diff --git a/HydroDF_Analysis.ipynb b/HydroDF_Analysis.ipynb
index 3c2bef7..4c7768b 100644
--- a/HydroDF_Analysis.ipynb
+++ b/HydroDF_Analysis.ipynb
@@ -74,10 +74,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "TUM: 15288 start date: 1980-01-10 00:00:00 end date: 2021-11-17 00:00:00\n",
-      "DAN: 14936 start date: 1980-10-26 00:00:00 end date: 2021-09-16 00:00:00\n",
-      "SLI: 14273 start date: 1982-10-21 00:00:00 end date: 2021-11-17 00:00:00\n",
-      "TES: 629 start date: 2005-03-01 00:00:00 end date: 2006-11-19 00:00:00\n"
+      "596: 13767 start date: 1988-06-23 00:00:00 end date: 2026-03-02 00:00:00\n",
+      "628: 13667 start date: 1988-10-01 00:00:00 end date: 2026-03-02 00:00:00\n",
+      "684: 17320 start date: 1978-10-01 00:00:00 end date: 2026-03-02 00:00:00\n",
+      "971: 9650 start date: 1999-10-01 00:00:00 end date: 2026-03-02 00:00:00\n",
+      "DAN: 6195 start date: 2004-10-01 00:00:00 end date: 2021-09-16 00:00:00\n",
+      "SLI: 5892 start date: 2005-10-01 00:00:00 end date: 2021-11-17 00:00:00\n",
+      "TES: 629 start date: 2005-03-01 00:00:00 end date: 2006-11-19 00:00:00\n",
+      "TUM: 6257 start date: 2004-10-01 00:00:00 end date: 2021-11-17 00:00:00\n"
      ]
     }
    ],
@@ -132,60 +136,96 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date</th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1982-10-21</th>\n",
-       "      <td>0.000</td>\n",
-       "      <td>NaN</td>\n",
+       "      <th>2005-10-01</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1982-10-22</th>\n",
-       "      <td>0.508</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.286</td>\n",
+       "      <th>2005-10-02</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1982-10-23</th>\n",
-       "      <td>1.270</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.286</td>\n",
+       "      <th>2005-10-03</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1982-10-24</th>\n",
-       "      <td>1.778</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.286</td>\n",
+       "      <th>2005-10-04</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1982-10-25</th>\n",
+       "      <th>2005-10-05</th>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>2.032</td>\n",
-       "      <td>NaN</td>\n",
-       "      <td>2.540</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "            TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm\n",
-       "Date                                          \n",
-       "1982-10-21       0.000         NaN       0.000\n",
-       "1982-10-22       0.508         NaN       2.286\n",
-       "1982-10-23       1.270         NaN       2.286\n",
-       "1982-10-24       1.778         NaN       2.286\n",
-       "1982-10-25       2.032         NaN       2.540"
+       "            596_SWE_cm  628_SWE_cm  684_SWE_cm  971_SWE_cm  DAN_SWE_cm  \\\n",
+       "Date                                                                     \n",
+       "2005-10-01         0.0         0.0         0.0       0.000         0.0   \n",
+       "2005-10-02         0.0         0.0         0.0       0.000         0.0   \n",
+       "2005-10-03         0.0         0.0         0.0       0.000         0.0   \n",
+       "2005-10-04         0.0         0.0         0.0       0.000         0.0   \n",
+       "2005-10-05         0.0         0.0         0.0       2.032         0.0   \n",
+       "\n",
+       "            SLI_SWE_cm  TUM_SWE_cm  \n",
+       "Date                                \n",
+       "2005-10-01         0.0         0.0  \n",
+       "2005-10-02         0.0         0.0  \n",
+       "2005-10-03         0.0         0.0  \n",
+       "2005-10-04         0.0         0.0  \n",
+       "2005-10-05         0.0         0.0  "
       ]
      },
      "execution_count": 4,
@@ -396,6 +436,7 @@
        "      <th>total_precipitation</th>\n",
        "      <th>wind_u</th>\n",
        "      <th>wind_v</th>\n",
+       "      <th>Date.1</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date</th>\n",
@@ -410,6 +451,7 @@
        "      <th></th>\n",
        "      <th></th>\n",
        "      <th></th>\n",
+       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
@@ -426,6 +468,7 @@
        "      <td>0.563703</td>\n",
        "      <td>2.807882</td>\n",
        "      <td>5.710911</td>\n",
+       "      <td>2006-01-01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-01-02</th>\n",
@@ -440,6 +483,7 @@
        "      <td>4.532128</td>\n",
        "      <td>4.467674</td>\n",
        "      <td>8.864378</td>\n",
+       "      <td>2006-01-02</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-01-03</th>\n",
@@ -454,6 +498,7 @@
        "      <td>0.575387</td>\n",
        "      <td>4.247262</td>\n",
        "      <td>3.778855</td>\n",
+       "      <td>2006-01-03</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-01-04</th>\n",
@@ -468,6 +513,7 @@
        "      <td>0.002358</td>\n",
        "      <td>1.485389</td>\n",
        "      <td>1.450410</td>\n",
+       "      <td>2006-01-04</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-01-05</th>\n",
@@ -482,6 +528,7 @@
        "      <td>0.000000</td>\n",
        "      <td>-0.779809</td>\n",
        "      <td>3.417216</td>\n",
+       "      <td>2006-01-05</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -512,13 +559,13 @@
        "2006-01-04           0.003240    -3.462835             0.002358  1.485389   \n",
        "2006-01-05           0.002849     1.320337             0.000000 -0.779809   \n",
        "\n",
-       "              wind_v  \n",
-       "Date                  \n",
-       "2006-01-01  5.710911  \n",
-       "2006-01-02  8.864378  \n",
-       "2006-01-03  3.778855  \n",
-       "2006-01-04  1.450410  \n",
-       "2006-01-05  3.417216  "
+       "              wind_v      Date.1  \n",
+       "Date                              \n",
+       "2006-01-01  5.710911  2006-01-01  \n",
+       "2006-01-02  8.864378  2006-01-02  \n",
+       "2006-01-03  3.778855  2006-01-03  \n",
+       "2006-01-04  1.450410  2006-01-04  \n",
+       "2006-01-05  3.417216  2006-01-05  "
       ]
      },
      "execution_count": 6,
@@ -568,53 +615,46 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Date</th>\n",
        "      <th></th>\n",
-       "      <th></th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2006-10-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.611643</td>\n",
+       "      <td>21.6</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.563504</td>\n",
+       "      <td>19.9</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.538019</td>\n",
+       "      <td>19.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.504039</td>\n",
+       "      <td>17.8</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-17</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.481386</td>\n",
+       "      <td>17.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no  flow_cms\n",
-       "Date                          \n",
-       "2006-10-13  11274790  0.611643\n",
-       "2006-10-14  11274790  0.563504\n",
-       "2006-10-15  11274790  0.538019\n",
-       "2006-10-16  11274790  0.504039\n",
-       "2006-10-17  11274790  0.481386"
+       "            Streamflow_cfs\n",
+       "Date                      \n",
+       "2006-10-13            21.6\n",
+       "2006-10-14            19.9\n",
+       "2006-10-15            19.0\n",
+       "2006-10-16            17.8\n",
+       "2006-10-17            17.0"
       ]
      },
      "execution_count": 7,
@@ -692,25 +732,25 @@
        "      <th>0</th>\n",
        "      <td>TuolumneRiverBasin</td>\n",
        "      <td>11274790</td>\n",
-       "      <td>2847.0938</td>\n",
+       "      <td>2847.0945</td>\n",
        "      <td>1165.1238</td>\n",
        "      <td>3972.5696</td>\n",
        "      <td>0.392479</td>\n",
-       "      <td>1249.464814</td>\n",
-       "      <td>0.745168</td>\n",
-       "      <td>0.374508</td>\n",
-       "      <td>0.071823</td>\n",
+       "      <td>1249.479609</td>\n",
+       "      <td>0.746451</td>\n",
+       "      <td>0.373225</td>\n",
+       "      <td>0.070541</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -719,25 +759,25 @@
       ],
       "text/plain": [
        "           Unnamed: 0  station_id  Average_Elevation_m  Minimum_Elevation_m  \\\n",
-       "0  TuolumneRiverBasin    11274790            2847.0938            1165.1238   \n",
+       "0  TuolumneRiverBasin    11274790            2847.0945            1165.1238   \n",
        "\n",
        "   Maximum_Elevation_m  Average_Slope     Area_km2  Open_Water  \\\n",
-       "0            3972.5696       0.392479  1249.464814    0.745168   \n",
+       "0            3972.5696       0.392479  1249.479609    0.746451   \n",
        "\n",
        "   Perennial_Ice_Snow  Developed,_Open_Space  ...  \\\n",
-       "0            0.374508               0.071823  ...   \n",
+       "0            0.373225               0.070541  ...   \n",
        "\n",
        "   Developed,_Medium_Intensity  Developed,_High_Intensity  \\\n",
        "0                     0.008978                   0.006413   \n",
        "\n",
        "   Barren_Land_Rock_Sand_Clay  Deciduous_Forest  Evergreen_Forest  \\\n",
-       "0                    8.326386           0.01026         37.994588   \n",
+       "0                    8.318691           0.01026         38.011261   \n",
        "\n",
        "   Mixed_Forest  Shrub_Scrub  Grassland_Herbaceous  Woody_Wetlands  \\\n",
-       "0      0.002565    45.493722              5.055856        0.638715   \n",
+       "0      0.002565    45.479614              5.066116        0.637433   \n",
        "\n",
        "   Emergent_Herbaceous_Wetlands  \n",
-       "0                      1.233824  \n",
+       "0                      1.231259  \n",
        "\n",
        "[1 rows x 21 columns]"
       ]
@@ -802,16 +842,16 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>Date.1</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "      <th>dayl_s</th>\n",
-       "      <th>prcp_mm_day</th>\n",
-       "      <th>srad_W_m2</th>\n",
-       "      <th>swe_cm</th>\n",
-       "      <th>tmax_C</th>\n",
        "      <th>...</th>\n",
        "      <th>longwave_radiation</th>\n",
        "      <th>potential_energy</th>\n",
@@ -852,16 +892,16 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2006-10-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.611643</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-13</td>\n",
+       "      <td>21.6</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39849.51</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>335.15</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.52</td>\n",
+       "      <td>39849.51</td>\n",
        "      <td>...</td>\n",
        "      <td>223.457644</td>\n",
        "      <td>0.038401</td>\n",
@@ -876,16 +916,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.563504</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-14</td>\n",
+       "      <td>19.9</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39705.43</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>368.37</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.76</td>\n",
+       "      <td>39705.43</td>\n",
        "      <td>...</td>\n",
        "      <td>219.173461</td>\n",
        "      <td>0.027793</td>\n",
@@ -900,16 +940,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.538019</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-15</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39562.00</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>402.91</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>15.72</td>\n",
+       "      <td>39562.00</td>\n",
        "      <td>...</td>\n",
        "      <td>221.013230</td>\n",
        "      <td>0.000000</td>\n",
@@ -924,16 +964,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.504039</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-16</td>\n",
+       "      <td>17.8</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39419.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>342.84</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>9.39</td>\n",
+       "      <td>39419.27</td>\n",
        "      <td>...</td>\n",
        "      <td>212.436870</td>\n",
        "      <td>0.624320</td>\n",
@@ -948,16 +988,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-17</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.481386</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-17</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.508</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>2.032</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39277.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>327.94</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>5.66</td>\n",
+       "      <td>39277.27</td>\n",
        "      <td>...</td>\n",
        "      <td>187.458054</td>\n",
        "      <td>4.542329</td>\n",
@@ -972,41 +1012,41 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 24 columns</p>\n",
+       "<p>5 rows × 28 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no  flow_cms  TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm    dayl_s  \\\n",
-       "Date                                                                           \n",
-       "2006-10-13  11274790  0.611643         0.0         0.0         0.0  39849.51   \n",
-       "2006-10-14  11274790  0.563504         0.0         0.0         0.0  39705.43   \n",
-       "2006-10-15  11274790  0.538019         0.0         0.0         0.0  39562.00   \n",
-       "2006-10-16  11274790  0.504039         0.0         0.0         0.0  39419.27   \n",
-       "2006-10-17  11274790  0.481386         0.0         0.0         0.0  39277.27   \n",
+       "                Date.1  Streamflow_cfs  596_SWE_cm  628_SWE_cm  684_SWE_cm  \\\n",
+       "Date                                                                         \n",
+       "2006-10-13  2006-10-13            21.6       0.000       0.000         0.0   \n",
+       "2006-10-14  2006-10-14            19.9       0.000       0.000         0.0   \n",
+       "2006-10-15  2006-10-15            19.0       0.000       0.000         0.0   \n",
+       "2006-10-16  2006-10-16            17.8       0.000       0.000         0.0   \n",
+       "2006-10-17  2006-10-17            17.0       0.508       0.508         0.0   \n",
        "\n",
-       "            prcp_mm_day  srad_W_m2  swe_cm  tmax_C  ...  longwave_radiation  \\\n",
-       "Date                                                ...                       \n",
-       "2006-10-13          0.0     335.15     0.0   12.52  ...          223.457644   \n",
-       "2006-10-14          0.0     368.37     0.0   12.76  ...          219.173461   \n",
-       "2006-10-15          0.0     402.91     0.0   15.72  ...          221.013230   \n",
-       "2006-10-16          0.0     342.84     0.0    9.39  ...          212.436870   \n",
-       "2006-10-17          0.0     327.94     0.0    5.66  ...          187.458054   \n",
+       "            971_SWE_cm  DAN_SWE_cm  SLI_SWE_cm  TUM_SWE_cm    dayl_s  ...  \\\n",
+       "Date                                                                  ...   \n",
+       "2006-10-13       0.000         0.0         0.0         0.0  39849.51  ...   \n",
+       "2006-10-14       0.000         0.0         0.0         0.0  39705.43  ...   \n",
+       "2006-10-15       0.000         0.0         0.0         0.0  39562.00  ...   \n",
+       "2006-10-16       0.000         0.0         0.0         0.0  39419.27  ...   \n",
+       "2006-10-17       2.032         0.0         0.0         0.0  39277.27  ...   \n",
        "\n",
-       "            potential_energy  potential_evaporation      pressure  \\\n",
-       "Date                                                                \n",
-       "2006-10-13          0.038401               0.139839  72107.765879   \n",
-       "2006-10-14          0.027793               0.143067  71877.921092   \n",
-       "2006-10-15          0.000000               0.156591  72003.823920   \n",
-       "2006-10-16          0.624320               0.159340  71788.350428   \n",
-       "2006-10-17          4.542329               0.116995  71563.357945   \n",
+       "            longwave_radiation  potential_energy  potential_evaporation  \\\n",
+       "Date                                                                      \n",
+       "2006-10-13          223.457644          0.038401               0.139839   \n",
+       "2006-10-14          219.173461          0.027793               0.143067   \n",
+       "2006-10-15          221.013230          0.000000               0.156591   \n",
+       "2006-10-16          212.436870          0.624320               0.159340   \n",
+       "2006-10-17          187.458054          4.542329               0.116995   \n",
        "\n",
-       "            shortwave_radiation  specific_humidity  temperature  \\\n",
-       "Date                                                              \n",
-       "2006-10-13           174.191132           0.003637     4.295980   \n",
-       "2006-10-14           190.454843           0.004275     3.669391   \n",
-       "2006-10-15           180.353373           0.003437     5.069112   \n",
-       "2006-10-16           190.753002           0.003852     3.643004   \n",
-       "2006-10-17           188.902233           0.002838    -2.503130   \n",
+       "                pressure  shortwave_radiation  specific_humidity  temperature  \\\n",
+       "Date                                                                            \n",
+       "2006-10-13  72107.765879           174.191132           0.003637     4.295980   \n",
+       "2006-10-14  71877.921092           190.454843           0.004275     3.669391   \n",
+       "2006-10-15  72003.823920           180.353373           0.003437     5.069112   \n",
+       "2006-10-16  71788.350428           190.753002           0.003852     3.643004   \n",
+       "2006-10-17  71563.357945           188.902233           0.002838    -2.503130   \n",
        "\n",
        "            total_precipitation    wind_u    wind_v  \n",
        "Date                                                 \n",
@@ -1016,7 +1056,7 @@
        "2006-10-16             0.001124  4.436657 -0.672672  \n",
        "2006-10-17             0.004309  1.149626 -2.636144  \n",
        "\n",
-       "[5 rows x 24 columns]"
+       "[5 rows x 28 columns]"
       ]
      },
      "execution_count": 10,
@@ -1060,16 +1100,16 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>Date.1</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "      <th>dayl_s</th>\n",
-       "      <th>prcp_mm_day</th>\n",
-       "      <th>srad_W_m2</th>\n",
-       "      <th>swe_cm</th>\n",
-       "      <th>tmax_C</th>\n",
        "      <th>...</th>\n",
        "      <th>longwave_radiation</th>\n",
        "      <th>potential_energy</th>\n",
@@ -1110,16 +1150,16 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2006-10-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.611643</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-13</td>\n",
+       "      <td>21.6</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39849.51</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>335.15</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.52</td>\n",
+       "      <td>39849.51</td>\n",
        "      <td>...</td>\n",
        "      <td>223.457644</td>\n",
        "      <td>0.038401</td>\n",
@@ -1134,16 +1174,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.563504</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-14</td>\n",
+       "      <td>19.9</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39705.43</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>368.37</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.76</td>\n",
+       "      <td>39705.43</td>\n",
        "      <td>...</td>\n",
        "      <td>219.173461</td>\n",
        "      <td>0.027793</td>\n",
@@ -1158,16 +1198,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.538019</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-15</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39562.00</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>402.91</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>15.72</td>\n",
+       "      <td>39562.00</td>\n",
        "      <td>...</td>\n",
        "      <td>221.013230</td>\n",
        "      <td>0.000000</td>\n",
@@ -1182,16 +1222,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.504039</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-16</td>\n",
+       "      <td>17.8</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39419.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>342.84</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>9.39</td>\n",
+       "      <td>39419.27</td>\n",
        "      <td>...</td>\n",
        "      <td>212.436870</td>\n",
        "      <td>0.624320</td>\n",
@@ -1206,16 +1246,16 @@
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-17</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.481386</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-17</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.508</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>2.032</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39277.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>327.94</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>5.66</td>\n",
+       "      <td>39277.27</td>\n",
        "      <td>...</td>\n",
        "      <td>187.458054</td>\n",
        "      <td>4.542329</td>\n",
@@ -1230,41 +1270,41 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 24 columns</p>\n",
+       "<p>5 rows × 28 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no  flow_cms  TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm    dayl_s  \\\n",
-       "Date                                                                           \n",
-       "2006-10-13  11274790  0.611643         0.0         0.0         0.0  39849.51   \n",
-       "2006-10-14  11274790  0.563504         0.0         0.0         0.0  39705.43   \n",
-       "2006-10-15  11274790  0.538019         0.0         0.0         0.0  39562.00   \n",
-       "2006-10-16  11274790  0.504039         0.0         0.0         0.0  39419.27   \n",
-       "2006-10-17  11274790  0.481386         0.0         0.0         0.0  39277.27   \n",
+       "                Date.1  Streamflow_cfs  596_SWE_cm  628_SWE_cm  684_SWE_cm  \\\n",
+       "Date                                                                         \n",
+       "2006-10-13  2006-10-13            21.6       0.000       0.000         0.0   \n",
+       "2006-10-14  2006-10-14            19.9       0.000       0.000         0.0   \n",
+       "2006-10-15  2006-10-15            19.0       0.000       0.000         0.0   \n",
+       "2006-10-16  2006-10-16            17.8       0.000       0.000         0.0   \n",
+       "2006-10-17  2006-10-17            17.0       0.508       0.508         0.0   \n",
        "\n",
-       "            prcp_mm_day  srad_W_m2  swe_cm  tmax_C  ...  longwave_radiation  \\\n",
-       "Date                                                ...                       \n",
-       "2006-10-13          0.0     335.15     0.0   12.52  ...          223.457644   \n",
-       "2006-10-14          0.0     368.37     0.0   12.76  ...          219.173461   \n",
-       "2006-10-15          0.0     402.91     0.0   15.72  ...          221.013230   \n",
-       "2006-10-16          0.0     342.84     0.0    9.39  ...          212.436870   \n",
-       "2006-10-17          0.0     327.94     0.0    5.66  ...          187.458054   \n",
+       "            971_SWE_cm  DAN_SWE_cm  SLI_SWE_cm  TUM_SWE_cm    dayl_s  ...  \\\n",
+       "Date                                                                  ...   \n",
+       "2006-10-13       0.000         0.0         0.0         0.0  39849.51  ...   \n",
+       "2006-10-14       0.000         0.0         0.0         0.0  39705.43  ...   \n",
+       "2006-10-15       0.000         0.0         0.0         0.0  39562.00  ...   \n",
+       "2006-10-16       0.000         0.0         0.0         0.0  39419.27  ...   \n",
+       "2006-10-17       2.032         0.0         0.0         0.0  39277.27  ...   \n",
        "\n",
-       "            potential_energy  potential_evaporation      pressure  \\\n",
-       "Date                                                                \n",
-       "2006-10-13          0.038401               0.139839  72107.765879   \n",
-       "2006-10-14          0.027793               0.143067  71877.921092   \n",
-       "2006-10-15          0.000000               0.156591  72003.823920   \n",
-       "2006-10-16          0.624320               0.159340  71788.350428   \n",
-       "2006-10-17          4.542329               0.116995  71563.357945   \n",
+       "            longwave_radiation  potential_energy  potential_evaporation  \\\n",
+       "Date                                                                      \n",
+       "2006-10-13          223.457644          0.038401               0.139839   \n",
+       "2006-10-14          219.173461          0.027793               0.143067   \n",
+       "2006-10-15          221.013230          0.000000               0.156591   \n",
+       "2006-10-16          212.436870          0.624320               0.159340   \n",
+       "2006-10-17          187.458054          4.542329               0.116995   \n",
        "\n",
-       "            shortwave_radiation  specific_humidity  temperature  \\\n",
-       "Date                                                              \n",
-       "2006-10-13           174.191132           0.003637     4.295980   \n",
-       "2006-10-14           190.454843           0.004275     3.669391   \n",
-       "2006-10-15           180.353373           0.003437     5.069112   \n",
-       "2006-10-16           190.753002           0.003852     3.643004   \n",
-       "2006-10-17           188.902233           0.002838    -2.503130   \n",
+       "                pressure  shortwave_radiation  specific_humidity  temperature  \\\n",
+       "Date                                                                            \n",
+       "2006-10-13  72107.765879           174.191132           0.003637     4.295980   \n",
+       "2006-10-14  71877.921092           190.454843           0.004275     3.669391   \n",
+       "2006-10-15  72003.823920           180.353373           0.003437     5.069112   \n",
+       "2006-10-16  71788.350428           190.753002           0.003852     3.643004   \n",
+       "2006-10-17  71563.357945           188.902233           0.002838    -2.503130   \n",
        "\n",
        "            total_precipitation    wind_u    wind_v  \n",
        "Date                                                 \n",
@@ -1274,7 +1314,7 @@
        "2006-10-16             0.001124  4.436657 -0.672672  \n",
        "2006-10-17             0.004309  1.149626 -2.636144  \n",
        "\n",
-       "[5 rows x 24 columns]"
+       "[5 rows x 28 columns]"
       ]
      },
      "execution_count": 11,
@@ -1314,16 +1354,16 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>Date.1</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "      <th>dayl_s</th>\n",
-       "      <th>prcp_mm_day</th>\n",
-       "      <th>srad_W_m2</th>\n",
-       "      <th>swe_cm</th>\n",
-       "      <th>tmax_C</th>\n",
        "      <th>...</th>\n",
        "      <th>Developed,_Medium_Intensity</th>\n",
        "      <th>Developed,_High_Intensity</th>\n",
@@ -1364,145 +1404,145 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2006-10-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.611643</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-13</td>\n",
+       "      <td>21.6</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39849.51</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>335.15</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.52</td>\n",
+       "      <td>39849.51</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.563504</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-14</td>\n",
+       "      <td>19.9</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39705.43</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>368.37</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>12.76</td>\n",
+       "      <td>39705.43</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.538019</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-15</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39562.00</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>402.91</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>15.72</td>\n",
+       "      <td>39562.00</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.504039</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-16</td>\n",
+       "      <td>17.8</td>\n",
+       "      <td>0.000</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>0.000</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39419.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>342.84</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>9.39</td>\n",
+       "      <td>39419.27</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2006-10-17</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.481386</td>\n",
-       "      <td>0.0</td>\n",
+       "      <td>2006-10-17</td>\n",
+       "      <td>17.0</td>\n",
+       "      <td>0.508</td>\n",
+       "      <td>0.508</td>\n",
        "      <td>0.0</td>\n",
+       "      <td>2.032</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>39277.27</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>327.94</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>5.66</td>\n",
+       "      <td>39277.27</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 45 columns</p>\n",
+       "<p>5 rows × 49 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no  flow_cms  TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm    dayl_s  \\\n",
-       "Date                                                                           \n",
-       "2006-10-13  11274790  0.611643         0.0         0.0         0.0  39849.51   \n",
-       "2006-10-14  11274790  0.563504         0.0         0.0         0.0  39705.43   \n",
-       "2006-10-15  11274790  0.538019         0.0         0.0         0.0  39562.00   \n",
-       "2006-10-16  11274790  0.504039         0.0         0.0         0.0  39419.27   \n",
-       "2006-10-17  11274790  0.481386         0.0         0.0         0.0  39277.27   \n",
+       "                Date.1  Streamflow_cfs  596_SWE_cm  628_SWE_cm  684_SWE_cm  \\\n",
+       "Date                                                                         \n",
+       "2006-10-13  2006-10-13            21.6       0.000       0.000         0.0   \n",
+       "2006-10-14  2006-10-14            19.9       0.000       0.000         0.0   \n",
+       "2006-10-15  2006-10-15            19.0       0.000       0.000         0.0   \n",
+       "2006-10-16  2006-10-16            17.8       0.000       0.000         0.0   \n",
+       "2006-10-17  2006-10-17            17.0       0.508       0.508         0.0   \n",
        "\n",
-       "            prcp_mm_day  srad_W_m2  swe_cm  tmax_C  ...  \\\n",
-       "Date                                                ...   \n",
-       "2006-10-13          0.0     335.15     0.0   12.52  ...   \n",
-       "2006-10-14          0.0     368.37     0.0   12.76  ...   \n",
-       "2006-10-15          0.0     402.91     0.0   15.72  ...   \n",
-       "2006-10-16          0.0     342.84     0.0    9.39  ...   \n",
-       "2006-10-17          0.0     327.94     0.0    5.66  ...   \n",
+       "            971_SWE_cm  DAN_SWE_cm  SLI_SWE_cm  TUM_SWE_cm    dayl_s  ...  \\\n",
+       "Date                                                                  ...   \n",
+       "2006-10-13       0.000         0.0         0.0         0.0  39849.51  ...   \n",
+       "2006-10-14       0.000         0.0         0.0         0.0  39705.43  ...   \n",
+       "2006-10-15       0.000         0.0         0.0         0.0  39562.00  ...   \n",
+       "2006-10-16       0.000         0.0         0.0         0.0  39419.27  ...   \n",
+       "2006-10-17       2.032         0.0         0.0         0.0  39277.27  ...   \n",
        "\n",
        "            Developed,_Medium_Intensity  Developed,_High_Intensity  \\\n",
        "Date                                                                 \n",
@@ -1514,29 +1554,29 @@
        "\n",
        "            Barren_Land_Rock_Sand_Clay  Deciduous_Forest  Evergreen_Forest  \\\n",
        "Date                                                                         \n",
-       "2006-10-13                    8.326386           0.01026         37.994588   \n",
-       "2006-10-14                    8.326386           0.01026         37.994588   \n",
-       "2006-10-15                    8.326386           0.01026         37.994588   \n",
-       "2006-10-16                    8.326386           0.01026         37.994588   \n",
-       "2006-10-17                    8.326386           0.01026         37.994588   \n",
+       "2006-10-13                    8.318691           0.01026         38.011261   \n",
+       "2006-10-14                    8.318691           0.01026         38.011261   \n",
+       "2006-10-15                    8.318691           0.01026         38.011261   \n",
+       "2006-10-16                    8.318691           0.01026         38.011261   \n",
+       "2006-10-17                    8.318691           0.01026         38.011261   \n",
        "\n",
        "            Mixed_Forest  Shrub_Scrub  Grassland_Herbaceous  Woody_Wetlands  \\\n",
        "Date                                                                          \n",
-       "2006-10-13      0.002565    45.493722              5.055856        0.638715   \n",
-       "2006-10-14      0.002565    45.493722              5.055856        0.638715   \n",
-       "2006-10-15      0.002565    45.493722              5.055856        0.638715   \n",
-       "2006-10-16      0.002565    45.493722              5.055856        0.638715   \n",
-       "2006-10-17      0.002565    45.493722              5.055856        0.638715   \n",
+       "2006-10-13      0.002565    45.479614              5.066116        0.637433   \n",
+       "2006-10-14      0.002565    45.479614              5.066116        0.637433   \n",
+       "2006-10-15      0.002565    45.479614              5.066116        0.637433   \n",
+       "2006-10-16      0.002565    45.479614              5.066116        0.637433   \n",
+       "2006-10-17      0.002565    45.479614              5.066116        0.637433   \n",
        "\n",
        "            Emergent_Herbaceous_Wetlands  \n",
        "Date                                      \n",
-       "2006-10-13                      1.233824  \n",
-       "2006-10-14                      1.233824  \n",
-       "2006-10-15                      1.233824  \n",
-       "2006-10-16                      1.233824  \n",
-       "2006-10-17                      1.233824  \n",
+       "2006-10-13                      1.231259  \n",
+       "2006-10-14                      1.231259  \n",
+       "2006-10-15                      1.231259  \n",
+       "2006-10-16                      1.231259  \n",
+       "2006-10-17                      1.231259  \n",
        "\n",
-       "[5 rows x 45 columns]"
+       "[5 rows x 49 columns]"
       ]
      },
      "execution_count": 12,
@@ -1578,16 +1618,16 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>Date.1</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "      <th>dayl_s</th>\n",
-       "      <th>prcp_mm_day</th>\n",
-       "      <th>srad_W_m2</th>\n",
-       "      <th>swe_cm</th>\n",
-       "      <th>tmax_C</th>\n",
        "      <th>...</th>\n",
        "      <th>Developed,_Medium_Intensity</th>\n",
        "      <th>Developed,_High_Intensity</th>\n",
@@ -1628,847 +1668,847 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2019-03-01</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.909299</td>\n",
-       "      <td>74.422</td>\n",
+       "      <td>2019-03-01</td>\n",
+       "      <td>244.0</td>\n",
+       "      <td>64.770</td>\n",
+       "      <td>61.722</td>\n",
+       "      <td>41.402</td>\n",
+       "      <td>60.198</td>\n",
        "      <td>82.296</td>\n",
        "      <td>122.936</td>\n",
+       "      <td>74.422</td>\n",
        "      <td>40066.17</td>\n",
-       "      <td>14.08</td>\n",
-       "      <td>280.15</td>\n",
-       "      <td>40.505</td>\n",
-       "      <td>3.27</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-02</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>11.071869</td>\n",
-       "      <td>75.184</td>\n",
+       "      <td>2019-03-02</td>\n",
+       "      <td>391.0</td>\n",
+       "      <td>65.278</td>\n",
+       "      <td>61.722</td>\n",
+       "      <td>41.656</td>\n",
+       "      <td>61.214</td>\n",
        "      <td>83.058</td>\n",
        "      <td>124.460</td>\n",
+       "      <td>75.184</td>\n",
        "      <td>40211.76</td>\n",
-       "      <td>28.55</td>\n",
-       "      <td>185.59</td>\n",
-       "      <td>40.371</td>\n",
-       "      <td>1.44</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-03</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>10.618800</td>\n",
-       "      <td>78.486</td>\n",
+       "      <td>2019-03-03</td>\n",
+       "      <td>375.0</td>\n",
+       "      <td>66.294</td>\n",
+       "      <td>63.246</td>\n",
+       "      <td>42.926</td>\n",
+       "      <td>62.484</td>\n",
        "      <td>86.868</td>\n",
        "      <td>128.524</td>\n",
+       "      <td>78.486</td>\n",
        "      <td>40357.90</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>477.81</td>\n",
-       "      <td>40.320</td>\n",
-       "      <td>3.90</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-04</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>9.854246</td>\n",
-       "      <td>78.232</td>\n",
+       "      <td>2019-03-04</td>\n",
+       "      <td>348.0</td>\n",
+       "      <td>66.548</td>\n",
+       "      <td>64.008</td>\n",
+       "      <td>43.180</td>\n",
+       "      <td>62.738</td>\n",
        "      <td>86.868</td>\n",
        "      <td>128.778</td>\n",
+       "      <td>78.232</td>\n",
        "      <td>40504.55</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>584.53</td>\n",
-       "      <td>40.320</td>\n",
-       "      <td>5.98</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-05</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>10.448899</td>\n",
-       "      <td>78.232</td>\n",
+       "      <td>2019-03-05</td>\n",
+       "      <td>369.0</td>\n",
+       "      <td>66.548</td>\n",
+       "      <td>64.008</td>\n",
+       "      <td>43.180</td>\n",
+       "      <td>62.738</td>\n",
        "      <td>86.614</td>\n",
        "      <td>129.032</td>\n",
+       "      <td>78.232</td>\n",
        "      <td>40651.69</td>\n",
-       "      <td>23.06</td>\n",
-       "      <td>278.81</td>\n",
-       "      <td>40.279</td>\n",
-       "      <td>1.48</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-06</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>12.827510</td>\n",
-       "      <td>80.772</td>\n",
+       "      <td>2019-03-06</td>\n",
+       "      <td>453.0</td>\n",
+       "      <td>67.564</td>\n",
+       "      <td>64.770</td>\n",
+       "      <td>43.434</td>\n",
+       "      <td>62.992</td>\n",
        "      <td>89.408</td>\n",
        "      <td>132.334</td>\n",
+       "      <td>80.772</td>\n",
        "      <td>40799.28</td>\n",
-       "      <td>19.66</td>\n",
-       "      <td>202.14</td>\n",
-       "      <td>40.210</td>\n",
-       "      <td>0.18</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-07</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>10.901968</td>\n",
-       "      <td>83.312</td>\n",
+       "      <td>2019-03-07</td>\n",
+       "      <td>385.0</td>\n",
+       "      <td>69.850</td>\n",
+       "      <td>65.786</td>\n",
+       "      <td>44.450</td>\n",
+       "      <td>64.008</td>\n",
        "      <td>92.456</td>\n",
        "      <td>135.890</td>\n",
+       "      <td>83.312</td>\n",
        "      <td>40947.30</td>\n",
-       "      <td>7.76</td>\n",
-       "      <td>429.45</td>\n",
-       "      <td>40.986</td>\n",
-       "      <td>1.75</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-08</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>8.919792</td>\n",
-       "      <td>83.566</td>\n",
+       "      <td>2019-03-08</td>\n",
+       "      <td>315.0</td>\n",
+       "      <td>73.660</td>\n",
+       "      <td>67.310</td>\n",
+       "      <td>45.974</td>\n",
+       "      <td>68.580</td>\n",
        "      <td>92.710</td>\n",
        "      <td>136.652</td>\n",
+       "      <td>83.566</td>\n",
        "      <td>41095.72</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>516.49</td>\n",
-       "      <td>40.986</td>\n",
-       "      <td>-3.42</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-09</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.560586</td>\n",
-       "      <td>83.312</td>\n",
+       "      <td>2019-03-09</td>\n",
+       "      <td>267.0</td>\n",
+       "      <td>75.438</td>\n",
+       "      <td>69.596</td>\n",
+       "      <td>47.498</td>\n",
+       "      <td>72.136</td>\n",
        "      <td>92.710</td>\n",
        "      <td>136.906</td>\n",
+       "      <td>83.312</td>\n",
        "      <td>41244.50</td>\n",
-       "      <td>3.88</td>\n",
-       "      <td>460.72</td>\n",
-       "      <td>41.375</td>\n",
-       "      <td>-1.31</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-10</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.909299</td>\n",
-       "      <td>83.820</td>\n",
+       "      <td>2019-03-10</td>\n",
+       "      <td>244.0</td>\n",
+       "      <td>75.946</td>\n",
+       "      <td>69.850</td>\n",
+       "      <td>47.498</td>\n",
+       "      <td>72.390</td>\n",
        "      <td>92.710</td>\n",
        "      <td>137.668</td>\n",
+       "      <td>83.820</td>\n",
        "      <td>41393.63</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>674.84</td>\n",
-       "      <td>41.375</td>\n",
-       "      <td>-1.06</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-11</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.286330</td>\n",
-       "      <td>83.566</td>\n",
+       "      <td>2019-03-11</td>\n",
+       "      <td>222.0</td>\n",
+       "      <td>76.454</td>\n",
+       "      <td>70.358</td>\n",
+       "      <td>47.752</td>\n",
+       "      <td>72.390</td>\n",
        "      <td>92.456</td>\n",
        "      <td>137.922</td>\n",
+       "      <td>83.566</td>\n",
        "      <td>41543.06</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>670.50</td>\n",
-       "      <td>41.375</td>\n",
-       "      <td>1.31</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-12</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.144746</td>\n",
-       "      <td>83.820</td>\n",
+       "      <td>2019-03-12</td>\n",
+       "      <td>217.0</td>\n",
+       "      <td>76.962</td>\n",
+       "      <td>70.866</td>\n",
+       "      <td>47.752</td>\n",
+       "      <td>72.390</td>\n",
        "      <td>92.710</td>\n",
        "      <td>138.176</td>\n",
+       "      <td>83.820</td>\n",
        "      <td>41692.78</td>\n",
-       "      <td>2.81</td>\n",
-       "      <td>517.15</td>\n",
-       "      <td>41.655</td>\n",
-       "      <td>5.47</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>5.918211</td>\n",
-       "      <td>83.820</td>\n",
+       "      <td>2019-03-13</td>\n",
+       "      <td>209.0</td>\n",
+       "      <td>78.232</td>\n",
+       "      <td>71.374</td>\n",
+       "      <td>48.768</td>\n",
+       "      <td>73.660</td>\n",
        "      <td>92.456</td>\n",
        "      <td>138.684</td>\n",
+       "      <td>83.820</td>\n",
        "      <td>41842.76</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>699.61</td>\n",
-       "      <td>41.655</td>\n",
-       "      <td>0.52</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>5.663360</td>\n",
-       "      <td>83.566</td>\n",
+       "      <td>2019-03-14</td>\n",
+       "      <td>200.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>92.456</td>\n",
        "      <td>138.684</td>\n",
+       "      <td>83.566</td>\n",
        "      <td>41992.97</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>733.03</td>\n",
-       "      <td>41.655</td>\n",
-       "      <td>5.77</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>5.804944</td>\n",
-       "      <td>83.820</td>\n",
+       "      <td>2019-03-15</td>\n",
+       "      <td>205.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>92.202</td>\n",
        "      <td>138.684</td>\n",
+       "      <td>83.820</td>\n",
        "      <td>42143.38</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>702.72</td>\n",
-       "      <td>41.655</td>\n",
-       "      <td>7.50</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.229696</td>\n",
-       "      <td>83.566</td>\n",
+       "      <td>2019-03-16</td>\n",
+       "      <td>220.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>91.948</td>\n",
        "      <td>138.684</td>\n",
+       "      <td>83.566</td>\n",
        "      <td>42293.98</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>686.98</td>\n",
-       "      <td>41.655</td>\n",
-       "      <td>9.69</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-17</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.079200</td>\n",
-       "      <td>81.788</td>\n",
+       "      <td>2019-03-17</td>\n",
+       "      <td>250.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>91.694</td>\n",
        "      <td>139.192</td>\n",
+       "      <td>81.788</td>\n",
        "      <td>42444.72</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>653.99</td>\n",
-       "      <td>41.592</td>\n",
-       "      <td>10.09</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-18</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.815437</td>\n",
-       "      <td>82.804</td>\n",
+       "      <td>2019-03-18</td>\n",
+       "      <td>276.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>91.440</td>\n",
        "      <td>139.192</td>\n",
+       "      <td>82.804</td>\n",
        "      <td>42595.59</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>585.96</td>\n",
-       "      <td>41.448</td>\n",
-       "      <td>9.36</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-19</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>8.523357</td>\n",
-       "      <td>83.312</td>\n",
+       "      <td>2019-03-19</td>\n",
+       "      <td>301.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>91.440</td>\n",
        "      <td>139.446</td>\n",
+       "      <td>83.312</td>\n",
        "      <td>42746.56</td>\n",
-       "      <td>7.29</td>\n",
-       "      <td>399.09</td>\n",
-       "      <td>41.341</td>\n",
-       "      <td>6.99</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-20</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>9.486128</td>\n",
-       "      <td>84.074</td>\n",
+       "      <td>2019-03-20</td>\n",
+       "      <td>335.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>92.456</td>\n",
        "      <td>140.462</td>\n",
+       "      <td>84.074</td>\n",
        "      <td>42897.61</td>\n",
-       "      <td>6.42</td>\n",
-       "      <td>328.51</td>\n",
-       "      <td>41.304</td>\n",
-       "      <td>2.80</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-21</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>8.325139</td>\n",
-       "      <td>83.820</td>\n",
+       "      <td>2019-03-21</td>\n",
+       "      <td>294.0</td>\n",
+       "      <td>80.264</td>\n",
+       "      <td>73.914</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>76.454</td>\n",
        "      <td>92.456</td>\n",
        "      <td>140.970</td>\n",
+       "      <td>83.820</td>\n",
        "      <td>43048.71</td>\n",
-       "      <td>2.33</td>\n",
-       "      <td>358.24</td>\n",
-       "      <td>41.295</td>\n",
-       "      <td>2.70</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-22</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.588902</td>\n",
-       "      <td>84.074</td>\n",
+       "      <td>2019-03-22</td>\n",
+       "      <td>268.0</td>\n",
+       "      <td>81.788</td>\n",
+       "      <td>75.184</td>\n",
+       "      <td>51.054</td>\n",
+       "      <td>76.962</td>\n",
        "      <td>92.710</td>\n",
        "      <td>141.478</td>\n",
+       "      <td>84.074</td>\n",
        "      <td>43199.83</td>\n",
-       "      <td>4.19</td>\n",
-       "      <td>486.67</td>\n",
-       "      <td>41.714</td>\n",
-       "      <td>4.11</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-23</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.843754</td>\n",
-       "      <td>84.074</td>\n",
+       "      <td>2019-03-23</td>\n",
+       "      <td>277.0</td>\n",
+       "      <td>82.296</td>\n",
+       "      <td>75.692</td>\n",
+       "      <td>51.054</td>\n",
+       "      <td>78.994</td>\n",
        "      <td>92.710</td>\n",
        "      <td>141.986</td>\n",
+       "      <td>84.074</td>\n",
        "      <td>43350.96</td>\n",
-       "      <td>4.22</td>\n",
-       "      <td>343.99</td>\n",
-       "      <td>42.136</td>\n",
-       "      <td>1.51</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-24</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.994250</td>\n",
-       "      <td>84.582</td>\n",
+       "      <td>2019-03-24</td>\n",
+       "      <td>247.0</td>\n",
+       "      <td>83.566</td>\n",
+       "      <td>76.200</td>\n",
+       "      <td>51.308</td>\n",
+       "      <td>79.502</td>\n",
        "      <td>92.964</td>\n",
        "      <td>143.510</td>\n",
+       "      <td>84.582</td>\n",
        "      <td>43502.06</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>755.23</td>\n",
-       "      <td>42.136</td>\n",
-       "      <td>7.89</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-25</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>6.796032</td>\n",
-       "      <td>85.090</td>\n",
+       "      <td>2019-03-25</td>\n",
+       "      <td>240.0</td>\n",
+       "      <td>84.328</td>\n",
+       "      <td>77.724</td>\n",
+       "      <td>52.324</td>\n",
+       "      <td>82.804</td>\n",
        "      <td>92.964</td>\n",
        "      <td>143.764</td>\n",
+       "      <td>85.090</td>\n",
        "      <td>43653.11</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>583.93</td>\n",
-       "      <td>42.049</td>\n",
-       "      <td>6.76</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-26</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.079200</td>\n",
-       "      <td>84.836</td>\n",
+       "      <td>2019-03-26</td>\n",
+       "      <td>250.0</td>\n",
+       "      <td>84.328</td>\n",
+       "      <td>77.724</td>\n",
+       "      <td>52.324</td>\n",
+       "      <td>82.804</td>\n",
        "      <td>93.218</td>\n",
        "      <td>143.764</td>\n",
+       "      <td>84.836</td>\n",
        "      <td>43804.08</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>408.20</td>\n",
-       "      <td>41.828</td>\n",
-       "      <td>6.05</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-27</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>9.457811</td>\n",
-       "      <td>85.598</td>\n",
+       "      <td>2019-03-27</td>\n",
+       "      <td>334.0</td>\n",
+       "      <td>84.328</td>\n",
+       "      <td>77.724</td>\n",
+       "      <td>51.308</td>\n",
+       "      <td>82.804</td>\n",
        "      <td>92.710</td>\n",
        "      <td>143.764</td>\n",
+       "      <td>85.598</td>\n",
        "      <td>43954.95</td>\n",
-       "      <td>25.39</td>\n",
-       "      <td>246.40</td>\n",
-       "      <td>41.720</td>\n",
-       "      <td>1.84</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-28</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>9.514445</td>\n",
-       "      <td>86.614</td>\n",
+       "      <td>2019-03-28</td>\n",
+       "      <td>336.0</td>\n",
+       "      <td>84.328</td>\n",
+       "      <td>77.724</td>\n",
+       "      <td>50.800</td>\n",
+       "      <td>82.804</td>\n",
        "      <td>95.758</td>\n",
        "      <td>148.336</td>\n",
+       "      <td>86.614</td>\n",
        "      <td>44105.70</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>471.78</td>\n",
-       "      <td>41.720</td>\n",
-       "      <td>1.50</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-29</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.957021</td>\n",
-       "      <td>86.868</td>\n",
+       "      <td>2019-03-29</td>\n",
+       "      <td>281.0</td>\n",
+       "      <td>86.106</td>\n",
+       "      <td>79.502</td>\n",
+       "      <td>52.324</td>\n",
+       "      <td>85.852</td>\n",
        "      <td>96.012</td>\n",
        "      <td>148.590</td>\n",
+       "      <td>86.868</td>\n",
        "      <td>44256.29</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>713.86</td>\n",
-       "      <td>41.720</td>\n",
-       "      <td>3.95</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-30</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>7.673853</td>\n",
-       "      <td>86.868</td>\n",
+       "      <td>2019-03-30</td>\n",
+       "      <td>271.0</td>\n",
+       "      <td>88.900</td>\n",
+       "      <td>82.296</td>\n",
+       "      <td>54.864</td>\n",
+       "      <td>88.138</td>\n",
        "      <td>96.012</td>\n",
        "      <td>148.590</td>\n",
+       "      <td>86.868</td>\n",
        "      <td>44406.70</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>740.84</td>\n",
-       "      <td>41.720</td>\n",
-       "      <td>6.55</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-03-31</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>8.268506</td>\n",
-       "      <td>86.868</td>\n",
+       "      <td>2019-03-31</td>\n",
+       "      <td>292.0</td>\n",
+       "      <td>88.900</td>\n",
+       "      <td>82.296</td>\n",
+       "      <td>54.864</td>\n",
+       "      <td>88.138</td>\n",
        "      <td>95.758</td>\n",
        "      <td>148.590</td>\n",
+       "      <td>86.868</td>\n",
        "      <td>44556.91</td>\n",
-       "      <td>0.00</td>\n",
-       "      <td>714.94</td>\n",
-       "      <td>41.710</td>\n",
-       "      <td>10.11</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2019-04-01</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>9.797613</td>\n",
-       "      <td>84.836</td>\n",
+       "      <td>2019-04-01</td>\n",
+       "      <td>346.0</td>\n",
+       "      <td>88.900</td>\n",
+       "      <td>82.296</td>\n",
+       "      <td>54.864</td>\n",
+       "      <td>88.138</td>\n",
        "      <td>95.504</td>\n",
        "      <td>148.590</td>\n",
+       "      <td>84.836</td>\n",
        "      <td>44706.89</td>\n",
-       "      <td>8.13</td>\n",
-       "      <td>443.96</td>\n",
-       "      <td>41.580</td>\n",
-       "      <td>8.73</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>32 rows × 45 columns</p>\n",
+       "<p>32 rows × 49 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no   flow_cms  TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm    dayl_s  \\\n",
-       "Date                                                                            \n",
-       "2019-03-01  11274790   6.909299      74.422      82.296     122.936  40066.17   \n",
-       "2019-03-02  11274790  11.071869      75.184      83.058     124.460  40211.76   \n",
-       "2019-03-03  11274790  10.618800      78.486      86.868     128.524  40357.90   \n",
-       "2019-03-04  11274790   9.854246      78.232      86.868     128.778  40504.55   \n",
-       "2019-03-05  11274790  10.448899      78.232      86.614     129.032  40651.69   \n",
-       "2019-03-06  11274790  12.827510      80.772      89.408     132.334  40799.28   \n",
-       "2019-03-07  11274790  10.901968      83.312      92.456     135.890  40947.30   \n",
-       "2019-03-08  11274790   8.919792      83.566      92.710     136.652  41095.72   \n",
-       "2019-03-09  11274790   7.560586      83.312      92.710     136.906  41244.50   \n",
-       "2019-03-10  11274790   6.909299      83.820      92.710     137.668  41393.63   \n",
-       "2019-03-11  11274790   6.286330      83.566      92.456     137.922  41543.06   \n",
-       "2019-03-12  11274790   6.144746      83.820      92.710     138.176  41692.78   \n",
-       "2019-03-13  11274790   5.918211      83.820      92.456     138.684  41842.76   \n",
-       "2019-03-14  11274790   5.663360      83.566      92.456     138.684  41992.97   \n",
-       "2019-03-15  11274790   5.804944      83.820      92.202     138.684  42143.38   \n",
-       "2019-03-16  11274790   6.229696      83.566      91.948     138.684  42293.98   \n",
-       "2019-03-17  11274790   7.079200      81.788      91.694     139.192  42444.72   \n",
-       "2019-03-18  11274790   7.815437      82.804      91.440     139.192  42595.59   \n",
-       "2019-03-19  11274790   8.523357      83.312      91.440     139.446  42746.56   \n",
-       "2019-03-20  11274790   9.486128      84.074      92.456     140.462  42897.61   \n",
-       "2019-03-21  11274790   8.325139      83.820      92.456     140.970  43048.71   \n",
-       "2019-03-22  11274790   7.588902      84.074      92.710     141.478  43199.83   \n",
-       "2019-03-23  11274790   7.843754      84.074      92.710     141.986  43350.96   \n",
-       "2019-03-24  11274790   6.994250      84.582      92.964     143.510  43502.06   \n",
-       "2019-03-25  11274790   6.796032      85.090      92.964     143.764  43653.11   \n",
-       "2019-03-26  11274790   7.079200      84.836      93.218     143.764  43804.08   \n",
-       "2019-03-27  11274790   9.457811      85.598      92.710     143.764  43954.95   \n",
-       "2019-03-28  11274790   9.514445      86.614      95.758     148.336  44105.70   \n",
-       "2019-03-29  11274790   7.957021      86.868      96.012     148.590  44256.29   \n",
-       "2019-03-30  11274790   7.673853      86.868      96.012     148.590  44406.70   \n",
-       "2019-03-31  11274790   8.268506      86.868      95.758     148.590  44556.91   \n",
-       "2019-04-01  11274790   9.797613      84.836      95.504     148.590  44706.89   \n",
+       "                Date.1  Streamflow_cfs  596_SWE_cm  628_SWE_cm  684_SWE_cm  \\\n",
+       "Date                                                                         \n",
+       "2019-03-01  2019-03-01           244.0      64.770      61.722      41.402   \n",
+       "2019-03-02  2019-03-02           391.0      65.278      61.722      41.656   \n",
+       "2019-03-03  2019-03-03           375.0      66.294      63.246      42.926   \n",
+       "2019-03-04  2019-03-04           348.0      66.548      64.008      43.180   \n",
+       "2019-03-05  2019-03-05           369.0      66.548      64.008      43.180   \n",
+       "2019-03-06  2019-03-06           453.0      67.564      64.770      43.434   \n",
+       "2019-03-07  2019-03-07           385.0      69.850      65.786      44.450   \n",
+       "2019-03-08  2019-03-08           315.0      73.660      67.310      45.974   \n",
+       "2019-03-09  2019-03-09           267.0      75.438      69.596      47.498   \n",
+       "2019-03-10  2019-03-10           244.0      75.946      69.850      47.498   \n",
+       "2019-03-11  2019-03-11           222.0      76.454      70.358      47.752   \n",
+       "2019-03-12  2019-03-12           217.0      76.962      70.866      47.752   \n",
+       "2019-03-13  2019-03-13           209.0      78.232      71.374      48.768   \n",
+       "2019-03-14  2019-03-14           200.0      80.264      73.914      50.800   \n",
+       "2019-03-15  2019-03-15           205.0      80.264      73.914      50.800   \n",
+       "2019-03-16  2019-03-16           220.0      80.264      73.914      50.800   \n",
+       "2019-03-17  2019-03-17           250.0      80.264      73.914      50.800   \n",
+       "2019-03-18  2019-03-18           276.0      80.264      73.914      50.800   \n",
+       "2019-03-19  2019-03-19           301.0      80.264      73.914      50.800   \n",
+       "2019-03-20  2019-03-20           335.0      80.264      73.914      50.800   \n",
+       "2019-03-21  2019-03-21           294.0      80.264      73.914      50.800   \n",
+       "2019-03-22  2019-03-22           268.0      81.788      75.184      51.054   \n",
+       "2019-03-23  2019-03-23           277.0      82.296      75.692      51.054   \n",
+       "2019-03-24  2019-03-24           247.0      83.566      76.200      51.308   \n",
+       "2019-03-25  2019-03-25           240.0      84.328      77.724      52.324   \n",
+       "2019-03-26  2019-03-26           250.0      84.328      77.724      52.324   \n",
+       "2019-03-27  2019-03-27           334.0      84.328      77.724      51.308   \n",
+       "2019-03-28  2019-03-28           336.0      84.328      77.724      50.800   \n",
+       "2019-03-29  2019-03-29           281.0      86.106      79.502      52.324   \n",
+       "2019-03-30  2019-03-30           271.0      88.900      82.296      54.864   \n",
+       "2019-03-31  2019-03-31           292.0      88.900      82.296      54.864   \n",
+       "2019-04-01  2019-04-01           346.0      88.900      82.296      54.864   \n",
        "\n",
-       "            prcp_mm_day  srad_W_m2  swe_cm  tmax_C  ...  \\\n",
-       "Date                                                ...   \n",
-       "2019-03-01        14.08     280.15  40.505    3.27  ...   \n",
-       "2019-03-02        28.55     185.59  40.371    1.44  ...   \n",
-       "2019-03-03         0.00     477.81  40.320    3.90  ...   \n",
-       "2019-03-04         0.00     584.53  40.320    5.98  ...   \n",
-       "2019-03-05        23.06     278.81  40.279    1.48  ...   \n",
-       "2019-03-06        19.66     202.14  40.210    0.18  ...   \n",
-       "2019-03-07         7.76     429.45  40.986    1.75  ...   \n",
-       "2019-03-08         0.00     516.49  40.986   -3.42  ...   \n",
-       "2019-03-09         3.88     460.72  41.375   -1.31  ...   \n",
-       "2019-03-10         0.00     674.84  41.375   -1.06  ...   \n",
-       "2019-03-11         0.00     670.50  41.375    1.31  ...   \n",
-       "2019-03-12         2.81     517.15  41.655    5.47  ...   \n",
-       "2019-03-13         0.00     699.61  41.655    0.52  ...   \n",
-       "2019-03-14         0.00     733.03  41.655    5.77  ...   \n",
-       "2019-03-15         0.00     702.72  41.655    7.50  ...   \n",
-       "2019-03-16         0.00     686.98  41.655    9.69  ...   \n",
-       "2019-03-17         0.00     653.99  41.592   10.09  ...   \n",
-       "2019-03-18         0.00     585.96  41.448    9.36  ...   \n",
-       "2019-03-19         7.29     399.09  41.341    6.99  ...   \n",
-       "2019-03-20         6.42     328.51  41.304    2.80  ...   \n",
-       "2019-03-21         2.33     358.24  41.295    2.70  ...   \n",
-       "2019-03-22         4.19     486.67  41.714    4.11  ...   \n",
-       "2019-03-23         4.22     343.99  42.136    1.51  ...   \n",
-       "2019-03-24         0.00     755.23  42.136    7.89  ...   \n",
-       "2019-03-25         0.00     583.93  42.049    6.76  ...   \n",
-       "2019-03-26         0.00     408.20  41.828    6.05  ...   \n",
-       "2019-03-27        25.39     246.40  41.720    1.84  ...   \n",
-       "2019-03-28         0.00     471.78  41.720    1.50  ...   \n",
-       "2019-03-29         0.00     713.86  41.720    3.95  ...   \n",
-       "2019-03-30         0.00     740.84  41.720    6.55  ...   \n",
-       "2019-03-31         0.00     714.94  41.710   10.11  ...   \n",
-       "2019-04-01         8.13     443.96  41.580    8.73  ...   \n",
+       "            971_SWE_cm  DAN_SWE_cm  SLI_SWE_cm  TUM_SWE_cm    dayl_s  ...  \\\n",
+       "Date                                                                  ...   \n",
+       "2019-03-01      60.198      82.296     122.936      74.422  40066.17  ...   \n",
+       "2019-03-02      61.214      83.058     124.460      75.184  40211.76  ...   \n",
+       "2019-03-03      62.484      86.868     128.524      78.486  40357.90  ...   \n",
+       "2019-03-04      62.738      86.868     128.778      78.232  40504.55  ...   \n",
+       "2019-03-05      62.738      86.614     129.032      78.232  40651.69  ...   \n",
+       "2019-03-06      62.992      89.408     132.334      80.772  40799.28  ...   \n",
+       "2019-03-07      64.008      92.456     135.890      83.312  40947.30  ...   \n",
+       "2019-03-08      68.580      92.710     136.652      83.566  41095.72  ...   \n",
+       "2019-03-09      72.136      92.710     136.906      83.312  41244.50  ...   \n",
+       "2019-03-10      72.390      92.710     137.668      83.820  41393.63  ...   \n",
+       "2019-03-11      72.390      92.456     137.922      83.566  41543.06  ...   \n",
+       "2019-03-12      72.390      92.710     138.176      83.820  41692.78  ...   \n",
+       "2019-03-13      73.660      92.456     138.684      83.820  41842.76  ...   \n",
+       "2019-03-14      76.454      92.456     138.684      83.566  41992.97  ...   \n",
+       "2019-03-15      76.454      92.202     138.684      83.820  42143.38  ...   \n",
+       "2019-03-16      76.454      91.948     138.684      83.566  42293.98  ...   \n",
+       "2019-03-17      76.454      91.694     139.192      81.788  42444.72  ...   \n",
+       "2019-03-18      76.454      91.440     139.192      82.804  42595.59  ...   \n",
+       "2019-03-19      76.454      91.440     139.446      83.312  42746.56  ...   \n",
+       "2019-03-20      76.454      92.456     140.462      84.074  42897.61  ...   \n",
+       "2019-03-21      76.454      92.456     140.970      83.820  43048.71  ...   \n",
+       "2019-03-22      76.962      92.710     141.478      84.074  43199.83  ...   \n",
+       "2019-03-23      78.994      92.710     141.986      84.074  43350.96  ...   \n",
+       "2019-03-24      79.502      92.964     143.510      84.582  43502.06  ...   \n",
+       "2019-03-25      82.804      92.964     143.764      85.090  43653.11  ...   \n",
+       "2019-03-26      82.804      93.218     143.764      84.836  43804.08  ...   \n",
+       "2019-03-27      82.804      92.710     143.764      85.598  43954.95  ...   \n",
+       "2019-03-28      82.804      95.758     148.336      86.614  44105.70  ...   \n",
+       "2019-03-29      85.852      96.012     148.590      86.868  44256.29  ...   \n",
+       "2019-03-30      88.138      96.012     148.590      86.868  44406.70  ...   \n",
+       "2019-03-31      88.138      95.758     148.590      86.868  44556.91  ...   \n",
+       "2019-04-01      88.138      95.504     148.590      84.836  44706.89  ...   \n",
        "\n",
        "            Developed,_Medium_Intensity  Developed,_High_Intensity  \\\n",
        "Date                                                                 \n",
@@ -2507,110 +2547,110 @@
        "\n",
        "            Barren_Land_Rock_Sand_Clay  Deciduous_Forest  Evergreen_Forest  \\\n",
        "Date                                                                         \n",
-       "2019-03-01                    8.326386           0.01026         37.994588   \n",
-       "2019-03-02                    8.326386           0.01026         37.994588   \n",
-       "2019-03-03                    8.326386           0.01026         37.994588   \n",
-       "2019-03-04                    8.326386           0.01026         37.994588   \n",
-       "2019-03-05                    8.326386           0.01026         37.994588   \n",
-       "2019-03-06                    8.326386           0.01026         37.994588   \n",
-       "2019-03-07                    8.326386           0.01026         37.994588   \n",
-       "2019-03-08                    8.326386           0.01026         37.994588   \n",
-       "2019-03-09                    8.326386           0.01026         37.994588   \n",
-       "2019-03-10                    8.326386           0.01026         37.994588   \n",
-       "2019-03-11                    8.326386           0.01026         37.994588   \n",
-       "2019-03-12                    8.326386           0.01026         37.994588   \n",
-       "2019-03-13                    8.326386           0.01026         37.994588   \n",
-       "2019-03-14                    8.326386           0.01026         37.994588   \n",
-       "2019-03-15                    8.326386           0.01026         37.994588   \n",
-       "2019-03-16                    8.326386           0.01026         37.994588   \n",
-       "2019-03-17                    8.326386           0.01026         37.994588   \n",
-       "2019-03-18                    8.326386           0.01026         37.994588   \n",
-       "2019-03-19                    8.326386           0.01026         37.994588   \n",
-       "2019-03-20                    8.326386           0.01026         37.994588   \n",
-       "2019-03-21                    8.326386           0.01026         37.994588   \n",
-       "2019-03-22                    8.326386           0.01026         37.994588   \n",
-       "2019-03-23                    8.326386           0.01026         37.994588   \n",
-       "2019-03-24                    8.326386           0.01026         37.994588   \n",
-       "2019-03-25                    8.326386           0.01026         37.994588   \n",
-       "2019-03-26                    8.326386           0.01026         37.994588   \n",
-       "2019-03-27                    8.326386           0.01026         37.994588   \n",
-       "2019-03-28                    8.326386           0.01026         37.994588   \n",
-       "2019-03-29                    8.326386           0.01026         37.994588   \n",
-       "2019-03-30                    8.326386           0.01026         37.994588   \n",
-       "2019-03-31                    8.326386           0.01026         37.994588   \n",
-       "2019-04-01                    8.326386           0.01026         37.994588   \n",
+       "2019-03-01                    8.318691           0.01026         38.011261   \n",
+       "2019-03-02                    8.318691           0.01026         38.011261   \n",
+       "2019-03-03                    8.318691           0.01026         38.011261   \n",
+       "2019-03-04                    8.318691           0.01026         38.011261   \n",
+       "2019-03-05                    8.318691           0.01026         38.011261   \n",
+       "2019-03-06                    8.318691           0.01026         38.011261   \n",
+       "2019-03-07                    8.318691           0.01026         38.011261   \n",
+       "2019-03-08                    8.318691           0.01026         38.011261   \n",
+       "2019-03-09                    8.318691           0.01026         38.011261   \n",
+       "2019-03-10                    8.318691           0.01026         38.011261   \n",
+       "2019-03-11                    8.318691           0.01026         38.011261   \n",
+       "2019-03-12                    8.318691           0.01026         38.011261   \n",
+       "2019-03-13                    8.318691           0.01026         38.011261   \n",
+       "2019-03-14                    8.318691           0.01026         38.011261   \n",
+       "2019-03-15                    8.318691           0.01026         38.011261   \n",
+       "2019-03-16                    8.318691           0.01026         38.011261   \n",
+       "2019-03-17                    8.318691           0.01026         38.011261   \n",
+       "2019-03-18                    8.318691           0.01026         38.011261   \n",
+       "2019-03-19                    8.318691           0.01026         38.011261   \n",
+       "2019-03-20                    8.318691           0.01026         38.011261   \n",
+       "2019-03-21                    8.318691           0.01026         38.011261   \n",
+       "2019-03-22                    8.318691           0.01026         38.011261   \n",
+       "2019-03-23                    8.318691           0.01026         38.011261   \n",
+       "2019-03-24                    8.318691           0.01026         38.011261   \n",
+       "2019-03-25                    8.318691           0.01026         38.011261   \n",
+       "2019-03-26                    8.318691           0.01026         38.011261   \n",
+       "2019-03-27                    8.318691           0.01026         38.011261   \n",
+       "2019-03-28                    8.318691           0.01026         38.011261   \n",
+       "2019-03-29                    8.318691           0.01026         38.011261   \n",
+       "2019-03-30                    8.318691           0.01026         38.011261   \n",
+       "2019-03-31                    8.318691           0.01026         38.011261   \n",
+       "2019-04-01                    8.318691           0.01026         38.011261   \n",
        "\n",
        "            Mixed_Forest  Shrub_Scrub  Grassland_Herbaceous  Woody_Wetlands  \\\n",
        "Date                                                                          \n",
-       "2019-03-01      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-02      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-03      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-04      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-05      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-06      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-07      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-08      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-09      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-10      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-11      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-12      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-13      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-14      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-15      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-16      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-17      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-18      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-19      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-20      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-21      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-22      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-23      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-24      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-25      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-26      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-27      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-28      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-29      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-30      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-03-31      0.002565    45.493722              5.055856        0.638715   \n",
-       "2019-04-01      0.002565    45.493722              5.055856        0.638715   \n",
+       "2019-03-01      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-02      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-03      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-04      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-05      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-06      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-07      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-08      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-09      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-10      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-11      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-12      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-13      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-14      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-15      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-16      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-17      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-18      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-19      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-20      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-21      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-22      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-23      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-24      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-25      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-26      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-27      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-28      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-29      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-30      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-03-31      0.002565    45.479614              5.066116        0.637433   \n",
+       "2019-04-01      0.002565    45.479614              5.066116        0.637433   \n",
        "\n",
        "            Emergent_Herbaceous_Wetlands  \n",
        "Date                                      \n",
-       "2019-03-01                      1.233824  \n",
-       "2019-03-02                      1.233824  \n",
-       "2019-03-03                      1.233824  \n",
-       "2019-03-04                      1.233824  \n",
-       "2019-03-05                      1.233824  \n",
-       "2019-03-06                      1.233824  \n",
-       "2019-03-07                      1.233824  \n",
-       "2019-03-08                      1.233824  \n",
-       "2019-03-09                      1.233824  \n",
-       "2019-03-10                      1.233824  \n",
-       "2019-03-11                      1.233824  \n",
-       "2019-03-12                      1.233824  \n",
-       "2019-03-13                      1.233824  \n",
-       "2019-03-14                      1.233824  \n",
-       "2019-03-15                      1.233824  \n",
-       "2019-03-16                      1.233824  \n",
-       "2019-03-17                      1.233824  \n",
-       "2019-03-18                      1.233824  \n",
-       "2019-03-19                      1.233824  \n",
-       "2019-03-20                      1.233824  \n",
-       "2019-03-21                      1.233824  \n",
-       "2019-03-22                      1.233824  \n",
-       "2019-03-23                      1.233824  \n",
-       "2019-03-24                      1.233824  \n",
-       "2019-03-25                      1.233824  \n",
-       "2019-03-26                      1.233824  \n",
-       "2019-03-27                      1.233824  \n",
-       "2019-03-28                      1.233824  \n",
-       "2019-03-29                      1.233824  \n",
-       "2019-03-30                      1.233824  \n",
-       "2019-03-31                      1.233824  \n",
-       "2019-04-01                      1.233824  \n",
+       "2019-03-01                      1.231259  \n",
+       "2019-03-02                      1.231259  \n",
+       "2019-03-03                      1.231259  \n",
+       "2019-03-04                      1.231259  \n",
+       "2019-03-05                      1.231259  \n",
+       "2019-03-06                      1.231259  \n",
+       "2019-03-07                      1.231259  \n",
+       "2019-03-08                      1.231259  \n",
+       "2019-03-09                      1.231259  \n",
+       "2019-03-10                      1.231259  \n",
+       "2019-03-11                      1.231259  \n",
+       "2019-03-12                      1.231259  \n",
+       "2019-03-13                      1.231259  \n",
+       "2019-03-14                      1.231259  \n",
+       "2019-03-15                      1.231259  \n",
+       "2019-03-16                      1.231259  \n",
+       "2019-03-17                      1.231259  \n",
+       "2019-03-18                      1.231259  \n",
+       "2019-03-19                      1.231259  \n",
+       "2019-03-20                      1.231259  \n",
+       "2019-03-21                      1.231259  \n",
+       "2019-03-22                      1.231259  \n",
+       "2019-03-23                      1.231259  \n",
+       "2019-03-24                      1.231259  \n",
+       "2019-03-25                      1.231259  \n",
+       "2019-03-26                      1.231259  \n",
+       "2019-03-27                      1.231259  \n",
+       "2019-03-28                      1.231259  \n",
+       "2019-03-29                      1.231259  \n",
+       "2019-03-30                      1.231259  \n",
+       "2019-03-31                      1.231259  \n",
+       "2019-04-01                      1.231259  \n",
        "\n",
-       "[32 rows x 45 columns]"
+       "[32 rows x 49 columns]"
       ]
      },
      "execution_count": 13,
@@ -2649,16 +2689,16 @@
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
-       "      <th>site_no</th>\n",
-       "      <th>flow_cms</th>\n",
-       "      <th>TUM_SWE_cm</th>\n",
+       "      <th>Date.1</th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>596_SWE_cm</th>\n",
+       "      <th>628_SWE_cm</th>\n",
+       "      <th>684_SWE_cm</th>\n",
+       "      <th>971_SWE_cm</th>\n",
        "      <th>DAN_SWE_cm</th>\n",
        "      <th>SLI_SWE_cm</th>\n",
+       "      <th>TUM_SWE_cm</th>\n",
        "      <th>dayl_s</th>\n",
-       "      <th>prcp_mm_day</th>\n",
-       "      <th>srad_W_m2</th>\n",
-       "      <th>swe_cm</th>\n",
-       "      <th>tmax_C</th>\n",
        "      <th>...</th>\n",
        "      <th>Developed,_Medium_Intensity</th>\n",
        "      <th>Developed,_High_Intensity</th>\n",
@@ -2699,145 +2739,145 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2021-09-12</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.236728</td>\n",
+       "      <td>2021-09-12</td>\n",
+       "      <td>8.36</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>44482.49</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>455.38</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>22.28</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>44482.49</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2021-09-13</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.302990</td>\n",
+       "      <td>2021-09-13</td>\n",
+       "      <td>10.70</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>44332.18</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>486.88</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>22.73</td>\n",
+       "      <td>44332.18</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2021-09-14</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.275239</td>\n",
+       "      <td>2021-09-14</td>\n",
+       "      <td>9.72</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>44181.67</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>447.48</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>22.50</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>44181.67</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2021-09-15</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.251170</td>\n",
+       "      <td>2021-09-15</td>\n",
+       "      <td>8.87</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>44031.00</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>424.99</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>21.18</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>44031.00</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2021-09-16</th>\n",
-       "      <td>11274790</td>\n",
-       "      <td>0.223986</td>\n",
+       "      <td>2021-09-16</td>\n",
+       "      <td>7.91</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>43880.19</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>420.08</td>\n",
        "      <td>0.0</td>\n",
-       "      <td>19.71</td>\n",
+       "      <td>43880.19</td>\n",
        "      <td>...</td>\n",
        "      <td>0.008978</td>\n",
        "      <td>0.006413</td>\n",
-       "      <td>8.326386</td>\n",
+       "      <td>8.318691</td>\n",
        "      <td>0.01026</td>\n",
-       "      <td>37.994588</td>\n",
+       "      <td>38.011261</td>\n",
        "      <td>0.002565</td>\n",
-       "      <td>45.493722</td>\n",
-       "      <td>5.055856</td>\n",
-       "      <td>0.638715</td>\n",
-       "      <td>1.233824</td>\n",
+       "      <td>45.479614</td>\n",
+       "      <td>5.066116</td>\n",
+       "      <td>0.637433</td>\n",
+       "      <td>1.231259</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>5 rows × 45 columns</p>\n",
+       "<p>5 rows × 49 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
-       "             site_no  flow_cms  TUM_SWE_cm  DAN_SWE_cm  SLI_SWE_cm    dayl_s  \\\n",
-       "Date                                                                           \n",
-       "2021-09-12  11274790  0.236728         0.0         0.0         0.0  44482.49   \n",
-       "2021-09-13  11274790  0.302990         0.0         0.0         0.0  44332.18   \n",
-       "2021-09-14  11274790  0.275239         0.0         0.0         0.0  44181.67   \n",
-       "2021-09-15  11274790  0.251170         0.0         0.0         0.0  44031.00   \n",
-       "2021-09-16  11274790  0.223986         0.0         0.0         0.0  43880.19   \n",
+       "                Date.1  Streamflow_cfs  596_SWE_cm  628_SWE_cm  684_SWE_cm  \\\n",
+       "Date                                                                         \n",
+       "2021-09-12  2021-09-12            8.36         0.0         0.0         0.0   \n",
+       "2021-09-13  2021-09-13           10.70         0.0         0.0         0.0   \n",
+       "2021-09-14  2021-09-14            9.72         0.0         0.0         0.0   \n",
+       "2021-09-15  2021-09-15            8.87         0.0         0.0         0.0   \n",
+       "2021-09-16  2021-09-16            7.91         0.0         0.0         0.0   \n",
        "\n",
-       "            prcp_mm_day  srad_W_m2  swe_cm  tmax_C  ...  \\\n",
-       "Date                                                ...   \n",
-       "2021-09-12          0.0     455.38     0.0   22.28  ...   \n",
-       "2021-09-13          0.0     486.88     0.0   22.73  ...   \n",
-       "2021-09-14          0.0     447.48     0.0   22.50  ...   \n",
-       "2021-09-15          0.0     424.99     0.0   21.18  ...   \n",
-       "2021-09-16          0.0     420.08     0.0   19.71  ...   \n",
+       "            971_SWE_cm  DAN_SWE_cm  SLI_SWE_cm  TUM_SWE_cm    dayl_s  ...  \\\n",
+       "Date                                                                  ...   \n",
+       "2021-09-12         0.0         0.0         0.0         0.0  44482.49  ...   \n",
+       "2021-09-13         0.0         0.0         0.0         0.0  44332.18  ...   \n",
+       "2021-09-14         0.0         0.0         0.0         0.0  44181.67  ...   \n",
+       "2021-09-15         0.0         0.0         0.0         0.0  44031.00  ...   \n",
+       "2021-09-16         0.0         0.0         0.0         0.0  43880.19  ...   \n",
        "\n",
        "            Developed,_Medium_Intensity  Developed,_High_Intensity  \\\n",
        "Date                                                                 \n",
@@ -2849,29 +2889,29 @@
        "\n",
        "            Barren_Land_Rock_Sand_Clay  Deciduous_Forest  Evergreen_Forest  \\\n",
        "Date                                                                         \n",
-       "2021-09-12                    8.326386           0.01026         37.994588   \n",
-       "2021-09-13                    8.326386           0.01026         37.994588   \n",
-       "2021-09-14                    8.326386           0.01026         37.994588   \n",
-       "2021-09-15                    8.326386           0.01026         37.994588   \n",
-       "2021-09-16                    8.326386           0.01026         37.994588   \n",
+       "2021-09-12                    8.318691           0.01026         38.011261   \n",
+       "2021-09-13                    8.318691           0.01026         38.011261   \n",
+       "2021-09-14                    8.318691           0.01026         38.011261   \n",
+       "2021-09-15                    8.318691           0.01026         38.011261   \n",
+       "2021-09-16                    8.318691           0.01026         38.011261   \n",
        "\n",
        "            Mixed_Forest  Shrub_Scrub  Grassland_Herbaceous  Woody_Wetlands  \\\n",
        "Date                                                                          \n",
-       "2021-09-12      0.002565    45.493722              5.055856        0.638715   \n",
-       "2021-09-13      0.002565    45.493722              5.055856        0.638715   \n",
-       "2021-09-14      0.002565    45.493722              5.055856        0.638715   \n",
-       "2021-09-15      0.002565    45.493722              5.055856        0.638715   \n",
-       "2021-09-16      0.002565    45.493722              5.055856        0.638715   \n",
+       "2021-09-12      0.002565    45.479614              5.066116        0.637433   \n",
+       "2021-09-13      0.002565    45.479614              5.066116        0.637433   \n",
+       "2021-09-14      0.002565    45.479614              5.066116        0.637433   \n",
+       "2021-09-15      0.002565    45.479614              5.066116        0.637433   \n",
+       "2021-09-16      0.002565    45.479614              5.066116        0.637433   \n",
        "\n",
        "            Emergent_Herbaceous_Wetlands  \n",
        "Date                                      \n",
-       "2021-09-12                      1.233824  \n",
-       "2021-09-13                      1.233824  \n",
-       "2021-09-14                      1.233824  \n",
-       "2021-09-15                      1.233824  \n",
-       "2021-09-16                      1.233824  \n",
+       "2021-09-12                      1.231259  \n",
+       "2021-09-13                      1.231259  \n",
+       "2021-09-14                      1.231259  \n",
+       "2021-09-15                      1.231259  \n",
+       "2021-09-16                      1.231259  \n",
        "\n",
-       "[5 rows x 45 columns]"
+       "[5 rows x 49 columns]"
       ]
      },
      "execution_count": 14,
@@ -2903,6 +2943,437 @@
    "metadata": {},
    "source": []
   },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Water Year 2017 rows: 365\n",
+      "SNOTEL cols used: ['596_SWE_cm', '628_SWE_cm', '684_SWE_cm', '971_SWE_cm', 'DAN_SWE_cm', 'SLI_SWE_cm', 'TUM_SWE_cm']\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Streamflow_cfs</th>\n",
+       "      <th>mean_SWE_cm</th>\n",
+       "      <th>prcp_mm_day</th>\n",
+       "      <th>tmax_C</th>\n",
+       "      <th>tmin_C</th>\n",
+       "      <th>srad_W_m2</th>\n",
+       "      <th>total_precipitation</th>\n",
+       "      <th>temperature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>count</th>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "      <td>365.00</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>mean</th>\n",
+       "      <td>1138.84</td>\n",
+       "      <td>33.56</td>\n",
+       "      <td>4.57</td>\n",
+       "      <td>11.43</td>\n",
+       "      <td>-1.10</td>\n",
+       "      <td>429.87</td>\n",
+       "      <td>0.17</td>\n",
+       "      <td>2.52</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>std</th>\n",
+       "      <td>1363.98</td>\n",
+       "      <td>39.79</td>\n",
+       "      <td>11.84</td>\n",
+       "      <td>8.40</td>\n",
+       "      <td>7.07</td>\n",
+       "      <td>168.17</td>\n",
+       "      <td>0.47</td>\n",
+       "      <td>7.99</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>min</th>\n",
+       "      <td>13.50</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-6.99</td>\n",
+       "      <td>-19.96</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-15.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>25%</th>\n",
+       "      <td>284.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>4.99</td>\n",
+       "      <td>-5.69</td>\n",
+       "      <td>318.67</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>-3.37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>50%</th>\n",
+       "      <td>570.00</td>\n",
+       "      <td>9.04</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>10.97</td>\n",
+       "      <td>-0.74</td>\n",
+       "      <td>444.84</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>1.15</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>75%</th>\n",
+       "      <td>1370.00</td>\n",
+       "      <td>74.75</td>\n",
+       "      <td>0.00</td>\n",
+       "      <td>18.71</td>\n",
+       "      <td>3.95</td>\n",
+       "      <td>543.28</td>\n",
+       "      <td>0.04</td>\n",
+       "      <td>9.69</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>max</th>\n",
+       "      <td>6830.00</td>\n",
+       "      <td>103.63</td>\n",
+       "      <td>86.98</td>\n",
+       "      <td>26.32</td>\n",
+       "      <td>11.75</td>\n",
+       "      <td>779.85</td>\n",
+       "      <td>3.06</td>\n",
+       "      <td>17.47</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       Streamflow_cfs  mean_SWE_cm  prcp_mm_day  tmax_C  tmin_C  srad_W_m2  \\\n",
+       "count          365.00       365.00       365.00  365.00  365.00     365.00   \n",
+       "mean          1138.84        33.56         4.57   11.43   -1.10     429.87   \n",
+       "std           1363.98        39.79        11.84    8.40    7.07     168.17   \n",
+       "min             13.50         0.00         0.00   -6.99  -19.96       0.00   \n",
+       "25%            284.00         0.00         0.00    4.99   -5.69     318.67   \n",
+       "50%            570.00         9.04         0.00   10.97   -0.74     444.84   \n",
+       "75%           1370.00        74.75         0.00   18.71    3.95     543.28   \n",
+       "max           6830.00       103.63        86.98   26.32   11.75     779.85   \n",
+       "\n",
+       "       total_precipitation  temperature  \n",
+       "count               365.00       365.00  \n",
+       "mean                  0.17         2.52  \n",
+       "std                   0.47         7.99  \n",
+       "min                   0.00       -15.82  \n",
+       "25%                   0.00        -3.37  \n",
+       "50%                   0.00         1.15  \n",
+       "75%                   0.04         9.69  \n",
+       "max                   3.06        17.47  "
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Select Water Year 2017 (Oct 2016 – Sep 2017) — a high-snowpack year for Tuolumne\n",
+    "wy_start = '2016-10-01'\n",
+    "wy_end   = '2017-09-30'\n",
+    "wy_df = Hydro_df.loc[wy_start:wy_end].copy()\n",
+    "\n",
+    "# Compute mean SWE across the CA SNOTEL sites for this water year\n",
+    "snotel_cols = [c for c in wy_df.columns if c.endswith('_SWE_cm')]\n",
+    "wy_df['mean_SWE_cm'] = wy_df[snotel_cols].mean(axis=1)\n",
+    "\n",
+    "print(f\"Water Year 2017 rows: {len(wy_df)}\")\n",
+    "print(f\"SNOTEL cols used: {snotel_cols}\")\n",
+    "wy_df[['Streamflow_cfs', 'mean_SWE_cm', 'prcp_mm_day', 'tmax_C', 'tmin_C', 'srad_W_m2',\n",
+    "        'total_precipitation', 'temperature']].describe().round(2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import os\n",
+    "os.makedirs('outputs', exist_ok=True)\n",
+    "\n",
+    "# ── Figure 1: Streamflow vs Mean SWE ─────────────────────────────────────────\n",
+    "fig, ax1 = plt.subplots(figsize=(14, 5))\n",
+    "\n",
+    "color_sf = '#1f77b4'\n",
+    "color_swe = '#d62728'\n",
+    "\n",
+    "ax1.set_xlabel('Date')\n",
+    "ax1.set_ylabel('Streamflow (cfs)', color=color_sf)\n",
+    "ax1.plot(wy_df.index, wy_df['Streamflow_cfs'], color=color_sf, linewidth=1.5, label='Streamflow (cfs)')\n",
+    "ax1.tick_params(axis='y', labelcolor=color_sf)\n",
+    "\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.set_ylabel('Mean SNOTEL SWE (cm)', color=color_swe)\n",
+    "ax2.fill_between(wy_df.index, wy_df['mean_SWE_cm'], alpha=0.3, color=color_swe)\n",
+    "ax2.plot(wy_df.index, wy_df['mean_SWE_cm'], color=color_swe, linewidth=1.5, label='Mean SWE (cm)')\n",
+    "ax2.tick_params(axis='y', labelcolor=color_swe)\n",
+    "\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 left')\n",
+    "\n",
+    "plt.title('Figure 1: Streamflow vs. Mean SNOTEL SWE — Tuolumne River WY2017')\n",
+    "fig.tight_layout()\n",
+    "plt.savefig('outputs/fig1_streamflow_vs_SWE_WY2017.png', dpi=150)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Figure 1 Analysis: Streamflow vs. SWE\n",
+    "\n",
+    "WY2017 was an exceptionally high-snowpack year for the Tuolumne River Basin. Mean SNOTEL SWE peaked at ~100 cm in late April/early May — roughly double the average. Streamflow remained low (~100–500 cfs) throughout the snow accumulation season (Oct–Apr) as precipitation was stored as snow rather than generating runoff. The snowmelt-driven streamflow peak (~6,700 cfs) lagged the SWE peak by about 6 weeks, occurring in mid-June as temperatures rose enough to melt the exceptionally deep snowpack. The rapid SWE decline in May–June corresponds directly with the sharp streamflow rise, confirming snowmelt as the dominant runoff mechanism in this high-elevation Sierra Nevada basin."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x1000 with 3 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# ── Figure 2: Snowmelt — SWE, Temperature, and SW Radiation ──────────────────\n",
+    "# Focus on the melt window: Feb – Jul\n",
+    "melt_df = wy_df.loc['2017-02-01':'2017-07-31']\n",
+    "\n",
+    "fig, axes = plt.subplots(3, 1, figsize=(14, 10), sharex=True)\n",
+    "\n",
+    "# Panel 1: SWE\n",
+    "axes[0].fill_between(melt_df.index, melt_df['mean_SWE_cm'], color='#4292c6', alpha=0.5)\n",
+    "axes[0].plot(melt_df.index, melt_df['mean_SWE_cm'], color='#08519c', linewidth=1.5)\n",
+    "axes[0].set_ylabel('Mean SWE (cm)')\n",
+    "axes[0].set_title('Figure 2: Snowmelt Dynamics — SWE, Temperature & SW Radiation (WY2017)')\n",
+    "\n",
+    "# Panel 2: Temperature (DayMet tmax and tmin)\n",
+    "axes[1].plot(melt_df.index, melt_df['tmax_C'], color='#d73027', linewidth=1.2, label='Tmax (DayMet)')\n",
+    "axes[1].plot(melt_df.index, melt_df['tmin_C'], color='#4575b4', linewidth=1.2, label='Tmin (DayMet)')\n",
+    "axes[1].axhline(0, color='black', linestyle='--', linewidth=0.8, alpha=0.5)\n",
+    "axes[1].fill_between(melt_df.index, melt_df['tmin_C'], melt_df['tmax_C'],\n",
+    "                     alpha=0.15, color='orange', label='Tmax–Tmin range')\n",
+    "axes[1].set_ylabel('Temperature (°C)')\n",
+    "axes[1].legend(loc='upper left', fontsize=9)\n",
+    "\n",
+    "# Panel 3: Shortwave radiation (DayMet srad)\n",
+    "axes[2].plot(melt_df.index, melt_df['srad_W_m2'], color='#fe9929', linewidth=1.2, label='SW Radiation (DayMet)')\n",
+    "axes[2].set_ylabel('SW Radiation (W/m²)')\n",
+    "axes[2].set_xlabel('Date')\n",
+    "axes[2].legend(loc='upper left', fontsize=9)\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "plt.savefig('outputs/fig2_snowmelt_swe_temp_srad_WY2017.png', dpi=150)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Figure 2 Analysis: Snowmelt — SWE, Temperature & SW Radiation\n",
+    "\n",
+    "The rapid SWE decline beginning in early May 2017 coincides with two converging drivers: (1) Tmin consistently rising above 0°C, eliminating overnight refreeze, and (2) SW radiation peaking near 750–780 W/m² — the highest sustained levels of the year. Through February–April, daytime highs occasionally exceeded 10°C but overnight temperatures remained sub-zero, preserving the snowpack. The steepest SWE decline (~30 cm in two weeks, early–mid May) matches the period when both Tmin crossed 0°C persistently and radiation remained high, indicating both temperature-index and radiation-driven melt were active simultaneously. Interestingly, a small SWE plateau occurs around mid-April during a cold snap visible in the temperature panel, confirming the snowpack's sensitivity to temperature."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1400x500 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# ── Figure 3: Rainfall–Runoff Response ───────────────────────────────────────\n",
+    "# Focus on the fall/early season when rain-on-ground events can occur (Oct–Jan)\n",
+    "rain_df = wy_df.loc['2016-10-01':'2017-01-31']\n",
+    "\n",
+    "fig, ax1 = plt.subplots(figsize=(14, 5))\n",
+    "\n",
+    "# Bar chart for precipitation (inverted, top of plot)\n",
+    "ax1.bar(rain_df.index, rain_df['prcp_mm_day'], color='#2166ac', alpha=0.7,\n",
+    "        width=1.0, label='DayMet Precipitation (mm/day)')\n",
+    "ax1.set_ylabel('Precipitation (mm/day)')\n",
+    "ax1.set_xlabel('Date')\n",
+    "ax1.invert_yaxis()  # precipitation reads top-down\n",
+    "ax1.set_ylim(rain_df['prcp_mm_day'].max() * 2.5, 0)\n",
+    "\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(rain_df.index, rain_df['Streamflow_cfs'], color='#d73027',\n",
+    "         linewidth=2.0, label='Streamflow (cfs)')\n",
+    "ax2.set_ylabel('Streamflow (cfs)', color='#d73027')\n",
+    "ax2.tick_params(axis='y', labelcolor='#d73027')\n",
+    "\n",
+    "lines1, labels1 = ax1.get_legend_handles_labels()\n",
+    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
+    "ax1.legend(lines1 + lines2, labels1 + labels2, loc='lower left')\n",
+    "\n",
+    "plt.title('Figure 3: Rainfall–Runoff Response — Tuolumne River Oct 2016–Jan 2017')\n",
+    "fig.tight_layout()\n",
+    "plt.savefig('outputs/fig3_rainfall_runoff_WY2017.png', dpi=150)\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Figure 3 Analysis: Rainfall–Runoff Response\n",
+    "\n",
+    "Several distinct rainfall–runoff events are visible in the Oct 2016–Jan 2017 period. The largest event (early January 2017) shows a clear flashy response: a multi-day atmospheric river event with daily precipitation exceeding 60 mm produced a streamflow spike from ~400 cfs to ~2,500 cfs within 1–2 days. The earlier October and November events also show rapid streamflow responses with short lag times (1–2 days), typical for a steep, high-elevation watershed where soils are thin and storage capacity is limited. An unexpected observation is that the November event produced a larger relative streamflow response than similar October precipitation — likely because antecedent soil moisture was higher after the October storms saturated the watershed, reducing infiltration capacity and increasing runoff efficiency."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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durS27MyZM7h48aLLiTzVPffcg/379+e4zdzav38//vzzT69/Axs1aoTDhw9rf5+JiKiE8lGlLxERUaFSWyV4+lGUrEvLnS+brVu3rlKpUiUlJSVFW7Zt2zYFgBIfH68tUy+93rp1q8s+PW1z8ODBCgDlhRdecFl3x44dCgAlMTHRZfk333zjcbknzzzzjJKQkKBdOuztMnh1DLm5HBZeWiWoxo4dqwBQDhw4oCiK4xL47JeSXrt2TSlXrpwybNgwbdlff/2lAFDeeecdl3W7du2qVK1aVWsF4HzJ/+HDhxUAyo4dOxRFUZS3335bCQ8PV27evKkMHjzYpVVCSkqKEh0drTz22GMu2z9//rwSFRXlsjwvrRJu3LihBAUFKRMmTHBZPnfuXEUQBO2y2DfeeEMBoFy6dClX270V5+NbunSpAkD54osvtNuzP08FbZWgUo9j/fr12rILFy4oBoNB+eCDD7RlTZs2Vbp16+ZyX1mWlZYtWyoAlHLlyin9+vVT3n77bZdLh31Bfb/+3//9n3Lp0iXl7NmzysaNG5WqVasqgiBo7VQmT56sAFD69evncv8TJ04okiS5tYA4dOiQYjAYtOU2m01JSEhQ4uPjlWvXrrms69zqQt2PM/Wz6ddff9WWnTx5UgkODna5xFv9XHN+L3trlZCRkaHY7XaXZUlJSUpQUJAydepUbVlOLQQGDx7s8tm3bt06BYAyffp0l/V69eqlCIKg/PPPPy7HZDKZXJYdOHBAAaC8+eabbvvK7q+//lKqVKmimEwmpXnz5srNmzdveZ+cZD9OWZaVGjVqKO3bt3d5ftLS0pSEhASlXbt22jL1OXv88ce1ZTabTalUqZIiCIIye/Zsbfm1a9eUkJAQZfDgwdoy9TVYsWJFJTk5WVu+cuVKBYCycOHCfI8p++tVXT+75cuXKwCUH3/8UVvmrVWCp79lKmS7tL+g7xtvXn75ZQWAy99j1d13361Ur15d+33EiBHKAw88oCiKojz33HPK3Xffrd3Wq1cvJTQ0VLFarW7b6dy5sxIVFaVIkqS8+OKLOY5H9emnnyoAlI8++khbpr62PvnkE7f1n332WQWAxxYfeW2VMGHCBI9tIlTLli1TACh79+7N1faIiKh4YsUtERGVKG+//Ta+++47lx9Pzp49i0OHDuHRRx9FeHi4trxly5aoW7dugccxcuRIl99XrVqFqKgotGvXzqUauFGjRggPD3dpNeDJ33//jYULF+K111675aXDS5Ys0doVFJT62KSkpABwXAKvXkoqyzKuXr0Km82Gxo0bY9++fdr9br/9dtx7771ITEzUll29ehWbNm3CgAEDPFY51a5dG/Xq1cPy5csBOC4R7datG0JDQ93W/e6773D9+nX069fP5fGUJAn33nvvLR9Pb9TLy1euXOlS8fr555/jvvvu0y6LVSf2Wb9+faFP5jRgwIAirboFsp5fAFixYgVEUXSZIK1fv37YtGmTS1sPQRDw7bffYvr06YiJicHy5csxatQoxMfHo0+fPj6fuX7YsGEoU6YM4uLi0KlTJ9y8eRNLly51q5JzvlQaAL744gvIsoxHHnnE5bVVvnx51KhRQ3tt7d+/H0lJSRg3bpzbRE+3quIDHK03GjVqpP1epUoVdOvWDd9++y3sdnuejzcoKEhrN2C323HlyhWthYfzezMvvv76a0iShDFjxrgsnzBhAhRFwaZNm1yWt23b1mWipHr16iEyMhLHjx/PcT83btxAhw4dcO+992L37t04cOAAHn74YVgsFm2dWbNmwWAwwGw25+tYfv/9dxw7dgz9+/fHlStXtOf15s2baNOmDX788Ue39/L//vc/7d+SJKFx48ZQFAXDhw/XlkdHR+OOO+7weIyPPvooIiIitN979eqFChUq4Ouvv873mLK/XgFH6xNVRkYGLl++jPvuuw8A8v3c30p+3zfeXLlyBQaDweXvsap58+b4999/cf78eQCOqlq1dUCzZs2wf/9+pKWlabfde++9MBjc5+B+++23YbFYULlyZUyaNOmWx3j06FGMGjUKTZo0weDBg7XlasW0p7/F6kSazlXV+SHLMlasWIEGDRrgzjvv9LhOTEwMAOR4ZRERERV/7n/RiIiIirF77rnH4+WL2Z08eRIAcNttt7nddttttxXoy67BYEClSpVclh07dgw3btxA2bJlPd7n4sWLOW5z7NixaNq0qUuYVhTUGa6dw4elS5di3rx5bn10ExISXO776KOPYvTo0Th58iTi4+OxatUqWK1WDBo0yOv++vfvj3nz5uHpp5/G7t27vfaMPXbsGICsvqXZRUZG5u4APejTpw/WrVuHPXv2oGnTpvj333/x22+/YcGCBS7rfPjhh/jf//6HF154AW3atEGPHj3Qq1cvLTzLL0mS8PLLL2Pw4MFYt24dHn744QJtLyeent/PPvsM99xzD65cuaJd4t6gQQNYLBasWrUKjz/+uLZuUFAQJk6ciIkTJ+LcuXPYvn07Fi5ciJUrV8JoNOKzzz7zum81hMmPnFqFqF555RW0aNECkiShdOnSuPPOOz2GOdlft8eOHYOiKKhRo4bH7RqNRgBZrRecZ5rPC0/bv/3225GWloZLly7l6hidybKMhQsXYvHixUhKSnIJf/Pbb/jkyZOIi4tzeX0A0IIk9XNU5dzvUxUTE3PLPt7vvPMOTp06hV27dqFChQpYu3YtHnroIfTr1w8rV66EJEk4fPgw6tevn++et+pnhnMAl92NGze0MMzT8URFRSE4ONjlsnl1uad2ENmfY0EQcNttt2mtXPIzpuyvV8BxUmzKlClYsWKF29+SGzdueN12QeT3fZMfzZs3xxtvvIFdu3ahTZs2+OOPPzB37lwAjr60NpsNP//8M+Lj43Hu3DmXwN1ZlSpVULZsWdSuXdsl7Pbk/Pnz6NSpE6KiorB69WpIkqTdpt7X00kEtRf4rbZ/K9u3b8eZM2fw9NNPe11HPbGXmxNFRERUfDG4JSIiugVvX4q8VcU5V76pZFlG2bJlXSpQneXUZ/CHH37AN998gy+++EL7wg84eummp6fjxIkTiI2NLVBY6c3hw4chSZL2Jf2zzz7DkCFD0L17dzz77LMoW7YsJEnCrFmztCBL1bdvXzz99NNITEzESy+9hM8++wyNGzfGHXfc4XV//fr1w4svvojHHnsMpUqVwoMPPuhxPbUK7dNPP/UYcHkK6HKrS5cuCA0NxcqVK9G0aVOsXLkSoiiid+/e2johISH48ccfsXXrVmzcuBHffPMNPv/8c7Ru3RqbN292+ZKfHwMGDMC0adMwdepUdO/evUDbyonaT1U9gXHs2DGtv6+nACYxMdEluHVWoUIF9O3bFz179kTt2rWxcuVKLFmyxOtzUaFChXyPOzeVyHXr1nWb6MiT7AGLLMsQBAGbNm3y+Dx6qgj0BzNnzsSkSZMwbNgwTJs2DbGxsRBFEePGjSv0qnBvvL3ub/V87d69G/Hx8dprok2bNvj000/Rr18/DBs2DHPnzsW6deswffr0fI9NfQxee+011K9f3+M62Z9bT8eT32MsrDF5CgQfeeQR7N69G88++yzq16+P8PBwyLKMDh065Oq5z+vfOE/jKOj7plSpUrDZbEhJSXE7UaD2q925c6d2BUaTJk0AAKVLl0aNGjWwc+dObRI05/62+XHjxg107NgR169fx44dOxAXF+dyu/o6PXfunNt9z507h9jY2AJPqpeYmAhRFLW+xJ6oJ0Syn0ggIqKShcEtEREFJHVipX/++cfttuzL1Gqn7Jd+Z682y0n16tXx/fffo1mzZnmuxDl16hQAx+Qy2Z05cwYJCQl44403MG7cuDxtNzf73b59O5o0aaJ9kV69ejWqVauGL774wuXL/uTJk93uHxsbi06dOiExMREDBgzArl27XKpWPalSpQqaNWuGbdu2YeTIkV5DP/Vy7LJly94ynMtrNVJYWBg6d+6MVatWYf78+fj888/RokULty/voiiiTZs2aNOmDebPn4+ZM2di4sSJ2Lp1a64Cw5yoVbdDhgzRbdbw1NRUrF27FpUrV9YqKBMTE2E0GvHpp5+6hS87d+7EokWLcOrUKY+VlSqj0Yh69erh2LFj2qXSnnhrY+Jr1atXh6IoSEhIwO23357jeoAj/M7P861WWzr7+++/ERoamuOJHG+v59WrV+OBBx7ARx995LL8+vXrLsFOXt4P8fHx+P77793CtKNHj2q3FwZBEHDu3DnYbDbtPf/II4/g4sWLeOqpp/Djjz8iJibG60mD3FCfr8jIyAK/P3Mr+3OsKAr++ecf1KtXr9DGdO3aNWzZsgVTpkzBK6+84nXfgPfnvrD+xuXmfeNNzZo1AQBJSUna46MqW7asFs6GhYWhVq1aLu1JmjZtil27duH06dOQJEkLdfMjIyMDXbp0wd9//43vv/8etWrVclunYsWKKFOmDH799Ve3237++WevIXxumc1mrFmzBq1atXL7u+MsKSkJoijm6/EmIqLigz1uiYgoIMXFxaFOnTr45JNPtMvFAcfliYcOHXJZNz4+HpIkuc0avnjx4lzv75FHHoHdbse0adPcbrPZbDn2A23dujXWrl3r9lOmTBk0btwYa9euRZcuXbT1z50759bGIK+uXr2Kfv36wW63a7PWA1nVZs7VZXv37sWePXs8bmfQoEE4cuQInn32WUiShL59+95y39OnT8fkyZPx1FNPeV2nffv2iIyMxMyZMz0e56VLl7R/h4WFAXAPJXLSp08fnD17Fh9++CEOHDiAPn36uNx+9epVt/uoX9adL589evSoFrzn1cCBA3HbbbdhypQp+bp/TtLT0zFo0CBcvXoVEydO1AKdxMREtGjRAn369EGvXr1cfp599lkA0HoQHzt2zOOxXb9+HXv27EFMTEyOAWTbtm3z/aOnHj16QJIkTJkyxa2KUlEU7ZL4hg0bIiEhAQsWLHB7beWm+nLPnj0uLVn+++8/rF+/Hg8++GCOFdthYWEeX8uSJLntd9WqVThz5ozb/YHcvR8eeugh2O12vPXWWy7L33jjDQiCgI4dO95yG7nRtm1bpKenY9asWS7LR48ejfbt2+PEiRNo166dNvb8aNSoEapXr47XX3/d5TNf5fyZUVg++eQTl/7Rq1evxrlz57THrTDG5OkzGYDHk2TenvvIyEiULl26QH/jcvu+8UYNWz2FoYCjivb333/H5s2btf62qqZNm2LPnj3YsWMH6tWr51axm1t2ux19+vTBnj17sGrVqhwD4J49e2LDhg1alS8AbNmyBX///bfL1Rn58fXXX+P69esYMGBAjuv99ttvqF27NqKiogq0PyIi8m+suCUiooA1c+ZMdOvWDc2aNcPQoUNx7do1vPXWW6hTp47Ll+ioqCj07t0bb775JgRBQPXq1bFhw4Zb9qV11rJlS4wYMQKzZs3C77//jgcffBBGoxHHjh3DqlWrsHDhQvTq1cvjfatUqeKxwnHcuHEoV66c26X0L774IpYuXYqkpKRcTVD2999/47PPPoOiKEhOTsaBAwewatUqpKamYv78+ejQoYO2bufOnfHFF1/g4YcfRqdOnZCUlIR3330XtWrV8hg8dOrUCaVKlcKqVavQsWNHrz1+nbVs2RItW7bMcZ3IyEi88847GDRoEBo2bIi+ffuiTJkyOHXqFDZu3IhmzZppYZM6AdSYMWPQvn37XAXIDz30ECIiIvDMM89AkiS33sJTp07Fjz/+iE6dOiE+Ph4XL17E4sWLUalSJZfLdO+88060bNkS27Ztu+VxZydJEiZOnIihQ4d6XWfLli1aT0Vn3bt313qvnjlzRus1m5qaiiNHjmDVqlU4f/48JkyYgBEjRgBwBPD//PMPRo8e7XFfFStWRMOGDZGYmIjnn38eBw4cQP/+/dGxY0e0aNECsbGxOHPmDJYuXYqzZ89iwYIFBW4Z4QvVq1fH9OnT8eKLL+LEiRPo3r07IiIikJSUhLVr1+Lxxx/HM888A1EU8c4776BLly6oX78+hg4digoVKuDo0aP4448/8O233+a4nzp16qB9+/YYM2YMgoKCtJDsVkF9o0aN8M4772D69Om47bbbULZsWbRu3RqdO3fG1KlTMXToUDRt2hSHDh1CYmIiqlWr5nZ80dHRePfddxEREYGwsDDce++9HnundunSBQ888AAmTpyIEydO4K677sLmzZuxfv16jBs3zmUisoJ47LHH8Nlnn+GVV17Br7/+igcffBA2mw3r1q3Djh070KxZMyxZsgQtWrTAsGHD8rUPURTx4YcfomPHjqhduzaGDh2KihUr4syZM9i6dSsiIyPx1VdfFcrxqGJjY9G8eXMMHToUFy5cwIIFC3DbbbfhscceK7QxRUZG4v7778fcuXNhtVpRsWJFbN68GUlJSW7rqp+FEydORN++fWE0GtGlSxeEhYXhf//7H2bPno3//e9/aNy4MX788Uf8/fffuT7W3L5vvKlWrRrq1KmD77//3uNz3Lx5c3z88cf45ZdfMGrUKJfbmjZtihs3buDGjRs5nvC7lQkTJuDLL79Ely5dcPXqVbce3QMHDtT+/dJLL2HVqlV44IEHMHbsWKSmpuK1115D3bp13T6zP/30U5w8eVKbQO3HH3/U2n4MGjTIrXI9MTERQUFBOfa0t1qt2L59O5588sl8Hy8RERUTChERUQnw8ccfKwCUX375xePtSUlJCgDl448/dlm+YsUKpWbNmkpQUJBSp04d5csvv1R69uyp1KxZ02W9S5cuKT179lRCQ0OVmJgYZcSIEcrhw4fdtjl48GAlLCzM6zjff/99pVGjRkpISIgSERGh1K1bV3nuueeUs2fP5vmY4+PjlU6dOrktHzx4sAJASUpKuuU2AGg/oigq0dHRSoMGDZSxY8cqf/zxh9v6siwrM2fOVOLj45WgoCClQYMGyoYNG5TBgwcr8fHxHvfx5JNPKgCUZcuWud2mPi+vvfZajuP09rhu3bpVad++vRIVFaUEBwcr1atXV4YMGaL8+uuv2jo2m0156qmnlDJlyiiCICi5/d+fAQMGKACUtm3but22ZcsWpVu3bkpcXJxiMpmUuLg4pV+/fsrff//tsh4ApWXLlrfcl7fjs1qtSvXq1RUAyqhRo7Tl6uPm7efTTz9VFMXxGlGXCYKgREZGKrVr11Yee+wxZe/evS77euqppxQAyr///ut1nK+++qoCQDlw4IBy4cIFZfbs2UrLli2VChUqKAaDQYmJiVFat26trF69+pbHrJetW7cqAJRVq1bluN7kyZMVAMqlS5c83r5mzRqlefPmSlhYmBIWFqbUrFlTGTVqlPLXX3+5rLdz506lXbt2SkREhBIWFqbUq1dPefPNN93240x9Pj/77DOlRo0a2ntp69atLuupn2vO7+Xz588rnTp1UiIiIlxeXxkZGcqECROUChUqKCEhIUqzZs2UPXv2KC1btnR7Da5fv16pVauWYjAYXD7DPL2PU1JSlKefflqJi4tTjEajUqNGDeW1115TZFn2eEzZxcfHK4MHD/b4GDu7efOmMnHiRKV69eqK0WhUSpUqpfTo0UP5+eefFavVqtx///2K0WhUvv/++1tuS1EU5ZdffvH4mb9//36lR48eSqlSpZSgoCAlPj5eeeSRR5QtW7Zo63h7bXh7n7Zs2VKpXbu29rv6Gly+fLny4osvKmXLllVCQkKUTp06KSdPnnS7f0HGpCiKcvr0aeXhhx9WoqOjlaioKKV3797K2bNnFQDK5MmTXdadNm2aUrFiRUUURZfXVlpamjJ8+HAlKipKiYiIUB555BHl4sWLbtsorPeNJ/Pnz1fCw8OVtLQ0t9v++usv7bMs++esLMtKdHS0AkD5/PPPc9yHt7+biuJ4HnP6XM3u8OHDyoMPPqiEhoYq0dHRyoABA5Tz58/nabvZ3/M3btxQgoODlR49euR4HJs2bVIAKMeOHctxPSIiKv4ERclHJ30iIqISrH79+ihTpozf9uAsbp5++ml89NFHOH/+vDaxDFEgEwQBo0aNcmtBQCXDtm3b8MADD2DVqlVer6Qgdzdu3EC1atUwd+5cDB8+3NfD8Wvdu3eHIAhYu3atr4dCREQ6Y49bIiIKWFarFTabzWXZtm3bcODAAbRq1co3gyphMjIy8Nlnn6Fnz54MbYmIyKuoqCg899xzeO211yDLsq+H47f+/PNPbNiwwWPPfCIiKnnY45aIiALWmTNn0LZtWwwcOBBxcXE4evQo3n33XZQvXx5PPPGEr4dXrF28eBHff/89Vq9ejStXrmDs2LG+HhIREfm5559/Hs8//7yvh+HX7rzzTreTzkREVHIxuCUiooAVExODRo0a4cMPP8SlS5cQFhaGTp06Yfbs2ShVqpSvh1esHTlyBAMGDEDZsmWxaNEi1K9f39dDIiIiIiIiKlbY45aIiIiIiIiIiIjIz7DHLREREREREREREZGfYXBLRERERERERERE5GfY4zYbWZZx9uxZREREQBAEXw+HiIiIiIiIiIiISghFUZCSkoK4uDiIYs41tQxuszl79iwqV67s62EQERERERERERFRCfXff/+hUqVKOa7D4DabiIgIAI4HLzIy0sejISIiIiIiIiIiopIiOTkZlStX1jLInDC4zUZtjxAZGcngloiIiIiIiIiIiApdblq0cnIyIiIiIiIiIiIiIj/D4JaIiIiIiIiIiIjIzzC4JSIiIiIiIiIiIvIz7HFLRERERERERFSC2O12WK1WXw+DKGBJkgSDwZCrPrY5YXBLRERERERERFRCpKam4vTp01AUxddDIQpooaGhqFChAkwmU763weCWiIiIiIiIiKgEsNvtOH36NEJDQ1GmTJkCV/sRUd4pigKLxYJLly4hKSkJNWrUgCjmr1stg1siIiIiIiIiohLAarVCURSUKVMGISEhvh4OUcAKCQmB0WjEyZMnYbFYEBwcnK/tcHIyIiIiIiIiIqIShJW2RL6X3ypbl20UwjiIiIiIiIiIiIiIqBAxuCUiIiIiIiIiIioGateujQ0bNuT7/snJyahevTouXbpUiKMqmHHjxmHIkCEF3o7dbkfdunXx559/FnxQfoLBLRERERERERERFZlWrVohKCgIERERiIqKQp06dTBhwoRCDRMFQUBYWBiSk5Ndlnfq1AmCIGDdunW52s6QIUMwbty4W65jMpkQHh6OqKgo3HPPPfjuu+/yOfKc/fHHH+jcuXO+7z9v3jx0794dZcqUKcRR3dqMGTMwduxYXfchSRKeeeYZvPTSS7rupygxuCUiIiIiIiIioiI1Z84cpKSk4Pr161i5ciXOnDmDRo0a4cKFC4W2j8qVK+Pzzz/Xfj937hz27t2LcuXKFdo+VE8++SRSU1Nx5coV9OnTBw8//DCuX7/utp7Vai30feeWzWbD+++/j6FDhxb5vr/66it07dpV9/306tULW7ZswalTp3TfV1FgcOsDN27cwKlTp3DixIkS/XPy5ElcunQJiqL4+iEnIiIiIiIiIj8kCAJq1aqFzz77DJGRkZg3bx4AIDU1Fd26dUPZsmURFRWF+++/HwcOHAAAXLp0CcHBwUhKStK2k5GRgZiYGOzdu1dbNnToUHz88cfa75988gkeeeQRBAcHu4zh+++/xz333IPo6GjUrl0bX375JQBg0aJFSExMxOLFixEeHo7atWvf8ngMBgNGjBiBmzdv4t9//8Wrr76Kzp07Y+TIkYiNjcULL7wARVGwaNEi1KxZE9HR0WjVqpXL5f3JyckYPXo04uPjERkZibvvvhv//fcfAKBq1apatfCSJUtQv359vPTSSyhVqhSqVKmCxYsXex3bzz//DLvdjjp16mjLhgwZguHDh6NXr17aMR4+fBjvvfceKlWqhDJlyrhsUz2eESNGICoqCgkJCdi2bRvWrVuH2267DTExMZg4caLLfi9cuIC///4b999/PwDgxx9/RN26dREeHo4ePXogJSXFZf2BAwciLi4OkZGRaNSoEbZu3QrAEXqXK1cO27Ztc1n/zjvv1AL6sLAw3H333di4ceMtn6viwODrAQSS48eP47vNm3H29Akoit3XwykagojomNJo2qwF7rvvPl+PhoiIiIiIiCigvJy4D2evpuu+n7jYEEwf0DDf9zcYDOjevbvWYkCWZfTv3x/Lli2DJEl4/vnn8cgjj+Do0aMoU6YMOnfujKVLl+LVV18FAKxduxZxcXG49957tW22a9cOb731Fo4ePYqaNWvi448/xqeffoqvv/5aW+fgwYPo3bs31qxZg1atWmH37t3o1KkTfv75Z4wZMwb79u1DdHQ0FixYkKvjsFqteOeddxAREYEaNWoAAL755ht8+OGHePPNN2GxWPDOO+/go48+wldffYWEhAQsXrwYXbp0wZEjR2AymTBkyBCkpaVhz549KF++PA4cOICQkBCP+zt8+DA6deqEc+fO4bfffkP79u1Rp04dLSR19vvvv6NmzZpuy1etWoVNmzZhxYoV+N///odu3bqhZ8+eOH78OHbs2IGHHnoIPXv21CqVN2/ejBUrVmDx4sWYMmUKBg4ciHbt2uHAgQM4efIkGjZsiJ49e6JhQ8frYcOGDWjfvj2MRiOuXbuGrl27Ys6cORg+fDg2bdqEXr16oV+/ftp42rRpg7fffhuhoaFYsGABevXqhRMnTiAiIgKDBg3CkiVL0KpVKwDAnj17cOHCBXTv3l27f61atfD777/n6vnydwxui8jJkyeR+OkSlI8NQfeOzVC2bGmIouDrYelKUYDklFQc+uMvfP3VF7DZbGjevLmvh0VE5ObC9XQs35GEkR3uQJBR8vVwiIiIiIgCUsWKFXH16lUAQGRkJPr06aPdNmXKFCxatAhnz55FxYoVMXz4cIwaNQqTJ0+GIAhYsmSJWwsAURTx6KOP4uOPP0a3bt1gMBhw9913u6zz3nvvYciQIWjdujUAoHnz5ujcuTNWrlyJSZMm5Xrs77zzDpYsWQKTyYSaNWviq6++QmRkJACgTp062uRbBoMBb7/9NmbOnKkFu2PGjMGcOXOwd+9e3H777Vi7di1OnjyJuLg4AECDBg287jcsLAyvvvoqjEYjmjRpggEDBuCTTz7xGNxeu3ZNG5OzTp06oVmzZgCARx55BJ9++immTJkCk8mENm3aICoqCocOHdKC20aNGqFHjx4AgL59+2LatGl44YUXEBYWhlq1aqFevXrYt2+fFtx+9dVXeOSRRwA4Qty4uDiMGDECANClSxftsVc5P4/PPvssZs6ciYMHD6JZs2YYPnw47rnnHrz11lsIDw/HkiVL0L9/fwQFBWn3iYyMxLFjx7w+ZsUJg9sisnPnTsRGGDCgb1cYDIHzsJcuFYNqVSsjyPQjdvy4Fffdd19AHT8RFQ87jlzAV7/8hwfqlsddVWN9PRwiIiIiokJTkCrYonbmzBnExjr+fzw9PR0TJkzA119/jatXr0IUHd0+L1++jIoVK6J9+/awWCzYvn07atSoge3bt+OTTz5x2+aQIUPQqlUrXLx40WNv1xMnTuCHH35waalgs9k8Bpw5GTlypNeq3CpVqrjtc+DAgZCkrKIRi8WC06dPIygoCEFBQW738SYuLg5Go1H7PT4+Htu3b/e4bkxMjNtkbQBcev6GhoYiIiLCpcI3NDQUqampXtf3tExdPyMjA9u2bcOSJUsAAGfPnkV8fLzL/uPj45GRkQHAUWk9adIkrFy5EhcuXIAoikhOTsbly5cBONoi1KlTB6tXr0bfvn3x+eef44cffnDZXnJyMmJiYjw+BsUNE7QiYLPZ8O+xo2jVpHbAhpYN7qqFXw/8jVOnTqFatWq+Hg4RkYsMq6N9jd3OntxERERERL5gs9mwfv16PPTQQwCAefPm4bfffsPOnTtRqVIlXL9+HTExMdo8OqIoYsiQIViyZAnuuOMOtG/f3uOkYzVq1EC1atWwbNkyjxNWVa5cGWPHjsXs2bM9jksNjAsi+zYqV66MBQsWoEOHDm7rXrhwAWazGf/99x8qV658y22fPXsWVqtVC29PnTqFihUrely3fv36mDJlSj6OIP+2bNmChg0bIjo6GoAjaD558qTLOqdOnULZsmUBAMuWLcOyZcvw7bffokaNGhAEweV5B4Dhw4djyZIlCAoKQnx8vFbZqzpy5Ah69eql74EVEU5OVgTS09Nht1kRExPl66H4TGxMFKDILmdoiIj8hcUqAwDsnEyRiIiIiKjIHT16FIMHD8aNGzcwfvx4AI6qyeDgYMTExCA1NRUvvfSS2/2GDRuGL774Ah999BGGDRvmdftLlizB9u3bPQa7I0aMwMcff4ytW7fCbrfDbDZjz5492mRh5cqVw/Hjxwt14vVRo0bhlVdewV9//QXAcazr169HSkoKypUrh27duuGJJ57AuXPnIMsy9u/fjytXrnjc1s2bNzFt2jRYLBbs3bsXiYmJGDBggMd177nnHgDAH3/8UWjHcitfffUVunTpov3eqVMnnDlzBh988AFsNhs2btzoUjGbnJwMk8mE0qVLw2KxYOrUqW6Tl/Xp0we//fYbZs+e7fa8p6Wl4ZdfftFOABR3DG6LgKIoUFA4Z2mKK/XYC/ODjoiosJhtjuDWZpd9PBIiIiIiosDw/PPPIyIiAlFRUejRowfKly+PX3/9VQtXx48fD0mSUK5cOdSpUwdNmjRx20a1atXQuHFjpKSkoFOnTl73Vb16da8Tpjdo0ADLly/Hyy+/jDJlyqBixYqYNGkSzGYzAOB///uf1sKhXr16hXDkwOjRozFkyBD06NEDkZGRuPPOO7Fs2TLt9qVLl6Jy5cpo3LgxoqOj8cQTTyA93fMEc3Xq1IHNZkOFChXQq1cvzJgxAw888IDHdQ0GgxZUF5UNGzaga9eu2u+xsbFYv349Fi5ciOjoaHz44YcuQfPgwYNRu3ZtxMfHo1q1aggJCUGlSpVcthkREYHevXvj6NGjbiH1mjVr8MADD7i1YyiuBIVJmovk5GRERUXhxo0bee5nktM2X587E326P4Aa1asWyjbzY826b/DqrIU4eeoMbqsWjxmvPoOO7Vp6Xf9/o17Ap8vXuS2/847b8PueDQCAabPfxPS5b7vcfnuNBBzau8llmd1ux6z5H6Fnn0dx1113FfxgiIgK0YKvjuCrX/7DlH710fxO97PwRERERETFQUZGBpKSkpCQkIDg4GBfD6dIDBs2DLGxsXj99dd9PZQit2TJEixYsAC///57ru+TnJyMBg0a4KeffkKZMmX0GxyA3377DY8++qguFb5Tp07FwYMHsXr1am2ZLMuoX78+VqxYgVq1ahX6PvPK2/sxL9ljYDZc9WMWiwUmk6nQt7tn7z4MemwCpk0aj4fat8Lnqzeg98DR2Lt1DWrXut3jfebNmojpr0zQfrfZ7Lj7/m7o2a29y3q1atbAprX/p/0eqH18iaj4smRW3Moyz2USERERERUX//77L1avXo3ffvvN10MpNiIjI/Hvv/8Wyb7sdrvX3sEFcenSJXzwwQfahGcqURRx8ODBQt+fLzFh87F2XQah1p01YJAMWL7qS9SpdTs2f+k+C2JBvfXep3iwTXNMGDMcAPDqxLHYsm03Fn+YiLfne25MHRUZgajICO339Ru/x7XryXh0QA+X9QwGCeXL6XuWhohIT+bMycmsnJyMiIiIiKhYGDFiBJYtW4YXXngBNWrU8PVwyAO1p25hmjFjBmbOnIlBgwahTZs2hb59fxO4TVf9yGcr1sFkMmLrpmV4c96rHtdZvuorxFZumOPPzj2/et3H3l9+R+uWTV2WtWvdDHt/+T3X41zy2Wq0btkE8ZVdZyf85/hJVK3VAnc0aIvBjz+DU6fP5nqbRET+QA1uWXFLRERERFQ8vPfee0hJScHEiRN9PRSfGTJkSJ7aJJQEEydOxM2bN/Huu+/6eihFghW3fuC2alUxa8qzOa7TucMDuLtRzk2wK1bw3pfx/MXLKFe2lMuysmVL48LFy7ka49lzF/Dt9zvwyfuuPWPubnQXPnxrFm6vkYBz5y9ixty30eahgdi360tERITnattERL6mtkqwMbglIiIiIiIiP8Hg1g80vKv2LdeJiAj3aRD62Yp1iI6KQNdOrmXoHdrdr/27bu07cE/ju1CjXmusXvcNhg7qVdTDJCLKF7PVEdza7bKPR0JERERERETkwODWD4SGhtxyneWrvsKo8ZNzXOfLle+jeZPGHm8rX7Y0Lly84rLs4sXLKFe29C33rSgKliR+gf6PdLvlxGnRUZGocVtV/Jt08pbbJSLyF2qrBLvCilsiIiIiIiLyDwxui4mCtkq49+762PrjHowZOVhbtmXbbtx7d/1b7vvHXT/j3+MnMXRgz1uum5p6E8eT/kP/R7recl0iIn+htkqwc3IyIiIiIiIi8hMMbouJgrZKGD1iENp2eRRvvPV/6PhgK6z6YiN++/0PLH5jqrbOy1Pn4ey5i/i/d+a43HfJZ2twT6O7ULvW7W7bfX7SHHTq8ACqVI7DuXMXMXX2W5AkEX16ds73WImIippaccset0REREREROQvRF8PgIpGk3sb4pP3X8dHn6zE3fd3wxdfbsaqz95yCWPPX7iE/06fdbnfjeQUrP1qM4Z4qbY9c/YCHn1sAure0xEDhj2NUrHR+HHz5yhTOlbX4yEiKkxqxa3M4JaIiIiIiHysVatWWLBgga+HgcTERDRt2rRA25g9ezaee+65QhpRwV2/fh2CIODEiRMF3lZiYiIGDBhQ8EHlgMGtj3331aeYN+ulItlXz+4dcPjnb5By/hD27/4KHdu1dLn9w7dn47uvPnVZFhUZgetnfsfwwY943OZnH83HiSM7kHL+EI7/sR2ffTQf1ROq6HYMRER6UCturZycjIiIiIhId61atYIkSTh48KC2LHugtmTJEtSvX9/j/ZcsWQJJkhAeHo7IyEhUrFgRPXv2xI8//ui2rqIouO2221CxYkXY7XaX21JSUvDkk0+iYsWKCA8PR+XKldG3b1+P++zYsSPCw8MRHh4Ok8kEg8Gg/R4e7v0K6ZyOIz9OnDgBQRC0/cbFxWHkyJFIT08vtH2oBgwYgN27d+f7/jdu3MD8+fOLPLg1m82Ijo7G5cuXdd1Pv3798PPPP2P//v267YPBLRERBTxW3BIRERERFa2YmBi8+OKL+b5/3bp1kZqaiuTkZBw6dAitW7dGx44dkZiY6LLetm3bcOrUKSQnJ2PTpk0utz399NM4ceIE9u3bh9TUVOzZswetWrXyuL9NmzYhNTUVqampeOmll9C5c2ft99TU1HwfR36dPn0aqamp2L17N7Zt24bp06e7rWOz2aD4cALmTz/9FPfffz9Kly5dpPvdunUr6tatq/t+RVHEgAEDsHjxYv32oduWSSMIAgD49M3ia4F87ETk3+yyolXassctEREREVHRePLJJ7Fr1y6PVbJ5FRsbi1GjRmHSpEl45plnIMtZV9J99NFH6Ny5M3r27ImPPvrI5X4//fQT+vXrh3LlHJO9V6pUCU888USe9//PP/+gffv2iI2NRfXq1bU2B/v378cTTzyBQ4cOaRWyp06dwv79+9G8eXPExsaiTJky6NevH65cuZKvY69atSo6deqkVS8LgoC33noLderUQVhYGFJTU/Hvv/+iS5cuKFOmDOLj4zF9+nSXx+i7777Dvffei+joaFSoUAGzZs0C4F4tXLVqVcyYMQMNGzZEZGQk2rdvj7NnXVtuOvvyyy/RunVr7Xe1Wvj//u//UK1aNYSHh+O5557DuXPn0K5dO0RGRqJly5Y4f/68dh/1eGrVqoWwsDAMGjQI165dQ58+fRAZGYkGDRrg6NGjLvv96quv0LVrVwCO6tuRI0ciNjYWCQkJWL16tcu6mzdvRuPGjREVFYUKFSrgySef1KqXFy5c6Bbkr1ixArVq1dJ+b9OmDb766iuvj0FBMbgtAkFBQRAEATdvpvl6KD6TejMNEAQEBwf7eihERC6stqz/YbGzVQIRERERlUD/PTXC44/17BkAgPXsGa/rqNL2/+bx9vMzXs3XmGJjY/H888/jhRdeKIxDBAD06tUL58+fx19//QXA0X5hzZo1GDJkCAYPHowNGzbgwoUL2vrNmjXD1KlT8f777+PgwYP5Kjqz2Wzo3Lkz7rrrLpw9exZr167F3LlzsWzZMjRo0ADvvvuuVh2cmpqKKlWqQBRFzJ49GxcuXMDhw4dx5syZfD8Ox48fx4YNG9CwYUNt2bJly7B582YkJydDkiS0adMGbdq0wZkzZ7Bjxw6sWLECH3/8MQBHuNytWzc899xzuHTpEo4ePYoHHnjA6/4+/PBDLFu2DOfPn0f58uUxcOBAr+v+/vvvqFmzptvyrVu34tChQ/j555+xcOFCPPLII1iwYAEuXboEk8mEmTNnuqy/fv167Ny5E8eOHcPmzZvRsmVLPPXUU7h69Srq16/v1orBObidMWMG9uzZg8OHD2P//v344osvXNYNCQnBBx98gKtXr2LXrl3YunUr5s+fDwAYOHAg9u7di6SkJG39jz/+GEOHDtV+r1WrFi5cuIBz5855fRwKgsFtETCZTKhUOQFH/z4esJWnR//6FwZjCOLj4309FCIiF2p/WwCwB+ZHNBERERGRT4wbNw4nT57EunXrCmV7FStWBABcvXoVgCPAjIiIQMeOHdGqVSvExcXhk08+0dZftGgRnnjiCSxZsgT33HMPypUrp4V2ubV3716cO3cO06dPR3BwMOrVq4fRo0djyZIlXu9z1113oXnz5jAajShXrhzGjx+Pbdu25Wm/8fHxiImJQdu2bdGxY0e89FLW/EnPPfcc4uLiEBQUhI0bNyImJgbjxo2DyWRClSpVMHbsWCxbtgwA8P7776Nv377o2bMnjEYjoqKicN9993nd78iRI1GzZk2EhoZi7ty52Lp1K06fPu1x3WvXriEyMtJt+csvv4ywsDDUqlVLeyxq166NoKAgPPzww9i3b5/L+s888wxiY2MRFxeHli1bonbt2mjevDkMBgN69+7tsv7vv/+O4OBg3HHHHQAcE4i99NJLiIuLQ3R0NCZPnuyy7RYtWqBBgwaQJAnVqlXDiBEjtOeiVKlS6Nq1K5YuXQoAOHPmDLZv345BgwZp91eP79q1a14fs4Iw6LJVcnPPvfdizapl2LxlJ+67pz6iIiN8PaQiYTZbcOToMWzb9Rvq1G/Cilsi8jtmm1Nwy4pbIiIiIiqBKr/5Xo63G+Mq3nKd0AaNEHqLdfIqJCQEkydPxksvvYQdO3YUeHtnzjgqiGNjYwE42iT0798fRqMRADBo0CD83//9H5599lkAjiukJ0yYgAkTJsBsNmPVqlUYNmwY6tSpgwcffDBX+zx9+jTi4uJgMpm0ZdWqVcNnn33m9T7//PMPJkyYgF9++QWpqamQZVkbY26dPHkS0dHRHm+rUiVr0vgTJ07g8OHDLuvKsozKlStr22nRokWu9+tckFeuXDkEBQXhzJkzqFSpktu6MTExSE5OdluutqYAgNDQULffs/cMzn6787FkX9+52hYAzp496zLm7AWFv/zyC1588UUcOnQI6enpsNlsWugLAMOGDcPIkSMxefJkfPLJJ3jwwQdRvnx57Xb1+GJiYtyOszAwuC0id911F1JTU7Hlu2/wy/6jCA4yQJJKdsGzLCswW2xQIKFW3UYubxwiIn9hsWaFtexxS0RERERUtIYPH4758+drVY0FsXr1apQvXx533HEHfv/9d+zbtw///vsvVqxYAcDR7/T69evYtWsXmjVr5nLfoKAgDBw4EG+88QYOHTqU6+C2UqVKOHv2LKxWqxa+njhxQgsyRdE9+3niiSdw++23Y+nSpYiOjsa6deswZMiQAhy5K+d9Vq5cGY0aNcJPP/3kcd34+Hj8888/ud72yZMntX9fvHgRZrNZq3TOrn79+jh69KhLn1u9ffnll5g3b572e1xcHE6ePIl7770XAHDq1CmX9fv164ehQ4di/fr1CAsLw4IFC1yqpdu1awebzYbt27dj6dKlWv9f1ZEjR1CuXDlUqFBBl+NhcFuEmjVrhsaNG+PYsWO4ceOGSyPokkgQBISGhqJ69eqIiory9XCIiDxyrriVGdwSERERERUpSZIwY8YMjBgxwu02RVGQkZHhssy5slV17do1rFy5EtOnT8d7770HURTx0UcfoUGDBvj6669d1h04cCA++ugjNGvWDFOmTEG7du3QoEEDmEwmbNy4EUeOHEGTJk1yPX61xcIrr7yCV199FceOHcObb76JuXPnAnBUi547dw7p6ekICQkB4KjSjIiIQGRkJP777z+89tprud5fXnXu3BkvvvgiFi9ejGHDhsFoNOKff/7BuXPn0KpVKzz22GNo3rw5OnfujC5duuDmzZv4888/vbZLeO+999CtWzdUqVIFzz//PO6//36P1bYA0KVLF2zduhVPPvmkbsfn7Ny5c0hKSnIJ5fv164fZs2ejefPmCA0NxdSpU13uk5ycjOjoaISFheHPP//EO++8oz1PgCMEHzp0KMaNG4erV6+ic+fOLvf/4Ycf0KlTJ92OicFtEQsKCkKdOnV8PQwiIspkZsUtEREREZFP9ezZE6+99hquXLnisvzgwYMuIRrgmNgKAA4dOoTw8HCIoojw8HDcd9992LhxI1q2bImMjAwkJibijTfecLmsHXD01e3bty8WLlwIg8GAkSNHIikpCaIoolq1avjwww/RtGnTXI/daDRiw4YNGD16NMqXL4+YmBiMHz8e/fv3BwC0bt0a9913HypWrAhZlnHw4EHMnz8fI0aMwNtvv43bb78dAwcOxB9//JGfh+6WwsPD8f333+O5557D1KlTkZGRgerVq2vtIho2bIg1a9Zg0qRJGDx4MMLDwzF27Fivwe2wYcPQr18//PPPP7jvvvuQmJjodd+DBg3CtGnTcOXKFZQqVUqX43O2YcMGdOzYEZIkactefvllXLx4EXXq1EFkZCRefvllbNy4Ubv9vffew/jx4/H888+jUaNG6Nu3L9avX++y3aFDh2LatGkYN26cS0sLWZaRmJioVXTrQVACdbYsL5KTkxEVFYUbN254bKBMREQly+9JVzHh418AAG3rVcCLver5eERERERERPmTkZGBpKQkJCQkcI4ZKnRVq1bFggUL0L1791zfZ9asWbh+/TrmzJmj38AydenSBY8++ih69+5dqNtNS0tD2bJl8dNPP7kUYy5btgwbN270Gl57ez/mJXssNk1W7XY7Jk2ahISEBISEhKB69eqYNm0anHNnRVHwyiuvoEKFCggJCUHbtm1x7NgxH46aiIj8ndma1SqBFbdERERERESF58UXXyyS0BYAWrRogQ4dOhTqNhVFwZtvvokGDRq4XUHfv3//HCuOC0OxaZUwZ84cvPPOO1i6dClq166NX3/9FUOHDkVUVBTGjBkDAJg7dy4WLVqEpUuXIiEhAZMmTUL79u1x5MgRnmkiIiKPnINb9rglIiIiIiIqnp577rlC3Z7dbkd0dDRKly6NNWvWFOq2c6vYBLe7d+9Gt27dtIa/VatWxfLly/Hzzz8DcCTgCxYswMsvv4xu3boBAD755BOUK1cO69atQ9++fX02diIi8l8WG3vcEhERERER3cqJEyd8PYQiJUkSUlJSfDqGYtMqoWnTptiyZQv+/vtvAMCBAwewc+dOdOzYEQCQlJSE8+fPo23bttp9oqKicO+992LPnj0+GTMREfk/58nJ7HY5hzWJiIiIiIiIik6xqbh94YUXkJycjJo1a0KSJNjtdsyYMQMDBgwAAJw/fx4AUK5cOZf7lStXTrvNE7PZDLPZrP2enJysw+iJiMhfObdKsLPgloiIiIhKAM5DT+R7hfE+LDYVtytXrkRiYiKWLVuGffv2YenSpXj99dexdOnSAm131qxZiIqK0n4qV65cSCMmIqLiwLlVAituiYiIiKg4kyQJAGCxWHw8EiJKS0sDABiNxnxvo9hU3D777LN44YUXtF61devWxcmTJzFr1iwMHjwY5cuXBwBcuHABFSpU0O534cIF1K9f3+t2X3zxRYwfP177PTk5meEtEVEAca64ZY9bIiIiIirODAYDQkNDcenSJRiNRohisanXIyoxFEVBWloaLl68iOjoaO2ESn4Um+A2LS3N7QNHkiTIsqM6KiEhAeXLl8eWLVu0oDY5ORl79+7FyJEjvW43KCgIQUFBuo2biIj8m3NwKzO4JSIiIqJiTBAEVKhQAUlJSTh58qSvh0MU0KKjo7VC0/wqNsFtly5dMGPGDFSpUgW1a9fG/v37MX/+fAwbNgyA48Np3LhxmD59OmrUqIGEhARMmjQJcXFx6N69u28HT0REfkttlWCURFjZKoGIiIiIijmTyYQaNWqwXQKRDxmNxgJV2qqKTXD75ptvYtKkSXjyySdx8eJFxMXFYcSIEXjllVe0dZ577jncvHkTjz/+OK5fv47mzZvjm2++QXBwsA9HTkRE/sxsdYS1ISaJFbdEREREVCKIosgshKgEEBRONegiOTkZUVFRuHHjBiIjI309HCIi0tnM1Qex5eA5lI8OQbBJwkejm/l6SERERERERFRC5SV7ZJdqIiIKaBarDAFAsEmC3c5zmUREREREROQfGNwSEVFAM9vsCDJKMIgC7LwIhYiIiIiIiPwEg1siIgpoZqsMk0GEKAqsuCUiIiIiIiK/weCWiIgCmtnqqLg1SiJssuzr4RAREREREREBYHBLREQBzmy1axW3ssyKWyIiIiIiIvIPDG6JiCigWWyy1uPWylYJRERERERE5CcY3BIRUUAzW2UEGUVIksiKWyIiIiIiIvIbDG6JiCigmW12mAwSJAGwKwxuiYiIiIiIyD8wuCUiooDmaJXgqLi12Tk5GREREREREfkHg68HQERE5CuKosBstSPIIEEQALusQFEUCILg66ERERERERFRgGPFLRERBSyLzVFhazKKkERHWMs2t0REREREROQPGNwSEVHAUoPbIIOkBbdsl0BERERERET+gK0SiIgoYJmtdgBAkFHUJiaTOUEZERERERER+QFW3BIRUcAyq60SDCIMWsUtg1siIiIiIiLyPQa3REQUsCxaxa0EMTO4tbPJLREREREREfkBBrdERBSw1IrbIKOkVdwyuCUiIiIiIiJ/wOCWiIgCltrj1mQQIUmOP4mcnIyIiIiIiIj8AYNbIiIKWBanilvJUXDLilsiIiIiIiLyCwxuiYgoYJm1HrciDJkVtzKDWyIiIiIiIvIDDG6JiChgma2OiluTQYSU2ePWylYJRERERERE5AcY3BIRUcBybpUgZga3ssKKWyIiIiIiIvI9BrdERBSwslolSDBqk5MxuCUiIiIiIiLfY3BLREQBSw1uTQZRq7jl5GRERERERETkDxjcEhFRwMpqlSDCwOCWiIiIiIiI/AiDWyIiClhaqwSDBElicEtERERERET+g8EtEREFLLPVUXFrMoqQBEdwa7PLvhwSEREREREREQAGt0REFMC0VgkGCVLm5GSsuCUiIiIiIiJ/wOCWiIgCltYqwSixxy0RERERERH5FQa3REQUsCw2R3BrMogQGdwSERERERGRH2FwS0REActsk2GUHKGtUWKPWyIiIiIiIvIfDG6JiChgWawyTAbHn0K14lZmxS0RERERERH5AQa3REQUsMxWO4KMEgBAygxubQxuiYiIiIiIyA8wuCUiooBlsWVV3Bokx3/Z45aIiIiIiIj8AYNbIiIKWC4Vt4La45bBLREREREREfkeg1siIgpYZqcet1Lm5GR2mZOTERERERERke8xuCUiooBlsWVV3BpEtkogIiIiIiIi/8HgloiIApbZKiPI6PhTKIpqxS2DWyIiIiIiIvI9BrdERBSwzDZ71uRkInvcEhERERERkf9gcEtERAHJLiuwy0rW5GQSK26JiIiIiIjIfzC4JSKigGS22gEgK7gVOTkZERERERER+Q8Gt0REFJDU4DZ7qwRW3BIREREREZE/YHBLREQByWJzVNZmVdw6/iQyuCUiIiIiIiJ/wOCWiIgCktYqIbPiVu1xy8nJiIiIiIiIyB8wuCUiooBktjoqbk3GzOCWrRKIiIiIiIjIjzC4JSKigKS1SjA4WiWwxy0RERERERH5Ewa3REQUkLRWCdl63Nrsss/GRERERERERKRicEtERAHJbHMEtyYDWyUQERERERGR/2FwS0REAcmS2eM2KLPHrSFzcjJZYXBLREREREREvsfgloiIApJacau2ShAFR3DLVglERERERETkDxjcEhFRQDJnVtyqrRJEUYAoCGyVQERERERERH6BwS0REQUki01tlSBpyyRRgI3BLREREREREfkBBrdERBSQzFbXVgmAI7i12xncEhERERERke8xuCUiooCkBrdqqwQgM7hlxS0RERERERH5AQa3REQUkLJaJWT9KTRIIoNbIiIiIiIi8gsMbomIKCBlWDy3SrDJsq+GRERERERERKRhcEtERAFJrbh1bpVgkATIrLglIiIiIiIiP8DgloiIApKnyclEQYCNk5MRERERERGRH2BwS0REAclskyEKAgyioC3j5GRERERERETkLxjcEhFRQLLZZRgNIgQhK7g1SCJ73BIREREREZFfYHBLREQByS4rLtW2QGbFLVslEBERERERkR9gcEtERAHJLisu1bYAWyUQERERERGR/2BwS0REAUn2UHFrkBjcEhERERERkX9gcEtEVIJ8/dtpHL+Q4uthFAt2WYGYLbgVWXFLREREREREfoLBLRFRCWG22jFv/R9Ys/ukr4dSLNhlBQYpW8WtKDK4JSIiIiIiIr/A4JaIqISw2mWX/1LO7LIC0UOPWxsfPyIiIiIiIvIDBr13kJSUhB07duDkyZNIS0tDmTJl0KBBAzRp0gTBwcF6756IKGDImZWiNjsrRnPDLiuQRE5ORkRERERERP5Jt+A2MTERCxcuxK+//opy5cohLi4OISEhuHr1Kv79918EBwdjwIABeP755xEfH6/XMIiIAoYtM3CUGTzmiqy4B7ecnIyIiIiIiIj8hS7BbYMGDWAymTBkyBCsWbMGlStXdrndbDZjz549WLFiBRo3bozFixejd+/eegyFiChgqIGjTeal/rlhtyuQJFbcEhERERERkX/SJbidPXs22rdv7/X2oKAgtGrVCq1atcKMGTNw4sQJPYZBRBRQZFbc5oldURAkurZ6l0QBsqJAlhWI2apxiYiIiIiIiIqSLsFtTqFtdqVKlUKpUqX0GAYRUUBRWyWwxW3u2O0KBCF7qwRHkGtXFIhgcEtERERERES+I956lYJp2bIlPvnkE6Snp+u9KyKigMaK27yRFQWGbK0SxMwg1870m4iIiIiIiHxM9+C2QYMGeOaZZ1C+fHk89thj+Omnn/K9rTNnzmDgwIEoVaoUQkJCULduXfz666/a7Yqi4JVXXkGFChUQEhKCtm3b4tixY4VxGEREfs9md/S2ZY/W3LF7aIegBrnsE0xERERERES+pntwu2DBApw9exYff/wxLl68iPvvvx+1atXC66+/jgsXLuR6O9euXUOzZs1gNBqxadMmHDlyBPPmzUNMTIy2zty5c7Fo0SK8++672Lt3L8LCwtC+fXtkZGTocWhERH5FVjg5WV7YZQUGtx63jt9ZtUxERERERES+pntwCwAGgwE9evTA+vXrcfr0afTv3x+TJk1C5cqV0b17d/zwww+33MacOXNQuXJlfPzxx7jnnnuQkJCABx98ENWrVwfgqLZdsGABXn75ZXTr1g316tXDJ598grNnz2LdunU6HyERke9lFtwydMwlu6wg+/xjkqhW3PIxJCIiIiIiIt8qkuBW9fPPP2Py5MmYN28eypYtixdffBGlS5dG586d8cwzz+R43y+//BKNGzdG7969UbZsWTRo0AAffPCBdntSUhLOnz+Ptm3basuioqJw7733Ys+ePV63azabkZyc7PJDRFQc2TOTWxv7s+aKXZYhSdkrbtnjloiIiIiIiPyD7sHtxYsXMW/ePNSpUwctWrTApUuXsHz5cpw4cQJTpkzBhx9+iM2bN+Pdd9/NcTvHjx/HO++8gxo1auDbb7/FyJEjMWbMGCxduhQAcP78eQBAuXLlXO5Xrlw57TZPZs2ahaioKO2ncuXKBTxiIiLfsGe2SlBbJlDOZAXINjeZ1uOWfYKJiIiIiIjI1wx676BSpUqoXr06hg0bhiFDhqBMmTJu69SrVw933313jtuRZRmNGzfGzJkzATgmPTt8+DDeffddDB48ON/je/HFFzF+/Hjt9+TkZIa3RFQsqVWiDB1zx26X3SYn0ypu2SeYiIiIiIiIfEz34HbLli1o0aJFjutERkZi69atOa5ToUIF1KpVy2XZnXfeiTVr1gAAypcvDwC4cOECKlSooK1z4cIF1K9f3+t2g4KCEBQUlOO+iYiKAzWw5WX+ueN5cjL2uCUiIiIiIiL/oHurhFuFtrnVrFkz/PXXXy7L/v77b8THxwMAEhISUL58eWzZskW7PTk5GXv37kWTJk0KZQxERP6MrRJyT5YVKACy5baQMhewapmIiIiIiIh8TfeKWwBYvXo1Vq5ciVOnTsFisbjctm/fvlxt4+mnn0bTpk0xc+ZMPPLII/j555/x/vvv4/333wcACIKAcePGYfr06ahRowYSEhIwadIkxMXFoXv37oV9SEREfoetEnJPDbmlbMmt2uOWE7wRERERERGRr+lecbto0SIMHToU5cqVw/79+3HPPfegVKlSOH78ODp27Jjr7dx9991Yu3Ytli9fjjp16mDatGlYsGABBgwYoK3z3HPP4amnnsLjjz+Ou+++G6mpqfjmm28QHBysx6EREfkVrVUCg9tbkmU1uPXW45aPIREREREREfmW7hW3ixcvxvvvv49+/fphyZIleO6551CtWjW88soruHr1ap621blzZ3Tu3Nnr7YIgYOrUqZg6dWpBh01EVOyoE2oxdLw1+y2CW5mPIREREREREfmY7hW3p06dQtOmTQEAISEhSElJAQAMGjQIy5cv13v3REQBgxW3uectuFUnK7PZ5SIfExEREREREZEz3YPb8uXLa5W1VapUwU8//QQASEpKgsIJdIiICo3M4DbX1MdIzBbcimyVQERERERERH5C9+C2devW+PLLLwEAQ4cOxdNPP4127dqhT58+ePjhh/XePRFRwLBpwS2rRW9FVrxU3GZOTmbniUUiIiIiIiLyMd173L7//vuQM0OEUaNGoVSpUti9eze6du2KESNG6L17IqKAoVaJslj01uz2zIpbwXOPW7ZKICIiIiIiIl/TPbgVRRGimFXY27dvX/Tt21fv3RIRBRytxy1Dx1tSHyu1wlZlYKsEIiIiIiIi8hO6BLcHDx7M9br16tXTYwhERAGHk5M5WGwyrqWaUS46xOs6ajsJt4pbyXGiUa3IJSIiIiIiIvIVXYLb+vXrQxAEKIoCIduX4uzsdrseQyAiCjjq5GRK5r+zT7wVKNbvPYWPvj+Gz59piagwk8d11HA7e49brVVCgIffRERERERE5Hu6TE6WlJSE48ePIykpCWvWrEFCQgIWL16M/fv3Y//+/Vi8eDGqV6+ONWvW6LF7IqKA5Bw2BvLkWhdvZMBql5GcbvW6zq2CW5nBLREREREREfmYLhW38fHx2r979+6NRYsW4aGHHtKW1atXD5UrV8akSZPQvXt3PYZARBRwnMNGu12BUfLhYHzImtnjN6cJxuTMYDt7VbKBFbdERERERETkJ3SpuHV26NAhJCQkuC1PSEjAkSNH9N49EVHAsMlZQWUg97m12ByPg5xD1bGa6RqyBbdqkMsJ3oiIiIiIiMjXdA9u77zzTsyaNQsWi0VbZrFYMGvWLNx55516756IKGA4V9zmFFqWdBaro3d6TtmrGsxmr7g1qpOTBfDjR0RERERERP5Bl1YJzt5991106dIFlSpVQr169QAABw8ehCAI+Oqrr/TePRFRwHCusmXF7a1aJTj+m73HbVbFbeA+fkREREREROQfdA9u77nnHhw/fhyJiYk4evQoAKBPnz7o378/wsLC9N49EVHAYHDroAa3OT0GalsJb5OTscctERERERER+Zpuwe0rr7yCbt26oVGjRggLC8Pjjz+u166IiAjZg9vA7dGq9bjNIXxVb5NE145BBrVVAnvcEhERERERkY/p1uP29OnT6NixIypVqoSRI0di06ZNLn1uiYiocNnsrLgFAKvaKiHHilvHbdkKbpGZ27LiloiIiIiIiHxOt+D2//7v/3D+/HksX74cERERGDduHEqXLo2ePXvik08+wdWrV/XaNRFRQHKekCynatOSzmLLnJwspx63asWt5PpnUBQEl9uJiIiIiIiIfEW34BYARFFEixYtMHfuXPz111/Yu3cv7r33Xrz33nuIi4vD/fffj9dffx1nzpzRcxhERAHBuco2kCtGLbmouLVrrRJclxszFwTy40dERERERET+QdfgNrs777wTzz33HHbt2oVTp05h8ODB2LFjB5YvX16UwyAiKpHsdlbcArmbnEwLbgXXXgliZu8E9rglIiIiIiIiX9NtcrJbKVu2LIYPH47hw4f7aghERCWKXWGPWyCPk5NJ2ScnywxuA/fhIyIiIiIiIj+he3CbkZGBN998E1u3bsXFixchZ5vpfN++fXoPgYgoIDhXiQZycGu2Onrc2nKomvU+OZkjyC0uFbcZFjsu3EhHfJlwXw+l0KRbbAgySFr1MxERERERUaDSPbgdPnw4Nm/ejF69euGee+6BIPCLGBGRHpzD2kAObrVWCYr3x0BR1B63rhW3UmZYWFx63C778ThW7EzCFy88gPBgo6+HU2DXUs0Y8MYOPNXpTnRsWNHXwyEiIiIiIvIp3YPbDRs24Ouvv0azZs303hURUUBjcOsIZK12tcet9/VsdjW4dT2ZKGk9bovH43cjzQK7rCDdbC8Rwe2FGxkwW+04c+Wmr4dCRERERETkc7pPTlaxYkVERETovRsiooDnHNYG6uRkarUtkHO7A1mtuJVcg9usHrfF4/GzZgbMNrl4tHa4FbPF0ebCbC0Zx0NERERERFQQuge38+bNw/PPP4+TJ0/qvSsiooDmHDYWl0v9C5tzcJvTY6BV3GZr3yMKasVt8QgO1T6+JSWoT7PYALg+j0RERERERIFK91YJjRs3RkZGBqpVq4bQ0FAYja6Xcl69elXvIRARBQTny/vlYlIxWtisToFrTmGmelv2VgkGyXE+s7gE39bMgNNaTFo73EpGZsWtxWb38UiIiIiIiIh8T/fgtl+/fjhz5gxmzpyJcuXKcXIyIiKduPS4LSFBXl5ZrLmruFWDbVHMXnGbeXtxCW61fr4lo0I1na0SiIiIiIiINLoHt7t378aePXtw11136b0rIqKAxsnJXCs1cwpfbV4qbgVBgEEUik3FrdryoZh0drglVtwSERERERFl0b3Hbc2aNZGenq73bihA/XHqOhZt+LPYVMcR6ck1uC0hSV4eOfdGteY0OZmX4BYAJEksNj1u1WO0FZPx3kq6FtyWjOMhIiIiIiIqCN2D29mzZ2PChAnYtm0brly5guTkZJcfooL47sBZrP/5FC6nZPh6KEQ+J7Pi1iXwy7ni1rGe6KF9jyQIKC6dJrJaJRSTAd9COicnIyIiIiIi0ujeKqFDhw4AgDZt2rgsVxQFgiDAbuflkJR/6mW1AVpcSOTCJucutCzJrE6BX05hpvpQSZKnilvBpYJ1++HzCDFJuOf2MoU30EKS1SqhZDzfam9bBrdERERERERFENxu3bpV711QAFOrswL1snAiZ85hbXHp0VrYzLkMbtXPDE+tEgyi4HLft74+itKRQX4a3JasVglpZsdnutnKk7pERERERES6B7ctW7bUexcUwNR+iCWl2oyoIJzD2kB9SzhPapVzcOu4zeAhuBVFQQvBFUXBjTQLIkONhTzSwlHSWiVkZAa2VlbcEhERERER6R/cAkBGRgYOHjyIixcvQs5WGdm1a9eiGAKVUBkMbok0Lj1uS0gFZl5Zct0qwXGb6LHiVtQC0TSzHXZZ8dsgUR2Xrbg05b0F9TNdbZlAREREREQUyHQPbr/55hs8+uijuHz5sttt7HFLBaVeVsvglsj1fWBXAvM9YXEK/HJqH6BWJ3ucnEzKqrhNTrc4tuunwW1Wj1v/HF9eqVdROFdOExERERERBSpR7x089dRT6N27N86dOwdZll1+GNpSQbFVAlEWl+C2hFRg5pVzwCrnEF6rN3nrcasGuynpjpND/lpxq/W4LSGfgWrfcn8NyomIiIiIiIqS7sHthQsXMH78eJQrV07vXVEAYqsEoiwuwW2AviesdueKW++PgRp4egpuRVHQgu8baf5dcWvNHKdcQp5vtcetxSZDCdCqcSIiIiIiIpXuwW2vXr2wbds2vXdDASrdyuCWSGWXFRglx8d6TtWmJZnFmrvJydTHR5Lc/wwaREFrNZGcZgXgGgj7EzWAtpaQCmv1ZJysKPxcJyIiIiKigKd7j9u33noLvXv3xo4dO1C3bl0Yja4zc48ZM0bvIVAJZZcVmDNDmpJSbUZUEHZZgcngmFirpExWlVe5nZxMfXw8FNxCkkTY7Y5L9lOcgltZVjxOZuZLaqBcUj4D08xZwbvZKsPgIVgnIiIiIiIKFLoHt8uXL8fmzZsRHByMbdu2QXCaCEYQBAa3lG9mp8q6ktLfkagg1OD2pjmAK25dglvvVbJqqGsQPVfc2jLvq05OBjhC0iBRKqyhFpgsZ1Wl2krI5GTOn+sWmx1h+v9vChERERERkd/S/RvRxIkTMWXKFLzwwgsQPXxBJsovdWIygK0SiABHUBkaZMz8d2C+J3JbcasG254qaEVR0CpY1VYJ6raDjP4T3Dq3bygJk9HZ7LLLMflrX2EiIiIiIqKionuSarFY0KdPH4a2VOgyMmcfB3KurCMKFM49bhnc5lyJrz4+niYnM4iC1jM2OT0ruPW3PrfO7TBKwlUHzifjAAa3REREREREuqepgwcPxueff673bigAOfdCDNSQisiZ2ioBAOx+FjIWFYvN8bkgIOcqVLWi1luPW/X2G04Vt1Y/CxJtLhW3/jW2/MjIFtw6t00gIiIiIiIKRLq3SrDb7Zg7dy6+/fZb1KtXz21ysvnz5+s9BCqhnKuzSsrEPET5pSiOfqemzEv5S8CV8/miVmkGm6ScJyeTFUii4NJ3XeXc4zYl3X+DW+cK4JJQcZuRGdSaDCIsNpkVt0REREREFPB0D24PHTqEBg0aAAAOHz7scpunL8xEueXcKqEkhBZEBaG+BdSK20A9mWGxyTCIAoySeMset6KXv0GiKGj3TU7LmpzM34JE51YJJeGqA/VkXFSoCZeSM/zu8SYiIiIiIipquge3W7du1XsXFKBYcUuURQ3u1ODWVgIunc8Pi02GySDBIIla1awndrvisb8t4Ki4tcsKFEVxnZzMzx5Tl8nJSsBnYHrmybioUKMjuGWrBCIiIiIiCnCcMYyKrTSn4NYWqNeFE2WSswW3JSDHyxerTYbJIEIShRxP6Nhl78Gtutxik3HTnFXZ78+tEkpSj9vIUBMAwOxnjzcREREREVFR0yW4feKJJ3D69Olcrfv5558jMTFRj2FQCefcKkFWAjSlIsqkVpdqk5PlUG1akllsdpiMjuA2pxM6dlmBeIvg9vpNi8vv/nbpvvPxWUvAyausVgmOXvisuCUiIiIiokCnS6uEMmXKoHbt2mjWrBm6dOmCxo0bIy4uDsHBwbh27RqOHDmCnTt3YsWKFYiLi8P777+vxzCohEtnxS2RRq0uNUpqcBuY7wmLTdYeg5xO6NhlBQZvrRIy738tM7iNDQ/CpeQM/6u4dRpPSTh5pQW3YY6KWws/14mIiIiIKMDpEtxOmzYNo0ePxocffojFixfjyJEjLrdHRESgbdu2eP/999GhQwc9hkABgD1uibLYtFYJEoAADm6tjlYJdkXJ8YSOoty64vZaqhkAUCoiKHOyLP+qAHXuY1wSTl5lOPW4BQAzK26JiIiIiCjA6TY5Wbly5TBx4kRMnDgR165dw6lTp5Ceno7SpUujevXqELzM5k2UWxlOwa29BFSbERWENjmZkRW3ocEmWKx2lx6w2dlkBQbRc7cgUQtuHRW3pSKCAPhfj1uLy+Rk/jW2/Mje49bfWlMQEREREREVNd2CW2cxMTGIiYkpil1RAElzmjTIVgIm5iEqCLXqXL3MP1Cr0K12R8WtLCvIyKFiU5YVeMlttVYLV50qbgH/u3S/pFXcZu9xy4pbIiIiIiIKdLpMTkZUFNgqgSiL2irBIAqOibkC9D1httphMogQRQE5FaHa7DJEL1d+qBW31zMrbktHBgPwv4pb57C2JFRYZwW3jopbf3u8iYiIiIiIihqDWyq2nKuxAjWkIlKpJy+kzOC2JExWlR8Wm6Pi1iAKObZKkBVAkrz0uM1cfDVbqwR/63FrLaGtEqLCHBW32Vsl/Hn6Bj7fmVTk4yIiIiIiIvIVBrdUbLHiliiLetm8GtzaS8Cl83kly4rWKkEShRw/F+yyDMlLxa3abuL6TbXi1j973Ja0Vglqa4vIEEfFbfZWCev3nsL7m/9GcpqlyMdGRERERETkCwxuqdhy7nFbEi4TJioItcJWFAWIghCQ7wm1AtVkkG7ZLsIuK1pAm52U2SrhaooZAoDYcLXi1t+CW6dWCSWgwjrdYoNBFBAa5Gi/n/3xVj/zU9KtRT42IiIiIiIiX2BwS8VWhsWOIKMEgMEtkVp8qfa4DcT3hBr0mQwiJEnMseJWlrN62WantlC4dtOC8BAjgoyOP5U5tV7wBedgsyRU3KZb7Ag2GbTHO3twq15lkZzG4JaIiIiIiAKD7sHthQsXMGjQIMTFxcFgMECSJJcfovxKt9gRllmZFYghFZEze2aoKIoCDJIYkO8J5+DWIAqw5dD31ZZTqwTR8acxNcOKyBAjTAbH3yqz1b+CW+dWCSWhXUyGxY4Qk6NaWhQEt57C6ZbMitsMm6e7ExERERERlTgGvXcwZMgQnDp1CpMmTUKFChUgePmiTJRX6RYbSkUG4WqqOSBDKiJn6qXyBkmEKOTc37WkUoM+k0GEeIuqY0XxXnHrvDwq1ASjwT8rbp2rbG1+Nrb8SM8MbgVBgMkgugXlaWbH88tWCUREREREFCh0D2537tyJHTt2oH79+nrvigKIoijIsNoREeyYfZzBLQU6dTIySRAy+7sW/yAvr9SKW2Nmxa1dVqAoiscThja7rPWyzc7gtDwy1AiTGtz6WY9b5yC5JHwGZljsiApzfKabDKJbq4QMC4NbIiIiIiIKLLq3SqhcuTKUEjBpCvkXi02GXVYQFsxWCURA1ntAFAVIkoBA/Ni1WLMmJ1OrZr19NNhlxWtwq/a4BYCIEKMfV9w69bgtAZ+B6RYbQkyOz3STQXJrlXCTk5MREREREVGA0T24XbBgAV544QWcOHFC711RAFErr7J63PpXoEJU1LJaJQiQBKFEXDqfV9l73ALeWwjYZcX75GSCa3BrEAUIyAqG/YVaASwKgtbjuDjLsDpaJQBAkNFTxa1/BbeHT13Du9/8xZPTRERERESkG91bJfTp0wdpaWmoXr06QkNDYTQaXW6/evWq3kOgEkidXTw8hK0SiICsVgmiIDj6uwZgmKRWxJqMIiTJcV5S9vI4yIri0hLBmXpfwNEqQRAEGA2i31XcWjOf8yCjWOwrbu2yAotNRpDREdwaDaJLUG6xydoxpvrJ5GTf7juLr/edRo8mVVA2KsTXwyEiIiIiohJI9+B2wYIFeu+CApA6u3g4WyUQAch6DxgkR4/b7BM7BQKLVZ2cTNKqZp0n8HKWU8WtIdvkZOo2s1eA+poaJIeYDFpwX1ypV1FkVdxKuG62ON2eFdb6S8Wt2ZbVc5fBLRERERER6UH34Hbw4MF674ICkFZxy8nJiABktQsRRUdwG4jvCbPaKkEStD61sofHQVEU2OWcKm5dJycDPE+W5WtqG4ggo1jsK6zVk3FqcOt4vLN63KaZs/7tN8GtVQ1u/aMCmIiIiIiISh7dg1sAsNvtWLduHf78808AQO3atdG1a1dIklQUu6cSSA1uQzN73HoKZ4gCiVZxmxncemsRUJJpPW6NUlaPWw+fDeqi3FTcRma2YzFKottkWb6mVhMHGyWXYLM4UkPQYKeKW+eq8XQ/rLjNyBxfcprlFmsSERERERHlj+7B7T///IOHHnoIZ86cwR133AEAmDVrFipXroyNGzeievXqeg+BSqAMLbiVIIlCse/vSFRQ6skLteLWW4uAksx5cjI1lPU0caEackteglvnQFetuDUaBG0yMH+htkoINkm4keYfYWZ+qcFziMnxvyVGSSg2FbfJxfyxJyIiIiIi/yXeepWCGTNmDKpXr47//vsP+/btw759+3Dq1CkkJCRgzJgxeu+eSii132GwyRHcsuKWAp3NKYyURCEgZ7q3OgW3Bi249VBxK2dN5OaJQXSdnMyxTT/scWuTIYkCjJJY7D8D0z30uLXJivb8pTlV3PrL5GTqCUR/CZKJiIiIiKjk0b3idvv27fjpp58QGxurLStVqhRmz56NZs2a6b17KqHSLFnVWay4JXKuIhUD9j2hVmiaDJJWNesp0LxVxa1Lj9sQx+RkRoOIm34SGKpsdhkGqWQ83xnZWiWYDI7w3GqTIZkkLSR1TLxnh9lqR5DRt+2W1CA/mcEtERERERHpRPeK26CgIKSkpLgtT01Nhclk0nv3VEI5V2dJYvGvNiMqKOcwUgzQKnQ1SDMaRBikzODPQ8sIdSIvg+QluM2sxDVKIoKMju1knyzLH1jtjgnWJEn02BKiOHG+igJwhO9AVhifZnbcXjoiGIB/VN2yVQIREREREelN9+C2c+fOePzxx7F3714oigJFUfDTTz/hiSeeQNeuXfXePZVQGU4zkEui4PFyaKJAkn1yskB8Tzj3uJVyqrjN7A0reGmVoFbcRoYatXUck5P5Vzhqs8swSiIMUvHvaZy9VYJacatOUKbeXjbaEdz6Q3sCLbj1g7EQEREREVHJpHtwu2jRIlSvXh1NmjRBcHAwgoOD0axZM9x2221YuHCh3runEirdrVWCfwUqREUt++RkARncWtVWCVnBracWAs4htydqj9vIEKO2zFFx61+fMza7AqNBhCQIkIt5T2Pnz3QAWqWzWnGbnllxWzbKf4Jbtb2DP4yFiIiIiIhKJt2D2+joaKxfvx5//fUXVq9ejdWrV+Ovv/7C2rVrERUVle/tzp49G4IgYNy4cdqyjIwMjBo1CqVKlUJ4eDh69uyJCxcuFMJRkL9xbZUQmJeFEznLPjlZIAa3alsE5+DW4+RkSlbI7UlWxW1WOx+TQYTVLvvVpG9WuwyDJMAgOZ5vfxpbXpndetw6/mu2Zau49ZPgVlEUrRrY12MhIiIiIqKSS/fJyVQ1atRAjRo1CmVbv/zyC9577z3Uq1fPZfnTTz+NjRs3YtWqVYiKisLo0aPRo0cP7Nq1q1D2S/5Drb4KZqsEIgBZFbdqcCtntqbx1g6gJFKrM4OMklNw614le6uKW7XHbVRoVsWtMfPSfZuswOilN25Rs2a2SpBE/xtbXqk9bIMzJxzLqrjNHtyGAPB9WGqTFe0EAHvcEhERERGRXnQJbsePH49p06YhLCwM48ePz3Hd+fPn52nbqampGDBgAD744ANMnz5dW37jxg189NFHWLZsGVq3bg0A+Pjjj3HnnXfip59+wn333Zf3AyG/lW6xQxIFrbKOFbcU6NR2IY7g1hF6yQpQTHO8fFErIE0GUWt3YPfQ+9W5rYQnzj1uVcbMyc4sVln7t69ZbbJrSG1XkJl7FjsZmc+de49b18nJ1IpbX09OlmHJmqguJd0acCdJiIiIiIioaOgS3O7fvx9Wq1X7d2EaNWoUOnXqhLZt27oEt7/99husVivatm2rLatZsyaqVKmCPXv2eA1uzWYzzGaz9ntycnKhjpf0kW6xI9goQRCEzB63DG4psGWvuAUck1dJYjFN8vJBrc40SqIWynqqxnduK+FJWJDjT2OpiCBtmVpxa7X7T59bm11BWLDT8y3LAIrn861NOJn52KutErIqbl2D2+Q0S1EP0YUaKAOO10SG1a715yUiIiIiIiosunzL2Lp1q8d/F9SKFSuwb98+/PLLL263nT9/HiaTCdHR0S7Ly5Urh/Pnz3vd5qxZszBlypRCGyMVjQxL1pdkkRW3RFpAKYmCFloW9wmr8spis2uhrSGzatbu4TGQbxHclosOwcyBDVGrcrS2TK0AVdsx+AO1VYIhswK4OH8Oqq0Q1FYJ2uNtzWqVEGSUEBXm6Dvs64pb5+AWcLRLYHBLRERERESFTffrPYcNG4aUlBS35Tdv3sSwYcNyvZ3//vsPY8eORWJiIoKDgwttfC+++CJu3Lih/fz333+Ftm3ST5rFpl1Sa2CPWyKX4Fbt0Wrz0CagJLPaFS3wE4Ws9gHZ2W/RKgEA7r29DCJCslolqNu12vyp4laG0SBqIXVxvvJAbX+j9ujN6nGrtkqwI9QkITzYEY76uset2am6G/D9eIiIiIiIqGTSPbhdunQp0tPT3Zanp6fjk08+yfV2fvvtN1y8eBENGzaEwWCAwWDA9u3bsWjRIhgMBpQrVw4WiwXXr193ud+FCxdQvnx5r9sNCgpCZGSkyw/5vwyLXZt9XGRwS+QU3Ipaj9biXIGZHxarXQtYjZJz+wBXWZOT5f5PYFbFrf8Et1a7DIMkaiG1zY/aOORVhlP7GyCrNYX6eGdYbAgJMiDIKMFkEH0elJozK4TVdhqcoIyIiIiIiPSg23V9ycnJUDJnNU9JSXGpkrXb7fj6669RtmzZXG+vTZs2OHTokMuyoUOHombNmnj++edRuXJlGI1GbNmyBT179gQA/PXXXzh16hSaNGlSOAdFfiPdYtd6HRpEkcEtBTy1uta5x62nNgElmcUma71RtXYRHj4bclNxm51aWWn1oypmm12BUcqqUi3On4PO7W8AICjzeVQnnEuz2LWrLCJCjEhN93GrhMxAuUxUMM5fT/d5kExERERERCWTbsFtdHQ0BEGAIAi4/fbb3W4XBCFPvWUjIiJQp04dl2VhYWEoVaqUtnz48OEYP348YmNjERkZiaeeegpNmjTxOjEZFV+OiWBYcUukUvvZSpKQY5uAksxik2E0OI49a8Iu78Gttx63npiM6mRZ/tHjVlEUrcetNhFbMX6+0yw2BJuyKqBNRtfJ4NLNNsSGO6pbI0KMSE737eRkGZkVt+oJxBusuCUiIiIiIh3oFtxu3boViqKgdevWWLNmDWJjY7XbTCYT4uPjERcXV6j7fOONNyCKInr27Amz2Yz27dtj8eLFhboP8j27rMBstSM4szpLYnBLlBVGClkTcwXi5GRqxa0kep+wS3Z6rHJLq7j1k1YJWrsHp8nJinOP2wyLPVtPYbXi1hGQpmeruP3v0s2iH6QTNcAvndkqgRW3RERERESkB92C25YtWwIAkpKSULlyZYh56CWYW9u2bXP5PTg4GG+//TbefvvtQt8X+Q+10kn9Es/gliir2lJ0apVQnIO8/LDaFIQHO/7WqOG1p9YG+WqV4Gc9btXWGAbJqTWGh36+xUWGU/sbwLWnsF1WkGG1IzTI8ZkfHmxASoYViqJoPXGLfLxWteI2BACDWyIiIiIi0oduwa0qPj4eAJCWloZTp07BYnG9vLFevXp6D4FKmHSLo7dhaJBzxW3xDSyICoPaz9bg1Coh4CYns2VNTpZjj1unxyq3TJnr+ktwq7YQMBlEGLTg1pcjKpgMa9aEk4BTcGu1O52sc3zmR4QYYZcVpFvs2t+BopZhcTzYpSIzJydjcEtERERERDrQ/RvPpUuXMHToUGzatMnj7Xa7f/QLpOJD/RKvfsmXJFbcEtkzUztRcKq4Lc5JXj5YbLLWizYrzPQQ3GZWq+alWjOrx61/PKZqcGuQREhqq4Ri+nyrFbUhTsFtkNPjnZbtZJ3aUiEl3eqz4FZt4RATboIkCkhO823PXSIiIiIiKpkKv39BNuPGjcP169exd+9ehISE4JtvvsHSpUtRo0YNfPnll3rvnkqgtGytEkSBwS2Rc89TrdpUxx633/1+Ft8fOKvb9vPDYpNhzKyMFXNoH6A+Loa8tErwsx636jgMUlbFra2YTk6mhqBq33LAtVVC9pN1zsGtr5gze9wGGyVEhZpYcUtERERERLrQvVTlhx9+wPr169G4cWOIooj4+Hi0a9cOkZGRmDVrFjp16qT3EKiEUVslqMGtIbPHrS/7HRL5mta3VUCRXDqfuP04BAFoe1fhTjKZX7KswGqXtUmtDKJahVo4PW5Nftfj1jEOoyRAKuaT0an9YkM8tEowW+1IM2dW3GYLblMzbEU5TBdmq+PxDzZKCA8xsMctERERERHpQveK25s3b6Js2bIAgJiYGFy6dAkAULduXezbt0/v3VMJlFV95TjvkFVd6LMhEfmcXVYgiQIEQciqNtUxubXaZb8JMQHXnq8AcgwzterkfExO5i/tCKz2rAprSVAnYvOPseVVemYwG2z00OPWqeI2RG2VEOz4ry/bE6hjMhlFRIaYkJruuxCZiIiIiIhKLt2D2zvuuAN//fUXAOCuu+7Ce++9hzNnzuDdd99FhQoV9N49lUDpmV+Y1eorKYdelkSBwq4o2qRkhszL+vV8S9jsil9dmq+GyEHGzOBW8N4+QOsHXAIqbg2SoPW4La6T0WVYXVshAI7+wyaDCItNxk2z61UW/lBxa3FqlRARYsCNNAuUYlrxTERERERE/kv3Vgljx47FuXPnAACTJ09Ghw4dkJiYCJPJhCVLlui9eyqB0rP1uJVymD2eKFDY7Yr2XtBCSw/9XQttf7LsV1XuaqCqtkpQK249Tk6WGbBJ+ai49ZfgVq24NUqi1tfXn4L0vMj+ma4yGSRYbHLWyToPk5P5itoqIcgoITLUBLusIN1i99lkaUREREREVDLp/g1j4MCB2r8bNWqEkydP4ujRo6hSpQpKly6t9+6pBNIuq81slaCGL46QSvJ2N6ISTW2VADi1D9ExWbXaFb+qMFQnuFJDTEMOk5OpHQXyEtwGacGtvSDDLDTq5GRGp8noPB1rcZAV3Lr+L4nJIMJstTt95vvR5GSZrzeTQURk5niS06wMbomIiIiIqFDp3iph6tSpSEtL034PDQ1Fw4YNERYWhqlTp+q9eyqB3Ctui/dlwkSFwTm4zTqZod97wuZnPW61ilvjrVuoyPmYnExtP2HVsap1558X8MHmv3O1blarBFELqfV8vvWU1bc8e8Wt6Fpxa8peceu7VgkZVjuCjRIEQdDGk8wJyoiIiIiIqJDpHtxOmTIFqampbsvT0tIwZcoUvXdPJVC6JXOG8SDXgKa4hhZEhcEuK1q4WBQVtza7DJtd9puq26xWCZk9bjNP6HhslZCPycm0HrdW/SpuN+8/ixU7k3LVr1sNbo0GMetYi2mrhAxvrRKMIsw2u/aZH5L5mR+uBbe+m5zMbJW110RkqFpx67vxUMmy5Id/sGnfGV8Pg4iIiIj8gO7BraIoEAT3L8cHDhxAbGys3runEiirOsu1VQInJ6NAJstOk5Pp/J5QFAU2WYGi4z7yyuoW3OYwOVlmSwHRw98mb9Qet1a7flXGahibm3YMWT1uBRik4n3yyluP2yCDBItVRprZteJWEgWEmgw+rbg1W+1ahXCkH7RuoJJDURSs2JGETftO+3ooREREROQHdGvGFhMTA0EQIAgCbr/9dpfw1m63IzU1FU888YReu6cSTP2SH2zk5GREKpssu/W41StUdd6uza7A4AetpdWwMzeTk6mL1HVyQ92unu0h1DA2w2J36/eanXOrBO351jFU1pNaUat+pquyt0pwDnYjQow+DUozrHYEGbL33PVdkEwlx400K6x2GRZr8Xw/ExEREVHh0i24XbBgARRFwbBhwzBlyhRERUVpt5lMJlStWhVNmjTRa/dUgqVn64fIVglEjhMXUraJufQ6meFcxWqxywj2g0kB1UBVrYzNqepYDT2lvFTcZj62Vh2DW3Ws5lwENmrlr1ESYcxskWH3k7YVeaVO9JW9x22QUcoMbtVWCVn/yxIRYvD55GThwY7AVm2VcIOtEqgQXE7OAKBvdT8RERERFR+6BbeDBw8GACQkJKBp06YwGo167YoCTIbFhiCj5DYREytuKZDZZEULIkWdT2Y4Bwo2PwkXsve4zao6dh+f+lkhSbnvFiQIAoySCEsRtErIyEUfXedWCVq7mGLe4zbIY8WtHWlmGyRR0MJzwFHlev56RpGO05nZKiM2XNTGArBVAhWOy8lmAFknNIiIiIgosOkS3CYnJyMyMhIA0KBBA6SnpyM9Pd3juup6RLmVbrEjxOkLflYvS/8IkIh8wbniVu+TGc5VrHpWoOaFOmmYSau49T45mRpo5yG31bat5/Gq4XNuAht1HAZJLPZXHWRkVhhnr7hVWyWkmR2tI5xbLkWEGJGaYYVdVrTjL0pmq10LmqNCTQCA5DQGt1RwasWtnm1ZiIiIiKj40CW4jYmJwblz51C2bFlER0d7nJxMnbTMbmdFAeVNusXu8gVfrayTi+llwkSFwS4rWpsAvYM8v6y4zaw2DVIfg5x63GYuy8vkZICjLYGeYYo61txU3Dr3uDWorRL85LnIK61VgoeKWwBITrMgLMj1f1fUNgU3zTZtcrCi5AhuHeMLMjraVaRkMLilgruc4qi4ZXBLRERERIBOwe0PP/yA2NhYAMDWrVv12AUFsHSLzSW4zepl6asREfmeXVa0IFLUu+LWucetn4QL2uRk6qSFglqJ72lyMrXiNm/Brcmob8WtGsbmrcetoFUOF9+KW2+tEhy/30izau0IVBEhjv99SUmzFHlwa7PLsMmKFjQLguCYLI0Vt1QItB63fvLZSkRERES+pUtw27JlS4//JioMZqvs8iW+uM+oTlQY7LICQ7bJyTxVmxbOvrLea1Y/6auqzsCuTtQligIEeA6v7XL+glu9K26t9ty3SlADaUerBO9tIYqDDKsdRqeWDyq1ovVGmgXlooNdbtP6ymbYimaQTtRg3Tlojgw1slUCFQrnHrfq1WlEREREFLh0m5zM2bVr1/DRRx/hzz//BADUqlULQ4cO1apyifIiw6m3IICsy4TZKoECmF1WtJMYOU3MVRicw0t/qQrLPjkZ4AhmbR4eg6zgNm9Nbo0697hVw9hc9bhVK24NojZpl7+0rcgrs8XuVm0LZD2XdllBiMn1f1d8OSGY2eZeIRwRYsR/l24W+Vio5FErbhU4quidJ+UjIiIiosCTx6lZ8u7HH39E1apVsWjRIly7dg3Xrl3DokWLkJCQgB9//FHv3VMJZLbaXXohqpdEF9cZ1YkKg11WtAm5cpqYq7D2pfKXsDCrVULWnzWDJHqenMye/4pbq47Hq/W4teS+x61REnRvjaG3DKsdISYPwa3T53z228OCHUFumk8qbtWevFmvtcgQI1IyrFB4ApEKSO1xC2RdSUBEREREgUv3ittRo0ahT58+eOeddyBJji9edrsdTz75JEaNGoVDhw7pPQQqQWRZgcUma5fQAs7VhfzCTIHLLitaEKn3e8K5PYLFT4Jbq5eKW4+Tk2WGa2I+etxaUvQ7XrVqODeTk1mdWiWovY39pW1FXmVY7C6f6Srn5zJ7cKtOxOeLEwdqsJ694tYuK7hptmkTpxHlldlqd6kiN9vsCCuai+OIiIiIyE/pXnH7zz//YMKECVpoCwCSJGH8+PH4559/9N49lTBqsOHaKiEzpGKlEwUwuyxrQaSk9+RkTu0H/KfiVg1usz4bRC/BbX573Jp07nGrPpa5CW5tTq0SJKl4n7zKyHYVhcoluA1yDa/UXsYWH4TV5szXgPMkmZGhvmvdQCWHc7Ut4D+taIiIiIjId3QPbhs2bKj1tnX2559/4q677tJ791TCmD3MPi6yVQJRZqsENbh1LLPpFOTZnN5r/hIseOpxa/BWcZvf4NZQNK0SzLm4PFoNbg2SqPtkdHozW2UEeWqV4BTCh2a7Xe1t7osTB+bMilvn11pkZs9dTlBGBaH2t1UrzPU8UURERERExYPu11+NGTMGY8eOxT///IP77rsPAPDTTz/h7bffxuzZs3Hw4EFt3Xr16uk9HCrmMrTegh4qbotpaEFUGFwmJxP0rbh1Di/95fJ8z5OTiR5P6OS34ladnEyPmd4VRdEe19z0uFUfd6MkQH06/KX6Oa+y9y1X5VRxa/DhhGxmD1d+qJOlJbPilgrgcrKj4jYuNhT/nk/RencTERERUeDSPbjt168fAOC5557zeJsgCNqXYLud/4NKOcuquPXU47Z4hhZEBaUoikvFrVqNqNfJDOewzF/CQm1ysmw9bm0ePhfUx0XMY/hqMkiQ1ce6kGd6d36uchPWqJXOBkmEAMVtG8WFoiheWyU4f86HemmV4IsTB56u/GCrBCoMasVtXIwjuM1N9T0RERERlWy6B7dJSUl674ICSIbVQ4/bYn6ZMFFBqS99sYgmJ/PXVglGSXSphJUkwWPVsTo5mZTH8FWdEMtql7VwvLA4P6a5qbjVWiWIAtSjKI6fgTbZEYQH36JVQvbJydTH3xevP7OHKz/UfzNoo4LIqrgNAeA/n69ERERE5Du6B7fx8fF674ICiKcvzKLOEzER+bvsl/7rfTLDteLWP953FpvsUm0LAJIgeOzzq45ZynPFbeaEWFYZIaZ8DtQL5/YTuQn/rPasoFrNkIvjVQdqSO2xVYJTxW324Nbow1YJ6pidx2cyqj1JeeUQ5d+VlAwIAMrHhALIastBRERERIFLl+D2yy+/RMeOHWE0GvHll1/muG7Xrl31GAKVUBkeLlFVwyq9JmIi8nfZJ9vSu+LW5bJ+v2mVILt8LgCOilpPPW5lWYGArMcpt9TL8/U4ZucAUv2cy4nVntWuwRHeCn4ToueFp890lUuPW5O3VglF//pT+yk7h83aa4MVt1QAl5PNiAkPQlgQTwQQERERkYMuwW337t1x/vx5lC1bFt27d/e6HvvaUl5lVdy6TkAEFM/LhIkKg9rHVQ1u1f+qLQEKm3NfUf/pcStr4ZnKIAoeZ2W3yXKeJyYDnCpudaiCcz7xZM5FcGvL1q5BFIRi+Rlotrj3LVe5tEoI8twqwRdhtaewWc/XBgWOy8lmlIoI0tqysPUGEREREekS3MpOl2vKxfDSTfJfZu0SVfeK2+IYWhAVhqyKW8eXfbUFQFG0SvCXHowWqx1Gg2sYK4reK27zWm0LOPW41SO4zWvFbbag2iB5bgvh79Rj9dTjNsiYQ8WtQQ1ufdnj1rlVghrc8mQ05Y8sK7ickoFq5cO1kxY8EUBEREREhTu7CpHO1H5vzl/yOTkZBTqbt1YJOlUjOm/XF5eqe+LocZutKlMUPX4u2BX4X8Wt3bniNvc9blWSKMLuJ89FXmR46FuuCnJqlRAW5LnHrdUnFbfuk2SadAz1KTBcT7PALisoHRmsnbTg64mIiIiIdA9ux4wZg0WLFrktf+uttzBu3Di9d08ljDopTJCheE9OlpJuxaUbGb4eBpUQbpOTZYZadt1aJThV3PpJX1Wr3X1yMlEUPE7YJcuKVp2cF1pfVZ0rbnPXKiGrxy3gOIFVHE9e5Tg5mdPnfHC2itusVgm+q7h1DW5ZIUkFcznZDAAoFRGkvZ5y81lARERERCWb7sHtmjVr0KxZM7flTZs2xerVq/XePZUwZg+X1RbHycne2vgnxny419fDoBLCbXIytVWCTqGWc0DoLz1urTb34NZb+wC7rOSv4tao34RYVnvee9wanY5XkopncKtWF3tqleD8fIZ66XHri4pvs4cqYfa4pYK6nOw4mVs6Mlh7b/P1RERERES6B7dXrlxBVFSU2/LIyEhcvnxZ791TCZM1KYzzJcLFr+L2/PUMXEkx+3oYVEK4V9zqO2Gf1R973Npcg0zA8Xh4+lzI7+RkasWtPq0S8tjjNlurBIMoFquTV6oMiw2Aa/WqynlZkFsbjMwTdj4Mbp2DZQa3VFBqxW3pyCCn1xMrbomIiIgCne7B7W233YZvvvnGbfmmTZtQrVo1vXdPJYxWneVhcjJbMZoIL91ig11WimWFHPkf94rbzOU6tUpwmZzMTypuLR4qbiUv7QMUOasqOS+CdAxTsve4VW7x3GVvlSBJQrHsceupb7lKDeJDTJLbZHKiKEASBZ8EpWar47XmPKasUJ9BG+XPlZTMituIIPa4JSIiIiKN4darFMz48eMxevRoXLp0Ca1btwYAbNmyBfPmzcOCBQv03j2VMBkeegsWx4rbNLOjysxqkyF5CCyI8iL75GSCIHgNLQtlf86Tk/lBsKAoiscet5IoeKzIzHfFrY4TUDmPU1YUWO0KTAbvY7TaZK2yGgAkwXNbCH+XU49bKTOcDTF5/l8VoyS6vBaLitlqd5sITxQFGCWRFbeUb1kVt8Ha68jM1xMRERFRwNM9uB02bBjMZjNmzJiBadOmAQCqVq2Kd955B48++qjeu6cSxlNvQTWAKU7Vq+lmx3FY7TKCweCWCkY9aeFcASgKOga3Lj1uff++U0MO59YBgKN9gKfHQJYVSFL+g1s9WyWogbsjHPR+UUz2VgmOilvfPxd55elknLMgg4QQLye3DJLoo1YJspfJ1BjcUv5dTjEj2CghPNiA1AzHyV2Lla8nIiIiokCne3ALACNHjsTIkSNx6dIlhISEIDw8vCh2SyWQp96CxTK4tWYFt0QFpQapBqfgVt+KW/9qlaCGZZ6qIBU4glrnUNsmK5Dy0SpBDUr1qLhVJycLCzIgOd2KDKsdESFGr+vbZAVGyfVSfbPVWujj0ltWxa3nkNpkEBEa5K3iVnCZ1K2oZFjtLn3WVSaD6BcV6FQ8XU7OQKmIIAiCwB63RERERKTRvcctANhsNnz//ff44osvtL59Z8+eRWpqalHsnkoQT70FJVHfiZgKm1pNB/jHZeZU/Nk9VNwWWasEPwhu1TGYsoVpag9Ye7Z+sdmD3NzSs+LWntmjOyzYEVJabjFBmc3u2ipBFAUUozbfGrXi1lOPWwBoc1cFtKpT3uNtRoOvKm7tHsdrMkisuKV8u5xsRunIYACc7I6IiIiIsuhecXvy5El06NABp06dgtlsRrt27RAREYE5c+bAbDbj3Xff1XsIVII4Kp1cvzBrk5MVk8uE1f62gG9mRKeSR22VkD3I07vi1ij5R4WhVau4dQ1u1QnI7HYFzh8bdlnxWDF5K2pFrx5htXoM4cFGAOlaoOmJOrGh8/NtEAW/CNHzytOEk86e7FjT63191Sohw2pHVKjJbbnR4JvJ0m5FURTMWnMIjaqXQvsGFX09HPIgw2JHaoYVpSODADj6lLNnMhEREREBRVBxO3bsWDRu3BjXrl1DSEiItvzhhx/Gli1b9N49lTBmq93tC77aq1K+xSzs/iLdkhXc8ksZFQZbZqml8+X/hiIIbkNMkl+cMPHa4zbzs8GWrRTVLiv5mpxMnSxMj/etesl/eGbFbYbF+z6ygnPXCuviNEGjKiPz89Bbj9ucGHzUKsFslb20SpD88tJ2m6xgy8Fz2HP0kq+HQl5cSckAAJSOCNKWsWcyEREREQFFUHG7Y8cO7N69GyaTa3VK1apVcebMGb13TyVMhsV9wh41rCourRLSzFlf7H0ROlDJ43FyMh2DPPV1G2Iy+EWVpxqWGbN/NmS2Ucn+OMhKfoPbzIpbXVolZPa4zQxuzTlU3KqPuUvFrSS6TBpXXJitMgS4V0vnhlEStR65RclstSPIY6sEETczbB7u4Vvq69Uf3qvkWXK643UTFZb1/8pBRglmPzwRQERERERFS/eKW1mWYbe7/4/n6dOnERERoffuqYQx22S33oJqWFVcZlRPd2qV4A+XmVPxp01OJjlX3Iq6ncywy46wLcgo+kUYZLE5jtPtpI7aRiXb42Cz5y+4VSt69am4dW6VAJdWCVa7jJcT9+GXfy4DyGoL4xxUi6JQLFuvpGf2ixXyMVmco1VC0X7u22UFVruMIIPn4NYfK27VvzOs3vRfVg9XDZgMIixWPmdEREREgU734PbBBx/EggULtN8FQUBqaiomT56Mhx56SO/dUwnjqVWCtwmI/FWaU4VYcQxayP9oFbdO4Zcg6FeFbsvsr2rwkx63aljmLbjN/jgoSv4mJ1MnP9MjrFY/CzxV3J65koY9f13Cjj8uuOzf6FJxq19rDD15+kzPLUerhKJ9/amvNY+tEoz+OTmZhcGt39Pe04ZswS2fMyIiIqKAp3urhNdffx0dOnRArVq1kJGRgf79++PYsWMoXbo0li9frvfuqYRx9BbMVnGrTUBUPL7gOE9OZikmYyb/ZvdQcSvp2uNWgUESYPSTS8Mt2uRkXk7qZKvKtOWzx61WcatDFZz6XGk9bp32kZphBQBcTnb0wfTU41bPnsZ6yrC4TziZW76YvEmdTM3TmI2Sf05Opv6d8YfqePLMU8VtkFHS3vtEREREFLh0D24rV66MAwcO4PPPP8eBAweQmpqK4cOHY8CAAS6TlRHlhtlqd6t0Uvs8FpfQwnlyMn+oVqTiz+6hx62kYwWmzS5nVtwWfcWjJ1YtuPVWces6Rjnfk5PpV3GrBn5qqwTnituU9MzgNsUMIKtVgnOPW0kUICsKZDl/1cS+Ys5slZAfjlYJRR3cOp4XT1XCJoMEq132u+dA63HLvzd+y1OfblbcEhERERGgc3BrtVpRs2ZNbNiwAQMGDMCAAQP03B2VcFpvQbeKW8d/5eLSKsHMVglUuLSKW+fgVtAvVLXaZRglESYfVDx6HM8tg1vXzwZ7QStudTjmnFolqFXNV5Idwa16vNknJwMcLWNE+E9oeCtmq4zocNOtV/TAKBV9X1+197DHVglOwX6QmL8wWg8Mbv2fp88wo0HUKryJiIiIKHDp2uPWaDQiIyNDz11QAPFW6SQIgq6XhRc251nQ+UWaCoPaJsS5ys8g6Tg5WWarBF9UPHqiBqnGPAS3+amIFEUBBlHQZQIqdYyeglu14vZ6mgUWm+zU4zbrGLJaxhSPz0FVusWW7x63RkmETVagFOFJOzVI8zRmNcz1h5MZzqxsleD3LHb3CRZNBv+Y/JGIiIiIfEv3yclGjRqFOXPmwGbzfR9EKt6yKp3cvzCLQvEJbl173BaPMZN/Uyfmc64iFUUBsk7f+W12GZLo6HHrD8GC9+DW8bst2/tMVhRIQv6qUh3HXPjvW3WbEZmtEpxP8KSkZ31mXPt/9s47zI3qXv/vNPWVtnh33SvGBpveQ0ILCSThd8kN6SShpF/ITS6k3HBvbnqvJCH1BkhuIIQkEAIhlFCc0MGAjQ22wd273r6rrtFoZn5/jM5oJI200mq0Gq2/n+fxY3ullY5GZ87Mec973m9Cto1KYHm+uWZ96U1Czmnw2bhXa4F937lZHPvlKtchlrHsOuGWipO5HtuMW1FAVlFndWGCIAiCIAiCcB9Nz7h9+umn8cADD+C+++7DUUcdhWAwWPT4bbfd1uwmEHOEguO2fJLfTo7bNDluCYdh2ikTKoHmFqvKaTokgYeUz9FtdaYnc8CWRiWYxckswoeu6zOOSjDeQ2jKeVsWlWB5D+a4BYCxmFwoTiZaM27zUQlttBikaXrDGbeAceysglczqbaAyBzQzXBkNwIrTkbCrXtRbM5pj8RDh7Go4xHbJ/6EIAiCIAiCcJamC7ednZ246KKLmv02xCEAc6DZTZjbSbi1Om7dsM2caH9YVEKZ47ZJTi0lp8Ej8qZY1upMTyZIeUrEO7v4ADZMzFS4lQS+ScJtcVSC1XFrrSw/FssgkH+OZOO4VdvInce+N7sxvRaYUKqoOmar1Gm1BUSP5G7HLV1v3Itis2ugkKmtli1KEQRBEARBEIcOTRdub7jhhma/BXGIwBxodu6sdhVu3bDNnGh/mFhnLU7Gc80r3KRqOkSBNx2PdkUDZxNTuJWmz7jN2Yjc9eCR+KY4KguOWyMqwS7jFgDG47L5OUVLxi37PO0kzqWzxlg4075jddzOFnJeUPfYRiXkhTaXFZQyi5O1Ud841MjaFCfzunQhgCAIgiAIgphdmraEr2kavvnNb+L000/HSSedhP/8z/9EOp1u1tsRhwBswuwVyyfMzSzE5DQpi5OOJmSEEzBHqTWuoJmLGUp+a7qZMdri7fmFiuzFYwMT9lRL7iszpM402kESeHPruZMwUc0nCRB5ztySDwCJTGGxZyyWMT9vUcZthUJsboYV+vI3GJUwm5EzchWXsCncumxcZ31L1fS26h+HEuw7su4aYP2JIpUIgiAIgiAObZom3H71q1/FNddcg1AohEWLFuHaa6/FFVdc0ay3Iw4BzKIwNpN8nuOgtcmENG113NKEjHAAJsYIsyTcqqoOQeCKohJaiSl6lBUnYwW7LI5brUHHrcg3xVFpFhzjOXglwRQ1ASCRVtAb9gEAxuKyWchMsjpuhfbLuG3Uccs+/6w6bs2MW5uohPzCQavPh1KsQjJdc9yJXYFFNp5Z3fcEQRAEQRDEoUfThNvf/OY3+MlPfoJ7770Xf/7zn3HnnXfipptugtZmFa8J95CpMmEWeG5WK4s3QkrOteW2ZsK9sCzbIuFWmAXHLcsYbbEYZCd6AAVXrXVRRzNF7pld/jwi3xRhLqdqEHgOvCncFjtuezq8CPmkouJkVsct++7dJhpWg7lXG3XczqbDlQnqPrviZGZUgruENuvxaYZbnGgc24xblzq4CYIgCIIgiNmlacLtvn378MY3vtH8/7nnnguO4zA4ONistyTmONUmzILgDsetqumYTMhVn5POqogEPABgOucIohGYW7NIuOWaV5xM1XQIPGeJSmixcJsfG6SS4mR28QE5G3dyPUgi3xQhJadqphDp8whlGbchv4R5YS/GYhnz+7aKPOzzNOs7bwbV4m9qQTQdt7P3mQsLiJWjEmSXCW0KOW5djyncCpRxSxAEQRAEQRTTNOE2l8vB5/MV/UySJCiKUuE3CKI61SbMQhMLMdXDHU/uw8Xf/yemktmKz0nJOYQDRgEimpARTlAtKkFvgpCnqBpEgSsqTtZKWLGwsqgEm630dseqHiSBb4r4pai6KTR7Rd4c73KqhoyiIuQTMS/sw3hcLmT6WkQeySzU1T7CbaZK/E0tSC0oTpatGpXgToek9fwk4dad2MW9UMYtQRAEQRAEAQBis15Y13Vceuml8Hq95s8ymQw+8pGPIBgMmj+77bbbmtUEYo7BHGiVHLeqC5xmByfTkBUVw1NpdAY9ts8pdtzShIxoHNUmt7XgwASEmWmUtui6UeBIEviCsNDq4mRq7Y5b5syfaXGyZkUlqJpe5LhNxIz813jaWOzs8EvwSQIyiopoylgYskYl8G1ZnIyN6TNbQy5kLM+m47ZycTKvW4Vbq+OWrjmuhC0+STbFySjjliAIgiAI4tCmacLtJZdcUvaz97znPc16O+IQYLqMWyXb+gkpm3xFU/bO8pyqQVE1RPKOWze4hIn2x85FahXyZuourfZeosAXhDMXZNxKAl8mxtpl3JrHaoaHRBJ5qJru+HHN5V3MgCEKsvEukTEE3JBPNN/v4GQaQCEqACiI1O3kuE3noxJ8DWbctqI4md0Coif/s1afD6UUZdzmSAR0I9lcIeOa4XVp9AZBEARBEAQxuzRNuL3hhhua9dLEIYpcxenEc80rxFQPrI2xlH1UQiovVHT4DeHWbRN8oj2xK7gl2IiWTmDN022FcGZHNqeVxSQAhWOQsytOJszM5WndvizMUHC0g4nPgCEKMoHQ6rj1e4xL9tCUIdxa3XksFqKtMm6r5JbXQisylqtF9khmsTR3iaPFwm379I9DCUXVy8YwTwszblVNx//evwPnH78Iy3pDs/7+BEEQBEEQRIGmZdwShNNkspUdt6LQvEJM9TCd4zYtG+45v1eEJPBU4ZtwBLuCWwXR0tk+Zo0lkFySwahUFG6NnzlZnIyJjKlsbka/Xwmrg9crGQXQNE03Hbcd+eJkADBk67h1R95wPaTzx9BOBK0FKf/5ZzMqQVZUSAJv238o45aYKYpl4YbRyv60ayiOWx/dg3ufHZj19yYIgiAIgiCKIeGWaBuYKGrnzuJ5zhVbhNkEK1qhOFmKCbceoWlFjoj2ZftAFB+87jFMJOS6fq/gIrUKt3zRY07B3I2CwLVEOLMjm9NMEdmKXXyAmXHLzUy4jeSzqyud4zMlpxY+g7WaPHPchnwiejoM4XYslgGAos9sRmO4YBysFdNx21ZRCfaLBADgkVwq3M7BjNupZBZb9021uhmOodiMYQXhdvYd3GzciaWpoDBBEARBEESrIeGWaBsKjtvySb7I844LVDPBFG4rOG5TsvEZ/B4BkkjCLVHMpj2T2DUcx86heF2/Z7pIuXLHrdMRIuy9JGvGrQuiEkrdaoB9XIRdHnA9dOYLC1Y6x2eKohY+AxvjMoqKRIYJtxLmhX0AAPZprMXJmIjuhsiYWpGrxA7UAnMcz3bGbaX2mkKby4pJzUXH7U0bduGq659CMuOs871VWM9/hkfML+Aos/+dMeHW6XGOIAiCIAiCqB8Sbom2gbmzKmVZ5lwgWEyfcWtMMgP5qAQ3uIQJ98CiNOoVV0wXqU1UguPCbV4EEgU3Zdyq9uMCEzMtMSrs3+IMq5NFgkY+9ZTDjltrVALbVSArasFx65fQGfQUCc5FGbfm990+whzLi/XP0HFrZso6PI4OT6Xx7du3mIuFVmRFregQZkJbqx3opcxFx+14XEZO05GU54awmM1ppmOb0cqohJgp3Do7zhEEQRAEQRD1Q8It0TZkFBU+SQBns8WZ5zmXOG5ry7gNeASIAjdnJtGEM7DidXKdjj0mzopC84VbthVftGTctnpruJLTbaMSmAPZKiyz9s80KqEzH5XgtHCbU3VTCGc53hlFRSLNMm5FCDyHrqDX/B2779sNC1i1Yu6iEBuLSnDaRfrISyO457kBbNk3WfZYRrFfJABau7W9GtYsdbe5gWcKix2yE9fbkWxOhafUcSu5ICohOTeEcYIgCIIgiHaGhFuibai2RVXkuSJXXasoRCVUyrjNO8y8Ijwi33LBi3AXmbwjW65za6xqk9vKjJlOC7dssUHkCxm3rXaOK6pmuh2tCEJ5cbJGoxKalXFrxD2UOm6tGbeG05cVKAOKHbdMxGynjFvmuJ1pxq3UJMc3235vNz5nc5ptzjpQEG7rPX+bjVXYdtqd3CpM4dZlx3qm2C0+sQWNVtwnxMlxSxAEQRAE4RpIuCXaBrnKhJnnOagucK+yCVaskuM2L8wFvaKRceuCNhPugQn79U7UC45by9Z5oVnFycodt63ux3IFF6Ro4zrW9fJYiXpoluNW1TTzOzMzbrNGxi0HY8wAioVb0SYqoZ0ct7KiQhL4GYvoheJ4zva/tLmAYheVoFVcQDSjG1y2IFcUleCyts2UZF64Zd9Vu2ObcdvCYnfsHiaeVtoqN5sgCIIgCGIuQsIt0TYYjlv7LitwnCsmF6yISDSVNQUiK+lswXFrZNzOjUk04QypKoJRNViuqVX/apaQ58aMW0Utz4cECuKsdWzINei4DfsN56vTTrScqhcct3kHqpxTkcjkEPRJ5mfp6TAKlAk8V/QZzGiMNhpTMtnKuyhqodD/nO3jzM1p55yttEgAGP1NEnjXRSVYhe1Wn6tOkc4vcslzJCpByWnwlJwLTMit93rgBMxxqwNIpCkugSAIgiAIopWQcEu0DdUm+TzPQYfz7sJ6kfMTdlXTkbCpdp0qyrjl54z7iXAGU4yoU/hhha2s+c9MyHPccWtx93pc4DDUdd0o7CNUdtwWZdw2KNyKAo+QT8KUg9mPuq4XOe68eWEwk1WRSCsI+UTzucxxK5Z8XlPEdMECVq3ISuVdFLUgCuXfrxNUikrQdb3qAiJgxCVQcbLmkzSjEuaGcJvNqebCDaOVxcniFrGW4hIIgiAIgiBaCwm3RNuQzVXeoiraVI9vBdYJcsxmsmN13FLGLVEKE/azM8i4LS221aziZMWO2+YIZ/XARDLb4mRCuXjN3MkzFW4BoDMoOSpmsOaxNnnzjtusoiKezqEj7/IFgJ6OvHDL23/frV68qofMNCLodHiaFNVRcNwWi4KKqkMHqrqEPSLvugJg1uuM2/J3Z4Ku62ZEQnoOOG41TUdO08ujElj/bkVUQpFwS45bgiAIgiCIVtI2wu3Xv/51nHTSSejo6EBfXx/e/OY3Y/v27UXPyWQyuOKKK9DT04NQKISLLroIw8PDLWox4TSZrFqxiA0TrVpZmIc5/xh2kx3TcesVIAncnHE/Ec5gZmvOIOO2VIg0hVuHFzNMxy1vybht4QIE25Zut33dLi6iUcctYBQoc7I4GTt+YmnGraIhkVGKhNt5YSMqoVTkYUJuO40pGUWFf4aFyYDmRSUkKzjfmZDrtSmEx/CIgusW5KwF1dqpf1RCVjTzPJ4Ljlv2nZQuPnEc17IFXnLcEgRBEARBuIe2EW43bNiAK664Ak888QTuv/9+KIqC17/+9Ugmk+Zz/uM//gN33nkn/vCHP2DDhg0YHBzEW97ylha2mnAKXdch51RzC3EpzXIX1kNO06FZRDK7yU5aVsHBmPhLIu+44EC0N2ZxsrozbqsItw73MbuM21ZuDWeiZ6mQCQACX16gjf17psXJAKAz4EEsrTjmbjWFm/xnYGJmSs4hKedqikpoVjG6ZuJcxm1zipOVOt+ZgFbNJSyJnOuEW0XVEMz3obkQz5OyFCTLzAHHLTv/7RafPKLQsoxbthhUqdgqQRAEQRAEMTuI0z/FHdxzzz1F/7/xxhvR19eHjRs34owzzkA0GsWvfvUr3HzzzTjnnHMAADfccAOOOOIIPPHEEzj11FNb0WzCIXKaDlXTKzpu3RCVwCb5XUEPJpNZRG0yMFPZHHweATxviF6artuKbkRjZLIqfnHfDrznrJXoDnlb3ZyaMQUjBxy3pgvd8agE5rjlzFzZVrr42LEqLewDVHfclkYN1ENn0JPPsVYQDnhm/DqlbWLRDszROR6XAcA+KqEkD1O0+axuR1Yq76KoBZYJ6vTCAcu4LXW+MwGtUnEy4zHBfcXJcho6Qx6Mx+U54bhNZeaWcJutsvjUCsetrKjI5jQsnRfEvrGko7sLCIIgCIIgiPppG8dtKdFoFADQ3d0NANi4cSMURcG5555rPmft2rVYunQpHn/88Za0kXAONjmrtEW1EJXQukkp21bLtjJXctz6PcZ6CZukzQUHlNvYvGcCdzy1D4+8ONLqptSMpulmP6/XYaVquo0DM5956nRUgmVbr+iCPszeu1pUgtV17ITjNhI0xNophwSNUsctEzPHYhkAKHLcBr0ifJJQ9nl5F+w6qBcj47Zxx+1sZdyaUQnTZNwqOXd9B4qqIeidO45bVpgMmBsZt+auAVvH7ewLtywmYVFPAABl3BIEQRAEQbSathRuNU3DJz7xCZx++ulYv349AGBoaAgejwednZ1Fz+3v78fQ0FDF15JlGbFYrOgP4T7YhLmy49boyq0ULdjki21ltttemMrmEPAan8GsGD0HHFBug+UetlP+oZxToZv/rq9PaHbFybjmFA5jjluB503XZ0sdt1W2Gds58XMOZNx2msKtM4KGKYYzx21+K76d45bjOKzoD5nOW4bkgkJx9aCoRk6prwHhlgldTn5mXdcrC7dmVMI0xclc5rjN5jQE8sKt22IcZoJVrG2nMb4SuWpRCVLrhNsl84IAKOOWIAiCIAii1bRNVIKVK664Alu2bMEjjzzS8Gt9/etfxxe/+EUHWkU0k4LTyX6twQ1uMza56p3GcRsOGCJMM0QHwoBN5luRDThTWL4tUL+4krPLuG1S5ikTPiWBMx2irezD2SqOWzsnPjscAtdIxq1xDjslaJhiOHPc5oXBsbxwG/RJRc//6sXHo7T5LM+3XRy3zF3eiHBrFmRzUNjK5jSzj8slGbc1RSVI7ipOpuVjhgKeuSPcJudoVIJdv/KKQlGhsNkgln+/3rAPksBTxi1BEARBEESLaTvH7ZVXXom77roLDz30EBYvXmz+fP78+chms5iamip6/vDwMObPn1/x9T772c8iGo2af/bv39+sphMNwCbQlZxOLO6xlaIFm9R3d3gh8Jzt9sKknDOdT27YZj5XyWSNY9pOwm3GUnCn3nZrmm5GIzBYcoLTuc+svwoCD57nIPCtLcbEsqXt8iHN4lXWjNu8iNtIVELY4aiEcsdtcVRCh794jTUS9JRl65p5vm1S8DAzzS6KWuA4DiLPOer4Tlm24Zc6Z7M1OG4lwV3Fydix8Uo8BIePVauwfkdzSbh1S8YtE4ojAQmRgIcctwRBEARBEC2mbYRbXddx5ZVX4vbbb8eDDz6IFStWFD1+wgknQJIkPPDAA+bPtm/fjn379uG0006r+LperxfhcLjoD+E+MtM4ndxQUd06qQ/7JVuXSsYSlWAW1nHRJH+uIJuO2/Y5tkmL47Ze4TanamUOUqFJxclUzTimLIZAEviWioVMXLN33Bp/W8cFJmSXZgLXQ2fA6Yzb4jaZMSr5sSHkl+x/0QIT7tvFcZudZhdFrYgO979U1noe2jtufVXa7BF5KKrW0muRlYKbU4Ak8HPielOUcdtGi3OVUCy54aW0Rrg1jm+HX0IkKFHGLUEQBEEQRItpm6iEK664AjfffDPuuOMOdHR0mLm1kUgEfr8fkUgE73//+3HVVVehu7sb4XAYH/vYx3Daaafh1FNPbXHriUaZLuPWrnr8bGPd7hgOeBArcamwLbjMcUsZt83DzLhtIzdWusjpV1+fUHUbx22TFjNMkTG/NV8U+Ja6+KqJHhxnOIKLHbf54mSNRCXkHbdObSFmjlsm3HIcB58kmP24owbhVnRBXEwpiqrhd//YjTefuhThks+QqaHQVy0Ywq2DjlvLNny5xHHLhFxP1Yxb4zFF1eDlG/tsTmA9PySxteeqU8w1x+30xclm9zOye5cOv+G4HZqMzur7EwRBEARBEMW0jeP2pz/9KaLRKM466ywsWLDA/PP73//efM73v/99XHDBBbjoootwxhlnYP78+bjtttta2GrCKcxJvlhduG2p49YiREQC5S4VJsz581mDhXxQ9wgtcwXTceuyIkHVSGUbEG7V8oxb9l+nFzPUEqHU02IxSKmSDwkYY0OR49aB4mQRx6MSmBheaJNV0OzwTb/GyjJu3ZSZ/ezOcfz6oVewYUt5gVAWZ+JvICoBYP3PQcetdQGlxHFr7qqolnFb4pZuNVZRcK44btl3xKG94nAqoVhc0aV485nJusORN9VgUQkdfgnhgISknHPVuEIQBEEQBHGo0TaO21puWn0+H6677jpcd911s9AiYjZhTic3O25ZxXGPwCES8CCenoJqKRrFhDkzKkGkjNtmwfpLO7mx0tmZRyWoml7mIGVCXvMct4WohFb24WwV0QNAmeNWy19LGsm49Yg8Ah7R8Yxba3yDTxLAfG61OG4FFzpuJxLG8bGKoQznHLeco6KSdRt+meM2O32bXSvcClxLtt03A1acLBLwIJ0t71vthvXeoRTzPkHV4RFnPmbVQ1FUQj4WJpZW0B3yzsr7EwRBEARBEMW0jeOWOLTJZKvnIbpBtGCOW48kIBKUoOk6kpmC6zadzzBljluzOBk5WRyn4Lhtn2Oblitna06Hputm5iyjWcWqSjNuDeHMBRElFccG3nQJA844bgHksx8dLk5mcXJax7qgr4aoBBdm3LIt13YLEWxMb9Rx63RUQrqK41aukqfMKAi37lg0YlE8Hua4nQPXG7bI1d3hNZ3b7cx0GbfA7PaneNo4b0N+CZGAMfZEHVqkIgiCIAiCIOqHhFuiLWATZl8Fp5MrohLy4pU3n3ELoCguodRx6zZn1lyiHTNumSsx5JPqnqTnVL3MQcoybzWHt9gyBx/L0JVElzhuKxQbE3muSMxk/xYbFG47gx7nHLc2bWKuzoBHrElkLgj17hlP2PGxOw+ddNw6GZVgLRJYOjazBZVqbZZcNq5bt+F7pLkRlZCUcxB4DpGAZPajdoZ9J3YFE9lOgtnsT/F0DkGvmD/GzuZ5EwRBEARBEPVDwi3RFmSm2aJaiEpopYBkcdwyl4rFkZcqcdwWMm7bfyLtNkzHbRtN6tmW386gVHemoabpZrEwhsA1x4FZKjK22sWXrVLYBzAiEeyE20aiEgAj5zaazDqSPVmISigXbmuJSQAKhdjc5Lhlwm3aRriVHRJuPQ73P3YehnxS2fjBxvhKOz8Ai9BWp2u+WRQVJ5sjjtuUnEPAK8LnEZCZA1EJ1XK6WV+bzf4UTyvmuBMOlt/LEARBEARBELMLCbdEW2Bm3FYUbpuT51kPZsVxkTddKtGkNSohX5yMMm6bTib/XbSXcGu0tTNo5AjW47DKaeXFyZoVH8JiEVj/lQS+xVEJ1bevi0JJxq1DUQmdAQ9yml6UiTpT7Bx3LM875K89it5twi3bXm3nimSLcZXG9FpxOiqB5ad2BT1l44c5xrdRxi0T/CSBhyTyrhGUGyGZySHgEeGTBOQ0ve0XP6stPrUiKiGWKgi37F5mKkmOW4IgCIIgiFZBwi3RFhTcWdUzbltZnMwqINk6bvNCRcDMuDXaPBccUG6j4Lhtn2PLHNldQWOiXI/wo2lVohIcPifMjFvmuBVb6+JTpnHcCjxXdAwcc9w6mP1oupitjtv85wnVkG/LKC3E1mqm8tur7RZQ2M8qFZysFdHhhQMWWdIZMoR5qxBecNxWEW4ld2WXz13HrWD2HTtHdzvBvhO7uJdWRG/E0wrCASbckuOWIAiCIAii1ZBwS7QF022r5d2QcWtx3IaD5blwpY5bNklzizNrLsHcfO2Uf8i2aEfyfacet7Cq62WZrTzXnMUMJpIxd6hRnKz1wm0lx63AF7fPqYxb9j054UQrPaZAQdDsqMtxW1yIrdVEa8i49VWJHagFSeAcHUOZg7qwgFJouxnZU7U4GYtKcMfYU8iA5uAR+TlxvUlnVQR8ohk7VG2cn0jIGJ5Kz1bTZkS1AovefH+arUXInKohlc2VOW4p45YgCIIgCKJ1kHBLtAXTFbIRm7QtvB7Y5MtbKeOWFSdjGbeiu5xZcwlWzK6dohJS+YI7IZ/RP+Q6BBZV1codt01azGD9VbA4blspBmUtxZfsEHgequ6847YzyAoQNu5Es3PcMcGmHset6DLHLTs2GRvRKVNDoa9acDoqIS2r4GBdQCm8dnaaRQLAEEiB+s7fZmJ13Hry7ngncplbSVI2imexHThyFcftt27bgs/+37Oz1bQZwfqvZFecbJYd3PG0IdCaGbfkuCUIgiCIQ4bBiZSrYteIAiTcEm2BmXFbYVst7yLhVrJm3BY5bvNRCSUZt63MB52ryFnju8goatuIFOmsCr9HtBSjqcNxq5U7bptVsK/UHSrxhnDWquM8nZgm8BxUtVy4bTjj1nTcNi5omG2yRCUUHLd1RCUIXEt3HViRFdXcwp62KSDF3Kv+hqMSnHV8J/OFr5igbF38kRUVHpEHx1XuOyz/1i3OVmuUiHnNcUkfmQmqpkNWVLM4GVA9KmE0lsFYLDNbzZsR1TNuZ9fBzYTbcH7c8UoCfJJQdC9DEARBEMTcY3AihUuufQR/23ig1U0hbCDhlmgLZEWFwHMVtze7wXFrxjmIAvweAZLAFztuzagElnFLxcmahVVscYuAMh2pvIuMTdRrdexpmg4d5Q7SZjluc6oGnuOKHLc6WnfumaKHjVsNKC/YpeUFZqGK+FYLzJHpSMatWl6cjAn4QV/tUQki754MU+vYZ7eVfbr4m1qRBB45TXds4SAl5xD0iWYcgnX8kHNaRWc3w23FyRTL+SHNgWsOu44GvbVFJWSyxgKCmxfwlCpj2Gw7uONp4/haF4wiAY8j4xxBEARBEO5lNJqBpuvYORRvdVMIG0i4JdoCOafBKwoVnU6m47aVWZtsu7NkOLLCAQkxS/5luqQ4GWXcNg/rRN4uX9ONpGUVfq9gCj+1xjywGIBSB6nQpMUMVdOLimixf7fKOV7NrQYY7bMeA+a+bTgqgVVbd8CJVhCfLcXJpPZ23Fqzf5kD3koma0QSVIsdqAWnXaQpOQe/RzS3qFvHj6yiVSyQyWCfxy3iaNbGcdvO1xwm3Aa8Inz5c6SacJvOqtB03dWfuXDvUL4oYDq4Z8lxG0sbAq113AkHJMq4JQiCIIg5Dot1HIm6e6fSoQoJt0RbkMmqVauPmyJVC101smIIEcz9Gwl4yhy3PMeZE3/KuG0Ouq4XC7dtknNrRCUIpmBXq9DAhMjZEm4VVYPIFy4dpsOwRf04m1Mh8lzF6AO+xHHLxgir+DwTOh103BbiG6yO27xwW5fj1j0Zt9M5bjOKCq9UeTGuVphL0am4BDM/VSw/D+WcaoqFlTC3tufcMe5Y85PnguM2WSTclovrpbCYjmpxCq2GRUF5bBy3pvN7lhbGEnnHLcu2BYzdBZRxSxAEQRBzG3av5PairocqJNwSbQHLFqxEISphtlpUTjanFQkRkYBUnHGbF+bY404LDoRBqeDZLgXK0tlcScZtjcJthcxWJgI6H5VQ6rhtbT9WVL2i2xYw4gOKHbdGO/kGBUNfXmR3IuO2UJyo0KZAfqEqnBeIa4EvyfNtJVZB2064TWWNLNlGcTpyJiXnEPDZZ9xmstWvQwBc52otctzm+1erFlmcoOC4FeBjUQkVRFlVKzht2e+5EWsBuVIKmcmzm3FbHJUgIaOobXMtJQiCIAiiflg9HnLcupPGZ00EMQvISnXHrRuiErI5rWjiFQ54kMgoyKkaRIE3BAGLUMHEr3Z2P7mR0smlXUV7t6HrOtJZFQFrVEKNE/VCVELxpL9QnMz5jFtrFmurXXzKNLmjAl9cvMqp4mSAEZfghHCrlBR8A4CzjpqPpJzD8St7an4dSeAhK+7Y0syOS3fIi4mEDE3Ti+Ip0rLacGEyoCB2Kw4I1pqWPw899udhNqdNG13htoxb1vc9Im+KgO18zUllLI7baYqTWcVaN0fmKLni3HArheic2fnOYnnhNmRx+rNiq7GUgt5I4+csQRAEQRDug+1SSso5xNNKXXFtRPMhxy3RFsiKVt1xmxc8WhmVkFU0c3stYLhUgMJEKJXNFQkVHopKaArM3ccmwe3gEpIVDZqu5x23gvmzWmCLFaWTfr5Zxck0vaiITiHjtnVRCdXGhkrFyRp13ALOZT/aFScL+SS849Ur6hKYSz9rK2HC7YIuP4DyhYjShayZ4qTj28wh99o73+V8vEM1TOHWJeOOUuS4bf+ohFT+OwrWkHFrFWvdHJWgqJXvbwoLAbPruA0HCk5/FptAcQkEQRAEMXex3iuNkuvWdZBwS7QFGaV6tiATYVq5TTibU82CNkB51Xmj+FRBqHDbltq5AhM8w/lVwnbIuGVh8H6L06/WiXrlqITmOW4Fy5b+VjsMs7nqizpCaXEyTQfPcQ0XJwOMnNspB8QMVthNajB313AXu0O4jeaLk/VFfADKhTMWHdMoTi4cWAtfmQsoJY7b6aISCgty7vgeCoXv5lhxMp9o9p9KblrmHAEKY6wbyeaKdzFYme1id/EqjtsoFSgjCIIgiDlL2rJTaYhybl0HCbdEWzCd06lZhZjqodQVbDpuUwo0TTccZhahopBx644J/lyBTeKZY6gdHLdpi2DEtv3X7LidRridrYzbVglVSklESSkCx5kuW8A4Xk7EJADGOS4rasPbsO0ctzNBFHj3OG5TWQg8h3lhQ7gtPUZOOW7ZOOqEGJm05KeWblHXdT1/HZpGuJ3lTNLpUKxRCXMgVz3JohI8IrymcGsvyloXC9welVDZcVvf9aBRYikFPkkout/qDJLjliAIgiDmOinLvdLIFDlu3QZl3BKuR9f1aR23zAGotTIqIach4i1kwTDh8LcbdmHvaAJJOVe0/ZCJR+28bdWNMIccE85lF0/YGal8GLzfK5jCUK2C83TCrdNCXk7Viib1rd5+PV3uKIsP0HUdHMc5K9zmXfVTySzme/wzfh2lQtxFvbgpKiGayiIS8JiuSGt/zqkaFFVzyHHr3AKY1XHL8lOZIKyoOnRg+qgEYXYzSaejqDgZc9y2sXBrLU5mOm4rHOviqAR3O26lSo5baXZd0naZdmbGbfLQcNwenEzBJwnoCnlb3RSCIAiCmDWs900jUXLcug1y3BKuh01YqjmdBI5tl22daGHk1BUm9fM6jJv+Z3eNwysJeNdrVuCj568xH+c4DpLAU8atw7CLDptsym0gjLNtvAFLxm2tE3Vt1oXbYset1GIXXzanFUWUlGLmX+ePg6Y7k28LGFEJABqOS8jZFCebCaWF2FpJNJlFOCCZAqhd3qgzGbfORyUEi5zvatHf3iqF8AD3ReCwBRWPKMz6tvtmwFzRQd/0GbfWeATKuK0NO+H2UMu4vfr6Z3DtnS+1uhkEQRAEMauk5BzYDGmIHLeugxy3hOthE2ZfFXcWc9y2NiqhuEjSUcu68NmLjsLS3hBWL+gAZyMWeUTeNRP8uQJzukXy2zvdvEWWwdro94p1Z8bmpotKcNiFntOK3WGtdvFlc5rpcrTDKmCLglHMzYl8W6Ag3LIc65mSUzUIvH1V+XoozfNtJVNJBYct6CgItxZxjQmkfgejEpyI6rDmp5Y6303hdpqoBIHnIPKcq6ISeM7oW9IcEG7NvmNZ5KolKiEtu+P7sEPJaRWd3GwBoZH7BFXTcdvje/GGExYh5KteITqWVrAyH2/CMPP6D4GMW13XMRrLmPcPBEEQBHGokM6qZp0HKk7mPki4JVwPm3x5qjidCuJM6yak2ZxWNKnneQ7nHrOw6u9IAu8ah9xcgQlE7ZRxawpGnkK2YK3tZo7bUjGSb5ILPacWRw046XicCdXcakC581jVdIgOCbdhS451I+TUysWJ6kF0SVRCTtWQyCiIBCTTFWkV0QriW+NRCUyMdKL/JfPiXtArms5aJpjJpnN1+u/JIwquKk7GjpGTecCtwhpnIfAcPCJfuTiZ3B5RCYqqIVQh7kUSOHAAsg1Ebzzzyhh+du92eCUB/3LykorP0zQdibRiFvZksP8fCo7bjKJC03WznxEEQRDEoUImq8LnEdAX8VFxMhdCUQmE60lZtkZWQjTdhbPSpDJUTZ9WQLJDEikqwWmY4Mkybitto3UTaYvj1ltnpiFz3JaKkTxvTPidL05WLDK20sWn6zqyilrTok7OItw65bhl7rVkg5P8nENissDz0HTd8e+8XmL5yvTWjFvreWj2d0czbhvvf0VFAk3HrfG6WdNxO32bPSJvPr/VKJb8VPNcbeNrTko28u7Zee2ThIoZt1axNuVyx22ljFuO4+CRhIYc3Mw1E09XX2BKyjnoQFlUgijwCHrFhheo2oFEvvidm/sLQRAEQTSDVDaHgEdEX8SHiYTc1gv9cxESbgnXk7TkDlaCCTFqq1x/lhzBehAFrq23rbqRgnDLHLfuP76FzE+hLFtzOtQKjlsgn3nqsAs9p9ln3LbCYZjTjIJR1TJuhZKxwcniZCyjlVW6nylGbrADjlsWGdPCIo2AUawNMKIkCtvZyx23TmTcevKf2YmojqSl8JW3NOPWzFqvQbiV3BOBk7UsKNYbw+JGUnKuqN/4PWJFN63V5e3myJxsrvqiryQ01p/G4jIAIJmpLryyBZcOf/l52eGXEDsEHLdsbGp0MY4gCIIgnGJ4Ko1v/OmFpu8GScuG47a/0yi4PBqjuAQ3QcIt4XqYKFLNcWuKMy3SK5hoMF3+YSmSyLd1hW83YmbctpHj1rp1nGWd1huVYCf8CQLffMet0DrHLXvPSm41oLw4mZPCbdBriHjTCSLTYRxTJxy3TKRurXDLMn8jQU+hgJRdcTJHHbcOZtzaON/Z+VjLropGhTYnKXLctvBcdYqknCtaxPV6+IpjfFq2FidzrxA3nXDbaBb+eCwv3E7jImWOXBYzZCXkE0036lwmlf+MsqJSjBVBEAThCh7YfBD3bxrE5j2TTX2fdNZYHO+PGMLtCMUluAoSbgnXwyYLoarCrdGVW7VFuDCpr0+I8Ai84xmkhzpmxm2wfTJu05aCO4BRub72qATjeYJN8TuB4xxdzNB1vSwjtpUZt+wYSVVED74k41bTHRRuzaiExvqYomoQ+cYvx4VYiNYKDlbHLStOJjepOJmTUQkpS8atKPBFCyhsQajmqAS3FCfLaZBEo1/MhaiEtKwiYLkX8EkC5GylqATLYoFLrwO6bsQsVVt88jbo4B6PG46Z6RaY4qbjtjxvN+iTDgkXakK2xmvM/c9LEARBuJ/BiRSAxo0i05HOqvB7BfR1GkVKh6fIcesmSLglXA9z3FbbVmsKFi2sbA/U5sayIol8W7uf3AgTWlhBlXYQblNmVEJeuJX4miMeKhUnYz9zcjGD5cRahdJWikFMHKtanCx/WHLNcNz6WFRCo45b3RHHrekubrnj1jgeVuG2KOPWIpA2ipQ/bk5EdZQKyh6RNyMS2Djiq2FXhUcSoOTcsSCXLXLccubP2pVSx20tUQkekS8qVOYm7MbUUjyiALmBhQAzKmEaIZJl2NpFJQR9IlJyDnqLY1iajdWlfSgI1QRBEIT7GZwwnK+NGkWqoagaFFWDXxLQnxduR6LkuHUTJNwSrqdQnMy+6jJQEG61Fk0qsnVso7UiCiTcOk3GUvjII9YugLaStCUqAchP1GsUnM3iZDbCn8hzptPUCdjCiFX4bGXGrVLDggkTM5mArarOFSeTBB4ekW+8OJmqVRVuaqW0EFurmMpnYUYCkhmVYHU/prLOO26dGEdTcg4ekTf7tNdyHppjfJs5bnOqbvYtTwsLCTqBruv5jNvCd+CTKkclZLIqOABdQa9r3ZO1jGFGsTsnohKqH4NqjtuQT4Sq6W0RPdQI1jiIRrPLCYIgCMIJmOM20UTHbWH+LKIvH5VAjlt3QcIt4XrYIFU9KoE5blsk3NZRuMaKJPBtvW3VjTCHnM8jwCsJbTHRTGVVCDxnTt69Uu39wnTc2kQl8A4XJ2Pnl3Vbr5PCWb3U4nQvdeM7GZUAACGf1HhxspL4iZliZty2OCrBmnHrrxKV4GzGrTPFyQIeS36qJJQXJ6tBYG80k9RJFMuiAPvbLW2rF1nRoOm6GSkDGON8NqfZLlClFRV+jwi/V3BtcbJa4l4aKXanqJq5kDLdOMWE25DNIjn72VzPuU2R45YgCIJwEbKimkXCEunmCbeFXWcCQj4RAY+IkSgJt26ChFvC9dRVnKxFTrOZRiV4RBJunSaTd/N5RAE+yb0TditpOQe/RwSXF18Np3Bt7VarOG4Fh6MSFFvHbeszbqtlS/MlbnxV021F7pkS8AqOOG7tisvVi9jiBSxG1HTceszFrLRNcTInHLeFqARnHLfW/FSrAJutO+PWHeN6NqfBU1qcrE2vOcypbb0X8OVFXLvxMi3n4PMICHjEov7nJmopsFhP5nkpE/mYBGD6zFYmyto5bpnLuZmTRjeQJMctQRAE4SKY2xZoblRC2rJjleM49HX6MEzFyVwFCbeE62GiSLU8xFZHJbBJY73bnaV8VMJcz42bTWTFyHQUeA7eKtto3UQqqxZt/zWcfrVN1M2+ZzPxF3jOURGPZadaRUZPSzNua4hKKBEzVc2ZPFlG0Cc1vA3byLh1ICqhJBaiVUwlFXT4JdNFzgFFCyhpM9O5ccctG3Od6OepkvxUI2uaOW5rj8NhC3Kt/h4A47z0mFEJxvFu16iElE3ePYvisBvnU3IOfo8An0eomIPbarIqE24rj0mNRG+MxQrC7XRCJBNlQzYZt8xxm3JpVrBTWBfh0uS4JQiCIFrMwcmCeNrMqIR0Sb2V/ogPI9GMK+5lCQMSbgnXk5RzEC3byO1gDrrWRyXUm3HLQUfrnMJzkYyimq44n1R7VmwrSWdzRdt/63HsxdOVXVICzzm6mKHYiAyiCzJuq4meTMxULcXJnMq4BYwFpUadWYqqOVOcjHfOfdoI0VQWnQEPAIDjOPg8ghk1ABiCCAfDSdgoTkYlpGS1SBS0LqDIdTlu8wJpi78HXdeRVdSyqIRWt2um2C3ismJxdo7adNb4Pv0eIzLHjQukZsZtlX7Frgczaf943NjmyMEQsqtNwOJpBTzHFcWFMJjLuZmTRjdgHcsTJNwSBEEQLWZgvOC4bWZcUaHeinG97+v0F8UtEa2HhFvC9SQzOQR9krmN3A6e58Bzzm4Lrwelhi3bdrT7RNqNyIpqurDqca62krSsmlmgQHG25nRUKygjOFycrBDLULh0SC0seFSP49Yq3AoORiUEveK0gsh0OBWVUBoL0SqiySzCwUJ/9HvEIsdjKqvC5xEcEdAdj0qwuICtCyjsfKxlcc7jkixZVdOho+DGN49VuzpuZRvHLYtKsBFuM/l+5vcIUDW95d+HHdlaohIklhNdf/vH81EJ87v80FGIm7Ajkckh6BNtz8uQKdzObTHTunsiNcc/K0EQBOF+BvJRCZLAN/W6ZI1KAAzHLQAMT1Jcglsg4ZZwPcn8ZGI6BIcLMdVDPdtorbR7lW83ksmqprhSjwDaSgzBqNhxW+tWaybchgPlwi3vcMYtczVa3aGSg47HemHbhz1VxDRTzLQKt046bn3itILIdORUvepW6VopfBetE241TUcsrZiOWyAfOWCNSpCLHeaN4JTjO5vToKiajeNWNR8HqjsjGW4Rbk2HfL49HMdBEnhze367UXDcFr4Dn6c8Q5lhFCcTzCxlN+adKzUUJ2OLcrF0/a4XFpWwrDcEoHpcQjyt2C4AAkYkzHS/PxdIWfoIFScjCIIgWs3ByTS8koCF3YGm7nphNWLYfVVfpx8AqECZiyDhlnA9yUyuar4tw+lCTE+9PIbr7t5W02uywjX1CrdSC7eZz1XknGauFvryW2TdjK7rSGfLHbdAbcJPtUrgosOOW8Um47aVBY9qKewjlMQHaJpuxic4ARP6Zipo6LpuRCXwDmTcuqA4WSKjQNV0dAYLwq1PEoqEtWSJs7URChm3jfU/OzendQGl4LitR7ht7dij2DjSWa56O1KoeDx9xq2a/878ecct0NjiSrNg/dZTZUxii3LxGRQGY47bJfOCAKqLkclMznTWlsIWz5NzPipBMa8nc12kJgiCINzPwHgSC7r8CPnEpu56YYXP2H3w/LxwO0QFylwDCbeE60nKtTtundQr/rbxAG57Yi827ZmY9rm1VLe3w3SLtelE2o0YjttCxq2q6S1xg9ZKNqdB0/USp19e+Kmh3fG0AoHnbIUw3umohHx7rI7VlkYl5E94b7WohJKCXaquw8HaZKbQMVN3Fvt6nMi4FUpiIVrBVNJwBUYswq3fIxYJa0Y0iLOOW8eE2woLKKZwW8PinOQSx63ddckjtrNwa3wH1oVcJsqWumkz5pY/0XyOnSu31bAxvtquASbcxlIzE26DXhHzwl4AqFpIsZrjtqPBca5dSMq5mo4VQRAEQTSbnKphJJrBou4AQj6xqddgFmnG7pn68lEJ5Lh1DyTcEq5G1/WySt+V4HnOFJacIJqfJN31zIFpnzvT4mSUces8sqU4Gfs+3Oy6ZZNDn8cqrrBMw+nbHU8r6KiQAe10xi1z3FodrjxnFL5phcuzEJVQecGENTWn6aaI72hxMl9jjttaCqzVimgWYmvdeDKVNMZNq+PWK/FFwloqWxwN0giFjNvG+p8p3PqKoxIAo5/VkqfMYOdvtsX52nbFBKW8i7gdsXXcmsJt8fnHJiBGcTLj+WnZfdcB1keq7RpgYupMHLdjsQx6OrzTRh2omo5UNme7cwMoOHDmesZtMpNDZ9ADkefmvEhNEARBuJvhqTRUTceingBCfgmyojbNFJApybjt7vBC4DkMk+PWNZBwS7iadFaFpus1OW6d3hYezVdRfPSlEUST1bPlsjPMuJXIces4hnBrHFdfA0VdnCSRUfA/Nz+HvaOJssdYpl7AU+yKA4BsDcJtLK0g5Lc/P0SHt0UzQdAqMnIc1zIxqBbRgxUiUzUd9z8/CFXTcfjCsGNtYILITN1Zik1u8EwxoxJa6Lhl42anJXPZ5ynOmk47GJXglOO2kJ9aHJUAGOOHrKjwiHzVIpmlv+cWx601P1WyFFxrN1JVMm4zJWM8c9f6LFEJaRdGJZTmENsRzgu30Rk6bns6vOYxqyS8Jswil5WiEg6RjFvZKIYb8Iqmw5sgCIIgWsHAhCGaLuwOWKLZmhNZZM5H8+8j8By6Q15MJOrP1yeaAwm3hKthk4RKLhArTm8Lj6UU8BwHRdVw3/ODVZ8rzzDj1kOOW0fJqRpymm4Ktt4K+YezzYv7pvDothE8vm207DHmFPPbRCXINWbchv0e28c6/BLiGcWx7OdCxm2xeCUJrRFuaxE9WJ6trKj4zUM7EfJJeMtpyxxrw3SCyHSwMcsJx60ZldDCjFu2yBUuybjN5d3O2ZxxjjrluBVZhnGDYqRdxq0ZWZJTkVG0mqNw2Lb3Vo/rdm7uds64ZfcDgRoybq3Vkd0clVBLTnc4X+ivXsdtOpvLb/33TSu8soInle61PCIPj8jP6YxbVTPy5oNeAUGfOKc/K0EQ7c1oLIOJhNzqZhBNZnAiBcAQblk0W7NifDIlUQkAEAlI05rXiNmDhFvC1bDJRC3uLJHnHRNudV1HNJXF8at60OGXcPfGA9D1yq9dT8VxK6JQXDiJaAwmoHtLhNtaIgeayWT+ojdpc/Gzy2301uEUTmRyFV1SnQEPVE1HwqGLfK6CO7RVYlAt29eZmPmXp/ZjOJrGu89YUdNCUK00WpyssJ3diagEF2Tcmo5bi3BrEc7SbLu7Qxm3HMc5snCQshEFredhNqeaIuF0FKIS3FeczDMHHLd2wm2pm7bQzwRzUaw0B9cNFO4dpnfc1ptxOx4zJvVGVEL1CV8sbfy8UsYtYIi6czkqwdq/gt7mZgkSBEHMFF3XcdX1T+Mrt25udVOIJjMwbgi3i7oDhdikJl2HCzuVCvdYkaDH3ElHtB4SbglXY4paNTlunRMsknIOqqZjXocXrztmIfaNJbFl31TF57OohFoK11hpZWGnuYicK2yPBSzO1RZP2FnBJrtVy7Rtxm1tUQmyokJWVIQqTLYjQani+86EnFmcrLifiwLfmoxbZfqIEibcbt0/he6QFxeevNTRNjQalZCzySGdKYXiZK0bT/aNJgEAvfmiBkBBpM0oKlJm9qgzUQmAIVg32v9Kq+kC1qgEFbKi1Zxh7sl/l7U45ptJ1mZRoFXueCdIyjmIPFd0vlcqTmadgLSD49bThIzb8XhBuA2ZGbX2r1Fw3FZeUJnrYqYZxeGTEPRJFJVAEIQrGRhPYXAihb0j5fFrxNxicDIFkefQG/EVsuZnkHdfCymbe6zOoAfprNpyAxRhQMIt4WqSNUwmGE4WYmJZcpGAhDeduBgA8NcqRcoKUQn1iRGUcessbPLOBHQmhrZaQGHC6ZSd4zZbLhiZTr9p2s0m8uEKwi0rEGX3vjOBZaeWioySyLUoKiHfnirCrWgpRPaes1YWCeROwMamSoLIdLBYA8HB4mSNFuqaKaqm46mXx7B6QbisOBlgLKAUtrA747gF2MJBY/3PWsyKUShOVsi4rQWP5fdaiZ3jVhLbNyohJasIeMWinGGvx353gvl9egTTPeLGjNusuYuhct8KeAUIPFe362UsZlSCnhf2mkX3Ku0MiJsZt5UXyY34APcdQ6dIWjKUA14ByYxSdacVQRBEK3h21wQAY4cTCWpzm8GJFOZ3+SHwXNOjEtJZtchtCwCR/O65enf8EM2BhFvC1dgVjKmE4GBUAhugwgEPlveFsG5JJzZsHaroeLErAlMLhYxbmhw4AbuBMR23or0ba7ZhCwF2Amq6WnGyXPV2TzfZdly4rSAytMrFx867ak53Pi/czu/0440nLHa8DcFpBJHpUJrguG1UxJwpW/dNIZ5WcOqa3qKfeyVrVAJbqHBOQJcE3hTAZopd4Str1Eo2p5n/nw4qTtYcUnKuLBu5YlQCWyDwFhy3zZrsNIJSw70Dx3EI+yXE6nTZjJmOW595D1XJMZvIRyVU2r0BGGPdTBeo2oEix61XRE7T2/ZcIQhi7vLcrnHz32yBjph7aJqOgxNpLOoOAChcn5sVWZTOqmX35uF8oWGn5pFEY5BwS7gasxhJzY5bZ26yY3lnCxuwXnfsQmRzGp7fPWH7/GxOhchzpnBSK6bjtk23rrqNTEnGrem4bfGKNMv9tFuxNLMYK1Szr0Z8mlzCSF64dS4qwb6QVqtcfEzYruZ0X9wTRMgn4SPnr3EkR7aU6QSR6VAqHNOZ0OqV8Se2jwBAmXDrN53vhagEJx23kgNRHakqUQmZfCRJvcJtq52tOZvifZLQGne8E9gJt5WiEjJNKE6WzWn4z99sxJM7yotMzvw1p497AYCOgFR3VMJYPuN2XtgLj8hD5LmK4jUTZKtn3IpIZ9WWZmg3E2vxu0CD4zpBEEQz0DS9aC46EiXhdq4yFs9AUTUs6gkCKMw36r0XqJW0nCu7NzcNQJRz6wpIuCVcDbtpDtXkuHUyKsEYoJgQsrjHWO1imXGl1OPGsiJSVIKjsMzTQnGygvDSSqYSrDiZXLb1MmkposPw1rjVejrHLeu/UYeEPFO4LVmgaFnGbQ1utfldfvz5s2fjNUf2N6UN0wki06GaucGNO267Qsb3PdmiSsOP7xhFd8iLwxeEi37uK3LcsoUKpzNuGxtDzd0dPmtUQsE5K+e02qMSWHGyaRzzzcZ0c1oWBTyisTNFa0PxLZpSzMVUhigY51+6ZIy3jqsBh4qT7R9L4OlXxvDIiyMNvY6VWhy3gDHGx+stTpa/X+nu8ILjOAR9UsWdASwzr3rGrXHs56qYaY1KYONAeo5+VoIg2pPdI3HE0oo5LyXhdu4yOJEGACzo8gPArEQl+Evi5CL5e64YOW5dAQm3hKthk4xgjY5bp2ryMMcaK+7U3eEFAExUEG5lpfZJvRWzOFmbOqDcRqZEuPVJ9vmHsw3bYpLNaWUisp3j1rpFuxrTRyU4u8XFbVEJSk6DUIPT3ZqJ6TTTCSLTYeb0OuC47Q7lx6nE7N9gDUyksG80iVMP7zXjKRhWV6RZBMzhjNtG+18qkwOHwpgBFM7DTJY5bmv7jiS3RCXk+1ZRxm2b7vKQFRWJjIKe/LXYis8jVnXc+hxy3I7HjfNqwsGFEXb+VytOBsCMSqgnc3UsnkFnwGN+50Ff5eJi8RqiEkJ+FgszN+MSrI7boFnMjYRbgiDcw3P5fNvzjlsEgITbuczAeAoAsKhn9qISyoTboLMGIKIxSLglXE3Skjk2HQLPIeeQcssGKFb0qSCIVHLcqnUXJgOsGbftNYl2K2bGbV5gMYWXFjturUVlSkXUahm3jQq3BcetM0KeYgq3JcXJBK4lIlU2pzUl/qBeAl5hxi60SmL4TPB5BAQ8oqPCUq08ud3YPl4akwBYC0g1x3ErCVzDju+JpIzOoKdI5GfnIftum51xm8mqjl4L7IqTFdzA7XXNYX2aXYut+CShTLi1ZtxKAg9J4BsuTsYcrJV23swExSbOwo5wwANV081Ij1oYj8mYFy4cr6C3cnExFpVQrZ6AGR8wR8XMlKWmQqDJziaCIIiZ8NzuCQg8h9cevQAAMErC7ZxlcCIv3OYzbs0FxSZEJei6jnQ2V2QiAgpRCU7NI4nGaP2MlyCqYDpua4xKcGr7Z6wkKiHkMyZ/lRy32Tq20VqRKCrBUSo7blsn3MqKWuT0mkoWX3BN4dZrv0W7GgXh1v788EpGvqNTK6UsisQu47YVBbFmet45TagBx23OPKbOuIK7Qh5HhaVaeXz7KCSBxwmresoes0YlsIxbpx23jfY/Q+TyFf2MjSPsPPPWuDhnCrd1jjtX/OIJfO+OrXX9TjVYVENpcTKg/RYLJ/Ju125bxy1fvpMhWxxB4/MIDTtuJ5og3GZtxHU72CJyrdl2uq5jPC4XOZSN4mKVHLcKgl6x6u6FUIOFGN2OdYdXiBy3BEG4DFXTsXn3JI5Y3Im+iA8ekccwCbdzlsGJFDgA/fmoBK8kQBL4psQVZXMaVE23iUpgRa7JcesGWj/jJYgqJDIKBJ6raYuq4bh1KOM2qYBDYVsCx3HoDnkrbkHO5jR4atxGa4WJNSTcOkMmaxxHX2nGbYMT9kZgq5Rs8aG0UFhSzoHnuKKJOxOIGnXcAsZF1/niZOUZt62KSpjOqTYbBLyVBZHpMAtIOeQc7u7wYnKWoxKSmRw27ZnAcSu7zW3pVnyWqIS0WQTMQcet2FjGsp3IBQDefN8yhdsax/jCTora2yQrKvaMJLBjMFbz70yHXcat5JLCafUyHjcmpz35HGcr/gpRCRwKY2nAIzYu3OZdv1PJrGN5+vVk3AJArEbhNp7JQVE19HQUFiOCXhHpbM42biGRyVW9jgDGAhV77lyEuWsDXtF0HZHjliAIt7B9IIpUNofjVnaD4zj0RXzkuJ3DjMYy6O7wFt3DhaoswDZCIV6q2FTR4ZfAwbki10RjtH7GSxBVSMkqgl6xpoxKQeCdc9ymFXT4pSL3SU+Ht3JxMkWr2Y1lpV3dT26l1HFba1ZsM2GrlMv7QgCAyZKL30RcRleoeIt2rRmZNQm3QY/jGbelIqMktKbgkaK6w3Eb9FUWRKYjVyF+YqZ0hzyIprKz6oB+5pUxqJqO09b02T7us0SWpGwynRtFEviGtv7HUgoUVSvaVg4Anny7WeZ5zcXJzOKCtY87YzFj8uXkJMxuG77UpouFzHHbU+KKBoxxvlS4TWVV+DyCmbfs8wgNF5pijltN152Ln8l/D6UFH0thRdliNb4v609FUQk+Eaqm20YHxfP3PNVgtQYSczXj1lKgMEhRCQRBuAyWb3vcim4AQF/Ej5Foekb3noT7GY3K6C255wn6xKZEJZi74UpMFQLPIRzwUFSCS2j9jJcgqpDMKDUVJgMAgYNjLphoKltWvborL4jYvUc2p87I+ecR6ndmEZUxM2497sm4ZaLpsl5DuC2deI9EM+iP+It+5pVqy6GMZ3Lwe4Sq+aidAQlTyawjN3ZMDCzdTmuKQbO8ACHPMFvaaYLeyoLIdCiqffzETGEZoKULBM3kcTPfdp7t435rxq2Z6exkVALXkFDNFuQqOW5jpuO2tr7Gfq8eh+dYzGhDUs45JhaZ2/AtfcuMcWizxcJxM+O23HHr8wi2UQlW54jfgaiEcUt2dKXYpHpRVCOne7rFabOyc40TNrs+Xa3gViKTM6MQKhE8BKISeI6DTxKoOBlBEK7j+d0T8Ig8jljSCQDoi/iQzqo0Ts1BVE3HRMJOuJXqyrqvlbSloGspkYCEKRJuXQEJt4SrMSYT0xcmAwCe5xwTbmMpxcx1YXR3eKFq9k6bGWfctum2VbdSKE5WyDU0ft6648u2lyzvN4Rbq/tVUTVMJmT0RkoEI6n24mRhf7mQYSUS9EBRtYZFC6AgMpY5blvkHM8q7nDchnwzn+Q77bjtYsLtLMYlvLh/CkvnBdFXsgDBMBdQsobjludqi7+plUYzbsdMkWuajNtahVtJQIdfqss9OxorPHcs5ozr1jxfbYqTtds1hwmldhm3fskQbq2O/0xJdeSA14GohLjzwm2t9w4ddWbcsoWAnhLHLVDuItU0HcnM9I5bM+N2jrpQU3IOgfwOL3asGnVpEwRBOIGsqNiybxLrl3aZ14zeiHHPMurQPQPhHibiMjRdN79jhhGV4LzjlsWY+WxMFZGgB1HKuHUFrZ/xEkQVkvkb6VoQed4R4VbPb4MsddyaTraSiu26riOb02YkRIgCRSUw/u/hnbj/+cGGXoMJtGyrsshzEHjOFY7bpb3Bov8DhkCjA+gtEbw8Ym2Cs7G9tfr5wSqCOhGXwM4vwSbjFkBDOaMzwU1RCcDMttXmnHbc5oUtp4Sl6dA0HcNTaSzsCVR8DltASWcNx63fI9QUf1MrkmDkm880qsNuWzlQLtzW09fmd/oxPFWHcGsReUdjDomCSuXiZI1ES7SC8bgMr8UJaYX1L+tnSsm5IuHWKE42szgTwLjOTySy5m6DcYcWRmoVbgtRCbUKt/k+bVmMYPdSpY7ZpJyDDky7SB70zu2M20QmZ/Yv9vdcFakJgmgv9o0mkc1pWL+00/xZHxNuKed2zjFa4b405BORlHOOGdUYhcLB5QaFzoAH8bTi+HsS9dP6GS9BVEDX9bwDojaXE88b2XON5myyAbHUccu2HI7HiydsOU2Hpusz2rJNjlsDVdPxfw/vxB8f29PQ67CcQ+a45TgOXlFoacYtc2gv6PTDI/JFAe8j+ZutvpIVVYHnIPLctBmZsZRiFtCrBBNunQiWL7hDiy8d7HjPdh5g1kXFyYCZbSFWnC5Olt9KPpGYHeF2PCEjp+mY32nvtgUKxQ4yiop0tvbFuFoxFw5mOPZXikqQBA4cCmKZXeG1SvRFfBiLZ2q+0bWKtU5Nwuz6Fvt3u11zJhIyukuywBmFhYHC+ZfJqkXOEb9HgKrpM44lSso5yIpqZpWzYmmNoqi1jWFmcbIahduhyTQAoL+zcG1hwmypGFnISq81KmFuOm+s95uNjOkEQRBOMzRljOmLLIvkzI1ZzyIx0R4UDAUlUQn5BVSn51uZalEJQQmarjclW5eoj9bPeAmiArKiQdX0mqMSBN7ozlqDWZ7R/MQoYpNxC5Q72bLM5dlQxm17TaKdZjRqCByDE42F7Mu54uJkgH3+4WzCtqxHgh50Bj1F2aNjeYGmN1y+/dcrCVUdt2x7a3ga4TacX4BwIp+ICWNSieOWiQPD+RvL2UKZYUSJ0zTizmLCntNRCbMl3LLvvL+KcCvwHCSBzxcnU+GvcTGuViTT8T2zcbSScMtxnFH4ihU9rKOv9Xf6oWp6zbEH1q2OTm17ZOKsx8Zx227XnIm4bBuTABQXv2OkS6ISzMWD7MwmO+y6v3pBOP9/54qT1bJowyJxao1K2DeaRFfQY47/QOWMWuagDU5zrzXXxcyUnDOPgSjw8EoCOW4JgnAFgxMpAMD8rsK9Vt8cjUqIpxV89GePY+PO8VY3pWWwxfzSjNuQvznXYbbwbVc4OOLgPJJojNbPeAmiAizDpebiZPktjI1a+WPJgtBmhU3qSwUR5oqkjNuZc3DSuCFJZXM1O4rsyGRV8BxXJCx6RN4U11tBNGVsrw35REQCxTlBzHFbGpUAGO2Wqzhu2fbW6XIJO4PG41MO5BMVipMV9/WF3YYDYHBidoXbbI2iR7NppGhPJRfzTGGO29nKuB3OO/vmd/qqPs8rCchk1bKiUU4gNijcjsUyEHmubJcFUDyue2rMuAWsixk1CrfRjCk0jjkUlWDnuPXkx8Z2ikpQNR1TySx6QhWEW08hQ5k9P6OoRbt1/Ja4jpkwkT+fVs7vAM9xDmbc1lbY1CvxkAS+JuFW13XsHU1gab4gJqPSOFVw3Fa/lgg8h6BXnLNRCUk5h6ClzwS9Igm3BEG4giHzXstGuJ1jUQkv7p/CjsEYHn1ppNVNaRmj5vyw+L4naNbUcNb9ygqe2e2IK+zcJMdtq2n9jJcgKsBumO0y7exwTLjNT2LCpcXJKhT9MSt31zGpZ/AcwKH93E9Oc3CyIPgNTs5c/JPzWcPW7bQ+j2BO6FtBNGkUuuM4Dp1BT1Fxu0pRCYCRc1tNcGb9dLpK4J35fhxzwnHLREa+2B1aEG5TDb9HrahmREnrL2PMpTUT4ZaNH6XHdKZ0Bj3gMHsZtwfzjtv5XZUzbgHDFSnnHbd2GVqNwBZqZroNfiwmo6fDB97mO7C69+t13ALASLS28Ww8LmNlfwckgXesOFk2p0HguaLP1Y6O24mEDB32hcmAgijLxnkWjeMviUoAZr69cDxW2B3RGfQ45mhXcnpNi08cxyEckGpa2ByPy0jKOTNXncHupUonfCz6IDRNVAJgTBrnopipqBqyOa1o0hrwCkjNUZGaIIj2YmgqDUngzbkoYFzjQj7JnEvMFQbGjbnEwCzOKdwGc1GXFs0NeWc+36iGGTVoF5WQ34FsV5ydmF1aP+MliAokze17syvcsoGpUlRCabYdE17qmdQzOI6DJPKHvOPWKvgx9+1MMCqJF/cXnyRUda42m6lU1lyt7Ax6kFFU8wI5mnf6dQXLnX5eia/qiktUWGAoJeJgxq2i6mVCEGCIVBxmV7g1ne4zWDBxmkqCSC0UohKcuRyLAo9IwGM6BJvN8KQxHk7nuPV5+HxxspztVqxGYGJkI1EJpTEJDOvCgLcux60h3A7VEB+iqBomEjJ6Iz7MC3udi0pQyxc22nGXB1uE6K7guPWWRCWkbbLafA06blkxsu4OL3o6vGa8RqPUU2Cxwy8hlp7+vN43mgQALCsVbisUUYync+brT0fAK87JnLuUTVxEwCuaLiSCIIhWMjSZxvxOf9n9d1/EV/MCcbvABNuB8WSLW9I6RmMZdAU9ZfcHbIHV6Z0vZlSCjXAbdrDINdEYJNwSrqVexy3vlHCbZIJY8SSGCSKlxclkm8rd9SAJ/IydYnMFq+P2YAPb7WVFLbvIsS3arSKaLAi3poiaXxwYjWYwL1zZ6VetqFqsxu2t7L2nGoigYKiqZiswekQevRFf0ffYbJgA4w7Hrb0gUgs5czu7M45bwFhkmpytjNtoGj5JmLYf+j0iYimjKq3TjttGohJUTcdkQi6r3MuwirX19LX+vIt+pIaohHFLlllv2OdccTKbKBH2/3aKSmAi6XQZt2xMYDm2PpuMW/acdDaHr/1xM/aOJmpqg1U87g55MB6XG8pjZ2TryOmOBDw1OW7ZZyqLSqiQUcsWnGqpJxDySbNehHI2KNxvFvpMyCfNSXcxQRDtha7rGJpKF+XbMvoiPozF5IYLc7uJA3nH7fBUpq12BznJWFQuK0wGzEJUgk2UGdu5SY7b1tP6GS9BVKBex63ouOO23MnYbSOIZG0KwNSDR+QP2QsTY3AiZV4sGnHcyopats3DJ/GQWyRSZHMaknLOdG935v9mBcpGohmzKmwpHrG647bWSuB+jwBJ4B1z3Fba0r+gK4DBiZQjYkYtsK1UC2xuZGebRjJu2aKNU45bwBC4Zqs42dCkMZmwxpPY4ZUEc2x13HHbQG4r24ZfyXHrlWbmuA0HJPgkAcM1iLCFrGsfeiM+xNJK1UWbWlFyWtmCYjs7bit9R6UTGTYBse6+YIIcc5U888o4Hth8EPc+O1BbGxKFNnSFvFBUzRHHi6KWf0eV6PAb+bLTTdD3TuO4LRUj2bUkXENUQsg3NzNu2dgd8JVEJci5WbumEQRB2DGRyCKb02yF296ID4qqzanCUcxpq+m6me17KKFpOsbiGVtDQbBJUQlpmwVvRiRfK4UyblsPCbeEa0nWWOmYUXDcNjYhZZOY0qgEwBBESrdIsglwPZN6K6JAUQkHJ9NYtaADQa/YUIErWdHKvgfmXG3FajQTS7vyW3w7839Hk1lksipiacU23xaY3nGbqHF7K8cZRZec2OKianpFgXFhtx9JOVdz1fNG2T1suMpW9IWmeWbzCVUQRGpBdbg4GWC4AlksQTPRNB0j0UxRsYxK+DyCuajWPMdt/ec4KwRm52wAjKxphlXEnQ6O49DX6TOLt1Vj1JKfOi8vTjqRc6uo5Y5bj9CeGbcA0NNhHwvDslz35MeElM2WP19exGW7L9j4sXukNsfteFxG0CvCKwmmgOxEXIKdK7oSYb8Hmq5PO87sG00i6BXLhG6fJEDgOZviZMb/a3HcBn0iFFVzZGHBTaRsdngFfRI0XTcjOAiCIFoBEy/tjApsDjFXcm4VVcPwVAbMCnDgEIxLmEploWo6em3uS5sXlVC5OFmEHLeugYRbwrUw90ytUQmOOW6TCniOsxWMu0NeZJRiQYRNYGbquJUOccdtPK0gnlawsDuAhd2BhlZXM4pqbptlMCG3FVuDmVjKYjfYYsBUMmsKM3YXZgDwTJNxy7IOa8kl7AxKjgi3OVUzs6RLWZAvTjXQgPBeD7uH4wCA5f2tF259kgCeKxdEaoE5bp2MSujO53E3O+d2IiFDUTUzz7UaPovo6bTjtpGoBJZZXovjtt485f6IHyOxzLSOPTYWzAv7TAc+E5QbwW4bPnN3tldUQj5ftkLG7eKeICSBx668GMvEWWs/KxQnY8KtMX7sGqo9KoH1ERbZ0GgBQFZgsR7HLVCIyanEvtEElvYGy1zwHMfB7ykvLsYW20I1XEvMuIU5FiFgRiX4rC7t5kyQ7RiNZfCbh16ZcU43QRBzl6HJyjvMCrFMc8OZOjSZhqbrWLs4AqCwu+5QYtSyC6uUUJOiEtJyDh6Rt53jeSUBfo+AqAORe0RjkHBLuJaUzY10NZjjtlFnZTSVRcgn2g5epiBimbDJDRQnA/IZt200iXYa60rygi4/RqLpGQvZsqKWueLYto9WOITY1iVrcTLAEG5HqlyYAcMZp6haxYWIegrKRIIeR1ZK7Rx8jIXdxg1lI1EX9bBnJIGgV6wofM8mHMch4J1ZtfVcExy3zOHd7Jzb4Xx+a/80hckAFC2o1LoYVytmVMIMxg0mkFYUbosct3UKt51+yIo67aLJmCXjljl/nShQZlf4ytNgIbdWMB7PQOA52/giwChMurwvhJ1DhhhrOkeKMm6LoxJ25YXbsXimpl0C43HZFGxZX2k0jkSpM2aJZaRXy7mNpbKYTGaxrNd+QSvkE20zbgMe+3ueUhqJhXEz7H7T6jYKeIWix5rJ7Y/vxa8f2olnXhlv+nsRBNFeDObnSfPzBgkr8yLsnmF24rGaDXPYnry6N///Q1C4rWLsaV5UQnlxbyuRgMeRyD2iMUi4JVxLvRm3bNKRa1C4jaWVihPEnvwgai1QllUaq25/qGfcMqFvYV641TGzlWM9v6WxkuO2FdsdY8li4dYsTpbMmtmX1aISgMpZlIkai5Ox909n1YbFayMqwX5yv7DbuKEcnGj+TZau69g1nMDy/tC02aqzRdBbLojUAhPQahFNasVugakZVHOBlOKz3BA2z3Fb/9jPtrtXKk7msWbc1rk4xwTt6XJuR6MZ8ByH7g6vuZDjRIGyrFI547adHLeTiSy6gl7bIo6MVfM7MJGQMZXMmsJtcVRCoYCZrKhFkTxMxK2ErKhIyrmC4zbkTFRCNlffbh021lcTmlm+7dKSfFtG0GfvuA3VkG9rbcNcy7m1K4bLRNzULHzWbQMxAMBLB6aa/l6Es+i6jr88tR/7xw69Ld3E7DBkCrdzPyqBOWyPWd4FnyQcko7bsWh+Md9mfuj3zHyHXzUM4bayjuGUAYhoDBJuCdfCJgahmoVbozs3GpUQSykIB+3FsMIW5MKELZsXC2YclSDwUHKHbvGLg5aVZLaaPDiDuIRshaxhtkW7NY5blpecd9yaOUFKYStMBccocw6zyX0psbQCgeeqXmgZTuUTKapW0Rm6IC/cHpyFqITxuIxERsHK/g7HXjM7eAAjP/g2sgf2z+j37QSRWmhWcTKg+VEJTJCsKSrB0k+bl3E7k6gE5ritcB5aHLf1jvG1bmEcjWXQHfJC4DlzPHDCPWPnkGf/b6ddHhMJGd0V8m0Zq+YbY8Hu4TjSMiuyUS7CpbMq9o4moek61i3pzP9O9bgE1keYYOtUxi27ZtWacWsKt1XG8X3TCbc2C0zJTK6mfFugcByTDm/TbDV2NRXYMUk02XGrajp2DEYBFARcon3YM5LAtXe9iBseeLnVTSHmKENTaQS9Ijps5sPzwj5wmDtRCcxhu6gngEU9gUNSuLXWPSiF540dfk5HJaTkXNX5ZGfAiNyjYp2thYRbwrUk5RwEnitzUFaCOdbUGbiuGLquI5rKVnTcsomb1cnGhLWZFyfjDmnHLXM+Lez2F7bbz0D8Y8KsXXEyAMgos3+M2Vb1rrzgH/AKkAQeU8msKdxWctyyokhyhXbH0wrCfqkmxymrCDrVYEVQVa3suA37JYR8kinENxNWUGi5g4XJpN4+5MbHMHD1x5B6bmPdvx+02YJcCyw32EnH7exFJRjftZMZt2osCl2tb5HFk++TMxlHx2IZ+CTB3BZdCltA8Yh83e7u/rw7ZmhqGsdtLIPeSL6AYdADgeeciUrIlTtumfjcLtccXdeL8mUrsTIv3O4cits6btm/M9kcduUjFc45egGAQt5tJSYTrMikp+jvyQYXRth3UGvGbTgv3FbLuN07aoyNlaISjHFKKZp8xdNKTTs32O8DczcqIWgZB9iYkG6ycLtvNGH22W0HojQxbjM27Z4EAGzeM0nfHdEUhibTmN/lt70HkQQeXSGvI/cMbmBgPAVfvgjoou4ARqLpOVcMczrYd1nJUBDyiU0pTmZXmIwRDniQzWlUrLPFkHBLuJZkJge/R6x5sswEJbWBG6dEJgdV080JUil22XZMWKvVNVOKJB7aGbcHJ42LdGfQY7o2Z7Ldnk18yjJumXCbnf2LTTQvlLKIBI7j0Bn0GBm3sQw8Im8WLitlOsdtPK3U7JLqdMhxm1P1qs7QBV3+WYlKYA65FVUKk8U3PIjRH32v5okUJ3nQedE7wIkihr78OUT/cntdkzA7QaQWVE13VLQFrMWTmuu4HZoyRM9IhT5sxZqdVW1Vf+zn12Hf+9+D9NYXMPTVL0DLTD8ZkcTGohLmhb0VrzNM6PSI9S/M9UcM4baaEyanapiIy6bTVuA5zOvwORKVoKjtH5UQSynIafr0wm1+LNg1nDBzbK1ivN/iuGXRCCcd1oOwX6rBcZsvHpdvg1cSEPJJDTtu6824ZdeKahm3e0eT8Ih8xcWUoFdETtPN71/XdSTlXM07m9g1Z64VJ2OTYOvEdbaKk710wHDbzu/0I5FRZuUaSjjHpj0TAIDJZJbiEgjHUTUdo7EM5ldZIO+L+OZUVMKingA4jsOingB0YFYMIW5iLCajwy8V7VSzEprhDr9qZLJqxfcDCpF/0QYNQERjkHBLuJZUHZMJAOC5xh23zMlSSYhgTjbrFuSC47YB4bZN3E/N4OBkGgvyK8n9ER94jptRgSu2Ilsp41auIIA2k6lUFgLPIWSZDDLhdjSaQW/YV0UwqsFxW4NgBhRn6zaComoQq4iMC7sDGItlmr46vifvuF1h47jVczlosozUE48h/sB9iN9797Svl3jkH5B3vozAscdj4bd/AGnBQoxf/3OM//Kn0LXazs1SQaRWqhV8mykdPhEiz2Ei2fyM2/5OexdIKdbxsZK7VUunkXr6SUgLFiKzdQtSTz+Bke9/a9rvoJGohLGYXNHVYLTbaGutOz+sdHcY8QdDVYTbiYQMHTCLkgFG3m6joqCu60ZxsjaPShhPFMcUVCIc8GBehw+7huLmIp01KkESeIg8h5Scw+7hBHySgPldAazo78Du4UTVoqZsAaTbIh73dHgbzpBmY0WtMSkdNThu948msXResOJikBl1kJ/0pWQVqqbX7rjN/34tBd3aCbviZCw2odnFybblhdsLT1kKoCDkEu5H13W8sHfSnH9s2jPZ4hYRc42RaBqqptvm2zL6Ij5MxOW2n0vKioqRaBqL8iaeRT1G5M+hFpcwGstULbwc9ElmnRMn0HUd6WwOgSrFyczi2pRz21JIuCVcSyKjTFuYTMtkkHl5O3S94FprJOOWFZNiQlcpAa8AnyQUTaqzSn2umVI8giHcHopbrFRNx/BU2nTaigKPvohvRqurLAqhUsZtaxy3RuyGtagOC3gfjWYqxiQABaGrkgg63fZWXVWR2bEdBz//WXQO7TbaU8WpVQu5Khm3gBF3oQNVhSon2DUUR3fIi7BNpEn6+Wex933vgP+EkyD29WP8Vz+DvHtXxdfSMhmM/fSHGPnet6DrOjwLF2PhN38A3/qjEbv7L8hsfaGmNpUKIrUynYt5JnD5QlfNLE6maTqGpzKY31m5D1spKk5W4eYw9fQT0LMygmechc63vRPB15yF1JOPYfKW31Z9bXb8lDoX7TJZFYmMUrEwmdFuYzyZycIcy6yt5oQZjZYXR5sX9mEi0dgkzMxPLbkuCTwHnuPaxnFr5stO47gFgJXzQ9gzkjBFxdIFAp9HRCarYs9IAsv6QhB4DqvmdyCVzWE4WnnMMsXjUuG2wSiSeh230xUnS+c/x9IKMQlAIeqAFdxiOXmhGoVbVsSs2WLmbJOUc5AEvuj+gfWfZsdCbBuIoqfDi1cf0QeAhNt2Yt9YEpPJLM4+aj4AIy6BIJyEFSarVgR2RX8IOoAX2rz/HZxMQ4eRbwsAi/N/Hxg/dJzsuq7njT2V73lYTQ2ndANZ0aADVR23zCjUqAGIaAwSbgnXkszkiir82jH2i+sw+KmP4+DnPwvf2CAAQGtgIGPClp0gBBiCSFfIU5QdmTUnXzPNuM27xRosqtaOsJVk6w3Jgi4/Dk6k674gmY7bkguPJz8Ry7aiOFkyW+aKjQQkpLMqUtkc+qpsffJU2dIsKyqyOa2iI11XFBz4j39D9I4/Ib3pOQReeMpsTyOoWuWMW8Bw3ALNLVCmajr2jSXNTMtSks88CV3OwLfmCPR98hromo6Rb38VWtp+xT7x8APQkgmEL/gX0zkqhEKY/7kvo/8z/w3/UcfU1K5QiSBSKyzj1mm6Q96GMzirMZnMQlG1mvJtgeKM20o5Wol/bgB4HqHTXg2O49D7savgWb4S0dv/gNzEeNnz0y9sQnrTc5BYxm2dYiQT5OZVEQULUQkzu13q7/RjuErG7RgrQmFZxGH/Hm+gQJmZn1qyKMBxXFvt8pgwi8dNL9yumt8BRdWw46BR4Mlbck0OeAUcnExjIiGbbn0Wt1ItLmEiXu767Q55kJRzDS0IZit8R5XwSsbCcaUFuOkKkwHlBbeYCFzr7qagd45m3GZyZeOSmefbRJE6k1WxeziBIxZHsKDLj0jAYzpwCffD8m1fc2Q/lveFsGnPxCFpwiCaR6GAc+V7rTPWGQsHD70wNCttahYDZmGyYP7vmcfntSuxlAJF1YruCUsJ+USoml5xR2a9pPLxUlWLkwWdidwjGoOEW8KVsNy16Ry3vtVrAACZzc9j8U8/j/N23IdceuaiUSydd9xW2YJe6mQzhdsGohKA9tm66iRM4FvYFTB/tqArgFQ2VzXHzw4WmO4tEViYkNuK4mRTySy6StzbnZb/V1tRNSMebARnNtmutMAQu/duKPv2wrNiJcT5C8E99wQ4XZuVqASguTdZQ5MpyIpqW5hM13WkNz4NsX8BpMVL4Dt8DbovuRzK4ACmbv+j7fOjf/0L+EAQHWedW/QY7/UieNqrAQBaOoWhr30Roz/9IeIP/R3ZgQNl2/fNPMQ6J/mNRCXouo6J3/0f9l76Lhy4+mMY/tZXMXnLb6Gl0+YCU7Ut4I0wVMNkworPplCUFTWRQOrZZ+A/+lgInV0AAN7jQde73wddUTB1+x/Knj/0tS9i9Gc/gqgb30W9UQlMNO2psiWNnYd2xSd1XYeuVD+n+jt9SGSUikJXoXqwRbjNjwuNFBtRKjhuAUMobJfrzUQdjtsV/cZizr7RJHySULTTATD6INsNsCq/8MME3F1VCpSNx2V4RL5I3GRC8ngDrttsnY5bwHC9VHLcMuF2WRXhNlAivLL81lqjEkzhd44Jt0k5V+bQLj1WzWDHYAyarmPtogg4jsPaRWHsHIq3jSP+UGdzPt/26GVdOHpZF8bj8iElMhHNx7zXqrJIvrwvhJX9HfjHi8NtsyhrB3PWMqdtV9CDgEfEgUMoKoHd982rcl/KrsPxjDNxCWmbqKBSWNH2RotcE41Bwi3hSrI5DaqmT+u4Db/hAqz88z1Y+O1rkV28EqcceBri3eUCTa2YxaQqCGIA0BPyYiqZNSMZmLBWOvnSZBmxe++GGq9esVpqIJ+x3WEryQu7Czck7N+DdcYlVHLcesXKAmgzUVQNSTlXFrthFW77IpVvxJgALdtM4NjEvcNffn5o6RQmb70ZQlc3Ihe8GcFXnQ59agJL44MOOW6rFycDmltIYNdw5XxbZd8e5EZHEDjpFNM9G3nThfAdfSzE3r6y52c2Pw9l/150nHseeH/l7yL52COQX9mB+L13Y/Ta7+DAFR/Anne9BYP//WnTXcPyEOud5BtRCTNz3KaefAxTv78JEEWo0SkkH38Ek7f8FhM3/Ro9HV7kNN3cCu00bGt5rY5bFo8g8JytUKUM7IfQ0YHgq88s+nngpFPgO3I9+EBBjFIGB8AHAuh8y9uROzgI8dG/Gz+vcwxl2/CrOW7ZeWgn3E5c/wvsufitiD/094q/z45Ppa34o3lXbbFw68s/1oBwW8XN6RF50+3pdliefHeo8jWZsdJSrNBuAmKN6GBO2+W1OG4TMrpDxQXsCgUAG3BFVxDX5Z0vQ8tkkHz6CUz+4Zaix8J+CbEKjpe9o8ZnqCUqIZkfF8xryTSL5Gp0CmoyAa/EQ+C5po0rrSKZyZUV+2R5f82MhXjpwBQA4IglnQCAtYs7oagadg5Vv28kWo+u69i0ZxLL+0KIBD04ZkU3AMq5JZzloBmVEKj6vHOOmo9ERsEzr4zNRrOaAlv0YE5bVqDsUMq4rUW4LVzHnbk2pbP282crnUGKSnADtVd+IohZhG1NC/rsXSC6oiA3OQGprx+A4byd+Mg12PWVr+D45YfP+H3ZFoDpHLc6gMmEjHlhnzlBLo1KmLjxl4j97S6kNj6N+dd8vuix7N49yI2NInDCSVW3xM91WBEylnFr/ffgRApHLI7U/FpylhWJK801FLBqfCe04TCAZQ22uHbYxa2zmuO2ylaYwMBOXLbx1+AOSwJHvqXosZi5vbW8n0bvuA1aLIp5H/kYeJ8PodPPQPS2P+DYyR14JbV+xp9H0/RpoxLmhX0QeQ6DMyguVytmYbL+cnEi+fSTAIDAiSebP+MEAQu/9A3b15q6/Q8AxyH8xv9X9T07Xvt6hM55HXKjI5C3b4P88nbIe3aB43lTzAmaeYj1CRrT5QaP/e/PoCXiCL7qNfCtWw8haBGnTj4N3e97PzrOewOEYAhaNovYXXcgdPa56HrOiBYYj8sVndmNMDw5vXCrqyrSzz8L37qjzPPS7xFti5n51hyBpb/6LVDiZOY4Dgu++m3zd7R0CoOfvRqeVavR/+n/Quxvd4H76x/hW/m+uoXbsbxo2lPF+c6iVkrFZnnny4je9WdwogjPipXm54WlTwAW4XYqjZX95fEeo1Hm+i3OuLU+NhOq5ae2k+N2PG4cg65pipMBhmAp5TPj7SYgVqc3c+f6PSIWdgeqOm4n4rK5m4BhFiptQLhli7VW4VaTZQx9+X8gdHWD83gg79gG35q18B99LADDGTtUIXpj72gSAs+Zk147Qub2f+N6yZyz1TJuU88+g+FvfRWBk05B/9X/iaBXREqe/eihZpKSc2VjGc9zCHhEpJqYj799IAoOwOoFYQDA2vw9z7YDU3Xd/xCzz+BEChMJGa850piHHL3c2Cmyec8k3njC4lY2jZhDDE2m0RX0VBXVAOCso+bjf//+Mh56YQinrSk3KrQDB8ZTCHjEop2Ki3oCePlgDJmsOu0xmAuwugfVdmSGmiTcVnPcsnkERSW0ljnpuL3uuuuwfPly+Hw+nHLKKXjqqada3SSiTthgVCkqIfHoP7H/I5ch+cSj5s8EQcQf1l8E+cjjZ/y+bHt+uEJxMgDoyjt/mBMoq2jgADNnEQBSzzyF2N/uAgQRqaceL2qnMjyEgc/8B9LPPwsAphDWzttbZsrgRAocUFSkq+DarE/8Y87UUuFW3PQkLt50C5bd8A0ogwONNbgOCosAxX3J+v9KF2Zd1xG663dYEj2Ajj/+CtnBA0WPJ9LG+VGan5vduwdTt/8R4oKF6Dj3PACAZ+VhEPv6sXZ0G6INbOtlGczVREaB5zC/y9/UrYK7h+PgACyzcZVl9+wG5/PDv85eoFZGhou2tndf8gF0v/cySPMXTPu+HMdB6utH6DVnoufyD2Hhl76BBV/4GgBAjccQPvAygIIgUis5TS8aOwAgvWUztJSxZUw5sA+Jhx/A8Ne+gL0XvxX7Pvg+jHzvm9BVFRzPo/MtbzPFXN7jQedb3gaxq8vM42xWzi0TjyoVJ9NVFSM/+DaGvvw5DH/jy/DyxvlZbRcFJwjgpHIByRRtU0lM/u63UKNTCJ5yGnifD93vuQRcKo7T9z2GXJ3FycZryE8tOG4L/V7XNIz94qcAx2Hht66Fd7kh3MYf+jv2f+gSjF//C2S2vQhd19GfH9sq5dyOxTLoDnmLnLG9EW/+seZsw5fEdipOZhR4rBYnEv3bnRj41MeR3brZjFCxi+NgP+sOeYsW0Fb0hTAwnrI9JqqmYyqZLesjzKU97oTj1vLZ4vf9DerUJDrOeR36Pv5JcB4vRn7wHagJY8EqHJCQyChlRVh3DcWxcec4VvZ3VD1WlRy3douAgBG7M/SVz0PPpNH97vcZz/VLc8pxy6K5SqMSgHwRmCZ+1m0HYljWFzK/FybcUoEy98OctcfkBdvukBdLeoJUoIxwlJEHXbcAAQAASURBVKGpdE2RVAu6AjhycScefWmkJcWYnWBgPIVFPYGixW8Wm9BMQ4ibsKt7UErQjCxyNirB7r4p+fgjyLy0FSGfCIHnGt65STTGnBNuf//73+Oqq67C5z//eTz77LM45phjcN5552FkZKTVTSPqwHSB2Ai3uq4jeuft4CQPfOsLhYOE/GRF03TIr+yYkUgXSyngOQ6hKuJCT4cxmDKnjZxT4ZGEogtN7J67wAeCWPiN74IPR6AM5gunZTIY/vqXoGfS8B1zLABAgg7oets4oJxkcCKNeWFfkdi6YIYFrjKm47YwrGUP7Id6/Y+REb3g00kk/vlww22uFZYDVM1xWxqVkJuchK7r4DgO2mUfw11r3gBkZYx+71vQc4WV1ZgZlVA62dYhdHah94pPgBONPsxxHPo+8SlseMOVmErNfHVWzTshrcKtlslg7Fc/Q/TOP5s/Wxj24OBEumnZqrtHEljYHbBdee//5Gex5KfXg5PKF15SzzyF/R+5HPGHHzR/5l2xEp1veXtD7dF1HQe/8F8IXf89RDLRhh232b17MPTl/8HQ174EAFjwha9hyc9uQPdlH0TojLPBBQJIPPpPRO+4reJrapkMFjx1L/oSI5hoQKyvxtBUGl5JKOvfjPSm55D858MQunuQfn4j8JufAroOf4k4oisKRn/8fYz+6HvITUxUfL/svr3Y98FLEP3LbZAWLjIXJkJnngNhyQqcfOAZ6MnK293tGGcZtx31ZdwmNjwIefuLCL/h/8Gbd9taif7lNgz+51UY+sI16BOMm9yRKfvxbCwml4mCPR0+8BzXmOM2L2JLIg8tk8HkLb9Fdu8e42dt5Lg1YgqqO8aze/dAfnk7hr7yeRynGsVZ7MaHgFcEdL3Mrb+iP2QUPRwt7z8TCRk6yjN2zaiEBs4vc7ExL65r2SymbrsVQmcXOl7/BkgLF6Hngx+FOjGG0R9/D7qSRYffOBYJS85tPK3g87c8D1XV8O8XHFH2PsrBQYz9/MfIvLS1rLhYokLsjq6qGP/1rzD20x9C7O3D4uv+F9KChcZnR3ZOFSerFs0V8IpNK042kZAxHE1j7aKCszbsl7CoO0AFytqATbuN69VReeEWAI5Z0YXhaNrMJSWIRshkVUwk5Kr5tlbOPmo+MoqKJ3eMNrllzpPJqhiNZcp2jLD/HypxCXZ1D0ph2ohTWfPMcVsq3MYf+juGv/kVDP7Xp5F8ZAMiAU/d9WcIZ5lzwu33vvc9fPCDH8Rll12GI488Ej/72c8QCARw/fXXt7ppRB0w8cPOti9vfwnZnS8jdNY5EEKFCRirzK6PDmHgUx/H+A2/rPt9o6ksOvxSWVGT3OQkks88CTUeMyeRbMKWzWllrqb+z3wOC77yLfhWr8HSn9+Azre8DbquY+wn1yK7Zxe63vVeBE88BbqSxerbr8Prdj4AJXboZZodnEybDltGh09E0Cva5qTqigIta7/aZ2bc5gUWLZ3G8De+DChZ3HrUW/HcOz6Jzre/2+FPUJmpfP9guUAAIO/aicDfbwcABD0CMrf+Gtm9u6Fls5i89WbDRf7IBgCANH8Bnl10PMZPOx/yKzsw+fubzNeJVxBuPctWYMmPfwH/+qOLfu47cj28fb1IZJQZZymbQpDAQVdVpJ59Bgf+498Qu/PPSD79BHRdR/zB+/HGe36IQHKyISdaJbI5DQPjKduYBIbY1WX7c9+R68D7/Yje/gcMfeXzSD71hCNt4jgO3RdfAk5O48KX7kQqXd9qdE7VIQgFR+nQN74EXVHQ/Z5LzOdI8xeg88KL0HfVZ7Dk2p9hxa13IPKvb634msrAfoT+divO2fVwU74HwIhK6O/02cYeAEDg+BPRf80XsOSn1yNw0qlQH9uAs3c9bOZGAoZT+eAXrkH87/ciNzkJoaM8SoAhLVoMobMTAND93svACcZ5zgkCAh/6GH5x4uXISH6jYFiNVb3H4jLCfgkekYeuKObvpZ7biN1vvxB7L38PPN++Bu/cfCtWvfCw4djWdcTuuRt8OIKud7236PXC556HJb/4NRZ++1qEzn4d0pueQ+4rn0FPcsx2e7uq6RiLZ8qcFQLPoTvkdaQ4WXBsEAOf+jiid/4Zwrx5AAAfcsi1gXCr6zom4nJZ8bjMthcx9I0vQ8sYx6f7PZdhwVe+BfA8Tr7nl1gcPWD2MzUeR+Kxf2L0Zz/CGbd8FZ/9x7dx1ot/Q26sMLFlERZ2ObdsgbbHA0z+8Rbs/cB7MfTVL6Bj4iCABh23JVEJ8fvvgTo5gchb3gbeawjDHa99PYKveg1STzyGwf/+T4R9Rr9ni3eapuObt72AwYkUPvqGtTgyn5XKSPzzYRy46krE/nYXBj/3n/ClYwAKcVSm47bkWjLy/W8hevsf4F1zBBZ96/vwLDK2fo/++Pu48IEfQ04kZ/y53Ua1aK4lqRG86y9fw9Rfbpu2EGG9MHF2bUkkwtrFEQxMpMzvmHAfuq5j895JLJ0XNHe3AEaRMgDYtKfyIiRB1IKWzWJw204AtReBPWNdPzgAD75wsIktmxm6riP13Eakt2y2fZw5aheXCrfdRn2DQ0W4HYvJCHrFqrEFTkclpEzhtvg9AyeditDZ50Lo7MLI976Jk4eeI8dti5lTGbfZbBYbN27EZz/7WfNnPM/j3HPPxeOPP97ClrmTXcNxxLduBZTym0N9wRKgIwxoGrhXXrL9fX3ZYYDXC2TS4PbtKn8Cx0FffaTx79gUuCEbB6zXB33ZKuPfo0PgJo1cxr0HY1g5sQ/d29PIhGLwHbEOADD5h1uQeNgoBBN504VFL8WE21dyAcxbdyIyjz2GketvArq6AV6AdtQJAMcB8Si4wf3lbfF4MRKVEQlIUA4OQhkegnJwAMlH/4nMi1sATUPkzW9F9+vfDk7XcPDxp7FpbDf8u3fjqOgkxm/cheye3Zj/X18AJ0nwrjQ+F+83LkJTf/w9Ev94CIGTTkXn295lHENFgajIOG3fJiSveB+2LlsO7bAjoPfOh3bm+Ua7JsfBjbCLsEWQ8AehLzXcXtzQAJA/dkXP6eyBvsCYcHF7dwKp/MTUImzo8xcB3b3Gc7a9AKjGhYCzPEdbfhgQCgO5HPiXni8/dgC0tccAkgQkYuB37Sh/H1GEvu444z9jw1D37MLifa/gGE8Pko9noes6hHAE/vVHY2F3APq2F7D5xlcAtg18y7PgtzyL3FveC+1V5xg/e/wh6N29AMchtn0UyydHIe2MQO8/EVo6Dd7nQ+fFl2LPC52YJ80ztrapOQh3/A4QBOjz+qF39QC8APA89MONfoapCfv+6g8U+uvIQbO/FhHphD5/MV46EEV/fBidAy8jrQ0ju2c3Jn7zK6iqhu6V78Fyj4Ton/+E6B23Q+jshDo+BmnhIghhYxLHnMPPrjsX/QdfRuqVfdi3axyITmJy42YsnxxFYE8E6Sk/Ev94GKEzz4Z//dG2W80BYJ6extm7HsbTf+GLbwgiXdAXLjW+8wN7gER+AcHU4zjovf2I+zshqVkc9o8/Yd9tL0GdmgTn8aD70g8i8v/ebLiEEwmEp4bw/tEbsO07L2No2RKjL685yhgrZBncnh1GFzX7hvG3vvZo4/yMTRntKBXfPF4cnLcCqqZjjZg0hFddhzo5gdzoCDLbXzKyaM96ra2YyAeCCL/x/2HqD7+DMjgAaekyBE8+1fZY1Uvg+BPhO/cNWP7H25G+4Vt4YfMxUM84D+ieN+34mMmqWDSyC8PfvB/prS9Ai0XR8/6PwLf2yIrvx0TLSnhXrYb3lFfh8PsexJ77/orNo4dB74hAX7XG+P3hQWBqwjjeVjq7ofcZsRHcvl1AxmbxpG8B0NmN4Wga5wSiSL+wydgxcHAQma0vIPPSViz6zg8hRDrN49t39X8i942v4JWJ5ejzCsju24v0pucQvfsvyB0cRPhNF6Ln8g9V/VycIKD3369GZusLCJx6etFjvsNWYzw4gIMTKbxwx33gH/071LPfCAiFfq539wLzjNw3bvfLgJKFtONlnJUewcEvPojMi1uw6NvXwrN0GbwrVsK7Zi30dBr88CgOGx9E+LHdGNj9KJbdcDMWfPkbUPbvK1o4NNvJcfCtXgPfx9fAd+Q6RP/8J3i6urF3NIFN9z8KLpWE7vUCHI+UnMOS8d1YDGNioqsq4vf9DZmXtuIDG56AkExg6wuHQ1u8HOpr/5/RfjljtJ/nS9+46Ho7sGUHTt33JJZtfByKV0D3xe8zr0WnbLobnfu2YUv0QeiLlhrfqShCW7SscC3YvgXQVACc0U84AOCgL10B+IOAooDbvcP2u9JXrTGOfTIBbmBv+RME0eyLmBgDNzZc/pxAEHL/EmQUFYuVSaRf2AQ9l0P8vr8h+fgjAC8g89JWBI47AUIoBP/6o7Hgf76M9DWfwXufvxlPnmCM5cknH8PYj79vvK0QwqQvgrWbNmDi/7zo+49PQ1eyWPSnn+Gyjduh7uvCC0cdDn3BEuhd86CvPBwvDaexeuxlHPmLX2JSSUCIdCL19BNIPfMkjltwHvaNRvD81v3F5zg7rXih8J0UXcfzP9o1jv54HJLIQ9c0xB+8H0JnF8Kvf2NRf+q76jOYWrrMcOIGvZDULLbd8TdMdgexbTCBsa3DeMfqPrzeOwZdXQROEKBGpzB+46+QeMh4ze4P/Rt0VQU/3zgHxEf+js2jz0PbncaKCRnSjnlIcYB35SoIkU6Ez38TxL4+dL3zveA9BcezZ+VhCCX/gnOfvx2bfp8F5/cbx2rxcqO9Bw8A8XK3qN7VA/TON56zdycgly9K6PMXAeFO4zkvv1h+DQCMex6fH8jK4Pa8Ut5vAOir1gKCACRi9vd6ogh9Jet/o4jtPYDlk3sw/0ASicfGoCWTkBYugn/dUZD7FyMqhTD4859h4A9/hPqGi6D39AGhMPSFS4y2Du4HErHydtiMOVa27BiFTxFwxOIItFQSoz/5IXRZxjmDk1i8dxybr3kQkaWLoZ7zJuO4JBPgX34REHjovGDet4DnC/1saqKsnwEAfH7zfhEjB8FN2QiL4U7jO0D+XsBmB4Pe218YI3ZuB3Il8wdNM94nGAJUFfw/7gP8AePeydKP9MOONO4XU8npz50aPhM3sBfc8EFAThv3sF4/4PVBW7gEmGdk0Iq//RkQnwKCHdBDHcbfwQ5oh68D2HXPHPdg9L98H9RXHm6Me7IMfttmJDMKul/eiVMP70HiMWOXVPC0V+Po5d1YNb4T6R/91RhL+hdA75pnfE+W+Q63Yyv4V14yxm1fAAgEAI8Xek9f4TPt22V8BzxfdK3W5/UVvoNd24FcuXijL1oKBDsAVQW3c1v5sQOgLz8M8HiBdArc/t3lT7BeU6KTxn1DKdY5XMV+FYE+Pz8PObAHSJUv+rjqM1n71d6d4EaHjPGEzRMEwZhbsfN/pp9J14xxM9gBpJMQHrwb3PiI8WdsBIhOIptT4Tnh41jQFYAyOIDEIxvAB4LQs1noOQV6NguhuweRfJ2G0OAuXKjtwouP78bGSBQiMyFFugvn9t6dlvZa5mj9C4uv//m5YNE8bvlhRntzOfDbLAKsdb649ujCXJDdI0SnIGy4B9zBA9BXrIZy9ZcBAMJ9fzbGSQB7R+I4amgQq/bHoaUXg/f7oSYS6N33IlZO7MLQE5PYlNxnvF7p+DBsM1/z1T5fA+r4HhWlcNzYX4uXGXNkVQW3Y0vRceEUBcjK0I45yeibqST4nduM8VDTDJ1F06DzPPR1x2FgPIWVfMLYHaip0NJp5MbHoI6PgQ8EMO/DVyLok9CbHEX0Hw9j805jXALPGZ95weLC9Xia+3jAuNaO7hrH8skhBPYGkM4OQldVBI49HkIohL6PfxLK8BAOfv4avOa5OzCVyuH53cb9FbfnFSBbvnhtaki6blzLbTA1JDlj9EmbNh52xLKKMU6HKnNKuB0bG4Oqqujv7y/6eX9/P7Ztsx/kZVmGLBc6XSxWfvM1V7n+7y/jhBu/hu70VNljvz/qrdjeuwaClsN/PfxN29//8akfxUSgG/PjQ/jQ078qe1zleXz1LENEP2roBfzri38pe85QqB+/OPkDAIDX7nwQp+81BPZ5AN4DoGu3F7GRc03hVn55O5ShIYTOPheepcWFppjF/3f/3I17M0fi32L/BH/9z83Hv3T2NQDH4cjhF/HWrbeXtWU0OA9Dp3wYx63oRvyhv2Pq1psBAJwkIXDSqfAduQ6BE06GEPGB03Ucdsv3MQXgdTBciNG9fnAeL3KjI5AWLip6bV3JIv73eyHOX4jeT3wSXH7SzQeCGL/80/jH9bdixeQeLHt5H4JbtyMl+fGdXT0AgBMPPIM37ri3rL17O5fg18cbmXNv2HEPTjqwsew5zyw6HneveQMA4JJn/w/LpvaVPedvh78eTy8+CQBw9SPfRzBbvqr5m+Muxp6u5fBnU/jUI98vexwAvvvqTyDpCWLZ5F5c8txvyx5PS358+zVXFX2mtwOI7JYw/IgxMPvWHQX/V7+NJfOC8D+0CZOPPVf0GoPhBXj0nwfw0van0Zmewr8/fp352Nr8H3XvbdBu+gPE7m4s/Pp3ofECpBcfwDOvjOGZV8Zw0oGn8YYd95W1TxY8+OaZnwIAHDf4HP7ftrvLnnMgsgjXn3ApAOD1L9+PU/eX52c/t+AY3HnEBQCAi3c+AO+PhnAw76gUe/sw/5PXQP7jAHwrurHwHfkt4qOjhgD6pn8xhVd2sfrb5mE80P0mZFUvcOMzOH7gWVyw/W9YC0DZdzsO5u/LtHSqzGlrZc2L/4C451Fkv/sorNPHF+avx+1HGosg79z8exw+Vj4ZfmDV2Xh02asAXkLv3i3g5oXQ+fo3oOOc1xXlw0b+5V+Ry0gQf3IttIfuBbuF/+nJH8RoqA+9yVF89Mlf2LbPPD9HXsJbt5THAIwFe/CTUz4CAFg98AKGb7qj7Dl8KISOs8+teAwib/oXRP9yO6QFC9H9rvdUfN5MmHfZB/DQQ5uwbN8rmNizAz8emFd1fNQ4Hl852xgfI2ICyWceg2fFKoTe/FaEL7iw7Pn10ve+y7Dv/oew/MFbMfkgsLdzKX59vOEQfeP2v+HEgWfLfufpxSfgb4cbC0aXPvsbLJ0qFz3+uuZ8bFx0AgDgjA2/xsFHiifu0pJlyI2PQ4h0mj/jfT4s/J8vY/SrD+DwoAfpFzZh/Fc/A3gePR+6wpx0TIdvzRHwrSnfCu73COA5Do9uG4Fv54M4fe+TwONPFj1nw4rXYMOKMwAA//bkzzAvOY4L8r+b7g7Bt/YIaHkxSejswsIvG9e90WgGH//WA/jI0gxWrwoZObyCAO+qw6Ztb/h156Pj7HMx79fP4oW9k3j6/luwerz4BvV9AJSl7wJwOjhBwOQfbzEWcTwR7EMflC074Hv+Bfx4bDEmAt3ojw/jw0//b9l7aRyHr5x9DQBg/fAWvGXrHXg9ACxdhIWf/zx8a9YCMFwvfCCAnAaMPfQQrNL9XWvfiGcXGotrn/nHt+HNlTsrrj/hEhyILEaHHMN/PPoj28/9rddcjYzkw6rxnbh40y1lj8e9IXz/9I8DAE7Z/xTOe/n+sufs6l6B3x5r7JA4Yts/cfDOwvcZOPVV6H7f5fAsLC4A5DtiHXr/60sY+OSn0SUZblb/0cdi3kf/Hf6jj8VTL2fwy/t34Odn+tF5RH5CJ0rgX3we8zIZSLuGMPFKYdJ17WlXIOrvxEJPEJLAoefSf0P49W9Adt8eTP3x94iL6/DKQBQ//Nnmmq95VlYAOL9zKYLefwXH8/AdsQ6epcvA+4odxpwoouudxnjVs2kQgWwKnhuuwySAfgDvEzn0DfgxtAFY/rvbwfn9kF/egcRD98N/7Ano/fgnzZ0ImqbDI/KY/9g9mNwQw/EATuSA0S/9GQAw/7+/hMCJJ8O//mjb60n4/Dch9oe7ccTLWzH1I+O+ese8w3DL0e8AAPzri3fgqKEtZb/36LLT8MAqY8H1g0//CgviQ2XP+fOR/4LN848CAFzz8DcgMgHNwi9PuhwHOxagKzWBjz3x07LHAeBrZ34GOUHE4WM78M7Nfyh7fNLfiR+ddgUA4PS9j+G1Ox/C+wB07pAwco9x3fUevhaLvvUDREJe/O9xl+DkA0/j1Xsfhe8n1wIAXuxbiz+uvwgA8LYtf8IRI+VzDLsxx8oaAGuOexuW94XAQUfysUcAjkMnJ6AvmYb69D5MPA18b2gBEt4OLI4ewOUbf132Pk25d3n+ZqyaKBe+7jvstXhiqbEg9x+P/hAdcvlOsZuOeSd29qyCX0nhU//8ednjAPC90z+OhDeEJVP7cdmzvyl7PCN68a0zPgkAOGHgWbxp+9/KnrM/shg3nGDsTDl/x704+cAzZc+xXtPeuXknVk7sKutXdxxxATYtMGLXKva7Ey/DwfDCon73dgA9e70Y+Ycx91h+y5/RG/FhXsSPzs2bMLHj+aLXqDTfsbJpwVG444h/AQC8e9MtOGy8XND4+6pz8Niy0wAAH3/sR4hkyuetNx/9Drwy7zBIahaf3fDtsscBy/gWG8AHnrmx7HFFkPD1Mz8NADjm4CZc+NJdZc8ZDC/A/554OQDg3FcewKv2le9karfPNBBeiF+deBkA4HWv/B2n7Xuy7DnPLzgafzni/1X9TPcfdg4eX1r9M7FzRcpl8dl/GLvqUpIfU/5OTPpWYLKzC7yuY3FPAMmnH8LkzeXninf1GvMeKrHhQZz5zJ9xdCKLhOUWb1bngqd/HElvqGwumBUkbFx4HJ4KnIzoDU8jnIni44/daN6DhAH8K4C+QR/UN74GvN8PZWA/4t/5Et43kYL2PDCVv+23fo/HDj6Pf9n217J21P89/g6HjZebLGr5Hm8+5h14pecweHIy/vMf37E9Lte+6kpEfZGaxvEz9QGM/qBcMwmc8ioAQFfQg1P2P4WlTz6P0kTtJ5echHtXvx4AcPnGG7E4Wi5q37n2jXiO3ett+DaWqVm8D4B3tw8H8zuA+j71Xwid/hoAgNQ/Hwu/9h3s+sjHIKWiuPqGpwEAVzzxU/Skyhdrbl1/Ebb1rQWna/jcQ1+3PR7XnfJhjAfnoS8xjI88VX5Pe+faN+Gy//kw1i3ttP39QxVOr3VPYRswODiIRYsW4bHHHsNpp51m/vzTn/40NmzYgCefLD9pv/CFL+CLX/xi2c+j0SjC4XBT29tqntwxiviGB8HL5asx6dVHIdfVC2gqOp7ZYPv7iaNPhe4LgE/GENxafsMEcIiffDYAQBo7CN+ucueuFgghud6oAO/dvxOegwV3jk8SsP6IJfAuWmxOknVFAUT7quSqpuPhFw4ikd/25hncA3FiFJymArqO5DFGnxDHh+HfuRVA8Wto/iCSR52M41f2oG9qAPIrL4MPhxE47gTTqWQeu21DSP79HvP/i5f0Y/kJ6yEtWFjRNaYMDoCPRIqqwgNAOpvDw1uGkc0Z7RQnRsBnUsguWmEcu+EB+PaWO5vUjk6kjjAGXu/eHfCMWFaO88cn27sA8rLDAQD+7ZsgJKJlz5EXr4TSZwjNwc1PgCtyUBjPSa9eD7WjE5ySRXDr0yUtMZ6TXHcidMkDIRGFb2f5CpsuSkitOxGA8R14B3ZD5HmsW9oJf94BKnR2wX/UMRiJpvHME9sgTI2ATyXBK1mkl6+B2tlTeMGcAv+ulyBOjZltCPslHL4wjNBrX1/kEtq0ewJ7LPmFnJKFGB2HODEKIT5lrHYKAhLH5y9So4Pw7dlefsyDYaSONEQr775X4BkqF7aU3gXIrDBEkv69W3FEKO9gFiUET3s1hFAIOwZjiAQk9Hf6oasq9FzO3Bpr5dGXRjAWL3YmGf1hOzoDHqxaYGzx5X0BBE9/TdFnLiU6NoXnbvsbVFUtclMrPX3IrDDEMP+OzRCj+cml5cogL16J7MJlEDgOr1roQdfCvopb5FVNx0ObBpAZH4c0MQJxYhSptcdCC4TAp5MIbmETxvzv518nfsIZAMdBnBwtjBWW99B8AaSOPAF+j4BXd6Sh7tsDABAinRB7+yD29pUJHnYogwPgO8JVt+XPlKdfGcPgWBzS+AiUnj6AF2oaH09cEsL8sKdsbGiU5x58CuO79wKaBi0YRvowYwHMt2c7pJHymzmlbxEyyw0nWuDFjcXjRZ7MsjVQ+heB5zicMLwZQSGffdzVDd8R64oE21K2DUTRE/KiGxlk9+6B0NlVtgA3U55+Zcwsiuc9sAuewT1Fj8uLVphjanDzE+AzxnMPO2o1Fp9yQtW+s2n3BFbO77DJlK6N/WNJPLtrHN69OyBNjoHLFs5pgedwzNmnovMI47jLO1+G2NuHMc2DJ3eMQdc1CNEJqOEugOfz/Wkjik5QANb+xK5xoseLk97+Jvg7i+9lBsaTeGbnOLhsBp7hAYgTI+B0DZnFq5CbZ7giQ88/Ci6XK3KdATpSRxxvXAuyGYSef8z288aPfw0gShCi4whs31T2uC55kDju1QAAz9A+ePeVLxap4S6k1h4HkedxCoYhjRrXN+/K1aYIXYmtrwxj/rwgejqLz6dERsGOgRiOX9VT9HM9l8PWwTh2Dk5BnByDZ2QAQjyav8fxI+QVcebaHoglY/QrB2PYun8KQmwSge3Pl39OQULieONzVrqO+7s7ceq7/sXYsZDNVh3DASMSaMOze8FvfRZQVQgAjlgYQsAjALkcOl53PjhRhDIyDPmVHQieerq5UMzYtHsCA1u2Q0hMQUjEsMAPLJkXAnge/mOPh9TXb//meUYn4njunkfAZdPgs1mowQ6kVxuCq2/ni5DGyx3U2QVLIS8xxPLAlqchpMrdnJmVa6HMMxYCO55+yNZxmzzyRGihMLhMCqHN9nE38RPPBHgB4uQY/C+Xb8vVvH7zftAzuAfeA7sg8ByOXNEHf9AHzuOF97DVEOf1YiSaxhPbx6BDB59KIPDSs+DUHHLdfUgfZhTB9L+yBeJEeR2NSmOOlb4Tj8f6Uw2BXFdVcIIAXdfxzxeHMRlNQoxOGPfi+XPf/8pWcHrepaWqgK4BvGB8ZgDSyEDle5f8/Zd338vwDB0oe47SO79wL7D9eYjR8iJb8tJVyM43duiEnn8UnE10Verwo417NTUH3/6d4DMpcHKm6N4yedQp0D1eCIkoAi+xBXqLs08QC/dj5rmjw3rfroYK92Oegd2QJkahebyAIIDLyuCzMtRQ2PyejBfWwSlZ8KkEhFQcQiqBbN8iY3wFENr4D3CaZjgzOc68B0mtORZasAOcnEZg2/PGcZR4HL28B4IgAByHwEmngPd6sWsojhd2j0KaGIU0PgQhNgVAL5rvCNFx8Jk0OF0Dn06Bl9PgsjJyXb3meeJ/+QXj/rbkPJAXr0J24bL8d/BY0fWk8B0ck/8OVHRsrDSHOw26z298By+WGz/A8YifdJbxHYwehG93+RyuuF+9As9QuSCo9MxHZpXhjjT6VbnQ46bPZP2epOEBSGMHjT6hqcZ8UtOQ6+4z7/Nr+0yPgrNxJqZXH41c17z8ex1ALtID3VccixDyijj7qAXgVAXyzleMcULygPNI4D1ecD4/xG7DPakMDiC9by82PbezqOC10rewcG+37TkI8fK5YGbJYVD683PBTY8XzwXzz0kfth5quMuYC76Qv5e3TgU4Dsl1J5XPBQUB6VXroPmDRZ9NGh2EZ+gA9LyrPOj34OglEQSOPxG8zwd1ahLJZ57CgZEYhizFyXReQOKEM/KvcRC+3eULZ2qoA6kjrX3Tbr5Ww5i3ZBWyC9iY91j598gBqdVHF/rmc48YbcwfM12UoEsS0ocdZY55/h0vGMeX4/KfnYcuikgebSyKHR/R0D05CAg8eK8Pwrx5ELvnFd2nPnnXw4iPjEGTvHn3rg5eTiPXOc/sd4Gtz0BIlgvNmeVrzHl/xzMbAE1F0Csaeetc8XzVyvBoFM9s2otcfmdMxX592HrkuvsATUPHMw+XPQ4Y1wDNHwSfjNvoCkBmxVqceuZxRVE0c5VYLIZIJFKT9jinhNtsNotAIIA//vGPePOb32z+/JJLLsHU1BTuuKPcoWXnuF2yZMkhIdwSBEEQBEEQBEEQBEEQBDF71CPczqniZB6PByeccAIeeOAB82eapuGBBx4ocuBa8Xq9CIfDRX8IgiAIgiAIgiAIgiAIgiBayZzKuAWAq666CpdccglOPPFEnHzyyfjBD36AZDKJyy67rNVNIwiCIAiCIAiCIAiCIAiCqIk5J9y+4x3vwOjoKP7nf/4HQ0NDOPbYY3HPPfeUFSwjCIIgCIIgCIIgCIIgCIJwK3Mq49YJ6smZIAiCIAiCIAiCIAiCIAiCqJVDNuOWIAiCIAiCIAiCIAiCIAhiLkDCLUEQBEEQBEEQBEEQBEEQhMsg4ZYgCIIgCIIgCIIgCIIgCMJlkHBLEARBEARBEARBEARBEAThMki4JQiCIAiCIAiCIAiCIAiCcBkk3BIEQRAEQRAEQRAEQRAEQbgMEm4JgiAIgiAIgiAIgiAIgiBcBgm3BEEQBEEQBEEQBEEQBEEQLoOEW4IgCIIgCIIgCIIgCIIgCJdBwi1BEARBEARBEARBEARBEITLEFvdALeh6zoAIBaLtbglBEEQBEEQBEEQBEEQBEHMJZjmyDTIapBwW0I8HgcALFmypMUtIQiCIAiCIAiCIAiCIAhiLhKPxxGJRKo+h9NrkXcPITRNw+DgIDo6OsBxXKubQxyCxGIxLFmyBPv370c4HG51cwjCNdC5QRB0HhBENej8IAh76NwgiNqgc4WYLXRdRzwex8KFC8Hz1VNsyXFbAs/zWLx4caubQRAIh8N0sSAIG+jcIAg6DwiiGnR+EIQ9dG4QRG3QuULMBtM5bRlUnIwgCIIgCIIgCIIgCIIgCMJlkHBLEARBEARBEARBEARBEAThMki4JQiX4fV68fnPfx5er7fVTSEIV0HnBkHQeUAQ1aDzgyDsoXODIGqDzhXCjVBxMoIgCIIgCIIgCIIgCIIgCJdBjluCIAiCIAiCIAiCIAiCIAiXQcItQRAEQRAEQRAEQRAEQRCEyyDhliAIgiAIgiAIgiAIgiAIwmWQcEsQBEEQBEEQBEEQBEEQBOEySLglCIIgCIIgCIIgCIIgCIJwGSTcEgRBEARBEARBEARBEARBuAwSbgmCIAiCIAiCIAiCIAiCIFwGCbcEQRAEQRAEQRAEQRAEQRAug4RbgiAIgiAIgiAIgiAIgiAIl0HCLUEQBEEQBEEQBEEQBEEQhMsg4ZYgCIIgCIIgCIIgCIIgCMJlkHBLEARBEARBEARBEARBEAThMki4JQiCIAiCIAiCIAiCIAiCcBkk3BIEQRAEQRAEQRAEQRAEQbgMEm4JgiAIgiAIgiAIgiAIgiBchtjqBtTK17/+ddx2223Ytm0b/H4/XvWqV+Gb3/wm1qxZYz4nk8ng6quvxi233AJZlnHeeefhJz/5Cfr7+2t+H03TMDg4iI6ODnAc14yPQhAEQRAEQRAEQRAEQRDEIYiu64jH41i4cCF4vrqnltN1XZ+ldjXE+eefj3e+85046aSTkMvlcM0112DLli148cUXEQwGAQAf/ehH8de//hU33ngjIpEIrrzySvA8j0cffbTm9zlw4ACWLFnSrI9BEARBEARBEARBEARBEMQhzv79+7F48eKqz2kb4baU0dFR9PX1YcOGDTjjjDMQjUbR29uLm2++GW9961sBANu2bcMRRxyBxx9/HKeeempNrxuNRtHZ2Yn9+/cjHA438yMQBEEQBEEQBEEQBEEQBHEIEYvFsGTJEkxNTSESiVR9bttEJZQSjUYBAN3d3QCAjRs3QlEUnHvuueZz1q5di6VLl1YVbmVZhizL5v/j8TgAIBwOk3BLEARBEARBEARBEARBEITj1BLR2pbFyTRNwyc+8QmcfvrpWL9+PQBgaGgIHo8HnZ2dRc/t7+/H0NBQxdf6+te/jkgkYv6hmASCIAiCIAiCIAiCIAiCIFpNWwq3V1xxBbZs2YJbbrml4df67Gc/i2g0av7Zv3+/Ay0kCIIgCIIgCIIgCIIgCIKYOW0XlXDllVfirrvuwj/+8Y+iAN/58+cjm81iamqqyHU7PDyM+fPnV3w9r9cLr9db8/urqgpFUWbUdoKYi0iSBEEQWt0MgiAIgiAIgiAIgiCIOUXbCLe6ruNjH/sYbr/9djz88MNYsWJF0eMnnHACJEnCAw88gIsuuggAsH37duzbtw+nnXaaI21IJBI4cOAA2rSeG0E0BY7jsHjxYoRCoVY3hSAIgiAIgiAIgiAIYs7QNsLtFVdcgZtvvhl33HEHOjo6zNzaSCQCv9+PSCSC97///bjqqqvQ3d2NcDiMj33sYzjttNMqFiarB1VVceDAAQQCAfT29tYUIEwQcx1d1zE6OooDBw5g9erV5LwlCIIgCIIgCIIgCIJwiLYRbn/6058CAM4666yin99www249NJLAQDf//73wfM8LrroIsiyjPPOOw8/+clPHHl/RVGg6zp6e3vh9/sdeU2CmAv09vZiz549UBSFhFuCIAiCIAiCIAiCIAiHaBvhtpZ4Ap/Ph+uuuw7XXXdd09pBTluCKIbOCYIgCIIgCIIgCIIgCOfhW90AgiAIgiAIgiAIgiAIgiAIohgSbgmiicRiMaxatQqjo6MNv9ZNN92Eiy++2IFWEQRBEARBEARBEARBEG6HhNs5xllnnQWv14uOjg5EIhGsX78eV199tSPCIYPjOASDQcRisaKfv+lNbwLHcfjzn/9c0+tceuml+MQnPlHx8XXr1iEUCiEUCkGSJHg8HvP/69ata+ATzB7f/e538eY3vxm9vb0AAFmW8fa3vx39/f3493//96LnqqqK7373u1i/fj2CwSAWLFiA888/Hw888AAA4F3veheeeuopPPfcc7P+OQiCIAiCIAiCIAiCIIjZhYTbOcg3v/lNxONxTE1N4dZbb8XAwABOOOEEDA8PO/YeS5Yswe9//3vz/wcPHsSTTz6J/v5+x95j69atSCQSSCQSuPjii/Fv//Zv5v+3bt3q2Ps0i1wuh1/84he47LLLzJ/93//9H4466igMDAwgnU7jwQcfNB+7+OKLcf311+O6667DxMQE9u7diyuvvBJ/+tOfAAA8z+Piiy92rOAeQRAEQRAEQRAEQRAE4V5IuJ3DcByHI488Er/97W8RDofx3e9+FwCQSCRw4YUXoq+vD5FIBGeccQY2bdoEABgdHYXP58Pu3bvN18lkMujq6sKTTz5p/uyyyy7DDTfcYP7/N7/5Dd7+9rfD5/MVteHvf/87Tj75ZHR2dmLdunX4y1/+AgD44Q9/iJtuugk/+clPGnLQchyHH//4xzjyyCMRDAbx3ve+F5OTk3jHO96BcDiM4447Dtu2bTOfn0gkcOWVV2Lp0qXo6+vD+973PkSjUfPx97znPVi4cCHC4TBOOOEEPPTQQ+ZjN954I4499lh8+ctfRl9fH/r7+/GDH/ygYtueeuopqKqK9evXmz9TVdX8o2kaVFUFAGzYsAG33347/vKXv+DMM8+E1+uFx+PBBRdcUCTUvva1r8Wdd945o2NFEARBEARBEARBEARBtA8k3B4CiKKIN7/5zdiwYQMAQNM0vPvd78bu3bsxPDyM4447Dm9/+9uh6zp6e3txwQUX4Ne//rX5+7fffjsWLlyIU045xfzZ6173Ouzfv98URW+44YYiZykAbN68GW9729vwjW98AxMTE/j5z3+O9773vdi+fTv+/d//vchF24iD9o477sAjjzyCl19+Gffddx/OPPNMfOxjH8PExASOPfZYfPrTnzafe/nll2NiYgKbN2/G7t27oSgKrrzySvPx1772tXjppZcwPj6Od77znXjrW9+KeDxuPr5161YEAgEMDAzg97//PT71qU9h586dtu16/vnnsXbt2qKfvfe978Vzzz2HxYsXw+Px4NxzzwUA3HvvvTj55JOxatWqqp/1yCOPxPDwMA4ePFj3cSIIgiAIgiAIgiAIgiDaB7HVDWhn/vumZzE4kW76+yzs9uMrFx/f0GssWrQIExMTAIBwOIx3vOMd5mNf/OIX8cMf/hCDg4NYtGgR3v/+9+OKK67A5z//eXAchxtvvLFMlOV5Hu973/twww034MILL4QoijjppJOKnvPzn/8cl156Kc455xwAwKtf/WpccMEFuPXWW/G5z32uoc9j5ZOf/CS6u7sBAGeeeSYEQcCrX/1qAMDb3vY2fOhDHwJguIn/9Kc/YWxsDJ2dnQCAL33pS1i3bh1uvPFGCIJQ9Dk/9alP4Wtf+xo2b96M008/HQAwb948XH311QCMPOHly5fj+eeftxVcJycnEQ6Hi34WCARwxx13lD13dHQUixYtmvazstebnJzEggULpn0+QRAEQRAEQRAE4W4mEjKiySxW9He0uikEQbgMEm4PEQYGBkxxM51O4+qrr8bdd9+NiYkJ8LxhvB4bG8OiRYtw3nnnIZvNYsOGDVi9ejU2bNiA3/zmN2Wveemll+Kss87CyMhImbALAHv27MGDDz5YFKmQy+XKxMxGsebqBgIBU5Rl/08kEmZ7NE3DihUrin6f53kMDQ1hwYIF+NznPodbb70Vw8PD4HkesVgMY2Njtu8FAMFgsMiRa6Wrq6usgFsl5s2bVxTpUAn2el1dXTW9LkEQBEEQBEEQBOFuvvvnrdi0ZwK3/ec58Ii0MZogiAIk3DZAoy7Y2SKXy+GOO+7AG9/4RgDAd7/7XWzcuBGPPPIIFi9ejKmpKXR1dUHXdQCGkHnppZfixhtvxJo1a3DeeefZFh1bvXo1Vq5ciZtvvhn79u0re3zJkiX4+Mc/jm984xu27WKC8WyxZMkS8DyPwcFBBAKBssd/+9vf4uabb8a9996L1atXg+O4ouNSL8ceeyy++MUv1vTc8847D9/73vewa9curFy5suLzXnzxRfT395PbliAIgiAIgiCIljMSTWPrvimctX4+OI5rdXPaElXTsWnPBNJZFS8PxrBuaWerm0QQhIugpZw5zrZt23DJJZcgGo3iqquuAmC4Nn0+H7q6upBIJHDNNdeU/d7ll1+O2267Db/61a9w+eWXV3z9G2+8ERs2bLAVdj/84Q/jhhtuwEMPPQRVVSHLMh5//HG89NJLAAz36q5du2YsjNbL/Pnz8eY3vxlXXnml6aIdGhrC7bffDsA4Lh6PB/PmzUM2m8WXvvSlim7aWjj55JMBoKb83rPOOgv/+q//igsvvBD//Oc/IcsyFEXBPffcgyuuuMJ83oMPPog3velNM24TQRAEQRAEQRCEE6iajs/d9By+8ofNuOuZA61uTtvyysEY0lmjaPWWfZMtbg1BEG6DhNs5yGc+8xl0dHQgEongLW95C+bPn49nnnnGFFevuuoqCIKA/v5+rF+/HqeddlrZa6xcuRInnngi4vF4VaFw1apVOPXUU20fO+644/C73/0O//3f/43e3l4sWrQIn/vc5yDLMgDgAx/4gBnhcPTRRzvwyafnxhtvRGdnJ0466SSEw2G85jWvwcaNGwEAl1xyCdatW4dly5Zh5cqV8Pv9WLx48YzfSxRFU7yuhZtuugmXXHIJPvKRj6C7uxtLly7Ftddei4suugiAUVTupptuKhJyCYIgCIIgCIIgWsGdT+3HK0NxCDyHn96zHXtGEq1uUlvywt6CWLt131TrGkIQhCvh9NmyO7YJsVgMkUgE0Wi0KIs1k8lg9+7dWLFiBXw+XwtbOHtcfvnl6O7uxne+851WN6VticViOO644/DEE0+gt7e3ode6+eab8de//hU33XSTQ61zhkPx3CAIgiAIgiCIQ5nJhIxLrn0EQZ+Iqy9ch8/+37NY3hfCjz90CryS0OrmtRWf/91zeGzbKBZ1B5DIKPjDp8+i2AmCmONU0h7tIMctYcvOnTvxxz/+ER/+8Idb3ZS2JhwOY+fOnQ2LtgDw7ne/23WiLUEQBEEQBEEQhx6/vP9lJOUcPnr+Gpx42Dy896xV2DUcx//e/3Krm9ZW6LqOLXunsGp+B048rAeTySwGJ9OtbhZBEC6ChFuijA9/+MM49thj8ZnPfAarV69udXMIgiAIgiAIgiDaClWbuxtbt+6bwr3PDeCEVT14zZFGHN/FZ67EUcu6cNsTe2m7fx3sH0tiKpXFUcu6cGS+KNlWyrklCMICCbdEGT//+c8Rj8fxX//1X61uCkEQBEEQBEEQRFtxwwMv423fehj7Rudm5uvP790OkefwsTcdYW7pF3gOH3r94QCAZ3eNt7J5bcULe6cAAEct68R6U7iNtq5BBEG4DhJuCYIgCIIgCIIgCMIBnts1jt9u2IVoKovv3vEitDnmvB2aTGPr/imcfdQCLJkXLHpsZX8HOAC7h+OtaVwbwgqTrV/Whb6IH71hH7aQ49aV3PX0fjzy0nCrm0EcgpBwSxAEQRAEQRAEQRANEk8r+OZtW+CTBJxxZD+27JvEXc8caHWzHOXRbSMAgFcf2Vf2mM8jYEF3ALtHnHEa3/b4Xlx1/dNIZ3OOvJ4beWHvJBb3BNAd8gIA1i3txN6RBOJppcUtI6z8Y+sQvn/ni/jJ3dtb3RTiEISEW4IgCIIgCIIgCIJokB/99SWMxjK44o1r8al/XY++iA+/vG8HRqOZVjfNMR55cRheScCJq+bZPr6iL4SB8RSyOa2h99F1HX98bC827ZnAL++bGwXPZEXFHU/tw2jM6A+j0QyGptJYv7TLfM66JZ3QAbx0gOIS3MLgRArf+fNWAMBwNI3xuNziFhGHGiTcEgRBEARBEARBEEQDPPjCQTyw+SBOW9OLNxy/CAGviI9fcCRS2RyuvetF6Hr7RyZMJbPYsm8KJ67qgc8j2D5nRX8IqqY3nO+7cyiO4WgaPMfhjqf24fndEw29nhv48V+34Yd3vYSP/eJJ7BlJ4IV8JMJRywrC7fr8v6lAmTvI5jR8+dZNSMo5nL1+PgDgxf1TrW0UcchBwi1BEARBEARBEARBzBBF1fDTv21HZ8CDqy9cZxbsOnVNL845agEe3z6KWx/d09pGOsDj20eh6bptTAJjZX8HAGD3cGPC7WP5SIb/+Jcj4ZUEfPv2LW0dmXD/84O4+9kDWNEXwmRCxsf/9ync9bQRo3HU8oJwu7I/BJ8kYOu+qRa1dG4iKyoeeuFg3U7wX963AzsGY3j3GSvxnrNWAQB9N8SsQ8ItQcxRzj//fNx9990Nv86ePXuwdu1ayDJtCSEIgiAIgiCIUjZsGcJEQsbbTl+OrnxWKeOKN67F0nlB/OK+Hbju7m1tXazskZeGIfAcTl1TWbhd0R8C0HiBskdfGkGHX8J5xy3CB85djaGptKORCb+8bwcu/9Gj+MfWoaa7ofeMJPCDO1/EvA4fvnPZSfjqe46HqmnYtGcC3SEv+oUssnv3IPXMU0B0EmsXR/DSgSjUNu4rbuL/s3ff4W2V1wPHv1dbsmzL8t4Zzt6bEKCMMMLeZZVROoAOKF1AKWW1lPbXFmihUEoLlNFBKXvvkUWGs5fjvbcl2dq6vz9kK1Es2bLjOIPzeR4/T3zve9/7Sh65Pvfcc9pdXn749y+49z8beXlVdcLHVTQ5eXFlFdOL0rj6xBKKMpKwmvSScStGnQRujzDHH388Wq2WjRs3RrZ1dnaiKAqVlZUAPPnkk8yePTvm8U8++SRarRar1UpKSgr5+flccMEFfPLJJ/3GqqpKSUkJ+fn5BIPBqH1Op5MbbriB/Px8rFYrhYWFXHLJJTHPuWzZMqxWK1arFYPBgE6ni3xutVqH90YcIq6++mpuuummUT/vhx9+SEtLC6effnpk2y9/+UtycnI47bTTaG+PftTo1Vdf5bjjjiM5OZn09HQWLlzIo48+CsCYMWNYvHhx5HMhhBBCCCFEWF8tVpNeyxnzC/rttyUZePCbi5hRnMaLK6u4598b8PqDMWY6tPV4A6wta2PWGDspZn3ccfnpSei1Gsr3I+O2scNNWaOTxZMy0WoUzl1UxMziNF5eXc3uRsew5+2jqirvlNZT1eLirn9t4MdPrtnvQHM8Hl+Qu/+1AX8wxO0Xz8SWZGB+SQa///pC7FYjS6Zk4Xz7DWpvvI7Ge++gZ90aphXa8PiDlDcemDV9mVQ0OfnuY6siNYOHEnT9bFs46/uqE8aj1ShoNAqTC1LZWe/AH9y/Gs5CDIUEbo9AaWlp3HrrrcM+fsaMGbhcLhwOB5s2beLEE09k2bJlPPvss1HjPvroI6qrq3E4HLz55ptR+37wgx9QWVnJunXrcLlcrFixguOPPz7m+d58801cLhcul4vbbruNM888M/K5yzUyHUkPBL//wHf6VFW1X1A8EQ8//DDXXHNN5POysjI+//xzKisrueyyy3jggQci+/785z9z1VVX8c1vfpPa2lpaW1v585//zGuvvRYZc9VVV/GnP/1pv16LEEIIIYQQR5qNVR3sanBwyuw8kuMENFPMeu6/ch5fmZbDJ1ub+Or/fcx9L2zko82NdHsOj8f/v9jVij8YYsmU+Nm2AFqNwpgs636VSugrk9B3Lo1G4ZJjxwKwtWb/m3Y1drppd3k5fnoOy+bmU1rRznV/XsGOupFvCPaf5ZVUtbi4dumEqFq2E/NSeP6Hx/H90yfhfP/dyHZv2U4m5qcA4Tq/YnhcHj//W1nF9x9fTZvTw4/Onc7YLOuQmr59vq0Zq0nPzDF7N49LxR8MUVa//zcQhEiUBG6PQDfccAOff/55zCzZobLb7XznO9/h5z//OT/60Y8IhfbcWXriiSc488wzueCCC3jiiSeijlu5ciWXXnop2dnZABQUFHDdddcN+fzNzc1cfvnl5ObmkpeXx0033RR5ZP+jjz7CZrPxyCOPkJ+fT1paGg888ADbt29n0aJFpKSkcO6559Ld3Q2EH/lXFIXHH3+cMWPGkJ6ezg033IDP54ucb926dZxwwgnY7XZKSkp4/PHHI/vuvPNOzjzzTK6//nrsdju33HIL1dXVnHzyyWRmZpKWlsYZZ5wRyWx+6KGHePbZZ3nkkUewWq1MmzYNCGewvvTSS5F5X3rpJcaMGRP5fMyYMdx3330cddRRWCwWtm7dOuD7sC+/389bb73FiSeeGNkWDAYJhUKEQiGCwWAkGOx0OvnpT3/KQw89xNe+9jVSU1NRFIV58+ZFBW6XLFlCbW0t27ZtG/LXUAghhBBCiCPVf5dXAXDeeCO+utq444x6LbdfNJNvnzqJ7FQT721s4J5/b+DKBz49LGpm9mUfDha4BRiTZaXV6cHpHl6iy+fbmzHoNMwfnxHZVpCRBEBtW8+w5txb3/t99KRMfnTudH7/9YWEVHjs7Z0jXjZh7e42zAYtFx49pt8+nVaDd9sWAk0NpJ53EZqUVHxluxibFX7qtLL50E1iOlTVtffw+5e38NXffsyf3tiOXqfhN1fNZ9ncfKYU2GhxeGhxeAadp7nLza4GB4smZqDT7gmbTS20AbBFyiWIUSSB2yOQ3W7npz/9KbfccsuIzXnhhRfS2NjIjh07gHD5hf/+979cffXVXHXVVbz22ms0NTVFxi9ZsoS7776bv/zlL2zcuHFY/wGqqsrZZ59NTk4Ou3fvZtOmTWzYsIF77703MsbpdFJZWUlFRQX/+c9/+NGPfsSPfvQjXnjhBWpqaigrK+Oxxx6Lmvd///sfpaWlbNq0ieXLl3PfffcB0NjYyMknn8z1119PS0sLL730Er/4xS94//33I8e+9dZbLFq0iObmZu655x5CoRA333wzNTU1VFVVYbFY+OY3vwnA97//fS6//HJuuOEGXC4XW7ZsSfi1P/nkkzz11FO4XC4mTpw46Puwt127dtHT08OkSZMi2yZNmsSCBQsYM2YMzzzzDD/4wQ8AWLFiBT09PVx88cUDrkev11NSUkJpaWnCr0EIIYQQQogjWV17D8u3N3PUpEw0j/0fdTd/F8+uHXHHazQKFy8Zw2M3HM3zPzyO7yybjMcf5Id//4JPtjSO4sqHxh8MsWpnC5PzU8lMMQ06vq/Obfkwyg843H42VXUwb3w6JoM2sj3HZkanUaht6x7ynPva3Bu4nd6bATtzTBqnzclnQ2U7q3a27vf8fbz+INtru5helIZWo8Qc05dtm3zCUowlE/FWVpBt1WPUa6mQwO2QhEIqtzy9ltfX1lKcZeVH507nuZuPY9ZYOwBTClMB2J5A1u3y7S0ALJkcfaNiSoENhaGVXBBif0ngdj/VfO/bMT/89XUA+Ovr4o7p07N+bcz9jb+8c9jruummm6iqqorK7Nwf+fn5AJHaqM899xzJycksW7aM448/nry8PJ5++unI+IceeojrrruOJ598koULF5Kdnc3vf//7IZ1zzZo17Nq1i9/+9rdYLBbS09O57bbbeO6556LG3XXXXRgMBpYuXYrdbuess86isLCQ1NRUTj/9dNatWxc1/s4778Rms5GXl8ett97KP/7xDwD+8Y9/cNxxx3HxxRej1WqZPn0611xzTdT5pk+fztVXX41Op8NisTBmzBiWLVuGyWQiJSWFn/3sZ3z66adRmcnDcf311zNp0qRIveJE3oc+HR0dWCwWtFpt1PZ77rmH5uZm3n//fTIywnevW1payMjIwGAwDLqmlJQUOjo69ut1CSGEEEIIcaR4aWU1KnDhnCx81ZWoXg+N99wR+VtwIFmpZs5fXMwfrl1IslnPXf/awL8+qzjwix6GL3a10u0NcOzU7ITGj81OBoaXMbpqRwvBkMqSKdHn0moU8tIt1LSMQOC2qoP0ZCNZqXuC0FedOB6jXstf3tk5Yk3Bttd14Q+Goh6131vI3UP38k8xTpiEoagYY8kECPgJ1lZRlJF0wOruHqnW7G6jvr2Hry4ZwyPfPoplc/Ojgv9TCsKB220JBF2Xb29Gr9WwYEJG1PYkk47iLOuIlOwQIlESuD1Cmc1mfvGLX3DbbbcNq0bqvurqwhcfdnv4btUTTzzBZZddhl6vR1EUvva1r/G3v/0tMt5oNPLDH/6Q5cuX09XVxe9//3tuueUW3nnnnYTPWVlZSWdnJ3a7HZvNhs1m48ILL4zK7E1OTsZsNkc+t1gskfIMfZ/vWye3uLg46t99r62yspI33ngjci6bzcZDDz1EQ0NDZHxRUVHUXC0tLVx22WUUFhaSkpLCcccdh9frxencv/9k9z5PIu/D3tLS0ujp6Uno656RkUFra2tUuYh4HA4HaWmxLzqEEEIIIYT4MnG6/by5rpZx2clMtQbRZWVjnj2PkMtJ4713oAYSq107MS+FP31rEWOyrPzlnZ1sqjr0EiXe3xj+e+iEGTkJje/LuB1OndvPtjWhURQWT8rst68gPYnGTjeB/WgM5fL4qWx2Mb3IhqLsyYLNSDFx0dHFVLW4eHv94IH3RGysDH8t4wVug52dGCdMInnpqQCYJk3BMH4CIY+HsdlW2pxeHMMsN/Fl9NoXNSjA2QuLYu4vyrRiNmjZXjdwfVqXx8+GinbmjLNjMer67Z9WGC650NzlHollCzGo/t+FYkgK//jYgPv1efmDjrHMmYdlkDHDce211/L73/+ep556ar/neuGFF8jJyWHSpEmUlpaybt06du/ezT//+U8AvF4vnZ2dfP755yxZsiTqWKPRyBVXXMEf/vAHNm3axCmnnJLQOQsLC8nKyooKnI6EqqqqSHC3uro6kk1cWFjIeeedF3lNsWg00fc6br31Vnp6eli3bh2ZmZmUlpYyZ86cSGmIfccDWK1Wenr21GaK9fr2Pm6o78OECROwWCzs2LGDqVOnDjj26KOPxmKx8J///IfLL7887ji/309ZWRmzZ89OaA1CCCGEEEIcyf63sgq3L8jFS8ZgLMqj6LEnUUMhXB++h9aWhqJL/E/tbJuZn54/g+sfXcHy7c1RTawOth5vgBU7WphRnEa2zTz4AUBGshGrST+kUgmhkMpTH5bx2bZmZo+1Y0vq/0RgYbqF5SGVxg53pObtUG2r7UIFphf1f48vXjKW176o5e/vl3HijNyobM3h2FjZgUGnYWJeasz9+tw88u69P/K3o2XeAizzFgAwpiOcfV3Z5Iob+BV7tDo8rNzZwvySDHLSYn+fajUKk/JT2V7bRTCkxi1fsXpXK4GQytGTY9dznlJo4/W1tWyt6SIrNbGfCSH2h2TcHsG0Wi2//OUv+dWvftVvn6qqeDyeqI9Yj/d3dHTw2GOPce+99/J///d/aDQannjiCebMmcP27dspLS2ltLSUbdu2cdJJJ0WalN11110sX74ct9tNMBjklVdeYevWrSxevDjh9S9YsIDCwkJuv/12nE4nqqpSVVXFm2++Ofw3Bbj77rvp7Oykvr6e++67LxKw/NrXvsYHH3zAf//7X/x+P36/n9LSUr744ou4czkcDiwWCzabjba2Nu66666o/dnZ2ZSXl0fV+J07dy7PP/88Ho+H8vJyHn744QHXO9T3Qa/Xc+qpp/Lhhx8O+l4kJydz//338/3vf59nn30Wh8OBqqqUlpZy9tlnR8YtX76c/Px8pkyZMuicQgghhBBCHMlcHj//XVFNnt3CiTNzI9sVjYbkk06JBN+GoiQnGbvVyMqdLSO51P322bYmvP4gJ+31OvsEu13U/fQHNN57B21P/jWyXVEUxmVbqWxyJdTrxOXx8/Pn1/PMx+VMyE3hp+dPjzmuL1hb3Tr8cgmbezOapxbZ+u1LMun42gnjaXd5eWNt/EZziQgEQ2yt6WRqoQ2DbuCwy96Zv332p9zEl9Gb6+oIhlTOXFAw4LgpBal4/EEqm+PfVPi8txFfrKxvgOm93zuHQ1NBcWSQwO0R7oILLqCkpKTf9o0bN2I2m6M+PvnkEwA2bdqE1WolJSWFadOm8fbbb/P6669z+eWX4/F4ePbZZ7nxxhvJycmJ+rjpppv497//jdPpRKfTcf3115OdnU16ejp33nknf/3rXzn66KMTXrtWq+W1116jrq6OKVOmkJqayhlnnEFZWdl+vSfnnHMOs2fPZvr06SxatIjbbrsNCNfxffvtt3nsscfIzc0lOzub73znOzgc8R+luOuuuygrKyMtLY0lS5awbNmyqP3f+MY3qKurw263M3PmTADuvfdeOjs7yczM5LLLLuPKK68c8ffhO9/5Dk8++WRC78f111/P3//+dx599FHy8vLIyMjgW9/6FmeeeWZkzNNPP813vvOdhOYTQgghhBDiSPbSqmpcHj+XHTcOrUah7ekncH36cdSYnjWrabzv7oRLJmg0CgsnZFDd0k1DR8/gB4yS9zc2otMofGVa//q27nVr8e7YRs+a1XS9/F/8TXsarI3NTqbbG6C5yzPg/D3eAN/7yypW7mjh5Fl5PPiNhXGzGAvSw4Hb2rbhvz9ba7ow6bWU5CTH3H/K7DwU9jQwG65d9Q48/iAz42RPd69eSd1Pf4BnZ3QzO9fyT2m8727G2PQAUuc2AcGQyhtra0lPNrJ4Uuws2T5TCmwAbItTo9YfDPHFrlamFKSSEacRX0G6hWSznm21nfuzbCESJqUSjjAfffRRv20rV66M+vzqq6/m6quvjjvHQPtMJlOkQdm+zjzzzEg92Z/97Gf87Gc/G3S9+7rzzjujPs/KyuLvf/97zLHHH388nZ2dUdsqKysHnA/goosu4pvf/GbMOefMmRO3Dm+suaZMmcLq1aujtn3rW9+K/Hv8+PGsXbs2an9RURGffvpp1Laf/OQnkX/v+xpg4PchlhNPPBG73c6bb77ZL5gcy9lnnx2VYbu3qqoqli9fziOPPJLw+YUQQgghhDgS9XgDvLC8ihybmZNn5RJ0ueh68T8kHXs81mO/EhnnLS+jZ9VyXJ98SPKJJyc091GTMnlrfR2rdrZy7qLYdTpHU7vLy7rdbSyamEGKpX/pgu7VKwDI/P4PaXnodzjefp30K68FouvcDlRiYe3uNqpbu/nqkjF885SJMbNP+xRkWACoaxtexm0wpLK1ppNJ+anotLFz2CxGHQXpSZQ1DFwHdTAbqwaub+vesB7vjm1orNElH/y1tfSsWk7ueRdiNekl4zYBX+xqpbnLwxVfGRe3/EGfKYW9DcpquzhzQWG//aUV7XR7A3HLJEA4Q3pqQSprdrfxj492c+6iIpLN+v17EUIMQDJuhThCvf322wkFbQdTXFzMtm3bMBqNI7AqIYQQQgghDl+vrK7B6Q5n2+q0Gnzl4afgjCUTosalnH42isVC53//hZpgs+i549LRaRRWHSLlEj7a1EhIVWOWSVADAdxrv8BYMhHr8Sehy83D+d47hHqbHo/rfdR/sIzR7bXhzMels/MGDNoCpCUZSDLqqGkdXsbt7kYnHn8w8qh7PBPyUqhr78HlGX5jsI2VHeg0SiTDc1/uTaVo0+zoc/OjthsnTATAV7aLMVlWyhMsN/Fl9tqaGjSKwunzBi6TAGC3GslONbO9rn/GraqqPP9JBRoldob53i7/yngykk08+UEZl/3uE/767k6CIfk6iQNDArdCCCGEEEIIIcQgPL4g//68kqxUE6fMyQPAW7YLAGPJxKixWquV1NPPxl9XS/eKzxOaP8mkY0ZxGqUV7Xh8iQV799fn25rZESOIBfD+xgbMBm3Mx8/dmzcS6unGsnAxikZDyrIzCTm66F7+GQBjsqwowNba2HP32V7XhdmgpTjTOuhaFUWhICOJmmHWuN3aW/5gWgKBW4DdDcMrUxAMqWyq6mBSfmrMBmfBrk781VWYps/sF6w2jg+XOfTu3sXYbCsuj582p3dY6/gyaHd5WbWzlQUl6Qk3z5tckEpVs4tuT3QZk9W7WtlQ2c4ps/PITx+4+d20IhtP33QMPz1/OhmpRp7/tILPtjYN+3UIMRAJ3IovjTFjxqCqKjab7WAvRQghhBBCCHGY+XBzI109Pr56zFj0vY/ae3fvAkXBOG58v/GpZ52LYjTR+Z/nE86aXDQxE18gxPqKthFdeywtXR7u/Gcptz+7nh5vdBCrrq2b7XVdHDMlO2bwsWd1uBxf0qJw8+nkE09BMRhxvvNGeLtJx5xx6aze2YLDHTtzNRhS2VHXxcS81EEfce9TkG6h3eXtt95EbK7ubUxWaIvavu/XZmJv4HZn/fDKJZQ3Oun2BuKXSdiyCQDzjFn99mlTUtFlZePtzbgFqJByCXF9sqWJkKpy8uy8hI+ZUpCKClE3LIIhlb+8sxOjXsvVJ/XvERSLTqvhlNn5/OS8GQDUtx86tanFkUUCt0IIIYQQQgghxCDWlLUCcML0nMg2b9ku9PmFaMyWfuO1qTZSTlmGr7oS7/atCZ3jqN5O9qt2to7Aigf21vo6QqpKu8vLsx+XR7arqspf3w1nEscLiKVddiVZP/kZ+qJiIJxhnPWT28j+yZ4+JyfPziUQUvloU2PMOapbXLh9QSbnpyS85sKM4TUo8wVCbKrqZEyWtV890oY7bqH83NNwLQ/3IRnf27hs1xDq3LY5vbQ6PKhqONsWiNuYzLNpIwDm6TNj7jeWTMRfW83YlHDAvLJJArfxfLy5EYNOE/m5SURfndutezUXe6e0nspmFxcuLiYzTlOyeLJSw+ObBmnEJ8RwSXMyIYQQQgghhBBiAKGQyvrydibkppCaFG7UpYZCJC89FY0pfqAn7dIrsH31crTWwUsBQDijNM9uYdXOFlRVHbTu63CFQipvravDbjWSZjXw3xVVnD4vn/z0JN5YW8cnW5v4yrQc5o6zxzxea7ViPfrYqG1J8xdFfX7s1GwefHUb75bWc/bC/o2gtvWWUZiyTwbsQArSwwHymtbuSGbsYALBEPf8ewOtTg+nzR0XtU8NBvHu2A5A+z/+jvXoY0k268mzW9iVYMZti8PDVQ9+htcfxKTXotUoaBSFaUWxA7dpl1yOedYcdLmxg+LJS0/FPGMW9qxwkPpwbFCmqirbaruYlJ94NvVQtTm9bKrq4Nip2ZgNiYe2JuSmYNJreeajclodXs4/qoi/v7+LVIuBrx4zdsjrSEsyoNMotDgkcCsODMm4HSIpDC5ENPmZEEIIIYQQR7qyRiddPb6oQKai0ZB20SWknnVu3OM0lqSEg7YQruN61MRMmrs8B/QR+XXlbTR2ujl1Th7fPX0K/mCIP7+1g6oWFw+/uZ3sVDM/OHtqzMCxZ+tmfNVVMf8O8Dc34Xj7DVRVxWzQcezUbLbWdlIboy5t36PqkwtSE153QW/t0VjzxRIMqfzyPxtZvr2Zk2bmcuUJ0Y/B+6qrUH3hGrKBhnoCreHGcBNyk6lp7cbtG7wkw2tf1OD1Bzl2SjbTimwkm/WcNDOXJFPsYKI21UbSUUfHDcpb5s4nZdmZ2NJt2K3Gw7JUwlvr6/ne46t4p7T+gJ3j0y1NqMBxgzQS25dRr+VXV8ylJDeZV7+o4Zo/fk6b08uVx4+P+zUbiEajkJFiorlTArfiwJCM2wTp9XoURaGlpYXMzMwDdudTiMOJqqq0tLSgKAp6vX7wA4QQQgghhDgMrS8P15ydV5IR2ZZoRqy/oZ7u1StIPv4ktKm2QccvnJjBiyur+GJXK+Oyk4e95oG8sbYOgGXzCsi3Wzhheg4fbm5kV70TfyDEbRfN6FdSoE/rE48RaGyg+Ol/gTa6/m3Xyy/ieP1ljBMmYRw3npNn5/Huhnre3VDPNSdNiBq7rbaL9GTjkB5NL8gIZ9wmUiohGFL59X839WYPZ/PT82f0y/707toBQNLiY+he8RnuTRtJPuEkJuSm8PGWJnY3OpkeJ3MWwB8M8cbaOrJTzfz8q7MGzS7119eh+n3oC4tRNAPn0fmbmxiblcSWmi5CIRXNAcpcHWn+YIh/fLgbgNU7W1g2N/+AnOfjLY0Y9dohlUnoM2usnT9+cxFrd7fx3CcVqKrKGQsKhr2WrFQT5VLSQhwgErhNkFarpaCggNraWiorKw/2coQ4ZCiKQkFBAVpt/6YFQgghhBBCHAnWlLWh12qYXmSLbGv+v/vwNzaQ/5sHUAa4FnZv3kj73x9Hl56J9ZjjBj3XtN7SAYk+qj9UXd0+Pt/WxJyxdvLt4UDot06dyPIdLbQ6PVx1wvi4wUrV78NXUY5l3oKYrzlp8RIcr79M98rPMY4bz+yxdjKSTbxb2sBVJ5REgo8eX5CKJhdHTx5a0M1s0JGRbKImgYzbjzY18MGmBpZMzuK2C2fGDKr2BW5Tz7+I7hWf4dm8IRy47WtQVucYMHD72dYm2l1evrF0QkIlAbpe/R+ON1+j8JEn0OfFD2h2vPBPOp55kqnn/5i1/iANne7I1+pQ9+baOpq63CjA+or2AxJ0Hm6ZhL0pisL8kgzm73UzZriyUk1srOrA7QsMez1CxCPfUUNgtVqZMGECfn/srphCfBnp9XoJ2gohhBBCiCOW1x9kU1UHM4rTMOr3XPd6dmxDk5Q0YNAWwDxjFgDuzRsSCtxajDpy08wHLIPvndJ6AiGVZfP2ZBhmpZr58bnT2FLdyeVfGR/3WF91FYSCGMaOi7nfNGUa2lQb3Ss+x37ZlWg1Cktn5fLPzyrYVNXBrLHhUhM76rsIqSpTCmxDXn9BhoUddV2DZjy/vLoGg07Dj86bjk4bO7vVu3MHWnsGpgmT0OXm4d4cbhw2ITccuB2sQdnLq2vQazVR7+VA3Js3oU3PiFvfto9p0hQASpq3AyVUNrkOi8Ct1x/k2Y/LSUsycPz0HP63qpqyRmfC9YgT1Vcm4St7NQo8mDJ7G5Q1d3kozky8NIoQiZDA7RBptVoJUgkhhBBCCCHEl8Tm6k78wRDzS9Ij24KdHQRbWzDPnD3o8brsHLQZmXg2bUz4nOOyk1m5swWvPxgVLN5fqqryxrpaks16jpmSFbXvhBm5nDAjd8DjveXhR+CN40pi7le0WiyLjsb5zhv4amswFBRGArfvbqiPBG631w69vm2fwowkSivaaXf5SE82xhxT1uBgS00np83JJyVOyQeAnF/cS6AlXNc2+YSTCXZ1ovr9pCYZyE41D5j1XN7kZFNVByfPysPW27BuIIGODvw1VVi/cuKgJTZMU6ejSbKSXr4JMkoob3KyZJ+v16Ho9TW1tDo9XH/aJMZmJ/O/VdWsL28b8cDtR31lEiZGZ2x3/vdfKAbjgHWnD4SsVDMggVtxYBxWzck++eQTzjrrLPLy8lAUhZdeeilq/9VXX42iKFEfp5122sFZrBBCCCGEEEKIw9663eH6tnPG7QnceivKATCOnxDzmL0pioJ5xiz8dTUEOjoSOuf4nGSCIZWqlsSacCVqze42qlu6OXlW3rACwr7ewK1hXPys3KTFSwDoXv4ZAGOzk5mYl8J7GxrYUt0JhAO3CgwY0PNVV+Fa/mm/7QXpvXVuByiX8MrqGgDOXlgY/8UAOns6pkmTAUi7+FIyvnk9Sm/vjgl5yVS3duP1B2Me+/Kq8DnOGeQcfTxbNgFgmj5z0LGKVotl/kL0dZWk+RyUDZL5eyjw+II890k56clGzlpQyPQiG3qthrW9Pz8jpdXhYXNVB4smZGAy7PkeVkMhOv71HP6mxhE932B8dbUU/+dPpHq6aOmSBmVi5B1Wgdvu7m5mzZrFww8/HHfMaaedRkNDQ+Tj+eefH8UVCiGEEEIIIYQ4kqzd3UaKWU9Jzp5GYb6K3szTOCUD9mWaNgMAz+bBs26D3S6mlK8iyeuivNE5jBXHmTek8uhbOzDoNFywuHhYcyhmE/qiYnSZ8bM/zTNmYTnqaAxFe85x89nT0GoUfvH8epo63Wyv66I4y4rFGP8h4J41q2n+zS/xNzdFbS9ITwKIW+fW6fbz/sYGJuWnMik/fkavr6oSX1UFajB2YLYkN4VgSI35NXB5/Ly3oZ4JuSkJZw27N28A9pTOGIxl0WI0Ciz2VrPzANU7Hkmvramho9vHZceNw6jXYtRrmVGcxubqzrjB7+H4OE6ZBH9dLarPGyldEmhpHrFzDqRn1XKM29Yzq2EjzRK4FQfAYRW4XbZsGffeey/nnXde3DFGo5GcnJzIR1pa/ELiQgghhBBCCCFEPF3dPsoaHMwZlx7VYKmvZIBhzNiE5jHPnE3SkuPQ2u1xx6iqiuvTj6j9zjdJfflpFtesorxp5AK3r35RQ2Wzi4uXjCEnzTysOdKvvJbChx4b8FF/Racj55Y7SDrq6Mi2CXkp3HLBDDq6ffzkqTU0d3mYPEBQFUCfF64D27NqRdT2woxwxm28+rPvltbj8QcHzYTt+M/z1N50AyGPO7Kt9YlHqb35u6iqGskG3tXQ/2vw0aZGPP4gZy8sHLTsQR9Fr8cwZhy67MTqslrmzEexWCg2+Gnu8tDu8iZ03MHy2bZmTHotp+9V73fOODtef5BtvaUxRsK7pfUkGXUsnhRdJsGzYxsAxkmT6Xr9FWpuuBbP1s37dS41GKR79Uq8leV7tvl9UWNSlp2FTqsh29UkgVtxQBxWgdtEfPTRR2RlZTFp0iSuv/562toGTsv3er04HI6oDyGEEEIIIYQQYn1FOypE1bcFyPjGdeTecz8aS1JC8+izssn+8W2YezNvY2l58P9o/t2vUQMB9DotWd4OKkaoQZnD7efJD8rISDZx6bGJZQmPhJBnTyDr2KnZfP2kCdS29QAwZYBM1ZDHg3nmbBSDke6Vn0fty7NbmJCbwrsbGujsjg6iqarKy6urSTbrOX6QxlXeXTvQ5xeiTdpTk1T1+/GVlxFoamRCb+B2Z33/oOOn25rRaRSOm5Y94Dn2lnHtdRQ88EjCgV6N2cyYp/6J4YLLw+uoO3RjFT3eAFtrOpk9zo5BtyfMNHd8+OdmpMolVDQ52dXg4Nip2f1KfXh7A7emSVMwTZ0OGi0Nd95GzXe/Rf3tP6Hpd78eUhmFUE83tTfdQNOv7qTrxf8A4HjnTWpvuiFcr7i5CX9jAxqzGdPYcRQ762jpdA8yqxBDd0QFbk877TSefvpp3n//fe6//34+/vhjli1bRjDOow8A9913H6mpqZGPwsLE6tMIIYQQQgghhDiylVa0AzB3XHTgVmtLS/iR932pqoqqqrg3b8Tx1ut75kxJJfmkUyh85K+knHY6PWMms7vRiaqqQz7Hw29s59o/fc4rq2vw+oM8/UEZTrefb50yIaou6FC4N6yn5dE/4q+vG3SsqqrU/fRmmu6/N2r7ZceNZenMXBSINCqLxfHGq1R9/Qq0NhuebVsIdu6pDawoCpceOxavP8iLK6qijltX3k5tWw/L5uYPWMM32NVJoKkR44RJUdvN08NfU/emDditRrJTzazb3U4otOdr4HT7WV/extzx6VhN8RufjQRFb2BifvwA8qGitKKdYEhl/vjon5MJuSlYTfpInej99d6GBgBOmZ3Xb59nxza0GZno0jMwjh1Hzm2/wDhxMqgq3rJddH/+Kb6qyoTP5d68KdxM7oSTsV/59fDGYBB/XS0Nd95KywO/pfbG6wl0dGCcPIVUfzc9jaNbX1d8OcQvKHMYuuSSSyL/njFjBjNnzmT8+PF89NFHnHTSSTGPufXWW7n55psjnzscDgneCiGEEEIIIYSgocONSa8l22aKbAt0dBBsb8VQVIyiNyQ8l2fHNloe+h2mGbPw7S7Du2sHitlC8kmnoOj12K+6NlKfM+Pb3yXwyha61tTS0e3DbjUmfB5VVXlvQz0Ot58HX9vKUx+U4fT4mVZo48SZuVFjA60taCyWhDKHezasw/nW66QuO2vQsYqiQCiId/cuVFWNZJkqisJPz5/BNSdNGLBcg3vLRlS/H9sFX6X1zw/R/cUqUk7e03j8mKnZFKRbeGlVNV89ZixJJh1uX4CH39iOVqNw5oKB/6b37toJgHHixKjtxonhQG5fgO/EmTk8/2kFa8vbWFCSAcCKHc0EQyrHTk0827bjP/8k2NlB+tXfiDQ/S4SqqqR//AonVmxnxz6lAQ4lfRm183vfoz5ajcKcsXY+396M0+0n2Tz8QHcopPL+xgayU83MKI4uiakGAih6A+ape7LJzbPmYJ41Z88Yv39I731fBm/q2eehywi/9ynLziTkdtP+9BP4geRTT0eXloZp4mS0Wg3Gmt1R3+9CjIQjKuN2X+PGjSMjI4OysrK4Y4xGIykpKVEfQgghhBBCCCFEq8NDRooxKhDTs/Jz6n74PdwbSoc0lzbNjr+uFudbr+OrLCf5tDPI/91DkWBSX9C2z9jscDO03UNsUNbq8OJw+zl5Vh7fWTYZo16LAtxw+uR+ASXnB+/SeM8dBLsHL8ngKy9HMRjQFySW6GQsmUDI0dWvSZRGowwYtFWDQTzbtmAsmUjSkuNAo8WzaUPUGK1G4avHjKXbG+C1NTWoqsrvX95KVYuLa5dOIN9uGXBt3rLewG1JdOBWl5GJotfjbwhnFffVa31jTW1kzKdbm9EoCkdPjt+gbV+uD9+lZ/WKIQUOIRzo9q5dzZKmteyq6RxW9vVoWFPWSlaqiYL0/u/7nPF2QqrKhsr2/TrHhsp2Whwels7Kjao3DeG6ygW/+yOZP/hJ3OP73vuQN7FawZ4d21CMpqgmewC28y/C/rVrMM2YRfpV1wJgnjOfredcz3bbWBw9/qG8LCEGdURl3O6rtraWtrY2cnNzBx8shBBCCCGEEELspdXhZXxOctQ2b0W4UZFh3PghzaXPysZ20aUApJx+NroBGmn3rFvDhKf/RoFuHuWNEyPZnokoawzXQp1eZOPMBYWcs6gIR4+PtBhZu9rkFDzbttD82/vI+fnd/YLHfVRVxVtehqF4bNwx+zKMnwCEg6T6rMSzU32V5ag9PZimTUdrtVLw0KPo8/L7jTt5dh5PfbCbF5aHyyV8sKmBJZOzuHjJmMFPotGgTbNj3Ke5nKLRoMvJi5SDyLNbmDsunc+3N9Pu8mI2aFlT1srMMWnYkhLLtg60t+Gvr8N64skJjd+XZd4CrBu2kFS/m1bn0WSmmAY/aBQ1dboj5SliZZrO6y0zsnJHC8dMSfz7YF/vlNYD4a97PINluna+9F86//M8hY/8FW2qLe44VVXx19ZgnDAp5ve77YKvYrvgq5HPdWlp6GbNw/tBGU1dHlIT/N4QIhGHVcaty+WitLSU0tJSACoqKigtLaW6uhqXy8WPf/xjVq5cSWVlJe+//z7nnHMOJSUlnHrqqQd34UIIIYQQQgghDitefxCXx09GSnTA01dehjbVhjYtfo3WeOyXX4X98qsGDNoCqKEgxtpyMrtbKB9ixm1ZQ3j8+Nzw06RajRIzaAuQfNoZJJ98Gu7StbT9/fG4cwbb2wg5uoYUrDZNCGez9mW3JsqzZTMA5ukzATAUFKJo+ocu9FoNFx8zhnaXl7+8s5N8u4WfnD89ocfU0y6+jKK/PRuz1EXGdd8l+0e3RT4/c34BwZDKu6X1rN7Zii8Q4tghBCA9mzdGvZ6hssxfhEGnYUJb2bAalP3jo9387qUtBEMHJls3XpmEPvnpFqYUpPJOaT0VTUP7Xu7j8QX5dGsTk/NTKczoX9aj41/P0vnKi4POo8vIJNTtouv1VwYcpygKRU88Q/aPbkl4jVlWPbmOelrahvcahYjnsArcrlmzhjlz5jBnTrhOyc0338ycOXO444470Gq1bNy4kbPPPpuJEydy7bXXMm/ePD799FOMxsTrAQkhhBBCCCGEEK3O8CPVGcl7/p5Ug0F81ZUYxo4/oHUs9bn5aBQoVl2UNw1exmBv5Y1ONIrC2CzrgOPanniMxrtuJ/2ab2KaPhPHay/hePO1mGO95eHyg8axiQdu9QVFKEZTpJ5soryV5aDRYJo8JbKte/VKut54td/YM+YVkGLWY9RrufOS2UNqFhbv62eeNgPj+JLI50dPycJmMfD6mlo+3tIEwJKpiZdJcG8KB25NwwzcGksmYLCnMaF115AblH1R1sqTH5Txxrpanv1497DOP5g1Za0owNxxsW9kKIrC986YQiik8tBr24ZV7uHzbU24fUFOntU/21YNheh65X90f/7ZoPMkLV6CLicPx+uvEHK7BxyraLVobQPfYNlb7uq3+eaav+PYviPhY4RIxGEVuD3++OMjHTj3/njyyScxm828/fbbNDc34/P5qKys5C9/+QvZ2cNPxRdCCCGEEEII8eXU6vAAkLHXo+n+2hpUnw/DuHHxDhsR+qws0GgoVJ1Ut7jwB0MJH1vW6KQgw4LJMHBJg57SdfjratBYksj+6e3osnNp+9tjMevd6nPzsV182ZCCj4pWS94vf0P2LT9P+BiAzO/dTOGjf49qmNb54r9pf+qJfvVJTQYtf7h2IQ9/axHj9ilpEY/zw/dp/csjBLs6Y+5XQyECrS0EXeH3Qa/VcOqcPOrae/hkSyNTC2xDKlfg3rwBXXbOkMpF7E3RaLAtXER2TytVO6oSPq7HG+APL2/FbNAyJsvK0x/uprRi/+rM7isYUlm7u50JeSmkWOKXB5hg13Npvp+NVR18sLFhSOdQVZX/rapGp1E4fkZOv/3+ulpC3S5MkyYPOpei1WI79wJC3S4c774Zd5zrs0/oXrViSEFm2/RpAPh2bk/4GCEScVgFboUQQgghhBBCiNHQ1ptxm75Xxm3Q0YXWnjGkzNPhUPQGdBmZZHk7CYRUalq6EzrO5fFT395DSc7ATbeD3S78tdUYJ4aDXdrkFNKv/TZpX7smZiaqoaAQ+2VXYkiwMVkfY8lEtEkDZ/7uS1GUfkHOpMVLUL0eelav6Dd+TJY10sgtEa7PPsLx9hsoxtjBV/fGUqq/8TVcn34Y2dbXpEwFjhlCtq2qqmRcex32r3094WNisZ1+FquOu5wtbYGEg4mPv7OTpi433zxlIndfOhuTQcsv/7ORdldizbkSsavBgcvjj1smoU/DXbdz/IdPYDPAo2/vpNsTSPgcq3a2sq22i9PnFcSsK+zZsQ0A414Z2gOxnngyWlsaXS+/iOqP3Uis/dknaXvy8SFl1WfOmo4KaCp3JXyMEImQwK0QQgghhBBCCLGPVkdvqYS9sivNM2ZR/LdnSDrmKwf8/Pq8fJJdraCqlCdYG7S8MZwlWpI7cCDTu2snqCrGvbIUkxYehe3s86MyXfuoweAQVr7XcX4fnu1b8dXVJjTevWkDzg/f7/cYe/IJS1EMRjr/98KwHrWPrCcYxLNtC8aSiWhMsQO3+tzw4/iB+vrItoKMJGaPDZcCOGZqYpmzqt9PqKsTy/yFWI85bthrBjBNnIRx8XG0+xWaOj2Djt9Q2c4rX9QwsziNs+YXkp+exA/Onka7y8t9L2wiMIQM7oGsKWsFYP749Jj7/Y0N+GqqSVp0NIrHzXeKPLS7vDz1YVlC86uqypMflKHXarjsK7Gz3L29gVvTpMQCtxqDgdSzzkVjtRJoa+23P+h0EGioxzRx8AzevZlTU+hMzcJSXzGk44QYjARuhRBCCCGEEEKIfcTKuO1zIOvb9kk990Ks3/kRCmrCDcp2N4abVw1WNsC7M1yHM1ZwKtDREVWSIOh0UHnZBbQ/93SiS4/wNzdTf8vNON9+I6Hxjrdep+Wh/+sXKNampJJ88mn4ystwb1g/5HX08VXsRu3pwTwjfskHXUYmaHX4G6Mf6f/RudO457I55NstA57D31BP6+N/purrl9P610eHvdZ9TcxNJsvVzM6qlgHHBUMqv3tpC0a9lh+dOw2NJvy9etLMXM6cX8C68jZu/cc6nO7Y2aZDsW53Oya9lqlFtpj72/76KLU3Xh+pVzy1eSuT81P538pqNlQOXrbhs23N7GpwcNaCwrjlKTw7tqFNz0CXPnDW795Szz6fggf+jD4nN+Z8AMYEA8F768oei9HZETMgLMRwSeBWCCGEEEIIIYTYR1+NW3tv4FZVVdqeeIzu1StH5fyW2XMpWno8er2OXQ2JBW7LeseVDBq43Q5aHYZ9Sj50r/iM6q9fRs9er9Hx+iuoXg/6vIIhvoJw9qpiseDdPfjj48FuF+4N6zEUj0Vr7V9eIfWc80Gjpet//xnyOvq4N28CBm4Upmi16LOz8TfUR23PTbNw9OSByySEPB7qb/8JjtdfRpuSOuSszYGU7FrBdasfp3HlmgHHbanupK69h/OPKiI/PTp7+ntnTOHM+YWsK2/j+39dRX17z7DXEwqp7KzvYnJBKnpt/9BST+k6etasImnJsZimTMM4aSruL1bx0zMnYNBpuO+FTTh6fAPO/+QHZZj0Wi49bmzccalnnIPtgq8Oae2KXh+5+RLyRa/BuyNcozaRmrn78hWNp0ufhLepacjH9qlr7xnxWsTi8CaBWyGEEEIIIYQQYh9tTi+pFgMGXfjP5mBrC12v/o+edV+M2ho0oSCzci1squpIqC7o7kYn6clG0qz9s4T3lv71b5H9k5+hMUaPM06aCkD38k8BCLpcdL3yP3S5eViPHXp5CEWjwThuAt7dZYOWW2h/+m+EXE5Szjg75n59VjYZN3yfjG9/d8jr6OPZvBE0WkyTpw44Tpebh7+xYcglIrpeeZFgWyv2K6+l4E9/IfXs84a91n0VHL0IRQF/6cDffyt3NAOxSzrotBpuOmsK1506iZqWbr77l1Ws293Wb5w/GMLtG/j7rbHTjdsXZFyM+sJqMEj73x9H0euxf+0aAKzHfgXV68FesYXvnjGFFoeH3760JW7pi4+3NFLZ7OKchYXYB/h+Tjn1dFJPP2vAtcaiqiqNv76Hhjtuidru2bENxWDEUBw/WByPb/6x/P7o79OdP/zmhQ++upWfPLVmRDKixZFBArdCCCGEEEIIIcQ+Wh0eMlL2BIy8FeUAGMeVjMr5/fV1VFx8Dme2rMYfDLGiNyAXTyAYorLZNWi2LYTr5yYtWtxvu85uxzRlGj3r1hDyeOh65UVCPd2kXXw5ilY7rNdhnDAR1ePGP0CdW/eWTTjffgPT9JkkLz017riUpaeiz8sf1joAUs86l/Svfytufds++tzwOYKdHQnPHWhvp/O//0afl0/q2eeNeDkNY2EhgbRMksq3DhjUW7GzBbvVyMTc2A3qFEXhoiVjuPuyOfgCQX781BoefmM7Xn+QYEjljbW1XPH7T7nygc/wD1ALt6IpXE85VlmO7lXL8VVVkHLWeZFGc0lLjgsHQzUKp83J48QZuSzf3swrX9T0O15VVf7xUTkWg45Ljo0fQN23FvJQKIqCNjkZ7/ateLZujmw3TZqC9cSlKDrdkOfMsFlAUWjpGl4DuEAwxJbqToIhlfXl/QPq4stJArdCCCGEEEIIIcReVFWlzemNqm/rq9gNgGHs8LPphkKbkQlqiCLViVaj8NHmxgHHV7d24w+GGB8nYNcn0NKMv7kpbqZj0uJjUL0eXJ9+RNdrL6HPy8d63PHDfBVgHD8BYMByCZ3/fg5FryfzhhsHDXiGfD4cb7+Bv75uyGsxz5pD6pnnDDrOfsXVjP3XS0Oqm6qxWLBdcDHpX//2sIJ+g1EUBfP0GaT1dLBmbezmXnXtPVS3dHPUxMxIbdt4jp6cxWM3HM20QhsvrqziukdX8I0/fc7vXt5CqzPcRGyg2sp9DfPGZfcva+H68H3QaEg989zINl1aGgUP/hnr0ceiKAo3nTWV3DQzf35zBw0d0SUbttd2UdXi4rS5+aRYDHHXUH/rD6m75eYBX+dAUs+7EBSF1icew/HOm3i2bSHt0q+Red33hjVfts3MrIYNOF7577COL2t04vGHs7zXxsiEFl9OErgVQgghhBBCCCH24vQE8AVCZCTvycz0VuwGjRZD0ZhRWYPGYECbnoGmrZnZY+2sKWsbMNNyd4L1bTtffpGab11FoCl2IDhp8RIg3CjMUDgG21eHn20L4YxbXXbugGUHsn96O9m33ZlQNq131w5a//wQjrdeH9I6gp0dqIHBy00AaEymIb9mjclE2sWXYZm/cEjHDcWYxfMB2PHJ6pj7V+4INy47alJmQvPl2y384dqFfGPpBOrbemhxeLjy+PH87KJwDeBttV1xj61ocqIAxZn9A7cpy84k7bIr0dntMY9VVZUkk44bz5qKPxji1dXRWbfvbgg3hjt5dl7c8wedDnyV5eFmcsNkyCsg+eRl+HbvovWRB2m89xewH5nSmSkm5jRswPDeK8M6flNlOMNboyisKWuLe3NFfLmM/G0gIYQQQgghhBDiMNbW25gsfa9SCb7y3egLCvrVhT2Q9Dl5eHfv4vjLslm7u40VO5o5ZXbs4GZZb3ZkSe4gjcl2bEOTkoouOyfmfl1GJsbJU9EkJZFz+92wn8EjfXYORY/9PeY+z7YtmKZMQ2NJwjJnXkLzmaZOR5OSinvLpiGto+XhB/Fs3Uzxk8+h6ONncQKofj/dq1eiTU7GPHP2oHN3vfoS1q+cgDYldUhrGqr0ubNRkpKormrE4wtiMkQHl1fuaEGv1TBvfHrCc2o1CpceN44TZ+ZiNmhJsRjo7A437Npe2wWLYh9X3ugiP93Sbw0Alrnzscyd32+7GgrRdP+9AOTcegfzxqVTkG7hzXV1XHViCUa9Fn8wxAebGijOtDJhgO9l96YNAJhnzEr4tcaScf33sJ13Ib7aakKu7v0qcZFlM9FlTIGuBkIez6AlOfa1qaoDjaJw4owc3tvYQH17T78Gc+LLRzJuhRBCCCGEEEKIvbQ6wzUqM3pLJaihENYTlg5Yf/VA0Oflo7p7ODrfiFaj8PHm+N3qdzc4MOm15KZZ4o4J+Xx4y3djmjhpwABV3j33k/vze1AUBUUzcmGDtqeewLN9KyGPh5Y//YH6W3+I86MPhjSHoiiYpkzDV1GecI3TQHsbni2b0OcXDBq07T0Jzb/7NV2vD5456W9uou2JR2l78q8JrWV/6PPyab3jEVZlz+aLstaofS6Pnw2V7cwdZ48ZTB1Mts0cKUtgSzKQZ7ewrbYz5livP0hde0/MxmTe3bviZooqGg0Eg/SsXoG3fDcajcJZCwpxuP18siX8vb1qZwtOt59TZucN+D3q2bQR2P/AraIo6HPzSFpwFMknnLRfc6VbjfiS7XgDIQJtrYMfsBdVVdlc3cn4nORIY7k1Ui5BIIFbIYQQQgghhBAiSqsjHLjty7hVNBrsl34N29nnj+o69Dm5AJi6WpkzLp01Za0xyyWoqkpZo5PxOclxa5uqwSAdzzwJwQDGiVMGPK+i1+/32vflr6+j69WXqL/lZmpu+AbO997GPHseljlzhzyXaco0CAXx7tw+6Nigy0XDnbcR6ulOqL4tgKLTocvKxt8weB1dX3VleE2TBn5PR4KiKCyZFs6U/mxrdBB/TVkbwZDKUZOyRuRcUwpSqW3rwRHj+62qpZuQqjJ2n8Ctr7aGuh9+j/a/Px533rTLrwKg7W+Poaoqp87Jx6jX8mpvk7L3ShtQgJNm5g64PvemDWjTM9Dlxi+nMNo0GoX04jz8gRBdNfVDOramtZuuHh8zitOYPdaORlFYWyaBWyGBWyGEEEIIIYQQIkprb6mEvWvcHgzJJ59G8ZPPY5w0heOn5xAIqXy+rbnfuMpmF063n0n58R/V73rpBbpeeRHjpCmkLDvjQC47Jn1ePgUPPIJp+kyCnR2kXX41OXfcgzbVNuS5TFOmAuFSCwMJeTw03nMH/uoq7Fdei/W4ExJfb04ugcZG1FBowHH+qkoADMVjEp57f6T1tHF548dUrCrFH9yzthXbw98XR01KvKHaQCb3fi9tj1HndndvWY6x+zQmc330PsCAdX6NY8eRvPQ0PJs30r3iM5LNek6YnsOWmk7Wl4fLgcwZl05mavyfvaDLRaCpAfPM2ftV2uBAKJxYDEDZtoohHbepqhOAGcU2ks16phSkUlrRTiA48PefOPJJ4FYIIYQQQgghhNhLmzM647bl0T9S9+MbCfl8o7oObXIyWltaONNySla4XMKW/k3FPtvWF7SL36gp5YxzSLv0a+Tdez/a5JQDtuaBGAoKyb3nfsY882/SLrpk2GUYjONKMM9bMGi2peuzj/Hu2ErqeRdhO/+iIZ1Dn5uH6vMSbB8469HXF7gtKh7S/MMVcrqYW7WKgsYdlFa0AxAMqaza1UpJTjJZqeYROc+UQhsA22OUS6hoCgdux+3VCE8NhXB9/AHajExM02cOOLf98itRLBban3qCkM/H2QsLAfjVC5sIhFSWzho421ZrtVL8zAvYr7x2CK9odEyeO4UtWVPY7hpaS6lNVeHGZNOL0wCYNz6dbm+A7XXxG8SJLwdpTiaEEEIIIYQQQuyl1eFBq1Gw9db89G7bSrDbhcaQQH3UEebZsQ01ECBl2gzmjU9n7e42Olxe0qx7mqR9vq0Zq0nPrDFp0cdu34pn6xZs51+ExmQi7auXj/by+1EUBcWyfw2XFL2e3J/fM+i45JNOQWuzYZkXPwM0Hn1vUNjf2IAuI35A3FtVgS4zC81+vqZEGceNx2K1UNhVwyebmzDoNLy5tg6n2885vQHQkTA+Jxm9VsO2GBm3FU2ucD1l254gsWfrZgItzaSef/GgAXmtLY20iy7DvWE9oe5uJuWnMTEvhZ31Dox6Lcf21ngdiMZoHNVGgYnKmzKeFcddgRpQuWYIx22q6qAg3YK99+d6Xkk6T3+0m7VlbUwvShvkaHEkk4xbIYQQQgghhBBiL21OL+nJRjQaBdXvw1dTjXHs+IOylqb7f0nbE48BcMrsPIIhlbfX76mf2dTpZleDg8WTMtFp9/yJ37N+LQ2/uI2Ofz1LoLVl1Nd9MPlqqlEDARRFIWn+omE9Tm8oHoNp6nQY4FhVVTHkFWCeM39/ljskil6PdcpUxnU38Obaam7+2xe8u6GeCbkpnLlg5AK3Bp2GktxkttV29Ws2VtHkZGy2NaqectfLLwKQfHxiDb5SzzmfnF/ciy4tHJQ8e2ERAMdMycJiHDjHsPPl/+LZMXh944Nl7jg7DR1u6tt7Ehrf4vDQ2OmOCtBOzk8lyahjrTQo+9KTjFshhBBCCCGEEGIvrQ4vOb3ZhL7qKggFMYwdd1DWYigqxrN1M2owyDFTs7Fbjbz6RQ0XLxmDRqNEat4umbKnKVX3yuU0/fZXaEwmcu64d8CM0cOVr76Wlgd/T/LxJ5Ky7MzI9kB7O/U/+zHG8RPIueOeYddANc+ag3nWnAHHKIpC9k9vH9b8+8M0dRppa9YyR+dg4uI5LJ2V269R2EiYUmBjW20X9e095KeHM4rbXV46un0s3qsJmhoMos/Nw3rcCQmXjNg7K1f1+zlpZi6NHT2cMid/wOP8zU20//1xkpeeimnS5GG8qgPvmK3vYNy8nfXl08izWwYdv7m3TMKM4j2BW51Ww+yxdlbubMHp9pNsHvmGgeLwIBm3QgghhBBCCCFEr2BIpbPbR3py+JFlb0U5EH5E/WAwFBWj+rwEmhrRazWcNjefxk43a8pagXB9W6Ney4KSPU2p2p76Kxqzmbxf/d8hG9zaX9pUG96d23Bv2hDZpgaDNP/hfkKOLpKXnnrINa4aKaYp07CadNw+x8A3T5l4QIK2AJMLwg3K9i6XUNHkAmBczp7GZIpWS/rXv0XmD34ypPmDTgfV37yS1icexaDTcM1JE8gfJNDpLl0HgGnGrCGdazRluZqZ2LaLtb0/o4OJNCbbp9TJvJJ0giE1UstYfDlJ4FYIIYQQQgghhOjV7vISUlUyehuT+cp3A2AYV3JQ1qPvzWD0VVcBcOb8AhTglS9q6Oz2samqg3nj0zEZtAAE2tsINNSTtGgxhuIxB2XNo0GbZMVQPBbPti2RR/k7/vUsnk0bSD71dKxLjt3vczg/fJ+GX9yKGgzG3O94+w1aHnmIoMu13+caCtOkyaSedxHGyVMP6HmmxAjcljf2NibrDRa7t2wi5A6XBBhqoFxjTUYNBvFs3ZzwMa5PPkTR67HMH3rd4tFiyc3BooTYvrOWUEgddPymqg7sViN5adGN5eaPTweQcglfchK4FUIIIYQQQggherU6vACRjFvbhV8l+7Y70WVmDXTYAdMXfPVVVwKQbTOzaFImq3a28srqakKqyjF7lUkIdXdjnrsA8+x5B2G1o8s0ZRrBjnYCTY043nubzn8/h2H8BNK//u0RmT/Q3Ih7w3rc69fG3N/zxSqc77+DxmQakfMlSmNJIv2qazFNnHRAz5ObZibVYmBrTWdkW0VzOEg9NttKoKODxnt/QcNdwysXoSgKpqnT8VdXEXQ6Bx0faGnGs2UTlvmL0CZZBx1/sOgyMzHpNSgdbZQ3Dfy62pxeypuczBqT1i/wnWe3kGMzS+D2S04Ct0IIIYQQQgghRK82pweAjJRwME5nTydp4VEH7bF7Q2ExuqxsFN2eFjVnLygkpKo883E5Wo3C4slZe40vIveOe7Ae+5WDsdxRZZoSzjh1b9pA16v/Q5eZRc7td6MxGkdkfusJSwFwfvhezP2+qgr0BQVRX5vRFPL5CDq6Bh84TIqiMKUwlfJGJ15/OOu4vNFJRrKJFIuBjmefRHX3YDv3wmGfwzR1OgCebVsGHev69GNQVaxfOXHY5xsNuoxMTHotqZ6uQYOuK7aHa1T3/Qw7P3yP2h98h5obr8NfXcX8knTq23sSbnQmjjwSuBVCCCGEEEIIIXrtnXEb7Hbhq6qM+6j8aNCYTBT95Sls518c2Ta/JIMcm5lgSGVmcRopX9LGRaYp0wDw7txB3r2/Jfeu+9ClpQ1yVOL0WdmYps+kZ/WKfuUQQj3dBFqaMRaPHbHzDUWgvY3qay6j/bmnBxzn/PgDWv74ezpe+Ceu5Z/i3b0LX10twa7OhM4zOT+VQEjlGw8v5/Zn11HZ7GJsdjjbtWfNagxjxmFZtHjYr8M0Nfw1TCRwa5o6jeSTl2GZN3/Y5xsNuoxMDHotdp+TdeUD16f9fHszWo3CwgnhGtWOt97AV1UJfj+qGmKelEv40pPArRBCCCGEEEII0avNGQ7cZqQYcW9YT+2N1+H6+IODvKpoWo3CmfMLADhmSnZke9DRRd2Pvo/rkw8P1tJGlS4zi+zb7iTtsivRJiejz8sf8XNYjz8J1e+n+7OPo7b31Rw+WHWEdfZ0dFnZuD75kJDHE3dcsL0d5/vv0PHMkzT/5pfU/fB71H7nG7Q98VhC5zlldh7HTc1Gp1FYvasVfzDE9GIbwW4Xwc4ODGPH7Vc2uqFoDJokK96d2wcda5o8lczv3IiiNwz7fKPBUFRM5jeuwzBtBhsr2/H4Yt/46fEGWF/ezuyxdpLNelRVxV9bjWnKVAofeQJDQREly1/m6OqVrC2TwO2X1cHJ5xdCCCGEEEIIIQ5BrY5wECw92YQ30phs/MFcEp4d23B+8C62cy9En5sHwPmLi0lNMrB0Vt6ecVs34y3bScjtPlhLHXVJC486oPNblxxL218ewfXZx6ScdkZku6+yAgD9QWwAl3ziybQ98Sjdq5aTHKd8gO28C0k+6WT8DQ346+sItDSj+rwYejOFVb8Pz47tmKfPjHl8ts3MLy6ZDUAgGKLN6SUjxUSgfBdA5PtxuBSNhrxf/x59Ts6A4/xNjegys1A0h37+odaWRupZ5zJtRRUfv7mdtbvbWDKlf43sNWXhQPjRvWUSgh3thLpd6AuLAFB0OvwrPuXozgB/Lj+GYEhFqzk4JVvEwXPof8cLIYQQQgghhBCjpM3pxWzQkmTS4aupBo0WQ0HRQV1ToKkR59tv4C3bFdlm1Gs5fV4BBt2eP+vdWzYBYJo2Y9TXeKTSmC3k3H4X2bfeEbXdOGkKaZddiXH8xIO0MrAefyLo9Djfe7vfPs+ObQQ7OwDQpqRimjSZ5BNOIu3iS7FfcXWkBnLLww/ScMet9MRpwLY3nVZDts0cDh4qCuZ5CzCOn7Dfr8NQWDRgFq0aClH/sx9Tf9uP9vtco2nRhHCZg+W9dWz39fm28PajJ2cC4K+tAYj6fWOcOIlsdyu+7h521B24esbi0CWBWyGEEEIIIYQQolerw0t6cri5VaC5CV1GxkFrPtWn73F8X03VgOM8W7egSUlFn18wCqv68jDPnI02yRq1zTh2HGkXXzaiNXWHSpucQtKCRXg2bcDf3BTZHurppunX91B3yw8Hrc9sO/9iNGYzTb/5Ja7ln+KrqiTU0z3ouY3jJ5D783uwzFuw369DDQToWb8W96YNMfd7tm4m2NqC+TC6IdF47y8I3fYdxmRZWbmjhWBIjdofCIZYubOVCbkpZKWaATDNmEXxk89jPf6kyDjTxMmYdRrynA2skXIJX0oSuBVCCCGEEEIIIYBQSKW5yx0JpASam9BlZQ9y1IGnzysAjTbctCiOYLcLX8VuzNNm7FfNURGbv7GB9ueexldbg6qqB7Vh3d6Sl56KLiubQG/gVlVV2p95imBHO7bzL0LRagc83lBUTPatd6D6/TT/5pfU3ngd9T+/ZTSWvoeq0nTf3XS+8M9+u0I+Hx3/ehYA63EnjO669odOR6C1hcUT7HT2+NheG50tu6mqA5fHH1VCQVEUtLY0tNY9NwmMEydh0GkY09PImt2to7Z8ceiQGrdCCCGEEEIIIQ5J7S4vdqtx1M7X1OXG7QsyJssabvik0RwSgVtFr0efX4CvujLuGO+2rRAKYZo6ffQW9iXSs/YLOv/9HJ0v/IvkE5fi+vgDbBddStrFlx3UdZnnzKPw0b8TcvfQ9epLON56HX9dDcaJk0leempic0yfScHv/ohn2xYC7W1ok1MGPablzw+htSZj/9o1+/sSUPR6jBMn4dm+DTUYjASbQz4fTffdjWfTBpJPXnbQGsENhy4jE0IhlmTreB5YsaOZaUW2yP7l21sAWDJ5T+C2Z81qtGl2jONLItuM4yegaDXMVFt5pLaLbk+AJJOE8r5M5KsthBBCCCGEEOKQ89HmRu759wYe+fZRTMpPHZVzVjS5ABibbUVjMjHmH/8+ZDIrDUXFdC//lJDHg8Zk6rffOHkq2bf8HMO4khhHi/2VesbZGMeX0PbXRyM1ZTXW5IO8KiLNuoKtrbQ98SiaJCupZ59P6nkXDamRl6F4TFRgVFVVVJ8PjbH/jRNVVXF9+hHGEfxeM02djmfzRrxlOzFNmgKA863Xca9fQ/LSU8m4/nsjdq7RoMsM160t1odvPi3f3sI3Tg7XQ1ZVlc+3NZNjMzM22xrZ1vzAbzEUFpF33+8i82jMZuxXXIPFZSJYplJa0R6z0Zk4ckmpBCGEEEIIIYQQo6aurZuv/vZjVu1sGXDcx5sbgfAjxaNld6MTgLFZex5VHuxR89GStORY0i65AjUYiLlfa7WSdNQS9IdAhvCRyjR5Knm/eYDM7/8Qy/yFJB119MFeUoSheAzZP7uTor89S/rXv7VftXdDPd1UX3MZbX95OOb+YGcnak9PuITHCOnLFK//6Q9o/v39AKSccTaZ37uZjBtuHFIQ+lCgywwHV0NtLRw1MZOqFhd1beHawR9saqSpy83Rk7MiZU2CnZ2EXE70hcX95rKdfxGTl4XLRGwcxd+H4tAgGbdCCCGEEEIIIUbN/1ZW0+r08MmWJhZNzIw5JhhSWVfeDuwJpo6GiiYXCjAm24pn2xZ8tTUkLT4mqubkwWI9+ti4+4IuF/7qSoxTpkl92wNM0WhIPvFkkk88+WAvpZ+kBUeNyDwaSxKKwYBn+7aY+wMNdQDoc/NG5HwA5hmzsH31cgIN9RgnTALCN02STzplxM4xmnTp4d9tgdYWFk+dxhvralm+vQW7tYtfv7gZu9XI+YuLIuP9tdUAGAqLYs6Xl2bGQoDqFteBX7w4pEjgVgghhBBCCCHEqHD7ArxTWg/A1prOuOO213bh8viBPeULRkNFs5NcuwWzQUfr55/ieO0lzLPmHBKB24E43nqNjmeeJPtnd45Y8E58uZkmT8X1yYcEnU60ydElIXz1vYHb/JHLuFW0WuyXfm3E5jvYDMVjyPvNg+jz8plrMGPUa/nP8ko6XD7Sk4387pr55KZZIuN91VUA6GMEbv3NTdT94DucaZ3KJ7alo/YaxKHh8Mo1F0IIIYQQQggxJC0ODz97Zh3lTaOXuRrP+xsa6PYGsBh0VLd243D7Y45bUxbunm6zGKhsdhEMqQd8bb5AiLq2nkiZhEBTI2i06NIzDvi5E6GqKnW33Ezjr++O3u734XjtZbTpGVjmzD9IqxNHGmNvnVnvjv5Zt/76WmBkM26PNBqTCdPESWitVkwGLfPGp9Pm9JKZYuIP1y4gPz0paryvJhy4NRT1L5WgS89ADQYp7m6gqdONx3do1N0Wo0MCt0IIIYQQQghxBHvsrR2s3NnC+xsaDuo6VFXl5dU1WAw6Lv/KOAC2xcm6XVPWRpJRx8mz8/AHQ9S0dh/w9VW3hAPEfc2CAs1N6DKzDpkat4qioPp8eHftjNru/PhDgp0dpJ51HopOHqoVI8M0ORy49ezc3m9f0vxFpF12JfqcnNFe1mEl0NGBt6IcgMuOHctxU7P5w7ULojJt+2jMFvRFxWjT7P32KVotxpIJZHbUgRqitu3A/z4Uhw4J3AohhBBCCCHEEWpjZQcf9jb52lnvOKhr2VLTSXmTk1Pm5DF3fHp4W3Vnv3FOt5/tdV3MGWdnQl4KMDp1bvtKMozLTkZVVfzNTeiyDq3u7YYxYwm2teL6/FMA1FCIrpdfRLFYSDnltIO8OnEkMYwZh2I09btRAOFGYmkXX4aiNxyElR0+Wv74e+p+fCMht5sphTZ+cclssm3mmGPTr7qWwocei1uj2jhxEsaQn8zuVqpaJHD7ZSK344QQQgghhBDiCBQMqTzy5nZ0GoUsm5kddV2EQioazcFpXvXK6hoAzlpQSGFGEia9Nmad23W72wipKvNLMhjXm/1a0eQEcg/o+vpKSYzNthJyuVDdPeizD62MwrSLLsW9fi3Nv/s1ikGPomjw11SReu6FaCxJg08gRIIUrZb8P/wJfXb0z52qqqCqKBrJAxyMZc483Ou+wL2xlKRFi/drLtPEyei0CvmOOmlQ9iUjP2lCCCGEEEIIcQR6e30duxocXLC4mKMmZtLtDdDQ0bPf83Z7Ar2B1MR1uLx8vLmRWWPsFCZB8z0/5yiTk221Xf3q164pawNgQUkGhRlJ6LUaykch47a8yYVBpyE/PQnV68EyfxHGiZMP+HmHQp+bR+5d96GxWmn+zS9Rg0GsJywl9cxzDvbSxBHIkFfQr1RIoKWZykvOo+OFfx6kVR0+LPMXAtCzZtWA47zlu2l59I94y3fHHWOcOBm9VkOus3FUSseIQ4cEboUQQgghhBDiCOPy+Pnbe7tISzJw+VfGMzk/XHJge93+l0t47O0dXP/oShw9voSP+WBTI4GQyjkLC+lZvQr3+jUs++hxPP5gVBBYVVXW7G6lIN1CTpoZnVbDmCwruxsPfIZZRZOT4kwrWo2CLiOTnNvvIuWUZQf8vENlKCom9xe/xHbhJVgWHkXWjT9Cl5F5sJcljkAhr5fuL1bi2atBmb++DtXnRWPuX6dVRNPn5qHPL6RnzepwpnIc3h3bcL71OsGuzrhjdPZ0Ch/5K+sXnSulEr5kJHArhBBCCCGEEEeYF1dU0dHt49qTJ5Jk0jExPxXY/zq3oZDKih0t+IOhIdWd7cuYnTs+HdXrAcCUFK71uGWvcgnVrd00d3lYUJIR2TY220qr0zOkQPFQOdx+2pzeSGOyQ51xfAlpX708bj1MIUaC6vXQ9Ms7cbzxamSbv6EOAH1e/sFa1mHFsmARwY52fOVlccf4aqoBMBQUDjiXIb+Aosxk6tp6+j2pII5cErgVQgghhBBCiCOIqqq8vb6e9GQjp8zOAyDfbiHJqGNHXdd+zV3W6KTd5QXCpQUSVdfeQ7JZT7JZT6C1BYDce38DRDco6yuTMH+vwO247GRgT/OwA6Gisa++bfhcXa+/Qssff0/I4zlg5xTiUKdNSUWXm4dnx/bINn99b+A2v+BgLeuwYpm/EH3xGEKu+L+/fDVVKCYz2kEy50NuN7Pbd5LZUUPjCJS9EYcHCdwKIYQQQgghxBFkc3UnjZ1uls7MRdvbiEyjUZiQl8Kuesd+ZWp9sas18u+h1J2ta+uhID38aHVf4DatMI+CdEukQVlnt4//Lq/CqNcye6w9cuz4nHAwdSgZvkO1d2MyAPf6NTg/+gDFYDhg5xTicGCaPI1AYz2Bjg6gN3Cr06NLzxjkSAFgnj6TwgcfxTxrTsz9qqrir6nGUFg0aAZ90Olg8ptPMLe+VMolfIkcVoHbTz75hLPOOou8vDwUReGll16K2q+qKnfccQe5ubmYzWaWLl3Krl27Ds5ihRBCCCGEEOIgeG9DPQBLe7Nt+0zKS8HjD+5XY5vVu1oxG7TYLIZIsHMwPd4A7S4vefZw4NZ+xdXk3nM/Xa+8yLK2dTR0uGnucnPnP0tp6nLzvTOmYDLsaYg0bhQCt33ZvH3Zvf7mJnRZWSiaw+pPZiFGnHnmLADqf3Ij3atW4K+vQ5+b169pmRieQEszwc4ODOPGDzpWn5WNLjubMR1V0qDsS+Sw+l+ou7ubWbNm8fDDD8fc/5vf/IaHHnqIRx99lFWrVpGUlMSpp56KRx5vEUIIIYQQ4kvpn59WcP+Lm7409QC9/iAfbW5iXHZyJAjZZ0+d2+GVS3C6/Wyr7WTOuHTG5yZT1dKd0Pta3x5+pLcv41aXkYl5xiycH73PxJ0rALj1H+vYVNXBBYuLWTY3XDvTtfxTXJ9+hH7rOuxJiQeKh6OiyUWqxYDdakBVVQJNTeizcw7Y+YQ4XFi/ciL2r3+LYLcL7+5d5N51H1k/+MnBXtZhxV9fR+Mv78T1yYf99ik6PWmXXIH16GMTmitl5mzs7g4aK+tHepniEKU72AsYimXLlrFsWeyunqqq8sADD3D77bdzzjnnAPD000+TnZ3NSy+9xCWXXDKaSxVCCCGEEEIcZP5giOc+KafbG2BMlpWvHjP2YC/pgFu1swWXx89lx/V/rZPyUwDYUefglNlDbyy0vryNYEhlQUkG9e09rN3dRkN7DwUZSQMeV9cWDtzm2y2ooRC+qkp0WVmYZ8wm6Y3XSHV3Utkcrmv77VMnRY7r+Nez+KsqAVh49Nf5oDmNYEiNlH8YKaGQSkWzk0n5qSiKQtDRher1oMvMHtHzCHE4UjQabGefT/JxJ6CYzGhMJsiSn42h0Fit9KxZhaLTYT3uhKh9OrudtEuuSHiu1Nmz0Lz8Kv6tm4ElI7xScSg6rDJuB1JRUUFjYyNLly6NbEtNTWXRokWsWLHiIK5MCCGEEEIIcTCsL2+n2xtAoyj87b1d7G50HOwlHXDvbmhAoyicNDO3374cm5lks56ddcN7H1btDNe3XTghI1ILNpEs2NrewG1eehLBzg7qfnADHc88hXnGTHQ6DTM8dRSmJ3H7RTMjQdmQx4O/pgZ98RhQFOaVL8cXCFHXNvKPBzd1uXH7gpEM5UBzEwA6CU4JEaG1pYWDtmLItCmpGCdOoad0HarfH7VPDQSGNJdp+kz0Wg3Gyu2o6pfjSZIvuyMmcNvY2AhAdnb0f67Z2dmRfbF4vV4cDkfUhxBCCCGEEOLw9/m2cADulvOnowL3vbAJrz94cBd1ADl6fKze2cKccXYyUvoHWBRFYVJ+KmWNDgLB0JDmVlWVL8paKcpIIifNHAlyljfF75TeZ+9SCYGWcGMyXWYmpumzUIBrCrz86duLSDbrI8f4KsshFMS65CtYFhxFZtVm7D1tCZ1vqJo6w6X18uxmADQpqaRdfjXmmbNH/FxCiC8ny4KFqO4e3Js2RLaF3D1UXnYB7f/4e8Lz6LKy6Zowm3qjnY5u34FYqjjEHDGB2+G67777SE1NjXwUFhYe7CUJIYQQQggh9lMwpLJ8ewtFGUmcNCuPrx0/nopmF39/v+xgL+2A+XBzI4GQysmz8uKOmZiXgi8QoqplaAHQiiYXbU4vCyaEO8kXZSah1ShUJJhxm2LWk2zWE2jtDdxmZKJLS0OfX4iycwtJxugqft7d4a+TccJEUs85H71Ww1E1qw9Ig7I2Rzhw2xfs1mdlk3bRJZgmTR7xcwkhvpySjj4GgO7ln0a2eXZsR/V50aSmJjyPoii4rvkBqwsXUt0iDcq+DI6YwG1OTrhwfFNTU9T2pqamyL5Ybr31Vrq6uiIfNTU1B3SdQgghhBBCiANvW20n7S4vS6ZkAXDZceOYWmDjheWVkQzQI80HGxsx6bUcMzUr7pi969wOxRdl4TIJfYFbo15Lfrol4Yzb/N7GZIGWZgB0meE12i68BPsVV0MoOgPYW7YrfJ7xJZimTidp4kRmN26kujL+05TD1er0ApCebBzxuYUQAsCQV4CheCzdK5ejBsNPfni3bwXANGnqkOYqygzXFR/qDThxeDpiArdjx44lJyeH999/P7LN4XCwatUqFi9eHPc4o9FISkpK1IfYf21O7wGpPyWEEEIIIUQiPtsaDhAeMzVcSk2rUThjfgEq4ezRI43T7WdbbSfzxqdjNsTvQT0pL5zZtaOua0jzr9rZilGvZWZxWmTb2KxkGtp7cPvi12js8QZod3nJt/cGbnszbrXp4QBw8gknkXzCUhStNuo4Q1ExSYuPQZsSbhhmv/hSyqYex+7Gkf/atTqiA7dN999L7c3flfqRQogRlXHdd8n/zQOR33ee7VtRDAaM48YPaZ7CJA1XlD6H5sVnDsQyxSEm/v/ohyCXy0VZ2Z5HmyoqKigtLcVut1NUVMRNN93Evffey4QJExg7diw///nPycvL49xzzz14i/6S+tULG9lc1cG3T53EeUcVoSgj2/lVCCGEEEKIeFRV5bNtTWSmmJiUtycxoy/rs+4IzLgtrWgnGFKZV5I+4LiMFCMpZv2QgtfBkMq22k6mF6Vh1O8JsI7LsfLxFqhscjGl0Bbz2LrexmR9732o2wUaLbrewC2Ev16Bhnr0efmRbbbzLoyaJ+moJTgbU2lYV0e7y4vdOnLZsW3OcKmEvsCtr6YaQkH5G0YIMaJMU6ZF/q0Gg3h2bMdYMhFFrx/gqP4ys2zk9LSglB25NdvFHodVxu2aNWuYM2cOc+bMAeDmm29mzpw53HHHHQD85Cc/4Xvf+x7f+ta3WLBgAS6Xi7feeguTdD4cdeWNTgIhlYff3M7d/9qAy+Mf/CAhhBBCCCFGQEWTi4YON0umZEUF3yKB27YjL3C7dncbAPPHDxy4VRSFokwrVS3dCWeUVjW78AVCTC6IrsPY16Csojl+ELivLEVfxm3WjT9i7L/+F5Vh2/qnP1B743UEHQNnAZfkhoPwZQ0jW+e21eklLcmATqtBDQYJNDeiy84d0XMIIQRA0OnA+f47+KqrUN09GCcPrUwCgFarwZ+ajtLVcQBWKA41h1XG7fHHHz/gxYWiKNx9993cfffdo7gqsS9Hjw+H289xU7NRFIWPtzSytaaLuePtTMhNYWJ+CtOL0gafSAghhBBCiGH4bFtvmYQp0bVe05IMmA3aI7LG7drdbeTYzOT1BkgHUpSRxObqDrp6/NiSDIOO31Efroc7MS+6rFxf4LZ8gIZhtX0ZtxlJkW2KPvqcppmzcb7/Ds733sF2/kU43nub7s8+IePb30Gfu6fR2sRX/sK3126nbOkEFk7IYKS0ObyRbNtAawuqz4e+oGDE5hdCiD6ON16l4/l/kHPnryj627PA8DL7DWlpGJqr6XJ5SLVKsuKR7LDKuBWHh76Ls4l5Kfz84pnceOZUtBqFd0rrefjN7dz419W8tLL6IK9SCCGEEEIcqT7f1oTVpGdGcXSygKIo5NstR1zGbUNHD/XtPcwvSY/7eH+grRXPrh34mxop7G1sk2hH8r56uPsGbrNtJiwG3YANyur2yrhV/T4cb76Gd3dZ1Bjr0cegTbXheOu18OPDWzbhLl2LxmqNGpdiVMjoaaWsfmj1eQeiqiptzj2BW39tuFm1Ib9wxM4hhBB9khYfA0D38s/Q2dPR2e3DmsecYUejqlRWNscdEwqp/P7lLXyyZeSbOorRI4FbMeJqe5uSFWQkoSgKZy8s5LkfHseLPz2B3141nxSznpdWVUuxfyGEEEIIMeLanF7KGp0cNTEDnbb/nzv56Raau9x4/UdObcC1ZeEyCfPilEnw7t5F9bVXUP/jG3G8+RpFvdmvNa2JBW531juwWQxkpUZndSmKwthsK+VNzrjX9nVtPaSY9SSb9QRaWmh97E+4Pvs4eh69geRTlhFobqJn3Rd4y3ahy8pGmxwdKDZmZWFUVOoqGxJadyKcngD+YIj05PBr89WFA7f6AgncCiFGnqGoGH1hMc533gjX0x6m1JxMAGoH+H1Y0ezk9bW1PP7uLom/HMYkcCtGXG1r+K56QXr0Y1qpSQbmjk9n6aw8atq62VozcnfKhRBCCCGEANhcFa75N2ts7CymPLsFFWjsdI/iqg6stbvb0CgKs8fFDtx2r1oBQOq5F2KZv5B8TQ9ZriaqEwjc+oMhyhudTMxPiZnNOz7DhL6tiRaHJ+bx9e09kdrCgZZwZpguM6vfuJRTloFGQ9f/XsBfW41x/IR+Y/SZWRh0GnoaG+nxBgZdeyLaetednhLOuE0+YSm5d/8a4/iSEZlfCCH2ZZoablLWdP+9w54j56QTeWHaeZT3aOOOWdN7U6++vUfiL4cxCdyKEVfb1o0CcetrnTY3XKfq7fV1o7gqEQypvLiiCkeP72AvRQghhBDigNlc3QnAzOLYPRXy08PZpkdKuYRgSGVdeTsT81JIMcfuTN6z9gs0SVbsX7sG8/SZKH/5A1ds/Cc1LfFLHPSpaHLhD4b6lUkACLpcfOVvt/LdlX+m5pPl/fZ3ewK0u7yRxmT+vsBtRma/sbrMLKzHfIVgVyeoKsaS/oFbbUYmep2GVI+D3QPU1R2KVqcXIFIqQZucgnnmbDTmwWsFCyHEcNjOuwhtegbp13572HNkT59MzZhZ7HLEf3pkXXk7mt4bbu9uqB/2ucTBJYFbMeJq23rISjVj1Me+8zM+J4UJuSl8uKkRj+/IeUTtULdyRwsPv7md5z+tONhLEUIIIYQ4YDZVdZCWZIhkee6rL4h4pARud9Z14fL445ZJCHZ14isvwzxnHoo2fH2us9tJDbqpaR48+Lmzt77tpPzUfvu0Viu6GXMAcGzb3m9/XxO4vmB5sK01fP4YgVuAzB/8hJRTzwDAEC/jVqsh1eugrMEx6NoT0eaIDtx6d5cRch852dhCiEOPPieX4ieewTJn3rDnUBSFsZkWqhu6YpZB8PqDbKxsZ/ZYO2OzrHy4qRFfILQ/yxYHiQRuxYgKhVTq2nooyBj4DvWpc/Lo8QX4dGvTKK1MlFa0A7Bie8tBXokQQgghxIHR7Qmwu9HJ9KK0uE26+gK6fU2zDndrdvfWty2JE7h1ODBNm4Fl/qLINp3djkEDjua2QWv97qwPB0j3zrht+r/7aHn4QQDSrvs+AL6G/nUW9zQmMwMDl0qAcCDCctTRZH7/hxgnTOy33zBmLOm/+BWbsqZR1jBSGbfhUgkZKSaCLhd1P/wurY8/MiJzCyHEgeKrruLyf9/O3J0fxyxVs7m6E18gxLzx6Zw8Ow+Xx8+qnRILOBxJ4FaMqDanF48/SEHvXfV4TpqZi16r4S0plzBq1pWHL+pr2rqpTbARxUC+KGvl1//dRDAkRc6FEEIIcWjYWttJSFWZXmyLO8ZuNWDSa4+YjNu1u9sw6bVMLbTF3G8oLCLv3t+QfPyJkW3aNDt6rQarzzVoAHtnvQO71UhGSrh5l6qq9KxZjb8h/NhtVl4GXp2RUHP/ruV9TYvze5uh6TIyMU6aisZqjXs+fVY2ySeejDap/xiNJYnsRQswZaSPWKmEvozbjBQj/t7GZIb8ghGZWwghDhRNcgoGDST5uqlo6l/2Zm1Z+AmHuePTOWlmLhpF4d1SKZdwOJLArRhRfRdn+zYm21eKxcDRkzMprWinoWN0L5pdHj+vrK7h6Q9388ib23ng1a3Ute1/IPNQ1tnto7LZhd0afgRs+Y79v9P2wvIq3t1QT+Mof/2EEEIIIeLpa0w2I059WwhndeanWyKP8R/OPL4gW2s6mT02HIhNlDbNjk6rYPW6qGmJfx3s9Qcpb3IyKX9Ptm2gpRnV48ZQVAyAXqelOyUDfUf/68v69nDJgb7yFGmXXEH+/b+Pmw2diFBPN7OSfFQ0OfEH9/+x3zanF61GIdViwF8bDtzq8wv3e14hhDiQtCkp6HUakvw9VDb3D9yuK28n1WKgJCeZjBQTc8ens2pni/S8OQxJ4FaMqJrW8AVwQcbAGbcAp83JB+Dt9aN71+f1NbU8+NpWnvqwjP+uqOLVL2r438rqUV3DaNvQWybh8uPGYdJrWbG9eb/mCwRDkT+M2pzyi18IIYQQh4ZNVZ2Y9FpKcvs30tpbvt1Cc5fnsK/3V9PaTTCkRgVW9+bdXUbdT2/GvWF91HZdmh290YAp6KF6gCexyptcBEMqE/P21Lf114Svmw2FRZFtm4+9iOdmX9rv+Nq2blLMepLjNE0bjoa7fs7J7/6ZQEilKkawYqjanF7SkoxoNQq+3oxbfYEEboUQhzZFq8Vgs2HxdVO+zxMInd0+djU4mDvOjkYTvlF28qxcAiGVDzf3fzpCHNokcCtGVKIZtwDzSjKwW418vGV0f3HU9F6cPvSNRTx383GkJRki3YePVOt7A7cLJmYwb3w6m6s79+tO2656B57eemhtzv71dIQQQgghRps/GGJbbSdTC21oNQNndOanWwip6mH/5FDdPs2/9tWzbg3eHVtBE/1nn3nOPIr+9TKbs6dHro1j2Vnf15hsT2DYV10FgL434xbAWDKRKl0aTrc/6vja1h4KexM6gi4XzQ/+H90rlyf68mLSZWZi8bjQhgLsGoE6t21OL+kp4afS/LW1oNGiz8nd73mFEOJAM6SlkRby9Mu47SuTOK8kI7LtmCnZmPRa3hnlxLl9uX2BQWuri2gSuBUjqq6tB51GIdtmHnSsVqOwaGIG1S3do1ouobHDjcWgY2phKtk2M1MLbZQ3OXH7AqO2htFWWt5OVqqJvDQziydnEVJVVu1sHfZ8Gyo7Iv9ud0nGrRBCCCEOvl31DnyBEDMGqG/bJ89+ZDQo6wu6FsZ52s29fg2K0YRp8tSo7YpWi8WoJyvVRPUApRJ21oUbk03YqzGZryYcuDUUjYlsy0nWY+9po7F6T4Oyrm4fXT2+yNoCTY24PnwPX3Vl4i8wBl1mFgadhhSPg90Njv2aKxRSaXd5SU8OB25DPd3oc3NRdLr9mlcIIUaDNjWVtJCbqpbuqN4za8t6A7fj7ZFtJoOWE2fksr2ui83VHf3mGg0eX5ArH/iM83/9IXf9s5T3N9Tj8vgHP/BLTgK3YkTVtHaTl24ZNMuhz6KJmQD7FUQcqoYON9k2U6S21rQiG8GQyvbarlFbw2hqdXioaetm9lg7ihIOlivA8v0ol7Chsj3y77YYHSyFEEIIIUbbpt4yTtOL4te3DfV00/3FSvLTwkkGh3uDsr7199WQ3Vuw24Vn+zbMM2ej6PuXKnB99gkL3ZXUtHYTitNsdme9g6xUU6RPAkDqGeeQ8Z2b0CYnR7YVOWr57spH6fjow8i2mt4n8YoyewO3reEauLqMzKG+zCi6jEy0WoXsUDfrK9r3K3Ors8dHMKRGArd59/6Gggf+vF/rE0KI0ZL53R9Qdu3P8QdDkb49qqqydncbhelJZKVGJ9RdfMwYFOD5TysOwmph+Y5m2l1ebEkGPt3axK/+u4mrH/yMsv28CXekk8CtGDGBYIjGTjcFcR7VimXuuHR0GoVVO/e/WVYigiGVFoeHnLQ9v8D6Lu6P1HIJffVtZ48N322zW41MLbSxpqxtWHXdgiGVzVWdTOitHdfm9I7cYoUQQgghhmlTVQdajcLUQlvcMa2PP0rTL+8kc3cpcPgHbmvburFbjSSZ+meIejZtgFAQ89x5MY9te+JR5u74GI8/SGuM0lceX5CqFhcT86Lr5xrHl5By8mlR29LGhGvCumvrItv6MnkjGbct4aQBXWZWoi8vJl1mFgpwQr6OymYXP3tmHR7f8IK3bY7wdWxf4BaIGeQWQohDkT4nl/wJ4bI1FU3hcgmVzS5aHB7mlaT3G1+YkcSxU7NZuaOF8qb9LzUzVO+V1qPVKPzpW4v490+O5zvLJuPyBLj5b1+w5QiNx4wECdyKEdPY4SYYUhOqb9snyaRjRnEapRXtw77gGopWh4dgSCU3bc8aJ+SloNdqjthfFKUV4eyTvsAtwFGTMunxBaIyZxNV1uCgxxdg4YQMkow6KZUghBBCiIMuFFLZUt1JSW4KJoM27rieL1YCoN34BUa9lvoO92gt8YCobeshP861t2frFgDMM+fE3K+1p5PsCwdXY5VL2F7XRTCkMjl/T2OykM9HsLt/Q7CcsfkENFr8jXtKJfSVcSjuzbgNdoavSbVp9n7HD4UuPVyz8aQxFs5aUMj6inZu/cdaerxDL3vWl4CQkWLCW1lO15uvEmhv26/1CSHEaAk6nRR3N2AMeKhodtHtCfCrFzYBcNzU7JjHXHLsWAD+OcpZtx0uL2t2t7GgJIM0qxG71cj5i4v51RVzCYZUfvLUGtbtlt+/sUjgVoyY2t6MhaFk3EK4XIIvEKK0YuhBxKFq7L04z90r49ag0zAxP4WtNZ1xHxM7nK2vaCPPbomqO7x4UvgRtQ82NsQ7LK6+r9PMMWmkJxtjZmgIIYQQQoym6tZuHG4/M4rjl0kItLcTcjnR5eaRddOPyUszUztAY65E/OOj3fzjo937NcdwOXp8ON3+uEkTKWeeQ/Ztd8ZttKVLs2Pq6QJVjdmgrO8P6Nnj9mRteTaWUnX5hTg/eDdqbEaqhS6zDU1rU2RbdWs3Oo1CTm/CRKg34KtJsg7hVfZnGDOWMf98ibQLLubGM6dw/lHFbKzq4LZn1g35Wr61t+RXRooR97o1tD32MIHmpkGOEkKIQ0P3Zx+j/c3PKHA2UNbg4O5/b6C8yck3lk5g1tjYN8km5acyd1w6H21uHNVeQx9tbiQYUjlpVvT/SXPHp/Obq+aj02q47Zl1rC+X4O2+JHArRkxtb02VoWTcQjj7ExiVcgl9WRV7l0oAmF5oo9sboLKlfwbB4ayp001Dh5vZY6J/aY/JsjKt0MY7pfX867Oh3Wnb2PsY4vSiNOzJRtqdknErhBBCiINrW2+vgmmFqXHHuEvXApB28eUoWi0F6Uk0d3nwB4deOgrA6fbzzEe7ee6T8oPSIbumdeCkCX1WNkkLj0LRxs5A1qbZ0SsqZr87ZsbtuvI2koy6qFIJvupwY7J9g8FajYLHlom+sxU1GH4valqie1+YZswi5cxz0VqHluSxL0WrRWMyhf+tKNywbBLHT89hU1UHDZ1Dy6Duy7hNTzbiq60Jv7b8wv1anxBCjBatzYaiQJExwIodLawpa+WMeQWRrNp4Lj12LMGQyr8/qxydhQLvbmjAYtBx9KT+5XKmFdn43TXzmVGcxvjclBhHf7lJ4FaMmEjGbZyutvEUpFvITTOzamcrqhq+Sx4Mqeysd0Q+HylNvRdzObbowO203jq3wymX4HT7cfQcmsHL0kh92+jsE0VRuOeyOYzJsvKXd3by0qrqhOYLhlQ2VXYwOT8Vk0FLerIRl8d/UP5YEUIIIYTos6MuHLidlB8/cKtNs2OZvxDz7Ll4K8s5evV/MPjckSeyhmrljhYCIRVfIBRpjDaa6trDwdZYpRJUVcVfX4fqj9+tW5uWhkajkKm6+2Xcujx+dtQ5mD3WHtV02FcTvmbUF43pN18oPRsPWgJdXfgC4d4XRXv9XWA9+lgyvnEdit4wpNcZi2fbFlyffQKEr2v7vu6dQyzhFSmVkGzEX1eHJiU1qumaEEIcyrSpNgAKjeG/xxeUZHDjWVMjjdjjmTPOzqT8VN5cV0dX94GPZdS0drOjrotjp2XHLWdUkpvCb6+eT4pZ6ozvSwK3YsTUtnZjNmixW4d2MaYoCkdNzKSpy01VSzduX4CfPbOO6x9dwcYRvghujJNxO63IBgwvcPuL50v51iMrcHniXxgfLOW9Bconx2jSkZpk4LdXz6cg3cIfX9/Gm+vq+o3Z1+5GJ93eADPHhAPBfY0cpEGZEEIIIQ6mXfUObBYDWammuGMsc+aRc/vd6NLS8FWUk7NtFXMa1g+7QdknW/c8Ur/2INTlq41k3PYP3IYcXdTccC2tf3kk7vGGwmLM02aQazdT1dIdlTCxoaKDkKoyd3x0cxtfdSXaNDtaa/9yB80nXcivj/khPUYr9e09BENqpDHZSOv417O0/OkPkTWnJYX//ujoHto1aZvTi16rwWrS4a+txlAg2bZCiMOHxmYDYE6mjlNm53HHV2dF3WyLR1EUls7MxR8MjUqTsvc21AOwdGbs0j1iYBK4FSOmtq2HgvSkQe/uxLKot1zCO+vr+OHf1/BFWSsQu1HC/mjocJNi1mMxRnfetSUZKEi3sLk6HChWVZXH39nJ9x9fRXCAWlmqqlLW4KDF4eHxd3aN6FpHQktXuG5XZkrsP2LsViP/d/UCcmxmHnx1K27fwE0dNlb21be1R44HaHdJ4FYIIYQQB0cgGGJ3o5MJeSlxr0P3fYrLesxx6GxpLKxdQ33r0P9o7fEG+GJXK7PG2LFbjawpOwiB27ZuFCDP3j9w629sBECfG/+PZOuxXyHvl7+lYOYU2l1eNlbuSZjoqzE4d9yecltqKIS/tgZ9YVHM+bIzkkFRaOjck8FblLkncNv4q7to+t2vE3+BA9BlZKJ63IS6w+ex9SaOdAwj4zY92Yjq6CLU7ZIyCUKIw4o2xQZArs7HT8+f0S/OMZC+ZLamzgPbs0ZVVd7b0EB6sjFu3V0xMAncihHh8QVpcXjidrUdzMziNEx6Lf/6vJIddV2c1HsnprlrZH+JNHa4+2Xb9plWlEZDh5t2l5dnPi7nn59VsKWmk8YBCnY7PQG6ezvYvramhg2VB77B2lC0OjykJRkw6OL/qGemmjh/cTH+YIhNVZ0Dzrehsq++rQ2A9JTejFuHBG6FEEIIcXBUNrvwB0NMyo9fF6/rxX9Te9MN+BvDjVkVvQHDSaeS6nGgblo35HOu3NmCPxjiK9OzmTvOTnmTc9SfQKpr6yEr1YxR3/+x00BT+HXqsgfPbjpnYSEK8OLKqsi2teVtZCSbojJmg22tqF4PhhhlEgBykjTMbNhI+6ovIskXhRl7MnO9ZbsINDUm8tIGpcsM10gMtDQDRJ74G27gNuT1Yll0NOYZM0dkfUIIMRo0SUkoRlOktvhQ9D2hMtIxl31trOqgsdPN0pm5CWUDi/4kcCtGRJsz/MOePcDjaQMx6rUsnJCBAtx45lRuPnsasKcm7UjwBUK0OT396tv26QtGPvjqVp78oCwS7KweoNtwfXs4qHvqnHwMOg2/f3nLIVXvtdXhJSNOtu3e5vTe+Rqog6PT7Wfd7jYm56dG7uSlW6VUghBCCCEOrp31DgAm5MUP3PasX4u/oR5d+p5H/5OPPhYAbW3lkM/56ZYmFOCYKdnMKwnPuW4UyyWoqhp+2i0jdtJEX4Ban5MTd46Qx0Pr438mef1nLJqYyfLtLTR2uGl1eKhu6WbOOHtUBrMuM4sx/3yJtK9eFnO+nDQL52x7leAn70Yybgv3Wl+o24XGMjKlE3QZ4af1+gK3ab3XpB1DeAosEAzR4QoHbvXZOeTcegfW404YkfUJIcRoUBSFMf/8H1k3/mjIx2b1xkWau0Yu5hLLy739dE6bm39Az3Mkk8CtGBEtvRmXmTECt4GWZpwfvj/oXaAfnjuNp248hrMXFmIyaEkx60c0bb+ly40K5MbNuLUB8Nm2ZnLTzNx6wQxg4HINDb2B2/kl6Vx1Qgm1bT0883H5iK15f4RCKq1ODxm9WbEDGZNlxWYxsL48fsbwO6X1ePxBzphfENnWN7cEboUQQghxsOyoCwduJ+XFbkwWcvfg2boF0/QZUY2xkrPCAdeQ0zGk83l8QVbtamV6cRrpyUbmjc8ARrfObavTi8cfJD9GmQQgktk6UMatotPheOMV3Gu/4NyjigipKq+sro5cD84d3/+RVo3JhDY5doA8NzsVpzGZYHMjNa3d2K1GrKZwkxk1EED1etDEqI07HJHAbWsLAKkWAwrQOYQmOx0uHyoklOQghBCHquGUqgRINukw6bUHNOO2ucvNZ9uamV+SQVHmyPz+/zKSwK0YEX21VPe98Al2dlD34xtpefC3dL30woBzWE168tP33IXPtplH9O5PfaQxWewL3ML0JOxWI2lJBu6/aj6ze7NQBwzc9s6Zm2bhoiVjmJCbwr8+qxjS3f4DpbPHRzCkJnQxqtEozBprp6zBgaOn/wVvKKTy8qpqUsx6jp++J3PDLs3JhBBCCHGQ7azvwm41xr1Z7d60EUJBLLPnRW03pdl4a8rplI+ZM6Tzrd7Vgtcf5Lip2UC4WevYLCtrd7f1q6V7oPQ1VIvX/CvQ1oYmyRqziVgfRadDm5JKoKOdeePSKUxP4vW1dazYEc5inTMuujFZz/q19JSui/sa05IMdCXZ0bU1U9PiilpbqCd8Pa1JGqGM2+wcDGPGoRjCgXitRiHFYqBjCIHb1t7r14wUIz2l62j6v/vwVVWOyPqEEGK0uDdvpOuNV4d8nKIoZNlMNB/AGrevrK4hGFI5b1Hs2ugiMRK4/RJTVXXEHutvdcQO3GptaVhPXIouM4v25/6Bd3dZwnNm20y0OrwEgqERWWNjJHAbnXEbdLkItLej0Sj8/usL+PN1i8m3W0ixGEi1GCKPesXS0B6eM99uRqtROHl2HsGQOuJN1YZjsMZk+5o7zo4KlFb0z7pdW95GXXsPp88riKqjZjbosBh00pxMCCGEEAeFPxiiosnFhNzkuFlH7vVrATDPnR+1XaPTUTbhKKqT84Z0zk+2NAFwbG/gFmBeSQbtLi8VTa4hzTVctb3XpwVx+kvk/OJeCh97ctB5tGl2gh3h6+BzjyrC5fHz8ZYmijKS+l1Dtj/zJC0P/S7u+6woCv60TNSebkLdzqjGZCFX+H0ZqcCtPieXggceIWXpqZFtaVbDkJIn+v5+SU824quupPuzjwl1j87XTwghRorzvbdp+8vDhDxDD8BmpZppdngOyE1Hrz/I62tqybNbWDghY8Tn/zIZUuB227Zt/OIXv+DEE09k/Pjx5ObmMnPmTK666iqee+45vF4J3hxObn92Pef/+sMRmStSKqE308G9ZROqP3zHO/3Ka8m+5Q4Amh/4LaEEv0+yUs2EVJXWEWp81RjJjt0TuG159I9UXXEhrX/5ExDOWti73ENRZhJVLd1xf5HVd/SQZNSRbNZHzd2XiXswtUbKVwxeKgFgTm/X4HUxyiW8tKoajaJw1oL+nXbtyQbJuBVCCCHEQVHRFG5MNjE/dpkEAM/O7WjT7Ojz+tfXSzLq6HYnnqXp9gVYubOFaYW2qGvG+b11br8oax3C6oevtjfjNl5jYEVRBsy27dMXuFVVlVNm55HU28dg7vjobFvV78dXVYmheOzAE2ZkE1Ihzd1B0V4Zt5rUVLJu/inWJccNuqbhsiUZ6Oz2Jzy+7/o1PdlIqHtkM4KFEGK0aFNtAAQdXUM+NjvVhNcfxNGT+O/ORH2wqRGH2895i4rQSFOy/ZJQ4HbdunUsXbqUOXPm8Nlnn7Fo0SJuuukm7rnnHq644gpUVeVnP/sZeXl53H///RLAPUwY9Ro8/iDB0P7fXWlxeNBqlEhjgJY//oHWR/+051zjS0i79Ar8NVWDlkzo05cZO1INyhp75+nrnuivr8P51usABFpaYh5TlJGEy+OPWy+rod1Nbpo5knmQEwnc9ozImvdHS18WdHJiGbd5dgvZqWZK9wncNnT0sGpHC4smZvTLVgZITzZJ4FYIIYQQB8XOuvAfqhMHaEyW+/O7yb3zVzEzRc9e+RQXvXp/wud75qNy3L4gp8yOztKdUZSGXqsZtTq3tW3daDVKzBJgwa5OnB++j7+3zu1AdHY7qs9HqLsbi1HHqXPCwe25+5RJ8FVVQMCPccLEAefTjBnHbvtYVBQK9grcapOsWI87AeP4CYm8vIQ43nmT1icejXyelmTA5fHjCyT2tF7f9b0tyRAp5aCYYwfChRDiUBUJ3HZ2DvnYvhuQTSNc51ZVVV5aWYVJr+WUOUN7qkX0p0tk0AUXXMCPf/xjXnjhBWw2W9xxK1as4MEHH+R3v/sdt91220itURwglt476j3eQCRjdLhaujykJxvRahT8TY0EGuth5uyoMbbzLkLRaElZdmZCc2ZFfomMUOC2w43daow86u/67OPIvkBzU8xj+mpzVbd0R4LSffzBEC0ODxPzsiLbDq2M295SCTEaxsWiKApzxtl5a30dLQ5P5PG4V1fXoALnxqlLk55sZENlO75ACINOqq8IIYRInNsXwO0LYrcm9nSIEPvaWR9uLDZQ4FZrS0NrS4u5T2MwYPK4UFV10AYv1S0uXlheyYTcFJbNK4jaZzJomVGcxqaqDrz+YFRpqQOhrq2HvDQL2hhZTN7dZbQ8+Fsyrvse+tPOGHAe87wFaHr/6Ae45qQSSnKTWTwpM2qcZ9cOAIwTJw04n2nOfP7SEv5a7J1xq4ZCoCjDbqITS8+6NfSsXkH6Vd9A0eki1+qd3V6yUmM3I96b0x3OMEuxGAj1hJMuJONWCHG40aaGnzgJdnUMOtbx7lsE29tI++rlQLg8JYSbiA30/+hQbarqpKzRyTkLiyJNKsXwJRRl2blzJzfccMOAQVuAxYsX889//pMf//jHI7E2cYCZDeHArdsX2O+52pzeSGane8P68Pyzohs9KFottvMvQmMe/EIKws3JAJpGqFh2Y4c7ElhVVRXXpx+jSU4h6ZivEHI6YtaEKe6tzVUdo85tc6ebkKqSZ9/zeswGHTaLIVKW4WDa0zAu8T+G+8olrC8PZ4u0Ob28sa6OgnRLv8yLPn0Nytol61YIIcQQ3fvvjXzr4eUjVs9efPnsrHf0NiaLfaM62NmBZ/tWQu44T0MlJaOEQvhcA9c2VVWVP76+nUBI5XtnTIkZMJ2Qm4wvEIrcPD9QgiGV+vYe8jNiZ4f6mxoA0OXkDjqX9ehjSb/y65GyCn1Zt/s+1urdtRMAU8nAGbc5vdfvBp0mkoQB4Hz/HSouOJOe0nWDrilR+swsCIUItIXLU9iSwo3KEi2X0PdocLJZT7C7GxQFjWTcCiEOM5pI4HbgUglBl4vWhx+g4/l/oAbCMaDs3ptcI92g7JMt4Sc+zlpQMMhIkYiEArd6/dAi5EMdLw4OizGcCdDj3b8GZf5giA6XNxIgdJeuA0XBPHNW7PH1dbQ//w9C7oGDmzl9d39G4JeI2xegs8cXedTfV1WBv6aKpCXHou+9qI2VdVuYuSfjdl/1kWZn0Rd4uXbzAcm4rWvr5uXV1QmXJWh1erGa9JEAfSJmj+0L3LZT19bN9x9fhdPt54qvjI9blya9N3Ar5RKEEEIMRW1rNyt3ttDR7WNHneNgL0cchnyBEBVNTibmx88S6lm/jvpbbo4kFvSTHD7W1dy/xv/ePt3axLryNk6dk8+0IlvMMdbeJ9i69/PaejCNnW4CIZWC9NjZoYGm8DWtPjtnxM6pS8/APGtO3MzlPjlpZk7f8SZnNq+KunYMdXdDKIjGlNiTYAmtKSvcHC7Q0gyEm5MBCTcoc7j9mPRaDDoN1iXHYrvoUhSNPD0mhDi86DOzME2ZhnaQJwac770NQMb130fRhWMEfU/nNo9wqYTKZhdmg5YxWYPXWheDS/h/pg8++ICpU6ficPS/sO7q6mLatGl8+umnI7o4cWD1lUpwe/cv47bd6UUFMlJMqKEQ7o2lGMaVoE2OfRHds34tnf96lp41qwacN9msx6TXjkiphL4M2L4sANcnHwFgPfZ4dJnhUgeB9v41ybJTzRh0mpgZtw3tvc3O7NEZxDk2M+0uLx7fyF60P/dJBQ+9to1Lf/cxd/2zlA0VA/+B0dLlGVK2LYS/hkUZSaza2cqNf11Nc5eHH54zjZNnx69Lk957kdzmPLDZJUIIIY4sL6+uify7dJD/04SIpaLJSSCkMmmAxzv9DXUA6HP/n73zjnOjurf4mRn1Lm1fb3PvxjTbVNNDLwkphEAKkPBCEt4jpBAgkEZLAoSEXkMCAUKvpphqDLj3tra3d/WuGc3c98doZlerUdvVrnfxfD8ffz6yNJq5dzUa3Tn33PNTHstI49WwO/s5GGd53L9iN8x6Da44NXtGq5kWUBZxIzrKsXU+ulKFyeqyFCbjensAmpbHuLlguzrR+fOfIvj2mzm3c138XdT87ta8+6txGjHLsxez3c1pz0sZsrS5dDfxmgoxzkEyX0jCrTdcWLG5YJSF3SS+x3LcCXB9+9KStU1FRUVlvNA1TkXtrX+F+ahjs25DeB7BN14B43DCetIp8vPlNgMoiFEJpaRtIIL6cnNJ43EOZgoWbu+++25cccUVsNkyB0Z2ux0/+tGPcOedd5a0cSpji+TEjI5SYBwYkqWaHOgHCMmISRiK+ejjAJpG+JOPsm4DiJmrlQ5DSYqTSYXJJMet/YyzUXb5/8Awdz4sy09C07OvwLT4sIz30TSF+nIzOhQct1IBstphBbtqXKa0Y5YKdygBLUNj8VQXPt7Rh2seX4vVu/oVtyWEwB1KZF02mItDp5UhEGURjidx07cOwZmH517eUJY6hjdUeEVmFRUVFZWDmzjL4+2NXagvM0OnoVXhVmVESE7tWbX2rNtwPd0AAE2VcmyA1iG+N+rNng340fZe9Afi+O5JMzJqHgxlyssP46ovHkSkT3l8Vir6U2NMKVZsOMm+XmjKK2RHVS4orRbsvmZwnR15ty0Em0mHxmk1aDSm318IqSiK0gq3KfOFWywy7DCLn00gS1Hh4YRiHKzGwlemqaioqEwGhGgE/ldeQNI3+LsWXfMZkgP9sJ56OmJbtyC2fSsAMdbGadGX1HEbinHwhhNorFDdtqWiYOF28+bNOP3007O+ftppp2H9+vUlaZTK+GCWoxJG5wpwB8XlSOU2PbRV1Wh88lk4v35R1u01TicM8xciumEd+MhgnljgtZfRe9sfQLjBwVaV3Yj+QByEkFG1UXLcShm3mopK2M8+DxRNgzYYQOuzD8Ibys3oC8QyHLQ93hhoisoYNEvHKHXOrT+cQJlVjzu+ewQeuepoMDSFN9Z3Km4bjieR4HhUFOm4BYCzjhCXAN5+6eE4dm5V3u3lqIQCl6WpqKioqKi8v7UHkUQS5y9rwIIGJ7a1+wquBK+iIrG/LwQAmFFjzbpNsqcbjKss6xJ9YcHheGDJ5Qg3ZM9u7faKk/VSLYBsUI3TAQCsJ3MVVynxpYRJV8phOhxtdQ0M8xcWtC+NU4w+SPqyT54E33sb/XfejqS3sAmWiilV0ERCac8JEUm4LV3xL01VDaynnwX9dNEF7ZIdtwVGJUQ5uUBz16+uwcDfVROSiorK5MTz5GPwPf8MAMD7n3/B+/jD6P71NbJ4m/T5QFttsH3lTPT+6WYEXvqv/N4qh6FkdYWAwZhJqV6QyugpWLjt6+vLmV2r0WgwMDBQkkapjA/GVFTCaIVbqQhWRcp5STFM3gJkluNOAJIcol98BgCIbdsCz6MPIPr5p+BDg2JulcMINinIA9SR0uMbdNwmvV5wPd0g/KAQG92wLmuxhIbUBadjWFxCjy+KSrsBGib9ayQJt5Ijt1R4w6xcdXtqlRWHTy/D2mY3/Ap/G9kFPQLH7fRqG+65fCkOmZr75kRCapOacauioqKiUgiEELy6pgNGHYNTD6nF4qkusEkBOzv8B7ppKpMMTygBhqbksYgSXE931pgEADCXu9BvqUJYYLJuIzmRhhbbUkKXcu8mfP6c240WqSBsNvdv1a9uQOXV1xa0L0qrA22xgvdndxzH1q9FeNVHoE2FFe5iHA4QNpFW+FeIRACNFpROWWweCYzFgoorfwrT4UcCGFqcLP99Ay8QRBJJ2Ezi/S3bsi/NnaaioqIymYh8+gkiqz4GALgu/h60U+qR7OtBz02/Bh/ww37mOWh87Cloyiugq6sH29Yqv7fSboA3nCjZBLoUM9mgOm5LRsHC7ZQpU7Bt27asr2/ZsgU1Nfkrl6pMHMxyxm1pohLKDRTcjzyA+K4d+Y991DEAzSC86mPw4TD67/4zKK0Wdfc9Ao1rUDCsShUoG+0MUK8vBoamUGk3IvDy8+j4nx/IFWgBoP/uP8P3zL8V31tfLhUoGxSUCSHo9sZkkXYo1bJwWzrHrSAQBKIsHEOcFacsqgEvEHywtSdje3fqBmMkUQnFYtIzMGgZVbhVUVFROYjp9kbx+2c34e9v7My77c7OAJp7gjjlkFqYDRrZxbhRjUtQKRJvKAGnWZ+1gKoQi4G2WKCtzR77ZNZScEU9iPX2Zt2mPxCHWa+BxZDdxJJ0D0C3TVx9yOWp7D1a/BEWFAaFytHCuFxp4+LhxJt3Q1ffWHBhMcbuAADwAb/8XPmVP8GUO+4e07xDvZaBWa+Br4CM21CMAwBYjTqQZBKETRQsTKuoqKhMNBiHQy7USBsMqL/3Ybi+dwW49jZ03/gr8MEAqJQRU9fYhORAv5w9XmkX9Qt3sDSu27Z+UTdpqszvuPU+/SQ6/+8qeP/9BOLNu0EEdfWVEgULt2eeeSZuvPFGxOOZH2YsFsNNN92Es88+u6SNUxlbZMctO9qoBPGcMHc2I/j6y4jv2J73PYzVBudFl8B22unwPHQvePcAyq74MXS1dSCEILZ5IwghqJKqHA7Ji/39s5tx+4tbi2pjfyCOMqseDE2BDwXlNkhoKirlC91wpGyWoQXKglEOUTaJGmfmAK/SbgRDUyUVbkMxDrxA0pbEHTO3CkYdg3c3Zwq3A6n4ipFEJRQLRVEos+rhKdGFXkVFRUVl8sAmBfz7o3247B+f4qPtfXj5i3Z0KhT0HMqrqaJk5y6pBwDMqrXBqGPUnFuVovGFWbis2cVL2mhEw4NPoPzHP8u6jYVO4iefPwDTey9n3aY/EJcrb2cjtnULqB2bAQD8GAu33rBYVItREKxj27Zg4IG/gy0is1bjKgPv9SpGkyW9XvDuAehnZo+SGI5x8WFwfus7aVFkmvIK6KdNL3gfheJ96p/ouPpKue0Osw6+AqISJOHWZtIOKZymLutVUVGZnNBGI4RIGJ5/Pio/5zj/a3Bd+gNw7W2IfPqJ/LyusQkAwLa3ARhcTTJQopzb9oEwtAyNagWtZDiMzQ62ZR/8zz+D7l9cDX8q7kElnYLT2G+44Qa8+OKLmDVrFn7yk59g9uzZAIBdu3bh3nvvBc/zuP7668esoSqlx6QrXcat06wDt20LAHGwVgjOr38Lkc9XI/zxBzAtOQrWU8UM5cArL8L7xMOovPY3qGoQ87mkQl99/hg+2t4LZ5EOA08oIbtjhVBQXKo1xDWgqagE27IPJJnMKOQwpcwECoNZLQDQnRJla12ZjluGplBhM5Q041bK6hrqrDDoGBw3rwrvbOpGhzsiO4OBQTG9PM9NRqlwWfVpfx8VFRUVlS8/CY7Hzx7+Ant7Q6gvM+OUxTV4fOVevLm+Ez/8ymzF93jDCXy4rRcLG52YViXmkmoYGosanVi/z4M4y8Ogy75kXWViQgjB/St2IxjlUOUwoNppwqImJ6a4xs7BSAiBN5zA1Or8SzFzuTwtTjt6KAoIKoutgkAwEIjjsDz5tol9zZAOI6RMAmOFL5xIW4U1lPiuHQiteAPWk08reH/2874G+3lfAwQBYNK/f4m9ewAA+pnK32klTIsPyyj6y7a1grZYoCkrL3g/hcCHguDaWsH7/dA4nXBYdOj25I8rC0Ylx61WjHEAQJtU4VZFRWWSQovXbmrYNdzx1W9AP30mtA1N8nNaSbhtbYFhzjxUSqucA6XRL9oGIqgrMylOLg7HfvZ5sJ1xNhLNuxH54jOYjlhakjZ82SjYcVtVVYXVq1djwYIFuO6663DBBRfgggsuwG9+8xssWLAAq1atQlVV/kJGKhMHfdiH2mAXoqOMSnAHEyi3GRDbtAG0zQ5d09SC32s87Ag4LvwWKq66Wh5UW088GbTFCs+jD6BSK86eS7M/H2/vAyAWZSg0g4XjBXjDCZSn3Kd8KATGak0bxGsrKgFBUFwmptcyqHYa0xy3Un5tTZYbklqXCT2+6KiLqklIWV3Ds8xOPUTMbHtvc3fa86PJuB0JZVY9AlEWHK8ubVBRUVE5WPhkRx/29oZw7pH1eOiqo/Ht46ah1mXC2xu7s/4evPhZGzhewIVHN6Y9f8hUF5ICwbZ2NWNyMuIOJfDCZ214d3M3/v3Rfvzl5W349ZNjW7Q4FOPA8QLKcuTbRtetgf/VF2VHpRJWow5RrQkkHFJ83Z8a31Q6ctdvYPc1g9Hr8fAR30fznGML68QI8Q2pezCcZJ8Y+aCtLjzCznTo4TAdenjGDT8AJJp3AyhOuFWi69djU/xLW1EJAPLKOZdZj0BUXKmWi2BMHFvbjFoIUXFcTxvVqAQVFZXJSdl3L4Pru5fDedElGa8ZDzlULkQJALqGJuimTgeVWhUhRSWUokBZnOXR54/lzbcV4nEk3WKNLIphYJgzD2XfvWxMVmZ8GShYuAWAxsZGvPnmm3C73fjiiy/w+eefw+12480338TUqYWLdSoTA+65J3H5uicQi478C8oLBO5QHFVGCmzLPhjnLwRFF35a0TodXN/5npyFBYi5WK6Lvwve54Vu8+dgaEp23ErCLVB4BosnFRsg5b3ywQBoa3r1YU2lOOmQLS6hodyMLk9UHgT2eMX2KGXcAkC1w4gYy8uz+aPFG1auHnzIVBfKrQa8t7kHwpAB6kAwAb2WgcVQsKl+VEg3D14151ZFRUXloOH1dZ3QMjS+f8pM6DQ0aJrCmYdNgT/K4rNdmb+n0UQSr67pQF2ZCUfPrkx77dBpZQCgxiVMUqSc+4uPn4ZHrjoaR8woR7c3ijg7OnNAIcd0WbMLt+FPPoT3sYeAHI5bs0GDqNYIOqIs3BZSmIzwPBL798Ewey48rjr46bGbOI+zPKJsEs4sjluutweUyQTaYlV8PRuEY+Wb6KFYjj0eru9fAV1Do8K7lGG7O9Hxsx8h8Por4r55HiQWHRNHK1NeAWBwDO+w6CAQgmA0d87t0KgETVU1qn51g1iDQ0VFRWUSomtsguOCCxUn4IajraxC3V33wnriKQAgx1OWIiqhwx0BAdBYkft6H3p3Bdp/+D3ENm8c9TEPBooSbiWcTieOPPJILFmyBM4hyr3K5EKbEi+T4XCeLbPjj7DgBYIarRi3oEkNnkaL+bgTAJpBbM1nqLAZ0B+Ioz8Qw45Ov2y5L/TCMtx9SmIxMDZ72jbaKXXQTZshLhFToKHCAo4X0Jty2nZ7cztua1IRCt0likuQHLcOc/rNCUNTOHlRNXr9MWxr98vPu4NxlFv1Y1oAYiiSm1kVblVUVFQODtoGwtja5sPy+VWwGQcLNn3lsClgaApvrO/KeM8b6zoRSSTxzWOnZhSTml5thcWgPWiE2yQvYF/v2C6nH0+k3/8alwlTq6yYXy+Oszry5B2P6pjypHZ24Zbr7QHjcOZ0UmoYGgmDBUxUeTws1VmoyiHccl2dIIk49DNmokaIgOnvzrrtaPFFxL/18FVYQ9uirZlS1BiQEIL2K76Lvj/fmvGarnEqHOd9LSNKLBeURguuvU12/wox8W9Im0tfYVwrmS/6RXOHFKfmi+QWbiVzhc2kBWOxwHzUsdDVN5S8fSoqKioTHZtJC72WQV8JhFupoHtjZfbrPeF5BF59EbTFAv2ceaM+5sFAwcJtPB7Hbbfdhl//+tfo6ckshqQy+WAsFtDU6IRbyfXqcFpgv+DrMCw6pGRtMy5ajNjmjagzibZ9yW17woLqtGMX2kapqETD40+j+rd/TNvGdNgRqLvzHzAuWqy4D+nC8+h7zYgmkujxxWAxaNNuVodSnXLiSkLvaJGKLCi5K05ZLMYlvL1x8CbZHUzkLaIxWiKfr0b39b9AYt9elKXcLm5VuFVRUVE5KHh9bScA4Kwj6tOed1n0OGp2BdbvdadlvSd5AS981gaXRY+TF2Uu4WZoCoc0ObG7K4hgrDSrVSYyr67pwA/v+2xMhc3xRHK/SuOBulTufodn7PonjY1yFSfjerqhKSAyIGm0AEkOhM90CEuO2wp79qgEIvAwHbkMhvkL8LV1/8bRHz6Z95gjxZdlFRYA8OEweK+nKHcsIGYA6xqbxHoPQ/4GfDgMfgT3CdJKOj7gBwAIEXEftKX0wq1mWFSCJGhLf6dsSI5bq1ELwil/9ioqKipfVqLr1qDvz7cg6fOBoihU2gwQWvdCYHNfO/PRlqp705DDcRtZvQrJgX7Yzzo3rYilSnYKFm4vu+wyNDc3o6ysDKeccspYtkllnKDNFlAUJQ+mRoLkZnXVVqDsu5fBfOSyUjUP1pNPg/3Mc1BtYRCOc3hrQxcMWgZnHV4HYHAgnb+N4sBectxSFAVaV1xxs5MWVuPoOZX4aHsffvzA52jpC2WNSQCAmlQFxZ4SOW6lwadDoSjbtCor5tU58P7WHgSjLGJsEuE4N+b5tqEP3kN8+1YwdrssYIfjoyt0p6KioqIy8UlwPN7Z1I2GCjMWNjoyXj/r8DoQAG9t6JSf+2BrLwaCcVywrAF6rfIyvmWzKyAQgivv+wyf7VaOLvqysKtLLITV4y3NBO+BxisLt+I4pb5MvGHrHENhWo5KyOI85cNhCMEAtDVT8u5r1dHfwiPn/FZxiamU+VflyD6u0jdNQ/X1N8N85DJwRgt08bEUrKW6BwpjWSLA8c2LYT6q+Ixd/YxZIGxCrjIOAKF33kLbpd9EfNeOovZF6/WgjCbwqYJvQkr8HZOoBKcLFVdfC9tXzgAAOMzimNQfzm0mCEiOW6MWwbffRMvXzkJs+9aSt09FRUVlIsL19SLy6cdgW/cDAJb1bsA5796LwOsvj2q/7QMR0BSFurLs13v/y8+D0ulhO+PsUR3rYKJg4faDDz7ANddcg1/84hdobm5Gf//EG1DffPPNoCgq7d+cOXMOdLMmLLTZDIrCiGbSJdyBdFG0lFiOW46yy34EZ624BKq1P4xlsytkF0fBwm1qu3KbHnwohNBH74Pt7szYzv/Cs/C/+JziPvRaBr+/aDGu/MpsdPuiCMa4PMKt5LgtlXCbgJahs2bWnr+0HmxSwFsbuuCWM33HdvYq2dcLxumCprwCeg2NZR1fQOhsH9NjqqioqKgceFbt6EM4zuHsI+oVl2MfPqMcVXYj3lzfhWdXteD9rT14ZlULjDoG5xxZr7BHkdMPnYKrzpiDUIzDDU9txG+f3ohAnuXOk5X2lCMl33LuyYI3nC6i1pWLE9gd7rETpoe7fIeT7BNXCGpr8jtuLWYDIlkmnwcCcdAUlfU4wxFMVmgTEZAs8VujxRvOHpXAWG1wXXQJzEuKN1LoZ84CACT27pGfi679HJRWK8aJFQljs4P3+wEAQjwG0DRoS+mFW4phYD3xFOgaxXorsuM2z3drqONWKl6nFidTUVE5WNA1NgEA2LZW8JEwjlj7MggBIq1tud+Yh7aBMGqcRug0ylJj0ucDu68Z5qOPzYivVMlOwcLt8uXL8be//Q1/+ctf0NDQgMrKyvxvOgDMnz8fPT098r9Vq1Yd6CZNWGiLFUSjhRAf+fJ2yXHr2LUenT//adpgr1RUWTSgBXH50vL5VXCYdWBoSj52PtzBOCiIxSu4rg4M3HUHomu+yNgu9NH7CL67Iut+KIrC149pwl0/WIJpVVYsm509z9du0sKoY0rmuPWGWTgtuqx5ZccvqIbLoscrX3TIhdzKx9BxSwgB19MtL8XTd+7DSfs+ANNa+s9fRUVFRWViIRUlO/UQZUGMoSmct7Qe3nACD72zB3/67xa09odx5uF1sGaJGAIAmqbw1aMa8fjPjsHy+VX4dFc//vXhvrHqxgFDEIgckeD/kgi3nlACDE3BbhJdoEadBuVWw5hGQQw6T5UFVUqjhfm4E6Cfld/EUcEF0bh/Pbj+vozX+gIxlFn10DDKt01EENB9wy8ReO1lAIBgtgICAR9WLnY2WnJFJYwG/YyUcNssjuX4UBDx3TthXHxY0SvVAIBxOGTHrXH+Qkx94Q3YTjuzdA0eAiFENqJIf5d8UQnBKAeTTgMNQ0OIihMMtLn0wrKKiorKRGSocOt76km5jlC0urionaFwvIAubzRnTIIQjcCwaHHWiEoVZQpOmX/00Udx9913o6+vDytXrhzLNo0KjUaD6urqA92MSYH56GPxyiW3YXdqud5IkPJjzWEvwvuaQQgpVfMAAJF1X6Dx9lswo+oUtNfMxZKZFWBoCuVWg+wszd/GBJwWPbQMDTYoFgJhrJmVdjUVlYhv2QQiCKDo7HMa8xscePiqo3Mek6IoVDuM6ClRxq0/wmatHgwAWobG2UfU4ckP9+G1NR0AxsYFLcH7vCCJOLS14vJDLU1BI/BIxEojVKuoqKioTEz29gSxpc2HkxfVwGbK/rv0zWOn4qSFNegPxDEQjCMY5XBKFqF3OOU2A278xiHYeefHWNPsLlXTJwwDwTjinDgh/WUSbp1mfVrRufpyE3Z1BUAIGZNiqZ5QAhaDNqurR9fYhKqf/7qgfdX6O3Hs9lcR3nUknKliVxIDgThqsxSjBQCuuwvxbVtk4ROpMWbU7YVtDNxEvhyO294/3QwhFkXtH+8oer9MWTkYp0vOio2uXwcIAkxHLh1RO13f+V5abixFUUAB1c5Hgvu+vyH07go0Pf2CXMg333crFONgM4kTSUIk5bg1qY5bFRWVgwPGagPjdCGxvxmURgt+6iz8ofJc/P6wwzFrhPvs8kTBCwSNFdnzzHVT6lD7+9tGeISDl4KFW5PJhN/85jdj2ZaS0NzcjNraWhgMBhx11FG49dZb0dCQvUJoIpFAIjEoAAaDX54Kv/mgKApGHYMYy494UD0QFAfNTEwc8DAlrharq2uAho1jzsBu1Cw/HgadOOCrsBfu4hgIxuXYACEkfr601ZaxnaaiEoTjwAcC0Dido257jcuEL/YMgBeIPIM1Eggh8EdYTK/OFJuHcvaR9Xjq4/34dJc44B7L4mRct1gITcqN01nEga4QH30lShUVFRWViUnbQBjX/WsDGJrCBUvzV1+vsBtG/FtEURSOnFGON9Z3otsbzSmcTTakwh1AflfgZMEbYjOKhNWVm7GxxQt3KDEmk8neUKLg+IJ8aOyiwBp1ezF0BJjgePgiLBZPdWV9b2JvMwBAP12ME6CsdggUhYgvgMzR5ujxhVlQgOxuTmtL825ohgnPhUJRFOr+8ZA8lo+u/RwAYDp8yYj2Z1w4WLA40bofXEc7jIceAWYMCpQxTvHzSQ70w9TQBC1DywJ3NoLRIcJtLOW4VaMSVFRUDiJ0jVMR37EVTU89j4HtHSAv7kW/f+T38+0D4sqHxkp19UKpKTgqYTKwdOlSPPHEE1ixYgXuv/9+tLS04LjjjkMolH2p0q233gq73S7/q6/Pnr32ZUOIxzG9dQOm+NqR4EaWw+VOiaJy0QEFQXQ0aKtrYJo+HSfyHbjy1MF8rQqbHoEoiwSXuwIsLxB4w4M3DHzqXGBsme3Upga6SYVlciOh2mEELxA5Y3ekhONJcLygWJhsKGVWPZbPH3Sb58u45Xq65Wq/xWKYtwD1D/0TlhNOEv9vFS/OQlx13KqoqKh8GehwR7C93Y8kL44P9veFcM2jaxGIsrjh64swt94x5m04YkYZAGDdXs+YH2s8kW5sgC+H41YQCHyRTBG1oXxsC5R5w7mF24F/3IWB++4paF9ahwMAEPP60p6XVpZV5piASOwTowX002cCAIJLT8IfT7gOifric2ELwRtJyLFhQ+GDAfB+H3T1+SdVsjHUgCGEQ9DPmjNiMwMhBEIsBpJMIrJ6Ffr/eht4z9g46DUVYoQf198HiqLgsujhzTMpMtxxS+kNoDQFe5pUVFRUJj3W006H69LLQAjgqKnEca2rYHzt3yPenzQx3ZDDcdt3+x/laCGVwino1+nKK6/EDTfcgLq6urzbPvvss0gmk7j44otH3bhiOeOMM+THixYtwtKlS9HY2IjnnnsOl112meJ7rrvuOlxzzTXy/4PB4EEj3hKOxYL3n4LHtRBRNim7WQt+PyFwhxJY2OiE0BMCKGpMlhiZjzoGbOu/YO1sBlyLAQwOoN3BOKbkqFjoCyfAC0R2/MiOWwXhVhr0JQf6gdmjL2pX6xILlPX4oqjOUcgsH4NL4vLni52/tAHvb+0BQ1NwKDgxCM/LFZPZ1v1wP/ogav94B7TVhS1flaBoWha6AUBnFj93ojpuVVRUVCY9hBD8/PG18IQSMOk0OGSqE9vb/Ygmkrj5W4tx9JzxqXNw6LQyMDSFtXvdOHfJ5BmbhWJczizftn7xxsak03wphNtAlAUvkAwRVSom2+GO4tBpZSU9ZoLjEUkkc46NouvWQFNVWHyawSE6bhP+9PiwvpTzqNKRfRzH7tsLymSCJjWWMhn1AEUhmlAudjZa/GFWcTKfbRcLymgbRp5PKEQjCK/6GNrqGtT87lYQbuTnZ/D1V+B59AHU/OnPgxmyY+C2BYaO4QcAAA6LLqfjluMFRNmk/D2tvPrn4CNjl8esoqKiMhGxHH2c/NhqFDDduw92/8ivhVLhVWnidjhJrxeRz1apeeIjoCDHbUVFBebPn48zzzwT999/P9auXYuuri54PB7s3bsXr776Kn75y1+ioaEBd911FxYuXDjW7S4Ih8OBWbNmYe/evVm30ev1sNlsaf8OFmiTGRRFwZCMIzaCwWUonkSC41Fh04MPhcT9jUF2lXnZMQCA8OpP5OckIXYgT86t9Hp56maCtlihrW8EY83MHNM1TYPtjLNHvMRsONKyzpuf2Yzr/rUe//pwH3pHUKxssAhF/uWA8+rtWNDgxLQqa1rOHCC6jTt/+kPE9+wGADCuMvDuAXTf8EtwvT1FtSm+czsSLfvl/xutFviNdsQ1pVmyqKKioqJy4PBFWHhCCcyotmJqtQVrmt2IsTx+/+1Dx020BcRq73Pq7Ni43wOOH9nKoNFACEGfv7jf7c0tXlxw6/tYuze7s7DNHYbVqEVDhflLEZXgTQlkw8cp9eXiOGgsCpR5QuIxszlu+XAYvN9X8MS03iW6Srnhwm0gt+NWYFkkmnfDMGuOXB/BSiWxoG8bYs1jU7DVF2YV823ZDlG41TU0jXjfhOfFvNiV7wAAKO3IC6BJJgk+4B/MkC1xpJqEvGoulc/rNOvgC7NZa2+EYhwAwJYSbhmHE7op+Q1KKioqKl9WrEYtYhoj6Fh4xHWL2gbCqLAZYNIr+0OHr1BRKZyCHLd/+MMf8JOf/ASPPPII7rvvPuzYsSPtdavVilNOOQUPPfQQTj/99DFp6EgIh8PYt28fLrnkkgPdlAkJxTCAwQBjMo5IInfkgBLu1GC2wmaA8+vfkivHlhptQyO0DY1g9+2Vs3jLU9EH+WIIpCVuktDruOBCOC64UHFbXX0Dyn/0k5K1e/FUF7517FRsafVh434v1jS70dwdxO+/fWhR+/Gl3DiOAhy3FEXh9ksPh6BwsY1t2QSuuwvRdV/AMGs2DLPnouJ/f4mBv/0ZPTf+CjV/uL3gG5yB++8BYTk0PPAYANFxe+8xP8WyWRVF9ExFRUVFZSKyv1eMFTrjsDqcv6wBkXgSiSRf0ARiqTlyRjm2t/uxo92PQ3LkjI4Fn+7qx03/2YSHfnwUplcXNrH/xvpOEAA72v04ckZ5xuuEELQPRNBQYYbNqMXenuCYFe8aLzyh1ATzMBG10m6ElqHHRLiVBG8lARMQVxUBgG7q9IL2Z7WZ0G6rhd6c/jkPBEThvsqhLNxSFIXKX90AWjfYDouQwFe3vwLhcwKcNLJ82GzEWR5RNgmXwpiQa5eE25E7bhmrDZqqGoQ/eh/GxYfDeuLJI9+X3QEAEAIBCJEwQDOg9GNzDWHKxfGnFHfmMOvA8QLC8aSi+z0YTQm3qaiExL5m0dxRoENbRUVF5cuGXssgoTeBBAUI0UjRtYsSHI/W/jCWzMwc+0iw+0RDpW6GKtwWS8FBPlVVVbj++utx/fXXw+fzob29HbFYDOXl5Zg+ffqEGHBee+21OOecc9DY2Iju7m7cdNNNYBgGF1100YFu2oSFGM0whEfmuO1PiablNgOMh4xNjhcgDoprfncbGIdDPs8k50N/HuF2YIi4XCieJx8DY7HCMH8B9NNmgNJmX+6YC72WwRWniTUZ2aSAH/x9FTo90aL34y/CcQsga+QF29YCYNDBDADWE04CCMHAPX9Bz83Xo/4fD+XN9yKCgGRvDwzzF6UfV8sgkRx/R5SKioqKSmlp7RczWKdWiYN2s0EDc+FDxpJyxIxyPPH+Xqzd6x534VaKNOjxxQoSbmNsEp/uFB1/XV7l33t/hEUoxqGx3AICgqRAsopLk4Vs7leGpjClzDRGjltxfFeWZVI7sV+8OdRPK1C4NWjx6BHfx09PnJv2vByVYFeOSqC0WpiPWJr2nMHlRAwYE0ODLyLFZ2WOCR1fvwimI5aCcY0ulkKKPYttXDc64TaVG8wHAxCiEdAWy5jdL9I6HervfwxMmSgYSBEagQir+N2SHbepWLHu638Jw5x5qLn5T2PSPhUVFZXJAG+yQiAEQihUtHC7tycEXiCYU5e5slkisbcZoBnoGqeOtqkHHSMahTudTjhHGFQ/lnR2duKiiy6Cx+NBRUUFjj32WHz++eeoqFBdgNmgTCYYfD5ERiDctqWKa9SXm9OyU8eC4YURBqMSCnPcSoW6fM8/A9pkhv3McxS3J8kkgm++BpIqsqWpqkb9fY+Oum86DY0pZWZsafVCEEhGjEEupEF6vuJk+eA62gGahrYuPSfQeuLJ4Hq74X/2KcR3bINx0eKc+0m6B0BYFtphS8qO7FoHW8gM4PBRtVNFRUVF5cDS0if+vjdVjs2y5mKYVWuD1ajFur0eXH7q+B5byp+Ns4WtSvp0Zz/iqaKp2SZq5fy3CjMCUXH/2cSlyYI3R2xBQ7kZn+zoQ4LjodeWbpwoFZ4qyzIxL7t6phVmLDAbxFuiUJxLe74/EIdRx8BiUL5lYttaoa2rTxsnmq1mBBkttGMh3MpO48wxocZVBs0oRVsAMB25FGzLPpiWHT2q/TB2cezO+/3QVFSC0oztOa6tqZUfS8K2N8zKWctDkYRbq1EDwvMg8Rho48jrUaioqKh8GaBMFggCAR8KFl0DZ3eX+Js3Z0oO4XZfM3RNU0HrRqdrHIx8qUpnPvPMMwe6CZOPxukY8LfCNgLhdl9qKeXUcj1avnYWrCefhoqfXpPnXSMnvmsHAq++hPIrfwKHxQYNTeUVbuWM29TAPvjGq9BUVmUVbimNBo1P/AeJPbvgf+FZxDZvRNI9UJKlU7VOI9btFeANJ+T2FMJgxu3oLnBseyu01TWKF0r7WefCcuzygioRJ3u6AaQPkAHg8JbPQfQGAKWLm1BRUVFRGX/294XgsuhhH+WEYSlgaApHTC/DB9t64Q0nxjWuQRJuowXGSb23WSwOWl9uRpcnqhiBIFVcbqwwo8MjvuaLKItLkwU541ZBuK0rN4MA6PZGMbXKWrpjhnIXbrWdfR4Mc+eDKbAYltWoxYLebSh7cw1wwo3y8/2BGCrtRkWnqBCNoPP/roL56GNRde118vMmPYOo1ghTOFRMlwoiW56wEI+D6+2GbkrdqHJpAcD5jW/DdNgRMMyZN6r9MFbx8+YDflT98vpR7asQuP4+sO2tMB1ymGx28EeUa2EEpKgEow5CTDRrqMVyVFRUDnaCU6ZhTfRYLLFlF1+zsSsl3M7OItwSQUDZD34I0GNn9vsyU1BxMpUvL8Il/4NnF30D0QLdJEPZ2xNCtcMIIycOiijd2N5Mcb29iKz+BOFVH4OmxZzbQjJurUYt9FoGhBDwoZA8kMwGbTDAuGgxTEcuAwAk+3pL0n6pWFm3t7hCJ95wAgxNwWIYuVNBYFlwPd1ZKw0zNntBoi0AcN1dAABt7ZT0Y+h0oLncxeJUVFRUVCY2gkDQNhCRYxImAkeksmI37POM63GlqvQxNv/kti+cwIb9Hhw5oxxz6+wIxzk5R3Mo7anVSg0VFjhS+ZqSQDxZ8YYSoKAc6TRWBcqkeIZsQr5h5mzYTj+r4P2ZDRrM8O5D5YYPIMTFsSUhBP2BeNbCZLFtWwGBzxA4LQYtoloTqDEQbqXJ/OF1DxK7d6Lrf3+M4Io3R30MSqMZtWgr7af+vkdR8ZP/HfW+CiH84Ur0/fEmRD7/dIhwm/kdBIY6brUQoqnCaSZVuFVRUTm4iTfOwttNJ4yoWPuuzgCmuExZVxBRNA3LcSfAcsxxo23mQYkq3B7kSBX/okU6bhMcjw53BDNqrBBSA1M6jyA6WszLjgalNyD8wXsAxJzbvBm3wbicb0vicSDJgbYWVmBEV98A/aw5o2v0EGpc4hKsHl9xObf+CAuHWVdUvMJwKIpC9fW/g+Pcr2bdhvA8Qu+/i+A7b+XcFxEEME5XhuOW1+rBqMKtioqKyqSmxxdFguMnREyCxBEzxOXfa5vd43pcXxFRCR9u6wUvEJx8SA3qykQBSCkuoW0gAoOWQaXdAEdKdJTEuMmKJ5SAw6wDozBOqU/9LTrcxWf858IXTkCnoRUjDIRYTBZfC8Wk0yCqNYlLRFMRB4EoBzYpZC1MFtu6CQAyIqZMeg16rNUI2Usf1ZZtFRabKkymLXASfrzQ1k4BZTDC8+iDCH/6yZgey3b6WaAMRvieeQpWnXiLKwm0wwmmYkrspiHCreq4VVFROcixGrTgeAEJrri6NcEYhy5vNGe+rRCNgCgUUFcpDFW4PcjR79qEM/asAOsvLoerpT8MgRBMr7bJwi1jGVvhljYYYD76OCSad4Pt6kSF3YBQjMt6Q0UIgTuYQEUq35YPBYtqp/GQQzHljrvzZr4WyqDjtribF1+YHfXSUEqrhenwI2GYtyDHRhR8zz4F31P/BOGUB7qAGKvQ+PjTGbk3RGeAJln4zSchBB9u6806qFZRUVFRGX9a5MJkY/ubXgzlNgNqXSY095TewZiLQEq4jRUg3L63uQdGHYOjZ1diSpn4e9/lzXSZtg9EUF9uBk1TcMquwMkv3CrFJACQIyBK7bj1psZGShEG4Q9XovWiCxDburng/dE0NaQoizhelMwBFdkct1s2gXE4M8RSo47BG3POwurTflTw8QtFikoYXpyM7WgHgAlX8IXr7kJ0zecIvPYSYhvXjemxGJsd9rPPA9fVAePWLwCIYoISoZhoWLEatSAJFpTeoDpuVVRUDnrKuBCuWPso3C+/WNT7Csm37b/zDrR/7yIQvviV3iojFG6TySTee+89PPjggwiFxEF0d3c3wuFwSRunMvZoOltwZOd6cN7ilh/uS908zaixgk+dA3SBOWKjQapuG/5wpeykdWfJuQ1EOXC8IA+4pYF4oY7bQvE+/ST6/nIriJB7ZqrGKTluC49KIITAl3Lcjgbe7wPhct8YUjQN66mngw/4EVn7edHHIHoDNBxb8Ezarq4g/vDcZry5vrPoY6moqKiojA1SYbKJFJUAABU2g7w8fjzgBSLnYOYTbrs8EezqCuDYuVUw6JhB4XaY4zYST8IdiqOhQhSIpOXuk1m4JYTkzB62GrVwmnXo9OQXblfv6seTH+wt6LieUEKxGBoAJPbvBQiBtq449ykxWyEQgA+K48U+vzheq7JnFq3i/T5wba0wLlqcIR7TNAWTXjOiwr/58IdZ0BQFu2m447YVtMUKxuEo+TFHg/dfj6Pvtt8DAOgiK5SPBPt5XwNlNIF/9TlQRMjruLUYtTDMnoOpz74M29nnjXn7VFRUVCYyJpMeNaFexDo7inrf7jz5tgCQ2LsHTHnFmBa0/zJTtHDb1taGhQsX4rzzzsNVV12FgYEBAMDtt9+Oa6+9tuQNVBlbDHZRxOSLzOHa2yMOaqdXD4lKGGPHLQAYFiwC43QhsuYzWbjNVqBMyr+VCoHRRhOsJ58G/YyZBR/P/8Kz8D71z9zb/Pc/iKz6CBSd++tk1GngsujRU0TGbYzlkeD4rMU3CmXgH3ej9eKv553hsp78FYBmEMoSl0B4Hp7HHkJ0Q6ZrIlAzFTsq5uR06w6lK3UTly+nWCU3cZbH4yubVeeyiopKSWjpC4MC0FQxsYTbMqse4TiHBDc+To1QjIOQmojMl3H7wTYxC//kQ8SVKLVOZeG2PeU6lYRbu0kHCoNZupORcDwJNilkFVEB0XXb4Y7mnNhN8gLuenUH/vnBPrnASTZ4gcAfYbOOjRL794FxOKFxOgvrhITVJtZDCIjHl8YnShm3XF8vGKcLhiyrsqZHujF39YvgenuKa0MevJEE7CZtWiwFIQRcext0DY2KDuQDyVAheTyiCBirFfZzzgff241D+rfLAu1wQjEOFkP633Gi/e1UVFRUxhujywEAYP3Bot63qzMAhqYwo0ZZD0p6PeD9PuinzRhtEw9aihZur776ahxxxBHw+XwwGgdnoC+44AKsXLmypI1TGXtk4TZU3BK2fb0hWAxaVNoNMC87GnV/ux+G+TmW4ZcIiqZRcfW1qLjyp7KTNlvOrSToSsKttnYKKn56DUyHHVHw8SJrvsgqYgKikAmKhmnJUQDEOIb+O29HcqBfcfsap7GojFvpZs45Ssct29EGTXV13hkujdMJ89KjENu0AVxPd8bryf4+BF59EbFNGzJe6z7sZPx3wVeRpDPz5pSQirT5JrHTaCLw2e5+/Puj/XhrQ9eBboqKisqXgJb+EGpcJhh0E8sRIQmD4+W6HSqm5nPc9vnE8Ya0RNCgY1BhM2Rk3EqFyRpTojhDU7CZdJPacSst3c8WlQAAdWUmhONczn5+sqNP3tcrX7TnPGYgykIgRNHlSzgObFsrdNOLvznky6uxacqh0FZWAgD6JOFWIePWMHsuGh57CtYTT1HcV03cjdm7P5ULupYKX5jNiEkQwmGAYSZcvi0A0EMqk4+H4xYA7Od+FWWXXoaexkVZoxKCMQ5WozheTbTuR2jlO+AD/nFpn4qKispExWIxgGW0SAYLF24JIdjdFcS0Kiv0WuWxY2LPbgAoykCnkk7Rwu0nn3yCG264ATpdupDU1NSEri5VOJhsaKxWUBQgRAuPuRAEgn29IcyosYKiKNAmM3SNU8GM04DMtPgwGObOzyvcuoPiDUC5beT5sNqqKvABf9YiF7zPCwg8NOViAYrI6lUIf/wBOq/+H4TefzfDXVLjNMIXYQsuBieJmo5RZNwKsRiSfb3QNTQVtL31K2cCAIIr3sh4TRJzhxcmAwBD6kJdqBuqN7UEcTLfsE4EvKlCJVtavQe4JSoqKpMdNimgyxPF1AlUmExCEm694+ROHfrblK84mbQkXir4CgBTykzo9qa7TNsH0h23AOAwT3LhNiWkl+UYp9Sncm67c6w4evmLDmgZGtOqrPhga6+cL6yEJ5hdLGY72oEkNyJXj1Bdh5dmnAHdnPkARKGdoSnZADAciqKyT4hbbCBDYhdKhS+cyHAaM1Yrmv71HMqv/GlJj1UK0h2343NdYSwWOL76deitpqyrkUIxDrZU3ER03RoM/P3OrKYLFRUVlYMFi0GLmNYo1wYqBHcwAW84gdlTssdRxnftAAAY5swbdRsPVooWbgVBAK+w3LqzsxNW68QpZKFSGLTZDIoCSKRwx22PL4o4x2N6tfh5c329YLs682a8lgpCCPhQCOUGcUmTJNAOR8q+lSIVgu+9jZ7f31jUwEyTKsCV7OtVfD3pFqNCJOHW9pUzUXX9zaB0Ogzc81f03fI7CLFBx01NqkBZb4E5t9mqBxeDXLCiQOHWeMihKLvix3BccGHGa5JzRFs7JeO16vZt+Pq2FxAtcAKnJ1WkbbJX0z7QSDfNW9v84AW1UqeKisrI6XCHwQtkwuXbAkBZahLWk+U3v9QMXQ2SLyohxiZh0DJpy67rykyIJJJpomxrSgickhoLAKJwO5lXnki/QS5r9nGKlPGfrTjr3p4gtrX7cMKCanzr2CZwvIAVG7OPJSQ3tFI8A9cl5ubrp00vrANDMBs0IACibBIJjseWVh8WNDihZdJvl5ID/Ri4927Ed+/Kui/aaoNACPigv+h2ZCPO8oixfNZVWBNxqT9jdwAQi+Rqp2SOHccKwnFoivaDcfcpvh6McrAatQAAISqel2pxMhUVlYMdq1GLqNYEUoRwu6uAfFu2dT9os2VCrgyZLBQt3J522mm4++675f9TFIVwOIybbroJZ555ZinbpjIOaCoqsXvqkeg3lhX8nn29g4XJALHwQOdVlwN86YswKBFa8QbaLvk6DO3N0DI0BgLKIujAMOGWbW1BbMNaIE8W7VA0lVUARHFaiaRHLOqmKS+XnzMfuQx1f38I5mOOR3Tt5wi9+7b8Wq1LvHnpynLzMhxJ1HSYdSCEQEgUf8PKtrcCAHQNjQVtT1EU7GedC8aRmQ0nCbcaBcetJeTB3P5dSLgLK3QnFWmbzE6jiYB0wx+Oc9jfO74V11VUVL5ctMqFySbeRPx4RyX4w0OF29yO22iCT3PbAkBtSpyVfu/ZpIDNLV7MrrVDM0QIdJh1CMU4JPnxmfwuNW7JcWtVdqUCg3+LbMLty6lohAuWNeC4+dVwmnV4dU1H1slIjzypnSncWo5bjsZ/Pw/joYXHYklYDRp8e/Mz8DzxKLa1+xHneCyZWZ6xXXTzRoTeXYFkX/b8WtpmByFA0p87r7cYssVSJPY1I/j2m+D9vpIdq1Qwdgdoqw3lP74ahpmzx+24fMCPM97+O+bsWZ2x+i3B8YhzPOwmSbgVzSu0yZSxHxUVFZWDCYtBgw+mLUfryd8q+D1SYbI5OYTb6t/+EVPuujdvTSCV7BT9l/vLX/6CTz/9FPPmzUM8Hse3v/1tOSbh9ttvH4s2qowh2soqrFt2IfY6pxb8nr09KeG2WrTDC+EwKL0BlHZ0OayFwpSJg2je60GF3ZAzKsGk08BsEG+mhKB4UaGt2W38w9FWVQPI7rjVz5yF8p/8H/TDbP+M1SouWaNpJH2DS9hrUgVLegp23KYG6RY9/M89jdZvnoekr7iBebJfdBsUKtxK8AE/gm+9njbg5bq7QOl0ssN4KEwq85qN5u8bmxRkR3QwyqpO0VHgHSJibGmbeDdthZDgeNzz+k609hce2aKiolJ69svC7cRz3JaPt3CbmhQz6hjEEvmE2ySMwzKBp5SJv/edblGs3LjfgxjL49h5lWnbScveA9HJWWBSiuvJ7bjNPvYJxjis3NKDeXUOzJ5ih05D46wj6tDrj2Fts1v5mKHcubqMxQLakF1IzobZqEVNqAfxndvlYx8xI9PYEN+yCQBgWLg46760DvEGNu4t3e/y0Mn8oUTXr4X7/nuQ9E68yCTj/IVo+tdzWbOAxwrG6QJFU7AkQhkTL1J8guS4JZLjdhyKp6moqKhMZKxGLfaWzUB33dyC37OrMwCDlkFjjpgtiqahTRniVEZG0cJtfX09Nm/ejOuvvx7/93//h0MPPRS33XYbNm7ciMrKyvw7UJlwGHVMTjcJISRNvNvXG4KWoVGfymgTwiHQ4xiToSkTB9FJtxsVNgMGsiybHAjEUW4fHNTzwSAovQG0rnCBWVvXANs550OXZcmdtrIKtlO+onghYqxWNP3nJZR99zL5uXyuk+EMZtzqEHxbLJLG2AoXngHA9e1L0fjks3LsQ6H4/vsM3A/+A/Ed2+TnHBd+E/pZcxRny+iUcMuF88du9PtjkM4oArHQiMrI8EdYOM06MDSFzS0T76atED7bPYBX1rTjvc2ZBfFUVFTGj9b+MLQMnbaUf6LgOkDCbY3TlDcqIZpIZjhupwxz3H66U4xpOmZO+lhZEuH8kfHpV6mRRdQcGbdmgwZ2k05x7PPW+k6wSQHnL62Xnzv7iHowNIVX1igXKZOdp8NipIggIPDma2DbWovtBgDAatAioLeBdw9g7V43XBa9HAsmH4MQxLZuhrahERpn5sokCZ3Nhs01CyFMmzWitijhiyj/rZNecaUT43SV7FilJPD6K+j942/Bh8ZvVRDFMBAsNlgToYycW+n/NuMQx61GO24GFBUVFZWJijShFY7EC4rBFASCPd1BzKy1pcVFDSW6aQPCqz8B4dT7/dFQlHDLcRymT5+O5uZmXHzxxbjjjjtw33334fLLL4cxJdqoTD5O+uhxLNu2Iuvrv/3PJvzyn+vl4hx7e0JoqrTImV98OAzGMn7CLeMSHbdJrxsVNj3CcQ4b9nnSxOX9vSH0B+NyTAIA8KFg0QKzxulE+WVXwjh/oeLr+S5AtD59cO2y6KDXMkU5bmmKgt2kg6aiEozDmb0QRg4Ym73opQm2M84GAATfeBWEEwe5xgWLUHPTHxW310jCbSx/37pT/ZduPvxqzu2I8YQSqHWZMKPGhi1tPgiT0L38xR4xK1rNO1ZRObC09IXRUGFOW8o/UTDqNDDrNeMm3HrDCTA0hQqbvoCohEzhttZlAgWgyxMBLxCs3tWPhgoz6srTXX2ScDtZr3+eUAIWgzZrJWmJWpdRcezz+rpOuCx6HL+gWn6uwm7A0bMrsbbZjR5fptjrDSVAAXAOEzC5nm54HroXofffHVFfrEYNAgY7OK8H7b0BHDGjLCM3luvsAO/zwrjo0Jz7Mhl1eGXuuWCPPH5EbVFCdtwOE6x5rxegGTD27MtUDySeR+5HdN0aUJrix6+jQbC7YE2EMtzswWGOW01VDQxz1YI5KioqKnotgxPaVuGkB64B16E8eTqUTk8EkUQyZ75t4LWX0H/nHSCT7xZ1QlHUyFyr1SIeV16WrjJ5cXk6UO3vApclX21zixcb9ntw0zObMBCMwx2KpzkQhHAI9HgKt3Y7wGjAezw4bn4VGJrCL/65Dlc/ugYrNnTh+n9vwBX3rUaC47Fs1uCSfiEcAlNETEIhdP/mF+i46vKsr7PdnfC//AK4VFwBRVGocRrlwlz58IVZ2E1aMDQFPugHbbcjtnUzPE8+WtD7hWgEwXdXyNm0xaCbUgfj4sMR+Xw1Oq66XC5yls2RIAm3yQKiEqQbsfn1DgCY1IVZDiSCQBCIsnCYdTikyYlQjJt0cQOCQOQlqWresYrKgSMST6IvEENTjqVuB5oyqx7u0PiMQwMRDnaTDia9Bhwv5MygjbE8TPp0UUqvZVBpN6LLE8WuzgB8ETbDbQsMiUo4wNe/Lk8E97y+s2hh3BtK5IxJkKh1meANJ9Lcy95wAt3eKJbNqsgoAHb8gioQADs6MjNiPeEEHKmVJkOJ79wOANBPn1FUHyTMBi2CBhuicQ7WRAhHKuTbxlIxCcZFi3PvKyXkRxKlq/8gF2UbJljzPq84sT/BswMpw/iafCiHKNyGhrnZgykhV8q4Lb/if1D7BzXuT0VFRQUQCzUKhIAP518lsbtLLGI2Z4qyxkIEAYmdO6CfPrOoVc8qmRT9C3/VVVfh9ttvRzI5PoWoVMYewWCGIRlHTGFwmeB4RBJJaBka6/a68at/rgcAWbglggDCcWDGMSqBomloXC4kPW4cO7cKT/zsWJx1eB12dwbw55e34Ys9Azh+XhXu+9EyfPWowVxX5zcvhv38rxV9PM+jD6LjqsszihsAQNLjzlmFlt3bDO8TDyOxa4f8XI3TiF5/rKBcV2/q5gQQM2c1DieCK95A4MX/IrZ9a973s60tcN97NyKfr867rRK2s84BBB5CJALC5r6ZY2pq8XHTMYhV568W2Zty3cytF2fn/OHJuUT0QBOMceAFApdVj0VN4pLNza2TKy5hd3dQFu696nmgonLAkJb0N1RM3JxHl1UPb2h8BE5fJAGXRQejThTgsrlu2aQAjhcyHLeAmHPb6Yli1U5x8vaYuZmxSk6zKMJ5D7Dj9p1N3XhlTTt+9vAX6PLkjzyS8IYTGUKiEjVOUbTr8Q5O7rakMpWnVWdOFtSXieehUlvcgYRcrG4o0XVfADQN4+LDCmv8MCxGDfwGB1hOgCMRwBHTM/NtDfMXwPGNb8Mwf0HOfZkNGpy8733gb8qrlApl7V437n1zF373zCa8uV6chB/uuE16PdC4JmZMwlCGu5fHGk15BSI6M0Jef9rzwzNuVVRUVFSGYLFAEAiEUDDvprtShcmyOW65jjYI0QgM8+aXtIkHI5mjzDysXbsWK1euxDvvvIOFCxfCPCzI/cUXXyxZ41TGCZMJhsAAogketmGxdpID7pwj6+EJJfDRdrFI1/QaUailaBpTn30ZhM+9jLDU1N5+l+zyrXWZcM1583Hx8mn4fM8ADptWhvryzBtP60mnjuhYQjwOrqsTQjAAxu6QnyfJJHifF4bZ2cO7dY1i0bdEawssx58IQMzL4wWCgUAc1c7s7oMEx6M/EMeyWRUQWBYkGgVjd8D5re8g8tmn8D75GGpvuzPnQJhtb0u1o6mIHg9iOnwJyv/nZzDMnZ+3uJmmohIfTjsBS2vyH6vHGwNNUfJFXnXcjoyhOX8LGpygKQpbWn24YFlxhegOJFJMgk5Dq45blQwEgYCixv+G/2BEdvNZiy/qNF6UWfXY1OJFnOVh0I3K2rvDAAEAAElEQVTtsmt/hMWUMrN8nDjLKwo90qR3NuF2w34P3tnYjXKrAbNrMx0pDrNWPt6BpLU/DApAfyCOqx9Zg1svORwzFdo7lDgrTu5nKxI2FDnj3xfFtNTk//5e0c0zrSpz8r+uPFXczZO+QinO8ugPxDCnrjrtecKxiG3cAP2sOWBsI4sMsBi02O+ailfnnAXX9CbYTJnuIH3TNOibpuXdl0mvgSvqBb2rFYTnRxRzBQC3Pr8VgSgrR0McP68KjmHt0s+cPaGLvpRd8WPw/vEvnkpfdBnu4hbjair9mjZcuPU89hC09Q2wnXr6uLdRRUVFZaJBW6wgBAXlku/qDMBm1MqTs8OJ7xBXwhjmqsLtaClauHU4HPja14p3LapMYExmGLgORBWKb0hFJ8ptevzwK7MQZ5PY2ubHjOr0wfxIB6QjRePKdEFUOYw4b0l+t2fRx6oSB8NcX1+acJv0egBCwJRnLqWT0NbVAxot2NYW+blal3hh6/ZGcwq3nalcvKlVFlAMg9o7/gZar4e2dgpsp5+F4JuvIrrmc5iXHpV1H4nW/QCQV3TNBkXTsH3lzIK2NWilm9v8QeY9vigqbAa5SviBvmEdDQmOh05DHxBhSfp+Osx6WI1aTK+2YnOrD4SQSSN0fb57ABaDFnPq7Njc4p1UbVcZe37xz3XgeAF/uOhQ2M3qEquxxCtXrJ+4LjTpN8MTToxpAbU4yyPG8nCYtHIEQrYCZdJSeJOCkCy10R9lce6R9aAVCnc4zBPjd7C1P4wpZSZccdos/PG5LbjmsbW48wdH5hRvPbLYX4RwO8Rxu79PvCmcWp0p3Bp1GpRbDehwpztuO9wREACNw5zhsW1bQRJxmJcsy9uWbFgMGgyYKzBgrsClCzPFWamIVSHLPS0GDaI6E0iMQIiERyQmRxNJBKIsTlhQjeu+tjBr9nT1r28set/jif2scw/Ica0pgTsYS/9uSVEJNpMWhBAEXn8ZpiXLVOFWRUVFBYDGbhejEoKZUUVD4XgB+3pDWDzVlfXeTYowMszJbnRTKYyihdvHH398LNqhcgChTBboeRaxaOZNg3Qj57TooGVo/PHiwxBJJGE2iKdO0udDbNN6GGbPhbZ2yri1OekeQKJ1Pwxz54Mx58/jY9vb0H3dz8W4hHMvKOpY2qoa8Zh9vcCs2fLzvFt0CmrKKxTfB4iCtq6hcZhwK9685CtQ1ppaQthUKQq3hiHHdnz9IoTefQv+55+BacmyrBdLtmU/aKsNTI42lgp9MoErv3gQVt1xwJL/y7odIQQ9vhhm1trk5X6TtSiLOxjHFfeuxlePasQlJ0wf9+NLN/pSvuCiJide+KwNrf1hTFVwME00PKEEmnuCOHFBNfRaBhwvIJJIwmKYuMKRyvjBJgVsafVBIARXP7IGt3/3cFQ51EKoY4UUWTO84NNEoixVcNQTHFvhNhCVikDp80YlSIKuMYvjVuKYuZn5tgBg0jPQMqVdcfD57gH8d3UrbvnOYXmLhgHiBGS3N4aj51Tg2LlV+NN3DsMv/7kOb23oyincSpOHriKiErqHZPy39IVRYTPAlmXJel25Cc3dwbQJvfYBcWw0PNKDNplgPupYmI4cjXA72I4jpjoyXg+ueBO+/zyJ2tvuhH76zJz7Muk1iGpN4s1vIDAi4bbPL44T68pME7Jg4ETHwoWxpGMthH0CsHxwjCYJt1aTDiQeAwQhZ+yZioqKysGEzmYDIQDrzx2VsL83BI4XMKcu+++brmkazISMeCWMyiDqKEAFiSXL8dqcMxFNcBmveYfdyNE0lbZUkG3dj4G//QWxbVvGp7Epwqs/Qd8fbwLX1lrQ9nwoCCESBkbg5NNUicvxuL6etOeTsnCrfDMmoWucCt7rBp/KiRl0neQuUNbSPyjc8pEwkgP9IKlsaY3TCcvJpyGxrxlcKg5hOITnwba2QD9t+rg4GHVGPSojblDe/pzbheJJRBJJ1DiNMOs1Jb9hHU/+9eF+BGMc9vXkX0oyFniG3TQf0iRm3G1pG/8liSNhTaoo2bLZFXKBHv8kFfFVSk+3NwqBEEyttKDDE8HPHl4z6YrvTSbkidoJ7GyWnJ1jnYc99G8xNCpBiUhcfN6sINzWpYRbs16DQ6YqZ5BSFAWnRVfSyKBPd/ZjU4sXvf78xUIBcYWPQIhcmO6waS6Y9Zq83zf5N6gAx22ZVQ+9lpEnrXmBoLU/jGlV2Sff68rMiCSSaX+b9pQDt7Ei/X2G2XNR9asboKsf+corvZaGlqZw7ep74PznXRmvS4XJtHX5j2ExaBDRmiAIyOtayob0+eWasIo370b/3/6KePPuER3jy4yZi+H05ndg3L057flQjAMFwKLXQIiI55Mq3KqoqKiIaCuqcP+SK4Azc5vdBguTZRdlHV/9Oqp+/uuStu9gpWjH7dSpU3OKQPv37x9Vg1TGH2rBYmzcSeMchVWAkhMyW+EJKbSatoxvFWpNmeggTXrcBW0vt9OaO69NCW0qKiHZ15f2vGnZMaj7x8NgHM6c7zcuPhQQeJB4HLDaUOUwgoIYF5CL1v4wGJpCXbkZkQ/ehfsfd6Hqht/BfMRSAIDz6xfBce5XszqdhWgUxkWLYZg7r8Cejg6DUQ+BooB47hvqnpRgXeM0gaIoOMylvWEdL7o8Eby1oRMA4I0cmKJakuAtiZ4LGhwABn9IJzpf7B4ABeDIGeUIpBww3jCLOoWMapWDD2mJ9NePaYKGoXH7i1vxiyfW4emfH59RgV5l9Mgu0wks3EqTVJJgOFb4U9d0u1kHKd1AKU4KyO24rXGZYDfpcOzcypznrN2kK+mklScUBwBE44UVEpZW+DSmhFuKotBUaUFLXyhnfM3g73l+JzxFUahxGuVJ6w53BBwvyHm3SkjCd4c7In/27QMR0BSV5mYeTYbs8DYev6Aazp028MPGl4TjEN+xDfrZ80Dr8wvVkuOWEAJhhMJtn1/8HHMJt2xbK8IfvAvz0ceM6BhfZkyVqdVmgfTJbH+UhdWoBU1TSMrC7dg5+FVUVFQmE2azHgOWSkTp3L91g4XJitdXVIqnaOH2f//3f9P+z3EcNm7ciBUrVuAXv/hFqdqlMo5ILpGogptEcrUMr2ArwYfFwT5jGd9l2ZoyMeM26S5MuJXCtRlr8e2kbXZUXvsb6Jqmpj+v00FXV5/3/dblJ8G6/CT5/zoNjQq7AXt7QvjPx/uxqdUHdzCO2y89HOW2wQIKLX1h1JeboWVohFNFHTRDRGJNWfZsXUDsa/X1NxfSxZJg0GnAMjroEvGc20luGynf12Eu7Q3rePH4yr3gBQKjjjlg7ZeWqUpVySU3vFQsZyS8trYDa5vd+N1Fi8fUqc3xAtbv82BevQN2s04Wi/wHSARXmXhIwm1DuRlz6x3Y3u7HK2va4Q+zqLBP3AJakxVfmIVZryloaf2BosyWEm6DuX9nRos/Ik4kOc06sElxbJQtKiGaut6a9Zl/Ny1D44mrj5Uz4LPhtOjQ7o6ULONbErYjBf4WtA6I3zXJcQsAU6ss2N7hhy/CZo1CkPJqC42tqHEasabZDV4gg/m2OWJ9pEKzXZ6ovKKkbSCCGqcx7TwNvPw8QivfQfUNvx91bNdvLlyEnq1NiO/elfZ5xPfsAmETMC46pKD9mPQadNqnYPtxF2JR49T8b1CgP+W4rXZkv97xXg8A5doPBzuM1Qqi0YIJpgu3/f44KlO/IUJMnEhQHbcqKioqIlajFq6oF6G9+4Gq7L95u7sCqLIbs0ZseR59EGxHG6p+dQNoozo5NlqKFm6vvvpqxefvvfderFu3btQNUhl/TBtX41cf/x387J8Dh6UPeH3hBGiKgl2hsi4ACGFx4E2Ps3DLpAaoSW+Rjltb8TNCFEXBcuzxGc8n9u8DVaB4O5wapwmbW7145L1mUAAIgNW7BnDuEnFfMTaJXn8MJywQYxr4gD/V/vSlCIQQhN5dAa67C2Xfu7zodpQSvY4BV4Bw25sSbmtTwm2pb1jHg709QXywrRfLZlWATQrY1TkyN81o8YZZmHQaeSkvTVMwaJmsAkMhrNrZj3V73fBH2DHNutza6kOUTWLJLHECwpWaHPJOQhH/YMQbTsBq1I6p81USbiUHtuQsD0RV4XYs8IYTE9ptCwyu/nGPteNWjonSIZiqQJ8tKiGaEJ9XctwCyJrfOhSHWYcExyPO8XKm7miQhNtoocKttMKnbFC8kkTclr5wVuG2yxuFWa+BzZTZR6Xf9FqXCbxA0B+IYX+vOH7MFZVQXy7e6HWmrgVJXkCnJ4IlM9MnriNrvkDS64WmojR5/pryCpDNGyFEImBSK8oSu3cCAAzzFxa0D72WQcRSht0zZo1YTO5NOW4r7Nkdt7zPCwBgnKpwOxyKohA326EL++XneIHAHYpjeo14rtBWG6ynnQn9tPGvU6CioqIyEbEYNfjWlucAjw045p+K20QTSbT1h3HcvCrF10kyidCHK8G4XKpoWyJKdsd1xhln4IUXXijV7lTGEb1BC32SBRvKzOn0hVk4zDowCpWQAUAIScLtOEcluMoAigJftON2ZFZ+IghIetwggiA/N3Dv3ej93fUFvd/94L3o+/Mt8v+vOHUmvn/yDNz5/SPxzLXLQQHY1OKVX28b5n4RAqIwODyWgaIoRD5fjcCrL4Lr7ko/5iMPwPPog4V3cpToNTRYRguKzROVkIqIqEk5dKQb1tGIjePNo+81AwB+cMoMOC06RNkkEtz4t98XTshiloReyyA+irb4UoKFdMM4VmxN5fAeMUO8AZcEI98YZ1eqjJ4+fwzfuesTPPXR2EYjScujJSe5NIEoxWqolBZ/uLSTNYm9e+B+8B8Q4qW7lhh0DCwGrbzaYKyQ4nscZh2MqYmxbCKo9LxpFIKr01y6Qp1JXpDbH0kU9lvQ1h/GFJcJOs3gbYHkhM2Vc9vtjaLWZcoQaIkgoO2738LAA39Pe34w4z+Glr4wtAwtu2qVqHIYwdCUnGvb7Y2CFwgahryHDwaQ2LMTxsWHgdKWZuJBUyHWLkj2D0Zkcb29AEUVJfCZ9JqC4yqU6PPH4LLo0z6X4SR9XoCmwdjVwi9KsBYH9JHB+ChPKA5eIKhOxU/optSh4sc/g3HR4gPUQhUVFZWJhcWgRUxrlHUeJZq7gyBA1sJksa2bIYSCsByTaX5TGRklE26ff/55uFzKhRdUJjZ6h/iF40OZg3NvOCE74ZRgHA7oGqeOWBAdKZRGA21DIyhjYRXGbWecjZrf3yZHLBSL9/GH0X7Zd+SCZACQHOgHkyeuQILr6UZ07ecgvHgTNbfege8sn45DprpQbjNgerUVW1q9IIQAEB0ugLhUEQCSfh8okwm0LvOzcHztG4AgIPDay/JzhBCEP3of8ZRDZDzQaWismHkati09L+d23d4YjDoG9pRDR75hnSQ5t7u6AljT7MbJi2owvdo2RHAcffsFgRQlXPrCbEZRGIOWyeoMK3SfwGA167GibSAMCsDU1OSE5OiarIXqDibe3tiFBMdj5xg6zQkh6HBH5YxLAHCYxWuGlMWqUjp4gSAQZUtamMz/8gsIvvU6fE8/WbJ9AoDLqhuHjNtM4TZfVIJJISqhUByp618pfkeGFm4rxHGb4Hh0e6NpMQnAUMet8o1bguMxEIzLYuxQeI8bQjCA0Io3EF79ify8tNKm2xvF/r4QGivM0ORw7WsYGjVOI7o84oSvNKndMKQwWXT9WoAQmI9cmrevhSILt0PGfBU//hkan3y2KOdQOWI479mb4HnsoRG1oz8QlwXGbPBeLxi7oyQZv19GgnUzsd/eACE1/u6TXczqqg0VFRUVJaxGUbhFJCxrE8OR8m2zFSaLrPoIAGBWWLWsMjKKtgcceuihaTPrhBD09vZiYGAA9913X0kbpzI+GO2iq0KIpA/OCSHwhVlMKcvuhnB87ZtwfO2bY9q+bNT/7YGCt9VWVkFbqWzlLwRN6r3Jnm5oK6sgsCyEYACaAmfodU1TEdu0HlxvD3RT6jJeX9Tkwouft6HdHUFjhUV2uEiilhAMgrE7FPdtmLcA2roGhD/9GGWXXwmKYcC7ByCEgtAdc1zxnR0hFEWhq3oWyitzF2vr9cdQ7TDK1xHphtUfZgvOyTuQSEVcTlwoxli45BvuhJzbOxK6vVH8+aVt2Nbux4M/PgrTcuT+AYNCyyJz+t/boGNG7P7lBSILFmMv3EZQPSSn0GrUgqEpNSphgiMIBCs2dAMAOlIiyljgj7AIx7k0N57kuA1GVMdtqQlEWRBkz7MvFkIIYls2ift+7SWYjz4WhjmlKZRZbjVgd9fYxtP4UjE0ei0DQ8pJmy07XKoPYMoSlVAITjnje/TXP09wULiNFOD2bB+IgGCwMJmEw6yD06zL6riV8uqHFgmT4Hq65ceJnTtgOVoci0gib3N3EP2BuJxbm4u6cjPWpXJx21PXnMaKweuCNEFtPOTQvPsqFNOSZaj7+0PQVFWnPV+sSUFnMkGbiIIPZ3ctZSPB8fCGEzikKfeYynLiySCxsf29nsz0HHsOVpi78B2OwMxk5gaHPnofoZXvoPzKn0BXmzk+V1FRUTnYsBg0iGqNIFEeQjQCxpy5snpXZwAUgJm1mb+LhOMQ+Xw1dFOnq9fVElL0KPO8885LE25pmkZFRQVOOOEEzJkzp6SNUxkfTE4HAECIpN+Ex1gxby2X43aywPX3gTaZ5ayyYtHPmg1AdHYYDzkUfMqFoSkvLE9NlypMwba2KAq3i6eKwu3mFp8s3Oo0NKqd4k3OlDv/IRdQGI6Uwet75t+Ibd0M0+LDkGgRlzDrp45vZpeOocDGszuheIGgzx/D0lmDf7dBx+3kWCI/6K4SL5+OUTqGCSF4bW0nHnx7txxxsKcrmFe49UdEoWW441avpUd88x+IshBSM6vSTflYwAsEne4IjhiSU0jTVMkrq6uUno0tXvQFxHOjLxBDnOXljOVSIi2NHircSjmapXDc8gLBrc9vwYJGJ85f2jDq/U12pO9dyX7vBQHll18JrrcHvuf+g4F/3I26v91fEldgmVWPSCI5ZuceIF5fJRHblM9xG0//TRgJ0rFKIdwOzf8txHHbNiAKs8Mdt4AYl7Cjww9BIKCHRWZ1e8UxiZLjluvqlB8n9u6RH1c5jaApCp/tHkjtP/+YrL7MjM93D6DXH0N7qq31Q4RbQSqS68gtcBYDY7WlibRsVyfi27fCdMSSooqA6cwm8AQQosVPcg0ERGdoVR7Hrf2Mc4re98GEFLUTinEwGzToS/1dK1N/V66rE/EtmwBeyLYLFRUVlYMKq1GLqNYEgRAIoZCicLu7K4jGSovi2Ce+ZxeESBjmYy4cj+YeNBQ9yrz55pvHoBkqBxKDLfVljKS7KqQl29mKUgCA77mnQZvMsJ+de3n8WBDbvhWxTRtgP/erYKy5Ra6em64DpdMV5dIdin7WHGhqahH++AO4vnsZklIV3wKjEnRTReE2vnM7LAou2EVNzlTOrQfnLqlHS18IjRUWOVuYomnFi6aE+djl8D3zb0RWfQTT4sPAtuwTjzvOxRbO3foi5vRsB/nBSsUb9IGAmC1WM8SZKt+wThLBLspKFcTFy6ckdIx0ievD7+zBs5+2ospuxGVHN+Let3ahtwC3q5TxOLyYkFGnGbHoOjSmYSwdt93eKJICQeOwbEOXRZe2zFdl4vHWelGQOXlRDVZu6UGnJ4IZNaWPyul0i6JQmuPWXLqM27fWd+KDbb3Y1xdShVsMLq93mEuTcUsxDCzHnwhAFNS0NbV5RVu2swOR1atgO/OcnJOsZanJKk8onnNF0GjwR1j5d0oqFpZVuGVHL9xKE5iliIDwFCncSo7aoS5WiaZKCzbs96AvEEONM12gleILal2ZwqLkuNVUVSOxby8Iz4NiGGgZGhU2gzz5M606f2FbKS6l0x1B20AEZVY9LIbBYmjlP7oKzosuAaUZfVG3obBdnSAsC/3UaYitXwvPYw+i5ne3FiXcmgwaxGkdhKjyxHsuelK/wfmEW5XcVIR68dXtLyGw0Yrqk46WoxIqU1EJkmmFNo/NtURFRUVlsiFFJXC0FoLCig5vOIG+QAxfOVS58KZx/kLUP/A46AIjLVUKo+iMW4Zh0N/fn/G8x+MBo+YrTUoYmx3PLfsets49Ie15acnycEffUIJvvoZwKsNkvInv3A7/f/8Drrc777Z8wA/NKNwYFEXBesLJ4P0+xDZvhBCNgjZbCq5grJtSD8poQnzHNsXXrUYtZtTYsLnFh2CMgyeUGCxMFo8j/OknYLs7Fd8LALq6elRe+xu4vnsZACCxfx9AM9A1NBXX0VFCtHoQEJCEcjEauTDZEOF2smXcxoZVEJeiHkYiOPICwVsbulBfZsbDVx2N0w8TfwB7vPlv8qS/V1lGxi094qiEoTEFhYjHI0USCobmFALi31LNuJ24BGMcVu3sx6JGJ5bNFq99kjO21Aw6bgfFIlvKOTXacyQc5/D4yr3icQYiCMXU6IVA6m86vNjhSEl63HIumu20M2BceIjidkI8ju7rf4HQR+8j+PYb8D39T3Rc+X1wQ4pCDUe65rnHKOdWSMXQSJNiei0NCsiaHR5NJKHXMlmLuBaCJCL1B0Z/3R0q3IYLiEpo7Q+DoSnUKRQJkxyxUu7+ULpSv1NKEUdcdxdAMzAffRwImwDb0Sa/NlTonV6AcCtN3rQPRNCRipMaCmO1Ka5kGi091/8C7lRxtcR+8XqhmzajqH1YDFrENXokFWpI5KPfLzlus2exsu1t6PjxZQi+93bR+z9YsILDgr4diO0TP8P+QAw6DS2PPSU3NG1ShVsVFRUVQCx0vWbqMXjtkluhnzot4/XdefJtAUBbXZM15lFlZBQt3GYLKE4kEtApFE5SmfhQDANfzQy4tekDaMl9l+1GjhACPhwe98JkEpoyUTjgPZ6c2wksCxKNjvriYVl+EmiTGUmPG+Yly9D01PMwLT26oPdSWi1qbr4FZT/4IQDxb+d54pG0bRY1OeGPsvh4Wy+AIYXJ+nrR/+c/Ifzh+7nbd+zx8mdhP+tclF32I9D60lUILwSi04MQZK0iLjlBhzp3pJvjwCQR7CJyBXFxoso5iiWuOzr8CMY4LF9QBbNBA5NeA7tJJzttciE5bod/Pw06BmxSAC8oX6sL2SdDU+jzx7Ne70eLtDR3eKai06xDnOMRY0dehVtl7Hh/cw84XsDph02Rq7qPVc5tpzsCLTMYFwOIhYrMeg2Co4xK+PeH++GPspibqoS7a4zzUicD0qRNKYRbwvPo+MkP0XfL79KeC6/6GKGP0n/H4rt2IL59K3ifD2XfvRzO73wPQjiE6BefZd3/oON2bITbcJwDLxD5b0FRFIw6DWJZJsSiCV5egTFSrEYtDFpGdgOOBs+Q63ihjtv6cjO0CkXCpAlkpZzbHl8Mei2TMXkIiC7Ymj/cBsPsuQCARPNgXIIUreAw6TKK4UXWfYGB++8B4Qa/41KG7sb9HsQ5PsMZnNjXnHNie6RoKquQHBCNKon9e6GprMq7ums4ZoMGCUaHZKT462RfAY7bpMctiuT8yAuSftkxVoqF5li3G4BYnKzSbpBj/4RIBKAZUOM8XlZRUVGZyFhNuqzGBilvflp15uqo+K4dCL795ogiglRyU/BI85577gEgDmAfeeQRWIYsY+N5Hh9//LGacTuJcSIG+NJvXr0hKfNOeTBDEgkgyYEeYW7saNGUicvVkh53zu14vw8ARi3caqtr0PjPZ0BpB5foDc17zodh9uD3I/DS8wi8/Dxcl3xfXj66eKoLL3zWhpe/aAcwWJiMD/jF9hfgGOZ6usF2tMO8ZBmMBRZOKyl6Q0q4VRYeB+RssUEHiSTcTpaiVLFhGbeyY3gEjtvPdok3hUfPqZSfq3Ya0ePNL9wOTqwMz7gVz6cExxe9dFeKe5haacHe3hD8ETZj/6VAqcAMMBg74Q2zmOIq7bJXldGzYmMXTDoNls8fLNgzVo7bDncEtS5ThovRbtaNKiqh0x3BS5+3YWaNDT8+Yw5++vAX2NkRwJEzCou9+bIiX0/MoxduE3v3gMSi0A11adA0PE88DEqrhXX5SfLT8W1bAADGhYtAaTSwn3kOfE//C7FtW2A/53zF/ZfZUsJtcGyEW2k1w9AYGoOOyV6cLJGEcZRZuxRFocphLElEjSeUgEHLwKTX5BVu4yyPXl8Mx8+vVnxdcrcqCbddnghqnUbFcZCmohKaikrwoRCqfnMzDHPmyq9JK26mVVsz3pvYtROht9+E/cxzoWtsAiAK9UYdgw37vQAyV2r0/ul30JSXY8odd+fsa7FoyiuQaN4NPhwG19kB05Kjit6HSa/BK/POxZLvLin6vX1yEa3swi2fiu1inPmLvB2sWKorEMTgKoA+fwzz6h3y60I0AtpkKmo8r6KiovJlp4xmUbNrMxL7XNBPn5n2Wq6M++CKNxD+cCWMiw9TVzKUmILvjO+66y4AolPwgQceSItF0Ol0aGpqwgMPjCw/VOXAc84nj4FLcMB1g0UOvHkct0IoCAAHTLhlysUb7aRnIOd2g8KnY9THlETb0EfvA4IA64mnjGg/XL/oqhXCIVlQXtgo5ty29Ke7EYtpf99fbgXb2oKmp54Hbci+vG7M0BtACMla4TiYmrmTqsMDoovOatROmiXyUZYHQ1PQaUR3ktT+kWTcrt41gDKrHjOHZITWOI3Y3RVAguNlEVYJb5ZiQobUe+IjEG6l7/zcegf29obQ64+PmXBbYTNktE+KnfCHWcXltyoHjr09QTT3BHHW4XVyQagquxEdYyDcskkBPb4Yjp6TGUVjN2nRHxi5K/H+t3cjKRBcdeYczKy1QcvQ2NHhH0Vrvxz45KiE0X/fY5s3AUDa5CFFUTAddiRC77wJrrsL2loxFia2dQsokwm6JlHkpU1m6GfOQnzbFjkXdTiSw3Os8rClvPWhwq1Rx2TPuE0k5QJIo6HKYcDG/V7FQmDF4A7GUWbVg6YoeYVINtrdERAoFyYDRMdold2YEZWQ5AX0B+JYNivzOyrEouD6eqGtmQLGaoV5ybK016UbPaXCZLRN/C1kuzpk4ZaiKNSVmdHcI445h0/4icJbY85+jgRNRSVACKLr1wCCAH2RMQmAWJm7x1qDWIVyDmAuev1x2IzanAX4kj5RzJaMDCqZWG1m9GmN0Pi9CMWTiHN8WvyE/ZwLwAfVVRcqKioqQ6kgMRy39kVEvnAqCLcxGLSM4mR/fOd2aOsboa1SnhBWGTkFRyW0tLSgpaUFy5cvx+bNm+X/t7S0YPfu3Xj77bexdOnSsWyryhgiGEzQcOk3w75wbsctL1XyPVBRCS5RuM0blRAQB2R0iXJWvP96HAN33QHfM0+NeB+MRVxux4dC8nNSzi0AmHQaOfOO9/vF9xTQfssxxwN8Eq3fOh/x5t0jbt+IMehBkD0qIZhyyknV4SWcZt2kEW5jiSSMOk2aO8Np0RUt3Ha4I+jwRHDU7Mq0m3TJjZQvY9aXpZiQ5PzKlseYe59iH6TMorEoUCYIBO3uSEZMAjDUcasWKJtorGkWVzacvKhGfq6+wowOdwTCCGI5ctHtjUIgJK0wmYTdpEMwyo0oxmPtXjc+3z2AExZUY2GjE1qGxqxaG3Z2Bkreh8mGP8JCp6FH7RwFgNjWTaB0+rRVJgBgOvxIAEB0wzoA4u9EYu8eGOctTBNojQsPAaXTZV1NI41JxioqQclxa9Jrska4xNjiJ8mUqHIYwfEC/KOMAvGEEii3GWAyaORM9my09otjkKbK7K6YqdUWdLgjSPKC/FyfPwZeIHKMwVDiO3eg639/jPD77wIQYzISLfvl+IMFjU40lJtx7NyqjPd6H3sIAMB1dqQ9XzfkOPVDhFvC8yDxGGhT6Sf6NOWDcVymI5fBMG9+0fsw6jTQJ+OIdnSCCEL+NwyhPxDLW5iM94rCreq4zY7VqEVIbwEV8KHPlxk/YV56FGynnn6gmqeioqIyIdHa7RAIAZ8y6g2lyxPFlLLMlQqE55EcGIC2uibjPSqjp+iM2w8++ABO58iLPKlMTIjBBD0bBT9kYO6NJKBlaFgMyjcktNEI66lnQD9j1ng1M/34BgPMx52Q9/imI5ag6ZmXYTnuhJIcl+vuGvU+6FROmhAOpT1/yFRx8D21yiJfDIuJSjAfe7z8WFtTvMNjtAzMWYK/L/0faKYrfybBGAejjsnI0nOYdSOKGjgQRBLJjDxDp1lfdHG11XJMQrpjScr/7fXlFk29YRYWg1Z2/krohzhui8UbTsBi0MqC2VgIt32BGBIcL2ekDsUhx06Mv4jfPhDG757ZhEgBxXwORnZ0+MHQFObUDRYiaCg3g00Ko3LAKtEhFyZTEG7NOnC8kNX9mA1eILj/rd3QaWj88LTB69OcOjvCcU4utHSw4guzcJr1o14uLCQSSOzaAcO8+aC06U4M46LFAKNBdP1aAGIOGvgkDPMXpm3n+Ma30fDYU9BWZgp7gHiNsxi0cI9RVII/nOk+NuiYnMXJjPrRC95VqcnavjzX/lwkOB6hGIcyqx5mvQbheO5YkdaUkzab4xYQo3M4XkCnZ/A70pWK81FaJimNkbSpgmH+l/6Lrv/7MRKp4lBlVj0e/9mxWNSUPqYh3GBbM4Tb1LXAYtCmOXykate0ufTLMTWVVaDNFmin1KH6+pthXLCo6H2YDRqcsu996H7/vxAihRcoS/IC3MFEzpgEAOB9XoCi1AIwObCbdFg75Qi0zDsOfanif5IxQkVFRUVFGZ3dBkIALpAu3LJJAQPBOGqdmb//vM8LCLy4YkWl5IzIItDZ2YlXX30V7e3tYNn0G+w777yzJA1TGV+IyQxGEBCPxGC2iQNgbygBp0WX9UZOW12DiquuHs9mZlD1818XtF0pYwPMxy1H5LNVRQ3ChyO5lPlg+sXwkCYnnl/dmnYTRRkM0FTXFjQw11ZWQVNTCxKLgTkAERaM1QavyYUkzUBp4WggwsJmzFxW4bTosKVNLAgzmsrc40EswWfcpDstOoTjHNikkCGkZmP1rgEYtAwWT013ylSnHLf5cm59kQRc1sy/pWEUjltvWNyn3IZRCAjZaOtXzrcFBp10/sj4i/gfbe/Dxzv6cPphU7BUYfnvwQwhBDs6AphebU2L75Crvbsj8jlTCiThVknct6fc+oEoW5TL8bU1HWgbCOM7y6elua3m1Tvwwmdt2NHhVxSKDxZ8YRbltuwxCVxfL9jWFpiX5s755Lq7AK1WMWOdNhphXLAQ8W2bIcTj0E+ficqf/xr6mbPTtyug0G25TQ9PqLQTBhK+1PXHPmRlSLaoBDYpgOOFURcnA4DK1HnZH4hjbv3I9iGtViiz6sElBUQTSRBCso7j2t0RaGgKU8pyOG6HFCiTxibdKRFXKdJGFm5ragFAnlxP7NkNw5x5WY8zdAUS25VebKw+5bhtrDCn9UUqfjIWOXqmVBHa0WAxaJBg9BAEAiESKXiFmjuYgEBIWj0AJRwXfhPm45YrRoqoiOi1NLY0HAHtjDIYU8X/JEGcEIK2S78J05FLUfmznx/IZqqoqKhMKCwWI1hGi4Q/PUqmzx+DQAhqXZnjfqmgpyrcjg1FjzRXrlyJc889F9OmTcOuXbuwYMECtLa2ghCCww47bCzaqDIOUKlBb9gfkIVbX5iFS6FaMABwvT2gdDpoXBM/VyvevBtCMAjjIYeC0oz+5sq85ChYTz0dlmOXj3gftNUK0AzIsCJeh08vw4kLqvGVQwfdss4LvwXnhd8qeN91d90HjGAZcSkwIomqUC+i/W4Y6zKzbUIxLiMmARhc7h+IslmjOSYKUTaZ4YIZKjhW2vMLWP4Iix0dfhwzpzIjx1aKSujJ43b1hlhMr86scC0Jt4kROG59YRbTqqxwmnXQMvSYOG7bBtIznIfiGFKcbLyR3Htjtfx6MtPtjSIQZXHSwvTvtCS+d7gjWDKzdMW9JOG2LktUAgAEohxqClz8E4xxeOKDvSi3GnDRcdPSXpubchDv7AykXXcPJggh8EcSmFGbeT2R8D7xCCKfrULlL6+H5ejjsm6nnzoNTf/6b5p7cijWU74C/ey5IMkkGKs160qY2OaNCK/+BOVX/Fjxd7vMqsfOjrHJpfRHxLYP/S0y6hjEOT5jclEqWGbUjX5sIf2u5IvJyYV0/Sqz6hGMcSAQV19ka583Nc7LNWHalMqibekL4YQF4jWgK0dhEq67C5ROD6ZMvCbIwu3ePTnbzgf94gONVox9GoJ0LWgYNuFH4nFQBuOYOG4pigLhOHTf8CtYTjgR9jPOyf+mYTRUmJHQiKsEhGjhrv5CCpMBgH76zIzsQZV0KIoS4xKiHPqGFcglLCvW6+CLHy+pqKiofJmxGLWIawzgQumrg3MVJqN0epiPOhb6adPHpY0HG0VHJVx33XW49tprsXXrVhgMBrzwwgvo6OjA8uXL8fWvf30s2qgyDtBmcWAe84o3QoQQ+MKJjMJHAEAEAQN/+ws6f/ojxdyT8ST47gp03/ArOW9XcZvXXkbvH24sOl8sG5RGg4qr/hfGQw4d8T5Mhx2JqS+8DsvxJ6Y9r9cyuOEbh2B+g2PE+6YNBtDG0rnfisHl6cCP1j6KyOpViq8Ho5xiERdpibz/AAh2xSIuix1WVKvIJf5f7BmAQAiOUii+VGk3gKYo9ORYus0mBYTjnOL3UypOVuxScjYpIBQT90nTFKochlEJCNloH8juuLWbdKAp6oCcB+6Ue08VbjPZkRLI5g6pxA0MZk2WukBZhzsCp1mneK2QJn6CRUSTPPn+XoRiHH542syMQj+VdgNcFj12HsQFysLxJJICUSwyIRHfvRMA4L73b7KjIhsUw2Rd5WI57gS4vn0pKJ0ObEd71qzi+K4dCL39Zlaxz2XRI8omEc1TfGsk9Plj0NBU2vknCZ/DJ8SiqdxbcwmiEiQxaTTRI9IEVLlNL7uAc8W/+MNsWrFQJerKzGBoCvuHFCjr9kWhoSlUKCw553q6oKmpAUWLtxiMxQJNTW3e3H0htQKp7LIfwvHV9PuJGTU2fHVZI85d0pD2vK6hEVOfeQmOr1+Uc98jxfvvJ5DYvQO8zzei91c7jIBRjJSR3MGKxwkn8N9PW8Gl4sqk395cGbeEEPCh0Ijyvg82FvqaceZLt4LfvhkUgHKbeN5KYvpYZCSrqKioTGZsRi067VPAVdSmPd8lrbhRyLjXT5+Bql/dMCqNRCU7RQu3O3fuxKWXXgoA0Gg0iMVisFgs+P3vf4/bb7+95A1UGR+Cy8/GLct/hXjqyxlK3cgpuR9D77yF+M7tsBx/4gErTCbBe9yIb9uMZH9f1m2Sfh8ok6mg5ZfjBcUwBWcJ+p57GqFUkY+JDpMa/LIKzhKOFxBlk4qOW+ckKUolCEQsRKPLjEoAChduV+/qB01RikvyNQyNSntu0VSKElCqAG8YYcbt8H1WO03o88dLflPYNhCGy6KHTUEsYGgKdpMW3gMQleAOqMJtNranRM35w4Rbp1kHs14ji/GlgBCCDnc0a2zBUMdtIbT2h/Hq2g7Mq3PgpCGF1SQoisK8ejv294VHFC/yZUDKF1e6ngBisQnH+RfCevJpECJh9P/tLyAKDjWutwfuB+8FOyyfVInYpg3o/OkPEXz9FcXXjQsPEbfbsknx9bLUaqBSZ6PzAsGODj9m19nTikZKRduGT4hJwvHwybyRUGbRQ0NTo1rpMOi4NcCUEpMjOcRtf5SVf7+yodcymDPFjrXNbjl7vdsTRY3TlOHUJTwPwrLQ1dalPW+YORvJnu60OITh8KlCsozVnvEaQ1O46sw5mFWrPOYcbTZzNgKvvAAA0E+bMaL3UxSF8goHuKSAZDj7dfLhd/bggbd348XP2gAAfakl/VU5ohKEcBhtl3wd7vv/PqK2HUwYDFqYw14k+vtQZjXIdRbGMmpDRUVFZTJjMWrw/IKvIfCNH6Y9L8XoKTluVcaWooVbs9ks59rW1NRg37598mtut3IFYJWJj91hQZLRyLMo3pB0I5c+oE96PfA8+SgYVzlcl3xvvJuZgZShkssBxAf8E65wA+F5hD/5CLFtW3JvRwj8zz+L8CcfjVPLRoc2Jdzy0cwbz1BMFFpsORy3gSILfI03khg6PFtTFm4LbP/G/V7MrbOnVS0fSrXTiF5fLKtoKkUJKDpu5aiE4hzm0j4lQaTaYUCC4+Ev4WdCCEFbfyRnlqjDrDsgjtuBlFPNHRyb3MzJzM4OP1wWfYaIQFEU6svNJXXc+iMswnEuu3BrHsy4LYT3NneDFwguP21mVnFnXr0DAiHY3TU2S+8nOtKEUzbHLcUwsJ97ASp+eg1sZ5wDTUUVSDJTDAx//AGCb72WcyIVAAJvvIq+W24GAOjnzFXcRj9zNii9AbEtmxVfl2KcSh2rsr83hEgiiUWN6Tkcg9nh6f2OJsTfhFJk3NIpB6sk2o0ET+r6VWbTy79T0SyO2zjLI8HxeR23APD9k2eA4wU8trIZvEDQ44sp5ttRDIPGx59G5bD6A7oZM0Hb7DnHauajj0XDY09DU1mFzv/9MYIr3sjbLrajHcF3VyDp9eTddjToRrHss7LaBUKAgX6v4uvecAIfbO0FADz10X4EIqws3udy3PKpPjMOx4jbdrDAOF0QBIB3e9J+x4RISrgdg6gNFRUVlcmMxSCOt6X7d4kuTwRahpZXLgzF88QjGPi7Wu9qrChauF22bBlWrRKXQZ955pn4+c9/jj/96U/4wQ9+gGXLlpW8gSrjw6E1esxy78GWtTsAKDtwwp9+gq5rrwaJRlF+5U8mxAy1JlV1OteNouCfeMItAPTfeRuCb7yacxsSj4GwCTCOAsMcDzBMKqKBi2Q6boMph1wux22hwueBQnIuZQq3hbu/2KSASCKZ84asxmlEJJHM+LGUyOWQkx23bHFLiKV9SmJylZy3WDoh0x1KIMomFWMSJJwWfcHO5VKR4HhZCFQdt+nE2CT294Uxt86uKHzWl5vhDSeynqvF0uHOvgQLKN5xKy0dz+bUA4A5Q3JuD0akyRlHFuflUHdt2eVXovLqn4PWp197CCEIf/whaJtdsTDZUDRVVfLjbE5GSquFYe58JHbvgJBIgAgCEnv3IOkRDQKDqxxK+33d2iYuiV/UlF40UopKkIRaCSXHLR8Kou8vt+aNlFCiymEclePWLTluLUOiErI4bn0R5Ql6JQ6dVoYlM8uxcksPVu/qB8cLOQuaDc8ltp91HpqefDZn7h3FMNC4XNCUl4Nt3Y9E6/687Ypt3Qz3vXeDG1bMrFRU/vJ6WE8/a1SFViqOORq3Lv8F9jcsVnz9lS/awfECTl5Ug0giiX9/tB99/hhMOg0shuwTAkmfKARrnK6s26iIaFJ5y0zYj8oh8R6y49aoOsdUVFRUhmI1ajG/bzuMzz+eVreg2xtDtcOomI0fXbcG8Z3bx7OZBxVFC7d33nknli5dCgD43e9+h5NPPhnPPvssmpqa8Oijj5a8gSrjgz3kwSU7XkDks9VI8oLsuB3q6BOCAZAkh/Irfwrzkokh0udz3BKeBx8KTjjhk2IY0CZzzmWDAMD7/QAmj6NCZ0k5bmPZhVsld4+zyIzYA0VMFm6HRSUU0f5IXPw7mHPckFVLBcp8yjfwvhyOW73sDCtu2be8z5STTRJuS1mgrK0/e2EyCadFhyibHFFxtZEyVKz1hib2OTje7OkKQiAka+62VCyos0SuW6noUfaohFTGbYGOW08oAaOOyVk8anatHQxNYcdBmnM7eD1Rjkrouek6dP3iahBC5Or1Assi/Okn8jZsawu4znZYjjkubxFQ4wIxBkE7pU7en+J2ixaDcBwSu3eCxGPouvZn6LvjFgCiMAmU/vu6pdUHmqIyYkHyRSUMjc8Jf/g+Iqs+yluMS4kqhzhpF46PbCLEE0rAYtDCoGNgMkhis7JwK61syLbyYzhXnDYLFIC7XxUn+JUct7FtWxB8+03wkfS6A7k+Z4lE637Ed24HY3eAMpnAdeYXY2XH5BhllFqOPg4VV/50VFEMsxpc4Bgd9vRkjvcSHI/X1naixmnEr766EHPr7HhlTTuae0KochhyHjfZ2wMAYCoyI5dU0jG4nCAUBQsbTps018+Yhdpb/gLT0qMOYOtUVFRUJh4WgwaN/nZY134gT3KJK26iiuYKQgiSA/2jmuhUyU1Rwi3P8+js7ERDg1gcwGw244EHHsCWLVvwwgsvoLGxcUwaqTL2MDYbjDoGTDSE7e1+2fkoiTgAYD3tDNTf/yhsp591oJqZgaasHKCorMKtEI9BW98AbW2t4usHEtpqE6vZ5oAP+AFgQjqGldCZjCAUBZ7PXKYfjInnlJLj1mEWz7NSLssfC6KsclTCYHGy/O4v6SY619LaGqf4g5hNuPWECnDcFil8eoZN1lSPgXCbqzCZxKB7efzOhYEh8Qi+SAK8oBZ7kZDybefWORRflwTW9hIJt5IALO03tmUTQu+/K18LzQYtaIpCIFKYsOUNJ+T4j2wYdAymVVkPWset5LxUEvAIzyPRvAeUPl1E8j75GPr//Cc5gzb8yQcAxOJj+aANBtTf9yhqb8u9nM50xBI4vvFtaMor5BU+iT07QXh+RLno3d4onv54f9bvNyEEW9p8mF5tlSfWkh43Bu6/ByaI1+1sUQmmIRNxkitY29hUcNskqlJuwP4RrnTwBAfP90HHrfJvgT81+VFIVAIATKuy4iuHTpHfN0Uh3y780Qdw338PwGV+P8OrPoY/lRmr2J7nn0X3dT8HCIFuSj24zva8bZoMGaVVZg0WBFowsH1Xxmsrt/QgEGXx1WWNYGgKV54+G7xAEI5zqHLmLjKbSBV700+fNSbt/jJhM+sR1Rph4mJpwi1jscAwbwE0rrID2DoVFRWViYfVqEVCo4dAiDxJ6g7GkRSIYr6tEA6BJOKqcDuGFCXcMgyD0047Db4RVlcdL+699140NTXBYDBg6dKlWLNmzYFu0oSHsdth1DEwcVF8uqtfdtw6zDp0/vyn8P7rcVAMA8ac3Sl3IKC0WpRddiWsp52h+DpjtqD+bw+g7NLLxrll+WGs1sIdt5NFuNXr8IcTroPvq5l/bzkqQSHj1qRnoGXoki97LTWS43a4e0+vZWDWawqKegin8gZzOW5rUzdsvXmEW5eCICU5w+JFZtwOd9zmc/2OhLaB/I5b1xgtgc6FVJjMZdGDF0jB+akHAzs6/GBoCrOnKEcNSI7bUuXcdnoioCkK1U4jCCHou/2PGLjnr2j7/rfRfd3PEf3kA1iN2oI/I08ogTJr9gI/Eg0VYuTDZCtQ9vjKZjz49u5R7SOXg59tbwNJxKGfNTvtefs55wOMBt4nHwMRBEQ++QhMeQX0c+YVdExt7ZS8xU11DY1wfftSaGuniMc872sAIeD6euQJnmKE24fe3oNH32vGR9t7FV9vd0cQiLJY1DS4Qsf90H0Ivf0mXJ+9DSCX43bwes62iwWmaGPxYmKlHFEzsuuueL6nhNt8jtvU5EchUQkS3ztpBnQa8dZB6caN6+kSi8EqjFmC77wJ39P/AhGUf5v4gB+02QJKo4G2rh683wc+HFbcVkIWbidwRikVj+KiLc/AueFjCEMmDQgheOGzNpj1Gpx+mHiOL2hw4vh5YpRIlT2PcNvaAk1FJTTOibWibCJiNWrx8txz8faMU9KiEvhwGEmvV7HYooqKisrBjNWoRYLRQxAIhNRKWqkWktKKGym2UoqxVCk9RUclLFiwAPv358+dOlA8++yzuOaaa3DTTTdhw4YNOOSQQ/CVr3wF/f3FZ40dTFAGI3QGHcooFp/tHpALfjgZHuy+ZjlLayJiP/s8mA49/EA3o2hoqw1COLfjlnE6YTn+ROjq68epVaPDoGMAikIimXljJmVgWhXcPRRFocyqL3mhmVITyRKVAIg3v4VFJeQXbgdF08zICUDMYXRZ9MrFybQjjUpIgMKg+8pp1kHL0CV13HZ7xdy+bEWQgCHu5XF0X7tDCVBEwKEWqUDZxJ5AGC8IIdjREcD0aiv0WuWlzrUusbK85KYeLZ2eKKqdRmgZGiSRgGHhITAfuxymJUchsX8fBu66A1MQKSjjlk0KCMU4xe/JcFwjEAInAu9s6sZ/P23NOslTCL4IC4am5EIUQ0nsEV2Chllz0p7XVlXDdsbZSOzdg8hnn6Lip9eg7Ac/BEUXPawsGF3Kwcq1tcJi0KQm+wq7TgwE4li9WxwHvramQ3GbLa1Svu2gECYdk1p8BIDBVRcSMTbzN4FtbQEAeB65v6C2DaXaMXLHbTSRRJRNysKttDIkkqU4mT+c3WmdjQq7AZefOgvz6x3y79RQuO4uaGumKC7x1zdOBUnEkexTFs6FYBC0TRTzdXXimIfrUv6s5PdEJr7jljabodXQoBMxdHsHf9PX7fOgtT+MMw6vS1vFc/lps1DtMOLQabmza6fccTdq/vTnMWv3lwmbSYt9ZdPRY6tNK04WeO0ltP/g2wW5u1VUVFQOJvRaBpzOCIEAQmoSVfoNU5q4lVY/q47bsaPoEfYf//hHXHvttXj99dfR09ODYDCY9u9Ac+edd+KKK67A97//fcybNw8PPPAATCYTHnvssQPdtAkNRVFgbHbU6Xl0e6PY0uqDQctAFxUdoRPd8UkIASGZyx/jzbvhffpJcD3dB6BVudE1NUE3dUZa4PdwDLPnovKaX0E/Y3IshdNrGMxy7wGzZW3Ga4FI9qgEACi3GTAQKF0hrLEgllCOSgCkolr5RR9J/LXkiEpwmHUwaBlFt6s3nEBrfxiHTXMp3xyPsDiZN8zCYdbJYfM0TaHKYRix80uJaCIJi1GTM7fvQEQluIMJLG/5BGe8fAeafK3whCb2eThedHujCERZzBuW9zkULUNjisuEHR3+rAJRoQgCQZcnirpUdhZtMKD61zei6trrUP3rG1F57a9hWX4SbDq6oIxbbw5n+nCkbSZ6zvZQCCHwhVkQAG+sH3lxJn+Yhd2kA61QaEISbvXDhFsAcF74TVAGI3xP/xOG+QthOfq4EbehECQRlW1vA0VRcFn0BRcTfH1dB3iBoMZpxJY2H1r6Mle7SIXJFjYMCreEFc8Hnc0KIPO6Ghn2myDEYuC9YlQCHyg+ekNy3PYFir/uSud7uS09KiGr4zY1+VGMcAsAXzuqEfdcsRQaJv0WQojHwXs90NYoR1NJ0RFsW4vi63wwAMbmENt+9HGovulP0NU35GyLtqoa+jnz8uYqH0gorQ46vQ56PoE9PYP3Sf/9tBU0ReGCpel9nOIy4alrjsdx83K7liiGgVZ1NhWEzaQDRQSY2QgqbJnFySi1OJmKiopKBlaXHSzHIx4Ux0yScKsUlaRraILr+1fAMHvuuLbxYKJo4fbMM8/E5s2bce6556Kurg5OpxNOpxMOhwPOA7xch2VZrF+/Hqeccor8HE3TOOWUU/DZZ58dwJZNDnQNTXDViEUO+gIxuKx68EHxxmMiF8fyv/Q8Wr95HrierozXEjt3wP/c00h6PQegZbkpu/QyTLn9TlBaZSFzMmLQMTh53wdwvpeZYxeMZY9KAIAKmx7+KDviolRd3ihe/rxdUcAvFVHZXZV5k+iy6BCMcUgq5PsOZTAqIfvnTqWWiisJtxv3iefyodOUM9n0WhoUgETRUQmJjMzcaqcJff54yf6mcY4XXdk5kNy44+l8HAjEsbBvO3QaGg3+DrVAWYodHeL1f16dPed2FyxrhC/C4pF3iy/GNJSBYBwcL6AuS7V685HLUPl/vwRTXYNgjEtbdqyEJOrly7gFgLIRZKYeaGIsDy51vVmxoSvvtScb3nAiqys5vncPmPIKaFyZ7j/G4YT9vK+C6+pEYvfOER27GLRT6mFcfJjs5ih0lQPHC3hzfReq7GIBKAB4dZjrlhCCzS0+NFVaYB8iZEqOTsNesSDX8KiEwYKVqUzcgX5QBlF85YP+YruISrsBFEaWLT78fDflE25T53qhGbf5kMaL2fJC9VOnAQDYttaM1wgh4INBMCnHrbamFqZDD8/rpHVd8n1MyZOVPBHQWS3QJxNo7haF2+3tfqzf58GJC6sVncv5iG3bgsgXn4Fw6m9VIViNGpy1+y384tO7YeQHr/EkKooQEzlqQ0VFReVAMX/JfKytPRTbwuJ4otsbA01Rihns2topcJz3NTneSqX0FC3cfvDBB/K/999/X/4n/f9A4na7wfM8qqrSZ6CrqqrQ26u8NCuRSCi6hrmUCzKZTCKZTMrPKT1mWRZ8Kh9p+GMhleWVSCSyPpbcosMfA4AgCFkfsyknCM/zio+TyWRaP/L1qfz6mzHj97+HUcdA4DnYTQx4vx+sIAAW24TtE20wgIvHEe/uzuhT3ONGUhDAOJ2T8nPq/9fj6L3t92ATiUlx7kFIgmV0SMaiGX0KRjlQECAlBAz/Prks4gs9ntCI+vSPN3bib69uRpcnMmafUzAs3kxraZLxfXJa9BD4JNyBaM7PyR+KgAg8zAZNzj5V2/Xo88cQjcXT+rF+nweEEMyvM2fth17LIJrgijr33IEo7EYmrU/VDgNi8UTePhX6OUVjHAxaJue557ToQIiAAX8Ym1u9uOqB1fjunR+AF8iYXPc4jkOfL4xPF58NHgRxWgNPKD4hvk+j6VMprhGb9/eDEIK59facfTr7iDosrLfj5c/2YUurb8R96nBHIAg8qu2ikNT35GPoufvPIDyf1iezlkKS4xBJJHP2yR0Uv682PfJ+TubUPMpAIDZpPifJGa6nBXhCcaze1T+ic88fYWEzaRT7VPWH21H+699m7ZPj/K+BmT0X8dQYayx/nyi9Hq7rboL1pFMhCAKsesAfSSCZ5HN+Tqt29METjOKMxZVY0ODA1Aoj3tnQgWgiKfep1x9DfyCC+XXWtH4I0Qg4QQD/xvMAgFAkltaPUEw8roYSIAgCdA2NqHniP9BMmwEhECj6GiEkObisevR6o0Wfe70e0RFjNzLgOA4mvQaCwCMQiSuee95QDEYdAxp8xudEBAGR1hbwqTYU+jkZj1gKbdM0xfONqa1DghCwrS0ZfUqEQtC4XKBcLvl5NhJBtKsz67mn1KeJOjaiLSaYBBa7O7zgOA5PfrgPRODxzaPrR9SngRf+i+7b/gAikIP296mYPpn1DEK0FgxDIen3yW3nwmGwhIA2miZdn76Mn5PaJ7VPap8mVp+OP+MovDn7dLzSI0qGHQNBlFvEqKrhfcrWv4nWp4n4ORVK0cLt8uXLc/6bbNx6662w2+3yv/pUlui7774LAFi5ciVWrlwJAHjrrbewatUqAMBLL72EtWvF5eDPPvssNm/eDAB48sknsWuXuLTw4YcflvOA7733XnR1iY7QO++8E263Wz5+KBQCy7K49dZbxRuBUAi33norAFGMvvNO0U3Q1dWFe++9FwCwf/9+PPzwwwCAXbt24cknnwQAbN68Gc8++ywAYO3atXjppZcAAKtWrcJbb72Vt0+bN67HkTPK0bf9I3CeNvABP17q6MbeVEG6idgnTUUlVru9eC/1mQ3t02sff4It/iAYm2PCfU7/vuduuB99AKtfezXr5/Tem28ivm0rVrz99qQ4995+/SWwjBY7+/sy+hSMcYh3bpUneIafe4FOscDOU0//p+g+7djbgbXNbrR++izaut1jdu59+sEKAMCOTWsyvk8Osw6evWvx3vsf5fyc3n31eUTcHTAbNDn7ZGUS4AWC3/7uD/LndMstt2B9cx8qzcCj992d1qfA669g36qPce+998KgZdDX3V7w9ynO8ujdtxn9e75I61OVwwjP3rV4850PSnLuBfweGHWanOeew6wDFw3ioXvvwTWPrcWmnfuxesV/EIyyY3bd27NjCzQVVXi7pw/+gTZ4QokJ8X0aTZ9Ge40QBILH778bFSYCl4lJ69Mtf/pTWp9omsK3lzjRs+F1/PWVbdi1u3lEferyRuFr2YjuPesAAK//9zl8/O67oBhG7lP44w8QveOHYNo2Ihhlc/apeb9YJOrN5x7L+zk98/g/AAAdXb2T5nNqae8BANB73wCSMbzyeUvR59599z+IOMcj6e9S7NP67TvwxoaNWftEG03YfMyJ2ERrSnbu5fqchvZp6/vPICkQ7NnfmvNzenVNB+IDrYi0fAaKojDH5EXblo/x3uYeuU9bWn3wtWxEsnd72udkO/0svNPTj22tLaAFHqtXvp7Wp86WvdBrGTz26CNyn+677z4MaPXgQyH89a9/LfoaUe0woq2js+hz7603XwMAtO3ahLfeegsMTSHSvhk7N36meO4179gMu0knf06E5/HQb2/Epzf8Gu0/uBh/OfcsfPq9ixFZ83lBn9NfHn0Mrl/8BjhiieK51+N247+MEfq58zL69O/nnkPDw0+ia+mxcp/e/O638cT3L8l67gHAs7+4Biv+cse4n3vFXiNWeAJgHE6sXbcO9zz8b6zb68Y0bQ+2r/sko0/5rhGEEPzn7RVotzlA6/UH5e9TsX0KeQfwyb5t0NA09m7fJvdpT3s7Xu4dAEXTk65PX8bPSe2T2ie1TxOrTw6zDtVsC1auXIk+fwybv/gQgqdZsU/vXXYpun59zYTv00T7nLq7i4jzJCPg448/JhdffDE56qijSGdnJyGEkCeffJJ88sknI9ldyUgkEoRhGPLSSy+lPX/ppZeSc889V/E98XicBAIB+V9HRwcBQNxuNyGEEI7jCMdxhBBCWJZVfJxIJEgymVR8zPO8fJxsjwVBIIIgZDwmhBCe57M+TiQShBBCksmk4mOO4wjLsoqPlfoRWL+W9D3xCHl39R5ywm9eI3e+tIWwXZ3E/fabJD4wMGH7lGhtIbvPOZX0PflYRp/ab76e7L7gTCIIwoT7nDwr3yH7zvsK8X34ftbPaf//XEbar7pi0px7vZ4geei8H5DPTj4po0/fv2cVufTOD7J+n1Zu6iAn3biCvLW2peg+PfT2LnLSjSvICde9St7d2Dlm597dL28mJ924gvR6wxnfp9fXdpATfvM6+XRHT87P6e6XN5MTr3+D9PqiOfv031X7yUk3riBrdnbL/djf7SUn3vAWufOVbWltj/T1kv0Xnk2azz2NtN32B3LZLW+QH/5jVcHfpy5PhJxw/Rvkvte3pvXps1395ITfvE7+/f6ekpx7p/12BfnNv9fnPfe+cfv75ITrXiU3/2cj+cOzG8kJ171K2vpDY3Ldi8UT5KQb3iT/uO0psuOcU8mdF15FfvPv9RPi+zTSPpXiGrGtzUdOuO5V8uCKXXI/+ESc9P39TtJx91+JwHEk3tOd1o9/rdxJTrpxBXlwxc4R9ekfb+wkJ1z/BukcCBKBZcmu888gHTffkNan8OerydpTTiC/+O7vybY2X84+SdeF3R3uvJ9Tvy9ETrpxBbnjhS2T5nP6eFsPOenGFeS1L/aR3z61gZx4w1tkf7e3qHOvpcdHTrpxBbnvje0ZfYrt2UVCWzaRRCw2ruders/Ju3oV6brhlyS2fx956K1t5KQbV5C93f6sn9Oudjc56cYV5I/PbJCfD0Zi5MybV5DL/r6KsCxLWJYld7y4lZxw/RukxxPK6EfPw/eTnWefSi78+dPklmc3pPXjJw+uJl+77X25T8EPVhL3+++R3r/fRfad9xUSGegv+BrBRaMkFouRPzy7iZx4w5skEIoUde7d8+oWctKNK0jnQFD+nL56y3vkqvtXKX5OF976Hrnqwc/kz8b/+itk5zmnkj3nnkbaf/pD0nnn7WTvN88ngRVvHJDrXscffkt2nXc6EVLtVjr3dn/9XNJ+46/G5dwbbZ+k69v37v6QnHzjCrKv2zei7xPb10t2nnMq6b3vbwe8T1Lbx/v3aSR9evPvT5AdZ51Kgp99Kre97f+uInu+d9Gk7dOX8XNS+6T2Se3TxOlTMuAn63/yU/LrS39L7np1OznhN6+TP7+4SbFPe799Ien69TUTvk8T7XPy+XwEAAkEAiQfRaf5v/DCC7jkkktw8cUXY8OGDbLNNxAI4JZbbsGbb75Z7C5Lhk6nw+GHH46VK1fi/PPPByDaj1euXImf/OQniu/R6/XQ6zPz77Sp3FHNkIIH2iFZpEMf63S6vI+HHqOYxzRNZ30s7Z9hGDAMk/F4aNuzPR7aj+TunQi/9F8cfsdyLGiswNI5VdDWVqJsSFbJROyTUFkFDU0DHndGn+hQEHqnExRFTbjPyZDKgaOjEcXzTaPRgAoGwDRNnTTnntVsRILRQQMCqSdSn0IxDjUuo/z/4X2qcVkAAIE4kfdZSJ8YjRbvbOqBhqaQ1OjgCbOgKGpMzr04LxbvsZn10Go1af1zWnSgGQ1CcT6jf0Pbzgo0KJqB2aCBTje4zfD21qZyPt1RQS7mtaMrAoqicNi0Mnn7xI5tSPb2oOZPf4H/uacQ/WwVjnb68fHi8wv+PvnCEdA0g3KHJe35w6aXwWY24qOdA7j4xJmjOvc0Wh2SBDBqmbzn3i2XHg5BAGbW2vDcp634YFsfQrHkmFz3QnEBoGgcsv416Gka2xafAW0wMSG+TyPtUymuER9t7wWt0WH5gmpQFAUNx6Hnd9cj0bwbxsWHo/s314Lr6Ubjk8/K/bjohNlYtduH5z9rxwXLmlChK65PnZ4I9KlrAdfRCi0RYJo2La1P1PyF0Gu1mBZoRyDKQqdzZO2TPyIuiaott4Gm6ax9BYByuxlahoY/yk2azymUysuudNpw9hIbVu3qx8ptA7i8xpm2fa5zL1UzEi6bMaN/vc8/i+jaL9D09Avj1qd8j7U8D9/WzeDaW1HlmgkACESTmF6j/Dmt2NQHADj/qKny81aTAacf0YCXv2jHr/+9CVxSwL7eEOrLrahO/Q4N7YdpSh0iDA1nzAeO0Gm/T4kkgVGvkfft+8+/QOl1qL31r6i4/ErQhsFCSLn6R3gevscehGHeAlTa60FRNIJxApul8HPPHxOX21U4zNBq6FRf9YglMz8bjUaDYJzHLLNO3rfx0MNQ9Z3vwbz0aLkQHB/wg7ZYQTGD2eTZ+pHcvBGB1Z/A+a3vQF9dI38ehXyf+O4u+NevhXnJMuhSY05TYxPYdV+A6+mGrqExre0AQHgeGjYBncWa0b+JNjZiGAYzaqygaQbtnjhOXlSDaTWOjD4N74dSn2K7d0JH0zDNmXfA+zS87RPhGpGtH8cvm4O+92iQcEjef/3td0JIsJO2T1/Gz0ntk9ontU8Tp088y8DesQdTzXPw/PpO0IwG9RW2jD5pBAFUJARNReWE79PwxxPhcyqUoqMS/vjHP+KBBx7Aww8/nNa5Y445Bhs2bCh2dyXnmmuuwcMPP4x//vOf2LlzJ/7nf/4HkUgE3//+9w900yY8jE0sQGNIRPD3Hy7F0XMqQVJZIBMZ2mgEbbEiOdCf8Zpx8WGwHHP8AWhVfhireLPBhzKrWwMA4TgI4RAYx4Et+lcMei0Dr8kFX0U9SHLw3CGEIBBlsxYmA4Byu3iD6w4WVxxo9a5+eMMJnHF43YjeXwyxBA8KgEGbWWBLKqrll5SQLETiSVAATLrc82ZTysSKnRv3DxbW25B6vHjqYKGg8Efvw/2Pu6CtqUH1Db8HbbWhLOxGvIgib1JBpuEFinQaGsfNq8S+3hBa+8MF70+JWKqwW77iZAAwvdqGmbXiwMCaOmdCsbG5Fg0ExfxHIxuFYcEimCrKC65U/2WFEIJPdvSh2mHErNTnEFr5NhLNu2E/96uovvH30E2bDiEUBJ+aMAMAhqbw7eOnghcIPt2VeT3OR5cniillJtA0hUSrWHleEpDkY1gsIPVTMdXXikA4nnN/nlACei0Ds0IxweFQFAWXRT+pPnupMJfDrMPh08pQ4zQWXaTMFxH761QoTpbYuwe6hsY08fFAI50PbFur3GZfjoJym1t9qHYYMa8+vcDeBUsbYNZrsLMzgB5fDJUOAy48uinj/e1XXAr3w/eDAlDBBRFn0wt9ReJJ+fwS4nEk+/+fvfOOkqQquPitXJ27J+edzTmQl5yTCipIEAVFRFAyCKIgAkoUEOQTBAUBAUEko4LkvORd2JxnJ8fOofL3R3VV5zQ7s7MD9Ttnz4Hq6qo3M93VXffdd28f2JY2UA5nyd+bpmmIvP0GVFGEJgqIffIRoh+8b5Z+9FVYUDYcFuCxs2Dp1Fd7B0/nLSeLCjJkVYM3rZiMbWqB78RTMt5zlMcLgqIwfP+96P/99UXPL2xcj8gbr0ITCv89hC2b0X35xYi89Xrm9vVrMfLAXyB2p0rj6KT4Kw/05z2WGtd/P5OhWCr26ceY/vGLoFT98//7B04b9bES6/XlmtysOWM0uq8GlEu/BqjJLhMAIBgWlNM5UUOysLCw2KkhbXYQBIEZXgpKshC4qcqes5+hwRjlsRbjQ8XC7bp163DAAblCmMfjQSAQGIsxbRcnnXQSbrnlFlx11VVYsmQJli9fjhdffDGnsMwiF0O4VdK+1PRecwU6zvj+RA2pbBqvuR51F16as73q+z9E9Y9+MgEjKg3p0gURNZJfuFWCAQCYVMItRRJ4b8ZBePMbF4C0pS7sMUGBompF26urnBxIgsBgsLgYk83zH3WZghGAcRVeYqIMO0ebDth0fE595mykRMt5VNCPQZK5x0inrcaB3WfU4NXPe/HWqj6oqoblm0cwo8GV0Xqu+EcAmgGZdB3RtXVwxYM57efFMIVbF5fz2KGL9Jvn17/oLft4+TDGYyshWGfjsun7RxLjI9wOhRIgNBWsEAUUBVPFIQSiovkF5avI2u4QBoIJHDC/3nytJ1avAkgKvu+eCoKiwE2dDgAQtm7OeO7uM2rAUCTeXVOZcCspKvoCcbQkJyyM5nl2ytScfZn5i8DLAoQtm3MeS2ckIqDKyeZ9v+bD52RNMXQyYEwSeR0MSJLAAfPq4Y+K6B6JlX+M5M9rXL8MVEGAMjwEpqV17AY8BjCNTQDNQNq2FVXJMQ8X+JupqoZefwytNY6c10BLjQPP/uoQ/OfXh+GJyw7C387bD8fumfuzKqEQmMYmcDNnA5wt57oaFxXYkpNRUncXoGlgWtughEOIffIRpAKiIwBE3ngNA7feiNDzT4O02UG5PRDWr0W9Wxd8Byr4LFRVDVsHImjOuqGyczSiiVzhNhg1/u76Z4kajxecRAYAsWMLYp99XHwMYf27I+n2FNyH5HkIa1cjsWFdxnYlGAQAUG6vuY3y6P+thIL5zxeL6se0TwLh9qMPQPz7CbTagK/t1oK22tGLhUxtPfiFi/X3gkXZcNOmoe3+R+E55lvmtuiHy3I+wywsLCwsdAiSBGGzoc2Z+g6V/T0DsITbHUXFwm1DQwM2btyYs/2dd97BtGmjn0EeS84991x0dHRAEAR88MEH2GuvvSZ6SJMCyp0UEtO+JCvBIEjeNlFDKhtu+sxJd7Eo5bgleBuqf3IOHHvvuyOHtd2wNAlBynR8heL6TaLbzkBTFP2flimMUaTueDMckOXQPRzFp5uHsd/cOtR5bPDa2fEVbgW5oPBYjvsL0AVIJ1/YeWxAEAQu+/YCeOwsbn12NT7aOIRATMQu06oz9pNHRkAn40AAwLn/QeiZsSuEChy36c69bBa1V6HKyeG1L/py/maVkDCF2/yOW02W8x7fxY+v43YoJMAuxkCRJBJrVuGA52+Hpiol/45fZt5e1QcAOGCePuGpaRoSa1aBnToNpE3/PGDb9c97cXPmTa+do7HrtCqs2DpS0d+szx+HompoSUaEOPbeF1Wnng6muSVnX/uSXQAA5Novih5zOCTknYwoRJWLgz8qQJ0kor0h3BoTYoZTs5JVB6Hk3yh7Uk3u118DO5s4RNA02OYWiB1bUeUqfs0diQgQZRWNvvzfYUoJ+posQxMSYKdOQ/Pv78DWqbvkCLcxQYad1z8TxK5tAAC2rR3Cpo3o++2vEf/ko4LHF5LOScc++wMAuDlzoYwMo07VVzf0V+C47RiMIByXsGCKN2O7g9Mdt9nXVn/Waye67F10nHoCoh8uy3t80uWGFosVXYVlfJcxvtvkg65vAMHx5sRM6rm66Gt8D03/b+OxbNRoUridBI5b0m4HAeBPP1iMC4+Zt13H8hz7bTT99iYQFSyvtNDdtXRVFYjkalFNltF//dUI/OvxCR6ZhYWFxc4LaXeAlwUsbq8CRRJorMr9TmWsjKHrLKPkeFLxp/6ZZ56JCy64AB988AEIgkBPTw8eeeQR/PznP8dPf/rT8RijxQ6CNB236cJtAJTXO0EjKh81HoOwaSPUREr0kwb60Xv1rxB5+40JG1cxCN4G5yGHg583P+/jlNMJz9eOgW3+wh08su1jargL8z54LsNpFIolsya3rcSWE47FluO/ji3fPhqhV17KeG6tpzLh9oWPuwAAx+yhO6Wq3RyGw5U5dishJiiwcynhUZNlbPvJD+B/7GFwDAU7S5d07EUTcsYxilHt4vDzb81HJCHh2sf1Zstdp1Vl7KOMDIOqqjH/3/vt72Dz3sdCUtSyXaOG8FGdR+SiSAIHLWhAz0gM63ry30CXQ7yIcCv19WLLd76BULIVPR2XffyjEuxSDFTSAU1DBS8nJtWS+bFE0zS8uaofdR4ec1r0zwRNFOE69Ai4Djnc3I+d0g6QJMQtm3KOsc+cOiiqhg83DOU8VoiuYV2EaanRRRh+5mx4jz8JBJ07UVK1eBEe2PX7WD93v4LHkxUVgZiImkqEWycHRdVMMbMUWwcieO7DztI7jhOBqAgHR4NLRrfUuo24mfKvgcb70p71vpT6dIc9Xd8wFkMdU9gp7ZAHB+AhdCfpSIH3aq9fFz7zLesrBzWuO5cNR6eNpczIF0B3iUuKasbeSNs69PG1tKbcogVERyDpUKFo83fMz54LAPD0bwUA9AfK/zuu3BYAACxoy1yhY+dpaEBOdE4gy3GbWLNaH3t7rsMdAKjkCiElUjgyRwkFQdoded+zBgRJgm2bAilLuDUMA5Qn5dblZsxC+2PPwPvN4/Mei3Q44D76G7obeifHFJfj0ZKrbbKJr/oC0WXvQpMmz2qAnZXEurVIrNfd3qZjexII/xYWFhYTBelwQI1F8YvjFuDmH+ye18Dk2O9ANN14mxXhM85UXE52+eWXQ1VVHHrooYjFYjjggAPAcRx+/vOf47zzzhuPMVrsIGifD4699wPTpDucNEWBGg6ZEQo7M6H//Rcjf/sLGq/7vSl0KiPDiC//FLZddpvg0eWHIAjUnX/JRA9jzGmMDWD2mrcgD3wHTHLmzRBCvMNdgKrAttseIDkeTDLDTpNlgCBQ6+axtisIWVFBU6Xnld5dM4AGr83MfK12cegcikLTtLKXR1dCXJTN5bkAAIKAPDQEYZO+CkFfal1c8IsmZPhqyr9R2GdOHY7ZoxXPf9QJiiSwsD11Y64pCpRQEPzcTPHfyJFNiAocfOnL/HBYAE0SBZ3AhyxqxFPLOvDqil7MaR7d9aBYxq0hGuTLhEw5bnOX+44FQyEBjCqBra4GqamgEkNwCpGvrHC7oTeMvkAcxy2dYr6HSI5D9Q/OyNiP5Hkwjc2QhwZzjrH3nDr84fnVeHfNgBm1UYquIV0ka66yQ1MUQFVNZ1Q2TrcD3VXtaBYKT0wYEyjVrvLzWY2M55GIkNd9ns1tz63Cqm0B7DWrBvXeHb8yJRAVM8ZZkxRuK5n8MpzwOe9LTQPT3LrTOW4BwHXE0bDvvid4noWdpQvG0/QkIyPyuUPKQU2KlKTDgdDLL+Kwj1/EU/O+aT4eT2bH2pMZt3R9A/hFS8A0NZuCrVIkQkwa6ANdV2c6Jw3hVtu0Hk5+VkV/x5UdfgDA/DZvxnYjfzeayFwtYkRkGLE7ibWrQFXXmJ/Z2ZDpK7J8+eOb1HDYjIAqBjulHcKGdZD9ftDJYymhEEDRINIilgiaLioCM3X1qDkrf/HwzoYRHWW4hMtFUxT0X3c11FgUpMMJbuYsEDSN6jPO3infmzs7/TdcA7q+Ec033ZZybE+CqA0LCwuLicL3ne8C0OD02gp+16WcTlBztm81iUVpKhZuCYLAFVdcgUsvvRQbN25EJBLBvHnz4LTC3Sc9lNeH+l9caf6/EgoBmjYpHLdGTEK6iKAE9BsZyjN5MmLTCTz1BILPPYXGa27IKejZqWF5aJpmupUAIJR099g0/Ua35qxzzRtETdMw+Kc7oIZDqFt4HDTowkmdp/jNtiir6PXHse+cOlNgqnZxEGUVkYRsllqNJTFBQUt16rJJUBTo2jpIA/qyYq+DNV1ehYgKMpxliKnpnH3kbKztCqLWw2fcfGtCArYlu4GbOcvclli3Fns+9QdsdS6GIB8ERxmXeX9EhM/JFXQCzWl2o6nKjjdW9uHso2ab7tRKSAlEueOR+noApJbfp7Mjyski9e2YevujCP73eUTv/COcYvQrK9y+lYxJOHBBSsApNBHSdPMf8t70Vrs4zGvx4qMNQxBlNaMsqRBdw/r1oqXGDmH9WvRccRlqfnoe3IcflbMvQRCo4gjYNq+B1N8EJo8rdLhA4V4xjFiF4bCAafWFl3sDwIaeEFYlXY7bhqITJtymxwDUuPXxVxKVYBRXZTsoHHvtDcdee4/BKMce24JF5n/7nKyZ0Z3Ndjtu0zJUhQ3rMXXbcpBtB5uPR03hVhe93UccDfcRRwNIc6gWyGfVNA3y4GDGtZtubIJj7/3Atk+FM5Q/m7YQK7cF0FbjyJlwMMYWFWTUpG03ohK8dhZKJAJpWwcc+x1Y8PhmB0IRB7Hr8KMAufSYjdxqsWOLKdyyU6fpQm3WdSa2/FMQBAHb4l1KHndnhrDrr0EtXn7+NACosRj4RYsBRYXU34v48k8BkkLt+ZbYOBpItxtqWH9Pmu9v2+iuDxYWFhZfBZz7F/5uYCBu6wDldk+qXp7JSMXCrQHLsnC5XHC5XJZo+yVFCRrCp3diB1IGpnA7kCrEMZwuO7PwPPzQ/RC3bEbjb36X85g8Mgwl4J90y7gInoemAVpabIXhuOUZSi/SSndWqioADbGPP8C8kAbw+2IwWFq47RmJQdU0tNSkvnQbS/2HQokxF241TUtm3KacaWLHVsj9qdIuj4PF2u4gVFXLK4IKkgJJUQu6YDVFAUFR5vmMm1iepfCns5Yi+5Ck3YHGq36btZGAu28Lahubyi4o80fEog5DgiBw8IIGPPLWZnzR4TcdzpVQaEk2kFpiLHZt02/g07L7OIYEQ5EIj1M52WAwgVqP/nqkvT5QJAHHV1i4fXfNgCm8GnRf+DNws+ag9pwLMvalHIU/+/eZU4vVXQEs3zKCPWfWFNzPoGs4CgdHw+dgEd66BVAV0FXVBfefG96Kg959GIn96vMLt6HChXuFMNz05eQbP/PBttTYh6LYY0bpn3EsUVUNwZhoxlkAughHk8SoohLyOeF3ZjRNgxqLosrFYdtgfhej6bgtkHFbCqa5Fc233gnK40XkrddBgIAtNGRem+NC8prG5V7PCYYB6XCaJaM545ck8LPngpuVWuZPEIQ5ee5c/54pDJdiMJhAXyCOr+2aJw86ObZYlghsxBd5nSyEtZ8DAPgibhnbgoWo/vFP877XDDxfO6as8dr32AtUdTW4adPNbVWnnJZ338E7bwPtq0JzHuE28s5bCL34AmrO/GneEsOdCaahEfa99ila3JYPyuVCw+VXAdBf8+KWzdBEYVKshNsZodweM19ZjesTO5PtO7aFhYXFzkbvNVeA8vrQcuudEz2ULzUVZ9zKsoxf//rX8Hg8aG9vR3t7OzweD6688kpIRUoLLCYHQ3/9Mwbv/iMAgG1uRetd98F15NcneFSlYQzhdjBNuE3eMO3MwrPU3YX4ik+hqWrOYynHsHcHj2o74W3QoGXkDRtuSfupZ2Dav57PuOkgKAq1518CurEJnl696Kgc4aFzSL9Zb6tNfek2lkWPh+gmSCpUTcu4SU9vxlYiEfgcLBRVQ6TADbdxI+5IP8ba1Rj4w83ouvBn2Prdb5u/t8TKz7HlpG8h8u7bAPSs2XLiH5ha3YHsEUIQyhRugzHRXDJbiIMW6Dfsy9blLo0vh2IZt+K2rQCAwT/cnLP0niAIuGwMwrGx/3zRNA3DYQFzI50IPv8MCJYDxdDgFMEU/sab/y3vxvItIzvkXOXQ649jZqPbnHiQh4cgdmwBtNxrlBqLIvzay0isWZXz2D5z9Wvye2sHch7LR/dwDE1VdhAEAaFjCwAUXWnAuD1QVQ1qgXJH4xqQL7e5EFVmwWDxLMlAVMSrn/eazbqdQ5W56MaCiCBDUTX40t63JEmgxs1X5LhNiDI4hspx0Y88+hBCL784ZuMdSzRNw7YzTkX/jb9FlZNFMCZCVnJfn33+OKqcXMFCyVKQPK8Xn9bUgm5oBEEAnpgfoqyfK5oWlSB2bkPv1VcgllZGxrS0gSwwuUGyLBqvvq6gYGnn6ByxtRBfbNO/Kyxs9+Y8ZkYlZH0mGZMTXgcLqbcHIEnwcwsLt+yUqfB845tjUgLLNDTCuc/+ZYmPlMdb0LUs9fYgsfJzPWppJ4efPRcNv7xquzoLCIIAN216UYHdojiUyw01EtbjeDQNdF395PuObWFhYbEDGXn4AWw5+duQ/f68j2uyDMU/MulK4icjFQu35513Hu69917cfPPN+Oyzz/DZZ5/h5ptvxn333Yfzzz9/PMZosQMR1q42bzwIhgHT1GwuZduZIT1eECxnthoC6Y7bnXf8lMsFqCrUWO6Nv+62dRbMedxZoQzHbTwVGWC4e9wFXLAEQYBpagYXGgGhqWVl+xkuq9aa1I3xaJYKl0tMzMwzBAA1lFo2Kg8OmOJnMJpf+DFuxNMdt8N/+ysib74GJRKGbdESqFE9V1GTJGhCAvEvlhce06cfY/D//gCpp9vcRnq8AMPAkwiW5bhVVA0JSTFv8IPPPY3uX1ys39ik0Vyti1SFliWXIpH8/XFZwq0qirpwkMQQcdNx2uhxcdwGYxIkRcWM3lUYvu/PYKfNwLR/PY/P2/YY15I7g4So4JZnVuHGJ78ou0huPDEc4elRHonVKwEA/LwFOfurCQGDf7wV4ddfzXmsrcaB5io73ls7ALXEz5YQFQyGEmhNZj9LHVtBOpygqgu7WDmPG6oGSKH8S7dHihTuFSI9KsFAUTXc9d+1+GzzsLntP590QVJU/OCQGeAZyixW25EEkj9f9oRLtZvDYLAyx62NyXxPaqqK4NNPIPr+u9s/0HGAIAjQNTWQtnWkXNJ5rrk9I7FRu20BQAmHIfX1QpNEMPWNIAkCvnjAvK6mZ9yKWzYhvvwTc/k1ADTfdBsaLv91ReeU+nrR/YuLsWBT+Y7blR0BALnFZEDqsyaWdSyj2I6hSHiO+RbaH34ib1RNucjDQ9j20x8h+NzTZe2vqSrEjq3QVBWaLKP/pt/lnSig3B4owfzCbXqUxZeVvuuuhv+xhyd6GF8aSLcb0DSo0QhsCxej7d4H4dzvgIkeloWFhcXOi6ZBS8ShxvN/15UG+gBVLboix2JsqFi4ffTRR/HAAw/grLPOwqJFi7Bo0SKcddZZuO+++/Doo4+OxxgtdiCkxwM1FEzmrw1A2Lp5UjTZEgQBuq4empi64Xbssx+qTvsRKHfpsoyJwijyUPM4ShS/H5Sv8iXpE43q9mF5w0LQzallm0ZUArNmOSLvvJX3eUxdAyhVgVOMYLAM4dVw3LamRSUY5Tzj4biNZ+UZAqn8QsrrAxTZjBso5NgznLhGCZgqCBA2rodt1z0w5a9/R8OV14JOilW2JbsCJAVleDjvsQAgsW4Nwq+8lPEeJQgCqrcankQIglRauI2LmT/X8P33QFi3GlLXtoz9OIaCg6NLuhELn8dw3Ga531QVNT89H94TvgsAkLZty34qXDyDyDiUkxkCl1uJAwQByu0GSVGodnE7JCphXU8QiqphMJQYtZN5LDGc8ekxI4nVups2uwAPACifD5THC3HLppzHCILAfnPrMBwWcPeL6/Dsh9vw9ur+vFnF3SP6e7ml2q4vB+7YCnZKe1GHOe/zAgDi/kDex0cqdNzKgwOw927NeC4ArOsO4sn3O/CLhz7Bcx92QlE1PP9RJ6qcHA6cX4/martZrLYjMYRKX5ZwW+vmEYiJpiu0FHFRyYlJUPwj0CRpp/4Szra2QQkGUE3p14Xs61JclOGPimjYDuE28sar6Dz7dCTWrwPd0ACCAHxxvymCmo5bloLY1QkAYFrbyjp2dNl7GPzznTkrDCivD8KGdWgY2AJJUcv6O67c5keVk8srUqcct5mfBdnFdqTdYcb05EP2+9Fx+ikYfvC+vI8rgQDk3h6oieIZ7wYjD/8NXRecDam7C0o4jOj770DcnHsdodxuaEIiYwWPgSncToKl7ko4jP5bbqjIxa6Egoh9tCxjYtNi+6Cra0DV1JoxCRYWFhYWxTE+YwuVa4pbkqvk2nfuyKIvAxULtxzHob29PWf71KlTwbLll4BY7JxQbg80UYQmCAi9+G90X/gzSIPlLXWdaFruuBtN199i/r9t4WJ4jzux6M3IRGMWmCTbq9NRAv6dOp+3EGp1HZ6deyzoRbua24IxCTxDIfL0PzH817vzPo9uaABT5YNdjJXlGOsciqLKyZkiKJASacZDdIvmyTM0nECtd98HbsYseO36WIKxAsKtERmRPIawYR2gyLDNz3UzEiQJyuuD4i+8jF4Z0R/LFvi1qlp4E0HT5VqMWFYzOuX1ARSdNzPQ62ARKOAmLkWhjFuS5+E+/Ch4jj0OACB25hFu7QzCcQmaNrauVMPZ7ZBiIJ0uEBSF6LL3sDi4oWBT/Viytis1YfPcR53jfr5SGKKqM0O4XQnKVwW6oTFnf4IgwE6dpjvnlNxJgoMXNoIiCTy1rAN/fGENrn5sOW59JjdWodsoJqu2QxkahBqLlixkdFTpy6wTgfxuvOGwAIYiy8663nbmaRj85UVwcVTG335jrx7FwNIk7nhhNX7x4McYCCZwzB6toCkSLdUO9AfjZU2SjCWGqz/bcVtrTl6V57qNi3JOfInUp+d20425f/OdBWMlTQ2hX+uzc4m3t5gMyHR0Ug4nhvY5GutrZppFi+ZkFEdDSS4hpNNc4vEvVmDk0YcyijrNx1Z+jvCL/wayrmkkz4Ntn4qqga1AMle9GOG4hM19YSyc4s070WEv4LgNxiR4nSzE7i4EnnoCUtpqpXyQNhsU/0jBzyOjtMz4TlMKftYcAPr1RQ0F9Od6cqMTyOS2fHEJxk3kZHHcRt95E8L6daV3TJJYtwYAwM2ZO15D+srhO/EUTPnr38HUNyC+8nMEnnqiaOGehYWFxVcdo8CxoHC7VY853J5VOxblUbFwe+655+K3v/0tBCH1JVkQBFx33XU499xzx3RwFjue9CZkM2PV7Z3AEZXPzizQFoJ06c3lap4vjo3X3oDq03+yo4e03XDJZbdCmlMoFBPhsbPQBAEEx+d9nufY4zD1wccgNrSVzLjVNA2dQ1FzabWB18GCJIhxWeZuOm7THKNKKACCYUDwutPJnRRRCombxs2zsXyVaW5FzU/Ph32vffLuT/l8kIsJt/4RgKJN57aBeMg38PS8Y80xFyOWLUiTFLjpM/Luuz3CbaJACZLhFqZcLlBeH6TOjpznungGkqJCkMpzEZaLEanBC1Ezb3H4wb9it1Wvwh8R8uZmjiVru4IgAOw+owYfbxxC9wQsuU8nnHQ1G2KnEolA3LYV/LwFBd2v7NTp0EQhrytsZpMbT19+CO47d1/8/ge7Y0aDCx9vGoKU9Xtd161f/9pqnaBqatH2t3/Ae+L3io7V7bIjyLshaPm/xgyHBVQ5ubJyodNpoxMZIuCmPn1sfzxzLyyc4sNnW0ZAkwS+sYe+osBw/Bvi844iENVF9mzHrREXMxgsb/IqLio55VpyUrhl6nde4dYQ9Lyafq3PnmjZ3mIyIE0YTLpNgkecgDV1c03BNmpE33C06TQl+dT54is+Q+Cfj0LOs2pCHugHSApUngI+fvYccPEIvIlgybiENZ0BaMgfkwCkruvRtLxco9jOa2cR/+QjjDx0H6TurqLnIXkeBMtBKRBNYnyHKbd8y8hpTaxZZR4z33OZhiYwU9qh5enQUGMxECwHgh51z/IOg7Qnb3xj5V/jhbW6cMvPtjJtx4PYxx9i5KH78kaVWVhYWFjomI7bAp9fSjgEgmXBtrTuyGF9JalYuP3ss8/wwgsvoKWlBYcddhgOO+wwtLS04Pnnn8eKFStw3HHHmf8sJh+G40ENBXU3IUVPimVoACD1dCP43+chDfRD6u9Dx49PxcBtN030sIrCz52P6rPOybu8kps+s6CAtjPDQcF3VzyO4JOPm9tCMQluOwM1EQfB51+6bAgs5ZTr+KMiooKcI9xSJAGfkx0nx61+42tLi0rg58yH84CDMfLQ/Qg88yS89uLCbSRhRCXoN5q0zwf3kV8r+GFHV1VD8fvzltcBgOwfAV1VlSNO0fMXY23tHAhKaYeqISbbWAqapkEJBqAKCYRe+k9O6Ysh3JbKLM2HEcmQLdz233w9On70fWiqCn7ufJBOV85zDSEx3zL77cGYIGDiEfPaR3t9cIpRaChdUrW9rOsOYUqdEyft2w4AeP6j4uLJeBNJ5ggbr0/S4UDrn/4K38nfL/gcY2lUvrgEQJ+kaK9zYtfp1dhvXj3iooLV2wIZ+7y/bhBVTg7TG1x67I3PVzJb3WNncMc+52Hk+B/nfXw4LFSWb/sjfZKsSYtmXD829Ibhc7CYWufEzT/YHSft246zjpxtZqsa16AdnXMbiKbKpdIxHLfl5IQD+oRK9ntS6u8DADANO29UgjGh7FaSwm3WNb93ZGwdt0CqWNHIOzeuaTaOgpZIADSTkUlvTAYZRanpyAP9oGtr8044c7PngSSAlmBXyYKyL5LvpYVT8r9fjKiEdMdtJCHpxXZOFon1awGCADdrdtHzAPpEc75YJwCm+FpuNBXl9YFpbkFi9Upz5Uq+sjLP149F6x1/BpsWvZT+WPUZZ5V1vomGoCgQHF+RSJhYtwYEx5dcfWBRPvLIMALPPonEhnVpju3RXyMsLCwsvuwY34EKOW5rzz4P7Y88Oek6eSYjFU9Te71eHH/88RnbWlsthf3LAr9wCap+8GNQvioowQAoT/7ldzsjifXrMHzPnzBM3g0YQtdO7sJlW1rzinZqPA4lFNRFOWZyRZBwPIsZwxshbkr9XOG4hKYqOzRBLNgkrWkawi/9B4uG+vCM0gpV1cxm+2w6k8VkbbW5kwrjlU8az4oUAADfCScDADrO+D4orw/eg78OIFXGlk00rZxMUxQowQDoPI4rg9rzLwbBsCDI/HNsyvAQ6Dw5lBxLgdBUCNHSOW6mC5ijoUkS7Lvsitinn2Do7j+CbZ8KfnZqmabPyULVNITjUs4S7VIUyrgVt3WAdDpAkCTqf3Fl3ue6bPpzwgkJtZ78ju3RMBhKAJoGx8JF4JMRQJTXB06IglQVDIWFMT1fOiMRAf3BOI7etRm7TKtCa7UDL37WjdMPnWG61nc02Rm3RmlgMbgZs2DbZXeQDmfR/QBgz5k1eOC1jfhwwxAWT9XjPXpGYugYjODoXZtBkgTEjq1Q4zFw02cW/RJYnRQoR8K54rqiaghERcxrLc/9BwBMsg23XokgKnghSApoisSW/jAWteuTIyxN4CdHZgpcLUnhdtvQjhVujUkFrzPbcav/XkqtWgD0a25cVHKiErjpM+E69AjQO7Hj1rHnXuDvfRB+yg588F5OVMKYOm5t+jF8y9/Ghe8+AvGga4EZNeZqBQdHw3n4UbAtWpLxfDJtIjwbeaAf7LTpec/Lz5kLgiDQEuouGZWwssMPO0tjWkPuhBeQ+rxKP46Rj+x1sFD8IyBdblBlvH8ptwdKOJz3MdNx68o/jnzwc+cj/MpL5qRPpX0E9t32qGj/iYa028sWbjVFgbBhPbiZsyflarKdFWVkGCN/+wuqTj3djDAxlgFbWFhYWOTCzZ6LphtuLXo/YIm2O4aKhdu//e1v4zEOi50EftZs8EnnhRIMgCrhetqZsC1cBG7WHJAOJ5iWFrDNrXAszb8EfWcnvnIF+q+7GjXnXgT3YUdO9HAqguNoSBQDOXmDIisqooIMt52BJiRAcIUdtyOPPIi5hAdPtrcgEBNNV1s2HYNGMVl+4XZTX7io8DsaYmJuxq0BXVsHqacbdSWiEqJpIqm4ZRO6f34+qk47A97jTsi7f6m8QPfXjsm7D9+5CVe+cSMSnu8DB8wsegzTccvRIFkWDVdei/jKz9F75WWIf74iQ7g1y9eiYsXCbUJUwNIkqLS/iZpIQO7vhWO/A4s+13TcFhDER4s/IoJjabT86ipzG+WrAkUCdimWjNwoX/yrBCPfdk6zBwRB4Jg9W3HXf9fijZV9OHKX4mLpeJFyhOu/b2HTBhA0U9TxxTa3oPE3vyvr+DMb3fDYWXy8cQhnHjELAMxStqWzawEAweeeQvjV/2HKw/8CVUy4dXGYObQB1GsbgaXnZDwWjIlQNQ3VrvJE995rf20WW1aLugDlj4iIizJEWcWMAqKY/7GHQf/jYTDzz9nhBWVGjrbHnuW49ejXzFKrFgBAkFSompYzmeLYa2849tp7jEY6PpB2B0i7A1XJ2I2RPBm3LE1W5LrORo3HQdjspnDGsjTcQtiMkki/djr2XJrzfMrjBaAXd6WjRCJQY1HQdfV5z0vXNyBw2vl4+3MJ+xYRbiVFxdruIBa1V2VcV9MxPq8iac7dQCT12lHjcVOYLgXldkPq7837mGP/g8C0Tqmo0I6ftwDRZe+BdDjh/c7JYBqbcvaR/X6E/vs8+HkLYF+ya56jTB5Iu71gK3c+6i+7Yqc3H0w2jDgOJRSCGo2C4PhJEbVhYWFhMVFQLheoPAXFACB2bEXsk4/g2O8AMAW+01iMHdanlUVBNFU1bzwmA3R1DZpvvn2ih1ERSiiIznN/AucBB6Pmx2entidv9Gjv5BHODTiagkCxUOK64yuUdPG5bQzYqdPAtrUXfC5T3wDn1m4AwGAwUVC47RwyhNtcp0SNm4eSzPDzFXj+aIilNYgDgCoI6L/hWjj22htMXT2EtatByyIcHF1YuE0TxuIfrAQAsFMLh7krwQCEDevBtk8FXVOb87jvxFPyPo+rrgKhaSBGBvM+nvlzpVxj5vNnzQHBskisXAEkXcUA4HPov8/gKHJudWdflts2mWfLtk0BoP+8gWeeBD9rNhx772fuZwq3ibEVbmOCnPFzA7rjliIJuMRIXjfnWLEmKdzOTbpCj1jShPte2YDnP+qcMOE25bjVfyeD/3c71GgEbfc+OCbHJ0kCu8+oxquf95pRBu+vGwRDkdh9ul7qJA0OgLDZS0b0VLs4LOn7HA3rNkD7xdkZrjRDtKxylZ5cUAJ+xD/9CPY990bD1dfj014CeH8Aw2EBvX5djJ3RWFi4JQlgOhGegKgECS4bkyPYVTk5ECjPcVsovmQyoCkKxC2bQPA2eOxsTsZtrz+GRp99u1YMNfzmd9DS+hyYZEGfOqhHSWR/JmRjRiXkybD3nvQ9cFPzO24JggC961JE131W1HE7EExAlFVMry/slqVIAjxDZRzHEP29ThZqLFa247DqBz+GpuQfD9vckjfOoBjOAw6G86BDC64oAQAtHkPgn4/C8+0TcoTbjh9+F/yCRaj/+S8rOu9E4f76N4EyX44ERU06R/FkINXjEdJf+1ZMgoWFhUVRNFWFEvCbpdnpxFd8hpGH7gM3fYYl3O4AKs64HR4exjnnnIN58+ahpqYGVVVVGf8sJjfSQD+2nXka/P98FFP++nc0XHnNRA/pSw1ps+t5wskiOAOjoXoyOZ4NOIaCSLHmMjQjNsBtZ9D0u5szBOps6PoG8NEgaEUumtHYORQFS5Oo8+Q6hQyHVTmOs0pId1cBusgYX/4JxJ4u0Mll1vLgADwO1rwxziaaVk6WWL0SIEnwRRqjE+vWou93VyG2/NOKxsrX10EDQAZyS3GySc9pTKxdjcE7b4PU1Qluzjwk1qwyy8OA1LJs/6iEWxl8VgSA2LEVAFJiPkkh+PQTiH70QcZ+hgPUKM8aK2KCjOb4IPpvuQHxVV8AAJiWFjCz9DKYznFc/r62KwieodBep4uCLhuDPWfUYE1XEKI8vqVohYgkhVtnUiiXhwbzThhkE/1wGbp/cTGknu6S++4xQxdoP944hGhCxudbR7DLtCpTPJQHBvTszxKCm52jIfEOKKoGNRrJeMzIOy3HcRv/fLl+vD2Xwr5kV/ia9C+eIxEBG3r1ZeEzG/M7312HHgEAaOUVdA7FoGmVZz+PFn9UyCkmAwCaIuFzcmVd/4z4knThUY3H0Hn+WQg899TYDXYc0CQJ3T8/H4En/gGfk83IuFVUDX3+OJqqRh+TAOgCKsmnXkO8kfmbLBuLCTJYmgRNkei68Gfou+7qjOfTVVWw77m3KfgaUE4nqr57atEVQQ5NhCceKFpOFjDjMopPUNo5Om9Ugs/BwrZ4CWy77Fb0+QbctOngZ+bPwlXj8YJZ7IUgaLqoaAsAlNerHz8rbkJTFP17k6JUdM6JxPO1Y+A5+piy9pX6+/IWsllsHwTPAzQDNRwEP3uOJY5bWFhYlEATEtj2o+9h+KH7cx4TtmwGUNyEZDF2VOy4PfXUU7Fx40acccYZqK+vnzT5pxblQfI85MEByENDAFDyS7XF9kEwDAibHWokMzfOKDPJntmaDPAsiRGa1ctakBJus5f05oOubwBFkvAIQQwVaUXvHIqipdqRd3mokfE4HBZQPCSgMrKdqUamH+X2mtl88kA/vHYW/cH82bKRuASSIMAzJAZWrwI7dXpRtxOdnAwzhPyM8Sz/FMP33YPq08+EfdfdMx6z2zhEOBecwdLCbdR0jdEQ12xG+NX/wbH/QbAtWIzE58uRWL8OtvkLAaQa7LPzJMshISoZxW4AIHVuA5By3FIuFyivD9K2joz9xqucLC4qmC74Ef3sTXNpuHOf/TFj7/0g3/oWlq0fxM+Onj3mn3OqqmFddxAzm9wZr2EjTzcYFcctW7cYpuOWZ6AmElDDobKEW02SIKxbjfjqlSUzcXeboWc6f7xxGDaWgqxq2Hu2PvGhqSrkoUHYl+xS1ngppwuKqkGJhDOys41l89XO0tec+IrPAAC2RUugxmOoiurvGX9ExMbeEHiGKlhw5dhnf4Rf/R/ayDheTkgIxqScsrDxIhAR0V6X32lZ6+HLKidLJIVbPs0JL/X1QdrWUbCEYmeB5HkQHA8lGERVO2dGjwC621hWNTT6ts9NF132Hiifz4yL4T36JEtwJIhAVERMVMzPA3lwICfflfL60PCr34zq3PzDf8J5y95H3zd2L7hPIE2ALYaTpzMEYDMqwcGi9qfnlz0mTRIh+/2gPF6QWZFHPVdeBjUSRts9D5R9PABIrF2NnssvBts+DS2335XzOGGzAzRjFpgZqHH9M3aylOdWSu9VvwTBc2i9488TPZQvFQRBgHK7oYRCaLjyJxM9HAsLC4udHoK3ASRpFramI27dDKqqpmB/jcXYUrFw+/bbb+Odd97B4sWLx2M8FhMM6XACJAlxyyaEXvoPbAsXl7wRt9g+KJcrp/BD8Y/oj02iqAoDnqGwrHUvTNlbLycLxZM3iRAwdN+fYVu8Cxy775X3uUx9AyiSgC/uLyg8CJKC/kAcB8zPvyTDcNyOdUFZujMVQFoTthvczNnwHHsc6JoaeBx+rO8JQtO0HMEvKsiwczTk7i6ooSD4Aw8uek7KZwi3IzmPyf19kDo7gDyiIsdQCPBu+IK5z8v5uZKCtJ2n0yYMvLDtsisSa1dnTN54SmT4Fj2PqKDGnXmzX/X9H8B1yGEZBWtMaxuE9esyfn/G0v1ImcKt4XwsJbjGBBluRRcA0r90EASBfefW4ZkPtmFLf6Rg8c9o6RyOIirImNuS+UUnPUN4IoTbSEIGQ5HgGBJyry5gUtU1JZ/Hz9UdysLa1UCJTO4qJ4eZjW58vHEIhma91yz9HErAD8iS6WAvBe3xQFU1qFnXT+O9X+0u7kTUNA2xFZ+BaWoGU1eP3t/+GvZPPgGx8DwMhxPY2BvG9AZXwaxs4/1Zr+lfZruGoztEuFVUvSCw0LlqXBw29oagqFrB7FMgvTAwNaEiJzNMs12iOyOU2w0lHEKVk0VMlJEQFfAshV6//p7enmIyABi47UbwCxej8de/BQBU1XixjQB6eobxnZteB0kSqPfq51ATCZB8eecbefQhxD5chsZrri/4Gc+63SA1FfFI4exkYwItu6AuGztHZ2QAB9LKySoh9L8XMfyXu9D4u5thW7Ao4zE1FDTzQytB2LAegH7zlw9daPOYn03m+ZI3kEbb9WTA/9jDCL/xGlpuu7PouGW/H3J/L5wHH74DR/fVwb7r7iC4Hf/5amFhYTEZIQhCXyGcNaGvSRLEzm2wLV4yMQP7ClKxnXLOnDmIx0s3lVtMTgiKAul0QdiwDkN3/xGJdWsmekhfekiXO2cZoBIOgXS5J2VpAktT+KJhIYKL9YxSMypBiSP0/DMQ1qwu/Nz2aXDutRQCxRUUbruHY9CQW0wmdmxF/++vR1XnWgBIFkuNHWZUAmtEJSSFW48H3LTpqP7RT8BOmQqPnYWsahllMAbRhJ6pKnV3ARQN27wFRc9JeX0AQeQVbk1xP0+cBkuTCPEeMLEwVKG4gB1Ny2lM/Uw+8DNno/Gq34JPC6T3badwm51xSzAs2ClTM/JJ2bZ2aEIC8uCAuc1w3IbKFG7/+2k3vnXD6yUdunFRgUtONksbDfCJBIbu+zMODOuvo3fW9Jd1zkpILyZLx5cUYAKjcDSPBeG4nptKEATkIT0fuRzHLV1VDbquHoki7+10dp9RjVBcwusr+zC9wZUSv8Jh0PUNoMsUDXmPG6oGxEcyHemGcFsoI9tA6umGMjQI22I9O5OpqwepqXCIUaztDiGSkDCjQEwCAPT++hcA9GImAOjcQQVlwZgIDShYEFjr0XO+SznjY8ZkVJpwK/VOHuGWdHughoKoSk7WGeJkz4j+dyjklC4HTRKhiWKGwOZ28ph1/fWY9ePTccD8BthYGnOaPfqSdkXOW/I1/OB9GLz7jxnbxG1bIW7bqk+UF4BNXo/EQLDgPv4yHbd2jjbz1QH9+k0AcEFC343XIvTKS0Wfb2CsLFFCuWNSwuGSZZr54OflLzzJOK/Xm3NO4wZyMjlulWgEcl9PSTe7sQqAn1/8+4HF6Kg99yJU/+gn6L/pdwj994WJHo6FhYXFTg/pcECNZX7HFbs7AVkqmNdvMfZUrArddddduPzyy3HVVVdhwYIFYLJan93uyr+4WexcUGlC4mR0fE42KJcrJxuy8dobocV3bEv5WGFkVQqy7uYyxDMnoeffFXM68LPnoPnKaxC44bWCGY1G7mhblnALgkD03bdgc3oAzBhzx21MUMAzlOlgU8KG4za/azIUE03B0SAqyHDwNBxL90H7o0+CKOKGA/SJFMrtgTySx3Gb3EZXVec+jyDw9twj0Nd6MvZgi9/Uxw3hlqMRMBy3Ba7jLhsDkiDgj1Qu3CZEGRyTmitUEwnEV64AN30W6DTxmW3RndrStg4z6N74PZbruF3bFUQkIaFzKIp5rd68+0iKCklR4ZAMx62+H0FRCD3/DOr22R9u2954Z80ATjt4RkU/aymMYrI5BRy32UVLO4pwQoIz6W5WEwmQbk9Zwi0A8HPmIfLW61DCoZICzh4zavCPt7dAUTXsPTt1fHZKe0VLrdmmJmysno52jUX69MVwWABFEiXjWZiGRjTd9AdTQKNr60ESQLUQxIot+vurUDEZoLsNbLvugeb5s4BXB9A1jpnI6ZRaIl+bjIsZDAlmdEw+Enkct1LScUvX7/zCLeX2QOrcZpZQ+iMimqrspnDbuB0Zt4WEwYb990MDgMMAc1WAsWKGyOO4TaxepbuY0yIJ5MFB0NU1RSdmOW8yfieUW2xmECzinI0t/xSR115GzTkXwpHMuDXGG4gmP5tiUcSWvQemriHn+fkgk+9rNWtMmiRCS8QLfm4Ug23Xc/H4ZBxPPhx7LoUSycyxnoyOWyMWKfvmN5vYx3rGu323Pcd9TF9V1Hgc0fffmVTCv4WFhcVEQdodOZOOBEXDedCh4LNW4FiMHxULt16vF6FQCIccckjGdvML7CQqCrDID+V2Q0rqiJTHyiwZb6pPPxOanOnOJAgCxCS6IUmHo0kcuuk1tNz4Zyh//7t5c+kgFchARtlLIWrdhTMatyXFkdbaTLfS4J9uBwCoa1eC9s3E0FgLt6Iec2DAz50P3/d/CLpRjxLpu+5qgCLh2f80AHrre3OWphpNyKhJusOyMwILwUxpB5lHfFX8IwBFmzfT2cjuKgQoW+m4AFEBRRJgaRJKKKg7vZMO2PiqLzB8/72oPv1M2BYsAkkS8DrYih23kqJCVrWM35+4ZRP6f/cbVJ12BrzHnWBu5+fNh+eYb4OqSS3RpykSNpZCOI+LOR+G866YeG8I1g5Jfz0ZogPBMLoLPhjA3rvX4aXPutEzEtsu9142a7uCqHJyqMuKQzAEqNE4mseCSFw2l5c79lwKx0OPl124xc+dj8hbryOxZjUcey4tuu+8Ni/sLI2YKGPprPKE4Xxw8xbgL1tp7NY4DVPStg+FEvA5uIIRBwYERZn5pQBA19aBANBCxNGh6BNNhRy3uiNT0IumWBUUSYxrmV06qVKqAlEJbqOgMQGg8Gd4Kv4l9b6U+/pAsNykKMakq6pA2u2oTl5K31nTj3mtHjMqocG7HcJtUlzLFgZVUYQmCKBcLvPaahRx5vtsozweCBvWQVNVM3ZG7u8DO6W96PnZZCmXHCks3PqLCLdDf7od8uAA+Lnz4eDboQFISPqqh0BMhNfJQjNyYu3lXduMCRklS7g1hOtCn0XFICgKUx7+F4gsE0g6vpO/n7ONmzYdTTfeVnasys6AIRIarxf/Yw9D7NiKusuuMF9Lmiwj/unH4GbOzpjQtBg7Im+/ieDzTwOYXMK/hYWFxURBOhyQRzJ7U9jWNtRdeOkEjeirScXC7fe+9z0wDINHH33UKif7klL1wzMx/Je7IGxcbzludwDslKkZ/69JEqLvvwN2ytSSN3c7IxxDgVZkkJEQtHjcXN5uJxSEkGz1LcLwg/fh8M/X4f6mwzEYTORkfRriSGtN5s2mUXQldWxBS72M4TJa1SshlpAznGn8zNkZDduKfwTyyDC8R+k3oNnim6ZpiCYkOFkSgWefBDdtBmwLS2eFN117Y97t8sgwKJ+v4DXYDhnuns2Q+tqKLnuOCTJsLA2CIODc70Aoi5akHlQUiJs2QNyy2cw0HI1wmy9LU+zYCiBVTGbATpmK6jPOyjmGy8aUXU4WjOr7FRNujbK50Jzd4N1/cYb7jfL5oPhHsN9cXbh9Z80ATty3vaxzl0KQFGzuD2PPmTU5fztfWsbtRBCOS5jVlCm+lPsZb999T9R5rsiI1igEQ5E4cEE9VnUGMDstLiLy7tuQBwfg+fqxRYUcA7OIMG2SR9M09IzEMa2+8DJ0QBdIYp99DNvCJabgRicd3g2q7u6jSKJgAZgS0a9DkbdeR3TZu2jY++foGt4xqyQCsfIct0MlCsryvS99J38P8tDQpPhuV3vexQCAqriE9mXd+Oe7WzEYTKBjIIIaFw+OoUocoTCGo5PKcuT1XH4x1GgkwxlOebxo/N3NZuZxOpTHA6gK1GgUlMsFNR6DGgmXFBwppwskCWjhSMF9/BHdOUtTualnLXfcja2nHI/g80/D/rVLAOgZ1jaWRiAiYmq9yxQQiTwRD3nHZEQlhLOinYwVWqNccUc5i79X80Ha7ODnzBvV+SYKQyRUYzHIfj/8jz0MABDWrAKfjE2SB/pBOhyw75G/B8Bi+xE7OyCs16OQLMethYWFRWkarrgaBLNjynctClOxcLty5Up89tlnmD17dumdLSYl/Ow5oBubksKt5bgdb9REAkrAD8pXBZLjIPtHMHDbTXAf8y3UnHH2RA+vYjiGhECz0DT9ZwvFJJAEAU7RxTSihNNU2LAOs/vXQqo/FD+7ZxmuPWWXjBKnbYNR1Lr5jLxUNR7LaLucG+vCB/TYOSSBZB6qrbCYRNfWQdi0Ad5keVkwlim+ibLuOnUTMkb+9he4Dj+6LOG2ENU/+ol5452PGimEo1/9M8IzJFSdclrB/WKCbDaju4/6esZjTEubPvbuTnOb18FiXXfh3MV8GO7W9PZ645hMa1tZx3Dy5Qu3/mhpx62R75lYtCeqsqIQKK8Pwsb12G16NXiGwjtr+sdMuF3bFYSiajkxCUBaOdkEZNwKkgJJUeHk9b9R+PVXoSky3CXKxgzo2jo4K3C/XfLN+VA1ZLhiw6/9D/EVy+E59ttlHaOa1XDsmuchvdkHLP4BAD1TO5KQ0Fxd/P2fWLsa/dddDd8pp8F34in6z5AUbn2a7kScUusES+evAlCjKUFNE0VMdwHvd8dKFoKNBYbjtlAUhOG4HQwWF26NqIT09+VkE8MAfVLnzjP3wo1PfoHXV/YBABZN2T63oqZpYJpbQVVllvORNpuZ/2xu47icsi4DI0pHCQVBuVyQB/TsbuO1Vgj7XnvjvmN+Db6IsBSIijnivRqPgeBtIO0OeI47AcGnnkBD12oALsQEGe+uGUAoLqHRZ4NqOm7LE6/MqISsMkC2dQpa732wrNU0oyH64TKE/vMcqs84G2zy80KJRPR4Bq9v0nQBmMJtNArK60X1j87C8P33IPTiv03hlmlqRuu9DwJyeatLLConPd7KctxaWFhYlCb7WqlpGnouvwS2xUuK3mNajC0Vl5Ptvvvu6OzsLL2jxaRFUxSQHAdu9jxrdmUHEH79ZXSefbpZSKEEAgAAOo97ZzLAMRREioWqaXji1TVYtn4Q9V4eTF0tXIceAba5pejzmfoGuCDiqmNmIJKQcPH9H+Klz7qxsTeEFVtG0DkUzSkmk4f15RvOAw4GAEz1b4U/IkBOLnceC2JCZlRC7zVXovsXF5v/T9fVA5oGj6AvI812pRplZR7o28kyXUaJdWsx8uhDkIeHMrbb5i+EY/fCrhzVWwVNQ0bJVz5iggwbl9+ZRvl8IB1O080M6AVaUUGGIJUfi5NI7sunZdxK3d0gGCZvhurAbTeh58rLMrZV4rg1MnhHikYlGG7D3Jt+2uuDFouBUSTsObMGq7cFMlrZtwdDWNpnTqbImVizCkTnZuw2tBrhYGGX3XhhOOONyYngM/9C4InHKjqGpqoQO7bqZU0lIAgiR+CUBwdA19aaS8pLUe21Y0nv5yDWrzK3Ga7XluriN+SxD5cBAOxp7yHK60X7Y8+g77ATARTPt1UjyeXhyS+z7YwASVHRFxj/8lbj2lI4KiHpuC0RF5MqXNTf/5okFZ0M2tmQensQ/PdzkHq6YedoXH3yEpx6kF6SMaWAU7pc+Jmz0fqnv8B18KEZ20mbPSd/XhVFKKFgTuQRkFZ6mMwPp+vq0PCb68zPqkKQLAvO4UBULHydDUTFjJgETdPQ97vfoP/6a6ApCjxf/yZA0Wj89DUAQMdABL9/ZiVcNgY/PGRGKg4iTzZv3jHxPKb8/QnUnn9JxnaCosDU1efkvY8VSsCP+PJPMz7LQv99Adt+fCrEji3jcs7xgJ8zF/WX/xr8vPkgCAKeY78Nfv5CRN9/J6N8jSCIslYcWIyOdGd4uW5zCwsLi68yYk8Xosveg5rQDQGKfwTCutWmZmGxY6hYuD3vvPNwwQUX4IEHHsAnn3yCzz//POOfxeQn+O9nEX7lJVT/8IyJHspXAnuy0Tz2kV5IoQT0hvTJGlNhCLfRhIzXPt6CafUu/OakJeBnzkbteReDmzGr6PPper0oZWmVij+csSecPIObn16Js+5+Hxf/7SMkJAVTs5ZBGw4obu48VJ91DoJ7HQYNGFWJViHiogJ7msAp9fVATaRu4I2lr86oXmqULdxGE8mSNkO4LXOJnrBpAwL/fBRSd5e5TVMUqLFo0fxR0u5AnObKEG4VODgast+PznPOROC5p8zHCIIA09IGMU24NVx+lcQlGEuy04VvqbsLdGOTmaebjhIMQNi0MWOby6Y3o6tq8czVhKiYQnEx4SomyiA0FdPvugLDD96X8Zh99z3h+ebxgKpgv7l10AC8u6b477EcFFXDW6v6MaXWialpwpLU14veq69A9yXn4ZurnoHc37/d56oUo/jNmRRu5aFB0LWV5c8Gnvonui44G8KmDRWfX9M0yAMDFWVWVvuckCgmI3Oze0R33pdy3MY+/gBUVQ3YqdPMbQRBgOR5VCWzhgvl2wIAO20GWu68F97vnKyfj9QF2x1RUFaqnIxjKLhsTMGCR4PU+zJZKLlhHbZ+9zgE//P8GI52/BA7tmL4L3chsS657Jkk8MNDZuDen+2NMw6bOS7nJGw2aJKUMTkRX/4pOk47CZG338zZ3zZ/IapOPR1UcoKKtNlh32U3s4SxEJokYdrwJjj7t+V9XFE1hGIifGnifeTN15FY9QWo6moQFAW6ugbOAw8GZbODViTc/vwahOMSLvv2AtR6eLAtrfCe9D2w7VPzniMflMuVM7EiDfQjsX6deUM31hjfhZRgStycjOVkdHUNHEv3hdixFfEvVkDTNLiOOBqaJCH82iuQeroxcNtNSKxfN9FD/VJDJicYSLcH3PTxuU5YWFhYfJmIvPYK+m+81rzfFrdsBgCwU8v//mCx/VS8vuikk04CAPzoRz8ytxEEYZWTfYmgXMbSvsKlGBZjB9PUDKZ1CmIfvg/t7HNTwq13chZT2FgKKsuBIIATd2vAYactrWjpsCHcSn19mLPvTNx19lL85+MukCQBl42Bi6exZ1ahkZIMTKera+HYcynsb28BNq7HUFjIycgdDaKsQlLUDOFRDYXATp2eGndy6ast4gdAmqVsBtGk49al6mIK5SjPEWYUlMj+kdR4tm5B9yXnourU0+E9/qS8z+NZCkHOXVK4jYsybBwNJeiH1N1pFtYYsK2t+qxqMADK4zWFgkBURH2Z5T+pJdlJZ5+qgnK5CsYkUB4vtHgMqiCYJW4uGwNV0xAV5KKRFYGoiPn9q3DYptfwiuucwj+3IIOXE2BHBqBmNZY7DzjYdMTtNZsFTRJ4b+0AjtmjuNhSik83DyMYE/HtpW2pMhpVxeD//QGakIB96b4gX3oVcvIasCMJx5OvTxsDNZGAGo2Arq4p8axM+FlzAACJNasrXnKvJpc+MxUItzRFQuQd0NJiC7qTjttiwq3Y0wWppxuuI7+Wk+UqbNqAOVs/AaF5sbDIcnuSZcG2tplO+Go5AoArKZaOBYGoCIok4OQLvw+KFTwaJMRM17nxupssuY+FMlenN4wuazWd+KovkFj5OVyHHwW6KtUySdr015WaiINKuiLNcjJb7mcNN31mhjikBAMgOL5krIAmSzjo9fvxUc0CAN/LeTwYE6EB8DpS0UPB554C6XCi6ns/NLfVnnMhVq0egPzE5/q1Z6820+3PTmlHVYU5+okN66AE/HDskSogjLzxKvyPPoTm2/4Ebtr0Is8eHUZkl5J0LQNpwu0kea0aaLKMobv/CDUWQ9t9D8O5z35QY1E49z8Y4df+h8hbr8Ox34ETPcwvNUbJnucb3wKXNnFnYWFhYZGf9KgfAEgkc8K5adbk146kYuF2y5bJsyzJYnSQTv3NGXz+aTj22nuCR/PVwLHX3gj86zEIyZsiYPIKtzRF4qwLvwOXf3/UzJttirbhV/+HyNtvouZn54Mpku/HJIVbuV9fUl7r5vGDQ2YU3B8A7LvtgYarrzdvGmtoGZ5EEMPh4q3q5WJktBrCrSbLUKORjAxoftZs1F12BfhZc8B/uAKBWOZy8UjyGI6kcFtuVIJReKOMpIRb2a8L1WQRVzbPUIhRPJRoYQegqmq6k5ilzOUu2ctdXUd8DfY99wbB6UKDsTS3Esdt9pJsgiTRfMsfC+6fclgFQCZfK4ZYG0lIRYVbf0TAQVvegicRwowvXgdwdN79ooICuxgDQaBolreTZzCryYO1XUFzgnK0vP6F/po+ZGGDuS380n90gejIr8G2eBdQ/3sNCAWgqlpG/ut4EzEc4Txtzqjni7EoBjdzNkBSSKxdDUDPuBbWrQHl9ZUsWpQHdJdxqezPbDSbA0QsJdwaUQnNVYWF29jHHwLQndXZhF76L2r+9x88cueDqG8qLADKIyNQwyFQXi8AY8KmGqHY+BfLBaIiPHa26Ouj1s3h080jRV+z8awJlckW02Nc/9RgZZnb5RD/fDkCjz8Cx9J9gXTh1p4UbuNxUwDSkk5TokTkgDwygv6bfgdhw1pMffzZosvhCd4GgiLBiTGIspqTtWzkHKdHJch9vWCnzQDlSkV8EBQFB88AmoZZtTaceUTxFS+l8D/8ABIb1mHqo6mVGUpYn+QfbTlZKVI5wQFzm3HzOJkct/LIMLb9SBfhPcedaIr3nqOPAaCvuiJYFrb0glCLMYeuq4PnuBPBz518ed4WFhYWE4ExSWpMmgprV4NguXGZrLUoTMVRCVOmTCn6z+JLQPImL7HSir7YUdiTAnn0g/dB2uxgmlvyNlRPFmbMaUf93ntlxD2IXZ2IL/8EKOHKZ1raUHXaGbAtXlL2+SiPF/Ylu4Jye6CEw2i+/jwcsul1bO4Ll35yGRhFVnZD4AgZN6opwY/y+uDcZ3/QNbXwOtgcx20s6bhl3S7wi5aUvSScSooGhqtY/29dxE13gmXDMxQirAMocmObHmFguJkMIco8zqzZcOy51LzJNBy3lcRQpDJuy2t5N8agpuX+GWKt4QwthD8qosfVCACY0fU5BDH//nFBhkOK6VmrWWK1sGUzun9xEcJv6tmQ0xqcCMWlomVnpRBlFe+s7sfMRjeak/mrmqZh5B9/B1Vdg+ofnAHK4wVJErAJUTNzdkcRTsu4NYRbqqYyxy1ps4GdOg2xjz9E+PVXoISC6P3NLxF6+cWSzyUYBs4DDi4ZpZKDwwk6ETMjNLqHY6jz8OCKvNZImx3s1OmwLVyS8xhdWwcCgFcoLgaGX3kRXRecDU2S0HrXffCc+H0AQDA2/n83XbgtnoFZ4+YhKSpCRcYTF2UwFAmG0r8KTraYnpSgN/arg1JL8TMnALzHn4S2v/0jw41ulnzlcdEqwQA2H/d1bP7WUdj241MhrFsNbuackhmmBEFAsTlhk+LmxFc6Rua2IdwaBZ354k3mcXFcs+Fh/KJpOON94f/XY+g876yc/PRikC43tFgsIypCTf7+jfKysSaVE5welRADwXKTppgMSLm1AcDzjW9mPCZ2bEHiixWwLVoybiVvFjqUyw3K6cLQX+/OKRq0sLCwsMjFdNzGYtAUBYm1a8DNmm3lse9gKhZuAeDvf/879t13XzQ1NaGjowMAcPvtt+PZZ58d08FZTAx88sa56jQr43ZHwU2fCaalTS+3OuZbaP3TX0FXTV7hVlNVKJFIRtFNua4kyumE97gTKsoekwcHzBttyuWCo30KZoS24c1kEVQ697+yAZf87SNzmXA5mI7RpONWTS7NzXZqaooCJRiAx8HmZtwmj8Eu3AVN195Y9lJyw3mdHpWgJP+7mLjPsxSeXHAcXLf8ueTPZedo86Y4n2ijybIp7BpLc4MVOAvNJdnJ31/0w2UYefShjEKWdAwnXXrovbEsvFRBWSAqotvdDJoiQGoaRrbkz4iMiTLsYgwkkRIGDAiSgLBujZkrPK1Bd7Bt7h99adiHGwYRFWQcnOa2VSMRqKEg7LvsBtLuAOXz6UvgxQj8Y1SGVi5GeZ6TZ0DyPOx7LAXb1l7xcWyLlgCKjNinH4OuqQXBMBn5zIVg26ag7uJfwL7bHhWdL7hwKZa17KEvHdc0dA/HirptAcB9+FFo+cOf8gokdJ0+oSINFM8ZNhx/lMcLpqkZHq/+pXZHCO6BqAifkyu6T6qgrHBcQlxUTLctACj+pHA7ST57SIcDIKmC15HtQTOKu7KW4lMuF2ifLyObW0skhds8RUek3W7e2NgWLUH9L65E03U3lzcGuxM2OW5+dqRjTAwaE2mK3w9QdF6XPCOLaEoMwaNmXlPkoUFInR0V3XgZLmMlLV5GCYf1+Aeu+GtytJB2B6pO+xEc+x9kblOj0RxRfWeH4HnQtXVw7L1fzqRr96UXAgBsi3aZgJF99ZAG+iB1bJ1Uwr+FhYXFRJHtuG28+jr4vnvqRA7pK0nFn1h33303rrrqKlx44YW47rrrzExbr9eL22+/Hd/85jdLHMFiZ4fy+jDtmdIOKYuxgyBJtNx5z3Ytw96ZkDq3oeuCs+E7+fvwnaw70VRBFxBIvrybu0qWpfddfw3USBhtf3kIAGBfvAtq1mxAZGsHtg4sQXuyCCocl/DEe1shyipufXYVfvWdhWWdIybo1zlHUnik6xrQ+NubcjJAuy+7EGokDO9+52FzXzjjZzCEMQdX2WWXZFk4DzgY7IyUkC31dOvjqC7uuAUAQSosUJtOYo6CMhzQz5fluNU0DR0/OBns9BlouvZGsxCpEsdt3MzS1McU++A9hF/9HzzHfCvv/rZFS1B/+a/Bpon3bnt5wq0/IuLD1j3gPuQwvL5uGLfbq9CYb0yCUtBxa7ihjXzgafW6cLulP4w9Z1bmQjUwYhIOWpASbgmaRs25F4Fp0EdIe31Q6hoRp/iKoijGgpTjlgbfPg8NV1w9quP4TvoeHPvsB27GLBAEAbqxyXy9jgfyXgfhzVgLTgkL0KC/pg1H82gwYlzkgeLZ0GpEd/OTDof+8w30gyaJiiY0RoMoq4gKcknHrZHtPRgUML0h/z56TErqeqQE/ABJgSwzf3uiIUgS9l13L1n0NRqUaAQgiJyJRiUcgritA2xLqznJpRaZlCQYFs2/vwMEx5kxQGVjd4IfGDHz0dPxZwm3TFMzpj7xHDQ5d18jlsd4zRqY4nQewbkQZDIOQQ0FgWT+uhoKgkyLZxhrCIKA97gTM7Y1Xf97qIl4gWfsnBAEgdZ7Hsj7WOPV12Hk0YfgPOiQHTuoryjhF/8NYPJlJFtYWFhMBJTbDbquHgRNg6Ao8HPnT/SQvpJU7Li988478Ze//AVXXHEFqDTHwe67744vvvhiTAdnYfFVwhD4/P98tKylxTszRPJGUE0rujIdt2xp4Xbw7j9i63ePy3sTmg95eAhUmohqW7AQdo5Ca7ALb61KuW5fXdELUVZR5+Hx2he9eHpZfjdmNvEsxy1ps8G2cDGYpuaM/SiXC0ogAK+Tg6SopmAJANFkhij/0RsYvPuPFTVw1138C3iPPQ6ALqQm1q8FO2VqjuCYDs9SmOLvQOw/z0IV84tJhiBt52g4DzgYtRddBroqU5gkCAJ0QyOkTv135TWF2/IdodkZt1JPN0iny3RvZcPU1cOxdF+zmA3Qs1eB8hy3ANA+pQ4KSReMN4gJMjZWT4f7ostzMppIuwOkyw25rxcAMLVeFz42jTJ6Iy7KeH/dIBa0+TIK3UibDe7DjoRtwSLzvNHLb8F7U/YxhZkdRSQtKmF7IHke/MzZ5vWMbW6FPNgPTSr+8ww/dB/6b7kBmqZVdL4at349GQ4L6BoqXUw2dM//oe/G32Ys9U7HFO1LOG4NYY+02TH8t7+g77dXwWOjER7nqATDaZmebZqPapf+exkp8j6Ni3KG47buokvR+n/3giBHtRhrQmi48hpUnXr6mB9Xd3Q6cn4X8eWfofeKSxFfmfq+6/vuqXp8QoFMaLZtSuWiLQCtrgFR1mF+/qRjTJz50l4HBEmCZHNfF0bmrZIl3KrxOEAzIJjir6WMYxnxFOG0eAqKKhrbMx4QFFV2wefOBEGSed9f/LwFaPrdzUU/0y3Gnkpe+xYWFhZfVbgZs9B274NwHXwYxI4tGff3FjuOir+db9myBbvskruUh+M4RIuU4FhYWJTG/9jD8D/6ECJvvzHRQ9kuDAdPuiNGFRIgWDZjiWkhKK8PWiIOYeP6kvtqkgg1FMy4aaZr68AxFGog4M1VugCjaRpe+LgTDo7Gn85aipZqO/780jp80eEveQ5jqaqZcRuJQAmHoKlq5rjdHmhCAj5GF5/SXZOGa4patxLhl/4z6iV6BEGg9Y/3oP5Xvym6H8dQmDu4FvJjD5jLurNJCao02CntcB14SN7l42zbFCj+ESiRCHiWAs9QOeVrxRCyMm7F7i4wzcVdcpqiZHwxMMvJyhBuj17/IuZ++Dx4KQ7i0b8g+J/nc/aLiwqCvAe+/Q7IGw/B1DdAShbkOXkGDV7bqIXbV1b0QpCUjJgEQP8Zs/EmHXSBChzNY0F6xu3I3/+GwT/fOSbHZZpbAFWF1NtbdL/4iuVIrF1d8aqDhg2f4Kcf3IPgmnXoHtGF25YCwq2mKIi88xbk/r6Cy8MpXxXY6TNzsp6zUSMpYY+uqQEUGXWkOO5OaePv5C7huC1noiMhKuZkCqBPHGRPRn1Vsc1fCMc+++VsN8vJYqlrKslxOfEJY0Hs5LNwz55n5o1KCJgCvi7QJ9asQuTtN/JOCBK8DSApqOFs4TZWkdsW0Fd5ME3NQNpnX/NNf0DzzbdXdJxKGbjjFnScoa/eibz9JsJvvFZw8sXCohS2JbtOmpUFFhYWFjsLmqah9+or0HPFpRM9lK8kFQu3U6dOxfLly3O2v/jii5g7d+5YjMnC4iuLsHWL/h8lCrx2dgzxT0sT3txHfK3s3GSjVTn++fKS+8pGUVea45Z0uUFQNGbV8dg6EMHWgQjWdgWxZSCCwxY3ocrJ4eqTl4ChSFz7+Aq8taoPilrY6WeWeCXFkOBzT6Hj1BNNF6p53qRbporQb6rTC8qMqAQqEQXB8RUJt6EX/42eqy5PLcllmJIOLp6hIJM0NGjQxMKuUwBwcBTURKKg25FtbQMASF0p122gAsdtPC3jVknmuhYTiFRBwJbjv46hNPEwVU5WKipBwNzhjXB0rIVIsWC/+AjB55/OEdljggxeEcGS+X9muqERysgwVEH/OafWO9E5FIUoq3n3L8RLn3Xjzn+vgdfO4uAFmX+z4fvvxdbvfQeyPzV54P7sHRyy6fUd77hN6EVVHEMh+tEyxFd8NibHZdumgGmbUnJ2Xh7oB1NmYV86bhqojQ4hOjCA7mFdTCvkuE2s/BxqOAT7HnsVPB5BUWi59U74Tjyl6Hk1WQLp1J2Mhtu/QRv/Urlwmc5oR/Jala/YyiAmpIRbTdMQX/FZyWzfnY3way9j4Lab8k6CbA++k7+P2nMuzNluCJ3pn23Cpo1IrFk1pucH9JUQQP6/YSAqgqFI2Dn97xd+5SUM3Hpj3lUqBEGAcrlyohLUeLzinFjH0n3Retd95mf0DkNRoAwPQRUEjDz6IIbvv2fHnt/iS0Xj1dej/ZF/TfQwLCwsLCYFmqIg8NQTCD79Lyj+EfCzLc1vIihbuL322msRi8Vw8cUX45xzzsHjjz8OTdPw4Ycf4rrrrsMvf/lLXHbZZeM5VguLLz3GkulCDsnJAsGwAEVniDWOvfbOaVIuBD9rDgiOR/zzFSX3NVqBqbS8V7q2DlP/9Tzaz9CF4rdW9eGFj/WCpK/vrguGU+tduPz4hYgkJFzz+Aqccee7+O+n3XkFXLPEK5kHaZThZJeTGcscvaousAbS8i6jggyKJEDEYxU7PaT+PiQ+Xw5lZBj+fz6KxNrVJZ9jYynIJAVNA7SCUQmpCIiuC85Gz6UX5N2PadGFWzEpVPucbEXCYnrGrVFUxTQXFm5JjgPB26CktYinhNvi8Rn+qAibJoJzOqGSFDpn7Qm5tweJVZlRPnFRwUmrn0LHaSfmPY7na8eg/vKrQJC6A3R6gwuKqmHbYPkFZY+/swU3P70SNS4ed/x4T3iylrfLA/1Q43FQ7lRkBP3Fx9hn2/vwh3fsMqRwXDJ/x/LQIOjq/Mu+K8V5wMFo/eM94GfPKbiPmkhADYfMmIJK8NTpcRrRkSC6h2MgCQKNvvxiVODZpwCShOvgwyo+TzbNN96G1rvvAwDQNfq4a+UIInGp6CTQ9mIIw+5Swq1RBJgnHxVICrVpUQlqNIre3/wSgccfGcPRjj+J9WsReet1qOlL98cRwpZ03KatJhl56D70/faqMT+Xs78DB255C4k8Yro/KsLnZE2Hujw0qBeEFcjsrDn3QlSd9qOMbdWnn4man5yzXWNUY1EEX3gWiQ3rtus4pTAmRWMfvAe5tweugw612qwtLCwsLCx2BCSJkYcfwMhD+vdefp6VcTsRlC3cXnPNNYhEIvjxj3+Mm266CVdeeSVisRhOOeUU3H333bjjjjtw8sknj+dYLSy+9LgOPwquw49C7XkXTfRQthuS50edgUMwDPi58yGsW206HguhBAIAkCE0EQQBgiCweGoVPHYWL6/oxRsr+zCn2YPpDSmRbP959Xjk4gNwygHTMBIRcMszK/HvpMCbTkrgTIocSUGRzMpoNYRctyHcRlPuu2hChp2joUbCIJ2VFWLQPr3lPb56JfyPPoTwa6+UfA7PUpBJBqpW2HEbTytdUwIB00GYjVH+I/X2AEg6bqNi2XmkRkYjR1MgHQ64j/5GyWB7yuPVy5KSODgaBEo7boMRATZVBOtygGcobK7VC85Ew82eJCbIsGsSSC43GgLQMwcdS/cxM/CmN+i/m8395cUlPP7OFtz7v/Vor3PijjP3REtN7t9cGugDXVuXscSar64CqWmIjARz9h9PwgkJThsNNRaFFouBrh0b4bYcjDxZOlkMVgnOah8IAkgEgugajqHOw4Olc7/aiB1bEf/0Izj22gdMY1PRY0Y/XIaBP96q59gWwciqpGt0x61XjkBD6TiP7aGY41bTNDNL2Mkno0UKCLeSokFRNdPVqQQDAPSYmsmEmbkazP9+Cf33BXT/4mKzaLAcNE1D3/XXIPDMkzmPmVEJaZ9taiKRt5hse+F7tuLALW9DyVPuF4iIGTnH8tAg6JraglEjjj2W5lxzbQsWwb7bHhWNSU0k4H/iMUQ/eF8/7+Aghv96N2IffVDRcSrF+DsHnvwnAMB16BHjej4LCwsLCwsLHYIgMlboWOVkE0PZwm36Dfr3vvc9bNiwAZFIBH19fejq6sIZZ5S3BNrCwqIwJMeh9pwLwU2fOdFD2W5a7rwHDb9KuZC6Lj4Xfb8rnsuajm3REmiSBHHLpqL7OffdH+2PPZOz/Dn6wfuIv/sW9p9Xj56RGBKSgq/v3pLz/ConhzMOm4kHLtDzDNd0BXL2MUu80hy3pNOVk2no3P9AtN3/KJxL9BzwUJrjNibIcHA01GgUVAGBtBBUUrgNv/QffRx7Fl7qbcAxFGSK1h23BbIAY6Iu6vCQoQmJHAexAd3QiLa//cMsAfI5OCiqVlAUyiYhKeAZCiRJgG1pRc1Z58I2f2HR51BerykmAQBJEnDwDMKJwqKYomqIRWKgAJA2O6pdHAZFXchQ47GMfWOiDF4VQeTJ9DXQZNl83rT6pHDbV57j9sVPu1Ht4vCHM/ZErTv3HJqmQR4cAF2X6TKlfFWgSALi8EhZ5xkrInEZLp6BPDQEAAWLlkZD8Pln4P/nowUfN0S10ThuKZdb/30FgugZiRWMSYh98iEAwPPtE0oeU9y8EZHXXobcnz82QFNVhF55CYl1a81xk24P7Iz+lWo84xIM4daZR7gNPv0vbDnxm5BHhsExJCiSyJuPCgAJMbMwUPHrr7dJK9wWcNyGXn4RwrrV0DQNSiQC/z8fNUXHQmiiiNiH70PcvDHnMdJuB2l3AGn6qJ4VW/g6Mlp4nxcAIIcyJ4s0TYM/KpjFZJqmQR4aKjrZomka1Hgs47t8sXicYvgfeQDR998BkPq9FyqaHCuMzGmxYwu4WXPATmkf1/NZWFhYWFhYpDBW9NC1dWN6j2BRPhVl3GbP5NvtdtTVVX6jZWFh8eWHrqrWb3CTyIMDGctLS+E6/EhMefAx8HPmldyX5PmcNm3/P/6OkUcexIHzdRefjaVyyqHSqXJycNkY9IzkjjGeFDmMPEElGMwrcpJ2B+iqKniTQl0gI+NWgpOn4T7q63Duf1DJnykdqkoXboUN60BwPGwLl5R8Ds9Q8PNexKbOBVHAVWpGQIh6NEch0YYgSb18J/kZYBRo+cvMuY1nlSCVA+XxQgkGM7Jp3XamqOM2FBNBS4IeSWGzodrFYSCRFG6zXntxQQGnSiBt+YU+eWgQW078JkYefQgA0FhlB8dQZTluVVVDrz+O6Q2ugkva1ajubGWyXKaUxwuSJCCNlC7NGys0TTOjEuThpHCblhm9vUTeeQvBF54t+DjT2obqM38GPhkVUwmkyw2SJJAIBJCQFLRU53eze487ES3/9xfws2aXPCbTNgUAIKxbk/dxNRbD0P/9AeFXXtT3r29A+0OPQzjwaABAMDZ++cThIlEJIw/dB2gaIm+8BoIgYOfoglEJRnwJb0xGJXOWjUmiyYJxHTbia7JRI2Gw02ea77PAE/9A8Plnih5TjemTNfkibSiXG+2PPonqtLx2bbwctz79Z5NDmaJ0XFQgyiq8Tr2YTI1EoAmJou/ZwTtvw9bvHgctuYJFUxRsPflbGLj1xorGRPI8CJaDkhyTuGWzvt09zsKtO/V56zrsyHE9l4WFhYWFhUUmxgpEy207cVRUaz5r1qySjc8jIzvWJWRhYbFzInZsgRKJmM5KTUiA4Liyn1+ugye+4jNomgb7kl0ztpNuN+SBfiyeWoX5rV7sNr0aNrb4Ja+pyo6ekVjO9v5AAixNmsuPlVAQbHOue1eTJAgb18PB6jfx/khaxm1CRp3HhqpTTivr50qHThNTbEt2BVnG75FnKayrnY1Nh34DS6dOy7uP4STm4hFI0EXDQkg93UisXQ3HPvubTi9/VERbGZOuCVExszR7r/01KK8XdedfUvQ5lMcLqArUaMR8LTh5GsFoYeE2EBUhUzQGDvoW5u6xFNWbWKzROPjOuRj2aZm/g5ggg1Okgq3qhoAl9/Xp/08SaK9zYnNfaeF2JCJAUlQ0eAuLOXK/ftzseADK5wNFEtBCfmiaVvIzdywQJBWSosLJ02Dqq+H7/g/Bzy09YVIuTHMzhHWroYTDoFy5bnOmrh6erx87qmNTLhdWHnoaPh7WX18tBRy3QCryoxS2xbsAJIXoxx/AffQ3ch43Sp6yhT23Xb8+hGLj6bjVhdjsqARNlgGC0IXbt9+A97gT4ODoguVkZvyL4bhNxpIYzsbJghFXoxaISlAjEdANjQAAyumEfY+liL73NqSB/pxJE/M5MX0iq1BebM7+icSoYj5KYU8Kt1pWqZgxYeZNvt60RBz8/IVgp04veCxjElWNhDNijApd/4pBut1QQ0EIWzdj5O9/A1VVDfuuu1d8nErg581H3cW/gLBhPZz7HTCu57KwsLCwsLDIhPLqEXa1F/x8oofylaUi4faaa66Bp8BSWgsLC4t0hu67B+LGDWh/9EloigJNFAvmiRZC6u9D7MNlcB16eIZ7N52RRx6EPDiAKX/LXIpNudxQY1GQqoI/nlk6WgAAmnw2rOsOZgiNANA5FEVzlR1ksqiq7S8P5c2NVRMJ9PzyEjgPOxIcs9B03mmahqggm47dSqGqa8C0TYG0rSMnEqIQfHLZdkIq3LZuiDdMTBcGCkUlAEDk7Tfg/8ffwbZNgcehi2/BMgvKYoIMG0tDU1UkVq4AP694TAIA+E45Db5TTssQx1w2Bp1DhYv7AlERAs1DOPxbsO/WhqqBtZAoFuIe+8OXJqLqxUwKGKVwVAJBUaDr6iH195rbpte7sK47iJGIgCpnYfG8L6CLIg2+wqII2zYFLXfemyMOsc2t6J+3FEOkC3FRMTNIxxMjfsJlY8A0NcP3nbHNqzcmOaSeLlBZTbTBfz8H+x57FRTRSkHQNMRd90H/sg4AyIlKUKIR9N/4W3iPPylncqcQlMMJfsFCJD5fDjWRAJn1GlGT2bfpr83osvdQ89kaAC0Ijqtwm8ywzRJuxc5tgKaBaZ2Cugsv1ffhaUQKRIsk0goDAUBTFZAO56Rz3DJNzfB883iw7VNzHtMUBWosCirt7+Q8+FBE33sbkTdfh++E/K9zoxy00GdO+PVXQTCMKSCSdkfRSa/RYkQlaFlZy0Z2ui95DaJr69B03e+LHsuYMFEiYdA1tSlxehROYcrtgRIOY/jeu6DJMuovu2L8oxLcHjgPOBjOAw4e1/NYWFhYWFhY5GJbsAh0VXVOTKDFjqOiO8KTTz7ZikawsLAoC9JmNzP0DJGzWJ5oPmIffYDh+/4MuqEBjj2W5t1HHh7Ku0SUSi7dVMJh0L7ychubqnTRp9cfw9RkpqkgKegPxLH/vJSwRHIckMf1SjocAElBDYXgtbNmVIIgqVBUDXXxEXRddA48x3wLrkMOL2tMxvnqLrgU4VdehGP3Pct6Ds9SqIsMoOnf7yDRfHLepS0xQQZFEvDsvhucf/5bwXIyQF/ODgBiZyd8bUsA6I7bckhICrwOFvLQIDRRBJPHrZxNvr+Zy8YgLiqQFRU0lZv0M5J0OFcloxyqXfrfaCgkoM7Dm+5VQVKhahqWfe9K7PGNws5SpqEBiTWrTefrtAZdANrcF0bVjCLCrV8XbhuLCLcEw4BN/k7TYae0o++YH6Lz3a3wR8UdItxGiuSmjgVMUzMA3bXNpwm38ZWfY/gvdyG+/FM0XHH1qI9f42JBKxJkislx3EZeewWJL1ZAOejQio7p2H0vJD5fjvjny+HYM/Pao0Z0IY1ypgTB8BuvwPbuuyCWXJiRbT3WhON6VjZFZjqxuanTMOWBf0DTUu8dB89gIJjIe5y4Kdzqry/vN4+H95vHj9u4xwumrh7Vp5+Z9zEz8iDtumbfZXeQbg8ib7wC73dOyutoN4V5e373tv8fD4F0uU3htu3P92/Xz1AIyu3BlobZCDszv3f7o/rnqc/J5ntaXozfgfHa1ZKOW2IUjlvK5YLU14OmG26FsG51WXFGFhYWFhYWFpMX38nfn+ghfOUpO+N2RyzXtLCw+PJA8jyg6k5bNaHfaFbquLUtXAwASHy+Iu/jmqJA8ftB5RFuzSW0BbIP89GYFG7Tc257RmLQALTU6O4rJRJB9OMP8raUEyQJyu2GEgrCbWfMZf2G682jxiFu2WQ6uiqBmz4DNWedW3Z5EM/ScAlh1H7xLsRtHXn30bNnaZAsB6ahMUOIyoZt0UXG2CcfwuPQBb5ApEzhNulglpLt6OUIt2osisSaVWbmKpBaHl6oFC0YFTF1ZAtqfn8poh8uQ01SuFV+/mP0XXOluZ9RykZW1RTNhaTrG6AJCajJkjSzoKy/eEGZ8fpp9BVeti92dULs6szI8DUwsivL/f1uL+nL7/tuuBZdl5w3psdnmpKO2+4uc5smiRi6+48gWBbVP/rJdh1/1kM34Kcf3guKJFCfFU8hbFgHAHDsvW9Fx7Qv3QdVp58Jblru8nPFEPbS3i90TR1IAG4hXLYTfTQYWcT5oLw+0D4f1Hgckbdeh4PRy8nyFVDFsxy3X0ZIux2t9z4I33dPNbcRNA3nAQdD6u6CsGF93ucx9Q3wfe+H4LLc4eYxbDbTsTqekDyPV/Y9Fatad8nYbkTweJKRNeE3X8PQX/8MJVL4umS8VtVkmZhRuljIVVwM2+Jd4Nhzb1BeLxx771fx8y0sLCwsLCwsLCqjbOF2NM2zFhYWX10MJ4+WiINyOtD425vg/toxFR2DaZsCyutD/Iv8wq0S8AOqkld8Y5pbwM9bUNH5mqr0Mafn3HYN6//dWqOLcGLHFvT/7jeILnsv7zGM/D+vgzWjEoxmd6eaFLDLzE7cHniGgkQxScdzfiHJiG8Qu7sgbNoITSkcq8C0tsG2ZFdE33kTtvdeAVCe49aIJbCxlCncGQ7MYgibNqLnl5dkNMAbglWhgjJ/VIRDioIa7ocmS6hOlsTJakqoAIC4IINWZNQOdUAeGS44BqZez8aU+vS4hGkNSeG2RM5tOVEJIw/dj67zzwbyfLZOe/rPOHL9/0xn3XhjTCw4eRpSdxe0CkoEy4FubILrsCPBzZpjbgs89QSk7i54TzwFTGPTdh2fdTphk+Jo8NpynNjitg5QNbUVC1RMXT283zw+b3MuyXJgp88EVVVtbqNrakGRBNyJEEJFCvS2l0LCbfi1l/W4BACBp5/AwG03oWVkKxRVgyDlTg4kkpMXRiRM6OUXEXn7zXEb93jSe/WvMHDHLTnbCYoCU1cPuioz/sF95NdQe9FlYJMldNkwTc3wnXAyuALZ4CRvNx2rSjSCwHNPIbF29Xb+FPlxcLT5+WFgrOQwVhbEP/sEoReeKbp8kXIaUQm6uLs9Gbfe405E3YWXgiAr6je2sLCwsLCwsLAYJWV/61JV1YpJsLCwKBvSpgudajwOgmFhW7g479LwYhAEAX7hYohbN+d1uMpDuhuTrskVbl0HHoKm628BO6W97PM1m47blMhnZKq2JtvqDQdvoRZtyu2BEtSF24Sk4MVPu3HfyxsAAHYlKdwWiSQYKxiKgEIx0DTd3ZiPuCDDztEIPP4Iui85Vy84KgBBEKi75JegG5uQ+McDcAmRspyFoqzHEthYOuW4LUO4NVrEjdIkQBcWgSLCbUQAJ4ugSBKk3WFGJQgUkyHcxgQFnkQA8/5xC0Iv/rvgGFyHH4UpD/zDdN65bAzqPDw295cQbv1xOHmmoDMSAOTBAdC1tXnFFr6vA23Bzoxyu/HE+H26bAyUkeEMQXIsIFkWtedeZEYOyH4/Ak89Aaa5dUyW5/NeN3hZQIsv09GvKQqk7k6wrfkFunJQggEoSce1gX33PdFy651m8SKgC7cEAXil8Dhn3OYKt/LICAb/eCuCz/wLAOA88BAAQNumTwAgb85tLMtx63/sYQSfe2rcxj2eSH19ELdsztmuhENIrFub40RlW9vgOvCQnOziciHtdlP4VAIBjNx/L2KffDSqY5Vi6eqXsfdHmX8XQ7j1OvTrmzw0CNLhLCrC8vMXovWeB8yMWH7+QrTefT8c+1pFXxYWFhYWFhYWOztfquny9vZ2EASR8e/GG2+c6GFZWHwloVxuUF4fNFmGJolQQsGiwmAh7MlM18G7/pj7oKqAnTLVbA3fXqpdHDiGQo8/5Tg0hFsjKsHMTSyQf0jX1oG02+G16YLI759ZiXfXDmB6gwszvfq2HeG4JQgCFMtBgwZVyO/cjAoy7CwNJRQEYbPr2b1FoFwuNPzqajReeQ0oX5WZKVsMowSJZym4j/o6ai+4NK+LMedcyXb7dNHMbU8uDS4g3AaiInhVBEHoTjJDuI0TjOmQA/SoBFYRQRBEUfGGcrlAeX0ZUUHT6l3oGIhAKFL61uuPFc23BQB5oB90bf7JUMbrg1OM7jDh1oiecLGkXuY0zhML0bffgCYkUHXq6SCY7c/VddZWgaEJLG3NfE/K/X3QJKniCSMDYdMGdPzwuwj994WS+1JeLwgA1RAQGifhVlH1ksNs4VZYp7s9jQkGtrkF3IxZqN20Aowi5jg2gcyMW01VoQQCZcew7GwY8TTZxFcsR88vLkT8s0/yPk/s2AJh86ac7YGnnsC2n/7IdNpnQ9ps0ISEXrppRA6MUgQuRcNIB6b2rc3Y5o/o13OPXX8dyENDoPJMXqZD8jyY+gbzGk+yLJjGpqLxOBYWFhYWFhYWFjsH4996soO59tprceaZqaIKl2v8nW0WFha5eI87Ad7jTgAAxJZ/ir6rf4Was86F++hvVHQcwyFEJ9vONU1D9N234dh7X/Bz56PljrvzPk/2+xF48nHYFi6GY6+9yzoXQRBo9NnQmx6VMBSD186aYokhghqO4mzqLvg5AODI/jBikoa5rV7sPqMatW4e/sc2ww/ssJtliuegaigYlRAXFNh5WhdtymxFZ1vbgNY2uN96p6wSpvQsTba1rWwRjXS6AJLMEG4Nx22kiHA7lVJAQG9L5zkaPEMhRjBQEymXbFxQwCoSCAIgirSqa5oGYd0aADALeJZMrcKy9YN4Z3U/Dl2cu8RfUlQMBhOY0+wpeFwlGoEajYCuq8/7OFdTDYe4GpsjOyYqwRDCHZr+9yTHoSE+9NJ/EHz2STRcfT3cx3wL3MxZ4Mao1IhxudHgtWH3OZm/c9LlRu15F4MZpeOWbZ8G0u5A9KMPMkoZwm++BnHrFvhO/r4phNE1tbDvuTeUcPW4lZNF0pzR6STW6cJeevGb86BDQX+xCjOGNyGa2D/nWEZUgo2j9DIuRZ7Ewq1Hj3pJlggaqBH9PU/mud4qwQC6L70AdEMjWv5wV4bzXR4ZhtzbU3BSgZ06HWo0Ak2SoCb08rdi15HtQbM5YRNjECQFHKOPMRCV4LYxoCkSmqZBGR4Ev2hJ8eOoKsQtm0CwHNjWNsjDQ1ACATAtrSUn7CwsLCwsLCwsLCaWL5XjFtCF2oaGBvOfYwc42ywsLIqjJcXO0dzcEgQB14GHwJa8MY289jIGbrkeQ3++s2j2tiaJCL3wDBIrP6/ofI0+G/oCcSiqBk3TsG0oarptAZj5n0SJm92p9S5c/M35OHrXZtQms1Yde++L2vMuLui0HGtUuwOrp+8Nfu783MdUDXFRhp2loATLF24N9l39P+y37PGS+8UNgYiloMbjecu48kFQFCiXG0ogYG5zJwWrQhmi/ogIL6kLxYYjutrFIarR5tJmIOW4JUs4bgmCQN9vr8LIww+Y247cpQksTeLZjzrzPmcgEIeG4vm2RuwHU0C4tdVUgdRUREYCBY8xlhiCoEPRRSjSOfafm5qqQOrphtTdpUegzJ0/ZqWnRvSIGs6MsKBcLrgOPQL8rNmjOi5BUbDtujvETRsyspBjH32A4NNPZGR8Mg2NaPjVbxCYsXjcHLepSIvMOffE2tUg7HYwaZMi3MxZIAkCvnighOOWguLX40go3+QUbkm3G1Bk0/1qoOYpkTOgPF54vnk8pG0dCL/2cv7nOfJPsPlOOBmN19wAkudTJV/j5LjVHE6QmoZoIPXa9kcFeJP5tmooCE2SSq9i0DR0X3Ie/I8+BAAIv/o/dF9ybkZhoIWFhYWFhYWFxc7Jl064vfHGG1FdXY1ddtkFv//97yGXWJotCAJCoVDGPwsLi+1H6u9D8IVnIXZ1Qk2KnSS//c4e5wEHwbZkN4RffhFbTzkeI//4e14B18xIDVf2nm6qskNRNQwE4wjGJEQSkllMBgAEw4KqrilYdiR2dyHwzJNmnms67JSpcB16xKiavEcD6XDizQVfM7NF00lICjQANo6GGgmDclXmAm4IdKO1f0PJ/QyBiGModJ59OnqvuLTsc9B19SDolEiVKifLf10PREX0zd8HdZddATIpRNe4efx3xmFouTUl9OuOWxEkARAlBBe6oTFjybTbzuKgBQ1YtS2ATX25r63eZMxGoy+/IxvQBUbS4SwcleCrAkkCwlDh4rSxxBAE3Y31aPzdzXAdduSYn4Np1HON+665Iu/y9O3BdejhaL37fnDTpmdsV+Px7S5WdeyxFwAg9vGHqeNGIiA4Pq8j021jEIpLUNWxL3QN5XHcapIEcdMG8LPmZgjJdE0t5LlLEOTdiCYKC7d2ljZzpCet4zb5XleCmXEJRrYtVUCA9R53AiiPF/5HHjQndoRNGxB9/109IqUMJ6pmOG5HUfJVDsakRDRtEicQEeFL5tuCIOA57gTYd92j6HEIigLpcEJJupDNcrICkT8WFhYWFhYWFhY7D18q4fb888/HY489htdffx1nnXUWrr/+elx22WVFn3PDDTfA4/GY/1pbW3fQaC0svtyI27Zi+K93Q1i3Zrsct9kQDIv6y38Nft4CaPEYAo8/kte5R3AcCJYdlXALAD0jcXQNJ4vJ0hy3nmO+hSn3PQy2uSXv88UtmzHywF8gbNqY81i5btOxwsbSpkCTTSzpwnPShJ5v6yq8tD8fKmcDIyVKCmOJtCxNNRYt6GLLR/Pv70DT7242/99pK1xOlhAVJCQFVEsbnPvsD5LVHWlVThadpBtobjNfJzFBBqmpIHhbwcgLA6auHsrwUEbB27F76s7G5z7MdasZwm0xx61t4WK0P/IvOA8+LO/j9j2X4r3djkOfwhYd21gRSchgKBI2lwO2BYvANuV/bW8PGYV0Y+S0NaDcHjCNTSCYzN9Xzy8vQffF527XsW1LdgUAJNasNrcVeh0P/vlO7LL8v1A1La/LdXsxBXZ76udUIhHYdtkd9l13z9iXrq6Bcs7lWFU/P79wmxwfz1IgOA62XfcoeE3b2XHufxDqLrsClCfzGqZG9es3WSAyi7TZ4Tv5+1ACfgSe+Reknm70XftrQJFRd+mvCjrC41+swOCfbofU0w3S5YZt8S6gx7jQzxxjUriNjejiuqyoCMUleB26eE+5Pag+7Yyy4oBIpwtqUsw2ncLjJDhbWFhYWFhYWFiMHTu9cHv55ZfnFI5l/1u7Vs93u/jii3HQQQdh0aJFOPvss3HrrbfizjvvhFCgmAcAfvnLXyIYDJr/OjvzL3+1sLCoDEMQUxMJ05U0Vll6JM+j/oqrwc2cDfte++TdhyAIkC431Apd9CnhNobOIf3mtqW6fIesIR7kK8vpvfIybDvztIrGsz201thx7Fv3ovPee3IeM4Rb3sai/aHHUXfBJZUdnOdBqirERPEcVtPZRyrQJGm7HF5uW+FyspFkHmw1p0FTUmJ1tZsHLyUwuHaDKb7GRRlfNCwEd/cjsO+yW9Fz0g2NgKZBSsYbAMCcZjdmNrrxyoqeHFGsz3TclhZE0h2S6fAzZ6N/4b7ok7e/uKscwnEJLhsDNR7XSwSVwsVro4WuqQXT1AznwYeBmzptTI+tiiKEzZvMCAoA0BQFUncnqGQ29mih3B7QDU0Zwr0aCeeNk4iv+Ax1XXom8njk3BqRFkbWMwDQPh8afvUbeI79ds7+Di6ZCZ3Ifb/ERQUUSYClSfCz56Lxqt/CtniXMR/zjoCbNl2frMleyaBpIBim6AoH1xFHg2luRfCZJwEAdH0D6n7+K9jmLyz4HKmrE+GXX4Q00A/7kl3ReM0NZgb2WKPOmo9Xpx+MBKdPFASTMRw+Z+WfpaTTaeb+asmSTaLExJWFhYWFhYWFhcXEs9OXk11yySX44Q9/WHSfadPy3wTutddekGUZW7duxezZ+TPuOI4DZxUzWFiMOYaTR43HgOSyYYIbuxxAyuFE0823F9/H7YGSJdzKQ4OQ+vvAz1uQ11HVXKWPO72gLD0qIbrsPUh9vfAc++28wpsZ0ZBWqmWgRMIFC2/Gg/ltPvChXgyt24jstQQxQ1DlRvcxYNzwx4MRcLbCf1ezBElJlrpV4LhNbFiHxKqVcB16BCiXCxxDgiaJvEJUIKoLZQue/hO2/SuEKQ/8A4Cecbu08wOEfvEn1N79F7BtUxATUsvES8HUNwAA5L4+04lKEASO3bMVtz67Ci+v6MG39kplixqO2zpP4d9J5O03oMkyXAUctwDgc7KIxEVIigqGGt851nBcgtNGI/LGqxi65//QeM0NYy7iESSJlj/9dUyPaSD39qD74nPgPfEUVJ2iT4zI/X3QJKnsMrxitN7114z3uhqNZjqIk1BuL/iBrQB0ga15jE2YRlSC21beNYR94TEctX49YgfmfkeKiwp4hhqznOGJRlMUQFUyXNe151yAmp+dX/RnJCgKtedcAJAkmKZmNN14W8EJFfM5ycmn7Ezd8YCeMRvvThFxlF3/XAlE9euo16H/nP5/PYbYsvdQf8U1oEtkFFMutxnho8bjAEXv0M8jCwsLCwsLCwuL0bHTO25ra2sxZ86cov9YNv9y0uXLl4MkSdTV7ZgiIAsLixRGLIKWSMDzzePQdv+jYNtG1+5e8BxJ130hnAccDOeBB2ds8//j7+i94lJzGW02dV4bSIJAz0gcncMxUCSBxqqUcBt+/RWMPHRfweXeZFK4VfNENKjRyqICtpd5rR7IJI1gIJLzWCzpFHWJEYT++wLEjq0VHdsQ5uOhcNH9DIGYl43iq/J//vjyzzDywF8g9+sZswRBwG1n85aTGcItpwgZeZPVThYixUJRNTPXMS7KaA10gnjvNbMVvhBMUzPo+gZoUuY5D1nYCAdH47kPOzPiInr9MdS4eLMBPh+BZ540S4LyIQ3048iHrsAhm99AIDL2zs1sIgkZLp4xM0Er+RtVQqn362ghXW4AmS53cVsHAGQUdo2WbCHPsf9BsO+ZuzSdcrvBJKKApo1LQZlZTmZPiW39N/0O/n8+mnd/cuMazBtYkzcqISEqsCUnLgLPPYXBO28bF6f1jkDYvAlbTjgGgWefynmsnNcbP2+B6ZgtJdoCaatJ4nFE3n4Dg3f9Me8Ki7HAmFgzVkiMJK8HhnArdmyFsHF9WSsZKI8HBMPof2dNA+VyfWmEewsLCwsLCwuLLzM7vXBbLu+//z5uv/12rFixAps3b8YjjzyCiy66CN///vfhm6RNyRYWk5mU4zYOkuNAV1XtcHeP99vfMR14xljCr/4PAMxCnmwYikSdh0ePP4auoSgavLYMx6MmJEDwfMEbXsqdFJGCuTfyaiSyQ4XbKbVOaDSDcCjXGRZLOmFdgT4M3fN/SKxeWdGx47MW4eUZhyJOF3dRGxm3vJR03FZQzEZ5vQAAJRAwtzl5GpE85WT+pKDBymJGbm2Nm4dA68KtlizJiwkKFvavROTeO6EJxYVb26IlaLvngZwMSZ6lcOQuzegYjODzjtRrqc8fL5pvC+huULquvuDjpMMBVozDKUbgj46vcKtpWioqIbmM2hBCJwuU1wuqphaxjz4wxUdDuGXb2rf7+LLfD/8//4H4is8AADU/Phveb38ndxxuNyhNBacICI5DVIJRymeUk2mahtinHyOxelXe/TmfD3Yphkg8dywxUYaN1ScX4p9+gsg7b4GgCk827MxQbjegqhnXCQAIv/ZyRqncWGGIpGo8jsTqVQj/7z/QlPHJL3eGBnHu+3eBeu3fAIDBoH698jl14VYZGgTp9pQVQ1R30WVof+hxEBSFhiuvQdvf8gv+FhYWFhYWFhYWOxdfGuGW4zg89thjOPDAAzF//nxcd911uOiii3DvvfdO9NAsLL6SkDY7+AWLwNQ3QOzYiviqLybc0SX19Zr/XUi4BfSc2+7hGHpGYmitzRQa1XgCZJHIB4KiYN9jKdgp7RnbNVmGJiTGzc2YD5IkwNptiEfjEOVMYSGejAvgkxEGRIXZs8qMeXi/bSkEprhIaWTc8jNnovXeB+E67Miyz5Fqiw+Y21w2Jm/GrT+5hJiWhIzCnXqvDSLFQlZV03EbE2XwqgSCKL8wL7FurVnoY3DMHnp0wn8+1kvKogkZobhUNN9WjUWhRsLFhVu7AxTHwiFG8cH6wbLGN1oESYWkqHDydEq4dZQvru8MECQJ1yGHQxkeQvzz5QAAqWsbAIAdg8JRTRLhf/RBRJe9W3Q/0u0BSRCwi7FxddwaUQlqNApNSICuzp/JwFZVgdQ0SMFc939cUMAnhVsl4DcnSSYj5nXCP5Kxffi+exB45l9jfr70GCDDsT9eJV+8nUdV3A91eAgA8NGGIRAA5rV6AejRP3RN7aiObbltLSwsLCwsLCwmBzt9xm257Lrrrli2bNlED8PCwiIJabOh6Xc3AwD6b7kB0XfexNR/vbBDxxB+8zWEXngWtRdeCra5BXJfj/mY4i8m3Nrw6eZhALnFZFoiDoIv7jJtuOLqnG1qdHyXoRfC7rCBGoliY2/IvNkHYLbe84ruxqu0NMxYZm0Is4UwMm7tdg5MhasfUsJtyr3ssjFY35MrRAWjuqhFifEMx22th4dMc1AUzRRZ4oICuyYBJAmiQNROOpokofeaX0ETJdgWLobzoEPgOvAQtNU6saDNh7dW9+PcuISBYOliMmmgHwBA1xaO8CEIAq76WtQOJnDv21tw5C5NqPOMjzAUTuYFu2wMlGgEIMmM399kwXXI4Qj881GEX3kJ9l12Q+35l8B70vfG5Geha+tAOl0QNm+G1NONwbvugPvIr8O5/4EZ+9l32wM8WAhruHFy3EpgKNKM4VCSYh5VXZN3f8rrBUnmz9uOi7LpDFcCftD1jWM+3h0FwTAgna6Mn1NTVaix6Lhcb6mqGri/diy46TMhbtoIEERZ15HR4Kj2AgC0aBiirOLjjcOY1+pFlZODpiiQh4dhby+v7E/s7kLi8+Ww774n4iu/AOXzwb5k13EZt4WFhYWFhYWFxdjxpXHcWlhY7LxogqAXodA7dq5IjUQgbFhnOrGk3vIdtwat1ZnCjyoIRR23hSCdLrTceS+8x51Y8XO3B/47p+D1qQdi1bZAxvZ4UrhlRxFhAADejtW48N0/Qvqk+ISZkXHLhANIbFhXMlM2HSop9KYLMk6ehqSoEKRMwdgfEUCpMkhVzci4pUgCdrcTckZUggwbZJC8rSzXmaaqqDr1dNgWLEL88+UY/MPNkJPC/9d2a4Yoq3h1Ra9ZTFYsKiH+6ScAAG7GrKLnZLxeTHdoSEgK7nlpfckxjpZI0sXptDF6lIfdUVbO584G09AI+9J9QPmqoGkaCJoG29wyJscmCALstOkQt26GPDKMxMrP814/bAsWofqEkxBjHXld4duLEWlhII/ok0u0ryrv/pTPB5IgQIQCOY/FRQU2loKmKFBCwUntuAUAyleV4bhVYzE9x3Ucomlonw81P/kZ7LvsBjUeB8Hx4/aesbscUEgSWiSMFVtHEBNl7D1bd9gqoRCgKqAKOK6zEdauxtA9/wdh62YM/flOBJ95clzGbGFhYWFhYWFhMbZMvrszCwuLScPI3/8G/z8fhZqIgyzhUh0PzLzZZHFMelRCdtlUOumOydaaTEHTNn8B+AWLip439NJ/0H/zddDUVDwBQVFgW9vAFFkiPx7M/PoRWFc/D6s7Axnbo6Zwm1zqW+HyeJYm4BbCkPNk+aZjZNxqH7yNnksvMLNHy4Fye8AvWAy6vsHc5rbrzrbsgjJ/VITdxqHtLw+i+vQzMx6Tp8/FzYdfCfdRXwegC7e8KpUdk0ByHDxHH4PGq68zjy12bAEAHDi/AQ6Oxr8/6UJfGcItXVcP25JdYd+luNON8vpgFyLYe1YN3ljZhxVbRoruP1r6AvqYa908Gn79W7TcOXnjhRouvwo1Pz4baiiI6IfLik7OVAo3bQY0IQFhgy6iF3q/OHgGJEGYDvCxJBST4E4rJpNLOG752fOwfOHhGKAyxUtZ0eMxeJbSSxRV1ZwkmaxQHm9Gxm1qhYNrXM873p9tDp5BnLYBsSjeX6vHpuw9R3frkzYb6i+/Cu7DjyrrWMbvQgkG9dieCldZWFhYWFhYWFhYTAxfmqgECwuLnY/Iu2+D5HkQLAuijPKUscYoWVKDhnDbA4K3of0fT+V1WibWrgbbPi3TcZuVcVt73sUlzyts3IDoe29DjZ4Hymi8j0SgDA+BrqsftzzEfDh4GlPrnVjVGdCdiMmf28yera2BNnueOc5y4ZxOCACkaG7xWToJUQEBgEzo+1UiEJM8j6bf3ZSxzcnrH1uRuIRad0ow8UdEeJxcXmG8rsqBFZ1BRBMyHDyNuKgg5q0DN8tb9lgMjOxiaVsHsGRX8CyFQxY14vmPOvHWKj0GoclXWBBx7ncAnPsdUPI8VT84A1Wnno6znbX4eNN7uPPfa3DPz/YBRWa+blVVQ1SQM5yYlbBtMAoAaKt1gOS4skqOdnbiX3yOgVuuR825F8FdQaZyMdip05LHXgEgvyAodmxF343XYj9tFoJTDh2T86YTSUhoSZtI4mfORtVpZ4Btn5p3f27adGza9Uh094czthvvfRtLATQD3ymngZ02fczHuyOpPe+ijHK1VF7z+ETT9Pz6F+CmTodz3wNMkXg8YGkSCdYOPhbB++sG0OizYUryM4nkeTiW7lP2sYzYCGVIF4B35OeQhYWFhYWFhYXF6LEctxYWFuMGabNBjcehJuITItyaomlYz0R1H/E1VJ1yWn7Rdv069Fx+MQbvuMUUbu0sDZ+j8uxCyuPRz5vmRo1/9jG6LjgbsU8/rvh420P/rTfijH9fh+GwgIFgKqYglnTcVh31NTTfdBvoAq69QnAuXQSQY8WF27ikwMbS0GK6QFhpJEM2hkCZ47iNCKjj9L9jdqZno4vGnMG16F3xBQD9Z19x0ClouPzXFZ+fmzELTTfcCtdhR5jbvrabviR/VWcADEWi2pX/ta4KQtnnYVvbwE5pR0u1Ayfu244tAxH8+cV1kNPa60ciAi66/yOcfMubiCbkin8WIE24rXEg9slHFTmid0Yi772NgVuuBwCwbe1jdlx+9ly4DjvSFLvyTUAQLAu5twe1SmTMM241TUMoLpkTF4A+ieA97oSiLn47RyEmyNA0zdyWMIVbGpTTCd+Jp8Cx+15jOt4dDVPfkFnSRVHg5y0A09g0LucTN22EsHUzPMd8C76Tvz8u5wD0mI43F34DT8/8OgaCCew9u878/NIkEZpc/vueSk42yIMD+rEtx62FhYWFhYWFxaTAEm4tLCzGDZLnoSXiIG0O0FXl5fCNJWZUQlK4de53ADzHfhvR999B+NX/Ze6bdCOJ3Z2wczTqPDymNjgzRF5NEtF/640IvfxiifMawm3A3KZGkkt3K4wk2G4UBXZVAKGpWJmWcxsTZJAEAY4Z3ccA79J/DrWUcCvI+pLsaFK4rfDnDzzzJAb/dLv5/4ZwG4mnBAtZURGKS2gThtBz2QWIvPl6xjHqHRRO/OJJhF/8D1RVz421sxRGA2mzgZ87P0OAntXkxsxG/bVW5+FBkrkTA5qmoevCn6L/1hvLOo8mSRC7u6CEwzjlgGmY0+zBU8s6cOF9H6JnJIa13UH89O5lWLnNj4SkoD8ZeVApnUNReOws3ByJvt/+Gv5/Pjqq4+wspJe+sa2tY3ZcpqERtedeBLa1DUDqepEOmbzeeNQEQrGxjUqIiwoUVTOjQspBTSRw+NM34/C1L0KQUoJ/PFkYaBvle2BnRIlEkFi3BkryOsu1T0PT9bfkFMiNFYTdDq3EtW+sGGmajjW8Hhez79zU6zv86svY8p1vIL7is7KOY6xAMQoSJ2MJoYWFhYWFhYXFVxFLuLWwsBg3CF533DbfdBuarvv9Dj8/5fWi5uzz4Nz/4AzHWeDpf2HkkYcy9mWamkHY7aA8XgDADafuhl8evzBjHzUeR/TtN8ycy0KQScetmhSMAUBJLqelXOObuZgNwbLgaAq0Kmfk3MYEvZwo+OxTGH7o/oqPa/PoP4caLxGVIOnnUWNRvf29wvb1xKovEH71ZTMvOJ/j1h/V3Y0+SncSEllLgBvqvQCAWDhqLhNf/MEzOeJ9uSiRCOKrvsh4TRmu28aq/GKIsH4d5N6egkVS2cQ+/Rhd5/wYsQ/fB89SuP3He+KkfduxpiuIs+56Hxf+9UOE4iKWJouKhsLlu3kNNE1Dx2AUrTWO1NLyPILkZMIsfaPocRGmbLvugeofnQWqujbnMdLuAEgKLiWOYEzMeH1sL0bZWXokRs8vL0HPr35e8DkEx8EeGUFV3I9IIvV+SY9KCP33BXSe+xOIHVvHbKwTQeyD99Dzi4uQWL1yh5yPtNmhxuPovvxiDD9437iey8GSsEkxuDgKC9q85nYlpH++lJvjS7mc4GbPA1PfAG72XDBp2eEWFhYWFhYWFhY7L5Zwa2FhMW6QNhs0UYCmKBNyfoJh4T7q6+BnzUb8k4+w9bSTEF32brLIxp9RHqapKuiaWsjJ/L/2Oicas7JK1USyyKtEGU3KcZuKSkg5TnesMEawHCiKQA1PYlWW49bO0Yi++xYib7xW8XHtHhf+sehEdCw8qOh+Rns9QIBMiuKVwLS0AqoCYcM6AOmO2zThNqILt56kcJsdx1BX5YRMUkiEo4iJMkhVQevKtxBb/mnF4wEA/6MPofeKS80lxwBwyKIGVDm5DGElncjbbwAAnAccVNY56Hp9+bvU3wcAYCgSPzlyNm48bTfwLIUqJ4c7frwXjtldd5UOj0K4DURFRBISptQ6oCRfn9Q4lzmNNwRBYMpDj6Ptr38f82OHXvoPBm65Hval++R13BIEAcrthkOOQ1E1xISxu+6lhNtUVILU21P02koQBFSnBw4xapYRAplRCXLAD6lr25iNc6KgkhMiRiFd9OMPMHTvXeb1fKwhbTaosSiEtashp5Vejgd7rX0Nl779BxxUD9BU6mu7MTFIljkZSDAsmm+6DbXnXoTmm/4A16FHlH6ShYWFhYWFhYXFhGOVk1lYWIwb9j32Al1Ti+CzT4GdNh32JbtOyDg0VYXU1ws1FARpd+g3+aoCNRoxc3AHbrtJL5wiSWiqCoLMndfSksItUUK4ZZpb4D3+JLDt08xtqaiEHS3csiAAzGuw443uMOKiDBtLIybKsHEU1FhsVPENNhuHDTUz0eYsno2bEBVUOTk0XHnNqMbv3O8ABJ9+ApE3XtNzRpPCVbqD0B/RRUs3qYtT2aU7tR4en1MsEIkiLshgFREkQYDkR1fOYyyXl7Z1mPmiTp7BYz8/MKc8DAA0RUH0nTdBNzaBnT6zrHMYx5WTy5oN9phRg4cv2h8AwDEU1vfo4s1wOIFK2Taki7WtNY6UCDTJhVsgNXEy5hAE5IF+iFs2F8yVJd1u2Pv0CZtgTISDH5uvWYZw67bpjnVNlqEEA+Dnzi/6PM3lhsPfl5GBHEtGJfAsBS2ZuzwRGeRjibFSwhBuhTWrEfrPc3B//dhxOR9pt5vnynb4jzVa8jNq99rM15IRATRur3cLCwsLCwsLC4udAstxa2FhMW64Dj4MvlNOw8hD9yHyxqsTMoaeKy9D589+DCnpiqIbGkF5vQAAZWTE3M8QyFwHHwZNzF8sVK7jlqmrR9Wpp4OfPcfcpokCQBAgd3AhDJGMJljY6ICianjtc93BGRcUODgaaiw6qsIwhiLAaTKkcLjofrFkxu1oYafNANPShsi7b0GTZTiNqIS0DNGRpOPWhfzCLUOR0DgOciyGmKiAU0QQROm/Y8ExTWkHgJwir3yiLQDEv1gBJeCH84CD8xbj5YO0O0A6XTnCLaALthyj/05r3LrgNhyq3HFrFJNNqXWkJhYmeVTCeMJNmw4A6L+h8CREzU/OwcC3zgCQW6C3PRjCrTM5caH4RwBNA1WiVJBw++CQoojmiUqwcxTUhJ6NTHCjey/sLJiOW78upprRNOOUKe455tuoOvVHADDqCaBycVRXgSCAOVn6rBIKgWDZiq5jgWee1OMd7rsHYk/XGI/UwsLCwsLCwsJiPLCEWwsLi3FFE8pzqY4XBE1DCQYg9/UANAO6ugaUzwcgszxMHhwAN2sOas+7uOCNsPmzjELkqLvoMkz91wsgqB1bCOQ+6utouvkOHHLgArhtDB55czMkRUVM0J23aiw2KjGZIAj87MN7sde/7yq4j6pqECQFNkbP0iy3RCf7PM4DD4EaCiL22cepqIQ0B6HhuLWzpO4wzuOAi1c3YYhyZDhuR+uUY9raAQBiZ3lLzMVNGwCCgHPfAyo6D13fYEYlFMJjZ0GRxKiiEgzhtrXWAU1TQVXVgPJY7r1CGH/3YtgWLAIzey4AjGlBmXEs4/UvjwwDQMnSR8rrBaWqiAVSedtGVALP0tAEfdJjtJMYOwuUxwMQhOmCTU1EjI+D3L7bHnAs3QfA+H+2HXXgPDT4bGDjkYztajhkFo6VS+zjDyCsXY3g80+bIreFhYWFxf+3d9/xbdTnH8A/d6e9vR3HK3uQQfZgBRqSQAizAQo0UGh/BcIepVA2ZRYoo0BLIQQKlBIg7BUgEEYYCYSVQbYzvLe2dHe/PzRsx/KWLcn+vF8vWvt0unss55z4o+eeLxFRcuOoBCLqNc41q1H95L8AAKIuMbfiilYbVI8b/j0l0ObkQJAk6PLyYZw4KdqNqgb8kGtrYBg7rt1jaTIyYT/5VOiHd3y7+/6/XA1NRiayr7gmuq2vQ1sg1P0bua37tEOH4N+rfsE76/fB7QvCrA2F0d0ZlQAAslYPna/tW/S9ARkqAJNOQNW//gHz7MNgnDipy+exHvkraHMHwTj+YIiSCINWark4WbjjNuPkxcj63W9jHuOXk5di1ff7UdDogy4Y6bjtXnArWSyQ0jPgL9nVqf0dp5wG6/yFXX6dtdk5CJaVQpXlNv/sSKKANLO+e8FtlQs6jYhsuxHStJkwT5vZ5WMMJKJOB8O4CdBktl6YLEJVFNhVLwRVQYM7dud+d0TeqLBFgtvqKgCA1EFwKxy5AP+pzsRJctP79M0XJ1OjHbepPSpBkCRI6RlQ1dDccsXphKA3QND03j9zm+7A6N2OW2NmOjSi0OKNRgDI/cvNUDyeLh2reUd9b9dNRERERPHB4JaIeo3sdEZ/2UxUx21khm2wvAymqdMBAMaJk1oEiMGqUAiiykGU/fVGmA+bA+sRR7U6ljZvMDKWnNup8warKqG43dHPnZ9/Cslmg3H8xG5/Ld2heL2QG+oh2ew4YUYBXvx8F/7z8XaoAMxaEbZFJ0I/ZFi3ji3rDZCcNW0+7g4viGRFKGTt7nxfTWYWLIcdEf3catS2WJysJtxx67Do2jxGjiP0529HuRMerRGB2XOhG9q9rxsAdMVDIdfWQFXVTo0/iLWYVUeyr/gTBG3bX1NEulUXfQ26Yk+lCwWZ5jZHPFBreX+9p93Ha194FunPPYvMUb+Nc8dteBxIOLg1TpiEvDvuhWbQ4HafZxw2HDvTq+FsalCPXpdGnQT7SYthPuyImDO9U03hE/+JXouKs7FXx37UrngBtc8th+OU02CaNqPXzgMAkr31HSIAIDnSIDnSunasZh3IB46UISIiIqLkxOCWiHpN89tvE3UrrmQLBbfZV1wTnU16oGBlBQBAm5uH+ldfgmZQXszgtmvntSNYXR39vOrRB6EbMrTPg1vnmtWoevRB5N50O0yTpuC0Q4vx+Pu/AAAMZiMyTz2/28dWdAZI/rY7bqPBrRq+HbsHQYqqqvDv3AFVDsJq1EZnfgKhjlurUYvAjxvgra2BZc6vWoWpxft+xlHbv8TO4RmoMaUDZ8yDaVj73Yrtyb3+lk6FXb7tW+H54XtYjjiyw9vaD9SZ0Faur0OmScL2Mh8URYXYyRDW65dRXu/BmIJcAID723UI7N0D67xjUv62+USSbHaIImAKeFAfx47bRk/4WgoHt5LFAqmDOwSA0BxbfdALb2PTbfbeZh23hpGjgJGj4lZnIjW/5s2zD4vO7+2Vc4WvM/OsQ6AfMrSDvXtGsttR8PjTLUJaVZbh27IJmuycdjvAD9R8tEJfz1snIiIiou5J/RYLIkpazbtsNbmDElKDGF5xW0pLh65oCIDQL72Vjz2E+jdeBQDoR43B4L8/CvtxJwCiiGBlZcxjNX78EfZecRF8O7Z3eF7JbofcUA9VVaEqChSPOyELPwnhERWRBddOmF6INHMoEDTpe/benao3QpL9UGU55uPucEBkVsLBrbH7QYHicmHf1Zei9rmnWwW3NY0+pFl0aHjzNVQ+8mDMDtjMHT/i0N1fYE9paK6jsYdfe2c7FF1ffoGap58ILSbVRXJjIxo/fB++bb+0uU/53+7AwhdvhSwrXQoK91Q1LUwGAM5PP0H1sn91uUZqSbLZIAoCTAE36uPYcdvoCUAAYA7/uQ1UlEfnubZHv3MzrllzH8zrP4tui45K0Gug+P1QVTVudSaSd8sm1L3+ChS/H46TFyP9jCW9di4h/LOsq6MKunUuUYQ2OweirumNHLmhAfuvuwp1L7/YpWM17/wXevDzmIiIiIj6DoNbIuo1kaAu84JLYJl9WEJqMM86FLnX3wrRao0GjIIkwfnxR3Cv/yZUp14P/ZCh0GRmQUpLj3bgHkiuroR/xzZAiR1UNifa7EAwANXjhuJxA4oCqZujAnpC0IU69FR/6FZ6g07CqYeGAuzMmj3Yd80VcH39ZfcObjRCVdsOL9zhuZzmOHTcShYLTFOmwfPDBmQqLji9QShKKHCqdfmRbtGHwvE2usjMjtAtwvU1DRhduRmaB2/pVADfFsXtQt1rL8O17qt29/Nu+hmCwQhdcde78uT6OlQ+fD+cX3zW5j7en36A3u/BpNINXZpzWxIObgsyQ8Gt4mwEJE3KzzpNNNFmhyiGgtt4zrht9AZgMWqjHdWVD92PPRf+vsPnWTJDXd5KY310m8cfui5NOg32Xb4Uey/pftd9MnGt/Rw1yx7v1pskXRUZM1B6wzVwb/i218/n370Lnh+/j36uNIS+n6K1a4uv6UeNgWAwwjBuQnTGOxERERElNwa3RNRrIr/c9uYtqx3RpKXB8/OP2HfZhQiUlUa3S460aMeaf99eBMpKoaoqNJnZkKtid9wqvlAwJnRiURdNWjoAQK6vh+IKhWTdnfHaE9EF2PxNIdIJ0wtw3twRmJatgW/LRiguZ1tPb9eOWcfj3kMug6yPfWu9OxwQ6Y0GGMYcBE12drfOE2GeORtQFOTV7oGiqnD7g/AFZDi9gXBw62lzbqPVEXrtdbIfaZ46qFt+hhroQbAmCKh56t9wfrK6zV3UgB++XzbDMHpMtxam04QXlQtWlMc+fviNCEkU4PDUoaYrwW1l6HtelBV6XRRnIySLpVPzeqltks0OAUCa6ouON4iHRk8gujAZAMg1VZAyMjt8njErFNwKDXXRbV6/DAGATiNC8Xn7TYAn2R0AgEDpfuy7+lLUvfpyr52r+d0Dglbbzp7xUfXvR1F+91+jn8uNDQBCf966wjhuAoa8sBJ5f72H1zoRERFRimBwS0S9RjsoD5Yj58L1xefw7ylJSA2qLMPz7bpQPc2Cw+bBbdW//oG9VyyFIAjQZGVBrq+LhrQtjhXuLBU70ZVoW3gCMn5/AbSD8qA4QyFZIkYliAeMSgAAvVbCGYcPhVUNLxpmMnfr2BqbHS6dGb5g7FutIzNutSNHI+/O+2Ce2rNFfDThoMomh74PTk8Qda7Q1+Uw66C43W2ulK4xmSCJAnSyHzrZD1EQerSqumg0QZOVjUDJ7jb38W3fBtXvh2HMQd07h04X6gAvL4v5eDD8BoMkCnB461HVheB2T5ULAoDBGaEASnY6E/Lns7+JzNR2qN4W4zx6qtETiM63VVUVwepqaDI6npksWayAJEJyNkS3Ob1B6LUSRFGA6vX2m0WqpPCbZYE9JfBt3YJgdew34OKh+WvWFzOhJZsdirMRajD0M1XuZsctEREREaUeBrdE1GskuwP64SPh27Kx1YrYfUWurYF/904ALRd7ktIcoRm0soxgZUV0gRfrr+Yhc+llMY+leEMLcXWq4zY9PTQzF6FAQTRboO1gBfjeEOmmU2J0lyruSCdw94JbW9CFotrdcNfWxXzc7Qt1hPZ0lm6EaA91l1mCoeC2wRNAjTP0dWVY9VDbGZUgGk2QJAE6OQCd7IcgAEIPAytdUTH8+/a2OePXu/FnAOh2cAsAmuxcBNoKbsOduKHgtq5LoxJ2V7qQm2aEXhvqBFacjRAtDIF6SkpLR+G/n8FPUxaiIY4zbhvcoVEJQOi6VX1eSJ1Y7E4QRfgMFmhcoeBWVVXsqnBGR2SoPm+/GY8hORwAAP++PaHPe/HPs274CBgmHAyg5z9HOiPSTSw3hL6PSkP3Om4DZaXYceIC7Dh5YVzrIyIiIqLew+CWiHqV6guHnQkKB8Q2frGVHGmAokBuaECwshLa8G3ppklTYDt6Qcyu2sjXIhq69rVIDgcG//0RmA/p+zm/+hGjUPzfV2BfeEKrx6IjHLoZPOTs/glnf/csXFu2xHw80nFr3LgeVf9+rFOLKbVHsqdBN3Q4tOGuRqcngFpnKKx0mHXQDRkK3ZBhMZ+rLShE1cgp8Gr0MKlBCOj+1910zCIgGECgdH/Mx3VFxTAfNgf6kaO7f46cHCgN9THnCDcPbtM8nQ9uZUXFvmo3CjObAnvj+IkwHDS+23VSiCBJ0GRlw2Izx63jNiAr8Abk6KgEuboaQFMHekf8Riu07kYAQEW9FzVOH0bn26HKMtRAAGIbo05SjSYtDQAQ2BsKbntzNI1ktkBXUBQ6Tw869zt9vnAoHXkDVA0GIegN0Q7vTossqtiJOe1ERERElBzi0wZFRBSDGgig5pllAJCwcEDU6ZB2+lnQDR/RYrtp8rTQ7acN9UAwACnccRuhKgoEseV7W7ZjF8E4aQqg6dpMQ0EQosFwXxMkqc3VwxWPG0APRiWYQ8f1N7piPh4dlbB9Mxo+eguOE0/p1nmi50tLQ/79/8DWH0uBFT+g0ROAM7wAWrpVj0E339Hmc00HT0blYisq1+yACeERET28xVlXWAwA8Jfsgi6/oPU5p0yDacq0Hp1DP2oM5MbGmPN7LUcdDdP0mah48D5Y3l2N2trOzSouq/MgICsoyGoKtrKvuKZHdVIT384dKKzdjXV+M4KyAo3U9ffI99e4sbfKhekjs6IBcGRUgtxQDwgCNJ3ouAWAz4/+A7bV+HEMgE17Q7fYj8m3RxcsFPrgVv++IKVnwHDQ+OibhL3ZQa4qCvwlu0Ln6aNRCUBTcGs/7gTYjzsBqhp7TE2bx+FoBSIiIqKUw+CWiHqPpulHTCLDgbTTz2q1zTx9JszTZ8K7ZTMARINV/7692H/N5bAvOhFpp53Z4jmG0WNhGD229wuOI8Xvh/fH76HJzIKuqLjFY+bZh0KbnROdDdlVmvCIBb8zdmAYGZWg8XsQRPxm/EZuGW/0BFAbnnGbZu54gaXctFDwuWPIFCyeNbfF6Izu0A8fAcvhR0LjSGv1mKqqcVn8x77weNgXHh/zMUEQIFltyFhyLl70jwVcnVsMq2lhsu4F9tS+yn/8HZN2lOKV8X9Agye0cF5XPfrOZqzdUok/zh+FGSNDnbVWY+jnqXHcBAxZ8QZURenUsSSHA/WVVVBVtUVwK+j0KPjnU/1ncTKrDXm3/w0NH7wHz/pvIFp678+36vXA++P30BYUdWp0Tk9JaemQ0jOgBlt2cXf1Z0yk1siYByIiIiJKfgxuiajXNP+lsi+6krpDaWyAoNNHZ9xGFoEJVla02jdWF26yU1wulN12A2zHLELmH5e2eMwwYhQMI0Z1+9i6SMets/2OW8nnQVAU4xJw1L++Etb9VQAKQ8FteMatAz5UPf4oTJOnwjR1eqvn+fftRcFLj2JUXS5qJkyDfdGsHteiKyhss1O18b23Uf/6K8i+8lrohw3v8blica//BqLFCsOo0cDgUlQ1dG5UQkll6PuVnxEKtgIV5ah5ZhksRxwJ87SZvVLrQCLZ7ND7tgIIvbnQ1eBWVVX8XFIHAPjXe1uwrTQ0zzTScQsAgkaDzkZ2GUEXiiu3wVM3E5v21sGs1yA/wwxBFKDNHdSl2lKBYexByLzgEuiLh/baOSI/y3T5BX3yd4J55myYZ86Ofu5a+xkUvx/WI47q0nEEQUDxi69DkKR4l0hEREREvSS1EggiSlnJtnK5f+8e7L3sQgQrK1D8v1dhPuRwAKGuUEFvQLCq9Yrk+y5fij2Xnt/XpfaIoAuvRB9jcbKe0oU7aIMud8zH3b4gREGA4HFBNJri0oHq/PxTiJ99ACDccev0QQBg8TvR8Pbr8G6NPW9X9Xqh+2k9sl2VMOp6P7TwbvoZgf37oMns3BzStigeNyoffQgN773d6rHKRx5A9b8fhSrLyFedCNRUQVY6vnW6rDY0L3dwRih4l6sq4frsEwRLS3tUK4VIdjs0cgBa2d+tObf7a9xo8AQwZ1wuCjLM+PCH0PclEtx6fv4Rrq/Wtrko3oEKd3+PM79/AbVbt2Hr/gaMGmyHKApQPB74tm9N2MKRvaHulRVoeOM12OYfG30zrjdEwtrIQmh9re6VFah5elm3nivqdAxuiYiIiFIIg1si6lXa/MLQ7aQ9vC093gSdDv5dOxAoK4UgCNFfZAVBgCYrO2bHreL1QhBT6xdeURfq9lP9rYPb/df/CXsu+r9uH1tnNcOr0SPQxh3bHr8Mo06C4nbHbUyCZLdDdDVCUBU4vUHUOP2wm3QQvKEwUmxjnq9oNEIjCtDLASx4/x/Yf/2f4lJP/RuvYs8lf4Ti9bbY7t28CdrB+dHV4LtL0OnR+MF7cH+7rsV2xe+HXFMNTXYOAmWlmPfSHZha8jXq3R0H9OV1HmglMTpeQg6PuojX92igk6w2iKIAU8CDBnfXg9vN4XEGs0dl4d7fTcXg9NCfaZspFNzWv/YKyu/+a+frCY/y2Ll1D/xBBWPyQ/NS/bt3Yt+VF6Pxow+6XGOy8vz4PRo/fL/Ls1+7K1Cyu0/Oo8oy6t94Fa4vPwcAyI2NnFdLRERENEAwuCWiXiUaDFDDoVoyiQRq9W+9Duenn7R4TJOZhWBlZatf/lWfN7rwTcrQaABRhOJvfRu93FAPqJ2bkxmLcXA+7jn8KpTPWhDzcZcvCLNBA/PsQ2E9cm63z9OcZLdDUBUYgr5ox63DooPiiQS3sTu7BaMJggDMHZOOIl0Aqq9zYwU6onjcCJTshn9PU4Aj19UiWF4K/agxPT6+IEnQZGYiWF7WYnuwKvTGgiYnF5qsbIiiALu3HtWdGJdQVudFjsMAUQx1QCvORgC9u5jTQCLa7BAFAaaAu1vBbWQO7egCBzJtBtx37jT87lfDMWlIaDGyYHUVpLS0TndNSo5QULt7R6hzd3Q4uI282ZCsY2y6Q3KkQfX7sPOU46AGuv7aJy1RRPXyJ9D44SoAgNJQD9FmS3BRRERERNQXOOOWiHpV1sVXJLqEmES9HoLJBNXtRs2zT8Fy2BHRxzRZ2VD9PiiNDdHVvIFQ0CH2wUI08SQIAgStDqq/dYihuFydXpk+lsjIAY8/9i3bHl8QRp0Gab8+vdvnOJBks0MAkCn6ozNuR+fboXhC4xpEUxsdt+Fwqsgqwa0EIMRpdIeuaAgAwL9rZ3ResPeX0LgGw8jRcTmHJjsXvh1bWyx4FiwvBxBaVE/U6SDY05DmqkN1ow8j2jmWqqoor/NgXFHTgmpKuONWYsdtXEhpaRDT0qGRg90albBxbz3sJh3ywovpZdkMOOuIYdHH5dqaLo0B0Iev8bLdpUDekGjHbeTNi0QuHBlvUpoj9IEiQ9Bq2923p4qW/xeIw/iXzhAEAZLdAbm+DmowCMXtavF3ExERERH1X+y4JaJepSsqhq6oONFlxBTputVkZbfY7jh5MfIf/CdEc1OQpapqqOM2BUMOTW5uzFBOcbshmru/8rpBJ2HS/g3Q/7Qu5uMuXxBmfXzfHxTtobAiU/ChssELtz+INIsOijsU3LYVyAp6PSAIUDxuKB5P3AL4yJ9t/+5d0W2+XzYDAPRxCm61OTlQ3e5owAog2oGryckFAEhZ2aGO28b2O27r3QF4AzJyHU1fv8yO27iyzZ0P8wNPYo+joMvBrS8gY3tpA8bk22POhFZlGXJdLaQuvOGizwiH9I31yHUYkRZeLE31hTpuU+4ugnZoHOl9di7JkdbjUShdO18ouJUbQ9erxI5bIiIiogGBwS0RDViiPhTCHhjcagflQVdU3OJWZNXnA1Q1JW8rLnjwn8i+4poW21RZhupxtzkTtjOMOglHb/sAGes+ivm4xyfDIsnY96fLUPfqy90+T3P6YSNgXbAQktWG0vAiW+kWPbSD8mA9egG0OYNiPk8QRaSdcTbMsw4BFDlu30dNdg4EvQH+3Tuj2xynnIZBf70nbm9YRMLZYEWzcQmSBM2gPGhyQ4/pB+XC4nehpqax3WOV1YVes1xH09dvGDsO9pNP7VIYSO2zmULzgxvaCW7rXH6c/eCn+HJL00KI20obEVTU6DiDA8n1dYCidKlT3pSeBqfODEUQWxxXCXfcptpdBO2RHI5El9BrJJsdcl0doMgwTDgYusLiRJdERERERH2AoxKIaMCyzp2P6iceaxXcqrKMQHkpRK0u+pig1SL/oX+lZMdtLNGZsD3ouDXqNPBp9ND6vK0eUxQVbn8Qdvjh+2Vz3LpPjQeNh/Gg8VCfXgd5ezUAIM2ig/GgUTAeNL7d56YtPj001xeA0MZIha4SRBG6ouIWHbei0QjjuAlxOT4AGCccHHrTwNrUYWc7egFsRzfNFjYPHoyApIWzrAJA27N1y8Nhd05aU1hnOngyTAdPjlu9A53idkH98H0MqSlHgzu3zf22ljZgb7Ubyz/ahhkjMyEIAjbvC/35HNNGcKv6/dANGwFtfkGn6zGb9Lj/0MsAABc0P24wCGi0/arjVlc8FAAg9KMwOkJyOKD6vBDNFuTdeleiyyEiIiKiPsLglogGLG1uqDvzwOA2WFmBvRf+HvYTf42Mc34PILRIlK6wqM9rjIfG1R9C9XpgO+a46DbRaMTg+x7uUcetXivCr9FD8LVefM4bCM29taqhjsOeBMSxWAxN8yvTLZ0PnkSjCXl33gcxjvMh085YAkEUoaoq5Lo6BPbvhX7YiLh19RpGj4Vh9Nh298k987c4d3c+pkntjzto6rjtf8FWslADAdQu+xcmmsagxDO1zf2qwgvJbS1twMY99Tio0IGNe+oAAKMGx/7zqc0dhPz7Hu5SPWZD0z/1xuQ7oh/bjjkOtmOOa7UIYyrTFhQCkiaub5wkC/2o0VC83tCia/3kDUQiIiIi6hhHJRDRgCXo9TCMnwjdAd1rmowMQBAQrCiPblO8Xvh374LcbM5oqmh46zXUvvy/FtsESYJ+2Aho8wZ3+7iCIEDW6iHG6Lh1+YIAAKvqBxC/4FZubMT+G67B2E0fR7elWXSoW/kSSm++Dorb1eZzy+/+K/Zffw0MYw6CbnB+XOoBQh2rxgkHQxAEuNd9hdK/XA3PhvVxO35EsLY2+nH18ifQ+EnTiApJr0O6zRANA9sSGS+R26zjtvzuv6L01hviXO3AFZmNbUWg3Rm31Y1N180rX+4GAGzeW4/CLDOsxvgtrGXWazCu/CfM2LcOwwe1DvZjzdJNZYPvfQjp4Tfc+hP7MYuQ++cb4N+xDZX/fBiB/fsSXRIRERER9QEGt0Q0YBnHT0TebXfDMOagFtsFrQ6SIw3BqqbZk/7du7D30vPR+P47fV1mjwl6PVS/v8U2xeNBoHQ/FG/r0LUrZJ0Bor/1MTzh4NakhOdomuIT3Ap6Pbw/fg9HbWl0W7pFD/+uHfBs+BaQ2r6RRG6oh3/3TgRrqqEc8Hr0lOL1Qq6rhW/LJgDxW5gsom7lSyg57yz49+2F4vWi/tWX4Fn/TdP5/X5Mqd4I885N7R6nvM4DnUZEmlkX3ebfvRPBqoq41juQCRoNBK0WJgTbD27DIfvQHCs+3ViOX/Y3oKzO06Ir9kDuDd+i+uknEayu6nQ9FoMW0/aux9x9a6HXNs3t9m7eiMaPP4rOuu0PBEGAfsjQVm/G9Se+bb+g8d232n2TioiIiIj6Dwa3REQxSOkZkGtrop9HV2A3pt4tqoJW1yq49fz8A/ZccC6cn33So2PXZAxGWXphq9utXb7QqARzOLiVLJYenSdC1OkgGIww+ZtCizSLLjSzV5Qg6HRtPlcwGKB6PSg590w4P1oVl3oAQHY6ses3J6H6mWXw/rIZmqzsLi0e1Rn64/xo9wAAO95JREFUkaMARUbDW69HO8Eji5YBgCAAh3+1AiO2fQlZafvW97I6D3LsxhZdlrLTCckcn+8PhQgGI0xqAA3u9jpufZBEAeccNRyyouL+134G0PZ8WwDw/vQD6leu6NIbLnqtiIzsNGRo5BbbGz98H5UP3NPqZwMlJ3/JbpTfd1e00z6e416IiIiIKHkxuCUiikGTnoFgTQ1URQGAaFAi6lMwuNW1Dm4VVyj4lHo4wuCnScfi1RlLWt1uHem4VYtHIPOCS6AbOrxH52lOstuh94bqFwUBNpMOitsN0Whs97bv5vN8BWP8ZrxKFgskRxq8m35GYE9J3LttAcAwdhx0RUPQ+NEq+HfvBABosnOijwtaHWSrA3ZPHepcsYM4VVVRXudtsTCZqqpQnE6IlvZn41LXiAYDDGoAbn8QQVmJuU91ow9pZj1mjsrCoDQjtpY2AGg/uJXr6wAAUhdCO0EQMHlcAawaNTQfNSz6M83QfxYn688UnxeuTz9GoCQ0VkOy8polIiIiGggY3BIRxSClp0PQaKIBZ7TjNgUXhRF0OkCRoQaD0W2q2w2g5yMMjDoJXr/cantkxq0+Lw+2+cdC2yxk7CnJZofWE5o17DDrIIkCFI8boqn9hdaaLxbWk0XZYtEVDUGwdD+gqqHu2DgTBAG2406A6vWg9oVnAaDVa6qkZ8LhrUd1Y+xb3+tcfvgCcouFyVSvF1BkBrdxZpxwMDx5QwGgzXEJ1Y0+ZNj0kEQBJ84oBAAYtBKG5LT9vZDr6wFR6vLM6Mj+zW+vV71eQJQATfzm6VLvkeyOpk80WggGLjBIRERENBAwuCUiiiHz/5ZiyP9ejXY1NXWnpd4vy/rhI2GaNhOq3BSwRgIcoYOwsyNFFb9gzoaVrWZuevyh4Naob3vmbHdJdjs07kZAVZFm0UFVVQTLSqHJym73ec27bMU4B/C6ouLox4ZRY+J67AjLYXMgmi0I7NsLoGXHLQBosnJgCnhQXVUX8/lldaE/w4OaddzKjaEuT9ESnxnEFJJ18RWoWngmgNjBraKoqHH6kGENdbvOnzQYJp0GYwsckMS2u8bl+npINhsEsWv/fIu8qRF5IwoAVL8PgkHf7xYn66+ad1lLViu/b0REREQDRPx/oyYi6gcESWrxeWTUgKBPvduKHSeeApx4SottcjjA6Wrn3oEyGypQsHcD/FXV0GRkRre7vaGQ2LZyOXb99DUK/rU8bnNubccej8axUyF8pyLNogcUBRl/uLDDMNY2dwH8O3fA+9MPcR2VADQFt9l/+gsMo8fG9dgRosEA67xjUL9yBYxTpkGTmdXicUPeIHgB1O7eB0wobPX88joPACDH0fQ6SVYbcv58AzTZua32p56xGkOdrA0xgts6tx+yokaDW6tRi0fPnwlTB290yA11EO1dn22qKxoC07SZQLOfa4rXl5KjXwYq0WCAYDBC9Xpgm39sosshIiIioj7C4JaIKAa5oR7udV9DVzwU+qHDYF94PGwLFoZWgeoHVE94VIKxZ8GtGA5AvY1ONO/ddYc7bjU+NxSXM64drqbJU2Ef5oG6YQ3SzDoIkgTrnKM6fJ6uqBiGsePg/emHuHdO64qGAACC5eVxPe6B0s86BxlnnxfzsbTRI/FdWjGEWnfMxyPBbfNRCaLRCPPMQ+Jf6ABX/84bKFjzDaA9JOYCZdUNoXEWkeAWAAoyO74WzbMO7da1ZD3iKFiPaHmNaPPyIFm5KF0qkewOiIPykHb6WYkuhYiIiIj6CINbIqIYglVVqHzoPqSdsQT6ocMAtO7CTRWuL7+A64tPkX72edGu2Iz/W4r0Jef1uIM4sriZt6GxxXZ3eMat1ueBoDdA0MT3r5tMqwEnzyjEoWNzoPj9ELTaDm8dVlUV9uNPhu2YRZBstrjWoyseguLnX+7xzOCOtPdncPDRv8LzaxVMl9JiPl5aG+64bTYqIVhdBclmh6DlnNN48m3aCMv3ayFOnhlzVEJkDnGmrWshbMaSc+NSHwBkX3pV3I5FfcO+6MS4/ywlIiIiouTGGbdERDFo0tMBAMGaagCAd+sWOL/4FEp4ZEIq8ZfsgnPN6tDCRmGCIEA0Grs8K/NAUnh2ps/parHd7QuNShD9Hojm+Hb1OT9bg92/OQnnZNVj4pB01Dz9JHadeQqCtbXtP+/jj7D7rF/Dt3VL3EN4QZJ6PbTtiCQKyHUYowHtgcpqPdBpRKSZddFt5XfdhpLzf9dXJQ4YgsEIURCgk/3tBrfNO257k3/3LlTcfzfcG77tk/NR77AcPgcN772N+jdeTXQpRERERNRHUia4vf322zF79myYTCY4HI6Y+5SUlGDhwoUwmUzIzs7G1VdfjWCzVdSJiDpLtNkBUYJcHQpuG997GxX33B6ddZtKBG0oqFMDTbV7vv8Onu+/6/GxNeZQcOtvFdyGfvaKHnfcF74S9DqoPi/khlAQHdhbAsgKpDb+bogQjaHuRvfXa6GqalxrSgZyXS2O2fw2bJvWQVFaf33ldR7kOozRzmQ1EIBv547omAeKH9FggCgCetkfe1RCY2ihuMwuBLf+vXuw/y9Xw/nFp12uR3G74FyzGv6SXU01PPMkGj98v8vHosSR6+vh37k9uqggEREREfV/KRPc+v1+LF68GBdccEHMx2VZxsKFC+H3+/HFF1/g6aefxvLly3HjjTf2caVE1B8IoggpPT3acat4Q0GLmIKLk0XGITQPnauXPY7Kxx7u8bE1WTn4On8qfJl5Lba7fUFIogB43D2eo3sgyeYAACjh4Na/pwTa/IIORyUI4bm2jR+81y9XZFdlGSO3fYVB1SXRjs7oY6qKsjoPcprNt/Xv3gkEA9APH9HXpfZ7gsEQ7biNtThZdzpug1WV8P78I5RmnfOdFekGV8KLEqqqivpXX4brq7VdPhYlTu2LzwMAFAa3RERERANGygzKuuWWWwAAy5cvj/n4+++/j40bN+KDDz5ATk4ODj74YNx222245pprcPPNN0On08V8HhFRWzQZmQhWVgAAVJ8PEKWUnAUaqVn1NYV5itsV6iruIU1OLt4dOR+HFY1qsd3tC8Ko02DQzbf3+BwHkuyhuuX6esguJ+SaahjHT+zweZGF1Por0WSCRhKgl33YX+NGlr1pfmqtyw9/UEFus/m2vq2/AAD0I0e1Ohb1jBgelaBtY1RCVaMPGlGAzdT5nydyfV3o2PauX7dieKSJ4g53xgcDgKLEddFA6n1ybQ0AQJWVBFdCRERERH0lZTpuO7J27VqMHz8eOTk50W3z589HQ0MDfv755wRWRkSpyjByNHTFQ6GqKhSvJ2WDP0HXelSC4nZDNJp6fGyTPjQr1uNvOZbG7Zdh1mugKxoS91vxo8FtQz0Ce/cCALT5hR0+TzSk5vevswSDERqNBEPQh3017haPlYfn3g5qFtx6t24BABiGj+y7IgcI/ajRcJyyGIrZHnvGbYMPGVZDlzq/lYZQl6Vkd3S5HjG8iKDqDv25ULyhN3EEPYPbVGI/8RQAgPWouQmuhIiIiIj6Ssp03HakrKysRWgLIPp5WVlZm8/z+XzwNetCa2jg7WdEFJJx3h+jH6s+X8qGHLqiYthPXgxt3mAAodukFY87Gub0hEFQcM63T0NrngWMvzi63e0NwqQFAvv3QbTbIcVxgTLBYISg1UKurw/NtwWgKyjo+HkpGrx3liAI0JjN0HtCHbfNldWFgtvmoxKClRXQZGVDcqT1aZ0DgfGg8TAeNB64f00bM259LUL0zoh03HYnuBUMRkAQIEdGJXg94e2pN/plIDNPnYGhr76b6DKIiIiIqA8lNLj985//jLvvvrvdfTZt2oTRo0f3Wg133nlndAwDEVFbNBmZ0TmRqUZfPBT64qHRz1WvJ3SbdBy+HqNRj4K6vRDK9rbY7vYHMUzjwZ4Lz4P9xF8j45zf9/hcEYIgYNDt90JyOKDJyIRhzEEdLkwGhL6HAKAtKIpbLclGb7PA0OjFLwd23NaFZjQ3D27zbrsbssvZp/UNNFajtlXHrayoqHX6MK7Q0aVjyeHZtlI3RiUIogjH4t9AOzgfAKCE37AWU/TNKCIiIiKigSKhwe2VV16Jc845p919hg4d2u7jEbm5ufj6669bbCsvL48+1pZrr70WV1xxRfTzhoYGFHSic4uI+j/fzh1oeOdNWH81DznXXJ/ocuJG9fuhzS+EJju7x8cyGrTwSzpo3C2DQrcvCIs2ND4hMl8zngzN5rJGOok7IkgStEXF0OXlx72eZGGfdyx2rd6J/TWeFttLw6MSch0tg7p4dkJTE9+2X1D52MMYYz0YH2qLWzxW4/RBRdcWJgMAy5yjoCsohNjN71n6GUuiH4t6Pay/mgc9x2QQERERESW1hAa3WVlZyMrKisuxZs2ahdtvvx0VFRXIDocRq1atgs1mw9ixY9t8nl6vhz4FV4knot4n19Wi8f23oR86DIZRvdf539v8u3eh4qH7YDvmONjmzodkd6DgH4/H5dhGnQS/RgejtykoVBQVHr8MK0KdhvGYpXsgubEBck01gjU10A7KgzZ3UKeeV/DgP+NeSzJJO/U3qHB+g/2lDVBVNTpDdX+NG3qtBIc5NO/YveFbBKsqYTnk8JSd3ZzM1GAQ/u1bkXbQcLiUIIKyAo0UWlagujHU7dpecNuw6l14vl2H7D/9Jfo9jI5fiANNVjayLr6i4x2JiIiIiCihUmbGbUlJCWpqalBSUgJZlrFhwwYAwPDhw2GxWDBv3jyMHTsWv/3tb3HPPfegrKwM119/PZYuXcpgloi6RZOeAQAI1lSj5vlnoCsohOWwOYktqhtURYF/+1bINdVxP7ZRr4FP0gO+puDW45cBABY1FNz2xmzZ6n8/Buea1QAA08xDkPvnG+J+jlSVl27E97tq0OAOwG7WISAr2LinDqPybNEQsHHVu3B98Skssw9NcLX9k2AIdTabxVDXeaMngDRL6N8i1Q3h4NbW9r9Nqh55AAAgV1VCkxV6M7p5EN8dlY88CH/JLgy+++/dPgYREREREfUtMdEFdNaNN96ISZMm4aabboLT6cSkSZMwadIkrFu3DgAgSRLefPNNSJKEWbNm4ayzzsKSJUtw6623JrhyIkpVUji4laurUPfi83B98VmCK+oeQR/qslTDcy0933+H2heeRbCmpsfHjnTcCs06bt3+UFhlinTc9sKoBLHZnE9dQWHcj5+qal98Hoe+ch9ERca+8JzbjXvq4A3ImDwsI7qfb9sv0Oblp+zc5mQnGkJvVpjVpuA2oqnjNvZ8WTUYjH4crK6Kflxyzm9Qfvdfu12TXFsD3/ZtAADPTz+g9Oa/wLvxp24fj4iIiIiIel/KBLfLly+Hqqqt/pszZ050n6KiIrz99ttwu92orKzEvffeC40mZZqKiSjJiBYLBK0WgfIyAE1ddKlG1IaDW78fAOD65ivUvvAs1IC/x8fWayR8WnQIfp62KLrN7QsHt0ro+L0xKkGyOaIfa/M5lzwiWF0FS+Ve6IM+lIaD2/XbQp3WU4eHFmeT6+sQLC+DvtmcYIovMfyzwhjuOm/0NIWx1Y2hheLaGpXg31MCAHCcchoMo0OjntRAAHJ9HSB2/59toskEBANQ/H4EKyvg2bAespOL0xERERERJTOmmkREbRAEAVJ6BgL794U+T9GxK5G6lXBQG9i7B4JOB01mz2eMi6KA3XljYStIi25z+0KjEjzT56D4ojMhSFKPz3MgqXnHLYPbKNFkhkYSYAh6ox2367dXw2LQYmSeDQDg27YVALgwVS8Swh23BiUASECDp+lNkqqG9mfcBkr3AaII/fAR0W1yYwMAQLI7ul2TaA51VysuF1RvKDwWU/RnGhERERHRQJEyHbdERIlgm38szDNmA+idztG+IEQ6bn3h4HbfHmjz8uMWqJr0muh4BKCp49ao10LU6yH0wp0Pkq0puNUOZnAbIRpN0EgiDLIP+2s8aPAEsGVfPSYPTYckhuaj+nZuBwDohw1PZKn9mqDXhxb/OvxoAECDu+WoBL1WgsUQ+7qwzD4Mxc+/AlVRUf/GqwAAub4eQMs3LLoqMhZDcbughMempOpdBEREREREAwWDWyKidjhOPhW2BQsBpG53mqDXI+vSq2CbfwwUjwfByoq4jheY88sHOPX56xCsrQXQFNzaq/bA9c2XcRnJcKDmAZbI8ClKNJshCkCGRsX+Gjc27KiGCmBKs/m22tw8mGbOhnZwfuIK7ecEQYD1V/NgPuggAC1n3FY1eJFh1be70JhoMKBx1buo+c8yqLIcGpOAlm9YdJVotgAId9z6vNHzEBERERFR8uKoBCKiDggGA8yHzYGueGiiS+kWQRRhPXIuAMC3PXSbfDwX9NJoJAhyEIrHBaSlRYNb2zerUf7dpyh69iVI4a7feNGPHI0hL73ZK928qSzSVZlnVPFNjRvrwvNtpwxvCm4thx4Oy6GHJ6S+gSbSVXvg4mRF2ZaY+6uyjPrXV8I4YSJ0RcXwbFiPYHkZlIZQx63Yg45b0/SZ0OTmQjtoEFxrQ8GtoEvNN6OIiIiIiAYK/sZLRNQO52drULvieWRfciX0w0Z0/IQkpqoqBIMR1gULYThofPyOazJDVQHF6QLQ1HGrDYRuxxaNxridK6I35ub2B4bRY5B18RXQlehQu9OHtVsqMTjdhEFpqTnmI5XtufR8KAqAtJOioxL8QQUNnkDb82337kHN00/AfvJi6AqLQs8p2QXj5GnIu/sBaPPyul2PLr8gOg/aNHU6JJsdksPR7eMREREREVHv46gEIqJ2qMEgArt3IVhZkehSeqTkD0tQev2foBucj6zzL4Zx3IT4HdxohqKqUFyhFeoji5NpAl4IegND1j6kHZQH66/mIb0oNAahxunD5GZjElRVRenNf0HdKy8mqsQBQxAlSP5QZ2tDuOO2prH9hcl8O7YBAPRDR0BXVAwA8JfshmSxwDBqNCSrrUc1qYoCNRiE8aDxcJz065Sd201ERERENFAwuCUiaocmPR0AUH7XbfBu3ZLganpGCa8kH2+COdRxG2xoANDUcasJ+Hql25Y6Nji96XWf2mxMguJywbNhPQL79iairAFFNBgAnw8mnSY6KqG6o+B2ezi4HTYc2vxCQBDgD79xFKyqhKqq3a7Hu2Uzdp6yEPVvvdbtYxARERERUd9icEtE1A4pvVno5XQmsJKeEXQ6qAE/Sm/+CyoffSiuxxYtoXmd/oZGAE3BrejzQGBw26cCFeXYedqJyPt4JQBAEgUcPCQ9+nikc1yTlZ2Q+gYSwWCE4vHAatRGRyVUN4bePMlsI7j1b98K0WSGJncQRIMBlsOPhH7YCFQ98U+U/N85QA+CW9FgAFQVisuFivvvxp6lv+/2sYiIiIiIqG8wuCUiakek4xYARH3qLuQj6PRQPR54fvwecm1NXI8dyB+KJ6b+DsFJMwE0Bbe6jEzoBufH9VzUPtFggOrzwiqGgsLRg+2wGLTRxyPBrZSZlZD6BpLI98JmlLC70onLn/wayz4IddRm2gyt9ldlGb4d26EbOhyCIAAAsi//ExwnL4ZcXwfJaoUgdv+fbaI5tHCd4nYjWFMNOdwhT0REREREyYuLkxERtUNoNgNS0LcOW1KFoNNFQztteIGieCkuysbLtjxsqpWRmw+4/TIkUcDgm26PBlDUN0RTKJzT+b04b+4IHFTgaPF4sKoSAKBlx22vi3SbHzbcgWpnACWVLgQVFYPTTRiSa221v+L1wDzrEOiGDmv9WEM9RLu9R/VEg1uXC6rXG+rAJSIiIiKipMbgloioHYIgQDMoD8HS/Sk9r1XQ6qIfa+PcBTt5aDrs3nr89P02HDl+ENy+IIw6DUPbBBA0Ggg6PRS3G2ccPrTV4xyV0HfSTj8LjhNOwRn5BThz3kEd7i+ZLci+7OoW23zbt6HmmScR2L8Phh4uKCgYjIAoQnG7oPh8Kf1GFBERERHRQMFRCUREHTBNmQ4AEFK4Qy3zwothOeIoAICuoDCux86x6XHlV4/A+tYLUFUVbl8QVi1Q8/wzcK/7Oq7noo6JJhMUlyvmY+YZs5C+5DyOSugD2uwc6IqKIUhSt48haDTwfP8dAECyO3pUjyAIEI2mcMetB0IKj34hIiIiIhoo2HFLRNQB05RpkGw2iGZLokvpNl1ePhCejxnvUQmCJEFrMkFxObGv2g23Lwi7EEDdi8/DumAhTFOnx/V81D7RZILiiR3cGkaPhWH02D6uaGCSXU7INTXQZGV3OJZAVVVUPvA3CDo9spZeGt2uzRsc/Viy9WxUAgDk3XU/RLMZey+7EJoUfiOKiIiIiGigYHBLRNQB06QpME2akugyekSur4Np6gwYJ06G1AsBtDHNDmOdF+u2V8PtkzFYIwMIhYjUt3Kuub7FaIzmVFXlCIs+4vxwFaqX/Qt5d94Hw5jYoxL8+/bC+fGHcK5ZjWB5GQzjJ7Z4XNBqoS0sgurxIP2c3/e4pki3fXt/RoiIiIiIKHkwuCUiGgBq/vMUGj94D0XPvtQrx7dmOGCsKsW6bVVw+4KwaAMAANHA4Lav6YqGxNyuyjJ2nXEKLEf+ClnnX9zHVQ08kcXJFK835uOB/fuw9+L/AxQFUnoG7CecAtuxi1rtpysshuuzTwBV7XFNgYpyKI0NMB40vsfHIiIiIiKi3sfglohoIAh3Wap+f68cXmezwiHuwfc7a+ENyLCq4eCWHbd9Tm6oh1xXB21BYYvu2mB1FVSfF4JGm8DqBg4xPENW8bhjPh4o3Q8oChynnYm0U89ocxauaAxdQ75fNsM44eAe1VT978fgXv81ip56HqLJxK5bIiIiIqIkx8XJiIgGAN+2rQCA+jdW9srxRbMFNiEAty8U2JoRDG1ncNvnap5+Ensv+SPUAwJDuaoSAKDJzk5EWQOOYAh13KptdNwaJ05C4RP/gf34k9pdwMx+4ikwTDgY2oKiHtckms2AomD32aejetnjPT4eERERERH1Lga3REQDgOLxAAA0Wb0T2mVf+WfoH3sh2tkr2WwwzzoU2txBvXI+apsQDssVV8sFygKVFQAATWZWn9c0EIkdjEoQNBpoMrM6nDmtG5yPvFvvgiYtrec1mcxN5w8Hy0RERERElLw4KoGIaADIufpa1L36MqxHHd0rxxf1eowu1MGs18DlC0IZMgI5vz+2V85F7YvcWq+42+i47aXwnloSDAYAbXfc+veUQHG7oB82AoKmb/45JpqbgtvIKAciIiIiIkpeDG6JiAYA/bARyLnyz712/EDpfvi2b8PUQXp8sisIk55/vSRKJJw7cLZqU8ctg9u+oB82AkNefqvNMQh1K1fA+dEqFP/3lb4Lbo1No0sEHYNbIiIiIqJkx1EJRETUY+51X6Pi3jsw3RLqLsza9DXK/3YHgjU1Ca5s4IncDn9gx23aaWch7457IdntiShrwBFEsd3ZtXJ9HQSttk9HFjTvuBWMhj47LxERERERdQ+DWyIi6rFIIDR1kAGLphVguL8Srs/XAKqS4MoGnmhwG55rHKFJS4Nh7DgIIv/q7wuqLMP15efwbtkU83Glvh6izQ4hPBe6L1jnHYOc624GAIh6BrdERERERMmOv70REVGPiRYrAEAf9OKyRWNhVPyh7UYugNTXzDNnY8jLb8FyyGEttvu2b4Xc2JigqgYgRUH5Xbeh/s3XYj4sN9RDcvR8wbGuEAQBpklTULjseZhnHdqn5yYiIiIioq5jcEtERD0WnavqdIb+P3ybPleu73uCJLW6RV92ObHvyotRvezxBFU18AhaLaDRtrk4mVxfD8lq69OaZKcTzs/WQK6t4ZsqREREREQpgKvH9LFgMIidO3eivr4eitL/byHW6XQoLCxEenp6okshol4kWSwAAMUVDm49HghGE2/LTwDF64Xnu3XQZOdCP2w4AECuqgIAaLKyElnagCPq9a1GVgCAGvBDtFigyczs03rk2hpUPvg3GMZNQO5fbm6xWBkRERERESUfBrd9aN26dXj/vbfhdTdCgAKpnwcaqqpCVlRA1KKwaBhO/81vYAmHO0TUv4gWK7R5gyGYQkGQ4nGzoy9BFLcL5Xf/FbaFJ0SD22BlBQBAk5WdyNIGHMFohOpr3XEraHUoevLZPq8n0hnv/ekHBPbvg37YiD6vgYiIiIiIOo/BbR/5+eef8fqrKzBhTBFmTpuLrMz0Pl2QJFH8fj+27yjBex99gaeffgrnn38hpHZW2Sai1KTJyETBo09GP7cevQCK25XAigauSBdlZFwF0Cy4zWTHbV8SDUYobYxKSITIwnUAIHBxMiIiIiKipMfgto989dWXKB6cgUXHHDUgAtsInU6HMaOHw2Ix4+kX3sKuXbswbNiwRJdFRL3MNnd+oksYsASDARDFFsF5sKoSADtu+5o2vwCqz9dqu3/vHri//QbmaTOhHZTXZ/UIen3Txzpdn52XiIiIiIi6h8FtHwgEAijZtR0LjpwyoELb5vIH58JmMWD79u0Mbon6qfrXVwJaDezHLEp0KQOaIAgQjaYWwa3idgOiyI7bPpb75xtibvdu3oiaZY9DOyivb4PbZv8G4SgTIiIiIqLk17+HrCYJr9cLRVFgsZg73rmfEgQBVrMRnhiLtBBR/1D/zhtofPdtqKqKkgvORfWT/0p0SQOWaDK1GJWQ+celGPLi6xANvD0+GSgN9QAAyZ6WsBo4KoGIiIiIKPkxuO0DqqoCQMK7bV9+9V2Mn3EMbIMmYPIhi/DOqk86fM5jTzyHCTOOhT1vIsZNX4BnX3i11T4PPfY0xk1fAHveRAwbNwdXXXcnvN7Wt4Ym+usnot4lmsyQXU6oPh+CpfshOxsTXdKApSsqhiYjs8U2QcObbPqa66u1qHl2OdRgsMV2uT4S3Nr7vCbrr+ZBtFghaLV9fm4iIiIiIuoa/haXZPx+P3S9MHdu7Vff4rd/uBK33XAFjp0/B/976U0sPusifLX6ZRw0dmTM5/xr2X9xw63347EHbsOUyeOxbv0PuODyG+Bw2HDcgqMAAC+89Aauv/U+PP7w7Zg5fRK2btuFP1x0LQQB+Nvt18b96yCi5CVZrQjs3wcl3FkfWSSL+l7u9bdGP/bv2wv3N1/BPPtQaLNzEljVwONe9zUaV70D+4m/hmSxRLfL9XUAAMnu6POasi6+AlkX9/lpiYiIiIioGxjcJtjRi36LsWNGQCNp8N8Vr2Pc2JF4//Vn4n6ef/zrP5j3q0Nx5SXnAQBu/sul+PDjL/DoE8/hkftvifmc5//3Gn5/zmlYfPKxAIChxQVY992PuO/BJ6LB7dqvv8OsGZNx+q9DMy2LC/Nx6skL8c36H+L+NRBRchNNZqgeN5TGhtDnnKGZFDzrv0HN8n9DVzyEwW0fi4ymUD1uoEVwWw9Bb+DoCiIiIiIiahdHJSSBZ194FTqdFqvfeR4P33dzzH3+u+INpBdMbve/z9aua/McX32zAUcdMbvFtqOPOgRffbOhzef4/H4Ymq1ADQBGowHffPsjAoEAAGDW9En4bsPP0aB2x649eHfVGiw4+vBOfOVE1J+IFisAIFhdFfrcxI7bRHF9/SWqn1kGNRCAd8smQBCgHxH77grqPUL4zQvF622xXTdkCExTpyeiJCIiIiIiSiHsuE0Cw4cW485brm53n+MWHIlpUya0u8/gQW13UpVVVCEnO6PFtuzsTJRXVLX5nKOPOhRPPfsSjl/4K0yaeBC+3fATnvrPSwgEAqiqrsWg3Gyc/utFqKquxZHHnglVVREMBvGH352Oa644v91aiaj/MYweA9Xviy6KJTC4TRj3t9+g8d234DjhZPh+2QxtQSEks6XjJ1JcRTtufS2D24wl5yWiHCIiIiIiSjEMbpPA5IkHdbiP1WqB1dq3v3Rfd9WFKC+vwmHzToeqqsjJzsBZp5+I+x56AqIYatb+5LOvcM/fH8dDf7sR06dOwPYdJbjy2jtwx98exXVXX9in9RJRYlmPOhrWo46GXF+HnD/fCF3xkESXNGBFup39e/cgWFkB69z5Ca5oYBIMsTtuiYiIiIiIOoPBbRIwmTqeA/nfFW9g6RU3tbvP6y8+jkNnTY35WG52Jsorqltsq6ioQk52Zsz9gdBYhMf/cQce+fstKK+oxqDcLDzx9IuwWszIykwHANxyx0M449Tjce6SxQCAcWNHweX24MLLb8Sfrzw/GvAS0cAh2R0wz5zd8Y7Ua0STGQDg+W49AEA/akwiyxmwdIPzYT70CIjNup0VjweVjzwA07QZsB5xVAKrIyIiIiKiZMfgNkX0dFTCjGkHY/WatbjkgrOj2z78+AvMmHZwh+fWarXIH5wLAFjxyls4dv6caCDr9nhahbOSFPpcVdUOj01E/Yd3y2bUvfQCbMcugnH8RAga/hWTKKI5FNwKOh3Mh82B4aBxCa5oYDJOnATjxEkttsm1NXB99gk0WdnAEQkqjIiIiIiIUgJ/q04RPR2VcNEff4u5i5bg7/9YhmPmzcGKV97C+g0/49G/3xrd5/pb78P+0gose+xuAMAv23Zi3bc/YtqUCaira8CDjy7Hz5u24olH74o+Z+H8I/Hgo8tx8PgxmDZ1Irbv2I2b73gIC+cfCUmSuv8FE1HKUdwuuL/5Ev69JQiW7sfgex+CfjgXxEoE0RgKbnWFRUg79YwEV0PNyQ31AADJZk9wJURERERElOwY3A4Qs2ZMxjOP34ub7ngAN/717xg+tBgrnv0HDhrbFKqUlVdiz9790c9lWcEDjzyFX7bthFajwRGHzcDH7/4XxYX50X2uveoCCIKAm+54EPtLy5GVkY5jFxyJW6+/rC+/PCJKApHb84MVFQAAwcjFyRJFmzcY5sPmQHKkJbqUAS2wfx+qn1kG65yjYJ55CABAbmgAAEgORwIrIyIiIiKiVMDgNsFWvfGfPjvXKScuwCknLmjz8SceuavF52NGDcPXn6xs95gajQbXX3MRrr/morjUSESpS4zcFSAHQ58zuE0Yw8hREE48BRX33430357LmcMJovh8cH/5OfRDhzUFt/V1ANhxS0REREREHUuZlaNuv/12zJ49GyaTCY42ulQEQWj13wsvvNC3hRIRDVBSuOM2QjQxuE0k76aNCOzbC0GnS3QpA5ZoMAAAFK8nui0a3LLjloiIiIiIOpAyHbd+vx+LFy/GrFmz8OSTT7a531NPPYUFC5q6StsKeYmIKL5Ec7M53KIIQa9PXDEDnNxQj+onHgMA6EeOTnA1A5dgMAIAVI83us0weizsJy8OLU5GRERERETUjpQJbm+55RYAwPLly9vdz+FwIDc3tw8q6jxBECAAUFU10aUklKIoEAQh0WUQUS8RtFqknXUOap9dDtFg5PWeSELTDTWSpfsLW1LPNHXcNgW3xnETYBw3IVElERERERFRCkmZUQmdtXTpUmRmZmL69OlYtmxZUoSlRqMRoqRBXV1DoktJGFVVUd/ohtls7nhnIkpZab8+HYVP/ReD730o0aUMaJExFeZZhya4koEt0nWuNhuVQERERERE1Fkp03HbGbfeeiuOOuoomEwmvP/++7jwwgvhdDpxySWXtPkcn88Hn88X/byhIf7hqkajwdDhI/HTxl8wZdI4SJIU93Mku207dsPlCWDEiBGJLoWIepkmLQ1IS0t0GQOaIEkY8vJbiS5jwBNEEWlnnA1tfn50W+ltN0DQaJF77Y0JrIyIiIiIiFJBQoPbP//5z7j77rvb3WfTpk0YPbpz8/luuOGG6MeTJk2Cy+XC3/72t3aD2zvvvDM6hqE3zZ59CJ59ZgteeOlNTJ86ETlZmZCkftfw3IKqqvB4fdi2fRc++3IDioeNQkFBQaLLIqJeVH7fXXB9+jEKHlsG7aC8RJczoAkD8E3CZJR26m9afO7fuYPzbYmIiIiIqFMENYGzBCorK1FdXd3uPkOHDoWu2YrYy5cvx2WXXYa6uroOj//WW2/huOOOg9frhb6NRXJiddwWFBSgvr4eNputc19IJ23ZsgXvvfcOqipKAVUGEj/FoXcJof/R6owYPXY8TjjhhBbfSyLqf8r+eiPc676G8eDJGHTzHYkuhyipqKqKnb9eBNPkqcj9y82JLoeIiIiIiBKgoaEBdru9U9ljQjtus7KykJWV1WvH37BhA9LS0toMbQFAr9e3+3g8jRo1CiNHjkRlZSXq6+uhKEqfnDeRdDod8vLy+uw1JqLEEk3hOdbs9iQCAJTddSuUxkbk3f43KC4XIAch2e2JLouIiIiIiFJAysy4LSkpQU1NDUpKSiDLMjZs2AAAGD58OCwWC9544w2Ul5dj5syZMBgMWLVqFe644w5cddVViS38AIIgIDs7G9nZvE2SiPohKfzXitLfbykg6hzF6YRv6y8I7N8HNXyrjWhjcEtERERERB1LmeD2xhtvxNNPPx39fNKkSQCA1atXY86cOdBqtXjkkUdw+eWXQ1VVDB8+HPfffz/+8Ic/JKpkIqIBRxCF0Adq/7+jgKgzHKechrLbbkDZ7Tcj/Xe/BwBIDkdiiyIiIiIiopSQ0Bm3yagrcyaIiKilykceROOqd2AYPxF5t7W/+CTRQFH3+iuoWfY49MNHwn7yYuiLh0KbNzjRZRERERERUQJ0JXsU+6gmIiIaAEyTpwAADKPGJLgSouRhX3QSrHPnw7ftFwTLShnaEhERERFRp6TMqAQiIkp+5lmHYuir7ya6DKKkIggCMv94EaT0DNiOOS7R5RARERERUYpgcEtERETUywStFulnLEl0GURERERElEI4KoGIiIiIiIiIiIgoyTC4JSIiIiIiIiIiIkoyDG6JiIiIiIiIiIiIkgyDWyIiIiIiIiIiIqIkw+CWiIiIiIiIiIiIKMkwuCUiIiIiIiIiIiJKMgxuiYiIiIiIiIiIiJIMg1siIiIiIiIiIiKiJMPgloiIiIiIiIiIiCjJMLglIiIiIiIiIiIiSjIMbomIiIiIiIiIiIiSDINbIiIiIiIiIiIioiTD4JaIiIiIiIiIiIgoyTC4JSIiIiIiIiIiIkoyDG6JiIiIiIiIiIiIkgyDWyIiIiIiIiIiIqIko0l0AclGVVUAQENDQ4IrISIiIiIiIiIiov4kkjlGMsj2MLg9QGNjIwCgoKAgwZUQERERERERERFRf9TY2Ai73d7uPoLamXh3AFEUBfv374fVaoUgCIkuhwaghoYGFBQUYM+ePbDZbIkuhyhp8Nog4nVA1B5eH0Sx8dog6hxeK9RXVFVFY2Mj8vLyIIrtT7Flx+0BRFFEfn5+ossggs1m418WRDHw2iDidUDUHl4fRLHx2iDqHF4r1Bc66rSN4OJkREREREREREREREmGwS0RERERERERERFRkmFwS5Rk9Ho9brrpJuj1+kSXQpRUeG0Q8Togag+vD6LYeG0QdQ6vFUpGXJyMiIiIiIiIiIiIKMmw45aIiIiIiIiIiIgoyTC4JSIiIiIiIiIiIkoyDG6JiIiIiIiIiIiIkgyDW6JOuPPOOzFt2jRYrVZkZ2fjxBNPxJYtW1rs4/V6sXTpUmRkZMBiseCUU05BeXl5i30uueQSTJkyBXq9HgcffHDMc6mqinvvvRcjR46EXq/H4MGDcfvtt7db388//4xTTjkFxcXFEAQBDzzwQKt91qxZg0WLFiEvLw+CIODVV1/tyktA1Ka+uj5uvvlmCILQ6j+z2dxhjY888giKi4thMBgwY8YMfP311y0ef/zxxzFnzhzYbDYIgoC6urouvw40cPWHa+CPf/wjhg0bBqPRiKysLJxwwgnYvHlz118MogP0h+tjzpw5rY57/vnnd/3FIDpAql8fu3btinlcQRCwYsWK7r0oRDGk+rUCANu3b8dJJ52ErKws2Gw2nHrqqa3qI4qFwS1RJ3zyySdYunQpvvzyS6xatQqBQADz5s2Dy+WK7nP55ZfjjTfewIoVK/DJJ59g//79OPnkk1sd69xzz8Vpp53W5rkuvfRSPPHEE7j33nuxefNmvP7665g+fXq79bndbgwdOhR33XUXcnNzY+7jcrkwceJEPPLII538qok6p6+uj6uuugqlpaUt/hs7diwWL17cbn3/+9//cMUVV+Cmm27Ct99+i4kTJ2L+/PmoqKiI7uN2u7FgwQJcd9113XwVaCDrD9fAlClT8NRTT2HTpk147733oKoq5s2bB1mWu/mqEIX0h+sDAP7whz+0OPY999zTjVeDqKVUvz4KCgpaHfeWW26BxWLBMccc04NXhqilVL9WXC4X5s2bB0EQ8NFHH+Hzzz+H3+/HokWLoChKD14ZGhBUIuqyiooKFYD6ySefqKqqqnV1dapWq1VXrFgR3WfTpk0qAHXt2rWtnn/TTTepEydObLV948aNqkajUTdv3tzt2oqKitS///3v7e4DQF25cmW3z0HUnt66Pg60YcMGFYC6Zs2advebPn26unTp0ujnsiyreXl56p133tlq39WrV6sA1Nra2g7PT9SWVL4GIr7//nsVgLpt27YO6yDqilS8Po444gj10ksv7fCcRD2VitfHgQ4++GD13HPP7bAGop5ItWvlvffeU0VRVOvr66P71NXVqYIgqKtWreqwDhrY2HFL1A319fUAgPT0dADA+vXrEQgEMHfu3Og+o0ePRmFhIdauXdvp477xxhsYOnQo3nzzTQwZMgTFxcX4/e9/j5qamvh+AUS9qLeujwM98cQTGDlyJA477LA29/H7/Vi/fn2Lc4uiiLlz5/bo3ETtSfVrwOVy4amnnsKQIUNQUFDQ7fqIYknV6+O5555DZmYmxo0bh2uvvRZut7vbtRG1JVWvj4j169djw4YNOO+887pdG1FnpNq14vP5IAgC9Hp9dB+DwQBRFPHZZ591uz4aGBjcEnWRoii47LLLcMghh2DcuHEAgLKyMuh0Ojgcjhb75uTkoKysrNPH3rFjB3bv3o0VK1bgmWeewfLly7F+/Xr8+te/jueXQNRrevP6aM7r9eK5557r8BeDqqoqyLKMnJycuJ2bqD2pfA08+uijsFgssFgseOedd7Bq1SrodLpu1UcUS6peH2eccQaeffZZrF69Gtdeey3+85//4KyzzupWbURtSdXro7knn3wSY8aMwezZs7tVG1FnpOK1MnPmTJjNZlxzzTVwu91wuVy46qqrIMsySktLu1UfDRwMbom6aOnSpfjpp5/wwgsvxP3YiqLA5/PhmWeewWGHHYY5c+bgySefxOrVq7FlyxaUlJREf6m2WCy444474l4DUU/05vXR3MqVK9HY2Iizzz47uu3TTz9tcX0899xzvVoDUSypfA2ceeaZ+O677/DJJ59g5MiROPXUU+H1euNdOg1gqXp9/N///R/mz5+P8ePH48wzz8QzzzyDlStXYvv27b1RPg1QqXp9RHg8Hjz//PPstqVel4rXSlZWFlasWIE33ngDFosFdrsddXV1mDx5MkSRsRy1T5PoAohSyUUXXYQ333wTa9asQX5+fnR7bm4u/H4/6urqWrzLV15e3uZiYbEMGjQIGo0GI0eOjG4bM2YMAKCkpARHHnkkNmzYEH0scmsIUTLo7eujuSeeeALHHXdci3e2p06d2uL6yMnJgV6vhyRJrVZs7cm5idqS6teA3W6H3W7HiBEjMHPmTKSlpWHlypX4zW9+060aiZpL9eujuRkzZgAAtm3bhmHDhnWrRqLm+sP18dJLL8HtdmPJkiXdqouoM1L5Wpk3bx62b9+OqqoqaDQaOBwO5ObmYujQod2qjwYORvtEnaCqKi666CKsXLkSH330EYYMGdLi8SlTpkCr1eLDDz+Mbot0yM6aNavT5znkkEMQDAZbdHD88ssvAICioiJoNBoMHz48+h+DW0oGfXV9ROzcuROrV69u1dFhNBpbXB9WqxU6nQ5TpkxpcW5FUfDhhx9269xEsfTHa0BVVaiqCp/P1+X6iJrrj9dH5Jf2QYMGdbk+oub60/Xx5JNP4vjjj0dWVlaX6yLqSH+6VjIzM+FwOPDRRx+hoqICxx9/fJfro4GFHbdEnbB06VI8//zzeO2112C1WqOzaux2O4xGI+x2O8477zxcccUVSE9Ph81mw8UXX4xZs2Zh5syZ0eNs27YNTqcTZWVl8Hg80X/4jx07FjqdDnPnzsXkyZNx7rnn4oEHHoCiKFi6dCmOPvroFl24B/L7/di4cWP043379mHDhg2wWCwYPnw4AMDpdGLbtm3R5+zcuRMbNmxAeno6CgsL4/2S0QDSV9dHxLJlyzBo0CAcc8wxnarviiuuwNlnn42pU6di+vTpeOCBB+ByufC73/0uuk9ZWRnKysqi18iPP/4Iq9WKwsJCvkFCHUr1a2DHjh343//+h3nz5iErKwt79+7FXXfdBaPRiGOPPTZOrxINVKl+fWzfvh3PP/88jj32WGRkZOCHH37A5ZdfjsMPPxwTJkyI06tEA1WqXx/Nz79mzRq8/fbbPXxFiGLrD9fKU089hTFjxiArKwtr167FpZdeissvvxyjRo2KwytE/ZpKRB0CEPO/p556KrqPx+NRL7zwQjUtLU01mUzqSSedpJaWlrY4zhFHHBHzODt37ozus2/fPvXkk09WLRaLmpOTo55zzjlqdXV1u/Xt3Lkz5nGPOOKI6D6rV6+Ouc/ZZ58dh1eIBrK+vD5kWVbz8/PV6667rks1Pvzww2phYaGq0+nU6dOnq19++WWLx2+66aYOvwaitqT6NbBv3z71mGOOUbOzs1WtVqvm5+erZ5xxhrp58+ZuvR5EzaX69VFSUqIefvjhanp6uqrX69Xhw4erV199tVpfX9+t14OouVS/PiKuvfZataCgQJVluUvHJuqs/nCtXHPNNWpOTo6q1WrVESNGqPfdd5+qKEqXXwsaeARVVdUup71ERERERERERERE1Gs445aIiIiIiIiIiIgoyTC4JSIiIiIiIiIiIkoyDG6JiIiIiIiIiIiIkgyDWyIiIiIiIiIiIqIkw+CWiIiIiIiIiIiIKMkwuCUiIiIiIiIiIiJKMgxuiYiIiIiIiIiIiJIMg1siIiIiIiIiIiKiJMPgloiIiIiIiIiIiCjJMLglIiIiogHvnHPOgSAIEAQBWq0WOTk5OProo7Fs2TIoitLp4yxfvhwOh6P3CiUiIiKiAYPBLRERERERgAULFqC0tBS7du3CO++8gyOPPBKXXnopjjvuOASDwUSXR0REREQDDINbIiIiIiIAer0eubm5GDx4MCZPnozrrrsOr732Gt555x0sX74cAHD//fdj/PjxMJvNKCgowIUXXgin0wkA+Pjjj/G73/0O9fX10e7dm2++GQDg8/lw1VVXYfDgwTCbzZgxYwY+/vjjxHyhRERERJQSGNwSEREREbXhqKOOwsSJE/HKK68AAERRxEMPPYSff/4ZTz/9ND766CP86U9/AgDMnj0bDzzwAGw2G0pLS1FaWoqrrroKAHDRRRdh7dq1eOGFF/DDDz9g8eLFWLBgAbZu3Zqwr42IiIiIkpugqqqa6CKIiIiIiBLpnHPOQV1dHV599dVWj51++un44YcfsHHjxlaPvfTSSzj//PNRVVUFIDTj9rLLLkNdXV10n5KSEgwdOhQlJSXIy8uLbp87dy6mT5+OO+64I+5fDxERERGlPk2iCyAiIiIiSmaqqkIQBADABx98gDvvvBObN29GQ0MDgsEgvF4v3G43TCZTzOf/+OOPkGUZI0eObLHd5/MhIyOj1+snIiIiotTE4JaIiIiIqB2bNm3CkCFDsGvXLhx33HG44IILcPvttyM9PR2fffYZzjvvPPj9/jaDW6fTCUmSsH79ekiS1OIxi8XSF18CEREREaUgBrdERERERG346KOP8OOPP+Lyyy/H+vXroSgK7rvvPohiaKmIF198scX+Op0Osiy32DZp0iTIsoyKigocdthhfVY7EREREaU2BrdERERERAiNLigrK4MsyygvL8e7776LO++8E8cddxyWLFmCn376CYFAAA8//DAWLVqEzz//HP/85z9bHKO4uBhOpxMffvghJk6cCJPJhJEjR+LMM8/EkiVLcN9992HSpEmorKzEhx9+iAkTJmDhwoUJ+oqJiIiIKJmJiS6AiIiIiCgZvPvuuxg0aBCKi4uxYMECrF69Gg899BBee+01SJKEiRMn4v7778fdd9+NcePG4bnnnsOdd97Z4hizZ8/G+eefj9NOOw1ZWVm45557AABPPfUUlixZgiuvvBKjRo3CiSeeiG+++QaFhYWJ+FKJiIiIKAUIqqqqiS6CiIiIiIiIiIiIiJqw45aIiIiIiIiIiIgoyTC4JSIiIiIiIiIiIkoyDG6JiIiIiIiIiIiIkgyDWyIiIiIiIiIiIqIkw+CWiIiIiIiIiIiIKMkwuCUiIiIiIiIiIiJKMgxuiYiIiIiIiIiIiJIMg1siIiIiIiIiIiKiJMPgloiIiIiIiIiIiCjJMLglIiIiIiIiIiIiSjIMbomIiIiIiIiIiIiSDINbIiIiIiIiIiIioiTz/2D+Kt95o4x5AAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 1400x900 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Precip correlation (DayMet vs NLDAS): 0.745\n",
+      "Temperature correlation (DayMet vs NLDAS): 0.979\n",
+      "\n",
+      "DayMet tmean range: -12.6 – 18.6 °C\n",
+      "NLDAS temperature range: -15.8 – 17.5\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ── Figure 4: DayMet vs NLDAS — Precipitation and Temperature ────────────────\n",
+    "fig, axes = plt.subplots(2, 1, figsize=(14, 9), sharex=True)\n",
+    "\n",
+    "# Panel 1: Precipitation comparison\n",
+    "axes[0].plot(wy_df.index, wy_df['prcp_mm_day'], color='#2166ac', linewidth=1.2,\n",
+    "             alpha=0.85, label='DayMet Precip (mm/day)')\n",
+    "axes[0].plot(wy_df.index, wy_df['total_precipitation'], color='#d73027', linewidth=1.2,\n",
+    "             alpha=0.85, linestyle='--', label='NLDAS Total Precip (mm/day)')\n",
+    "axes[0].set_ylabel('Precipitation (mm/day)')\n",
+    "axes[0].legend(loc='upper right', fontsize=9)\n",
+    "axes[0].set_title('Figure 4: DayMet vs. NLDAS — Precipitation & Temperature (WY2017)')\n",
+    "\n",
+    "valid = wy_df[['prcp_mm_day', 'total_precipitation']].dropna()\n",
+    "corr_precip = valid['prcp_mm_day'].corr(valid['total_precipitation'])\n",
+    "axes[0].text(0.02, 0.92, f'r = {corr_precip:.2f}', transform=axes[0].transAxes,\n",
+    "             fontsize=10, bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))\n",
+    "\n",
+    "# Panel 2: Temperature comparison\n",
+    "# NLDAS 'temperature' is stored in Celsius in this dataset\n",
+    "axes[1].plot(wy_df.index, wy_df['tmean'], color='#2166ac', linewidth=1.2,\n",
+    "             alpha=0.85, label='DayMet Tmean (°C)')\n",
+    "axes[1].plot(wy_df.index, wy_df['temperature'], color='#d73027', linewidth=1.2,\n",
+    "             alpha=0.85, linestyle='--', label='NLDAS Temperature (°C)')\n",
+    "axes[1].axhline(0, color='black', linestyle=':', linewidth=0.8, alpha=0.5)\n",
+    "axes[1].set_ylabel('Temperature (°C)')\n",
+    "axes[1].set_xlabel('Date')\n",
+    "axes[1].legend(loc='upper left', fontsize=9)\n",
+    "\n",
+    "corr_temp = wy_df['tmean'].corr(wy_df['temperature'])\n",
+    "axes[1].text(0.02, 0.08, f'r = {corr_temp:.2f}', transform=axes[1].transAxes,\n",
+    "             fontsize=10, bbox=dict(boxstyle='round', facecolor='wheat', alpha=0.5))\n",
+    "\n",
+    "fig.tight_layout()\n",
+    "plt.savefig('outputs/fig4_daymet_vs_nldas_WY2017.png', dpi=150)\n",
+    "plt.show()\n",
+    "\n",
+    "print(f\"Precip correlation (DayMet vs NLDAS): {corr_precip:.3f}\")\n",
+    "print(f\"Temperature correlation (DayMet vs NLDAS): {corr_temp:.3f}\")\n",
+    "print(f\"\\nDayMet tmean range: {wy_df['tmean'].min():.1f} – {wy_df['tmean'].max():.1f} °C\")\n",
+    "print(f\"NLDAS temperature range: {wy_df['temperature'].min():.1f} – {wy_df['temperature'].max():.1f}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Figure 4 Analysis: DayMet vs. NLDAS Comparison\n",
+    "\n",
+    "**Temperature (r = 0.98):** DayMet and NLDAS daily mean temperatures track each other extremely well (r = 0.98) across WY2017, with nearly identical seasonal cycles from roughly −15°C in winter to +18°C in summer. NLDAS tends to run slightly colder than DayMet (especially during winter cold spells), which is consistent with NLDAS being a lower-resolution grid product that is less able to capture terrain-driven temperature inversions. The high correlation makes either product suitable as a temperature driver for hydrologic modeling.\n",
+    "\n",
+    "**Precipitation (r = 0.75):** Agreement is weaker for precipitation, which is expected — precipitation is spatially heterogeneous and both products use different methods to downscale or reanalyze it. DayMet precipitation magnitudes are substantially larger than NLDAS for the same events (e.g., 80 mm/day vs ~2 mm/day in January 2017), suggesting NLDAS may significantly underestimate orographic precipitation at this high-elevation Sierra Nevada site. This is an important caveat when selecting a meteorological forcing dataset: DayMet's statistical downscaling and orographic correction make it better suited for mountain watersheds."
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -2920,7 +3391,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "hyriver",
+   "display_name": ".venv (3.12.11)",
    "language": "python",
    "name": "python3"
   },
@@ -2934,7 +3405,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.20"
+   "version": "3.12.11"
   }
  },
  "nbformat": 4,
diff --git a/USGS_NWIS.ipynb b/USGS_NWIS.ipynb
index 6f4820d..a1504bb 100644
--- a/USGS_NWIS.ipynb
+++ b/USGS_NWIS.ipynb
@@ -1,5 +1,14 @@
 {
  "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install pynhd dataretrieval folium contextily"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
diff --git a/build_hydrodf.py b/build_hydrodf.py
new file mode 100644
index 0000000..5694538
--- /dev/null
+++ b/build_hydrodf.py
@@ -0,0 +1,278 @@
+"""
+build_hydrodf.py
+================
+Exercise #2 — Collect, process, and save the HydroDataFrame and select figures
+for USGS NWIS station 11274790 (Tuolumne River at Hetch Hetchy Reservoir, CA).
+
+Usage:
+    python build_hydrodf.py
+
+Outputs:
+    files/NWIS/streamflow_<station_id>.csv   — USGS daily streamflow
+    files/HydroDF/HydroDF_<station_id>.csv   — Combined HydroDataFrame
+    outputs/fig1_streamflow_vs_SWE_WY2017.png
+    outputs/fig2_snowmelt_swe_temp_srad_WY2017.png
+    outputs/fig3_rainfall_runoff_WY2017.png
+    outputs/fig4_daymet_vs_nldas_WY2017.png
+"""
+
+import os
+import sys
+import warnings
+import pandas as pd
+import matplotlib.pyplot as plt
+import matplotlib.dates as mdates
+from dataretrieval import nwis
+
+warnings.filterwarnings("ignore")
+
+# ── Configuration ─────────────────────────────────────────────────────────────
+STATION_ID  = "11274790"
+BASIN_NAME  = "TuolumneRiverBasin"
+SNOTEL_PATH = "files/SNOTEL"
+DROP_SNOTEL = {"TES"}            # sites with too many missing values
+WY_START    = "2016-10-01"       # Water Year 2017
+WY_END      = "2017-09-30"
+OUTPUT_DIR  = "outputs"
+NWIS_DIR    = "files/NWIS"
+HYDRODF_DIR = "files/HydroDF"
+
+
+# ── Helper ────────────────────────────────────────────────────────────────────
+def ensure_dirs(*paths):
+    for p in paths:
+        os.makedirs(p, exist_ok=True)
+
+
+# ── Step 1: Fetch and save streamflow if not already present ──────────────────
+def fetch_streamflow(station_id, out_dir):
+    out_path = os.path.join(out_dir, f"streamflow_{station_id}.csv")
+    if os.path.exists(out_path):
+        print(f"[streamflow] Using cached file: {out_path}")
+    else:
+        print(f"[streamflow] Downloading from USGS NWIS for site {station_id}...")
+        df, _ = nwis.get_dv(sites=station_id, start="1980-01-01", parameterCd="00060")
+        df.index = pd.to_datetime(df.index).tz_localize(None).normalize()
+        df.rename(columns={"00060_Mean": "Streamflow_cfs"}, inplace=True)
+        df.drop(columns=["00060_Mean_cd", "site_no"], errors="ignore", inplace=True)
+        df.index.name = "Date"
+        df = df.reset_index()
+        df.to_csv(out_path, index=False)
+        print(f"[streamflow] Saved {len(df)} rows → {out_path}")
+    return out_path
+
+
+# ── Step 2: Load SNOTEL files and build merged SNOTEL dataframe ───────────────
+def load_snotel(snotel_path, drop_sites=None):
+    drop_sites = drop_sites or set()
+    dfs = {}
+    for fname in os.listdir(snotel_path):
+        if not fname.endswith(".csv"):
+            continue
+        name = fname.split("_")[1]
+        if name in drop_sites:
+            continue
+        df = pd.read_csv(os.path.join(snotel_path, fname))
+        df["Date"] = pd.to_datetime(df["Date"])
+        df.set_index("Date", inplace=True)
+        swe_col = "Snow Water Equivalent (m) Start of Day Values"
+        df.rename(columns={swe_col: f"{name}_SWE_cm"}, inplace=True)
+        df[f"{name}_SWE_cm"] = df[f"{name}_SWE_cm"] * 100
+        df.drop(columns=["Water_Year"], errors="ignore", inplace=True)
+        dfs[name] = df
+        print(f"  [snotel] {name}: {len(df)} rows "
+              f"({df.index.min().date()} – {df.index.max().date()})")
+
+    latest_start = max(df.index.min() for df in dfs.values())
+    soonest_end  = min(df.index.max() for df in dfs.values())
+    print(f"[snotel] Common overlap: {latest_start.date()} – {soonest_end.date()}")
+    for k in dfs:
+        dfs[k] = dfs[k][(dfs[k].index >= latest_start) & (dfs[k].index <= soonest_end)]
+
+    return pd.concat(dfs.values(), axis=1)
+
+
+# ── Step 3: Load all dataframes and merge ─────────────────────────────────────
+def build_hydrodf(station_id):
+    print("\n[build] Loading data sources...")
+
+    SNOTEL_df = load_snotel(SNOTEL_PATH, drop_sites=DROP_SNOTEL)
+
+    PyDayMet_df = pd.read_csv(f"files/PyDayMet/PyDayMet_{station_id}.csv")
+    PyDayMet_df["Date"] = pd.to_datetime(PyDayMet_df["Date"])
+    PyDayMet_df.set_index("Date", inplace=True)
+    PyDayMet_df.drop(columns=["Date.1"], errors="ignore", inplace=True)
+
+    NLDAS_df = pd.read_csv(f"files/NLDAS/NLDAS_{station_id}.csv")
+    NLDAS_df["Date"] = pd.to_datetime(NLDAS_df["Date"])
+    NLDAS_df.set_index("Date", inplace=True)
+    NLDAS_df.drop(columns=["Date.1"], errors="ignore", inplace=True)
+
+    streamflow_df = pd.read_csv(f"files/NWIS/streamflow_{station_id}.csv")
+    streamflow_df["Date"] = pd.to_datetime(streamflow_df["Date"])
+    streamflow_df.set_index("Date", inplace=True)
+
+    basin_info = pd.read_csv(f"files/basin_info/basin_info_{station_id}.csv")
+
+    # Align to overlapping period
+    begin_date = max(df.index.min() for df in [SNOTEL_df, PyDayMet_df, streamflow_df, NLDAS_df])
+    end_date   = min(df.index.max() for df in [SNOTEL_df, PyDayMet_df, streamflow_df, NLDAS_df])
+    print(f"[build] Overlapping period: {begin_date.date()} – {end_date.date()}")
+
+    for df in [SNOTEL_df, PyDayMet_df, streamflow_df, NLDAS_df]:
+        mask = (df.index >= begin_date) & (df.index <= end_date)
+        df.drop(df.index[~mask], inplace=True)
+
+    Hydro_df = pd.concat([SNOTEL_df, PyDayMet_df, NLDAS_df, streamflow_df], axis=1)
+
+    # Reorder: Streamflow_cfs first
+    if "Streamflow_cfs" in Hydro_df.columns:
+        cols = ["Streamflow_cfs"] + [c for c in Hydro_df.columns if c != "Streamflow_cfs"]
+        Hydro_df = Hydro_df[cols]
+
+    Hydro_df.fillna(0, inplace=True)
+
+    # Add basin attributes as constant columns
+    for col in basin_info.columns:
+        Hydro_df[col] = basin_info[col].iloc[0]
+
+    print(f"[build] Hydro_df: {Hydro_df.shape[0]} rows × {Hydro_df.shape[1]} columns")
+    return Hydro_df
+
+
+# ── Step 4: Save HydroDF ──────────────────────────────────────────────────────
+def save_hydrodf(Hydro_df, station_id, out_dir):
+    out_path = os.path.join(out_dir, f"HydroDF_{station_id}.csv")
+    Hydro_df.to_csv(out_path)
+    print(f"[save] HydroDF saved → {out_path}")
+
+
+# ── Step 5: Generate and save figures ─────────────────────────────────────────
+def make_figures(Hydro_df, wy_start, wy_end, out_dir):
+    wy_df = Hydro_df.loc[wy_start:wy_end].copy()
+    snotel_cols = [c for c in wy_df.columns if c.endswith("_SWE_cm")]
+    wy_df["mean_SWE_cm"] = wy_df[snotel_cols].mean(axis=1)
+
+    # Figure 1: Streamflow vs SWE
+    fig, ax1 = plt.subplots(figsize=(14, 5))
+    ax1.set_xlabel("Date")
+    ax1.set_ylabel("Streamflow (cfs)", color="#1f77b4")
+    ax1.plot(wy_df.index, wy_df["Streamflow_cfs"], color="#1f77b4", linewidth=1.5,
+             label="Streamflow (cfs)")
+    ax1.tick_params(axis="y", labelcolor="#1f77b4")
+    ax2 = ax1.twinx()
+    ax2.set_ylabel("Mean SNOTEL SWE (cm)", color="#d62728")
+    ax2.fill_between(wy_df.index, wy_df["mean_SWE_cm"], alpha=0.3, color="#d62728")
+    ax2.plot(wy_df.index, wy_df["mean_SWE_cm"], color="#d62728", linewidth=1.5,
+             label="Mean SWE (cm)")
+    ax2.tick_params(axis="y", labelcolor="#d62728")
+    lines = ax1.get_legend_handles_labels()[0] + ax2.get_legend_handles_labels()[0]
+    labels = ax1.get_legend_handles_labels()[1] + ax2.get_legend_handles_labels()[1]
+    ax1.legend(lines, labels, loc="upper left")
+    plt.title("Figure 1: Streamflow vs. Mean SNOTEL SWE — Tuolumne River WY2017")
+    fig.tight_layout()
+    path1 = os.path.join(out_dir, "fig1_streamflow_vs_SWE_WY2017.png")
+    plt.savefig(path1, dpi=150)
+    plt.close()
+    print(f"[fig] Saved {path1}")
+
+    # Figure 2: Snowmelt dynamics
+    melt_df = wy_df.loc["2017-02-01":"2017-07-31"]
+    fig, axes = plt.subplots(3, 1, figsize=(14, 10), sharex=True)
+    axes[0].fill_between(melt_df.index, melt_df["mean_SWE_cm"], color="#4292c6", alpha=0.5)
+    axes[0].plot(melt_df.index, melt_df["mean_SWE_cm"], color="#08519c", linewidth=1.5)
+    axes[0].set_ylabel("Mean SWE (cm)")
+    axes[0].set_title("Figure 2: Snowmelt Dynamics — SWE, Temperature & SW Radiation (WY2017)")
+    axes[1].plot(melt_df.index, melt_df["tmax_C"], color="#d73027", linewidth=1.2, label="Tmax (DayMet)")
+    axes[1].plot(melt_df.index, melt_df["tmin_C"], color="#4575b4", linewidth=1.2, label="Tmin (DayMet)")
+    axes[1].axhline(0, color="black", linestyle="--", linewidth=0.8, alpha=0.5)
+    axes[1].fill_between(melt_df.index, melt_df["tmin_C"], melt_df["tmax_C"],
+                         alpha=0.15, color="orange", label="Tmax–Tmin range")
+    axes[1].set_ylabel("Temperature (°C)")
+    axes[1].legend(loc="upper left", fontsize=9)
+    axes[2].plot(melt_df.index, melt_df["srad_W_m2"], color="#fe9929", linewidth=1.2,
+                 label="SW Radiation (DayMet)")
+    axes[2].set_ylabel("SW Radiation (W/m²)")
+    axes[2].set_xlabel("Date")
+    axes[2].legend(loc="upper left", fontsize=9)
+    fig.tight_layout()
+    path2 = os.path.join(out_dir, "fig2_snowmelt_swe_temp_srad_WY2017.png")
+    plt.savefig(path2, dpi=150)
+    plt.close()
+    print(f"[fig] Saved {path2}")
+
+    # Figure 3: Rainfall–runoff (Oct–Jan)
+    rain_df = wy_df.loc["2016-10-01":"2017-01-31"]
+    fig, ax1 = plt.subplots(figsize=(14, 5))
+    ax1.bar(rain_df.index, rain_df["prcp_mm_day"], color="#2166ac", alpha=0.7,
+            width=1.0, label="DayMet Precipitation (mm/day)")
+    ax1.set_ylabel("Precipitation (mm/day)")
+    ax1.set_xlabel("Date")
+    ax1.invert_yaxis()
+    ax1.set_ylim(rain_df["prcp_mm_day"].max() * 2.5, 0)
+    ax2 = ax1.twinx()
+    ax2.plot(rain_df.index, rain_df["Streamflow_cfs"], color="#d73027",
+             linewidth=2.0, label="Streamflow (cfs)")
+    ax2.set_ylabel("Streamflow (cfs)", color="#d73027")
+    ax2.tick_params(axis="y", labelcolor="#d73027")
+    lines = ax1.get_legend_handles_labels()[0] + ax2.get_legend_handles_labels()[0]
+    labels = ax1.get_legend_handles_labels()[1] + ax2.get_legend_handles_labels()[1]
+    ax1.legend(lines, labels, loc="lower left")
+    plt.title("Figure 3: Rainfall–Runoff Response — Tuolumne River Oct 2016–Jan 2017")
+    fig.tight_layout()
+    path3 = os.path.join(out_dir, "fig3_rainfall_runoff_WY2017.png")
+    plt.savefig(path3, dpi=150)
+    plt.close()
+    print(f"[fig] Saved {path3}")
+
+    # Figure 4: DayMet vs NLDAS
+    fig, axes = plt.subplots(2, 1, figsize=(14, 9), sharex=True)
+    axes[0].plot(wy_df.index, wy_df["prcp_mm_day"], color="#2166ac", linewidth=1.2,
+                 alpha=0.85, label="DayMet Precip (mm/day)")
+    axes[0].plot(wy_df.index, wy_df["total_precipitation"], color="#d73027", linewidth=1.2,
+                 alpha=0.85, linestyle="--", label="NLDAS Total Precip (mm/day)")
+    axes[0].set_ylabel("Precipitation (mm/day)")
+    axes[0].legend(loc="upper right", fontsize=9)
+    axes[0].set_title("Figure 4: DayMet vs. NLDAS — Precipitation & Temperature (WY2017)")
+    corr_p = wy_df["prcp_mm_day"].corr(wy_df["total_precipitation"])
+    axes[0].text(0.02, 0.92, f"r = {corr_p:.2f}", transform=axes[0].transAxes,
+                 fontsize=10, bbox=dict(boxstyle="round", facecolor="wheat", alpha=0.5))
+    axes[1].plot(wy_df.index, wy_df["tmean"], color="#2166ac", linewidth=1.2,
+                 alpha=0.85, label="DayMet Tmean (°C)")
+    axes[1].plot(wy_df.index, wy_df["temperature"], color="#d73027", linewidth=1.2,
+                 alpha=0.85, linestyle="--", label="NLDAS Temperature (°C)")
+    axes[1].axhline(0, color="black", linestyle=":", linewidth=0.8, alpha=0.5)
+    axes[1].set_ylabel("Temperature (°C)")
+    axes[1].set_xlabel("Date")
+    axes[1].legend(loc="upper left", fontsize=9)
+    corr_t = wy_df["tmean"].corr(wy_df["temperature"])
+    axes[1].text(0.02, 0.08, f"r = {corr_t:.2f}", transform=axes[1].transAxes,
+                 fontsize=10, bbox=dict(boxstyle="round", facecolor="wheat", alpha=0.5))
+    fig.tight_layout()
+    path4 = os.path.join(out_dir, "fig4_daymet_vs_nldas_WY2017.png")
+    plt.savefig(path4, dpi=150)
+    plt.close()
+    print(f"[fig] Saved {path4}")
+
+    print(f"\n[fig] Precip correlation DayMet vs NLDAS: {corr_p:.3f}")
+    print(f"[fig] Temp  correlation DayMet vs NLDAS: {corr_t:.3f}")
+
+
+# ── Main ──────────────────────────────────────────────────────────────────────
+if __name__ == "__main__":
+    ensure_dirs(NWIS_DIR, HYDRODF_DIR, OUTPUT_DIR)
+
+    # 1. Fetch streamflow
+    fetch_streamflow(STATION_ID, NWIS_DIR)
+
+    # 2. Build combined HydroDF
+    Hydro_df = build_hydrodf(STATION_ID)
+
+    # 3. Save HydroDF
+    save_hydrodf(Hydro_df, STATION_ID, HYDRODF_DIR)
+
+    # 4. Generate and save figures
+    print("\n[fig] Generating figures...")
+    make_figures(Hydro_df, WY_START, WY_END, OUTPUT_DIR)
+
+    print("\n✓ Done. All outputs saved.")
diff --git a/getdata.ipynb b/getdata.ipynb
new file mode 100644
index 0000000..7a9f231
--- /dev/null
+++ b/getdata.ipynb
@@ -0,0 +1,117 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "446b3211",
+   "metadata": {},
+   "source": [
+    "# NDVI vs Temperature Plot\n",
+    "\n",
+    "This notebook plots basin-mean NDVI and air temperature for USGS 11274790 in 2012. Precipitation is excluded, and temperature is shown on the second y-axis in red."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "63d8e6e7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1400x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "gage_id = '11274790'\n",
+    "year = 2012\n",
+    "\n",
+    "ndvi_path = f'files/GIMMS/GIMMS_NDVI_daily_{gage_id}.csv'\n",
+    "met_path = f'files/NLDAS/NLDAS_{gage_id}.csv'\n",
+    "\n",
+    "ndvi_df = pd.read_csv(ndvi_path, parse_dates=['Date'])[['Date', 'ndvi']]\n",
+    "met_df = pd.read_csv(met_path, parse_dates=['Date'])[['Date', 'temperature']]\n",
+    "\n",
+    "plot_df = pd.merge(ndvi_df, met_df, on='Date', how='inner')\n",
+    "plot_df = plot_df[plot_df['Date'].dt.year == year].copy()\n",
+    "\n",
+    "fig, ax1 = plt.subplots(figsize=(14, 6))\n",
+    "\n",
+    "# Left axis: NDVI\n",
+    "ax1.plot(plot_df['Date'], plot_df['ndvi'], color='forestgreen', linewidth=2.8, label='NDVI')\n",
+    "ax1.set_xlabel('Date', fontsize=12)\n",
+    "ax1.set_ylabel('NDVI', color='forestgreen', fontsize=12)\n",
+    "ax1.tick_params(axis='y', labelcolor='forestgreen')\n",
+    "ax1.grid(True, alpha=0.25)\n",
+    "\n",
+    "# Right axis: Temperature (red)\n",
+    "ax2 = ax1.twinx()\n",
+    "ax2.plot(plot_df['Date'], plot_df['temperature'], color='red', linewidth=2.6, alpha=0.9, label='Temperature')\n",
+    "ax2.set_ylabel('Temperature (°C)', color='red', fontsize=12)\n",
+    "ax2.tick_params(axis='y', labelcolor='red')\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 left', frameon=True)\n",
+    "\n",
+    "plt.title(f'NDVI vs Temperature ({year})\\nUSGS {gage_id} basin', fontsize=20)\n",
+    "fig.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ce88f20b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ab7415f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a11877e5",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "hyriver",
+   "language": "python",
+   "name": "hyriver"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.14.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/supporting_scripts/dataprocessing.py b/supporting_scripts/dataprocessing.py
index edfa7d8..db3fff9 100644
--- a/supporting_scripts/dataprocessing.py
+++ b/supporting_scripts/dataprocessing.py
@@ -25,6 +25,49 @@ def clean_nwis_dataframe(df):
         
     return df
 
+
+def interpolate_to_daily(df, value_columns=None, date_column='Date', method='time'):
+    """
+    Resample a time-indexed dataframe to daily cadence and interpolate numeric values.
+
+    Parameters:
+    df: pandas DataFrame with either a datetime index or a datetime column.
+    value_columns: list of columns to interpolate. If None, all numeric columns are used.
+    date_column: name of the datetime column to use or restore after interpolation.
+    method: interpolation method passed to pandas.DataFrame.interpolate.
+    """
+    daily_df = df.copy()
+
+    if date_column in daily_df.columns:
+        daily_df[date_column] = pd.to_datetime(daily_df[date_column])
+        daily_df.set_index(date_column, inplace=True)
+    else:
+        daily_df.index = pd.to_datetime(daily_df.index)
+        daily_df.index.name = date_column
+
+    daily_df.sort_index(inplace=True)
+
+    if value_columns is None:
+        value_columns = daily_df.select_dtypes(include='number').columns.tolist()
+
+    daily_index = pd.date_range(daily_df.index.min(), daily_df.index.max(), freq='D')
+    daily_df = daily_df.reindex(daily_index)
+
+    if value_columns:
+        daily_df[value_columns] = daily_df[value_columns].interpolate(
+            method=method,
+            limit_direction='both'
+        )
+
+    other_columns = [column for column in daily_df.columns if column not in value_columns]
+    for column in other_columns:
+        daily_df[column] = daily_df[column].ffill().bfill()
+
+    daily_df.index.name = date_column
+    daily_df[date_column] = daily_df.index
+
+    return daily_df
+
 '''
 The function to process raw SNOTEL data for a given site and water year,
 and calculate the min, mean, median, max SWE for each day of the water year
diff --git a/supporting_scripts/getData.py b/supporting_scripts/getData.py
index a456764..8a223f5 100644
--- a/supporting_scripts/getData.py
+++ b/supporting_scripts/getData.py
@@ -1,4 +1,5 @@
 import os
+import io
 import sys
 import pytz
 import urllib3
@@ -11,6 +12,9 @@
 from dataretrieval import nwis
 pd.options.mode.chained_assignment = None
 
+GIMMS_START_DATE = '1981-07-01'
+GIMMS_END_DATE = '2013-12-16'
+
 def getSNOTELData(SiteName, SiteID, StateAbb, StartDate, EndDate, OutputFolder):
     #the api changed and we need to pull the site id out - 3-1-2026
     site_id = SiteID.split('_')[0]
@@ -22,28 +26,47 @@ def getSNOTELData(SiteName, SiteID, StateAbb, StartDate, EndDate, OutputFolder):
     url = url1+url2+url3+url4
     print(f'Start retrieving data for {SiteName}, {SiteID} \n {url}')
 
-    http = urllib3.PoolManager()
+    http = urllib3.PoolManager(
+        headers={
+            'User-Agent': 'Mozilla/5.0',
+            'Accept': 'text/csv,text/plain,*/*',
+            'Connection': 'keep-alive'
+        },
+        retries=urllib3.Retry(total=3, backoff_factor=0.5, status_forcelist=[500, 502, 503, 504]),
+        timeout=urllib3.Timeout(connect=5.0, read=30.0)
+    )
     response = http.request('GET', url)
+    if response.status != 200:
+        raise RuntimeError(f'Failed to retrieve SNOTEL data for {SiteID}: HTTP {response.status}')
+
     data = response.data.decode('utf-8')
-    i=0
-    for line in data.split("\n"):
-        if line.startswith("#"):
-            i=i+1
-    data = data.split("\n")[i:]
+    lines = [line.strip() for line in data.splitlines() if line.strip() and not line.startswith('#')]
+    if not lines:
+        raise ValueError(f'No parseable data returned for {SiteID}')
 
-    df = pd.DataFrame.from_dict(data) 
-    df = df[0].str.split(',', expand=True)
-    df.rename(columns={0:df[0][0], 
-                        1:df[1][0]}, inplace=True)
-    df.drop(0, inplace=True)
-    df.dropna(inplace=True)
-    df.reset_index(inplace=True, drop=True)
-    df["Date"] = pd.to_datetime(df["Date"])
-    df.rename(columns={df.columns[1]:'Snow Water Equivalent (m) Start of Day Values'}, inplace=True)
-    df.iloc[:, 1:] = df.iloc[:, 1:].apply(lambda x: pd.to_numeric(x) * 0.0254)  # convert in to m
+    csv_start = 0
+    for idx, line in enumerate(lines):
+        if line.lower().startswith('date,'):
+            csv_start = idx
+            break
+
+    csv_text = '\n'.join(lines[csv_start:])
+    df = pd.read_csv(io.StringIO(csv_text))
+    if df.shape[1] < 2:
+        preview = '\n'.join(lines[:5])
+        raise ValueError(f'Unexpected SNOTEL CSV format for {SiteID}. Preview:\n{preview}')
+
+    df = df.iloc[:, :2].copy()
+    df.columns = ['Date', 'Snow Water Equivalent (m) Start of Day Values']
+    df['Date'] = pd.to_datetime(df['Date'])
+    df['Snow Water Equivalent (m) Start of Day Values'] = pd.to_numeric(
+        df['Snow Water Equivalent (m) Start of Day Values'], errors='coerce'
+    ) * 0.0254  # convert inches to meters
+    df.dropna(subset=['Date', 'Snow Water Equivalent (m) Start of Day Values'], inplace=True)
     df['Water_Year'] = pd.to_datetime(df['Date']).map(lambda x: x.year+1 if x.month>9 else x.year)
 
-    df.to_csv(f'./{OutputFolder}/df_{SiteID}_{StateAbb}_SNTL.csv', index=False)
+    output_path = os.path.join(OutputFolder, f'df_{SiteID}_{StateAbb}_SNTL.csv')
+    df.to_csv(output_path, index=False)
 
 def getCaliSNOTELData(SiteName, SiteID, StartDate, EndDate, OutputFolder):
     StateAbb = 'Ca'
@@ -235,6 +258,55 @@ def get_usgs_streamflow(site_id, start_date="1980-01-01", end_date=datetime.date
     except Exception as e:
         print(f"An error occurred: {e}")
         return None
+
+
+def get_GIMMS_NDVI_15day(basin_polygon_coords, begin_date=GIMMS_START_DATE, end_date=GIMMS_END_DATE):
+    import ee
+
+    dataset_start = pd.Timestamp(GIMMS_START_DATE)
+    dataset_end = pd.Timestamp(GIMMS_END_DATE)
+    begin_ts = pd.Timestamp(begin_date)
+    end_ts = pd.Timestamp(end_date if end_date is not None else GIMMS_END_DATE)
+
+    if end_ts < dataset_start or begin_ts > dataset_end:
+        raise ValueError(
+            f"Requested dates fall outside the GIMMS availability window of {GIMMS_START_DATE} to {GIMMS_END_DATE}."
+        )
+
+    begin_ts = max(begin_ts, dataset_start)
+    end_ts = min(end_ts, dataset_end)
+
+    print("Authenticating with Earth Engine...")
+    ee.Authenticate()
+    print("Initializing Earth Engine...")
+    ee.Initialize()
+    print("Earth Engine initialized successfully.")
+
+    basin_polygon = ee.Geometry.Polygon(basin_polygon_coords)
+
+    gimms_collection = (
+        ee.ImageCollection("NASA/GIMMS/3GV0")
+        .select("ndvi")
+        .filterBounds(basin_polygon)
+        .filterDate(begin_ts.strftime('%Y-%m-%d'), (end_ts + pd.Timedelta(days=1)).strftime('%Y-%m-%d'))
+    )
+
+    results = gimms_collection.map(lambda img: get_all_metrics(img, basin_polygon)).getInfo()
+    df = pd.DataFrame([feature['properties'] for feature in results['features']])
+
+    if df.empty:
+        empty_df = pd.DataFrame(columns=['ndvi'])
+        empty_df.index = pd.DatetimeIndex([], name='Date')
+        return empty_df
+
+    cols = ['date'] + [column for column in df.columns if column != 'date']
+    df = df[cols]
+    df['date'] = pd.to_datetime(df['date'].str.split('T').str[0])
+    df.rename(columns={'date': 'Date'}, inplace=True)
+    df.set_index('Date', drop=True, inplace=True)
+    df.sort_index(inplace=True)
+
+    return df
     
  #Main Data Fetcher
 def get_NLDAS_daily(basin_polygon_coords, begin_date='2025-01-01', end_date=None):
@@ -323,8 +395,6 @@ def get_NLDAS_hourly(basin_polygon_coords, begin_date = '2025-12-30', end_date =
 # Spatial Reduction Function
 def get_all_metrics(image, basin_polygon):
     import ee
-    ee.Authenticate()
-    ee.Initialize()
     stats = image.reduceRegion(
         reducer=ee.Reducer.mean(),
         geometry=basin_polygon,
@@ -335,10 +405,65 @@ def get_all_metrics(image, basin_polygon):
     
 
 if __name__ == "__main__":
-	SiteName = sys.argv[1]
-	SiteID = sys.argv[2]
-	StateAbb = sys.argv[3]
-	StartDate = sys.argv[4]
-	EndDate = sys.argv[5]
-	OutputFolder = sys.argv[6]
-	
+    import argparse
+    from pynhd import NLDI
+    import dataprocessing
+
+    def _get_basin_polygon_coords(usgs_gage_id):
+        basin = NLDI().get_basins(usgs_gage_id)
+        geometry = basin.to_crs("EPSG:4326").geometry.iloc[0]
+        return list(geometry.exterior.coords)
+
+    parser = argparse.ArgumentParser(
+        description="Download basin-mean GIMMS NDVI from Earth Engine and interpolate to daily."
+    )
+    parser.add_argument("--gage-id", default="11274790",
+                        help="USGS gage ID used to define the basin through NLDI.")
+    parser.add_argument("--start-date", default=GIMMS_START_DATE,
+                        help="Start date (YYYY-MM-DD).")
+    parser.add_argument("--end-date", default=GIMMS_END_DATE,
+                        help="End date (YYYY-MM-DD).")
+    parser.add_argument("--output-folder", default="files/GIMMS",
+                        help="Folder where CSVs and plots will be written.")
+    args = parser.parse_args()
+
+    os.makedirs(args.output_folder, exist_ok=True)
+
+    basin_polygon_coords = _get_basin_polygon_coords(args.gage_id)
+
+    gimms_15day = get_GIMMS_NDVI_15day(
+        basin_polygon_coords,
+        begin_date=args.start_date,
+        end_date=args.end_date,
+    )
+
+    gimms_daily = dataprocessing.interpolate_to_daily(gimms_15day)
+
+    gimms_15day_out = gimms_15day.copy()
+    gimms_15day_out['Date'] = gimms_15day_out.index
+    gimms_daily_out = gimms_daily.copy()
+
+    gimms_15day_csv = os.path.join(args.output_folder, f"GIMMS_NDVI_15day_{args.gage_id}.csv")
+    gimms_daily_csv = os.path.join(args.output_folder, f"GIMMS_NDVI_daily_{args.gage_id}.csv")
+    plot_path = os.path.join(args.output_folder, f"GIMMS_NDVI_{args.gage_id}.png")
+
+    gimms_15day_out.to_csv(gimms_15day_csv, index=False)
+    gimms_daily_out.to_csv(gimms_daily_csv, index=False)
+
+    fig, ax = plt.subplots(figsize=(10, 5))
+    ax.plot(gimms_daily_out['Date'], gimms_daily_out['ndvi'],
+            label='Daily interpolated NDVI', color='forestgreen')
+    ax.scatter(gimms_15day_out['Date'], gimms_15day_out['ndvi'],
+               label='15-day GIMMS NDVI', color='black', s=12)
+    ax.set_title(f"GIMMS NDVI for Basin Upstream of USGS Gage {args.gage_id}")
+    ax.set_xlabel('Date')
+    ax.set_ylabel('NDVI')
+    ax.grid(True, alpha=0.3)
+    ax.legend()
+    fig.tight_layout()
+    fig.savefig(plot_path, dpi=200)
+
+    print(f"Saved 15-day data  : {gimms_15day_csv}")
+    print(f"Saved daily data   : {gimms_daily_csv}")
+    print(f"Saved plot         : {plot_path}")
+