPHHjiz5C36CPpk2bpnnluAlOyOuQZmSY9WFGEJG8xufFzTz6HSKHgRFJgigVpAdhUG8MWCDEYAYcwpExUWYFjGMPM6HJNYjAsYboaMyUm89dc+Qz8R5wnkFkxHmwb98+PZc4nvA+IF5DDIYQAqEbInpKCCCnT59WoQ0ReohUxO+YlfGoCIKwTHdy2HAzgB87hFpC7QL4EUVuFn7AXQGjGVz043I5x36dKX+4aHjqwuHJ907V+KaTs1dFrt+BGY6vyz5i/90f7D/2nafgsZc6+w43WhikYZAdwzQOA7eUnACCcamDaV3cm99rHNIAHM3uDMxpCIigwAwXXOohJEBQMO45gLEPox/MfyOaA1EgSP3AQATRIMbMu3lbpM0gNNuIqMFMPAb7MPuD4bv5vVy1OS6QMmN+HfKtccOKSAkDI/0CN7RICzL6yXgdwpmxjWMIOGZMc+TIYW8bPgMiSoxjw93XmQUXAMEEpo54Dv8jrBo39M4+P+7rYFLoWPISAwHknyemzzyFcewZ/ZccYL/Yv7PrA+8zvQ98p4jwQlQYJpoh6CKKnngXSNtEJZuU5ubNm3o/gN83c7UXq2IJTxDMDsCsBqGRiNKA8IFQUgAzIADnW8wM4CYEqjfKB+EmBmqoVcKbiBvGqKgOo/cNqSv0ihBC0hz1vpfUDAbaGAAicsBcQtAVmJRBXjcWRDTgf0SUujPDBjEAg39EXRgmo+bcaICSjcgxxySO2agPN5VIuZk8ebJWgTGiWHA/k1DMvifGQBvpJoMGDYq1rZGi4wheA+EIN9mOPhLmyga41zJHMLj7OsfBN/ZhZGbHV9EP74E0G5QHdYRlfQm5B855XIeQxhhfNRFvBSI0vI8gAON6hOssIqJgkI20QVzfcZ3GNQXiK6LWjN8JpNghlQ+CNibcixUrphEQuH4bIJ0PEWwYf7Zu3dq+HtF92A5jUrOtAt4DEXmIjDOu0/i9QKqiu+C6B+8SpP6lJP/73/80xRLiGtI74xJtIegjAhGpl7gmoy+dVX5BVB+yMYxITPQvLC6M4xT9j8+K7xHfDYxgjd8RRDEi5QtplYhsTOyxbRnJHKIHUmeQK4uZDsxgoAON/E/8qKJDcNOAL2nWrFmaqwRfEOIl+Pip9DGtu8iQjqyHTgghxDXwqUB6CmZGkcfsiKOJnhncWyBNAzdh7lqnwUwVN6n43xkwv4OXGW4izS78M2fOtJdcRCouxBjcqDsjrjY7A879qAxgiDvmxZW/C9JLMGDATbvja4xBVVK+zgxSQ5AGbS5f7Ph5MLhAKpHje6SF6hiEuAsG/BBVMcjEYNFcQSQtAJNo+EoiagHXQPgeIW0UYrS5lC62gXcTxAtnZWGN3xK8HvYKAMLJokWLYkVDIMUMogjWo2KKOVINptOYxIdIgCpljmbdqZGIiAj9HUTAgfF54otagwCHAAT4eSLK0bE8rvk3Fqmg6FeIOhCH8DdAtB9eBzEJkYwQvpFOCfBbjmpA+N7wO+Dqt8KrRBCIHMg9xQGIgwx5tWanWxh/IUwSJzs6CAfY4MGDtYOIt+Ajo9uKFMkpcvmm8wsVIYQQYoDJEdzYwmQU0R24AUVkyDvvvBNvpAVK6CINF69zBxgRIpUGqTHOgOFnp06ddPbRvEA0gbixfPlyvSlG1QE8RuWB1atX60wkbhJxQ+lYwjE+MPOIQQA+C2748fm///57vbF1BQZOyDHHoAB530gzwQ0nIlVgupjUr3ME3iyYwMJ3hPYipceoDIOoHHxvmLGFBwj6BtVvYM6X0rOjhFgBDFqRcoZzBgNJD9bDSDEwcMagHemHxmQ5+gGDefhJOoJID4wfDYHEEUQawOfJKIWO6zJEX6M6qQGiTnCNQnVSc/lzrIfAi2ubESWHaz3Gqc7Ae6HqFSb1EWUCYdkZMLOG4ILtEKlheEoh+gITAIg0wfPYl1FpFSBTomTJklpBBmmgeN4RlLHF2BoVwBC5iOt6fKCduF6j/QCVYfA7gOu0I+g/47uAdcXDDz9sbyM8ntAmI7US5XMNgcQc1YS+vJ/KWpYRQQhBPvjDxXzlyy0iX2+4yg4hhBASJ7i5xU0ZjEBxYwrRAbOBmD0yp6Q4A74TiD7Fjas7N1qYdEE0grPJF6SIIAIEN4WO4OYYESDGTTPCgjGwx+QPPEOMNBvkYyNcOCHg5hgzbBAT6tatqzeeKGEbXzlCDB5w04s+g1cJBBlUaEFKcnK8zgxCqREdAwELk10YBKD9ADe/EFQwyw3xCMILooRxk+3KAJ+QtAwG2zBrxnUMYiGuL4im8mZwzUc6pLvRYYgUgfmyo9eQGfhFIWIPIH3RWcQfruFY36ZNGxXQEQ1hXP8Tkt6I6x9EXZjbwpcKmQ2OHDhwQAWMn376SbeDQbXZGBrXXVS9QVAAhBmI0QCRKkg1+f3331Ugh6G1Iwg2QNYFolUQvQIhBCKFeVm6dGms18FAHYKb8RuI6zXSLuMqYgJwPCLlxih4ge3Nnp+IDoTAg99hpMTgdxHtQ4QNfs8TC8MkiKV47mObfL9LZGxZ6neEEELiBwP+9957TxdHDHEDM1DOwnxRxcR8I2aeRXX82xHcKBrPx7ctojPMYBbM3QgUA2ezbQA3i7/88kucN9yOQIBB6VwsrgYEEDscK4y48zosZjBD7dg3CKnG4gyIRogSwUIIiR9c2+CriHQyRKxBJHCssJjWQPQdrtGIeMAgPL60CgzmMcCHgABRA9EdMMI2gNjw999/q6CNCAUI6BBLIEQkFKROIsoDptIY6DtLJ4T3JQTiAgUK2KMlIJIb11KIJ4aQAAHGiKbD61DSPcO/qTgQneFtYpTNhi8TvDjhI4VrM367EoKjP0d8kUf4DYFohEhHHJ+u9mMGEZEJjYp0BkeSxFKERtw7KdKawRMhhBBCCLk/kGqGNAAM9hAp8Nhjj6WZLsVgEzP/EEAwOEV6DAbu3gYG04geg8DhCsMTBNtBMIBogZLScYEoj6eeekqjzxxFc6QxwssCpb8hHCB9w/B6QpVTRFW4w6ZNm1SwR0oIhBWUOXbWLkezW8dxkbkkNkQZo1qZK5Pc9evXa6QkPgdAqWX4njhGgMQVCYKIv7Nnz8Z4L0SHuDLhRgoSUm4QMYiy6AbY3izq4zHEnqSuokURhFgKX997J27G9AxiIoQQQggh7oHoKgx2MZBFOsDmzZs1tD4tYUQAYHCKaCqknCHywJu8QuB3gdRDmGsaZtL4fPD0cEz/gCAA01IIYvGlSHbo0EHNsh2jEBCxgT6E0IEBOxakb2DgjvQ9pDOiHYi4MMxXEXXhLErk+vXrGokBv5G4ShzDzBX7NlKbkLKCdfFNEiM1FH4pISEhGgmJFEakn2A9RAyUhjd46aWXYph4mxf0hbPSvUi5/Pzzz+3nGwQhZ9EkEIwggMC7BCmaZrAeflKokgaQGgnhKamhCEIshZ+vj0zoKNKjaUFPN4UQQgghhFgAzE7DiBLVJjGIhZ8MfGtgVpwWwWw7KnNgwAkjS6Q+eFNUCFJRUFoVUT8QerDAaylHjhyxtoVwAEECvhkQB1wRFBSkZtNGCooBqpgg9cQw8jSA4IbICpTKhTcTBBgINDArRfl1Z7Ro0UK3wb4gECDqwhn4PEjHQfoNvJ82btzoUjAxg6gL7LdixYqaJoMIEETMQBBDqgwiWe4HtAELzi/0qdkgFqbhRuonqrju2LFDI0qM6BKjAgxSHtFvOCbRFxCUElJK2F18bN4k/SUByE3KkiWLGpBBiUvpUkRQ9RCmhrxaEptzczLJoVO3peSD9aRY9/XsPx5/qQKeu+w/bz72EIoLh3eYjJpDbL0BzIThdx+/90kdauvtsO9Sf//Fde568n7XE2DAhQExBscY8GEGHQMvVJ40V5uMD2/sNwxEIQzBaBORDmkJRHFgsI6oB4gcaQFEm2TLlk3vH3AOwBQWpeS9BXfPUf7iE0uRI6OfLNggsm7vdU83hRBCCCGEWACj/KZRJQUGlxgIIhXCVWlUY5CMQZV58TaQ2oCoEPhAAKQzoMws8S4Q94DqMEh7KV26tEakICLEbPCalqAIQizFsIWhsu6QiM+/3iCEEEIIISRtAlED6QxxLSg3alSCGjNmjPpFwKwSfgh4Hh4JrsAAEbPKxpKQcs9WAmkiKG0Krwb0Ubly5bTiiDelyKRl4H+DMulIh0FE1MqVK9VzA1VuvCWiKaFQBCGWNEZl2DIhhBBCSNpmwIABcvjw4TgXVL1AqWzwwAMP2F+L9IfixYurMaQrRo8erWH1xgJDUW8mY8aMOjh+8803tToIPBlgXEn3BOuCFDBUwLlz546KH6tXr75v7w9vgCIIsRS+/7oe58rqXXnphBBCCCEkYaCqB0wk41rgh4LID4gef/zxh/218ERAJQ+YWroCr8FMuXnxdlA+GP4gSCGCmeylS5c0YgaVTeIrI5vazHBfe+01PQbg+4L/+/Xrp5Va8L0j8qV69epaFaZatWpaPtlgwYIFdtNcbIvPD6NOM+PHj9f1SK0y07NnTz1OHE1W0Y+oTAThDakoWCA2JQS0Ze7cuTHWofrKgQMHYqw7ffq0vV1oNyI+du3apUa48VWQuR9QRhiGw/AaefTRR7WSjDMQcQSDVpy/WMxArEG0ClJ1sKDN5pK5+Fw4n1F1536OR4ogxFIgAmRYS5GWtfJ7uimEEEIIIcQCYFAK889XXnlFfvnlFxVD+vfvr889/vjjnm5eqiRr1qw6SDeqjqDEbKlSpTSyAAJDagclclFqdevWrXLw4EH1PWnSpIndAwafD4a5OA5QvhaDaqOErSMoWYvXX7x4Uf9GehUiZSBkmIFnDHw3sN6cZnX37l31n4HgduzYMdm/f7+W1DVKFt+PCGLm8uXL6u0Czw+Y3OLzoO34bCkRRd++fXvta4gfI0eOlM6dOzvdDkbueB5RKc5EOKxHGWssEEGGDh1qf/6NN96QDRs2qFBilONNDBRBiKV484ksUiKPyB9n7ni6KYQQQryc3r17x5r9I4RYE5TH7dq1q5Yuxcw/ZsvXrl2rBqkkfpBSUbt2bRUXUJb122+/tXutpDZg7AoRAr4vxvcLEQCCFyIxHIFAcevWLZcmuYieQClhCEEAg/RKlSqpwGAGEReNGzeWYcOGxSgPi/Uo/QoPGz8/P10HAQSRNs7Ae1WtWlX7uXXr1hpFAiDkQYxBpAX8PQzwWeFXkydPHpk9e7ZGqeA9jfQvpDMh4gJ+L2DNmjXSqFEjSWrQJkTYAJQBxjnm7BhBhBXeH0KUI/ie0FdGuyEsOQo4+D7Qj/dz/FEEIZbin1CbvPuLyN5jNzzdFEIIIcQrwCwlBgq4ocdjRxBubZhMpk+fXj0WjNlhI3Tc2c2s8Vx8xpXr16/XGUuYUCJkHTOBaAtuojGIsQIUzFI/mH1GSVzM5mNgtWrVqgSVx03rIApk8eLFGl1RoEABNZhdtmyZPpfaPEN2796t7XVMtXDFN998Iw0bNpRcuXLFeY5/+umn+hjRMEj9cATCB9a3adNGo42OHj2q65GKUqtWLbfbP3PmTDX03bdvn4pPSOsBEDggbCDS4vvvv9eoCwC/GhzLzz77rAQGBmpbK1eurNdzeN5ge0SHQPQzRJzGjRvH2QYIPhBbnC3ulNSdNWuWtGzZMtERKGhf3rx5ZcmSJVrW2uzTgz7ZtGmTph4llntSDSEWYeYPt+XwOSiA1O8IIYSQpAADAAgbGMhgdveJJ56ItQ1uwvv27au53BA2UDkCs3m42Y6LLl26aDizwWOPPabvZdzUAwgemCFFmPd7772nM6AYpGIQcP36da/6kuFDgcE4IVYF5ycEJKSZwJsBYDCKwS6uC/DZSE7fiaQC3iBoK1JMcF4aAoErChcuLPnz51dPCogaiLQwl5dFiguq6TRt2lSjFBBxBLFk0qRJCW7bF198IQsXLtQSzRAyIAYY4DqN9/7ggw+06guiPxA5AtED3wHSbE6ePKlCFaItIHhcvXpVt8E1FoLJ6tWr9fVxge80sSID0lQgXmzcuFESC9qISI+JEydqCozR3nbt2ulyv3AkSSxpjMrqMIQQQuIDN4tTpkzR8GdEF8Bk7X//+1+MbVA9AuHG8AxACC7KCB4/fjzGNpg9RnUJlJF84YUX9IbZAIN03CgikgJREi1atNCcb8coCcyYYiYOJo3ISzeqTOAGHL9pGPCbeffddzV/HJ8BkRIYVMC4D58B+0A+NG66zWzZskXN6PBZERo9aNAgNZmLD8xe4gYZizmE2wz6BjfiqBaBG1LMspqNBF2BtuB1xoJZSvST4zrk0WMAhXD1YsWK6edE2L05Fzwu8L0iDx/vh+8Js4jGZzeiNCZMmCC5c+fW7xozpuHh4Qk6VjDr2qpVq1jHCgQczBB/9913MaJbDENFDAbq16+v3xsGB9geAxbHmV9E3BgYbYYnAwY5OIbQfngxwLQSwlHBggV1kEWIJ0BkA85dgNQQ+DQgegupRjgunUWVpRQ4v3AdxuDfFYYnyJAhQ9Q/A6lS8RltIsoD5qbY1nEsMm/ePBWJUXkF5/JXX32l1wWcsxCLIE64AyIcIAajkguu8TNmzLC3C2kviA6BUA0RGn/juoLFaA8EGMOzBddBiAlIf8HjBg0aqNB98uRJu4CV1JEgiBbCtQpCGa639wM+E8R3CEJJDUUQYimM603B3AkzEiKEEJL2GDt2rKZTwP0fA1jc7GKg/+uvv+rz586d00EtbiAxC4jZPdzkmk3/1q1bpwNd/I8bWogaWMyDVQgYCE3GzCgG0wgBNgslqBKA2Sy8HjN3iHLATTTAzTJuTh3TPvA39m2eUcXgF4IMwtFxc4n8a+N9cLMMt31EWuAmGTeiuJlGCdG4wGdDu2FghwVCCqpCxAf6LCnNESGG4DuAsV9CwewrjP/w3UHUggCBfjCH6GMQgOfwPWJwsnTpUr1RT8ixAoHJ2bGCART6DhEvaAsWeCcYjBo1SgUpvD++I3fB+5w/f14HlxgIQTyBYAfBbfv27eoPgMXby7aS1A/ESvhwIEoCoh0ETUQcAOP/lARiLdJ1IKQi4gPgeoCBvaPIjWvsyy+/rKkzOP/jokOHDnq+47wzg4gNRG9A6ID4iQXXDERjrFixQq9PaAcMWA3zVfwuOIsSgbAOoRVCJ8QPiM6GYAuBFl4i8AXBNc2oYOMK/LZgO3hzQITH37ju1atXL94JZYj7SKNxtmAywBkQfHEthfCCyJnEgHQ1szcLDGjhjZLk2EgMbt68iV9M/T+lCQ8Pty1btkz/J85544mstjc7i822pSf7j8dfqoHnLvvPm4+9u3fv2g4dOqT/OxIWFmb7559/7IuxDf43r8d24M6dOzHWG+2+fft2jPURERG63tk+3AX7TJcunW3Lli0x1vfp08fWrVs3ffzSSy/ZihQpYgsNDXW6j169eunzkZGR9nWPP/64rUuXLvr46NGjes+wefNm+/NXrlyxBQcH25YsWaJ/z58/X7fZtm2bfZvDhw/ruu3bt+vfixcvtmXLls3ejr1799p8fHxsJ0+e1L/XrVun2y9atMi+j6tXr+r74LWgR48etn79+sVo/8aNG22+vr5OvzuDl19+2da+fXv73+3atbONGTMmxjbog7ffflsf47sxPtO0adNsUVFR+neWLFls7lCvXj3b4MGDY60/ePCgrVy5ctreBx980Pbss8/aVqxY4dY+d+3ape05deqUy+8xe/bsevwZfPjhh7aMGTNq+905VkaPHm0rVqyYy3MN74G+M4PvD+2aOXNmjPWvvPKKrWLFirbr16/r+wP0L/rZvD/8bTwPypQpY6tbt679bxyXGTJksH311VcJPnc9eb9rZdhv7nH58mX9H9e03Llz2+rUqWObMmWK7ciRI7aUAufq+PHjbaVLl7Y98MADen3BdQXnHc7NHDlyaPteffVV/X/9+vW2PHny6HUC17SOHTvqfoxtXV3PfvjhB702V65cOdbzOPfbtGmjj//++289r4sWLWqrUKGCXufeeuutWK8JCQmx1a9f35Y1a1a9LuE8LViwoP3626pVK1v58uXt+8V1Yv/+/fbXV6lSRX8zDPA+Tz31lD6+deuWLSAgwPbBBx/Yr4Pjxo2zJRX+/v7aVlzfjAW/iQDvg/czqFSpki1v3rx6zS9QoIDtySef1PU7d+7U59Bu9BOuqydOnEjyc5QiSCI7LjngQMoNlhWxzesrtgNfxLzRYP/x+PMkPHfZf9587MU1kMIgOF++fPZl6NChuh7/m9djO9C1a9cY67/44gv7jaR5vXEDV6pUqVj7cJcdO3bo7zkGieYFN4DVq1fXbZo3b65tMg80zeCGtWXLljHWDRo0yNagQQN9/N133+lNn1kkAQ8//LBtwoQJ+hg30862wQ3uggUL9DEEnly5ctkHs3iPhg0b2rc1RJDTp0/Heh/cwAPc5AcGBsb4rOnTp9fX4ftzBtqEm8///e9/9nVff/213sSa24ubbGPf+CzY7/Dhw1WISSoRBGBf+N5mzJihwoyfn58KEfGBtjZq1MiWKVMmW6dOnWxz5861Xbt2Lcb3aHxnBhCaDOHEnWOlRYsWtp49Y0/AuCOCbNq0KVEiiOOx9+ijj9qef/75GOsKFy5smzVrltM2UQRJeiiCJAxc2xYuXGhr27atirY4HyBKpBbxzSyCeJIbN26o2A+GDBmi/ZQ/f34VbSDORkdHe7R93niO0hiVWIoTFyJkyo8i00rdEfp5E0KIZxk4cKD069fP/rdh+IjUD4TuGyB3GcBvwggFBkgtAPCWMJe6Q8gvQMqB4z7cxdgf9o2QZDPGvoz3iQtHE0uEThv7dlURAesdjQGdGQUa65BXDxM9pGMgjQOmd/CIcAdjH2gTfC6QduGIq7Dkn3/+WUO2YV5qBt/RL7/8ov4m5lQcpOfAzwP+KEbpwqQE4dnwE8CCdBT4Z6BfUNYRPiGuQA488s+RyoN2w08Fr0HKSFyvc/w+7/dYcQXC1x0/p+OxY06fiuvYi+t4JCS1gWub4TeE9A+kZsCHA+keOAfgK4I0DaT2IVXMKI2aFkDKDNIo4YeEFD5UQOnfv78u8PyAr4kVDGatCkUQYim+2hgit+6K+CSy3BIhhJCkvcE1jPHMGEZtjmAA7c4g0eB+bohRRhADWJQHRP6zM5BnDH8PDEATKrIY7wFPCAy2DQ8IGPGhLGK5cuXs22Eb+IagEgFA6UTkh6McrMEzzzyjVVPggI/2QAxxBPnmhqCBvHG8j7EP3DDDywK58O4CUQreJBAMzCBPHc+ZRRDky5v3nRIlMdG/wB1zVwwW6tSpo8v48ePVVBa+H4ax6u+//65GjYaYgb7MmDGjmovCY8OdYwWeLq6qu+A8MAt8cYEynBcuXIjRh8izJ8SbwfUfpWOxAJxLqF4CIQDGlziHYNwJXwmIJPDBcPb7YkVwrkP0wHUUv2vwFZk+fbpeS1CaF+VkjYonMJ0myQ9FEGIp/P7VPlgdhhBCSFwYN5qIKMBM+SOPPKKRC4gWwOC3V69eau6GqAGY1sEYL0uWLDo4hlhRpkyZeDsYN6u4cYV7/Zw5c/Q9X3rpJY0mMJfww40uomYw04fHMCtFFQVDFAEQTbAOJpow3HQWeYCysqh8AuNBCBe4oUYFEYDX4fX4TGgPhCUYcSJCAp/RERiQYgYSAxCIL2bQNzCMxTYYsKcEMPiDgAExCSapqF4wevRonSU2i0XOgAiFGWaUpoRhLP5G281CFAZUMEmEaR9MAl955RX9HnA/4c6xgm3RjxCN0C7HYwUGt4isgcCF7wjPuwKVYtA+DHww44voFVSCwMCPkLQCBA5EDWLB+Y7rEQw1cc4BnIcQlVHFBAtK86IqlvF8ageRZSgRi4jG3bt3q9knKk7BsBUGq7he45rF894zcDqdWLJEbrH8rm8uCCGEEAAnfkQFvPXWWzogRrg1brSNFAkMVlHWFGUNEQGAG+2PPvrI6Uy/K5DCgtehagdCuzHjh2oA5n1gBhQiRffu3XUbCBxwvHcEg3QM1iGCOAMRGoMHD9b3QwUSCBjGTCkiFVDJBGUhUboVJSvHjRunqSvOQJUECCWYiXUEs7EQBpKjLKErjO8Gs8QQPiA8QPyAQODvH/ecHQYRqKCCqjx4LYQOzLKaI1nwOSFaocILKrngfcwpW+4cK6jW4upYgfAEMQQDNQhHqALkCuwfJTBRUhPfE9IDIMIQklbBeYZUPlzTjIlOnBNIk0HUFCqkoLIJKmMBRHlNnjxZq9FAYMA27kZiJRUQTCHeQCxFNS4I4LhuGKWBIZoipQ/Xf1y3IYog6gNA8IXwSwHEc/jAGMSD75/qgPIP9R7lnFL6wERYGG6c8COekBuwtMT8Qbnk8uUrMnLo8yLVYtaoZv/dH+w/9p2n4LGXuvsOJfpwo4ebVGcpLlYGN7H43cfvfXJFGCLd5sUXX7SXaYwLzIhCHEG5WzPIF4cwgRSYrFmzSlrpu6QCXibo/2XLlklqISX6L65z15P3u1aG/eYZIHBA4EWaG0RkRMIhsg6ipAEitN58800VRRDplT9/fhWB8T/OgSZNmuh2iNbCOYffTJyHEHsRkYV1SF3E7yoiyiBmopwuhBaUqjbKXyNSDa/BtkijMzx5EAEIcRRldvGeOP+87TfTm85RpsMQS/FU48zy+sIrsv/4NXmwmqdbQwghhNw/uJFH6gpmDhGRQAhJnRhzx0ltCkziB8ICBAosiKyDWTMiQIwFKWn4XiB4IqIOaXFYf+nSJY2+2rp1q90/CSatAJF08A0qX768vsYAUWHDhg1TLye8F4QPY4Evk/H9I3IFUWJYnz17dvvrjefN+yQpg9H38cV5UAQhluLQX+Hy4WqR2g3CPN0UQgghJEmA38RXX32l/h6uUmHSMjAsNUxSnXHo0CGXFXAISUpu3bql/xcqVIgdayFwjXDm0wORAmmGzvyXsBjARwgLQAolIk5I6j9X4/JmoghCLMX6Q/fy/QIDeegSQghJ/SAVA0t8KTNY4jLSTMvZy5gBjqt6Cp6Pi7j6lpCEHotnzpxRzxxPlS/FTDdEGLSDqUzsy9TEP6ng2MRvJQSQ+H4XOJIkluLJgW9LxYc+kRrtXvJ0UwghhBCSAsAYNSGlfwlJLuAbgbLKqQEMMimCsC9TI5k9fGzGFQFiQBGEWIrM5bpInXJdPN0MQgghhBBCCCEWJHXbeRNCCCEkVZCW0zEIsSI8ZwkhxMIiCErDIe/O2WLUizaMs1D3HXXvc+bMqfWm6cpLCCGEJB6j9K7hpk8IsQbGOZtc5bOJZ0BZVpSAxf+EfZmaCLLQsWmJdJjatWtrXWYz48aNk9WrV0vVqlXt9aNbtWqlNZ03bdokV69elV69eqkKjpJzhBBCCEk4fn5+kjVrVi0zCNKnT+8xQ8CkJjo6WidLQkNDNdefsO+84djDvS8EEJyzOHdxDhPvAQPMV1991dPN8ArYl2m3Py0hgqCGM+ovG6A+NOoyo6SccSP2yy+/aPkjuNEabrDTp09XR/aJEyfSOIgQQghJJMZvsCGEeAsYLN69e1eCg4O9RthJKdh3qb//IICY758JIYRYSARxBALIlStXYpSc27p1q1SoUCFGOZxmzZpJWFiY7Nq1Sxo0aOB0X3gei7m0jyG0YElJjPdL6ff1Fth/7D8ee9aE5641+g5pptmyZZPIyEiv8RrAZ9myZYtGnKICCWHfecOxB1EF+0QECN7HGbzXJISkZXxsFryTadmypf6/YsUK+7p+/frJqVOnNCLEMSwH9eG7devmdF8I2ZkwYUKs9V9++aWG/BJCCCGEEOJNIF2me/fucvPmTUZLE0LSHB6d9nAlQJiB8anh+wHOnj0rP//8syxZsiTWts7CCaHxxBVmOHr0aBk6dGiMSJBChQpJ06ZNU/xHAar8qlWrpEmTJjSxYv+lODz+2Heegsce+47HnvXgeWvt/jMin4m1KVq0qJw+fTrGulGjRsmkSZM81iYr8cEHH8jUqVPVe7J8+fIyc+ZMqVu3rqebZSledTKez5Mnj1y4cEFSMx4VQeDp0bVr13hPbjPz58+XHDlySNu2bWOsR87j9u3bY6y7fv26/sjgi3AFIkWcOdjiB8lTbtqefG9vgP3H/uOxZ0147rLveOxZD5631uw/3md6D6+99pr07dvX/nfGjBk92h6rsHjxYnnxxRdVCKlTp47MmTNHWrRooR6ThQsX9nTzLEX58uW1YImBFcyYPSqCIL8Yi7sgqgMiSM+ePWNdvGvVqqUGqFDy8uXLp+uQGgOBo0qVKknedkIIIYQQQgjxJJkyZaIBbiKYMWOG9OnTR5555hn9G1EgyDb48MMP5a233krqr8mr8ff3t9wxaCkXsLVr18rJkyf1gHUE6SsPPPCA9OjRQ8Oarl27JsOHD1dlNCFpLYZFiifCBBG1ghxNvDcVevYfjz/rwHOX/cdjz5rw3GXfpdVjz7jPtaA1IHFg8uTJ8vrrr2s6/+OPPy4jRozQyprENShPjcIZL730UqzxJAyLScI4duyYFidB8EGNGjXkzTfflOLFi0tqxlIiyMcff6wu2uXKlYv1HMJuli9fLs8//7yGNKHkGAyfpk2blqD3uHXrlv6PCwkhhBBCCCHeCu57s2TJ4ulmkEQyePBgqVy5slbu2rFjh3odYsJ43rx57NM4QJXRqKioWJYJVvCySG3UqFFDPvvsMyldurRcvHhR3njjDR2vHzx4UC0sUiuWrA6TnERHR8v58+c1tCy56ra7wjBlPXPmDJ262X8pDo8/9p2n4LHHvuOxZz143lq7/3D7DwEEs7e+vr4p/v4kaQtHGHzzzTfSqVMnHeSn5gGop8FYr0CBAhr1AUsFA1grLFy4UI4cOeLR9lmZO3fuSIkSJWTkyJExio+kNiwVCZIS4IegYMGCHm0Dfgw98YPoLbD/2H889qwJz132HY8968Hz1rr9xwiQ1EliCkcY1KxZU///888/KYLEATwpkUXgGPVx6dKlOAtqkPjJkCGDPPjgg5oik5qhCEIIIYQQQgghqYCEFo4ws2fPHv3fKBJBnAPPFBTOQJnqDh062Nfj73bt2rHb7oOwsDA5fPhwqi81TBGEEEIIIYQQQizE1q1bZdu2bdKgQQON6kGKzJAhQ6Rt27Ys8eoGSNVAQQ2kFSElZu7cufLXX3/Jc889l/xfnhcxfPhwadOmjR5ziKSBJwjS/Xr16iWpGYogqQg46r7yyiv6P2H/8fizDjx32X889qwJz132HY89YuXr1+LFi9U/BLPvRYoU0aqY8GIg8dOlSxe5evWqvPbaa/L3339LhQoVZMWKFdqPxH3Onj0r3bp1Ux+aXLlyaUoWxLnU3o80RiWEEEIIIYQQQkiagHbQhBBCCCGEEEIISRNQBCGEEEIIIYQQQkiagCIIIYQQQgghhBBC0gQUQTzArVu35MUXX1TDmODgYKldu7Y6OhvYbDZ59dVXJX/+/Pp8/fr15eDBg5IW2bBhgzoOoy98fHxk2bJlMZ53p69gFjVw4EAtN4ba1XDNholPWiC+/vv222+lWbNm2jd4fu/evbH2kVb7L66+i4iIkFGjRmkddPQJtunZs6ecP38+xj7Sat+5c+zhvC1btqz2S7Zs2aRx48ayffv2GNuk1f6Lr+/MPPvss7rNzJkzY6xPq33nTv/17t1b15sXGLmZYf/Fffyh/CGOKVSkyJQpk/Yfqiqk9f6L79hzPO6MZerUqZLW+44QQlISiiAe4JlnntE61AsXLpT9+/dL06ZNdQBw7tw5fX7KlCkyY8YMee+991QcyZs3rzRp0kTFk7TGnTt3pGLFitoXznCnryA4LV26VBYtWiSbNm2S27dvS+vWrSUqKkrSev/h+Tp16sikSZNc7iOt9l9cfRcSEiK7d++WcePG6f8Qk44ePao3q2bSat+5c+yVLl1an8M1EH1TtGhRvRZevnxZ0nr/xdd3BhhgQTjCgMuRtNp37vZf8+bNtRqAsaAigBn2n+v+O378uDzyyCMqYq5fv15+//13vRamS5cuzfdffMee+ZjD8sknn6gI0rFjxzTfd4QQkqLYSIoSEhJi8/Pzs/34448x1lesWNE2ZswYW3R0tC1v3ry2SZMm2Z8LDQ21ZcmSxTZ79uw0/W3hcF26dKn9b3f66saNG7aAgADbokWL7NucO3fO5uvra/vpp59sabn/zJw8eVKf37NnT4z17L/4+85gx44dut3p06fZdwk49gxu3ryp261evZr950bfnT171lagQAHbgQMHbEWKFLG9/fbbPG/d7L9evXrZ2rVr5/JY5HUv7v7r0qWL7cknn2T/JcF1D8dhw4YNeewRQkgKw0iQFCYyMlJn4swzJgCpHJitO3nypFy4cEFnRM11wOvVqydbtmxJ6eamatzpq127dmnqgnkbzJqiFjj7M37Yf+5z8+ZNndHLmjUr+y6BhIeHy9y5czW0HrOoPPbiJjo6Wnr06CEjRoyQ8uXLx3qe5238IIIhd+7cGpHUt29fuXTpEvvPzWNv+fLl2m9IpUQf1qhRI0baB48/97h48aL2ZZ8+fdh3hBCSwlAESWGQO1urVi15/fXX1T8Agsjnn3+uIc0IjcSgHuTJkyfG6/C38Ry5hzt9hf8DAwPVc4D9mXDYf+4RGhoqL730knTv3l0yZ87MvnOTH3/8UTJmzKii8Ntvv61pgsiD57EXN5MnTxZ/f38ZNGgQz9tE0KJFC/niiy9k7dq1Mn36dE2lbNiwoXox8NiLG4hFSK1CCiVSin755Rfp0KGDPPbYY/Lrr7+y/xLAp59+qveE6DsD/uYSQkjKQBHEA8ALBJGSBQoU0MiFd955RwdPfn5+9m0wo2wG2zuuI4nvK/bn/cH++w9EGnXt2lVnSD/44AP2XQJo0KCBmvEiKgsDqs6dO8eYkeexFxvMss+aNUsWLFiQ4N8Enrf36NKli7Rq1UojAmFiuXLlSvX0waw8+y9ucJ0D7dq1kyFDhsjDDz+sAjD8ZmbPns3+SwDwA3niiSdiRQbz3CWphfiMuVMz8BlzNAw3c+rUKZcFAVIjKPwAr6r7BeI//Jyi/72WxwW8jRy97rwJiiAeoESJEjpjgtmUM2fOyI4dO3QgVaxYMTX2BI5RHxgYOEY8pHXc6Stsg1D769evu9yGxN3H7D/X4LzFwB2pWYhiMKJA2HfugcoHJUuW1MoSH3/8sUY34H/2n2s2btyo16/ChQtrf2E5ffq0DBs2TG/62HcJJ1++fFqt7dixY+y/eECkFo65Bx54IMb6cuXK2avD8HfDvfP4jz/+UKN8M+w7klxgsgGTrZhwcATV2iBoplaSo32FChXSCHyI4WmJkSNHypgxY8TX9z8JYMKECVKwYEE1vMZ1yQCpooiUhF2DN0IRxMMDANx8YYD+888/68yKIYRgQGWAQShEE5TSJf/hTl9VqVJFAgICYmyDi96BAwfYn27A/otfAMHAafXq1ZIjRw723X2CSAUjJYHHnnPgBbJv3z6dvTIW+BzBHwS/I+y7hHP16lWdkMDvMfsvbpBeWq1atRg3ygCRNBCS2H/uAbEX1zjDA8mA1z2SnJFHKL2MAa25nHVqvyeAl2JyAEEIYwiIumlJCMM96+OPP25fh+MBUZDfffedZiUMGDDA/hyyFbDu3XffFa8kpZ1YiU2rkqxcudJ24sQJ2y+//KKVYapXr24LDw/X7kG1E1Q4+fbbb2379++3devWzZYvXz7bP//8k+a679atW1qxBAsO1xkzZuhjowKHO3313HPP2QoWLKhVJ3bv3q1O7OjzyMhIW1rvv6tXr+rfy5cv1+dRRQd///3337a03n9x9V1ERIStbdu22i979+7V/jKWsLAwW1rvu/j67/bt27bRo0fbtm7dajt16pRt165dtj59+tiCgoK02kla77/4zltHHKvDpOW+i6//8NywYcNsW7Zs0apY69ats9WqVUsr7fB3I/7+A/i9RdW1uXPn2o4dO2Z79913terdxo0bbWn9+HPn3EUlrPTp09s+/PBDp/tIq31Hkg/85mbKlMl25MgRre40YcIE+3Pz58/XY9W8YB3A448++sjWvn17W3BwsK1kyZK27777zv7aypUr26ZNmxaj2hGuBTjGAe6JsA+8L1i4cKGtSpUqtowZM9ry5Mmj9+wXL160vx7XY2yPcRK2w3Xmk08+cdm+V155xVaoUCFbYGCg3vsPHDgwxu/ixIkTbU899ZS+H7abM2eOy6qIxnujeudDDz2k9yMYm+3bty/Ovp0+fbqtQoUKek7jvO3fv79eB8z9i3EKPlPZsmVtGTJksDVr1sx2/vx5+za4p0TbsV327NltI0eOtPXs2TNGFbN69erZBg8ebP8b95ojRoyw5c+fX98bbcVniAu8R6dOnWKs++GHH/R+FmPQbdu22apVqxbj+fXr12v/orqpt0ERxAMsXrzYVrx4cT2oUOL1hRde0JJ85tKvOLHxHE7CRx99VAf4aRHjouS4oMShu3119+5d24ABA/TCgot469atbX/99ZctLRBf/zn78cOCPk3r/RdX3xk/ns4W849QWu27+PoP/dKhQwf98TZuXvAjjDLDZtJq/8V33rojgqTVvouv/3Aj17RpU1uuXLn0Brtw4cK63rFv2H9xH38ff/yxDojSpUunA/Rly5ax/9w8dzEQwzlpvu/jsUeSE5yvVatWtQ96ixYtqvfPANdECMPly5e3T+YYA14cuxjYf/nllyp4Dho0SAUFTKCBoUOH6m8LwP7we5MzZ06dWAN4He7Pze1YsWKF7fjx4zoJUrNmTVuLFi1inT8QITBJ/Oeff2o5eGft+/rrr22ZM2fW/UFk3L59uwqz5t9FtOf999/Xtr/11ls2X19f2+HDh+MUQcqVK6fvDfEDnw19ZUxSOwO/vWvXrtWJ7TVr1tjKlCmjQogB7rPxW9O4cWPbb7/9ppM+eI/u3bvbt3njjTe0rRCY0T4IofhscYkgeH3t2rVtGzZs0H6aOnWqjoOOHj3qsq24VmPy2Ex4eLitefPmNn9/f1vWrFlVfHUU0Hx8fFQM8TYoghBCCCGEEEKIF4LB8syZM+1RBxAqVq1aZX8eE18YIDsCUWDs2LGxBsSIZgfff/+9Ri9ERUVpVCzE5SFDhmiEAujXr59GnrgCEx94DyNywhAiHEVVZ+1DBEbp0qVdChQQQZ588kn73xBpcufObY/AciWCICLaAGIPBEtMXrvLkiVLbDly5LD/bUw2QqgwgDCDSBgDPIaIYYCoLwj0rkQQ7Avfw7lz52K8d6NGjTTK1hX4rj777DOnz128eDFGJLOZbNmy2RYsWGDzNugJQgghhBBCCCFeBvx7UIABVewAPDBQIQseIe7w0EMPxfAyRFlno4rbo48+Krdu3ZI9e/aoH1+9evW06ptRLnv9+vW6zgDbwf8Q/kHYDyqeAEePkqpVq8bbLvha3L17V4oXL64GnkuXLo3lH2JuOyrBwAMkvgp0tWrVsj/Onj27lClTRg4fPuxy+3Xr1kmTJk204ic+U8+ePdVn6s6dO/Zt0qdPr0UxDOA/ZbTj5s2bcvHiRalevXoMvxL4A7li9+7d6pdSunRpyZgxo31Bvx8/ftzl69BfrqpR5c6dWz2fnBEcHCwhISHibaQdNxhCCCGEEEIISUMmvBAHMEg3wAAaRQNQmCFbtmxxvh7bmYGYYJRXzZIli1ZtgdgB082GDRtK3bp11bAbBpwwTDaEDogCTZs21eXzzz+XXLlyqfjRrFkzLWpgBmKLO9VdIPCg8AHM6Z9//nmZOnWqCgFGm+Nqe0JwVY4eldlatmwpzz33nLz++usqmsBotE+fPmqeb+CsHfcCbVy/h+PzZvAZIJTs2rVL/zcDMSSu6l6O1TLd4dq1a/p9eRuMBCGEEEIIIYQQLwLix2effSbTp0+PUVHs999/12iML774QrdDBEBUVFSi3gMiB6IhNmzYoI+zZs2qJbTfeOMNjS5A+Wxw5MgRuXLlikyaNEmFkrJly8YblWHgqn2IUGjbtq288847KsRs3bpV9u/fL/fDtm3b7I8hGEDIQVudsXPnTu1j9G/NmjU1MuP8+fMJej8ISXny5NFoHQN8VkTNuKJSpUq6DfqvZMmSMRZEu8T1ukOHDiWofcePH5fQ0FB9rbfBSBBCCCGEEEII8SJ+/PFHHcgjMgGDbTOdOnXSKBGURC1atKicPHlSBZKCBQtqWgfKo7oDhI9Zs2ZpFATED2Mdyqo+9thj9u0KFy6sYgbWI3LiwIEDGj3hDs7a99VXX6kQUKNGDU03WbhwoYoiRqnuxPLaa69Jjhw5VJgYM2aMRk+0b9/e6bZIcYEIgs/Upk0b2bx5s8yePTvB74nSxW+99ZaKGBBcsD98b64iUCC2PPHEE5p6AwEGAgUEprVr18qDDz6o0SnOQNTNp59+mqC2bdy4UVOOzOk83gIjQQghhBBCCCHEi4DI0bhx41gCCOjYsaOKCvCXwOPmzZurnwfSHiAwuAt8QQC8P4xBOx5DoDD7gWC/CxYskK+//lrFEkSETJs2za33cNY+RJx89NFHUqdOHfX+WLNmjfzwww8qYNwPaNfgwYPVk+Pvv/+W77//3qVXBlKBZsyYIZMnT5YKFSpoZA3EjIQyatQo6datm4oa8CRBSgsEC1f+HWD+/Pm6/bBhw9S3BBEx27dv1zQhVzz55JMaCYI0IndBX8NzxRvxgTuqpxtBCCGEEEIIIYSkNEingciCCAwILJ4Enh9II+rcubPb0TLuMnLkSDVjnTNnTrzbIlqnUaNGmhLkTEizOowEIYQQQgghhBBCUhgYrCKqBWIDPE369++v6T/du3dP8vdCig9ShqLc8ICBvwk8ZbxRAAGMBCGEEEIIIYQQkibxZCTImTNntIQxIi+QoIHUGqTlGKlGJHmgCEIIIcQrQdk95B7DCAx5w6dOnZJixYqp6zpyeZMLzOS0aNFC827dKfVHCCGEEEJSDqbDEEKIBejdu7eajjkuf/75p6eblmqZO3euhn1CAHEXuNDPnDkz1vpXX33VbeEE7uzVq1eXt99+O0HtJYQQQgghyQ9FEEIIsQhwR4dbuXlBZIOzCAgiWmbumWee8UhXPPXUU/Lhhx+6lXdLCCGEEEJSDooghBBiEYKCgiRv3rwxFj8/P6lfv74MGDBAhg4dqjXtmzRpotujFBrqxaPcGmre9+jRQ2vJG9y5c0dLrOH5fPnyab157OvFF1+0b4Nok2XLlsVoB/JlUerO4Ny5c9KlSxfJli2blqdr166dpp6Yo1jat2+v5fDwPtjmhRdekIiICPs2YWFh6lqO8m74nKVKldLyfsiPLVmyZKxSesid9fX1lePHjzvtK5T9Q5RMq1at4nRgR+m30qVLqzFZQnAWlYMoEgOUt7t69ar8+uuvCdovIYQQQghJXiiCEEKIFwDfC39/f9m8ebOWPkOUSL169TSFY+fOnfLTTz/JxYsXteSawYgRI2TdunWydOlS+eWXX9QYbNeuXQl635CQEDUTg5CyYcMG2bRpkz5G1Io5IgXvA8EC/6OtEFHMQgrEmEWLFsk777wjhw8fltmzZ+t+IC48/fTTMn/+/Bjv+8knn0jdunWlRIkSTtuFtkDcyJw5s9Pn0Tb0BfoGbUbaTEIwR+NAbIFQYzYxCwwMlIoVK8rGjRsTtF9CCCGEEJK8+Cfz/gkhhCQRP/74owoDBjDf/Prrr/UxBuFTpkyxPzd+/HipXLmyvPnmmzGEA0RaoAxb/vz5NdIC5c+MyBGIEwULFkxQmyBcICJj3rx5KlgACBaIFoGo0rRpU12HKJH33ntPI1fKli2rERpr1qzRSAy0Z8mSJbJq1Spp3Lixbl+8ePEYqSX4PDt27FCvDUSQfP755zJ16lSX7UIkCj6jM27fvq3vf/fuXW2jY/m3UaNGydixY52arBogCgcgUqVjx466D4hPZgoUKBAjIoYQQgghhHgeiiCEEGIREHEBnwkDc+WRqlWrxtgWER2IujCLJgaIyIAAgIF9rVq17OuzZ88uZcqUSVCb8D6IhMiUKVOM9aGhoTFSVcqXL68CiAHSYlBFBezdu1efQ+SKM7AtRAuIOBBBIAZh/48//rjLduHzpUuXzulz3bp1U7EHIkz69OljPY8IGaTwmEGECqJLHHn55Zdl69at8ttvv0lwcHCM5/A3ImUIIYQQQkjqgSIIIYRYBIgeiPhw9Zyj30WbNm1k8uTJTkWFY8eOufWeiO5AtIMZs5cH3qdKlSryxRdfxHptrly57I8DAgJi7RevBY7igTNgcApPE1RcQaQJPEicCRgG8EYxRBZH4JOCSJJt27ZJw4YNnb7WsZ8hEDmCfaA9iCZxFkFz7do1l+k6hBBCCCHEM9AThBBCvBCkwhw8eFDNOjGgNy+GmAJhAkKAwfXr1zU1xVHIgO+FAcQTc3QD3gfrcufOHet9HNNM4iopC0EkLhNRCBdoNyJhVq5cqT4hcVGpUiU5cuRILAEH9O/fXyZNmiRt27ZNtHEpoj8gzCAFpmbNmk63gXkr2kEIIYQQQlIPFEEIIcQLQfUVRCIg9QNeGidOnFDzU4gHKNuKNJk+ffpo6gfSQjBgRwoI/D3MIFICXh6otgIT0eeeey5GVMcTTzyhkROoCAMT0JMnT6qwMHjwYDl79qxbbYVQ06tXL20bKtFgH4iugE+IAdJl0L7Ro0erwGJO43GVOoTqNxCCnDFw4EB54403pHXr1mqMmhAuXLggHTp0kK5du2oVGPyN5fLly/Zt4AWCqjmGxwkhhBBCCEkdUAQhhBAvBKagqBQDwQMD9QoVKqgwgegMQ+iAsSgqmiAiAoP1Rx55RFNbzKBsLsxUsV337t1l+PDhMdJQ8BheGYULF5bHHntMypUrp2IGPDlcVWZxBiI8OnXqJM8//7wap8IwFSKGGYg28DGJLwoEoAwv2uMsTccApYAnTJigUSZbtmxxu62IMEGlHRjJIrXIWKpVq2bf5quvvlJT2IRWnSGEEEIIIcmLj81ZrDAhhJA0Sf369bWs7syZMyW1AVEH7UOESZ48eeLdHp4gEHecGbcmJ2FhYVKqVCkVQurUqZNi70sIIYQQQuKHkSCEEEJSNRAVIGSMGzdOOnfu7JYAYniNoGxwSpepPX36tIwZM4YCCCGEEEJIKoTVYQghhKRqEFGBVBhEqCxcuDBBr4XXSEpTunRpXQghhBBCSOqD6TCEEEIIIYQQQghJEzAdhhBCCCGEEEIIIWkCiiCEEEIIIYQQQghJE1AEIYQQQgghhBBCSJqAIgghhBBCCCGEEELSBBRBCCGEEEIIIYQQkiagCEIIIYQQQgghhJA0AUUQQgghhBBCCCGEpAkoghBCCCGEEEIIISRNQBGEEEIIIYQQQgghkhb4P6y5qXesGGgXAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 1100x800 with 4 Axes>"
       ]
@@ -11206,7 +10962,7 @@
     "    f_crimac / 1000,\n",
     "    ts_crimac,\n",
     "    color=crimac_color,\n",
-    "    linewidth=2,\n",
+    "    linewidth=1.2,\n",
     "    label=\"CRIMAC reference\",\n",
     ")\n",
     "\n",
@@ -11215,7 +10971,8 @@
     "    ts_api_plot.values,\n",
     "    color=api_color,\n",
     "    linestyle=\"--\",\n",
-    "    linewidth=2,\n",
+    "    linewidth=0.8,\n",
+    "    alpha=0.9,\n",
     "    label=\"echopype API TS_spectrum\",\n",
     ")\n",
     "\n",
@@ -11282,12 +11039,12 @@
    "id": "7a70f471",
    "metadata": {},
    "source": [
-    "Print of import and their version"
+    "Print of imports and their version"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 59,
    "id": "7d490e20",
    "metadata": {},
    "outputs": [
@@ -11295,8 +11052,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Notebook generated: 2026-06-19 15:35:35.320966\n",
       "Python: 3.12.13\n",
-      "echopype: 0.11.2.dev22+gc1a2a5660\n",
+      "echopype: 0.11.2.dev57+g1f9b67a33\n",
       "numpy: 2.4.4\n",
       "pandas: 3.0.2\n",
       "xarray: 2026.4.0\n",
@@ -11305,8 +11063,10 @@
     }
    ],
    "source": [
+    "from datetime import datetime\n",
     "import sys\n",
     "\n",
+    "print(\"Notebook generated:\", datetime.now())\n",
     "print(\"Python:\", sys.version.split()[0])\n",
     "print(\"echopype:\", ep.__version__)\n",
     "print(\"numpy:\", np.__version__)\n",

From 6344c5398f49016aa3fba1824f9fed9a7be74748 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Sat, 20 Jun 2026 16:26:22 -0700
Subject: [PATCH 10/11] update data fetching and gitignore

---
 .gitignore              |  5 +++--
 notebooks/utils/data.py | 48 +++++++++++++++++++++++++----------------
 2 files changed, 32 insertions(+), 21 deletions(-)

diff --git a/.gitignore b/.gitignore
index 9bf58c0..4581f19 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,8 +6,9 @@ __pycache__/
 # C extensions
 *.so
 
-# Example datasetss
-notebooks/example_data/ts_spectrum_example_data/
+# Example datasets
+notebooks/example_data/*
+!notebooks/example_data/.gitkeep
 
 # Distribution / packaging
 .Python
diff --git a/notebooks/utils/data.py b/notebooks/utils/data.py
index b89357a..0f3e30a 100644
--- a/notebooks/utils/data.py
+++ b/notebooks/utils/data.py
@@ -1,4 +1,7 @@
 from pathlib import Path
+import shutil
+from zipfile import ZipFile
+
 import pooch
 
 EXAMPLE_DATA_DIR = Path("example_data")
@@ -7,7 +10,7 @@
     "ts_spectrum_example_data": {
         "release": "example-data-v1",
         "asset": "ts_spectrum_example_data.zip",
-        "sha256": "A35A1108DCFAFAE725D826FFA23EA2E111FDB420E7CE433E49E1797381BB6763",
+        "sha256": "dae603937d05d0d0a5dd41c90b9eafa3c540c95e0f6b298ceeddc7f23d163f4b",
         "files": [
             "IMR-D20211215-T143432-TSf.raw",
             "crimac_tsf_reference_outputs.npz",
@@ -22,14 +25,9 @@ def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
 
     dataset = DATASETS[name]
     dataset_dir = data_dir / name
-
     expected_files = [dataset_dir / file for file in dataset["files"]]
-
-    if all(file.exists() for file in expected_files):
-        print(f"Using local dataset: {dataset_dir}")
-        return dataset_dir
-
-    print(f"Downloading dataset: {name}")
+    expected_sha256 = dataset["sha256"]
+    marker_file = dataset_dir / ".sha256"
 
     fetcher = pooch.create(
         path=data_dir,
@@ -37,26 +35,38 @@ def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
             "https://github.com/echostack-org/echopype-examples/"
             f"releases/download/{dataset['release']}/"
         ),
-        registry={
-            dataset["asset"]: f"sha256:{dataset['sha256']}",
-        },
+        registry={dataset["asset"]: f"sha256:{expected_sha256}"},
     )
 
-    zip_path = Path(
-        fetcher.fetch(
-            dataset["asset"],
-            processor=pooch.Unzip(),
-        )
+    # This verifies the cached zip hash.
+    # If the local zip is missing/stale/corrupted, Pooch redownloads it.
+    zip_path = Path(fetcher.fetch(dataset["asset"]))
+
+    local_extract_valid = (
+        all(file.exists() for file in expected_files)
+        and marker_file.exists()
+        and marker_file.read_text().strip() == expected_sha256
     )
 
-    zip_path.unlink(missing_ok=True)
+    if local_extract_valid:
+        print(f"Using local dataset: {dataset_dir}")
+        return dataset_dir
+
+    print(f"Extracting dataset: {name}")
+
+    if dataset_dir.exists():
+        shutil.rmtree(dataset_dir)
+
+    with ZipFile(zip_path) as zip_file:
+        zip_file.extractall(data_dir)
 
     missing_files = [file for file in expected_files if not file.exists()]
     if missing_files:
         raise FileNotFoundError(
-            "Dataset download/extraction finished, but some expected files "
-            "are missing: "
+            "Dataset download/extraction finished, but some expected files are missing: "
             + ", ".join(str(file) for file in missing_files)
         )
 
+    marker_file.write_text(expected_sha256 + "\n")
+
     return dataset_dir
\ No newline at end of file

From 95efe5f77c477206d0458ee40c782652865cdff0 Mon Sep 17 00:00:00 2001
From: Lloyd Izard <76954858+LOCEANlloydizard@users.noreply.github.com>
Date: Sat, 20 Jun 2026 16:53:47 -0700
Subject: [PATCH 11/11] changing displayed information, check with zip checksum

---
 notebooks/getting_started_FM_TS.ipynb | 364 +++++++++++++-------------
 notebooks/utils/data.py               |  12 +-
 2 files changed, 190 insertions(+), 186 deletions(-)

diff --git a/notebooks/getting_started_FM_TS.ipynb b/notebooks/getting_started_FM_TS.ipynb
index 39ffba6..af116c2 100644
--- a/notebooks/getting_started_FM_TS.ipynb
+++ b/notebooks/getting_started_FM_TS.ipynb
@@ -59,7 +59,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 3,
    "id": "a253416f",
    "metadata": {},
    "outputs": [],
@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 4,
    "id": "c0fefef8",
    "metadata": {},
    "outputs": [
@@ -98,7 +98,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Using local dataset: example_data\\ts_spectrum_example_data\n"
+      "Verifying dataset archive: ts_spectrum_example_data.zip\n"
      ]
     }
    ],
@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 5,
    "id": "cdedca3c",
    "metadata": {},
    "outputs": [
@@ -132,8 +132,8 @@
        "        <div class=\"xr-obj-type\">EchoData: standardized raw data from Internal Memory</div>\n",
        "    </div>\n",
        "    <ul class=\"xr-sections group-sections\">\n",
-       "        <li class=\"xr-section-list\"><input id=\"idata_af55cced81155a18216c1c80c2773993\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "            <label for=\"idata_af55cced81155a18216c1c80c2773993\" class=\"xr-section-summary\">Top-level: contains metadata about the SONAR-netCDF4 file format.</label>\n",
+       "        <li class=\"xr-section-list\"><input id=\"idata_c270525a298197d8a05ad1217d21fc34\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "            <label for=\"idata_c270525a298197d8a05ad1217d21fc34\" class=\"xr-section-summary\">Top-level: contains metadata about the SONAR-netCDF4 file format.</label>\n",
        "            <div class=\"xr-section-inline-details\"></div>\n",
        "            <div class=\"xr-section-details\">\n",
        "                <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -691,12 +691,12 @@
        "    sonar_convention_version:    1.0\n",
        "    summary:                     \n",
        "    title:                       \n",
-       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-466df8aa-aba3-4353-bfbe-a3e4babe495f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-466df8aa-aba3-4353-bfbe-a3e4babe495f' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-10c3052a-50c6-4af0-986d-92679ad58171' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-10c3052a-50c6-4af0-986d-92679ad58171' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-be3869f8-bda8-4ab2-82d0-c449a9ac82db' class='xr-section-summary-in' type='checkbox' checked /><label for='section-be3869f8-bda8-4ab2-82d0-c449a9ac82db' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
+       "    date_created:                2021-12-15T14:34:32Z</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6085aa9e-c505-43fd-b112-95ab9733c86a' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-6085aa9e-c505-43fd-b112-95ab9733c86a' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'></div></li><li class='xr-section-item'><input id='section-5ce9f7f7-197a-46b9-93f8-30bdbbf73f2c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-5ce9f7f7-197a-46b9-93f8-30bdbbf73f2c' class='xr-section-summary'>Data variables: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'></ul></div></li><li class='xr-section-item'><input id='section-6ce7eb6f-c589-447f-aa36-bc4d982c994b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-6ce7eb6f-c589-447f-aa36-bc4d982c994b' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(8)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conventions :</span></dt><dd>CF-1.7, SONAR-netCDF4-1.0, ACDD-1.3</dd><dt><span>keywords :</span></dt><dd>EK80</dd><dt><span>sonar_convention_authority :</span></dt><dd>ICES</dd><dt><span>sonar_convention_name :</span></dt><dd>SONAR-netCDF4</dd><dt><span>sonar_convention_version :</span></dt><dd>1.0</dd><dt><span>summary :</span></dt><dd></dd><dt><span>title :</span></dt><dd></dd><dt><span>date_created :</span></dt><dd>2021-12-15T14:34:32Z</dd></dl></div></li></ul></div></div><br></div>\n",
        "                </ul>\n",
        "            </div>\n",
        "        </li>\n",
-       "        <ul><li class=\"xr-section-list\"><input id=\"idata_b1c4faccf962c4bc31d9aaaa8f5c9aba\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_b1c4faccf962c4bc31d9aaaa8f5c9aba\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
+       "        <ul><li class=\"xr-section-list\"><input id=\"idata_93b8004d06ec10231ff3095dd5ad54a7\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_93b8004d06ec10231ff3095dd5ad54a7\" class=\"xr-section-summary\">Environment: contains information relevant to acoustic propagation through water.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -1256,11 +1256,11 @@
        "    sound_velocity_profile        (time1, sound_velocity_profile_depth) float64 16B ...\n",
        "    sound_velocity_source         (time1) &lt;U6 24B &#x27;Manual&#x27;\n",
        "    transducer_name               (time1) &lt;U7 28B &#x27;Unknown&#x27;\n",
-       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-005d6503-b9bf-4640-af84-18dcccd73b41' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-005d6503-b9bf-4640-af84-18dcccd73b41' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-0bd0521b-24a5-41ae-a7cd-97b5dcd09a35' class='xr-section-summary-in' type='checkbox' checked /><label for='section-0bd0521b-24a5-41ae-a7cd-97b5dcd09a35' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-4128c7c4-2c02-4ef7-a1d3-47bfde5de4b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4128c7c4-2c02-4ef7-a1d3-47bfde5de4b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29ad7140-3d3d-46bd-8984-9a5bb024665d' class='xr-var-data-in' type='checkbox'><label for='data-29ad7140-3d3d-46bd-8984-9a5bb024665d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-620ba013-057c-4308-b2d5-4b95668f5f61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-620ba013-057c-4308-b2d5-4b95668f5f61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e45c014b-8dc2-4d17-b386-dd468a05e533' class='xr-var-data-in' type='checkbox'><label for='data-e45c014b-8dc2-4d17-b386-dd468a05e533' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-65c1c6fc-3af9-496c-9830-5e8ccff0830c' class='xr-section-summary-in' type='checkbox' checked /><label for='section-65c1c6fc-3af9-496c-9830-5e8ccff0830c' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-3be7d80f-29ab-4592-9523-e2265e9bae67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3be7d80f-29ab-4592-9523-e2265e9bae67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53584571-d86a-41be-9c8d-2d513e4aa64c' class='xr-var-data-in' type='checkbox'><label for='data-53584571-d86a-41be-9c8d-2d513e4aa64c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-5f5facda-96c4-4bce-aaf1-336bb50c7c75' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f5facda-96c4-4bce-aaf1-336bb50c7c75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8e976be-cdb9-4bbb-a5bd-dea4a3e907d0' class='xr-var-data-in' type='checkbox'><label for='data-c8e976be-cdb9-4bbb-a5bd-dea4a3e907d0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-42f26e19-72bc-459a-80d6-891917d55dd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42f26e19-72bc-459a-80d6-891917d55dd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75bf026c-c1a2-45a1-bd71-e54d058ea743' class='xr-var-data-in' type='checkbox'><label for='data-75bf026c-c1a2-45a1-bd71-e54d058ea743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-da449f00-c0d1-4a28-b068-f6a20ebb3bf7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da449f00-c0d1-4a28-b068-f6a20ebb3bf7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b00402d-50e0-4ef7-8763-52e03cfa1f31' class='xr-var-data-in' type='checkbox'><label for='data-6b00402d-50e0-4ef7-8763-52e03cfa1f31' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-989a7ceb-0090-49b9-b96e-b7ffff992165' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-989a7ceb-0090-49b9-b96e-b7ffff992165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3cd4f6b-53b0-4157-a628-d20861f2733b' class='xr-var-data-in' type='checkbox'><label for='data-b3cd4f6b-53b0-4157-a628-d20861f2733b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-d2f39fd5-0754-4bd6-b47d-22bd9625b186' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2f39fd5-0754-4bd6-b47d-22bd9625b186' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5b31fdb-38db-487e-bde4-d6efb43af69a' class='xr-var-data-in' type='checkbox'><label for='data-c5b31fdb-38db-487e-bde4-d6efb43af69a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-635802e1-9262-47df-ab87-e11af36b3ffe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-635802e1-9262-47df-ab87-e11af36b3ffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-026bd23b-d9fb-4c84-8c9a-22ae2127e863' class='xr-var-data-in' type='checkbox'><label for='data-026bd23b-d9fb-4c84-8c9a-22ae2127e863' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-d979d40d-6fda-4bab-863c-0ff0a713e505' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d979d40d-6fda-4bab-863c-0ff0a713e505' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1497722-9772-4904-b01f-996dbd562723' class='xr-var-data-in' type='checkbox'><label for='data-c1497722-9772-4904-b01f-996dbd562723' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-a7a78fb3-119d-42cd-ad06-399cf2798165' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a7a78fb3-119d-42cd-ad06-399cf2798165' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f48c4e6d-f556-4a40-8c9a-9d25bdaf87e5' class='xr-var-data-in' type='checkbox'><label for='data-f48c4e6d-f556-4a40-8c9a-9d25bdaf87e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
+       "    transducer_sound_speed        (time1) float64 8B 1.5e+03</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1300c8c8-f32a-4c80-bcf5-932db99e8808' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-1300c8c8-f32a-4c80-bcf5-932db99e8808' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>sound_velocity_profile_depth</span>: 2</li></ul></div></li><li class='xr-section-item'><input id='section-46b8df18-986d-4c66-9811-271f973df403' class='xr-section-summary-in' type='checkbox' checked /><label for='section-46b8df18-986d-4c66-9811-271f973df403' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-1af2e925-10a2-47a0-9ac5-642544c447b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1af2e925-10a2-47a0-9ac5-642544c447b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ebdb352-7012-4101-99e5-bf4ac26d869b' class='xr-var-data-in' type='checkbox'><label for='data-6ebdb352-7012-4101-99e5-bf4ac26d869b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA position datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to environmental variables. Note that Platform.time3 is the same as Environment.time1.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>sound_velocity_profile_depth</span></div><div class='xr-var-dims'>(sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 1e+03</div><input id='attrs-46349704-2de5-4016-b25d-fc8381bf2520' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46349704-2de5-4016-b25d-fc8381bf2520' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1683322-9a75-4587-9948-bbbab98ecca8' class='xr-var-data-in' type='checkbox'><label for='data-f1683322-9a75-4587-9948-bbbab98ecca8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>axis :</span></dt><dd>Z</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([   1., 1000.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-42c71ced-46de-4582-a87e-6feefbf8912d' class='xr-section-summary-in' type='checkbox' checked /><label for='section-42c71ced-46de-4582-a87e-6feefbf8912d' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-58fcea3a-325d-4124-952c-06c31cf8a623' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-58fcea3a-325d-4124-952c-06c31cf8a623' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8060a38e-69b5-4ffb-9a43-87296282ffa7' class='xr-var-data-in' type='checkbox'><label for='data-8060a38e-69b5-4ffb-9a43-87296282ffa7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>acidity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-fecd93f5-2a45-4646-a574-5c91269e7108' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fecd93f5-2a45-4646-a574-5c91269e7108' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b89ce8f-19f4-4cbb-87fe-8599044a8456' class='xr-var-data-in' type='checkbox'><label for='data-0b89ce8f-19f4-4cbb-87fe-8599044a8456' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([8.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-625f6cfc-3148-4552-90d0-88835c3bf71e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-625f6cfc-3148-4552-90d0-88835c3bf71e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02191b16-4e75-4835-9f8d-3b6478a0fffd' class='xr-var-data-in' type='checkbox'><label for='data-02191b16-4e75-4835-9f8d-3b6478a0fffd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([32.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-ad83f69a-f13a-4e79-9b8d-6685d1d116fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad83f69a-f13a-4e79-9b8d-6685d1d116fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2be5191-8680-44e4-be1c-9016452d867f' class='xr-var-data-in' type='checkbox'><label for='data-b2be5191-8680-44e4-be1c-9016452d867f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([9.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed_indicative</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-c201a130-110d-49a7-8e6e-fdf430b1982d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c201a130-110d-49a7-8e6e-fdf430b1982d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08a8ef28-538d-4e40-8242-03e467948664' class='xr-var-data-in' type='checkbox'><label for='data-08a8ef28-538d-4e40-8242-03e467948664' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1485.4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_profile</span></div><div class='xr-var-dims'>(time1, sound_velocity_profile_depth)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03 1.485e+03</div><input id='attrs-83ccedd0-9832-432b-b84f-d2be61ec7609' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83ccedd0-9832-432b-b84f-d2be61ec7609' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ccbb2d8-7b84-4e81-b277-23ebb27fc052' class='xr-var-data-in' type='checkbox'><label for='data-5ccbb2d8-7b84-4e81-b277-23ebb27fc052' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sound velocity profile</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd><dt><span>units :</span></dt><dd>m/s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>parsed from raw data files as (depth, sound_speed) value pairs</dd></dl></div><div class='xr-var-data'><pre>array([[1485.4, 1485.4]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_velocity_source</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;Manual&#x27;</div><input id='attrs-d6f13e39-a163-4942-b7c6-95f2205c79ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d6f13e39-a163-4942-b7c6-95f2205c79ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20e3eaff-10f0-4fe4-9417-dce3123b329f' class='xr-var-data-in' type='checkbox'><label for='data-20e3eaff-10f0-4fe4-9417-dce3123b329f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Manual&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>&lt;U7</div><div class='xr-var-preview xr-preview'>&#x27;Unknown&#x27;</div><input id='attrs-48acf26c-970a-4fd2-99e2-421ff44a59c9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-48acf26c-970a-4fd2-99e2-421ff44a59c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8179fa3c-ec62-4e1f-91d3-368348c30512' class='xr-var-data-in' type='checkbox'><label for='data-8179fa3c-ec62-4e1f-91d3-368348c30512' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;Unknown&#x27;], dtype=&#x27;&lt;U7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_sound_speed</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+03</div><input id='attrs-d43e247c-d163-4dcf-8de5-4f5ef52974a7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d43e247c-d163-4dcf-8de5-4f5ef52974a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1af0e278-00ed-4c1e-8271-786692b74f44' class='xr-var-data-in' type='checkbox'><label for='data-1af0e278-00ed-4c1e-8271-786692b74f44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1500.])</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><li class=\"xr-section-list\"><input id=\"idata_2caaefaf61acd5231f7765cb6c9770fa\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_2caaefaf61acd5231f7765cb6c9770fa\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_d6302e41722f84d4a373af1907be84bb\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_d6302e41722f84d4a373af1907be84bb\" class=\"xr-section-summary\">Platform: contains information about the platform on which the sonar is installed.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -1830,19 +1830,19 @@
        "Attributes:\n",
        "    platform_name:       \n",
        "    platform_type:       \n",
-       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f3438db7-c95b-43ed-912a-5f24e0e75f28' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f3438db7-c95b-43ed-912a-5f24e0e75f28' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-7c1f2ab5-7624-43cc-9171-66e48fe53ca3' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c1f2ab5-7624-43cc-9171-66e48fe53ca3' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-2daedaba-719d-4a58-8f86-74c37b269349' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2daedaba-719d-4a58-8f86-74c37b269349' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-475f3967-0c5e-4d1d-be45-05325abd6a3b' class='xr-var-data-in' type='checkbox'><label for='data-475f3967-0c5e-4d1d-be45-05325abd6a3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-1c27c294-f73d-4848-ae33-51322d6d3cf8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c27c294-f73d-4848-ae33-51322d6d3cf8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3390f87-77dc-4ddf-b19f-9e3a3eae7b10' class='xr-var-data-in' type='checkbox'><label for='data-b3390f87-77dc-4ddf-b19f-9e3a3eae7b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "    platform_code_ICES:  </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-327aedc5-9339-4942-9cdd-022bba4755b5' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-327aedc5-9339-4942-9cdd-022bba4755b5' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4811c53a-bc4f-44f4-ad89-90cf9fb8c41b' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4811c53a-bc4f-44f4-ad89-90cf9fb8c41b' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-a381ba55-7090-449f-a81d-020355dfbe7b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a381ba55-7090-449f-a81d-020355dfbe7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc694780-2240-493d-821e-928d4599ac46' class='xr-var-data-in' type='checkbox'><label for='data-cc694780-2240-493d-821e-928d4599ac46' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a84dfd8a-5890-417f-9b14-1757441cd0ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a84dfd8a-5890-417f-9b14-1757441cd0ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-799901dd-3cd5-4b11-a25e-876189ee7092' class='xr-var-data-in' type='checkbox'><label for='data-799901dd-3cd5-4b11-a25e-876189ee7092' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-bd69fd79-ba80-430d-9401-924725055735' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd69fd79-ba80-430d-9401-924725055735' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f602ff0-9294-4fca-98a8-79db2c0ea8d7' class='xr-var-data-in' type='checkbox'><label for='data-9f602ff0-9294-4fca-98a8-79db2c0ea8d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-ede6f2b2-c292-4a79-a655-1041899db5f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ede6f2b2-c292-4a79-a655-1041899db5f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b316030-a6c1-4562-ae7e-4bf0f7774eb8' class='xr-var-data-in' type='checkbox'><label for='data-4b316030-a6c1-4562-ae7e-4bf0f7774eb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-81b52fbb-170a-4baa-9092-8a5cfef4fcfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-81b52fbb-170a-4baa-9092-8a5cfef4fcfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c60e6569-0f52-4e97-a61a-b4479533e747' class='xr-var-data-in' type='checkbox'><label for='data-c60e6569-0f52-4e97-a61a-b4479533e747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-33a9c5fd-5221-43ab-b83c-bdf91e5129c0' class='xr-section-summary-in' type='checkbox' /><label for='section-33a9c5fd-5221-43ab-b83c-bdf91e5129c0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-8775f1e5-6764-4a2c-a2be-ede40dcacec9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8775f1e5-6764-4a2c-a2be-ede40dcacec9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0d21760-d200-4e6c-910c-3bd4d19b572d' class='xr-var-data-in' type='checkbox'><label for='data-f0d21760-d200-4e6c-910c-3bd4d19b572d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e7d04f5-d77f-4d73-8f07-58e667960c60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e7d04f5-d77f-4d73-8f07-58e667960c60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e7f9245-998d-4b0d-8911-c24427fbb23c' class='xr-var-data-in' type='checkbox'><label for='data-8e7f9245-998d-4b0d-8911-c24427fbb23c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-1c2afac4-dfbd-4d22-aad3-5a1f83a58378' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c2afac4-dfbd-4d22-aad3-5a1f83a58378' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1125222-f66e-47fe-9c71-1c855e4e80b3' class='xr-var-data-in' type='checkbox'><label for='data-e1125222-f66e-47fe-9c71-1c855e4e80b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-4b6401f6-a55b-4cc2-974a-3c0691f993f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b6401f6-a55b-4cc2-974a-3c0691f993f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40e23467-bec8-4c0c-9298-0f1c86a6e2c2' class='xr-var-data-in' type='checkbox'><label for='data-40e23467-bec8-4c0c-9298-0f1c86a6e2c2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
-       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-b88ab12b-0696-4cd5-a4c8-240c009e6fe9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b88ab12b-0696-4cd5-a4c8-240c009e6fe9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c4c98e4-9d5e-45f6-ab4e-7b1acf0d216e' class='xr-var-data-in' type='checkbox'><label for='data-0c4c98e4-9d5e-45f6-ab4e-7b1acf0d216e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
-       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-aab60972-d8a4-4bf1-b671-002f56281b34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aab60972-d8a4-4bf1-b671-002f56281b34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e75528c-dd94-4036-a6cc-b062ec8a4389' class='xr-var-data-in' type='checkbox'><label for='data-5e75528c-dd94-4036-a6cc-b062ec8a4389' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-2739c187-5e7e-45cf-8dde-59a1fb52757a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2739c187-5e7e-45cf-8dde-59a1fb52757a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6310886e-e5fd-4fe0-a022-a40975b64c3b' class='xr-var-data-in' type='checkbox'><label for='data-6310886e-e5fd-4fe0-a022-a40975b64c3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-e9bea373-f3e8-4e7d-9bd8-0427354b4387' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e9bea373-f3e8-4e7d-9bd8-0427354b4387' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0de39ed-7d23-4bc0-a8fb-ea5fc10591b6' class='xr-var-data-in' type='checkbox'><label for='data-d0de39ed-7d23-4bc0-a8fb-ea5fc10591b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-e16553d1-65d7-49e9-b14c-6c51db0c5c32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e16553d1-65d7-49e9-b14c-6c51db0c5c32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cddbbe7d-323e-47ce-aabe-e9843283ecd0' class='xr-var-data-in' type='checkbox'><label for='data-cddbbe7d-323e-47ce-aabe-e9843283ecd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-165e4135-df6a-4523-8b98-85c2a3bdf47c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-165e4135-df6a-4523-8b98-85c2a3bdf47c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-325b4124-02a4-4e15-9fc7-81f2b0ed1454' class='xr-var-data-in' type='checkbox'><label for='data-325b4124-02a4-4e15-9fc7-81f2b0ed1454' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-bd0fa28d-40f3-4d3a-aff2-b137c1e016c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd0fa28d-40f3-4d3a-aff2-b137c1e016c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc6b645b-b60d-481d-a089-8d40d4c8ec75' class='xr-var-data-in' type='checkbox'><label for='data-fc6b645b-b60d-481d-a089-8d40d4c8ec75' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-6612ae11-9794-4d77-8619-1866add3734e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6612ae11-9794-4d77-8619-1866add3734e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27f19950-2773-472a-b925-46a8becdf000' class='xr-var-data-in' type='checkbox'><label for='data-27f19950-2773-472a-b925-46a8becdf000' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-59363ca5-f2a6-443f-80e1-b5daeff5e707' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59363ca5-f2a6-443f-80e1-b5daeff5e707' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9740d8f5-7035-45c5-8b5a-c4ffbd71ba43' class='xr-var-data-in' type='checkbox'><label for='data-9740d8f5-7035-45c5-8b5a-c4ffbd71ba43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2e78be18-6cce-4478-a0a1-3af6ceee3bb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e78be18-6cce-4478-a0a1-3af6ceee3bb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06e0ab36-64fc-444d-afe9-630ec6b3c302' class='xr-var-data-in' type='checkbox'><label for='data-06e0ab36-64fc-444d-afe9-630ec6b3c302' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2c81913c-dc05-47ea-9081-95512df9aa0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c81913c-dc05-47ea-9081-95512df9aa0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-376cf13c-28e6-4307-ab2f-e63284d50285' class='xr-var-data-in' type='checkbox'><label for='data-376cf13c-28e6-4307-ab2f-e63284d50285' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-7e7b9dcb-f0eb-4720-aca0-151811d10244' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e7b9dcb-f0eb-4720-aca0-151811d10244' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8941085f-690b-41f3-b02c-3764251fc565' class='xr-var-data-in' type='checkbox'><label for='data-8941085f-690b-41f3-b02c-3764251fc565' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-c2d0f870-699a-4ceb-a80f-7b2495c8bd92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2d0f870-699a-4ceb-a80f-7b2495c8bd92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-347b8132-04b8-481c-8469-5223c3b240c1' class='xr-var-data-in' type='checkbox'><label for='data-347b8132-04b8-481c-8469-5223c3b240c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-0614355f-bfc5-41d2-907a-9d4ac614464f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0614355f-bfc5-41d2-907a-9d4ac614464f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35b67c62-141f-45b6-8c66-d0ec2e74a3b1' class='xr-var-data-in' type='checkbox'><label for='data-35b67c62-141f-45b6-8c66-d0ec2e74a3b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-4e483728-207b-4ada-a689-35a2cd83ec08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e483728-207b-4ada-a689-35a2cd83ec08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c406df33-fdf2-4927-83cd-ef965adabb4c' class='xr-var-data-in' type='checkbox'><label for='data-c406df33-fdf2-4927-83cd-ef965adabb4c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-6eb4e23f-eb86-433e-8c96-5a0dc5a894c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6eb4e23f-eb86-433e-8c96-5a0dc5a894c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-004b8d22-48a0-4ffb-be46-1ef386bfde51' class='xr-var-data-in' type='checkbox'><label for='data-004b8d22-48a0-4ffb-be46-1ef386bfde51' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-3c9b1c25-c098-4381-b137-abe97ff8551c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c9b1c25-c098-4381-b137-abe97ff8551c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2270a9a9-8d6d-4232-adca-ffeb7740c605' class='xr-var-data-in' type='checkbox'><label for='data-2270a9a9-8d6d-4232-adca-ffeb7740c605' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-0c64e889-285f-4cbc-86a3-a8c4ad828848' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c64e889-285f-4cbc-86a3-a8c4ad828848' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-102db525-a351-4d83-b000-ce41273650ae' class='xr-var-data-in' type='checkbox'><label for='data-102db525-a351-4d83-b000-ce41273650ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-f22ce601-1ab8-4849-8866-42a794f85b82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f22ce601-1ab8-4849-8866-42a794f85b82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c61cf7c7-ea5d-4d8d-9688-a4b5786577e3' class='xr-var-data-in' type='checkbox'><label for='data-c61cf7c7-ea5d-4d8d-9688-a4b5786577e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-c29d3bf6-1072-4093-aa38-d5875c6dd693' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c29d3bf6-1072-4093-aa38-d5875c6dd693' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15bdc6bf-066c-43fc-8cc3-59bc089ee110' class='xr-var-data-in' type='checkbox'><label for='data-15bdc6bf-066c-43fc-8cc3-59bc089ee110' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
-       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-ffd2e270-0fb6-466a-9f87-da47a7123117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffd2e270-0fb6-466a-9f87-da47a7123117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-869e85ac-af60-4ca1-a7ff-e53b90bd6a42' class='xr-var-data-in' type='checkbox'><label for='data-869e85ac-af60-4ca1-a7ff-e53b90bd6a42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-12bd1958-c27f-4f23-ad96-7c7a05433677' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12bd1958-c27f-4f23-ad96-7c7a05433677' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30e91e24-380f-486c-a4b7-0f668ce54303' class='xr-var-data-in' type='checkbox'><label for='data-30e91e24-380f-486c-a4b7-0f668ce54303' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3f725047-b4e1-4931-84a7-b4d254c5a7fd' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3f725047-b4e1-4931-84a7-b4d254c5a7fd' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-f7b4f55a-218d-407c-8b46-f9d6caa56406' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7b4f55a-218d-407c-8b46-f9d6caa56406' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71802e7a-390e-4cf4-9fd9-6b25e83c1a69' class='xr-var-data-in' type='checkbox'><label for='data-71802e7a-390e-4cf4-9fd9-6b25e83c1a69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c9b31338-0879-454c-a52b-9b69c1ef194e' class='xr-section-summary-in' type='checkbox' /><label for='section-c9b31338-0879-454c-a52b-9b69c1ef194e' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>latitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-022f4b4b-7c3a-4604-baca-ce6739cacac0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-022f4b4b-7c3a-4604-baca-ce6739cacac0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd7874aa-8c29-4a4e-be42-e609098301b0' class='xr-var-data-in' type='checkbox'><label for='data-fd7874aa-8c29-4a4e-be42-e609098301b0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-03dfe483-d1c8-402f-85e4-a94d0af20959' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-03dfe483-d1c8-402f-85e4-a94d0af20959' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7b0e11f-f899-49c3-a676-5fc016d8375f' class='xr-var-data-in' type='checkbox'><label for='data-b7b0e11f-f899-49c3-a676-5fc016d8375f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sentence_type</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-d92ec861-83cd-4b59-8c74-c546e5565e4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d92ec861-83cd-4b59-8c74-c546e5565e4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fa0b6af-26b3-49a6-8cef-182190853bf9' class='xr-var-data-in' type='checkbox'><label for='data-5fa0b6af-26b3-49a6-8cef-182190853bf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA sentence type</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.34 0.34 0.4 ... -2.13 -2.02 -2.02</div><input id='attrs-ca59e1b7-29c4-43f2-b51b-2c94fd96f9a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca59e1b7-29c4-43f2-b51b-2c94fd96f9a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e66f2a2a-90ae-4234-a63e-fc2168d8cae8' class='xr-var-data-in' type='checkbox'><label for='data-e66f2a2a-90ae-4234-a63e-fc2168d8cae8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.34      ,  0.34      ,  0.40000001, ..., -2.13000011,\n",
+       "       -2.01999998, -2.01999998], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.73 1.73 1.28 ... -2.93 -2.93</div><input id='attrs-25822c41-5198-484c-b685-ef1b72f04137' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25822c41-5198-484c-b685-ef1b72f04137' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1040c795-cc06-419f-a9ed-81174ab26157' class='xr-var-data-in' type='checkbox'><label for='data-1040c795-cc06-419f-a9ed-81174ab26157' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll_angle</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd></dl></div><div class='xr-var-data'><pre>array([ 1.73000002,  1.73000002,  1.27999997, ..., -3.16000009,\n",
+       "       -2.93000007, -2.93000007], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vertical_offset</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-0d984482-09c6-434f-8e61-1d7b7f15d395' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d984482-09c6-434f-8e61-1d7b7f15d395' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f64b4828-868b-4976-9641-b5e20c61fee7' class='xr-var-data-in' type='checkbox'><label for='data-f64b4828-868b-4976-9641-b5e20c61fee7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform vertical offset from nominal water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-11eb24d2-b08a-4bc4-9f86-aacf64b2658c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11eb24d2-b08a-4bc4-9f86-aacf64b2658c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b8ad22d1-fbff-4987-a786-81a922361316' class='xr-var-data-in' type='checkbox'><label for='data-b8ad22d1-fbff-4987-a786-81a922361316' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-6f76998f-28ee-4c52-abc8-0dfdd28348c0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6f76998f-28ee-4c52-abc8-0dfdd28348c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6155e902-1864-491f-9c8a-81db8a551db9' class='xr-var-data-in' type='checkbox'><label for='data-6155e902-1864-491f-9c8a-81db8a551db9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drop_keel_offset_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bb0ea270-cd95-4b0e-8f31-9673a90a64a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bb0ea270-cd95-4b0e-8f31-9673a90a64a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e0299b4-e1f5-4f11-bd69-98f5d756e808' class='xr-var-data-in' type='checkbox'><label for='data-4e0299b4-e1f5-4f11-bd69-98f5d756e808' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level_draft_is_manual</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-0f9a16fc-6c92-422d-9b60-18c0e90144ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f9a16fc-6c92-422d-9b60-18c0e90144ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b60e8cc-c1b5-40e1-9d3e-13f6beb1a61e' class='xr-var-data-in' type='checkbox'><label for='data-5b60e8cc-c1b5-40e1-9d3e-13f6beb1a61e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-8b9c04ac-cfc7-4703-8074-5b4ef44cad2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b9c04ac-cfc7-4703-8074-5b4ef44cad2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0d5a1db-77ce-43c9-9d4b-116684d061a7' class='xr-var-data-in' type='checkbox'><label for='data-d0d5a1db-77ce-43c9-9d4b-116684d061a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-518d4b58-7e56-4e3e-acbf-9d39e4838fb5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-518d4b58-7e56-4e3e-acbf-9d39e4838fb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8c8871f-35e5-4b05-becd-01231e0c0980' class='xr-var-data-in' type='checkbox'><label for='data-d8c8871f-35e5-4b05-becd-01231e0c0980' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_offset_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0</div><input id='attrs-96d5b7a9-3179-4533-b3bc-91bc79ca3990' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96d5b7a9-3179-4533-b3bc-91bc79ca3990' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac290853-813d-43f1-99fb-04af35b529a7' class='xr-var-data-in' type='checkbox'><label for='data-ac290853-813d-43f1-99fb-04af35b529a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-axis distance from the platform coordinate system origin to the sonar transducer</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-146b5f0d-32b2-4e3f-945d-f657b0b55bde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-146b5f0d-32b2-4e3f-945d-f657b0b55bde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-671db071-e17e-4318-8498-95db4af5ffcb' class='xr-var-data-in' type='checkbox'><label for='data-671db071-e17e-4318-8498-95db4af5ffcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-8d0f6cb7-0405-43fe-8b88-03e7555ba721' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d0f6cb7-0405-43fe-8b88-03e7555ba721' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36afad5d-6cf6-4260-bf78-6d068960e810' class='xr-var-data-in' type='checkbox'><label for='data-36afad5d-6cf6-4260-bf78-6d068960e810' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-538f41a0-4259-4118-bf9b-3a1dd1dec797' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-538f41a0-4259-4118-bf9b-3a1dd1dec797' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a525abf6-511f-4209-86c2-fa9fba9483e7' class='xr-var-data-in' type='checkbox'><label for='data-a525abf6-511f-4209-86c2-fa9fba9483e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the motion reference unit sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-337da16e-b187-4de0-a80f-ce626674de12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-337da16e-b187-4de0-a80f-ce626674de12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d46d3cf-a106-4426-9eda-911ba08f189b' class='xr-var-data-in' type='checkbox'><label for='data-3d46d3cf-a106-4426-9eda-911ba08f189b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the x-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-f6a7fe4e-14a8-4116-8c5d-266fcf3e8b85' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6a7fe4e-14a8-4116-8c5d-266fcf3e8b85' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-011ca185-4da1-4a87-9485-5da1cddb5453' class='xr-var-data-in' type='checkbox'><label for='data-011ca185-4da1-4a87-9485-5da1cddb5453' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the y-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>MRU_rotation_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2df47ebe-d50d-4e62-89e5-c050029cf227' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2df47ebe-d50d-4e62-89e5-c050029cf227' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56fa0747-fd82-40de-b494-7f3a94c66e30' class='xr-var-data-in' type='checkbox'><label for='data-56fa0747-fd82-40de-b494-7f3a94c66e30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Extrinsic rotation about the z-axis from the platform to MRU coordinate systems</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(–180.0, 180.0)</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-089d368f-ee25-4582-af6b-608fe0010bd9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-089d368f-ee25-4582-af6b-608fe0010bd9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12ffb1b8-b0d8-46f4-a136-c794ef0696e5' class='xr-var-data-in' type='checkbox'><label for='data-12ffb1b8-b0d8-46f4-a136-c794ef0696e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the x-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-6c6c5216-1d0e-469c-8e7f-a30acf887ee7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c6c5216-1d0e-469c-8e7f-a30acf887ee7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00cfe31c-9867-498a-9b0b-4c518ef45b8d' class='xr-var-data-in' type='checkbox'><label for='data-00cfe31c-9867-498a-9b0b-4c518ef45b8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the y-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>position_offset_z</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-27f2751c-a95c-4e01-876d-7aa1ee4a7cea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27f2751c-a95c-4e01-876d-7aa1ee4a7cea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df1c4be2-fd33-4c80-94df-560178ca19c1' class='xr-var-data-in' type='checkbox'><label for='data-df1c4be2-fd33-4c80-94df-560178ca19c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance along the z-axis from the platform coordinate system origin to the latitude/longitude sensor origin</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(nan)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-719d974a-0fd6-4987-9c95-d5453c36e255' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-719d974a-0fd6-4987-9c95-d5453c36e255' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cac27c06-c848-49c4-9d8a-59ac4f42a57d' class='xr-var-data-in' type='checkbox'><label for='data-cac27c06-c848-49c4-9d8a-59ac4f42a57d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.46 1.46 1.46 ... 0.04 0.04 0.04</div><input id='attrs-af1012e2-dd96-45d2-9aa0-76306968381e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af1012e2-dd96-45d2-9aa0-76306968381e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ceb74fe-64ec-4b5b-8366-b4ae335ebf0c' class='xr-var-data-in' type='checkbox'><label for='data-7ceb74fe-64ec-4b5b-8366-b4ae335ebf0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform heading (true)</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>valid_max :</span></dt><dd>360.0</dd></dl></div><div class='xr-var-data'><pre>array([1.46000004, 1.46000004, 1.46000004, ..., 0.04      , 0.04      ,\n",
+       "       0.04      ], shape=(1266,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>latitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-2e856569-92b8-4211-ac37-108c2289377f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e856569-92b8-4211-ac37-108c2289377f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a013324-2e17-46e0-b757-33f5ff7339a7' class='xr-var-data-in' type='checkbox'><label for='data-1a013324-2e17-46e0-b757-33f5ff7339a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>valid_range :</span></dt><dd>(-90.0, 90.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>longitude_mru1</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan</div><input id='attrs-c1c16e43-b567-4f42-899d-1bb38aff3daa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1c16e43-b567-4f42-899d-1bb38aff3daa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d22ab179-0fa6-452c-b120-e284c2a50e20' class='xr-var-data-in' type='checkbox'><label for='data-d22ab179-0fa6-452c-b120-e284c2a50e20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Platform longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>valid_range :</span></dt><dd>(-180.0, 180.0)</dd><dt><span>comment :</span></dt><dd>Derived from the Simrad MRU1 Datagrams which are a wrapper of the Kongsberg Maritime Binary Datagrams.</dd></dl></div><div class='xr-var-data'><pre>array([nan])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-439af2dd-522f-44f2-bdbf-044a3071d27e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-439af2dd-522f-44f2-bdbf-044a3071d27e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>platform_name :</span></dt><dd></dd><dt><span>platform_type :</span></dt><dd></dd><dt><span>platform_code_ICES :</span></dt><dd></dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_5e5f256a0eb846f1ee15ba21cda6cda0\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_5e5f256a0eb846f1ee15ba21cda6cda0\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_0397fd596f87c6dc390cf5867fc631fd\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_0397fd596f87c6dc390cf5867fc631fd\" class=\"xr-section-summary\">NMEA: contains information specific to the NMEA protocol.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -2399,22 +2399,22 @@
        "Data variables:\n",
        "    NMEA_datagram  (nmea_time) &lt;U26 453kB &#x27;$SDVLW,630.103,N,630.103,N&#x27; ... &#x27;$...\n",
        "Attributes:\n",
-       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ab03e6bf-faae-46c5-ba95-3ef00a6dfab1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ab03e6bf-faae-46c5-ba95-3ef00a6dfab1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-f99d42eb-3dea-4847-a867-4a8a900a6be4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f99d42eb-3dea-4847-a867-4a8a900a6be4' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-c0801019-3c4d-47fc-b302-09ac340a83d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0801019-3c4d-47fc-b302-09ac340a83d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-481820d9-84ef-4caf-91b6-cbe56ee2acf8' class='xr-var-data-in' type='checkbox'><label for='data-481820d9-84ef-4caf-91b6-cbe56ee2acf8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
+       "    description:  All NMEA sensor datagrams</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4e099fa4-ece2-4545-9778-1868db3476a8' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4e099fa4-ece2-4545-9778-1868db3476a8' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>nmea_time</span>: 4351</li><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>time1</span>: 1</li><li><span class='xr-has-index'>time2</span>: 1266</li><li><span class='xr-has-index'>time3</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-2193a899-ce0b-4932-bc34-b4f7c739130a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-2193a899-ce0b-4932-bc34-b4f7c739130a' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>nmea_time</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-c40ec5af-9e4c-455b-83ee-0b6bd4cb874b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c40ec5af-9e4c-455b-83ee-0b6bd4cb874b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-515f1ceb-9b02-4a6e-89e5-d25b89ac897b' class='xr-var-data-in' type='checkbox'><label for='data-515f1ceb-9b02-4a6e-89e5-d25b89ac897b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA sensor data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.661453000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:32.825344000&#x27;, ..., &#x27;2021-12-15T14:40:09.311146000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.381834000&#x27;, &#x27;2021-12-15T14:40:09.456507000&#x27;],\n",
-       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-10b6daac-14bd-4f00-88ab-da21153bfadc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10b6daac-14bd-4f00-88ab-da21153bfadc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a52a84d1-5610-4eee-82f0-4a260bbf5100' class='xr-var-data-in' type='checkbox'><label for='data-a52a84d1-5610-4eee-82f0-4a260bbf5100' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(4351,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-dac0f9d7-9ef0-4fa5-a185-1d6aeb295324' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dac0f9d7-9ef0-4fa5-a185-1d6aeb295324' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab420ae6-6b76-430b-b74c-899973ffc228' class='xr-var-data-in' type='checkbox'><label for='data-ab420ae6-6b76-430b-b74c-899973ffc228' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-30b02f71-b952-4b15-bf79-6845be0db4cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-30b02f71-b952-4b15-bf79-6845be0db4cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f49f2b15-2400-48eb-84c2-de80d60c5fab' class='xr-var-data-in' type='checkbox'><label for='data-f49f2b15-2400-48eb-84c2-de80d60c5fab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-a834bbb8-db8d-40f7-85a3-3b46312f5d10' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a834bbb8-db8d-40f7-85a3-3b46312f5d10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7766e6c4-0280-41f7-b3cb-cf0249691ca1' class='xr-var-data-in' type='checkbox'><label for='data-7766e6c4-0280-41f7-b3cb-cf0249691ca1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time1</span></div><div class='xr-var-dims'>(time1)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-d8f8bffc-dcf4-4cbf-bea4-1bf701f0a264' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8f8bffc-dcf4-4cbf-bea4-1bf701f0a264' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4e0facc-7d14-46f7-8771-3d92225c7657' class='xr-var-data-in' type='checkbox'><label for='data-e4e0facc-7d14-46f7-8771-3d92225c7657' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for NMEA datagrams</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to NMEA position data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time2</span></div><div class='xr-var-dims'>(time2)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-b8d33944-292a-419d-a47a-4becdb4dd2b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8d33944-292a-419d-a47a-4becdb4dd2b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-696cea83-0c4f-4daf-8db8-bbaf84d743e3' class='xr-var-data-in' type='checkbox'><label for='data-696cea83-0c4f-4daf-8db8-bbaf84d743e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-461a7d0a-71a2-4e4e-9529-2b6c857075ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-461a7d0a-71a2-4e4e-9529-2b6c857075ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e1a5768-0f3d-46e5-963d-51f4391cd0b3' class='xr-var-data-in' type='checkbox'><label for='data-3e1a5768-0f3d-46e5-963d-51f4391cd0b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-810f2fca-e83a-4758-b95d-fdd09b2628e4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-810f2fca-e83a-4758-b95d-fdd09b2628e4' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-dd846d3f-f26c-43c4-b2a8-94d49e915363' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd846d3f-f26c-43c4-b2a8-94d49e915363' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc831e00-52ea-4a33-8c82-f0c75fa9401f' class='xr-var-data-in' type='checkbox'><label for='data-cc831e00-52ea-4a33-8c82-f0c75fa9401f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time3</span></div><div class='xr-var-dims'>(time3)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-cc49717e-ccdd-449f-b451-03ed7ff89238' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc49717e-ccdd-449f-b451-03ed7ff89238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e433f0c0-2beb-4627-aeb4-f9c0ec74f847' class='xr-var-data-in' type='checkbox'><label for='data-e433f0c0-2beb-4627-aeb4-f9c0ec74f847' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>Timestamps for platform motion and orientation data from the Kongsberg Maritime Binary Datagram</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>comment :</span></dt><dd>Time coordinate corresponding to platform motion and orientation data from the Kongsberg Maritime Binary Datagram.</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-be95ee4b-848c-4e79-8f12-80fcec407347' class='xr-section-summary-in' type='checkbox' checked /><label for='section-be95ee4b-848c-4e79-8f12-80fcec407347' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>NMEA_datagram</span></div><div class='xr-var-dims'>(nmea_time)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;$SDVLW,630.103,N,630.103,N&#x27; ......</div><input id='attrs-6fcbbfe1-ef59-47a1-bb38-70285a3e2a22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fcbbfe1-ef59-47a1-bb38-70285a3e2a22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2da638b4-07be-44a3-8490-550472a96b40' class='xr-var-data-in' type='checkbox'><label for='data-2da638b4-07be-44a3-8490-550472a96b40' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>NMEA datagram</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;$SDVLW,630.103,N,630.103,N&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
        "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, ..., &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;,\n",
        "       &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;, &#x27;$IIDBS,1.6,f,0.5,M,0.3,F&#x27;],\n",
-       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7c0ad2bf-cc41-4dc2-9a01-a96fc8439802' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7c0ad2bf-cc41-4dc2-9a01-a96fc8439802' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      shape=(4351,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3bb3ba10-b52d-4dd5-90aa-cfdc0960a332' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3bb3ba10-b52d-4dd5-90aa-cfdc0960a332' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>All NMEA sensor datagrams</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_fc759f4bd03ec0b9edadc04249f655fb\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_fc759f4bd03ec0b9edadc04249f655fb\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_6f24c11b32254a9d9b50a55b529d0b32\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_6f24c11b32254a9d9b50a55b529d0b32\" class=\"xr-section-summary\">Provenance: contains metadata about how the SONAR-netCDF4 version of the data were obtained.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -2969,12 +2969,12 @@
        "Attributes:\n",
        "    conversion_software_name:     echopype\n",
        "    conversion_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    conversion_time:              2026-06-19T22:27:36+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9546de2f-55f2-404a-a0c6-b6ba488f8985' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-9546de2f-55f2-404a-a0c6-b6ba488f8985' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-c5bacf51-03c5-413a-a76c-3903929eaee1' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c5bacf51-03c5-413a-a76c-3903929eaee1' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bd5f06a2-1625-4ecb-8349-8630c6cd991f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd5f06a2-1625-4ecb-8349-8630c6cd991f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1302b8e3-8e13-4cab-9270-f9f7abad1f19' class='xr-var-data-in' type='checkbox'><label for='data-1302b8e3-8e13-4cab-9270-f9f7abad1f19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5ed6b1d9-399c-4aa7-8d18-62e9998cb277' class='xr-section-summary-in' type='checkbox' checked /><label for='section-5ed6b1d9-399c-4aa7-8d18-62e9998cb277' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a0e813e3-fba7-49cf-b2ba-bea993f9eee7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0e813e3-fba7-49cf-b2ba-bea993f9eee7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-313f3b69-032b-42fa-99e8-9c6fce2c735d' class='xr-var-data-in' type='checkbox'><label for='data-313f3b69-032b-42fa-99e8-9c6fce2c735d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9df7e6c1-c36e-485a-81bd-bc414239ddef' class='xr-section-summary-in' type='checkbox' checked /><label for='section-9df7e6c1-c36e-485a-81bd-bc414239ddef' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>conversion_time :</span></dt><dd>2026-06-19T22:27:36+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
+       "    conversion_time:              2026-06-20T23:48:16+00:00</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d2d5ed05-f8c4-4484-99ce-b502444974b2' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d2d5ed05-f8c4-4484-99ce-b502444974b2' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-63a365e8-75c5-4735-8126-4c28c5b682a3' class='xr-section-summary-in' type='checkbox' checked /><label for='section-63a365e8-75c5-4735-8126-4c28c5b682a3' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bbc4724f-1fa1-4420-8360-9a228a2fc6fa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bbc4724f-1fa1-4420-8360-9a228a2fc6fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e6e70cd-2e6e-44fb-9ff5-0ca6159c84d8' class='xr-var-data-in' type='checkbox'><label for='data-8e6e70cd-2e6e-44fb-9ff5-0ca6159c84d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8102cf9a-ce76-45e9-b1d9-860ece857eb5' class='xr-section-summary-in' type='checkbox' checked /><label for='section-8102cf9a-ce76-45e9-b1d9-860ece857eb5' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-25ad3eae-7812-497a-907b-4ef06861c5cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25ad3eae-7812-497a-907b-4ef06861c5cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-beed36c7-4bb4-4036-a70d-c876c3aa19b9' class='xr-var-data-in' type='checkbox'><label for='data-beed36c7-4bb4-4036-a70d-c876c3aa19b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dc978d97-e718-42a0-842a-34e2a3099cbd' class='xr-section-summary-in' type='checkbox' checked /><label for='section-dc978d97-e718-42a0-842a-34e2a3099cbd' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>conversion_software_name :</span></dt><dd>echopype</dd><dt><span>conversion_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>conversion_time :</span></dt><dd>2026-06-20T23:48:16+00:00</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><li class=\"xr-section-list\"><input id=\"idata_e017acaf583ff66d9b16ff6d413232ed\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_e017acaf583ff66d9b16ff6d413232ed\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
+       "                </li><li class=\"xr-section-list\"><input id=\"idata_7eb9d6251e8ad56cbd04abb5e4bbde67\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_7eb9d6251e8ad56cbd04abb5e4bbde67\" class=\"xr-section-summary\">Sonar: contains sonar system metadata and sonar beam groups.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -3540,14 +3540,14 @@
        "    sonar_serial_number:     \n",
        "    sonar_software_name:     \n",
        "    sonar_software_version:  21.15.0.0\n",
-       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f32c58cd-f9bc-4c58-aac0-0f96591d1c8c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-f32c58cd-f9bc-4c58-aac0-0f96591d1c8c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-32e60346-0fbc-4c0b-8ad6-e867a8692c81' class='xr-section-summary-in' type='checkbox' checked /><label for='section-32e60346-0fbc-4c0b-8ad6-e867a8692c81' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-0b08d36a-55da-4707-bcc9-f9c5788a1a0a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b08d36a-55da-4707-bcc9-f9c5788a1a0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f535f44c-5df8-4aa4-b164-69abdefc4955' class='xr-var-data-in' type='checkbox'><label for='data-f535f44c-5df8-4aa4-b164-69abdefc4955' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    sonar_type:              echosounder</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1995a849-28db-403a-88ea-185c82fe2b91' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-1995a849-28db-403a-88ea-185c82fe2b91' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group</span>: 1</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-233e1bbe-1cce-493e-ade0-5e16a2fa2521' class='xr-section-summary-in' type='checkbox' checked /><label for='section-233e1bbe-1cce-493e-ade0-5e16a2fa2521' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-b043bdbc-2657-48b3-a372-f3ed7e66d761' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b043bdbc-2657-48b3-a372-f3ed7e66d761' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1438dd7-4d35-43b5-9c1b-88e4efae3d7a' class='xr-var-data-in' type='checkbox'><label for='data-c1438dd7-4d35-43b5-9c1b-88e4efae3d7a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-3b3e89bb-cdc0-4261-b23c-63602e77ab22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b3e89bb-cdc0-4261-b23c-63602e77ab22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5235f98-8767-4fcc-b87b-d240bcaded9b' class='xr-var-data-in' type='checkbox'><label for='data-c5235f98-8767-4fcc-b87b-d240bcaded9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-61d64ba3-b092-4f3f-b085-657a4359d686' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61d64ba3-b092-4f3f-b085-657a4359d686' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef7f185c-2774-4e34-b61a-cb732db98d07' class='xr-var-data-in' type='checkbox'><label for='data-ef7f185c-2774-4e34-b61a-cb732db98d07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-63d7f800-a37a-46be-8543-e4c938fd5632' class='xr-section-summary-in' type='checkbox' checked /><label for='section-63d7f800-a37a-46be-8543-e4c938fd5632' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-11b87fec-11bc-44a8-ac7c-e73938eb5767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b87fec-11bc-44a8-ac7c-e73938eb5767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9897c83-f0e2-42c4-a451-c99676830371' class='xr-var-data-in' type='checkbox'><label for='data-d9897c83-f0e2-42c4-a451-c99676830371' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-3134e8af-9855-4bf7-8813-b6ba9e17245b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3134e8af-9855-4bf7-8813-b6ba9e17245b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3a3f02e-c9a4-4e96-bb12-fd16b46c08a7' class='xr-var-data-in' type='checkbox'><label for='data-a3a3f02e-c9a4-4e96-bb12-fd16b46c08a7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-ce5e816d-efa3-45d7-8432-db74bc9538a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce5e816d-efa3-45d7-8432-db74bc9538a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-554f01a1-37f0-4117-8138-2cb448febaf5' class='xr-var-data-in' type='checkbox'><label for='data-554f01a1-37f0-4117-8138-2cb448febaf5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-c1d22575-a630-4f4a-b7d1-f64e64e68919' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1d22575-a630-4f4a-b7d1-f64e64e68919' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c524d8-de22-493e-a8f4-809dc4e2a1f4' class='xr-var-data-in' type='checkbox'><label for='data-f4c524d8-de22-493e-a8f4-809dc4e2a1f4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-5f06b944-39f6-422e-9b7d-bed0b9d3d7f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f06b944-39f6-422e-9b7d-bed0b9d3d7f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-18620fa5-a1b5-4299-9ac7-f82d5ea3b04f' class='xr-var-data-in' type='checkbox'><label for='data-18620fa5-a1b5-4299-9ac7-f82d5ea3b04f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
-       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-a497ce38-e366-482a-8d14-299df70668c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a497ce38-e366-482a-8d14-299df70668c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-655855a2-e416-4822-a981-20b916093e90' class='xr-var-data-in' type='checkbox'><label for='data-655855a2-e416-4822-a981-20b916093e90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95f4aeb2-d411-4c72-b3c7-81dad442297f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-95f4aeb2-d411-4c72-b3c7-81dad442297f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-a67685a8-7916-48a4-aebb-2eb0e48ac755' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a67685a8-7916-48a4-aebb-2eb0e48ac755' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc52a52-6fef-4784-a65e-e85b33024dca' class='xr-var-data-in' type='checkbox'><label for='data-2cc52a52-6fef-4784-a65e-e85b33024dca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-996d2a4b-c125-4b99-879c-2af1542db317' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-996d2a4b-c125-4b99-879c-2af1542db317' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02972114-9c14-47f8-96c9-c0e24d4786c9' class='xr-var-data-in' type='checkbox'><label for='data-02972114-9c14-47f8-96c9-c0e24d4786c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2f122ed7-c3cd-420b-860c-fea977ceffd0' class='xr-section-summary-in' type='checkbox' checked /><label for='section-2f122ed7-c3cd-420b-860c-fea977ceffd0' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-59c79847-ce0a-46b6-be75-edf8425451fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59c79847-ce0a-46b6-be75-edf8425451fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90ce6c80-3c60-4ae3-95c4-6d128281131c' class='xr-var-data-in' type='checkbox'><label for='data-90ce6c80-3c60-4ae3-95c4-6d128281131c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U6</div><div class='xr-var-preview xr-preview'>&#x27;747008&#x27; &#x27;747015&#x27; &#x27;747019&#x27; &#x27;747022&#x27;</div><input id='attrs-20e2512b-73c4-4a73-82f1-48e10e9ed547' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20e2512b-73c4-4a73-82f1-48e10e9ed547' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dc22f75-ef7b-4c9f-832c-4bd89ba5f1f0' class='xr-var-data-in' type='checkbox'><label for='data-7dc22f75-ef7b-4c9f-832c-4bd89ba5f1f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;747008&#x27;, &#x27;747015&#x27;, &#x27;747019&#x27;, &#x27;747022&#x27;], dtype=&#x27;&lt;U6&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_name</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U9</div><div class='xr-var-preview xr-preview'>&#x27;ES333-7CD&#x27; ... &#x27;ES120-7CD&#x27;</div><input id='attrs-936d2aec-1a8d-45c1-b61b-8fb701413432' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-936d2aec-1a8d-45c1-b61b-8fb701413432' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01b2a535-83b0-4c1d-b70e-42b7175a3c9d' class='xr-var-data-in' type='checkbox'><label for='data-01b2a535-83b0-4c1d-b70e-42b7175a3c9d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;ES333-7CD&#x27;, &#x27;ES70-7CD&#x27;, &#x27;ES200-7CD&#x27;, &#x27;ES120-7CD&#x27;], dtype=&#x27;&lt;U9&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transducer_serial_number</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;220&#x27; &#x27;134&#x27; &#x27;166&#x27; &#x27;146&#x27;</div><input id='attrs-91fffe43-a9c5-4937-bf58-fb2a7d987f0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91fffe43-a9c5-4937-bf58-fb2a7d987f0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56f8944e-b170-4617-ab09-ce1d3a5ac98a' class='xr-var-data-in' type='checkbox'><label for='data-56f8944e-b170-4617-ab09-ce1d3a5ac98a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transducer serial number</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;220&#x27;, &#x27;134&#x27;, &#x27;166&#x27;, &#x27;146&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_group_descr</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U93</div><div class='xr-var-preview xr-preview'>&#x27;contains FM-only or CW-only com...</div><input id='attrs-c54169be-046b-4ccc-ad67-37751abcbe37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c54169be-046b-4ccc-ad67-37751abcbe37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3413ebc-e4cc-4a5f-81e4-c73ef0a0c001' class='xr-var-data-in' type='checkbox'><label for='data-e3413ebc-e4cc-4a5f-81e4-c73ef0a0c001' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group description</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.&#x27;],\n",
+       "      dtype=&#x27;&lt;U93&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>waveform_encode_descr</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;complex_FM&#x27;</div><input id='attrs-0907e737-dead-44ae-9515-f0eb2952759c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0907e737-dead-44ae-9515-f0eb2952759c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42d39457-8b6d-48ec-b36d-b1efa18c364e' class='xr-var-data-in' type='checkbox'><label for='data-42d39457-8b6d-48ec-b36d-b1efa18c364e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;complex_FM&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-22dca50d-81ae-4b12-98aa-431ec498b52d' class='xr-section-summary-in' type='checkbox' checked /><label for='section-22dca50d-81ae-4b12-98aa-431ec498b52d' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>sonar_manufacturer :</span></dt><dd>Simrad</dd><dt><span>sonar_model :</span></dt><dd>EK80</dd><dt><span>sonar_serial_number :</span></dt><dd></dd><dt><span>sonar_software_name :</span></dt><dd></dd><dt><span>sonar_software_version :</span></dt><dd>21.15.0.0</dd><dt><span>sonar_type :</span></dt><dd>echosounder</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_9a571ee6078d0483d2474ada8d6dca21\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_9a571ee6078d0483d2474ada8d6dca21\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
+       "                </li><ul><li class=\"xr-section-list\"><input id=\"idata_c26295eeb4312311e8f2f3838890127c\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_c26295eeb4312311e8f2f3838890127c\" class=\"xr-section-summary\">Beam_group1: contains FM-only or CW-only complex backscatter data and other beam or channel-specific data.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -4122,14 +4122,14 @@
        "    transmit_frequency_stop        (channel, ping_time) float64 41kB 3.8e+05 ...\n",
        "Attributes:\n",
        "    beam_mode:              vertical\n",
-       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-16714ab7-ba53-4d02-b47d-3c21c2edf560' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-16714ab7-ba53-4d02-b47d-3c21c2edf560' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ebabef8e-4c98-4cd1-8580-818e6b716b05' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ebabef8e-4c98-4cd1-8580-818e6b716b05' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-b0b40441-8944-4af1-9461-eed9f9ee2bf4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0b40441-8944-4af1-9461-eed9f9ee2bf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5011029b-0a5d-4563-8e4e-4a46e66d8e02' class='xr-var-data-in' type='checkbox'><label for='data-5011029b-0a5d-4563-8e4e-4a46e66d8e02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    conversion_equation_t:  type_3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d6c20b4d-93e2-4834-be57-10a6b214bef5' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d6c20b4d-93e2-4834-be57-10a6b214bef5' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>channel_all</span>: 4</li><li><span class='xr-has-index'>beam_group_index</span>: 1</li><li><span class='xr-has-index'>beam_group</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-38363bd7-e110-46da-bbe4-8f877fa20a34' class='xr-section-summary-in' type='checkbox' checked /><label for='section-38363bd7-e110-46da-bbe4-8f877fa20a34' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-87cbbd6f-00b9-49d8-b6c6-2dafe414f3eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87cbbd6f-00b9-49d8-b6c6-2dafe414f3eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efc772c0-b851-4315-9b89-53382959ad6d' class='xr-var-data-in' type='checkbox'><label for='data-efc772c0-b851-4315-9b89-53382959ad6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-4c2c1968-4398-4031-91ae-26b55100c8cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c2c1968-4398-4031-91ae-26b55100c8cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c50ef79-050a-4572-9255-432b12bf6992' class='xr-var-data-in' type='checkbox'><label for='data-8c50ef79-050a-4572-9255-432b12bf6992' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-862d4e0a-7e7e-42bf-9fe8-95066309d3be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-862d4e0a-7e7e-42bf-9fe8-95066309d3be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ec6364e-e218-4ab7-bdf9-894c59eb7718' class='xr-var-data-in' type='checkbox'><label for='data-8ec6364e-e218-4ab7-bdf9-894c59eb7718' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-ca952524-e9c6-407d-b5ec-1748765cd236' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ca952524-e9c6-407d-b5ec-1748765cd236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1b0534b-57a3-4c1f-bee8-6edbe2d19c10' class='xr-var-data-in' type='checkbox'><label for='data-d1b0534b-57a3-4c1f-bee8-6edbe2d19c10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-6dce6893-b8dc-48de-8ac7-3bbe7428f7fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6dce6893-b8dc-48de-8ac7-3bbe7428f7fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b93c522-dec1-44c8-8bbc-88dd61503a73' class='xr-var-data-in' type='checkbox'><label for='data-0b93c522-dec1-44c8-8bbc-88dd61503a73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-1b21242c-b9b2-48fc-bcad-975040559ddd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1b21242c-b9b2-48fc-bcad-975040559ddd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e292630a-11e9-4a81-ba38-4321b228c2cb' class='xr-var-data-in' type='checkbox'><label for='data-e292630a-11e9-4a81-ba38-4321b228c2cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-fb965b96-0726-45f0-abb9-3706feacf429' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb965b96-0726-45f0-abb9-3706feacf429' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a39b7e95-ef67-4540-866d-d2b783ce8d0e' class='xr-var-data-in' type='checkbox'><label for='data-a39b7e95-ef67-4540-866d-d2b783ce8d0e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam</span></div><div class='xr-var-dims'>(beam)</div><div class='xr-var-dtype'>&lt;U21</div><div class='xr-var-preview xr-preview'>&#x27;1&#x27; &#x27;2&#x27; &#x27;3&#x27; &#x27;4&#x27;</div><input id='attrs-0153b46b-eeca-47ae-a14b-41d3c32613bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0153b46b-eeca-47ae-a14b-41d3c32613bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4d3ec03-638c-43ff-9382-9a3f6823e477' class='xr-var-data-in' type='checkbox'><label for='data-b4d3ec03-638c-43ff-9382-9a3f6823e477' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1&#x27;, &#x27;2&#x27;, &#x27;3&#x27;, &#x27;4&#x27;], dtype=&#x27;&lt;U21&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel_all</span></div><div class='xr-var-dims'>(channel_all)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-acc9e1ae-9cd5-4698-b8dd-a09140a64f13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-acc9e1ae-9cd5-4698-b8dd-a09140a64f13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c245ca6-17a9-4868-a9cb-99ca2d06f887' class='xr-var-data-in' type='checkbox'><label for='data-2c245ca6-17a9-4868-a9cb-99ca2d06f887' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Vendor channel ID</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-c09385ec-1a86-43b2-be9b-29c875bd6403' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c09385ec-1a86-43b2-be9b-29c875bd6403' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3eb05c5b-a3c0-4495-8a31-366a94ee523d' class='xr-var-data-in' type='checkbox'><label for='data-3eb05c5b-a3c0-4495-8a31-366a94ee523d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-255ebe58-51e9-4b8f-8055-4d5fe8dc2b5d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-255ebe58-51e9-4b8f-8055-4d5fe8dc2b5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd2411c4-1553-4536-a264-f681a924792c' class='xr-var-data-in' type='checkbox'><label for='data-cd2411c4-1553-4536-a264-f681a924792c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4aa9d58a-96bf-4a5f-a253-59d28593945d' class='xr-section-summary-in' type='checkbox' /><label for='section-4aa9d58a-96bf-4a5f-a253-59d28593945d' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-afc25fc7-dc1e-48e2-8d3c-d3e4b8dc9b4f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afc25fc7-dc1e-48e2-8d3c-d3e4b8dc9b4f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cef487e9-0c2c-4ffe-a250-9c04fb548852' class='xr-var-data-in' type='checkbox'><label for='data-cef487e9-0c2c-4ffe-a250-9c04fb548852' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-0b6f10b1-a048-4f22-82c9-942ed8b42685' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b6f10b1-a048-4f22-82c9-942ed8b42685' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b36fba18-404a-44f5-9395-aa4aa736460f' class='xr-var-data-in' type='checkbox'><label for='data-b36fba18-404a-44f5-9395-aa4aa736460f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-dd4e97fd-ad58-4d8a-b64e-5b07639809ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd4e97fd-ad58-4d8a-b64e-5b07639809ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48286bf6-95fc-4a2f-929c-04bf92ff4752' class='xr-var-data-in' type='checkbox'><label for='data-48286bf6-95fc-4a2f-929c-04bf92ff4752' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-05d831ef-dca1-406c-966e-8ba81b56177f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05d831ef-dca1-406c-966e-8ba81b56177f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bf171d7-6ff4-48e2-a397-781f9eb19e0c' class='xr-var-data-in' type='checkbox'><label for='data-9bf171d7-6ff4-48e2-a397-781f9eb19e0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-01dcfa68-f9db-41c4-bac0-12451ba72060' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01dcfa68-f9db-41c4-bac0-12451ba72060' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7764fa8-f164-48dc-b900-131e50a1f96e' class='xr-var-data-in' type='checkbox'><label for='data-b7764fa8-f164-48dc-b900-131e50a1f96e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-552a0ce0-27df-4170-bde2-7bbec4556796' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-552a0ce0-27df-4170-bde2-7bbec4556796' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44676c09-2634-458e-8bf5-451b79f18ffe' class='xr-var-data-in' type='checkbox'><label for='data-44676c09-2634-458e-8bf5-451b79f18ffe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-d774731a-039b-4fe7-99ea-e0e28fb484e5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d774731a-039b-4fe7-99ea-e0e28fb484e5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46f6cb9f-2fa8-454c-9612-8cecafafac26' class='xr-var-data-in' type='checkbox'><label for='data-46f6cb9f-2fa8-454c-9612-8cecafafac26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-bc9e1d4a-9f72-4ded-ba47-8992da60736c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc9e1d4a-9f72-4ded-ba47-8992da60736c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1910bb1f-5652-4901-82dd-91cc89de83ee' class='xr-var-data-in' type='checkbox'><label for='data-1910bb1f-5652-4901-82dd-91cc89de83ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-b725c36a-3ae9-4715-8fe0-661983ce53f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b725c36a-3ae9-4715-8fe0-661983ce53f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-928653c2-c0be-4d8a-a4c9-7a99d6c8d7c1' class='xr-var-data-in' type='checkbox'><label for='data-928653c2-c0be-4d8a-a4c9-7a99d6c8d7c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-9c7df37d-dbe2-41f8-9a11-143fe1bc6044' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9c7df37d-dbe2-41f8-9a11-143fe1bc6044' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1075ba7-9e9d-4965-af68-e0ae7e029f30' class='xr-var-data-in' type='checkbox'><label for='data-b1075ba7-9e9d-4965-af68-e0ae7e029f30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-64b98d40-0a23-4cbe-a24f-736141933a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64b98d40-0a23-4cbe-a24f-736141933a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c91e40-ced9-492b-8fb5-acabf184b539' class='xr-var-data-in' type='checkbox'><label for='data-e0c91e40-ced9-492b-8fb5-acabf184b539' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-4eddb006-3879-4367-a6b1-ccde1b8ede68' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4eddb006-3879-4367-a6b1-ccde1b8ede68' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3a31b83d-49e4-4f36-99f0-235763b93f57' class='xr-var-data-in' type='checkbox'><label for='data-3a31b83d-49e4-4f36-99f0-235763b93f57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-d98926eb-77fa-4d7e-93e6-c217b5181ca3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d98926eb-77fa-4d7e-93e6-c217b5181ca3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-27c3cfce-56f9-41c2-811f-da79ccabc5be' class='xr-var-data-in' type='checkbox'><label for='data-27c3cfce-56f9-41c2-811f-da79ccabc5be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-bb9b6864-76be-4b53-b6e9-db5d611c2fa4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb9b6864-76be-4b53-b6e9-db5d611c2fa4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a60abf6c-285c-4440-b9db-e964db9d5d54' class='xr-var-data-in' type='checkbox'><label for='data-a60abf6c-285c-4440-b9db-e964db9d5d54' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-615327d4-3c7c-492f-be87-bc0e9e189b95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-615327d4-3c7c-492f-be87-bc0e9e189b95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa5458aa-e064-4048-b039-3abe70a7c3c8' class='xr-var-data-in' type='checkbox'><label for='data-fa5458aa-e064-4048-b039-3abe70a7c3c8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-715cb9eb-a59b-4085-a75d-516002973317' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-715cb9eb-a59b-4085-a75d-516002973317' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8eca4316-c2b4-4eed-856c-e25687f95745' class='xr-var-data-in' type='checkbox'><label for='data-8eca4316-c2b4-4eed-856c-e25687f95745' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group_index</span></div><div class='xr-var-dims'>(beam_group_index)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1</div><input id='attrs-61145d2a-ddd4-45b5-9b27-bf543126df8d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-61145d2a-ddd4-45b5-9b27-bf543126df8d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23062569-c71c-42fd-b805-b31c9f4565e5' class='xr-var-data-in' type='checkbox'><label for='data-23062569-c71c-42fd-b805-b31c9f4565e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>beam_group</span></div><div class='xr-var-dims'>(beam_group)</div><div class='xr-var-dtype'>&lt;U11</div><div class='xr-var-preview xr-preview'>&#x27;Beam_group1&#x27;</div><input id='attrs-7d10f535-df26-4988-a0d5-2902963be541' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d10f535-df26-4988-a0d5-2902963be541' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-150d4030-0ec2-4823-9c9f-97f7df7a2097' class='xr-var-data-in' type='checkbox'><label for='data-150d4030-0ec2-4823-9c9f-97f7df7a2097' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam group name</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;Beam_group1&#x27;], dtype=&#x27;&lt;U11&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e4f9ae38-9db3-4226-979c-e442c612ca53' class='xr-section-summary-in' type='checkbox' /><label for='section-e4f9ae38-9db3-4226-979c-e442c612ca53' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(26)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-79650c6f-f1ed-4b22-b4fd-8c063b8ec374' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-79650c6f-f1ed-4b22-b4fd-8c063b8ec374' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d40bcbe-9b45-4f81-be9d-7acd7b187b8c' class='xr-var-data-in' type='checkbox'><label for='data-7d40bcbe-9b45-4f81-be9d-7acd7b187b8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 1 1 1</div><input id='attrs-083c5c91-fc03-43ba-a8f9-9aa48501bb4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-083c5c91-fc03-43ba-a8f9-9aa48501bb4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1770e46f-4552-4f3e-8b97-3bc80a852bf4' class='xr-var-data-in' type='checkbox'><label for='data-1770e46f-4552-4f3e-8b97-3bc80a852bf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>type of transducer (0-single, 1-split)</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.73 6.96 6.79 7.26</div><input id='attrs-411605c2-5587-4048-9049-8e48f71cf517' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-411605c2-5587-4048-9049-8e48f71cf517' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ca76f5d-1732-4709-a2fc-dc6fcc8c251b' class='xr-var-data-in' type='checkbox'><label for='data-3ca76f5d-1732-4709-a2fc-dc6fcc8c251b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along alongship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_minor and beamwidth_transmit_minor), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.73000002, 6.96000004, 6.78999996, 7.26000023])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_twoway_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.77 6.87 6.85 7.28</div><input id='attrs-59fbb95e-fbe1-4189-8fb7-ea41636369ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59fbb95e-fbe1-4189-8fb7-ea41636369ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99d8bb48-0094-4b71-ad34-a51b841a45e1' class='xr-var-data-in' type='checkbox'><label for='data-99d8bb48-0094-4b71-ad34-a51b841a45e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Half power two-way beam width along athwartship axis of beam</dd><dt><span>units :</span></dt><dd>arc_degree</dd><dt><span>valid_range :</span></dt><dd>(0.0, 360.0)</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders to avoid potential confusion with convention definitions. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. The convention defines one-way transmit or receive beamwidth (beamwidth_receive_major and beamwidth_transmit_major), but Simrad echosounders record two-way beamwidth in the data.</dd></dl></div><div class='xr-var-data'><pre>array([6.76999998, 6.86999989, 6.8499999 , 7.28000021])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_x</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-d50af170-efd3-45c2-a46c-43117d49b47a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d50af170-efd3-45c2-a46c-43117d49b47a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6a32fc5-554c-4aea-9e2c-847a9275e540' class='xr-var-data-in' type='checkbox'><label for='data-d6a32fc5-554c-4aea-9e2c-847a9275e540' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>x-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_y</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-48acccd6-535a-4dee-a385-91d1886e40a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48acccd6-535a-4dee-a385-91d1886e40a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6c4951c-ed68-429a-8089-25fd1c7be883' class='xr-var-data-in' type='checkbox'><label for='data-a6c4951c-ed68-429a-8089-25fd1c7be883' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>y-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_direction_z</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan</div><input id='attrs-be02decd-9db9-4e45-a6c2-925009090c63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be02decd-9db9-4e45-a6c2-925009090c63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6e78c73-eb53-4085-b76e-6399833a6906' class='xr-var-data-in' type='checkbox'><label for='data-e6e78c73-eb53-4085-b76e-6399833a6906' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>z-component of the vector that gives the pointing direction of the beam, in sonar beam coordinate system</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>valid_range :</span></dt><dd>(-1.0, 1.0)</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.07 -0.08 0.01 -0.07</div><input id='attrs-147c834e-b145-42cf-88f5-fdf5c503a4f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-147c834e-b145-42cf-88f5-fdf5c503a4f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b254fbb6-2b86-46c6-98d0-c0d9388b9998' class='xr-var-data-in' type='checkbox'><label for='data-b254fbb6-2b86-46c6-98d0-c0d9388b9998' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical alongship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([-0.07, -0.08,  0.01, -0.07])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07 -0.06 0.01 -0.01</div><input id='attrs-71d31970-2226-4f69-808c-8c954fdab0e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-71d31970-2226-4f69-808c-8c954fdab0e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b03bc5bc-b09c-4f8e-9fbd-2a2040e4472a' class='xr-var-data-in' type='checkbox'><label for='data-b03bc5bc-b09c-4f8e-9fbd-2a2040e4472a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>electrical athwartship angle offset of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([ 0.07, -0.06,  0.01, -0.01])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-5ba6d925-3ea7-4857-a466-0d5f5376f91b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ba6d925-3ea7-4857-a466-0d5f5376f91b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e195b22d-27a1-4931-8e5c-01416a99d7f9' class='xr-var-data-in' type='checkbox'><label for='data-e195b22d-27a1-4931-8e5c-01416a99d7f9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>alongship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The alongship angle corresponds to the minor angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>23.0 23.0 23.0 23.0</div><input id='attrs-3d9954eb-3ff1-40b2-befd-c8b189ee4937' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d9954eb-3ff1-40b2-befd-c8b189ee4937' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6514a79a-9600-490a-a4c0-1d49e5a1a46b' class='xr-var-data-in' type='checkbox'><label for='data-6514a79a-9600-490a-a4c0-1d49e5a1a46b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>athwartship angle sensitivity of the transducer</dd><dt><span>comment :</span></dt><dd>Introduced in echopype for Simrad echosounders. The athwartship angle corresponds to the major angle in SONAR-netCDF4 vers 2. </dd></dl></div><div class='xr-var-data'><pre>array([23., 23., 23., 23.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.7 -20.7 -20.7 -20.7</div><input id='attrs-23bbad25-d5f4-446c-97ab-afc2793b279e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23bbad25-d5f4-446c-97ab-afc2793b279e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f6aee50-27ce-4cae-a8c4-aecc58d27e0f' class='xr-var-data-in' type='checkbox'><label for='data-7f6aee50-27ce-4cae-a8c4-aecc58d27e0f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Equivalent beam angle</dd><dt><span>units :</span></dt><dd>sr</dd><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd></dl></div><div class='xr-var-data'><pre>array([-20.7, -20.7, -20.7, -20.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_software_version</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U4</div><div class='xr-var-preview xr-preview'>&#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27; &#x27;2.54&#x27;</div><input id='attrs-4a3bf0d1-cc93-4b2c-b176-7b33373ca0e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a3bf0d1-cc93-4b2c-b176-7b33373ca0e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eae550e1-3fdb-42f2-adf4-eb332f46c626' class='xr-var-data-in' type='checkbox'><label for='data-eae550e1-3fdb-42f2-adf4-eb332f46c626' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;, &#x27;2.54&#x27;], dtype=&#x27;&lt;U4&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam_stabilisation</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-36b78538-dcdd-489d-9a34-2996b6f69efd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36b78538-dcdd-489d-9a34-2996b6f69efd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e1c5297-f9a1-4c67-bf32-ee6aea6de3ef' class='xr-var-data-in' type='checkbox'><label for='data-7e1c5297-f9a1-4c67-bf32-ee6aea6de3ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Beam stabilisation applied (or not)</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;not stabilised&#x27;, &#x27;stabilised&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>non_quantitative_processing</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int16</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-f2b20c40-961d-479c-a1e3-4c9516322d01' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2b20c40-961d-479c-a1e3-4c9516322d01' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a99799fb-3bb2-4253-a85d-3f9be3754d84' class='xr-var-data-in' type='checkbox'><label for='data-a99799fb-3bb2-4253-a85d-3f9be3754d84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Presence or not of non-quantitative processing applied to the backscattering data (sonar specific)</dd><dt><span>flag_values :</span></dt><dd>[0]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;None&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array(0, dtype=int16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_r</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.015e-06 -3.043e-06 ... nan nan</div><input id='attrs-f497845e-e3e3-4c83-b445-3a5a7ff24e2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f497845e-e3e3-4c83-b445-3a5a7ff24e2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82fd4f0b-508f-431f-9f46-c2d6510028c3' class='xr-var-data-in' type='checkbox'><label for='data-82fd4f0b-508f-431f-9f46-c2d6510028c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (real part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 2.01457806e-06, -3.04280593e-06,  9.71826069e-08,\n",
        "          -3.96171856e-07],\n",
        "         [-2.57343663e-06,  2.95345012e-06, -3.57061339e-07,\n",
        "          -4.56580392e-06],\n",
@@ -4169,7 +4169,7 @@
        "         [            nan,             nan,             nan,\n",
        "                      nan],\n",
        "         [            nan,             nan,             nan,\n",
-       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-c025c4f4-f6c8-4826-9cc1-d59e6d0cf365' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c025c4f4-f6c8-4826-9cc1-d59e6d0cf365' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc38090-9c3f-42ab-96f1-a6bc53679010' class='xr-var-data-in' type='checkbox'><label for='data-2cc38090-9c3f-42ab-96f1-a6bc53679010' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>backscatter_i</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample, beam)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.127e-06 -7.477e-07 ... nan nan</div><input id='attrs-8d7f6a04-d18b-4331-bfe9-ee3f67f11224' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d7f6a04-d18b-4331-bfe9-ee3f67f11224' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59c9eb3c-415e-4a07-8478-e0b301577bfc' class='xr-var-data-in' type='checkbox'><label for='data-59c9eb3c-415e-4a07-8478-e0b301577bfc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Raw backscatter measurements (imaginary part)</dd><dt><span>units :</span></dt><dd>dB</dd></dl></div><div class='xr-var-data'><pre>array([[[[-1.12652685e-06, -7.47656998e-07,  1.54780153e-07,\n",
        "          -3.68357291e-06],\n",
        "         [-6.13030397e-06,  9.28021564e-06,  3.91020649e-06,\n",
        "          -3.28862302e-06],\n",
@@ -4209,51 +4209,51 @@
        "         [            nan,             nan,             nan,\n",
        "                      nan],\n",
        "         [            nan,             nan,             nan,\n",
-       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-6178c2ef-451b-440c-8688-8a25c646a3d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6178c2ef-451b-440c-8688-8a25c646a3d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72740fc0-3aaf-48c1-a7b0-d079f5653c96' class='xr-var-data-in' type='checkbox'><label for='data-72740fc0-3aaf-48c1-a7b0-d079f5653c96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
+       "                      nan]]]], shape=(4, 1266, 3534, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_interval</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.333e-06 5.333e-06 ... 8e-06 nan</div><input id='attrs-5fcac97f-85f1-4f45-a497-f0955600a73d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fcac97f-85f1-4f45-a497-f0955600a73d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5abe6e96-ba96-4163-8f2f-ae5b556f4fd5' class='xr-var-data-in' type='checkbox'><label for='data-5abe6e96-ba96-4163-8f2f-ae5b556f4fd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Interval between recorded raw data samples</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[5.33333e-06, 5.33333e-06, 5.33333e-06, ..., 5.33333e-06,\n",
        "        5.33333e-06, 5.33333e-06],\n",
        "       [2.13333e-05, 2.13333e-05, 2.13333e-05, ..., 2.13333e-05,\n",
        "        2.13333e-05, 2.13333e-05],\n",
        "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
        "        8.00000e-06, 8.00000e-06],\n",
        "       [8.00000e-06, 8.00000e-06, 8.00000e-06, ..., 8.00000e-06,\n",
-       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-b7fdba7f-23be-4648-b553-42e598f715e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b7fdba7f-23be-4648-b553-42e598f715e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eeeb6885-9efe-430a-9329-532f044efa1e' class='xr-var-data-in' type='checkbox'><label for='data-eeeb6885-9efe-430a-9329-532f044efa1e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
+       "        8.00000e-06,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_power</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>40.0 40.0 40.0 ... 100.0 100.0 nan</div><input id='attrs-51dd69db-5555-4488-8c9c-aacdf4aeeeef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-51dd69db-5555-4488-8c9c-aacdf4aeeeef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-12328e22-8797-433a-bcfb-2e64e6165190' class='xr-var-data-in' type='checkbox'><label for='data-12328e22-8797-433a-bcfb-2e64e6165190' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal transmit power</dd><dt><span>units :</span></dt><dd>W</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[ 40.,  40.,  40., ...,  40.,  40.,  40.],\n",
        "       [ 75.,  75.,  75., ...,  75.,  75.,  75.],\n",
        "       [105., 105., 105., ..., 105., 105., 105.],\n",
-       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-236b0567-0a28-480e-a8f0-723712932f11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-236b0567-0a28-480e-a8f0-723712932f11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5b5bd45-e011-481f-ab92-8b8f27b8a21e' class='xr-var-data-in' type='checkbox'><label for='data-a5b5bd45-e011-481f-ab92-8b8f27b8a21e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
+       "       [100., 100., 100., ..., 100., 100.,  nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_duration_nominal</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.002048 0.002048 ... 0.002048 nan</div><input id='attrs-78b2958c-e687-43b9-8026-8d9ebc49b620' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78b2958c-e687-43b9-8026-8d9ebc49b620' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fbea357-0124-4698-9ab8-6297730fdc87' class='xr-var-data-in' type='checkbox'><label for='data-8fbea357-0124-4698-9ab8-6297730fdc87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Nominal bandwidth of transmitted pulse</dd><dt><span>units :</span></dt><dd>s</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048, 0.002048],\n",
        "       [0.002048, 0.002048, 0.002048, ..., 0.002048, 0.002048,      nan]],\n",
-       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-949453f7-db3a-4117-9a9e-bbc155f2f233' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-949453f7-db3a-4117-9a9e-bbc155f2f233' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-902d3b41-5add-4933-b56f-d202ce4fe42b' class='xr-var-data-in' type='checkbox'><label for='data-902d3b41-5add-4933-b56f-d202ce4fe42b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.003488 0.003488 ... 0.01085 nan</div><input id='attrs-2aedaed7-fd05-4e5e-a345-c4d3bc8d4681' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2aedaed7-fd05-4e5e-a345-c4d3bc8d4681' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a541a8bf-d5fd-46fc-892a-8bfda6c6834f' class='xr-var-data-in' type='checkbox'><label for='data-a541a8bf-d5fd-46fc-892a-8bfda6c6834f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Hann window slope parameter for transmit signal</dd></dl></div><div class='xr-var-data'><pre>array([[0.00348772, 0.00348772, 0.00348772, ..., 0.00348772, 0.00348772,\n",
        "        0.00348772],\n",
        "       [0.0177557 , 0.0177557 , 0.0177557 , ..., 0.0177557 , 0.0177557 ,\n",
        "        0.0177557 ],\n",
        "       [0.00574449, 0.00574449, 0.00574449, ..., 0.00574449, 0.00574449,\n",
        "        0.00574449],\n",
        "       [0.0108507 , 0.0108507 , 0.0108507 , ..., 0.0108507 , 0.0108507 ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-23e02e02-8fb0-44b1-970e-21d8c9728dd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-23e02e02-8fb0-44b1-970e-21d8c9728dd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6bea46b-c214-4570-a876-8032fea17bfb' class='xr-var-data-in' type='checkbox'><label for='data-b6bea46b-c214-4570-a876-8032fea17bfb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel_mode</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-af82fc26-ab4a-4393-bfd8-1e5aa0383097' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-af82fc26-ab4a-4393-bfd8-1e5aa0383097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1504dc3f-c3aa-4809-9d57-de1d978a2d85' class='xr-var-data-in' type='checkbox'><label for='data-1504dc3f-c3aa-4809-9d57-de1d978a2d85' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver mode</dd><dt><span>flag_values :</span></dt><dd>[0, 1]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Active&#x27;, &#x27;Unknown&#x27;]</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 1.,  1.,  1., ...,  1.,  1.,  1.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0., nan]],\n",
-       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-0127ac16-311b-46e8-a35f-205acfde11f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0127ac16-311b-46e8-a35f-205acfde11f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94e4f8a1-6c39-4e41-946d-886ec245d0cc' class='xr-var-data-in' type='checkbox'><label for='data-94e4f8a1-6c39-4e41-946d-886ec245d0cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
+       "      shape=(4, 1266), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_type</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;LFM&#x27; &#x27;LFM&#x27; &#x27;LFM&#x27; ... &#x27;LFM&#x27; nan</div><input id='attrs-ddceeb24-813c-46bd-b577-0f4393a614e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddceeb24-813c-46bd-b577-0f4393a614e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38054fe0-ffac-4808-82c5-78023d9c8273' class='xr-var-data-in' type='checkbox'><label for='data-38054fe0-ffac-4808-82c5-78023d9c8273' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Type of transmitted pulse</dd><dt><span>flag_values :</span></dt><dd>[&#x27;CW&#x27;, &#x27;LFM&#x27;, &#x27;FMD&#x27;]</dd><dt><span>flag_meanings :</span></dt><dd>[&#x27;Continuous Wave – a pulse nominally of one frequency&#x27;, &#x27;Linear Frequency Modulation – a pulse which varies from transmit_frequency_start to transmit_frequency_stop in a linear manner over the nominal pulse duration (transmit_duration_nominal)&#x27;, &quot;Frequency Modulated &#x27;D&#x27; - An EK80-specific FM type that is not clearly described&quot;]</dd></dl></div><div class='xr-var-data'><pre>array([[&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;],\n",
        "       [&#x27;LFM&#x27;, &#x27;LFM&#x27;, &#x27;LFM&#x27;, ..., &#x27;LFM&#x27;, &#x27;LFM&#x27;, nan]],\n",
-       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-e763f1ea-9bcb-4e4b-bf1e-628915d6a3e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e763f1ea-9bcb-4e4b-bf1e-628915d6a3e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bcf3b356-f0d1-483d-a151-c53bf17adf2d' class='xr-var-data-in' type='checkbox'><label for='data-bcf3b356-f0d1-483d-a151-c53bf17adf2d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
+       "      shape=(4, 1266), dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sample_time_offset</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-259504f5-72ec-405a-b0b9-878d998f9204' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-259504f5-72ec-405a-b0b9-878d998f9204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bab3cfeb-cb92-441d-bbad-6569dd862192' class='xr-var-data-in' type='checkbox'><label for='data-bab3cfeb-cb92-441d-bbad-6569dd862192' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Time offset that is subtracted from the timestamp of each sample</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ...,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-98dabb34-7c53-4c84-ba28-1297db46fffe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-98dabb34-7c53-4c84-ba28-1297db46fffe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b20cce3e-885c-4883-bfb0-bdf748ddbaf9' class='xr-var-data-in' type='checkbox'><label for='data-b20cce3e-885c-4883-bfb0-bdf748ddbaf9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
+       "       [ 0.,  0.,  0., ...,  0.,  0., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_start</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.8e+05 2.8e+05 ... 9e+04 nan</div><input id='attrs-c85dfdf3-210e-4d30-a14b-9768625b997f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c85dfdf3-210e-4d30-a14b-9768625b997f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c85d1624-48ea-4846-8a9c-0f683c8c132b' class='xr-var-data-in' type='checkbox'><label for='data-c85d1624-48ea-4846-8a9c-0f683c8c132b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Start frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[280000., 280000., 280000., ..., 280000., 280000., 280000.],\n",
        "       [ 55000.,  55000.,  55000., ...,  55000.,  55000.,  55000.],\n",
        "       [170000., 170000., 170000., ..., 170000., 170000., 170000.],\n",
        "       [ 90000.,  90000.,  90000., ...,  90000.,  90000.,     nan]],\n",
-       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-4e2fe97a-1a9f-422f-a48c-dac9a55c15f9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e2fe97a-1a9f-422f-a48c-dac9a55c15f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e3ca00e-fe6e-4a85-b396-08ba46158eac' class='xr-var-data-in' type='checkbox'><label for='data-3e3ca00e-fe6e-4a85-b396-08ba46158eac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
+       "      shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transmit_frequency_stop</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.8e+05 3.8e+05 ... 1.7e+05 nan</div><input id='attrs-346b81d7-256e-4614-accf-a2b8704a66db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-346b81d7-256e-4614-accf-a2b8704a66db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a856ccf4-42b6-46fb-9ef8-02a384aff2ba' class='xr-var-data-in' type='checkbox'><label for='data-a856ccf4-42b6-46fb-9ef8-02a384aff2ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Stop frequency in transmitted pulse</dd><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[380000., 380000., 380000., ..., 380000., 380000., 380000.],\n",
        "       [ 85000.,  85000.,  85000., ...,  85000.,  85000.,  85000.],\n",
        "       [260000., 260000., 260000., ..., 260000., 260000., 260000.],\n",
        "       [170000., 170000., 170000., ..., 170000., 170000.,     nan]],\n",
-       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-345b838f-4987-45fa-9896-18a65fed9b11' class='xr-section-summary-in' type='checkbox' checked /><label for='section-345b838f-4987-45fa-9896-18a65fed9b11' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
+       "      shape=(4, 1266))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c0283f39-c9e0-451e-93a1-561279bf2993' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c0283f39-c9e0-451e-93a1-561279bf2993' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>beam_mode :</span></dt><dd>vertical</dd><dt><span>conversion_equation_t :</span></dt><dd>type_3</dd></dl></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
-       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_49ab8b1531c39f631344eb2a600c7231\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
-       "                    <label for=\"idata_49ab8b1531c39f631344eb2a600c7231\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
+       "                </li></ul><li class=\"xr-section-list\"><input id=\"idata_80da8eec40424a9fc3a1ee7bb297975f\" class=\"xr-section-summary-in\" type=\"checkbox\">\n",
+       "                    <label for=\"idata_80da8eec40424a9fc3a1ee7bb297975f\" class=\"xr-section-summary\">Vendor_specific: contains vendor-specific information about the sonar and the data.</label>\n",
        "                    <div class=\"xr-section-inline-details\"></div>\n",
        "                    <div class=\"xr-section-details\">\n",
        "                        <ul id=\"xr-dataset-coord-list\" class=\"xr-var-list\">\n",
@@ -4824,41 +4824,41 @@
        "    PC_coeffs_imag               (channel, filter_time, PC_filter_n) float64 13kB ...\n",
        "    WBT_deci_fac                 (channel, filter_time) float64 32B 8.0 ... 12.0\n",
        "    PC_deci_fac                  (channel, filter_time) float64 32B 1.0 ... 1.0\n",
-       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8ab69df9-bb30-432f-8f7c-f7f81e82300e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-8ab69df9-bb30-432f-8f7c-f7f81e82300e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-1d94f0e1-86ce-47ec-8d0f-6f4d495bd83a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-1d94f0e1-86ce-47ec-8d0f-6f4d495bd83a' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-d070c3bf-3004-4b87-bb5a-079a694273a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d070c3bf-3004-4b87-bb5a-079a694273a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-089f62cf-7424-4636-b0ff-bb8d026bab24' class='xr-var-data-in' type='checkbox'><label for='data-089f62cf-7424-4636-b0ff-bb8d026bab24' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    config_xml                   &lt;U100225 401kB &#x27;&lt;?xml version=&quot;1.0&quot; encoding...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DatasetView</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d00a3ec0-4b44-4fe9-82f0-cb4f550795b6' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d00a3ec0-4b44-4fe9-82f0-cb4f550795b6' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>pulse_length_bin</span>: 5</li><li><span class='xr-has-index'>cal_channel_id</span>: 4</li><li><span class='xr-has-index'>cal_frequency</span>: 413</li><li><span class='xr-has-index'>filter_time</span>: 1</li><li><span>WBT_filter_n</span>: 119</li><li><span>PC_filter_n</span>: 391</li></ul></div></li><li class='xr-section-item'><input id='section-018a5379-a72a-4071-a06b-8310d1003f45' class='xr-section-summary-in' type='checkbox' checked /><label for='section-018a5379-a72a-4071-a06b-8310d1003f45' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-60d7ad0e-f85b-4e75-b2a4-7f2e00a96872' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-60d7ad0e-f85b-4e75-b2a4-7f2e00a96872' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e21c0545-454e-4f11-9143-c8d836e3a838' class='xr-var-data-in' type='checkbox'><label for='data-e21c0545-454e-4f11-9143-c8d836e3a838' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-ce1a612a-5d30-4684-a3ca-5636219ae3f9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce1a612a-5d30-4684-a3ca-5636219ae3f9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ce67dd6-586f-40a2-9e37-ef445a426acd' class='xr-var-data-in' type='checkbox'><label for='data-2ce67dd6-586f-40a2-9e37-ef445a426acd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-b418f4b3-a962-4b51-a8ed-e256abc0a21d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b418f4b3-a962-4b51-a8ed-e256abc0a21d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f00378c0-1f3e-480a-a363-6c6bc4b60e4e' class='xr-var-data-in' type='checkbox'><label for='data-f00378c0-1f3e-480a-a363-6c6bc4b60e4e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "      dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>pulse_length_bin</span></div><div class='xr-var-dims'>(pulse_length_bin)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4</div><input id='attrs-1b2cd971-f361-4ea9-aa28-1ac16e30479f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1b2cd971-f361-4ea9-aa28-1ac16e30479f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4ecdfd8-93aa-4fa0-8e64-fb07716263a4' class='xr-var-data-in' type='checkbox'><label for='data-e4ecdfd8-93aa-4fa0-8e64-fb07716263a4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0, 1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_channel_id</span></div><div class='xr-var-dims'>(cal_channel_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-3dd78834-d96e-4469-8b10-8de7d6cb210b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dd78834-d96e-4469-8b10-8de7d6cb210b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-361f8770-42d5-46e1-9712-5543573acd49' class='xr-var-data-in' type='checkbox'><label for='data-361f8770-42d5-46e1-9712-5543573acd49' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>ID of channels containing broadband calibration information</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-847c8da8-68c5-42ac-9ec4-7601c8330d25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-847c8da8-68c5-42ac-9ec4-7601c8330d25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f068ea1-cacb-48cf-8b57-56a0f3bb3fd0' class='xr-var-data-in' type='checkbox'><label for='data-5f068ea1-cacb-48cf-8b57-56a0f3bb3fd0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-43ceadea-e2fb-4b6a-b931-d492a5470f10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43ceadea-e2fb-4b6a-b931-d492a5470f10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-529d6818-cc7f-43de-ab5d-943cd42a8d06' class='xr-var-data-in' type='checkbox'><label for='data-529d6818-cc7f-43de-ab5d-943cd42a8d06' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ad8c9476-e103-4e79-afac-0ed92872440a' class='xr-section-summary-in' type='checkbox' /><label for='section-ad8c9476-e103-4e79-afac-0ed92872440a' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-8e7cef15-4280-4f58-ab09-602c33c985b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e7cef15-4280-4f58-ab09-602c33c985b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-489503c1-7abf-4a28-bb3d-53474cf70006' class='xr-var-data-in' type='checkbox'><label for='data-489503c1-7abf-4a28-bb3d-53474cf70006' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-1c8d64cb-5a0d-49c3-9e3a-5af8cc5727a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1c8d64cb-5a0d-49c3-9e3a-5af8cc5727a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37ef0cca-14c4-4d3d-9a1b-aac3d31ff75a' class='xr-var-data-in' type='checkbox'><label for='data-37ef0cca-14c4-4d3d-9a1b-aac3d31ff75a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>cal_frequency</span></div><div class='xr-var-dims'>(cal_frequency)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>55000 55480 55961 ... 379099 380000</div><input id='attrs-7d35c54a-c9b4-4575-9905-fdaf3ae7b4d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d35c54a-c9b4-4575-9905-fdaf3ae7b4d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e574c73-8669-4a6f-aee9-edb6b0505f3f' class='xr-var-data-in' type='checkbox'><label for='data-4e574c73-8669-4a6f-aee9-edb6b0505f3f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency of calibration parameter</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 55000,  55480,  55961, ..., 378098, 379099, 380000], shape=(413,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filter_time</span></div><div class='xr-var-dims'>(filter_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453</div><input id='attrs-20e712ee-edee-4761-b07f-54d262dbed9f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-20e712ee-edee-4761-b07f-54d262dbed9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6e1c21a-a9e4-47b6-af0b-0595cf513eeb' class='xr-var-data-in' type='checkbox'><label for='data-d6e1c21a-a9e4-47b6-af0b-0595cf513eeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4f5f6bdb-9fc3-453f-b5f3-3d4074ea1b79' class='xr-section-summary-in' type='checkbox' /><label for='section-4f5f6bdb-9fc3-453f-b5f3-3d4074ea1b79' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(21)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-b54ca5cd-db4a-44cd-9000-5226a0c06195' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b54ca5cd-db4a-44cd-9000-5226a0c06195' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77609ebe-b41d-4de1-9fdf-699545b37f88' class='xr-var-data-in' type='checkbox'><label for='data-77609ebe-b41d-4de1-9fdf-699545b37f88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... -0.4 0.0 0.0</div><input id='attrs-a2f1df99-e8a6-4de1-bd95-3bd63d51c5a1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a2f1df99-e8a6-4de1-bd95-3bd63d51c5a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c271cb9-1027-435f-8d68-056d2214dfe2' class='xr-var-data-in' type='checkbox'><label for='data-2c271cb9-1027-435f-8d68-056d2214dfe2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.  ,  0.  ,  0.  ,  0.  ,  0.  ],\n",
        "       [ 0.  ,  0.  , -0.02,  0.  ,  0.  ],\n",
        "       [ 0.  ,  0.  , -0.26, -0.01,  0.  ],\n",
-       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-0f2f6b55-6edc-44c8-9663-94a156641a9e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f2f6b55-6edc-44c8-9663-94a156641a9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba819b80-5e72-4157-a1fe-c5f658b680e9' class='xr-var-data-in' type='checkbox'><label for='data-ba819b80-5e72-4157-a1fe-c5f658b680e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
+       "       [ 0.  ,  0.  , -0.4 ,  0.  ,  0.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.0 25.0 25.0 ... 27.2 27.0 27.0</div><input id='attrs-cf0dc588-acd4-4184-ade0-ad827e024d84' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf0dc588-acd4-4184-ade0-ad827e024d84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d8f8959-e34c-4e28-872e-47d0082f72c1' class='xr-var-data-in' type='checkbox'><label for='data-8d8f8959-e34c-4e28-872e-47d0082f72c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.  , 25.  , 25.  , 17.57, 25.  ],\n",
        "       [27.  , 27.  , 27.59, 27.  , 27.  ],\n",
        "       [26.  , 26.  , 27.48, 27.33, 26.  ],\n",
-       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-fddb2038-678b-44d6-9c10-fbb913fd46ce' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fddb2038-678b-44d6-9c10-fbb913fd46ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15b49629-d0fc-4fe6-953c-7991c3d7e169' class='xr-var-data-in' type='checkbox'><label for='data-15b49629-d0fc-4fe6-953c-7991c3d7e169' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
+       "       [27.  , 27.  , 27.2 , 27.  , 27.  ]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pulse_length</span></div><div class='xr-var-dims'>(channel, pulse_length_bin)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.4e-05 0.000128 ... 0.001024</div><input id='attrs-56791af0-57e2-4de6-a871-5b7304b1b5ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56791af0-57e2-4de6-a871-5b7304b1b5ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e5857b4-8d14-40ac-9c84-468b78dc47d1' class='xr-var-data-in' type='checkbox'><label for='data-6e5857b4-8d14-40ac-9c84-468b78dc47d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
        "       [1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03, 2.048e-03],\n",
        "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03],\n",
-       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-42219133-dd54-43ed-9059-60a28591315b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-42219133-dd54-43ed-9059-60a28591315b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0273085-0649-46d6-9bb4-5515e8642d26' class='xr-var-data-in' type='checkbox'><label for='data-f0273085-0649-46d6-9bb4-5515e8642d26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-16cfb3d0-f290-4f0d-9d63-54498c498f50' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16cfb3d0-f290-4f0d-9d63-54498c498f50' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3313fd22-d79d-44e8-92e2-58da427fcc33' class='xr-var-data-in' type='checkbox'><label for='data-3313fd22-d79d-44e8-92e2-58da427fcc33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-89c5cafd-c41c-4f8d-96f5-ee2c3c8efc95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89c5cafd-c41c-4f8d-96f5-ee2c3c8efc95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbb2e3f7-a1c8-4d94-b387-4d33e9d6d711' class='xr-var-data-in' type='checkbox'><label for='data-cbb2e3f7-a1c8-4d94-b387-4d33e9d6d711' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2b4c52c0-fd4e-4212-b505-7a500b49753b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b4c52c0-fd4e-4212-b505-7a500b49753b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c72a8a1-b846-4fc8-aa73-21e8624b863b' class='xr-var-data-in' type='checkbox'><label for='data-4c72a8a1-b846-4fc8-aa73-21e8624b863b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
+       "       [6.400e-05, 1.280e-04, 2.560e-04, 5.120e-04, 1.024e-03]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-8123d9f5-a1d4-4559-bf12-60ff44721472' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8123d9f5-a1d4-4559-bf12-60ff44721472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46f85675-72f7-401a-b35c-b281ae270ff6' class='xr-var-data-in' type='checkbox'><label for='data-46f85675-72f7-401a-b35c-b281ae270ff6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-f45eb200-9db1-4481-8330-3fcf79cac198' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f45eb200-9db1-4481-8330-3fcf79cac198' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2760336b-5a0f-482a-8167-66dd4099f0bb' class='xr-var-data-in' type='checkbox'><label for='data-2760336b-5a0f-482a-8167-66dd4099f0bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>transceiver_type</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U3</div><div class='xr-var-preview xr-preview'>&#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27; &#x27;WBT&#x27;</div><input id='attrs-e4ccb501-c9df-4ece-98f4-e5030b319ca5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e4ccb501-c9df-4ece-98f4-e5030b319ca5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe25901b-5525-4dcb-b769-da68f8d63cfe' class='xr-var-data-in' type='checkbox'><label for='data-fe25901b-5525-4dcb-b769-da68f8d63cfe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Transceiver type</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;, &#x27;WBT&#x27;], dtype=&#x27;&lt;U3&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-6d4e5fce-f41b-44f3-8178-99380cb3073a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6d4e5fce-f41b-44f3-8178-99380cb3073a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08eaea91-77e1-4c19-9092-0b6caea6ca0c' class='xr-var-data-in' type='checkbox'><label for='data-08eaea91-77e1-4c19-9092-0b6caea6ca0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., 27.85, 27.85, 27.82],\n",
        "       [20.59, 22.95, 24.07, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-0eb10fb3-7046-4acc-b19d-46db91fc079c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0eb10fb3-7046-4acc-b19d-46db91fc079c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f8bc207c-8fb5-41e0-9db5-66c92651a9fb' class='xr-var-data-in' type='checkbox'><label for='data-f8bc207c-8fb5-41e0-9db5-66c92651a9fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-04c14f57-afd6-4508-b95d-680cf2780d5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04c14f57-afd6-4508-b95d-680cf2780d5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5bbf91f-dfd5-4b1b-85d7-d9ebee692322' class='xr-var-data-in' type='checkbox'><label for='data-b5bbf91f-dfd5-4b1b-85d7-d9ebee692322' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., nan, nan, nan],\n",
        "       [nan, nan, nan, ..., nan, nan, nan],\n",
-       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f33f1882-7abe-4bd9-a0c9-90c0265f0dd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f33f1882-7abe-4bd9-a0c9-90c0265f0dd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a58e997c-1580-4bf0-9c90-dc9b094af1ca' class='xr-var-data-in' type='checkbox'><label for='data-a58e997c-1580-4bf0-9c90-dc9b094af1ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>phase</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d0614459-329e-435a-bde1-dd936556de40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0614459-329e-435a-bde1-dd936556de40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f283bc9-9012-4879-86dc-151fb878363b' class='xr-var-data-in' type='checkbox'><label for='data-2f283bc9-9012-4879-86dc-151fb878363b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ...,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0., ..., nan, nan, nan],\n",
        "       [nan, nan, nan, ..., nan, nan, nan],\n",
-       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1a97fe5c-dbee-4b61-93cc-136f833677bc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a97fe5c-dbee-4b61-93cc-136f833677bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd3f2c8b-e303-42cb-bdec-0c4ff67edc3e' class='xr-var-data-in' type='checkbox'><label for='data-fd3f2c8b-e303-42cb-bdec-0c4ff67edc3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
+       "       [nan, nan, nan, ..., nan, nan, nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2dccee99-cc83-46a9-a1b0-b222d22fad57' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2dccee99-cc83-46a9-a1b0-b222d22fad57' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54f077d4-28e6-4860-bbb6-65ced1a47039' class='xr-var-data-in' type='checkbox'><label for='data-54f077d4-28e6-4860-bbb6-65ced1a47039' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.01, 6.  , 5.97],\n",
        "       [9.33, 8.67, 8.3 , ...,  nan,  nan,  nan],\n",
        "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-406927d1-8af9-4a30-94e2-53d1ac1cde40' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-406927d1-8af9-4a30-94e2-53d1ac1cde40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c274b6c-22a0-40fd-b768-bcc180d2ca69' class='xr-var-data-in' type='checkbox'><label for='data-8c274b6c-22a0-40fd-b768-bcc180d2ca69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-247c11cf-03b4-423a-b854-52d8a8913782' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-247c11cf-03b4-423a-b854-52d8a8913782' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f87a36b-3c2a-46cc-a774-3f34cd58fa6b' class='xr-var-data-in' type='checkbox'><label for='data-1f87a36b-3c2a-46cc-a774-3f34cd58fa6b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., 6.05, 6.01, 5.99],\n",
        "       [9.5 , 8.24, 8.38, ...,  nan,  nan,  nan],\n",
        "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
-       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-79a2d876-5e55-4ae3-881c-f0e71fe576de' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79a2d876-5e55-4ae3-881c-f0e71fe576de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8815e99d-3275-483c-bf35-11e2289612ca' class='xr-var-data-in' type='checkbox'><label for='data-8815e99d-3275-483c-bf35-11e2289612ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
+       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-2a0a2e55-8865-434c-8351-20732829169d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a0a2e55-8865-434c-8351-20732829169d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1b4e95f-f001-47bd-be37-98b6b8f9c86f' class='xr-var-data-in' type='checkbox'><label for='data-f1b4e95f-f001-47bd-be37-98b6b8f9c86f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.01, -0.01,  0.  ],\n",
        "       [ 0.04, -0.18, -0.26, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-95e9881d-28c2-4b44-a0dc-74c4dc2f3167' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-95e9881d-28c2-4b44-a0dc-74c4dc2f3167' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-840a3da7-e040-4bf8-a52f-3e6eb05a1cb5' class='xr-var-data-in' type='checkbox'><label for='data-840a3da7-e040-4bf8-a52f-3e6eb05a1cb5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(cal_channel_id, cal_frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a77af12c-2abf-4185-97a1-aade3a9ea456' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a77af12c-2abf-4185-97a1-aade3a9ea456' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e4e8435f-affd-47ea-a2a4-1215509103e4' class='xr-var-data-in' type='checkbox'><label for='data-e4e8435f-affd-47ea-a2a4-1215509103e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[  nan,   nan,   nan, ..., -0.05, -0.05, -0.08],\n",
        "       [ 0.35, -0.02,  0.02, ...,   nan,   nan,   nan],\n",
        "       [  nan,   nan,   nan, ...,   nan,   nan,   nan],\n",
-       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-f25ce175-9c60-47b4-bf19-0c857035e2c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f25ce175-9c60-47b4-bf19-0c857035e2c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1c138d1-278a-4351-9672-89319b2b3b2e' class='xr-var-data-in' type='checkbox'><label for='data-f1c138d1-278a-4351-9672-89319b2b3b2e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
+       "       [  nan,   nan,   nan, ...,   nan,   nan,   nan]], shape=(4, 413))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.144e-05 -0.0001601 ... 9.705e-06</div><input id='attrs-4a42926d-3812-44e7-bebf-9bb28c5be086' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a42926d-3812-44e7-bebf-9bb28c5be086' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3addedb-dff7-4505-a528-749a2736be01' class='xr-var-data-in' type='checkbox'><label for='data-b3addedb-dff7-4505-a528-749a2736be01' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.14427166e-05, -1.60068841e-04, -3.74446070e-04,\n",
        "          5.80396911e-04,  1.79292378e-03, -5.69819706e-04,\n",
        "         -4.36119642e-03, -1.06982014e-03,  6.37054257e-03,\n",
        "          3.98992328e-03, -5.19806752e-03, -4.50613070e-03,\n",
@@ -4898,7 +4898,7 @@
        "         -5.42755188e-05,  1.08743296e-03,  1.58825796e-03,\n",
        "          1.45288126e-03,  9.33228002e-04,  3.50838847e-04,\n",
        "         -6.20377104e-05, -2.31620375e-04, -2.17583845e-04,\n",
-       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-fcd85c89-abfe-416d-a3db-37864feb3f78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcd85c89-abfe-416d-a3db-37864feb3f78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c375bd5-9a2b-4365-adbd-d988ec5442f1' class='xr-var-data-in' type='checkbox'><label for='data-4c375bd5-9a2b-4365-adbd-d988ec5442f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
+       "         -1.59145377e-04,  9.70470410e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, WBT_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.63e-05 0.000117 ... 9.655e-06</div><input id='attrs-852a4f52-e64a-4521-8b9d-91dc745a69b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-852a4f52-e64a-4521-8b9d-91dc745a69b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-71dca4de-a0ca-4de6-9223-df10575503a1' class='xr-var-data-in' type='checkbox'><label for='data-71dca4de-a0ca-4de6-9223-df10575503a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.63023958e-05,  1.16975585e-04, -3.52505565e-04,\n",
        "         -9.13087046e-04,  7.09498825e-04,  2.99199694e-03,\n",
        "          9.69185190e-18, -5.61309094e-03, -2.52190628e-03,\n",
        "          6.28564134e-03,  4.88218758e-03, -3.27457441e-03,\n",
@@ -4938,7 +4938,7 @@
        "         -2.52039032e-03, -1.88605406e-03, -8.73966317e-04,\n",
        "          6.09558374e-05,  6.21019106e-04,  7.48717517e-04,\n",
        "          5.76159859e-04,  3.03197594e-04,  8.55612234e-05,\n",
-       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-c9ebcd75-8a62-410e-8186-065847d11f8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c9ebcd75-8a62-410e-8186-065847d11f8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c617a237-2384-4c6c-bb40-71f8448abc8d' class='xr-var-data-in' type='checkbox'><label for='data-c617a237-2384-4c6c-bb40-71f8448abc8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
+       "         -2.66669540e-05,  9.65512845e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_real</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0003825 -0.001017 ... nan nan</div><input id='attrs-6bfa46a6-3441-478b-986b-51d4366ae24c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bfa46a6-3441-478b-986b-51d4366ae24c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2fc0a0e-3877-4645-a63b-e079a6ebf871' class='xr-var-data-in' type='checkbox'><label for='data-d2fc0a0e-3877-4645-a63b-e079a6ebf871' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (real part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.82524973e-04, -1.01727119e-03,  1.55105174e-03, ...,\n",
        "                     nan,             nan,             nan]],\n",
        "\n",
        "       [[-2.92797376e-05,  1.22475076e-05,  2.08751826e-05, ...,\n",
@@ -4949,7 +4949,7 @@
        "\n",
        "       [[-3.34112738e-05, -1.13061478e-03, -2.34585186e-03, ...,\n",
        "                     nan,             nan,             nan]]],\n",
-       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-69e6647a-78dc-459c-899c-170705d41c58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69e6647a-78dc-459c-899c-170705d41c58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a310df1-be38-4571-a08c-f38f96bc8c18' class='xr-var-data-in' type='checkbox'><label for='data-6a310df1-be38-4571-a08c-f38f96bc8c18' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_coeffs_imag</span></div><div class='xr-var-dims'>(channel, filter_time, PC_filter_n)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0002779 0.00123 ... 0.0 0.0</div><input id='attrs-f52ab33f-70c2-4bee-b75a-66ef50bee04d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f52ab33f-70c2-4bee-b75a-66ef50bee04d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ddecd98-19fe-428c-8214-3993b4efc2cf' class='xr-var-data-in' type='checkbox'><label for='data-9ddecd98-19fe-428c-8214-3993b4efc2cf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression filter coefficients (imaginary part)</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.77920655e-04,  1.22966967e-03,  1.45653449e-03, ...,\n",
        "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
        "\n",
        "       [[-5.08991980e-05,  3.11717099e-06, -1.25777024e-05, ...,\n",
@@ -4960,13 +4960,13 @@
        "\n",
        "       [[ 1.31017148e-18, -2.90292519e-04, -1.28964300e-03, ...,\n",
        "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]],\n",
-       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-5547ca8a-272b-4c0d-b590-176ee622afd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5547ca8a-272b-4c0d-b590-176ee622afd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4af02dc3-8cca-48cb-90bc-8e0dcd35bf66' class='xr-var-data-in' type='checkbox'><label for='data-4af02dc3-8cca-48cb-90bc-8e0dcd35bf66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
+       "      shape=(4, 1, 391))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WBT_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0 8.0 6.0 12.0</div><input id='attrs-f1ed28de-e27a-41c6-9b37-f28c879d8286' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1ed28de-e27a-41c6-9b37-f28c879d8286' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33509e8d-3426-4764-9eb5-563df2355c30' class='xr-var-data-in' type='checkbox'><label for='data-33509e8d-3426-4764-9eb5-563df2355c30' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Wideband transceiver decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[ 8.],\n",
        "       [ 8.],\n",
        "       [ 6.],\n",
-       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-164725e3-2395-437d-a6fc-98b11aa1db72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-164725e3-2395-437d-a6fc-98b11aa1db72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab938bc7-b1a3-4010-8a19-69caaacfaf42' class='xr-var-data-in' type='checkbox'><label for='data-ab938bc7-b1a3-4010-8a19-69caaacfaf42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
+       "       [12.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PC_deci_fac</span></div><div class='xr-var-dims'>(channel, filter_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.0 4.0 2.0 1.0</div><input id='attrs-4a55d7e8-64fe-42f2-8ccb-23c0dfbca785' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a55d7e8-64fe-42f2-8ccb-23c0dfbca785' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c7192c7-3910-4c53-b9a5-7d5c402a416c' class='xr-var-data-in' type='checkbox'><label for='data-5c7192c7-3910-4c53-b9a5-7d5c402a416c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Pulse compression decimation factor</dd></dl></div><div class='xr-var-data'><pre>array([[1.],\n",
        "       [4.],\n",
        "       [2.],\n",
-       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-f3b1ec17-e0a0-4c6a-bd4d-5bc85f376cb8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f3b1ec17-e0a0-4c6a-bd4d-5bc85f376cb8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ea3ad4c-a81a-447c-b74d-23635e58ce99' class='xr-var-data-in' type='checkbox'><label for='data-3ea3ad4c-a81a-447c-b74d-23635e58ce99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGK from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGK&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.GGK.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;4&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;4&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;VTG from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;VTG&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Ground&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;CourseNotUsedMagnetic&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Annotation&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;External Depth From LAN Port 9 Pressure&quot; Type=&quot;EchoDepth&quot; Port=&quot;Lan Port 10&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;DPT from External Depth From LAN Port 9 Pressure&quot; SensorType=&quot;EchoDepth&quot; Type=&quot;DPT&quot; SubscriptionPath=&quot;External Depth From LAN Port 9 Pressure@EchoDepth.DepthTransducer&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Depth&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;TowedBodyDepth&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;MotionBinary From LAN Port 1 8000&quot; Type=&quot;MotionBinary&quot; Port=&quot;Lan Port 2&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;MRU from MotionBinary From LAN Port 1 8000&quot; SensorType=&quot;MotionBinary&quot; Type=&quot;MRU&quot; SubscriptionPath=&quot;MotionBinary From LAN Port 1 8000@MotionBinary.MotionData&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Roll&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Pitch&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heading&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heave&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n    &lt;/ConfiguredSensors&gt;\\n&lt;/Configuration&gt;&#x27;,\n",
+       "       [1.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>config_xml</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U100225</div><div class='xr-var-preview xr-preview'>&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;u...</div><input id='attrs-1496a9cb-59ca-4527-adfb-f863b2b3c208' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1496a9cb-59ca-4527-adfb-f863b2b3c208' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08ba0824-c640-439b-907e-a8cc56aeb14d' class='xr-var-data-in' type='checkbox'><label for='data-08ba0824-c640-439b-907e-a8cc56aeb14d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;&lt;?xml version=&quot;1.0&quot; encoding=&quot;utf-8&quot; ?&gt;\\n&lt;Configuration&gt;\\n    &lt;Header Copyright=&quot;Copyright(c) Kongsberg Maritime AS, Norway&quot; ApplicationName=&quot;&quot; Version=&quot;21.15.0.0&quot; FileFormatVersion=&quot;1.27&quot; TimeBias=&quot;0&quot; /&gt;\\n    &lt;ActivePingMode Mode=&quot;Direct&quot; /&gt;\\n    &lt;Transceivers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747015&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747015&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6607&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:07&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.102&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747015&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 500W CH2: 503W CH3: 489W CH4: 500W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;1&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747015-15 ES70-7CD_ES&quot; LogicalChannelID=&quot;WBT 747015-15 ES70-7CD&quot; ChannelIdShort=&quot;ES70-7CD Serial No: 134&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;0.000128;0.000256;0.000512;0.001024;0.002048&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES70-7CD&quot; SerialNumber=&quot;134&quot; Frequency=&quot;70000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.59;27;27&quot; SaCorrection=&quot;0;0;-0.02;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0799999982118607&quot; AngleOffsetAthwartship=&quot;-0.0599999986588955&quot; BeamWidthAlongship=&quot;6.96000003814697&quot; BeamWidthAthwartship=&quot;6.86999988555908&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55000&quot; Gain=&quot;20.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;9.33&quot; BeamWidthAthwartship=&quot;9.5&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;0.35&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55480&quot; Gain=&quot;22.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.67&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;55961&quot; Gain=&quot;24.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.3&quot; BeamWidthAthwartship=&quot;8.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56441&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;8.2&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;56922&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.09&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57402&quot; Gain=&quot;26.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.21&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;57883&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.12&quot; BeamWidthAthwartship=&quot;8.06&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58363&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.1&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;58844&quot; Gain=&quot;26.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.05&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59324&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.15&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;59805&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.17&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60285&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;7.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;60766&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.14&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61246&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.18&quot; BeamWidthAthwartship=&quot;8.02&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;61727&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;7.9&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62207&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.85&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;62688&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.72&quot; BeamWidthAthwartship=&quot;7.92&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63168&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.81&quot; BeamWidthAthwartship=&quot;7.81&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;63649&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64129&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;64610&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.73&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65090&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;65571&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66051&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;66532&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67012&quot; Gain=&quot;26.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.29&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67492&quot; Gain=&quot;26.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.26&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.27&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;67973&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68453&quot; Gain=&quot;27.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;68934&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;6.9&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69414&quot; Gain=&quot;27.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;69895&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70375&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.89&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;70856&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.64&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71336&quot; Gain=&quot;27.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.76&quot; AngleOffsetAlongship=&quot;-0.31&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;71817&quot; Gain=&quot;27.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72297&quot; Gain=&quot;27.78&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.71&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;72778&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.75&quot; BeamWidthAthwartship=&quot;6.61&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73258&quot; Gain=&quot;27.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.48&quot; AngleOffsetAlongship=&quot;-0.2&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;73739&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74219&quot; Gain=&quot;27.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;74700&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.38&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75180&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;75661&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76141&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;76622&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.19&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77102&quot; Gain=&quot;27.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.18&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;77583&quot; Gain=&quot;28.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.36&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78063&quot; Gain=&quot;28.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.25&quot; AngleOffsetAthwartship=&quot;-0.13&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;78544&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79024&quot; Gain=&quot;27.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.4&quot; AngleOffsetAlongship=&quot;-0.28&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79505&quot; Gain=&quot;27.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.2&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;79985&quot; Gain=&quot;27.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.26&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.24&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80465&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;80946&quot; Gain=&quot;27.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.17&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81426&quot; Gain=&quot;27.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;81907&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.16&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82387&quot; Gain=&quot;27.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;82868&quot; Gain=&quot;27.41&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.23&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83348&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;83829&quot; Gain=&quot;27.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.72&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84309&quot; Gain=&quot;27.33&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;5.85&quot; AngleOffsetAlongship=&quot;-0.21&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;84790&quot; Gain=&quot;27.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.9&quot; BeamWidthAthwartship=&quot;5.91&quot; AngleOffsetAlongship=&quot;-0.22&quot; AngleOffsetAthwartship=&quot;-0.15&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;85000&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.26&quot; AngleOffsetAthwartship=&quot;-0.19&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747022&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747022&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660e&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0E&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.104&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747022&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 508W CH2: 499W CH3: 488W CH4: 501W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;2&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747022-15 ES120-7CD_ES&quot; LogicalChannelID=&quot;WBT 747022-15 ES120-7CD&quot; ChannelIdShort=&quot;ES120-7CD Serial No: 146&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES120-7CD&quot; SerialNumber=&quot;146&quot; Frequency=&quot;120000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;27;27;27.2;27;27&quot; SaCorrection=&quot;0;0;-0.4;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;-0.00999999977648258&quot; BeamWidthAlongship=&quot;7.26000022888184&quot; BeamWidthAthwartship=&quot;7.28000020980835&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96246&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.06&quot; BeamWidthAthwartship=&quot;8.18&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;96727&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.08&quot; BeamWidthAthwartship=&quot;8.11&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97207&quot; Gain=&quot;26.04&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.97&quot; BeamWidthAthwartship=&quot;7.74&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;97688&quot; Gain=&quot;26.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.64&quot; BeamWidthAthwartship=&quot;8&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98168&quot; Gain=&quot;26.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;98649&quot; Gain=&quot;26.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99129&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;99610&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100090&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.51&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;100571&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101051&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.47&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;101532&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102012&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.41&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102492&quot; Gain=&quot;26.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;102973&quot; Gain=&quot;26.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103453&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;103934&quot; Gain=&quot;26.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104414&quot; Gain=&quot;26.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.38&quot; BeamWidthAthwartship=&quot;7.47&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;104895&quot; Gain=&quot;26.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.41&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105375&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;105856&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106336&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;106817&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107297&quot; Gain=&quot;26.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;107778&quot; Gain=&quot;26.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.28&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108258&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.23&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;108739&quot; Gain=&quot;26.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.27&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109219&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.19&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;109700&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.15&quot; BeamWidthAthwartship=&quot;7.21&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110180&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.25&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;110661&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.28&quot; BeamWidthAthwartship=&quot;7.06&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111141&quot; Gain=&quot;26.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.11&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;111622&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112102&quot; Gain=&quot;26.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.05&quot; BeamWidthAthwartship=&quot;7.12&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;112583&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.2&quot; BeamWidthAthwartship=&quot;7.07&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119309&quot; Gain=&quot;26.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;119790&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120270&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;120751&quot; Gain=&quot;26.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121231&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.69&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;121712&quot; Gain=&quot;26.88&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122192&quot; Gain=&quot;27.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;122673&quot; Gain=&quot;27.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123153&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.52&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;123634&quot; Gain=&quot;27.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124114&quot; Gain=&quot;27.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.47&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;124595&quot; Gain=&quot;27.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125075&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;125556&quot; Gain=&quot;27.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126036&quot; Gain=&quot;27.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126517&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;126997&quot; Gain=&quot;27.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.21&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127477&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;127958&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128438&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;128919&quot; Gain=&quot;27.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.22&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129399&quot; Gain=&quot;28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;129880&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.19&quot; BeamWidthAthwartship=&quot;6.31&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130360&quot; Gain=&quot;28.12&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;130841&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.28&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145255&quot; Gain=&quot;29.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;145736&quot; Gain=&quot;29.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.52&quot; BeamWidthAthwartship=&quot;5.59&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146216&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;146697&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147177&quot; Gain=&quot;29.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.49&quot; BeamWidthAthwartship=&quot;5.47&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;147658&quot; Gain=&quot;29.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.4&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148138&quot; Gain=&quot;29.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.18&quot; BeamWidthAthwartship=&quot;5.45&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;148619&quot; Gain=&quot;29.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149099&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;149580&quot; Gain=&quot;29.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150060&quot; Gain=&quot;29.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.47&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;150541&quot; Gain=&quot;29.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.53&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151021&quot; Gain=&quot;29.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.25&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151502&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;151982&quot; Gain=&quot;29.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.26&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152462&quot; Gain=&quot;29.86&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;152943&quot; Gain=&quot;29.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.19&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153423&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.36&quot; BeamWidthAthwartship=&quot;5.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;153904&quot; Gain=&quot;29.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.32&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154384&quot; Gain=&quot;29.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.27&quot; BeamWidthAthwartship=&quot;5.29&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;154865&quot; Gain=&quot;30.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.23&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155345&quot; Gain=&quot;30.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.25&quot; BeamWidthAthwartship=&quot;5.22&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;155826&quot; Gain=&quot;29.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.24&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156306&quot; Gain=&quot;30.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.2&quot; BeamWidthAthwartship=&quot;5.24&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;156787&quot; Gain=&quot;30.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.19&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157267&quot; Gain=&quot;30.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.15&quot; BeamWidthAthwartship=&quot;5.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;157748&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.22&quot; BeamWidthAthwartship=&quot;5.13&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158228&quot; Gain=&quot;30.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.21&quot; BeamWidthAthwartship=&quot;5.16&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;158709&quot; Gain=&quot;30.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.14&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159189&quot; Gain=&quot;30.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.11&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;159670&quot; Gain=&quot;30.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.13&quot; BeamWidthAthwartship=&quot;5.04&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160150&quot; Gain=&quot;30.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.12&quot; BeamWidthAthwartship=&quot;5.06&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;160631&quot; Gain=&quot;30.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.06&quot; BeamWidthAthwartship=&quot;5.01&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161111&quot; Gain=&quot;30.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;161592&quot; Gain=&quot;30.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.04&quot; BeamWidthAthwartship=&quot;5&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90000&quot; Gain=&quot;21.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.82&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90480&quot; Gain=&quot;21.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.57&quot; BeamWidthAthwartship=&quot;8.48&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.17&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;90961&quot; Gain=&quot;21.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.33&quot; BeamWidthAthwartship=&quot;8.59&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91441&quot; Gain=&quot;21.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.37&quot; BeamWidthAthwartship=&quot;8.56&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;91922&quot; Gain=&quot;22.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.23&quot; BeamWidthAthwartship=&quot;8.87&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92402&quot; Gain=&quot;22.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.54&quot; BeamWidthAthwartship=&quot;8.31&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;92883&quot; Gain=&quot;23.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.6&quot; BeamWidthAthwartship=&quot;8.45&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93363&quot; Gain=&quot;23.69&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.16&quot; BeamWidthAthwartship=&quot;8.58&quot; AngleOffsetAlongship=&quot;-0.16&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;93844&quot; Gain=&quot;24.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.11&quot; BeamWidthAthwartship=&quot;8.34&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94324&quot; Gain=&quot;24.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.14&quot; BeamWidthAthwartship=&quot;8.55&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;94805&quot; Gain=&quot;25.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95285&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.03&quot; BeamWidthAthwartship=&quot;8.27&quot; AngleOffsetAlongship=&quot;-0.15&quot; AngleOffsetAthwartship=&quot;0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;95766&quot; Gain=&quot;25.65&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;8.04&quot; BeamWidthAthwartship=&quot;8.24&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113063&quot; Gain=&quot;26.61&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;6.92&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;113544&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.84&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114024&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.91&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114505&quot; Gain=&quot;26.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.87&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;114985&quot; Gain=&quot;26.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.78&quot; BeamWidthAthwartship=&quot;7.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115465&quot; Gain=&quot;26.75&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.17&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;115946&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.76&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116426&quot; Gain=&quot;26.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.65&quot; AngleOffsetAlongship=&quot;-0.14&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;116907&quot; Gain=&quot;26.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.13&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117387&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.61&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.11&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;117868&quot; Gain=&quot;26.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.66&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118348&quot; Gain=&quot;26.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.88&quot; AngleOffsetAlongship=&quot;-0.12&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;118829&quot; Gain=&quot;26.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131321&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;131802&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132282&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.06&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;132763&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.03&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133243&quot; Gain=&quot;28.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;133724&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134204&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.93&quot; BeamWidthAthwartship=&quot;6.03&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;134685&quot; Gain=&quot;28.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135165&quot; Gain=&quot;28.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.81&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;135646&quot; Gain=&quot;28.8&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136126&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.95&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;136607&quot; Gain=&quot;28.9&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.83&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137087&quot; Gain=&quot;29.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.88&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;137568&quot; Gain=&quot;29.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.68&quot; BeamWidthAthwartship=&quot;5.8&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138048&quot; Gain=&quot;29.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.88&quot; BeamWidthAthwartship=&quot;5.77&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;138529&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.78&quot; BeamWidthAthwartship=&quot;5.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139009&quot; Gain=&quot;29.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.73&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139489&quot; Gain=&quot;29.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.73&quot; BeamWidthAthwartship=&quot;5.7&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;139970&quot; Gain=&quot;29.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.71&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140450&quot; Gain=&quot;29.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.55&quot; BeamWidthAthwartship=&quot;5.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;140931&quot; Gain=&quot;29.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.59&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141411&quot; Gain=&quot;29.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.61&quot; BeamWidthAthwartship=&quot;5.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;141892&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.42&quot; BeamWidthAthwartship=&quot;5.6&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142372&quot; Gain=&quot;29.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.63&quot; BeamWidthAthwartship=&quot;5.69&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;142853&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143333&quot; Gain=&quot;29.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;143814&quot; Gain=&quot;29.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.57&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144294&quot; Gain=&quot;29.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.55&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;144775&quot; Gain=&quot;29.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.69&quot; BeamWidthAthwartship=&quot;5.71&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162072&quot; Gain=&quot;29.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.01&quot; BeamWidthAthwartship=&quot;5.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;162553&quot; Gain=&quot;29.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.97&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163033&quot; Gain=&quot;29.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.87&quot; BeamWidthAthwartship=&quot;4.89&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163514&quot; Gain=&quot;29.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.91&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;163994&quot; Gain=&quot;29.45&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.99&quot; BeamWidthAthwartship=&quot;4.96&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164474&quot; Gain=&quot;29.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.9&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;164955&quot; Gain=&quot;29.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165435&quot; Gain=&quot;28.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.81&quot; BeamWidthAthwartship=&quot;4.84&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;165916&quot; Gain=&quot;28.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.78&quot; BeamWidthAthwartship=&quot;4.81&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166396&quot; Gain=&quot;28.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.72&quot; BeamWidthAthwartship=&quot;4.76&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;166877&quot; Gain=&quot;28.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.64&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167357&quot; Gain=&quot;27.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.71&quot; BeamWidthAthwartship=&quot;4.72&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;167838&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.82&quot; BeamWidthAthwartship=&quot;4.66&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168318&quot; Gain=&quot;27.6&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.67&quot; BeamWidthAthwartship=&quot;4.64&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;168799&quot; Gain=&quot;27.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.65&quot; BeamWidthAthwartship=&quot;4.67&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169279&quot; Gain=&quot;27.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;169760&quot; Gain=&quot;26.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.74&quot; BeamWidthAthwartship=&quot;4.8&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;26.73&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;4.8&quot; BeamWidthAthwartship=&quot;4.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747019&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747019&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b660b&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:0B&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.101&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747019&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 511W CH2: 500W CH3: 506W CH4: 486W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;3&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747019-15 ES200-7CD_ES&quot; LogicalChannelID=&quot;WBT 747019-15 ES200-7CD&quot; ChannelIdShort=&quot;ES200-7CD Serial No: 166&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES200-7CD&quot; SerialNumber=&quot;166&quot; Frequency=&quot;200000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;26;26;27.48;27.33;26&quot; SaCorrection=&quot;0;0;-0.26;-0.01;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;0.00999999977648258&quot; AngleOffsetAthwartship=&quot;0.00999999977648258&quot; BeamWidthAlongship=&quot;6.78999996185303&quot; BeamWidthAthwartship=&quot;6.84999990463257&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;180900&quot; Gain=&quot;25.97&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.58&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;181891&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;182882&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.43&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;183873&quot; Gain=&quot;25.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.44&quot; BeamWidthAthwartship=&quot;7.44&quot; AngleOffsetAlongship=&quot;0.07&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;184864&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.4&quot; BeamWidthAthwartship=&quot;7.36&quot; AngleOffsetAlongship=&quot;0.06&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;185855&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.33&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;186846&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.35&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;187837&quot; Gain=&quot;25.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.29&quot; BeamWidthAthwartship=&quot;7.29&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;188828&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.3&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;189819&quot; Gain=&quot;26.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;190810&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.14&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;191801&quot; Gain=&quot;26.21&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.13&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;192792&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.06&quot; BeamWidthAthwartship=&quot;7&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;193783&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;6.8&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.14&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;194774&quot; Gain=&quot;26.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;195765&quot; Gain=&quot;26.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.77&quot; BeamWidthAthwartship=&quot;6.85&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;196756&quot; Gain=&quot;26.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;197747&quot; Gain=&quot;27.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;198738&quot; Gain=&quot;27.2&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;199729&quot; Gain=&quot;27.31&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.68&quot; BeamWidthAthwartship=&quot;6.66&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;200720&quot; Gain=&quot;27.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.63&quot; BeamWidthAthwartship=&quot;6.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;201711&quot; Gain=&quot;27.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.6&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;202702&quot; Gain=&quot;27.66&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.67&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;203693&quot; Gain=&quot;27.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;204684&quot; Gain=&quot;27.49&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.45&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;215585&quot; Gain=&quot;28.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.23&quot; BeamWidthAthwartship=&quot;6.27&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;216576&quot; Gain=&quot;28.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;217567&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;218558&quot; Gain=&quot;28.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;219549&quot; Gain=&quot;28.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;220540&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.16&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;229459&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.99&quot; BeamWidthAthwartship=&quot;6.06&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;230450&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.02&quot; BeamWidthAthwartship=&quot;6.08&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;231441&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.96&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;232432&quot; Gain=&quot;28.4&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;5.92&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;233423&quot; Gain=&quot;28.44&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.92&quot; BeamWidthAthwartship=&quot;5.87&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;234414&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.87&quot; BeamWidthAthwartship=&quot;5.86&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;235405&quot; Gain=&quot;28.35&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;236396&quot; Gain=&quot;28.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;5.98&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;237387&quot; Gain=&quot;28.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.95&quot; BeamWidthAthwartship=&quot;5.94&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;238378&quot; Gain=&quot;28.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;5.93&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;239369&quot; Gain=&quot;28.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.96&quot; BeamWidthAthwartship=&quot;5.84&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;252252&quot; Gain=&quot;28.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;253243&quot; Gain=&quot;28.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.32&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;254234&quot; Gain=&quot;28.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.29&quot; BeamWidthAthwartship=&quot;5.44&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;255225&quot; Gain=&quot;28.62&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.3&quot; BeamWidthAthwartship=&quot;5.37&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;256216&quot; Gain=&quot;28.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.31&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;257207&quot; Gain=&quot;28.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.33&quot; BeamWidthAthwartship=&quot;5.42&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;258198&quot; Gain=&quot;28.89&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.35&quot; BeamWidthAthwartship=&quot;5.38&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;259189&quot; Gain=&quot;28.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.38&quot; BeamWidthAthwartship=&quot;5.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;260000&quot; Gain=&quot;28.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.41&quot; BeamWidthAthwartship=&quot;5.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170000&quot; Gain=&quot;25.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.9&quot; BeamWidthAthwartship=&quot;8.03&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;170990&quot; Gain=&quot;25.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.92&quot; BeamWidthAthwartship=&quot;8.08&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;171981&quot; Gain=&quot;25.98&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.86&quot; BeamWidthAthwartship=&quot;8.01&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;172972&quot; Gain=&quot;25.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.79&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;173963&quot; Gain=&quot;26.07&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.66&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;174954&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;175945&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.67&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;176936&quot; Gain=&quot;26.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;177927&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.61&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;178918&quot; Gain=&quot;25.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.57&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;179909&quot; Gain=&quot;25.96&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.52&quot; BeamWidthAthwartship=&quot;7.55&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;205675&quot; Gain=&quot;27.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.43&quot; BeamWidthAthwartship=&quot;6.51&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;206666&quot; Gain=&quot;27.68&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.41&quot; BeamWidthAthwartship=&quot;6.32&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;207657&quot; Gain=&quot;27.72&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.34&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;208648&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.41&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;209639&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.35&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;210630&quot; Gain=&quot;27.87&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.33&quot; BeamWidthAthwartship=&quot;6.35&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;211621&quot; Gain=&quot;27.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.3&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;212612&quot; Gain=&quot;27.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;213603&quot; Gain=&quot;28.01&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.28&quot; BeamWidthAthwartship=&quot;6.18&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;214594&quot; Gain=&quot;28.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.27&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;221531&quot; Gain=&quot;28.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.1&quot; BeamWidthAthwartship=&quot;6.21&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;222522&quot; Gain=&quot;28.14&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.07&quot; BeamWidthAthwartship=&quot;6.07&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;223513&quot; Gain=&quot;28.1&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;224504&quot; Gain=&quot;28.09&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.1&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;247297&quot; Gain=&quot;28.02&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.62&quot; BeamWidthAthwartship=&quot;5.61&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;248288&quot; Gain=&quot;28.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.54&quot; BeamWidthAthwartship=&quot;5.57&quot; AngleOffsetAlongship=&quot;0.05&quot; AngleOffsetAthwartship=&quot;-0.11&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;249279&quot; Gain=&quot;28.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.48&quot; BeamWidthAthwartship=&quot;5.51&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;250270&quot; Gain=&quot;28.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.44&quot; BeamWidthAthwartship=&quot;5.48&quot; AngleOffsetAlongship=&quot;0.04&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;251261&quot; Gain=&quot;28.51&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.43&quot; BeamWidthAthwartship=&quot;5.46&quot; AngleOffsetAlongship=&quot;0.03&quot; AngleOffsetAthwartship=&quot;-0.12&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n        &lt;Transceiver TransceiverName=&quot;WBT 747008&quot; IPAddress=&quot;&quot; MarketSegment=&quot;Scientific&quot; SerialNumber=&quot;747008&quot; Impedance=&quot;5400&quot; Multiplexing=&quot;0&quot; RxSampleFrequency=&quot;1500000&quot; TransceiverType=&quot;WBT&quot; EthernetAddress=&quot;0090720b6600&quot; Version=&quot;[0] Ethernet: 00:90:72:0B:66:00&amp;#x0D;&amp;#x0A;[1] Parts-list: WBT 371790/F&amp;#x0D;&amp;#x0A;[2] Product: WBT&amp;#x0D;&amp;#x0A;IP Address: 10.1.48.103&amp;#x0D;&amp;#x0A;Subnet mask: 255.0.0.0&amp;#x0D;&amp;#x0A;Default gateway: 10.1.48.1&amp;#x0D;&amp;#x0A;Serial number: 747008&amp;#x0D;&amp;#x0A;Embedded software: Rev. 2.54&amp;#x0D;&amp;#x0A;FPGA TX firmware: Rev. 5&amp;#x0D;&amp;#x0A;FPGA RX firmware: Rev. 7&amp;#x0D;&amp;#x0A;CH1: 506W CH2: 490W CH3: 490W CH4: 498W&amp;#x0D;&amp;#x0A;TRD1: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD2: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD3: Unable to detect transducer&amp;#x0D;&amp;#x0A;TRD4: Unable to detect transducer&amp;#x0D;&amp;#x0A;&quot; TransceiverSoftwareVersion=&quot;2.54&quot; TransceiverNumber=&quot;4&quot;&gt;\\n            &lt;Channels&gt;\\n                &lt;Channel ChannelID=&quot;WBT 747008-15 ES333-7CD_ES&quot; LogicalChannelID=&quot;WBT 747008-15 ES333-7CD&quot; ChannelIdShort=&quot;ES333-7CD Serial No: 220&quot; MaxTxPowerTransceiver=&quot;2000&quot; HWChannelConfiguration=&quot;15&quot; PulseDuration=&quot;6.4E-05;0.000128;0.000256;0.000512;0.001024&quot; PulseDurationFM=&quot;0.000512;0.001024;0.002048;0.004096;0.008192&quot;&gt;\\n                    &lt;Transducer TransducerName=&quot;ES333-7CD&quot; SerialNumber=&quot;220&quot; Frequency=&quot;333000&quot; FrequencyMinimum=&quot;1000&quot; FrequencyMaximum=&quot;1000000&quot; MaxTxPowerTransducer=&quot;6000&quot; Gain=&quot;25;25;25;17.57;25&quot; SaCorrection=&quot;0;0;0;0;0&quot; EquivalentBeamAngle=&quot;-20.7&quot; DirectivityDropAt2XBeamWidth=&quot;0&quot; AngleSensitivityAlongship=&quot;23&quot; AngleSensitivityAthwartship=&quot;23&quot; AngleOffsetAlongship=&quot;-0.0700000002980232&quot; AngleOffsetAthwartship=&quot;0.0700000002980232&quot; BeamWidthAlongship=&quot;6.73000001907349&quot; BeamWidthAthwartship=&quot;6.76999998092651&quot; BeamType=&quot;1&quot;&gt;\\n                        &lt;FrequencyPar Frequency=&quot;280000&quot; Gain=&quot;24.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.99&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;281001&quot; Gain=&quot;24.92&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.94&quot; BeamWidthAthwartship=&quot;7.97&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;282002&quot; Gain=&quot;24.95&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.91&quot; BeamWidthAthwartship=&quot;7.85&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;290010&quot; Gain=&quot;25.27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.67&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;291011&quot; Gain=&quot;25.29&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.77&quot; BeamWidthAthwartship=&quot;7.86&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;292012&quot; Gain=&quot;25.38&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.63&quot; BeamWidthAthwartship=&quot;7.68&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;293013&quot; Gain=&quot;25.36&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.72&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;311031&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.38&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;312032&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.22&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;313033&quot; Gain=&quot;25.22&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.31&quot; BeamWidthAthwartship=&quot;7.34&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;314034&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.37&quot; BeamWidthAthwartship=&quot;7.6&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;315035&quot; Gain=&quot;25.18&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.5&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;316036&quot; Gain=&quot;25.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.36&quot; BeamWidthAthwartship=&quot;7.43&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;317037&quot; Gain=&quot;25.15&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.33&quot; BeamWidthAthwartship=&quot;7.42&quot; AngleOffsetAlongship=&quot;-0.1&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;318038&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.16&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;319039&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.21&quot; BeamWidthAthwartship=&quot;7.23&quot; AngleOffsetAlongship=&quot;-0.09&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;320040&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.18&quot; BeamWidthAthwartship=&quot;7.32&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;321041&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.3&quot; AngleOffsetAlongship=&quot;-0.08&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;322042&quot; Gain=&quot;25.23&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;323043&quot; Gain=&quot;25.3&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.04&quot; BeamWidthAthwartship=&quot;7.02&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;324044&quot; Gain=&quot;25.24&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.07&quot; BeamWidthAthwartship=&quot;7.2&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;325045&quot; Gain=&quot;25.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.09&quot; BeamWidthAthwartship=&quot;7.26&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;326046&quot; Gain=&quot;25.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.03&quot; BeamWidthAthwartship=&quot;7.15&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;327047&quot; Gain=&quot;25.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.08&quot; BeamWidthAthwartship=&quot;7.18&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;328048&quot; Gain=&quot;25.48&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.92&quot; BeamWidthAthwartship=&quot;7.03&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;329049&quot; Gain=&quot;25.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.01&quot; BeamWidthAthwartship=&quot;7.17&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;330050&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.94&quot; BeamWidthAthwartship=&quot;7.13&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;331051&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.93&quot; BeamWidthAthwartship=&quot;7.14&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;332052&quot; Gain=&quot;25.64&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.8&quot; BeamWidthAthwartship=&quot;6.96&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;333053&quot; Gain=&quot;25.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.87&quot; BeamWidthAthwartship=&quot;7.09&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;334054&quot; Gain=&quot;25.74&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.83&quot; BeamWidthAthwartship=&quot;6.93&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;335055&quot; Gain=&quot;25.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.81&quot; BeamWidthAthwartship=&quot;6.82&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;336056&quot; Gain=&quot;25.94&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.7&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;337057&quot; Gain=&quot;26.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;338058&quot; Gain=&quot;26.13&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.74&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;339059&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.49&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;340060&quot; Gain=&quot;26.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.46&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;341061&quot; Gain=&quot;26.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;342062&quot; Gain=&quot;26.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.47&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;343063&quot; Gain=&quot;26.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;344064&quot; Gain=&quot;26.39&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.57&quot; BeamWidthAthwartship=&quot;6.68&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;345065&quot; Gain=&quot;26.32&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.55&quot; BeamWidthAthwartship=&quot;6.57&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;346066&quot; Gain=&quot;26.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.51&quot; BeamWidthAthwartship=&quot;6.62&quot; AngleOffsetAlongship=&quot;0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;347067&quot; Gain=&quot;26.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.67&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;348068&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.63&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;349069&quot; Gain=&quot;26.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.58&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;350070&quot; Gain=&quot;26.81&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.65&quot; BeamWidthAthwartship=&quot;6.69&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;351071&quot; Gain=&quot;26.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.6&quot; BeamWidthAthwartship=&quot;6.75&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;352072&quot; Gain=&quot;26.91&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.48&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.09&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;353073&quot; Gain=&quot;26.93&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.62&quot; BeamWidthAthwartship=&quot;6.73&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;354074&quot; Gain=&quot;27&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.54&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;355075&quot; Gain=&quot;27.16&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.54&quot; BeamWidthAthwartship=&quot;6.56&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;373093&quot; Gain=&quot;27.77&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.12&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;374094&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.11&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;375095&quot; Gain=&quot;27.84&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.11&quot; BeamWidthAthwartship=&quot;6.17&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;376096&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.08&quot; BeamWidthAthwartship=&quot;6.09&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;377097&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.04&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;378098&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.01&quot; BeamWidthAthwartship=&quot;6.05&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;379099&quot; Gain=&quot;27.85&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6&quot; BeamWidthAthwartship=&quot;6.01&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;380000&quot; Gain=&quot;27.82&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;5.97&quot; BeamWidthAthwartship=&quot;5.99&quot; AngleOffsetAlongship=&quot;0&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;283003&quot; Gain=&quot;24.99&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.89&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;284004&quot; Gain=&quot;25.03&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.89&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;285005&quot; Gain=&quot;25.06&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.83&quot; BeamWidthAthwartship=&quot;7.93&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;286006&quot; Gain=&quot;25.11&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.8&quot; BeamWidthAthwartship=&quot;7.91&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;287007&quot; Gain=&quot;25.17&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.79&quot; AngleOffsetAlongship=&quot;-0.07&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;288008&quot; Gain=&quot;25.19&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.71&quot; BeamWidthAthwartship=&quot;7.84&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;289009&quot; Gain=&quot;25.26&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.69&quot; BeamWidthAthwartship=&quot;7.73&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;294014&quot; Gain=&quot;25.42&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.6&quot; BeamWidthAthwartship=&quot;7.65&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;295015&quot; Gain=&quot;25.43&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.62&quot; BeamWidthAthwartship=&quot;7.78&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;296016&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.55&quot; BeamWidthAthwartship=&quot;7.51&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;297017&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.59&quot; BeamWidthAthwartship=&quot;7.64&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;298018&quot; Gain=&quot;25.53&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.53&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;299019&quot; Gain=&quot;25.52&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;300020&quot; Gain=&quot;25.59&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.56&quot; BeamWidthAthwartship=&quot;7.63&quot; AngleOffsetAlongship=&quot;-0.06&quot; AngleOffsetAthwartship=&quot;-0.02&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;301021&quot; Gain=&quot;25.57&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.53&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;302022&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.54&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;303023&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.49&quot; BeamWidthAthwartship=&quot;7.52&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;304024&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.5&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.03&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;305025&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.48&quot; BeamWidthAthwartship=&quot;7.46&quot; AngleOffsetAlongship=&quot;-0.05&quot; AngleOffsetAthwartship=&quot;-0.01&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;306026&quot; Gain=&quot;25.55&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.42&quot; BeamWidthAthwartship=&quot;7.39&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;307027&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.31&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;308028&quot; Gain=&quot;25.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.39&quot; BeamWidthAthwartship=&quot;7.48&quot; AngleOffsetAlongship=&quot;-0.04&quot; AngleOffsetAthwartship=&quot;0&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;309029&quot; Gain=&quot;25.58&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.34&quot; BeamWidthAthwartship=&quot;7.37&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;310030&quot; Gain=&quot;25.54&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;7.35&quot; BeamWidthAthwartship=&quot;7.4&quot; AngleOffsetAlongship=&quot;-0.03&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;356076&quot; Gain=&quot;27.08&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.53&quot; BeamWidthAthwartship=&quot;6.55&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;357077&quot; Gain=&quot;27.25&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.5&quot; BeamWidthAthwartship=&quot;6.58&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;358078&quot; Gain=&quot;27.28&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;359079&quot; Gain=&quot;27.37&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.44&quot; BeamWidthAthwartship=&quot;6.5&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;360080&quot; Gain=&quot;27.46&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.4&quot; BeamWidthAthwartship=&quot;6.44&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;361081&quot; Gain=&quot;27.34&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.39&quot; BeamWidthAthwartship=&quot;6.43&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.04&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;362082&quot; Gain=&quot;27.63&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.34&quot; BeamWidthAthwartship=&quot;6.37&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;363083&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.29&quot; BeamWidthAthwartship=&quot;6.33&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;364084&quot; Gain=&quot;27.5&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.32&quot; BeamWidthAthwartship=&quot;6.36&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;365085&quot; Gain=&quot;27.76&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.25&quot; BeamWidthAthwartship=&quot;6.29&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;366086&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;367087&quot; Gain=&quot;27.56&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.23&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;368088&quot; Gain=&quot;27.71&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.2&quot; BeamWidthAthwartship=&quot;6.2&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.06&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;369089&quot; Gain=&quot;27.83&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.15&quot; BeamWidthAthwartship=&quot;6.13&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.07&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;370090&quot; Gain=&quot;27.79&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.16&quot; BeamWidthAthwartship=&quot;6.1&quot; AngleOffsetAlongship=&quot;-0.01&quot; AngleOffsetAthwartship=&quot;-0.08&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;371091&quot; Gain=&quot;27.67&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.13&quot; BeamWidthAthwartship=&quot;6.15&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                        &lt;FrequencyPar Frequency=&quot;372092&quot; Gain=&quot;27.7&quot; Impedance=&quot;75&quot; Phase=&quot;0&quot; BeamWidthAlongship=&quot;6.14&quot; BeamWidthAthwartship=&quot;6.12&quot; AngleOffsetAlongship=&quot;-0.02&quot; AngleOffsetAthwartship=&quot;-0.05&quot; /&gt;\\n                    &lt;/Transducer&gt;\\n                &lt;/Channel&gt;\\n            &lt;/Channels&gt;\\n        &lt;/Transceiver&gt;\\n    &lt;/Transceivers&gt;\\n    &lt;Transducers MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Transducer TransducerName=&quot;ES70-7CD&quot; TransducerSerialNumber=&quot;134&quot; TransducerCustomName=&quot;ES70-7CD Serial No: 134&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES120-7CD&quot; TransducerSerialNumber=&quot;146&quot; TransducerCustomName=&quot;ES120-7CD Serial No: 146&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES200-7CD&quot; TransducerSerialNumber=&quot;166&quot; TransducerCustomName=&quot;ES200-7CD Serial No: 166&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n        &lt;Transducer TransducerName=&quot;ES333-7CD&quot; TransducerSerialNumber=&quot;220&quot; TransducerCustomName=&quot;ES333-7CD Serial No: 220&quot; TransducerMounting=&quot;Towed&quot; TransducerOrientation=&quot;Vertical&quot; TransducerOffsetX=&quot;0&quot; TransducerOffsetY=&quot;0&quot; TransducerOffsetZ=&quot;0&quot; TransducerAlphaX=&quot;0&quot; TransducerAlphaY=&quot;0&quot; TransducerAlphaZ=&quot;0&quot; /&gt;\\n    &lt;/Transducers&gt;\\n    &lt;ConfiguredSensors MergeOperation=&quot;AddNodeTree&quot;&gt;\\n        &lt;Sensor Name=&quot;GPS From LAN Port 2 GPS&quot; Type=&quot;GPS&quot; Port=&quot;Lan Port 3&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;GLL from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GLL&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Geographical.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Global.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;RMC from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;RMC&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Specific.PositionSpeedCourse&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;3&quot; /&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;GGK from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;GGK&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.GGK.Position&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Latitude&quot; Priority=&quot;4&quot; /&gt;\\n                &lt;Value Name=&quot;Longitude&quot; Priority=&quot;4&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;VTG from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;VTG&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.Ground&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Course&quot; Priority=&quot;2&quot; /&gt;\\n                &lt;Value Name=&quot;CourseNotUsedMagnetic&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Speed&quot; Priority=&quot;2&quot; /&gt;\\n            &lt;/Telegram&gt;\\n            &lt;Telegram Name=&quot;ZDA from GPS From LAN Port 2 GPS&quot; SensorType=&quot;GPS&quot; Type=&quot;ZDA&quot; SubscriptionPath=&quot;GPS From LAN Port 2 GPS@GPS.TimeInfo&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;TimeInfo&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;Annotation From LAN Port 3 Annotation&quot; Type=&quot;Annotation&quot; Port=&quot;Lan Port 4&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;Annotation from Annotation From LAN Port 3 Annotation&quot; SensorType=&quot;Annotation&quot; Type=&quot;Annotation&quot; SubscriptionPath=&quot;Annotation From LAN Port 3 Annotation@Annotation.Text&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Annotation&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;External Depth From LAN Port 9 Pressure&quot; Type=&quot;EchoDepth&quot; Port=&quot;Lan Port 10&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;DPT from External Depth From LAN Port 9 Pressure&quot; SensorType=&quot;EchoDepth&quot; Type=&quot;DPT&quot; SubscriptionPath=&quot;External Depth From LAN Port 9 Pressure@EchoDepth.DepthTransducer&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Depth&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;TowedBodyDepth&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n        &lt;Sensor Name=&quot;MotionBinary From LAN Port 1 8000&quot; Type=&quot;MotionBinary&quot; Port=&quot;Lan Port 2&quot; TalkerID=&quot;&quot; X=&quot;0&quot; Y=&quot;0&quot; Z=&quot;0&quot; AngleX=&quot;0&quot; AngleY=&quot;0&quot; AngleZ=&quot;0&quot; Unique=&quot;0&quot; Timeout=&quot;20&quot;&gt;\\n            &lt;Telegram Name=&quot;MRU from MotionBinary From LAN Port 1 8000&quot; SensorType=&quot;MotionBinary&quot; Type=&quot;MRU&quot; SubscriptionPath=&quot;MotionBinary From LAN Port 1 8000@MotionBinary.MotionData&quot; Enabled=&quot;1&quot;&gt;\\n                &lt;Value Name=&quot;Roll&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Pitch&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heading&quot; Priority=&quot;1&quot; /&gt;\\n                &lt;Value Name=&quot;Heave&quot; Priority=&quot;1&quot; /&gt;\\n            &lt;/Telegram&gt;\\n        &lt;/Sensor&gt;\\n    &lt;/ConfiguredSensors&gt;\\n&lt;/Configuration&gt;&#x27;,\n",
        "      dtype=&#x27;&lt;U100225&#x27;)</pre></div></li></ul></div></li></ul></div></div><br></div>\n",
        "                        </ul>\n",
        "                    </div>\n",
@@ -5346,7 +5346,7 @@
        "└── Vendor_specific: contains vendor-specific information about the sonar and the data."
       ]
      },
-     "execution_count": 3,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -5358,7 +5358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 6,
    "id": "f13c5766",
    "metadata": {},
    "outputs": [
@@ -5391,7 +5391,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "id": "e71a1ea3",
    "metadata": {},
    "outputs": [],
@@ -5414,7 +5414,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 8,
    "id": "9aaa027a",
    "metadata": {},
    "outputs": [],
@@ -5439,7 +5439,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 9,
    "id": "5cd9732a",
    "metadata": {},
    "outputs": [
@@ -5509,7 +5509,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "id": "d8840697",
    "metadata": {},
    "outputs": [],
@@ -5616,7 +5616,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 11,
    "id": "409937dd",
    "metadata": {},
    "outputs": [
@@ -5660,7 +5660,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 12,
    "id": "966cd986",
    "metadata": {},
    "outputs": [
@@ -5719,7 +5719,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 13,
    "id": "cbb9344f",
    "metadata": {},
    "outputs": [
@@ -5772,7 +5772,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 14,
    "id": "e8c17f15",
    "metadata": {},
    "outputs": [
@@ -5780,7 +5780,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_19676\\2179791150.py:11: RuntimeWarning: divide by zero encountered in log10\n",
+      "C:\\Users\\lloyd\\AppData\\Local\\Temp\\ipykernel_5860\\2179791150.py:11: RuntimeWarning: divide by zero encountered in log10\n",
       "  return 20 * np.log10(np.abs(x))\n"
      ]
     },
@@ -5820,7 +5820,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "id": "97d6ab29",
    "metadata": {},
    "outputs": [
@@ -5869,7 +5869,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "id": "53fa2d58",
    "metadata": {},
    "outputs": [
@@ -5909,7 +5909,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 17,
    "id": "1b365099",
    "metadata": {},
    "outputs": [
@@ -5982,7 +5982,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 18,
    "id": "e5132f50",
    "metadata": {},
    "outputs": [
@@ -6013,7 +6013,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 19,
    "id": "7d27cb81",
    "metadata": {},
    "outputs": [
@@ -6064,7 +6064,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 20,
    "id": "d975c349",
    "metadata": {},
    "outputs": [
@@ -6106,7 +6106,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 21,
    "id": "d6b32d7c",
    "metadata": {},
    "outputs": [
@@ -6148,7 +6148,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 22,
    "id": "9150ec46",
    "metadata": {},
    "outputs": [
@@ -6199,7 +6199,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 23,
    "id": "3ae46a66",
    "metadata": {},
    "outputs": [
@@ -6253,7 +6253,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 24,
    "id": "ee60b061",
    "metadata": {},
    "outputs": [
@@ -6298,7 +6298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 25,
    "id": "c337ced4",
    "metadata": {},
    "outputs": [],
@@ -6357,7 +6357,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 26,
    "id": "118b42f1",
    "metadata": {},
    "outputs": [
@@ -6418,7 +6418,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 27,
    "id": "3291a82c",
    "metadata": {},
    "outputs": [
@@ -6462,7 +6462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 28,
    "id": "730f90e2",
    "metadata": {},
    "outputs": [
@@ -6501,7 +6501,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 29,
    "id": "ecbdd657",
    "metadata": {},
    "outputs": [
@@ -6527,7 +6527,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 30,
    "id": "7679300e",
    "metadata": {},
    "outputs": [
@@ -6594,7 +6594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 31,
    "id": "2aa34af3",
    "metadata": {},
    "outputs": [
@@ -6626,7 +6626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 32,
    "id": "5cbb42d1",
    "metadata": {},
    "outputs": [
@@ -6699,7 +6699,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 33,
    "id": "f4e0e279",
    "metadata": {},
    "outputs": [
@@ -6736,7 +6736,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 34,
    "id": "77ef947d",
    "metadata": {},
    "outputs": [
@@ -6773,7 +6773,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 35,
    "id": "f8caa9c9",
    "metadata": {},
    "outputs": [
@@ -6812,7 +6812,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 36,
    "id": "158cf758",
    "metadata": {},
    "outputs": [
@@ -6840,7 +6840,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 37,
    "id": "540bf3ce",
    "metadata": {},
    "outputs": [
@@ -6879,7 +6879,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 38,
    "id": "bc21412a",
    "metadata": {},
    "outputs": [
@@ -6918,7 +6918,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 39,
    "id": "91b67d71",
    "metadata": {},
    "outputs": [
@@ -6967,7 +6967,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 40,
    "id": "455add3c",
    "metadata": {},
    "outputs": [
@@ -7000,7 +7000,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 41,
    "id": "a24e5128",
    "metadata": {},
    "outputs": [
@@ -7027,7 +7027,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 42,
    "id": "e0d8abd9",
    "metadata": {},
    "outputs": [
@@ -7066,7 +7066,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 43,
    "id": "90f1d082",
    "metadata": {},
    "outputs": [
@@ -7102,7 +7102,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 44,
    "id": "0a14d495",
    "metadata": {},
    "outputs": [
@@ -7133,7 +7133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 45,
    "id": "7ca23f61",
    "metadata": {},
    "outputs": [
@@ -7156,7 +7156,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 46,
    "id": "2903e237",
    "metadata": {},
    "outputs": [
@@ -7195,7 +7195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 47,
    "id": "70228c93",
    "metadata": {},
    "outputs": [
@@ -7248,7 +7248,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 48,
    "id": "6ff2975a",
    "metadata": {},
    "outputs": [
@@ -7476,7 +7476,7 @@
        "13 -4.762531e-05  0.016260      0.071437  "
       ]
      },
-     "execution_count": 46,
+     "execution_count": 48,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -7604,7 +7604,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 49,
    "id": "c39cc60e",
    "metadata": {},
    "outputs": [
@@ -8187,13 +8187,13 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:29:44+00:00\n",
-       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4a7a8833-2c9a-409b-a78b-acf62dcbdcb0' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4a7a8833-2c9a-409b-a78b-acf62dcbdcb0' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-4a69778b-70f6-46f5-97af-9fff53184ea5' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4a69778b-70f6-46f5-97af-9fff53184ea5' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-cb5ab5d1-b01f-41a7-b44c-1c244fa174ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cb5ab5d1-b01f-41a7-b44c-1c244fa174ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af0c1f83-8b40-442b-912b-998ed32b9f22' class='xr-var-data-in' type='checkbox'><label for='data-af0c1f83-8b40-442b-912b-998ed32b9f22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
+       "    processing_time:              2026-06-20T23:49:45+00:00\n",
+       "    processing_function:          calibrate.compute_Sp</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6e7e3a7d-b4ed-4981-9d95-af936a06b48e' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-6e7e3a7d-b4ed-4981-9d95-af936a06b48e' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 4</li><li><span class='xr-has-index'>ping_time</span>: 1266</li><li><span class='xr-has-index'>range_sample</span>: 3534</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-cd8ce362-16c4-47c6-9a6d-2fea80f4719a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-cd8ce362-16c4-47c6-9a6d-2fea80f4719a' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747008-15 ES333-7CD_ES&#x27; ......</div><input id='attrs-77c97856-748e-4a60-addb-a1d983d18fd7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-77c97856-748e-4a60-addb-a1d983d18fd7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9127a27-ce23-41ef-b085-9dd922403a38' class='xr-var-data-in' type='checkbox'><label for='data-b9127a27-ce23-41ef-b085-9dd922403a38' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747008-15 ES333-7CD_ES&#x27;, &#x27;WBT 747015-15 ES70-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747019-15 ES200-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-4439134c-3a76-4fa4-ad67-70d891f6e106' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4439134c-3a76-4fa4-ad67-70d891f6e106' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4301ffcb-a85f-49a2-99d4-ef573d7d2682' class='xr-var-data-in' type='checkbox'><label for='data-4301ffcb-a85f-49a2-99d4-ef573d7d2682' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ping_time</span></div><div class='xr-var-dims'>(ping_time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-f69c769d-4267-48f8-ad22-4f2032698ab9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f69c769d-4267-48f8-ad22-4f2032698ab9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ad09206-806b-47e1-876f-9fe4303e6a4f' class='xr-var-data-in' type='checkbox'><label for='data-7ad09206-806b-47e1-876f-9fe4303e6a4f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Timestamp of each ping</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ..., &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;, &#x27;2021-12-15T14:40:09.422045000&#x27;],\n",
-       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-b02a1d4a-4d63-42c9-bcd8-1748aeac028a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b02a1d4a-4d63-42c9-bcd8-1748aeac028a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7dd4f55-3951-4cc5-8a03-523b3cf19a0d' class='xr-var-data-in' type='checkbox'><label for='data-a7dd4f55-3951-4cc5-8a03-523b3cf19a0d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-5c2f88e2-5105-409a-86df-2902299b708c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c2f88e2-5105-409a-86df-2902299b708c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-abfc6f65-6ffe-4152-a72f-d970987c5eeb' class='xr-var-data-in' type='checkbox'><label for='data-abfc6f65-6ffe-4152-a72f-d970987c5eeb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-42b3088e-6795-4676-8f1c-107d48bbbf1a' class='xr-section-summary-in' type='checkbox' /><label for='section-42b3088e-6795-4676-8f1c-107d48bbbf1a' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-99fb031e-608e-4c73-a1d8-56e56fd8e76e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-99fb031e-608e-4c73-a1d8-56e56fd8e76e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b55cf9b-29c6-4078-836a-e5e980f41579' class='xr-var-data-in' type='checkbox'><label for='data-6b55cf9b-29c6-4078-836a-e5e980f41579' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
+       "      shape=(1266,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_sample</span></div><div class='xr-var-dims'>(range_sample)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 3530 3531 3532 3533</div><input id='attrs-facf6353-a4df-4d63-bc8f-8d71af8a2054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-facf6353-a4df-4d63-bc8f-8d71af8a2054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a43db6ad-64e2-4bf6-9593-31b6e8e34bc5' class='xr-var-data-in' type='checkbox'><label for='data-a43db6ad-64e2-4bf6-9593-31b6e8e34bc5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Along-range sample number, base 0</dd></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 3531, 3532, 3533], shape=(3534,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-0b3954c0-17c0-4b85-a7ce-35ad4b0646f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b3954c0-17c0-4b85-a7ce-35ad4b0646f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06b089c1-fdd8-4e47-b1b6-cd837cad684f' class='xr-var-data-in' type='checkbox'><label for='data-06b089c1-fdd8-4e47-b1b6-cd837cad684f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8fb70a61-2036-4673-b1c1-78e76aadf6ad' class='xr-section-summary-in' type='checkbox' /><label for='section-8fb70a61-2036-4673-b1c1-78e76aadf6ad' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>Sp</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d672beba-c442-4d08-9349-bde511522dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d672beba-c442-4d08-9349-bde511522dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dabb206c-f1d0-4de8-9cc9-19943aa57e1c' class='xr-var-data-in' type='checkbox'><label for='data-dabb206c-f1d0-4de8-9cc9-19943aa57e1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Point scattering strength (Sp re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[          nan,           nan,           nan, ...,\n",
        "         -195.57397259, -218.79009715, -150.30546618],\n",
        "        [          nan,           nan,           nan, ...,\n",
        "         -198.89271647, -222.29194801, -150.30546618],\n",
@@ -8233,7 +8233,7 @@
        "                   nan,           nan,           nan],\n",
        "        [          nan,           nan,           nan, ...,\n",
        "                   nan,           nan,           nan]]],\n",
-       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-e99134ec-e7df-4f3d-864c-a68a823c5867' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99134ec-e7df-4f3d-864c-a68a823c5867' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1f5c036-fff1-45ae-bc03-29284e907fdd' class='xr-var-data-in' type='checkbox'><label for='data-a1f5c036-fff1-45ae-bc03-29284e907fdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>echo_range</span></div><div class='xr-var-dims'>(channel, ping_time, range_sample)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.003961 0.007922 ... nan nan</div><input id='attrs-1bfa8612-5735-470b-bf5c-299be9b97583' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bfa8612-5735-470b-bf5c-299be9b97583' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ff0290-8f50-476f-88fb-62d25c63c1fe' class='xr-var-data-in' type='checkbox'><label for='data-77ff0290-8f50-476f-88fb-62d25c63c1fe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Range distance</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
        "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
        "        [0.00000000e+00, 3.96106419e-03, 7.92212838e-03, ...,\n",
        "         1.39865177e+01, 1.39904787e+01, 1.39944398e+01],\n",
@@ -8273,80 +8273,80 @@
        "                    nan,            nan,            nan],\n",
        "        [           nan,            nan,            nan, ...,\n",
        "                    nan,            nan,            nan]]],\n",
-       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-3b8df520-0c81-4d0c-94fd-fa005afcdd39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b8df520-0c81-4d0c-94fd-fa005afcdd39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34bc4343-40ac-4898-9df1-23b9510cbf65' class='xr-var-data-in' type='checkbox'><label for='data-34bc4343-40ac-4898-9df1-23b9510cbf65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-2a7bd036-ad2b-4e5b-8e06-b85d4d2f99fa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2a7bd036-ad2b-4e5b-8e06-b85d4d2f99fa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c9bc31f1-5391-48c0-84f6-7c087178d41a' class='xr-var-data-in' type='checkbox'><label for='data-c9bc31f1-5391-48c0-84f6-7c087178d41a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-0390066d-a482-4b4f-ac8f-838f05d57080' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0390066d-a482-4b4f-ac8f-838f05d57080' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba6bc0e1-46e1-437b-b38b-6268e5fd7584' class='xr-var-data-in' type='checkbox'><label for='data-ba6bc0e1-46e1-437b-b38b-6268e5fd7584' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
+       "      shape=(4, 1266, 3534))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>frequency_nominal</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.33e+05 7e+04 2e+05 1.2e+05</div><input id='attrs-fc9e2f0c-ca8f-4887-8896-e94b5db8337a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc9e2f0c-ca8f-4887-8896-e94b5db8337a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1922088-b80f-40dc-8bc9-977ccd26bbc4' class='xr-var-data-in' type='checkbox'><label for='data-e1922088-b80f-40dc-8bc9-977ccd26bbc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Transducer frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([333000.,  70000., 200000., 120000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_speed</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.485e+03</div><input id='attrs-19065501-1903-4f2e-b810-21883428644d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-19065501-1903-4f2e-b810-21883428644d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4bb6afc-14a5-4d61-81ba-3d63b5767691' class='xr-var-data-in' type='checkbox'><label for='data-a4bb6afc-14a5-4d61-81ba-3d63b5767691' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(1485.4)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sound_absorption</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.07527 0.07527 ... 0.0377 nan</div><input id='attrs-392d9a5a-e00f-40b9-a5c4-5bbb3e39943e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-392d9a5a-e00f-40b9-a5c4-5bbb3e39943e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4faa3d9d-970c-48d5-9874-b80502ecec8b' class='xr-var-data-in' type='checkbox'><label for='data-4faa3d9d-970c-48d5-9874-b80502ecec8b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd><dt><span>valid_min :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>array([[0.07527219, 0.07527219, 0.07527219, ..., 0.07527219, 0.07527219,\n",
        "        0.07527219],\n",
        "       [0.02167407, 0.02167407, 0.02167407, ..., 0.02167407, 0.02167407,\n",
        "        0.02167407],\n",
        "       [0.05300738, 0.05300738, 0.05300738, ..., 0.05300738, 0.05300738,\n",
        "        0.05300738],\n",
        "       [0.03770373, 0.03770373, 0.03770373, ..., 0.03770373, 0.03770373,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-a30c85ba-a138-4049-999c-901d55289b06' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a30c85ba-a138-4049-999c-901d55289b06' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4bb956f9-7074-43b7-93d2-75dbd4a3d21a' class='xr-var-data-in' type='checkbox'><label for='data-4bb956f9-7074-43b7-93d2-75dbd4a3d21a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-310cdb44-825b-4d34-8a80-a6abb2e9a5d0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-310cdb44-825b-4d34-8a80-a6abb2e9a5d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28d6de51-0ff1-4b01-95b5-0cc7f1ee5c10' class='xr-var-data-in' type='checkbox'><label for='data-28d6de51-0ff1-4b01-95b5-0cc7f1ee5c10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-8494ac63-4551-4453-9ee6-d53d3aae4bc3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8494ac63-4551-4453-9ee6-d53d3aae4bc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d636e27f-37ca-4f8a-a260-586b1827fe34' class='xr-var-data-in' type='checkbox'><label for='data-d636e27f-37ca-4f8a-a260-586b1827fe34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-cfd179b0-9775-4f40-81bc-8b7d4b128282' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cfd179b0-9775-4f40-81bc-8b7d4b128282' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8c1c3b2-dd19-47d8-a53b-996941691440' class='xr-var-data-in' type='checkbox'><label for='data-e8c1c3b2-dd19-47d8-a53b-996941691440' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-6665f89a-60d1-4259-aeb3-31236efee495' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6665f89a-60d1-4259-aeb3-31236efee495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cef341c6-1ed5-4ec9-b16d-5b3b00d413d2' class='xr-var-data-in' type='checkbox'><label for='data-cef341c6-1ed5-4ec9-b16d-5b3b00d413d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-12d2c173-7ab5-46cd-b40a-d303ff3d4734' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-12d2c173-7ab5-46cd-b40a-d303ff3d4734' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19497490-f707-4d9c-9e63-5dfc7a533b6a' class='xr-var-data-in' type='checkbox'><label for='data-19497490-f707-4d9c-9e63-5dfc7a533b6a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temperature</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9.7</div><input id='attrs-e90b325a-97b2-40da-ae00-db46049a7480' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e90b325a-97b2-40da-ae00-db46049a7480' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc05a5cd-9a57-4189-a81c-ab4da3a10bc9' class='xr-var-data-in' type='checkbox'><label for='data-dc05a5cd-9a57-4189-a81c-ab4da3a10bc9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(9.7)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>salinity</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>32.0</div><input id='attrs-e2b0f1da-ce3f-44c0-867c-21c3c5394714' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e2b0f1da-ce3f-44c0-867c-21c3c5394714' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-79e26cb1-6e01-4330-9a64-8e89d34a2336' class='xr-var-data-in' type='checkbox'><label for='data-79e26cb1-6e01-4330-9a64-8e89d34a2336' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(32.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.0</div><input id='attrs-b1498d1e-ab44-4f40-9c50-6207f83247fe' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b1498d1e-ab44-4f40-9c50-6207f83247fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df9ed66a-676e-4cfd-b0be-f33bc0dd0aff' class='xr-var-data-in' type='checkbox'><label for='data-df9ed66a-676e-4cfd-b0be-f33bc0dd0aff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(5.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pH</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>8.0</div><input id='attrs-10e220b2-5314-4168-86c1-fd105bcfa956' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-10e220b2-5314-4168-86c1-fd105bcfa956' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb5fbc0e-1b09-483b-82b2-8daeca836cca' class='xr-var-data-in' type='checkbox'><label for='data-cb5fbc0e-1b09-483b-82b2-8daeca836cca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(8.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>formula_absorption</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;FG&#x27;</div><input id='attrs-73222eb1-9c95-4aa8-90a7-d7c068f0f2b9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73222eb1-9c95-4aa8-90a7-d7c068f0f2b9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11a41e89-a4a1-4dfc-8fd4-11585f878027' class='xr-var-data-in' type='checkbox'><label for='data-11a41e89-a4a1-4dfc-8fd4-11585f878027' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;FG&#x27;, dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>sa_correction</span></div><div class='xr-var-dims'>(ping_time, channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 nan</div><input id='attrs-069709f1-d1f1-4969-92ca-331580c8512e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-069709f1-d1f1-4969-92ca-331580c8512e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfdefee9-a412-4872-bcc0-c69708243532' class='xr-var-data-in' type='checkbox'><label for='data-bfdefee9-a412-4872-bcc0-c69708243532' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       ...,\n",
        "       [ 0.,  0.,  0.,  0.],\n",
        "       [ 0.,  0.,  0.,  0.],\n",
-       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-83a4be53-4de2-465f-9546-e766aee30c67' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-83a4be53-4de2-465f-9546-e766aee30c67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88b4f137-61fc-4650-95e1-12c671a01aa1' class='xr-var-data-in' type='checkbox'><label for='data-88b4f137-61fc-4650-95e1-12c671a01aa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
+       "       [ 0.,  0.,  0., nan]], shape=(1266, 4))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>gain_correction</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>25.52 25.52 25.52 ... 28.04 nan</div><input id='attrs-a8541166-1d74-478b-ac99-bf9d566aed3b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a8541166-1d74-478b-ac99-bf9d566aed3b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2470384-8b17-41d9-b7b1-c2cc1567d271' class='xr-var-data-in' type='checkbox'><label for='data-a2470384-8b17-41d9-b7b1-c2cc1567d271' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[25.517003  , 25.517003  , 25.517003  , ..., 25.517003  ,\n",
        "        25.517003  , 25.517003  ],\n",
        "       [27.40875   , 27.40875   , 27.40875   , ..., 27.40875   ,\n",
        "        27.40875   , 27.40875   ],\n",
        "       [28.04229062, 28.04229062, 28.04229062, ..., 28.04229062,\n",
        "        28.04229062, 28.04229062],\n",
        "       [28.0375    , 28.0375    , 28.0375    , ..., 28.0375    ,\n",
-       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-e99b8a64-b13a-4a7c-ace7-0783d3dc5dcc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e99b8a64-b13a-4a7c-ace7-0783d3dc5dcc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a6682000-525c-477b-85da-b1b7c5f8f5b3' class='xr-var-data-in' type='checkbox'><label for='data-a6682000-525c-477b-85da-b1b7c5f8f5b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
+       "        28.0375    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>equivalent_beam_angle</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-20.62 -20.62 -20.62 ... -21.4 nan</div><input id='attrs-db67ceb1-348b-4ded-85b7-ff6c62b34dad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db67ceb1-348b-4ded-85b7-ff6c62b34dad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87c9c124-8108-43cd-9098-976435cb7334' class='xr-var-data-in' type='checkbox'><label for='data-87c9c124-8108-43cd-9098-976435cb7334' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>valid_range :</span></dt><dd>(0.0, 12.566370614359172)</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>standard_name :</span></dt><dd>sound_frequency</dd></dl></div><div class='xr-var-data'><pre>array([[-20.62139413, -20.62139413, -20.62139413, ..., -20.62139413,\n",
        "        -20.62139413, -20.62139413],\n",
        "       [-20.7       , -20.7       , -20.7       , ..., -20.7       ,\n",
        "        -20.7       , -20.7       ],\n",
        "       [-21.32816929, -21.32816929, -21.32816929, ..., -21.32816929,\n",
        "        -21.32816929, -21.32816929],\n",
        "       [-21.39524213, -21.39524213, -21.39524213, ..., -21.39524213,\n",
-       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-ce3b1944-a2e1-4321-aea1-0878c84725a2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ce3b1944-a2e1-4321-aea1-0878c84725a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbff2b2f-4f9a-4f69-8c3f-59262c999a47' class='xr-var-data-in' type='checkbox'><label for='data-fbff2b2f-4f9a-4f69-8c3f-59262c999a47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
+       "        -21.39524213,          nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.041 -0.041 ... -0.0575 nan</div><input id='attrs-4a327597-95b1-484c-90ab-15c6e9ad7789' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a327597-95b1-484c-90ab-15c6e9ad7789' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91afcb10-c33f-4283-83a6-d0acf06ae5b2' class='xr-var-data-in' type='checkbox'><label for='data-91afcb10-c33f-4283-83a6-d0acf06ae5b2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[-0.040999  , -0.040999  , -0.040999  , ..., -0.040999  ,\n",
        "        -0.040999  , -0.040999  ],\n",
        "       [-0.2209375 , -0.2209375 , -0.2209375 , ..., -0.2209375 ,\n",
        "        -0.2209375 , -0.2209375 ],\n",
        "       [-0.00590313, -0.00590313, -0.00590313, ..., -0.00590313,\n",
        "        -0.00590313, -0.00590313],\n",
        "       [-0.0575    , -0.0575    , -0.0575    , ..., -0.0575    ,\n",
-       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-50dc169f-a583-4207-99a5-df23ef131b62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-50dc169f-a583-4207-99a5-df23ef131b62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2249eddc-7100-48bd-a19e-4cd6a9309ba0' class='xr-var-data-in' type='checkbox'><label for='data-2249eddc-7100-48bd-a19e-4cd6a9309ba0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
+       "        -0.0575    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_offset_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0195 0.0195 0.0195 ... 0.0175 nan</div><input id='attrs-b4d35041-8b89-4d95-9e9b-4380fec7fb32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b4d35041-8b89-4d95-9e9b-4380fec7fb32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c27b9ce-f78d-438a-b723-39b96fc99772' class='xr-var-data-in' type='checkbox'><label for='data-5c27b9ce-f78d-438a-b723-39b96fc99772' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.0195005 ,  0.0195005 ,  0.0195005 , ...,  0.0195005 ,\n",
        "         0.0195005 ,  0.0195005 ],\n",
        "       [-0.124375  , -0.124375  , -0.124375  , ..., -0.124375  ,\n",
        "        -0.124375  , -0.124375  ],\n",
        "       [-0.08590313, -0.08590313, -0.08590313, ..., -0.08590313,\n",
        "        -0.08590313, -0.08590313],\n",
        "       [ 0.0175    ,  0.0175    ,  0.0175    , ...,  0.0175    ,\n",
-       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-52ce2ce0-6de0-4002-91c7-9afae64847ae' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-52ce2ce0-6de0-4002-91c7-9afae64847ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b10aa4bc-904a-49ce-b405-505e8e084a02' class='xr-var-data-in' type='checkbox'><label for='data-b10aa4bc-904a-49ce-b405-505e8e084a02' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "         0.0175    ,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-d16f5046-203b-4e95-b2c6-76f6d1287b73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d16f5046-203b-4e95-b2c6-76f6d1287b73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-298f87f6-88f7-43f3-8278-6a4559d0b251' class='xr-var-data-in' type='checkbox'><label for='data-298f87f6-88f7-43f3-8278-6a4559d0b251' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
        "        22.79279279, 22.79279279],\n",
        "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
        "        23.        , 23.        ],\n",
        "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
        "        24.725     , 24.725     ],\n",
        "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
-       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-56bce38b-7018-441c-93fc-52b2ab05d35c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-56bce38b-7018-441c-93fc-52b2ab05d35c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8c4996cc-8733-4a73-b6b3-447a8b408904' class='xr-var-data-in' type='checkbox'><label for='data-8c4996cc-8733-4a73-b6b3-447a8b408904' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_sensitivity_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>22.79 22.79 22.79 ... 24.92 nan</div><input id='attrs-7f504da6-ada7-4550-b871-098cc1a6bddd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f504da6-ada7-4550-b871-098cc1a6bddd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0456e090-5f1e-4dbd-b183-b88be29b551f' class='xr-var-data-in' type='checkbox'><label for='data-0456e090-5f1e-4dbd-b183-b88be29b551f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[22.79279279, 22.79279279, 22.79279279, ..., 22.79279279,\n",
        "        22.79279279, 22.79279279],\n",
        "       [23.        , 23.        , 23.        , ..., 23.        ,\n",
        "        23.        , 23.        ],\n",
        "       [24.725     , 24.725     , 24.725     , ..., 24.725     ,\n",
        "        24.725     , 24.725     ],\n",
        "       [24.91666667, 24.91666667, 24.91666667, ..., 24.91666667,\n",
-       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-22d618ad-b8da-46b4-a80d-d267e6fcb7c6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-22d618ad-b8da-46b4-a80d-d267e6fcb7c6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98cef8e4-5988-4ee7-853c-0f66e2beb0fb' class='xr-var-data-in' type='checkbox'><label for='data-98cef8e4-5988-4ee7-853c-0f66e2beb0fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
+       "        24.91666667,         nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_alongship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.943 6.943 6.943 ... 6.17 6.17 nan</div><input id='attrs-f4573ed4-9f1b-4d2d-a3d4-7a0944d6c7c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f4573ed4-9f1b-4d2d-a3d4-7a0944d6c7c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-906181f4-12c6-4a0f-95a0-4ba1e8fcb018' class='xr-var-data-in' type='checkbox'><label for='data-906181f4-12c6-4a0f-95a0-4ba1e8fcb018' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[6.9434965 , 6.9434965 , 6.9434965 , ..., 6.9434965 , 6.9434965 ,\n",
        "        6.9434965 ],\n",
        "       [6.9290625 , 6.9290625 , 6.9290625 , ..., 6.9290625 , 6.9290625 ,\n",
        "        6.9290625 ],\n",
        "       [6.25361251, 6.25361251, 6.25361251, ..., 6.25361251, 6.25361251,\n",
        "        6.25361251],\n",
        "       [6.17      , 6.17      , 6.17      , ..., 6.17      , 6.17      ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-538ef8a2-bf58-4108-8d19-bf61c3831b32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-538ef8a2-bf58-4108-8d19-bf61c3831b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a506c1b-b29d-461e-8b83-2868bba8d1c6' class='xr-var-data-in' type='checkbox'><label for='data-5a506c1b-b29d-461e-8b83-2868bba8d1c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beamwidth_athwartship</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.132 7.132 7.132 ... 6.277 nan</div><input id='attrs-89f7ef9f-9380-48cb-9498-69099f11be11' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-89f7ef9f-9380-48cb-9498-69099f11be11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-169b2c8c-cd59-4280-81c9-a2aba3fb84f6' class='xr-var-data-in' type='checkbox'><label for='data-169b2c8c-cd59-4280-81c9-a2aba3fb84f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[7.131998  , 7.131998  , 7.131998  , ..., 7.131998  , 7.131998  ,\n",
        "        7.131998  ],\n",
        "       [6.7325    , 6.7325    , 6.7325    , ..., 6.7325    , 6.7325    ,\n",
        "        6.7325    ],\n",
        "       [6.24638749, 6.24638749, 6.24638749, ..., 6.24638749, 6.24638749,\n",
        "        6.24638749],\n",
        "       [6.2775    , 6.2775    , 6.2775    , ..., 6.2775    , 6.2775    ,\n",
-       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-ab00af5c-ec0e-4801-bc2c-2ba19d84d50c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ab00af5c-ec0e-4801-bc2c-2ba19d84d50c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a3bb0ee-0acf-4042-80d3-4bcbc36a7092' class='xr-var-data-in' type='checkbox'><label for='data-6a3bb0ee-0acf-4042-80d3-4bcbc36a7092' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
+       "               nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transducer</span></div><div class='xr-var-dims'>(channel, ping_time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>75.0 75.0 75.0 ... 75.0 75.0 nan</div><input id='attrs-b5871bd2-523c-48a0-a15e-9b0d22b86eb6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5871bd2-523c-48a0-a15e-9b0d22b86eb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4baf4f73-2a0e-4409-9ba7-24a1007f9e86' class='xr-var-data-in' type='checkbox'><label for='data-4baf4f73-2a0e-4409-9ba7-24a1007f9e86' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[75., 75., 75., ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., 75., 75., 75.],\n",
        "       [75., 75., 75., ..., 75., 75., 75.],\n",
-       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-9b26ee2e-197f-418c-9246-c34a331048a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b26ee2e-197f-418c-9246-c34a331048a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e9235ef-a2cc-496c-a66e-363a99575a5c' class='xr-var-data-in' type='checkbox'><label for='data-3e9235ef-a2cc-496c-a66e-363a99575a5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-4617d66a-4fc6-4f68-a5b0-aa6260307e12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4617d66a-4fc6-4f68-a5b0-aa6260307e12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7405164c-7471-4ecc-914e-986019768774' class='xr-var-data-in' type='checkbox'><label for='data-7405164c-7471-4ecc-914e-986019768774' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-a02b51c1-7e0f-412b-8ba5-d262e7c1a89d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a02b51c1-7e0f-412b-8ba5-d262e7c1a89d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4c45e45-f36d-459d-9537-fb6a0c14d536' class='xr-var-data-in' type='checkbox'><label for='data-f4c45e45-f36d-459d-9537-fb6a0c14d536' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-01a7c272-f985-4204-86eb-1ae37af5c85f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01a7c272-f985-4204-86eb-1ae37af5c85f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42aca939-d6f1-4782-9d81-0645801ffdb8' class='xr-var-data-in' type='checkbox'><label for='data-42aca939-d6f1-4782-9d81-0645801ffdb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79a718aa-25ca-4ddb-867e-3b972e21fa1f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-79a718aa-25ca-4ddb-867e-3b972e21fa1f' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:29:44+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
+       "       [75., 75., 75., ..., 75., 75., nan]], shape=(4, 1266))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>impedance_transceiver</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>5400 5400 5400 5400</div><input id='attrs-0c70e769-9331-4ae9-ae44-de7f52cf1bc8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c70e769-9331-4ae9-ae44-de7f52cf1bc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaace22b-c207-4521-aaa4-44a8e4c92e00' class='xr-var-data-in' type='checkbox'><label for='data-eaace22b-c207-4521-aaa4-44a8e4c92e00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ohm</dd><dt><span>long_name :</span></dt><dd>Transceiver impedance</dd></dl></div><div class='xr-var-data'><pre>array([5400, 5400, 5400, 5400])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>receiver_sampling_frequency</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5e+06 1.5e+06 1.5e+06 1.5e+06</div><input id='attrs-15482aa4-84d0-4c38-9668-86417be3d040' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15482aa4-84d0-4c38-9668-86417be3d040' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea69615c-fc53-4569-8715-94c15799f588' class='xr-var-data-in' type='checkbox'><label for='data-ea69615c-fc53-4569-8715-94c15799f588' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>Hz</dd><dt><span>long_name :</span></dt><dd>Receiver sampling frequency</dd></dl></div><div class='xr-var-data'><pre>array([1500000., 1500000., 1500000., 1500000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-14395ee1-e49e-41cc-92b0-6778cbdbaf25' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14395ee1-e49e-41cc-92b0-6778cbdbaf25' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c20b1f3-48d8-46cc-ab33-bbcf937a6687' class='xr-var-data-in' type='checkbox'><label for='data-9c20b1f3-48d8-46cc-ab33-bbcf937a6687' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-db97f6ae-b8d0-4434-b10f-3f83f6e759ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-db97f6ae-b8d0-4434-b10f-3f83f6e759ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d1feaf6-78af-4fba-bcc7-9b073edef4d8' class='xr-var-data-in' type='checkbox'><label for='data-9d1feaf6-78af-4fba-bcc7-9b073edef4d8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1fcac28f-3fd1-451a-8429-4b2d6dcdd5d8' class='xr-section-summary-in' type='checkbox' checked /><label for='section-1fcac28f-3fd1-451a-8429-4b2d6dcdd5d8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-20T23:49:45+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_Sp</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 287MB\n",
@@ -8374,11 +8374,11 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:29:44+00:00\n",
+       "    processing_time:              2026-06-20T23:49:45+00:00\n",
        "    processing_function:          calibrate.compute_Sp"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 49,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -8400,7 +8400,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 50,
    "id": "0892fb0d",
    "metadata": {},
    "outputs": [
@@ -8489,7 +8489,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 51,
    "id": "fbc2ca91",
    "metadata": {},
    "outputs": [
@@ -9048,17 +9048,17 @@
        "    target_range      (target_id) float64 10kB 5.805 5.805 5.805 ... 5.781 5.781\n",
        "    target_range_min  (target_id) float64 10kB 5.306 5.306 5.306 ... 5.306 5.306\n",
        "    target_range_max  (target_id) float64 10kB 6.298 6.298 6.298 ... 6.298 6.298\n",
-       "    raw_ping_index    (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1817ff15-4059-4f19-8d79-e9064b6c5dd1' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-1817ff15-4059-4f19-8d79-e9064b6c5dd1' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-14673265-fe56-4d4f-a393-6fc458555e06' class='xr-section-summary-in' type='checkbox' checked /><label for='section-14673265-fe56-4d4f-a393-6fc458555e06' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-617b56af-117a-4b5d-933b-27510c0ce54f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-617b56af-117a-4b5d-933b-27510c0ce54f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c0abee7-81b3-4ac3-ba34-a2b86e5282cb' class='xr-var-data-in' type='checkbox'><label for='data-5c0abee7-81b3-4ac3-ba34-a2b86e5282cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-d0b9a958-2260-453b-bc03-9ed9cbffcec6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d0b9a958-2260-453b-bc03-9ed9cbffcec6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed137115-748a-4cfb-b516-72aaec8a355a' class='xr-var-data-in' type='checkbox'><label for='data-ed137115-748a-4cfb-b516-72aaec8a355a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
+       "    raw_ping_index    (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-dafe2554-92ec-4cbb-a2d8-33bb1f3d071c' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-dafe2554-92ec-4cbb-a2d8-33bb1f3d071c' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>target_id</span>: 1265</li></ul></div></li><li class='xr-section-item'><input id='section-7b25e42b-b072-466d-8c55-24cd89741bd3' class='xr-section-summary-in' type='checkbox' checked /><label for='section-7b25e42b-b072-466d-8c55-24cd89741bd3' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-e15e832c-3f88-4ff8-91cb-1259c33bde14' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e15e832c-3f88-4ff8-91cb-1259c33bde14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c16c75a-f838-4149-96af-94caf0774cb8' class='xr-var-data-in' type='checkbox'><label for='data-1c16c75a-f838-4149-96af-94caf0774cb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>channel</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27; ......</div><input id='attrs-f75321fa-82f0-4f4b-ab27-b5f93a0ab693' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f75321fa-82f0-4f4b-ab27-b5f93a0ab693' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd9dbb09-495b-4dd9-9eed-c61aaccbae07' class='xr-var-data-in' type='checkbox'><label for='data-bd9dbb09-495b-4dd9-9eed-c61aaccbae07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, ..., &#x27;WBT 747022-15 ES120-7CD_ES&#x27;,\n",
        "       &#x27;WBT 747022-15 ES120-7CD_ES&#x27;, &#x27;WBT 747022-15 ES120-7CD_ES&#x27;],\n",
-       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-2fcde00e-f292-46e0-bad0-d6d909b0e3e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2fcde00e-f292-46e0-bad0-d6d909b0e3e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63c0f0e2-a264-4eb8-ac73-f8f74dc355df' class='xr-var-data-in' type='checkbox'><label for='data-63c0f0e2-a264-4eb8-ac73-f8f74dc355df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "      shape=(1265,), dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-d168ab2d-c0d5-479e-a77d-769c30d0cf70' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d168ab2d-c0d5-479e-a77d-769c30d0cf70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7de09ef-a012-4556-932a-7c1355c665f2' class='xr-var-data-in' type='checkbox'><label for='data-d7de09ef-a012-4556-932a-7c1355c665f2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "       &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "       &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "       &#x27;2021-12-15T14:40:09.162188000&#x27;],\n",
-       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c619845c-f10b-43ec-97e2-a45202e47157' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c619845c-f10b-43ec-97e2-a45202e47157' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-a6f6e174-ed72-407f-9356-25db93e0f067' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a6f6e174-ed72-407f-9356-25db93e0f067' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b631dad-9682-48cf-981e-184f66445a1a' class='xr-var-data-in' type='checkbox'><label for='data-4b631dad-9682-48cf-981e-184f66445a1a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-b16def64-ca41-46f1-a012-919aaddc20c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b16def64-ca41-46f1-a012-919aaddc20c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35822fee-068a-49f9-8260-edf49b1e8669' class='xr-var-data-in' type='checkbox'><label for='data-35822fee-068a-49f9-8260-edf49b1e8669' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
-       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-26148d73-6d3c-4914-8c19-5a60e650396f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26148d73-6d3c-4914-8c19-5a60e650396f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78736372-9ed7-4551-8471-d7cdca778ee4' class='xr-var-data-in' type='checkbox'><label for='data-78736372-9ed7-4551-8471-d7cdca778ee4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
-       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-1d471f85-ed22-4d4b-ac45-2554ac634a95' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1d471f85-ed22-4d4b-ac45-2554ac634a95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19490380-d94c-4820-b641-8a2ee54c60ab' class='xr-var-data-in' type='checkbox'><label for='data-19490380-d94c-4820-b641-8a2ee54c60ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
+       "      shape=(1265,), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c909215e-3140-426e-8387-3fc34b5d6c86' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c909215e-3140-426e-8387-3fc34b5d6c86' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-ea3a411f-07fe-4994-8181-b691b1ca6356' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ea3a411f-07fe-4994-8181-b691b1ca6356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7833ce3-8a05-453e-902a-8fbb38689cdf' class='xr-var-data-in' type='checkbox'><label for='data-c7833ce3-8a05-453e-902a-8fbb38689cdf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "       5.7811768], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_min</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.306 5.306 5.306 ... 5.306 5.306</div><input id='attrs-f7653458-3247-4c73-b4c5-e4d564c05d31' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f7653458-3247-4c73-b4c5-e4d564c05d31' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab178686-b663-4e17-b482-2d5e870b6d44' class='xr-var-data-in' type='checkbox'><label for='data-ab178686-b663-4e17-b482-2d5e870b6d44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([5.3058488, 5.3058488, 5.3058488, ..., 5.3058488, 5.3058488,\n",
+       "       5.3058488], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range_max</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.298 6.298 6.298 ... 6.298 6.298</div><input id='attrs-08076139-f70f-4e16-a365-c60df65ef34c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08076139-f70f-4e16-a365-c60df65ef34c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-844257e3-5193-4d65-9835-90b44d066fb8' class='xr-var-data-in' type='checkbox'><label for='data-844257e3-5193-4d65-9835-90b44d066fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([6.298096, 6.298096, 6.298096, ..., 6.298096, 6.298096, 6.298096],\n",
+       "      shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ping_index</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-1da6224e-1a3e-484b-9894-c435514029cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1da6224e-1a3e-484b-9894-c435514029cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-694870c9-82ba-4258-b77a-393a6e5bb5c0' class='xr-var-data-in' type='checkbox'><label for='data-694870c9-82ba-4258-b77a-393a6e5bb5c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li></ul></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 192kB\n",
@@ -9074,7 +9074,7 @@
        "    raw_ping_index    (target_id) int64 10kB 0 1 2 3 4 ... 1261 1262 1263 1264"
       ]
      },
-     "execution_count": 49,
+     "execution_count": 51,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -9099,7 +9099,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 52,
    "id": "e0ca3c72",
    "metadata": {},
    "outputs": [
@@ -9141,7 +9141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 53,
    "id": "0e515b3a",
    "metadata": {},
    "outputs": [
@@ -9175,7 +9175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 54,
    "id": "35823982",
    "metadata": {},
    "outputs": [
@@ -9743,9 +9743,9 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:32:44+00:00\n",
-       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-4b7617aa-3c8c-40e7-9c4a-369fa002dd31' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-4b7617aa-3c8c-40e7-9c4a-369fa002dd31' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-bfcfcaa7-a11c-4f38-b591-4373a92013a6' class='xr-section-summary-in' type='checkbox' checked /><label for='section-bfcfcaa7-a11c-4f38-b591-4373a92013a6' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-8c8e44ca-1796-48c9-ae32-33739007040f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8c8e44ca-1796-48c9-ae32-33739007040f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1712598-76c8-41c8-aeb4-5a82959ef54c' class='xr-var-data-in' type='checkbox'><label for='data-c1712598-76c8-41c8-aeb4-5a82959ef54c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-8f29476a-92d5-49c5-9efb-c7bcad8e9897' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f29476a-92d5-49c5-9efb-c7bcad8e9897' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3abd539f-d3f7-4532-9b30-b91672b62307' class='xr-var-data-in' type='checkbox'><label for='data-3abd539f-d3f7-4532-9b30-b91672b62307' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-8d2e3a9f-e18f-4059-bf3d-b9850dafdb6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8d2e3a9f-e18f-4059-bf3d-b9850dafdb6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65fd6ad2-f9aa-4e73-9910-d15a9067d0f7' class='xr-var-data-in' type='checkbox'><label for='data-65fd6ad2-f9aa-4e73-9910-d15a9067d0f7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
-       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-16a6ac73-9d7a-4ee8-a16c-171476165066' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16a6ac73-9d7a-4ee8-a16c-171476165066' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edb540ff-6bd0-4b69-9aab-ca05fc19adcb' class='xr-var-data-in' type='checkbox'><label for='data-edb540ff-6bd0-4b69-9aab-ca05fc19adcb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-976c3fd4-d598-48ac-a9b5-49894c1bf125' class='xr-section-summary-in' type='checkbox' checked /><label for='section-976c3fd4-d598-48ac-a9b5-49894c1bf125' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-ea6931cb-ff67-471b-b470-347974ddd7d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea6931cb-ff67-471b-b470-347974ddd7d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88772d63-506d-4f4e-abf6-52f1be70e35b' class='xr-var-data-in' type='checkbox'><label for='data-88772d63-506d-4f4e-abf6-52f1be70e35b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "    processing_time:              2026-06-20T23:52:26+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-dd79968f-8bbb-4e74-8bb7-2b9b42756b8f' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-dd79968f-8bbb-4e74-8bb7-2b9b42756b8f' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-ba680cf9-1edb-4210-ae54-ac34df44f261' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ba680cf9-1edb-4210-ae54-ac34df44f261' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-961261f9-96e0-49e3-a181-7296d4504fd6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-961261f9-96e0-49e3-a181-7296d4504fd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d645b29b-2872-48be-adb0-73dcd6c0392c' class='xr-var-data-in' type='checkbox'><label for='data-d645b29b-2872-48be-adb0-73dcd6c0392c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-cc5e9509-dc84-4b5b-8c09-b336b8a1642e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cc5e9509-dc84-4b5b-8c09-b336b8a1642e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-621f8e16-6ed3-40b1-9b13-a860bbc7eaf2' class='xr-var-data-in' type='checkbox'><label for='data-621f8e16-6ed3-40b1-9b13-a860bbc7eaf2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-812676b4-e8d6-4a87-bc8d-8cd1af80af2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-812676b4-e8d6-4a87-bc8d-8cd1af80af2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9084fd0-01c4-4241-836b-f6ffb32212d4' class='xr-var-data-in' type='checkbox'><label for='data-e9084fd0-01c4-4241-836b-f6ffb32212d4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-10fc4f7d-1658-4292-953f-13cf44b1232a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10fc4f7d-1658-4292-953f-13cf44b1232a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b244e3e7-fa92-4218-8205-20365d993cc0' class='xr-var-data-in' type='checkbox'><label for='data-b244e3e7-fa92-4218-8205-20365d993cc0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f57ce944-c4db-4a6b-a7ac-e1e8dd9b87dd' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f57ce944-c4db-4a6b-a7ac-e1e8dd9b87dd' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-417fe632-dac3-40aa-8b80-1568e02e612d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-417fe632-dac3-40aa-8b80-1568e02e612d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1fcfc22-ec20-417b-9417-081c9eea1cb1' class='xr-var-data-in' type='checkbox'><label for='data-a1fcfc22-ec20-417b-9417-081c9eea1cb1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
        "         -50.89344838, -51.56443826],\n",
        "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
        "         -53.05996696, -53.87369709],\n",
@@ -9757,15 +9757,15 @@
        "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
        "         -41.36476302, -41.37227431],\n",
        "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
-       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-0d9ece50-38f3-4ceb-9b1a-0cd8019f2bb2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0d9ece50-38f3-4ceb-9b1a-0cd8019f2bb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab9b5104-1406-4dbe-af52-3695a5d2a273' class='xr-var-data-in' type='checkbox'><label for='data-ab9b5104-1406-4dbe-af52-3695a5d2a273' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-998266aa-c355-4800-9433-2fed87160d86' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-998266aa-c355-4800-9433-2fed87160d86' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d434e36-ef2b-4b3f-bb0e-ad80e53a4b69' class='xr-var-data-in' type='checkbox'><label for='data-6d434e36-ef2b-4b3f-bb0e-ad80e53a4b69' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
-       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-3e12bfbd-dfc3-40ce-9916-38def277e131' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e12bfbd-dfc3-40ce-9916-38def277e131' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50366880-56ec-4cda-9fd6-838e1bbbc2da' class='xr-var-data-in' type='checkbox'><label for='data-50366880-56ec-4cda-9fd6-838e1bbbc2da' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
-       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-5b5e2ab7-1a9e-4c5c-8ec6-93eeb7342147' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b5e2ab7-1a9e-4c5c-8ec6-93eeb7342147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eb56b03a-42ad-4092-bcaa-87410fb200f5' class='xr-var-data-in' type='checkbox'><label for='data-eb56b03a-42ad-4092-bcaa-87410fb200f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-d394a264-cf9c-4ce7-a5f2-14eebb34c532' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d394a264-cf9c-4ce7-a5f2-14eebb34c532' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd15a4a7-2419-4176-815f-9d2f13048eca' class='xr-var-data-in' type='checkbox'><label for='data-dd15a4a7-2419-4176-815f-9d2f13048eca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-0a2a487f-3588-406e-b424-d46c938c52e0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0a2a487f-3588-406e-b424-d46c938c52e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd3d7376-1245-4c6b-a82f-8660abfe893c' class='xr-var-data-in' type='checkbox'><label for='data-fd3d7376-1245-4c6b-a82f-8660abfe893c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-08a7060d-a6c9-48e8-86b2-94466a19d66a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-08a7060d-a6c9-48e8-86b2-94466a19d66a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1c54769-1b8e-4815-984a-dbbd918771b9' class='xr-var-data-in' type='checkbox'><label for='data-d1c54769-1b8e-4815-984a-dbbd918771b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-632d4963-6d01-4a2b-a350-c0cda111fee1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-632d4963-6d01-4a2b-a350-c0cda111fee1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7a8914d-04be-4958-acdc-64fc1a591c9a' class='xr-var-data-in' type='checkbox'><label for='data-d7a8914d-04be-4958-acdc-64fc1a591c9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
-       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-bc9db149-38fa-43cb-875f-2de9ad84e1c5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc9db149-38fa-43cb-875f-2de9ad84e1c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-074b1161-3845-448d-bcea-6ad2f211a995' class='xr-var-data-in' type='checkbox'><label for='data-074b1161-3845-448d-bcea-6ad2f211a995' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-7232b93a-4fc8-460b-9393-58464f04c15c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7232b93a-4fc8-460b-9393-58464f04c15c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3807545-7afd-4855-a0e1-8d7e1029e9fb' class='xr-var-data-in' type='checkbox'><label for='data-e3807545-7afd-4855-a0e1-8d7e1029e9fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c4c1a8e8-dccf-464a-9589-ab8f6bc480f9' class='xr-section-summary-in' type='checkbox' checked /><label for='section-c4c1a8e8-dccf-464a-9589-ab8f6bc480f9' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:32:44+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-dc4ff287-9847-4cc6-834b-01222c210f7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dc4ff287-9847-4cc6-834b-01222c210f7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b20bdf-fdc6-4b3b-a274-9366b5484af2' class='xr-var-data-in' type='checkbox'><label for='data-54b20bdf-fdc6-4b3b-a274-9366b5484af2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-9ffe2e1b-b895-4bb6-98c9-3d686ae4ecfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ffe2e1b-b895-4bb6-98c9-3d686ae4ecfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fdd2f254-cda6-4919-8e07-15d5549c3aef' class='xr-var-data-in' type='checkbox'><label for='data-fdd2f254-cda6-4919-8e07-15d5549c3aef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3fe3d567-985a-48f2-89bb-bc542f91152e' class='xr-section-summary-in' type='checkbox' checked /><label for='section-3fe3d567-985a-48f2-89bb-bc542f91152e' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-20T23:52:26+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 10MB\n",
@@ -9787,11 +9787,11 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:32:44+00:00\n",
+       "    processing_time:              2026-06-20T23:52:26+00:00\n",
        "    processing_function:          calibrate.compute_TS_spectrum"
       ]
      },
-     "execution_count": 52,
+     "execution_count": 54,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -9818,7 +9818,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 55,
    "id": "56d8ea09",
    "metadata": {},
    "outputs": [
@@ -9857,7 +9857,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 56,
    "id": "c980db68",
    "metadata": {},
    "outputs": [],
@@ -9882,7 +9882,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 55,
+   "execution_count": 57,
    "id": "c96bb8ce",
    "metadata": {},
    "outputs": [
@@ -10450,9 +10450,9 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:35:32+00:00\n",
-       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d42c7f64-c3a5-47f4-baf6-c26f1f2bf0d3' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-d42c7f64-c3a5-47f4-baf6-c26f1f2bf0d3' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-a57763c8-9b55-4a2a-9e15-9c15c6baa481' class='xr-section-summary-in' type='checkbox' checked /><label for='section-a57763c8-9b55-4a2a-9e15-9c15c6baa481' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-617ea556-592d-44c2-8676-84165dfd7e8b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-617ea556-592d-44c2-8676-84165dfd7e8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-90f28064-8cd0-425c-b17e-6a205ff0eef7' class='xr-var-data-in' type='checkbox'><label for='data-90f28064-8cd0-425c-b17e-6a205ff0eef7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-483e2f35-e0b7-41cd-b210-fff7cb5b731e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-483e2f35-e0b7-41cd-b210-fff7cb5b731e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1d066a9-1bc2-4627-ba96-5600678e3fa1' class='xr-var-data-in' type='checkbox'><label for='data-c1d066a9-1bc2-4627-ba96-5600678e3fa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-4a655da4-19b8-4acb-8440-31db7b7931a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a655da4-19b8-4acb-8440-31db7b7931a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce9e1ef7-821b-4bd5-af7f-de64d4a205e7' class='xr-var-data-in' type='checkbox'><label for='data-ce9e1ef7-821b-4bd5-af7f-de64d4a205e7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
-       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-a5ace771-b9cf-4867-ab13-e253c82ba143' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a5ace771-b9cf-4867-ab13-e253c82ba143' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a009e095-3aa5-4437-aca8-2bf1439cf513' class='xr-var-data-in' type='checkbox'><label for='data-a009e095-3aa5-4437-aca8-2bf1439cf513' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f5d01d24-ec31-4c60-9e0d-c70cbbee3213' class='xr-section-summary-in' type='checkbox' checked /><label for='section-f5d01d24-ec31-4c60-9e0d-c70cbbee3213' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-8aa1c98b-c790-4d3d-8afd-82c033a417db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8aa1c98b-c790-4d3d-8afd-82c033a417db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7cf45bf3-06f6-48b0-adf8-dfb6c0ad0a84' class='xr-var-data-in' type='checkbox'><label for='data-7cf45bf3-06f6-48b0-adf8-dfb6c0ad0a84' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
+       "    processing_time:              2026-06-20T23:53:34+00:00\n",
+       "    processing_function:          calibrate.compute_TS_spectrum</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8b676f12-badd-418e-9f85-fde7a7055028' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-8b676f12-badd-418e-9f85-fde7a7055028' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>channel</span>: 1</li><li><span class='xr-has-index'>target_id</span>: 1265</li><li><span class='xr-has-index'>frequency</span>: 1000</li><li><span class='xr-has-index'>filenames</span>: 1</li></ul></div></li><li class='xr-section-item'><input id='section-94e9b10b-c7f4-40cf-b641-1f7a13524a48' class='xr-section-summary-in' type='checkbox' checked /><label for='section-94e9b10b-c7f4-40cf-b641-1f7a13524a48' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>channel</span></div><div class='xr-var-dims'>(channel)</div><div class='xr-var-dtype'>&lt;U26</div><div class='xr-var-preview xr-preview'>&#x27;WBT 747022-15 ES120-7CD_ES&#x27;</div><input id='attrs-db435058-5ace-4593-a3de-48ed02b12db2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db435058-5ace-4593-a3de-48ed02b12db2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0d2e671-2e81-4d89-b13e-b371af6a3fe6' class='xr-var-data-in' type='checkbox'><label for='data-d0d2e671-2e81-4d89-b13e-b371af6a3fe6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;WBT 747022-15 ES120-7CD_ES&#x27;], dtype=&#x27;&lt;U26&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>target_id</span></div><div class='xr-var-dims'>(target_id)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 ... 1261 1262 1263 1264</div><input id='attrs-4f2d2f5a-8a18-4245-ac65-b5ce15cee776' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4f2d2f5a-8a18-4245-ac65-b5ce15cee776' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd0be67c-91b0-4406-be52-72a0f75c259e' class='xr-var-data-in' type='checkbox'><label for='data-dd0be67c-91b0-4406-be52-72a0f75c259e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([   0,    1,    2, ..., 1262, 1263, 1264], shape=(1265,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>frequency</span></div><div class='xr-var-dims'>(frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>9e+04 9.008e+04 ... 1.7e+05</div><input id='attrs-e5062014-33f0-4915-a3e3-d45efcb6eacd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5062014-33f0-4915-a3e3-d45efcb6eacd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6325937-fb12-4214-b716-9ae452c59345' class='xr-var-data-in' type='checkbox'><label for='data-f6325937-fb12-4214-b716-9ae452c59345' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency</dd><dt><span>units :</span></dt><dd>Hz</dd></dl></div><div class='xr-var-data'><pre>array([ 90000.     ,  90080.08008,  90160.16016, ..., 169839.83984,\n",
+       "       169919.91992, 170000.     ], shape=(1000,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-68efbf66-6ee5-4008-99d9-0de35779e350' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68efbf66-6ee5-4008-99d9-0de35779e350' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3de99d0-5c04-4184-8f73-56190b6b80c9' class='xr-var-data-in' type='checkbox'><label for='data-a3de99d0-5c04-4184-8f73-56190b6b80c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Index for data and metadata source filenames</dd></dl></div><div class='xr-var-data'><pre>array([0])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-46277bd3-a33a-4ba6-aa9e-bbe08db8834f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-46277bd3-a33a-4ba6-aa9e-bbe08db8834f' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>TS_spectrum</span></div><div class='xr-var-dims'>(channel, target_id, frequency)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-44.54 -44.51 ... -41.55 -41.53</div><input id='attrs-1353a555-a586-4b9c-be6d-3620152005f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1353a555-a586-4b9c-be6d-3620152005f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c939ab9-ee9e-4e39-8f7f-4622b3566023' class='xr-var-data-in' type='checkbox'><label for='data-4c939ab9-ee9e-4e39-8f7f-4622b3566023' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Frequency-dependent target strength spectrum (TS(f) re 1 m^2)</dd><dt><span>units :</span></dt><dd>dB</dd><dt><span>waveform_mode :</span></dt><dd>BB</dd><dt><span>encode_mode :</span></dt><dd>complex</dd></dl></div><div class='xr-var-data'><pre>array([[[-44.54238287, -44.51222504, -44.67212217, ..., -50.98526821,\n",
        "         -50.89344838, -51.56443826],\n",
        "        [-44.77269773, -44.76391201, -44.79523357, ..., -53.15417453,\n",
        "         -53.05996696, -53.87369709],\n",
@@ -10464,15 +10464,15 @@
        "        [-44.80446127, -44.87624942, -44.96809241, ..., -41.51594295,\n",
        "         -41.36476302, -41.37227431],\n",
        "        [-44.96236474, -45.03630205, -45.11222419, ..., -41.70476154,\n",
-       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-05dbb1dc-c053-4ddb-b6a5-c6322f6c2b4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-05dbb1dc-c053-4ddb-b6a5-c6322f6c2b4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2435ba6a-6cbb-4126-9d5f-d9c0930e38fd' class='xr-var-data-in' type='checkbox'><label for='data-2435ba6a-6cbb-4126-9d5f-d9c0930e38fd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
-       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-9a3bcf42-b605-40df-8bd8-eac50f54f1bd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a3bcf42-b605-40df-8bd8-eac50f54f1bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2cc5d31f-ea66-42bb-aa50-ebe25b088fdc' class='xr-var-data-in' type='checkbox'><label for='data-2cc5d31f-ea66-42bb-aa50-ebe25b088fdc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
-       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-7a4afd91-5957-4906-9cb1-598a9bc641da' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7a4afd91-5957-4906-9cb1-598a9bc641da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a91be634-31af-45f7-a91a-2ac7a10ba45e' class='xr-var-data-in' type='checkbox'><label for='data-a91be634-31af-45f7-a91a-2ac7a10ba45e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
-       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-718e12a6-be37-402f-9cfb-195324fed9ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-718e12a6-be37-402f-9cfb-195324fed9ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-686277da-7bb8-414c-b778-87917358375d' class='xr-var-data-in' type='checkbox'><label for='data-686277da-7bb8-414c-b778-87917358375d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
+       "         -41.55277491, -41.53386956]]], shape=(1, 1265, 1000))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>target_range</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.805 5.805 5.805 ... 5.781 5.781</div><input id='attrs-bfdb3c62-483c-4e49-8f67-b66ac9465631' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bfdb3c62-483c-4e49-8f67-b66ac9465631' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df7edc0e-b0b5-4757-81b3-c342dd5a6240' class='xr-var-data-in' type='checkbox'><label for='data-df7edc0e-b0b5-4757-81b3-c342dd5a6240' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[5.8049432, 5.8049432, 5.8049432, ..., 5.7811768, 5.7811768,\n",
+       "        5.7811768]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_alongship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.852 2.139 ... -0.00917 0.153</div><input id='attrs-185176d0-9b5c-4ffe-ae82-dececc5b2fd2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-185176d0-9b5c-4ffe-ae82-dececc5b2fd2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53c45bca-5b98-4e30-b273-668c4a3a26cb' class='xr-var-data-in' type='checkbox'><label for='data-53c45bca-5b98-4e30-b273-668c4a3a26cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 1.85155244,  2.13900475,  2.43819163, ..., -0.20675028,\n",
+       "        -0.00917041,  0.15295288]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angle_athwartship</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.524 4.304 ... -0.02378 -0.1533</div><input id='attrs-118d9f43-6242-43f9-9f35-b4b8bd0213c3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-118d9f43-6242-43f9-9f35-b4b8bd0213c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-efb382c1-0cfb-4669-8e83-d0fb0f32add6' class='xr-var-data-in' type='checkbox'><label for='data-efb382c1-0cfb-4669-8e83-d0fb0f32add6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 4.52383117,  4.3039932 ,  4.01408127, ...,  0.07863162,\n",
+       "        -0.02377829, -0.15330624]], shape=(1, 1265))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ping_time</span></div><div class='xr-var-dims'>(channel, target_id)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2021-12-15T14:34:32.661453 ... 2...</div><input id='attrs-849e425d-293e-4dd4-b24c-a28c48fd3936' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-849e425d-293e-4dd4-b24c-a28c48fd3936' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11ad9882-3253-4e79-b69b-2541f016d987' class='xr-var-data-in' type='checkbox'><label for='data-11ad9882-3253-4e79-b69b-2541f016d987' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[&#x27;2021-12-15T14:34:32.661453000&#x27;, &#x27;2021-12-15T14:34:32.911352000&#x27;,\n",
        "        &#x27;2021-12-15T14:34:33.161251000&#x27;, ...,\n",
        "        &#x27;2021-12-15T14:40:08.662388000&#x27;, &#x27;2021-12-15T14:40:08.912287000&#x27;,\n",
        "        &#x27;2021-12-15T14:40:09.162188000&#x27;]],\n",
-       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-33c389f7-8681-4c37-b237-5861e9b0a44d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33c389f7-8681-4c37-b237-5861e9b0a44d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebd9b8aa-5efc-4f19-bab0-caaea0890ab1' class='xr-var-data-in' type='checkbox'><label for='data-ebd9b8aa-5efc-4f19-bab0-caaea0890ab1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
-       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-29e56c80-c8b1-479b-9c23-38730ea20713' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29e56c80-c8b1-479b-9c23-38730ea20713' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0799c5ca-d2e9-4dc3-9bd4-42123de790c0' class='xr-var-data-in' type='checkbox'><label for='data-0799c5ca-d2e9-4dc3-9bd4-42123de790c0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2e9cb365-b2f7-405f-9467-43f5980f839a' class='xr-section-summary-in' type='checkbox' checked /><label for='section-2e9cb365-b2f7-405f-9467-43f5980f839a' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-19T22:35:32+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
+       "      shape=(1, 1265), dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>source_filenames</span></div><div class='xr-var-dims'>(filenames)</div><div class='xr-var-dtype'>&lt;U67</div><div class='xr-var-preview xr-preview'>&#x27;example_data\\\\ts_spectrum_examp...</div><input id='attrs-4ebb5c81-5e37-4b29-8e6c-cf54efe1a8ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ebb5c81-5e37-4b29-8e6c-cf54efe1a8ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-173f8d07-8223-4d57-b9c7-2739609540df' class='xr-var-data-in' type='checkbox'><label for='data-173f8d07-8223-4d57-b9c7-2739609540df' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Source filenames</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;example_data\\\\ts_spectrum_example_data\\\\IMR-D20211215-T143432-TSf.raw&#x27;],\n",
+       "      dtype=&#x27;&lt;U67&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-0a4acd86-944a-4dd4-aab8-356b68101bfe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a4acd86-944a-4dd4-aab8-356b68101bfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ed90672a-5ab4-46a6-a2ac-1595b31d48a6' class='xr-var-data-in' type='checkbox'><label for='data-ed90672a-5ab4-46a6-a2ac-1595b31d48a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Distance from the platform coordinate system origin to the nominal water level along the z-axis</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e929a911-d8dc-4863-b20a-c94e39f82930' class='xr-section-summary-in' type='checkbox' checked /><label for='section-e929a911-d8dc-4863-b20a-c94e39f82930' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>processing_software_name :</span></dt><dd>echopype</dd><dt><span>processing_software_version :</span></dt><dd>0.11.2.dev57+g1f9b67a33</dd><dt><span>processing_time :</span></dt><dd>2026-06-20T23:53:34+00:00</dd><dt><span>processing_function :</span></dt><dd>calibrate.compute_TS_spectrum</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
        "<xarray.Dataset> Size: 10MB\n",
@@ -10494,11 +10494,11 @@
        "Attributes:\n",
        "    processing_software_name:     echopype\n",
        "    processing_software_version:  0.11.2.dev57+g1f9b67a33\n",
-       "    processing_time:              2026-06-19T22:35:32+00:00\n",
+       "    processing_time:              2026-06-20T23:53:34+00:00\n",
        "    processing_function:          calibrate.compute_TS_spectrum"
       ]
      },
-     "execution_count": 55,
+     "execution_count": 57,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10531,7 +10531,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 56,
+   "execution_count": 58,
    "id": "19c69452",
    "metadata": {},
    "outputs": [
@@ -10589,7 +10589,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 57,
+   "execution_count": 59,
    "id": "5016286d",
    "metadata": {},
    "outputs": [
@@ -10713,7 +10713,7 @@
        "5     0.000000  0.000000      0.000000  "
       ]
      },
-     "execution_count": 57,
+     "execution_count": 59,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -10772,7 +10772,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 58,
+   "execution_count": 60,
    "id": "a8ee9fe9",
    "metadata": {},
    "outputs": [
@@ -11044,7 +11044,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 61,
    "id": "7d490e20",
    "metadata": {},
    "outputs": [
@@ -11052,7 +11052,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Notebook generated: 2026-06-19 15:35:35.320966\n",
+      "Notebook generated: 2026-06-20 16:53:35.993376\n",
       "Python: 3.12.13\n",
       "echopype: 0.11.2.dev57+g1f9b67a33\n",
       "numpy: 2.4.4\n",
diff --git a/notebooks/utils/data.py b/notebooks/utils/data.py
index 0f3e30a..7345341 100644
--- a/notebooks/utils/data.py
+++ b/notebooks/utils/data.py
@@ -18,6 +18,7 @@
     },
 }
 
+
 def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
     """Download and extract an example dataset if it is not available locally."""
     if name not in DATASETS:
@@ -38,9 +39,11 @@ def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
         registry={dataset["asset"]: f"sha256:{expected_sha256}"},
     )
 
-    # This verifies the cached zip hash.
-    # If the local zip is missing/stale/corrupted, Pooch redownloads it.
-    zip_path = Path(fetcher.fetch(dataset["asset"]))
+    print(f"Verifying dataset archive: {dataset['asset']}")
+
+    # Verify the cached zip archive. If it is missing or its checksum does
+    # not match the expected SHA256, Pooch automatically downloads a fresh copy.
+    zip_path = Path(fetcher.fetch(dataset["asset"], progressbar=True))
 
     local_extract_valid = (
         all(file.exists() for file in expected_files)
@@ -49,7 +52,6 @@ def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
     )
 
     if local_extract_valid:
-        print(f"Using local dataset: {dataset_dir}")
         return dataset_dir
 
     print(f"Extracting dataset: {name}")
@@ -69,4 +71,6 @@ def fetch_dataset(name: str, data_dir: Path = EXAMPLE_DATA_DIR) -> Path:
 
     marker_file.write_text(expected_sha256 + "\n")
 
+    print("Dataset ready.")
+
     return dataset_dir
\ No newline at end of file