diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 5cccdab..b2c21aa 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -19,9 +19,9 @@ jobs:
         python-version: ["3.11", "3.12", "3.13"]
 
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
     - name: Install uv
-      uses: astral-sh/setup-uv@v4
+      uses: astral-sh/setup-uv@v7
       with:
         enable-cache: true
     - name: Set up Python ${{ matrix.python-version }}
@@ -31,6 +31,4 @@ jobs:
     - name: Build the package
       run: uv build
     - name: Test with pytest
-      env:
-        PYTHONPATH: ${{ github.workspace }}/src
-      run: uv run pytest
+      run: uv run pytest tests
diff --git a/CITATION.cff b/CITATION.cff
index bef805a..6e0071e 100755
--- a/CITATION.cff
+++ b/CITATION.cff
@@ -2,7 +2,7 @@
 # Visit https://bit.ly/cffinit to generate yours today!
 
 cff-version: 1.2.0
-title: eso4clima-wp1-prototype
+title: ClimaNet
 message: >-
   If you use this software, please cite it using the
   metadata from this file.
diff --git a/README.md b/README.md
index c3cf5b8..bf6da0c 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
-# eso4clima-wp1-prototype
+# ClimaNet: A Climate Aware Spatio Temporal Encoder Decoder
 
-[![License](https://img.shields.io/github/license/ESMValGroup/eso4clima-wp1-prototype)](https://opensource.org/licenses/Apache-2.0)
+[![License](https://img.shields.io/github/license/ESMValGroup/ClimaNet)](https://opensource.org/licenses/Apache-2.0)
 
 ## Installation
 
diff --git a/climanet/__init__.py b/climanet/__init__.py
new file mode 100644
index 0000000..02a9ffb
--- /dev/null
+++ b/climanet/__init__.py
@@ -0,0 +1,9 @@
+from climanet import st_encoder_decoder
+from climanet.dataset import STDataset
+from climanet.utils import regrid_to_boundary_centered_grid
+
+__all__ = [
+    "STDataset",
+    "st_encoder_decoder",
+    "regrid_to_boundary_centered_grid"
+]
diff --git a/src/dataset.py b/climanet/dataset.py
similarity index 100%
rename from src/dataset.py
rename to climanet/dataset.py
diff --git a/src/st_encoder_decoder.py b/climanet/st_encoder_decoder.py
similarity index 100%
rename from src/st_encoder_decoder.py
rename to climanet/st_encoder_decoder.py
diff --git a/src/utils.py b/climanet/utils.py
similarity index 100%
rename from src/utils.py
rename to climanet/utils.py
diff --git a/mkdocs.yml b/mkdocs.yml
index 79f6fc2..e4737cc 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -1,6 +1,6 @@
-site_name: "eso4clima-wp1-prototype"
-repo_url: https://github.com/ESMValGroup/eso4clima-wp1-prototype/
-repo_name: eso4clima-wp1-prototype
+site_name: "ClimaNet"
+repo_url: https://github.com/ESMValGroup/ClimaNet/
+repo_name: ClimaNet
 
 nav:
   - Introduction: index.md
diff --git a/notebooks/example.ipynb b/notebooks/example.ipynb
index 93f9507..bfdbb2c 100644
--- a/notebooks/example.ipynb
+++ b/notebooks/example.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 1,
    "id": "11ad68b2-7502-4dc4-8b78-d0a4fb53255d",
    "metadata": {},
    "outputs": [],
@@ -17,12 +17,12 @@
     "import torch\n",
     "import torch.nn.functional\n",
     "from torch.utils.data import DataLoader\n",
-    "from st_encoder_decoder import (\n",
+    "from climanet.st_encoder_decoder import (\n",
     "    SpatioTemporalModel,\n",
     "    pred_to_numpy,\n",
     ")\n",
     "\n",
-    "from dataset import STDataset"
+    "from climanet import STDataset"
    ]
   },
   {
@@ -35,7 +35,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "13a3b0c8-1d92-460d-84a4-a3a59ca081af",
    "metadata": {},
    "outputs": [],
@@ -64,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "id": "a9e054ab-995f-4483-a47b-84df84e6961e",
    "metadata": {},
    "outputs": [],
@@ -82,20 +82,1247 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "ac735a7d",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 795kB\n",
+       "Dimensions:    (time: 31, bnds: 2, lat: 80, lon: 80)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 248B 2020-01-01T11:30:00 ... 2020-01-31T...\n",
+       "  * lat        (lat) float32 320B -39.88 -39.62 -39.38 ... -20.62 -20.38 -20.12\n",
+       "  * lon        (lon) float32 320B -49.88 -49.62 -49.38 ... -30.62 -30.38 -30.12\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) datetime64[ns] 496B ...\n",
+       "    ts         (time, lat, lon) float32 794kB ...\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.4 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Fri Oct 31 09:28:31 2025: cdo daymean 202001_ERA5_masked_ts...\n",
+       "    frequency:    day\n",
+       "    CDO:          Climate Data Operators version 2.2.2 (https://mpimet.mpg.de...</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-ab97a31f-ebcd-4868-a28f-ada891158bd4' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-ab97a31f-ebcd-4868-a28f-ada891158bd4' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 31</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 80</li><li><span class='xr-has-index'>lon</span>: 80</li></ul></div></li><li class='xr-section-item'><input id='section-cd8f1836-3ddd-4a92-8530-7dcfb3ec2270' class='xr-section-summary-in' type='checkbox' checked /><label for='section-cd8f1836-3ddd-4a92-8530-7dcfb3ec2270' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>2020-01-01T11:30:00 ... 2020-01-...</div><input id='attrs-f00004e3-1559-42e3-936a-a52fa0f19570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f00004e3-1559-42e3-936a-a52fa0f19570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1f719888-056b-4a94-9fcc-cbf61c87bad6' class='xr-var-data-in' type='checkbox'><label for='data-1f719888-056b-4a94-9fcc-cbf61c87bad6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-01T11:30:00.000000000&#x27;, &#x27;2020-01-02T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-03T11:30:00.000000000&#x27;, &#x27;2020-01-04T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-05T11:30:00.000000000&#x27;, &#x27;2020-01-06T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-07T11:30:00.000000000&#x27;, &#x27;2020-01-08T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-09T11:30:00.000000000&#x27;, &#x27;2020-01-10T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-11T11:30:00.000000000&#x27;, &#x27;2020-01-12T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-13T11:30:00.000000000&#x27;, &#x27;2020-01-14T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-15T11:30:00.000000000&#x27;, &#x27;2020-01-16T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-17T11:30:00.000000000&#x27;, &#x27;2020-01-18T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-19T11:30:00.000000000&#x27;, &#x27;2020-01-20T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-21T11:30:00.000000000&#x27;, &#x27;2020-01-22T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-23T11:30:00.000000000&#x27;, &#x27;2020-01-24T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-25T11:30:00.000000000&#x27;, &#x27;2020-01-26T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-27T11:30:00.000000000&#x27;, &#x27;2020-01-28T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-29T11:30:00.000000000&#x27;, &#x27;2020-01-30T11:30:00.000000000&#x27;,\n",
+       "       &#x27;2020-01-31T11:30:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-39.88 -39.62 ... -20.38 -20.12</div><input id='attrs-f205c56f-3256-4797-8574-7f2c5d13af11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f205c56f-3256-4797-8574-7f2c5d13af11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56d401f4-0eee-4476-8a0c-81dad87a79dd' class='xr-var-data-in' type='checkbox'><label for='data-56d401f4-0eee-4476-8a0c-81dad87a79dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-39.875, -39.625, -39.375, -39.125, -38.875, -38.625, -38.375, -38.125,\n",
+       "       -37.875, -37.625, -37.375, -37.125, -36.875, -36.625, -36.375, -36.125,\n",
+       "       -35.875, -35.625, -35.375, -35.125, -34.875, -34.625, -34.375, -34.125,\n",
+       "       -33.875, -33.625, -33.375, -33.125, -32.875, -32.625, -32.375, -32.125,\n",
+       "       -31.875, -31.625, -31.375, -31.125, -30.875, -30.625, -30.375, -30.125,\n",
+       "       -29.875, -29.625, -29.375, -29.125, -28.875, -28.625, -28.375, -28.125,\n",
+       "       -27.875, -27.625, -27.375, -27.125, -26.875, -26.625, -26.375, -26.125,\n",
+       "       -25.875, -25.625, -25.375, -25.125, -24.875, -24.625, -24.375, -24.125,\n",
+       "       -23.875, -23.625, -23.375, -23.125, -22.875, -22.625, -22.375, -22.125,\n",
+       "       -21.875, -21.625, -21.375, -21.125, -20.875, -20.625, -20.375, -20.125],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.88 -49.62 ... -30.38 -30.12</div><input id='attrs-ce9d1dba-14c9-40c1-a50e-fdb366ce2949' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce9d1dba-14c9-40c1-a50e-fdb366ce2949' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-437b1065-0f67-4eab-ae06-a2aefcd76fd5' class='xr-var-data-in' type='checkbox'><label for='data-437b1065-0f67-4eab-ae06-a2aefcd76fd5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-49.875, -49.625, -49.375, -49.125, -48.875, -48.625, -48.375, -48.125,\n",
+       "       -47.875, -47.625, -47.375, -47.125, -46.875, -46.625, -46.375, -46.125,\n",
+       "       -45.875, -45.625, -45.375, -45.125, -44.875, -44.625, -44.375, -44.125,\n",
+       "       -43.875, -43.625, -43.375, -43.125, -42.875, -42.625, -42.375, -42.125,\n",
+       "       -41.875, -41.625, -41.375, -41.125, -40.875, -40.625, -40.375, -40.125,\n",
+       "       -39.875, -39.625, -39.375, -39.125, -38.875, -38.625, -38.375, -38.125,\n",
+       "       -37.875, -37.625, -37.375, -37.125, -36.875, -36.625, -36.375, -36.125,\n",
+       "       -35.875, -35.625, -35.375, -35.125, -34.875, -34.625, -34.375, -34.125,\n",
+       "       -33.875, -33.625, -33.375, -33.125, -32.875, -32.625, -32.375, -32.125,\n",
+       "       -31.875, -31.625, -31.375, -31.125, -30.875, -30.625, -30.375, -30.125],\n",
+       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4aa04044-fe0a-4c85-985e-707c911a6635' class='xr-section-summary-in' type='checkbox' checked /><label for='section-4aa04044-fe0a-4c85-985e-707c911a6635' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b8bbec60-6231-413d-80e0-c382d3869386' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b8bbec60-6231-413d-80e0-c382d3869386' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2ed7be4-660f-4340-a322-8d49b23e63ab' class='xr-var-data-in' type='checkbox'><label for='data-e2ed7be4-660f-4340-a322-8d49b23e63ab' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[62 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd175c37-50a2-4551-9174-b6be5d0c1860' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd175c37-50a2-4551-9174-b6be5d0c1860' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e43dc41-7dab-4f90-9cd4-d1124362048a' class='xr-var-data-in' type='checkbox'><label for='data-2e43dc41-7dab-4f90-9cd4-d1124362048a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>long_name :</span></dt><dd>Skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>GRIB_paramId :</span></dt><dd>235</dd><dt><span>GRIB_dataType :</span></dt><dd>an</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>skt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>359.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Skin temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>skt</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>GRIB_surface :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[198400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-61b627c7-f888-4f3d-ac61-95381d9d2265' class='xr-section-summary-in' type='checkbox' checked /><label for='section-61b627c7-f888-4f3d-ac61-95381d9d2265' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.2.4 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Fri Oct 31 09:28:31 2025: cdo daymean 202001_ERA5_masked_ts.nc 202001_day_ERA5_masked_ts.nc\n",
+       "Fri Oct 31 09:21:42 2025: cdo cat 20200101_ERA5_masked_ts.nc 20200102_ERA5_masked_ts.nc 20200103_ERA5_masked_ts.nc 20200104_ERA5_masked_ts.nc 20200105_ERA5_masked_ts.nc 20200106_ERA5_masked_ts.nc 20200107_ERA5_masked_ts.nc 20200108_ERA5_masked_ts.nc 20200109_ERA5_masked_ts.nc 20200110_ERA5_masked_ts.nc 20200111_ERA5_masked_ts.nc 20200112_ERA5_masked_ts.nc 20200113_ERA5_masked_ts.nc 20200114_ERA5_masked_ts.nc 20200115_ERA5_masked_ts.nc 20200116_ERA5_masked_ts.nc 20200117_ERA5_masked_ts.nc 20200118_ERA5_masked_ts.nc 20200119_ERA5_masked_ts.nc 20200120_ERA5_masked_ts.nc 20200121_ERA5_masked_ts.nc 20200122_ERA5_masked_ts.nc 20200123_ERA5_masked_ts.nc 20200124_ERA5_masked_ts.nc 20200125_ERA5_masked_ts.nc 20200126_ERA5_masked_ts.nc 20200127_ERA5_masked_ts.nc 20200128_ERA5_masked_ts.nc 20200129_ERA5_masked_ts.nc 20200130_ERA5_masked_ts.nc 20200131_ERA5_masked_ts.nc 202001_ERA5_masked_ts.nc</dd><dt><span>frequency :</span></dt><dd>day</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.2.2 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 795kB\n",
+       "Dimensions:    (time: 31, bnds: 2, lat: 80, lon: 80)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 248B 2020-01-01T11:30:00 ... 2020-01-31T...\n",
+       "  * lat        (lat) float32 320B -39.88 -39.62 -39.38 ... -20.62 -20.38 -20.12\n",
+       "  * lon        (lon) float32 320B -49.88 -49.62 -49.38 ... -30.62 -30.38 -30.12\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) datetime64[ns] 496B ...\n",
+       "    ts         (time, lat, lon) float32 794kB ...\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.4 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Fri Oct 31 09:28:31 2025: cdo daymean 202001_ERA5_masked_ts...\n",
+       "    frequency:    day\n",
+       "    CDO:          Climate Data Operators version 2.2.2 (https://mpimet.mpg.de..."
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "daily_subset"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "id": "da7ffd93",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
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+       ".xr-section-item > input:enabled + label,\n",
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+       "\n",
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+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label::before {\n",
+       "  content: \"📁\";\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked + label {\n",
+       "  padding-bottom: 0px;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input:checked ~ .xr-sections {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-contents > input + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-group-box-ellipsis {\n",
+       "  font-size: 1.4em;\n",
+       "  font-weight: 900;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  letter-spacing: 0.15em;\n",
+       "  cursor: default;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: \"(\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: \")\";\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: \",\";\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  border-color: var(--xr-background-color-row-odd);\n",
+       "  margin-bottom: 0;\n",
+       "  padding-top: 2px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "  border-color: var(--xr-background-color-row-even);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  border-top: 2px dotted var(--xr-background-color);\n",
+       "  padding-bottom: 20px !important;\n",
+       "  padding-top: 10px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in + label,\n",
+       ".xr-var-data-in + label,\n",
+       ".xr-index-data-in + label {\n",
+       "  padding: 0 1px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > pre,\n",
+       ".xr-index-data > pre,\n",
+       ".xr-var-data > table > tbody > tr {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
+       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
+       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
+       "  color: var(--xr-font-color0);\n",
+       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
+       "  stroke-width: 0.8px;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 26kB\n",
+       "Dimensions:    (time: 1, bnds: 2, lat: 80, lon: 80)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 8B 2020-01-16T11:30:00\n",
+       "  * lat        (lat) float32 320B -39.88 -39.62 -39.38 ... -20.62 -20.38 -20.12\n",
+       "  * lon        (lon) float32 320B -49.88 -49.62 -49.38 ... -30.62 -30.38 -30.12\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) datetime64[ns] 16B ...\n",
+       "    ts         (time, lat, lon) float32 26kB ...\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.4 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Fri Oct 31 09:31:04 2025: cdo timmean 202001_ERA5_full_ts.n...\n",
+       "    CDO:          Climate Data Operators version 2.2.2 (https://mpimet.mpg.de...</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-05396108-dbb6-41a3-bf71-544072a9d098' class='xr-section-summary-in' type='checkbox' disabled /><label for='section-05396108-dbb6-41a3-bf71-544072a9d098' class='xr-section-summary'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 80</li><li><span class='xr-has-index'>lon</span>: 80</li></ul></div></li><li class='xr-section-item'><input id='section-ad6bf22c-f6ce-46b3-bff8-8bcc3107b11f' class='xr-section-summary-in' type='checkbox' checked /><label for='section-ad6bf22c-f6ce-46b3-bff8-8bcc3107b11f' class='xr-section-summary' title='Expand/collapse section'>Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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'>2020-01-16T11:30:00</div><input id='attrs-6f003e62-ed00-4249-88c3-91618831922e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f003e62-ed00-4249-88c3-91618831922e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bc2278c-c41e-42ea-b20a-f5e5c96c474e' class='xr-var-data-in' type='checkbox'><label for='data-9bc2278c-c41e-42ea-b20a-f5e5c96c474e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-01-16T11:30:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-39.88 -39.62 ... -20.38 -20.12</div><input id='attrs-f9ae76c0-1ace-474d-839c-3c90cf59ab22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9ae76c0-1ace-474d-839c-3c90cf59ab22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2035f65d-462f-4be2-a274-cf631ad821f1' class='xr-var-data-in' type='checkbox'><label for='data-2035f65d-462f-4be2-a274-cf631ad821f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([-39.875, -39.625, -39.375, -39.125, -38.875, -38.625, -38.375, -38.125,\n",
+       "       -37.875, -37.625, -37.375, -37.125, -36.875, -36.625, -36.375, -36.125,\n",
+       "       -35.875, -35.625, -35.375, -35.125, -34.875, -34.625, -34.375, -34.125,\n",
+       "       -33.875, -33.625, -33.375, -33.125, -32.875, -32.625, -32.375, -32.125,\n",
+       "       -31.875, -31.625, -31.375, -31.125, -30.875, -30.625, -30.375, -30.125,\n",
+       "       -29.875, -29.625, -29.375, -29.125, -28.875, -28.625, -28.375, -28.125,\n",
+       "       -27.875, -27.625, -27.375, -27.125, -26.875, -26.625, -26.375, -26.125,\n",
+       "       -25.875, -25.625, -25.375, -25.125, -24.875, -24.625, -24.375, -24.125,\n",
+       "       -23.875, -23.625, -23.375, -23.125, -22.875, -22.625, -22.375, -22.125,\n",
+       "       -21.875, -21.625, -21.375, -21.125, -20.875, -20.625, -20.375, -20.125],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.88 -49.62 ... -30.38 -30.12</div><input id='attrs-f86cf890-b27e-460d-862d-91a5a9886dca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f86cf890-b27e-460d-862d-91a5a9886dca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fc47518-6773-4812-b999-a3f87d81f3b5' class='xr-var-data-in' type='checkbox'><label for='data-7fc47518-6773-4812-b999-a3f87d81f3b5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-49.875, -49.625, -49.375, -49.125, -48.875, -48.625, -48.375, -48.125,\n",
+       "       -47.875, -47.625, -47.375, -47.125, -46.875, -46.625, -46.375, -46.125,\n",
+       "       -45.875, -45.625, -45.375, -45.125, -44.875, -44.625, -44.375, -44.125,\n",
+       "       -43.875, -43.625, -43.375, -43.125, -42.875, -42.625, -42.375, -42.125,\n",
+       "       -41.875, -41.625, -41.375, -41.125, -40.875, -40.625, -40.375, -40.125,\n",
+       "       -39.875, -39.625, -39.375, -39.125, -38.875, -38.625, -38.375, -38.125,\n",
+       "       -37.875, -37.625, -37.375, -37.125, -36.875, -36.625, -36.375, -36.125,\n",
+       "       -35.875, -35.625, -35.375, -35.125, -34.875, -34.625, -34.375, -34.125,\n",
+       "       -33.875, -33.625, -33.375, -33.125, -32.875, -32.625, -32.375, -32.125,\n",
+       "       -31.875, -31.625, -31.375, -31.125, -30.875, -30.625, -30.375, -30.125],\n",
+       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cfc43990-d00d-471d-b2b4-3e49e3cc69f4' class='xr-section-summary-in' type='checkbox' checked /><label for='section-cfc43990-d00d-471d-b2b4-3e49e3cc69f4' class='xr-section-summary' title='Expand/collapse section'>Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ba6bb637-2fd2-4028-adff-6551135fd23b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba6bb637-2fd2-4028-adff-6551135fd23b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e90525a3-f248-4642-9fe0-4e9a8ed8f4fa' class='xr-var-data-in' type='checkbox'><label for='data-e90525a3-f248-4642-9fe0-4e9a8ed8f4fa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>[2 values with dtype=datetime64[ns]]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ts</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-76cb7844-e2ea-42d6-8f8f-5d3f21e01534' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-76cb7844-e2ea-42d6-8f8f-5d3f21e01534' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c25a9f6e-b378-4d46-a715-59f3762d9ad8' class='xr-var-data-in' type='checkbox'><label for='data-c25a9f6e-b378-4d46-a715-59f3762d9ad8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>unknown</dd><dt><span>long_name :</span></dt><dd>Skin temperature</dd><dt><span>units :</span></dt><dd>K</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>GRIB_paramId :</span></dt><dd>235</dd><dt><span>GRIB_dataType :</span></dt><dd>an</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>1038240</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>surface</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>regular_ll</dd><dt><span>GRIB_uvRelativeToGrid :</span></dt><dd>0</dd><dt><span>GRIB_NV :</span></dt><dd>0</dd><dt><span>GRIB_Nx :</span></dt><dd>1440</dd><dt><span>GRIB_Ny :</span></dt><dd>721</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>skt</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Latitude/Longitude Grid</dd><dt><span>GRIB_iDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jDirectionIncrementInDegrees :</span></dt><dd>0.25</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>0</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>90.0</dd><dt><span>GRIB_latitudeOfLastGridPointInDegrees :</span></dt><dd>-90.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfLastGridPointInDegrees :</span></dt><dd>359.75</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Skin temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>skt</dd><dt><span>GRIB_totalNumber :</span></dt><dd>0</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>GRIB_surface :</span></dt><dd>0.0</dd></dl></div><div class='xr-var-data'><pre>[6400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-673fbf81-b42b-4107-a5b7-b69672f998e7' class='xr-section-summary-in' type='checkbox' checked /><label for='section-673fbf81-b42b-4107-a5b7-b69672f998e7' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.2.4 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Fri Oct 31 09:31:04 2025: cdo timmean 202001_ERA5_full_ts.nc 202001_mon_ERA5_full_ts.nc\n",
+       "Fri Oct 31 09:06:53 2025: cdo cat 20200101_ERA5_full_ts.nc 20200102_ERA5_full_ts.nc 20200103_ERA5_full_ts.nc 20200104_ERA5_full_ts.nc 20200105_ERA5_full_ts.nc 20200106_ERA5_full_ts.nc 20200107_ERA5_full_ts.nc 20200108_ERA5_full_ts.nc 20200109_ERA5_full_ts.nc 20200110_ERA5_full_ts.nc 20200111_ERA5_full_ts.nc 20200112_ERA5_full_ts.nc 20200113_ERA5_full_ts.nc 20200114_ERA5_full_ts.nc 20200115_ERA5_full_ts.nc 20200116_ERA5_full_ts.nc 20200117_ERA5_full_ts.nc 20200118_ERA5_full_ts.nc 20200119_ERA5_full_ts.nc 20200120_ERA5_full_ts.nc 20200121_ERA5_full_ts.nc 20200122_ERA5_full_ts.nc 20200123_ERA5_full_ts.nc 20200124_ERA5_full_ts.nc 20200125_ERA5_full_ts.nc 20200126_ERA5_full_ts.nc 20200127_ERA5_full_ts.nc 20200128_ERA5_full_ts.nc 20200129_ERA5_full_ts.nc 20200130_ERA5_full_ts.nc 20200131_ERA5_full_ts.nc 202001_ERA5_full_ts.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.2.2 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset> Size: 26kB\n",
+       "Dimensions:    (time: 1, bnds: 2, lat: 80, lon: 80)\n",
+       "Coordinates:\n",
+       "  * time       (time) datetime64[ns] 8B 2020-01-16T11:30:00\n",
+       "  * lat        (lat) float32 320B -39.88 -39.62 -39.38 ... -20.62 -20.38 -20.12\n",
+       "  * lon        (lon) float32 320B -49.88 -49.62 -49.38 ... -30.62 -30.38 -30.12\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) datetime64[ns] 16B ...\n",
+       "    ts         (time, lat, lon) float32 26kB ...\n",
+       "Attributes:\n",
+       "    CDI:          Climate Data Interface version 2.2.4 (https://mpimet.mpg.de...\n",
+       "    Conventions:  CF-1.6\n",
+       "    history:      Fri Oct 31 09:31:04 2025: cdo timmean 202001_ERA5_full_ts.n...\n",
+       "    CDO:          Climate Data Operators version 2.2.2 (https://mpimet.mpg.de..."
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "monthly_subset"
    ]
@@ -110,7 +1337,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "id": "7ab48e70-d84a-4907-8fa6-1a7cd6658c3e",
    "metadata": {},
    "outputs": [],
@@ -129,7 +1356,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "id": "31646135",
    "metadata": {},
    "outputs": [],
@@ -153,7 +1380,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "id": "d366da78-bb5d-4bcc-8ca9-59866a410dd8",
    "metadata": {},
    "outputs": [],
@@ -168,10 +1395,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "d2496468-7d5a-4f1a-9bf1-13e8fd4bad1f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The loss is 30.19863510131836 at epoch 0\n",
+      "The loss is 6.372329235076904 at epoch 20\n",
+      "No improvement for 10 epochs, stopping early at epoch 29.\n",
+      "training done!\n",
+      "10.819591522216797\n"
+     ]
+    }
+   ],
    "source": [
     "best_loss = float(\"inf\")\n",
     "patience = 10  # stop if no improvement for <patience> epochs\n",
@@ -231,10 +1470,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "bda9f068",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([1, 1, 31, 80, 80]) torch.Size([1, 1, 31, 80, 80]) torch.Size([1, 80, 80]) torch.Size([80, 80])\n"
+     ]
+    }
+   ],
    "source": [
     "dataset_pred = STDataset(\n",
     "    daily_da=daily_subset[\"ts\"],\n",
@@ -258,7 +1505,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "15d5fbee",
    "metadata": {},
    "outputs": [],
@@ -272,7 +1519,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "e88ecbc0",
    "metadata": {},
    "outputs": [],
@@ -285,20 +1532,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "e581aa17-3916-47be-a1b6-447015f3f3da",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x76a2cb50b230>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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vv33U6zC+/vprvPXWWwCAbdu2oaioKHTtM888EwMHDoy6nBs2bECvXr0wZcqU0JEoP/74I3r37o1rrrkG7dq1g8ViwRdffIF//etfaNWqFUaOHBm6TjTtv2zZMtx0001iWXPOnDkYNGgQ+vTpg7/+9a/YvHkznnzySdx8881hlgRXXXUVunbtiptuugnfffcd0tPT8fTTTyMQCOC+++6rUZsqSr3kuFhhKsr/MX36dPOkk04yLRZLmJt3y5YtzSFDhoTiLVy40ARgfv7552Hpp0yZYgIw9+3bFxY+ZMgQMyEhQVzv2WefNTt37mzGxcWZSUlJZqdOncy77rrL3L17d8zrdiQuuugiE8ARX1XZvHmz2adPHzM+Pt5MTU01r7/+ejM3NzcszpAhQ6rNs6pL+s6dO82rrrrKTE5ONhMTE80BAwaYP/74Y8R1CAQC5owZM8yWLVuaDofD7Nixo/mvf/1LxFu9evURy3TRRRfVur2qOm/n5eWZQ4YMMRs1amQ6nU6zS5cu5rvvvnvEvI/m4H2o37FX5f4ZTTkPtUllh+99+/aZt956q9muXTszISHBdDgc5imnnGLeeeedom+bZuTtf6j8CxcuFO8tW7bMPOuss0yn02k2a9bMvOeee+gRQ/n5+eawYcPMxo0bm/Hx8eZFF10knkNFaegYplkDUxhFURRFUZTfCapZUhRFURRFqQYdLCmKoiiKolSDDpYURVEURVGqoV4Mlnbs2IFhw4ahdevWiIuLw8knn4wpU6bA6/WGxfv666/xhz/8AS6XC82bN8eDDz541Lx//fVX9O/fH/Hx8cjMzMS4cePg9/vrqiqKoiiKotQz6oV1wJYtWxAMBvHMM8+gbdu22Lx5M2655Ra43W489NBDAIDi4mL06dMHvXv3xrx58/DNN9/gb3/7G1JTU8NM1ioTCATQv39/ZGdn49NPP8WePXswePBg2O12zJgx41hWUVEURVGUE5R6uxtuzpw5mDt3Ln766ScABw3VJk2ahNzc3JB774QJE/Cf//wHW7ZsoXn897//xYABA7B7925kZWUBAObNm4fx48dj3759YS7AiqIoiqL8PqkXM0uMoqIiNGrUKPT/unXrcOGFF4YNcPr27YvZs2ejoKAAaWlpIo9169ahU6dOoYHSoTTDhw/Ht99+i7PPPpte2+PxhB0uGQwGkZ+fj8aNGx/TIzwURVGU+oVpmigpKUHTpk3DjpCJNRUVFUKqUlMcDgdcLldM8qqv1MvB0rZt2/DEE0+EluCAg6eWt27dOizeoUFQbm4uHSzl5uaGDZSqpjkSM2fOVPdaRVEUpcbs3LkTzZo1q5O8Kyoq0LplInL3Bo4eOQKys7Px888//64HTMd1sDRhwgTMnj272jjff/892rVrF/p/165d6NevH66++mrccsstdV1EysSJEzF69OjQ/0VFRWjRogV27tyJ5OTk41ImRTkReeaHASLMY9pFWJ43RYT5gvJX92/l8kdPil2eqea0yE0ajUi8NbmniLD92xqLMKZVMF1BGRiIcGbZVeVLzCKv4EiQswKmKfMPeK0iLOghH+0e2Z6mjdTMIGVJ8YiwrJQSEfbbnkYizCB1sznJJhrSdAYpS2KcbBcruUMZCaUiLEDaz+2Tcgu3V555V1Yh+63DLgcjFlJfS6V6BMo8+HbIE6EDq+sCr9eL3L0B/PxlSyQn1W72qrgkiNadf4HX69XB0vFizJgxYecVMdq0aRP6e/fu3ejVqxe6d++OZ599NixednY28vLywsIO/Z+dnU3zzs7OxoYNG6JKAwBOp5MeIJmcnKyDJUWpRFyi/IgxTBnm9MovIgsZLNkt8ovN4ZBfvA6yvOG0+0SYLUE+xxbyhUC+Y+t8sGSNJ4MbUhDTJgdLsJCPdtImkQ6WrPHyujYymLPEybYzrCS/WgyWrHEyopXEs5PyGaZsAxsZLFltsl9YSd+z2mU9jjZYCpXlGEg2kpMstR4sKQc5roOljIwMZGRkRBR3165d6NWrFzp37oyFCxeKtd5u3bph0qRJ8Pl8sNsPfvCuXLkSp512Gl2CO5TmgQcewN69e5GZmRlKk5ycjA4dOtSiZoqiKIpyfAmYQQRquYUrYJIfBb9D6sWQc9euXejZsydatGiBhx56CPv27UNubm6Yrui6666Dw+HAsGHD8O233+K1117DY489FrZctmzZsrAlvT59+qBDhw648cYb8b///Q/vvfce7rnnHuTk5NCZI0VRFEWpLwRhxuSl1BOB98qVK7Ft2zZs27ZNCOIOOR+kpKRgxYoVyMnJQefOnZGeno577703zGOpqKgIW7duDf1vtVqxfPlyDB8+HN26dUNCQgKGDBmCadOmHZuKKUoDZ7P7JBFWHpDLGYXeOBHWyOkWYRUB+ZHlD8plqNxyuRzevHGBCCtwy+tayuVvSH8y0aaQeIZPLq0EHfLLxkSVMsfL/L3lcmnS9JNrlpCPcWdkS4RsIcjwyWu4MuUSZl4R0dyUy7JYUuRymLeM2LKQ8llccpmrOCDLl5RQIcvnluXzBmRfKSmVS4dOp6xvMCjL5/PL/DxE22S1Hb4fQSmdU+oB9WKwNHTo0KNqmwDgjDPOwMcffxxVPi1btsQ777xTyxIqiqIoyolFEEHUdhGt9jk0DOrFYElRFEVRlOgImCYCtfSdrm36hkK90CwpiqIoiqIcL3RmSVGUmDB18+UizGJI3Ugzl9QOpRIPpN3lqSLMYZHanp2lMl6SQ/oC7fXKsqQnSV3UrsQEEQaiV2EEnRH+Cq+iKTIscqkjWCH1MIZd5h8keidLGbETIFjc8vdywCWvUUp0PZmNpM/S3gr5lcI2U7H6WojOyiTtnhAv763TJrVNpRVyk46L2EekJJXLtOXEUoJYAlQQ7ZUrXmq0ApV1VsRGoK6IhUBbBd4H0cGSoiiKojRAgjAR0MFSTNBlOEVRFEVRlGrQmSVFURRFaYDoMlzs0MGSoiiKojRAdDdc7NDBkqIoUTPw4xEiLNmRGVHaX0rlYavtU/JEmMMqRbv5HmkiWeyR4uMEuxTZJtukcWGph5w1VyDVCd5GUkRtKyYCbPK94kskppQVlmr/BwCLn5hIEsEzE3izyQCLR6a1l0QmXGeiZXbQcbBACqMdWVK8790r7yM9Vi9R9oGyCnnPWFiAGHi6S8mZnilS4M3OcvOUEZPQEhnmtVXvSxQkppp1RfD/XrXNQ1HNkqIoiqIoMWLu3Lk444wzQgfLd+vWDf/9739D71dUVCAnJweNGzdGYmIirrzyytAB9oe444470LlzZzidTpx11lnHuAYcHSwpiqIoSgMk8H+74Wr7ioZmzZph1qxZ+PLLL/HFF1/g4osvxuWXX45vv/0WADBq1Ci8/fbbWLJkCT788EPs3r0bf/7zn0U+f/vb33DNNdfEpB1igS7DKYqiKEoDJGAefNU2j2gYOHBg2P8PPPAA5s6di/Xr16NZs2Z4/vnn8fLLL+Piiy8GACxcuBDt27fH+vXr0bVrVwDA448/DgDYt28fvv7669pVIEboYElRlGo59Y3pIuykNKkRCZpSdJLqlHqQJvHFImzD/hYirNQj9SUG0ZKw6/64L0OE7StLFGEMZsoIcg2rlPHAL6U4cBTJtB5bZFohUQxijGgrlNopaznJnwSZ5BuAlde9W7ads2WhzC9O6qfYAbRWotEKxBOjygKpCQo4iEaLYLWS/IipZ+EBYkJKDEFB0iJBliVAdFuVTUiD5ZGV/0SjuDj8uXU6nXA6SV0rEQgEsGTJErjdbnTr1g1ffvklfD4fevfuHYrTrl07tGjRAuvWrQsNlk5EdBlOURRFURogwRi9AKB58+ZISUkJvWbOnHnE637zzTdITEyE0+nE3//+dyxbtgwdOnRAbm4uHA4HUlNTw+JnZWUhNzc3ZvWuC3RmSVEURVEaIEEYCLApxSjzAICdO3ciOTk5FF7drNJpp52GTZs2oaioCK+//jqGDBmCDz/8sFblON7oYElRFEVRlGo5tLstEhwOB9q2bQsA6Ny5Mz7//HM89thjuOaaa+D1elFYWBg2u5SXl4fs7Oy6KHbM0GU4RVEURWmABM3YvGpdjmAQHo8HnTt3ht1uxwcffBB6b+vWrfj111/RrVu32l+oDtGZJUVRqod8WHoD8qMj2SFPg9+Ue1JEl2AmgA47OUmenAbfJEUKxgPE+O+M9N0i7LPdLUWY3R2hGaTUHsMm/RcRIKsV1orw/IJOWX9XLjF9lLp6LtwmP4Ntbhnmkf6gMIgLoTVNqtmZsN5aLPsF8daE4ZD1tXhJG5N2gVeKrx3xPhHm2x0vwkxnZBaLpk1el9UNGdLoNAhiVmo/LOo2/MdO4B2IwTJctOknTpyIyy67DC1atEBJSQlefvllrFmzBu+99x5SUlIwbNgwjB49Go0aNUJycjJGjBiBbt26hYm7t23bhtLSUuTm5qK8vBybNm0CAHTo0AEOB3sI6h4dLCmKoiiKEhP27t2LwYMHY8+ePUhJScEZZ5yB9957D5deeikA4JFHHoHFYsGVV14Jj8eDvn374umnnw7L4+abbw7TOJ199tkAgJ9//hmtWrU6ZnWpjA6WFEVRFKUBcjxmlp5//vlq33e5XHjqqafw1FNPHTHOmjVrorrmsUAHS4qiKIrSAAmaBl0ujTYPRQdLiqIoitIgOR4zSw0VHSwpihKi9WJpNOeMk2LXfUXS0bnUI4WXTiLSLnG7RNhJjQpFWF5xkgjze+VH1s59UqVsd8jrJtmkGLekUIqA46VOHewgeYvUFMMg2t2ArC5sVUTkgYD8QvLLolEBuaexvD/20si+4JwFMiwY4bdCcbG0K2f1N9xE8OxjInqZ1iSu3kaJLKCXzH6Y8bIw1lKZ1tJENqo/X940VjdzL4lnJS7zlUTpQSJQV058dLCkKIqiKA2QACwI1NIhqH4ezhJ7dLCkKIqiKA0QMwaaJVM1SwDUlFJRFEVRFKVadGZJUZQQP18/UYS1WvigCDPIye/sF6if6DOC5ET3X31Sd5SQKMVDzbL3ibB4mxQP7SmVxzL8VJouwqz7pbOkvVQEwUr0SX6mRZKyKFikfApmlSawSM9HWIl2ykriGUTvFJByImpAyWC6KDNPVta0ECPR4sgMPf0JkV3XIOanQWJoaZLrWj0krJyUxSTisATZv4NZ8oaYpG4guihUjsfS1BEq8I4dOlhSFEVRlAZIwLQgwOzco8ojRoWp5+gynKIoiqIoSjXozJKiKIqiNECCMBCs5ZxIkB0O+TtEB0uKoiiK0gBRzVLs0MGSoighWj/5TxloEFPBQvnR4UuX6uM4ItIOuOQv3YCPCMGJYLzEI4XGRRVEzUzwBuU1AgnS9NASIGUhn5TOQvKLm3yvmIYMdBWEX9edLduEmVKycliYEQ4RhzPpis0tw5iY3Sf9QRFMkm0XtMuLmKTMjiJSPtJ2TOQelycjlmcR4XYiEWk7ZDwLMci0lMt6BElFrKWRGW4GnYf7ikE2OCgnPjpYUhRFUZQGSGwE3roMB+hgSVEURVEaJAc1S7U8SFeX4QDoYElRFEVRGiTBGBx3ogLvg6h1gKIoiqIoSjXUi5mlHTt2YPr06Vi1ahVyc3PRtGlT3HDDDZg0aRIcjoMnna9ZswaPPPIINmzYgOLiYpxyyikYN24crr/++mrzNoj48pVXXsFf//rXOqmLohwPWj8hhdtWImI17OT0dpcU8jLRrmHIX6CeCumQ7XBKS+uTMg+IMB8RZKc4pEV2Mglj7CgmFtbkpHurR9aDnThvI/GYSJlJRkxreEQmZDZI2UiTwJsqwxhVXcMBLtz2k+vaS4hLOElrK2cXlkHMsZyJ11naoEOGsftjL5IVNm0yQ1+aTMxc0WGXaQNpxJ7dL9M6cw9XLlBxDB28VbMUM+rFYGnLli0IBoN45pln0LZtW2zevBm33HIL3G43HnroIQDAp59+ijPOOAPjx49HVlYWli9fjsGDByMlJQUDBgyoNv+FCxeiX79+of9TU1PrsjqKoiiKUucEYVGfpRhRLwZL/fr1CxvMtGnTBlu3bsXcuXNDg6W77747LM3IkSOxYsUKLF269KiDpdTUVGRnZ8e+4IqiKIqi1HvqrWapqKgIjRpVfzJkJHEAICcnB+np6Tj//POxYMECmEeZdvR4PCguLg57KYqiKMqJRMA0YvJS6snMUlW2bduGJ554IjSrxPj3v/+Nzz//HM8880y1eU2bNg0XX3wx4uPjsWLFCtx+++0oLS3FHXfcccQ0M2fOxH333Vfj8itKXXLKrEdEmIVokdjsOjup3SCah0A8EbaUSH2StbHUE9ltUiPy24E0mdYqr+GNlx9Zu0pSRFj7xnkiLNEhhUFM12IvI0aVxKjRCMoGtPiJjslydJNLZxGpayL5LeuUQXF7ZRjTJzG9E/sa9CWQtPLWwlosM2SaJaa9YjDdFtPGsbI4CmWYP1GGBSzEIHSPvAiT+QTtpAHJM8SMTsPiHcNVrUAMdsMFdBkOwHGeWZowYQIMw6j2tWXLlrA0u3btQr9+/XD11VfjlltuofmuXr0aN910E5577jl07Nix2jJMnjwZPXr0wNlnn43x48fjrrvuwpw5c6pNM3HiRBQVFYVeO3fujK7iiqIoiqLUG47rzNKYMWMwdOjQauO0adMm9Pfu3bvRq1cvdO/eHc8++yyN/+GHH2LgwIF45JFHMHjw4KjL1KVLF0yfPh0ejwdOJ/kZB8DpdB7xPUVRFEU5EQiaFgRruRsuqLvhABznwVJGRgYyMjIiirtr1y706tULnTt3xsKFC2GxyA6wZs0aDBgwALNnz8att95aozJt2rQJaWlpOhhSFEVR6jW6DBc76oVmadeuXejZsydatmyJhx56CPv27Qu9d2gX2+rVqzFgwACMHDkSV155JXJzcwEADocjJPJetmwZJk6cGFrae/vtt5GXl4euXbvC5XJh5cqVmDFjBsaOHXuMa6goiqIoyolKvRgsrVy5Etu2bcO2bdvQrFmzsPcO7VxbtGgRysrKMHPmTMycOTP0/kUXXYQ1a9YAOLg7buvWraH37HY7nnrqKYwaNQqmaaJt27Z4+OGHj6iFUpT6ABMjM7dEJkS1ljFlK8mPhTENeVDmV1IQLyOWyo+iYLoUh+87QJwQCd+ZWSLMXSZni50FMq3dLSsXIAJ5v0uG2d3yV7it4ui/zI0AiyPLYdsv4zkKpTFiaTPp3Gj1ybR+JzFQJG1SkSbjWb0yjJpNEhNJv0uGMXG4lfiNMvE66/Mmyc+1X4Y5C2W7uJuSupFrMNG8WST7vKXSLbIQIXtdEQRqvZstQn1+g6deWAcMHToUpmnS1yFeeOEF+v6hgVLlfA7Rr18/bNy4ESUlJSgtLcWmTZtw22230SU+RVEURalPHDKlrO1LqSczS4qiKIqiREdsjjvRwRJQT2aWFEVRFEVRjhc6s6QoMaLdVGkGyQz0Ak5iXOioEhYkOoNMKeAIlsoLOMljHSTXtBNtRcBFykZ0GUyfZCRJUYeflM9wkFNPLeSQ0kKyI9Ul01qdMqy0NE6E2R1S22N3k6J4mGZJNoKzgNSD6basRI9UJcgfJxM6SmU5fPHk8GOytTsuX5atvBExkSSHAVu8MsybTA6ljfDwXyaZcRFdFDtIlx6uSwiQruIoiSweu4azUIZ5kmWYhZyjaxDdVuXDjgPseaojgjAQpNaj0eWh6GBJURRFURokugwXO7QVFEVRFEVRqkFnlhRFURSlARIbU0qdUwF0sKQoiqIoDZKgaSBYW5+lWqZvKOhgSVGOQvvJUrjNhJ0g5nv2UhnGRKZWd/ivN9NGDAR9UhlqKSfCW/LZ5iiQgUx8bvhJvKTIBNlmiczQQvKzkNPqg3YiNPYQI00i5g4UkoYnQnDDItXHjlJ53aBD/pK2lcu0RpAItw1SX//RTSmdhTJ/e6nsZM59Ml7QRYTbJK0tTtaLCcsN0reZISMTc7M+xZ4BphmmZqoE1r/tZSSMGISyexFwyAxtJeT5IyakTM5jkMfFXklsfixNKZXYoYMlRVEURWmABGOwDKemlAfRwZKiKIqiNECCpgXBWu5mq236hoK2gqIoiqIoSjXozJKiKIqiNEACMBCopalkbdM3FHSwpDQ4zvqHFGR7Gsl4duLw6z6JCJfTZTxrGbOwlkEBaSRNqSoYD1gi/IAi2mFHUYRJmTiVuAsz0betVEb0ZUvrYnYNv5e5UMt4THhrBoggmYSZxAE9QATyzL3ZXiIVzkzMHbTJepgkP5MczB23K1yRXHxqoohTlikzi98ry2ZaSV1J2zExd9w+mV/AJctrLyP1J33FGqEQPECE4MwpPmiXZU7cIzMsbi7LXNFYpnWSjQ4M6rxP9hEwp2/qJl7pmQwQh++64ngsw82dOxdz587Fjh07AAAdO3bEvffei8suuwwAUFFRgTFjxuDVV1+Fx+NB37598fTTTyMrKyuUx6+//orhw4dj9erVSExMxJAhQzBz5kzYbMdvyKLLcIqiKIrSAAng8OxSzV/R0axZM8yaNQtffvklvvjiC1x88cW4/PLL8e233wIARo0ahbfffhtLlizBhx9+iN27d+PPf/7z4TIHAujfvz+8Xi8+/fRTLFq0CC+88ALuvffe2DVMDdCZJUVRFEVRYsLAgQPD/n/ggQcwd+5crF+/Hs2aNcPzzz+Pl19+GRdffDEAYOHChWjfvj3Wr1+Prl27YsWKFfjuu+/w/vvvIysrC2eddRamT5+O8ePHY+rUqXA4yBTfMUBnlhRFURSlAXJoGa62LwAoLi4Oe3k8RzeMCgQCePXVV+F2u9GtWzd8+eWX8Pl86N27dyhOu3bt0KJFC6xbtw4AsG7dOnTq1ClsWa5v374oLi4OzU4dD3RmSWlwFJxFNCc+qVWoyCBaF5fUQ1jcxPiRmEYy/IkyP2u5/I3iyQovc3ITKahqFC+d97JOlY5/G744RRakkRRKnJQlj363EYFJhV8KOIrLpTAjK1GWb29hkgjz24i5pk1eNy1J5ldaIa+bkSzboGv6DhFWTkQnbwc7ybL45TXKif7FJ6tGsZLvFFuL8MTMyJBp4MqJKIoZpHpSZGI7MeAsOlne2/JMmR/T6/ibyoolfCfbriKdGEE2Yq6uhDLZV0qJPomJ3izemuv+vMkyzO6WYYXticYxg9zw/MMNGCQGp3VFLA/Sbd68eVj4lClTMHXqVJrmm2++Qbdu3VBRUYHExEQsW7YMHTp0wKZNm+BwOJCamhoWPysrC7m5uQCA3NzcsIHSofcPvXe80MGSoiiKoijVsnPnTiQnHx5FOp1Eyf5/nHbaadi0aROKiorw+uuvY8iQIfjwww+PRTHrDB0sKYqiKEoDxISBYC23/pv/lz45OTlssFQdDocDbdu2BQB07twZn3/+OR577DFcc8018Hq9KCwsDJtdysvLQ3Z2NgAgOzsbGzZsCMsvLy8v9N7xQjVLiqIoitIAObQMV9tXbQkGg/B4POjcuTPsdjs++OCD0Htbt27Fr7/+im7dugEAunXrhm+++QZ79+4NxVm5ciWSk5PRoUOHWpelpujMkqIoiqIoMWHixIm47LLL0KJFC5SUlODll1/GmjVr8N577yElJQXDhg3D6NGj0ahRIyQnJ2PEiBHo1q0bunbtCgDo06cPOnTogBtvvBEPPvggcnNzcc899yAnJ6fapb+6RgdLSp3R84OxIqx5YqEIe6nL/Ijya/XMQyLMSJQueLYkcjK7X/46ik+UQszGiVLFycTC+b4EEeYjLn3rfm0l41WQx66KYaLb7RJRTmm8X4R1T9smwsrOkqJdLylbu+Q8EZZI1Mg+4haY6SgWYZ1cO0XYpXFSyLs3wI6hlzyV30WE7fGkiDALUeimETVux/hdImxLc6lm/vH8k2Rh2EoG2QwAqwwzfbLvWePD2yUxsULEaZ2WL8IOVMSLMLtFqsP3/CSXK9gmB0uFLFswTtYhu/UBEZbklGX+ySEdXA0ivk5NkP0szi6fZY9fPitZiXLzQ3ac7I9dk38SYb95pTttPOnzS3acI8LKKqTK3UbMT+Pj5GaKli0P9z2f24tfRYy6IWgaCJq1W4aLNv3evXsxePBg7NmzBykpKTjjjDPw3nvv4dJLLwUAPPLII7BYLLjyyivDTCkPYbVasXz5cgwfPhzdunVDQkIChgwZgmnTptWqHrVFB0uKoiiK0gAJwIJALdU20aZ//vnnq33f5XLhqaeewlNPPXXEOC1btsQ777wT1XXrGtUsKYqiKIqiVIPOLCmKoihKA+R4LMM1VHSwpCiKoigNkCAsCNZyAam26RsKOlhSYkL7ZfeJMK83TYQlOaSY8uTXHhBhxi9SyApm8ZFPrIWJkBV2KTJ1l0ohdFmC3G2xa3+qCGOCcZPkBwuxB/YT5/Aq5Qvul+XY3Ug2wFpIt+6dxakirEmSFMB+eaC5CPMHpJg7zi4FqzaLFAFvS5Ji6TfItmNPUH7s5Hvk/XZYpXC50COF742c5SLsu8LTRVivrB9FWF6JtOG2EEF2MFWKj5lw2yiTfcAgbu/BKiJ/tyHr9W25FGmzfhcol+1pWCPrd8FE2caGh1yDCJnzy+U9C5DNC/Ep8v6UumX/LvIR8bpTbhAo98g2LkmS+W0vlmJzH+nfRWWy7a3kuWWe/U6HLF9Jqcxvq+fwsxEok8L4uiJgGgjUcmaotukbCjpkVBRFURRFqQadWVIURVGUBohqlmKHDpYURVEUpQFimhYEa+nAbcbAwbshoIMlJWpOfWO6CPMRwzYL0U3sLpW6m8QEuYZflCDX/Q2iuSB+dwgQs0CDaC7gJHoNolVgOgyqRSL5wSM1Emzx21oaHo8ZA5ZWSF1Gs8wCEbafGBeW+4ieipCVIA3/Sn3y3jZLKBRhyTZ5H5l5Z6q9TITFWaUuaqdbat4SiX5qT5nUHTV2yWuUBmT7ZSXJ+hYlJYowBEjfI2FmHOlTTNtkD49nEA1YwCf7DnumDAcxxywn/Y50WYtbxgsSfV9hqexTrTKkUWVJonxumQ7OJLMVccSokqVNiZf9zGmV2iG3V95vh03GY/kxHZONGI6WlclrOF2yjwaCh/sA0z4pJz46WFIURVGUBkgABgK1PEi3tukbCjpYUhRFUZQGSNCsveYoqFNhAHQ3nKIoiqIoSrXozJKiKIqiNECCMRB41zZ9Q6FeDJZ27NiB6dOnY9WqVcjNzUXTpk1xww03YNKkSXA4HKE4rVu3FmnXrVuHrl27HjHvX3/9FcOHD8fq1auRmJiIIUOGYObMmbDZ6kXTxJSu700UYUzo6PdKsXCwQgoxDXLiPDOl3F0gT5J3FMgH1JsmBZaOosgeZF8yMZkj4mtWDybuJQe9I5BAxL1Ee2shpn/24vBr+AwZJz2xVIT5g7K8ewple7bPyhNhm3c3EWH7rFLcnBgn75mLCGoLvVIE7CUC3TK/7D/tU2X5IhVz5xPxcZxNmkim22X7lRCTS1uBfPYDjWR9bcWk75myvgEi1g9aw68RJH2RbUoIkE0OIKJykLS035XIeD7ZxIgnfcATkO3kzZftmZDpjiie25AbCawJ8j4Wl0tRtdsj03r95F4QU8/0FFk+ZkrJxNyBEtmXPWTXiVEpjBmL1hVBGAjWUnNU2/QNhXoxItiyZQuCwSCeeeYZtG3bFps3b8Ytt9wCt9uNhx56KCzu+++/j44dO4b+b9y48RHzDQQC6N+/P7Kzs/Hpp59iz549GDx4MOx2O2bMmFFn9VEURVGUukYdvGNHvRgs9evXD/369Qv936ZNG2zduhVz584Vg6XGjRsjO1seE8BYsWIFvvvuO7z//vvIysrCWWedhenTp2P8+PGYOnVqaNZKURRFUZTfL/V2MbKoqAiNGjUS4YMGDUJmZiYuuOACvPXWW9XmsW7dOnTq1AlZWVmhsL59+6K4uBjffvvtEdN5PB4UFxeHvRRFURTlROKQZqm2L6WezCxVZdu2bXjiiSfCZpUSExPxz3/+Ez169IDFYsEbb7yBK664Av/5z38waNAgmk9ubm7YQAlA6P/c3NwjXn/mzJm47z55cGx94oy37xVhJcXSMJJpKZgegmlzzANyjX9HQB5u6YiTuoSgM7L9qhYpa4Ff+iDCUSjLXJEemcmlSfQL5CxY2IpkoLWMTGEzqUuVpI4Cme7nX+VBtaenyn6aFCdN9iqIvsRHzDbtLqnNKSiUDZrslNfwEv0U0x0lO2Tar/bJQ31LiAmn3Sb1OS5ymOmOfXL5fTkxKTTIDQ+4iL6NGTqSA5sDpN/aia7OW/VwXYP0E7b6QfqOpUDqZmzlJDHt2zLMUSTTFu2Wnw0pJ8v7yHSKrO2MCnIQdby8t8ECObsfIIfrBsjnj5UYfTpc8hp5+8nnHtNgssOJiRFtoED2M1S6brCcaMzqiCBicNyJapYAHOeZpQkTJsAwjGpfW7ZsCUuza9cu9OvXD1dffTVuueWWUHh6ejpGjx6NLl264LzzzsOsWbNwww03YM6cOTEv98SJE1FUVBR67dy5M+bXUBRFURTlxOC4ziyNGTMGQ4cOrTZOmzZtQn/v3r0bvXr1Qvfu3fHss88eNf8uXbpg5cqVR3w/OzsbGzZsCAvLy8sLvXcknE4nnE7y60FRFEVRThDMGOyGM3VmCcBxHixlZGQgIyMjori7du1Cr1690LlzZyxcuBAWy9EnxTZt2oQmTeT26EN069YNDzzwAPbu3YvMzINLHCtXrkRycjI6dOgQWSUURVEU5QQkaMZgGU53wwGoJ5qlXbt2oWfPnmjZsiUeeugh7Nu3L/TeoRmgRYsWweFw4OyzzwYALF26FAsWLMD8+fNDcZctW4aJEyeGlvb69OmDDh064MYbb8SDDz6I3Nxc3HPPPcjJydGZI0VRFEVRANSTwdLKlSuxbds2bNu2Dc2aNQt7z6ykHpw+fTp++eUX2Gw2tGvXDq+99hquuuqq0PtFRUXYunVr6H+r1Yrly5dj+PDh6NatGxISEjBkyBBMmzat7it1nCn+TYoawQSMTFBaTsSZiVK0aJJDhVIbSQO4UrccmNpKIzvlPUjcHWzywHn442SYtYIIdImBYNwedjK7zI/NVhOPQtjlQffwNApvK1bX1AxpqughSvMDhdJYkp2YzsTcfq8ssM0h7225TzZ8VoKs2Le5cjnbZiV9hZ1C75TC/8IiaUDZLLNAhJVVyPJ1arRHhH25r5kIs5fI/u0nAmKiZ4eNCPrZZoCqBpFBu3xWXPvIc0auyX74034nHz14U4mBItnA4WgkxdyBIClfkWz3cnlZmA5yXSKqNp2y4dnGBFe83EhQtls+ByDtzNrPsMnrWorldc3G8rosP0vlZ8h/DAXe6uAdM+rFYGno0KFH1TYNGTIEQ4YMiTqfli1b4p133qllCRVFURTlxEKX4WKHDhkVRVEURVGqoV7MLCmKoiiKEh16Nlzs0MGSoiiKojRAdBkuduhgqYHRcj4x4SQuxRZyIjdz0DXcxMmWiI+NEpIfWeRNcEhBZEGuPObcSZy52Q8cqzwMHWBu4sTV28pcjg1ZaB/TiUqtNTwZRERN3JsZVR3GqZCX6O+3l0inapPcn0K3VLizE9iZy7OFiMMPFMsGrfDLj5M4ciNLSmRZWmYdEGG7ClJFGDuxfWeuPPbIQgS6Novs3wUFsh52qSuHzS2vy9zjLSRtgG1CqLKBIeggmw1cJB3ZvMBE2jZ3ZF9w9mIZj/U9EBf7/SWy7UgTI1gm+4XhZacAEHF8PHHPL5ENWhYgfZl9npUQ1/psKUH3MRdudnLBfhKPOf5X2jgR9LEGrht0sBQ7IhosnXPOOVFlahgG3nrrLZx00kk1KpSiKIqiKMqJQkSDpU2bNmHMmDFITCQ/satgmiZmzZoFj4f95FcURVEU5VigM0uxI+JluHHjxoVcro/GP//5zxoXSFEURVGU2qODpdgR0WDp559/jvhYEgD47rvv0LRp0xoXSqk51jK5dm+Q09GtHqIPKJdaAH+C1H6Y6XLW0EqMC/1l0rlxX7GcnbTny27ItBmOIhnmZ7qOCCc1maGlxc/aSsazSo8+GEQ3ESBmmBXpzAgw/H+mOWEnv5cmkwuQk9orSFiQGHAyw9EKYlRpIaetlwTlzQiQtCiV9/tnv/x8SUiWjdy0qewEBtHk5RVLHdz3hVmyLHmyzI5CGc0i/TupMSnTLDFtU1VdkEn6GMuL9UULeZYD0rtTGJ8CXFfIjDW9+0iGBCfT6BWS54I8t+yZ8hMdXJAYWpoBGc/ilddldfMHSd2I3glZpIBE42e6Wcc4wt9KvSGiwVLLli2jyrR58+Y1KoyiKIqiKLHBRO23/pPx4O+SGu2GKywsxIYNG7B3714Eg+G/TgcPHhyTgimKoiiKUnN0GS52RD1Yevvtt3H99dejtLQUycnJMIzDDWkYhg6WFEVRFEVpUES9ejpmzBj87W9/Q2lpKQoLC1FQUBB65efn10UZFUVRFEWJkkMzS7V9KTWYWdq1axfuuOMOxMdHJvhTji1M7Olnxm5EJGkhQnBmsGYSIbOfCIPZUjkT47LyscQB4v/mLGaiVZnWRrSZrt0yrTtbpvVJrTA/ST5CQS6rm62KyaWViIIrMmU6u0MqjyscRLlOBNnWQiJEJRgV8t5aD8gG8GfJBnAmygYIOGWZ/R6Zn9crw/LL5OdOhSeyepT7IhS5E9NAk9xvR7EMY4LpquJ9AHCUhPe98nTS74iRKiuHQfqdQfTJFmIEyfonSwsWliADTatsu6BdPmfMDJOazlbIwLg8GVaeJa8RSJLl89qJuSj53GN9PmAhIvIysvmBmMIGK1+jXE0p6yNRzyz17dsXX3zxRV2URVEURVEU5YQjopmlt956K/R3//79MW7cOHz33Xfo1KkT7PbwX3WDBg2KbQkVRVEURYkanVmKHRENlq644goRNm3aNBFmGAYCATZfqyiKoijKscQ0DZi1HOzUNn1DIaLBUlV7AOXEoOPER2RgmuzYzBSPaZYCGTIi0xjZiP7FQbQzjLISKTximg5q+sjiEc2FaSUaLTvRETDvOFINZobJDhtl2iYGTVvFbzJAdCiOAqKlyZbxrKVydd0kmjJ2kDDTl4BIoIJOEo/cHw+73+SQ28bpJSLMRw57TiAH82YkylONA0FZ39wiaeoJoi9h+jaGrTwyk8cAOYC1KkwnxIxZWd/xprIMZRC7t8wckjzysJXKC/uJ3ouW2SBtLM+upc8jDSP9kX42FEemPQumyofNZIfmkn6LRvLGBUmfsu49XGimh6orgjBq7bNU2/QNhajv2osvvkjPffN6vXjxxRdjUihFURRFUeoXM2fOxHnnnYekpCRkZmbiiiuuwNatW8PibN++HX/605+QkZGB5ORk/OUvf0FeXl5YnK+++gqXXnopUlNT0bhxY9x6660oLZU/io4lUQ+WbrrpJhQVyZ/aJSUluOmmm2JSKEVRFEVRasextg748MMPkZOTg/Xr12PlypXw+Xzo06cP3G43AMDtdqNPnz4wDAOrVq3CJ598Aq/Xi4EDB4ZWsHbv3o3evXujbdu2+Oyzz/Duu+/i22+/xdChQ+uiiSImausA0zTDjCgP8dtvvyElJSUmhVIURVEUpXYca83Su+++G/b/Cy+8gMzMTHz55Ze48MIL8cknn2DHjh3YuHEjkpMPLosvWrQIaWlpWLVqFXr37o3ly5fDbrfjqaeegsVycD5n3rx5OOOMM7Bt2za0bdu2VvWpKREPls4++2wYhgHDMHDJJZfAZjucNBAI4Oeff0a/fv3qpJCKoiiKohw/iovDjcWcTiecTmJ+V4lDq1CNGjUCAHg8HhiGEZbO5XLBYrFg7dq16N27NzweDxwOR2igBABxcQcPDF+7du2JP1g6tCNu06ZN6Nu3LxITD58e73A40KpVK1x55ZUxL6ByZJj40U6WdakAlIigjSKZoUlMKX0JcvXWWyJVl4mNpdrT7iIK6iKpMrWXEdPMACkzM9/zE4G3TZY5aCOGdwdkWm8iEUITkal1nwxj2kgmAq76442dGs/ut4e0nZOcrM6EwUyQbfOztEQwTsTCFtJ/gilSPGuQPnUgj4ivSTuVx8mGD/hlxMxGUjButcoK24vJyfREuG0EmYmrLB+LB4MYHFbZcOAsJP0umRizMr/RCA9OCDqZ6lsGeckCAds0YSmSXx9WIvBmUBE52YjC+i0zhHUUElPPRBkvQOphy2OKcXJdtqmB7XNIlB9KRiXBuBGB4D9WxNI6oHnz5mHhU6ZMwdSpU4+cLhjEnXfeiR49euD0008HAHTt2hUJCQkYP348ZsyYAdM0MWHCBAQCAezZswcAcPHFF2P06NGYM2cORo4cCbfbjQkTJgBAKM7xIOLB0pQpUxAIBNCqVSv06dMHTZo0qctyKYqiKIpSC2K5DLdz587Q0hmAo84q5eTkYPPmzVi7dm0oLCMjA0uWLMHw4cPx+OOPw2Kx4Nprr8U555wTmknq2LEjFi1ahNGjR2PixImwWq244447kJWVFTbbdKyJSrNktVpx22234fvvv6+r8iiKoiiKcoKRnJwcNliqjn/84x9Yvnw5PvroIzRr1izsvT59+mD79u3Yv38/bDYbUlNTkZ2djTZt2oTiXHfddbjuuuuQl5eHhIQEGIaBhx9+OCzOsSZqgffpp5+On376Ca1bt66L8iiKoiiKEgPMGCzDRTMzZZomRowYgWXLlmHNmjXVjhPS09MBAKtWrcLevXvp6R9ZWVkAgAULFsDlcuHSSy+NsvSxI+rB0v3334+xY8di+vTp6Ny5MxISwk97jHTkqSiKoihK3WECMNk55VHmESk5OTl4+eWX8eabbyIpKQm5ubkAgJSUlJBIe+HChWjfvj0yMjKwbt06jBw5EqNGjcJpp50WyufJJ59E9+7dkZiYiJUrV2LcuHGYNWsWUlNTa1eZWhD1YOmPf/wjgINnwFW2EDhkKaDHnRw7mMCUiYdZb7cTN2jmqutJlwpQ4wATgsu0br88Nt3wyoiJBaR8ZfK6fhcTccowOxGZMsE4K7O1giheSUS7W8ZzFsgbUtJSrutbPcRJuar49oAshruprKu/kJyEToSyASIv8CcSsaubuA+Tk9+JSTEV25tEfI1C2X+c5BR6TxO5GcBfHCevQcqS6yHKYBIxab+M5iiRFQk4iEibCKZZP2OCcau3ShgTCpMNCM4iGdFRLPuiO1vW31JIrkG0zXa3DGPPGdtwYKWnBcgwP9nAwD5/rCTMIPmxz0J2XWc+a1MZz30SuUYR2fxAunewhDyTlcoXIKcONBTmzp0LAOjZs2dY+MKFC0M+SVu3bsXEiRORn5+PVq1aYdKkSRg1alRY/A0bNmDKlCkoLS1Fu3bt8Mwzz+DGG288FlU4IlEPllavXl0X5VAURVEUJYYEYcA4hsedmBFMY82aNQuzZs2qNs6JeBpI1IOliy66qC7KoSiKoihKDNGDdGNH1IMlACgsLMTzzz8f2hXXsWNH/O1vf1MHb0VRFEU5QQiaBowY+Sz93ol6sPTFF1+gb9++iIuLw/nnnw8AePjhh/HAAw9gxYoVOOecc2JeSIXz7cxRIqztg4+IMHa6fCCOaHg85HRwYtoXcJGpViIRsZKTygPkpHKmMWLGkszcLy5f5kd1BET/YRCTy4BLJnYWSw2LLz4yv4+4fVJ3U54hHztbFa0Lq3+Zn+hQvJF9kEWq32DaJjoLT25PIIGcQl8ky8zM/Uxyf2wFsp0C8URDx7wC3eSjLVHeC6qTYZoy1n5Fsl9QzSCpW1V88UT/RLROvjjSj0n9nUWynbzJsnBM61O1LwKAn5TPWiHTGkTyFySfDc5CEo9ooCI1U2UaKHuxDAtIyRu9rqNQhvmSZBjT6dmI5quy0ecx9KRUYkjUg6VRo0Zh0KBBeO6550JHnvj9ftx8882488478dFHH8W8kIqiKIqiRIdpxmA3XC3TNxRqNLNUeaAEADabDXfddRfOPffcmBZOURRFUZSaoZql2BG1d3hycjJ+/fVXEb5z504kJZF5SkVRFEVRlHpM1IOla665BsOGDcNrr72GnTt3YufOnXj11Vdx880349prr62LMiqKoiiKEiWHZpZq+1JqsAz30EMPwTAMDB48GH7/QcGk3W7H8OHDj+qdUFN27NiB6dOnY9WqVcjNzUXTpk1xww03YNKkSXA4Diovp06divvuu0+kjY+Ph9tNFHf/R2VjzUO88sor+Otf/xq7ChxDmGDVkLpW2In5IBM62ktlWEAedE/NDNnp4AY51Z4JSpkJoI0YVTKRNhNdMuEpW4ynhpZF0mnPuU+mDTqJ0adbNr49XsbzVxHuWtzklHdSL2YCyESxTmJyaZL7zQS/fgdpY9KezOjUQvqehZwQzwToDvLYVjiIwJlcg/0MZH3KTtqZic3t5Uy5zDYhRGZcWFUg7yhlZpbE+DSfPCtx8gKOUmLqSsThbOMD6z+sX7B7y9I6SmQYgzVTkASy69qI0SMToDsLyXNL+pSjJALj2CPA2qqy0eexNKXU3XCxI+rBksPhwGOPPYaZM2di+/btAICTTz4Z8fFkO0KM2LJlC4LBIJ555hm0bdsWmzdvxi233AK3242HHnoIADB27Fj8/e9/D0t3ySWX4Lzzzjtq/gsXLkS/fv1C/x9PS3VFURRFUU4sauSzBBycsenUqVMsy3JE+vXrFzaYadOmDbZu3Yq5c+eGBkuJiYlITEwMxfnf//6H7777DvPmzTtq/odOPVYURVGUhoLuhosdUWuW3G43Jk+ejO7du6Nt27Zo06ZN2OtYUVRUhEaNGh3x/fnz5+PUU0/FH/7wh6PmlZOTg/T0dJx//vlYsGBBRJbtiqIoinIic3CwVFvN0vGuxYlB1DNLN998Mz788EPceOONaNKkCdX81DXbtm3DE088EZpVqkpFRQUWL16MCRMmHDWvadOm4eKLL0Z8fDxWrFiB22+/HaWlpbjjjjuOmMbj8cDjObzwXFxM3M8URVEURWkQRD1Y+u9//4v/9//+H3r06FHri0+YMAGzZ8+uNs7333+Pdu3ahf7ftWsX+vXrh6uvvhq33HILTbNs2TKUlJRgyJAhRy3D5MmTQ3+fffbZcLvdmDNnTrWDpZkzZ1Ix+YmAL4EIVtnp4GURDnKJ4y1zDGYiW2K4TQXeTCzsKJIZMjF30E7qQQbwfiJkjd8l1fDFpyaKMHembISEXKYqljBHcCa0rer0zeplI+JzPxHbs1PjmQs31UWTe2vxEQFsoYxXdhJxnHbIm2stj2xC2ydvBUyrvAbLj7mEGxUyHhMkM1E+cywPEsF40BKZwDs+N1wFXHCatE4P2mVCFxF4U8d68sz7XaTfEQd8PxEyW8hGAra5wE42a7Dn20+c4k1ibW2QeHF75TVKWsi0FY1lWkdRhI731gg3IRSRtMwRvFK8AGm3ukJ9lmJH1IOltLS0ape/omHMmDEYOnRotXEqL+3t3r0bvXr1Qvfu3fHss88eMc38+fMxYMAAZGVlRV2mLl26YPr06fB4PHA62dkPwMSJEzF69OjQ/8XFxWjevHnU11IURVGUusIEHedHnYdSg8HS9OnTce+992LRokW13gGXkZGBjIyMiOLu2rULvXr1QufOnbFw4UJYLPzX6c8//4zVq1fjrbfeqlGZNm3ahLS0tCMOlADA6XRW+76iKIqiHG90Zil2RD1Y+uc//4nt27cjKysLrVq1gt0ePuf41Vdfxaxwh9i1axd69uyJli1b4qGHHsK+fftC71XdxbZgwQI0adIEl112mchn2bJlmDhxIrZs2QIAePvtt5GXl4euXbvC5XJh5cqVmDFjBsaOHRvzOiiKoiiKUj+JerB0xRVX1EExqmflypXYtm0btm3bhmbNmoW9V3nnWjAYxAsvvIChQ4fCapVihKKiImzdujX0v91ux1NPPYVRo0bBNE20bdsWDz/88BG1UPWBQIp0LrSUybagp3kTMZKfnCRvJdoPT6a8bkIT6WgZCMi0eXFyhjLjM7nwX54hf+FUPs07BJk3Zmadxa3k8TxMm8GoaCwfHYtfXthDTnq3kdPkC9uG17c8U17THyfTxZ8qRRPlm1NFmLexvD/ODCmCYr8hA15Z19Jy8tFhI+IUt4xn2iLT3ZhJRLdWLPPzNZMuf9mZRExCyE1Mk9clQpmKRhH2PSahI2aiJc2qXIM1POnHnlSi6yH5e5NlGDOYLW4hG74ik2kDiSFsY9nucV9LfZ+nMdGyNSb3lrUB0aO5TyLaMyK2s3pkhkwHx9rZl0wMa0tlfiVtSOJM6YYZzD98v4PM4LSu0HW4mBH1YGnKlCkRxXvllVcwaNAgJCQkRF2oqgwdOvSo2iYAsFgs2LlzZ8T5VPVvUhRFUZQGQyyOK9FlOAA18FmKlNtuuw15eXl1lb2iKIqiKMoxocYO3kdDjR0VRVEU5fihDt6xo84GS4qiKIqiHD90N1zs0MFSPabd0mkirElLKdo9N13quPJ9UlTNTpfe8EtLERaoIN3GI1d0y0qkULZRY6kytWRLweOBs6X4mok4TScRS5IwLxGlW5Pl8eBJSVIJ3jo1X4TtK5daPLtFKm13/yTPHGTGnJYq5Qu6ZB1anZIrwir8Ughf0oyp1IlZIIllt8k6BIlZYEqW7GcnJUlRdddGP4uw/URlayWbC/7fTx1EmMcu62v65W6FA8Xy/rTJ3C/CAtmybvvOIz5yrLFcsq0Mq7xvpl/2vUB8eN9LTpSi4JNTD4iw/RXyubVZ5DV/3EHOuvTKclTtdwAQjJP5ZTQrEGEO0ld2dWA7R+S9dSbIZ89pl6Jvj09+1jRKlH0vK6FEhJ2ftkOE7fXKzxU7ab/l2zuKMK9HliXok+3nsMt2yTztsCTF7/bgyMpa5URFB0uKoiiK0hAxjdoLtHVmCYAOlhRFURSlQaKapdhRZ7vhWrZsKQwrFUVRFEVR6htRzyzt3LkThmGEzCE3bNiAl19+GR06dMCtt94aird58+bYlVKhVOyV+oU9pVIn9P/2S4e6INFRoCyy7mCQg1XZAafGflmW0nipVfCUyhMqreQazHCTlcVCDBODdmK4SepbQk4O3lzWROZHzDVZfgZpFxCZVTC1SruUS+1HYYUsW6lbtrFRRIwgU6QepDxf5ldB9FTMRNJL7llpmSzLD/vkcUYB0vf85eSHFZn9N4nuxiBmmL4D8oTh/YlSx1RcKtuA9u8U2W9NoldBGTu1mvQ9M7z9ioIyr69KZNnMAHkumEEoNcckh8MSbZxB9Ie+oOyPpeSzBm4Zz5IiNXSs/3i95FRochDzXo+8htsj89tRKA1H/QGZttwt07JDwNlnpoX0PU+xbJffKvXvYLnUp9UZakoZM6KeWbruuuuwevVqAEBubi4uvfRSbNiwAZMmTcK0aVJwrCiKoijKsefQbrjavpQaDJY2b96M888/HwDw73//G6effjo+/fRTLF68GC+88EKsy6coiqIoSk0xa/lSANRgsOTz+eB0HpxmfP/99zFo0CAAQLt27bBnz57Ylk5RFEVRFOU4E/VgqWPHjpg3bx4+/vhjrFy5MnS22u7du9G4ceOYF1BRFEVRlOjRZbjYEbXAe/bs2fjTn/6EOXPmYMiQITjzzDMBAG+99VZoeU45NphE/GghBmtBYqYGZvBIhLxM7MmwlUrhJBOPMvGjI5EIQBOIWJoIbyMVrYIYKxrkJHULMRX0ERNOFo/lZxIxKvuJYikJvwYzBmRi7vg42XZFCVKwCiLcNtjh53HkCHtmoukkYnvSp/zeyNrO4pD5ceEy6aOlRNBP+kBJmRQQx8d5RFhRImk/Iug3iOCXmaQaTAhexdDRIM9twEfE0mwjBel3YG1HllQsRJBtks0QxcVSbN44VRrMlifKPko3k7DnMV5uQmCCdodLxrOSPlXhkWJ7ZrrK8vOQDQesfweIoN9C8jMr9x9S9zpDBd4xI+rBUs+ePbF//34UFxcjLe3wboNbb70V8fFyd5aiKIqiKEp9pkY+S6Zp4ssvv8QzzzyDkpKDNvMOh0MHS4qiKIpywmDE6KVEPbP0yy+/oF+/fvj111/h8Xhw6aWXIikpCbNnz4bH48G8efPqopyKoiiKokSDLsPFjKhnlkaOHIlzzz0XBQUFiIs7vI79pz/9CR988EFMC6coiqIoinK8iXpm6eOPP8ann34KhyNcBNmqVSvs2rUrZgX7vXPa9EfC/vcnEGGniwhMiSCbnXLPwoLxRJxKtKPWCpnWLg/9hs8kjrfZ0gnZRwTo9gIpPPU1kuJMWyEb7xOH6CQifCdu0F4PccRmInLSfkiUwk6iR4ZBTnq3F4eHyVYCEptIMXI5EbHaCmR7BjJkjlYSDyWy3QMJrO1kPA8JM2nfI300kdVYYiHO5rYScr9J2niXFMOz9mPtEkiTOdqKSd8zSfsRsb5pCY/nY87kRAgcYP2OifJJkIV8NthLZX6+RJnW6SLO+34i3s+X4ngzXfZbg/U9g2wSSZAV8ZINFyyMCcsrSJuyDSYGeXCZmNtWLMvsZw99JdgzUWf8jmaWiouLI46bnCxPtTgaUQ+WgsEgAgHZgX/77TckJSVFXQBFURRFUeoA0zj4qm0e9YDU1FQYRmRlZWOYoxH1YKlPnz549NFH8eyzzwIADMNAaWkppkyZgj/+8Y9RF0BRFEVRFKU2HDqGDQB27NiBCRMmYOjQoejWrRsAYN26dVi0aBFmzpxZo/yjHiz985//RN++fdGhQwdUVFTguuuuw48//oj09HS88sorNSqEoiiKoiixxTQPvmqbR33goosuCv09bdo0PPzww7j22mtDYYMGDUKnTp3w7LPPYsiQIVHnH/VgqVmzZvjf//6HV199FV9//TVKS0sxbNgwXH/99WGCbyVy2t/7iAgLVmlKexHRzdiJHoR0bDqLSsztmE7IGuEB2USqAWehDCvLI30kTWoGAq7InlCrTAp/vEzrKJD6BQ8x36Pr86z9mKFlAdG/EH0XkXIhWCWpg2ixCnfLdXZX43IRxjQyrF5WjywbaztbEdGPMSNE1k4kzCRpDaJ1sbO2Y/kRM1U7ab+CPbL94hqR9iOGluwLw0JMUgMOUhaibfJWef4MC6kYa09maEr6na2cNRQJItEc5LOmPDdBhNmbSY1IkOin2GeShdzbAOt7TD/G+h6DNSlJ682XZqVMG2dhppSkr9iKiH6qcr8gedcZx1izNHPmTCxduhRbtmxBXFwcunfvjtmzZ+O0004Lxdm+fTvGjh2LtWvXwuPxoF+/fnjiiSeQlZUVivPDDz9g3Lhx+OSTT+D1enHGGWdg+vTp6NWrV0TlWLduHd2Zf+655+Lmm2+OvEKVqJHPks1mww033IAHH3wQTz/9NG6++WYdKCmKoijKicQhzVJtXxHy4YcfIicnB+vXr8fKlSvh8/nQp08fuN1uAIDb7UafPn1gGAZWrVoVGgwNHDgQweDhgeeAAQPg9/uxatUqfPnllzjzzDMxYMAA5ObmRlSO5s2b47nnnhPh8+fPR/PmzSOuT2WinlkCgJdeegnPPPMMfvrpJ6xbtw4tW7bEI488gjZt2uDyyy+vUUEURVEURam/vPvuu2H/v/DCC8jMzMSXX36JCy+8EJ988gl27NiBjRs3hnakLVq0CGlpaVi1ahV69+6N/fv348cff8Tzzz+PM844AwAwa9YsPP3009i8eTOys7OPWo5HHnkEV155Jf773/+iS5cuAIANGzbgxx9/xBtvvFGjukU9szR37lyMHj0al112GQoKCkKq8rS0NDz66KM1KoSiKIqiKLHFMGPzqilFRUUAgEaNGgEAPB4PDMOA03nYosXlcsFisWDt2rUAgMaNG+O0007Diy++CLfbDb/fj2eeeQaZmZno3LlzRNf94x//iB9++AEDBw5Efn4+8vPzMXDgQPzwww813ogW9czSE088geeeew5XXHEFZs2aFQo/99xzMXbs2BoVQlEURVGUGBNDzVJVHyOn0xk26KlKMBjEnXfeiR49euD0008HAHTt2hUJCQkYP348ZsyYAdM0MWHCBAQCAezZswfAwR3277//Pq644gokJSXBYrEgMzMT7777bth5tEejefPmmDFjRpSVPTJRD5Z+/vlnnH322SLc6XSG1iWVI9N2thRzW8ldsFc50DsgNYiwlcqJQSaSjN9NhLJEY8iExyweM6D0psqwIDv4PJnYBTKjuBIiPg7KArJr2MpIWiKpsxBzSHZavWsPMctjTw4TbrN7S9rP0yj8vlmIcZ0tRZr7BYmewFZKjPJIPCZGZm0XcMp4TADLxL2u3VJ8TPsF7XtELE1MFL1pxLCVdDNnmtytEAjIC9uYMSczJiXPBhNWs2eoqkEkE6k7DxDT2Qi1wSyeTWrZ4U0hbUf6iiWVbMIgz6OVmDQGyPMdJH3PWk4+z9hmhQpSOdL3bLvlFzm7LrPmoX2PCfXTI/PrMR2H62EGIhSon2BU1fpMmTIFU6dOPWL8nJwcbN68OTRjBAAZGRlYsmQJhg8fjscffxwWiwXXXnstzjnnHFgsB9vXNE3k5OQgMzMTH3/8MeLi4jB//nwMHDgQn3/+OZo0aRJReT/++OOQXGjJkiU46aST8NJLL6F169a44IILoq5/1IOl1q1bY9OmTWjZsmVY+Lvvvov27dtHXQBFURRFUeqAGJpS7ty5M8z5urpZpX/84x9Yvnw5PvroIzRr1izsvT59+mD79u3Yv38/bDYbUlNTkZ2djTZt2gAAVq1aheXLl6OgoCB0vaeffhorV67EokWLMGHChKMW+Y033sCNN96I66+/Hl999RU8noM/NIuKijBjxgy888470bUBajBYGj16NHJyclBRUQHTNLFhwwa88sormDlzJubPnx91ARRFURRFqQNiuAyXnJx81GNCTNPEiBEjsGzZMqxZswatW7c+Ytz09HQABwdHe/fuxaBBgwAAZWVlABCaaTqExWIJ2zFXHffffz/mzZuHwYMH49VXXw2F9+jRA/fff39EeVQl6sHSIZuAe+65B2VlZbjuuuvQtGlTPPbYY/jrX/9ao0IoiqIoilK/ycnJwcsvv4w333wTSUlJoa3+KSkpIXuhhQsXon379sjIyMC6deswcuRIjBo1KuTF1K1bN6SlpWHIkCG49957ERcXh+eeew4///wz+vfvH1E5tm7digsvvFCEp6SkoLCwsEZ1i2qw5Pf78fLLL6Nv3764/vrrUVZWhtLSUmRmZtbo4oqiKIqi1BHH2JRy7ty5AICePXuGhS9cuBBDhw4FcHAgM3HiROTn56NVq1aYNGkSRo0aFYqbnp6Od999F5MmTcLFF18Mn8+Hjh074s0338SZZ54ZUTmys7Oxbds2tGrVKix87dq1oeW+aIlqsGSz2fD3v/8d33//PQAgPj4e8fHxNbrw74GOE6WY20aE2swl21LlkG8m8GbpmDjTL813YSuVYT6y0aCq0PxI2MmBz5GKUVFKTi8nh9Az8bGFOHgbbKaWuQO7IxOR+xNIWiI09qTLCzNRKNuK6ywIz4+6fMsgeIulbsBB2sRGVKwWLwkjwmgmjre6Sb1IASNuu8ak7UqY6lsGOQoiE1WzhveWyvZzkvZj6n2r1NtTR3kfef6qCtWZG3+ASEJsZST/ZCaWjszB214cmcO8Qdyr3cXyQ8lOXM1RJjO0EPd41n8CbGOGm2wuICLyQAJx1yabYryZ8sPGVhjZV6PjgCwLfXa9hwMNb9SOPTXnGA+WzAjORpk1a1bYTnrGueeei/feey/yC1fhlltuwciRI7FgwQIYhoHdu3dj3bp1GDt2LCZPnlyjPKNehjv//POxceNGIfBWFEVRFEU53kyYMAHBYBCXXHIJysrKcOGFF8LpdGLs2LEYMWJEjfKMerB0++23Y8yYMfjtt9/QuXNnJCSE/2w65LipKIqiKMpxJIa74eoLgUAAn3zyCXJycjBu3Dhs27YNpaWl6NChAxITE2ucb9SDpUMi7jvuuCMUZhgGTNOEYRghR29FURRFUY4ftXXgPpRHfcJqtaJPnz74/vvvkZqaig4dOsQk3xqZUiqRwfQFzgIZxrQJVfUQbD2fmvsRHQXT9dhYPKITYlopTyNyXbIMz0zwrPulSSHTV9iJv6mlkJSPtB3XMTFTRhnPQTQXLD8rqZtB9E6s/SrS2fHv4f8yPVUgTwo4bMTIz0H0YwYxuWR6EFYvC2kT2veIFoP1KXoNf2Rt5yXaJvbD10Y0Vb48qa90FEjNiaOQlI/8BmSmlEzzZSHPWlVNFTWuJG1H25Pof/xESlrV+BQ40nNL+soB+aBZyP12FMn8DGLoSfse02AS09Cg/AiBxScbkGrK2DX8MkOmtfNmkJtLsJQRHZPB/65zjrFm6UTh9NNPx08//VStdUG0RK00a9myZbWvumLQoEFo0aIFXC4XmjRpghtvvBG7d+8Oi/P111/jD3/4A1wuF5o3b44HH3zwqPn++uuv6N+/P+Lj45GZmYlx48bB74/soVAURVEU5cTi/vvvx9ixY7F8+XLs2bMHxcXFYa+aEPXM0ltvvUXDDcOAy+VC27ZtYzqaO0SvXr1w9913o0mTJti1axfGjh2Lq666Cp9++imAg+fW9OnTB71798a8efPwzTff4G9/+xtSU1Nx66230jwDgQD69++P7OxsfPrpp9izZw8GDx4Mu90e0zNlFEVRFEU5Nhw6LHfQoEEwKu0Ero1cKOrB0hVXXBHSKFWmsm7pggsuwH/+85+oDr07GpV9GFq2bIkJEybgiiuugM/ng91ux+LFi+H1erFgwQI4HA507NgRmzZtwsMPP3zEwdKKFSvw3Xff4f3330dWVhbOOussTJ8+HePHj8fUqVPhcJB1GkVRFEWpBxiIgWYpJiU5tqxevTrmeUa9DLdy5Uqcd955WLlyJYqKilBUVISVK1eiS5cuobNgDhw4gLFjx8a8sIfIz8/H4sWL0b17d9jtB9eb161bhwsvvDBsgNO3b19s3boVBQVEKPR/aTp16oSsrKywNMXFxfj222+PeH2PxxOTaT1FURRFUWLLRRddVO2rJkQ9szRy5Eg8++yz6N69eyjskksugcvlwq233opvv/0Wjz76KP72t7/VqEDVMX78eDz55JMoKytD165dsXz58tB7ubm5Yvnv0CAoNzeXznLl5uaGDZSqpjkSM2fOxH333SfCu058ClbnYVWqjUifqKi4mAz9xXBeju9dBVLs6m5ChK1kt6RJ7jw7qd0gs5VMxGolYnYmRvUlELGni/30iVCQHaEZpkmEnfG58rplWZGZejKBMxX3MnG4hQjaq5h/srbzk7Zjp6gzBWmQCOGZGJf+jCSC7Pgi0naZkbUdExXTtmMC5wpiDslMXdmzF8+MH2U9mKCd/aykfY/VjdTDXhZ+3fLGEfY7Km6WYUyUS01ISVq2mYRtkAg6WET58DGhfqRtxzaJOPfIsLJsGeZLlI3AzD8jFc3DSvoe2UhA+57zcH5B0ofrjN+hdcAhCgoK8Pzzz4dMtDt06ICbbroJjRqRHUoREPVd2759Oz1MLzk5GT/99BMA4JRTTsH+/fuPmteECRNgGEa1ry1btoTijxs3Dhs3bsSKFStgtVoxePDgiBxDY83EiRNDs2pFRUXYuXPnMS+DoiiKolSLGaNXPeOjjz5Cq1at8Pjjj6OgoAAFBQV4/PHH0bp1a3z00Uc1yjPqmaXOnTtj3LhxePHFF5GRkQEA2LdvH+666y6cd955AIAff/wRzZs3P2peY8aMCZ0XcyQqn+OSnp6O9PR0nHrqqWjfvj2aN2+O9evXo1u3bsjOzkZeXl5Y2kP/Z2eTnx3/F75hw4ao0gCA0+mE00l+qiuKoiiKclzJycnBNddcg7lz58JqPTjbGQgEcPvttyMnJwfffPNN1HlGPVh6/vnncfnll6NZs2ahAdHOnTvRpk0bvPnmmwCA0tJS3HPPPUfNKyMjIzTgipZg8OAUsMdz0EyjW7dumDRpUkjwDRzUV5122mlHFJp369YNDzzwAPbu3Rs6DHjlypVITk6OmZGVoiiKohwXfqc+S9u2bcPrr78eGigBB80qR48ejRdffLFGeUY9WDrttNPw3XffYcWKFfjhhx9CYZdeeiksloOreldccUWNCnMkPvvsM3z++ee44IILkJaWhu3bt2Py5Mk4+eST0a1bNwDAddddh/vuuw/Dhg3D+PHjsXnzZjz22GN45JHDh9kuW7YMEydODC3t9enTBx06dMCNN96IBx98ELm5ubjnnnuQk5NTo5kjmwewVupYtvLIellV/QJATOvIsnGk6+/sMFxmqOdLIoVjh0KSXhOUK7NU+8B0Mr4kWQ+mVWD6Kavn6G0HAEErM1aMzIDSTurBrkHbj2DaiOFdSnhZmO7BUSTLy3QZNqLhYR94tgpmUhjZwaq07SLte6T/eFMie1Zo3yOPKusr9iJZEVY39jwyWDuz55QZp1a9H8z0kpnaMs2Sh/wWZPUy7bJegQjPQWcH0PrZQbXkuWUwnRm9t+Q5C5A2YHpLe0lkByx7U2U92A6yIGm/YCNy44gBrGvv4fYLELPMuuL36OANAOeccw6+//57nHbaaWHh33//Pc4888wa5Rn1YAkALBYL+vXrh549e8LpdIb5GNQF8fHxWLp0KaZMmQK3240mTZqgX79+uOeee0KDmpSUFKxYsQI5OTno3Lkz0tPTce+994bZBhQVFWHr1q2h/61WK5YvX47hw4ejW7duSEhIwJAhQzBt2rQ6rY+iKIqiKHXDHXfcgZEjR2Lbtm3o2rUrAGD9+vV46qmnMGvWLHz99dehuJGeZ2uYUSqkg8EgHnjgAcybNw95eXn44Ycf0KZNG0yePBmtWrXCsGHDosmuQVBcXIyUlBR0GjYDVkel3XAxnFnyxZHZF/ILxZNCZlDILzE6s8TOGIxwZonBZpbYURdsRibpV5JfLWaWfGQnFDsOwUvKwnYO1mZmif1CrTolEenOOjazlPQL+fFSi5klPzuaohZtx/qPL7nmM0usj7K+wo6QYTMwyT/X/cxS1Vk4T1pkR8qwZ9lLZnUjnVli/ZjBjiRiM0vJ2yPbMxTpzFLEfS9FhtFdsTGeWaJbpI46s1SBbbPvRlFREd0sFQsOfSe1uv8BWFxkO2IUBCsqsOOeSXVa3lhzaJXrSNTkPNuoZ5buv/9+LFq0CA8++CBuueWWUPjpp5+ORx999Hc5WFIURVGUE47fqWapLs6wjXqw9OKLL+LZZ5/FJZdcgr///e+h8DPPPDNsm7+iKIqiKMeP36tmKdJzavv374/58+ejSZMmR40b9WBp165daNu2rQgPBoPw+Zg72u8HR4kJayWTQKuXGN75ZZgRIGFVZoZNi5w/ZtPWzkI5pexNJFOSZGbWlS/DqLiXTd2T5YdITfWYCNjuPnqbAJG1HcAFyWxK3lVIxNeJzJCPpCXWYmxZxiRi86rxIjVzZCJWG1nW5UaDMszil4EmmdKmfY+I973MEJW0iXN/ZLpH1u7sw5wuCZJL2NwkjArk5UWsZFmUxYMh26+qwaqDmHxWFf0D/NlzkgMKWF+pbIwYKhrpA0xsb1plGBPMM1E6Ncgkzy1d1qQbM2Q8Z6EMY7ICZpDp2hfZ0iH77GKwpfHKAn4z+mPJlDrio48+Qnl5ZLsSojal7NChAz7++GMR/vrrr+Pss8+ONjtFURRFUeqCQw7etX0p0c8s3XvvvRgyZAh27dqFYDCIpUuXYuvWrXjxxRfDjh9RFEVRFOU48jvVLNUFUc8sXX755Xj77bfx/vvvIyEhAffeey++//57vP3227j00kvrooyKoiiKoijHjRr5LP3hD3/AypUrY10WRVEURVFixO9V4F0X1GiwpHCsFUHYAocVk0zgzVy3fQlygs/uDlde2sqI8JaIH5mAnIkz4w7I/BzFUnlY0lyqGpm/U1XBKgCYhTLMT/yOmH8Q86hiAlVfggxjvlUsPyaCtfpIPLJkb98n4zmKIm0/UjdH+EVo2xHRN3UcZ23nkJXwu2SYgwqeI2s75g3F+qirQObnLJL9sbSpVDNbiZiZCW+ZUzzzO7KXkLQl8j4GHEcXaQOAnQicraT9WFuJ/Im3kb2U9LsSGebOkuVlAnxWB1tZZBsamGM76yv+CJ9btjGBOYIzgTcrC+sXTAzvKpB9r6SZbD92DeYjxpz2K99vyzF08NZluNgR0WApLS0tYpfu/HyypUpRFEVRFOUE4u6770ajRo0iihvRYOnRRx8N/X3gwAHcf//96Nu3b+hctnXr1uG9997D5MmToy+toiiKoiixJwbLcPVxZmnRokVIT09H//79AQB33XUXnn32WXTo0AGvvPJKyIdp4sSJEecZ0WBpyJAhob+vvPJKTJs2Df/4xz9CYXfccQeefPJJvP/++xg1alTEF1cURVEUpY74nS7DzZgxA3PnzgVwcDLnqaeewiOPPILly5dj1KhRWLp0adR5Rq1Zeu+99zB79mwR3q9fP0yYMCHqAjQk7GVB2GzE5a0STLPkypcaiaqakADRlzADPKZ/Ylokb5LUg7B4cQdkWHljmZbpmKwVsi0CLpY2MvNOPzkfj+kN2PlmJvl5ZRAxEtXxEE0I014x4veT9mtE2qCK1oPVPxAn7y07J4tpK5g2hbYdMxwluiNmZsjOL2QaG3ZOH4OVz5MamZbEQrRnTLfF+h7tt+S5dRZHpuWijq1V8JLnlup/SBsbQaYBIyaXSURLw3RHRCdUkSbD2PlurN+CPFNOYv7KtEisP7K+54+XYUyPxuJxk0tZPnbuJtOe2YiOsKLSSk8gwvP4lJqzc+fOkHn2f/7zH1x55ZW49dZb0aNHD/Ts2bNGeUZtHdC4cWO8+eabIvzNN99E48aNa1QIRVEURVFijBmjVz0jMTERBw4cAACsWLEiZGvkcrkiduyuStQzS/fddx9uvvlmrFmzBl26dAEAfPbZZ3j33Xfx3HPP1agQiqIoiqLElt+rdcCll16Km2++GWeffTZ++OEH/PGPfwQAfPvttxGfG1eVqGeWhg4dik8++QTJyclYunQpli5diuTkZKxduxZDhw6tUSEURVEURVFiwbhx49ClSxfs27cPb7zxRmjV68svv8T1119fozxr5LPUpUsXLF68uEYXVBRFURRFqSs6d+6MPXv2IDMzMyx8xIgRyMrKwt133x11nhENloqLi5GcnBxxpiUlJUhKIsd+N3CMgAmj0pxlwEUEueVSnWiQE7irrhPTU+PZSejEUM9WKsOcBVLZ6Y8jwmNihmkjYlQmnrV4IzSgJGZ0QRsRC7tJI7ATzZkxJ/EJY+3HzCvtpP3i9suy+Jl43U3uR/zRDQ6ZcJSJcZkBJRMZ291E4E76nUlE70wAy3AWyzaxk/7jyifia/KsOEpJGxOBM+srTFNNxbis7xFBOxOCgwirQTYXRHJavYP0bWZmyYTbAWekbSf7J+srzISV9r1In1sSj4nS2YYLZqjLCuggYnvW5+MOsL4X2aYOFo8+G6TI9kpmr2pKWfeYpkm9Id1uN1wuV43yjNiUko3SjsRJJ52ETZs2oU2bNjUqlKIoiqIoteP3plkaPXo0AMAwDEyePBnx8Ye3PwYCAXz22Wc466yzapR3RIMl0zQxf/58JCYmRpSpz0d+hiiKoiiKotQRGzduBHBwzPLNN9/A4Tg8Ze9wOHDmmWdi7NixNco7osFSixYtotrplp2dDbs9grlnRVEURVHqjno0M1RbVq9eDQC46aab8Nhjj0UlHzoaEQ2WduzYEbMLKoqiKIpyDPidapYWLlwY8zxrtBtO4TgKK2CrpKEMOiNr3iA50bzqae1SJgy49kqlYNGp0qLW30SWIyGPuIYTYScTNQbIKeLM6Zu6HpPT5W0eJm6NTMzNHNHZSfcgAvS4PNJ+baT4ryxTCmPj9rE7ImHC5YBTxos7EF5f1nZMxGolwmMmKmeC2iARBhPNO0CEkvG5cqm96GRpE16WJa/hIiJbJshmruOs77nyieM2ud/MTdxCRO628kjvLbFiZt2WiL7j9oW3X2FbWVkmDGfO0kykHbQdfRMBALgKmGBcxrOSzRpWslmDbYZgm1PY/aHu8eTzJzFXKvULT5afcWWZrK+Qa5C+x4TbftIutP1I3SrHC3jr4ehD0cGSoiiKojREfm8C77pEB0uKoiiK0hD5nS7D1QVRO3griqIoiqL8ntCZpRhS2C4JVsdhzYudGMOVp8uFeS8R7FfVD9mIkVlpkwQRxszjItUMWMlaOovnIOaDFWmyXu4mRAxAfqV40uSYvdH3MmJ5uszPmyLzY7AT0ktOihNhFiZXIWX2JskyM9NDbzIz15QZljQLb79yZmlGysFOUW/0rXysKxqTtmMbRcgts5JzJ8sypACGGqeyvke0H6ztfPGk7xHdUVmGvBflWTI/RiHRCzb+RhawvBbtx55Jd3aV9mO+mqQvMlNO2nbEE7iyMeIhyrJkfmXZzGxThhUmyJub+g3pe+kyO29qZLo1i0cGlp4U2dcW63usXVg8dm/tJTKspJUsX0W6zNBReLifBSpIReuIY70MN3PmTCxduhRbtmxBXFwcunfvjtmzZ+O0004Lxdm+fTvGjh2LtWvXwuPxoF+/fnjiiSeQlXXwoV2zZg169epF89+wYQPOO++8WtWnptRoZunjjz/GDTfcgG7dumHXrl0AgJdeeglr166NaeEURVEURakhZoxeEfLhhx8iJycH69evx8qVK+Hz+dCnTx+43QdH6m63G3369IFhGFi1ahU++eQTeL1eDBw4EMHgwUFm9+7dsWfPnrDXzTffjNatW+Pcc8+NQaPUjKhnlt544w3ceOONuP7667Fx40Z4PAenPIqKijBjxgy88847MS+koiiKoihRcow1S++++27Y/y+88AIyMzPx5Zdf4sILL8Qnn3yCHTt2YOPGjSEPpEWLFiEtLQ2rVq1C79694XA4kJ2dHcrD5/PhzTffxIgRI+gRJseKqGeW7r//fsybNw/PPfdcmPFkjx498NVXX8W0cIqiKIqiHH+Ki4vDXocmSqqjqKgIANCoUSMAgMfjgWEYcDoPL3W7XC5YLJYjrky99dZbOHDgAG666aYY1KLmRD1Y2rp1Ky688EIRnpKSgsLCwliUSVEURVGUWnJIs1TbFwA0b94cKSkpodfMmTOrvXYwGMSdd96JHj164PTTTwcAdO3aFQkJCRg/fjzKysrgdrsxduxYBAIB7Nmzh+bz/PPPo2/fvmjWrFlM2yZaol6Gy87OxrZt29CqVauw8LVr1/7uD86tSDVgrWSaV9pMip6DxHjNJHehqoFckIgzfeSoPn8KOeU+Taqb/RXs1hMTyR2ywEZAhjmI+JGZzLnbSLWrQU4Wz7dIRz52AnnQQUz6HFJgaakgJn2Jsq2cyfLXUtO0IhFWWEHE4UQJWbg9TYQZfnKqfVn4//54YpbYQnaCQLEUIxedTNwMyc+igDOy9rQSEXSAiHvNFHlvGzUuFWGlFVIczmb6/T/LDm7xHb3tAG7U6G8hnwMzIPM7ECQKdGaaGUfawEaML72s74Wrsu1J0uGxaWPZ74orpGmqnzRe6Y5UEcb6nbWcmEMyM8wW8gG3WWX9Cy2RnR8Kl3z2rHaZn98jP0QsCbKtUhPlLoRT0vaJsP0VclOMg+zq+OYn+cVc7pH30SBhppMoxttV6qRlZLdJXRHDZbidO3eGHR9SeXaIkZOTg82bN4fNGGVkZGDJkiUYPnw4Hn/8cVgsFlx77bU455xzYLHItvztt9/w3nvv4d///nctK1F7oh4s3XLLLRg5ciQWLFgAwzCwe/durFu3DmPHjsXkyZProoyKoiiKohxHkpOTIz5r7R//+AeWL1+Ojz76SMwI9enTB9u3b8f+/fths9mQmpqK7OxsOtmycOFCNG7cGIMGDYpJHWpD1IOlCRMmIBgM4pJLLkFZWRkuvPBCOJ1OjB07FiNGjKiLMiqKoiiKEi3HWOBtmiZGjBiBZcuWYc2aNWjduvUR46anH/SUWLVqFfbu3SsGRKZpYuHChRg8eHCYPvp4EfVgyTAMTJo0CePGjcO2bdtQWlqKDh06IDExwulXRVEURVHqnGPts5STk4OXX34Zb775JpKSkpCbmwvgoKY5Lu6gdGHhwoVo3749MjIysG7dOowcORKjRo0K82ICDg6ifv75Z9x88821q0CMqLEppcPhQIcOHWJZlnqPPx4wKy3jWshmAT8xUWSmdY4qaZkGw8o2IxTLiMEK6VxoJde0lUW2LZM9PJ5UGUYNMn2kImQJn2lTfEQjYpB41jLZrYN2oiUpk3oID+Q6/I6yDBFmEv2Hxc1OAiWQZvYlh9eNmfH5vUQ/VirDbKQ9vSlEi0T0KvZSomFh20AMosMhYpd8d6pMynRHbqIHidCo0SdlKPSQV5O0H0gfYGl9yaT9iLmg4ScaFqJjQml4H/UT7dQvJbLfsfytrO3IPTOIeWXARZ4LUi+vR95bcoYzDKINNFPlB4HJdFxu8nVEdIpeU2reDgRkfvnF8nMvSOIFqX6TQE4aZ/okpo/07juscQyS566hMHfuXABAz549w8IXLlyIoUOHAji4SWzixInIz89Hq1atMGnSJIwaNUrk9fzzz6N79+5o165dXRc7IiLqJX/+858jznDp0qU1Lkx1DBo0CJs2bcLevXuRlpaG3r17Y/bs2WjatCmAg66fjzzyCDZs2IDi4mKccsopGDduHK6//vpq82W+Da+88gr++te/1kk9FEVRFOWYcByW4Y7GrFmzMGvWrKPGe/nllyO/8DEgIuuAytsFk5OT8cEHH+CLL74Ivf/ll1/igw8+QEpKhGdP1IBevXrh3//+N7Zu3Yo33ngD27dvx1VXXRV6/9NPP8UZZ5yBN954A19//TVuuukmDB48GMuXLz9q3gsXLgxzC73iiivqrB6KoiiKciyIpXXA752IZpYWLlwY+nv8+PH4y1/+gnnz5sFqPTiFHQgEcPvtt0eslK8JlafpWrZsiQkTJuCKK66Az+eD3W7H3XffHRZ/5MiRWLFiBZYuXYoBAwZUm/chNb6iKIqiKEpVojalXLBgAcaOHRsaKAGA1WrF6NGjsWDBgpgW7kjk5+dj8eLF6N69e7Uq+aKiopBzaHXk5OQgPT0d559/PhYsWHDUqUSPxyPcTBVFURTlhOIYnw3XkIla4O33+7FlyxahXN+yZUvoILy6Yvz48XjyySdRVlaGrl27VrvE9u9//xuff/45nnnmmWrznDZtGi6++GLEx8djxYoVuP3221FaWoo77rjjiGlmzpyJ++67T4QbgXABqp8IT5nomZ0aHqxyZ4hvGhfeEmzuSEW7pGxE7MpEtg7pPYiA9G2ErVAKan2NZQMwU0YmDGZCcGasyE4WDxLhrUFOV0c5EQYT4anJRORE7Mk+fOwl4fH8ccQwslAKW0Hq6pe6VtpOtE1IVdk0PDMIZTDxMTMrZfeCCqjJZZkhql96N8JSRIT/CbIz++PIddlmBSLKZn2P3e9I2s+oiKzfsc0LrO2YQNkmvRwRIF6D/lL5o9TVSCb2JJKvFCJKZ20HZubI+q2NiKrJcxsgm0mYAa5hl33AJJtEQIpnIaaZ7H5U/uxin2N1xjHWLDVkop5ZuummmzBs2DA8/PDDWLt2LdauXYt//vOfuPnmm6M+u2XChAkwDKPa15YtW0Lxx40bh40bN2LFihWwWq0YPHgwnQVavXo1brrpJjz33HPo2LFjtWWYPHkyevTogbPPPhvjx4/HXXfdhTlz5lSbZuLEiSgqKgq9du7cGVW9FUVRFKWuMWL0Umows/TQQw8hOzsb//znP0NnuTRp0gTjxo3DmDFjosprzJgxoe2ER6Kyq2d6ejrS09Nx6qmnon379mjevDnWr1+Pbt26heJ8+OGHGDhwIB555BEMHjw4qvIAQJcuXTB9+nR4PJ4j2rk7nc6jWr0riqIoitIwiHqwZLFYcNddd+Guu+4KaXVqKuzOyMhARob0EomEQ0t+lU8+XrNmDQYMGIDZs2fj1ltvrVG+mzZtQlpamg6GFEVRlPqNLsPFjBqbUgI1HyRFy2effYbPP/8cF1xwAdLS0rB9+3ZMnjwZJ598cmhWafXq1RgwYABGjhyJK6+8MuQc6nA4QiLvZcuWYeLEiaGlvbfffht5eXno2rUrXC4XVq5ciRkzZmDs2LHHpF6KoiiKUlccawfvhkzUg6XWrVtTI8dD/PTTT7UqECM+Ph5Lly7FlClT4Ha70aRJE/Tr1w/33HNPaAZo0aJFKCsrw8yZMzFz5sxQ2osuughr1qwBcHB33NatW0Pv2e12PPXUUxg1ahRM00Tbtm3x8MMP45ZbbqlROS0+oPLByUw86SOnwtjlYfJCTEhFu0R8bSXOz0zIywSrASaKJddggnQm8CaXQHk2ceEmJ3c7CoiDN3GhtpG2M4gLNWt3i5cI333ykWCntTPBdCCe1I2KQolzthApExflRlKIaimUwltnvryml1igOdgmTvLByDYqMAExcwRnH7TcSVqGsU0NrD/KtgOthzc9sr7nJH3PkyYztJM+z+4bcxivKnK3MHd21u9I27HNEAiS+0PazlEkw7zkN3AgjmzC8MpnxZovwwKN5SeBtZg8Z6TMAeLaH7TItF7mzk7yY22KONLRSFoL6Sv2EnK/k2R2lfsjFbcrJzxRD5buvPPOsP99Ph82btyId999F+PGjYtVucLo1KkTVq1aVW2cF154AS+88EK1cYYOHRqmkerXrx/69esXgxIqiqIoygmGLsPFjKgHSyNHjqThTz31VJirt6IoiqIoxxkd7MSEqK0DjsRll12GN954I1bZKYqiKIqinBDUSuBdmddffz0it+yGTCAOqHxovUk0AtT4kYh7/FU24zFdU6SmlJHCNCzsBHtmzkb87uAsJCeGH5CFrsggugSyGZFdw+qRYUxjw+rmsUWmsWH3jJkK2gvJifCkfCy/qiakdqIlCTilPokZPDJTQQbVvxDtENMEVS0vwPVZ1KSFhLH7Y2V9j8DagGlx/AnEEDVJFprpp1iZqe6PaAt53yPXiABmGuooYvoxkjiCfncwPxnm2yc7ldG0TIT5icaIPbhWohcMOMkzVSKfKS8xMIUlQh0QMa+05Mvnykb0d4wgOUCC6Zgqt7PBDEPrCBV4x46oH9mzzz47TOBtmiZyc3Oxb98+PP300zEtnKIoiqIoNUQ1SzEj6sHS5ZdfHjZYslgsyMjIQM+ePdGuXbuYFk5RFEVRFOV4E/VgaerUqXVQDEVRFEVRYokuw8WOqFUvVqsVe/fuFeEHDhyA1UoW1BVFURRFOfaYMXop0c8ssYNrgYPHjjgc5FT03xEWT/jok5lSMtE3Ey5XPUmdmVLSE8PJLYjfJ+8ZE4ebRCTJymYvI8LtZCLYJIpSf5zMj/1ysRHDP2bmZpIezATJrP2sZaTMLlmY+D1EsEl+FzChMfs5wow0Panh/zOxNDPoo0Z5JH+2iYD1gar9DuD3jNWBCaPj82QYbTvWH0k8ZgRZte0A3qf8cZF96lOj09r0PdJ+VQ08mSg/0rajGxBIe0baduzLMZDEdgPIi9hKZAEDpO1YPWzkeWQCdEuFvG7QIQvt2ifjsT7FPuNYPJvUs8NLjHKZYW3l8gWDx270oTNLsSPiwdLjjz8OADAMA/Pnz0di4mFL5EAggI8++kg1S4qiKIqiNDgiHiw98sgjAA7OLM2bNy9syc3hcKBVq1aYN29e7EuoKIqiKEr06G64mBHxYOnnn38GAPTq1QtLly5FWlpanRVKURRFUZRaooOlmBG1Zmn16tV1UY4GgcMNWCtpQyxe2cuCDmLQ5mHr3uH/+xNkOmoYSfCRtHY30R2RAyDZOj3TSNhLiS6KrPuzwzJtpcTMkWi72No5PeiXnIvJjCpZ3QwiYKCHHzP9BzmAlOlfGI7C8P+p/onADPCYEaYR4aG0loBsZNZ/2P1h/YIdIku1H6Tt7CRepDor2veYNo6YHrJ2oQciExkPa2cwvWGVulGNFUtH+pM3NbJ4VBtJDDNp3yOJg27pyGhn/YII91gfZbo6avpIDsoOkM9VpgNjOk+mO2L6KdYHHMWR6Twra970IN36SUSDpdGjR2P69OlISEjA6NGjq4378MMPx6RgiqIoiqLUHBV4x46IBksbN26Ez3dw2P/VV1+FmVIqiqIoinICostwMSOiwVLlpbc1a9bUVVkURVEURVFOOKI2pfzb3/6GkhIpEnC73fjb3/4Wk0IpiqIoilI7DNOMyUupgcB70aJFmDVrFpKSwtXA5eXlePHFF7FgwYKYFa6+YfWYsFbqWEwEa8+XClAmTrRWEYcbRNnKxK5MOMnKYa0gBofEZI6ZXHpSIluGZafGx+2TYewaTATMhPABZ2SCeSaqZOJRJjKl7RehiJoZNXoi2EjKTo137ZPKW3ZCvK2cnN5OBP3+uMjajk3Dm9bINhywTQ422naRCXS9KTKMwYS8rjwi2iV1Y8JyW0WE7UfiUUPLKreS9TEmNI9UGB1x25FHmT17zlz5VcHarupGBYBvuKBmk+zZI32KmYHS5zHCZ9niIX2PiOs9jSMz961qOAoAptWkf9c5ugwXMyIeLBUXF8M0TZimiZKSErhch78FAoEA3nnnHWRmZtZJIRVFURRFUY4XEQ+WUlNTYRgGDMPAqaeeKt43DAP33XdfTAunKIqiKErN0N1wsSPiwdLq1athmiYuvvhivPHGG2jUqFHoPYfDgZYtW6Jp06Z1UkhFURRFUaJEl+FiRsSDpYsuugjAQSfv5s2bw2KJWhuuKIqiKMoxQmeWYkfUAu+WLVsCAMrKyvDrr7/C6w1XzJ1xxhmxKVk9xOINF3gzUWjQJsV/jiJiBVwVsiPBmS/VimVNpKLYm0gEh2SwG6lLMQtjAmJbmcww4JIiZeZUzMTSQbush7NIXsO0MAtdcir5bpm2tIksH3Oh5u7kMoy6ZLPT6qs4LjPBKhOGB6hIPTIhvLNQNjJ1yCabZp0FUj3rbiIL42N9j7Qdcw6HN7K0jhLS94jIPWiX9fATAb7FT9qPbMJwFpIbzk6wJ20alx+e1p1N+h15Llhe9Bll4mbSp+hGCtJn2TPKwlhZ6D1jzuGk7SL9rClPJ8777Lklz57BPn7psyyvwdqZ5Rd2ckGF+hTWR6IeLO3btw833XQT/vvf/9L3AwHm968oiqIoyjFFl+FiRtRraXfeeScKCwvx2WefIS4uDu+++y4WLVqEU045BW+99VZdlFFRFEVRlCg5tAxX25dSg5mlVatW4c0338S5554Li8WCli1b4tJLL0VycjJmzpyJ/v3710U5FUVRFEVRjgtRD5bcbnfITyktLQ379u3Dqaeeik6dOuGrr76KeQHrE7YKE7ZK2ouqxpIAYPjlYri1IoKlS3YeHwmzlZPFdmZoSe68NyEy40sW5otnJ4ETrUthZHoaO9GcGETXwnRhJvkpxDRaQWKsSM3tyC+rINFh+JJkGNWwsLavktYSJ+PYic6DmgqSNrH4WL+LTHPD+x65LrtnkbZdhNompmthaVmfchSxvhKZuaYRkG3F+55MyzR0VePV1MwSALyJMozB0jJdDzNSZean7HOAaaAY7Plm+fnJfWQwbRMrC332iBaQlSVoJ59d8cyxVZa5siGqQT5j6gxdhosZUS/DnXbaadi6dSsA4Mwzz8QzzzyDXbt2Yd68eWjSpEnMC6goiqIoSs3QJbjYEPXM0siRI7Fnzx4AwJQpU9CvXz8sXrwYDocDL7zwQqzLpyiKoiiKclyJerB0ww03hP7u3LkzfvnlF2zZsgUtWrRAenp6TAunKIqiKEoNMU1qOxN1Hkr0g6WqxMfH45xzzolFWRRFURRFiRFqShk7IhosjR49OuIMH3744RoXpr7jKPLDZjusNDTIiNxaTpSIRLhsVPWrIkLUoI0IqIlRpSVR3uaAS6ZlJpLsdHkqYiXxmMg2SEwUmRCTlYWZBTIDRmYOycrHyuIqkGJ7b5Jsq4CLiMP3s+tGGFYlOyayZSe1O4uJ6N0t62D1yEZhomWDtDETKDNzVdcB6dDnS5KVDThle9rLmIGrCOLPAWlP2vdIme0R9j0r6WfsuWV9lIuFw8viIgaX3kTS7xwyrzjW75galT23pD2Z2SQV9LtJGBOqB8nnIDG+5DMYkbUBE+97U0jdSLs480lRSDzWp8LMJv8PX3L1Gx0a8uBj5syZWLp0KbZs2YK4uDh0794ds2fPxmmnnRaKs337dowdOxZr166Fx+NBv3798MQTTyArKyssr//3//4fpk2bhq+//houlwsXXXQR/vOf/xzjGh0mosHSxo0bI8rMYLtmFEVRFEU59hzj3XAffvghcnJycN5558Hv9+Puu+9Gnz598N133yEhIQFutxt9+vTBmWeeiVWrVgEAJk+ejIEDB2L9+vWhY9TeeOMN3HLLLZgxYwYuvvhi+P1+bN68uZYVqR0RDZZWr15d1+VQFEVRFCWGGEE+0x5tHpHy7rvvhv3/wgsvIDMzE19++SUuvPBCfPLJJ9ixYwc2btyI5ORkAMCiRYuQlpaGVatWoXfv3vD7/Rg5ciTmzJmDYcOGhfLq0KFD7SpSS/Q0XEVRFEVpiJgxegEoLi4Oe3k8RzeMKio6aNDVqFEjAIDH44FhGHA6naE4LpcLFosFa9euBQB89dVX2LVrFywWC84++2w0adIEl1122XGfWdLBkqIoiqIo1dK8eXOkpKSEXjNnzqw2fjAYxJ133okePXrg9NNPBwB07doVCQkJGD9+PMrKyuB2uzF27FgEAoGQJdFPP/0EAJg6dSruueceLF++HGlpaejZsyfy84nA7BhR691wx4pBgwZh06ZN2Lt3L9LS0tC7d2/Mnj0bTZs2BQDs2LEDrVu3FunWrVuHrl27HjHfX3/9FcOHD8fq1auRmJiIIUOGYObMmbDZom8aa4Uf1soCbyKgpU7S8VKhaisNT2stJ8dbs5OxPTKe4ZdKZkuFFJobxVLt6m3RSIRZPVJA7E+U12BiYV+ybFcmvLUSJ/IgOfndz9quTJbPRtyqmXDZQoTQ1Cl9v7yGvUiqVktbSCtu5pwtBPdE7MraKS6flKNU3tsgcVMPxMl7YSuV/YdtSmAiVYuHxAvIa7D+Yy2Ufa+8ZSpJK9uO9QG2dOCPZ3b0MshOBPK8/WSYQdLaPEz0ER7G+h0VRpO+Yy+Qv/DLmkmVNms7ttED5PuIbXJgGz0cJaTt7KTtiFjaRkT+VtJ2BjnwgPXHQDkR9JfIiGyTRGkTsnmGuJgH2IYVN/k8q/RYWZi4vY6I5W64nTt3hpbOAITNDjFycnKwefPm0IwRAGRkZGDJkiUYPnw4Hn/8cVgsFlx77bU455xzQnqlYPBgP500aRKuvPJKAMDChQvRrFkzLFmyBLfddlvtKlRD6s1gqVevXrj77rvRpEkT7Nq1C2PHjsVVV12FTz/9NCze+++/j44dO4b+b9y48RHzDAQC6N+/P7Kzs/Hpp59iz549GDx4MOx2O2bMmFFndVEURVGUOieGPkvJyclhg6Xq+Mc//oHly5fjo48+QrNmzcLe69OnD7Zv3479+/fDZrMhNTUV2dnZaNOmDQCETgKprFFyOp1o06YNfv3119rVpRbUm8HSqFGjQn+3bNkSEyZMwBVXXAGfzwe7/fDwvnHjxsjOzo4ozxUrVuC7777D+++/j6ysLJx11lmYPn06xo8fj6lTp8LhIHtUFUVRFEURmKaJESNGYNmyZVizZg1d7TnEIRPrVatWYe/evRg0aBCAg2bXTqcTW7duxQUXXAAA8Pl82LFjB1q2bFn3lTgC9VKzlJ+fj8WLF6N79+5hAyXg4HJdZmYmLrjgArz11lvV5rNu3Tp06tQpzN+hb9++KC4uxrfffnvEdB6PR4jdFEVRFOVEorbnwkW7jJeTk4N//etfePnll5GUlITc3Fzk5uaivLw8FGfhwoVYv349tm/fjn/961+4+uqrMWrUqJAXU3JyMv7+979jypQpWLFiBbZu3Yrhw4cDAK6++uqYtk801JuZJQAYP348nnzySZSVlaFr165Yvnx56L3ExET885//RI8ePWCxWPDGG2/giiuuwH/+85/QiLUqubm5wgjr0P+5ublHLMfMmTNx3333iXCr2wsrMT+sTDBOLnLb88kx51WnTg05y2V4iTbFKfO3Fsv8A8nS9dBKTAUde0tFmDc7SYQxrYvFLbUUAadMawTlmJ3pK0y71KY4C+V1mRYpQO4LMxBkOhR7iWxnX6Isi4PoZFz7Zfkq0sk9qqJFsRHNlieN6H+IPstSLkURQZvUFzhYv2MQzRbT4wWdRANVQvpAoiyL1S/r4cyTOqaKJgnyGm55f6xl5NmwS/2YwYwliaYqSPqPM58YzJLH38+0cVWuy7RD9mKZv58YzBpBeS9c+2W7V2SQdicaKBbmi5efPxamqSIaI2b+6iiWbUyNNEmDsi9vbwJpv3KimYxnn88ynqtQhnmS2WeIzI0ZrFakHU4bOJZ2hMfYZ2nu3LkAgJ49e4aFL1y4EEOHDgUAbN26FRMnTkR+fj5atWqFSZMmha0cAcCcOXNgs9lw4403ory8HF26dMGqVauQlpZWm5rUiuM6szRhwgQYhlHta8uWLaH448aNw8aNG7FixQpYrVYMHjwY5v8NKtLT0zF69Gh06dIF5513HmbNmoUbbrgBc+bMiXm5J06ciKKiotBr586dMb+GoiiKotQnTNOkr0MDJQCYNWsWcnNz4fV68cMPP2D06NHC0Nput+Ohhx5CXl4eiouLsXLlyjAt8vHguM4sjRkzJqwRGYdEX8DBAVF6ejpOPfVUtG/fHs2bN8f69evRrVs3mrZLly5YuXLlEfPOzs7Ghg0bwsLy8vJC7x0Jp9N51J0AiqIoinI80bPhYsdxHSxlZGQgIyOjRmkPbS+szhhr06ZNIWU9o1u3bnjggQewd+9eZGZmAgBWrlyJ5OTk4+4WqiiKoii1Ioa74X7v1AvN0meffYbPP/8cF1xwAdLS0rB9+3ZMnjwZJ598cmhWadGiRXA4HDj77LMBAEuXLsWCBQswf/78UD7Lli3DxIkTQ0t7ffr0QYcOHXDjjTfiwQcfRG5uLu655x7k5OTozJGiKIqiKADqyWApPj4eS5cuxZQpU+B2u9GkSRP069cP99xzT9igZvr06fjll19gs9nQrl07vPbaa7jqqqtC7xcVFWHr1q2h/61WK5YvX47hw4ejW7duSEhIwJAhQzBt2rSaFdQfBMzD4kiTiLkNIh41/BEcvlNBnMxIMqu3XAYWyt161n3EeS5BCmBRLkXA1jIpDg/Ek7r6iPkgE24Tka3JjCqJ8JS1ATPzs1jIryPyi8lOJirtJbLtnQeIwR8xeWQGkcxEMeAKr6/pi6z+zDCSCeGZESSIMJganYKoWElaGzFONYrkBgHL3kKZX5zsU5YyeTPsbvkjxh8v293ii0y4bGHPHhFk28rJc0tE7tTAtIK0fdVLkvtjKyL130+E63FEuE36hbVcPqPUWJM8j1YveaZ85LklKlhmCAvyjLK2C0b4DeUoJf2xghhQFskwv5OIw0l+vjj5XJkyCCaph919+O/6akr5e6deDJY6deoUOqH4SAwZMgRDhgypNs7QoUOFRqply5Z45513altERVEURTmxOMa74Roy9WKwpCiKoihKdOjMUuyol6aUiqIoiqIoxwqdWYohRn4hDMth8zYjXh5myfQQsJKF76rxLCTOnjwR5D+thQgLZkkjSMdvBRGVI5gktSRBBzFk/K1QhJnEpNDBjCpTSTsRmBaAHXDK08p4rlxpeljaVp59VJYltR7xeeRgY3JrmdkgO0Q0bl94fgFy+KiLmBRay6QAgpmVsraDjbQda2MSZs2VmjfvaU1FWCBbmki6dhLHe1KWQILU4gScsu+5dsn8TIfse043Met0EZNHotlh+jamDWOGqEFWliplLj1Vmu2VZ8r6x+fJ54dd00/0NawvuvbJ/ILM/LWAmXxGpu1iyzgBF/k8Y9JN0veqPisAUNhWmmYGyGlVroLIdFZB1h/Jnh+WH7tuZa2Un+jp6oygyfVh0eah6GBJURRFURokqlmKGboMpyiKoiiKUg06s6QoiqIoDRADMRB4x6Qk9R8dLCmKoihKQ0QdvGOGDpZiSEWn5rDZDguimTEcO/nbm0RWQ6v0Txs5QdvWUoqRbW5yYjoRYgZTpfDWQsTC7CR5KxHK+rJlWUqbS3G4lRiylTSX9U/5SbZdWYYsiy9R5sewSW9NlGWlkPLJdma/zILEyM5CDDcDRIDuKJL3yJMaLiIvPUmms1YQU0GXbOO0LbKRmUjdlxDZie6077WS/YeZD5pWIj5OJ32PPCv+JFlm9kyVNyN97ySSlpgolmXK8qVuk/enLFMKkn1sXwLT0ZO+Z22RXqVsMo5J8vKkkXp5ZL28qbK8zGiRPaPuLPJ5RILKmsjrpn0vn9HyxrIi3lSZH2s7C2mX4lZSQc1E2gbRmlcQwbhBPFd9skvBJveDoPAUmZ8nXV7YeeDw/QhUqPqlPqKDJUVRFEVpgKjPUuzQwZKiKIqiNER0N1zM0PlARVEURVGUatCZJUVRFEVpgBimCaOWAu3apm8o6GAphhS1dsDqOCw+9CUQISI7pZrchaousPZSKST0EWG4L0WGBZOY0pEoo4PyGgk7jy4+BwAnMWVmAtjS1uTkd3I6eNAmG4WdQB6UelcaZi+VYf6mTHhKHH5TpWDa9MgbaQRlW8X/Qk51J/HsJeH/Mxfg4raROf96UmrT74iYu5z0PdJ9AsnklPcUqW72lpMbBFlm5w7SCKYMq9p2AOAnfa+ijVQLmz55L7wpsmFY+wVJWwXtMsxaQUTuCeH30kiWZUtr5BZhheXERpoQ+FmK6I2ArJddXgL+OJJhWxkxwSWfi32ppGOwQwvipKraZpefU/6AvD9xibJPZSTIB/zMtN0iLK9CnmbAWP9rKxFWVkH6Bek/tnhZt4RWh9XhgTLpml5nBMGd0aPNQ9HBkqIoiqI0RHRmKXaoZklRFEVRFKUadGZJURRFURoiuhsuZuhgKYZ4UgBrJUkBM1TzSykBjWetsqwdkN5xFIuHCASI2IcZsdndRFtBtB8WktbdhMQj9WIPnpWU2SDr5KwNqrbTkcIiNa2zlRLNl0fqZCx+cuI6Ma1jWhfWBp4qh86zNmbpDFIO5oviS5CBFi87NV6GsTqwtrOUy4heJoBhbecmp7y7iEEoSVuRGVndGAaJx/qeL5lo7Vj7kXowHVPV/hMsk8/oAa90RmT1t7jJDaKf7LIcVfsdwOvFWrOsXD4Xhodo9FLkB0GQaP48bqllM+yy3YuIGNLnl/ntLZX6KRavooxo41iF2WeXi5ipknuZ7z2slQpSzV4doQ7eMUOX4RRFURRFUapBZ5YURVEUpQGiDt6xQwdLiqIoitIQ0WW4mKHLcIqiKIqiKNWgM0sxxAiEC18DRNvKxMdMLFtVk81Ep+xUcoaNCLeZ4JmFWaTvHC2vg5jbMUG2o4AIeYnPXqRibiZUp4Jk1n5M9E1+RNnKSEOTIHY/rKz9SJmtVdrPz9qukBgopsqK+eOJCNhHwkg5mPEnbTtmcslOjS+XZTatxPjTRkTQEQr/bcUyHus/lkIprA0kECNEIoanQvoAua6TpKXPd5V4rIux0+lZuzMBOTHCZOW1lcv8mCGqt1gGJmfIh74kUbax6Sd9gJTFcJKGIs+jnRha2m0ybblHlsVqkR3IRq7rKyebYki/DTJROsmvchuYpC/VFUaQPzPR5qHoYElRFEVRGia6DBczdBlOURRFURSlGnRmSVEURVEaImpKGTN0sKQoiqIoDRA9Gy526GAphlh8gKXSwqadODqz09ptRBxdVVTnI87fVqb/ZO67zG2ZCI+ZIJ3FszCBNzn53UeeMW+KDGP1dxaQtKTtHPKwce7AzNpPHl5Ooe1H3MmpqJiI0onGFI7i8MYygvI+etIjO9HeQdrOJ82gYWNtR+4Zc51nruusLOxeMPdzJmhnAnTW7hH3vQx5I5njtKNAls+bJjO0k/ZjKnfmgm9Wua5B+iLrd1RUTpzOWRuzZ9lRLMN8STIsSETVHp/8+rDkS8FzsJG8sLUkMhfrQJK8rq9CXrfYK5XvQR8RlhOxuTOZ7RyRQUEi+raWyuuSW1Qlo2Mn8FbNUuxQzZKiKIqiKEo16MySoiiKojRETAC13fqvE0sAdLCkKIqiKA0S1SzFDh0sxZCAC0Blg0Vm/MiMC4kOo+ph7Xai6yHL9JGf40PKYSfaDxvT9ZBrsHo5C2VEf5yMyIwQmVElKzPTsLCD7ln7RWrqGSlMO8N0UUaQNGCVsjiLZBxvIdExES0N006xtouk3wGAnehaguS0+kj7HjMDZdoZKzFMjDi/IhnmOyA7mi9FCoNY+1HDzUjbj/QLs4afvKwcjiKiH2Ntx57bCNvOmycbxWgpRVvBuMimMZi+zZ9ADCOLZEMF7DKeGYjMYdbikPfbe0DeNGaIamFGtMQQ1FZI9FOVzUqJUaty4qODJUVRFEVpiJiIgcA7JiWp9+hgSVEURVEaIrobLmbofKCiKIqiKEo16GBJURRFURoiwRi9ImTmzJk477zzkJSUhMzMTFxxxRXYunVrWJzt27fjT3/6EzIyMpCcnIy//OUvyMvLC4vTqlUrGIYR9po1a1YNGiB21JtluEGDBmHTpk3Yu3cv0tLS0Lt3b8yePRtNmzYFAEydOhX33XefSBcfHw+3m6h7/w/DkKq9V155BX/961+jLqPVE34oODvRm4lCucgyfOrTlyDLyUwv/UQYHb+XnPLOxOdWeQ0mKLWXE/FxEjHLI6riIDnRnD2MNlI3ZqrH6sHE0az9Ij1xPX5fhO0XYRhtv8TwiCYRpzLROxNVM7PEQIT9jomRmWiZ3R8mjI7Pk2FBsjGBboYgYczA1EsMN5nOIhAf2c4EbhJLng1SD9Z+rF2s5eH5sXsbcdsx4TF7blnbEZNYZiQaSJLCaBtpE2uJvGmBgPyaCTqIwWqZTEsF42XkaytemlfadstGNW0RPssknr1YRvSmMedQ0lcqCcFN/7Fb1jrWu+E+/PBD5OTk4LzzzoPf78fdd9+NPn364LvvvkNCQgLcbjf69OmDM888E6tWrQIATJ48GQMHDsT69ethqeTqPG3aNNxyyy2h/5OSiFvqMaTeDJZ69eqFu+++G02aNMGuXbswduxYXHXVVfj0008BAGPHjsXf//73sDSXXHIJzjvvvKPmvXDhQvTr1y/0f2pqakzLriiKoijHnGOsWXr33XfD/n/hhReQmZmJL7/8EhdeeCE++eQT7NixAxs3bkRy8sFfOYsWLUJaWhpWrVqF3r17h9ImJSUhOzu7dmWPIfVmGW7UqFHo2rUrWrZsie7du2PChAlYv349fL6DP5kTExORnZ0deuXl5eG7777DsGHDjpp3ampqWFqXi+29VhRFUZTfJ8XFxWEvj4ccE1OFoqKDPhSNGjUCAHg8HhiGAafz8Kyfy+WCxWLB2rVrw9LOmjULjRs3xtlnn405c+bA7yfnHx1D6s1gqTL5+flYvHgxunfvDrudnzE0f/58nHrqqfjDH/5w1PxycnKQnp6O888/HwsWLIB5lJG0x+MRHUdRFEVRTigOzSzV9gWgefPmSElJCb1mzpxZ7aWDwSDuvPNO9OjRA6effjoAoGvXrkhISMD48eNRVlYGt9uNsWPHIhAIYM+ePaG0d9xxB1599VWsXr0at912G2bMmIG77rqr7topAurNMhwAjB8/Hk8++STKysrQtWtXLF++nMarqKjA4sWLMWHChKPmOW3aNFx88cWIj4/HihUrcPvtt6O0tBR33HHHEdPMnDmT6qPs7nCjP6uX6E7IKYs2DzsIM/x/dgBvpAfBcr0T0fWQAz8jNQa0l0amBWCHSDKNjY3oeph5pZXomFi7U81SBRsUy3iRtp+X6qIim8K2u8O1GUw/xrQkNjfRjbBzQUla1nYG+fHGDoKNvO/JMKZ38hI5AovH9DnsMGWq7SG3wlYqOyltF5I20kOmWftVrRu7P5GkAyI/nDpSI1qmxWL195ZITZCDHOQddrr4oSBm+kj6XoD1PTfRRRGXz0A8Mbkk99ubQfROxaQRSBs48kk88rkXdByur+Grnwfp7ty5M7R0BiBsdoiRk5ODzZs3h80YZWRkYMmSJRg+fDgef/xxWCwWXHvttTjnnHPC9EqjR48O/X3GGWfA4XDgtttuw8yZM4963briuM4sTZgwQSjeq762bNkSij9u3Dhs3LgRK1asgNVqxeDBg+ks0LJly1BSUoIhQ4YctQyTJ09Gjx49cPbZZ2P8+PG46667MGfOnGrTTJw4EUVFRaHXzp07o6+8oiiKotQTkpOTw17VDVr+8Y9/YPny5Vi9ejWaNWsW9l6fPn2wfft27N27F/v378dLL72EXbt2oU2bNkfMr0uXLvD7/dixY0esqhM1x3VmacyYMRg6dGi1cSo3YHp6OtLT03Hqqaeiffv2aN68OdavX49u3bqFpZk/fz4GDBiArKysqMvUpUsXTJ8+HR6P54idwel0HrfRraIoiqJERBB0RjHqPCLENE2MGDECy5Ytw5o1a9C6desjxk1PTwcArFq1Cnv37sWgQYOOGHfTpk2wWCzIzMyMvDAx5rgOljIyMpCRkVGjtMHgwTtYVWT2888/Y/Xq1XjrrbdqlO+mTZuQlpamgyFFURSlXnOsrQNycnLw8ssv480330RSUhJyc3MBACkpKYiLO+hBsnDhQrRv3x4ZGRlYt24dRo4ciVGjRuG0004DAKxbtw6fffYZevXqhaSkJKxbtw6jRo3CDTfcgLQ0cijlMaJeaJY+++wzfP7557jggguQlpaG7du3Y/LkyTj55JPFrNKCBQvQpEkTXHbZZSKfZcuWYeLEiaGlvbfffht5eXno2rUrXC4XVq5ciRkzZmDs2LHHpF6KoiiK0lCYO3cuAKBnz55h4QsXLgytIm3duhUTJ05Efn4+WrVqhUmTJmHUqFGhuE6nE6+++iqmTp0Kj8eD1q1bY9SoUWE6puNBvRgsxcfHY+nSpZgyZQrcbjeaNGmCfv364Z577gmbAQoGg3jhhRcwdOhQWK1SeFdUVBTmJmq32/HUU09h1KhRME0Tbdu2xcMPPxxmhBUNVq8JayUVIBMauwrlnGbATkS63vB4RpAYthERMBP3snJYqaicCCeJSaMnJbJ5XSYCjtsXWfmY+NpeFmHbeci8MfMjJNpM2n6krareH+BI7SfL50lhLnhHv2bcXpmMmXwyUbk9X4b5nazfyXis7xE97RHE9iSM9j1iakomdz2pMowKt0nfc+0jonkiKmbmjVbSHwMu1vdI+5G6Ve17rJ2YgJw9FxYiqqbPbaoMYzCzVsfeyIwlmWDcXhSZOS3fmEA+98gGaMMvH2ba95hRsF/WzU8MTL3pzICS5EfMNcPiHUN997H2WTraTnLgoCVAdW7c55xzDtavXx/xNY8V9WKw1KlTp5DbZ3VYLJZqxdZDhw4N00j169cvzIxSURRFURoMQZNvZYw2D6V++iwpiqIoiqIcK+rFzJKiKIqiKFFyjJfhGjI6WFIURVGUBkkMBktMFPg7RAdLMcTqNWGr1DGZ2JM5CzuLanbmjWu/VDC6T5Ln2jEHatMSmUM0c9VlYczBmwmyK9IiFapLMSVtu0KfDGSQ591ZIBWlZU3iRJgvgQicrTKMiYWJeTGN5ygNbyvWdmUZsgH8TGRMmoQJzZ1F5IZT8amM58qX98fdRH6ceBNr0fdIPSykDzBBNnPFZ23AhMYWX2RpnWSzRqTi3art586Wbccc9Vnb0WeUaJGZgJqJuVk8H3FY95NTBZhrv0kE2Q5yQhRLywTZ8XtkWBk5b9WXSE4VYM74pK2YaN60Ebf3cnI/2PNXaTOFUXEM1S86sxQzVLOkKIqiKIpSDTqzpCiKoigNkaCJWi+j6W44ADpYUhRFUZSGiRk8+KptHooOlmKJtcKENVBJs0S0DxZiZmitIIvmVWBaBbbGbyuX+VNjN3LnmbaJ6YnYdX3xJK1dRmQ6D3880QIwI0iiY7JE0HYAYDUiE5PYymR+zKaE6ae4tolchBSlavsF7TKhsygyLQ0zULT4ifEn6StUc2KQepE6sHtGfAtpm/iotinStDKMGUYynQzT4jBDSyNITrAn7cxgbYUq/ZG1HU1I2sRL6kDLQfusDPNL2SPsRZGlZfoxBtMiMaNT1geY4SbVUZYw3ZGM50uO7D4G7bIPBIlxKjMhde47XJEA0YQpJz46WFIURVGUhogKvGOGDpYURVEUpSGimqWYobvhFEVRFEVRqkFnlhRFURSlIaLLcDFDB0sxxFnkg81WSUVJ+pi1XDqWGQES0R8uJmRaT2aS5jwg1YP+ROkK54+Tae1l8hpBW2TCaBaPiY8D5KR7u5uIZ92ynazlUsVp+IjAO8BE39JskhlLOvJl+wUSZPsFXFItayNGkqa9Zu1H244IW+1lxAzULetvJRsLDCL6NgLMHVJeOEjK5zog748vUbZTwCXbnYmlqcA7wjBm1skEzjbS59l9ZJs1WPtZ/Ew0Lz9mq97vOGLy6U0ibUf6QBwRDNPPC7JJhG42IMJt1nb2UrK5gAi32QYJtuHAIMJ6usGEfGs5IhSg+5mx7QFyDfp5KxOzeP4EUjeT/13nmIjBYCkmJan36DKcoiiKoihKNejMkqIoiqI0RHQZLmboYElRFEVRGiLBINjZjtHnoehgKYZYKgKw2A5rD5iRXVUzOgAIxMvbYHWHH5JrrSCua0xeUiEP12U6FGcu0U4VS0c5b8t0WTZiDsl0UUzTYRJtk61UlsVCtF0mMWoMxsnrWogGiuVnkF9MRrlsP4tXCkUcXnI/iktFkL9FJslPpg0khF+D6dj8pJ/Qw0eJUWfQQfQvxAzU5iZmoMSok3ltsj7KDsi17pUiG1uRFKyUtUwm15AZBoj+juksmE6PaWfspaT9iPaMaa8M0n5MAyXKQTRlVPNI6m8vJgdCN5Wn8DLdlZ9oCF358roVafKOW4nGiGnPmP6OGeDaiP6OHfQbJAfzssNrWTxnAQkrlm1aehLpK/KjgZr7OgurP6zXcixNKXVmKWaoZklRFEVRFKUadGZJURRFURoiOrMUM3SwpCiKoigNEXXwjhm6DKcoiqIoilINOrMUQ6xlXliJiVplgvFSLGwrIM54Vac+DZnOIEJh0ylVjdYiqZIMJEmTRqtfClsde6Vo2ZstjzmnIm03MchMk8JTVg+jTKY1E+Rx6NZidnw5+SUUR0SXrP1cRKheKq9hJsr2M3yyDWx7pVuer2mqCLOWhtfXUibVpKZVtjszGmRCa2rASe4ZI0hEwGzTANuoYC+R9WCbAdiOG9de2e4VWbLdbUyAXk5E2lnyiHgmmObtJ8vsKCCKXwIzMK0qfA/Eyzj2ElkOf6JsY4MYYboOyLJVpJPPnnJWfxnmS5T9h/U9C/GD9ZOf5M4i+YwGya4BZobJNg34iQGlvYTEkx8/MN2yHs5CWT5PMqkv2edhJY9VRdrhvwPHcIrCNIMwzdrtZqtt+oaCDpYURVEUpSFimrVfRlPNEgBdhlMURVEURakWnVlSFEVRlIaIGQOBt84sAdDBkqIoiqI0TIJBLvKKBtUsAdDBUmzxB8M6lknE3AZzOSYCTVQV0AaJMzdzoGbO0oXFIsiy74CMl0hUkuXSptdaJoXWAeKkzcpiLSNC8FIi5rYTISurG3NJJ+JjJhhnv5gMHxH35hfKtHv3y7AEoh6tkNet6s4OAMG4Kg7ePqmUtZST+hNM4tbNXNdZv2N9isHiWbxEaE02F1j3y3hmnHxWmOu6rUzG88cRAbUvMuGyjQjBTZtUJzBXdAu5BnPoB3PnrpoXaTtbkew79gNEuO5ibUeevQr5TAWckbmaW4j7t52IuZlI206cuS3Eod4IyrYzraQ/mjKeo5i4fxM3cVcBcRgnTuyOEuJ27iLlI0IWg7SLvdI+GeYErpz46GBJURRFURoiugwXM3SwpCiKoigNEDMYhFnLZTi1DjiIDpYURVEUpSGiM0sx4/+3d+dRUVzZH8C/3SINDbIICChb1MjihsvRQYnLGZVoVMwk45gYgQzBwai4ZVB+MSaiiPsSJ8Yt7jguGRlNRAVHXIJojKO4EVwiYBLARBGMjkB3398fhg5FPZo2gnTj/ZzDOVbVq1d1q/rJo+r2e9xZqkOKkvtQVJlSWlEmz+0R5jQoRbOmV/uACvIo6Ici2Tqtr5dsnc5NPnu75feC6bcF56YTDARJFvLEBMsf5YMvisopSgQjxQniF+bOiK6dYLBFIQt5ThX9UChbp/N7QV6uhb28uu8FOUuCQfqomTyPiZrKr4vFD9VyyCzkTbNJsfzakYOt/DweCa6T4NqR6HMnupxKwbn8IJ+a/qG/m2ydzl0ev/UPgkFYBcfVWglybJrKC1oXyOvTCa6x6qE8/w6CQWRF+WIiotwm0TUlwTFUP0jzCO/7N5eVedhSPoimukCQ8CK43RrBQJii/CSrnwX5goK4VPfk10QjGEhTmMcloBPcR1IK2rwgT8jmtjwfq+QF+WflYQvBdRf9tyc4rM5C0F4Evy0tRYNrNpXvWzVXSlvOnQ9zxJ0lxhhjrDHSkbg3+CT4yRIA7iwxxhhjjRMRgKcdOoA7SwCP4M0YY4wxZhA/WWKMMcYaIdIR6ClfwxE/WQJghp2lsrIy9OzZE1lZWTh37hwCAwP12y5cuIDx48fjzJkzcHFxwcSJExEbG2uwvvz8fIwbNw7p6emwtbVFeHg4EhMTYSFIsK1VEyWgrJL0KBjQEdbGJUxXf+YnSrpUWgtmYP+uQF6XlTxRVDTQIpXJkz2VLs7ydd/Ly+n+Jx98UCkY5JIeyssp3F3l5e7IE4gVasGgj00FM9iLkpkFCb8Ktfz6Kb/7Xl7OSn7PdHfkmaK6Mvn9tmjhIj9GvrycttpnRXTtoJEntupaOcnWNbnzi2wdiRL1BQnUopnkhcm4tvJrp869J99XJb8/ypIHsnUolycuK5uLvpggGFy0TLCv4N6KlHk5yI9RKL8/Omt5G9KpBNdPkMytE7Rdra30ftjkypP3qw9UCgBN7svPTTj4q4O8rSh/EexbJvhMCT4ryjL5fXzgJj+GTYH8F2uFrbztaaxFA1DKVgmTpctt5ddTXSR/1aRVyfdt+kA0GKZgAEpr+TGaPhC8zhJ0JET7Vj0XUZz1hnR4+tdwPHQAYIadpdjYWLRs2RJZWVmS9aWlpRg0aBAGDBiA1atX4+LFi/jrX/8KBwcHjB07VliXVqvFK6+8Ajc3N5w8eRIFBQUICwtD06ZNMW/evGcRDmOMMcZMnFnlLB04cACpqalYvHixbFtSUhLKy8uxYcMGtG/fHqNGjUJMTAyWLl1aY32pqam4cuUKtm3bhsDAQAwePBhz5szBJ598gnLBX7qMMcaYuSAd1ckPM6POUlFREaKiorB161aoBa9jMjMz0adPH1ha/vboOiQkBDk5OSguFgyu8es+HTt2hKurq2Sf0tJSXL58ue6DYIwxxp4V0tXNDzOP13BEhIiICERHR6N79+7Izc2VlSksLMQLL0gHFKzsBBUWFsLR0VG4T9WOUvV9alJWVoayKvk9JSWPB2TUVJ/sVjTJq2iySMGkktUHXSWtYCJPnSB/Qyea3VJQPcmfnBEJJrkVHkMwEaygPqVOMBCkoJxCKxgYTzRxsGiWTtH4gaKcJcH1UwiOQTrBRMc6+d8Uonh1gusnulaia1B9X6WgDEiQX6KR56GQ4J6RVpBLoxFMIivKWVIK8r0E90wh+BzrBJMaiz9T8mtHomMY+XmE1ri/AzWC66cUHFcnik0jyFkSTPKqbSIYvFErPa5CcJ10gomOhddEK/9caDWCHEcj99UZ+VnRlsuPoRFMRK2pEAyQKcjtEuXyaAVtWSMY+FI0o4dOsK9CMCGwMGdJkGcmmpxZmLMk2LfquWgrHv26a/0/sdGg4qkH8NZA8P/ac6hBO0szZszAggULDJbJzs5Gamoq7t+/j7i4uGd0ZoYlJiZi9uzZsvVHCzY0wNnUsx+fYl/BQM1C8nxkMfEDQtP20+/c756R5c7+zvrNgeC7CnXuxjM4RmP1dUOfgHm7c+cO7O3lswPUBUtLS7i5ueGrwpQ6qc/NzU3y1uZ51KCdpWnTpiEiIsJgmdatW+PIkSPIzMyESiX9Rkr37t0xevRobN68GW5ubigqkk7/Ubns5iafhqFy/ddfS1t8bfsAQFxcHKZOnapfvnfvHry9vZGfn19vH/76VlpaCk9PT9y6dQt2dvJvIZmLxhBHY4gB4DhMSWOIAWgccZSUlMDLywvNm8unuKkrVlZWuHnzZp3l3lpaWsJK8K3g50mDdpZcXFzg4iL/anV1H3/8MebOnatf/vHHHxESEoKdO3eiZ8+eAICgoCC8//77qKioQNNfv06elpYGX19f4Su4yn0SEhJw+/ZttGjRQr+PnZ0dAgICajwflUol67gBgL29vdk24Ep2dnZmHwPQOOJoDDEAHIcpaQwxAI0jDqVobsY6ZGVl9dx3cOqSWSR4e3l5oUOHDvqfdu3aAQDatGkDDw8PAMCbb74JS0tLREZG4vLly9i5cydWrFgheQKUnJwMPz8//fKgQYMQEBCAMWPGICsrC4cOHcLMmTMxfvx4YWeIMcYYY88fs+gsGcPe3h6pqam4efMmunXrhmnTpmHWrFmSMZZKSkqQk5OjX27SpAm+/PJLNGnSBEFBQXjrrbcQFhaG+Pj4hgiBMcYYYybILL4NV52Pj4/wmwSdOnXCiRMnatwvIiJCliPl7e2NlJSnS4JTqVT48MMPzfppVGOIAWgccTSGGACOw5Q0hhiAxhFHY4jheaQgnviFMcYYY6xGjeY1HGOMMcZYfeDOEmOMMcaYAdxZYowxxhgzgDtLjDHGGGMGcGfJCD4+PlAoFJKf+fPnS8pcuHABL730EqysrODp6YmFCxfWWm9+fj5eeeUVqNVqtGjRAn//+9+h0cjnVqprZWVlCAwMhEKhwPnz5/XrP/roI1mcCoUCNjY2BusT7bNjx44GiSE3N1d4PqdOnTJYn6ndi6NHjyI0NBTu7u6wsbFBYGAgkpKSaq3PlO4FYB7tYvjw4fDy8oKVlRXc3d0xZswY/Pjjb/P8mEu7qC0Oc2gbtcVgLu2itjgA82gbrApitfL29qb4+HgqKCjQ//zyyy/67SUlJeTq6kqjR4+mS5cu0T//+U+ytramNWvW1FinRqOhDh060IABA+jcuXOUkpJCzs7OFBcXV+/xxMTE0ODBgwkAnTt3Tr/+/v37khgLCgooICCAwsPDDdYHgDZu3CjZ73//+1+DxHDz5k0CQIcPH5acT3l5eY11meK9SEhIoJkzZ1JGRgZdv36dli9fTkqlkr744guD9ZnSvTCXdrF06VLKzMyk3NxcysjIoKCgIAoKCtJvN5d2UVsc5tA2aovBXNpFbXGYS9tgv+HOkhG8vb1p2bJlNW5ftWoVOTo6UllZmX7d9OnTydfXt8Z9UlJSSKlUUmFhoX7dp59+SnZ2dpJ66lpKSgr5+fnR5cuXZb/cqjt//jwBoOPHjxusEwAlJyfX7YkaYCiGyl8IhuIS1Wfq94KIaMiQIfT2228bLGNK98Kc2kVVe/fuJYVCUWMnwlTbRXXV4zCntlGptntBZJrtorrqcZhr23ie8Ws4I82fPx9OTk7o0qULFi1aJHn0mZmZiT59+khmZQ4JCUFOTg6Ki4uF9WVmZqJjx45wdXWV7FNaWorLly/XSwxFRUWIiorC1q1boVaray2/fv16tGvXDi+99FKtZcePHw9nZ2f06NEDGzZsEA4aWheMjWH48OFo0aIFgoODsW/fPoN1msO9AB6PQG/M5Jumci/MpV1UdffuXSQlJaFXr176OSarM8V2UZ2hOEy9bVQy5l4AptcuqhPFYY5t43nHnSUjxMTEYMeOHUhPT8ff/vY3zJs3D7GxsfrthYWFkg8wAP1yYWGhsM7fs8/TICJEREQgOjoa3bt3r7X8o0ePkJSUhMjIyFrLxsfHY9euXUhLS8Nrr72Gd999FytXrqyL05YwJgZbW1ssWbIEu3fvxv79+xEcHIwRI0YY/KVg6vcCAHbt2oUzZ87g7bffNljOlO6FObSLStOnT4eNjQ2cnJyQn5+PvXv3CsuZYruoylAc5tA2aouhOlNrF1UZisOc2gb7VcM91GpY06dPJwAGf7Kzs4X7fvbZZ2RhYUGPHj0iIqKBAwfS2LFjJWUqX0tcuXJFWEdUVBQNGjRIsu7BgwcEgFJSUuo8jhUrVlDv3r1Jo9EQUe2P5Ldv304WFhaSR77G+uCDD8jDw6PBY6g0ZswYCg4OrnG7qd+LI0eOkFqtps2bNxt9LpUa8l6YQ7uo9NNPP1FOTg6lpqZS7969aciQIaTT6WT1Pst2UZ9xVHoWbaO+YniW7aKu42jItsF+H7OcG64uTJs2TTZPXHWtW7cWru/Zsyc0Gg1yc3Ph6+sLNzc3FBUVScpULru5uQnrcHNzw9dff/1E+4gYG8eRI0eQmZkpm4+oe/fuGD16NDZv3ixZv379egwdOlT2l4wxevbsiTlz5qCsrMyo+Y/qK4aq55OWllZj3aZ8L44dO4Zhw4Zh2bJlCAsLM/pcKjXkvTCHdlHJ2dkZzs7OaNeuHfz9/eHp6YlTp04hKChIss+zbBf1GUfVc6rvtlEfMTzrdlHXcTRk22C/U0P31szRtm3bSKlU0t27d4not2S9qkmIcXFxRiXrFRUV6detWbOG7Ozs9E+s6lJeXh5dvHhR/3Po0CECQJ9//jndunVLUva7774jhUJR6zdMajJ37lxydHSsi9OWeJIYqnrnnXeoS5cuNW431XuRnp5ONjY29I9//ON3H6sh74U5tAuRvLw8AkDp6emS9abaLmpSUxxVmVrbqE4Ugym3i5pUj8Nc28bzjDtLtTh58iQtW7aMzp8/Tzdu3KBt27aRi4sLhYWF6cvcu3ePXF1dacyYMXTp0iXasWMHqdVqyddA9+zZI2kIlV8DHTRoEJ0/f54OHjxILi4uz+xroIZe/cycOZNatmypf8VSVfU49u3bR+vWraOLFy/StWvXaNWqVaRWq2nWrFn1efpEJI5h06ZNtH37dsrOzqbs7GxKSEggpVJJGzZsqDEGU7wXla8Y4uLiJF93vnPnTo1xmNq9MId2cerUKVq5ciWdO3eOcnNz6T//+Q/16tWL2rRpI/sFZMrtwpg4TL1tGBODObQLY+Iwh7bBpLizVIuzZ89Sz549yd7enqysrMjf35/mzZsn+480KyuLgoODSaVSUatWrWj+/PmS7Rs3bqTqD/Jyc3Np8ODBZG1tTc7OzjRt2jSqqKio95iIau4sabVa8vDwoP/7v/8T7lc9jgMHDlBgYCDZ2tqSjY0Nde7cmVavXk1arbY+T5+Iau4s+fv7k1qtJjs7O+rRowft3r3bYAxEpncvwsPDhTkRffv2rTEOU7sXRKbfLi5cuED9+/en5s2bk0qlIh8fH4qOjqbvv/9eUs7U24UxcZh62zAmBnNoF8Z+pky9bTApBdEz+v4kY4wxxpgZ4qEDGGOMMcYM4M4SY4wxxpgB3FlijDHGGDOAO0uMMcYYYwZwZ4kxxhhjzADuLDHGGGOMGcCdJcYYY4wxA7izxBiAfv36YfLkyY3quBERERgxYsRT1eHj4wOFQgGFQoF79+7VWG7Tpk1wcHB4qmOxmkVEROjvw7///e+GPh3GnjvcWWKsAe3Zswdz5szRL/v4+GD58uUNd0IC8fHxKCgogL29fUOfSqN39OhRYcd0xYoVKCgoaJiTYozBoqFPgLHnWfPmzRv6FGrVrFkzk5nVvKKiAk2bNm3o03jm7O3tubPKWAPiJ0uMCRQXFyMsLAyOjo5Qq9UYPHgwrl27pt9e+drp0KFD8Pf3h62tLV5++WXJX/8ajQYxMTFwcHCAk5MTpk+fjvDwcMmrsaqv4fr164e8vDxMmTJF/8oFAD766CMEBgZKzm/58uXw8fHRL2u1WkydOlV/rNjYWFSfyUin0yExMREvvPACrK2t0blzZ3z++ee/6/ps2rQJXl5eUKvVePXVV3Hnzh1Zmb1796Jr166wsrJC69atMXv2bGg0Gv32b7/9FsHBwbCyskJAQAAOHz4sec2Um5sLhUKBnTt3om/fvrCyskJSUhIAYP369fD394eVlRX8/PywatUqybFv3bqFkSNHwsHBAc2bN0doaChyc3P1248ePYoePXrAxsYGDg4O6N27N/Ly8oyKvba4li5dio4dO8LGxgaenp5499138csvv+i35+XlYdiwYXB0dISNjQ3at2+PlJQU5Obmon///gAAR0dHKBQKREREGHVOjLH6xZ0lxgQiIiLwzTffYN++fcjMzAQRYciQIaioqNCXefjwIRYvXoytW7fi+PHjyM/Px3vvvaffvmDBAiQlJWHjxo3IyMhAaWmpwXyTPXv2wMPDQ//a60leuyxZsgSbNm3Chg0b8NVXX+Hu3btITk6WlElMTMSWLVuwevVqXL58GVOmTMFbb72FY8eOGX9hAJw+fRqRkZGYMGECzp8/j/79+2Pu3LmSMidOnEBYWBgmTZqEK1euYM2aNdi0aRMSEhIAPO7cjRgxAmq1GqdPn8batWvx/vvvC483Y8YMTJo0CdnZ2QgJCUFSUhJmzZqFhIQEZGdnY968efjggw+wefNmAI+fPoWEhKBZs2Y4ceIEMjIy9J3Z8vJyaDQajBgxAn379sWFCxeQmZmJsWPH6junhtQWFwAolUp8/PHHuHz5MjZv3owjR44gNjZWv338+PEoKyvD8ePHcfHiRSxYsAC2trbw9PTEv/71LwBATk4OCgoKsGLFiie6N4yxetKw8/gyZhr69u1LkyZNIiKiq1evEgDKyMjQb//555/J2tqadu3aRUS/zQh+/fp1fZlPPvmEXF1d9cuurq60aNEi/bJGoyEvLy8KDQ0VHpeIyNvbm5YtWyY5tw8//JA6d+4sWbds2TLy9vbWL7u7u9PChQv1yxUVFeTh4aE/1qNHj0itVtPJkycl9URGRtIbb7xR43URnc8bb7xBQ4YMkaz7y1/+Qvb29vrlP/7xjzRv3jxJma1bt5K7uzsRPZ4J3sLCggoKCvTb09LSCAAlJycTEdHNmzcJAC1fvlxST5s2bWj79u2SdXPmzKGgoCD9cXx9fUmn0+m3l5WVkbW1NR06dIju3LlDAOjo0aM1xl2T2uIS2b17Nzk5OemXO3bsSB999JGwbHp6OgGg4uJi4faq14cx9uxwzhJj1WRnZ8PCwgI9e/bUr3NycoKvry+ys7P169RqNdq0aaNfdnd3x+3btwEAJSUlKCoqQo8ePfTbmzRpgm7dukGn09Xp+ZaUlKCgoEByvhYWFujevbv+Vdz169fx8OFDDBw4ULJveXk5unTp8kTHy87OxquvvipZFxQUhIMHD+qXs7KykJGRIXniotVq8ejRIzx8+BA5OTnw9PSU5EJVvVZVde/eXf/vBw8e4MaNG4iMjERUVJR+vUaj0ef0ZGVl4fr162jWrJmknkePHuHGjRsYNGgQIiIiEBISgoEDB2LAgAEYOXIk3N3da429trjUajUOHz6MxMREfPvttygtLYVGo5Fsj4mJwbhx45CamooBAwbgtddeQ6dOnWo9NmOs4XBnibHfqXqisUKhkOUJ1QWlUimrt+rrQGNU5szs378frVq1kmxTqVRPd4I1HG/27Nn405/+JNtmZWX1RHXZ2NhI6gWAdevWSTqHwOPOaGWZbt266fObqnJxcQEAbNy4ETExMTh48CB27tyJmTNnIi0tDX/4wx+eKq7c3FwMHToU48aNQ0JCApo3b46vvvoKkZGRKC8vh1qtxjvvvIOQkBDs378fqampSExMxJIlSzBx4sQnui6MsWeHO0uMVePv7w+NRoPTp0+jV69eAIA7d+4gJycHAQEBRtVhb28PV1dXnDlzBn369AHw+AnEf//7X1mydlWWlpbQarWSdS4uLigsLAQR6fNqzp8/LzmWu7s7Tp8+rT+WRqPB2bNn0bVrVwBAQEAAVCoV8vPz0bdvX6NiqIm/vz9Onz4tWXfq1CnJcteuXZGTk4O2bdsK6/D19cWtW7dQVFQEV1dXAMCZM2dqPbarqytatmyJ7777DqNHjxaW6dq1K3bu3IkWLVrAzs6uxrq6dOmCLl26IC4uDkFBQdi+fXutnaXa4jp79ix0Oh2WLFkCpfJxSuiuXbtk5Tw9PREdHY3o6GjExcVh3bp1mDhxIiwtLQFA9hlgjDUs7iwxVs2LL76I0NBQREVFYc2aNWjWrBlmzJiBVq1aITQ01Oh6Jk6ciMTERLRt2xZ+fn5YuXIliouLDSYS+/j44Pjx4xg1ahRUKhWcnZ3Rr18//PTTT1i4cCFef/11HDx4EAcOHJB0BCZNmoT58+fjxRdfhJ+fH5YuXSoZq6dZs2Z47733MGXKFOh0OgQHB6OkpAQZGRmws7NDeHi40XHFxMSgd+/eWLx4MUJDQ3Ho0CHJKzgAmDVrFoYOHQovLy+8/vrrUCqVyMrKwqVLlzB37lwMHDgQbdq0QXh4OBYuXIj79+9j5syZAFBrovXs2bMRExMDe3t7vPzyyygrK8M333yD4uJiTJ06FaNHj8aiRYsQGhqK+Ph4eHh4IC8vD3v27EFsbCwqKiqwdu1aDB8+HC1btkROTg6uXbuGsLCwWmOvLa62bduioqICK1euxLBhw5CRkYHVq1dL6pg8eTIGDx6Mdu3aobi4GOnp6fD39wcAeHt7Q6FQ4Msvv8SQIUNgbW0NW1tbo+8NY6yeNGzKFGOmoXqi9d27d2nMmDFkb29P1tbWFBISQlevXtVv37hxoyShmYgoOTmZqjapiooKmjBhAtnZ2ZGjoyNNnz6d/vznP9OoUaNqPG5mZiZ16tSJVCqVpK5PP/2UPD09ycbGhsLCwighIUGS4F1RUUGTJk0iOzs7cnBwoKlTp1JYWJgkmVyn09Hy5cvJ19eXmjZtSi4uLhQSEkLHjh2r8bqIEryJiD777DPy8PAga2trGjZsGC1evFh2PQ4ePEi9evUia2trsrOzox49etDatWv127Ozs6l3795kaWlJfn5+9MUXXxAAOnjwIBH9luB97tw52fGTkpIoMDCQLC0tydHRkfr06UN79uzRby8oKKCwsDBydnYmlUpFrVu3pqioKCopKaHCwkIaMWIEubu7k6WlJXl7e9OsWbNIq9XWeB2eJK6lS5eSu7u7/nOzZcsWSdL2hAkTqE2bNqRSqcjFxYXGjBlDP//8s37/+Ph4cnNzI4VCQeHh4ZJjgxO8GWsQCqJ6SLJgjMnodDr4+/tj5MiRklG7TZmPjw8mT578TKaCycjIQHBwMK5fvy5JnGe/USgUSE5OfuppbBhjT4bHWWKsnuTl5WHdunW4evUqLl68iHHjxuHmzZt48803G/rUnsj06dNha2uLkpKSOq03OTkZaWlpyM3NxeHDhzF27Fj07t2bO0oC0dHR/DqOsQbET5YYqye3bt3CqFGjcOnSJRAROnTogPnz5+uTsM1BXl6e/pt3rVu31ict14UtW7Zg7ty5yM/Ph7OzMwYMGIAlS5bAycmpzo7xpNq3b1/jSN5r1qypMam8vt2+fRulpaUAHg9RUfUbgoyx+sedJcYY+1XVzmF1rq6usrGbGGPPB+4sMcYYY4wZwDlLjDHGGGMGcGeJMcYYY8wA7iwxxhhjjBnAnSXGGGOMMQO4s8QYY4wxZgB3lhhjjDHGDODOEmOMMcaYAdxZYowxxhgz4P8B1Jti+pO7bCQAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "monthly_subset[\"ts_pred\"].plot()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "65c7de6c-0b13-4cb8-912f-02e8ed953c71",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x76a2cb389d10>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# original target\n",
     "monthly_subset[\"ts\"].where(~lsm_subset[\"lsm\"].values).plot()"
@@ -306,10 +1595,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "ea56d33c-fd54-4353-bd88-06990ed9641c",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x76a2c9a88910>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# Mean Absolute Error\n",
     "target = monthly_subset[\"ts\"].where(~lsm_subset[\"lsm\"].values)\n",
@@ -327,7 +1637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "8367e4a7",
    "metadata": {},
    "outputs": [],
@@ -340,7 +1650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "c2524855",
    "metadata": {},
    "outputs": [],
@@ -354,7 +1664,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "eso4clima-wp1-prototype",
+   "display_name": "ClimaNet",
    "language": "python",
    "name": "python3"
   },
diff --git a/pyproject.toml b/pyproject.toml
index 48b84d2..7c9685a 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,5 +1,9 @@
+[build-system]
+requires = ["setuptools>=68", "wheel"]
+build-backend = "setuptools.build_meta"
+
 [project]
-name = "eso4clima-wp1-prototype"
+name = "ClimaNet"
 version = "0.1.0"
 description = "Machine Learning workflow predicting satellite observations from climate models."
 readme = "README.md"
@@ -27,3 +31,6 @@ docs = [
     "mkdocstrings[python]>=1.0.2",
     "mkdocs-include-markdown-plugin",
 ]
+
+[tool.setuptools]
+packages = ["climanet"]
diff --git a/src/__init__.py b/src/__init__.py
deleted file mode 100644
index e69de29..0000000
diff --git a/tests/test_dataset.py b/tests/test_dataset.py
index c4a7e3e..c9cd895 100644
--- a/tests/test_dataset.py
+++ b/tests/test_dataset.py
@@ -3,7 +3,7 @@
 import torch
 import xarray as xr
 
-from dataset import STDataset
+from climanet import STDataset
 
 
 def _make_datasets():
diff --git a/uv.lock b/uv.lock
index 686d0a5..c46fe83 100644
--- a/uv.lock
+++ b/uv.lock
@@ -3,14 +3,14 @@ revision = 3
 requires-python = ">=3.11"
 resolution-markers = [
     "python_full_version >= '3.14' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version >= '3.12' and python_full_version < '3.14' and platform_machine == 'ARM64' and sys_platform == 'win32'",
+    "python_full_version < '3.12' and platform_machine == 'ARM64' and sys_platform == 'win32'",
     "python_full_version >= '3.14' and platform_machine != 'ARM64' and sys_platform == 'win32'",
     "python_full_version >= '3.14' and sys_platform == 'emscripten'",
     "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
-    "python_full_version >= '3.12' and python_full_version < '3.14' and platform_machine == 'ARM64' and sys_platform == 'win32'",
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     "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
-    "python_full_version < '3.12' and platform_machine == 'ARM64' and sys_platform == 'win32'",
     "python_full_version < '3.12' and platform_machine != 'ARM64' and sys_platform == 'win32'",
     "python_full_version < '3.12' and sys_platform == 'emscripten'",
     "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
@@ -105,11 +105,11 @@ wheels = [
 
 [[package]]
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+    { url = "https://files.pythonhosted.org/packages/13/5c/af990f019b8dd11c5492a6371fe74a5b0276357370030b67254a87329944/async_lru-2.2.0-py3-none-any.whl", hash = "sha256:e2c1cf731eba202b59c5feedaef14ffd9d02ad0037fcda64938699f2c380eafe", size = 7890, upload-time = "2026-02-20T19:11:42.273Z" },
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 [[package]]
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 [[package]]
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+version = "2.18.0"
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 [[package]]
@@ -174,13 +174,22 @@ css = [
     { name = "tinycss2" },
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+[[package]]
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+version = "2.6"
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+wheels = [
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+version = "0.1.0"
+source = { editable = "." }
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+    { name = "einops" },
+    { name = "jupyterlab" },
+    { name = "matplotlib" },
+    { name = "netcdf4" },
+    { name = "torch" },
+    { name = "xarray" },
+]
+
+[package.dev-dependencies]
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+    { name = "pytest" },
+    { name = "ruff" },
+]
+docs = [
+    { name = "mkdocs" },
+    { name = "mkdocs-include-markdown-plugin" },
+    { name = "mkdocs-jupyter" },
+    { name = "mkdocs-material" },
+    { name = "mkdocstrings", extra = ["python"] },
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+    { name = "einops", specifier = ">=0.8.2" },
+    { name = "jupyterlab", specifier = ">=4.5.3" },
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+    { name = "torch", specifier = ">=2.10.0" },
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+    { name = "pytest", specifier = ">=9.0.2" },
+    { name = "ruff", specifier = ">=0.14.14" },
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+    { name = "mkdocs-include-markdown-plugin" },
+    { name = "mkdocs-jupyter", specifier = ">=0.25.1" },
+    { name = "mkdocs-material", specifier = ">=9.7.1" },
+    { name = "mkdocstrings", extras = ["python"], specifier = ">=1.0.2" },
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+
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