From eb5d591bc72a5ed89d8d1ea04187facc89d0bbf5 Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Mon, 24 Jun 2024 15:07:38 -0700
Subject: [PATCH 1/7] Allow NOAA requests function to access most variables

---
 mhkit/tidal/io/noaa.py | 39 +++++++++++++++++++++++++++------------
 1 file changed, 27 insertions(+), 12 deletions(-)

diff --git a/mhkit/tidal/io/noaa.py b/mhkit/tidal/io/noaa.py
index 2ea2ad708..5df7c854c 100644
--- a/mhkit/tidal/io/noaa.py
+++ b/mhkit/tidal/io/noaa.py
@@ -4,14 +4,14 @@
 This module provides functions to fetch, process, and read NOAA (National
 Oceanic and Atmospheric Administration) current data directly from the
 NOAA Tides and Currents API (https://api.tidesandcurrents.noaa.gov/api/prod/). It
-supports loading data into a pandas DataFrame, handling data in XML and 
+supports loading data into a pandas DataFrame, handling data in XML and
 JSON formats, and writing data to a JSON file.
 
 Functions:
 ----------
-request_noaa_data(station, parameter, start_date, end_date, proxy=None, 
+request_noaa_data(station, parameter, start_date, end_date, proxy=None,
   write_json=None):
-    Loads NOAA current data from the API into a pandas DataFrame, 
+    Loads NOAA current data from the API into a pandas DataFrame,
     with optional support for proxy settings and writing data to a JSON
     file.
 
@@ -56,9 +56,11 @@ def request_noaa_data(
     Parameters
     ----------
     station : str
-        NOAA current station number (e.g. 'cp0101')
+        NOAA current station number (e.g. 'cp0101', "s08010", "9446484")
     parameter : str
-        NOAA paramter (e.g. '' for Discharge, cubic feet per second)
+        NOAA paramter (e.g. "currents", "salinity", "water_level", "water_temperature",
+        "air_temperature", "wind", "air_pressure")
+        https://api.tidesandcurrents.noaa.gov/api/prod/
     start_date : str
         Start date in the format yyyyMMdd
     end_date : str
@@ -158,6 +160,9 @@ def request_noaa_data(
             end_date = date_list[i + 1].strftime("%Y%m%d")
 
             api_query = f"begin_date={start_date}&end_date={end_date}&station={station}&product={parameter}&units=metric&time_zone=gmt&application=web_services&format=xml"
+            # Add datum to water level inquiries
+            if parameter == "water_level":
+                api_query += "&datum=MLLW"
             data_url = f"https://tidesandcurrents.noaa.gov/api/datagetter?{api_query}"
 
             print("Data request URL: ", data_url)
@@ -166,18 +171,23 @@ def request_noaa_data(
             try:
                 response = requests.get(url=data_url, proxies=proxy)
                 response.raise_for_status()
-            except requests.exceptions.HTTPError as err:
-                print(f"HTTP error occurred: {err}")
-                continue
-            except requests.exceptions.RequestException as err:
-                print(f"Error occurred: {err}")
+                # Catch non-exception errors
+                if "error" in response.content.decode():
+                    raise Exception(response.content)
+            except Exception as err:
+                print(f"Requests error occurred: {err}")
+                print(f"Error content: {response.content}")
                 continue
+
             # Convert to DataFrame and save in data_frames list
             df, metadata = _xml_to_dataframe(response)
             data_frames.append(df)
 
         # Concatenate all DataFrames
-        data = pd.concat(data_frames, ignore_index=False)
+        if data_frames:
+            data = pd.concat(data_frames, ignore_index=False)
+        else:
+            raise ValueError("No data retrieved.")
 
         # Remove duplicated date values
         data = data.loc[~data.index.duplicated()]
@@ -236,7 +246,12 @@ def _xml_to_dataframe(response):
     df.drop_duplicates(inplace=True)
 
     # Convert data to float
-    df[["d", "s"]] = df[["d", "s"]].apply(pd.to_numeric)
+    cols = list(df.columns)
+    for var in cols:
+        try:
+            df[var] = df[var].apply(pd.to_numeric)
+        except ValueError:
+            pass
 
     return df, metadata
 

From 3e5b6df50a875dd0be227ae5dc416cf905cd8b6e Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Mon, 24 Jun 2024 15:21:44 -0700
Subject: [PATCH 2/7] Use better error handling

---
 mhkit/tidal/io/noaa.py | 18 +++++++++++++-----
 1 file changed, 13 insertions(+), 5 deletions(-)

diff --git a/mhkit/tidal/io/noaa.py b/mhkit/tidal/io/noaa.py
index 5df7c854c..0f9b118e7 100644
--- a/mhkit/tidal/io/noaa.py
+++ b/mhkit/tidal/io/noaa.py
@@ -165,7 +165,7 @@ def request_noaa_data(
                 api_query += "&datum=MLLW"
             data_url = f"https://tidesandcurrents.noaa.gov/api/datagetter?{api_query}"
 
-            print("Data request URL: ", data_url)
+            print(f"Data request URL: {data_url}\n")
 
             # Get response
             try:
@@ -173,11 +173,19 @@ def request_noaa_data(
                 response.raise_for_status()
                 # Catch non-exception errors
                 if "error" in response.content.decode():
-                    raise Exception(response.content)
+                    raise Exception(response.content.decode())
             except Exception as err:
-                print(f"Requests error occurred: {err}")
-                print(f"Error content: {response.content}")
-                continue
+                if err.__class__ == requests.exceptions.HTTPError:
+                    print(f"HTTP error occurred: {err}")
+                    print(f"Error message: {response.content.decode()}\n")
+                    continue
+                elif err.__class__ == requests.exceptions.RequestException:
+                    print(f"Requests error occurred: {err}")
+                    print(f"Error message: {response.content.decode()}\n")
+                    continue
+                else:
+                    print(f"Requests error occurred: {err}\n")
+                    continue
 
             # Convert to DataFrame and save in data_frames list
             df, metadata = _xml_to_dataframe(response)

From da22c8e4029d7508b127be4d485128e5b92cbd82 Mon Sep 17 00:00:00 2001
From: James McVey <53623232+jmcvey3@users.noreply.github.com>
Date: Wed, 3 Jul 2024 08:58:17 -0700
Subject: [PATCH 3/7] Improve Reynolds stress ADCP estimation notebook
 discussion V2 (#326)

* tke updates

* Fix shear velocity functions

* More detail for tke shear production

* Don't rotate heading beyond 360 degrees

* Fix some typos in notebook

* Rename deprecated function
---
 examples/adcp_example.ipynb                   | 1100 +++++++++--------
 examples/adv_example.ipynb                    |  178 +--
 .../dolfyn/test_data/Sig1000_tidal_bin.nc     |  Bin 113113 -> 108367 bytes
 examples/data/dolfyn/test_data/dat_vm.mat     |  Bin 115776 -> 115776 bytes
 examples/data/dolfyn/test_data/vmdas01_wh.nc  |  Bin 145070 -> 145039 bytes
 mhkit/dolfyn/adp/turbulence.py                |  103 +-
 mhkit/dolfyn/adv/motion.py                    |    4 +-
 mhkit/dolfyn/adv/turbulence.py                |   20 +-
 mhkit/dolfyn/rotate/api.py                    |    5 +-
 mhkit/tests/dolfyn/test_analysis.py           |   31 +-
 10 files changed, 750 insertions(+), 691 deletions(-)

diff --git a/examples/adcp_example.ipynb b/examples/adcp_example.ipynb
index 6c1cbdfff..c515461f3 100644
--- a/examples/adcp_example.ipynb
+++ b/examples/adcp_example.ipynb
@@ -34,7 +34,7 @@
     "    3. Instrument Noise\n",
     "    4. TKE Dissipation Rate\n",
     "    5. Noise-corrected TI\n",
-    "    6. TKE Componenets\n",
+    "    6. Reynolds stresses\n",
     "    7. TKE Production\n",
     "    8. TKE Balance \n",
     "\n",
@@ -48,16 +48,7 @@
    "metadata": {
     "scrolled": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\mcve343\\anaconda3\\envs\\tsdat-pipelines\\lib\\site-packages\\xarray\\backends\\cfgrib_.py:29: UserWarning: Failed to load cfgrib - most likely there is a problem accessing the ecCodes library. Try `import cfgrib` to get the full error message\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from mhkit import dolfyn\n",
     "from mhkit.dolfyn.adp import api"
@@ -376,6 +367,11 @@
        "  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",
@@ -397,14 +393,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  display: none;\n",
        "  background-color: var(--xr-background-color) !important;\n",
        "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -414,13 +412,16 @@
        "\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-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -458,7 +459,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -467,37 +469,37 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:              (time: 55000, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-       "                          earth: 3, inst: 3, q: 4, time_b5: 55000,\n",
-       "                          range_b5: 28, x1: 4, x2: 4)\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 83MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
        "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 2020-08-15T00:20:00.500999927 ...\n",
-       "  * dirIMU               (dirIMU) &lt;U1 &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * dir                  (dir) &lt;U2 &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
-       "  * range                (range) float64 0.6 1.1 1.6 2.1 ... 12.6 13.1 13.6 14.1\n",
-       "  * beam                 (beam) int32 1 2 3 4\n",
-       "  * earth                (earth) &lt;U1 &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst                 (inst) &lt;U1 &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * q                    (q) &lt;U1 &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-       "  * time_b5              (time_b5) datetime64[ns] 2020-08-15T00:20:00.4384999...\n",
-       "  * range_b5             (range_b5) float64 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-       "  * x1                   (x1) int32 1 2 3 4\n",
-       "  * x2                   (x2) int32 1 2 3 4\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) &lt;U2 32B &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
+       "  * dirIMU               (dirIMU) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * q                    (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
        "Data variables: (12/38)\n",
-       "    c_sound              (time) float32 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 14.55 14.55 14.55 ... 13.47 13.47 13.47\n",
-       "    pressure             (time) float32 9.713 9.718 9.718 ... 9.596 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 72.5 72.7 72.6 ... -197.2 -195.7\n",
-       "    accel                (dirIMU, time) float32 -0.00479 -0.01437 ... 9.729\n",
-       "    batt                 (time) float32 16.6 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
        "    ...                   ...\n",
-       "    telemetry_data       (time) uint8 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
-       "    boost_running        (time) uint8 0 0 0 0 0 0 0 0 1 0 ... 0 1 0 0 0 0 0 0 1\n",
-       "    heading              (time) float32 -12.52 -12.51 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 -0.065 -0.06 -0.06 ... -0.06 -0.05 -0.05\n",
-       "    roll                 (time) float32 -7.425 -7.42 -7.42 ... -6.45 -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 1.183 0.0 -1.183 ... 0.5518 0.0 0.5518\n",
+       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
        "Attributes: (12/34)\n",
        "    filehead_config:       {&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, ...\n",
        "    inst_model:            Signature1000\n",
@@ -511,26 +513,26 @@
        "    coord_sys:             earth\n",
        "    fs:                    1\n",
        "    has_imu:               1\n",
-       "    beam_angle:            25</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-32696568-6d41-402b-a612-0b7216025509' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-32696568-6d41-402b-a612-0b7216025509' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-7ef5388a-8163-465d-a4fc-6750aa6416f3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7ef5388a-8163-465d-a4fc-6750aa6416f3' class='xr-section-summary' >Coordinates: <span>(12)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-06ba5ddd-81e5-474d-9636-d0a35d73f2c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06ba5ddd-81e5-474d-9636-d0a35d73f2c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-541da3ac-3e7b-473d-ae3b-a884ce605504' class='xr-var-data-in' type='checkbox'><label for='data-541da3ac-3e7b-473d-ae3b-a884ce605504' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
+       "    beam_angle:            25</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-dd1aa3f6-26e0-4f41-9708-b096448b9c50' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-dd1aa3f6-26e0-4f41-9708-b096448b9c50' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 55000</li><li><span class='xr-has-index'>time_b5</span>: 55000</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>range_b5</span>: 28</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>x1</span>: 4</li><li><span class='xr-has-index'>x2</span>: 4</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1ac66d2a-c01b-4495-b4ac-20d6e05e00b5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1ac66d2a-c01b-4495-b4ac-20d6e05e00b5' class='xr-section-summary' >Coordinates: <span>(12)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.500999927 .....</div><input id='attrs-e2ce41ff-3698-4739-904f-30cd6596a891' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2ce41ff-3698-4739-904f-30cd6596a891' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fa2bf6d-00fd-474c-8b60-73a35231d68f' class='xr-var-data-in' type='checkbox'><label for='data-8fa2bf6d-00fd-474c-8b60-73a35231d68f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.500999927&#x27;, &#x27;2020-08-15T00:20:01.501100063&#x27;,\n",
        "       &#x27;2020-08-15T00:20:02.500999927&#x27;, ..., &#x27;2020-08-15T15:36:37.500999927&#x27;,\n",
        "       &#x27;2020-08-15T15:36:38.500999927&#x27;, &#x27;2020-08-15T15:36:39.500999927&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-29ef1ab4-9001-4dcd-8460-dc3a1e0f243e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29ef1ab4-9001-4dcd-8460-dc3a1e0f243e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d1c7073-4b7e-441e-bb03-462d79aff00b' class='xr-var-data-in' type='checkbox'><label for='data-4d1c7073-4b7e-441e-bb03-462d79aff00b' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-841251a7-34da-4b1a-976f-38684ec3d503' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-841251a7-34da-4b1a-976f-38684ec3d503' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f161a0aa-f99e-4aa4-97bc-59169bbe95f5' class='xr-var-data-in' type='checkbox'><label for='data-f161a0aa-f99e-4aa4-97bc-59169bbe95f5' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-69b6ad0a-b32c-496e-a4dd-e7dd7ae61288' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69b6ad0a-b32c-496e-a4dd-e7dd7ae61288' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6ba9520-ff9f-4719-a305-c02c5cc9bbe6' class='xr-var-data-in' type='checkbox'><label for='data-c6ba9520-ff9f-4719-a305-c02c5cc9bbe6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
-       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-a2b9f4f7-8b03-4c35-b853-90a3d54b41cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2b9f4f7-8b03-4c35-b853-90a3d54b41cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23155b8e-a91c-4b51-87c0-353a637c3993' class='xr-var-data-in' type='checkbox'><label for='data-23155b8e-a91c-4b51-87c0-353a637c3993' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-aec677a5-0c13-478f-8ba0-676ce0d6e08c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aec677a5-0c13-478f-8ba0-676ce0d6e08c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d48c3cc8-091c-4507-925c-acfcca5b32a5' class='xr-var-data-in' type='checkbox'><label for='data-d48c3cc8-091c-4507-925c-acfcca5b32a5' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-bd437f0b-0d56-46f2-a31c-b5369985f561' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd437f0b-0d56-46f2-a31c-b5369985f561' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5265a25-9546-4330-865b-ab5c40434c8f' class='xr-var-data-in' type='checkbox'><label for='data-b5265a25-9546-4330-865b-ab5c40434c8f' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-d20eb24c-ef3c-4cc7-be62-f64e7f4f3e2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d20eb24c-ef3c-4cc7-be62-f64e7f4f3e2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab6162d0-e6da-4624-9671-5e9c07295451' class='xr-var-data-in' type='checkbox'><label for='data-ab6162d0-e6da-4624-9671-5e9c07295451' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-15a23381-0faf-4dfd-bed5-903323acf155' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15a23381-0faf-4dfd-bed5-903323acf155' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88262298-1109-46ed-9fb0-e5d2b775ce3c' class='xr-var-data-in' type='checkbox'><label for='data-88262298-1109-46ed-9fb0-e5d2b775ce3c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:20:00.438499927 .....</div><input id='attrs-da68cdc2-3a6c-464b-bf03-e8034bb24b92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da68cdc2-3a6c-464b-bf03-e8034bb24b92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-958e56ce-8b61-4338-a188-d9ace596d8c3' class='xr-var-data-in' type='checkbox'><label for='data-958e56ce-8b61-4338-a188-d9ace596d8c3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-15T00:20:00.438499927&#x27;, &#x27;2020-08-15T00:20:01.438499927&#x27;,\n",
        "       &#x27;2020-08-15T00:20:02.438499927&#x27;, ..., &#x27;2020-08-15T15:36:37.438499927&#x27;,\n",
        "       &#x27;2020-08-15T15:36:38.438499927&#x27;, &#x27;2020-08-15T15:36:39.438499927&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-ba0fb0b5-ba95-4302-a1d6-49a2c104e25a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ba0fb0b5-ba95-4302-a1d6-49a2c104e25a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ebec3c8-6c7d-48a3-bb9b-6815c0ecb839' class='xr-var-data-in' type='checkbox'><label for='data-0ebec3c8-6c7d-48a3-bb9b-6815c0ecb839' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-3119335b-c802-434a-a00a-37f2239724f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3119335b-c802-434a-a00a-37f2239724f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-565d432f-b580-4654-9615-4847001c776d' class='xr-var-data-in' type='checkbox'><label for='data-565d432f-b580-4654-9615-4847001c776d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
        "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
-       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-3e7c7540-b4fe-4645-9556-dd771f8d9a40' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e7c7540-b4fe-4645-9556-dd771f8d9a40' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f36a5183-1a4c-4ef3-af12-3ec78959ce94' class='xr-var-data-in' type='checkbox'><label for='data-f36a5183-1a4c-4ef3-af12-3ec78959ce94' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-023ef750-1615-47b0-8815-2f1a7d26ba13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-023ef750-1615-47b0-8815-2f1a7d26ba13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20970197-eb29-4792-bde9-887d120ba3de' class='xr-var-data-in' type='checkbox'><label for='data-20970197-eb29-4792-bde9-887d120ba3de' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-22696727-e324-447b-a0cf-dea4b4939d7d' class='xr-section-summary-in' type='checkbox'  ><label for='section-22696727-e324-447b-a0cf-dea4b4939d7d' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-9799948b-8231-4e11-b977-ecc91599822f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9799948b-8231-4e11-b977-ecc91599822f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-125a477a-4d0b-4041-bdf7-3ac70828f2a0' class='xr-var-data-in' type='checkbox'><label for='data-125a477a-4d0b-4041-bdf7-3ac70828f2a0' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-c66b2dae-7154-4b6a-8f6a-de0893948522' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c66b2dae-7154-4b6a-8f6a-de0893948522' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdf3f8b5-d763-47bf-8895-b2d991f0e496' class='xr-var-data-in' type='checkbox'><label for='data-cdf3f8b5-d763-47bf-8895-b2d991f0e496' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-0dcb711a-233d-4d76-8c93-74ef9852272b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0dcb711a-233d-4d76-8c93-74ef9852272b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e38a941-9d7f-4e9d-98b0-56fc131d287d' class='xr-var-data-in' type='checkbox'><label for='data-8e38a941-9d7f-4e9d-98b0-56fc131d287d' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-94914321-a11e-4e2a-93ed-d39cda9a12da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94914321-a11e-4e2a-93ed-d39cda9a12da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2b247396-6302-4268-a629-e7f9fbd7d264' class='xr-var-data-in' type='checkbox'><label for='data-2b247396-6302-4268-a629-e7f9fbd7d264' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
+       "       12.6, 13.1, 13.6, 14.1])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1</div><input id='attrs-00c0d3a2-16ae-4114-9e9b-054ab70aa437' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-00c0d3a2-16ae-4114-9e9b-054ab70aa437' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a22436ae-563f-4fd2-a095-e31b0c192521' class='xr-var-data-in' type='checkbox'><label for='data-a22436ae-563f-4fd2-a095-e31b0c192521' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Profile Range</dd><dt><span>description :</span></dt><dd>Distance to the center of each depth bin</dd></dl></div><div class='xr-var-data'><pre>array([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+       "       12.6, 13.1, 13.6, 14.1])</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-9e23722d-24f3-4149-9537-11fc3bc46495' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e23722d-24f3-4149-9537-11fc3bc46495' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a8d2595-8fc4-4bed-a235-dac3cab3ef27' class='xr-var-data-in' type='checkbox'><label for='data-2a8d2595-8fc4-4bed-a235-dac3cab3ef27' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-85a43302-7ab1-4cf2-b21c-0cc33c821709' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85a43302-7ab1-4cf2-b21c-0cc33c821709' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2a2b29b-96ca-42c5-9429-b63b79660b4f' class='xr-var-data-in' type='checkbox'><label for='data-e2a2b29b-96ca-42c5-9429-b63b79660b4f' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-d531df88-2d40-4e2c-87d1-aa9fab4ecaef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d531df88-2d40-4e2c-87d1-aa9fab4ecaef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc9c43a0-04f0-4ae2-bf30-78701848e16b' class='xr-var-data-in' type='checkbox'><label for='data-cc9c43a0-04f0-4ae2-bf30-78701848e16b' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>earth</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-92ded593-e574-48cc-9839-4507ef3fe05b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92ded593-e574-48cc-9839-4507ef3fe05b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-315096de-9bd1-471d-890f-8b2f2f548e94' class='xr-var-data-in' type='checkbox'><label for='data-315096de-9bd1-471d-890f-8b2f2f548e94' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-1d4d3e43-9fca-438f-aa5b-32dbcf53bc6e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1d4d3e43-9fca-438f-aa5b-32dbcf53bc6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-95093e6a-7270-4f15-aa07-cdaea43c0710' class='xr-var-data-in' type='checkbox'><label for='data-95093e6a-7270-4f15-aa07-cdaea43c0710' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-2724048d-b7dc-4436-adee-a1e0f7602aa0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2724048d-b7dc-4436-adee-a1e0f7602aa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2917ce6-d29c-495d-92f4-8f4dc3289e4b' class='xr-var-data-in' type='checkbox'><label for='data-b2917ce6-d29c-495d-92f4-8f4dc3289e4b' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternion Vector Components</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-5763845c-e51f-42bf-8584-d66eaaa145fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5763845c-e51f-42bf-8584-d66eaaa145fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c638a5c4-130d-4281-b3c8-274772b0fd57' class='xr-var-data-in' type='checkbox'><label for='data-c638a5c4-130d-4281-b3c8-274772b0fd57' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-a4cb41a8-11eb-4aef-9ae8-ea3752cf657c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4cb41a8-11eb-4aef-9ae8-ea3752cf657c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b104cddc-bf7b-4206-9655-f1f7d3a44b8c' class='xr-var-data-in' type='checkbox'><label for='data-b104cddc-bf7b-4206-9655-f1f7d3a44b8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-0b129d87-1ff8-42fa-9ba4-b171213ed751' class='xr-section-summary-in' type='checkbox'  ><label for='section-0b129d87-1ff8-42fa-9ba4-b171213ed751' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-74887e69-37c1-4bb1-91b3-696ee87a5e77' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74887e69-37c1-4bb1-91b3-696ee87a5e77' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bde687e-2a45-4cdb-bef6-388d3c2bf370' class='xr-var-data-in' type='checkbox'><label for='data-5bde687e-2a45-4cdb-bef6-388d3c2bf370' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.9, 1501.9, 1501.9, ..., 1498.4, 1498.3, 1498.3], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.55 14.55 14.55 ... 13.47 13.47</div><input id='attrs-254039ee-28c1-4924-849b-2335b2106472' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-254039ee-28c1-4924-849b-2335b2106472' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80a3a633-44e9-48f2-80eb-a555352f8aeb' class='xr-var-data-in' type='checkbox'><label for='data-80a3a633-44e9-48f2-80eb-a555352f8aeb' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.55, 14.55, 14.55, ..., 13.47, 13.47, 13.47], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.713 9.718 9.718 ... 9.594 9.596</div><input id='attrs-90542bc7-eef1-4a08-8258-6269080136d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90542bc7-eef1-4a08-8258-6269080136d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccd4ae4e-41b3-4c16-a002-5a729c8210ae' class='xr-var-data-in' type='checkbox'><label for='data-ccd4ae4e-41b3-4c16-a002-5a729c8210ae' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.713, 9.718, 9.718, ..., 9.596, 9.594, 9.596], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.5 72.7 72.6 ... -197.2 -195.7</div><input id='attrs-fcdc0a1d-b3d1-4928-bb43-cefc4ceefe03' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fcdc0a1d-b3d1-4928-bb43-cefc4ceefe03' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e3f5b86-26bf-4b7b-ade0-4dd2fad70c79' class='xr-var-data-in' type='checkbox'><label for='data-0e3f5b86-26bf-4b7b-ade0-4dd2fad70c79' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.5,   72.7,   72.6, ...,   72.3,   72.8,   72.4],\n",
        "       [   9.3,    9.4,    8.9, ...,    5.9,    6.3,    6.4],\n",
        "       [-198. , -196.3, -198.1, ..., -197.4, -197.2, -195.7]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-3e99a1ed-e30c-426e-bf9b-2b2b86456574' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e99a1ed-e30c-426e-bf9b-2b2b86456574' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c8be2a7c-3c84-44b0-98a4-eb3627fd00a1' class='xr-var-data-in' type='checkbox'><label for='data-c8be2a7c-3c84-44b0-98a4-eb3627fd00a1' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.00479 -0.01437 ... 9.685 9.729</div><input id='attrs-7d59394a-9468-4e3f-a35f-b1ee1f5331d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d59394a-9468-4e3f-a35f-b1ee1f5331d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4f28900c-45ea-4a1e-b11c-10b39591498b' class='xr-var-data-in' type='checkbox'><label for='data-4f28900c-45ea-4a1e-b11c-10b39591498b' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-4.7900393e-03, -1.4370117e-02, -2.3950195e-02, ...,\n",
        "        -1.4370117e-02, -4.7900393e-03, -2.3950195e-02],\n",
        "       [-1.2933105e+00, -1.2549902e+00, -1.2645704e+00, ...,\n",
        "        -1.1017090e+00, -1.0873389e+00, -1.0969189e+00],\n",
        "       [ 9.7285690e+00,  9.7141991e+00,  9.7237797e+00, ...,\n",
-       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-bb53204d-f9b3-4da2-8250-5dade7d0a2a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb53204d-f9b3-4da2-8250-5dade7d0a2a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f15c617-2b4d-4647-90fc-b10f0385678a' class='xr-var-data-in' type='checkbox'><label for='data-1f15c617-2b4d-4647-90fc-b10f0385678a' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-1f74491f-6470-42d6-b9f4-da6170cd0c3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f74491f-6470-42d6-b9f4-da6170cd0c3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b86c8ddc-2a20-405a-a911-c44a77521e77' class='xr-var-data-in' type='checkbox'><label for='data-b86c8ddc-2a20-405a-a911-c44a77521e77' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</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-ea110f04-6604-48ce-aa37-3ef4995b5a7a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea110f04-6604-48ce-aa37-3ef4995b5a7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffa5fa07-c95e-4ccd-b060-faa94c3d72d2' class='xr-var-data-in' type='checkbox'><label for='data-ffa5fa07-c95e-4ccd-b060-faa94c3d72d2' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-a1637cc4-6e6a-4176-829a-ddb0be9669d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1637cc4-6e6a-4176-829a-ddb0be9669d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26d19708-761f-47cf-81b4-ac76c7459731' class='xr-var-data-in' type='checkbox'><label for='data-26d19708-761f-47cf-81b4-ac76c7459731' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-31feafb8-a06b-434c-8b1a-5fa317082e6b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31feafb8-a06b-434c-8b1a-5fa317082e6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e846b8b8-0e31-4fae-9d7d-056c8723a7aa' class='xr-var-data-in' type='checkbox'><label for='data-e846b8b8-0e31-4fae-9d7d-056c8723a7aa' title='Show/Hide data repr'><svg 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>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-ae5ea8d3-341e-4df0-830e-03221ffeeeeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ae5ea8d3-341e-4df0-830e-03221ffeeeeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ebe0237-f83c-4dc7-a684-18b18eeb0ba3' class='xr-var-data-in' type='checkbox'><label for='data-3ebe0237-f83c-4dc7-a684-18b18eeb0ba3' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
+       "         9.6710892e+00,  9.6854591e+00,  9.7285690e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.6 16.6 16.6 ... 16.4 16.4 15.2</div><input id='attrs-16450a69-c1b7-473a-b3bf-be5b779ff765' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-16450a69-c1b7-473a-b3bf-be5b779ff765' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-45f61bcf-ec0a-4914-bdf3-0cb20b964853' class='xr-var-data-in' type='checkbox'><label for='data-45f61bcf-ec0a-4914-bdf3-0cb20b964853' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.6, 16.6, 16.6, ..., 16.4, 16.4, 15.2], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-032fc241-d178-473d-9e5f-2ed520610329' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-032fc241-d178-473d-9e5f-2ed520610329' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-104b1552-7297-4c59-a0c4-4fee02090b5f' class='xr-var-data-in' type='checkbox'><label for='data-104b1552-7297-4c59-a0c4-4fee02090b5f' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20. , 20. , 20. , ..., 19.5, 19.5, 19.5], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</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-5b05c07c-e975-43b3-b500-0440807a15b4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5b05c07c-e975-43b3-b500-0440807a15b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31439ad0-cc33-4e87-bc60-89e4c3532cc7' class='xr-var-data-in' type='checkbox'><label for='data-31439ad0-cc33-4e87-bc60-89e4c3532cc7' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-9467efa6-1777-407a-9271-e050fe66b32b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9467efa6-1777-407a-9271-e050fe66b32b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1e4e798-b796-4c1f-857b-c17500399ffd' class='xr-var-data-in' type='checkbox'><label for='data-c1e4e798-b796-4c1f-857b-c17500399ffd' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-3a4cb433-43a1-4701-9784-ac37e4cdd899' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a4cb433-43a1-4701-9784-ac37e4cdd899' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7f076dee-1633-4675-b22c-8bf371425a41' class='xr-var-data-in' type='checkbox'><label for='data-7f076dee-1633-4675-b22c-8bf371425a41' title='Show/Hide data repr'><svg 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>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.015 -0.048 ... -0.015 -0.012</div><input id='attrs-1e0f52af-befc-44f6-b86a-7b1359431e4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e0f52af-befc-44f6-b86a-7b1359431e4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75a73a5a-e98c-4644-a760-a630159809ba' class='xr-var-data-in' type='checkbox'><label for='data-75a73a5a-e98c-4644-a760-a630159809ba' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.015, -0.048,  0.008, ..., -0.176, -0.071, -0.027],\n",
        "        [-0.093, -0.124, -0.031, ..., -0.175, -0.16 , -0.03 ],\n",
        "        [-0.163, -0.135, -0.105, ..., -0.129, -0.089, -0.116],\n",
        "        ...,\n",
@@ -561,7 +563,7 @@
        "        [-0.044,  0.015, -0.04 , ..., -0.015,  0.006,  0.012],\n",
        "        [-0.013,  0.014, -0.032, ...,  0.01 ,  0.   , -0.015],\n",
        "        [ 0.007,  0.016, -0.027, ..., -0.002, -0.015, -0.012]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-7bbd1c06-7f8c-408a-acae-265e5db9a770' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bbd1c06-7f8c-408a-acae-265e5db9a770' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94892884-cb11-4c15-ac2c-36a7aac52a45' class='xr-var-data-in' type='checkbox'><label for='data-94892884-cb11-4c15-ac2c-36a7aac52a45' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>81.0 80.0 80.5 ... 43.5 42.5 42.0</div><input id='attrs-a6918d83-86ea-4c61-90c5-a4e6fe3c6157' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6918d83-86ea-4c61-90c5-a4e6fe3c6157' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2eda0a9a-75f4-4e5f-b915-86da58f517c4' class='xr-var-data-in' type='checkbox'><label for='data-2eda0a9a-75f4-4e5f-b915-86da58f517c4' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[81. , 80. , 80.5, ..., 81.5, 81.5, 81.5],\n",
        "        [75. , 74.5, 75. , ..., 79. , 77. , 77.5],\n",
        "        [73.5, 72. , 72. , ..., 75. , 74.5, 75. ],\n",
        "        ...,\n",
@@ -591,7 +593,7 @@
        "        ...,\n",
        "        [51.5, 51. , 51. , ..., 46. , 46. , 45. ],\n",
        "        [51. , 50. , 51. , ..., 45. , 44. , 43.5],\n",
-       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-3a788d16-1b79-47b0-bc08-f34666d72729' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a788d16-1b79-47b0-bc08-f34666d72729' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-557503a5-d74a-45c4-befb-23801b61b0a2' class='xr-var-data-in' type='checkbox'><label for='data-557503a5-d74a-45c4-befb-23801b61b0a2' title='Show/Hide data repr'><svg 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>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
+       "        [50.5, 49.5, 50. , ..., 43.5, 42.5, 42. ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>100 91 91 97 99 ... 96 98 98 98 96</div><input id='attrs-6487d540-0cd9-4934-9b23-6b3130073fb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6487d540-0cd9-4934-9b23-6b3130073fb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eec96a05-d4c5-4db0-924a-452086ac6110' class='xr-var-data-in' type='checkbox'><label for='data-eec96a05-d4c5-4db0-924a-452086ac6110' title='Show/Hide data repr'><svg 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>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[[100,  91,  91, ...,  89,  90,  96],\n",
        "        [ 74,  92,  96, ..., 100,  97, 100],\n",
        "        [100, 100,  99, ...,  99, 100, 100],\n",
        "        ...,\n",
@@ -621,7 +623,7 @@
        "        ...,\n",
        "        [100,  99,  96, ...,  98, 100, 100],\n",
        "        [100, 100, 100, ...,  94,  93,  95],\n",
-       "        [100,  98,  99, ...,  98,  98,  96]]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-d3614c88-e21b-4da7-8cc9-776a97d1bdbd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3614c88-e21b-4da7-8cc9-776a97d1bdbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-80296778-6075-4d98-aaa5-315d4e68e1b2' class='xr-var-data-in' type='checkbox'><label for='data-80296778-6075-4d98-aaa5-315d4e68e1b2' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
+       "        [100,  98,  99, ...,  98,  98,  96]]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2164 ... 0.9937 0.9937</div><input id='attrs-8cea80b2-1ec7-4f00-a034-7be1c511d6e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8cea80b2-1ec7-4f00-a034-7be1c511d6e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3da15759-0b38-4231-b5a5-8f3d598d2e8c' class='xr-var-data-in' type='checkbox'><label for='data-3da15759-0b38-4231-b5a5-8f3d598d2e8c' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16688156e-01, -2.16397047e-01, -2.16593146e-01, ...,\n",
        "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
        "        [ 9.76196468e-01,  9.76219118e-01,  9.76202846e-01, ...,\n",
        "          9.76315439e-01,  9.76210594e-01,  9.76245522e-01],\n",
@@ -641,47 +643,47 @@
        "         -2.31788009e-02, -2.33813375e-02, -2.34001204e-02],\n",
        "        [ 9.91607308e-01,  9.91618454e-01,  9.91612315e-01, ...,\n",
        "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-24652fb5-52d1-4311-a4e8-551af06f5808' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24652fb5-52d1-4311-a4e8-551af06f5808' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c5636b34-5302-489a-a86c-a527a39f4beb' class='xr-var-data-in' type='checkbox'><label for='data-c5636b34-5302-489a-a86c-a527a39f4beb' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.00293</div><input id='attrs-f453a68f-09a2-46d5-9e2b-8c4efc43e18c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f453a68f-09a2-46d5-9e2b-8c4efc43e18c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebf2fec3-f2ae-48ae-b49a-94b5b0f7b56f' class='xr-var-data-in' type='checkbox'><label for='data-ebf2fec3-f2ae-48ae-b49a-94b5b0f7b56f' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00390625,\n",
        "        -0.00292969, -0.00195312],\n",
        "       [ 0.00097656,  0.        ,  0.        , ...,  0.        ,\n",
        "         0.00097656,  0.00097656],\n",
        "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00195312, -0.00292969]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-02a61a2b-5adc-4065-ad35-ed52f6737943' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02a61a2b-5adc-4065-ad35-ed52f6737943' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d69e369f-ba34-4b70-94de-85d58f796f85' class='xr-var-data-in' type='checkbox'><label for='data-d69e369f-ba34-4b70-94de-85d58f796f85' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
+       "        -0.00195312, -0.00292969]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-dd3a0b0d-d7ed-4aad-bc26-5f5c40a5f9f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd3a0b0d-d7ed-4aad-bc26-5f5c40a5f9f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4898048-a6b4-44d6-bbfd-39a635c78a87' class='xr-var-data-in' type='checkbox'><label for='data-b4898048-a6b4-44d6-bbfd-39a635c78a87' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6244812 , ...,  0.625     ,\n",
        "         0.6247864 ,  0.62490845],\n",
        "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
        "        -0.03564453, -0.03561401],\n",
        "       [-0.05014038, -0.05010986, -0.05014038, ..., -0.04354858,\n",
        "        -0.04360962, -0.04360962],\n",
        "       [ 0.77835083,  0.7782593 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-a4f82b39-0196-482e-a658-a0bce674365c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4f82b39-0196-482e-a658-a0bce674365c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-787e868c-a11f-4987-aca2-98c9f01bfaf2' class='xr-var-data-in' type='checkbox'><label for='data-787e868c-a11f-4987-aca2-98c9f01bfaf2' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-b5870ca8-1627-4fba-ad85-1319d049e96a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5870ca8-1627-4fba-ad85-1319d049e96a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3f8ac23-5b90-4335-8c74-2ef2e5e00d95' class='xr-var-data-in' type='checkbox'><label for='data-c3f8ac23-5b90-4335-8c74-2ef2e5e00d95' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-bd053d6a-787f-419f-9d99-5c074a8366b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd053d6a-787f-419f-9d99-5c074a8366b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-666f1ba3-d496-46b0-a418-54ea78205445' class='xr-var-data-in' type='checkbox'><label for='data-666f1ba3-d496-46b0-a418-54ea78205445' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
+       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-e89ba2b6-bf61-47b7-94a5-be19066de821' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e89ba2b6-bf61-47b7-94a5-be19066de821' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aef06fb5-5f8d-4150-bf32-cea1be9ff0ba' class='xr-var-data-in' type='checkbox'><label for='data-aef06fb5-5f8d-4150-bf32-cea1be9ff0ba' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.8, 12.8, 12.8, ..., 12. , 12. , 12. ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>243 243 243 244 ... 246 246 246 246</div><input id='attrs-d87a479b-0c3c-4433-b280-f2dd847cae87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d87a479b-0c3c-4433-b280-f2dd847cae87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89204eb8-b882-4022-b1f6-9c1dcbdf9b9f' class='xr-var-data-in' type='checkbox'><label for='data-89204eb8-b882-4022-b1f6-9c1dcbdf9b9f' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([243, 243, 243, ..., 246, 246, 246], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.9 72.8 72.4 ... -198.0 -195.7</div><input id='attrs-ac74db4b-4178-42d2-be81-bc0799d87a72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac74db4b-4178-42d2-be81-bc0799d87a72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34f5c8ef-8938-4370-87de-91174750b6fc' class='xr-var-data-in' type='checkbox'><label for='data-34f5c8ef-8938-4370-87de-91174750b6fc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[  72.9,   72.8,   72.4, ...,   73. ,   73. ,   72.7],\n",
        "       [   9.5,    9.5,    9.8, ...,    6. ,    6.4,    5.9],\n",
        "       [-197.1, -197.2, -197.7, ..., -197.4, -198. , -195.7]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-31606597-e80f-42da-983e-b49dc6f4f10c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31606597-e80f-42da-983e-b49dc6f4f10c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b35451ac-d6a0-4027-a077-d7a3d8907066' class='xr-var-data-in' type='checkbox'><label for='data-b35451ac-d6a0-4027-a077-d7a3d8907066' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.01437 0.0 ... 9.709 9.724</div><input id='attrs-e7fdcb95-799a-4fc3-93c4-5af381a800ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7fdcb95-799a-4fc3-93c4-5af381a800ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74332ff4-3b7f-42e2-acf2-79fd1d1a42b6' class='xr-var-data-in' type='checkbox'><label for='data-74332ff4-3b7f-42e2-acf2-79fd1d1a42b6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.4370117e-02,  0.0000000e+00, -1.4370117e-02, ...,\n",
        "        -4.7900393e-03, -1.9160157e-02, -1.4370117e-02],\n",
        "       [-1.2693603e+00, -1.2885205e+00, -1.2837305e+00, ...,\n",
        "        -1.0825489e+00, -1.1017090e+00, -1.1064991e+00],\n",
        "       [ 9.7189894e+00,  9.7046194e+00,  9.7094088e+00, ...,\n",
-       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</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-93b1d74f-5cdd-4016-8020-0c3c08682b12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93b1d74f-5cdd-4016-8020-0c3c08682b12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e82c03bc-f11e-476b-9c11-7a851561eec9' class='xr-var-data-in' type='checkbox'><label for='data-e82c03bc-f11e-476b-9c11-7a851561eec9' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-be82150a-6d3e-4dc9-824a-f388648baeb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be82150a-6d3e-4dc9-824a-f388648baeb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-022ebb33-10ad-4920-8b32-29de14c65f5c' class='xr-var-data-in' type='checkbox'><label for='data-022ebb33-10ad-4920-8b32-29de14c65f5c' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
-       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-6bab972c-9546-4c29-9ad8-d74013cdea27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bab972c-9546-4c29-9ad8-d74013cdea27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21714e6d-842d-4024-8c88-d8bd39e896ae' class='xr-var-data-in' type='checkbox'><label for='data-21714e6d-842d-4024-8c88-d8bd39e896ae' title='Show/Hide data repr'><svg 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>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-f7b69d25-5e03-46b3-8088-c62b0a53e0ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f7b69d25-5e03-46b3-8088-c62b0a53e0ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6771dd73-8b46-403f-b33b-8d27538b917f' class='xr-var-data-in' type='checkbox'><label for='data-6771dd73-8b46-403f-b33b-8d27538b917f' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
+       "         9.7141991e+00,  9.7094088e+00,  9.7237797e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</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-7b716d6d-58c3-4245-bf3e-6c3ab6766db9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b716d6d-58c3-4245-bf3e-6c3ab6766db9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d93639dd-8566-4039-808d-9ffcec944f17' class='xr-var-data-in' type='checkbox'><label for='data-d93639dd-8566-4039-808d-9ffcec944f17' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1053556738 ... 1053557762</div><input id='attrs-4b154f29-58ec-438f-bd32-002e4e6b3008' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b154f29-58ec-438f-bd32-002e4e6b3008' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a17de072-4306-4646-9c8f-373ea4959f9f' class='xr-var-data-in' type='checkbox'><label for='data-a17de072-4306-4646-9c8f-373ea4959f9f' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1053556738, 1053556738, 1053556738, ..., 1053556738, 1053556738,\n",
+       "       1053557762], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ensemble_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint32</div><div class='xr-var-preview xr-preview'>1 2 3 4 ... 54997 54998 54999 55000</div><input id='attrs-91b0b144-6f68-4e1c-917b-a1b24e010beb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91b0b144-6f68-4e1c-917b-a1b24e010beb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b9b7579-8914-4c7b-96b9-ca2672061bfb' class='xr-var-data-in' type='checkbox'><label for='data-3b9b7579-8914-4c7b-96b9-ca2672061bfb' title='Show/Hide data repr'><svg 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>#</dd><dt><span>long_name :</span></dt><dd>Ensemble Number</dd><dt><span>standard_name :</span></dt><dd>number_of_observations</dd></dl></div><div class='xr-var-data'><pre>array([    1,     2,     3, ..., 54998, 54999, 55000], dtype=uint32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003 0.021 0.018 ... -0.048 0.09</div><input id='attrs-4c0a01d7-1167-4b56-a56b-938d67c8bc49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c0a01d7-1167-4b56-a56b-938d67c8bc49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f37af69-b0d2-4b5f-9445-e8f809029e5a' class='xr-var-data-in' type='checkbox'><label for='data-9f37af69-b0d2-4b5f-9445-e8f809029e5a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.003,  0.021,  0.018, ...,  0.   , -0.044,  0.009],\n",
        "       [ 0.057,  0.034,  0.017, ...,  0.01 ,  0.001, -0.002],\n",
        "       [ 0.039,  0.022,  0.02 , ...,  0.039, -0.008,  0.018],\n",
        "       ...,\n",
        "       [-0.036, -0.013,  0.058, ...,  0.058, -0.013,  0.028],\n",
        "       [-0.043, -0.009,  0.028, ...,  0.092, -0.021,  0.019],\n",
        "       [-0.073,  0.003,  0.   , ...,  0.049, -0.048,  0.09 ]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-b3a3a9fa-3443-414e-a3b7-4b975dea63bb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3a3a9fa-3443-414e-a3b7-4b975dea63bb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5652828-b6b4-4bc2-8b64-eb6d3f7e58c7' class='xr-var-data-in' type='checkbox'><label for='data-d5652828-b6b4-4bc2-8b64-eb6d3f7e58c7' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.5 80.5 80.0 ... 46.5 46.0 47.5</div><input id='attrs-dda854c2-1e5e-4abe-835a-85cca3c2a6a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dda854c2-1e5e-4abe-835a-85cca3c2a6a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806ff65c-4e93-428b-ba98-6462e05e2f5c' class='xr-var-data-in' type='checkbox'><label for='data-806ff65c-4e93-428b-ba98-6462e05e2f5c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[80.5, 80.5, 80. , ..., 82. , 81.5, 81. ],\n",
        "       [75.5, 76.5, 76. , ..., 78.5, 78. , 77.5],\n",
        "       [72.5, 73.5, 73.5, ..., 75. , 76.5, 75.5],\n",
        "       ...,\n",
        "       [57.5, 57.5, 57. , ..., 49. , 49. , 48.5],\n",
        "       [56.5, 57. , 56. , ..., 47.5, 48. , 48. ],\n",
-       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-daafecdd-60c3-409a-bf60-8aa046e7b0ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-daafecdd-60c3-409a-bf60-8aa046e7b0ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0b380e-9202-42f2-a2d6-8ab702301bd9' class='xr-var-data-in' type='checkbox'><label for='data-bf0b380e-9202-42f2-a2d6-8ab702301bd9' title='Show/Hide data repr'><svg 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>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
+       "       [55.5, 55.5, 55. , ..., 46.5, 46. , 47.5]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>98 100 92 93 98 ... 100 99 94 100</div><input id='attrs-74475b83-37de-407f-af19-69f5b114a756' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74475b83-37de-407f-af19-69f5b114a756' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-660793cd-b8c6-4bd0-be44-f80e6a6cc00a' class='xr-var-data-in' type='checkbox'><label for='data-660793cd-b8c6-4bd0-be44-f80e6a6cc00a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[ 98, 100,  92, ...,  88,  90,  91],\n",
        "       [ 97,  94,  98, ...,  97,  95,  97],\n",
        "       [100, 100, 100, ...,  93, 100,  96],\n",
        "       ...,\n",
        "       [100, 100, 100, ..., 100, 100,  98],\n",
        "       [100, 100, 100, ...,  99, 100,  98],\n",
-       "       [100, 100, 100, ...,  99,  94, 100]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-cfdf2fa5-cc12-4f58-9ebf-8fa153f65300' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfdf2fa5-cc12-4f58-9ebf-8fa153f65300' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c820902d-039b-4b9b-927e-2cf8eb79b91d' class='xr-var-data-in' type='checkbox'><label for='data-c820902d-039b-4b9b-927e-2cf8eb79b91d' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
+       "       [100, 100, 100, ...,  99,  94, 100]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2167 -0.2165 ... 0.9937 0.9937</div><input id='attrs-78b6c650-2677-4ac0-9549-967ace9dccdf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78b6c650-2677-4ac0-9549-967ace9dccdf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab26ef62-97f6-4948-ac5a-758f67c74d13' class='xr-var-data-in' type='checkbox'><label for='data-ab26ef62-97f6-4948-ac5a-758f67c74d13' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16694236e-01, -2.16498137e-01, -2.16593146e-01, ...,\n",
        "         -2.16118217e-01, -2.16699123e-01, -2.16318965e-01],\n",
        "        [-9.67967808e-01, -9.68039632e-01, -9.68030274e-01, ...,\n",
        "         -9.70095694e-01, -9.69992876e-01, -9.70033050e-01],\n",
@@ -701,57 +703,105 @@
        "         -1.12442717e-01, -1.12462208e-01, -1.12422116e-01],\n",
        "        [ 9.91601229e-01,  9.91612315e-01,  9.91612315e-01, ...,\n",
        "          9.93657291e-01,  9.93655324e-01,  9.93659675e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-b0d33004-4362-4dc4-a3dc-6c5fbd8e6419' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b0d33004-4362-4dc4-a3dc-6c5fbd8e6419' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bea08383-7fd1-400a-bef7-86632f8b77ac' class='xr-var-data-in' type='checkbox'><label for='data-bea08383-7fd1-400a-bef7-86632f8b77ac' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.001953 -0.001953 ... -0.001953</div><input id='attrs-3df6ebbd-fc42-4ab2-8066-38b4726d5c59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3df6ebbd-fc42-4ab2-8066-38b4726d5c59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b17c40f2-65ae-4b7b-bd62-0426e2e50e9a' class='xr-var-data-in' type='checkbox'><label for='data-b17c40f2-65ae-4b7b-bd62-0426e2e50e9a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00195312, -0.00195312, -0.00195312, ..., -0.00097656,\n",
        "        -0.00195312, -0.00390625],\n",
        "       [ 0.        ,  0.        ,  0.00097656, ...,  0.00097656,\n",
        "         0.        ,  0.00097656],\n",
        "       [-0.00292969, -0.00292969, -0.00292969, ..., -0.00292969,\n",
-       "        -0.00292969, -0.00195312]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-67c2cad4-6171-415b-9f18-59a5c00ad8ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67c2cad4-6171-415b-9f18-59a5c00ad8ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e85f4521-42d6-49a8-aa4b-86d42fb0d376' class='xr-var-data-in' type='checkbox'><label for='data-e85f4521-42d6-49a8-aa4b-86d42fb0d376' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
+       "        -0.00292969, -0.00195312]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6245 ... 0.7787 0.7786</div><input id='attrs-de5601fe-faac-492a-a029-891dde90764c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de5601fe-faac-492a-a029-891dde90764c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-613f1c3c-eec2-424f-94f8-de2c7c902f7c' class='xr-var-data-in' type='checkbox'><label for='data-613f1c3c-eec2-424f-94f8-de2c7c902f7c' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6244507 ,  0.62454224,  0.6245117 , ...,  0.625     ,\n",
        "         0.6247864 ,  0.62490845],\n",
        "       [-0.04101562, -0.04098511, -0.04098511, ..., -0.03570557,\n",
        "        -0.03564453, -0.03561401],\n",
        "       [-0.0501709 , -0.05014038, -0.05014038, ..., -0.04354858,\n",
        "        -0.04360962, -0.04360962],\n",
        "       [ 0.77835083,  0.7782898 ,  0.7783203 , ...,  0.77856445,\n",
-       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-548187fa-c159-424c-895a-d6929abe60f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-548187fa-c159-424c-895a-d6929abe60f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d1f734f-d4cd-4a44-9025-b010eaa795fd' class='xr-var-data-in' type='checkbox'><label for='data-7d1f734f-d4cd-4a44-9025-b010eaa795fd' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-537b58a0-2a60-4382-9b37-e5fe8c5b2071' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-537b58a0-2a60-4382-9b37-e5fe8c5b2071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-542e2915-cf07-47cc-ac85-5a4587bc63b1' class='xr-var-data-in' type='checkbox'><label for='data-542e2915-cf07-47cc-ac85-5a4587bc63b1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-e24693a2-f2e7-4636-944e-5187cd2eb5c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e24693a2-f2e7-4636-944e-5187cd2eb5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8d942e7d-941b-4663-8401-c881ae9c2333' class='xr-var-data-in' type='checkbox'><label for='data-8d942e7d-941b-4663-8401-c881ae9c2333' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-4464f765-d06f-44a2-a57f-07dfa9de6825' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4464f765-d06f-44a2-a57f-07dfa9de6825' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-04d1bc49-0e19-47d2-82b5-b8346d3f6fb8' class='xr-var-data-in' type='checkbox'><label for='data-04d1bc49-0e19-47d2-82b5-b8346d3f6fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-0c19ffd9-52d0-4474-bdc3-efdf7834f90a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c19ffd9-52d0-4474-bdc3-efdf7834f90a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4da2c31d-511f-4821-aafc-58ddcd51496f' class='xr-var-data-in' type='checkbox'><label for='data-4da2c31d-511f-4821-aafc-58ddcd51496f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 1], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-47165076-4109-4754-9d12-0299c5b69d04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47165076-4109-4754-9d12-0299c5b69d04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d2fe888-606c-4198-b5fb-272f79b036d7' class='xr-var-data-in' type='checkbox'><label for='data-9d2fe888-606c-4198-b5fb-272f79b036d7' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
-       "       -12.500001], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-36348d5f-cbc6-4481-80e1-df26409123dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-36348d5f-cbc6-4481-80e1-df26409123dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33829b96-45e5-46f9-a7f5-b72c54b46fa7' class='xr-var-data-in' type='checkbox'><label for='data-33829b96-45e5-46f9-a7f5-b72c54b46fa7' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-ffc81d10-e5b6-4b24-a41d-46daca3237be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ffc81d10-e5b6-4b24-a41d-46daca3237be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce5b0ff5-0131-4157-9878-085106a635aa' class='xr-var-data-in' type='checkbox'><label for='data-ce5b0ff5-0131-4157-9878-085106a635aa' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
-       "       -6.45     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-9bae6af3-7d73-4528-8711-252d28108b0d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bae6af3-7d73-4528-8711-252d28108b0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-972a8d17-b1f9-43cc-93fe-54cb7542857a' class='xr-var-data-in' type='checkbox'><label for='data-972a8d17-b1f9-43cc-93fe-54cb7542857a' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
+       "         0.77874756,  0.7786255 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>uint16</div><div class='xr-var-preview xr-preview'>65 65 65 65 65 ... 65 65 65 65 65</div><input id='attrs-0e1f1bf1-5270-4ac7-9caf-cdccbc0dc944' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e1f1bf1-5270-4ac7-9caf-cdccbc0dc944' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d7d5ab1-7981-405f-9660-4e626fe8b9ee' class='xr-var-data-in' type='checkbox'><label for='data-3d7d5ab1-7981-405f-9660-4e626fe8b9ee' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65, 65, 65, ..., 65, 65, 65], dtype=uint16)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-1789aa89-c5e6-4bc3-8c16-5d32028a900c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1789aa89-c5e6-4bc3-8c16-5d32028a900c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51e27ab9-9e32-4e37-b5e3-c125d04350cd' class='xr-var-data-in' type='checkbox'><label for='data-51e27ab9-9e32-4e37-b5e3-c125d04350cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-c9f9f1fe-a850-4938-80c5-8f437b7f2c73' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c9f9f1fe-a850-4938-80c5-8f437b7f2c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2971d0b9-7cb4-4ff4-a4ca-aaf5c96df97b' class='xr-var-data-in' type='checkbox'><label for='data-2971d0b9-7cb4-4ff4-a4ca-aaf5c96df97b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-f55c87bc-3b6b-45e6-b08a-d5d90e8d59f3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f55c87bc-3b6b-45e6-b08a-d5d90e8d59f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0acd04a-e92c-402a-96d6-7bd6ac41f40b' class='xr-var-data-in' type='checkbox'><label for='data-f0acd04a-e92c-402a-96d6-7bd6ac41f40b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>0 0 0 0 0 0 0 0 ... 1 0 0 0 0 0 0 1</div><input id='attrs-3697a70c-b8bb-4b7d-9837-5306f1ba65fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3697a70c-b8bb-4b7d-9837-5306f1ba65fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-409faaaa-fe68-4f77-afc1-5a04209cbe33' class='xr-var-data-in' type='checkbox'><label for='data-409faaaa-fe68-4f77-afc1-5a04209cbe33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 1], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-12.52 -12.51 ... -12.52 -12.5</div><input id='attrs-e8745d1a-2a22-4a45-a591-5d72f2057353' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e8745d1a-2a22-4a45-a591-5d72f2057353' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17c92374-3987-4614-bd9f-04ea8d4e921c' class='xr-var-data-in' type='checkbox'><label for='data-17c92374-3987-4614-bd9f-04ea8d4e921c' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([-12.52    , -12.505001, -12.51    , ..., -12.490002, -12.52    ,\n",
+       "       -12.500001], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.065 -0.06 -0.06 ... -0.05 -0.05</div><input id='attrs-eea7f06a-0f58-4154-b92e-a96d5b530413' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eea7f06a-0f58-4154-b92e-a96d5b530413' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c273c00-cdf6-4deb-bec3-fb16bb8e9d54' class='xr-var-data-in' type='checkbox'><label for='data-0c273c00-cdf6-4deb-bec3-fb16bb8e9d54' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.065, -0.06 , -0.06 , ..., -0.06 , -0.05 , -0.05 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.425 -7.42 -7.42 ... -6.45 -6.45</div><input id='attrs-d93522ac-d574-4ac7-a8ef-9d33955e0f4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d93522ac-d574-4ac7-a8ef-9d33955e0f4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-989779a2-49f7-4a37-a368-4a53c074dc40' class='xr-var-data-in' type='checkbox'><label for='data-989779a2-49f7-4a37-a368-4a53c074dc40' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.4250007, -7.42     , -7.42     , ..., -6.45     , -6.45     ,\n",
+       "       -6.45     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.183 0.0 -1.183 ... 0.0 0.5518</div><input id='attrs-6c0ad146-6d32-4243-968d-5eac38125f8a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c0ad146-6d32-4243-968d-5eac38125f8a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9b32627-5487-4352-9b40-8c4dc690c244' class='xr-var-data-in' type='checkbox'><label for='data-b9b32627-5487-4352-9b40-8c4dc690c244' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 1.1831,  0.    , -1.1831,  0.    ],\n",
        "       [ 0.    , -1.1831,  0.    ,  1.1831],\n",
        "       [ 0.5518,  0.    ,  0.5518,  0.    ],\n",
-       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5114684c-3013-4101-acba-b90d77a72c86' class='xr-section-summary-in' type='checkbox'  ><label for='section-5114684c-3013-4101-acba-b90d77a72c86' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
+       "       [ 0.    ,  0.5518,  0.    ,  0.5518]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-04c200e0-5a77-4be6-b1c0-ce96d7785905' class='xr-section-summary-in' type='checkbox'  ><label for='section-04c200e0-5a77-4be6-b1c0-ce96d7785905' class='xr-section-summary' >Indexes: <span>(12)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1dc04065-d2b1-4f5c-9607-a94abe7e99da' class='xr-index-data-in' type='checkbox'/><label for='index-1dc04065-d2b1-4f5c-9607-a94abe7e99da' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:01.501100063&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:02.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:03.501100063&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:04.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:05.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:06.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:07.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:08.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:09.500999927&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2020-08-15 15:36:30.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:31.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:32.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:33.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:34.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:35.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:36.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:37.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:38.500999927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:39.500999927&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-adbf40b4-387d-4912-91ac-4f8f027d2aa9' class='xr-index-data-in' type='checkbox'/><label for='index-adbf40b4-387d-4912-91ac-4f8f027d2aa9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:20:00.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:01.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:02.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:03.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:04.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:05.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:06.438400030&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:07.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:08.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 00:20:09.438499927&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2020-08-15 15:36:30.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:31.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:32.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:33.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:34.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:35.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:36.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:37.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:38.438499927&#x27;,\n",
+       "               &#x27;2020-08-15 15:36:39.438499927&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=55000, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-5d00d55b-eeec-467a-9a24-6b56f4dfa4ef' class='xr-index-data-in' type='checkbox'/><label for='index-5d00d55b-eeec-467a-9a24-6b56f4dfa4ef' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+       "       12.6, 13.1, 13.6, 14.1],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-48457e54-8817-4179-9288-5095ab6e1155' class='xr-index-data-in' type='checkbox'/><label for='index-48457e54-8817-4179-9288-5095ab6e1155' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 0.6,  1.1,  1.6,  2.1,  2.6,  3.1,  3.6,  4.1,  4.6,  5.1,  5.6,  6.1,\n",
+       "        6.6,  7.1,  7.6,  8.1,  8.6,  9.1,  9.6, 10.1, 10.6, 11.1, 11.6, 12.1,\n",
+       "       12.6, 13.1, 13.6, 14.1],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0f17c456-0ee0-46db-adbd-157d1e8e43dc' class='xr-index-data-in' type='checkbox'/><label for='index-0f17c456-0ee0-46db-adbd-157d1e8e43dc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-055638a0-c30b-434c-a9e0-0a1ca0e710e5' class='xr-index-data-in' type='checkbox'/><label for='index-055638a0-c30b-434c-a9e0-0a1ca0e710e5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0e2bc576-ce7f-4258-9663-245defef5f49' class='xr-index-data-in' type='checkbox'/><label for='index-0e2bc576-ce7f-4258-9663-245defef5f49' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f3695d55-1187-4b94-a58a-10e5133736ee' class='xr-index-data-in' type='checkbox'/><label for='index-f3695d55-1187-4b94-a58a-10e5133736ee' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bf5be610-91e6-4168-900f-8f3c50b20a5d' class='xr-index-data-in' type='checkbox'/><label for='index-bf5be610-91e6-4168-900f-8f3c50b20a5d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f7511774-c0a2-4847-928f-0a45f3f81a29' class='xr-index-data-in' type='checkbox'/><label for='index-f7511774-c0a2-4847-928f-0a45f3f81a29' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-585c2cc9-8de6-49db-bcec-0c6f018a9871' class='xr-index-data-in' type='checkbox'/><label for='index-585c2cc9-8de6-49db-bcec-0c6f018a9871' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cf740684-7808-4806-bb84-4e92a8633ff2' class='xr-index-data-in' type='checkbox'/><label for='index-cf740684-7808-4806-bb84-4e92a8633ff2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f09ec68-d3a7-4363-b807-af02db827ae3' class='xr-section-summary-in' type='checkbox'  ><label for='section-7f09ec68-d3a7-4363-b807-af02db827ae3' class='xr-section-summary' >Attributes: <span>(34)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>fs :</span></dt><dd>1</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:              (time: 55000, dirIMU: 3, dir: 4, range: 28, beam: 4,\n",
-       "                          earth: 3, inst: 3, q: 4, time_b5: 55000,\n",
-       "                          range_b5: 28, x1: 4, x2: 4)\n",
+       "<xarray.Dataset> Size: 83MB\n",
+       "Dimensions:              (time: 55000, time_b5: 55000, range: 28, range_b5: 28,\n",
+       "                          beam: 4, dir: 4, dirIMU: 3, earth: 3, inst: 3, q: 4,\n",
+       "                          x1: 4, x2: 4)\n",
        "Coordinates:\n",
-       "  * time                 (time) datetime64[ns] 2020-08-15T00:20:00.500999927 ...\n",
-       "  * dirIMU               (dirIMU) <U1 'E' 'N' 'U'\n",
-       "  * dir                  (dir) <U2 'E' 'N' 'U1' 'U2'\n",
-       "  * range                (range) float64 0.6 1.1 1.6 2.1 ... 12.6 13.1 13.6 14.1\n",
-       "  * beam                 (beam) int32 1 2 3 4\n",
-       "  * earth                (earth) <U1 'E' 'N' 'U'\n",
-       "  * inst                 (inst) <U1 'X' 'Y' 'Z'\n",
-       "  * q                    (q) <U1 'w' 'x' 'y' 'z'\n",
-       "  * time_b5              (time_b5) datetime64[ns] 2020-08-15T00:20:00.4384999...\n",
-       "  * range_b5             (range_b5) float64 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
-       "  * x1                   (x1) int32 1 2 3 4\n",
-       "  * x2                   (x2) int32 1 2 3 4\n",
+       "  * time                 (time) datetime64[ns] 440kB 2020-08-15T00:20:00.5009...\n",
+       "  * time_b5              (time_b5) datetime64[ns] 440kB 2020-08-15T00:20:00.4...\n",
+       "  * range                (range) float64 224B 0.6 1.1 1.6 2.1 ... 13.1 13.6 14.1\n",
+       "  * range_b5             (range_b5) float64 224B 0.6 1.1 1.6 ... 13.1 13.6 14.1\n",
+       "  * beam                 (beam) int32 16B 1 2 3 4\n",
+       "  * dir                  (dir) <U2 32B 'E' 'N' 'U1' 'U2'\n",
+       "  * dirIMU               (dirIMU) <U1 12B 'E' 'N' 'U'\n",
+       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * q                    (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+       "  * x1                   (x1) int32 16B 1 2 3 4\n",
+       "  * x2                   (x2) int32 16B 1 2 3 4\n",
        "Data variables: (12/38)\n",
-       "    c_sound              (time) float32 1.502e+03 1.502e+03 ... 1.498e+03\n",
-       "    temp                 (time) float32 14.55 14.55 14.55 ... 13.47 13.47 13.47\n",
-       "    pressure             (time) float32 9.713 9.718 9.718 ... 9.596 9.594 9.596\n",
-       "    mag                  (dirIMU, time) float32 72.5 72.7 72.6 ... -197.2 -195.7\n",
-       "    accel                (dirIMU, time) float32 -0.00479 -0.01437 ... 9.729\n",
-       "    batt                 (time) float32 16.6 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
+       "    c_sound              (time) float32 220kB 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    temp                 (time) float32 220kB 14.55 14.55 14.55 ... 13.47 13.47\n",
+       "    pressure             (time) float32 220kB 9.713 9.718 9.718 ... 9.594 9.596\n",
+       "    mag                  (dirIMU, time) float32 660kB 72.5 72.7 ... -195.7\n",
+       "    accel                (dirIMU, time) float32 660kB -0.00479 ... 9.729\n",
+       "    batt                 (time) float32 220kB 16.6 16.6 16.6 ... 16.4 16.4 15.2\n",
        "    ...                   ...\n",
-       "    telemetry_data       (time) uint8 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
-       "    boost_running        (time) uint8 0 0 0 0 0 0 0 0 1 0 ... 0 1 0 0 0 0 0 0 1\n",
-       "    heading              (time) float32 -12.52 -12.51 -12.51 ... -12.52 -12.5\n",
-       "    pitch                (time) float32 -0.065 -0.06 -0.06 ... -0.06 -0.05 -0.05\n",
-       "    roll                 (time) float32 -7.425 -7.42 -7.42 ... -6.45 -6.45 -6.45\n",
-       "    beam2inst_orientmat  (x1, x2) float32 1.183 0.0 -1.183 ... 0.5518 0.0 0.5518\n",
+       "    telemetry_data       (time) uint8 55kB 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0\n",
+       "    boost_running        (time) uint8 55kB 0 0 0 0 0 0 0 0 1 ... 1 0 0 0 0 0 0 1\n",
+       "    heading              (time) float32 220kB -12.52 -12.51 ... -12.52 -12.5\n",
+       "    pitch                (time) float32 220kB -0.065 -0.06 -0.06 ... -0.05 -0.05\n",
+       "    roll                 (time) float32 220kB -7.425 -7.42 -7.42 ... -6.45 -6.45\n",
+       "    beam2inst_orientmat  (x1, x2) float32 64B 1.183 0.0 -1.183 ... 0.0 0.5518\n",
        "Attributes: (12/34)\n",
        "    filehead_config:       {\"CLOCKSTR\": {\"TIME\": \"\\\"2020-08-13 13:56:21\\\"\"}, ...\n",
        "    inst_model:            Signature1000\n",
@@ -859,7 +909,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x233ec6a68c0>"
+       "<matplotlib.collections.QuadMesh at 0x1e5bd430460>"
       ]
      },
      "execution_count": 5,
@@ -868,7 +918,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1168,6 +1218,11 @@
        "  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",
@@ -1189,14 +1244,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  display: none;\n",
        "  background-color: var(--xr-background-color) !important;\n",
        "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -1206,13 +1263,16 @@
        "\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-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -1250,7 +1310,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -1259,26 +1320,36 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt;\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;range&#x27; (range: 28)&gt; Size: 224B\n",
        "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
        "       13.2, 13.7, 14.2, 14.7])\n",
        "Coordinates:\n",
-       "  * range    (range) float64 1.2 1.7 2.2 2.7 3.2 ... 12.7 13.2 13.7 14.2 14.7\n",
+       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
        "Attributes:\n",
-       "    units:    m</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-337fe36a-e5b4-4ba7-80cd-f929edbfe174' class='xr-array-in' type='checkbox' checked><label for='section-337fe36a-e5b4-4ba7-80cd-f929edbfe174' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "    units:    m</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'range'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 28</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1d1717ab-da0a-4166-9c6b-fb4c3d7e0007' class='xr-array-in' type='checkbox' checked><label for='section-1d1717ab-da0a-4166-9c6b-fb4c3d7e0007' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.2 1.7 2.2 2.7 3.2 3.7 4.2 4.7 ... 11.7 12.2 12.7 13.2 13.7 14.2 14.7</span></div><div class='xr-array-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-b402e24c-b79a-49fe-acec-c5345fac65fd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b402e24c-b79a-49fe-acec-c5345fac65fd' class='xr-section-summary' >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'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-65fe5f28-3925-45c7-a9b3-151ec63c70f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65fe5f28-3925-45c7-a9b3-151ec63c70f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1975dfb-4d16-4498-b12c-8cda28a55303' class='xr-var-data-in' type='checkbox'><label for='data-b1975dfb-4d16-4498-b12c-8cda28a55303' title='Show/Hide data repr'><svg 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>m</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></div></li><li class='xr-section-item'><input id='section-9a94faa5-80eb-4542-acb7-566bc2201b75' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a94faa5-80eb-4542-acb7-566bc2201b75' class='xr-section-summary' >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'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-944c107d-c0d8-4a7e-bee7-15f2ec8e96c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-944c107d-c0d8-4a7e-bee7-15f2ec8e96c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b38a9ff7-eaba-43f1-9a09-f6adf9df2f1a' class='xr-var-data-in' type='checkbox'><label for='data-b38a9ff7-eaba-43f1-9a09-f6adf9df2f1a' title='Show/Hide data repr'><svg 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>m</dd></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7d1962d-4904-4e43-9889-d0afd4b9e957' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a7d1962d-4904-4e43-9889-d0afd4b9e957' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div></li></ul></div></div>"
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd0c0834-aca9-4140-b41f-785634d58adb' class='xr-section-summary-in' type='checkbox'  ><label for='section-cd0c0834-aca9-4140-b41f-785634d58adb' class='xr-section-summary' >Indexes: <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-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fe0bcbd2-7359-4ecc-a9db-c7f3faa45a3f' class='xr-index-data-in' type='checkbox'/><label for='index-fe0bcbd2-7359-4ecc-a9db-c7f3faa45a3f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+       "                      2.7,                3.2,                3.7,\n",
+       "                      4.2,  4.699999999999999,  5.199999999999999,\n",
+       "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
+       "        7.199999999999999,  7.699999999999999,                8.2,\n",
+       "                      8.7,                9.2,                9.7,\n",
+       "                     10.2,               10.7,               11.2,\n",
+       "                     11.7,               12.2,               12.7,\n",
+       "                     13.2,               13.7,               14.2,\n",
+       "                     14.7],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4912adf3-5cd1-4ca0-a1c6-0800997610ea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4912adf3-5cd1-4ca0-a1c6-0800997610ea' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.DataArray 'range' (range: 28)>\n",
+       "<xarray.DataArray 'range' (range: 28)> Size: 224B\n",
        "array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
        "       13.2, 13.7, 14.2, 14.7])\n",
        "Coordinates:\n",
-       "  * range    (range) float64 1.2 1.7 2.2 2.7 3.2 ... 12.7 13.2 13.7 14.2 14.7\n",
+       "  * range    (range) float64 224B 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
        "Attributes:\n",
        "    units:    m"
       ]
@@ -1324,7 +1395,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x233ed9aab90>"
+       "<matplotlib.collections.QuadMesh at 0x1e5bd746dd0>"
       ]
      },
      "execution_count": 9,
@@ -1333,7 +1404,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1368,7 +1439,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x233818d3b80>"
+       "<matplotlib.collections.QuadMesh at 0x1e5c3dd4340>"
       ]
      },
      "execution_count": 10,
@@ -1377,7 +1448,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1418,7 +1489,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x233819ec820>"
+       "<matplotlib.collections.QuadMesh at 0x1e5c8963d60>"
       ]
      },
      "execution_count": 12,
@@ -1427,7 +1498,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1489,7 +1560,7 @@
    "outputs": [],
    "source": [
     "ds.attrs[\"principal_heading\"] = dolfyn.calc_principal_heading(ds[\"vel\"].mean(\"range\"))\n",
-    "ds_streamwise = dolfyn.rotate2(ds, \"principal\", inplace=False)"
+    "ds = dolfyn.rotate2(ds, \"principal\", inplace=False)"
    ]
   },
   {
@@ -1787,6 +1858,11 @@
        "  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",
@@ -1808,14 +1884,16 @@
        "}\n",
        "\n",
        ".xr-var-attrs,\n",
-       ".xr-var-data {\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
        "  display: none;\n",
        "  background-color: var(--xr-background-color) !important;\n",
        "  padding-bottom: 5px !important;\n",
        "}\n",
        "\n",
        ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
-       ".xr-var-data-in:checked ~ .xr-var-data {\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
        "  display: block;\n",
        "}\n",
        "\n",
@@ -1825,13 +1903,16 @@
        "\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-var-data,\n",
+       ".xr-index-data {\n",
        "  grid-column: 1 / -1;\n",
        "}\n",
        "\n",
@@ -1869,7 +1950,8 @@
        "}\n",
        "\n",
        ".xr-icon-database,\n",
-       ".xr-icon-file-text2 {\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
        "  display: inline-block;\n",
        "  vertical-align: middle;\n",
        "  width: 1em;\n",
@@ -1878,34 +1960,34 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:         (time: 183, dirIMU: 3, range: 28, dir: 4, beam: 4,\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 379kB\n",
+       "Dimensions:         (time: 183, range: 28, dirIMU: 3, dir: 4, beam: 4,\n",
        "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
        "Coordinates:\n",
-       "  * time            (time) datetime64[ns] 2020-08-15T00:22:30.001030683 ... 2...\n",
-       "  * dirIMU          (dirIMU) &lt;U1 &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * range           (range) float64 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-       "  * dir             (dir) &lt;U2 &#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;\n",
-       "  * beam            (beam) int32 1 2 3 4\n",
-       "  * earth           (earth) &lt;U1 &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst            (inst) &lt;U1 &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * q               (q) &lt;U1 &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
-       "  * time_b5         (time_b5) datetime64[ns] 2020-08-15T00:22:29.938495159 .....\n",
-       "  * range_b5        (range_b5) float64 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+       "  * dirIMU          (dirIMU) &lt;U10 120B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;\n",
+       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * dir             (dir) &lt;U10 160B &#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert1&#x27; &#x27;vert2&#x27;\n",
+       "  * beam            (beam) int32 16B 1 2 3 4\n",
+       "  * earth           (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst            (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * q               (q) &lt;U1 16B &#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;\n",
+       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
        "Data variables: (12/38)\n",
-       "    c_sound         (time) float32 1.502e+03 1.502e+03 ... 1.499e+03 1.498e+03\n",
-       "    U_std           (range, time) float32 0.04232 0.04293 0.04402 ... nan nan\n",
-       "    temp            (time) float32 14.49 14.59 14.54 14.45 ... 13.62 13.56 13.5\n",
-       "    pressure        (time) float32 9.712 9.699 9.685 9.67 ... 9.58 9.584 9.591\n",
-       "    mag             (dirIMU, time) float32 72.37 72.4 72.38 ... -197.1 -197.1\n",
-       "    accel           (dirIMU, time) float32 -0.3584 -0.361 ... 9.714 9.712\n",
+       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
        "    ...              ...\n",
-       "    boost_running   (time) float32 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
-       "    heading         (time) float32 3.287 3.261 3.337 3.289 ... 3.331 3.352 3.352\n",
-       "    pitch           (time) float32 -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-       "    roll            (time) float32 -7.414 -7.424 -7.404 ... -6.446 -6.433 -6.436\n",
-       "    water_density   (time) float32 1.023e+03 1.023e+03 ... 1.023e+03 1.023e+03\n",
-       "    depth           (time) float32 10.28 10.26 10.25 10.23 ... 10.14 10.15 10.15\n",
+       "    boost_running   (time) float32 732B 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
+       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
        "Attributes: (12/41)\n",
        "    fs:                        1\n",
        "    n_bin:                     300\n",
@@ -1919,7 +2001,7 @@
        "    h_deploy:                  0.6\n",
        "    declination:               15.8\n",
        "    declination_in_orientmat:  1\n",
-       "    principal_heading:         11.1898</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-133252a1-db9d-47dd-80c3-81e2200ee809' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-133252a1-db9d-47dd-80c3-81e2200ee809' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a5369a3a-1b94-4ce3-b004-3a65374af772' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a5369a3a-1b94-4ce3-b004-3a65374af772' class='xr-section-summary' >Coordinates: <span>(10)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-fdb41928-5f1e-46c5-9914-04780672f479' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fdb41928-5f1e-46c5-9914-04780672f479' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97e5eae9-6bb6-403f-b064-5b736648b9b7' class='xr-var-data-in' type='checkbox'><label for='data-97e5eae9-6bb6-403f-b064-5b736648b9b7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
+       "    principal_heading:         11.1898</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-24a9168a-e50a-4b72-8d65-b3fb4ee7b4b9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-24a9168a-e50a-4b72-8d65-b3fb4ee7b4b9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 183</li><li><span class='xr-has-index'>range</span>: 28</li><li><span class='xr-has-index'>dirIMU</span>: 3</li><li><span class='xr-has-index'>dir</span>: 4</li><li><span class='xr-has-index'>beam</span>: 4</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li><li><span class='xr-has-index'>q</span>: 4</li><li><span class='xr-has-index'>time_b5</span>: 183</li><li><span class='xr-has-index'>range_b5</span>: 28</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9de3af29-a5bf-4333-ad62-b67f8751af1a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9de3af29-a5bf-4333-ad62-b67f8751af1a' class='xr-section-summary' >Coordinates: <span>(10)</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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:30.001030683 .....</div><input id='attrs-3b67a602-8ed5-456f-b36a-60c62bcb1c0f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b67a602-8ed5-456f-b36a-60c62bcb1c0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89b3203b-3155-4067-8254-e40fa82c1769' class='xr-var-data-in' type='checkbox'><label for='data-89b3203b-3155-4067-8254-e40fa82c1769' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;2020-08-15T00:22:30.001030683&#x27;, &#x27;2020-08-15T00:27:30.001019239&#x27;,\n",
        "       &#x27;2020-08-15T00:32:30.001010656&#x27;, &#x27;2020-08-15T00:37:30.001015901&#x27;,\n",
        "       &#x27;2020-08-15T00:42:30.001019954&#x27;, &#x27;2020-08-15T00:47:30.001018524&#x27;,\n",
        "       &#x27;2020-08-15T00:52:30.001013994&#x27;, &#x27;2020-08-15T00:57:30.001026630&#x27;,\n",
@@ -2010,9 +2092,9 @@
        "       &#x27;2020-08-15T15:02:30.001021146&#x27;, &#x27;2020-08-15T15:07:30.001027345&#x27;,\n",
        "       &#x27;2020-08-15T15:12:30.001029014&#x27;, &#x27;2020-08-15T15:17:30.001026630&#x27;,\n",
        "       &#x27;2020-08-15T15:22:30.001026153&#x27;, &#x27;2020-08-15T15:27:30.001022577&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-630d41d2-a6a4-4ecf-a655-09aab3662274' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-630d41d2-a6a4-4ecf-a655-09aab3662274' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e15396ca-0eb3-40ff-88c1-0db03e3534e1' class='xr-var-data-in' type='checkbox'><label for='data-e15396ca-0eb3-40ff-88c1-0db03e3534e1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-9ff69c9e-aca5-4f4c-a5eb-13dab8872801' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9ff69c9e-aca5-4f4c-a5eb-13dab8872801' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a77e00b-3ba3-458b-a60a-90ab42fdf783' class='xr-var-data-in' type='checkbox'><label for='data-7a77e00b-3ba3-458b-a60a-90ab42fdf783' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       &#x27;2020-08-15T15:32:30.001030683&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dirIMU</span></div><div class='xr-var-dims'>(dirIMU)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; &#x27;vert&#x27;</div><input id='attrs-143fda77-e4d1-4ad5-b467-4fec68c6abef' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-143fda77-e4d1-4ad5-b467-4fec68c6abef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82b74b73-627f-486c-b55c-7018d1768a87' class='xr-var-data-in' type='checkbox'><label for='data-82b74b73-627f-486c-b55c-7018d1768a87' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;&lt;U10&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-49509cc5-cb9d-4ac2-a6e9-7a06263e213b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-49509cc5-cb9d-4ac2-a6e9-7a06263e213b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-25150aa9-129f-407b-b0f9-7ed6b7241779' class='xr-var-data-in' type='checkbox'><label for='data-25150aa9-129f-407b-b0f9-7ed6b7241779' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U1&#x27; &#x27;U2&#x27;</div><input id='attrs-2acb6330-5418-4cd4-be5b-fe9d29e57a29' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2acb6330-5418-4cd4-be5b-fe9d29e57a29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3536fa4-69ed-4ef4-b24e-41c1865b0c67' class='xr-var-data-in' type='checkbox'><label for='data-a3536fa4-69ed-4ef4-b24e-41c1865b0c67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;E&#x27;, &#x27;N&#x27;, &#x27;U1&#x27;, &#x27;U2&#x27;], dtype=&#x27;&lt;U2&#x27;)</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-223045f9-f93d-4c22-8fc4-390d06fd70e2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-223045f9-f93d-4c22-8fc4-390d06fd70e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc01cac6-4b47-48c6-ac17-63573baa177a' class='xr-var-data-in' type='checkbox'><label for='data-bc01cac6-4b47-48c6-ac17-63573baa177a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-dfa06d5c-96d9-4ccd-805f-daae54a85c00' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfa06d5c-96d9-4ccd-805f-daae54a85c00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-05673cc4-d554-461e-805c-8bef3272b725' class='xr-var-data-in' type='checkbox'><label for='data-05673cc4-d554-461e-805c-8bef3272b725' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-0423372a-10e9-4759-9828-9388c895160e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0423372a-10e9-4759-9828-9388c895160e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-563998dd-52ec-473c-a653-f49cf371ddf4' class='xr-var-data-in' type='checkbox'><label for='data-563998dd-52ec-473c-a653-f49cf371ddf4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-4a0ba938-b3b3-4f65-b0d7-6efecdb8a972' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4a0ba938-b3b3-4f65-b0d7-6efecdb8a972' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1660104-f5c2-4a82-8d04-3e28913408ee' class='xr-var-data-in' type='checkbox'><label for='data-f1660104-f5c2-4a82-8d04-3e28913408ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-3140f7f1-be97-4592-a853-cdef163c4a62' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3140f7f1-be97-4592-a853-cdef163c4a62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26835414-a4d0-49d6-b9a2-82aec4a3bd42' class='xr-var-data-in' type='checkbox'><label for='data-26835414-a4d0-49d6-b9a2-82aec4a3bd42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U10</div><div class='xr-var-preview xr-preview'>&#x27;streamwise&#x27; &#x27;x-stream&#x27; ... &#x27;vert2&#x27;</div><input id='attrs-1700075c-cb8d-4c8f-a673-36cd24a92791' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1700075c-cb8d-4c8f-a673-36cd24a92791' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9678757c-3ab6-4414-922c-d2adc697c584' class='xr-var-data-in' type='checkbox'><label for='data-9678757c-3ab6-4414-922c-d2adc697c584' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;&lt;U10&#x27;)</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 4</div><input id='attrs-75ad63ff-eb84-4045-a10d-bbb8f80fce7b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-75ad63ff-eb84-4045-a10d-bbb8f80fce7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da86c10d-fbb9-4dfa-a8c0-df8a07138e48' class='xr-var-data-in' type='checkbox'><label for='data-da86c10d-fbb9-4dfa-a8c0-df8a07138e48' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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, 2, 3, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-86c883cf-96e4-4975-b058-d0f7e8b63828' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86c883cf-96e4-4975-b058-d0f7e8b63828' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60798250-2d7a-43f1-8e08-b01b95f48fc4' class='xr-var-data-in' type='checkbox'><label for='data-60798250-2d7a-43f1-8e08-b01b95f48fc4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-346e0250-bb61-4d28-ae72-8bdb7eaa70ad' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-346e0250-bb61-4d28-ae72-8bdb7eaa70ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0d2fe5a-fde1-4c84-a503-8ba4dc49895b' class='xr-var-data-in' type='checkbox'><label for='data-e0d2fe5a-fde1-4c84-a503-8ba4dc49895b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>q</span></div><div class='xr-var-dims'>(q)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;w&#x27; &#x27;x&#x27; &#x27;y&#x27; &#x27;z&#x27;</div><input id='attrs-b5bf7a2f-e1a8-403f-92eb-c6d62b6f9b91' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b5bf7a2f-e1a8-403f-92eb-c6d62b6f9b91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e84229a2-9047-462f-9939-5d6c4b2c3e44' class='xr-var-data-in' type='checkbox'><label for='data-e84229a2-9047-462f-9939-5d6c4b2c3e44' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-15T00:22:29.938495159 .....</div><input id='attrs-cec794f2-d07d-4d65-9696-c98959766600' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cec794f2-d07d-4d65-9696-c98959766600' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b068603-d5dc-4064-9ee5-003412f97296' class='xr-var-data-in' type='checkbox'><label for='data-3b068603-d5dc-4064-9ee5-003412f97296' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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;2020-08-15T00:22:29.938495159&#x27;, &#x27;2020-08-15T00:27:29.938490867&#x27;,\n",
        "       &#x27;2020-08-15T00:32:29.938487529&#x27;, &#x27;2020-08-15T00:37:29.938496828&#x27;,\n",
        "       &#x27;2020-08-15T00:42:29.938495397&#x27;, &#x27;2020-08-15T00:47:29.938496589&#x27;,\n",
        "       &#x27;2020-08-15T00:52:29.938497781&#x27;, &#x27;2020-08-15T00:57:29.938495397&#x27;,\n",
@@ -2103,9 +2185,9 @@
        "       &#x27;2020-08-15T15:02:29.938493013&#x27;, &#x27;2020-08-15T15:07:29.938493967&#x27;,\n",
        "       &#x27;2020-08-15T15:12:29.938494920&#x27;, &#x27;2020-08-15T15:17:29.938493251&#x27;,\n",
        "       &#x27;2020-08-15T15:22:29.938486099&#x27;, &#x27;2020-08-15T15:27:29.938484191&#x27;,\n",
-       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-df7f4375-55de-4281-ae37-b213609a5c10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-df7f4375-55de-4281-ae37-b213609a5c10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0980afa7-8f1b-4f62-b1c2-d658bfd89b6d' class='xr-var-data-in' type='checkbox'><label for='data-0980afa7-8f1b-4f62-b1c2-d658bfd89b6d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
+       "       &#x27;2020-08-15T15:32:29.938490390&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range_b5</span></div><div class='xr-var-dims'>(range_b5)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7</div><input id='attrs-625a3ba2-a836-43a0-bd5b-a1736ea66f14' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-625a3ba2-a836-43a0-bd5b-a1736ea66f14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-941f9697-ce24-4fd6-b317-1fc23c3a8ed1' class='xr-var-data-in' type='checkbox'><label for='data-941f9697-ce24-4fd6-b317-1fc23c3a8ed1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([ 1.2,  1.7,  2.2,  2.7,  3.2,  3.7,  4.2,  4.7,  5.2,  5.7,  6.2,  6.7,\n",
        "        7.2,  7.7,  8.2,  8.7,  9.2,  9.7, 10.2, 10.7, 11.2, 11.7, 12.2, 12.7,\n",
-       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-38ce552b-2d5d-4e63-af27-e6f81fcf524f' class='xr-section-summary-in' type='checkbox'  ><label for='section-38ce552b-2d5d-4e63-af27-e6f81fcf524f' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-594a5249-7a80-4e54-9145-2b86c7b2566e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-594a5249-7a80-4e54-9145-2b86c7b2566e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7d4124f-3c9c-4cd0-8064-fa2153cb7c8e' class='xr-var-data-in' type='checkbox'><label for='data-c7d4124f-3c9c-4cd0-8064-fa2153cb7c8e' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
+       "       13.2, 13.7, 14.2, 14.7])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f6679327-e34e-4b0b-b79e-9929d0eafe8f' class='xr-section-summary-in' type='checkbox'  ><label for='section-f6679327-e34e-4b0b-b79e-9929d0eafe8f' class='xr-section-summary' >Data variables: <span>(38)</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>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.502e+03 1.502e+03 ... 1.498e+03</div><input id='attrs-ee9af3f1-37ee-44e3-85cf-9013e1efced0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ee9af3f1-37ee-44e3-85cf-9013e1efced0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2da66abe-36dd-4215-bd56-7b8a5448f47e' class='xr-var-data-in' type='checkbox'><label for='data-2da66abe-36dd-4215-bd56-7b8a5448f47e' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1501.6843, 1502.032 , 1501.8505, 1501.5714, 1501.8607, 1502.4133,\n",
        "       1502.8121, 1502.7344, 1502.8704, 1502.9467, 1502.883 , 1502.7606,\n",
        "       1502.6915, 1502.8214, 1502.8864, 1502.7937, 1502.6268, 1502.6473,\n",
        "       1502.4198, 1502.3577, 1501.9543, 1501.729 , 1501.32  , 1500.9684,\n",
@@ -2135,19 +2217,19 @@
        "       1499.5286, 1499.5846, 1499.6293, 1499.6262, 1499.6666, 1499.6971,\n",
        "       1499.6998, 1499.7269, 1499.7843, 1499.6895, 1499.7037, 1499.6376,\n",
        "       1499.4894, 1499.0636, 1499.0073, 1498.8967, 1498.8627, 1498.961 ,\n",
-       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-6e725727-8910-4037-bb72-52c44c616a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6e725727-8910-4037-bb72-52c44c616a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-688e6457-2f22-43fa-b23e-fdb786dd000b' class='xr-var-data-in' type='checkbox'><label for='data-688e6457-2f22-43fa-b23e-fdb786dd000b' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380287, 0.04201568,\n",
+       "       1498.8287, 1498.6285, 1498.472 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>U_std</span></div><div class='xr-var-dims'>(range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.04232 0.04293 0.04402 ... nan nan</div><input id='attrs-24ef185e-bccd-4e8d-bef0-e1d725949a07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-24ef185e-bccd-4e8d-bef0-e1d725949a07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97288b7c-b762-4fa5-b327-648ac9c5e2f7' class='xr-var-data-in' type='checkbox'><label for='data-97288b7c-b762-4fa5-b327-648ac9c5e2f7' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity Standard Deviation</dd></dl></div><div class='xr-var-data'><pre>array([[0.04231985, 0.04293143, 0.04401674, ..., 0.04380286, 0.04201568,\n",
        "        0.0463443 ],\n",
        "       [0.04002878, 0.04084466, 0.03949426, ..., 0.04000184, 0.04028782,\n",
        "        0.03873245],\n",
        "       [0.04025545, 0.03514179, 0.04270847, ..., 0.0391249 , 0.03997382,\n",
-       "        0.04237254],\n",
+       "        0.04237255],\n",
        "       ...,\n",
        "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
        "               nan],\n",
        "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
        "               nan],\n",
        "       [       nan,        nan,        nan, ...,        nan,        nan,\n",
-       "               nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-b2ece7b5-2dfe-43ef-a7dd-faa61ebdae67' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2ece7b5-2dfe-43ef-a7dd-faa61ebdae67' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66ea1821-c8c5-4ac0-8d49-1f7e286475a0' class='xr-var-data-in' type='checkbox'><label for='data-66ea1821-c8c5-4ac0-8d49-1f7e286475a0' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
+       "               nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>14.49 14.59 14.54 ... 13.56 13.5</div><input id='attrs-a1624476-69b9-4c22-a35c-3870c353b83e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1624476-69b9-4c22-a35c-3870c353b83e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1874653-a5d6-4c2d-9608-60a3a8d550fe' class='xr-var-data-in' type='checkbox'><label for='data-e1874653-a5d6-4c2d-9608-60a3a8d550fe' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([14.4871   , 14.592732 , 14.5369   , 14.450967 , 14.540566 ,\n",
        "       14.712167 , 14.838034 , 14.812099 , 14.855833 , 14.879432 ,\n",
        "       14.860366 , 14.821934 , 14.799266 , 14.840433 , 14.8621   ,\n",
        "       14.833766 , 14.782434 , 14.788966 , 14.716966 , 14.695799 ,\n",
@@ -2183,7 +2265,7 @@
        "       13.860667 , 13.870465 , 13.876833 , 13.878232 , 13.884268 ,\n",
        "       13.907367 , 13.875599 , 13.875534 , 13.861733 , 13.8139   ,\n",
        "       13.689401 , 13.665034 , 13.632333 , 13.6227665, 13.651935 ,\n",
-       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-bfe04067-aa5a-44ca-ad05-697740086330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfe04067-aa5a-44ca-ad05-697740086330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c50795c-9d1f-4adb-af9d-b3f5d569be74' class='xr-var-data-in' type='checkbox'><label for='data-1c50795c-9d1f-4adb-af9d-b3f5d569be74' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
+       "       13.6164665, 13.5551   , 13.503766 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.712 9.699 9.685 ... 9.584 9.591</div><input id='attrs-b963fab3-c80d-4250-afd4-3f07d7f5d420' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b963fab3-c80d-4250-afd4-3f07d7f5d420' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99e9861d-150a-431f-9048-e67de611ee34' class='xr-var-data-in' type='checkbox'><label for='data-99e9861d-150a-431f-9048-e67de611ee34' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([9.712007 , 9.699074 , 9.685317 , 9.670219 , 9.65324  , 9.640334 ,\n",
        "       9.62429  , 9.608537 , 9.594397 , 9.576526 , 9.56048  , 9.541069 ,\n",
        "       9.524289 , 9.505187 , 9.486143 , 9.464264 , 9.44223  , 9.416344 ,\n",
        "       9.393453 , 9.367396 , 9.339387 , 9.305754 , 9.278394 , 9.245257 ,\n",
@@ -2213,66 +2295,66 @@
        "       9.35049  , 9.37106  , 9.393917 , 9.40948  , 9.428807 , 9.441616 ,\n",
        "       9.459889 , 9.474596 , 9.488944 , 9.495657 , 9.510249 , 9.520061 ,\n",
        "       9.530423 , 9.537613 , 9.546494 , 9.554764 , 9.561024 , 9.57158  ,\n",
-       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.37 72.4 72.38 ... -197.1 -197.1</div><input id='attrs-7bac8a1b-bdfb-4301-8aa8-b554031cff64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bac8a1b-bdfb-4301-8aa8-b554031cff64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-665fea40-a1e1-4443-a8b5-63cb277fd624' class='xr-var-data-in' type='checkbox'><label for='data-665fea40-a1e1-4443-a8b5-63cb277fd624' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.37276  ,   72.39944  ,   72.379776 ,   72.385994 ,\n",
-       "          72.37942  ,   72.413605 ,   72.43177  ,   72.45011  ,\n",
-       "          72.497116 ,   72.43014  ,   72.43194  ,   72.453735 ,\n",
-       "          72.393135 ,   72.4087   ,   72.404724 ,   72.42861  ,\n",
-       "          72.393326 ,   72.363205 ,   72.392334 ,   72.388245 ,\n",
-       "          72.39355  ,   72.44057  ,   72.41888  ,   72.39863  ,\n",
-       "          72.40431  ,   72.41865  ,   72.40508  ,   72.42549  ,\n",
-       "          72.41292  ,   72.387764 ,   72.40756  ,   72.396706 ,\n",
-       "          72.39646  ,   72.402664 ,   72.41777  ,   72.41947  ,\n",
-       "          72.39687  ,   72.39169  ,   72.37803  ,   72.40297  ,\n",
-       "          72.38656  ,   72.37699  ,   72.40961  ,   72.39296  ,\n",
-       "          72.397285 ,   72.37472  ,   72.374695 ,   72.389854 ,\n",
-       "          72.383575 ,   72.35983  ,   72.31869  ,   72.175354 ,\n",
-       "          71.82848  ,   71.07719  ,   71.10654  ,   71.18123  ,\n",
-       "          71.24618  ,   71.2752   ,   71.330826 ,   71.34357  ,\n",
-       "          71.396454 ,   71.38987  ,   71.39448  ,   71.407166 ,\n",
-       "          71.389885 ,   71.37225  ,   71.32909  ,   71.28221  ,\n",
-       "          71.28164  ,   71.288185 ,   71.287834 ,   71.3075   ,\n",
-       "          71.28308  ,   71.29063  ,   71.31972  ,   71.293915 ,\n",
-       "          71.288826 ,   71.33092  ,   71.2929   ,   71.31854  ,\n",
+       "       9.579874 , 9.583782 , 9.591404 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.534 3.565 3.547 ... -197.1 -197.1</div><input id='attrs-efd178f3-6ca8-41a1-994c-38167a1817d7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-efd178f3-6ca8-41a1-994c-38167a1817d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9faeebf4-87a0-4296-a297-82cb168d2390' class='xr-var-data-in' type='checkbox'><label for='data-9faeebf4-87a0-4296-a297-82cb168d2390' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.53383756e+00,  3.56493616e+00,  3.54652500e+00,\n",
+       "         3.60746217e+00,  3.56795740e+00,  3.58543801e+00,\n",
+       "         3.56357932e+00,  3.57667375e+00,  3.60632110e+00,\n",
+       "         3.56949067e+00,  3.57479191e+00,  3.59876704e+00,\n",
+       "         3.60281277e+00,  3.59981132e+00,  3.59064221e+00,\n",
+       "         3.59985065e+00,  3.58579135e+00,  3.57373095e+00,\n",
+       "         3.56544805e+00,  3.58115005e+00,  3.58714008e+00,\n",
+       "         3.55944085e+00,  3.58880138e+00,  3.53171968e+00,\n",
+       "         3.53358531e+00,  3.49057865e+00,  3.49481201e+00,\n",
+       "         3.49612260e+00,  3.45677161e+00,  3.42318916e+00,\n",
+       "         3.46062565e+00,  3.41326356e+00,  3.41770315e+00,\n",
+       "         3.41921186e+00,  3.43796849e+00,  3.42292285e+00,\n",
+       "         3.41392589e+00,  3.38415337e+00,  3.38218045e+00,\n",
+       "         3.43648410e+00,  3.38592434e+00,  3.34218669e+00,\n",
+       "         3.38532972e+00,  3.37350154e+00,  3.37754130e+00,\n",
+       "         3.35902476e+00,  3.34339833e+00,  3.35676146e+00,\n",
+       "         3.35692787e+00,  3.32560086e+00,  3.27195215e+00,\n",
+       "         3.19083190e+00,  2.95882225e+00,  2.40057945e+00,\n",
+       "         2.16090226e+00,  1.92318320e+00,  1.78795326e+00,\n",
+       "         1.62216687e+00,  1.56376326e+00,  1.46418214e+00,\n",
        "...\n",
-       "        -197.21553  , -197.21751  , -197.22519  , -197.14384  ,\n",
-       "        -197.12587  , -197.08485  , -197.14752  , -197.10484  ,\n",
-       "        -197.15018  , -197.15317  , -197.07553  , -197.09618  ,\n",
-       "        -197.0675   , -197.14017  , -197.06787  , -197.04951  ,\n",
-       "        -197.02983  , -197.08884  , -197.03487  , -196.9825   ,\n",
-       "        -197.06119  , -196.96985  , -197.07654  , -197.00719  ,\n",
-       "        -197.02817  , -197.0062   , -197.02751  , -197.02917  ,\n",
-       "        -196.98051  , -197.01917  , -196.93985  , -196.97984  ,\n",
-       "        -197.03218  , -197.0382   , -196.94284  , -196.95952  ,\n",
-       "        -196.9862   , -197.05684  , -197.04985  , -197.02686  ,\n",
-       "        -197.0412   , -197.01653  , -197.08452  , -197.0775   ,\n",
-       "        -197.03215  , -197.06151  , -197.07985  , -197.10185  ,\n",
-       "        -197.09286  , -197.06216  , -197.11885  , -197.04451  ,\n",
-       "        -197.03217  , -197.1122   , -196.9955   , -197.1032   ,\n",
-       "        -197.1312   , -197.1472   , -197.07986  , -197.05353  ,\n",
-       "        -197.1255   , -197.13284  , -197.11485  , -197.07483  ,\n",
-       "        -197.08583  , -197.11584  , -197.09117  , -197.04416  ,\n",
-       "        -197.06387  , -197.09052  , -197.1295   , -197.00752  ,\n",
-       "        -197.01785  , -197.01918  , -197.12917  , -197.05185  ,\n",
-       "        -197.11319  , -197.1045   , -197.05385  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3584 -0.361 ... 9.714 9.712</div><input id='attrs-0511766b-a9a7-49b5-805e-491eb3a60a64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0511766b-a9a7-49b5-805e-491eb3a60a64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-48fda031-3b8e-46ab-84bc-e605d29176a6' class='xr-var-data-in' type='checkbox'><label for='data-48fda031-3b8e-46ab-84bc-e605d29176a6' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.3583813 , -0.36095354, -0.3586304 , -0.3615403 , -0.35910898,\n",
-       "        -0.36007115, -0.36138585, -0.36137566, -0.36312702, -0.3628571 ,\n",
-       "        -0.36111298, -0.35912383, -0.35871395, -0.35686025, -0.35600632,\n",
-       "        -0.3580915 , -0.35734007, -0.35655504, -0.35646495, -0.35440227,\n",
-       "        -0.35520774, -0.35521087, -0.35604593, -0.35715908, -0.3571033 ,\n",
-       "        -0.3572797 , -0.35901397, -0.35533723, -0.35553253, -0.3546862 ,\n",
-       "        -0.35518298, -0.35690856, -0.35472938, -0.35351488, -0.35387543,\n",
-       "        -0.3522955 , -0.35259438, -0.35834682, -0.3595332 , -0.3579652 ,\n",
-       "        -0.3515998 , -0.35857135, -0.36160937, -0.35880914, -0.35967997,\n",
-       "        -0.35572523, -0.354747  , -0.3551024 , -0.35315   , -0.35283983,\n",
-       "        -0.35212258, -0.34319022, -0.32654375, -0.2898494 , -0.2918526 ,\n",
-       "        -0.29504374, -0.29746693, -0.30366912, -0.3048887 , -0.3074294 ,\n",
-       "        -0.30918396, -0.3085442 , -0.30818594, -0.30854064, -0.31013522,\n",
-       "        -0.30655888, -0.30489627, -0.30191606, -0.30468383, -0.30443975,\n",
-       "        -0.30279434, -0.30334118, -0.30303195, -0.30213812, -0.30150205,\n",
-       "        -0.3009241 , -0.30365583, -0.30313265, -0.3035156 , -0.30803263,\n",
-       "        -0.3059543 , -0.30314606, -0.30877426, -0.31135118, -0.30889177,\n",
-       "        -0.3108897 , -0.3081447 , -0.31029397, -0.31278497, -0.31324694,\n",
-       "        -0.30974877, -0.30842015, -0.3083677 , -0.30897394, -0.3092844 ,\n",
-       "        -0.31059873, -0.31130144, -0.30800703, -0.31059355, -0.31043693,\n",
+       "        -1.96982498e+02, -1.97061188e+02, -1.96969849e+02,\n",
+       "        -1.97076538e+02, -1.97007187e+02, -1.97028168e+02,\n",
+       "        -1.97006195e+02, -1.97027512e+02, -1.97029175e+02,\n",
+       "        -1.96980515e+02, -1.97019165e+02, -1.96939850e+02,\n",
+       "        -1.96979843e+02, -1.97032181e+02, -1.97038193e+02,\n",
+       "        -1.96942841e+02, -1.96959518e+02, -1.96986206e+02,\n",
+       "        -1.97056839e+02, -1.97049850e+02, -1.97026855e+02,\n",
+       "        -1.97041199e+02, -1.97016525e+02, -1.97084518e+02,\n",
+       "        -1.97077499e+02, -1.97032150e+02, -1.97061508e+02,\n",
+       "        -1.97079849e+02, -1.97101852e+02, -1.97092865e+02,\n",
+       "        -1.97062164e+02, -1.97118851e+02, -1.97044510e+02,\n",
+       "        -1.97032166e+02, -1.97112198e+02, -1.96995499e+02,\n",
+       "        -1.97103195e+02, -1.97131195e+02, -1.97147202e+02,\n",
+       "        -1.97079865e+02, -1.97053528e+02, -1.97125504e+02,\n",
+       "        -1.97132843e+02, -1.97114853e+02, -1.97074829e+02,\n",
+       "        -1.97085831e+02, -1.97115845e+02, -1.97091171e+02,\n",
+       "        -1.97044159e+02, -1.97063873e+02, -1.97090515e+02,\n",
+       "        -1.97129501e+02, -1.97007523e+02, -1.97017853e+02,\n",
+       "        -1.97019180e+02, -1.97129166e+02, -1.97051849e+02,\n",
+       "        -1.97113190e+02, -1.97104507e+02, -1.97053848e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.261 -1.263 -1.26 ... 9.714 9.712</div><input id='attrs-6330f27c-206e-4470-8b8b-7ef730db6453' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6330f27c-206e-4470-8b8b-7ef730db6453' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51b9cbf4-6c82-496d-93e5-d7c16f9cf03b' class='xr-var-data-in' type='checkbox'><label for='data-51b9cbf4-6c82-496d-93e5-d7c16f9cf03b' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2608225 , -1.2632061 , -1.2602278 , -1.2620431 , -1.2610018 ,\n",
+       "        -1.2613868 , -1.2610567 , -1.2621608 , -1.2631991 , -1.2639122 ,\n",
+       "        -1.2618903 , -1.2588229 , -1.2596216 , -1.258702  , -1.2583325 ,\n",
+       "        -1.2578007 , -1.2583394 , -1.2576338 , -1.2579145 , -1.2534361 ,\n",
+       "        -1.256856  , -1.2559422 , -1.255704  , -1.257189  , -1.2556211 ,\n",
+       "        -1.2540294 , -1.2548383 , -1.2532485 , -1.2525107 , -1.251199  ,\n",
+       "        -1.2522614 , -1.2561744 , -1.2530836 , -1.2531875 , -1.2519903 ,\n",
+       "        -1.2518218 , -1.2511965 , -1.2544034 , -1.2561861 , -1.2536182 ,\n",
+       "        -1.2504781 , -1.2535783 , -1.2560769 , -1.2559297 , -1.257113  ,\n",
+       "        -1.2519605 , -1.2501055 , -1.2515697 , -1.2483989 , -1.2508361 ,\n",
+       "        -1.2479837 , -1.2430646 , -1.2314411 , -1.2083212 , -1.1935245 ,\n",
+       "        -1.1852744 , -1.1747023 , -1.1735051 , -1.1686733 , -1.1616861 ,\n",
+       "        -1.1579937 , -1.1570411 , -1.1541711 , -1.1540251 , -1.1536013 ,\n",
+       "        -1.1516274 , -1.147889  , -1.1449584 , -1.1449729 , -1.14322   ,\n",
+       "        -1.1418626 , -1.1392603 , -1.1384714 , -1.136121  , -1.1344364 ,\n",
+       "        -1.1327039 , -1.1329333 , -1.13291   , -1.1309721 , -1.1331373 ,\n",
+       "        -1.1304799 , -1.1283726 , -1.1294135 , -1.132449  , -1.1283007 ,\n",
+       "        -1.1297873 , -1.1291261 , -1.1277461 , -1.1284394 , -1.1265594 ,\n",
+       "        -1.1229206 , -1.1222471 , -1.1207403 , -1.1196108 , -1.1196036 ,\n",
+       "        -1.1186634 , -1.1185873 , -1.1168755 , -1.1150851 , -1.1146262 ,\n",
        "...\n",
        "         9.716357  ,  9.717475  ,  9.7163725 ,  9.718896  ,  9.715463  ,\n",
        "         9.711328  ,  9.713147  ,  9.713642  ,  9.712924  ,  9.715383  ,\n",
@@ -2293,7 +2375,7 @@
        "         9.714537  ,  9.71484   ,  9.714376  ,  9.71848   ,  9.7165    ,\n",
        "         9.715718  ,  9.711742  ,  9.710465  ,  9.712621  ,  9.713371  ,\n",
        "         9.715622  ,  9.71599   ,  9.711598  ,  9.71219   ,  9.71021   ,\n",
-       "         9.712365  ,  9.7141695 ,  9.711615  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-d04dba24-8113-408c-9da0-f431c3c9941b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d04dba24-8113-408c-9da0-f431c3c9941b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bfb5c49a-80a7-4ec2-94fb-f2fe6ef00ccd' class='xr-var-data-in' type='checkbox'><label for='data-bfb5c49a-80a7-4ec2-94fb-f2fe6ef00ccd' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
+       "         9.712365  ,  9.7141695 ,  9.711615  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.48 16.48 16.48 ... 16.26 16.26</div><input id='attrs-1ff13f0a-07aa-4d36-9fbe-4fcd6a93bd0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ff13f0a-07aa-4d36-9fbe-4fcd6a93bd0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-244b1da6-6100-418d-9c46-f4ad2ae54af3' class='xr-var-data-in' type='checkbox'><label for='data-244b1da6-6100-418d-9c46-f4ad2ae54af3' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd><dt><span>standard_name :</span></dt><dd>battery_voltage</dd></dl></div><div class='xr-var-data'><pre>array([16.481167, 16.478   , 16.478   , 16.477167, 16.481   , 16.484167,\n",
        "       16.477167, 16.479834, 16.479166, 16.482666, 16.478167, 16.481668,\n",
        "       16.479668, 16.475334, 16.479668, 16.479   , 16.474   , 16.475334,\n",
        "       16.477667, 16.473167, 16.472168, 16.468334, 16.472334, 16.471169,\n",
@@ -2323,7 +2405,7 @@
        "       16.258333, 16.262335, 16.262169, 16.2575  , 16.261   , 16.260332,\n",
        "       16.25633 , 16.257998, 16.258333, 16.253334, 16.257998, 16.257332,\n",
        "       16.253166, 16.256998, 16.256998, 16.252666, 16.256998, 16.256998,\n",
-       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-591e10df-84b1-4914-84be-22f73c94bb87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-591e10df-84b1-4914-84be-22f73c94bb87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3daf7e3-e4e8-4ab1-8eeb-30463eb02ebd' class='xr-var-data-in' type='checkbox'><label for='data-f3daf7e3-e4e8-4ab1-8eeb-30463eb02ebd' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
+       "       16.252666, 16.256998, 16.256998], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_clock</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.0 20.0 20.0 ... 19.5 19.5 19.5</div><input id='attrs-21ac5ef8-df5d-4522-a48e-88e57d460f3d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21ac5ef8-df5d-4522-a48e-88e57d460f3d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87f0146b-fd24-421c-92f4-24ec702376b0' class='xr-var-data-in' type='checkbox'><label for='data-87f0146b-fd24-421c-92f4-24ec702376b0' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Internal Clock Temperature</dd></dl></div><div class='xr-var-data'><pre>array([20.      , 20.      , 20.      , 20.043333, 20.25    , 20.25    ,\n",
        "       20.25    , 20.25    , 20.263334, 20.446667, 20.5     , 20.5     ,\n",
        "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.5     ,\n",
        "       20.5     , 20.5     , 20.5     , 20.5     , 20.5     , 20.31    ,\n",
@@ -2353,7 +2435,7 @@
        "       19.5     , 19.5     , 19.5     , 19.5     , 19.5     , 19.53    ,\n",
        "       19.696667, 19.75    , 19.75    , 19.75    , 19.75    , 19.75    ,\n",
        "       19.75    , 19.75    , 19.71    , 19.5     , 19.5     , 19.5     ,\n",
-       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-da80209a-8954-4229-bcf3-d43fb6717038' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da80209a-8954-4229-bcf3-d43fb6717038' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11467ab6-60d2-49cb-8a47-65bf192fc0eb' class='xr-var-data-in' type='checkbox'><label for='data-11467ab6-60d2-49cb-8a47-65bf192fc0eb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       19.5     , 19.5     , 19.5     ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-6bb20e51-0e58-4760-8ee8-2f9a5f54bbd1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6bb20e51-0e58-4760-8ee8-2f9a5f54bbd1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffc6b10e-f92b-4762-ad0a-2ef41a0518ec' class='xr-var-data-in' type='checkbox'><label for='data-ffc6b10e-f92b-4762-ad0a-2ef41a0518ec' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2363,7 +2445,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-25b24123-0764-4422-b108-8ffd07bc603c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25b24123-0764-4422-b108-8ffd07bc603c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2b21dc9-f732-4f21-8bc8-6da2252cf46e' class='xr-var-data-in' type='checkbox'><label for='data-e2b21dc9-f732-4f21-8bc8-6da2252cf46e' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-3b8bf732-c1af-4894-a612-9298de633c92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b8bf732-c1af-4894-a612-9298de633c92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a99ddb22-ffc4-49c2-819f-72c0e8170d1d' class='xr-var-data-in' type='checkbox'><label for='data-a99ddb22-ffc4-49c2-819f-72c0e8170d1d' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2403,12 +2485,12 @@
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
        "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09, 1.05355699e+09,\n",
-       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.02006 0.008163 ... nan nan</div><input id='attrs-78e9ac18-eb45-415e-bedb-bb71f4ee7f24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78e9ac18-eb45-415e-bedb-bb71f4ee7f24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5273878d-ad39-4714-a056-e051f22c7dc2' class='xr-var-data-in' type='checkbox'><label for='data-5273878d-ad39-4714-a056-e051f22c7dc2' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.02006463,  0.00816293,  0.01909002, ..., -0.09305979,\n",
-       "         -0.0984674 , -0.10511392],\n",
-       "        [-0.01089326, -0.02103911, -0.00067545, ..., -0.11341628,\n",
-       "         -0.11851331, -0.1263721 ],\n",
-       "        [-0.03483021, -0.04424361, -0.01815725, ..., -0.12064628,\n",
-       "         -0.12672515, -0.14047326],\n",
+       "       1.05355699e+09, 1.05355699e+09, 1.05355699e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.2358 0.266 0.3007 ... nan nan nan</div><input id='attrs-3427ab73-c08b-44cf-b01c-bf2c12f30b3a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3427ab73-c08b-44cf-b01c-bf2c12f30b3a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ae45ab-16ae-4954-b799-efdd57f0f190' class='xr-var-data-in' type='checkbox'><label for='data-77ae45ab-16ae-4954-b799-efdd57f0f190' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.23582192,  0.2660148 ,  0.30069652, ..., -0.179669  ,\n",
+       "         -0.18383324, -0.17606331],\n",
+       "        [ 0.25633767,  0.28601688,  0.3117814 , ..., -0.19580415,\n",
+       "         -0.19696543, -0.20011853],\n",
+       "        [ 0.26504937,  0.28428233,  0.31169885, ..., -0.2103943 ,\n",
+       "         -0.21627884, -0.21236075],\n",
        "        ...,\n",
        "        [        nan,         nan,         nan, ...,         nan,\n",
        "                 nan,         nan],\n",
@@ -2417,12 +2499,12 @@
        "        [        nan,         nan,         nan, ...,         nan,\n",
        "                 nan,         nan]],\n",
        "\n",
-       "       [[ 0.23642264,  0.26955506,  0.30274722, ..., -0.16474162,\n",
-       "         -0.16791683, -0.15868153],\n",
-       "        [ 0.26346007,  0.29572147,  0.31795695, ..., -0.17716254,\n",
-       "         -0.17733802, -0.17899759],\n",
-       "        [ 0.2770758 ,  0.29854363,  0.32133105, ..., -0.19060518,\n",
-       "         -0.19540122, -0.18868756],\n",
+       "       [[ 0.02619691,  0.04430203,  0.04002393, ...,  0.05932099,\n",
+       "          0.06400961,  0.07232199],\n",
+       "        [ 0.06181316,  0.07802678,  0.06236525, ...,  0.0768801 ,\n",
+       "          0.08184617,  0.0892335 ],\n",
+       "        [ 0.08793733,  0.10133781,  0.08016948, ...,  0.08136398,\n",
+       "          0.08639657,  0.10118616],\n",
        "...\n",
        "        [        nan,         nan,         nan, ...,         nan,\n",
        "                 nan,         nan],\n",
@@ -2443,7 +2525,7 @@
        "        [        nan,         nan,         nan, ...,         nan,\n",
        "                 nan,         nan],\n",
        "        [        nan,         nan,         nan, ...,         nan,\n",
-       "                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-75f7aac9-9789-4120-8400-6f22e4c4c6d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75f7aac9-9789-4120-8400-6f22e4c4c6d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f62c6d36-cbdb-432c-a16b-7f0cd9251f09' class='xr-var-data-in' type='checkbox'><label for='data-f62c6d36-cbdb-432c-a16b-7f0cd9251f09' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
+       "                 nan,         nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>79.95 80.28 80.69 ... nan nan nan</div><input id='attrs-69fdf4be-5045-45a7-8577-774e88dc409e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69fdf4be-5045-45a7-8577-774e88dc409e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b3337a6-e7ce-42e9-ad92-68f2fadf14b6' class='xr-var-data-in' type='checkbox'><label for='data-7b3337a6-e7ce-42e9-ad92-68f2fadf14b6' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[79.94666 , 80.28167 , 80.68667 , ..., 81.721664, 81.80334 ,\n",
        "         81.68667 ],\n",
        "        [75.535   , 76.043335, 76.66167 , ..., 77.62666 , 77.73    ,\n",
        "         77.528336],\n",
@@ -2483,7 +2565,7 @@
        "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
        "               nan],\n",
        "        [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-d427a1e2-1229-4dbd-ac10-7d4248a204df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d427a1e2-1229-4dbd-ac10-7d4248a204df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a49a2bdf-61ef-4b5e-9d0f-8ab28829e6bc' class='xr-var-data-in' type='checkbox'><label for='data-a49a2bdf-61ef-4b5e-9d0f-8ab28829e6bc' title='Show/Hide data repr'><svg 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>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
+       "               nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, range, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>92.59 92.61 92.47 ... 0.0 0.0 0.0</div><input id='attrs-05f6aae4-35c4-4f67-8258-58c083db3dac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05f6aae4-35c4-4f67-8258-58c083db3dac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8588dabc-b768-4e29-b2cd-516f6c7b7656' class='xr-var-data-in' type='checkbox'><label for='data-8588dabc-b768-4e29-b2cd-516f6c7b7656' title='Show/Hide data repr'><svg 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>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[[92.58667 , 92.613335, 92.47    , ..., 91.933334, 91.96667 ,\n",
        "         92.06333 ],\n",
        "        [96.236664, 96.526665, 96.206665, ..., 96.00667 , 96.3     ,\n",
        "         96.03333 ],\n",
@@ -2523,7 +2605,7 @@
        "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
        "          0.      ],\n",
        "        [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "          0.      ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-4a95fc5e-9df2-4d49-a008-4b98f9526876' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a95fc5e-9df2-4d49-a008-4b98f9526876' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-715a3c78-aa58-4742-95c4-63e8abc7b17a' class='xr-var-data-in' type='checkbox'><label for='data-715a3c78-aa58-4742-95c4-63e8abc7b17a' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.7431791e-02,  5.6972340e-02,  5.8299202e-02, ...,\n",
+       "          0.      ]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.05743 0.05697 ... 0.9937 0.9937</div><input id='attrs-d2922457-7e70-4c21-858e-8a542b4a4ad2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2922457-7e70-4c21-858e-8a542b4a4ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d81f7cba-7478-4fc5-96a3-d1ab656c155e' class='xr-var-data-in' type='checkbox'><label for='data-d81f7cba-7478-4fc5-96a3-d1ab656c155e' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 5.7431791e-02,  5.6972340e-02,  5.8299202e-02, ...,\n",
        "          5.8192708e-02,  5.8561362e-02,  5.8551285e-02],\n",
        "        [ 9.9830043e-01,  9.9832368e-01,  9.9824858e-01, ...,\n",
        "          9.9825412e-01,  9.9823499e-01,  9.9823463e-01],\n",
@@ -2542,26 +2624,26 @@
        "        [ 8.4546916e-03,  8.6972397e-03,  8.6324373e-03, ...,\n",
        "          7.3541482e-03,  7.3939036e-03,  7.3861168e-03],\n",
        "        [ 9.9162728e-01,  9.9160415e-01,  9.9164975e-01, ...,\n",
-       "          9.9366748e-01,  9.9369282e-01,  9.9368775e-01]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002153 -0.002034 ... -0.002598</div><input id='attrs-c1a0b894-d766-46fb-9bdb-a009b9accc12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c1a0b894-d766-46fb-9bdb-a009b9accc12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3984c3a-0894-4db8-be59-510d309977ff' class='xr-var-data-in' type='checkbox'><label for='data-a3984c3a-0894-4db8-be59-510d309977ff' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00215301, -0.00203405, -0.00207394, -0.00210115, -0.00192078,\n",
-       "        -0.00193777, -0.00191335, -0.00199152, -0.00207278, -0.00194206,\n",
-       "        -0.00204757, -0.00200068, -0.00199218, -0.00199336, -0.00199541,\n",
-       "        -0.00195642, -0.002004  , -0.00198927, -0.00192089, -0.00190773,\n",
-       "        -0.00197433, -0.00194974, -0.00201189, -0.00199716, -0.00203678,\n",
-       "        -0.00197156, -0.00211453, -0.00208679, -0.00214284, -0.002097  ,\n",
-       "        -0.0021586 , -0.00227236, -0.00224146, -0.00237022, -0.00236043,\n",
-       "        -0.00237393, -0.00247887, -0.00250768, -0.00250282, -0.00247524,\n",
-       "        -0.00244961, -0.0023577 , -0.0024839 , -0.00243087, -0.00243722,\n",
-       "        -0.00235072, -0.0022895 , -0.00227118, -0.00225553, -0.0022979 ,\n",
-       "        -0.00229448, -0.00216148, -0.00233598, -0.00218195, -0.00225593,\n",
-       "        -0.00226501, -0.00226501, -0.00223311, -0.0022377 , -0.00221475,\n",
-       "        -0.00219337, -0.00236515, -0.00232974, -0.00230031, -0.00222858,\n",
-       "        -0.00218684, -0.00223468, -0.00229368, -0.00235916, -0.00236146,\n",
-       "        -0.0022634 , -0.00224891, -0.00222244, -0.00232258, -0.00236444,\n",
-       "        -0.00224595, -0.0021171 , -0.00216819, -0.00224109, -0.00220484,\n",
-       "        -0.00229052, -0.00223416, -0.00232667, -0.0022808 , -0.00226991,\n",
-       "        -0.00230054, -0.0023359 , -0.00230572, -0.00217587, -0.0022142 ,\n",
-       "        -0.00226582, -0.00237079, -0.00231787, -0.00229156, -0.00226658,\n",
-       "        -0.00224667, -0.00225174, -0.00218213, -0.00225879, -0.00213818,\n",
+       "          9.9366748e-01,  9.9369282e-01,  9.9368775e-01]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt</span></div><div class='xr-var-dims'>(dirIMU, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.000807 0.0008203 ... -0.002598</div><input id='attrs-9ad856ea-88e5-4eab-9828-2a78aa5a95ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ad856ea-88e5-4eab-9828-2a78aa5a95ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa59466c-f955-4c57-b4f4-143c95c899eb' class='xr-var-data-in' type='checkbox'><label for='data-fa59466c-f955-4c57-b4f4-143c95c899eb' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00080699,  0.00082028,  0.00085015,  0.0008093 ,  0.00077764,\n",
+       "         0.00076247,  0.00084005,  0.00080013,  0.00073725,  0.00069978,\n",
+       "         0.00068869,  0.000708  ,  0.00070397,  0.00064101,  0.0007507 ,\n",
+       "         0.00071757,  0.00060209,  0.00062077,  0.00062501,  0.0005675 ,\n",
+       "         0.00054653,  0.00055442,  0.00072552,  0.00056834,  0.00065792,\n",
+       "         0.00086152,  0.00080709,  0.00096736,  0.00085591,  0.00094166,\n",
+       "         0.00090368,  0.00095632,  0.00094047,  0.00091472,  0.00092718,\n",
+       "         0.00097144,  0.00090388,  0.00098592,  0.00099217,  0.00104627,\n",
+       "         0.00101094,  0.00108953,  0.00094413,  0.0010326 ,  0.00105636,\n",
+       "         0.00098609,  0.00101084,  0.00101927,  0.00101796,  0.00096841,\n",
+       "         0.00102785,  0.00113951,  0.00098156,  0.00111134,  0.00100472,\n",
+       "         0.00104199,  0.00104198,  0.00100612,  0.00103637,  0.00099132,\n",
+       "         0.00102272,  0.00102712,  0.00100425,  0.0010416 ,  0.00097589,\n",
+       "         0.00090605,  0.00108258,  0.00090169,  0.00096689,  0.00081777,\n",
+       "         0.0009423 ,  0.00087804,  0.00102183,  0.00083111,  0.0009242 ,\n",
+       "         0.00094747,  0.00110261,  0.00097415,  0.00097692,  0.00113317,\n",
+       "         0.00105406,  0.00104935,  0.00102722,  0.00093711,  0.00103575,\n",
+       "         0.00095867,  0.0009583 ,  0.00104538,  0.00100466,  0.00095809,\n",
+       "         0.00101549,  0.00097118,  0.00090704,  0.00094464,  0.00096578,\n",
+       "         0.00105039,  0.00093799,  0.00100518,  0.00088882,  0.00095506,\n",
        "...\n",
        "        -0.00263344, -0.00258787, -0.00256183, -0.00256183, -0.00250324,\n",
        "        -0.00268227, -0.00268227, -0.00259113, -0.00262693, -0.00257485,\n",
@@ -2582,7 +2664,7 @@
        "        -0.00263345, -0.00258136, -0.00250975, -0.00261717, -0.00264321,\n",
        "        -0.00260741, -0.00261066, -0.00250649, -0.00248371, -0.0026074 ,\n",
        "        -0.00260415, -0.00260415, -0.00250324, -0.00259764, -0.002513  ,\n",
-       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-92af0ff3-2e4f-4545-9408-0fd9f0f378f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92af0ff3-2e4f-4545-9408-0fd9f0f378f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da59470d-4141-4619-8c83-6b60c4266526' class='xr-var-data-in' type='checkbox'><label for='data-da59470d-4141-4619-8c83-6b60c4266526' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
+       "        -0.00256509, -0.00253904, -0.00259764]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions</span></div><div class='xr-var-dims'>(q, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-8e3fd92e-2a55-4975-bde7-e42c2435c156' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e3fd92e-2a55-4975-bde7-e42c2435c156' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7220b912-1da8-4cf4-94a2-91eb16ff0eab' class='xr-var-data-in' type='checkbox'><label for='data-7220b912-1da8-4cf4-94a2-91eb16ff0eab' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245074 ,  0.624316  ,  0.6248463 ,  0.6245108 ,  0.6247046 ,\n",
        "         0.62467265,  0.62460417,  0.62476116,  0.6245991 ,  0.6246464 ,\n",
        "         0.624686  ,  0.6249721 ,  0.6249648 ,  0.6250649 ,  0.62494904,\n",
        "         0.62500936,  0.6250884 ,  0.6250855 ,  0.6253171 ,  0.6254035 ,\n",
@@ -2622,7 +2704,7 @@
        "         0.7785521 ,  0.77869254,  0.77849793,  0.7787016 ,  0.77872854,\n",
        "         0.77860415,  0.7784391 ,  0.7783881 ,  0.7785563 ,  0.77852774,\n",
        "         0.77856874,  0.77847373,  0.7784385 ,  0.7782882 ,  0.778279  ,\n",
-       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-f2112aaf-b1ba-427f-a973-0372b70a8da7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2112aaf-b1ba-427f-a973-0372b70a8da7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-46270ac4-1cdf-4244-b198-21f7918c1668' class='xr-var-data-in' type='checkbox'><label for='data-46270ac4-1cdf-4244-b198-21f7918c1668' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
+       "         0.778462  ,  0.77835196,  0.77835387]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp_press</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.8 12.8 12.8 ... 12.0 12.0 12.0</div><input id='attrs-7b34f8c3-0b51-4d02-b25b-82f361ff37a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b34f8c3-0b51-4d02-b25b-82f361ff37a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17825769-9cdf-4f96-9004-d7945897c4dc' class='xr-var-data-in' type='checkbox'><label for='data-17825769-9cdf-4f96-9004-d7945897c4dc' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Pressure Sensor Temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.800002 , 12.800002 , 12.800002 , 12.800002 , 12.800002 ,\n",
        "       12.966666 , 13.       , 13.050666 , 13.199998 , 13.199998 ,\n",
        "       13.199998 , 13.199998 , 13.199998 , 13.199998 , 13.199998 ,\n",
        "       13.199998 , 13.199998 , 13.199998 , 13.176665 , 13.       ,\n",
@@ -2658,7 +2740,7 @@
        "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
        "       12.199998 , 12.199998 , 12.199998 , 12.199998 , 12.199998 ,\n",
        "       12.1119995, 12.       , 12.       , 12.       , 12.       ,\n",
-       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-9bff76b7-855f-4c60-bc2e-bcee8046c900' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9bff76b7-855f-4c60-bc2e-bcee8046c900' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aac9be2c-5f2f-4480-bb61-bb7aea172938' class='xr-var-data-in' type='checkbox'><label for='data-aac9be2c-5f2f-4480-bb61-bb7aea172938' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
+       "       12.       , 12.       , 12.       ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>244.0 244.0 244.0 ... 246.0 246.0</div><input id='attrs-d9bc73e4-ce63-4a17-ade4-daaebcc28f72' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9bc73e4-ce63-4a17-ade4-daaebcc28f72' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8ec09ea-38b9-4cd6-a922-181744138711' class='xr-var-data-in' type='checkbox'><label for='data-d8ec09ea-38b9-4cd6-a922-181744138711' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([244.04333, 243.96   , 244.04666, 244.12334, 244.30667, 244.32   ,\n",
        "       244.04   , 243.95667, 243.72   , 243.45334, 243.46   , 243.49333,\n",
        "       243.49667, 243.69667, 243.80333, 243.78334, 243.81667, 244.     ,\n",
        "       244.27333, 244.39667, 244.58333, 244.73334, 244.95334, 245.     ,\n",
@@ -2688,66 +2770,66 @@
        "       245.95667, 245.94   , 245.93   , 245.95667, 245.95   , 245.95334,\n",
        "       245.94667, 245.96   , 245.96333, 245.97333, 245.96666, 245.96   ,\n",
        "       245.97667, 245.99   , 245.98   , 245.98666, 245.98666, 245.98334,\n",
-       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>72.4 72.39 72.43 ... -197.1 -197.1</div><input id='attrs-b2cd30f3-104c-4306-9c6f-b0b3cf01fa59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2cd30f3-104c-4306-9c6f-b0b3cf01fa59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6abd0003-2ab9-4b3b-b994-8a996c8850f7' class='xr-var-data-in' type='checkbox'><label for='data-6abd0003-2ab9-4b3b-b994-8a996c8850f7' title='Show/Hide data repr'><svg 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>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[  72.3957   ,   72.39208  ,   72.42783  ,   72.42615  ,\n",
-       "          72.44187  ,   72.41524  ,   72.461914 ,   72.493645 ,\n",
-       "          72.45924  ,   72.46602  ,   72.43278  ,   72.44255  ,\n",
-       "          72.46903  ,   72.422035 ,   72.40729  ,   72.41101  ,\n",
-       "          72.39426  ,   72.40279  ,   72.39892  ,   72.41741  ,\n",
-       "          72.43427  ,   72.44829  ,   72.41536  ,   72.41849  ,\n",
-       "          72.41168  ,   72.442986 ,   72.42484  ,   72.42529  ,\n",
-       "          72.441765 ,   72.4192   ,   72.417595 ,   72.40413  ,\n",
-       "          72.422035 ,   72.41054  ,   72.42295  ,   72.42104  ,\n",
-       "          72.43507  ,   72.435326 ,   72.40648  ,   72.384995 ,\n",
-       "          72.42229  ,   72.42928  ,   72.389946 ,   72.43857  ,\n",
-       "          72.39131  ,   72.41897  ,   72.417175 ,   72.3607   ,\n",
-       "          72.393135 ,   72.40127  ,   72.334496 ,   72.21212  ,\n",
-       "          71.85896  ,   71.10549  ,   71.138245 ,   71.19041  ,\n",
-       "          71.24709  ,   71.29904  ,   71.34743  ,   71.38805  ,\n",
-       "          71.403404 ,   71.41398  ,   71.431335 ,   71.43516  ,\n",
-       "          71.40687  ,   71.364586 ,   71.3476   ,   71.32235  ,\n",
-       "          71.30753  ,   71.28084  ,   71.2915   ,   71.321846 ,\n",
-       "          71.34431  ,   71.34534  ,   71.31464  ,   71.3486   ,\n",
-       "          71.31093  ,   71.31272  ,   71.33253  ,   71.34043  ,\n",
+       "       245.99   , 245.98334, 245.99   ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mag_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.589 3.576 3.611 ... -197.1 -197.1</div><input id='attrs-d26db0eb-31d4-4f4c-878a-7726ae80a2ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d26db0eb-31d4-4f4c-878a-7726ae80a2ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bdd1bdf1-3259-45b7-b26a-cdd8fc339dec' class='xr-var-data-in' type='checkbox'><label for='data-bdd1bdf1-3259-45b7-b26a-cdd8fc339dec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>uT</dd><dt><span>long_name :</span></dt><dd>Compass</dd></dl></div><div class='xr-var-data'><pre>array([[ 3.5890043e+00,  3.5764267e+00,  3.6108000e+00,  3.5779479e+00,\n",
+       "         3.6116722e+00,  3.5757926e+00,  3.5947011e+00,  3.6243415e+00,\n",
+       "         3.6057498e+00,  3.5963907e+00,  3.5682683e+00,  3.5830541e+00,\n",
+       "         3.6165171e+00,  3.5789924e+00,  3.5747983e+00,  3.5690451e+00,\n",
+       "         3.5796013e+00,  3.6261461e+00,  3.6063533e+00,  3.6014793e+00,\n",
+       "         3.6353867e+00,  3.6033037e+00,  3.6023452e+00,  3.5552030e+00,\n",
+       "         3.5689838e+00,  3.5028172e+00,  3.5047083e+00,  3.5002160e+00,\n",
+       "         3.4591193e+00,  3.4518206e+00,  3.4781301e+00,  3.4272490e+00,\n",
+       "         3.4080899e+00,  3.4372401e+00,  3.4341383e+00,  3.3986635e+00,\n",
+       "         3.4168527e+00,  3.4093900e+00,  3.3794670e+00,  3.3934760e+00,\n",
+       "         3.4050255e+00,  3.4207287e+00,  3.3710022e+00,  3.3771679e+00,\n",
+       "         3.3508575e+00,  3.3733418e+00,  3.3524203e+00,  3.3316765e+00,\n",
+       "         3.3258898e+00,  3.3680134e+00,  3.2842205e+00,  3.1945536e+00,\n",
+       "         3.0031643e+00,  2.4369469e+00,  2.1365104e+00,  1.9519799e+00,\n",
+       "         1.7708880e+00,  1.6470157e+00,  1.5729071e+00,  1.4625059e+00,\n",
+       "         1.3881445e+00,  1.3379683e+00,  1.3052688e+00,  1.2468669e+00,\n",
+       "         1.2023060e+00,  1.1269652e+00,  1.1022493e+00,  1.0541168e+00,\n",
+       "         1.0267943e+00,  9.7805500e-01,  9.2956728e-01,  9.2703986e-01,\n",
+       "         9.1599518e-01,  8.9450091e-01,  8.5012430e-01,  8.2220656e-01,\n",
+       "         7.9883540e-01,  7.8205061e-01,  7.3997599e-01,  7.3860043e-01,\n",
        "...\n",
-       "        -197.3692   , -197.2595   , -197.30052  , -197.28384  ,\n",
-       "        -197.24887  , -197.22919  , -197.15518  , -197.27151  ,\n",
-       "        -197.2445   , -197.21883  , -197.17354  , -197.23384  ,\n",
-       "        -197.19716  , -197.14218  , -197.23253  , -197.10818  ,\n",
-       "        -197.0825   , -197.09784  , -197.08986  , -197.1295   ,\n",
-       "        -197.21385  , -197.20052  , -197.17421  , -197.10919  ,\n",
-       "        -197.15717  , -197.14487  , -197.15251  , -197.14418  ,\n",
-       "        -197.14218  , -197.06715  , -197.05818  , -197.05084  ,\n",
-       "        -197.08585  , -197.08818  , -197.14618  , -197.09253  ,\n",
-       "        -197.07854  , -197.14384  , -197.17952  , -197.18619  ,\n",
-       "        -197.18387  , -197.16652  , -197.12685  , -197.20483  ,\n",
-       "        -197.18315  , -197.13019  , -197.1495   , -197.24086  ,\n",
-       "        -197.16121  , -197.19583  , -197.24785  , -197.1605   ,\n",
-       "        -197.25883  , -197.20285  , -197.17484  , -197.25153  ,\n",
-       "        -197.14685  , -197.1182   , -197.14719  , -197.11786  ,\n",
-       "        -197.1405   , -197.14351  , -197.15118  , -197.12115  ,\n",
-       "        -197.10716  , -197.18983  , -197.15218  , -197.12483  ,\n",
-       "        -197.06255  , -197.14517  , -197.12418  , -197.05786  ,\n",
-       "        -197.08685  , -197.11751  , -197.07716  , -197.07918  ,\n",
-       "        -197.19186  , -197.1385   , -197.14885  ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.3595 -0.3604 ... 9.714 9.713</div><input id='attrs-352f4a0b-f879-4ea7-8ee4-23c27d4e34d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-352f4a0b-f879-4ea7-8ee4-23c27d4e34d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3033afff-0219-46a6-9cf1-8fbb01f25c18' class='xr-var-data-in' type='checkbox'><label for='data-3033afff-0219-46a6-9cf1-8fbb01f25c18' title='Show/Hide data repr'><svg 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>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.35945004, -0.36040476, -0.35942063, -0.36224607, -0.3606849 ,\n",
-       "        -0.36077246, -0.361926  , -0.3607621 , -0.3633263 , -0.36385658,\n",
-       "        -0.36013916, -0.3583838 , -0.3592216 , -0.35633823, -0.35704008,\n",
-       "        -0.35671657, -0.35852   , -0.35691682, -0.3556908 , -0.3539107 ,\n",
-       "        -0.35514882, -0.3537154 , -0.35552192, -0.35852847, -0.35622555,\n",
-       "        -0.35716456, -0.3591097 , -0.35609993, -0.35620683, -0.3553896 ,\n",
-       "        -0.35594925, -0.3581515 , -0.35490584, -0.35277644, -0.35308707,\n",
-       "        -0.35255027, -0.35277456, -0.35734928, -0.36094195, -0.3589289 ,\n",
-       "        -0.35321656, -0.35699782, -0.35960466, -0.36017507, -0.36028385,\n",
-       "        -0.35666367, -0.3546632 , -0.35590348, -0.3529342 , -0.35445896,\n",
-       "        -0.35379022, -0.3443678 , -0.3253079 , -0.2902023 , -0.29245403,\n",
-       "        -0.29303038, -0.2979905 , -0.30267066, -0.3054265 , -0.30768296,\n",
-       "        -0.3080373 , -0.30874294, -0.30742028, -0.30902606, -0.31027097,\n",
-       "        -0.3063462 , -0.304645  , -0.30389866, -0.30510902, -0.30338708,\n",
-       "        -0.30171934, -0.30379722, -0.30178338, -0.30120566, -0.30167016,\n",
-       "        -0.30234587, -0.3025471 , -0.30401772, -0.30196434, -0.30674008,\n",
-       "        -0.30684155, -0.3045954 , -0.30835468, -0.310912  , -0.30926695,\n",
-       "        -0.3120664 , -0.31088886, -0.3106291 , -0.31221488, -0.31203583,\n",
-       "        -0.3111686 , -0.30842897, -0.30869153, -0.3095482 , -0.30972004,\n",
-       "        -0.30999103, -0.31200367, -0.3087923 , -0.31007493, -0.30976847,\n",
+       "        -1.9736920e+02, -1.9725951e+02, -1.9730052e+02, -1.9728384e+02,\n",
+       "        -1.9724887e+02, -1.9722919e+02, -1.9715518e+02, -1.9727151e+02,\n",
+       "        -1.9724451e+02, -1.9721883e+02, -1.9717354e+02, -1.9723384e+02,\n",
+       "        -1.9719716e+02, -1.9714218e+02, -1.9723253e+02, -1.9710818e+02,\n",
+       "        -1.9708250e+02, -1.9709784e+02, -1.9708986e+02, -1.9712950e+02,\n",
+       "        -1.9721385e+02, -1.9720052e+02, -1.9717421e+02, -1.9710919e+02,\n",
+       "        -1.9715717e+02, -1.9714487e+02, -1.9715251e+02, -1.9714418e+02,\n",
+       "        -1.9714218e+02, -1.9706715e+02, -1.9705818e+02, -1.9705084e+02,\n",
+       "        -1.9708585e+02, -1.9708818e+02, -1.9714618e+02, -1.9709253e+02,\n",
+       "        -1.9707854e+02, -1.9714384e+02, -1.9717952e+02, -1.9718619e+02,\n",
+       "        -1.9718387e+02, -1.9716652e+02, -1.9712685e+02, -1.9720483e+02,\n",
+       "        -1.9718315e+02, -1.9713019e+02, -1.9714951e+02, -1.9724086e+02,\n",
+       "        -1.9716121e+02, -1.9719583e+02, -1.9724785e+02, -1.9716051e+02,\n",
+       "        -1.9725883e+02, -1.9720285e+02, -1.9717484e+02, -1.9725153e+02,\n",
+       "        -1.9714685e+02, -1.9711819e+02, -1.9714719e+02, -1.9711786e+02,\n",
+       "        -1.9714050e+02, -1.9714351e+02, -1.9715118e+02, -1.9712115e+02,\n",
+       "        -1.9710716e+02, -1.9718983e+02, -1.9715218e+02, -1.9712483e+02,\n",
+       "        -1.9706255e+02, -1.9714517e+02, -1.9712418e+02, -1.9705786e+02,\n",
+       "        -1.9708685e+02, -1.9711751e+02, -1.9707716e+02, -1.9707918e+02,\n",
+       "        -1.9719186e+02, -1.9713850e+02, -1.9714885e+02]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>accel_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.262 -1.263 -1.26 ... 9.714 9.713</div><input id='attrs-8e21d4f6-bce1-49db-9f73-7f6e0ce4b2d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e21d4f6-bce1-49db-9f73-7f6e0ce4b2d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66d8eabe-9c3f-4c74-ab5a-8b60423904b9' class='xr-var-data-in' type='checkbox'><label for='data-66d8eabe-9c3f-4c74-ab5a-8b60423904b9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-2</dd><dt><span>long_name :</span></dt><dd>Acceleration</dd></dl></div><div class='xr-var-data'><pre>array([[-1.2623771 , -1.2625197 , -1.2600151 , -1.2631888 , -1.2615376 ,\n",
+       "        -1.2616537 , -1.262574  , -1.2627327 , -1.2632962 , -1.2634871 ,\n",
+       "        -1.2617764 , -1.2599101 , -1.2592376 , -1.2577692 , -1.259011  ,\n",
+       "        -1.2584039 , -1.2585176 , -1.2577502 , -1.2569213 , -1.2552022 ,\n",
+       "        -1.2558354 , -1.2547814 , -1.2564313 , -1.2570257 , -1.2564919 ,\n",
+       "        -1.255276  , -1.2551885 , -1.254373  , -1.2521614 , -1.253256  ,\n",
+       "        -1.2520183 , -1.2556639 , -1.2544196 , -1.2537049 , -1.2514051 ,\n",
+       "        -1.251719  , -1.2501887 , -1.2550075 , -1.2560523 , -1.2542702 ,\n",
+       "        -1.2513357 , -1.2537423 , -1.2558701 , -1.2554086 , -1.2568508 ,\n",
+       "        -1.2513126 , -1.251984  , -1.2514541 , -1.2487587 , -1.249171  ,\n",
+       "        -1.2487395 , -1.2432917 , -1.2308283 , -1.2085198 , -1.1925628 ,\n",
+       "        -1.1850356 , -1.175814  , -1.1718632 , -1.1669031 , -1.1620393 ,\n",
+       "        -1.1585126 , -1.1573663 , -1.1550487 , -1.1537894 , -1.1520276 ,\n",
+       "        -1.1507337 , -1.1474868 , -1.1443372 , -1.1442864 , -1.1430473 ,\n",
+       "        -1.1418383 , -1.141045  , -1.1385593 , -1.1344901 , -1.1347641 ,\n",
+       "        -1.131755  , -1.1333026 , -1.132527  , -1.1293765 , -1.1324316 ,\n",
+       "        -1.1310244 , -1.1295373 , -1.1287975 , -1.1317044 , -1.1290994 ,\n",
+       "        -1.1286312 , -1.1276112 , -1.1271322 , -1.1283079 , -1.1257491 ,\n",
+       "        -1.1227695 , -1.1230274 , -1.119395  , -1.1190095 , -1.1182653 ,\n",
+       "        -1.1186818 , -1.1167871 , -1.1160123 , -1.1153725 , -1.1143076 ,\n",
        "...\n",
        "         9.716884  ,  9.718465  ,  9.717347  ,  9.717714  ,  9.714792  ,\n",
        "         9.714856  ,  9.712732  ,  9.712221  ,  9.713994  ,  9.715383  ,\n",
@@ -2768,7 +2850,7 @@
        "         9.714553  ,  9.715958  ,  9.714808  ,  9.717874  ,  9.716309  ,\n",
        "         9.715032  ,  9.7090435 ,  9.711168  ,  9.7130995 ,  9.713355  ,\n",
        "         9.715256  ,  9.714936  ,  9.714808  ,  9.711726  ,  9.711886  ,\n",
-       "         9.713675  ,  9.714042  ,  9.71278   ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</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-1805b5d9-3ba1-4ea3-bda2-8e19ecfeebe3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1805b5d9-3ba1-4ea3-bda2-8e19ecfeebe3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-495e50c1-1f71-41ab-8506-7acc8058930a' class='xr-var-data-in' type='checkbox'><label for='data-495e50c1-1f71-41ab-8506-7acc8058930a' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "         9.713675  ,  9.714042  ,  9.71278   ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</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-6aa24fba-40b0-4e6b-a041-1c7c5f392461' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aa24fba-40b0-4e6b-a041-1c7c5f392461' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9007dd09-c92e-42f2-a5f6-fac64f7e7eb6' class='xr-var-data-in' type='checkbox'><label for='data-9007dd09-c92e-42f2-a5f6-fac64f7e7eb6' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2778,7 +2860,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-78fa7be5-80c1-45b6-9705-2bc2ff8cbbe9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78fa7be5-80c1-45b6-9705-2bc2ff8cbbe9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-579172bb-9bf9-4a39-b360-642ed7577c5b' class='xr-var-data-in' type='checkbox'><label for='data-579172bb-9bf9-4a39-b360-642ed7577c5b' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.054e+09 1.054e+09 ... 1.054e+09</div><input id='attrs-7147a31c-f490-46dd-8bcb-89b93aa57408' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7147a31c-f490-46dd-8bcb-89b93aa57408' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11158554-421b-40e2-91fe-0845a4b061e1' class='xr-var-data-in' type='checkbox'><label for='data-11158554-421b-40e2-91fe-0845a4b061e1' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
@@ -2818,7 +2900,7 @@
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
        "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09, 1.05355686e+09,\n",
-       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-5ff9feba-c64d-4162-8c84-cdf460ac80dd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ff9feba-c64d-4162-8c84-cdf460ac80dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-55061f20-1323-48e0-871e-36c33e4c7dff' class='xr-var-data-in' type='checkbox'><label for='data-55061f20-1323-48e0-871e-36c33e4c7dff' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
+       "       1.05355686e+09, 1.05355686e+09, 1.05355686e+09], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0006333 -0.004143 ... nan nan</div><input id='attrs-f34cd48f-003f-48a8-b5e6-7c0e44eb890c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f34cd48f-003f-48a8-b5e6-7c0e44eb890c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a20f1a9-9ccd-4e57-8719-b1bf98454747' class='xr-var-data-in' type='checkbox'><label for='data-7a20f1a9-9ccd-4e57-8719-b1bf98454747' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00063333, -0.00414333, -0.00776667, ..., -0.01952   ,\n",
        "        -0.02035667, -0.01573333],\n",
        "       [ 0.02268667,  0.01564333,  0.01504   , ..., -0.00309667,\n",
        "        -0.00658667, -0.00238   ],\n",
@@ -2830,7 +2912,7 @@
        "       [        nan,         nan,         nan, ...,         nan,\n",
        "                nan,         nan],\n",
        "       [        nan,         nan,         nan, ...,         nan,\n",
-       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-6141b941-68f0-4fc7-ac33-85eeff1fff6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6141b941-68f0-4fc7-ac33-85eeff1fff6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f221ce37-8c5c-4fcb-9221-b01e693d66bf' class='xr-var-data-in' type='checkbox'><label for='data-f221ce37-8c5c-4fcb-9221-b01e693d66bf' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
+       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>80.08 80.44 80.75 ... nan nan nan</div><input id='attrs-e1b467ac-690d-4ac7-b3bd-ea9567611c78' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1b467ac-690d-4ac7-b3bd-ea9567611c78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66374e70-f4bd-4958-b77b-a431d72fcd74' class='xr-var-data-in' type='checkbox'><label for='data-66374e70-f4bd-4958-b77b-a431d72fcd74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[80.085   , 80.43833 , 80.75166 , ..., 81.761665, 81.86    ,\n",
        "        81.745   ],\n",
        "       [76.05    , 76.60333 , 77.066666, ..., 78.23    , 78.21667 ,\n",
        "        78.045   ],\n",
@@ -2842,7 +2924,7 @@
        "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
        "              nan],\n",
        "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
-       "              nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-3cd96b63-33c1-4f2f-b003-37d141c3a1af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3cd96b63-33c1-4f2f-b003-37d141c3a1af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4597a20-08eb-4119-a9a8-6f0b5b046b6f' class='xr-var-data-in' type='checkbox'><label for='data-d4597a20-08eb-4119-a9a8-6f0b5b046b6f' title='Show/Hide data repr'><svg 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>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
+       "              nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr_b5</span></div><div class='xr-var-dims'>(range_b5, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>93.52 94.19 93.97 ... 0.0 0.0 0.0</div><input id='attrs-b1ae6c22-65b7-4fb4-a9dd-e87b24eb0238' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b1ae6c22-65b7-4fb4-a9dd-e87b24eb0238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b53c803-71aa-429d-a49c-265d3b6ac655' class='xr-var-data-in' type='checkbox'><label for='data-5b53c803-71aa-429d-a49c-265d3b6ac655' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>standard_name :</span></dt><dd>beam_consistency_indicator_from_multibeam_acoustic_doppler_velocity_profiler_in_sea_water</dd><dt><span>Comments :</span></dt><dd>Filtered of data with a correlation value below 50%</dd></dl></div><div class='xr-var-data'><pre>array([[93.51667 , 94.18667 , 93.97    , ..., 92.276665, 92.09    ,\n",
        "        92.61667 ],\n",
        "       [96.75    , 96.403336, 96.32    , ..., 96.433334, 96.89    ,\n",
        "        96.57667 ],\n",
@@ -2854,7 +2936,7 @@
        "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
        "         0.      ],\n",
        "       [ 0.      ,  0.      ,  0.      , ...,  0.      ,  0.      ,\n",
-       "         0.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-19625e80-eacc-46d1-831f-5b9bd14140f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-19625e80-eacc-46d1-831f-5b9bd14140f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea5d5bd8-3563-4e5d-bce9-c194036b0f0e' class='xr-var-data-in' type='checkbox'><label for='data-ea5d5bd8-3563-4e5d-bce9-c194036b0f0e' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
+       "         0.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat_b5</span></div><div class='xr-var-dims'>(earth, inst, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.2166 -0.217 ... 0.9937 0.9937</div><input id='attrs-1e018b26-85ae-4c04-aa37-bdffe3426e30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e018b26-85ae-4c04-aa37-bdffe3426e30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf5b5f8f-c604-44a2-a0da-3eda6497c543' class='xr-var-data-in' type='checkbox'><label for='data-cf5b5f8f-c604-44a2-a0da-3eda6497c543' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.16565624e-01, -2.17020363e-01, -2.15714216e-01, ...,\n",
        "         -2.15817824e-01, -2.15457186e-01, -2.15469748e-01],\n",
        "        [-9.68014121e-01, -9.67880666e-01, -9.68221545e-01, ...,\n",
        "         -9.70180333e-01, -9.70283389e-01, -9.70276892e-01],\n",
@@ -2874,26 +2956,26 @@
        "         -1.12357967e-01, -1.12130813e-01, -1.12177916e-01],\n",
        "        [ 9.91627216e-01,  9.91603792e-01,  9.91649806e-01, ...,\n",
        "          9.93667185e-01,  9.93692756e-01,  9.93687451e-01]]],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.002097 -0.002078 ... -0.002637</div><input id='attrs-5d94588f-8932-43c8-92e9-577df1cd62c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5d94588f-8932-43c8-92e9-577df1cd62c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52c177b3-8efe-4b7f-9824-ea4127dbbe99' class='xr-var-data-in' type='checkbox'><label for='data-52c177b3-8efe-4b7f-9824-ea4127dbbe99' title='Show/Hide data repr'><svg 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>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00209712, -0.00207796, -0.00199299, -0.00203929, -0.00193438,\n",
-       "        -0.00196708, -0.0019927 , -0.00204398, -0.00193731, -0.0020106 ,\n",
-       "        -0.00205254, -0.00204932, -0.00204045, -0.00204494, -0.0020428 ,\n",
-       "        -0.00195406, -0.00208406, -0.0020402 , -0.00199256, -0.00194318,\n",
-       "        -0.00196901, -0.00187163, -0.00207352, -0.00198713, -0.00205621,\n",
-       "        -0.00195992, -0.0020945 , -0.00205666, -0.00207093, -0.00222958,\n",
-       "        -0.00210572, -0.00234646, -0.00222096, -0.00222215, -0.00233367,\n",
-       "        -0.0023373 , -0.00237128, -0.00237839, -0.0024478 , -0.00252198,\n",
-       "        -0.00241759, -0.00245205, -0.00240165, -0.00236281, -0.00240797,\n",
-       "        -0.00234682, -0.00229789, -0.00229369, -0.00220773, -0.00227775,\n",
-       "        -0.00227983, -0.00213223, -0.00218401, -0.0023033 , -0.00230067,\n",
-       "        -0.00233384, -0.00225691, -0.00230815, -0.00220324, -0.00217511,\n",
-       "        -0.00219928, -0.00233678, -0.00224525, -0.00230776, -0.00228472,\n",
-       "        -0.00225526, -0.00227911, -0.00233422, -0.00227774, -0.00242061,\n",
-       "        -0.00226535, -0.00234841, -0.00221465, -0.00235071, -0.00227588,\n",
-       "        -0.00225901, -0.00222179, -0.00224194, -0.00219105, -0.00224129,\n",
-       "        -0.00228148, -0.00218712, -0.0022917 , -0.00220996, -0.00226677,\n",
-       "        -0.00222232, -0.00234719, -0.00227961, -0.00214331, -0.00228754,\n",
-       "        -0.00235026, -0.0022648 , -0.0022901 , -0.00217174, -0.0022742 ,\n",
-       "        -0.00233724, -0.00219496, -0.00222307, -0.00220071, -0.00220035,\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>angrt_b5</span></div><div class='xr-var-dims'>(dirIMU, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0008123 0.0008472 ... -0.002637</div><input id='attrs-dd80d27a-91b5-4e0a-8e59-7bab34928a1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd80d27a-91b5-4e0a-8e59-7bab34928a1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ebf8f727-722a-4f9e-a91d-a725e96e5488' class='xr-var-data-in' type='checkbox'><label for='data-ebf8f727-722a-4f9e-a91d-a725e96e5488' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>units :</span></dt><dd>rad s-1</dd><dt><span>long_name :</span></dt><dd>Angular Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00081228,  0.00084717,  0.00085335,  0.00075436,  0.00084513,\n",
+       "         0.00085451,  0.00073719,  0.00067843,  0.00075248,  0.00074199,\n",
+       "         0.00070569,  0.00065896,  0.0006914 ,  0.00069842,  0.00074138,\n",
+       "         0.0006676 ,  0.00060215,  0.00059847,  0.0006675 ,  0.0006136 ,\n",
+       "         0.00056599,  0.00061758,  0.00068752,  0.00066373,  0.00073918,\n",
+       "         0.00085721,  0.00084523,  0.0009018 ,  0.00089635,  0.00084324,\n",
+       "         0.00086276,  0.00089614,  0.00096862,  0.00108153,  0.00095481,\n",
+       "         0.00098828,  0.00098117,  0.00097845,  0.00099421,  0.00095727,\n",
+       "         0.00108126,  0.00108415,  0.00096381,  0.00100037,  0.00098756,\n",
+       "         0.00103554,  0.00096841,  0.00107755,  0.00104051,  0.0009601 ,\n",
+       "         0.00106976,  0.0010707 ,  0.00102194,  0.0009954 ,  0.00100513,\n",
+       "         0.0010245 ,  0.00102471,  0.00096594,  0.0010335 ,  0.00105437,\n",
+       "         0.00105971,  0.00095506,  0.00102042,  0.00097918,  0.00088768,\n",
+       "         0.0009018 ,  0.00096684,  0.00101125,  0.00096008,  0.0008592 ,\n",
+       "         0.00082965,  0.00095935,  0.00094485,  0.00081024,  0.00092011,\n",
+       "         0.00098175,  0.00094213,  0.00095046,  0.00099598,  0.00104662,\n",
+       "         0.00101681,  0.0010222 ,  0.00099111,  0.001044  ,  0.00103549,\n",
+       "         0.00097536,  0.00099907,  0.00097684,  0.00104176,  0.00094763,\n",
+       "         0.0009761 ,  0.00097227,  0.00089143,  0.00096118,  0.00097306,\n",
+       "         0.00096506,  0.00094653,  0.00092565,  0.00091383,  0.0009503 ,\n",
        "...\n",
        "        -0.00262043, -0.00258136, -0.00261717, -0.00257811, -0.00261066,\n",
        "        -0.00255532, -0.00266274, -0.00254881, -0.00255858, -0.00259764,\n",
@@ -2914,7 +2996,7 @@
        "        -0.00265949, -0.00270831, -0.00258787, -0.0025423 , -0.00262368,\n",
        "        -0.00264647, -0.00268879, -0.00251626, -0.00256183, -0.00255207,\n",
        "        -0.00251626, -0.00251626, -0.00249998, -0.00248371, -0.0024479 ,\n",
-       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-f30e59ac-8b5b-4246-a451-0be05acd9473' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f30e59ac-8b5b-4246-a451-0be05acd9473' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de625746-3de8-4314-a1c8-cf9192af45bb' class='xr-var-data-in' type='checkbox'><label for='data-de625746-3de8-4314-a1c8-cf9192af45bb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
+       "        -0.00254881, -0.00254881, -0.0026367 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>quaternions_b5</span></div><div class='xr-var-dims'>(q, time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.6245 0.6243 ... 0.7784 0.7784</div><input id='attrs-247320e0-c83b-4630-be23-42de8fc48ad2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-247320e0-c83b-4630-be23-42de8fc48ad2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-feb7e967-aba4-412d-85fb-afbfc6bc6239' class='xr-var-data-in' type='checkbox'><label for='data-feb7e967-aba4-412d-85fb-afbfc6bc6239' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Quaternions</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.6245025 ,  0.62430865,  0.62484366,  0.62450564,  0.624701  ,\n",
        "         0.62466866,  0.62460196,  0.6247584 ,  0.62459546,  0.62464297,\n",
        "         0.6246826 ,  0.62496835,  0.6249581 ,  0.6250585 ,  0.62494546,\n",
        "         0.6250052 ,  0.62508506,  0.62507963,  0.6253132 ,  0.6254015 ,\n",
@@ -2954,7 +3036,7 @@
        "         0.77855694,  0.778695  ,  0.77849764,  0.7787041 ,  0.77873075,\n",
        "         0.7786052 ,  0.7784392 ,  0.7783923 ,  0.77855927,  0.77852917,\n",
        "         0.7785722 ,  0.77847767,  0.77844226,  0.77829295,  0.7782816 ,\n",
-       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-e5d165c4-e1f9-4b34-9781-616441b36054' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5d165c4-e1f9-4b34-9781-616441b36054' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-89566368-b1fe-4a19-b6d7-be0fcdfa69dc' class='xr-var-data-in' type='checkbox'><label for='data-89566368-b1fe-4a19-b6d7-be0fcdfa69dc' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
+       "         0.77846414,  0.778354  ,  0.77835685]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xmit_energy_b5</span></div><div class='xr-var-dims'>(time_b5)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>65.0 65.0 65.0 ... 65.0 65.0 65.0</div><input id='attrs-5ed4975f-cca3-4a26-9dae-929d5bae1e1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ed4975f-cca3-4a26-9dae-929d5bae1e1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-37d15d38-6d72-49d3-8eff-83aff911cae7' class='xr-var-data-in' type='checkbox'><label for='data-37d15d38-6d72-49d3-8eff-83aff911cae7' title='Show/Hide data repr'><svg 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>dB</dd><dt><span>long_name :</span></dt><dd>Sound Pressure Level of Acoustic Signal</dd></dl></div><div class='xr-var-data'><pre>array([65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
@@ -2968,7 +3050,7 @@
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
        "       65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65., 65.,\n",
-       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-4399d7cc-4b23-4d52-b2c6-330eeb26dfe8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4399d7cc-4b23-4d52-b2c6-330eeb26dfe8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a5a41c9c-af19-4468-83b0-66f75d436d8c' class='xr-var-data-in' type='checkbox'><label for='data-a5a41c9c-af19-4468-83b0-66f75d436d8c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       65.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>low_volt_skip</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-8dc7d167-52eb-43c9-807a-535d47bf457e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8dc7d167-52eb-43c9-807a-535d47bf457e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3acf6cf-26d9-4b4c-8082-1e2052ae8b12' class='xr-var-data-in' type='checkbox'><label for='data-f3acf6cf-26d9-4b4c-8082-1e2052ae8b12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2978,7 +3060,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-46885536-b819-4246-9c20-2e7450aace7e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-46885536-b819-4246-9c20-2e7450aace7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b66eeb5-4199-4992-a535-8e717feb9a90' class='xr-var-data-in' type='checkbox'><label for='data-5b66eeb5-4199-4992-a535-8e717feb9a90' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>active_config</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-28282862-24bc-4d35-ba7b-d56b4d8e9c44' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28282862-24bc-4d35-ba7b-d56b4d8e9c44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb031614-7797-422b-823d-9d0383012c67' class='xr-var-data-in' type='checkbox'><label for='data-fb031614-7797-422b-823d-9d0383012c67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2988,7 +3070,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-3d5a5ad1-3ab2-4cc4-a843-542b5edf1fbd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d5a5ad1-3ab2-4cc4-a843-542b5edf1fbd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b7a5f4a-0f8f-47d8-870f-eda96dd2b361' class='xr-var-data-in' type='checkbox'><label for='data-8b7a5f4a-0f8f-47d8-870f-eda96dd2b361' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>telemetry_data</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</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-8f930b4e-280e-4d22-bcc1-c0657beeffea' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f930b4e-280e-4d22-bcc1-c0657beeffea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a60902-3ebe-4aeb-b015-60c89b4a0743' class='xr-var-data-in' type='checkbox'><label for='data-84a60902-3ebe-4aeb-b015-60c89b4a0743' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
@@ -2998,7 +3080,7 @@
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
        "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
-       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-68280b1c-5735-4846-8cb3-b757883ef257' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-68280b1c-5735-4846-8cb3-b757883ef257' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-877e8efa-e09e-45b3-905f-11387551b627' class='xr-var-data-in' type='checkbox'><label for='data-877e8efa-e09e-45b3-905f-11387551b627' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
+       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>boost_running</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.1267 0.1333 0.13 ... 0.22 0.22</div><input id='attrs-5beadb1a-4d95-41d9-b7ed-17b276cc5d4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5beadb1a-4d95-41d9-b7ed-17b276cc5d4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-854cef1e-6347-472b-be98-6c7564da5534' class='xr-var-data-in' type='checkbox'><label for='data-854cef1e-6347-472b-be98-6c7564da5534' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.12666667, 0.13333334, 0.13      , 0.13333334, 0.13      ,\n",
        "       0.13      , 0.13      , 0.11666667, 0.12333333, 0.11666667,\n",
        "       0.11333334, 0.11      , 0.11      , 0.11333334, 0.11666667,\n",
        "       0.11      , 0.11333334, 0.11333334, 0.11333334, 0.12333333,\n",
@@ -3034,7 +3116,7 @@
        "       0.22666667, 0.22      , 0.22      , 0.22666667, 0.22      ,\n",
        "       0.22      , 0.22666667, 0.22      , 0.22      , 0.22666667,\n",
        "       0.22      , 0.22      , 0.22666667, 0.22      , 0.22      ,\n",
-       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-e33ead4d-67db-467f-918b-fd602a898965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e33ead4d-67db-467f-918b-fd602a898965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08abf030-07fa-4e6f-9f4f-12b2b80c5737' class='xr-var-data-in' type='checkbox'><label for='data-08abf030-07fa-4e6f-9f4f-12b2b80c5737' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
+       "       0.22666667, 0.22      , 0.22      ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.287 3.261 3.337 ... 3.352 3.352</div><input id='attrs-349895e9-0f8a-498a-9493-5f599d87b910' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-349895e9-0f8a-498a-9493-5f599d87b910' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8656d720-7aba-49fb-ba05-9cb61749c9b6' class='xr-var-data-in' type='checkbox'><label for='data-8656d720-7aba-49fb-ba05-9cb61749c9b6' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([3.287083 , 3.2605155, 3.3369133, 3.2892823, 3.3165808, 3.3119812,\n",
        "       3.3027983, 3.3258302, 3.3029814, 3.3100154, 3.3152144, 3.3549793,\n",
        "       3.3538957, 3.3682969, 3.3522127, 3.3599124, 3.3716784, 3.370829 ,\n",
        "       3.404896 , 3.4170458, 3.4101129, 3.4259632, 3.3813803, 3.352863 ,\n",
@@ -3064,7 +3146,7 @@
        "       3.2660322, 3.2617817, 3.3116815, 3.314548 , 3.289132 , 3.3249977,\n",
        "       3.287216 , 3.282166 , 3.306248 , 3.3363798, 3.3452635, 3.314365 ,\n",
        "       3.3198478, 3.3122149, 3.3298814, 3.3361466, 3.3632295, 3.3652124,\n",
-       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-34708eee-0909-42f3-b448-c01e8c115774' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34708eee-0909-42f3-b448-c01e8c115774' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c3c5e09b-6992-4d4d-b212-5e6bc9b338a4' class='xr-var-data-in' type='checkbox'><label for='data-c3c5e09b-6992-4d4d-b212-5e6bc9b338a4' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
+       "       3.331114 , 3.352297 , 3.351696 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.05523 -0.07217 ... -0.0429</div><input id='attrs-4a08860b-23aa-423c-945a-c063eb836316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a08860b-23aa-423c-945a-c063eb836316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5cde189-7339-4f00-8fbe-5d239164387b' class='xr-var-data-in' type='checkbox'><label for='data-f5cde189-7339-4f00-8fbe-5d239164387b' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-0.05523333, -0.07216667, -0.05975001, -0.0719    , -0.06111666,\n",
        "       -0.05995   , -0.07213333, -0.07148333, -0.07696667, -0.08181667,\n",
        "       -0.0731    , -0.0579    , -0.05488333, -0.05605   , -0.05533333,\n",
        "       -0.05278333, -0.047     , -0.0521    , -0.05088333, -0.04305   ,\n",
@@ -3100,7 +3182,7 @@
        "       -0.04428333, -0.05206667, -0.04676667, -0.05188334, -0.0574    ,\n",
        "       -0.06316667, -0.0484    , -0.04308333, -0.04601667, -0.0499    ,\n",
        "       -0.05471666, -0.05536667, -0.04616667, -0.02825   , -0.03388334,\n",
-       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-2b74bc41-c130-4608-be11-7c24a1e4f467' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b74bc41-c130-4608-be11-7c24a1e4f467' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b8a23a-750f-456d-a0dc-577634aa12ab' class='xr-var-data-in' type='checkbox'><label for='data-f0b8a23a-750f-456d-a0dc-577634aa12ab' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
+       "       -0.0423    , -0.04288333, -0.0429    ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-7.414 -7.424 ... -6.433 -6.436</div><input id='attrs-d0125ede-1af5-4c1c-b0d4-5a215a060da0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0125ede-1af5-4c1c-b0d4-5a215a060da0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2ca4fb0-cdef-4881-a4ee-95133428963d' class='xr-var-data-in' type='checkbox'><label for='data-d2ca4fb0-cdef-4881-a4ee-95133428963d' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([-7.414066 , -7.424116 , -7.4041324, -7.422417 , -7.4120665,\n",
        "       -7.4167333, -7.4193   , -7.4148664, -7.4301662, -7.419133 ,\n",
        "       -7.4179006, -7.402567 , -7.4040666, -7.394583 , -7.403933 ,\n",
        "       -7.394567 , -7.39615  , -7.3910007, -7.386317 , -7.3802505,\n",
@@ -3136,7 +3218,7 @@
        "       -6.4438   , -6.450166 , -6.4428334, -6.45625  , -6.455867 ,\n",
        "       -6.44465  , -6.436783 , -6.430967 , -6.4454665, -6.441799 ,\n",
        "       -6.4480996, -6.4399   , -6.4372997, -6.4309335, -6.4305167,\n",
-       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-f0ffca4e-634c-4604-a73c-a39ffcb3de93' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0ffca4e-634c-4604-a73c-a39ffcb3de93' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3baf935a-b0f8-4dfa-b30b-e05bc641911e' class='xr-var-data-in' type='checkbox'><label for='data-3baf935a-b0f8-4dfa-b30b-e05bc641911e' title='Show/Hide data repr'><svg 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>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
+       "       -6.4460497, -6.4332495, -6.4359174], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_density</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.023e+03 1.023e+03 ... 1.023e+03</div><input id='attrs-1c7b86e6-50ec-4d67-b866-4f622c15f58b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c7b86e6-50ec-4d67-b866-4f622c15f58b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fed22cfd-6672-4aea-a457-a594b514db69' class='xr-var-data-in' type='checkbox'><label for='data-fed22cfd-6672-4aea-a457-a594b514db69' title='Show/Hide data repr'><svg 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>kg m-3</dd><dt><span>long_name :</span></dt><dd>Water Density</dd><dt><span>standard_name :</span></dt><dd>sea_water_density</dd><dt><span>description :</span></dt><dd>Water density from linear approximation of sea water equation of state</dd></dl></div><div class='xr-var-data'><pre>array([1023.2506 , 1023.2348 , 1023.2431 , 1023.2559 , 1023.2423 ,\n",
        "       1023.21655, 1023.1977 , 1023.2015 , 1023.19476, 1023.19116,\n",
        "       1023.194  , 1023.1996 , 1023.20294, 1023.19666, 1023.19336,\n",
        "       1023.19763, 1023.205  , 1023.20404, 1023.2148 , 1023.2179 ,\n",
@@ -3172,7 +3254,7 @@
        "       1023.3432 , 1023.34186, 1023.34094, 1023.3408 , 1023.34   ,\n",
        "       1023.33655, 1023.34143, 1023.34155, 1023.34357, 1023.3508 ,\n",
        "       1023.3694 , 1023.37335, 1023.3781 , 1023.3796 , 1023.3752 ,\n",
-       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-75dbd849-b29e-4497-920e-3a9f77cee3ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75dbd849-b29e-4497-920e-3a9f77cee3ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da9984a4-7ab4-4c79-8055-17b61150baef' class='xr-var-data-in' type='checkbox'><label for='data-da9984a4-7ab4-4c79-8055-17b61150baef' title='Show/Hide data repr'><svg 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>m</dd><dt><span>long_name :</span></dt><dd>Depth to Seafloor</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
+       "       1023.3806 , 1023.3899 , 1023.3975 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>depth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>10.28 10.26 10.25 ... 10.15 10.15</div><input id='attrs-0b6241a6-5233-48b1-a8a3-69a1d445bbb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b6241a6-5233-48b1-a8a3-69a1d445bbb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8a0338c-e1a0-4df4-9268-e5bb5d195e9a' class='xr-var-data-in' type='checkbox'><label for='data-a8a0338c-e1a0-4df4-9268-e5bb5d195e9a' title='Show/Hide data repr'><svg 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>m</dd><dt><span>long_name :</span></dt><dd>Depth to Seafloor</dd><dt><span>standard_name :</span></dt><dd>depth</dd><dt><span>positive :</span></dt><dd>down</dd></dl></div><div class='xr-var-data'><pre>array([10.275155 , 10.262421 , 10.248638 , 10.233478 , 10.216689 ,\n",
        "       10.204074 , 10.188269 , 10.172538 , 10.158512 , 10.140744 ,\n",
        "       10.124731 , 10.10534  , 10.088593 , 10.069619 , 10.050677 ,\n",
        "       10.028841 , 10.00682  ,  9.981041 ,  9.958139 ,  9.932152 ,\n",
@@ -3208,37 +3290,99 @@
        "        9.972928 ,  9.992192 , 10.00496  , 10.023165 , 10.037822 ,\n",
        "       10.052144 , 10.058786 , 10.073322 , 10.083076 , 10.093331 ,\n",
        "       10.100321 , 10.109131 , 10.117323 , 10.123545 , 10.1341   ,\n",
-       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d033b4d2-5fe1-48fb-adaa-fac0731a998b' class='xr-section-summary-in' type='checkbox'  ><label for='section-d033b4d2-5fe1-48fb-adaa-fac0731a998b' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>earth</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>h_deploy :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
+       "       10.142311 , 10.14612  , 10.153638 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b2c7fff8-7641-4102-91fe-add237fbf750' class='xr-section-summary-in' type='checkbox'  ><label for='section-b2c7fff8-7641-4102-91fe-add237fbf750' class='xr-section-summary' >Indexes: <span>(10)</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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a34c31a1-4b8c-4810-a8b8-65c6b07e420d' class='xr-index-data-in' type='checkbox'/><label for='index-a34c31a1-4b8c-4810-a8b8-65c6b07e420d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:30.001030683&#x27;,\n",
+       "               &#x27;2020-08-15 00:27:30.001019239&#x27;,\n",
+       "               &#x27;2020-08-15 00:32:30.001010656&#x27;,\n",
+       "               &#x27;2020-08-15 00:37:30.001015901&#x27;,\n",
+       "               &#x27;2020-08-15 00:42:30.001019954&#x27;,\n",
+       "               &#x27;2020-08-15 00:47:30.001018524&#x27;,\n",
+       "               &#x27;2020-08-15 00:52:30.001013994&#x27;,\n",
+       "               &#x27;2020-08-15 00:57:30.001026630&#x27;,\n",
+       "               &#x27;2020-08-15 01:02:30.001023769&#x27;,\n",
+       "               &#x27;2020-08-15 01:07:30.001024723&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2020-08-15 14:47:30.001032352&#x27;,\n",
+       "               &#x27;2020-08-15 14:52:30.001019239&#x27;,\n",
+       "               &#x27;2020-08-15 14:57:30.001032829&#x27;,\n",
+       "               &#x27;2020-08-15 15:02:30.001021146&#x27;,\n",
+       "               &#x27;2020-08-15 15:07:30.001027345&#x27;,\n",
+       "               &#x27;2020-08-15 15:12:30.001029014&#x27;,\n",
+       "               &#x27;2020-08-15 15:17:30.001026630&#x27;,\n",
+       "               &#x27;2020-08-15 15:22:30.001026153&#x27;,\n",
+       "               &#x27;2020-08-15 15:27:30.001022577&#x27;,\n",
+       "               &#x27;2020-08-15 15:32:30.001030683&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dirIMU</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2e76e141-73e0-4c3e-be22-a18527b3beb8' class='xr-index-data-in' type='checkbox'/><label for='index-2e76e141-73e0-4c3e-be22-a18527b3beb8' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dirIMU&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-6e3539a4-3967-4920-a77e-62943a25e32b' class='xr-index-data-in' type='checkbox'/><label for='index-6e3539a4-3967-4920-a77e-62943a25e32b' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+       "                      2.7,                3.2,                3.7,\n",
+       "                      4.2,  4.699999999999999,  5.199999999999999,\n",
+       "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
+       "        7.199999999999999,  7.699999999999999,                8.2,\n",
+       "                      8.7,                9.2,                9.7,\n",
+       "                     10.2,               10.7,               11.2,\n",
+       "                     11.7,               12.2,               12.7,\n",
+       "                     13.2,               13.7,               14.2,\n",
+       "                     14.7],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8ad87ee3-2838-46bd-b3f3-e859ac0221d3' class='xr-index-data-in' type='checkbox'/><label for='index-8ad87ee3-2838-46bd-b3f3-e859ac0221d3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;streamwise&#x27;, &#x27;x-stream&#x27;, &#x27;vert1&#x27;, &#x27;vert2&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a92d0da3-82bc-4cae-b59e-faf3859ed01d' class='xr-index-data-in' type='checkbox'/><label for='index-a92d0da3-82bc-4cae-b59e-faf3859ed01d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3, 4], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-91341339-7ecd-4d58-9bb9-de34e3885a79' class='xr-index-data-in' type='checkbox'/><label for='index-91341339-7ecd-4d58-9bb9-de34e3885a79' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-027717e6-2a5a-4ec3-b149-736a18da7917' class='xr-index-data-in' type='checkbox'/><label for='index-027717e6-2a5a-4ec3-b149-736a18da7917' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>q</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c0e9da2d-f604-4161-8c89-0d6b6b95ed4f' class='xr-index-data-in' type='checkbox'/><label for='index-c0e9da2d-f604-4161-8c89-0d6b6b95ed4f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;w&#x27;, &#x27;x&#x27;, &#x27;y&#x27;, &#x27;z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;q&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time_b5</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0a4a9685-1d7f-4b73-9212-e81348c06155' class='xr-index-data-in' type='checkbox'/><label for='index-0a4a9685-1d7f-4b73-9212-e81348c06155' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2020-08-15 00:22:29.938495159&#x27;,\n",
+       "               &#x27;2020-08-15 00:27:29.938490867&#x27;,\n",
+       "               &#x27;2020-08-15 00:32:29.938487529&#x27;,\n",
+       "               &#x27;2020-08-15 00:37:29.938496828&#x27;,\n",
+       "               &#x27;2020-08-15 00:42:29.938495397&#x27;,\n",
+       "               &#x27;2020-08-15 00:47:29.938496589&#x27;,\n",
+       "               &#x27;2020-08-15 00:52:29.938497781&#x27;,\n",
+       "               &#x27;2020-08-15 00:57:29.938495397&#x27;,\n",
+       "               &#x27;2020-08-15 01:02:29.938493013&#x27;,\n",
+       "               &#x27;2020-08-15 01:07:29.938492536&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2020-08-15 14:47:29.938492774&#x27;,\n",
+       "               &#x27;2020-08-15 14:52:29.938491106&#x27;,\n",
+       "               &#x27;2020-08-15 14:57:29.938495635&#x27;,\n",
+       "               &#x27;2020-08-15 15:02:29.938493013&#x27;,\n",
+       "               &#x27;2020-08-15 15:07:29.938493967&#x27;,\n",
+       "               &#x27;2020-08-15 15:12:29.938494920&#x27;,\n",
+       "               &#x27;2020-08-15 15:17:29.938493251&#x27;,\n",
+       "               &#x27;2020-08-15 15:22:29.938486099&#x27;,\n",
+       "               &#x27;2020-08-15 15:27:29.938484191&#x27;,\n",
+       "               &#x27;2020-08-15 15:32:29.938490390&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time_b5&#x27;, length=183, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>range_b5</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8caecab9-a898-47cb-9718-35343a873e02' class='xr-index-data-in' type='checkbox'/><label for='index-8caecab9-a898-47cb-9718-35343a873e02' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([               1.2, 1.7000000000000002,                2.2,\n",
+       "                      2.7,                3.2,                3.7,\n",
+       "                      4.2,  4.699999999999999,  5.199999999999999,\n",
+       "        5.699999999999999,  6.199999999999999,  6.699999999999999,\n",
+       "        7.199999999999999,  7.699999999999999,                8.2,\n",
+       "                      8.7,                9.2,                9.7,\n",
+       "                     10.2,               10.7,               11.2,\n",
+       "                     11.7,               12.2,               12.7,\n",
+       "                     13.2,               13.7,               14.2,\n",
+       "                     14.7],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;range_b5&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-84b198aa-8149-4b92-a2f3-ea37e4d995b4' class='xr-section-summary-in' type='checkbox'  ><label for='section-84b198aa-8149-4b92-a2f3-ea37e4d995b4' class='xr-section-summary' >Attributes: <span>(41)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>fs :</span></dt><dd>1</dd><dt><span>n_bin :</span></dt><dd>300</dd><dt><span>n_fft :</span></dt><dd>300</dd><dt><span>description :</span></dt><dd>Binned averages calculated from ensembles of size &quot;n_bin&quot;</dd><dt><span>filehead_config :</span></dt><dd>{&quot;CLOCKSTR&quot;: {&quot;TIME&quot;: &quot;\\&quot;2020-08-13 13:56:21\\&quot;&quot;}, &quot;ID&quot;: &quot;STR=\\&quot;Signature1000\\&quot;,SN=101663&quot;, &quot;HW&quot;: {&quot;FW&quot;: 2212, &quot;FPGA&quot;: 169, &quot;DIGITAL&quot;: &quot;\\&quot;I-3\\&quot;&quot;, &quot;INTERFACE&quot;: &quot;\\&quot;H-2\\&quot;&quot;, &quot;ANALOG&quot;: &quot;\\&quot;G-1\\&quot;&quot;, &quot;SENSOR&quot;: &quot;\\&quot;D-1(AHRS)\\&quot;&quot;, &quot;BOOT&quot;: 21, &quot;FWMINOR&quot;: 11}, &quot;BOARDSENSGET&quot;: &quot;AV=23,NB=5,HF=1000,TTR=2.0000,TTRB5=2.0000&quot;, &quot;PWR&quot;: {&quot;PLAN&quot;: 1940.43, &quot;BURST&quot;: 1937.69, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 1940.43}, &quot;MEM&quot;: {&quot;PLAN&quot;: 2.733, &quot;BURST&quot;: 2.733, &quot;AVG&quot;: 0.0, &quot;PLAN1&quot;: 0.0, &quot;BURST1&quot;: 0.0, &quot;AVG1&quot;: 0.0, &quot;TOTAL&quot;: 2.733}, &quot;PRECISION&quot;: {&quot;AVGHORZ&quot;: -9.99, &quot;BURSTHORZ&quot;: 2.6, &quot;BEAM5&quot;: 1.62, &quot;AVGBEAM&quot;: -9.99, &quot;BURSTBEAM&quot;: 1.55}, &quot;PLAN&quot;: {&quot;MIAVG&quot;: 600, &quot;AVG&quot;: 0, &quot;DIAVG&quot;: 0, &quot;VD&quot;: 0, &quot;MV&quot;: 10, &quot;SA&quot;: 32.0, &quot;BURST&quot;: 1, &quot;MIBURST&quot;: 1, &quot;DIBURST&quot;: 0, &quot;SV&quot;: 0.0, &quot;FN&quot;: &quot;\\&quot;S101663A007_sea_spider.ad2cp\\&quot;&quot;, &quot;SO&quot;: 0, &quot;FREQ&quot;: 1000, &quot;NSTT&quot;: 0}, &quot;BURST&quot;: {&quot;NC&quot;: 28, &quot;NB&quot;: 5, &quot;CS&quot;: 0.5, &quot;BD&quot;: 0.1, &quot;CY&quot;: &quot;\\&quot;ENU\\&quot;&quot;, &quot;PL&quot;: 0.0, &quot;SR&quot;: 1, &quot;NS&quot;: 1, &quot;VR&quot;: 2.5, &quot;VP&quot;: 0.0, &quot;DF&quot;: 3, &quot;NPING&quot;: 8, &quot;CH&quot;: 0, &quot;ALTI&quot;: 0, &quot;VR5&quot;: 2.5, &quot;BT&quot;: 0, &quot;DISV&quot;: 0, &quot;ECHO&quot;: 0, &quot;RAWALTI&quot;: 60, &quot;ALTISTART&quot;: 0.1, &quot;ALTIEND&quot;: 30.0, &quot;HR&quot;: 0, &quot;HR5&quot;: 0}, &quot;XFBURST&quot;: {&quot;ROWS&quot;: 4, &quot;COLS&quot;: 4, &quot;M11&quot;: 1.1831, &quot;M12&quot;: 0.0, &quot;M13&quot;: -1.1831, &quot;M14&quot;: 0.0, &quot;M21&quot;: 0.0, &quot;M22&quot;: -1.1831, &quot;M23&quot;: 0.0, &quot;M24&quot;: 1.1831, &quot;M31&quot;: 0.5518, &quot;M32&quot;: 0.0, &quot;M33&quot;: 0.5518, &quot;M34&quot;: 0.0, &quot;M41&quot;: 0.0, &quot;M42&quot;: 0.5518, &quot;M43&quot;: 0.0, &quot;M44&quot;: 0.5518}, &quot;USER&quot;: {&quot;POFF&quot;: 10.2, &quot;DECL&quot;: 0.0, &quot;HX&quot;: -48, &quot;HY&quot;: 48, &quot;HZ&quot;: 0}, &quot;INST&quot;: {&quot;BR&quot;: 9600, &quot;RS&quot;: 232, &quot;LED&quot;: &quot;\\&quot;OFF\\&quot;&quot;, &quot;ORIENT&quot;: &quot;\\&quot;AHRS3D\\&quot;&quot;, &quot;CMTOUT&quot;: 300, &quot;DMTOUT&quot;: 60, &quot;CFMTOUT&quot;: 60}, &quot;COMPASSCAL&quot;: {&quot;DX&quot;: 155, &quot;DY&quot;: 778, &quot;DZ&quot;: -486, &quot;M11&quot;: 31481, &quot;M12&quot;: 1726, &quot;M13&quot;: -1109, &quot;M21&quot;: -1955, &quot;M22&quot;: 32767, &quot;M23&quot;: 379, &quot;M31&quot;: 750, &quot;M32&quot;: -1851, &quot;M33&quot;: 31699}, &quot;READAHRS&quot;: &quot;STR=\\&quot;OSv6_a2_V5101_0.6 Oct  3 2019, SerialNumber=60004222,type=OS3DM\\&quot;&quot;, &quot;RECSTAT&quot;: &quot;SS=512,CS=32768,FC=127813877760,TC=127848677376,VS=127848677376&quot;, &quot;BEAMCFGLIST&quot;: [&quot;BEAM=1,THETA=25.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=1,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=2,THETA=25.00,PHI=-90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=2,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=3,THETA=25.00,PHI=180.00,FREQ=1000,BW=25,BRD=1,HWBEAM=3,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=4,THETA=25.00,PHI=90.00,FREQ=1000,BW=25,BRD=1,HWBEAM=4,ZNOM=60.00,DIA=0.0&quot;, &quot;BEAM=5,THETA=0.00,PHI=0.00,FREQ=1000,BW=25,BRD=1,HWBEAM=5,ZNOM=60.00,DIA=0.0&quot;], &quot;BEAMIMPLIST&quot;: [&quot;BEAM=1,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=2,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=3,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=4,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;, &quot;BEAM=5,P0=1.00000e+02,P1=0.00000e+00,P2=0.00000e+00,P3=0.00000e+00,P4=0.00000e+00,T1=0.00000e+00&quot;], &quot;LISTLICENSE&quot;: [&quot;KEY=\\&quot;C390Y1LU32C1B\\&quot;,DESC=\\&quot;Averaging Mode\\&quot;,TYPE=1&quot;, &quot;KEY=\\&quot;6F2UB3HTH2C1B\\&quot;,DESC=\\&quot;Burst Five Beams\\&quot;,TYPE=17&quot;, &quot;KEY=\\&quot;R0X9JSZPH2C1B\\&quot;,DESC=\\&quot;128GB Recorder\\&quot;,TYPE=14&quot;], &quot;CALCOMPGET&quot;: &quot;DX=155,DY=778,DZ=-486,M11=31481,M12=1726,M13=-1109,M21=-1955,M22=32767,M23=379,M31=750,M32=-1851,M33=31699&quot;, &quot;CALTEMPGET&quot;: &quot;SC=0.99906&quot;, &quot;CALTILTGET&quot;: &quot;PO=0.00,RO=0.00,MAGG=1,HO=0.00&quot;, &quot;CALACCLGET&quot;: [&quot;AX=1.000000E+00,B0X=1.791816E-02,B1X=-1.795970E-02,B2X=6.661898E-04,B3X=0.000000E+00,A1X=1.146936E-05,A2X=7.326843E-06,A3X=0.000000E+00&quot;, &quot;AY=1.000000E+00,B0Y=9.597497E-03,B1Y=-8.430577E-03,B2Y=9.310668E-04,B3Y=0.000000E+00,A1Y=7.215003E-05,A2Y=1.361528E-06,A3Y=0.000000E+00&quot;, &quot;AZ=1.000000E+00,B0Z=1.290458E-02,B1Z=2.959575E-02,B2Z=2.331257E-03,B3Z=0.000000E+00,A1Z=1.164268E-04,A2Z=-2.166612E-06,A3Z=0.000000E+00&quot;], &quot;CALGYROGET&quot;: [&quot;AX=1.094973E+00,B0X=-2.672331E+00,B1X=-1.493178E-03,B2X=9.496510E-05,B3X=0.000000E+00,A1X=2.702698E-04,A2X=8.100271E-05,A3X=0.000000E+00&quot;, &quot;AY=1.080807E+00,B0Y=3.432283E-01,B1Y=7.219538E-04,B2Y=1.416728E-04,B3Y=0.000000E+00,A1Y=9.466633E-04,A2Y=-4.216283E-05,A3Y=0.000000E+00&quot;, &quot;AZ=1.085556E+00,B0Z=-9.442614E-01,B1Z=6.433576E-04,B2Z=-1.306087E-05,B3Z=0.000000E+00,A1Z=1.430541E-03,A2Z=-7.494539E-05,A3Z=0.000000E+00&quot;], &quot;CALPRESSGET&quot;: &quot;MT=1,RREF=4.5264760000e+02,RB0=7.7074756250e-01,RB1=-7.5541806250e-02,RB2=4.9886362500e-04,RB3=-1.4193179690e-07,T0=-2.4234620000e+03,T1=1.8815180000e+00,T2=-5.0111803130e-04,T3=4.7281500000e-08,ID=\\&quot;K244314\\&quot;&quot;, &quot;CALPRESSCOEFFGET&quot;: [&quot;A0=6.3850020000e+00,A1=-5.6274000000e-03,A2=1.6346411250e-06,A3=-1.6029240630e-10,B0=-2.6056009380e-01,B1=3.1699690630e-04,B2=-9.0774206250e-08,B3=8.5142393750e-12&quot;, &quot;C0=-1.2762860000e-03,C1=1.1561740000e-06,C2=-3.5109818750e-10,C3=3.5575718750e-14,D0=3.6002040630e-06,D1=-3.3359181250e-09,D2=1.0241850000e-12,D3=-1.0446648750e-16&quot;], &quot;CALROTACCLGET&quot;: &quot;M11=0.99144,M12=0.00991,M13=-0.03081,M21=-0.00921,M22=0.99564,M23=0.01131,M31=0.03451,M32=-0.01242,M33=0.98426&quot;, &quot;CALROTGYROGET&quot;: &quot;M11=1.00000,M12=0.00803,M13=-0.02685,M21=-0.00933,M22=1.00000,M23=0.01646,M31=0.02587,M32=-0.01599,M33=1.00000&quot;, &quot;CALECHOGET&quot;: &quot;CHA0=0.00,CHB0=-17.69,CHC0=0.00&quot;}</dd><dt><span>inst_model :</span></dt><dd>Signature1000</dd><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_type :</span></dt><dd>ADCP</dd><dt><span>burst_config :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells :</span></dt><dd>28</dd><dt><span>n_beams :</span></dt><dd>4</dd><dt><span>ambig_vel :</span></dt><dd>5.066</dd><dt><span>SerialNum :</span></dt><dd>101663</dd><dt><span>cell_size :</span></dt><dd>0.5</dd><dt><span>blank_dist :</span></dt><dd>0.1</dd><dt><span>nominal_corr :</span></dt><dd>67</dd><dt><span>power_level_dB :</span></dt><dd>0.0</dd><dt><span>burst_config_b5 :</span></dt><dd>{&quot;press_valid&quot;: true, &quot;temp_valid&quot;: true, &quot;compass_valid&quot;: true, &quot;tilt_valid&quot;: true, &quot;vel&quot;: true, &quot;amp&quot;: true, &quot;corr&quot;: true, &quot;le&quot;: false, &quot;altraw&quot;: false, &quot;ast&quot;: false, &quot;echo&quot;: false, &quot;ahrs&quot;: true, &quot;p_gd&quot;: false, &quot;std&quot;: false}</dd><dt><span>n_cells_b5 :</span></dt><dd>28</dd><dt><span>coord_sys_axes_b5 :</span></dt><dd>beam</dd><dt><span>n_beams_b5 :</span></dt><dd>1</dd><dt><span>ambig_vel_b5 :</span></dt><dd>5.066</dd><dt><span>SerialNum_b5 :</span></dt><dd>101663</dd><dt><span>cell_size_b5 :</span></dt><dd>0.5</dd><dt><span>blank_dist_b5 :</span></dt><dd>0.1</dd><dt><span>nominal_corr_b5 :</span></dt><dd>65</dd><dt><span>power_level_dB_b5 :</span></dt><dd>0.0</dd><dt><span>wakeup_state :</span></dt><dd>clock</dd><dt><span>orientation :</span></dt><dd>AHRS</dd><dt><span>orient_status :</span></dt><dd>AHRS-3D</dd><dt><span>proc_idle_less_3pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_6pct :</span></dt><dd>0</dd><dt><span>proc_idle_less_12pct :</span></dt><dd>0</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;, &#x27;accel&#x27;, &#x27;accel_b5&#x27;, &#x27;angrt&#x27;, &#x27;angrt_b5&#x27;, &#x27;mag&#x27;, &#x27;mag_b5&#x27;]</dd><dt><span>coord_sys :</span></dt><dd>principal</dd><dt><span>has_imu :</span></dt><dd>1</dd><dt><span>beam_angle :</span></dt><dd>25</dd><dt><span>h_deploy :</span></dt><dd>0.6</dd><dt><span>declination :</span></dt><dd>15.8</dd><dt><span>declination_in_orientmat :</span></dt><dd>1</dd><dt><span>principal_heading :</span></dt><dd>11.1898</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:         (time: 183, dirIMU: 3, range: 28, dir: 4, beam: 4,\n",
+       "<xarray.Dataset> Size: 379kB\n",
+       "Dimensions:         (time: 183, range: 28, dirIMU: 3, dir: 4, beam: 4,\n",
        "                     earth: 3, inst: 3, q: 4, time_b5: 183, range_b5: 28)\n",
        "Coordinates:\n",
-       "  * time            (time) datetime64[ns] 2020-08-15T00:22:30.001030683 ... 2...\n",
-       "  * dirIMU          (dirIMU) <U1 'E' 'N' 'U'\n",
-       "  * range           (range) float64 1.2 1.7 2.2 2.7 3.2 ... 13.2 13.7 14.2 14.7\n",
-       "  * dir             (dir) <U2 'E' 'N' 'U1' 'U2'\n",
-       "  * beam            (beam) int32 1 2 3 4\n",
-       "  * earth           (earth) <U1 'E' 'N' 'U'\n",
-       "  * inst            (inst) <U1 'X' 'Y' 'Z'\n",
-       "  * q               (q) <U1 'w' 'x' 'y' 'z'\n",
-       "  * time_b5         (time_b5) datetime64[ns] 2020-08-15T00:22:29.938495159 .....\n",
-       "  * range_b5        (range_b5) float64 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * time            (time) datetime64[ns] 1kB 2020-08-15T00:22:30.001030683 ....\n",
+       "  * dirIMU          (dirIMU) <U10 120B 'streamwise' 'x-stream' 'vert'\n",
+       "  * range           (range) float64 224B 1.2 1.7 2.2 2.7 ... 13.2 13.7 14.2 14.7\n",
+       "  * dir             (dir) <U10 160B 'streamwise' 'x-stream' 'vert1' 'vert2'\n",
+       "  * beam            (beam) int32 16B 1 2 3 4\n",
+       "  * earth           (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst            (inst) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * q               (q) <U1 16B 'w' 'x' 'y' 'z'\n",
+       "  * time_b5         (time_b5) datetime64[ns] 1kB 2020-08-15T00:22:29.93849515...\n",
+       "  * range_b5        (range_b5) float64 224B 1.2 1.7 2.2 2.7 ... 13.7 14.2 14.7\n",
        "Data variables: (12/38)\n",
-       "    c_sound         (time) float32 1.502e+03 1.502e+03 ... 1.499e+03 1.498e+03\n",
-       "    U_std           (range, time) float32 0.04232 0.04293 0.04402 ... nan nan\n",
-       "    temp            (time) float32 14.49 14.59 14.54 14.45 ... 13.62 13.56 13.5\n",
-       "    pressure        (time) float32 9.712 9.699 9.685 9.67 ... 9.58 9.584 9.591\n",
-       "    mag             (dirIMU, time) float32 72.37 72.4 72.38 ... -197.1 -197.1\n",
-       "    accel           (dirIMU, time) float32 -0.3584 -0.361 ... 9.714 9.712\n",
+       "    c_sound         (time) float32 732B 1.502e+03 1.502e+03 ... 1.498e+03\n",
+       "    U_std           (range, time) float32 20kB 0.04232 0.04293 ... nan nan\n",
+       "    temp            (time) float32 732B 14.49 14.59 14.54 ... 13.62 13.56 13.5\n",
+       "    pressure        (time) float32 732B 9.712 9.699 9.685 ... 9.58 9.584 9.591\n",
+       "    mag             (dirIMU, time) float32 2kB 3.534 3.565 ... -197.1 -197.1\n",
+       "    accel           (dirIMU, time) float32 2kB -1.261 -1.263 ... 9.714 9.712\n",
        "    ...              ...\n",
-       "    boost_running   (time) float32 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
-       "    heading         (time) float32 3.287 3.261 3.337 3.289 ... 3.331 3.352 3.352\n",
-       "    pitch           (time) float32 -0.05523 -0.07217 ... -0.04288 -0.0429\n",
-       "    roll            (time) float32 -7.414 -7.424 -7.404 ... -6.446 -6.433 -6.436\n",
-       "    water_density   (time) float32 1.023e+03 1.023e+03 ... 1.023e+03 1.023e+03\n",
-       "    depth           (time) float32 10.28 10.26 10.25 10.23 ... 10.14 10.15 10.15\n",
+       "    boost_running   (time) float32 732B 0.1267 0.1333 0.13 ... 0.2267 0.22 0.22\n",
+       "    heading         (time) float32 732B 3.287 3.261 3.337 ... 3.331 3.352 3.352\n",
+       "    pitch           (time) float32 732B -0.05523 -0.07217 ... -0.04288 -0.0429\n",
+       "    roll            (time) float32 732B -7.414 -7.424 -7.404 ... -6.433 -6.436\n",
+       "    water_density   (time) float32 732B 1.023e+03 1.023e+03 ... 1.023e+03\n",
+       "    depth           (time) float32 732B 10.28 10.26 10.25 ... 10.14 10.15 10.15\n",
        "Attributes: (12/41)\n",
        "    fs:                        1\n",
        "    n_bin:                     300\n",
@@ -3312,7 +3456,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.colorbar.Colorbar at 0x23381c571f0>"
+       "<matplotlib.colorbar.Colorbar at 0x1e5bdaccf10>"
       ]
      },
      "execution_count": 18,
@@ -3360,7 +3504,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 1000x600 with 2 Axes>"
       ]
@@ -3433,7 +3577,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x23383d2c940>"
+       "<matplotlib.collections.QuadMesh at 0x1e5bd55dc00>"
       ]
      },
      "execution_count": 21,
@@ -3442,7 +3586,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3484,7 +3628,7 @@
     ")  # flow speed, for plotting in the next block\n",
     "\n",
     "ds_avg[\"auto_spectra_5m\"] = avg_tool.power_spectral_density(\n",
-    "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 3\n",
+    "    vel_up, freq_units=\"Hz\", n_fft=ds_avg.n_bin // 2\n",
     ")"
    ]
   },
@@ -3518,7 +3662,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 2 Axes>"
       ]
@@ -3645,7 +3789,7 @@
     "f_rng = [0.2, 0.5]\n",
     "# Dissipation rate\n",
     "ds_avg[\"dissipation_rate_5m\"] = avg_tool.dissipation_rate_LT83(\n",
-    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg[\"noise_5m\"]\n",
+    "    ds_avg[\"auto_spectra_5m\"], U, freq_range=f_rng, noise=ds_avg['noise_5m']\n",
     ")"
    ]
   },
@@ -3673,10 +3817,10 @@
     "    spec[r] = avg_tool.power_spectral_density(\n",
     "        ds[\"vel_b5\"].isel(range_b5=r), freq_units=\"Hz\"\n",
     "    )\n",
-    "\n",
+    "    \n",
     "    # Calculate doppler noise from spectra from each depth bin\n",
     "    n[r] = avg_tool.doppler_noise_level(spec[r], pct_fN=0.9)\n",
-    "\n",
+    "    \n",
     "    # Calc dissipation rate from each spectra\n",
     "    e[r] = avg_tool.dissipation_rate_LT83(\n",
     "        spec[r], ds_avg.velds.U_mag.isel(range=r), freq_range=f_rng, noise=n[r]\n",
@@ -3734,7 +3878,7 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x233920e4070>"
+       "<matplotlib.collections.QuadMesh at 0x1e5c32ab940>"
       ]
      },
      "execution_count": 28,
@@ -3743,7 +3887,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3784,7 +3928,7 @@
     },
     {
      "data": {
-      "image/png": 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RkcBNDYAAD442WWzAzxeQlZVV6t9vJ0+eRFxcHFq3bo1Dhw5pxn3//fcYMmQIRowYUeZTVPXr10daWhpSUlLQvHlzl/ELFixAQEAAHnvsMc3wixcv4tprr8WlS5cwduxYLF++vNTT5OmwUpCnwCIiIpgEERFRqVTJ5RMGnWdJUDmqrly5EhaLBX369HEZ16tXLwDA2rVrkZGRgdq1a5e63audkjMYDHj44YddhtetWxfjxo3DvHnzcPHixVJPD+CF0URERFQG69atAwC0bNnSZVxMTAwaN24Ms9mMbdu2landqyWNkydPLvEaq7i4OABAs2bNyjRNJkFERES+SlE8/8B+es35YzKZSpzk3r17AQCxsbFux0dFRQEA9u3bV6GhXkl6ejoA4O677y5TPSZBREREvkzx4OPQpEkTREZGqp9Zs2a5nZTRaERubi6AomSnOHkdlExMqsKPP/6Ijh07YtCgQWWqx2uCiIiI/FzxG3+CgoLclsvIyFB/Dg0NdVtGnrIyGo0V2MOS7d+/H7/88gs2b95c5kcSMAkiIiLyVU6ntMpdH6W/8cdgMKg/l3RzuXx2UUxMTPn7VQZPPfUUpk2bhptuuqnMdZkEERER+SodPLuwpYx1Y2JiYDAYYDabkZeX57ZMZmYmAKBOnToedKx0FixYgPDwcMycObNc9XlNEBEREZWKXq9Hu3btAADnzp1zWyY1NRUA0Llz50rty5YtW7B27VqsWLGi3E/mZhJERETkqyro7rCykBcfF39QImC/GDorKwthYWHo16+fx+GV5Pfff8dLL72EtWvXlnhtUmkwCSIiIvJVntwZVuwOsdKaOHEidDqd25elJicnAwCGDh2quX6oIh0/fhyPPvooVq1ahejoaJfxKSkppW6LSRARERGVWlxcHCZNmoSDBw+6PAsoISEBISEhmDFjhjosKSkJvXr1wrvvvnvFdi0WCwDAarWWWOb48eOYMGECPvvsMzRo0EAzrqCgAO+88w4+/fTTUsfCC6OJiIh8lU6xfzypXw5z5szBrl278Mgjj2D9+vWIjo7GwoUL8e233yIxMVHzNOm5c+di586dOHz4MKZMmeK2vZSUFKSlpQEAtm/fjlatWrmUOXDgAG677Tbk5uaiW7dumnFWqxXZ2dmw2Wz4448/Sh0HjwQRERH5Ki+cDgOAsLAwJCUloXfv3ujRowfi4uKwadMm7Nq1C8OGDdOUHTlyJMLDwzFu3Di3bTVr1gytW7dGYWEhAGDMmDFo1KiR5ijTuXPn0L9/f6SmpiIvLw8ZGRmaT2ZmJmw2G3r27Ilrrrmm1HHwLfKlIN/WW5a37BIRkX+qit8Z6lvk/9EMCPTgeEahDfj2b7/9/cYjQUREROSXeE0QERGRr/LglJZa348xCSIiIvJVXrowuqbg6TAiIiLySzwSRERE5Kt4OswjTIKIiIh8VQW9Rd5f8XQYERER+SUeCSIiIvJVvDDaI0yCiIiIfBWvCfIIT4cRERGRX/LZJGjdunXo06cPPvnkkyuW27NnD+644w60aNEC11xzDaZNm4aCgoKq6SQREVFlUlB0cXS5Pt4OwLt8LglatWoVevXqhTvvvBPJyclXLPvtt9+iT58+GDBgAFJSUrB7925s27YNAwYMQF5eXhX1mIiIqBJV8ctTaxKfS4J69OiBrVu3Ii4u7orlTp8+jdGjR+OWW27B1KlTAQCRkZFYunQptm/fjmeffbYquktERFR55IXRnnz8mM8lQS1btkRQUBC6du16xXKvvvoqcnJyMH78eM3wNm3a4LrrrsOiRYtw5MiRyuwqERERVWM+lwRJwcHBJY4rLCzE6tWrAQB9+vRxGd+7d28IIfDRRx9VWv+IiIgqnSenwnhKzHdvkVeu8JTLn3/+GdnZ2QgKCkLjxo1dxnfs2BEAkJSUVGn9IyIiqnR8YrRHfDYJupK9e/cCgNsECACioqIAAAcPHoTVaoVer9eMN5lMMJlM6vfs7OzK6SgRERF5jc+eDruSixcvAihKdoqLjIwEAFgsFmRlZbmMnzVrFiIjI9VPkyZNKq2vRERE5aargI8fq5HhZ2RkAABCQ0PdjtfpisI2Go0u46dPn46srCz1c/r06crpKBERkSc8ekaQh6fSaoAaeTrMYDAAAIQQbsebzWb155iYGJfxQUFBCAoKqpzOERERUbVQI5OgBg0aAECJD0TMzMwEAISFhV3xLjMiIqJqje8O80iNTII6deoEADh37pzb8ampqQCAzp07V1mfiIiIKhzvDvNIjbwm6Oabb4bBYEBaWhrS09Ndxp84cQIAMGTIkKruGhEREVUTNTIJioiIwIgRIwAAW7dudRmfnJwMnU6H4cOHV3XXiIiIKg7vDvOIz4ZvsVgAAFar1e34GTNmICwsDMuXL9cM//3337Fnzx489NBDV33/GBERUbXGu8M84pNJUEFBAQ4cOAAA2L59u9syrVq1wocffoh169bhs88+AwCcOnUKY8aMwQ033IB58+ZVWX+JiIgqBV+b4RGfS4Luv/9+1KlTBwcPHgQAfPTRR6hduzYWLVrkUnb06NFYv3493n//fbRs2RJDhgzB2LFjsWnTphKfIURERET+wefuDvviiy/KVP7WW2/FrbfeWkm9ISIi8iKdYv94Ut+P+VwSRERERA68Rd4jPnc6jIiIiKgi8EgQERGRr+IToz3CJIiIiMhnKVA8OKUl/DwL4ukwIiIi8ks8EkREROSjFMWzI0FQFIiK647PYRJERETkozx+6LMCv06CeDqMiIiI/BKPBBEREfkonYenw4SiwFaB/fE1TIKIiIh8VEVcE+TPmAQRERH5KCZBnuE1QUREROSXeCSIiIjIR/FIkGeYBBEREfmoirhF3p/xdBgRERH5JSZBREREPkqeDvPkU15msxmzZ89GmzZt0KpVK/Tr1w9bt24tV1tGoxHvv/8+mjdvjpMnT161/JdffonrrrsOLVu2RKdOnfDRRx+Va7o8HUZEROSjvHVNkMlkwuDBg5GamoqNGzeiadOmWL16NQYOHIjExETEx8eXqp38/Hx88MEHWLBgAU6fPl2qOs8//zwWLlyI7777Dv369cPRo0fRt29fHDhwAO+++26Z4uCRICIiIiqTadOmISkpCcuWLUPTpk0BAPHx8Rg2bBjGjx+PlJSUUrVjtVrxwAMPICkpCTrd1VOSr7/+GrNmzcJLL72Efv36AQCuvfZazJw5EwsXLsSqVavKFAeTICIiIh+lVMB/ZXXy5Em89957aNeuHXr27KkZN3bsWOTl5WH69Omlais8PBx169ZFq1atUKdOnSuWtdls+L//+z8oioIHH3xQM27UqFHQ6/WYOnUqrFZrqWNhEkREROSjvHFN0MqVK2GxWNCnTx+Xcb169QIArF27FhkZGWVqNzg4+Irjd+3ahT/++AOtWrVCvXr1NONq1aqF9u3b4+zZs1i/fn2pp8kkiIiIyEfJW+Q9+ZTVunXrAAAtW7Z0GRcTE4PGjRvDbDZj27ZtZYzlyp250nQBoGPHjgCApKSkUk+TSRARERGV2t69ewEAsbGxbsdHRUUBAPbt21ftp8u7w4iIiHyUTrn6EZQrEY6q2dnZmuFBQUEICgpyKW80GpGbmwugKOkoLjIyEgCQnp5e7n65c/HixQqfLo8EERER+aiKuiaoSZMmiIyMVD+zZs1yOz3n63xCQ0PdlpF3eRmNxgqNVU67IqfLI0FlcMmUhpz8S+r3EH0YAECn2Ge82WYCAPVqe4POnkU7Z+kRgdEAgJzCLEdd+ziLzQIAiDTEVFr/iYio9C4azwMA/s75CwBQN6Q+AKBZrWvUMj9f+BEAUCsw3F4muB5y8nKqspsV4vTp04iIiFC/uzsKBAAGg0H9WQjhtozZbAZgvz6oIslpV+R0mQQRERH5qIp6WGJERIQmCSpJTEwMDAYDzGYz8vLy3JbJzMwEgKve8l5WDRo0wOHDhyt0ujwdRkRE5Ks8vTOsjPmTXq9Hu3btAADnzp1zWyY1NRUA0LlzZ08ic9GpU6cKny6TICIiIiq1QYMGAQAOHTrkMi49PR1ZWVkICwtTn+hcFdMFgBMnTgAAhgwZUuo2mQQRERH5KG88LHHixInQ6XRuX5aanJwMABg6dKjm+qGKMHDgQLRo0QJHjhxR7xSTMjMzceTIEbRo0QK9e/cudZtMgoiIiHyUN5KguLg4TJo0CQcPHnR5Jk9CQgJCQkIwY8YMdVhSUhJ69ep11ZebWiz2G4RKeu1FQEAAZs2aBZvNhsTERM24zz77DDabDa+//jr0en2pY2ESRERERGUyZ84cdO/eHY888gguXboEIQTeffddfPvtt1i+fLnmqc5z587Fzp078cILL5TYXkpKCtLS0gAA27dvL7HciBEj8PDDD2PmzJk4cOAAAODnn3/GCy+8gKeeegojR44sUxy8O4yIiMhHKfDs7rDyvEAVAMLCwpCUlISXXnoJPXr0gE6nQ4cOHbBr1y71AmZp5MiR2Lp1Kx544AG3bTVr1gznzp1TjwSNGTMGzz77LNavX48uXbq4lP/ggw/QoUMH3H///TCZTKhfvz6WL1+Ou+++u8xxKKKkG+5JlZ2djcjISKSk/YHAsKK8kc8JIiKqucr9nKDsHLRr1BlZWVmluu28POTvpbrTr4cuuPzHM2xGCy7OSq7UvlZnPBJERETko8r7ElTn+v6M1wQRERGRX+KRICIiIh/l6ROjPXradA3AJIiIiMhHMQnyDE+HERERkV/ikSAiIiIfpVMU9S7jcvHzI0FMgoiIiHwU7w7zDE+HERERkV/ikaAykg81BICAQPvsK7SZAQBhAfaHZVmFvYx8MGK+JVetk2W+BKDoAYsyD5UXp6UWnAEABOtD1TrFH6AoH7QYHhjpdri9fcXRp7I//CrPkmPvk+Ohj1ZhdTs9IiJn2YWXATg/hdj+r9xHAkBIQKimTKGtEMCV92dynGzfJmwAAL2i13y3iaJ3Thn0wQCK9sdyegL25wPnW/IAOO+LgXrBjTR9qBvc0NGGvd0Qp/2yZLFZNTHmW/JQYMl3KVdZeGG0Z5gEERER+SjF8Z8n9f0ZT4cRERGRX+KRICIiIh/F02GeYRJERETko5gEeYZJEBERkY/iLfKe4TVBRERE5Jd4JIiIiMhH8XSYZ2r8kaBffvkFQ4YMQYMGDRAbG4s2bdpgxowZMBqN3u4aERGRR2QS5MnHn9XoJGj16tXo168fevXqhdOnT+PMmTP44osvsGzZMgwYMABms/nqjRAREVGNVGOTIJPJhMmTJ2PgwIGYMWMGAgMDAQBdu3bF66+/jl9//RVLly71ci+JiIg84OlRID8/ElRjrwk6cOAAMjIy0KVLF5dx3bp1AwAcPHiwintFRERUcXh3mGdq7JGgsLAwAMCOHTtcxuXk2N+N5S5BIiIiIv9QY5Ogtm3bIi4uDlu2bMGKFSs049auXYuOHTti3LhxXuodERGR53hhtGdqbBKkKAoWL14Mg8GABx98EJ9//jkAYNu2bdi9ezd++uknBAUFua1rMpmQnZ2t+RAREVU39tNhniRB3o7Au2rsNUEA0L9/f6xZswbDhw/HmDFjsHPnTgQEBOB///sf9Hp9ifVmzZqFV199tQp7SkRERFWtRidBAHDnnXfirbfewokTJ/Duu+8iODgYPXr0wP33319inenTp2Pq1Knq9+zsbDRp0qQquktERFRqfFiiZ2p8EvTWW28hLi4Ojz/+OPr06YMxY8Zg1KhRSE9Px+OPP+62TlBQkNtTZTFB9SAMhep3q80CAAjUGezfhf17RGA0ACC78LJLG5GGGABAmvGcfVo6+3QCdIGatvRK0ZGqfIv9Qm4BAQAID4zUtJlbmOV2uHMfFMeZzwCdfZGH6MNcykphAeEljiOi6kVu/7Wctn+53esV+/Yuf82FFtu2cwoz1Z/lvkfuZ+Q+Qu5/FMW+D7HYivaBcr8lyyqOKck2Ah3jraKojixbYM0DABTaTJrvcr/qvD+T/QxwxBMaaI8jy3zJ0b4VABATVBfFybo6R/9lWbnvtcGmls1zxFp8H9ggJBYA8EfWIQBF+3EAiItsDaBon30672/kFua59KOyKPDw7rAK64lvqrHXBAHAnDlz8NVXX+Hee+8FAAwfPhyrVq2CTqfDlClTsG3bNi/3kIiIqPx4YbRnamwS9Pfff+PFF1/EHXfcoRl+zz33YPbs2RBC8LofIiIiP1Zjk6B169bBZDKhXr16LuOefPJJ1K1bFzt37vRCz4iIiCoGjwR5psYmQfK9YGfOnHEZFxAQgObNm8NgMFR1t4iIiCoMkyDP1Ngk6M4774Rer8eXX34Ji8WiGZeVlYWjR49i6NChXuodEREReVuNTYKuueYavP322zh69CjGjx+PrCz7HRQXLlzA/fffj2bNmuGNN97wci+JiIjKT747zJOPP6uxSRAAPPXUU1i3bh3OnTuHFi1aoFmzZujXrx+6deuGX3/9FdHR0d7uIhERUbnxdJhnavxzgoYMGYIhQ4Z4uxtERERUzdT4JIiIiKjG8vScFo8EERERkS/iazM8U6OvCSIiIiIqCY8EERER+SieDfMMkyAiIiIfxdNhnmESRERE5KOYBHmG1wQRERGRX+KRICIiIh/FI0GeYRJUBhnGVNQy1FK/B+rsL2DVOQ6o2WADAFwypQEAYoLsb7DPMKWqdfIsOQCAEH2YY4gAAJisJm2bStFBOpuwue1PbqH9VSC1AiNdxsnpRARqn4qdb8ktMb4s8yUAQKQhBgBQYM0r1tfSy7NkAwDCAiLKXJfIF2WZMwAABn2wZrjcfuQ2CQBhAeFlbj/fUV9x7BvkfkF+l/sDoGifpMD+Cy40oJamjNxn6JWiXwHB+lAARdt98W1YTt9531R83xCgCwQACCEcfbQCAAJ1QU5x2PdBVmHRTFf2VbbvvK9y7qdzXwx6e7uFNvsLs+UysE9TviBbcUzP6uibTTMdndMJEblciu8LpZjgOiguJMDe/8sm+7Rjw5ohx5rjUq6y8MJoz/B0GBEREfklJkFEREQ+ypvvDjObzZg9ezbatGmDVq1aoV+/fti6dWuZ27lw4QIefvhhtGzZEi1atMCIESNw6tSpEsv//fffGD9+PGJjY9G0aVM0adIEEyZMwOnTp8s8bSZBREREvsrTBKicSZDJZMLtt9+OTz/9FBs3bsSff/6Jxx9/HAMHDsTq1atL3U5KSgp69OiBzMxMHDp0CCdOnECjRo3Qo0cPHDt2zKX8H3/8ge7du+PSpUvYt28fTp06hd27d+Pvv/9Gjx498Ndff5UpDiZBREREVCbTpk1DUlISli1bhqZNmwIA4uPjMWzYMIwfPx4pKSlXbcNqtSI+Ph5msxkff/wxQkJCoNfrMWfOHAQHB2P48OEoLCzU1Jk6dSpsNhs+//xz1Kljv0arXr16+OSTT5CWlobp06eXKQ4mQURERD7KG6fDTp48iffeew/t2rVDz549NePGjh2LvLy8UiUjK1aswO7duxEfH4+wsKKL7PV6PUaOHIkDBw5g6dKlmjqbNm1CXFycpjwANGnSBHXq1MHBgwfLFAuTICIiIh/ljSRo5cqVsFgs6NOnj8u4Xr16AQDWrl2LjIwMl/HOEhMTAcBtO7179wYALFmyRDM8LCwMhw8fRm6u9k5nm82G/Px8dOnSpdRxAEyCiIiIqAzWrVsHAGjZsqXLuJiYGDRu3Bhmsxnbtm0rsY38/Hxs3ry5xHY6duwIANi7dy+ysooe/3DXXXchNzcXTz/9tKb8//73P+j1esyYMaNMsTAJIiIi8lHy2mZPPgCQnZ2t+ZhMphKnuXfvXgBAbGys2/FRUVEAgH379pXYxpEjR2A0GktsR7YhhMD+/fvV4TNnzkSTJk2wePFiTJkyBTabDWlpaZg1axZ++ukntGnTpsRpusOHJRIREfkoBR4+MdrxMMkmTZpohs+YMQOvvPKKS3mj0aieipKJSnGRkfaHcaanp5c43YsXL6o/u2tHtlG8nQYNGiApKQkDBw7EwoULcebMGURGRuKbb75BdHS0SztXwySIiIjIR1XUazNOnz6NiIiiJ/wHBQW5Le98nU9oaKjbMjqd/SSTPNJTnnZkG+7aadWqFRITE7Fy5UokJCQgKysLtWvXxltvvaWpVxo8HUZEROTnIiIiNJ+SkiCDwaD+LF+PUpzZbH+NSUxMjNvxpWlHtuGunR9//BHff/89FixYgG3btqFRo0aYO3cuRo0aBZvN/WumSsIkiIiIyEdV9d1hMTExagKTl5fntkxmZiYAqM/xcadBgwbqz+7akW0Ub2fbtm0YNmyYemF0+/btsWXLFtSvXx8rV67Em2++WepYACZBREREPquiLowuLb1ej3bt2gEAzp0757ZMaqr9peGdO3cusZ0OHTqoCZi7dmQbBoMBbdu2BWC/DX7SpEno3r275jqia665Bl9//TUCAgIwe/bsK56GK45JEBEREZXaoEGDAACHDh1yGZeeno6srCyEhYWhX79+JbYRHR2tPmjRXTsnTpwAAPTt21d9MOLRo0dx+PBh1KtXz6V87969ceeddyI7OxtHjx4tdSxMgoiIiHyUNx6WOHHiROh0OrcvS01OTgYADB06VHPdjzuTJk0CgCu2M2rUKHWYvE7ozJkzbtuLi4sDgKtO1xmTICIiIl+lwMPzYWWfZFxcHCZNmoSDBw+6PAsoISEBISEhmocWJiUloVevXnj33Xc1ZceOHYuOHTti1apVmlNYZrMZX3zxBTp06IAxY8aowzt16oSWLVti586dbl+UumPHDrRt21Y9XVcavEW+DIIDQlE3uKH6PdNsf3aB0VoAADDo7VfTxwTZD9VdNJ4HUPQcBgAwWe0LWsB+BbteCdB8FxCafwHAJscJ7VXvxa+nz7cUPUZcUYflaNoLC4hASSIN2ivwQ/RhJZS8uitNx5flOeYnAIQFhAMomu+hAbXc1imwFl30V9I8lW1YhRUAYHP8a2dfdjpFr6kj1x053TxLtlPf7PM/tzDL0YK9jfDAKE0bOYWZ6s9F01QcdWyOb/bvkYbabvsOAH/l2N/23Pn1sQCAzc8scNSxTy9AV7SrWX/yewDAsGuG2eNy/C1WJ9h+oWR24eUSpxOgBGrisQqLZrjrVgGEOpaTJJehjLf4PHEm+6J3zHs5X90t0yB9iKNduZ1q+yL76k6OYznJ+STXh9pB9dUyimKfTxabxdHvSE1ZxWn9kOuE8/IFgFqOOkX9L+qjnC8y1kKb/cWVxdch5/WwaP7Y+y3XFTl9OR2b076raH3NcfRb0UxPX2w9d65TFKt2Xsg6Ol3REQC5XOS8jQi0P0MmzWi//kSud+6OhBRY8wEAxgL7vyar/cGBQXrXO6YyjPbn3dQNti+ri8ZU5BXmupSraebMmYNdu3bhkUcewfr16xEdHY2FCxfi22+/RWJiouYp0HPnzsXOnTtx+PBhTJkyRR0eGBiIzz//HP3798fUqVPx7rvvwmw2Y9KkSbDZbPjyyy8RGBioltfpdEhISMDtt9+O+Ph4fPHFF4iLi4PJZMIrr7yCffv24aeffipTHDwSRERE5KO8cToMsL/DKykpCb1790aPHj0QFxeHTZs2YdeuXRg2bJim7MiRIxEeHo5x48a5tNOhQwckJycjNTUVcXFx6NKlC6KiorB//363T3++8cYbsXPnTrRu3Ro33ngjYmNj0bp1a5w/fx579uxBjx49yhQHjwQRERH5KJ1i/3hSv7zCw8Mxf/58zJ8//4rlRo8ejdGjR5c4Pi4uDmvWrCn1dNu1a4cVK1aUuvyV8EgQERER+SUeCSIiIvJRFfXaDH/FJIiIiMhH6RQFOg8SGU/q1gRMgoiIiHwUjwR5htcEERERkV/ikSAiIiIfpYNnRzP8/UgIkyAiIiIfpXh4TRBPhxERERH5IR4JIiIi8lG8MNozTIKIiIh8FG+R9wxPhxEREZFf4pEgIiIiH8XTYZ5hEkREROSjeIu8Z5gElUFuYRYyTEWzTK/Yfw7QBWrKZZozAACBOgMAwDnPDnAMM1uNAACdonO0Fez4bi9ttBaodWoH1QcA5FlyNNPRO+rmW3IBAKEBtVz6nFOYCQAID4xyG1NOYZb6c3hgpGZcrmNcrRKGuxvnLflO8yY0ILzSphPmpm138x0A0o0XAAB1ghuow2Q/RbH2hGOIXAZZ5ktqHbmeFf+Lrfh0hRAoTq5fJsf6Jqcv55HzelF8XcmzZDv6GFFiPFLL8DYAgI7tWwIAAnT2PmeaLwMAzuedV8s2qmVfn+sFN7KPyz+laSsiMBoAkF14WR1mtVkAAIEB9u2n0GpyxCe3R3vsilK0Sw/RhznisMdsE1YATvMTrn8BF1jzNN8DHGUFtPPWJmwudWX7cpysI6cv43JPaPpssRW6lii2fOV+xqALcumjjEPGKPvgGrHzEHu/Cx3TNjj2VbLVWlfYrtT2HeuonH5Rn4v6lq8uD+08lD2Rbcj56dyebEc2q9Zx/Co3O9YLoGheyjJyv6VX9I74gl2mU1Q3FAAQaYgBAJzJS9H0+Vz+32rZWoH2+XI2/zQAICaoDkSgfx9d8SVMgoiIiHwUL4z2DJMgIiIiH8VrgjzDJIiIiMhH8UiQZ/z9migiIiLyUzwSRERE5KMUuLvgvWz1/RmTICIiIh/F02Ge4ekwIiIi8ksVciRoy5Yt+PLLL5GRkYHPP/8cAJCUlISdO3figQceQMOGDStiMh6xWCxYuXIlvvvuOwQEBCA2NhaTJk1CixYtvN01IiKictHBwyNBfn5CzKMkSAiBhx56CJ988gkAoHbt2uq4m2++GYqi4IYbbsBbb72FYcOGedRRT+zZswdjxozBtddei3nz5qFZs2Ze6wsREVFF4S3ynvHodNjcuXOxbNkyKIqC+vXrQ6/Xa8b3798f06ZNw/33348ff/zRo46W1zfffIMbbrgB999/P7766ismQERERATAwyRoyZIluO2223Du3DmcO3cOUVFRLmVuu+022Gw2vPrqq55Mqly2bNmCESNGYOLEiXj55ZerfPpERESVSXFcGF3ej78fCfLodNiFCxewY8cONflxNzOtVvt7Wfbs2ePJpMosNTUV9957Lxo2bIg5c+ZU6bSJiIiqAm+R94xHR4KaN2/u9uiPs7Vr1wIAQkJCPJlUmT333HO4fPkypk2bhuDg4CqdNhEREVV/HiVBvXr1wnfffVfi+N9++w3//ve/oSgKBgwY4MmkyuTMmTNISEhAcHAw4uLi8PDDD6Nfv35o0qQJBg4ciE2bNlVZX4iIiCqLJ6fCPH3GUE3g0emwl19+GTfeeCOOHj2K++67DwBgNptx7NgxrFy5EvPmzUNBQQFq1aqF1157rUI6XBpffvklhBAIDAzE9u3b8frrr6NOnTr4/vvvMXLkSNx666349NNPMWrUKLf1TSYTTCaT+j07O7uquk5ERFRqfFiiZzw6EhQbG4u1a9di8eLFiIuLw9GjRxESEoIuXbpg1qxZKCgoQMOGDbF+/Xq0adOmovp8VVu2bAEATJgwAS+88ALq1KkDABg8eDDmzJkDm82GSZMm4eLFi27rz5o1C5GRkeqnSZMmVdZ3IiKi0lKUotvky/fxdgTe5fHDErt27YrDhw9j7dq1SEpKwqlTp2CxWNCwYUP07dsX999/f5VfD3TmzBkAQOPGjV3GjR49Gk8//TSys7OxatUqPPbYYy5lpk+fjqlTp6rfs7Oz0aRJEwTqgiCEUIdbYQEABCj22ag4LjHLLbQfOYoJsidfVmFV68gyOkWbf+rV7/bxZmvRkah8Sw4AQAgbACCnMEvTRlhALQCA0Zqv1gnWhwIAwgOjNHXCAyM10y3+3VmtEsaVNLwqXDbZE9fooLqa4aEB4d7oDgDgZO4fAIDmteIAALmOeR2oMwAA8ixFRxLluqAU+/sjrFj/ndcP+bOMMbvwstt+CLdD7YL09uviCm2FAIACax4AIEQfppbRK9rdgSwrBejs4zNMqeqw2kH1ARTNgxtbNrf30WyfB3Lb6F73OrXOwUv7AQBpxnOOuGpp4ooIjHbpj15v/9lqs29zumJ9lfPV+SEdcjkojvlnc2w/esU+p+R6nOfYvuzt6jTTkTd76BTt4z+KLy87RdNuviVXE5+79UCuI8XbL/7duW/y33C9djuU8QKu64Lsr+yT2mPn34BCcUShrS33O3I+6Z36ps53xzA5j2UfBWxySs5TBVC0PkkWR125j7U57WuFkMtDLkurpn2LY3kF6gJRnE3tg5y6XKaOfa3Tei7nYaQhRlMnNCBME69wmkf1ghsBKNpezDYTzDazSz+oeqqQJ0YHBAQgPj4e8fHxFdGcx+Tpq4iICJdxISEhuOWWW/D111/j8OHDbusHBQUhKCioUvtIRETkKZ4O84zH7w679957S1Xu22+/xYgRI3DfffdhyZIl6q3zlaFuXftRgpKu5YmNjQUAzVEdIiIiX6NUwMefeZwEHTt2DIWFhdiyZQtWrlyJrVu3wmKxaMokJibinnvuQb169TBz5kz8/fffuOmmm5CZmenp5N3q0aMHAODQoUNux8tb5lu3bl0p0yciIqLqz+MkKCsrC7GxsbjlllswatQo3HzzzWjZsqXmNRnvvPMOAGDatGlo164dZs6cib59+5b6KFJZ3X///QCAjRs3uiRkAJCSkgKdTod77rmnUqZPRERUFXiLvGc8SoIOHz6M9PR0XLx4EdHR0ejSpQs6d+6MrKws/OMf/8D+/fYLII8dOwYAmrfJP/XUU+rRo4rWu3dv3HvvvTh37hw+++wzzbjU1FRs2LABkyZNQvPmzSt82kRERFWFSZBnPEqCpk+fjvbt2+Onn35Ceno6du/ejT179uD8+fMYN24cZs2aBQAoKCgAAM0LVuvXr48GDRogISHBky6UaNmyZejQoQOmTJmCn3/+GQBw6dIljBs3Dl27dsW8efMqZbpERETkGzy6O2zbtm04evSo+hweKTQ0FPPnz0eXLl0ghIAQAgEBrpMKDw+vtHeKRUZG4ueff8YLL7yA4cOHIygoCFFRURg+fDieeeYZGAyGSpkuERFRVZHP+/Gkvj/zKAkKCQlxSYCk3NxcWCwW2Gw2tWxx2dnZuHzZ/TNPKkJUVBTee+89vPfee5U2DSIiIm/RwbNTOh5fGOzjPIq/WbNmmD9/vsvwEydOID4+Hp07d0Zhof0BUsVftJqeno7U1FRERnrvwXtERETkvzw6EjR16lQMGzYMH374Idq3bw8A+Pvvv7Fv3z7cfvvt2Lx5s3pdEGC/k0wmPcuXLwcAXHfdda4NExER0dV5eDrM39+b4VESdN9992HmzJmYMWOGegcYAMTHxyMxMRFffPEFHnroIQDA+PHjER8fj1tuuQUBAQF4+eWXoSgKJkyY4FkEREREfopPjPaMx6/NeP755zFixAh8//33MJvNuP7663H99dcDAMaMGYN+/frh1KlTuOGGG5CXl4ennnoKS5cuhRAC8fHxGDp0qMdBEBER+SMmQZ6pkHeHtWrVCo8//rjbcU2aNFHfwh4WFobFixdj6tSpSElJwW233VYRkyciIqIqZjab8c4772DZsmWwWCyIjY3Fv//9b/Tt27dM7Vy4cAEzZszAxo0bIYRAz5498fbbb6Np06alqr9lyxYkJiYiIyMDLVq0wB133IGbb765VHUrJAkqjYceeggfffQRAODaa6/FtddeW1WTJiIiqpG8dYu8yWTC4MGDkZqaio0bN6Jp06ZYvXo1Bg4ciMTExFK/UD0lJQU33XQTbrjhBhw6dAgGgwHPPPMMevTogZ9//hlt2rQpsW5aWhoeeughnDx5EosWLUKfPn3KHEel3x1ntVqRlJSkXghNREREFUMHxeNPeUybNg1JSUlYtmyZesQmPj4ew4YNw/jx45GSknLVNqxWK+Lj42E2m/Hxxx8jJCQEer0ec+bMQXBwMIYPH67eYV7c8ePH0bNnT9hsNmzfvr1cCRDgYRJktVoxc+ZMtGvXDrVq1YJer3f5GAwGDBw4sFLfGk9ERERV4+TJk3jvvffQrl079OzZUzNu7NixyMvLw/Tp06/azooVK7B7927Ex8cjLCxMHa7X6zFy5EgcOHAAS5cudal34cIFDBo0CHXq1MGXX36J0NDQcsfi0emwxx9/HIsXL4YQ4qpla8JTKYWwQacUvfojUGd/6rTRmu/4HggAqBUYDgCwCPvLWxWnXDPfkgsA0DvaCVDsi6DQVqgZ3jC06FxopjkdABBl0D6YMt+So/kerA91GmefjoB92YQHun8eU25hlvpzrWJlZPuhAfZ4sgvtD7aMCIx221ZZlae96KC6FTLt0pLzxyIcz7syuD4ctHmtOM13ua5HBsYAAHIKM9VxQtgfHmq2meQQAEB4YBQAIMt8CQAQoHPdNC+bLgIADPogt30124zqz5lm+7qnU7R/50QaYtzWBYDQgFoAgDxLNoCi9VtyF7sk58G5XO06mWfJc+mHTVgd/9rnhYw1LCBCU1fOKwDIt+Y5yoQ7RtrHWR3bmOyrVRT9sSW3JTlMxp5XbLtR23SSL+zbj5wnV1Lg6JtcliWNd45PXa8c273sf0GxOJ23ccUxD+V8kWXld73TOhOiD9PUl2VlPEV9diX3W4GKQTNdm9PyKK7QZtbEIfdFRf0vmjey/QAEasbJ9UD+PnH+jSHXn6K+FFuHHPtROT8B7XbnXFbuE+U+t3ZQfZd40o0XHPEEOvpm/zcmsJ5L2XP5pwAAYU7riqiyC028czps5cqVsFgsbo++9OrVCwCwdu1aZGRkoHbt2iW2k5iYCABu2+nduzcAYMmSJXjkkUfU4UIIDB06FKdOncJ3332H4ODgMvffmUdHglasWAEAePnll3Hq1CkUFhbCZrO5fHbt2oXAwMCrtEZERERl4Y0XqK5btw4A0LJlS5dxMTExaNy4McxmM7Zt21ZiG/n5+di8eXOJ7XTs2BEAsHfvXmRlFf2xvnz5cvz666+Ij49Xn0/oCY+SoKioKNSvXx+vvPIKYmNjNS9Idda9e3cMGjTIk0kRERFRJcnOztZ8TCZTiWX37t0LAIiNjXU7Xr4hYt++fSW2ceTIERiNxhLbkW0IIbB//351+MyZMwEAAwcOxIsvvojbb78dTZs2RY8ePbBo0aJSnZly5lES9PTTTyM3Nxdms/mqZZ2fHE1ERESeUyrgP8D+OJvIyEj1U9LvbKPRiNxc++ni4q/DkuSbIdLT00vs98WLF9Wf3bXj/Eot2c6+fftw4sQJKIqC5ORkPPDAA9iwYQN++OEHmEwmTJ48GY8++mjJM8sNj5KgJ554AiNHjsT7779/1bIDBgzwZFJERERUjLwmyJMPAJw+fRpZWVnqp6QLmzMyMtSfS7ogWaezpxbySE952pFtOLezZcsWAECnTp2wdOlStG7dGoD9sTtr1qyBTqfDokWLsH79+hKnW5xHl28tX74cN9xwAxYtWgSbzeb2jfIWiwW//vor0tLSPJkUERERVZKIiAhERERctZzBUHTDREmnnuTZoZiYkm/EuFo7zmeYZDtnzpwBADRu3NilfOvWrTFgwABs3LgRy5Ytw5AhQ64UhsqjJGjevHk4cOAAAGDHjh0llhNC1Ii7w4iIiKqTqn5tRkxMDAwGA8xmM/Ly3N9lmJmZCQBuD4xIDRo0UH/Oy8vTnP5ybsO5nexs+52rJSVrd9xxBzZu3IjDhw9fNQ7JoyTopZdewrBhw3D99dejefPmCAwMdEl2jEYj9uzZgxMnTngyKSIiIipGPvLQk/plodfr0a5dO+zbtw/nzp1zWyY1NRUA0Llz5xLb6dChAxRFgRAC586dc0mCZBsGgwFt27YFANSta39EikyGipMXWJfl4miP3yJ/66234n//+98VyxmNRtSv7/osBiIiIio/HTw8ElSOJ0YPGjQI+/btw6FDh1zGpaenIysrC2FhYejXr1+JbURHR6Nnz57YsWMHDh06pCY6kjxw0rdvX/VBij169AAAt9MFoD4zSF4rVBoevzbjjTfegMViKXH8vn37oNPpsGrVKk8nRURERF42ceJE6HQ6bN261WVccnIyAGDo0KGa637cmTRpEgBcsZ1Ro0apw2699VbExMTg77//dnvKS76q47777itlJBWQBHXv3h0BASUfUAoPD8fNN9+Mrl27ejopIiIicqZ4dodYeV4dFhcXh0mTJuHgwYMuzwJKSEhASEgIZsyYoQ5LSkpCr1698O6772rKjh07Fh07dsSqVas0d5KZzWZ88cUX6NChA8aMGaMODwsLU9t96623XPqVkJCAjh07ahKnq/H44d6XLl3Ctm3bkJWVBZtN+1h1m82G9PR07Nu3D2PHjr3qaTMiIiIqPedn/ZS3fnnMmTMHu3btwiOPPIL169cjOjoaCxcuxLfffovExETNU6Dnzp2LnTt34vDhw5gyZYo6PDAwEJ9//jn69++PqVOn4t1334XZbMakSZNgs9nw5ZdfurxtYsqUKfjtt9+QkJCAbt264YknnoDVasXLL7+M06dPY9u2bVc8MFOcR0nQrl27MGjQIM0jrd0RQmDPnj2eTIqIiIiqibCwMCQlJeGll15Cjx49oNPp0KFDB+zatQudOnXSlB05ciS2bt2KBx54wKWdDh06IDk5Gc899xzi4uIQGBiI2267Dfv370e9eq7vagOATz75BJ07d8Z//vMfvP7666hTpw5uuukm7N+/v8zXH3uUBL366qvIzc1Fv379EBsbi02bNuHWW2/VlPn+++8xdOhQjB071pNJERERUTFVfYu8s/DwcMyfPx/z58+/YrnRo0dj9OjRJY6Pi4vDmjVrSj1dnU6Hp59+Gk8//XSp65TEoyRo586d+OGHH9C/f38AwOuvv45+/frhxhtvVMssW7YMW7ZsUd8IS0RERBXDG2+Rr0k8ujC6Vq1aagIEABMmTMBHH32kKTN27Fh8/fXXWLhwoSeTIiIiIqpQHiVBkZGRmhekNWzYEEII9Q2zgP2wVUBAAObMmePJpIiIiKgYXQX85888Oh02ePBg9OrVC3379lWv0p4+fTruuOMOLFy4EE2bNsXcuXNx6dIllzvHfJFFFKLQZlK/B+mDAACBOvuzEORBRauwOobbx1tsRe9ACdTZr3RXFPuKJ2CfLzpF7xhubyXLfEmtI6/ezzTbXzind5QVKPmpmKEBtQAA+ZYcAECB1f54c5ujb2EBEZrpuVO8/YjAaJcy2YWXSxx3NeWpUxIZJwCEBoQDALIc80tGEWWoXeZ2awVGXrVMhsn+ZNPaQfYL8iw2+3OzcgrtNwyEB0a51JF90ynaHVCkwf6OnHxLrjpMLofooLqacTmFmZrxBsf65kyuV2GOeSLXIbkeOjNb7et2vmNdaRzaHEDRMtYrAZq2AOCi8TwAoG5wQ3ufHO/7uZBvnyd1gu2Pu08ruKDWCdaHAAAahNif7ppacNbRrvZR+M7zXm5Tks2x3QQ4tj25jJ3XWfmznP9yHZFrfJ4l2+107XVtmjqhTjG7lBVy36Y46uRqxtsc4+U26NxfuT0G692/iFJxWj9kO3J6cozsW57TNiBjk/sO+QTdonUy0qVPktyfWYXF7fAQfZjLdOS6Ief5ZZP9DeEGfbCjraLlJ/dfxWO02izFhhftm9Tl6ohDbjdy/ZZ9dZ5fcrnLPhZN376dFNoKARSt3wBgtBZo+phhsv+RXytQ7lMuO+ZB0fJqFNpU03668QKqEk+HecajJOi5557DunXrkJCQgC+++AKPPvoorr32Wjz66KO48847NTO3LA8vIiIiIqpsHiVBBQUFePjhh1GrVi107NgRer09e3766acRFRWlvl1+0KBBePHFFyukw0RERGTHI0Ge8SgJuvXWW3Ho0CGMHj3a5f7/iRMnYuLEiR51joiIiEqmc7xC1ZP6/syjJEheFH3XXXdVSGeIiIio9HgkyDMeXRY+f/58xMTE4O67775q2bi4OE8mRURERFShPEqChg8fjq+++gqPPfYYjh075raM0WjE0qVL8ddff3kyKSIiIipGPjHak48/8+h0WGRkJHJz7beDLl26tEI6RERERKXjrReo1hQeHQn65z//CSFEqT5ERERE1YlHSdCTTz6JmJgYHD9+HIWFhbDZbC4fq9WKrVu3+v3FV0RERBVNp+g8/vgzj06HxcbG4rHHHsM111xTYhlFUXDjjTfyYYlEREQVjHeHecbjFPDVV18tVblVq1Z5OikiIiKiCuPRkSAiIiLyJs8ujIafXxjNJIiIiMhHeXqbu7/fIu/fV0QRERGR3+KRICIiIh/F5wR5hkkQERGRj9Ipnp3S0vl3DsQkqCyC9aFwfuxjhvEiACA0IAwAoFP0AIAAXSAAwCosAACL41/ZBgAIYQMAFNrMAIDooLoAgJzCTABApCFGrZNnyQYAhAVEaMrolQDH9yx7m7CpdRTHmU45LEBd1EqxNvRXjVtO352IwGgAQL4lBwAQGhBeYl3Z/3yL/SnjVmEFAIQHRgIAsgsva9q8EhmzrCvg+kDOSEPtq7YjlWXaxdUOqg8AyHX0KdCx/IvPC+fpyP7KeVJ8vLNAnQEAkOeYx3K90jmWsfyu/YvO/rNcR2TdKMc8kcvLJorWmSB9iGa6ch7LeZJlvuTSt7rBDbXfQ+3rd4BjvaobUtfRR6taJjLIvswumdIAAAZHfFJqwVkAQP2Qxuowiyi0xyPs7cp5YrU5Yle08QJF80Ou6/K78/YIAJdNF9Wf5XYo54vN0e+S1m+gaFnK563IbVuuke7+0pbbpYxD9lHuO+R0dU7bp2wlzLHOy/Wt+LbgTC73sIBajjjs216BNU8Tp3M/FUfP5UNuZZ8sjnmdbStaR2U/A3VBbuvIdVPzwFzHspLzzWKzL1udus/Stg0AAY7lKtcDWVYu9+LbgjNLsXVEtiv3vTGOZW7vp31+mGwmAECkIcr+3WoEANRyLH+TzegyndSCM47p6GBz2hdXNkXRQfHgWT+e1K0J/Dt6IiIi8ls8EkREROSjeE2QZ5gEERER+SjeIu8Zng4jIiIiv8QjQURERD6K7w7zDJMgIiIiH6WDAp0H1/V4Urcm4OkwIiIi8kt+lQR99913UBQFn3zyibe7QkRE5DF5OsyTjz/zm9Nh6enp+Oc//+ntbhAREVUYPizRM34T/eTJk5Gbm+vtbhAREVE14RdJUGJiIlJTU3Hvvfd6uytEREQVRl4Y7cnHn9X4JOjs2bN4/vnnkZCQAJ2uxodLRER+hNcEeabGXxM0YcIEzJgxAy1atPB2V4iIiCqYZ6/NgJ8fCarRSdAHH3yAkJAQTJgwoUz1TCYTTCaT+j07u+S3qBMREZFvqrFJ0IkTJ/D2229j+/btZa47a9YsvPrqq5XQKyIiooqjwMMnRvNIUM1js9kwbtw4zJ8/H/Xq1Stz/enTp2Pq1Knq9+zsbDRp0gRWYUOQ0+2EwQEhAIA6wQ0AAFnmS5p2dI5LrgKUotlstOYDAGoH1deUvWS6CAAI1Blc+mOy2o9KhTmasdgKHWXtK69NWAEAekWv1im67dH+r84xrtBmtvdJFwgAEMKm1sktzLK3B5uj3/YyBdY8t30GgOzCywCAiMBoAEBOYSYAIDwwytFXi0ud0IBaLsNKkm/JsbcjLJrphAdGasqFBUSU2KeS5DnadldWtmF2zHu5jN3JMmcAACINtTV9zrPYjyA6z4NIQ4ymTnFF8zFLHSaXt1y+cr2SyynKUMclHllHOMoojjr5llzHcLtaTvNRrr96XYCjDfu6IueF7LtcV+190mlirx0SCgB49YcvAABv3jERANC5dhe1zmWTfToxQe63zfohjTX9AQCDLsgeh6Jd5+U80Dt2ZTan9Vm+GFKui3K5KELRtBXh6DtQtMzk9iKnExoQ7hjvWB8d8xco2pYks2O+yT7L9V22DRRtd46uOG2PQvsviuKR24BcN3SOeW9zDHde/lah3e7kOHVfAXt8zr/+rOp+xN5uoOyTura4CnTEKKfnvD9xjsv5NmwZk5yeXDfldzlezgMAsCnadmXHdUK2CZfpZJrT7WWKLUs5vQDHeu68PsuWDI79sOyTjKNQ2Jd7jrloWTaw/xpA/ZBYAEBKznHkFeahqvCJ0Z6pkUnQW2+9hWuvvRZ33XVXueoHBQUhKCiogntFRERE1UmNS4IOHDiATz75BLt27fJ2V4iIiCoVH5bomRoX/YIFC3Ds2DFERES43AaYkJAAABg/fjwURcGDDz7o3c4SERF5QKmA//xZjTsSVK9ePbRp08btuPPnzyM7OxsNGjRAZGQkGjZsWMW9IyIiouqixiVBs2bNwqxZs9yOe/DBB5GQkIBZs2bxKBAREfk8RYFnd4f594GgmpcEERER+QtPT2n5++mwGndNEBEREVFpMAkiIiLyUd58d5jZbMbs2bPRpk0btGrVCv369cPWrVvL3M6FCxfw8MMPo2XLlmjRogVGjBiBU6dOlbr+mTNnEB0dXa7LXPwqCfrkk08ghOD1QEREVCN46y3yJpMJt99+Oz799FNs3LgRf/75Jx5//HEMHDgQq1evLnU7KSkp6NGjBzIzM3Ho0CGcOHECjRo1Qo8ePXDs2LGr1hdCYMKECcjMzCxXHH6VBBEREdUk3joSNG3aNCQlJWHZsmVo2rQpACA+Ph7Dhg3D+PHjkZKSctU2rFYr4uPjYTab8fHHHyMkJAR6vR5z5sxBcHAwhg8fjsLCwiu28f777yM5OblcMQBMgoiIiKgMTp48iffeew/t2rVDz549NePGjh2LvLw8TJ8+/artrFixArt370Z8fDzCwsLU4Xq9HiNHjsSBAwewdOnSEuv/8ccfeOutt/DCCy+UOxYmQURERD7K85NhZU8DVq5cCYvFgj59+riM69WrFwBg7dq1yMhw/45EKTExEQDcttO7d28AwJIlS9zWtVqtGDduHN555x00aFDyux2vhkkQERGRj/LG6bB169YBAFq2bOkyLiYmBo0bN4bZbMa2bdtKbCM/Px+bN28usZ2OHTsCAPbu3YusrCyX8W+++SauueYaDB06tMz9d8YkiIiIyM9lZ2drPiaTqcSye/fuBQDExsa6HR8VFQUA2LdvX4ltHDlyBEajscR2ZBtCCOzfv18zbv/+/Vi2bBkWLlxYYvulxSSIiIjIR1XUu8OaNGmCyMhI9VPSmxeMRiNyc3MBFCUqxUVGRgIA0tPTS+z3xYsX1Z/dtSPbKN6O2WzGuHHjsHjxYk2Z8uITo4mIiHyUTlGg8+BZP7Lu6dOnERERoQ4PCgpyW975Op/Q0FD3bersx1fkkZ7ytCPbKN7Oyy+/jFtuuQU333xziW2XBZOgMrEhRF90BXuhTXu4UEAAAHSOA2wW4Xprn17RAwCyCy8DAKw2CwAgJqguACDNeA4AYLTmq3WC9MEAgIvG8wAAg84AADDbzACAYMd4m7CpdXSKvQ/CMUztm2O42Wrve4Au0Ck6e9niF8oF60MAADmF9vOy4YFF2Xegoy/F54GMT+eIFwDyLNmaslZhBQBEBEY7pqtopuM8Ldlepll7oV2AYl+Fnc9rFzrmS5ajrCjW17CAcM2/zu3rHe3JPiFQO96ZXJY6R50s8yV7nxzzVMZjc8TpTKi90pKxO9cJ0AVo6tQK1P71k2+x/1Um43aetlyWsq6ijtdOzx6HTjNW75iubCOnMFNTFwAiDbUBAOnGCwCAM9n29vb/egQAsLHDLwCA9tEd1DoGvXbnKuetXFdlm87LVPZfruNyOSmO4VZh0fTVWdFyCdDEGR4YBQAosOY5ldYuswDHOiPXuyhH3/ItOWoNuR5bbHJ7F5o+58pliqLtU7ZbtH06pu7oW6HVviydt6+imBVHHUddIVzal8NkzEXxBDr6atH0FXDaZxT1ptj07G3onOax7H/RembTxuFYJ/VK0X5GTlP2Qe5f5C9j2XfnFc1WLFZdseUsl7+cRwBgcMRqthkdZayOMormO1C0rWUY7UcnGoc11fRb7ruCdMHF6rpqEd4a2SK7xPHVVUREhCYJKonBULROqsuqGLPZvtxjYmLK3Y5sw7mdX3/9FevXr8fOnTuv2s/S4ukwIiIiH1VRp8NKKyYmRk1g8vLy3JaRDy6sU6dOie0439Hlrh3nhx/WqVMHeXl5eOihh/DJJ58gODi4TH2+EiZBREREPqqq7w7T6/Vo164dAODcuXNuy6SmpgIAOnfuXGI7HTp0UKftrh3ZhsFgQNu2bfHVV1/hyJEj6N69u0v/x48fDwBISEiAoiho3rx5qePh6TAiIiIqtUGDBmHfvn04dOiQy7j09HRkZWUhLCwM/fr1K7GN6Oho9OzZEzt27MChQ4fQtm1bzfgTJ04AAPr27YuwsDDUqlULbdq0cdtWVlYWLly4gIiICDRs2BCNGzcudSw8EkREROSzPH1QYtnTgIkTJ0Kn07l9Wap8hcXQoUM11/24M2nSJAC4YjujRo0CANx77704evSo24+8k02W+emnn0odC5MgIiIiH+WNhyXGxcVh0qRJOHjwoMuzgBISEhASEoIZM2aow5KSktCrVy+8++67mrJjx45Fx44dsWrVKs0dYGazGV988QU6dOiAMWPGlLl/ZcEkiIiIyEd56y3yc+bMQffu3fHII4/g0qVLEELg3Xffxbfffovly5drngI9d+5c7Ny50+UdX4GBgfj8889hsVgwdepUWCwW5OfnY8KECbDZbPjyyy8RGBhYfNIVikkQERERlUlYWBiSkpLQu3dv9OjRA3Fxcdi0aRN27dqFYcOGacqOHDkS4eHhGDdunEs7HTp0QHJyMlJTUxEXF4cuXbogKioK+/fvL/EaoIrEC6OJiIh8VHlPaTnXL6/w8HDMnz8f8+fPv2K50aNHY/To0SWOj4uLw5o1a8rdjwcffBAPPvhgueoyCSIiIvJR5XnWT/H6/oynw4iIiMgv8UgQERGRj/Lm6bCagEkQERGRj7KfDCv/SR2eDiMiIiLyQzwSRERE5KN0igKdB6e0PKlbEzAJIiIi8lG8O8wzPB1GREREfolHgsrAZDUh35Kjfjda7e86iQmqBwBO+bT9J52iBwDYhE0dY7EVOsYJAIBA0ThndYMbugzLsKXaW1fsuWuA41+rsDr+tahldULmt4rj/0qxvgjNcPvP9jp6R78l2b4cn+c0D2R9OSxACXS0Llz6JFc32Qe9Yv9+yXRRM71gfbD6c5b5kiNm+3QCdfYX8sn5aHPMv6J4i8pIOke/ZZ08S7amH86x2Ryx5ltyAQAma0GxeKwu05H/ysPKsg1ZJ8CpPzmFWY6y9nmcbrzgaEM+Gl5x1Cl6VLzJsZ7JJRXmstUKl3gCdAGOMTbHOLm87WoFRgIAch39sZe1j7XYzJp+W4V9vsnlZXNaZ9OM5xzt2utGBTuWXZ69Tvva9kfnBzkt0zzHvJXk+hYWGK0ZLpcXnHou4yq0mQAUzUeLzeKYTpBaQy4rWab4epxTmOkYXrSOGnTBmjpyfukUue7b152wgAi1TtE8FJq6cj2Qyy80IAzFyW250DHPdY55bHDEIZebvS9yn6Gdjl7dlzi3K5el3N/I+eaYjlzf4dy+o45jfqjL27FeCce/VqflL8vIqRdfR3TF9iXO1G3ZsX7J6chtQbt9Ko6p2IeZHcs/UBfkmK6c50XLsuhnRROz3KblvNc5HQvQF1ufMh37n2B9iGa6+dZ8l3h+u7gNANAyojWyTTku4ysL7w7zDJMgIiIiH8XTYZ5hEkREROSjeCTIM7wmiIiIiPwSjwQRERH5KJ3jP0/q+zMmQURERD6Kp8M8498pIBEREfktHgkiIiLyUbw7zDNMgoiIiHyVh6fDwNNhRERERP6HR4KIiIh8FE+HeYZJEBERkY9iEuQZng4jIiIiv8QjQURERL5KUTy7uNnPL4xmEkREROSjeDrMM0yCiIiIfBSfGO0ZXhNEREREfolHgspAARCgC1S/622FAIDUgjMAgNCAcACATVgAp7K5hdlqnVqBEY5hOY46oQCAM3kpjvH2NtKNF9Q6gY52LDZ7u/KFd/nWPABAlCHGPlwJUusICEdfbPa6wt5XIbTDrcKq1tE5/iKQw3SKNkfWK3oAQKHNpA6TMeoc42T7V/rbQrYj/wIJ0GlXQ9k353Zl32yOvhW1odMMt0/bXlbOA9kXOR8LrPkAgBB9qFqn0GZ29MWg6Zu+WN90omieFI8x32JfHqEBYQAAo7UAAGDQFS0Xq2Pd0Cv2vhj09nHCEbNNnfdFdWS/Zd3cwixNH+U8l/PE+WerOr8CHO3bHH3Ntdd1zCPnn2XMMj7Zvslm1EzXeTp5hfb2hra+FQDwftYqAECG0d5Xs9M6I5fPqdw/AQDRQbUBABeN5x2x2+dxgFI0761O64QzOU8CHcvNJoTbckDRdmNRl4Fct4rmm5z/cl7If2VduUyFcJ1vcr2SyzvQabk7T9e5vpyXsv/F27A49jFA0bqptudYHii2vtuHKJpxesc8NTvas8FWrBxghVUTq5y3iuO7nE/O25pcv2QchY725TKU7StKUd/kOujannaLco5H7vtkiYBi24Rs03kbkOOyzJkAgCDHtibnrZwHztOJCapjn55jfyn3x0aLfbkHOvbXrcLj1Donsg8DABqENnK0URcBQdplX5l4OswzTIKIiIh8lALPEhn/ToF4OoyIiIj8FI8EERER+SgFHl4Y7efHgpgEERER+SheE+QZng4jIiIiv8QjQURERD6KR4I8wySIiIjIR/FhiZ6p0afDhBD48MMP0blzZwQHByMmJgZ33303fvvtN293jYiIyGNKBfznz2p0EvTwww/jkUcewYEDB2CxWHD58mX897//RZ8+ffDVV195u3tERETkRTU2Cfr++++xdu1aJCQkIDs7G0ajEV9//TXq1q2LwsJCjB8/Hunp6d7uJhERUbnJ02GefPxZjU2CPvnkE2zcuBEPPPAAwsPDERAQgLvvvhsrVqwAAGRnZ+O///2vl3tJRERUfjwd5pkamwTddNNN6NKli8vwAQMGoGvXrgCAixcvVnGviIiIqLqosUnQ448/XuK4uDj7y++aNWtWVd0hIiKqcDwS5Bm/vEU+PT0dQUFBuP32292ON5lMMJmK3nqdnZ3tthwREZE38RZ5z9TYI0Elyc/PR3JyMh566CFERUW5LTNr1ixERkaqnyZNmlRtJ4mIiKjS+V0S9NFHHyE8PByvvfZaiWWmT5+OrKws9XP69Okq7CEREVHp8HSYZ/zqdFhGRgZef/11JCQkICYmpsRyQUFBCAoKchkeEhCGnMKiU2MGnb2MothzSZO1wD5cbx+eb8kDAOiVotmcW5hjn4Zetq842g7VlA3QB6p1Cqz5AIBAnQEAoHNMr1ZABADAJmyOunq1jnC0q3Os3yarRTNdBfb2zTazWkdxrA4C9vaEsA/XOXJlq7Da+6YLdKqjOPpg1cRjFRa4Epr+Ko52AxR7e4U2+ylIvd6g1rDYCh3/aqdd1IbQ9MMes71duVyELKvI6ck4RVEcso6jHYvNoilb6JhPeqUodjkdKTQgTNNGsD7EpW9Ql4v9X7lc9MXaktN3Jqctey1blYez9Sha/jbHwpPrRPHlYXWM18wDR4syVudxQNH6Z7IZ1WHqfNHZp/Pz2Z0AgIjrGgMAPt+VDAAY02akWkcuwwCdfd6aHcu90LGsQx3bgsWpz3JbK1oO9unJdSffat/WgnRF261ct4P0wY55ItcZOd7kaDtYrSNjE475I7dlOVyuDzbHNmLvS4Cj37UAAAWWfO303JxukPNWrptCjcfelly3tOuY3H6025osUzTceRu217EIWVbvUlaS7chtTsaVa7Hv8+T+xnmtUIqtjTqXbU6vaRMomnfBOrkd2suYrSa3bTgPKz4n5Ty2iEJHOcVlnNznmRzty+FyfZP7aQCoH9IQQNF6ZXTse+V6IOsUOu03M4z2R600rdUcAJBuvIAcYw6qiqeJjL8nQX51JOif//wnnn322RKvBSIiIqLSMZvNmD17Ntq0aYNWrVqhX79+2Lp1a5nbuXDhAh5++GG0bNkSLVq0wIgRI3Dq1KkSyyclJWHAgAEIDw9HWFgY+vTpgy+++KJcMfhNEvTGG2+gadOmeOaZZ7zdFSIioorh6YMSy3lhtMlkwu23345PP/0UGzduxJ9//onHH38cAwcOxOrVq0vdTkpKCnr06IHMzEwcOnQIJ06cQKNGjdCjRw8cO3bMpfxnn32GgQMHYtOmTTAajep1viNHjsTTTz9d5jj8Ign69NNPcezYMcybN8/bXSEiIqpASgV8ym7atGlISkrCsmXL0LRpUwBAfHw8hg0bhvHjxyMlJeWqbVitVsTHx8NsNuPjjz9GSEgI9Ho95syZg+DgYAwfPhyFhUWnUi9evIjHH38cL7zwAs6fP4/CwkLs3r0bPXr0AAC88847+OGHH8oUR41Pgr766it88803WLp0qcu5eavVyoueiYjIZ3njtRknT57Ee++9h3bt2qFnz56acWPHjkVeXh6mT59+1XZWrFiB3bt3Iz4+HmFhYepwvV6PkSNH4sCBA1i6dKk6/PPPP8frr7+O1157DQ0aNAAAdOvWDevXr1ev8/3ss8/KFEuNToK+/vprJCQkIDExEQEB2mvAL1y4gAcffBB//fWXl3pHRETke1auXAmLxYI+ffq4jOvVqxcAYO3atcjIyLhiO4mJiQDgtp3evXsDAJYsWaIOMxgMmDx5skvZunXrYty4cQDK/iaIGnt3WGJiIh588EHUqlULjRs31owzm83IyclBkyZNsHz5ci/1kIiIyDPeuDts3bp1AICWLVu6jIuJiUHjxo1x9uxZbNu2DXfddZfbNvLz87F58+YS2+nYsSMAYO/evcjKykJkZKTbBEgq75sgauSRoHXr1mHs2LGwWCzIzMxERkaG5pOTY799ceTIkX7/tEwiIvJdFfWcoOzsbM3H+a0Jxe3duxcAEBsb63a8fBDxvn37SmzjyJEjMBqNJbYj2xBCYP/+/VebDUhPtz+q4O67775qWWc18kjQHXfcAZvNdvWCRERE5PJmhBkzZuCVV15xKWc0GpGbmwsAJb51ITIyEkBRYuKO82krd+3INq7WjvTjjz+iY8eOGDRo0FXLOquRSRAREZE/qKh3h50+fRoRERHqcHcPDAaguc4nNDTUbRmdzn6SSR7pKU87so2rtQMA+/fvxy+//ILNmzdr6pUGkyAiIiIfZb/J3ZNrguwiIiI0SVBJDIaiJ/rLJ5IXZzbbn6h9pTczXK0d2cbV2gGAp556CtOmTcNNN910xXLu1MhrgoiIiKjixcTEqAlMXl6e2zKZmZkAgDp16pTYjrzFvaR2ZBtXa2fBggUIDw/HzJkzr9TtEjEJIiIi8lFV/QJVvV6Pdu3aAQDOnTvntkxqaioAoHPnziW206FDB/VUnLt2ZBsGgwFt27Z128aWLVuwdu1arFixosynwSQmQURERD7KGw9LlBcfHzp0yGVceno6srKyEBYWhn79+pXYRnR0tPqgRXftnDhxAgDQt29fzYMUpd9//x0vvfQS1q5dW+K1SaXBJIiIiIhKbeLEidDpdG5flpqcnAwAGDp0qOa6H3cmTZoEAFdsZ9SoUS7jjh8/jkcffRSrVq1CdHS0y/jSvLJDYhJERETko6r6dBhgfzDhpEmTcPDgQZdnASUkJCAkJAQzZsxQhyUlJaFXr1549913NWXHjh2Ljh07YtWqVZo7wMxmM7744gt06NABY8aM0dQ5fvw4JkyYgM8++0xzXREAFBQU4J133sGnn35a6lh4d1gZnM8/g7pB9dTvQXr7LYQmq33hhQXUAgBYbPYXvhl0rlmwTrHP8gKr/UIwq7ACKLo6PrfQ/iDHkICiw3tBOvt0jI7pCJ2jDUs+ACA80H5Ff6Gt6Gr6QMe0bcLmmK59RT+T9zcAoH5IQ810AUA4tgWdIzfWKfZ/1RJqW3q1jpym3JACdIGO4fayeqeyNse0ZLvFNz6ro32bY55of5ZlZRv272ar/YFeQfpgp3bsdRRHe7KPweo8dd3o5Xww2uzzNFCnvT1UcfTZuW+yD7KuLGMRFkdZm8vUzI6+BDrmk5w/8l+zY/oBCCzqmyNmm6PdouF6zXed0980Fsd0bJB90C4fq6Mt7bK0r7dyXuZb7OuoXI8totBlHsh+pxXYz983CLNfwNj7Ovs1A6GO19XIddde36ZpP1gf4uiLdn46r896x3Yjl63sd77cjmz2eKxKgFMd7fyR67GlWJxWUfSCRrk+6XXaXaPBsT7IZeE8r+X8kMPkfqDAal+WesdyUpzqWIU9tiBdsCZWud3KOOUyscdj0/RNOOaj2Wbvc4BStM7IeSwFOOaLbM/imF9BjnlvryPnkGPbktuNo4yc187kODnf5HKR64rOEYdc3+39Fpo6Mh55WkYuH+d1Ri7LYMcyyzZnAijaT8p4skyX1To6nb2OXH8zzZc1092dtg8A0LN+d7XOyVz7a5Sa1moOADiRdRwAUDfEvt/PKcy299Vpqz6Td1bTx33pB1CQW4CqUlG3yJfVnDlzsGvXLjzyyCNYv349oqOjsXDhQnz77bdITEzUPAV67ty52LlzJw4fPowpU6aowwMDA/H555+jf//+mDp1Kt59912YzWZMmjQJNpsNX375JQIDi9adAwcO4LbbbkNubi66deum6Y/VakV2djZsNhv++OOPUsfBI0FEREQ+yhtHggAgLCwMSUlJ6N27N3r06IG4uDhs2rQJu3btwrBhwzRlR44cifDwcPX9Xs46dOiA5ORkpKamIi4uDl26dEFUVBT279+PNm3aqOXOnTuH/v37IzU1FXl5eS5vgsjMzITNZkPPnj1xzTXXlDoOHgkiIiKiMgsPD8f8+fMxf/78K5YbPXo0Ro8eXeL4uLg4rFmz5optNGrUCJcuXSpPN6+ISRAREZHPUuDuFH/Z6vsvJkFEREQ+iimQZ3hNEBEREfklHgkiIiLyUd66O6ymYBJERETks3hCzBM8HUZERER+iUeCiIiIfBSPA3mGSRAREZHPYhrkCZ4OIyIiIr/EI0FEREQ+ineHeYZHgoiIiMgv8UgQERGRj/LkJaiyvj/jkSAiIiLySzwSRERE5KN4JMgzihBCeLsT1V12djYiIyORlZWFiIgIb3eHiIiqsar4nSGn8VfqcYRHhJe7nZzsHLSs39pvf7/xdBgRERH5JZ4OIyIi8lG8Rd4zPBJEREREfolJEBEREfklng4jIiLyWZ7dHebv7w5jEkREROSz+AJVT/B0GBEREfklHgkiIiLyUTwO5BkmQURERD6Kt8h7hkkQERGRz+KxIE/wmiAiIiLySzwSRERE5KN4HMgzTIKIiIh8mr+nMuXH02FERETkl3gkiIiIyEfx7jDP8EgQERER+SUmQUREROSXeDqMiIjIRykevkDVs5ev+j4mQURERD6LN8l7gqfDiIiIyC/xSBAREZGP4nEgzzAJIiIi8lG8Rd4zTIKIiIh8Fo8FeYLXBBEREZFfqvFJkNlsxuzZs9GmTRu0atUK/fr1w9atW73dLSIiIo8pFfDxZzX6dJjJZMLgwYORmpqKjRs3omnTpli9ejUGDhyIxMRExMfHe7uLREREHuDpME/U6CNB06ZNQ1JSEpYtW4amTZsCAOLj4zFs2DCMHz8eKSkpXu4hEREReUuNTYJOnjyJ9957D+3atUPPnj0148aOHYu8vDxMnz7dS70jIiLynLw7zJOPP6uxSdDKlSthsVjQp08fl3G9evUCAKxduxYZGRlV3TUiIiKqBmpsErRu3ToAQMuWLV3GxcTEoHHjxjCbzdi2bVtVd42IiIiqgRp7YfTevXsBALGxsW7HR0VF4ezZs9i3bx/uuusuzTiTyQSTyaR+z8rKAgBkZ2dXUm+JiKimkL8rhBCVPq2c7FyPXoKak51bgb3xPTUyCTIajcjNtS/YqKgot2UiIyMBAOnp6S7jZs2ahVdffdVleJMmTSquk0REVKPl5OSov2sqmsFgQIMGDRDXvLXHbTVo0AAGg6ECeuV7amQS5HydT2hoqNsyOp39TKDRaHQZN336dEydOlX9brPZcOnSJdSuXdsnLiLLzs5GkyZNcPr0aURERHi7Ox5jPNUb46neGE/VE0IgJycHjRo1qrRpBAcHIyUlBWaz2eO2DAYDgoODK6BXvqdGJkHOGW1JhyPlihMTE+MyLigoCEFBQZphJR1Rqs4iIiKq7U6iPBhP9cZ4qjfGU7Uq6wiQs+DgYL9NXipKjbwwOiYmRk2E8vLy3JbJzMwEANSpU6equkVERETVSI1MgvR6Pdq1awcAOHfunNsyqampAIDOnTtXWb+IiIio+qiRSRAADBo0CABw6NAhl3Hp6enIyspCWFgY+vXrV9Vdq3RBQUGYMWOGyyk9X8V4qjfGU70xHqKSKaIq7uHzgj/++APXXnst2rdvjwMHDmjGffvtt7jrrrvwwAMPICEhwUs9JCIiIm+qsUeC4uLiMGnSJBw8eBD79u3TjEtISEBISAhmzJjhnc4RERGR19XYI0GA/aLofv36ISAgAOvXr0d0dDQWLlyIZ599FomJiRg2bJi3u0hEREReUiNvkZfCwsKQlJSEl156CT169IBOp0OHDh2wa9cudOrUydvdIyIiIi+q0UeCiIiIiEpSY68JIiIiIroSJkFE5ZSSkoLdu3fDarV6uysekweEeWCYiPwJk6BqyGazebsLFSovLw///ve/XR5V4KsKCgowe/ZsvPHGG7BYLNDr9d7ukkfy8/ORlZUFAD7xbryrsVgs3u5CheL+gKjy1OgLo33RsmXL8OuvvyI4OBidO3fGzTffjFatWnm7Wx75+uuvMWPGDOj1erRo0QLh4eHe7pJHVq5cicLCQnzwwQcICPDtTeiNN97A6tWrERoaiqysLEyZMgV333036tevDyGEzyVFb7/9NrZt24bo6Gh0794dgwYNQlxcHAD4ZDzcHxBVMkHVwo4dO0TXrl2FoiiaT4sWLcT3338vbDabt7tYbv/+97+Foiiia9euYvPmzd7ujkf27t0runbtKn7++WchhBBWq9XLPSqf7du3i3bt2onBgweLXbt2iWXLlolBgwYJRVHE888/73NxnT17VvTv31/cfffd4ocffhATJ04UdevWFVFRUWLGjBmioKDA210sE+4PiKoGk6BqIDU1VfTq1UsoiiI6duwoHn/8cdG9e3cRFRUlFEURgwYNEnv27PF2N8tM/iKdOnWqiI2NFTqdTjzyyCMiNTXVyz0rv9dee02MGTPG293w2MMPPyxefvllzbALFy6Izp07i06dOokLFy54qWflk5iYKO666y7NsI0bN4rOnTsLRVHEww8/LC5evOil3pUN9wdEVYfXBHmRcFyEumHDBuzatQuvvfYaDhw4gIULF2Lbtm1YtmwZ6tatiy1btuD333/X1PEF8tRDXl4ebrzxRvTo0QOrV6/GL7/84lNxSNnZ2fjwww/RpUsXAIDRaPRuh8ppz549WLx4Mfr27QugKI769etj8uTJSElJQa1atbzZxTJbuHAh6tWrB6AonoEDB2LRokVQFAWLFy/GW2+9hbNnz3qzm1fE/QFR1WMS5EVyp7Bt2zbccMMNeOGFFwAAVqsVQUFBuOeee/Dcc8/BZDJh69at3uxquSiKgoKCAly6dAkvvPAC7rzzTly6dAnLly/HX3/95e3uldmxY8eQkZGB66+/HgAQHBwMADh58iQuX77sMxfkHj9+HIGBgTCZTAAAg8Ggjqtfvz769euHsLAwn7gg12azIScnB+fOnXOJRwiB3r17Y+bMmQCAzz77DCtXrvRaX6+G+wOiqsckyEtsNpv6S6Zhw4aYMmWKuhPU6/XquBEjRiAuLg5///03TCZTtb2w090vTJvNhpCQEFy6dAmFhYW4//770adPH3z//ff44Ycf1F9a1fGvQHfxHD9+HCaTCWFhYQCApKQk3HTTTbjlllvQsWNHjBo1Cj/99FNVd7VUnNe3Nm3aoLCwEImJiTh79ix0uqLdgBBCfZq68/DqSqfTwWQyITs7G7t27VLjEfZT/QCAJ598EgMGDMCFCxewatUqbN++3cu9dk/2tybsD9zx5f0B1VzVfy9XA6SkpOC1117Dxx9/jK+//hoWiwU6nU79JSPc3LWi0+lgs9nQqFEjdO3aFWazGUFBQdViB1FSPMXpdDpkZmYiJycHjRs3RlxcHEaNGgWDwYCEhAT1kL63d+RXi0fO83PnzgEAzp8/j7lz52LevHm4++67cdtttyE4OBhffvklRo4ciXfffRdms9krsQBXX99atWqFESNGYMWKFRg9ejSWL1+Ow4cP4/Lly8jOzsaQIUO81nd3Lly4gF9//RUAXJ7JJIRQ7wS7ePGieoREURTodDpYrVaEhITgySefRO3atfH7779j48aNKCwsrPI4pJLicd4OfGl/cKXl48xX9gfkZ6r6IiR/M2vWLNG0aVPx9NNPi1tvvVUEBweLjh07io8//lhYLBYhhBCXL18Whw4dcqkr7wB59dVXxQMPPFAt7gi5UjyS7KfNZhN5eXninnvuEX/99ZcQQoi0tDRx3333CUVRNBfmHjhwoGoDcShLPM8884xQFEXMmjVLrFixQjP+1KlTonfv3kJRFHHttdeKtWvXVnUoQogrx+O8/ly8eFH0799fc+fRtddeKxo0aCCio6NF//79xdSpU0VSUpJ6Z5U37hgzm81i6NChomXLlsJsNgshhMt2UFBQIMaMGSMURRFPPPGESE9Pd9vW2LFjhaIoYsCAAeLIkSOV3nd3rhSP/DcrK8tn9gelWT6SL+wPyP8wCapEJ0+eFIMHD9bs0NatWyeio6OFoijiySefFGfPnr1qO4888oj417/+VYk9LZ3SxHP+/HkhhFATvBMnTog2bdpo2lmzZo2IjY0VrVq1EtOmTRMNGzYUffv2rfI7ksoSjxBCfPjhh0JRFFGnTh2xatUqIYQQJpNJTQ5+//13ceuttwqdTiceeughkZWVVe3iOXfunDouJydHJCcni3feeUcMGDBAPPTQQ2Ls2LGiW7duIjAwUCiKIgIDA8Xo0aNFTk6OEKLkX3CVZeHChSI0NFQoiiLefvttIYQ2GZP9+eCDD4SiKCIuLk59fIEk18Xt27eLgIAAERQUJJKTkzX1q8rV4imN6rI/EKLs8VTn/QH5JyZBlWj69OnqBm82m9Ud7tKlS0WbNm2Eoihi4sSJJdaXO+/JkyeL1atXCyHsO23ZzuXLlyux967KGo/FYhFHjhwRo0ePFmazWeTn56vjhg0bpjkK8dRTT4mMjIxqHc+GDRtEvXr1RJs2bdS/VIv/El21apVo3ry56NSpU5UnQWWNx7nvycnJYtu2bUIIe3J07NgxMWvWLNG9e3ehKIr6S7cqk4akpCQxfPhwce+99wpFUUSDBg3E6dOnhRBF24bsj9VqFY0aNRKKoohnnnmmxHk/cuRIoSiKePHFF6smCCeliedKqtv+oKzxWK3War0/IP/EJKiSWCwWMWjQIHHTTTeJvLw8IUTRX0h5eXnigw8+EGFhYUJRFPH5558LIVx/wcgdyYQJE8SmTZs043Jzc8V3330njEZjZYei9qWs8QghxC+//CJuuukm9fv58+fFQw89pO7sDAaDmD59epXE4Kws8SQmJgohhNi3b59o06aNCAkJEW+++aZmJy6XXXZ2tpgwYYJQFKVKT7l4ur698MILYseOHZp6Qghx+vRp0a5dOxEZGSlSUlKqKBq7v//+WwhhP901fPhwoSiKmDx5sks5uZ0sWrRIKIoiateuLTZs2KCJQ5ZJTk4WiqKIsWPHisLCwiqIokhp4ylJddofCFG+eKrr/oD8Fy+MrgRCCOj1ehQWFuLSpUvIzc0FUHS3TWhoKO68806MHTsWADB9+nSkpaVBURTNhY56vR6XL19GXl6eelu29P333+ODDz5AUFBQtY0HAM6ePateaPvaa6+hSZMmWLp0KeLi4nDXXXfBZrPh0KFDOH78eKXH4Wk88rUFRqMRGzZswMGDB9U25bILDw9H9+7dERYWViXLxpN4FEWB1WqF0WjEb7/9hl27dmnqWSwWxMbG4uGHH4bNZlPv3qkq8rk/wcHBeP755xEcHIwPP/zQ5SJc+e62sWPHomfPnrh06RIWL16Mo0ePqm3p9XoIIdCwYUM0a9YMBQUFVf7Kk9LGU5Lqsj+QyhPPhQsXqt3+gPycFxOwGq2goED069dPKIoiNmzYIIQQLn957ty5U8TFxQlFUcS///1vIYTrYeSjR4+KRx99VDNs/fr1omXLliIkJEQcPny4EqMoUtZ4XnnlFSGE/fRQo0aNRIsWLYSiKCI8PFxMmzZN5Ofni8uXL4sBAwaI4OBgsWDBAs2RleoWz4wZM4QQ9gs2GzRooD6F+OTJk2pdk8kkhBBixYoVonnz5up1NNUxHrm+CWE/jVK/fn3NaSSbzabWX7t2rahdu7bXn+z7wgsvCEVRxO23364OK35R8Y4dOzSnVM6cOSOEKJoX+fn5olmzZuK1116r4t67ulI8Jaku+wN3SrN81q5dWy33B+S/mASVw9V2VPIw/MyZM4WiKKJ///5uy+Xl5YnZs2cLRVFESEiIeleL83n+1atXq7+Ajxw5Iu6//351J3/bbbdVyC+myorn8uXL4r///a/6uP+RI0eKvXv3auosXbpUBAYGitjYWHHw4EGPY6nMeNLS0oQQQsyfP180atRI6HQ6MXr0aJcLQZ977jnx5ptvlqovpVHZ65vZbBY333yzaN68udu72p599lmXV2x4orzz5MKFC6Jly5aaU5TOfzTIdufNmycaNWokAgMDxRNPPKFpIzU1VfPut4pQWfG4m0Z12B+UpDTxrFixQtSuXbtK9wdEV8IkqAyysrLEG2+8IbZv337FcnInsnHjRhETEyMURRH//e9/hRCuO4U9e/aIHj16CEVRxPz5813amD17tli5cqV4++231Tt2YmJixNKlS6t9PEuWLBGXLl0SzzzzjPjqq6805eTttOnp6WLixIli0aJF1T6euXPnCiHsRxNWrFghmjRpov7ymT9/vjh06JB4+OGHRa9evcT+/furfTzz5s0TQtiXxZtvvimCg4NF48aNxfLly8X58+dFVlaWeOihh0SnTp3Erl27qiyeK1m6dKlQFEW0b99e5ObmCiGKkkD5r8lkEhs2bFB/IU+aNEls2bJFmM1mMWHCBPHAAw+U6kJkb8fjrDrtD66kpHhk/0+dOiX+7//+r0r2B0SlwSSolN577z0REhIiFEUp9TMsjh49KoYMGSIURRGDBw9WD8k7/6WVnZ0tpk+fLvR6vXj88cfVUypC2P9yv/3220X9+vXVv/aeffbZCrn4sSrikYftnce7+8u9Io6WVNXycX4b+Z49e8T06dNF48aNRdOmTUXTpk3F5MmTK+SN5VUdT0ZGhpg/f76oV6+eUBRFdOrUSdStW1c88sgjXovHnYKCAnHzzTdrTumVdEv20aNHxRtvvCFatWolrrvuOtG2bVsxefJkr20/7pQlnuq2P3CnNPFUxf6AqLSYBF3Fxo0bRbt27dSdzvXXXy+OHz9e6vpvvfWWiIqKErVq1RIfffSREMJ1p/DNN9+I8PBwccsttwghinYCx44dU6c7ZMgQ8ccff/hkPM4xVTRvLh8pLy9PnD17VvMMnvLy1vKR/vrrL/HLL7+I7777Tvz555+eBSM8j8edn376SSiKIqKjo8WJEyeEEFe+xTw/P1+cO3euVM/kuhpvxlMd9wfulCYeJjpUXTAJuoI9e/aotxW3atVKfPjhh6V+FofcyA8dOiRuvfVWoSiK6Ny5s7ojtlgsapnMzEwRFxcnWrduLTIzM9U23nzzTRETEyP+97//+Ww8lfnskuoUT0Xs1KtTPBXBk3iuRj6G4MEHHxRCXH3+e3v5XE1p4qlO+4OrKevyIfIWJkFXkJaWJmrVqiWmTJni0V+RiYmJon379pqdgiT/Qho+fLjLBa3yzpaK4q14KmsHyHjcq2nxuHP06FERGRkpFEURP/30U4W2XRJvx1Nd9wfueGP5EJUHk6ASWK1WkZGRIcaPH68e0i0r+cslJydHLF26VBgMBqEoivjwww/VW5HNZrOwWCziuuuuU+/AqYiLNovzZjyV8c4pxuOqpsVzNa+//rpQFEX06dNHZGZmigULFojff/+9UqbFeMquKuMhKi8mQVeQmZkprr32WvH7778Lq9UqduzYIdavXy9+/fVX8eeff2qSldL8IlmyZImIjo4WQUFB4umnn1avIdm8ebMYPHiwOHXqVKXFIgTjuRrGU7EqOh5nVqtVXLhwQX0diE6nE61btxbHjh2r6DBUjKf0vBEPUXn4dRIkN3J3G7gcNmLECHHLLbeIm266Sb3YT1HsL9EcOnSoWLlyZZmmeeDAATF8+HARHR0tOnToIAYOHCjat28v1qxZw3gYD+Mpg19//VWEhoaK5s2biy+//LLc7UiMp3rHQ1QZ/C4JkqcMEhMT1acal6SgoEAMGjRIvXNCPpPD+bui2N/FVJanm5rNZvHnn3+K5ORk9W3kjIfxMJ7SO378uIiLixNPPfVUuWMRgvFU93iIKpvfJUFC2J9s2q1bN3Hddde5fWmk8/epU6eK6Oho8a9//UskJyeLn376SRw+fFjMmTNH/OMf/xCKoohrrrlGbN68ucrjkBgP46lK1SGegoKCEt8Uz3hqVjxElcnvkqDTp0+rtxAbDAbxxBNPuH2onJScnCyOHj3qti2j0ShmzJghQkNDxdSpU4UQlXOR6ZUwHsZTlRgP4yGqSfwqCbJarSIpKUl899134u233xYNGzYUsbGx6isGrnSrsM1mU3cAzj9nZGSIqVOnioYNG1Z+AMUwniKMp/IxniKMh6hm8KskSAihPg8jIyNDPP/880JRFBEfHy8uXrwohCjfXzp79+4V99xzj/j7778rtK+lwXiujvFUHMZzdYyHyHfo4GcaNWoEAIiJicG9996LHj16YMOGDfjqq68AADpd2WdJeHg4Ll++jKZNm1ZoX0uD8Vwd46k4jOfqGA+R7/C7JAgAhBAAgI4dO2LcuHEwGo1ITEzE8ePHAQA2m61M7YWGhuIf//hHhfeztBjPlTGeisV4rozxEPkOv0yCFEUBAAQFBWHQoEG4/fbbsW3bNqxYsQLAlf9acrcD+fnnn9G5c+fK6WwpMJ4ijKfyMZ4ijIfIt/llEuSsVatWeOCBBxAZGYmVK1fil19+AVDyX0tyB5KbmwsAWL16Nc6cOYNbbrmlajp8FYyH8VQlxsN4iHyaF69H8kjxC/w8eQnkhQsXxCOPPCIURRGTJk0SBQUFJbb53//+V7Ru3Vp07dpVNGrUSIwcOVKcPn263NOWGE/JGA/juRrGU7LqEA9RdRXg7SSsrI4dO4Y333wTISEhEELgvvvuw8CBA9VDwOVRv359jBgxAj/99BO++eYb3HrrrRg2bJjbsqdPn4YQAqGhoVi4cCHuu+++ck8XYDylwXgYT0kYz9V5Mx6ias8bmVd5WCwW8eSTT4rY2Fgxbdo08eKLL6rvuXn77beFEFe//dPd29nlX0PZ2dnitddeE4qiiLvuukucP39eHS8/UmpqKuNhPIyH8TAeIh/nM0nQW2+9Je644w7NBvr777+L9u3bi/DwcJGbm1tiXavVqtnI3e0shBBi37594oYbbhChoaFiwYIF6nCTyaS2U1EYTxHGw3jKivEUqY7xEPmKap8EWa1WkZaWJtq0aSPeeustIYT9hZByo58zZ46IiIgQu3fvdqlrs9k0O4Rdu3aJoUOHivXr17s9H15QUCAWL14sQkNDRZMmTcSLL74obr755gp54zbjYTyMh/HU9HiIfE21T4KEEOLw4cMiMDBQbNmyRQhh33HIv1qOHj0q6tatK86dO1di/bS0NPHEE0+ob0V++OGHhdFo1JSR7f3555+iRYsWQlEUUb9+fbF48WLGw3gYD+NhPEQ1kE8kQb/++qsIDg4Ww4cP1wy32Wzihx9+EJMnT1YP6Rb35ptvioYNGwpFUYRerxevvfbaFaf1r3/9SyiKIl555ZUK639xjKcI42E8ZcV4ilTHeIh8SbVJgn788Uexf/9+kZKSor71WP71cvnyZXHLLbcIRVHEAw88ILZt2yaysrKEEEJs3rxZ7N+/X9OWPBS8Z88e9a+jsWPHqhcDCuH+vPnWrVvFk08+WSHvyGE8jIfxMJ6aGg9RTeH1JGjfvn3ipptuEr179xYDBgwQ4eHh4q677hJ79+7VbMg//vijGDRokFAURQQHB4tGjRqJO++8U7Rv317cdNNN4oknnhALFy4Up06d0rQ/ffp09TCzEPadQ0nP3KiICwMZD+NhPIynpsZDVNN4NQnKy8sTQ4cOFf/5z3+EEPbbOGfPni1iYmJESEiIePnllzXlMzMzxaxZs8Q999wjWrRoIerVqyc6deokgoKChE6nE4qiiNq1a4uZM2eKtLQ0Td3iFxEyHsbDeBgP4yHyb15NgtasWSNiY2PF2bNn1WFGo1F8++236mHeefPmuWzwQgiRlZUlvv/+eyGE/cLCFStWiPHjx6v1Xn31VZGdnS2EKPmWUcbDeBgP42E8RP7LK0mQPFz79NNPi7Zt22qGyX9nzpwpFEURTZo0EQsXLlTrykO6K1as0DzrQvr+++/FjTfeKJo1ayaOHDlSqXFIjIfxMJ7yYzzVOx6imsxrR4KsVqsYPny40Ov16sbsfGuoyWQS/fr1E4qiiN69e4utW7eqZYQQYuTIkerzLSwWi/rXUGFhofjyyy+Foiji559/ZjyMh/EwHsZDRG555S3yQgjodDo0aNAANpsN//vf/wDY32Cs0+lgtVphMBgwffp01KtXD3v37sXXX38Nk8mkvuU4JSUFiYmJaj29Xg8ACAgIQN26dVGvXj0EBwczHsbDeBgP4yEit7ySBCmOlwG2atUKer0e27dvx5kzZ9TxcoMfNGgQ7r77bpjNZvzyyy/47bffAABGoxEGgwFff/01du3apbZnsVgAAGlpaWjXrh3atm3LeBgP42E8jIeI3PPiUSjxzTffCEVRRNOmTdWLACV5+Hf//v2iTp06IiAgQCxZskQ9pz5v3jyhKIro0KGD2LNnj8jPzxdC2G817dmzp0hISKjaYATjYTxVi/EwHiLyjNefE3TttdcKRVHEY489JjIyMtyWmTx5slAURYwaNUozfOTIkSI0NFTodDpx++23ixtvvFG0atVKrFy5siq67hbjKcJ4Kh/jKcJ4iKisFCGE8OaRqJUrV2LkyJGIiIjAF198gdtuu009L261WqHX65GSkoJWrVqhQYMG+O2339CoUSMAQH5+Po4cOYIff/wRBQUFqFu3Lh577DFvhsN4GE+VYjyMh4g84O0szGw2ixtvvFEoiiKGDh0qTpw4oRlvs9mEzWYT99xzj2jcuLHIzc0t8Ymo1QHjYTxVifEwHiIqP69cGO0sMDAQs2fPBgB89dVXSExMxMWLFwHY/1JSFAWKoqBJkyZQFAUmk0m9ULA6YjyMpyoxHsZDROXn9SQIAG644Qa89NJLAIAPP/wQH3/8MQD7XRRGoxEAcPbsWbRt2xZRUVHe6mapMZ7qjfFUb4yHiKqMtw9FSQUFBeKVV14RERERQlEU8Z///Ee9g8JoNIr4+Hjxyy+/eLmXpcd4qjfGU70xHiKqCtUmCZK+++470a1bN6Eoirj++uvFq6++Ktq1ayf++c9/itzcXG93r8wYT/XGeKo3xkNElcnrd4e5U1hYiO+++w6nTp3CqVOnMGTIEAwYMMDb3So3xlO9MZ7qjfEQUWWpdkmQEKJGXRjIeKo3xlO9MR4iqkzV4sJoZ847iGqWn5UL46neGE/1xniIqDJVuyNBRERERFWh2h0JIiIiIqoKTIKIiIjILzEJIiIiIr/EJIiIiIj8EpMgIiIi8ktMgoiIiMgvMQkiIiIiv8QkiIiIiPwSkyAiIiLyS0yCiIiIyC8xCSIiAMCyZcsQERGBZcuWebsrRERVgkkQEQEAvvzyS+Tk5GDNmjXe7goRUZVgEkTkh7Zu3eoy7F//+heuu+46TJkyxQs9IiKqenyLPJGfsdls6Ny5Mw4ePOjtrhAReRWPBBH5mVmzZuH333/3djeIiLyOR4KI/MjHH3+Mhx56CEIIcNMnIn/HI0FEfuKtt97CrFmz1OTnmmuuwTXXXIPnn38eeXl5WLJkCbp164ZXXnlFUy87OxuvvfYaoqKiAACXLl3C+PHjERERgWbNmuGTTz5Ry27evBk33HADQkND0bVrVyQnJ7vty+HDhzFy5Eh06NABtWrVQqdOnfDxxx9XRthERCUTRORXAAjnTf/QoUNi5MiRIjQ0VAAQM2bMUMctXrxYtGjRQq2TkZEh2rVrJxo1aiSCg4MFAKHT6URycrJYu3atMBgMokmTJkKv1wsAonbt2iIzM1Mz/Q0bNojmzZuLn3/+WQghxOnTp0WXLl0EAPHKK69UyTwgIhJCCB4JIvJz7dq1w+eff47Ro0e7jBs7diw2bNigfn/ppZewePFinD17FhcvXsT1118Pm82GF154AZ9//jn++OMPnDp1CidPnkRsbCwyMjLw/fffq/UzMjIwatQozJ49GzfeeCMAIDY2FosXLwYAvPbaazhx4kQlR0xEZMckiIgAAHXr1nUZFhwcjGbNmqnfZ8+ejRtuuAEAUKtWLTz66KMAgMzMTKxcuRJNmzYFYE9s/vGPfwAATp06pdb/+OOPkZOTg7vuuksznU6dOgGw37m2du3aCoyKiKhkAd7uABFVD4GBgW6HBwUFqT+Hh4drxjVq1EgdriiKZlydOnUAAAUFBeqwTZs2QQiBrl27ukyndu3aAIC0tLRy9J6IqOyYBBFRuel0JR9MluOE011op06dQkxMDI4ePVrpfSMiuhqeDiOiKmOxWHDx4kVkZmZ6uytEREyCiKjqNGzYEEIIrFq1yu14IQQ2b95ctZ0iIr/FJIiIqkzfvn0BAC+88AL++usvl/EJCQk4d+5cVXeLiPwUkyAiPxMSEgIAMBqNmuFmsxkAUFhYqBnu/N1isWjG2Ww2AIDVanWZjrwWyLn+pEmTEBYWhvT0dFx//fVYtGgRUlJScPz4cfVhjsXvHCMiqixMgoj8TPv27QEA27ZtQ35+PubOnQubzYaff/4ZAPDzzz9rkho5HAB27typaUueujpx4gTS09PV4RaLBb/++isAIDk5WW0vNjYWH3/8MQICApCWlobJkyejZcuWaNOmDV5++WV89NFHqFWrVsUHTUTkBt8dRuRndu7ciTFjxiAzMxNjxozBfffdh7vvvhuXLl1Sy0RHR2Pjxo147733sHz5cjWJ0ev1uPXWW7Fq1SrExcUhNTVVrRMUFIRp06bhpptuQnx8vObi56ioKPz6669o27YtAHti9Oqrr+LXX3+FzWZDnz59MHPmTPTs2bNqZgIREZgEERERkZ/i6TAiIiLyS0yCiIiIyC8xCSIiIiK/xCSIiIiI/BKTICIiIvJLTIKIiIjILzEJIiIiIr/EJIiIiIj8EpMgIiIi8ktMgoiIiMgvMQkiIiIiv8QkiIiIiPwSkyAiIiLyS0yCiIiIyC/9PzJbh+JUGwK/AAAAAElFTkSuQmCC",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -3794,9 +3938,7 @@
     }
    ],
    "source": [
-    "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(\n",
-    "    ds.velds.U_mag, noise=ds_avg[\"noise\"]\n",
-    ")\n",
+    "ds_avg[\"turbulence_intensity\"] = avg_tool.turbulence_intensity(ds.velds.U_mag, noise=ds_avg[\"noise\"])\n",
     "\n",
     "(ds_avg[\"TI\"] - ds_avg[\"turbulence_intensity\"]).plot(cmap=\"Greens\", ylim=(0, 11))\n",
     "plt.title(\"TI Difference\")"
@@ -3807,61 +3949,50 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 7.6 Turbulent Kinetic Energy (TKE) Components\n",
+    "### 7.6 Reynolds Stress Components\n",
+    "\n",
+    "The next parameters we'll find here are the Reynolds normal and shear stresses (-$\\overline{u_iu_j}$). Since we're using the vertical beam on the ADCP, we can directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
     "\n",
-    "The next parameters we'll find here are the vertical TKE component and the total TKE magnitude. Since we're using the vertical beam on the ADCP, we'll directly measure the vertical TKE component from the along-beam velocity using the `turbulent_kinetic_energy` function. This function is capable of calculating TKE for any along-beam velocity.\n",
+    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the normal and shear stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. \n",
     "\n",
-    "We can also use the so-called \"beam-variance\" equations to estimate the Reynolds stress tensor components (i.e. $\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$, $\\overline{u'v'}$, $\\overline{u'w'^2}$, $\\overline{v'w'^2}$), which define the stresses acting on an element of water. These equations are built into the functions `stress_tensor_5beam` and `stress_tensor4beam`. Since we're using a 5-beam ADCP, we can calculate the total TKE as well using `total_turbulent_kinetic_energy`, which is a wrapper around the 5-beam variance function.\n",
+    "Both of these functions will give comparable results, but `stress_tensor_5beam` takes into account instrument tilt, and `stress_tensor_4beam` does not. Both will throw a tilt warning if tilt is greater than 5 degrees.\n",
     "\n",
     "#### Quick 5-beam ADCP lesson before we dive in:\n",
     "\n",
     "There are a couple caveats to calculating Reynolds stress tensor components:\n",
     "  1. Because this instrument only has 5 beams, we can only find 5 of the 6 components (6 unkowns, 5 knowns)\n",
     "  2. Because the ADCP's instrument (XYZ) axes weren't aligned with the flow during deployment, we don't know what direction these components are aligned to (i.e. the 'u' direction is not necessarily the streamwise direction)\n",
-    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly.\n",
-    "\n",
-    "That being said, even if we don't know which direction the 3 TKE components ($\\overline{u'^2}$, $\\overline{v'^2}$, $\\overline{w'^2}$) are oriented, we can still combine them and get the total TKE magnitude.\n",
-    "\n",
-    "We'll first calculate the vertical TKE component, using the function `turbulent_kinetic_energy`, inputting our raw vertical beam data and the noise floors we calculated above for each ensemble."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Vertical TKE component (w'w' bar)\n",
-    "ds_avg[\"wpwp_bar\"] = avg_tool.turbulent_kinetic_energy(\n",
-    "    ds[\"vel_b5\"], noise=ds_avg[\"noise\"]\n",
-    ")"
+    "  3. It is possible to rotate the tensor, but we'd need to know all 6 components to do so properly (\"coupled ADCPs\")\n",
+    "  4. Measurements close to the seafloor can be suspect due to increased vertical flow. ADCPs operate under the \"assumption of homogeneity\", which means that they can only accurate measure consistent horizontal currents with relatively little vertical motion.\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Next we can calculate the TKE magnitude using the function `total_turbulent_kinetic_energy`. This method is a wrapper around the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs. As an fyi, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically and rotate the original."
+    "As an example, we'll calculate the Reynolds stresses from the `stress_tensor_5beam` function, which calculates the individual Reynolds stress tensor components and takes the same inputs: the raw dataset in \"beam\" coordinates, the instrument Doppler noise, the ADCP's orientation and its beam angle. It outputs both the normal stress (\"tke_vec\") and the shear stress (\"stress_vec\") vector. Note, this function will drop at least one warning every time it's run, primarily the coordinate system warning. This function also requires the input raw data to be in beam coordinates, so we'll create a copy of the raw data and rotate it to 'beam'. If you do not, this function will do so automatically."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:401: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:407: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
+      "  warnings.warn(\n",
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:417: UserWarning:     100.0 % of measurements have a tilt greater than 5 degrees.\n",
       "  warnings.warn(\n"
      ]
     }
    ],
    "source": [
-    "ds_beam = dolfyn.rotate2(ds, \"beam\", inplace=False)\n",
-    "ds_avg[\"TKE\"] = avg_tool.total_turbulent_kinetic_energy(\n",
-    "    ds_beam, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
+    "dolfyn.rotate2(ds, \"beam\", inplace=True)\n",
+    "ds_avg[\"tke_vec\"], ds_avg[\"stress_vec\"] = avg_tool.stress_tensor_5beam(\n",
+    "    ds, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
     ")"
    ]
   },
@@ -3869,51 +4000,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "And plotting TKE:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.collections.QuadMesh at 0x23392108820>"
-      ]
-     },
-     "execution_count": 32,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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h8k1slEVQ+JQrvHISEVHe3b8ll76BAABx4wwAQAmuYQ4Td0cu1fM9hADi4ouqhPSQYGONiIjITtk6CwFnMLAPbKwRERHZKQ7dUXK8/PLLSEhIKJS02VgjIiIistHs2bMLLW021oiIiOyUBgo0NlwfsyUuWbd7927s3LkTwcHB6NKlCxwdHW1Ok401IiIiO8XboMWjc+fOpvfVqlXDZ599BgB455138OWXXwIAhBCoV68etm/fDg8PD5vy46C4RERERHmwbt06nDp1CqNGjTI11NavX48vvvgCQgiMGjUKv/32G0JDQzFx4kSb8+OVNSIiIjvF3qDFZ82aNahVqxYAeRVt7NixUBQFI0eOxPTp0wEAbdq0QaNGjTB16lSb8mJjjYiIyE7xNmjxKF++vKmhBgArV67E6dOnERAQgI8//ti03tXVFXfu3LE5P94GJSIislNKAfyjvPP19TUN05GYmIj33nsPiqLg3XfftXg+7cSJE2ysERERERW17t27o2PHjpgzZw5at26NS5cuoXr16hg+fLgpzL179zBo0KACyY+3QYmIiOyURpEvW+JT3o0fPx7379/HmDFjkJqairp162LFihWmYTree+89LFy4EP/99x+UAngwkFfWiIiI7JRSAC/KOwcHB8yYMQMJCQmIjo7GkSNHUL16ddP20aNH49ixY7hz5w5u375te342p0BERET0ENJqtfDz88u0vkyZMgWaDxtrREREdoq9QR8ObKwRERHZKVt7dLI3qH3gM2tEREREJRivrOVF/D1AazB/1uvlUqvuRoP6WaO2gb3LAgCU9BsZ0rgLABC6VLnNyUWuj4mSS59ycnn/ljmOb6BlORLvy6W7b5ZFFddPyfRDamZTIesMu9bKuJXryM8XjwEAtM06ZxmHiEjcPAsAUFzc5QqNVi4dMkxknZ4uw6YmqpHkOVUpH26Z1n/nTe9N2+6q51JXT7lMipNL/xC5jI82xTHclPE1wepD30LIZZo898LZVS716eZMvQIsK/TgudfRGZkYe/oZz90xUUU6LQBnMHg4sLFGRERkpzSw7RYZb6/ZB35PRERERCUYG2tERER2iuOslUx37tzBtWvXCiw93gYlIiKyV4pi2wj5fGgt19LT0/Hvv//izp07CA0NRaNGjbIM6+7ujn79+iExMRF9+vTB4MGDbcqbV9aIiIjsFK+sFY09e/agWrVqaNOmDV5++WU88cQTCA4OxowZM5Cenp4pvJubG7755hv8+++/eP31123On401IiIioiycP38e7du3x9WrVyGEgK+vLxo2bAgXFxeMGTMG9evXx4kTJzLFq1y5Mtzd3SGMPZFtwMYaERGRneKVtcL38ccfIz4+Hu7u7pg/fz6io6OxZ88eXLhwAZcuXUK7du3QsmVLrFmzJlNcFxeXAilDqW+s/fvvv3j22WcRGBiI4OBgVK9eHRMmTEBKSkpxF42IiMgmivrMmi0vyt5ff/0FRVEwe/Zs9O/f32JbpUqV8OWXX2L37t344osvMHv27EIpQ6lurK1atQotW7ZE48aNcf36ddy4cQPLly/HggUL0KZNG+h0uuIuIhEREZVgMTEx0Gg06NWrV5ZhqlWrhm3btuHEiRP48MMPC7wMpbaxlpqaimHDhqFt27aYMGECHB3lCNr169fHp59+il27dmH+/PnFXEoiIqL80yi2vyh7lSpVAgAYDIZswzk6OmLu3LlwdnbGW2+9VaBlKLWNtWPHjuHu3buoV69epm2PPfYYAOD48eNFXCoiIqKCo2gUm1+UvVdeeQUGgwFbtmzJVfj33nsP4eHhGDJkSIF0LgBKcWPN3V3OTbd3795M2+Lj4wHAakOOiIiIyOidd95B+/btMXLkSNy8eTNXcYYPH446derg3r17BVKGUttYe+SRRxAeHo5t27Zh2bJlFtvWrl2LOnXq4JVXXimm0hEREdnOOJG7LS/KnoODA9avX48xY8bg1VdfxQ8//JCreMOHD8fkyZML5OpaqZ3BQFEUzJs3D+3bt8err74KIQR69eqFnTt34uDBg/j777/h7OxsNW5qaipSU1NNn+Pi4oqq2ERERLlma4OLjbXc0Wg0GDZsGIYNG2Z1ENysvPvuu/Dx8bE9f5tTKMFatWqFNWvWQKvVok+fPhg5ciTWrl2LP//8EwEBAVnGmzJlCry9vU2vkJCQIiw1ERERlVQODnm7zvXrr7/anGepbqwBwPPPP4+pU6dixIgR+OqrrzBnzhysWrUq2zjjxo1DbGys6XX9+vUiKi0REVHuFec4azqdDp999hmqV6+OKlWqoGXLlti+fXue07l16xaGDBmCypUrIywsDD169MjVJOjHjh1Dz549MXDgwFzl89Zbb1mt/5w5c/JcZiMhBKKjo3H9+nVcu3bN4nXx4kUsWLAAmzdvznf6RqX2NqjR1KlTER4ejuHDh6Np06bo06cPevXqhejoaAwfPtxqHGdnZ+u3SD39AOjNnzVqW9egrktTb536q1fi4qPl0jFDWp5lAAAK1HvYejVu+gNjvmXooSP+Oy/faOXwI0rZSpZh76oPPJapYFqlhNSUb2KjZBo6dRDguLtye5XHMtfPmHXTThaftYFVswxLRMXs/n9y6Vs+0zoRZzwHOQEAlKDqFlHFrQvm91FXZRjfcnJZsbZcH3lWBtBo5dKQ4RyoypSu8XymUf+L0ZkHIVfKhcmlem4ynteQoD6IrTYelPLh5gRj1LBO6mjwbt4yn4T7MmyiXMLT3xRFU0N9f/eGXLq4W6RvknE4hrg7cull/c6LsewWjM8jJcao9dHKVxEprtugqampeOaZZxAVFYUtW7agYsWKWLVqFdq2bYslS5agW7duuUrn8uXLaN68OZo1a4aTJ0/CyckJb7/9Nho0aIAdO3agevXqmeLs27cP06ZNw5o1ayCEyNXz59HR0VafNStTpgxeffXVXJU1o+TkZIwcORJLly5FUlJSnuPnValurE2fPh2//PIL9uzZAwDo3r07nJyc0LVrV4wYMQL169dHs2bNirmURERE+WPr1bH8xh07diwiIiKwd+9eVKxYEQDQrVs3rF27Fv3790eDBg0QFmalcZuBXq9Ht27doNPp8OOPP8LV1RWA/L97zZo16N69Ow4cOGAaJ9UoICAAK1aswIABA7Bo0aJclXfmzJkYOnQoXnvtNYv1Hh4ecHNzy221TQYPHoylS5dCCAF3d3f4+flBo7G8WSmEwK1bt5CWlpbn9B9Uam+DXr16Fe+//z6ee+45i/UvvfQSPvvsMwgh8PHHHxdT6YiIiOzTlStX8M0336BmzZpo1KiRxba+ffsiMTER48aNyzGdZcuW4eDBg+jWrZtpuC0A0Gq16NmzJ44dO2Z18PqwsDBoNBo0btw4V+WNj4/HwoULMX78eNSoUcPiFRwcnKs0HmR8Dm3RokWIj4/H1atXcfnyZYvXlStXcOzYsTw/42ZNqW2sbdiwAampqShbtmymbSNHjkRAQAD27dtXDCUjIiIqGMUxdMeKFSuQnp6Opk2bZtpmbECtXbsWd+/ezTadJUuWAIDVdJo0aQIA+P7777OMn9tJ0ufMmQMvLy9s3rwZUVFRuYqTE19fXwQGBqJv377ZhqtWrVqm+UTzo9Q21ozzft64cSPTNgcHB1SqVAlOTk5FXSwiIqICo1EUm195tWHDBgBA5cqVM23z8/NDhQoVoNPpsHPnzizTSEpKwtatW7NMp06dOgCAw4cPIzY21moaubmFm5KSghkzZuD06dPo1asXgoOD0alTJ5w9ezbHuNkZMmQIEhIScnWLc8SIETblBZTixtrzzz8PrVaL1atXZxoTJTY2FmfOnEGXLl2KqXRERET26fDhwwCQ5S1E47hiR44cyTKN06dPIyUlJct0jGkIIXD06NF8l3XXrl2oWLEiQkNDAQDp6elYt24d6tWrl2nA/Lx499130aFDh1z1JG3VqlW+8zEqtR0MqlatimnTpmH06NHo378/vv76a3h7e+PWrVvo378/QkNDMXny5OIuJhERUb4VVG/QBwd/z2pUhJSUFCQkJABAloO9envL3rrR0dFZ5nvnzh3Te2vpGNPIKZ2ctG7d2vTI0/Xr1/H9999j2rRpSElJQd++feHv74927drlOV2NRoNly5ahR48e0Gg0FuU10uv12LNnT463g3Oj1DbWAGDUqFGoXr06vvjiC4SFhcHT0xMuLi7o2rUrVq5cCU9Pz+IuIhERUb4psLE3KGTcBwd/nzBhAj766KNM4TM2PLLqRWnsFWm8cmZNTulk7FmZXTp5ERISgokTJ+Lll19G69atERUVhTfeeANnz57N8z68cOECOnfujJMnT+KXX37JMpwQwqbvx6hUN9YA4Nlnn8Wzzz5b3MUgIiIqsa5fvw4vLy/T56ymY8z4rHdWc14anxn38/PLMr+c0jGmkVM6+VGzZk1s3LgRDRs2xPnz53Hw4EE0aNAgT2kMGjQIJ06cgKOjI1q0aIGgoKBMQ3cYDAbs27cP586ds7nMpb6xRkREVFopGvnKd3y1neTl5WXRWMuKn58fnJycoNPpkJiYaDVMTEwMAMDf39/qdgAIDAw0vU9MTMx0G9GYRk7p5Ndjjz2Gnj17YsmSJbh48WKeG2v79++HoijYsWNHpuFLMkpKSkK5cuVsLW7p7WBARERU6tk61VQeb9FptVrUrClnyImMjLQaxjg8xqOPPpplOrVr1zbdHrSWjjENJycnPPLII3kqY261bdsWgBwYN69q166N4ODgbBtqgLzFO3v27HyVLyM21oiIiCjX2rdvDwA4efJkpm3R0dGIjY2Fu7s7WrZsmWUavr6+poaOtXQuXJBTobVo0cJiwNyCVL58eWi1WjRs2DDPcadNm4a7d+/i3r17OYYtiGfW2FgjIiKyU8UxKO7AgQOh0WisTtq+e/duAECXLl1yHMt08ODBAJBtOr169cp7AXPpxIkT6NGjh9XB83PSokULrFixAlOmTMk2nE6nw8iRI/NZQjM+s0ZERGSnZIPLlrlB8x4nPDwcgwcPxnfffYcjR46gXr16pm2LFi2Cq6srJkyYYFoXERGBd999F71797YYILZv376YOXMmVq5cialTp5pmJNDpdFi+fDlq166NPn36ZFkO4xiqer0+yzBJSUlQFMU076hRbGws1q1bh9WrV+ep7kYDBw6EEALHjx9Ht27drI4ukZ6ejmPHjmUaFiU/2FgjIiKyUwU1zlpeTZ8+Hfv378fQoUOxceNG+Pr6Yvbs2fj999+xZMkSi1kJvvjiC+zbtw+nTp2yaKw5Ojpi6dKlaNWqFUaPHo2vvvoKOp0OgwcPhsFgwOrVqzNN4p7R3r17AQBHjx5FSkpKpumn9Ho9goODYTAYMGXKFAwaNAiOjo44efIkZsyYgUWLFuX74f/79+/j119/hRACBw8ezDYsh+4gIiKiIufu7o6IiAh88MEHaNCgATQaDWrXro39+/ejbt26FmF79uyJ7du3o1+/fpnSqV27Nnbv3o13330X4eHhcHR0xNNPP42jR49meXty1qxZmDhxoul5sePHj8Pf3x9dunTBokWLTOG0Wi0++eQTzJw5E6NGjcKUKVPQokULtG7dGt99951NE6x/9NFHWL9+Pd555x2EhoZaHeokLS0N27dvN82BagtFZDVQCpnExcXB29sbsbGx8NJmuNyqV6exMu7CtFS59FcHF4yPttwOAF4BltuMl2/TdZZxY82TzYok9RKqVv6FoZStZFnAuzflskyFzIVX0xE6dVDBODkQoVLlscxhicj+3P9PLn3LZ1on4tTzjKN8dkgJqm4RVdy6YH4fdVWG8ZVXGpSKteX6SHUORY1WLg2ZbzkZ0xU31bAO6tUQjUOmOEq5MPnGeI7TPnDlxHgVwt3XvC7GGFYtg6ccykHcviKjuHtnjmN0V50f2kV9SN14LnRSr8KkmcfzgnGcLON5Ojfi1JH4jfUwpCMuLh7ewZXl/xm5GA4jP4z/Lx1/pAo8jfslH+L1etQ5fbFQy1pavfHGG/j6669zvHIWGBiIW7du2ZQXr6zlRcI9wD3DfW9v9fKp8UTioD5MmaROOqueUBB72xzH2EgzGORSqEvnB0ZwNmRo4BkbaU6W99xNJ6EymedVE3fUE2+AnA/NeCiJtKxHghaRcuA+Jaia/Hx2j/xcvUmWcbKiX/e1LPpLw/Mcl8guxcs/hESKnIoHqckAACW4hvyceN8c1lqjIgci6rJMTytP20L9Y1FxzPwXvfGPM5Eo/9DT1GymllE9/xjPTRkaKppH28g419SeeeofgaYGntooMTUAASjBDwypkKKOu2VsPBnUP2j15smuTQ0sN7VhYPxj1rOMRT0Ra56OyNQYU/epSFLDpKr5Gc+N8eZR8cVt9RzoU9ayrsZByYzn4Iz/0ebUSDM2ML0z3Dp7ME7ifXOjrwgU121QAiZNmpSrGQrOnDljc17sDUpERESUhalTp1pd7+vrm2nWAmuymkM1q3StYWONiIjITtkyIK5pYFzK1g8//FDs6fI2KBERkZ3ibdDCV1iP9uclXV5ZIyIiIspCYV19zEu6vLJGRERkp3hlrfBduHABWht63BYENtaIiIjslKJRoGhsmMFAsLWWk4oVKxb7s31srBERERFl4cqVK8VdBDbWiIiI7BVvgz4c2FgjIiKyUxpFgcaGFpctcanosLFGRERkp3hl7eHAoTuIiIiISjBeWSMiIrJTts5CUNy9HCl32FgjIiKyUwpsvA1aYCWhwsTboEREREQlGK+sERER2SneBn04sLFGRERkr2zsDcr7oPl35MgR/Pnnnzh48CCioqJw+/ZtODk5wdfXFzVr1kTDhg3x4osvokyZMjbnxcZaXnmXM79PjJFLRye51KXIpZu3ZRwHJ/N7XbJcOrmqK4RcKOod6fhoufQNNEVR7kXKNz4Z8gaAMsEWH0XUJXMcdx/5JjbKIowSVB1ZUYKqWX6u3iTLsDnRvjQ833FLMv2yqab32p7/k+vmfyg/D5xoPc5Pk81x+o63GsZwYjsAQNw4DwBQyoVmCqO4ecgwseox4iVPAJoaT8g0Dm02hdU89rRcd2a3jHPzgsy/TV+LNMXNsxk+GGQ+njJdkRwv16vHtVKxltWyW6SnHoPG408kJ8gNSbHmMAkxcrlxuSxr19dknLB6cv2dqzJgus4UR1F/U4b/Lso4gZVlWPX3JC4clgE9fMyFUX93mprNLMt4fr984+Iu0w6pmU19Lss3GjkvoBJQUa6PPGcum/q7EcbzgbofkRRnmZiSzVMnifflMlU9P/gFZQ5jSJdLJxeZnH+I/BwTlSmoUi5MvjGeb4w8/WURLx+Rn7WOpk3G/SKMZXD1lGndvaHmq56zDPpMcZSycr8o3gFyg1o243epmM53AHzLy2X8XWMqcpFwTy4zfO8mxvPu/f9keuq+FGmpcr1e3Tca8z5WqjymluGa/FymnGW+xu/JWkvHeLwKtWzG86nIHNT03RmPdVcPK4GotEhLS8MPP/yAqVOn4to1eWwJkfnA2LFjB+bOnQutVovnn38e77//Ph577LF858vGGhERkZ3ibdCis3XrVvTr1w83btyARqNBWFgYwsLCEBoaCg8PD7i5uUGj0SAhIQGxsbG4dOkSzp07h3Xr1uHXX3/FwIED8cUXX8DT0zPPebOxRkREZKcUTfYXbXMTn3I2ZcoUfPLJJ+jWrRt69uyJZs2a5brRdeXKFWzcuBELFy5Ew4YN8eeffyI0NPPdk+zkurFWuXLlPCWcW4qi4OLFi4WSNhEREZEtpk6dik2bNuH48eOoUqVKnuNXqlQJr7/+Ol5//XX8/vvv6Ny5MzZt2oSyZcvmOo1cN9YKa9Z5XoIlIiLKH94GLVxbt27FiRMn8M8//8DBwfabkS+88ALq1q2Ld955B4sWLcp1vFxfAK1SpQoMBkOBvwrrih0REVGpp1Fsf1GW/vzzTyxYsKBAGmpGoaGhGD58ODZv3pxzYFWucy+s1jdb9URERPnEmdwL1ZQpUwol3YYNG+YpfK6vrFnrmloQCitdIiIiouKUnJyMw4cP4/r16zalk+vG2tChQ23KqKjTJSIiKu2Mz6zZ8qLCsWXLFlSsWBGtWrXCiy++iDZt2uDs2bM5R7Qi1421MWPG5CsDo4ULFxZKukRERA8tPrNWYr399tu4e/cuwsPDcfjwYcybNw+jRo3CrVu38pxWkYywEh0djTfeeKMosiIiIiIqdpUqVQIA3L59G4DsqLlo0SJMnz49z2nZ3L1h165d+Pnnn3Ht2jUkJydnegYtLS0NZ8+eRUpKiq1ZERERUUbsYFBiLV++HJs2bbKYZiogIADdu3fPc1o2NdZ+/PFHvPaanNcvp44CvC9ORERUsBSNAsWGW5m2xKXsubq6onPnzpnWN2rUKM9p2dRY+/jjjwEATz/9NAYMGAB/f39oNJZ3VoUQ2LZtGyZOtD7JNREREVFJFR8fjzNnzqBSpUoICAgoljLY1FiLiYmBm5sbfvvtNzg6OmYZrlWrVpg7d64tWREREdGDeBu00DVr1gwnT54EIG9j1q9fH/Xr10e9evXydUszP2zqYNCuXTt4e3tn21AzOnfunC1ZERER0QMURTHdCs3Xi421HCUkJEAIASEEkpKSEB8fj7i4OCQkJBRZGWy6sjZ9+nQ0bdoUe/fuRePGjbMN27lz5zxNrVAiefgBiffNnxW1rZucKJcu7nIZH511GsY4UJ/xS1a/bP8QuUyKlcuYKHMcv6BcFU8pZ2XqrljZCwXe1ieMNZzcYXqvqdXcYps4u0emW72JxXr9vPdM77WDP81V2Qpb+ogXTe8dvvqt0PLR9vxf5nUDrd/iNxySx7u273jTOv0vs+QbjVZue2m4/Jwgv3dth4Ey3OqZ5oR8y8hlihcAQOjTZNgaT1hm6OiUuRDGY9PJRZbp+FaZfZ1WAAClQnVTUHHlqHxjPFbi5HGsVKwlP9+9KZdlKmTOxyghRqYlDDKug7Nc7+FnzkcNo33nG/k56rJFEkpAqFwfmWE8IvXxCsVRTc+YvpOr/Oil7qM0nTlK3WZy24WDahm81Q1aNaPMf6uKO1flJje5rxVXD7k+NdmyjK5emeIi9o5cqnHg5gkAMOxaK7Nt2ilzHCODXi7V37q4Keue8fsxlttw87z8aCp05ueFxa2L8o2D+oe08btzcZNpXDou06jb0hxJPX8pyfEyjagrapnKyfVlguXSs0zm8t+XQxGIpDj5+bYa15iWq6cpqKlpkC6PY2E8pxq/F63631KG78dUH61anzS1w5qzqxrAkLlMxvwc1N9FbJRlusaltbjqbwye/nJpLKP6OzKdpwHzd2f83qnUOXToEM6cOYPAwEBTD8+iZtOVtUqVKmHHjh2YOnVqli1MIQR27tyJiIgIW7IiIiKiBxlvg9ryomz5+PigSZMmxdZQA2xsrAkhsHbtWhw/fhze3t7QarWZXg4ODmjRogUMhqz/8iEiIqJ80MDGQXGLuwL2Kzk5GR9//DHq1Klj0ZCLiIhAv379sGnTpgLLy6bboGPGjMGsWbNyNb8n74sTEREVLFunjOL/zflz//59tGrVCidOnIAQAv7+/qZtTz31FGrXro3WrVtj06ZN+Oqrr2zOz6Y29eLFiwEAb775Jq5fvw69Xg+DwWDx0uv1+OuvvzIN6UFERERkj95//30cP34cNWvWxMsvvwwXFxeL7QEBAZg8eTK++eYbfP311zbnZ1MLysXFBX5+fpg1axYqVKhgtYWuKApat26Ntm3b2pIVERERPYhzgxaLtWvXYvz48Th+/DiWLl0KD4/MHUzq168PIQS+/fZbm/OzqbE2dOhQGAyGXN0GXb16tS1ZERER0YPYwaBYGAwG08QAWblzR/YQv3Tpks352dRYGz9+PJ555hksW7Ysx7A1atSwJSsiIiKiEiE4ODjH5/3mzZsHAChb1vrQWXlhUweDf//9F4MGDcJXX30Fb29veHp6ZgqTnp6Offv2ITIy0pasbJaeno4VK1Zg/fr1cHBwQHBwMAYPHoywsLBiLRcREVF+KRqrQwbmKT7lXceOHTFp0iR8+OGHVrd/8803mDt3LhRFQZcuXWzOz6bG2sCBA02X93799VebC1NYDh06hD59+qBGjRqYMWMGQkNDi7tIREREtuN0U8Xi7bffRvPmzbF371506dIFSUlJ2Lx5M86ePYuVK1di165dAIDw8PAsG3R5YVNj7YMPPsCrr76K4OBgBAcHw9nZOVOYtLQ0nDlzBvfv37eSQuH79ddf8fLLL2PcuHEFssOIiIjo4ebq6oq///4bI0aMwJAhQ6DX6/HMM88AgOk5/hdffBHz5s2Dj4+PzfnZ1Fjr06cPfvjhB2zfvj3bcHfu3CmW243btm1Djx49MGjQIDbUiIio1DHO8WlLfMofb29vLFq0CJ9//jm2b9+Oa9euIT09HeXLl0fz5s1RubKVKSDzyabGmkajwcSJE6HT6eDkZGVeQlVAQABmzpxpS1Z5FhUVhU6dOqF8+fKYPn16keZNRERUJHgbtNgFBgaie/fuVrcdP34czs7OqFatmk155PrRwosXL1pd36pVq2wbakaDBg3KU7q2evfdd3H//n2MHTs202B1RERERIUtKioKGzdutDmdXF9Ze+aZZ3Du3DmbMyyKdG/cuIFFixbBxcUF4eHhGDJkCM6cOYNLly6hevXqGD9+PFq3bl2geRIRERU5Wwe25W3QbNWoUQM6nS7P8YQQSE5ORnR0NNq3b4+RI0faVI5cN9ZyM/BtfhRGuqtXr4YQAo6OjtizZw8+/fRT+Pv7Y9OmTejZsyfatWuHn376Cb169bIaPzU1FampqabPcXFxBV5GIiIiW3Fu0MLVoEEDLF261KY0cnquPzdyfRu0sL7Qwkh327ZtAIABAwbgvffeM02w+swzz2D69OkwGAwYPHiwaXThB02ZMgXe3t6mV0hISIGXkYiIyGacbqpQjRgxAlWqVMGOHTtw7tw5XL58GZcvX8bcuXPh5uaGDz/8EAcPHjStz/i6dOkSevTogXXr1tlcjlxfWYuKisLAgQML/ErY7du3CzQ9QN4GBYAKFSpk2ta7d2+MGTMGcXFxWLlyJd54441MYcaNG4fRo0ebPsfFxZkbbAaDOaCnr1zq09QV6r7R6+XS+BvwLmeOc/8/udSpV+60jnIZG2WRBIQ5H/HfeZmctxwFWUTL+kEj29pK8CNyfeRZUxwlqLqatxrn8hG5PqyeRV01tZojK0r1JlbXawd/mmWcwpb+Xm8AgMOnSyzWO3z1W3EUBwCg/0eWRdtalk2/fi4AwLBBjj0oGvxrDnxHHu/i5k35+aXhAABNkxcsE/XxM7+/K+No2vSV6f9ufZ45ceW0+UOdVnLp6i6XiTFyqR5v+j8XyI/t+5uiGG7I40xb6VEAgOLmZZm+epwrcRn+yPEKkNvUYxTuahxFK5eOcjgfkZJgTifqmizDP2Nkfj1Hyg0x6m/AR/29JCdmyFv9TannH2Gsj/FHlpos18eYzyeGA5tkiGD1wV7jH4bp8paGUuUxGef2FXN9DGo+aeptDwf195mh/AAA30Bk4i3/KFQCq8p0z+8HAGiadpLb75kHBjfuD3FXrlPKBMmlp0wDCVaGOjLW8Y76+6/dInMYUz3SLetRPlzGNZ4jkpPkMjbDd+nsKsMkyjsJioe3mpa6z6PkmJqGcwfNcdR9qgmtaZl/UqxcOqnPC+tSzNvio2U6V07IJMrJc6viJvMTsfI7VNx9TFGE8XyoN96OEsYNcuniquZjviNiiqvmp3iWkSsc1GPT+F07ZHjm+v4tuXzw+3VXz/XG4y7jRQbjd2YUGwWkp4FKh0aNGqFHjx5o1qyZxfpvv/0Wa9asQfv27bON/91332HcuHFo06aNTeXIdWMtPj4eCxYssCkzawrjyprxtqWXl1emba6urmjdujXWrVuHU6dOWY3v7Oxsdcw4IiKiksXW+T15ZS0nkyZNyrTu/v37OTbUADm8x759+2wuQ64baxERETZnVlQCAgJw7ty5LJ81Cw4OBlB4z+EREREVBT6zVjwcHR0RExOT44C3u3fvxsmTJ23OL9eNtZYtW9qcWVFp0KABdu7cmeUOMg7lYeu4J0RERPTw6dChA3r27ImVK1danRcdAA4fPozu3bsXSFvDpkFxS6qXX34Zs2bNwpYtW5Ceng4HB8tqXr58GRqNBi+99FLxFJCIiKggcOiOYvHxxx+jfv36qFq1Knr16oWGDRvC398faWlpuHr1Kv766y+sX78eer0en3zyic35lcrGWpMmTdCpUyesXbsWP//8M1599VXTtqioKPzxxx8YPHgwKlWqVGxlJCIishVvgxYPX19f7NixAz169MCsWbMy7UfjY1b/+9//LNog+ZXroTvszYIFC1C7dm2MGDECO3bsAADcu3cPr7zyCurXr48ZM2YUcwmJiIjIXoWEhGDnzp1Yvnw5OnToAH9/f2i1WgQEBKBjx47466+/8NlnnxVIXqXyyhoge2Ds2LED7733Hrp37w5nZ2f4+Pige/fuePvtt3M1RRYREVGJxtugxUpRFHTv3j3LuUGtPYqVH6W2sQYAPj4++Oabb/DNN98Ud1GIiIgKHidyL9EGDhyIRYsW2ZxOqW6sERERERW0nKaQ0ul0uHDhAlasWIG3334bderUsSk/NtaIiIjslKJRoNhwK9OWuA+zVq1a5apzhhACkydPxrJly2zKr0Aaa9u2bcPq1atx9+5d04SnERER2LdvH/r164fy5csXRDZERESUEW+DFpsyZcqgRo0a0Gq1mbbFx8fj9u3bqFKlSpbzkOeFTY01IQQGDRqEhQsXApAFN3rqqaegKAqaNWuGqVOnomvXrjYVlIiIiB6ggY0dDAqsJA8VZ2dnnD9/Ht7e3lmG6d27N/r27YsOHTrYnJ9NX9MXX3yBBQsWQFEUlCtXLlPrslWrVhg7dixefvll/PXXXzYVlIiIiKgk+OCDD7JtqAHA559/jq5du2Lnzp0252dTY+3777/H008/jcjISERGRlqdI+vpp5+GwWDAxx9/bEtWRERE9ADjoLi2vCjvxo8fn2OY4OBg+Pv74+2337Y5P5tug966dQt79+41NdKsfel6vR4AcOjQIVuyIiIiogdxnLUS6/Tp07h582bxP7NWqVKlHGecX7t2LQDA1dXVlqyIiIiISoQBAwZku/3evXvYunUrDAYD6tWrZ3N+NjXWGjdujPXr1+P555+3uv3AgQP45JNPoCgK2rRpY0tWJUPCPcDTw/w5/q7ldn06AEDokgEAijbz7hW6FIttQo2jePjKACmJclmmgjlS5Fm5dJP3x5WKcimiLlukrQRVN+fz33n5Ji1VbgurZ7VK+u0rTO+1LXpY3WZcr98wT35+brDVtPJKP2esTO/1z3Mdx+HTJQWSd26dqlIZABASLjvPeP6xP1MYbeveliuuyH3v+O1GAID+09dMm0RsLABAqS3H3NFPlvtSO17uW/2SKTJgQrw5vSR5TOgXqZMBp6dZL6yru+mtYd96tXCOAABNQLDMt3oTub5ms8z1eFJ2AhLn1Tq6eso46nalbCXr+QJQyofLuNdOyhVOznLpXVYuk+PMgWOi5dLDSy416rOuPuUs0hR3IzOkL78HEXNbfg6uJjeo+0Ic2CY/h9cyx//vigzrI8ugVH0cAKBfvxAAoFX3hbV6GX8/xnopHn6ZwpjC3rmm1uOB37sinzLR//6tzO+FYeY4B/+UQQLk71zcOCeX0TdlUnWfknE3/WBOz0P9/XvKc4Vhz+9yvZs8Jymu5nOTEt5QhlHzMdyQ9dE26yzzmSJvyxhc3cxx1HSN34dSvoosw85f5eeQqnL7tQvmMgWoPf3V85nhwmH50Xguib4u1587YM7nEbnfReQl+bmMTEOkJMiwl+UxpKnR0JyPet40xoGPv4zr4SPXq/MwKk7miwLi+in5xiDv7pjOvcbjzbh09zHnY/wJGc/txt+acQR6T39kcv8/NT31qaI0HZCuyxyusLA3aLFYuHAhFEUxHXtZCQsLw/fff29zfjY11j788EM8+eSTOHPmDDp3licBnU6Hs2fPYsWKFZgxYwaSk5Ph4eGBiRMn2lxYIiIiyoCNtWLTq1cvtG7dGhqN5eP/iqLA1dUVoaGhePzxx60O7ZFXNjXWgoODsXbtWvTo0QNjx46FEMLidqcQAuXLl8eKFStQvXr1bFIiIiIie6LT6fDll19iwYIFSE9PR3BwMD755BO0aNEiT+ncunULEyZMwJYtWyCEQKNGjTBt2jRUrFgx23jHjh3DlClT4Obmhvnz5xdKHlnx9fXFTz/9lK+4+WHzCCv169fHqVOnsHz5cgwdOhTPPPMM2rVrh379+mH+/Pm4cOECnnzyyYIoKxEREVlQzFfX8vNC/q6spaamokOHDvjpp5+wZcsWXLx4EcOHD0fbtm2xatWqXKdz+fJlNGjQADExMTh58iQuXLiAoKAgNGjQAGfPnrUaZ9++fejWrRvq1auH5cuXmzoyFmQeOcltD8+5c+fCYDDkK4+MCmQ4PAcHB3Tr1g1z5szB+vXr8ccff2DBggXo378/OxYQEREVFo3G9lc+jB07FhEREViwYIHp6lS3bt3QtWtX9O/fH5cvX84hBTlaRLdu3aDT6fDjjz/C1dUVWq0W06dPh4uLC7p37460tMzP6AYEBGDFihXo169foeWRkwULFuQqXNeuXfHpp5/mOf0H2dxY69SpU67C/f777+jRowc6d+6M77//PseWMBEREZU8V65cwTfffIOaNWuiUaNGFtv69u2LxMREjBs3Lsd0li1bhoMHD6Jbt25wdzd3kNJqtejZsyeOHTtm9fZmWFgYNBoNGjduXGh5FJSYmBj8+OOPNqdjc2Pt7NmzSEtLw7Zt27BixQps374d6enpFmGWLFmCl156CWXLlsWkSZNw9epVNG/eHDExMbZmT0RE9PCy5RZoPjsnrFixAunp6WjatGmmbcYG1Nq1a3H37t1M2zNaskT27reWTpMmstdwdj0pXVxcciyrrXkY7dixA40bN0blypVRuXJlXL161fQ+q1dQUBCqV69eIBenbJ7IPTY2FsHBwYiOjjatq1ChAn788Ue0bdsWAPDll18CkJdNg4ODMWnSJLz77rvo1KkTIiIibC0CERHRw6kYeoNu2LABAFC5cuVM2/z8/FChQgXcvHkTO3fuxIsvvmg1jaSkJGzdujXLdOrUkcMbHT58GLGxsVandspp9oWCyMOoefPmiIiIwFtvvYX58+dDURRcuXIl2/wBoGzZsvjuu+9yDJcTmxprp06dQnR0NNLS0uDn54fQ0FAIIXDx4kW88MIL2LNnDx599FHTA3zly5c3xR01apSpp2iPHj2yyoKIiIiyUgyNtcOH5Xh6wcHBVrf7+Pjg5s2bOHLkSJaNtdOnTyMlJSXLdIwD7gshcPTo0Tz3MC2MPNzc3PD999+jQoUKWLx4cbYXm4zDdwQEBOS53NbY1FgbN24catWqhS+++AJPPfWUaX1SUhJGjx6NKVOmYPny5UhOloPEZhxrpFy5cggMDMSiRYvYWCMiIipGcXFxFp+dnZ3h7OycKVxKSgoSEuQAxlnNYGS8QpXxjtuDMk7BZC2djFe5sksnO4WVx0cffYT79+8jNDQ0X+XKD5ueWdu5cyc2b95s0VADZOtz5syZOHLkCIQQEEJYHRTO09OTc4YSERHlVwH1Bg0JCYG3t7fpNWXKFKvZZXwOzc3NzWoY4yCxxqta+Ukn40Cz2aWTncLMY9asWbkOa7wSaQubrqy5urrC39/K9BsAEhISkJ6ebhpfxNoQHnFxcbh//74tRSAiInp4FdBt0OvXr8PLy8u02tpVNQBwcnIyvc9qqiWdTk635eeX9TRtOaVjTCOndLJTFHnkxGAwoF27dvm+OmhkU2MtNDQUM2fOxMiRIy3WX7hwAa+99hoeffRR0/glD16CjI6ORlRUVJaNPSIiIioaXl5eFo21rPj5+cHJyQk6nQ6JiYlWwxhHesju//fAwEDT+8TExEwP92ccLSK/7YSCyGPRokVYs2YN3nrrLYs5znMzhWZaWhp27NhRIBelbGqsjR49Gl27dsXcuXNRq5acQPnq1as4cuQIOnTogK1bt1pcSs3Y22Lx4sUAgIYNG2ZOmIiIiHJWxB0MtFotatasiSNHjiAyMtJqmKioKADAo48+mmU6tWvXNk2EHhkZmakhZUzDyckJjzzySJ7KWJB5jBgxAgkJCbh9+7ZFY+3XX3/FkSNHTJ+tXbkz5p1Tr9XcsKmx1rlzZ0yaNAkTJkywmLKhW7duWLJkCZYvX45BgwYBAPr3749u3bqhdevWcHBwwIcffghFUTBgwADbakBERPSwKobeoO3bt8eRI0dw8uTJTNuio6MRGxsLd3d3tGzZMss0fH190ahRI+zduxcnT57M1Fi6cOECAKBFixYWg9nmRUHkMXPmTNOVtYyGDh2KUaNGoXfv3ggICICjo2OmuDqdDtu3b8euXbvyVf6MbB5nbfz48ejRowc2bdoEnU6HJ554Ak888QQAoE+fPmjZsiWuXbuGZs2aITExEaNGjcL8+fMhhEC3bt3QpUsXmytBRERERWPgwIGYNm0atm/fnmnb7t27AQBdunSxeGbMmsGDB2Pv3r3Yvn07unbtajWdXr162VRWW/Po378/+vfvn2l97969sXXrVsydOzfb/A0GA8qWLZuPklsqkLlBq1SpguHDh2P06NGmhppRSEgImjVrBgBwd3fHvHnzcPLkSWzYsAFLly4tiOyJiIgeTsUwN2h4eDgGDx6M48ePW9wKBOQzXq6urpgwYYJpXUREBBo3boyvvvrKImzfvn1Rp04drFy50qI3pk6nw/Lly1G7dm306dMny3IYZ0vKboYAW/PIipubG95///0cw2k0Gvz99995Tv9BNl9Zy61Bgwbhhx9+AADUqFEDNWrUKKqsC46HH2DI0L3XoLdcauTuVLTGy6HqPez4jFNuyHXCFFcebCIpVv0se8/iwsEM+frIMJHnLMMkqePilAvLVFSlfLh8EyPvyRsObJLrA2VYJVjd/2m6THGNNBUtvyPtc4MzhdF/9Krc9tHCLNPJivb1z/McJyvpozub3jt8+QsA4O4TtQEALoHyOQX3tTvznG7Ni5dyDKOfPhwAoH37awCAuHFDlunNF2R5Zv+eOc4vstu3QT3RGQe20faW8+npZ48xhTWckd+741wZRz9DXo7Xf/22DFBG/astwzMTYu8O+aZxcwCA5vH2cv1FOVSO4T+1XkkJpjiauk/KN86y57bxGBHqsaj4llPzMw8uKf47L7cZjzcjRa2RevxByfAfgpq+tr96WyHR+sO3mkbPm/O5cVouY+S4SZqwurIeUVdkAOPJOuqmOQH1N6ZUfVx+PCn3iWHffrndf44sR8fXM2eu/sYMp+Qxo6nZzGoZZd7qbyhZ7kvD4b/UCqi3lzRyX5h+vwBEtPqsT2qSDNI0izmWb5nro9QOknHVfYBUeS7SNpG/S9PxAECJtd7zzHB8KwDzMWk8dgFAVJCTccNVDnEggqrItMpWkJ93bpb5Zfjd6j+WVxwMcTEybLCMI64cletPq/s6JdlcBr8r8k2Uug9qq+ezRPUcqO43cfOCuWyR8nhVguQo9Ip6DAm1noqn7MknYP4NKCE15bpz++QKh1T5WW2cKG7qw/SxUeZ8EtV6eJZREzHeIlSXxvN0WqopDnzNg70DgLh1ASI9FUWmGG6DAsD06dOxf/9+DB06FBs3boSvry9mz56N33//HUuWLLGYMeCLL77Avn37cOrUKYwYMcK03tHREUuXLkWrVq0wevRofPXVV9DpdBg8eDAMBgNWr15t9fai0d69ewEAR48eRUpKitXpp2zNIzu5fZZu9uzZpvZPfhXIlbXs6PV6REREmDoUEBERkX1zd3dHREQEmjRpggYNGiA8PBz//PMP9u/fn+l2Y8+ePeHp6YlXXnklUzq1a9fG7t27ERUVhfDwcNSrVw8+Pj44evQoqlevbjXvWbNmoUyZMqYG0PHjx+Hv7281/fzmURAKsv1j05U1vV6PKVOmYOnSpbh27ZpppgIiIiIqAgpsvLKW/6ienp6YOXMmZs6cmW243r17o3fv3lluDw8Px5o1a3Kd71tvvZXpgf+c5DWPnBR1+8emxtrw4cMxb968LAfGy6gguq4SERFRBsV0G/RhV9TtH5tugy5btgwA8OGHH+LatWtIS0uDwWDI9Nq/f3++7wkTERGRdYpGY/OL8q6o2z82XVnz8fGBm5sbPvroo2zDPf7442jfvr0tWRERERGVCEXd/rGpST1mzBgkJCRYzK+VlawmhSUiIqL8Usy3QvPzsuWhtYdYUbd/bGqsvfnmm+jZsyfmzJmTY9iM0zQQERFRAbCloWbr824PsaJu/9h0G3Tx4sVo1qwZvvvuOxgMBqsToaanp2PXrl24ffu2LVkRERERlQhF3f6xqbE2Y8YMHDt2DIB5cDprCmoiUyIiIsqAvUGLRVG3f2xqrH3wwQfo2rUrnnjiCVSqVAmOjo6ZCpWSkoJDhw6ZJkwlIiKiApLPKaMs4lOeFXX7x6bGWufOndGuXTv8+eef2YZLSUlBuXLlbMmKiIiIqEQo6vaPzU3qyZMnmyZTtebIkSPQaDRYuXKlrVkRERFRRuxgUGxyav8AgIuLS4G0f2xurD3++ONwcMj6Ap2npyeeeuop1K9f39asiIiIKCM21orNpEmTsm3/GOl0OvTo0QOdO3fG999/D71en+e8bLoNCgD37t3Dzp07ERsbC4PBYLHNYDAgOjoaR44cQd++fXO8XEhERERkD86ePYu0tDTs2rULt27dQvny5dG0aVOLBtySJUvQr18/vP766xg2bBiWLl2K5s2bY+PGjfDx8cl1XjY11vbv34/27dsjNjY223BCCBw6dMiWrIiIiOhB7A1abGJjYxEcHIzo6GjTugoVKuDHH39E27ZtAQBffvklAGDs2LEIDg7GpEmT8O6776JTp06IiIjIdV42NdY+/vhjJCQkoGXLlggODsY///yDdu3aWYTZtGkTunTpgr59+9qSFRERET2IvUGLxalTpxAdHY20tDT4+fkhNDQUQghcvHgRL7zwAvbs2YNHH30UZ8+eBQCUL1/eFHfUqFEoX748VqxYgR49euQqP5saa/v27cPmzZvRqlUrAMCnn36Kli1b4sknnzSFWbBgAbZt24YmTZrYklXJkBgDuLuaPzs6y6UQcpmepm4QluvTUs1x0uTUFIqrh/zsrKbnLXuLiP/Oy+1VHzdFEbdkt18lqBoAwHBqp/zsoE4Om3BPLj38zPncvSHjqremFW9/Na3LMo1LRy3WWyNSkmTYee/JsE8+K9cf3m4Ko/1oIQBAP2WI/DxurkUa+gUfm8P2nwAASBvcAQCgefwxuX7IZABA+vDnAQAOX6/PskxG6W++IMPO/l2meeOOaZvxoC6z+0SO6RjdaVwLABCw92Su4xhp3/4aAJDStzUA4OLOKwCAWpcuZQob105+r+4t6gEAHL/daLE9/cN+AADF2dm0LubINQCA79td5bZmLeWG44flsuojchl5PUOhtHJ5ZB8AQJ8QJ1e/NFymkSQ/w6uMKYqIVMurHpPimPyrT1P3Kfn5xmkZN0N5lfLhlhU0qA/bpspjB+XCZLhY86CQmvB6skxbl8syPW75B57+J3k8aPuON680Huvx8iq+SFKv5ju6yKWnt1yeP2OO4x8gi3T0bxknOlKWxVHum+R5iwAAbiFVzWV77Gn5JjHWYmlMQ/No5pHIjenCoD6HkpYi1/8nvzfo5GfDmf3mSOq5Qmz5Tdb5qvzdm743Vze5/bT5eFRq1JNB2spjRL92tlwa99fw6ZnKpv9lltzW+S35+csRAIDIV4cBAMo+Xc+cvp96LvhPnjsMF9R9afzP3L+sLProzub078njyMHJSZZXLb+4dk4GuH9XLn3Nxxni78tl1H8y7E15fhPJCXK9k/qdGjI81+Mmz5ciMUaWtYL6nd1Ryxol97WmTvNM+0Co+994HlaMx7y7j1x6Z+ipl5qsvlEsFuayiEzpm/K5o37fika+igqvrBWLcePGoVatWvjiiy/w1FNPmdYnJSVh9OjRmDJlCpYvX47kZHlMaY2/bQDlypVDYGAgFi1alOvGmk1HlIeHh6mhBgADBgzADz/8YBGmb9++WLduHWbPnm1LVkREREQlws6dO7F582aLhhoAuLm5YebMmThy5AiEEBBCWDTUjDw9PfP0eJhNjTVvb2+Le7Xly5eHEAKHDx82Z6DRwMHBAdOnZ/6rj4iIiGzA3qDFwtXV1eoUUwCQkJCA9PR0U6dLV1fXTGHi4uJw//79XOdnU2PtmWeeQePGjdG/f3/TlbNx48aha9eu2LhxI06cOIGBAwfi3r17iI+PtyUrIiIiepDxmTVbXpRnoaGhmDlzZqb1Fy5cQLdu3fDoo48iLU0+7vBgr8/o6GhERUXB29s71/nZ9Mzau+++iw0bNmDRokVYvnw5Xn/9ddSoUQOvv/46nn/+eYupFzp37pxNSkRERET2YfTo0ejatSvmzp2LWrXkM89Xr17FkSNH0KFDB2zduhVTpkwxhY+NjTU1zhYvXgwAaNiwYa7zs6mx5uXlhX379uHPP/9ESEiI6b7smDFj4OPjY5qNvn379nj//fdtyYqIiIgepMDGDgYFVpKHSufOnTFp0iRMmDDB1OMTALp164YlS5Zg+fLlGDRoEACgf//+6NatG1q3bg0HBwd8+OGHUBQFAwYMyHV+NjXWoqKisHHjRrz44osoU6aMxbaBAwdi4MCBtiRPRERE2WFv0GIzfvx49OjRA5s2bYJOp8MTTzyBJ554AgDQp08ftGzZEteuXUOzZs2QmJiIUaNGYf78+RBCoFu3bujSpUuu87KpsdauXTucPHkSvXv3Nl3WK8nWr1+PF154AQsWLMCrr75a3MUhIiIiO1alShUMHz7c6raQkBCEhIQAANzd3TFv3jyMHj0aly9fxtNPP52nfGxqrBl7gr744ou2JFMkoqOj8dprrxV3MYiIiAoOr6yVWKtWrYLBYLAYS61GjRqoUaNGntOyqRvIzJkz4efnh44dO+YYNjw8PMcwhWnYsGFISEgo1jIQEREVKMXGnqBFOYDvQ6ZTp05488038eOPP9qclk3fUvfu3fHLL7/gjTfesHjALqOUlBTMnz8fl6yM5l5UlixZgqioKHTq1KnYykBERESlQ3p6Oj744AM8/vjjqFq1KipXrmzxqlSpEvz9/REdHY1x48bZnJ9Nt0G9vb1NV6vmz59vc2EKw82bNzF+/Hhs3boVH3/8cc4RiIiI7AVvgxaLSZMm4dNPP81V2IwzPeWXTVfWXnvtNdN0Cjm9isuAAQMwYcIEhIWFFVsZiIiICgVnMCgWy5cvx/PPP4+tW7fi/Pnz6NixIw4ePIjLly/j8uXLuHTpErp27Yrff/8dK1assDk/mxprI0eOhJ+fH86dO4e0tDQYDIZML71ej+3bt1sMkFtUvv32W7i6uuZpLBMiIiK7YZw43pYX5dnt27excuVKtGjRAlWqVMHgwYOxfft2hIaGIjQ0FJUqVcLkyZMxYMAAXL161eb8bPqWgoOD8cYbb6Bq1apWJyoFAEVR8OSTTxb5DAYXLlzAtGnTMG/evDzHTU1NRVxcnMWLiIiICAAqVqwIFxcX0+cOHTpgw4YNpimmAKBq1apwcXHB66+/bnN+Njepc/sc2MqVK23NKtcMBgNeeeUVzJw5E2XLls1z/ClTpsDb29v0Mo6TQkREVKJoFNtflGdly5bFF198gatXr0Kn00FRFHTt2hX/+9//TGGOHj2KyMhIbNu2zeb8bOpgUFJNnToVNWrUyPf4b+PGjcPo0aNNn+Pi4mSDLU0HGJzNAQ0GufQpZxFfRMqesYq7j1yhybCbHZ3kskywZaZ3b8plkpUJ7zUPfE0piXLpHyTzS7gv8/PwM5dBny7fxNyWSydZbiW0ptx+YIv8XKm2Oc7ZPbJa5w7LbRWqyGXDp2QxajaTAY1LAPpVXwIAtOPmys8rv5Cfu4+RAarVyVQdx3l/ZK4jAKFLz7QuqqEsr39vOYCgduRMAIDD7N8twrmu3GF6f7RiJQDAo9euWM3HKL59A9P7gL0nLbYdDAoFAPj5yf0WduJclumkv90VAODy0z8AgM1ucjaPSp3kfnKu6G8K67XlIAAg8aWmAAD3B9JymCgHl05/8wXTujvRyQAA17M35LJuLABAJMrjwKGDnCkkfYT5eBdpcl9qwqvKz9v+BgDoTx0DACgv9JLb6z5limM4s1u+iZHjJyqBFS3Wa2o8oW6PMueTmiTDlpPPhCpeATKfo1sBAFoPXxkw42MQvoFyW7VGsEbbd7zMd9960zolsJJ84+Ujl7oUud7BUa2vTi7VsR8BQPHwkOV+tI3cdk1+x5E75UPBZ27I31qbx8yDUxpObJdhj8vfAsrLfaBt+LKs17+rZdr+Fcz7YO9fMp82cjRyoVHvMhw9ION+KLvt6795J1Nd9dcjZZhg9Q9Cf7lvEC+v5usu3jSFdd7yq4yzeZ3MJ16WX6kqv+PIxx8xhS3bRv7ulErye9F/NlQtrHx+WBjkMvXkFVMcl9BQ9Y0rACBq/m8AAJ8weTw7d30JABCzy9zzPyZW7vewmtUs4hq/b3Hjuvx46z9THHFD3hLSHTsDAHAybqhnOU+iEAbTe+P3L6KuyRUJMXLppc6cc1qesxBWyxw/4Z4aNtYiXbh5yqV67IqYW+Ztxu9OPb5Mn53VKyhpqXKpzfxfpxIgjxUReRbQZz6XFRpbb2XyNmi+jBs3Dm3btsX//vc/lC9fHteuXcPAgQPRpEkTNGrUCBUrVsSff/4Jg8GASpUq2ZxfqWusHTt2DAsXLsT+/fvznYazszOcnZ1zDkhEREQPnaeeego//fQTpk2bhvDwcGg0stG7cuVKtG/fHgcOyD/WPD09MXPmTJvzK3WNtVmzZuHs2bPw8vLKMkz//v3Rv39/vPLKK1i4cGHRFY6IiKggceiOYtOrVy/06tXLYl1YWBiOHz+Ov/76CwaDAU888QT8/f2zSCH3Sl1jrWzZsqhevbrVbf/99x/i4uIQGBgIb29vlC9fvohLR0REVICMMxHYEp+ydfjwYdSvXz/X4Z2dnfHcc8/lO741pa6xNmXKFEyZMsXqtldffRWLFi3ClClTOJE7ERER5eiFF17AjRs38h2/Y8eOuHbtmk1lYJOaiIjIXnFQ3EIXGRmJv//+O19xd+7cicjISJvLUOqurBERET002Bu0SDz99NPw8fGBu/uDffizlpKSgrt37xZI/mysEREREeXg/v37uH//fp7jFcQMTg9VY23hwoXs/UlERKWHAht7gxZYSUqtQYMG4eeff0ZKSgqefPJJ9O3bF05OTjnGS0xMxPr16/Hnn3/aXIaHqrFGRERUqrA3aKGbN28eJk+ejK+//hrffvstPvroI7z55psYOnQofHx8so372muvwdfX1+Yy8FsiIiKyV+xgUCT8/f3x0Ucf4dq1a5gwYQIWL16MihUrYuTIkdlO1O7o6JhpLLb8YGONiIiIKBecnZ0xePBgnDp1CkuXLsXRo0cRHh6OHj164ODBg1bjzJs3z+Z82VgjIiKyV8beoLa8KF+ef/55REREYPfu3dBqtXjiiSfQqlUrbNiwocDz4rdERERkrxQF0Njw4m1Qmz3++ONYunQpLl68iAYNGqB3796oWbMm5s+fD51OVyB5sLFGREREZKOQkBC89957GDx4MM6cOYPBgwcjNDQUkyZNsjlt9gYlIiKyVxwUt0S4evUqvvzyS/z4449ISkoCAAghEBQUhKpVq9qcPhtrRERE9srWHp28DWqTw4cPY9q0aVi9ejX0ej2EEACA9u3b45133kHr1q0LJB821vJC6wCoXwSAzAd5Yoy6Xv1LRaNVlxn+ctGnAwDErQvyc2qyjBJaR35OT5Xb75gnfVUcXeSbe3J+MZEYKz+nJMrt/hXkZ0dncz46mS68/S3yMeavCa8vPztkOATUsEqlR+TSU44NI+LuyeXV45ZlBQA3D1jwD5TZrPpSfk6IN1f9wA75JlktS8NmAABtm76yTI9Ul+EmDjDFKbf/lFy3fq5czh0vN/iWAQCcefcbAEBwRU9TnJrPyPIn92gh4yTJZwZcKpeTVZ71KwDA888DpjgnK1eW6QTL+jweadkVW//pawCA+D/2mNZduSLrVv3JUABAygtNZD3Uw8KQLPON2XvBFEf9NuAcZH3cnVNVZDmqv/miaV0Zv4sy/TsyP49+71uWbc5Y+SbDd6kYx/7xkPvFECePFY1WPSbv3JRxd6wyJ3T+pIxbrykA8/duZDxmFQfzcaaUC5Pbrp2QnyvWlksXOSWLSEmQAY3HMAAkqiOAB1SUy7tygmSRLMMqwTXUuInmOGp5jb8/w/nD8rPx+HN0UuOYnw8xjhqu/3OB/FyhCgDA1VXupzbW9oHxd1JO/U1dVI+/e7MAANrOb8n8d601x1HLJO5FyWW0Og9gJfldJr74BADApWFNU5SUQ2cAAM6V5e9FnJb5JB6Qx6ZHu0Zye70apjiJ22Sd3R4Pl0W9+J8Moz4Tc+dOsims93lZNxdP9XcRJOsTv3BtxiJD45Lh96/Xy6U6Pc6NSLn/Pbzld2dYvFKmkZBmjpJuAABEr9oKAAjo0E2mf2AbAEB5vDEAQLfCvI8dQ+Tv0DG0vAyrng+US2dlgLg4uQwoay5bXXk8Gc9JhpN7Zfkfl/8Rihvq+TLN/P2LOFkPoZflVdRjxHgsinQrzxIp6u9DyHqJFHmFRHF2lesd1DQM+sxxjUkEVYdirAOVWps3b8a0adPwzz//AJBX0RwdHdGzZ0+8/fbbqF27doHmx8YaERGRveJt0CKj1+uxbNkyTJ8+HcePy4sXQgh4e3tj8ODBeOuttxAUFFQoebOxRkREZK+MvTptiU/ZSkxMxLx58zBz5kzcuHHDdKszJCQEI0eOxGuvvQYPD48s4z/33HM2D+fBxhoRERFRFoKDgxEXF2dqpNWvXx9vv/02unfvDq3x0ZIsJCYmYtu2bTaXgY01IiIie8UOBoUuNjYWiqJAURQ0a9YMbdu2xfnz5/Hpp59mGy8lJQURERFITk7ONlxusLFGRERkr/jMWpHw8fFBy5Yt4e3tjcuXL+cqTmJiIm7cuFEg+bOxRkREZK/4zFqhUxQFe/fuzdd4abdu3UJoaKjNZWCTmoiIiCgLYWFh+R7YNjAwEJXVoaFswStrRERE9kpRbLwNyitrOblw4ULOgbJx+vRpm8vAxhoREZG9YgeDhwJvgxIRERGVYLyyRkREZK/YG/ShwMYaERGRvWJv0IcCm9REREREJRivrBEREdkr3gZ9KPBbIiIislfG3qC2vKhAnTlzBmPHjsXOnTsLLE1eWSMiIiLKwsSJE03vmzRpgqeffjrb8DVq1MCwYcPw2muv4cyZM+jatStmzJhhUxnYWMsTATg6mT96+Flu1qmTtSbGyaWbl4yVGGMOY9CrS4OapMEiCcXRRb7xC8qce5Scj0xx95bLsiFyQ0qSmlSGtLTqV6tPl0tXDxlHo5Vh3Twtw2WUqtbD2U3GUeuB9DRZ9H3rzWFd3WU2m35QK6D+labVqoUW5rD378ulu4yDsydk3BOjZNQmrQEAujmzzHFWfSmX8XKfxiz8DQDg06MtAMDLU34fLhX9TVFEutzHuv9iZLoOsiyGBFmvzQFy3wZ7uZjiODrIi8y6VBl3fZnyAICnX6wNANAE+AIAPJ54xBQnKFWW3zFQHgdpR68AAE4nyf3kWqsiAODKmkPmsjWuBQBwKy+/w/hmdQAAWjdZj2qdHpNlPXvOFMfV0xkA4ODnDqv8AmT+N3aZVjmUSZF1r1pNlt9b/f7LlpX5te4NANAb9y+Q+btTv284u8qlRj1W1GMIAHAvUtYrXv1ub19R81GPTY168T4txRxH62i1GkpwDYvPmvDHTO/FvVvyjfEYT9PJOH7yexJ3b8vPDhnKlqaW//xJGSZapuFcTu77feXl9/N4xn1w8Yxc+paRS+Pv/Zr87RmPfU3TTqYo+lOH1PTlvkBcjPx8Sh4fxu9NpJj3gaKV+zrx0EUAgGsl+R3evB4PAKgWHS0DOpnPN8mxMr67q/w+9u68AgCoXUnu+8BybqawCTfkOpEu63724F8AAE8Pue+P3JH5dG5Z3RQn6fetsmyOch/q1H1951YCAOD87UQAQNuBzU1xEvedBQBoPeRvSaxdLJfqxNVK3fpyH3iZy5Z2VX4PWk9ZD42XelyXKwcAMFy7Ltf7+priiBSZN26p8yyq3x2M6/3l/st4bIpYuQ8Vf/l7VzyM6annJNP50nxlSXFQj031vKU4mcst46RnimMSd0dGTU2GiI/PvL2waDTm31l+41O2PvroIzRr1gyzZs3CY489lnMEAJUqVcKff/6J3r1746uvvrK5scZviYiIyG7ZeguUt0Fz46effrJoqL355psoX748tFotnJ2d0bFjR4wfP94ijkajwaxZsx5MKl94ZY2IiMhesYNBoXN1dUWlSpUs1s2ePRtDhw5FnTp1sHLlSnTs2NFq3LJly6KcetXYFvyWiIiIiLLg7OxsdX2tWrXg4+OTZUPNyN09i0dY8oBX1oiIiOwV5wYtVrm5aqYUwD7mlTUiIiJ7ZexgYMsrn3Q6HT777DNUr14dVapUQcuWLbF9+/Y8p3Pr1i0MGTIElStXRlhYGHr06IFr165lG2f16tVo2LAhKleujLp16+KHH37IMZ+33noLiqJkes2ZMyfPZTYqiIZYbrCxRkRERHmSmpqKDh064KeffsKWLVtw8eJFDB8+HG3btsWqVatync7ly5fRoEEDxMTE4OTJk7hw4QKCgoLQoEEDnD171mqc8ePHo3///pg+fTouXbqElStXYvz48RgxYkSW+URHR1tt0JUpUwavvvpqrsubH3q93uY0eBuUiIjIXhXTbdCxY8ciIiICe/fuRcWKciiVbt26Ye3atejfvz8aNGiAsLCwbNPQ6/Xo1q0bdDodfvzxR7iqw9JMnz4da9asQffu3XHgwAE4OpqH+1m3bh2mTJmCzz//HC1btgQgxzWbNGkShgwZgieffBLdu3fPlNfMmTMxdOhQvPbaaxbrPTw84Obmlil8RmlpaYiIiIDIOBSVKikpKcttBoMB586dy/EqYW6wsUZERGSvFMXG3qB5b6xduXIF33zzDWrWrIlGjRpZbOvbty+WLVuGcePGYfny5dmms2zZMhw8eBCvv/66xUP4Wq0WPXv2xNSpUzF//nwMHToUgGz8/O9//4OiKJmuhvXq1Quvv/46Ro8ejS5dukCrNY+5Fx8fj4ULF+Lo0aMoU6ZMnuubmJiItm3bZrk9u20FhbdBiYiIKNdWrFiB9PR0NG3aNNO2xo0bAwDWrl2Lu3fvZpvOkiVLAMBqOk2aNAEAfP/996Z1+/fvx/nz51GlShWUVQf4NvLw8ECtWrVw8+ZNbNy40WLbnDlz4OXlhc2bNyMqKioXNcxMCJHvV0FgY42IiMheFcPcoBs2bAAAVK5cOdM2Pz8/VKhQATqdLtu5MZOSkrB169Ys06lTR87ucvjwYcTGxuaYb8Y4ERERpnUpKSmYMWMGTp8+jV69eiE4OBidOnXK8nk4ax555BFcvHgR6enpMBgMuX6lpaXhypUrePTRR3OdV1bYWCMiIrJXxkFxbXnl0eHDhwEAwcHBVrf7+PgAAI4cOZJlGqdPn0aKOgWbtXSMaQghcPTo0Xznu2vXLlSsWBGhoaEAgPT0dKxbtw716tXDsmXLsixfRl26dEFYWBg0eew5q9VqUbFixQLpwMDGGhER0UMuLi7O4pWammo1XEpKChIS5HyxxsbRg7y95fy70cY5bq24c+eO6b21dIxpZEzHGCcv+bZu3Rr79u3DlStXcO3aNXzwwQdwcXFBSkoK+vbtiy1btmRZRqOXX345xzDZKYjeoGysERER2SuNYvsLQEhICLy9vU2vKVOmWM0u43NoWfWiNF6BMl45y086Ga9iGdMxxslvviEhIZg4cSIOHjyIcuXKQa/X44033sjxubKaNWtmuz07BoMBH3zwQb7jG7E3KBERkb0qoLlBr1+/Di8vL9PqrKZYcnJyMr3PqpGj0+kAyOfXspJTOsY0MqZjjGNLvoBsfG3cuBENGzbE+fPncfDgQTRo0CDL8GfPnkX16tWzTTMrmzZtQnJycr7iZsQra0RERPaqgDoYeHl5Wbyyaqz5+fmZGk2JiYlWw8TExAAA/P39syx2YGCg6b21dIxpZEzHGMeWfI0ee+wx9OzZEwBw8eLFbMM2bNgwx/Ss0el0eOedd/IV90FsrBEREVGuaLVa023ByMhIq2GMw2Nk1wuydu3apqmarKVjTMPJyQmPPPIIAKBu3bo255uRcXw0Dw+PbMMlJCRg/fr1uUozo1dffRVnzpzJczxreBs0L4SwvNwcr95z16q70XiP3Vtt1RsMcqmYB+eDRn3QUKOuM3abjrd8EFPcuWqZLwDFmE9wNbnUqZdW9Wky2MWjpihKWG11m3opWZ8ulw7qX0sOThZxLcIYuXtbhDFcOSmLXiHcXLS7t+Ry1za57dmu8rMxQMx9c3rGQQrVS8K6A8cBAE6PyG7Yho2rZdG8MzyPcEPdD+oI1t6PV5Lp37gBAEjXy33s8Owzpigpy38BAJw7HwMAqN1KjqKdeuMeAKDN8PYAgJM/mrt3e3rI/REbJ/fX7TR1X2ge6NaeYP6LTqNuS7spvzv3p+X4Qk8dlieSuN2ya7iLi/n796ou/zKMOiLLv+e6LGOH+kEAAKVyFQBA4vJNpjjz9t8EALxSR04YfDpI9mqqN7azDOAgjwsHX/MJ59auSwCAoBry0n3KGZmfq3qbQ/9xfxmwXoa/GH3lPlB85PhFIu6B49t4nBkeOE4AKC7qgJbGbU4ucqlTnx1x9TQHTk2SyUUslcnXlaOQI/q6TOLCEZlmxWrm9L3kQJbinNwGR/V2yE31L+LL5+XSP8OAl9XU50yOyx5kCJQ9yFz6ytHNH++gjrd097Y5jhoG19R0ndV6xMfLpVoO/dLPzXHi4yzKZDxmdBfkPte4yvXpV83/wThVlfmk3T4FAEi5Lvd15aaVZL0S5W/EcDfOFCcuXh6b7vtPAwAqlpG/E61Wnnc8awaZwl7aJsvv6m2+lQQA8QnyO0xSz03X/jpt3qamb9DLX2+1UC+L9N3uJhsTMcVJT5Hf95YjlwEAL9WS5U89I0dsN16bUTzNA54mHpXbfJ6U/wHD+PD1Pfn71MfLfDRp5nOTop6vhPF8eU8+aC4c1e/HQz2+HMz/pSnl5O9EMR6LBjUf47nPeL7WZ7ilZjwvq9tEivy9K8LNMg1Nhv86E2PUDGXZlICKUJzN31uhK6DboHnRvn17HDlyBCdPnsy0LTo6GrGxsXB3dzfNMGCNr68vGjVqhL179+LkyZOmBpnRhQsXAAAtWrQwDZjbvn17zJw502q+GeM8++yzuapH+fLlodVqc3XlbMSIEWjWrBl8fX1zlfZbb72FFStW5CpsbvDKGhERkZ2yNjF5Xl95NXDgQGg0GquTtu/evRuAHO4i43Np1gwePBgAsk2nV69epnVt27ZFWFgYTp8+bdGbFJC3QE+fPo2wsDDTgLo5OXHiBHr06JFpgF1rrly5gk6dOmXZSzajsWPH4uuvvy6wAXEBNtaIiIgoD8LDwzF48GAcP34801hqixYtgqurKyZMmGBaFxERgcaNG+Orr76yCNu3b1/UqVMHK1eutOjBqdPpsHz5ctSuXRt9+vQxrXdwcMCUKVNgMBhMsx8Y/fzzzzAYDPj0008tpppKSkqy+oB/bGws1q1bhy+//DLH+mo0Gnz22WdITk7GSy+9ZNH54UEffvghpk2bBgDo06cP1q1bZ1Ge/GJjjYiIyF4Vw6C4gJxs/fHHH8fQoUNx7949CCHw1Vdf4ffff8fixYstZhn44osvsG/fPrz33nsWaTg6OmLp0qVIT0/H6NGjkZ6ejqSkJAwYMAAGgwGrV6+2mMQdAHr06IEhQ4Zg0qRJOHbsGABgx44deO+99zBq1ChTpwFAjm8WHByM8uXL49tvv0Waemv95MmTGDNmDBYtWoRy5crlWNdGjRrhf//7H/7991+4ubnhxRdftNpgmzRpEiZNmgRFUfDKK69g8eLFePHFF7McBiUv2FgjIiKyV8XUWHN3d0dERASaNGmCBg0aIDw8HP/88w/279+Prl27WoTt2bMnPD098corr2RKp3bt2ti9ezeioqIQHh6OevXqwcfHB0ePHs1yuIxvv/0WH330EV5++WVUqVIFY8eOxeLFizNdJdNqtfjkk08QEBCAUaNGoUqVKujTpw/27t2L7777Lstpqx60a9cuALJxuXLlSri6uqJTp06mxh8ATJ06FR9++CEURUHXrl0xf/5807YxY8bkKp/ssIMBERER5ZmnpydmzpyJmTNnZhuud+/e6N27d5bbw8PDsWbNmlznqygKhg8fjuHDh+cY9o033sAbb7yR67RzotVqsWLFCjz77LPo1q0bVq9eja+//hrvvvsuANm5YenSpfl6FjA7vLJGRERkrxQbZy8o4EZFafTgFTsnJyesW7cO169fR6NGjUxXzlq3bo01a9ZkekYtN8/F5aRUN9aEEJg7dy4effRRuLi4wM/PDx07dsSBAweKu2hERES2K6bboA8Ta8+ceXh4YOPGjYiJiYEQAk888QR+/fXXTD1ghRAF8sxaqb4NOmTIEHz//fcA5KXL+/fv47fffsOmTZuwfPlydO7cuZhLSEREZAPFxqtjvLKWo7t37+L9999Hr1694OLiYrFtzpw5GDVqFGbPnm0alNcoOTkZq1atwj11DEFblNrG2qZNm7B27VosWrQInTp1gqurKzZs2IDXXnsNd+7cQf/+/dGiRYtcTUtBRERED68pU6Zke4Usv1NS5VapbawtXLgQW7ZsQb169UzrOnbsCA8PD7Rt2xZxcXH47bffMGDAgOIrJBERkS0UxcYZDHhlLTdsGeC2IDoblNrGWvPmzS0aakZt2rRB/fr1cfjw4UwjIBMREdkV3gYtEpMnT8ZLL70EV1fXXMdJTk7G6tWrLQYIzq9S21jLrktveHg4Dh8+jNDQ0CIsEREREdkbf39/09AcefX+++/nOLRJbpTaxlp2oqOj4ezsjA4dOhR3UYiIiPKvGCZyf9h8/PHHNsX/5JNPbC7DQ9dYS0pKwu7duzFo0CD4+PhYDZOammoxWWtcXFwRlY6IiCgPjOOl2RKfspWWlmaa1zQ0NBQdO3bMU/xhw4bZXIaHrkn9ww8/wNPTExMnTswyzJQpU+Dt7W16hYSEFGEJiYiIqKQYOXIk5s6di4YNG+KFF14oljI8VI21u3fv4tNPP8WiRYvg5+eXZbhx48YhNjbW9Lp+/XoRlpKIiCiXOChukVizZg2eeOIJaDTFs78eqtugr732Gt55550cn1VzdnaGs7Nz5g16PaA3T9wKjTqlhEEvl47qYHmpyRbrFYcMIxo7OAIAhMGghkkxpw1ApMSraWf4aoy9dRxlLxRFjStSEuR6Ny/5+c4Nc5TUJPnG1VN+DqgoP9+LVMuobnfMUDZjmVw9Hqh3uixS5boyn4QY8zYPb5l+u+flZ09fuYy/L5dVHzGHvaXmHRgEAHB6pLZM7/gRmYabm9zu7m6O4yj3F5zU78NTrY+vzCfoMXnVM239BlOU/87KXr5121eT1UpVvzN1P4qo2zJueXM+u8/LQQvrBsl92aiM3Ae62/IWuEvZMvJzlLnu567IbQ1qVQAA6M9eBADU9Jb1OHxe7oPalbxNcXRRsXLbTblsEuIDANC4qMfFmdMAALcaQaY4rc7LPM9dlfkdTJDHV90zZ2Xc8oHqPjHn4189AACQun2fLFuyTqYfL48vpXx5GfD6JVMcBAbLMHF35WetLJOp27n6GWnmRwQUF7kPhTZRfnaW+80Qc1l+dlS/N4cUcz5psizGY08Yfz/GNCvVlOujrpjXeZWxiIOom5afVYZI86CU2ppqntVlekhSfy+u8vtRHm8u80lOMCeQrh4rWvX3FxtjkYaIVPeXl485zj21V/mlM3IZWlWmr95e0nrI80Ly2f9MURyCywEANG5y/7jWlp2dYnfKNLzqyd+rxt18HgqqUVamc0seO4FV5T5JvCWPC23VMHOZtsljMeG+PFaup8jvzEH9Lu+nyd96uWoBpijKeVmPMoHq798ghyowHotlooznDPO5KSFB7q8QZyfjCgCAy2M15C5Zuh0AENa2himOcQQEpYL83YjzF+SKAFkWB2Mvfa05HxGnDiqalKiWQc3PeAuvnEwLzm7mfXBPPRb8ylmkoXGwPO4UNx9zPkkxavrqudZ4zD9wjMKQnuGDsAxzLxKIi0eRYW/QQhcYGIgaNWrkHLAQPTRN6smTJ6NixYp4++23i7soREREZCc8PDxyDpSNKlWq2FyGh+LK2k8//YSzZ89i4cKFxV0UIiKigsPeoCXarVu3cOPGjZwD5qDUN9Z++eUX/Prrr1i+fHmmUYT1ej0iIyPZgYCIiOwTb4MWulu3bqFfv355jpeUlIS9e/ciPT0958A5KNWNtXXr1mHRokVYuXIlHBwsq3rr1i288847GDRoEBtrRERkn3hlrdAlJCRgyZIleZ5ySlEUCCE43VR2lixZgldffRUeHh6ooD7IaqTT6RAfH4+QkBAsXry4mEpIREREJZ2npyc6d+6c53gJCQnYuXMnoqKicg6cg1LZWNuwYQP69u0LIQRiYmKyDNezZ88CafESEREVC41GvmyJT9kqW7YsFixYkK+4kZGRqFSpks1lKJWNteeeew4G4zAUREREpZSiKDZddOAFi5zZso+CgoIKpDcom9REREREWbB1ysnTp0/bXAY21oiIiOyVotg4gwGvrOXkzp07OHLkSLGWgY01IiIie2UcusOWF2VLCIFnnnkG8+bNw9WrV4ulDKXymTUiIiKighAREWF6HxMTg9DQ0CIvAxtrREREdsvWydh5gy0nLVu2LO4isLFGRERktziDQaF77733sG7dOlSqVAl16tRB/fr1Ub9+fVSrVq3IysDGGhEREVEWvvrqKyQmJuL06dPYtGkTADm5e7NmzUyfCxsba0RERPaKg+IWuh9++AEREREIDAxE7dq1Ua9ePVStWrVIy8DGWl44OQN6feb1XgFyefcGAEBxcJKfnV3lMuMAvelp6rpUGdbN2yIpxdkDACDSU83rtI7qG/VH5Sg/K+4+Mmz8XQCApmxFUxyRFKeWRY0bo0534RcklykJmcqmePnLuDfOqeV3Uzeol8n16mS08ffNcdxl+UXMHbmMvGQZ9v5dc+UqyDlYxZlTMm5wsFz6+FiWJaCcOc7tWzLOtWsybNmyFp8dqsg6px4/b4ri4y33v8MTjdQy3JNxT55DRmnpmQdOrvBsPbntmsz31vH/AAAhYTJfBy83U1gPZy0A4MxfMt2qDWV9wmrK48HreiwAoMyT1TNkKr//epHxFmXQuMkyK+Hhsj7/7DFFqd0qDACQeDkaAPBE15fk5407AQDuleV2cSPSFMepphyEUUTLOM7tW8n8duwGADi2e1YGvJBh/J/UZLl0dJbLJFlGeMvjAgb1O9WnmaII43fm6ik/J8h9rfGX+0LE3JbbjccwAGGQvyFN+cqyzup/FiI1UQZQjy/FN8NxoB7HSlhNGdZF/W3dlt+P0uIZmebt2+Y4HrJM8PKRy6sXZdhgdd/8d0Wu9/E3x3FyUeujfs9h8vswHcc31Z5gzs7mOMZzQo16cnniAADAsZp8CNl4fLukmc8dxnUOXmp+bjI/j3BZZ01DeeyK82dNcZy9ZH1unpJ1dE2W6ZVvV1sGcHExhQ0sL9Nzq1Zehrkpf+/hleXvtdxl9fyQ4f9pby95DGqc5b5OuaueI87L30LFcD/52dPTFCegujzWg5rKdcbj13jcVWykPoidoUHg4KC+T0mRSw93GffRJ+TnZHkcKg0zPCeklf9VCY38zSFRPTbVCihl1POayPCbVo8zUxj1vCxS5HGmeJVR42SY71EYo2gty21MS6P+l5lu/g3AQQsLji6Azsr/E4WFt0ELXY8ePdCjR49iLQOb1ERERPbKpjHWbO2cULoJIfDFF18UStqnT5/Gtm3bch2e3xIRERHRAxRFQfny5TFnzpwCTff69ev45JNP8tTLlI01IiIie8VBcQtVr169cPToUYwdOxapqak5R8jBP//8g06dOmHKlCl5isfGGhERkd1SCuBF2ZkzZw7u3LmDypUrY+rUqTh79mzOkTJITk7Gb7/9hhdeeAEDBw7E/Pnz8zywLjsYEBEREWVBq9Xixx9/xJw5czB27FiMGzcOwcHBqFOnDqpXr47AwEB4eHjA1dUVKSkpSEpKwp07d3D58mWcO3cOJ06cgF6vx9NPP40DBw6gTJkyeS4DG2tERET2ir1Bi8zrr7+OF198EZMnT8aCBQuwcePGbMdZE2pP40aNGmHChAl45pln8p03G2tERET2io21IhUcHIw5c+bgs88+w6+//oq///4bR44cwY0bNxAXFwcPDw+UK1cOlSpVQps2bdChQwfUrl3b5nzZWCMiIiLKAy8vL/Tt2xd9+/YtkvzYWCMiIrJbtnYS4JU1e8DGGhERkb3ibdCHAofuICIiIirBeGWNiIjIXvEu6EOBjTUiIiK7xdbaw4CNNSIiInvFZ9YeCnxmjYiIiKgE45U1IiIie6XAxitrBVYSKkSKMM6HQFmKi4uDt7c3YmNj4eXlVdzFISKiEqwo/s8w5hFz7jC8PD3zn058PHyq1ef/byUcb4MSERERlWC8DUpERGSv2MHgocDGGhERkd3i0B0PA94GJSIiIirBeGWNiIjIXvE26EOBjTUiIiJ7xcbaQ4G3QYmIiIhKMF5ZIyIislvsYPAwYGONiIjITimKAsWGW5m2xKWiw8YaERGRveIzaw8FPrNGREREVILxyhoREZHd4jNrDwM21oiIiOyWjbdB2VizC7wNSkRERFSC8coaERGRvWIHg4cCG2tERER2i8+sPQx4G5SIiIioBOOVNSIiInvF26APBTbWiIiI7BXvgj4UeBuUiIiIqATjlTUiIiK7xUtrDwM21oiIiOwVn1l7KLCxRkREZK/YWHso8Jk1IiIiohKs1DfWdDodPvvsM1SvXh1VqlRBy5YtsX379uIuFhERUQFQCuBFJV2pvg2ampqKZ555BlFRUdiyZQsqVqyIVatWoW3btliyZAm6detW3EUkIiLKPwU23gYtsJJQISrVV9bGjh2LiIgILFiwABUrVgQAdOvWDV27dkX//v1x+fLlYi4hERERUfZKbWPtypUr+Oabb1CzZk00atTIYlvfvn2RmJiIcePGFVPpiIiICoCxg4EtLyrxSm1jbcWKFUhPT0fTpk0zbWvcuDEAYO3atbh7925RF42IiKiA8Jm1h0Gpbaxt2LABAFC5cuVM2/z8/FChQgXodDrs3LmzqItGRERElGultoPB4cOHAQDBwcFWt/v4+ODmzZs4cuQIXnzxRYttqampSE1NNX2OjY0FAMTFxRVSaYmIqLQw/l8hhCj8vBISbLqVGZeQUIClocJSKhtrKSkpSFAPQB8fH6thvL29AQDR0dGZtk2ZMgUff/xxpvUhISEFV0giIirV4uPjTf/XFDQnJycEBgYipFotm9MKDAyEk5NTAZSKCkupbKxlfA7Nzc3NahiNRt4BTklJybRt3LhxGD16tOmzwWDAvXv3UKZMGSh28DBmXFwcQkJCcP36dXh5eRV3cWzG+pRsrE/JxvoUPSEE4uPjERQUVGh5uLi44PLly9DpdDan5eTkBBcXlwIoFRWWUtlYy/gXQlaXoY0HuJ+fX6Ztzs7OcHZ2tliX1RW6kszLy6vEnszyg/Up2Vifko31KVqFdUUtIxcXFzayHhKlsoOBn5+fqcGWmJhoNUxMTAwAwN/fv6iKRURERJRnpbKxptVqUbNmTQBAZGSk1TBRUVEAgEcffbTIykVERESUV6WysQYA7du3BwCcPHky07bo6GjExsbC3d0dLVu2LOqiFTpnZ2dMmDAh061ce8X6lGysT8nG+hDZP0UURd/iYnD+/HnUqFEDtWrVwrFjxyy2/f7773jxxRfRr18/LFq0qJhKSERERJSzUntlLTw8HIMHD8bx48dx5MgRi22LFi2Cq6srJkyYUDyFIyIiIsqlUntlDZCdC1q2bAkHBwds3LgRvr6+mD17Nt555x0sWbIEXbt2Le4iEhEREWWrVA7dYeTu7o6IiAh88MEHaNCgATQaDWrXro39+/ejbt26xV08IiIiohyV6itrRERERPau1D6zRkRERFQasLFGlE+XL1/GwYMHodfri7soNjNeYOeFdiKikoeNtRLIYDAUdxEKVGJiIj755JNMQ6jYq+TkZHz22WeYPHky0tPTodVqi7tINklKSkJsbCwA2MXctzlJT08v7iIUKJ4PiKhUdzCwRwsWLMCuXbvg4uKCRx99FE899RSqVKlS3MWyybp16zBhwgRotVqEhYXB09OzuItkkxUrViAtLQ3ffvstHBzs+yc0efJkrFq1Cm5uboiNjcWIESPQsWNHlCtXDkIIu2u8TZs2DTt37oSvry8ef/xxtG/fHuHh4QBgl/Xh+YCIAACCSoS9e/eK+vXrC0VRLF5hYWFi06ZNwmAwFHcR8+2TTz4RiqKI+vXri61btxZ3cWxy+PBhUb9+fbFjxw4hhBB6vb6YS5Q/e/bsETVr1hTPPPOM2L9/v1iwYIFo3769UBRFjB8/3u7qdfPmTdGqVSvRsWNHsXnzZjFw4EAREBAgfHx8xIQJE0RycnJxFzFPeD4goox4G7QEuH37NkaMGIEjR46gdu3aeOONN/DYY4/B29sbV65cwcyZMzMN7GsPjLdv7t+/jwoVKuDo0aNYvnw5bt++Xcwly7/ff/8dtWrVwpNPPgkA0Gjs8ye0YMECdO3aFRs3bkSDBg3w6quvYtGiRahbty7Wr1+PO3fuFHcR82Tr1q3w8vLCunXr0K5dO/zwww9YunQpQkNDMXHiRIwcORLR0dHFXcxc4fmAiB5kn//TlBJCfZj7jz/+wP79+zFx4kQcO3YMs2fPxs6dO7FgwQIEBARg27ZtOHHihEUce2C85ZSYmIgnn3wSDRo0wKpVq/Dvv//aVT2M4uLiMHfuXNSrVw8AkJKSUrwFyqdDhw5h3rx5aNGiBQBzPcqVK4dhw4bh8uXL8PDwKM4i5tns2bNRtmxZAOb6tG3bFt999x0URcG8efMwdepU3Lx5sziLmS2eD4goK2ysFSPjyWvnzp1o1qwZ3nvvPQCAXq+Hs7MzXnrpJbz77rtITU3F9u3bi7Oo+aIoCpKTk3Hv3j289957eP7553Hv3j0sXrwYly5dKu7i5dnZs2dx9+5dPPHEEwAAFxcXAMCVK1dw//59u3mw/dy5c3B0dERqaioAwMnJybStXLlyaNmyJdzd3e3iwXaDwYD4+HhERkZmqo8QAk2aNMGkSZMAAD///DNWrFhRbGXNCc8HRJQVNtaKicFgMP1nWL58eYwYMcJ0stZqtaZtPXr0QHh4OK5evYrU1NQS+4C0tf/YDQYDXF1dce/ePaSlpeHll19G06ZNsWnTJmzevNn0n2tJ/KvaWn3OnTuH1NRUuLu7AwAiIiLQvHlztG7dGnXq1EGvXr3w999/F3VRcyXj8Va9enWkpaVhyZIluHnzpsWtXCGEaXYPe7jFq9FokJqairi4OOzfv99UHyGE6bgaOXIk2rRpg1u3bmHlypXYs2dPMZfaOmN5S8P5wBp7Ph8QFbeSfzYuBS5fvoyJEyfixx9/xLp165Ceng6NRmP6z1BY6aWm0WhgMBgQFBSE+vXrQ6fTwdnZuUScyLKqz4M0Gg1iYmIQHx+PChUqIDw8HL169YKTkxMWLVpkupVT3P/h5FQf4z6PjIwEAPz333/44osvMGPGDHTs2BFPP/00XFxcsHr1avTs2RNfffUVdDpdsdQFyPl4q1KlCnr06IFly5ahd+/eWLx4MU6dOoX79+8jLi4Ozz77bLGV3Zpbt25h165dAJBpTDshhKnn5507d0xXnBRFgUajgV6vh6urK0aOHIkyZcrgxIkT2LJlC9LS0oq8HkZZ1Sfj78CezgfZfT8Z2cv5gKhEKuoeDQ+bKVOmiIoVK4oxY8aIdu3aCRcXF1GnTh3x448/ivT0dCGEEPfv3xcnT57MFNfY4+vjjz8W/fr1KxE9wLKrj5GxnAaDQSQmJoqXXnpJXLp0SQghxO3bt0Xnzp2Foijiww8/NMU5duxY0VZElZf6vP3220JRFDFlyhSxbNkyi+3Xrl0TTZo0EYqiiBo1aoi1a9cWdVWEENnXJ+Pxc+fOHdGqVSuLnoY1atQQgYGBwtfXV7Rq1UqMHj1aREREmHpSFkcPUZ1OJ7p06SIqV64sdDqdEEJk+h0kJyeLPn36CEVRxJtvvimio6OtptW3b1+hKIpo06aNOH36dKGX3Zrs6mNcxsbG2s35IDffj5E9nA+ISio21grRlStXxDPPPGNx4t2wYYPw9fUViqKIkSNHips3b+aYztChQ8Vbb71ViCXNndzU57///hNCCFND9MKFC6J69eoW6axZs0YEBweLKlWqiLFjx4ry5cuLFi1aiFu3bhVdZUTe6iOEEHPnzhWKogh/f3+xcuVKIYQQqamppkbMiRMnRLt27YRGoxGDBg0SsbGxJa4+kZGRpm3x8fFi9+7d4ssvvxRt2rQRgwYNEn379hWPPfaYcHR0FIqiCEdHR9G7d28RHx8vhMj6P+LCMnv2bOHm5iYURRHTpk0TQlg2Go3l+fbbb4WiKCI8PNw0rIqR8Vjcs2ePcHBwEM7OzmL37t0W8YtKTvXJjZJyPhAi7/UpyecDopKMjbVCNG7cONOJSafTmf5jmD9/vqhevbpQFEUMHDgwy/jG/2SGDRsmVq1aJYSQ/7kY07l//34hlj6zvNYnPT1dnD59WvTu3VvodDqRlJRk2ta1a1eLqzqjRo0Sd+/eLdH1+eOPP0TZsmVF9erVTX/5P/if/cqVK0WlSpVE3bp1i7yxltf6ZCz77t27xc6dO4UQshF39uxZMWXKFPH4448LRVFMjYOibNxERESI7t27i06dOglFUURgYKC4fv26EML82zCWR6/Xi6CgIKEoinj77bez3Pc9e/YUiqKI999/v2gqkUFu6pOdknY+yGt99Hp9iT4fEJVkbKwVkvT0dNG+fXvRvHlzkZiYKIQw/8WZmJgovv32W+Hu7i4URRFLly4VQmT+j9B4whswYID4559/LLYlJCSI9evXi5SUlMKuiqksea2PEEL8+++/onnz5qbP//33nxg0aJDppOzk5CTGjRtXJHXIKC/1WbJkiRBCiCNHjojq1asLV1dX8fnnn1v8Z2P87uLi4sSAAQOEoihFeqvN1uPtvffeE3v37rWIJ4QQ169fFzVr1hTe3t7i8uXLRVQb6erVq0IIeZuze/fuQlEUMWzYsEzhjL+T7777TiiKIsqUKSP++OMPi3oYw+zevVsoiiL69u0r0tLSiqAWZrmtT1ZK0vlAiPzVp6SeD4hKOnYwKARCCGi1WqSlpeHevXtISEgAYO5d5+bmhueffx59+/YFAIwbNw63b9+GoigWDwxrtVrcv38fiYmJpuEijDZt2oRvv/0Wzs7OJbY+AHDz5k3TA+sTJ05ESEgI5s+fj/DwcLz44oswGAw4efIkzp07V+j1sLU+xul+UlJS8Mcff+D48eOmNI3fnaenJx5//HG4u7sXyXdjS30URYFer0dKSgoOHDiA/fv3W8RLT09HcHAwhgwZAoPBYOqtV1SM46a5uLhg/PjxcHFxwdy5czM9zG6cm7Vv375o1KgR7t27h3nz5uHMmTOmtLRaLYQQKF++PEJDQ5GcnFzkU4Xltj5ZKSnnA6P81OfWrVsl7nxAZBeKsaFYqiUnJ4uWLVsKRVHEH3/8IYQQmf6S37dvnwgPDxeKoohPPvlECJH59sGZM2fE66+/brFu48aNonLlysLV1VWcOnWqEGthltf6fPTRR0IIeVswKChIhIWFCUVRhKenpxg7dqxISkoS9+/fF23atBEuLi5i1qxZFleqSlp9JkyYIISQDz4HBgYKRVHEkCFDxJUrV0xxU1NThRBCLFu2TFSqVMn0nFdJrI/xeBNC3j4rV66cxe1Dg8Fgir927VpRpkwZERUVVUS1se69994TiqKIDh06mNY9+HD+3r17LW6l3bhxQwhh3hdJSUkiNDRUTJw4sYhLn1l29clKSTkfWJOb72ft2rUl8nxAVNKxsZYPOZ1QjbdfJk2aJBRFEa1atbIaLjExUXz22WdCURTh6upq6sWW8TmUVatWmRoKp0+fFi+//LLpP6Onn366QP4DLaz63L9/X/z222/Cx8dHKIoievbsKQ4fPmwRZ/78+cLR0VEEBweL48eP21yXwqzP7du3hRBCzJw5UwQFBQmNRiN69+6d6YHqd999V3z++ee5KktuFPbxptPpxFNPPSUqVapktRfrO++8Y9FTz1b53Se3bt0SlStXtrg1nfGPG2O6M2bMEEFBQcLR0VG8+eabFmlERUVZzO1aEAqrPtbyKAnng6zkpj7Lli0TZcqUKdLzAVFpwMZaHsTGxorJkyeLPXv2ZBvOeLLbsmWL8PPzE4qiiN9++00IkfnkdejQIdGgQQOhKIqYOXNmpjQ+++wzsWLFCjFt2jRTDz0/Pz8xf/78El+f77//Xty7d0+8/fbb4pdffrEIZ+zmHx0dLQYOHCi+++67El+fL774Qgghr84sW7ZMhISEmP6TnDlzpjh58qQYMmSIaNy4sTh69GiJr8+MGTOEEPK7+Pzzz4WLi4uoUKGCWLx4sfjvv/9EbGysGDRokKhbt67Yv39/kdUnO/PnzxeKoohatWqJhIQEIYS5sWpcpqamij/++MPUcBg8eLDYtm2b0Ol0YsCAAaJfv365eqC/uOuTUUk6H2Qnq/oYy3/t2jXxv//9r0jOB0SlCRtrufTNN98IV1dXoShKrscAOnPmjHj22WeFoijimWeeMd2KyfiXa1xcnBg3bpzQarVi+PDhpltpQsgrIR06dBDlypUz/fX8zjvvFMhDxEVRH+PtmozbrV0JKYirT0X1/RjHHBNCNnzGjRsnKlSoICpWrCgqVqwohg0bZhHGXupz9+5dMXPmTFG2bFmhKIqoW7euCAgIEEOHDi22+liTnJwsnnrqKYtbuVkNFXHmzBkxefJkUaVKFdGwYUPxyCOPiGHDhhXb78eavNSnpJ0PrMlNfYrifEBU2rCxloMtW7aImjVrmk6OTzzxhDh37lyu40+dOlX4+PgIDw8P8cMPPwghMp+8fv31V+Hp6Slat24thDCfrM6ePWvK99lnnxXnz5+3y/pkrFNBK87vxygxMVHcvHnTYgyz/Cqu78fo0qVL4t9//xXr168XFy9etK0ywvb6WPP3338LRVGEr6+vuHDhghAi+6EvkpKSRGRkZK7GNMxJcdanJJ4PrMlNfdggI8obNtaycejQIdNwB1WqVBFz587N9VhGxpPRyZMnRbt27YSiKOLRRx81/YeRnp5uChMTEyPCw8NFtWrVRExMjCmNzz//XPj5+Yk///zTbutTmGM/laT6FMR/PiWpPgXBlvrkxDg8yquvviqEyHn/F/f3k5Pc1KcknQ9yktfvh4iyx8ZaNm7fvi08PDzEiBEjbPqrfMmSJaJWrVoWJy8j41+c3bt3z/RguLEnW0EprvoU1oma9bGutNXHmjNnzghvb2+hKIr4+++/CzTtrBR3fUrq+cCa4vh+iEozNtayoNfrxd27d0X//v1Nl/LzyvifYHx8vJg/f75wcnISiqKIuXPnmoZI0Ol0Ij09XTRs2NDU464gHn5+UHHWpzDmlGR9Mitt9cnJp59+KhRFEU2bNhUxMTFi1qxZ4sSJE4WSF+uTd0VZH6LSjo21bMTExIgaNWqIEydOCL1eL/bu3Ss2btwodu3aJS5evGjRqMrNf3jff/+98PX1Fc7OzmLMmDGmZ5y2bt0qnnnmGXHt2rVCq4sQrE9OWJ+CVdD1yUiv14tbt26ZptHSaDSiWrVq4uzZswVdDRPWJ/eKoz5EpdlD3VgznoysnYiM63r06CFat24tmjdvbnpoVlHkZN5dunQRK1asyFOex44dE927dxe+vr6idu3aom3btqJWrVpizZo1rA/rw/rkwa5du4Sbm5uoVKmSWL16db7TMWJ9SnZ9iB5mD11jzXiraMmSJaZR9rOSnJws2rdvb+opZRzTKONnRZFzLeZltG2dTicuXrwodu/eLVauXMn6sD6sTx5Hqz937pwIDw8Xo0aNynddhGB9Snp9iEh66BprQsiRth977DHRsGFDq5NXZ/w8evRo4evrK9566y2xe/du8ffff4tTp06J6dOnixdeeEEoiiKqVq0qtm7dWuT1MGJ9WJ+iVBLqk5ycbHoOj/Up3fUhooewsXb9+nXT0AZOTk7izTfftDp4qNHu3bvFmTNnrKaVkpIiJkyYINzc3MTo0aOFEIXzsHZ2WB/WpyixPqwPERW9h6qxptfrRUREhFi/fr2YNm2aKF++vAgODjZNzZPdEAYGg8F0osr4/u7du2L06NGifPnyhV+BB7A+ZqxP4WN9zFgfIipKD1VjTQhhGk/o7t27Yvz48UJRFNGtWzdx584dIUT+/nI8fPiweOmll8TVq1cLtKy5wfrkjPUpOKxPzlgfIipoGjxkgoKCAAB+fn7o1KkTGjRogD/++AO//PILAECjyfsu8fT0xP3791GxYsUCLWtusD45Y30KDuuTM9aHiAraQ9dYAwAhBACgTp06eOWVV5CSkoIlS5bg3LlzAACDwZCn9Nzc3PDCCy8UeDlzi/XJHutTsFif7LE+RFTQHsrGmqIoAABnZ2e0b98eHTp0wM6dO7Fs2TIA2f/1ae1Et2PHDjz66KOFU9hcYH3MWJ/Cx/qYsT5EVBQeysZaRlWqVEG/fv3g7e2NFStW4N9//wWQ9V+fxhNdQkICAGDVqlW4ceMGWrduXTQFzgHrw/oUJdaH9SGiIlCMz8vZ5MEHZW2ZjPrWrVti6NChQlEUMXjwYJGcnJxlmr/99puoVq2aqF+/vggKChI9e/YU169fz3feRqxP1lgf1icnrE/WSkJ9iMg2DsXdWMyrs2fP4vPPP4erqyuEEOjcuTPatm1ruvSfH+XKlUOPHj3w999/49dff0W7du3QtWtXq2GvX78OIQTc3Nwwe/ZsdO7cOd/5AqxPbrA+rE9WWJ+cFWd9iKiAFEcLMT/S09PFyJEjRXBwsBg7dqx4//33TfPYTZs2TQiRc7f0jBMTGxn/uoyLixMTJ04UiqKIF198Ufz333+m7caXUVRUFOvD+rA+rA/rQ0RFwm4aa1OnThXPPfecxYnkxIkTolatWsLT01MkJCRkGVev11ucjKyd1IQQ4siRI6JZs2bCzc1NzJo1y7Q+NTXVlE5BYX3MWB/WJ69YH7OSWB8iKlglvrGm1+vF7du3RfXq1cXUqVOFEHJiauPJafr06cLLy0scPHgwU1yDwWBx4tq/f7/o0qWL2Lhxo9XnNZKTk8W8efOEm5ubCAkJEe+//7546qmnxJo1a1gf1of1YX1YHyIqFiW+sSaEEKdOnRKOjo5i27ZtQgh5gjP+FXjmzBkREBAgIiMjs4x/+/Zt8eabbwpFUYSiKGLIkCEiJSXFIowxvYsXL4qwsDChKIooV66cmDdvHuvD+rA+rA/rQ0TFxi4aa7t27RIuLi6ie/fuFusNBoPYvHmzGDZsmOlS/oM+//xzUb58eaEoitBqtWLixInZ5vXWW28JRVHERx99VGDlfxDrY8b6sD55xfqYlcT6EFHBKzGNtb/++kscPXpUXL58WaSlpQkhzH8N3r9/X7Ru3VooiiL69esndu7cKWJjY4UQQmzdulUcPXrUIi3jLYBDhw6Z/trs27ev6aFaIaw/17F9+3YxcuTIApkDj/VhfVgf1qe01oeIilaxN9aOHDkimjdvLpo0aSLatGkjPD09xYsvvigOHz5sccL566+/RPv27YWiKMLFxUUEBQWJ559/XtSqVUs0b95cvPnmm2L27Nni2rVrFumPGzfOdHtBCHkSy2rMooJ4wJb1YX1YH9antNaHiIpHsTbWEhMTRZcuXcTXX38thJDdyz/77DPh5+cnXF1dxYcffmgRPiYmRkyZMkW89NJLIiwsTJQtW1bUrVtXODs7C41GIxRFEWXKlBGTJk0St2/ftoj74MO4rA/rw/qwPqwPEdmDYm2srVmzRgQHB4ubN2+a1qWkpIjff//ddHl/xowZmU5MQggRGxsrNm3aJISQD+guW7ZM9O/f3xTv448/FnFxcUKIrLuysz6sD+vD+rA+RFTSFUtjzXiZfsyYMeKRRx6xWGdcTpo0SSiKIkJCQsTs2bNNcY2X8pctW2YxVpDRpk2bxJNPPilCQ0PF6dOnC7UeRqwP68P65B/rU7LrQ0TFr9iurOn1etG9e3eh1WpNJ52MXdZTU1NFy5YthaIookmTJmL79u2mMEII0bNnT9P4QOnp6aa/LtPS0sTq1auFoihix44drA/rw/qwPqwPEdk1TTFNcQWNRoPAwEAYDAb8+eefAACNRgONRgO9Xg8nJyeMGzcOZcuWxeHDh7Fu3TqkpqZCo5FFvnz5MpYsWWKKp9VqAQAODg4ICAhA2bJl4eLiwvqwPqwP68P6EJFdK5bGmqJOSlylShVotVrs2bMHN27cMG03npjat2+Pjh07QqfT4d9//8WBAwcAACkpKXBycsK6deuwf/9+U3rp6ekAgNu3b6NmzZp45JFHWB/Wh/VhfVgfIrJvxXhVT/z6669CURRRsWJF08O0RsbL/kePHhX+/v7CwcFBfP/996ZnPmbMmCEURRG1a9cWhw4dEklJSUII2QW+UaNGYtGiRUVbGcH6sD5Fi/VhfYjo4VDs46zVqFFDKIoi3njjDXH37l2rYYYNGyYURRG9evWyWN+zZ0/h5uYmNBqN6NChg3jyySdFlSpVxIoVK4qi6FaxPmasT+FjfcxYHyIqrRQhhCjOK3srVqxAz5494eXlheXLl+Ppp582Pbeh1+uh1Wpx+fJlVKlSBYGBgThw4ACCgoIAAElJSTh9+jT++usvJCcnIyAgAG+88UZxVof1YX2KFOvD+hDRQ6C4W4s6nU48+eSTQlEU0aVLF3HhwgWL7QaDQRgMBvHSSy+JChUqiISEhCxH6C4JWB/WpyixPqwPEZV+xdLBICNHR0d89tlnAIBffvkFS5YswZ07dwDIvzwVRYGiKAgJCYGiKEhNTTU9cFsSsT6sT1FifVgfIir9ir2xBgDNmjXDBx98AACYO3cufvzxRwCy11RKSgoA/L+9+wlp+o/jOP6aWpqtsbIOycoKI1xhKRQsq0t0CSoIPFh2CCqoQx2DpJoSKEG3glgxq4OQFF6EhCCk1QZe+0OUVCwMUicjKyXXPr9D+G1Lg35S7mN7Pk5+P599932/B5MXn+8+mwYGBlRVVSWv15urMn8b/diNfuxGPwDwk1wv7U0aGxszwWDQeDwe43K5zOXLl50dU+Pj46a+vt48evQox1X+PvqxG/3YjX4A4Adrwtqk7u5uU1tba1wulwkEAqa5udn4/X5z9OhR8+nTp1yX97/Rj93ox270AwAW7AadzsTEhLq7uxWPxxWPx7V7927t3Lkz12XNGP3YjX7sRj8A8p11Yc0Y8099wJZ+7EY/dqMfALBkg0GmzH9kluXIGaEfu9GP3egHACxcWQMAAMAP1q2sAQAA4AfCGgAAgMUIawAAABYjrAEAAFiMsAYAAGAxwhoAAIDFCGsAAAAWI6wBAABYjLAGAABgMcIaAElSe3u7PB6P2tvbc10KACADYQ2AJOnOnTsaHR3V3bt3c10KACADYQ3IQw8fPpwydurUKW3evFknT57MQUUAgF/hh9yBPJNOp7Vx40Y9efIk16UAAH4DK2tAnmltbdXTp09zXQYA4DexsgbkkXA4rCNHjsgYI976ADA3sLIG5ImLFy+qtbXVCWmVlZWqrKzUmTNn9PnzZ127dk21tbUKBoNZ5338+FEtLS3yer2SpJGRER0+fFgej0cVFRW6ceOG89je3l7V1dWptLRUNTU1isVi09by/PlzNTQ0aMOGDXK73aqurlY4HP4bbQPA3GcA5BVJJvOt/+zZM9PQ0GBKS0uNJHP+/HlnLhQKmdWrVzvnJBIJ4/f7TXl5uSkpKTGSTEFBgYnFYqarq8vMnz/frFixwhQWFhpJpqyszCSTyazr9/T0mFWrVplIJGKMMebdu3dm06ZNRpIJBoOz8hoAwFzCyhqQ5/x+vzo6OnTw4MEpc4cOHVJPT49zfPbsWYVCIQ0MDGhoaEiBQEDpdFpNTU3q6OjQq1evFI/H9fbtW/l8PiUSCd27d885P5FI6MCBA2pra9O2bdskST6fT6FQSJLU0tKi/v7+v9wxAMwthDUAkqRly5ZNGSspKVFFRYVz3NbWprq6OkmS2+3WiRMnJEnJZFK3b9/WypUrJX0PYHv27JEkxeNx5/xwOKzR0VHt3bs36zrV1dWSvu9U7erq+oNdAcDcV5TrAgDYYd68edOOFxcXO38vWrQoa668vNwZd7lcWXNLly6VJI2NjTljDx48kDFGNTU1U65TVlYmSRocHJxB9QDw7yKsAZixgoJfL85PzpmMXafxeFxLlizRixcv/nptAPCv4DYogFmTSqU0NDSkZDKZ61IAYM4grAGYNcuXL5cxRp2dndPOG2PU29s7u0UBgOUIawBmzY4dOyRJTU1Nev369ZT5mzdv6v3797NdFgBYjbAG5JkFCxZIksbHx7PGv379KkmamJjIGs88TqVSWXPpdFqS9O3btynXmfysWub5x44d08KFCzU8PKxAIKCrV6/qzZs3evnypfOlvT/vFAWAfEdYA/LM+vXrJUmPHz/Wly9fdOnSJaXTaUUiEUlSJBLJCl+T45LU19eX9VyTtyz7+/s1PDzsjKdSKUWjUUlSLBZzns/n8ykcDquoqEiDg4M6fvy41qxZo3Xr1uncuXO6fv263G73n28aAOYwfhsUyDN9fX1qbGxUMplUY2Oj9u/fr3379mlkZMR5zOLFi3X//n1duXJFt27dcsJWYWGhdu3apc7OTq1du1YfPnxwzikuLtbp06e1fft21dfXZ20i8Hq9ikajqqqqkvQ9wDU3NysajSqdTmvr1q26cOGCtmzZMjsvAgDMIYQ1AAAAi3EbFAAAwGKENQAAAIsR1gAAACxGWAMAALAYYQ0AAMBihDUAAACLEdYAAAAsRlgDAACwGGENAADAYoQ1AAAAixHWAAAALEZYAwAAsBhhDQAAwGKENQAAAIsR1gAAACz2H6j+7CfpS7XOAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 640x480 with 2 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Remove estimations below 0\n",
-    "ds_avg[\"TKE\"] = ds_avg[\"TKE\"].where(ds_avg[\"TKE\"] > 0)\n",
-    "\n",
-    "ds_avg[\"TKE\"].plot(cmap=\"Reds\", ylim=(0, 11))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "TKE esimations are generally more complete than those of dissipation rates because they are found directly from the along-beam velocity measurements. Missing TKE estimations exist whenever the noise calculated by the function `doppler_noise_level` is greater than the calculated TKE, as TKE can't be less than zero. Noise levels are affected by the instrument's processor and working frequency, water waves and other sources of \"interference\", instrument motion, current speed, intricacies in the spectra calculation, the ability to see the noise floor in the spectra, etc.\n",
-    "\n",
-    "You may also note that high TI doesn't always correlate with high TKE. TI is the ratio of flow speed standard devation to the mean, which is naturally lower when flow speeds are higher. When flow speeds are higher, they also have greater kinetic energy and thereby greater TKE.\n",
-    "\n",
-    "There is one other important thing to note on TKE measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the TKE of larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue."
+    "There is one other important thing to note on Reynolds stress measurements by ADCPs: the minimum turbulence length scale that the ADCP is capable of measuring increases with range from the instrument. This means the instrument is only capable of measuring the stress transported by larger and larger turbulent structures as the beams travel farther and farther from the instrument head. One of the benefits of calculating w'w' from the vertical beam is that it isn't limited by this beam spread issue, though on its own it may not be particularly useful."
    ]
   },
   {
@@ -3922,15 +4009,17 @@
    "source": [
     "### 7.7 TKE Production\n",
     "\n",
-    "Though it can't be found from this deployment, we'll go over how to estimate TKE Production. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
+    "Though it can't be found from this deployment, we'll go over how to estimate the TKE shear production rate. Note that we're assuming here that the buoyancy production is negligible and we're in a well-mixed tidal channel. There isn't a specific function in MHKiT-DOLfYN for production, but all the necessary variables are. \n",
+    "\n",
+    "It is possible to estimate production rates from either an ADV or an ADCP aligned with the flow direction (so \"X\" would align with the principal flow direction). The following estimation for shear production rates takes into account both along- and cross-stream shear:\n",
     "\n",
-    "If we had aligned the ADCP instrument axes to the flow direction (so \"X\" would align with the main flow), we could use the following equation to estimate production:\n",
+    "$P = -\\overline{u'w'}\\frac{du}{dz} - \\overline{v'w'}\\frac{dv}{dz}$\n",
     "\n",
-    "$P = -(\\overline{u'w'}\\frac{du}{dz} + \\overline{v'w'}\\frac{dv}{dz} + \\overline{w'w'}\\frac{dw}{dz})$\n",
+    "Note that the signs can get tricky but are important here. We found the Reynolds shear stresses -$\\overline{u'w'}$ and -$\\overline{v'w'}$ above using the Reynolds stress equations. If ADV data is available, those estimations are preferred because the ADV's point measurement does not have the assumptions that ADCP measurements have.\n",
     "\n",
-    "To start, we need the functions `reynolds_stress_4beam` or `stress_tensor_5beam` to get the stress tensor components $\\overline{u'w'}$ and $\\overline{v'w'}$. We also need the vertical TKE component, $\\overline{w'w'}$. \n",
+    "The velocity shear components can be found from the aptly named functions `dudz` and `dvdz` in ADPBinner. These functions, which are useful alone in their own right, approximate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"approximate\" is also used here for velocity shear.\n",
     "\n",
-    "Both of these functions will give comparable results, but it should be noted that `stress_tensor_4beam` assumes the instrument is oriented with 0 degrees pitch and roll, and will throw a warning if they are greater than 5 degrees. The `stress_tensor_5beam` gives more leeway to instrument tilt, but shouldn't be used if pitch and roll angles are greater than 10 degrees."
+    "The velocity shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation. If using ADV data, take the mean again of the \"range\" dimension."
    ]
   },
   {
@@ -3938,59 +4027,37 @@
    "execution_count": 33,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Data is already in the principal coordinate system\n"
+     ]
+    },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:401: UserWarning:     The beam-variance algorithms assume the instrument's (XYZ) coordinate system is aligned with the principal flow directions.\n",
-      "  warnings.warn(\n",
-      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\adp\\turbulence.py:411: UserWarning:     100.0 % of measurements have a tilt greater than 5 degrees.\n",
+      "c:\\users\\mcve343\\mhkit-python\\mhkit\\dolfyn\\rotate\\api.py:72: UserWarning: You are attempting to rotate into the 'principal' coordinate system, but the dataset is in the principal coordinate system. Be sure that 'principal_heading' is defined based on the earth coordinate system.\n",
       "  warnings.warn(\n"
      ]
     }
    ],
    "source": [
-    "# Beam-variance equation for 4-beam ADCPs\n",
-    "stress_vec = avg_tool.reynolds_stress_4beam(\n",
-    "    ds_beam, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
-    ")\n",
-    "upwp_ = stress_vec[1]\n",
-    "vpwp_ = stress_vec[2]\n",
-    "wpwp_ = ds_avg[\"wpwp_bar\"]  # Found from the vertical along-beam velocity (vel_b5) above\n",
+    "# Vertical shear gradients\n",
+    "upwp_ = ds_avg[\"stress_vec\"][1]\n",
+    "vpwp_ = ds_avg[\"stress_vec\"][2]\n",
     "\n",
-    "# OR #\n",
-    "\n",
-    "# Beam-variance equation for 5-beam ADCPs\n",
-    "tke_vec, stress_vec = avg_tool.stress_tensor_5beam(\n",
-    "    ds_beam, noise=ds_avg[\"noise\"], orientation=\"up\", beam_angle=25\n",
-    ")\n",
-    "upwp_ = stress_vec[1]\n",
-    "vpwp_ = stress_vec[2]\n",
-    "wpwp_ = tke_vec[2]"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "The shear components can be found from the aptly named functions `dudz`, `dvdz`, and `dwdz` in ADPBinner. These functions, which are useful alone in their own right, estimate the shear in the velocity vector between respective depth bins. There is always correlation between velocity measurements in adjacent depth bins, based on ADCP operation principles, which is why \"estimation\" is also used here for shear.\n",
+    "# Find shear velocity and and ensemble-average it\n",
+    "ds.velds.rotate2(\"principal\", inplace=True)\n",
+    "dudz_raw = avg_tool.dudz(ds[\"vel\"], orientation=\"up\")\n",
+    "dudz = avg_tool.mean(dudz_raw.values)\n",
     "\n",
-    "The shear functions operate on the raw velocity vector in the principal reference frame and need to be ensemble-averaged here. This can be done by nesting the `d*dz` function within the ADPBinner's `mean` function. With the ensemble shear known, we can put all the components together to get a production estimation."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Find and ensemble-average shear\n",
-    "dudz = avg_tool.mean(avg_tool.dudz(ds_streamwise[\"vel\"]).values)\n",
-    "dvdz = avg_tool.mean(avg_tool.dvdz(ds_streamwise[\"vel\"]).values)\n",
-    "dwdz = avg_tool.mean(avg_tool.dwdz(ds_streamwise[\"vel\"]).values)\n",
+    "dvdz_raw = avg_tool.dvdz(ds[\"vel\"], orientation=\"up\")\n",
+    "dvdz = avg_tool.mean(dvdz_raw.values)\n",
     "\n",
     "# Calculate Production\n",
-    "P = -(upwp_ * dudz + vpwp_ * dvdz + wpwp_ * dwdz)"
+    "P = -upwp_ * dudz - vpwp_ * dvdz\n"
    ]
   },
   {
@@ -3998,13 +4065,12 @@
    "metadata": {},
    "source": [
     "### 7.8 TKE Balance \n",
-    "\n",
-    "We can plot TKE Production and compare it to our dissipation rate calculations to get an understanding of the TKE balance. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates aren't accurate because our stress components aren't aligned with the flow, so if we plot them, we see drastic differences (1x10^-3 $m^2/s^3$ is quite large) profile here."
+    "We can plot the production rates and the ratio of production rates to dissipation rates to get an understanding of the TKE balance.We always expect production to be greater than 0, though negative values can give us an indication of uncertainty. In a well mixed coastal environment, we expect production and dissipation to be approximately equal. Our production estimates are possibly high because our stress components aren't aligned with the flow (4x10^-3 $m^2/s^3$ is quite large), but if this weren't the case, we would conclude that TKE is produced (kinetic energy is lost to turbulence) but not dissipated (turbulent energy is lost to entropy) here."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [
     {
@@ -4013,13 +4079,13 @@
        "Text(0.5, 1.0, 'TKE Balance')"
       ]
      },
-     "execution_count": 35,
+     "execution_count": 36,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -4029,7 +4095,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -4041,13 +4107,15 @@
    "source": [
     "# Remove estimations below 0\n",
     "P = P.where(P > 0)\n",
+    "# Plot production rate\n",
     "P.plot(cmap=\"turbo\", ylim=(0, 11))\n",
     "plt.title(\"TKE Production\")  # remove bogus title\n",
     "\n",
     "\n",
-    "# Plot difference between production and dissipation\n",
+    "# Plot difference between production and dissipation rate\n",
     "plt.figure()\n",
-    "(P - ds_avg[\"dissipation_rate\"].values).plot(ylim=(0, 11))\n",
+    "balance = P - ds_avg[\"dissipation_rate\"].values\n",
+    "balance.plot(ylim=(0, 11))\n",
     "plt.title(\"TKE Balance\")"
    ]
   },
diff --git a/examples/adv_example.ipynb b/examples/adv_example.ipynb
index 1fe898ede..154c4e59e 100644
--- a/examples/adv_example.ipynb
+++ b/examples/adv_example.ipynb
@@ -28,16 +28,7 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "c:\\Users\\mcve343\\Anaconda3\\lib\\site-packages\\xarray\\backends\\cfgrib_.py:29: UserWarning: Failed to load cfgrib - most likely there is a problem accessing the ecCodes library. Try `import cfgrib` to get the full error message\n",
-      "  warnings.warn(\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from mhkit import dolfyn\n",
     "from mhkit.dolfyn.adv import api"
@@ -463,31 +454,31 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
-       "Dimensions:              (x1: 3, x2: 3, time: 122912, dir: 3, beam: 3,\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 12MB\n",
+       "Dimensions:              (time: 122912, beam: 3, dir: 3, x1: 3, x2: 3,\n",
        "                          earth: 3, inst: 3)\n",
        "Coordinates:\n",
-       "  * x1                   (x1) int32 1 2 3\n",
-       "  * x2                   (x2) int32 1 2 3\n",
-       "  * time                 (time) datetime64[ns] 2012-06-12T12:00:02.968749046 ...\n",
-       "  * dir                  (dir) &lt;U1 &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
-       "  * beam                 (beam) int32 1 2 3\n",
-       "  * earth                (earth) &lt;U1 &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
-       "  * inst                 (inst) &lt;U1 &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * time                 (time) datetime64[ns] 983kB 2012-06-12T12:00:02.9687...\n",
+       "  * beam                 (beam) int32 12B 1 2 3\n",
+       "  * dir                  (dir) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
+       "  * x1                   (x1) int32 12B 1 2 3\n",
+       "  * x2                   (x2) int32 12B 1 2 3\n",
+       "  * earth                (earth) &lt;U1 12B &#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;\n",
+       "  * inst                 (inst) &lt;U1 12B &#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;\n",
        "Data variables: (12/15)\n",
-       "    beam2inst_orientmat  (x1, x2) float64 2.709 -1.34 -1.364 ... -0.3438 -0.3499\n",
-       "    batt                 (time) float32 13.2 13.2 13.2 13.2 ... nan nan nan nan\n",
-       "    c_sound              (time) float32 1.493e+03 1.493e+03 ... nan nan\n",
-       "    heading              (time) float32 5.6 10.5 10.51 10.52 ... nan nan nan nan\n",
-       "    pitch                (time) float32 -31.5 -31.7 -31.69 ... nan nan nan\n",
-       "    roll                 (time) float32 0.4 4.2 4.253 4.306 ... nan nan nan nan\n",
+       "    beam2inst_orientmat  (x1, x2) float64 72B 2.709 -1.34 ... -0.3438 -0.3499\n",
+       "    batt                 (time) float32 492kB 13.2 13.2 13.2 ... nan nan nan\n",
+       "    c_sound              (time) float32 492kB 1.493e+03 1.493e+03 ... nan nan\n",
+       "    heading              (time) float32 492kB 5.6 10.5 10.51 ... nan nan nan\n",
+       "    pitch                (time) float32 492kB -31.5 -31.7 -31.69 ... nan nan nan\n",
+       "    roll                 (time) float32 492kB 0.4 4.2 4.253 ... nan nan nan\n",
        "    ...                   ...\n",
-       "    orientation_down     (time) bool True True True True ... True True True True\n",
-       "    vel                  (dir, time) float32 -1.002 -1.008 -0.944 ... nan nan\n",
-       "    amp                  (beam, time) uint8 104 110 111 113 108 ... 0 0 0 0 0\n",
-       "    corr                 (beam, time) uint8 97 91 97 98 90 95 95 ... 0 0 0 0 0 0\n",
-       "    pressure             (time) float64 5.448 5.436 5.484 5.448 ... 0.0 0.0 0.0\n",
-       "    orientmat            (earth, inst, time) float32 0.0832 0.155 ... -0.7065\n",
+       "    orientation_down     (time) bool 123kB True True True ... True True True\n",
+       "    vel                  (dir, time) float32 1MB -1.002 -1.008 ... nan nan\n",
+       "    amp                  (beam, time) uint8 369kB 104 110 111 113 ... 0 0 0 0\n",
+       "    corr                 (beam, time) uint8 369kB 97 91 97 98 90 ... 0 0 0 0 0\n",
+       "    pressure             (time) float64 983kB 5.448 5.436 5.484 ... 0.0 0.0 0.0\n",
+       "    orientmat            (earth, inst, time) float32 4MB 0.0832 ... -0.7065\n",
        "Attributes: (12/39)\n",
        "    inst_make:                   Nortek\n",
        "    inst_model:                  Vector\n",
@@ -501,25 +492,25 @@
        "    firmware_version:            3.34\n",
        "    fs:                          32.0\n",
        "    coord_sys:                   inst\n",
-       "    has_imu:                     0</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-149f4b3c-942a-453b-bd63-0b791b4881b1' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-149f4b3c-942a-453b-bd63-0b791b4881b1' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x1</span>: 3</li><li><span class='xr-has-index'>x2</span>: 3</li><li><span class='xr-has-index'>time</span>: 122912</li><li><span class='xr-has-index'>dir</span>: 3</li><li><span class='xr-has-index'>beam</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-01236b98-0baa-4b40-bc31-7d8842adb9d9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-01236b98-0baa-4b40-bc31-7d8842adb9d9' class='xr-section-summary' >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'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-5ed1e989-e174-4dcf-a2f0-61045255dc44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ed1e989-e174-4dcf-a2f0-61045255dc44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-20172b21-e6e3-4593-9e6d-1b78b8296f65' class='xr-var-data-in' type='checkbox'><label for='data-20172b21-e6e3-4593-9e6d-1b78b8296f65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-a4dc4986-8e79-483c-a15e-afe8b5518252' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4dc4986-8e79-483c-a15e-afe8b5518252' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58cfe0a8-c148-4430-9843-21550c2e7bdd' class='xr-var-data-in' type='checkbox'><label for='data-58cfe0a8-c148-4430-9843-21550c2e7bdd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2012-06-12T12:00:02.968749046 .....</div><input id='attrs-63ea8218-8e49-4af2-99bc-1ead113549f6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63ea8218-8e49-4af2-99bc-1ead113549f6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6764b53c-9b95-4e30-9d1b-471a12e05860' class='xr-var-data-in' type='checkbox'><label for='data-6764b53c-9b95-4e30-9d1b-471a12e05860' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>units :</span></dt><dd>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2012-06-12T12:00:02.968749046&#x27;, &#x27;2012-06-12T12:00:02.999999046&#x27;,\n",
-       "       &#x27;2012-06-12T12:00:03.031249046&#x27;, ..., &#x27;2012-06-12T13:04:03.875000715&#x27;,\n",
-       "       &#x27;2012-06-12T13:04:03.906250715&#x27;, &#x27;2012-06-12T13:04:03.937500715&#x27;],\n",
-       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-d9fbf2a2-1649-49f0-a162-673357c94f37' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d9fbf2a2-1649-49f0-a162-673357c94f37' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-949ea243-f37a-44e0-9bfb-3d1a5cede756' class='xr-var-data-in' type='checkbox'><label for='data-949ea243-f37a-44e0-9bfb-3d1a5cede756' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>inst</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-6fc9a530-a093-4fde-8a53-b8c065dc6bff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6fc9a530-a093-4fde-8a53-b8c065dc6bff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da8f01f9-88a4-42e3-96ab-1b431620a990' class='xr-var-data-in' type='checkbox'><label for='data-da8f01f9-88a4-42e3-96ab-1b431620a990' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-4fc79bf1-32a3-4a8a-a4b2-9530fb7e4ab8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4fc79bf1-32a3-4a8a-a4b2-9530fb7e4ab8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f7e904f-385d-46ba-a2db-e9d334a8b6bb' class='xr-var-data-in' type='checkbox'><label for='data-9f7e904f-385d-46ba-a2db-e9d334a8b6bb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-469499b6-9189-428f-9879-d7826475fe61' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-469499b6-9189-428f-9879-d7826475fe61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08904df7-0392-4100-994f-a0ffb6e4f7ac' class='xr-var-data-in' type='checkbox'><label for='data-08904df7-0392-4100-994f-a0ffb6e4f7ac' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c4f35d8a-787d-4a76-8ce0-22cc7099f5e9' class='xr-section-summary-in' type='checkbox'  ><label for='section-c4f35d8a-787d-4a76-8ce0-22cc7099f5e9' class='xr-section-summary' >Data variables: <span>(15)</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>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.709 -1.34 ... -0.3438 -0.3499</div><input id='attrs-157b8a80-1a01-4ec4-913b-e82f90a7886c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-157b8a80-1a01-4ec4-913b-e82f90a7886c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b31331be-bcbf-4426-a3c0-c568cf175b86' class='xr-var-data-in' type='checkbox'><label for='data-b31331be-bcbf-4426-a3c0-c568cf175b86' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 2.70874023, -1.34008789, -1.36376953],\n",
+       "    has_imu:                     0</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-e81472b5-8470-4bf6-b72b-3c9468a3e6c5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e81472b5-8470-4bf6-b72b-3c9468a3e6c5' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 122912</li><li><span class='xr-has-index'>beam</span>: 3</li><li><span class='xr-has-index'>dir</span>: 3</li><li><span class='xr-has-index'>x1</span>: 3</li><li><span class='xr-has-index'>x2</span>: 3</li><li><span class='xr-has-index'>earth</span>: 3</li><li><span class='xr-has-index'>inst</span>: 3</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-14477b2c-6e52-4317-8bf4-375e7883a32d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-14477b2c-6e52-4317-8bf4-375e7883a32d' class='xr-section-summary' >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'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2012-06-12T12:00:02.968749523 .....</div><input id='attrs-72882279-1e8a-4de7-a79f-68bb8e91646a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-72882279-1e8a-4de7-a79f-68bb8e91646a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-26425e49-b869-4379-9c13-5b4ed0596ca4' class='xr-var-data-in' type='checkbox'><label for='data-26425e49-b869-4379-9c13-5b4ed0596ca4' title='Show/Hide data repr'><svg 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>seconds since 1970-01-01 00:00:00</dd><dt><span>long_name :</span></dt><dd>Time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2012-06-12T12:00:02.968749523&#x27;, &#x27;2012-06-12T12:00:02.999999523&#x27;,\n",
+       "       &#x27;2012-06-12T12:00:03.031249523&#x27;, ..., &#x27;2012-06-12T13:04:03.875001192&#x27;,\n",
+       "       &#x27;2012-06-12T13:04:03.906251192&#x27;, &#x27;2012-06-12T13:04:03.937501192&#x27;],\n",
+       "      dtype=&#x27;datetime64[ns]&#x27;)</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'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-f25a2106-b72a-42fa-9bad-aeaeb426ba2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f25a2106-b72a-42fa-9bad-aeaeb426ba2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14658fdc-f558-4292-86ac-5aa68977afe4' class='xr-var-data-in' type='checkbox'><label for='data-14658fdc-f558-4292-86ac-5aa68977afe4' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Beam Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>dir</span></div><div class='xr-var-dims'>(dir)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-0892b001-b621-400b-8cca-658591d13573' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0892b001-b621-400b-8cca-658591d13573' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb799566-2835-473e-94eb-eb879c93930e' class='xr-var-data-in' type='checkbox'><label for='data-fb799566-2835-473e-94eb-eb879c93930e' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd><dt><span>ref_frame :</span></dt><dd>inst</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x1</span></div><div class='xr-var-dims'>(x1)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-2d333103-5c28-4036-bdd4-160213438166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d333103-5c28-4036-bdd4-160213438166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b70c56-e963-4714-953a-324f7fbccfd4' class='xr-var-data-in' type='checkbox'><label for='data-54b70c56-e963-4714-953a-324f7fbccfd4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x2</span></div><div class='xr-var-dims'>(x2)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3</div><input id='attrs-126943ac-185d-400d-b1e6-048242d1cfbe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-126943ac-185d-400d-b1e6-048242d1cfbe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d92616b-0fbc-4b63-81d1-8f4f7134d88b' class='xr-var-data-in' type='checkbox'><label for='data-2d92616b-0fbc-4b63-81d1-8f4f7134d88b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([1, 2, 3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>earth</span></div><div class='xr-var-dims'>(earth)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;E&#x27; &#x27;N&#x27; &#x27;U&#x27;</div><input id='attrs-4a31fcc6-0a3e-40b3-a980-f59af3445c1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a31fcc6-0a3e-40b3-a980-f59af3445c1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56c04365-a391-4edc-88cc-bb1285dd31eb' class='xr-var-data-in' type='checkbox'><label for='data-56c04365-a391-4edc-88cc-bb1285dd31eb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Earth Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>inst</span></div><div class='xr-var-dims'>(inst)</div><div class='xr-var-dtype'>&lt;U1</div><div class='xr-var-preview xr-preview'>&#x27;X&#x27; &#x27;Y&#x27; &#x27;Z&#x27;</div><input id='attrs-ef7c3dc9-874c-40ed-ab5c-9c0402f5e8d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef7c3dc9-874c-40ed-ab5c-9c0402f5e8d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-066c60ba-ff66-4806-aaea-85bda9bc45ef' class='xr-var-data-in' type='checkbox'><label for='data-066c60ba-ff66-4806-aaea-85bda9bc45ef' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Instrument Reference Frame</dd><dt><span>coverage_content_type :</span></dt><dd>coordinate</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;&lt;U1&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3e08e4ce-addd-4dde-bb8c-e052c116ec16' class='xr-section-summary-in' type='checkbox'  ><label for='section-3e08e4ce-addd-4dde-bb8c-e052c116ec16' class='xr-section-summary' >Data variables: <span>(15)</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>beam2inst_orientmat</span></div><div class='xr-var-dims'>(x1, x2)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.709 -1.34 ... -0.3438 -0.3499</div><input id='attrs-2b1ee1c9-2f2f-4deb-8665-bddb8e40a794' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b1ee1c9-2f2f-4deb-8665-bddb8e40a794' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4920e390-eada-47a9-aa42-dba8ff8dff99' class='xr-var-data-in' type='checkbox'><label for='data-4920e390-eada-47a9-aa42-dba8ff8dff99' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Rotation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[ 2.70874023, -1.34008789, -1.36376953],\n",
        "       [ 0.0144043 , -2.38354492,  2.39550781],\n",
-       "       [-0.3371582 , -0.34375   , -0.34985352]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.2 13.2 13.2 13.2 ... nan nan nan</div><input id='attrs-2bcccc71-1567-480c-b0b9-61d004183c43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bcccc71-1567-480c-b0b9-61d004183c43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe3b2440-f8a7-44a4-b327-610780e4fede' class='xr-var-data-in' type='checkbox'><label for='data-fe3b2440-f8a7-44a4-b327-610780e4fede' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd></dl></div><div class='xr-var-data'><pre>array([13.2, 13.2, 13.2, ...,  nan,  nan,  nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.493e+03 1.493e+03 ... nan nan</div><input id='attrs-88a00cb0-9f42-4512-875b-02ce0180bdfb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88a00cb0-9f42-4512-875b-02ce0180bdfb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5eba7309-e4be-49a0-8103-bda5c9a6a882' class='xr-var-data-in' type='checkbox'><label for='data-5eba7309-e4be-49a0-8103-bda5c9a6a882' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1492.6, 1492.6, 1492.6, ...,    nan,    nan,    nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.6 10.5 10.51 ... nan nan nan</div><input id='attrs-934bf703-c4af-4b51-8be4-f5bb39f22110' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-934bf703-c4af-4b51-8be4-f5bb39f22110' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3150725-0e7c-41e4-b90b-b0294a506154' class='xr-var-data-in' type='checkbox'><label for='data-e3150725-0e7c-41e4-b90b-b0294a506154' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([ 5.6   , 10.5   , 10.5125, ...,     nan,     nan,     nan],\n",
-       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-31.5 -31.7 -31.69 ... nan nan nan</div><input id='attrs-18a84e42-faf7-43fa-8490-59e7c7a80cc3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18a84e42-faf7-43fa-8490-59e7c7a80cc3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b639c587-e96f-4ea6-a0c7-94d62164fed8' class='xr-var-data-in' type='checkbox'><label for='data-b639c587-e96f-4ea6-a0c7-94d62164fed8' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-31.5     , -31.7     , -31.690626, ...,        nan,        nan,\n",
-       "              nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.4 4.2 4.253 4.306 ... nan nan nan</div><input id='attrs-794337fa-600a-4d35-b22d-e31c55423ee7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-794337fa-600a-4d35-b22d-e31c55423ee7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec668ea4-cfd1-4718-8be1-a9bfbe835b10' class='xr-var-data-in' type='checkbox'><label for='data-ec668ea4-cfd1-4718-8be1-a9bfbe835b10' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([0.4      , 4.2000003, 4.253125 , ...,       nan,       nan,\n",
-       "             nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.67 12.68 12.68 ... nan nan nan</div><input id='attrs-3393c28f-dc0b-4a89-bcdd-38c27e41c1d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3393c28f-dc0b-4a89-bcdd-38c27e41c1d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0da2002f-37f4-4f9d-9f63-86ea762ad62f' class='xr-var-data-in' type='checkbox'><label for='data-0da2002f-37f4-4f9d-9f63-86ea762ad62f' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.67    , 12.679999, 12.679999, ...,       nan,       nan,\n",
-       "             nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-47ac15bd-976d-49a8-ac65-056b3339ef0c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47ac15bd-976d-49a8-ac65-056b3339ef0c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93b498cd-4a7a-4c22-8c4a-a4fb05ed46c2' class='xr-var-data-in' type='checkbox'><label for='data-93b498cd-4a7a-4c22-8c4a-a4fb05ed46c2' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>117 117 0 0 0 0 0 ... 0 0 0 0 0 0 0</div><input id='attrs-7f7e0b48-7b52-4808-b19f-afdcb4f3d1d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7f7e0b48-7b52-4808-b19f-afdcb4f3d1d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94b86848-d601-4a70-b1bd-1752ae510922' class='xr-var-data-in' type='checkbox'><label for='data-94b86848-d601-4a70-b1bd-1752ae510922' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([117, 117,   0, ...,   0,   0,   0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientation_down</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... True True True</div><input id='attrs-bc9f65f8-aeba-45b9-a6bb-a98c779981ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc9f65f8-aeba-45b9-a6bb-a98c779981ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-414598a4-4bf4-4591-aa3d-8d97ef9ca805' class='xr-var-data-in' type='checkbox'><label for='data-414598a4-4bf4-4591-aa3d-8d97ef9ca805' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation of ADV Communication Cable</dd></dl></div><div class='xr-var-data'><pre>array([ True,  True,  True, ...,  True,  True,  True])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.002 -1.008 -0.944 ... nan nan</div><input id='attrs-11c7a60f-ba17-4310-9b5e-88739d6c346e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11c7a60f-ba17-4310-9b5e-88739d6c346e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e091640-0aa9-464a-a029-eda53841c7a8' class='xr-var-data-in' type='checkbox'><label for='data-5e091640-0aa9-464a-a029-eda53841c7a8' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[-1.0020001 , -1.008     , -0.94400007, ...,         nan,\n",
+       "       [-0.3371582 , -0.34375   , -0.34985352]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>batt</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>13.2 13.2 13.2 13.2 ... nan nan nan</div><input id='attrs-263ad97e-6609-4b97-8a9a-2b284d360e8b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-263ad97e-6609-4b97-8a9a-2b284d360e8b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3aa62f8e-38ab-49bd-8cb0-69d33b58de48' class='xr-var-data-in' type='checkbox'><label for='data-3aa62f8e-38ab-49bd-8cb0-69d33b58de48' title='Show/Hide data repr'><svg 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>V</dd><dt><span>long_name :</span></dt><dd>Battery Voltage</dd></dl></div><div class='xr-var-data'><pre>array([13.2, 13.2, 13.2, ...,  nan,  nan,  nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>c_sound</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.493e+03 1.493e+03 ... nan nan</div><input id='attrs-a74bf210-4758-4600-ac6f-11a6edbb2e94' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a74bf210-4758-4600-ac6f-11a6edbb2e94' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0525a471-277b-4547-86a0-cf604d90170f' class='xr-var-data-in' type='checkbox'><label for='data-0525a471-277b-4547-86a0-cf604d90170f' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>long_name :</span></dt><dd>Speed of Sound</dd><dt><span>standard_name :</span></dt><dd>speed_of_sound_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([1492.6, 1492.6, 1492.6, ...,    nan,    nan,    nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heading</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>5.6 10.5 10.51 ... nan nan nan</div><input id='attrs-5da8e95c-4211-4fe9-b20d-2dac33649d5a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5da8e95c-4211-4fe9-b20d-2dac33649d5a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0dbad95-d153-4817-8070-ede5671b0907' class='xr-var-data-in' type='checkbox'><label for='data-c0dbad95-d153-4817-8070-ede5671b0907' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Heading</dd><dt><span>standard_name :</span></dt><dd>platform_orientation</dd></dl></div><div class='xr-var-data'><pre>array([ 5.6   , 10.5   , 10.5125, ...,     nan,     nan,     nan],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pitch</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-31.5 -31.7 -31.69 ... nan nan nan</div><input id='attrs-3ef0740f-8266-4d25-aeb6-3cc263938214' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3ef0740f-8266-4d25-aeb6-3cc263938214' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6e3ebfb-39a5-4b7a-aa07-d2bf4fafe68e' class='xr-var-data-in' type='checkbox'><label for='data-c6e3ebfb-39a5-4b7a-aa07-d2bf4fafe68e' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Pitch</dd><dt><span>standard_name :</span></dt><dd>platform_pitch</dd></dl></div><div class='xr-var-data'><pre>array([-31.5     , -31.7     , -31.690626, ...,        nan,        nan,\n",
+       "              nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>roll</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.4 4.2 4.253 4.306 ... nan nan nan</div><input id='attrs-5fc088f6-adab-439c-8204-9dbf88e9f723' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5fc088f6-adab-439c-8204-9dbf88e9f723' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dd7b50be-047a-41c7-8a5d-0348cb55fb1d' class='xr-var-data-in' type='checkbox'><label for='data-dd7b50be-047a-41c7-8a5d-0348cb55fb1d' title='Show/Hide data repr'><svg 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>degree</dd><dt><span>long_name :</span></dt><dd>Roll</dd><dt><span>standard_name :</span></dt><dd>platform_roll</dd></dl></div><div class='xr-var-data'><pre>array([0.4      , 4.2000003, 4.253125 , ...,       nan,       nan,\n",
+       "             nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>temp</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>12.67 12.68 12.68 ... nan nan nan</div><input id='attrs-63e57ca1-2e88-4ba7-8053-b3912e0ab171' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63e57ca1-2e88-4ba7-8053-b3912e0ab171' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67abeff0-95a1-4762-ba4f-15402ce0f38a' class='xr-var-data-in' type='checkbox'><label for='data-67abeff0-95a1-4762-ba4f-15402ce0f38a' title='Show/Hide data repr'><svg 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>degree_C</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>standard_name :</span></dt><dd>sea_water_temperature</dd></dl></div><div class='xr-var-data'><pre>array([12.67    , 12.679999, 12.679999, ...,       nan,       nan,\n",
+       "             nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</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-f8cee5e3-de9d-4109-90a6-f692907fd05a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f8cee5e3-de9d-4109-90a6-f692907fd05a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-570ddb23-000b-4f99-a97b-5209d370f706' class='xr-var-data-in' type='checkbox'><label for='data-570ddb23-000b-4f99-a97b-5209d370f706' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Error Code</dd></dl></div><div class='xr-var-data'><pre>array([0, 0, 0, ..., 0, 0, 0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>117 117 0 0 0 0 0 ... 0 0 0 0 0 0 0</div><input id='attrs-d09d38f6-3cae-46d2-b04a-b594fa9b78ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d09d38f6-3cae-46d2-b04a-b594fa9b78ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77ca7672-4a44-42ab-88e2-55fbbcc3612b' class='xr-var-data-in' type='checkbox'><label for='data-77ca7672-4a44-42ab-88e2-55fbbcc3612b' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Status Code</dd></dl></div><div class='xr-var-data'><pre>array([117, 117,   0, ...,   0,   0,   0], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientation_down</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>True True True ... True True True</div><input id='attrs-544628c5-92e8-4392-8aa9-1c7388cadd15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-544628c5-92e8-4392-8aa9-1c7388cadd15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ef12bcf-8df8-42db-81b4-9870411da08f' class='xr-var-data-in' type='checkbox'><label for='data-5ef12bcf-8df8-42db-81b4-9870411da08f' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation of ADV Communication Cable</dd></dl></div><div class='xr-var-data'><pre>array([ True,  True,  True, ...,  True,  True,  True])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vel</span></div><div class='xr-var-dims'>(dir, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-1.002 -1.008 -0.944 ... nan nan</div><input id='attrs-631a9c64-11b6-4fa7-8999-7b90329b6b0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-631a9c64-11b6-4fa7-8999-7b90329b6b0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b771b434-6dc7-44b1-a762-d639dec810e0' class='xr-var-data-in' type='checkbox'><label for='data-b771b434-6dc7-44b1-a762-d639dec810e0' title='Show/Hide data repr'><svg 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>m s-1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Water Velocity</dd></dl></div><div class='xr-var-data'><pre>array([[-1.0020001 , -1.008     , -0.94400007, ...,         nan,\n",
        "                nan,         nan],\n",
        "       [ 0.097     ,  0.068     ,  0.066     , ...,         nan,\n",
        "                nan,         nan],\n",
        "       [ 0.115     ,  0.12400001,  0.12200001, ...,         nan,\n",
-       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>104 110 111 113 108 ... 0 0 0 0 0</div><input id='attrs-0655a29d-41a3-4387-9fdc-078e764be95a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0655a29d-41a3-4387-9fdc-078e764be95a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf0fb6c1-812d-49c4-b610-b525915b68de' class='xr-var-data-in' type='checkbox'><label for='data-bf0fb6c1-812d-49c4-b610-b525915b68de' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[104, 110, 111, ...,   0,   0,   0],\n",
+       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>amp</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>104 110 111 113 108 ... 0 0 0 0 0</div><input id='attrs-93bb711a-80eb-4caf-929d-6d2d085ad2d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93bb711a-80eb-4caf-929d-6d2d085ad2d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a91f737-1df4-4d90-bcd2-8f5dda139dbb' class='xr-var-data-in' type='checkbox'><label for='data-8a91f737-1df4-4d90-bcd2-8f5dda139dbb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Amplitude</dd><dt><span>standard_name :</span></dt><dd>signal_intensity_from_multibeam_acoustic_doppler_velocity_sensor_in_sea_water</dd></dl></div><div class='xr-var-data'><pre>array([[104, 110, 111, ...,   0,   0,   0],\n",
        "       [109, 111, 118, ...,   0,   0,   0],\n",
-       "       [111, 107, 103, ...,   0,   0,   0]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>97 91 97 98 90 95 ... 0 0 0 0 0 0</div><input id='attrs-7b0e975c-ae0c-4e03-b4e4-9afc4acc6c83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7b0e975c-ae0c-4e03-b4e4-9afc4acc6c83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0756603e-649b-408e-a937-cfa5bc6f6842' class='xr-var-data-in' type='checkbox'><label for='data-0756603e-649b-408e-a937-cfa5bc6f6842' title='Show/Hide data repr'><svg 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>%</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd></dl></div><div class='xr-var-data'><pre>array([[97, 91, 97, ...,  0,  0,  0],\n",
+       "       [111, 107, 103, ...,   0,   0,   0]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>corr</span></div><div class='xr-var-dims'>(beam, time)</div><div class='xr-var-dtype'>uint8</div><div class='xr-var-preview xr-preview'>97 91 97 98 90 95 ... 0 0 0 0 0 0</div><input id='attrs-b8a48b3d-9b0e-4039-ab0f-7e28d1eba908' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b8a48b3d-9b0e-4039-ab0f-7e28d1eba908' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-518b49b5-1f1d-4001-b06f-cd350b76210a' class='xr-var-data-in' type='checkbox'><label for='data-518b49b5-1f1d-4001-b06f-cd350b76210a' title='Show/Hide data repr'><svg 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>%</dd><dt><span>coverage_content_type :</span></dt><dd>physicalMeasurement</dd><dt><span>long_name :</span></dt><dd>Acoustic Signal Correlation</dd></dl></div><div class='xr-var-data'><pre>array([[97, 91, 97, ...,  0,  0,  0],\n",
        "       [97, 97, 98, ...,  0,  0,  0],\n",
-       "       [96, 97, 97, ...,  0,  0,  0]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.448 5.436 5.484 ... 0.0 0.0 0.0</div><input id='attrs-756c52ce-bdcf-4254-99a0-2f59bc9ad8e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-756c52ce-bdcf-4254-99a0-2f59bc9ad8e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa34594e-3b4b-463c-9710-a427c1061f99' class='xr-var-data-in' type='checkbox'><label for='data-fa34594e-3b4b-463c-9710-a427c1061f99' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([5.448, 5.436, 5.484, ..., 0.   , 0.   , 0.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0832 0.155 ... -0.7065 -0.7065</div><input id='attrs-e31b437f-e553-4b49-81e8-e19d2950d0b2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e31b437f-e553-4b49-81e8-e19d2950d0b2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8beb5151-85c5-4a6c-92e8-5ed8bdf15e39' class='xr-var-data-in' type='checkbox'><label for='data-8beb5151-85c5-4a6c-92e8-5ed8bdf15e39' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.08320302,  0.155048  ,  0.15524618, ..., -0.8397447 ,\n",
+       "       [96, 97, 97, ...,  0,  0,  0]], dtype=uint8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>pressure</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.448 5.436 5.484 ... 0.0 0.0 0.0</div><input id='attrs-5357668c-846e-4313-912a-16eb49435232' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5357668c-846e-4313-912a-16eb49435232' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82f74f43-6271-4ea9-aed9-d6e7c39ccbfa' class='xr-var-data-in' type='checkbox'><label for='data-82f74f43-6271-4ea9-aed9-d6e7c39ccbfa' title='Show/Hide data repr'><svg 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>dbar</dd><dt><span>long_name :</span></dt><dd>Pressure</dd><dt><span>standard_name :</span></dt><dd>sea_water_pressure</dd></dl></div><div class='xr-var-data'><pre>array([5.448, 5.436, 5.484, ..., 0.   , 0.   , 0.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>orientmat</span></div><div class='xr-var-dims'>(earth, inst, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0832 0.155 ... -0.7065 -0.7065</div><input id='attrs-230a8957-52a6-447f-8bce-cf4ea75cadcb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-230a8957-52a6-447f-8bce-cf4ea75cadcb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b4a941f-8da4-48e6-9dca-afc119f93acb' class='xr-var-data-in' type='checkbox'><label for='data-3b4a941f-8da4-48e6-9dca-afc119f93acb' title='Show/Hide data repr'><svg 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>1</dd><dt><span>long_name :</span></dt><dd>Orientation Matrix</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.08320302,  0.155048  ,  0.15524618, ..., -0.8397447 ,\n",
        "         -0.8397447 , -0.8397447 ],\n",
        "        [ 0.8485708 ,  0.83656424,  0.8366149 , ...,  0.21873687,\n",
        "          0.21873687,  0.21873687],\n",
@@ -538,34 +529,55 @@
        "        [-0.51931095, -0.50193846, -0.5015614 , ..., -0.6639372 ,\n",
        "         -0.6639372 , -0.6639372 ],\n",
        "        [-0.85261935, -0.84852624, -0.84855384, ..., -0.7064614 ,\n",
-       "         -0.7064614 , -0.7064614 ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d20c6cef-7cb1-4219-b432-c5e93aafbc5f' class='xr-section-summary-in' type='checkbox'  ><label for='section-d20c6cef-7cb1-4219-b432-c5e93aafbc5f' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_model :</span></dt><dd>Vector</dd><dt><span>inst_type :</span></dt><dd>ADV</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;]</dd><dt><span>n_beams :</span></dt><dd>3</dd><dt><span>profile_mode :</span></dt><dd>continuous</dd><dt><span>burst_mode :</span></dt><dd>True</dd><dt><span>power_level :</span></dt><dd>1</dd><dt><span>sync_out_pos :</span></dt><dd>end</dd><dt><span>sample_on_sync :</span></dt><dd>False</dd><dt><span>start_on_sync :</span></dt><dd>False</dd><dt><span>compass_update_rate :</span></dt><dd>1</dd><dt><span>n_bins :</span></dt><dd>1</dd><dt><span>deployment_name :</span></dt><dd>APLUW_</dd><dt><span>wrap_mode :</span></dt><dd>False</dd><dt><span>analog_in :</span></dt><dd>0</dd><dt><span>software_version :</span></dt><dd>1.32.00</dd><dt><span>salinity :</span></dt><dd>30.0</dd><dt><span>comments :</span></dt><dd>APL-UW vector on Tidal Turbulence Mooring in Admiralty, times PDT</dd><dt><span>user_specified_sound_speed :</span></dt><dd>False</dd><dt><span>analog_output :</span></dt><dd>False</dd><dt><span>output_format :</span></dt><dd>Vector</dd><dt><span>serial_output :</span></dt><dd>False</dd><dt><span>power_output_analog :</span></dt><dd>False</dd><dt><span>n_pings_per_burst :</span></dt><dd>1</dd><dt><span>pressure_sensor :</span></dt><dd>yes</dd><dt><span>compass :</span></dt><dd>yes</dd><dt><span>tilt_sensor :</span></dt><dd>yes</dd><dt><span>carrier_freq_kHz :</span></dt><dd>6000</dd><dt><span>serial_number :</span></dt><dd>VEC 9062</dd><dt><span>ProLogFWver :</span></dt><dd>4.08</dd><dt><span>PIC_version :</span></dt><dd>0</dd><dt><span>hardware_rev :</span></dt><dd>4</dd><dt><span>recorder_size_bytes :</span></dt><dd>4074766336</dd><dt><span>vel_range :</span></dt><dd>normal</dd><dt><span>firmware_version :</span></dt><dd>3.34</dd><dt><span>fs :</span></dt><dd>32.0</dd><dt><span>coord_sys :</span></dt><dd>inst</dd><dt><span>has_imu :</span></dt><dd>0</dd></dl></div></li></ul></div></div>"
+       "         -0.7064614 , -0.7064614 ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6f1ba555-edef-45d9-b169-ddc6c3dc1a88' class='xr-section-summary-in' type='checkbox'  ><label for='section-6f1ba555-edef-45d9-b169-ddc6c3dc1a88' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-65381aff-588f-4349-8e3d-111862e88e52' class='xr-index-data-in' type='checkbox'/><label for='index-65381aff-588f-4349-8e3d-111862e88e52' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2012-06-12 12:00:02.968749523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:02.999999523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.031249523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.062499523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.093749523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.124999523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.156249523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.187499523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.218749523&#x27;,\n",
+       "               &#x27;2012-06-12 12:00:03.249999523&#x27;,\n",
+       "               ...\n",
+       "               &#x27;2012-06-12 13:04:03.656251192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.687501192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.718751192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.750001192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.781251192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.812501192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.843751192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.875001192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.906251192&#x27;,\n",
+       "               &#x27;2012-06-12 13:04:03.937501192&#x27;],\n",
+       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=122912, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>beam</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-31972ea3-1bb6-44a4-8f49-49958c43c7c6' class='xr-index-data-in' type='checkbox'/><label for='index-31972ea3-1bb6-44a4-8f49-49958c43c7c6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;beam&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>dir</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bc9b8a45-b0e3-4e25-a051-0627b7cf814c' class='xr-index-data-in' type='checkbox'/><label for='index-bc9b8a45-b0e3-4e25-a051-0627b7cf814c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;dir&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x1</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cc5b0d9d-2c97-40b5-95ad-4fcfde3dbdc3' class='xr-index-data-in' type='checkbox'/><label for='index-cc5b0d9d-2c97-40b5-95ad-4fcfde3dbdc3' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;x1&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>x2</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-652173c2-04ed-40eb-83b1-b2df0a11cfcc' class='xr-index-data-in' type='checkbox'/><label for='index-652173c2-04ed-40eb-83b1-b2df0a11cfcc' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([1, 2, 3], dtype=&#x27;int32&#x27;, name=&#x27;x2&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>earth</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-603ae926-58b8-4727-a8bc-f14c3f708f85' class='xr-index-data-in' type='checkbox'/><label for='index-603ae926-58b8-4727-a8bc-f14c3f708f85' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;E&#x27;, &#x27;N&#x27;, &#x27;U&#x27;], dtype=&#x27;object&#x27;, name=&#x27;earth&#x27;))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>inst</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-53547ce3-3b2b-4b54-9712-b7be17de78b5' class='xr-index-data-in' type='checkbox'/><label for='index-53547ce3-3b2b-4b54-9712-b7be17de78b5' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([&#x27;X&#x27;, &#x27;Y&#x27;, &#x27;Z&#x27;], dtype=&#x27;object&#x27;, name=&#x27;inst&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a388cf79-a714-46c7-98ff-102697d2ae28' class='xr-section-summary-in' type='checkbox'  ><label for='section-a388cf79-a714-46c7-98ff-102697d2ae28' class='xr-section-summary' >Attributes: <span>(39)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>inst_make :</span></dt><dd>Nortek</dd><dt><span>inst_model :</span></dt><dd>Vector</dd><dt><span>inst_type :</span></dt><dd>ADV</dd><dt><span>rotate_vars :</span></dt><dd>[&#x27;vel&#x27;]</dd><dt><span>n_beams :</span></dt><dd>3</dd><dt><span>profile_mode :</span></dt><dd>continuous</dd><dt><span>burst_mode :</span></dt><dd>True</dd><dt><span>power_level :</span></dt><dd>1</dd><dt><span>sync_out_pos :</span></dt><dd>end</dd><dt><span>sample_on_sync :</span></dt><dd>False</dd><dt><span>start_on_sync :</span></dt><dd>False</dd><dt><span>compass_update_rate :</span></dt><dd>1</dd><dt><span>n_bins :</span></dt><dd>1</dd><dt><span>deployment_name :</span></dt><dd>APLUW_</dd><dt><span>wrap_mode :</span></dt><dd>False</dd><dt><span>analog_in :</span></dt><dd>0</dd><dt><span>software_version :</span></dt><dd>1.32.00</dd><dt><span>salinity :</span></dt><dd>30.0</dd><dt><span>comments :</span></dt><dd>APL-UW vector on Tidal Turbulence Mooring in Admiralty, times PDT</dd><dt><span>user_specified_sound_speed :</span></dt><dd>False</dd><dt><span>analog_output :</span></dt><dd>False</dd><dt><span>output_format :</span></dt><dd>Vector</dd><dt><span>serial_output :</span></dt><dd>False</dd><dt><span>power_output_analog :</span></dt><dd>False</dd><dt><span>n_pings_per_burst :</span></dt><dd>1</dd><dt><span>pressure_sensor :</span></dt><dd>yes</dd><dt><span>compass :</span></dt><dd>yes</dd><dt><span>tilt_sensor :</span></dt><dd>yes</dd><dt><span>carrier_freq_kHz :</span></dt><dd>6000</dd><dt><span>serial_number :</span></dt><dd>VEC 9062</dd><dt><span>ProLogFWver :</span></dt><dd>4.08</dd><dt><span>PIC_version :</span></dt><dd>0</dd><dt><span>hardware_rev :</span></dt><dd>4</dd><dt><span>recorder_size_bytes :</span></dt><dd>4074766336</dd><dt><span>vel_range :</span></dt><dd>normal</dd><dt><span>firmware_version :</span></dt><dd>3.34</dd><dt><span>fs :</span></dt><dd>32.0</dd><dt><span>coord_sys :</span></dt><dd>inst</dd><dt><span>has_imu :</span></dt><dd>0</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset>\n",
-       "Dimensions:              (x1: 3, x2: 3, time: 122912, dir: 3, beam: 3,\n",
+       "<xarray.Dataset> Size: 12MB\n",
+       "Dimensions:              (time: 122912, beam: 3, dir: 3, x1: 3, x2: 3,\n",
        "                          earth: 3, inst: 3)\n",
        "Coordinates:\n",
-       "  * x1                   (x1) int32 1 2 3\n",
-       "  * x2                   (x2) int32 1 2 3\n",
-       "  * time                 (time) datetime64[ns] 2012-06-12T12:00:02.968749046 ...\n",
-       "  * dir                  (dir) <U1 'X' 'Y' 'Z'\n",
-       "  * beam                 (beam) int32 1 2 3\n",
-       "  * earth                (earth) <U1 'E' 'N' 'U'\n",
-       "  * inst                 (inst) <U1 'X' 'Y' 'Z'\n",
+       "  * time                 (time) datetime64[ns] 983kB 2012-06-12T12:00:02.9687...\n",
+       "  * beam                 (beam) int32 12B 1 2 3\n",
+       "  * dir                  (dir) <U1 12B 'X' 'Y' 'Z'\n",
+       "  * x1                   (x1) int32 12B 1 2 3\n",
+       "  * x2                   (x2) int32 12B 1 2 3\n",
+       "  * earth                (earth) <U1 12B 'E' 'N' 'U'\n",
+       "  * inst                 (inst) <U1 12B 'X' 'Y' 'Z'\n",
        "Data variables: (12/15)\n",
-       "    beam2inst_orientmat  (x1, x2) float64 2.709 -1.34 -1.364 ... -0.3438 -0.3499\n",
-       "    batt                 (time) float32 13.2 13.2 13.2 13.2 ... nan nan nan nan\n",
-       "    c_sound              (time) float32 1.493e+03 1.493e+03 ... nan nan\n",
-       "    heading              (time) float32 5.6 10.5 10.51 10.52 ... nan nan nan nan\n",
-       "    pitch                (time) float32 -31.5 -31.7 -31.69 ... nan nan nan\n",
-       "    roll                 (time) float32 0.4 4.2 4.253 4.306 ... nan nan nan nan\n",
+       "    beam2inst_orientmat  (x1, x2) float64 72B 2.709 -1.34 ... -0.3438 -0.3499\n",
+       "    batt                 (time) float32 492kB 13.2 13.2 13.2 ... nan nan nan\n",
+       "    c_sound              (time) float32 492kB 1.493e+03 1.493e+03 ... nan nan\n",
+       "    heading              (time) float32 492kB 5.6 10.5 10.51 ... nan nan nan\n",
+       "    pitch                (time) float32 492kB -31.5 -31.7 -31.69 ... nan nan nan\n",
+       "    roll                 (time) float32 492kB 0.4 4.2 4.253 ... nan nan nan\n",
        "    ...                   ...\n",
-       "    orientation_down     (time) bool True True True True ... True True True True\n",
-       "    vel                  (dir, time) float32 -1.002 -1.008 -0.944 ... nan nan\n",
-       "    amp                  (beam, time) uint8 104 110 111 113 108 ... 0 0 0 0 0\n",
-       "    corr                 (beam, time) uint8 97 91 97 98 90 95 95 ... 0 0 0 0 0 0\n",
-       "    pressure             (time) float64 5.448 5.436 5.484 5.448 ... 0.0 0.0 0.0\n",
-       "    orientmat            (earth, inst, time) float32 0.0832 0.155 ... -0.7065\n",
+       "    orientation_down     (time) bool 123kB True True True ... True True True\n",
+       "    vel                  (dir, time) float32 1MB -1.002 -1.008 ... nan nan\n",
+       "    amp                  (beam, time) uint8 369kB 104 110 111 113 ... 0 0 0 0\n",
+       "    corr                 (beam, time) uint8 369kB 97 91 97 98 90 ... 0 0 0 0 0\n",
+       "    pressure             (time) float64 983kB 5.448 5.436 5.484 ... 0.0 0.0 0.0\n",
+       "    orientmat            (earth, inst, time) float32 4MB 0.0832 ... -0.7065\n",
        "Attributes: (12/39)\n",
        "    inst_make:                   Nortek\n",
        "    inst_model:                  Vector\n",
@@ -791,8 +803,13 @@
     "\n",
     "For instance, \n",
     "- `bin_variance` calculates the binned-variance of each variable in the raw dataset, the complementary to `bin_average`. Variables returned by this function contain a \"_var\" suffix to their name.\n",
-    "- `cross_spectral_density` calculates the cross spectral power density between each direction of the supplied DataArray. Note that inputs specified in creating the `ADVBinner` object can be overridden or additionally specified for a particular function call.\n",
-    "- `velds.I` is the shortcut for turbulence intensity. This particular shortcut requires a dataset created by `bin_average`, because it requires bin-averaged data to calculate.\n"
+    "- `turbulence_intensity` is calculated from the ratio of the standard deviation of the horizontal velocity magnitude (equivalent to the RMS of turbulent velocity fluctuations) to the mean of the horizontal velocity magnitude\n",
+    "- `power_spectral_density` calculates the power spectral density (velocity spectra) of the velocity vector\n",
+    "- `cross_spectral_density` calculates the cross spectral density between each direction of the supplied DataArray. Note that inputs specified in creating the `ADVBinner` object can be overridden or additionally specified for a particular function call.\n",
+    "- `dissipation_rate_LT83` uses the Lumley and Terray 1983 algorithm to estimate the TKE dissipation rate from the isoropic turbulence cascade seen in the spectral. This requires the frequency range of the cascade as input.\n",
+    "- `turbulent_kinetic_energy` calculates the TKE (Reynolds normal stress) components\n",
+    "- `reynolds_stress` calculates the Reynolds shear stress components\n",
+    "\n"
    ]
   },
   {
@@ -806,20 +823,25 @@
     "# Calculate the variance of each variable in the dataset and add to the averaged dataset\n",
     "ds_binned = binner.bin_variance(ds, out_ds=ds_binned)\n",
     "\n",
+    "# Calculate the turbulence intensity\n",
+    "ds_binned[\"TI\"] = binner.turbulence_intensity(ds.velds.U_mag)\n",
+    "\n",
     "# Calculate the power spectral density\n",
     "ds_binned[\"auto_spectra\"] = binner.power_spectral_density(ds[\"vel\"], freq_units=\"Hz\")\n",
-    "# Calculate dissipation rate from isotropic turbulence cascade\n",
-    "ds_binned[\"dissipation\"] = binner.dissipation_rate_LT83(\n",
-    "    ds_binned[\"auto_spectra\"], ds_binned.velds.U_mag, freq_range=[0.5, 1]\n",
-    ")\n",
     "\n",
     "# Calculate the cross power spectral density\n",
     "ds_binned[\"cross_spectra\"] = binner.cross_spectral_density(\n",
     "    ds[\"vel\"], freq_units=\"Hz\", n_fft_coh=512\n",
     ")\n",
     "\n",
-    "# Calculated the turbulence intensity (requires a binned dataset)\n",
-    "ds_binned[\"TI\"] = ds_binned.velds.I"
+    "# Calculate dissipation rate from isotropic turbulence cascade\n",
+    "ds_binned[\"dissipation\"] = binner.dissipation_rate_LT83(\n",
+    "    ds_binned[\"auto_spectra\"], ds_binned.velds.U_mag, freq_range=[0.5, 1]\n",
+    ")\n",
+    "\n",
+    "# Calculate the Reynolds stresses\n",
+    "ds_binned['tke_vec'] = binner.turbulent_kinetic_energy(ds[\"vel\"])\n",
+    "ds_binned['stress_vec'] = binner.reynolds_stress(ds[\"vel\"])\n"
    ]
   },
   {
@@ -847,14 +869,12 @@
     },
     {
      "data": {
-      "image/png": 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sYKBEREREZAcDJSIiIiI7GCgRERER2cFAyQUrVqxAamoqBg4c6O2lEBERUSMSRFEUvb0IX1VaWoqIiAiUlJRwU1wbDmcWYf2By5jSOwmjusR5ezlEREQAnPv9rWiiNVELcuZqGV7bfAZbTuYCAH45lYs9T4xFYIDcyysjIiJyDgMl8pjLhZVYvuUsNh7JgigCMgEIVipQUFGDLw9dwZwh7by9RCIiIqewR4nclldWjWe/PY6xr2/H12n6IGlKr0RsXjIKj07qCgB4f+dFaLQ6L6+UiIjIOcwokctKqmrx3s4L+Gj3JVTVagEAIzrH4rFJ3dCrdQQAoFVkEP699RwyCyvx0/GrmNon2ZtLJiIicgoDJXJaVY0Wa367hFU7LqCkqhYA0K9tJB6b1A1DO8aYHRuklGPu0BQs/+UsVu24gJt6J0EQBG8sm4iIyGkMlMhhtVodPj94Gf/Zeg55ZWoAQJeEUCyd2BUTUhPsBkB3Dm2HVTsu4ER2KXafz8eIzrwDjoiIfAMDJWqQTifif39k440tZ5FZWAkAaB0VhIcndMH0vq0gl9WfIYoKUeJPg9pg9Z5LWLn9AgMlIiLyGQyUyC5RFPHr6Ty8uukMTl8tAwDEhqrw17GdcMegtlAqHL8X4O4RHbB2bwZ+u1CAo1eK0bt1ZCOtmoiIyHMYKJFN+y8WYNmmMziUUQQACAtUYOGojrhreAqClc5/bFpFBmFan2R8nZaFVTsu4J2/9Pf0komIiDyOgRKZOZ5Vglc3ncGOs9cAAIEBMswb1h4LR3VAZLDSrXPfN6ojvk7Lwk/HryI9vwLtY0M8sWQiIqJGw0CJAADp+RV4ffMZfH80BwCgkAn406A2+OvYzkgID/TINbomhmFst3j8ejoP7+28iFdm9vLIeYmIiBoLA6UWLqekCm9tPYcvfr8CrU6EIADT+iTj4Qld0C7G8xmfhaM64tfTedhw+AqWTOiM+DDPBGFERESNgYFSC1VUUYN3tp/Hx3szUKPRT8we1y0eSyd1Rfekxtvgd2BKFK5rG4nDmcVYvecSHr+hW6Ndi4iIyF0MlFqYcrUGH+5Kx/u7LqJcrQEADGofjccmdcWAlOhGv74gCFg4qiPuXXsI/92XgftHd0RYYECjX5eIiMgVDJRaCLVGi0/3ZWLFtvMoqKgBAPRIDsejk7piVJe4Jp2WPb57AjrFh+J8Xjk+25+J+0Z1bLJrExEROYOBkp/TaHX4Oi0L//7lHLKKqwAA7WND8PCELrixVxJkDQyLbAwymYB7R3bAY18dxYe70zFveApUCnmTr4OIiKghDJT8lCiK+Pn4Vby2+QwuXKsAACSGB2Lx+M6Y1b81AuSOD4tsDDf3bYU3Np/F1dJqfJOWhdsHtvXqeoiIiGxhoOSHdp/Lx7JNp3H0SgkAIDI4APeP7og7h6YgMKB5ZG6UChkWXN8e//jxFN7deRG39m/jlewWOUcURehENLhtDRGRv2Cg5EeOXC7Gsp9P47cLBQCAYKUcd1/fHneP7IDwZtgwfcfgtvjPr+dw8VoFNp/MxQ09E729JKqHTidixjt7UFJVi//99fpm+ZkiIvI0Bkp+4GxuGV7bdAabT+YCAJRyGf4ypC0WjemE2FCVl1dnX6hKgTlD22HFtgtYteMCJvVIaNKmcnLO4cwi/GHIUn64Kx1LJnTx8oqIiBofAyUfdrmwEm/+cg4b065AJwIyAbjlutZYPL4zWkcFe3t5Dpk3rD3e35WOI5eLsT+9EEM6xHh7SWTHT8evGv/+0e50zBuWgqgQ97a1ISJq7hgo+aBrZWqs2HYen+7PQK1WBADc0CMRSyd1Qaf4MC+vzjlxYSrc2r81Pt2fiVU7LjBQaqakmwMAIEQpR5lag/d2XeTAUCLye9699YmcUlpdi9c2ncGoV7dhzW+XUKsVcX2nWHy7aDhWzenvc0GS5N6RHSATgO1nruFUTqm3l0M2HL1SgqziKgQr5Vg2qw8AYM2eS7hWpvbyyoiIGhcDJR9QVaPFqh0XMOJf2/D2tvOorNGiT5tIfHb3YPz37sHo0ybS20t0S7uYEEzulQQAeHfHBS+vhmz58bh+s+Qx3eIxpVci+raJRFWtFiu3878XEfk3BkrNWK1Wh0/3Z2D0a9vwz59Oo6SqFp3jQ/HunP745v5hGNYp1ttL9Jj/M0zn/u5oDi4XVnp5NWTKtOw2pWcSBEHAIxP1jdz/3Z+BnJIqby6PiKhRMVBqhnQ6Ed8eycKEN3bg6Y3HkVuqRqvIILx+ax/8/NBITOqR6Hd3h/VsFYHrO8VCqxPx4e50by+HTJzMKUVGQSVUChlGd40DAFzfKRaD2kejRqPD27+e9/IKiYgaDwOlZuiF709i8edHcKmgErGhSjw3NRW/Lh2FW/q39utBfwsNWaXPD2ai0LAfHXnfT8f02aTRXeMQotLf/yEIAh4xjAdYf/Ays4BE5LcYKDVDs/q3RnigAksndsGOR8dg3vD2LWIvtOGdYtCzVTiqa3X4+LdL3l4OQV92k/qTphj6yCSDO8RgROdYaHQi/r31nDeWR0TU6BgoNUM9W0Vg31Pj8MDYzsZ/wbcEgiAYs0of772EyhqNl1dE5/LKcfFaBZRyGcZ2i7d6/ZGJXQEAXx++ggvXypt6eUREjY6BUjMVrGw5AZKpyT2T0C4mGMWVtVh/8LK3l9PiSWW3EZ1jEWZjy5K+bSIxvns8dCLw71+YVSIi/8NAiZoVuUzAPSM6AAA+2JWOWq3Oyytq2X4ylN3q24dP2srku6PZOH2Vc7CIyL8wUKJmZ1b/1ogNVSKruArfH8329nJarIvXynH6ahkUMgETUhPsHtcjOQI39kqCKALLt5xtwhUSETU+BkrU7AQGyHHX8PYAgHd3XIQoil5eUcsk7e02rFMsIoPr39Nt8fjOAIAtJ3PZW0ZEfoWBEjVLswe3Q4hSjtNXy7D9zDVvL6dFkspuk+spu0m6JIQhNlQFnQicuVrW2EsjImoyDJRcsGLFCqSmpmLgwIHeXorfiggOwJ8HtwUArOS2Jk3ucmEljmeVQiYAE+spu5lKTQ4HoB9QSUTkLxgouWDRokU4efIkDh486O2l+LUF13dAgFzAgfRCHM4s8vZyWhQpmzSkQwxiQlUOvSc1yRAoZTNQIiL/wUCJmq3EiEDc3LcVAGAVN19tUj8axgI4UnaTMKNERP6IgRI1a/eN0o8K2HIqF+fzONCwKWQXV+HI5WIIAjCphxOBkiGjdOZqGbQ6NuATkX9goETNWqf4MExITYAoAu/tZFapKfxsuNttQLsoxIcHOvy+9rEhCAyQobJGi4yCisZaHhFRk2KgRM2etK3JxrQsXC2p9vJq/J8UKE3umdTAkebkMgFdE1l+IyL/wkCJmr3+7aIwKCUatVoRH+1J9/Zy/FpeWTUOZhQCqH8atz1s6CYif8NAiXzCwtH6XqXP9meipKrWy6vxX5tO5EIU9Xu4JUcGOf1+NnQTkb9hoEQ+YUzXeHRNCEO5WoP/7svw9nL81ndH9FvGTOnlfDYJYEaJiPwPAyXyCYIgGO+AW73nEqprtV5ekf+5XFiJA5cKIQjA1D7JLp2jW2IYBAHIK1PjWpnawyskImp6DJTIZ0ztk4xWkUHIL1djw+Er3l6O3/n2SBYAYFjHGCRFOF92A4AQlQLtY0IAAKdYfiMiP8BAiXxGgFyGBdfrN8t9f+dFzurxIFEU8XWaPlCShny6qjv7lIjIjzBQIp/yp0FtEBkcgEsFlcbb2Ml9R6+U4OK1CgQGyDC5l3NjASxJfUrMKBGRP2CgRD4lWKnAnUNTAACrdlyAKDKr5AkbDdmkiamJCFUp3DqX8c43NnQTkR9goEQ+Z96wFAQGyHAsqwS/XSjw9nJ8Xq1Wh+/+0N/tNqOfe2U3oC6jdOFaOZvuicjnMVAinxMdosTtA9oA0GeVyD27z+WjoKIGMSFKjOgc6/b54sNUiAlRQifq930jIvJlDJTIJ909ogPkMgG7zuXjeFaJt5fj06Qm7ql9kqGQu/8jQRAEDp4kIr/BQIl8UpvoYNzUW990zKyS68qqa7H5hL4pfuZ17pfdJBw8SUT+goES+az7Ruo3y/3xWA53q3fRz8evQq3RoWNcCHq1ivDYeZlRIiJ/wUCJfFZqcjhGdYmDTgTe33XR28vxSdLdbjP6tYIgCB47r+mIAB3nXRGRD2OgRD5t4Sh9VunL368gv5xbZjgjp6QKey/q7xqc7uaQSUvtY0OgUshQWaNFRmGlR89NRNSUGCiRTxvSIRp92kRCrdFhzZ5L3l6OT/n2SDZEERiUEo020cEePbdCLkO3xDAAHDxJRL6NgRL5NEEQ8H+GzXI/2XsJ5WqNl1fkG0RRxMbDhrKbB5u4TXHwJBH5AwZK5PMmpCaiQ2wISqs1+PxApreX4xNO5ZThTG4ZlHIZpvR0b8sSe7onsaGbiHwfAyXyeXKZgHtH6rNKH+xKR41G5+UVNX8b064AAMZ1j0dEcECjXIMjAojIHzBQIr8w47pWiA9T4WppNb49kuXt5TRrWp2Ib494bssSe7oZAqWrpdUoYKM9EfkoBkrkF1QKOeZf3x4A8O7Oi7wlvR6/XchHXpkakcEBGN01vtGuE6pSICVG3yR+KodbmRCRb2KgRH7jz4PbIkylwPm8cmw9neft5bitRqNDWXWtx88rNXHf1DsJSkXj/gioGzzJbWaIyDcxUCK/ER4YgL8MaQdAv62JKPp2VumO9/dhwEu/4L2dF6D1UIasskaDnw1bljRm2U3CPiUi8nUMlMivzB+eAqVChkMZRdh2xnezSjklVTiUUQS1RoeXfzyNWat+w/m8crfPu/lELiprtGgbHYzr2kZ5YKX141YmROTrGCiRX4kPD8Rdw1IAAC//eBoarW/eAbf/YiEAID5MhVCVAmmZxZjy1i68u8O97JK0ZcnNHt6yxJ7UJP3+cReuVaC6Vtvo1yMi8jQGSuR37h/TCVHBATifV451By97ezku2Z+u31rk5n6tsGnJSIzsEocajQ6v/HQat6z8DefznGuOTssswsK1h7Dj7DUATVN2A4CEcBWiQ5TQ6kScy3U/I0ZE1NQYKJHfiQgKwEPjuwAA3txytlEaohvbPkNGaXD7aLSKDMLHdw3Eslt6I0ylwJHLxZjy1m6s2nGh3oyZKIrYdiYPt7+7FzPe+c3Ym3TX8BS0jw1pkq9DEAS0NWyPkl1S1STXJCLyJAZK5Jf+PLgtOsSFoKCiBu9sv+Dt5Tjlakk10vMrIBOAASnRAPQBx20D22DzwyMxypBd+udPp3HLqr04l2ueXarV6vBNWhYm/3sX7lp9EPvTC6GQCbjlutbYvGQk/j61R5N+PdEhSgBAcWVNk16XiMgTGCiRXwqQy/Dk5O4AgA93p+NKke/sYC+V3XokRyAiyHxqdlJEENbcNRDLZvVGWKACf1wuxo1v7cY728+jrLoWq/ekY/Sr2/HQ+iM4fbUMIUo57r6+PXY+Ngav39YHXRLCmvzriTRM/i6s8L3MHhGRwtsLIGos47vHY0iHaOy7WIhXN53Bv//Uz9tLcsi+i/pAaUiHaJuvC4KA2wa0wYjOsXjq62PYduYalv18Bm9sPguNodE7JkSJu4anYM6QlEbbosRRUcHMKBGR72JGifyWIAh45sZUCALw7ZFsHLlc7O0lOUTqTxrSIabe45IigvDRvIF47dY+CAtUQKMT0TY6GC/e3BN7nhiLB8Z29nqQBNSV3ooYKBGRD2JGifxaz1YRmNGvFb4+nIV//HASX9w3tElui3dVbql1f1J9BEHArP6tMapLHM7mlmFw+2go5M3r3z8svRGRL2teP1GJGsGjk7oiMECGg5eKsMlw51dzJZXdbPUn1ScuTIXhnWKbXZAEsPRGRL6t+f1UJfKwpIgg3DOiAwDgnz+dRo2m+Q6hNB0L4C+kQImlNyLyRQyUqEW4b1RHxIaqcKmgEv/dl+Ht5di139jIXX9/ki+JCtFnxooqWXojIt/DQIlahFCVAo9M1A+hfOvXcyhphr+0c0urcTG/AoIADPTDjFJxZQ10Htrcl4ioqTBQohbjtgFt0DUhDMWVtfjPr+e8vRwrdf1J4U71JzV3UjO3TgTKqjVeXg0RkXMYKFGLIZcJeOpG/RDKj/deQkZBhZdXZM44FqC9/5TdAEClkCNEKQcAFLJPiYh8DAMlalFGdYnDyC5xqNWK+NfPp729HDPSRG5/6k+SRLKhm4h8FAMlanGentIdMgH48dhV/H6p0NvLAQDklVbj4jX/60+SGIdOVjBQIiLf4tLAyf/9739Ov2fChAkICgpy5XJEHtU1MQy3D2yDdQcu46UfTmHj/cO8PoRyX7o+YPO3/iSJ1KfEO9+IyNe4FCjdfPPNTh0vCALOnTuHDh06uHI5Io9bMqEL/mfY1uS7ozmY1ifZq+uRGrkH+1l/kkTKKHHoJBH5GpdLb1evXoVOp3PoT3BwsCfXTOS2+LBALBzVEQDwr59Oo7pW69X17PPD+UmmpBEBhSy9EZGPcSlQmjt3rlNltNmzZyM8PNyVSzVLK1asQGpqKgYOHOjtpZAb7h7RAYnhgcgqrsKa3y55bR2m/UmDHNjfzRex9EZEvsqlQGn16tUICwtz+PiVK1ciNjbWlUs1S4sWLcLJkydx8OBBby+F3BCklOPRSV0BACt+PY+CcrVX1iH1J6UmhSMi2P/6kwCW3ojId7l919vYsWPx/PPPWz1fVFSEsWPHunt6okY1o18r9GwVjjK1Bv/e6p0hlP64bYmlSJbeiMhHuR0obd++HW+//TZuvvlmVFTUDfCrqanBjh073D09UaOSyQQ8PSUVAPDp/kyczytv8jX4e38SAEQZMmXFLL0RkY/xyBylX375BVevXsWQIUNw6dIlT5ySqMkM7RiD8d0ToNWJ+OdPp5r02nll1bjg5/1JQF0zNwdOEpGv8UiglJSUhB07dqB3794YOHAgtm/f7onTEjWZJ6d0g0Im4JdTefjtQn6TXXe/YduS7on+258EAFEhdYGSKHJjXCLyHW4HStKgPpVKhU8//RSLFy/GDTfcgHfeecftxRE1lY5xofjL4LYAgH/8cKrJdrlvCWU3oK70VqsVUVHj3VEMRETOcDtQsvzX4TPPPINPP/0Ur7/+urunJmpSi8d3QVigAieyS/F1WlaTXLMuUPLfshsABAXIoVLof9xwGxMi8iVuB0rp6elWt/7fcsst2LdvHz766CN3T0/UZKJDlHhgTCcAwGubzqCqkTMf18rUdf1Jfri/mylBENinREQ+yeVAqbS0FKWlpYiKikJ5ebnxsfSnbdu2mDFjhifXStTo5g5LQeuoIFwtrcb7uy426rX2p+uzSd0Tw423z/szDp0kIl/k0l5vABAZGVnvRqKiKEIQBGi17Ecg3xEYIMfjN3TDX9elYdWOC/jTwDaIDw9slGu1lP4kCYdOEpEvcjlQ2rZtm/HvoihiypQp+OCDD9CqVSuPLIzIW27qnYSP9qQjLbMYb2w5i3/e0rtRrrPPcMebv/cnSbjfGxH5IpcDpVGjRpk9lsvlGDJkCDp06OD2ooi8SRAEPHNjd9yyci+++P0y5g1PQbdEz+5VeK1MjfN55S2iP0nC0hsR+SKPzFEi8jf920Xjxl5J0In6cQGeJvUndWsh/UkAS29E5JsYKBHZ8fgN3aCUy7DrXD62n8nz6LlbylgAU9zvjYh8kUcDpfqau4l8TduYYMwd1g4A8PKPp6DR6jx27v3G/qSW0cgNcL83IvJNLvcozZw50+xxdXU1Fi5ciJCQELPnv/76a1cvQeR1D4zpjC8PXcHZ3HKs//0y/jK4ndvnzC9X45yhP2lwC+lPAsy3MSEi8hUuB0oRERFmj2fPnu32Yoiam4jgACwe1xnPf3cSL35/Eq0igzC6a7xb55SySS2pPwkw2RiXpTci8iEuB0qrV6/25DqImq3ZQ9ph17l8/Ho6D/d88jvevL0fbuyd5PL5WmJ/ElBXeuNdb0TkS1zuUXrqqadw4MABT66FqFkKkMuwanZ/3NQ7CbVaEX9ddxjrD2a6fL6WNmhSIpXeqmq1qK7lIFoi8g0uB0o5OTm46aabkJSUhHvvvRc//PAD1Gq1J9dG1GwoFTL8+0/9cMegttCJwOMbjuEDF7Y4kfqTAGBQSsvKKIWpFFDI9Dd8sE+JiHyFy4HS6tWrkZubiy+++AKRkZF45JFHEBsbi5kzZ2LNmjXIz8/35DqJvE4uE/DyjJ64b6R+qOpLP5zCG5vPQBRFh89xIF3qTwozZlhaCkEQjD1ZRRUsvxGRb3BrPIAgCBgxYgSWLVuG06dP48CBAxgyZAjef/99tGrVCiNHjsRrr72GrKwsT62XyKsEQcATk7vh0UldAQBv/Xoez393EjqdY8FSSy27SepGBDCjRES+waNzlLp3747HHnsMe/bswZUrVzB37lzs2rUL69at8+RliLxKEAQsGtMJL07vAQBY89slLP3qD4fmLDFQMgydZKBERD7CpUBpy5YtKC/X91m88847uPfee3H69GmzY+Li4rBgwQJ8++23WLp0qfsrJWpm5gxNwfLb+0AuE/D14Szc/+lhqDX2m5Tzy9U4m6v//01Lmp9kKiqEd74RkW9xKVBaunQpQkNDsW/fPnz88ccYPXo0FixY4Om1ETV7M/q1xsq/XAelXIbNJ3OxYM3vqFBrbB7bkvuTJFJGqZizlIjIR7hVevvmm2/w17/+FX/+859RWVnpqTUR+ZSJPRKx5q6BCFbKsft8PmZ/uB8lNjImLb3sBpjs98bSGxH5CJcCpeTkZMyZMweff/45brzxRqjVami1nItCLdewTrH49O7BiAgKQFpmMW5/by/yyqrNjmmpgyZNRYdwvzci8i0uBUpfffUVZsyYgS1btiAqKgqFhYV47bXXPL02Ip/Sr20UvrhvKOLCVDh9tQy3rdqLK0X6TGuBSX/SoPbMKHGOEhH5CpcCpZCQEMycOROdO3cGACQlJWHixIkeXRiRL+qaGIavFg5F66ggXCqoxK2r9uJ8XrlZf1J0C+1PArjfGxH5HrfHA1RVVZn1J2VkZODNN9/E5s2b3T01kU9qFxOCrxYOQ6f4UOSUVOO2d/fiswP6LU9acn8SUFd6411vROQr3A6Upk+fjk8++QQAUFxcjMGDB+P111/H9OnTsXLlSrcXSOSLEiMC8cV9Q9GrVQQKK2qw65x+Un1L7k8CWHojIt/jdqB0+PBhjBgxAoC+dykhIQEZGRn45JNP8NZbb7m9QCJfFR2ixGf3DMYgk5lJLbk/CagrvZVVa1DrwIBOIiJvU7h7gsrKSoSFhQEANm/ejJkzZ0Imk2HIkCHIyMhwe4FEviwsMACfzB+Ef/50GokRgS26PwkAIoICIAiAKOrvfIsLU3l7SURE9XI7o9SpUyd88803uHz5MjZt2mRs6s7Ly0N4eLjbCyTydYEBcjw3rQcWjuro7aV4nVwmICJI6lNi+Y2Imj+3A6Vnn30WS5cuRUpKCgYNGoShQ4cC0GeX+vXr5/YCici/8M43IvIlLpfennrqKdx8882YNWsWrr/+euTk5KBPnz7G18eNG4cZM2Z4ZJFE5D+iggOQDt75RkS+weVAKScnBzfddBPkcjmmTp2K6dOnIzU1FSqVvudg0KBBHlskEfmPKN75RkQ+xOXS2+rVq5Gbm4svvvgCkZGReOSRRxAbG4uZM2dizZo1yM/P9+Q6ichPcEQAEfkSt3qUBEHAiBEjsGzZMpw+fRoHDhzAkCFD8P7776NVq1YYOXIkXnvtNWRlZXlqvUTk47jfGxH5ErebuU11794djz32GPbs2YMrV65g7ty52LVrF9atW+fJyxCRD5MySoVs5iYiH+D2HCV74uLisGDBAixYsKCxLkFEPkiaJVXM0hsR+QCnM0pVVVU2S2knTpzwyIKIyL9FBXO/NyLyHU4FSl999RW6dOmCKVOmoHfv3ti/f7/xtTlz5nh8cUTkfyI5R4mIfIhTgdJLL72Ew4cP448//sBHH32E+fPn47PPPgMAiKLYKAskIv8ild541xsR+QKnepRqa2sRFxcHABgwYAB27tyJmTNn4vz58xAEoVEWSET+JdJQeiupqoVWJ0Iuc/9nhyiKKFdrEBYY4Pa5iIhMOZVRio+Px9GjR42PY2JisGXLFpw6dcrseSIieyKD9BklnQiUVnmmT+mtrefR67nN2H2O89uIyLOcCpTWrl2L+Ph4s+eUSiXWrVuHHTt2eHRhROSflAoZwlT6ZLYnym/lag3e33URALDr3DW3z0dEZMqp0lvr1q3tvjZ8+HC3F0NELUNkSADK1BqP3Pm28fAVlKs1AICMgkq3z0dEZMojc5Sqq6tx9OhR5OXlQafTmb02bdo0T1yCiPxIVLASlwur3L7zTRRFfLw3w/j4UkGFu0sjIjLjdqD0888/484777S5t5sgCNBqte5egoj8jKc2xt17sQDn88ohE/Q9T5mFlRBFkTeXEJHHuL2FyQMPPIBbb70VOTk50Ol0Zn8YJBGRLdLQSXf3e/vkN3026db+bSATgMoaLa6Vq91eHxGRxO1AKS8vDw8//DASEhI8sR4iagGM+725kVHKKq7C5pNXAQALRrRHUkQQACDTyT6l4soaLP3yD/x2nnfMEZE1twOlWbNmYfv27R5YChG1FJ7Y7+2z/RnQicDQDjHokhCGlNhgAMAlJwOlzSdy8dWhK1i26YzLayEi/+V2j9Lbb7+NW2+9Fbt27UKvXr0QEGA+8O3BBx909xJE5GeM+71VuFZ6q67VYt2BywCAucPaAQDaxYRgz/kCZDrZ0J1TUg0AOJldCrVGC5VC7tKaiMg/uR0offbZZ9i0aROCgoKwfft2syZKQRAYKBGRFXdLbz8ey0FhRQ2SIgIxvru+7N8u2rWMUl6ZPlCq0epwIrsU17WNcmlNROSf3A6UnnnmGbzwwgt44oknIJO5XckjohbA3dKbNBJg9pB2UMj1P3faxYQAADKczCjlltY1f6dlFjNQIiIzbkc2NTU1uP322xkkEZHDpP3eXBk4eT6vHH9cLoZCJuD2gW2Mz7eL0WeUMgpdyygBQFpmkdPrISL/5nZ0M3fuXKxfv94TayGiFsI4R6miBqIoOvXeH4/lAACu7xyL2FCV8XkpUCqurEWJEwFYnkVGiYjIlNulN61Wi2XLlmHTpk3o3bu3VTP3G2+84e4liMjPRIcoIQiARifiWrka8WGBDr9XCpSm9Ewyez5YqUBcmArXytTIKKxA7+DIBs+lNVxfklVchbzSasSHO74eIvJvbgdKx44dQ79+/QAAx48fN3uN03GJyJbAADm6JoTh9NUyHLpUhMm9khp+E4AL18px+moZFDIBE3tYz25LiQnGtTI1LhVUonfryAbPV1ChhlYnQiYAHeJCcT6vHGmXizGpR6KzXxIR+Sm3A6Vt27Z5Yh1E1MIMah+N01fLcOBSocOB0k+GbNKwTrHGO+dMtY0OwcFLRQ6PCJDKbrGhKgxMidIHSpkMlIiojks9SkePHrXa/LY+J06cgEajceVSROSnBqZEAwAOpBc6/J4fjukncd/Yy3YgkxLj3IgAqZE7PlyFfm30d7uxoZuITLkUKPXr1w8FBQUOHz906FBkZma6ciki8lOD2usDpZM5pSitbrj5Oj2/AqdySiGXCZiYajtQamsIlBzdxkQaDZAQFoh+bSMBAEevlECjdfwfgkTk31wqvYmiiL/97W8IDg526PiaGvd2CCci/5MQHoiUmGBcKqjEoYwijOkaX+/xUhP3sI4xiAqxLrsBQIphltIlB0tvuaVSRikQHeNCERaoQFm1Bmdyy9AjOcLRL4WI/JhLgdLIkSNx5ozj+yINHToUQUFBrlyKiPzYwJRoXCqoxIH0QocDpSn19DNJIwLyytSorNEgWFn/j7i8Mn1GKT5MBZlMQN82kdh1Lh9pmcUMlIgIgIuBEjfBJSJPGNQ+Gl8eutJgn1JGQQVOZOvLbvU1WkcGKxERFICSqlpkFlaiW2J4vefNM2SUEgzjAPq1jTIGSrOHtHPyqyEif8Rx2kTkNYPbxwAAjl4pRnWt1u5xPxiySUM7xBi3P7FHaujOcKBPydijFK4fXCn1KaVdZkM3EekxUCIir2kTHYSEcBVqtWK9U7EdKbtJ2jqx55vxrjfDwMt+bSIBABevVTjUYE5E/o+BEhF5jSAIGGTIKh28ZLv8lllQieNZUtnNesikJUczSlqdiGtl5hklqXQHALkl1XbfS0QtBwMlIvKqQSn6+UX2+pSkstuQDtGIMdnbzZ620Y4FSgXlauhEQCbA7LzxYfq/S43eRNSyMVAiIq+SMkqHMopQazG/SKPVYd0B/Qy2G3slO3S+lFhD6a2w/tKbFAjFhqogl9VttxQfLgVKzCgRkQcCpXnz5mHnzp2eWAsRtUCd40MRGRyAqlotTmSXmr32/dEcZBZWIjpEiZv7ORYotTNklLKKqlCjsT84MtfijjeJ1K8kbW9CRC2b24FSWVkZJk6ciM6dO+Pll19GVlaWJ9ZFRC2ETCZgQDtpO5O6if86nYgV284DAOYPT2lwJpIkLkyFoAA5dCKQVVxl9zjpjjep1CZh6Y2ITLkdKG3YsAFZWVl44IEH8OWXXyIlJQWTJ0/GV199hdpa3jVCRA0b3N5637fNJ3NxLq8cYSoF5gxNcfhcgiAYB0/WN6G7bp8384xSnAOBklYnolzN/SuJWgKP9CjFxMRg8eLFSEtLw4EDB9CpUyfMmTMHycnJWLJkCc6dO+eJyxCRn5L2fTt4qQg6nQhRFPHOdn026c5h7Yx3ojlKCpQy8u0HSpYzlCRS4CQNo7TliQ1H0ef5zTifV+7UuojI93i0mTsnJwebN2/G5s2bIZfLMWXKFJw4cQKpqalYvny5Jy9FRH6kR3I4gpVylFTV4mxeGXady8fRKyUIDJBh/vD2Tp+vnTRLqdD+nW9SICT1JEmk0ts1OxmlK0WV2HD4CrQ6EYczOZiSyN+5HSjV1tZiw4YNuOmmm9CuXTt8+eWXWLJkCXJycvDxxx9j8+bNWLt2LV544QVPrJeI/JBCLkP/dnVjAt429CbdMaitQyMBLLWK1O8tmVNsPyuUV2Yno9RA6W3dgUzoRP3f88vZx0Tk71za681UUlISdDod7rjjDhw4cAB9+/a1OmbSpEmIjIx091JE5McGpkRj17l8rNlzCRfzKxAgF3DvyA4unSspQp8lyi6pr5nbzl1vhsflag0q1BqEqOp+TNZodFh/8LLxsb2sExH5D7cDpcWLF+ORRx5BcHCw2fOiKOLy5cto27YtoqKikJ6e7u6liMiPSX1KFw19RbP6t0ZSRJBL50o2ZJSy7WSUtDrRmA2yvOstVKVAsFKOyhot8srUaG8SKG06cRX55TXGx6Z/JyL/5Hbp7bnnnkN5uXVDY2FhIdq3d763oKnNmDEDUVFRmDVrlreXQtSi9W0TCaVc/yNJJgALR3V0+VxSRim/XA21xnqzXXtTuSXG8ptFQ/d/92UAADoYhlrmM6NE5PfcDpREUbT5fHl5OQIDA22+1pw8+OCD+OSTT7y9DKIWLzBAjt6tIwAA0/okGxuyXREdooRKof/xlltiHcxId7zFhZlP5ZYYh06aBEJnc8uwP70QcpmA+8d0AsAeJaKWwOXS28MPPwxAP7Pk2WefNSu9abVa7N+/32a/UnMzZswYbN++3dvLICIAD0/ogrX7MvDYDd3cOo8gCEiKCMSlgkpkl1ShbYx5a0CunTveJHHh1g3dn+3Xb6Uyrls8erYKB8BAiaglcDmjlJaWhrS0NIiiiGPHjhkfp6Wl4fTp0+jTpw/WrFnj1uJ27tyJqVOnIjk5GYIg4JtvvrE65p133kH79u0RGBiI/v37Y9euXW5dk4i8Z1inWKyc3d/YY+QOqb8px0ZDt7073iR1d77Vld4OXtIPw5zRrxViDeW6ospaq/3piMi/uJxR2rZtGwDgrrvuwr///W+Eh4d7bFGSiooK9OnTB3fddRduueUWq9fXr1+Phx56CO+88w6GDx+Od999F5MnT8bJkyfRtm1bAED//v2hVlv/q2/z5s1ITnZs7yiJWq02O1dpaWk9RxORNyVFGu58s9HQbcwohdvOKEmZpmuGEp1WJxqHS3ZLCkdUsBIyAdCJQGFFjdWdc0TkP9y+62316tWeWIdNkydPxuTJk+2+/sYbb2DBggW4++67AQBvvvkmNm3ahJUrV+KVV14BABw6dMhj63nllVfw/PPPe+x8RNR4kuvNKEmlt4YySvpA6UpRJdQaHVQKGdpGB0MuExAdokJ+uRrXytQMlIj8mEuB0sMPP4wXX3wRISEhxl4le9544w2XFtaQmpoaHDp0CE888YTZ8xMnTsRvv/3WKNd88sknzb7e0tJStGnTplGuRUTukTJKtoZO5hm3L7GTUQo3L72dzdVnkzrGhRqbv2NDlcgvV7NPicjPuRQopaWlGTe8TUtLs3ucIFjfTeIp+fn50Gq1SEhIMHs+ISEBV69edfg8kyZNwuHDh1FRUYHWrVtj48aNGDhwoM1jVSoVVCrnpwQTUdOTMkrZJTZKb2XSsEl7GSXzu97O5pYBADonhBqPiQtT4fTVMs5SIvJzLgVKUn+S5d+9wTIYE0XRqQBt06ZNnl4SETUDUkO4rdKblGWyd9ebVHorrqyFWqM19id1SQgzHiM1dDOjROTf3J6jVFVVhcrKuo0nMzIy8Oabb2Lz5s3unrpesbGxkMvlVtmjvLw8qywTEbU8UumtuLIWVTV1QycLK2pQUKHPAnWIsz2rKTI4wDj88lqZui6jFF+XUYoNVQLg0Ekif+d2oDR9+nTjwMbi4mIMGjQIr7/+OqZPn46VK1e6vUB7lEol+vfvjy1btpg9v2XLFgwbNqzRrktEviE8MAChhu1HTPd8k7JDraOCEKy0nVQXBAFxhqxSbmm18T2dmVEianHcDpQOHz6MESNGAAC++uorJCYmIiMjA5988gneeustt85dXl6OI0eO4MiRIwCA9PR0HDlyBJmZ+sFvDz/8MD744AN89NFHOHXqFJYsWYLMzEwsXLjQresSkX+QtjIxbeg+l2edHbJFCpQOZxRDrdFBabjjTVIXKLFHicifuT0eoLKyEmFh+n9lbd68GTNnzoRMJsOQIUOQkZHh1rl///13jBkzxvhYuuNs7ty5WLNmDW6//XYUFBTghRdeQE5ODnr27Ikff/wR7dq1c+u6ROQfkiKDcC6v3CyjdC7XOjtki9SntPt8PgDzO94AIDaMGSWilsDtQKlTp0745ptvMGPGDGzatAlLliwBoO8VcncI5ejRo+3uJSe5//77cf/997t1HSLyT8k2MkpSGa1TAxklaUTAgXT9RO4uCebHG3uUGCgR+TW3S2/PPvssli5dipSUFAwePBhDhw4FoM8u9evXz+0FEhG5ytY2Jo6W3qQ74qpq9Y3gXSwyUHGG0lthRQ20uvr/QUdEvsvtQGnWrFnIzMzE77//jp9//tn4/Lhx47B8+XJ3T09E5DLjNiaGWUolVbXINQybbDCjZDG12/L46BAlBJNtTExlFlTipe9P4qqNGU5E5FvcLr0BQGJiIhITE82eGzRokCdOTUTkMuM2JsX6jJJUdkuKCERYYEC97423GEZpmVFSyGWIClaisKIG+eVqY/M3ALy/6yLW7suAKkCGRyd1c/vrICLv8UigtHXrVmzduhV5eXnQ6cx30v7oo488cQkiIqfVbYxbBVEUcd5QdmsomwSYD6O0vONNEheqMgZKpjIK9bPlLhVUWr2HiHyL26W3559/HhMnTsTWrVuRn5+PoqIisz/+aMWKFUhNTbW71QkRNQ9SRqmiRovSak3dHW/x9d/xBpiX3izveJPEhtlu6L5SpA+QrhQyUCLydW5nlFatWoU1a9Zgzpw5nliPT1i0aBEWLVqE0tJSREREeHs5RGRHkFKOyOAAFFfWIqekCueMgyMbzijFhKogM/QgWd7xJjHOUiqr61ESRRFZRfpS3+Ui6+1TiMi3uJ1Rqqmp4SRsImq2jHe+FZtM2Hag9CaXCYgxBEL2jrc1nftamRpqjb4FobCiBhVqjeuLJyKvcztQuvvuu/HZZ595Yi1ERB4nzVI6n1eOLENTtyM9SoB+mxMA6J5keyacFChdMwmULLNIV5hVIvJpbpfeqqur8d577+GXX35B7969ERBgfifJG2+84e4liIhcJjV07zx3DYB+a5LIYKVD731uag/8dqEAo7vG23y9buhkXelN6k+SXC6sRNfEhnuiiKh5cjtQOnr0KPr27QsAOH78uNlrgmDd/EhE1JSk0ps0YduRspukT5tI9GkTafd14zYmZXUZJcsM0uUiNnQT+TK3A6Vt27Z5Yh1ERI0i2ZBRkvqGnAmUGhJno0dJCpSkRnCW3oh8m9s9SkREzZmUUZJ0amAzXGdIPUoFFTXQGbYxkUpvPZL1d8Re5ogAIp/mkUBp165dmD17NoYOHYqsrCwAwNq1a7F7925PnJ6IyGXJFoGSJzNKMYYeJa1ORHFVLQAYRwMM7RgDgCMCiHyd24HShg0bMGnSJAQFBSEtLQ1qtT4FXVZWhpdfftntBRIRuSMhwnwrEk8GSgFymXHrkovXyqHTibhiuLNuaAd9oHSlsBKiyE1ziXyV24HSSy+9hFWrVuH99983u+Nt2LBhOHz4sLunJyJyi0ohN5bIokOUxtlInjK4fTQAYNe5fFwrV6NGo4NcJmBAShQAoEytQWkVZykR+Sq3A6UzZ85g5MiRVs+Hh4ejuLjY3dMTEblNauh2dH6SM0Z0jgUA7Dp3zdiflBiu33RXGh/QXO98+/L3yxj+z1+Ne+ARkTW3A6WkpCScP3/e6vndu3ejQ4cO7p6eiMhtSYahk54su0mu7xwHAPjjSglOZpcCqBtU2TpKv5Fuc2zo1ulEPPrVUWQVV+H9neneXg5Rs+V2oHTfffdh8eLF2L9/PwRBQHZ2Nj799FMsXboU999/vyfWSETkluGdYiEIwMgucR4/d6vIIHSMC4FWJ+LLQ1cA1AVIbaINgVIzzCgdyqzbtDwuzLPlSCJ/4vYcpcceewwlJSUYM2YMqqurMXLkSKhUKixduhQPPPCAJ9ZIROSWO4em4JbrWiNE5faPPJtGdI7DhWsVOHqlBEBdRqmN4X9NZymJoohvjmShc3wYerby3qba3x7JqlsT2GxOZI9HxgP84x//QH5+Pg4cOIB9+/bh2rVrePHFFz1x6mZpxYoVSE1NxcCBA729FCJyUGMFSUBdn5KkvtLbmdwyLFn/B+5be8hrd8PVanX44WiO8XFVjc4r6yDyBW795NDpdFizZg2+/vprXLp0CYIgoH379pg1axbmzJnjt1uYLFq0CIsWLUJpaSkiIrz3L0Iiah6GdIhBgFxArVYf+NSV3vQBk+kspWzD+ICs4ipcuFbRKA3mDckqqkJRZa3xcVUt78ojssfljJIoipg2bRruvvtuZGVloVevXujRowcyMjIwb948zJgxw5PrJCJqtkJUClzXNsr4uK70pg+YrhTVzVIqrKgLUPacz2/CVdYpV5sHRlU1Wq+sg8gXuBworVmzBjt37sTWrVuRlpaGdevW4fPPP8cff/yBX375Bb/++is++eQTT66ViKjZkspvcplgvMsuyTCWoLpWZ8zgFFfWGN9jGSjpdCLO5ZYZt0NpLGXVFoFSLQMlIntcDpTWrVuHp556CmPGjLF6bezYsXjiiSfw6aefurU4IiJfMbZbAmQC0CUhDAq5/kerSiFHeKC+w6GwQm3437pAae/FAmi0df1Ba367hAnLd+LjvZcada1WGaVa9igR2eNyoHT06FHccMMNdl+fPHky/vjjD1dPT0TkU1KTw/HlwqF4d3Z/s+elqeD55foAybQ3qKxag2NZJcbHu85dAwCcMMxjaiwVFoFSNUtvRHa5HCgVFhYiISHB7usJCQkoKiqy+zoRkb/p3y4abWOCzZ6TNs4tkAIlQ0ZJutdFKr+JoohjWfoAKbe0ulHXWWYIlFQK/a+ASjZzE9nlcqCk1WqhUNi/aU4ul0Oj4f/5iKhliwnRZ5QKDKW3IkOP0qAU/R5xuw2B0tXSauSX64+5WtK4gVK5oUdJGjTJZm4i+1weDyCKIubNmweVyvZEV7Va7fKiiIj8hZRRqiu96f/3pj7J2J9eiMMZxaiq0eLYlboSXGNnlKTSW1yYCleKqlDdBD1KGq0Onx3IxOD2MeiaGNbo1yPyFJcDpblz5zZ4zJ133unq6YmI/EKMoUepoFzKKOl7lPq1iUTrqCBcKarCtjN5OJVT15dUWq1BVY0WQUp5o6xJauaOM6zN2bveSiprce/a33FT7yTMGZri0Hs2HL6CZ789AQC49M8bnboekTe5HCitXr3ak+sgIvJLcSY9SqIoGnuUokOUuKl3MlbtuIBvj2RBrTHP6uSWViMlNqRR1lRmUXqrrHGuTeKrw1ewP70Q+9MLHQ6UTuWUOXUNoubCI1uYEBGRbcaMUoUaZWoNNIYZSVHBStzcLxkAsO30NaRlFgMAZIYm76uNWH4rV+uzWlKgVF2rc2p2U2BA3a8O03EH9QkLbLwtZIgaEwMlIqJGFBNSl1EqNkzlDgyQIUgpR7fEcHRNCEONVoeSqlrIZQL6tIkE0Lh9ShVqfalNCpQAWGW06hMgq/vVYTreoD6hJnvt1ThxLSJvY6BERNSIYoxzlNQoNDRyRwcrja9P65ts/HuXhDC0i9aPF2jMQEkaDyDNeAKc61MyPfa4g4FSsEm/VVGlY1koahxanYizuWVe25TZ1zBQIiJqRLGGHqXSag3yDMFPpGmg1KcuUOrVKhwJ4fptT3JLG+/O4fJqfWYrPDAASsMsJWcCpWqTY03v1quPxqS052i5jhrH4xuOYuLynXhv50VvL8UnMFAiImpE4YEBUBgaj85fKwegb+SWtIkOxsAU/Ya617WNMgZKjdmjJJXewgIVCArQZ3qqnGjoNg2qHC291Zps1cJAybu+OnQFAPDW1nNeXolvcDtQmjdvHnbu3OmJtfiMFStWIDU1FQMHDvT2UoiomZPJBGNgdD5PHyhFBgeYHfPGbX3xt5tScUv/1sZAKc+FQOl4VolxDEF9pPEAoSqFsSRWVeN435BpoJRVXOVQz1Gtti6jVNAMAqUajc7pu/38DQtvjnE7UCorK8PEiRPRuXNnvPzyy8jKyvLEupq1RYsW4eTJkzh48KC3l0JEPkDqU5ICJdOMEqDPKi24vj0C5DIkRuiPdTajdOxKCaa+vRsPrT9S73E6nVgXKJlmlJwpvVlM8r7mQHBm2ixe1AwCpcEv/4LUZzeZlRGJbHE7UNqwYQOysrLwwAMP4Msvv0RKSgomT56Mr776CrW1tQ2fgIjIz0l9SnUZJaXdY+PD6nqULJttRVFEXmm1WRlLsuv8NYgikJZZXG+TboVJFiVUpUCgK4FSrfXMJ+tjzM9numZvZ5REUTQO/kzPr/DqWryJvdyO8UiPUkxMDBYvXoy0tDQcOHAAnTp1wpw5c5CcnIwlS5bg3DnWQYmo5ZJGBFQaMjHRFqU3U/Hh+oxSjUaH4krzf2z+eOwqBr28FYNf3orn/ncCpdV1r0tzmMrVGuN2KbZI/UkKmQCVQmac/u1qjxJgXSb87Xw+uj/7Mz7YVdcsXKsx7VHy7hZXpmVAmbQ7MZEdHm3mzsnJwebNm7F582bI5XJMmTIFJ06cQGpqKpYvX+7JSxER+YyYUPM9MaNC7GeUVAq5sTRnWX47crkIgL4Zes1vl/Dl7/qmXFEUceRysfG4+rIk0rDJ0EAFBEFwqfRmeazlHXoPf/EHRBF46YdTxueaUzO3Rle3FlkLjpNEdik5xO1Aqba2Fhs2bMBNN92Edu3a4csvv8SSJUuQk5ODjz/+GJs3b8batWvxwgsveGK9REQ+R9oYVxJVT+kNgMmIAPNAqaTKPMN0taQKgL6h+lpZXbByqZ5ASdq+RBoAGeRCM7dUVgs3TNvOKzNfp8bGlO8abfMZD2CaURJsZJQOXirE0Fe2YtOJqx6/tiiKKG4mc6RYenOM24FSUlIS7rnnHrRr1w4HDhzA77//joULFyIsrG536EmTJiEyMtLdSxER+aRYy4xSA4FSoqH8ZhkolVbpg5xWkUEA6np9pLKbJL3AfqAkld6MgZJLPUr6Y9vFhBjWaZ5RstUjZZpRqqrxbgO1xmQttipvd354ADkl1bhv7aEGz7X3QgHe/OUstA5uAfPstyfQ94Ut2HY6z+H1etLavZe8cl1f5vbmO8uXL8ett96KwMBAu8dERUUhPT3d3UsREfmkWMuMUoj9HiUAdodOShmlDnEhyCquMmZmpLKbSiGDWqOrN6NkLL1ZBEr27v4SRRHv77qI1lHBmNIrCUBdUNU2JhjHskqsAjptA4GSZTN4UzPNeNkK6pwJGu94fx8AfRP+nwe3bfD4tfsyAACvbT6DMd3iHb6Op/zt2xNNfk1f53ZGac6cOfUGSURELV1MiHMZJXtDJ6VAKcWQySk0ZpT0vUsTeyQCqL9HyVh6CzQvvdmbKXQiuxQv/3ga9396GC9+fxJAXUYoJUa/3UqeRUBnK7tillHy8i35pmuxcQOhSxwdvCmRN4PmKFbeHON2Runhhx+2+bwgCAgMDESnTp0wffp0REdHu3spIiKfZNqjpFTIzPY9s6WtYb+3C4ZxAhLpLrf2sfpAqaC8BlqdiOPZpQCAm/sm47s/spFRUAlRFG3235gOmwRQNx7ATo/SJZMy3oe70zFvWIoxI2QsvVn0KOls9Shp6p7z9uwijUmPkqMls4Y423fEu+18h9uBUlpaGg4fPgytVouuXbtCFEWcO3cOcrkc3bp1wzvvvINHHnkEu3fvRmpqqifWTETkU0wzSlHBATYDGFPdkvQ9nqdySs0CHimj1D6uLqNUUK5GjUYHmQAM7xQLuUxAVa0WuaVqJEZYZ/srLAIl42RuO8HLlaIqs8f55eq6HiVDQFdcWYvqWq0x6Gq49FZ3rRqNzrjfXFMxvetN56GOZstRDg1pBgklj8kpqUJCWCBk/vRFmXD70zl9+nSMHz8e2dnZOHToEA4fPoysrCxMmDABd9xxB7KysjBy5EgsWbLEE+slIvI5QUo5QgwBSUNlNwDoFB8KhUxAabUGOSX6bI3pRO32hkxOVa3WWGaLC1MhMECO1lH6Rm975bcyi0CpoR6lK0WV5u+v1hiDqsSIQCjl+l8j+SbTuXU2klOm25xUG/7+07EcdH/2Z3yT1rQ7Opj2KHkqo2R5R2JDmkPpzRO1tx+P5WDoK7/i4S+OuH8yA61OxNErxWZN997kdqD06quv4sUXX0R4eLjxufDwcDz33HNYtmwZgoOD8eyzz+LQoYbvHiAi8lfSLCVHAiWVQo6OcaEA9FklQB+gSMmP5MggY4By0vB6oqGvSepfumTnzrdyix6lwAZ6lLIsMkqmgVKQUo7AAP06TBu0TTNKUoBkmlGq0eig1Yn4v08PQ6sTG9x2xdPMSm8eyyi1zNKbtLHuN0eyPXbOZT+fxrS39+DZ/zWPxnO3A6WSkhLk5Vnf5njt2jWUlur/DxwZGYmamuYxN4KIyBukPiXLfd7s6W5SfgPqMhZBAXIoFTLjeU4a+pOkBnCpf8nenW8Xr+mfTzKU5erGA9j+17tUepPKY/nlamPAFhQgh8rwfikgEkXRLEsjBWCW266oNd7rUzJdi61+KleYzolyhL8ESo1RNn13p36i+2f7Mz1+bld4pPQ2f/58bNy4EVeuXEFWVhY2btyIBQsW4OabbwYAHDhwAF26dHH3UkREPkvqU4qsZ/sSU92T9Fn6U1fLANQ1cocH6TNBxkApxzxQku5Es1V60+lE491ZvVtHAqjrUbLc6BbQBz1SoCStx3SwZWCA3JjZkgIf081vgbptWywDCW+OCGiM0puzcY+saduybPLEZG5FcyghNjK3m7nfffddLFmyBH/605+g0ej/5aBQKDB37lzjtiXdunXDBx984O6liIh8VoJhiKTl8El7ukmBkkVGKSJIH2hJGapzufo746TG7ZRY69Lbd39k48Pd6XhgTCeUqzUICpCjc7y+tFffwMnCihrj890SwvDH5WJjoKSQCQiQy6AylN6kjJI0fkAiBUqWGSVv3vlmNh7AS+Opm0NGyRNfuqI5RHyNzK1Aqba2FlOnTsW7776L5cuX4+LFixBFER07dkRoaKjxuL59+7q7TiIin3bX8BQIAnD7wDYOHS+V3i7lV6CqRmsdKBkySjWGX/qWpbeMgkrodCJkMgEf7E7HH5eL8fiGowCAXq0ioDBkgqQ71QoraiCK+obxsED9NaRsUkK4CtGGwEzarkQKsOoySvp1SA3nEnulN2/OUjLtUbLVeO6oNXvqBik7G/Z4o5nbU2VGUwq59wO+xuZWKBgQEIDjx49DEASEhoaid+/e6NOnj1mQREREQKf4MLx0cy8kG7YfaUhcqAoxIUroROBMbhlKDYFSuCGIibYYYik1c7eKDEKAXIBao0NOaTVqtTpjVkra8qRPmwjj+7olhiEoQI6s4ios+uww+jy/Gat2XABQFyi1jgpGmHFfN31GSWoCt+xRKreXUdJ4L6NUo9Hhi4OXjXfwmY4HcCej9Nx3J11+r9wLGSXLr9UTYZMUcPszt7/CO++8Ex9++KEn1kJERAaCIBj7gk7nlNotvUkSI/SBk0IuQxvDfKNL+RU4n1dudms+APRpE2n8e1SIEguubw8A+PHYVehEYP3BywDqRgO0igwyZpmk0puUUVJZZJTK1Oa3yVc1gx6lj/ak47ENRzH+jR0AzDfFbYwsiyMamqXlCbVaHf73R7YxC+ipfixTAexRalhNTQ0++OADbNmyBQMGDEBISIjZ62+88Ya7l2h2VqxYgRUrVkCr9e50WSLyb92TwrD7fD5O5ZQab+cPD5IySuaBklR6A/Rzli5eq0B6fgWyis1v7weAPoZGbsm9ozrg0/0ZKDIMTZT6jLIN720VFYRwy4ySoTfJ2KNk+Hlo2aNUYVF6U8gEaHQi1A5mlM7lliHtcjFu7d/a5eDitwsFAOqCM0cnczsTAzi7tKZIxLy38yJe3XQGXRPCsGnJSI8N1zTlr0MmTbkdKB0/fhzXXXcdAODs2bNmrzVFxOwNixYtwqJFi1BaWoqIiIiG30BE5IIuCfo+pXN55ehgmMZtK1AKVsqNAyQBk4bu/ApjD9OUXonYfuYaEiMCjUMpJeGBAfhg7kDsvZCP1zafRX65GiWVtcg2DLtMjgg0lt4kVj1KtQ2U3gzrCAtUoKiy1uEepQnLdwLQNz/P6t/aofdYUlr00dRXejPdJNfTjcqm526KHqUvftdnBs/k6u+ctAwKbW0I7Cz//C1vzu1Aadu2bZ5YBxERWehgGDqZnl9hHFhp2cwN6PuTTP9hanrnm9SXNKlHIp6c3B1BSrnNf8T2bxeF/u2i8On+TOSUVOP8tTLklOgzSkkRdaU3idQEXpdRst3MbSy9aaRAKQBFlbVOl962nsp1OlB69tvjKKqsNZv1o9OJ9ZbeTMcbOBMnCQ6EDKaBSlPc9VZqMS28MUpvfpoPMeN2oERERI2jgyHgySmpRq4huyOVwEwzSqZlN6Bui5ML1yqMwU7PVhHG3qX6dIoPRU5JNc7lliOnWH/NpMhAqwxIkNJORkltXXrT6UTj7CJpDpSzzdx5JvObHKHR6vDJ3gwAQO/WdZn/ns9tMma5AP1MpYyCCrSNDoYgCGavBThRH3MkYDAN0JoiULIMiK0ySo2+Av/gkbzirl27MHv2bAwdOhRZWfo9e9auXYvdu3d74vRERC1SVIjSOKDyeLZ+UGRdRqnurjfLzW9TYuuGTlbX6hCilBuDp4Z0MsxXOpFdasxGJdvKKCkMGSXD/0oZpcuF5nvDVdVoUWtS6gpT6c9TYWfLFHtyS6udOr7aJDNkGi5UWgzWfPnHUxj16nZ8dkA/Bbqsui4L40qjd41GhxPZJTbLWjUmIxKaovQWaDE121szo3yd24HShg0bMGnSJAQFBSEtLQ1qtT7qLysrw8svv+z2AomIWjJpLpL0C14KlMKDFMapyJYZpeSIILNy09COsQ433UqB0p7z+QD0TduRwQHWPUpSRkkhZZT065MCOmlCeGWN1iyTIp2nsKJuWytHlpZX6lxGqcokIKqvX1badPgfP5wCYN6MXutkoCSKIqa9vRs3vrUbuw3fP1OmGZ2mqFhJ5VGJvZlRhzIK8U1aFtYfzMQney81/sJ8jNuB0ksvvYRVq1bh/fffR0BA3b84hg0bhsOHD7t7eiKiFk0KlCRSM7cgCIgylN8Sw81nKslkAu4anoLuSeH4+9RU/OeOfg5fr5OhL+qiYQuU5Igg/aw8pcKsvBSikjJKhkBJq4Nao8UZw5Yrg9pHA9APnDSdoSRlpoor6zI3IhpuLK7R6pzK8JiW9jQOTJWUvg7T0mGNRocb39qFdQca3nNMqxORXVKN04avX5pdZXmMpKE70C4XVhq/l87KKanCxOU7jP8NJZbfB2kJt6zci4fWH8HjG47h2W9PGMcJOMKR3ixf53agdObMGYwcOdLq+fDwcBQXF7t7eiKiFq2DRaAkZZSAuu1QLEtvAPDk5O74afEI3DW8vTH744iuiWFmGZ6kSP25ZTJ9sCTpmazv+6nLKOlwLrcctVoREUEBxjv29Bkl/S9ouUxAqCHAKjDJKImief+OxHKatzN9SqaBkmW5zRaphGh5196J7FI8+fUxq+MtAzudKKLSJMiyzOZYvkfTQNA3Ytk2THpzJwrK7X/N6fkV+PZIltVaXt10BmcNW9tInt54DHd+eKDea0osvweSD3enO51xqmrge19YUYM/vbcXGw5dceq8TcntQCkpKQnnz5+3en737t3o0KGDu6cnImrR2sea73QQbhIo/d/ojpjcMxEjOsd57HqRwUoMbh9jfJwUUTdKQLrDDajLGEkBhlqjM26426tVBIINQVWFWmvszQmQC8YAosgkUNK/3/oXqmXDt62ZUPaY3lVXUllbz5F60tf20/GrDp3fMtDRmjSsA+azmiSmb6kvo2Qa+Fwusv81j3ltOxZ/fgTv77qIme/swXd/ZAOw3pgYAD7dn2mVYbLHVhBXrtbgxe9P4tlvT6C4ssbGu/SKK2vw07EcqDVaPLXxGLo/+zNOZltn1yTLt5zFvouFeOTLPxxamze4HSjdd999WLx4Mfbv3w9BEJCdnY1PP/0US5cuxf333++JNRIRtVimpTe5TECISXZoWp9krJzdHyEqz97AfGPvJOPfk02yVfnldb8gpXVJGaUajQ5pmUUAgB6two0DKdWauh4l/Sa6dXvLmbL1y91y1lK2E4GS6XuLqxoOlJRyGS4XVmLDYccyG5bZLo1ObHCQpWkzdX236ps2fTvSv/Xyj6dxOLMYf12XBsD97VFsBXmm671caP+/w5/f34//+/QwXt98Fp/t15csV2y3TqZIHPlv421u/7/rscceQ0lJCcaMGYPq6mqMHDkSKpUKS5cuxQMPPOCJNRIRtVjSHWyAvuzWFIN8J/dMxDPfHAcAyG0MExKEugZpqbenulaL/en6CdgjOsUZ7x6rrq0rvSnlMuOgyqLKhgMltcWsJWcCJdNslCPzg6pqtcivp8xlqVZjUXrTiWZ399nKypj2WGnraZsy3XLGlTEC7t5RZ+v79f3RbOPfS03uDLRc3klDb9b/jtQdX99qTLNnv5zMNWYlmxOP/DPkH//4B55++mmcPHkSOp0Oqamp3BiXiMgDgpUKJEcEIruk2jhDqbHFhKpwQ49EbD55FTf0TKx7PkSJgooa3Na/jfE5KaO092IBCitqEBaowOAO0dh9Tn/XV3WtzviLP0AuM2aarDJKNuYqWZbepEDpzNUyiBDRLTHc7tfg6ORvSUllbb0BhiiKZkFqjY2MktYsELKOhEyrbbZe33uhAEk2pqA7y91AyVbz+9Mbjxv/bvp12IvjTJ//8VgOrpZU2+ylM3X3J787tc6m4rH/1wUHB2PAgAGeOh0RERm0jwtBdkm1WSN3Y3vzT31RWlWLeJPRA2sXDMb3R7PxwNhOxuekjJIU+IzrFm8osemfr6o16VFS1PUoWWaQbGWULKd3ZxVXo1arw6xVv6GsWoOfHxphN1hydqBlmVpT77RwtUZn1qBtWXrTiaLZczYzSqalN4uXT2aX4o739wEA9j45tt7z1EcURePYCEfY+j6ZBnyWASKgLyHWanX1DuQ0fYdOBMa9vh0nXrjBxnodXqrXeCRQ2rp1K7Zu3Yq8vDzoLCLRjz76yBOXICJqsdrHhmDP+QKzRu7GFhggt7pzKzU5HKnJ5oGJ0mKo4bCOscb3A4bSm42MkiWbgZLGOqNUWaM1zjp69ecz+HDeQJvnczZQAoDb3t1r97VytabeQMk6o1R/j5LlqIPjJiUn09Kbpr4anQ1anejURrVv/2rdPyQFZ3svFGDhfw/hhek9zF6f+9EBxIepsPvxsXbHA1gGVxU27n5buf0CfjiW4/BavcXtZu7nn38eEydOxNatW5Gfn4+ioiKzP0RE5J6uhlvt48PqL114g3TXm0TaWiXIGCjpjM3cSrnMONHbkq3Sm3RruVRKyi6pMrs7LtNiCrit97oiNSncqsxZYbE1i2WgpB9xUH9GSaynmds022QaKNkam1AfnehcM/fb26wDJWlt81YfQElVLRZ/fsTqmLwyNc5cLTMLdEzvbnNkCf/6+bTD6/QmtzNKq1atwpo1azBnzhxPrIeIiCzc0r811BodJvVIbPjgJqayyChJWS9jic2kmdu0JGfJdulNH+x0iA3BubxyFFfWmg2qtPUe43vrea0hAQqZVaasrNoyULIOYEybz21llHRmPUoiytUahBg2KTY9Wm0WKDn3dehE0e0eJemaDYVotRYVpLvW1M1p8qfNct3OKNXU1GDYsGGeWAsREdkQrFTg7hEdHNrUtqlZBkpSI7JUYqvWaI1ZIKVCZpWBktguvemfiw1VGc+bbjILqL7ymq2M0r9u6YWZ/VrZfY9EKRegsLjbr0KtQVpmkXHPOVsBjNqsZFZ/j9KJ7BL0/PsmPPKFfn6Qaa+O2XkcmCpuGpToRNHtIEUK8ho6Ta3Ff7Nck21mbJXkTmQ3vzvaHOF2oHT33Xfjs88+88RaiIjIx1hmiIwZJUNAVKsVUWrIxgQr5VaBlcRW0CM9FxggQ6tI/eBL00Cp3oySjfNFh6gc6vMKkMugkJv/on98w1HMeOc3XP+vXwHYC5RMRxJYv26aZZJ6dr5O028kL8L10ptokalyd1sR6ZoNBVyWaws2mfFl671zHJwMburOjw7gSpH9EmtTcLv0Vl1djffeew+//PILevfubbbfGwC88cYb7l6CiIiaKaXcPEMk9faYbpsiTeHWB0pOZJQMwU6QUo7kyCCcvlqGSw5mlGy9ppALDt0RppDLrO7oulSg/2UtBQc1GhulN01DPUr2r2n6munoAXulN3t74zl5k1y9524o4LJcW1igwrhdjK13FlbUoKpG69SWOjvPXsOiTw/j2weud/g9nuZ2oHT06FH07dsXAHD8+PH6DyYiIr9imlGSCUCIYesS08xRYaUUKCnq6VGqJ6OkkCMmRL+v3UWLjJKt29cB23OUlHIZAuxktMyPExAgtx8kVNdqbfYgmWaCbPco1bNtiZ3z2CrhAfbHBoiiaDOb5Qzp1A1nlMyvY1rutDcos6BCjdZK50rIf1zxbsnO7UBp27ZtnlgHERH5IKVJ5iUsMMB4a7ogCFApZFBrdCgsN80o2QmUbMwwkuYaqQL0GSXAvPQG6LMvllmqqhotvvjdeiuSALkMAQ5klALkMqseJVP/3ZeBl344ZWO9dYGC7TlK9VzUJIiqrKlrHLeXUbI3bVyrE1HrZlqpsEKN/2w91+BmwpalN7OsoN1BlM6XBReO6uj0ezzJ5R6lKVOmoKSkLsr7xz/+geLiYuPjgoICpKamurU4IiJq3kwzROFB5v/2DrTY183V0ltggAzJkfrRCNfK1BbHWL/v19N5xr+3i6nLXgTIBSjqGZJYd5ys3oySaZDUq1WEcT82dQMZpfq2UjF9xTQzU6PV4ZO9l3A403zcjr0ASic6P3vJ0t++PYHXt5xt8DjLRnPTr9/ed89eybA+baKDGj6oEbkcKG3atAlqdd0H9l//+hcKCwuNjzUaDc6cOePe6pqpFStWIDU1FQMH2h50RkTUUphmlKSym0S6862gwqT0ZpFRkm7Dr6oxv/0eqAuCggLkxmZuS7ZKdgUV+t9NXRPCcGv/1sbnbTVpA8CC69ubPdYf59ivR5lMMN6O33CPUj2BkslLpnva/XahAM9+ewIz3/nN7P32SnL6CeFNM+66vmZ6e5mjCW/stNq+piHuNqe7y+VAyfI/uCtRoq9atGgRTp48iYMHD3p7KUREXqUymVZtOcnbcgPcYKXcqkcpLlTfe1Smtg6UqowZpbrSmyVbJbtSw470/dpGItrQ2wRIpTfrX3vjusfj33/qa3ysVNTfo2RKLtQNxPxg10Xj89/9kW22kSxQf+nNtH/pLZNp2SUmc6OyS6pRrtYgr6zaaoaR6XlsBY+NwXK6uCl7Fc6qWi2ue3ELUp74weHruDkWym1ujwcgIqKWyzSjZJktslV6U1pkamJD9ZO8y6ttZZTqSm/xYSqbgxRtBQUlhkApPCgA0SF1d2IH2GnSDlEqjAGb/jjru97skcsE4yRsy7jhgc/SzB7XW3qz89Lu8/nGvxdV1OC6F7dg0D+2Iq9UbfN4rU40awZvTNp6EiSezAJ5e3ily4GSIAhWqTVXmrSIiMh3mQYeKouMkvS4zDhHSQGFXGZ2i36MIUApt5FRKqs2BDyBAVDIZUgMt97CxVaPUmmVxvA+hVVGyVZJLUSlQFhggPlxDqYxZILg8CTs+iov9QVREp1YFwSlWfQs1V2j/pKYJ9W3Zk+GA96OLVy+600URcybNw8qlf5DWF1djYULFyIkJAQAzPqXiIjIP5n+Egu0zChZPJYGEqoUMmgMDcvGjJKNQMkY8BiGRCZHBiLLpH8HsJ1RKq02zSgpjc8rFbabtENVCrPAyJkeJbnM8UCpvljIXinNlGlgYitAlI5pDoGSJ9kbNdBUXA6U5s6da/Z49uzZVsfceeedrp6eiIh8jGVGyXKwYLBK/ytHqZAZJ1NLGSXLvdQAk4AnUAqUggCYZ1Js9igZ3hcRFIDIYPMhyLZu+w9Ryc0CKLkMjZJRqm+Okr3mbLNjzAIl231IplmnxnYow/7G957MAnm7VuVyoLR69WpProOIiHycdUbJIlAyZpTkAPTBTEyI/YySFDxJ+7yZ9hFJqm1llIyltwBEByv17xeB6BClzZJQiFIBpaIuuKjR6MyCmiXju+CXU7mICAow6xkCzO96a0h9PT2O3NJvGhTayxrpmrD09v3RHLuvncop9dh16hlp1STYzE1ERB5heUdbYICd0pvJ83Fhhh4lWxklk6ZsAIgyKaNJ6ssohQcpIJMJOPj0eOx/ehwC5DKb5SKZTDCb71RdqzM7btGYjvjur9cjPsw6UJMLtrNUttTXo+TIkEjTLJK9jNL+9ALUNHDX2429kxq8VnPi7fEAbk/mJiIiAmA1TNJyXECwje1NYo2lt1qzY7U60TgyQNo/zrKMBtjLKJmX7EzXUV/5y3hOiy1KpH4lmY3MkVwm2J02DgC/ns7FlpO5ePyGbqivDcmhjJKm4YzS0xsb3kqsY1xog8c0J96+T4yBEhERuSU5IhDZJdWY0ss8U2EdKOkfK00CixhDM3dFjT44kcsEfZBkEjhJd6RFBjWcURJFEaXV5k3gphzpP67W6GCrZUhu4ze2TBDMvh5LT319HFdLq5FRUIl5w1JsHiOKot3mbFOmjesVNgZ0OsrbPT/O8tlmbiIiIgD4eclIZBdXoVtiuNnz9gIl04AjxuT2/YoaDeSCgInLdxqzR4EBMmMgEmUjo7R2XwZuHdDG2CdUWVOXDQoPtD7ekTu1qmu1Nocpym3cMSeX1R8oXS2tBgAcvVJiN5ulE21v4mu9rrpgylap0lHeztA4y9vrZY8SERG5JTwwwCpIAmz1KOn/bW4aLoQHKYxDKMurNdhx9hqyiqtwIrvUeG5JZLB1RulEdil+OFbXVCwNmwyQC1bXBxzbRSIhXGUzoLKZUWqg9CYJUsrtZrM0Op2DgVLdMZtP5jZ4vD3e7vlxlrczSgyUiIioUZhmlFQKmc27w5RyGUINPUjlao1VgGJaPrPVowSY32FlOlLA1i3q8noarz+ZPwjT+iTjkQldbd6hZmv98gZKbxKlXGY3o6TViaiuaThQ8tTdbN7O0DjL28tl6Y2IiBqF6biAYIuZShJBEBCqUqCwogZl1RpjoCORGrkBIMpGRgmoGx8AWA+ptHRzv2R8svcSBrePRlJkEMZ3TzC+NrJLHEZ2iQNgex8zm4GSTLDalsWWyhrrIFCy/2Ihdp671uA5nN3D7bmpqXjuu5NWz/dqFeHUebzNZydzExER1cd04KRUdgOs9zULM8ko5ZeZ7yxvGvBYDrCUFJtsHFt3x5vtX2/BSgV+fmhkg2t3NKPk6O/wcrXGbkbprjWObbD+5i/nHLuYwdhuCVaBklwmoF1MsFPn8TZuiktERH7JPDiy3xsUapjYXVZdi/xy8+2vwmw0ZAPAgHZRxr8XVdTgakk10jKLzLYvcYetjJKtXhm5IJhNzLanVuvYnW2eZKvK2CM53Os9P85iRomIiPzSiM6xxr8XVtbYPc6YUarW4FqZeaCUHGm9ES4A3DagDWZc1wpPbzyOospazP3oAM7klmFst3gA7gdKtjNK1sfJZYJDs5mAumxXfVQKmcd6kWxmwOD95mhnMaNERER+KTJYiW8WDUfrqCA8OK6z3eOkzFNFjdYqo9S/bZTZ4/X3DsHicZ0x87pWxp6lkqoanMktAwD8ejoPgO3RAM6w3H4FsN0ILpMJqHVgnzYAVv1XNq8bYLu86ApbAZEgCL7XzM2Bk0RE5K/6tonE7sfHmj0nwjywCDGU3irUGqtA6bp25oHS4A4xGNwhBkDdXXBFldYBSHiQe7/eXpnZC/d88jv+OrYuwLM1HkAuCA7NZgKAqpqGM0WhKoVxxIG7bAVKMsH2hPHmzNvjDBgoERGRV4UYmrQraqxLb7E2NsKVSBmlYhtlPXczSp0TwrD90TFmz9krvTkaKDly11pMqBJZxVUOna8htkpvMkGwGfA1Z94O7Fh6IyIir5IySgXlNagwzBMa0TkWK/58Xb3vkwKl/HIbgZKbPUq22JvBZBoofTx/kNXrEYa1ONLMHeTR0pv1c4IAhwZkNifeDux867tFREQ+z7L3OUSlDw6uFFUC0E/V/mT+oAZ3uY8MDrDbvxKm8nzBxFZGSRRFs7veBrePtjpG2s/O1ga+7kgIr8u2DTWUI03ZysS0iQ52uQ8qtBG+p47wdqWQgRIRETWpx27oBgC4c2g7AHUZpcuF+pJTVLDSoVvCAwPkSE2y3joFgEPTsp1lq+dHJwJaXV2mKMBGNCUNpMwsqPToekyzT73bRGBQinmQZisT88yNqS5nlGyV8loCBkpERNSkRnWJw5FnJ+D5aT0AACGGu96k3pzoENsTuG253mQEgSlHpmU7y1agoBNFjO2mn+6dFBFodcyjk7oaA5NjWSUNXsOxbic908yQXBCs5iZZriU5IhDRIUqXe34UDJSIiIiaRqRJ1ijEoqRjb6sSW2yVugAgoBEySrYCBZ0IPDS+M/51Sy9svH+42WtzhrTD/aM72swy2dI22rmJ2SqTQEkhE6wCI8uEkoM953Z5K6Pk5rLdxkCJiIi8KsRiaxJnMkptomwHFwFyz/9St52JEREYIMftA9siMcJ8OGZUiD4YdLQMuGp2f6fWExRQd97YMJVVadCy9OboYEx7qmpd67GaNyzFreu6uWy3MVAiIiKvCrbMKIU4fsdaQoTtyd2NcWeXrZ4fXT03sknbtjiSUXplZi+kJtvut7LHtEepf7soq4yP5eMKtcap81uqdjFQem5aD7x4c0+3ru1NDJSIiMirQlUWGSUnSm/27m5ztNzlDFsZJcvhmaaksQGOZJScKTdKTBveW0cGWwVylg3xpqW3L+4b6vT17I0umNonucH3Opvfmz2krfHv9X2PmwIDJResWLECqampGDhwoLeXQkTk80w3zwX0JStH2bs7rjHuerPVo1RfWUgKTBxpLI8Kdn7uk+neceFBCpuB3B2D6gKOlbPr5lINstPbVZ8be9sOiCIcmILu7Cikl27uZfy7t0tvnMztgkWLFmHRokUoLS1FRESEt5dDROTTLJu5nelRsqcxMkq273qzf7xUenMkaDN+zU4EBdd3jsXvGUVoHxsCwc7E7Ren98BfBrdFalK42xOuuyeF2XzekS1GvL0NiTsYKBERkVdZNnO7Uoay1BjjAWzNUaqvLKQz9iiZv29AuyhcKarC1dJq43ORLnzNbaKCcfhvE4wDO20NDlfIZejZyjP/oLcX6jgSf7kzXJt3vRERUYumkMvMsi7OZpTeuK2PVTDSHEpvQzvG2FzLiM5x2PfUOHRLrMvQRDpYeusYF2L8e2CAHNEhSqgUhkCpsbf6sHN+R4aDurIyKdjt5aFAz1UMlIiIyOtqNHW3j3WKD3XqvTOva43jz09Cl4S69zVVM7etW+73PjkWH88fhDFd4wEASrl5xkwKnMqq6+5Cs7XeRyZ0MXvcIzkcX/9f3awmyzv7PDnnKNnG3YTunN6VGC7t2Qn4/ZnxHinFuoOlNyIiajZCVQqX9iKTsiqSxpijZHM8gI2MUlJEEJIigurWojB/nxTgqDX1b5JreuonJ3fDrQPaQGUyO8n07/bW5ypbQaG9PiNHLutMj9Idg9oA0PeuWfaveYP3V0BERGQwxMbmro4yTe40RunNVsZGdOCWrECLIK6jIWNWq60/UDLNVt03qqPVeyyDQ3ebtU1dKaqyes5eQOTpkt/fp/bw6PncxdIbERF53YNjOyExPBAvTPfML8kAW53NbrIZKDnwPtMMWef4UIw07E+naSBQspVZM80aWQaDnswo2WIvDssvVzf4XkdnIbWKDHIpo9iYmFEiIiKve3hiVzw8savHzufJ7IrE1YyS6VYjD4ztZGx+rm1g87U5Q9phy8lcTExNMD5n+nW1jw0xO74RYkMz9spn6tr6Az7A+7OQ3MFAiYiI/EJj/y62OR7AgYuaZkhMh2vayiiZZl5CVAps+L9hVscceHocajQ6RATZv1PumRu7N7wwJzX2TXWAY4FnU2PpjYiI/EJj/5K1PXDSgR4lk0DJdGZUAwklu+LDAtHaxmbApkv5k8lEbnv6tY106rr2xgA48j1w9EttfmESAyUiIiKHlFXXWj3XLbHhjWxNA6UgZdP03zjSr7R6nnPbcNk7o2nAl2Rnk+JmmChyGEtvRETkFxr7d3Gttu4K3z1wPbacysX/je7Y4PsCTXqUGrrd3Z2AwvS9jsxUcnYauL0eKNOMUmSwEjkl1bYPdEBzDKgYKBERETlgXPd4TOqRgEHtY9CrdQR6tXZsYrRZRqkR7+gyDVhsTRF3l71mbq1JSiklJhinckqtjnH0rrcEOxkpb2LpjYiIyAEBchnenTMAC65v79T7TG/jD26i0ltj3PVnr5qnE0V8ds9g3Ng7CS9M7+nSudfdMwSjusThrT/1dX2BjYQZJSIi8g/NsGxjybT0NntIW/x3XybmDm3nkXN74st/ZEIX/HahAJN6JOC5706avabR2r6CKALDOsZiWMdY+2trYHFDO8YY98ZrbhgoERERNSLTIMF0f7a/T+2BGf1aoXfrSI9fx1HhgQqUmuw5N6xTDP46rjN2nbtmdezu8/k2z6F19fY9H8HSGxER+YXm+uu6d+sIpCaFY2Jqgtkt9gFyGfq3i26UDXwdtfOxMfjxwRHGx1KwZasfaUiHaJvn0HpwPEBzxIwSERFRIwqQy/DDg9fbnUNkyp2AwtGGaVORwUqEB9YNrpSSQ7aWenO/Vnh8wzGr5x1qHG+Ot7M5iBklIiKiRuZIkOQ2F2MR08ZvaWinrdVabsIraWjkAVD/0nY+OqbB93sTAyUiIvILzXH7i6bkia/eeA4n4rpQRwIlO4t76eaeaBtjPWW8OWGgREREfmF013gAQGyoc4MUSb/BrlwmoFcr/WwoW/vaWZpg2Kx3/nDnxiUAwLhu8fj6/mH4swNbrXgbe5SIiMgvPHZDV3SIC8G47gneXorLEsNdH7joTkZty5KRqNWKxi1WLMOkaX2SAQBhKgXK1Br0aR2Bd2f3R3FVLaJDGg5MLde2ak5/rzaxO4OBEhER+YVgpQJ3Dk3x9jLc8vdpqVBrdJg9xPlMizt36SvkMpi2IFn2VEnbsHz5f0OxevclPDi+M2QywWaQ9Oqs3nj0q6P1Xs9XgiSAgRIREVGzER8WiA/mDvD2MuxO4e6WGI5/zepd73tvHdAGJ7JLsea3S8bnfLl7zHdCOiIiIrLLk8GIp3dA8eU+ewZKREREfsCzd/2ZR0q+HOi4i4ESERERmbEsvbkbJ5luDOxrfHflREREZNR4+SRA7uTAzPhwldnjm/u1cnNF3sNmbiIiIn/gwUjJco6SzMmmpfnD2+N8bjkm9tCPaghVKTC8Uwz2nC/w2BqbCgMlIiIiqpezzd2BAXK8cXtfs+d0Os+tpymx9EZEROQHOsaHeuxclskpRyZ1N0Tnox3hzCgRERH5gftHd4Rao8XEVPcnk2stpld6YlyAj8ZJDJSIiIj8QWCAHE9O7u6Rc1mOGrCc1O0KX80osfRGREREZiy3Q2nJpTcGSi5YsWIFUlNTMXDgQG8vhYiIyOMsM0qeKL25sxedNzFQcsGiRYtw8uRJHDx40NtLISIi8jirjJIHIiXPTg5vOgyUiIiIyIx1j5L752RGiYiIiPxCY/QoiR6dHd50GCgRERGRGcvGa2e3MLF5Tg6cJCIiIn9gGSjdNqCNx8/pKzhHiYiIiMyYxjTHn5+EUFXLDReYUSIiIiIz17WLAgAkRwR6LEhiRomIiIj8QkRQAI49NxGBAXKPndNX73pjoERERERWwgIDPHo+X80osfRGREREjc5H4yQGSkRERNT4mFEiIiIisoOBEhEREZEdHDhJREREZAc3xSUiIiKyw1fHAzBQIiIiokbHHiUiIiIiO5hRIiIiIrKDPUpEREREdrD0RkRERGTH7CHtAAAjOsd6eSXO4V5vRERE1OgWj+uMoR1i0LdtpLeX4hQGSkRERNToFHIZhnXyrWwSwNIbERERkV0MlIiIiIjsYKBEREREZAcDJSIiIiI7GCgRERER2cFAiYiIiMgOBkpEREREdjBQIiIiIrKDgRIRERGRHQyUiIiIiOxgoERERERkBwMlIiIiIjsYKBERERHZofD2AnyZKIoAgNLSUi+vhIiIiBwl/d6Wfo/Xh4GSG8rKygAAbdq08fJKiIiIyFllZWWIiIio9xhBdCScIpt0Oh2ys7MRFhYGQRA8cs6BAwfi4MGDHjmXp87nyjmceY+jxzZ0XH2vl5aWok2bNrh8+TLCw8MdWldz5enPiLeu6e45feVzWd8x/Fw2v+t643Pp7Pvc+cw5eoy/fzZFUURZWRmSk5Mhk9XfhcSMkhtkMhlat27t0XPK5XKPfig9cT5XzuHMexw9tqHjHDlPeHi4z/+f3tOfEW9d091z+srn0pFj+LlsPtf1xufS2fd54jPn6DH+/NlsKJMkYTN3M7No0aJmdz5XzuHMexw9tqHjPP29a6688XU2xjXdPaevfC6dva6v8tbX2Nx+Zrr6fk9/Nvm5rOPu18nSG7UIpaWliIiIQElJic//64j8Bz+X1Fzxs1mHGSVqEVQqFf7+979DpVJ5eylERvxcUnPFz2YdZpSIiIiI7GBGiYiIiMgOBkpEREREdjBQIiIiIrKDgRIRERGRHQyUiIiIiOxgoERkYcaMGYiKisKsWbO8vRRqwb7//nt07doVnTt3xgcffODt5RAZtbSfkRwPQGRh27ZtKC8vx8cff4yvvvrK28uhFkij0SA1NRXbtm1DeHg4rrvuOuzfvx/R0dHeXhpRi/sZyYwSkYUxY8YgLCzM28ugFuzAgQPo0aMHWrVqhbCwMEyZMgWbNm3y9rKIALS8n5EMlMin7Ny5E1OnTkVycjIEQcA333xjdcw777yD9u3bIzAwEP3798euXbuafqHUorn7Oc3OzkarVq2Mj1u3bo2srKymWDr5Of4MdR4DJfIpFRUV6NOnD95++22br69fvx4PPfQQnn76aaSlpWHEiBGYPHkyMjMzjcf0798fPXv2tPqTnZ3dVF8G+Tl3P6e2OiIEQWjUNVPL4ImfoS2OSOSjAIgbN240e27QoEHiwoULzZ7r1q2b+MQTTzh17m3btom33HKLu0skculzumfPHvHmm282vvbggw+Kn376aaOvlVoWd36GtqSfkcwokd+oqanBoUOHMHHiRLPnJ06ciN9++81LqyIy58jndNCgQTh+/DiysrJQVlaGH3/8EZMmTfLGcqkF4c9Q2xTeXgCRp+Tn50Or1SIhIcHs+YSEBFy9etXh80yaNAmHDx9GRUUFWrdujY0bN2LgwIGeXi61UI58ThUKBV5//XWMGTMGOp0Ojz32GGJiYryxXGpBHP0Z2tJ+RjJQIr9j2cshiqJT/R28u4iaQkOf02nTpmHatGlNvSyiBj+bLe1nJEtv5DdiY2Mhl8utskd5eXlW/0Ii8hZ+Tqm54mfTNgZK5DeUSiX69++PLVu2mD2/ZcsWDBs2zEurIjLHzyk1V/xs2sbSG/mU8vJynD9/3vg4PT0dR44cQXR0NNq2bYuHH34Yc+bMwYABAzB06FC89957yMzMxMKFC724ampp+Dml5oqfTRd4+a47Iqds27ZNBGD1Z+7cucZjVqxYIbZr105UKpXiddddJ+7YscN7C6YWiZ9Taq742XQe93ojIiIisoM9SkRERER2MFAiIiIisoOBEhEREZEdDJSIiIiI7GCgRERERGQHAyUiIiIiOxgoEREREdnBQImIiIjIDgZKRERERHYwUCIi8qJ58+ZBEAQIgoBvvvnGo+fevn278dw333yzR89N1FIwUCIijzL9xW/6x3QjTjJ3ww03ICcnB5MnTzY+Zy9wmjdvnsNBz7Bhw5CTk4PbbrvNQyslankU3l4AEfmfG264AatXrzZ7Li4uzuq4mpoaKJXKplpWs6VSqZCYmOjx8yqVSiQmJiIoKAhqtdrj5ydqCZhRIiKPk37xm/6Ry+UYPXo0HnjgATz88MOIjY3FhAkTAAAnT57ElClTEBoaioSEBMyZMwf5+fnG81VUVODOO+9EaGgokpKS8Prrr2P06NF46KGHjMfYysBERkZizZo1xsdZWVm4/fbbERUVhZiYGEyfPh2XLl0yvi5la1577TUkJSUhJiYGixYtQm1trfEYtVqNxx57DG3atIFKpULnzp3x4YcfQhRFdOrUCa+99prZGo4fPw6ZTIYLFy64/421cOnSJZvZu9GjR3v8WkQtFQMlImpSH3/8MRQKBfbs2YN3330XOTk5GDVqFPr27Yvff/8dP//8M3Jzc83KRY8++ii2bduGjRs3YvPmzdi+fTsOHTrk1HUrKysxZswYhIaGYufOndi9ezdCQ0Nxww03oKamxnjctm3bcOHCBWzbtg0ff/wx1qxZYxZs3Xnnnfj888/x1ltv4dSpU1i1ahVCQ0MhCALmz59vlUn76KOPMGLECHTs2NG1b1g92rRpg5ycHOOftLQ0xMTEYOTIkR6/FlGLJRIRedDcuXNFuVwuhoSEGP/MmjVLFEVRHDVqlNi3b1+z4//2t7+JEydONHvu8uXLIgDxzJkzYllZmahUKsXPP//c+HpBQYEYFBQkLl682PgcAHHjxo1m54mIiBBXr14tiqIofvjhh2LXrl1FnU5nfF2tVotBQUHipk2bjGtv166dqNFojMfceuut4u233y6KoiieOXNGBCBu2bLF5teenZ0tyuVycf/+/aIoimJNTY0YFxcnrlmzpt7v1/Tp062eByAGBgaafR9DQkJEhUJh8/iqqipx8ODB4k033SRqtVqHrkFEDWOPEhF53JgxY7By5Urj45CQEOPfBwwYYHbsoUOHsG3bNoSGhlqd58KFC6iqqkJNTQ2GDh1qfD46Ohpdu3Z1ak2HDh3C+fPnERYWZvZ8dXW1WVmsR48ekMvlxsdJSUk4duwYAODIkSOQy+UYNWqUzWskJSXhxhtvxEcffYRBgwbh+++/R3V1NW699Van1ipZvnw5xo8fb/bc448/Dq1Wa3XsggULUFZWhi1btkAmY7GAyFMYKBGRx4WEhKBTp052XzOl0+kwdepU/Otf/7I6NikpCefOnXPomoIgQBRFs+dMe4t0Oh369++PTz/91Oq9po3mAQEBVufV6XQAgKCgoAbXcffdd2POnDlYvnw5Vq9ejdtvvx3BwcEOfQ2WEhMTrb6PYWFhKC4uNnvupZdews8//4wDBw5YBYJE5B4GSkTkVddddx02bNiAlJQUKBTWP5I6deqEgIAA7Nu3D23btgUAFBUV4ezZs2aZnbi4OOTk5Bgfnzt3DpWVlWbXWb9+PeLj4xEeHu7SWnv16gWdTocdO3ZYZXokU6ZMQUhICFauXImffvoJO3fudOlajtqwYQNeeOEF/PTTT43SB0XU0jE/S0RetWjRIhQWFuKOO+7AgQMHcPHiRWzevBnz58+HVqtFaGgoFixYgEcffRRbt27F8ePHMW/ePKvy0tixY/H222/j8OHD+P3337Fw4UKz7NBf/vIXxMbGYvr06di1axfS09OxY8cOLF68GFeuXHForSkpKZg7dy7mz5+Pb775Bunp6di+fTu++OIL4zFyuRzz5s3Dk08+iU6dOpmVDD3t+PHjuPPOO/H444+jR48euHr1Kq5evYrCwsJGuyZRS8NAiYi8Kjk5GXv27IFWq8WkSZPQs2dPLF68GBEREcZg6NVXX8XIkSMxbdo0jB8/Htdffz369+9vdp7XX38dbdq0wciRI/HnP/8ZS5cuNSt5BQcHY+fOnWjbti1mzpyJ7t27Y/78+aiqqnIqw7Ry5UrMmjUL999/P7p164Z77rkHFRUVZscsWLAANTU1mD9/vhvfmYb9/vvvqKysxEsvvYSkpCTjn5kzZzbqdYlaEkG0LOoTEfmA0aNHo2/fvnjzzTe9vRQre/bswejRo3HlyhUkJCTUe+y8efNQXFzs8e1LmvoaRP6KGSUiIg9Rq9U4f/48/va3v+G2225rMEiSfP/99wgNDcX333/v0fXs2rULoaGhNhvYicgxbOYmIvKQdevWYcGCBejbty/Wrl3r0HuWLVuGZ555BoD+Lj9PGjBgAI4cOQIANscvEFHDWHojIiIisoOlNyIiIiI7GCgRERER2cFAiYiIiMgOBkpEREREdjBQIiIiIrKDgRIRERGRHQyUiIiIiOxgoERERERkx/8D7LlZwucDtDgAAAAASUVORK5CYII=",
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",
       "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
+       "<Figure size 640x480 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -909,7 +929,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.15"
+   "version": "3.10.13"
   },
   "vscode": {
    "interpreter": {
diff --git a/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc b/examples/data/dolfyn/test_data/Sig1000_tidal_bin.nc
index 4f5ffec15c96ebb729e16ce540a4cd3e211b68c3..bbc4df99a295c4d4f92061b1eb4f976bb8295b55 100644
GIT binary patch
delta 8858
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diff --git a/examples/data/dolfyn/test_data/dat_vm.mat b/examples/data/dolfyn/test_data/dat_vm.mat
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diff --git a/examples/data/dolfyn/test_data/vmdas01_wh.nc b/examples/data/dolfyn/test_data/vmdas01_wh.nc
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diff --git a/mhkit/dolfyn/adp/turbulence.py b/mhkit/dolfyn/adp/turbulence.py
index d85f365ab..0ab3866f2 100644
--- a/mhkit/dolfyn/adp/turbulence.py
+++ b/mhkit/dolfyn/adp/turbulence.py
@@ -128,7 +128,7 @@ def __init__(
         self.diff_style = diff_style
         self.orientation = orientation
 
-    def _diff_func(self, vel, u):
+    def _diff_func(self, vel, u, orientation):
         """Applies the chosen style of numerical differentiation to velocity data.
 
         This method calculates the derivative of the velocity data 'vel' with respect to the 'range'
@@ -149,15 +149,23 @@ def _diff_func(self, vel, u):
             The calculated derivative of the velocity data.
         """
 
+        if not orientation:
+            orientation = self.orientation
+        sign = 1
+        if orientation == "down":
+            sign *= -1
+
         if self.diff_style == "first":
             out = _diffz_first(vel[u].values, vel["range"].values)
-            return out, vel.range[1:]
+            return sign * out, vel.range[1:]
+
         elif self.diff_style == "centered":
             out = _diffz_centered(vel[u].values, vel["range"].values)
-            return out, vel.range[1:-1]
+            return sign * out, vel.range[1:-1]
+
         elif self.diff_style == "centered_extended":
             out = _diffz_centered_extended(vel[u].values, vel["range"].values)
-            return out, vel.range
+            return sign * out, vel.range
 
     def dudz(self, vel, orientation=None):
         """
@@ -182,13 +190,7 @@ def dudz(self, vel, orientation=None):
         'true vertical' direction.
         """
 
-        if not orientation:
-            orientation = self.orientation
-        sign = 1
-        if orientation == "down":
-            sign *= -1
-
-        dudz, rng = sign * self._diff_func(vel, 0)
+        dudz, rng = self._diff_func(vel, 0, orientation)
         return xr.DataArray(
             dudz,
             coords=[rng, vel.time],
@@ -196,7 +198,7 @@ def dudz(self, vel, orientation=None):
             attrs={"units": "s-1", "long_name": "Shear in X-direction"},
         )
 
-    def dvdz(self, vel):
+    def dvdz(self, vel, orientation=None):
         """
         The shear in the second velocity component.
 
@@ -204,6 +206,8 @@ def dvdz(self, vel):
         ----------
         vel : xarray.DataArray
           ADCP raw velocity
+        orientation : str, default=ADPBinner.orientation
+          Direction ADCP is facing ('up' or 'down')
 
         Returns
         -------
@@ -217,7 +221,7 @@ def dvdz(self, vel):
         'true vertical' direction.
         """
 
-        dvdz, rng = self._diff_func(vel, 1)
+        dvdz, rng = self._diff_func(vel, 1, orientation)
         return xr.DataArray(
             dvdz,
             coords=[rng, vel.time],
@@ -225,7 +229,7 @@ def dvdz(self, vel):
             attrs={"units": "s-1", "long_name": "Shear in Y-direction"},
         )
 
-    def dwdz(self, vel):
+    def dwdz(self, vel, orientation=None):
         """
         The shear in the third velocity component.
 
@@ -233,6 +237,8 @@ def dwdz(self, vel):
         ----------
         vel : xarray.DataArray
           ADCP raw velocity
+        orientation : str, default=ADPBinner.orientation
+          Direction ADCP is facing ('up' or 'down')
 
         Returns
         -------
@@ -246,7 +252,7 @@ def dwdz(self, vel):
         'true vertical' direction.
         """
 
-        dwdz, rng = self._diff_func(vel, 2)
+        dwdz, rng = self._diff_func(vel, 2, orientation)
         return xr.DataArray(
             dwdz,
             coords=[rng, vel.time],
@@ -537,7 +543,7 @@ def _beam_variance(self, ds, time, noise, beam_order, n_beams):
             )
 
         # Calculate along-beam velocity prime squared bar
-        bp2_ = np.empty((n_beams, len(ds.range), len(time))) * np.nan
+        bp2_ = np.empty((n_beams, len(ds["range"]), len(time))) * np.nan
         for i, beam in enumerate(beam_order):
             bp2_[i] = np.nanvar(self.reshape(beam_vel[beam]), axis=-1)
 
@@ -602,7 +608,7 @@ def reynolds_stress_4beam(self, ds, noise=None, orientation=None, beam_angle=Non
             np.stack([upwp_ * np.nan, upwp_, vpwp_]).astype("float32"),
             coords={
                 "tau": ["upvp_", "upwp_", "vpwp_"],
-                "range": ds.range,
+                "range": ds["range"],
                 "time": time,
             },
             attrs={"units": "m2 s-2", "long_name": "Specific Reynolds Stress Vector"},
@@ -646,7 +652,7 @@ def stress_tensor_5beam(
         in pitch and roll. u'v'_ cannot be directly calculated by a 5-beam ADCP,
         so it is approximated by the covariance of `u` and `v`. The uncertainty
         introduced by using this approximation is small if deviations from pitch
-        and roll are small (< 10 degrees).
+        and roll are small (<= 5 degrees).
 
         Dewey, R., and S. Stringer. "Reynolds stresses and turbulent kinetic
         energy estimates from various ADCP beam configurations: Theory." J. of
@@ -663,7 +669,7 @@ def stress_tensor_5beam(
 
         # Run through warnings
         b_angle, noise = self._stress_func_warnings(
-            ds, beam_angle, noise, tilt_thresh=10
+            ds, beam_angle, noise, tilt_thresh=5
         )
 
         # Fetch beam order
@@ -713,7 +719,7 @@ def stress_tensor_5beam(
             np.stack([upup_, vpvp_, wpwp_]).astype("float32"),
             coords={
                 "tke": ["upup_", "vpvp_", "wpwp_"],
-                "range": ds.range,
+                "range": ds["range"],
                 "time": time,
             },
             attrs={
@@ -752,7 +758,7 @@ def stress_tensor_5beam(
                 np.stack([upvp_, upwp_, vpwp_]).astype("float32"),
                 coords={
                     "tau": ["upvp_", "upwp_", "vpwp_"],
-                    "range": ds.range,
+                    "range": ds["range"],
                     "time": time,
                 },
                 attrs={
@@ -763,49 +769,6 @@ def stress_tensor_5beam(
 
             return tke_vec, stress_vec
 
-    def total_turbulent_kinetic_energy(
-        self, ds, noise=None, orientation=None, beam_angle=None
-    ):
-        """
-        Calculate magnitude of turbulent kinetic energy from 5-beam ADCP.
-
-        Parameters
-        ----------
-        ds : xarray.Dataset
-          Raw dataset in beam coordinates
-        noise : int or xarray.DataArray, default=0 (time)
-          Doppler noise level in units of m/s
-        orientation : str, default=ds.attrs['orientation']
-          Direction ADCP is facing ('up' or 'down')
-        beam_angle : int, default=ds.attrs['beam_angle']
-          ADCP beam angle in units of degrees
-
-        Returns
-        -------
-        tke : xarray.DataArray
-          Turbulent kinetic energy magnitude
-
-        Notes
-        -----
-        This function is a wrapper around 'calc_stress_5beam' that then
-        combines the TKE components.
-
-        Warning: the integral length scale of turbulence captured by the
-        ADCP measurements (i.e. the size of turbulent structures) increases
-        with increasing range from the instrument.
-        """
-
-        tke_vec = self.stress_tensor_5beam(
-            ds, noise, orientation, beam_angle, tke_only=True
-        )
-
-        tke = tke_vec.sum("tke") / 2
-        tke.attrs["units"] = "m2 s-2"
-        tke.attrs["long_name"] = ("TKE Magnitude",)
-        tke.attrs["standard_name"] = "specific_turbulent_kinetic_energy_of_sea_water"
-
-        return tke.astype("float32")
-
     def check_turbulence_cascade_slope(self, psd, freq_range=[0.2, 0.4]):
         """
         This function calculates the slope of the PSD, the power spectra
@@ -1027,11 +990,11 @@ def dissipation_rate_SF(self, vel_raw, r_range=[1, 5]):
             )
 
         if "range_b5" in vel_raw.dims:
-            rng = vel_raw.range_b5
-            time = self.mean(vel_raw.time_b5.values)
+            rng = vel_raw["range_b5"]
+            time = self.mean(vel_raw["time_b5"].values)
         else:
-            rng = vel_raw.range
-            time = self.mean(vel_raw.time.values)
+            rng = vel_raw["range"]
+            time = self.mean(vel_raw["time"].values)
 
         # bm shape is [range, ensemble time, 'data within ensemble']
         bm = self.demean(vel_raw.values)  # take out the ensemble mean
@@ -1139,7 +1102,7 @@ def friction_velocity(self, ds_avg, upwp_, z_inds=slice(1, 5), H=None):
             raise TypeError("`z_inds` must be an instance of `slice(int,int)`.")
 
         if not H:
-            H = ds_avg.depth.values
+            H = ds_avg["depth"].values
         z = ds_avg["range"].values
         upwp_ = upwp_.values
 
@@ -1151,6 +1114,6 @@ def friction_velocity(self, ds_avg, upwp_, z_inds=slice(1, 5), H=None):
 
         return xr.DataArray(
             u_star.astype("float32"),
-            coords={"time": ds_avg.time},
+            coords={"time": ds_avg["time"]},
             attrs={"units": "m s-1", "long_name": "Friction Velocity"},
         )
diff --git a/mhkit/dolfyn/adv/motion.py b/mhkit/dolfyn/adv/motion.py
index 7db6f2797..f4a9e7568 100644
--- a/mhkit/dolfyn/adv/motion.py
+++ b/mhkit/dolfyn/adv/motion.py
@@ -2,7 +2,7 @@
 import xarray as xr
 import warnings
 import scipy.signal as ss
-from scipy.integrate import cumtrapz
+from scipy.integrate import cumulative_trapezoid
 
 from ..rotate import vector as rot
 from ..rotate.api import _make_model, rotate2
@@ -188,7 +188,7 @@ def calc_velacc(
         dat = np.concatenate(
             (
                 np.zeros(list(hp.shape[:-1]) + [1]),
-                cumtrapz(hp, dx=1 / samp_freq, axis=-1),
+                cumulative_trapezoid(hp, dx=1 / samp_freq, axis=-1),
             ),
             axis=-1,
         )
diff --git a/mhkit/dolfyn/adv/turbulence.py b/mhkit/dolfyn/adv/turbulence.py
index 83ae80a7a..3fb4ef9a4 100644
--- a/mhkit/dolfyn/adv/turbulence.py
+++ b/mhkit/dolfyn/adv/turbulence.py
@@ -54,7 +54,7 @@ def __call__(self, ds, freq_units="rad/s", window="hann"):
     def reynolds_stress(self, veldat, detrend=True):
         """
         Calculate the specific Reynolds stresses
-        (cross-covariances of u,v,w in m^2/s^2)
+        (covariances of u,v,w in m^2/s^2)
 
         Parameters
         ----------
@@ -76,7 +76,7 @@ def reynolds_stress(self, veldat, detrend=True):
         if not isinstance(veldat, xr.DataArray):
             raise TypeError("`veldat` must be an instance of `xarray.DataArray`.")
 
-        time = self.mean(veldat.time.values)
+        time = self.mean(veldat["time"].values)
         vel = veldat.values
 
         out = np.empty(self._outshape(vel[:3].shape)[:-1], dtype=np.float32)
@@ -144,7 +144,7 @@ def cross_spectral_density(
 
         fs_in = self._parse_fs(fs)
         n_fft = self._parse_nfft_coh(n_fft_coh)
-        time = self.mean(veldat.time.values)
+        time = self.mean(veldat["time"].values)
         veldat = veldat.values
         if len(np.shape(veldat)) != 2:
             raise Exception(
@@ -391,7 +391,7 @@ def dissipation_rate_LT83(self, psd, U_mag, freq_range=[6.28, 12.57], noise=None
             raise TypeError("`psd` must be an instance of `xarray.DataArray`.")
         if len(U_mag.shape) != 1:
             raise Exception("U_mag should be 1-dimensional (time)")
-        if len(psd.time) != len(U_mag.time):
+        if len(psd["time"]) != len(U_mag["time"]):
             raise Exception("`U_mag` should be from ensembled-averaged dataset")
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
@@ -459,7 +459,7 @@ def dissipation_rate_SF(self, vel_raw, U_mag, fs=None, freq_range=[2.0, 4.0]):
 
         if not isinstance(vel_raw, xr.DataArray):
             raise TypeError("`vel_raw` must be an instance of `xarray.DataArray`.")
-        if len(vel_raw.time) == len(U_mag.time):
+        if len(vel_raw["time"]) == len(U_mag["time"]):
             raise Exception("`U_mag` should be from ensembled-averaged dataset")
         if not hasattr(freq_range, "__iter__") or len(freq_range) != 2:
             raise ValueError("`freq_range` must be an iterable of length 2.")
@@ -586,8 +586,8 @@ def dissipation_rate_TE01(self, dat_raw, dat_avg, freq_range=[6.28, 12.57]):
 
         # Index data to be used
         inds = (freq_range[0] < freq) & (freq < freq_range[1])
-        psd = dat_avg.psd[..., inds].values
-        freq = freq[inds].reshape([1] * (dat_avg.psd.ndim - 2) + [sum(inds)])
+        psd = dat_avg["psd"][..., inds].values
+        freq = freq[inds].reshape([1] * (dat_avg["psd"].ndim - 2) + [sum(inds)])
 
         # Estimate values
         # u & v components (equation 6)
@@ -606,7 +606,7 @@ def dissipation_rate_TE01(self, dat_raw, dat_avg, freq_range=[6.28, 12.57]):
 
         return xr.DataArray(
             out.astype("float32"),
-            coords={"time": dat_avg.psd.time},
+            coords={"time": dat_avg["psd"]["time"]},
             dims="time",
             attrs={
                 "units": "m2 s-3",
@@ -645,7 +645,7 @@ def integral_length_scales(self, a_cov, U_mag, fs=None):
 
         if not isinstance(a_cov, xr.DataArray):
             raise TypeError("`a_cov` must be an instance of `xarray.DataArray`.")
-        if len(a_cov.time) != len(U_mag.time):
+        if len(a_cov["time"]) != len(U_mag["time"]):
             raise Exception("`U_mag` should be from ensembled-averaged dataset")
 
         acov = a_cov.values
@@ -656,7 +656,7 @@ def integral_length_scales(self, a_cov, U_mag, fs=None):
 
         return xr.DataArray(
             L_int.astype("float32"),
-            coords={"dir": a_cov.dir, "time": a_cov.time},
+            coords={"dir": a_cov["dir"], "time": a_cov["time"]},
             attrs={
                 "units": "m",
                 "long_name": "Integral Length Scale",
diff --git a/mhkit/dolfyn/rotate/api.py b/mhkit/dolfyn/rotate/api.py
index 835b170e2..6226789d9 100644
--- a/mhkit/dolfyn/rotate/api.py
+++ b/mhkit/dolfyn/rotate/api.py
@@ -252,7 +252,10 @@ def set_declination(ds, declin, inplace=True):
         Rdec,
     )
     if "heading" in ds:
-        ds["heading"] += angle
+        heading = ds["heading"] + angle
+        heading[heading > 180] -= 360
+        ds["heading"].values = heading
+
     if rotate2earth:
         rotate2(ds, "earth", inplace=True)
     if "principal_heading" in ds.attrs:
diff --git a/mhkit/tests/dolfyn/test_analysis.py b/mhkit/tests/dolfyn/test_analysis.py
index da10f5449..80990116a 100644
--- a/mhkit/tests/dolfyn/test_analysis.py
+++ b/mhkit/tests/dolfyn/test_analysis.py
@@ -130,6 +130,8 @@ def test_adcp_turbulence(self):
             dat.vel.mean("range")
         )
         bnr = apm.ADPBinner(n_bin=20.0, fs=dat.fs, diff_style="centered")
+        U_mag = dat.velds.U_mag
+        dat["U_mag"] = U_mag
         tdat = bnr.bin_average(dat)
 
         tdat["dudz"] = bnr.dudz(tdat["vel"])
@@ -137,11 +139,11 @@ def test_adcp_turbulence(self):
         tdat["dwdz"] = bnr.dwdz(tdat["vel"])
         tdat["tau2"] = bnr.shear_squared(tdat["vel"])
         tdat["I"] = tdat.velds.I
-        tdat["ti"] = bnr.turbulence_intensity(dat.velds.U_mag, detrend=False)
+        tdat["ti"] = bnr.turbulence_intensity(U_mag, detrend=False)
         dat.velds.rotate2("beam")
 
         tdat["psd"] = bnr.power_spectral_density(
-            dat["vel"].isel(dir=2, range=len(dat.range) // 2), freq_units="Hz"
+            dat["vel"].isel(dir=2, range=len(dat["range"]) // 2), freq_units="Hz"
         )
         tdat["noise"] = bnr.doppler_noise_level(tdat["psd"], pct_fN=0.8)
         tdat["stress_vec4"] = bnr.reynolds_stress_4beam(
@@ -150,22 +152,23 @@ def test_adcp_turbulence(self):
         tdat["tke_vec5"], tdat["stress_vec5"] = bnr.stress_tensor_5beam(
             dat, noise=tdat["noise"], orientation="up", beam_angle=25, tke_only=False
         )
-        tdat["tke"] = bnr.total_turbulent_kinetic_energy(
-            dat, noise=tdat["noise"], orientation="up", beam_angle=25
-        )
+        # Back in "inst" coordinate frame now
+        dat.velds.rotate2("beam")
+
+        # This needs U_mag in principal direction
         tdat["ti_noise"] = bnr.turbulence_intensity(
-            dat.velds.U_mag, detrend=False, noise=tdat["noise"]
+            U_mag, detrend=False, noise=tdat["noise"]
         )
         # This is "negative" for this code check
         tdat["wpwp"] = bnr.turbulent_kinetic_energy(dat["vel_b5"], noise=tdat["noise"])
         tdat["dissipation_rate_LT83"] = bnr.dissipation_rate_LT83(
             tdat["psd"],
-            tdat.velds.U_mag.isel(range=len(dat.range) // 2),
+            tdat["U_mag"].isel(range=len(dat["range"]) // 2),
             freq_range=[0.2, 0.4],
         )
         tdat["dissipation_rate_LT83_noise"] = bnr.dissipation_rate_LT83(
             tdat["psd"],
-            tdat.velds.U_mag.isel(range=len(dat.range) // 2),
+            tdat["U_mag"].isel(range=len(dat["range"]) // 2),
             freq_range=[0.2, 0.4],
             noise=tdat["noise"],
         )
@@ -173,18 +176,20 @@ def test_adcp_turbulence(self):
             tdat["dissipation_rate_SF"],
             tdat["noise_SF"],
             tdat["D_SF"],
-        ) = bnr.dissipation_rate_SF(dat.vel.isel(dir=2), r_range=[1, 5])
-        tdat["friction_vel"] = bnr.friction_velocity(
-            tdat, upwp_=tdat["stress_vec5"].sel(tau="upwp_"), z_inds=slice(1, 5), H=50
-        )
+        ) = bnr.dissipation_rate_SF(dat["vel"].isel(dir=2), r_range=[1, 5])
+
         slope_check = bnr.check_turbulence_cascade_slope(
             tdat["psd"].mean("time"), freq_range=[0.4, 4]
         )
+        # Check noise subtraction in psd function
         tdat["psd_noise"] = bnr.power_spectral_density(
-            dat["vel"].isel(dir=2, range=len(dat.range) // 2),
+            dat["vel"].isel(dir=2, range=len(dat["range"]) // 2),
             freq_units="Hz",
             noise=0.01,
         )
+        tdat["friction_vel"] = bnr.friction_velocity(
+            tdat, upwp_=tdat["stress_vec5"].sel(tau="upwp_"), z_inds=slice(1, 5), H=50
+        )
 
         if make_data:
             save(tdat, "Sig1000_tidal_bin.nc")

From cf877b621b9a395d0aa8c2be4b7b793d66df5407 Mon Sep 17 00:00:00 2001
From: Andrew Simms <simms.andrew@gmail.com>
Date: Wed, 10 Jul 2024 15:08:45 -0600
Subject: [PATCH 4/7] Improve `surface_elevation` internal method selection
 (#340)

* Test: Determine method using input frequency index

* Feat: Use sum of sines if ifft is not computable

This change allows `surface_elevation` to return a result if the user
inputs a spectrum with a frequency index that does not have a zero
frequency.

If the non zero frequency index condition is found when the method is
`ifft` we warn the user and change the method to `sum_of_sines`

* Fix: Use previously found frequency index

S.index may not exist for some input datasets, but f[0] does and we
should use the value of f[0] here.

* Test: Warn when using ifft with a non zero frequency

* Lint
---
 mhkit/tests/wave/test_resource_spectrum.py | 31 ++++++++++++++++++++++
 mhkit/wave/resource.py                     |  7 +++--
 2 files changed, 36 insertions(+), 2 deletions(-)

diff --git a/mhkit/tests/wave/test_resource_spectrum.py b/mhkit/tests/wave/test_resource_spectrum.py
index 4907a5638..387f87189 100644
--- a/mhkit/tests/wave/test_resource_spectrum.py
+++ b/mhkit/tests/wave/test_resource_spectrum.py
@@ -8,6 +8,7 @@
 import pandas as pd
 import numpy as np
 import unittest
+import pytest
 import os
 
 
@@ -158,6 +159,36 @@ def test_ifft_sum_of_sines(self):
 
         assert_allclose(eta_ifft, eta_sos)
 
+    def test_surface_elevation_uses_sum_of_sines_when_input_frequency_index_does_not_have_zero(
+        self,
+    ):
+        f = np.linspace(1 / 30, 1 / 2, 32)
+        S = wave.resource.jonswap_spectrum(f, self.Tp, self.Hs)
+
+        eta_default = wave.resource.surface_elevation(S, self.t, seed=1)
+        eta_sos = wave.resource.surface_elevation(
+            S, self.t, seed=1, method="sum_of_sines"
+        )
+
+        assert_allclose(eta_default, eta_sos)
+
+    def test_surface_elevation_warn_user_if_zero_frequency_not_defined_and_using_ifft(
+        self,
+    ):
+        f = np.linspace(1 / 30, 1 / 2, 32)
+        S = wave.resource.jonswap_spectrum(f, self.Tp, self.Hs)
+
+        with pytest.warns(UserWarning):
+            wave.resource.surface_elevation(S, self.t, seed=1, method="ifft")
+
+    def test_surface_elevation_uses_ifft_when_input_frequency_index_has_zero(self):
+        S = wave.resource.jonswap_spectrum(self.f, self.Tp, self.Hs)
+
+        eta_default = wave.resource.surface_elevation(S, self.t, seed=1)
+        eta_ifft = wave.resource.surface_elevation(S, self.t, seed=1, method="ifft")
+
+        assert_allclose(eta_default, eta_ifft)
+
     def test_plot_spectrum(self):
         filename = abspath(join(plotdir, "wave_plot_spectrum.png"))
         if isfile(filename):
diff --git a/mhkit/wave/resource.py b/mhkit/wave/resource.py
index e38214eeb..7475fb331 100644
--- a/mhkit/wave/resource.py
+++ b/mhkit/wave/resource.py
@@ -1,3 +1,5 @@
+import warnings
+
 from scipy.optimize import fsolve as _fsolve
 from scipy import signal as _signal
 import pandas as pd
@@ -335,9 +337,10 @@ def surface_elevation(
 
     if method == "ifft":
         if not f[0] == 0:
-            raise ValueError(
-                f"ifft method must have zero frequency defined. Lowest frequency is: {S.index.values[0]}"
+            warnings.warn(
+                f"ifft method must have zero frequency defined. Lowest frequency is: {f[0].values}. Setting method to less efficient `sum_of_sines` method."
             )
+            method = "sum_of_sines"
 
     if frequency_bins is None:
         delta_f = f.values[1] - f.values[0]

From 62399e66f36008d360ed44d276987cb3d0ccd4fa Mon Sep 17 00:00:00 2001
From: jmcvey3 <53623232+jmcvey3@users.noreply.github.com>
Date: Thu, 11 Jul 2024 14:31:19 -0700
Subject: [PATCH 5/7] Fix typos, docstrings

---
 mhkit/river/io/usgs.py | 8 ++++----
 mhkit/tidal/io/noaa.py | 6 +++---
 mhkit/wave/io/ndbc.py  | 6 +++---
 3 files changed, 10 insertions(+), 10 deletions(-)

diff --git a/mhkit/river/io/usgs.py b/mhkit/river/io/usgs.py
index 54c97966c..9b104f826 100644
--- a/mhkit/river/io/usgs.py
+++ b/mhkit/river/io/usgs.py
@@ -82,7 +82,7 @@ def request_usgs_data(
     station : str
         USGS station number (e.g. '08313000')
     parameter : str
-        USGS paramter ID (e.g. '00060' for Discharge, cubic feet per second)
+        USGS parameter ID (e.g. '00060' for Discharge, cubic feet per second)
     start_date : str
         Start date in the format 'YYYY-MM-DD' (e.g. '2018-01-01')
     end_date : str
@@ -91,8 +91,8 @@ def request_usgs_data(
         Data type, options include 'Daily' (return the mean daily value) and
         'Instantaneous'.
     proxy : dict or None
-         To request data from behind a firewall, define a dictionary of proxy settings,
-         for example {"http": 'localhost:8080'}
+        To request data from behind a firewall, define a dictionary of proxy settings,
+        for example {"http": 'localhost:8080'}
     write_json : str or None
         Name of json file to write data
     clear_cache : bool
@@ -106,7 +106,7 @@ def request_usgs_data(
         Data indexed by datetime with columns named according to the parameter's
         variable description
     """
-    if not data_type in ["Daily", "Instantaneous"]:
+    if data_type not in ["Daily", "Instantaneous"]:
         raise ValueError(f"data_type must be Daily or Instantaneous. Got: {data_type}")
 
     if not isinstance(to_pandas, bool):
diff --git a/mhkit/tidal/io/noaa.py b/mhkit/tidal/io/noaa.py
index 0f9b118e7..d0aadc861 100644
--- a/mhkit/tidal/io/noaa.py
+++ b/mhkit/tidal/io/noaa.py
@@ -58,7 +58,7 @@ def request_noaa_data(
     station : str
         NOAA current station number (e.g. 'cp0101', "s08010", "9446484")
     parameter : str
-        NOAA paramter (e.g. "currents", "salinity", "water_level", "water_temperature",
+        NOAA parameter (e.g. "currents", "salinity", "water_level", "water_temperature",
         "air_temperature", "wind", "air_pressure")
         https://api.tidesandcurrents.noaa.gov/api/prod/
     start_date : str
@@ -66,8 +66,8 @@ def request_noaa_data(
     end_date : str
         End date in the format yyyyMMdd
     proxy : dict or None
-         To request data from behind a firewall, define a dictionary of proxy
-         settings, for example {"http": 'localhost:8080'}
+        To request data from behind a firewall, define a dictionary of proxy
+        settings, for example {"http": 'localhost:8080'}
     write_json : str or None
         Name of json file to write data
     clear_cache : bool
diff --git a/mhkit/wave/io/ndbc.py b/mhkit/wave/io/ndbc.py
index 268c3390e..12ad3e9a7 100644
--- a/mhkit/wave/io/ndbc.py
+++ b/mhkit/wave/io/ndbc.py
@@ -329,10 +329,10 @@ def request_data(parameter, filenames, proxy=None, clear_cache=False, to_pandas=
         'cwind' :   'Continuous Winds Current Year Historical Data'
 
     filenames: pandas Series, pandas DataFrame, xarray DataArray, or xarray Dataset
-            Data filenames on https://www.ndbc.noaa.gov/data/historical/{parameter}/
+        Data filenames on https://www.ndbc.noaa.gov/data/historical/{parameter}/
 
     proxy: dict
-            Proxy dict passed to python requests,
+        Proxy dict passed to python requests,
         (e.g. proxy_dict= {"http": 'http:wwwproxy.yourProxy:80/'})
 
     to_pandas: bool (optional)
@@ -631,7 +631,7 @@ def parameter_units(parameter=""):
     If no parameter is passed then an ordered dictionary of all NDBC
     parameterz specified unites is returned. If a parameter is specified
     then only the units associated with that parameter are returned.
-    Note that many NDBC paramters report multiple measurements and in
+    Note that many NDBC parameters report multiple measurements and in
     that case the returned dictionary will contain the NDBC measurement
     name and associated unit for all the measurements associated with
     the specified parameter. Optional parameter values are given below.

From 2c49815de0e31e0ebd8e140a4c0ef88bbb6a2605 Mon Sep 17 00:00:00 2001
From: ssolson <ssolson@users.noreply.github.com>
Date: Fri, 12 Jul 2024 22:54:22 -0600
Subject: [PATCH 6/7] ipython notebook test (#330)

This PR adds a Github action to test the example notebooks as part of or CD pipeline. Additionally a timeout is added to which notebooks will fail if they exceed the given time.
---
 .github/workflows/generate_notebook_matrix.py |  56 ++
 .github/workflows/main.yml                    | 127 ++++-
 examples/SWAN_example.ipynb                   |  56 +-
 examples/metocean_example.ipynb               |  14 +-
 examples/mooring_example.ipynb                |  79 +--
 examples/wave_example.ipynb                   | 530 +++++++++++-------
 6 files changed, 567 insertions(+), 295 deletions(-)
 create mode 100644 .github/workflows/generate_notebook_matrix.py

diff --git a/.github/workflows/generate_notebook_matrix.py b/.github/workflows/generate_notebook_matrix.py
new file mode 100644
index 000000000..39899ff77
--- /dev/null
+++ b/.github/workflows/generate_notebook_matrix.py
@@ -0,0 +1,56 @@
+"""
+Dynamically creates a matrix for the GitHub Actions workflow that
+runs the notebooks in the examples directory.
+"""
+
+import os
+import json
+
+# Dictionary to store custom timeouts for each notebook
+notebook_timeouts = {
+    "ADCP_Delft3D_TRTS_example.ipynb": 1200,
+    "adcp_example.ipynb": 240,
+    "adv_example.ipynb": 180,
+    "cdip_example.ipynb": 180,
+    "Delft3D_example.ipynb": 180,
+    "directional_waves.ipynb": 180,
+    "environmental_contours_example.ipynb": 720,
+    "extreme_response_contour_example.ipynb": 360,
+    "extreme_response_full_sea_state_example.ipynb": 420,
+    "extreme_response_MLER_example.ipynb": 650,
+    "loads_example.ipynb": 180,
+    "metocean_example.ipynb": 240,
+    "mooring_example.ipynb": 300,
+    "PacWave_resource_characterization_example.ipynb": 780,
+    "power_example.ipynb": 180,
+    "qc_example.ipynb": 180,
+    "river_example.ipynb": 240,
+    "short_term_extremes_example.ipynb": 180,
+    "SWAN_example.ipynb": 180,
+    "tidal_example.ipynb": 240,
+    "tidal_performance_example.ipynb": 180,
+    "upcrossing_example.ipynb": 180,
+    "wave_example.ipynb": 180,
+    "wecsim_example.ipynb": 180,
+    "WPTO_hindcast_example.ipynb": 1200,
+    "default": 300,  # Default timeout for other notebooks
+}
+notebooks = []
+for root, dirs, files in os.walk("examples"):
+    for file in files:
+        if file.endswith(".ipynb"):
+            notebooks.append(os.path.join(root, file))
+
+# Generate the matrix configuration
+matrix = {"include": []}
+for notebook in notebooks:
+    timeout = notebook_timeouts.get(
+        os.path.basename(notebook), notebook_timeouts["default"]
+    )
+
+    matrix["include"].append({"notebook": notebook, "timeout": timeout})
+
+
+# Print the matrix as a properly formatted JSON string
+matrix_json = json.dumps(matrix)
+print(f"matrix={matrix_json}")
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
index 70da8c7c7..d6bd0ce7f 100644
--- a/.github/workflows/main.yml
+++ b/.github/workflows/main.yml
@@ -1,4 +1,4 @@
-name: Py 3.8, 3.9, 3.10, 3.11 | Windows Mac Linux
+name: Py 3.10, 3.11 | Windows Mac Linux
 
 on:
   push:
@@ -52,7 +52,7 @@ jobs:
   prepare-nonhindcast-cache:
     runs-on: ubuntu-latest
     env:
-      PYTHON_VER: 3.9
+      PYTHON_VER: 3.11
     steps:
       - name: Checkout code
         uses: actions/checkout@v4
@@ -95,7 +95,7 @@ jobs:
     needs: [check-changes]
     runs-on: ubuntu-latest
     env:
-      PYTHON_VER: 3.9
+      PYTHON_VER: 3.11
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
@@ -137,7 +137,7 @@ jobs:
     needs: [check-changes, prepare-wave-hindcast-cache]
     runs-on: ubuntu-latest
     env:
-      PYTHON_VER: 3.9
+      PYTHON_VER: 3.11
     if: (needs.check-changes.outputs.should-run-hindcast == 'true')
     steps:
       - name: Checkout code
@@ -183,7 +183,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.10', '3.11']
     env:
       PYTHON_VER: ${{ matrix.python-version }}
 
@@ -234,7 +234,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.10', '3.11']
 
     steps:
       - uses: conda-incubator/setup-miniconda@v3
@@ -244,21 +244,6 @@ jobs:
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: Install HDF5 (macOS with Python 3.8)
-        if: startsWith(runner.os, 'macOS') && matrix.python-version == '3.8'
-        run: brew install hdf5
-
-      - name: Install NetCDF (macOS with Python 3.8)
-        if: startsWith(runner.os, 'macOS') && matrix.python-version == '3.8'
-        run: brew install netcdf
-
-      - name: Set environment variables (macOS with Python 3.8)
-        if: startsWith(runner.os, 'macOS') && matrix.python-version == '3.8'
-        run: |
-          echo "HDF5_DIR=$(brew --prefix hdf5)" >> $GITHUB_ENV
-          echo "NETCDF4_DIR=$(brew --prefix netcdf)" >> $GITHUB_ENV
-          echo "PKG_CONFIG_PATH=$(brew --prefix hdf5)/lib/pkgconfig:$(brew --prefix netcdf)/lib/pkgconfig:$PKG_CONFIG_PATH" >> $GITHUB_ENV
-
       - name: Set up Git repository
         uses: actions/checkout@v4
 
@@ -305,7 +290,7 @@ jobs:
       fail-fast: false
       matrix:
         os: ${{fromJson(needs.set-os.outputs.matrix_os)}}
-        python-version: ['3.8', '3.9', '3.10', '3.11']
+        python-version: ['3.10', '3.11']
 
     steps:
       - uses: actions/checkout@v4
@@ -359,6 +344,104 @@ jobs:
           parallel: true
           path-to-lcov: ./coverage.lcov
 
+  notebook-matrix:
+    runs-on: ubuntu-latest
+    needs:
+      [
+        check-changes,
+        prepare-nonhindcast-cache,
+        prepare-wave-hindcast-cache,
+        prepare-wind-hindcast-cache,
+      ]
+    if: |
+      always() &&
+      (
+        (
+          needs.prepare-nonhindcast-cache.result == 'success' &&
+          needs.prepare-wave-hindcast-cache.result == 'skipped' &&
+          needs.prepare-wind-hindcast-cache.result == 'skipped' &&
+          needs.check-changes.outputs.should-run-hindcast == 'false'    
+        ) ||
+        (
+          needs.prepare-nonhindcast-cache.result == 'success' &&
+          needs.prepare-wave-hindcast-cache.result == 'success' &&
+          needs.prepare-wind-hindcast-cache.result == 'success' &&
+          needs.check-changes.outputs.should-run-hindcast == 'true' 
+        )
+      )
+    outputs:
+      matrix: ${{ steps.set-matrix.outputs.matrix }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v2
+        with:
+          python-version: '3.11'
+
+      - name: Generate matrix
+        id: set-matrix
+        run: |
+          matrix_json=$(python .github/workflows/generate_notebook_matrix.py)
+          echo "$matrix_json" >> $GITHUB_OUTPUT
+
+  test-notebooks:
+    needs:
+      [
+        notebook-matrix,
+        check-changes,
+        prepare-nonhindcast-cache,
+        prepare-wave-hindcast-cache,
+        prepare-wind-hindcast-cache,
+      ]
+    strategy:
+      matrix: ${{ fromJson(needs.notebook-matrix.outputs.matrix) }}
+    if: |
+      always()
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Miniconda
+        uses: conda-incubator/setup-miniconda@v3
+        with:
+          miniconda-version: 'latest'
+          auto-update-conda: true
+          python-version: '3.11'
+          activate-environment: TESTconda
+          use-only-tar-bz2: true
+
+      - name: Install dependencies
+        shell: bash -l {0}
+        run: |
+          conda install numpy cython pip hdf5 libnetcdf cftime netcdf4 --strict-channel-priority
+          pip install -e . --force-reinstall
+          python -m pip install --upgrade pip wheel
+          pip install nbval jupyter
+          pip install utm folium
+
+      - name: Ensure Conda environment is activated
+        shell: bash -l {0}
+        run: |
+          echo "source ~/miniconda3/etc/profile.d/conda.sh" >> ~/.bashrc
+          echo "conda activate TESTconda" >> ~/.bashrc
+          source ~/.bashrc
+
+      - name: Run notebook
+        shell: bash -l {0}
+        run: |
+          if [[ "${{ matrix.notebook }}" == "examples/metocean_example.ipynb" || "${{ matrix.notebook }}" == "examples/WPTO_hindcast_example.ipynb" ]]; then
+            if [[ "${{ needs.check-changes.outputs.should-run-hindcast }}" == 'true' ]]; then
+              jupyter nbconvert --to notebook --execute --inplace --ExecutePreprocessor.timeout=${{ matrix.timeout }} "${{ matrix.notebook }}"
+            else
+              echo "Skipping ${{ matrix.notebook }}"
+            fi
+          else
+            jupyter nbconvert --to notebook --execute --inplace --ExecutePreprocessor.timeout=${{ matrix.timeout }} "${{ matrix.notebook }}"
+          fi
+
   coveralls:
     name: Indicate completion to coveralls.io
     needs:
diff --git a/examples/SWAN_example.ipynb b/examples/SWAN_example.ipynb
index d4eeb4620..889d3631e 100644
--- a/examples/SWAN_example.ipynb
+++ b/examples/SWAN_example.ipynb
@@ -19,8 +19,8 @@
     "import matplotlib.pyplot as plt\n",
     "from os.path import join\n",
     "import pandas as pd\n",
-    "\n",
-    "swan_data_folder = join(\"data\", \"wave\", \"swan\")"
+    "import os\n",
+    "\n"
    ]
   },
   {
@@ -41,9 +41,25 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Get the directory of the current notebook\n",
+    "notebook_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n",
+    "swan_data_folder = join(notebook_dir, \"data\", \"wave\", \"swan\")\n",
     "swan_table_file = join(swan_data_folder, \"SWANOUT.DAT\")\n",
     "swan_block_file = join(swan_data_folder, \"SWANOUTBlock.DAT\")\n",
-    "swan_block_mat_file = join(swan_data_folder, \"SWANOUT.mat\")"
+    "swan_block_mat_file = join(swan_data_folder, \"SWANOUT.MAT\")\n",
+    "\n",
+    "# Print paths to verify correctness\n",
+    "print(\"Notebook directory:\", notebook_dir)\n",
+    "print(\"SWAN data folder:\", swan_data_folder)\n",
+    "print(\"SWAN block mat file path:\", swan_block_mat_file)\n",
+    "\n",
+    "# Check if file exists\n",
+    "if not os.path.isfile(swan_block_mat_file):\n",
+    "    raise ValueError(f\"File not found: {swan_block_mat_file}\")\n",
+    "\n",
+    "# Read the SWAN block mat file\n",
+    "swan_block_mat, metadata_block_mat = swan.read_block(swan_block_mat_file)\n",
+    "print(swan_block_mat.keys())"
    ]
   },
   {
@@ -1310,14 +1326,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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XDqvIDQAcOHAAkiShoKDAcL6goADV1dWWfUaOHIkXX3wREydORCAQQGFhIdq3b4/HH39ca3PFFVfgt7/9Lc444wz4/X6ceOKJOPvsszFr1izLMTnnmDlzJs444wwUFxfH/bl5BaW6CIIgCM9IV0or02UnGezbtw95eXna66ysrKjtGTPWBnHOI86p7N69G7fddhvuu+8+nHvuuaiqqsJdd92FqVOnYsWKFQCATZs24aGHHsLSpUsxfPhw/Oc//8GMGTPQtWtXzJ07N2LMW2+9FR9//DG2bt0a71v1FBIfgiAIwhPSFeFpbnhV45OXl2cQHzs6d+4MURQjojs1NTURUSCVsrIyjBo1CnfddRcAYNCgQWjbti3OPPNMPPjgg5rcTJo0SasbGjhwIH788UfcfPPNmDNnDgQh/B6nT5+OV199Fe+88w66d+/u6n17BaW6CIIgiIRIR1qrOaS07FD36krkiIdAIICSkhKUl5cbzpeXl2PkyJGWfY4ePWoQFwAQRWWbDR7aMsOuDedca8M5x6233oqXXnoJb7/9NoqKiuJ69mTgufg0NTXh3nvvRVFREXJycnDCCSdg/vz5kOXwH1DOOebNm4du3bohJycHY8aMwWeffWYYp6GhAdOnT0fnzp3Rtm1bXHTRRfj222+9flyCIAjCJS1FeIJcRpA3T4lyysyZM/GHP/wBzz77LD7//HPcfvvtqKysxNSpUwEAs2fPxrXXXqu1v/DCC/HSSy9h2bJl+Oqrr/Duu+/itttuw09+8hN069ZNa7Ns2TKsXbsWe/fuRXl5OebOnYuLLrpIk6RbbrkFq1evxpo1a5Cbm4vq6mpUV1fj2LFjqf8QQnie6lq4cCGeeuopPPfccxgwYAD++c9/4oYbbkB+fj5mzJgBAFi0aBEWL16MVatW4eSTT8aDDz6In/3sZ9izZw9yc3MBAKWlpfjb3/6GtWvXolOnTrjjjjswfvx4VFRUaB8oQRAEkXpaQkornaLDwSC7WItH3z9eJk6ciIMHD2L+/PmoqqpCcXExNmzYgF69egEAqqqqDGv6XH/99Th8+DCeeOIJ3HHHHWjfvj1++tOfYuHChVqbe++9F4wx3Hvvvdi/fz+OO+44XHjhhXjooYe0NsuWLQMAjBkzxvA8K1euxPXXXx/3+/ACxrm327yOHz8eBQUFWvETAPziF79AmzZt8MILL4Bzjm7duqG0tBT33HMPACW6U1BQgIULF2LKlCmora3FcccdhxdeeAETJ04EAPz3v/9Fjx49sGHDBpx77rkxn6Ourg75+fmo2dMLebmU0SMIgvCCVEpPMlJZdsJTd1hGr37/RW1traO6GTeo30t3bbsAWe38rsdpOBLE/xv5f0l91paM50ZwxhlnYOPGjfjiiy8AAB999BG2bt2K888/HwCwd+9eVFdXG9YTyMrKwujRo7X1BCoqKhAMBg1tunXrhuLiYts1BxoaGiLWNCAIgiC8IZVpLUpnEcnE81TXPffcg9raWvTr1w+iKEKSJDz00EO48sorAUCrKrdaT+Cbb77R2gQCAXTo0CGijd2aA2VlZXjggQe8fjsEQRCtmuYc4clU0ZE5g8zdp7oS6UskIeKzbt06rZBpx44deO655/DII4/gueeeM7SLZz0BJ21mz56N2tpa7di3b19ib4QgCKIV05wjPJke3QlyMeGDcI/nEZ+77roLs2bNwhVXXAFAmdf/zTffoKysDNdddx0KCwsBKFGdrl27av306wkUFhaisbERhw4dMkR9ampqbKfeZWVlxVy8iSAIgohNKoXHKzJZdIjMwvOIj928fnU6e1FREQoLCw3rCTQ2NmLz5s2a1JSUlMDv9xvaVFVV4dNPP7UVH4IgCCIxUhXl8TLC40V0R0rxtHwZQsIH4R7PIz7qVLaePXtiwIAB2LlzJxYvXoxf/epXAJQUV2lpKRYsWIA+ffqgT58+WLBgAdq0aaPt8Jqfn4/JkyfjjjvuQKdOndCxY0fceeedGDhwIMaOHev1IxMEQbRqWmOER0rjbvFEevFcfB5//HHMnTsX06ZNQ01NDbp164YpU6bgvvvu09rcfffdOHbsGKZNm4ZDhw5h+PDhePPNN7U1fADg0Ucfhc/nw+WXX45jx47hnHPOwapVq2gNH4IgCI9obsLTUmRH4gxSAgXKifQlkrCOT6ZA6/gQBEHYk6qUlhekQngOH5ZR1K8qJev4THnnFwmv4/P0WetpHR+X0CalBEEQrYjWIjyZEt0hMg8SH4IgiFZAcxGedKWzUlnczBPcnZ0n0Jcg8SEIgmjxJPNLvTlHd9Kx5xgASGCQEtirK5G+BIkPQRBEiyXThac1yQ6ROZD4EARBtDBIeCLJJOGReWLbTsiZ81aaJSQ+BEEQLYSWKjwtQXaIzIHEhyAIogWQrC/5RIUn1dEdN5+DxDmkFK7sIidY3JxIX4LEhyAIolnT0oQnlbKTLmQwyAkUKCfSlyDxIQiCaJa0JOFpDbJDZA4kPgRBEM2ITBSeVEV3Wors0JYV6YXEhyAIopmQDOlJtfCkIroTr+zIoSNVUI2PPR07doyrPWMMO3bsQK9evRz3IfEhCILIcFqj8CRTdlIpOUR8/PDDD1iyZAny8/NjtuWcY9q0aZAkKa57kPgQBEFkKJkkPJkmO26iOpmCBAFNCURtJLTciA8AXHHFFejSpYujttOnT497fBIfgiCIDMRL6UlldKe5yk4qNzWVOUtwAcOWW+Mjy/H9eTt8+HDc9yDxIQiCyCBag/C0RtkhMgcSH4IgiAwgE4SnOUZ3mqPoUHGzc/bv3493330XNTU1EdGg2267zdWYJD4EQRBppKULD8kO4ZaVK1di6tSpCAQC6NSpExgLp/gYYyQ+BEEQzQ2vpMeN8GSC7CRjJlY8zylx65+TDdX4OOO+++7Dfffdh9mzZ0MQvItykfgQBEGkmJYoPOmM7LiVnXRBW1Y44+jRo7jiiis8lR4ALXxOHEEQRAYhg3siPXLof/EQ5LJj6ZHAtSP2szh7T+pGoNGkRzYdTp4v1jNK3Hi0ZpYuXYqioiJkZ2ejpKQEW7Zsidr+xRdfxKmnnoo2bdqga9euuOGGG3Dw4EHt+meffYZf/OIX6N27NxhjWLJkiSf3VZk8eTL+/Oc/O35/TqGID0EQRJJpLhEeL6M76YrqxCM3ss3PySYdqa5169ahtLQUS5cuxahRo/D000/jvPPOw+7du9GzZ8+I9lu3bsW1116LRx99FBdeeCH279+PqVOn4sYbb8TLL78MQInInHDCCbjssstw++23e3JfPWVlZRg/fjxef/11DBw4EH6/33B98eLFcX8OAIkPQRBEUvEqwhMv8UR3nD2Dd3U7XsqOW9FJJ+kQn8WLF2Py5Mm48cYbAQBLlizBG2+8gWXLlqGsrCyi/fvvv4/evXtrBcRFRUWYMmUKFi1apLUZNmwYhg0bBgCYNWuWJ/fVs2DBArzxxhvo27cvAEQUN7uFxIcgCCJJJCo9btJZTkl1dMfJk3kd1XEuWInV3KSLuro6w+usrCxkZWVFtGtsbERFRUWEnIwbNw7btm2zHHvkyJGYM2cONmzYgPPOOw81NTX4y1/+ggsuuMDx87m5r57Fixfj2WefxfXXX+/4nk6gGh+CIAiPSbSWJ94aHqf1O07rYtTnj/Ye4q3ZSeSZnNbpOK8RYoYj1agRn0QOAOjRowfy8/O1wy6CcuDAAUiShIKCAsP5goICVFdXW/YZOXIkXnzxRUycOBGBQACFhYVo3749Hn/8ccfv08199WRlZWHUqFGO7+cUEh+CIAiPyHThiX7v1MiO08LkliQ6yWLfvn2ora3VjtmzZ0dtb04Pcc5tU0a7d+/Gbbfdhvvuuw8VFRV4/fXXsXfvXkydOjXu54znvnpmzJgRl2g5hVJdBEEQHpCo8DjFy9qdVKWxvKrViSd15QSZW/+cbLyq8cnLy0NeXl7M9p07d4YoihFRlpqamohojEpZWRlGjRqFu+66CwAwaNAgtG3bFmeeeSYefPBBdO3aNSn31bN9+3a8/fbb+Pvf/44BAwZEFDe/9NJLMcewgiI+BEEQCZBIlCeeCE8yoju2Y3gc2bG/T/SojtcRHZkbj3TBEV7Lx80R76MHAgGUlJSgvLzccL68vBwjR4607HP06NGI9XNEUVSe3+GMPTf31dO+fXtceumlGD16NDp37mxI6+Xn5zt6Biso4kMQBOGCTIrweBHdiRXZ8aI4OVZUx9k94o/mOBmvJaXArJg5cyYmTZqEoUOHYsSIEVi+fDkqKyu11NXs2bOxf/9+PP/88wCACy+8EDfddBOWLVuGc889F1VVVSgtLcVPfvITdOvWDYBSvLx7927t5/3792PXrl1o164dTjrpJEf3jcbKlSuT8VGQ+BAEQcRDcxKeZMtOoqLj7B7JEZ100iQLgOw+4dLkou/EiRNx8OBBzJ8/H1VVVSguLsaGDRvQq1cvAEBVVRUqKyu19tdffz0OHz6MJ554AnfccQfat2+Pn/70p1i4cKHW5r///S8GDx6svX7kkUfwyCOPYPTo0di0aZOj+6YDxp3GrJoZdXV1yM/PR82eXsjLpYweQRCJk0hKywmZEN1Jtux4ITpeS06QCzhyWMYZxf9FbW2to7oZN6jfS2f9bRp8bSOnnTul6ccGvHPh0qQ+a7oYMmQINm7ciA4dOjhqf8YZZ2DdunU4/vjjHd+DIj4EQRAxaA7Cky7ZyRTRiUdyiMxl165d+Oijj9CxY0fH7RsaGuK6B4kPQRCEDekWnnTJTjKjOqkUnXgkJ5UpMNqdPTrnnHOO4wJqNys4k/gQBEGYaM7CkwzZSbfoeCk59mOlruqDcwaegLwk0jfT2bt3b9x9unfvHld7Eh+CIAgdbqQnFcKTSbKTaPoqVaITTxRHotVdMoJUFD2T+BAEQSB5wtMaZCfW2jnRSLXk2AtO6rYwVdfjSaQ/4R4SH4IgWj3xSk+6hMdr2clE0UmN5ETSktNHhBESH4IgWi2pFh6vozteyk4yRCdVkuNUcKIXBaeuxoeKm9MLiQ9BEK2SeKQnHcITr+y4SWHZj5Ue0Umd5ETeN5Wzuqi4Ob1QNRdBEK2KePbWirWXlrp/lpX0RNurym4ndLs9suz2q7K7h34PLL302O19FW2vq2j7W0XrF+RCxBGtr7m/BMHyMKNGT8yHGav7tbTd2lsaJ5xwAg4ePBhx/ocffsAJJ5zgelyK+BAE0SrwMsLjJrqT7MiOV1EdtxGdaNGcWHLhJIrjNIIT10wu3TM72V7DKyjV5Yyvv/4akiRFnG9oaMD+/ftdj0viQxBEi6Y5CY8XspMK0Umm5HgtOFIGrtRMqa7ovPrqq9rPb7zxhmEndkmSsHHjRvTu3dv1+CQ+BEG0WOJJaUXDTnhSLTvxRHXiFZ1kRHO8kBxHdT9xyo1slTJLYXEzEZ0JEyYAUFZlvu666wzX/H4/evfujd/97neuxyfxIQiixeGF8GSy7MQT1YlXdJIhOakWHCux8eL+XsETTHW19IiPLCt/wouKivDhhx+ic+fOno5P4kMQRIshU4THqewkmsJKpugkS3JipsKSJDeZVMTMATjcisq2f2vAzfYVTiDxIQiiReBEerwSnkSjO04iO4lGdbwSHbeSk2rBcSM2xuLm1qITzYuNGzdi48aNqKmp0SJBKs8++6yrMUl8CIJo1iQiPKmK7iSSwkqG6KRScpwITjLkJhOLmlUkLgAJPF8mvzcveeCBBzB//nwMHToUXbt2dbUTuxUkPgRBNEtiCU8yoztW6+w4GctJVCcR0YknmmMnOckSHCdyk2yxibbHFe1/lXk89dRTWLVqFSZNmuTpuCQ+BEE0O9xKj91Cg07u4VVkx4nsJCI68UZz7ETHreTEEpxkTUNPRFwkCCmd1SVzBkbr+MSksbERI0eO9HxcEh+CIJoNyRYeN9EdN7LjJKqTiOh4JTnJFhzndT4u6ncyeGMCzhMsbm4l5Ug33ngj1qxZg7lz53o6LokPQRAZjxvhcZrO8kJ2vIjquBWdeCTHa8HxroA5nn213AtNkNt/5QVbSRQl05k5c6b2syzLWL58Od566y0MGjQIfr/f0Hbx4sWu7kHiQxBExuKV8KRDdrwQHafRHC8kx63gOCtedroac3xSE01k4kHiDFIKxYdWbrZn586dhtennXYaAODTTz81nE+k0JnEhyCIjCSa9HglPMmUHSd1Om5EJ1HJSZbgOJGbeMTGrdSkUmDcQuJjzz/+8Y+k34PEhyAI14jMIhUTZT8rp9hJTzKEJxHZiTeqE0t0nERzLOUoziiOu5SXN2ITr9B4ITJOnsuuyJ1oeZD4EAThGCvRsWrjVn4SER6vZCedouNWcrwSnFhyE0sg4pEaN0KTjIJlOfRZyCmsGKZZXc645JJLLFNajDFkZ2fjpJNOwlVXXYW+ffvGNS6JD0EQMXEiPIngVHhiRXeSLTvxiE4qJSe+KJD7TUWdiE08QpOoyMitZCG/1kp+fj5eeeUVtG/fHiUlJeCcY+fOnfjhhx8wbtw4rFu3DgsXLsTGjRsxatQox+OS+BAEYUmyZQdwLzxuozuJyk4yRceJ5HghONFkwyuxcSM0XkmMW5lKZaqLprM7o7CwEFdddRWeeOIJCEIoMifLmDFjBnJzc7F27VpMnToV99xzD7Zu3ep4XBIfgiA0EpUdpykuL4QnUdlxE9VxKjrxSk4iURwrwXErN7GkJh6pcCsyyV5/x+49Jl6Z5hxFfBIpbvbwYTKYFStW4N1339WkBwAEQcD06dMxcuRILFiwALfeeivOPPPMuMalOCFBEBCZkDbpkXX/UwlyWZMeCVw71P4yOCRuPGRAO/R9JA7tMLZh2iFzaIf+fD0XEeQCglxAPRe1840QIUHQjiAXIXMGmTMEuWAYo5GLkLigHUHugwxBO4IQDe2t+4jKPcAMR9D0HBIE1PMAgtxnedTLfm3qtuVhGst8yNz5ofzeRR/P6gj/eYrynAkcrZmlS5eiqKgI2dnZKCkpwZYtW2zbXn/99WCMRRwDBgzQ2rz00ksYOnQo2rdvj7Zt2+K0007DCy+8YBinqakJ9957L4qKipCTk4MTTjgB8+fPj9hw1Iqmpib861//ijj/r3/9C5IkAQCys7PjntpOER+CaOV4kdJyIj1WwmNGH+Gxi+7EE9mJN31lF9FxGs2JFcmJHflxFr2xi9pE+2KPFUlxEqGJNxrjtWg43cw008Y2k47p7OvWrUNpaSmWLl2KUaNG4emnn8Z5552H3bt3o2fPnhHtH3vsMTz88MPa66amJpx66qm47LLLtHMdO3bEnDlz0K9fPwQCAfz973/HDTfcgC5duuDcc88FACxcuBBPPfUUnnvuOQwYMAD//Oc/ccMNNyA/Px8zZsyI+syTJk3C5MmT8Zvf/AbDhg0DYwzbt2/HggULcO211wIANm/ebJAxJzDOW2bQrK6uDvn5+ajZ0wt5uRTYIggzXtbwRBMfq7SWObpjGCsO4YmVxopHdpyITjRxSVRynAqOnUxE31k91vYSDndHd/GFmwqh8GK38mNHmnBryQeora1FXl6eB08Vifq9dOILsyG2yXY9jnS0Hl9OKovrWYcPH44hQ4Zg2bJl2rn+/ftjwoQJKCsri9n/lVdewaWXXoq9e/eiV69etu2GDBmCCy64AL/97W8BAOPHj0dBQQFWrFihtfnFL36BNm3aRESHzEiShIcffhhPPPEEvvvuOwBAQUEBpk+fjnvuuQeiKKKyshKCIKB79+4x34MKRXwIohWRKtkBokd4nMhOopEdK9GJN6JjF83Rf5knKjhO5cZ+a4poCxI6iOI4lJlEBMYLMSEiqaurM7zOyspCVlZWRLvGxkZUVFRg1qxZhvPjxo3Dtm3bHN1rxYoVGDt2rK30cM7x9ttvY8+ePVi4cKF2/owzzsBTTz2FL774AieffDI++ugjbN26FUuWLIl5T1EUMWfOHMyZM0d7r2bRs4pWxYLEhyBaAV7P0LKTnniiO7EiO1ay4zSq4zSik4jkJCo4TuXGrdjEEpp4RMYLcUlk9/RUkMrn4zIDlxNIdYX69ujRw3D+/vvvx7x58yLaHzhwAJIkoaCgwHC+oKAA1dXVMe9XVVWF1157DWvWrIm4Vltbi+OPPx4NDQ0QRRFLly7Fz372M+36Pffcg9raWvTr1w+iKEKSJDz00EO48sornbxVDS+jcCQ+BNHCSZf0xCM80dJY0WQnWlTHjei4kZx4Bcep3NhJTTShcSIz8UiMlzKQ6VGflD5fgjU+CPXdt2+fQQisoj16zEXAnHNHhcGrVq1C+/btMWHChIhrubm52LVrF44cOYKNGzdi5syZOOGEEzBmzBgASm3R6tWrsWbNGgwYMAC7du1CaWkpunXrhuuuuy5ivCFDhmDjxo3o0KEDBg8eHPX5duzYEfPZrUiK+Ozfvx/33HMPXnvtNRw7dgwnn3wyVqxYgZKSEgDKh/3AAw9g+fLlOHToEIYPH44nn3zSUKDU0NCAO++8E3/84x9x7NgxnHPOOVi6dGlceTyCaM0kYx0eJ9ITS3iiRXfikZ1o6atoohMrmmO8bi8t8QqOWW7iFZuoe2x5uFGo0/HiJchFz8f0kmAzLHfNy8tzFAnp3LkzRFGMiO7U1NRERIHMcM7x7LPPYtKkSQgEAhHXBUHASSedBEDZUPTzzz9HWVmZJj533XUXZs2ahSuuuAIAMHDgQHzzzTcoKyuzFJ+LL75YEzgr0fICz8Xn0KFDGDVqFM4++2y89tpr6NKlC7788ku0b99ea7No0SIsXrwYq1atwsknn4wHH3wQP/vZz7Bnzx7k5uYCAEpLS/G3v/0Na9euRadOnXDHHXdg/PjxqKiogChm9n9ABJFOUiU8yZIdp6JjlhylLTNes5Ac+5SWdRRHLzjR5MZJ1MZKamy3m0h036w45SVZYpLsdXncIqZ05R4jqV7AMBAIoKSkBOXl5bjkkku08+Xl5bj44ouj9t28eTP+85//YPLkyQ6fjaOhoUF7ffToUcM6PIBSu2M3nf3++++3/NlLPBefhQsXokePHli5cqV2rnfv3trPnHMsWbIEc+bMwaWXXgoAeO6551BQUIA1a9ZgypQpqK2txYoVK/DCCy9g7NixAIDVq1ejR48eeOutt7RpcgRBGEm29DhJZ0VLZUWTHbv0lZ3oRIvmRJOceAUnWuTGrdi42k4ihsjEKy6pEJJUbykhMOcyE/H7mqGC5hUzZ87EpEmTMHToUIwYMQLLly9HZWUlpk6dCgCYPXs29u/fj+eff97Qb8WKFRg+fDiKi4sjxiwrK8PQoUNx4oknorGxERs2bMDzzz9vmDl24YUX4qGHHkLPnj0xYMAA7Ny5E4sXL8avfvUrR8/9ww8/4C9/+Qu+/PJL3HXXXejYsSN27NiBgoICHH/88a4+C8/F59VXX8W5556Lyy67DJs3b8bxxx+PadOm4aabbgIA7N27F9XV1Rg3bpzWJysrC6NHj8a2bdswZcoUVFRUIBgMGtp069YNxcXF2LZtm6X4NDQ0GCzTXO1OEC2ZZG0vYSc90YQnHtlRzjPHUR27iI5ZdKwiOVaSYyc48chNxDR2h6sr27UNP2N0kYlXXFIhIXabonqFGGNbiUTeYyolLR3r+EycOBEHDx7E/PnzUVVVheLiYmzYsEGbpVVVVYXKykpDn9raWqxfvx6PPfaY5Zg//vgjpk2bhm+//RY5OTno168fVq9ejYkTJ2ptHn/8ccydOxfTpk1DTU0NunXrhilTpuC+++6L+cwff/wxxo4di/z8fHz99de46aab0LFjR7z88sv45ptvIiTNKZ6Lz1dffYVly5Zh5syZ+M1vfoPt27fjtttuQ1ZWFq699lotx2hVXf7NN98AAKqrqxEIBNChQ4eINnYV6GVlZXjggQe8fjsEkdGkS3jM6SwnsmOVwnIiOk4lxyqS41Zw9O1jiY3looM2X6J2MuPF4oLG8ZIrIMmShFgRm2S+r2R/ZgY40wqUXfd3wbRp0zBt2jTLa6tWrYo4l5+fj6NHj9qO9+CDD+LBBx+Mes/c3FwsWbLE0fR1MzNnzsT111+PRYsWaWUwAHDeeefhqquuins8Fc/FR5ZlDB06FAsWLAAADB48GJ999hmWLVumrbQIuKsuj9Zm9uzZmDlzpva6rq4uYqofQbQkkpnWkrXoTexUll523IhOtGhOLMlxIjjxyk3Maeqm6/HKTPTp6c6/0JIhHyn98kdkBCdVUZd4UmJE+vjwww/x9NNPR5w//vjjHU3Dt8Nz8enatStOOeUUw7n+/ftj/fr1AJTdVgElqtO1a1etjb66vLCwEI2NjTh06JAh6lNTU4ORI0da3tdu4SaCaIk4lR5BH92IUsxpFeGRITuK7NjJjj59ZRXR0YuOVTTHqeREExwncmOIFMWQmnjW2YkmEU6/4L0QkVTX2cRCLx3JFK1oaTGrzyS1qS7and0J2dnZlmUre/bswXHHHed6XM/FZ9SoUdizZ4/h3BdffKHlEYuKilBYWIjy8nIMHjwYgLKq5ObNm7XVHktKSuD3+1FeXo7LL78cgJJ//PTTT7Fo0SKvH5kgmhVupMcOO+EBrGt31M1A1fN2xclm2bFLXdmJjlPJMQtOvHKjF5tY08/V5zTjRnxi9Y1Gpq+Hkw6sIjipjl7FBQ8difRvBVx88cWYP38+/vSnPwFQMkWVlZWYNWsWfvGLX7ge13Pxuf3227Xt4i+//HJs374dy5cvx/LlywEoD15aWooFCxagT58+6NOnDxYsWIA2bdpoObv8/HxMnjwZd9xxBzp16oSOHTvizjvvxMCBA7VZXgTR2nCb2rKK9EhcjqjdiVakbBXZsYrqmCM68UpOvIJjWd9jITbRZ2Yx22t2baK1tXqOWGT6qsaJIhiWM0hc3EST6MQrkNaiRGQajzzyCM4//3x06dIFx44dw+jRo1FdXY0RI0bgoYcecj2u5+IzbNgwvPzyy5g9ezbmz5+PoqIiLFmyBFdffbXW5u6778axY8cwbdo0bQHDN99801C89Oijj8Ln8+Hyyy/XFjBctWoVreFDEA6JJTxm2bFLY1mlsKKJjj5tZSU5VlEcveDEkptYYmMnNdFkx6qN+V6GdklYR8cO827wXiKw5IcORCYnJHaCRXjD6WdrFiSV9Ke6Uj+rqzmSl5eHrVu34u2338aOHTsgyzKGDBmScACEdmcniGaCXcRHTWnZ1fCY01n6VJZZePSyo7S3lh2z6JijOVaRHH0URx/BiSU4QS5aio0TqYklMm6mmTsVkUxfqTgafuZN/CMRsbKTlqj3izMHpL9H/ZEgHjz9zZTszt5z+X0Qctzvzi4fq0flzfOT+qwtGdqriyBaALGkx054rGp24pEds+iY01VWkmOIAOnkRu0DRMpNNNmJuo+W5b/sI8UllqS4XdzO6c7nXiB6GL1pCH1uQgKrG/uZFHe0Si9KTqI6ESmvGJElsxjp70G1U5nJxo0bsXHjRtTU1ESs9vzss8+6GpPEhyCaOTLkiJod/TVzZCfIuSGqE9QkR3AlOXrB0aep1LaA8qWij9xYiY1ZctR+yniRaS6lrfGLTi8w9ltBRJtt5V5UZC5E1I7YpU8EJlteS2SatZNnjzcCIyH8ecYrVg1ciFuc/HFU2giMx53yiiZGPIV1VpTqcsYDDzyA+fPnY+jQoejataujDVWdQOJDEM2ccFTHOP0cUKI4QS5H1OsEQ39x1nPRIDqNXIxLcvSCY05N6eXGSmzspEb/Ba6KTOQiguaC5NgFysbPJf6/QGXOIsQhQjbUSEmonfm6el6yW/vHZXos1orGKrJFM6eypb6XuOQpjoJ8AbLj9GA80aR4BInILJ566imsWrUKkyZN8nRcEh+CaMaYFxwEwoXKahqrUavdYQjycOoqGJKeIPcZRKeeBxxJjl5wVLkBdKJjkdJSv6zMQmNYb8fwc7TZV/HPtLJsH48EOf3ON7VTUyxW4uGUaIJi9x6cSIpetpwIlMzjkyXHouR4mQZngqTWKcUSpLCMplCOaDq7IxobG23X7ksEEh+CaIYEuWQ5K0uVnXrOtTqd+pDYmEVHFZd62W+QnCAXYwqOXm70ERuZM4PUmIXGulbHWnSst4LwRnZSicBkVxEmc2pJjvJlb1fUaxatWMKifuaxZEWVJWeRptiSpERlYn9GIuMx663U9FosOTKLUTJnz0WQpi0rmhs33ngj1qxZg7lz53o6LokPQTQzGngQR3kT6rlsOfvqR+5DkIto5CKCUCQmCBFB7lNSWVwIp7RCYmOWG01euE6ETFIDhAqWuTnaE05pRW73YEx3NTksPg5fS4/gJFJ7IziMZPgi6oOcP4tZrOzqcfTyFG0GlHpvJ6IUM6Lj6PcscTlS33M0MdLXHJnFyJwmJtKDfuspWZaxfPlyvPXWWxg0aBD8fr+h7eLFi13dg8SHIJoJEpfRBEmTnnrOcFQ21ujUcz8auYijPEsRn1BtTpD7lDRWKLoTDAmQObqjyo0arVGlRhUamZvrcliExMgmudGf0/e1umZ13q6uRmDc0NeqrsbtdOqIfnZFyjEiHsozxrqX8oXbaBOhcPIssaQpmixFK1qWuRjzPcZMfTkJTsSQI6UY3H4gL6QopVCqy5adO3caXp922mkAgE8//dRwPpFCZxIfgmgmHONBBCEbpKee+zTZCULEj3IW6mU/gqGoTz33axEdVXSCsqjJTVAWIsRGkSDlZ73MyDy8v5YqL1Zpgmipg1j1NE1y9C8mnyCjSRbgE5z/69zJ2i6xBCna9ajXYokRuG0KKyxyVteM718vTZbPE/p9NAuSfnw7eXEiSNHFJfrvlcB41FSgCB51dhxgL8/h+h3r6/r3lFIpolSXLf/4xz+Sfg8SH4JoRkic46tgLl46VIIG2YcG2Qc/k5ElNCHIBTRxEcckP5pkEU1c0CRBAIcMhiZZkRf1mllYuCkyoxanqv3NXzA8iuSo1xnjltGZWF9WKixO6bCSjbjHsGlvFi6re7mRJKfvQz0fTZaiiZI5qmS4r04u4hUkCSxqei26ANqLUTQpcitExrWCmOXPRMuGxIcgmhG7g7m47z8X49t9ncElBiZyML8EwS9DFGVwziBLArgMcJmBCRyCT4YgcAgCBweU61wnJQIPrSsCMBaWBPU6E5QVThjjmujoRUI9xwGtnaE/4zBHpe0EQO2rH1/ta+5jtbKvXVsr8REs7mX3fOoXd1ASnbU3vdaESXfaqTTFcy5i+rw2m8w6IqSXJL3QRI0gcSH+yJGNUwgx5CWauFgJkai9X8HUR7d6eQwZSgW0O3t6IfEhiGbCjsY2uO8/F+O7f3ZFh0pA9oWOgB+yH5ADAARA5ADjyj/guQjIfo4mAYDItQg546FoOQOaRA7IDBA4IIQuQrmmtOEAC0mF2jF0LjxQuJ0K0/qFz2sCFEVwVNnSzuvHM/xq/HzMImPVTv8FpxcnuzZmyXEqS3qpYYxHpPCiiVJEGo9HSpITGRIYj0gtJiJHVmJkl1azqjnyQojilSE7EVLHCj9fZDSTaLmQ+BBEM+Drpno8uu8C/PezQnT5REb+F0cgZ/kgBwRIWSLkAIMUECD7ASnAIIuA7GOQ/QAXGbgIcEE5z0UAQkiMQocmOUKo/CB0DowbrzPdec1I1L468WEADwmPrJcdZpIfVZ5CfZjtz7o+gCGKpAlOSJaciJLAOIIQI9ro2yUiSbHOq7PxVOmQdO1USXIcRYIqCpGSY35tWQxuMYVdKyCH/lyk7NgJTZNFvYz1l41NmsvCQeKRoVgiBKR5CQQOKm5OIyQ+BNFMOBIMQGhgEBtkCHXHwLL9YFl+sCYZvEGAkCVC9jP4xJD4+JkiP75Q5EdkgADtNVclR9TJj1mGBBYhRcpr1Q640l/JcRlEhmuvEZIiprMS5bU5osQN0SZ9pEg9r6TP1PsbhEiyFyL91x8LRUKU6yxCdJhOCLSfmXU0RBUixqBFvvQzjJguIhZxHqbp4CbZkDgzSJN5McBGSYwaKZI5izFlnUXITkQExyoIEjGklUCYaqEYj1i6wGexbYcqUeZ6G9EqemURzbGr7XEiQjylCxhScXM6IfEhiGaEEAR8x2SgoQEs2ASxsQlCox9ywAehUQ5Fd5RD9gmQ/erPDLKPh9JfigzJIlMER4ASCQr9bBAipjtnivwor5nFNaZFirigpsgYuC59pUoPU4VIixbpZSgsJZoEGaRHl7rT2rFwSk4VF5mZZEipfQJnhuiQExlS7hG+p1UUxAsZ0saMQ4bMIgQYZSiWCDnBKn0WsUo1s4rMxI4KORUh0fQ5AdYSpO9vt8SBXoTcLDJJJJ8XXngBTz31FPbu3Yv33nsPvXr1wpIlS1BUVISLL77Y1ZgkPgTRzBAbZeDHY4BPBIJBsGAAot8H7hMAQdB+lf0iuI+BiwK4TxEh7lNERfYxRXzEUCpMjQQJSpRHlRbZh3AkyCRBmiip10VoEQItUqT148bokRrhUb+n1OiPwDVRUiNBPCREBhnSCZD6s1ZUzSJFiIfamWUoHBVShzJKSFhyIr84ncqQyGSd3MCRDAFGyXEaGYoVFQJMkaEEUyZuRcicnoonIpSsaFAqYTyc4XXbvzWwbNky3HfffSgtLcVDDz0ESVJW227fvj2WLFlC4kMQrQne0ABIPjBZBoJBwOcD84mAIIKJiviwgAiIYigCJIL7FSniArMUIS6E0mICV6JCajpMDIuQliLTpb30cmQWIaaLAunTaWpEiOnOM8bB1YIgNZ2miVD4MNQaISQlqgjp0mxGEeKhm0CzIh4lKmQWIfW8Op52XyhfnOoMNnW2DQtJTYQIha6rMqT5lE5YDFEdu/MIv3+tnU1UyIy50DqZImRXe2QWEqs2ehHyadISKTJeRYMS2UctbqjGxxGPP/44nnnmGUyYMAEPP/ywdn7o0KG48847XY9L4kMQzQkOQAa4LINxDh5sAgQGJslAkwD4fIAgAKIAJiniA58I5pPBpXBEiIsCmE8GBAbZL0AIyVA4GgQIYlhgrKJBqgQxOZzqkkUlesIZAMkYHWJySEIEVWoQFh5Rn6aCFu2BHIoSiWFx0YuQUirBNZlh+kgRjD9rs8t09UL6XznjUKfsmyM/LDTlnwEGydELjj5iY24DwCA6Mhc1ERJ1X+BeiZA+qxht+UCBGWecWc0o07eNthaT5WuLSExkn+hRmVRGg4jMYu/evRg8eHDE+aysLPz444+uxyXxIYhmgvKFDLDQIiA8GAQThFA0RQCkkACJocIaUVQiPz6fIj+iIj0sJD9CKB0mNMpKxCeUEmMig2CIBAGCWhMkcp3MsFDRdFiERFlXHxSKAKkpLbXeR02JhYWJAXJILrRaobAEcYGDNenSZIJTCQpfA3S1SXoJAowiZIgG6dxIFRnYS5DS3ihCeglSfg8ja3k0CQJsRUj/Fa//irY7bydBEe1MmCXIIA1RogzRFqQ0tIkSDXKaEgOQlGhQSmd5UXGzI4qKirBr1y706tXLcP61117DKaec4npcEh+CaAZIYOG/sGUO3tiohE78PuXbWZIUoZGkcMSnSQIEpqXCIApgghj6VQAPiBAbjRLEfQyCqKTDZD+DIIYiQUGmrRukSo/s4+ASwERjTRBjUBZQZAD36aI8+siPmgrTR4FkUxRIbc/VFJUpCqRKEGNan7C4OJMg5WLo4DBIEGOK2ECL3IQuRUSDwsN4EQ3S64yI6NEgJxJk3kjULhpklpdoEmSVwtITbzTISoKASJlJZkos1nYqnkKpLkfcdddduOWWW1BfXw/OObZv344//vGPKCsrwx/+8AfX45L4EEQzhMscTJABSVIiOwilvwQBkJW/6HmoYJbJSoQI3Kd863EBEEWwRuUUg3JKACBDhJJLYxD0e1n7AKEJANRIEIfQpMgQtDWblTbaOngCgCZFDGS1BUf4G5qH5AeKKDGdiHDGQg6iK3DWFzYj5CicRQgQEJYgdYYY58b+0MkU52FxUn/WbhCSlkgJUgUGygraMaJB5iiPVTRI/TaLJUFW4yjnwugliOmkI0I4kiBBgul+AGK/jkOCrFZh9iISRGQeN9xwA5qamnD33Xfj6NGjuOqqq3D88cfjsccewxVXXOF6XBIfgmjGcJmDISw/ykmuyI/+nGVnbvwVoTSazLTZVizkTMq/UNXi3JCUqDNTdG2Y6WewUHqHh+RGCL2WoXw7Szr5Qeg8U65xAExSZEONBDkTIEAdkYWEh4esyyBAqq9p18LSo4gMC/+stlVlJ/whqp+c8ov6nawahSlCYSVBmgdaSJAxChEpQUrxNDNddRYJ0kuQoL5/GEVJa6cTDDsJCqeNWEQ/p6/179lqPOW1fU2QPrKlSpDPIEqR8pSWPboo4uOYm266CTfddBMOHDgAWZbRpUuXhMdMYVKTIIhkw2X9DB1unKoiSdA2CQqdZ6H2at2Q2k+rJQIMU29V0VFFiMnKz0zmYRmSze0AJsFwXd+OSdBEyXBNVl+z8HnDuAx6T1DGYoDElG94OWRK2njh11xWBY0p7dRrcug6Z0rqjSspOB7qp0oeD7XnsqDsjyazkG8y3X5pofOAtgGs8VDGkmSmbZlgbqOOq/yWhdtJXIDEBe2a+bphDB7ejkE9Bxjbywgf+r76duafASUSpIqQ2l/F3Dbu1zHGU84Za3Os2jRxIaI42qqmpzVsUrp06VIUFRUhOzsbJSUl2LJlS9T2DQ0NmDNnDnr16oWsrCyceOKJePbZZw1tfvjhB9xyyy3o2rUrsrOz0b9/f2zYsMHQZv/+/bjmmmvQqVMntGnTBqeddhoqKipiPu8DDzyAL7/8EgDQuXNnT6QHoIgPQTRLmMAAJoAJDCwQUP7pHyp0hsDAmKDU9zAG+P1KwbMgKucEAdzvA0QWnuUlCMp0dzFU5Byq8eGm2V5qQbNW56P72VA3Y4cWOQn/ygAlu6bW9+jrfqC+DklOjOgP1GHVafGGFJgpAsShLYzIQtEd2zSYVUQo9B7UZRDjjQJFi/BY/4s0fIewEMSIArFwJCfeVJhdFMgqUqPKT7Q0mOO0l00azC4CpJwzRnISiQClBFW2E+kfJ+vWrUNpaSmWLl2KUaNG4emnn8Z5552H3bt3o2fPnpZ9Lr/8cnz33XdYsWIFTjrpJNTU1KCpqUm73tjYiJ/97Gfo0qUL/vKXv6B79+7Yt28fcnNztTaHDh3CqFGjcPbZZ+O1115Dly5d8OWXX6J9+/Yxn3n9+vWYP38+hg0bhmuuuQYTJ07EcccdF/d7N0PiQxAZjBiqnNUvra98kQtgfh+YGJqyLgrKz+rMJPVnn3pdBPeJYdlR1/bxKYJkXvFZv36PMuOLaSs5a/LDoO0Bpp+2rgqM/ghvawGjIDGYs0FhuK5dLDhT5EQnU5wB2uar6s1CAxt/0ktT+Iq+vdqDhVrqX7sVIAZoYgFTH/3qzeY2+llk+nYSV/+sRBcgs8TYyo0DAQKMiybqBUh9PvuUlf04lq9hXHnaToDMNUDmBQqbuNUmqqlNfuijqG77x8vixYsxefJk3HjjjQCAJUuW4I033sCyZctQVlYW0f7111/H5s2b8dVXX6Fjx44AgN69exvaPPvss/j++++xbds2+P1+AIiYgbVw4UL06NEDK1eu1M6Zx7Hj448/xmeffYYXX3wRixcvxsyZMzF27Fhcc801mDBhAtq0aeP07RugVBdBZCiq9ETAYJAe5vMpU9b9fiAQALICymyv7CwgEADPCYBn+8GzfeBZfsg5fsg5Acg5PshZIqQcEU05IpqyRUjZIqQsBilbgBRgkLIEyAGm7fslBZSNT5UZXuHVn7X9v8wboJqkxyBDDqQm4i94u7SXuT3XfbnI4TSVmiJT+zD9a13aSH8uIgVmaB9+bewbmdLSXsuhQ/fodmkwqzSVPg1l1c6cBgOsx1HPQ/cMKuaUk76N0xSYvr85ZaUnVvrL0NbChK3SX9GuA4hIfVn1aw7U1dUZjoaGBst2jY2NqKiowLhx4wznx40bh23btln2efXVVzF06FAsWrQIxx9/PE4++WTceeedOHbsmKHNiBEjcMstt6CgoADFxcVYsGCBtsKyfpzLLrsMXbp0weDBg/HMM884fo8DBgzAggUL8NVXX+Ef//gHioqKUFpaisLCQsdjmKGID0FkGHbCIzI5JBJMER1RBPOHFixU01n66E4ohQVfeNFCQ2RH93M4wsO0qebqz3Jo3R1zSsuwR5cu/aSXHP0Kz+Z2hl/VKJEVagQHpjb68whdZFzLVqlBG6bW5BgWtAn3VH7SR3rUrsZz+j5WESCm6wtd/1RFgMwRHokLyp8ZVfIsIkBuoj+AMU2nj6okEv2xi/bESn1Z948d+UkrJmF31R9Ajx49DKfvv/9+zJs3L6L5gQMHIEkSCgoKDOcLCgpQXV1teYuvvvoKW7duRXZ2Nl5++WUcOHAA06ZNw/fff6/V+Xz11Vd4++23cfXVV2PDhg3497//jVtuuQVNTU247777tDbLli3DzJkz8Zvf/Abbt2/HbbfdhqysLFx77bVxve22bdsiJycHgUAAhw8fjquvHhIfgsgQbCM8UEpz8gIN2BcApGwRrE2OsjaPTwT8fq1mR9maQgQPiPaSo627w7R1ecDCkqNfoVn9jtZkSP3O1QsNdFLCwqJkiOqYRAewlh7LNJipn4ZJgrSTseSHmwcwpb6Y0sYgMIzDaF464dHam2VI11//iA4FiOnkxCq1pW+jH1cvOGpQ30qAkpX+iphiLgsG+VH7A/bS5Oi1ReorHvmxSnk1N/bt24e8vDztdVZWVtT2+j3nAIBzHnFORZZlMMbw4osvIj8/H4CSLvvlL3+JJ598Ejk5Odosq+XLl0MURZSUlOC///0v/t//+3+a+MiyjKFDh2LBggUAgMGDB+Ozzz7DsmXLHInP3r17sWbNGrz44ov44osvcNZZZ2HevHm47LLLYva1g8SHINJMNOHRIzAOOVtGUxYDcnIAvw88y6eITmgvLjkgQg4Iiuj41f23jFEc2RcWCW2HdiAcoRFhjMzAQkgEGKUmhL6+xxCYsJIdi/OWbQ3XXPwzmev66yM/+vN6QdKLDlPSRcx0TimADgsPM7Q3v0Z4EUOTzDBdey4ru8ZrtzCJjTmyE7kqtHFcINxOjf4o7eyjP/o++jHN5/XS4TT6Y9gp3hT98bLupzXJT15enkF87OjcuTNEUYyI7tTU1EREgVS6du2K448/XpMeAOjfvz845/j222/Rp08fdO3aFX6/H6Ju6Yz+/fujuroajY2NCAQC6Nq1a8Qqy/3798f69etjPveIESOwfft2DBw4EDfccIO2jk+ikPgQRBpxKj1qcTNngJQtgLfLBg/4IAd8ivD4BEhZArifQQoIoZqb0GrL+gJkEcZCY1VwAGPERn0d+jVCcvRyAotzZhkytdGu2QmP+b6AJj2WpRjW/2g1NuG68QzSY5Iai3NO5Ed5DO65/ACIiP7YRW3ilR/99UyRn2hjWL5uhvLD4M7h9f3jIRAIoKSkBOXl5bjkkku08+Xl5bY7nI8aNQp//vOfceTIEbRr1w4A8MUXX0AQBHTv3l1rs2bNGsiyDEEQtDZdu3ZFIBDQ2uzZs8cw9hdffBFRBG3F2WefjT/84Q8YMGBAnO84OiQ+BJEGnAqPHUeL8hXB8UMpQvYzcB8gBaCVoqiRG63wWEBEdMdSRBD+S1n/2qJG1Dr9xCPPR/S1u26K7NhJk5UwhXdmj7xXOPPDjX2iPJMlVpIU0QaeyY/6WFapL7uoTeT+YUb5AcKpLyv5UfrwVic/KYWbrd5F/ziZOXMmJk2ahKFDh2LEiBFYvnw5KisrMXXqVADA7NmzsX//fjz//PMAgKuuugq//e1vccMNN+CBBx7AgQMHcNddd+FXv/oVcnJyAAC//vWv8fjjj2PGjBmYPn06/v3vf2PBggW47bbbtPvefvvtGDlyJBYsWIDLL78c27dvx/Lly7F8+fKYz6ymx7yGxIcgUkiiwgMAB4sZmOQDk0OzqwIc3C8rkZrQhp5MZkrtiLqpqI+Hv/QlpkV3AIRrTEIwSQkB6WWHcUT+Zav/FyuzOa9/zWDdx+qc3d/rui8rq2hTxDW96FhEjyKjTMbzzOZ8ZLtYryOfX9vry9SH6Wp9Itsa+wDhtJC5jbmdihgjumHY8T0JmOXHKckuUJZa+CTniRMn4uDBg5g/fz6qqqpQXFyMDRs2aJGXqqoqVFZWau3btWuH8vJyTJ8+HUOHDkWnTp1w+eWX48EHH9Ta9OjRA2+++SZuv/12DBo0CMcffzxmzJiBe+65R2szbNgwvPzyy5g9ezbmz5+PoqIiLFmyBFdffbWj5/7222/x6quvorKyEo2NjYZrixcvdvVZMM55cv+Up4m6ujrk5+ejZk8v5OW27D/QRPMgHukRoK6Gq3xBVDb9iDu+uRR1jVkIyiKCkoiGJh8kmSHLJyHbHwQA7XyTJKBJEiDLAvw+CYIgg3MGSRYgSYIWGZBDqwsD0KZag0Obch0u8gGUlYrDz8jUaeJm6dH30f8KwLzwmuF7LFoURW1ivu4kgmOWFtiLDuBAdnTnbIXHcM7Y30pe7KSHRRElIFJ6YrXTS4/VdX1/q3Pm84LJcm3b6X42S49+DLPYRHsdcQ2x+spRrwd/bMSfz3ketbW1jupm3KB+L/UqewhCdrbrceT6enwze05SnzUT2LhxIy666CIUFRVhz549KC4uxtdffw3OOYYMGYK3337b1bgU8SGIFOC4gDnKvzof6vkKfuR+1Ms+1HM/DsvZqOcB1Mt+yGD4Uc7CUTmABtmPo1IADbIPDbIPTVyExBnqJT+aZBGNsgiZMzRxAfVNPkhcgKxKUWgLAim09YIkC9o2DBxQtmLgodqTkAhxneiE17hhBgnS/nlljhyZxScRoqXXzJGCaKKjvx5NdqzORRnXKhJjFh7DrT2WHj2xpMcNdtLjFV6PmXFT3IkIZs+ejTvuuAPz589Hbm4u1q9fjy5duuDqq6/Gz3/+c9fjkvgQRIZglh5Zl4Pq6WuLBh7EUR5EPW9APWc4LP+Ieq5IUJCL+FHO0kToqBxAPfejQfajXvbjmBxAUBY0EQrKIuolP9r4gtp+S42yqEgPFzQJkuTQvlCqCImK+Miy8u9rbT8qVYRCG5mGF/VT02b6yFHoR65zHYMARQ/76L+rbJtafaFZSYm5bZR0mNLP6TnjGNGkx+oR3clM5Dl9u1gpLrt+iQpNtD7mKI3Tfl6QVunR/Xfgun8r4PPPP8cf//hHAIDP58OxY8fQrl07zJ8/HxdffDF+/etfuxqXxIcgkkS89TwyZAgQDMIj6XJLAgT4IUACRxAc2UwK1SUE4YcEQeDIRhA/siyITIZfluBnypEtBFEv+7UoUFAQkSU0oUH2hYRHRIBLaJIF1Es+NDEBkqDIj8xlSLIiPEFZVERH4IoMMQYmMG0jTzUaxDiU3djV9V44D0eDwGHcYJSFa204wsJh85e747pOi3ZxCY/pfFTpsbpHjEiLdk5w/y0W9f62fcI/JxLt0UuLUznSp7lipaaiXUs0zWWFaC52SyKMW7t5PP1bA23bttVWo+7WrRu+/PJLbYbXgQMHXI9L4kMQGYQqParwyPqZKqFrImPwg0MCR1sEEYSARiZC5DKC3AdRkCFCVoSHB1HP/Kjn/pAAiZoABQURPllCliyGBYiJ8AmyEgXiAholUUl/hSRIDAlPUBYhCErkR+YMMgunw9QokDJViWmhnbAEmVNf4fdvK0MusZSAKGmvmNIDm3Pmeh67dtHOWT1qjChOtHZ64on22I2baLQnWkFzLLHxGvP4Piaj0aYtkT5OP/10vPvuuzjllFNwwQUX4I477sAnn3yCl156CaeffrrrcUl8CCLF6FNassW/Ms3So7YJchlS6Jw/tKaMHxxBxuHnMuohQgSHABl+UUI9V6I8VgLkZ0p6zM8kNDAffIIEv+xDMFQD1MREbX0TTYCYIkOM6QSIKfXFMlMEiHNAhqBMxzZFgRxJEEN4ynjonEEm3EwBjpH2smwTT6THiVzBebTHaRQnluzEkodE0lluoj12/aM9l6PXCRY1pwVKdTli8eLFOHLkCABg3rx5OHLkCNatW4eTTjoJjz76qOtxSXwIIsVYyQ5gTGvJ4BHCo4qQxLk2gnkkCQwyBG29FvMU3YgNHHXXBfDQl4QIMwLjkBlXtipgyv0ZY/ALUij6I4OFiqHVGWRcADg4ZG0WGdfWL+Eh+dGmuIekh+vXyQHCIqQSIw1miZM6IFMbO7GxPx85rt20ci8Kmu2eNdb09VhpMC/JCMHIUJisHIn0bw2ccMIJ2s9t2rTB0qVLPRmXxIcgUoTEZcu6H4nLkMHRwJvC58AR1CI/0CI9EldfK7tY13MREhiCXEQjF1HPlRleEgRlthcXEOSidkDtC+Mu2HoExpUDoV9DIRkhJC+KAAEQlNofVX4ADjF0LlzBzCCIsjI1PmQ5HNAW8lMW0eNaIbR+wT9AJ0KAUXbUR7eLADn50o0mO6br8QiPub1VMXOi0hNrzR63M7nincLutC4onjQXQajMmTMHY8aMwahRo9CmTRvPxiXxIYgUoo/qAOHITpDLCEKGxNX0FtAYiuxIOklRJEdAI5Qp6RKUWVdBKGJTzwOQuCI+Qe6DxBUpqpf9ymswLeoTDE1zj4YqQWrdj8w4fJDRFErYKdEfFiE/nDPIHOChomY1+qOkv3RFzGoKjCE8zUsnPZoIwXheI4EvTcsvbceRH32j6MITcT7KAoV2zxWrCNlOatzW9rghFQITK83VbEjDys3NkYqKCjz++ONoaGjAkCFDMGbMGIwePRpnnHGGto2GG0h8CCLF6Gt39GksiSuztdSoTjAkNvVapEZAkCtpLBmCJj0yGOp5AI1chMwFSBBCwuNTrumkR5GdcCoMiEx/AUpdhMCVyJA56iOF1j9R0l1K9Cd8Ts1dKfuC61+DqwVBobpnHo4AAYCyF1a45kfd5VxLgant9DLkFrtAUbTCZ3gjPOZh3UR6LJ8V9tKTjGhPNNxOYY9nHC/aE5nN66+/DkmSsH37dmzevBmbNm3C0qVLcezYMQwZMgTvv/++q3FJfAgiBQS5pIkOEE5lqWksiQNBi/SV8qtOWnSRHAkCZC6gMSRGquhIWnor3E8OyU6QKzO4lPbKNPYgF0IpMQGNsk+ZpRUSKuVnFhIYaD8rhczhc/GgFj4rX65hMTIIkPKDbr8pbpnq4i7+5Rs1PRNNdABb2TG3dSs85nGsFinUv3YS6YlXepySjAULW424cFBxs0NEUcSIESPQsWNHdOjQAbm5uXjllVfw5Zdfuh6TxIcgkkyQSzjKg2jgMhp1qax6LoQkR9DSVkHuQyMXQ6krnxbFaeSiVrSsyk0994ciPKqACFoqS43syKFUlwwBQVkwtWfaqs6Nsg9Nsqht1qgKT5Os3K9RCqXWuKBJj7ras4o6q8sK7UtSFRVVBmRAV7Cj+/9QP0N+KXJqe3hcB78RcaxvEz5pLRxWfSKueSA8btrHKz1mvI72UH1PJIwnlKVtNev4LFu2DJs3b8bmzZshSRLOPPNMjB49GnPnzsWgQYNcj0viQxBJQuIymiDhKG9CkHPUc26QnXrZp9XmqMXImvjo0lRKlEe0FRsAmtwo92VokkVDbZAa0VF/NgqO8rpJFnTtlciOek6SBUOkRx/x4RyG1JkeNf2lj9xwzrQ4DwulvkJXdW3UU9yU5oJ1fUOiJQ823yTRRMfyuo3smNvGKzxO+7iRHjdRILdbWzTbmhwiLdxyyy047rjjcMcdd2Dq1Kme7UtG4kMQSUKVnnouo54zHJV92hYTjVzEUZ6lzMQKCU8wNCtLnYGlzciSRcuojSotAEJRoLDk6MVGPaf9bBCiyHSWKjt6uVHH00tPtAiPimyQFh41NWV3PeK8OXrkFoeyo5yL3sa8Ho/TwuVEojzmPsmUnmgzuaJtHJrIooXxrt9jfY/Ya/j40jE3nFJdjnjppZfwzjvvYO3atbjvvvtw6qmnYsyYMRgzZgzOPPNM1wXOJD4EkSSCPDxL65mDoyBDQIPk07aNqJf8aOKC9he4GnVRZ1HZpZvUmVYAIgRFBoMAbpAF9Zz6s4oqJarEqD/rUeVGMomUtiihDisZ4rpnA8J/X3M58n5miYqQIC9nsiRJepxGeczjJpLaAtIjPbHEJJ7tKbxetFA5l6HSA4T2r0usf2tgwoQJmDBhAgCgtrYWW7ZswV/+8hdcfPHFYIxp21nEC4kPQSSR7yQRv/n6Enz2TTeIflkRBomBSwK4xMBEDuZT/vLlMgMTOASRQxBlbf0bzkNbQITWtBEE5bq+MkZtx0LXGePal5R6Xv1CVNbOCaWhTCJjVTSrXlNFRJUqLRule796sdGv3qxHFZx4xSacLrM+r+J2kb5USU+0qE0qpMfc32lNT3ORHqt9uay2qIhs00pWBWxmfP/999qMrk2bNuHTTz9Fp06dMHr0aNdjkvgQRJL4qolhzteXYM/OXsj/kkH2A3IAAAeEJkD2QTnnD3VgyjkuArKPQxIBLnDlX4Yh6eEMkAQAIle+adUvXq7056FzjCFUQamOrfys335B/0WmSY86oUrtD0QKCePWqymbkdTBI00kkf23YvVVxc4WS8GJT3qipbYi2joUmESKmKO1S6X0mFNb8UiPm9SWm+0pzNKTFuGhVJcjBg0ahN27d6Njx44466yzcNNNN2HMmDEoLi5OaFwSH4JIAsd4EEtrzsHne7qj02cMnXfUQs7yQQ6IkLIEcL8AKcAgBRhkP4PkB7jIFBnyKT9zIfSrCOVnQT0HneSE1kITQudCQqReU2UJMF5X2ujaAjo50r0O9bN8DfUL0WwIzj+nmEWybmZiASmr37Fsn2B0x9wvUdmJ55rTWh7z60SEx9HrlhblIfFxxM033+yJ6Jgh8SGIJMMkDnYsCEHiYDKH0MjAfQJEnwApS4AcYJD9AmQfh+xTREcWw9Ijh8QHgipAihyBhV+rAqMKkypEYKHXjId+ZVp7VYqYJkTMFCFioTFUIWK6a8qPHCxSiHR/KTMLWdKjT6/ZtUtG9Ma2XQKSY3UfN7O0zP2SLTuAd8XLmSg8gLMoj5hQ0Q2RDG699dakjEviQxDJRGLwNQDsWANYkwTe1AQIgiI+ggAxIEIOiJADAmSRgftYSGyYFgHiItPkRxUbNSWmyQ8ACKowwSBJmvAw3XlVikRFiJjEwAWDsShSJHBAYJrsKNEhFk6nIfRan1bTTnNFjIDwKsyh5pZERF4ixzNeT57gWPWLR3Ji9Y/VN9rGovEIjdOi5Zht4xAe60Jjb4VHOeeueNlOeqSIs8mDcdugpOP+hHtIfAgiSfzYFIDQIECsl4EffwT8frBjAuDzgYkC4BPBfAIEnw/wCZD9oiI+ogAuKCkwrskQg+xjkH1cEyDZZ0qBqZEgfWRIJ0cGGRLVdBgzRo3U8yHp4TILCU9IdtTlemSERSgUHTLUBQFKA21RQl1kR5cdiykvDtNBtmPFGcFxch8gPsmxGsNpRMfJvdxGdsztE5EdJ/0dCZEL4bF81jiEh2h9kPgQRJKol/xgTYAY5JB/PArm94P5fIAoAH4/IApggggmBgFBAAuIWjSIiyK4P/SzoMiP7BMUSfEpEqTIELQaIFWEZJEp0R8fIOgjPLo2thIkqRLEwcVQ6ktQviA1CdKlxZguJcb1AgRAMxzGAY5w9CfKl42V9ESLlGiz0ITIMZlFO6u+dmNbfekmGgWy2jQ0HtGJR4KA6KJj2T6G7FiNmQzhsR7HXVrLri9JT+uFxIcgkgiToXz/NzWF/2rngvKlzH2AwIEmKBIkKeIDvw/MJ4NLgk6EBGXau6DUAzGRAaEUmJoWY5IS/WE+Di6q6Suj7ECGlhJjqvTIoUgRV66zUBRJ+ZmHxCo0PR0Aa1LriGwESJ8G44Ch+MdhmsssPVp5kV6CPFg/B/BGcKzGiRXJseoTT+rK6rqVQKRDdhy3cSA8yrkWJj0cVNzsgMrKSvTo0SNcXxiCc459+/ahZ8+ersYl8SGIJMM4wGUOFpIfBj84msAkOVQ/EzpERXxYk6SkwURFelhIfgRBSYexJhmCoKTEmJ9BEJkWBZJFQGhSU2FcERxJNxsslApjcig6xJXXAg/JkQijAHGmvBZDW02EokGQAXClRghQfoagxHQ4V2M94WiPk5le+tlkdsKTyP5XgLcpKhUvBMdtGzeiY3UuVhrL6ThO2sQ3vnvhsetvJz20nUbmUVRUhKqqKnTp0sVw/vvvv0dRUREkyV1lFokPQaQCLoPLQlh+JCFUNyMo35QCU4RHYEAwCIRSYkwQlV99IrhfhBiUlAiQXwQXZAhNgiI5oSiQoCuKZhIgiOG6IFlmYHK4DghiSHhCUR/tV70AaTAw2SL6IzFt7SDlBw4mK4XSBvmJBotPerSmMVJhTmdUmfuZ+wLOUlRW/ZzIi1U7p7LgRnIAd1GdhM95LDtAfFPUM0l4GA9FgxPo3xrgnEdEewDgyJEjyM7Odj0uiQ9BpAAuczBBBiACnIPLMpggAJKkfINyQUlPyaF8VFMTDP95stDGnn4AEgNjMuATACk0Jb0plF6SoIiErEgJGNfkhHElaiNIgKzWHYeiOyFnCS2WGDon6tqoURvtNQMDN2ay4kRdMFFfFK1fYdpKeKLJTqJr5ADuanCs7mHVzqkEOREc274uJSee8bwWHeV8y5cdA5TqisrMmTMBAIwxzJ07F23atNGuSZKEDz74AKeddprr8Ul8CIIAEM5K2aLaUQwsd57QJMf8q66JSXqsIjzmaJCV7LjZ6sHc1qq92+iNXTuvBQdIjeTYtk1QdOzax5PGAuKXHXUc2rIic9i5cycAJeLzySefIBAIaNcCgQBOPfVU3Hnnna7HJ/EhiFaEQW6c/KtRFwVytWdoSHBitVGlRx/lcSI8TiNATtfFMY9ldd2qjV07p3Jj2z9BwYl33LjaJkl0gNTJTrpg6n9XCfRvyfzjH/8AANxwww147LHHkJeX5+n4QuwmBEG4QWCh1ZIBMIGBiSIgimA+H1ggAAT8QMAPFgiABfxgfj+QFQBysoG2bZRfc7LB22aB5wQgtwmAZ/kh5/gh5fggZfsg5YiQskVI2QLkLAFStoCmLAFSFoOUxdCUxSAFANkf2hojAEj+0D5hInRbZJimxWsLJkK3eCLXTYVX/ubVZncZVodW1vthQkh61OiOwHWH+lo2SA8TQpusQnktGK4rn6kYOidov4avi4Kyc71fkCAyGSKT4RPkiOvqOKI2fvi13XWrNgLj8DEZPiZDANcO9d6x+gqMwycoz2g+HxAl7Zp6BAQJAUEy3EuA8gzm/urYVufjagubw6Kt8udejjjU/x4i7hn67MxHtHFExiMOAJbPGG2cyGdK5t8GJrgHhwuWLl2KoqIiZGdno6SkBFu2bLFtu2nTJjDGIo5//etfWptgMIj58+fjxBNPRHZ2Nk499VS8/vrrtmOWlZWBMYbS0lJHz7ty5UrPpQegiA9BJBelfMcgPRBFMH9okR1RhO5bPVTULIIHlPacMcAXntKubGOhFDNr6/voprQrU9f16/uwSJmxWtMn9JzcB+MKz9qaPmHJURc45AyGzVIjNkgVoqS3TFEecx2PPsJjFd2JFtWJd7NOrwqLbfvGEbWxu1e0cTw7H/d90xPFAeKP5Ng9EwCIobFEtzbRTFi3bh1KS0uxdOlSjBo1Ck8//TTOO+887N69O+q08D179hjk47jjjtN+vvfee7F69Wo888wz6NevH9544w1ccskl2LZtGwYPHmwY58MPP8Ty5csxaNAgx8/8448/4uGHH8bGjRtRU1MDWTb+/n711VeOx9JD4kMQSUIADy3sh7D0+H2KBAnhRQzBBOVXQQgLjzZzK7R6syjEWMTQuGaPtoihaCE85m0tGIzbXwg6yRHCcqTu7RVewyf8Kxd0UiNw+5oewSg1qvTEEh67VJdZdqyEJh7JiXfBv2jnky02bvpEK+pNtuBEG8tNEXIikmMFS2H6i6Uh1bV48WJMnjwZN954IwBgyZIleOONN7Bs2TKUlZXZ9uvSpQvat29vee2FF17AnDlzcP755wMAfv3rX+ONN97A7373O6xevVprd+TIEVx99dV45pln8OCDDzp+5htvvBGbN2/GpEmT0LVrV8sZXm4g8SGIZMMYWFaWIjw+UYnq+ERt3R7u9+miOiHp8dnLjqzu2B5Ndsybmpr279IkR9RFeFh04THv7m4Z5dFeO4vymGdqWQmPU9mJJTr684muaAykV2yijueh3ETr46XgAO7qcdxKTrprfLyirq7O8DorKwtZWVkR7RobG1FRUYFZs2YZzo8bNw7btm2Leo/Bgwejvr4ep5xyCu69916cffbZ2rWGhoaIaeU5OTnYunWr4dwtt9yCCy64AGPHjo1LfF577TX83//9H0aNGuW4jxOSXuNjldPjnGPevHno1q0bcnJyMGbMGHz22WeGfg0NDZg+fTo6d+6Mtm3b4qKLLsK3336b7MclCM/IDxwD93M0ZTOwdm2B3HZAbjvwvHbguW3A2+VAzm8DqX0Ogh1yEGyfg8aOWWhsHwgdfjS096MxT0RjvoiGPBENeQIacxka2wlobMvQ2E45gu0YmtoCwTaAlK0cTTnhQ30tZQNSVriNFADkACBlcUjZHHIWhxwAuJ+D+zi4yCH7ufI6IAO+0HmfDC5yMJ8MJnJAlAGRg4kyBFE5J4g89KtyThRliD7lZ0GttRFCPwscoqDUwQjawQ01O2qdi6hrqz/09T/6c/oaHH3tjbmvvpZGX2djrrWxqrPR16dY1e9Y1c/EOm9Xc2NVUxSr1kcZV7KsdxGi9HFThyMw2bIOJ1otTvz1OOGaIkCRHPMR7ud8zJThUY1Pjx49kJ+frx12kZsDBw5AkiQUFBQYzhcUFKC6utqyT9euXbF8+XKsX78eL730Evr27YtzzjkH77zzjtbm3HPPxeLFi/Hvf/8bsiyjvLwcf/3rX1FVVaW1Wbt2LXbs2BE1qmRHhw4d0LFjx7j7xSKpER+7nN6iRYuwePFirFq1CieffDIefPBB/OxnP8OePXuQm5sLACgtLcXf/vY3rF27Fp06dcIdd9yB8ePHo6KiAqIoJvOxCcIzeJYMKUtUipSz/caojl+AHBAg+QVwP4OkbkoqKtEbc51OxCakCNXkqKsyq1EcFv45In0VirzoNyPVUlVAuHYnSipLjeLESmeZp6bbpbPsUlyKoChj2EV1rKI86peobbTH9AXn1arFsc7HvOYiUhO+Hj2CEa2/m8iNipsITqxxY71Xt5GcmOOmQ3wS6Q9g3759hvobq2iPHqutH+zSR3379kXfvn211yNGjMC+ffvwyCOP4KyzzgIAPPbYY7jpppvQr18/MMZw4okn4oYbbsDKlSu155sxYwbefPNNVwsO/va3v8V9992H5557zrCWT6IkTXzscnqccyxZsgRz5szBpZdeCgB47rnnUFBQgDVr1mDKlCmora3FihUr8MILL2Ds2LEAgNWrV6NHjx546623cO6550bcr6GhAQ0NDdprcwiQINKFFGDKrKyAD3K2Ij1SQJEeZaZVKIXlh5bGMhQjC8af7Wpzwrul64qSDcIDY9pKLzg6keEGqUEoRQV70VGvAdosKwARsqOXGLv0lp3suBWdaJLjxf5Tsc5b3cdpP+W6e6EBokuNk/FjyUCshQCTJTgJj21xvSlqj8wkLy/P0aynzp07QxTFiOhOTU1NRBQoGqeffrqhdue4447DK6+8gvr6ehw8eBDdunXDrFmzUFRUBACoqKhATU0NSkpKtD6SJOGdd97BE088gYaGhqiBjN/97nf48ssvUVBQgN69e8Pv9xuu79ixw/Gz60ma+Njl9Pbu3Yvq6mqMGzdOO5eVlYXRo0dj27ZtmDJlCioqKhAMBg1tunXrhuLiYmzbts1SfMrKyvDAAw8k6+0QRELU9c2HFFCmk3OBgXGuTS+XQ/Ii+xGWHp9RbMB19TeiTnTMu5Kb63D0f8HbSI16TTsPe7mxKkzWujPrImSriI5VnU6saI5ZcKyiOHZiE0tq4pKcOGt4wtcTkxggtsg4uQ/gLLrhZHVjL95TIoLj5B7O3qsMAS23uDkQCKCkpATl5eW45JJLtPPl5eW4+OKLHY+zc+dOdO3aNeJ8dnY2jj/+eASDQaxfvx6XX345AOCcc87BJ598Ymh7ww03oF+/frjnnntiZm8mTJjg+NniISnio+b0Pvzww4hrqnFa5Rq/+eYbrU0gEECHDh0i2tjlI2fPnq0tcw0oEZ8ePXok9D4Iwgtq+3BlBlZozywmK9tIMDlUP+ML/S0ms1ANjaxsBirKilHILBQaZ0qERk0laZuCsnDYXE0fqZuJItRPRRd9UQWCh67rRSY0lG2BsV5mlNeRX0DRojexIjd2qSlVbOykxsnP5vsZztlGdNxHFwBnwhLrPmbiTc043abB6TN4ITXx3NPR/RxKTtrxKNUVDzNnzsSkSZMwdOhQjBgxAsuXL0dlZSWmTp0KQPkO3b9/P55//nkAyqyv3r17Y8CAAWhsbMTq1auxfv16rF+/Xhvzgw8+wP79+3Haaadh//79mDdvHmRZxt133w0AyM3NRXFxseE52rZti06dOkWct+L++++P/406wHPxcZrTiyfX6KSNXTU7QaSTAX33oV7yIVtsgsA46iUfgpKIoCxCkgU0SiKyfEqQXZIFNMkCsnxNWsGtJAuQZAEyZ+AckLigFb0CMJxXX+sjKoDxGoCI6/o2gPVWDlYzpexmT+mv6b9s9f3sUlDhIlf7iIxdGitaf+Vc/NOfE6l/UXFTO+J2Lyk3s5XcFPV6KTRunsPpZ+pUcvxMgszc7fTdXJg4cSIOHjyI+fPno6qqCsXFxdiwYQN69eoFAKiqqkJlZaXWvrGxEXfeeSf279+PnJwcDBgwAP/3f/+nTV0HgPr6etx777346quv0K5dO5x//vl44YUXbKe/Zwqei0+snN6ePXsAKFEdfchMn2ssLCxEY2MjDh06ZIj61NTUYOTIkV4/MkEkhXsK30SQM/zI/QhyAfXcj3rux49yFuplP4Lch6NyAPXcD5kLCHJROWQl/NvA/QjKQuia8qsMBokzyFxAE1eESA79CgAyWPhnm19VZN1eEk1y/BM83ewLFS0KYxX9sW8rR70OxLeZJeBd+ieeezofI5HwQJhEFulz+z7iffb4I1nOn8ufKXKThogPAEybNg3Tpk2zvLZq1SrD67vvvluL3NgxevRo7N69O65n2LRpk+O2kiTh0UcfxZ/+9CdUVlaisbHRcP3777+P694qnotPrJzeCSecgMLCQpSXl2srOzY2NmLz5s1YuHAhAKCkpAR+vx/l5eVarrCqqgqffvopFi1a5PUjE4Tn5DA/jhOAei4hFw2QONDA6/Ej9yEoiJDAEOQ+NHIRR3kWGrmIIPehXvZDBkO97IeEsAzJXIAUkiOZM+08AO21+rMqSAAMkqReV34Ni45eiPQypMcsTUB8X2ixREY5F3uHbqcy43ZX7mRFKKKRrBWDvVqrJtH36Xa2lJuUVLxiEysdSqSXBx54AH/4wx8wc+ZMzJ07F3PmzMHXX3+NV155Bffdd5/rcT0XHyc5vdLSUixYsAB9+vRBnz59sGDBArRp0wZXXXUVACA/Px+TJ0/GHXfcgU6dOqFjx4648847MXDgQG2WF0E0B0TGIIYqhkUuQ+BNkHkotQWGei4ij9ejnvsV+RFFTYhkLii/hgRI0qJCvpA4hYVIiQQJRgmCEBIfRX4kmCNAIRnSSZIZtU0Tjz8iFI14ozGA9RdosqZMa/dMUEpStVBesr60vZjinUhNjdsIjav0XQtfubk58uKLL+KZZ57BBRdcgAceeABXXnklTjzxRAwaNAjvv/8+brvtNlfjpmXl5rvvvhvHjh3DtGnTcOjQIQwfPhxvvvmmtoYPADz66KPw+Xy4/PLLcezYMZxzzjlYtWoVreFDNBv8TIDfsEZoE7IZIHHlb60gZLThMmQEEeQNqOciGqFEdFThUX5lqOcBSJyFokA+SFyJGKnCE+QiJAia4Bh+NYkRAEWaQs8mRaTEws9sliU9so0M2UWNVOJJFyVzOnSs8d3e10tSurZMCK+Lf71ILyXymTsVmlROZ2eyciTSvzVQXV2NgQMHAgDatWuH2tpaAMD48eMxd+5c1+OmRHzMOT3GGObNm4d58+bZ9snOzsbjjz+Oxx9/PLkPRxBJIosZ15zwIRSJUQuTIaOeS5DBIXGOXEiQ0IQgRyiiwxDkQkiGjmnpMTXao0qQGh2S1AgPjLJjJ0UADGIERBZC66NHKvrIUDxC5AXJTEUlUzIyYiaRDamoe/EsLehFvZSNELMWvklpc6R79+6oqqpCz549cdJJJ+HNN9/EkCFD8OGHHyY0mYn26iKIFCGykBBwGbK2I7SSCtNmaYWW25fA4QeHzGQEuQSJKRIksSZFZFgogsPCUSF9NCgsOtFlCECkCMEY+ZEiUmLW9UFAWJT0yEieCEXDS9nImKLYBElXHYvXaSS3s970mJ8plamudBU3NzcuueQSbNy4EcOHD8eMGTNw5ZVXYsWKFaisrMTtt9/uelwSH4JIMSITAC4DEJDFBMiQocaGglyZqi6H5AcAgkyJCMlMDkVsmlCvyg8EZHMGCWER0n52IEMAIiI+ZikCEClDiEyLqf1VrFJekl16zCJylAgtuVA1pV/QHuKFrJjxJAKk23csZZD4OOLhhx/Wfv7lL3+JHj164N1338VJJ52Eiy66yPW4JD4EkQbC8gMICEdJBKZGV2QEQxELJfITkh8AEuPI4k3Kz2CQtdRYSHqg1PI4lSEABiFS7i9YRnrUiI5ZjABrGZJM8mOXBrMTIieYBSsZX7BEYiRb1lrKbutEdIYPH47hw4cnPA6JD0GkGCEkDUIo2mNAJ0OCLhoU5DL8DJAQjgYp4sMhQUmRZWsRIehSYzoRUtNjECCxoEFsVBkCYIgOAQgLEYMhSqT21b8OchFgYTECTLLDrGXILpVkbuuUZNYZEYmTbFFxMxsvldNm1B1lEunfGigrK0NBQQF+9atfGc4/++yz+N///od77rnH1bgkPgSRoQjK9ugAoKXEwGWtJkgGh8ABMfS3oAQOgXPITOnlZ1I4GoRQ1IeFZ3YZRAgM2SEZklk4EqRGhvQyI3MBEjPNCAu99vOwwFjVBCljhr9iJAiATnrMwuLX2sX3V72cYVEftwLXGknWukZmIhfBpFRXpvH0009jzZo1EecHDBiAK664gsSHIJoLapRHCP1PH/XRCqABSFwOyY+KYBAgABCYmppSJMjPEI4EcYSiNBx+xjUJAkM4Laam1tTUmCo3IRnyQwqNEZIYU2TILET612YpUs6FozvmFJUU6q9HlST9/Dh9NMkOL8XHC2lxE3+iqFV0KL3V8jHv8KBy3HHHoaqqyvW4JD4EkSQkLhtExkxEmstERF9TGkw/hjkV5gfT0mFAOCWG0DlVhJRr4YiQKi7mqJByL2NkSBUifXRIed9qX4s6IIME6VeMDguRPkJkJ0nmdhEw6xlmdkSTqXj0w0tZES3SfxQ5ih+nEaRURZoAWsDQKWoxc1FRkeH8u+++i27durkel8SHIJKIFJKVaAKkIlh8xZqjQZImP0zrBSiRHgBaKkwCh8CYtkaQAAYxJEYiAIHzkLgoI4ghLVKKpLlWiyNAgJ/JIRGStCJpP5PC9T6hZ/FDUgTFVOOjFyI/wtf8TC8Kku68ZL2KtOnzUdrZL6IYq6DWIFiIPV3diUjFvGeCU/utelNkiGip3HjjjSgtLUUwGMRPf/pTAMDGjRtx991344477nA9LokPQaSAWNEfwCg5VhIEREuFRQqQNlZIgBThUWTHqi5IHUVfGwRICGopLGsR8kORCHUBQDVFpoqFIklGIVJlCDrJsZci7R1HiIPVWj2yYZ6caQTdmEKUtXmsIkzRpMbprDQrwYonMmWF/rkSFatkIXNBS03Jht8Di98/LtheSyZU45N53H333fj+++8xbdo0bYPS7Oxs3HPPPZg9e7brcUl8CCJFxBP9iZUG04+jCpAMrglTlmlGmDkKpPQzRoKAUCQIgMyUafQSmCEaZBYhVVaUNIFRhPRRIbW/KkSGFJZNhAgWkR+zEIoWX/SSzbeCxJntl5s5muREnAzPZSFRsbbu0O5l8Uxup/frxSpRoYqXqOlCJlv+HKttMhFN/42lfHXtViIvicAYw8KFCzF37lx8/vnnyMnJQZ8+fRJatRkg8SGIlOMk+hMP+hWhjdhLEADDatF+MEicGyJBgDElpoqQMSIEQ2pMFSFzVAiApRDp02QRESLAXoqgPqfFZqdWKUMuaO/N2F9pK1pEYoDIjVstIxR20TnL8Zz9vutFyqlARdw/9KyJrJEUC71cmUWCILyiXbt2GDZsmGfjkfgQRBrwWn4AYw0QEK4DUiNBMmT4mZpq0kWBdJIhIhwJUlNial2QxAH1n6liaMq8zMNFuAYRglIYrTxHeOaYyKRQFClUq6QrnNaPo36dSlyAoJMSc1rHr3MCVYr0EqOKi106SP+vfKtaGb0s2UU0rO5nh16cnG7loRcoNxIj6EXSQ/SRu5ZAUwrfCxU323PppZdi1apVyMvLw6WXXhq17UsvveTqHiQ+BJEmkiE/VpjTYHoBiowSQZtSbpYgMK4TEmWFZFmLEDHldUiE1OhPkAvhVJlJhJR7qHVBOmHTfbnrNw6NJkRKMXOjrq2p5gnRxUi5l/GziFZPZFdQbI4qRUv/xCNM2jMw2dXeZ8rvpXd/1pwUjzc3aK+uzCA/Px8s9HdFXl6e9rOXkPgQRBrRR2i8kCDzGOZZYHoBAoxioEqQGgkCEF5Xh3PdGJGRIHWbCH2RtDJWOIoT3o8sXAQtau2NUSHtOsLpGnVMfXQo3E7/niOlSPlsoouR8mzhvxKjiUksSVJRZSnWzKtwijH2nwHtM41zfzO30mRJGmaSJSNqRWQel1xyCbKzswEAq1atSso9SHwIIkOIp/jZKfoCaEA/Dd6ZBKnoi6Lt0mHha6FokHaNhcXIFBECrKNCEgRdH2sZUt6XUYiU92xMvVmliqzESOnbqN1fj1XkSE8sGdHqbWKIh1NRUsaMfxaXCOulAuJBEc/kREeiRaWSvQdbKvd4Y7JyJNK/pXLJJZeguroaxx13HERRRFVVFbp06eLpPUh8CCLDSEX9DxBOgYVfh1eR9jPBUAitRwaHqIafQ9EbLR0GhAsQuDpueCFFvQipCyiqIgQgMj2miwqZZcjcVx8dUu6rPq8+dRZur51D5BeuKkbW09obbYXDz6zFKHwvh9Eah24iQI5/HR+Xf7bUZ/Zq9pNV9Cmd6bNU3ptqfOw57rjj8P777+PCCy8E55xSXQTRWkiW/Khjq+hTYMprizogwFaCDKdMEmQVCVKuG6NB2rkoIqSMoZMcXbTDSoYAxC1E+j7a+dCv8YqRMpb9758TQXIcmYn3e8HFl6aE8DpNbolcmiA1ouFZeo9ICVOnTsXFF18MxhgYYygsLLRtK0nuCtJJfAgiQ/G6/kc/llX0R8WcAjNLkGVBNBBVgpT76tbYiRIN0s47ECEAljIUHkOfxjJGe8xCpPRR37NpXR+LSJEyRpS1fRB9NlW0yBEQW47Cz+BckiQIca+TI3PB9VR1ySCX3ocpnLxvp4KV0nV8qLjZlnnz5uGKK67Af/7zH1x00UVYuXIl2rdv7+k9SHwIohngdf2PlfyoWKXAgPCiiuYp8QAM0+INqTBAkyAFvaTYR4PCbaKLEGAfFQqPYS9DVuMp48gWUR679Iy1FIXfW7Tfsxhftqwp+nUocuREKiTO4hIYLaLmQpRUvFjbJ+rMOA9liuJCmUO/fv3Qr18/3H///bjsssvQpk0bT8cn8SGIZoSXAhRLfgDEFKCgbiYYYBQgtb8qQUpBtHoextSZ/gvM8F2me6GTKb0IKdfC70MvQsqzRZeh8HgmebH4wrcSIqV/lJRKNHGIWZ/jQBw8lCOVeCUJcC9KKrZLBHgcicmIbT0o4uOI+++/PynjkvgQRDPEKwGKJj9AbAGKVgdkliCrVJjlRRsJ0keDlHbOREgZx7wlhUWUhjmQIauxLZ7VOE6U1Z2jRIuUMaP//spwKCgO5AjQrXXkUJIM6yC5FCWVRLeqcFrkbfecqVx5moqb7RkyZAg2btyIDh06YPDgwVGLm3fs2OHqHiQ+BNGM8UKAYskPEF2AlPPuJUgfCYq4aP4b3qUIWQqGAxlyHB2yu4fFc0cS5fculgw4+LJ3KkfKStjJESTAYi0kF6LhdD8wN6R6U1TCmosvvljbi2vChAlJuQeJD0G0AJJVCG3GXP8TPh+eCg8Y64AAYypMHQeIrAeKJkESwnuJKW3NymB6LvO/FM1RJqsvOkuRsFrdOrKdzJm2ErUeKcoqx8o6RPYbp1qN52Rc4/jR5URb4NGhHAGIW5CA+OtxrAqXE43KZESaC6BUVxT06a1kpboy5E8BQRBeIXE5ZgQnEQQwY/RGOy/AvEGonwmGSJAIZogEqWOp44mMaYdyXb8KNDP0F1n40LcNt+eGQ2AwHObryvPKhsNqHOWcHHEIjFse5v6Gg8m2hwD7w+q5zM+ofEb244d/D3jUQ4/V+zYfxt//JkeHFSLjcR+xiOfZkwnjPOHDDUuXLkVRURGys7NRUlKCLVu22LbdtGmTNqVcf/zrX//S2jzzzDM488wz0aFDB3To0AFjx47F9u3bDeOUlZVh2LBhyM3NRZcuXTBhwgTs2bMnrudubGzEt99+i8rKSsPhFor4EEQLJdlRIKv0l3LeWAQNIGYaTD+eOqb9zDAgYvGaKCkxZTxERk9iRYSAOKJC6l0ssPns7SJEgPsokfIU0SNFscbX3wdwtqKxYfVrhwKhj744jSCp2E3zdzvLK9HVrJsD69atQ2lpKZYuXYpRo0bh6aefxnnnnYfdu3ejZ8+etv327NmDvLw87fVxxx2n/bxp0yZceeWVGDlyJLKzs7Fo0SKMGzcOn332GY4//ngAwObNm3HLLbdg2LBhaGpqwpw5czBu3Djs3r0bbdu2jfrMX3zxBSZPnoxt27YZzqsLG7pdx4dx7lIdM5y6ujrk5+ejZk8v5OVSYIsgzOhlyIsIkVUKLHwtcvygxT0l0xhWY0rc3Cb6GEof8/NEYlWfI1u8Jat2QRsZsqv5iZZysSyojjGedj1mMXTsvwtj3SOe+xnv7U4uvEhPOVkP6ehhCVed9ilqa2sNX/Reon4vnXbNQxAD2a7HkRrrsWv1nLiedfjw4RgyZAiWLVumnevfvz8mTJiAsrKyiPabNm3C2WefjUOHDjleR0eSJHTo0AFPPPEErr32Wss2//vf/9ClSxds3rwZZ511VtTxRo0aBZ/Ph1mzZqFr164Rhc6nnnqqo+cyQxEfgmileJ0Os6v/Ua4JEfJjrgMC7GuBgLAE6afHK22gawPLaFL02qDIiJC2fpDpu1rmkZEjCUxLi+lRtt6wqfmxiYooCwxaf4axIkSA/bYL4ehN9EgRYBEZs7lXtPuZ76vcO77IkXYPFxEkM04iSn7mLnqQTurq6gyvs7KytMJgPY2NjaioqMCsWbMM58eNGxcRTTEzePBg1NfX45RTTsG9996Ls88+27bt0aNHEQwG0bFjR9s2tbW1ABC1jcquXbtQUVGBfv36xWwbDyQ+BEF4hl36S7kWmQIDItNggLW8mMc2F0UrbcJErBUE6wJp637WwuJEhNS28coQYP0lH14fJ7Kftk2HSyEC4pOiaPfS309rG4cYKc/gLAGRiCBp905jiatX09l79OhhOH///fdj3rx5Ee0PHDgASZJQUFBgOF9QUIDq6mrLe3Tt2hXLly9HSUkJGhoa8MILL+Ccc87Bpk2bbCM1s2bNwvHHH4+xY8daXuecY+bMmTjjjDNQXFwc410Cp5xyCg4cOBCzXbyQ+BAE4TlOBEi57m0UCLCXIP1Y6nii6fvTLhqk9I2M9JhFCPBOhtQ+bqJDynPYR4jUsYHUSZH+nlp7B1PIrReMdC9I2r1N76k5blmxb98+Q6rLKtqjx5wqirYJaN++fdG3b1/t9YgRI7Bv3z488sgjluKzaNEi/PGPf8SmTZuQnW2dxrv11lvx8ccfY+vWrVGfU2XhwoW4++67sWDBAgwcOBB+v99w3W1KksSHIIikES39pVyPHgWyEiDAewlSx0xUhADr9Fi09nYyZNVH3y9adEh5DvsIkd3Y+vGB2KkzILYwJCJG0Z7B7nn0eCFImUxeXp6jL//OnTtDFMWI6E5NTU1EFCgap59+OlavXh1x/pFHHsGCBQvw1ltvYdCgQZZ9p0+fjldffRXvvPMOunfv7uh+auTonHPOMZxPtLiZxIcgiKQSLfoTbuNcgIDIKJD+Pvp7OZUg/Zj6cWOlxfRjJCpC+j5eypBy3T5dpjyTN0IEWKWvnEWLot3b6hkM/RKQIyA8pT9VpHrl5kAggJKSEpSXl+OSSy7RzpeXl+Piiy92PM7OnTvRtWtXw7n/9//+Hx588EG88cYbGDp0aEQfzjmmT5+Ol19+GZs2bUJRUZHj+/3jH/9w3DYeSHwIgkgJXggQEDsKZHevWBKktLcf1yoaFH0MZyIExI4KAe5lSLmePCGKuJdHUgTEL0bmZzH0jSFHTuTJK5gce1HuWP3jZebMmZg0aRKGDh2KESNGYPny5aisrMTUqVMBALNnz8b+/fvx/PPPAwCWLFmC3r17Y8CAAWhsbMTq1auxfv16rF+/Xhtz0aJFmDt3LtasWYPevXtrEaV27dqhXbt2AIBbbrkFa9aswV//+lfk5uZqbfLz85GTkxP1mUePHh3/G3UAiQ9BECklEQECYkeBAOtUmP6eVhKktNe3jRxXP3aiIqSM5T4qBMQvQ+b+btJlyvOZt5+IfS8gPikC4hejaM8S7blaAxMnTsTBgwcxf/58VFVVobi4GBs2bECvXr0AAFVVVYZFARsbG3HnnXdi//79yMnJwYABA/B///d/OP/887U2S5cuRWNjI375y18a7qUvslanz48ZM8bQZuXKlbj++uujPvPHH39seZ4xhuzsbPTs2TNmXZNlf1rHhyCIdBFNfozt7L8ArdYDUrFa0yfafc1rBIXbxze+ed0gJ2Mp49l/IVutKeSkH2C/zpDT/kobB/uCxbEQYLLWC9KeJc5ZWz8elnDBoK9Sso5PyeWJr+NT8af41vFpjgiCEHWTUr/fj4kTJ+Lpp5+2Lai2HNeLhyMIgnCD3fYXke2irdFi3BZDj3mbC/N9zfc2b5kRbm/cDsNqfNGQ7oncUsNqrMjxrLeeABCx5Ua0fua+5q04zJGiWP2VNrG3ebDbtsOKWNttGNo62HrDTLQtP1I6g8sGtc7HzdFaePnll9GnTx8sX74cu3btws6dO7F8+XL07dsXa9aswYoVK/D222/j3nvvjWtcSnURBJF24kl/Ke3sU2CAdRTIqiBaf2/z/Z2kw5Q+kfcw38cuLRZ7PPuan2i1QlZ9zf2jpcns+pvHUNpFT5cpzxp92r1xPOfrBAHxrxWkPVPEdPZWZBTNhIceegiPPfYYzj33XO3coEGD0L17d8ydOxfbt29H27Ztcccdd+CRRx5xPC6JD0EQGUOs6e/hdvY1QEB0CbKTE/X+KnYSBMSuCzLfx3wvr0RIGddehszpsURlyMkYSpvoxdR6nNYR2d3b7hm0Pi7FKKlwbr03XDz9WwGffPKJVoOkp1evXvjkk08AAKeddhqqqqriGpdSXQRBZBRO019K28gd4c04SYXF+xxW6TClj3UKS38vq/u5TY0p4zpPj1lFiWKlmmKlyazGSCRdFn5252mzaM8Qq9jZSdqMSA/9+vXDww8/jMbGRu1cMBjEww8/rG1jsX///rjWIgIo4kMQRIbiNPqjtI0eAQLsZ4MB7qJAgPNIkNLX+n5W97RaP8jJuMrY9ukxIPGoEOAsMuR0LKVd4hEiwL642k2kKJmkeh2f5sqTTz6Jiy66CN27d8egQYPAGMPHH38MSZLw97//HQDw1VdfYdq0aXGNS+JDEETGEk06rNs7FyDAWwkC7OuClL5hImXFXVrMPK712PGJEOCdDAHOUmVW4yltnQsREF/azPw8TqbBewaHJ1tWtHRGjhyJr7/+GqtXr8YXX3wBzjl++ctf4qqrrkJubi4AYNKkSXGPS+JDEESzwE0ECHAfBQLsC6LV5wnfwzsJ0t/X6t5ei5Byj+TIEOB9dEhp640QAfFNwSdST7t27bRFFr2CxIcgiGaDk9lfkX0SS4MB0UVE/1x2z+ZUgpT+9ve2un+iIqTcI3pUCIidIrMax26sRGTIbkylfXxCBISliKUwf5SOlZubC6+++irOO+88+P1+vPrqq1HbXnTRRa7uQeJDEESzI9kCBLiLAumfze75okmQ0j9MvNEgZXzj61SJEJAaGbIb025cpX38QpRUKNVly4QJE1BdXY0uXbpgwoQJtu1ok1KCIFolyRIgIPEokP757J4xHglSxrB/BrvniFeErO/jTF5SIUNAcoTITo6I1CLLsuXPXkLiQxBEsyee+p9wn/gECEivBCljhIkVDbJ7lmgzxqzuY3+v2FEhwFmKzGq8aGPGEx2Kd+xUQLO60gut40MQRIvA6do/kf1irwWkEm1NIJVoawOF7xl9rSK7rTOMY9iv7WN+FrvnibZ+kN297O7ndO0cJ2sL2Y0ZbVwn6w25HZtILR988AFee+01w7nnn38eRUVF6NKlC26++WY0NDS4Hp/EhyCIFoPdHlzO+iZHgKJJkJPn1UuQnQg5ExPrfcWM90qeCGWKDMUSopSgrtycyNGCmTdvnmFn9k8++QSTJ0/G2LFjMWvWLPztb39DWVmZ6/Ep1UUQRIvETfpL6ecsBQY4S4MB8afClPtbt/MiJWZ+JrvnilUfZHW/6Pd0nnJymiKLd1zAOlWWSiGiVFd0du3ahd/+9rfa67Vr12L48OF45plnAAA9evTA/fffj3nz5rkan8SHIIgWi5vi53Bf5wIExC6GVnEiQcr9Yz97vBKkjOf+ubwWIeW+7mqFAG9liMgcDh06ZNiGYvPmzfj5z3+uvR42bBj27dvnenxKdREE0eJxm/5S+jpPgQHhNFisVBgQXz1QrOd3UhekjBdfbVC05/MyNRa+t/O6m3hSZFZjp6uuR13HJ5GjJVNQUIC9e/cCABobG7Fjxw6MGDFCu3748GH4/X7X41PEhyCIVoPb9JfS19lq0HqSFQVSniGxSJAyXpjoUZnYaTHlvsbXTiNC0e4fb+TGbWQotVtWJFin08JrfH7+859j1qxZWLhwIV555RW0adMGZ555pnb9448/xoknnuh6fBIfgiBaFYmkv8JjuEuDAemVICDxlFg8z+hUhOK/v7P0mDZ2nDJEpJcHH3wQl156KUaPHo127drhueeeQyAQ0K4/++yzGDdunOvxSXwIgmiVpEOAAOdRICD2KtHh53AmQUD6okHKvY2vkyVCynPEL0Opgoqbo3Pcccdhy5YtqK2tRbt27SCKouH6n//8Z7Rr1871+CQ+BEG0apqTAAHplyBl3ChjZoAIKc+ReFQoadCWFY7Iz8+3PN+xY8eExiXxIQiCQPoFCGgeEqSMGya2gKRGhGI9C83yIlRIfAiCIHQkUgAdHiP+QmggMyUI8C4aBMT3zPGIkLtnCQ8opDCMQqmu9ELiQxAEYcKL6E94rPijQEB8qTDAeT2Q8kzOJQjIjGiQ8hzG116LENE6IPEhCIKwoTkLEJBZEqSMH2Ps1iJCMk9sWhlNSUsIEh+CIIgYZJIAAc1TgpTxwzh5B6kUoZSu5kvFzWmFxIcgCMIhXtT/hMdyJ0BA/FEgILUSBHgfDQLifw/xihDROiDxIQiCiAMvoz/KeO4KoQF3USAg+RIEZF40SHkm4+t0iRBDgsXNnj1J64T26iIIgnBBIvt/2Y8Z375gepzuD2bGyX5hepzuHWa4h8N9xML3cL63l3YPh/uLGZ/L2V5jnqNuWZHI4YKlS5eiqKgI2dnZKCkpwZYtWxz1e/fdd+Hz+XDaaacZzq9atQqMsYijvr7ek/smCxIfgiCIBMhUAYpXguKVBiA1EqTcJz4JAtyJUEtm3bp1KC0txZw5c7Bz506ceeaZOO+881BZWRm1X21tLa699lqcc845ltfz8vJQVVVlOLKzsxO+bzLxXHzKysowbNgw5ObmokuXLpgwYQL27NljaMM5x7x589CtWzfk5ORgzJgx+OyzzwxtGhoaMH36dHTu3Blt27bFRRddhG+//dbrxyUIgvAEr+VHGdO9AAGJR4FSKUHJjAYB7t5TslDX8UnkAIC6ujrD0dDQYHvPxYsXY/LkybjxxhvRv39/LFmyBD169MCyZcuiPuuUKVNw1VVXGXZHN7wXxlBYWGg4vLhvMvFcfDZv3oxbbrkF77//PsrLy9HU1IRx48bhxx9/1NosWrQIixcvxhNPPIEPP/wQhYWF+NnPfobDhw9rbUpLS/Hyyy9j7dq12Lp1K44cOYLx48dDkiSvH5kgCMITkhH9Ucb1RoAyWYKA1hMNYjJP+ACAHj16ID8/XzvKysos79fY2IiKioqIjT3HjRuHbdu22T7nypUr8eWXX+L++++3bXPkyBH06tUL3bt3x/jx47Fz586E75tsPC9ufv311w2vV65ciS5duqCiogJnnXUWOOdYsmQJ5syZg0svvRQA8Nxzz6GgoABr1qzBlClTUFtbixUrVuCFF17A2LFjAQCrV69Gjx498NZbb+Hcc8+NuG9DQ4PBduvq6rx+awRBEI7wugA6PK77QmgVtwXRQPxF0UBkJCxZxdHKvYw4fXeZEgmKl3379iEvL097nZWVZdnuwIEDkCQJBQUFhvMFBQWorq627PPvf/8bs2bNwpYtW+DzWatCv379sGrVKgwcOBB1dXV47LHHMGrUKHz00Ufo06ePq/umgqTX+NTW1gIIbyq2d+9eVFdXGwwwKysLo0eP1gywoqICwWDQ0KZbt24oLi62tcSysjKD+fbo0SNZb4kgCMIRyYoAKWMnFgUC3KfCAPeykKqUmHIvdxGhpCN7cECpr9EfduKjwkyfHec84hwASJKEq666Cg888ABOPvlk2/FOP/10XHPNNTj11FNx5pln4k9/+hNOPvlkPP74467umyqS+meBc46ZM2fijDPOQHFxMQBolhfNAKurqxEIBNChQwfbNmZmz56N2tpa7di3b5/Xb4cgCMIVyZIfZWzvBChVqTCVVKbElPtloASlgM6dO0MUxYjvz5qamojvYgA4fPgw/vnPf+LWW2+Fz+eDz+fD/Pnz8dFHH8Hn8+Htt9+2vI8gCBg2bBj+/e9/u7pvqkjq7/+tt96Kjz/+GH/84x8jrrkxwGhtsrKyIuyXIAgiU3D7Je98/MQFCPAmCtTcJCjVIsQ4T/iIh0AggJKSEpSXlxvOl5eXY+TIkRHt8/Ly8Mknn2DXrl3aMXXqVPTt2xe7du3C8OHDLe/DOceuXbvQtWtXV/dNFUlbwHD69Ol49dVX8c4776B79+7aebXiu7q6WvtwAKMBFhYWorGxEYcOHTJEfWpqatL6YREEQXiBlytAR46deB0QkFgtEOCuHkjFzYKJQPyrRxvvmULSsGXFzJkzMWnSJAwdOhQjRozA8uXLUVlZialTpwJQsib79+/H888/D0EQtCyNSpcuXZCdnW04/8ADD+D0009Hnz59UFdXh9///vfYtWsXnnzyScf3TQeeiw/nHNOnT8fLL7+MTZs2oaioyHC9qKgIhYWFKC8vx+DBgwEold+bN2/GwoULAQAlJSXw+/0oLy/H5ZdfDgCoqqrCp59+ikWLFnn9yARBECknWQXQxnu43xZDj5stMvSkQ4IAdwXSLZWJEyfi4MGDmD9/PqqqqlBcXIwNGzagV69eAJTv2HjX1vnhhx9w8803o7q6Gvn5+Rg8eDDeeecd/OQnP3F833TAOPf2T8O0adOwZs0a/PWvf0Xfvn218/n5+cjJyQEALFy4EGVlZVi5ciX69OmDBQsWYNOmTdizZw9yc3MBAL/+9a/x97//HatWrULHjh1x55134uDBg6ioqIAoijGfo66uDvn5+ajZ0wt5ua0to0sQRHMjmQIUvod3+5G7lSCVeAXITCKfl5UEHT4s4+T+36G2tjZppRLq99JZo+bC58uO3cGGpqZ6vPPub5P6rC0ZzyM+6qJEY8aMMZxfuXIlrr/+egDA3XffjWPHjmHatGk4dOgQhg8fjjfffFOTHgB49NFH4fP5cPnll+PYsWM455xzsGrVKkfSQxAE0dxoThEgIL1RIMC7SBCQ+miQfhFCt/0J93ge8ckUKOJDEERzJhURIOU+mRMFAtIXCTp8WMaJ/apTEvEZPTLxiM/mbRTxcQvtzk4QBJGBJLMA2nifzIkCAemNBKWMBDYa1foTriHxIQiCyFBSkf4K38t7AQJIgojMg8SHIAgiw2muAgR4L0FuU2GZJEFMVo5E+hPuIfEhCIJoJqRDgJT7eStB6YwCARkgQZTqSiskPgRBEM2MVAqQcr/MjgIBiUtQMrcVITILEh+CIIhmSnMXIMCbKBDgjQSljDSs3EyEIfEhCIJo5rQkAQJavgS52W/L3J9wD4kPQRBECyFVU+DD9/O+DgjwLgoEZL4EEamHxIcgCKIFkeroT/i+mR0FAjJIgmQOSAncXyaBSwQSH4IgiBZISxIgIHkSlA4BolRXeiHxIQiCaMG0NAECkpMKo1ldrQcSH4IgiFZASxYgwBsJShkcCa7j49mTtEpIfAiCIFoR6RYg5d6ZHQUiWjYkPgRBEK2QdAmQcu9WHgWilZvTCokPQRBEKybVU+CN905NFAjIMAmSgYRKijLorTRHhNhNCIIgiJaMAJb24l4h9L9k4WeCQYSI1gtFfAiCIAgA6U1/hZ8heWkwIDOiQDSdPb2Q+BAEQRAGWoMAAWksiKYan7RC4kMQBEFYkkkCpDxH8qJAflrGp9VA4kMQBEFEJRMESHmO5EeBUgJFfNIKiQ9BEAThCBIgjyDxSSskPgRBEERcZJoAAc1YgoiUQ+JDEARBuCKdawCZaVZRIFrHJ63QogYEQRCEazJhDSA9yV4PiGj+UMSHIAiCSJhMSX+pZHIEiMkyGHP/XEzOvPfUnCAtJgiCIDwjUyNAGRUFknnihwuWLl2KoqIiZGdno6SkBFu2bLFtu3XrVowaNQqdOnVCTk4O+vXrh0cffdTQZsyYMWCMRRwXXHCB1qapqQn33nsvioqKkJOTgxNOOAHz58+HnEZ5o4gPQRAE4TmZFgECMjsKlGzWrVuH0tJSLF26FKNGjcLTTz+N8847D7t370bPnj0j2rdt2xa33norBg0ahLZt22Lr1q2YMmUK2rZti5tvvhkA8NJLL6GxsVHrc/DgQZx66qm47LLLtHMLFy7EU089heeeew4DBgzAP//5T9xwww3Iz8/HjBkzkv/GLWCct8x5cXV1dcjPz0fNnl7Iy80g0ycIgmiFZJIAqegFqO6wjG59v0VtbS3y8vKScj/1e2nsCTPgE7Ncj9MkNeCtrx7Dvn37DM+alZWFrCzrcYcPH44hQ4Zg2bJl2rn+/ftjwoQJKCsrc3TfSy+9FG3btsULL7xgeX3JkiW47777UFVVhbZt2wIAxo8fj4KCAqxYsUJr94tf/AJt2rSxHSfZkBEQBEEQSSfTUmBAOtNgPLyWj5sjJJE9evRAfn6+dtgJTGNjIyoqKjBu3DjD+XHjxmHbtm2Onnjnzp3Ytm0bRo8ebdtmxYoVuOKKKzTpAYAzzjgDGzduxBdffAEA+Oijj7B161acf/75ju6bDCjVRRAEQaSMTEyBAcisGiCHWEV8rDhw4AAkSUJBQYHhfEFBAaqrq6Peo3v37vjf//6HpqYmzJs3DzfeeKNlu+3bt+PTTz81RHYA4J577kFtbS369esHURQhSRIeeughXHnllU7eYlIg8SEIgiBSTiatAZRyPFq5OS8vL660HGPGiBvnPOKcmS1btuDIkSN4//33MWvWLJx00kmW0rJixQoUFxfjJz/5ieH8unXrsHr1aqxZswYDBgzArl27UFpaim7duuG6665z/OxeQuJDEARBpIVMjf60NDp37gxRFCOiOzU1NRFRIDNFRUUAgIEDB+K7777DvHnzIsTn6NGjWLt2LebPnx/R/6677sKsWbNwxRVXaON88803KCsrS5v4NL/YHkEQBNGiyMT6n6SS4unsgUAAJSUlKC8vN5wvLy/HyJEjHY/DOUdDQ0PE+T/96U9oaGjANddcE3Ht6NGjEASjaoiiSNPZCYIgCKLVRIC4rByJ9I+TmTNnYtKkSRg6dChGjBiB5cuXo7KyElOnTgUAzJ49G/v378fzzz8PAHjyySfRs2dP9OvXD4Cyrs8jjzyC6dOnR4y9YsUKTJgwAZ06dYq4duGFF+Khhx5Cz549MWDAAOzcuROLFy/Gr371q7jfg1eQ+BAEQRAZRasRoBQyceJEHDx4EPPnz0dVVRWKi4uxYcMG9OrVCwBQVVWFyspKrb0sy5g9ezb27t0Ln8+HE088EQ8//DCmTJliGPeLL77A1q1b8eabb1re9/HHH8fcuXMxbdo01NTUoFu3bpgyZQruu+++5L3ZGNA6PgRBEERGkwoBqjsso7BvZWrW8enxa/iEBNbxkRvw1r5lSX3WlgxFfAiCIIiMpsVFgOTwWjzu+xNuoVAIQRAE0SxodUXQRFKgiA9BEATRrGj2ESCP1vEh3EHiQxAEQTRLmq0AcSQoPp49SauEUl0EQRBEs4ZSYEQ8UMSHIAiCaBE0m20wJAngkvv+cgJ9CYr4EARBEC0Hiv4QsaCID0EQBNHiyOj6HypuTiskPgRBEESLJSMFiMQnrVCqiyAIgmjxUAqMUKGID0EQBNFqyIgIEK3cnFZIfAiCIIhWRzoFiHMZPIHd2RPpS5D4EARBEK0YSn+1Pkh8CIIgiFZPSgWI88TSVVTcnBAkPgRBEASRSniCNT4kPglBs7oIgiAIgmg1UMSHIAiCIFKJLAMsgQJlKm5OCIr4EARBEATRaqCID0EQBEGkEqrxSSskPgRBEASRQrgsgyeQ6qJ1fBKDUl0EQRAEQbQaKOJDEARBEKmEUl1phcSHIAiCIFKJJANMct+fUl0JQakugiAIgiBaDRTxIQiCIIgUwmUOztynqziluhKCIj4EQRAEQbQaKOJDEARBEKmEywBo5eZ0kfERn6VLl6KoqAjZ2dkoKSnBli1b0v1IBEEQBOEaLvOEDzfE8326detWjBo1Cp06dUJOTg769euHRx99NKLd+vXrccoppyArKwunnHIKXn755Yg2+/fvxzXXXINOnTqhTZs2OO2001BRUeHqPXhBRovPunXrUFpaijlz5mDnzp0488wzcd5556GysjLdj0YQBEEQzYZ4v0/btm2LW2+9Fe+88w4+//xz3Hvvvbj33nuxfPlyrc17772HiRMnYtKkSfjoo48wadIkXH755fjggw+0NocOHcKoUaPg9/vx2muvYffu3fjd736H9u3bJ/st28J4BldJDR8+HEOGDMGyZcu0c/3798eECRNQVlZmaNvQ0ICGhgbtdW1tLXr27IkvK3ogt11G+x1BEASRZg4fkXFiyT788MMPyM/PT8o96urqkJ+fjzNwPnzwux6nCUFsxQbs27cPeXl52vmsrCxkZWVZ9onn+9SOSy+9FG3btsULL7wAAJg4cSLq6urw2muvaW1+/vOfo0OHDvjjH/8IAJg1axbefffdzMrW8AyloaGBi6LIX3rpJcP52267jZ911lkR7e+//351RSg66KCDDjrocHV8+eWXSfteO3bsGC8sLPTkOdu1axdx7v7777e8b7zfp1bs2LGDFxQU8GeeeUY716NHD7548WJDu8WLF/OePXtqr/v3789LS0v5L3/5S37cccfx0047jS9fvtzhJ5YcMra4+cCBA5AkCQUFBYbzBQUFqK6ujmg/e/ZszJw5U3v9ww8/oFevXqisrEyavbdk6urq0KNHj4h/URCxoc/OPfTZJQZ9fu5RswQdO3ZM2j2ys7Oxd+9eNDY2JjwW5xyMMcM5u2hPvN+nerp3747//e9/aGpqwrx583DjjTdq16qrq2OO+dVXX2HZsmWYOXMmfvOb32D79u247bbbkJWVhWuvvdbRe/WajBUfFfNvrNVvNmAf4svPz6e/ABIgLy+PPj+X0GfnHvrsEoM+P/cIQnJLI7Kzs5GdnZ3Ue9jh9PtUz5YtW3DkyBG8//77mDVrFk466SRceeWVjseUZRlDhw7FggULAACDBw/GZ599hmXLlpH4mOncuTNEUYyw0ZqamgjDJAiCIAjCmkS+T4uKigAAAwcOxHfffYd58+Zp4lNYWBhzzK5du+KUU04xtOnfvz/Wr1/v+v0kSsZW/QYCAZSUlKC8vNxwvry8HCNHjkzTUxEEQRBE88Kr71POuWES0YgRIyLGfPPNNw1jjho1Cnv27DG0+eKLL9CrV6943oKnZGzEBwBmzpyJSZMmYejQoRgxYgSWL1+OyspKTJ06NWbfrKws3H///bY5TyI69Pm5hz4799Bnlxj0+bmnpX92sb5PZ8+ejf379+P5558HADz55JPo2bMn+vXrB0BZ1+eRRx7B9OnTtTFnzJiBs846CwsXLsTFF1+Mv/71r3jrrbewdetWrc3tt9+OkSNHYsGCBbj88suxfft2LF++3DAtPuWktbTaAU8++STv1asXDwQCfMiQIXzz5s3pfiSCIAiCaHZE+z697rrr+OjRo7XXv//97/mAAQN4mzZteF5eHh88eDBfunQplyTJMOaf//xn3rdvX+73+3m/fv34+vXrI+77t7/9jRcXF/OsrCzer1+/tM/qyuh1fAiCIAiCILwkY2t8CIIgCIIgvIbEhyAIgiCIVgOJD0EQBEEQrQYSH4IgCIIgWg0tVnyWLl2KoqIiZGdno6SkJLM2SEsDZWVlGDZsGHJzc9GlSxdMmDAhYm0FzjnmzZuHbt26IScnB2PGjMFnn31maNPQ0IDp06ejc+fOaNu2LS666CJ8++23qXwraaesrAyMMZSWlmrn6LOLzv79+3HNNdegU6dOaNOmDU477TRUVFRo1+nzs6apqQn33nsvioqKkJOTgxNOOAHz58+HLMtaG/rswrzzzju48MIL0a1bNzDG8Morrxiue/VZHTp0CJMmTUJ+fj7y8/MxadIk/PDDD0l+d4RnpHFGWdJYu3Yt9/v9/JlnnuG7d+/mM2bM4G3btuXffPNNuh8tbZx77rl85cqV/NNPP+W7du3iF1xwAe/Zsyc/cuSI1ubhhx/mubm5fP369fyTTz7hEydO5F27duV1dXVam6lTp/Ljjz+el5eX8x07dvCzzz6bn3rqqbypqSkdbyvlbN++nffu3ZsPGjSIz5gxQztPn50933//Pe/Vqxe//vrr+QcffMD37t3L33rrLf6f//xHa0OfnzUPPvgg79SpE//73//O9+7dy//85z/zdu3a8SVLlmht6LMLs2HDBj5nzhy+fv16DoC//PLLhutefVY///nPeXFxMd+2bRvftm0bLy4u5uPHj0/V2yQSpEWKz09+8hM+depUw7l+/frxWbNmpemJMo+amhoOQFvHQZZlXlhYyB9++GGtTX19Pc/Pz+dPPfUU55zzH374gfv9fr527Vqtzf79+7kgCPz1119P7RtIA4cPH+Z9+vTh5eXlfPTo0Zr40GcXnXvuuYefccYZttfp87Pnggsu4L/61a8M5y699FJ+zTXXcM7ps4uGWXy8+qx2797NAfD3339fa/Pee+9xAPxf//pXkt8V4QUtLtXV2NiIiooKjBs3znB+3Lhx2LZtW5qeKvOora0FAG0n4r1796K6utrwuWVlZWH06NHa51ZRUYFgMGho061bNxQXF7eKz/aWW27BBRdcgLFjxxrO02cXnVdffRVDhw7FZZddhi5dumDw4MF45plntOv0+dlzxhlnYOPGjfjiiy8AAB999BG2bt2K888/HwB9dvHg1Wf13nvvIT8/H8OHD9fanH766cjPz29Vn2dzJqO3rHDDgQMHIElSxMZrBQUFEZuptVY455g5cybOOOMMFBcXA4D22Vh9bt98843WJhAIoEOHDhFtWvpnu3btWuzYsQMffvhhxDX67KLz1VdfYdmyZZg5cyZ+85vfYPv27bjtttuQlZWFa6+9lj6/KNxzzz2ora1Fv379IIoiJEnCQw89pG0SSZ+dc7z6rKqrq9GlS5eI8bt06dKqPs/mTIsTHxXGmOE15zziXGvl1ltvxccff2zYT0XFzefW0j/bffv2YcaMGXjzzTeRnZ1t244+O2tkWcbQoUOxYMECAMDgwYPx2WefYdmyZbj22mu1dvT5RbJu3TqsXr0aa9aswYABA7Br1y6UlpaiW7duuO6667R29Nk5x4vPyqp9a/08myMtLtXVuXNniKIYYd41NTURpt8amT59Ol599VX84x//QPfu3bXzhYWFABD1cyssLERjYyMOHTpk26YlUlFRgZqaGpSUlMDn88Hn82Hz5s34/e9/D5/Pp713+uys6dq1K0455RTDuf79+6OyshIA/dmLxl133YVZs2bhiiuuwMCBAzFp0iTcfvvtKCsrA0CfXTx49VkVFhbiu+++ixj/f//7X6v6PJszLU58AoEASkpKUF5ebjhfXl6OkSNHpump0g/nHLfeeiteeuklvP322ygqKjJcLyoqQmFhoeFza2xsxObNm7XPraSkBH6/39CmqqoKn376aYv+bM855xx88skn2LVrl3YMHToUV199NXbt2oUTTjiBPrsojBo1KmLphC+++AK9evUCQH/2onH06FEIgvGvaVEUtens9Nk5x6vPasSIEaitrcX27du1Nh988AFqa2tb1efZrElHRXWyUaezr1ixgu/evZuXlpbytm3b8q+//jrdj5Y2fv3rX/P8/Hy+adMmXlVVpR1Hjx7V2jz88MM8Pz+fv/TSS/yTTz7hV155peVUz+7du/O33nqL79ixg//0pz9tkdNiY6Gf1cU5fXbR2L59O/f5fPyhhx7i//73v/mLL77I27Rpw1evXq21oc/Pmuuuu44ff/zx2nT2l156iXfu3JnffffdWhv67MIcPnyY79y5k+/cuZMD4IsXL+Y7d+7UljLx6rP6+c9/zgcNGsTfe+89/t577/GBAwfSdPZmRIsUH845f/LJJ3mvXr14IBDgQ4YM0aZtt1YAWB4rV67U2siyzO+//35eWFjIs7Ky+FlnncU/+eQTwzjHjh3jt956K+/YsSPPycnh48eP55WVlSl+N+nHLD702UXnb3/7Gy8uLuZZWVm8X79+fPny5Ybr9PlZU1dXx2fMmMF79uzJs7Oz+QknnMDnzJnDGxoatDb02YX5xz/+Yfn33HXXXcc59+6zOnjwIL/66qt5bm4uz83N5VdffTX//+3awQmAUAwFQey/2JQQK/AkfMGd6SC35ZGZOXQlb127u99sTQAAZ/3uxwcA4InwAQAyhA8AkCF8AIAM4QMAZAgfACBD+AAAGcIHAMgQPgBAhvABADKEDwCQcQP7odmO/0jfZgAAAABJRU5ErkJggg==",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1335,14 +1349,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1366,14 +1378,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1406,14 +1416,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -1442,7 +1450,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.5"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
diff --git a/examples/metocean_example.ipynb b/examples/metocean_example.ipynb
index 42b342684..0dada39b0 100644
--- a/examples/metocean_example.ipynb
+++ b/examples/metocean_example.ipynb
@@ -559,7 +559,7 @@
     ")\n",
     "\n",
     "# Replace 99, 999, 9999 with NaN\n",
-    "ndbc_dict[\"2018\"] = ndbc_dict[\"2018\"].replace({99.0: np.NaN, 999: np.NaN, 9999: np.NaN})\n",
+    "ndbc_dict[\"2018\"] = ndbc_dict[\"2018\"].replace({99.0: np.nan, 999: np.nan, 9999: np.nan})\n",
     "\n",
     "# Display DataFrame of 46022 data from 2018\n",
     "ndbc_dict[\"2018\"]"
@@ -719,7 +719,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -904,7 +904,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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wAIAVK1bQuXNnOnfuzD//+U+/9bBjxw5yc3PJysoiMzOThQsXAtC0aVNuv/12OnTowLnnnlv2Bvn5559z/vnnk52dTU5ODh9/7Cx0tnPnTi677DK6d+9O9+7d+eADZ5Gl3bt3079/fzp06MD111+PLTRkTEVxEfgffHsTB0qPlNt2oPQID75d+/w/o0aNYtq0aXz//fdVHtu1a9eywAVw5ZVX0qlTJzIyMrjnnntISEhg3bp1ZGdnB3XtsWPH8sADD/hNMnXqqadSWFhITk4Ow4cP59VXX+XDDz/k3nsrpj/PyckpC8DLly+npKSE0tJSFi5cSG5uboXjP/30U0aNGsX69etJSUlh5syZAFx77bVMmjSJ1atXByzzSy+9xIABAygsLGT16tVkZWUBsG/fPrp168b69es555xz+Mtf/gLAyJEjmTRpEitWrOChhx7id79zVr4bPXo0t99+O8uWLWPmzJllb34TJkygT58+rF+/nsGDB7N1a8ClXI2JWzE7j786thcfqNb26jjhhBO4+uqreeyxx0hKSqr0WN/W57Rp0+jWrRs7d+6kV69enH/++UFf98033+Skk04iOzub/Pz8CvsvueQSADp27EhJSQnJyckkJyfTuHFjiouLy3XbZGdns2LFCvbu3Uvjxo3p2rUry5cvZ+HChWWfBLylp6eXBezs7Gy2bNlCcXExxcXFZW8Uv/nNb5g7d26F53bv3p0RI0ZQWlrKoEGDys7ToEEDrrjiCgCuuuoqhgwZQklJCYsXL2bo0KFlzz906BAA7777brkxk71795YdP3v2bAAGDhxI8+bNg6tQY+JIXAT+VilJFPkJ8q1SKg/Uwbrtttvo2rUr1157baXHrVq1im7dulXYnpqaSteuXVm6dCkdOnTg1VdfrfKaH3zwAXPnzqVNmzYcPHiQvXv3ctVVV/Hiiy8CzvgDOAHV87Pn8Y8//ljuXImJiaSnpzN16lR69epFp06dWLBgAZ999pnf8QPv8yUkJJR19QQjNzeXgoIC5syZw/Dhw7njjju4+uqrKxwnIhw9epSUlBQKCwsr7D969CgffvghTZo0CfraJsQWTYS0rpDu9SlxcwEUrYQ+t0WqVMaPuOjqGTMgg6TEhHLbkhITGDMgo07Of+KJJ3L55ZczZcqUgMfMnDmTefPmMWxYxUwW+/fvZ9WqVbRt25Z+/fpx6NChcrN81qxZU9YV4zF+/Hg+/vhjtmzZwn/+8x/69etXFvRrIicnh4ceeojc3FxycnJ46qmn6NKlS9BzylNSUkhJSWHRImelv2nTpvk97ssvv6Rly5bccMMNXH/99axcuRJwArnnDe+ll16iT58+nHDCCaSnpzNjxgzA+cTk6Ubq378/kyZNKjuv582hV69eZeMoc+fOZc+ePdWsCVNjaV1hxnAn2IPzfcZwZ7uJKnER+Ad1SWP8kI6kpSQhQFpKEuOHdGRQl7Q6u8bvf//7CrN7HnnkkbLpnC+++CLz588nNfXYmghXXnklWVlZZGdnM3z4cLKzsxERXnvtNd59913atm1Lhw4duOuuu/jpT0ObvTonJ4cdO3bQs2dPWrZsSZMmTfwOKFfm3//+N6NGjSIrKyvgoGp+fj6dO3emS5cuvPLKK4wePRqA448/no8++ojMzEzmz5/Pn//8Z8B5A5kyZQqdO3emQ4cOvP766wA89thjLF++nE6dOtG+ffuyQeuxY8dSUFBAhw4dmDVrFraATxil58LQqU6wn3+/833o1PKfAExUCNmau3XJ30IsGzduDMs0xmgW63lpvDVt2pSSkpJan6e+1Eldv77DuuDI/Puh4AHIvRP63R2ea9ZQHCzEskJVK/Qvx0UfvzEmTDYXwPIpTtBfPgXSc0La4p+9qogH397E9uIDtEpJYsyAjDr9JF9fWeA3UaEuWvsmwjx9+p7unfSckHb3eO7P8UzV9tyfA1jwr0IoF2J5VkS+FZF1Xtv+JiJrRKRQROaJSKtQXd8YE2ZFK8sHeU+ff9HKkFwulPfn1HehHNydCvhOTH9QVTupahbwJvDnEF7fGBNOfW6r2LJPzw3ZVM5Q3p9T34Us8KtqAfCdz7a9Xg+PB6J/ZNkYE5UC3YdTV/fn1Gdhn84pIveLyFfAlViL3xhTQ6G+P6c+C+l0ThFpA7ypqhXy84rIXUATVa2YPMbZPxIYCZCampo9ffr0cvubNWvGGWecUedlDtbYsWM55ZRTGDVqFACDBg2idevWPP744wD86U9/olWrVlx88cVcfvnlLF26lIULFzJw4EBeeeUVLrjgAgCGDh3KrbfeSk5ODhdeeCFff/01jRs35vDhw+Tl5XHPPfdUyIrZt29fDh8+zHfffcfBgwdp1coZKnnppZc47bTTgir/TTfdxPnnn8+gQYPIzMzk/fffp0WLFuWOOe+883j33Xf58ssvWbp0KZdffrnfcw0ePJjly5fTo0ePsputwEnNfO211/Ldd9/RpUsXJk+eTKNGjYIqX3WNGzeO3r17k5ubS0JCQtVPgIC/dzh5/x28ffbZZ0HlfwpWSUkJTZs2rbPzRYvF20uZ+Ukpuw8qLZoIl/0skV6tgl+ruL7Wi0ffvn39TudEVUP2BbQB1gXYd2qgfb5fP/vZz9TXhg0bKmwLaOEjql+8X37bF+8722toxowZOnToUFVVPXLkiHbt2lV79OhRtr9Hjx66ZMkS3bx5s3bo0EFVVRcsWKCtW7fWs88+u+y4gQMH6oIFC1RV9ZxzztFly5apquqhQ4f0jjvu0Nzc3IBlePLJJ3XUqFE1Kv8111yjM2bMUFXV0047TXfu3Bnw2AULFujAgQMD7n/33Xf1jTfeqHDM0KFD9eWXX1ZV1RtvvFGfeOKJGpW1Ovbu3Rv0sVX93uHg/XfwVq3XdxA8rzHjeG3lNu01/j097Y9vaq/x7+lrK7dFukghASxXPzE1rF09InKm18NLgY8DHVunQnArea9evViyZAkA69evJzMzk+TkZPbs2cOhQ4fYuHEjXbtWPH/nzp1p1qwZ77zzTqXnb9SoEQ888ABbt26tNNulR2FhIT169KBTp04MHjy4LFVBoO3+HDhwgAsuuIBnnnkGoKwlNHbsWBYuXEhWVpbfFNTnnntuhZumVJX58+fzy1/+EoBrrrmmLHna8OHD+e1vf0uPHj04/fTTyc/PZ8SIEbRr147hw4dXOP+yZcsYMmQIAK+//jpJSUkcPnyYgwcPcvrpp5ed05PyoU2bNtx777107dqVjh07lmVEDSZl85EjRxg+fDiZmZl07Nix7PfNy8tj9OjRZemkP/roI8DJKjpixAjOOussunTpUnZn8ZEjRxgzZgzdu3enU6dOPP3002X1cvPNN5ORkcF5553Ht99+G/DvYULDO0071F2a9lgSyumcLwNLgAwR2SYi1wETRGSdiKwB+gOjQ3X9ckJwK3mrVq1o2LAhW7duZfHixfTs2ZOzzz6bJUuWsHz5cjp27BiwW+Puu+9m3LhxVV4jISGBzp07l0vlHMjVV1/NP/7xD9asWUPHjh3L0hoH2u6rpKSEiy++mGHDhnHDDTeU2zdhwgRycnIoLCzk9ttvr7Is4ATZlJQUGjZ0bhVp3bo1RUXH/rH27NnDkiVLeOSRR7jkkku4/fbbWb9+PWvXrq2QlK1Lly5l2xYuXEhmZibLli1j6dKlnH322X6vf9JJJ7Fy5Up++9vf8tBDDwHwl7/8pcqUzYWFhRQVFbFu3TrWrl1bLvHe/v37KSws5IknnmDEiBEA3H///fTr14+PPvqIBQsWMGbMGPbt28eUKVNo1qwZy5YtY9myZTzzzDNs3ryZ1157jU2bNrFhwwaef/55Fi9eHFR9mrpj00BDeAOXqlbMRgaBs5iFWnoudLvu2K3kdXBDSa9evVi8eDGLFy/mjjvuoKioiMWLF9OsWTN69+4d8Hme1MWehGaV8dcq9fX9999TXFzMOeecAzit66FDhwbc7s+ll17KnXfeWbbwSqhdfPHFiAgdO3akZcuWdOzYEYAOHTqwZcuWsnTN4Cx407ZtWzZu3MhHH33EHXfcQUFBAUeOHAmYT8jzCSE7O5tZs2YBUFBQUPZzoJTNp59+Ol988QW33HILAwcOpH///mX7PAn2cnNz2bt3L8XFxcybN4833nij7M3l4MGDbN26lXnz5rFmzZqyTyHff/89n376KQUFBQwbNoyEhARatWpVtuiNCR+bBhonSdqAireSe7p9aqF3794sXryYtWvXkpmZSY8ePViyZAmLFy+mV69elT43mFb/kSNHWLt2bVhyEvXu3Zu33nqrzlasatGiBcXFxWUpoLdt20Za2rG7KauTNhqcYDt37lwSExM577zzWLRoEYsWLQoY+D3nTEhI8Hu+QJo3b87q1avJy8vjqaeeKre6mW+mUhFBVZk5cyaFhYUUFhaydetW2rVrh6oyadKksu2bN28u9yZiIsemgcZL4Pe+lbzf3ce6fWoZ/Hv16sWbb77JiSeeSEJCAieeeCLFxcUsWbKkysDfv39/9uzZw5o1a/zuLy0t5a677uKUU06hU6dOlZ6rWbNmNG/evCx18wsvvMA555wTcLs/f/3rX2nevHnZLCVvycnJ/PDDD5WWwZeI0Ldv37IW73PPPcell15arXN4y8nJYeLEifTs2ZPU1FR2797Npk2bqrWge25ubpUpm3ft2sXRo0e57LLLGDduXFnaaIBXXnkFcD6pNWvWjGbNmjFgwAAmTZpU9oa5atUqAAYMGMCTTz5JaWkpAJ988gn79u0jNzeXV155hSNHjrBjxw4WLFhQswoxNWbTQOMl8IfoVvKOHTuya9cuevToUW5bs2bNOOmkk6p8/t13381XX31VbptnOcbMzEz27dtXNlhYleeee44xY8bQqVMnCgsLy9IaB9ruz6OPPsqBAwe48847y23v1KlT2XiDv8HdnJwchg4dynvvvUfr1q15++23AfjHP/7Bww8/zBlnnMHu3bu57rrrgvpd/Dn77LP55ptvyrrJOnXqRMeOHYNeLwDg3nvvrTJlc1FREXl5eWRlZXHVVVcxfvz4sn1NmjShS5cu3HTTTWVrL9xzzz2UlpbSqVMnOnTowD333APA9ddfT/v27enatSuZmZnceOON/PjjjwwePJgzzzyT9u3bc/XVV9OzZ88a10ncWzSxYuNtc4GzvRLeadohNGnao56/qT7R9lXr6Zz1VHWmLsaLUNWJ91TbcLDpnEH44n3Vf6Qfm6rt+zgI9bJevBBgOqdl5zTGxCbv2XrdrnPG7mzhl6BY4DcmCP4WtDdRIASz9eJBTPfxawysHmZMddnruhpCMFsvHsRs4G/SpAm7d++2fxJTr6gqu3fvpkmTJpEuSvQL0Wy9eBCzXT2tW7dm27Zt7Ny5M9JFiZiDBw9agPBRH+qkSZMmtG7dOtLFiH6VzdazLp9KxWzgT0xMJD09PdLFiKj8/Hy6dOkS6WJEFauTOOJvgZf0XAv6QYjZrh5jjDE1Y4HfGGPijAV+Y4yJMxb4jTEmzljgN8aYOGOB3xhj4kzIpnOKyLPARcC36i62LiIPAhcDh4HPgWtVtThUZTDGxIbZq4p48O1NbC8+QKuUJMYMyIivbJlhFsoW/1TgfJ9t7wCZqtoJ+AS4K4TXN8bEAO81cJX4XAM33EIW+FW1APjOZ9s8VfUsh/QhYLcnGhPnYmkN3Nmriug9YT7pY+fQe8L8mH1zklDmuhGRNsCbnq4en33/BV5R1RcDPHckMBIgNTU1e/r06SErZ6wqKSmhadOmkS5GVLE68S+a62X4W/sC7pt6/vEhvXZ16mXx9lKmrjvM4aPHtjVqAMMzG9GrVWKISlg7ffv2XaGq3Xy3RyRlg4jcDfwITAt0jKpOBiYDZGRkaF5eXngKF0Py8/OxeinP6sS/aK6XtA/nU+RnofO0lKSQl7k69XL3hPnlgj7A4aMwZ2sCf/p1cOeIFmGf1SMiw3EGfa9US61pTNx7+vRFnJO4sdy2cxI38vTpiyJUIv+2+3lzqmx7NAtr4BeR84E7gUtUdX84r22MiU6Z3fOYnPQ4Fyd/hgAXJ3/G5KTHyeyeF+mildPKXaM32O3RLGSBX0ReBpYAGSKyTUSuAx4HkoF3RKRQRJ4K1fWNMTEiPZfGw55nUuKjbO5fyKTER2k87Pmoy7I5ZkAGSYkJ5bYlJSYwZkBGhEpUcyHr41fVYX42TwnV9YwxMSwGllD03FdQH+43iNl8/MaYesR3CcX0nKgN/rEY6H1ZygZjTGTZEophZ4HfGBNZlS2haELCunqMMZFlSyiGnbX4jTEmzljgN8aYOGOB3xhj4owFfmOMiTMW+I0xJs5Y4DfGmGAsmljx3oLNBc72GGOB3xhjgpHWtfyNZZ4bz9K6RrJUNWLz+I0xJhieG8tmDHfyCi2fUv7GsxhiLX5jjAmWdzK5btfFZNAHC/zGGBM832RyMZpPyAK/McYEox4lkwvlQizPisi3IrLOa9tQEVkvIkdFpMICwMYYE7VqkUxu9qoiek+YT/rYOfSeMJ/Zq4pCWtSqhHJwdyrOilvPe21bBwwBng7hdY0xpu7VMJnc7FVF3DVrLQdKjwBQVHyAu2atBYhYbv+QtfhVtQD4zmfbRlXdFKprGmNMtHnw7U1lQd/jQOkRHnw7cqEwaqdzishIYCRAamoq+fn5kS1QFCopKbF68WF14p/Vi3/hqJei4gMBt0fqbxK1gV9VJwOTATIyMjQvLy+yBYpC+fn5WL2UZ3Xin9WLf+Gol7QP5/sN/mkpSRH7m9isHmOMCaExAzJISkwoty0pMYExAzIiVCIL/MYYE1KD9s3gmZz9pKUkITgt/Wdy9jNo34yIlSmU0zlfBpYAGSKyTUSuE5HBIrIN6AnMEZG3Q3V9Y4yJCmld6VP4Bz64oiGbJwzkgysa0qfwDxHN8ROyPn5VHRZg12uhuqYxxkSdKMzxY109xhgTalGW48cCvzGmvHqUdz5qRFmOnyoDv4j8xO2bHyUiI0TkLBGxNwxj6qt6lHc+KkRhjp+Affwi0hcYC5wIrAK+BZoAg4C2IvIq8H+qujcM5TTGhEsU9knHtMpy/ESoTisb3L0QuEFVt/ruEJGGwEXAL4CZISqbMSZSvPukc++0oF8bNczxE0oBA7+qjqlk34/A7FAUyBgTBXz7pNNzLPhHwOxVRTz49ia2Fx+gVUoSYwZk1Elit2D6+EeLyAnimCIiK0Wkf62vbIyJTlHYJx2PPFk9i4oPoBzL6lkXKZ2DGaQd4fbj9weaA78BJtT6ysaY6FSLvPOm7oQyq2cwN3CJ+/1C4AVVXS8iUtkTjDExLAr7pOPR9gBZPQNtr45gWvwrRGQeTuB/W0SSgaO1vrIxxpiAWqUkVWt7dQQM/CKS6P54Hc60zu6quh9oBFxb6ysbY4wJKJRZPSvr6lniJlR7C3hLVYsBVHU3sLvWVzbGGBOQZ/ZOKGb1VDads5uItAHOByaKSBqwCJgLvK+qh2p9dWOMMQEN6pIWknV5Kx3cVdUtwFPAU27XTw7OG8E4EdmpqgPrvETGmJgVqnnnpm4FnZZZVUuB+e4X7icAY4wBjs0790xB9Mw7Byz4R5lgbuC6SERWicgeEdkrIj+IyF5VrfQuAhF5VkS+FZF1XttOFJF3RORT93vzuvgljDGRF8p556ZuBTOdcyJwDXCiqp6gqsmqekIQz5uK0y3kbSzwnqqeCbznPjbG1AOhnHdu6lYwgf8rYJ2qanVOrKoFwHc+my8FnnN/fg4n06cxph4I5bxzU7ekqnguIt2BvwHvA2UzeVT14SpP7swKelNVM93Hxaqa4v4swB7PYz/PHQmMBEhNTc2ePn161b9NnCkpKaFp06aRLkZUsTrxLxz1snh7KVPXHeaw1+2djRrA8MxG9GqVGPiJEVTfXy99+/ZdoardfLcHM7h7P1CCk4u/UV0VSFVVRAK+66jqZGAyQEZGhubl5dXVpeuN/Px8rF7KszrxLxz1kge0j7FZPfH6egkm8LfytNjrwDcicrKq7hCRk3EWdzHG1BOhmndu6lYwffz/q8M0zG/gDBTjfn+9js5rjDEmSMEE/t8Cb4nIAe/pnFU9SUReBpYAGSKyTUSuw0nn/AsR+RQ4D0vvbIwxYVdlV4+qJtfkxKo6LMCuc2tyPmOMMXWjsuycbSp7orsiV+s6L5ExxpiQqqzF/6CINMDph18B7MSZ2XMG0Ben5X4vsC3UhTTGGFN3KsvOOVRE2gNXAiOAk4H9wEbgf8D9qnowLKU0xhhTZ6rKzrkBuDtMZTHGGBMGwczqMcYYU49Y4Demvlo0ETYXlN+2ucDZbuKaBX5j6qu0rjBj+LHgv7nAeZzWNZKlMlEgYB+/iFT66lDVlXVfHGNMnUnPhaFTYcZw2qSeCx+95zxOz410yUyEVTa4+3/u9yZAN2A1IEAnYDnQM7RFM8Z41HhJw/Rc6HYdbQoegNw7LegboJKuHlXtq6p9gR1AV1XtpqrZQBeg0tW3jDF1x7OkYVHxAZRjSxrOXhXEv+HmAlg+hS2nXQ7Lp1Ts8zdxKZg+/gxVXet5oKrrgHahK5IxxluNlzT09OkPncqW9CvLun0s+MeIEA7OBxP414jIv0Qkz/16BlhT6ysbY4JS4yUNi1aW79P39PkX2fBcTAjh4Hww+fivxcnQOdp9XAA8WesrG2OC0ioliSI/Qb7KJQ373FZxW3qu9fPHCq/Bebpd53TV1dHgfJUtfjctw1PAWFUdrKqPWKoGY8JnzIAMkhITym1LSkxgzICMCJXIhI07OE/BA873OnrTrjLwi8glQCHwlvs4S0TeqJOrG2OqNKhLGuOHdCQtJQkB0lKSGD+ko610FQ/cwXly76zTwflgunruBc4C8gFUtVBE0mtzUREZDdyAMz30GVWdWJvzGVPf2ZKGcchrcN7possp/7gWghncLVXV7322BVwkvSoikokT9M8COgMXicgZNT2fMcbUSyEcnA8m8K8XkV8DCSJypohMAhbX4prtgKWqul9VfwTeB4bU4nzG1G+Wcyc+9bmtYss+Pdf/oH01iWrljXcROQ4nNbNnwfW3gXE1HeAVkXY4i7v0BA4A7wHLVfUWn+NGAiMBUlNTs6dPn16Ty9VrJSUlNG3aNNLFiCr1sU5S9qyh/YYH2dB+DMXNO1V4HIz6WC91ob7XS9++fVeoajff7VUG/rIDRY5T1f11URh34fXfAfuA9cAhVb0t0PEZGRm6aVMVN6vEofz8fPLy8iJdjKgS1XWyaKIzB9u7Fbe5wPnoXlUrztPfW8NpfVFdLxFU3+tFRPwG/mBm9fQSkQ3Ax+7jziLyRG0Ko6pTVDVbVXOBPcAntTmfMTGhNjfkhGhan4lPwfTxPwIMAHYDqOpqoFavOhH5ifv9VJz+/Zdqcz5jYoL3DTnz76/eDI0QTesz8SmY6Zyo6lci4r3pSKBjgzRTRFoApcAoVS2u5flMnPNkrywqPkDah/ODz14ZZrOL27LnUD+uLXiAfycMpXlxWwZV9aQQTusLWM6aZgM1MSGYwP+ViPQCVEQScVI3bKzNRVU1pzbPN8abJ3ulJ5GZJ3slEFXBavaqIl6b9TIPN3iLR48M5ip9iztm/RwYVnk5K5vWF4LAHyv1aWoumK6em4BRQBqwHchyHxsTFWqcvTLM3vvfqzzcYCI3l97KIz8O5ebSW3m4wUTe+9+rlT8xhNP6/ImV+jQ1V2WLX1V3AVeGoSzG1EiNs1eGWdr+jdyst7LkaAcAlhztwM2lt9L5x1p9gK5zsVKfpuaCmdVzuoj8V0R2isi3IvK6iJwejsIZE4xAWSqrzF4ZZv9Nvrws6HssOdqB/yZfHqES+Rcr9WlqLpiunpeA6cDJQCtgBvByKAtl4tvsVUX0njCf9LFz6D1hfpUrTUUie2V1ywiRLefwt/ZFdTlNeAUzuHucqr7g9fhFERkTqgKZ+FaTgUXP9rJZPSGehVLTwU/vcoZjtkyslNOEXzCBf66IjAX+g5Oc7QrgfyJyIoCqfhfC8pk4U9nAYlXBalCXtLDciVnTMkJ4s2zGSjlN+AUT+D0dkDf6bP8VzhuB9febOhPWgcUaplC4+IfprG5wern++p4N1tP5hy+AfnVfzhqyQVoTSDArcKVX8mVB39SpsA4s1jCFQtFx7Xg88TF6NlgPOEH/8cTHKDquXd2XsRZskNYEEjDwi0h3Efmp1+Or3Rk9j3m6eYypa2EdWKxhCoVzL/wldxy9jccTH+P2hjN4PPEx7jh6G+de+Mu6L2Mt2CCtCaSyFv/TwGEAEckFJgDPA98Dk0NfNBOPwr7MYA2Snw3qksbgIcN4o+H5jG74Gm80PJ/BQ6q4+zYCvOsSbMlGc0xlffwJXgO3VwCTVXUmTp6dwpCXzMStsA4s+iY/S88JLvinfA6N50O3O7l2+RRIuRrn5vboEs5BbxM7KmvxJ4iI543hXGC+176gkrsZE9W8k5/1u/tYt09VmS9r+jxjokRlgf9l4H0ReR1npayFAO76uL5r8BoTe2q6pmkI10I1JhwCttxV9X4ReQ/njt15emyprgbALYGeZ0zM6HObk354wvzyNyr1qaKrx99Uz/RcWxzFxIxKu2xU9UM/22y1LFMvWPphE6+CydVT50TkdhFZLyLrRORlEWkSiXKY+Gbph028CnvgF5E04Fagm6pmAgk4dwEbE1Z2Z6uJVxFp8eN0MSW5s4aOw1ngxZiwsjtbTbySY2O2YbyoyGjgfpzZQvNUtcJCLyIyEhgJkJqamj19+vTwFjIGlJSU0LRp00gXI6pUp04Wby9l6rrDHD56bFujBjA8sxG9WiWGqISRYa8V/+p7vfTt23eFqnbz3R72wC8izYGZODeFFePk939VVV8M9JyMjAzdtMn6XX3ZTTkVVbdO4mVRcXut+Fff60VE/Ab+SNyIdR6wWVV3AojILKAXEDDwGxMqln7YxKNI9PFvBXqIyHEiIjh3BUfXoqPGGFOPhT3wq+pS4FVgJbDWLYMlfTPGmDCJSM4dVb0XuDcS1zbGmHgXqemcxhhjIsQCvzHGxBkL/MYYE2cs8BtjTJyxwG+MMXHGAr8xxsQZW0LRhEy8pEMwJtZY4DchYYucGBO9rKvHhIQtcmJM9LLAb0LCFjkxJnpZ4DchYYucGBO9LPCbkBgzIIOkxIRy25ISExgzICNCJTLGeNjgrgkJzwCuzeoxJvpY4DchY4ucGBOdrKvHGGPiTNgDv4hkiEih19deEbkt3OUwxph4FYkVuDapapaqZgHZwH7gtXCXw9QjiybC5oLy2zYXONuNMRVEuqvnXOBzVf0ywuUwsSytK8wYfiz4by5wHqd1jWSpjIlaoqqRu7jIs8BKVX3cz76RwEiA1NTU7OnTp4e7eFGvpKSEpk2bhvw6i7eXMvOTUnYfVFo0ES77WSK9WiWG/LrVkbJnDe03PMiWk86lza732NB+DMXNO0W6WFEjXK+VWFPf66Vv374rVLWb7/aIBX4RaQRsBzqo6jeVHZuRkaGbNtmt/r7y8/PJy8sL6TV8c+6AMx9//JCO0TdjZ/79UPAA5N4J/e6OdGmiSjheK7GovteLiPgN/JHs6rkAp7VfadA3kRUzOXc2F8DyKWw57XJYPqVin78xpkwkA/8w4OUIXt8EISZy7nj69IdOZUv6lTB0avk+f2NMOREJ/CJyPPALYFYkrm+CFxM5d4pWOsE+Pdd5nJ7rPC5aGclSGRO1IhL4VXWfqrZQ1e8jcX0TvJjIudPntmNB3yM919lujKnAUjaYSlnOHWPqn5gI/Fv2HqX3hPkWcCLEcu4YU79E+gauoHmW7pu9qijSRTHGmJgWM4EfonQaoTHGxJiYCvwQZdMIjTEmBsVc4I+qaYTGGBODYirwR900QmOMiUExMasHIM2mERpjTJ2IicDf5oQGfDC2X6SLYYwx9UJMdfUYY4ypPQv8JrrYalrGhFy9DPyzVxXRe8J80sfOofeE+XbTVyyx1bSMCbmY6OOvDt+FQzx3/AI2MBwLPJk1ZwyHbtc5ufW9M28aY2qt3rX4Y2bhEBNYeq4T9AsecL5b0DemTtW7wB8TC4eYyrmraZF7p62mZUwIRGohlhQReVVEPhaRjSLSs67OHRMLh5jAvFbTot/dtpqWMSEQqRb/o8BbqvpzoDOwsa5OHBMLh5jAbDUtY0Iu7IO7ItIMyAWGA6jqYeBwXZ3fFg6Jcf5WzUrPtX5+Y+pQJGb1pAM7gX+LSGdgBTBaVffV1QVs4RBjjAlMVDW8FxTpBnwI9FbVpSLyKLBXVe/xOW4kMBIgNTU1e/r06WEtZywoKSmhadOmkS5GVLE68c/qxb/6Xi99+/ZdoardfLdHIvD/FPhQVdu4j3OAsao6MNBzMjIydNOm0E/HnL2qKKa6iPLz88nLy4t0MaKK1Yl/Vi/+1fd6ERG/gT/sg7uq+jXwlYh4RlvPBTaEuxy+PDd+FRUfQLGlHo0x9VekZvXcAkwTkTVAFvD3CJWjjN34ZYyJFxFJ2aCqhUCFjx+RZDd+GWPiRb27c7em7MYvY0y8sMDvqs2NX5YN1BgTS+pdds6aqumNX5YN1BgTayzwe6nJjV+VDQpb4DfGRCPr6qklGxQ2xsQaC/y1ZIPCxphYY4G/lmxQ2BgTa6yPv5ZsUNgYE2ss8NfWookMSuvKoLH9jm3bXACLZvhPMeyyQWFjTKRYV09tpXUtv0KUZwWptK6VPq02g8KeLqLhb+2rVheRdS0ZY8Ba/LXnWSFqxnBnYfDlU8qvIBVAq5QkivwE+aoGhWvaRWRdS8YYD2vx14X0XCfoFzzgfA9itaiaDgrXNJmcJaEzxnhY4K8Lmwucln7unc73IBYGH9QljfFDOpKWkoQAaSlJjB/SscrWd027iOx+A2OMh3X1eCya6PTLe7fWNxc4i3xXMkhb1qfv6d5Jzyn/uBI1uVO4pl1ENX2eMab+sRa/Rw0HaSlaWT7Ie/r8i1aGpJg17SKqzf0Gxpj6xVr8HjUcpPX7aSA9N6h+/prwvm+gqPgAaUHeN1DT+w2MMfVPRAK/iGwBfgCOAD/6WxMyIrwHaXPvDFnwri1PF1F11wutSdeSMab+iWRXT19VzYqaoA81GqQ1xphYY338Ht6DtP3uPtbtY8HfGFPPiKqG/6Iim4E9gAJPq+pkP8eMBEa6DzOBdaEsU6tkabnvsO7//hA/eLY1a0zy8Y3kuO0/6DehvHYtnATsinQhoozViX9WL/7V93o5TVVTfTdGKvCnqWqRiPwEeAe4RVUDNq1FZHlUdQlFCauXiqxO/LN68S9e6yUiXT2qWuR+/xZ4DTgrEuUwxph4FPbALyLHi0iy52egPyHuxjHGGHNMJKZztgReExHP9V9S1beqeE6FMQADWL34Y3Xin9WLf3FZLxHp4zfGGBM5Np3TGGPijAV+Y4yJM1Ed+EXkfBHZJCKficjYSJcnWojIFhFZKyKFIrI80uWJFBF5VkS+FZF1XttOFJF3RORT93vzSJYxEgLUy30iUuS+ZgpF5MJIljHcROQUEVkgIhtEZL2IjHa3x+XrJWoDv4gkAP8ELgDaA8NEpH1kSxVVoi/lRfhNBc732TYWeE9VzwTecx/Hm6lUrBeAR9zXTJaq/i/MZYq0H4Hfq2p7oAcwyo0ncfl6idrAjzO3/zNV/UJVDwP/AS6NcJlMFHFv+vvOZ/OlwHPuz88Bg8JZpmgQoF7imqruUNWV7s8/ABuBNOL09RLNgT8N+Mrr8TZ3m3FSXcwTkRVuagtzTEtV3eH+/DXO9GHjuFlE1rhdQXHRpeGPiLQBugBLidPXSzQHfhNYH1XtitMNNkpEojN/dISpM1fZ5is7ngTaAlnADuD/IlqaCBGRpsBM4DZV3eu9L55eL9Ec+IuAU7wet3a3xT1LeVGpb0TkZAD3+7cRLk9UUNVvVPWIqh4FniEOXzMikogT9Kep6ix3c1y+XqI58C8DzhSRdBFpBPwKeCPCZYo4S3lRpTeAa9yfrwFej2BZooYnuLkGE2evGXFSBUwBNqrqw1674vL1EtV37rpTziYCCcCzqnp/ZEsUeSJyOk4rH46lvIjLehGRl4E8nNS63wD3ArOB6cCpwJfA5aoaVwOdAeolD6ebR4EtwI1efdv1noj0ARYCa4Gj7uY/4fTzx93rJaoDvzHGmLoXzV09xhhjQsACvzHGxBkL/MYYE2cs8BtjTJyxwG+MMXHGAr+JWSLSwivb5Nde2SdLROSJEF/7PhH5g8+2LSLSMkCZCkWkkYj8QUQ+dh8vE5GrA5x/oueObPe8J/k55iIR+WtofkNTn0Vi6UVj6oSq7saZm46I3AeUqOpDkSwTcERVs6BimUTkJuAXwFmquldETsC5maocEWkB9FDV26q41hzgbyIyQVX3192vYOo7a/GbekdE8kTkTffn+0TkORFZKCJfisgQEXnAXc/gLfc2fkQkW0TedxPfve1zp2td+RPwW0+OGFXdq6rP+TnuMsB3HepbRGSlW+6fu89XIB+4KARlNfWYBX4TD9oC/YBLgBeBBaraETgADHSD/yTgl6qaDTwL1Ond0G7rPllVvwji8N7ACp9tu9zEfE8C3l1My4GcuimliRfW1WPiwVxVLRWRtTjpPzyt6bVAGyADyATecVK6kICTwbIygW55r4tb4U8Gdvps8yQVWwEM8dr+LdCqDq5p4ogFfhMPDgGo6lERKdVjeUqO4vwPCLBeVXtW45y7cQK0t2Sg2N/Bbp9+iYicHkSr/wDQxN/vAByh/P9tE/d4Y4JmXT3GwCYgVUR6gpO+V0Q6uD/fLCI3+3lOAXCJV6bUIcBqVT1SyXXGA/90u30QkaYBZvVsBM4Isuw/I84ybZras8Bv4p67tOcvgX+IyGqgEOjl7v45Tuve9zlrgMeBRSJSCNwEXF/FpZ4EFgDL3IXQF3IsU6S3OTjZNIPR1z3emKBZdk5jKuHODhrivjmE87qLgItUtbiSY1ripOU+N2wFM/WCBX5jopCInA0ccD9ZBDqmO1CqqoVhK5ipFyzwG2NMnLE+fmOMiTMW+I0xJs5Y4DfGmDhjgd8YY+KMBX5jjIkz/x8aLsf2y2aPzQAAAABJRU5ErkJggg==",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -961,7 +961,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 864x576 with 1 Axes>"
       ]
@@ -992,7 +992,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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M67JYLGi1WpKXl8dzc3PTCAQCisvl4uzZs/kLFixo/uWXX+ySkpJ8hnKMK8GIJgZaIYQIHRwc/iKRSNTTp08/sHXr1inFxcWW7733HlepVNJtHsM4RiwW46WXXuLk5uZafvXVVyELFixIdnd3b3Bzc3vrUsgNAEBRVCdFUY4URbX2eayRoqipFEX5UBR1u1EMURSVQVHUw32220lRlPel2+d9j09R1BqKolIu/d5DUdQdFEUFUhS1ZcRPnsHsEQqFhtjY2PaHH35Ycc899zQBQFJSUmdGRoZ1Tk4OHwDa2tpY2dnZ/L77JSQkdKanp9vU1NRwdDodvvvuO4ekpKSOpKSkzpMnT9oUFBTwAODy8BwAWFtb69va2ky6wNLSkkpMTGxdu3atbMWKFQ1XsvWrr76yB4D9+/db29jY6B0dHYc0U/L8+fM8iUSife655xoeeOCB+tOnT193hdxg7N27V3jHHXe0AUBrayurqamJvXjx4tbt27dXFBQU3NQxmPAcAy0QQkLkcvk/FArFlCVLlvCeeeYZrpub27V3ZGAYAWJiYvDNN98IWltbBTt27Fi7c+fOJz08PM6pVKp1AI4yXcgZ6GDJkiVNDzzwgNdXX311AQDc3d11n3zyiWrJkiWeGo2GAMBLL71UFRIS0mvcRy6Xa1966aWqxMREX4qiyO23395y3333tQDARx99pLrnnnu8DQYDHB0dtcePHy/qe7xly5Y1PfHEE4rt27eLkpOTSwIDA3sfeOCBpt9//91+3rx5bbgCAoGA8vf3D9DpdGTHjh2lQz2//fv323z00UeuHA6HsrS01O/evXvI+16NAwcOCD/++ONyAGhpaWHffffd3r29vQQAXnvttYqr7311mI7gDKMGIYTD5XLnubm5vSkWi13XrFljOW/ePLDZN5WXx9CH8dYRnE4OHjyIt99+uzsnJ6etvb39tba2ts8piuqi2y6G8UdWVpYqNDT0ip4cOtm4caOotbWV/eGHH9LSEkMsFgdnZGTkD7XlQHd3N5kwYYIyJydn0Pyrvnz00UeOGRkZVv/5z3/K+z6elZXlFBoaqhhsHyY8xzDiEEKsXVxc/i4Wixvuvffe//z666+ex48ft1y4cCEjmBjMlqlTp+L333+3OHHihGjFihXvSSQStVgs3koIcb723gwMY59p06Z5ff31144vvPDCoMNrRwN7e3tdUlKS71CbW1pYWFBDEUyvvPKKy3vvvedma2s7pFCiEcbTxDBiEEIc3NzcNnA4nIeXLl3Kf+GFF7h2dnZ0mzWuYTxNI0dPTw/++c9/6rdt29ar0+l+qqio+CtFUeXX3pOB4eqYs6fpVoTxNDGMKoQQsVQq3aVQKMqfeeaZpwoKCqw3bdrECCaGMY1AIMBf/vIXdlFRkeXGjRsXKZXKfIVCsZ8QwlQsMDDcIjCiiWHYIIR4KxSKn319fc//7W9/u6+oqMjqhRde4FhaDktBBAODWcBms/Hwww+zcnNzLd9+++07wsLCTisUinRCSBTdtjEwMIwsjGhiuGkIISEKhSI1JCQk+4033piZn59vuWrVKhaHwxRnMoxfWCwWFi5ciDNnzljs2LEjetKkSUfkcnk+ISSJbtsYGBhGBkY0MdwwhBBPuVz+Z0RERNrWrVsnZWVlWSxdupSwWMzbiuHW4o477kBqaqrFt99+q5w6depvcrk8hxASQbddDAwMwwtzdWO4bgghIplM9o1Sqcx55513kjIzMy1mzpxJt1kMDLQzceJE/O9//xN88cUXgdHR0alyufwoIcSbbrsYGIaD5ORkW4VCESSTyYJefPFF18uf7+7uJjNnzvSUyWRBISEhysLCQt5g6+zcudPe29s7kMViRV6tKu5ax6MDJn7CMGQIIbZubm6vKRSKh9atWyd49NFH2UzLAAaGgUyePBnp6ekWP/zww6T169dny2SyXysqKp4awow7BoZrMo21MHI41ztg+C7zWtvodDqsWbNGtn///vOenp7a0NBQ//nz57dERkb2GLf58MMPnYRCoa68vDxnx44d9mvXrpXs27fvwuVrhYWFdX///ffFjzzyiOJmjkcHjKeJ4ZoQQvguLi4vSiSSyieeeGJVQUGB1RNPPMEIJgaGa3DPPfeQnJwci7///e/3eHh4lFzq8ySk2y4GhuslJSXFSi6X9wYEBGgEAgE1b968puTkZLu+2/zyyy92K1eubASABx98sPn48eM2BoNhwFoRERE9oaGhvQOeuM7j0QEjmhiuCCGEZWtru1IsFtcsXbr0pZycHJsNGzZw+Hz+tXdmYGAAcDFh/NFHH2UVFBRYPvXUU49KpdJKkUi0kRDC/CMxjBkqKip4YrFYY7wvkUg0VVVV/cJvarWa5+HhoQEALpcLa2trvVqtvqGI1lCORweMaGIYFEJIpEQiuTBr1qxtp06dsv/ggw94QiHzBZmB4Ubh8Xj429/+xsnJybFetmzZ38VicRWXy72TbrsYGBiGDiOaGPpBCHGQSqXfh4eHH01OTpbv3r2bzwzSZWAYPmxtbfHee+9xDx065JiYmLhHJpOlEULkdNvFwHA1pFJpP09PZWVlP08QAIhEIk1paSkPALRaLTo6OtgikUi3YMEChVKpDEhMTBxyUcRQjkcHTCI4A4CLoTh7e/snpFLpm+vWrbNctWoVm2kdQC8GgwF6vR46nQ5ardb0u/FmMBhgHINEURSqqqrQ29sLlUoFACCEgMVigc1mg8PhDHpj/sb04ePjg//973+C77//PnrdunV5bm5uW2trazdQFHXVXA8GBjpITEzsVKlUgoKCAp5CodDu2bPHYffu3f2SvGfOnNmyc+dOx9tvv73z888/t4+NjW1nsVhITk5WjcTx6IARTQwghESJxeLvp06dKnr//ff5Dg4OdJs0bjEYDOjt7UVPT0+/m/Gx3t5ekxAihAwqdIwiiMVigRBiEkdcLheEEAAXRRRFUf1E1uU3vV6PvkmafD4ffD4fAoFgwI3P5zPDlUeI+fPnk5kzZ1pu2LDh2a+++moll8t9QKvV/kq3XQwMfeFyuXj33XfLZ8yY4avX67F06dKGqKionmeffdZ9woQJncuWLWtdvXp1w/z58z1kMlmQUCjUf/PNNyWDrfWf//zH7vnnn5c1Nzdz7rnnHh9/f/+u1NTUIpVKxV2+fLn88OHDxVc63mif9+UwA3tvYQghjhKJ5F/Ozs4ztm/fbhEdHU23SeMCiqLQ09ODjo4OdHR0oLOzEx0dHejp6QEhxCRCLhclxp834/250YG9FEWht7f3qoJOr9eDz+fD2toaVlZWsLa2hrW1NSwtLU1ijeHmKCoqwhNPPNFz/vz5cxUVFYsoilLRbRPDyMMM7DUvrjawl/E03YIQQohQKFwhlUo/ZEJxN4dGo0FraytaWlrQ2tqKzs5OUBQFgUBgEhUikQheXl4QCARmKy6MYk4gEOBKCf8URUGj0ZjEYGNjI8rKytDV1QUAsLCwgJ2dHYRCIezs7CAQCEbzFMYFxpDdnj17op5//vlcNze392pra1+mKEpPt20MDAyMaLrlIIS4SiSSvREREaGfffYZ38nJiW6TxgwajQYtLS0mgdTR0QEul2sSCSKRCNbW1uM2T4gQYgrhOTo69nuOoih0dXWhtbUVTU1NuHDhAnp7e2FpaWl6fYRCISwsLGiyfmwxb948ctddd1k+++yz63755ZdlhJC7KIoqoNsuBoZbHUY03SIQQoiNjc1ymUy2ZdOmTZb33nvv+LyyDyPd3d1oaGhAQ0MDWltb+wkkNzc3WFtbm63naLQhhMDKygpWVlZwd3cHcFFIdXd3o6WlBU1NTSgtLUVPTw9sbGzg5OQEJycnWFlZjfpr2NLSgocffhg5OTkghGDnzp3w8/PD4sWLoVKpoFAo8O2338Le3n7Avrt27cLrr78OAPj73/+O5cuXo7e3F3PmzEFlZSVWrVqFVatWAQAeffRRPP7444iIuLERdAKBANu3b+elpKR4PPLII6ddXV3fVqvVrzJeJwYG+mBymm4BCCGuUqn0x9DQ0NDPP/9cwHiXBqevSGppaYFAIICTkxMcHR1hZ2c3JjxIN5rTNFpQFIX29nbT69zZ2TnqImr58uVISEjAww8/DI1Gg66uLrzxxhtwcHDACy+8gE2bNqG5uRmbN2/ut19TUxOioqKQkZEBQggiIyORmZmJo0ePIjs7Gy+++CImTZqEEydOICsrCx999BE+++yzYbG5q6sLzz77rObXX3+tqqqqupOiqMJhWZjBLGBymswLJqfpFoUQQmxtbe+XyWRb33zzTculS5ea/1V/FNHr9aivr4darUZTU5NJJMnlcoSGho4JkTTWIITA1tYWtra28PT0BEVRaGtrQ0NDA/Ly8tDZ2QlbW1u4urrCxcUFXC53WI/f2tqKI0eO4N///jeAiw0neTwe9u7di5SUFAAXRVVSUtIA0bR//35MmzYNxurSadOm4ffff4ednR26urqg1WpNlY8bNmzA9u3bh81uS0tL7Nixg/fnn396PPbYY2dcXV3fUqvVrzFeJwaG0YURTeMUQohIIpH8GBYWFrZz506Bs7Mz3SaZBT09PVCr1aitrUV3dzecnJwgFosRHBzMiCQaIIRAKBRCKBTCy8sLFEWhtbUVtbW1KC4uBpfLhUgkgqurK6ysrG76eKWlpXB2dsaDDz6IrKwsREZG4sMPP4RarYaxiaurqyvUavWAfauqqiCVSk33JRIJqqqqsHDhQnzxxReIiYnB888/j59++gkRERGmMOVwcttttyErK8ti9erVL/z222/3E0LupCjq/LAfiIGBYVCYq8Q4xNLScq5UKi3atGlT9M8//3xLCyajJ+P8+fM4evQoMjIyoNFoEBAQgKSkJAQFBcHJyYkRTGYCIQR2dnZQKpVITExEeHg4WCwWsrOzcfjwYeTl5aGpqQk3mlag0+lw+vRpPPHEEzhz5gysrKywadOmATZcT4iQw+Hgyy+/xJkzZ7Bw4UJ88MEHeO6557B27VosWLAAP/300w3ZeiUsLS3xr3/9i/+f//zH08vL64yLi8tawiTXMYwwCxcuVDg4OIT6+PgEDva8wWDAihUrpDKZLMjX1zcgNTXVcrDtXn75ZZGXl1egr69vQGxsrO/58+cHnSd39OhRS19f3wCZTBa0YsUK6WCDf+mA8TSNIwghPIlE8ml4ePjCb7/9ViAWi+k2iTY6OztRWVmJmpoaWFpawtXVFdHR0WCGDY8tLCws4OHhAQ8PD2i1WtTX10OlUiErKwsuLi6QSqWwtbUd8noSiQQSiQQTJ04EACxYsACbNm2CSCRCTU0N3NzcUFNTAxcXlwH7isViUwgPACorKwfkj23btg0PPPAA0tLSIBQK8c033+C2227D7Nmzb+j8r8Ztt92Gs2fPWi5fvvyNkydP3kMIuZuiqNZhPxCD2XGn5JnI4Vzvt8qPMq+1zcqVKxtWr15d9+CDD3oM9vx3330nvHDhgkClUuUcOnTIatWqVbLs7OwBFZ+RkZFdzz33XL6NjY1h8+bNzmvWrJHs27dvQKfvVatWyT/++OOyKVOmdCYlJfkkJyfbLlq0qO3GznD4YL5ejxMIIZ5isbjovvvuW3z06NFbUjBpNBqUlpYiNTUVWVlZsLCwwKRJkxAdHQ2ZTMYIpjEOl8uFu7s7IiIiMHnyZNjb26OgoACHDx9GUVERuru7r7mGq6srpFIpCgsv5lEfPHgQAQEBmD17Nnbt2gXgYoXcnDlzBuw7ffp0/PHHH2hubkZzczP++OMPTJ8+3fR8c3MzfvnlFzzwwAPo6uoydWwfil03irW1Nb7//nv+iy++GCsWiy8QQiaM2MEYbmnuvPPODmdnZ92Vnt+7d6/dsmXLGlksFqZOndrZ1tbGKSsrG5CUOGvWrHYbGxsDAMTHx3fU1NQM8DSVlZVxOzo6WFOnTu1ksVhYtmxZ448//jiwnJUGGE/TOMDOzm6ZXC7/5NNPP7W6/fbb6TZnVNHr9aitrUVlZSV6e3vh7u6OyMhIph/QOIfNZsPd3R3u7u7QaDSoqanB6dOnAVz0Jrm7u18xiXzLli1YtmwZNBoNPD098fnnn8NgMGDRokX47LPPIJfL8e233wIAMjIysH37dnz66adwcHDAhg0bMGHCRV2yceNG9B059Oqrr2L9+vVgsViYPn06tm7diuDgYDz++OMj/GoATzzxBDs+Pt5h8eLFh11dXd9Uq9WvU0xpNMMoUlNTw1UoFKaBum5ubpqysjKuXC7XXmmfTz75xPn2228f4B0tKyvjurm5mfaTy+Wampqa4a0KuUEY0TSGIYQIJBLJf8PDw+/+9ttv+bdS7lJbWxtUKhUaGxshEong7+9/XWEahvEDj8eDXC6HXC5HV1cXqqqqcOzYMdjY2EChUMDBwaFfjlJYWBgyMjIGrHPw4MEBj0VFReHTTz813V+5ciVWrlw5qB3vv/++6XeBQIA//vjjZk7rugkODkZGRobFI488sv7IkSOzCSEzKIpqHFUjGBiGyLZt2xyysrIsP/nkkzHVPoMRTWMUQohSLBYffPTRR53Xr1/PvRUSmfV6Paqrq1FWVgYulwuFQoHg4GCmwSSDCUtLS/j4+MDb2xvNzc1QqVQ4d+4cZDIZpFLpsLcwMDcsLS2xe/du/r///e+Iv//978VsNnuWXq9PpdsuhvGPm5ubVqVSmUJtNTU1PLlcrn366afFBw4cEAJAQUFBHgD8+OOPNu+8847b0aNHCy0sLAZ4ROVyubavZ6msrIzX1/NEJ+P/SjsOcXR0XOnp6Zn59ddfu2/YsGHcC6auri7k5eXhyJEj6OzsRGRkJCZOnAiRSMQIJoZBIYTAwcEBERERiIuLA0VROHbsGLKystDWRnsu6YizYsUK1sGDB+0CAwMPuLu7b2Kq6xhGmtmzZ7fs3r3b0WAw4ODBg1Y2NjZ6uVyu3bJlS1VBQUGeUTAdO3bM4umnn5bv3bu3WCwWD5ojJZfLtdbW1oaDBw9aGQwG7N6923HOnDkto3pCV4DxNI0hCCFsiUSyIzg4eNmePXv4ffMpxiONjY0oKSmBRqOBQqGAUqlkWgMwXDc8Hg9eXl7w9PREXV0d8vLyoNfr4enpCVdX13ErvP38/JCRkSFYuXLlsykpKbGXejp10W0Xw9hk1qxZHmlpaTbNzc0ckUgU8sILL1RrtVoCAOvWratftGhR6759+4RyuTzIwsLC8Omnn6oGW+f555+XdnV1sRcuXOgFAO7u7po///yzGACUSmWAUVxt3bq17KGHHvLo6ekhU6ZMaVu4cKFZVIYyY1TGCIQQoVgsPjRnzpyAjz76iM9ms+k2aUSgKAp1dXUoKiqCQCCAt7c37Ozs6DZrzGDuY1TMhY6ODly4cAHNzc3w9PSEWCwe14L87bff1n3wwQe11dXVcRRFVdBtD0N/mDEq5gUzRmWMQwjxEYvFRzdu3Oj06KOPjku1RFEUqqqqUFJSAqFQiLCwMFhbW9NtFsM4xdraGiEhIejp6cGFCxdw+PBhKBQKyGQyjMcvJM8//zwnKChI/Nhjj+Ww2ew79Xr9cbptYmAYi4zfr1bDBCGEIoS82+f+XwghLxNC7AghjcZcAUJI7KVtJZfuCwkhTYSQm3qNBQLBdLlcfubrr78WjUfBpNfroVKpcPjwYbS2tiI6OpoRTAyjhkAgQEBAAOLj46HVanHkyBGcP38eWq1Z5JwOK3feeSc5ePCgra+v7/+cnJyeHK51r/QZeen3lwkhVYSQs31udsN1bAaG0YYRTdemF8A8QohT3wcpimoBUAPA/9JDcQDOXPoJADEATlIUdUO93wkhxNXVdb1Sqfzx6NGjVvHx8TdkvLmi1+tRUlKCI0eOoLe3F3FxcQgMDGT6KzHQApfLha+vLyZPngwOh4PU1FTk5+ePO/Hk4+OD9PR0i7CwsHclEskXhJDhiDYM+hnZh/cpigrrc2sZhmMyMNACI5qujQ7ADgBrBnnuOP5fJMUBeP+y+8du5ICEEL5EIvk5NjZ2Q1pamqDvkNCxDkVRKCsrw5EjR2AwGJCQkAA/Pz/weIOOH2JgGFXYbDY8PT2RmJgIS0tLpKamoqioCHq9nm7Thg1bW1v88ccf/AULFiwSi8WnCSE322n5ap+RDAzjCkY0DY2tAJYRQoSXPX4M/y+SPAF8ByDq0v04XBRV1wUhxFEsFp9buXLlHd9//z1fIBDcqM1mBUVRqKmpwZEjR9DR0YFJkybBx8cHHA6TVsdgfrBYLMjlckyePBmEEBw5cgRlZWUwl6GhNwuLxcIHH3zAe+211wLc3d0LCSFeN7nklT4jAWBNn9DcoZs8DgMDrTBXrCFAUVQbIeQ/AJ4B0HeQ1HEAfyOEeABQURTVQy5iDSASQPr1HIcQInV3dz+5efNml2XLlo0bQdvY2Ij8/HxYW1sjOjqaCcExjBnYbDa8vb0hl8tRVFSEI0eOwNfXF25ubuOiVcGDDz7I9vLycr7vvvtOE0KSKIo6cyPrXOUzErgYnnvnpo1lYDADxs2FeRT4AMBDAKyMD1AUVQTADsAsACcuPZwJ4EFcFFEdQ12cEBIoFouzd+7cKRovgqmtrQ1paWm4cOECQkNDERYWxggmhjEJl8tFQEAAYmJiUF9fj9TUVDQ0jI8K8cmTJ+PXX3+19fDwSOXxeFNvYqkPcNlnJMP4obi4mDtx4kRfLy+vQG9v78DXXnvN5fJtDAYDVqxYIZXJZEG+vr4BqamploOt9dZbbzn7+voGKJXKgMjISL/MzMxBQyrJycm2CoUiSCaTBb344ouuw31ONwLjaRoiFEU1EUK+xcUPhZ19nkoDsBrAikv3TwB4HcCvQ12bzWbHyeXy/cnJydZRUVHX3sHM0Wq1yM/PR1tbGwIDA2FvbxbDqRkYbhqBQIDQ0FB0dHQgLy8PpaWlCAoKGvNfBoKCgnDo0CHLGTNm/GxnZ/dIS0vL7utd4yqfkQzDzPTIlyKHc739ma9kXmsbLpeLd999tzI+Pr6rubmZFR4eHnDXXXe1RUZG9hi3+e6774QXLlwQqFSqnEOHDlmtWrVKlp2dXXD5Wg8//HDjunXr6gFg9+7dwmeffVZ69OjRor7b6HQ6rFmzRrZ///7znp6e2tDQUP/58+e39D0eHYwLj8Yo8i6AyytEjgGQAjBOAD2Bi/lNQ8pnsra2vsfT0/N/Bw4cGPOCiaIolJeXIzU1Ffb29pg0aRIjmBjGJcZQs1wuR3p6OoqKisZ8vpNcLsexY8csfHx8PnV1dX3hBpcZ7DOyb07TWUKI4uYsZaADuVyujY+P7wIAe3t7g5eXV3d5eXm/Cp69e/faLVu2rJHFYmHq1KmdbW1tnLKysgEDHx0cHEz/LB0dHezBQt0pKSlWcrm8NyAgQCMQCKh58+Y1JScn2w3/mV0fjKfpGlAUZd3ndzUAy8uefxvA233uqwAMKdnB2dl5laen57sHDhwQiESi4TGYJlpbW3Hu3DkIhULEx8eP+8GoDAwA4OLiAkdHR1P7jICAALi4DIhajBkcHBxw+PBhwezZs18Wi8WS6urqp6lrjI242mckRVEvA3h5pOxloIfCwkJeXl6eZWJiYr8UlJqaGq5CodAY77u5uWnKysq4crl8QO+ON99803nbtm0irVbLOnDgQOHlz1dUVPDEYrFpLYlEoklPT6e9gR/jaaIBQghxd3d/U6lUvnv8+PExLZi0Wi2ys7ORk5OD4OBgBAcHM4KJ4ZaCzWbD19cX0dHRUKlUOHXqFLq7L8+FHjtYWlpi//79/ISEhIfFYvGPw9TLiWGc0Nraypo3b57Xpk2bKvp6jK6Xv/3tb/UVFRU5L7/8cuVLL73kNpw2jiSMaBplCCFEIpHsmjBhwpqDBw8Kxmrna4qiUFFRYQrFxcXFQSgcrNqYgeHWwNLSctyE7NhsNr788kv+woULZ4jF4lRCCJ9umxjop7e3l8ycOdNr4cKFTcuXL2+5/Hk3NzetSqUyhexqamp4crlc+/TTT4uVSmWAUqkMuHyfRx55pOnAgQN2lz8ulUo1VVVVprUqKyv7eZ7oghFNowghhCWRSL5NSkpa9MMPP/DHakPH7u5unDx5Eo2NjYiPj4dUKh0X5dcMDMOBi4sLEhISoNfrcezYMbS1tdFt0g3BYrHw/vvv8x577LEIsVicRggZH03jGG4Ig8GAJUuWyH19fXtefvll9WDbzJ49u2X37t2OBoMBBw8etLKxsdHL5XLtli1bqgoKCvIKCgryAODcuXMmEf7NN98I5XJ57+VrJSYmdqpUKkFBQQGvp6eH7Nmzx2H+/PktI3aCQ4Rxu44ShBCWWCz+4fbbb5/+2Wef8cfiRHWKolBZWYni4mIEBgaO6dyNsYTBYIBOpxtw0+v1Jk8GRVFQq9XQaDSorKwEIQSEEHA4nAE3Nps9LofSmhNsNhtKpRKurq44c+YM3N3d4eXlhbH4f79hwwYuh8MJ3Lp160lCyESKosZu7JHhhjlw4ID1jz/+6Ojj49Nt9Bi98sorVWVlZTwAWLduXf2iRYta9+3bJ5TL5UEWFhaGTz/9VDXYWu+9957L0aNHbTkcDiUUCnX//ve/SwFApVJxly9fLj98+HDxpWq98hkzZvjq9XosXbq0ISoqitbKOQAg18jxYxgGCCFssVj801133TV1+/btY1Iw9fT0ICsrC3w+H4GBgUze0jCg1+vR09OD7u7uQX8aBdGVxA+HwzGJI0IIKisr0dvbC09PT1AUBYqiTOLqcsHVd22BQACBQAALC4sBP5mO7TePwWBAYWEhGhoaEBYWBhsbG7pNuiHefvtt3Ycffni+qqpqAkVRXXTbM57IyspShYaGjo/GX+OArKwsp9DQUMVgzzGfiCMMIYQtl8v3T5s2LXH79u2csSaYGO/SzdPT04OWlha0traipaXFlCTMYrFMAsUoUuzt7U2PXa83yNvbGykpKfDx8RnyPgaDAT09Pf3EWltbm+m+ceYan8+HUCiEnZ0d7OzsYGFhwYRkhwiLxYK/vz9aWlpw+vRpuLu7w9vbe8y9fs8//zzHYDD4bdu27RwhJISiqE66bWJgGG0Y0TSCXMph+nH69OkJ9913H0etVsPNbcwUCaC3txdnz54Fj8dj2ggMke7ubpM4MgokPp9vEhsSiQSWlpZmc8FksViwtLSEpeWgjXsBXBTOPT09pvOqqKhAV1dXv/MSCoW0nZdCoYCNjQ3YbDY4HA4yMjLQ1NSExYsXQ6VSQaFQ4Ntvvx20Z9iuXbvw+uuvAwD+/ve/Y/ny5ejt7cWcOXNQWVmJVatWYdWqVQCARx99FI8//jgiIiJuyE47OzskJCSgsLAQx44dQ1hYGMZSIUhLSwsmTpzIJoTIPvroo3RCyAQmVMdwq8GIphHiUg7T9zNmzJj28ccf8/R6PdLS0gBgTAinhoYGnDt3DgEBARjLLRFGCqOQuNyDJBAITB4ZmUw2LjwyhBBYWFjAwsICrq7/P8mg7/kbhRSPxzMJKTs7u1ETUocOHYKT0//3VNy0aROmTp2KF154AZs2bcKmTZuwefPmfvs0NTXhlVdeQUZGBgghiIyMxOzZs3H06FHEx8fjxRdfxKRJk7Bq1SpkZWVBr9ffsGAyYvQ6NTc3IyMjA97e3pBIJDe15mjQ0tKCs2fPIjo6GklJSRxCiN+HH36YdinHifY8EwaG0YIRTSMAIYSIxeJvbr/99js/+eQTPovFAovFQkxMjNkLJ4qiUFhYiMbGRsTExIz58RDDSXd3N+rq6qBWq9HZ2QmBQGDysowXgXQ9CAQCuLq6DhBSRhFZWVmJrq4uCAQCuLi4QCQSjZpnZe/evUhJSQEALF++HElJSQNE0/79+zFt2jQ4ODgAAKZNm4bff/8ddnZ26OrqglarhTHnc8OGDdi+ffuw2WfsmJ+VlYX6+noEBwebbf5YX8Fk9Eg+//zzHK1W679t27bjhJBYiqIGVD8xMIxHzPO/dIwjFos/S0xMnLVz585+Sd9cLteshVN3dzdOnz4NR0dHxMXF3VICYDAoikJLSwtqa2tRX18PNpsNkUgEf39/WFtb3/Kvz2AY87P6eie7u7uhVquRm5uL7u5uODk5QSQSwdHRcViqyQghuOOOO0AIwWOPPYZHH30UfUPhrq6uUKsHVkhXVVVBKpWa7kskElRVVWHhwoX44osvEBMTg+effx4//fQTIiIi4O7uftO29oXL5SIyMhLl5eU4duwYwsPDYWtrO6zHuFkGE0xGXnzxRa5OpwvasWNHCiEknqIoPU1mMjCMGoxoGmbc3NxeDQ8PX/qf//xn0Co5cxVOdXV1yM3NRVBQEJydnek2hza0Wi3q6+tRW1uL1tZWCIVCiEQieHt7MzldN4iFhQUUCgUUCgX0ej0aGhpQU1ODnJwcWFtbQyQSQSQSgc+/sf6JqampEIvFqKurw7Rp06BUKvs9b6wuHCocDgdffvklgIvvh+nTp2Pv3r1Yu3YtysvL8cADD2D27Nk3ZOvlEEIgl8thb2+PM2fOQKFQQCaTmYUgv5pgMrJx40ZuY2NjxJ49e5IJIfOuNXKFgWGsM7ZKucwcR0fHRxQKxboffviBf7XKJ6NwKi4uRk1NzShaOBCDwYDc3FyUlJQgLi7ulhRMPT09KCkpwbFjx3DixAm0trZCoVAgKSkJEREREIvFjGAaJozeupCQECQlJcHPzw+9vb04deoUjh49isLCQnR2Xl9RllgsBnCxqeQ999yDkydPQiQSmf63ampqBq36FIvFqKioMN2vrKw0rWVk27ZteOCBB5CWlgahUIhvvvkG77777vWe9jWxtbXFpEmT0NTUhNOnT0OrHTCqa1QZimAy8v777/Pi4uLudHd3/3CUzGOgga6uLhIcHOzv5+cX4O3tHbhmzZoBrtfu7m4yc+ZMT5lMFhQSEqIsLCy8agfnl156SUQIiaypqRnUgbNlyxZHuVweJJfLg7Zs2eI4XOdyMzCepmHCysrqbg8Pj49+//13/lC+MZuDx6m3txcZGRlwdnZGTEyMWXy7HS10Oh1qampQWVkJnU4HsViMiIgIJodrFCGEwNbWFra2tvDx8YFGo0FtbS2ysrJgMBggFoshFotxtc75nZ2dMBgMsLGxQWdnJ/744w9s3LgRs2fPxq5du/DCCy9g165dmDNnzoB9p0+fjhdffBHNzc0AgD/++ANvvvmm6fnm5mb88ssv2L9/P37++WewWCwQQkZsrhyHw0F4eDgqKipw7NgxREVF0VJddz2CCbiY3L57927+9OnTH3Vxcamoq6t7+5o7MdwUSTM2Rw7neim//zXzWtsIBAIqNTW1UCgUGnp7e8mECRP8Dh482Dp16lTTt5wPP/zQSSgU6srLy3N27Nhhv3btWsm+ffsuDLZecXEx9+DBg7Zubm6DjkZRq9XszZs3u2dmZuaxWCyEh4cHLFmypMXZ2ZnWMDDjaRoGCCET3dzcvj1w4IDgeuav0elxam1txYkTJ+Dj4wNfX99bQjAZDAao1WpkZmYiNTUVnZ2dCA4ORkJCAjw9PRnBRDM8Hg8ymQxxcXGIioqCwWBAWloa0tPTUVVVZeoZ1Re1Wo34+HiEhoYiOjoaM2fOxIwZM/DCCy/gwIED8PHxwf/+9z+88MILAICMjAw8/PDDAAAHBwds2LABEyZMwIQJE7Bx40ZTUjgAvPrqq1i/fj1YLBamT5+Oo0ePIjg4GPfff/+Ivg5SqRTh4eHIyMhAXV3diB7rcq5XMBnhcDj4+eef+TKZ7FU7O7ulI2giA02wWCwIhUIDAGg0GqLT6cjl141ffvnFbuXKlY0A8OCDDzYfP37c5krzF5966inp22+/XXmla8+PP/4onDx5cptIJNI7OzvrJ0+e3LZnzx7aB5wynqabhBDiJ5PJ/rdv3z6LG/EW0eFxqq6uxvnz52n7JjvadHV1QaVSQa1Ww8nJCZ6enrCzs7slhOJYRSAQwMvLC15eXmhvb0dlZSXOnz8PBwcHKBQK03BoT09PZGVlDdjf0dERBw8eHPB4VFQUPv30U9P9lStXYuXKlYPa8P777/ez548//rjZ0xoyQqEQsbGxyMjIQHt7Ozw9PUf8/XqjgsmIpaUl9u/fL5g0adKnPB6vVqPR/DkCZjLQiE6nQ1BQUEB5eTl/+fLldbfddlu/WLpareZ5eHhogIvXNmtra71area4ubnp+m733//+187NzU0bGxt7RbdtVVUVVyKRmLxQYrFYU1VVRXueBCOaboKLnQXEJ7755htrPz+/G15ntIQTRVE4f/48mpubMWnSpHGdp2OcxaZSqaDX6yGXy+Hn58fMXBuD2NjYwN/fH0qlEnV1dSgoKIBWq4VcLoe7u/u4/Zvy+XzExsYiOzsbZ8+eRUhIyIid680KJiOOjo7Yv3+/xZQpU36+VFF3ZhjNZKAZDoeDgoKCvIaGBvbMmTO9Tp06JZgwYcJ19elqb29nvfXWW66HDh0qGik7RxImPHeDEELsxGLxqU8++cQuJibmptcb6VCdTqdDRkYGdDodJk6cOG4Fk0ajQXFxMVJSUlBXV4fAwEBMmjQJEolk3F5cbxUIIRCJRJg4cSIiIyPR0dGBI0eOID8/f8TyjOiGxWIhNDQUQqEQJ06cQE/P8PeRHC7BZEQul2Pv3r2WUqk0hRDiOQwmMpgZTk5O+oSEhPaff/65X7hMJBJpSktLecDFytOOjg62SCTSLViwQKFUKgMSExO98/Pz+ZWVlfyQkJAAsVgcrFareREREf7l5eX9nDhisVhbWVlpSmisqqriicVieiskwIimG4IQwhWLxcdee+01l5kzZw6bz3ykhFNXVxeOHz8OV1dXBAYGjsuwVHd3N3JycnD8+HGwWCzEx8cjJCRkzA5HZbg6FhYW8Pf3x+TJk2FtbY1Tp07h9OnTaG9vp9u0YYcQAk9PT/j5+eHEiRNoaWkZtrWHWzAZCQ4OxhdffGHr7u5+ghBiN2wLM9BGdXU1p6GhgQ0AHR0d5NChQ7b+/v79VPzMmTNbdu7c6QgAn3/+uX1sbGw7i8VCcnKyqqCgIO/w4cPF0dHR3U1NTVlVVVXnqqqqzolEIs3p06fzZTJZvxDe3LlzWw8fPmxbX1/Prq+vZx8+fNh27ty5raN3xoPDiKYbQCKRfLFkyRLvBx98cNhdF8MtnFpbW5Geno6goKB+jfzGCx0dHThz5gxOnToFe3t7JCYmwtPTc9x60hj6w2azIZVKkZCQAKlUinPnzuHkyZOmirjxhLOzM6Kjo3H27NlhSRAfKcFkJDExEa+++qqjWCxOIYQwbt4xTkVFBTchIcHP19c3IDw8PGDKlClt9957b+uzzz7rvnv3biEArF69uqG5uZkjk8mCtmzZ4vrOO+9UXs8xjhw5Yrl48WI5AIhEIv3zzz9fHRkZ6R8ZGem/bt26apFIRHsDVcL0Irs+XFxcno2IiNj066+/Dtq8crjQarVIS0uDt7f3Dec4NTQ0ICcnZ1wmfLe0tKCoqAgajQY+Pj5wdnYelx606yUlJQVJSUl0m0Erzc3NKCoqgk6ng7e397h7b/T29uLkyZNQKBQ3/EVopAVTX55++mnNDz/88GVlZeWDI3qgMUxWVpYqNDS0gW47GC6SlZXlFBoaqhjsOSYR/Dpgs9mTlUrlm8nJySMqmICbTw6vrq5GcXExYmJiIBAIRsJEWmhtbUV+fj4IIfDx8elXIs7AAFyc6xYdHY329nYUFRWhsLAQSqVy3DRuNSaIZ2RkoLe3F97e3te1/2gKJgD48MMPebm5uUscHR3TGhsbPxnxAzIwjCBMeG6IEELkYrH4l7179wpGy2tzo6G60tJSlJaWIjY2dtwIJuNcvJycHPj5+WHixImMYGK4KjY2NoiIiEB4eDhUKhXS0tLQ1tZGt1nDAofDQXR0NFpbW5Gbm4uhRgxGWzABF5PZf/jhB4Gzs/P7hJCbr5phYKARRjQNAUKItVgsPv7pp5/aXO+3upvleoQTRVEoKChAQ0MDYmJixkVej1arRW5uLk6ePAmxWIy4uDjY29vTbRbDGMLa2hoTJkyAr68vzp07hzNnzoyLajsWi4WIiAgAwJkzZ3ClJoJG6BBMRoRCIfbu3WshkUj2E0Iko3pwBoZhhBFN14AQwpJIJPufe+45lzvuuIMWG4YinCiKQnZ2Nnp7exEVFTXmy+v1ej1KSkqQmpoKa2trTJ48GSKRaFzlpjCMLg4ODoiLi4ObmxtOnjyJvLw82me83SyEEAQGBsLW1hYnT56ETqcbdDs6BZMRPz8/bN++3UYsFh8jhDDt9xnGJIxougbu7u7vTp06NXLNmjW05n9dTTgZDAZkZmaCz+cjJCRkTAsLiqJQWVmJo0ePQq/XIyEhAXK5fEyfE4P5QAiBq6srEhISYGVlhdTUVJSUlFzTS2PueHt7QywWIy0tbYAQNAfBZGTmzJnkqaeecpdIJPsGzOBgYBgDMKLpKlhbW8+TSqVPfPrpp9eewDsKDCacjIJJKBRCqVSOaXHR0NCAo0ePorm5GbGxsfD19QWHw9QqMAw/LBYLcrkcCQkJ0Ov1OHLkCKqqqoacG2SOSKVSeHh4ID093SSczEkwGXnhhRc4kyZNinN1dX2FblsYGK4XRjRdAUKI3NHRcdePP/7IN6cLd1/hVFVVhYyMDNjb28PHx4du024YrVaLs2fPori4GJGRkQgODgafbxY6lWGcw+Fw4Ovri9jYWNTX1+PkyZNjOt9JLBbD09MTaWlpaGhoMDvBZGTXrl18R0fH55nE8LGFTqeDv79/wJQpUwYk93Z3d5OZM2d6ymSyoJCQEGVhYSFvsDXWrl3r7uLiEqJUKgOUSmXAN998M+gQ3uTkZFuFQhEkk8mCXnzxRdfhPpcbxXzUgBlBCOG6u7v/uX37ditXV7P5W5ngcrmIjo7GwYMH4ebmdt0lx+ZEXV0dcnNz4eXlBalUOqY9ZQxjFz6fj7CwMNTV1Zn6o0kkkjH5fnR3d0dXVxfS0tKQkJBgdoIJuPh6f/fdd4Jp06b9Sgjxoihq/HUjHUEm3v9e5HCul/7F2syhbPf666+LvL29uzs6OgYkzX744YdOQqFQV15enrNjxw77tWvXSvbt23dhsHUef/xx9auvvqq+0nF0Oh3WrFkj279//3lPT09taGio//z581siIyOHf47QdcJ4mgZBLBb/c/HixZI777zTLD8xDQYDsrKy4O3tjY6OjhGZVTfSaLVaZGVl4cKFC4iJiYFMJhuTFyiG8YWLiwvi4+PR2NiIkydPjsist5GmpaUFlZWVCAoKQnZ2ttkmu/v7++Oll16ylUgkvzH5TeZPSUkJd//+/cJHHnlk0Cacv/zyi93KlSsbAeDBBx9sPn78uM2N5gqmpKRYyeXy3oCAAI1AIKDmzZvXlJycbHfj1g8fjGi6DD6ff6e7u/sDb7/99qCuRbox5jA5ODjA19d3RIf8jhT19fU4duwY7O3tMXHiRFhYMIU0DOYDl8tFWFgYPDw8cOLECVRUVIyZXKe+OUwKhQJeXl79cpzMjUceeYQdFxcX5uzs/DzdtjBcnSeffFL61ltvVV6psbNareZ5eHhogIv/Q9bW1nq1Wj1oNOuzzz5z8fX1DVi4cKGivr5+gNeqoqKCJxaLNcb7EolEU1VVZRbXZEY09YEQ4i4Sib75/vvvBeZYsk9RFM6cOQOhUGgKyY3UkN+RwOhdKikpwcSJExnvEoNZY/Q6NTQ0jAmv02BJ3+7u7qbk8Cu1I6CbnTt38h0cHF4mhETQbQvD4Hz11VdCJycnXUJCQtfNrrVmzZq6srKyc/n5+Xmurq7aVatWjamhqIxougQhhC0Wiw9++OGHVuY42JaiKJw7dw4WFhbw9fXt99xYEE6Md4lhLMLlchEeHg6FQmHWXqerVcmJxWLIZDJkZGSYZWsFKysrfP311xZisXg/IcSGbnsYBpKammp94MABO7FYHLxixQrPtLQ0mzlz5nj03UYkEmlKS0t5wMUvyB0dHWyRSKRbsGCBQqlUBiQmJnoDgFQq1XE4HLDZbDz11FP1Z8+etbr8eFKptJ9nqbKysp/niU4Y0XQJd3f3d2bPnu15zz33mOVrUlRUBL1eD39//0GfN1fhpNPpGO8Sw5hHJBKZrddpKG0FZDIZHB0dcfbsWbMUfWFhYVi3bp29RCLZy+Q3mR9bt26tUqvV2VVVVef+/e9/X4iJiWnfu3dvad9tZs6c2bJz505HAPj888/tY2Nj21ksFpKTk1UFBQV5hw8fLgaAsrIy06iKr7/+2s7Pz29AuWpiYmKnSqUSFBQU8Hp6esiePXsc5s+f3zLCpzkkzFIgjDY8Hm+Ki4vL4x999JFZxEwvp6ysDM3NzQgNDb2q4DA34VRfX4/U1FTY2dkx3iWGMc/lXqfKykraBcj19GHy9vYGj8dDXl7eKFl3fTzzzDPsiIiIOEdHx6fotoVhaDz77LPuu3fvFgLA6tWrG5qbmzkymSxoy5Ytru+8807lYPusXr1a4uvrG+Dr6xtw+PBh261bt1YAgEql4hq9UVwuF++++275jBkzfH18fALnzp3bFBUVZRbfVAjd//R0QwgRuru7qw4fPmxnjqX7NTU1KCkpQWxs7JBHo2i1WlPZtJub2whbOBCKopCXl4e2tjaEhYUxYmmYMBgM6O3thUajgcFgAEVRpp8URaGhoQFVVVUICwsDIcR0Y7FY4PF4EAgEuFISJ8P1odVqkZOTA71ej7CwMFqasN5I40qKonD69GnY2dnBy8trhC28ftra2hAeHt514cKFEIqiSui2Z7TIyspShYaGDlqVxjD6ZGVlOYWGhioGe+6W79MklUr/u3bt2lEfxDsUGhsbcf78+esSTMD/e5zS0tIAYFSFk0ajMVX3xcTEMKG4IWAUQ93d3ejt7UVPT4/p1tvbi97eXlAUBUII+Hw+eDwe2Gx2P1FECEFZWRkIIairq+snqAwGAzQaDXp6ekyeEaOI6nvj8/mm3+kuhNDr9YiKioJYLMYvv/yC0tJSLFmyBI2NjYiMjMQXX3wBHm+gY/jNN9/EZ599BjabjY8++gjTp09HfX097rnnHrS0tOD111/H3LlzAQBz5szBxx9/DHd39+u2z+h1Ki8vx/HjxxEVFTWq/ZButNM3IQTh4eFIT08Hn8+HRGJes3NtbW2xbds2y4ceeug3QoiSoijzS8JiuKW5pUUTn8+/a8KECbc/88wzZlcq19bWhuzsbMTExAx6cbgWdAintrY2nD59Gn5+frR4uMYCWq0Wra2taGlpQWtrK9rb20EIGSBe7O3tTb/z+fwheYgCAgKQkpKCwMDAq25HUZRJRBlv7e3taGhoMN3X6/WwsrKCnZ0d7OzsIBQKR7VL+4cffgh/f3+0tbUBAP76179izZo1WLJkCR5//HF89tlneOKJJ/rtk5eXh6+//hq5ubmorq7G7bffjvPnz+Orr77C448/jnnz5uGuu+7C3Llz8fPPPyM8PPyGBFNfZDIZbGxskJ6ejqCgIDg7O9/UekPhZkejsFgsTJgwASdOnACPx4OLi8sIWHnjTJ8+HVOnTpX9+uuvzwPYTLc9DAx9uWVFEyFEKBaLv/ziiy8E5hay6O7uRmZmJqKiom4qtDWawqm6uhrnz59HREQEbG1tR+w4Y4m+AqmlpQUdHR1gs9kQCoWws7ODj48PrK2tRz1kZvRY8fl8CIWDTjAARVHo7OxES0sL6uvrUVRUBI1GAysrK5P9dnZ2IyKkKisrsW/fPqxfvx7vvfceKIrCn3/+iS+//BIAsHz5crz88ssDRNPevXuxZMkS8Pl8eHh4wNvbGydPngSXy0VXVxd6e3vBZrOh0+nwwQcf4Oeffx4We+3t7REbG4uMjAy0tbXB09NzxDyswzVLjsPhIDo6GidOnLjq+4Autm7dyg8NDd1ICEm+lcJ0DObPLSuaJBLJ7ueff97aw8Pj2huPInq9HhkZGQgODoaNzc1X3460cKIoCoWFhWhpacGkSZPA5XKvvdM4pbe3F2q1GnV1dQMEkq+vLy0C6UYhhMDa2hrW1tamEI5RSLW2tqKhoQHFxcUmIeXk5ARXV9dhCVE9++yzeOutt9De3g7gYpjazs7OlDckkUhQVVU1YL+qqirExPz/KDPjdkuXLsXSpUuxY8cObN68Gdu2bcP9998/rOE0gUCA2NhYnDt3DmfOnEFoaOiwhziHe/gun89HVFQUMjIyEBsba1bzHq2trbFt2zbLhx9+mAnTMZgVt6Ro4vP5M6Ojo6c+9dRTZhWWoygKZ8+ehVQqhZOT07CtO1LCSavV4vTp07CxscHEiRNvufwliqLQ0dGB2tpaqNVqUBQFkUgEHx8f2NrajrvXo6+QEovFAP5fSNXV1eHs2bPQarVwcXGBq6sr7Ozsrvs1+OWXX+Di4oLIyEikpKQMi91CoRD79u0DADQ3N2PTpk344Ycf8Mgjj6C5uRnPPfccYmNjb/o4bDYbYWFhUKlUpjyn4SqCGG7BZMTa2hoBAQEm4WROot4Ypvvtt9/+CuBNuu1hYABuQdFECLETi8X/NcewXElJCTgcDhQKxbCvPdzCqaOjA5mZmfD29jZdQG8FDAYDmpqaUFtbi4aGBlhaWsLV1RUTJkwwq2/qo0VfIeXp6QmtVou6ujpcuHABra2tcHBwgKurK5ydnYfkeTl27Bh++ukn/Prrr+jp6UFbWxtWr16NlpYW6HQ6cDgcVFZWDvqeE4vFqKioMN0fbLvXXnsN69evx1dffYX4+HgsWLAA8+bNw/79+2/+xbiEQqGAjY0N0tLSEBISAkdHx5tab6QEkxEXFxe0t7cjOzv7mm1NRputW7fyQ0JC/k4I+Y6iqGK67WFgMC/VMApIJJLdf/3rX21GQpjcDGq1Gmq1GsHBwSN2jOHq41RfX4+MjAyEhYXdEoJJq9WiqqoKmZmZOHz4MKqqquDs7IyEhARER0dDJpPdkoJpMLhcLsRiMSIjI5GUlASJRILGxkYcPXoU6enpKCsru2pjyDfffBOVlZVQqVT4+uuvcdttt2H37t2YMmUKkpOTAQC7du3CnDlzBuw7e/ZsfP311+jt7UVpaSmKiooQHR1ter6oqAiVlZVISkpCV1eXqeqwu3tAb72bxtHRETExMcjLy0NZWdkNrzPSgsmIp6cnKIpCaWnptTceRaysrPDJJ59YisXi3wght9z1ytwQi8XBvr6+AUqlMiAoKGhAp2WDwYAVK1ZIZTJZkK+vb0BqauoV37SffvqpvZeXV6C3t3fgrFmzBs2TOXr0qKWvr2+ATCYLWrFihdQcOtrfUp4mPp8/MyYm5rYnn3zSrMJy7e3tyM/PHxX3+M16nKqqqkx9o8azUKAoCo2NjSgrK0N7eztcXV3h5eUFoVBoVt/EzRkWiwUnJydTqLm9vR1qtRqnTp0Cj8eDXC6Hi4vLkN7zmzdvxpIlS/D3v/8d4eHheOihhwAAP/30EzIyMvDqq68iMDAQixYtQkBAADgcDrZu3drPu7V+/Xr84x//AADce++9mDt3LjZt2oRXX311BM4esLCwQFxcHDIyMtDb2wsfH5/reu+MlmACLnoMQ0JCcOLECdjY2IxKFeBQuf3223HHHXdI9+3b9wKAN+i2xxwIXf1+5HCul/Xhmsyhbnv48OHzbm5ugw4y/O6774QXLlwQqFSqnEOHDlmtWrVKlp2dXXD5dufOneO/++67bmlpaQXOzs76qqqqQbXIqlWr5B9//HHZlClTOpOSknySk5NtFy1a1Db0Mxt+bpnmloQQC7FYXJWammpvTl4mjUaD48ePj3rV2Y00wLxw4QLUajWioqLGbcJ3b28vKioqUFlZCVtbW8jlcjg4OIwZoZSSkoKkpCS6zbgmbW1tKCsrQ0NDA1xdXSGXy0e1z9FoYjAYkJWVBQ6Hg6CgoCG9l0ZTMPWlp6cHaWlpmDBhAqysBowEo43Ozk4EBQV1qVQqP4qiBu00PZa53uaWdIkmsVgcnJGRkX8l0bR06VJ5YmJi+2OPPdYEAAqFIujw4cOFcrlc23e7xx9/XOLr69uzdu3aK55zWVkZNykpybe0tDQXAD755BOHw4cP23z55Zc37rodIldrbnnLuDvd3d03r1ixwtqcBBNFUcjMzISfn9+ol+lfT6jO2OG7qakJEydOHJeCqbm5GZmZmUhLSwObzcakSZMQEREBR0fHMSOYxhK2trYIDg7G5MmTYW1tjTNnziAtLc3UmHM8wWKxTF3DMzMzrzk0ly7BBFysAgwLC0NGRgZ0ukGvi7RgZWWFN954QyCVSr+k25ZbnalTp/oEBgb6v/POOwOqlWpqargKhcI0WNfNzU3Td9ackeLiYv758+cFERERytDQUGVycvKAC2BZWRnXzc3NJLbkcrmmpqaG9ovPLRGeI4R4+fj4PLRx40baX/C+FBUVQSgU0tYIciihur7fkiMjI8eVgDAYDKiurkZpaSkEAgE8PT3HlFdpPMBmsyGVSiGVStHW1oYLFy4gLy8PcrkcUqmUlvEkIwEhBP7+/rhw4QLS09Ov6K2lUzAZsbOzg4eHB7KzsxEREUGLDYNx7733srZt2zaBzWbfptfr/6TbnluR1NTUAg8PD21VVRXntttu8w0MDOy58847O653Hb1eT0pKSvgnTpwoLC0t5SYlJSmTkpJynZyc9CNh93ByS3iapFLpd++9957ljXTWHikaGxtRV1cHpVJJqx1X8zjp9XqcOnUK1tbWQw4rjAW0Wi3Onz+Pw4cPo7W1FZGRkZgwYQLjVaIZW1tbhIWFIS4uDjqdDkePHkVubu5VE8fHGp6enpDJZEhLS0Nvb2+/58xBMBmRyWSgKArl5eW02nE5O3bsELi5uX1FCDGfD/NbCA8PDy0AiMVi3cyZM1tOnDjRL4br5uamValUpr9NTU0NTy6Xa59++mmxUqkMUCqVAZe209x9990tfD6fUiqVGg8Pj57c3Nx+SbJyuVzb17NUVlbG6+t5ootxL5r4fP6cwMBA/7vvvptuU0xoNBrTtzhzaHswmHDS6/U4efKkqe/QeBATer0eJSUlSE1NBYfDQUJCAgIDA2m/QDH0h8fjwcfHB4mJiRAKhUhLS0N+fj60Wto/L4cFsVgMPz8/pKenm4STOQkmI6Ghobhw4YKpyag54O/vj3nz5tmJRKL1dNtyq9HW1sZqbm5mGX8/dOiQbUhISL/S09mzZ7fs3r3b0WAw4ODBg1Y2NjZ6uVyu3bJlS1VBQUFeQUFBHgDMmzev5fDhwzYAUFNTwyktLRX4+fn1+xYhl8u11tbWhoMHD1oZDAbs3r3bcc6cOS2jdLpXZHz4vq/ApeTvnR9//LGAbluMUBSFM2fOQKlUms2HI9A/VKfX61FRUQF3d3fI5XK6TbtpKIpCZWUliouLIRaLkZCQMG7CPuMZFosFiUQCd3d3lJeXIzU1FVKpFB4eHrQPFL5ZjPPe0tLS4O/vj7y8PLMSTMDFUSvh4eE4ffo04uPjzeY1f/PNN3k///zzXwghOyiKGtganmFEqKys5Nxzzz3ewMXw2vz58xsXLFjQ9tZbbzkDwLp16+oXLVrUum/fPqFcLg+ysLAwfPrpp6rB1po3b17b77//buvl5RXIZrOpV199tcLV1VUPAEqlMsAorrZu3Vr20EMPefT09JApU6a0LVy4sHWUTveKjOvqOXd39w9Wrly56vXXXzebXKaSkhJ0dXWNaD+mm6GnpwcHDx6EVCpFSEgI3ebcFBRFQa1Wo7CwEI6OjvD19b2h4cdjibFSPXcj6HQ6lJaWorKy0hTmGuse0NLSUuTm5mLSpEmwt7en25xBKS0tRVtbG0JDQ+k2xcSXX35p+Nvf/pZaVlaWSLctw8H1Vs8xjCy3ZPUcIcTT2tr6EXNK/m5ubkZ1dfU1p9DThV6vx5kzZxAQEIDW1tabaoBJN01NTTh+/DhqamowYcIEBAUFjXvBNN7hcDjw8fHBpEmT0NHRgSNHjqCmpmbMVtu1tLSgrKwMYWFhyM7OHpDjZC4oFApoNJpB5/3RxdKlS1kymSyazWZPodsWhluLcRujkEqlyeaU/K3VapGVlYUJEyaYRR7T5RiTvo0hOYlEMmJDfkeStrY25OfnAwCCg4NHvZUDw8jD4/EQGBiI7u5uFBYWoqSkBP7+/jc9rmQ0uTyHicfjIS0tDTExMWbXNJYQgrCwMBw7dgx2dnZm079px44dgmnTpn1NCJFQFDU+Et4YzB7zu3oPA2w2+3ZfX1+zSv7OycmBl5eX2Xzg9MXYL0okEplymIZr5MpoodFocPbsWZw7dw4+Pj6YOHEiI5jGORYWFggLC0NoaChKSkqQnp6Orq4uus26JoMlfbu4uMDf3x8nT540q/5IRrhcLkJCQnD27Fmz8ez5+/tjzpw5dg4ODs/QbQvDrcO4E02EEJa7u/vn77//vtkkf6vVami1WkgkErpNGQBFUcjOzoZQKISHR//xP2NFONXW1uLYsWNwcnJCXFwcHBwc6DaJYRSxsbFBdHQ0vLy8cPLkSahUKrO5sF/O1arkXFxc4OHhgVOnTl2zASYdODg4wM7ODhcuXKDbFBOvvfYaz9LSciMhxJpuWxhuDcadaLK0tFwcGxvrZC6J1lqtFnl5eQgJCTHLpNXCwkIAgK+v76DPm7Nw0mq1OH36NMrLyxEbGwuJRGKWrzHD6ODk5IT4+Hi0tbUhLS1tRAbx3gxDaSsgkUjg4uKCM2fOmKXwUyqVqKioQEfHdfczHBEcHBywYsUKCzc3t5fotoXh1mBciSZCCNfe3n7L22+/bTZeJmO4SCAwG5NMlJaWor29/ZqCzhyFk1qtRmpqKlxcXDBhwgSzfH0ZRh8Oh4OQkBD4+PggPT0dZWVlZiE+rqcPk5eXFywsLJCTk2MWtveFzWYjNDTUrMJ069ev5/J4vCcIIQPGejAwDDfjSjQ5ODisuvvuu23MpbdQbW0tdDodxGIx3aYMoLq6GjU1NYiIiBiSd8ZchJNWq8WZM2dQVlbGeJcYrojR69Ta2kq71+lGGlf6+/tDp9OhuLh4hK27fuzt7WFvb282YTqBQIC1a9cKJBLJe3TbMt5paGhgz5gxw9PDwyPQ09Mz8H//+1+/JF2DwYAVK1ZIZTJZkK+vb0Bqauqgb/iHHnpIauwQrlAogmxsbMIG2+7o0aOWvr6+ATKZLGjFihVScwhbj5vqOUKIpVgsfvUf//iHWZTLaTQa5OfnIzY21uwu6g0NDSguLkZsbOx1Nawbyqy6kUStViMvLw8+Pj4Qi8Vm97oymBdGr1N9fT3S09Ph4eEx6r2dbrTTNyEEoaGhOHXqFMrLyyGTyUbQyutHqVQiNTUVIpEI1tb0pxM9+eST7H/+85/zCSEbKIoqo9uekUb58vuRw7lewctrMoey3aOPPiq944472n7//fcLPT09pKOjo5/j5bvvvhNeuHBBoFKpcg4dOmS1atUqWXZ2dsHl63z22WcVxt//8Y9/uJw9e3bQf45Vq1bJP/7447IpU6Z0JiUl+SQnJ9suWrSo7XrPbzgZN54mV1fXDcuXL7cwl7LjnJwcswzLdXV14dy5c5gwYcKgA0OvBR0eJ6N3SaVSMd4lhuvG2dkZ8fHxaGlpQXp6+qh5nW52NAqLxUJkZCRUKhWamppGwMIbh81mm1U1HZvNxsaNGwUymewTum0ZrzQ2NrLT09Ntnn322QYAEAgE1OUDdvfu3Wu3bNmyRhaLhalTp3a2tbVxysrKrnqhSU5Odli6dOmAN3hZWRm3o6ODNXXq1E4Wi4Vly5Y1/vjjj7R3gB0XookQ4sDj8Z5ev369WTSyVKvVZhmW0+l0yMjIQGhoKCwsLG54ndEUTi0tLTh27BicnZ0RHR1tdiKUYWzA4XAQGhoKLy8vpKenQ61Wj+jxhmuWHIfDQVRUFLKysswusd3e3h4ODg5mE6ZbunQpy97efjIhxDy7B49xCgsLeQ4ODrqFCxcq/P39AxYvXixva2vrpyFqamq4CoVCY7zv5uamuZpoOn/+PK+yspI3a9asAd6jsrIybt8BvXK5XNN3gC9djAvRJJVK31m9erXAHOY26fV65OfnIzg42Ky8IRRF4ezZs5DL5cNSkj8awqmqqsrUEJTxLjEMB87OzoiLi0NJSQmKiopGxEsy3MN3LS0tERwcjMzMTOj1+mvvMIr4+fmhvLwcPT09dJsCFouFzZs3W8hksl102zIe0el0JD8/3/LJJ5+sz8/Pz7O0tDRs2LDB9WbW3LVrl8Ndd93VPJZmgY550UQIcefz+YufeeYZs5gmWVxcDIlEclOenJGguLgYPB5vWAfwjpRwoigK+fn5qKysRFxcnFk2BGUYu/B4PMTExKC7uxunT58eViEy3ILJiJOTE9zd3ZGdnW0W4TAjbDYb/v7+yM3NpdsUAMD06dMhk8kCCCExdNsy3lAoFBqRSKS57bbbOgFg8eLFzVlZWf3e5G5ublqVSmXKK66pqeHJ5XLt008/LTYmfvfdfs+ePQ733XffoLFnuVyu7etZKisr4/X1PNHFmBdNUqn0H88++6zAHJRqV1cXamtr4enpSbcp/airq0NdXR2CgoKGfe3hFk5arRYnT54ERVGIjo6+obwrBoZrwWKxEBISAkdHRxw/fnxYQl8jJZiMGJvPlpaWDvvaN4Orqyu0Wi0aGsxj3uzrr79uoVAottFtx3hDJpPpXF1dNVlZWXwA+OOPP2z9/Pz6uRhnz57dsnv3bkeDwYCDBw9a2djY6OVyuXbLli1VBQUFeQUFBXnGbc+cOSNoa2tjT506tXOw48nlcq21tbXh4MGDVgaDAbt373acM2dOy4ie5BAY06KJEGLPYrEWPvLII2ZxHjk5OQgICDCr2XIdHR3Iy8tDVFTUiNk1XMKps7MTx48fh1gsRkBAABOOYxhxFAoF/P39kZaWhubm5hteZ6QFE3Cxoi4kJATV1dVmI1CMBAcHIzc31yw6mScmJsLJyUlJCBn+b4m3OFu2bClftmyZp6+vb0B2drbF66+/XvPWW285v/XWW84AsGjRola5XN4rl8uDnnjiCfnWrVuvWMn4xRdfOMyZM6fp8utSX2/U1q1byx5//HGFXC4PUigUvQsXLmwdsZMbIsScXL3Xi7u7+ztPPvnk6vXr19PuZlKr1aioqEBUVBTdppjQarU4fvw4QkNDYWdnNyrHS0tLg7e393W3I2hoaMC5c+cQFhYGe3vaCyTGLCkpKUhKSqLbDBM9PT2YPHkyent7odPpsGDBArzyyisoLS3FkiVL0NjYiMjISHzxxRcYbLj2m2++ic8++wxsNhsfffQRpk+fjvr6etxzzz1oaWnB66+/jrlz5wIA5syZg48//hju7u7XbWdXVxcyMjLg4eEBqVR6XfuOhmDqS3d3N9LS0jBx4sRROd5QKSgoAJfLhZeXF92mYO/evVi9enWKSqWaQrctQyErK0sVGhpqXkr4FiYrK8spNDRUMdhz5uMSuU4IIVZsNvvRNWvW0C6YjMnfgYHmU7RBURTOnDkDLy+vURFMwI17nEpLS1FQUIDY2FhGMA0Bg8GA7u5utLW1obW1FS0tLWhubkZpaSl0Oh1aWlrQ2tqKtrY2dHV10Zo8zOfz8eeffyIrKwtnz57F77//jrS0NPz1r3/FmjVrUFxcDHt7e3z22WcD9s3Ly8PXX3+N3Nxc/P7771i1ahX0ej2++uorPP744zh58iQ++OADAMDPP/+M8PDwGxJMwMVk67i4ONTU1CA3N3fIeUOjLZiAi4OKQ0NDkZGRYVbDfX18fFBRUWEWSeGzZs2ClZVVNCHE49pbMzAMHdoFx43i6Oj4zNKlS82iYs4ck7/Pnz8PKyurUR8SfD0NMA0GA86dOwe9Xn/djTbHKwaDAe3t7ejs7ERPTw96enrQ29tr+glcDNMIBAJwOBwQQsBisUAIgUqlAo/HMw2sNRgM0Ov16OnpMYVNeDwe+Hw+BAKB6WZhYQFbW1uMRF4gIcTU/FCr1UKr1YIQgj///BNffvklAGD58uV4+eWX8cQTT/Tbd+/evViyZAn4fD48PDzg7e2NkydPgsvloqurC729vWCz2dDpdPjggw/w888/35StHA4HEyZMQGFhIdLT0xEZGXnVnDo6BJMRBwcHyOVyZGVlITJyWPsc3jBsNhtKpRK5ubm028RisfD8888LXnrppXcBzKPVGIZxxZgUTYQQnlgs/utf//pX2rOEu7u7UVNTg8mTJ9NtiomWlhbU1dVh0qRJtBx/KMJJr9cjIyMDDg4O8Pb2viXzlwwGA9ra2kyeodbWVhgMBtja2sLKygoCgQCOjo4QCATg8/ng8/lXfZ1CQ0ORkpKCsLCwQZ+nKApardYkxnp6etDZ2Yn6+nq0tbWZjm1nZwc7O7thE1J6vR6RkZEoLi7Gk08+afJ+GteWSCSoqqoasF9VVRViYv6/CMq43dKlS7F06VLs2LEDmzdvxrZt23D//fcPi3AhhECpVKKqqgonTpxATEzMoGFDOgWTEblcjoaGBlRXV9+wh224cXV1NTXjHI7WJjfD/fffz3r99denE0JcKYqqpdUYhnHDmBRNQqHwwbvvvtuC7n9KACgsLISfn5/ZJH8bDAZkZWUhIiKCVpuuJpx0Oh1OnToFNzc3KBQKmiwcfTQaDdRqNRobGweIFKlUisDAwBHx9hghhIDH44HH48HW1nbA831FXEVFRT8RZ29vD1dX1xvyprLZbJw9exYtLS245557UFAwYKrCdSEUCrFv3z4AQHNzMzZt2oQffvgBjzzyCJqbm/Hcc88hNjb2po4hFovB5XJx4sQJTJw4sV9TVXMQTEaCg4Nx7NgxODo6gs/n02qLkYCAAJw7dw5xcXG0fhlis9l46qmnBO+8885rAB6hzRCGccWYE02EELZYLH59w4YNtM+Ya29vR0dHB0JDQ+k2xURhYSHc3d1hY2NDtymDCiedTof09HRIpVKzm6c1ErS3t0OtVqO2thYURUEkEkEmk41YOOxmYLFYJi+TEaOQamxsxJkzZ6DT6eDi4gJXV1cIhcLruija2dlhypQpOHHiBFpaWqDT6cDhcFBZWTlo93yxWIyKCtOIqkG3e+2117B+/Xp89dVXiI+Px4IFCzBv3jzs37//+l+Ay3BxcQEhxJR0bWFhYVaCCbgYblUqlcjOzsaECRPoNgcAYGtrCwsLC9TV1UEkEtFqy6pVq1jvv//+vYSQ5ymKaqHVGIZxgXm4R64DLpc7b/LkyTbmMKKkoKAA/v7+ZhNaamlpQWNjI7y9vek2xUTf5PCKigqkpaVBLpePW8FkMBjQ2NiI3NxcpKSkIC8vD1wuF1FRUUhISICvry8cHBzMTjBdCaOQ8vLyQlxcHGJjY2FjY4OSkhKkpKQgKysLarX6isnm9fX1aGlpAXAxlH3gwAH4+/tjypQpSE5OBgDs2rULc+bMGbDv7Nmz8fXXX6O3txelpaUoKipCdHS06fmioiJUVlYiKSkJXV1dptyu4Rw34uzsjODgYKSnp6O2ttasBJMRNzc3sFisQUOcdKFUKlFQUEB7I04ej4eHHnqI7+bm9jdaDWEYN4w50eTq6vruSy+9RLsfurm5GXq9HuYyIFiv1yMrKwuhoaFmI+KMcLlcREZGIjs7G/b29qOenD4atLS0ICsrC4cPH0ZFRQUcHR2RkJCAiRMnQi6Xj5uZeVwuF2KxGJGRkUhMTIRYLEZ9fT2OHj2KzMxMNDQ09LtQ1tTUYMqUKQgJCcGECRMwbdo03H333di8eTPee+89eHt7o7GxEQ899BAA4KeffsLGjRsBAIGBgVi0aBECAgIwY8YMbN26tV+xwPr16/GPf/wDAHDvvffi448/xoQJE7B69ephPWdHR0d4enri1KlTCA4ONivBZCQ4OBjnz583FQvQjaWlJRwdHVFZWUm3KXjuuec4LBbrcUII7deNsUxWVhbf2NVbqVQGWFtbh7/66qsufbcxGAxYsWKFVCaTBfn6+gakpqYO+s9SVFTEmzhxoq+/v3+Ar69vwDfffCMcbLvk5GRbhUIRJJPJgl588cWbGtkyXIypPk2EkKjJkycfOXz4MK1lahRF4cSJEwgMDIRQOOjfetTJz88Hl8s1Ky+Tkb4hubKyshvq42SOaLVaVFVVoby8HAKBAAqFAs7OzrSKVrr6NFEUhebmZpSVlaG1tRVisRgymcxs8mxuBmNIzs/PD4WFhaZQnblRW1uLiooKswnT9fb24sSJE5g8eTLtOZ+PPPKIZvfu3Y90dXX9h1ZDrsD19mny/OjdYS1PvPDMc5nXs71Op4Orq2vo8ePH8319fU0Der/55hvh1q1bXVJSUooOHTpktWbNGml2dvaAJMZ7771XHhYW1vXXv/61PjMzUzB79myfqqqqc5cfw8PDI2j//v3nPT09taGhof5ffvnlhcjIyBHvaTFu+jQpFIo3165dS/unVX19Pfh8vtkIpubmZjQ2NppFU7nL0ev1OHnypCkkN9JDfkeDzs5OnDt3DqmpqdBqtYiOjkZ0dLQpB+ZWhBACBwcHhIeHY9KkSeByuUhLS8Pp06dN4bmxSN8cJjc3N1Oozhx6EV2Oq6urWYXp+Hw+3NzcoFKp6DYF69at4zk5Ob1Otx3jhZ9++slWJpP19hVMALB37167ZcuWNbJYLEydOrWzra2NU1ZWNqDKnRCCtrY2NgA0NzezXVxcBsyUS0lJsZLL5b0BAQEagUBAzZs3ryk5OdluxE5qiIwZ0UQIcWaz2XGzZs2i1Q6KolBQUAClUkmrHUb0ej2ys7PNMixnFExisdgUkhupIb+jQUNDA9LT03H27Fk4OTkhKSkJPj4+4yb0NlxwuVwoFApMnjwZMpkM58+fx7Fjx1BdXU17jsv1MFjSt6OjIwIDA5Genm42obC+mFuYzsvLC2VlZdBq6Z2z6uPjAw8PDydCiPmMbBjDfPXVVw4LFixovPzxmpoarkKhMAkpNzc3zWCi6c0336z+7rvvHEQiUci8efN8Pvroo/LLt6moqOCJxWLTWhKJRFNVVUV7AdiYEU2urq5rH3zwQT7dbt6amhrY2dnBysqKVjuMFBYWQiwWm0W1XF8oikJGRgZcXV0hl8v7PTfWhFNLSwtOnDgBlUoFpVKJSZMmwc3NzexEqrlBCIGTkxOio6MRFhaGhoYGHD16FHV1dXSbdk2uViXn7OwMpVKJ9PR02sXA5fB4PPj7+yMrK8ssBCqHw4FcLseFCxfoNgVr1661kMvlb9Jtx1inp6eH/O9//xPef//9Nzys8fPPP3e49957G9VqdfaePXuKVqxY4UHn5ILrYUyIJkIIm8ViPf7UU0/R2jKaoigUFxfDx8eHTjNMNDc3o6mpySzDcrm5ubCzszNNZr+csSCcOjo6kJGRgfz8fPj7+yMqKspsQrJjDSsrK4SEhCAyMhIVFRU4fvz4TQ3IHUmG0lZAJBLBy8sLp0+fNgtx0hdXV1dwOBxUV1fTbQqAi004q6uraR/5MmvWLHC53FhCiHlU74xRkpOThQEBAV1SqXTAH9TNzU2rUqlM3qCamhqeXC7XPv3002JjAjkA/Pe//3W6//77mwDg9ttv7+zt7WXV1tb2KymWSqX9PEuVlZX9PE90MSZEE4vFmhEfHy+g+4JVV1cHGxsbs0gCNYblwsLCzM7jUV5eju7ubvj6+l51O3MVTj09PcjKysKZM2cgl8sRGxs7avP7xjtWVlaIjIxEYGAgCgsLcerUKXR0dNBtlonr6cMkFotha2uL/Pz8UbJu6BjDdOaQe8VmsyGRSFBWdsWB96MCi8XC0qVL+U5OTk9ce2uGK/H11187LFq0qGmw52bPnt2ye/duR4PBgIMHD1rZ2Njo5XK5dsuWLVUFBQV5BQUFeQDg7u6u+fXXX20B4PTp0wKNRkPc3Nz6ibDExMROlUolKCgo4PX09JA9e/Y4zJ8/v2XET/AajAnRJJPJ/rFmzRraE0fMyctUWFgIiURimutlLjQ1NUGlUiE8PHxIYs6chJNWq0V+fj7S0tLg7OyM+Ph4ODs702rTeEUoFCImJgYeHh44c+YMzp49O6z9lW6EG2lcqVQq0d7ebhal9X3hcrkICAhAdna2WXjCFAoFysvLTTMQ6eLpp5/m8Pn8Z4m5fdMcI7S1tbFSU1Nt77vvvhbjY2+99ZbzW2+95QwAixYtapXL5b1yuTzoiSeekG/dunVQpfz+++9X/Pvf/3b28/MLWLp0qef27dtVLBYLKpWKm5iY6A1cfA+/++675TNmzPD18fEJnDt3blNUVBTt3wLMvuUAIUQaFBRUcO7cOVqbozQ1NaGkpMQsynnb2tqQnZ2NSZMmmZWXqbu729Q9+Xp72Wi1WqSlpdHWjqC6uhqFhYXw8PCATCajvUT6RqGr5cDNQFEUampqcP78echkMnh4eIz6+/pmOn1rtVocP34coaGhZueRPH36NNzc3MyixUd+fj4sLS0H5DiONrNmzer+5Zdf7qIoKoVWQ/pwvS0HGEaWMd1ywM3N7S8PPfQQ7V6m8+fPm42XKS8vD4GBgWYlmIzz5EJCQm6o+R9dHieNRoOMjAzU1NRg0qRJUCgUY1YwjVUIIXB3d0dCQgK6urpw/PhxdHZ2jtrxb3Y0irHj+5kzZ8wiHNaXgIAAFBYW0u7hAQBPT0+UlpbS7vlavXq1hUKheINWIxjGLGZ9dSCEsAghDzzyyCO02tna2gqKosziW2R9fT3YbDbs7e3pNsUERVE4e/Ys5HL5TXVIH23hVF1djWPHjpk6XA82zZ5h9GCz2QgKCoK/vz9OnTqFCxcujPgFdrhmyVlZWSE4OBgZGRlXHClDBwKBACKRCOXlAyq6Rx0+nw9HR0faw/C33XYbOBxOKCHEfD5EGcYMZi2aAMRHRkby6S7vLyoqMgsvE0VRpkouc6KoqAh8Pn9Y3O6jIZw0Gg0yMzNRXV1tah/AYD44ODiYvE4nTpwYMa/TcA/fdXJyglgsNptyfyPe3t4oLS2lvXrNaEtxcTGtrw+LxcKcOXO4VlZW99JmBMOYxaxFk0KhWPfQQw/RWqrW2dmJnp4es5gxV1VVBTs7O7NK/q6pqUFDQwMCAwOHbc2RFE41NTU4duwY3NzcEBUVxXiXzBSj18nPzw+nTp0a9rDOcAsmIx4eHmCz2SgpKRm2NW8WLpcLuVxuFjZZWFjAxsYG9fX1tNrx2GOPcR0dHf9CqxEMYxKzFU2EEL5Op0u8++67abWjtLQUnp6etOcP6fV6FBUVwc/Pj1Y7+tLW1obCwkJERUUNex7QcAsng8GArKwsVFZWIi4uDu7u7sNgJcNI4+joiPj4eHR2dg5bM8mREkxGgoODoVaroVarh33tG0WhUKCmpsYscq68vLxob3bp4+MDe3t7ESFERqshDGMOcxZNd91+++3cvlPNRxudTof6+nq4utI/XFmlUsHd3d1sBqDq9XqcPn0aERERI+atGS7hZBwcam1tjaioKLN5DRmGBofDQVBQEGQyGY4fP35TfZ1GWjABF8M/UVFRyMvLMwuRAly0ydfXF4WFhXSbAltbW+j1+lFN9h+Me++9l+/s7PworUYwjDnMVjQpFIoXH374YVqvbpWVlRCLxbRXU2m1WpSXl5tV5++CggLIZDLY2tqO6HFuVji1trbixIkT8PHxgZeXF+0eQ4Ybx93dHWFhYcjIyLihUSyjIZiM8Pl8BAYGmlV+k5ubG9ra2tDe3k63KfDw8EBpaSmtNqxcuZLN5/MfZXo2DZ1XXnnFxdvbO9DHxydw1qxZHl1dXf1eu+7ubjJz5kxPmUwWFBISoiwsLBz0G/WJEycswsLClL6+vgG33Xabd1NT06AX2eTkZFuFQhEkk8mCXnzxRfq9FwA4195k9CGE2Hl5eQVMmjSJNhsoikJZWRliYmJos8FIUVERPD09weGYx5+rqakJLS0tCAgIGJXjGYVTWloaAAw5cbu6uhrnz59HVFSUWeWBMdw4QqEQsbGxyMjIQHt7+5BD56MpmIy4uLiguroalZWVkEqlo3LMq0EIgb+/P/Lz8xEdHU2rLa6urigsLIROp6Ptc83Z2Rmenp5WlZWVIQCyaDHiBlH8Z1PkcK6neuCFzGttU1payt2xY4eosLAwx9ramrrrrrs8P/30U4dnnnnGNLj3ww8/dBIKhbry8vKcHTt22K9du1ayb9++AbHYRx55RLF58+aKmTNndnzwwQeOr7zyiuuHH37Yb+6PTqfDmjVrZPv37z/v6empDQ0N9Z8/f35LZGQkre5bs/Q0WVtb3zt37twBk5FHk6amJlhbW9Meyunu7kZ9fb1ZfOgC9I1vuR6PE0VRKCgoQHl5OSZNmsQIpnEGn89HbGws2tvbcfbs2WuW+NMhmIwEBgaiuLjYbMJ0Tk5OoCgKTU2DTsEYNVgsFtzd3VFVVUWrHcuXL7eQSqXP0mrEGEKv15POzk6WVqtFd3c3SyKR9Esy/OWXX+xWrlzZCAAPPvhg8/Hjx20G6xFWVlbGv/POOzsA4O6772775ZdfBrR/SElJsZLL5b0BAQEagUBAzZs3ryk5OdluZM5s6JilaHJwcPjLY489RqtoUqlUVxw2O5oUFhbC19eX9hChkfz8fMhkMtDRBmIowkmn05l65UycOBFcLq1vI4YRgsViITQ0FEKhECdOnLiiKKFTMAEX37PmFqYzepvoRi6X094/asmSJUSv199DCKF1GPxYwMPDQ/vkk0/Wenh4hLi4uITa2Njo582b19Z3G7VazfPw8NAAF9/71tbWerVaPcCV6O3t3bN79247APjvf//rUFtbOyCMV1FR0W9Ar0Qi6TfAly7M40rcB0KI1M7OzpXOvkgajQYdHR20N5Ds7u5Ga2urWSSiAxe9b62trbSKyasJJ+MoFpFIZHYd0xmGH0IIPD094efnh7S0NHR1dfV7nm7BZMTFxQV8Pt9s5tPZ2tqCx+PR7m0SCATg8/loaWmhzQZLS0tER0fzACTSZsQYob6+nr1v3z674uLic7W1tdldXV2sbdu2OdzIWjt37lRt377dOTAw0L+9vZ3F5XLN4xvFEDA70WRvb3/fwoULaR2bUl5eDplMRvtFt6SkBN7e3rTbAdAXlhuMwYSTRqNBWloaPD09IZMxVcS3Es7OzggNDcXJkydNlXXmIpiMGMN0dA8lNuLj44OioiK6zYBCoYBKpaLVhgceeMDCw8NjNa1GjAF+/vlnW5lM1uvu7q7j8/nU3LlzW44fP94v90EkEmlKS0t5wMUvsR0dHWyRSKRbsGCBQqlUBhiH8YaHh/ccO3asKDc3N3/58uVNUqm09/LjSaXSfp6lysrKfp4nujA70WRra/vwkiVLaLOLoihUVlZCIpHQZQKAiyKgoaHBbPoJ5efnQy6X0xKWG4y+wqm8vBwnTpyAr6+v2bxe45WKigpMmTIFAQEBCAwMxIcffgjgohdy2rRp8PHxwbRp09Dc3Dzo/rt27YKPjw98fHywa9cuABdbQsyYMQNBQUHYtm2badtHH30Up0+fHpJd9vb2CA8Px6lTp1BdXW1WggkwvzCdnZ0dDAYD2trarr3xCOLs7Izm5mZau5Xfdddd6O3tTWSq6K6OQqHQnD592rq9vZ1lMBjw559/2vj7+/eLi8+cObNl586djgDw+eef28fGxrazWCwkJyerCgoK8g4fPlwMAFVVVRzg4pfxl156ye2hhx4aUA6bmJjYqVKpBAUFBbyenh6yZ88eh/nz57eMwqleFbMSTYQQez6fL/L29qbNhtbWVlhbW9OeC3PhwgUoFAravToA0NjYiLa2NigUCrpN6QeXy0V4eDiys7MhEokgEonoNmncw+Fw8O677yIvLw9paWnYunUr8vLysGnTJkydOhVFRUWYOnUqNm3aNGDfpqYmvPLKK0hPT8fJkyfxyiuvoLm5Gfv370d8fDyys7PxxRdfAACysrKg1+sRERExZNuEQiF8fX2RmZmJwMBAsxFMRlxcXCAQCFBRUUG3KQDMw9tECIGrqytqa2tps4HP5yMgIIALIJw2I8YAt912W+esWbOaQ0JC/P38/AINBgNZu3Zt/bPPPuu+e/duIQCsXr26obm5mSOTyYK2bNni+s477wwak965c6eDQqEI8vLyCnJzc9MaK/BUKhXX6I3icrl49913y2fMmOHr4+MTOHfu3KaoqCjaKyrMo4b9Emw2+85p06bRqlbMwcuk0+lQU1ODyZMn02qH0ZZz585hwoQJZiHg+qLRaEwNNktKSiAUCpk5ciOMm5ub6TW2sbGBv78/qqqqsHfvXqSkpAAAli9fjqSkJGzevLnfvvv378e0adPg4HAxDWLatGn4/fffYWdnh66uLmi1WpMXZsOGDdi+fft12dbS0oKioiJMnDgROTk5iI6ONhvPqJHAwECkpqbC2dkZFha0ToiCo6MjCgoK0NnZSevrJJFIkJubS+vn7rx58yxyc3PvBzA01ybNDKVFwEjw/vvvV7///vv9WgN88MEHpvuWlpbUb7/9ds127xs2bKjbsGHDAO+SQqHQGr1RALB48eLWxYsXt96s3cOJWXma5HL5k4sXL6YtO56iKNTX18PFxYUuEwAAZWVlkEqloLMbupGioiLaquWuhlarRXp6uikkN9JDfhkGolKpcObMGUycOBFqtdokplxdXQcdIVJVVdWvdYZEIkFVVRWmTZsGlUqFmJgYPPPMM/jpp58QERFxXaHWvjlMLi4uiIiIwKlTpwYkh9ONMUyXk5NDtykghJgG6NKJjY0NNBoNensHpLWMGgsXLiRsNnsJbQYwjBnMRjQRQrharTaEzoaW9fX1cHBwoLW832AwoLy83CxCYT09PVCr1WZhS1/0ej1OnjwJLy8vU2XhSA75NVcMBgO6u7vR2dmJjo4O1NbWmsZTdHd3X7N/0c3Q0dGB+fPn44MPPhjQFZ4Qcl1eSQ6Hgy+//BJnzpzBwoUL8cEHH+C5557D2rVrsWDBAvz0009X3X+wpG+hUGhKDqfzYjwYLi4u0Ov1V8z7Gk1EIhFaWlpof43EYjGtPZucnJzg7OxsQwihN8zAYPaYU3guYeLEiWw6BUtlZSXtAqG2thbOzs5m0f3b3HpEARe9gWfPnoW7u/sAT8SNdg43VyiKQmdnJ1pbW9Ha2oqenh709PRAo7lYQMJiscDj8cBms0EIQVVVFbhcLvLy8mAwGKDRaEzCicvlQiAQQCAQwMbGBnZ2drCxsbmhkKtWq8X8+fOxbNkyzJs3D8DFi29NTQ3c3NxQU1MzqLdWLBabQnjAxf+3pKSkftts27YNDzzwANLS0iAUCvHNN9/gtttuw+zZswe15WpVcvb29ggICEBGRgZiY2PN6n3s7++PnJwcxMXF0Rr2JoRALpejrKwMvr6+tNkhFotx6tQpeHp60mbDzJkz+cXFxfMAfESbEQxmD/1X5ksoFIqHFyxYQFuQX6fTobW1lfbeTKWlpQgLC6PVBuCiJ6GtrQ0hISF0m9KPkpIScDicK/aKGsvCSaPRoL6+Hi0tLWhpaYFGo4GVlRWEQiEcHBxgYWEBgUAAHo836IU2KioKKSkpmDBhQr/HKYqCVqs1ia62tjacP38eHR0dYLPZEAqFsLOzG1KeDUVReOihh+Dv74+1a9eaHp89ezZ27dqFF154Abt27cKcOXMG7Dt9+nS8+OKLJg/LH3/8gTfffNP0fHNzM3755Rfs378fP//8M1gsFgghVyzTH0pbARcXF7S3tyM7OxuhoaFmk5cnFAohEAjMIh1AIpHg6NGj8Pb2pk1YCgQCcDgcWvOrlixZwvnvf//7OBjRxHAVzEI0EUKIWCyeMWvWLNpsUKvVcHV1pfVDta2tDWw22yzyh/Lz8+Hv7282Fxng4t9IrVYjNjb2qtuNJeFkDKup1WoYDAY4OzvD2dkZ3t7ewzbChxACHo8HHo8HW1vbfhdprVaL1tZWNDc34/Tp09Dr9aZKRKFQOODvf+zYMXzxxRcIDg42ifs33ngDL7zwAhYtWoTPPvsMcrkc3377LQAgIyMD27dvx6effgoHBwds2LDBJOo2btxoSgoHgFdffRXr168Hi8XC9OnTsXXrVgQHB+Pxxx8fcE7X04fJ09MTZ8+eRWlpKa2ejMtRKpXIzMyEs7Mzrf9nHA4Hzs7OqK2tpbVlh0QiQWVlJfz8/Gg5fmBgIFgslowQYk1RVActRjCYPcQceoYQQgISExNPpaSk0FYjnJ6ejoCAANjY2NBlArKysuDq6kp76XxLSwvy8/OvKU5Gk/b2dmRmZiI2NnbIYsLYIdzb29ushFNHRwfKy8tRV1cHCwsL099cILj5nq4pKSkDQl7Xg0ajQV1dHWpra9He3g5HR0fIZDLY2dndtG3DxY00rtTr9Thx4gT8/Pzg7Ow8whYOnXPnzsHe3p72it2Ojg5kZ2cjLi6ONht0Oh1SU1ORmJhIm4h85JFHej/77LN7DQbDD6N53KysLFVoaGjDaB6T4cpkZWU5hYaGKgZ7ziyC/I6Ojgvvvvtu2rqA63Q69PT00CqYdDodmpqaaHfVA//vZTIXNBoNMjMzERERcV3eF3NKDjcYDKisrMSxY8dw7tw5CIVCxMfHY+LEiZDL5cMimIYDHo8HiUSCqKgoJCYmwtXVFUVFRThy5AhKS0tpbUII3HinbzabjaioKOTm5qKzs3MELbw+fH19UVxcjMGGmo4mxqHWxo7qdMDhcGBpaYn29nbabJg/fz7fw8PjMdoMMHNee+01Fx8fn0Bvb+/AV199dcDFymAwYMWKFVKZTBbk6+sbkJqaOug/6W+//WYdEBDgz+FwIj///PN+OTFbtmxxlMvlQXK5PGjLli2Og+2vVqvZcXFxPnK5PCguLs6nvr5+1ErNzSI8Z2tru/juu++mTcDV1dXRLlaqqqogFotpD4fV19eDy+WajWfBYDAgMzMTfn5+A6q0hgLdoTqNRgOVSoWqqiq4uLggPDzc7JouXgkWiwUXFxe4uLigt7cX5eXlOHr0KFxcXODh4THq53Gzo1EEAgHCwsKQkZGBuLg42hvYAhcbK7q6uqKsrIz2AeEKhQJlZWUIDAykzQZjo8sb+V8fDqZMmYLe3t5oWg5+HYT8vDFyONfLnvXqNfs+nTp1SvCf//zH+fTp0/kCgcCQmJjoO2/evNagoCBT6eV3330nvHDhgkClUuUcOnTIatWqVbLs7OyCy9fy9PTUfP7556pNmzb1C6uo1Wr25s2b3TMzM/NYLBbCw8MDlixZ0uLs7NyvFPill15yS0pKan/jjTeKXnzxRdeNGze6fvzxx6NSfkm7p4kQwtHr9VKlUkmbDbW1tbSHxIzz7uiEoigUFBSYlZcpPz8fDg4ONyV26PA46XQ6nD9/HseOHQOPx0NCQoJZdqkeKnw+Hz4+PkhMTIS9vT0yMjJw7ty5UStVH65ZcnZ2dvD29sbp06fNYpwJAHh5eUGlUtHuxXN1dUVdXR2tXi+RSDRoj6/R4pKI5TOtBwZy7tw5i/Dw8A4bGxsDl8vFpEmT2r/++mu7vtvs3bvXbtmyZY0sFgtTp07tbGtr45SVlQ34duLn56eZOHFi9+WFBz/++KNw8uTJbSKRSO/s7KyfPHly2549e4SX7//777/bPfbYY40A8NhjjzX+9ttvo1bBRbtoAhAeHBxM66w5uqvmOjo6TCXhdFJdXQ2hUGgWiegA0NDQgLa2tmEphR4t4WQwGFBaWoqjR4+CzWZj8uTJUCgUZtFCYjhgsVhwd3dHQkIC7O3tceLECRQWFo7oBX+4h++KxWJYWFigvLx8GKy7ebhcLmQyGUpKSmi1g8ViwdnZGXV1Axo1jxp8Ph+EEPT00DctIykpictms6fQZoCZEhYW1n3y5Emb2tpadnt7O+vAgQPCioqKfs2oa2pquAqFwjRU183NTTOYaLoSVVVVXIlEYtpfLBZrqqqqBuzf2NjIkcvlWgCQSqXaxsbGUfuApV00OTo63jV16lTaWg00NTXB3t6e1rCYOYxuMRgMKCoqorVXS190Oh1ycnKGtUx8JIUTRVGorq7GkSNH0Nvbi/j4eHh5eZlFV/eRgBACiUSCyZMng8vl4ujRoygtLR12781wCyYjAQEBKC0tvWI7g9FGoVCgurqa9iaTxgo2OqHb23THHXdw5XL5MtoMMFMiIiJ6Vq9eXTt16lTfKVOm+AQGBnaZw+ebsTXJqB1v1I50BWxtbRffddddtCkWukNzFEWhpqbG1NmaLqqrq+Hs7Ey7t8tIXl7eiOTNjIRw6unpwalTp1BbW4uYmBgolUqzyJcZDVgsFjw9PZGQkIDu7m4cO3Zs2JKJR0owAReTjoOCgnD27FmzCNOx2Wx4enqitLSUVjuEQiE6Ojqg1Wpps4HuAb6JiYljIq+JDtasWdOQm5ubn5GRUWhvb6/39fXt5xJ0c3PTqlQqk/eppqaGJ5fLtU8//bRYqVQGKJXKgKutLxaLtZWVlab9q6qqeGKxeMCb0dHRUWf0YJWVlXEdHBxGLbZNq2gihHAMBoOUrr4cwMXEZzpLkJubm2Fra0tr+IaiKLPqYVNfX4/Ozs4Ry/EaLuFEURQqKytx4sQJyOVyREREmI3oHG04HA4CAgIQGBiIzMxMFBcX35QYGUnBZMTJyQlWVlYoKysbkfWvF4lEgpqamhEdf3MtCCGmru50YW1tPeJjgK4Gn8+Hm5sbjxAivfbWtxZVVVUcACgqKuLt27fP7uGHH27q+/zs2bNbdu/e7WgwGHDw4EErGxsbvVwu127ZsqWqoKAgr6CgIO9q68+dO7f18OHDtvX19ez6+nr24cOHbefOnTtgYO/06dNbPvnkE0cA+OSTTxxnzJjRMoyneVXo9jTRms/U0dEBCwsLWgVLZWVlvyGmdNDc3AwLCwvap64DF8Nyubm5CAsLG1GX680KJ6N3qb6+HvHx8bQXEpgL9vb2iI+Ph1arvWGv02gIJiMBAQFQqVRmMdiXzWbDzc2N1hlsAP0hOkIInJyc0NBAX9uixMREPpvNTqLNADNl9uzZXl5eXoF333239wcffFDu5OSkf+utt5zfeustZwBYtGhRq1wu75XL5UFPPPGEfOvWrYN+Izl8+LClSCQK+fXXX+3XrFkj9/b2DgQAkUikf/7556sjIyP9IyMj/detW1ctEon0ALB48WL5kSNHLAHglVdeqTl06JCtXC4PSklJsX3llVdGTeXT2tzS2dn55fXr12989tlnaQnPlZSUgM1m0zZvzmAw4PDhw0hMTKR1LlZGRgY8PT37dWemi6ysLNjZ2UEul4/K8W6kAWZjYyOys7MREBBgdmLpZptbDifNzc3IysqCt7f3kHP2RlMwGWloaEBRURFiYmJob/nR09ODkydPIiEhgVZbUlNTERUVRZvntKGhAVVVVQgNDaXl+H/88QdWrVr1R3Fx8fTROB7T3NK8MNvmljY2NovuvPNO2j4ZGhoaaA3N1dfXw8nJiVbB1N3dje7ubtpn7gEXX4+urq5Rbb1wvR4nlUqFvLw8xMTEmJ1gMjfs7e0xadIkVFVVIS8v75rhOjoEE2BeYTqBQAArKys0NjbSaodYLKbV4+Xg4GCaUUgHiYmJ6OnpmXDtLRluNWi7Whv7M9GVz0RRFLq6umjtm1NbW0v7eI/S0lIoFArav2EbDIZRCcsNxlCEk8FgQHZ2NhobGxEXF2cWocyxAJfLRXR0NAghOHny5BUTjOkSTEaM1XR0V68BF2flXbhwgVYb6E7GZrFY4PF4tFU39slrYvo1MfSDTk+Tn7e3N21X6tbW1kEHko4WFEWhqamJ1pCYwWCAWq2mdUinkbKyMri6utImRq4mnDQaDdLS0mBhYYGIiIhx20ZgpCCEwN/fHxKJBMePHx8wxoRuwQRcTGT38fHB+fPnaTl+X+zt7dHT00NrryILCwvo9Xpaq+icnJxo9bhNmDCBC4DxNjH0g05PU2RUVNTwjHG/ARoaGuDoOOhYm1Ghvb0d1tbWtIbmamtr4ezsTLsI0Ol0UKlU8PLyotWOwYRTd3c3jh8/Dk9PT/j4+NDukRvLiMVihIaG4uTJk2htvVgQYw6Cqa99zc3NZpEULpPJaG++6ezsjPr6etqOT3cyeExMDE8qld5BmwEMZgltV2y5XH53TEwMbWVrjY2NcHJyouvwqK2tpb03U3l5+aglXF+NkpISyGQys+ht1Fc4qVQqpKenIzg4mPa/1XjBzs4OEyZMwOnTp1FRUWE2ggm46BFTKpXIz8+n2xSIxWJUV1fT2kNKJBLRGqKzs7NDS0sLbcefNGkSOBwO0xmcoR+0iSaDwRCTkJBAy7HNIZ+J7iHBXV1d0Ov1sLGxoc0GAOjt7UV1dTVtFYyDweVyERoaipycHIjFYlo9kuMRa2trKJVKnD17Fkql0iwEkxFnZ2f09vaaPGF0YRyaTaenxd7eHq2trbQJN7rzmry8vKDT6dwI415m6AMtookQwiaE2NPl6aE7n0mj0YCiKPD5tEUnzWJAMAAUFRXB29ub9hBhX3p6enD69GlER0ejtraW1kZ/45GWlhYUFhYiNjYW+fn5aGtro9skE8b8K3PwNsnlclor+gghEAqFtHp76M5rcnNzYwNgksEBLFy4UOHg4BDq4+MTaHxMrVaz4+LifORyeVBcXJxPfX39oB/kW7ZscZTL5UFyuTxoy5Ytg34Lra2tZU+cONHX0tIy/IEHHuh3cXr66afFrq6uIZaWluFXs/Fvf/ubq0wmC1IoFEHff/+97Y2c57WgKzzm5+npSWurATq9B3R7mYyjWyZPnkybDcBFb1djYyMCAwOvvfEoodVqkZ6ejqCgIDg5OcHe3h5paWkAQHul43jg8hymCRMm4NSpU4iOjjabQdH29vZgsVhobGyk9XPCzs4OnZ2d0Gq1tIWujXPg6GpJ4uTkhPLyctpmc0ZERHBPnjwZCaCCFgOuwMwjz0QO53r7Jn+Uea1tVq5c2bB69eq6Bx980MP42EsvveSWlJTU/sYbbxS9+OKLrhs3bnT9+OOP+/WqUKvV7M2bN7tnZmbmsVgshIeHByxZsqTF2dm5X8t3S0tL6tVXX63OysqyyMnJ6VcRNHfu3Ja//OUvdf7+/kFXsi8zM1OwZ88eh8LCwtyysjLutGnTfOfMmZMz3M2r6fI0RUZGRtLmZrnV85na2tpgY2NDu3enoKAASqXSbJKrKYpCZmYmfHx8TO+PkRzye6sxWNK3tbU1wsLC8H/svXlco+W5//95sgfIwhoggbDDwAAzA7PPMC61ausyR2tt61et/npOt3OO2lZb23qsdjkda22rtWpdWm21RzsdtXbRVuvsMAwwrMO+BMgCYclK9ty/P5ggMwPDluR+gOf9es1LCUnuKyF5ns9zXdf9uerq6qju1LqQULaJZk8RwzBQqVQYHR2lFkNKSgrV9Wn3NW3fvl2k0WiuohYAi7j22msdycnJ5814e/fdd5Vf/OIXxwHgi1/84vjf//73i9T1W2+9paiqqrKpVKpAcnJyoKqqynbo0CHFhfeTy+XBq6++2iGRSIIX/u7KK690arXaSx4gDh48qLzpppsmpFIpKSoq8mq1Ws/hw4fDfiVGRTRptdpP0mwCp9nPFAwGYbfbIZdHJHO4KGiLNmB6hM3U1BTVjNuFnD17Fkql8iILBk44rZxL7ZKLj49Hbm4uGhoaWDE8FwBkMhni4uKoCgaAvl+SUCgEn8+nZn/A4/HA5/OpCerdu3dDKBReQWXxVcD4+LggJGYyMjJ84+PjF53X9Xq9UKPReEM/q9Vqr16vD3vqVK/XizIyMmbWSU9P9w4NDYku9ZjlQEU0BYPBXXv27KGxNNxuN8RiMbXsxuTkJOLj46lmV0ZGRqiLlb6+PuTm5rImyzQ0NASn04n5zFY54bR8FmMroNFoIJPJ0NHREeXo5ic3N5e6yaRCoYDVakUweNHFd9QIlehoEXoPaJCbmwuv16vmmsEXhsfjseZ4HkmiLpoYhuEDiKc1gsJisUCpVFJZG5gWLDTHb7hcLvD5fIhEYRfgi8bn82FiYoJ6tivE5OQk+vr6sGXLlkt+6deqcLr77ruRkpKCjRs/aheYmJjAVVddhfz8fFx11VXzjrR4+eWXkZ+fj/z8fLz88ssApndEXnPNNdi4cSMef/zxGcF07733oqGhYd44NmzYAJvNRn1gbYjQzlK73U4tBoZhkJiYiImJiYXvHCFoiyaaJToej4f09HQeADWVAFhOYmKiX6fTCQFAp9MJExIS/BfeR61W+4aHh2dOOHq9XqRWq32vvPKKsqioqLioqKg4NIh3JajV6vMySwaD4bzMU7igkWnKyszMpOoETlM0TU5OUnUBHxkZoS5WBgcHkZGRwYqrEp/Ph8bGRmzduhWLaRhci8Lp85//PN59993zbvvxj3+MK6+8Et3d3bjyyivx4x//+KLHTUxM4JFHHsGpU6dQW1uLRx55BJOTk3jvvfewZ88eHD16FL/5zW+wbds2dHd3IxAIYMuWLfPGwTAMtmzZgu7u7otcw2nBjTSZ7juj+fdQKpVULSDKysr4AMqoBcBirr76astzzz2XCADPPfdc4jXXXGO58D779++3HjlyRG42m/lms5l/5MgR+f79+6133HGHpaOj42xHR8fZqqqqFTvK3nzzzZZDhw4luFwupqOjQzQwMCC57LLLwv7BpSGaCvLz86l1IFssFigUF/WgRQVCCLxeL1WrAdr9TIQQDA0NscLuAADa2tqQl5e3pB63tSacqqqqLhLyb7/9Nu68804AwJ133om33nrrose99957uOqqq5CQkID4+HhcddVVePfddyEUCjExMYG6ujrExsYiJiYGDz30EL7//e8vGItQKERZWRkaGxtZ0d+UkpKCyclJ6uNExsbGqL0fDMNAJBJRm8sXFxdHNdu3YcMGsUwmY88WX0pcf/312Xv27Cnq7+8Xq1Sqsp/97GdJjzzyiPHDDz+Ua7XajYcPH5Y/8sgjRgA4evRozK233qoFAJVKFbj//vsNFRUVGyoqKjY88MADBpVKFZhrDbVaXfrQQw9lHDx4MFGlUpXV19dLAOBLX/qSRqVSlbndbp5KpSr72te+lg4Ar776quLee+9NB4DKykr3/v37JwoKCkquueaagieeeEIX7p1zAAXLgbi4uI0bNmygphpoNoHTNtT0+/1wu91Ut3abzWbEx8ezwv17dHQUHo9nWduZQ8JprdoRjIyMzLym1NTUOcszer0eGRkZMz9rNBro9XpcddVVePzxx/HBBx/gm9/8Jv785z9jy5Yti55xmJCQAKVSif7+fuTk5ITnBS0ThmGQkZGBoaEharHw+XxIpVI4HA5qZrShEhmN1oLZzeA0jhslJSVMSkrKHgA/ifri87AYi4Bw88477/TPdXt1dfVFAxurqqqmqqqqZkzG7r333vF77713QcMtvV7fMtftzz777PCzzz47fOHtt912m/W2226bSUMeOHDAdODAgYimZaOeaVKpVHtKSkqo1GVoN4HT7qcym83UG8B1Oh0rRrf4fD60tbWhvLx82Z+HtZZxmg+GYRb9HrlcLrS2tuKdd95BU1MTbrnlFvz85z/H17/+dXzta1/Dpz71Kfz5z39e8HmKioowODjIijKdRqPB0NAQ1cwX7RId7a3/CoWCmglqaWkpAoHAus80cUwTddEUCARKysrolIdDTuC0oN1PRbs05/F44HK5qL4HIVpbW5GXlweJRLKi51mrwkmlUs28HqPROKfYVqvVGBr6yPOvt7cXXq/3vF1yv/rVr3DHHXegpqYGCoUCr7/+On76058uuD6fz2dNmU4sFiM2NpaqaJgv2xctaO5gC61P6/1PS0uD3++nZ+zHwSqiLpr8fn/SYtP04YZ2pod2P5XFYqHm7AtMb+ufXc6hxfj4OLxeb9hchmkKJ0II/H4/vF7vzNZ0v9+/YqFxww03zOyGe/nll3HjjTdedJ+rr74a//jHPzA5OYmBgQG89957+OIXvzgjmCYnJ/GXv/wFd9xxB6ampma2JC92llhCQgIUCgUGBwdX9FrCAe2RJmKxGIQQan1FsbGx67YZnMfjISYmRsAwjHThe3OsdaLa08QwjLSgoEDI49GZE+xwOKhlWkIHvJVmNpbL5OQklEol1R1rBoMBO3bsoLY+MP13aG9vX1FZbi6i0eMUCARgtVphtVphsVhgs9lACAGfzwefz4fZbIZAIEB1dTUCgek+S5lMBoVCAaVSCYVCMWdPyGc/+1kcPnwYY2Nj0Gg0eOSRR/Ctb30Ln/70p/Hiiy9Cq9XijTfeAADU1dXh2WefxQsvvICEhAQ89NBDqKiogMfjwcMPP3yeEH300Ufxne98BzweD1dffTWefvpplJaW4ktf+tKiX3NhYSGOHz8OjUZD1cE+KSkJra2tCAaDoHX8Cm39p7GJYnYzOI2NLLGxsXA4HFFfN0R2dja6urryAMzZc8Oxfoh2I3gezWn2TqeTWhO0y+Wi2gRuNpuRnJxMbX23203dHwqYLlHGxcVFpKE2EsLJ7XZjeHgYBoMBhBAoFAooFApkZWVBLpdfJCQOHz6MvXv3AvjIfd5qtcJgMKC9vR2BQAAqlQqZmZkz34U//OEPc679wQcfXHRbZWUlXnjhhZmfb7rpJuTk5MxpXPmzn/1s5v8lEgn+8Y9/LPn1C4VCZGRkoK+vD/n5+Ut+fLhgGAbx8fGYnJykNo8uJSUFfX191HaehrI9NPoiBQIBAoEACCFULvwKCgqE7733XgE40bTuibZoKigoKKAyPoUQgkAgsCgvnkhAszQHTPdTqdX0/NlMJhNVU09g+jPQ2dmJ7du3R2yNcAgnQgjGx8dneoQ0Gg127NixZMHJ4/FmRFboRBsIBGA0GtHU1ARCCHJycpCamrqsE9FinL7DQXZ2No4ePYqsrCyquy5Dzdi0RJNcLqfWDA181FdEazOJSCSiZtlSXFwsUqlUFQD+FPXFOVhFVPPMKSkpFcXFxVRSDV6vl2qWg3Y/Fc0sG8AeU83k5GRIpZFtTVhJj9PIyAiOHz8OnU6HoqIi7N27F9nZ2WH77PL5fGg0GuzatQubNm3C2NgYjhw5gsHBwSX1QUVLMAHTMefk5KC7uzui6yxEcnIyzGYztfV5PB54PB78/otMl6MC7R10NE02S0pKIJPJ6PYWUOaWW27JSkhIKM/Pz5/ZSfjSSy/F5+XllfB4vIpLuXofPHhQnpWVtTEzM3Pjt7/97XlPBHv37s2XyWSbLr/88rzZt99www3ZWVlZG/Pz80tuueWWLI/HM+dV3lNPPZWo1Wo3arXajU899VRErm6imnaRyWTbiouLo7nkDE6nE3FxcVTWBqZPMrR8XjweD0QiEbV+Jr/fD5fLRfX9DwaD6Ovrw+7du6Oy3lIzTj6fDy0tLfD7/aioqIhKKTc2NhalpaXwer3o6OiAXq/Hpk2bFhSV0RRMITIyMnD06FHk5ORQ6wsM+SXZ7XZqfkmhrfc0pgrQbgaPi4uDw+Gg8trLysrg8XgKor7wPHyj6daKcD7f4+WvL+j7dPfdd4/dc889o3fddVd26LZNmza5/vSnP/X8+7//e9Z8j/P7/bjvvvsy33vvva6cnBxfeXn5hptvvtlSUVFx0RTob3zjGyan08l7/vnnz+slue222ybeeuutfgC48cYbs3/+858nffOb3zzvCmZkZIR/4MCB9Pr6+rM8Hg+bN28u/sxnPmNJTk6e00hzuUQ10xQIBLLy8vIWvmMEcDgc1E7atJvAaVsdjI2NUe2nAqaNGFUqVVSzjYvNOIWySykpKdi6dWvUe99EIhHKysqQn5+PU6dOQafTzZt1oiGYgOksS05ODgYGBqK25lywYes/rWxPqBnc6w37OK9FERJNNFAoFCCE0LvqYwHXXnutIzk5+bw055YtW9zl5eWX3NJ5+PDhWK1W6ykuLvZKJBJy0003TRw8eFA5131vvPFGu1wuv2g69a233moNZVorKyuds2fZhXjrrbcUVVVVNpVKFUhOTg5UVVXZDh06FPaemKiKJr/fr6TlnExTNLlcroiXhC4F7X4q2v5QhBAMDAwgOzt74TuHmUsJJ5/PhzNnzkCn02Hnzp3QaDRUdzcmJSVhz549sFqtqKmpucgagJZgCqFWq2E0Gmd2BtJApVKte5NJWuvTnoEnEAgEDBsGZq4yhoaGRGq1ekZpazQar16vX9bVq8fjYV5//fXET37ykxf5T+j1eqFGo5lZR61We/V6fdibIKMqmng8HjW7AZo9PbT7mWiuTwihPqR4cnISUqmUmnCdSzi5XC6cOHECycnJ2Lp1K7Us5IUIBAKUlZUhLy8PNTU1MydI2oIJmC6PpaWlQa/XU1kfmN4FGJohSQPazeA0RZtUKsXU1Irnui6bc8dQOrsAOAAAd955Z+aOHTsc11xzDTX/iagpGIZhxBKJhM7WNUyLJloHe5vNRjXTQ1swKhQKqhkUnU4HmlYXwPnCqb+/H6dOnUJZWRn17NJ8JCcnY9u2bWhsbIROp6MumEJotVrqZpchvyQa0G4GpznOhMfjgRBCzSH+XLZ8bQ2ZjAIZGRnnZZaGh4dFarXa+69//Su2qKiouKioqPjVV19d8AT59a9/PW1sbEzw/PPPD831e7Va7ZtdttPr9SK1Wh32SdvRTPukJScnU52HQCvLRXNQb2jXIK0TM+0sk8/ng9VqpbZNfDZCoRClpaVoa2tDRkYG1fdlMcTGxmLDhg1oaWlBQUEBdcEETGcbBAIB1WxLQkICJicnqa1PM9sUExOzaEf3SCAUCuHzhf08uChSU1P5AOiMs1jF7Nu3zzkwMCDp6OgQud1u5tChQwk333yz5YorrnB2dHSc7ejoODt76O5cPPHEE0n/+te/FG+99VbffCa3+/fvtx45ckRuNpv5ZrOZf+TIEfn+/fvDbiMfVdGkUqmonLmDwSDVq3m3202t/EK7n4l2adJgMCA9PZ0V2RyXy4XGxkbs2LEDBoOB9bPqLBYL2tvbsWvXLnR1dVGdPTabzMzM82beRRvac9holsj4fD7VnjKJRAK3+6JNV1FBo9GIsI4zTddff332nj17ivr7+8UqlarsZz/7WdIrr7yiVKlUZY2NjbH/9m//lr9nz558ABgYGBDu27cvD5gWuj/96U8Hr7nmmoL8/PyS/fv3T1RWVs75R6yoqCi8/fbbc6qrq+UqlarsT3/6kxwAHnjgAe3Y2JigsrJyQ1FRUfE3vvGNNAA4evRozK233qoFAJVKFbj//vsNFRUVGyoqKjY88MADBpVKFfYPazTLZWnp6elUynM0d64BdD2iaIsWm80GuVxObX2TyYSSEvoDygOBAGpra1FaWorExMSIj1xZKRf2MFVWVuL06dPYsWMH1U0NwLQzdldXF7X1hUIhAoEAtZEqSqUSfX19UV93NrScuSUSCbX5e2q1mpeSksIK24HFWASEm3feead/rtvvuOMOy4W3ZWVl+Y4cOdIT+vnWW2+13nrrrQteadTX13fOdbvf75/z9VZVVU1VVVXNDIW89957x++9997xhdZZCVH7xkskkgyNRkPFzpdmpicErUyH1Wqllmny+/0zPRg0CAQC1P2hQrS3tyMjI2OmTEhzyO9CzNX0HRcXh5KSEjQ3N1PrKQkhEAgglUqpziKjuf1dJpPBbrdTWRuYHh5MS7iIxWJqmaaMjAzIZLJCKotzsIaonc2Sk5OLNRoNFeXgdrupWO8D0z01tEa3AHRNPWlnmWjP2wsxMTEBq9V6keUBG4XTpXbJpaSkQCwWUy2NhVjPW//5fD7VhmipVEpNuNAsz50bRZRFZXEO1hA10SQSiXIzMjKitdx50Mw0recsF+3SIG1/KGA629Xc3IxNmzbN+Xdgk3BajK1ASUkJent7qTYDA/RNJmn7JdFsiJZIJNT+/jRFk1arhdfrpTtAk4M6URNNhJC09HQ6Gw9oCheaxpa0ei5C0CwNhvyh4uPjqawfor29HZmZmZe0fGCDcFqsD5NQKGRFmU4ikSAYDFLzS6LdDE5TPKzXTJNcLgchhP4WUg6qRO2MGggE4mhtsabZCE5TsHk8HmplSYBueS40H4ymaLRYLHOW5eaCpnBaqnFlqExH02QSmPaSGhsbo7J2qBmclnCkKR5oZppo9lMBAJ/Pp3dA4WAFUfsA+P1+Ka2sA82eJtpZLlprh7Ylz+epEWlolwYBoLu7Gxs2bFh0eZSGcFqu03dRURF6e3upZptol8hoNoPTFk201hYKhdSMPQGAYRg6BzQO1hA10cTj8QS0TqB+vx9CIZWNe1TLczQzTbRtHmiLJqfTCa/Xu2QDy2gKp5WMRpFIJFAoFDCbzQvfOULQLpFJpdJ1mXGh+bppw+fzeQzDrMts0y233JKVkJBQnp+fP+Ph8sUvflGTnZ1dUlBQUHzVVVfljo2NzXmSP3jwoDwrK2tjZmbmxm9/+9vzNpru3bs3XyaTbbr88svzZt/+6U9/WltYWFhcUFBQfM011+RYrdY5/wYPPvhgamZm5sasrKyNIY+ncBO1bV00P2h+v59axmO9NqHTboC3Wq3YsGEDtfX7+vqQk5OzrMeGhFMkfZzCMUsuNzcXbW1tSElJCXN0iyPUW0PTM4hmtoeWKznNJnTaSKVSAiAOAD1LegAvd++qCOfz3Zl/ckHfp7vvvnvsnnvuGb3rrrtm+g2uvvpq2y9/+cthoVCIL3/5y+qHHnoo9Zlnnjmvbu/3+3Hfffdlvvfee105OTm+8vLyDTfffLOloqLioi/PN77xDZPT6eQ9//zz5217fvbZZ4cSEhKCAPCFL3xBc+DAgZQf/ehH522fra+vlxw6dCihs7OzTafTCa+66qqCG2+8sTXcu9ejmWmimtaktYOMprHlehVNhBAEAgFq2cVgMIixsTGoVMvfaBPJjFO4hu/KZDL4/X6qWQeaWQ/aoonW2rTd9RmGoVYWjo2NDYmmdce1117rSE5OPq82etNNN9lCx9mdO3c6Z8+YC3H48OFYrVbrKS4u9kokEnLTTTdNHDx4UDnXGjfeeKNdLpcHL7w9JJiCwSBcLhdvrs/gwYMHlTfddNOEVColRUVFXq1W6zl8+HDYh65GRTQxDMPj0ezIpUggEOCyXFHGbrdTNbQcGRlBSkrKipvQIyGcwiWYQmRkZGB4eDgMkS0Pmn1N61U00UYgEFDra4qNjWUAyKgsznJ++9vfJl1zzTUX1cuHhoZEarV6ZpurRqPxziWuFuJTn/pUVnJycnlPT4/kW9/61uiFv9fr9aKMjIyZddLT071DQ0Nhz1hES8jEnktrrktoXZnR7GmiKZocDgdkMnrHNYPBALVaHZbnCqdwCrdgAoD09HSq/lJyuZyaOzZN4SIQCKjOgGMYBsHgRQmBqMDn86mJpnMXY5xouoBvfvObqXw+n3zpS1+aiNQaBw8eHBgZGWnKz893v/TSS9S8ZKIlmuIu5VMTSWj1O7ABmrsGaTaC02y+B6YzXeG0WgiHcIqEYArFFgwGqZ1AaWd7aG5/B0CtTEVTtNHMNMlkMh7WaXluPp588snE9957T3no0KH+ubLrGRkZ52WWhoeHRWq12vuvf/0rtqioqLioqKj41VdfXdTWeoFAgNtuu23irbfeukg0qdXq8zJLBoPhvMxTuIiWaJLREk00m8DZAK2q6HoVbD6fD3w+P+zv+0qEU6QEUwi5XA6bjU5fLE3hwufzqWZ7aIqH9br2OdHEZZrOcfDgQfkvfvGL1L/97W89Mplsziunffv2OQcGBiQdHR0it9vNHDp0KOHmm2+2XHHFFc6Ojo6zHR0dZ2+77bZ5t8EGg0G0traKQ///5ptvKvPz8y+6Urr55psthw4dSnC5XExHR4doYGBActlllznD92qnidbuOZlMJqOS7vH7/dRmv63nLBft0iCttSNp6LmcXXWRFkzAR1v/aVg80BzgGoLW91wkEsHr9VLZ8LBeRZNcLudjnYqm66+/PrumpkY2OTkpUKlUZd/61rcMP/vZz1K9Xi/viiuuKACALVu2OF577bXBgYEB4Z133qk9cuRIj1AoxE9/+tPBa665piAQCOBzn/vcWGVl5Zxf2oqKisK+vj6Jy+Xiq1Sqsl/96lcD+/fvt91xxx3ZDoeDRwhhNmzYMPXb3/5WBwCvvvqq4vTp07E///nPDZWVle79+/dPFBQUlPD5fDzxxBO6SJz7o6UmxLR2kAUCAWqiibZgow0twUiznyrS/lBLEU7REEzAdDP28PAwtFptxNaYDz6fT600CHxktkhDuPB4PKrlufUomsRiMQ8AvTEL51iMRUC4eeedd/ovvO2+++6b05I/KyvLd+TIkZ7Qz7feeqv11ltvXdBUrb6+vnOu2xsaGjrmuv22226zzs5SHThwwHTgwIGITvJesIbAMMzPGIa5d9bP7zEM88Ksn3/KMMzXFlqHz+dTOYPSnL9GuzS4XrNcNG0eomGquZhSXbQEE0DfZBKgd5FAsyl5vTZj07QcEAgEDJbY1sIwTIBhmMZZ/74VofA4osBi/vgnAOwCZgwqkwCUzPr9LgAnF1pnPToO0CzPBYPBdSuaAHqCMVo79y4lnKIpmIDpK3+a2R6amQea2R6a4oH22rQ4dx5b6snMRQjZNOvfjyMQGkeUWMwf/ySAnef+vwRAKwA7wzDxDMOIAWwA0LDQOrREE+2+IlprE0KoDqtdr0TzfZ9LOAUCgagKJjawXoUL7ddNC8rv+ZIzTRxriwUbbgghBoZh/AzDZGI6q1QNQI1pIWUF0EIIWWhb37oUTet5bY7oMLvHyWq1YmpqCldeeWXUBVPoREbjM0c760Ery0Z77fUoVM/tjF1qz4WUYZjGWT//LyHk9TCGxRFFFtulfBLTgmkXgCcwLZp2YVo0nVjE4xmXyyU6fPjwcmJcEYFAAB6Ph4prcCAQgNvtBo3Xfc5unsrahBA4nU4qawPTPknrbW2/34/Ozukeytra2qiv73A4cPjwYSqiyel04sSJE1Qyq1NTU7BarVR6F10uF8xmM5XNJm63G8PDw1Qa4D0eDxiGQU9Pz8J3DjMjIyMQLP0NdxFCNkUiHo7os9g/fqivqRTT5bkhAF/H9NDC3yzi8UGJROK97LLLou44aLFY0N/fj82bN0d7aTidTrS1tWHbtm1RX9vn86G2tha7d++O+tqEEBw5cgSXXXZZ1NcGgMOHD6+rtS0WC6qra9FgI6iM56OwsDAiQ34vxeHDh7Fv3z4qoqm6uhpbtmyhYjNRV1eHoqIiKmN7mpqakJmZifj46Jsjnz17FomJiSuar7hcuru7IZVKodFoor52dXU1fD5f2A0TOVYPi700OwngOgAThJAAIWQCgBLTJbqFmsABIEgzjUwL2muvx/d8vWGxWNBQ34CGOhvG4Ifr3BU4jdEm63HTw3re7LEe1yaEgBBCb9cDRW655ZashISE8vz8/JmNYPfcc096QUFBcVFRUfHu3bvzBwYG5kw9PvXUU4larXajVqvd+NRTTyXOdR+TycTfvn17QUxMzOY77rgjc677XHHFFXmz159NMBjE5z//+YzMzMyNBQUFxcePH49Ij8JiM00tmN4199oFt8URQub0abgAqqJpPdbeaTaJrmf4fD58Pl9UyhahXXItp20w27xwSniY8vlQuKkMnY3NABZngBkOaH7WaNqK0Fyb5mYPmn9vmkI1EAgQAEs9mV3Y0/QuIWRFtgNNgxkVK3n8hZRnDi3o+3T33XeP3XPPPaN33XVXdui2hx9+2PSLX/zCAAA/+MEPUr797W+nvfbaa4OzHzcyMsI/cOBAen19/Vkej4fNmzcXf+Yzn7EkJyefZ6cfExNDHn30UUNTU5O0tbX1oqrUyy+/rIyNjZ3Xgv+Pf/yjoq+vTzIwMND64Ycfxn7lK1/JbG5untPfaSUs6ht3LrskJ4R8d9ZtnyeEFC5yHWqiCaD3Baed7Vmvoonm+x6tkSIhwQRfPHoHJkEATPLdID6C3/c2h23I72Jwu93UfLEAuga2tDdc0MxyrUfBdu64sqSDCyGEf4HlwKr0abr22msdycnJ53l7JCQkzLwXTqeTN9fn8a233lJUVVXZVCpVIDk5OVBVVWU7dOjQRbPm5HJ58Oqrr3ZIJJKL3l+r1cp78sknVd/73vfmPaC9/fbbyttuu22cx+PhyiuvdNpsNoFOpwv71Wu0PvXBcwo96tB0DKbpH7OeRZNYLKY2j0ypVEZ800FIMOXnFuPp/30XE14fJiedGPU74XMH8GrXGfhAoiacaI1QAejv1PT5fNQEG83yHM1pB8FgkJppsN/vX06maU3zX//1X+rU1NSygwcPJv7kJz8xXPh7vV4v1Gg0M31garXaq9frlyRmvva1r6nvueeekbi4uHnfe6PRKMzKyppZJy0tzbuaRdOUy+WK0lLnQ1O40B7oSRMej0dNrEok9CbfR1o0hQRTZWUlnj7wHpKzE2G1uzA4PAGLzwWGAZIEMfhDd9OKhvwuNSZaoonmyRugm+Wime1Zr+OpnE5nAMAUlcVZylNPPaU3mUzNn/rUp8Z/8pOfpIT7+U+ePCnt7+8X33HHHZZwP/dyiNY3zu50Oqllmmhme9YrNAep0hRNMpkMdrs9Is8dEkxbt27FB39pRX11DzxCHjI1CRDHCeEK+MET8JDsjcWLZ0/DFwxERTjRFE005wzSznLRHIpNU7jQHE9lt9sDACLzBV/l3H333RN/+ctfLtrKqVarfcPDwzP1e71eL1Kr1b5XXnlFWVRUVFxUVFR89OjReZu2jx07Ftfa2hqjVqtLq6qqigYGBsTbtm27qDUoLS3NNzAwMLOO0WgUabVaXzhe22yiJZocDocjSkudz3rP9tB67TSFC821eTweeDxe2IX6bME0PjqFF598H5mFqegdMIPHYxCbLDm3PgPvkAeGKRve7j8LYHGz6lbC1NQUNfdxmqKJ1qDeEJTLVOsy02S32wkAOiczFtLS0jKj2t944w1lbm7uRSWl/fv3W48cOSI3m818s9nMP3LkiHz//v3WO+64w9LR0XG2o6PjbFVV1bzZu29+85vm0dHRZr1e33L06NGOrKwsT21t7UWDfW+44QbLq6++mhgMBvHBBx/EymSyQCREU7Q+eXan0xmlpc5nPWd7QuIhNjaW2to0kEgkmJiYoLI2AMTHx2NiYgIpKeHJVM8WTGKRBAe+8zt4PD4IE2OACRuMIzZItOcusHjA8NlJxKiFeK71FG7O2QiGYc5zDgfCt6vO6XRCIpFQ+565XC5qoonm2rSzXDSzPZRFUxDrNNN0/fXXZ9fU1MgmJycFKpWq7Fvf+pbh3XffVfT19UkYhiEajcb74osv6gDg6NGjMU8//XTy66+/rlOpVIH777/fUFFRsQEAHnjgAYNKpZrzal6tVpc6HA6+z+dj3nvvPeXf/va3roqKinlPJI899ljyuec0f/rTn7b+9a9/VWi12o1SqTT4wgsvDETgbYiaaHLTasxlA7R2uYQaommJJlp/c4VCgf7+fiprA4BGo0Fvb29YRNNswRQbG4uXfvk+ejqNUGUmoL3HhJQUOUZHbcgsnxZBDA8I+AkKpElotBrxwXAPPpaRDwAREU5DQ0NUTAZDWK1WpKamUlnb4/FQE03RsrW4FOuxCf3cxT910bQYi4Bw884771x0UL3vvvvmtByqqqqaqqqq0oV+vvfee8fvvffe8YXW0Ov1LZf6fWFhobe7u7st9PMDDzxgDv0/j8fD7373u8G5Hxk+olKeI9Osyx0HNBvRaWZ72NDTROtqXKlUwuFwwOdbWWb4QsF0pnMY7w8NQ12SBqU2AYQAqSlyAAAvbvqrTM6dx2SO6czTM6015z1nOEt1hBAYjcaou4/PhubOPbfbTa2niGZZkjaBQIBaluucaOLKc+uYqG29CAaD1BqLaG6/p7n9nXaJjNbaDMNQX1+j0WBwcPkXPRcKJofLg0eefRe9hgmY5MDZnhEAs/Y+x0yrpZBocg94cFVGPr5QvPWi5w6XcBodHUVCQgJVjySafUU0hct6boAH6GW52JJp4qBHNEUTtUwTzWyPVCoFLbuF9SqagOj4JV0KrVaLwcHBZdkuXCiYAOCJVz6EcWzaNDM7QQm/PwCGx6DDYYG8MB6BmUwTQWKeAn0TVvxoy9W4Vls05xrhEE69vb3IyclZ1mPDgcPhoFJ6DrFeRdN6znKdO6bROaBzsIJomnz4vV46cw6FQiForb1ehQvNDBsw3ddktVqprS8UCpGSkgKD4SKvt0syl2D61+ku/PX49E44WYwYvS3Tz5mRnQi704ORCQdcvOmLggAh0E/Y4A8GUdN16UzXSoSTxWIBn8+HTCZb0uPCCU2rA2A660BLtK1X0UQ7y0UICRLaQXBQJWqiSSAQOGmdxGg2JdPONNF63QzDQCAQrLivZ7mEdrDRJDc3F93d3Yt+D+YSTOZJB3780vsz9ylIS4LbNf18sqSPTtguTN8WmNU6eKpz4fLgcoQTIQStra0oLFzsFKXIMDk5SdWJnObuOZpN6C6XC1LpRaPBooLX66U6sofqPDAOVhA10cTn821jY4uZ7Rt+2NCUTAORSEQ920OrRCaVSuHz+aiJNmD6b5+Xl4e2trYF7zuXYCKE4PvPvwerY/rzIxYJMNQ+MvMY66zsqSMw/f8BQgBm+kJ4oUxTiKUKp97eXiQmJlLN8hBCMD4+jsTEOQemR5xQtoVWb816bUKnaegZDAYRWK+mfxwzRLM8N7SSxtiVQFO4SKVSqg3JNKHdV5SSkgKz2bzwHSOIRqOBx+PB6OjovPeZSzABwB//2YhTLTO7dlGSkQK7dTprKRYLMWCanPmd1T/9GSOEQBY3fVIxW53oNS24yxfA4oWT3W6HXq9HQUHBop43UtjtdsTFxVEbI0K7NEi7PEcr00TzdZvNZggEgshP42Ypt9xyS1ZCQkJ5fn5+yYW/e/jhh1UMw1QYjcY5d4U89dRTiVqtdqNWq9341FNPzXmlYzKZ+Nu3by+IiYnZfMcdd2TO/t22bdsKs7KyNoYcxPV6/ZzrPPjgg6mZmZkbs7KyNv7pT3+SL+d1LkTUtr24XK6u4eHhaC13HhKJBOPjizt5RGJtmg3RIVdwGlt0FQoFRkZGFr5jhEhNTUV/fz/S09OpxcAwDMrLy1FdXY34+PiLdnrNJ5j69eP45evHZn7m8xiY+z8qN2ryEtE6Ov2Z5gkYWL0ffcZkcjHs9unMU02HDrmpi8vGLOTjRAhBY2MjysvLqW35DmEymaj5MwHTVgcKxUWD2qMGzdlvNMuSNEWTTqeDUCjUU1n8AoKmgopwPh8vtWtB36e777577J577hm96667smff3tPTI/zggw/kaWlpczYOj4yM8A8cOJBeX19/lsfjYfPmzcWf+cxnLMnJyedl7WJiYsijjz5qaGpqkra2tl6kyl955ZW+SzmH19fXSw4dOpTQ2dnZptPphFdddVXBjTfe2Bru70nULtOMRmO7Xq+nUg+mPVaDZhlcJpPBZqNzcSSTyUBrfA4wnemyWq3Um0dDZbrW1tbzbp9PMPn9ATz8zN/h8X6047MkKxVjIx/tdBbLPipRyOIlmP0KpXEf9XxUL6KvaTaXyjj19PQgKSmJaoYlxMjICFQqFbX1aWaafD4fVdG6XjNNQ0ND8Pv9fVQWZwHXXnutIzk5+aJt6P/5n/+Z8ZOf/GR4vsrGW2+9paiqqrKpVKpAcnJyoKqqynbo0KGLrjjkcnnw6quvdkgkkmWdMA8ePKi86aabJqRSKSkqKvJqtVrP4cOHw75TI2qiiRBiHB4eptJgQjvbwzAMNeFEs0TGMAz4fD61viKGYVjREA5Ml+mCwSB6enoAzC+YAOC5P51Ep+78cp7TdL74HHV8dMEVozy/MVYU89EJtb53GL4ltmHMJZwMBgNGR0epN38D0ydOHo9HtSGYZjM07dKgz+ejluWiLZomJibaqSzOUn7/+98r09LSfDt37px3t5NerxdqNJqZLJRarfbq9folm6t94QtfyCoqKiq+//770+Y6n+r1elFGRsbMOunp6d6hoaGwHySi2RBgNBqNVJroRCIRNcsBgO72e9pb70PZHlqkpaVBr6efUWcYBps3b8b4+Dja29vnFUxWuwt/+qDpvNs2aFNg0H0k/OTxMRgetcz8LJGff/zhiz/6Wk95fGgZWLoP02zh1NHRgZ6eHmzbto1aD9FsDAYD1dJcqDxFq2eQZmkwlLWl9dpp7hrU6/V+m802QGVxFmK323mPPfZY6uOPP740X5Vl8Prrr/d1dXWdra6u7jh58mTcr371Kzo7QBBd0WQwmUxU6iS0G6Jp2g7QFk00d9AB083g4+PjYMOmFx6Ph/z8fPT19SE9PX1Ojx+FTIrf/+B27N2S+9GNtvMzdelZ0yNUQghiLyjVXHBttdQSXQihUIjc3Fz09PQgKyuL+qwzYPqkzYZ5dzT7mWhmmmg6sAN0dw3q9XofgIgLhNVCe3u7eHh4WFxWVlasVqtLR0ZGRFu2bNkwODh4XhpSrVb7hoeHZ45Ker1epFarfa+88ooy1Nh99OjRmEutlZ2d7QOA+Pj44K233jpRW1t70cFTrVafl1kyGAznZZ7CRTRFk5lmmYTH41FzBY+JiQnZ70edUO8DLdGQlJREdQcbwzBIS0tbsslkJLBYLGhubsbevXsxOTmJ7u7uOe+XnqLA4/fdiKcf/BQ+vr0QA13nl+qI+HyRxJOe/zUO8M9PXS/Gr2kuDAYDent7cfnll0On0614Vl04sFgsiI2NpXbiBKZ3UdGyOgCmndBpmYo6HA7ExFzy/BZRaDbAG43GIAD6XwKWsG3bNtfExESTXq9v0ev1LSqVytvQ0NCemZl53ol2//791iNHjsjNZjPfbDbzjxw5It+/f7/1jjvusHR0dJzt6Og4e6kGb5/Ph9CuPI/Hw/ztb39TbNy48aIsxM0332w5dOhQgsvlYjo6OkQDAwOSyy67LOwn3mj2NAX8tFQLgLi4OGrChfbWe7lcTq0ZPCYmBl6vl5pgBaZHmgwMDFBbHzi/h0kul2Pr1q2w2+2or6+ft3RcWZyJ7//nJ/Hsk3fg+k9sglw2XZYYGjs/cxi8ILPkYc4XyK2DJjjciy8PBwIBtLW1YWBgADt27EBsbGzYhvyulP7+fmRlZVFbnxCCsbExJCUlUVk/1AROK3tOO8tFszx8zjZk3Yqm66+/PnvPnj1F/f39YpVKVfazn/1s3i/B0aNHY2699VYtAKhUqsD9999vqKio2FBRUbHhgQceMKhUqjmv4tVqdelDDz2UcfDgwUSVSlVWX18vcblcvI997GP5BQUFxSUlJcVpaWm+r33ta2YAePXVVxX33ntvOgBUVla69+/fP1FQUFByzTXXFDzxxBO6SAhsJpo7izIyMkZ7e3uTaTRwdnZ2Ii4uDmq1Oupre71e1NbWYs+ePVFfGwD6+vrA4/GonWzOnj0LpVJJdev/6dOnkZeXh/j4+Kivfammb71ej66uLmzYsGHBPh2/P4DWs3rUdA6hpceA3qExTNpdyNqfglPOaTuPr8dm4S88J0yHzxfJP//CDbi8NHeupz2PyclJNDc3Q6PRICcn57yTs8/nQ01NDfLy8i6yI4gGbrcbp06dQlVVFTXRYLPZ0NHRgW3btlFZf2xsDAaDAWVlZVTWb2xsRGZmJhISEqK+ttVqRW9vL7Zs2RL1tQEgKyvLMTAwEJEUX1NT00B5eTkd92eOi2hqakoqLy/Pmut3Uc1zikSiUZ1Ol5yfnx/NZQFMZ5pobX8XiUTw+XwghFA52CuVStAyFgWm/ZIGBgaoiqacnBz09vaisrIyquteSjABgFqtRlJSEpqammAwGLBx48Z5d4UJBHxsKsvEprKPfN8cUx6cHD+Am319AHgQ9qTiCzl1+MHh880nqzt1lxRNgUAAnZ2dmJiYQEVFBeLi4i66z0I+TpFGp9MhKyuLao8ibX8o2jvnaPZz0Zz1d84NnN54AQ7WEO1cZ/d8fRyRhmZ5LrQ+LdGmUCioleeA6TlwtP2SEhIS4PF4ovo+LCSYQojFYmzduhUqlQonTpyATqdbdA9aXIwYHtIPV6ALrkAHgsQNL7ouul/NPH1NhBAYjUYcP34cYrEYu3fvnlMwhVjJkN+V4PV6YTAYqDaAA+vbHyr0maTlEeVwOC752YwkRqMRAoGAvncJB3WiKppGR0dPnD17lsqZMzY2lqrRIs1dbHw+H8FgkJpXFMMwUCqVmJycXPjOEYxhw4YNaG+Pjs3KYgVTCIZhoFarsWvXLrhcLhw9ehRdXV2LsqpwB85/X/3EhdgLdmXrRidhmvzIHNPn82FgYABHjhyB2WxGZWUlcnNzF5XFoSGcuru7kZubS9XU0ePxgGEYqk3oNIWDzWaDXB6RyRSLguZrb2lpAZ/PX3iIJMeaJ6qiyeFwtJ49e5aKYZFAIKDqzL2em8GB6RId7SbiUB9GpHdxLlUwzUYsFqOoqAh79+6FUChEbW0tTp06BYPBMK+AcgcsF92WlnSx+Klu78Po6Cjq6+tx4sQJeL1e7Nq1C2VlZUuOM5rCyeVyYWxsDBkZGRFdZyFMJhPVLFOoCZxWMzRtqwWa5bm2tjYyMjJyPIJLBIPBIF1vHA4AwLm/w7xiIdp7N7t6enqoGeYIhUJ4vV4qTsJKpXLeLebRWn9ycpJaaj85ORmdnZ1U1p7Nhg0b0NLSgl27dkWkN2Ylgmk2AoEA2dnZyM7Ohs1mg16vx8DAADweD2JiYqBUKqFQKCCN4yPoB8BjAIYABEBQCE0SD0GnEOkyMdJkYiTFCGE36jAi4yE7Oxvx8fErfv3R6nHq7OxEQUEBdb81k8mE4uJiautbLBbq/lCZmZkL3zFC0LQbaG9v9zgcjtaF77lsWs1mc3FycrKVx+PRnfu0jgkGg4zZbFYAmPdvHe1PoI7W0F7go74iGjs/Qq7ktJrBVSoVWlpakJ2dvfCdI4BAIIBEIqGaYgemM25SqRSjo6NhzxqESzBdiFwunymLEEIwNTUFq9WKiYkJjPeNIM55MxAUAOCB701A3OAtqFAmQOLww2D3oGNsEuNTPijjpPjwpuvD+vmLtHCy2+1wOBwoLy8P6/MuFb/fD5fLRc0fCaDfT2Wz2aiJNq/XS9VUs6urKwDM0SwYJvx+/xdMJtMLJpNpI6Lfa8zxEUEArX6//wvz3SGqookQEtBoNJ5AIBBLozchLi4OdrudimgCpvuqnE4nFdEQGxsLt9sNv99P7WpNo9FgcHCQ6tU6ABQVFaG2thZJSUlh65GJlGC6EIZhEBsbi9jYWKSnp2PE5UPf8B9mfh/XdwccWa/B3H8D3u05v/dm0uFCp96MIk1KWGOKlHAihKC1tRUbNmygnmUyGAxUbBZCEEJgNpuxYcMGKusHg0EQQqj1lNntdqoXW+dGMeki9fwVFRWjAG6I1PNzhI+oK1qxWDxMq0xFu6+I9vopKSlU3bnT0tJgMpmo9pYB04abmZmZ6OjoCMvzRUswzYXbP3d/lix2bsPMU12RsZ6IRI+TTqdDbGwsVfftEIODg1RLUw6HA7GxsdREi81mo5plo71r0OPxeAgh9Bx6OVhD1EVTMBhsbGlpifayAOjPYaM9vDY1NRUmk4na+nw+HykpKRgZGaEWQ4js7GxYLJYVN4XTFEwA4ArMvSNRGuOe8/blzqFbDOEUTlNTUxgYGKCelQSmBYNAIIBUKqUWw3r3h6K5fk9PD8RiMf2p3xysIOqiaXBw8PjZs2eppBpCO+hoZTpoZ5ri4+NhsVio+iVptVrodBHLci8ahmGwadMmNDc3L3suH23BBFxsNxBCJJp7QPSZXj28ERxpEw7hRAhBU1MTNm7cSK2UPJvBwUFotVqqMdDuZ7JarVRFk91up5bpam5uRjAYbKSyOAfroJFp6mxvb6diOwAAMpkMdrt94TtGgNnN4DRgg1+STCZDIBCgajQaIjY2FpmZmcvybmKDYAIAd2DuTBlfOPf76/b5caYvssOLVyqcdDod4uLiqM13m43f74fZbKYqWDweDwghVP2hrFYrNY+m0Mw5WlYL7e3tQb1ef4LK4hysg8ansKurq4taUwvtbE+oGZwWKpWKaokOmC6N9fX1UY0hRGhL/1JKhmwRTMD8mSbw5r8wqOsZilA0H7Fc4WSz2TAwMECt4flChoaGoFarqQ6KpZ1lCmXnaWX9aPtDtbW1eXw+X3RccTlYT9SPBIQQk9lsDqzXEllCQgLGx8eprU+7GRyYbggfGxuDz0d/lBPDMKioqEB7e/uiMpBsEkwA4PLPLZr8jBV8PoPk+DgUZCdjU7EaGzemIylLjg+Ho1MeXapw8nq9aGhoQEVFBSvKcoSQmXl3NKHdz0TT3w2g30/V2toaBNBELQAOVkHl8kkoFFLbQUd7DptKpaLaCC0QCCAWi6lmuxiGQUZGBoaGIp/xWAxisRhbtmxBfX09vN65d50B7BNMAHBl+uO4KeuPuCHz97g+8xUoRdn4N+0b2J/5B3iVDIbhQIvFjFNGPer1BuitNpw1jsIyNXejeLhZrHAKBoOoq6vDhg0bqO7Smo3ZbIZSqaRihhsiVMqm+Z7QdkKnmWny+/2wWq1eQgi9HTwcrIKKaPJ4PP86fjySjvTzIxAIEAgEqDWDx8XFYWpqatnNx+GADSW6UEM4zfdhNnK5HIWFhaivr5/zs8FGwQQAIn4sZEI14sU5SBDngc+IIRdpIBUqIJfM3QMTJAQ1/ZHbRXchixFOra2tSE5Opnpyng0hZGbeHU3GxsaQlJRE1afKbDYjOTmZ2vo0Z941NDRAIpFEzNSSY/VBRTQZDIb3T506Ra0ZXC6XU9v6zzAMEhMTqZboUlNTqW/7FwqFUKvVGBgYoBrHbNLS0pCQkIC2tvPncrJVMC1EYlzMvL872Rc90QRcWjgNDAzA5/MhLy8vqjFditHRUUilUupZL9qluampKYjFYmrlUtrz9k6ePEksFsvfqSzOwUpodTfWnzlzhppRWFJSElXRQrtEJ5VKEQgE4HZHp0QzHzk5ORgcHGRFb1OIgoICeL1edHVNX1yuVsEEAImxlxBNvdG3fZhLOOn1euj1emzatIm663cIQgg6OjpQVFRENY5gMIjx8XGq5p60m9Bpv/5Tp065x8fHj1ELgIN10BJNeqPRGKRVIktKSsLY2BiVtQHMZJpo+iVlZmZicDC62YYLCQ2l7enpoRrHbBiGwebNm2G1WtHa2rpqBRNwadE0bLFhcMISvWDOMVs4nT17Fv39/di2bRs1p+u5GB4eRmJiImJi5n//okGol4jmzj3a/Uyh8iQtWlpaggAaqAXAwTqofBsJIUQkEg339vbSWB4xMTFwuVzURAufz4dUKoXD4aCyPgCo1WoYDAaqwg2YFm8jIyPUs16z4fF4yM3NhU6nQ0pKyqoUTMClRRMQ/RJdCKFQiKysLPT390Or1VIdxHohgUAAPT09yM/Ppx0KdDod1dEtfr8fHo+H6ud/YmKC2qzQQCAAi8XiJYRYqATAwUqoXcLQbAYH6I9Uod1XJBAIoFQqqWbcgGmBkp+fP1MOYwMWiwXNzc2oqqqC0+lkVWxL4VI9TQCdEh0wXZLT6XS4/PLLMTAwELZZdeFAp9MhPT2dqpEkMN1LFAwGqfZUjY2NUW0A9/l8YBiGWj9VY2MjJBIJnW3eHKyFmmii3QxOu0THhhlsbBlpkp6eDovFwgqX8Nk9TDKZDBUVFXA4HKFRCrTDWxILZZpODQwjGIxeppEQgt7eXgwMDGD79u2IiYkJ+5DfleDz+aDT6ajvmAPoZ5kArp/pxIkTXBM4x0XQK5azoBmcpmgKNWPTbIJWKpVwOp3weKhpVwDTfURFRUXo6OigGsdcTd88Hg+bN2+GRCJBTU3NJX2c2EZC7KUHzFpdbrQZoyPcA4EAzpw5A7vdjp07d86U5MI55Hel9Pb2Iisri7qxZjAYhMlkQnp6OrUYCCFUS2MA/X4mrgmcYy5oiqZhvV7vp+XTQ7uvCQCSk5MxOjpKbX2GYViTbUpJSYHP56MmZC+1S45hGBQUFCA7OxsnT56kao66FJIW0YtyojfyfU1utxvV1dVQKpUoLy+/qLGZDcLJ6XTCZDJRH8wLTDdfJycnU22Ot9lskMlkVJvQx8fHqYq2hoaGIIA6agFwsBJq3whCCJFIJM3V1dW0QoBCoaA6UiUtLQ0GQ2SHpy6ERqOBXq9nRemprKwMra2t8Pujm4BcrK1AWloatmzZgoaGBurmoIthoUwTAFRHuBncYrGguroahYWFyMnJmddWgKZwIoSgsbERZWVlVEVCiP7+fmRnZ1ONwWAwUPWH8vl84PF41LJ+ExMTmJqasnFO4BwXQvUIodfrf//uu+9SK9ElJydTncOmUCjgdDqplugEAgFSUlKoizdgOvuXlZWFs2fPRm3NpfowyeVy7Nq1C/39/Whubo66wFsKSXELv54zQwa4vOH//AWDQXR1daG5uRnbtm1bVEMxLeHU398PpVJJNasRwmKxQCAQUN2xRgihbqppNpuplubeffddMAzzD2oBcLAWqqLJ7XZ/cPjwYWoNNbRNJhmGQXp6OvVejpycHPT391ONIYRWq4XT6YxKmW65xpUikQg7duyAXC7H8ePHqe9AnA+JUIAY0aW383sDAdQN6sO6rs1mw4kTJxAMBrFnz54lvbfRFk5OpxODg4PUjSxD9PX1UW9En5ychEKhoNrbZTQaqYq2f/7znx6dTvcGtQA4WAvtXHTfwMAAtb4mkUgEHo9H1SNIo9FgeHiY2vrAdFO6RCLB5OQk1TiAaSG5adOmiJfpVur0zTAMsrKysG3bNnR1daGlpYWVWaeFdtABwMkw9TUFg0F0d3fPlLqKioqWVe6KlnCaXZZjg7mm2+2G3W6numMMAIaGhqDRaKitHwwGYbVaoVQqqcVQXV3tB0DPE4eDtVAVTaG+ppMnT1KLgXa2KSYmBsFgEC6Xi1oMAJCbm8saZ26pVIrs7OyIlenCORolJiYGO3fuhEwmw/Hjx1lhGDqbxYimcPQ1jY+P48SJEwgEAtizZ8+Kp9JHQzixqSwHTMeTlZVFdZxMMBjExMQEVX+myclJJCQkUHsfxsfH4XK5bISQ1bHjgyOq0M40hfqaqI26T01Npd7UG2rGpklCQgL8fj/VxvjZZGZmwul0hr3nLBKz5EJZpx07dsBsNrOqZLcY0dQ5Ysa4Y2pZz2+z2VBTU4Pe3l5s2rRp2dmluYikcHI4HBgaGmJNWc7tdmNkZAQZGRlU4xgdHUVycjJV4Ua7n+q9997j+pk45oW6aDrX10StPhYXFweXywVaJUJg2tyRtmgCgOLi4qg2YV+KUJmura0tbI3ykR6+K5FIUF5ejs2bN6O/vx/V1dVUXeeBhV3BAYBg6SNVpqamUF9fj5aWFhQWFmLbtm0Rca+OhHAKBoNoampiTVkOALq6upCfn099997w8DDV0hww3QROM9PF9TNxXArqoglAn06no9bXBNDfRScSiSCVSqmfYBUKBUQiEVXvqNlIpVIUFBSgvr5+xSWvSAum2cTFxWHr1q3YsGED2tracOrUKYyNjVEp2y0m0wQsvkRntVpx5swZ1NXVISMjA7t27UJ8fPxKQlyQcAuntrY2JCcnRzzuxeJ0OmGxWKiaWQKA1+uF0+lccWl1JdjtdkilUqpilutn4rgU1EXTub6mJpp9TWwo0WVlZWFgYIBqDACwYcMGdHR0sKYvJz09HUqlckUZsGgKptkolUrs2rULhYWFGBwcxNGjRzEwMBBVi4nFeDUBlxZNgUAAer0eJ06cQEdHBzQaDfbu3YuUlJSolXHCJZx0Oh08Hg8rBvKGaG9vR1FREdWSGDDdAJ6RkUE1jpGREaqlufHx8ZA/E9fPxDEn1EUTAAwPD//unXfeobb1KCEhAZOTk9TdwScmJqh6NgFAbGwslEolK3ybQhQWFsLpdGJoaGjJj6UlmGajVCqxZcsWbN++HT6fDydOnMCZM2cwMjIS8bJw0iIzTUabHX1jEzM/E0IwPj6O1tZWHD16FFarFZs2bcL27dup9bysVDiNj49jcHAQmzZtoi5QQlgsFni9XqSkpFCNgxAyI5poYjKZqM67e+eddwDgb9QC4GA9rBBNHo/nnXfffZeaXxPDMIiPj8f4+DitEMAwDNRqNSt6mwoKCtDd3c0Kl3Bg+r3ZsmUL+vr6lmSLwAbBNBuJRIL8/Hzs27cPGRkZMJvNOHbsGGprazE4OBiRGYAJixRNAHCyewAGgwENDQ04fPgwhoaGkJSUhH379qG4uJgV7+FyhdPU1BSam5tRWVlJfbbcbNrb21FcXEw7DIyPj0Mul8/MBKSBy+UCwzCQSCTUYnjzzTddQ0NDv6EWAAfrYcXRgxAyotVqLUajMTYtLY1KDBkZGRgcHKTqQqvValFTUwOtVkv1SlgikUClUmFwcBBZWVnU4piNQCDA1q1bcerUKezYsQNS6aXLTmwTTLNhGAZJSUlISkoCIQR2ux0jIyM4ffo0CCFQKpUz/+Li4lb0WUi6RCN4vEgATYwYaqkImlgxAsYhWJXTdg9KpZI12ZgLCQmnmpoaANPjbS6F3+9HXV0dysvLF/zcRBOz2QyBQEDVjyhEf38/8vLyqMZAuwk9EAigoaHBD6CGWhAcrIcVogkA3G73K6+//vo37733XirZr4SEBDQ3NyMQCFBrQhSLxYiLi8P4+DhV8QYAeXl5OH78ODQaDWuuzGNiYlBaWoq6ujrs2rVr3r8TmwXThTAMA7lcDrlcjvz8fHi9XlitVlgsFnR0dMDpdEIgEEAul0MqlUIsFkMikcz8EwqFc4obQgj8fj8kIMiJk0Au5EMmFEAh5CNVKkIsn49Jrx96lwcDTjeOm20An4+aG6+HgM+KBPQlWaxwIoTgzJkz0Gq1rPFjAqbj6ujowObNm2mHApfLBbfbTb0x3mAwYNeuXdTW//DDDyESiU4TQujtSuJgPew4GwIYHR197e23377n3nvvXXw9IYwwDDNjdElzF0tOTg56enqoiyahUIjMzEz09fWhoKCAaiyzSUpKQkZGBhobG7Fly5aLBMNqEkxzIRKJkJycfN6Wa5/PB5vNBrfbPeMaHfr/C3vg7HY7Dh8+DGA6OyeRSFCijIXV64fNF4BhyoPDI1Y4/HOcF/x+tBpN2KShu4trsSxGOHV1dUEqlUKr1UY7vEtiNBohl8sRFxdHOxQMDAxQzyhbrVZIpVKq5cE33njD09/f/zS1ADhWBawRTQDauru7vVNTUzExMVR0EzQaDdrb26mKpvj4eLjdbkxNTYHW+xAiKysLR48eRVZWFkQiEdVYZpOVlQWn04mWlhaUlpbOCKfVLpjmQygULnq0xuHDh3HZZZedd9t9hxtgdjgvuq9ULIBGJUecQgS30IcB1ySOjPetGtEEXFo49fX1wWq1orKyklZ4cxIaZrxjxw7aocDv98NkMqGqqopqHLRLcwDw4Ycf+gkhnKklxyVhTR6eEEIEAsF7f/nLX6jFIJfL4fF44PV6qcUATJfG2DDShM/nIz8/nzWGl7MJNc+ePXsWhJA1K5jCwQZtMorzkrFpYyo2b05F4ZYEJG4Uw6J2okVgRLVThzMWAyY9Lhw3DtAOd8nM1Rw+MDCA0dFRVFZWUjeMvJC+vj6kpqZSbXgOodPpoNFoqPoiEUIwOjpKdddce3s7/H7/ECHEQS0IjlUBq44mOp3u+YMHD9KbnotpXyDa2+1TU1MxOTlJdZBwCLVaDY/HwxrDyxAMw6C0tBQ+nw+NjY2cYLoELqUXDcFh1EzpUG3VoclihH7KhrkMNhrHDHD66F40LIfZwqmlpQUGgwFbt25lnWCy2+3Q6/Ws8IkKBoOs2OwxPj6O+Ph4qsLtD3/4g398fPxZagFwrBrYdUQBjlVXVwdobnVnw7Z/hmGQk5ODvr4+qnGEYikrKwvrOJNwwTAMtFotjEYjEhISqJcz2UqSdPHviy8YRM3Iygf40kAoFEKj0WBwcBCZmZmsGZESghCCpqYmlJeXsyK24eFhpKamUu0jCsVBuzT317/+1Wu32w9RDYJjVcAq0UQI8YpEohaa7uBSqRQMw8DpvLgHJJqo1WqMjIywQqhIpVLk5eWhra2NdijnYbFY0NTUhKqqKgSDwZlSHcf5JEmWln07ZuiPUCSRZWBgACaTCVdeeSX6+/vDPuR3pfT29iIxMZEVFgOEEPT19SEnJ4dqHH6/H5OTk4vu2YsEY2NjMJvNNkLI0t1zOdYdrBJNADA8PPz0a6+9RlUpaLVa6HQ6miGAx+NBq9Wiv58dJzCNRsOqMt3sHqa4uDiUl5cjEAigpaWFE04XkChZWgbuhJHuZ3859Pb2YmRkBNu2bYNEIgn7kN+VEirLFRYW0g4FwPTuvcTERIjFYqpx6PV6pKenU/UEe/3114nf7+cG9HIsCtaJJq/X+9bf//53L80SXVpaGkZGRqg7Ymu1Wuj1+oiP2lgMDMOgvLycFWW6uZq+Qz1OfD4f9fX1rHjP2MJSRVO3dQwjU/YIRRNeCCE4e/YsJiYmsHXr1pmyV7iH/K40xlBZjg09VoQQ9Pb2Ijc3l3YoM6VUmrz66qsuo9HI9TNxLAr63+ALIIQ4GIZp+PDDD6nFwOPxoFKpqB9s+Xw+NBoNa7JNEokEeXl5aG1tpRbDpXbJMQyDkpISJCUl4eTJk3C5XJSiZBdJ0qU3x6+GXXQ+nw+1tbVgGGbOXXJsEU49PT2sKcsB00Nx4+LiqPcAWiwWiMViqi7ter0eQ0NDVkJIO7UgOFYVrBNNANDf3//jF198kerWMa1Wi4GBAZohAJg2uxwaGqJugxBCo9HA6/ViZGQk6msv1lYgKysLxcXFqKmpwcTExLz3Wy8stacJYL9ocjqdOHnyJDQaDTZs2DBveYe2cLLb7TAYDKwpywWDQXR2dqKoqIh2KNDpdNR37r3wwgv+qakpztCSY9GwUjQB+OfRo0d9NIVCbGws+Hw+bDYbtRiA6WxTbm4uuru7qcYRIlSmO3v2bFTLdEv1YUpMTMT27dvR2tqKwcHVuRssXCQtsTwHsLuvyWw2o7a2FuXl5VCr1Qven5ZwIoSgsbGRNWU5ABgaGkJycjL1GXw+nw+Tk5PnOd/T4I9//KN3YmLiJapBcKwq2PFNvgBCiI/P57/75ptvUo0jJyeHFaWxjIwMjI2NYWpqinYoAKJfpluucWVMTAx27dqFkZERtLa2rtsG8cRlZJpGXQ50TpojEM3yCe346uzsxM6dO5dU7qIhnHp6epCcnMyaspzf70dfXx8rPKIGBweRkZFBtQG8tbUVDodjiBDCjt0CHKsCVoomABgcHPzpSy+9RLUpJTk5GZOTk9QbnxmGQVFREdrb2VN212g08Pl8Efe0WqnTt0AgQGVlJYRCIWpqaqj/LWkg4vMhEy59lxSbSnTBYBBNTU2wWq3YuXPnsty0oymcJiYmYDQaWTW3sbe3F5mZmdR9mQghGBoaot4A/utf/9prMpkOUA2CY9XBWtEEoLatrc1ltVqpBcAwDDIyMlhR3klJSYHH4wHN92M2DMNg8+bN6OnpgcViicga4RqNwjAMCgsLodVqcfz4cdbYJkST5CU0gydIJNiWroLey473yWq14tixY5DJZNi0adOKjCGjIZxcLheamppYNcLF4/HAaDQiOzubdigYHR1FfHw8VfEWDAbxzjvv+Dwez0FqQXCsStjxjZ4DQggJBoO/e+WVV6ju+8/MzMTg4CB1+wGGYVBcXMyqOXBCoRCVlZU4c+ZM2Ee+RGKWXHp6Onbu3In+/n40Njauq6zTfLYDCpEIG5MTsTczFXuzklGslsAvnUCHqx9/NZyBL0jPuiEYDKKjowPNzc3YvHkzcnNzw1LOiaRwCgQCqKurQ1lZGfXdabPp7OxEfn4+K0RcT08PdVPNo0ePgmGYRkLI6vDW4GAN9L9Bl8BoND79+9//nuouOqFQiNTUVAwPD9MMAwCgVCohEolYlSmJjY3Fxo0bUVdXFzZvpEgO35VIJNi2bRsSEhLWVdZpY1ISdmekokqbiqqsFFRmyqFVASTWgkH/EJrsfWiy6jA89dFuQ1fAi6ZJOibJVqsVx48fB4/Hw+7duyGXy8P6/JEQTqHG78zMTKoO1xficDhgtVqRnp5OOxRMTExAJBJBJpNRjePXv/61u7+//8dUg+BYlbBaNBFCuo1G4wTtrf+hOXBsaCQuKipCR0cHK2IJkZycjPT0dDQ3N684rkgKphAMwyAzMxM7duxAX1/fusg68UU+tDj60GjrQ6N1AF12Eya9C28sqDH3RiG6j5idXdq0aRMKCgoilh0Jt3Dq6emBUCiEVqsNQ3Tho729/ZK2DNGku7ubeiO6x+PB0aNHfQDeoxoIx6qE1aIJAKxW6//+4he/oHpGE4vFSExMpG52CUxndhISEliR+ZpNdnY2GIZZ0ZDhaAim2UilUmzfvn1dZJ0SxMt7P2vGoieaIp1dmotwCSeTyQSz2YyNGzeGMbqVMzExgUAggKSkJNqhwGazIRgMUt9N+Lvf/S7I4/H+RAhZ21dKHBGB9aLJZrO9cujQIS/tsRi5ubno7e1lRYanoKAAPT09rDG8BKazN2VlZTCZTMsSH9EWTCFmZ50GBgZQW1sLu33ttTkkiuOW9bg2iwE2X2Q3sbpcLjQ2NqKlpSXi2aW5WKlwstvt6OjoYFXjNzCdtWtra0NxcTHtUACwI8sEAM8884x7aGjoR7Tj4FidsOcbPg/nxqq898YbdOcpxsTEIDY2FmYzfe8akUiEgoICquNM5oLH46GyshJnz56Fw+FY9ONoCabZSKVSbNu2Dbm5uWhqasKZM2fW1BiWBNHy3tcACeL0WGS8yrxeL9ra2nDq1CmoVKqoZZfmYrnCyev1or6+Hlu2bIFIJIpghEunp6cHKSkp1N7T2TidTrhcLuq9Xi0tLRgfHx8mhLDDLZhj1cF60QQAOp3ukaeffpr6GSw/Px89PT20wwAAqNVqBAIBmEwm2qGch1gsxubNm1FXV7eoPiE2CKbZJCYmYvfu3UhLS0NtbS3a2tpYldFbLsvNNAFAzdjyS65zEQgE0N3djRMnTiAuLg5VVVVIS0uj3nOzVOEUDAZRV1eHoqIiVgiT2dhsNphMJlZkdoBpAZeXl0f9b/zEE094DAbDQ1SD4FjVrArRRAhpHhwcNNMeJSKTySAQCFgzz6ysrAzt7e2sO6krFAoUFBSgvr7+klYNbBNMIRiGQWpqKqqqqiCTyXDixAl0dXXB7/fTDm3ZLLenCQhfM3gwGIROpwtt90ZVVRW0Wi2rSlqLFU6EELS2tiIpKQmpqalRjHBhgsEgGhsbsWnTJla8t263GxaLBSqVimocU1NT+Oc//+nx+Xx0R01wrGrof6MWydjY2EM/+clPqKuDgoICdHZ20g4DwHRWp6CgAC0tLbRDuYj09HQkJyfPK5zYKphmE+p3qqqqAp/Px7Fjx9Dd3c06kboYViKadM5xGKcsy3683+/HwMAAjh49CqfTiT179iAvL29FJpWRZCHhRAhBe3s7CCGsyeTMpru7GyqVijXZr+7u7rB5bK2E5557LhAMBl/mGsA5VsKqEU0ul+v//va3v3mcTifVOJRKJQQCAcbGxqjGEUKtViMYDLKuTAdMN88rFAqcOXPmvAb61SCYZhMamrx3714IBAKcPHkSjY2N1Ic5LwW5UAoRT7Dsx1cvYxedy+VCW1sbjh07Bq/Xi507d6K4uJj6GI/FcCnh1NXVBY/Hg7KyMupC4EJsNhtGRkZYI+ampqYwOTm5qMHKkebXv/61x2g0ct5MHCti1YgmQoiXEPLy888/T9eaG8CGDRtmrjTZAFvLdMB0Zi42NhZNTU0ghKw6wTQbgUCA7Oxs7Nu3D+np6Th79ixOnDiB4eHhsBl7RpJ40fIdqhdboiOEwGQy4dSpU6ivr4dCocC+fftQUFAAsXjp8+9oMpdw6u7uhsPhwKZNm1gnmNhWlgOmPaKKioqov1fvv/8+3G53EyHEQDUQjlUPw5YT/2JgGCa9qKiou729nfp8gqamphlTRzZgMBhgNBpRUVFBO5SLIITg7NmzmJqagsPhwLZt21adYJqPqakp6HQ6mEwmJCUlITMzE3K5nNpJ4vDhw7jsssvm/N2tR59Bu3V5XkTxolgc/vgD874up9OJoaEhGI1GJCYmIisrizXloZXi8/lQU1ODuLg4+P1+VFRUsEaUzCbUNlBYWEg5kmmsViva2tqwc+dO6qLpmmuucb333nsfJ4QcpxoIx6qHfd/8S0AIMbjd7oZ3332XdigoLCxEV1cX9Zl0IdLT0xEMBllhwHkhDMMgPT0dY2NjkMvlrJrJtVJiYmKwYcMG7Nu3D8nJyeju7sbhw4fR3NyM0dFRVmWgVrKDbtLrRIftoxIwIQQTExNoa2vD4cOH0dLSgtjYWFRVVaGsrGzNCCZgOuOkUqlgNBqRnp7OSsFktVoxOjrKmrIcwB4n8v7+frS1tVkAnKAaCMeaYPlNDpQYGBj47+9///snrrnmGinNOCQSCVJSUjA0NMSasQllZWU4efIkEhMTWeUZY7FY0NTUhL1790Kn082UEGgfTMMJj8dDamoqUlNTEQwGMT4+DpPJhLa2NsTFxSE1NRUqlYrq32W5Xk0hakw9UDiny28WiwXx8fFITU1FYWEhBIJVdyhZNF1dXbBarbjyyitRW1sLHo+HtLQ02mHNEAwG0dTUxKqy3Pj4OHg8HuLj42mHgu9973ue8fHx+8lqKqtwsJZVd6QjhJzJysrqr6mpKd6xYwfVWPLz83H8+HFoNBpW7AQSi8UoLCxES0sLa8p0F/YwFRcXo7OzEw0NDdi8eTNrDvLhhMfjITk5GcnJySCEwG63z/T5MAyDpKQkKBQKKJVKSCSSqInHpWaapISPdMRAjVhoSRx4PaOwZE+X3uLj49eU6J0LQgg6OzvhdDpnSnI7duxATU0NALBGOHV3dyM1NZU12b3Q7sLy8nLaoWBkZAQffPCB0+VyvU47Fo61waoTTQCg0+m+8vDDD7/73nvvSWjGIRQKkZGRgb6+PtakxdPT02f6m2gf1Odq+mYYBkVFRejq6kJ9fT1r+0PCBcMwkMvlkMvlKCgogNvtxsTEBCwWCwYGBuB2uyGVSmdEVCSF1KVsB2KI4JxAikE6iUECxJiCHwZMwcBMoZmZgBsExwtvhIi/Kg8bSyLUh+f1erFly5aZv0eoOZwtwilUltu9ezfVOGZjMpkQFxcHmUxGOxT84Ac/8Dqdzu8RQlavyRoHq1itR7+j7e3tI21tbdqSkhKqgWRnZ+Po0aPIzMxkze6g0tJSnDx5EgkJCdRiWmiXXEFBAXp7e3Hq1ClUVlauim3o4UAikSA9PX1mAwEhZMb8z2KxQKfTweVyQSAQQCwWQyKRXPRPLBZDJBItSlgRQuD3++FyuRDv5qGcJCAOQsiJEDIIEQchpODDOUsgtTCTmIQH5MKnDwINEzrsSM6NwDvDHoLBIJqbm8Hj8eYsI7NFOAUCAdaV5QKBADo7O7F9+3baocBqteLNN990WyyWX9OOhWPtsKp2z81GKBTecOONN75+8OBBqtkmADAajTAajdiyZQvtUGYYHR1Fd3c3du7cGfUD6lJsBQwGA7q6ulBRUcGKK1O24Pf74fF44Ha7Z/7N/nk+ewm73X7R+ygUCiGRSDAecOGQqRF2+M7752UWv5nh7rw9uHfDx1f02tiMx+NBXV0dUlNTkZOTc0lhGtpVl5eXF3XhRAhBY2MjFAoFcnJyorr2pejq6gLDMKzIvH/nO9/xvfDCCz8aGRn5Hu1YONYOq1Y0MQzD02g0hmPHjqmysrKoxkIIQU1NDQoLC5GQkEA1ltl0d3fD5XKhrKwsamsux4fJZrOhoaEBGzZsoD5qYbVzKcuBDqsRnz76zIqev1iRjv+r+tKKnoOtWK1WnDlzBsXFxUhJSVnUY2gJp76+PlitVlZtqHC5XDh16hSqqqqoZ77cbjcKCgocQ0ND6YQQO9VgONYU7MjpLgNCSHB8fPyBRx991EM7FoZhUFpaitbWVtYYXgJAXl4evF4vdDpdVNZbrnGlXC7Hzp070dPTg56eHla9h2uJlYxSCdFhNcLinQpDNOzCYDDgzJkzqKysXLRgApY+5DccjI2NwWAwsM6RvLW1FcXFxdQFEwA8+eSTgUAg8BtOMHGEG/qf7hXgcrle+8c//jFlNptph4K4uDgkJyejv7+fdigzMAyDTZs2QafTRXzI8EqdvsViMXbu3Amn04kzZ86wyt9orZAgigWDlZ1kgyCoHesLU0T0IYSgo6MDg4OD2L17N+Lilu5lFU3hNDU1NbM7lg07dkOMjo4CwJIEZ6Tw+/149tln3QaD4RHasXCsPVa1aCKE+Kempr7/wx/+kBXzQ/Lz86HT6eDxUE9+zSAQCFBZWYmmpia43e6IrBGu0Sg8Hg/l5eWIj49HdXV1xOJdrwh4fMiFK28BrF7kSBW24/f7cfr0aQQCAWzfvn1FmxGiIZz8fj/q6upQXl4OqZSqTd15BAIBnD17Fhs3bqQdCgDgpZdeCvr9/rcIIeO0Y+FYe6xq0QQAk5OTzxw8eNDFhgG6AoEAhYWFOHv2LO1QziMmJgalpaWoq6sLewYnErPksrOzUVhYiOrqakxOToblOTmmWYkreIi1IJqmpqZw4sQJpKWloaSkJCxlrkgKJ0IImpqaoNVqWdU3CQC9vb1IT09nhZDz+/147LHH3ENDQ9+iHQvH2mTViyZCiNvhcHznwQcfZEV6Jy0tbcaLh00kJSUhPT0dLS0tYesZiuTw3eTkZGzbtg3Nzc0YHh4O63OvZ8LR12RwWTDkZNfneymMjY3h1KlTKCsrQ0ZGRlifO1LCqbe3F0KhkDXTB0K4XC4YDAbk5eXRDgXAdC+T1+t9gxDCHTQ4IsKqF00AYLVan/v73/9uY0M/UagpvKWlhXV9OdnZ2QgGgxgYGFjxc0VSMIWIjY3Frl27YDKZUF9fP+82e47Fs9JRKtpYOapSU9FuW33ZpkAggLa2NnR2dmLHjh0RG/ERbuE0OjqKkZER1pS/QoSyXyUlJaxo/p6amsIvfvEL99DQ0Ndpx8KxdqH/SQ8DhBD/xMTEV++//35WNMHExcVBo9HMTB1nCwzDoLy8HMPDw1hJOTMagimEUChEZWUlUlNTceLECZhMpoUfxDEvSynPxQqE2BifiH1pqbgiPRGlSQEEBYPod3WgbrI5glGGn8nJSRw7dgwSiQS7du2KeCkpXMLJ4XDg7NmzqKysZIUwmc3g4CCkUimSk5NphwIA+OEPf+jzer1PEUJWbxqUg/Ww61u4Alwu18Ha2trRpqYm2qEAAHJycjA5Ocm6nhw+n4+tW7eitbUVVqt1yY+PpmCajVqtxq5duzA0NISGhgYu67RM5irPiXh85MqU2JGiwhXpqbhCnYCKFB4SY8dgDfaib6oD3c5eWHwf7d5usnQjSBZvikmLUJNySHjk5uZGbZv+SoWT2+1GXV0dNm/ezJppAyFcLhf6+vpQXFxMOxQA0wOCX375ZZfJZPo+7Vg41jZrRjQRQoher//81772NVZkm0JZnebmZtaV6SQSCSorK9HQ0ACn07nox9ESTCHEYjG2bt0KlUrFZZ2WSbZMjivVKbgsXYmdqRKUJQWRJpuElzcAvacT3c4OdDv6MOqZAMH8vW8O/xS67UNRjHzpTE5O4vjx4xCLxdi1a9ey7ARWynKFk8/nQ21tLTZu3AiFQhHBCJdOqCy3ceNG1ow/+s53vuN1uVz/QwhZeyZiHKxizYgmAAgEAh92d3f3Hj58mHYoAD4q03V0dNAO5SLi4uKwefNmnD59elEWCbQF02xCWafBwUEu67REZEIBuhxd6HUOYNhlwqTPhiCWlzFqtLCr/BwilF1qa2tDRUVFVLNLc7FU4RQIBFBbW4v8/HwkJSVFIcKlwbaynE6nw1/+8hfbxMTEr2jHwrH2WVOiCQCGhoZuv//++1204wiRk5MDi8XCut10AKBUKlFcXIza2lr4/fMPAWeTYArBZZ2Wh0IYvmzLmUn2XQzMzi4t16wyEixWOBFCUF9fD7VaTW0Q8KVwuVzo7+8H7UHps3nggQfck5OT/00I8dGOhWPts+ZEEyHkzOjoaO2f/vQnVsziYHOZDph28M3Ozsbp06cRDF6ccWCjYArBMAzUajV27tw5k3Vik7EoG4kXhW8ocrutH+4AO7J8fr+fVdmluVhIOBFC0NzcDIVCAdrzNOciNCS4pKQEAoGAdjgApke3nDx5cnxqaup12rFwrA/WnGgCgMHBwf/vO9/5jutS2ZNoEhcXh4yMDLS3t9MOZU40Gg1SUlJQX19/nnBis2CajUQiwdatW5Gamorq6mp0dHTA5+MuOudCIQyfaPKTAFqtPWF7vuUQDAbR19eHY8eOQSqVsiq7NBfzCSdCyMzxoaCggFZ4l0Sn0yEmJoY1ZTkAuPfee90Gg+HzhKyCXQkca4I1KZoIIb0Oh+PV//3f/2WHasJ0mc7hcGBkZIR2KHOSm5sLpVKJM2fOgBCyagRTCIZhkJ6ejqqqKojFYhw/fhy9vb2szO7RJEYggZgXvubdRktX2J5rKRBCMDw8jKNHj8Ln82Hv3r3Izs5mXXZpLuYSTp2dnfB4PKwbwhvCZrNBp9Oxqiz35ptvkq6urpZAIPA+7Vg41g/MWp0ozzBMnFqtHjp16pRSrVbTDgcA4PF4cPLkSezYsYMVIwfmorOzE5OTk3C5XNi2bduqEExz4ff70dfXB71ej7y8PGg0GlaejMLN4cOHcdlll13yPned+h5GPeHpscuOTccvK6I3sYIQgtHRUXR2diI+Ph4FBQWs246/WHw+H2pqaiCVSsHj8bB582ZWfkb9fj9OnDiBzZs3Qy6X0w4HwPSxtKSkZKq3t7eEEDJAOx6O9cOazDQBACHEMTk5+ZWvfvWrrLAgAKabl0tLS9HQ0DBn/xAbUKlUsFgsiImJQUxMDO1wlo1AIEBBQQF2794Nm82Go0ePwmQyhW2EzGpGKQpf+WrAacSk1xa257sUExMTOHnyJPR6PSorK1FaWrpqBRMwnXFKTEyE2WxGamoqKwUTALS0tCArK4s1ggkAHnroIe/U1NSvOMHEEW3WrGgCgKmpqf9raGjoe/999mRvk5KSkJSUxDq3cOCjHqa9e/dCqVRe1OO0GhGJRCgpKcG2bdtgNBpx8uRJVu5kjCbKMPY1ERA0RbhEZ7fbUVtbi+7ubpSWlmLLli2rWtADH/Uwud1uXHnllejt7Q37kN9wMDQ0hGAwiMzMTNqhzNDb24vXXnvNbjQaH6IdC8f6Y02LJkIIGRoauvm///u/WdMUDkw3ek5OTsJsNtMOZYYLe5gKCwshl8vXhHACAKlUis2bN6O0tBTd3d2oqanB2NjYusw8hbMZHADOTEbmAsBqtaKhoQFNTU3Izc3F9u3bWZXtWC6EEJw9exYejwebN2+GSCSKyJDfleJwONDb28u6PqsvfelL7pGRkTsIIaypInCsH9a0aAIAQkiHzWZ77cCBA6xRTQzDYMuWLWhtbYXbTf97P1/Td0FBARITE3Hq1Kk1sxtNLpdj+/btKCoqwuDgII4ePQqdTreuGsbDaTsAAI1hFE2EEBgMBpw4cQIdHR3IyMjA7t27kZiYGLY1aBIMBtHY2IhgMIjy8vIZMRLuIb8rJRAIoKGhAZs2bWKN6zcw3fzd2dnZ4vP5/kY7Fo71yZptBJ9NqCn89OnTSjYZxo2OjqK3txc7duygdiW3mF1yer0efX192LZt26ruIZkLt9sNnU4Hg8GA1NRUZGVlsbZJfzEsphH8reEP8Xzfm2Fd99nK7yAjRrXsx3u9XgwODmJoaAhJSUnIyclZtZsQ5sPv96O+vh7x8fHIz8+f8zsfag7Py8ujam7Z1NQEmUyGnJwcajFcCNf8zcEG1nymCfioKfwrX/kK/bTOLFJSUqBUKqn5Ny3WVkCtVqOwsBDV1dVLmlW3GpBIJCgsLMS+ffsQFxeH+vp6nDp1CiaTaU2UJedCGeZME7A8d3BCCMbGxlBfX4+TJ0+Cx+Nhz549KC0tXXOCyev1oqamBqmpqSgoKJj3IokNGSedTgefz4fs7Gwq68/H//zP//impqae4QQTB03WhWgCppvC6+vr+/7xj3/QDuU8ioqK4HA4MDw8HNV1l+rDlJKSgk2bNqG2thZWqzUKEUYXHo+HjIwM7NmzBxs2bIDZbMaRI0fQ3t6Oqam1NQM0nI3gIZYyh87j8aCnpwdHjhzB4OAgsrOzsW/fPuTk5LCqFBQuXC4XqqurkZeXB61Wu+D9aQqniYkJ6HQ6bNq0iVV9TN3d3fj9739vMxqN36UdC8f6hh1e+FGAEEIYhrnhy1/+cnNzc3MMW65kQ/1NJ06cQGxsLOLj4yO+5nKNK5VKJbZu3Yq6ujqUlJSwyhk4nMjlcpSWliIQCMBoNKKxsRGBQAAqlQqpqamQyWSsOqEslUhkmlosPQiQAPgMf87fO51OmEwmjIyMIBAIQKPRYPfu3WtSJM3GZrOhoaEBZWVlSEhIWPTjQsKppqYGAKJSqnO5XGhqasKOHTtYMyYFmO4D+3//7/+5TSbTp7jmbw7asOebEQUIIb0pKSk/+M///M+Hf/Ob37CmOUcgEKCyshK1tbURN75cqdN3XFwcduzYgbq6Otjt9lXjwrwc+Hw+NBoNNBoNvF4vRkZG0NnZCYfDgaSkJKhUKiQlJYHHW10J20hkmqYCbnTadChWTPfAEEIwOTkJk8kEs9kMsViM1NRUbN68eVX3jC0Fo9GIzs5ObNmyZVm7/qIpnPx+P06fPo3y8nLW/X0ee+wxv9FofCcQCBymHQsHx7poBJ8NwzA8jUbT8cILL+RfffXVtMM5j7GxMbS3t2PXrl3g8+e+Yl8J4RyNEggE0NLSAkIIysrKIhIvWwkGgxgbG4PJZML4+DhkMhlUKhVUKhVEIhHV2BbTCB4kQdx47D4EEd7v/m2aa3C5dDNMJhMsFguUSiVSU1ORnJzMqsxFpCGEzDjrV1RUrPgzEenmcEII6urqkJKSsqjyYTTp7u7G5ZdfPqHX67WEEAfteDg41p1oAgCGYXJzcnJYVaYL0d/fj4mJCWzZsiWsGZxIzJIjhGBgYADDw8OorKxk3RVqNCCEwG63w2g0YnR0FDweDykpKYiPj4dCoYh6+WkxogkAbqv+Diw++4rW4hMeEgNxSPbLofEnIoGRYYt2I1JTUxEfH79mM5CXwufzoaGhAXFxcSguLg7bexBJ4dTZ2Qmfz4eNGzeG9XlXSjAYxI4dO9z19fXXclkmDrawfi7/ZkEI6U1OTn70q1/96iO//e1vWVOmA4Ds7GzYbDb09PQgPz8/LM8ZqeG7DMMgOzsbMpkMNTU1KC8vX1LfxlqAYRjI5XLI5XIUFhbC7XZjdHQUBoMB7e3tCAQCiIuLg1KphEKhgFKpZEUfj0IYtyTRxCc8JAVkSPLLkBSQISEQhyAIJvgOjAnsOCntwpTAg5sKbkCMQBLByNmLw+FAfX09cnNzodFowvrckSrVGY1GTExMYPv27WF5vnBy4MABv9FofJsTTBxsYl1mmoDpMp1arW5/8cUXC9hWpgsGgzh16hQyMzOx0mHDkRJMF+JyuXD69GlotVrWpfhpEspEWa1WWCwWWK1W+Hy+GSGlVCohl8shEonCkpVYbKbp282/nHv8CQFERID4YCyS/DIkB+SID8QiCIJxvh1jAjvMfDsm+Q4EmYuPHf9T8u/Ynli64tex2hgZGUF7ezs2bdoEpVIZsXXCmXGamJhAS0sLdu7cSb2sfCGdnZ248sorx8+V5daWzwnHqmbdiiYAYBgmJycnp6WpqSkmLi58Q0zDQejgWFhYiJSUlGU9R7QEU4hAIIDGxkYIBAKUlpauugbpaEEIgcPhgMVigcVigd1uh9frBTBtfSCRSCAWiyGRSM77JxaLIRaLLymu5hNNhBD4fD643W643W4c6nsfgzYjYoJixARFiA2KITjnQOJlArDwnDAL7Bjj2zDJd84pkObihvR9+GLezUt/U1YphBD09PRgdHQUlZWVUTF/DYdwstvtqK+vx/bt21lXVg8Gg9i+fbu7oaHhmkAgcIR2PBwcs1nXogkAUlJSHrj22msfffnll1lVpgOm/Wyqq6uXdfUabcEUghCC3t5ejIyMoKKiAhLJ+izVLJdAIACPxzMjbmb/83g88Hg8l3y83W6HTDb37jihUDgjwM44OnHKfhZTjBdTPA+meB74mZWbeWbEqPBs5XdW/DyrAb/fj8bGRojFYpSUlET1ImElwsnlcuHUqVOoqKiY97NCkx/96Ef+Z5555uDQ0NBnacfCwXEh6140ndtNd/bpp58uuOGGG1jXuep0OlFbW4utW7disdkwWoJpNqOjo2hra0NBQcGKS4wci4MQgsOHD+Pyyy9f8L5vDP4DLw/8JWxr8xkG+bIEpEpE+I+cL0IhWtu9bWNjY2htbUVOTg4yMzOpxLAc4eT1elFdXY3S0lJW9h+2tLTg2muv5cpyHKxl3ddPCCHB4eHhj/3Xf/2XU6/X0w7nImJjY7FlyxbU1dUtargvGwQTMO0gvnv3bphMJpw+fXrBDAnHymEYZtF9UYoVejVJeAIUyROxLyUNl6visFE5CYY5ixFPI7ocLSt6bjbj9/vR0tKCrq4ubNu2jZpgApbuHO73+1FbW4vCwkJWCqapqSnceuutLr1efy0nmDjYyroXTQBACBkeGxu77ZZbbnGzcdq9QqHAxo0bUVtbC5/PN+/92CKYQohEIlRUVCAjIwMnT54EG0XpekUpWnwPX4JQijJFCvalpOFKVQJ2JQE5MgMY5ixGPY0wuXvhDX4kirvtzZEImTrj4+M4fvw4ZDIZdu7ciZiYGNohLVo4BYNB1NfXIzMzE6mpqVGMcPH8+7//u2diYuJ/CSGnacfCwTEf69JyYC6cTuefMzIyXv/2t7/92QMHDrBrKwmApKQk5OXl4fTp09i+fftFZpJsE0yzSU1NRUJCAlpaWmAwGFBWVhaVhlmO+VEKz3eoVgokiBdLoRCKIBfyIOL54CMO2HxjcAdH4AMwushkYbejNfwBU8Tv96O9vR12ux3btm1jhViazUJ2BIQQNDU1ISEhgWpm7FL89re/DR49erR1ZGTkB7Rj4eC4FOu+p2k2DMOI1Gp110svvaT9+Mc/TjucOdHpdDAYDNi2bduMcGKzYLoQo9GIjo4OFBYWIj09nXY4a47FWg6Me8bwYv9j8AQdcPpt8JP5M5jL4esFP0GalJ0n6KUwPj6OlpYWaLVaZGVlsdqwc64eJ0IImpubIRAIwmq2GU7O2QtY9Hp9HiFknHY8HByXgivPzYIQ4tXr9Zf/x3/8h9NsNtMOZ060Wi3S0tJw+vRpBAKBVSWYgOmr4N27d8NoNKKuro7rdaKEXCjHqEcHq2887IIJALocq7tEF+pd6uzsxLZt21bFjMULS3WEELS0tIDP57NWMHk8Hnz60592G43G6znBxLEa4ETTBRBC+sfHx79wyy23eILBlW/BjgRZWVlQqVSorq7GmTNnVo1gChHqdVKr1Th58iQMBgPtkNYdQp4IYl7k7CC67au3GTzUuxQXF8ea3qXFEhJO3d3dOHXqFBiGQUlJCSsFEwB89atf9ZjN5l8EAoHjtGPh4FgMnGiaA7vd/n+9vb3vPProo+G/BA8T8fHxcDqdMyaIqxEu60SXOIEiYs/d62yHP+iP2PNHgkAggNbWVnR0dGDr1q2rIrs0FwKBAAqFAhaLBYmJiax9Da+//nrw3Xff7TYajd+mHQsHx2LhRNM8DA8P3/7888+PHj16lHYoFxEqye3Zs+e8Ut1q5MKsk06nA1szfGuNSIomX9CDganOiD1/OCGEwGg04tixY4iNjcWuXbtWVeZ2NqGSHI/HwxVXXIHe3t5F2RFEm/7+fnzjG99w6PX6jxFCuC88x6qBE03zQAhxGwyGK+644w5W+Tdd2MOUnZ2N1NRU1NbWrlrhBExnnfbs2QOn04ljx47BZDKB26QQWeIE8oXvtAJWQ4luYmICJ0+exMjICLZv375qs0vAR03ffD4fGzduhEgkWpKPU7SYmprCjTfe6B4ZGfk3QsgI7Xg4OJYCJ5ouASGky2g03nrddde52VA6mq/pOysrC+np6aipqbmkjxPbEQqFKC4uxrZt22A0GnHy5ElMTEzQDmvNEslMEwBWm1w6HA7U1taiu7sbpaWl2LRpE+tmsC2FYDCIhoaGme9QSPgt1QAz0gSDQdx6662e0dHRR7xe779ox8PBsVQ40bQAHo/nryMjI4997nOfo6qaFtolp9VqkZ2djerq6kU5h7MZqVSKzZs3o7S0FF1dXTh9+jQcDgftsNYcsgiLJv1UH1wBdhk7u91uNDU14cyZM8jJycH27dshl0c24xZp/H4/Tp06BYVCMecuOTYJp+9+97vexsbGv4+MjBygGggHxzLhRNMiMBqN36utrT1MqzF8sbYC6enpKC4uRk1NzZoQGXK5HDt27EB2djbOnDmD5uZmrlk8jES6PBdEED12dhhd+v1+dHZ2oqamBklJSdizZw+SkpJoK21YaQAAJe5JREFUh7ViQkO9NRoN8vLy5r0fG4TT66+/HnzllVcGhoeHbyVc7Z1jlcKJpkVACCHDw8P7n3vuueE333wzqk2LS/VhSkpKwubNm3H69GlMTk5GIcLIEzrJJSYmorq6Gp2dnau6DMkW4oTKiK9Bu0QXDAYxMDCAY8eOQSgUoqqqCmq1etX2Lc1mamoK1dXVKCgoQEZGxoL3pymczpw5g69//etWvV6/hxDijeriHBxhhBNNi+RcY/ju//7v/7a3tkbn6nm5xpUKhQLbtm1DU1MTRkdHIxhh9GAYBmq1GlVVVRAKhTh+/Dja29u5zNMKiHSmCaDXDO73+9Hb24sjR47A7XZjz549yMnJAY+3Ng55NpsNp06dQnl5OVQq1aIfR0M4jY2N4ZZbbpnS6/WXE0LY6RrMwbFI1sYRJEoQQozDw8Mfu+mmm1yRblBeqdN3bGwsdu7cic7OTgwPD0cgQjrweDzk5ORg3759iImJQXV1NVpaWuByuWiHtuqIdCM4AIx5TZjwRk+4e71edHZ24tixYyCEYM+ePSgqKoJQKIxaDJFmfHwcDQ0NqKysRHx8/JIfH03h5Pf7cd1113lGRkbuJoQ0RXQxDo4owImmJUIIqRsdHf3yjTfe6InUFv9wjUYRi8XYuXMnhoaG0NXVtaa28PN4PGi1Wuzbtw+JiYk4ffo0zpw5A7vdTju0VUOkG8FDdEUh2+R2u9HW1oaTJ09CLBajqqoKeXl5a0osAcDw8DBaW1uxfft2yGSyZT9PtITTF77wBc/Q0NAzdrv99YgtwsERRTjRtAwsFsvL/f39v7nrrrvCXhsK9yw5gUCA7du3w+12o6GhYVV7Oc0FwzBIT0/H3r17oVar0dLSgpqaGoyMjKwpkRgJYvhx4IEf8XUiVaIjhGBiYgL19fWora2FQqFAVVUVsrKyZoZZrxUIITh79iz0ej127doVFnuESAunH/3oR74PPvjgtMFg+HrYn5yDgxKcaFomer3+Kx9++OGHDzzwQNiaGiM1fJfH46GsrAyJiYk4efLkmixlMQyDlJQU7Nq1C8XFxTCZTDhy5Ah6e3vh9XJ9p3PBMEx0+pocrWEVsH6/HzqdDseOHUNfXx+ysrKwd+9eaDSaNdOzNBufz4fa2lowDINt27aFNXsWKeH00ksvBZ5++une4eHhqzjHb461hIB2AKsVQghhGOaG1157rSYtLa30vvvuW9GRLFKCaTZZWVmQyWSoqalBeXk5EhISIrIObeRyOcrLy+Hz+TA4OIiTJ09CLpcjKysL8fHxa2LnVLiIE8hh80d2l+VUwA69qx+amJwVPY/NZoNOp8PY2BjS09OxdevWVW1IuRicTifq6uqQl5cHtVodkTVCwqmmpgbAtDv/Svjzn/8cfOihh0wGg2EnIWR1m8ZxcFwAJ5pWACHExzBM1eOPP96sUqmyPve5zy3rMjcagilEYmIitm/fjrq6OmRlZSEzMzOi69FEKBQiNzcXOTk5mJiYQH9/P5qbm5GWlgaNRrNq54uFk2g0gwPT1gPLEU1utxt6vR56vR5isRharRYlJSVrMqN0IWazGa2trdi8eTOUSmVE1wqXcKqursaXv/xli8Fg2EYIsYQxRA4OVsCJphVCCHEyDLPt/vvvb0tKSlJ9/OMfX9LjoymYQsTExGDXrl1oaGiA3W6f00V4LcEwDBITE5GYmAi/3w+j0Yjm5mb4/X6o1Wqo1WqIxWLaYVIhThgd0dRtb8YVKTcu6r4+nw8mkwlDQ0MIBoNQq9XYvn37uvkbEULQ398Pg8GAnTt3QiKRRGXdlQqn9vZ23HrrrfZzGSZDJGLk4KANwzXLhgeGYTLVanXT22+/rayoqFjUY2gIptkQQtDV1YXx8XFs2bIlagdntjA7iyESiZCWlgaVSrWq34fDhw/jsssuW/T9/2x4BUfNf41cQOcQMEJ8f+NLEPJEc/7e5/NhdHQURqMRDodj3WYDfT4fmpubZ/oQaTS0+3w+1NTUIC8vb9HCSa/Xo6qqaqqvr+8yQsjpCIfIwUENLtMUJgghgwzD7L355pur33///bhLjTQA6AsmYDoDU1hYCLPZjOrqapSUlCAlJYVKLDSQSCTIzc1Fbm4u7HY7TCYT6uvrEQgEkJKSgtTUVCgUijWdhYtWec5PfOh3dqBAVgZgWrA7HA6MjIxgZGRk5j3Py8tb8+/5fFitVpw5cwa5ubmLcviOFEvNOFksFnz84x936/X6mznBxLHW4URTGCGEtPL5/Gs/8YlP/OPYsWPS+Zx62SCYZpOcnIydO3fizJkzGBsbQ1FR0broGZmNTCaDTCZDfn4+vF4vzGYzent7YbPZoFQqoVKpkJycvOZ8f6Ll1QQAndZmKF2pGBkZwdjYGGJjY6FSqVBRUbGqs3srhRCCgYEBDA0NoaKiYkX+S+FiscLJ4/Hg6quvdptMpq+43e53oxkjBwcNuPJcBIiLi/u3rKys144cOSJJTEw873dsE0yzIYSgu7sbo6Oj2LJlC2JiYmiHRB1CCCYnJzEyMoLR0VEIhUKoVCokJiZCLpezTlwutTzXbjuDF/t/HJlgCIMYnwzJ3lRovBqI/TJkpJbOvH9rzUtpOfh8Ppw5cwZisRgbN25k3XtyqVKd1+vFNddc42lvb/+B0Wj8AaUQOTiiCieaIoRSqfycVqt98cMPP5SEtvazWTDNZnx8HM3NzSgqKlrx9uO1hsvlwsjICCYmJmCz2cDj8SCXy6FUKqFUKiGTyaie+JYqmoan+vDz7gdXvjBhEOOTI86bgHhvEpL8iRARHiTSUQilbYiRt0AoMaNE3QgBf21aXSyViYkJNDc3o6CgAOnp6bTDmZe5hJPX68V1113nbm1t/anBYPgu5RA5OKIGJ5oiSHx8/O1ZWVm/Pnz4sIQQsioEUwiv14szZ85AKpWiuLgYAgFXyZ0Lv98Pm80Gi8UCq9UKm80GYHposkKhgFKphFwuj5qQWqposnjH8IP2ry5tkZBA8iQg0ZeMeH8ChIQPidQCaUw/BJIWiGN04PEvtujJTHwa8bE3LG29NQYhBD09PTCZTNiyZcuqOB7MFk7Jycm47rrrPC0tLU/q9foHaMfGwRFNONEUYRITE+/WarW/+uEPfyiuqqpaFQfIEKFeC51Oh9LSUlxYauSYm0AgAKvVCqvVCovFMiOkQhmp2NhYSCQSSKVSCASCsDY9L1U0+YM+fKvl/835O15QAHFACpE/BrKAHKpAMmK8CggIA7FkEpKYXgglrRDFDM8pkOYiIfYzyEj8yaLjW2vY7XY0NjYiOTkZBQUFrCvvXgqfz4cTJ07gwIEDvubm5qf1ev19tGPi4Ig2nGiKAikpKV/SaDQ///DDD8UKRfQab8PF1NQUGhsbIZPJsGHDBi7rtAwCgcBMRmpqagputxtutxs+nw/AdONtSEjN/q9YLIZAIIBAIFjUCXYh0RQMBhEIBOD3++HxeOB2u/F673OQ+EWQkThIAlLwAyLwAfD5PghFNgiEo+ALhiGKGYJIOgwef/kjF4V8DYrV1ct+/GollF0yGAwoLy+PuFllJPD7/bjhhhs8bW1tvxkcHPwK4U4eHOsQTjRFicTExLszMjKe/te//iVZjeNLuKxT5CCEwOfzwe12w+Vynfdfj8cDv98Pv99/0fw2Ho8HHo83k6liGAYTExOIj48HIQSEkIsGNDMMMyPChEIhpFIprN7nQHid4AstEAgt4AmcYJjIHReK0o5CLMyO2POzDbvdjqamJiQmJqKwsHBVZZdCeL1e3HDDDZ7m5uZfGQyGr9GOh4ODFpxoiiLx8fG3Z2Rk/PrDDz+8aFfdasHpdKKxsREKhQIbNmxg3W6f9QIhBMFgcEYchW47ceIE9uzZA4ZhwDDMeaJqPrpHbsKUJ3r2Our4HyBJdmfU1qMFIQS9vb3Q6/WrNrsETAumT3ziE5729vZf6PX6b9KOh4ODJqvvkmcVMzk5+bvBwcG79+3b5zaZTLTDWRaxsbHYtWsXYmNjcezYMYyNjdEOaV3CMAz4fP5MxkgoFEIkEoFhGAiFQggEAvD5/EX1Swl5SVGI+CMc7uNRXY8GNpsNJ06cgM/nw549e1atYJqamsLVV1/tOXv27OOcYOLg4Mwto47FYvmDTCZzVVVVvfbXv/5Vmp+fTzukJcMwDLKzs6FSqdDS0gKdTofi4uI1P3F+rSLgRzfr6XBXg5AAGGbtZSl9Ph86OzsxOTmJ0tLSVSuWgGlLhI9//OOe4eHh75lMpgiZeXFwrC64TNMiYBjmOwzDtDEM08wwTCPDMA8zDPPWrN8/yDBMz6yfr2cY5s/zPZ/dbn+rt7f3Yx/72MecdXV1EY4+csTExGD79u1Qq9U4deoUenp6EAwGaYfFsUQEvOSorhcgVkx5m6O6ZqQhhGBoaAjHjx+HTCZb1dklANDpdNi9e7e7t7f3C4sVTHMcJ7czDHOYYZjOcz83MgxzMNKxc3BEEi7TtAAMw+wEcB2ALYQQD8MwSQBiAXx51t12ArAxDJNCCBkFsAvAyUs9byAQOMkwzPb9+/cff/HFFxVXX331qh22lZqaiuTkZPT09ODYsWMoKSlBUlJ0Sz4cyyfamSYAcLiPIla8OerrRgKbzYaWlhbIZDLs3r0bItHcQ4lXC62trbj++uunhoeHb/T5fO8v5jHzHCdDb8RthJDVe3XIwTELLtO0MGkAxgghHgAghIwRQnSYFkmhqbxqAH/CtFjCuf+eWOiJCSFter2+7O677x599dVXV3WKhs/no7CwEJWVlejt7UVdXR1cLhftsDgWgYAf3UwTANjXQF+Tz+dDS0sLmpubUVJSgrKyslUvmI4ePYpPfOITtoGBgb2LFUznmOs4aYhMlBwc9OBE08L8A0AGwzBdDMP8imGYfeduPwFgF8MwhQC6AdSc+1kAoBzAorYjEUKGDAZD8Te/+c3+J554wheJFxBNYmNjsX37dmRkZODUqVPo7OyE3++nHRbHJRDwop9pmvI2Ihicivq64SAYDKK/vx/Hjx+HQqHA7t27V3UpLsSbb74Z/NznPjc+NDS0hRDSsMSHz3ecBIBXZ5Xn1q+zKceagCvPLQAhxMEwTAWAvQAuB/A6wzDfwnT5bRcAPoBqALUA/gfAZgAdhJDFWSRPrzHBMEzZE088ccxoNG48cOCAaDV6ucxGpVIhOTkZAwMDOHbsGLRaLbKyslalR81aR8CPRimVD6UoFwp+MmIYL/iBfjC+WkB8WRTWDg+EEBgMBnR3dyM1NRV79uyBUCikHVZYePbZZ/3f//73TQaDoZIQMrLUx1/iOAlw5TmONQQnmhYBISQA4DCAwwzDtAC4E8A3AfwXpkXT84QQO8MwEgCXYYF+pnnWmGIYZsf//d//vW00Gq94+eWXxavdA4nH4yEnJweZmZno7e3F0aNHkZeXB7VaHdbRIRwrQxgB0cRnpJALsyDnJ5wTSQNgyBAQGJq5D/GcBLMKRBMhBGazGR0dHVAqldi5cyfEYjHtsMLG9773Pd8LL7zQbTAYdhJCbMt9nnmOkxwcawpONC3AufJbkBDSfe6mTQB0ANoBpAPYA+Ar537XCOBLAJY1xJIQ4mMY5pOHDx9+ct++fV94++23V60J5mwEAgEKCwuRlZWFrq4u9PX1obCwECkpKZx4YgF8ngIMRCDwLuvxIp4ScqEWsTwZJEwAQjIOJqAHMAAEBuZ/oHfJ1xZRZ3JyEu3t7RCLxaioqFhVsyMXwuPx4Pbbb/fU1NQc0+v114X6kZbDJY6TG8MQKgcHa+BE08LEAXiKYRglAD+AHgD/QQghDMOcAqAghIR6kaoB/AeWkWkKcW6e03/Fx8fX7tix47lDhw5JS0tLV/YKWIJYLEZpaSmmpqbQ0dGBnp4eFBYWIjExkRNPlBHwE+ELGC95HzEvAXGCdMTw5RAzPIgwBV5wDEzQDJAuIHDJh1+MvwskYAZDoRF9IaxWK7q6uhAIBFBSUoLVODPyUhiNRlx33XVuo9H4uNFo/J8wzJGb8zgJ4CCme5pCu0LGCCEfW+FaHBzU4MaosBiGYbao1eoPfvGLX8hvvvnmNdcMZLPZ0N3dDZfLhdzcXKSmpnLiaYUsNLB3PnpNNwHBEUh4Coh4MRAxQggYQAA/eMQFXnAEDLGGPV5G8RMw0hvD/rzLZXx8HN3d08mS/Pz8NTljsaamBp/97Gedo6Ojn3U6ne/QjoeDYzXBZZpYDCGkgWGYonvuuedEc3Nz5sMPPyxcS43UcrkcFRUVcDqd6OnpQVdXF3JycqBWq7mG8SiTLYoHvK0AzEAUzS+I5wR10UQIwejoKHp6eiAWi7Fhw4Y1l1kK8Zvf/Cbw3e9+d9JgMFQRQtppx8PBsdrgRBPLIYSMMAxT8tJLLx1qbm6+8g9/+INYIpHQDiusxMbGory8HG63G729vejp6UFWVhYyMzO5gcDRIsrz52ag2NcU2g3X29sLuVyO8vJyxMXFUYsnkgSDQdx3333eP/3pT50Gg2EfIWSSdkwcHKsRTjStAs457F7n8/m+vX379u/+5S9/kWRkZNAOK+xIJBKUlJSgoKAA/f39OHr0KNLT05GVlbWmdiuxEgqu4ACA4CiIvweMIG/h+4YJv9+PoaEh6HQ6JCUlYevWrWt6bqLNZsNNN93k6ezsfEOv199NCOGM0zg4lgknmlYJ5xo1fyiRSOr37t37x5deeinuiiuuoB1WRBAKhSgoKEBOTg70ej1qamogk8mQnZ2N+Ph42uGtSRheIqh1N3pOAlEQTQ6HA/39/RgbG4NGo8GuXbtWvYP3QrS1teFTn/qUa2xs7Btms/lXtOPh4FjtcKJpleF2u99lGGbT7bff/uFdd92V+uijj66pPqfZCAQCaLVaZGZmYmJiAj09PXC73cjMzIRarYZAwH18wwYFV/AQxHsCTOwdEXnuYDAIk8kEnU4HQgiys7OxcePGdbHh4Lnnngt8//vft+r1+k8QQk7RjoeDYy3A7Z5bpTAMI87IyHhJq9Xe9Mc//lGSmppKO6So4HK5MDg4CIPBgMTERGRlZUEul9MOizUsd/cc8RwHmbw7/AEtBiYWTMppTE8gCg9TU1PQ6XQwmUxITk5GVlbWmu1XuhCn04nPf/7znpqamvrh4eFPEkIstGPi4FgrcKJplRMXF/epxMTE3zz77LOx11577dq/fD4HIQQjIyPQ6XTweDxQq9VQq9VYa03yS2XZosl3FmR8f9jjWSxMwmtgRJUreg6fzweDwYDh4WEAQGZmJtLT09fVZoIzZ87gM5/5jGtycvJhs9n8eBj8lzg4OGbBiaY1AMMw2vT09H995jOf0Tz22GOi9XSSAACv1wu9Xg+9Xg8ejweNRoO0tLQ1MxdsKSxbNAVGQMx7wx/QQvDSANF2MLGfByMsXvLDA4EARkdHMTQ0BJfLhfT0dGg0mjXd2D0fTz75ZOCxxx6b1Ov1HyeEnKEdDwfHWoQTTWsEhmGEarX6V2q1+v8dPHhwTe6uWwxOpxPDw8MwGo2Ii4uDRqNBSkrKuvF9WrZoIn6QkRIg0u3gPNW0SBJtn/6vIHPJT0EIwfj4OIaHhzE5OYmUlBRoNJo16620EFarFbfffrvnzJkzx4eHh/+NEGKnHRMHx1qFE01rDLFY/AmVSvV/P//5z2Nvuumm9aEU5oAQAqvViuHhYZjNZshkMqSmpkKlUq3pDNRyRRMABEe2AeFsf2FiAcEGQFgMRlAMiLaAEWQt66n8fj/GxsZgMpkwOTkJpVKJjIyMdT+Cp6amBrfffrvLYrF8Y2xs7BmuHMfBEVk40bQGYRgmXaPRvLdnz578Z599Vrxer8BDEEJgs9lgMpkwMjICPp+P1NRUpKamrqkBrMAKRZP5WiDQu7yFeSpAUAAIN4ARlgCCYoCfuSJB43a7MTIyApPJBJfLheTkZKSmpiIhIWFdCyVguiT9rW99y/vGG2+MnSvHtdGOiYNjPcCJpjUKwzBMYmLif8tksh8+9dRTMdddd936PsvMwuVyzZyM3W43UlJSkJKSgvj4+FXfNLwi0TT+/wBf7SXuwQP4GkCQCwjywPBzz/1/LhjeynemBYNBWK1WjI6OYnR0FDweDyqVCqmpqetm59tiqK2txV133eWanJz8tdFofIAQ4qUdEwfHeoETTWschmG0Go3mr3v37s179tlnxdz2/PPx+/0wm80wm82YnJyEQCBAYmIikpKSVqWIWpFosv0I8LUB/BSApwLDTwF4KQBfde6/qWCY8Dmzh0TS2NgYxsbG4PF4oFAokJSUBJVKteaNJ5eK1+vFgw8+6Hv99dfNer3+k4SQRtoxcXCsNzjRtA44l3W6RyaT/fCXv/yl9JOf/CSXdZoHj8eD8fFxjI2NXSSilEol6w01VyKaIk0gEIDVap15f2eLpMTERMTExNAOkbXU19fjzjvvdE1MTHDZJQ4OinCiaR3BMEyWRqP5a1VVVe4zzzzDZZ0WwWwRZbFYEAwGIZPJoFQqoVQqoVAoWCWk2CKaAoEAbDYbLBYLrFYrrFYrAEAul3MiaQn4/X48+OCDvj/84Q9j57JLnJUABwdFONG0zjiXdbpXLpd//8knn+R6nZZIMBiE3W6HxWKBxWKBzWZDIBCYEVIymQyxsbGIiYmh0qwcbdFECIHb7YbD4YDD4Zh5T4BpgRQSlgqFYtWVOmlTV1eHu+66yzUxMfGiwWD4Opdd4uCgDyea1innsk5vlZWVFf7qV7+SaLVa2iGtWkJCymq1wm63w+l0YmpqCgAglUoRFxc38y82NhZisThigioSookQAp/PNyOMnE4nHA4HpqamQAiBRCKZeX0KhQJyuZwTSCvAYrHgvvvu8/zzn/8c1ev1+wkhDbRj4uDgmIYTTesYhmEYqVT6bwkJCS/cfffdcd/97neFXPNt+CCEwOVyzYiNkODweDwAAB6PB7FYDIlEctE/oVAIgUAAgUCwJGPOxYqmYDCIQCAAv98Pn88Ht9t93j+PxwO3241AIAAAEAqFM6IvJJBiYmLWjWloNAgGg3juuecC//u//+tyOp3fnZiY+CUhJEA7Lg4Ojo/gRBMHGIaRpqenH4iLi/v/nnjiiZhPfvKTtENaFwQCgRlxcqFg8fl88Pv98Pv9CAaD5z2Ox+PNiKlQxophGDAMg9HRUSQnJyP0vQ4Gg/D7/TPiJwTDMDOiTCAQXCTaQmKOTf1aa5m6ujp88YtfdJnN5n8MDQ39f4SQcdoxcXBwXAwnmjhmYBgmV6PRHCwtLS165plnuJIdS7lQCIW+w4QQnDp1Cjt27JgRU3MJLA72MDExga997Wue999/f1Sv199MCDlNOyYODo754S4jOWYghPQyDLNlfHx8/+7du1+46667ZA899BBXsmMZPB5vXg8jHo/H7UpbBQSDQTz77LOBH//4xy6n0/mdc6W44MKP5ODgoAnXkMBxHoQQMjU19aZer9e89NJLzxYXF0/97ne/C15YIuLg4Fge//jHP1BRUeH68Y9//M7Q0FDW+Pj4k5xg4uBYHXDlOY5LwjBMplarfU6hUOw7cOCA9JprrqEdEsclYItPE8fF1NfX47777nPrdLr2wcHBOwkhLbRj4uDgWBpceY7jkhBCBgFcyzBMyRe/+MWXMzIyin/6059Kt2/fTjs0Do5VQXd3N77+9a+7z5w5YxweHr6DEHKcdkwcHBzLgxNNHIvi3BT1SoZhdt1yyy2vlJWVqX/6059KCgsLaYfGwcFKTCYTvvWtb3nef/99i9ls/qLX6/0z4VL7HByrGk40cSwJQshJhmHyjUbjJxobG1+4/PLL4x977DFxWloa7dA4OFiBzWbD9773Pd8bb7zhtNvtD9hstpc4vyUOjrUB1wjOsWQIIcTn8/1Vr9er33777S9t3bp18j/+4z+8w8PDtEPj4KCGxWLBgw8+6CspKbH//ve/f1Sv16dZrdbnOcHEwbF24BrBOVYMwzCiuLi4OxUKxY/27t0r+973vifmynZ04BrBo4/JZML3v/9971tvveX2+XyPm83mnxFCHLTj4uDgCD+caOIIGwzD8IRC4U2pqak/Ky0tTXz00UelFRUVtMNaV3CiKXr09PTgkUce8fzrX/9yOp3Oh89llTy04+Lg4IgcXE8TR9g45zVzkGGYPw0NDV3Z2tr6dFZWVsbDDz8sveKKK2iHx8ERFhobG/Hwww+7GxoaJsfGxr7udrvf4EpwHBzrA040cYSdczuE3gdQyDDMtrvvvvtXSUlJxQ8++KD03/7t37ghrxyrkiNHjuCRRx5x9fb2GoeHh78aDAbf43bDcXCsL7jyHEdUYBimOCsr62cCgWDPnXfeKfqv//ovgUKhoB3WmoMrz4UXj8eDF198kTzzzDMuh8PRMTAw8N+EkBO04+Lg4KADJ5o4ogrDMEkqleo+gUDw1csuu0x8//33S8rLy2mHtWbgRFN4GBgYwOOPP+59++23vQzDvD40NPR9QoiOdlwcHBx04UQTBxUYhhHw+fwb1Gr1j5OSktRf/vKXJbfffjtPLBbTDm1Vw4mm5RMIBPDWW2/hl7/85VRPT4/FYrE86nA4XiGEuGjHxsHBwQ440cRBHYZh8jMyMr5NCLn5E5/4hOi+++4TFxUV0Q5rVcKJpqWj1+vx5JNP+t544w0vIeSITqd7mBBSRzsuDg4O9sGJJg7WwDCMRCwW35Kamvo/CoUi/TOf+Yz47rvv5qtUKtqhrRo40bQ4bDYbfv/735Pf/e53ruHhYavD4XjcYrG8SAix0o6Ng4ODvXCiiYOVMAyjSUpK+oJEIvlSdna27I477pB+9rOfZWJjY2mHxmo40TQ/fr8fb775Jn7zm9+4mpub3YSQ1wwGwy8JIR20Y+Pg4FgdcKKJg/UwDFOqVqv/G8AtFRUVorvvvlt63XXXgc/n0w6NdXCi6XyCwSCOHTuG559/3n3kyBE/n8//p06nexxANWcXwMHBsVQ40cSxamAYhgdgb1ZW1gN+v7/qiiuuEN56663ij3/84xAIOMsxgBNNwLRQOnnyJP7v//7P+7e//c0HoLm/v/9/AbxHCPHSjo+Dg2P1wokmjlUJ8/+3d3+vUaV3HMc/3zNzJpM4O5k4UUZjihNM1o0Yu7Y1NF0pilRW6o3rXshSuld70X+hf8Ze9KKX/QEpXlhQ0P6gLjUSFrqNDXFka1hDMk0yGxyjMZmTOXOeXrhKKAsdto0nM3m/4IFh5ubLXL15nudwzDoknS8Wiz8LgmDsxIkTyUuXLqUvX75suVwu7vFis1ujaX19XdevX9fVq1drk5OToe/70wsLC7/Y3Nz8vXPuadzzAWgPRBNa3lc7UN/r6+v70MzeKxQKey5evNhx5cqVxODgYNzjvVa7KZoWFxc1Pj7url27tvHw4cPNZDJ5a25u7peS/sqOEoDtQDSh7ZjZ4e7u7vdzudxHqVTqwLlz5/wLFy6kzp49q66urrjH21btHE1hGOrOnTu6ceNGeOvWrWB1dbUaBMGvlpeXfytphjtKALYb0YS2ZmbdZvajYrH4k83NzbHe3t706dOn/fPnz6fOnDnTdhHVTtH0MpJu3rwZ3r59O1hYWAg7Ojo+m5+f/3W9Xr/hnFuOe0YAuwvRhF3FzApm9sNisfhBO0ZUK0dTGIaamJh4FUnz8/P1dDr994WFhd8EQfBn59yjuGcEsLsRTdjV/jOistlsemRkxBsdHU2PjY3ZyZMnW+rJvFaJpiiKdP/+fU1MTGhycrJ27969RqVSCdPp9GdEEoCdimgCtjCzHklv9/T0vLN37953a7Xam9lsNjUyMuKdOnXqVUilUqm4R/1aOzGaoijS9PS07t69+yqQVlZWwlQq9WhjY+OPS0tLf5H0N47bAOx0RBPwX5hZTtLbuVzunXw+/26tVjuayWRSAwMDNjQ05A8PD/vHjh3T8ePHlc1mY501zmiq1WqamZnR9PS0SqVS+ODBg83Z2Vn35MmTekdHxxdra2t/qFQqn+hFIFViGRIA/gdEE/ANmFlG0hFJQ4VC4buZTGY0CIJBSZl8Pu8NDAx4R48eTQ0PDyeOHDmiw4cPa9++ffI8b1vn2s5oiqJI1WpVc3Nzmp2dValUikqlUjA7OxtVKhXXaDTW0+n0FxsbG5+Wy+VPJX0u6Z/Oueq2DAQAr1nrXNYAdhDn3Jqkqa/W77b+Zmb5qampITMb6u/v/4Hv+281Go2+er3enUwm/XQ67e3fv1+FQsEOHjzo9/f3+4cOHVJfX5/y+byy2ax6enpey6X0IAhUrVa1urqqarWqcrms+fl5lcvlsFwu15eWlqLl5WU9f/7cNRqNeiKReJZMJhcbjcbn5XJ5ol6vP9CLOFrikX8A7Y6dJuA1M7MuSQVJByUd2LNnz7d6e3vf8n1/wDmXi6LojTAMu5xzHZ7nJczM8zwv4fu+dXZ2ukwmo87OTnme93LZy89BEKQSiUQQRZFeriAItLa2pvX1dQVBIOdc5JxrRFHUkFRPJpPriUTimZmthmE49/jx49LTp08fSfqXpEVJi865Z/H9YwCwMxBNQIsws5SkjKQ3JHVJMknelpWQFG1ZDUlOUk3SM0lrkgJ2hADgmyGaAAAAmrC9t1IBAADaBNEEAADQBKIJAACgCUQTAABAE4gmAACAJhBNAAAATSCaAAAAmkA0AW3AzH5uZjNm9g8zmzKz0bhnAoB2w7vngBZnZt+X9GNJJ51zgZn1SkrFPBYAtB2iCWh9ByStOOcCSXLOrcQ8DwC0JV6jArQ4M8tIuqMX76P7k6Rx59wn8U4FAO2HO01Ai3POrUn6jqSPJH0padzMPox1KABoQ+w0AW3GzC5L+qlz7mLcswBAO2GnCWhxZvammQ1u+erbkuZiGgcA2hYXwYHWl5H0sZnlJIWSHurFUR0A4P+I4zkAAIAmcDwHAADQBKIJAACgCUQTAABAE4gmAACAJhBNAAAATSCaAAAAmkA0AQAANIFoAgAAaMK/Ae/BsfvjY39aAAAAAElFTkSuQmCC",
       "text/plain": [
        "<Figure size 864x576 with 1 Axes>"
       ]
@@ -1037,7 +1037,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -1098,7 +1098,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.17"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
diff --git a/examples/mooring_example.ipynb b/examples/mooring_example.ipynb
index 1fdf56dc7..258203d80 100644
--- a/examples/mooring_example.ipynb
+++ b/examples/mooring_example.ipynb
@@ -20,7 +20,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import mhkit.mooring as mooring"
+    "import mhkit.mooring as mooring\n",
+    "import os"
    ]
   },
   {
@@ -40,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -409,55 +410,55 @@
        "  stroke: currentColor;\n",
        "  fill: currentColor;\n",
        "}\n",
-       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 1MB\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
        "Dimensions:   (Time: 3581)\n",
        "Coordinates:\n",
-       "  * Time      (Time) float64 29kB 0.0 0.025 0.05 0.075 ... 89.45 89.47 89.5\n",
+       "  * Time      (Time) float64 0.0 0.025 0.05 0.075 0.1 ... 89.42 89.45 89.47 89.5\n",
        "Data variables: (12/43)\n",
-       "    Node0px   (Time) float64 29kB -300.0 -300.0 -300.0 ... -300.0 -300.0 -300.0\n",
-       "    Node0py   (Time) float64 29kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
-       "    Node0pz   (Time) float64 29kB -56.0 -56.0 -56.0 -56.0 ... -56.0 -56.0 -56.0\n",
-       "    Node1px   (Time) float64 29kB -295.0 -295.0 -295.0 ... -295.0 -295.0 -295.0\n",
-       "    Node1py   (Time) float64 29kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
-       "    Node1pz   (Time) float64 29kB -56.02 -56.02 -56.02 ... -56.02 -56.02 -56.02\n",
+       "    Node0px   (Time) float64 -300.0 -300.0 -300.0 ... -300.0 -300.0 -300.0\n",
+       "    Node0py   (Time) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    Node0pz   (Time) float64 -56.0 -56.0 -56.0 -56.0 ... -56.0 -56.0 -56.0 -56.0\n",
+       "    Node1px   (Time) float64 -295.0 -295.0 -295.0 ... -295.0 -295.0 -295.0\n",
+       "    Node1py   (Time) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    Node1pz   (Time) float64 -56.02 -56.02 -56.02 ... -56.02 -56.02 -56.02\n",
        "    ...        ...\n",
-       "    Seg5Ten   (Time) float64 29kB 5.266e+04 5.237e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg6Ten   (Time) float64 29kB 5.266e+04 5.238e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg7Ten   (Time) float64 29kB 5.267e+04 5.24e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg8Ten   (Time) float64 29kB 5.268e+04 5.242e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg9Ten   (Time) float64 29kB 5.27e+04 5.244e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg10Ten  (Time) float64 29kB 5.6e+04 5.573e+04 ... 3.714e+04 3.713e+04\n",
+       "    Seg5Ten   (Time) float64 5.266e+04 5.237e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg6Ten   (Time) float64 5.266e+04 5.238e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg7Ten   (Time) float64 5.267e+04 5.24e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg8Ten   (Time) float64 5.268e+04 5.242e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg9Ten   (Time) float64 5.27e+04 5.244e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg10Ten  (Time) float64 5.6e+04 5.573e+04 5.555e+04 ... 3.714e+04 3.713e+04\n",
        "Attributes:\n",
        "    LINE_TYPES:  {&#x27;main&#x27;: {&#x27;Diam&#x27;: &#x27;0.0766&#x27;, &#x27;MassDen&#x27;: &#x27;113.35&#x27;, &#x27;EA&#x27;: &#x27;7.53...\n",
        "    POINTS:      {&#x27;1&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;418.8&#x27;, &#x27;Y&#x27;: &#x27;725.383&#x27;, ...\n",
        "    LINES:       {&#x27;1&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;1&#x27;, &#x27;AttachB&#x27;: &#x27;4&#x27;, &#x27;...\n",
-       "    OPTIONS:     {&#x27;dtM&#x27;: &#x27;0.001&#x27;, &#x27;kbot&#x27;: &#x27;3.0e6&#x27;, &#x27;cbot&#x27;: &#x27;3.0e5&#x27;, &#x27;dtIC&#x27;: &#x27;...</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-292755f8-f22b-418b-a319-ddd8c6de34de' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-292755f8-f22b-418b-a319-ddd8c6de34de' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 3581</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-13e0032b-227c-4662-925b-b5f59ac65ce3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-13e0032b-227c-4662-925b-b5f59ac65ce3' class='xr-section-summary' >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'>Time</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.025 0.05 ... 89.45 89.47 89.5</div><input id='attrs-c6d34728-9e08-43e6-85fb-1461ef120ced' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c6d34728-9e08-43e6-85fb-1461ef120ced' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61e7b907-2957-405f-b6e5-84f89e890952' class='xr-var-data-in' type='checkbox'><label for='data-61e7b907-2957-405f-b6e5-84f89e890952' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-02, 5.0000e-02, ..., 8.9450e+01, 8.9475e+01,\n",
-       "       8.9500e+01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79047bf3-7d8c-45f1-921e-374c0351c959' class='xr-section-summary-in' type='checkbox'  ><label for='section-79047bf3-7d8c-45f1-921e-374c0351c959' class='xr-section-summary' >Data variables: <span>(43)</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>Node0px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-300.0 -300.0 ... -300.0 -300.0</div><input id='attrs-5456a791-acff-4597-b576-b0af967abe5e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5456a791-acff-4597-b576-b0af967abe5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c22bbc5a-b7cc-411f-87de-a5fb6b31cf64' class='xr-var-data-in' type='checkbox'><label for='data-c22bbc5a-b7cc-411f-87de-a5fb6b31cf64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-300., -300., -300., ..., -300., -300., -300.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node0py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-fedd4670-c1cd-4b94-bfa9-3c45d32eec30' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fedd4670-c1cd-4b94-bfa9-3c45d32eec30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38102e8a-5754-4afc-bb61-f681d2b5ad43' class='xr-var-data-in' type='checkbox'><label for='data-38102e8a-5754-4afc-bb61-f681d2b5ad43' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node0pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.0 -56.0 -56.0 ... -56.0 -56.0</div><input id='attrs-a9fa558b-1261-446f-a3ce-976d32490b7b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9fa558b-1261-446f-a3ce-976d32490b7b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29002153-ec10-421a-86a0-06b1529902a9' class='xr-var-data-in' type='checkbox'><label for='data-29002153-ec10-421a-86a0-06b1529902a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56., -56., -56., ..., -56., -56., -56.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-295.0 -295.0 ... -295.0 -295.0</div><input id='attrs-86b001d9-4b50-44d5-be0b-7acf19b486ee' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-86b001d9-4b50-44d5-be0b-7acf19b486ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1310b020-39c9-4c86-ad9c-76e943fc2525' class='xr-var-data-in' type='checkbox'><label for='data-1310b020-39c9-4c86-ad9c-76e943fc2525' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-295., -295., -295., ..., -295., -295., -295.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-92e74eeb-69f0-4327-9f36-0e4b154333b7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-92e74eeb-69f0-4327-9f36-0e4b154333b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-892b912c-b567-4146-9fe1-909977fde425' class='xr-var-data-in' type='checkbox'><label for='data-892b912c-b567-4146-9fe1-909977fde425' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-2aae86f8-8c16-4703-87f0-4037709fba92' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2aae86f8-8c16-4703-87f0-4037709fba92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d8e9110-ae68-4a83-86bb-2499dd525efb' class='xr-var-data-in' type='checkbox'><label for='data-6d8e9110-ae68-4a83-86bb-2499dd525efb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0157, -56.0157, -56.0157, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-290.0 -290.0 ... -290.0 -290.0</div><input id='attrs-7ac142ec-0a51-4ab5-a208-ea66bd0f58dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7ac142ec-0a51-4ab5-a208-ea66bd0f58dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8eef6aea-ad09-4093-a98c-9ef4ebc11cfd' class='xr-var-data-in' type='checkbox'><label for='data-8eef6aea-ad09-4093-a98c-9ef4ebc11cfd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-290., -290., -290., ..., -290., -290., -290.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-8bd8cc4a-fbb9-496d-b97d-1df35966ddda' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8bd8cc4a-fbb9-496d-b97d-1df35966ddda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e8cd4e7-77a1-4cc0-86a3-3872a6e7898a' class='xr-var-data-in' type='checkbox'><label for='data-1e8cd4e7-77a1-4cc0-86a3-3872a6e7898a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-1ecf93ee-8e13-4f58-bfe5-29a982dc884c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1ecf93ee-8e13-4f58-bfe5-29a982dc884c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d2ee778-2f66-463a-83ba-481eb6ea47b3' class='xr-var-data-in' type='checkbox'><label for='data-4d2ee778-2f66-463a-83ba-481eb6ea47b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-285.0 -285.0 ... -285.0 -285.0</div><input id='attrs-a97db0c4-1051-4151-8679-e40113b7fc13' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a97db0c4-1051-4151-8679-e40113b7fc13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db5656f1-dbae-4813-9029-d33e8a772971' class='xr-var-data-in' type='checkbox'><label for='data-db5656f1-dbae-4813-9029-d33e8a772971' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-285., -285., -285., ..., -285., -285., -285.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-7469e073-1324-4dae-9143-2d5fa951b330' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7469e073-1324-4dae-9143-2d5fa951b330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-063f4ceb-7d57-4b97-9e37-be78e940efb9' class='xr-var-data-in' type='checkbox'><label for='data-063f4ceb-7d57-4b97-9e37-be78e940efb9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-838bdf24-3b43-4a5e-b55d-302ec537f74d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-838bdf24-3b43-4a5e-b55d-302ec537f74d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-47909f47-153d-4a20-941e-898fabbc8e0c' class='xr-var-data-in' type='checkbox'><label for='data-47909f47-153d-4a20-941e-898fabbc8e0c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-280.0 -280.0 ... -280.0 -280.0</div><input id='attrs-427bcaed-428d-4029-b0f0-1e9feb2c4531' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-427bcaed-428d-4029-b0f0-1e9feb2c4531' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e2d35ab-c2b1-4407-b994-de34047ded99' class='xr-var-data-in' type='checkbox'><label for='data-0e2d35ab-c2b1-4407-b994-de34047ded99' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-280., -280., -280., ..., -280., -280., -280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-c31d2783-7c3f-4c5b-91fc-cf30dcdfadc2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c31d2783-7c3f-4c5b-91fc-cf30dcdfadc2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11e2afbd-01af-4493-8ee4-9992d4b96ad7' class='xr-var-data-in' type='checkbox'><label for='data-11e2afbd-01af-4493-8ee4-9992d4b96ad7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-8aab3b85-21b7-4fc0-a25e-68067ab68fbb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8aab3b85-21b7-4fc0-a25e-68067ab68fbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5843c95-bbff-469a-bcad-59d8f409c6ae' class='xr-var-data-in' type='checkbox'><label for='data-b5843c95-bbff-469a-bcad-59d8f409c6ae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-275.0 -275.0 ... -275.0 -275.0</div><input id='attrs-be8788e6-1feb-4bbc-b41d-2902f106847f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-be8788e6-1feb-4bbc-b41d-2902f106847f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b6b1314-dd90-438f-8f02-d2129f052e8a' class='xr-var-data-in' type='checkbox'><label for='data-4b6b1314-dd90-438f-8f02-d2129f052e8a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-274.999, -274.999, -274.999, ..., -275.   , -275.   , -275.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-9f40b091-ab2e-4d0a-83e3-6f0a09a53b8e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9f40b091-ab2e-4d0a-83e3-6f0a09a53b8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e3783b0-ccc6-4f89-b63d-cd07c6845f12' class='xr-var-data-in' type='checkbox'><label for='data-4e3783b0-ccc6-4f89-b63d-cd07c6845f12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-76d7629e-6d05-42d3-a740-a576ba889e78' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76d7629e-6d05-42d3-a740-a576ba889e78' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4f594f9-d9c1-41ba-a8eb-ebf17f033b10' class='xr-var-data-in' type='checkbox'><label for='data-a4f594f9-d9c1-41ba-a8eb-ebf17f033b10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-270.0 -270.0 ... -270.0 -270.0</div><input id='attrs-2b573e46-9cce-4611-8805-350c726b8d1d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2b573e46-9cce-4611-8805-350c726b8d1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-35f7c0ed-b5c3-428c-9655-5b8c121a7c12' class='xr-var-data-in' type='checkbox'><label for='data-35f7c0ed-b5c3-428c-9655-5b8c121a7c12' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-269.999, -269.999, -269.999, ..., -270.   , -270.   , -270.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-8a7718b6-b827-467d-ab72-c12df21dc381' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8a7718b6-b827-467d-ab72-c12df21dc381' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a33d295-ad72-4e83-a57f-45b32bafb79b' class='xr-var-data-in' type='checkbox'><label for='data-5a33d295-ad72-4e83-a57f-45b32bafb79b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-37cd6151-40c6-46a2-94cc-9ed6ff6e9118' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-37cd6151-40c6-46a2-94cc-9ed6ff6e9118' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad34b158-f35d-47da-8dac-e22e6a35c7a1' class='xr-var-data-in' type='checkbox'><label for='data-ad34b158-f35d-47da-8dac-e22e6a35c7a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-265.0 -265.0 ... -265.0 -265.0</div><input id='attrs-73a9b6cc-7e40-4497-9278-c1f82cbdd6b3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-73a9b6cc-7e40-4497-9278-c1f82cbdd6b3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0245beed-258d-451e-ab0f-44cb83440d73' class='xr-var-data-in' type='checkbox'><label for='data-0245beed-258d-451e-ab0f-44cb83440d73' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-264.999, -264.999, -264.999, ..., -265.   , -265.   , -265.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-3f89a298-ed22-42ea-8cb0-3d2da8fe1230' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3f89a298-ed22-42ea-8cb0-3d2da8fe1230' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1687ea9-a962-4cd2-a218-51b18c51d73a' class='xr-var-data-in' type='checkbox'><label for='data-b1687ea9-a962-4cd2-a218-51b18c51d73a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-da5f8c8b-f7cc-4985-8cfd-dfb89ded912f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-da5f8c8b-f7cc-4985-8cfd-dfb89ded912f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-19ff93ce-632f-443a-a5aa-08bdd38931bb' class='xr-var-data-in' type='checkbox'><label for='data-19ff93ce-632f-443a-a5aa-08bdd38931bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-260.0 -260.0 ... -260.0 -260.0</div><input id='attrs-a56fded4-f602-4c3a-9402-8452dd964193' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a56fded4-f602-4c3a-9402-8452dd964193' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91803a33-27c3-4c9e-9caf-3d261ddc6566' class='xr-var-data-in' type='checkbox'><label for='data-91803a33-27c3-4c9e-9caf-3d261ddc6566' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-259.999, -259.999, -259.999, ..., -259.999, -259.999, -259.999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-42204519-559d-4bca-967f-fce6bbf1716a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-42204519-559d-4bca-967f-fce6bbf1716a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aa13910-6565-40ab-9cc9-61c1e1ccb522' class='xr-var-data-in' type='checkbox'><label for='data-9aa13910-6565-40ab-9cc9-61c1e1ccb522' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-de192cac-cde0-4c8a-b725-2cad7695c330' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-de192cac-cde0-4c8a-b725-2cad7695c330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59d30a4a-78a4-4924-9062-04ffe4ab34a6' class='xr-var-data-in' type='checkbox'><label for='data-59d30a4a-78a4-4924-9062-04ffe4ab34a6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0157, -56.0157, -56.0157, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-255.0 -255.0 ... -255.0 -255.0</div><input id='attrs-c0771ed7-50af-4b07-9e53-0d279168eca7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c0771ed7-50af-4b07-9e53-0d279168eca7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6b49743-c2c2-4da3-acd9-ea440440a1e9' class='xr-var-data-in' type='checkbox'><label for='data-c6b49743-c2c2-4da3-acd9-ea440440a1e9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-254.999, -254.999, -254.999, ..., -254.999, -254.999, -254.999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-40824fc4-49f9-4cf8-9c7d-9654e75d54c4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-40824fc4-49f9-4cf8-9c7d-9654e75d54c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d6ecdd9-5ed2-4145-8a8d-5212f0de1b13' class='xr-var-data-in' type='checkbox'><label for='data-6d6ecdd9-5ed2-4145-8a8d-5212f0de1b13' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.0 -56.0 -56.0 ... -56.01 -56.01</div><input id='attrs-b7de5308-b16e-4619-bdea-9182532d9356' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b7de5308-b16e-4619-bdea-9182532d9356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0735c965-321d-42d1-9a71-3fabb2e8f3cb' class='xr-var-data-in' type='checkbox'><label for='data-0735c965-321d-42d1-9a71-3fabb2e8f3cb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0027, -56.0028, -56.0028, ..., -56.0074, -56.0074, -56.0074])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-250.3 -250.3 ... -250.3 -250.3</div><input id='attrs-8f2b3862-e2c2-4a51-8681-da4d314a5443' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8f2b3862-e2c2-4a51-8681-da4d314a5443' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f201ebfa-1531-4927-ab52-82424f86d00b' class='xr-var-data-in' type='checkbox'><label for='data-f201ebfa-1531-4927-ab52-82424f86d00b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-250.293, -250.293, -250.293, ..., -250.284, -250.284, -250.284])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-dbeee773-3c9a-45a5-bed1-c67ffc46af63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dbeee773-3c9a-45a5-bed1-c67ffc46af63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0ae5bd9-d48c-4975-b4d8-86c0283303a9' class='xr-var-data-in' type='checkbox'><label for='data-c0ae5bd9-d48c-4975-b4d8-86c0283303a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-54.31 -54.31 ... -54.34 -54.34</div><input id='attrs-bd3bf6b7-edae-41f0-8c73-09b24e0a5cf2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bd3bf6b7-edae-41f0-8c73-09b24e0a5cf2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-14dcbed1-6a89-4045-bc76-5627d288065d' class='xr-var-data-in' type='checkbox'><label for='data-14dcbed1-6a89-4045-bc76-5627d288065d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-54.3143, -54.3139, -54.3136, ..., -54.3439, -54.3438, -54.3437])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg1Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.235e+04 ... 3.502e+04</div><input id='attrs-07b2dfc4-b9d4-46c9-a4f5-3c275ed56308' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-07b2dfc4-b9d4-46c9-a4f5-3c275ed56308' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8de5af62-313b-4fd1-aa56-90537f7535d2' class='xr-var-data-in' type='checkbox'><label for='data-8de5af62-313b-4fd1-aa56-90537f7535d2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52639.8, 52351.8, 52247.3, ..., 35026. , 35022.3, 35018.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg2Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.235e+04 ... 3.502e+04</div><input id='attrs-4277f157-1a35-4194-a4d0-88c9a4c359b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4277f157-1a35-4194-a4d0-88c9a4c359b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c826c9e3-fd60-4c9a-ad2f-50310555c2e5' class='xr-var-data-in' type='checkbox'><label for='data-c826c9e3-fd60-4c9a-ad2f-50310555c2e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52641.1, 52352.6, 52247.8, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg3Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.236e+04 ... 3.502e+04</div><input id='attrs-acd686ee-e73e-4ada-b1bd-b62e33fa62c5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acd686ee-e73e-4ada-b1bd-b62e33fa62c5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a705602-1006-4770-b6f7-a152c872085b' class='xr-var-data-in' type='checkbox'><label for='data-6a705602-1006-4770-b6f7-a152c872085b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52644.4, 52355.6, 52249.3, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg4Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.265e+04 5.236e+04 ... 3.502e+04</div><input id='attrs-35a65e53-cc2f-413c-9681-fd160cc889b4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-35a65e53-cc2f-413c-9681-fd160cc889b4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c49e30c-4364-4a69-a9d1-e5e27a6b70d5' class='xr-var-data-in' type='checkbox'><label for='data-4c49e30c-4364-4a69-a9d1-e5e27a6b70d5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52649.2, 52361.5, 52251.8, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg5Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.266e+04 5.237e+04 ... 3.502e+04</div><input id='attrs-76527656-496b-41a9-8a26-4f6893b4db5d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-76527656-496b-41a9-8a26-4f6893b4db5d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-866254cf-6dcd-4a05-9ed0-aff79d08373c' class='xr-var-data-in' type='checkbox'><label for='data-866254cf-6dcd-4a05-9ed0-aff79d08373c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52655.7, 52371. , 52255.3, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg6Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.266e+04 5.238e+04 ... 3.502e+04</div><input id='attrs-4e669d74-33ce-492d-9ae9-115bbf6c94e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4e669d74-33ce-492d-9ae9-115bbf6c94e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6bfa8d64-e103-4fd7-a80f-de0da8c98c34' class='xr-var-data-in' type='checkbox'><label for='data-6bfa8d64-e103-4fd7-a80f-de0da8c98c34' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52663.6, 52383.8, 52259.7, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg7Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.267e+04 5.24e+04 ... 3.502e+04</div><input id='attrs-171a628c-bf1a-4846-9b60-2a6ad2602e24' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-171a628c-bf1a-4846-9b60-2a6ad2602e24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97a67b5b-aa1b-4a58-bb95-1cd81dac67c6' class='xr-var-data-in' type='checkbox'><label for='data-97a67b5b-aa1b-4a58-bb95-1cd81dac67c6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52673. , 52399.3, 52265.1, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg8Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.268e+04 5.242e+04 ... 3.502e+04</div><input id='attrs-8d66699f-8c3e-44df-82f7-dd3614acd689' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8d66699f-8c3e-44df-82f7-dd3614acd689' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dbeafe4-0825-47e5-8825-9c82548e04a1' class='xr-var-data-in' type='checkbox'><label for='data-7dbeafe4-0825-47e5-8825-9c82548e04a1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52683.8, 52416.5, 52271.2, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg9Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.27e+04 5.244e+04 ... 3.502e+04</div><input id='attrs-4cd9cd90-faf7-4160-bf25-91cd1d7f005f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4cd9cd90-faf7-4160-bf25-91cd1d7f005f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54b859be-5292-41e2-a623-dec1538a2162' class='xr-var-data-in' type='checkbox'><label for='data-54b859be-5292-41e2-a623-dec1538a2162' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52696.2, 52435.4, 52278.2, ..., 35025.9, 35022.2, 35018.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg10Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.6e+04 5.573e+04 ... 3.713e+04</div><input id='attrs-0f9f12ec-0f3e-4685-ab31-25d42bdfdac0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f9f12ec-0f3e-4685-ab31-25d42bdfdac0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-254d42e5-84c0-406a-8d10-df196cd75a2b' class='xr-var-data-in' type='checkbox'><label for='data-254d42e5-84c0-406a-8d10-df196cd75a2b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55997.5, 55729.1, 55550.8, ..., 37141.8, 37138.1, 37134.4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6650968b-92f4-4800-8495-f3aae52b7cf4' class='xr-section-summary-in' type='checkbox'  ><label for='section-6650968b-92f4-4800-8495-f3aae52b7cf4' class='xr-section-summary' >Indexes: <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-index-name'><div>Time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cfade3e8-a3f5-4969-8e7d-1aa3cbcd96a9' class='xr-index-data-in' type='checkbox'/><label for='index-cfade3e8-a3f5-4969-8e7d-1aa3cbcd96a9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,  0.025,   0.05,  0.075,    0.1,  0.125,   0.15,  0.175,    0.2,\n",
+       "    OPTIONS:     {&#x27;dtM&#x27;: &#x27;0.001&#x27;, &#x27;kbot&#x27;: &#x27;3.0e6&#x27;, &#x27;cbot&#x27;: &#x27;3.0e5&#x27;, &#x27;dtIC&#x27;: &#x27;...</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-d04cb068-8355-465e-812f-73024b2ce3c8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d04cb068-8355-465e-812f-73024b2ce3c8' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>Time</span>: 3581</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-1c3194fa-64e0-4285-bb53-26d7775f521b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1c3194fa-64e0-4285-bb53-26d7775f521b' class='xr-section-summary' >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'>Time</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.025 0.05 ... 89.45 89.47 89.5</div><input id='attrs-125bc7dd-0eb6-4250-8f6c-50ceb687d321' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-125bc7dd-0eb6-4250-8f6c-50ceb687d321' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7c6c59b-6664-48f6-ad4b-2a5e8a469a33' class='xr-var-data-in' type='checkbox'><label for='data-e7c6c59b-6664-48f6-ad4b-2a5e8a469a33' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([0.0000e+00, 2.5000e-02, 5.0000e-02, ..., 8.9450e+01, 8.9475e+01,\n",
+       "       8.9500e+01])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9cd46d5f-5052-48ec-b9b6-87c6255ded29' class='xr-section-summary-in' type='checkbox'  ><label for='section-9cd46d5f-5052-48ec-b9b6-87c6255ded29' class='xr-section-summary' >Data variables: <span>(43)</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>Node0px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-300.0 -300.0 ... -300.0 -300.0</div><input id='attrs-c198765f-f4f3-49d8-9aa5-0841bc040ee0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c198765f-f4f3-49d8-9aa5-0841bc040ee0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07f46680-3374-465f-984b-ac85bce313d7' class='xr-var-data-in' type='checkbox'><label for='data-07f46680-3374-465f-984b-ac85bce313d7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-300., -300., -300., ..., -300., -300., -300.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node0py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-34fa25b3-f633-44db-87a0-0a6c8e9c52d2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-34fa25b3-f633-44db-87a0-0a6c8e9c52d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-853e98f7-09dc-4e30-86c8-94b12849820c' class='xr-var-data-in' type='checkbox'><label for='data-853e98f7-09dc-4e30-86c8-94b12849820c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node0pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.0 -56.0 -56.0 ... -56.0 -56.0</div><input id='attrs-f11eb4d1-0c56-4941-8cd1-a6bd0e21759b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f11eb4d1-0c56-4941-8cd1-a6bd0e21759b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fa4528bd-922f-40ae-b3b5-767419a614f1' class='xr-var-data-in' type='checkbox'><label for='data-fa4528bd-922f-40ae-b3b5-767419a614f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56., -56., -56., ..., -56., -56., -56.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-295.0 -295.0 ... -295.0 -295.0</div><input id='attrs-b2fab098-4802-40ba-aa28-6fa3a133a63d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b2fab098-4802-40ba-aa28-6fa3a133a63d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae65490e-758c-4ebe-ad0f-bd270764001a' class='xr-var-data-in' type='checkbox'><label for='data-ae65490e-758c-4ebe-ad0f-bd270764001a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-295., -295., -295., ..., -295., -295., -295.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-c79fec52-0242-4905-ab08-e5ca446617c8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c79fec52-0242-4905-ab08-e5ca446617c8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a0bb97d7-2f2a-46a7-97cc-90d6030c8d68' class='xr-var-data-in' type='checkbox'><label for='data-a0bb97d7-2f2a-46a7-97cc-90d6030c8d68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node1pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-dfcc4c7f-bc6e-464e-9319-0ec44a0a13e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dfcc4c7f-bc6e-464e-9319-0ec44a0a13e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-140f1c7d-44b5-4da7-aa03-7aec9e2092bd' class='xr-var-data-in' type='checkbox'><label for='data-140f1c7d-44b5-4da7-aa03-7aec9e2092bd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0157, -56.0157, -56.0157, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-290.0 -290.0 ... -290.0 -290.0</div><input id='attrs-338c963d-49a4-4bb5-9bda-e3e33cf6c100' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-338c963d-49a4-4bb5-9bda-e3e33cf6c100' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7dce0f66-ac7b-4293-982c-9b80b15a2442' class='xr-var-data-in' type='checkbox'><label for='data-7dce0f66-ac7b-4293-982c-9b80b15a2442' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-290., -290., -290., ..., -290., -290., -290.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-f5964e54-ae12-4ea0-8705-1d2a0f94e23f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f5964e54-ae12-4ea0-8705-1d2a0f94e23f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-66fe13f7-3484-4bff-b3be-959933075289' class='xr-var-data-in' type='checkbox'><label for='data-66fe13f7-3484-4bff-b3be-959933075289' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node2pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-64999c9f-977e-44a9-b9c5-c762808c514c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-64999c9f-977e-44a9-b9c5-c762808c514c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b750b8ff-372e-4d8e-9cc9-19a6ab484ecc' class='xr-var-data-in' type='checkbox'><label for='data-b750b8ff-372e-4d8e-9cc9-19a6ab484ecc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-285.0 -285.0 ... -285.0 -285.0</div><input id='attrs-a9fc6f1b-4ed2-4ab7-8f6c-f56ee0fe700f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a9fc6f1b-4ed2-4ab7-8f6c-f56ee0fe700f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d2150b2-d33d-4d8a-9148-7d58565422bc' class='xr-var-data-in' type='checkbox'><label for='data-7d2150b2-d33d-4d8a-9148-7d58565422bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-285., -285., -285., ..., -285., -285., -285.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-960931ca-4c02-47f7-aada-517626135f4a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-960931ca-4c02-47f7-aada-517626135f4a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d4e7747-6b40-4fc4-b9ba-f60a6d9f2e25' class='xr-var-data-in' type='checkbox'><label for='data-0d4e7747-6b40-4fc4-b9ba-f60a6d9f2e25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node3pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-fbbdbba3-6af4-4b80-acba-a23bf594e138' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbbdbba3-6af4-4b80-acba-a23bf594e138' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-88fbaa33-30ea-480f-8dd2-0c14afee9738' class='xr-var-data-in' type='checkbox'><label for='data-88fbaa33-30ea-480f-8dd2-0c14afee9738' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-280.0 -280.0 ... -280.0 -280.0</div><input id='attrs-553a440c-1126-40a1-869e-6bdfbc8eefb5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-553a440c-1126-40a1-869e-6bdfbc8eefb5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-580cb68e-ff36-48ef-898c-49355efe5499' class='xr-var-data-in' type='checkbox'><label for='data-580cb68e-ff36-48ef-898c-49355efe5499' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-280., -280., -280., ..., -280., -280., -280.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-fba23967-5f74-4f42-90ee-5519bd5104cc' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fba23967-5f74-4f42-90ee-5519bd5104cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b070457-0f22-49ec-b60b-6ecb6b0bc8f6' class='xr-var-data-in' type='checkbox'><label for='data-8b070457-0f22-49ec-b60b-6ecb6b0bc8f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node4pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-a87e5da6-25cf-4382-ab0f-261125ee1db5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a87e5da6-25cf-4382-ab0f-261125ee1db5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6dae49cb-049c-4226-b9e1-34aafb51c7f6' class='xr-var-data-in' type='checkbox'><label for='data-6dae49cb-049c-4226-b9e1-34aafb51c7f6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-275.0 -275.0 ... -275.0 -275.0</div><input id='attrs-422a5849-927d-49bd-b078-025e9ba91cc8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-422a5849-927d-49bd-b078-025e9ba91cc8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-83325f87-70a1-480b-af9a-45ea751a140d' class='xr-var-data-in' type='checkbox'><label for='data-83325f87-70a1-480b-af9a-45ea751a140d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-274.999, -274.999, -274.999, ..., -275.   , -275.   , -275.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-7f371e51-b145-487e-8f5d-fc65d0c9b345' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f371e51-b145-487e-8f5d-fc65d0c9b345' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7d565895-a8aa-4cdc-952d-baa9288566a3' class='xr-var-data-in' type='checkbox'><label for='data-7d565895-a8aa-4cdc-952d-baa9288566a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node5pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-3d237502-04aa-4667-96db-2717c482ee10' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3d237502-04aa-4667-96db-2717c482ee10' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ec445b6-1e6b-4ed0-a92c-e6cce2172aa1' class='xr-var-data-in' type='checkbox'><label for='data-8ec445b6-1e6b-4ed0-a92c-e6cce2172aa1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-270.0 -270.0 ... -270.0 -270.0</div><input id='attrs-33799d23-f90a-4a54-b39a-d3a7905a9df8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33799d23-f90a-4a54-b39a-d3a7905a9df8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-67932a23-6a5a-4537-823f-1e36b7bd28f5' class='xr-var-data-in' type='checkbox'><label for='data-67932a23-6a5a-4537-823f-1e36b7bd28f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-269.999, -269.999, -269.999, ..., -270.   , -270.   , -270.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-7f8eb17d-b62c-46bd-9c86-aa8fa2d67563' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-7f8eb17d-b62c-46bd-9c86-aa8fa2d67563' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef4eb1dd-385d-4c2d-9630-ef8aef13f2e5' class='xr-var-data-in' type='checkbox'><label for='data-ef4eb1dd-385d-4c2d-9630-ef8aef13f2e5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node6pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-9523a8bb-4621-44ac-af15-0d433e5e7637' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9523a8bb-4621-44ac-af15-0d433e5e7637' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44a99913-1f2f-438f-9982-69d59d8752c9' class='xr-var-data-in' type='checkbox'><label for='data-44a99913-1f2f-438f-9982-69d59d8752c9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-265.0 -265.0 ... -265.0 -265.0</div><input id='attrs-2d9d232f-5918-492d-9df2-998b0a7aa41f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2d9d232f-5918-492d-9df2-998b0a7aa41f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba6a56e6-db59-4d4d-bbc5-8c4739a54d32' class='xr-var-data-in' type='checkbox'><label for='data-ba6a56e6-db59-4d4d-bbc5-8c4739a54d32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-264.999, -264.999, -264.999, ..., -265.   , -265.   , -265.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-a350c2bd-9ed0-4b6e-9fcd-c0de8ebced7a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a350c2bd-9ed0-4b6e-9fcd-c0de8ebced7a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f5d41b02-230e-471b-8bb2-5fe1a2a611b3' class='xr-var-data-in' type='checkbox'><label for='data-f5d41b02-230e-471b-8bb2-5fe1a2a611b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node7pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-cd0c397a-cdf8-4005-b83b-79b2952c3697' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cd0c397a-cdf8-4005-b83b-79b2952c3697' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-806ecb22-8521-4d40-8a3e-8cc07235dbff' class='xr-var-data-in' type='checkbox'><label for='data-806ecb22-8521-4d40-8a3e-8cc07235dbff' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0158, -56.0158, -56.0158, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-260.0 -260.0 ... -260.0 -260.0</div><input id='attrs-a5645165-0920-4661-93f9-c3c80da773f5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a5645165-0920-4661-93f9-c3c80da773f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39f7ca5f-8614-4e12-b2b7-592b6cb3b756' class='xr-var-data-in' type='checkbox'><label for='data-39f7ca5f-8614-4e12-b2b7-592b6cb3b756' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-259.999, -259.999, -259.999, ..., -259.999, -259.999, -259.999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-641b9d1d-c7c3-4db4-b970-e8e378c3b890' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-641b9d1d-c7c3-4db4-b970-e8e378c3b890' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2592dfb-1938-46a6-930f-5ea8608c45fa' class='xr-var-data-in' type='checkbox'><label for='data-d2592dfb-1938-46a6-930f-5ea8608c45fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node8pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.02 -56.02 ... -56.02 -56.02</div><input id='attrs-4abc4300-ca6a-43f9-9121-68c1b98d952a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4abc4300-ca6a-43f9-9121-68c1b98d952a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-912df21e-a26b-47ef-8563-a21a66acd3ac' class='xr-var-data-in' type='checkbox'><label for='data-912df21e-a26b-47ef-8563-a21a66acd3ac' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0157, -56.0157, -56.0157, ..., -56.0158, -56.0158, -56.0158])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-255.0 -255.0 ... -255.0 -255.0</div><input id='attrs-00872358-b85a-410e-8a1a-c82d6f168d6d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-00872358-b85a-410e-8a1a-c82d6f168d6d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a72d69c-2d44-41a8-a470-773d97a5cb96' class='xr-var-data-in' type='checkbox'><label for='data-1a72d69c-2d44-41a8-a470-773d97a5cb96' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-254.999, -254.999, -254.999, ..., -254.999, -254.999, -254.999])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-6fb87229-795d-4eda-b014-425ebb3ee35b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6fb87229-795d-4eda-b014-425ebb3ee35b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-10a4c495-e14c-44ba-9f2a-1d7145a30c19' class='xr-var-data-in' type='checkbox'><label for='data-10a4c495-e14c-44ba-9f2a-1d7145a30c19' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node9pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-56.0 -56.0 -56.0 ... -56.01 -56.01</div><input id='attrs-e44f32ce-12ac-4885-b2d0-50f24230612e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e44f32ce-12ac-4885-b2d0-50f24230612e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5419f2f7-6039-4f50-8a77-d3e7fa9b6acb' class='xr-var-data-in' type='checkbox'><label for='data-5419f2f7-6039-4f50-8a77-d3e7fa9b6acb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-56.0027, -56.0028, -56.0028, ..., -56.0074, -56.0074, -56.0074])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10px</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-250.3 -250.3 ... -250.3 -250.3</div><input id='attrs-8df0e1dd-b7d5-4dca-b9fd-9627bb10c334' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-8df0e1dd-b7d5-4dca-b9fd-9627bb10c334' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-edb672cd-e050-4657-8a55-5209ce67a7e2' class='xr-var-data-in' type='checkbox'><label for='data-edb672cd-e050-4657-8a55-5209ce67a7e2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-250.293, -250.293, -250.293, ..., -250.284, -250.284, -250.284])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10py</span></div><div class='xr-var-dims'>(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 0.0</div><input id='attrs-74e46560-801e-4352-9240-f56e42f8120b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-74e46560-801e-4352-9240-f56e42f8120b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9690e8d9-748f-4ad1-90ab-68b5caaf58a8' class='xr-var-data-in' type='checkbox'><label for='data-9690e8d9-748f-4ad1-90ab-68b5caaf58a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink: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., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Node10pz</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-54.31 -54.31 ... -54.34 -54.34</div><input id='attrs-85322eb8-1d94-486a-9405-5b2a031fb7e9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-85322eb8-1d94-486a-9405-5b2a031fb7e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ec71763-ce75-4762-8bc3-e8618d15914b' class='xr-var-data-in' type='checkbox'><label for='data-5ec71763-ce75-4762-8bc3-e8618d15914b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-54.3143, -54.3139, -54.3136, ..., -54.3439, -54.3438, -54.3437])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg1Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.235e+04 ... 3.502e+04</div><input id='attrs-3e82b43d-0c0d-42fe-8319-fa14512802e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e82b43d-0c0d-42fe-8319-fa14512802e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ed27e7f-75a9-440b-abac-a2645b765675' class='xr-var-data-in' type='checkbox'><label for='data-0ed27e7f-75a9-440b-abac-a2645b765675' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52639.8, 52351.8, 52247.3, ..., 35026. , 35022.3, 35018.7])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg2Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.235e+04 ... 3.502e+04</div><input id='attrs-bc6a69ad-953b-4b03-bb49-91bd7f390aeb' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-bc6a69ad-953b-4b03-bb49-91bd7f390aeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b66ac87c-2044-4ce8-a2a3-81e15150f56b' class='xr-var-data-in' type='checkbox'><label for='data-b66ac87c-2044-4ce8-a2a3-81e15150f56b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52641.1, 52352.6, 52247.8, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg3Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.264e+04 5.236e+04 ... 3.502e+04</div><input id='attrs-ee951233-4064-4c5c-8af0-17c598444939' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ee951233-4064-4c5c-8af0-17c598444939' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a3e1267-68ba-4986-ba32-3c3a4706e542' class='xr-var-data-in' type='checkbox'><label for='data-7a3e1267-68ba-4986-ba32-3c3a4706e542' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52644.4, 52355.6, 52249.3, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg4Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.265e+04 5.236e+04 ... 3.502e+04</div><input id='attrs-426a32b9-245e-4337-8fed-d9b1546d6614' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-426a32b9-245e-4337-8fed-d9b1546d6614' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3025ff42-6e8a-47d6-a62e-30589654452d' class='xr-var-data-in' type='checkbox'><label for='data-3025ff42-6e8a-47d6-a62e-30589654452d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52649.2, 52361.5, 52251.8, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg5Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.266e+04 5.237e+04 ... 3.502e+04</div><input id='attrs-c5b40cb7-46a1-4687-938f-c840eb585d3f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c5b40cb7-46a1-4687-938f-c840eb585d3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5aa7134-c0f4-4a69-957a-d84babcd3a32' class='xr-var-data-in' type='checkbox'><label for='data-b5aa7134-c0f4-4a69-957a-d84babcd3a32' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52655.7, 52371. , 52255.3, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg6Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.266e+04 5.238e+04 ... 3.502e+04</div><input id='attrs-d2a56769-6f18-4776-b607-741cd9b394e7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d2a56769-6f18-4776-b607-741cd9b394e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f28fe0fb-35b7-4ef3-ad9f-4c9a136eb230' class='xr-var-data-in' type='checkbox'><label for='data-f28fe0fb-35b7-4ef3-ad9f-4c9a136eb230' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52663.6, 52383.8, 52259.7, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg7Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.267e+04 5.24e+04 ... 3.502e+04</div><input id='attrs-5b073a4c-e475-468b-9b8f-eb54752a842a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5b073a4c-e475-468b-9b8f-eb54752a842a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cf9efc2-533c-4108-8a1f-470c8f05ce66' class='xr-var-data-in' type='checkbox'><label for='data-3cf9efc2-533c-4108-8a1f-470c8f05ce66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52673. , 52399.3, 52265.1, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg8Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.268e+04 5.242e+04 ... 3.502e+04</div><input id='attrs-1f327247-8a5e-4fd2-9fd3-881b165a37fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1f327247-8a5e-4fd2-9fd3-881b165a37fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e9a0a6f-f345-4e80-948c-6e15ccfbc01f' class='xr-var-data-in' type='checkbox'><label for='data-0e9a0a6f-f345-4e80-948c-6e15ccfbc01f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52683.8, 52416.5, 52271.2, ..., 35025.8, 35022.2, 35018.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg9Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.27e+04 5.244e+04 ... 3.502e+04</div><input id='attrs-28f222e2-92cb-41ce-a1ef-756d4692ad0a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-28f222e2-92cb-41ce-a1ef-756d4692ad0a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92684df4-97a4-4e2f-b6c2-5574541a3a66' class='xr-var-data-in' type='checkbox'><label for='data-92684df4-97a4-4e2f-b6c2-5574541a3a66' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([52696.2, 52435.4, 52278.2, ..., 35025.9, 35022.2, 35018.6])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Seg10Ten</span></div><div class='xr-var-dims'>(Time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.6e+04 5.573e+04 ... 3.713e+04</div><input id='attrs-046a622c-b4e7-446f-af0b-9a0cbbe1cf6b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-046a622c-b4e7-446f-af0b-9a0cbbe1cf6b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02d055ca-1370-4591-95c2-4579193a2108' class='xr-var-data-in' type='checkbox'><label for='data-02d055ca-1370-4591-95c2-4579193a2108' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([55997.5, 55729.1, 55550.8, ..., 37141.8, 37138.1, 37134.4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1887a670-6fdd-4881-9a0b-dc9b18c5aa21' class='xr-section-summary-in' type='checkbox'  ><label for='section-1887a670-6fdd-4881-9a0b-dc9b18c5aa21' class='xr-section-summary' >Indexes: <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-index-name'><div>Time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fb1da581-4edc-4567-82ef-bb91cfae6bfd' class='xr-index-data-in' type='checkbox'/><label for='index-fb1da581-4edc-4567-82ef-bb91cfae6bfd' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([   0.0,  0.025,   0.05,  0.075,    0.1,  0.125,   0.15,  0.175,    0.2,\n",
        "        0.225,\n",
        "       ...\n",
        "       89.275,   89.3, 89.325,  89.35, 89.375,   89.4, 89.425,  89.45, 89.475,\n",
        "         89.5],\n",
-       "      dtype=&#x27;float64&#x27;, name=&#x27;Time&#x27;, length=3581))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a5c03016-6963-4780-a296-29c603a2d456' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a5c03016-6963-4780-a296-29c603a2d456' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>LINE_TYPES :</span></dt><dd>{&#x27;main&#x27;: {&#x27;Diam&#x27;: &#x27;0.0766&#x27;, &#x27;MassDen&#x27;: &#x27;113.35&#x27;, &#x27;EA&#x27;: &#x27;7.536E8&#x27;, &#x27;BA/-zeta&#x27;: &#x27;-1.0&#x27;, &#x27;EI&#x27;: &#x27;0&#x27;, &#x27;Cd&#x27;: &#x27;2.0&#x27;, &#x27;Ca&#x27;: &#x27;0.8&#x27;, &#x27;CdAx&#x27;: &#x27;0.4&#x27;, &#x27;CaAx&#x27;: &#x27;0.25&#x27;}, &#x27;units&#x27;: [&#x27;(m)&#x27;, &#x27;(kg/m)&#x27;, &#x27;(N)&#x27;, &#x27;(N-s/-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>POINTS :</span></dt><dd>{&#x27;1&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;418.8&#x27;, &#x27;Y&#x27;: &#x27;725.383&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;2&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;-837.6&#x27;, &#x27;Y&#x27;: &#x27;0.0&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;3&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;418.8&#x27;, &#x27;Y&#x27;: &#x27;-725.383&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;4&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;20.434&#x27;, &#x27;Y&#x27;: &#x27;35.393&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;5&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;-40.868&#x27;, &#x27;Y&#x27;: &#x27;0.0&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;6&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;20.434&#x27;, &#x27;Y&#x27;: &#x27;-35.393&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;units&#x27;: [&#x27;(-)&#x27;, &#x27;(m)&#x27;, &#x27;(m)&#x27;, &#x27;(m)&#x27;, &#x27;(kg)&#x27;, &#x27;(m^3)&#x27;, &#x27;(m^2)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>LINES :</span></dt><dd>{&#x27;1&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;1&#x27;, &#x27;AttachB&#x27;: &#x27;4&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;2&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;2&#x27;, &#x27;AttachB&#x27;: &#x27;5&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;3&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;3&#x27;, &#x27;AttachB&#x27;: &#x27;6&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;units&#x27;: [&#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(m)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>OPTIONS :</span></dt><dd>{&#x27;dtM&#x27;: &#x27;0.001&#x27;, &#x27;kbot&#x27;: &#x27;3.0e6&#x27;, &#x27;cbot&#x27;: &#x27;3.0e5&#x27;, &#x27;dtIC&#x27;: &#x27;2.0&#x27;, &#x27;TmaxIC&#x27;: &#x27;60.0&#x27;, &#x27;CdScaleIC&#x27;: &#x27;4.0&#x27;, &#x27;threshIC&#x27;: &#x27;0.01&#x27;}</dd></dl></div></li></ul></div></div>"
+       "      dtype=&#x27;float64&#x27;, name=&#x27;Time&#x27;, length=3581))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d560eb7-d760-4b56-b43f-07d6f9163d6e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d560eb7-d760-4b56-b43f-07d6f9163d6e' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>LINE_TYPES :</span></dt><dd>{&#x27;main&#x27;: {&#x27;Diam&#x27;: &#x27;0.0766&#x27;, &#x27;MassDen&#x27;: &#x27;113.35&#x27;, &#x27;EA&#x27;: &#x27;7.536E8&#x27;, &#x27;BA/-zeta&#x27;: &#x27;-1.0&#x27;, &#x27;EI&#x27;: &#x27;0&#x27;, &#x27;Cd&#x27;: &#x27;2.0&#x27;, &#x27;Ca&#x27;: &#x27;0.8&#x27;, &#x27;CdAx&#x27;: &#x27;0.4&#x27;, &#x27;CaAx&#x27;: &#x27;0.25&#x27;}, &#x27;units&#x27;: [&#x27;(m)&#x27;, &#x27;(kg/m)&#x27;, &#x27;(N)&#x27;, &#x27;(N-s/-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>POINTS :</span></dt><dd>{&#x27;1&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;418.8&#x27;, &#x27;Y&#x27;: &#x27;725.383&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;2&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;-837.6&#x27;, &#x27;Y&#x27;: &#x27;0.0&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;3&#x27;: {&#x27;Attachment&#x27;: &#x27;Fixed&#x27;, &#x27;X&#x27;: &#x27;418.8&#x27;, &#x27;Y&#x27;: &#x27;-725.383&#x27;, &#x27;Z&#x27;: &#x27;-200.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;4&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;20.434&#x27;, &#x27;Y&#x27;: &#x27;35.393&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;5&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;-40.868&#x27;, &#x27;Y&#x27;: &#x27;0.0&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;6&#x27;: {&#x27;Attachment&#x27;: &#x27;Vessel&#x27;, &#x27;X&#x27;: &#x27;20.434&#x27;, &#x27;Y&#x27;: &#x27;-35.393&#x27;, &#x27;Z&#x27;: &#x27;-14.0&#x27;, &#x27;M&#x27;: &#x27;0&#x27;, &#x27;V&#x27;: &#x27;0&#x27;, &#x27;CdA&#x27;: &#x27;0&#x27;, &#x27;CA&#x27;: &#x27;0&#x27;}, &#x27;units&#x27;: [&#x27;(-)&#x27;, &#x27;(m)&#x27;, &#x27;(m)&#x27;, &#x27;(m)&#x27;, &#x27;(kg)&#x27;, &#x27;(m^3)&#x27;, &#x27;(m^2)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>LINES :</span></dt><dd>{&#x27;1&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;1&#x27;, &#x27;AttachB&#x27;: &#x27;4&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;2&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;2&#x27;, &#x27;AttachB&#x27;: &#x27;5&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;3&#x27;: {&#x27;LineType&#x27;: &#x27;main&#x27;, &#x27;AttachA&#x27;: &#x27;3&#x27;, &#x27;AttachB&#x27;: &#x27;6&#x27;, &#x27;UnstrLen&#x27;: &#x27;835.35&#x27;, &#x27;NumSegs&#x27;: &#x27;20&#x27;, &#x27;Outputs&#x27;: &#x27;-&#x27;}, &#x27;units&#x27;: [&#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;, &#x27;(m)&#x27;, &#x27;(-)&#x27;, &#x27;(-)&#x27;]}</dd><dt><span>OPTIONS :</span></dt><dd>{&#x27;dtM&#x27;: &#x27;0.001&#x27;, &#x27;kbot&#x27;: &#x27;3.0e6&#x27;, &#x27;cbot&#x27;: &#x27;3.0e5&#x27;, &#x27;dtIC&#x27;: &#x27;2.0&#x27;, &#x27;TmaxIC&#x27;: &#x27;60.0&#x27;, &#x27;CdScaleIC&#x27;: &#x27;4.0&#x27;, &#x27;threshIC&#x27;: &#x27;0.01&#x27;}</dd></dl></div></li></ul></div></div>"
       ],
       "text/plain": [
-       "<xarray.Dataset> Size: 1MB\n",
+       "<xarray.Dataset>\n",
        "Dimensions:   (Time: 3581)\n",
        "Coordinates:\n",
-       "  * Time      (Time) float64 29kB 0.0 0.025 0.05 0.075 ... 89.45 89.47 89.5\n",
+       "  * Time      (Time) float64 0.0 0.025 0.05 0.075 0.1 ... 89.42 89.45 89.47 89.5\n",
        "Data variables: (12/43)\n",
-       "    Node0px   (Time) float64 29kB -300.0 -300.0 -300.0 ... -300.0 -300.0 -300.0\n",
-       "    Node0py   (Time) float64 29kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
-       "    Node0pz   (Time) float64 29kB -56.0 -56.0 -56.0 -56.0 ... -56.0 -56.0 -56.0\n",
-       "    Node1px   (Time) float64 29kB -295.0 -295.0 -295.0 ... -295.0 -295.0 -295.0\n",
-       "    Node1py   (Time) float64 29kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n",
-       "    Node1pz   (Time) float64 29kB -56.02 -56.02 -56.02 ... -56.02 -56.02 -56.02\n",
+       "    Node0px   (Time) float64 -300.0 -300.0 -300.0 ... -300.0 -300.0 -300.0\n",
+       "    Node0py   (Time) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    Node0pz   (Time) float64 -56.0 -56.0 -56.0 -56.0 ... -56.0 -56.0 -56.0 -56.0\n",
+       "    Node1px   (Time) float64 -295.0 -295.0 -295.0 ... -295.0 -295.0 -295.0\n",
+       "    Node1py   (Time) float64 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0\n",
+       "    Node1pz   (Time) float64 -56.02 -56.02 -56.02 ... -56.02 -56.02 -56.02\n",
        "    ...        ...\n",
-       "    Seg5Ten   (Time) float64 29kB 5.266e+04 5.237e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg6Ten   (Time) float64 29kB 5.266e+04 5.238e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg7Ten   (Time) float64 29kB 5.267e+04 5.24e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg8Ten   (Time) float64 29kB 5.268e+04 5.242e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg9Ten   (Time) float64 29kB 5.27e+04 5.244e+04 ... 3.502e+04 3.502e+04\n",
-       "    Seg10Ten  (Time) float64 29kB 5.6e+04 5.573e+04 ... 3.714e+04 3.713e+04\n",
+       "    Seg5Ten   (Time) float64 5.266e+04 5.237e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg6Ten   (Time) float64 5.266e+04 5.238e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg7Ten   (Time) float64 5.267e+04 5.24e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg8Ten   (Time) float64 5.268e+04 5.242e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg9Ten   (Time) float64 5.27e+04 5.244e+04 ... 3.502e+04 3.502e+04\n",
+       "    Seg10Ten  (Time) float64 5.6e+04 5.573e+04 5.555e+04 ... 3.714e+04 3.713e+04\n",
        "Attributes:\n",
        "    LINE_TYPES:  {'main': {'Diam': '0.0766', 'MassDen': '113.35', 'EA': '7.53...\n",
        "    POINTS:      {'1': {'Attachment': 'Fixed', 'X': '418.8', 'Y': '725.383', ...\n",
@@ -465,14 +466,18 @@
        "    OPTIONS:     {'dtM': '0.001', 'kbot': '3.0e6', 'cbot': '3.0e5', 'dtIC': '..."
       ]
      },
-     "execution_count": 2,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "fpath = \".\\data\\mooring\\line1_test.out\"\n",
-    "inputfile = \".\\data\\mooring\\TestInput.MD.dat\"\n",
+    "# Get the directory of the current notebook\n",
+    "notebook_dir = os.path.dirname(os.path.abspath(\"__file__\"))\n",
+    "\n",
+    "# Define the relative paths\n",
+    "fpath = os.path.join(notebook_dir, \"data\", \"mooring\", \"line1_test.out\")\n",
+    "inputfile = os.path.join(notebook_dir, \"data\", \"mooring\", \"TestInput.MD.dat\")\n",
     "\n",
     "ds = mooring.io.read_moordyn(fpath, input_file=inputfile)\n",
     "ds"
@@ -391082,7 +391087,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,
diff --git a/examples/wave_example.ipynb b/examples/wave_example.ipynb
index 02680f530..d3c2ba897 100644
--- a/examples/wave_example.ipynb
+++ b/examples/wave_example.ipynb
@@ -35,6 +35,14 @@
    "execution_count": 2,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\users\\sterl\\codes\\mhkit-python\\mhkit\\wave\\io\\ndbc.py:99: UserWarning: Could not infer format, so each element will be parsed individually, falling back to `dateutil`. To ensure parsing is consistent and as-expected, please specify a format.\n",
+      "  data = pd.read_csv(\n"
+     ]
+    },
     {
      "data": {
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        "      <th>Te</th>\n",
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@@ -555,6 +567,7 @@
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@@ -601,6 +614,10 @@
        "      <th></th>\n",
        "      <th>Hm0</th>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>index</th>\n",
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@@ -629,6 +646,7 @@
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@@ -675,6 +693,10 @@
        "      <th></th>\n",
        "      <th>J</th>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>index</th>\n",
+       "      <th></th>\n",
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@@ -703,6 +725,7 @@
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        "2018-01-01 02:40:00  3278.298930\n",
@@ -742,6 +765,7 @@
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+       "index\n",
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        "2018-01-01 02:40:00    7.498263\n",
@@ -770,6 +794,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "index\n",
       "2018-01-01 00:40:00    0.939574\n",
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       "2018-01-31 23:40:00    2.895928\n",
       "Name: Hm0, Length: 743, dtype: float64\n",
+      "index\n",
       "2018-01-01 00:40:00     3354.825613\n",
       "2018-01-01 01:40:00     3916.541523\n",
       "2018-01-01 02:40:00     3278.298930\n",
@@ -861,7 +887,7 @@
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
+       "      <th>y_centers</th>\n",
        "      <th>0.0</th>\n",
        "      <th>1.0</th>\n",
        "      <th>2.0</th>\n",
@@ -880,6 +906,26 @@
        "      <th>15.0</th>\n",
        "      <th>16.0</th>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>x_centers</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
@@ -1327,77 +1373,80 @@
        "</div>"
       ],
       "text/plain": [
-       "      0.0   1.0   2.0   3.0   4.0   5.0       6.0       7.0       8.0   \\\n",
-       "0.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "0.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.120286  0.053376   \n",
-       "1.0    NaN   NaN   NaN   NaN   NaN   NaN  0.110686  0.068070  0.049452   \n",
-       "1.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.019749  0.018673   \n",
-       "2.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.013882  0.012547   \n",
-       "2.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.007244   \n",
-       "3.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.004500  0.005660   \n",
-       "3.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.003924   \n",
-       "4.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.003185   \n",
-       "4.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.002343   \n",
-       "5.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.001913   \n",
-       "5.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.002101   \n",
-       "6.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "6.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "7.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "7.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "8.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "8.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "9.0    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "9.5    NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "10.0   NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
-       "10.5   NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "y_centers  0.0   1.0   2.0   3.0   4.0   5.0       6.0       7.0       8.0   \\\n",
+       "x_centers                                                                     \n",
+       "0.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "0.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.120286  0.053376   \n",
+       "1.0         NaN   NaN   NaN   NaN   NaN   NaN  0.110686  0.068070  0.049452   \n",
+       "1.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.019749  0.018673   \n",
+       "2.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.013882  0.012547   \n",
+       "2.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.007244   \n",
+       "3.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN  0.004500  0.005660   \n",
+       "3.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.003924   \n",
+       "4.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.003185   \n",
+       "4.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.002343   \n",
+       "5.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.001913   \n",
+       "5.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN  0.002101   \n",
+       "6.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "6.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "7.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "7.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "8.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "8.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "9.0         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "9.5         NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "10.0        NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
+       "10.5        NaN   NaN   NaN   NaN   NaN   NaN       NaN       NaN       NaN   \n",
        "\n",
-       "          9.0       10.0      11.0      12.0      13.0      14.0      15.0  \\\n",
-       "0.0        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
-       "0.5        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
-       "1.0   0.065912       NaN  0.056593  0.029950  0.017234       NaN       NaN   \n",
-       "1.5        NaN       NaN  0.012473  0.011205  0.012307  0.010432       NaN   \n",
-       "2.0   0.009672  0.008770  0.008585  0.007525  0.005272  0.007809       NaN   \n",
-       "2.5   0.006488  0.005788  0.005652  0.005180  0.004260  0.003623  0.004509   \n",
-       "3.0   0.004691  0.004109  0.003952  0.003104  0.003408  0.002291  0.001792   \n",
-       "3.5   0.003674  0.003020  0.002746  0.002247  0.002000  0.002257  0.002033   \n",
-       "4.0   0.002513  0.002386  0.002147  0.002246  0.001605  0.001730       NaN   \n",
-       "4.5   0.002087  0.001919  0.001590  0.001438       NaN       NaN       NaN   \n",
-       "5.0   0.001720  0.001716  0.001411  0.001219  0.001345       NaN       NaN   \n",
-       "5.5   0.001516  0.001331  0.000902  0.001033       NaN       NaN       NaN   \n",
-       "6.0   0.001097  0.000895       NaN  0.000858  0.000987       NaN       NaN   \n",
-       "6.5   0.000837  0.001024  0.000419       NaN  0.000688       NaN       NaN   \n",
-       "7.0        NaN       NaN       NaN  0.000461  0.000633       NaN       NaN   \n",
-       "7.5        NaN  0.000553       NaN       NaN  0.000312  0.000437       NaN   \n",
-       "8.0        NaN       NaN       NaN       NaN       NaN  0.000443  0.000351   \n",
-       "8.5        NaN       NaN       NaN       NaN       NaN       NaN  0.000418   \n",
-       "9.0        NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
-       "9.5        NaN       NaN       NaN       NaN       NaN       NaN  0.000153   \n",
-       "10.0       NaN       NaN       NaN       NaN       NaN       NaN       NaN   \n",
-       "10.5       NaN       NaN       NaN       NaN       NaN       NaN  0.000204   \n",
+       "y_centers      9.0       10.0      11.0      12.0      13.0      14.0  \\\n",
+       "x_centers                                                               \n",
+       "0.0             NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "0.5             NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "1.0        0.065912       NaN  0.056593  0.029950  0.017234       NaN   \n",
+       "1.5             NaN       NaN  0.012473  0.011205  0.012307  0.010432   \n",
+       "2.0        0.009672  0.008770  0.008585  0.007525  0.005272  0.007809   \n",
+       "2.5        0.006488  0.005788  0.005652  0.005180  0.004260  0.003623   \n",
+       "3.0        0.004691  0.004109  0.003952  0.003104  0.003408  0.002291   \n",
+       "3.5        0.003674  0.003020  0.002746  0.002247  0.002000  0.002257   \n",
+       "4.0        0.002513  0.002386  0.002147  0.002246  0.001605  0.001730   \n",
+       "4.5        0.002087  0.001919  0.001590  0.001438       NaN       NaN   \n",
+       "5.0        0.001720  0.001716  0.001411  0.001219  0.001345       NaN   \n",
+       "5.5        0.001516  0.001331  0.000902  0.001033       NaN       NaN   \n",
+       "6.0        0.001097  0.000895       NaN  0.000858  0.000987       NaN   \n",
+       "6.5        0.000837  0.001024  0.000419       NaN  0.000688       NaN   \n",
+       "7.0             NaN       NaN       NaN  0.000461  0.000633       NaN   \n",
+       "7.5             NaN  0.000553       NaN       NaN  0.000312  0.000437   \n",
+       "8.0             NaN       NaN       NaN       NaN       NaN  0.000443   \n",
+       "8.5             NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "9.0             NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "9.5             NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "10.0            NaN       NaN       NaN       NaN       NaN       NaN   \n",
+       "10.5            NaN       NaN       NaN       NaN       NaN       NaN   \n",
        "\n",
-       "          16.0  \n",
-       "0.0        NaN  \n",
-       "0.5        NaN  \n",
-       "1.0        NaN  \n",
-       "1.5        NaN  \n",
-       "2.0        NaN  \n",
-       "2.5        NaN  \n",
-       "3.0        NaN  \n",
-       "3.5        NaN  \n",
-       "4.0        NaN  \n",
-       "4.5        NaN  \n",
-       "5.0        NaN  \n",
-       "5.5        NaN  \n",
-       "6.0        NaN  \n",
-       "6.5        NaN  \n",
-       "7.0        NaN  \n",
-       "7.5        NaN  \n",
-       "8.0        NaN  \n",
-       "8.5   0.000405  \n",
-       "9.0        NaN  \n",
-       "9.5        NaN  \n",
-       "10.0  0.000281  \n",
-       "10.5  0.000225  "
+       "y_centers      15.0      16.0  \n",
+       "x_centers                      \n",
+       "0.0             NaN       NaN  \n",
+       "0.5             NaN       NaN  \n",
+       "1.0             NaN       NaN  \n",
+       "1.5             NaN       NaN  \n",
+       "2.0             NaN       NaN  \n",
+       "2.5        0.004509       NaN  \n",
+       "3.0        0.001792       NaN  \n",
+       "3.5        0.002033       NaN  \n",
+       "4.0             NaN       NaN  \n",
+       "4.5             NaN       NaN  \n",
+       "5.0             NaN       NaN  \n",
+       "5.5             NaN       NaN  \n",
+       "6.0             NaN       NaN  \n",
+       "6.5             NaN       NaN  \n",
+       "7.0             NaN       NaN  \n",
+       "7.5             NaN       NaN  \n",
+       "8.0        0.000351       NaN  \n",
+       "8.5        0.000418  0.000405  \n",
+       "9.0             NaN       NaN  \n",
+       "9.5        0.000153       NaN  \n",
+       "10.0            NaN  0.000281  \n",
+       "10.5       0.000204  0.000225  "
       ]
      },
      "execution_count": 10,
@@ -1458,7 +1507,7 @@
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
+       "      <th>y_centers</th>\n",
        "      <th>0.0</th>\n",
        "      <th>1.0</th>\n",
        "      <th>2.0</th>\n",
@@ -1477,6 +1526,26 @@
        "      <th>15.0</th>\n",
        "      <th>16.0</th>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>x_centers</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
@@ -1924,77 +1993,80 @@
        "</div>"
       ],
       "text/plain": [
-       "      0.0   1.0   2.0   3.0   4.0   5.0       6.0       7.0       8.0   \\\n",
-       "0.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "0.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.002692  0.001346   \n",
-       "1.0    0.0   0.0   0.0   0.0   0.0   0.0  0.001346  0.006729  0.004038   \n",
-       "1.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.005384  0.002692   \n",
-       "2.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.002692  0.005384   \n",
-       "2.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.013459   \n",
-       "3.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.001346  0.021534   \n",
-       "3.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.006729   \n",
-       "4.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.009421   \n",
-       "4.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.016151   \n",
-       "5.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.002692   \n",
-       "5.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.001346   \n",
-       "6.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "6.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "7.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "7.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "8.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "8.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "9.0    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "9.5    0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "10.0   0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
-       "10.5   0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "y_centers  0.0   1.0   2.0   3.0   4.0   5.0       6.0       7.0       8.0   \\\n",
+       "x_centers                                                                     \n",
+       "0.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "0.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.002692  0.001346   \n",
+       "1.0         0.0   0.0   0.0   0.0   0.0   0.0  0.001346  0.006729  0.004038   \n",
+       "1.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.005384  0.002692   \n",
+       "2.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.002692  0.005384   \n",
+       "2.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.013459   \n",
+       "3.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.001346  0.021534   \n",
+       "3.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.006729   \n",
+       "4.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.009421   \n",
+       "4.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.016151   \n",
+       "5.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.002692   \n",
+       "5.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.001346   \n",
+       "6.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "6.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "7.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "7.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "8.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "8.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "9.0         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "9.5         0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "10.0        0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
+       "10.5        0.0   0.0   0.0   0.0   0.0   0.0  0.000000  0.000000  0.000000   \n",
        "\n",
-       "          9.0       10.0      11.0      12.0      13.0      14.0      15.0  \\\n",
-       "0.0   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
-       "0.5   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
-       "1.0   0.001346  0.000000  0.002692  0.002692  0.001346  0.000000  0.000000   \n",
-       "1.5   0.000000  0.000000  0.009421  0.004038  0.006729  0.005384  0.000000   \n",
-       "2.0   0.018843  0.018843  0.029610  0.021534  0.001346  0.002692  0.000000   \n",
-       "2.5   0.052490  0.055182  0.018843  0.025572  0.022880  0.005384  0.001346   \n",
-       "3.0   0.044415  0.047106  0.020188  0.012113  0.010767  0.010767  0.001346   \n",
-       "3.5   0.040377  0.029610  0.047106  0.004038  0.008075  0.004038  0.001346   \n",
-       "4.0   0.017497  0.029610  0.040377  0.002692  0.004038  0.005384  0.000000   \n",
-       "4.5   0.013459  0.017497  0.022880  0.012113  0.000000  0.000000  0.000000   \n",
-       "5.0   0.008075  0.008075  0.010767  0.022880  0.001346  0.000000  0.000000   \n",
-       "5.5   0.012113  0.006729  0.004038  0.014805  0.000000  0.000000  0.000000   \n",
-       "6.0   0.002692  0.002692  0.000000  0.005384  0.001346  0.000000  0.000000   \n",
-       "6.5   0.002692  0.002692  0.001346  0.000000  0.002692  0.000000  0.000000   \n",
-       "7.0   0.000000  0.000000  0.000000  0.001346  0.004038  0.000000  0.000000   \n",
-       "7.5   0.000000  0.001346  0.000000  0.000000  0.001346  0.008075  0.000000   \n",
-       "8.0   0.000000  0.000000  0.000000  0.000000  0.000000  0.002692  0.002692   \n",
-       "8.5   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.001346   \n",
-       "9.0   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
-       "9.5   0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.001346   \n",
-       "10.0  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
-       "10.5  0.000000  0.000000  0.000000  0.000000  0.000000  0.000000  0.001346   \n",
+       "y_centers      9.0       10.0      11.0      12.0      13.0      14.0  \\\n",
+       "x_centers                                                               \n",
+       "0.0        0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "0.5        0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "1.0        0.001346  0.000000  0.002692  0.002692  0.001346  0.000000   \n",
+       "1.5        0.000000  0.000000  0.009421  0.004038  0.006729  0.005384   \n",
+       "2.0        0.018843  0.018843  0.029610  0.021534  0.001346  0.002692   \n",
+       "2.5        0.052490  0.055182  0.018843  0.025572  0.022880  0.005384   \n",
+       "3.0        0.044415  0.047106  0.020188  0.012113  0.010767  0.010767   \n",
+       "3.5        0.040377  0.029610  0.047106  0.004038  0.008075  0.004038   \n",
+       "4.0        0.017497  0.029610  0.040377  0.002692  0.004038  0.005384   \n",
+       "4.5        0.013459  0.017497  0.022880  0.012113  0.000000  0.000000   \n",
+       "5.0        0.008075  0.008075  0.010767  0.022880  0.001346  0.000000   \n",
+       "5.5        0.012113  0.006729  0.004038  0.014805  0.000000  0.000000   \n",
+       "6.0        0.002692  0.002692  0.000000  0.005384  0.001346  0.000000   \n",
+       "6.5        0.002692  0.002692  0.001346  0.000000  0.002692  0.000000   \n",
+       "7.0        0.000000  0.000000  0.000000  0.001346  0.004038  0.000000   \n",
+       "7.5        0.000000  0.001346  0.000000  0.000000  0.001346  0.008075   \n",
+       "8.0        0.000000  0.000000  0.000000  0.000000  0.000000  0.002692   \n",
+       "8.5        0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "9.0        0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "9.5        0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "10.0       0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
+       "10.5       0.000000  0.000000  0.000000  0.000000  0.000000  0.000000   \n",
        "\n",
-       "          16.0  \n",
-       "0.0   0.000000  \n",
-       "0.5   0.000000  \n",
-       "1.0   0.000000  \n",
-       "1.5   0.000000  \n",
-       "2.0   0.000000  \n",
-       "2.5   0.000000  \n",
-       "3.0   0.000000  \n",
-       "3.5   0.000000  \n",
-       "4.0   0.000000  \n",
-       "4.5   0.000000  \n",
-       "5.0   0.000000  \n",
-       "5.5   0.000000  \n",
-       "6.0   0.000000  \n",
-       "6.5   0.000000  \n",
-       "7.0   0.000000  \n",
-       "7.5   0.000000  \n",
-       "8.0   0.000000  \n",
-       "8.5   0.001346  \n",
-       "9.0   0.000000  \n",
-       "9.5   0.000000  \n",
-       "10.0  0.001346  \n",
-       "10.5  0.001346  "
+       "y_centers      15.0      16.0  \n",
+       "x_centers                      \n",
+       "0.0        0.000000  0.000000  \n",
+       "0.5        0.000000  0.000000  \n",
+       "1.0        0.000000  0.000000  \n",
+       "1.5        0.000000  0.000000  \n",
+       "2.0        0.000000  0.000000  \n",
+       "2.5        0.001346  0.000000  \n",
+       "3.0        0.001346  0.000000  \n",
+       "3.5        0.001346  0.000000  \n",
+       "4.0        0.000000  0.000000  \n",
+       "4.5        0.000000  0.000000  \n",
+       "5.0        0.000000  0.000000  \n",
+       "5.5        0.000000  0.000000  \n",
+       "6.0        0.000000  0.000000  \n",
+       "6.5        0.000000  0.000000  \n",
+       "7.0        0.000000  0.000000  \n",
+       "7.5        0.000000  0.000000  \n",
+       "8.0        0.002692  0.000000  \n",
+       "8.5        0.001346  0.001346  \n",
+       "9.0        0.000000  0.000000  \n",
+       "9.5        0.001346  0.000000  \n",
+       "10.0       0.000000  0.001346  \n",
+       "10.5       0.001346  0.001346  "
       ]
      },
      "execution_count": 11,
@@ -2085,7 +2157,7 @@
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
+       "      <th>y_centers</th>\n",
        "      <th>0.0</th>\n",
        "      <th>1.0</th>\n",
        "      <th>2.0</th>\n",
@@ -2104,6 +2176,26 @@
        "      <th>15.0</th>\n",
        "      <th>16.0</th>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>x_centers</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
@@ -2551,53 +2643,80 @@
        "</div>"
       ],
       "text/plain": [
-       "      0.0   1.0   2.0   3.0   4.0   5.0      6.0      7.0      8.0      9.0   \\\n",
-       "0.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "0.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN  224.996  117.594      NaN   \n",
-       "1.0    NaN   NaN   NaN   NaN   NaN   NaN  212.762  202.713  188.707  187.103   \n",
-       "1.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN  176.402  199.802      NaN   \n",
-       "2.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN  203.667  216.857  192.965   \n",
-       "2.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  193.397  203.529   \n",
-       "3.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN  170.739  216.459  197.484   \n",
-       "3.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  194.894  214.108   \n",
-       "4.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  217.289  189.403   \n",
-       "4.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  197.994  194.238   \n",
-       "5.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  198.149  196.527   \n",
-       "5.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  249.158  212.561   \n",
-       "6.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN  182.314   \n",
-       "6.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN  164.712   \n",
-       "7.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "7.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "8.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "8.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "9.0    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "9.5    NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "10.0   NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
-       "10.5   NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN      NaN   \n",
+       "y_centers  0.0   1.0   2.0   3.0   4.0   5.0      6.0      7.0      8.0   \\\n",
+       "x_centers                                                                  \n",
+       "0.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "0.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN  224.996  117.594   \n",
+       "1.0         NaN   NaN   NaN   NaN   NaN   NaN  212.762  202.713  188.707   \n",
+       "1.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN  176.402  199.802   \n",
+       "2.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN  203.667  216.857   \n",
+       "2.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  193.397   \n",
+       "3.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN  170.739  216.459   \n",
+       "3.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  194.894   \n",
+       "4.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  217.289   \n",
+       "4.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  197.994   \n",
+       "5.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  198.149   \n",
+       "5.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN  249.158   \n",
+       "6.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "6.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "7.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "7.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "8.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "8.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "9.0         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "9.5         NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "10.0        NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "10.5        NaN   NaN   NaN   NaN   NaN   NaN      NaN      NaN      NaN   \n",
+       "\n",
+       "y_centers     9.0      10.0     11.0     12.0     13.0     14.0     15.0  \\\n",
+       "x_centers                                                                  \n",
+       "0.0            NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
+       "0.5            NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
+       "1.0        187.103      NaN  213.926  174.154  164.886      NaN      NaN   \n",
+       "1.5            NaN      NaN  201.883  191.598  221.705  190.124      NaN   \n",
+       "2.0        192.965  201.633  216.268  209.634  162.569  232.530      NaN   \n",
+       "2.5        203.529  196.907  212.883  211.277  202.760  199.263  272.421   \n",
+       "3.0        197.484  200.895  212.107  193.837  222.185  169.497  122.296   \n",
+       "3.5        214.108  202.725  206.901  184.099  186.077  221.659  186.201   \n",
+       "4.0        189.403  201.362  207.532  207.971  172.771  213.854      NaN   \n",
+       "4.5        194.238  205.559  203.195  197.980      NaN      NaN      NaN   \n",
+       "5.0        196.527  222.219  215.221  204.002  254.004      NaN      NaN   \n",
+       "5.5        212.561  212.734  168.655  208.220      NaN      NaN      NaN   \n",
+       "6.0        182.314  159.418      NaN  208.418  241.347      NaN      NaN   \n",
+       "6.5        164.712  233.890  110.517      NaN  207.919      NaN      NaN   \n",
+       "7.0            NaN      NaN      NaN  155.691  229.022      NaN      NaN   \n",
+       "7.5            NaN  166.855      NaN      NaN  128.897  198.053      NaN   \n",
+       "8.0            NaN      NaN      NaN      NaN      NaN  230.281  184.510   \n",
+       "8.5            NaN      NaN      NaN      NaN      NaN      NaN  248.338   \n",
+       "9.0            NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
+       "9.5            NaN      NaN      NaN      NaN      NaN      NaN  116.230   \n",
+       "10.0           NaN      NaN      NaN      NaN      NaN      NaN      NaN   \n",
+       "10.5           NaN      NaN      NaN      NaN      NaN      NaN  190.849   \n",
        "\n",
-       "         10.0     11.0     12.0     13.0     14.0     15.0     16.0  \n",
-       "0.0       NaN      NaN      NaN      NaN      NaN      NaN      NaN  \n",
-       "0.5       NaN      NaN      NaN      NaN      NaN      NaN      NaN  \n",
-       "1.0       NaN  213.926  174.154  164.886      NaN      NaN      NaN  \n",
-       "1.5       NaN  201.883  191.598  221.705  190.124      NaN      NaN  \n",
-       "2.0   201.633  216.268  209.634  162.569  232.530      NaN      NaN  \n",
-       "2.5   196.907  212.883  211.277  202.760  199.263  272.421      NaN  \n",
-       "3.0   200.895  212.107  193.837  222.185  169.497  122.296      NaN  \n",
-       "3.5   202.725  206.901  184.099  186.077  221.659  186.201      NaN  \n",
-       "4.0   201.362  207.532  207.971  172.771  213.854      NaN      NaN  \n",
-       "4.5   205.559  203.195  197.980      NaN      NaN      NaN      NaN  \n",
-       "5.0   222.219  215.221  204.002  254.004      NaN      NaN      NaN  \n",
-       "5.5   212.734  168.655  208.220      NaN      NaN      NaN      NaN  \n",
-       "6.0   159.418      NaN  208.418  241.347      NaN      NaN      NaN  \n",
-       "6.5   233.890  110.517      NaN  207.919      NaN      NaN      NaN  \n",
-       "7.0       NaN      NaN  155.691  229.022      NaN      NaN      NaN  \n",
-       "7.5   166.855      NaN      NaN  128.897  198.053      NaN      NaN  \n",
-       "8.0       NaN      NaN      NaN      NaN  230.281  184.510      NaN  \n",
-       "8.5       NaN      NaN      NaN      NaN      NaN  248.338  264.534  \n",
-       "9.0       NaN      NaN      NaN      NaN      NaN      NaN      NaN  \n",
-       "9.5       NaN      NaN      NaN      NaN      NaN  116.230      NaN  \n",
-       "10.0      NaN      NaN      NaN      NaN      NaN      NaN  244.634  \n",
-       "10.5      NaN      NaN      NaN      NaN      NaN  190.849  212.411  "
+       "y_centers     16.0  \n",
+       "x_centers           \n",
+       "0.0            NaN  \n",
+       "0.5            NaN  \n",
+       "1.0            NaN  \n",
+       "1.5            NaN  \n",
+       "2.0            NaN  \n",
+       "2.5            NaN  \n",
+       "3.0            NaN  \n",
+       "3.5            NaN  \n",
+       "4.0            NaN  \n",
+       "4.5            NaN  \n",
+       "5.0            NaN  \n",
+       "5.5            NaN  \n",
+       "6.0            NaN  \n",
+       "6.5            NaN  \n",
+       "7.0            NaN  \n",
+       "7.5            NaN  \n",
+       "8.0            NaN  \n",
+       "8.5        264.534  \n",
+       "9.0            NaN  \n",
+       "9.5            NaN  \n",
+       "10.0       244.634  \n",
+       "10.5       212.411  "
       ]
      },
      "execution_count": 14,
@@ -2636,8 +2755,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MAEP from timeseries =  1767087.527586333\n",
-      "MAEP from matrices =  1781210.8652839188\n"
+      "MAEP from timeseries =  1767087.5275863332\n",
+      "MAEP from matrices =  1781210.865283919\n"
      ]
     }
    ],
@@ -2646,10 +2765,15 @@
     "maep_timeseries = wave.performance.mean_annual_energy_production_timeseries(L, J)\n",
     "print(\"MAEP from timeseries = \", maep_timeseries)\n",
     "\n",
-    "# Calcaulte maep from matrix\n",
-    "maep_matrix = wave.performance.mean_annual_energy_production_matrix(\n",
-    "    LM_mean, JM, LM_freq\n",
-    ")\n",
+    "# Calcaulte maep from matrix \n",
+    "# See Issue #339\n",
+    "# maep_matrix = wave.performance.mean_annual_energy_production_matrix(\n",
+    "#     LM_mean, JM, LM_freq\n",
+    "# )\n",
+    "\n",
+    "T = 8766  # Average length of a year (h)\n",
+    "maep_matrix = T * np.nansum(LM_mean * JM * LM_freq)\n",
+    "\n",
     "print(\"MAEP from matrices = \", maep_matrix)"
    ]
   },
@@ -2668,14 +2792,12 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x288 with 2 Axes>"
+       "<Figure size 640x480 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -2702,7 +2824,7 @@
     {
      "data": {
       "text/plain": [
-       "<AxesSubplot:xlabel='Te (s)', ylabel='Hm0 (m)'>"
+       "<Axes: xlabel='Te (s)', ylabel='Hm0 (m)'>"
       ]
      },
      "execution_count": 17,
@@ -2711,14 +2833,12 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
-       "<Figure size 432x432 with 2 Axes>"
+       "<Figure size 600x600 with 2 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -2755,7 +2875,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.8"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

From 38e9150badfb05b9a0010039e1d1a5e8cedc211c Mon Sep 17 00:00:00 2001
From: ssolson <sterlingolson@yahoo.com>
Date: Mon, 15 Jul 2024 09:15:54 -0600
Subject: [PATCH 7/7] save sorted values

---
 mhkit/river/graphics.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/mhkit/river/graphics.py b/mhkit/river/graphics.py
index 396ce1271..7272ded81 100644
--- a/mhkit/river/graphics.py
+++ b/mhkit/river/graphics.py
@@ -118,7 +118,7 @@ def plot_velocity_duration_curve(V, F, label=None, ax=None):
     """
     # Sort by F
     temp = xr.Dataset(data_vars={"V": V, "F": F})
-    temp.sortby("F", ascending=False)
+    temp = temp.sortby("F", ascending=False)
 
     ax = _xy_plot(
         temp["V"],