diff --git a/notebooks/GIS/OPERA_EGIS_access.ipynb b/notebooks/GIS/OPERA_EGIS_access.ipynb
index a528a57b..fec4a5ee 100644
--- a/notebooks/GIS/OPERA_EGIS_access.ipynb
+++ b/notebooks/GIS/OPERA_EGIS_access.ipynb
@@ -122,7 +122,9 @@
    "source": [
     "## Programmatic Access\n",
     "\n",
-    "For programmatic access examples, see `OPERA_EGIS_access_Python.ipynb` in the [PO.DAAC Cookbook](https://podaac.github.io/tutorials/notebooks/GIS/OPERA_EGIS_access_Python.html)."
+    "For programmatic access examples, see `OPERA_EGIS_access_Python.ipynb` in the [PO.DAAC Cookbook](https://podaac.github.io/tutorials/notebooks/GIS/OPERA_EGIS_access_Python.html).\n",
+    "\n",
+    "For a science use case demonstrating surface water extent time series analysis, see `OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb` in the [PO.DAAC Cookbook](https://podaac.github.io/tutorials/notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb)."
    ]
   }
  ],
@@ -142,7 +144,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.13"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/GIS/OPERA_EGIS_access_Python.ipynb b/notebooks/GIS/OPERA_EGIS_access_Python.ipynb
index 6008c3aa..aa106beb 100644
--- a/notebooks/GIS/OPERA_EGIS_access_Python.ipynb
+++ b/notebooks/GIS/OPERA_EGIS_access_Python.ipynb
@@ -11,7 +11,7 @@
     "Author(s): Nicholas Tarpinian, Brandi Downs, Catalina Taglialatela *(NASA PO.DAAC)*\n",
     "\n",
     "_Created: 2026-06-01_ <br>\n",
-    "_Last Updated: 2026-06-24_ <br>\n",
+    "_Last Updated: 2026-06-29_ <br>\n",
     "\n",
     "\n",
     "\n",
@@ -313,145 +313,145 @@
       "text/html": [
        "<style type=\"text/css\">\n",
        "</style>\n",
-       "<table id=\"T_b5ff9\">\n",
+       "<table id=\"T_345c5\">\n",
        "  <thead>\n",
        "    <tr>\n",
        "      <th class=\"blank level0\" >&nbsp;</th>\n",
-       "      <th id=\"T_b5ff9_level0_col0\" class=\"col_heading level0 col0\" >objectid</th>\n",
-       "      <th id=\"T_b5ff9_level0_col1\" class=\"col_heading level0 col1\" >name</th>\n",
-       "      <th id=\"T_b5ff9_level0_col2\" class=\"col_heading level0 col2\" >datetime</th>\n",
-       "      <th id=\"T_b5ff9_level0_col3\" class=\"col_heading level0 col3\" >cloud_coverage</th>\n",
-       "      <th id=\"T_b5ff9_level0_col4\" class=\"col_heading level0 col4\" >tileid</th>\n",
-       "      <th id=\"T_b5ff9_level0_col5\" class=\"col_heading level0 col5\" >spacecraft_name</th>\n",
-       "      <th id=\"T_b5ff9_level0_col6\" class=\"col_heading level0 col6\" >downloadurl</th>\n",
+       "      <th id=\"T_345c5_level0_col0\" class=\"col_heading level0 col0\" >objectid</th>\n",
+       "      <th id=\"T_345c5_level0_col1\" class=\"col_heading level0 col1\" >name</th>\n",
+       "      <th id=\"T_345c5_level0_col2\" class=\"col_heading level0 col2\" >datetime</th>\n",
+       "      <th id=\"T_345c5_level0_col3\" class=\"col_heading level0 col3\" >cloud_coverage</th>\n",
+       "      <th id=\"T_345c5_level0_col4\" class=\"col_heading level0 col4\" >tileid</th>\n",
+       "      <th id=\"T_345c5_level0_col5\" class=\"col_heading level0 col5\" >spacecraft_name</th>\n",
+       "      <th id=\"T_345c5_level0_col6\" class=\"col_heading level0 col6\" >downloadurl</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
-       "      <td id=\"T_b5ff9_row0_col0\" class=\"data row0 col0\" >6280533</td>\n",
-       "      <td id=\"T_b5ff9_row0_col1\" class=\"data row0 col1\" >OPERA_L3_DSWx-HLS_T12STF_20250104T182649Z_20250107T030638Z_S2B_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row0_col2\" class=\"data row0 col2\" >2025-01-04 18:26:49</td>\n",
-       "      <td id=\"T_b5ff9_row0_col3\" class=\"data row0 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row0_col4\" class=\"data row0 col4\" >T12STF</td>\n",
-       "      <td id=\"T_b5ff9_row0_col5\" class=\"data row0 col5\" >Sentinel-2B</td>\n",
-       "      <td id=\"T_b5ff9_row0_col6\" class=\"data row0 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STF_20250104T182649Z_20250107T030638Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
+       "      <td id=\"T_345c5_row0_col0\" class=\"data row0 col0\" >6280533</td>\n",
+       "      <td id=\"T_345c5_row0_col1\" class=\"data row0 col1\" >OPERA_L3_DSWx-HLS_T12STF_20250104T182649Z_20250107T030638Z_S2B_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row0_col2\" class=\"data row0 col2\" >2025-01-04 18:26:49</td>\n",
+       "      <td id=\"T_345c5_row0_col3\" class=\"data row0 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row0_col4\" class=\"data row0 col4\" >T12STF</td>\n",
+       "      <td id=\"T_345c5_row0_col5\" class=\"data row0 col5\" >Sentinel-2B</td>\n",
+       "      <td id=\"T_345c5_row0_col6\" class=\"data row0 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STF_20250104T182649Z_20250107T030638Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
-       "      <td id=\"T_b5ff9_row1_col0\" class=\"data row1 col0\" >6280534</td>\n",
-       "      <td id=\"T_b5ff9_row1_col1\" class=\"data row1 col1\" >OPERA_L3_DSWx-HLS_T11SQA_20250104T182649Z_20250107T030637Z_S2B_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row1_col2\" class=\"data row1 col2\" >2025-01-04 18:26:49</td>\n",
-       "      <td id=\"T_b5ff9_row1_col3\" class=\"data row1 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row1_col4\" class=\"data row1 col4\" >T11SQA</td>\n",
-       "      <td id=\"T_b5ff9_row1_col5\" class=\"data row1 col5\" >Sentinel-2B</td>\n",
-       "      <td id=\"T_b5ff9_row1_col6\" class=\"data row1 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQA_20250104T182649Z_20250107T030637Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
+       "      <td id=\"T_345c5_row1_col0\" class=\"data row1 col0\" >6280534</td>\n",
+       "      <td id=\"T_345c5_row1_col1\" class=\"data row1 col1\" >OPERA_L3_DSWx-HLS_T11SQA_20250104T182649Z_20250107T030637Z_S2B_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row1_col2\" class=\"data row1 col2\" >2025-01-04 18:26:49</td>\n",
+       "      <td id=\"T_345c5_row1_col3\" class=\"data row1 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row1_col4\" class=\"data row1 col4\" >T11SQA</td>\n",
+       "      <td id=\"T_345c5_row1_col5\" class=\"data row1 col5\" >Sentinel-2B</td>\n",
+       "      <td id=\"T_345c5_row1_col6\" class=\"data row1 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQA_20250104T182649Z_20250107T030637Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
-       "      <td id=\"T_b5ff9_row2_col0\" class=\"data row2 col0\" >6280536</td>\n",
-       "      <td id=\"T_b5ff9_row2_col1\" class=\"data row2 col1\" >OPERA_L3_DSWx-HLS_T11SPA_20250104T182649Z_20250107T030633Z_S2B_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row2_col2\" class=\"data row2 col2\" >2025-01-04 18:26:49</td>\n",
-       "      <td id=\"T_b5ff9_row2_col3\" class=\"data row2 col3\" >2</td>\n",
-       "      <td id=\"T_b5ff9_row2_col4\" class=\"data row2 col4\" >T11SPA</td>\n",
-       "      <td id=\"T_b5ff9_row2_col5\" class=\"data row2 col5\" >Sentinel-2B</td>\n",
-       "      <td id=\"T_b5ff9_row2_col6\" class=\"data row2 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPA_20250104T182649Z_20250107T030633Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
+       "      <td id=\"T_345c5_row2_col0\" class=\"data row2 col0\" >6280536</td>\n",
+       "      <td id=\"T_345c5_row2_col1\" class=\"data row2 col1\" >OPERA_L3_DSWx-HLS_T11SPA_20250104T182649Z_20250107T030633Z_S2B_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row2_col2\" class=\"data row2 col2\" >2025-01-04 18:26:49</td>\n",
+       "      <td id=\"T_345c5_row2_col3\" class=\"data row2 col3\" >2</td>\n",
+       "      <td id=\"T_345c5_row2_col4\" class=\"data row2 col4\" >T11SPA</td>\n",
+       "      <td id=\"T_345c5_row2_col5\" class=\"data row2 col5\" >Sentinel-2B</td>\n",
+       "      <td id=\"T_345c5_row2_col6\" class=\"data row2 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPA_20250104T182649Z_20250107T030633Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
-       "      <td id=\"T_b5ff9_row3_col0\" class=\"data row3 col0\" >6280539</td>\n",
-       "      <td id=\"T_b5ff9_row3_col1\" class=\"data row3 col1\" >OPERA_L3_DSWx-HLS_T11SQV_20250104T182649Z_20250107T030643Z_S2B_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row3_col2\" class=\"data row3 col2\" >2025-01-04 18:26:49</td>\n",
-       "      <td id=\"T_b5ff9_row3_col3\" class=\"data row3 col3\" >10</td>\n",
-       "      <td id=\"T_b5ff9_row3_col4\" class=\"data row3 col4\" >T11SQV</td>\n",
-       "      <td id=\"T_b5ff9_row3_col5\" class=\"data row3 col5\" >Sentinel-2B</td>\n",
-       "      <td id=\"T_b5ff9_row3_col6\" class=\"data row3 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQV_20250104T182649Z_20250107T030643Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
+       "      <td id=\"T_345c5_row3_col0\" class=\"data row3 col0\" >6280539</td>\n",
+       "      <td id=\"T_345c5_row3_col1\" class=\"data row3 col1\" >OPERA_L3_DSWx-HLS_T11SQV_20250104T182649Z_20250107T030643Z_S2B_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row3_col2\" class=\"data row3 col2\" >2025-01-04 18:26:49</td>\n",
+       "      <td id=\"T_345c5_row3_col3\" class=\"data row3 col3\" >10</td>\n",
+       "      <td id=\"T_345c5_row3_col4\" class=\"data row3 col4\" >T11SQV</td>\n",
+       "      <td id=\"T_345c5_row3_col5\" class=\"data row3 col5\" >Sentinel-2B</td>\n",
+       "      <td id=\"T_345c5_row3_col6\" class=\"data row3 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQV_20250104T182649Z_20250107T030643Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
-       "      <td id=\"T_b5ff9_row4_col0\" class=\"data row4 col0\" >6280541</td>\n",
-       "      <td id=\"T_b5ff9_row4_col1\" class=\"data row4 col1\" >OPERA_L3_DSWx-HLS_T11SPV_20250104T182649Z_20250107T030641Z_S2B_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row4_col2\" class=\"data row4 col2\" >2025-01-04 18:26:49</td>\n",
-       "      <td id=\"T_b5ff9_row4_col3\" class=\"data row4 col3\" >4</td>\n",
-       "      <td id=\"T_b5ff9_row4_col4\" class=\"data row4 col4\" >T11SPV</td>\n",
-       "      <td id=\"T_b5ff9_row4_col5\" class=\"data row4 col5\" >Sentinel-2B</td>\n",
-       "      <td id=\"T_b5ff9_row4_col6\" class=\"data row4 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPV_20250104T182649Z_20250107T030641Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
+       "      <td id=\"T_345c5_row4_col0\" class=\"data row4 col0\" >6280541</td>\n",
+       "      <td id=\"T_345c5_row4_col1\" class=\"data row4 col1\" >OPERA_L3_DSWx-HLS_T11SPV_20250104T182649Z_20250107T030641Z_S2B_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row4_col2\" class=\"data row4 col2\" >2025-01-04 18:26:49</td>\n",
+       "      <td id=\"T_345c5_row4_col3\" class=\"data row4 col3\" >4</td>\n",
+       "      <td id=\"T_345c5_row4_col4\" class=\"data row4 col4\" >T11SPV</td>\n",
+       "      <td id=\"T_345c5_row4_col5\" class=\"data row4 col5\" >Sentinel-2B</td>\n",
+       "      <td id=\"T_345c5_row4_col6\" class=\"data row4 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPV_20250104T182649Z_20250107T030641Z_S2B_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
-       "      <td id=\"T_b5ff9_row5_col0\" class=\"data row5 col0\" >6302387</td>\n",
-       "      <td id=\"T_b5ff9_row5_col1\" class=\"data row5 col1\" >OPERA_L3_DSWx-HLS_T12STE_20250108T181539Z_20250113T211514Z_L8_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row5_col2\" class=\"data row5 col2\" >2025-01-08 18:15:39</td>\n",
-       "      <td id=\"T_b5ff9_row5_col3\" class=\"data row5 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row5_col4\" class=\"data row5 col4\" >T12STE</td>\n",
-       "      <td id=\"T_b5ff9_row5_col5\" class=\"data row5 col5\" >Landsat-8</td>\n",
-       "      <td id=\"T_b5ff9_row5_col6\" class=\"data row5 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STE_20250108T181539Z_20250113T211514Z_L8_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
+       "      <td id=\"T_345c5_row5_col0\" class=\"data row5 col0\" >6302387</td>\n",
+       "      <td id=\"T_345c5_row5_col1\" class=\"data row5 col1\" >OPERA_L3_DSWx-HLS_T12STE_20250108T181539Z_20250113T211514Z_L8_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row5_col2\" class=\"data row5 col2\" >2025-01-08 18:15:39</td>\n",
+       "      <td id=\"T_345c5_row5_col3\" class=\"data row5 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row5_col4\" class=\"data row5 col4\" >T12STE</td>\n",
+       "      <td id=\"T_345c5_row5_col5\" class=\"data row5 col5\" >Landsat-8</td>\n",
+       "      <td id=\"T_345c5_row5_col6\" class=\"data row5 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STE_20250108T181539Z_20250113T211514Z_L8_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
-       "      <td id=\"T_b5ff9_row6_col0\" class=\"data row6 col0\" >6308325</td>\n",
-       "      <td id=\"T_b5ff9_row6_col1\" class=\"data row6 col1\" >OPERA_L3_DSWx-HLS_T11SQA_20250109T182731Z_20250111T022843Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row6_col2\" class=\"data row6 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row6_col3\" class=\"data row6 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row6_col4\" class=\"data row6 col4\" >T11SQA</td>\n",
-       "      <td id=\"T_b5ff9_row6_col5\" class=\"data row6 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row6_col6\" class=\"data row6 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQA_20250109T182731Z_20250111T022843Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
+       "      <td id=\"T_345c5_row6_col0\" class=\"data row6 col0\" >6308325</td>\n",
+       "      <td id=\"T_345c5_row6_col1\" class=\"data row6 col1\" >OPERA_L3_DSWx-HLS_T11SQA_20250109T182731Z_20250111T022843Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row6_col2\" class=\"data row6 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row6_col3\" class=\"data row6 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row6_col4\" class=\"data row6 col4\" >T11SQA</td>\n",
+       "      <td id=\"T_345c5_row6_col5\" class=\"data row6 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row6_col6\" class=\"data row6 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQA_20250109T182731Z_20250111T022843Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
-       "      <td id=\"T_b5ff9_row7_col0\" class=\"data row7 col0\" >6308326</td>\n",
-       "      <td id=\"T_b5ff9_row7_col1\" class=\"data row7 col1\" >OPERA_L3_DSWx-HLS_T12STF_20250109T182731Z_20250111T022849Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row7_col2\" class=\"data row7 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row7_col3\" class=\"data row7 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row7_col4\" class=\"data row7 col4\" >T12STF</td>\n",
-       "      <td id=\"T_b5ff9_row7_col5\" class=\"data row7 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row7_col6\" class=\"data row7 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STF_20250109T182731Z_20250111T022849Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
+       "      <td id=\"T_345c5_row7_col0\" class=\"data row7 col0\" >6308326</td>\n",
+       "      <td id=\"T_345c5_row7_col1\" class=\"data row7 col1\" >OPERA_L3_DSWx-HLS_T12STF_20250109T182731Z_20250111T022849Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row7_col2\" class=\"data row7 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row7_col3\" class=\"data row7 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row7_col4\" class=\"data row7 col4\" >T12STF</td>\n",
+       "      <td id=\"T_345c5_row7_col5\" class=\"data row7 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row7_col6\" class=\"data row7 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STF_20250109T182731Z_20250111T022849Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
-       "      <td id=\"T_b5ff9_row8_col0\" class=\"data row8 col0\" >6308327</td>\n",
-       "      <td id=\"T_b5ff9_row8_col1\" class=\"data row8 col1\" >OPERA_L3_DSWx-HLS_T11SPA_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row8_col2\" class=\"data row8 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row8_col3\" class=\"data row8 col3\" >2</td>\n",
-       "      <td id=\"T_b5ff9_row8_col4\" class=\"data row8 col4\" >T11SPA</td>\n",
-       "      <td id=\"T_b5ff9_row8_col5\" class=\"data row8 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row8_col6\" class=\"data row8 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPA_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
+       "      <td id=\"T_345c5_row8_col0\" class=\"data row8 col0\" >6308327</td>\n",
+       "      <td id=\"T_345c5_row8_col1\" class=\"data row8 col1\" >OPERA_L3_DSWx-HLS_T11SPA_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row8_col2\" class=\"data row8 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row8_col3\" class=\"data row8 col3\" >2</td>\n",
+       "      <td id=\"T_345c5_row8_col4\" class=\"data row8 col4\" >T11SPA</td>\n",
+       "      <td id=\"T_345c5_row8_col5\" class=\"data row8 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row8_col6\" class=\"data row8 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPA_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
-       "      <td id=\"T_b5ff9_row9_col0\" class=\"data row9 col0\" >6308330</td>\n",
-       "      <td id=\"T_b5ff9_row9_col1\" class=\"data row9 col1\" >OPERA_L3_DSWx-HLS_T12STE_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row9_col2\" class=\"data row9 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row9_col3\" class=\"data row9 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row9_col4\" class=\"data row9 col4\" >T12STE</td>\n",
-       "      <td id=\"T_b5ff9_row9_col5\" class=\"data row9 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row9_col6\" class=\"data row9 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STE_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
+       "      <td id=\"T_345c5_row9_col0\" class=\"data row9 col0\" >6308330</td>\n",
+       "      <td id=\"T_345c5_row9_col1\" class=\"data row9 col1\" >OPERA_L3_DSWx-HLS_T12STE_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row9_col2\" class=\"data row9 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row9_col3\" class=\"data row9 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row9_col4\" class=\"data row9 col4\" >T12STE</td>\n",
+       "      <td id=\"T_345c5_row9_col5\" class=\"data row9 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row9_col6\" class=\"data row9 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T12STE_20250109T182731Z_20250111T022845Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
-       "      <td id=\"T_b5ff9_row10_col0\" class=\"data row10 col0\" >6308331</td>\n",
-       "      <td id=\"T_b5ff9_row10_col1\" class=\"data row10 col1\" >OPERA_L3_DSWx-HLS_T11SQV_20250109T182731Z_20250111T022841Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row10_col2\" class=\"data row10 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row10_col3\" class=\"data row10 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row10_col4\" class=\"data row10 col4\" >T11SQV</td>\n",
-       "      <td id=\"T_b5ff9_row10_col5\" class=\"data row10 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row10_col6\" class=\"data row10 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQV_20250109T182731Z_20250111T022841Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
+       "      <td id=\"T_345c5_row10_col0\" class=\"data row10 col0\" >6308331</td>\n",
+       "      <td id=\"T_345c5_row10_col1\" class=\"data row10 col1\" >OPERA_L3_DSWx-HLS_T11SQV_20250109T182731Z_20250111T022841Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row10_col2\" class=\"data row10 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row10_col3\" class=\"data row10 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row10_col4\" class=\"data row10 col4\" >T11SQV</td>\n",
+       "      <td id=\"T_345c5_row10_col5\" class=\"data row10 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row10_col6\" class=\"data row10 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SQV_20250109T182731Z_20250111T022841Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th id=\"T_b5ff9_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
-       "      <td id=\"T_b5ff9_row11_col0\" class=\"data row11 col0\" >6308332</td>\n",
-       "      <td id=\"T_b5ff9_row11_col1\" class=\"data row11 col1\" >OPERA_L3_DSWx-HLS_T11SPV_20250109T182731Z_20250111T022840Z_S2A_30_v1.0_B01_WTR</td>\n",
-       "      <td id=\"T_b5ff9_row11_col2\" class=\"data row11 col2\" >2025-01-09 18:27:31</td>\n",
-       "      <td id=\"T_b5ff9_row11_col3\" class=\"data row11 col3\" >0</td>\n",
-       "      <td id=\"T_b5ff9_row11_col4\" class=\"data row11 col4\" >T11SPV</td>\n",
-       "      <td id=\"T_b5ff9_row11_col5\" class=\"data row11 col5\" >Sentinel-2A</td>\n",
-       "      <td id=\"T_b5ff9_row11_col6\" class=\"data row11 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPV_20250109T182731Z_20250111T022840Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
+       "      <th id=\"T_345c5_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
+       "      <td id=\"T_345c5_row11_col0\" class=\"data row11 col0\" >6308332</td>\n",
+       "      <td id=\"T_345c5_row11_col1\" class=\"data row11 col1\" >OPERA_L3_DSWx-HLS_T11SPV_20250109T182731Z_20250111T022840Z_S2A_30_v1.0_B01_WTR</td>\n",
+       "      <td id=\"T_345c5_row11_col2\" class=\"data row11 col2\" >2025-01-09 18:27:31</td>\n",
+       "      <td id=\"T_345c5_row11_col3\" class=\"data row11 col3\" >0</td>\n",
+       "      <td id=\"T_345c5_row11_col4\" class=\"data row11 col4\" >T11SPV</td>\n",
+       "      <td id=\"T_345c5_row11_col5\" class=\"data row11 col5\" >Sentinel-2A</td>\n",
+       "      <td id=\"T_345c5_row11_col6\" class=\"data row11 col6\" ><a href=\"https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-protected/OPERA_L3_DSWX-HLS_V1/OPERA_L3_DSWx-HLS_T11SPV_20250109T182731Z_20250111T022840Z_S2A_30_v1.0_B01_WTR.tif\" target=\"_blank\">Download Granule</a></td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n"
       ],
       "text/plain": [
-       "<pandas.io.formats.style.Styler at 0x1f03a833a60>"
+       "<pandas.io.formats.style.Styler at 0x1a034b4d690>"
       ]
      },
      "metadata": {},
@@ -593,7 +593,7 @@
        "    &lt;style&gt;html, body {width: 100%;height: 100%;margin: 0;padding: 0;}&lt;/style&gt;\n",
        "    &lt;style&gt;#map {position:absolute;top:0;bottom:0;right:0;left:0;}&lt;/style&gt;\n",
        "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.js&quot;&gt;&lt;/script&gt;\n",
-       "    &lt;script src=&quot;https://code.jquery.com/jquery-3.7.1.min.js&quot;&gt;&lt;/script&gt;\n",
+       "    &lt;script src=&quot;https://code.jquery.com/jquery-1.12.4.min.js&quot;&gt;&lt;/script&gt;\n",
        "    &lt;script src=&quot;https://cdn.jsdelivr.net/npm/bootstrap@5.2.2/dist/js/bootstrap.bundle.min.js&quot;&gt;&lt;/script&gt;\n",
        "    &lt;script src=&quot;https://cdnjs.cloudflare.com/ajax/libs/Leaflet.awesome-markers/2.0.2/leaflet.awesome-markers.js&quot;&gt;&lt;/script&gt;\n",
        "    &lt;link rel=&quot;stylesheet&quot; href=&quot;https://cdn.jsdelivr.net/npm/leaflet@1.9.3/dist/leaflet.css&quot;/&gt;\n",
@@ -606,7 +606,7 @@
        "            &lt;meta name=&quot;viewport&quot; content=&quot;width=device-width,\n",
        "                initial-scale=1.0, maximum-scale=1.0, user-scalable=no&quot; /&gt;\n",
        "            &lt;style&gt;\n",
-       "                #map_a88c17ae7d9a29e2f63f385efc2da169 {\n",
+       "                #map_4018ae191b83f68da32f5e66e6050673 {\n",
        "                    position: relative;\n",
        "                    width: 100.0%;\n",
        "                    height: 100.0%;\n",
@@ -653,14 +653,14 @@
        "&lt;div&gt;&lt;span style=&quot;display:inline-block;width:15px;height:15px;background:#afafaf;border:1px solid black;&quot;&gt;&lt;/span&gt; HLS Cloud/Cloud Shadow&lt;/div&gt;\n",
        "&lt;/div&gt;\n",
        "    \n",
-       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_a88c17ae7d9a29e2f63f385efc2da169&quot; &gt;&lt;/div&gt;\n",
+       "            &lt;div class=&quot;folium-map&quot; id=&quot;map_4018ae191b83f68da32f5e66e6050673&quot; &gt;&lt;/div&gt;\n",
        "        \n",
        "&lt;/body&gt;\n",
        "&lt;script&gt;\n",
        "    \n",
        "    \n",
-       "            var map_a88c17ae7d9a29e2f63f385efc2da169 = L.map(\n",
-       "                &quot;map_a88c17ae7d9a29e2f63f385efc2da169&quot;,\n",
+       "            var map_4018ae191b83f68da32f5e66e6050673 = L.map(\n",
+       "                &quot;map_4018ae191b83f68da32f5e66e6050673&quot;,\n",
        "                {\n",
        "                    center: [36.25, -114.35],\n",
        "                    crs: L.CRS.EPSG3857,\n",
@@ -674,146 +674,152 @@
        "\n",
        "        \n",
        "    \n",
-       "            var tile_layer_7cbdbdf0ba97046a78958c453d3e42c2 = L.tileLayer(\n",
-       "                &quot;https://{s}.basemaps.cartocdn.com/light_all/{z}/{x}/{y}{r}.png&quot;,\n",
-       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca href=\\&quot;https://carto.com/attributions\\&quot;\\u003eCARTO\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 20, &quot;maxZoom&quot;: 20, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abcd&quot;, &quot;tms&quot;: false}\n",
-       "            );\n",
-       "        \n",
-       "    \n",
-       "            tile_layer_7cbdbdf0ba97046a78958c453d3e42c2.addTo(map_a88c17ae7d9a29e2f63f385efc2da169);\n",
+       "            var tile_layer_0e1638d49014d4bc5f9c2a62de4d4eb9 = L.tileLayer(\n",
+       "                &quot;https://cartodb-basemaps-{s}.global.ssl.fastly.net/light_all/{z}/{x}/{y}.png&quot;,\n",
+       "                {&quot;attribution&quot;: &quot;\\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors \\u0026copy; \\u003ca target=\\&quot;_blank\\&quot; href=\\&quot;http://cartodb.com/attributions\\&quot;\\u003eCartoDB\\u003c/a\\u003e, CartoDB \\u003ca target=\\&quot;_blank\\&quot; href =\\&quot;http://cartodb.com/attributions\\&quot;\\u003eattributions\\u003c/a\\u003e&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var tile_layer_c8505fac42c7d4ee4b73e09914d9fdda = L.tileLayer(\n",
+       "            var tile_layer_acdb3caf7cf9742bddfb58054654e3fd = L.tileLayer(\n",
        "                &quot;https://{s}.tile.opentopomap.org/{z}/{x}/{y}.png&quot;,\n",
        "                {&quot;attribution&quot;: &quot;Map data: \\u0026copy; \\u003ca href=\\&quot;https://www.openstreetmap.org/copyright\\&quot;\\u003eOpenStreetMap\\u003c/a\\u003e contributors, \\u003ca href=\\&quot;http://viewfinderpanoramas.org\\&quot;\\u003eSRTM\\u003c/a\\u003e | Map style: \\u0026copy; \\u003ca href=\\&quot;https://opentopomap.org\\&quot;\\u003eOpenTopoMap\\u003c/a\\u003e (\\u003ca href=\\&quot;https://creativecommons.org/licenses/by-sa/3.0/\\&quot;\\u003eCC-BY-SA\\u003c/a\\u003e)&quot;, &quot;detectRetina&quot;: false, &quot;maxNativeZoom&quot;: 18, &quot;maxZoom&quot;: 18, &quot;minZoom&quot;: 0, &quot;noWrap&quot;: false, &quot;opacity&quot;: 1, &quot;subdomains&quot;: &quot;abc&quot;, &quot;tms&quot;: false}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            tile_layer_c8505fac42c7d4ee4b73e09914d9fdda.addTo(map_a88c17ae7d9a29e2f63f385efc2da169);\n",
-       "        \n",
-       "    \n",
-       "            var rectangle_7eaec8f48a04523cec99aaaa6a163e2f = L.rectangle(\n",
+       "            var rectangle_9b9f8ec2fdeb6a2cfe1a0cf77eb0b86c = L.rectangle(\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;bubblingMouseEvents&quot;: true, &quot;color&quot;: &quot;red&quot;, &quot;dashArray&quot;: null, &quot;dashOffset&quot;: null, &quot;fill&quot;: false, &quot;fillColor&quot;: &quot;red&quot;, &quot;fillOpacity&quot;: 0.2, &quot;fillRule&quot;: &quot;evenodd&quot;, &quot;lineCap&quot;: &quot;round&quot;, &quot;lineJoin&quot;: &quot;round&quot;, &quot;noClip&quot;: false, &quot;opacity&quot;: 1.0, &quot;smoothFactor&quot;: 1.0, &quot;stroke&quot;: true, &quot;weight&quot;: 3}\n",
-       "            ).addTo(map_a88c17ae7d9a29e2f63f385efc2da169);\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_bdd3c876888c42aaf13319ee1dafd457 = L.imageOverlay(\n",
+       "            var image_overlay_5c3f7eaee5cd5dbb2f09f3379418dc82 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_274dd106fb697dc4ce2822150b54e3b4 = L.imageOverlay(\n",
+       "            var image_overlay_a1cbab759240b2c8e68f2b76a4c3ca92 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_06547650180556ed8dfb58b08588064c = L.imageOverlay(\n",
+       "            var image_overlay_268d73ef2846b83e71d2cff10d205e49 = L.imageOverlay(\n",
        "                &quot;data:image/png;base64,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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_36aadba00c96223e34e3c67b2ceb4004 = L.imageOverlay(\n",
+       "            var image_overlay_4d0ee7254815147044aaadf2228a5a58 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_2f411fad339674aa3ca37725a71cd8f8 = L.imageOverlay(\n",
+       "            var image_overlay_61288c14285e94efee612c793ad92290 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_7f12b2c2b41151b19a92546b9ef2585d = L.imageOverlay(\n",
+       "            var image_overlay_d97a6f4a478e70ea9e0073291acf0ca7 = L.imageOverlay(\n",
        "                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QwC4xNvlbG0WmD139FuUOCjeyng8vRwr9D0u8X3heTcGUk2vu9TjcbSZvO/T7cfW/1Ps09r3tl4DGRAAblV68JGrkZP31xqeFniO+xS7qGGK3296XlrKKof8fMi21+w9x2JmZH+3ACCdvj8+fDg6M8y8xKKmdSf2ej+elA3RgH7d61rSMdvC63R2LZEuYl9inutsxjn2Odb2TQYEgKy67tjw//2n1nMRS3XM80fNL8CxA4QUAUxKTwowuIfg43mvUz/JqEwtrYY+ffyWrVKprVn+YibdWDu/zrcvAAGgeL8GH6OPl8Px4rcWYEy/d2YWq5IGKq3yHqwrKUB+gvkg/+y2Uq6k/nkyIce8gXwUMqPXXuYjpIxqr8k8JrsiAAGgWB8v5Ev/ev9/bCPkmX2CUgnOzg3yU2zriveg35nBa+3xMcHHPKDY6i9Z+9rWfox+2/8xALjHcvp+PQjZ2gZlE9hRgrHE8gnnje6CmyFrv/fZc+103ZHh3wIQAIo37btIPTA4chF/wgCl1t6Q0l932j7flBZIdwELDaZYG2VpO5tT9+5vEgDKmQnrClGDhmHPLwqGrpwdq+SAJOb1L/k159m2BuOhmZFcNye67lxgMHW2dDVmHZDxa3pAACDQa5/JyQb2UqfrvUvsHePS7jCTXo41d5a2vVd+FDID3lXnhe8//v2lWX5a0rTVIL7Vt3Gmb26vN2Rpe9PHKsECoFlHBr9PCzxKdiTzIQCpX47PWIoZ8HKeDz5PGuW39ink69OpfPeyI6HPGbPi+vB1GRAAmtVSMFFSCdaZu9vTO7+QY2rdrWMxty7Bsb80le/aY44I2T8ZEACaG5gMdxOP3r18WhakpMBjb9rPkMcv/R/m/vzjU5XHSb+ywnjsyumppyyPXdzV/QMAmmhCHwOPudi7iU8d1Cz1gJQSnNxVV0+Z9pq+p1/fG3jHPPZJugQBR+zjQt+P0da2lGAB0IS9GurQxnLlP2nNByxL70Mp5VY5ynrYLxGKudsee2e+xub8PvC8Frud6boesc8pAAGgaaErqvNmPvPO2p+p0AHT1uP2Zvy5O4iFq/UXB1Mx2xwDj/FnhuA8poRLDwgALFxcQy/AMRfrmKk/a5sud61MY8389Zr/bE3lNKy7agHSnFIdq92Jvo89Z7czBOcxmRYZEAA4aOuO/NKc/eO/x7+fMqhaWrhs6c/4vb3tbP3ueyVZd71myq/u8aTPyZrU+99dEJTl7oUrpKoSgJaUthL6kjNlPlszzKx9vyRLGZu//1lu4g/9+dTlH7E/A0/VTY73pSzI9P9Ht5+rUf+/DOZ1TwEAzwxA1kqlji7StbTdUl+Bq8rE1l67owMfJViU6opjs1s5d6R4rpyfPSVYALBxgRzNy4uGTEDIRbaUmZtCLe3z0fKX0CDmTGlVqQEcpC6N6iYD/hLWxNnL8O797OvNnOR7BQC7F6Fyh49bJQ2xjdSjtZ8p4VWYrg/y119fLt+nWtdlgNS62eejhs/L+DuYBQsAZhfHvXKhoxfdFNsK2fbWY0dfv35cmDDH4Gae9ahhUAVX6AvIdsTYW2F9yixYADC7eIZc6IdSrNgFDO+YdenutTOANvQbWeP59wQgAHDAdEaolFNYjtsKnXFqLWOzFXSUdCe1pH0B8ny+BSAAVCkmgxBTOpBiEL23gvjeqt/Tr4X+zLifBvzAXf7r/7ptDwBo1tVN6EPwEZpBSK2UUieBBk9jfZd6fVi/5Na9AaBJOWfBuiMYuSMI2Zu162qayYHQ84MSLACqdmXwsVTmNb/Q5p5Zau/rVwVHT864lJK1ogyOh+tfRx85AJpbByRHVuTomiFHG9efHAAAja1pcufOANCmuwOQuxYRO6P+Vwxopa9HCRYA2XXdvUUOOZ59bxGxtTVEpl+PWWcEoCRDpnnt3CUDAsAtWsiChN4RnAZEbb4qQK2WSkRlQAAg44V4Kzsi+KBlMWv3UK75OkVL5zUBCAAUMBgSfNC6u9buIa3p5BvDv5dKXgUgADRrK8hYGgydCUrGnxVoAC34+5/1c54eEABu0WoPCEBL9IAAAACX28oYy4AAcAsZEGJZcBHqoAcEAHgERXv1MgNWW2RAALiFDAgwkt1qiwwIAE3Zu9PqTizkJ7vVVrApAwLALWRAANoMQGRAACCQ7AjA+WyXAAQAAoMOKzUDHDeuiq4EC4BbKMECaJMMCAAAt94Rpy0CEACY0OcB+Zj9qk3iTgBuoQQLoE0yIACwkP0Y/i0bAtdRftUuAQgALMxyZcYruJbyq3YJQABgxVIQIisCcI4eEABuoQcEoE0yIAAAQDYCEAAAIBsBCAAAkI0ABAAyTi9q6lGgdQIQALhgetG1QMPUo/BOQN7m+y0AAaBpV02rK9AAnxOWz4um4QWg2al4h7txAgWAPOdVGRAAmndV8GGxQqBVfR9QopprZwCgtAwIkJesIwM9IAAAZOGWQ7umEw4IQAAAgGzBpwAEAADIRgACAABkIwABAACyEYAAAADZCEAAAIBsBCAAACSfahXWCEAAAEgSeFjngxACEAAAThkCD9kPQglAAAA4TfaDUAIQAAAgGwEIAACQjQAEAADIRgACAABkIwABAOA233/8+8vfR36WZ7FcDAC36Xvz5gC0RgYEAADIRgACAABkIwABAIAGdIU0XwhAAABociDcmr4vo3Hf2w/AbTShA7RHBgQAAMhGAAIAwClKqoghAAEA4BQr+hBDAALAbbrOfVNgWwlN06SlCR2AW2lEB2iLDAgAAJCNAAQAgEsNxZYKLhlLbwUgAABc3qSuUb1dXffr3wIQAACy0lhed6Zr/mc0BqG/3baHAADAYy2V1W1lusaZD2VAAACAD7b6dubfWyqzmz5mOu26aXgBuJVpeKF+w9BTD8jz3q/uZ6Sw9t7tff/Xx74HIDIgAABcRvDxPH2/P3nA3qxmW98XgAAAcJlxAGsa3ufpuv3Mx1qAMv36NPsxEIAAAHD5rFZKsMrUzWasmr6XS+/ZmNE6837qAQHgVnpAoG5KsI77/uPfl8+/f3q5432Zf//M+zjPgAhAALiVAAQgn9hAIqbRfH0bSrAAAEjgqr6O4c7/UxYrnO7nE/a579Ou7REbfLx+7fjmAOA8GRDgqa4skaqlfE4AAkBxBCAAZUlRdrWVATELFgBQNNO3UqonlFwddeWsZQIQAKBopm+FPNI0nL//vZT9GAhAAChWzXcXgeerrf+jT7Bo5HQV9TWa0AG4lR4QgPq8BTEyIAAAkHxq4Nqytd3FKQolWAAAcKLkqtZSrNhgZdr/sRXGCEAAAAgaaLY8I9kYZIzZjtqyHucbzt8Cl5BjpOHDCIAS6AEBqHPGLLNgAQBwySCUNvUrwcfWFLwDJVgAACQdgFK37me51dxQlrb2vSkBCAAARGix/6Ob9ACtBRhjn8xW9uP1++l3DwDi6AMBKFdIVmP6uL0ARAYEAAAWtJjpOFNq9/c/byVYe2RAALidDAhAHfayHwMZEAAAKND3SjMwAhAAACgwyPhc2QrrIwEIAADcFGh8rijICCm/GghAAADg4pKnmgKNswQgABSr1vpnoEyChDwEIAAUy2AAeMJNEjdLXoLLrwYCEAAAOMHNkpco/wcJA/VBUq7omgAAAABJRU5ErkJggg==&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_c8710f0131d3c76ff6edc5c90f55888b = L.imageOverlay(\n",
+       "            var image_overlay_19ae5559c99b319c985ba8ce982da952 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_cb0b9e668eb0328ed7825ab5eea3ba26 = L.imageOverlay(\n",
+       "            var image_overlay_9d83a01e49358ce166061044cfebb029 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_1a9f23b30f9990333d8509397f7a3bb7 = L.imageOverlay(\n",
+       "            var image_overlay_eac84fbbc64a33f3b570d9c7ad263843 = L.imageOverlay(\n",
        "                &quot;data:image/png;base64,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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_0873bbc4c79d62e58e568ed73fdd7821 = L.imageOverlay(\n",
+       "            var image_overlay_e2b918ecc61d58de08f9f09ae05dfdbe = L.imageOverlay(\n",
        "                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        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_85156afcf8be824d5f8e966b7fbda129 = L.imageOverlay(\n",
+       "            var image_overlay_cacec2e8372ce8e558f5d9a4c1725904 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var image_overlay_1412a36e05947f3f2a819618d5be030b = L.imageOverlay(\n",
+       "            var image_overlay_d7131c8d6cfe00ed765fa5047e19ae84 = L.imageOverlay(\n",
        "                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&quot;,\n",
        "                [[35.9, -114.9], [36.6, -113.8]],\n",
        "                {&quot;opacity&quot;: 0.75}\n",
-       "            );\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
        "        \n",
        "    \n",
-       "            var layer_control_aa247ac1404bd1e6264fbceaf777edc4_layers = {\n",
+       "            var layer_control_076549abe6f9f043c20ec204b0695153 = {\n",
        "                base_layers : {\n",
-       "                    &quot;cartodbpositron&quot; : tile_layer_7cbdbdf0ba97046a78958c453d3e42c2,\n",
-       "                    &quot;Topography&quot; : tile_layer_c8505fac42c7d4ee4b73e09914d9fdda,\n",
+       "                    &quot;cartodbpositron&quot; : tile_layer_0e1638d49014d4bc5f9c2a62de4d4eb9,\n",
+       "                    &quot;Topography&quot; : tile_layer_acdb3caf7cf9742bddfb58054654e3fd,\n",
        "                },\n",
        "                overlays :  {\n",
-       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 0% | OID 6280533&quot; : image_overlay_bdd3c876888c42aaf13319ee1dafd457,\n",
-       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 0% | OID 6280534&quot; : image_overlay_274dd106fb697dc4ce2822150b54e3b4,\n",
-       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 2% | OID 6280536&quot; : image_overlay_06547650180556ed8dfb58b08588064c,\n",
-       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 10% | OID 6280539&quot; : image_overlay_36aadba00c96223e34e3c67b2ceb4004,\n",
-       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 4% | OID 6280541&quot; : image_overlay_2f411fad339674aa3ca37725a71cd8f8,\n",
-       "                    &quot;2025-01-08 | Landsat-8 | \\u2601 0% | OID 6302387&quot; : image_overlay_7f12b2c2b41151b19a92546b9ef2585d,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308325&quot; : image_overlay_c8710f0131d3c76ff6edc5c90f55888b,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308326&quot; : image_overlay_cb0b9e668eb0328ed7825ab5eea3ba26,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 2% | OID 6308327&quot; : image_overlay_1a9f23b30f9990333d8509397f7a3bb7,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308330&quot; : image_overlay_0873bbc4c79d62e58e568ed73fdd7821,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308331&quot; : image_overlay_85156afcf8be824d5f8e966b7fbda129,\n",
-       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308332&quot; : image_overlay_1412a36e05947f3f2a819618d5be030b,\n",
+       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 0% | OID 6280533&quot; : image_overlay_5c3f7eaee5cd5dbb2f09f3379418dc82,\n",
+       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 0% | OID 6280534&quot; : image_overlay_a1cbab759240b2c8e68f2b76a4c3ca92,\n",
+       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 2% | OID 6280536&quot; : image_overlay_268d73ef2846b83e71d2cff10d205e49,\n",
+       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 10% | OID 6280539&quot; : image_overlay_4d0ee7254815147044aaadf2228a5a58,\n",
+       "                    &quot;2025-01-04 | Sentinel-2B | \\u2601 4% | OID 6280541&quot; : image_overlay_61288c14285e94efee612c793ad92290,\n",
+       "                    &quot;2025-01-08 | Landsat-8 | \\u2601 0% | OID 6302387&quot; : image_overlay_d97a6f4a478e70ea9e0073291acf0ca7,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308325&quot; : image_overlay_19ae5559c99b319c985ba8ce982da952,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308326&quot; : image_overlay_9d83a01e49358ce166061044cfebb029,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 2% | OID 6308327&quot; : image_overlay_eac84fbbc64a33f3b570d9c7ad263843,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308330&quot; : image_overlay_e2b918ecc61d58de08f9f09ae05dfdbe,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308331&quot; : image_overlay_cacec2e8372ce8e558f5d9a4c1725904,\n",
+       "                    &quot;2025-01-09 | Sentinel-2A | \\u2601 0% | OID 6308332&quot; : image_overlay_d7131c8d6cfe00ed765fa5047e19ae84,\n",
        "                },\n",
        "            };\n",
-       "            let layer_control_aa247ac1404bd1e6264fbceaf777edc4 = L.control.layers(\n",
-       "                layer_control_aa247ac1404bd1e6264fbceaf777edc4_layers.base_layers,\n",
-       "                layer_control_aa247ac1404bd1e6264fbceaf777edc4_layers.overlays,\n",
+       "            L.control.layers(\n",
+       "                layer_control_076549abe6f9f043c20ec204b0695153.base_layers,\n",
+       "                layer_control_076549abe6f9f043c20ec204b0695153.overlays,\n",
        "                {&quot;autoZIndex&quot;: true, &quot;collapsed&quot;: false, &quot;position&quot;: &quot;topright&quot;}\n",
-       "            ).addTo(map_a88c17ae7d9a29e2f63f385efc2da169);\n",
-       "\n",
+       "            ).addTo(map_4018ae191b83f68da32f5e66e6050673);\n",
+       "            tile_layer_acdb3caf7cf9742bddfb58054654e3fd.remove();\n",
+       "            image_overlay_5c3f7eaee5cd5dbb2f09f3379418dc82.remove();\n",
+       "            image_overlay_a1cbab759240b2c8e68f2b76a4c3ca92.remove();\n",
+       "            image_overlay_268d73ef2846b83e71d2cff10d205e49.remove();\n",
+       "            image_overlay_4d0ee7254815147044aaadf2228a5a58.remove();\n",
+       "            image_overlay_61288c14285e94efee612c793ad92290.remove();\n",
+       "            image_overlay_d97a6f4a478e70ea9e0073291acf0ca7.remove();\n",
+       "            image_overlay_19ae5559c99b319c985ba8ce982da952.remove();\n",
+       "            image_overlay_9d83a01e49358ce166061044cfebb029.remove();\n",
+       "            image_overlay_eac84fbbc64a33f3b570d9c7ad263843.remove();\n",
+       "            image_overlay_e2b918ecc61d58de08f9f09ae05dfdbe.remove();\n",
+       "            image_overlay_cacec2e8372ce8e558f5d9a4c1725904.remove();\n",
+       "            image_overlay_d7131c8d6cfe00ed765fa5047e19ae84.remove();\n",
        "        \n",
        "&lt;/script&gt;\n",
        "&lt;/html&gt;\" style=\"position:absolute;width:100%;height:100%;left:0;top:0;border:none !important;\" allowfullscreen webkitallowfullscreen mozallowfullscreen></iframe></div></div>"
       ],
       "text/plain": [
-       "<folium.folium.Map at 0x1f03c5a4160>"
+       "<folium.folium.Map at 0x1a034a50bd0>"
       ]
      },
      "metadata": {},
@@ -955,11 +961,23 @@
     "\n",
     "display(m)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed608948-0e7d-41be-82bc-a45a4fc76b6d",
+   "metadata": {},
+   "source": [
+    "### Next Steps\n",
+    "\n",
+    "This notebook introduced the fundamentals of accessing OPERA DSWx-HLS through the EGIS REST API.\n",
+    "\n",
+    "For a science use case demonstrating **surface water extent time series analysis** using the EGIS REST API and OPERA DSWx-HLS, including raster export, mosaicking, quality filtering, and trend analysis, see [Earthdata GIS OPERA DSWx-HLS Science Use Case: Analyzing Surface Water Extent Change at Lake Mead](OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb)."
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Geospatial_310",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -973,7 +991,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.14"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb b/notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb
new file mode 100644
index 00000000..e4685453
--- /dev/null
+++ b/notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb
@@ -0,0 +1,1346 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1e68b311",
+   "metadata": {},
+   "source": [
+    "## Earthdata GIS OPERA DSWx-HLS Science Use Case: Analyzing Surface Water Extent Change at Lake Mead\n",
+    "<br>\n",
+    "\n",
+    "Authored by Brandi Downs, Nicholas Tarpinian, Catalina Taglialatela (NASA PO.DAAC)\n",
+    "\n",
+    "_Created: 2026-06-05_ <br>\n",
+    "_Last Updated: 2026-06-29_ <br>\n",
+    "\n",
+    "\n",
+    "\n",
+    "## Summary\n",
+    "\n",
+    "This guide shows how to use Python to access the OPERA DSWx-HLS Image Service from the NASA [**Earthdata GIS (EGIS)**](https://gis.earthdata.nasa.gov/portal/home/index.html) REST API and perform a surface water time series analysis. This EGIS service allows users to interactively explore and visualize OPERA DSWx-HLS data directly from the Image Service without having to download and manage data files locally.\n",
+    "\n",
+    "Using Lake Mead, USA, as an example, the notebook demonstrates how to query and export OPERA DSWx-HLS observations (specifically the `B01_WTR` layer) for a user-defined area of interest, mosaic multiple image tiles acquired on the same date, remove mosaics containing excessive fill values and cloud coverage, and calculate changes in open water extent through time. The workflow concludes by analyzing seasonal and long-term trends to quantify temporal changes in water extent and demonstrate how OPERA DSWx-HLS can be used to monitor evolving hydrologic conditions.\n",
+    "\n",
+    "For an introductory tutorial on accessing OPERA DSWx-HLS data through the EGIS REST API using Python, see:<br>\n",
+    "[Earthdata GIS OPERA DSWx-HLS Image Service Access - Programmatic](OPERA_EGIS_access_Python.ipynb)\n",
+    "\n",
+    "For more details on these services and the latest available services, please visit the [EGIS OPERA Image Service page](https://gis.earthdata.nasa.gov/portal/home/group.html?id=780767a6cee24331baae8557c78d2e8a#overview).<br>\n",
+    "For more details on the `B01_WTR` layer available through NASA EGIS, please see [OPERA_L3_DSWX-HLS_V1_B01_WTR](https://gis.earthdata.nasa.gov/portal/home/item.html?id=59caecb96b5b42dd85aa3001a10f7786)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bb0293d8-41d5-423b-b2c2-aa571636ca4e",
+   "metadata": {},
+   "source": [
+    "### Learning Objectives\n",
+    "- **Programmatic Access:** Connect to and interact with the OPERA DSWx-HLS REST Image Service API from EGIS using Python.\n",
+    "- **User Configuration:** Define your geographic area of interest, time range, and data fields.\n",
+    "- **Time Series Generation:** Export, mosaic, and organize OPERA DSWx-HLS observations into a consistent time series of raster arrays.\n",
+    "- **Open Water Analysis:** Calculate open water extent for each observation and generate a time series of surface water area.\n",
+    "- **Trend Analysis and Visualization:** Visualize temporal changes in open water extent and evaluate seasonal and long-term trends using statistical smoothing and linear regression."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4cb19346-0a36-42bb-b594-bab1950d492d",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "### Memory Requirements\n",
+    "At the time of writing, this workflow exports and processes more than three years of OPERA DSWx-HLS observations for the example area of interest. During processing, the notebook may require more than 4 GB of RAM, and this requirement will continue to increase as additional OPERA DSWx-HLS observations become available. Systems with insufficient available memory may experience significantly slower performance or cause the Jupyter kernel to terminate. If this occurs, consider reducing the date range or using a smaller area of interest.\n",
+    "\n",
+    "However, note that the time series and trend analyses later in this notebook are intended for longer observational records. Reducing the date range—particularly to less than one year—may limit the usefulness of those analyses."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "215d725f-f9b3-4a75-9c31-52dd75ff90dd",
+   "metadata": {},
+   "source": [
+    "## Step 1: Set Up the Environment\n",
+    "\n",
+    "In this section, we import the required Python packages, define helper functions used throughout the notebook, and configure the HTTP requests needed to interact with the OPERA DSWx-HLS Image Service through the Earthdata GIS (EGIS) REST API."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "79e84239-95b1-4424-905e-d66407210714",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "✓ All required packages are installed.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# First, check that all required packages are installed\n",
+    "\n",
+    "import importlib\n",
+    "\n",
+    "required_packages = {\n",
+    "    \"requests\": \"requests\",\n",
+    "    \"pandas\": \"pandas\",\n",
+    "    \"numpy\": \"numpy\",\n",
+    "    \"matplotlib\": \"matplotlib\",\n",
+    "    \"PIL\": \"Pillow\",\n",
+    "    \"pyproj\": \"pyproj\",\n",
+    "    \"rasterio\": \"rasterio\",\n",
+    "    \"statsmodels\": \"statsmodels\",\n",
+    "    \"psutil\": \"psutil\"\n",
+    "}\n",
+    "\n",
+    "missing = []\n",
+    "for module, package in required_packages.items():\n",
+    "    try:\n",
+    "        importlib.import_module(module)\n",
+    "    except ImportError:\n",
+    "        missing.append(package)\n",
+    "\n",
+    "if missing:\n",
+    "    print(\"The following required packages are not installed:\\n\")\n",
+    "    for pkg in missing:\n",
+    "        print(f\"  - {pkg}\")\n",
+    "    packages = \" \".join(missing)\n",
+    "    print(\"\\nInstall the missing packages using your preferred package manager.\\n\")\n",
+    "    print(\"Conda:\")\n",
+    "    print(f\"    conda install -c conda-forge {packages}\\n\")\n",
+    "    print(\"Pip:\")\n",
+    "    print(f\"    pip install {packages}\")\n",
+    "else:\n",
+    "    print(\"✓ All required packages are installed.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "ee51ad88",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Import Python packages\n",
+    "\n",
+    "import requests\n",
+    "import pandas as pd\n",
+    "import time\n",
+    "import numpy as np\n",
+    "from rasterio.io import MemoryFile\n",
+    "from pyproj import Transformer\n",
+    "from concurrent.futures import ThreadPoolExecutor, as_completed\n",
+    "from datetime import datetime\n",
+    "import matplotlib.pyplot as plt\n",
+    "from matplotlib.colors import ListedColormap\n",
+    "from matplotlib.patches import Patch\n",
+    "from statsmodels.nonparametric.smoothers_lowess import lowess\n",
+    "import os\n",
+    "import psutil"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d1278dd0-9458-43a3-950a-4fb1f2b3ff88",
+   "metadata": {},
+   "source": [
+    "### Note\n",
+    "\n",
+    "The Image Service limits the execution time of individual export requests to **1200 seconds (20 minutes)**. In this notebook, export and download requests are given a shorter client-side timeout of **120 seconds (2 minutes)** to prevent very large or stalled requests from running too long. This notebook exports each date separately, which helps avoid long-running requests. However, very large areas of interest or periods of high server demand may still cause an individual request to exceed the notebook timeout. If this occurs, consider reducing the geographic extent or increasing the export pixel size before rerunning the notebook."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "0e55f242",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "OPERA DSWx-HLS Image Service ready to query.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Image Service URL\n",
+    "URL = \"https://gis.earthdata.nasa.gov/image/rest/services/C2617126679-POCLOUD/OPERA_L3_DSWX-HLS_V1_B01_WTR/ImageServer\"\n",
+    "\n",
+    "# Persistent session\n",
+    "SESSION = requests.Session()\n",
+    "\n",
+    "\n",
+    "def to_epoch_ms(date_str):\n",
+    "    \"\"\"Convert a date string to Unix epoch milliseconds expected by ArcGIS ImageServer for time queries.\"\"\"\n",
+    "    return int(pd.Timestamp(date_str, tz=\"UTC\").timestamp() * 1000)\n",
+    "\n",
+    "\n",
+    "def get_json(url, params=None):\n",
+    "    \"\"\"Send a GET request and return JSON response.\"\"\"\n",
+    "    p = dict(params or {})\n",
+    "    p.setdefault(\"f\", \"json\")\n",
+    "    r = SESSION.get(url, params=p, timeout=120)\n",
+    "    r.raise_for_status()\n",
+    "    data = r.json()\n",
+    "    if \"error\" in data:\n",
+    "        raise RuntimeError(f\"Server Error: {data['error']}\")\n",
+    "    return data\n",
+    "\n",
+    "\n",
+    "def query_all_features(url, params, page_size=1000):\n",
+    "    \"\"\"Query all records from an ArcGIS REST endpoint using pagination.\n",
+    "    This function keeps requesting more records until all matching records are retrieved.\"\"\"\n",
+    "    all_features = []\n",
+    "    offset = 0\n",
+    "    while True:\n",
+    "        p = dict(params)\n",
+    "        p[\"resultOffset\"] = offset\n",
+    "        p[\"resultRecordCount\"] = page_size\n",
+    "        data = get_json(url, params=p)\n",
+    "        features = data.get(\"features\", [])\n",
+    "        all_features.extend(features)\n",
+    "        exceeded = data.get(\"exceededTransferLimit\", False)\n",
+    "        if not exceeded or len(features) == 0:\n",
+    "            break\n",
+    "        offset += len(features)\n",
+    "    print(f\"\\nRetrieved {len(all_features)} total records.\")\n",
+    "    return all_features\n",
+    "\n",
+    "\n",
+    "def get_utm_epsg_from_bbox(bbox):\n",
+    "    \"\"\"\n",
+    "    Choose a UTM EPSG code based on the center of AOI lon/lat bounding box.\n",
+    "    bbox should be xmin,ymin,xmax,ymax in EPSG:4326.\n",
+    "    \"\"\"\n",
+    "    xmin, ymin, xmax, ymax = map(float, bbox.split(\",\"))\n",
+    "    center_lon = (xmin + xmax) / 2\n",
+    "    center_lat = (ymin + ymax) / 2\n",
+    "    utm_zone = int((center_lon + 180) // 6) + 1\n",
+    "    if center_lat >= 0:\n",
+    "        epsg = 32600 + utm_zone\n",
+    "    else:\n",
+    "        epsg = 32700 + utm_zone\n",
+    "    return epsg\n",
+    "\n",
+    "\n",
+    "def export_date_mosaic_array(date, url, analysis_bbox, analysis_epsg, width, height, output_format=\"tiff\"):\n",
+    "    \"\"\"\n",
+    "    Export one mosaicked raster for a single date over the AOI.\n",
+    "    This makes one ImageServer export request per date.\n",
+    "    \"\"\"\n",
+    "    start = pd.Timestamp(date, tz=\"UTC\")\n",
+    "    end = start + pd.Timedelta(days=1)\n",
+    "    img_params = {\n",
+    "        \"bbox\": analysis_bbox,\n",
+    "        \"bboxSR\": str(analysis_epsg),\n",
+    "        \"imageSR\": str(analysis_epsg),\n",
+    "        \"size\": f\"{width},{height}\",\n",
+    "        \"format\": output_format,\n",
+    "        \"adjustAspectRatio\": \"false\",\n",
+    "        \"time\": f\"{int(start.timestamp() * 1000)},{int(end.timestamp() * 1000)}\",\n",
+    "        \"f\": \"json\",\n",
+    "        \"pixelType\": \"U8\",\n",
+    "        \"noData\": 255,\n",
+    "        \"interpolation\": \"RSP_NearestNeighbor\",\n",
+    "    }\n",
+    "    export_info = get_json(f\"{url}/exportImage\", params=img_params)\n",
+    "    r = SESSION.get(export_info[\"href\"], timeout=120)\n",
+    "    r.raise_for_status()\n",
+    "    with MemoryFile(r.content) as memfile:\n",
+    "        with memfile.open() as src:\n",
+    "            arr = src.read(1)\n",
+    "            transform = src.transform\n",
+    "            crs = src.crs\n",
+    "            nodata = src.nodata\n",
+    "    return date, arr.astype(np.uint8), transform, crs, nodata\n",
+    "\n",
+    "\n",
+    "def make_export_tiles(x_min, y_min, x_max, y_max, pixel_size_m, max_w, max_h):\n",
+    "    \"\"\"\n",
+    "    Split projected AOI bbox into smaller tiles that stay within ImageServer max size. This preserves the\n",
+    "    native (30 m) resolution instead of downsampling images that are larger than the ImageServer max size.\n",
+    "    \"\"\"\n",
+    "    tile_width_m = max_w * pixel_size_m\n",
+    "    tile_height_m = max_h * pixel_size_m\n",
+    "    tiles = []\n",
+    "    y0 = y_min\n",
+    "    while y0 < y_max:\n",
+    "        y1 = min(y0 + tile_height_m, y_max)\n",
+    "        x0 = x_min\n",
+    "        while x0 < x_max:\n",
+    "            x1 = min(x0 + tile_width_m, x_max)\n",
+    "            width = int(np.ceil((x1 - x0) / pixel_size_m))\n",
+    "            height = int(np.ceil((y1 - y0) / pixel_size_m))\n",
+    "            tiles.append({\n",
+    "                \"bbox\": f\"{x0},{y0},{x1},{y1}\",\n",
+    "                \"x_min\": x0,\n",
+    "                \"y_min\": y0,\n",
+    "                \"x_max\": x1,\n",
+    "                \"y_max\": y1,\n",
+    "                \"width\": width,\n",
+    "                \"height\": height\n",
+    "            })\n",
+    "            x0 = x1\n",
+    "        y0 = y1\n",
+    "    return tiles\n",
+    "\n",
+    "\n",
+    "def export_date_mosaic_tiled_array(date, url, export_tiles, analysis_epsg, full_width, full_height, x_min, y_max, pixel_size_m, \n",
+    "                                   output_format=\"tiff\"):\n",
+    "    \"\"\"\n",
+    "    Loop through the tiles for a given date, export each tile, and stitch them back together into one full raster array.\n",
+    "    Each tile stays within maxImageWidth/maxImageHeight.\n",
+    "    \"\"\"\n",
+    "    full_arr = np.full((full_height, full_width), 255, dtype=np.uint8)\n",
+    "    output_crs = None\n",
+    "    for tile in export_tiles:\n",
+    "        date_out, tile_arr, transform, crs, nodata = export_date_mosaic_array(\n",
+    "            date=date,\n",
+    "            url=url,\n",
+    "            analysis_bbox=tile[\"bbox\"],\n",
+    "            analysis_epsg=analysis_epsg,\n",
+    "            width=tile[\"width\"],\n",
+    "            height=tile[\"height\"],\n",
+    "            output_format=output_format\n",
+    "        )\n",
+    "        if nodata is not None:\n",
+    "            tile_arr[tile_arr == nodata] = 255\n",
+    "        col0 = int(round((tile[\"x_min\"] - x_min) / pixel_size_m))\n",
+    "        row0 = int(round((y_max - tile[\"y_max\"]) / pixel_size_m))\n",
+    "        row1 = row0 + tile_arr.shape[0]\n",
+    "        col1 = col0 + tile_arr.shape[1]\n",
+    "        full_arr[row0:row1, col0:col1] = tile_arr\n",
+    "        output_crs = crs\n",
+    "    return date, full_arr, output_crs\n",
+    "\n",
+    "\n",
+    "def print_memory_usage():\n",
+    "    \"\"\"Print the current RAM usage of the Python process.\"\"\"\n",
+    "    process = psutil.Process(os.getpid())\n",
+    "    mem = process.memory_info().rss / 1024**3  # GB\n",
+    "    return f\"RAM usage: {mem:.1f} GB\"\n",
+    "\n",
+    "\n",
+    "meta = get_json(URL)\n",
+    "max_h = meta.get('maxImageHeight')\n",
+    "max_w = meta.get('maxImageWidth')\n",
+    "\n",
+    "print(\"OPERA DSWx-HLS Image Service ready to query.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ea6dd3f7-138b-4767-862f-f445b8fcd29e",
+   "metadata": {},
+   "source": [
+    "## Step 2: Query and Export OPERA DSWx-HLS Data\n",
+    "\n",
+    "In this section, we define the analysis parameters for the Lake Mead example, including the area of interest, date range, cloud coverage threshold, output fields, and export resolution. The notebook then queries the OPERA DSWx-HLS Image Service for matching observations, exports the data for each available date, mosaics multiple tiles acquired on the same date, and stores the resulting raster arrays for time series analysis.\n",
+    "\n",
+    "For this example, we retrieve all available observations regardless of cloud coverage by setting `MAX_CLOUD_COVERAGE` to `100`. Observations with cloud cover are filtered later in the workflow. Reducing this threshold can decrease the number of exported scenes, resulting in faster execution and lower memory usage.\n",
+    "\n",
+    "### Notes\n",
+    "- `START_DATE` is inclusive whereas `END_DATE` is exclusive. Data are retrieved over the interval `[START_DATE, END_DATE)`.\n",
+    "- To view all available metadata fields that can be requested from the Image Service using the `FIELDS` variable, run the optional cell below."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ab4df9ed-83ea-40b6-91f0-159751d8b3a6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "['objectid', 'name', 'minps', 'maxps', 'lowps', 'highps', 'category', 'centerx', 'centery', 'shape', 'processingdate', 'tileid', 'datetime', 'productgenerationdatetime', 'cloud_coverage', 'spacecraft_name', 'downloadurl', 'urldisplay']\n"
+     ]
+    }
+   ],
+   "source": [
+    "# OPTIONAL: Print all available metadata fields\n",
+    "fields = [f.get('name') for f in meta.get('fields', [])]\n",
+    "print(fields)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d8d2a39f-4d05-4375-8992-0a20d1f99abe",
+   "metadata": {},
+   "source": [
+    "### A Note on Parallel Processing\n",
+    "\n",
+    "To reduce overall runtime, this notebook uses Python's `ThreadPoolExecutor` to export multiple acquisition dates concurrently. By default, up to four dates are processed simultaneously (`max_workers = 4`), although the optimal value depends on your available CPU resources, internet connection, and Image Service load.\n",
+    "\n",
+    "Increasing `max_workers` may reduce execution time by submitting more export requests in parallel, but it can also increase system resource usage and place additional load on the Image Service. Decreasing `max_workers` will reduce the number of concurrent requests but may increase the total runtime."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5e2e32d4-39e0-4966-b14c-9b2a6a3e19a9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Querying the OPERA DSWx-HLS Catalog...\n",
+      "\n",
+      "Retrieved 4032 total records.\n",
+      "Found 4032 scene records.\n",
+      "Found 838 unique dates.\n",
+      "Using EPSG:32611 for analysis.\n",
+      "Requested full-resolution export width: 2567, height: 1916\n",
+      "Using 2 export tile(s) to preserve 30 m resolution.\n",
+      "Processing completed for 838/838: 2026-06-23. RAM usage: 4.1 GB\n",
+      "\n",
+      "------------------------------------------------------------ \n",
+      "\n",
+      "Removed 456 dates containing only nodata pixels.\n",
+      "Stored mosaicked raster arrays for 382 dates.\n",
+      "x coordinate shape: (2567,)\n",
+      "y coordinate shape: (1916,)\n",
+      "Output CRS: EPSG:32611\n",
+      "Total RAM usage: 4.1 GB\n",
+      "Total runtime: 11.8 minutes\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Define Area of Interest (xmin, ymin, xmax, ymax)\n",
+    "# For this example, we are using Lake Mead, USA\n",
+    "BBOX = \"-114.86,35.97,-114.02,36.47\"\n",
+    "\n",
+    "# Define Date Range (YYYY-MM-DD)\n",
+    "START_DATE = \"2023-01-01\"   # inclusive\n",
+    "END_DATE = pd.Timestamp.utcnow().strftime(\"%Y-%m-%d\")   # gets today's date; exclusive\n",
+    "\n",
+    "# Define maximum acceptable cloud coverage (%)\n",
+    "MAX_CLOUD_COVERAGE = 100\n",
+    "\n",
+    "# Define specific fields to request from the Image Service\n",
+    "FIELDS = \"objectid,name,datetime,cloud_coverage,tileid,spacecraft_name,downloadurl\"\n",
+    "\n",
+    "# DSWx-HLS fill / nodata value\n",
+    "NODATA = 255\n",
+    "\n",
+    "# OPERA DSWx-HLS native pixel size is 30 m.\n",
+    "PIXEL_SIZE_M = 30\n",
+    "\n",
+    "print(\"Querying the OPERA DSWx-HLS Catalog...\")\n",
+    "\n",
+    "t0 = time.perf_counter()\n",
+    "\n",
+    "# Query ImageServer catalog records\n",
+    "query_params = {\n",
+    "    \"geometry\": BBOX,\n",
+    "    \"geometryType\": \"esriGeometryEnvelope\",\n",
+    "    \"spatialRel\": \"esriSpatialRelIntersects\",\n",
+    "    \"inSR\": \"4326\",\n",
+    "    \"where\": f\"cloud_coverage <= {MAX_CLOUD_COVERAGE}\",\n",
+    "    \"time\": f\"{to_epoch_ms(START_DATE)},{to_epoch_ms(END_DATE)}\",\n",
+    "    \"outFields\": FIELDS,\n",
+    "    \"returnGeometry\": \"false\",\n",
+    "    \"orderByFields\": \"datetime ASC\",\n",
+    "    \"resultRecordCount\": 1000\n",
+    "}\n",
+    "\n",
+    "features = query_all_features(f\"{URL}/query\", query_params)\n",
+    "\n",
+    "if not features:\n",
+    "    print(\"No scenes found. Try expanding your date range, bounding box, or cloud coverage tolerance.\")\n",
+    "\n",
+    "else:\n",
+    "    df = pd.DataFrame([f[\"attributes\"] for f in features])\n",
+    "    df[\"datetime\"] = pd.to_datetime(df[\"datetime\"], unit=\"ms\")\n",
+    "    df[\"date\"] = df[\"datetime\"].dt.date\n",
+    "    unique_dates = sorted(df[\"date\"].unique())\n",
+    "    print(f\"Found {len(df)} scene records.\")\n",
+    "    print(f\"Found {len(unique_dates)} unique dates.\")\n",
+    "\n",
+    "    # Automatically choose an analysis CRS from the AOI\n",
+    "    ANALYSIS_EPSG = get_utm_epsg_from_bbox(BBOX)\n",
+    "    print(f\"Using EPSG:{ANALYSIS_EPSG} for analysis.\")\n",
+    "\n",
+    "    # Convert AOI bbox to analysis CRS and define export size\n",
+    "    xmin, ymin, xmax, ymax = map(float, BBOX.split(\",\"))\n",
+    "    transformer = Transformer.from_crs(\"EPSG:4326\",f\"EPSG:{ANALYSIS_EPSG}\",always_xy=True)\n",
+    "\n",
+    "    # Transform all four corners for a safer projected bounding box\n",
+    "    corners_lon = [xmin, xmin, xmax, xmax]\n",
+    "    corners_lat = [ymin, ymax, ymin, ymax]\n",
+    "    xs_corners, ys_corners = transformer.transform(corners_lon, corners_lat)\n",
+    "    x_min = min(xs_corners)\n",
+    "    x_max = max(xs_corners)\n",
+    "    y_min = min(ys_corners)\n",
+    "    y_max = max(ys_corners)\n",
+    "    full_width = int(np.ceil((x_max - x_min) / PIXEL_SIZE_M))\n",
+    "    full_height = int(np.ceil((y_max - y_min) / PIXEL_SIZE_M))\n",
+    "    print(f\"Requested full-resolution export width: {full_width}, height: {full_height}\")\n",
+    "    export_tiles = make_export_tiles(\n",
+    "        x_min=x_min,\n",
+    "        y_min=y_min,\n",
+    "        x_max=x_max,\n",
+    "        y_max=y_max,\n",
+    "        pixel_size_m=PIXEL_SIZE_M,\n",
+    "        max_w=max_w,\n",
+    "        max_h=max_h\n",
+    "    )\n",
+    "    print(f\"Using {len(export_tiles)} export tile(s) to preserve {PIXEL_SIZE_M} m resolution.\")\n",
+    "\n",
+    "    # Build one mosaicked raster per date\n",
+    "    dates = []\n",
+    "    values = []  # list of 2D raster arrays, one per date\n",
+    "    x_coords = None\n",
+    "    y_coords = None\n",
+    "    output_transform = None\n",
+    "    output_crs = None\n",
+    "\n",
+    "    # Process multiple dates in parallel using worker threads\n",
+    "    # If max_workers=4, up to 4 dates can be exported simultaneously\n",
+    "    max_workers = 4\n",
+    "    removed_nodata_count = 0\n",
+    "    \n",
+    "    with ThreadPoolExecutor(max_workers=max_workers) as executor:\n",
+    "        \n",
+    "        # Submit one export task per date. executor.submit() immediately returns a Future object,\n",
+    "        # which acts as a placeholder for the result while the export runs in the background.\n",
+    "        # Build a dictionary that maps each Future back to its corresponding date\n",
+    "        # so we can identify which date completed when the result is returned.\n",
+    "        future_to_date = {\n",
+    "            executor.submit(\n",
+    "                export_date_mosaic_tiled_array,\n",
+    "                date,\n",
+    "                URL,\n",
+    "                export_tiles,\n",
+    "                ANALYSIS_EPSG,\n",
+    "                full_width,\n",
+    "                full_height,\n",
+    "                x_min,\n",
+    "                y_max,\n",
+    "                PIXEL_SIZE_M,\n",
+    "                \"tiff\"\n",
+    "            ): date\n",
+    "            for date in unique_dates\n",
+    "        }\n",
+    "\n",
+    "        # Process completed exports as they finish. as_completed() returns Futures in \n",
+    "        # completion order, which may differ from the chronological order of unique_dates.\n",
+    "        for i, future in enumerate(as_completed(future_to_date), start=1):\n",
+    "            \n",
+    "            # Retrieve the date associated with this completed export.\n",
+    "            date = future_to_date[future]\n",
+    "            \n",
+    "            try:\n",
+    "                # Retrieve the export result from the completed Future.\n",
+    "                date, arr, crs = future.result()\n",
+    "            except Exception as e:\n",
+    "                # Skip dates whose export failed without stopping the entire run.\n",
+    "                print(f\"\\nSkipping {date}: export failed\")\n",
+    "                print(e)\n",
+    "                continue\n",
+    "                \n",
+    "            # Remove exports that contain only nodata values, indicating no valid pixels were found within the AOI.\n",
+    "            if np.all(arr == NODATA):\n",
+    "                removed_nodata_count += 1\n",
+    "                continue\n",
+    "                \n",
+    "            # Create coordinate vectors once using a common output grid.\n",
+    "            if x_coords is None or y_coords is None:\n",
+    "                x_coords = x_min + (np.arange(full_width) + 0.5) * PIXEL_SIZE_M\n",
+    "                y_coords = y_max - (np.arange(full_height) + 0.5) * PIXEL_SIZE_M\n",
+    "                output_crs = crs\n",
+    "                \n",
+    "            # Store the date and corresponding raster array.\n",
+    "            dates.append(date)\n",
+    "            values.append(arr)\n",
+    "\n",
+    "            print(f\"Processing completed for {i}/{len(unique_dates)}: {date}. {print_memory_usage()}\", end=\"\\r\")\n",
+    "            \n",
+    "    if dates:\n",
+    "        # Results were collected in completion order. Sort by date while keeping each raster array paired with its corresponding date.\n",
+    "        results = sorted(zip(dates, values), key=lambda x: x[0]) \n",
+    "        dates = [r[0] for r in results]\n",
+    "        values = [r[1] for r in results]\n",
+    "\n",
+    "    print(\"\\n\")\n",
+    "    print(\"-\" * 60, \"\\n\")\n",
+    "    print(f\"Removed {removed_nodata_count} dates containing only nodata pixels.\")\n",
+    "    print(f\"Stored mosaicked raster arrays for {len(dates)} dates.\")\n",
+    "    print(f\"x coordinate shape: {x_coords.shape if x_coords is not None else 'N/A'}\")\n",
+    "    print(f\"y coordinate shape: {y_coords.shape if y_coords is not None else 'N/A'}\")\n",
+    "    print(f\"Output CRS: {output_crs}\")\n",
+    "    print(f\"Total {print_memory_usage()}\")\n",
+    "    print(f\"Total runtime: {(time.perf_counter() - t0)/60:.1f} minutes\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c2d484fa-7c0f-4e71-9058-c1078a6bbaf5",
+   "metadata": {},
+   "source": [
+    "## Step 3: Visualize the Exported Mosaics\n",
+    "\n",
+    "Before proceeding with the time series analysis, we visualize a subset of the exported DSWx-HLS mosaics to verify that the data were retrieved successfully and to gain an initial understanding of the surface water conditions observed throughout the study period.\n",
+    "\n",
+    "The mosaics are displayed using the projected analysis coordinate reference system (CRS) rather than latitude and longitude. Working in a projected CRS preserves the native 30-meter pixel spacing and enables accurate area calculations later in the workflow. For ease of interpretation, the axis labels are shown in approximate latitude and longitude by transforming the projected tick locations. These lat/lon labels are intended for visual reference only and do not represent a true geographic reprojection of the imagery."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "00b2b74a-83e1-477e-b1f6-2077ab9d60db",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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4ceMAAE2aNMGBAwewfPlyxMbGltjWnTt38PLLL2PlypWoVKmSwX1u3rwZ69evx8aNGxEdHY309HSMHTsWVatWxaBBg/S+ZsqUKRg/frz4d3Z2NmrUqIGLFy8iKChI0nvdsWOH+O+ePXtKek1pGNqf5nJH6Nmzp1gGexwHIiKpcnJyEBYWhsDAQEcXpdScJb4C1omxRGT/uia5NmvX110pxhKR63N4sszLy0scgDgmJgZpaWlYsmQJli5dirJlyyIqKkpr/QYNGmD//v16t3X27FmcP38ezz77rLhMPQNX2bJlcerUKdSqVQsTJ07E5MmT8eKLLwIAnnzySVy4cAEJCQkGK/Pe3t7w9vYusVw905gUL730kqT1rMXPz09vlxo/Pz+7lkNXUFCQeCzUY92Y6vpDRGRPrtD1z1niK2CdGEtE2nVNzfEEWc8iS6ivGax9HnaFGEtErs/hyTJdgiAgLy8PXl5eaN68OU6dOqX1/OnTpxEeHq73tfXr10dGRobWsqlTp+LOnTtYsmQJwsLCAAD37t0r0U/ew8PD5aa2l3PFSLMCR0RkKSbcpWN8JSIiczC2EpE7c2iy7N1330X37t0RFhaGO3fuYNOmTUhJSUFycjIAYOLEiejXrx/at2+PuLg4JCcnY/v27UhJSRG3MXDgQFSrVg0JCQnw8fFBw4YNtfah7m6iufzZZ5/F3LlzUaNGDURHR+Po0aNYtGgRhg4davP3bC26ySbdYKZSqQwGOKVSKSlZJXU9c+iWiUHYPhQKQF7z3hKRLTG+EtmPAsUDMRG5A96kIiJ34dBk2T///INXXnkFV65cQXBwMBo1aoTk5GR07twZABAfH4/ly5cjISEBY8aMQb169bBlyxa0bdtW3EZWVpbZs6ksXboU06ZNw8iRI3Ht2jVUrVoVr7/+Ot5//32rvj9HkJrc0gxwhl5jy9ZfDLD2w0QZuTKeS/RjfLU+XiCSIXINsfyuki0ZuzFPROQKFILAy2hL5OTkIDg4GNnZ2Q4ZT0VqyzBrbcsaGFCJyBZ0x+UpTVLD0ed2KibHz4HJMiKi0p0L5XhuJyIyRHZjlpF9cMwwIiIi6ZgkI5IPU8ORkO3wWBORu2CyjIiInBor7kREREREZE3mDUZCsqFUKp3iAtEZykhEREREREREpMaWZU7MVFdKzYE3rdXt0pLtMWFGRESuiOOYETmGLWZsJyIi0sRkmZMyp4LAAfyJyJ3wXERE5Pp4riciIltisszFWbtFGRERERVjbCQiV6A7qzQREXHMMrKQvjHTVCoVm8QTERERERERkVNjsswFOeKOEO9CEREREREREZErUAiCIDi6EM4oJycHwcHByM7ORlBQkEPKYKgVlyWDnkp9DZNiROTK5HBuJ34ORESOZosJTHhuJyJnwmSZheR4sre0C6SxRJm+55gwIzlQAODJi6xNjud2d8TPgYjIsWxR/+e5nYicCbthuojSjBXGccbIGTFRRkRERGQbvDlORO6Os2GSSQyWJFdsXUZERERkW7wWICJ3xGSZG5IyPhmDIhERERGR++L1ABG5MybLXIQ6mJWmSyUDIjkbtiojIiIiIiIia+OYZS7G0oQXE2VERERERERERGxZ5pLMTXwxUUZEREREahwTVJu65wbrzERE7oPJMjfFYE9ERERE+jBRRkRE7o7JMjemOb4Zk2dERERERIaxhRkRkftgsoxKYBKNiIiIiKiYNSbSIiIi58JkmRvRTYIxEUZEREREJA3rzkRE7oPJMjdlrBk5KwJERERE7oWD+hMRET1WxtEFIPlTqVRsdk5ERETkwpgoIyIieozJMjfCrpdERERERERERMYxWeaGNJNmUlqMMclGcqB49CAiIiLrSMrMFf/NGEtERPQYk2VE5BQEsIsIERGRNfWI8hf/LaA4eWZJ0ozDdRARkavhAP9E5BTUlXcmzIiIiEpPMykmqP+O8gcUgEJ4vNwUdaLM2ORRREREzobJMjfGygw5C3YNISIish6FTqasRJx9tEAh8CYVERG5J3bDJCKnwMo6ERFR6elNjGk+dJ7THNdMH958JSIiV8RkGRERERGRu7Byc22OV0ZERK6IyTIicgqm7mwTERGRcZbkyXpG+xt9ni3LiIjIFTFZRkSypq7Y94zyZ1dMIiIiOxMMBF+VSsVWZURE5LI4wD8RyY5C/A+0BitTLzdUcSciIiIjzG1apife6ibIOAsmERG5IibLiEie1PPYcypMIiIiuzLWmoyIiMgdsBsmEREREREBYOttIiIigC3LiEiu2KKMiIjI7hR6hjtgizIiInI3TJa5CY4nQU5H3Q2TiIiIZIn1SiIiclXshklE8sWuIERERHalrxumUqlkYoyIiNwKW5YRkdPgOCpERESWUUhorS01zjJxRkREro7JMjfBSg05C4UCj7tgMjlGRERkF/oSZSqVCkqlUmvMMtYpiYjIHbAbJhHJilhZ1zNmmZS74kRERGQ+fTGWiTEiInJXbFlGRPKkp9LObphERCRnnFCJbIWt+4iI7IvJMiKSFYX4H21MlBERkZxpJjOckbE4y+SMYzn7d4uIyBkxWUbkZuR819tQN0smyoiIiGyDMZaIiKgkJsuISNZYiSciIiod3oxybnK8wUlE5OqYLCMiIiIicmV6Js0hIudQWFiI/Px8RxeDyCV4eXmhTBlp81wyWUbkZnTvTjqyW2aJfbMyT0RETkpOrX/ULcnULccYXuVLdzwyOX2PyLEEQcDVq1dx+/ZtRxeFyGWUKVMGkZGR8PLyMrkuk2VEBKC4slaaCpo5szTpVgwVikcVej01efE5IiIiN6UvxkqJu7pJM33PM8YSyZM6URYSEgI/Pz8oDPWnJiJJioqKcPnyZVy5cgU1atQw+ZtisozIzSmVSrvNsmRsP5oVdt3zFivzRERE0uir+6vjaFJmLnpG++t9jhzDnvUwch6FhYVioqxixYqOLg6Ry6hcuTIuX76MgoICeHp6Gl2XyTIiEitqjp4p01hyn5V5IiL35OjYZA5zWlnbYr/x8Yb3WRxj/Q0+J6cY60yfuTW4y/sk6dRjlPn5+Tm4JESuRd39srCwkMkyIrIPzYqeuRcLiYkqoxV8IiIiubNl6yBDMVYX4ymRa2HXSyLrMuc3xWQZkRsxdqe2NMkuS/dJRERkTc4QcxzV+syZ8LgQEZGjSZszk8jNqbsoutKYEo54P0qlEkqlkne9iYhIMnXsUHO1eExE5Go+//xzREZGwsfHB82aNcO+ffvM3kaHDh2gUCiwadMmreWLFy9GRESEWdtSKBQm40bLli3xxhtvaC1btmwZFAoF/vvf/2otHzZsGFq3bi1p34MHD+YNACfFZBmRmVy9gm7u+9OXSNS9sNFHM2EmJXkmp7FUiIhInqTEH1vuW9+/jTEn5kpJEvKCjIgcbfPmzRg7dizee+89HD16FO3atUP37t2RlZVl9rZ8fHwwdepUcQw3W4qLi8OePXu0lqWkpCAsLEzv8ri4OJuXSdPDhw/tuj9isoxIElepfGpeRNjigsJYCzz1crGbuADEs5UZERGZSWr8clQLanP3LWVdKdtSKpVGJ8oxhjekiMhaFi1ahGHDhuHVV19FgwYNsHjxYoSFhWHZsmVmb6t///7Izs7GypUrja63bNky1KpVC15eXqhXrx7WrVsnPqduhRYfHw+FQmGwVVpcXBxOnTqFK1euiMtSU1MxZcoUpKSkiMsuXryIv/76C3FxcSgsLMSwYcMQGRkJX19f1KtXD0uWLBHXnTFjBtauXYtvv/0WCoUCCoVC3NalS5fQr18/lC9fHhUrVkTv3r1x/vx58bXqFmkJCQmoWrUq6tatK+2gkdVwzDIiiVwlYWaKue9T88LALGZU6FmJJyIiV6EbZ9XxszTjrTFRRkRy8PDhQxw5cgSTJ0/WWt6lSxccOHBA/HvGjBlYs2aNVnJIn6CgILz77ruYNWsWBg0aBH//kjP6JiYm4q233sLixYvRqVMn7NixA0OGDEH16tURFxeHtLQ0hISEYPXq1ejWrRs8PDz07qtNmzbw9PRESkoK+vfvj8zMTNy/fx9Dhw7FO++8gzNnzqBOnTrYs2cPvLy80Lp1axQVFaF69er4+uuvUalSJRw4cACvvfYaQkND8cILL2DChAk4efIkcnJysHr1agBAhQoVcO/ePcTFxaFdu3bYu3cvypYtizlz5qBbt244fvy4OGPj7t27ERQUhF27dkHgydrumCwjIoP0DUKsW5k3lCQr7d18xgMiIioNOXTHtIRKpTL7RpS5iTLGWCKyhevXr6OwsBBPPPGE1vInnngCV69eFf+uVKkSatWqJWmbI0eOxJIlS7Bo0SJMmzatxPMLFizA4MGDMXLkSADA+PHjcfDgQSxYsABxcXGoXLkyAKBcuXKoUqWKwf34+/ujefPmYrIsJSUFbdu2hbe3N9q0aYOUlBTUqVMHKSkpaNGiBfz8/AAAM2fOFLcRGRmJAwcO4Ouvv8YLL7yAgIAA+Pr6Ii8vT2vf69evR5kyZbBq1SpxdsbVq1ejXLlySElJQZcuXcQyrVq1SkyekX2xGyYRSaLbTcTcZFh8vPQul6zEExGRu3CXlutE5D4UOhl8QRC0lo0ePRq7d++WtC1vb2/MmjUL8+fPx/Xr10s8f/LkSbRp00ZrWZs2bXDy5Emzyx0XFyd2k0xJSUGHDh0AALGxsVrLO3bsKL5m+fLliImJQeXKlREQEICVK1eaHJ/tyJEj+PPPPxEYGIiAgAAEBASgQoUKePDgAc6ePSuu9+STTzJR5kBMlhGRFs4yRkREZF9MmBGRK6hUqRI8PDy0WpEBwLVr10q0NjPHyy+/jIiICMyZM0fv86aSc1LFxcXh9OnTuHTpElJTUxEbGwvgcbIsKysL586dEwf3//rrrzFu3DgMHToUP/zwA9LT0zFkyBCTg/EXFRWhWbNmSE9P13qcPn0aL730krievm6nZD/shklEBknpaqlUKg0+X5oxVIiIiNyJZjw156YVJ8ohIrnw8vJCs2bNsGvXLsTHx4vLd+3ahd69e1u83TJlyiAhIQF9+vTBG2+8ofVcgwYNsH//fgwcOFBcduDAATRo0ED829PTE4WFhSb307p1a3h7e+Pzzz/H/fv30axZMwBATEwMsrOzsWLFCvj4+KBly5YAgH379qF169ZiF1AAWi3DgOJjorvvp556Cps3b0ZISAiCgoIkHgWyN4e2LFu2bBkaNWqEoKAgBAUFoVWrVvj++++11jl58iR69eqF4OBgBAYGomXLlkabNW7duhUxMTEoV64c/P390aRJE63ZMIDiAQXVs1GoH8b6LxO5O2N3vA1V6OPjmSgjchTGVyLXph7agIkyIpKb8ePHY9WqVfjiiy9w8uRJjBs3DllZWRgxYoS4zqeffoqnn37arO326NEDLVq0wIoVK7SWT5w4EWvWrMHy5ctx5swZLFq0CFu3bsWECRPEdSIiIrB7925cvXoVt27dMrgPX19ftGjRAkuXLkWbNm3EyQA8PT3RqlUrLF26VEyoAUDt2rVx+PBh7Ny5E6dPn8a0adOQlpamtc2IiAgcP34cp06dwvXr15Gfn48BAwagUqVK6N27N/bt24dz584hNTUVb731Fv7++2+zjgvZjkNbllWvXh0ffvghateuDQBYu3YtevfujaNHjyI6Ohpnz55F27ZtMWzYMMycORPBwcE4efIkfHx8DG6zQoUKeO+991C/fn14eXmJs2GEhISga9eu4nrR0dH48ccfxb8NzYpBpEnfgPe2eI0jGZqly1yJicWvY0WeyP4YX4mci7mxtjQxluOCEpEt9evXDzdu3MCsWbNw5coVNGzYEN999x3Cw8PFda5fv16iBZYU8+bNQ+vWrbWWKZVKLFmyBPPnz8eYMWMQGRmJ1atXi+ONAcDChQsxfvx4rFy5EtWqVTM6C2dcXBz27t2r9XqguCvmjz/+KHbBBIARI0YgPT0d/fr1g0KhQP/+/TFy5EitG5TDhw9HSkoKYmJicPfuXezZswcdOnTA3r178c4776BPnz64c+cOqlWrhqeffpotzWREIchsDtIKFSpg/vz5GDZsGF588UV4enqWuHNtrqeeego9evTA7NmzARTf+VapVEhPT7d4mzk5OQgODkZ2dja/0G5EtzIrJfnlbMkyXaUdv4wVeXImrnxud5b4Crj250Cuy9J4X5o4yxhLzoTndukePHiAc+fOITIy0uiNLCIyjzm/LdkM8F9YWIhNmzYhNzcXrVq1QlFREZKSklC3bl107doVISEhaNGihVkVCkEQsHv3bpw6dQrt27fXeu7MmTOoWrUqIiMj8eKLL+Kvv/4yuq28vDzk5ORoPYiMjeWlb6B8Dp5vGivxRNYl9/gKMMYS2QtjLBERkTQOT5ZlZGQgICAA3t7eGDFiBBITExEVFYVr167h7t27+PDDD9GtWzf88MMPiI+PR58+fZCammp0m9nZ2QgICICXlxd69OiBpUuXonPnzuLzLVq0wJdffomdO3di5cqVuHr1Klq3bo0bN24Y3GZCQgKCg4PFR1hYmNWOATk3Jr+sh5V4IutxlvgKMMaSa1AqleJDKtYhiIiI5Mnh3TAfPnyIrKws3L59G1u2bMGqVauQmpqKcuXKoVq1aujfvz82btwort+rVy/4+/vjq6++MrjNoqIi/PXXX7h79y52796N2bNnQ6VSleh3rJabm4tatWph0qRJGD9+vN518vLykJeXJ/6dk5ODsLAwNiN2Q/oqtuaM8+VsXTHt2Q2TyTJyNFfqIuIs8RVgjCX3Ze+hDhhnyZFcKcbaGrthEtmGOb8thw7wDxRPpaoegDgmJgZpaWlYsmQJli5dirJlyyIqKkprffXUsMaUKVNG3GaTJk1w8uRJJCQkGKzM+/v748knn8SZM2cMbtPb21uc9YLIFM3p33WXOxtD74WI5M1Z4ivAGEvuizGWiIhInhzeDVOXIAjIy8uDl5cXmjdvjlOnTmk9f/r0aa2ZNMzZpiF5eXk4efIkQkNDLSozkT7mdsVwJrZ4X4mJ+sd5IyLrYHwlcg62qjuwVRkREZF0Dm1Z9u6776J79+4ICwvDnTt3sGnTJqSkpCA5ORkAMHHiRPTr1w/t27dHXFwckpOTsX37dqSkpIjbGDhwIKpVq4aEhAQAxeOexMTEoFatWnj48CG+++47fPnll1i2bJn4mgkTJuDZZ59FjRo1cO3aNcyZMwc5OTkYNGiQXd8/uQdXuGusr+JuTtdTIrIvxlci56SOrZox1lrxVaFgwoyIiEgqhybL/vnnH7zyyiu4cuUKgoOD0ahRIyQnJ4uDBcfHx2P58uVISEjAmDFjUK9ePWzZsgVt27YVt5GVlYUyZR43kMvNzcXIkSPx999/w9fXF/Xr18f69evRr18/cZ2///4b/fv3x/Xr11G5cmW0bNkSBw8eNPuOOrknS+74umoLM03q92hppT4+XslKPJGVML6SXGjGBHeIhbZgrZtujLFERETSOXyAf2fFASqJ9FNX6JVKJRQK817LsxE5Gs/t8sDPwXUwWWYeQ8dLX7KMg/uTs+G5XToO8E9kG041wD8RuRYmyYiIiEzTvLlky6EMGGOJiIjMx2QZEZlkTssAcxNl6tewMk9E5Ho0u+jLoZWZHMqgWw5TibLSJtIYY4mIiMwnu9kwich5WZAngyCwEk9E5Mo4AYx5jM2mrdn1MjFRZXJbjLFEZG979+7Fs88+i6pVq0KhUJQqBpw4cQIvvPACKleuDG9vb9SpUwfTpk3DvXv3rFdgC/3xxx9QKBQ4dOiQ1vIWLVrA29tbq4wPHz6En58f/u///k/Stkt73Mg6mCwjIqsRwIo5ERE5B93WbvakTojpS4rplklzXSkJMiJybQqFfR/mys3NRePGjfHpp5+W6n0ePHgQLVq0wMOHD5GUlITTp0/jgw8+wNq1a9G5c2c8fPiwVNsvrfr16yM0NBR79uwRl929exdHjx5FSEgIDhw4IC4/dOgQ7t+/j7i4OLuWMT8/3677czVMlhGRScYq9aVlSRC2B/VFlO6DiIjMY6v4YQm5lMNeLL3YJSKyVPfu3TFnzhz06dPH4m0IgoBhw4ahQYMG2Lp1K/7zn/8gPDwczz//PLZv345ffvkFH3/8sbi+QqHAsmXL0L17d/j6+iIyMhLffPON1jYvXbqEfv36oXz58qhYsSJ69+6N8+fPi88PHjwYSqUSCxYsQGhoKCpWrIhRo0YZTTh16NABKSkp4t/79u1D3bp10atXL63lKSkpqFatGurUqYO0tDR07twZlSpVQnBwMGJjY/Hbb7+J60ZERAAonrlcoVCIfwPA9u3b0axZM/j4+KBmzZqYOXMmCgoKtI7D8uXL0bt3b/j7+2POnDkSjzjpw2QZETkUW6EREbkHW954Mbccupzhhoi+8plqacbW3kQkRzNmzNBKAulKT09HZmYmxo8fjzJltFMWjRs3RqdOnfDVV19pLZ82bRr69u2LY8eO4eWXX0b//v1x8uRJAMC9e/cQFxeHgIAA7N27F/v370dAQAC6deum1UJtz549OHv2LPbs2YO1a9dizZo1WLNmjcFyxsXFYf/+/WLCas+ePejQoQNiY2O1Wpzt2bNHbFV2584dDBo0CPv27cPBgwdRp04dPPPMM7hz5w4AIC0tDQCwevVqXLlyRfx7586dePnllzFmzBhkZmZixYoVWLNmDebOnatVpunTp6N3797IyMjA0KFDDZadTOMA/0RkE4LwuGJv7vT2REREtuTohJ0mfbNhGkvcmTN7Jgf3JyI5qlSpEmrVqmXw+dOnTwMAGjRooPf5Bg0aYP/+/VrLnn/+ebz66qsAgNmzZ2PXrl1YunQpPv/8c2zatAllypTBqlWroHjU3Hb16tUoV64cUlJS0KVLFwBA+fLl8emnn8LDwwP169dHjx49sHv3bgwfPlxvOTp06IDc3FykpaWhVatWSElJwcSJE9G+fXu88soruHfvHsqWLYuDBw+K3VI7duyotY0VK1agfPnySE1NRc+ePVG5cmUAQLly5VClShVxvblz52Ly5MkYNGgQAKBmzZqYPXs2Jk2ahOnTp4vrvfTSS0ySWQmTZUQyJZcZuyylUACJiY4uheX0XYw44+dARESuRWqi7HGrM6WNSkJEZJnRo0dj9OjRFr9eEAQx6aXWqlWrEn+np6cDAI4cOYI///wTgYGBWus8ePAAZ8+eFf+Ojo6Gh4eH+HdoaCgyMjIMlqNOnTqoXr06UlJSEB0djaNHjyI2NhYhISGIjIzEzz//DG9vb9y/f19Mkl27dg3vv/8+fvrpJ/zzzz8oLCzEvXv3kJWVZfQ9HzlyBGlpaVotyQoLC/HgwQPcu3cPfn5+AICYmBij2yHpmCwjIpsQBEChUDq6GKXC5BgRkXtQn+8ddaNK3/6JiNxV3bp1AQCZmZlo0qRJief/+OMP1KlTx+R21Am1oqIiNGvWDBs2bCixjrolFwB4enqWeH1RUZHRfXTo0AF79uxBo0aNUKdOHYSEhACA2BXT29sb4eHhYrfTwYMH499//8XixYsRHh4Ob29vtGrVyuSEBUVFRZg5c6beseB8fHzEf/v7+xvdDknHMcuIiIiIiHQ4OnFV2mRdfLzjx4cjIrJEkyZNUL9+fXz88cclklXHjh3Djz/+iP79+2stP3jwYIm/69evDwB46qmncObMGYSEhKB27dpaj+Dg4FKVNS4uDgcOHMCuXbvQoUMHcXlsbCxSUlKQkpKi1fVy3759GDNmDJ555hlER0fD29sb169f19qmp6cnCgsLtZY99dRTOHXqVIny165du8S4bmQdPKpEZHVSZ9/iOCpERCQnjk4uaU6CUNpkHWMsETnC3bt3kZ6eLnaBPHfuHNLT07W6GX766ad4+umnDW5DoVBg1apVyMzMRN++ffHrr78iKysL33zzDZ599lm0atUKY8eO1XrNN998gy+++AKnT5/G9OnT8euvv4pdPQcMGIBKlSqhd+/e2LdvH86dO4fU1FS89dZb+Pvvv0v1fuPi4pCbm4svvvgCsbGx4vLY2FgcPnwYBw8eFAf3B4DatWtj3bp1OHnyJA4dOoQBAwbA19dXa5sRERHYvXs3rl69ilu3bgEA3n//fXz55ZeYMWMGTpw4gZMnT2Lz5s2YOnVqqcpPhjFZRiRTcpk1zNY4pT0REZFljE2gI/XGFRGRNR0+fBhNmzZF06ZNAQDjx49H06ZN8f7774vrXL9+XWusMH3atGmDgwcPwsPDA8888wxq166NKVOmYNCgQdi1axe8vb211p85cyY2bdqERo0aYe3atdiwYQOioqIAAH5+fti7dy9q1KiBPn36oEGDBhg6dCju37+PoKCgUr3fyMhIhIeH486dO1rJsmrVqqFGjRp48OCBVrLsiy++wK1bt9C0aVO88sorGDNmjNh1U23hwoXYtWsXwsLCxOPYtWtX7NixA7t27ULz5s3RsmVLLFq0COHh4aUqPxmmEATed7JETk4OgoODkZ2dXeofGJGrklpJ51mI5ILndnng5+A46tZMrn6jxhS5HgdDrc2MJc0YY0kueG6X7sGDBzh37hwiIyO1xqMi/RQKBRITE2V3zib5Mee3xQH+ichmBAFIysxFz2gONElERM6DF1xERETujd0wicimekQZT5TxjjcRkXxodv9XqVQOH+SeHtNs7aabzEtMVOl9DWMsERGRZdiyjIgcSt1VkxV6IiIi62KMJSJ3wJGlyBaYLCNyYpp3/OXYZSQpMxc9ovwhCBxkmIiIqDQ04zxb/BEREdkWk2VEZDM9ovyZJCMiclJyvAlD2owN7K9JoWDrMiIiInMwWUYOJ/fWUVQ6UluVqVuhERERkWG6rcrU45VJTZwRERGRaUyWkayoVComzFyAbgJUfTdbX9JMXcnPPw0gSmnrohEREbkMzYH99SXNtAf+V4KIiIikYbKMHIbjbZSesyUWOXYZERGRcbZqcc+umERERNIxWUZEVqeu3JubGGPLQiIiIttgooyIiEi6Mo4uABG5LnXFXBCAHSdy9a7DMVaIiIikUyqV4sNUDI2PL17Hs25n+xSOiMgJnT9/HgqFAunp6ZJfM3jwYIfe5P/jjz/QsmVL+Pj4oEmTJg4rhytjsoyIbEqdMOsR5W/wrrZmxZ+IiIikEQTTXTUFAW47gY5KpRIfRGQfCQkJaN68OQIDAxESEgKlUolTp06ZvZ0OHTpAoVBAoVDA29sbdevWxQcffIDCwsJSlU9fkissLAxXrlxBw4YNS7VtXStWrEDjxo3h7++PcuXKoWnTppg3b55Vtj19+nT4+/vj1KlT2L17t1W2aa4XX3wR3bt311r2/fffQ6FQYNq0aVrLZ8+ejapVq0ra7owZM2SRAGQ3THIYJkbck75xyzgTJhERUTGlUml2csdYncqdY6wlx5JI7pIy9ffWsBVzzx+pqakYNWoUmjdvjoKCArz33nvo0qULMjMz4e9v3raGDx+OWbNm4cGDB9ixYwfGjBkDDw8PvPPOO2ZtBwAKCwuhMDBGjIeHB6pUqWL2No3573//i/Hjx+OTTz5BbGws8vLycPz4cWRmZpZquw8fPoSXlxfOnj2LHj16IDw83EolNl9cXBwmTJiAgoIClC1bnFpKSUlBWFgY9uzZo7VuSkoK4uLi7Fq+/Px8eHp6Wvx6s1uW5eXlYd++fVi3bh1WrFiBrVu34ty5cxYXgIjIXSvxRLoYY4kIgFVbW7t7jGXLdSL7Sk5OxuDBgxEdHY3GjRtj9erVyMrKwpEjR8zelp+fH6pUqYKIiAiMHj0aTz/9tJgAX7RoEZ588kn4+/sjLCwMI0eOxN27d8XXrlmzBuXKlcOOHTsQFRUFb29vDBkyBGvXrsW3334rtlpLSUkp0Q2zsLAQw4YNQ2RkJHx9fVGvXj0sWbLErLJv374dL7zwAoYNG4batWsjOjoa/fv3x+zZs8V1OnTogLFjx2q9TqlUYvDgweLfERERmDNnDgYPHozg4GAMHz4cCoUCR44cwaxZs6BQKDBjxgwAwDvvvIO6devCz88PNWvWxLRp05Cfn6+1/W3btiEmJgY+Pj6oVKkS+vTpIz738OFDTJo0CdWqVYO/vz9atGiBlJQUg+8xLi4Od+/exeHDh8VlKSkpmDx5MtLS0nDv3j1xu7/88ouYLDNWzjVr1mDmzJk4duyY+BmtWbMGAJCdnY3XXnsNISEhCAoKQseOHXHs2DFx3+oWaV988QVq1qwJb29vCKUYsFNyy7IDBw5g6dKlUKlUePjwIcqVKwdfX1/cvHkTeXl5qFmzJl577TWMGDECgYGBFheISJetZoUix+BsmEQlMcYSkTXoi7GcBZOIHCk7OxsAUKFCBXHZjBkzsGbNGpw/f96sbfn6+uLWrVsAgDJlyuCTTz5BREQEzp07h5EjR2LSpEn4/PPPxfXv3buHhIQErFq1ChUrVkSVKlXw4MED5OTkYPXq1WK5Ll++rLWfoqIiVK9eHV9//TUqVaqEAwcO4LXXXkNoaCheeOEFSWWtUqUKUlNTceHChVK3/po/fz6mTZuGqVOnAgDmzZuHTp06oVu3bpgwYQICAgIAAIGBgVizZg2qVq2KjIwMDB8+HIGBgZg0aRIAICkpCX369MF7772HdevW4eHDh0hKShL3M2TIEJw/fx6bNm1C1apVkZiYiG7duiEjIwN16tQpUa66deuiatWq2LNnD1q2bIk7d+7gt99+w44dO/Dpp5/i559/RufOnXHw4EHcv39fTJYZK2e/fv3w+++/Izk5GT/++CMAIDg4GIIgoEePHqhQoQK+++47BAcHY8WKFXj66adx+vRp8fv1559/4uuvv8aWLVvg4eFRquMuqWVZ79698dxzz6FatWrYuXMn7ty5gxs3buDvv//GvXv3cObMGUydOhW7d+9G3bp1sWvXrlIVikiNTeddl+aA//ZuTk4kJ4yxRGRLhibYISKyNUEQMH78eLRt21ZrPLBKlSqhVq1akrdTVFSE5ORk7Ny5E08//TQAYOzYsYiLi0NkZCQ6duyI2bNn4+uvv9Z6XX5+Pj7//HO0bt0a9erVQ3BwMHx9feHt7Y0qVaqgSpUq8PLyKrE/T09PzJw5E82bN0dkZCQGDBiAwYMHl9i+MdOnT0e5cuUQERGBevXqia8vKiqSvA21jh07YsKECahduzZq166NKlWqoGzZsggICECVKlXEZNnUqVPRunVrRERE4Nlnn8Xbb7+tVea5c+fixRdfxMyZM9GgQQM0btwY7777LgDg7Nmz+Oqrr/DNN9+gXbt2qFWrFiZMmIC2bduKiUV9OnToILY+27dvH+rWrYvKlSsjNjZWXK7umqn+zI2V09fXFwEBAShbtqz4Gfn6+mLPnj3IyMjAN998g5iYGNSpUwcLFixAuXLl8L///U8sz8OHD7Fu3To0bdoUjRo1Mtj1VgpJLcu6dOmCb775Ru8XCQBq1qyJmjVrYtCgQThx4kSJzCwRuR99LQI1z1XaA/67dxcRcm+MsURkLnWM1WxxrxljtVuSMcYSkWOMHj0ax48fx/79+0ssHz16tMnXf/7551i1ahUePnwIAHjllVcwffp0AMCePXvwwQcfIDMzEzk5OSgoKMCDBw+Qm5srjo3m5eWFRo0aWVT25cuXY9WqVbhw4QLu37+Phw8fmjXofGhoKH755Rf8/vvvSE1NxYEDBzBo0CCsWrUKycnJKFNG+ohYMTExktb73//+h8WLF+PPP//E3bt3UVBQgKCgIPH59PR0DB8+XO9rf/vtNwiCgLp162otz8vLQ8WKFQ3uMy4uDmPHjkV+fj5SUlLQoUMHAEBsbCyWLl0KoDhZ1rFjR8nl1OfIkSO4e/duibLcv38fZ8+eFf8ODw9H5cqVjW5LKknJslGjRkneYHR0NKKjoy0uEBG5HpVKpXd6e3YNIWKMJSLz6La6N3TTXL2ccZaIHOHNN9/Etm3bsHfvXlSvXt2ibQwYMADvvfcevL29UbVqVbFb3YULF/DMM89gxIgRmD17NipUqID9+/dj2LBhWmN0+fr6WtSy6Ouvv8a4ceOwcOFCtGrVCoGBgZg/fz4OHTpk9rYaNmyIhg0bYtSoUdi/fz/atWuH1NRUxMXFoUyZMiXG1NIdYwyApIkRDh48KLYa69q1K4KDg7Fp0yYsXLhQXMfX19fg64uKiuDh4YEjR46U6L6obrmmT1xcHHJzc5GWloY9e/Zg4sSJAIqTZQMHDsTNmzfxyy+/YNCgQZLLaah8oaGhesdQK1eunPhvcyeRMIazYRKR3bHiTkREVHqmrgHV8VZfSzQiIlsQBAFvvvkmEhMTkZKSgsjISIu3FRwcjNq1a5dYfvjwYRQUFGDhwoViCy2pXSS9vLxQWFhodJ19+/ahdevWGDlypLhMs/WSpaKiogAAubnF3eMrV66MK1euiM8XFhbi999/t2jWyJ9//hnh4eF47733xGUXLlzQWqdRo0bYvXs3hgwZUuL1TZs2RWFhIa5du4Z27dpJ3m+tWrUQFhaGbdu2IT09HbGxsQCKW9ZFRERg4cKFePDggfiepJRT32f01FNP4erVqyhbtiwiIiIkl680JLf9O3PmDLp06YKWLVsanRGByFZYwXMu6tmn4uOVJVqVaVbuOeA/EWMsEUknpT6kjq2MsURkb6NGjcL69euxceNGBAYG4urVq7h69Sru378vrvPpp5+KY49ZolatWigoKMDSpUvx119/Yd26dVi+fLmk10ZEROD48eM4deoUrl+/rrclV+3atXH48GHs3LkTp0+fxrRp05CWlmZWGd944w3Mnj0bP//8My5cuICDBw9i4MCBqFy5Mlq1agWgeCyypKQkJCUl4Y8//sDIkSNx+/Zts/ajWeasrCxs2rQJZ8+exSeffILExEStdaZPn46vvvoK06dPx8mTJ5GRkYGPPvoIQPFg/QMGDMDAgQPF2djT0tIwb948fPfdd0b3HRcXh88//xy1a9fGE088IS5Xd8WsWbMmatSoIbmc6kkb0tPTcf36deTl5aFTp05o1aoVlEoldu7cifPnz+PAgQOYOnWq1myc1iQ5WTZs2DD06dMHS5YsQd++fVFQUGCTAhFpUidcmChzPeweQvQYYywRmUNq3Ug3xqpUKk6eREQ2tWzZMmRnZ6NDhw4IDQ0VH5s3bxbXuX79eqlaajVp0gSLFi3CvHnz0LBhQ2zYsAEJCQmSXjt8+HDUq1cPMTExqFy5Mn7++ecS64wYMQJ9+vRBv3790KJFC9y4cUOrlZkUnTp1wsGDB/H888+jbt266Nu3L3x8fLB7925x3K2hQ4di0KBBGDhwIGJjYxEZGWlRqzKgeMKocePGYfTo0WjSpAkOHDiAadOmaa3ToUMHfPPNN9i2bRuaNGmCjh07anUtXb16NQYOHIi3334b9erVQ69evXDo0CGEhYUZ3XdcXBzu3LkjjlemFhsbizt37mi9Jynl7Nu3L7p164a4uDhUrlwZX331FRQKBb777ju0b98eQ4cORd26dfHiiy/i/PnzWgk6a1IIup1kDQgLC8P27dvRsGFD+Pn54fLly6hUqZJNCuUMcnJyEBwcjOzsbJOD0RG5M2N3tZkoI7lx1LmdMVYbYyyRcUmZuegZbXxcFn2JMjXehCRH4LldugcPHuDcuXOIjIyEj4+Po4tD5DLM+W1JHrPs1VdfxYgRIxAaGopOnTq5dSWeiEwzlSRj1xCixxhjicgQ3fHGdBNliYkqrfWVSqXeGMsEGRERkXSSk2XTp09Hp06dcPv2bXTt2tWWZSIiJ2bwbrcAwOC09kTujTGWiEzRbBmmM7xLCYyxREREpWPWbJht2rSxVTmIyEWoE2XqO93qwf0F8T9EpA9jLBHpMnd8MbYeIyIisg7JA/ybQ+IwaETkgnR//oKg/w43BxkmsgxjLJF7YKKMiIjIcSQlyxo0aICNGzfi4cOHRtc7c+YM3njjDcybN88qhSMiInJ1jLFEVBqcNZyIiMj6JHXD/Oyzz/DOO+9g1KhR6NKlC2JiYlC1alX4+Pjg1q1byMzMxP79+5GZmYnRo0ebPa0qEbkWQQDUN8T13RlXV+wVCo6rQsQYS0SloVKp9CbLGGOJiIgspxDM6M9x4MABbN68GXv37sX58+dx//59VKpUCU2bNkXXrl3x8ssvo1y5cjYsrnxw6mMi/dhthJyZI8/tjLGPMcYSFTN0w0l3uW4sVc+GyWQZyQnP7dI9ePAA586dQ2RkJHx8fBxdHCKXYc5vy6wB/lu3bo3WrVuXqnBE5Lo4BhmR5RhjiUiXvsSYPgpFyWWCwNZlREREljIrWUZEZIihyrx6NkxNmjNlshJPRERkmlKpRFJmbol4qy/OAvoTaERERCQNk2VEZHeaFXt1pZ/dMYmIiLTpJsZ6RPlDdVr663lDioiIyDJMlhGRVehLdqlUKiQmqgze9SYiIqLSMRZnOXYZERGRZco4ugBERERERO5EpVKJD3OxJTaRe1PY+WGuhIQENG/eHIGBgQgJCYFSqcSpU6e01hk8eDAUCoXWo2XLluLzN2/exJtvvol69erBz88PNWrUwJgxY5CdnW12efbs2YO4uDhUqFABfn5+qFOnDgYNGoSCggIL3p11DR48GJMnTwYAKBQKjv8sM0yWEZFFTFXypZzs1WOXERERkWVMtd5mqzIisqfU1FSMGjUKBw8exK5du1BQUIAuXbogNzdXa71u3brhypUr4uO7774Tn7t8+TIuX76MBQsWICMjA2vWrEFycjKGDRtmVllOnDiB7t27o3nz5ti7dy8yMjKwdOlSeHp6oqioyCrv11JFRUVISkpC7969HVoOMsyiZNnZs2cxdepU9O/fH9euXQMAJCcn48SJE1YtHBERkbthjCUiNaVSKT6IiJxBcnIyBg8ejOjoaDRu3BirV69GVlYWjhw5orWet7c3qlSpIj4qVKggPtewYUNs2bIFzz77LGrVqoWOHTti7ty52L59u1ktwnbt2oXQ0FB89NFHaNiwIWrVqoVu3bph1apV8PLyAgCsWbMG5cqVw86dO9GgQQMEBASIiTy1oqIizJo1C9WrV4e3tzeaNGmC5ORk8fm+ffvizTffFP8eO3YsFAqFWHcrKChAYGAgdu7cKa7z888/o0yZMmjRooXesv/999948cUXUaFCBfj7+yMmJgaHDh0Sn9++fTuaNWsGHx8f1KxZEzNnzpRFazlXYnayLDU1FU8++SQOHTqErVu34u7duwCA48ePY/r06VYvIBHJk6nKu1KpRHy80uAdb7YqIyqJMZaIiIhcibrrpGYyDABSUlIQEhKCunXrYvjw4eINQmPbCQoKQtmyj4dd79ChAwYPHmzwNVWqVMGVK1ewd+9eo9u+d+8eFixYgHXr1mHv3r3IysrChAkTxOeXLFmChQsXYsGCBTh+/Di6du2KXr164cyZM2I5UlJSxPVTU1NRqVIlpKamAgDS0tLw4MEDtGnTRlxn27ZtePbZZ1GmTMmUzN27dxEbG4vLly9j27ZtOHbsGCZNmiS2htu5cydefvlljBkzBpmZmVixYgXWrFmDuXPnGn2fZB6zk2WTJ0/GnDlzsGvXLjEbCwBxcXH45ZdfrFo4IiIid8IYS+QeStNiTHOYA2NdMAWBXTCJyLEEQcD48ePRtm1bNGzYUFzevXt3bNiwAT/99BMWLlyItLQ0dOzYEXl5eXq3c+PGDcyePRuvv/661vIaNWogNDTU4P6ff/559O/fH7GxsQgNDUV8fDw+/fRT5OTkaK2Xn5+P5cuXIyYmBk899RRGjx6N3bt3i88vWLAA77zzDl588UXUq1cP8+bNQ5MmTbB48WIAxcmyEydO4Pr167h16xZOnDiBsWPHigm0lJQUNGvWDAEBAeI2t23bZrAL5saNG/Hvv/9CpVKhbdu2qF27Nl544QW0atUKADB37lxMnjwZgwYNQs2aNdG5c2fMnj0bK1asMHgsyHxmz4aZkZGBjRs3llheuXJl3LhxwyqFIiLnpwAAAZJGBmX3EqJijLFEpKZOimnGSHMGf1YomCwjIscaPXo0jh8/jv3792st79evn/jvhg0bIiYmBuHh4UhKSkKfPn201s3JyUGPHj0QFRVVopX9l19+aXT/Hh4eWL16NebMmYOffvoJBw8exNy5czFv3jz8+uuvYqLNz88PtWrVEl8XGhoqtnTLycnB5cuXtVqFAUCbNm1w7Ngx8T1UrFgRqamp8PT0ROPGjdGrVy988sknAIqTZbGxseJrT548ib///hudOnXSW+709HQ0bdq0RGs8tSNHjiAtLU2rJVlhYSEePHiAe/fuwc/Pz+hxIWnMTpaVK1cOV65cQWRkpNbyo0ePolq1alYrGBE5H61KvIkBh5kgIyqJMZaIAP1JMXMSZUySEZGjvfnmm9i2bRv27t2L6tWrG103NDQU4eHhYrdGtTt37qBbt24ICAhAYmIiPD09LSpLtWrV8Morr+CVV17BnDlzULduXSxfvhwzZ84EgBLbVSgUEHROpAqFdgsAQRDEZQqFAu3bt0dKSgq8vLzQoUMHNGzYEIWFhcjIyMCBAwcwduxY8bXbtm1D586d4evrq7e8hparFRUVYebMmSUSiwDg4+Nj9LUkndndMF966SW88847uHr1KhQKBYqKivDzzz9jwoQJGDhwoC3KSERE5BYYY4nIGhQSWnUTEdmCIAgYPXo0tm7dip9++qnEDUB9bty4gYsXL2p1qczJyUGXLl3g5eWFbdu2WS0JVL58eYSGhpaYndOQoKAgVK1atUTruAMHDqBBgwbi3+pxy1JSUtChQwcoFAq0a9cOCxYswP3797Vapn377bfo1auXwX02atQI6enpuHnzpt7nn3rqKZw6dQq1a9cu8dA3BhpZxuyWZXPnzsXgwYNRrVo1CIKAqKgoFBYW4qWXXsLUqVNtUUYichJsLUZUOoyxRAToj6dKpdKs8cqIiBxh1KhR2LhxI7799lsEBgbi6tWrAIDg4GD4+vri7t27mDFjBvr27YvQ0FCcP38e7777LipVqoT4+HgAxS3KunTpgnv37mH9+vXIyckRxxmrXLkyPDw8AAADBw5EtWrVkJCQoLcsK1asQHp6OuLj41GrVi08ePAAX375JU6cOIGlS5dKfk8TJ07E9OnTUatWLTRp0gSrV69Geno6NmzYIK7ToUMHvPXWWyhbtizatWsnLnv77bfx1FNPISgoCABw7do1pKWlGW0t3L9/f3zwwQdQKpVISEhAaGgojh49iqpVq6JVq1Z4//330bNnT4SFheH5559HmTJlcPz4cWRkZGDOnDmS3xcZZ3ayzNPTExs2bMCsWbNw9OhRFBUVoWnTpqhTp44tykdETsjUHe3ERBXU8YEJNqLHGGOJSE3zQspkrNQZI5TjlRG5Lrn/tJctWwagOFGkafXq1Rg8eDA8PDyQkZGBL7/8Erdv30ZoaCji4uKwefNmBAYGAigek+vQoUMAgNq1a2tt59y5c4iIiAAAZGVlGW1J9Z///Af79+/HiBEjcPnyZQQEBCA6OhoqlUprDDFTxowZg5ycHLz99tu4du0aoqKisG3bNq36WcOGDVGpUiWEh4eLibHY2FgUFhZq7Wv79u1o0aIFQkJCDO7Py8sLP/zwA95++20888wzKCgoQFRUFD777DMAQNeuXbFjxw7MmjULH330ETw9PVG/fn28+uqrkt8TmaYQdDvjkiQ5OTkIDg4Wp7Alosf0JcsE4fHyxESVuJzJMpITntvlgZ8DUclkmb5WCOrWZTtO5KJntL/Wc6zhk9zw3C7dgwcPcO7cOURGRnIMKhfTq1cvtG3bFpMmTXJ0UdySOb8tSS3Lxo8fL3nnixYtkrwuEbkeQ63K1Mt3nMhF/unifzNRRsQYS0SmmRrcn4kyIiLn0LZtW/Tv39/RxSAJJCXLjh49qvX3kSNHUFhYiHr16gEATp8+DQ8PDzRr1sz6JSQip6FSqZCYaHwclZ7R/khMfLy+GhNn5K4YY4ncl24STDMWqv9tKFFmLNYqIP+uWkRE7ogtypyHpGTZnj17xH8vWrQIgYGBWLt2LcqXLw8AuHXrFoYMGSIOZEdERETSMMYSkdUxW0ZERFQqZs8runDhQiQkJIiVeKB4+tU5c+Zg4cKFZm1r2bJlaNSoEYKCghAUFIRWrVrh+++/11rn5MmT6NWrF4KDgxEYGIiWLVsiKyvL4DZXrlyJdu3aoXz58ihfvjw6deqEX3/9VWudhIQENG/eHIGBgQgJCYFSqcSpU6fMKjsRPaZQFD/i45VG73Tro1Qq2aqM6BFrxVjGVyLnICX+mRtXiYiIqPTMTpbl5OTgn3/+KbH82rVruHPnjlnbql69Oj788EMcPnwYhw8fRseOHdG7d2+cOHECAHD27Fm0bdsW9evXR0pKCo4dO4Zp06YZHYgtJSUF/fv3x549e/DLL7+gRo0a6NKlCy5duiSuk5qailGjRuHgwYPYtWsXCgoK0KVLF+Tm5ppVfiIiImuyVoxlfCVyHuqbRgYTZxa0EOOYZURERKVj9myYAwcORGpqKhYuXIiWLVsCAA4ePIiJEyeiffv2WLt2bakKVKFCBcyfPx/Dhg3Diy++CE9PT6xbt87i7RUWFqJ8+fL49NNPMXDgQL3r/PvvvwgJCUFqairat28vabuczYWomKEB/fURBOPjsxA5mqPP7baMsc4SXwHHfw5EciJ1zDLNWafVfxPJCc/t0nE2TCLbsPpsmJqWL1+OCRMm4OWXX0Z+fn7xRsqWxbBhwzB//nzLSoziSvc333yD3NxctGrVCkVFRUhKSsKkSZPQtWtXHD16FJGRkZgyZYpZF9f37t1Dfn4+KlSoYHCd7OxsADC6Tl5eHvLy8sS/c3JyJJfBHXCgdjcmoHhsFCIqNVvEWLnHV4AxlkiTqZkvybWpP3/Wp4mIHMvsbph+fn74/PPPcePGDRw9ehS//fYbbt68ic8//xz+/v6mN6AjIyMDAQEB8Pb2xogRI5CYmIioqChcu3YNd+/exYcffohu3brhhx9+QHx8PPr06YPU1FTJ2588eTKqVauGTp066X1eEASMHz8ebdu2RcOGDQ1uJyEhAcHBweIjLCzM7PdK5KxUKpX4KIGJMnIhO/9wbHdBa8ZYZ4mvAGMskbni9SRS1K3KBIGtypwVE6VERPJhdssyNX9/fzRq1KjUBahXrx7S09Nx+/ZtbNmyBYMGDUJqairKlSsHAOjduzfGjRsHAGjSpAkOHDiA5cuXIzY21uS2P/roI3z11VdISUkx2MRu9OjROH78OPbv3290W1OmTMH48ePFv3NycliZJ7enUM+2ZSRhlpioEv+tWQfkHVOSo671zb/pYwvWiLHOEl8Bxlgis/FGFRGR1axZswZjx47F7du3bbqflJQUxMXF4datW2J9jOTL7GRZXFwcFEYGKfrpp5/M2p6Xlxdq164NAIiJiUFaWhqWLFmCpUuXomzZsoiKitJav0GDBpIq3gsWLMAHH3yAH3/80eAFx5tvvolt27Zh7969qF69utHteXt7w9vbW+K7cj9MfLg2zc+3RPcAB1TY2UWBXJU1Y6yzxFeAMZbImhQKtiwjIsdJSEjA1q1b8ccff8DX1xetW7fGvHnzUK9ePXGdwYMHlxiHtUWLFjh48KD49+uvv44ff/wRly9fRkBAgLid+vXrm12mPXv2YP78+Th06BDu37+PiIgIdO/eHePHj0e1atUsf7Pk0sxOljVp0kTr7/z8fKSnp+P333/HoEGDSl0gQRCQl5cHLy8vNG/evMSU86dPn0Z4eLjRbcyfPx9z5szBzp07ERMTo3cfb775JhITE5GSkoLIyMhSl5vI3Ugd2D8+XqnVusxS+hJkKpWKCTNyKbaMsc4cX9WNWIncgam4qTuwvybdQf7JuUit03CsYPdm7+665n7H1DNjN2/eHAUFBXjvvffQpUsXZGZmag0p0a1bN6xevVr828vLS2s7zZo1w4ABA1CjRg3cvHkTM2bMQJcuXXDu3Dl4eHhILs+KFSswcuRIDBo0CFu2bEFERASysrLw5ZdfYuHChVi0aJFZ74/ch9nJso8//ljv8hkzZuDu3btmbevdd99F9+7dERYWhjt37mDTpk1ISUlBcnIyAGDixIno168f2rdvj7i4OCQnJ2P79u1ISUkRtzFw4EBUq1YNCQkJAIq7hkybNg0bN25EREQErl69CgAICAhAQEAAAGDUqFHYuHEjvv32WwQGBorrBAcHw9fX16z3oMaKPLkbcyrkmhV7ayTOiFyVtWKsK8VXlUqFRAAq8KKQ3EPxzNH6n/Os21nS68l98MYhyY26rqG2evVqhISE4MiRI1ozY3t7e6NKlSoGt/Paa6+J/46IiMCcOXPQuHFjnD9/HrVq1ZJUlr///htjxozBmDFjtOpYERERaN++vdFul8uWLcOCBQtw8eJFREZGYurUqXjllVcAAOfPn0dkZCSOHj0q3ui8ffs2ypcvjz179qBDhw4AgO+++w5jx47FxYsX0bJlyxI3Pi9cuIDRo0dj//79ePjwISIiIjB//nw888wzkt4f2ZbZA/wb8vLLL+OLL74w6zX//PMPXnnlFdSrVw9PP/00Dh06hOTkZHTuXFwRiI+Px/Lly/HRRx/hySefxKpVq7Blyxa0bdtW3EZWVhauXLki/v3555/j4cOHeO655xAaGio+FixYIK6zbNkyZGdno0OHDlrrbN682ez3vWPHDgBMlJHzMziAvw6lUgmlUll8AWtB4kv9+tJQb4OVQ3IX5sZYV4ivwOMYS+SuNG82xccr0TNKHuMqEhFJZWhm7JSUFISEhKBu3boYPnw4rl27ZnAbubm5WL16NSIjI7XGNO3QoQMGDx5s8HXffPMNHj58iEmTJul93tC4YYmJiXjrrbfw9ttv4/fff8frr7+OIUOGYM+ePQb3pevixYvo06cPnnnmGaSnp+PVV1/F5MmTtdYZNWoU8vLysHfvXmRkZGDevHniDUhyPIsH+Nf1yy+/GBzk15D//ve/JtcZOnQohg4davB5zbvgQHGW1xSBt9zsik3FXUtpmn6X5qfH7w65M3NjrCvFV3VynshdFLfaVop/xyuVj8cHZRdLInIihmbG7t69O55//nmEh4fj3LlzmDZtGjp27IgjR45ojWH6+eefY9KkScjNzUX9+vWxa9cure6aNWrUQGhoqMH9nzlzBkFBQUbX0WfBggUYPHgwRo4cCQAYP348Dh48iAULFiAuLk7SNpYtW4aaNWvi448/hkKhQL169cSEmFpWVhb69u2LJ598EgBQs2ZNs8pJtmV2sqxPnz5afwuCgCtXruDw4cOYNm2a1QpGRPZh6WD5xsZM0ScxUSV2K2Hii+RETteejLH68ZxBrsJUzNV7PpJ4kuK9YPck9/OjQvwP8KiBEbkRQzNj9+vXT/x3w4YNERMTg/DwcCQlJWnVhQYMGIDOnTvjypUrWLBgAV544QX8/PPP4g3EL7/80uj+BUEwOnGSISdPntTqBgoAbdq0wZIlS8zaRsuWLbX236pVK611xowZgzfeeAM//PADOnXqhL59+5Z6NnSyHrOTZUFBQVofeJkyZVCvXj3MmjULXbp0sWrhnEHPnj0dXQQiq5GSOFMqlRw8mGRPXTk3dPGoOc6k5io5AIJtWTATGGO1McY6F7YkLz0BliXweUOK7EkdpqQkaAXxP0BOjq1KRHJkzszYoaGhCA8Px5kzZ7SWBwcHIzg4GHXq1EHLli1Rvnx5JCYmon///pLKULduXWRnZ+PKlStmty7TTbJpJt7KlCkjLlPLz88vsb4pr776Krp27YqkpCT88MMPSEhIwMKFC/Hmm2+aVVayDbOTZWvWrLFBMciVsdImb/x8yNWIiTAjdRS5NsBgjCVyXexOTNbmiDqcwsiNKCLAspmxb9y4gYsXL5pMaKln9pbqueeew+TJk/HRRx/pnUTp9u3bescta9CgAfbv34+BAweKyw4cOIAGDRoAACpXrgwAuHLlCpo2bQoASE9P19pGVFRUifP+wYMHS+wrLCwMI0aMwIgRIzBlyhSsXLmSyTKZMHuA/5o1a+LGjRsllt++fZt9bIlIEl4wkK1ImZlYzg0jGWOJ3Jul5yfNoREYY12fIyY5SsrMBWA6USbnGEv2MWrUKKxfvx4bN24UZ8a+evUq7t+/DwC4e/cuJkyYgF9++QXnz59HSkoKnn32WVSqVAnx8fEAgL/++gsJCQk4cuQIsrKy8Msvv+CFF16Ar6+v1kyRAwcOxJQpUwyWJSwsDB9//DGWLFmCYcOGITU1FRcuXMDPP/+M119/HbNnz9b7uokTJ2LNmjVYvnw5zpw5g0WLFmHr1q2YMGECAMDX1xctW7bEhx9+iMzMTOzduxdTp07V2saIESNw9uxZjB8/HqdOncLGjRtL3BQdO3Ysdu7ciXPnzuG3337DTz/9JCbkyPHMbll2/vx5FBYWlliel5eHS5cuWaVQROQYpipe6tbI6lkwzR23TJOlY6UR6aNOkjn7zW7GWHJmPJ8bJzXGEslNcWsyzsRK0ixbtgxA8UyVmlavXo3BgwfDw8MDGRkZ+PLLL3H79m2EhoYiLi4OmzdvRmBgIADAx8cH+/btw+LFi3Hr1i088cQTaN++PQ4cOICQkBBxm1lZWWKXSENGjhyJunXrYsGCBYiPj8f9+/cRERGBnj17Yvz48Xpfo1QqsWTJEsyfPx9jxoxBZGQkVq9erfWevvjiCwwdOhQxMTGoV68ePvroI60hM2rUqIEtW7Zg3Lhx+Pzzz/Gf//wHH3zwgdbkSoWFhRg1ahT+/vtvBAUFoVu3bnpbwJFjKASJU1dt27YNQPEXZ+3atQgOfjyqS2FhIXbv3o1du3bh1KlTtimpzOTk5CA4OBgbNmzASy+95OjiENmVOtFlySD/unhxRaVhrCWZ5nOa16DGgp763J6dnY2goCBrFFESxlhtmjHWz8+P5wlyO5YkzjRjbHy8kl3lqNTUX0N9XyV1jFXo/GHse+eoGOuMHjx4gHPnziEyMtKs2bCJyDhzfluSW5apK6oKhQKDBg3Ses7T0xMRERFYuHCh+aUlIqdgjW4d8fHKEgkzlUrFC2GyiJQul2pyv2ZkjCVyb5ox1tJW26Vp7U2kS+rYZFpjhMo92BIRmUFysqyoqAgAEBkZibS0NFSqVMlmhXImnKmL3IG+RBkr5eQo6u+jYCLJ6kx1dsZYw5hMJ2dkzlADthpjjAOxk6WkfHf41SIiV2f2AP/nzp1jJZ6ILBav58KBgxG7J5VKpfWw5PWuhjG2JEu/H0RyYO53lzeiyNGYZCUiKiapZdknn3yC1157DT4+Pvjkk0+MrjtmzBirFIyI5IuVeTKXrZIdrjBRBGMsERHJBRNlRETFJCXLPv74YwwYMAA+Pj5GZ2dQKBSsyBORcQoAiY4uBNmTNRNlChR3v3SllkaMsUTuTalxTktMVFn1hhRbCZE5zBkLlIjI1UlKlp07d07vv4mo9DQv+p2hdYw1KvHxSiUSXSjZQYZZO6llqBLvzC3MGGONc8bPlExzttjnzJIyc9Ejyt/RxSCZY6KMiEib5AH+1WbNmoUJEybAz89Pa/n9+/cxf/58vP/++1YrHBHJAy9kSArFoznmbdWKQV2RT8rMNbqeMyfOGGO1cRIdclbmnn8ez4hrvTI8PhczUUYSMFtGRKTF7AH+Z86cibt375ZYfu/ePcycOdMqhSJyd3Id0NpqlXid7ThjUoMeUyj0J8pK+x029DvoEeVv8Dsjx9+NORhjSarSTI4hJzz/P2bNRFliomt8P8iOmCgjItJidssyQRCg0BPNjx07hgoVKlilUETuRHOsEkOVWjm0lFGpVEhM5OD+VJI6QVbc4qu4BYM1EmW6/xbc4KKaMZbcBZNkRPLCXBkRkTbJybLy5ctDoVBAoVCgbt26WpX5wsJC3L17FyNGjLBJIYlcnVLmA5bLuWwkH/mnd0F12vLXm/qeufL3kDGWzMVkk2uxZqsyoPjGVmKiyrobJSIiciOSk2WLFy+GIAgYOnQoZs6cieDgYPE5Ly8vREREoFWrVjYpJJE70L3w0ew+oX6OAyKTXLlyIsseGGOpNBgbnNfjz05p9W3Hxys5EyZJwuHKnEudOnXsur8zZ86YtX5CQgK2bt2KP/74A76+vmjdujXmzZuHevXqiesMHjwYa9eu1XpdixYtcPDgQfHvDh06IDU1VWudfv36YdOmTWaVR6FQwNvbG6dOnUJ4eLi4XKlUoly5clizZo1Z29OkWUYvLy9UqlQJTz31FIYMGYI+ffqYta0ZM2ZApVIhPT3d4vKQdUlOlg0aNAgAEBkZidatW8PT09NmhSJyd7qJB32JCJVKZbeLIna9JGfkTAkExljnI4fu8eQ6EhNVNo21znQ+JCLnlpqailGjRqF58+YoKCjAe++9hy5duiAzMxP+/o8nHOnWrRtWr14t/u3l5VViW8OHD8esWbPEv319fS0qk0KhwPvvv18iQWcN6jLm5+fj0qVLSExMxIsvvojBgwfj//7v/6y+P7Ifswf4j42NFSvx9+/fR05OjtaDiGzLVSq58fFKKJVKl3k/JG/O0vKNMZYsoT6X8nzqXJzlvESOx8kayJkkJydj8ODBiI6ORuPGjbF69WpkZWXhyJEjWut5e3ujSpUq4kPf2Kx+fn5a62i2vDfHm2++ifXr1yMjI8PgOnl5eRgzZgxCQkLg4+ODtm3bIi0tzeS21WUMCwtDy5YtMW/ePKxYsQIrV67Ejz/+KK73zjvvoG7duvDz80PNmjUxbdo05OfnAwDWrFmDmTNn4tixY+KwHOoWb4sWLcKTTz4Jf39/hIWFYeTIkXongyLrMztZdu/ePYwePRohISEICAhA+fLltR5EVHqmLnxc5aLIykO0kAPp+07K7TvqDLMHMsY6D/V3Xu7fKbIvuX0f1GOhMaHqGuT03SKSKjs7GwBKJMNSUlIQEhKCunXrYvjw4bh27VqJ127YsAGVKlVCdHQ0JkyYgDt37mg936FDBwwePNhkGVq3bo2ePXtiypQpBteZNGkStmzZgrVr1+K3335D7dq10bVrV9y8eVPCu9Q2aNAglC9fHlu3bhWXBQYGYs2aNcjMzMSSJUuwcuVKfPzxxwCKu5e+/fbbiI6OxpUrV3DlyhX069cPAFCmTBl88skn+P3337F27Vr89NNPmDRpktllIvOZnSybOHEifvrpJ3z++efw9vbGqlWrMHPmTFStWhVffvmlLcpI5NbkULlNTFSJD6tuU2YXFVR6jv6uOjvGWCLXICW26Z4vbTEgv74xy5zhxgHZD8crI1sSBAHjx49H27Zt0bBhQ3F59+7dsWHDBvz0009YuHAh0tLS0LFjR+Tl5YnrDBgwAF999RVSUlIwbdo0bNmypcQ4YDVq1EBoaKiksiQkJCA5ORn79u0r8Vxubi6WLVuG+fPno3v37oiKisLKlSvh6+uL//73v2a/7zJlyqBu3bo4f/68uGzq1Klo3bo1IiIi8Oyzz+Ltt9/G119/DaC4e2lAQADKli0rtqJTdzkdO3Ys4uLiEBkZiY4dO2L27Nni68i2JI9ZprZ9+3Z8+eWX6NChA4YOHYp27dqhdu3aCA8Px4YNGzBgwABblJPI7ekO8m/tpATHMyFb0Dc5BRnGGOt8eL4ka1InzDhWKGmy5XmGiTKypdGjR+P48ePYv3+/1nJ1qykAaNiwIWJiYhAeHo6kpCQxITZ8+HCtderUqYOYmBj89ttveOqppwDArBuJUVFRGDhwIN555x0cOHBA67mzZ88iPz8fbdq0EZd5enriP//5D06ePCn9DWsQBEFrdvP//e9/WLx4Mf7880/cvXsXBQUFCAoKMrmdPXv24IMPPkBmZiZycnJQUFCABw8eIDc3V2sMOLI+s1uW3bx5E5GRkQCAoKAgsVli27ZtsXfvXuuWjohkQbP7hi1n1uKdbtcgh9aQzooxlsi9GOoeaY1WZprx2lBrMsZc98bhMMiW3nzzTWzbtg179uxB9erVja4bGhqK8PBwozNvPvXUU/D09DR7dk5NM2fOxNGjR0uc+4RHJ0zN5JZ6ue4yKQoLC3HmzBmxTnfw4EG8+OKL6N69O3bs2IGjR4/ivffew8OHD41u58KFC3jmmWfQsGFDbNmyBUeOHMFnn30GAOJ4Z2Q7ZifLatasKTYnjIqKEpsAbt++HeXKlbNm2YhID1slIswZz8TaCTPdCjwr72Rrcu2GxBhLZD59lzGO+n1rxlFz92/t2G7B9R25EXa/JFsRBAGjR4/G1q1b8dNPP4kJI2Nu3LiBixcvGu1SeeLECeTn50vudqlPWFgYRo8ejXfffReFhYXi8tq1a8PLy0urBVx+fj4OHz6MBg0amL2ftWvX4tatW+jbty8A4Oeff0Z4eDjee+89xMTEoE6dOrhw4YLWa7y8vLTKBACHDx9GQUEBFi5ciJYtW6Ju3bq4fPmy2eUhy5idLBsyZAiOHTsGAJgyZYo4rsq4ceMwceJEqxeQiOTHHhVwuSUxqHTk3NpMTt81xlgi8xm74JdjUtwYpVKJ+Hil3bphyvW8TLbFRBnZ0qhRo7B+/Xps3LgRgYGBuHr1Kq5evYr79+8DAO7evYsJEybgl19+wfnz55GSkoJnn30WlSpVQnx8PIDibpGzZs3C4cOHcf78eXz33Xd4/vnn0bRpU62ukgMHDjQ6aL8+U6ZMweXLl7VmqvT398cbb7yBiRMnIjk5GZmZmRg+fDju3buHYcOGGd3evXv3cPXqVfz99984dOgQ3nnnHYwYMQJvvPEG4uLiABQn47KysrBp0yacPXsWn3zyCRITE7W2ExERgXPnziE9PR3Xr19HXl4eatWqhYKCAixduhR//fUX1q1bh+XLl5v1fslyZo9ZNm7cOPHfcXFx+OOPP3D48GHUqlULjRs3tmrhiFyJQmFeiyz1+ua+zhKGxivTt5x3qslScr5gVZetY8eODi0HYyyRZXRjpanWXQoFsONELnpG+5c6xuqLlaZiqSHWjrGPt6fU27VTpVIxYeZG1EkyJsrIlpYtWwageKZKTatXr8bgwYPh4eGBjIwMfPnll7h9+zZCQ0MRFxeHzZs3IzAwEEBxK6vdu3djyZIluHv3LsLCwtCjRw9Mnz4dHh4e4jazsrJQpox57X8qVKiAd955B++++67W8g8//BBFRUV45ZVXcOfOHcTExGDnzp0mZyNfuXIlVq5cCS8vL1SsWBHNmjXD5s2bxcQfAPTu3Rvjxo3D6NGjkZeXhx49emDatGmYMWOGuE7fvn2xdetWxMXF4fbt2+LxWrRoEebNm4cpU6agffv2SEhIwMCBA816z2QZhSBY5zL84sWLmD59Or744gtrbE72cnJyEBwcjOzsbEkD8xEBjyutur+6pMxc9IjyL7GOvkqzIDxe3xqJNH0XEkqlEgpFyTFT1MutReqYLKzIuwY5J8vU7t27hwEDBsju3M4YS2SaoRirGStNxVh9TMVZY8kwYzFW3w0xW9+QMhR3GWfJHnhul+7Bgwc4d+4cIiMj4ePj4+jiELkMc35bZnfDNOTmzZtYu3attTZH5FbUiS/NSrKhCrNCAfSM9pe0rj6aXVIMJS9UKpXeCjVblRE5BmMskeXUSSlL4uaOE7kWxz5Dr1PHWPXz6rIxxhIREcmH2d0wichyuhV23TvdljD2WmMteQw9p1Qq9T7n6Gns7dEdlWzL0HeLiMgadGPsjhOPW2Fbqme0v8l1NFuKaZ7jdIajEddVr6N5U8peMVbffuw15AM5HscqIyKSzmoty4jIfKW5k5yYqBIf+iq4liYl7Dl+idSLA95tdx1y7+rTs2dPRxeBiKxEtxW2pYwlkTTjuKl9yfH8p9kdlbGWiIjoMSbLiCyUlJkLwHh3Sd0uH7aqiKq7Vmo+SkuzUu/oVmUA73i7CrYsIyIpTCVw7BljDXWT1Lc/zXip+W/NmKqbNHNkjNV8D4yzbsBOCVFnm4WWiEgfyd0w+/TpY/T527dvl7YsRE5Fs2uGsQq6LSrvUgfGt5Tm7FlSylCain58vP4ZuvRt09DgzUSaTM2CJ0eMsUQlSWnxZO/WUOpZNNWT8uhjKGEGaLbk0l7uaJotzBhjyVo42yoROTPJybLg4GCTz3MKU3JVpmarklqxdGQXB80Ke2mTbbZO1mnuQ11u9bFLTFRBnQNhBYx0lfY7sWPHDusUxEyMsWSIsZkWXYVTxFgBYqscKeOYGSLXro66rfSYMHM9CvBzdUYCPzQiqzLnNyU5WbZ69WqLCkNka/au1JWmy4KhQXRtXXnWvbNtSUswYwmyxESVTVqXmVMGIsB0azK5tjpjjCW5smeMTcrM1UpEySrGyjTJZQu8NndRDhjd31UT/Pbg6ekJALh37x58fX0dXBoi1/Hw4UMAgIeHh8l1ORsmOb3iad39tSrJ1qrcG5tm3tLt27MSamkCSzcpZY/xVKQmzAytzwoZmSLXRBmRMY4+t+mLrbaLsZYnykr7OirG1tuuia3KnI+HhwfKlSuHa9euAQD8/PygkGvTVCInUVRUhH///Rd+fn4oW9Z0KozJMnIpmmNuqO9Q63btsEZ3DmtXODTLLYW9BwM2lcSyeXk0ur+osZUZSaFUKiUlx6SuR+RudFtT644j5oox1m0JAFSP/+QYZq5B/O7zc3Q6VapUAQAxYUZEpVemTBnUqFFDUvKZyTJyej2i/PXe6dY3AL+UCp++3436dbbsjiKXyrwjk1C6rcXEJNyj4xKvVCJRT0KDd79JH90EmO5Aw5rPM1FGpJ+U+McY6yIUABK1F6lbmjHOOidHjT/H74t1KBQKhIaGIiQkBPn5+Y4uDpFL8PLyQpkyZSSty2QZuQxDFWFrVo6t2f2ESjKZqFMA8RoziKnXVyc6WDmTNz3XYQ7FBBmRcZrxjjHWPYg3qfSM+8bPRd50hyRjbth1eHh4SBpfiYisi8kyshp7NdfXN2uWte4YW2tcMku5851vfYkyR4ydRrYVr1SWqMzray1YWoYSp6YSZD179rR6WYisobTdHs3Zz44TuVqttq25bU2MsfanO9N0CcKjc7IK4t0NpVLJRKaTKDGGPz8vIiKLMVlGVqOuSOkmr6w5CHtpK7nGEnpSK/G2rihqdkdxFqWdDdOc/RjDFmbypvvTESv1NhgvTN93gS3JyJntOJGrd3gBze+1tWJsjyh/reVSk0yMsTImPBqSTPXoT0OfqZ4mwI+/Y0obFY6sQd9Ph7kyIiLLMVlGVvW4WxyQmGi9lkDGKrXq2TA16d55N/ScOevYk5wq8ebOUlma/WgedyY2bE/zGOsef1uz11dcd5wyQ9Tr5OTk2LZA5LZ0z2nmJrbUCSxrxQfNVkKmtmlqnDF9y429njHWAR7dndD83pnb0q64LqA0sRbJgaJEEzMiIjKXtJHNiBxA3UrNWCVbodAeyF8fY5Vyfdt3d/HxSq0kp6MG/FcqlRa3kuBnaj5BKJ5B1q771Ph3aT5vInehFc+scCEsJcaaKgdjrHMTBPOSlyqVip+pzCkAsSUhERFZTiEIjr6/55xycnIQHByM7OxsBAUFObo4sqLVWkWpBAyMcWFq7IukzFyTiTBDpNzZlvo6R3F0ZdSSJJklLQmlHHNLW5kx+WKcse5b1uzapcvYDW9btCg0pyvmvXv3MGDAAJ7bHYwx1jgxPghgjLWQo2OsrWmOTSb1uOsbPsMYxlh5knOjMp7biciZsBsmWZ1W5elRxctQpV3f8scV2JKVeENdBqTeCZdyl5zsw5xjrrRwTCuOYWac1OMitSujFI6oxFuz/ERyoNsFUqtLJR7/xvRNiPMYY6yr0kx2WdJ10l7DL5D1sfslEZH1MFlGWpIyc0sM7FsampVnQ5Voc+7umqrE6/vb2Ppyn9nJFWfuelwBV5r1OksTZmQd1kg8Svkqq7dvq89aX/n5vSJ7sXbMMRRjNX9rjLEklSCYdz60ZQtkMh+7XxIRWReTZQ4mt4qGNRNltmZJBVzzNUmZuRAE+b5fRyfKpNxZ1u12aWhKen3bsWdrH7Ywk8ZWSSPNHmPmskeSlIlYshfNFmHWSCIVjzNomzhW2hgr90SZ7uyiroCtwdxTaWIsEREZxgH+SS9zWoPpW8cZBvWVe2LQ0cdPaqVb38XQjhOPB4q3ZuWdyS7no+4RUppKfGk/d35vSK6kxljd9dTLeso4jsk5UQaYnhxILjTjqdZg/I/+n5ioEh/6mHv+4/nSOSRl5kIB68RYIiLSjy3LXFBpWtHoTiUvpbKrbgFlq4qxo1tYuTJDLcGkULc8U6mAxER165zi5/JP70JiomXbNcXW3fScnW5rVXNarxo6thadSx7939LTgu4+jU1AIHUbRI5Wmhir9zlI695sjCu2sHJmup+3Op5qns8TEwGogHgzhzOQiq1t5avEuL7MkhER2QyTZQ5mz4s5UxfAmhV3UwkqzQSZvgGGNbdJljH0GWjePS7N7JOa3wfdpJmU1mC66+irWNuqS4hC8ehiwUyuPNB7UmYu8k/v0lrmqIsdOfzsLW1NsXHjRusXhqzK2A0hOXe5VijUrYT8TSao1Od/zfX0vTdrxFi5t7K2Fc0YW9q4qrtdoPSfjZQbhaZirLm/g9LEDI4rb3t6vw6KR8eeB5+IyOqYLLMzW49RZqyiY2p/+ipmpu5861ufrMdQZV4tMVFlVsVeuxKvNNiyzNA2zR38N16pRKINEjalScJZo9WU3Gi+J/Vnp++z0r3YlvpZ6lvP5HF7dOWke06wVoXeWMuH0nymPXv2tPi15Fia3wfNxLhcEmjaCbLi/6sTYvoSVomJKuSfBnQnQ7F2nHXnuK2v3lOaFtelTZRp3rDULAvgBK2pFUDSo++y3Merc2q6zUkf/a3+zvG4ExFZD8csI5GxsVM0W48lZebarSKkW5FVj8uhOYaHq9Mao0SP0owtZgmlUgmlUgnPup1N79M6uyxB30WMulzmUqlU8r8IkUjzuNjyAtjQcVaPnyJW5PX0xbT1hbnU74D6c3eVz96dSP2ty+3zNdSSrGe0f4kYq6/c8fFKm3Rtd3eCUHxsS5tMtXadyBFJTGPHwNTx2XEi9/EYelZqXUeP6T2Wevph85gTEVkPW5bZmWZrCN3WINaoaNnqzrlm0kpd4bdHQNbcR3FLmeJ/55/eBUQpbV8AF2ZO6yz1uirV4++Ybpc/fWx5oWrt77ozd9FUl1t3Jjprb9+QpEwDXcrUFXkzW6xaq1xSyaXlEZlP8xzjWbczekT5yypBJpVujLWkm7k1y+Bu5DjmanGZlADUQw+ozN6GJXFNqVRadI7uEeVffMrXaFVs6zFt3Yr6GGp+n4zc5OYxJyIqPbYskwk5TPctdaBhezPVsspd6FZ4TbUw0DxmxlriaW7H2IxaaoZaPVjC0u0Y+z6UJuHhjBfZmi2kNMuvbi1h7HWllZRZ/L0yOPaSoUHJZdDqwNKWiCRf+ad3GRwvz5zPWv29tjZJcezROupWZPZoSaYZY9X/dteYGx+vRLxSqdWd3Vya3x99LeONxdikzFy93z9DMdyWN0jNpTVrq+aM6m6chHUUdZKSx52IqHSYLJMRKV1GjK1T2qAo5fX2Dry6FTZ3v7hVX+BLaYmo+VmZO4CzsW2bsy1HfV7ukDAzdC7QTZgZGwTdFEMJJXUl3NIZ9FiBJ1sRUDxWoibN77CUONsjyr94uAGd5faIsfaeHcNdk2KA/u+CoNGtzdJjIyVGGtp2z2h/va83tE17xyt1TDAUY/W+L7Zysg49rbQNrsoYS0RkFeyG6QCmpuRWN5uXMhB5aZpa685mKbcuGIbel7snzIDHx0bdXcIUfd8TfTNf6ju2Uma9NMRZEk+uRt/g5lJY8tuy9JyhUqmQmPi4a7UzJlbJ8fR9fgIAxaMbCuoxNtUtttS9G9W/Ec0x9sQWjwCEKP9SzzKnG2NNzYBpb0xg2EZxy7DHn7O+lmTF52VlieXO/JkYLLtO3VJ38hmegyXSMz6ZyZc48feJiEgOmCxzEEsuZDVpzpD4eBNKrcq5qVksdZ83dtHr6BZlZJjUJKeUdXTHN7FH92BbjRVmKiltjDOPX2Zr1jgXGLp45DEna9G8IE9MBKDSv16iSgUkFt880Pxuaw0LpND/bykzRWsmTowlypwtxlo0Q65M6SZuNI+NOqkvpTvs48/QNgnR0tYbrU23PAbrnTq/meLx1x4v45iREjFRRkRkd0yWOZihyo+h7lXmVdiss569McCbT3dgd33JCM3vjvYxtjypZC22qiyXJmFG+hlqHWNouRzGYyTSpXuuSUyUFl+l0IytcmpJpsYYW8yc+KB7HjNnzFBDuzD3O+cMN39M1SvVz8st8UdERKQPk2UyYdWLeuHxpDn6yDVJRvZR2gslY12E5VjxdfeEme54TVLW06V9zih58V/c3U17mblJMrYqIGvT/O3rngdKe05w94STvvOKM7YQMlVWe8cPZ57F0JyhPCyd3ZOIiMiemCyTESmVMt07kbqthRQK44kyzfXkyFkriXJS3P3o8d/qiwFzZ5DU3Y7u+ta8gLDVxZU7J8nMGcTfFM1WY+pxoDT/Bh63oGGSjJyVqZY+koY4AGOsM9M3lpaheKevtZktj685cdce51VDZZHy/TdUTyHr4O+ciMg6HDob5rJly9CoUSMEBQUhKCgIrVq1wvfff6+1zsmTJ9GrVy8EBwcjMDAQLVu2RFZWltHtbtmyBVFRUfD29kZUVBQSNQdHAHDnzh2MHTsW4eHh8PX1RevWrZGWlmb192eu0l7YqysnpsYek2slnqzH1IxVltK8kCzNPnRf485JLUeS+tmpE2E7TuQCMH92VWP42dsG42sx9TnKGt8zKTEWbhhjNWOBqyY9dN+jvpsC6gSFepZN9cNS+l4v5+OrWVYpyRpX/85Yk7nnFHc7BxER2YpDk2XVq1fHhx9+iMOHD+Pw4cPo2LEjevfujRMnTgAAzp49i7Zt26J+/fpISUnBsWPHMG3aNPj4+Bjc5i+//IJ+/frhlVdewbFjx/DKK6/ghRdewKFDh8R1Xn31VezatQvr1q1DRkYGunTpgk6dOuHSpUs2f8/2oi9Qyrl5vyDIt2zuSm9lS8/FgCYplV5HV4yl7l/zPbpixVPqcSgeoLz496mZJONvVt4YX6WJj1daNFYZYyzZkjW7DNuK9K77xvEmrmnm/nb5Wycisg6FIMjrlFqhQgXMnz8fw4YNw4svvghPT0+sW7dO8uv79euHnJwcrTvo3bp1Q/ny5fHVV1/h/v37CAwMxLfffosePXqI6zRp0gQ9e/bEnDlzJO0nJycHwcHByM7ORlBQkPQ3aIKUwdml0DfTJbuGkFSas61KYcmYZfZKmunrVmPuxYejE3zGWHohJfU9qb8Lhn6j1riQk9PxtdW5XQ6cJb4C1v8cDH1PLR3UnzFWm77zrLuSek409N3TF3edLcYC0n4LrPtJZ+65Ra7H1pVjLBG5HtmMWVZYWIhvvvkGubm5aNWqFYqKipCUlIRJkyaha9euOHr0KCIjIzFlyhSjFYBffvkF48aN01rWtWtXLF68GABQUFCAwsLCEnfPfX19sX//foPbzcvLQ15envh3Tk6O+W9SguLKtnYTf1vM0OUo6rGPpIz9Qs5Drne+Ade8cLPn8bZVAsAVPxe5knt8BWwfYw0lG9SxtjRxVlL3TDvT/N0yztqHockkpDJ2c0ruMVZf+aTEDn5HpTHn3MJjSURkPQ7thgkAGRkZCAgIgLe3N0aMGIHExERERUXh2rVruHv3Lj788EN069YNP/zwA+Lj49GnTx+kpqYa3N7Vq1fxxBNPaC174okncPXqVQBAYGAgWrVqhdmzZ+Py5csoLCzE+vXrcejQIVy5csXgdhMSEhAcHCw+wsLCrHMA9BCE4sqHuvKemKgye9BszcAqpwp8jyh/MZAzoJOjuHuixtz3b+i3asmphWPU2I+zxFfAfjHWWt89OSbIAO3ulux66RhSElvWugkqF4bO64LweKxLzdmn1Mv4HTVObucXIiJ34/BkWb169ZCeno6DBw/ijTfewKBBg5CZmYmioiIAQO/evTFu3Dg0adIEkydPRs+ePbF8+XKj21ToRBdBELSWrVu3DoIgoFq1avD29sYnn3yCl156CR4eHga3OWXKFGRnZ4uPixcvluJdm1baVldyrHzIsUxkf3JJlsihDO7E0rGhyHLOEl8B+8ZYfb99c29IqckprjmyLBysXV7k9DmIY10+Ok3sOJGLnlH+pqduJ1l37SYicgcO74bp5eWF2rVrAwBiYmKQlpaGJUuWYOnSpShbtiyioqK01m/QoIHR7hxVqlQR73KrXbt2TetueK1atZCamorc3Fzk5OQgNDQU/fr1Q2RkpMHtent7w9vb25K3aLHi8cssf61cgqycLibINDl8Z+RGLuPxyK0rTqKZY/PwXGBfzhJfAcfEWF3mdMksXldZYnxHRySE+btyPHPOzbb+jsgpUaZPjyh/7MgsHpJDgcff36TMx8N0kGV1MR47IiLrcnjLMl2CICAvLw9eXl5o3rw5Tp06pfX86dOnER4ebvD1rVq1wq5du7SW/fDDD2jdunWJdf39/REaGopbt25h586d6N27t3XehBWoA158vFKrS6Y5HJn0UDetZ+B2PpqfmTUr9Wx1YF/GjrU1km6WnF8465ljMb5KI7WVmaO/y4yxTspNPjNDvw+FAugZ7S92xVQoHiXKopgoU7P03MIYS0RkXQ5tWfbuu++ie/fuCAsLw507d7Bp0yakpKQgOTkZADBx4kT069cP7du3R1xcHJKTk7F9+3akpKSI2xg4cCCqVauGhIQEAMBbb72F9u3bY968eejduze+/fZb/Pjjj1p3y3fu3AlBEFCvXj38+eefmDhxIurVq4chQ4bY9f2bollp0Py3nAMhKzrOz9Lvl25yRm6toPSJj1da3P1K7kwdf5VKZXHy0th3RHOsRV08P9gP46tt6d5IsFeLMv6G5Mms2SrNnG3aknLIgfq7aihe9Iz2F//dI8rfXXKIJpWmjs/zAxGRdTk0WfbPP//glVdewZUrVxAcHIxGjRohOTkZnTt3BgDEx8dj+fLlSEhIwJgxY1CvXj1s2bIFbdu2FbeRlZWFMmUeN5Br3bo1Nm3ahKlTp2LatGmoVasWNm/ejBYtWojrZGdnY8qUKfj7779RoUIF9O3bF3PnzoWnp6f93rwLYpB2frqVNEEApNT99VXQLZ0RTM7seSEi12MntSLP8ckci/HVOH2/Zc3fXGKiSnbfYcZY52PPOOioRJmxYQqSMnMB+MOQHSdyH49pRgBKJlHldh4iInInCkFg9csSOTk5CA4ORnZ2NoKCguy6b4X4H8fjt8f1aCZDipNlKqPry+lOtjk036fUO/yuliyz5P2UtmWr3M8Zjjy302OO+hw0f3fxSqXjY61Q3GsvKZNJBWei/h7pSx6pW1RZu2WZnJJl6m6V6t+PvjF0BaH46R38bov0xX1zk2WMsURE1uPwAf7JAgYq7+rKiFwG9ifno/u9Kc0kE/Zg6cD7TJQ55sJK7pV4Ii0mYq09qH8yTCa4Bs2uh6Whef62drwwN64a6oK6IzMXPfF4HDLd301SZi52gN9ta2KMJSKyLibLnJBcgqFcykG2of58jdXDNbuYOEMLMyaRi5XmszI3UaBev3gwZ14Ukbxp/jYEoWSLLnueQxhjnZfUJJM1El32jr3GkmkKBYozvNH+eicy0L6pWzzIP1tNEhGRXMluNkyynLoSz4QAuRtTFwvGZoiS43gg5lz82PtCydzzi/rCiBdD5Iz0JcrsEWMTE1WyHbeQLKP7tbHWZDpyIH5XBTx+owr9CV/1MvV4ZYwNj2l+tvHxSsn1E86MS0RkG2xZ5iLsnSBjKxHXoztWmZqxu9+OvpiTetFgalYua+3HmqTMLirnSRRYcSdXwptQVGp6YqzUlttyotnt0lDXSzXNoUF0Y0KPKH+2KtPDnLESGWeJiGyLLcvIItYad4Pkw1ilS453si1h6D2aunsrhwsWpVIpKYFGRERkKXWssaSFs1biSyh+aLbI1Ew6MwFtgJmJMn1JSyIisg62LCOL8G6Wa3KXz1Xzfaor7PHxSqOD/atUKocnDa0x4UJp3wMnECF3k5Rp/5bUjj7XkPXpO3facqB+WzNWdq0Yq/M6zWPA1mUlMcYSEckHk2VEJIm+izdnqtyru4EY65Ip94SZIBjvtmOMtcotpRLvLklXcg+8kCdr0XdutHRWZzlSqVTYcaIz1MllKfFCasJMX1dOV8REGRGRfDBZ5uQYVMmR5DqmiprmTJ3WqmTrq7DbqxIv52OtyV0uasj1McaSIzlL8kxdTs0xyqTQnABGnTBzZIx1Rs7yHSEickZMlsmAK91VJPfjDN9Z3RZhxiry6vHLjLUw0yTXir2tEpmSLoR4UUMyxFhLZFuaM11qjW2rOUumDt2E2Y4TAPRMEqD7Gs39uRJ2wyQikg8my4jI7UipjBob9F/3tbp/W6sCr9kyzhK2SAhIqsQrwIQZkYMxOWgfhmYqlsoVP5sSXSpNxA2F4nGCbceJ3EfjBD4i+Isv35GZi55R/i6ZJFNjooyISD6YLJMBZ6woyaHlDJE5dC9oEhNNz4JpicREFVSq4m2X5jeiWV7NpJm+C2B7ds/kXW9yVnLvNq6ptDFW9306erxFd1Oa413amySOoi53aWOfOmEm0og3PVH8nEJnRnZXqo8KwqO3zDhLRORwTJY5MV6wEhln75nGNLtuJiaqoFA83r+hyry+CyNDs15KvQCz9UWWqYSZK124kGsx57fhrDHWWRKCrsKZkrD2UuK3o44J+pY/WtYz2l+MLZoJsx0niluTqdfrEeUvvm7HCcPjnDkzI71WiYjIjpgsI7srbZcFotKyRYsyfRITVUb3pa/1WPHrDG9TX3LN3Is1V7uwICJyJGu28lWfz521hZk+OzIfj2EmjmemGYMeZYc0k2zqBNmOE7ni/3tGFyfG1K/VWgculjQzkjFzmfdIRCRzTJbJnCMqS+ogbOiuui2CNLuIkC1pXsAYS16VGJTYCuxVqdWXMNP9W/0bs2aZdCdC4O+YnIkjxvXSbA2jj63OGYyztmeL4+sKSTN1XC1uOfYoxqq//8aaUQmPu15qJtt6QCPZJgDqCQFcKolk4JioE4NERGR7TJY5CblUctVN5F2qQkJu7/H32d9kstiY+Hil5Fk0TbGkpUJpzhGGEmv6qI+Ntd4rkSM4qutcicHPNdgrxnLwf3mz9xAC1qBUKiUlgLVirGaiTP1vze/+o797avxm1K3SWA0lIiJbY7KMzGKLMVxYUSd7s+UFqW7CzFatAsxJbpm7LWPbV6lURruJEpHl1DE2KTPXaFLNGMZUsjd1PNWMrcZirFiX1KxT6i7TTZoBjwf+zwQUj8Y1s/R34qzc7f0SETkSk2VOwt6VX1sObMzBcMne9H3njCXKTA1eb+x5c1pbWfN3bUnyzBa/Q7m0giUyxZGxyFSMleMFsSt0B3RGznC89cVTi25GPWoxptCTRNOaIRPaA/+ztwMREdkCk2VUgrPOAEZkjNTxukozy6OxRJmUiS2SMosvBtQXyqW9kNd3kWWP5IA1W70ROYIt46AcYixvWpGtlCbGqrtdCoJGAzM9M2Rqre+C7D2eIRER6cdkmRMz1cLFltT7ZeAmd6D5Pdf33bf0olO3FZb6YkBOF7GGEl3qiRKktKRjazOSK0Pfy9KMXWgN9oixlv4m2cLM/nSPudOPOaczVpnu11zswvnoCUF4fDNJHSd7yrD1JRERuRYmy2TOVCXIkQkzWzKULHDKSiGVitTEkbW+G1LHM7PWmGeaFwCJiSrkny79Nm1JdzZR9d+C4DwDURMRuQpnuxmhbjVmLH4aek5MlOnMWq07L4AzM9aqjBNsERHZF5NlLsCchJn67pxuRcPS/VrKmSp2JJ2Uu91SB652ZOLFVCVes8Ja2nL2iPKX7aD5+loxqMupmzQjckXm3pCyZoyVG0tm6CXrcLU6k6XVx+Lfo7/Gv0u3PTlRiP8xTH1+keOYhkRErojJMhchtUJfvI51gizvcJEx+u52G6vklfYCzJZdg3TLlpgIqFTW2ZetLzyNjZVmat/Gni/Z/VJpcluudsFH7sGcLpnWjLFyxd+x47nbmHMKADs0/hbrnprdOZ2c8Og/+s4zmnVtJsqIiOyHyTIXYqpCr2/cJWuwR9KMlXPXkH96F1Qy72aoy9gFiZwvVhxRbne7gCP3YuqmlC1j7I4T9mlNImUiEpIfVx1HTv3d3wGIM1+qlwvC41yZK9681azTq1ududp7JCKSuzKOLgBZn6kpvNVjJFmDQqH9f2txtQqfu1AqleIDsH8ySXO/1ti3tcuv+712te+5QsHumeTaDF2s2jJRBsAu3TqZ6HZOrhZHNAlC8Xe/Z7S/dgsyzS6YMk8gKRSPE16a/we035LR04bicbLeFccpJiKSK7Ysc1G6d8A177r1iNI/QGppueKdPSo9e1yAGUrOWdr1z1ZldvoZzPTQfB/q845uCzNXea9EgP5W3Jrxz1YT7zDGkj6u2qpMTd93PikzFz3hX/w705g1U050zwGC+B/9CTND5w3N9++qk3oREckVk2UuTF/CDLBtdw5W5knNnl3ypHQ5tPaFBAe71n9M1b9/V71wI1LTG2Mf9QtjwoxsTTfGusu4kHrHBVQACnWy2ujrbPv7KZEgk9IS9dF/NMtn7NTB3z8Rkf0wWebi9FXYe0b7F4/1IKHbiLnrELkDzQsSzX+bkzjTTOLZsrunqW3ru7iSUh53uCgjMqVEjH3076TMXAjC4wt6Z4ixHHOQnIGh3xz0tNTS91pb0SyTOfsRB/bXXUZERA6nEASmOiyRk5OD4OBgZGdnIygoyNHFMcpYBdzUnW993w5TzcSJNJlz8WVp4sncbWvS11LD2L51W5QZK7MlF5/qMb/UZZL6ekNdHxUKfTNXSk92uduA3850bndlzvQ5GIuxSZnGhzxgjHUe+s7vcuDq3TB16SalpNZjbdWyzNIkmbtypnM7ERGTZRZytpO9unuIANMVCzVj3wypTc2JANOVeUe2ZoiPV0pOlnnW7QygeNw/c1pfmfv+lEqlwSSXVJoD7Wtux10uqCzlbOd2V+VMn4OYEGOMdXrGxlqUchOFbM9Q0svUTLXWSpYxmV06znRuJyJiN0w3oW9AYjltj1yboy8kjLXwklrJVSqVSMq03Xh/mlQqFRITS7+dx+9NWfqNEZFe6nOCOYkyUxhj7Y9dUJ2DsZhtqKWZpb8jUzeamSQjInJtTJa5EWtXup1l2m4iS8YS00d9UWxJSzFLXmcppVKJxEQVNHfn6IQlkSvTvEi31mzTjLGOo+98yXOovEn6nei0MNPXpVPfmGha44nx90hE5DaYLHMj4gw7FoxTpot3u8kVSO1mY8lFkqMurHhBR+Q4xRfaxhNlzhBjnXkcLGNdKY1xxvdKJRltlamesVbP8+q/9SW9mSAjInJPTJa5GQFAkoG73pZUBliBcF/6Bsa3lL1mYbP0YkilUkl+rbH1bNXCjBd5RI5n6nzIGEvkIAK0Z83U+V2px/XUrIvkn4Y4HIJKxThLROSOmCxzQz2i/Es1OxC7hhBgv8/fGjNkGqvkWquLpqn96K5nzYSZvlYgrNgTOYa+li2MsUT2JQgaMVsFQHMcUI2/NSfDUd8Yk+vMp0REZF9Mlrk5cyvjrMSTLmOVSn3dYQx1kTGWFHOGgZfNrUxbIwmo3o4zHB8id2NJnJRLjHXm5IAzl90UZ+4e6wiax8nQDNPFvzWl1jIeXyIiApgsIzPIpRJP8lFc+Sy5XF/yxlRCR/MiQG4VVUvKY62ZM00lw8zpIkpE8sUY61xMJa4sHTvNGvsm/eLjldotzsAYSkREhpVxdAHIObAST/rY4vugUqns1lLK0lktpSy3RqIMkFZGex4ze3C190NkCmOs87DW+Um9HXO2JcebSc5E/fviMSQiIinYsoxMsuZA7uR6TM0oaWhQe80WU6WtuFqrS6Pu9nTvPpvaty59r2ElnYg0McaSubGQccR8ur8xHkMiIjKFyTIyiZV491baFg/qLg6mKqbGZoo01hVRd7ulqQBb8lpDFzlSk3bWakHFij+Rc2KMdV5SZj82h2aXQHa1JCIiciwmy8go3vEma3z+psZu0Z2BSt861m49Zmg/5jyvSeq4J7YYx8bVLqZc7f0QGcIY63z0xSJzz1nsZk5ERCR/TJaRUazEk1SlbUll7rgtcrnYMFQWznZJRKYwxsqHLQfkLw25louIiMjVMVlGRBZxdALH3hcN5nQFLe1+bLk+ERFpc3Q8U+P5nIiISD6YLCMio9TdhErbXcgW3SjtzdJWXhy02Xo4jg8RyYXU85Bu6zBjY3SWdl9ERERkHUyWkVEcT8V9GOrqoe/zt0WyyxkvBKxRZmd830RkHYyx8uCo87C1JwggIiIi62GyjIgkUV/QKRRAYqJ5rzXVqsyZLgpsWVbdY+NMx8VeeEzInbAlpWvRbZ3Mz5WIiEi+mCwjIgCmZ/hKysxFz2h/JCaqLN6HscH9edFARKQfz5HOjZ8dERGR82GyjIxi9xBS6xFlfqLMknFZSJuxY8cLMCLnxhjr+gy1DuT5m4iISN6YLCOTOKaK+9FXiTc34WXpYPjuwNBvSrd1nz1m3yQixzIWY3kedS3sVktEROQ8mCwjIpvgBZ5h1ppVlIhcH3/zzk1fC2t2qyUiIpI/JsuIyKHc8YJBSmtNdzwuREREREREcsBkGRGRnRlKlHGWNCIi18RzOhERkXNhsoyMUigcXQJyZbx4MD5DKMBjROTKGGOJiIiI5InJMjKKA/uTmrGkDccnIyIyH2MsERERkTyVcXQBiMj5SW39xFZShvHYEBERERERyQNblpFRUgYiJ5LSskydDGJSSJuh48HjROT6GGOJiIiI5Ikty4jIJahUKnYHJSIiIiIiolJjyzIyine8yRpctZWUtWevdNXjRET6McYSkS1xsiAiIssxWebCVCoVgyPZhe73zNpJJDlKysx1dBGIiIiI9GJreyKi0mGyjEzimCpkLkckyOy9zx5R/lCdtusuicgFMcYSka3xBjoRkfkcOmbZsmXL0KhRIwQFBSEoKAitWrXC999/Lz4/ePBgKBQKrUfLli2NbjM/Px+zZs1CrVq14OPjg8aNGyM5ObnEepcuXcLLL7+MihUrws/PD02aNMGRI0es/h7lSD22k9QxnliJJ2dmy7HMNCuevINLcsL46jwYY4nIFpRKJespRESl4NCWZdWrV8eHH36I2rVrAwDWrl2L3r174+jRo4iOjgYAdOvWDatXrxZf4+XlZXSbU6dOxfr167Fy5UrUr18fO3fuRHx8PA4cOICmTZsCAG7duoU2bdogLi4O33//PUJCQnD27FmUK1fONm/UQdQB0hpd4njn232oP2tX60rJu6rkThhfnQtjLBHZCus+RESWcWiy7Nlnn9X6e+7cuVi2bBkOHjwoVua9vb1RpUoVydtct24d3nvvPTzzzDMAgDfeeAM7d+7EwoULsX79egDAvHnzEBYWpnWREBERUcp34xwsvavESrz72HEiF4C/o4thNUql0mZ3Uw1tV3c5K6pkb4yvzoUxloiIiEheZDNmWWFhIb755hvk5uaiVatW4vKUlBSEhISgXLlyiI2Nxdy5cxESEmJwO3l5efDx8dFa5uvri/3794t/b9u2DV27dsXzzz+P1NRUVKtWDSNHjsTw4cONbjcvL0/8Ozs7GwCQk5Nj9nu1t44dOwIAduzYofd5qe8hOBh49LbJhfWMBjZs2Ki1TP0dUX+Hevbsafdylca9e/cAWO/3auq3pN6f7nKSP/VnJbhQ9kLu8VW9bWeNsday849cdK3vOjcqiIh0uWKMJSIXJjjY8ePHBX9/f8HDw0MIDg4WkpKSxOc2bdok7NixQ8jIyBC2bdsmNG7cWIiOjhYePHhgcHv9+/cXoqKihNOnTwuFhYXCDz/8IPj6+gpeXl7iOt7e3oK3t7cwZcoU4bfffhOWL18u+Pj4CGvXrjW43enTpwsA+OCDDz74cIPH2bNnrRPkHMhZ4qsgMMbywQcffLjTwxViLBG5PoUgODa1//DhQ2RlZeH27dvYsmULVq1ahdTUVERFRZVY98qVKwgPD8emTZvQp08fvdv7999/MXz4cGzfvh0KhQK1atVCp06dsHr1arG1h5eXF2JiYnDgwAHxdWPGjEFaWhp++eUXvdvVvet9+/ZthIeHIysrC8HBwaU5BGSGnJwchIWF4eLFiwgKCnJ0cdwGj7tj8LjbX3Z2NmrUqIFbt245/ThbzhJfAcZYOeD5xjF43B2Dx90xXCnGEpHrc3g3TC8vL3EA4piYGKSlpWHJkiVYsWJFiXVDQ0MRHh6OM2fOGNxe5cqVoVKp8ODBA9y4cQNVq1bF5MmTERkZqbUd3YuFBg0aYMuWLQa36+3tDW9v7xLLg4ODGWQdQD3DG9kXj7tj8LjbX5kyDp0s2iqcJb4CjLFywvONY/C4OwaPu2O4QowlItcnuzOVIAhad5c13bhxAxcvXkRoaKjJ7fj4+KBatWooKCjAli1b0Lt3b/G5Nm3a4NSpU1rrnz59GuHh4aUrPBERkUwxvhIRERERSePQlmXvvvsuunfvjrCwMNy5cwebNm1CSkoKkpOTcffuXcyYMQN9+/ZFaGgozp8/j3fffReVKlVCfHy8uI2BAweiWrVqSEhIAAAcOnQIly5dQpMmTXDp0iXMmDEDRUVFmDRpkviacePGoXXr1vjggw/wwgsv4Ndff8X//d//4f/+7//sfgyIiIisjfGViIiIiMhyDk2W/fPPP3jllVdw5coVBAcHo1GjRkhOTkbnzp1x//59ZGRk4Msvv8Tt27cRGhqKuLg4bN68GYGBgeI2srKytJryPnjwAFOnTsVff/2FgIAAPPPMM1i3bp1Wv/jmzZsjMTERU6ZMwaxZsxAZGYnFixdjwIABksvu7e2N6dOn6+02QrbD4+4YPO6OweNuf65yzJ05vgKu8zk4Ex5zx+Bxdwwed8fgcSciZ+LwAf6JiIiIiIiIiIjkQnZjlhERERERERERETkKk2VERERERERERESPMFlGRERERERERET0CJNlREREREREREREjzBZRkRERERERERE9AiTZXZ29+5d5OfnO7oYRERELoXxlYiIiIishckyO8rMzET//v1x7do1RxfFbZw+fRqbNm1ydDHczvXr13H16lVHF8PtCYLg6CK4jaKiIkcXwa0xvjoGY6xjMMbKA2OsfTC+EpGjMFlmJ8eOHUPLli2RlJSEpUuXOro4biE9PR1NmjTBv//+6+iiuJW//voLUVFRSEhIwJUrVxxdHLdx9uxZzJgxA6NHj8acOXMAAAqFgpV5G/v7779x584dlClThhV6B2F8dQzGWMdgjHUMxlj7Y3wlIkcr6+gCuAN1RX7UqFEIDg7Gzp07cfnyZVStWtXRRXNZx44dQ9u2bfHGG2/gzTffdHRx3EpaWhquX7+OFStWoKCgAO+//z6eeOIJAMV3BxUKBRQKhYNL6VoyMjLQuXNntGrVCvfv38fXX3+NkydPYsOGDTzWNvTHH38gKioKdevWxa+//oqgoCAUFRWhTBneh7IXxlfHYIx1HMZY+2OMtT/GVyKSA55xbOzw4cNo27Ytxo8fjwULFqBLly749ddfsXv3bkcXzWWdOXMGbdu2xauvvoqFCxeioKAAa9euxQcffICEhAT8+++/vBNoQ40bN8aYMWOQlJSE5cuXY+bMmbh9+zaA4jGFWLG0rosXL6Jfv34YNGgQEhMTsW3bNqxduxZpaWk4evSoo4vnsq5du4ZRo0ahe/fu8Pb2Rtu2bZGTk8M74HbE+OoYjLGOxRhrX4yx9sf4SkRywZZlNvTw4UO88cYbGDp0KObOnQtBENCiRQsMGTIEn376Kbp06SLeDSTrWb16NcqWLYvGjRvjzp07eO6555CdnY0HDx7g2rVrWLduHT777DPExcU5uqguqVy5ckhMTERCQgK2bNmCvn37wt/fH5cuXYK/vz9WrFjBO4NWIggCkpOTERISgrfffhsA4OXlhSeffBI5OTm4deuWg0vouk6cOIFq1aph8ODBqFKlCgYMGIC2bdti//79CAoKQmFhITw8PBxdTJfF+Oo4jLGOxRhrP4yxjsH4SkRywWSZDXl5eeH7779HpUqVAEC829ehQwckJibiwoULeOKJJ9is2MpmzJiB7OxsLFu2DLNmzUKDBg2wefNmVK5cGd7e3mjXrh0mTJiAw4cP8w6slQiCAIVCgcLCQjzxxBOIjIzEsWPHoFQqkZKSgg4dOsDb2xvbt2/nd92KFAoFWrRogbt37yIkJAQAUFBQgOrVq6NSpUq4e/eug0voutq3bw8PDw+0b98eALBu3Tq8/PLLaNu2Lfbt24fg4GCxS1RRUREr9lbG+Oo4jLH2xxjrGIyxjsH4SkRywYhqAwUFBeK/1RV54PGsOf3790edOnUwbdo0AGDFxgr+/vtvnD17FgUFBfDy8sLixYvRtGlT1KlTBx9//DHCw8Ph5+cHDw8PrFmzBsePH8dPP/3k6GI7vXv37okVFkEQ4OHhAYVCgRo1auD48eMAiis55cuXR15eHnbs2MEBia2sQYMGGDduHIDic0zZssX3QDw9PbUq8t988w1ycnIcUkZXpFmRB4CGDRti48aNKFOmDNq1ayd2GVmwYAF27tzpwJK6FsZXx2CMdQzGWMdjjLU/xlcikgvWIq3s1KlTGDt2LLp3746PPvoIf/31l/ic+g4IALz66qu4ePEiDh48CIDTT5dGRkYG2rRpg/Xr1+Pu3bsoKiqCp6cnPvvsM0ycOBGRkZFa61+6dAk1a9ZERESEYwrsIk6dOoU+ffpg69atYmU+Pz8fAFC9enVkZWVhzJgx2LFjBzIyMvD9999jyZIlWLRoEQoLCx1ceud1+fJl7Ny5E1988QWuX78OT09P8fyhbnkAFHdT8/LyAgC8//776NevH27cuOGwcju7c+fOYc2aNZgzZw6OHj2K69evi8+pz+tRUVFihT42NhbDhw/HO++8g1q1ajmq2C6F8dUxGGMdgzHWMRhj7Y/xlYhkSyCrycjIECpUqCAMHDhQeO6554QGDRoIq1at0lqnqKhIEARBuHLlihAeHi68+eabjiiqyzhz5owQEhIiTJo0ScjNzZX0msmTJwvt27cXbty4YePSua6CggLh9ddfFxQKhdCrVy9h+/btQmFhofj8Dz/8IJQpU0YICwsTjhw5Ii7fuXOnkJmZ6Ygiu4Tjx48L9evXFxo3biyEhIQIVapUEf78809BEATx+Ofn5wsFBQVCgwYNhB9++EGYP3++4OfnJxw+fNiRRXdqx48fFypVqiS0bNlSqF27tlC+fHlh8ODBwoEDB8R1NL//6enpgqenp1CxYkXht99+c0SRXQ7jq2MwxjoGY6xjMMbaH+MrEckZk2VWcuPGDaFVq1bCu+++Ky4bMmSIMG7cOKGgoECsxAtCcaAVBEGYPXu2ULduXeHOnTtaz5N0CQkJwvPPPy8IQnHlcs2aNcKkSZOEDRs2CMePH9da99ChQ8I777wjBAUFCceOHXNEcV3KF198ITz33HNCbGys0KJFC+Hbb78Vn7t165bw/vvva30GmpUdMt+ff/4pVK1aVXj33XeFS5cuCdeuXRO6d+8uxMbGCgUFBSXWb9u2rVCrVi3Bx8dHSEtLc0CJXUNOTo4QGxsrjB8/Xrh3754gCIKwevVqoWvXrkJsbKyQmpoqrltUVCQUFhYKr7/+uuDj4yOcOHHCUcV2KYyvjsMY6ziMsfbFGGt/jK9EJHfshmklubm5uHXrFtq2bSsu8/b2xqlTp9C6dWuMHj0aP/74IwCI4x306tULu3btQkBAAAfBtdBvv/2GsLAwAMUDO69atQq7d+/Ghx9+iNdee0085pcuXcKqVaugUqmwd+9eNGrUyJHFdglly5aFv78/vv/+e3h6emL+/PnYt28fRowYgVOnTuH999/Hk08+Ka7PsYMsl5eXh0WLFqFLly6YPn06qlatisqVK2PAgAG4efNmiW5m+fn5uHHjBv766y+kpaUhJibGQSV3foWFhbh06RKefPJJ+Pr6AgAGDx6McePGwd/fH/PmzcOJEycAFHfROXr0KP744w/s378fUVFRjiy6y2B8dRzGWMdhjLUfxljHYHwlIrljZLWSe/fuAQB+/fX/27vz+Kaq/P/j77RAgULLjoBsgoIFUUSUKoL6BRfoQGF03GbAfd9/7qKAyuAyOjKooOM6ijLjMNQREBQV9wUUkV1AkUUQR4RChQLt/f1REpI0e5Oce29ez8ej0CY3Nycnyf2c+7ln+ULffPON7r//fr3wwgs66aSTNGDAAP3888+67777tHr1at9jevTooXbt2pkqsit0795dP//8sx577DHVq1dP//rXv7RgwQJNmjRJ7du31+OPP67t27erdevWuuuuu/Tuu+/qyCOPNF1sVxgwYIA2bdqkevXq6c0331StWrV01lln6ZVXXlFOTo6ys7OZKyhJcnJy1KpVK3Xo0ME3R4ok9erVS1u2bNHmzZt9E59blqXatWtrwoQJWrlypbp3726q2K5QWVmppk2b6qeffpJ0YIL50047TZdddpk2btyomTNn+rbv2bOnSkpK1KtXLyPldSPiqznEWHOIselDjDWD+ArA7mqZLoBbdOnSRWeffbZee+01ffzxx1qwYIFeeeUVDRs2TJI0d+5cnXfeeVq7dq06d+5suLTu0b59ez333HPaunWrevTooVatWkmSTjjhBG3atEmXXnqptmzZovz8fLVv395wad1n9erV+vbbb3XYYYepZcuW+vTTT9W1a1dt2bJFlZWVXOlOolGjRlW7zbIs1alTR/Xq1fP1qFm1apU6deqkgQMHpruIrtSkSRMVFhbqr3/9q4YPH65DDz1UFRUVys7O1tChQ/XZZ5/p8ccf1w033KDatWsrKytLjRo1Ml1sVyG+mkOMNYsYmz7E2PQjvgKwO6JsEnhXahkzZoxmzZqlxx9/XM2bNw9YoaWgoEAHHXQQVwGTbOTIkTrllFM0a9YsLV68WFu3bvXd17t3b7Vv355VoVKgsrJSrVq10nHHHafc3Fxddtll+vjjjzV79mw1adJEN954o95++23TxXQl7zHEsixVVFTI4/EoJydHknTrrbdqyJAhKisrM1lE1/Ae2x999FF17dpVRUVF+vHHH5Wdne3bpk+fPmratKnKy8sZ7pcCxFeziLFmEGPNIcamB/EVgBOQLEuCrKws30G/Xbt2qlWrlrKzs7V7927f7U888YR2795Nd+0k8jbQJ0+erPPOO09vv/22Hn/8ca1atUrl5eWaPHmy9u7dq+bNmxsuqft4r2ZnZWWpbdu2euONNzR9+nSddNJJ+ve//6327durS5cuhkvpTt4Go7cBX15ern379mnUqFF68skn9eKLLyovL89wKd0hKytLlmXJ4/Ho2WefVePGjdW3b1998MEH+uWXXyRJ77zzjnJycmjIpwjx1RxirDnEWHOIselBfAXgBB6LS7EpMWTIEH388cc68cQT5fF49Mknn2j27Nnq2bOn6aK51pVXXqm5c+dqy5Yt6t69u9asWaPZs2frqKOOMl001/E2cGbNmqWXX35ZN998s44++mhf93mGh6TH6tWrNWTIEB133HF65ZVX9MknnzCXRwpt3rxZl19+uT777DPl5+erTZs2+vrrr/Xee+9xnEkj4qsZxNj0IcbaAzE2fYivAOyIZFkcVq1apSVLlqi4uDjsVQ7/Bswdd9yh9evXq2XLlrr88st12GGHpbO4rhBvnc+fP1/ff/+96tSpo6OPPpoJnhMUS71LVStI7dq1q9ocEt6GPuITa71LVXX81VdfqXfv3mrUqJHeffddGpQJiqfeJWnatGnasGGDsrKyNGjQoIAhgUgM8dUMYqwZxFgziLHpR3wF4GQky2K0detWdezYUTt27NBLL72k888/v9o23it+wY0YGjWJiafOucqaPPHUO5In0Xq/9NJLde2116pHjx7pKqqrcJwxj/hqBp99M4ixZhBj049jDACnYzXMGDVp0kSnnHKK9uzZoxEjRqi8vFwXXHBBwIHdG2D//e9/q2fPnr5VuWjIJyaeOp82bZp69eqlQw45xFRxXSOeen/ttdd0zDHHqGPHjqaK6xrx1rv3GPP0009zjKmBmhxnSNQkB/HVDGKsGcRYM4ix6Ud8BeB4FqLat2+fVV5ebp166qnWrFmzrIcfftjKzs62Xn75ZcuyLGv69OnW7t27LcuyrEWLFlkej8e6/vrrrb1795ostqNR52ZQ72YkUu/XXXcd9V5DfN7N4z0wg3o3g3o3gxibfnzWAbgBPctikJWVpezsbJ144on64YcfdPPNN6usrEwXXHCBJk6cqIqKChUWFqply5bq0aOHSkpK1LlzZ9WqRfUmijo3g3o3g3o3g3o3j/fADOrdDOrdDOo9/ahzAG7A4PAYeLsBZ2dna8aMGZKk0aNHq3v37vriiy80ePBgtWzZUlJVt+EhQ4aooKDAWHndgDo3g3o3g3o3g3o3j/fADOrdDOrdDOo9/ahzAG5AsiyMysrKarcdd9xxvhWJRo4cqS1btujSSy/VQw89pMmTJ0ti/pSaoM7NoN7NoN7NoN7N4z0wg3o3g3o3g3pPP+ocgOuYGv9pV9999531/fffW5ZlWRUVFQH3/fDDD9YJJ5xgFRYWWi1btrS++uory7Is6+abb7aaNWtmbdu2Ld3FdQXq3Azq3Qzq3Qzq3TzeAzOodzOodzOo9/SjzgG4FckyPytWrLA8Ho+Vm5trrVy50rKsAwf9yspKa/PmzdZJJ51k9ezZ0/ryyy8DHvvzzz+nvbxuQJ2bQb2bQb2bQb2bx3tgBvVuBvVuBvWeftQ5ADfzWJZlme7dZgf/+9//NGLECNWpU0e7du3SwoUL9cEHH6hr166qrKz0LXP8xRdfqEmTJr5l65E46twM6t0M6t0M6t083gMzqHczqHczqPf0o84BuB1zlu23du1atW7dWldeeaWee+45HXvsserfv79WrFihrKws7d27V5J07LHHcrBPEurcDOrdDOrdDOrdPN4DM6h3M6h3M6j39KPOAbie6a5tdjJ//nzf7+vWrbMGDRpkNW/e3Fq+fLllWVXdiisrK63du3ebKqLrUOdmUO9mUO9mUO/m8R6YQb2bQb2bQb2nH3UOwM0YhikFdBX2t2HDBl1++eWaP3++r1vx2LFj1blzZ5133nms3lID1LkZ1LsZ1LsZ1Lt5vAdmUO9mUO9mUO/pR50DyAims3WmbNu2zdqzZ0/U7TZs2GANGjTIat26tXXOOedYHo/HWrp0aRpK6D7UuRnUuxnUuxnUu3m8B2ZQ72ZQ72ZQ7+lHnQPINBmZLFu6dKnVtGlT67777qu2xHEo3333ndW0aVOradOm1sKFC1NfQBeizs2g3s2g3s2g3s3jPTCDejeDejeDek8/6hxAJsq4ZNnGjRutXr16Wd26dbNycnKscePGWZWVlWG3r6iosK666iqrdu3a1pIlS9JYUvegzs2g3s2g3s2g3s3jPTCDejeDejeDek8/6hxApqplehhoOlVWVur9999Xhw4dNGbMGH366ae64oorJEl33HFHyHH0K1as0MaNG/XZZ5+pW7du6S6y41HnZlDvZlDvZlDv5vEemEG9m0G9m0G9px91DiCjmc7WpduKFSusWbNm+f5+6qmnrKysLGvcuHEB3Yr9r5iUlpamtYxuQ52bQb2bQb2bQb2bx3tgBvVuBvVuBvWeftQ5gEyVcckyf94D/NNPP+076FdWVlp79uyxpkyZwhj7FKDOzaDezaDezaDezeM9MIN6N4N6N4N6Tz/qHEAmyahhmF6WZcnj8fiWPL700kslSVdccYUsy9IPP/yg1157TYsWLTJZTFehzs2g3s2g3s2g3s3jPTCDejeDejeDek8/6hxAJsq4ZFlFRYWys7O1Y8cOSVLDhg0lVR30KysrdeWVVyo/P19z585Vu3btTBbVNahzM6h3M6h3M6h383gPzKDezaDezaDe0486B5CpskwXIJ28B/u1a9eqR48eWrBgge++PXv2aNGiRcrPz9cnn3yiXr16GSype1DnZlDvZlDvZlDv5vEemEG9m0G9m0G9px91DiCjpXfUp3k//PCD1bx5c+uiiy4KmIhy9uzZVosWLaz58+cbLJ07UedmUO9mUO9mUO/m8R6YQb2bQb2bQb2nH3UOIFN5LMuyTCfs0qWyslKPPPKI1q9frwkTJgQsd/zjjz8qOztbLVu2NFhC96HOzaDezaDezaDezeM9MIN6N4N6N4N6Tz/qHEAmy6hkmSTt2rVL9erVM12MjEKdm0G9m0G9m0G9m8d7YAb1bgb1bgb1nn7UOYBMlXHJMgAAAAAAACCcjJrgHwAAAAAAAIiEZBkAAAAAAACwH8kyAAAAAAAAYD+SZQAAAAAAAMB+JMsAAAAAAACA/UiWAQAAAAAAAPuRLAMAAAAAAAD2I1kGAAAAAAAA7EeyDAAAAAAAANiPZBmQodauXSuPx6Ovv/46Jfv3eDwqKSmp8X7uvvtuXXbZZTFte+aZZ+rRRx+t8XMCAFATxFgAAJyNZBlgwAUXXKDi4mKjZWjbtq02bdqk7t27S5LmzZsnj8ejbdu2GS2Xv59++kkTJkzQnXfe6btt586dOuecc9SqVSudc845Kisr8913zz33aNy4cSotLTVRXACADRBjY0OMBQAgPJJlQIbKzs7WQQcdpFq1apkuSljPPvusCgsL1aFDB99tjz32mBo0aKC33npL9evX12OPPea7r0ePHurQoYOmTJmS/sICALAfMRYAAGcjWQbY0Pvvv69jjz1WOTk5atWqlW6//Xbt27fPd/9JJ52k6667TrfeequaNGmigw46SGPGjAnYx4oVK9S3b1/VrVtXBQUFmjt3bsCwDf8hImvXrtXJJ58sSWrcuLE8Ho8uuOACSVKHDh0CGsuSdNRRRwU836pVq9SvXz/fc7399tvVXtPGjRt19tlnq3HjxmratKmGDh2qtWvXRqyHqVOnasiQIQG3bdu2TYcddpiOOOIIde3aVdu3bw+4f8iQIXr11Vcj7hcAkLmIsVWIsQAAhEeyDLCZjRs3atCgQerdu7cWLVqkSZMm6dlnn9X9998fsN2LL76o3Nxcff7553rooYd07733+hrQlZWVKi4uVv369fX555/r6aef1l133RX2Odu2batp06ZJklauXKlNmzZpwoQJMZW3srJSw4cPV3Z2tj777DNNnjxZt912W8A2v/32m04++WQ1aNBAH3zwgT766CM1aNBAp59+uvbs2RNyv7/++quWLFmiY445JuD2a665Rk899ZRq166t559/Xtdff33A/ccee6y++OILlZeXx1R+AEDmIMZWIcYCABCZffuGAxnqySefVNu2bfX444/L4/Goa9eu+vHHH3XbbbfpnnvuUVZWVY67R48eGj16tCTp0EMP1eOPP6533nlHAwcO1FtvvaU1a9Zo3rx5OuiggyRJ48aN08CBA0M+Z3Z2tpo0aSJJatGihRo1ahRzeefOnavly5dr7dq1OvjggyVJf/7zn3XGGWf4tpk6daqysrL0zDPPyOPxSJKef/55NWrUSPPmzdOpp55abb8//PCDLMtS69atA27v0KGDVq1apS1btqhly5a+/Xm1adNG5eXl2rx5s9q3bx/z6wAAuB8xtgoxFgCAyEiWATazfPlyFRYWBjRQTzjhBO3cuVMbNmxQu3btJFU15P21atVKW7ZskVR15bpt27a+RrxUdTU4VeVt166drxEvSYWFhQHbfPnll1q9erUaNmwYcPvu3bu1Zs2akPvdtWuXJKlu3brV7svKygp4bf7q1asnqepKOwAA/oixVYixAABERrIMsBnLsqpdybUsS5ICbq9du3bANh6PR5WVlWH3kaisrCzf83vt3bu3WtmCy+KvsrJSvXr1CjkpcPPmzUM+b7NmzSRVDRUJt00oW7dujbhfAEDmIsZWIcYCABAZc5YBNlNQUKBPPvkkoIH8ySefqGHDhmrTpk1M++jatavWrVunn376yXfb/PnzIz6mTp06kqSKioqA25s3b65Nmzb5/i4tLdX3338fUN5169bpxx9/9N326aefBuzj6KOP1qpVq9SiRQt17tw54Cc/Pz9keTp16qS8vDwtW7YsyqsNtGTJEh188MG+EwEAALyIsVWIsQAAREayDDBk+/bt+vrrrwN+1q1bp6uuukrr16/XtddeqxUrVuj111/X6NGjddNNN/nmUolm4MCB6tSpk0aOHKlvvvlGH3/8sW/y4XBXw9u3by+Px6MZM2bo559/1s6dOyVJp5xyil566SV9+OGHWrJkiUaOHKns7Gzf4wYMGKAuXbpoxIgRWrRokT788MNqEx2ff/75atasmYYOHaoPP/xQ33//vd5//31df/312rBhQ8jyZGVlacCAAfroo49ies1eH374Ycj5WQAAmYMYS4wFAKAmSJYBhsybN089e/YM+LnnnnvUpk0bzZo1S1988YWOPPJIXXHFFbr44os1atSomPednZ2tkpIS7dy5U71799Yll1zie3yo+Umkqkl7x44dq9tvv10tW7bUNddcI0m644471K9fPxUVFWnQoEEqLi5Wp06dfI/LysrS9OnTVV5ermOPPVaXXHKJxo0bF7Dv+vXr64MPPlC7du00fPhwHX744brooou0a9cu5eXlhX0dl112maZOneob+hLN7t27NX36dF166aUxbQ8AcCdiLDEWAICa8FihJkMA4Doff/yx+vbtq9WrVwc0xO3Msiz16dNHN9xwg84999yo2z/xxBN6/fXX9dZbb6WhdAAAVCHGAgDgLkzwD7jU9OnT1aBBAx166KFavXq1rr/+ep1wwgmOacRLVcNZnn76aX3zzTcxbV+7dm1NnDgxxaUCAGQ6YiwAAO5GzzLApf7xj3/ovvvu0/r169WsWTMNGDBAjzzyiJo2bWq6aAAAOBoxFgAAdyNZBgAAAAAAAOzHBP8AAAAAAADAfiTLAAAAAAAAgP1IlgEAAAAAAAD7kSwDAAAAAAAA9iNZBgAAAAAAAOxHsgwAAAAAAADYj2QZAAAAAAAAsB/JMgAAAAAAAGA/kmUAAAAAAADAfiTLAAAAAAAAgP1IlgEAAAAAAAD7kSwDAAAAAAAA9iNZBgAAAAAAAOxHsgxIk3fffVcXXXSRunbtqtzcXLVp00ZDhw7Vl19+WW3br776SgMGDFCDBg3UqFEjDR8+XN99913ANt9++61uvvlm9erVS40aNVKTJk10wgkn6N///ne1/b3wwgvyeDwhfzZv3hzza4ilXF4//PCDLrroIrVu3Vo5OTlq06aNhg0bFtPz7NixQ7feeqtOPfVUNW/eXB6PR2PGjAm57d/+9jf16dNHzZo1U05Ojtq1a6dzzjlHS5cujfl1AQCczWSM9Xr99dfVv39/5eXlKTc3V926ddPTTz8d82tIV4yVpJ07d+qGG25Q69atVbduXR111FGaOnVqte2IsQCATEWyDEiTSZMmae3atbr++us1a9YsTZgwQVu2bFGfPn307rvv+rZbsWKFTjrpJO3Zs0f/+te/9Nxzz+nbb7/ViSeeqJ9//tm33VtvvaWZM2fq97//vV577TVNmTJFhx56qM466yzde++9Icvw/PPP69NPPw34adq0aUzlj7VckrRkyRL16tVLS5Ys0V/+8he9/fbbevTRR9W4ceOYnuuXX37R008/rfLychUXF0fd9owzztAzzzyjt956S2PHjtXChQt13HHHaeXKlTE9HwDA2UzH2AceeEDDhw9X9+7d9a9//Uv//e9/ddVVV2nPnj0xlT+dMVaShg8frhdffFGjR4/Wm2++qd69e+vcc8/VK6+8ErAdMRYAkLEsAGnx008/Vbttx44dVsuWLa3/+7//89121llnWc2aNbO2b9/uu23t2rVW7dq1rVtvvdV3288//2xVVlZW2+fgwYOt+vXrW7t37/bd9vzzz1uSrPnz5ydc/ljLVVlZaR111FHWUUcdFVCGeFRWVvpe288//2xJskaPHh3z45ctW2ZJsu6+++6Enh8A4CwmY+yCBQusrKws68EHH0y4/OmMsTNnzrQkWa+88krA7QMHDrRat25t7du3L+LjibEAgExAzzIgTVq0aFHttgYNGqigoEDr16+XJO3bt08zZszQ73//e+Xl5fm2a9++vU4++WRNnz7dd1uzZs3k8Xiq7fPYY4/Vb7/9pq1btyat7PGU64MPPtDXX3+tG264QTk5OQk9n3eIaKKaN28uSapVq1bC+wAAOIfJGPv4448rJydH1157bUJlT3eMnT59uho0aKCzzjor4PYLL7xQP/74oz7//POIjyfGAgAyAckywKDt27frq6++Urdu3SRJa9as0a5du9SjR49q2/bo0UOrV6/W7t27I+7zvffeU/PmzUOeOBQVFSk7O1tNmjTR8OHDtWTJkpjKGU+5PvjgA0lSw4YNNWjQINWtW1cNGjRQUVGRVqxYEdPzJaKiokLl5eVasWKFLrnkErVo0UIXXnhhyp4PAGBv6YqxH3zwgQ4//HBNmzZNXbp0UXZ2tg4++GDdfvvtMQ3DTHeMXbJkiQ4//PBqyS7v84dqGxBjAQCZhmQZYNDVV1+tsrIy3XXXXZKq5gaRpCZNmlTbtkmTJrIsS7/++mvY/T3zzDOaN2+eRo0apezsbN/tBx10kO666y4988wzeu+993Tfffdp/vz56tOnjxYtWhS1nPGUa+PGjZKqrlC3bt1aM2fO1OTJk7VkyRKdeOKJ2rRpU9TnS0Rubq7q1q2rww8/XMuXL9e8efPUtm3blDwXAMD+0hVjN27cqFWrVum6667Tddddp7lz5+qCCy7QX/7yl5gSSumOsb/88kvY5/Ivjz9iLAAg09B/GjDk7rvv1pQpUzRx4kT16tUr4L5IQxDD3ffmm2/q6quv1plnnlltKMjpp5+u008/3fd3v379NHjwYB1xxBG655579Prrr0uSKisrVVlZGfBc/icEsZTL+/jCwkI988wzvvu7d++unj176oknntD9998vy7JUUVERsI+aDOn45JNPtGfPHq1Zs0Z//etfdfLJJ+udd97x9SgAAGSOdMbYyspK7dixQ6+++qrOOeccSdLJJ5+ssrIyPfbYYxo7dqw6d+5sqxgbbx0QYwEAmYaeZYABY8eO1f33369x48bpmmuu8d3uXZky1FXdrVu3yuPxqFGjRtXumzNnjoYPH66BAwdqypQpMc331aFDB/Xt21efffaZ77aLLrpItWvX9v383//9X9zl8m572mmnBWx31FFHqVWrVvrqq68kSe+//37Ac9WuXVtr166NWu5wjj76aPXp00fnn3++3nvvPVmWpTvvvDPh/QEAnCndMTZc3DvjjDMkyRf37BJjmzZtGva5pNA93IixAIBMQ88yIM3Gjh2rMWPGaMyYMdUamp06dVK9evW0ePHiao9bvHixOnfurLp16wbcPmfOHBUXF6t///6aNm2a6tSpE3NZLMtSVtaBnPmYMWMCTiwaNmwYd7lCzbkS6vl69eql+fPnB9zfunXrmMseScOGDdW1a1d9++23SdkfAMAZTMTYHj16aPPmzdVutyxLknxxzy4x9ogjjtCrr76qffv2BfQ28z5/9+7dwz6Ht9zEWACA65lZhBPITPfee68lyRo1alTYbf7whz9YLVq0sEpLS323/fDDD1adOnWs2267LWDbOXPmWHXr1rUGDBhg7dq1K66yfPfdd1aDBg2s4uLimLaPtVy//vqrVb9+fWvgwIEBj//yyy8tSdZ9990XVzl//vlnS5I1evTouB7TuHFjq6ioKK7nAgA4l6kY+9RTT1mSrClTpgTcft1111lZWVnW2rVro5Y9nTF21qxZliRr6tSpAbeffvrpVuvWra19+/ZFfDwxFgCQCTyWtf+yF4CUeuSRR3TzzTfr9NNP1+jRo6vd36dPH0nSihUr1Lt3bx199NG6/fbbtXv3bt1zzz3aunWrvv76a9+S7R999JFOPfVUtWzZUs8995zq1asXsL+CggLfEvQDBgxQv3791KNHD+Xl5Wnx4sV66KGHtGPHDn3yySdRryLHUy7/1zpy5Eide+652rx5s+6++255PB4tXLgw5BCPYG+++abKysq0Y8cOXXTRRTrrrLP0hz/8QZI0aNAg1a9fX9u3b9fAgQN13nnn6dBDD1W9evX07bffasKECVq3bp3ef/99HXPMMVGfCwDgbCZj7N69e9WnTx+tWbNG9957rwoKCjR37lz95S9/0ZVXXqmJEydGLX+6Y+ypp56qBQsW6MEHH1Tnzp316quv6u9//7tefvllnX/++ZJEjAUAZDbT2TogU/Tv39+SFPbH34IFC6z/+7//s+rXr2/l5eVZxcXF1urVqwO2GT16dMT9vffee75tb7jhBqugoMBq2LChVatWLat169bWH//4R2vlypVxvYZYyuX197//3erevbtVp04dq2nTptb5559vrV+/Pubnat++fdjX9v3331uWZVm7d++2LrnkEuvwww+3GjRoYNWqVcs6+OCDrT/+8Y/W0qVL43ptAADnMhljLcuyfvnlF+vyyy+3WrZsadWuXds67LDDrIcfftiqqKiI+TWkM8bu2LHDuu6666yDDjrIqlOnjtWjRw/r1VdfDdiGGAsAyGT0LAMAAAAAAAD2YzVMAAAAAAAAYD+SZQAAAAAAAMB+JMsAAAAAAACA/YwmyyZNmuRbnS8vL0+FhYV68803A7ZZvny5hgwZovz8fDVs2FB9+vTRunXrYtr/1KlT5fF4VFxcHHD7vn37NGrUKHXs2FH16tXTIYcconvvvVeVlZXJemkAABhDfAUAAAASV8vkkx988MF64IEH1LlzZ0nSiy++qKFDh2rhwoXq1q2b1qxZo759++riiy/W2LFjlZ+fr+XLl6tu3bpR9/3DDz/o5ptv1oknnljtvgcffFCTJ0/Wiy++qG7dumnBggW68MILlZ+fr+uvvz7prxMAgHQivgIAAACJs91qmE2aNNHDDz+siy++WOecc45q166tl156Ka59VFRUqH///rrwwgv14Ycfatu2bSopKfHdX1RUpJYtW+rZZ5/13fb73/9e9evXj/u5AABwAuIrAAAAEBvbzFlWUVGhqVOnqqysTIWFhaqsrNTMmTN12GGH6bTTTlOLFi103HHHBTTKw7n33nvVvHlzXXzxxSHv79u3r9555x19++23kqRFixbpo48+0qBBg5L5kgAAMI74CgAAAMTH6DBMSVq8eLEKCwu1e/duNWjQQNOnT1dBQYE2b96snTt36oEHHtD999+vBx98ULNnz9bw4cP13nvvqX///iH39/HHH+vZZ5/V119/HfY5b7vtNm3fvl1du3ZVdna2KioqNG7cOJ177rlhH1NeXq7y8nLf35WVldq6dauaNm0qj8eT8OsHANiHZVnasWOHWrduraws21xPSohT4qtEjAWATOCmGAsgA1iGlZeXW6tWrbLmz59v3X777VazZs2spUuXWhs3brQkWeeee27A9r/73e+sc845J+S+SktLrQ4dOlizZs3y3TZy5Ehr6NChAdu9+uqr1sEHH2y9+uqr1jfffGP94x//sJo0aWK98MILYcs5evRoSxI//PDDDz8Z8LN+/frEA5tNOCW+WhYxlh9++OEnk37cEGMBuJ/t5iwbMGCAOnXqpIkTJyo3N1ejR4/WqFGjfPffdttt+uijj/Txxx9Xe+zXX3+tnj17Kjs723ebdwWurKwsrVy5Up06dVLbtm11++236+qrr/Ztd//99+vll1/WihUrQpYr+Kr39u3b1a5dO61fv155eXk1ft1AJpkxY4bv96KiIoMlySzeeqfOwystLVXbtm21bds25efnmy5OUtk1vko1j7H+xxTpwGc81Gc+3LZuFPxa7cTN9S5Fr3u3v344S7RjZbI+r26OsQDcx/gwzGCWZam8vFx16tRR7969tXLlyoD7v/32W7Vv3z7kY7t27arFixcH3DZq1Cjt2LFDEyZMUNu2bSVJv/32W7Wuv9nZ2RGXts/JyVFOTk612/Py8kiWAXGqX7++7/d3331XklRcXGyoNJnjvPPOM12EuISaQytdnxM3Dv2za3yVah5j/Y8p3sf53+6/j3DbupH/dz6WOenSJROO98Gfs2Bu/tzBeUIdK8877zzfcSPZn1c3xlgA7mM0WXbnnXfqjDPOUNu2bbVjxw5NnTpV8+bN0+zZsyVJt9xyi84++2z169dPJ598smbPnq033nhD8+bN8+1jxIgRatOmjcaPH6+6deuqe/fuAc/RqFEjSQq4/Xe/+53GjRundu3aqVu3blq4cKEeffRRXXTRRSl/zQAOnCjZ6eQNcBPia3jFxcW+Y08mJG3sJlPqPFKcy5Q6gHOE+kz6f3ZLSkr43ALIOEaTZT/99JP+9Kc/adOmTcrPz1ePHj00e/ZsDRw4UJI0bNgwTZ48WePHj9d1112nLl26aNq0aerbt69vH+vWrYt7gsiJEyfq7rvv1lVXXaUtW7aodevWuvzyy3XPPfck9fUBABKXaMOcRAjx1Ss4YeH9O9M+G3a9MFGT76qpx4bi8Uj2mtQESB3/40mmHUsBZBbbzVnmFKWlpcrPz9f27dvpSg8ANlKThjzHdntI9vuQ6QlUuyTLwvW2cnqyLNbn88rUzyGcKTimEmMBZArbzVkGAEAycEIKLz4L9pDMpJ2T3lMnlRWZgx5iABBZfOMrAACwueLiYhr+gB++D6HZpccdAACwH3qWAQBsK5HJsTN9yB0QSvDwKbvgewqYFyluhvuO8t0F4HYkywAArmHHZACA0EydbHOSDySWQCfGAsgkJMsAAAAygH+SyA4nvcyZBNifHY4VAGACyTIAgG3FcwJNgx5wrpKSEhJmQJrFOq0BAGQiJvgHALiCf6Ofk24AAJKPRXQAZAp6lgEAHCHUkC0m8wcSF/w9StdzBj8f31/Anoi1ADIZPcsAAI7n35CnMQ9EZ/J7wncUSExJSYmRoZHEVgCZiJ5lAABHsNvk5AASx4k3AACwM5JlAAAAGczEcEwA8SPJDADpwzBMAIDjMCQEqJlQiTG+VwAAAFVIlgEAHI8TfCB5+D4BzmNqPjMAcCuGYQIAHIuTeiA1UjVHYElJSczf21Ar4AIIFPz9jOc7BgAIj55lAAAAGSjWnijBwzNNnIj7lzNcub2307sGbsVnHADSh55lAOAC9MCAm3k/33y2zQqVMEvGSXus+6DHDBAbvisAUHMkywDAZUgswE3oQZF8yRy2lUjSrCbvKZ8HIBCr2QJAapAsAwAXoLEMQEq8l2mkJHu4+0wdb8K9Li4QwO0ifcaLi4tpAwBAEpEsAwCHo3EMt5oxY4bq169vuhiOlexepnY41pAQA8Lj+wEAyUOyDABchIYy3IjPdc0kmjSzQ3LMH58DAACQLqyGCQAA4BLBK1eG2yYcuyXIAAAATCBZBgAO53/iy4kugJpy2nGkpKTE95MJzwsAAFKPYZgA4AIMT4JbBS9e4cbPeqKT8scqkX3aMQEUy6qdNVnZEwAAwIueZQAAAHCkUEk9Oyb6AACAs3gsy7JMF8KJSktLlZ+fr+3btysvL890cYCM4JHEAQupxLHdHpz+PjihF5xTE0rBdRrpddi5/u1o5rIySdLgglzDJYFbOf3YDiCzMAwTgGN4E2WJJM2ccPIKIDy+w6ElawhncXGxIxJo/sMsTcxR5s9tn8XBBblclLIRjnkAYBbJMgCOE09DPvjkhvlsAKSaHY8xkZJq3r+dkjCLVaqP925Mnnnj68xlZfQwswnaLQBgBnOWAbAl73CQmnJaA5PV1QCY5LRjptPZ9XhPosw8vosAYBY9ywBkFBqfANwk1mNapO2Ch3vZtYeZt1ymyhbr8M9Yh8/578dOvYc8kmbQs8wW7PKZAIBMRLIMgC1FaqT7z6nCUBEgM3DSmHr+CRs7JsxiKQ+fk/jNXFamooJcX1y1JGl/XCXGAgAyFckyALYUbZLhRCchttPV+2Cxnpgy6S+AdDI1ob5d1fTYa7d6LCrI1YxlZb4EGQAAIFkGwIY8Qf+HMmNZmWbGuD879pAAALsLtRCAXY+ldrp4UJOypPtiiDfOenuW0XMbAIAqJMsAOI9HGmyFbsCHW/HNTidSsYilvPQwA5Aotx03wiXxnPQ67TCHmX/CjEQZACCTsRomAOeJcfylXXtAhOM/V1A8nPY6AdiX/4q8wceWTDjWpGMBgeLiYtsk8fzDqSfEbQAAZCp6lgGwJ/8xmEEt93ga8naeoyyURMrqpNcHwFmcdgxNVKoTZKF6PQfXa6jkZLrrPtH5QAEAcBuSZQDsJ3iyMv/L3WFa8pnQ4wEAAAAAkHoMwwRgP+Eua4eZ8T9SoiwTekQAQCqlY2ii3aTy9dq1PulRBgDAASTLANhPpGUwg9jxhCOVgl+vXZKB4eY4AuAsdjmmuEm4hWdM8kjyeKp+tP/HE0fsRfoQWwHADIZhArCVSG11K8bL3nY5GUmF4uJi2zWa7VYeADVjx+OMU0VaJMF/ReNQ9Z2qWBYuKRZrjEX68D0EAHNIlgGwlzivbGfySZ0dk4LB74cdywggOu9318nH13iOPyaPVU6uY6SXXXuXA4AbMQwTgGMwRKRKcXGxbRvInPQBsIt4jkd2HEpup7IAAJBp6FkGwF68K16GuivMEJFM7l1mB27ogQIgEN/n5HDM8ZEhmLbkf2HM9p8hAHAZkmUA7CVc77EoDXm79rTKZLwngDtwQcL9yJXZWzrntAMAVCFZBiApkjFPFZMOuweNeMA9SkpKqn2nnZA8i3fOsmS8pnCxMNH6S+YcVTOXlamoW26124mx5vkv9hDpNi9iLACkHskyADWWjBOMsB3K/BrxkRqOMI/3BcgcdkyeBSca4o0ZNTmGxfv6Ex2e6U1cJnKBikSZ/YVKTEvEVwAwgQn+ATiOHU7KAMDNnHRyHm3REzvGjFCLCTipzpFc4RJkfCYAwBx6lgGwhQjz+gMADHDKiXq43jh2UNMe0bEMD03GNAiwN95jAEg/epYBqLFwDTfvlfNQDX2PJ/AnHP/7vFdZaSgCAPyZ7qUV7fliKZ836Rcc6xIdlhdvjIU5TDMBAPbjsSxmK0hEaWmp8vPztX37duXl5ZkuDmALwY29cCcH0SbyD3U/RyqkA8d2e+B9OCCVPUpSsW+TQx7tmGiIVsexJtHiMWxY9X1IxFg7y5TVLjm2A3AShmECSJuSkhINi9D4i3b1206Nea4CA3CyVCW1Qq3ml8mixYhkrcIZC3qR2Vc6PwcAgNiQLAOQdJEafNNLSjRMxWkrCwAg/Uyc+DvpIoZ/WZOZUEv0tdvtglQmCreaa/B9AID0IFkGJJGTGuqpEG74pRtl6nsMIL1Seaxx63HMzhP+S4nFSHrsAQCQXiTLAAAAbCiV8xilOplk+uJJPBev6MEjzVhaJinXdDEAALANVsMEUiDcCpCZItKwkkRPRBgeAgBwuuC2QbS2QqhVpVOxKvTgAhJldsLK3wBgHj3LgCQyfSXd7oqLi8X8wgCQOZKxumNNhBqSmY4pE0z0VisuLtbMZfQQcxMSZgBgDskyII2cPKdZTRv+xcXFCa/ERa8yAJmIFfLiE+8Fq0gxOR3Jrlj26/+aIpX3QIyNP1FGjAUAoDqSZUAKODEZlqhYTyjiTZTReAeAzJRIkjDSY0wkHBNpB9RkjjpiLAAAyUWyDEBEoRrv4a5uB9/u/T/uDmU04gHAtcIltvxjSrwJM6f0wAsXN+N9XLjbYkGiDACA6EiWAWkUaul3O/dCS/Tkw/+1JTL0knY8AFSxc4yoiVDx0HQ5nCjR6Q0AAEBkRlfDnDRpknr06KG8vDzl5eWpsLBQb775ZsA2y5cv15AhQ5Sfn6+GDRuqT58+WrduXdh9/uc//9ExxxyjRo0aKTc3V0cddZReeumlgG3GjBkjj8cT8HPQQQel5DUCbuf0Ew3AjYivcJJwK/9Fuj2e/YTbLp45wwAAQGYx2rPs4IMP1gMPPKDOnTtLkl588UUNHTpUCxcuVLdu3bRmzRr17dtXF198scaOHav8/HwtX75cdevWDbvPJk2a6K677lLXrl1Vp04dzZgxQxdeeKFatGih0047zbddt27dNHfuXN/f2dnZqXuhgENFGwYT6b5hxcUJjL8EkAzEV6RLsnpJB8eTSPsLtcJlqH0koyyme4FHqhd6lQEAkDpGk2W/+93vAv4eN26cJk2apM8++0zdunXTXXfdpUGDBumhhx7ybXPIIYdE3OdJJ50U8Pf111+vF198UR999FFAY75WrVpc7YZRbr1a7dbXBTgJ8RV2E24xmEiT8scST5wyV1k48a7g6ZVoomzG0jIlsmImAACZxugwTH8VFRWaOnWqysrKVFhYqMrKSs2cOVOHHXaYTjvtNLVo0ULHHXdcXI0Jy7L0zjvvaOXKlerXr1/AfatWrVLr1q3VsWNHnXPOOfruu++S/IqAzOT0ExfAbYivSKVYhzMm+zlLSkoSijfxDNO0s0Qn6S/qRqIMAIBYGE+WLV68WA0aNFBOTo6uuOIKTZ8+XQUFBdqyZYt27typBx54QKeffrreeustDRs2TMOHD9f7778fcZ/bt29XgwYNVKdOHQ0ePFgTJ07UwIEDffcfd9xx+sc//qE5c+bo73//uzZv3qzjjz9ev/zyS9h9lpeXq7S0NOAHQHiWEmvMs0oXkBxOia8SMTaTRRtuGW2bcPtMZsIrlYkzb9IvkfnT4o2XM5aWEWMBAIiRx7LMhs09e/Zo3bp12rZtm6ZNm6ZnnnlG77//vho1aqQ2bdro3HPP1SuvvOLbfsiQIcrNzdWrr74adp+VlZX67rvvtHPnTr3zzju67777VFJSUm0IiVdZWZk6deqkW2+9VTfddFPIbcaMGaOxY8dWu3379u3Ky8uL70UDDhPv1Xtvg97j+yc2NOJhWmlpqfLz811xbHdKfJWIsW4WS8IrWowJ99hwjwvePtwQUDsILluoOcrC1SExFk7jphgLwP2MJ8uCDRgwQJ06ddLEiROVm5ur0aNHa9SoUb77b7vtNn300Uf6+OOPY97nJZdcovXr12vOnDlhtxk4cKA6d+6sSZMmhby/vLxc5eXlvr9LS0vVtm1bDvbIGLEkzGjIw+nc3JC3a3yViLFOFi0RFS7RE+12f9ESXHZOhkWTSGz1infeMmIsTHNzjAXgPkYn+A/FsiyVl5erTp066t27t1auXBlw/7fffqv27dsntM9wysvLtXz5cp144olht8nJyVFOTk5czwu4SSwTMvtjkS7AXuwaXyVirJvFk+jKRMG9yUL1Lgs1THPmsjJZVi4rYgIAkCJGk2V33nmnzjjjDLVt21Y7duzQ1KlTNW/ePM2ePVuSdMstt+jss89Wv379dPLJJ2v27Nl64403NG/ePN8+RowYoTZt2mj8+PGSpPHjx+uYY45Rp06dtGfPHs2aNUv/+Mc/Aq5o33zzzfrd736ndu3aacuWLbr//vtVWlqqkSNHpvX1A04VqjEfzBLL2gOmEF+RSZzWmywc7+uIJcYOLiBRBgBAKhlNlv3000/605/+pE2bNik/P189evTQ7NmzfZMFDxs2TJMnT9b48eN13XXXqUuXLpo2bZr69u3r28e6deuUlXVgnYKysjJdddVV2rBhg+rVq6euXbvq5Zdf1tlnn+3bZsOGDTr33HP1v//9T82bN1efPn302WefxX1FHchkqTg58XgYJgIkA/EV6ZKORFWsE+A7VajXRowFAMAs281Z5hSMuQciS+SKN0cjmMax3R54H9wj1Nxk0Sb9T2TeskxDjIUTcWwH4CS2m7MMSCcnTwpsVzOXlamoW64si2GYAIBAoebj8oo0DDGWVTUzgTeuEmMBAEgtkmWAH5JnNTe4IFdSfI14rnYDgLvFO5F/uEVl3D4kMxpvkowYCwBAapEsg6tFS37F0+AmkRabRK50M48KALiTN17GkiwLF2djmfA+UxBjAQBID5JlyBjJvBrNcJDQfG14K/iG8GjAA4C7JTIHWXDMjjfecoGrCjEWAIDEkCxDRsn04Rs1Fe3kw/L9s3/uMuWmo1gAAIcy3WvMaYsJWP4xthsxFgCAVMmKvglgPyUlJb6fSEI1eGN5XKz7QnhFBbE14pmgGAAyW3FxcUpjrBuHcMaaKCPEAgCQGHqWwfXimS8lWmM9nn0li9OuevvE2EJniAgAuJt/77FI8SuZMTbSvoJ7SbsxmeZFiAUAIDEky+BIiSSLktkgdkSyKsWC6zK4TrxJMHqOAQDiiZsmY6xT4jsxFgCA1CJZhozilEZwOMFXytP9euJJOHo8in5Jm0veAIAUimUhASciSQYAQGqRLANsymkreQUvnmBZMYzEjCWhBgBAEkW68OOU2GtZJMwAAEglJviHo8U60b/TOOX1RDuRmLGsLD0FAQAgQeFimVNiMQAASD56lsF1nHJVOBmCe3OlQyzPd+Bqd+TVupjcHwDMMBE/nMAJE/7H2qOMGAsAQOJIlsHR/Bu1dm/cxsMNJzAzlpbFvLQ9AMBe3H7hKdbXRFIRAIDM5LEsrjslorS0VPn5+dq+fbvy8vJMFyejhJvc3u0N+2CmJvmPB1e/4TQc2+2B98G8aCseu50T2hTEWDgNx3YATsKcZXAduzZqk624uNj2r9WyqnqYAQDsLdr8n26cH9TpiLEAAKQOwzDhWME9q+yeOMpUgwuYtwwAnISkmHPaFMRYAABSg55lcBQnDD1ECBEa6x5P7ENJAACp4e2tTKLMXYixAAAkhp5lgIPZfU4Vj6ryZNb+30OKeCcAIBX8Lz7FciHKjjEm1eweY70sK0pCjN5lAADEjWQZHIkr385gKYYr2iTKAMAY/3gaLrbaOVGU6eg1BgBAajAME47ihEntEYj5UgDAuYi59mZ5u29HQkINAIC4kSwDkBL+bXPLitygJ6EGAEDs/HuUWYocR4mxAADEj2GYcCSudFexez14PIGN9FDTk1Utex95NS8AQPrZIcaYXNjHDq8/kmoxNsTcZSTKAABIDMkyAClhSfL4N9zDTORf1O1AooxGPQAkRzqTTOmYCL+kpMT2yat08ibGos1ZFtADjRgLAEDMSJYBBjhlha2a8ibMvO1zT4SVL2nEA4B92CU2+a/WGauMibFWYO+ySIkzYiwAAPEhWQYgLvGehFhBv4dqy9OIB4DkctOwRTcnvGoq2jDM4G0AAEBsSJYBSKtwjXkAgD3Em5yyezLL5Lxn6UaMBQAgOeJOlpWXl+uLL77Q2rVr9dtvv6l58+bq2bOnOnbsmIryAa6UyLASAO5HjEUyBceZmiSL0j20sSbPlwlJMQAAkFoxJ8s++eQTTZw4USUlJdqzZ48aNWqkevXqaevWrSovL9chhxyiyy67TFdccYUaNmyYyjIDruDfmHfSVe+alpEr3kB1xFg4Sbon20/W8zkp1iaqWoxlCCYAAAnJimWjoUOH6swzz1SbNm00Z84c7dixQ7/88os2bNig3377TatWrdKoUaP0zjvv6LDDDtPbb7+d6nIDrlRSUpI5Pc5owAOSiLFIvlCxxM0Jomgy8bX75injAhUAAAmJqWfZqaeeqtdee0116tQJef8hhxyiQw45RCNHjtTSpUv1448/JrWQgNt5G/JuT5QFLGHv+wfIbMRY2Em4xFKqEk7hensle7qCTJj+ILhXGRP7AwCQuJiSZVdffXXMO+zWrZu6deuWcIGATOa2q9/eJe3DDb30iHwZQIxFqjk1tiS73E6th3Cixdh0zzMHAICbsBom4GB2nX/FW67p0yWPp7ja/aGudtv1tQCA0yR6HOX4e4ATEk3hEmXEWAAAai6mOcskadWqVTr11FPVp08fzZs3L4VFAuB23sa9JSb8ByRiLNIr1HBEU0mU4uJi2ydwnDafqDeuFhcXa9gw+9cvAAB2FHPPsosvvljnnXeeevbsqUGDBumnn35SrVp0TANMCp7rzEkNYs/+MZjBV8Cd+FqAmiLGIl0iJX2c0JsqXZwyl2i43mW+i1LEWAAAEhJzz7Lvv/9effr0Ua9evbRjxw5t27YthcUC4GTengLRGuP+bXga7shkxFikQ6yJsmjbwj4i9c72T5QRYwEAiE/Ml60vueQSXXHFFWrVqpUGDBigZs2apbJcAOJgx0ZwtAZ8qLvt+DqAdCDGwo5KSkoy/rhs19cfNcYyxQEAADUSc7Js9OjRGjBggLZt26bTTjstlWUC4GAe3z/7WVV/W5Y0c1mZirrl+m4GUIUYCyAW4ZJgwQmyUJP82zXxBwCAHcU1IcoJJ5yQqnIAcCu/xvvggtyQDXgAxFi7cNucTuHmIXPiMMtkvDdue3/9EV8BAEiemOcsi4dFtAYylv+337IO/ABIDmJsejgxmeRWqViN0qnvb/DXnxgLAEBqxJQsO/zww/XKK69oz549EbdbtWqVrrzySj344INJKRwAZ2POFCA6YqwZ3gSMf9LEqQmUSGrag8pOdRLLwjGx7AMAACCamIZhPvHEE7rtttt09dVX69RTT9Uxxxyj1q1bq27duvr111+1bNkyffTRR1q2bJmuueYaXXXVVakuNwAb817ljpYr83i4Ig4QY+3JTUmVUK+luLjYVomwSJL9Xjj9vfXFWC5IAQCQMh4rjvEcn3zyif75z3/qgw8+0Nq1a7Vr1y41a9ZMPXv21GmnnaY//vGPatSoUQqLax+lpaXKz8/X9u3blZeXZ7o4gC15G/KhjjIeMck/7MfksZ0Ye0A63odwc3llmlgSZt76cfN8X04UMcZyMQo2xPkTACeJa4L/448/Xscff3yqygLApUJd/Z6xtEwqyE1/YQCbIsZmDjsl6oITYeHu91dSUmK83DggVIwlUQYAQM3ElSwDgGhmLivT4BiSYEXdqraZsTS27QEgmUwke+w87DHelTLtljDLlF5vscbYSL3OAABAdHENw8QBdCMGwvN4qpJg3oRYJByBYCcc2+3Bje9DPIkyOyd8Qr0OO5Q3U5JlUnxzlRFjYSduPLYDcC96lgFIuqrGeWy9xZhXBQCcw64LA2RCkswrngn+ibEAACSGZBkAAEAUkRJEmZSokeybMAMAAEgWkmUAUsayWNoegPORGKou0xKEdkSMBQAgdRJKlq1Zs0bPP/+81qxZowkTJqhFixaaPXu22rZtq27duiW7jABcjOEhQCBirLvEmmgj+YR4zVxWpmhTHhBjAQBITFa8D3j//fd1xBFH6PPPP9d//vMf7dy5U5L0zTffaPTo0UkvIADninU+FQBViLH2FCmRRZILpsSyiA4xFgCAxMSdLLv99tt1//336+2331adOnV8t5988sn69NNPk1o4AO5mWVz1BvwRY+2ruLjY9wM4ATEWAIDExT0Mc/HixXrllVeq3d68eXP98ssvSSkUAJewJHFVG4gZMdZ+/IdRBifKoiXOmOsMKUWMBQAgZeJOljVq1EibNm1Sx44dA25fuHCh2rRpk7SCAXC2aEM/uNoNVEeMdYZU9y6LlKADJGIsAACpFvcwzPPOO0+33XabNm/eLI/Ho8rKSn388ce6+eabNWLEiFSUEYCDeDzeSYcBxIsYm5n8E2LBvdH8/y4pKaG3WoZjDjIAANLDY1nxXXvau3evLrjgAk2dOlWWZalWrVqqqKjQeeedpxdeeEHZ2dmpKqutlJaWKj8/X9u3b1deXp7p4gC2w1VvOJHpYzsxtorp9yFZ4l0JM55EGD3OMhsxFk7klmM7gMwQ9zDM2rVra8qUKbr33nu1cOFCVVZWqmfPnjr00ENTUT4ADhTTKpiqmm4FwAHEWPegBxhSJZYYO3NZmQYXRF8tEwAAhBZ3ssyrU6dO6tSpUzLLAsDFLCuwgT9jWZlEQx4IiRibORLpVYZA3rrL5N52wTGWRBkAADUTU7LspptuinmHjz76aMKFAeB84S54B18JpyEPVCHGZi47J3dYZMCewvUq897O8EsAAJIjpmTZwoULA/7+8ssvVVFRoS5dukiSvv32W2VnZ6tXr17JLyEAx/B49l/dNl0QwEGIse4UrcdYogmodCSuwi0yYPekmVPKmShfjI0QZEmaAQCQHDGthvnee+/5fn73u9/ppJNO0oYNG/TVV1/pq6++0vr163XyySdr8ODBcT35pEmT1KNHD+Xl5SkvL0+FhYV68803A7ZZvny5hgwZovz8fDVs2FB9+vTRunXrwu7z73//u0488UQ1btxYjRs31oABA/TFF18EbDN+/Hj17t1bDRs2VIsWLVRcXKyVK1fGVXYAgbwrYMa6UhcregFVUhFjia/2U1xcHPAT6n47iGc4qF1W57RL3aUDsRMAgPSIezXMNm3a6K233lK3bt0Cbl+yZIlOPfVU/fjjjzHv64033lB2drY6d+4sSXrxxRf18MMPa+HCherWrZvWrFmjY489VhdffLHOPfdc5efna/ny5erdu7datGgRcp/nn3++TjjhBB1//PGqW7euHnroIf3nP//R0qVL1aZNG0nS6aefrnPOOUe9e/fWvn37dNddd2nx4sVatmyZcnNjGxrGai7AAYk23rny7U5O7t1h+tierBjr5PgqmX8f0s0Oq2AmUgaGaqYHMRZukWnHdgDOFneyrGHDhnr99dd1yimnBNz+7rvvaujQodqxY0eNCtSkSRM9/PDDuvjii3XOOeeodu3aeumllxLeX0VFhRo3bqzHH39cI0aMCLnNzz//rBYtWuj9999Xv379YtovB3vggEQa8jTi3Sn4hNtpJ9Cmj+2pjLFOia+S+fch3UwlyxLtFRZuiKnTvu9OQYyFW2TasR2As8U0DNPfsGHDdOGFF+rf//63NmzYoA0bNujf//63Lr74Yg0fPjzhglRUVGjq1KkqKytTYWGhKisrNXPmTB122GE67bTT1KJFCx133HFxN+x+++037d27V02aNAm7zfbt2yUp4jYAQounEe/feGcoCVBdKmIs8RWh1DRR5v09XILMO0TTDsM0nYwYCwCAGTFN8O9v8uTJuvnmm/XHP/5Re/furdpJrVq6+OKL9fDDD8ddgMWLF6uwsFC7d+9WgwYNNH36dBUUFGjz5s3auXOnHnjgAd1///168MEHNXv2bA0fPlzvvfee+vfvH9P+b7/9drVp00YDBgwIeb9lWbrpppvUt29fde/ePex+ysvLVV5e7vu7tLQ0vhcKuJWluGf0jzZBMeyvpKQk4rxLnCAnJpkx1inxVSLGOkW4xBg9ypLPO5l/IuhV5mzxTGXAUGgASJ24k2X169fXk08+qYcfflhr1qyRZVnq3LlzXHOR+OvSpYu+/vprbdu2TdOmTdPIkSP1/vvvq1GjRpKkoUOH6sYbb5QkHXXUUfrkk080efLkmBrzDz30kF599VXNmzdPdevWDbnNNddco2+++UYfffRRxH2NHz9eY8eOje/FAZkgjqRX1SIAVccKGvPOFGsSjEZ7YpIZY50SXyVirJOEOgZE+747eR5DU4iRCL4oxfcIANIr7mSZV25urnr06FHjAtSpU8c3AfExxxyj+fPna8KECZo4caJq1aqlgoKCgO0PP/zwmBref/nLX/TnP/9Zc+fODVvOa6+9Vv/973/1wQcf6OCDD464vzvuuEM33XST7+/S0lK1bds2ajkAN/N4pBlLy1TULbYT+Vi3AzJdMmKsU+KrFD3GcpJYxa6vP1RP01An+aEeF7wtDvD2LmOV6cwR7bvi/3ukYdAAgJqLO1l28sknyxMhGr/77rs1KpBlWSovL1edOnXUu3fvakvOf/vtt2rfvn3EfTz88MO6//77NWfOHB1zzDEhn+Paa6/V9OnTNW/ePHXs2DFquXJycpSTkxPfi4GjMXFxbGJJgPk39pNxtZwTLLhVKmOsXeOrRIx1imQOrw4++ed4HlosCbBkx1g4A20hAEituJNlRx11VMDfe/fu1ddff60lS5Zo5MiRce3rzjvv1BlnnKG2bdtqx44dmjp1qubNm6fZs2dLkm655RadffbZ6tevn04++WTNnj1bb7zxhubNm+fbx4gRI9SmTRuNHz9eUtXQkLvvvluvvPKKOnTooM2bN0uSGjRooAYNGkiSrr76ar3yyit6/fXX1bBhQ982+fn5qlevXrxVApeJdFWPBkmVeK9e+7avQSM+VKOQ9yT9qO/USlaMJb46Syxz/Tn5uxdc9liSbpk8F5PH90+M25Moc43i4uJq349QF2+ZFxQAUi/uZNlf//rXkLePGTNGO3fujGtfP/30k/70pz9p06ZNys/PV48ePTR79mwNHDhQUtWqYJMnT9b48eN13XXXqUuXLpo2bZr69u3r28e6deuUlXVgUc8nn3xSe/bs0ZlnnhnwXKNHj9aYMWMkSZMmTZIknXTSSQHbPP/887rgggvieg1eHtUoDwCboPERG2+DPO4hH3xRMkomn+wmKlkx1k3xVZKGFRdn9KEjFd+fRBJY0fYVS0+XeBNlmcja/08iF6ZImDlfuGRYpJVnibEAkHwey0pOWF29erWOPfZYbd26NRm7s73S0lLl5+drypQpOu+880wXB0kSrYFOY6S6eBvziR5xGG7gPE5MlnmP7du3b1deXp7p4vgQYzNHtCkAUnUsrGmCKvgEP9KJfajHRtrGKcePVEhXjIX9+X/3nfodsWuMBYBQEp7gP9inn34adkUswMmc0gBJp3iHiHjVpBHP++Asmd4zJNmIsZkj1mNdMnuTJOP7WpN9BCcAE3ldTkzOR5LIZP0kyjID8RUA0iPuZNnw4cMD/rYsS5s2bdKCBQt09913J61gQCpEa0zHemU847HiFuJg9++RnT7OxFjYWbS5kmL5rkfaBz2Iq7CqJUKJd3imnXgvsv7r8zLTRQGAmMWdLMvLywtYqSsrK0tdunTRvffeq1NPPTWphXOCoqIi00VAjGK9EueERoctWLJXlgHwE8+aEv7blErKT35xYkaMRTSpjFGxLDQQ7bGpep5YLnYBSI9oi0oET1HrnYevtDT6CuoAYBdxJ8teeOGFFBQDgOOQKEMMTJzAOnkdCWIsTIj2Pa3p/cksC4ADjMTYGBaScGoMBgB/WdE3CXTIIYfol19+qXb7tm3bdMghhySlUIDblZSUZOScEwwtyRzFxcVpb8TH2pvMzh9DYiwySby90fx7pEWKocRYuJUdksnREmV8DAG4Rdw9y9auXauKiopqt5eXl2vjxo1JKRSQKZy23DcNcdiVk3uT+SPGVue046QbRKrvZM/tWZPHR5vjzGmfHWIsYmHX3mRebojFACDFkSz773//6/t9zpw5ys8/MKtLRUWF3nnnHXXo0CGphXOCGTNmqH79+o5qjGWqZL5HsVyxjudkwyn8G0qJNuq9Da54Gl5AOJF6k3kTaMEfVTt+7IixcJJUt3lqGh+JscRYJIf3cxTqs1QtxvKZA+AyMSfLvA0jj8ejkSNHBtxXu3ZtdejQQY888khSCwc4WbQr2k5NsCbjyjdXz5EMsfYmc0LbnRgLJJdjY6zvnxrsgxiLJIiacN0fhH2bOCHYAkAcYk6WVVZWSpI6duyo+fPnq1mzZikrlNM4tUEGJMJ7xToZuPKNRMWSKHPSR4sYG1pRUZHy8vJMFwM2U9N2V3CvMzu145K50DQxFomKaRJ/PlsAXC7uOcu+//77VJQDcA07NbqTjavVsAO3zE8WCjE2kHeqA8ndx1bEzs2fA2Is7GDmsjJZVq7pYgCAcTEly/72t7/psssuU926dfW3v/0t4rbXXXddUgrmJE6bQBY1F24+FLd/DpLZqwxIlNsSZcRYIFA6Y6xd4rY3QUGMhWlFBbmui7MAkAiPZUXvRNuxY0ctWLBATZs2VceOHcPvzOPRd999l9QC2lVpaany8/M1ZcoUJvh3sWgrbWWaVDXi6cqPWKW6V5n32L59+/a0Df8jxlYXHGMl+xyHk7kSJCJLdV3bbTgmMRampXrorokYCwCJiqlnmf+wEIaIVGe6cYXU8G9E03uwCj3LYJJbh18SYyPj2OscyU5uZdp7T4yFaSRWAeCArHgfcO+99+q3336rdvuuXbt07733JqVQTlJUVGS6CIBjhVuOHMhUxNhAyYqxJSUlIYf1JaK4uNiXxEnmfp0uuB68deOk+vEvs5PKHQ4xFvEgUQsAgeJOlo0dO1Y7d+6sdvtvv/2msWPHJqVQAOwpFQ0pN52YADVFjIUTOfX47d9zzQ692IixAADYR9yrYVqWJU+IaL5o0SI1adIkKYUC7MAODWcAB2RCBwlirHMQI5ybJPPH+whUoRciAASKOVnWuHFjeTweeTweHXbYYQGN+YqKCu3cuVNXXHFFSgoJwLxUdc/nRAUgxqYaxxkkIp3zlRJjAQCwl5iTZY899pgsy9JFF12ksWPHKj8/33dfnTp11KFDBxUWFqakkADMSlUj3q0TtiP53P5ZIcbCzZyySE5xcbGR3nLMFQXTUr0KJgA4UczJspEjR0qqWuL++OOPV+3atVNWKACZgXYZUIUY6zzJXvnRiUwll9IlU99XAACQwJxl/fv39/2+a9cu7d27N+D+vLy8mpcKgK3MWFqmom65Sd9vqN5C3hMvTlKQiYix6UGiC+GY+DxYFr3LEBltIwBIv7hXw/ztt990zTXXqEWLFmrQoIEaN24c8APAfYoKkp8ok1SVLQuD1buQiYixzlFcXOw7cc3kY1UiJ+/+KzRmct15pWyqAxJwrsP3BQDSJ+5k2S233KJ3331XTz75pHJycvTMM89o7Nixat26tf7xj3+koowADJuxrMx0EZDB3D5fmT9iLJwkkWQXJ/vpwxxUiBWfFQCoLu5k2RtvvKEnn3xSZ555pmrVqqUTTzxRo0aN0p///GdNmTIlFWUEYNjggtyUNKRC7TO4lwInVsikNjwxNj28vcIY0pS4eI7N1HNklpX8ZAXJD3fhOwQA6Rf3nGVbt25Vx44dJVXNnbJ161ZJUt++fXXllVcmt3QAbMXb+GZoB9Ilk3qVScRYJ+IkNrJo9UP9HZDMGMvqhu6Tiu8KnxMACC/uZNkhhxyitWvXqn379iooKNC//vUvHXvssXrjjTfUqFGjFBQRgN2kejJit6+whthkWqJMIsbC2aKdzHNcjw0T/iMdSJQBQGRxJ8suvPBCLVq0SP3799cdd9yhwYMHa+LEidq3b58effTRVJQRgM0kqxEf3FDz/5veBpktExNlEjEWzhG8uEEix2yO86GlI8Yis/FZAIDoPJZVs0PlunXrtGDBAnXq1ElHHnlkssple6WlpcrPz9f27duVl5dnujhwgHgbJt5kQToaNP5X+6OdvKTqarf3SjqNt8xmOklmt2M7MdYe70Omiic2xLu/ZO3TK9H4Ybe4Q4xFKpn+DHBsB+AkcU/wH6xdu3YaPny4mjRpoosuuigZZQJcydtQjdYQ9t5v+f3ufVzwY5PRqA43LMb/udMh3c8He+I8LhAx1n68K0Bm2pBCu7/eeGJscLxJZYyNVI5UP4fJ54M9kSwFgNjVOFnmtXXrVr344ovJ2h2QcYIb8OEatKEa9alq/EY7kUiVdD4X4ATE2PSJlAgLvj1TE2fJkO4hmLHGzbTFWMtgjBUxFgCAaOKeswxA4oKvfCdj5auaPnb69AN/B5y8WPIbC5r4c9SEfz2ZHjqA9DA9DBOZK1TCiyRYcqU6QZaqGDtjaZmk3IQeGy5uWfv/MZK0CuplRozNHLzPABA7kmWAQclqJEdq+Hh8/8iX+Aq10lbwSYwvR2bw6nMyTnQAIBqSYu6UrNgxuCByoixU0imW5zYd24ixAACER7IMSJB/gzhUsiqZV7ZjKUvVkwX2yqn2nCHmLBk2rLja4+zCv5xcCUUyJXvicjhXpERZ8IqP0bZLh5qsPlkTJoZNRrwQlM4Yq/AxMtRwzeDbZiwti5pwM4EYm3kS7SUJAJko5mTZ8OHDI96/bdu2mpYFcJxIE+bGOtlwcgskeRJJfHn8Op+ZGhYSA4YPwK2IsekXS2+yTO9xZjqRbJveWftjqxTlglQYRd0OJCdijbHTp5dI2n9BK02Ise5X1C2X9xgAYhRzsiw/Pz/q/SNGjKhxgQA7Cm5ABjd0w85JEnS7fw+wlA1v9NRs17E2/tPdkPdPTNLQc6dMnq+MGOtcphNKbpBojA3eR0p5Av5LfDdxJMq8v6cjzhJj3W/msjJZFr3KACBWMSfLnn/++VSWA3CMmgxb8A3blAKyAnbtyRVOcENeSu/Vb6Se24cpFhcX26rXEDE29Wr6fqf7MxP8XN7voRu/j/4SjbH+wzHDXqhyAP/4CiSTyV5l3uPZKaecYqYAAJAA5iyDK/jmD9P+TltJujIaaen4RPfv5Cu2Rhrxwb3wIpwQITVKSkpSfoJuoleZ/3xUbk9AID6hElOpSJTFk5RO9uc0nucOnqOTGJt8dkmSeee0Isa6i13ezxkzZpguAgDEjGQZXMWbKPMKNbQj1sZCpCvRyW5w2HmeMC9jDflQixSQMEu5WCc2TwZTwy/t1LMMqRcu8RVLAsrEZyXWnmzJmPA/1kRccKwixrqPf+8jYqw78D4CQGJIlsEVQl3pDnXFOtF5T9LRcHRyYz7dQzCdWk9ORI8r2F0iQ4Zj3S7Vq2BGe7xdvn/RYqz3b8uKnrwjxtof9YRk8x4PSktLzRYEAOJAsgyuEa4hnMxGXzKHnyA5eD+cI1QPMpOT+tslEQF7SnWiLNJzhtq36XkEY4mx/mVMZNhopsZYuwzBDCWTF15xi0z7PgFAspAsQ9LE03urps9T7ep2klaXjGXOFO98HqnAle8wvO8DdQNklBkzZqh+/foRky6pTFrZ6TkjbZvMHm7RepDFIzhhlqx5yRLl1BibqhUxq9oz0uCCA22amcuqbivqlqsZS8s0OEXtHaRHJiafASBZSJYhabyNUP9J9r23J0u4Rm6subJIZYq1Ee/fqEwF/+EodpGOq96h6nvmsjIVxVDfNVmhFOljp15lQDgmEmUmhHodYWNsEpJMscbYVB/D7RBjTfQkC93uqb46oreNY1nSzGX743C3A3GYGOscJMoAoGZIliFpPH6/+LdBkxGsIzZqQzTiI10Vr0miLF1MJ8ribcin6qr34ILcwERoknoQwjzeRthRKifyjzaMMpb5y0KVb9iw4tTG2DD3x5N0iifGJmPBgnjLk6mifW78k2RwlpnLymRZvH8AUBMky5A01v5/fI1Qv8RGIgmzSFe4o20TvH247dzYYA5OdKV78v1EzVxWFrbXXryjMLmaam/0KEOsioqKlJeXl5bniiVRZsdeZdOnl8jjiT9hVpMY679NpBgbKf5ES4qZnqMtGm+sdUqMTWZcJMbam0eSleJREACQCbJMFwDu421AWb5/YuvNFW4/oR7n/Ym3TNEeb1n2aAAmWgY7TxIc1v46T+rwVofOSwMgdiUlJSntCRYsmQmbRMsdrgx2irHBpk8vCfhxcoz18o+13tdVtePYHp9Igi3R+O5t18S6Grh3zrLgx3t/9/5PjLUvG3zFAMAVSJYhJYIbZSEbVVFW1oo07CPU7dEag9Hus0MD3i7ScaXc957F8ZgZy8qiPsDjkcRVb9uiVxlQM8XFxdWSZvH0nvYmGZMZY0tKSkImc0Ld5t+jLPh1pDP5mRI2SiAlq10TKnFaNcSv5vtG8tnoIwgAjscwTASINBQuEf5TTMXTmI9n2+AGW7QGXHAvMzs3+OK5euuUXmXecnrPieLprRHTZ3P/h46kjP3QiEe6xTOUL9ycYLE8NhbJHkro3V+kC0yhbp8+Pfw+kxFjUyF4Vc1kSaSHlN1j7YHyFcf92Kr62L8KZkFu2PoZXJCb9PYiam7msjKJ9wQAkoZkGQI4qeGTSIPdrYkyp0jGSYZvbjzvDcF15Dnwv0fyNfphjv80hkCyJDt54vheTTGKtedwpF5kNRUq+ZXs+g/eX/DzmU6UDRtWHHV/8fby9t9fognGqvc9tmSYR1U9vomx5lW1aXOJswCQRCTLEJI3kRQuoeTfayfUNt4GqN2TUXYWTyPe1JVu7ypswe93qLInu4xWmOcJNrgg1/aJUTejhx/SJdSE8dGSBaYm9Y8aYz2Bx1O7xNhkJrTiTebEukpmrGU0fTEq1kSZf4z1f4x/Ii0VbQBv7zEpN+RFJ+9q1fRkMst7fKCNAwDJR7IMAaI10EOJ1OBPhhlLy1y9fHnYYUL+Y1htyL+h7n3vva/FO8wnlivnKeG/EqtoRJpAbzKkSqxJEzuyY4w13Ys52Qm4VAmOZbfccosefvjhmLdPpJeYf8JMOjB9gf/9qYyxRd2qEmVS4MT/9CQzzxdjCbIAkDIky+Dj3xiP1ni2FHhlPPjxXt6rkjWRqY0yS9LMGBKF8TaUgxNbXvE25L3vfaSTuGhlq8nJrmd/l6Xgp672ufXQqDSN3mVIhZokRkwMufR4qo6JJSWSZRXL4wl/scQ/QRYpxqZSPPO9JeM5UsFb7uCVU4uLi2ucJAyXKAuV2JICk1/xxO1Ix89UJcr86yW4DeafNPMfqskcZunj/Ux4CK4AkFIky+ATquEYrXEeant/bu4RliyRTkL8G57Bwx29J16RBCfA/Hs0BE/yHG9Dvmr1s8CTkXTxfi5nLiuTp1tuwGfU8p/PLAZO7qVid/6HDs/+f0hYIlXCfYeDv+PxHKuSdVzwHi+9wq1SGfyc0WJssnqEBQ/vC44BTpzPLdKCDV6h4mrw71J8Qyal0DE2lv2ELOP+/9P9HnjrIDgJdmB4ZvWJ/pnyID38L1hLgZ9V6h8AkifLdAFgH/5XC/35LxvubTilq0EU7sqvd1hAJrCswNeb6NVw//crXIN9+vSSuBvzJofveFfrCmb5/gkUvDKr6TlrMgp1jiQpLi6OKYkV3Jso0WSDdz8mLgikWqh4YvfVHsMJfn9ifb+C53tKZYyNR+3DBkoye8y0rNC9+/17k/nfFm5uPaRW8OJVAIDkoGeZDdhlbp+iCN3n/RuP3t5i6QjIwVfLvL1TirqFTpK4lbdhGmuPsnTy9vCym5BTvnkCE2ZV9VmcUZ+lVIk6GiR4HrmUlwhuFioRkopkVqgETE17m/n3+A3fi6s4LTE2uMebW8TSqyyUeHuUpZJ/8inRGJuMz2s4/j3MvILbbN72AcMza65a3Iwy6oN2DQDUHMmyFIrWQPD4/WKHoBbLfPImJgIOuOLr+yczBA/L8TaAYjkH8G8gV/VMS25j1X//gwtyVfJt/Puo2dL2sW68//8Qn9tIcwGl8iTDjaK+JX5XBfxXMrXDsQ/2F2n+rFgSI8kcLh7PsSHU8/kPeTfJThddksH/PUl0vjX/eeJirR/vqtDJFvwaEomxiYr19XgXAPBv7/q3E73JNJI3NRep+oLb5fEuIgIACI1kWQrFlChT/IEsXK+MmgbFWJJgJhNliK8+Ik3Qmy6JXt1PFu9V7Whz54VKlHn/J2GWmLAfVY/kseKfWw6ZK9QxJFTCLNy2kW5PlWjP503E2CFp5iT+MSUZx+ZQk/4nc5+pZo8YW/W7d0GnUG0P2nI159/29wTfEITefACQHCTLTAmemNOSZoQIbqF6nwVMml2DBFnAajoyv3x8sExvXIVrAHskxTtqxv9zkqyGdfBJRqhGux0mhY6lwcjkuDUX/F4XFxcHHL+CccUbiYqUxA6+PVXHoEgJm5o8J8mz2IX6HIQ6DoV7bCSx9uD2SvR4FmoYrhR7ItAuMTamkRSeql7uJHES458om7GsTEVW+ClRvBcIibEAUDNM8G9IQADbPyypqCA3dLIqePUrVZ903/e7DtwWicdTFWyDb4u0fTplcoCPNpF0LFUT6oTL44mvYR3upC3S5Np27YUV64IQ3s+d/2s0Mbm304Sqm4BjRtDxzi5Dz+F+6T4m2f044V3ExYlDMOPtRRU8LDPe9yaWz45/nEw0TgTHWqfFV6kqORNq/rKZy6qGaFoKv1gAYufxyDdvr+/vMIixAFBzJMtswPL/P6h3l/8cXb6kWHBwDOhqdqCnWjjehxd1C5OcM4wAH124IUiRxHtylK55ddJxchlrA90/8Wz3k15HCHWsYnZ/ZLhhw4p9P6H+RmJiOWbb9bjuff8jxfJEy56O12xZB+Yvk6ouUHl/j7YQABIUJVFGHQNAzTEM02ZCTbIfdeL9EA+IeC5KALW14KvnsSTCUtkYDj6B8+995SQBjccIXyqStcnhS7Z6k2PUK5LErsceuyZivJzYm6wmwg3XjXWopve+ahPtp/B9TtVcU8mc5y2cqhibWy1JFuo1EWdTi2kOACA5jPYsmzRpknr06KG8vDzl5eWpsLBQb775ZsA2y5cv15AhQ5Sfn6+GDRuqT58+WrduXcT9Tps2TQUFBcrJyVFBQYGmB62LvmPHDt1www1q37696tWrp+OPP17z589P+uurCW8Pl4CT+yhCzWkWaTs7snPZ0sk7DDBaIz7c4yy/7oqWlfyTpGQPS0znSWakz1i4+6K9F5kspvfO4/cj8mbp4Jb4OmPGjIC/Q81RFfwTLFXf3ViH6QX/IH3CJYliibHBQm1rJTnGFkVIlMVbVlNxy5sYC+5NhpqJp6cYbWkASA6jPcsOPvhgPfDAA+rcubMk6cUXX9TQoUO1cOFCdevWTWvWrFHfvn118cUXa+zYscrPz9fy5ctVt27dsPv89NNPdfbZZ+u+++7TsGHDNH36dP3hD3/QRx99pOOOO06SdMkll2jJkiV66aWX1Lp1a7388ssaMGCAli1bpjZt2qTltccjlt4w/ttFuqJEt2x3idQQTkdjKR1Xq2sq1Gc+3FfJf7ELO78mO4mpp0XAEl6MxEwHN8ZXu30n/Xsu0asstaK995Hq3/s+Jfr5SWTag4Q58OAYKsb6D72MZQEAJBc9ywAgOTyWZa/DaZMmTfTwww/r4osv1jnnnKPatWvrpZdeivnxZ599tkpLSwOuoJ9++ulq3LixXn31Ve3atUsNGzbU66+/rsGDB/u2Oeqoo1RUVKT7778/pucpLS1Vfn6+tm/frry8vNhfYBTeAFfjpFaIoZjBq1/aib0+he6T6IlctV4Q+z9XkYaxRHuucMmVVJyABH+f/FfiinViXP8EGqqL9H77Pj9+2Um712Oqju124JT4Kh14H6ZMmaL69etLin3lyXStiOl9rlD7t1sPsuBkWaqHEyZbtLgRS9xJpWTF2BlLy7T327cDbov385zOpHJwjPVf5X3G0jIVdcuNeswnsRMbj++fyOxel26OsQDcxzZzllVUVOi1115TWVmZCgsLVVlZqZkzZ+rWW2/VaaedpoULF6pjx4664447IjYEPv30U914440Bt5122ml67LHHJEn79u1TRUVFtavn9erV00cffZTsl5W4qBOVRX94yF3aMFEGewp5sueRSiL0UIhnguV0NOh9Q5P3N+bjmeg/eB+oAb/esXGMLEeSZEp89SZU/I8xqU4IxbJ//0RVKpNokXqP2a1XXrxqcoHFKYkyqWqS/KCRzXH3YAw3V1sqBMdY/9u985fNXHbgdv8Y7O1tRoyNUYztd5KPAJA8xpNlixcvVmFhoXbv3q0GDRpo+vTpKigo0ObNm7Vz50498MADuv/++/Xggw9q9uzZGj58uN577z31798/5P42b96sli1bBtzWsmVLbd68WZLUsGFDFRYW6r777tPhhx+uli1b6tVXX9Xnn3+uQw89NGw5y8vLVV5e7vu7tLQ0Ca++Om+Dw7IkTw0TZv5skyTzm1ctVQHdCUMD0yVdPQec0EMh+LNmWbFfqUV18b7n06eXSPsfwnczPZwSX6XIMTbRz4sTjktALJzwWQ4ZYz25kiXN2D8k0384JsMyU4NEGQAkj9EJ/iWpS5cu+vrrr/XZZ5/pyiuv1MiRI7Vs2TJVVlZKkoYOHaobb7xRRx11lG6//XYVFRVp8uTJEffpCcoMWZYVcNtLL70ky7LUpk0b5eTk6G9/+5vOO+88ZWdnh93n+PHjlZ+f7/tp27ZtDV51ZN5AN2NZWcJBz78KbJMoU+CieAR0+wrX+8Hp894Ec/JiGE7g/by47XPjFE6Jr1L4GFtUVBTxcamYyDzVvb/S/X1wY3I61qH/dn3tGRNjiaFJYad2PABkEuM9y+rUqeObgPiYY47R/PnzNWHCBE2cOFG1atVSQUFBwPaHH354xOEcBx10kO8qt9eWLVsCroZ36tRJ77//vsrKylRaWqpWrVrp7LPPVseOHcPu94477tBNN93k+7u0tDSlCbOqXldVV90SmcPMdg2UEHOoIXPZ9QQGyee2kz8ncUp8lZIXY+OZPzEcJ31mQ5XVrcdXt76uZLNdPXkkLT0w0b+3dxmT/seGRBkAmGO8Z1kwy7JUXl6uOnXqqHfv3lq5cmXA/d9++63at28f9vGFhYV6++3AyVHfeustHX/88dW2zc3NVatWrfTrr79qzpw5Gjp0aNj95uTkKC8vL+AnpfYPEfMkMMGPf3LNeJDdv6x6goJGXQAANHhJREFUOhNl/r0MvPPXOGEIQyok0mhOdUPbdg35CLyreXk8B37gjCFBqM6u8VUyEGNdKNk97OzCba+r9mEDTRch7Yq65QbEz5nLqib/9yK+JoftLpQDgMMZ7Vl255136owzzlDbtm21Y8cOTZ06VfPmzdPs2bMlSbfccovOPvts9evXTyeffLJmz56tN954Q/PmzfPtY8SIEWrTpo3Gjx8vSbr++uvVr18/Pfjggxo6dKhef/11zZ07N+Bq+Zw5c2RZlrp06aLVq1frlltuUZcuXXThhRem9fVH4puM3xv4fEtZRn+sL1GWkpLFhoDtPk7qbZEs/o15ic91vEmyYcOKM/JzYweZHl9NJ3SnTy9J6XDOA8ei1D2Haf4LNsQzwb3/49Mh3oUkwvWmyoRjZVG3XN8qmdKBuWszPbaGkkjykNW7ASC5jCbLfvrpJ/3pT3/Spk2blJ+frx49emj27NkaOLDqqtuwYcM0efJkjR8/Xtddd526dOmiadOmqW/fvr59rFu3TllZBzrIHX/88Zo6dapGjRqlu+++W506ddI///lPHXfccb5ttm/frjvuuEMbNmxQkyZN9Pvf/17jxo1T7dq10/fiY+Af7Hy/xzMk00C2zG4B2k1XoxPl35CPpVEf/PlKZBhwpLLYSayvy26fa6dL52ptmcot8XXGjBmqX7++728nfW5SkfzIhGNRqPfYdPIzmniG/4aKsfG+vnCx3G7fj2ox1pKKPAy9jCbRNlcmHB8AIJ08lsWhNRGlpaXKz8/X9u3b0z5cxJZd1ZmTzDEiNcqDe0J4E2XxnvSFasjbrREvVR8KEgpHyAOindD5Pj9+PWKdNqeSyWM7DvC+D1OmTEkoWWb35Eq8vc5SuXK0nQS/vzUpo6njTLQFB/zbcIkkyrz7CX4uOx5XY2mvEmMDuT1RRowF4CTGJ/hH/JLZ06em7BicwzU87diQNCFST7NQny23Dg2pep3Rr3B7h4m4nf9nAnAyOyaB4uV/3OU76VzxDtFMZP92ZZd2aqZgCCYAJJ/tJvhHdB6PNGNpWVXvjRBDNTM5ULrhJCndvJMnh7riXZPGrp0nZY7ndWXC98n/e5Podyigp4xHZidNhCvZ9XiSaXgfIguuH/+/vYvGSInFWDvHVX8kytKL9j8ApAY9yxyoKhjmHsiTGQqOTgjKoeYRcUJDM9VirYNk9CqzU33TgE+NeIaU2enzANiRW3vzRuK240K4hFlwCIrnvXZCHRFjay7eJKp3eye0yQHAaUiWuYhvFcwMbKw4YaJbt7Nzfbt9DhCToiXKhhUXM58haszOx5d4OTm5bLfyOI5L22fEWHNIlAFA6pAsc4l0J8hmLC1TLPM92QmN/MiCh2BGk+q5WJLJ+3ri/Z7QCI0s0kk/9YZkccuk/k4Wz2qPNdm3myUSY53C+3piWTTH38xlZRpc4Ky2ZKqxSjcA2AfJMiSkqFuu4wJ1Jg7DjOc1B3f9d+OJp50Wx7CTRL8T06eXRO0l44RVUeF80Y5XTknu23EIZqq+s5l2LAhuMznh8xgvEl8AADchWYaE2DlRlsor4G5n5/c1mfxfJ8kzAOkSzxBMu0o08ZhpybFMFmuMdeKF11SL5aIedQYA6UGyDK4Q3AgnSVYl0ZOTWOvPiSc/8SbKPB5JlrF1NBwpVEPeiZ8VmFdUVBTxficd652YKEvW9zbR/WRSYs6JZQ4l3mkPGIoZiAt4AGAfJMtSyL+Bl6pGEEEV8ajpUFS3NOalOL87nqp5mcOtOpWpc5uFO/n3rw83fWZgD/EmT0x+Bp2YIEu2VNY/xxfni6V3WabG2HCoDwBID5JlNsLcPqGx0mX6OWV+n0R5PFWLVAwuyI0raRZqW5JnALySmRxLdZyLZcqCkpKSGpUj2a+B2O8MiS6m431ccA/wTIqxDMMEAPsgWZZCbk84pEOi9edtUGfipP6RxFMP/p9ft9VfVWM08WEfwQ3Z4L8zviGb6a8ftpTqmBxrosx/En/TPc9SWR+mh3DanVtfl5T4Yjr+j/N/fCbFWEaMAIB9kCxLsXiTE5Iz5mBJx1W9UD3tnDT8xg1CJR2dnkBLx2c31NVxAMkRb6ysae8oU1Jd7kj153+sj1YOJ9YtbMZvioPgHmbhenR773cbVu0GAPsgWWZDsTY8My2YxnJi5PREDlIr1BXrZAqe2Nj7v3fIp1OE+x7FmrB24fkLDEvHHKCRDBtWHNAjLNT98ezL7oK/58EJM2IsQpm5rExF3RKIdfsX0vFPmEnhe5SFiuVuSpyRMAMAeyBZBltjKKs9ZNxJkqWqxnucQjZuLUnLDtzv9Aa99/2nIQ87S2bsSGdyy/+5TBwrnNTDHfaTUKLMK0RM8SWN9sdk4g4AIJ1IltmciUn/oy37bfJkP9Trp1GPZLEs3wVueRJMmHn3E2B/rzKnJcoS6c3jtNcIe5sxY4bq168f8r5oCbFkxcvp00s0bFhx1N5lsbJzjI2EntuoqVh6TIWa7D+T5iyLJpNfOwCkG8kyG7NjEsiyqrrZp2tIWbQ6iHS/6WE7bub0ug1ufPs3Pn2/1uAKttN7kNG7BHYU67Emlcck/55f3sRZsnqeeffn/drZ9djq1DngkD4RY2yUZLH3voAYGnTxyukxFgDgDCTLHMQOjdOqxk2u7RspnOTDn69hHdTgjvo5rkHvMjdMQBzumMNIGKRLUVGR8vLyJIVeaMQr1fHR27vMX6qHZ5KUglOES14lK/6FCsVuiLEAAHsjWYaQ7DovRPAwEHrAmOG0EzhvY9q/wR2pge37/Ps2PvB7tSEhURJqbrwCXoMcIhAX7zBM/2NOTY73NZnLLHgIZk2SZXaOscXFxVHrm0Qe/PlirBVbEivS5z84xoZaJbNqQ/nmMXNbjAUA2APJMhszNbm9XRvx/mIdBkhjHsHiaVT7GudBjX/v7TOWlmmwcl2ROIpnaK3T5lqC86VjbrJ0iTXGOu11AVL0OBDq8++Nqf6P9a6sGXZ/bgi8YRBjAcAeSJbZXKTGssmlpen+jkjcMqeZR5Isv3nMgraRcgO2z2gcC5BGNTmuhOs1FU9P5XSukJlu9NS2PycvthCu91n13wMTZaF6kGV83AUApBTJMofjJL2KqV54cKdkD+tw0zCRsFe8dWAlUSBZvHOWper4nsxkQ02HaQavtmmX40ao5KITkzROF6runTwcNpHPdvB3wndhyybflXiE+y7RqwwA7INkmQvEkzCLZRWieJ7XLkiU2Ycb3otkf7bt9F0JJ+rQS98/4TngZcJhvHOWSelL0Ji8+OKfYLPjccOpiRk3yfQYGyph5gZc+AYA+yFZ5hKxJsySGYzteCWPHmb2womVs/l/l6ziYskKnTSz23EAqKlosSTU6pjJZscYC/vI5Pjqhu9G8LBvy6r6O9ycbgCA9CNZ5iJWmBNZ//u93JY08280ZnID0m6cPEQkVt5JiMMKMXGxo+0fa+l9Od4hMOHmdgOSwcRxhIsvsJNMX/17xtIySfLFW1fF1SDB7XU3v1YAsDOSZS5j7f8nOBmWqiDrfR4CObyCTzDtkjBL1aIDgwtyNWPpgVW7vN8J39xDJZKmSyUl9kzkVkucWwH/HdjO/7YQk5NZ8lshtCBC8hCIk8nvTaQEhX/vsuD5ypLF//tJjIUU+jNpx9iSbMFxJdrk/3YRaQ6yqnIX+7bznyol1OthXlAASK8s0wVAakRbMSgVjQrmW4BXcMPd7VfCBxccWLUr0nfLTvXg6xEmVfUK8/5I0v77hg0rrvopLvYlw4J5H+f9PWIvOyBORUVFposgKXwyIlVJslA8nqpjiJ2OI7CHTPpM+CeU/GOY3QSUT34xNmjuYP+eY+FWCbX8LmLR1AaA9CFZ5mKWpYAGRHDgTgUSZvCyW8KsuLjYFlffw53spuO74z0G+DfIfQkyPwGN+v2tc4/kS6pFYter+0BNxZswmz69JK3JNGQWu8VYE/wTTDOXlUVMJBmNscE9sUPc7v+YmcvKwj4HIRYA0sdjWZzaJKK0tFT5+fnavn278vLyTBcnolgmC41lqep0LmcdqtFnh0QH4mPHYSLpGBZabShmCKGWi0/l0bimw7kyZV4yJx3b3czE+xAcd8IdJ+yalIjnuEaMdQc7xth0qOl3MBV1lZQYm+BjnYQYC8BJ6FmWofyDeqxX20JdHYvn8bGiEe8ednzf0pIos6I/l0fVh1Ok4sp3qKvciQjVAw1wq0jfXacf14ix7pGJ71s8cTLVK9ZKSY6xBFkAsBUm+M8Avm7qlgLmHYrW4AgXtP27vScbjfia89ahXerNLuVIK79eYmFX1PMc+C/ZDeR0LfBhmt0+63C2eD5HTl0pkxjrPpn4/g0bVhwQ19L5XUznKAs7I/4CyAQkyzKEZVWdlFfNg1DzCbiDJyhNFYIwnCZUgznaiXWi36OZyw6swhlqP5nWeAcyVagT11gSCMRYOE1wXIv0OQ83FUKs0zEED40kxgJAZiFZlkk8UpFyk9YzLJXzK9CATxx1Z0/e92XmsjINLgifsPb/XoWbA+XA7blBf2dW453POmIVbm6nWOcpcwp6ewCxix5jI2+XyTjGAMgEzFmWQWYsLYspURbLvAmp6lFmlxULgVSJlCjzF6qxHmpFW/9VtWjEA5BiT5o5cSgp4M//Mx5P+zHWGCsRYwEgU9GzLIN4T9LDJcwSaQTQcADSh+8bUDPBJ9NuvzhDMgyZIDhhFsvn3n+IpnchAGIsAMAfPcsyVPAVsngaCJmyvDWQSmF7hIX4XnFFG6gZei27PzEIeMX7WSfGAgBCoWdZhou3cUCiDEgta/8/fNcAJBO9zAAAAGJHzzLEjJN3IH240g0AQM3QoxIAkCiSZYiJkxJlJSUlXEGHIznh+wXAXYiZcKNIQ69JoAEAYsEwTETl8XASD6Qa3zEAyDz+iUqSOKnnrWPqGgAQDckyRMVJfOYJ7mVAoxIA4OWNEcSGxNCTDwAA+2MYJiLyDr90IhqjyROuLr3Dd6hrAHCmeFcK9T/ec+xPLuozNbyfcZK7AIB40LMMEbmlVxnDHGqupKQkYt1Fux8ATEs0FhBDkEz+n6FIF6NCbQ8AANKDZBlcJ5ZGKCIrLi6Oqe5i3Q4ATIn1GBXP8HM3HfdqOuyepE7yUH8AANgHyTJkFBqisYu1rqhTACakOkkTS4+fTMRFkuSKtGIj9QwAgDkkyxCR01fCpLEJAIhFcNKC2AHTuBgFAIA5JMvgejQ2AcBd4klkhbpoQlwILZ4exayICQAA3MxjWU7uN2ROaWmp8vPztX37duXl5ZkuTso4vWcZAMQjU47tdhftfQiVLAvXk7gmyZxM6V1GwgtAOhBjAThJlukCwN5IlAEAnCBZia2SkpKMSZJ5ZdrrBQAAiIZhmIiK3mUAALcLThiRQAIAAMhcJMsAAICjeIcNBq+IGW+Ci4RYFYZhAgAABCJZBgAAHCc4Ueb/f7yPBwAAAPyRLAMAAK4ULiFGTyoAAABEwgT/iMjjMV0CAACqKy4u9v0k+vh4bnezTFzUAAAAIBJ6liEiJvYHALhVqLnP3Jw0CvV6AQAAUB3JMgAA4ErhJv1PRrIokQUF7CBSmUPNAwcAAJCJGIaJiBiGCQBAdU5LlMWb/PK+PoZoAgCATESyDAAAuBJJniqJ9hKj/gAAQKYiWYaI7DJnGVe2AQCxSkbMiLR4gJOHKDq57AAAAOlCsgyOQsIMABBJLHEiloSRW+INyTEAAID4GU2WTZo0ST169FBeXp7y8vJUWFioN99803f/BRdcII/HE/DTp0+fiPvcu3ev7r33XnXq1El169bVkUceqdmzZ1fbbuPGjfrjH/+opk2bqn79+jrqqKP05ZdfJv01ugHzlgGAs7glvs6YMSPk7d6eY8HzarklwRWJt8dbLEkw/9Uva1JHJNwAAECmMZosO/jgg/XAAw9owYIFWrBggU455RQNHTpUS5cu9W1z+umna9OmTb6fWbNmRdznqFGj9NRTT2nixIlatmyZrrjiCg0bNkwLFy70bfPrr7/qhBNOUO3atfXmm29q2bJleuSRR9SoUaNUvVRHMz0Uk9W5ACA+boqv0ZI7iSR/4nlMcNxJZxwK9VyxxMRYk2mJlgEAAMDtapl88t/97ncBf48bN06TJk3SZ599pm7dukmScnJydNBBB8W8z5deekl33XWXBg0aJEm68sorNWfOHD3yyCN6+eWXJUkPPvig2rZtq+eff973uA4dOtTw1bibx2MmaZYJvQQAINncGl9NxYRICaN4E1rJGiaayLbhtg9XJhJlAAAgUxlNlvmrqKjQa6+9prKyMhUWFvpunzdvnlq0aKFGjRqpf//+GjdunFq0aBF2P+Xl5apbt27AbfXq1dNHH33k+/u///2vTjvtNJ111ll6//331aZNG1111VW69NJLk//CXMJ07zIAQGIyNb76D0GMddtE9p/ofYkm/mqawPI+r/9+iouLQ5aHnt0AACBTGU+WLV68WIWFhdq9e7caNGig6dOnq6CgQJJ0xhln6KyzzlL79u31/fff6+6779Ypp5yiL7/8Ujk5OSH3d9ppp+nRRx9Vv3791KlTJ73zzjt6/fXXVVFR4dvmu+++06RJk3TTTTfpzjvv1BdffKHrrrtOOTk5GjFiRMj9lpeXq7y83Pf39u3bJUmlpaXJqgrbm7OiTKd1zU3rc/7222++34uKijKqvgGkn/cYY7ngCoFT4qsUPsb269dPeXl5vvfFPyZEE+tjTMWWU045xfe7/9xsweXx306Kv90Rbt43737C3R9uewBIlJtiLIAMYBlWXl5urVq1ypo/f751++23W82aNbOWLl0actsff/zRql27tjVt2rSw+9uyZYs1dOhQKysry8rOzrYOO+ww66qrrrLq1avn26Z27dpWYWFhwOOuvfZaq0+fPmH3O3r0aEsSP/zwww8/GfCzZs2aOKOZ/TglvloWMZYffvjhJ5N+3BBjAbif8Z5lderUUefOnSVJxxxzjObPn68JEyboqaeeqrZtq1at1L59e61atSrs/po3b66SkhLt3r1bv/zyi1q3bq3bb79dHTt2DNiP9+q61+GHH65p06aF3e8dd9yhm266yff3tm3b1L59e61bt075+fkxv17UTGlpqdq2bav169crLy/PdHEyBvVuBvWeftu3b1e7du3UpEkT00WpMafEV4kYawccb8yg3s2g3s1wU4wF4H7Gk2XBLMsKGIrh75dfftH69evVqlWrqPupW7eu2rRpo71792ratGn6wx/+4LvvhBNO0MqVKwO2//bbb9W+ffuw+8vJyQk5NCU/P58ga0BeXh71bgD1bgb1nn5ZWUYXi04Ju8ZXiRhrJxxvzKDezaDezXBjjAXgPkaTZXfeeafOOOMMtW3bVjt27NDUqVM1b948zZ49Wzt37tSYMWP0+9//Xq1atdLatWt15513qlmzZho2bJhvHyNGjFCbNm00fvx4SdLnn3+ujRs36qijjtLGjRs1ZswYVVZW6tZbb/U95sYbb9Txxx+vP//5z/rDH/6gL774Qk8//bSefvrptNcBAADJRnwFAAAAEmc0WfbTTz/pT3/6kzZt2qT8/Hz16NFDs2fP1sCBA7Vr1y4tXrxY//jHP7Rt2za1atVKJ598sv75z3+qYcOGvn2sW7cu4OrE7t27NWrUKH333Xdq0KCBBg0apJdeekmNGjXybdO7d29Nnz5dd9xxh+6991517NhRjz32mM4///x0vnwAAFKC+AoAAAAkzmiy7Nlnnw17X7169TRnzpyo+5g3b17A3/3799eyZcuiPq6oqEhFRUVRtwsnJydHo0ePDrtqGFKDejeDejeDek8/t9S5k+Or5J73wUmoczOodzOodzOodwBO4rEs1u4FAAAAAAAAJInZFQEAAAAAAID9SJYBAAAAAAAA+5EsAwAAAAAAAPYjWQYAAAAAAADsR7IszXbu3Km9e/eaLgYAAK5CfAUAAECykCxLo2XLluncc8/Vli1bTBclY3z77beaOnWq6WJknP/973/avHmz6WJkPBY7Tp/KykrTRchoxFcziLFmEGPtgRibHsRXAKaQLEuTRYsWqU+fPpo5c6YmTpxoujgZ4euvv9ZRRx2ln3/+2XRRMsp3332ngoICjR8/Xps2bTJdnIyxZs0ajRkzRtdcc43uv/9+SZLH46Exn2IbNmzQjh07lJWVRYPeEOKrGcRYM4ixZhBj04/4CsC0WqYLkAm8Dfmrr75a+fn5mjNnjn788Ue1bt3adNFca9GiRerbt6+uvPJKXXvttaaLk1Hmz5+v//3vf3rqqae0b98+3XPPPWrZsqWkqquDHo9HHo/HcCndZfHixRo4cKAKCwu1a9cu/etf/9Ly5cs1ZcoU6jqFVqxYoYKCAh122GH64osvlJeXp8rKSmVlcR0qXYivZhBjzSHGph8xNv2IrwDsgCNOii1YsEB9+/bVTTfdpL/85S869dRT9cUXX+idd94xXTTXWrVqlfr27atLLrlEjzzyiPbt26cXX3xRf/7znzV+/Hj9/PPPXAlMoSOPPFLXXXedZs6cqcmTJ2vs2LHatm2bpKo5hWhYJtf69et19tlna+TIkZo+fbr++9//6sUXX9T8+fO1cOFC08VzrS1btujqq6/WGWecoZycHPXt21elpaVcAU8j4qsZxFiziLHpRYxNP+IrALugZ1kK7dmzR1deeaUuuugijRs3TpZl6bjjjtOFF16oxx9/XKeeeqrvaiCS5/nnn1etWrV05JFHaseOHTrzzDO1fft27d69W1u2bNFLL72kJ554QieffLLporpSo0aNNH36dI0fP17Tpk3T73//e+Xm5mrjxo3Kzc3VU089xZXBJLEsS7Nnz1aLFi30//7f/5Mk1alTR0cccYRKS0v166+/Gi6hey1dulRt2rTRBRdcoIMOOkjnn3+++vbtq48++kh5eXmqqKhQdna26WK6FvHVHGKsWcTY9CHGmkF8BWAXJMtSqE6dOnrzzTfVrFkzSfJd7TvppJM0ffp0/fDDD2rZsiXdipNszJgx2r59uyZNmqR7771Xhx9+uP75z3+qefPmysnJ0Yknnqibb75ZCxYs4ApskliWJY/Ho4qKCrVs2VIdO3bUokWLVFxcrHnz5umkk05STk6O3njjDT7rSeTxeHTcccdp586datGihSRp3759Ovjgg9WsWTPt3LnTcAndq1+/fsrOzla/fv0kSS+99JL++Mc/qm/fvvrwww+Vn5/vGxJVWVlJwz7JiK/mEGPTjxhrBjHWDOIrALsgoqbAvn37fL97G/LSgVVzzj33XB166KG6++67JYmGTRJs2LBBa9as0b59+1SnTh099thj6tmzpw499FD99a9/Vfv27VW/fn1lZ2frhRde0DfffKN3333XdLEd77fffvM1WCzLUnZ2tjwej9q1a6dvvvlGUlUjp3HjxiovL9eMGTOYkDjJDj/8cN14442Sqo4xtWpVXQOpXbt2QEP+tddeU2lpqZEyupF/Q16SunfvrldeeUVZWVk68cQTfUNG/vKXv2jOnDkGS+ouxFcziLFmEGPNI8amH/EVgF3QikyylStX6oYbbtAZZ5yhhx56SN99953vPu8VEEm65JJLtH79en322WeSWH66JhYvXqwTTjhBL7/8snbu3KnKykrVrl1bTzzxhG655RZ17NgxYPuNGzfqkEMOUYcOHcwU2CVWrlyp4cOH6z//+Y+vMb93715J0sEHH6x169bpuuuu04wZM7R48WK9+eabmjBhgh599FFVVFQYLr1z/fjjj5ozZ46ee+45/e9//1Pt2rV9xw9vzwOpaphanTp1JEn33HOPzj77bP3yyy/Gyu1033//vV544QXdf//9Wrhwof73v//57vMe1wsKCnwN+v79++vSSy/Vbbfdpk6dOpkqtqsQX80gxppBjDWDGJt+xFcAtmUhaRYvXmw1adLEGjFihHXmmWdahx9+uPXMM88EbFNZWWlZlmVt2rTJat++vXXttdeaKKprrFq1ymrRooV16623WmVlZTE95vbbb7f69etn/fLLLykunXvt27fPuvzyyy2Px2MNGTLEeuONN6yKigrf/W+99ZaVlZVltW3b1vryyy99t8+ZM8datmyZiSK7wjfffGN17drVOvLII60WLVpYBx10kLV69WrLsixf/e/du9fat2+fdfjhh1tvvfWW9fDDD1v169e3FixYYLLojvbNN99YzZo1s/r06WN17tzZaty4sXXBBRdYn3zyiW8b/8//119/bdWuXdtq2rSp9dVXX5kosusQX80gxppBjDWDGJt+xFcAdkayLEl++eUXq7Cw0Lrzzjt9t1144YXWjTfeaO3bt8/XiLesqkBrWZZ13333WYcddpi1Y8eOgPsRu/Hjx1tnnXWWZVlVjcsXXnjBuvXWW60pU6ZY33zzTcC2n3/+uXXbbbdZeXl51qJFi0wU11Wee+4568wzz7T69+9vHXfccdbrr7/uu+/XX3+17rnnnoD3wL+xg/itXr3aat26tXXnnXdaGzdutLZs2WKdccYZVv/+/a19+/ZV275v375Wp06drLp161rz5883UGJ3KC0ttfr372/ddNNN1m+//WZZlmU9//zz1mmnnWb179/fev/9933bVlZWWhUVFdbll19u1a1b11q6dKmpYrsK8dUcYqw5xNj0IsamH/EVgN0xDDNJysrK9Ouvv6pv376+23JycrRy5Uodf/zxuuaaazR37lxJ8s13MGTIEL399ttq0KABk+Am6KuvvlLbtm0lVU3s/Mwzz+idd97RAw88oMsuu8xX5xs3btQzzzyjkpISffDBB+rRo4fJYrtCrVq1lJubqzfffFO1a9fWww8/rA8//FBXXHGFVq5cqXvuuUdHHHGEb3vmDkpceXm5Hn30UZ166qkaPXq0WrdurebNm+v888/X1q1bqw0z27t3r3755Rd99913mj9/vo455hhDJXe+iooKbdy4UUcccYTq1asnSbrgggt04403Kjc3Vw8++KCWLl0qqWqIzsKFC7VixQp99NFHKigoMFl01yC+mkOMNYcYmz7EWDOIrwDsjsiaJL/99psk6YsvvtA333yj+++/Xy+88IJOOukkDRgwQD///LPuu+8+rV692veYHj16qF27dqaK7Ardu3fXzz//rMcee0z16tXTv/71Ly1YsECTJk1S+/bt9fjjj2v79u1q3bq17rrrLr377rs68sgjTRfbFQYMGKBNmzapXr16evPNN1WrVi2dddZZeuWVV5STk6Ps7GzmCkqSnJwctWrVSh06dPDNkSJJvXr10pYtW7R582bfxOeWZal27dqaMGGCVq5cqe7du5sqtitUVlaqadOm+umnnyQdmGD+tNNO02WXXaaNGzdq5syZvu179uypkpIS9erVy0h53Yj4ag4x1hxibPoQY80gvgKwu1qmC+AWXbp00dlnn63XXntNH3/8sRYsWKBXXnlFw4YNkyTNnTtX5513ntauXavOnTsbLq17tG/fXs8995y2bt2qHj16qFWrVpKkE044QZs2bdKll16qLVu2KD8/X+3btzdcWvdZvXq1vv32Wx122GFq2bKlPv30U3Xt2lVbtmxRZWUlV7qTaNSoUdVusyxLderUUb169Xw9alatWqVOnTpp4MCB6S6iKzVp0kSFhYX661//quHDh+vQQw9VRUWFsrOzNXToUH322Wd6/PHHdcMNN6h27drKyspSo0aNTBfbVYiv5hBjzSLGpg8xNv2IrwDsjiibBN6VWsaMGaNZs2bp8ccfV/PmzQNWaCkoKNBBBx3EVcAkGzlypE455RTNmjVLixcv1tatW3339e7dW+3bt2dVqBSorKxUq1atdNxxxyk3N1eXXXaZPv74Y82ePVtNmjTRjTfeqLffftt0MV3JewyxLEsVFRXyeDzKycmRJN16660aMmSIysrKTBbRNbzH9kcffVRdu3ZVUVGRfvzxR2VnZ/u26dOnj5o2bary8nKG+6UA8dUsYqwZxFhziLHpQXwF4AQky5IgKyvLd9Bv166datWqpezsbO3evdt3+xNPPKHdu3fTXTuJvA30yZMn67zzztPbb7+txx9/XKtWrVJ5ebkmT56svXv3qnnz5oZL6j7eq9lZWVlq27at3njjDU2fPl0nnXSS/v3vf6t9+/bq0qWL4VK6k7fB6G3Al5eXa9++fRo1apSefPJJvfjii8rLyzNcSnfIysqSZVnyeDx69tln1bhxY/Xt21cffPCBfvnlF0nSO++8o5ycHBryKUJ8NYcYaw4x1hxibHoQXwE4gcfiUmxKDBkyRB9//LFOPPFEeTweffLJJ5o9e7Z69uxpumiudeWVV2ru3LnasmWLunfvrjVr1mj27Nk66qijTBfNdbwNnFmzZunll1/WzTffrKOPPtrXfZ7hIemxevVqDRkyRMcdd5xeeeUVffLJJ8zlkUKbN2/W5Zdfrs8++0z5+flq06aNvv76a7333nscZ9KI+GoGMTZ9iLH2QIxNH+IrADsiWRaHVatWacmSJSouLg57lcO/AXPHHXdo/fr1atmypS6//HIddthh6SyuK8Rb5/Pnz9f333+vOnXq6Oijj2aC5wTFUu9S1QpSu3btqjaHhLehj/jEWu9SVR1/9dVX6t27txo1aqR3332XBmWC4ql3SZo2bZo2bNigrKwsDRo0KGBIIBJDfDWDGGsGMdYMYmz6EV8BOBnJshht3bpVHTt21I4dO/TSSy/p/PPPr7aN94pfcCOGRk1i4qlzrrImTzz1juRJtN4vvfRSXXvtterRo0e6iuoqHGfMI76awWffDGKsGcTY9OMYA8DpWA0zRk2aNNEpp5yiPXv2aMSIESovL9cFF1wQcGD3Bth///vf6tmzp29VLhryiYmnzqdNm6ZevXrpkEMOMVVc14in3l977TUdc8wx6tixo6niuka89e49xjz99NMcY2qgJscZEjXJQXw1gxhrBjHWDGJs+hFfATiehaj27dtnlZeXW6eeeqo1a9Ys6+GHH7ays7Otl19+2bIsy5o+fbq1e/duy7Isa9GiRZbH47Guv/56a+/evSaL7WjUuRnUuxmJ1Pt1111HvdcQn3fzeA/MoN7NoN7NIMamH591AG5Az7IYZGVlKTs7WyeeeKJ++OEH3XzzzSorK9MFF1ygiRMnqqKiQoWFhWrZsqV69OihkpISde7cWbVqUb2Jos7NoN7NoN7NoN7N4z0wg3o3g3o3g3pPP+ocgBswODwG3m7A2dnZmjFjhiRp9OjR6t69u7744gsNHjxYLVu2lFTVbXjIkCEqKCgwVl43oM7NoN7NoN7NoN7N4z0wg3o3g3o3g3pPP+ocgBuQLAujsrKy2m3HHXecb0WikSNHasuWLbr00kv10EMPafLkyZKYP6UmqHMzqHczqHczqHfzeA/MoN7NoN7NoN7TjzoH4Dqmxn/a1XfffWd9//33lmVZVkVFRcB9P/zwg3XCCSdYhYWFVsuWLa2vvvrKsizLuvnmm61mzZpZ27ZtS3dxXYE6N4N6N4N6N4N6N4/3wAzq3Qzq3QzqPf2ocwBuRbLMz4oVKyyPx2Pl5uZaK1eutCzrwEG/srLS2rx5s3XSSSdZPXv2tL788suAx/78889pL68bUOdmUO9mUO9mUO/m8R6YQb2bQb2bQb2nH3UOwM08lmVZpnu32cH//vc/jRgxQnXq1NGuXbu0cOFCffDBB+ratasqKyt9yxx/8cUXatKkiW/ZeiSOOjeDejeDejeDejeP98AM6t0M6t0M6j39qHMAbsecZfutXbtWrVu31pVXXqnnnntOxx57rPr3768VK1YoKytLe/fulSQde+yxHOyThDo3g3o3g3o3g3o3j/fADOrdDOrdDOo9/ahzAK5numubncyfP9/3+7p166xBgwZZzZs3t5YvX25ZVlW34srKSmv37t2miug61LkZ1LsZ1LsZ1Lt5vAdmUO9mUO9mUO/pR50DcDOGYUoBXYX9bdiwQZdffrnmz5/v61Y8duxYde7cWeeddx6rt9QAdW4G9W4G9W4G9W4e74EZ1LsZ1LsZ1Hv6UecAMoLpbJ0p27Zts/bs2RN1uw0bNliDBg2yWrdubZ1zzjmWx+Oxli5dmoYSug91bgb1bgb1bgb1bh7vgRnUuxnUuxnUe/pR5wAyTUYmy5YuXWo1bdrUuu+++6otcRzKd999ZzVt2tRq2rSptXDhwtQX0IWoczOodzOodzOod/N4D8yg3s2g3s2g3tOPOgeQiTIuWbZx40arV69eVrdu3aycnBxr3LhxVmVlZdjtKyoqrKuuusqqXbu2tWTJkjSW1D2oczOodzOodzOod/N4D8yg3s2g3s2g3tOPOgeQqWqZHgaaTpWVlXr//ffVoUMHjRkzRp9++qmuuOIKSdIdd9wRchz9ihUrtHHjRn322Wfq1q1buovseNS5GdS7GdS7GdS7ebwHZlDvZlDvZlDv6UedA8hoprN16bZixQpr1qxZvr+feuopKysryxo3blxAt2L/KyalpaVpLaPbUOdmUO9mUO9mUO/m8R6YQb2bQb2bQb2nH3UOIFNlXLLMn/cA//TTT/sO+pWVldaePXusKVOmMMY+BahzM6h3M6h3M6h383gPzKDezaDezaDe0486B5BJMmoYppdlWfJ4PL4ljy+99FJJ0hVXXCHLsvTDDz/otdde06JFi0wW01WoczOodzOodzOod/N4D8yg3s2g3s2g3tOPOgeQiTIuWVZRUaHs7Gzt2LFDktSwYUNJVQf9yspKXXnllcrPz9fcuXPVrl07k0V1DercDOrdDOrdDOrdPN4DM6h3M6h3M6j39KPOAWSqLNMFSCfvwX7t2rXq0aOHFixY4Ltvz549WrRokfLz8/XJJ5+oV69eBkvqHtS5GdS7GdS7GdS7ebwHZlDvZlDvZlDv6UedA8ho6R31ad4PP/xgNW/e3LrooosCJqKcPXu21aJFC2v+/PkGS+dO1LkZ1LsZ1LsZ1Lt5vAdmUO9mUO9mUO/pR50DyFQey7Is0wm7dKmsrNQjjzyi9evXa8KECQHLHf/444/Kzs5Wy5YtDZbQfahzM6h3M6h3M6h383gPzKDezaDezaDe0486B5DJMipZJkm7du1SvXr1TBcjo1DnZlDvZlDvZlDv5vEemEG9m0G9m0G9px91DiBTZVyyDAAAAAAAAAgnoyb4BwAAAAAAACIhWQYAAAAAAADsR7IMAAAAAAAA2I9kGQAAAAAAALAfyTIAAAAAAABgP5JlAAAAAAAAwH4kywAAAAAAAID9SJYBAAAAAAAA+5EsAwAAAAAAAPYjWQZkqLVr18rj8ejrr79Oyf49Ho9KSkpqvJ+7775bl112WUzbnnnmmXr00Udr/JwAANQEMRYAAGcjWQYYcMEFF6i4uNhoGdq2batNmzape/fukqR58+bJ4/Fo27ZtRsvl76efftKECRN05513+m7buXOnzjnnHLVq1UrnnHOOysrKfPfdc889GjdunEpLS00UFwBgA8TY2BBjAQAIj2QZkKGys7N10EEHqVatWqaLEtazzz6rwsJCdejQwXfbY489pgYNGuitt95S/fr19dhjj/nu69Gjhzp06KApU6akv7AAAOxHjAUAwNlIlgE29P777+vYY49VTk6OWrVqpdtvv1379u3z3X/SSSfpuuuu06233qomTZrooIMO0pgxYwL2sWLFCvXt21d169ZVQUGB5s6dGzBsw3+IyNq1a3XyySdLkho3biyPx6MLLrhAktShQ4eAxrIkHXXUUQHPt2rVKvXr18/3XG+//Xa117Rx40adffbZaty4sZo2baqhQ4dq7dq1Eeth6tSpGjJkSMBt27Zt02GHHaYjjjhCXbt21fbt2wPuHzJkiF599dWI+wUAZC5ibBViLAAA4ZEsA2xm48aNGjRokHr37q1FixZp0qRJevbZZ3X//fcHbPfiiy8qNzdXn3/+uR566CHde++9vgZ0ZWWliouLVb9+fX3++ed6+umnddddd4V9zrZt22ratGmSpJUrV2rTpk2aMGFCTOWtrKzU8OHDlZ2drc8++0yTJ0/WbbfdFrDNb7/9ppNPPlkNGjTQBx98oI8++kgNGjTQ6aefrj179oTc76+//qolS5bomGOOCbj9mmuu0VNPPaXatWvr+eef1/XXXx9w/7HHHqsvvvhC5eXlMZUfAJA5iLFViLEAAERm377hQIZ68skn1bZtWz3++OPyeDzq2rWrfvzxR91222265557lJVVlePu0aOHRo8eLUk69NBD9fjjj+udd97RwIED9dZbb2nNmjWaN2+eDjroIEnSuHHjNHDgwJDPmZ2drSZNmkiSWrRooUaNGsVc3rlz52r58uVau3atDj74YEnSn//8Z51xxhm+baZOnaqsrCw988wz8ng8kqTnn39ejRo10rx583TqqadW2+8PP/wgy7LUunXrgNs7dOigVatWacuWLWrZsqVvf15t2rRReXm5Nm/erPbt28f8OgAA7keMrUKMBQAgMpJlgM0sX75chYWFAQ3UE044QTt37tSGDRvUrl07SVUNeX+tWrXSli1bJFVduW7btq2vES9VXQ1OVXnbtWvna8RLUmFhYcA2X375pVavXq2GDRsG3L57926tWbMm5H537dolSapbt261+7KysgJem7969epJqrrSDgCAP2JsFWIsAACRkSwDbMayrGpXci3LkqSA22vXrh2wjcfjUWVlZdh9JCorK8v3/F579+6tVrbgsvirrKxUr169Qk4K3Lx585DP26xZM0lVQ0XCbRPK1q1bI+4XAJC5iLFViLEAAETGnGWAzRQUFOiTTz4JaCB/8sknatiwodq0aRPTPrp27ap169bpp59+8t02f/78iI+pU6eOJKmioiLg9ubNm2vTpk2+v0tLS/X9998HlHfdunX68ccffbd9+umnAfs4+uijtWrVKrVo0UKdO3cO+MnPzw9Znk6dOikvL0/Lli2L8moDLVmyRAcffLDvRAAAAC9ibBViLAAAkZEsAwzZvn27vv7664CfdevW6aqrrtL69et17bXXasWKFXr99dc1evRo3XTTTb65VKIZOHCgOnXqpJEjR+qbb77Rxx9/7Jt8ONzV8Pbt28vj8WjGjBn6+eeftXPnTknSKaecopdeekkffvihlixZopEjRyo7O9v3uAEDBqhLly4aMWKEFi1apA8//LDaRMfnn3++mjVrpqFDh+rDDz/U999/r/fff1/XX3+9NmzYELI8WVlZGjBggD766KOYXrPXhx9+GHJ+FgBA5iDGEmMBAKgJkmWAIfPmzVPPnj0Dfu655x61adNGs2bN0hdffKEjjzxSV1xxhS6++GKNGjUq5n1nZ2erpKREO3fuVO/evXXJJZf4Hh9qfhKpatLesWPH6vbbb1fLli11zTXXSJLuuOMO9evXT0VFRRo0aJCKi4vVqVMn3+OysrI0ffp0lZeX69hjj9Ull1yicePGBey7fv36+uCDD9SuXTsNHz5chx9+uC666CLt2rVLeXl5YV/HZZddpqlTp/qGvkSze/duTZ8+XZdeemlM2wMA3IkYS4wFAKAmPFaoyRAAuM7HH3+svn37avXq1QENcTuzLEt9+vTRDTfcoHPPPTfq9k888YRef/11vfXWW2koHQAAVYixAAC4CxP8Ay41ffp0NWjQQIceeqhWr16t66+/XieccIJjGvFS1XCWp59+Wt98801M29euXVsTJ05McakAAJmOGAsAgLvRswxwqX/84x+67777tH79ejVr1kwDBgzQI488oqZNm5ouGgAAjkaMBQDA3UiWAQAAAAAAAPsxwT8AAAAAAACwH8kyAAAAAAAAYD+SZQAAAAAAAMB+JMsAAAAAAACA/UiWAQAAAAAAAPuRLAMAAAAAAAD2I1kGAAAAAAAA7EeyDAAAAAAAANiPZBkAAAAAAACw3/8HlrI+VNgqa2gAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1200x800 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot a few mosaics to explore the data\n",
+    "\n",
+    "# Select dates to plot\n",
+    "date_str = [\"2023-06-04\", \"2024-06-08\", \"2025-06-13\", \"2026-06-03\"]\n",
+    "target_date = [datetime.strptime(x, \"%Y-%m-%d\").date() for x in date_str]\n",
+    "plot_indices = []\n",
+    "for d in target_date:\n",
+    "    plot_indices.append(dates.index(d))\n",
+    "\n",
+    "\n",
+    "# DSWx class colors\n",
+    "col_notwater = \"#ffffff\"    # 0 (not water)\n",
+    "col_openwater = \"#0000ff\"   # 1 (open water)\n",
+    "col_psw = \"#b4d5f4\"         # 2 (partial surface water)\n",
+    "col_snowice = \"#00ffff\"     # 252 (snow/ice)\n",
+    "col_clouds = \"#afafaf\"      # 253 (clouds)\n",
+    "col_nodata = \"#242424\"      # 255 (no data)\n",
+    "cmap = ListedColormap([\n",
+    "    col_notwater,   \n",
+    "    col_openwater,   \n",
+    "    col_psw,   \n",
+    "    col_snowice,   \n",
+    "    col_clouds,   \n",
+    "    col_nodata    \n",
+    "])\n",
+    "\n",
+    "# Plot DSWx arrays\n",
+    "n = len(plot_indices)\n",
+    "ncols = 2\n",
+    "nrows = int(np.ceil(n / ncols))\n",
+    "fig, axes = plt.subplots(\n",
+    "    nrows,\n",
+    "    ncols,\n",
+    "    figsize=(12, 4 * nrows),\n",
+    "    squeeze=False\n",
+    ")\n",
+    "axes = axes.ravel()\n",
+    "\n",
+    "# Plot coordinates in lat/lon\n",
+    "to_latlon = Transformer.from_crs(\n",
+    "    f\"EPSG:{ANALYSIS_EPSG}\",\n",
+    "    \"EPSG:4326\",\n",
+    "    always_xy=True\n",
+    ")\n",
+    "\n",
+    "for ax, idx in zip(axes, plot_indices):\n",
+    "\n",
+    "    if idx >= len(dates):\n",
+    "        ax.set_title(f\"Index {idx}\\nout of range\")\n",
+    "        ax.axis(\"off\")\n",
+    "        continue\n",
+    "\n",
+    "    arr = values[idx]\n",
+    "    \n",
+    "    plot_arr = np.full(arr.shape, 5, dtype=np.uint8) \n",
+    "    plot_arr[arr == 0] = 0\n",
+    "    plot_arr[arr == 1] = 1\n",
+    "    plot_arr[arr == 2] = 2\n",
+    "    plot_arr[arr == 252] = 3\n",
+    "    plot_arr[arr == 253] = 4\n",
+    "    plot_arr[arr == 255] = 5\n",
+    "\n",
+    "    im = ax.imshow(\n",
+    "        plot_arr,\n",
+    "        cmap=cmap,\n",
+    "        vmin=0,\n",
+    "        vmax=6,\n",
+    "        interpolation=\"none\",\n",
+    "        extent=[\n",
+    "            x_coords.min(),\n",
+    "            x_coords.max(),\n",
+    "            y_coords.min(),\n",
+    "            y_coords.max()\n",
+    "        ],\n",
+    "        origin=\"upper\"\n",
+    "    )\n",
+    "\n",
+    "    ax.set_title(f\"{dates[idx]}\")\n",
+    "    \n",
+    "    # Convert x tick positions to lat/lon\n",
+    "    xticks = np.linspace(x_coords.min(), x_coords.max(), 5)\n",
+    "    yticks = np.linspace(y_coords.min(), y_coords.max(), 5)\n",
+    "    ax.set_xticks(xticks)\n",
+    "    ax.set_yticks(yticks)\n",
+    "    lat_labels = [\n",
+    "        f\"{to_latlon.transform(x_coords.mean(), y)[1]:.2f}\"\n",
+    "        for y in yticks\n",
+    "    ]\n",
+    "    lon_labels = [\n",
+    "        f\"{to_latlon.transform(x, y_coords.mean())[0]:.2f}\"\n",
+    "        for x in xticks\n",
+    "    ]\n",
+    "    \n",
+    "    ax.set_xticklabels(lon_labels, rotation=45)\n",
+    "    ax.set_yticklabels(lat_labels)\n",
+    "    ax.set_xlabel(\"Longitude (°)\")\n",
+    "    ax.set_ylabel(\"Latitude (°)\")\n",
+    "\n",
+    "legend_elements = [\n",
+    "    Patch(facecolor=col_notwater, label=\"0: Not Water\"),\n",
+    "    Patch(facecolor=col_openwater, label=\"1: Open Water\"),\n",
+    "    Patch(facecolor=col_psw, label=\"2: Partial Surface Water\"),\n",
+    "    Patch(facecolor=col_snowice, label=\"252: Snow/Ice\"),\n",
+    "    Patch(facecolor=col_clouds, label=\"253: Clouds\"),\n",
+    "    Patch(facecolor=col_nodata, label=\"255: No Data\"),\n",
+    "]\n",
+    "\n",
+    "fig.legend(\n",
+    "    handles=legend_elements,\n",
+    "    loc=\"upper right\",\n",
+    "    bbox_to_anchor=(1.02, 0.9)\n",
+    ")\n",
+    "\n",
+    "plt.tight_layout(rect=[0, 0, 0.8, 1])\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8929c5bd-9257-4bb9-b410-a0734e7fc365",
+   "metadata": {},
+   "source": [
+    "## Step 4: Filter Mosaics Before Analysis \n",
+    "\n",
+    "Before moving to the time series analysis, we will remove mosaics that may adversely affect the analysis. First, mosaics containing excessive nodata pixels are excluded because they do not provide sufficient valid observations over the area of interest. We then calculate open water extent and cloud coverage for the remaining mosaics, allowing us to identify and remove observations with excessive cloud cover before constructing the final time series."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "86d12753-806d-4268-bb58-a96b92e91493",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Filtering out mosaics containing more than 1000 nodata pixels (0.02% of the image).\n",
+      "Number of original dates before filtering: 382\n",
+      "Number of dates after filtering: 245\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Remove mosaics containing excessive nodata pixels\n",
+    "\n",
+    "# Maximum allowable number of nodata pixels in a mosaic.\n",
+    "# Mosaics exceeding this threshold are excluded from subsequent analysis.\n",
+    "MAX_NODATA_PIXELS = 1000\n",
+    "\n",
+    "# Total number of pixels in each mosaic (all mosaics share the same dimensions).\n",
+    "num_px = values[0].size \n",
+    "\n",
+    "print(\n",
+    "    f\"Filtering out mosaics containing more than {MAX_NODATA_PIXELS} nodata pixels \"\n",
+    "    f\"({100 * MAX_NODATA_PIXELS / num_px:.2f}% of the image).\"\n",
+    ")\n",
+    "\n",
+    "# Count the number of nodata pixels in each mosaic.\n",
+    "nodata_values = {}\n",
+    "for d,v in zip(dates, values):\n",
+    "    count = np.sum(v==NODATA)\n",
+    "    nodata_values[d] = count\n",
+    "\n",
+    "# Retain only mosaics with acceptable nodata coverage.\n",
+    "filtered = [\n",
+    "    (d, v)\n",
+    "    for d, v in zip(dates, values)\n",
+    "    if nodata_values[d] <= MAX_NODATA_PIXELS\n",
+    "]\n",
+    "dates_filtered = [d for d, v in filtered]\n",
+    "values_filtered = [v for d, v in filtered]\n",
+    "\n",
+    "print(f\"Number of original dates before filtering: {len(dates)}\")\n",
+    "print(f\"Number of dates after filtering: {len(dates_filtered)}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "972c2db9-8528-420c-85ae-23f959cbe3c9",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Count open water and cloud pixels for each mosaicked raster\n",
+    "# after removing mosaics with excessive nodata.\n",
+    "\n",
+    "nwater = []       # number of open water pixels\n",
+    "ncloud = []       # number of cloud pixels\n",
+    "ncloud_pct = []   # percent cloud cover\n",
+    "water_km2 = []    # open water area (km2)\n",
+    "\n",
+    "for v in values_filtered:\n",
+    "    nw = np.sum(v == 1)    # count pixels classified as open water (class 1)\n",
+    "    nc = np.sum(v == 253)  # count pixels classified as clouds (class 253)\n",
+    "    nwater.append(nw)\n",
+    "    ncloud.append(nc)\n",
+    "    ncloud_pct.append(100*nc/num_px)           # calculate cloud cover percentage\n",
+    "    water_km2.append(nw*PIXEL_SIZE_M**2/1e6)   # calculate water area in square km\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "58281626-b047-462b-a72d-19cce39882f5",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot open water area and cloud percentage through time\n",
+    "\n",
+    "fig, ax1 = plt.subplots(figsize=(10, 5))\n",
+    "\n",
+    "# Water area\n",
+    "ax1.plot(\n",
+    "    dates_filtered,\n",
+    "    water_km2,\n",
+    "    marker=\"o\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1.5,\n",
+    "    label=\"Open Water Area\",\n",
+    "    color=\"blue\"\n",
+    ")\n",
+    "ax1.set_xlabel(\"Date\")\n",
+    "ax1.set_ylabel(\"Open Water Area (km²)\")\n",
+    "ax1.grid(True)\n",
+    "\n",
+    "# Clouds\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(\n",
+    "    dates_filtered,\n",
+    "    ncloud_pct,\n",
+    "    marker=\"s\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1,\n",
+    "    linestyle=\"--\",\n",
+    "    label=\"Cloud Cover (%)\",\n",
+    "    color=\"gray\"\n",
+    ")\n",
+    "ax2.set_ylim(0, 100)\n",
+    "ax2.set_ylabel(\"Cloud Cover (%)\")\n",
+    "\n",
+    "# Combined legend\n",
+    "lines1, labels1 = ax1.get_legend_handles_labels()\n",
+    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
+    "ax1.legend(lines1 + lines2, labels1 + labels2, loc=\"upper center\", bbox_to_anchor=(0.5, -0.15))\n",
+    "\n",
+    "plt.title(\"Open Water Area and Cloud Cover Through Time\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d445940d-e05f-45f7-a51f-04ab7aaa1635",
+   "metadata": {},
+   "source": [
+    "The plot above provides an initial view of changes in Lake Mead's surface water extent through time. While seasonal patterns are already apparent, several sharp decreases in open water area coincide with periods of high cloud cover. These decreases are likely caused by clouds obscuring the water surface rather than true reductions in lake extent. In the next step, we filter out mosaics with excessive cloud cover to produce a more reliable time series for trend analysis."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "ed5415a6-85aa-4907-aacf-c35fbb476fcf",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of dates before cloud filtering: 245\n",
+      "Number of dates after filtering with <= 10% cloud cover: 162\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Filter out mosaics with excessive cloud coverage\n",
+    "\n",
+    "# Maximum allowable cloud cover percentage in a mosaic.\n",
+    "# Mosaics exceeding this threshold are excluded from the time series analysis.\n",
+    "MAX_CLOUD_PERCENT = 10\n",
+    "\n",
+    "filtered = [\n",
+    "    (d, v)\n",
+    "    for d, v, cp in zip(dates_filtered, values_filtered, ncloud_pct)\n",
+    "    if cp <= MAX_CLOUD_PERCENT\n",
+    "]\n",
+    "\n",
+    "dates_cloud_filtered = [d for d, v in filtered]\n",
+    "values_cloud_filtered = [v for d, v in filtered]\n",
+    "\n",
+    "print(f\"Number of dates before cloud filtering: {len(dates_filtered)}\")\n",
+    "print(f\"Number of dates after filtering with <= {MAX_CLOUD_PERCENT}% cloud cover: {len(dates_cloud_filtered)}\")\n",
+    "\n",
+    "\n",
+    "# Get updated count of cloud and water pixels per mosaicked raster after filtering by cloud percentage\n",
+    "nwater_f = []       # number of open water pixels\n",
+    "ncloud_f = []       # number of cloud pixels\n",
+    "ncloud_pct_f = []   # percent cloud cover\n",
+    "water_km2_f = []    # open water area (km2)\n",
+    "\n",
+    "for v in values_cloud_filtered:\n",
+    "    nw = np.sum(v == 1)    # count pixels classified as open water (class 1)\n",
+    "    nc = np.sum(v == 253)  # count pixels classified as clouds (class 253)\n",
+    "    nwater_f.append(nw)\n",
+    "    ncloud_f.append(nc)\n",
+    "    ncloud_pct_f.append(100*nc/num_px)           # calculate cloud cover percentage\n",
+    "    water_km2_f.append(nw*PIXEL_SIZE_M**2/1e6)   # calculate water area in square km\n",
+    "    "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "96fcbeec-f3bb-472e-8096-983640a2544b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot open water area and cloud percentage through time after filtering for cloud cover\n",
+    "\n",
+    "fig, ax1 = plt.subplots(figsize=(10, 5))\n",
+    "\n",
+    "# Water area\n",
+    "ax1.plot(\n",
+    "    dates_cloud_filtered,\n",
+    "    water_km2_f,\n",
+    "    marker=\"o\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1.5,\n",
+    "    label=\"Open Water Area\",\n",
+    "    color=\"blue\"\n",
+    ")\n",
+    "ax1.set_xlabel(\"Date\")\n",
+    "ax1.set_ylabel(\"Open Water Area (km²)\")\n",
+    "ax1.grid(True)\n",
+    "\n",
+    "# Clouds\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(\n",
+    "    dates_cloud_filtered,\n",
+    "    ncloud_pct_f,\n",
+    "    marker=\"s\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1,\n",
+    "    linestyle=\"--\",\n",
+    "    label=\"Cloud Cover (%)\",\n",
+    "    color=\"gray\"\n",
+    ")\n",
+    "ax2.set_ylim(0, 100)\n",
+    "ax2.set_ylabel(\"Cloud Cover (%)\")\n",
+    "\n",
+    "# Combined legend\n",
+    "lines1, labels1 = ax1.get_legend_handles_labels()\n",
+    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
+    "ax1.legend(lines1 + lines2, labels1 + labels2, loc=\"upper center\", bbox_to_anchor=(0.5, -0.15))\n",
+    "\n",
+    "plt.title(\"Open Water Area and Cloud Cover Through Time\")\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a7c6a04-cdfc-4af2-a355-1205f267fcf5",
+   "metadata": {},
+   "source": [
+    "## Step 5: Analyze Surface Water Extent\n",
+    "\n",
+    "With the quality-filtered mosaics prepared, we can now quantify changes in surface water extent through time. The filtered time series contains both short-term variability and longer-term changes in surface water extent. To better visualize these patterns, we first apply **LOWESS (Locally Weighted Scatterplot Smoothing)**, a non-parametric smoothing technique that estimates the underlying trend in the time series while reducing the influence of short-term fluctuations. We then fit a **linear regression model** to estimate the overall long-term rate of change in surface water extent over the observation period.\n",
+    "\n",
+    "> **Note:** The analyses in the remainder of this notebook are intended for time series spanning at least one full year. If you reduced the temporal range to less than one year (for example, to reduce memory usage), the seasonal and long-term trend analyses presented below may not produce meaningful results."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "b96f1d80-4192-45e5-8f12-6732200b801d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Fit a LOWESS curve to the filtered time series\n",
+    "\n",
+    "# Convert dates to numeric days since first observation.\n",
+    "# LOWESS operates on numeric x-values rather than datetime objects.\n",
+    "x = np.array([(d - dates_cloud_filtered[0]).days for d in dates_cloud_filtered])\n",
+    "y = np.array(water_km2_f)\n",
+    "\n",
+    "# Apply LOWESS smoothing to the time series.\n",
+    "# frac = Fraction of neighboring observations used for each local regression.\n",
+    "# Larger values produce a smoother curve, while smaller values follow short-term variations more closely.\n",
+    "water_lowess = lowess(\n",
+    "    y,\n",
+    "    x,\n",
+    "    frac=0.1,\n",
+    "    return_sorted=False\n",
+    ")\n",
+    "\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "\n",
+    "\n",
+    "# Water area observations\n",
+    "plt.plot(\n",
+    "    dates_cloud_filtered,\n",
+    "    y,\n",
+    "    marker=\"o\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1,\n",
+    "    label=\"Open Water Area\",\n",
+    "    color=\"lightgray\"\n",
+    ")\n",
+    "\n",
+    "# Overlay the LOWESS-smoothed trend\n",
+    "plt.plot(\n",
+    "    dates_cloud_filtered,\n",
+    "    water_lowess,\n",
+    "    linewidth=2.5,\n",
+    "    label=\"LOWESS Smooth\",\n",
+    "    color=\"blue\"\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Open Water Area (km²)\")\n",
+    "plt.title(\"Open Water Area Through Time\")\n",
+    "plt.grid(True)\n",
+    "plt.legend(loc=\"upper center\", bbox_to_anchor=(0.5, -0.15), ncol=2)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2f315b36-5f99-4d30-8364-1c32784beb6f",
+   "metadata": {},
+   "source": [
+    "Even after filtering observations with excessive nodata and cloud cover, a few observations remain that fall well below the LOWESS-smoothed curve. These observations may arise from anomalous measurements or classification artifacts and can obscure the underlying temporal signal.\n",
+    "\n",
+    "To identify these observations, we calculate the residuals between the observations and the LOWESS curve and use the **median absolute deviation (MAD)** to detect unusually large negative deviations. Because MAD is based on the median rather than the mean, the detection threshold is not unduly influenced by the very outliers we are trying to identify."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "c14793c6-8c37-4f3a-baf1-e65ee75e930d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Removed 24 low outliers\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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QnD59GpMnT/b1cAghpF6hoJsQQohLd911Fz744AM899xz6NatGyZPnozExESkpaXh448/xp9//okPPvgAXbt2LXffjRs3QiaToW/fvjh16hRef/11dOjQwbEmNjk5GbNnz8aMGTNw6dIlDBgwAGFhYcjOzsZff/2FwMBAR+snT+AD6U2bNmH48OGi29q2bYuIiAhs2rQJ8fHxaNasmeO2QYMGYdWqVWjZsiXat2+Pv//+GwsWLCg389+0aVMEBARgzZo1aNWqFYKCghAXF4e4uDh8+umnuPfee9G/f3+MHz8e8fHxyM/Px5kzZ3D06FF8//331f5+8vLysHnzZvTv3x/333+/y2Pef/99fPXVV3j33XcrrIA+e/Zs7NixA127dsXUqVPRokULGI1GXLlyBT/99BM++eQTNGrUCPfddx8WLVqEUaNG4X//+x/y8vKwcOHCchcl/MGbb77pWKv+xhtvIDw8HGvWrMG2bdswf/58x0WKjh07okWLFnjxxRdhtVoRFhaGTZs2lWu5Fh4ejhdeeAHvvvsuwsLCMGzYMFy7dg2zZs1CbGwsJJK6v1ovKCgIixcvxrhx45Cfn4/hw4dDq9UiNzcX//zzD3Jzc7Fs2TJfD5MQQuqkuv9XghBCiNdMmTIFf/zxBxo1aoRp06ahd+/eeOGFFxAbG4v9+/djypQpLu+3ceNGnD17Fg888ADeeOMNDB48GL/++qtjHSnAzaSvX78e58+fx7hx49C/f39Mnz4dV69eRffu3T36fbRu3RoxMTFgWVaUWg5wM7h33303WJYt12/5ww8/xOjRo/Huu+9i8ODB2LJlCzZu3IimTZuKjlOr1fjiiy+Ql5eHfv36oWPHjvjss88AcAH/X3/9hdDQUDz33HPo06cPnnrqKezcuRN9+vSp0fezevVqmEwmTJo0ye0x//vf/5Cbm4utW7dW+FixsbE4cuQI+vXrhwULFmDAgAGOWXK+zzkA9O7dG1988QVOnDiBwYMHY8aMGRg+fDheeeWVGn0P3tSiRQscOHAALVq0wDPPPIOhQ4fi5MmTWLlyJV566SXHcVKpFFu3bkXLli3x5JNPYuzYsVAqlViyZEm5x5wzZw7efvttbNu2DUOGDMFHH32EZcuWQavVVmmpQV0wevRo7N69G8XFxZg0aRL69OmDZ599FkePHsU999zj6+ERQkidxbCsU4NGQggh5CbMnDkTs2bNQm5urmONKCH11eXLl9GyZUu8+eabeO2113w9HEIIIX6K0ssJIYQQQirxzz//4Ntvv0XXrl0REhKCc+fOYf78+QgJCcHEiRN9PTxCCCF+jIJuQgghhJBKBAYG4siRI1ixYgUKCwuh0WjQs2dPzJkzh6p6E0IIqRCllxNCCCGEEEIIIV5ChdQIIYQQQgghhBAvoaCbEEIIIYQQQgjxEgq6CSGEEEIIIYQQL6FCagDsdjsyMjIQHBwMhmF8PRxCCCGEEEIIIX6OZVno9XrExcVBInE/n01BN4CMjAwkJCT4ehiEEEIIIYQQQuqY9PR0NGrUyO3tFHQDCA4OBsD9sEJCQrzyHBaLBb/++iv69esHuVzulecgvkWvccNBr3XDQK9zw0Cvc/1Hr3HDQa91/edvr3FRURESEhIc8aQ7FHQDjpTykJAQrwbdarUaISEhfvELQjyPXuOGg17rhoFe54aBXuf6j17jhoNe6/rPX1/jypYoUyE1QgghhBBCCCHESyjoJoQQQgghhBBCvISCbkIIIYQQQgghxEso6CaEEEIIIYQQQryEgm5CCCGEEEIIIcRLKOgmhBBCCCGEEEK8hIJuQgghhBBCCCHESyjoJoQQQgghhBBCvISCbkIIIYQQQgghxEso6CaEEEIIIYQQQrxE5usBEEJIQ6XT6ZCTkwOz2QyFQgGtVguNRuPrYRFCCCGEEA+ioJsQQnxAp9MhPT3dsW0ymRzbFHgTQgghhNQflF5OCCE+kJOT43J/bm5uLY+EEEIIIYR4EwXdhBDiA2az2eV+k8lUyyMhhBBCCCHeREE3IYT4gEKhcLlfKpWCZdlaHg0hhBBCCPEWCroJIcQHtFqty/1WqxUXL15EaWlpLY+IEEIIIYR4AwXdhBDiA/xMt0wmA8MwUKlUSExMRNOmTQEAly5dQkZGBmw2my+HSQghhBBCbhJVLyeEkFrGsiwyMzOhVCqRkpIChmFEtzdt2hR5eXnIyclBUVERYmJioNFoyh1HCCGEEEL8H810E0JILdPpdCgtLUVsbKzLQJphGERGRqJZs2ZQq9W4du0arl69SkXWCCGEEELqIAq6CSGkFtlsNmRlZSEkJARBQUEVHiuXy5GYmIjExESYTCZcuHABOTk5sNvttTRaQgghhBBysyi9nBBCalFubi5sNhtiYmKqfB8+QM/JyUFOTg50Oh3i4uIQGBjoxZESQgghhBBPoKCbEEJqiclkQl5eHqKioty2DHNHIpEgJiYGoaGhuH79Oi5fvozQ0FDExMRAJvPsR7lOp0NOTg7MZjMUCgW0Wi00Go1Hn4MQQgghpKGgoJsQQmpJVlYWZDIZIiMja/wYKpUKTZo0QUFBAbKysqDX6x3BuCcKrel0OqSnpzu2TSaTY5sCb0IIIYSQ6qM13YQQUgv0er0jQJZIbu6jl2EYhIeHo3nz5ggKCnLMfBuNxpseZ05Ojsv9ubm5N/3YhBBCCCENEc10E0KIl9ntdmRmZiIwMBAhISEee1yZTIaEhASEhYUhIyMDFy9eRGRkJKKiomoc2JvNZpf7qXI6IbT0ghBCSM34dKZ72bJlaN++PUJCQhASEoIuXbrg559/BgBYLBa8/PLLaNeuHQIDAxEXF4exY8ciIyND9BgmkwlTpkxBZGQkAgMDMWTIEFy7ds0X3w4hhLiUl5cHs9nstkXYzQoKCkJKSgoiIyNx48YNpKamQq/X1+ix3K01VyqVNzNEQuo8fumFyWQCy7KOpRc6nc7XQyOEEOLnfBp0N2rUCHPnzsWRI0dw5MgR9O7dG/fffz9OnTqF0tJSHD16FK+//jqOHj2KjRs34vz58xgyZIjoMZ577jls2rQJa9euxf79+1FcXIxBgwbBZrP56LsihBCBxWJBbm4uIiIioFKpvPY8EokE0dHRSElJgUKhwNWrV5Geng6LxVKtx9FqtdXaT0hDQUsvCCGE1JRP08sHDx4s2p4zZw6WLVuGQ4cOYeLEidixY4fo9sWLF6NTp05IS0tDYmIidDodVqxYga+//hp9+vQBAKxevRoJCQnYuXMn+vfvX2vfCyGEuJKVlQWGYWotaFUqlUhOToZOp0NmZiZSU1MRHR2N8PDwKs2yazQa2Gw2R1aRVCpFfHy8R9PiCamLaOkFIYSQmvKbQmo2mw1r165FSUkJunTp4vIYnU4HhmEQGhoKAPj7779hsVjQr18/xzFxcXFo27YtDhw4UBvDJoQQt0pKSqDT6RAdHQ2pVFprz8t/TjZr1gwajQaZmZm4dOkSDAZDle6vVqsBAHK5HHK5nAJuQkBLLwghhNSczwupnThxAl26dIHRaERQUBA2bdqE1q1blzvOaDTilVdewahRoxwngFlZWVAoFAgLCxMdGx0djaysLLfPaTKZRFemi4qKAHBpoNVNxawq/nG99fjE9+g1bjiq8lqzLIuMjAyoVCoEBQX57PdCq9UiKCgI2dnZuHjxIsLCwhAZGVlhoTV+Ri8oKAgFBQUwGo21etHAX9B7umGo6uscERFRrq4MAISHh9PviJ+j93LDQa91/edvr3FVx8GwLMt6eSwVMpvNSEtLQ2FhITZs2IDly5dj7969osDbYrHgoYceQlpaGvbs2eMIur/55hs89thj5VK7+vbti6ZNm+KTTz5x+ZwzZ87ErFmzyu3/5ptvHDM8hBByM4KDg6HVanHt2jW/ST8NDQ1FWFgY7HY7cnNzUVpa6vK4gIAAxMXF4fr164iPj0dWVhZKSkpqebSE+J/AwEBER0eDYRjYbDbk5ubSe4MQQhqw0tJSjBo1CjqdrsLMQJ8H3WX16dMHTZs2xaeffgqAC7hHjBiBS5cuYdeuXYiIiHAcu2vXLtxzzz3Iz88XzXZ36NABQ4cOdRlYA65nuhMSEnDjxg2vpVFaLBbs2LEDffv2hVwu98pzEN+i17jhqOy1ttlsuHz5MgIDAxEbG1vJYwE5OYDJxH3N/7NaGcfXZrP4NuEYwGJhKrmdvz/3eCaTHcXFJhiNNgAyMIwSJpMdJpMF7duXYtq0fISGBqKgoAApKSlIS0tDQEAAYmJivPTT9F/0nm4YqvM622w2XLhwARKJBHK5HMnJybUzSHJT6L3ccNBrXf/522tcVFSEyMjISoNun6eXl8W34QCEgDs1NRW7d+8WBdwAcPvtt0Mul2PHjh0YMWIEACAzMxMnT57E/Pnz3T6HUql0uQaLX7/oTbXxHMS36DVuONy91rm5uWBZFrGxsZDL5TAagUuXgIsXgQsXuH/811euALXbbEGC8h/9UgBy/P23GnK5HVOmcFWalUolgoKCUFxc3KB/p+k93TBU5XXm0whDQkKg0+kgk8m80gaQeAe9lxsOeq3rP395jas6Bp8G3a+99hruvfdeJCQkQK/XY+3atdizZw+2b98Oq9WK4cOH4+jRo/jxxx9hs9kc67TDw8OhUCig0WgwceJETJs2DREREQgPD8eLL76Idu3aOaqZE0JIbdDpdDh+PB9Hj8qQliZHdnYiMjPluHgRuHYN8K+cIve++ioSI0bkIzraigsXLiA4OBhmsxlms9ltISlCGgp+UiAkJASFhYWwWCz0viCEEFIpnwbd2dnZGDNmDDIzM6HRaNC+fXts374dffv2xZUrV7BlyxYAwC233CK63+7du9GzZ08AwPvvvw+ZTIYRI0bAYDDgnnvuwapVqxpk0R9CiG9culSEl1+2YcOGZLCsb2e9pFJALhf+KRTi7bL/LJZiWCwMjh0LBAAYjRIsWRKNt966LlqKU1xcjPDwcF9+a4T4nMlkglwuR0BAAACuyCsF3YQQQirj06B7xYoVbm9LTk5GVZabq1QqLF68GIsXL/bk0AghpFI2G7B8OfDqq4HQ6ap+oS88HGjaFEhJ4f4lJwNqdfmAuLKAuewxMhlQQVFyl1JTM2EwmDBqVBOcOsUVkty8ORSjR+ehRQsjAK4FWUlJCQXdpMEzmUxQKpWQyWSQSCR+UySREEKIf/O7Nd2EEFIXnD0bhjfflOCffwBuTbRYZKQFiYlmtG8fKAqwmzYFynQ59CmtVov09HRMm5aFCROaAABYlsGiRdH49NOr/22zKC4uBsuyovWrOp0OOTk5jtRzrVYLjUbjk++DkNpgNBoREhIChmGgVCop6CaEEFIlFHQTQkgVsSyLy5dL8corwPffdy93e0qKEdOmZeG220qhVtuhUqmQkpLig5FWHR8kq1S56NmzCHv2cJU3DxwIxoEDQejalSuiZrFYYDKZoFKpAHABd3p6uuNxTCaTY5sCb1If2e12WCwWx3uAgm5CCCFVVc1EREIIaVhsNht0Oh0uX07HjBnZ6NBBhe+/DxQdExLCYvr0TKxbdwHduhVDrbYD4GaR6wKNRoOUlBTMm8dAKhWW9bz3XjRsNjj6EhcXFztuy8nJcflYubm5Xh8vIb7AB9h89xOVSgWTyVSlpXCEEEIaNprpJoSQMsxmM/R6PYqKilBaWoq//grA3LnxOH++fKvBsWOBefMYBASokZtb4ljzqdVqK+zX6I86dQrGuHEmfPEF932ePx+AP/9sig4dAlBQUIDi4mJERkYC4H5GrtDMH6mvygbdSqXSMftNxdQIIYRUhIJuQkiDUNH6Y5ZlYTAYHIG2yWQCwzDQ60OwYEEKNm4sH2w3blyIlSuD0KMH/zGqqRdp1e+8o8S6dQA/qf3hhwF4/HEgKCgIubm5sNvtkEgkUCgULgNsPiAhxB85fw5IpVIwDAOr1YpGjRpBr9dXWCzQZDJBJpM5uqPwv+smk4mCbkIIIRWi9HJCSL3Hrz/mU0H59cdZWVm4fv06zp07h0uXLiE/Px8BAQGIjk7Ajz+2Qt++CeUC7tBQ4KOPbFi4cC+6dq1/aaXR0cDkycL26dPAtm1c0G2322EwGAC4T52vKyn1pOEp+zlgtVphsVjAsiwUCgUyMjKg0+nc3p/PYuHJ5XKqYE4IIaRKKOgmhNR77tYf37hxAyUlJQgNDUXjxo3RsmVLnDnTCHffrcErr0jgtIQZDAM8/jhw/jzw5JN2SKveIazOmTqVa0XGmzePW78qlUod67o1Gg0SEhIgk3Ez/XK5HImJiXUupZ40HO4+BwA4qvJXVJOgbNDNVzA3Go2eGyQhhJB6iYJuQki95279McMwaN68OWJiYpCXF4iHHmLQrx9w7pz4uDvuAA4dAj7/HIiKqoUB+1hsLDBunLD9xx/AgQMMAgMDUVJS4tiv0WgQ9l//s7q4hp00LO4+B5y5m7VmWRZms7nc8gmqYE4IIaQqKOgmhNR77tZbcrNUwJw5QMuWwIYN4tsjIrhA+88/gU6damGgfuTFF7nZfd78+VyKeWlpKWw2m2M//7XzPkL8UVXWXfNBtcXCXWzasAFYuRJYtMiGXbuCwDDioJuvB3Hq1CmkpqZWmJ5OCCGk4aJCaoSQek+r1Yp6SvOOHYvDgAHAxYvi/QwDPPkk8PbbQAV1leq15s2BYcOAjRu57S1bgLS0IMhkQElJiWNWmw+27Xa7r4ZKSJW4+xwAuOCZYRgYDEYsWZKBDz6IxsWLzmtIZACSsHSpEZ9+qkf37sHQ6XSOINu5VgRAveoJIYSI0Uw3IaTBUCgUYBgG2dlBeOmlFhgxQl0u4O7SBThyBFi6tOEG3LyXXxZvf/ihHHK5XJRiTjPdpK4ICgoCAMhkMjAMA7mc+30GuKUmx48HYOzYxpgyJa5MwC04e1aF3r2D8NJLRly75nr9N/WqJ4QQUhbNdBNC6jWWZZGTk4OgoCBotcmYO5dLlS67DFOr5faPGQNI6HIkAC6lvmdPYM8ebnvNGgZPPx0CiUSoMEcz3aSu4C8WNW7cWLQ2+9dfL2PBgnDs3Fm12WmbjcHChSp89VUSHnkkDw89VACNRrjoRGu8CakbKmolSoin0aklIaReKywshMlkwoULMWjdGnjrLXHALZUCzz7LVSUfN44C7rKcZ7stFuCrr8JgMplgsVgAUNBN6g69Xg+FQuEIuHU67r1/333J5QJuudyOceNu4IcfUrFr11n8+us59O0rXq+dkyPHhx/GoG/fFpgzJxYZGdysOfWqJ8T/uWslSnUZiLfQ6SUhpN6y2+3Izs7B+vVxuPdeFa5eFd/evTtw7BjwwQcAXdx2rX9/oH17YXvVKiV0Oolj1pDSy0ldwLIs9Ho9goODAQC//w506AB89BFgtTKiY++9txBbtqTixRez0LSpCVFRVsTGWrBoUTreey8N4eFW0fEGgwRr10bgvvuaY8aMeBQWxtTa90UIqZhOp0Nqamq5YofuWgjS8hDiLRR0E0LqrevXCzFtWjRmzQqH1ek8OS4O+OYbLm26XTufDa9OYBhg+nRhu7iYwYYNWhQXF4NlWZrpJnWC0WiE1WqFQhGM6dO5ZRNlL8J17FiMtWsvYP78a2jUyOLycfr1K8K2befx7rtGJCWJb7NaGWzZEoZOnYLw0EPcBT1CiO+4m80+d+6c22UgtDyEeAsF3YSQOs/Vlezz5+3o00eNn34KFR07ejRw9izwyCPilljEvYcfhijA+PrrMOTllToCbalUSkE38Wt6vR46nRyDBgViwQKAZYXbmjRh8dZbx7F6dSbatq34hFulUqF160Z45RUVLlwA1q0D7riDFR3DssD69cBttwEDB3Ktx9xxNwtHCLl57maz+eVRrtDyEOItFHQTQuo0V1eyv/66EHfcweL8eZXjOJkMWLIE+Oor4L8MU1JFMhkwbZqwfeOGFBs2BMJgMAAA5HI5pZcTv8QHtcePF2DMmGQcOiS+0vb448Dhw1a0a3cVjRsno02bNm5PulUqFVJSUhzt8mQy4KGHgL/+YvDFF9dx553lA/affwa6dQN69AB++UUc7NOaUkK8y2w2V/s+Wq3WCyMhhIJuQkgd53wl22Jh8N570ZgyJQl6vdDyJzbWjr17gWeeodntmpowAYiIELa//DIS+flccKBQKGimm/gdPqj9919g9OgmuHxZCKYjI4HNm4HPPy9/Ec7dSbe7/QwD9O/P4Msvr2L/fm52u6zffwcGDOAC8LQ0bh+tKSXEu2Sy6jVpio2NdVxUI8TTKOgmhNRp/JXsy5cVePTRJli1Kkp0++23l2DDhqvo2tUXo6s/AgOByZOF7bQ0JTZs4Kbt5HI57HY7WJZ1c29Cal9OTg4uXVLgsceaIDdX7tifkGDBwYPAkCGu76fRaJCQkACVSgWGYaBSqZCYmFjhybharYbZbEbnzlZs28at537oofIX+Q4c4FrxHTrkfhaO1pQScvMKCwsrTCN3plQqIZFIYLVaKz+YkBqioJsQUqcpFAps2hSKhx9OwZkzAaLbxoy5gc8/v4yQkFIfja5+mTwZCHD6ES9fHgGW5V4DlmUp6CZ+RaezYNq0RFHWS6tWBnz99SWkpFR8X41Gg5SUFLRp00aUUu6OWq0GAJSWcp81t9zCrfc+cwYYP55LRedlZ3OF3H79NdzlY1V3do4QImBZFmFhYcjOzkZ4eLjoAppcLnd5n+joaISGhqKgoICytojXUNBNCKmzSkuBWbMS8cYbjWAwCB9noaFWLF58FdOnZ0Eup8IonhIZya2B5Z0+HYC//grEjRs3AFAFc+Jf3n23ES5cEOo63HZbCb744jLi46UV3Ktm5HI5ZDKZI+jmtWgBrFwJnD/PFVbjmUzACy/EYvFiLcq+bSwWC3Jzc+kiFiHVxLKsI9iOjIxEbGys6AJaixYtREG4UqmCVJqE/PwQhIWFw2q1Qq/X+/rbIPUUXU4lhNRJqanA8OHAv/+KA+o77yzGnDnXoNUKaWJUGMVzXngBWLqUhc3G5c1+8UUkOnfmei/pdDpEOC/8JsRHVq4ENm4UZqejoixYtCgNQUF2r3weMAwDtVpdLujmNW7MreseP56rbM777DMtLl9W4u23ryE8XImoqCgYjUZkZ2fDYDAgPj4eUqnnLxIQUt/Y7XakpaWhuLgY2dnZaNGiBRgXRVwCAjQ4fFiDnTuB334TWgeGhKjQsmVTtG5tRo8ewK23Aq1bA/zkuE6nQ05ODsxmMxQKBbRaLTQaTS1+h6Suo5luQkids349cPvtwL//CvukUmDuXOCnn2xITJRVeS0mqZ7kZGDgQGEm4MCBYJw5w80m5uXl+WhUhAhOnACeflrYlkpZLFhwDfHxcq9+HqjVahgMBrcZH4GBwHffAa+/Lt6/Y4cG//tfS6hUKdBoNIiOjkZiYiKKi4tx6dIlGI1Gr4yXkPrCarXi8uXLKC0tRaNGjVBcXOzyuOvXgTvuAEaNAr74Qgi4AaCoCPjrrwCsWqXBY49xS0SCgrg2o2lp1GmA3DwKugkhdYbFws20PvQQ4JwBFh1tx65dwMsvA2Fh1VuLSapv3Dhx1eWVKyMBVNz7lJDaoNcDDz5og3Oc+vrrRowb19jrnweBgYFgWbbCIFkiAWbPBtasAZxXvfzzjxR33eU86xaCpk2bAgAuXbpEJ/eEuGEymXDp0iVYLBY0btwYgYGBLo9LTeW6B5w4UfXHNpu592r//irk5pZPDnbVaYBvU3jq1CmkpqbSe5c4UNBNCKkTMjO54kPvvy/e37lzCY4eBbp398mwGqT27VncdZdw1eO330Kg10uoABTxKZYFHnvMjNRUIR27e/ciDBt2sVZOfPl1oiUlJZUeO2oUsHcvEBUlzIqnpQG9e3OzcQBXi6JJkyYICgpCeno6srKyaJ03IU4MBgMuXboEAGjSpAkCAgJcHnf8OBdwX7ki7FOruTZ+8+cDn3wCPPkk0LkzoFKVf4+dPavEmDFNcPWqQrTfaDSKPlv4NoU0I05coaCbEOL3zp0DunTh2u04mzTpBtat0yEujj7KapNWq8WIEfmObbNZgl27QiirgNQ6flbp5MmTePPNDGzYIJwUx8SYMWfOdUgktdP7urJ13WV17gxs3ZqFZs2E1mGXLnGBd1YWty2VSpGQkICYmBjcuHEDV65cobZGhADQ6/W4fPkyFAoFmjRpAoVC4fK4n38GevQAcpwStFq14s4rfv4ZeOklYNIkYNkyrpVfXp4FmzenYtmyYjRqJNzn+nUFxo5tglOnVKLH54Nqm82GLP6NW0ZtfP4Q/0dnqoQQv3bwINC1q3jtVVgYsG5dKSZPzoJW67rtDvEejUaDkSNDERJic+z7+WcNVYkntcp5Vun0aRXmzo1x3CaTsVi4MB2hodzvaG31vuaD7qrOSIeHl+D77/PRooWw7/x5oE8f4L+mAGAYBpGRkUhOTobRaMTFixeRm5tLKaykwSooKMDVq1cRGBiIxo0bu8yyYlngvfeAQYO49dq8jh25oobOAbUztVqB9u3l6NMnC3/8waJVK+G9nJ8vw4QJjXHggDiF/dq1azhz5ozbJVa19flD/BsF3YQQv/Xjj8A99wD5wqQqWrcGjh4FOnXKRUBAAFQqlfsHIF6j1WowfLiQxnvoUBCys6llGKk9Of9NXen1EkyblgiLRTileeGFLHToYHBs19YFIbVaDZvNBrPZXOmxdrsdJpMJCQkK/PYb8N8SbgDAqVNAv35AQYGwLygoCCkpKWAYBtnZ2ZTCShoclmWRk5OD69evIywsDImJiZBIyocyZrMEEyZI8eKLELXku+cermJ5ZGTFzxMREQGj0QijMRWffXYW7dsL2SulpVI880wSfv5ZqFzOsizi4+PdzrbTBWkCUNBNCPFTy5cD998PGITzZnTrBuzbB8THW6DX6xEWFua7ARI88ojwtc3GYPNm1ycchHiD2WwGywJvvBGPa9eE37177tFh9GhxJf3aahuoVqsBoEop5vzsl0qlQnw8FwwkJgq3HzvGrTl1nqWTy+Uu2yABlMJK6jeWZZGRkYGcnBxotVrExcW5fC9kZAAzZnTDmjXiEOfpp7l08uDgyp+L70BgNpsRGmrD559fxt13C3VMrFYJpk9PwLffcpl2KpUKYWFhiI6Odvl41LaUABR0E0L8DMty1X2feEJ8hXrYMODXX4HwcC61jGEY6pHpY716Ac7nGJs20dV8Unvkcjm++ioCO3cKnwPx8WbMnn0d/Ll4bbcNlEqlUCqVVQq6+SrnfLZOUhKwaxcQFycc89dfwMCBgHMHJHez6JTCSuorvgd3QUEB4uPjodVqXQbchw8DXbvKkJoqXJCXybhCaR9/LPTcrkxOjrhDh1rN4sMPr+L++8XZJO+8E4fNm0MdQbVGo0FCQoLjPS2RSKhtKXGgoJsQ4jesVq6C6Jtvivc/9RTw/fdAQAB3tbugoAAajQZSqdT1A5FaIZUCDz8sbP/1lxJpab4bD2k4bDYW778fgYULYx375HI73nsvDSEh3NW6xMREn7QNDAwMrHLQrVAoROmxTZtygbfzxaw//gCGDBGyfiiFlTQkfA/u4uJiJCUluc1wW70auPtuICNDCMYjI7kMkkmTqvecri5syeXA229fw9Sp4otbb74Zj927hc8YjYZrWxoREQGpVEoBN3GgoJsQ4hcMBmD4cOCzz8T7336bu0LNx9clJSWwWCwID6cCav7AOcUcAL77zjfjIA2HwQA89JAFn3wSIdr/8stZaNPGWOuz22Wp1WqYTKZKq4wbDAaXNSlatAB27gQinL693buBBx4ATCb3qaqUwkrqA+c+1+fPn8eFCxdgNpvRuHFjBLvIDbfZgJdfBsaM4d4fvHbtWBw+XLN2ou4ubKlUSnz4oRIzZjg/P4OHHwb27Cl7rAoWiwU2mw2EABR0E0JqifMf0rLVdvPzuWq9mzcLx0ul3LruGTMAhhHuf+XKFTAM47ZKKKldnTsDjRsL299847uxkPovOxvo2ZPFpk3ik+JZs4DZs+PQtm1bn8xuO6vKum6+AJq7QpBt23LLaUJDhX3btwMjRgBqtZDCyqfYhoWF0YwaqfPK9rk2m82wWq3QarWO95X4eC4LZP588f4uXTKwd68Vyck1G0dlF7beeovLyuOZTNw4jh4V9vHvbVr2QXgUdBNCvK7sH1LnartXrwJ33SXuwR0QwAXgEyeWvz/AnbBStV7/wDDAyJHC9vHjwNmzPhsOqcdOnAA6dQL++ktIH1UquQs9b7wBuKkvVuvkcjlkMlmFQTc/A1ZR94XbbuMCbefJvS1bgEcfBQIDuRTWNm3aQKPRoLi42FH8iZC6quxaal6Bcxn//5w/D9x5J/DTT+L9r79uw0svHUZQUM3H4bw2m2GYctkzDAMsWcJdBOPp9Vzhw/PnuW1+uQdfu8GViiYjSP1DQTchxOvc/SHdv1+Hrl3FQVpEBJdKed99ld+fqvX6B0oxJ962fTt3cc65ZkBUFLf+uezvn68xDOPo1+1O2SJq7nTuzAUVzpN8338PPPYYl1YLAFFRUbBYLCgsLLzZoRPiU1UtEvjrr9x7w/ncQa0G1q8HXn/dDhddxKqNX5vdpk0bl9kzUinw9ddcaz9ebi7Qty9w7RpXRE2pVLoNuiuajCD1EwXdhBCvc/WH9PDhQIwcGY+MDGFfcjJXNOiOO2woLi5Gbm4url696jY9i9K2/EPbtkCzZsL61e++46rQE+IJS5ZwF+H0QscetG7N4s8/ga5dfTeuiqjVahgMBrezz0ajERKJBPIqlFPu1g3YuhVwjs9Xr+bSW+12LnDXaDTIzc2l2W5Sp1VWJJBlgfffB+69F3C+xpSUxGXLPfhgLQzSiUIBbNjAzbjz0tK4QDwvDxUG3TSZ0PBQ0E0I8TqZTCba3r49BJMmJaG4WKg+3qaNGRs2ZEIiScWZM2dw5coVx0mkuyrlVK3XPzAMMGyYcAHkzBng5Enua0qfIzVltQJTpwJTpojbB/bubcWBA4yoloC/UavVYFnW7Qm30WgUrcmuTO/ewKZN3Ek+b/ly7ufDsjTbTeqHitZSm0zAhAnACy+IPw+6d+dahXXoUEuDLCMoCNi2DWjTRth35gzX6s9qDXDMZJdFrf8aHgq6CSFepdPpHEXPWBZYsSISL72UCItF+Pjp3LkYy5dfQEhICdRqNeLj45GSkoJWrVqhcePGiHNuXOuEqvX6j2HDxIXtvvuO0udIzRUVcYWJFi8W7x81qgjbt0uh0bi+n78ICAgAwzBuU8z5oLs6BgwA1q3j+g7zPv4YWLaMm+0OCQlBbm6uyxN8Hl0EI/5Mo9EgNlZoA8ivpS4pCUHPnsCqVeLjJ00Cduzglpr4Ung48Msv3Iw776+/gCefDIXVanPZyYBa/zU8FHQTQryKT6GyWIBZs+LwwQcxotvvvbcQy5ZdRXAwi5SUFMTHxyMsLEw0C1RZURPiWzqdDmFh2Wje3ODY9913QHY2pc+R6rHZgC+/BNq1A37+WdjPMCymT8/E8uUKyOV+UjGtAvy67pKSknK32e12mM3magfdAHD//VzhOOc1qy++CKSmchchK5rtpotgpC7gM9tatmyJlJQUnD8fgo4dgUOHhGNkMmDpUuCTT8TZH74UH1/+AsCOHXL8+GOoy4wXav3X8FDQTQjxCn5GxWQyIS9PiieeaIwNG8S9tcePz8Xcudcgl7OVXt2trKgJ8Q3+RN5isWDAgCLH/gsXgOPHXQdHlD5HXDl6FOjSBRg/XlwwLTCQxZIl6XjuOSAgoPqBqq/wxdTKzjxXtYiaOw89BCxaJGwbDMC4cYBMxs125+TkuJztpjWkpC4wGAyODgDffgvcfTdw/bpwe0QEF9w+9ZTvxuhOs2bcjLfzW3vhwhhkZrr+m+e89E4ul9NkQj1HQTchxOOcZ1ROngzAww+n4O+/Ax23S6UsXn/9OqZNy3bM2NDV3brJ+UR+wADxjNmvv4a6vA+lzxFnOh23brtjR25tprNGjYANG7LRq1dJnfuMUKvVsNls5dZu3mzQDXA/r969he2DB4EFCype201rSEldYDAYoFAE4NVXgVGjAOdJ4rZtuc+Inj19NrxK3XorMGOGsJ2fL8OsWeL3On+O5Jx2brFYKlwaQuo+CroJIR7HB2I//BCKceMaIztbqNAbHGzDxx9fxaOPFlOqeD3gfCKfkGBG69ZCivmOHeEuq5jXteCJeAfLAt9+C7RsyVUody6OFBAAPP44sGdPKeLjbyAmJsZtQUV/pf6vz1fZdd1GoxFKpRKSm+hrJJEAK1cCzh+bb74JnD8fgODgYJdru2kNKfF3LMsiP9+Ip56Kxty54tuGDuUqlPtzAUXeSy8BLVoI2998E4QDB4RtyjppmCjoJoSUc7PFdkwmM5Ys0eL11xvBbBY+Zpo2NWLjxmt45JFwtGjRglLF64GyJ/LOs91paRLk5CQ7jqH0OcI7d47rZztqFJCVJb7toYe4NcqffcaCZTMQEBCA0NBQn4zzZkilUiiVSpdB983McvMSE4GPPhK2LRZgzBhAo9HCbDaXm+2mNaTE3+l0JkydmohffhFfCHrjDa41V3CwjwZWTUolV+DQ2ZNPsvivpixlnTRQFHQTQkRuttgOywJLlsTi00/FJ3J9++qwfv119OmTREFXPVL2hL1/f/HvybZtQWjWrBkALvWVXvuGzWAAXn8daN8e+O038W1Nm3LF0z7/XIfSUu6in9FoREhISJVba/kbfl03j28j5qnZ5bFjuRlA3okTwLx5rme7+YKUfMYAwzB0EYz4DZMJGDFCioMHgxz71GquYv+sWeLigXVBr17cRTDeiROM4yIZZZ00THXsV5gQ4m03k/bEssCrrwKffioumDZ1ajbeey8dTZr4uK8H8biyleWbNJGiY0dhndq6dQDLMpDL5W6v7pO6qzpZMT//zK3JfPttwPlXQaHgZrJOnAC6dBEu+vGys7PrbIVttVoNk8nkWLtpsVhgt9sREBDgkcdnGODTT8UVk+fPBy5dioHZbC73c9NoNKIgO7iuTB2Ses1sBkaM4Kp980JCgN27ucyXumrhQiAsTLjw9cYbXJFIyjppmCjoJoSI1DTtiWWB6dOBefPE+998MwNTpuiRlEQzKvVV2cryo0YJFVmvX+fW4SkUCgq665mqZsWkpwPDhwMDBwKXLokfo29f4ORJbiYrIKD+rXUMDOQKSPKz3Z4oolaWVssF3jy7HXjiCSUkEteVzO12OxiGAcuy9J4kfmHqVGDLFmE7KAjYvh3o1Ml3Y/IErRaYN0/I0ikt5b5X/mI1X72cbzFI50j1GwXdhBCRmqQ9sSzXK3bhQvH+998vxsyZcbRuu4F56CFuBo733XcUdNdH7gLkzMxMFBYWorCwBPPmWdGqFYsNG8THxMYCa9dy7XX+W30AwP3Fvbq61pFvfeQcdEulUlGrIE8YNoxLNeddvAh88EEszGYzzp07J8pEsNlsjpl2V/2DCfEGd1kxW7aILxqp1Sx++olrH1gfTJwI3Hab8D7bvJn7p9FoEBYWBrlcjuDg4Dq7hIZUHQXdhBCR6qY9sSzwwgvivrEMw2L27Gt46im5y/uQ+i0+nuutylu/HpBKuaCbWqLUH+4uolitVmzdmo9OnaR45RUZSkqEk0mJhMXEicXYty8X/foVoKSkGCaTCXa7vcIU8rq61pGfwXIOuvmlGJ724YdAQoKw/fnncvzxRxCsVqsoE8FsNkOpVEImk1HQTWqFu6yY1NQiPP64cBzDsFi8+Drat6+by0lckUiABQuKIZUKf/umTAGKi7msE4lEAplMJmofRuonCroJISJlZ2AqaunFssBzzwEffCDsYxjgvfcKMWJEidtZc1L/Pfyw8HVWFnD4cADsdjtsNpvvBkWqpKrrtF29vwsKpJg1KxFjxzZBaqo4hfrWW83YsiUTr7ySBbP5Bq5fv44rV64gNTUVp0+fRnp6utsx1eW1jmq1GgaDAXa73WOVy10JDeXaiDl744146HTiUz2LxeKorE5BN6kNrrJiWBZ48kkJnFeOjB9/A506FVareGtdcOutUowZc8OxnZ4OzJ4tBN1yuZyC7gaAgm5CiIhOp4NMJoNSqURERITb1HCW5a7WOresYRhg1SrgvvtyKV2qgXvwQXG12c2buUDDwvdMIX6pOt0LIiIiHF/b7cDGjWEYPLgZ1q8Xf16EhXHpo0eOKHDffdxyk1atWqF169Zo1qwZkpOTER8fX+G46vLyFLVaDZZlUVpaCrPZ7LWgGwDuuYf7XObl5Mjx7rtxomNYloVEIoFKpaqzafukbnGVFbNhQxh27RIqlTdvbsDkyUJwXlfrOLiiUqnw1FO5aNTI7ti3aBFw+rQUDMNAJpPBZrPBbrdX8CikrqOgmxDiwLIsioqKoNFoIJFI3M5K2u3AM88AH38s7JNIgK++Ah5+2ASz2YygoCCX9yUNQ3Q01zKFt3mzFFar+5Rk4h+qU8iMP0G8fDkY48Y1wZtvxkOnE2fKjBsHnD0L/O9/5Vv+SCQSKJVKBAUFISwszG0KuTeD1NoQEBAAhmGQn58PwPvfz9y5QPPmwva2baH45RfxRQupVAqVSgWz2Uwn+sTrymbFpKUpMH9+jGNbLrfj3XevQaEQUrDr0wUhpVIJtdqOd98tceyz2YBXXw0DIHFkGNJsd/1GQTchxKG0tBRWqxUajQZSqdTlyZjdDjz9NLBsmbBPIgG+/hoYPRooLi4GwzCOqr2k4XJOMb9xg8Hhw8EUdPs5d6+P0Wh0rMfn088vX87GokUxGDYsEcePq0XHt24N7N3LZb5UNTO8vrbRYRgGAQEBKCoqAuD99elqNXcBVCIRApi3347DjRtSxzYfdANUTI14n/N72GoFXn21EQwG4ffx2Wez0by5OMiuq3UcXOEvMPburceQIcL+v/9WYt26YMjlXP0bCrrrNwq6CSEOOp0OcrkcAQEBkEgk5YJuux2YNElcaVQqBdasAUaN4raLi4uhVqshlUpBGrYHHgCcSwT8+msYBd1+rqI6DOfOnUNaWhrS09Oxb58MDz6YgpUrI2GzCctI1GqubeDx40D37tV77rI93yuqJ1HXONfKuHjxotfXq3buDLz2mvC6FBbK8PXXWsTGxgKAY003UL9mFIl/0mg0jgvxK1Zo8e+/wkW6u++2YsyYvHL3qesX28riayh89BH3Ocl7660wXLnCfT7Q8qv6jYJuQggALrVcp9MhJCQEDMOUSy/ner8Cy5cL95FKgW++AUaO5I+xo7i4mFLLCQAgIgLo00fY3rkzEKWlFHT7M76VVFnR0dEICQmBTleEZcuiMHFiY6Sni2ei7r8fOH0amD4dkNewcUHZnu/1IeDW6XSOWW4AFa6T96TXX+cyDngbN4ZCIuECH6lUColEAoVCQTPdxOvsdjsMBgOuXYvFsmVCMK3RAGvWyJCUVD8vtjlTqVQwGo1ITGQxe7awv7RUgscek4JlGZrpruco6CaEAABKSkpgs9mg0WgAQJRebrNxvSa/+EI4Xirl+uyOGCHsKy0tBcuyCA4Ors2hEz82fLjwdWGhFAcPUgaEvzKbzdDpdAgKCip3AhwVFQWtNg6zZ8dh6dJo0f20WgsWL07DDz8ASUm+Gbs/q846eU9SKIDnnxe2CwulWL2aO6nnM5H4QIAQb9Lr9SgpYfHss2FwLhWzdCnX5q4+XmwrS6VSwW63w2q14vnnxTVPDh1isHNnGM1013MUdBNCAABFRUWO1HKdTofCwkKYTCacP5+KcePMWLVKOFYmA9atEwdUAPeHla98TggADBrEVbXn7dihpl7dfohlWWRkZEAmkyEhIaHcCXBpKbdcYP36cNH9hg/Pxw8/pGLAAMpgcMfdkoraSOseNYprJcb77DM5WFYIuqltGKkNhYWFWLkyDufPC2HHww8Djzziw0HVMucaChIJ8OWXgEolLOFbtiwSFgvNdNdnFHQTQhyp5RqNBkVFRUhPT3ekls+bF4o1a4R1njIZ8P333Al4WXxqObUKI7zoaKBrV2F79+4QmM10Nd/f6HQ6FBcXIy4urlw9hhs3uFZUW7cK+6RSFm+9dQ1vvpmB4GB7vVt/6Unu1snXxsVJtRqYMEHYPnlSiRMnuJodABcI2Gw2SmslXmO1WnH6tBkrVoQ69sXFcbPcDelUQS6XQyKROC5yJSQAjzxS4Lg9NVWBnTtruC6H1AkUdBNCRKnlzqmQq1dH4Isvohzbcjmwfj0wdGj5xzCbzTCZTJRaTsq5/37h6+vXFTh2jE7w/YnVakVmZiY0Gk259++VK0C3bsChQ8I+tZrFp59mYtgwXb1df+lJvq7K/tRT4u1vv41wFHOjCubE24qKijBvXjTMZiHC/uADIDzc/X3qI4ZhymWWjBlzA3K5kPn16afc5y/fIeLUqVNITU31ev0HUjso6CaEOKqW831bAWD79hBRH02AS4dyDqCcFRcXAwAVUSPllL1Is3mzT4ZB3MjKygLLso7K1rzjx4EuXYBz54R9UVHAnj0MJk6Mq9frLz3J11XZU1KAvn2F7JJffglBRoYV6enpMBqNYBiGgm7iNZs2mbB3r/C73qtX+aVpDYVKpXIsK2FZFlFRFjz0kLD85M8/1di9uxjp6ekwmUxgWbbWCi8S76Ogm5AGjmVZFBUVQaPRgGEYKBQK/PlnIF59tRFYVrgy/dpruRWuv6JWYcSdZs2AVq2E7W3bKIXOXxQXF6OwsBAxMTGitla7dnEtv7KyhGObNAEOHAA6dvTBQOs4XxeKGj5cyGCyWCTYuJGbZszNzYVSqaS2YcQr9HozZs8WprSlUmDx4oaVVu6MD7pZlnXUNpkyRfzeW7DAdc0TbxdeJN5HQTchDZhOp8P58+dhs9lQVFQEnU4HiyUaL7yQAKtV+HgYPz4XL7/sfv0hy7LUKoxUyHm2+8QJOdLTfTYU8h+73Y7r168jMDAQYWFhjv3ffQcMGADo9cKxt93GBdwpKT4YKLlpd95ZiEaNhBm1bdu4LhUmk4kqmBOvmTvXjLQ04dxh8mSgTRsfDsjHVCqVY/aa7w7TujVXcJT3yy9BSE8vXweCLozVfRR0E9JA6XQ6pKenO1pUmM1mXL2ajiefVKOoSJjxGjxYh/ffV1Y4M1NaWgq73U5BN3Gr7LIESjH3vZycHFitVsTFxTmKHy5dylUUdu5c068fsGcPVxSP1E0BAQoMHlzo2L54UYUbN7hOE86zb4R4Sno6i/ffVzu2o6KAmTN9Nx5/wBdPNBqNjqBbIpHgpZeEY+x2Bl9+GeH2vqTuqlHQnZ6ejn379uGXX37B0aNH6eoLIXWQq96xX34ZiX37hIC7fXsDPv7YiNDQilMhi4uLIZVKERAQ4PFxkvqhY0fAeckwBd2+ZTAYcOPGDURFRUGpVIJlgVmzgGeeAZxjrzFjuKrlVB+xbtNqtbjzzmLRvr/+CoRWq4VSqYTdbnfb2oyQmpg2zQaDQQgz5s4Vt69riGQyGWQyWbmg++67gU6dhA/ezZvDUFAgXqpHHSLqvioH3VevXsWrr76K5ORkJCcno0ePHrj33ntxxx13QKPRoG/fvvj+++8dv0SEEP9W9gTrzBkVPvpI+FAPDAQWLcqBRFJ5pWm9Xk+twkiFJBJgyBBhe88eFoWFPhtOg8b35FYqlYiMjITdDkydWn4Wato0YNUqwE3HK1KHaDQa3HtvBAIChHO0U6eiERIS4qhgThMoxFP27gW+/164gN+pEzB+vO/G40/KZpYwDAOGgWi222iU4LvvuNluhUJBHSLqiSoF3c8++yzatWuH1NRUzJ49G6dOnYJOp4PZbEZWVhZ++ukndOvWDa+//jrat2+Pw4cPV+nJly1bhvbt2yMkJAQhISHo0qULfv75Z8ftLMti5syZiIuLQ0BAAHr27IlTp06JHsNkMmHKlCmIjIxEYGAghgwZgmvXrlXjR0BIw+TcO9ZgYPDKK41E67g//JBbv2mxVNxT2Wq1wmg0Umo5qZRzirnVyuCnn3w3loYsLy8PBoMB8fHxsFolePRRYMkS8TFz5wILFnAXS0j9EBWlQffuwgu6fz/3N0Amk0EqldK6buIRViswZYp4qcLixfRZwuNrKDjPdAPAsGEMkpKEyZBvvomAwcAgMjKSAu56okpvAYVCgYsXL2L9+vUYO3YsWrZsieDgYMhkMmi1WvTu3Rtvvvkmzp49i/nz5+Pq1atVevJGjRph7ty5OHLkCI4cOYLevXvj/vvvdwTW8+fPx6JFi7BkyRIcPnwYMTEx6Nu3L/RO1V2ee+45bNq0CWvXrsX+/ftRXFyMQYMGwWaz1eDHQUjDERkZ6fh60aIYXLqkcmwPGwZMmADI5XJYrRXPdPOtwqg/N6lM795AUJBwMvbDD74bS0Pj3Pc1KysLQUFBYFk1hgwB1q4VjpNIgOXLgZdfbrgVhuuzXr2Ery9d4vqwu+ofTEhNLVsGnDghfHhMmMDNdBOOSqWCxWJxTGjwQbdUCkycKLQFKyiQYvPmMMpAqUeqFHQvWLAAUVFRVXrAgQMHYngVG/ANHjwYAwcORPPmzdG8eXPMmTMHQUFBOHToEFiWxQcffIAZM2bggQceQNu2bfHll1+itLQU33zzDQDuJGLFihV477330KdPH9x6661YvXo1Tpw4gZ07d1ZpDIQ0dAcPhmHtWqFoR2ws8Pnn3Am3TCardKZbr9dDpVKJ2g0R4opSCdx7r7D9888AnU94H1800Tml8fp1A3r1suKXX4TjFApg/Xpg4kQfDZR4nXPQDQC//87979w/mJCays0F3nhD2NZoWLz7ru/G44/4gmgGgwGAEHQDwMMPGxERIUwafvllJEpK6GJYfVHls2SLxYKLFy+iZcuWAICDBw+iS5cuHhuIzWbD999/j5KSEnTp0gWXL19GVlYW+vXr5zhGqVSiR48eOHDgACZNmoS///4bFotFdExcXBzatm2LAwcOoH///i6fy2Qyif64FBUVOb7HygKMmuIf11uPT3yvrr3GBQUFKC0Nwv/9X5xo/4oVVoSEsLBYuD8GNpsNJpNJ9IeBx7cK02g0deb79oS69lr7k0GDGMdav+JiYMcOK/r398+qyfXldc7OzhZtZ2XJ8OSTybh4UTgFCA5msWGDDT17sqjj32611ZfXuSratQOCgmQoLuZmInfvtuORR2yOz/lTp05BLpcjMjKyXmUvNaTX2JdeeUWKwkLhXOGNN+wIC7PX6meKv7/W/LlUSUkJAG6JHp9qrlYzePTRAnz0EZeJeO2aAj/+qMAzz/jn9+Ir/vYaV3UcVQ66x40bhyNHjuCBBx7A3LlzMW3aNBw4cKDGA+SdOHECXbp0cawJ3bRpE1q3bu147OgyPUqio6Md6etZWVlQKBSi/qL8MVlZWW6f891338WsWbPK7f/111+hVqtd3MNzduzY4dXHJ75XF15jqVSKpKQkPP98DHJyhDSwwYMvwmw+6VhrGxAQgLi4OOzcudNlmrlSqUSjRo1w4sSJBpmaWBdea38jlcogld4Lm4078ViyJB02279ef16+F7VcLofFYkFBQYHjpKcydf11btKkiaPI4eXLCkyalIzMTKGmg0ZjwhtvHERpqa5Br7Ov669zVTVrdieOHePOrbZvL8XevYcQExMDAI4ewhkZGcjKyqrye6SuaCivsS9cuBCKlSu7O7YTE/VIStqNn37yzUVVf36tExISYLfbwTAMtm/f7tgfGhqKBx6IwKefhsJk4kK0FSvC0LjxzwD88+K0L/nLa1xaWlql46ocdP/zzz84f/48Zs+ejSVlK67chBYtWuD48eMoLCzEhg0bMG7cOOzdu9dxe9lqyCzLVlohubJjXn31VbzwwguO7aKiIiQkJKBfv35eK1ZgsViwY8cO9O3bF3K53CvPQXyrLr3G+fn5+OmnUhw4ICwbaduWxZo1iVCpEh37TCYTrly5gm7durm8IJWXl4f8/Hz06tWrQVUur0uvtT/65BMz9u/nagj8+28yBgxohJISPW7cuAGLxeLxmTa9Xo+MjAzHtlKpRExMDOLi4ip8jqq8znq998btCc7f+6lTKjz1VDIKCoQ//UlJLLZtk6B587t8NUSfa2jv5xMnJDh2jPs6KysISmUTAMJJI/9ZnpSUhOTk5NofoBc0tNe4ttntQPfuUrCscB6wfHkAeva8t4J7eUddeK0zMjKg1+shkUgwcOBAx36dToesrCxMmMBg2TJu38mTashk96BfP2ojwfO315jPmK5MlYPuuDguBfWNN97Ao48+isuXL9dsZGUoFAqkpKQAAO644w4cPnwYH374IV5++WUA3Gx2rFNz15ycHMfsd0xMDMxmMwoKCkSz3Tk5Oejatavb51QqlS6bzMvlcq+/eLXxHMS36sJrrNfr8dlnjRzbEgmwZg2D4GDxuPk0KJZlXX5PpaWlCAoKElVCb0jqwmvtjwYNMmP/fu7rzEwG+/ebEB0tBMVmsxkZGRlISEiARqO56efLy8tzuT8/Px/h4eGV3t/d66zT6UTBvKfH7Qn8937+vBITJzZGSYnQ+7VVKxt27JAiPp5+h4GG834uu6770CG5qNYCz2w217ufR0N5jWvbypXAX38J20OHmtC3b/nz7Nrkz691QECAI+h2HiMfmzz7rA2ffiqB3c5dxPjwQwXuu88/vxdf8pfXuKpjqHIB/x49ejhy1pctW4bOnTvXbGSV4FObGjdujJiYGFHqgNlsxt69ex0B9e233w65XC46JjMzEydPnqww6CakITMajdi3T4pDh4Rq5aNGAe3blz9WIpFAIpG4TC232WyOoJuQ6hg8WJwm9/33ZpfH5ebmeuT5yvak591s4aicnByX+z01bk8wm80wGBi89FKCKOBu374U+/dLER/vw8ERn+jYEQgIELaPHnWd4edqcoKQsnQ64JVXhO2AADsWLZK6vwOBSsWdf5XNEOSDt4QEK/r3F2ZPd+yQ4+TJ2hsf8Y4qB93/93//5/hlCAkJwQ8e6PXy2muvYd++fbhy5QpOnDiBGTNmYM+ePXj00UfBMAyee+45vPPOO9i0aRNOnjyJ8ePHQ61WY9SoUQAAjUaDiRMnYtq0afjtt99w7NgxjB49Gu3atUOfPn1uenyE1EcFBYVYulTr2JZIgNdfd30swzBuK5jzrcIo6CbV1bSpHK1aGRzbO3a4rqXhqWrK7jIxbjao8FYw70kKhQLz58eKWgJ27lyMr7/ORBUm+Uk9pFAAznVwjx51/Rmu1Wpd7ifE2VtvAc7XH595RofGjambSUWcC4GlpqZCp+NahfFdYCwWCyZMyBfdZ+HC2h0j8bwavSuuX7+OP/74Azk5OY6Ke7ypU6dW+XGys7MxZswYZGZmQqPRoH379ti+fTv69u0LAJg+fToMBgOefvppFBQUoHPnzvj1119F6+Xef/99yGQyjBgxAgaDAffccw9WrVoFqZSuspGGS6fTIScnB2azGQqFAlqtFhqNBizL4tdfzThyJNBx7KOPAs2bu38svvBUWcXFxVAqlQ02tZzUnFwuR69euThzhptuu3RJhatXFUhKEgexnppp02q1SE9Pd7n/ZigUCpcBtj/NEO7YEYL164XoWqu1YMGCdCQn0xR3Q9a9O7BrF/f1+fNSqFSJsNuzHCnlsbGxXqtxQ+qPCxeAjz4Sths1MuPFF6s8n9cg6XQ6ZGZmOrZNJpPj71NISAgYhoHVakXr1gbcfbcZ+/Zx51jffMNi4sTLCA83iM7rSN1R7aB75cqVePLJJ6FQKBARESFKjWAYplpB94oVKyq8nWEYzJw5EzNnznR7jEqlwuLFi7F48eIqPy8h9Rnfk5fn/IEukUjx0UdCT26p1P0sN08ul5eb0WNZFnq9nj7wSY1IJBL062fA0qXCvs2bQzF1qjhd21MzbfzvaUZGBmw2m8eCCm8F855y9mwpXnkl0rHNMCzeey8HHTrEU0DVwPXoId4+fjwEDz4YjPPnz0Oj0dDvB6mS6dMhagf24ouZUCrpvKAiFS1L0mg0kMlksFqtYFkWkycbHUG3xcJg5cpgvPBCqei8js7D6o5qX45644038MYbb0Cn0+HKlSu4fPmy49+lS5e8MUZCSDVU9IG+bZsBR48Ks9yjRwPNmlX8eK7Sy00mE6xWq19VaSZ1S7t2LJKShN+rr76KQload3KhVCqRmJjo0RN/jUaD0NBQAEBYWJhHHluj0YhmtVUqlcfHXVNmsx2jRwN6vZD19dprDEaPpoCbAJ07c2nmvL17uYkOtVpd79qEEe/45Rdg0yZh+447StC7tx7Xrl1zpEuT8ipblsSfc7Esi3vusaJNGyGjeN26cOj1QujmT/VDSOWqHXSXlpZi5MiRjqrGhBD/4u4D3Wg0YcECIeCWSoH/+7/KH08ulzuuuvKKi4sdJ2iE1IRSqcDUqcKaNZOJwZw5sWBZeC1w5X+HXS2XqCmbzQaA67uakpLiNwHta6+V4u+/hfdnly7Am2/6cEDErwQEcIE3j+/UGhgYCIPB4Pi9JsSV7Gxg7FghGGQYFtOnZ4JPfqVg0L3Kaow4L+mTSBi89JJwTEmJVLRcyJ/qh5DKVTtynjhxIr7//ntvjIUQ4gHuPtAPHw7B0aPCSfiYMcB/3foqJJfLwbKs6CRMr9cjKCiILr6RGpPL5RgwIB+9ewv7DhwIxi+/hJSrFeJpngq6bTabo7K/80UpX9u504T33xcusIWEAN98A/hBZxXiR7p3F74+cQLIz+eCboCbYCENk06nQ2pqKk6dOiUq8sWz24HRoy3IyRH+/o8cmY9WrYyObQoG3XO3/IjfL5PJHJMnDMNg1CgJoqOFv1mrV0fAYuGubvhT/RBSuWqv6X733XcxaNAgbN++He3atSvXm2zRokUeGxwhpPpcrTNlWeDjj4W1nVWd5QbE1TRlMpmjVVhMTIzHxkwaHoVCAbvdhsWLbbj1Vin4BI1582LxyCMmr7Sy4gNjd9kg1eV8YumroJsvmmgymcAwDAoLJRgzpqmjvysAfPYZkJzsk+ERP9ajBzBnjrC9bx8wZIgCUqkUpaWltHyoAaqoJgy/dviDD4CdO4Vz/2bNjHjhhSzR41Aw6B7/c8zNzYXJZIJSqYRWq3VkSfFrugEu6JbLgcceK8TcuVEAgJwcObZt02Do0EK/qR9Cqqba01TvvPMOfvnlF2RnZ+PEiRM4duyY49/x48e9MERCSHVoNBqo1WowDOModPjnn8H4+2+hMevYsUDTplV7PP7CGj87WFJSApZlqVUYuSl8Rkbjxma8/LIQsN64Icfs2d6ZknVOL/dEkOzr2Rz+BJkfh93OYubMOGRlCdkuEyYADz/sqxESf9a1KyBzmnrh13UHBgbSuu4GqqKaMADw99/intwqlR0LFqRDpRJ/nlIwWDGNRoOUlBS0adOm3LIkPrsQEPp4P/aYFcHBQrbhqlWRiIqK9pvlTKRqqh10L1q0CF988QXOnDmDPXv2YPfu3Y5/u/j+E4QQn2JZFhqNBo0aNXIxy81i6lR9lR+Ln+nmr7wWFxdDoVDQlWxyU/ig22w24/nnjUhIEALYVasUyMpyd8+bV3a5RE2ZTCbHRSlfzHSXPUH+/vsw7NwpVLJt0sQsaudDiLPAQOCOO4Tt33/n93Prur29zIP4n4qKfOn1wMiR4mrlL7+ciaZNhc9uhmH8pphkXSVzuhLGB90REQqMGCHUQLl4UYVdu6gXel1T7aBbqVTirrvu8sZYCCEewLIsjEYjVCoVcnJycPBgEI4fF9Z3DhlSiKCg7Co/HsMwomqa/HpuQm6GVCqFRCL57yTPiBdfFKJss5nBkiWef06WZR11CDyRYs6nBjIM45Og2/l7uHBBifnzYx3bcrkd8+alIzDQ1T0J4Tiv6z52DNDpALVaDZZlYTAYfDcw4nGVrdUG3NeEUSiUeOYZri83r18/HR58sEB0XEJCAgXcN8l52S4fdCuVSjz6aB7kcuHvzNKlNPFR11Q76H722WepJzYhfsxsNoNlWSiVSpjNZnz6aZTjNpmMxRNP5FQ7LZavpmk2m2GxWCjoJjeNYRgoFApYLBYYjUb062dCy5bC7UuXAsXFnn9e/qTSE8XU+KAb8M1MN/+9GI0MXnopASaT8Cf9+eezccst/lPcjfgn537ddjvwxx9c6zuJREIp5vWI81IUlmUda7XLBt7u0sK3bo3H118L20lJLGbPzoJMJgXDMH7VLrGuczXTrVQqERVlxYABwuu1f78ax455rhMH8b5qB91//fUXvvzySzRp0gSDBw/GAw88IPpHCPEtPqBWqVQ4cSJE1Jd78OBCJCRYqp0azrcN41uFBdL0GfEAhUIBs9kMg8EAtVqFadOE2woKgJUrPft8LMuWmWGvObvdDrPZ7Jjp9gX+BPm992Jw4YLKsf/uu/UYPTqP1lWSSt11F+DchILWdddPla3V5mk0GsQ7VbGUyWS4fr0xXn5ZqAkjlQLLlxsQGGhBUlKSy3XJpOakUqnjbwr/v0wmg1QqxZgxN0THvvcetfarS6oddIeGhuKBBx5Ajx49EBkZCY1GI/pHCPEto9EIqVQKmUyGL78UKowzDIsJE7g/sNU9GefTy/V6PdRqNaRSqUfHTBomuVwOs9kMo9GIgIAAjB4NREZaHbcvWgRYrRU8QA1w1WDlNz3TzQftvkwv12g0OHw4DmvXRjj2RUZasGDBDSQl0awTqZxGA9xyi7DNr+tWq9UwGAx+1QqP1FxFa7XL4jNopFIp9PoQjBsXKPocXrgQaNEiD0qlEgEBAeXuT24Ov6SP/5r/X6lUolUrI+68U2jN9v33Sri5nkL8ULVX4a/09NQDIcSjjEYjlEolTp9msH27sDaoT58itGwpgVZb/ZNx5/Ty6OhoTw+ZNFD8TDfAZWaoVMD48XosXBgGALhyBVi3Dhg1yjPPxwcQfFr7zeBPVn0ZdGdlAdOmhYr2ffONHJ07N671sZC6q0cP4OhR7usjR4CSEq6YWnZ29n9ZKGqX9+Pb1ZnNZigUCmi1Wpp88VMKhcJlgO0q640/TqEIxv/+F45spxIwjz4KPPOMFefPFyE6OtpnWT71HT/R4fzzVSqVKC0txaRJJTh0iMtsMpsZLFtmx5tvVnsOlfhAtV+l1atXu73tpZdeuqnBEEJunslkgkqlwoIF4v1z5mhqnAJmsVhgt9vBsizy8/NdFmAhpLqci/aoVNxJxNixpVCrharJr74KlJZ67jn5me6bTS83mUyOjBKg9td0syzw5JNAQYHwZ3z6dKBv31odBqkHnNd1W63AgQNAQEAAGIZBqZs3X1XXCBP/4C67LSoqqtw+o9EIhUKJ116LxPHjwrKVW24BPvsMKCrSgWVZhIaGemm0pOxMNyD8jbnttkwkJQl/vz7+GDAaQeqAagfdkydPxo8//lhu//PPP19hQE4I8T673Q6TyYQbN9RYs0bY36sX0LFjzR5Tp9MhP19oVWE2m+nkiniEc+B75coV6HQ6REQwGDNG+N1KSwPmzfPM85Wd6b6ZQNm5iJovZnvWrAE2bxa2b7kFeOutWh8GqQfuvlu8/fvv3O+0Wq12u667qmuEiX/QaDSOANs5fdnV7LfRaMTKlVFYt04IuCMigE2bgIAAFgUFBQgJCREV/CKeo9PpHBe7rl69Cp1OB51Oh8LCQgBcDYZRo4S13bm5Enz7rS9GSqqr2kH32rVrMXr0aPzOL/wBMGXKFKxbtw67d+/26OAIIdXDBzGffSZeg/XyyzV/TDq5It6g0+mQmZnp2OZnyiwWC/73v1zExQnHzpsHXL7smeflZ7rtdvtN9eouG3TX5kx3RgYwZYqwLZPZMXv2VRgMdCGMVF94ONCunbC9dy/3P19MzdXvdnXWCBP/wC8TaN68OVq2bAmtVoucnBxcv35d1Ers669VmDdPWCYgk7H4/nsgLIxrOWY0GmEwGOjCuxfwGST83yZ+kiMrK0t03NChhQgOFv5+vf8+Cyq/4P+qHXQPGDAAn3zyCYYOHYojR47g6aefxsaNG7F79260dO73QgipdUajEcXFEqxaJVyBvuUWoF+/mj8mnVwRb3B3McdgMCAgwCZaHmEyQVTZvKb44IHvg1rTdd18Oq0vgm6WBf73P+C/SQ8AwFNP5aJxYz1loJAac04x//NPwGDggm4+e6osd/2cq9sZg9Qeu51btiP5r1x9VFQUgoKCUFBQ4FgmsHRpMGbOjAPLCtk7CxaU4LbbuGCQPx+wWCz0eeMF7v4ulv1bpVbbMXy4kIF44gSDXbu8OjTiATVaeT9y5EjMmTMH3bp1w9atW7F37140b97c02MjhFST0WjErl1hKCkR/mBOnw7cTPYrnVwRb3B3McdqtcJms2HkSBbdugn7N20Cduy4+efl+4MDNQ+6+dR0XwTdX34JbNsmbLdubXB0JQAoA4XUjHPQbTZzgTe/rttVirm7tpHUps5/lQ26GYZxfAayLLBoUTQ++CBGdJ+JE3PRp88VXLt2zeVj0ueNZ1Wn1sioUfmQSoW/O++/740REU+q0oKMF154weV+rVaLW2+9FUuXLnXsW7RokWdGRgipNpPJhM2bheri4eHAAw/c3GNqtVqkp6e73E9ITbmrpstXymdZOxYvluL224H/zhUxdSrwzz+Am+tAleIDY74Pak2LqTlXLq9Np09zPwOeXG7HnDnX4Ly0kjJQSE107y7e/v13oGdPCQICAlBSUoKICKEtndlsRmFhIdRqNUwmE2w2G1QqFbRaLbWp82N2ux0Mw4hqUJjNZthswOzZcdi4MVx0/OTJ2fjf/7ig2t1FRfq88azK/i46i4mxYOhQKzZs4DK3tm0Dzp4FKOnYf1Up6D527JjL/U2bNkVRUZHjdmodQIhvXbhgw19/CcVPRo4EbjYu4FvA5ObmOlJq6eSK3Cx3F3NCQ0ORm5sLu92OW26RYtIkYNky7razZ7kesa+9VrPnZFnWcdJ5M23DTCaTY204UDsz3Xl5wODBgF4v7Js8OQcpKeITNMpAITWh1XIn62fPctvO67oLCgoc7x2WZXHt2jVIpVIkJSUhJycHer0eKSkpvhs8qRI+6BZT4qWXorBjh7jV24wZmRg5Mq/Sx6TPG89y93cxNjYWLMuWOw+bPl2ODRuE4z78UPh7SfxPlYJuKpBGiP+z2WzYtEmc8jd2rGceW6PRUP9V4lHuLubIZDLk5ubCZrNBLpfjrbeA774D+AL6M2cC990HdOhQs+flTzpvpm2Y0Wh09OfmH9ObQbfZDAwfDly6JOzr3LkYY8feKHcsZaCQmurRQwi6Dx7kfu/UajVyc3NhNpuhVCqRm5uL0tJSNGnSxJExQuoGlmUdqeUAUFwMTJmShN275Y59MhmLt9++hvvuq9pabfq88azKJjnKnod16gR06cLi4EHuffjll8Dbb3PV5on/oW7qhNQTRqMJW7eGOrZbtOA+kAnxVxoN1zu+TZs2jh7y/Ekhv/4wIgJwXrVksXAXk2qS1egcGLtK16sq5yJqgHeDbpblKpXv2SPsS0oy4b330kRp5SqVComJiZSBQmrMeV23wQAcPixUvC4pKUFpaSlycnIQFRXl2A/Ufo96UjN2u93x+ZqfD/TpA1HArVTa8eGHV/Hoo4zbGWw+U4g+b7zH1d/FikybJlz4Mhi4XurEP1Up6H7yySddpju48t1332GNc4NgQkit2LfPirQ04Q/l2LE3V0CNEF+QSqUAIGrnNXYscP/9wjH//svNeNcEPzNX0/TyspXLnfd7w+LF4pOo4GAbFi++Co3G7tinUqmqdHJGSEVcresuLi4GwzDIyMjApUuXoFAoRLObNNNdd/BBd0YG91r/+adwW3Awi08/vYLu3YsRGhrqdgY7ISGhysEgqR1DhwIJCUKP2M8/N1NVeT9VpaA7KioKbdu2xb333otly5bh8OHDuH79OvLy8nDhwgVs2bIF06dPR2JiIj744AO0b9/e2+MmhJSxZo1UtD16tI8GQshNcBV0MwwXeEZFCcfNnw8cOFC9xy47022z2ardq9tqtcJut5eb6faGX38Fnn9e2JZKWSxcmIbGjcVp8VTMiHhCfDzQtKmw/dtvXFso5/eN2WxGUVGRD0ZHbpbdbkdamhzdugGnTgn7o6KAH34oxO23lwIAMjMzAXABtkqlopltP1dcrMOQIcL6+8uXFfj992wKvP1QlYLut956C6mpqejevTs++eQT3HnnnUhMTIRWq0WLFi0wduxYXLp0CcuXL8fBgwfRrl07b4+bEOLEaAS2bBEKqPXqBSQm+nBAhNQQH8CWDYa1WuDTT4Vtux0YNw5w0c2oSo9f07ZhriqXeyO9/OxZYMQIoXI7AEyfnoWuXct/w1TMiHiKc4r5oUNSWK3ljynbJorSy+uG06dlGDkyHpcvC/sSE4Gff9ZDq73u2GcymRzZrdVJcya+kZOTg169xBfC9u4NpnZufqjKa7q1Wi1effVV/PPPP8jLy8PRo0fxxx9/4Ny5cygoKMD69evRr18/b46VEOLG1q0sioqEme5x43w4GEJuAsMwkEqljjXdzoYNExcHvHCB60NfVWVnugH/DLrz87lK5c4TFaNG6TFqVL7L46mYEfEU56C7pESCs2cDyh3jnFlB6eV1w08/FWP48Cjk5gqFIFq2BPbvB0JCslzeh4K2usFsNqN5cxPi4oQMqN27QxzvU51Oh9TUVJw6dQqpqak0A+5DNSqkFhoaig4dOuDOO+9ESkoKfegS4mNffimc8KvVN9+bmxBfkkgkbtO+P/wQaNRI2F66lEvDrir+75VMJqtRr25+PXfZv3ueCrotFuChh7gLCrwuXUx48cWrSEpKpJRP4lVl13UfOaIudwxlVtQtq1eXYNgwNfR64cJ8mzal2LatCAkJcPsZSMtW6gaFQgGGAXr2FPpJHj+uRn6+BFeuXEF6ejpMJpOjHkl6ejoF3j5C1csJqeNycoDt24UA4IEHgOBgHw6IkJvkbqYbAEJDgZUrxfsmTAAKCip/XOfAmO+zXZOZ7rJBhydnup97Dti1S9hOTrZh/vxLSE6OR3BwcLUr2xJSHcnJ4qVJR44EljumbGYFpZf7r08+AcaNU8NsFk73O3UqxvLlV2C35wAQltqURRdX6gb+/eicYm63MzhyRIvi4mKX96EsBt+goJuQOu7bbwGbTQi6KbWc1HVSqbTCAmd9+gCTJwvb168DU6dW7bGdZ6hr0qvbXdDtCUuXcv94wcEsPvzwEpo1C0dYWJhHnoOQyjinmB87Fgy53H1mBWU6+ieWBd58E3jqKS4A4/Xvr8OyZVcRFGR3zGS7W55Cy1bqBo1Gg4SEBNx1lw3BwcLfzf37I9y+PymLwTco6CakDnG1NufLL4Xb4+O5ImqE1GUVpZfz5s0DmjUTtlevBjZsqPhxy87IVXem22azwWq1emWme+dO8YUDiYTFggVpuO22ADr5JbXKOeguKmJgMFScWUEz3f7FagUmTQJmzxbvf/TRG5g/Px0KBfd68Z9jfNBGy1bqLo1Gg1atUnDffcISgl9+AVjWdbYCZTH4BgXdhNQROp2u3Nqc337LwbFjwjGjRwNSqfvHIKQuqCi9nKdWA199BUic/opNmgRkZ1f82M5X/qvbq9tVETX+MW8m8Dh/nlvH7XydYfr0bPTrZ0dcXBzNJpJaVXZd99697o+l303/YjAADz4IfP65eP+zz2bh5ZezRJ+XzhfzaNlK/TBkiPB1SQlw9mysy+PoQq5vUNBNSB2Rk5NTbt+PP4aKtp0rOxNSV1WWXs67807glVeE7bw84IknuNRKV1zNdPN9t6vCXdDt6rGrqqCAq1ReWCjsGz68EI89pkdiYiIkEvozTWpXSgoQ63SuXlHQTfxHfj639GbLFmGfVAp88QWLSZMKIJNJaSa7nhswAJAJBerx22+BjiwGXnx8PL32PlKjv+br16/HiBEjcOedd+K2224T/SOEeEfZtac2mzjovvVWG1q3ruVBEeIFVUkv5735JtChg7C9dSuwapX748uu6Qaq3jbMZDJBLpeXC4RrOttntQIjR3Iz3byOHQ14/fUsJCcnQUppK8QHGEacYv777+J+8eJjPd+jnlRfejpw993AgQPCPrWaC8AfecQEm82GRo0a0Ux2PRcWJs5U2bIFCAnhshhatmwJhmGqXTyUeE61g+6PPvoIjz32GLRaLY4dO4ZOnTohIiICly5dwr333uuNMRJCUL7C6KFDQcjNlTu2aZab1BdVSS/nKRTA119z//OefRa4erX8sSzLlksvB9y3zCnLVRE1oOaBxwsviNudJSRY8P77aWjWLMltRWFCaoPziXteHnDmjO/GQip26hTQpQtw+rSwLyKC64IwcCBQXFwMhmEQGFi+Ej2pf5xTzDMygKNHua9lMhnCwsKQl5dX5b+vxLOqHXQvXboUn332GZYsWQKFQoHp06djx44dmDp1KvV98zJ6jzRsZdfgbN4c6vhaJmMxahSloZL6gQ+6qxrItmsHvPWWsK3XA+PHV/6ZWZOZbk8F3Z9+CixeLGwHBtrx0UdX0L59HAICAqr1WIR4mvNMN0Ap5v7q4EGgWzeugwMvKQn44w+gc2duW6/XIygoiJaqNBCDB4u3nZcbREZGwmazoaAqPTaJx1X7HZiWloauXbsCAAICAqDXc83Yx4wZg2+//dazoyMAuAJa27dfQbt2BqxadZ0ubjRQGo0GUVFRAICCAil27hTSw3r2LIVWSwVtSP3AnxxWNcUcAKZNA+66S9jes0cc1ALlZ7qr06vbbrfDbDa7rfpanaB7925xyzOGYTFvXjq6d49AcHBwlR+HEG9p1Qr4788NAPdBN6WX+86RI8CAAayoHkTbtjYcOAC0aMFt22w2lJaWIigoyCdjJLWvSROgbVth2znoVigU0Gg0uHHjBr1vfaDaQXdMTAzy8vIAAElJSTh06BAA4PLly/QCeoFOp8OHHxbjgQcScfp0AF56SYt//smgwLuB4oth/PJLLCwW4e07erTRV0MixOP4tczVSYGTSoEvvwScMyhfeQU4e7bi+1W1Vzd/zM3OdF+4AAwfzq3n5r3wQhYefFCJ8PDwKj0GId7GMOIU899/d1+gkNS+EyeAfv3sKCoSLiJ27FiMzz47h8BA7vxQp9PhwoULYFkWeXl5dN7YgNx/v/D18eNAWpqwHRUVBYvFgkLnqzWkVlQ76O7duze2bt0KAJg4cSKef/559O3bFw8//DCGDRvm8QE2dDk5OTh9WgWDgXupbtyQ4/XX45GTk+vjkRFfsNlssNuBtWuFWe6YGDOonAKpT/iguzoz3QDQtCmwcKGwbTRytQ74ALfsTDdQ9V7dFVUur2ohNZ2OW2+Xny/sGzq0AFOnWhEdHV2lxyCktjgH3VlZQGqq+2Np0sV7dDodUlNTcerUKaSmpuLvv/Xo2xcoKBBO4bt0KcayZVcRHGxHTk6Oo8Uo/9lmNpuRnp5OgXcD4byuG+AKjPJUKhWCg4NpttsHqh10f/bZZ5gxYwYA4Mknn8SqVavQqlUrzJo1C8uWLfP4ABs6s9mMF1/MQkqKMJP5++8hWLmSCmI0RHa7HYcPB+PiReGtO3x4AQIDVRXci5C6pSbp5bxJk4D+/YXtw4eBd991HxQoFIoqzXSbTCZIpVLInPux/KcqM918pXLnglS33VaKd94pQKNG8dTvmPidqqzrpt9b7+KDZ5PJBJZlkZ9vwf33K5GdLRxz220l+PDDq1Aquc8gk8mEa9euuXy83FyasGkI7rgDiIkRtp1TzAFubbfJZHIsESa1o9pBt0QiEZ10jBgxAh999BGmTp1K1Va9QKFQQKXi1vspFEKq5XvvRePff304MOITdrsd338f5tiWSlk88EABMjJoyQGpP2qSXs5jGGDFCiA0VNg3ezbw99/87eVnuqvSq9tdETX+MSsLuqdPB7ZvF7bj4iz4+OMsNG+eRAWOiF9q145rQcSrqJgazZh5R05Ojmj700+jcP26cK7dtm0pPv74KgIChJ+/TCZz+3rwGTukfpNIxAXVdu8GioqE7cDAQKjVaty4caP2B9eA1egv/b59+zB69Gh06dIF1/8rmfj1119j//79Hh0cESpWN29uwosvZjn2m80SjBwJlJb6amTEFzIyWPz2m1BoqXfvIkRFWWEymSh1jNQbxcXFALjCnampqdX+vY6PBz7+WNi2WoFx4wCTqfysHH+x2Oq8yNqFioJuoOKgY8UK4P33hW212o6lS6/httsaUS9u4rckEq73M2/v3vLrummm27ucs3AuX1bg668jHNuxsWZ88slVBAWJLxjGxcW5/ayq6DOM1C/OKeYWC/DLL+LbIyMjUVpaipKSktodWANW7aB7w4YN6N+/PwICAnDs2DHHVTO9Xo933nnH4wNs6DQaDRISEqBSqfDIIwXo2VO4VHXmDNfnlTQc336rgtUqnOQ89FC+6HZKHSN1nU6nE6VG1vSC0iOPAA89JGyfPs1g8eJolzPdQMW9ulmWrXSmmz+urN9/B556yvlYFvPmXUO/fjGUHUb8nvO67mvXgCtXfDaUBoVfx81/prAsMG9eLKxW4bT9pZeyoNEIS3BUKhUSExMREhJSrsUoz91+Uv/ccw/g3H2ybIp5cHAwlEolzXbXomoH3W+//TY++eQTfP75546TFQDo2rUrjvId2IlHaTQapKSkoG3bNliwIB/R0cKMzKefAhs3+nBwpNbYbMCaNcJa/sREEzp3Fl+hpNQxUteVTafkVfeCEsMAS5cCzvXJvvoqAvv3i9dkV6VXt8ViAcuylQbdZf37LzBsGDfLwJs6NRtjx4ZSL25SJ1S2rruiC06kevhA++TJk4513Lzdu4Pxxx9CltuddxajTx9hEkalUiElJQUhIVyRVecJG4ZhRAE5aRgCAoB+/YTtbdvEXTMYhkFkZCT0ej2MRuqAUxuqHXSfO3cO3Z0vff4nJCSEys/XguTkILzzzjUwjPAH7vHHgfR0Hw6K1IoffwSuXxcChoceykfZpaCUOkbqOnczzjW5oBQZCSxfLmyzLIPBg4PwxRfCPr5OSUUz3RW1CwNcBx6nTnEzDc6VygcPLsC0aVY68SV1xi23AM6t43//3WdDqdecC6aVZTQymD8/1rEtk7F49dVMOF/rczWDzU/YtGnTRhSQk4bDOcW8oAAouwo4NDQUcrmcZrtrSbWD7tjYWFy4cKHc/v3796NJkyYeGRRxLzg4GJ06FeO554QTxIICYMwYbiaU1F+LFwtfK5Us7r+/sNwxlDpG6jp3Kdc1vaA0aBAwcaJ438SJwIwZwvrUytqGmc1mMAwjyu5yVjboPneOC7idz2Nuv70Eb76ZAZ2ukGovkDpDJgO6dRO2KyqmRmrOXYYPAKxeHSEqnjZpkhmtWzM0g00qNWgQRBdnnFuHAdzfroiICBQWFlapiwe5OdUOuidNmoRnn30Wf/75JxiGQUZGBtasWYMXX3wRTz/9tDfGSJwolUoolUpMmZKLTp2E/Xv3AjNnGkW9HMue2JXt9UgnfnXH6dPAb78J26NGMWjfPo5Sx0i94421iIsWAbfeKk5/fecdroe32cwF+pUF3UqlskpFoy5cAHr3hqilT4cOXIVhvqUP1V4gdYlzcuOlS9zabh6ll3uGu4AnP1+K5cujHNvR0cA77yhpBptUiVYLdO4sbP/4Y/ljwsPDIZVKkZeXV3sDa6CqHXRPnz4dQ4cORa9evVBcXIzu3bvj8ccfx6RJkzB58mRvjJGUERwcDKNRjzVrWFHa17vvKvHnnxJH0R/n4kNlez1Steu6ZckS8faUKZQ6Ruonfi0i35pSqVTe9AWlkBBg714rnnhCPJu0ejUwcCBgMFTcq7uyyuV84HH5MovevYGMDOG2tm1LsWzZFQQGChWGqfYCqUuq0q+b3Bx3GT6ffRaFkhKhw8Fbb3GfZ4RUlXPrsPPnuX/OJBIJIiIikJ+fX2kXD3JzqhV022w27N27F9OmTcONGzfw119/4dChQ8jNzcVbb73lrTGSMkJCQmCz2RAbW4qlS4X9NhuDV15JgF4vvKzXrl1Damoq0t0s+qYZF/+n0wFffSVsd+pkwa23+m48hHibRqNBYmIiAKBRo0YeuaCkUgFTp+bg888NcM4S/+03YNiwCKSns25n6/iZbncYhkFWlhx9+0pF9TVatzbik0+uIDhY3NKHai+QuuT22wG1Wth2ta6bZrpvjqtMnrQ0Bb77TmgR1qoV8NhjtTkqUh8MGiTe3rat/DHh4eFgWZayYb2sWkG3VCpF//79odPpoFarcccdd6BTp04ICgry1viICwEBAZDJZNDr9Rg9Ghg9Wrjt+nUF3norzrFWkWXZCl8fmnHxfytXAs5tFJ94gqpMkvqPn/nx1DozPigYOdKG7dvFs0WnT8vw6KNNcexY+av8UqkUdru9wkD59GkpJkxIxpUrQvp5u3bA1q1maDT2csdT7QVSlygUQJcuwrbzTDf16fYMjUYDuVwOiUTiWDK2fHljUYvQefO4NfaEVEe7dkBCgrDtKsWc79Vts9koG9aLqp1e3q5dO1y6dMkbYyFVxDAMgoODUVTEtYv4+GMgIUE4Mf3551Bs2RIKgGsjERsb6/aEkWZc/Jvdzr2+PK3WgiFDKP2H1H8ymQxSqdRjFwadZ+J69+aquDZqJNyekyNHr14y7Nolvh9fPI3/rMzNBXbuBBYu5C54tm0L3HmnGunpwmdpq1bcMUlJgY7vhWovkLrMOcX83DkgK8t3Y6mP7HY7rFYroqOj0aZNG+TlpWDTJiElp3v38jOWhFQFw4h/d37/ncugdOapVp2kYtUOuufMmYMXX3wRP/74IzIzM1FUVCT6R2pHcHAwzGYzTCYTQkKAlSvNkMmEk8o5c2KRlqZwzKh4ozgR8b6ff+YKM/EeeigfKpXU/R0IqUeUSqXHZrqLi4sBAFevXkVqaioSE3U4eBBo3144pqiIwYAB3Fpvux1ITQUOHIjHRx9p8eCDSsTHc4Vp+vYFXnoJWLOGaw3mrHlzLmVdqwUMBgMAoHHjxlR7gdRpZdd18ynmVEjNM/h6OwEBAbDbgRdeEN++YIG4CjUh1eEcdFutwC+/iG/3ZKtO4l61g+4BAwbgn3/+wZAhQ9CoUSOEhYUhLCwMoaGhCAsL88YYiQtBQUFgGMZxoeOee4IwfXqx43aDQYo33miKgADuBI8vTsRXu+Yfg04A/dvChcLXcjmL4cPzISnbnJuQekqhUHjkj75Op0NmZiYAiFLngoN1+P13rr0Xz2LhWjCGhABt2sgxe3ZbfP65Fj/9xIgKpLnSs6cNu3YBsf+11C0pKYFUKnVbJImQuqJTJ8A5MY76dXsWf4FOpVLhyy+BAweE20aMgKhbDSHV1bu3uC5D2RRzT7fqJK5Ve3XI7t27vTEOUk0SiQRBQUHQ6/WIiuLaSTz1VDF++02CP//kUhr//luK2bO5apcAF3hrNBoAQHZ2Nm7cuAGLxeK29yzxrcOHgT17hO2RI22IjLRR0E0aDIVCgaKiIrAse1NrRytKnUtJ0eCnn4CRI4uwaZNwEdK5joI7cXHALbcArVtbcOutaRg2LA4BAQGO20tLS6FWq2ndK6nzVCqu9RAfbJetYE4z3TfHYDBAqVSisFCC6dOF/QEBwPz5vhsXqR9UKqBPH2DLFm77p58Amw2Q/pc4qdVqXRZcpmxYz6p20N2jbI6Rk+PHj9/MWEg1hYSE4Pr167BarZBKpSgt1WPxYgb9+weioIA75p13gH79gLvvFt83MjISeXl5uHHjBmL5aRniVxYsEG9Pncql/0illF5OGgalUgm73Q6bzeZoIVYTlaXOKRTA++8XIj7ejiVLQssdJ5WyaNmSwS23wPGvQwfgv+udMBptuHDBIAo8WJaFwWBwXBQlpK7r0UMIuk+eBG7cAAIC6IKSJxiNRgQEBGDGDO7nyvu//wOSknw3LlJ/DBokBN15ecCffwJdu3Lb/ITc9evXYbfboVKpoNVqKRvWw266DqJOp8OaNWuwfPly/PPPP7DZbJ4YF6mC4P+adOv1eqjVapjNZrRoocZnnwEPPcQdY7dzxX7++QcIDRXuK5VKERkZidzcXERGRtJst5+5cAHYsEHYHjQIaNHChqtXQTPdpMHgU9vMZnONg26j0eh2Fs45dU6hkGPKlBx07x6Kb78F4uOBNm0sCAu7irvuCkWjRpHVfl673Y7AwMAajZsQf9Ojh5A5B3DFCPv29d146guWZWE0GnHpUgQ+/VTY36IFMG2a78ZF6peBA8XbW7cKQTfABd56vR5msxlNmjSp3cE1EDU+e9+1axdGjx6N2NhYLF68GAMHDsSRI0c8OTZSCZlMBrVa7ShixzAMgoKCMHw4MGGCcFxaGvDUU0DZ886IiAgwDEPVCf3QokXcBRPe9OlwXNCioJs0FPw6s5qu6zaZTLhy5Yrbi4rOqXNyuRwWiwXDh7PYuBFYvBgYNcqANm2M0GgqXtfmqphUSUmJo2I5IfVBly7illV791IhNU8wGo3Q6Ri8+GKw6Dzt44/F6+gJuRnx8cBttwnbrlqHSaVSmjz1omqdvV+7dg1vv/02mjRpgkceeQRhYWGwWCzYsGED3n77bdx6663eGidxQy6XQ6/XIzs7GwzDQK/XAwA+/BBISRGOW7uWq7TrjJ/tLigogMViqcVRk4rk5HC9uXl33gl068a1FAEo6CYNh0QigVwur1EFc7PZjMuXL0MqlaJp06aiQpKuWncpFAqwLAur1Sp6DP62irgKPEpLSxEQEEDvV1JvqNVAx47Cdtl13aRmLl40Ydy4Jvj3X2Hp2MiR4gKPhHiCcxXzkyeBK1fEt0ulUtHfQOJZVT4bGDhwIFq3bo3Tp09j8eLFyMjIwOLFi705NlIJnU4nalxvt9sdzeyDgrgg23n579NPA5cvix8jIiICEomEZrv9yJIlgNEobE+fzrUKsdvtkEgkVJSJNCg1qWBusVhw+fJlSCQSJCcnQyaTQaPRICUlxW3rLn423PkCpNlshsViqTRwLht0syzrKKJGSH3iXNbn+HGgsJD7mma6a+bkSaBfv2BcuCBkxEREAO+958NBkXpr8GDx9rZt4m2pVAq73U7vZy+pctD966+/4vHHH8esWbNw3333UTEnP1BZM/tOnYBZs4T9ej3w6KNcjz6eVCpFREQEzXb7ieJiLujmNW8ODBnCfW2zUeVy0vBUt1c3H3ADQHJycpXrVfCz2a6C7qriT1QsFgusVisF3aTecQ66WRY4dIjOBWtq924uiy0zU/gZJiRwGQRxcT4cGKm3brsNiIkRtsummEulUrAs68isJJ5V5TP4ffv2Qa/X44477kDnzp2xZMkSmh31sao0s3/lFXHl8oMHgTlzxMfTbLf/+OILOCrPA1wRFf76lt1up4tdpMHhZ7qrcuXdarXiypUrsNvtSE5OrlZ/bIlEAolEIvpcNZlMVQr4y2aflPzXb4yCblLfdO0KOF/73b+fLgTXxLffAgMGAE7JimjfnjtHa9PGd+Mi9ZtEAtx3n7C9axc32cPjzzFpXbd3VPnTskuXLvj888+RmZmJSZMmYe3atYiPj4fdbseOHTsca4lJ7alKM3upFPj6a+C/bgAAgNmzgQMH4HSMsLa7JmsniWdYrVwBNZ5WC4wdK2zz6eWENCRKpRIsy1Y642yz2XDlyhVYrVY0btxY9DlYFQzDOIqpAdz7zWKxVGmmu2x6eWlpKZRK5U21OSPEH4WEiIsx7dvHnaRTOmrVsCzXDnTUKMD5dKtnTxt+/50rdkWINzmv6zabgZ07hW0Kur2r2mfwarUaEyZMwP79+3HixAlMmzYNc+fOhVarxRA+D5bUCndN68vuT0oCPvlE2LbbgUceEc+ohoeHQyKR4IZzg0hSq77/Hrh6Vdh+9lnAufAxpZeThoi/uFjRBUE+4LZYLDUKuJ2fiw+y+eerzky3c9BNs9ykvnJOMT92jEFJCf1dqgqbjfu7Pn26eP999xXip5/EkyOEeEufPoDznJ1zijkF3d51U5+ULVq0wPz583Ht2jV8++23nhoTqSKNRlNpRV7eyJHiWdO0NOCJJ4Q2YjTb7VssC8yfL2wHBnJt3pxRejlpiCprG2a323H16lWYTCYkJyffVIsu50rp/PNV5/OQZVnYbDaYTCYKukm95Rx022wM/vmHftcrYzAAI0ZwrQidTZ6sx8KFOQgIoL/tpHYEBQG9egnb27YJLWop6PYuj1yelEqlGDp0KLZs2eKJhyPVUFlFXmdLlojbiG3YAHz2mbDNz3bT2u7at3MnVwmW97//AWFh4mMovZw0RAzDQKFQuAx++YDbaDQiOTkZAQEBN/Vc/Ew3y7IwmUyOSq5VGSMgVC0HaD03qb+6deM6avCOHFFTenkF8vKAvn2BjRuFfQzDnZM9/3wuAgNv7nOLkOpyrmKelQUcPcp9TUG3d9EZfAMSHMz163Yu5vvcc1zLCoBmu33JeZZbJuNel7IovZw0VK4qmPMtEktLS5GYmOiRIFcul8Nutztmq6taiM25kFpJSQlkMlm1irgRUpeEhXFFv3hHjgT6bjB+LiODK2b7xx/CPpWKC8CffpqFwWC46YuFhFSXczE1QEgxZxgGEomEgm4voTP4Bub224F584Rto5FLPf9vcgYRERGQSqU0212Ljh4VF7J45BEgMbH8cZReThqqsr26WZbFtWvXUFxcjMTERAQFBXnkeZx7dVcn6Aa4kxXn/txlK5oTUp84p5ifOBGA0lKa6S4rLQ3o3h04c0bYFx4O/PYbMHQoHF0ZbmZJDCE1kZwMtG0rbG/dKnwtlUop6PYSnwbd7777Ljp27Ijg4GBotVoMHToU586dEx1TXFyMyZMno1GjRggICECrVq2wbNky0TEmkwlTpkxBZGQkAgMDMWTIEFy7dq02v5U65bnngIEDhe1Tp4AXXuC+lkgkiIqKotnuWrRwoXj7xRddH0fp5aSh4me6WZYFy7K4fv06ioqKkJCQgODgYI89j3PRtpoE3Xa7HQaDgVLLSb3nHHRbrRIcPkwXhJ1dvMgF3BcvCvuSk7nOMV27ctsGgwEAaKab+IRzFfOjR4Hr17mvKej2nmqdwVssFjz22GO4dOmSR5587969eOaZZ3Do0CHs2LEDVqsV/fr1c/Q4BYDnn38e27dvx+rVq3HmzBk8//zzmDJlCjZv3uw45rnnnsOmTZuwdu1a7N+/H8XFxRg0aBD90rjBMMCqVUBsrLDv00+5Nd4At7ZbJpMhJyfHJ+NrSC5fBtatE7YHDBCn7fH4Ak0UdJOGiK8ofvr0aZw5cwaFhYVISEiosIZFTUilUjAMg9LSUrAsW+0q6AaDASzLUtBN6r277xZv799PQTfv4kXuooRzN5LmzYF9+4AWLYR9RqMRCoWCMtiITzgH3QDw00/c/xR0e0+1zuDlcjk2bdrksSffvn07xo8fjzZt2qBDhw5YuXIl0tLS8PfffzuOOXjwIMaNG4eePXsiOTkZ//vf/9ChQwccOXIEAKDT6bBixQq899576NOnD2699VasXr0aJ06cwE7nnF0iEhUFrFkjLoYycSJw5Qo32x0ZGYnCwkK3FYOJZ7z/PtdGhFe2lQiPL1JDf5xJQ6PT6RzLXViWrVJhs5rii7bp9XoAqPZMd0lJCRiGoZkrUu9FRQGtWwvb+/fXzwvCOp0OqampOHXqFFJTU6HT6So8PisL6NdPmDUEgDZtgL17gUaNxMfSem7iS3feCURECNv8um6ZTEZBt5fIqnuHYcOG4YcffsALfD6yB/EfZuHh4Y593bp1w5YtWzBhwgTExcVhz549OH/+PD788EMAwN9//w2LxYJ+/fo57hMXF4e2bdviwIED6N+/f7nnMZlMomCyqKgIADebws+oeBr/uN56/Jro1g14+WUJ5s7lAjmdDnjkETt++82G4OBg5ObmIjs7G7HOU+LEreq+xjduAMuXywBwVz5uv92Ou+6ywdXdrVYrAC7o8KffoYbKH9/P9VV2drbL/Tk5OV6ZUZZKpSgtLXWs0Qaq/jrbbDao1WrH+5XUDfR+rpm775bg9Gnu/OHwYSmKiy2oZnJIranJa6zX65GRkeHYNplMSE9Ph81mc7msRacDBgyQ4dIlYTajQwcWP/9sRUQERH/bWZYrohYYGEi/dx5G7+eqGzBAijVruAtmO3eyKCri/nZZrVa//vn522tc1XEwbDX7PMyZMwcLFy7EPffcg9tvvx2BgeKqlVOnTq3OwzmwLIv7778fBQUF2Ldvn2O/2WzGE088ga+++goymQwSiQTLly/HmDFjAADffPMNHnvssXIzsv369UPjxo3x6aeflnuumTNnYtasWeX2f/PNNw0uLdBmYzBjxl04e1a43DV8+HmMHn0GGo0GERERSEtLo5NIL/juu+b49ttWju2XXjqMu+7KcHmsTCZDUlISrl+/DqPRWFtDJMTnGjdu7HJZhd1ux+XLlz3+fJGRkdBoNDCZTNWqDZKYmAi5XI78/HwUFBR4fFyE+Jt9++Lx3nt3OLbfeWcfWrfO9+GIPKtRo0ZQKBSioogsy8JsNpf7bDCbJZg9+06cPBnl2Bcfr8e77+5HSEj5+jhyuRyJiYnIyMhwrO0mpLbt3x+HhQs7Orb/7/8Ool8/K4KCgpCWlubDkdUtpaWlGDVqFHQ6XYXL3qoddDdu3Nj9gzFMjdd7P/PMM9i2bRv279+PRk45OAsXLsTnn3+OhQsXIikpCb///jteffVVbNq0CX369HEbdPft2xdNmzbFJ598Uu65XM10JyQk4MaNGx5fI8izWCzYsWMH+vbt66iQ6y+uXgU6dpShsJD7w8IwLLZvt6FHDxsuXbqEwMBAmu2uguq8xqWlQEqKDDducD/zJk1YnDplhbvscaPRiKtXryIpKYkqnfoBf34/1zeXL192WdRRqVQiOTnZ48+XkZEhSi9PS0tD165dK3ydnWfEZDIZtFqtRwu8Ee+i93PNZGYCSUnCz+vNN22YMcN7yz9uRk1e4/Pnz7vsP84wDJo3b+7YttmARx6R4ocfhIuD8fEs9uyxIinJ9WMXFRUhMzMTKSkptGzMw+j9XHWFhUBcnAxWK3cuOmmSDbNm3UBeXh6aNWvm28FVwN9e46KiIkRGRlYadFc7vdwbMwtTpkzBli1b8Pvvv4sCboPBgNdeew2bNm3Cff81lWvfvj2OHz+OhQsXok+fPoiJiYHZbEZBQQHCwsIc983JyUFXvkRkGUql0mWBHLlc7vUXrzaeo7pSUoDly4Hhw7ltlmUwfrwM//zDnTxmZmYiOjq62kWFGqqqvMZr1nDp5bxp0xioVO7vwwcdCoXC735/GjJ/fD/XN9HR0UhPT3e539M/e51O5wi4Ae59FxMTA6PR6DYLSqfTiVJQrVYrMjIykJCQAI1G49HxEe+i93P1JCYCLVuyOHuWO2H/5RcpZs707wCyOq9x2VaFPKVS6XgMlgWmTAF++EG4PTQU2L6dQUpKxX/T5XI5XUT3Ino/Vy4qiiuKuHs3t/3TT1K8844CdrsdMpnM71tf+strXNUx1Ljyhdlsxrlz524q7ZhlWUyePBkbN27Erl27ys2i82usy6YWSqVSRzGd22+/HXK5HDt27HDcnpmZiZMnT7oNukl5Dz4ITJokbGdmAuPHAxpNGGQyGfXt9iCbDXjvPWE7MpL7WVd8H66oBVUvJw2NRqNBQkICVCoVGIaBSqVCYmKiV7KSXHVsYFkWeXl51boPAPrMJA3CvfcKM8F//gnUp1/7yMhIl/u1Wq3j65kzue4vPJWKK0jl3APZFSqiRvyFcxXz9HTg7FkugKRiap5X7TP40tJSTJw4EWq1Gm3atHHk/E+dOhVz586t1mM988wzWL16Nb755hsEBwcjKysLWVlZjvUtISEh6NGjB1566SXs2bMHly9fxqpVq/DVV19h2LBhALgTsokTJ2LatGn47bffcOzYMYwePRrt2rVDnz59qvvtNWjvvy/+Q/HTT8DixVzfbqpk7jkbNwLOqzCmTAEqKyXAX2SiNDTSEGk0GqSkpKBNmzZISUnx2jIgV2nsDMO43F/RfQDQ5yVpEAYOFIJulgV+/tmHg/EwPrWcz/KTSCSiC35LlwKzZwvHS6XA998Dd91V+eMajUYKuolfGDxYvP3rr1zXDgq6Pa/aQferr76Kf/75B3v27BGlxfTp0wffffddtR5r2bJl0Ol06NmzJ2JjYx3/nB9n7dq16NixIx599FG0bt0ac+fOxZw5c/Dkk086jnn//fcxdOhQjBgxAnfddRfUajW2bt1KAUo1BQQAa9dy//Nefhm4dCmM+nZ7CMsC8+YJ22o18Mwzld+PD7r9PdWHkLrMVYswlmUrbB3m7jZajkMagm7dgKAg4eR82zYfDsbD8vPzERwcjGbNmiEyMhIMwzhqNaxbB0yeLD5++fLyvY9dMZvNsNvtFHQTv9CsGddHnvfzz9zKYwq6Pa/aQfcPP/yAJUuWoFu3bqIAoHXr1rh48WK1HotlWZf/xjvl2sbExGDlypW4fv06DAYDzp49ixdeeEH03CqVCosXL0ZeXh5KS0uxdetWJCQkVPdbI+D6SX7wgbBtsQCjRkmgUkVBp9PR7M1N2rMHcGpDj4kTxX0S3bHZbJBIJBR0E+JFzmmjPIZhEFHBm9TVfSraT0h9olAw6Nq12LG9fTtctr2sawwGA4xGo6NWUHBwMGw2G4xGI377DRg9mruIzps7t/JlYs6PDYDWcxO/4Xyx6PBhBnl5Ugq6vaDaQXdubq7Lk4mSkhIKCOqJJ54AHnpI2L5wAfi//wuHXC6/qdlunU6H1NRUnDp1CqmpqY6+7A3J/PnC11IpUNV293a7nTI3CPGysuvHlUolsrKyKqxEXptrzgnxR927C8UHi4qAP/7w4WA8pKCgADKZzPHeDwgIgEQiwf79BgwdKr6w8PzzwPTpVX9so9EIuVyO/2/vvuObqvo/gH9uZnc6oAtKi1Q2KJsyLChLVKyioo+KKPqoLEHE53E9KIKACwV/igNRfBRxoKgoiFBGWSrjYe/RIi0F2qY78/z+iEmazqQkTZt83q9XX3DPvbn30MNN8r3nnO9RKFzOZUzkERWDbiEkZGSEMuj2AJeD7l69emF1hfFD1kD7ww8/REpKivtqRl4jScAHH8BhqYvPP5ewfn0LaLXaeq0TrdVqkZWVBZ1OByEEdDodsrKy/Crw3rfP0gtgdeedgLMrHpnNZiZRI2oAFeePJyUloaSkxKXXeHLOOVFjI0kSBgwogiTZu31/+smLFXIDs9mMgoICRERE2L7jymQy5OZqcPfdGhTbO/Zx333A669bvjc5i0nUqLEZMACo+LH1xx/BDLo9wOVv8XPnzsVzzz2Hxx9/HEajEW+//TaGDh2KTz75BHPmzPFEHckLwsOB5cvhsG70008H49y5oHpl5WWGX+C11xy3Z8xw/rXW4eVERESNSVSUCd27+8687sLCQpjNZoSHh9vKsrOBBx6IRV6e/UvRiBHAxx8Drnw0CyFQVlbGoeXUqCiVlsDb6o8/Qhh0e4DL3+L79euHrVu3orS0FG3atMGvv/6KmJgYbN++HT169PBEHclLUlIcM3OWlEj4179a4eLFQpd7u/09w29mpiVJndWQIUD37s6/nsPLiYiosRo2zP4Zf+QI4GKKn0YlLy8PwcHBtmSIBQWWADsz0/4Z3KcP8M03lmDFFUyiRo3VoEH2v58/r8TZs16ris+qV9dZly5d8Omnn+LAgQM4dOgQ/vvf/6JLly7urhs1Av/6F3DDDfbtffsUWLgwzuW53f6e4fett4CKS9q7Mv8L4PByIiJqfKzDr4cNc8ye1lR7u3U6HUpLS20J1MrKgFtvtUwPs0pONmD1aiA42PXzWzssGHRTY5Oa6ri9dStzDriby9/i5XJ5tQHX5cuX2RPng+Ry4LPPgObN7WWffhqJn34yu9Tb7c8ZfvPzLXPkra691tLT7QoOLyciosaqSxcT4uPt20016M7Pz4dcLkdYWBh0OuCuu4DNm+374+JM+OCDTERGippPUouysjImUaNGqXt3ICTEvr1tW81LZVL9uPwtXojq32h0Ol2ta5lS0xUXB3z6qWPZ88+3xL59l50+h0ajQVxcnG3bnzL8vvceUDEX09NPu5Z0BeDwciIiapwsvd0CI0fayzZuhEPCsaZACIH8/HyEh4fDYJDhjjsck8JFRADff1+G5s3LapwyVxfO56bGSqFwnNe9c6d/jERtSE4/alu4cCEAy5vrRx99hJAKj0NMJhM2b96M9u3bu7+G1CjceKNleas337Rs5+crMGmSBhs2lCEkxLlhUtbhVOHh4WjZsqWnqtqolJcDb79t305MdFyOzVkcXk5ERI3ZzTcDH31k+bteD/z2G5CW5tUquaSoqAgmkwlBQRFVAu7gYMt2jx6BOHJEQnFxscvT44QQKC8vR1RUlJtrTuQeqan2VXYyM5XIygISErxbJ1/idNC9YMECAJY3jcWLFzv0uqlUKiQlJWHx4sXuryE1GnPnAps2Abt2Wbb/+CMEL75YgNdfdy7oNv49qbmm0RK+aNkyoOJsjCeftDxNdBWHlxMRUWN2ww2ASmUJuAHLEPOmFHTn5eVBJgvEffcFVAm4f/kF6NcPAOQICgpCcXGxy8GzwWCAyWTifG5qtCrP616xIgePPBIIjUbjnQr5GKe//p8+fRoAMHjwYKxcudKWZIL8h0plycDdrZt92Nhbb2kwcqQO119f9xNffwu6TSbL+p1WkZHA+PGun0cIweHlRETUKEmSBCEEQkKAwYOBtWst5atXA0K4Pp3KG/R6PfLySvDss1fb6g/YA+6BA+1lISEhyM3NdXkEWllZGQBweDk1WldfrUVgYCjKyiz/r3fsUGHEiCwAYODtBi53naWnpzPg9mPJyUDFAQ0mk4SxY+XIz6/7tdY1//wl6P7hB+D4cfv2xIn1y3Zq/X2xp5uIiBoTrVYLs9mMnJwcHD9+HNdfX2bbl50N7Nnjxcq54MKFAjz5ZCusXWvPTVRdwA1Ygm4hBEpLS126RllZGRQKBZSurjNG1EDy83Nx7bX2/9d//mn50nrx4kVvVcmn1Ct94rlz5/DDDz8gMzOzSjKJN62Tfsln3XsvsG6dPbnaX38p8OCDJnz3nbzWJ9r+1NMtBDB/vn07IACYNKl+57I+rGDQTUREjYVWq0VWVpZtW6fToUuXTADtbGWrV1uyIjdm5eUC998fhE2b7LmKagq4AUtPtUKhQHFxsUN+o7qvU86h5dSo6fV69OpVgu3bLf+vz55VIzdXgZgYncNxWq0Wubm50Ov1UKlUiI6OZk+4E1wOutevX49Ro0ahdevWOHr0KDp37owzZ85ACIHujf2dldzmnXeA7duBY8cs26tWyfH++8Bjj9X8Gn8KujMygJ077dsPPgjUd3U0s9kMABxeTkREjUZ1y8cmJBjQpo0eJ09aeox/+gl44YWGrpnzdDogLc3kdMANWIbTh4SEoNiF9OxCCJSVlTGJGjVqKpUKPXqUOJTt3h2EtDR7B2t1D9us2wy8a+dy19kzzzyD6dOn48CBAwgICMC3336LrKwspKam4s76pGWmJikkxDK/u+IqcdOmCRw4UPNr/Gl4+auv2v8uSZYEavVlDbrZ001ERI1FTctmDRxYaPv7H384JhNtTHQ6YPRoYO1ae/9TXQG3VUhICMrLy2EwGJy6ljWJGudzU2MWHR2Nzp3LoFKZbWV79gQjukKvUXUP2wAOQXeGy9/iDx8+jAceeAAAoFAoUFZWhpCQEMyaNQvzK46nJZ/XrZtjcFleLmHMGKCmaU7+0tN98KDjUiOjR1vmwtcXh5cTEVFjo6r41L2CIUPsQ1GFAH7+uaFq5DxrwL16tb3M2YAbgG1YubO93eXl5QDA4eXUqGk0GrRp0xJdutjv4QMHwhEWFmbbrulhm06nq7ac7Fz+Fh8cHGz7xcbHx+PkyZO2fZcuXXJfzahJmDLFsjan1aFDwNSp1R/rL0H3ggWOw8Cffrr+59Jqtfjrr78AAJmZmdBqtVdSNSIiIreIrmHO1IgRoag4yvSHHxqoQk7KyAB6964ccAunA27A0ukUEBDgdNDNJGrUVGg0Ggwdan84dOCAHIX2wSs1Pmxzdd16f+Ry0N23b19s3boVAHDTTTdh+vTpmDNnDh566CH07dvX7RWkxk2SgKVLgfh4eyD94YfA1187HieEaNLDy7VaLY4fP46DBw/i+PHjNQa/ly8HYPlyeza5QYOAXr3qf82srCzb8DXrvBkG3kRE5G0ajQYJCQm2IdOSJKFVq1aIigrDyJH249auBf7u6PWq/Hw1HnpIjoEDgX377OWBgWZ8/XWJ0wG3VWhoKIqLi+v8TqPVanH58mUYjcZavz8QNRYDBtj/bjYDO3bYt2t62FZTOdm5HHS/+eab6NOnDwDgxRdfxNChQ7FixQokJiZiyZIlbq8gNX7NmgGffy5BkuwfPI88Apw5Yz/GbDZDCAGFQtHkgm5r8KvT6SCEqDX4/eqrtjAY7EH3lfRyc94MERE1ZhqNBsnJyWjVqhWEELae3FGj7MeUlgLr13upggDOngWmTpXh0UeH4r//dfzaGxZmxHvvnUFCwhmXg+GQkBCYTCbb0PHqWL8/WHOz8OE5NQX9+sHhO31Ghn2f9WGb9PdyRSqVCq1atXIYgk7Vczrofv7557FhwwbEx8eja9euAICgoCC8++672LdvH1auXInExESPVZQat0GDgOees29rtcA99wDWHCPWXm6lUtnkgm5ng98DB4B165Js2127AiNG1P+6nDdDRERNQWhoKBQKBfLz8wEAN94IVBxJvWpVw9fp1CnLyiHJycC778qh1ztO/br11nz88MNx9OhhSUTj6gPtoKAgyGQyFBUV1XgMH55TUxQRAbRrZ08SuGWL436NRmPLMxQXF8eA20lOB93Lly/HkCFDEB4ejtTUVLz44ovYvHlzjYEB+Z+ZMyWkpBht2zt2AM8+ewlardY2n1uhqNfS8F7lbPD7zDNymM32Xu7XX0et65bXpaa5X5w3Q0REjYkkSYiIiEBBQQFMJhM0GsvDeKsff7QMU20IWVnAo48C7doBn3wCGI2O+9u1K8OyZacwe/ZfiIoy2cpdfaAtSRKCg4NrndfNh+fUVPXubQ+6d+4EKv5Xrjhl1NkM/uRC0H3y5ElkZWXhww8/RHJyMj777DMMGjQIERERGDJkCObMmYNt27Z5sq7UyCkUwAcflCIszP4Jt3hxBPbtO4/Cv7MwNMWebmeSRqxZA6xda7+dRo4Ehg6t/zXNtXw74bwZIiJqbCIiImA2m22f97feat+XkwP8/rtnr5+TAzzxhKVn+4MPqgbbycn5WLHCiFWrzqFbt6rLrNTngXZoaChKS0ttAUhlTDpFTVXfvvYbqKwM2LPHvq/id1Rj5RuNauTSnO4WLVrg/vvvx5IlS3Dy5EmcPXsW7733Hlq1aoVXX30V1113nafqSU2EWn0B06ZdsG0XF8vxwQfNUVBQAABNck53XUkjjEbgqafs5XK5wGuv1f96QgicP38eBoMBMTExCAgIgCRJCAgI4LwZIiJqlFQqFUJCQpCXlwfAcV43cOVDzPV64ORJID3d0oM9axYwfjwwZAjQti3QqhWwcKFjjxwA9O8P/PyzEa+9thm33SYQG+u+RFDWpcNKSkpcOicfnlNj16+fY+dPxXndFR8ysafbefUe63vy5Els3LgRGzZswMaNG2EymTB48GB31o2aIL1ej7Q0HT77LAqnTlkymn75ZST+8Y88JCbKIJPJ3Bp0a7Va5ObmQq/XQ6VSITo6GpqKa5W4gfV858+ft73RRERE2ILfJUssa3NbPfKIGR07yqucx1l5eXkoKChAixYtEBERgebNm9e/8kRERA0kIiICWVlZKC8vR0JCALp3B3bvtuxbtQqYO7fm12q1lqRnZ88CmZmOf549a+nJduXrQ8+ewOzZwLBhgNEobOuFazQaCCFw7tw5AEBAQACio6Pr9UBbpVJBpVKhqKio2tdrNBpcvHgRer0eQgio1ep6X4uoISUlyRAbq0dOjmW0RkYGMH26ZZ+1p1uhULCn2wVOB92nT59Geno60tPTsXHjRmi1WvTv3x+pqamYNGkSevXq1STn65J7qVQqCKHDk09ewKRJlsR6RqMMCxfG4u23cyBJktuCbmtWUCtrVlAAHgm8i4qKoNfrIZfLUVZWBiEEiookvPCC/bigIMPf2/ULuktKSpCdnY2oqChERES4pe5EREQNITQ0FHK5HPn5+YiLi8Ott9qD7sOHgc8+syRYqy6wrrgW8JXo0gV4+WVLT3tNeVWCg4MBAImJiQgNDb2i64WEhKCoqAhCCFtG54rMZjMiIiIQFxd3RdchakgKhQLdupXil1/sQbcQlnvK2gGlVqvZ0+0Cp6PkNm3aoFWrVpgwYQKmTJmC7t27Qy6vf28e+abo6GhkZWXhuuuK0LNnCf780/LBtmZNGA4cKMKgQe4LumvLCuruoBuwfHDKZDJERkbi7NmzKC0txdy5waiYhPTOO4+hefO29Tq/Xq9HZmYmgoODERsb66ZaExERNQyZTIaIiAjk5eUhJiYGo0bJMHOmff/Yse68FhAfDyQmWn5atQL69gVuucWyrzbWnjpZXQc6ITQ0FHl5edDr9VXmagshqi0nauwUCgV69NDil1/CAQCXLgFHjwLt2zsG3Vz+znlOB9133nknNm/ejLlz5yIjIwOpqakYPHgwunXrVu2TPfJP1mA3NzcXTz6Zg3/8o41t3/z5URg0qAwAanwi7IqGzgpqrXNISAhUKhX27i3AggXBtv2tWwvcdNMpAK4H3WazGZmZmZDJZA7rHxIRETUlERERuHTpEo4dOwaFwoQWLdrir7+qX42jNoGB9mC6YmBt/bNFC8dlyVxhDRrcEXQHBwdDkiQUFxdXCa6t31NqSqhG1FhZerodcxVkZDgG3QEBAcjLy7N1SlHtnA66V6xYAQA4cuSIbYj5a6+9hvLycgwYMACpqakYNGgQevXq5bHKUtOg0Wig0WggSSdwyy2l+PHHIADA778HYM0aI7p2dU/QrVKpqg2wPfVE2Ww2Q6FQQJIkREVFYepUOSpefvZsE1Qq19dEsSZO0+l0uOqqqzhNg4iImqzy8nIA9qzGQ4cW4JNPquYmad7cMYiuHGBHRTm/7Kar+V2sPd3uGLEpk8kQFBSEoqIiREVFOexj0E1NlUwmw9VX6xEWZkZhoSWgzsgAHn7YEnRLkmRb2tZoNPL/uBNc/nbfvn17tG/fHo8//jgA4NChQ/jiiy8we/ZsPPPMM5xQTzbBwcGYNCkba9ZcBYPB8sn50kuBWLECbhlibh3KXl25J1R8knfkSDh++cX+YZ2SAtxxh8Avv7h+3suXL6OgoAAtW7ZEYGCgu6pLRETU4CpP/frnPy/i0iUlCgpUuO++IKSmWoLroCD3XK8++V3c2dMNWOZ15+bmVunx0+l0DsEJUVNh+X8rR69eBqxfb+nMsmYwN5vNkMvlDLpdVK8utQsXLmDjxo3YuHEj0tPTcezYMajVagwcONDd9aMmLDg4GPHxl/Hooya8847lv9qxY3J8910EOne+8qC7clZxtVqNmJgYj2UFNZvNfyeCA2bMcHw6/uabzj+Rr6i4uBg5OTmIiopCeHi4eypKRETkJZWnfoWGmjF37jlIkoROnTq59Vpmsxk5OTnV7qstv4s7e7oBy7zuCxcuoLS01LaMGABbzzunjFFTpFAo0KtXuS3oPnkSyM4GABPkcrltZCaTqTnH6Ud8X3/9NSZMmICOHTsiPj4eY8eOxYEDB3DXXXdh/fr1KCgoQHp6uifrSk2MNTvo5MlahIba1/R7991oFBW5J5maRqOxBatt2rTx6DIcQgjIZDJ8/TWwfbu9fPRoPfr2df18er0eWVlZTJxGREQ+o6YeL3dN/TIajcjPz0dmZiaOHDlS4xf+2vK7WB+iuysYVqvVUCgUKC4urlIHJlGjpsqSTK3coWzrVstIEblcDrlcDkmSOMrZSU4H3ffeey/27t2L2267DWvXrkVBQQG2bNmCWbNmYfDgwXxToSrkcjkCAwMhlxdg/Hh7iu9Ll5R4+233PfW1DlW3Prn2FLPZDL1ehn/9y16mUglMnnze5eHyTJxGRES+qKYpXlcy9Uun0+HixYs4deoUjhw5gr/++gsGgwHNmjWrV5BvDRrcxZpktaioyKHc2tNN1BQpFAp06lSKiv+FMzLs909hYSGEEMjOzsbx48eZybwOTg8vz8/Pt/VcEjkrODgYly5dwr33luPrr6Px11+W5zwLFsgxZQoQGXnl17AGvO5aiqwmZrMZS5YE48wZe9nkyXpERRWjrKzM6TlbQgj89ddfTJxGREQ+p/LUr4CAAERHR7s0Ek0IgdLSUhQWFqKoqAh6vd4W2MbHxyM0NNT2matWq13O7+KJbMshISEoKCiAwWCAUqmE2WyGwWBgpxQ1WQqFAnJ5KXr1svRwA8CWLcCUKZbRq67mUvB3Tr/jMOCm+rD24AYECDz+uD25SmGhhGefzXPLU7GGCrovX5ZhwQJ7orPoaOCFF1RQqVS4fPmyC+e5DK1Wy8RpRETkkzQaDaKjoyFJktNTv0wmky0p2pEjR3D69GlotVoEBwejVatW6NChAxITExEZGenwkFuj0SAhIcH2ADsgIACtWrWq9Zru7ukGYJvLbR1izszl1NTJ5XIYjUYMGGAv27sXKCwUNU7fuHjxYrXlVM9EakTO0Gq1DjffyJGX8MEHEcjMtDz1XbYsHHfffRTdurnnqZgnh5cLIfB//9ccRUX251QvvwxoNBIMhkjk5OSgWbNmdZ7HmjitWbNmfBJIREQ+S6lUQggBo9GI0tLSapf00uv1KCoqQmFhIUpLSyGEQEBAACIjIxEaGorAwECnpl9pNBqYzWb89ddfuOqqq+rsxfZET7dCoUBgYCCKi4sRERFhC7rZ001NlUKhgNlsRr9+Zlj7ac1mYPduFXr3Lqv2NbXlUvB3XMmcPKbysiFKJRx6u8vKZFiypPkVPxVriJ7ugwfN+OYb+1j4zp2Bhx6y/D0iIgIymQwFBQW1nsOaOC0kJAQxMTEeqysREZG3WXujCwoKkJWVBZ1OByGEbRjq0aNHcezYMVv28djYWLRt2xbJycmIiYlBUFCQS/lOrNdzJpOyJ3q6AUtvd3Fxse3fKZPJPHIdooZgHT3Su7djorQ//wyocWokHzLVjEE3eUzlZUMA4MYbtUhOtmdC/OqrSJw9axlSdvz4cRw8eNDlZAwNkUht7lwJJpP9w/+NNwDr+41cLkd4eHitQbc1cZpcLmfiNCIi8nnWYdV5eXnV7jeZTEhISED79u3RunVrREVFXdFQbFeCbk/0dAOWoNtkMqGsrIzLhVGTZw2sNRoTKq72t3t3YI3TN64kYaKvY9BNHlPdh6dcDkycaO/t1utl+PDDmGqfgrs639tTPd1nzwIrVtg/NG+4ARg2zPGYyMhImEwmh/U5K9br3Llz0Ov1aNWqFZ96ExGRz5PJZJDJZDUGwUIIaDQat30mWoNuZ5YvMplMHgm6g4KCIJPJUFxczOXCqMmzBt1GoxEDB9rL9+0LgkoVjISEBNt3fZVKVWcuBX/n8jtOSUkJXnjhBfTr1w/Jycm46qqrHH6IrGp62nXDDYXo0ME+F+TbbzXIyqqa+dvZYeee7ulesAAOvdzPPFP1mICAAAQFBVU7T/vSpUsoLCxEixYtEBAQ4JE6EhERNSaSJEGpVNYYVLs7ILUO5Xa2p9sTD8CtGdaLi4u5XBg1edZ7pHIytbIyGQ4cUEKj0dhiv9jYWAbcdXA5kdrDDz+MTZs24f7770dcXByHzVCNrAHoxYsXbU98rR9GkydfwIQJSQAAo1HC4sXRmDPnL4fXO5uMwZNzui9fBj780L597bVmXH999c+qIiIiUFpa6rB8WFFRES5cuIDmzZszcRoREfkVpVIJSZJgMpmq7PPEMFSFQuH0nG5P9HQDliHm58+fB8D5rdS0WUerVA66AWDnTiUGDbIE5pIkOXXf+TuXg+5ffvkFq1evRv/+/T1RH/IxGo2m2mDTbD6Obt1KsGePZSm61avD8eijF9GqlX0euLMfVp4Mut97DygttW9Pn26CJFX/QR0cHAyDwYCCggKEhYXZhsmHhoZyjgsREfkdlUoFo9GIhIQEZGdnw2g01mvdbmcplco6v/wLITzW0209v1Vubi4kSeJDd2qyFAoFjEYjWrUCWrYEzp2zlG/fbrl/rCNaqsvjRI5cfswXERGByMjIug8kqoXBoHfIZG4ySfjgg+YOx7gaqLp7eHlZGbBwoX27ZUs9Ro+u+XhJklBWVobCwkIcPHgQJ06cgEwmQ8uWLTkihIiI/I71y7hGo0F4eDhUKhWSk5M9NgxVqVTWOafb+l3BEz3dWq0W2dnZtm3rqiWu5qghaiwUCgVMJhMkCQ693du2SbA+X3LmYRfVI+h++eWX8Z///AelFbv/iFykUqnQt28JunUrsZX99FM4srJUUCgULiVj8ERPd3k58J//ABWnlT/wwCUolTUHz0VFRbY6CyFs65MWFxe7rV5ERERNhVKphNlshslk8tgyXZWvV9eXf2vQ7Ym6VF4q1epKl0Yl8hZrTzfgGHRfvCjh+HHL3xl0O8floPuNN97A2rVrERMTgy5duqB79+4OP0TOiI6OhiShSm/3Rx/FIDg42KWn4O5MpKbTAe++CyQnA6+/bi+PijLj1lvza30yfunSpWoDf37YEhGRP7ImEjMYDA0SdFsDhNoewnuyp7umIbbO5qghamwqBt0VM5gDQEaG5U8G3c5xeU53WlqaB6pB/sY6v0mtvugwt3vVqjBMmJCPhATXz3klPd16PfDJJ8Ds2UBWVtX906aVITBQ1DpM3GAwVLufH7ZEROSPrElF9Xo9TCaTbQkiT1/PYDDUmDncmtTNEw8AVCpVtZ/5TKhGTZVcLrcF3Z06AWFhZhQWWh5YZWQADz1kn9YhRO3fk/2dy+9+M2fO9EQ9yA9Zk6y9+iowdKilzGSS8M47GgwebHb6KfSVDC83GIDPPgNefhk4c6bq/mbNgBdeAO65pwwXL8pqfTNRKpXQ6XRVjuGHLRER+SOFQmHLbGwymTz+eVhxre6agm5P9nRHR0cjq5on90ymSk1VxdEjcrmEnj312LDBsvztli2WY5x52EX1GF4OAAUFBfjoo4/wzDPPIC8vDwCwe/du/PXXX3W8kqiqG24AKibD//HHcBw+7HwWxPoMLzcagWXLgA4dgPHjqwbckZHA3LnA6dPAlCkAUPfTu2bNmlV7DD9siYjIH0mSZFvGq6HmdAOodairJ3u6NRoNEhISEBAQAEmSEBAQ4FKOGqLGxjo6xfodu2fPctu+EyeAnBzn7juqR0/3vn37MGTIEGg0Gpw5cwaPPPIIIiMj8d133+Hs2bNYtmyZJ+pJPkySgBdfdOztfuUVCZ9/7tzrXe3pPnAAGD0aOHas6r7wcOCpp4DJk4GKn5Fmc90976GhocjJyUFiYiL0ej3UarXHlkUhIiJqClQqlW14uafWxrayritc25d/T/Z0AzUvlUrUFFmDbqPRCLlcju7dywCE2/Zv3QqkpTHodobL7zhPPvkkxo0bh+PHjyMgIMBWfuONN2Lz5s1urRz5j8q93StWqHDypGvncKanu7wcGDWqasAdFmYJ/M+cAZ57zjHgtp7bmQ/okpISJCUloVOnTh5dFoWIiKgpsCZZ8uTa2FYVe9ZrYln+SOLcUyInVAy6AaBz5zIolfZOrowMy6gRuVzOoLsOLgfdf/zxBx599NEq5S1atEBOTo5bKkX+x9rbbWUySZgzx7nXutLT/cYbliHjVqGhljnbZ84AM2cCNT2cZnIIIiIi1ymVSpSXW4akejrotl6vrp7uhqgHkS+w3ivWoFulMuGaa+z3V8V53Qy6a+dy0B0QEIDCwsIq5UePHkXz5s3dUinyT5V7u5ctA06dqvt1zs7pPncOeOUV+3ZMjGU+yqxZQERE7ddwtqebiIiI7FQqle1zuqGCbmuAUJ2GGOZO5CsqB90mkwl9+9qD6z17gKIiBt3OcPld59Zbb8WsWbNsv1hJkpCZmYl///vfGD16tNsrSP6jam83nOrtdran+1//AkpL7dvz5gHO5jhj0E1EROQ6a5IlgD3dRE2NdcpGxaC7Xz+Tbb/ZDGzbxqDbGS5HEa+//jouXryI6OholJWVITU1FcnJyQgNDcUcZ8cDE9XghhuAlBR7j/Wnn1a/lFd1agu6MzKAL76wb/fuDYwd63y9zGYzh5cTERG5qKGDbuuc7pq+E7Cnm8g1CoUCJpMJZrMZQgikpJhR8Svx5s2W+1yvd37lIX/k8rtOWFgYMjIy8O2332LevHmYNGkSfv75Z2zatAnBwcGeqCP5EUkCXnrJfiebTMA779T+mrqGl5tM1mW/7BYuBFz5zBVC8EOaiIjIRd7o6QZQ4xBz9nQTucba021dbi8yUoauXe37t2yx3Hdms9l2DFXl8pJhVtdffz2uv/56d9aFCAAwZIiETp3KcfCgJTv+Rx9ZkpyFhlZ/fF3Dyz/+2DLnxGrsWKBPH9fqxOHlRERErisqKrL9/dSpU4iOjvbokloVg+6KAb+V2Wy2ZWQmorpZM5NbO7fkcjmuuw743/8s+3fuBEwm+7JhfKhVvXpFEevXr8fNN9+MNm3aIDk5GTfffDN+++03d9eN/JQkAePG2ZP1abXA4sVldbxGqranu6AAePZZ+3ZIiGUut6s4vJyIiMg1Wq0WWVlZtm2dToesrCxotVqPXdMaaNc0v9RkMjEoIHJB5Z5ua9BtpdcDe/eqAHCt7tq4HHS/8847GDFiBEJDQ/HEE09gypQpCAsLw8iRI/FOXeOAiZyg1Wpx/fUXERVlv3H/7/9kyM+v/kPaOvS7up7ul14CLl2ybz//PBAX53qdOLyciIjINbm5udWWX7x40WPXlMvlkCSpxi//HLlG5DytVgutVgu9Xm97gCaXyzFwoONx27ZZRo8w6K6Zy+86c+fOxYIFC7B8+XJMmTIFU6ZMwRdffIEFCxbglYrrMRHVU25uLlQqgTFj8mxlZ8+q8c03JVWOrbgMSeWe7sOHHeeDJycDU6fWr078kCYiInJNTYmVdDqdx65pzbbMnm6iK2MdqWLNj2C9p0pKShATA7Rtaz92y5ba7zuqR9BdWFiIESNGVCkfNmxYtet3E7nK+iF95515UCrtgfTHH4dVOdYadFfu6RbCEmBXzKPy5puAWl2/OjHoJiIico1Kpaq2XF3fD2Mn1bR8kRCCn+dETqprpErFIebbtgEymYpBdy1cftcZNWoUvvvuuyrlq1atwi233OKWSpF/s35IN2tmwsiR9iHlO3aE4MCB6l9TOej+8Ufg11/t+4cPB26+uf51EkJwTjcREZELoqOjXSp3F6VSWW328ooP6omodjWNVLGWVwy6S0qAY8eCGXTXwuX0jR06dMCcOXOwceNGpKSkAAB27NiBrVu3Yvr06Vi4cKHt2CmV12kickJ0dLRt3sh9913GqlURtn1vvy3w4Yf24LdyT7cQAnq9hCeftJ9PoQDeeguob8xsPS8/pImIiJxnzVJ+8eJF6HQ6qNVqREdHIyys6sg1d1IqlSgrq5qAtWIiKCKqnUqlqnYqiHWkSsWgGwD+/DMQbdt6LkliU+dy0L1kyRJERETg0KFDOHTokK08PDwcS5YssW1LksSgm+ql4od0hw469O5dht9/DwQAfPaZwOzZZsTEWD4wKz+1FkJgwQIJJ0/azzdlCtC+ff3rY50rzqCbiIjINRqNxqNLhFXHOre08ig1fp4TOa9iJ1jlcgBITAQSEgDrITt3BuDOO6ved2ThctB9+vRpT9SDyEHFD+lnngFuu81SrtPJMH/+JcybFwaVSlUl6D53zozZs+0fptHRwH/+c2V1sV6DbyBERESNn1KphBACJpPJYU3uiusME1HtKnaClZeXA7D0clccqXLddcDnn1v+vnOnAiZT1fuOLOr9qO/SpUu4fPmyO+tCVK1bbgFat7Zvf/65BkePnnIYOmb9AH32WRlKKiQ5f+UV4EofsPPJOBERUdNhXau78rxufp4TuUaj0SA5ORnNmzcHUDUJYsUh5vn5Mpw8qa5xLri/c+ldp6CgABMnTkSzZs0QExOD6OhoNGvWDJMmTUJBQYGHqkj+Ti4HJk+2b+fmKrF+fQROnTqFCxcuAAAuX76MvXsD8fnn9v/SPXoADz545dfnhzQREVHTYQ26Kyd1Yk83Uf1Y753CwkIcP34cWq1l7nbled27djGZWk2cjiLy8vLQp08ffPrppxg9ejTeeOMNvP7667j99tvxySefICUlBfn5+S5dfO7cuejVqxdCQ0MRHR2NtLQ0HD16tMpxhw8fxqhRo6DRaBAaGoq+ffsiMzPTtl+n02Hy5Mlo1qwZgoODMWrUKJw7d86lulDj9tBDQEiIfXv58mgEBAQ4POx5550Yh9csXAi4I062vtFweDkREVHjZx3aWlPQzYfoRM7TarUOo5t1Oh2ysrKg1WrRrh3wdyc4AAbdtXH6XWfWrFlQqVQ4efIk3n//fUydOhXTpk3DBx98gBMnTkCpVGLWrFkuXXzTpk2YOHEiduzYgXXr1sFoNGLYsGEoqTA++OTJkxgwYADat2+PjRs34n//+x9eeOEFBAQE2I6ZOnUqvvvuO3z55ZfIyMhAcXExbr75ZluWSmr6NBpL4G31++8Sdu+2r/9ZViZh165g2/bddwP9+rnn2lxihIiIqOmQJMmWTK0ik8kEmUzGh+hELqhtvW5JAgYOtJft3h0MvZ5Bd3WcjiK+//57vP7664iJiamyLzY2Fq+++mq163fXZs2aNRg3bhw6deqEa665BkuXLkVmZiZ27dplO+a5557DyJEj8eqrr6Jbt2646qqrcNNNN9ky52m1WixZsgRvvPEGhgwZgm7duuG///0v9u/fj99++82l+lDjNnmy47JfH39sT+Swf38QjEb7zjvvdN91+WSciIioaVEqldX2dPOznMg1Nc3Rti4nVnGIeW6uAidPioaoVpPjdGq57OxsdOrUqcb9nTt3Rk5OzhVVxjo/IDIyEoDlzXH16tV4+umnMXz4cOzZswetW7fGM888g7S0NADArl27YDAYMGzYMNt54uPj0blzZ2zbtg3Dhw+vch2dTuew7lxhYSEAyzAkTw2JsJ6XQy7qLzERGDlSjtWrLR+Y69aFISdHidhYA3btCnI4tk8fA9z1q7a2WV0jJ9jG/oNt7R/Yzv6B7eyb5HI59Hq9w3c7o9EImUzGtvZhvJ/dT6lUVht4q1QqGAwGpKQAgNJWvnWrHH37eu7339ja2Nl6OB10N2vWDGfOnEHLli2r3X/69GlERUU5e7oqhBB48sknMWDAAHTu3BmAZThDcXEx5s2bh9mzZ2P+/PlYs2YNbr/9dqSnpyM1NRU5OTlQqVSIiIhwOF9MTEyNDwHmzp2Ll156qUr5r7/+iqCgoGpe4T7r1q3z6Pl9XZ8+zbB6dX8AgMkkYfnySEydmoPdu+1DyxMSSvDnn+4b5RASEoKYmBj8+uuvtqHmtWEb+w+2tX9gO/sHtrNviYqKQlBQEPbv328ry8rKgkqlws8//+zFmlFD4P3sPsHBwYiNjbWtv2398+zZszh06BBMJiAoaCRKSy2B9/btiga5xxpLG5eWljp1nCSciSIAjB8/HidOnMC6deugUqkc9ul0OgwfPhxt2rTBkiVLXK8tgIkTJ2L16tXIyMiwBfbnz59HixYtcM899+CLL76wHTtq1CgEBwdj+fLl+OKLL/Dggw869FwDwNChQ9GmTRssXry4yrWq6+lOSEjApUuXHNaecyeDwYB169Zh6NChtqya5DohgO7dFTh40DKUPDzcjA0bTqN//ySUlVmykT70kBmLF7tvPn9BQQEuXLiAtm3b1joPjG3sP9jW/oHt7B/Yzr7p8uXLyMvLw9VXX21r465du0IIgYSEBG9XjzyE97NnFBUV4fLly9Dr9VCpVIiKikJoaKht/6hRcqxZYxmJmpCgw/HjnpuW2djauLCwEM2aNYNWq601jnS6p/ull15Cz549cfXVV2PixIlo3749AODQoUN49913odPp8Nlnn9WrspMnT8YPP/yAzZs3O/SkN2vWDAqFAh07dnQ4vkOHDsjIyABgmU+u1+uRn5/v0Nudm5uLfjVk0lKr1VXWmQMswyc83XgNcQ1fN20a8PDDlr8XFMjwf//XBhWW7EZqqgxKpftudEmSIJPJqjxsqgnb2H+wrf0D29k/sJ19S0BAgG0Ot7VdhRBQKBRsZz/A+9m9IiMjbdN/q5OaCqxZY/l7VpYa58/r0bq1f8RUztbB6cikZcuW2L59Ozp27GibU52WlobnnnsOHTt2xNatW11+ciiEwKRJk7By5Ups2LABrVu3dtivUqnQq1evKsuIHTt2DImJiQCAHj16QKlUOgwxyM7OxoEDB2oMuqlp+8c/gGbN7NuVB1dUzKLoDmazmZlOiYiImhDrF2Gj0WgrYyI1Is+ovF73pk1m71SkEXO6pxsAWrdujV9++QX5+fk4fvw4ACA5ObnWJx+1mThxIr744gusWrUKoaGhtjnYGo0GgYGBAIAZM2ZgzJgxuO666zB48GCsWbMGP/74IzZu3Gg7dvz48Zg+fTqioqIQGRmJp556Cl26dMGQIUPqVS9q3AIDgUcfBebMqbovLs6EpCS5W68nhOCHNBERURNiDboNBoNtdKPZbIZc7t7vCEQE9OwJBAQA5eWW7S1bgHHjvFqlRqdekURERAR69+6N3r171zvgBoD33nsPWq0WgwYNQlxcnO1nxYoVtmNuu+02LF68GK+++iq6dOmCjz76CN9++y0GDBhgO2bBggVIS0vDXXfdhf79+yMoKAg//vgj31h92IQJgKKaR0Z9+xrg7k5pPhknIiJqWhR/f0momFmYn+dEnqFSAX372re3bnWpX9cvePU34mQONzz00EN46KGHatwfEBCARYsWYdGiRe6qGjVy8fHAmDHA5587lvfpYwAQ4NZrcXg5ERFR0yKTySCXy6sE3eyQIfKM664D/h6IjKNHFbh8GbiCha18Dh/3UZM1dWrVst69dVULrxCHlxMRETUtWq0WZrMZubm5OH36NIKDg9nTTeRBlXMq/Z3zmv7Gdx5qsnr2BNLS7NsREUa0bevcAvWu4Ic0ERFR06HVapGVlWUbUanX6xEbGwsAuHjxIrRarTerR+STUlIcp35u3uy9ujRGjCSoSXv3XaBPH8vwlf/85xIkybkpC67g8HIiIqKmIzc3t0qZNQA3GAzIyspi4E3kZsHBQI8e9m0G3Y4YdFOTFhcH7NgBXLwIjBpVCrPZ/UsUcHg5ERFR06HX66uUVX54fvHixYaqDpHfqLh02J49AkVF3qtLY8NIgnyCJFk+UJ1NzucKDi8nIiJqOlQqVZ3H6HTuzwFD5O8qzus2mSRs3+69ujQ2jCTIZ8hkMo/0dDPoJiIiajqio6PrPMa6djcRuc+AAXCY6skh5naMJMhneLKnm3O6iYiImgaNRoOEhAQEBNiXEK38/cCZwJyIXBMRAXTpYt9m0G3HlcvJZ0iSxDndREREBI1GA41GAwDIy8vD6dOnERAQALVajejoaISFhXm5hkS+6brrJOzbZ/n7778D5eVAhedffouRBPkMmUzGOd1ERETkIDQ0FOfOnUPbtm2RnJzMgJvIgyrO69bpgD/+8F5dGhNGEuQzPDW8XAjB4eVERERERHWoGHQDHGJuxaCbfIYnEqkJITi8nIiIiIjICXFxwFVXGW3bDLotGEmQz/BET7c1iGfQTURERERUt5QUe9C9bRtgNNZysJ9gJEE+wxOJ1Kzn4/ByIiIiIqK6DRhg7wQrLgb27vVeXRoLBt3kMzyRSM16PvZ0ExERERHVLTXVsbOKQ8wZdJMP4fByIiIiIiLvSk5WICbGYNtm0M2gm3yItafbnYE3h5cTERERETlPoZCjZ89S23ZGBuDmGaBNDoNu8hnWwNgTQTd7uomIiIiI6iZJEnr31tm2L18GDh/2YoUaAUYS5DOsgbE7k6lxTjcRERERkWtSUgwO2/4+xJyRBPkM9nQTEREREXlfhw5ARITJts2gm8hHWINud/Z0c043EREREZFrVColevSwz+vevBlwc77jJoVBN/kMa2+0O3u6redi0E1ERERE5BylUolu3Ypt2+fPA6dPe7FCXsagm3yGp4aXy2QyBt1ERERERE5SKpXo0aPEocyfh5gz6Caf4YlEamazmQE3EREREZELlEol2rUrR2iovTOMQTeRD/BET7cQgknUiIiIiIhcoFQqoVAAvXsbbWUMuol8gKd6uhl0ExERERE5TyaTQS6XO6zXffKkZW63P2I0QT7DU3O6ObyciIiIiMg1SqUSvXqVOZRt2eKlyngZg27yGZ5YMozDy4mIiIiIXKdUKtGxYwnUanuZvw4xZzRBPsOT2cuJiIiIiMh5KpUKMpkBffvayxh0EzVxkiRBkiS3Bd1arRbFxcUoLi7G8ePHodVq3XJeIiIiIiJfp1QqYTAYMGCA/bv5gQPA5cterJSXKLxdASJ3kslkdQ4v12q1yM3NhV6vh0qlQnR0NDQaTZVjsrKybNs6nc62XflYIiIiIiJypFQqYTabMWCAGYDcVr51KzBqlPfq5Q0MuslnaLVamEwmXLhwAQUFBS4F0+Xl5VCr1TAYDDAajcjPz6/2GhcvXmTQTURERERUB6VSCQDo2dMAuVwOk8lSvmULg26iJqm2YFqlUsFoNNYZTAOWnnKFQlFjb7lOp6u2nIiIiIiI7KxBt0qlR7duAfjzT0u5P2YwZ9BNPiE3N7facmswLZfLaw2mJUlChw4dbEnTjh8/Xm2Ara6YfpGIiIiIiKqlUFhCTYPBgIEDYQu6d+0CSkqA4GAvVq6BMZEa+QS9Xl9tuSRJ6NixIzp06ICrr766xqBZrVY7ZCmPjo6u9riayomIiIiIyE6SJFsytYED7eVGI7Bzp/fq5Q0MusknqFSqasvrG0xrNBokJCQgICAAkiQhICAArVq1QlhYmPsqTURERETkw+wZzB3L/W2IOYeXk0+Ijo52mNNdsbwiaxK0ixcvQqfTQa1WIzo6utpgWqPRMGkaEREREVE9WYPuhASgXTvg6FFLOYNuoiaIwTQRERERUeOiVCpRWloKABg40B50b98OGAzA37nWfB6DbvIZDKaJiIiIiBoPa0+3EAIDB0r46CNLeWkpsGcP0Lu3d+vXUDinm4iIiIiIiNzOmnfJaDQ6JFMD/GuIOYNuIiIiIiIicjvrWt0GgwFJSUCLFvZ9DLqJiIiIiIiIrkDFoFuS4NDbnZEBmM1eqlgDY9BNREREREREbieTySCTyWAwGAA4Bt2XL9sTq/k6Bt1ERERERETkdpIk2ZKpAfDbed0MuomIiIiIiMgjlEol9Ho9AKBTJyAiwr6PQTcRERERERHRFajY0y2TAf372/cx6CYiIiIiIiK6AhWDbsBxiPnZs0BWlhcq1cAYdBMREREREZFHKJVKmEwmmP9OVe6P87oZdBMREREREZFHVFw2DAB69AACA+37GXQTERERERER1VPloFulAvr0se9n0E1ERERERERUT5WDbsBxiPnBg5Y1u30Zg24iIiIiIiLyCJlMBoVCUWPQDQBbtzZwpRoYg24iIiIiIiLymMoZzFNSALncvt/Xh5gz6CYiIiIiIiKPqRx0h4QA3brZ9zPoJiIiIiIiIqoHrVaLkpISFBcX4/jx49BqtQAch5jv2gWUlHipgg2AQTcRERERERG5nVarRVZWFkwmEwBAp9MhKysLWq3WIeg2GoGdO71UyQbAoJuIiIiIiIjcLjc3t9ryixcvYsAAxzJfHmLOoJuIiIiIiIjcTq/XV1uu0+nQvDnQvr29jEE3ERERERERkQtUKlW15Wq1GoDjvO7t24EKudZ8CoNuIiIiIiIicrvo6Ohqy6OiogA4Bt2lpcCePQ1Rq4bHoJuIiIiIiIjcTqPRICEhAQEBAZAkCSqVCpIkoeTvVOUVg27Ad4eYM+gmIiIiIiIij9BoNEhOTkanTp3Qtm1bxMfHo6CgAIWFhUhMBFq2tB/LoJuIiIiIiIjoCoSHhyMkJATnz5+HyWR06O3OyADMZu/VzVMYdBMREREREVGDkCQJLVq0gBAC2dnZDkH35cvAkSPeq5unMOgmIiIiIiKiBqNUKhEXFwetVotrrily2OeLQ8y9GnTPnTsXvXr1QmhoKKKjo5GWloajR4/WePyjjz4KSZLw1ltvOZTrdDpMnjwZzZo1Q3BwMEaNGoVz5855uPZERERERERUHxqNBmFhYdBoziEiQtjKGXS72aZNmzBx4kTs2LED69atg9FoxLBhw2zZ7Cr6/vvvsXPnTsTHx1fZN3XqVHz33Xf48ssvkZGRgeLiYtx8880wmUwN8c8gIiIiIiIiF0iShPj4eMhkQPfu5bZyXwy6Fd68+Jo1axy2ly5diujoaOzatQvXXXedrfyvv/7CpEmTsHbtWtx0000Or9FqtViyZAk+++wzDBkyBADw3//+FwkJCfjtt98wfPhwz/9DiIiIiIiIyCUKhQLx8fHo2lWL9esDAQCZmZafVq28XDk38mrQXZlWqwUAREZG2srMZjPuv/9+zJgxA506daryml27dsFgMGDYsGG2svj4eHTu3Bnbtm2rNujW6XTQ6XS27cLCQgCAwWCAwWBw27+nIut5PXV+8j62sf9gW/sHtrN/YDv7Prax/2BbN01BQUEYMKAUCxbYyzZuNOKee0SVYxtbGztbj0YTdAsh8OSTT2LAgAHo3LmzrXz+/PlQKBSYMmVKta/LycmBSqVCRESEQ3lMTAxycnKqfc3cuXPx0ksvVSn/9ddfERQUdAX/irqtW7fOo+cn72Mb+w+2tX9gO/sHtrPvYxv7D7Z1UyRHQMBIlJdbZj8vX54FjWZfjUc3ljYuLS116rhGE3RPmjQJ+/btQ0ZGhq1s165dePvtt7F7925IkuTS+YQQNb7mmWeewZNPPmnbLiwsREJCAoYNG4awsLD6/QPqYDAYsG7dOgwdOhRKpdIj1yDvYhv7D7a1f2A7+we2s+9jG/sPtnXT1rOnCRkZlqA7MzMJI0e2rHJMY2tj64jpujSKoHvy5Mn44YcfsHnzZrRsaf/lbtmyBbm5uWhVYUC/yWTC9OnT8dZbb+HMmTOIjY2FXq9Hfn6+Q293bm4u+vXrV+311Go11Gp1lXKlUunxxmuIa5B3sY39B9vaP7Cd/QPb2fexjf0H27ppGjwYsPa/HjokobBQiaio6o9tLG3sbB28mr1cCIFJkyZh5cqV2LBhA1q3bu2w//7778e+ffuwd+9e2098fDxmzJiBtWvXAgB69OgBpVLpMMQgOzsbBw4cqDHoJiIiIiIiosZj4EDH7eXLM3H8+HFb3q+mzKs93RMnTsQXX3yBVatWITQ01DYHW6PRIDAwEFFRUYiq9HhDqVQiNjYW7dq1sx07fvx4TJ8+HVFRUYiMjMRTTz2FLl262LKZExERERERUeOVkgLI5QImk2WK8K5dgRg0qBBZWVkALHFfU+XVnu733nsPWq0WgwYNQlxcnO1nxYoVLp1nwYIFSEtLw1133YX+/fsjKCgIP/74I+RyuYdqTkRERERERO4SEgJ06GBfYWr37mDb3y9evOiNKrmNV3u6haiaBr4uZ86cqVIWEBCARYsWYdGiRW6oFRERERERETW07t2LceBAAADg0KFAlJZKCAoSDss9N0Ve7ekmIiIiIiIiAoDevfW2vxuNEvbvtyznXF0S7KaEQTcRERERERF53YgRIQ7bu3dbgu7o6GhvVMdtGHQTERERERGR17VpE4a2bU227b17Q9GqVSuEhYV5sVZXjkE3ERERERERNQqpqfZk2Hv3BiEwsGkH3ACDbiIiIiIiImokKq7XXVoK7Nnjvbq4C4NuIiIiIiIiahQqBt0AsHOnd+rhTl5dMoyIiIiIiIjIKjERmDoV6NrVEoC3aePtGl05Bt1ERERERETUKEgSsGCBt2vhXhxeTkREREREROQhDLqJiIiIiIiIPIRBNxEREREREZGHMOgmIiIiIiIi8hAG3UREREREREQewqCbiIiIiIiIyEMYdBMRERERERF5CINuIiIiIiIiIg9h0E1ERERERETkIQy6iYiIiIiIiDyEQTcRERERERGRhzDoJiIiIiIiIvIQhbcr0BgIIQAAhYWFHruGwWBAaWkpCgsLoVQqPXYd8h62sf9gW/sHtrN/YDv7Prax/2Bb+77G1sbW+NEaT9aEQTeAoqIiAEBCQoKXa0JERERERERNSVFRETQaTY37JVFXWO4HzGYzzp8/j9DQUEiS5JFrFBYWIiEhAVlZWQgLC/PINci72Mb+g23tH9jO/oHt7PvYxv6Dbe37GlsbCyFQVFSE+Ph4yGQ1z9xmTzcAmUyGli1bNsi1wsLCGsV/EPIctrH/YFv7B7azf2A7+z62sf9gW/u+xtTGtfVwWzGRGhEREREREZGHMOgmIiIiIiIi8hAG3Q1ErVZj5syZUKvV3q4KeQjb2H+wrf0D29k/sJ19H9vYf7CtfV9TbWMmUiMiIiIiIiLyEPZ0ExEREREREXkIg24iIiIiIiIiD2HQTUREREREROQhDLqJiIiIiIiIPMSvg+65c+eiV69eCA0NRXR0NNLS0nD06FGHY4QQePHFFxEfH4/AwEAMGjQIBw8etO3Py8vD5MmT0a5dOwQFBaFVq1aYMmUKtFqtw3lGjRqFVq1aISAgAHFxcbj//vtx/vz5Ouu4f/9+pKamIjAwEC1atMCsWbNQMfdddnY2/vGPf6Bdu3aQyWSYOnXqlf1SfIwvtPG4ceMgSVKVn06dOl3hb8e3NGRbW+l0Olx77bWQJAl79+6ts468n6+ML7Qx72fnNGRbJyUlVWmPf//733XWkffzlfGFNub97JyGfu9evXo1+vTpg8DAQDRr1gy33357nXXk/XxlfKGNPX4/Cz82fPhwsXTpUnHgwAGxd+9ecdNNN4lWrVqJ4uJi2zHz5s0ToaGh4ttvvxX79+8XY8aMEXFxcaKwsFAIIcT+/fvF7bffLn744Qdx4sQJsX79enH11VeL0aNHO1zrzTffFNu3bxdnzpwRW7duFSkpKSIlJaXW+mm1WhETEyPuvvtusX//fvHtt9+K0NBQ8frrr9uOOX36tJgyZYr49NNPxbXXXiueeOIJ9/2CfIAvtHFBQYHIzs62/WRlZYnIyEgxc+ZM9/2ifEBDtrXVlClTxI033igAiD179tRaP97PV84X2pj3s3Masq0TExPFrFmzHNqlqKio1vrxfr5yvtDGvJ+d05Bt/c0334iIiAjx3nvviaNHj4ojR46Ir7/+utb68X6+cr7Qxp6+n/066K4sNzdXABCbNm0SQghhNptFbGysmDdvnu2Y8vJyodFoxOLFi2s8z1dffSVUKpUwGAw1HrNq1SohSZLQ6/U1HvPuu+8KjUYjysvLbWVz584V8fHxwmw2Vzk+NTWVbwJ1aOptLIQQ3333nZAkSZw5c6bG85Ln2/rnn38W7du3FwcPHnQqIOP97H5NvY2F4P3sLE+2dWJioliwYIFL9eH97H5NvY2F4P3sLE+1tcFgEC1atBAfffSRS/Xh/ex+Tb2NhXD//ezXw8srsw5fiIyMBACcPn0aOTk5GDZsmO0YtVqN1NRUbNu2rdbzhIWFQaFQVLs/Ly8Pn3/+Ofr16welUlnjebZv347U1FSHxd+HDx+O8+fP48yZM6780+hvvtDGS5YswZAhQ5CYmFjjecmzbX3hwgU88sgj+OyzzxAUFORUfXg/u58vtDHvZ+d4+r17/vz5iIqKwrXXXos5c+ZAr9fXWh/ez+7nC23M+9k5nmrr3bt346+//oJMJkO3bt0QFxeHG2+80WEIc3V4P7ufL7Sxu+9nBt1/E0LgySefxIABA9C5c2cAQE5ODgAgJibG4diYmBjbvsouX76Ml19+GY8++miVff/6178QHByMqKgoZGZmYtWqVbXWKScnp9prV6wbOc8X2jg7Oxu//PILHn744VrP6+882dZCCIwbNw6PPfYYevbs6XSdeD+7ly+0Me9n53j6vfuJJ57Al19+ifT0dEyaNAlvvfUWJkyYUGudeD+7ly+0Me9n53iyrU+dOgUAePHFF/H888/jp59+QkREBFJTU5GXl1djnXg/u5cvtLEn7mcG3X+bNGkS9u3bh+XLl1fZJ0mSw7YQokoZABQWFuKmm25Cx44dMXPmzCr7Z8yYgT179uDXX3+FXC7H2LFjbRP4O3XqhJCQEISEhODGG2+s9drVlVPdfKGNP/nkE4SHhyMtLa3uf7Af82RbL1q0CIWFhXjmmWdqvD7vZ8/zhTbm/ewcT793T5s2DampqejatSsefvhhLF68GEuWLMHly5cB8H5uCL7QxryfnePJtjabzQCA5557DqNHj0aPHj2wdOlSSJKEr7/+GgDv54bgC23sifu5+rGxfmby5Mn44YcfsHnzZrRs2dJWHhsbC8DyBCQuLs5WnpubW+VpSVFREUaMGIGQkBB899131Q4pbtasGZo1a4a2bduiQ4cOSEhIwI4dO5CSkoKff/4ZBoMBABAYGGi7fuWnL7m5uQCqPimi2vlCGwsh8PHHH+P++++HSqWq76/C53m6rTds2IAdO3Y4DFECgJ49e+Lee+/Fp59+yvvZw3yhjXk/O6eh3rsr6tu3LwDgxIkTiIqK4v3sYb7QxryfnePptra+tmPHjrYytVqNq666CpmZmQDA+9nDfKGNPXY/u2VmeBNlNpvFxIkTRXx8vDh27Fi1+2NjY8X8+fNtZTqdrsqkf61WK/r27StSU1NFSUmJU9fOzMwUAER6enqNx7z77rsiPDxc6HQ6W9m8efOY2MEFvtTG6enpAoDYv3+/U9f3Nw3V1mfPnhX79++3/axdu1YAEN98843IysqqsX68n6+cL7Ux7+faefO9+8cffxQAxNmzZ2s8hvfzlfOlNub9XLuGamutVivUarVDki29Xi+io6PF+++/X2P9eD9fOV9qY0/dz34ddD/++ONCo9GIjRs3OqSILy0ttR0zb948odFoxMqVK8X+/fvFPffc45DevrCwUPTp00d06dJFnDhxwuE8RqNRCCHEzp07xaJFi8SePXvEmTNnxIYNG8SAAQNEmzZtHLLoVVZQUCBiYmLEPffcI/bv3y9WrlwpwsLCHNLbCyHEnj17xJ49e0SPHj3EP/7xD7Fnzx5x8OBBD/zGmh5faWMhhLjvvvtEnz593Pwb8h0N1daVnT592qnM1ryfr5yvtLEQvJ/r0lBtvW3bNvHmm2+KPXv2iFOnTokVK1aI+Ph4MWrUqFrrx/v5yvlKGwvB+7kuDfne/cQTT4gWLVqItWvXiiNHjojx48eL6OhokZeXV2P9eD9fOV9pYyE8dz/7ddANoNqfpUuX2o4xm81i5syZIjY2VqjVanHdddc5PPmwPg2p7uf06dNCCCH27dsnBg8eLCIjI4VarRZJSUniscceE+fOnauzjvv27RMDBw4UarVaxMbGihdffLHKE5nqrp2YmOiOX1GT5yttXFBQIAIDA8UHH3zglt+LL2qotq7M2YBMCN7PV8pX2pj3c90aqq137dol+vTpIzQajQgICBDt2rUTM2fOdKrHlPfzlfGVNub9XLeGfO/W6/Vi+vTpIjo6WoSGhoohQ4aIAwcO1FlH3s9Xxlfa2JP3syTE37PIiYiIiIiIiMitmL2ciIiIiIiIyEMYdBMRERERERF5CINuIiIiIiIiIg9h0E1ERERERETkIQy6iYiIiIiIiDyEQTcRERERERGRhzDoJiIiIiIiIvIQBt1EREREREREHsKgm4iIyA+MGzcOkiRBkiQolUrExMRg6NCh+Pjjj2E2m50+zyeffILw8HDPVZSIiMjHMOgmIiLyEyNGjEB2djbOnDmDX375BYMHD8YTTzyBm2++GUaj0dvVIyIi8kkMuomIiPyEWq1GbGwsWrRoge7du+PZZ5/FqlWr8Msvv+CTTz4BALz55pvo0qULgoODkZCQgAkTJqC4uBgAsHHjRjz44IPQarW2XvMXX3wRAKDX6/H000+jRYsWCA4ORp8+fbBx40bv/EOJiIgaEQbdREREfuz666/HNddcg5UrVwIAZDIZFi5ciAMHDuDTTz/Fhg0b8PTTTwMA+vXrh7feegthYWHIzs5GdnY2nnrqKQDAgw8+iK1bt+LLL7/Evn37cOedd2LEiBE4fvy41/5tREREjYEkhBDergQRERF51rhx41BQUIDvv/++yr67774b+/btw6FDh6rs+/rrr/H444/j0qVLACxzuqdOnYqCggLbMSdPnsTVV1+Nc+fOIT4+3lY+ZMgQ9O7dG6+88orb/z1ERERNhcLbFSAiIiLvEkJAkiQAQHp6Ol555RUcOnQIhYWFMBqNKC8vR0lJCYKDg6t9/e7duyGEQNu2bR3KdTodoqKiPF5/IiKixoxBNxERkZ87fPgwWrdujbNnz2LkyJF47LHH8PLLLyMyMhIZGRkYP348DAZDja83m82Qy+XYtWsX5HK5w76QkBBPV5+IiKhRY9BNRETkxzZs2ID9+/dj2rRp+PPPP2E0GvHGG29AJrOkffnqq68cjlepVDCZTA5l3bp1g8lkQm5uLgYOHNhgdSciImoKGHQTERH5CZ1Oh5ycHJhMJly4cAFr1qzB3LlzcfPNN2Ps2LHYv38/jEYjFi1ahFtuuQVbt27F4sWLHc6RlJSE4uJirF+/Htdccw2CgoLQtm1b3HvvvRg7dizeeOMNdOvWDZcuXcKGDRvQpUsXjBw50kv/YiIiIu9j9nIiIiI/sWbNGsTFxSEpKQkjRoxAeno6Fi5ciFWrVkEul+Paa6/Fm2++ifnz56Nz5874/PPPMXfuXIdz9OvXD4899hjGjBmD5s2b49VXXwUALF26FGPHjsX06dPRrl07jBo1Cjt37kRCQoI3/qlERESNBrOXExEREREREXkIe7qJiIiIiIiIPIRBNxEREREREZGHMOgmIiIiIiIi8hAG3UREREREREQewqCbiIiIiIiIyEMYdBMRERERERF5CINuIiIiIiIiIg9h0E1ERERERETkIQy6iYiIiIiIiDyEQTcRERERERGRhzDoJiIiIiIiIvIQBt1EREREREREHsKgm4iIiIiIiMhDGHQTEREREREReQiDbiIiIiIiIiIPYdBNRERERERE5CEMuomIiIiIiIg8hEE3ERERERERkYcw6CYiIiIiIiLyEIW3K0BE5E9MJhMMBoO3q0FE5POUSiXkcrm3q0FExKCbiKghCCGQk5ODgoICb1eFiMhvhIeHIzY2FpIkebsqROTHGHQTETUAa8AdHR2NoKAgfgEkIvIgIQRKS0uRm5sLAIiLi/NyjYjInzHoJiLyMJPJZAu4o6KivF0dIiK/EBgYCADIzc1FdHQ0h5oTkdcwkRoRkYdZ53AHBQV5uSZERP7F+r7LXBpE5E0MuomIGgiHlBMRNSy+7xJRY8Cgm4iIiIiIiMhDGHQTERERUaP34osv4tprr/V2NYiIXMagm4iIapWVlYXx48cjPj4eKpUKiYmJeOKJJ3D58mVvVw3FxcVQKpVYsWKFQ/mYMWMgSRJOnjzpUN6mTRs8++yzTp07KSkJb731lruqWqNt27ZBLpdjxIgRHr8WVTVu3DikpaXVuL+srAwzZ85Eu3btoFar0axZM9xxxx04ePCg7Zg1a9ZAkiTk5OQ4vDY2NhYJCQkOZefOnYMkSfj1118BAIMGDYIkSVV+HnvsMdtr0tPTMXjwYERGRiIoKAhXX301HnjgARiNRtsx77//Pq655hoEBwcjPDwc3bp1w/z582v9t3/77bfo06cPNBoNQkND0alTJ0yfPr3O31lDkCQJ33//vberQUTkFgy6iYioRqdOnULPnj1x7NgxLF++HCdOnMDixYuxfv16pKSkIC8vz6v1CwkJQc+ePZGenu5QvmnTJiQkJDiUnzt3DqdOncLgwYMbtI56vb7W/R9//DEmT56MjIwMZGZm1nqsEMIh0CLP0ul0GDJkCD7++GO8/PLLOHbsGH7++WeYTCb06dMHO3bsAAAMGDAACoUCGzdutL328OHDKC8vR2FhIU6cOGErT09Ph1KpRP/+/W1ljzzyCLKzsx1+Xn31VQDAwYMHceONN6JXr17YvHkz9u/fj0WLFkGpVMJsNgMAlixZgieffBJTpkzB//73P2zduhVPP/00iouLa/y3/fbbb7j77rtxxx134Pfff8euXbswZ86cOv+/EhFRPQgiIvKosrIycejQIVFWVnbF5yooKBDHjh0TBw4cEMeOHRMFBQVuqGHNRowYIVq2bClKS0sdyrOzs0VQUJB47LHHbGWJiYli1qxZ4p577hHBwcEiLi5OLFy4sEr9H3nkEdG8eXMRGhoqBg8eLPbu3WvbP3PmTHHNNdeIZcuWicTERBEWFibGjBkjCgsLa6zjM888I9q1a2fbPnTokAgLCxNz584V9957r6182bJlQqlUipKSEnHixAkxatQoER0dLYKDg0XPnj3FunXrbMempqYKAA4/Vlu3bhUDBw4UAQEBomXLlmLy5MmiuLjY4ffw8ssviwceeECEhYWJsWPH1lj34uJiERoaKo4cOSLGjBkjXnrpJYf96enpAoBYs2aN6NGjh1AqlWLDhg3CbDaL+fPni9atW4uAgADRtWtX8fXXX9teZzQaxUMPPSSSkpJEQECAaNu2rXjrrbdqrIc/e+CBB8Stt95a7b558+YJSZIc/o8KIYTJZBI9e/YUHTt2FGazWQghREpKinj00Udtx7z77rvipptuEiNHjhQffvihrfyhhx4S/fv3t22npqaKJ554osb6LViwQCQlJdX6b7j11lvFuHHjaj2msieeeEIMGjSo1mOs9+OSJUtEQkKCCA4OFo899pgwGo1i/vz5IiYmRjRv3lzMnj3b4XVnz54Vo0aNEsHBwSI0NFTceeedIicnx+GYd999V1x11VVCqVSKtm3bimXLltn2JSYmOtx7iYmJDvVx5f3Bne+/RET1xZ5uIqImQqvVIisrCzqdDkII6HQ6ZGVlQavVeuR6eXl5WLt2LSZMmGBb79YqNjYW9957L1asWAEhhK38tddeQ9euXbF7924888wzmDZtGtatWwfA0kt70003IScnBz///DN27dqF7t2744YbbnDoMT958iS+//57/PTTT/jpp5+wadMmzJs3r8Z6Dh48GEePHkV2djYAS0/iwIEDcf311zv0PKanp6NPnz4ICgpCcXExRo4cid9++w179uzB8OHDccstt9h6mleuXImWLVti1qxZtp5HANi/fz+GDx+O22+/Hfv27cOKFSuQkZGBSZMmOdTptddeQ+fOnbFr1y688MILNdZ9xYoVaNeuHdq1a4f77rsPS5cudfh9Wj399NOYO3cuDh8+jK5du+L555/H0qVL8d577+HgwYOYNm0a7rvvPmzatAkAYDab0bJlS3z11Vc4dOgQ/vOf/+DZZ5/FV199VWNd3E2rBTIyvPfjjtviiy++wNChQ3HNNdc4lMtkMkybNg2HDh3C//73PwCW/4cVR1akp6dj0KBBSE1NrVLuymiL2NhYZGdnY/PmzbUes2PHDpw9e9al8x48eBAHDhyo9biTJ0/il19+wZo1a7B8+XJ8/PHHuOmmm3Du3Dls2rQJ8+fPx/PPP2/r9RdCIC0tDXl5edi0aRPWrVuHkydPYsyYMbZzfvfdd3jiiScwffp0HDhwAI8++igefPBB2+/pjz/+AAAsXboU2dnZtm1rfVx5fyAiahS8GvITEfmBmnpaTCaTKC0tdfrn6NGjYv/+/VV+jh496vQ5TCaT0/XesWOHACC+++67ave/+eabAoC4cOGCEMLSOzVixAiHY8aMGSNuvPFGIYQQ69evF2FhYaK8vNzhmDZt2oj3339fCGHpyQoKCnLouZoxY4bo06dPjfUsKSkRSqVSfPHFF0IIIe68807x6quvCoPBIEJCQsSxY8eEEEK0bt1avPDCCzWep2PHjmLRokW27cTERLFgwQKHY+6//37xz3/+06Fsy5YtQiaT2do3MTFRpKWl1Xidivr162frgTYYDKJZs2YOPe7Wnu7vv//eVlZcXCwCAgLEtm3bHM41fvx4cc8999R4rQkTJojRo0c7VS932LJFCMB7P1u2OFfP2nq6AwICauyF3r17twAgVqxYIYQQ4tdffxUAxPnz54UQQkRHR4vff/9d7NixQ8THxwshhMjMzBQAxPr1623nSU1NFUqlUgQHBzv8fPLJJ0IIy6iFcePGCQAiNjZWpKWliUWLFgmtVms7x/nz50Xfvn0FANG2bVvxwAMPiBUrVtR6vxcXF4uRI0faepLHjBkjlixZ4nB/Vnc/Dh8+XCQlJTmcu127dmLu3Lm234NcLheZmZm2/QcPHhQAxO+//y6EsPy/f+SRRxzqc+edd4qRI0fatqt776nP+wN7uomoMVB4KdYnIvJ7Op2uSqKv+tDr9U6fp02bNlV6retL/N0jW3Ed3JSUFIdjUlJSbMnIdu3aheLiYkRFRTkcU1ZW5lD/pKQkhIaG2rbj4uKQm5tbYz2CgoLQu3dvbNy4Effccw82bdqEGTNmQKFQoH///ti4cSPUajVOnz6N66+/HgBQUlKCl156CT/99BPOnz8Po9GIsrKyOudU79q1CydOnMDnn3/u8Hswm804ffo0OnToAADo2bNnrecBgKNHj+L333/HypUrAQAKhQJjxozBxx9/jCFDhjgcW/F8hw4dQnl5OYYOHepwjF6vR7du3WzbixcvxkcffYSzZ8+irKwMer2emZ/dqPL///79+0OlUmHjxo245pprUFZWhu7du0MIgcLCQhw/fhzbt2+HWq1Gv379HM5177334rnnnnMoi46OBgDI5XIsXboUs2fPxoYNG7Bjxw7MmTMH8+fPx++//464uDjExcVh+/btOHDgADZt2oRt27bhgQcewEcffYQ1a9ZAJqs6sDE4OBirV6/GyZMnkZ6ejh07dmD69Ol4++23sX37dgQFBQGoej/GxMRALpc7nDMmJsZ2jx4+fBgJCQkOCeQ6duyI8PBwHD58GL169cLhw4fxz3/+06E+/fv3x9tvv13n793V9wciosaAQTcRkZeo1Wq0adPG6eOzsrKqTXKkUqmqZEiu7ZrOSk5OhiRJOHToULXZnY8cOYKIiAg0a9as1vNYgxKz2Yy4uDiHId9W4eHhtr8rlcoqr7cmjKrJ4MGDsWLFChw8eNAW7ACwDe1VqVQICAhA3759AQAzZszA2rVr8frrryM5ORmBgYG444476kwiZTab8eijj2LKlClV9rVq1cr29+Dg4FrPA1iSXxmNRrRo0cJWJoSAUqlEfn4+IiIiqj2f9XexevVqh9cC9vb96quvMG3aNLzxxhtISUlBaGgoXnvtNezcubPOepFd27ZtcejQoWr3HTlyBABw9dVXA7A//ElPT0deXh4GDBgAuVwOAOjXrx/S09Oxfft2pKSkICAgwOFcGo0GycnJtdalRYsWuP/++3H//fdj9uzZaNu2LRYvXoyXXnrJdkznzp3RuXNnTJw4ERkZGRg4cCA2bdpU63D2Nm3aoE2bNnj44Yfx3HPPoW3btlixYgUefPBBANXfj7Xdo0IIhwdxVpXLKx9T0+sqq8/7AxGRtzHoJiLyEplM5lKvc0xMDLKysqqUx8bGuq33uqKoqCgMHToU7777LqZNm+ZwjZycHHz++ecYO3aswxdl67zOitvt27cHAHTv3h05OTlQKBRISkpya10HDx6M2bNn44svvnAIdlJTU7Fo0SKo1WqHYGfLli0YN24cbrvtNgCWpcfOnDnjcE6VSgWTyeRQ1r17dxw8eLDOAKkuRqMRy5YtwxtvvIFhw4Y57Bs9ejQ+//zzKvPErTp27Ai1Wo3MzEykpqZWe8yWLVvQr18/TJgwwVbmjlEVrujSBdiypUEvWeX6V+ruu+/Gc889h//9738O87rNZjMWLFiAjh07OpQPHjwYX375JfLz8zFo0CBbeWpqKjZu3Ijt27fbgtkrERERgbi4OJSUlNR4TMeOHQGg1mMqS0pKQlBQkEuvqe66mZmZyMrKsj0MPHToELRarW0kSIcOHZCRkYGxY8faXrdt2zbbfsASXFe+/4iImioG3URETYRGowEAXLx4ETqdDmq1GtHR0QgLC/PYNd955x3069cPw4cPx+zZs9G6dWscPHgQM2bMQIsWLTBnzhyH47du3YpXX30VaWlpWLduHb7++musXr0aADBkyBCkpKQgLS0N8+fPR7t27XD+/Hn8/PPPSEtLc2pIdk369esHtVqNRYsWOQzT7dWrF7RaLb799lvMmDHDVp6cnIyVK1filltugSRJeOGFF6r0liUlJWHz5s24++67besz/+tf/0Lfvn0xceJEPPLIIwgODsbhw4exbt06LFq0yOn6/vTTT8jPz8f48eNt7Wp1xx13YMmSJTUG3aGhoXjqqacwbdo0mM1mDBgwAIWFhdi2bRtCQkLwwAMPIDk5GcuWLcPatWvRunVrfPbZZ/jjjz/QunVrp+t4pTQaYMCABrvcFdFqtdi7d69DWWRkJKZNm4ZVq1bhlltuwRtvvIE+ffrgwoULeOWVV3D48GH89ttvDg+dBg8ejJdffhnZ2dl46qmnbOWpqamYN28eioqKqu11Li0trbLGt1qtRkREBN5//33s3bsXt912G9q0aYPy8nIsW7YMBw8etP2fe/zxxxEfH4/rr78eLVu2RHZ2NmbPno3mzZtXmfJh9eKLL6K0tBQjR45EYmIiCgoKsHDhQhgMhipTF1wxZMgQdO3aFffeey/eeustGI1GTJgwAampqbZ7fMaMGbjrrrtsiRR//PFHrFy5Er/99pvtPElJSVi/fj369+9v+10QETVZ3ptOTkTkH5p6Ip8zZ86IcePGidjYWKFUKkVCQoKYPHmyuHTpksNxiYmJ4qWXXhJ33XWXCAoKEjExMVWWqSosLBSTJ08W8fHxtnPde++9tqRL1iWBKlqwYIFtyaDaWJf52rFjh0P5DTfcIACILRUya50+fVoMHjxYBAYGioSEBPHOO+9UWbpp+/btomvXrkKtVjssGfb777+LoUOHipCQEBEcHCy6du0q5syZ4/B7qJyArbKbb77ZIWlURbt27RIAxK5du2yJ1PLz8x2OMZvN4u233xbt2rUTSqVSNG/eXAwfPlxs2rRJCCFEeXm5GDdunNBoNCI8PFw8/vjj4t///neV3y1ZEqmh0vJwAMQDDzwghLAk6nv++edFcnKyUCqVIjIyUowePVrs37+/yrnKysqEWq0WISEhwmAw2Mp1Op0ICgoSgYGBQqfTObymuuXpAIjhw4cLISwJ2+677z7RunVroVarRVRUlLjuuuvEDz/8YDvHN998I0aOHCni4uKESqUS8fHxYvTo0WLfvn01/rs3bNggRo8eLRISEoRKpRIxMTFixIgRDvdJdfdjdYnnKt87V7pkmBBC/PDDDyI5OVkoFIoqS4ZVVNf7Q1N//yUi3yAJUc3aJERE5Dbl5eU4ffo0WrduXWUupy9JSkrC1KlTMXXqVG9XhYgIgP+8/xJR48Z1uomIiIiIiIg8hEE3ERERERERkYcwkRoREblF5ezfRERERMSebiIiIiIiIiKPYdBNRNRAmLeSiKhh8X2XiBoDBt1ERB6mVCoBWNbiJSKihmN937W+DxMReQPndBMReZhcLkd4eDhyc3MBAEFBQZAkycu1IiLyXUIIlJaWIjc3F+Hh4ZDL5d6uEhH5Ma7TTUTUAIQQyMnJQUFBgberQkTkN8LDwxEbG8sHnUTkVQy6iYgakMlkgsFg8HY1iIh8nlKpZA83ETUKDLqJiIiIiIiIPISJ1IiIiIiIiIg8hEE3ERERERERkYcw6CYiIiIiIiLyEAbdRERERERERB7CoJuIiIiIiIjIQxh0ExEREREREXkIg24iIiIiIiIiD/l/NqhSnuWK6zQAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Remove low outliers that deviate strongly from the LOWESS fit\n",
+    "\n",
+    "# Calculate residuals between the observed water area and the LOWESS-smoothed curve.\n",
+    "residuals = y - water_lowess\n",
+    "\n",
+    "# Calculate the median absolute deviation (MAD) of the residuals.\n",
+    "mad = np.median(np.abs(residuals - np.median(residuals)))  \n",
+    "\n",
+    "# Retain observations that are not unusually far below the LOWESS curve.\n",
+    "# Here, low outliers are defined as observations more than 3 MAD below the smoothed curve.\n",
+    "MAD_THRESHOLD = 3\n",
+    "mask = residuals > (-MAD_THRESHOLD * mad)\n",
+    "\n",
+    "dates_clean = np.array(dates_cloud_filtered)[mask]\n",
+    "x_clean = x[mask]\n",
+    "y_clean = y[mask]\n",
+    "\n",
+    "# Recompute LOWESS using cleaned data\n",
+    "water_lowess_clean = lowess(\n",
+    "    y_clean,\n",
+    "    x_clean,\n",
+    "    frac=0.1,\n",
+    "    return_sorted=False\n",
+    ")\n",
+    "\n",
+    "print(f\"Removed {np.sum(~mask)} low outliers\")\n",
+    "\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "\n",
+    "# Water area observations\n",
+    "plt.plot(\n",
+    "    dates_clean,\n",
+    "    y_clean,\n",
+    "    marker=\"o\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1,\n",
+    "    label=\"Open Water Area\",\n",
+    "    color=\"lightgray\"\n",
+    ")\n",
+    "\n",
+    "# Overlay the LOWESS-smoothed trend\n",
+    "plt.plot(\n",
+    "    dates_clean,\n",
+    "    water_lowess_clean,\n",
+    "    linewidth=2.5,\n",
+    "    label=\"LOWESS Smooth\",\n",
+    "    color=\"blue\"\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Open Water Area (km²)\")\n",
+    "plt.title(\"Open Water Area Through Time\")\n",
+    "plt.grid(True)\n",
+    "plt.legend(loc=\"upper center\", bbox_to_anchor=(0.5, -0.15), ncol=2)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1727382f-7606-483e-8f4f-6af262008388",
+   "metadata": {},
+   "source": [
+    "Finally, we fit a linear regression model to estimate the long-term rate of change in surface water extent.\n",
+    "\n",
+    "Because surface water exhibits a strong seasonal cycle, it is good practice to fit the linear trend over a time period that begins and ends at approximately the same time of year. Doing so minimizes the influence of seasonal variability on the estimated long-term trend, allowing the regression to better represent long-term changes in surface water extent."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "8e376627-9298-4df9-ae3e-f18af4f91e88",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Slope: -3.10 km²/year\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Fit a linear regression model to the cleaned time series\n",
+    "\n",
+    "# Define the date range used for estimating the long-term trend.\n",
+    "# The start and end dates should ideally span an integer number of years\n",
+    "# so that the regression is less influenced by seasonal variability.\n",
+    "TREND_START_DATE = \"2023-06-01\"\n",
+    "TREND_END_DATE = \"2026-05-31\"\n",
+    "\n",
+    "dates_clean = np.array(dates_clean)\n",
+    "\n",
+    "trend_start_date = datetime.strptime(TREND_START_DATE, \"%Y-%m-%d\").date()\n",
+    "trend_end_date = datetime.strptime(TREND_END_DATE, \"%Y-%m-%d\").date()\n",
+    "\n",
+    "# Select observations within the trend analysis period\n",
+    "trend_mask = (dates_clean >= trend_start_date) & (dates_clean <= trend_end_date)\n",
+    "\n",
+    "x_trend = x_clean[trend_mask]\n",
+    "y_trend = y_clean[trend_mask]\n",
+    "\n",
+    "# Fit a first-order (linear) regression model\n",
+    "slope, intercept = np.polyfit(x_trend, y_trend, 1)\n",
+    "\n",
+    "# Evaluate the fitted trend line\n",
+    "water_trend_clean = slope * x_trend + intercept\n",
+    "\n",
+    "print(f\"Slope: {slope * 365.25:.2f} km²/year\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "e3d226de-0d4d-4179-b962-75378d550689",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x500 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Plot open water area with seasonal and long-term trend lines\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "\n",
+    "# Water area observations\n",
+    "plt.plot(\n",
+    "    dates_clean,\n",
+    "    y_clean,\n",
+    "    marker=\"o\",\n",
+    "    markersize=4,\n",
+    "    linewidth=1,\n",
+    "    label=\"Open Water Area\",\n",
+    "    color=\"lightgray\"\n",
+    ")\n",
+    "\n",
+    "# Overlay the LOWESS-smoothed trend\n",
+    "plt.plot(\n",
+    "    dates_clean,\n",
+    "    water_lowess_clean,\n",
+    "    linewidth=2.5,\n",
+    "    label=\"LOWESS Smooth\",\n",
+    "    color=\"blue\"\n",
+    ")\n",
+    "\n",
+    "# Overlay the linear trend line for the selected trend analysis period\n",
+    "plt.plot(\n",
+    "    dates_clean[trend_mask],\n",
+    "    water_trend_clean,\n",
+    "    linewidth=2,\n",
+    "    linestyle=\"--\",\n",
+    "    color=\"red\",\n",
+    "    label=f\"Trend ({slope * 365.25:.1f} km²/yr)\"\n",
+    ")\n",
+    "\n",
+    "plt.xlabel(\"Date\")\n",
+    "plt.ylabel(\"Open Water Area (km²)\")\n",
+    "plt.title(\"Open Water Area Through Time\")\n",
+    "plt.grid(True)\n",
+    "plt.legend(loc=\"upper center\", bbox_to_anchor=(0.5, -0.15), ncol=3)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44295e27-bfb1-4f44-8c96-765d587cd81f",
+   "metadata": {},
+   "source": [
+    "## Conclusions\n",
+    "\n",
+    "Using OPERA DSWx-HLS observations from the Earthdata GIS (EGIS) Image Service, we constructed a quality-filtered time series of Lake Mead's open water extent and evaluated how it changed over time. After removing observations with excessive nodata, cloud cover, and statistical outliers, we applied LOWESS smoothing to visualize seasonal variability and fit a linear regression model to estimate the long-term trend.\n",
+    "\n",
+    "For the 3-year trend analysis period of `2023-06-01` through `2026-05-31`, the fitted linear regression indicates a change in open water extent of **-3.1 km² per year**. A negative slope indicates a long-term decrease in surface water extent, while a positive slope indicates an increase. This value should be interpreted within the context of the selected analysis period and reflects the average rate of change over that interval.\n",
+    "\n",
+    "Although this notebook uses Lake Mead as an example, the same workflow can be applied to any region covered by OPERA DSWx-HLS. By modifying the area of interest, date range, and filtering parameters, users can investigate seasonal and long-term changes in surface water for lakes, reservoirs, rivers, wetlands, and other hydrologic systems around the world."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/quarto_text/GIS.qmd b/quarto_text/GIS.qmd
index 0139d718..32f8b7c5 100644
--- a/quarto_text/GIS.qmd
+++ b/quarto_text/GIS.qmd
@@ -34,6 +34,7 @@ Tutorials
 
 - OPERA L3 DSWX-HLS_V1 - [EGIS Access Guide](../notebooks/GIS/OPERA_EGIS_access.ipynb)
 - OPERA L3 DSWX-HLS_V1 - [EGIS Python Guide](../notebooks/GIS/OPERA_EGIS_access_Python.ipynb)
+- OPERA L3 DSWX-HLS_V1 - [EGIS Python Guide: Lake Mead Time Series Analysis](../notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb
 
 ## **StoryMaps**
 
diff --git a/quarto_text/OPERA.qmd b/quarto_text/OPERA.qmd
index d26d0a92..0626c6ed 100644
--- a/quarto_text/OPERA.qmd
+++ b/quarto_text/OPERA.qmd
@@ -54,6 +54,7 @@ podaac-data-subscriber -c OPERA_L3_DSWX-HLS_V1 -d ./data/OPERA_L3_DSWX-HLS_V1 --
 - OPERA L3 DSWX-HLS_V1 EGIS - [EGIS Services Endpoints List](../notebooks/GIS/OPERA_DSWx-HLS_EGIS_Services.md)
 - OPERA L3 DSWX-HLS_V1 EGIS - [Access](../notebooks/GIS/OPERA_EGIS_access.ipynb)
 - OPERA L3 DSWX-HLS_V1 EGIS - [Access with Python](../notebooks/GIS/OPERA_EGIS_access_Python.ipynb)
+- OPERA L3 DSWX-HLS_V1 EGIS - [Science with Python: Lake Mead Time Series Analysis](../notebooks/GIS/OPERA_EGIS_access_Python_LakeMead_timeseries.ipynb
 
 [**StoryMap**: Exploring Water Surface Extent with Satellite Data](https://storymaps.arcgis.com/collections/413c17cba4b44be18e445c1caaf03fff?item=1)
 
diff --git a/quarto_text/SWOT.qmd b/quarto_text/SWOT.qmd
index 008449bc..e264178e 100644
--- a/quarto_text/SWOT.qmd
+++ b/quarto_text/SWOT.qmd
@@ -135,7 +135,7 @@ Basic Access SWOT Oceanography data [in the cloud](../notebooks/datasets/DirectC
 
 SWOT Raster Multifile Access & Quality Flag Application [in the cloud](../notebooks/datasets/SWOT_Raster_Notebook_cloud.ipynb) | [locally](../notebooks/datasets/SWOT_Raster_Notebook_local.ipynb)
 
-[Hydrocron: Time series API Multi-reach tutorial](../notebooks/datasets/Hydrocron_SWOT_timeseries_examples.ipynb) - See [Hydrocron documentation](https://podaac.github.io/hydrocron/intro.html) and more description under tools below. [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11176233.svg)](https://doi.org/10.5281/zenodo.11176233)
+[Hydrocron: Time series API multi-reach tutorial](../notebooks/datasets/Hydrocron_SWOT_timeseries_examples_basic.ipynb) - See [Hydrocron documentation](https://podaac.github.io/hydrocron/) and more description under tools below. [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11176233.svg)](https://doi.org/10.5281/zenodo.11176233)
 
 SWOT Pixel Cloud (PIXC) Area Aggregation [locally](../notebooks/datasets/SWOT_PIXC_Area_localmachine.ipynb)
 
@@ -197,7 +197,7 @@ Below are data resources to support the user in learning about, accessing and ap
 
 [HiTIDE subsetter for Sea Surface Height Products](https://hitide.podaac.earthdatacloud.nasa.gov/) - select KaRIn instrument in `sensors`, see video tutorial [here](https://www.youtube.com/watch?v=S8MIHltlwWA)
 
-[Hydrocron: Time series API](../notebooks/datasets/Hydrocron_SWOT_timeseries_examples.ipynb) - Currently for rivers and lakes see [Hydrocron documentation](https://podaac.github.io/hydrocron/intro.html) and more description under tools below. [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11176233.svg)](https://doi.org/10.5281/zenodo.11176233)
+[Hydrocron: Time series API](../notebooks/datasets/Hydrocron_SWOT_timeseries_examples_basic.ipynb) - Currently for rivers and lakes see [Hydrocron documentation](https://podaac.github.io/hydrocron/) and more description under tools below. [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11176233.svg)](https://doi.org/10.5281/zenodo.11176233)
 
 [Transform SWOT Hydrology lake shapefiles into time series](../notebooks/GIS/SWOTshp_CSVconversion.ipynb) - work around for lake time series while Hydrocron is under development to include lakes.
 
@@ -205,7 +205,7 @@ NetCDF to Geotiff Conversion - [mac or Linux](../notebooks/GIS/Subscriber_nc_to_
 
 ### **Tools**
 
-[Hydrocron](https://podaac.github.io/hydrocron/intro.html) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11193245.svg)](https://doi.org/10.5281/zenodo.11193245) - an API that repackages the river (L2_HR_RiverSP) and lake (L2_HR_LakeSP) shapefile datasets into csv or GeoJSON formats that make time-series analysis easier. SWOT data is archived as individually timestamped shapefiles, which would otherwise require users to perform potentially thousands of file operations per feature to view the data as a timeseries. Hydrocron makes this possible with a single API call. 
+[Hydrocron](https://podaac.github.io/hydrocron/) [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11193245.svg)](https://doi.org/10.5281/zenodo.11193245) - an API that repackages the river (L2_HR_RiverSP) and lake (L2_HR_LakeSP) shapefile datasets into csv or GeoJSON formats that make time-series analysis easier. SWOT data is archived as individually timestamped shapefiles, which would otherwise require users to perform potentially thousands of file operations per feature to view the data as a timeseries. Hydrocron makes this possible with a single API call. 
 
 [WISP (Water Information from SPace) by USGS](https://apps.usgs.gov/wisp) - developed by USGS, leverages Hydrocron to provide interactive visualization and download of SWOT HR L2 data alongside USGS gauge measurements.