diff --git a/live_code_01_07_2025.ipynb b/live_code_01_07_2025.ipynb
deleted file mode 100644
index ec398576d..000000000
--- a/live_code_01_07_2025.ipynb
+++ /dev/null
@@ -1,1351 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import pandas as pd\n",
-    "import matplotlib.pyplot as plt\n",
-    "import matplotlib.colors as mcolors\n",
-    "from mpl_toolkits import mplot3d"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>id</th>\n",
-       "      <th>diagnosis</th>\n",
-       "      <th>radius_mean</th>\n",
-       "      <th>texture_mean</th>\n",
-       "      <th>perimeter_mean</th>\n",
-       "      <th>area_mean</th>\n",
-       "      <th>smoothness_mean</th>\n",
-       "      <th>compactness_mean</th>\n",
-       "      <th>concavity_mean</th>\n",
-       "      <th>concave points_mean</th>\n",
-       "      <th>...</th>\n",
-       "      <th>radius_worst</th>\n",
-       "      <th>texture_worst</th>\n",
-       "      <th>perimeter_worst</th>\n",
-       "      <th>area_worst</th>\n",
-       "      <th>smoothness_worst</th>\n",
-       "      <th>compactness_worst</th>\n",
-       "      <th>concavity_worst</th>\n",
-       "      <th>concave points_worst</th>\n",
-       "      <th>symmetry_worst</th>\n",
-       "      <th>fractal_dimension_worst</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>842302</td>\n",
-       "      <td>M</td>\n",
-       "      <td>17.99</td>\n",
-       "      <td>10.38</td>\n",
-       "      <td>122.80</td>\n",
-       "      <td>1001.0</td>\n",
-       "      <td>0.11840</td>\n",
-       "      <td>0.27760</td>\n",
-       "      <td>0.30010</td>\n",
-       "      <td>0.14710</td>\n",
-       "      <td>...</td>\n",
-       "      <td>25.380</td>\n",
-       "      <td>17.33</td>\n",
-       "      <td>184.60</td>\n",
-       "      <td>2019.0</td>\n",
-       "      <td>0.16220</td>\n",
-       "      <td>0.66560</td>\n",
-       "      <td>0.7119</td>\n",
-       "      <td>0.2654</td>\n",
-       "      <td>0.4601</td>\n",
-       "      <td>0.11890</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>842517</td>\n",
-       "      <td>M</td>\n",
-       "      <td>20.57</td>\n",
-       "      <td>17.77</td>\n",
-       "      <td>132.90</td>\n",
-       "      <td>1326.0</td>\n",
-       "      <td>0.08474</td>\n",
-       "      <td>0.07864</td>\n",
-       "      <td>0.08690</td>\n",
-       "      <td>0.07017</td>\n",
-       "      <td>...</td>\n",
-       "      <td>24.990</td>\n",
-       "      <td>23.41</td>\n",
-       "      <td>158.80</td>\n",
-       "      <td>1956.0</td>\n",
-       "      <td>0.12380</td>\n",
-       "      <td>0.18660</td>\n",
-       "      <td>0.2416</td>\n",
-       "      <td>0.1860</td>\n",
-       "      <td>0.2750</td>\n",
-       "      <td>0.08902</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>84300903</td>\n",
-       "      <td>M</td>\n",
-       "      <td>19.69</td>\n",
-       "      <td>21.25</td>\n",
-       "      <td>130.00</td>\n",
-       "      <td>1203.0</td>\n",
-       "      <td>0.10960</td>\n",
-       "      <td>0.15990</td>\n",
-       "      <td>0.19740</td>\n",
-       "      <td>0.12790</td>\n",
-       "      <td>...</td>\n",
-       "      <td>23.570</td>\n",
-       "      <td>25.53</td>\n",
-       "      <td>152.50</td>\n",
-       "      <td>1709.0</td>\n",
-       "      <td>0.14440</td>\n",
-       "      <td>0.42450</td>\n",
-       "      <td>0.4504</td>\n",
-       "      <td>0.2430</td>\n",
-       "      <td>0.3613</td>\n",
-       "      <td>0.08758</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>84348301</td>\n",
-       "      <td>M</td>\n",
-       "      <td>11.42</td>\n",
-       "      <td>20.38</td>\n",
-       "      <td>77.58</td>\n",
-       "      <td>386.1</td>\n",
-       "      <td>0.14250</td>\n",
-       "      <td>0.28390</td>\n",
-       "      <td>0.24140</td>\n",
-       "      <td>0.10520</td>\n",
-       "      <td>...</td>\n",
-       "      <td>14.910</td>\n",
-       "      <td>26.50</td>\n",
-       "      <td>98.87</td>\n",
-       "      <td>567.7</td>\n",
-       "      <td>0.20980</td>\n",
-       "      <td>0.86630</td>\n",
-       "      <td>0.6869</td>\n",
-       "      <td>0.2575</td>\n",
-       "      <td>0.6638</td>\n",
-       "      <td>0.17300</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>84358402</td>\n",
-       "      <td>M</td>\n",
-       "      <td>20.29</td>\n",
-       "      <td>14.34</td>\n",
-       "      <td>135.10</td>\n",
-       "      <td>1297.0</td>\n",
-       "      <td>0.10030</td>\n",
-       "      <td>0.13280</td>\n",
-       "      <td>0.19800</td>\n",
-       "      <td>0.10430</td>\n",
-       "      <td>...</td>\n",
-       "      <td>22.540</td>\n",
-       "      <td>16.67</td>\n",
-       "      <td>152.20</td>\n",
-       "      <td>1575.0</td>\n",
-       "      <td>0.13740</td>\n",
-       "      <td>0.20500</td>\n",
-       "      <td>0.4000</td>\n",
-       "      <td>0.1625</td>\n",
-       "      <td>0.2364</td>\n",
-       "      <td>0.07678</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>564</th>\n",
-       "      <td>926424</td>\n",
-       "      <td>M</td>\n",
-       "      <td>21.56</td>\n",
-       "      <td>22.39</td>\n",
-       "      <td>142.00</td>\n",
-       "      <td>1479.0</td>\n",
-       "      <td>0.11100</td>\n",
-       "      <td>0.11590</td>\n",
-       "      <td>0.24390</td>\n",
-       "      <td>0.13890</td>\n",
-       "      <td>...</td>\n",
-       "      <td>25.450</td>\n",
-       "      <td>26.40</td>\n",
-       "      <td>166.10</td>\n",
-       "      <td>2027.0</td>\n",
-       "      <td>0.14100</td>\n",
-       "      <td>0.21130</td>\n",
-       "      <td>0.4107</td>\n",
-       "      <td>0.2216</td>\n",
-       "      <td>0.2060</td>\n",
-       "      <td>0.07115</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>565</th>\n",
-       "      <td>926682</td>\n",
-       "      <td>M</td>\n",
-       "      <td>20.13</td>\n",
-       "      <td>28.25</td>\n",
-       "      <td>131.20</td>\n",
-       "      <td>1261.0</td>\n",
-       "      <td>0.09780</td>\n",
-       "      <td>0.10340</td>\n",
-       "      <td>0.14400</td>\n",
-       "      <td>0.09791</td>\n",
-       "      <td>...</td>\n",
-       "      <td>23.690</td>\n",
-       "      <td>38.25</td>\n",
-       "      <td>155.00</td>\n",
-       "      <td>1731.0</td>\n",
-       "      <td>0.11660</td>\n",
-       "      <td>0.19220</td>\n",
-       "      <td>0.3215</td>\n",
-       "      <td>0.1628</td>\n",
-       "      <td>0.2572</td>\n",
-       "      <td>0.06637</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>566</th>\n",
-       "      <td>926954</td>\n",
-       "      <td>M</td>\n",
-       "      <td>16.60</td>\n",
-       "      <td>28.08</td>\n",
-       "      <td>108.30</td>\n",
-       "      <td>858.1</td>\n",
-       "      <td>0.08455</td>\n",
-       "      <td>0.10230</td>\n",
-       "      <td>0.09251</td>\n",
-       "      <td>0.05302</td>\n",
-       "      <td>...</td>\n",
-       "      <td>18.980</td>\n",
-       "      <td>34.12</td>\n",
-       "      <td>126.70</td>\n",
-       "      <td>1124.0</td>\n",
-       "      <td>0.11390</td>\n",
-       "      <td>0.30940</td>\n",
-       "      <td>0.3403</td>\n",
-       "      <td>0.1418</td>\n",
-       "      <td>0.2218</td>\n",
-       "      <td>0.07820</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>567</th>\n",
-       "      <td>927241</td>\n",
-       "      <td>M</td>\n",
-       "      <td>20.60</td>\n",
-       "      <td>29.33</td>\n",
-       "      <td>140.10</td>\n",
-       "      <td>1265.0</td>\n",
-       "      <td>0.11780</td>\n",
-       "      <td>0.27700</td>\n",
-       "      <td>0.35140</td>\n",
-       "      <td>0.15200</td>\n",
-       "      <td>...</td>\n",
-       "      <td>25.740</td>\n",
-       "      <td>39.42</td>\n",
-       "      <td>184.60</td>\n",
-       "      <td>1821.0</td>\n",
-       "      <td>0.16500</td>\n",
-       "      <td>0.86810</td>\n",
-       "      <td>0.9387</td>\n",
-       "      <td>0.2650</td>\n",
-       "      <td>0.4087</td>\n",
-       "      <td>0.12400</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>568</th>\n",
-       "      <td>92751</td>\n",
-       "      <td>B</td>\n",
-       "      <td>7.76</td>\n",
-       "      <td>24.54</td>\n",
-       "      <td>47.92</td>\n",
-       "      <td>181.0</td>\n",
-       "      <td>0.05263</td>\n",
-       "      <td>0.04362</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>...</td>\n",
-       "      <td>9.456</td>\n",
-       "      <td>30.37</td>\n",
-       "      <td>59.16</td>\n",
-       "      <td>268.6</td>\n",
-       "      <td>0.08996</td>\n",
-       "      <td>0.06444</td>\n",
-       "      <td>0.0000</td>\n",
-       "      <td>0.0000</td>\n",
-       "      <td>0.2871</td>\n",
-       "      <td>0.07039</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>569 rows × 32 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "           id diagnosis  radius_mean  texture_mean  perimeter_mean  area_mean  \\\n",
-       "0      842302         M        17.99         10.38          122.80     1001.0   \n",
-       "1      842517         M        20.57         17.77          132.90     1326.0   \n",
-       "2    84300903         M        19.69         21.25          130.00     1203.0   \n",
-       "3    84348301         M        11.42         20.38           77.58      386.1   \n",
-       "4    84358402         M        20.29         14.34          135.10     1297.0   \n",
-       "..        ...       ...          ...           ...             ...        ...   \n",
-       "564    926424         M        21.56         22.39          142.00     1479.0   \n",
-       "565    926682         M        20.13         28.25          131.20     1261.0   \n",
-       "566    926954         M        16.60         28.08          108.30      858.1   \n",
-       "567    927241         M        20.60         29.33          140.10     1265.0   \n",
-       "568     92751         B         7.76         24.54           47.92      181.0   \n",
-       "\n",
-       "     smoothness_mean  compactness_mean  concavity_mean  concave points_mean  \\\n",
-       "0            0.11840           0.27760         0.30010              0.14710   \n",
-       "1            0.08474           0.07864         0.08690              0.07017   \n",
-       "2            0.10960           0.15990         0.19740              0.12790   \n",
-       "3            0.14250           0.28390         0.24140              0.10520   \n",
-       "4            0.10030           0.13280         0.19800              0.10430   \n",
-       "..               ...               ...             ...                  ...   \n",
-       "564          0.11100           0.11590         0.24390              0.13890   \n",
-       "565          0.09780           0.10340         0.14400              0.09791   \n",
-       "566          0.08455           0.10230         0.09251              0.05302   \n",
-       "567          0.11780           0.27700         0.35140              0.15200   \n",
-       "568          0.05263           0.04362         0.00000              0.00000   \n",
-       "\n",
-       "     ...  radius_worst  texture_worst  perimeter_worst  area_worst  \\\n",
-       "0    ...        25.380          17.33           184.60      2019.0   \n",
-       "1    ...        24.990          23.41           158.80      1956.0   \n",
-       "2    ...        23.570          25.53           152.50      1709.0   \n",
-       "3    ...        14.910          26.50            98.87       567.7   \n",
-       "4    ...        22.540          16.67           152.20      1575.0   \n",
-       "..   ...           ...            ...              ...         ...   \n",
-       "564  ...        25.450          26.40           166.10      2027.0   \n",
-       "565  ...        23.690          38.25           155.00      1731.0   \n",
-       "566  ...        18.980          34.12           126.70      1124.0   \n",
-       "567  ...        25.740          39.42           184.60      1821.0   \n",
-       "568  ...         9.456          30.37            59.16       268.6   \n",
-       "\n",
-       "     smoothness_worst  compactness_worst  concavity_worst  \\\n",
-       "0             0.16220            0.66560           0.7119   \n",
-       "1             0.12380            0.18660           0.2416   \n",
-       "2             0.14440            0.42450           0.4504   \n",
-       "3             0.20980            0.86630           0.6869   \n",
-       "4             0.13740            0.20500           0.4000   \n",
-       "..                ...                ...              ...   \n",
-       "564           0.14100            0.21130           0.4107   \n",
-       "565           0.11660            0.19220           0.3215   \n",
-       "566           0.11390            0.30940           0.3403   \n",
-       "567           0.16500            0.86810           0.9387   \n",
-       "568           0.08996            0.06444           0.0000   \n",
-       "\n",
-       "     concave points_worst  symmetry_worst  fractal_dimension_worst  \n",
-       "0                  0.2654          0.4601                  0.11890  \n",
-       "1                  0.1860          0.2750                  0.08902  \n",
-       "2                  0.2430          0.3613                  0.08758  \n",
-       "3                  0.2575          0.6638                  0.17300  \n",
-       "4                  0.1625          0.2364                  0.07678  \n",
-       "..                    ...             ...                      ...  \n",
-       "564                0.2216          0.2060                  0.07115  \n",
-       "565                0.1628          0.2572                  0.06637  \n",
-       "566                0.1418          0.2218                  0.07820  \n",
-       "567                0.2650          0.4087                  0.12400  \n",
-       "568                0.0000          0.2871                  0.07039  \n",
-       "\n",
-       "[569 rows x 32 columns]"
-      ]
-     },
-     "execution_count": 2,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cancer = pd.read_csv('dataset/wdbc.csv')\n",
-    "cancer\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "RangeIndex: 569 entries, 0 to 568\n",
-      "Data columns (total 32 columns):\n",
-      " #   Column                   Non-Null Count  Dtype  \n",
-      "---  ------                   --------------  -----  \n",
-      " 0   id                       569 non-null    int64  \n",
-      " 1   diagnosis                569 non-null    object \n",
-      " 2   radius_mean              569 non-null    float64\n",
-      " 3   texture_mean             569 non-null    float64\n",
-      " 4   perimeter_mean           569 non-null    float64\n",
-      " 5   area_mean                569 non-null    float64\n",
-      " 6   smoothness_mean          569 non-null    float64\n",
-      " 7   compactness_mean         569 non-null    float64\n",
-      " 8   concavity_mean           569 non-null    float64\n",
-      " 9   concave points_mean      569 non-null    float64\n",
-      " 10  symmetry_mean            569 non-null    float64\n",
-      " 11  fractal_dimension_mean   569 non-null    float64\n",
-      " 12  radius_se                569 non-null    float64\n",
-      " 13  texture_se               569 non-null    float64\n",
-      " 14  perimeter_se             569 non-null    float64\n",
-      " 15  area_se                  569 non-null    float64\n",
-      " 16  smoothness_se            569 non-null    float64\n",
-      " 17  compactness_se           569 non-null    float64\n",
-      " 18  concavity_se             569 non-null    float64\n",
-      " 19  concave points_se        569 non-null    float64\n",
-      " 20  symmetry_se              569 non-null    float64\n",
-      " 21  fractal_dimension_se     569 non-null    float64\n",
-      " 22  radius_worst             569 non-null    float64\n",
-      " 23  texture_worst            569 non-null    float64\n",
-      " 24  perimeter_worst          569 non-null    float64\n",
-      " 25  area_worst               569 non-null    float64\n",
-      " 26  smoothness_worst         569 non-null    float64\n",
-      " 27  compactness_worst        569 non-null    float64\n",
-      " 28  concavity_worst          569 non-null    float64\n",
-      " 29  concave points_worst     569 non-null    float64\n",
-      " 30  symmetry_worst           569 non-null    float64\n",
-      " 31  fractal_dimension_worst  569 non-null    float64\n",
-      "dtypes: float64(30), int64(1), object(1)\n",
-      "memory usage: 142.4+ KB\n"
-     ]
-    }
-   ],
-   "source": [
-    "#take a closer look at our data\n",
-    "cancer.info()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['M', 'B'], dtype=object)"
-      ]
-     },
-     "execution_count": 4,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#investigate the diagnosis column and return all our unique labels\n",
-    "cancer[\"diagnosis\"].unique()\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['Malignant', 'Benign'], dtype=object)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#clean diagnosis values M --> Malignant, B --> Benign\n",
-    "\n",
-    "cancer['diagnosis'] = cancer['diagnosis'].replace({\n",
-    "    \"M\": \"Malignant\",\n",
-    "    \"B\" : \"Benign\"\n",
-    "})\n",
-    "\n",
-    "cancer['diagnosis'].unique()\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Benign       0.627417\n",
-       "Malignant    0.372583\n",
-       "Name: diagnosis, dtype: float64"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#see distribution of diagnosis\n",
-    "\n",
-    "cancer['diagnosis'].value_counts()\n",
-    "cancer['diagnosis'].value_counts(normalize = True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "diagnosis\n",
-       "Benign       62.741652\n",
-       "Malignant    37.258348\n",
-       "dtype: float64"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#Another method\n",
-    "cancer.groupby(\"diagnosis\").size()\n",
-    "(cancer.groupby(\"diagnosis\").size() / cancer.shape[0])*100"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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jj3nvvfd47733DGMawsPDzR5Dp9MxcOBAkpOTmTZtGq1atcLNzQ2dTkeXLl2u+8MvLS2N+Ph4swN7r+7vDQkJsev4jRo1YvHixSiKgrOzM9HR0bi6ulq8T2ZmJhqNxtB/Xk5RFIKDg8nMzLQrhuo+LugHTm/cuBEAJycnGjRogKenp+H26n6efX19jX53dHQ0u73i9PS0tDSysrIM+1uLy5TqfmzlevXqRZMmTfjyyy9ZunQpkydPRlGUSvtlZmZSVlbGp59+yqeffmoxpl9++YX77ruP4cOH89xzzxEcHIxGo2H27NlG4yrK+fn5Vdrm5ORk9e9Qo9Hw0EMP8emnn5KVlYW3tzfz588nJCSEQYMGGfb73//+R3h4OEuWLOHdd9/F2dmZQYMG8f777xsNYL1aZGQkCQkJFmMoV/4+N/U6hIaGsnr1aqNtrq6uODs7G21zcnIyeh9lZGQQGhpqcsxJucTERHr27ElMTAyffPIJUVFRODs7s3PnTh5//HGj5/CBBx7g2WefZf78+cyYMYOjR4+ya9cuZs2aZdNjNMXJyYlHH32UDz/8kPfff5/S0lKWLl3KM888g5OTk13HmjBhAuPGjeOjjz7CxcWFe++91+R+aWlpCCEICgoyeXvDhg2Ba/ucv/q9WP4YqiMhrg0yuaknHBwceP311/n44485fPgwgOEie/78eSIiIkze7/Dhwxw4cID58+czZswYw/b4+Pgqicvf3x8XFxeTH+Tlt1dk6mJiibOzsyHBs5Wfnx9lZWVkZGQYJSJCCFJTU+nUqZNdx6vu44J+oLilx1ndz/O18vf3x8/Pj5UrV5q8vWIrhaVj1NRjGzduHK+++iqKohj9PVTk4+ODWq3moYceMtsqGh0dDcB3331HdHQ0S5YsMYrr6sGyVWHcuHG8//77LF68mBEjRvD7778zefJk1Gq1YR83NzemT5/O9OnTSUtLM7Ti3HHHHRw/ftzssQcNGsSnn37K9u3brc6oK78opqSkVLotOTm50utli4CAADZv3oxOpzOb4Pz222/k5+fzyy+/GFokAPbv319pXx8fH4YOHcqCBQt4++23mTdvHs7OzowcOdLu2CqaNGkS77zzDnPnzqWoqIiysjImTpxo93HuvvtuHn/8cd555x0eeeQRs7P9/P39URSFTZs2mUygyrdV9+d8fSSTmzooJSXF5Lei8qbF0NBQAAYOHIharWb27Nl07drV5LHKP3Cv/sP48ssvK+1rKXM39+3y9ttv57///S9+fn6GD/za1r9/f9577z2+++47pkyZYtj+888/k5+fbzQd2JZvzddy3KpWF59n0Me1ePFitFotcXFxFvetC++hMWPGsGPHDmJjY81Or3d1daVv377s27eP1q1bm22VAv3fl6Ojo1Fik5qaanK21PWKjY0lLi6OefPmodVqKS4uZty4cWb3DwoKYuzYsRw4cICZM2dSUFBgttVzypQpzJ07l8cee6zSVHDQJ/C//fYbw4YNo2vXrri4uPDdd98xfPhwwz7nz59n3bp1ZlshLBk8eDCLFi1i/vz5ZrtoTH2WCSHMdlGPGzeOpUuXsnz5cr777juGDRuGt7e3xTistV6EhIQwfPhwZs2aRUlJCXfccQeRkZHWHl4lLi4uvPbaa2zcuJFJkyaZ3e/222/nnXfe4cKFC9x3331m97Pnc/5mIZObOmjQoEGEh4dzxx130KxZM3Q6Hfv37+fDDz/E3d2dp59+GtBPr3355Zd56623KCwsNEzrO3r0KBcvXmT69Ok0a9aMRo0a8eKLLyKEwNfXlz/++KNS0zFAq1atAPjkk08YM2YMDg4OxMTE4OHhQatWrVi8eDFLliyhYcOGODs706pVKyZPnszPP/9Mr169mDJlCq1bt0an05GYmMiqVauYOnWq1YteVRswYACDBg3ihRdeICcnh+7du3Pw4EFef/112rVrx0MPPWT0mE09rus9blWri88z6KdRf//99wwZMoSnn36azp074+DgwPnz51m/fj1Dhw5l2LBhgPnnuiYfW2hoKL/99pvV/T755BN69OhBz549mTRpElFRUeTm5hIfH88ff/xhGH91++2388svv/DYY49x7733kpSUxFtvvUVISAinTp2qkpgrGj9+PI8++ijJycl069aNmJgYo9vj4uK4/fbbad26NT4+Phw7doyFCxfStWtXi9250dHRhhahtm3b8sQTT9CuXTsAjh49yty5cxFCGBKEadOm8fLLLzN69GhGjhxJZmYm06dPx9nZmddff93uxzVy5EjmzZvHxIkTOXHiBH379kWn0xkS0fvvv58BAwbg6OjIyJEjef755ykqKmL27NlcvnzZ5DEHDhxIeHg4jz32GKmpqRYTwXIeHh40aNCAZcuW0b9/f3x9ffH39zcqW/D0008b3o8Vx0DZ65lnnuGZZ56xuE/37t35z3/+w7hx49i9eze9evXCzc2NlJQUNm/eTKtWrZg0aZJdn/M3jdobyyyZs2TJEjFq1CjRpEkT4e7uLhwcHERkZKR46KGHxNGjRyvtv2DBAtGpUyfh7Ows3N3dRbt27Yxmfhw9elQMGDBAeHh4CB8fHzF8+HCRmJhoclbASy+9JEJDQ4VKpRKAWL9+vRBCiLNnz4qBAwcaqr1WHNGfl5cnXn31VRETEyMcHR0NU2inTJliNFUREI8//rjNz4O5qeBXM1WhuLCwULzwwguiQYMGwsHBQYSEhIhJkyaJy5cvG+1n6XGZYutxr2W2lDVV8Txf/ZqXzwC5eqZS+YyKjIwMq7GWlpaKDz74QLRp08bwHmzWrJl49NFHxalTpwz71dX3kKnZUkIIkZCQIMaPHy/CwsKEg4ODCAgIEN26dRNvv/220X7vvPOOiIqKEk5OTiI2NlbMmTPH8PxVZC72Bg0aiDFjxtj0eLKzs4WLi4vZmUUvvvii6Nixo/Dx8RFOTk6iYcOGYsqUKYap4tacPn1aPPbYY6Jx48bCyclJuLi4iObNm4tnnnmm0izKr7/+WrRu3drweg0dOtSo2q8Q5t/bpp6fwsJC8dprr4kmTZoIR0dH4efnJ/r16ye2bt1q2OePP/4wvM/CwsLEc889J1asWGH0WVXRyy+/LACT0+iFqDxbSggh1qxZI9q1ayecnJwEYPK1iYqKErGxsZW2m1NxtpQlpqaCCyHE3LlzRVxcnHBzcxMuLi6iUaNGYvTo0WL37t2GfWz9nDf3t13+WWBqtmx9pAhhYsEVSZIkSZIqOXjwIG3atOHzzz/nscceq+1wJDNkciNJkiRJVpw+fZpz587x8ssvk5iYSHx8vNWZm1LtkXVuJEmSJMmKt956iwEDBpCXl8ePP/4oE5s6TrbcSJIkSZJ0Q5EtN5IkSZIk3VBkciNJkiRJ0g1FJjeSJEmSJN1QbroifjqdjuTkZDw8PGqsRL0kSZIkSddHCEFubq7VdcjgJkxukpOTza7DJEmSJElS3ZaUlGRxwWi4CZOb8oX8kpKSjFZdliRJkiSp7srJySEiIsKmBXlvuuSmvCvK09NTJjeSJEmSVM/YMqREDiiWJEmSJOmGIpMbSZIkSZJuKDK5kSRJkiTphiKTG0mSJEmSbigyuZEkSZIk6YYikxtJkiRJkm4oMrmRJEmSJOmGIpMbSZIkSZJuKDK5kSRJkiTphnLTVSiWJEmS6q6U7EJ+3nOepEuFeLs6cEebUFqGedV2WEYycotZuO0sP++9QHZhKZG+rjzQJZJ7O4TjpFHXdngSoAghRG0HUZNycnLw8vIiOztbLr8gSZJUh3y+Pp4PV50AQKUoCECrE9zaMpiZI9ri7FD7iUN8eh4jvtzG5YISdFeungoggI4NfFg4IQ4Xx9qP80Zkz/VbdktJkiRJtW7JrkTe//sEOgE6AWU6gfZK9rDqSCqv/HqoliMEIQSTvttDVmGpIbEBfWIDsDfxMu//faJWYpOMyeRGkiRJqlU6neCTtafM3y7gl30XuJBVWINRVbYj4RKn0vMMSdfVdAIW70qkoKSshiOTriaTG0mSJKlWHUvNITmryPJOAtYeS6uZgMzYl5iF2sqC1AUlWk6l5dVMQJJZMrmRJEmSalVRqdbqPipFobDE+n7VSa36twvK8n5WMiCp2snkRpIkSapVUX5uVhMCrRA0DfKooYhM69E4ADM9Uga+ro61HqckkxtJkiSplvm5OzGkZbDZBEelQLCnM72aBtRwZMaah3rStaGfxURsQs9oHDXy0lrb5CsgSZIk1bpptzcn0MOpUuKgViloVCr+N7Jdneju+XRUO5oEugP6pAv+7Ya6p30YE3s3qq3QpApknRtJkiSpTriYV8xn6+JZujuJghItakVhUMsgnujbhOahdefzurhMy8rDqfy27wKX8kuI9nfj/s6RxEX7oii1n4DdqOy5fsvkRpIkSapTSrU6sgtLcXfS1InCfVLdYM/1Wy6/IEmSJNUpDmoV/u5OtR2GVI/J5Ea6PiUFcG4LlBZAQCwENK3tiCRJkqSbnExupGuj08GmD2DLJ1BSoWBVZBe483Pwb1x7sUmSJEk3NTlbSro2f78E6//POLEBSNoF39wCl8/VTlySJEnSTU8mN5L9Mk/Dji9M3ya0UJwDmz6s2ZgkSZIk6QqZ3Ej2O7AYFAszGHRaOLgYykpqLiZJkiRJukImN5L9cpPBWi2HsmJ9C44kSZIk1TCZ3Ej2cw/C6vJxakdwknWEJEmSpJonkxvJfm1G6ruezFGpodVw0DjWXEySJEmSdIVMbiT7+TeBDmMBE11Tihoc3KDn1JqOSpIkSZIAmdxI1+q2j6DHFNA4G28PbgXj/wY/uXicJEmSVDtqPbmZNWsW0dHRODs706FDBzZt2mTT/bZs2YJGo6Ft27bVG6BkmkoNt7wOz56C+xbCsK/g0Y3w6D8Q1Ly2o5MkSZJuYrWa3CxZsoTJkyfzyiuvsG/fPnr27MngwYNJTEy0eL/s7GxGjx5N//79ayhSySxnT2h+J7QZASFtajsaSZIkSardVcHj4uJo3749s2fPNmyLjY3lrrvuYsaMGWbvd//999OkSRPUajW//fYb+/fvt/mcclVwSZIkSap/7Ll+11rLTUlJCXv27GHgwIFG2wcOHMjWrVvN3m/evHmcPn2a119/3abzFBcXk5OTY/QjSZIkSdKNq9aSm4sXL6LVagkKCjLaHhQURGpqqsn7nDp1ihdffJHvv/8ejca2NT9nzJiBl5eX4SciIuK6Y5ckSZIkqe6q9QHFylWVboUQlbYBaLVaRo0axfTp02natKnNx3/ppZfIzs42/CQlJV13zJIkSZIk1V22NX9UA39/f9RqdaVWmvT09EqtOQC5ubns3r2bffv28cQTTwCg0+kQQqDRaFi1ahX9+vWrdD8nJyecnJyq50FIkiRJklTn1FrLjaOjIx06dGD16tVG21evXk23bt0q7e/p6cmhQ4fYv3+/4WfixInExMSwf/9+4uLiaip0SZIkSZLqsFpruQF45plneOihh+jYsSNdu3blq6++IjExkYkTJwL6LqULFy6wYMECVCoVLVu2NLp/YGAgzs7OlbZLkiRJknTzqtXkZsSIEWRmZvLmm2+SkpJCy5YtWb58OQ0aNAAgJSXFas0bSZIkSZKkimq1zk1tkHVuJEmSJKn+qRd1biRJkiRJkqqDTG4kSZIkSbqhyORGkiRJkqQbikxuJEmSJEm6ocjkRpIkSZKkG4pMbiRJkiRJuqHI5EaSJEmSpBtKrRbxkyRJkuq2lOxC1hxNo6BES5Mgd3o3DUStqry4sSTVJTK5kSRJkiopLtPy+rIjLN2dhBCgUkArIMjTiY9HtKVbI//aDlGSzJLdUpIkSVIlz/90kCW7k9AJEOgTG4CM3GLGzN3J4QvZtRqfJFkikxtJkiTJyMm0XJbtT8bU4jw6ATodzFxzquYDkyQbyeRGkiRJMvL7/mSL42q0QrD2eBp5xWU1GJUk2U4mN5IkSZKRrMISrA0ZFgJyi0prJB5JspdMbiRJkiQj4T6u6Ez1SVXgpFHh4+pYQxFJkn1kciNJkiQZubt9GIpivu1GrVK4p0M4zg7qGoxKkmwnkxtJkiTJSKCHMy/cGmPyNrVKwd/dkcn9m9RwVJJkO5ncSJIkSZX8p1cj3r+3NeE+LoZtKgUGNg/i18e6E+jpXIvRSXWBTie4mFdMdmHdG3sli/hJkiRJJg3vGME97cM5nppLQUkZDfzcCPBwqu2wpFpWqtXxzeYE5m9JIDWnGIDW4V481qcRt7YMqeXo9BQhrIwau8Hk5OTg5eVFdnY2np6etR2OJEmSJNUbpVodD3+7m40nM6iYPKgUfQ2kFwc3Y2LvRtVybnuu37JbSpIkSZIkm/y4+3ylxAb0iQ3AuyuOcyYjr8bjuppMbiRJkiRJssm3285avF2lUli0M7FmgrEUR20HIEmSJElS/XA6Pa9Sq01FWp3gZJpsuZEkSZIkqZ6wVttIpYCrY+3XP5LJjSRJkiRJNhnSKtjiumM6Abe2DK7BiEyTyY0kSZIkSTZ5uGdD1IqCqQLWapVCA19XmdxIkiRJUnVKuJjPxpMZHDyfhU53U1U+qRZNgzyYO7YTbo76MnkalYLmSktOtL8bP/ynC06a2u+WkkX8JEmSbiI6neCfUxlsO52JTifo0MCHW5oH4aC+sb7rHr6QzRu/H2H3ucuGbRE+LrwwuBm3tw6txcjqvx5N/Nn5Sn/+OJDMgfPZOKpV9IkJoFeTAFQWuqxqkiziJ0mSdJM4ezGfcfN2kpBZYPi2XaYTBHs68/WYjrQM86rlCKvG0eQc7pm9leIyLaYaa967pzX3dYqo+cCk6yKL+EmSJElGcotKuf+r7SReLgT0SU3ZlSt/Rm4xo+ZsJy2nqDZDrDJv/3WUkjKdycQGYPqfRygs0dZsUFKNksmNJEnSTeCXvRdIyylCa+KKrxWCvOIyvt9+rhYiq1rJWYVsPZ2J1kKnRH6xlr+PpNZgVFJNk8mNJEnSTeCPg8kWb9cJWLbf8j71QUq29dYntUrhQlZhDUQj1RaZ3EiSJN0E8orKLFaWBcgrLquRWKqTn5uj1X10OmHTflL9JZMbSZKkm0BMsIfF4mtqRT/Nt76L8nejZagnlibtaNRKnajFIlUfmdxIkiTdBEZ1jjQ53qacVsBDXRvUYETV56UhsQCYy2+e6NsEb1fZcnMjk8mNJEnSTaBztC+jryQvV1/0FfRl9W9tcWO0ZnRv7M+c0R3x93AC/n28zg4qnh3YlKf6N6694KQaIevcSJIk3SSEEPywM5Ev/zlD4qUCAII9nRjfI5oJPRpa7Laqj8q0OjadukjipQK8XR3oHxuEu5OsXVtf2XP9lsmNJEnSTUYIQVpOMTohCPJ0vuGSGunGZM/1W6awkiRJNxlFUQj2cq7tMCQbFJVqKSrV4uHsIJNQO8jkRpIkSZLqmH2Jl/l8/WnWHk9DCPB2deCBuEgm9m6Eh7NDbYdX58kBxZIkSZJUh6w9lsa9X2xj/Yl0ygeOZBWUMnvDae6dvY3swtLaDbAekC03kiRJklTD4tNz+W57InvOXUajVujfLJARnSJxd9Iwecl+dDpRqeiiTujv98maU7x2R/Naibu+kMmNJEmSJNWghdvP8dpvh1GpFEPtoQNJWczecJpx3aPJLTJfKVorYPGuRJ6/NQZnB3VNhVzvyG4pSZIkSaohOxMuMe23wwgwKqqoE1BYquXLjafRWBk4XFCiJdWGNbRuZjK5kSRJkqQa8vXmM2ZnPekElGoFOhsqtLg4ylYbS2S3lCRJkiTVkM2nLlpcBgP0SY45KgWah3gS5Cmn8lsiW24kSZIkqYbY0irj7eKAWjHfuvNk/yZVHdYNRyY3kiRJklRDOjTwMZu4gL5lZlRcJJ2ifQDQqBQ0KgWVAmqVwptDWzDoBlkDrDrJbilJkiRJqiETekSzJT7T5G0K+gRmTLconhsUw+5zl1l+KIW8ojIaBrhzb4dwAq4sBipZJpMbSZIkSaoh/ZoF8UTfxny2Ph51hangapWCAnw6sr1hPE2nKF86RfnWYrT1l0xuJEmSJKkGPTsohi4N/Zi3NYF9iVk4qBX6xwYxrlsUTYI8aju8G4JMbiRJkiSphvVo4k+PJv61HcYNSyY3kiRJkiRdFyEEa4+lM3/rWQ6ez8JBreKW5kGM7x5NTHDNt0bJ5EaSJMlGe85dZs6mM2w4kU6ZVtAqzIux3aO4s00oioUZMJJ0IxNCMP2Po8zfeha1oqC9Mt39pz3n+XnPeWY90J6BNTzDSxHChkn3N5CcnBy8vLzIzs7G09OztsORpJuWEIK/j6Qyd4v+m55GpaJfs0Ae7hlN63Dv2g6vkp/3nOfZnw6gUv4dBKpS9HVHRnaK4L93t7phEpzU7CJ+2JnIhuPplAlB5yhfHuzSgMaB7rUdmlQH/XUwhcd/2GvyNgVw0KjY+mI//N2vb6aXPddvmdxIklTjhBC8/vsRFmw7h1rRLwYI+hkjQgg+HtGWoW3DajfICi5kFdLr3fWGb6SmfDqyHXe0Ca3BqKrHlviLTPh2FyVlOkOlXLVKQScEM4a14v7OkbUboFTn3D1rC/uTssxWVlYp+kHUj/VpfF3nsef6LYv4SZJU41YcTmXBtnPAv4kN6BcS1Al4ZukBUrILaym6yhbvTERgPrFRKTBvS0INRlQ90nOLmPDtLoorJDagf12EgJd+OcT+pKxai0+qe4QQHEjKtrhkhE7A3nOXay4oZHIjAaQchMO/QPwaKJUrzUrVb+6WBCwtfCyEYNHOpJoLyIoDFr6Vgv7D+9CF7JoLqJos2ZlESZkOcw1UKpXC3M31P4mTqpbKSiahXKmuXJPkgOKbWfJ++P1JSD347zZnL+j9AnR5TP+OlKRqcOi89W96+xNr9pueJY4aFQpYaLsBB3X9/664Of6ixddFqxNsPJVRcwFJdZ6iKPRo4s/Gk+YXBBUCejQJqNG46v9fo3Rt0o7CvMGQdsR4e1E2/P0ybHy/duKSbgoqK9/iFOpWstAnJtBiYqNWKfRrFlhj8VQXS2OKytmy8KN0c3mkZ0OziY1KAW9XB4a1q9kxdHXn00OqWWvfhLJiEFrTt//zDuTJb2hS9egbE2C1mbpPTM1+07PkrnZh+Lk5ojYTshCCh3s2rNmgqkHnKF+L3YVqlULnKL+aC0iqF7o18uetoS0Ma2OVUwAPZw0LxnfG3almO4pkcnMzKrgEJ1eaT2xA3454+Keai0m6qTzcs6HZFgCVAl6uDtxVw9/0LHF30vDdw3F4uzoC//bYlq/U/PGItrSN8K69AKvIqLhIVIp+jSNTtDrB+O5RNRmSVE881DWK1c/0ZnTXBrSL9KZLtC+v3BbLP8/1rZXSDnLMzc0oPwPLowcARQ25KTUSjnTzaR/pwwf3tuH5nw4i0M+QKr+gero48N2EODycHWo1xqvFhniy6YW+/LYvmQ0n0inR6mgT7s3IzpEEeznXdnhVItzHlZn3t+XpRftBwWhRR61O8NygGLo1lksGSKY1DnTn9Tta1HYYgExubk6u/mBteKTQgnvNVpSUbi73dAgnrqEvi3Ymsi8xC0e1ir7NAhnWPgzPOpbYlHN11DAqLpJRcTdurZfbW4fSJNCD+VvPsv5EOlqtoGOUD2O7RRHXUHZJSfWDLOJ3s/r+Pv3Ub3NdUyo1TDkGHkE1G5ckSZIkmSCL+EnW9Z8GagdQzLwFekyViY0kSZJUL8nk5mYV3ArGLgf/GOPtTh5wy3To+3LtxCVJkiRJ10mOubmZhXeAx7ZB8l7IPK1PbKJ7g6NrbUcmVbWyYji7WV/HyK8RBLeWRRptoNMJzmbmU6oVNPBzxdlBXdshSZJkg1pvuZk1axbR0dE4OzvToUMHNm3aZHbfzZs30717d/z8/HBxcaFZs2Z8/PHHNRjtDUhRIKwDtL4PYgbLxOZGIwRs/wI+aArf3Q0/jYMve8EXPeH8ntqOrs4SQvD9jnP0fG89/T78h0EzN9L+rdW89edR8ovLajs8SZKsqNXkZsmSJUyePJlXXnmFffv20bNnTwYPHkxiYqLJ/d3c3HjiiSfYuHEjx44d49VXX+XVV1/lq6++quHIJame2PwRrHwBirKMt6cfgflD9OuKSZW89/cJXvn1MMlZ/y7eWVCiZd6WBEbN2U5hiYUaUZIk1bpanS0VFxdH+/btmT17tmFbbGwsd911FzNmzLDpGHfffTdubm4sXLjQpv3lbCnpplFwSd9ioys1fbuihkZ94cGfazauOu5Eai6DZm40e7uiwCtDYm+IisSSVJ/Ui9lSJSUl7Nmzh4EDBxptHzhwIFu3brXpGPv27WPr1q307t27OkKUpPrt8M+gs9CFIrQQvxby0msupnpg8a5Ey0tDCFiw7VzNBSRJkt1qbUDxxYsX0Wq1BAUZTzcOCgoiNTXV4n3Dw8PJyMigrKyMN954g4cfftjsvsXFxRQXFxt+z8nJub7AJam+yE0FlcZ8yw0AAvLSwL3+L/pYVRIu5ptdBBD0pS/PXy6ouYAkSbJbrQ8oVq6asSGEqLTtaps2bWL37t188cUXzJw5k0WLFpndd8aMGXh5eRl+IiIiqiRuSarzPIItrx8GgAJuMrGpyNPZwewCmeXcHOVEU0mqy2otufH390etVldqpUlPT6/UmnO16OhoWrVqxSOPPMKUKVN44403zO770ksvkZ2dbfhJSkqqivAlqe5rcbd+XI05ihoa9au2Yo0FJWWsP57O8kMpnM7Iq5ZzVIfbW4egtTASUa1SGNoutOYCkiTJbrX29cPR0ZEOHTqwevVqhg0bZti+evVqhg4davNxhBBG3U5Xc3JywsnJ6bpilaR6yc0Pej8P6/+v8m2KSt9l1X9alZ9WpxN8svYUczadoaDCrKLO0b68d09rovzdqvycValfs0BahnpyLDW3UveUSgEnjYpH5GBiSarTarVb6plnnuHrr79m7ty5HDt2jClTppCYmMjEiRMBfavL6NGjDft//vnn/PHHH5w6dYpTp04xb948PvjgAx588MHaegiSVLf1eg4Gvg1OV80s8G8KY/+E0HZVfsrXfz/C/9aeMkpsAPacu8ywWVu4UGF6dV2kUatYMCGOTlE+gL6lRnNlgHGghzPfPxxHA7+6naBJ0s2uVjuOR4wYQWZmJm+++SYpKSm0bNmS5cuX06BBAwBSUlKMat7odDpeeuklEhIS0Gg0NGrUiHfeeYdHH320th6CJNVtigLdnoROD8OZf6A4B3wbQVj7aqlQHJ+ex8LtpmcSaXWCnKIyZm+I5+27WlX5uauSr5sji//TlcMXsll/PJ1SrY5W4d70axZoeSaVJEl1glwVXJKkKvPuyuN8tfGMxdlGzg4qDr8xCI261uczSNJNbd3xNOZtOcvec5dRqRT6NA1gQs+GtI3wru3QTLLn+i2H/EuSVGXScor0Sz5YUFSqI79Yi5erTG4kqba8s+I4X/xzGrWioL3yN7v8cCp/Hkrh/XvbcG+H8FqO8PrITxdJkqpMgIeT1e4uJ40KNye5AKUk1Zb1J9L54p/TAIbEBvRdx0LA8z8dIDGzftdyksmNJElV5p724Ra7pNQqhbvbh8kuKUmqRfM2J1gcO6ag8P2O+l2FW37CSJJUZZoGeTCiYwSmPjbVKgU3JzWP9Wlc43FJVSOroISEi/nkFFmqei3VdfuSsix+CdEKwZ7EyzUYUdWTY24kSapS/zesJT5ujszbkkBxmc6wvWWoJx/e14YIX9dajE66FocvZPPhqhNsOJGBQJ+oDm4ZzLMDY+p83SKpMltm/Dmo6nfbh0xuJEmqUhq1ihcHN+Oxvo3YGn+RolIdTYM8aB4qZyfWR7vPXmLUnB1ohaD8u75WJ1hxOJWNJzP45bFuNA70qNUYJfv0jQnk9wPJZltvFAX6xATUcFRVq36nZpIk1Vmezg7c2jKEu9qFycSmnhJC8MzSA5TpdJUuhFqdIL9Yy6u/Ha6l6KRrNaFHNOaqwKgU/dppwzvW73UYZXIjSZIkmbQj4RKJlwowNzxDKwTbz1zi7MX8mg1Mui4tw7z4eERb1CrFaJFYRQFXRw3fju+Er5tj7QVYBa6pW0qn0xEfH096ejo6nc7otl69elVJYJIkSVLtOpNhW9KScDFfjr2pZ4a2DaNjlC8/7DjHnnOX0ahU9Grqz30dI/B2rd+JDVxDcrN9+3ZGjRrFuXPnKjVrKYqCVqs1c09JkuqbMq2O7MJS3Jw0ODvI2jQ3G1vrEbk5yeGb9VGYtwvPDWpW22FUC7vfkRMnTqRjx4789ddfhISEoFTD+jSSJNWuS/klfL4+nsW7Eskv1qJSYEDzIJ7s14SWYV61HZ5UQ/rEBOKoVlGi1Zndx9/dkfaR3jUXlCTZwO7k5tSpU/z00080bixrVUjSjehiXjHDPt9CclaRoXqpTsCaY+msO57Ot+M7062Rfy1HKdnjcn4Ja46lkV9cRnSAOz0a+9s0HdjLxYFHekUza/1pzFVFmXxLU1mUUapz7E5u4uLiiI+Pl8mNJN2gZiw/RnJ2kVFZdrhSml2BpxfvZ9uL/eQFrR7Q6gTvrjzO3C0JlGkFiqJf+ivEy5kPh7ehW2PrSeozA2IoLNEyb+tZFPQ1UrQ6gUpReGZgUx6Ii6z+ByJJdrI7uXnyySeZOnUqqamptGrVCgcHB6PbW7duXWXBSZJUs7ILSlm233z9C52AjNxi1h5PZ1CL4BqOTrLXm38cYcG2c4ZWl/J8NS2niNHzdvLTxG5WV4BWqxReu6MFE3o25Pf9yWTmFRPi7cLQtqH4uztVa/ySdK0UYW6yuxkqE1ULFUVBCFEvBhTbs2S6JN1sDp7P4s7PtljcR6NSmHxLE57o16SGopKuxfnLBfR8b73ZRdpVCnRv7M/CCXE1G5gkXSN7rt92t9wkJCRcc2CSJNVtLjbMiNIJIWdO1QN/HEhBAbNjZXQCNp26yKX8knpf00SSrmZ3ctOgQYPqiEOSpDqgcaA7kb6uJF4qMLuPEDCwueySqusuF5SgVinotJYb5y8XyORGuvFcc3GCo0ePkpiYSElJidH2O++887qDkiSpdiiKvsvpmaUHTN6uUuC21iFE+snFL+u6MG8Xyiys/Az68TQBHnLcjHTjsTu5OXPmDMOGDePQoUOGsTaAod5NXR9zI0mSZXe3Dyc9t5j3Vh4HQHXlb7tMJ+jXLJD37mlTm+FJNrqzTShv/3WUUjMtN2qVwpCWwXg6O5i8XZLqM7vncj799NNER0eTlpaGq6srR44cYePGjXTs2JENGzZUQ4iSJNW0ib0bsfXF/kwdGMM97cMZ1z2K35/oztdjOuHiKMfb1Ac+bo68cKvp6rNqlYK7k4ZnB8XUcFSSVDPsni3l7+/PunXraN26NV5eXuzcuZOYmBjWrVvH1KlT2bdvX3XFWiXkbClJkm4mP+5O4qPVJ0nJLgJAAXo08Wf6nS1oGOBeu8FJkh2qdbaUVqvF3V3/B+Hv709ycjIxMTE0aNCAEydOXFvEkiRJUrUY3jGCe9qHc+hCNnnFZTTwcyXcR46Zkm5sdic3LVu25ODBgzRs2JC4uDjee+89HB0d+eqrr2jYsGF1xChJkiRdB5VKoY2VYn2SdCOxO7l59dVXyc/PB+Dtt9/m9ttvp2fPnvj5+bFkyZIqD1CSJEky7UhyNt9uPcv2M5dQKdCraQCjuzagcaBHbYcmSbXK7jE3ply6dAkfH596sUK4HHMjSdfmXGY+i3clkZCRj4ezhiGtQ+jdJACVDQswSqal5RRxIjUXR42KthHedhVH/G77Oab9dhjVlbWeAMNimP+7vx23tQ6plpglqbZU65ibcvHx8Zw+fZpevXrh6+tLFeRIkiTVUZ+vj+eDv0+gUinodAKVSuHHPedpE+7F/HGd8ZFF4OySllPEtGWHWXM0jfJSNJ7OGh7t3YhJvRtZTRgPns9i2m+HEWC0Dlj5/59avI+WYZ408HOrrocgSXWa3VPBMzMz6d+/P02bNmXIkCGkpKQA8PDDDzN16tQqD1CSpNr1274LvP/3CcOFtOIF9XByDpO+31Or8dU3l/JLuHvWVtYeS6dijb2cojLe//sEr/9+xOox5m85azUB+n5H4vWGKkn1lt3JzZQpU3BwcCAxMRFX139H3I8YMYKVK1dWaXCSJNUuIQSfrjuFucuoVifYfuYSB89n1WRY9dpXG8+Qml1oduX1hdvPcSI11+Ixtpy+aPb+oH9dNsdfvK44Jak+szu5WbVqFe+++y7h4eFG25s0acK5c+eqLDBJkmrfhaxCTmfkm118EfTjPNYeS6+xmOozIQSLdiZiabknBViyy3Kriy2jnORIKOlmZndyk5+fb9RiU+7ixYs4Ock1SiTpRlJSprO6jwIU27CfBCVaHdmFpRb3EcCaY2kW9+ne2N8weNgUtUqhR2P/awmRgpIyFu1M5D8LdjN23k4+XHWCC1mF13QsSaotdic3vXr1YsGCBYbfFUVBp9Px/vvv07dv3yoNTpKk2hXq7YK7k+V5B2U6QYtQOfPQFo5qFS42zIhKvFRIwsV8s7eP6x6Nzky3lHLl58EuDeyO72RaLr3eW89Lvxxi9bE0NpzI4PP18fR6dz0/7Tlv9/EkqbbYndy8//77fPnllwwePJiSkhKef/55WrZsycaNG3n33XerI0ZJkmqJs4OakZ0jMNdIoFLA182RQS2CazawekpRFO5qF2p1P5UCv+41n0y0DPNixt2tUBSMWnDUKgW1SuGzUe2I8LWvCnFhiZYHvt7B5QJ9y1L5BFidAK0QPPfTAXafvWTXMSWpttg9Fbx58+YcPHiQ2bNno1aryc/P5+677+bxxx8nJETWVZCkG83kW5qy7XQmR5JzjMbeqFUKGpXC56Pa46ix+3vSTWtExwgW7UyyuI9KUcjIK7a4z/2dI2kX6cOCbWfZdjoTlUqhV5MAHuragGh/+6eA/3EgmYxc8+dUKQpzNp2hY5SvydvLtDrWHk9n3bF0SrQ6mod4cm+HcFkmQKoV11TnJjg4mOnTp1d1LJIk1UFJlwtIyymqNKhYAd4a2oKujfxqI6x6KzbUEwe1QqmFUcUCCPJ0tnqsmGAP/m9YqyqJ66e9lhMurU6w7rjpgePnLxfw0Dc7SbiYr29JEoLf9l/g/VUnmDmiLUNayS++Us2yOblJTLStZkJkZOQ1ByNJUt2SXVjKA3N2kFVQUuk2rRBMW3aEztF+RF1DS4Gtikq1nM7IQ0GhcaB7vW8lctKoGdYujJ/3XjA7nVunE9zdLtzkbdXh8/Xx7Ey4bHU/rU4ghDCqRl+q1fHg1ztIulxo2MdwW5mOJ37Yy8+TutEu0qfqA5ckM2xObqKjow3/L69GXPENXv6G12q1VRieJFWNU2m5zNl0hhWHUikq09Ik0IPRXRtwb4dwNOr6fbGsTj/vOc+l/BKTU8GF0A8mnr/1LG/c2aLKz11SpuN/a0+xYNtZcorKAPB2cWBc92ge79uoXr9uT/ZrworDqeReeVxXm9Ajmki/mlm5e/fZS7z/9wmr+6kUaBHqVWmZnVVH0jibWWDyPgJ9d9aXG8/wxYMdqiJcSbKJzcmNoiiEh4czduxY7rjjDjSaa165QZJq1KZTGUyYvxutEIZvlcdSc3jxl0OsOZbGFw92qNcXyur095FUizVutDrBisMpVZ7caHWCRxfuZsPJDCqu7JJVWMrMNSc5nprD56Pa19t1rVwd1bg6qs0mN4GeNVdWY96Ws6grrE9ljk7AuO5RlbavPppq8f5anWDN0bRKLT6SVJ1s/kQ/f/48kyZNYsmSJdx2220sXLgQR0dH2rRpY/QjSXVJfnEZk77bS6lOZ/ThW37BXHssnflbz9ZOcPVAQYn1ltji0qqvcbP8UArrTxgnNuUEsOJwKutP1N/CgZ+tj+diXuWuvnLvrjhBem5RjcSy+9wlq4kNwD3twxjWLqzS9qJSndlp6eXKdAIbTiFJVcbm5CY4OJgXXniBY8eO8dNPP3H58mXi4uLo0qULc+bMQaeTRbykuuf3A8nkFZeZvEiC/kI5d0uCXPjVjFZhnhaLxakUaF4NNW5+2JFodvo56Gdq/VBP104q1epYsivJYkIhEPy850KNxGPp9S0X7uPCB8PbmGx5iQ3xxFKDjAI09Hez6TySVFWuqS2+R48efPPNN5w6dQpXV1cmTpxIVlZWFYcmSdfvQFIWGisfqslZRWQVWK4ae7N6oEsDixdhnYDRXaOq/LwJF/MtftPX6oTFInd12eWCEqstYipFIfGS6XEsVa1/syCrCeywdmFmu5RGdIpAsbLYw1gT3VmSVJ2uKbnZunUrDz/8ME2bNiUvL4/PP/8cb2/vKg5Nkq6fg41jaTRq+a3SlBahXjw7sCmAUUtK+X/v6xjOoBZBVX5eb1cHi7crgJeVfeoqdyeNxVYp0LcoerrUzLjGMd0aGKoaX01R9H9Do+LMz4IN9nLmv3e3RMG4Faj8mH1iAhjVWc6ilWqWzclNSkoK7777Ls2aNWPYsGF4enqydetWdu7cycSJE1Gp5IBMqe7pExNAmYUmAJUC7SK88XCunxfKmvBEvyZ8+VAHo6m8TYLcee+e1rx7T+tqGSSqbymwvM/dJsZ/1Aeujhr6xwahtvAAtTrBnW2sVzKuCo0DPfhsVHs0asUo6VIp4KRR8fWYjoR4uVg8xohOkXz/cBzdGvkZkqRwHxdevb05X43uKAfsSzVOETYONnB0dCQ0NJQxY8Zw55134uBg+mLQunXrKg2wquXk5ODl5UV2djaennI9nBudVie45aN/SLxUYLZ75cuHOsjlA2xUXKZFpwMXR+vrI12P7IJSBs3cSEZecaXXTa1SCPVyZuXkXrhZWfequqTnFLHicCrZhaVE+royqEWwXc/JofPZDJu95UrdGOPbVArcEhvEV6M7VnHUlqVkF7JoRyI7Ei6hAD2a+DOiUyQBHvbN3Cop01Gm0+HioJazo6QqZc/12+bkpmLLTPkb9uq71oc6NzK5ufkkXSpg1JztJF0uRKXox4mUT119aXAzHu3dqLZDlExIzCzgPwt3czw190rVW33hwNZhXnzxUAdCvS23JlQHrU7w3+XHmLclAQGoFYUyncDdScP/DWvJ0La2tyZtPnWRp5fsIzOvBI1KQSf0ic4dbUJ5797WONuwwObN5nJ+CT/vPc/x1FycHVQMbB5Mj8b+NVYSILuglB/3JLH6aBqFpVpahXnxQFyDahlUL1VWLcnNuXPnbDp5gwb2r0Rbk2Ryc3MqKtWy/FAKfx9JpaBES0yQByPjImkU4F7boUkWCCHYfe4yOxP0CzZ2beRHuwjvWmsReOvPo3yzOcHkbQowZ3RHbmlu+xikUq2OtcfSOZWWi4ujmoHNg2useF99s2z/BZ778SClOh0qRT+EuXxF+vnjOtvdwmSvo8k5PPD1drIKSg21n8q/JD1/awyP9WlcreeXqim5uVHI5KaOu3wWzmwAnRbCO0FI3e7mlG4e6blFdJ2xzmz3pqJA00B3Vk7uVW3JV/n6TquPplJYqqNZsAfDO4YT6GF9Har6bMeZTO6fs91kSQe1SqFZsAd/PNGj2lpwikq19Hh3HZfzSzC3JNjXdia2kv3suX7LMsNS3VCUDb89Bsf/Qj9XRNH/G9YR7p0LPnWrRTDpUgELtp1l1dE0Sst0tInwZky3KLo0lItI3qj+PpJmsVidEHAiLY8zF/OrpUUwNbuI0XN3cDItD7VKQQjBXwfh49Un+e/drbivY0SVn7OumLXhNCrA1KAHrU5wJDmHzfEX6dU0oFrO/9fBFItFF9UKfLnxtExu6hCZ3Ei1T1sGC4dB8n4wNPhe+TdlP8wdBBO3gFvdSBw2n7rIhG93Uab7dzmHtNw0VhxO5cl+jZk6MKaWI5SqQ05hKSoblinIKfy3ZlJecRl/HkjmbGYBni4abm8Vek3dTjqdYOy8nZzO0Nf2qRiDTghe+OkgYd4udG/sb/ex67riMi0bT2ZYXAZEo1JYdTS12pKbLfEXLS8xIWDX2cuUanU2l5+QqpdMbqTad+IvuLDH9G26MshLg93fQO/nazYuE7IKSnhkwW5KtDqjJvLyD71P18XTOtybAfIb3A0n0tfVamKjKBDmox/o/NOe80z77TCFpVoc1PoL4/srT3Bvh3D+b1gru1Y3/+dkBsdTc83erlIUZm2Iv0GTG53FxAb0X4UKS6qvSr5WCJuqmOturlEedZpMMaXad2AJKBZmhggd7Puu5uKx4Kc95ykq05pdzkGtwNebztRsUPVQUamWeVsSuOXDf4h5dQWd3l7NjOXHSMkuvOZjnkrLZfHORJbuSiKpGqr7DmgehKezxmwtXrVKoV9MIIEezqw5msazPx6gsFTfkVKq1a+tJICf9p5n2rLDdp17zbE0i5W2tUKwJT6TotK6PVv1Wng4aQi0MlhYJwQxwdU3OaB9pI/Zv3nQT9+PDfbASSNnuNUVdic3b7zxhs0zpyTJJvnpIKx8KBdk1kwsVuxMuISlr5FaAbvPXpZrVVmQX1zGfV9u480/jnI6I4/iMh0ZeSV8vTmBW2du4oSFFgpTUrOLGPnVdgZ8vJEXfznE8z8fpNd763lkwW6yq3BZDWcHNTPubg0KlQoMqlUKbk5qXr29OUIIPlx1wmwRQiFg6e4kLmTZnsgVlVpvvQAo0d54a/wpisKYblEWqzprVAr3dqi+MUfD2ofh6qg2+5rqBEzo2bDazi/Zz+7k5o8//qBRo0b079+fH374gaKimlm5VrqBeTcAlaVvPAp41Y1qtDZNgpF1yyx6b+VxDl/IRmCcJ2p1grziMiZ+t8fm5DCnqJThX2xl59lLRtsFsO5YOg98s52Ssqq74N/WOoR5YzvRPOTfmRqKAv2aBbLs8R5E+7uReKmAY6m5Fr/pK8CKQyk2n7d5qKfVlbeDPZ3wqKWihtVtQo9o2jfwqZTgqFX6KeHv3tMaXzfHaju/p7MDXz7UEUe1ymiJifJVW0Z2iuCe9nXjM0rSszu52bNnD3v37qV169ZMmTKFkJAQJk2axK5du6ojPulm0O5B/dRvSzqMr5lYrLA2G0qtKHRp6Csrs5qRX1zGkt1JZhfFLF8Qc9tp21rqluxM4nxWocmxMFohOHwhhxWHbU8ibNEnJpC/nurJP8/1Ydnj3dn58i3MGd2RaH83AHKLyqweQydg5pqTPLNkPwfPZ1nd/572YThqVGbzZkWBMd2ijd53RaVaTqbl6hchtZIYVQWdTrD51EWeWbKfUXO2M3XpAbadzqySVkxnBzXfTYjjmQFNjbqoujXy44dHunB3+/DrPoc1PZr4s3JyLx7q0oAgTye8XRzo0tCPLx/qwH/vbiX/5uuY66pzU1ZWxh9//MG8efNYuXIlMTExPPzww4wdOxYvL6+qjLPKyDo3dZAQsHQMHPudSn0+ihoCm8OEv8HRrVbCqyi7sJTu76yjoKTM7AV63rhO9I0JrNnA6omD57O487MtFvdRqxSmDmxqU1G0AR/9w6n0PLO3qxTo0difBRPi7I71WmUVlNDh7TVWBx+D/rHqdIK37mrJg10slzv482AyTy3ap68EX+HYigJdov2YP74TTho1hSVaZq45yfc7Eskr1idaYd4uTOrTiAfiIqvlIlxUquXRhXv452SGYVZR+b+DWgTx6cj2dg2gtkSnE+QWl+GkUckqzjcZe67f1/Vu0+l0lJSUUFxcjBACX19fZs+eTUREBEuWLLmeQ0s3E0WBe7+BHpONExiVA7QeAWP/rBOJDYCXiwNzx3bC2UFt1ERe3lT93KAYmdhYoLahyJoQAgcbF+LNzDdfewT0LSTpucU2HauqeLs6MqRlsE2PVasTCGDab4c5fCHb4r63tw7lx4ld6RsTaHjvhXm78PLgWENiU1Sq5cFvdjBn0xlDYgNwIauQV387zIwVx6/noZk1/fcjbDqVYXhMFf9ddTSNd6rwvCqVgpeLg0xsJIuuqYN2z549zJs3j0WLFuHk5MTo0aP5/PPPadxY/03rww8/5KmnnmLEiBFVGqx0A1M7wC1vQK/n4MJe/RTw4NZ1prZNRZ2jfVn/bB9+2JHI6qNpFJdpaRfpzeiuUbQO967t8Oq0mCAP/NwcLSYlOoHN9UpCvZy5nF9idrCtSoEIn5pfzuDFIbFsO5PJ5YJSm1pwVCqFBdvO8t69bSzu16GBL1+P8UWrE5RqdZUu8It2JrL33GWzz8dXG88wtG0oLUKrrmX9Yl4xP+45b7YlUwj4fsc5Jg9ogqez6QWXJamq2d1y07p1a7p06UJCQgLffPMNSUlJvPPOO4bEBmD06NFkZGRUaaDSTcLRDaJ7QqO+dTKxKRfk6cyUAU1Z/nRP1k7twwfD29a5xEbYWJujJmnUKh7tbX5WiVql0KOxPzHBHjYdb2RcpMVZRDoBwzsYj8coLNFyKb/EpqTjWoV5u/D7Ez24s00oGrVtLThbbRxnBPrnyVTLxXfbLc9kVasUFu9Msvk8tth+JpMyK89lcZmOXQmXLO4jSVXJ7pab4cOHM378eMLCzI8MDwgIQKe78aYkSlJdcC4znw0nMijV6mgR6mU0gFkIwZ8HU5i7OYH957NQodC1kR//6dWw2qq3Auw5d5kF286yLzELR42KAc2DeLBLA8JMrNz9cI+GnL2Yzw87kwzjMspXa28W7MGnI9vZfN47Wofy+rIjFi+uiZcLDDF+tv4UG05kIAR4OmsYFdeAx/o2qpYWhVBvFz4e0ZY3h7bg9v9t5pyV2jvmerEKSsr4ec95ft57gcy8YiJ8Xbm/cyRDWgajuaoabuKlAovJXvmA7apUauP0c1v3k6SqYHdyI4TAx8en0vbCwkLef/99XnvttSoJTJIkY3nFZTz74wFWHk5FQT9USScg2t+Nz0e1JzbEgzf/OMq8rWdRKfruAC2CbWcy2Rx/kVdvi+XhaqjF8b+1p/ho9Umj8vQJGfnM25LA3LGd6NbIuGquSqXw37tbM7xjBEt2JXH2Yj4+bo4MbRtK/9ggu8rX/3Myw2qrwbwtZ4n0dWXid3tQUAxTtHOKyvhq42nWHkvjp0nd8HKpni4TD2cHbmkexPytZ822FqlVisnkMz2niBFfbePsRX1iJNCPn9l6OpPFjfwM47/KuTlqyCo0X9tHpYCnS9VOF28V5m11HwVoGVY3J5lINya7u6WmT59OXl7l2QkFBQVMnz69SoKSJMmYTid4+NtdrD6SCugvcuXXycTMfO7/ahs/7j7PvK1n9fubWBri7b+O2V0gz5p1x9P4aPVJo/OAfhp2cZmOR741X0ivXaQP79zTmsWPdmX2gx24tWWI3evy7Dl32WLlXtAnA1OW7Ncne1d10+kEnMnIZ+aak3ad11a5RaV8u/UsOxMyLXeDCRjTNarS5qcX7yfxUqFRTaDyw2w/k8m7K40H6t7VLsziQGad0Ld2VaXGge50behn9rxqlUK/2EDCa2Hsk3Tzsju5EUKYnEp44MABfH19qyQoSZKMbTl9ke1nLqE1cX3UCsgv0TJz7UmLFza1SmHh9rNVGtecjQmYG1IiBBSUaPlxT9WO8ajI1lnN+SVas901WiFYsiupypcuSLiYz4CPNvLG70c4fCHH5D5qlYJaUfj4/rY0CTIeZ3QiNZdtZ8wnRTqhH0BccVbUhB7RODuoTHZxqVUKscEe1bJy9Qf3tSHQw6nSeVWKftD3jGGtqvyckmSJzcmNj48Pvr76vv2mTZvi6+tr+PHy8mLAgAHcd9991RmrJN20lu1Ptpi4aHWClKwii60DWp1gf5Ll6cZXE0Kw59xl5m9JYOH2c5zLzDe6bddZ0wlXRTurcSBpt0b+FrulFMDLRYODlUG9BSVaUrOrrtq6VicYP28nGXnFlSoxlwv2cmZctyjWTu3NnW0qt6bsTMi0Wuy6qFTHkQpTyCN8XfluQhzuJioVN/R3ZeHDcdWyanWYtwt/PdWTJ/o1IcjTCQe1QqiXM5NvacqfT/Yk0NO5ys8pSZbY3Pk6c+ZMhBCMHz+e6dOnGxXpc3R0JCoqiq5du1ZLkJJUX8Wn5/L1pgSWH0qhqFRH40B3xnRrwD3twysNBrUkq8D67B5b5v4421FI7XRGHo9/v5fjqbn6FpIrCz8OahHE+8Pb1IlS//2aBRLp68oFM1WKBdApypf1J6zP3nRxrLq6KRtPZpCQaX4AsYL+tXjltljTLeFJWWw8lWHTa1qRVif44p/TlaokqxQ4lZ7Pb/suVMu4KwBfN0eeGdCUZwY0rZbjS5I9bP50GjNmDADR0dF069YNBwdZr0CSLNl86iLj5+9CK4ThwnssNYcXfj7EqqNpfPFgB5u/RYf7uBoN2DXFxUFFiVaY3UdR9Ctb2yI9p4j7vthmGJxacajKmqPpjJu3i6WPdqVTlK9+PImFq3Dn6OrrrlarFOaN68TIr7aTcaVYn7iyXasTjO8ezT3tw1hzLN3sMVQKtAj1IqgKWxe2nr6IRqWYbVUSwNnMAtJzi43Om5ZTxMTv9rAvMcumZnVnBxUtKgzU/XnPef4+klZpv/Iw/u+vY/SPDTIsFSFJNyqbPllzcv7tL27Xrh2FhYXk5OSY/JEkST99d9L3eyjV6YySjfIkYd2xdOZtSbD5eCM6RVhMbFQKjOgUiUoxvW6nSgEPJw33dbRt5eS5W86abS3SXumq2nAinUd6RZtNbBQFXB3VDK/G1ZoBGgW4s2Zqb16/ozkdonxoFuzBnW1C+WliV167ozktwrzo1STA7NggnYCn+jep0phsLaHz274LhlpEhSVa7v9yGwfP67uZrE2cVikwsnOkURfUt9vOWhyHpFIUfthhuRaOJN0IbEpufHx8SE/Xf/Px9vbGx8en0k/5dkmS4Pf9yeQWlZldGVqgn6Js64KGsSGejOlqeu0htUqhYYA7Uwc25avRHXHSqFCuJDnlFzpPFwcWTojDx8aVk3/ee97qWJoXfz7I6fR8JvVpZIjDEJMCThoVc8Z0xMu1+lt5PZ0dGNs9mp8mdmPl5F58PKItHaP+bTH67IF2xF1Z9FSjUtCoFFSK/v9v39XS5hYtW3Vo4GN1ijrAjBXH+WxdPAC/H7hAQmaB1e7H8qe5S0M/Xri1mdFtJ9Msr0auFYLjVTxjTpLqIpu6pdatW2eYCbVu3Tq5+qkkWXHgfLbFbgmAlOwisgpL8bUx4XjjzhaE+bjw5T9nDMsXaNQKd7UN5dXbmuPh7EDfmEC2vdSfn/acZ/e5S6hVCt0b+3NX2zDc7BgjY276dkUZeSX8d8UxXB3VvH1XS3advWQo4jeweRAPmCniVxs8nR34/uE49iZmsfxQCnlFZTQMcOOeDuH4uztZP4CdBjQPIsjTiYzcYqutOB+tOck9HcJZtj8ZRcFicqJRKXSO9mVk50gGmyji56xRU6o1vyq5ooCLXJNJugnY9GnXu3dvw//79OlTXbFI0g3D2uyccraU5i+nKAr/6dWIcd2jOZqcQ4lWR5NAd7xdjZMjHzdHHunVkEe49oGj3q4ONi04KYS+O2XG8mP883zfakkUqoqiKHRo4EOHBtXfwuygVvHNmE6M/GobucWWp5grwE97znMpv8RiYgP6JO2HR7qYvf3WlsH8su+C2dYfIWBQi2Br4UtSvWf3nMCGDRsybdo0Tpw4USUBzJo1i+joaJydnenQoQObNm0yu+8vv/zCgAEDCAgIwNPTk65du/L3339XSRySVJV6Nw2w2GqjUqB1uNc1lf13UKtoE+FNpyjfSolNVXG1Y+aQTkBhqZYlu6qvnk191DLMi58mdbO6n6IoJF0qoFGAu8Xp/ioFGvhbLoT3cM+GZsddqVUKYd4u3NY6xGpMklTf2Z3cPPHEE6xcuZLY2Fg6dOjAzJkzSUlJuaaTL1myhMmTJ/PKK6+wb98+evbsyeDBg0lMTDS5/8aNGxkwYADLly9nz5499O3blzvuuIN9+/Zd0/klE3Q6OLMBdn0Dh36CIvvqokh6fWICaRjgZvZipRPw2JWxKteiqFTL4p2J3PXZFjr/3xqGfLKJuZsTjAq6XY/UHPtqvugErD9ufkbSjSA1u4iVh1NZfTSNyxZWNa+ogZ8baivd+EKAl6sDIztHWhxvoxPwYFwDSsp0LNt/gdHf7GDQzI2Mn7+LlYdT0OoEMcEezBndERdHNQr6hKa8gnO4tws/PBJncsFNSbrRKOIalw0+efIk33//PYsXL+bMmTP07duXBx98kNGjR9t8jLi4ONq3b8/s2bMN22JjY7nrrruYMWOGTcdo0aIFI0aMsHlNq5ycHLy8vMjOzsbT09PmWG8KCRvht8cgu8I3cI0zdH8aer8Iqqov/nUjS7pUwKg520m6XGhYGLJ8ivLzt8bwWJ/G13Tc3KJSHvx6BwfOZxvGaJRfPqP8XFkysSuBHtc3rbn5ayspKLGvYm/rcC9+f6LHdZ23LrqcX8Irvx1i5eFUw/gZjUpheIdwXrujhdX6OI9/v5eVR1ItJi6+rg68dkdzNpzI4Lf9yZVuVynQtaEf/xvVjvHzdnHgfLbhPVX+b7cKa03lFZfx674LHEjKwkGtom9MAP2aBdpVW0mS6hp7rt/XnNxUtH37diZNmsTBgwfRam37QCwpKcHV1ZUff/yRYcOGGbY//fTT7N+/n3/++cfqMXQ6HVFRUTz//PM88cQTJvcpLi6muPjfsQM5OTlERETI5OZqSbtg3mAQWhAmJqF2fxoGvFnzcdVzRaValh9KYeXhVApKtMQEezCycySNA92v+ZjP/XiAX8zMZlKrFLo29OO7h+OuI2p4ZMFu1h1Ptzpzp+J5R3dtwOt3tLC4n7gyWyctp4gADyeah3jW6QkKBSVl3PX5Fk5n5Fd6LlQKxEXrn2tL3UnHU3MY+tkWSrU6q4OL372nFRfzSvhmcwKXrrQOeThpeKBLAybf0oSpS/ULp169RlZ5PKM6R/L2DbLUgRD6RV+PpeTi7KCiX7NAQrzqxgB1qXbYk9xcV4nRnTt38sMPP7BkyRKys7O59957bb7vxYsX0Wq1BAUZT8EMCgoiNTXVpmN8+OGH5OfnW1z2YcaMGXJBT1usfVOf1JhKbAC2fgZdHgMPORjRHs4Oau5uH87d7cOr5HiX8kv4dd8Fs9O0tTrB5viLnM7Io1HAtSdQD/eIZvXRysXgzNEJwYNdTE9VL7c1/iLT/zxqtHhn40B3Xru9uckVseuCpbuSOJWWZ7JSsE7AtjOZrD2WxkALg3SbBXvy/cNxPLloHylWlnj4v7+OsevVW/hPr4bEp+ehE4JGAe44O6i5kFXI8sMpZgcd6wQs2Z3Es4NirmksVqlWh1pRUFlZiLQmHDyfxVOL9nE2s8Cwwr2iwLB2YfzfsFaya02yyu42ypMnT/L666/TpEkTunfvztGjR3nnnXdIS0tjyZIldgdw9bc2cwtzXm3RokW88cYbLFmyhMDAQLP7vfTSS2RnZxt+kpLkoMdKctPg7EZ9q41ZAg7/UmMhSaYdupBtU/2U3Wevbz2nuIZ+vDm0hWHchjlqlYIC/N9drSwmU5tPXeTBb3ZwMs24xsrpjDzGztvJuuO2J1I1abGVQdJqBZbu1u9TUFLG6Yw8k2tUOWpML2Z5tZyiMtYfz8BBrSI2xJMWoV6GC/nOhEyrs6lKtYJ9iVnWT3RFSZmOuZsT6PXeepq8soImr67g0YW72Z9k+zGq2pmMPO7/ajuJl/TLV+iuLPuhE/Drvgs88cM+qqDDQbrB2d1y06xZMzp27Mjjjz/O/fffT3DwtX2T9/f3R61WV2qlSU9Pr9Sac7UlS5YwYcIEfvzxR2655RaL+zo5OeHkVHenp9YJBZnW91HUkG99fR6petn6nVqxeU/zRneNoktDPxZuO8eec5dx1KiI8nMlObuQQ+dzUCnQs2kAD/eINiqYdzUhBNN+O6RfQFJcfZv+32m/HaHP84EWWw3Scoo4mpKDk1pFu0ifKl0LytI5LV1GtQLOXSrglV8P8dOe8xSX6Vs+W4Z6MmVAU/rHBhGfrr9Y27LquKLoz2mKzlrJ4vL9bLzwl5TpmPDtLjafumjYptUJ1hxLZ/XRND4f1Z7BrWp+ZtXsDacpLjPdhacTsOZYGgfOZ9M2wrvGY5PqD7uTm+PHj9O06fUvjObo6EiHDh1YvXq10Zib1atXM3ToULP3W7RoEePHj2fRokXcdttt1x2HhL6rSVGZ75IC0JWBV1jNxSSZ1CbCGyeNynARNUUBujbyq5LzNQ3y4K27Wl7XMfYlZVlcRFIAF7IK2Xn2El0aVo47PbeI15YdYdWRfwf0ujtpGN8jmqf7N7HYsnS9AjycyCooNZvgKMD5S4WcyUgyGpNzNCWHCd/u5t17WrHtdKbZi/XVhNCf05T2NtTnUasUWod7Wz8RMH9rApvjL1Z6bFqdQAEmL9lPt0b+NVJhuuK5l+1PtjjWS61S+G3fBZncSBbZ3S1VFYlNuWeeeYavv/6auXPncuzYMaZMmUJiYiITJ04E9F1KFWdfLVq0iNGjR/Phhx/SpUsXUlNTSU1NJTtbTle+Lq6+0HSwvnXGHLUDtLyn5mKSTPJyceC+jhFmuzjUikL/2EAifC3XQ7GFTidYdzyNRxbs5taZG3nomx38tu8CxWX2zaJKybJtWnlyVmGlbVkFJdwzayurj6YZJQd5xWV8uvYUL/x80K5Y7GVtLS4BFJdpK12My3999bfD/HHA8sW6Ig8nDf2ame5mj/Z3o3fTALPJnFpRuKN1iNnkyChuIZi35azF5UFKynT8vPe8TXFXlaJSLSVay01UQgguF9g2FV+6edmd3Gi1Wj744AM6d+5McHAwvr6+Rj/2GDFiBDNnzuTNN9+kbdu2bNy4keXLl9OggX5gYkpKilHNmy+//JKysjIef/xxQkJCDD9PP/20vQ9Dutotb4CDi/kE55bp4CLXDqsLXrkt1tDCUX6dK/83JtiDD4a3ue5zFJdpeXjBbsbP18+aOp6ay5b4i0xesp+7Z20ly46Li63LS5jab+6Ws1zIKjSZHAj0lX0Pns+yORZ73d85kih/0/WKFP6dhm1OmVZYXaOroheHNLM4WPb94a2J9HUxrB1WHgfoX/vpQ21rZcsrLrM6uFmlUjiSXLOLIbs6qvF0ttyhoChKnVnWQ6q77E5upk+fzkcffcR9991HdnY2zzzzDHfffTcqlYo33njD7gAee+wxzp49S3FxMXv27KFXr16G2+bPn8+GDRsMv2/YsAEhRKWf+fPn231e6SoBTWHCaoi8agqxRzDc+Rl0fax24rpBFJVq2X4mk02nMkjPta9A3tWcHdQsGN+ZLx5sT6+mATQOcCcu2o+P7mvDr493q5KqxR+uOsn6E/qifOWJRflF/HhqLs8sPWDzsTpH+xJkpTXB19WR7o39K21ftCPRYvKgUSn8uLv6WhfcnTQsfbQrvZr4G41iUin69aOsNcioVYpN3WZOaoV372nFA3GWZ5wFejjzx5M9efW25jQN8sDXzZEWoZ68fVdLfp7UDS8X27qQHGyod6MATg41WxdHURRGdo60+JxpdYLhNq5uL9287B5z8/333zNnzhxuu+02pk+fzsiRI2nUqBGtW7dm+/btPPXUU9URp1QTgprDuBWQeRounQEnTwjvCCo57fJaaXWCz9bF8/WmM+ReqR6sUmBIqxDeuLPFNa/FpFGruLVlCLe2rPoBn/nFZSzcds5sl4VWJ1h3PJ2Ei/lE+7tZPZ5apfDybbE8vXi/2X1eHNKs0gVXCEFGnuX1rcp0gpTsyt1ZiZkFzN2SwLL9F8gv1tLAz5XRXRtwX6cInDT2vZ8DPJyYN64ziZkF7Eu6jKIoxEX74uygZtX0VRbvK4DYEA+OJudYTIQECo4a2xIJdycNE3pEM6FHtB2Pwpizg5pujfzYfibTbFxlOsEtseZnolaX//RqyJ8HU0jNKTLZYvdo74Y2ve+km5vdaXlqaiqtWumLRLm7uxvGu9x+++389ddfVRudVDv8GkGTAfpWHJnYXJeXfjnIx2tOGhIb0LeArDicyr2zt5JdaH317Zp28Hw2hTbM7Nl22oZZdlcMbRvGh8Pb4H1Vy4Kns4Z37m5lcmyLoihWWyLUKgU/N+MEcX9SFrd+spGF289xuaCUEq2O+PQ8Xlt2hNHf7LRp1pIpkX6uDG0bxp1tQgnydMbLxYHujf0sTvHW6gSdonyttvCUaHU8s+SA0cyl6vZYn8Zm41KrFJoEutO7ac0nN37uTvz6eDdubRFs9Nz6uTny2u3NefHWZjUek1T/2N1yEx4eTkpKCpGRkTRu3JhVq1bRvn17du3aJadcS1IFB89nsdRMl4lWJ0i8VMD8LWd5+pYmNRyZZbbUEFGwfcpxuXs6hHN7mxA2nMgg/UqF4j4xgRbHmAzvEM68rWfNDsjV6gTD2v87i69Mq+PRhbspKtUaXbjL/7vr7CU+XXeK5wZVzQXy6f5N2XZ6G0qFc5QrXzLh261nbTqWosCn607Ro0nl7rnq0KOJP+/c3YpXfj2MQCAAlaJfHiTKz5Vvx3eu1plolgR6OPP5A+3JyC3mdEYeThoVrcK85PIRks3sfqcMGzaMtWvXAvqlEqZNm0aTJk0YPXo048ePr/IAJam+Wro7yeLFQSfgh53najAi2zQP9cRBbWWxR6CDDVOTr+akURPp60pesZaTaXlsO51pcSbRwz0b4uXsYPJ5VCn61dfjov+dyLDmWDppOcVmWyR0AhZuO2f3jC9zOkf7MuuBDrg66RM0hwpjbAY0D6JVuJfNFYd0AnYkXKrR1rz7O0ey5cV+TL6lKUNahjC0bShfPNiBvyf3IrQODNoN8HCiS0M/2kX6yMRGsovdLTfvvPOO4f/33nsvERERbNmyhcaNG3PnnXdWaXCSVJ8lXzY9y6ei9Jxim6ty1xRvV0fubh/OT7uTzK5f1S7Cm9gQ62uzJWcV8vuBZC7mFuPl4sCmUxfZefYSKkXf7aTVCcK8XZj9YHuT9VmCvZz5cVJXJi/ez6EL/5Z8UClwd/tw3r6rpdFzd/B8FhqVYrGKc05RGRcuF9LwOpanqOjWlsH0bjqAPw8mE5+Rh5ujhltbBtM0yIMJ3+6ya7YUQGGJ1uaBwVUh2MuZp/rXrdZDSbpe17W2FOhX9o6Lu75F+iTpRuTr7mRYBdwcLxeHOpXYlJt2e3OOp+ToVx7n3y4XlQLBns78b2Q7i/fX6QTvrDzOnE1nDFOmK9Yd1FUoV3whq5B7v9jG35N7mRwo2ijAnT+e7MGh89kcupCNo0ZFryb+BHpWXvlco1IsVhQuZ8tsIXu4OKpNzuBxdlBbnS5ekaezBj/3yrPdjiRnczwlF2cHNT0a12xhPUmqj+xObmbMmEFQUFClLqi5c+eSkZHBCy+8UGXBSVJ9NqxdGD/tMT9NWa1SuLdD1SyoWdXcnTQsebQrv+67wA87ErlwuRBfd0eGdwjn/s6RVlsWPll7iq82ngH+XRfIkpIyHePm7WTd1D5ml2BoFe5Fq3Avi8fpHRPA/9bFm71dASJ8XQn30Xe5ZBeWsu54GtkFpTTwc6NnE/8q7f64JTaQvw6m2LSvWlEYGRdplHidSstl6o8HOHj+31YrR7WK0d0a8OKtzWRXjSSZYXdy8+WXX/LDDz9U2t6iRQvuv/9+mdxI0hXdGvnRo7E/W09frHRxV6sUPJ01TOh57dN5q5uzg5qRnSMZ2TnSrvvlFZfx5cbTdp/vbGYBfx1K4Y42oXbft1z7SB/aRnhz6EK22cJ/k/o0Qgj4eM1JvthwmhKtDuXKytOBHk68e29r+sZUzSyhwS1D+ODvk2anNZdTKwpNgtx5om9jw7akSwXc+8U28irMtAP9zKpvNiVwOb+ED+9rWyVxStKN5pqmgoeEVK6tERAQQEqKbd9QJOlmoCgKX43uwJ1tQinveTJUkw3y4MeJ3Qjxqv1Bm7YSQrD19EWeWrSPOz/bzNh5O00ux7DxZAZFpTau8niVBdvOXleM5c95wyvdW+WNQOWDfB/t1ZD7O0Xw/qoT/G/tKUOp//KJXxm5xUyYv4vtZ2yf5m6Js4OaHx6JI9TL2RDH1Q1Tns4aHunVkB8ndsXD+d8WsVkbTpNXXGY2Sft57wWOpdRsBWFJqi/sbrkpH0AcHW38jXPLli2Ehl77Ny5JuhG5OmqYeX87XhjcjE0nL1Ks1dEqzIs24V51cqyNOVqd4NkfD/DrvguGcUQqBTacyGD2Bg9+eCQOvysFCa9uabDHibTc64410MOZv57qyd9HUvnzYDK5RWU0CnDn/s4RtAj1IiO32NBldjWBPgF9/+8T/Dyp23XHAtDAz411z/Zh9dE01h1Pp6RM/x4Y1DIIJ40aXzfHSmOAtDrBL3vPW11A8pe953nltuZVEqck3UjsTm4efvhhJk+eTGlpKf369QNg7dq1PP/880ydOrXKA5SkG0GIlwv3daq/JeNnb4jn130XgMrLMcRn5PHED/tY9J8uADQKuPbqsS4Wat7Yw1Gj4o42oSa7uFYcTrFYo0cnYM+5y1zIKqyyNYwc1CqGtAphSCvbKkoXlJRZXPkdACHIyLVcwVmSblZ2JzfPP/88ly5d4rHHHqOkRL94nrOzMy+88AIvvfRSlQcoSVLtKinT8fXmBLO3a3WCbWcyOZaSQ2yIJ+0jfWgU4EbCxXybZwmBvgvptlbV3/qbmVeCWlEos1KE8FJeSa0t0OjqqMHFQW25UrSiEORVecaYJEnXkNwoisK7777LtGnTOHbsGC4uLjRp0kRWJ5ZuelkFJWw9nUlJmY4WoZ40CfKo7ZBskp5bxFf/nGHVkVTKdILYEE9evq0ZjQL08Z9IzSWrwHJhOZUCW+IvEhviiaIovD+8DSO/2k5Jmc6mqdkK+taWsd2ibIo5q6CE3KIyAjycTFY4LinTsepoKjvOXAL0xfYGtQjGUaMizMfFYh0c0FcLDq7FxEGtUhjeMZzvdyRarM48vI7OtpOk2nbNdW7c3d3p1KlTVcYiSTbZfiaT+VvPsufsZdRqhf7NAhnbLarWkomSMh3/99dRftiZSGmFim0dGvjw0X1taOBXNxb5E0Lw+4Fk5m85y+HkbBzUKlqEerL77GWjBCQ5u4i1x9MZ1y2Kl2+LZdsZ29Y7qpgwtI/04cuHOjB23i6b7uvp4sBXD3Ug0s/V4n67zl7i49Un2XplXSuNSmFAiyCm39mCQA99MnIkOZvx83eRllOM5sro3YXbzxHo4cS8cZ0Y0iqE15YdNjvoWa0o9IkJIMDKSubV7bE+jfnrUApZBaUmE5wH4yJpHFg/EmhJqmmKsGUhmQry8/N55513WLt2Lenp6eh0xh8QZ86YHqhXV+Tk5ODl5UV2djaentYrrEp1y8w1J5m55pRRcbzymTCfj2rPrS2DazQeIQSP/7CXFYdTK62irVYpeLs6sPypngSZKDhXk4QQvPDzQZbuPm9XUTlXBzUFNi40ufTRrnSusBTC15vO8N/lx6ye6+UhzXioSxQujpbH26w5msYjC3YDlddxclArzB/XiZhgT/p/+A+5RaWVp98rCu7OGtZO7c2SXYm8//dJk+dxcVDx+xM96kTLW2JmAS/+ctCQzAG4Oal5pGdDnurXxGxNoPomr7iMn3Yn8eOe81zMKybcx5WRnSO5s02ozaulSzc+e67f1zSg+J9//uGhhx4iJCSkXs34kOq3jSczmLnmFIDRN1mtTqAATy7ay6bn+9ncnZBTVMqfB1JIvFSAl4sDt7cOIcLXcsvB1fYlZbH8UKrJ27Q6QVZBKXM2nuHV22t3Rsuy/cmGRTztGQdjS2KjVik0CnCjU5TxWlPZhaWoFMXqAps9mwRYTWyKSrVM/XG/2S6uUq1gzNxdjO7awGRiA6AVgtyiUhZsO8tv+5LNJnnODmrDzK/rtTMhk62nM/F2daB/syC731+Rfq788EgXEi7mcyI1F2cHFXHRflafr/okPbeI+77YxrnMAkCfuGbkFrPn3GUW7UxkwfjOuDlddzF96SZj9ztmxYoV/PXXX3Tv3r064pEks+ZuSTC7nIFAn0ws2pnIlAFNrR5r8c5EXv/9CCVlOtQq/QX4vZXHub9zBG8ObWlzef5f9p63uMSCVidYujup1pObeVsS7GqxsZVKAW9XB754sEOlLzqRvq5Wx7aoVQohNiSjq46mkV1oeYp5mU6wdPd5i49RJ2DpriRSc8zPMsouLGXRzkQer1BQz15/H0nluR8PkFP0b8xv/H6UztG+zH6gvd3JU5SfKx7OGrQ6gaNGhVYnKNXqLK6oXl9MWbyfpMuFRolr+Wu4L/Ey//fXUf57d+taiU2qv+xObnx8fPD19bW+oyRVsV0JlyzW/dAJ/ZgMa1YcSuHFXw4Zfq94AV68MwmNSsVbd7W0KaaM3GKri2PmFJVRptXVWKl8IQRrjqUzd3MC+5OyUKsU8ovLbBrYaw9fN0ce6tKAB7s0MDk+ZUirEF7//QgFJaZbf9QqhcEtg/F2rbyW0tVOp+fZlJzZUmPnckGp0XpZV9MJ+HXvhWtObv46mMLjP+w1edvOhEvcNWsLf0/uhaujbR+/v+27wOwN8ZxIywP0A69LrwzUDvdxYWy3KEZ3jaqX3Tfx6blsOW2+YKJOwI97zvPCrbFyPS3JLnb/Nbz11lu89tprFBQUVEc8kmSWLV2g1oYgCCH4YNUJzO0mgO93nCMtp8immII8nQ2DVs3xdnWo0cTm/5Yf45EFu9mRkElhqZa8akhsFODp/k2YMqCp2YG3bk4a3r6SJF790qlVCl4uDrxwazObzufmpLa51Ult4fVQqxQ0auuLa2YXWp4dZk5Jmb77zJKkS4X8bGHNsYo+Wn2SyUv2czI9r8I5/p2Bdv5yIf/31zHGzttZqVJ0fbDr7GWr+5RqBQcvZFV/MNINxe5P3A8//JC///6boKAgWrVqRfv27Y1+JKm69Gzib/HCpSjQvXGAxWOczsjjdEa+xYubEPpuBVvc2yHcYteLWlEYUYPF+9YdT+frTfqaNFXdBVWRAEJtqAFzd/twvh7dkZgKg3NVCgxsHsSyx7vbPAZlUAvbBoqrFCy2pGl1gmbBHhbfRyoFovztGxsD+sTykQW7bVp6YuG2c1b3OZaSw//WnrpybAvnBbadyWTelrM2Rlp32DpiU7F5T0nSs7tb6q677qqGMCTJugk9ollx2HTSoSj66rb3dbRc96PiGAhzVCqFXBv2A2gd7s1d7cJYtu9CpYRJrVLwd3fk4R4NbTpWVZi7OQG1AtpqTGwAfF0d6RNjOZEsd0vzIPrHBnIus4DcojLCfFzwdbPeFVVRAz83BrUI4u8jaWb3USkwuGUwPq6OfLcj0ajrqfz/D8ZFckvzIItT1HUCHuzSoNL246k57Dl3GbWi0LWRX6Up/n8cTOGfk7ZNm0+3obLwop2JFsdzVSQEzN96lkd7NaxXkzziGvpZ3cdJo6J1hOXV4CXpanYnN6+//np1xCFJVnWM8uWtu1ry2m+HUVX40Fcp+nEIX4/paHWgZoSPq9WxG1qdINq/cm2aolItyVmFODuoCfFyNlxEPri3NcGezszfmmD0rb1bIz/euad1jdZL2X8+y+bEpvyC7+qoRq1AbrHWsL1VuBfHknPQCmH0XJVfNt+8q4XNg65B36UYZeI5tccn97djyP82cSYjv/Lx0c9ymjIghkYBbrQI82LOpjOGfaP93XjkyqKZAHe2CeGPAymVElJFgV5NAritwjIJyVmFPL14n1EXigLcEhvEB8PbGMaCzN2cYHEsT0WBNrwnTqTm2pTYlEvNLiK3uAxP5/ozNiXa340+MQFsOnXR5GNVKTCyc2S9ekxS3XDN8+v27NnDsWPHUBSF5s2b065du6qMS5JMeqhLA7pE+7Jw+zl2nb2Mo1qhb7NARnaOtKmWTICHEwOaB7HmWLrJD1MF/RiZW2KDDNtyikr5ePVJluxKMgyObRbswdP9mzC4VQgatYoXBzfjiX6N2ZmQSXGpjuahnrVSvE+jUgGWx15E+LgQ7e+Go0ZFv2ZBDG0bipuThpTsQnKLygj2csbT2YG9iZeZ/vsRDpzPNtw3yt+Nl4fEMqB5kIUzVA9nBzVrpvTmzT+P8v2Oc0YFE5uHevLeva1pHOgO6C+I93eKMFRW9nZ1MGrR+HhEO2KCPflmcwKX8vXLyDhpVMRF+/LykFjDGKnswlLu+3IbKdnGY7AE+i7AB77Zzi+TuuOgVjh4PsvmsU1ju0dZ3cfdSWP3DDfHCglnWk4RS3YlcTQ5BycHFbfEBhmqNNclH93Xlvu/2sbJtDwURd8KVd762KWhHy8Otm1cliRVZHcRv/T0dO6//342bNiAt7c3Qgiys7Pp27cvixcvJiDAtqbq2iKL+ElJlwq46/MtZBUaV34tH4bx1UMdueXKxTu3qJR7Z28jPj3XqEWk/EP4tdubM75HdJXHmF9cxu8HkjmekoOzg5oBzYPo0MDHapfDlCX7+f1Astlv/Arwym2xPNzT9q6y+PQ8krMK8XVzpEWoZ53o9igoKWNrfCb5JfoVv1uGXVu3xam0XB5duIczF/P1g56FPnHpGxPAzBHtWLQrkfdWHreYYPxvZDvuaB1Ck1dWWJ36DvrkcvUzva1O4/5pz3me/fGATY9DrSh0aeTL9w/rFy9dujuJl345hBACIUClKGiFIMLHhe8f7mK1EnRNKyrV8vuBZH7ac56LucWE+7gwsnMkA5oH1dhgfKnus+f6bXdyM2LECE6fPs3ChQuJjY0F4OjRo4wZM4bGjRuzaNGia4+8Bsjk5gaSdhR2fwNJu0DjCDGDof0YcPO3etfzlwt4/+8T/HUwxXBB6hTlw9SBMXSpMA7gw1Un+Hx9PDoBTpRwi2ovDZRUcnDjb21HLim+bH2pX5VWIF59NI3Ji/eRX6I1zMQq0wk6NPBhzuiOFserHL6QzZ2fbTZ5MVYp+taAjc/3tWn69Y0uI7eYwZ9s5LKJ5Q3UikKLME/yi8o4fbFyN1g5laIvQvjt+M6Mm7eTjWa6V8pF+rjw59M9bepmKSrVMvDjjVzIKrTaPaUA3z0cR/fG/mw/k8nIr7abbEVSqxTCvV1YM7W3Xd2KklQXVGty4+XlxZo1ayqtK7Vz504GDhxIVlaW3QHXJJnc3CC2fwErXwSVCnRXumEUFTi6wYO/QoRt657lFJWSll2El4sDgVclKDqdoMPbq7lcUMog1U7edZiDt5JPqVChRiBQWKAdSEHfN3i8f2yVPKz9SVncM3srOp0wOUC5Zagnvz7W3WLZ/WX7LzBlyf5KCY6jWmHeuE5WZ5TdLComrua4OarJN1Onp1xsiCcrnu7J1viLjPp6h8l9FMDDWcP2l/vbXN8G9En4uHm7OFVhKrgpL97ajIl9GgEwdt5Os2NYys16oD1DKowrkqT6wJ7rt92pu06nw8Gh8rcOBweHSutMSVK1OPMPrHwBEP8mNgBCByX58P09UJRt9u4VeTo70CTIo1JiA5BXUsblglJ6qA4x2+ETPNF/g3dQdKgUgVrRMUa9klaH36+KRwXArA3x+odi4jatTnDgfDZbTluekeOk0Xd3XJ3+lOkEb/15jJwi+2q45BSVMm9LAqO/2cH9X21jxopjJGZef52rk2m5PP/TAVq8vpJGLy9nwEf/sHD7OUq1NfM58tMey9WMVYp+5pylTji1AhG++inx3Rr78+bQFigY19pRAC9XB354pItdiU1esb7rrVcT6y2Ru68Ur9TqBP+czLCY2KhVCmuPpdschyTVR3YPKO7Xrx9PP/00ixYtIjQ0FIALFy4wZcoU+vfvX+UBSlIl2z4DRQ3CxDdqoYOiHDiwGOIeva7TOGvUqBR4TrMEgf5CdjWVAj0u/wo5b4Nn6HWdr1SrY83RNIsXXI1KYcXhVHo2Md36kl9cxjNL9yNE5QRJJ/QJxadrT/HKbbYtB3H4QjYPfrOD7CsDcwWwK+EyczaeYcbdrRjRKdKm41xt86mLjJ+/C60QhgtxfHoer/12mOUHk+nXLIijKTk4qBX6xAQyoHlQlXejZFkp1KcT4OPqaLEsgFbAyArPweiuUXRv7M8POxLZn5SFk0Y/kPeeDuF4udg+42fpriRe//0IhaVaq4UpAdYcT2drfAYdonwt1sQBfT2ekhpKICWpttid3Hz22WcMHTqUqKgoIiIiUBSFxMREWrVqxXfffVcdMUqSsTMbTCc2V+9zncmNo0bFiCaCNomWV7pXEHB0GXSZdF3nKynTWZ0ZI4SgwMISA38cSDa73AHoL9iLdibx7KAYQwuPOXnFZTz0zQ5yCkuNEiXtlavniz8folGAOx2j7FuOpbBEy6Tv91Cq0xldiMv/u+3MJbaduYRa0U8hX7r7PJG+riyc0LlKZ6CFebtwOj3P7Ayn8mJ+ns4ajqXkVJpiryjQJyaA3k2NE81GAe5Mu461xJYfSuH5nw8afrd1ttRTi/ez65VbiPJz5VxmgdnHJYAWobJLXrqx2f1VKCIigr179/LXX38xefJknnrqKZYvX86ePXsID7dcQE2SqoSw9q3zqu6q6zCuvbf1nVRqKLReRt4aV0e11fonAgzTnU05kZZrdTmIvOIyMmwoIvfrvgtcLjC9wjbou2zmbDKf+MWn57LhRDoHkrLQVTjIHweSyS0qs9rCoBX/rvt1IauQUXN2UGTDKuW2eiDOcquTTsDGkxc5l5lPTLCH0fPq4qBmQvdovniwg8XxT2aPrRPsOJPJr/vOs+FEOiVl+ve0EIL3Vx6/pnq8F/NK2JeUxbju5mfvKehb/4Z3kJ/V0o3tmuvcDBgwgAEDBlRlLJJkm/BOkLTTfOuNooLILlVyqqZNYhGoUDCfUCm6MvCJuu5zKYrC6K4N+Gj1SbMJhYLCfR0jKCnTcbmgBDcnDe5O//4Zuziobaq14mJlGnKpVsdve89bLEqn1Qk2nMiotH1/UhavLztsVB8n0teVlwY3Y3CrEA5eyEKjUmyaNl3xXBeyCllxOIVh7armwnx/p0h+3nOeoyk5FltHcou1HEvJpV+zQMZ2j0KtKLSO8DZ63u2x4UQ6r/52mPOXCw3bfF0deXFwM1pHeJFwHeOZjiZn80BcJJtOZRjG1ZQ/NLVKQQjBR/e1tXtVckmqb2xuuVm3bh3NmzcnJyen0m3Z2dm0aNGCTZs2VWlwkmRS18ctdEspoHaA9qOr5lxufiixtyMUC8mAoxs0H1olp5vQoyGtwrwqjbMo//35wTF8ufEM7d5aRdx/19Lq9b8ZM3cne87pB5QOahFscTCpo1JGrzAFPwsz15fsSqTLf9eyJ9F6UTrdVc0vB5KyGPHlNg5dMB7QnXSpgEnf7+XXfeeveeyMStFPk68qLo5qFk7obFT4zhwBrD2eTplO0K2x/zUnNptOZTB+/i4uVEhsAC4VlPD8zwdZujvpmo5bzs1Rg0at4osHO/DWXS1pdKWVT6NSGNA8iJ8mdeOONtc3NkyS6gOb/0JnzpzJI488YnL6lZeXF48++igfffQRPXv2rNIAJamSZrdD96dhyyfGA4tVakAFwxfYVOvGZgOmo5zdpB+obJRUXWnXuO0jfYJjo7MX81m8K4mEi3m4OWm4rVUIfWICUasUXBzVLPpPF2atP83C7ecMq1O3jfBmTNcoZq45SeKlQsO4FwFsjr/IplMZhuKD3Rv5sf3MJcM+AMFk8rhmGfeqN+KSWQL/dYCW90Cv58C/sWG/hdvOMm3ZEZseh0qBNuHeRtve+vMopdrKY4fKf3192RE+GtH2mhZ51An9eJ2qdOhCDkVltg+uXbwzkb4xgdd0LiEEb/151ORg73LzNp+9pmOD/t044MoCoxq1ige7NODBLg3Q6gSqK+OXJOlmYXNyc+DAAd59912ztw8cOJAPPvigSoKSJIsUBQa8CdG9YedXcH63vrWm2W3Q+VEIaFq15/NtCA+vhVXT4MRyDJemgGbQf5r+vDb6fH08H/x9wrA2llql8MveC7QM9eTb8Z3xc3fC1VHDs4NiePqWJlzMK8ZJo8bXzZGXfz1E4uVCo6QF9F02CjBlqX5A6awHO/CfBbvZkXAJjUohnHR+cpiGN3lolCsXcl0pHP4Rjv8J45ZDSBsKSsqYseK4zY9FJzAa33EuM5/d5yyPPcopKqOoREtMkDvxGfl2rZ2kVvQ1ZapS6lXLKlhzKs1yvRlLjqfmctLK/a9nvdNbmgeabFGytAK6JN2obE5u0tLSTNa3MRxIoyEjo3L/uyRVm8b99T81wa8RjPwBctMgOwmcvcCvsT7RstGy/Rd4/+8TAIaLevm/x1JzmfjdHpY+2tXwDdtBrSLES19DpaCkjJ/3nDebDAggt6iM5YdSuLt9OIv/04XdZy8xc+0pHkuaYZzYlNNpobQQfnkUHtvGqiNpFmdalStf7+ihLg0Y0irYsP1CVqGFe/1739ScIuaN68wDc7aTkFlgOF75khbm6IR+LNCcjWfo2yyAxoEeVs9njZ+7fZWar+6Gs4ctg7ivVfMQD754oEO1HV+S6hubk5uwsDAOHTpE48aNTd5+8OBBQkJkxUvpBucRpP+xkxCCT9fFmx2gq9UJdp29zP6kLNpF+lS6PTmrkGIr3ScalWJUyfb3AymcO32M7k4Hzd9JaCHjGJzfTXquL+oraxBZ0izYg6f6N2VQiyCjrg5/Gwap6oQ+oQj1duHvKb1ZeSSVvw+nkldcRuNAN06k5rIlPlMf2pX7lCc/Api75SxCCP5v+TH6NQvk4xFt7aofc7VOdk5jbxJ07QlVoOf1D+J1dVQxolMky/YnU1yqJdjLmcf7NmZYuzDZ7SRJFdic3AwZMoTXXnuNwYMH4+xsPBqxsLCQ119/ndtvv73KA5SkG0FKdhHxVkroq1UK646nm0xuXGyobCsEuF6ZBbXtTCYLt5+jr+qCbQGmHyXAo7/VxAbg8wc6EO1feYxRk0B3YoLcOZmeZ7YFxtlBxYDm+tYeR42KO9uEcmeFAa5aneC77eeYuyWBcxVmDZUnhRVbrv45mcGE+btY+mjXa5qODZZbikwZeB2roccEeRAb7MGJtFy7VvquKMTLldfvaMHrd7S45jgk6WZg87SFV199lUuXLtG0aVPee+89li1bxu+//867775LTEwMly5d4pVXXqnOWCWpbivKhrx0kzV2SmwZtCr0SwI0m7aCFq+t5PHv97IvUT+GJdTLmdgQD4u9YFohuLWlPnH4fnsiapVCETZ2uzi4MrB5sMUp4ipFP7DZVGID+gGrLw3Rr7FlLszJtzS1ONNIrVIY0y2KDc/24eibgxjVORJFUcy2du0+d5lN8ZaXo7DEw1lDgI3Tot0c1RZnGpWvbP2/taeYtyWh0ngeRVF47TqSEkWBe2V9Gkmyic0tN0FBQWzdupVJkybx0ksvUb7epqIoDBo0iFmzZhEUdO3faiSp3jq1BjZ9AInb9L+7+kPnR/Qzuhz0Y2ZCvJ3xcNZYKeUvSM0uMlzIVx5JZfnhFN6/tw33dghn8i1NeXThHpP3VSlwS2yQvtukpIDc5OP46nTsoSnZwhUvxULtFLUjNO6Pm5OG52+NYfofRyvtolyZbfPyEMsLhPaJCeSLBzvwyq+HuJhXYtju6qhm8i1NeKRnQ4v3//d8Cq6OGn4/kGx1naTf9ydXqhJsK5VKYUw3y7WFys24pzXOZpK/FYdSeOHng+QUlaFR6bv23vrzKA/ENeC1O5obpr93beTHHW1CWbY/2a441SqFQA8nRnU2Ljx4JiOP5YdSyCkqI8rPjTvahOBhw4rjknSjs3tVcIDLly8THx+PEIImTZrg41O5Gb2ukquCS1Vqz3z442l94cCKlZMVlb7Y4OhlhgRnxopjzNl4xu4uCQXoFOWDDnBQqdh19hI6IVBdadHQ6gR9YwL47K4o3La8A/t/gDL94N79ukac0IUzQvOP+aPHTYTB7xi2fLf9HB+sOkFWwb9rL0X5ufLfYa3o1ti2KfbFpVpm/xPP/sRsXJ00PNglkq4N/UyOC9HpBIWlWpwd1EYze4QQRL+03Oq5bokN5Osxtq0Cb0pRqZYHv97B3sTLJl+bMG8X3h7W0uwU8M2nLvLQ3B1gYoq3AoyKi+T/hrUybBs7b6fJ4oeWtI3w5rNR7Qj3cQWguEzLCz8d5Lf9yaivLPBZphU4aVS8PayVbOGRbkj2XL+vKbmpz2RyI1WZ3DT4uDnozLTGKCroNw16PgPoZzyNmrODg+ezrnnMhfrKFPL+zQIJ9nLG3VnD7a1CaeWrhTn9IDvRqFtMKxQUBBt1remlOogOFYIrZfgVHbQZCXd+qp9KX0FJmY4tpy+SVVBChI8rHRr42Dxg9fCFbB5duIcLWYVoVP8mYG0jvPnqoQ6GFdgv5hXzxYbTLN6VRF5xGU4aFXe1C+OxPo0Ma0h1m7GWZAvTtdUqfVXn6x2DUlSq5etNZ/h22zkycotRgHaR3oztFsWdbcMs3veuz7dYfE0VBTa/0I8wb32S+58Fu1l9NM3qtG+1ojChRzR3tg2lZZiX0W1Tl+7n130XzJ7zmzEd6R8rW9KlG4s91++qXWZXkm4m+xZaXudK6PR1eK58f3B11LD4P114/tZmhgudk0ZlcrVxc8q7aNYeT6d/bCAvDY6lVbgXbHgHshIrjfdRK/oaOF1Ux7i95P/4XDuU33Q9+Va5g8wx/8CwLyolNqAf7Ns3JpBh7cLpGOVrc2KTnFXIqDnbDeNNynT/rvp96EI2o77eQXGZlpTsQu74dDPztp4l78pCoMVlOn7ac57bP93MsRR9JfQHujSwuCq2Vie4/xpXJq94jJ/2nOfXfRcMiU3Ppv68cGszq4lNclYh+5MsJ6sKsPxgiuH3/rGBVhMbVwc13z8Sx8u3xVZKbM5l5vPLXvOJjaLAh6tPWjlD3ZSZV0x8ep6heKUkXatrXltKqmVF2bB7nv4Cm5cO7kHQYQx0GAtO11//Q7JBxnHMD529IjcFSgsMFYydHdRM7N2Iib0bGSrHtp6+yuJYHHOeWrSPO9uG8UCHIFrsW2h2SQpFAUdRRpz6FB+XDSfQw4m5Yzvhd9VFsyrM33qW/BKtyVlXWp0gPj2PlYdT+eNACum5xZXG02h1+lXPn1q0j1VTejGmWxR/HEjmVFqeyWM+3COamOBrf79rdYLHv9/L30dSDdsEsCU+k00nL/Leva0Z3jHC5H1Tsgt5+6/K45OuplIUcor+vVjf2SaMD1edJDO/xOR4IgX4/pE4k7PmAFYeTrVYE0gIOJqcQ9KlAiJ8Xa3GVxfsT8riw1Un2HRKPzhcpcCtLYN5dmAMDQPMLxQrSebI5KY+yk2DuYMg6+y/n3DFOfoKunu+hfErq3b5AVsk7oBdX0PKfnBwheZ3Qvux4OZXs3HUJAfXK5XnLOyjqEBtejZO+fiSfs0C+fNgil3VegHyirUs3pnIhh172epsebFFoVJza2AeHXu2Z2CLoGte38maX/ddsPg4VAos3ZXE1jOZZi/OWgGn0vPYm3iZDg18WfJoV95deZyf95w31PoJ8nBiUp9GjOkWdV3xLt2dxMoKiY0hhiuP4cVfDtGzSQDBXsblL5IuFXDXrC1czi+pdN+rlemEUZLh4qjmh0fieODrHaTlFKO6kqgoiv498fGItmYTG4D84jJUimK1oGB5i1hdt/1MJg99s8No5XidgL+PpLHp1EV+mdTtuuoLSTcnmdzUR8se13dBVPpwE3DpjH6A6/3f10wsQsDa6bD5Y1Bp/h1/knoQtvwPxvwOIW1qJpaaFnsn7P3W/O2KGpreCmrLf2YTekTzxwH7Zs+U0wnIx8IqmFeoFYhrFgWtq7fQprULqk5Ael6x1foyCnAsJZcODXzxcnHgv8Na8dLgZpzJyMdRo6JpkEeVLCswb0uCxZXPhRAs2ZXE07c0Mdr+yq+HyCootWnslKujmttaGT/vjQM9+Oe5vvx1MIX1J9Ip1epoHe7NfR0jCPCwPDU9OsDN6orqGrVC6JWuz7pMpxNMXXqAMp2o9J7Qt+JpmbbsCIv/06V2ApTqLTnmpr65dAbiV5tfFVto4fhfkH2+ZuI58os+sQHjgbVCB8W58N09UGrf+j31RqN+ENz6yoKdV7ty4e0xxephWod78/GItqhVisXxJeZk4842bSxaYeHPWVcGLe6y/+B2ivJztdhRp1YphNtw0RXoxyNV5OHsQJsIb2JDPKsksdHpBKfS8iw2vAkBR5Irr3C+8dRFqy1t5RG+NbQlblfV9tHpBMVlOu5oE8pno9rz5UMdebxvY6uJDcDgliF4OGvMPs9qlcKdrUOvq3JzTdl2JpMLWYUWWvEE289kci4zv2YDk+o9mdzUNxf22rCTgAum66FUuS3/03e9mAxDC/kZcPS3momlpqlU8ODP+gQH9C1XKg2ggIMzDJ8PEbZNUR7aNoxNz/fl8b6N6dHYjx6N/HBQK9ZG9Bh8or0HECZbEnSoOOjWjSfXl/Hd9nPV2l3xUJcoi8mCVid4rG9jqxdetUqhd4y+dk1aThGzN5zm5V8P8cHfJziZllslsSqKvoXD2j5OV9W2OZVu2/kDPZ2YM7oj91SYln05v4QZK47R9s1VtJm+itjXVvLED3sNA6ht4eyg5r17WqMoVEqG1SqFAHcnXhjczObj1aYzF21LWhJs3E+SysluqfrGXCJxNVUNvLQlBfoxNtbiSNgIbe6v/nhqg3sgPLIezm7Wt5iVFUFQC2g9ApztKzUQ6u3C1IExht83nEjnkQW70QmsthJs1zXnydInec/hK9xEEaWoUSHQKDpWa9vzzKWHKbyUzB8Hknlv5XHmjetEhwb2ratki3s7hPP7gQvsTLhkMtEa07UBnaJ8mdSnEe+YWYFcpcB9HcMJ9HDm8/XxfLjqxJXt+mnln62PZ2jbUN6/tw2Ommv/fqYoCv1jg1h9NM3s86sT+jo6Fbk42Pa39dLgZgyosFxDZl4xd8/ayvnLBWivnE6rE6w4nMrqo2ksGN+ZuIa2jVEb3CqE7ybE8fGak+w6q69i7aBWGNYujKkDYwjytN5VWRd4Otv2XHrYuJ8klZPvmPomqoe+G8REiX8DlcP/t3ee4VEVbQO+z9lNTwiQAEkglNB7712lgyi+ChaKFEUUFcXyWj7Lq2JFbKigAioCFkRB6b33HjqEUBJCT0JI2T3z/ZhkkyXbEhIgYe7rCmTPmTPzzO5mz7NPhYqtb4AwngTAirw38ClqaBpUaS9/CpBONcsy/5n2TFkbw5ztp7jipmP3v0Yrlqc1ordpA9W0U6QIX+YbLTgo7LN9klItDPxuI8tf6FzgN0Fvs87UR1vw2dJDTN9wnMTMLLDwYF9GdqzKoNaVAHi8QxRnk9L4fs0xTLqGEAJNkzV8utUN48276zJzU6ytizrYd+T+e+dp/L1NjOvX4LrkfaxDFIscBBSDtIKElfC1tbTIokmlkpT08+KSi3RlL5NGxxr2StH78/dz8tJVm2KThdUQCCEYPWM7616+A7OHwd5tqoXSplooCUmpJKdaKFfCN5f761anU82yeJt00q3OSyqUC/KhUWTRKRSruDVQRfyKInOegJ0zHddY0XSZpdTn0xsjy8Q2kLAPcFHv5e4vocnAGyPPLUBiagZLos9w4Uo6FUr50blWWXzMzns2eUJqhpVW7y0lMdWzIFZP6FKnHJMGNi20btJpFiux51Mw6RqVQwIcNrc8cjaZ37ac5PSlq5QO8KZfk/I0qFASqyFo98Ey4lwU8NM1WP/fO69bQft752me/3WHVDKQFiKrIahQyo+fh7WksoNeWt+uPMI4J5YnDXi0bWW7PlKXr2bQ7J3FZFyr2VzD5EHN7Kw9twMfLzzAl8sPOz3/wX316X+dtYwUxYO83L+LlpqvkPT8GC7GwvE1MiNHWLP/r9IRur9342Rp/ST8NcrxOU0HnxJQ774bJ48LktMszN52kr92nCbxagZVywbyUIuKtK8eWiA3eCEEE1cc4fOlh0izGOiadGuU9Pfif33ruWy66A5fLxOTBjVj8A+bSLcaNjeKq0wfdyyOPsOnSw7xXJca+ZbLFT5mk9sU3qplAnnZQXxI9OlEl4oNZCbq7UvgoZbXd+O7u2EEbaqG8OuWE+w9lYi3WeeOWmXpVjfMqdvrsQ5RXLiSzqRVR9F1za5reb8m5W0NRLM4fv6KW8XGpGsciE+87ZSb57rU4Gq6hSnrYgD5PFgMgVnXeLFbLaXYKPKFUm6KIt4BMsX64ALZRyjxNJQoD40fgepdnGTvFBKNHpJBzlu+y1awQP7u5QsP/QreN7+Q2IkLKQyYtIHTl2TPJYEMZlywJ55+Tcrz0X8aXncGzsQVR65xo8j/L6dk8PSM7fh6ma7rxtWiSmkWPtuBKeuOMXfnaZJSLfh66SReteRbwfl86SH6NAi/7joiV9OtzN11mmX7EkizWKkbEcyDLSvaKjHnlZR090HPmuZ+XEq6hQV74om7nEpIgDc96oUT7J87mDk00IdRnap5LF9WB/SHW1bi920nibt0lZBAH/o1KU8NB8+lq27rWQghnDbmLM7ousbrfeoyvEMUc3ee5nxyOhEl/bi7YQSlAjzsaq9QXINySymun6QzsPoTOLpCZkf5lpRpx82HQfDNb+AnhKDHZ6s5lJDstCLsf3vW4rEOVfO9RmJqBs3fWWIrMudojagyASx5ruN1W4mOnk3m4e82Enc51WWlWk8w6RqDW1fm//rUcT4o8TRs+0nWLjL7QI0eskijWaYtH05I5pHvNhKfmC2PTELSGNevPg80d1zh1xUfLtjPxBVH3I6b+mhzOjlpaDljUyz/mxdNSroVk65hGAKzSWP0HdUZfUe1AnXHHT2bzE8bjrPq4FkMAa2iSjOwVWXqRMjPGMMQdPxoOScvXnWpiK4Y28mhG0yhUCi3lOJGYc2Aha/Alu/BMDI7Y1vB5C2Da28BxQZg07EL7I93nr4rgMmrjzG0bRWPgzmvZUn0GaeKTdYaR85eYX98ErXD869Up1msPPL9RhKS0uS8Du6UJl12so69cNXtfFZDcPRcsvMB26fD3KdlfJcwpEVuzx+wrCIM+ovUoEoM/H4jZ5Pt5ZEeGMFLf+yiYog/rTzMAgKYt+u0W8VGA8KCfWlfvYzD83/tOMV/Z++22ydAhlUwfvFBzCYtT5YaV8zfHcfoGdttbimA2AspzNx0gnfvrc9DLSui6xpP31mdF37f5XAO2W4gXCk2CkUBoercKPLPP8/DpsmZmVsi2yV1JQGm3w8nNt9U8bJYd+Q8Zjcup7NJacScd93CwBUXUzLsao601vfynddH7PV5lL0+j/Kd10e01vdyMcV9uX5XLNgTz+lLqS5Tw2uHl2DVi3fwRCf3lihdk8XxHBKzRlbDNizZwetZr/HlU/DjPSzYdZy4y87l0XWNSauOupUjCyEEXy07jDujiknXmJBZ+PBaDEM4TTPPYvyig5y4kP/XO4vY8ymMnrEda44GoYAtOPnVP3ez6+QlAO5vFsnYrjVkmwVNw6Rrtvdlhxpl+Pj+68v8yiupGbJ9xz1frqXFu0vo/flqpq2L4UoRadugULhCWW4U+ePCUdj2Iw7DWYUBaLD8PRj0542WLLc4hTDyWsqX9LPF2DxmmssrXjOwCB2zJpWCTvpO7jJt5+JRDaq+kO91Vhw4awtUdsaeU4nEXbrKS91rsfvkZdYcPud0rCGgV/0wxyfXfpZtjbsWYYVLx7m4ZQ66VtOpPFZDsPLAWVuqtzsuXElnnwsrG0irTZ+G4U5rwuw4ecltMLLFEPT5cg3D21Vhz6lEBIJmlUpzf7MKlPT3PM5j+sbjCOH8naPrGlPWHOPNu+sR5GvmqTuqc2+TCvy+5STHL1wh2M+LhhWC2RxzkZ6frQagbbVQBrWufF0NQd2RmJrBw5M3svvUZZsr8WxSGnv/3suP62OY9XhrQgPdV0tWKG5VlOVGkT/2zHZdUFBY4egyuHL+xsnkhGaVSrntxVPK34uKpfPvErijVllK+nvRUDvMK14zAGyKTc7fS61957qqR6dbDY9SwX/ZFAvA233r4uulO2zrYNI1apU0uDP+e1j1cWZKfyaGFXF4ifM2HwCaidrJ69zG/FiF48rJjnCXUZQldwln1iZkALcnXErJ4ONFB1kYHc+ivWd4b/4+Wo9bxqqDZz0TFlh75JzDbuVZWA3BnztO0/DtRTR6exHvz99PoLeZZ+6qzvgHGlEvIpjnft3JzM0niDmfQsz5FGZuPkGPz1bx+9bCa6Hy5t97iT4tqyJniS8yf2LOp/D8rzsLbW2F4kaglBtF/rh60bNqyamXCl0Ud7SrFkrlEH+n2VCaBkPaVHFZ7fZKmoVfNsYybOpmBn6/kQ8W7Ldza3ibdd69pz4DzYuxuOrxpJulK88FMeeu8NmSQ7z5914mrTpCQlK2FaJ++WCX12ax/ohUKqPKBPLzsJa2rBOzrtmehwbaEX66OgqvdZ8ilr8HE1tx+ft+WK9eBsOK5qiOUg4EglBfXLqQNA1qhnne5LJMkA8hbjJkLIagfoWSTs9Hls5bhlaW5UUISLVYGT5ti8e9jPISzJ2YamHSqiO2buIHzyTxwu87c1WgthpSGXzx950F1moiJ+eS0/hrx2mnSpnVEKw8eJYY1fJAUYRRbilF/ihZ0fW3epCVkgMdZ7IUKNYMOLgQzh8C70Co1RtKZHdh1nWN7wY3p/+367mYkm6zImS5d+6oVZZRnZ3Hpxw8k8RDkzdwLjndVs9k3eGzbFv1D+9F7aGqXzIEhdGr0cOklIjBfMWFUmBYIHajw1MWq8Hrf+1hxqYTmDQNTZNVeT+Yf4DHO0bh62Vic8wFj56SnNV8m1UuzfqX72Rx9Bl2nbqE99VzdNr1Ak04gIYBRnaTx4DY5Wz9sDdbO/xAVyOcKlqc02aeQgjCa7XEdFpDWIVD14wQMLRtZY9khszsrTaV+XTJQYeKQ1aMUG8X3c2rlQ2icWRJdpy4lGdHoxDS0jRt3XHXGWSZtKsWyv64JJfWm5wYQsbpfLjwACZdppQ705A0TePH9TG8c0/9PO3BHbtOXnLbzgNgy/GLKsBZUWRRyo0if9S/Hxa+6rhKMshaO/XuA5/CixsA4NBiWbH5ytnMthQGzH8Rmj4KPT4Ak3RfVCsbyKIxHZixKZY/t58mKTWDqDIBPNKqEj3qhTu1LKRmWHn4u41czHR1CMCbDL4wf0E30xYsJ3TQDGmR2fYj/t6B7mU2OXapjJu/n5mbTgDyBpt9Z5bFAR8zzWOkvpOapkb8Zu3IZRyvpWvQuqp9PIq3WadXg3B6NQiHXweDdtDha2fWDFqIXTy9cD2nTN152zzF4RqGAKum499yMBPKWBk9Y5utsm+WDIaQBfLub5q3VPDHO0ax8eh51mVan7KehqwA3K8fbuK2HsxrvWvzwDfrc7U68ASrIVgUHe+RcvNwy0p8v+YYmou4m1zzC8HsbScJC/Z1qWRYDcGaQ87jpZxx+WoGu05eQghoWKFkrro+nrZjLZy61QrFjUEpN4r84V8aur4DC17KfU4zyVo3d7xauDLEboAZ/aVCA9n9toSALT9Ii07fL2zDQwJ9eOqO6jx1R3W3U6dbDNYfPc+ivfGczUy7zuIV83Tu0mXcjC2uxsjMMEl3kVYN8rmp2T3X4QtX0pm2LsbFDVIwx9qWsaaZtDZHM9r8J4PSX2ansE9n1pDtAx5qWcnxNJZ02DfXpdUtQ5gI1RL5xXon7fQ9dNU3I9AwaVI6i9DREIxJH8WH3qXp1cBMZOm2TF51lMX7zpBhFdQOC2JI2yr0a1zeYdsFV/iYTUx5tAUzN8fy47rjHDt3BV9vnV71wxnRPsptwcH4y6mM/W1nvhSbLNJdpPXnpGKIP58/2JjRM7YD7hucZpFmMbBcj4AOuJpu5d1/o/l180lbryZvk85/mpbntd518PeWH/eNK5bEy6S5jG/SNGgZVfCNVRWKG4VSbhT5p9VI8CsJy9+FS7GZBzWo3hW6j5Ouq8Jk+buZJn2HDhHY/hO0HwOlozyeUgjBzxuO88migw4bI5YkiYdMy2w3+ryhSQtPs2G5zizbn+Am6FkjgVLspipNtUMEilSmeX9A+7TPSEJWgM6yPn3xYGPnlYEzUty6EzUEJbRkDKEzKuMZ+puWM8S0kOqcxIKJJUYTJlt6s0evwWeZPbMaVCjJFw81cf8UeIi3WWdQ68oMal05T9cJIRg2dRPHzuU/zdukazTMEdOTlTL988ZYTl5MIcjXi35NyvNomyqEBfvSs344NcOC+Gn9cWZtjuVqhmeKUbPKpYjf5TyN3qRrTuv4XEuG1WDIlE1sjrHvxp5uNZi5+QSHEpKZPrwV3madkv7e3N+0AjM3n3AY6G3SNLrUKUeFUje/srhCkV+UcqO4PhoOgPoPwJk9kJYkFYkSzuMhCowr5+DYKtdjNF1mdXUY6/G0360+xrv/7st1XMPAjMH75kl4a/msA2LyIv3+n5l71MTW2N3oGrSpGkqXOuVISbd41CcqRcj0XJNmUEKkcJ9pFTO0npQN8qFTzbIMblOJamVdWDZ8SoBfKRkQ7gQNCEe6hAx0ZljvZIb1TjQMBBogg5LvbRRx3S0rCpotxy+yN+76gnCthmBIZpzQxSvp3Pf1Oo7mCK5NzUjju1XHmLX5BL8+3poa5YJsPbKmZfZHckeV0ACe6lyNuTtPOx0jhLB1UXfH/D3xbDzmOB7LELA55iL/7D7NvY1lYc3Xe9flyNkrbDx2AZMmiy5muRJrhQfxwX03tuaOQlHQKOVGcf3oOoQX7ofh1XQrF1PSCfbzIsDHDFcvub9I013exK/l8tUMPl50wOE5gY4VwUERSXfyk8qtkVIiira/wsWUnbbibT9viCU82Jdn76ruVrHREFTR4+2k6qDv4kjlR/hpWEvPxNB1aDYUsWYCmlMLjmCNUT9zzWyFS2QmV+qadHeM7Og4CNswBOlWAx+zXmgdx52xfH/Cdc/xeMco2lYL5dctJ3h9zh6HlaetQpCUamHkz1tZmtlSI91qeBx388yd1aleLohPHmjI87/uRMsRr2TSNYQQfPJAQ497fs3cFOuy/pGuwYxNJ2zKjZ+3ienDW7Io+gwzN8Vy6tJVygb58kDzCvSsH37dXewVipuNUm4UtzSx51OYsOQgc3edJsMqMGka3eqV47kOEVTTvcBwUdPEsECpyh6vNX93nNNYCx0DA505RjueZk7eNgGAwP/ifkLSY7hIeTsXVEJiGh8s2E/5kn7EXb7q2FWAlXb6bipo2QGmugZempUGFTxLD7fR5mm0fXOxnjuMiez9Gpnf3j+wDOAMMiC5Y80yrDxwVnrUMm/AYcG+fPlQk1wWouPnr/D1iiP8uf0UaRaDYD8vHmxRkcc7RBVaA8RDZ5JYfiCBDKugbkQJEhJdF+9zx4DmkbzcvRa/bj7Bi384bpWQhdUQHD17hfVHz9OmaihBPmbKBvnYWmM4445aZbincXkA7m1cgfrlg/lp/XFWZwYPt6seyqDWbixw13DyouP3TRaGgFMX7dtxmE06PeuH07P+DbC0KhQ3GKXcKG5ZDick0+/rtVxJs9q+1VqFYOHeMyzff5a1NftQ+shfzmNITF5QoYVMvQ4q51bRSUhKw6RrNsXDCwuPmBYz2LSIyvoZ0oWZhUYzrghvArT8tVEowyUOU97umFUILl7J4O425fllYyxWYV/K34SVEqTwtnnqNddpbDNq8GCLHLFNQsD+f2DjNxC3Qz4HNXtBq1FQLjP7x68kDFvEpb9eI2DfLHw1qSAeE+F8ltGPv422aED/5pG8f18Djp+/wtJ9CaRZDGqHB9GheplcQcJ7Tl1mwKQNXM3Ifq0uX81g8qojzNt1mtmj2lA2yDdfz5kjLl/N4JmZ220Vm7MsHyV88/+R1rlWGd65px7pVsOha9IRJl1jx4lLtKkaiqbJNPaPFx1wWv/GrMPH9zeyO1atbBBv9a2Xb7kBQgO9OXExxem6GlBGVRxW3EYo5UZxy/LKn7u5kmrNVUPEaggyRAYfnGrI+77L0VITr1FwMp0pQREwqUP24ciWMsMrsoXD9coG+dhuzN5kMMXrQ1rr0WQ5Zrw1Cz30TXbWjrySIBxbWQSCtJiNrOiQyLKDF/g+riLHjHC8yKCvvo5nvf6ws9oYQsbDRHUblR34KYRMi985I7NtQqacO2fInwd+glo95TG/UoQM+IqN+1/i8z+WcCIZTlIWQ8h060daVeLVXrUBqBQSwNB2VZzuSQjB0zO3k5JuyWU9sAqIu5zKm3/vZeLDTd0+P2kWK4cTktHQqFo2wKF7xGoIHp2yiZ0nLtuei6y7elKqZ/FQJXzNJGaOrVjan0fbVmZgq0qYTTrLo89w2UEwuSOEEHZ9y4a1q8KKAwlsPX7R7rkw6RqGEHx0f0NKF4IV6/5mkWyLveRcTuC+ZrdGI1uF4kagCZGXGptFn7y0TFfcPI6eTeaOT1Y6OCN4xLSEUea/iNCyAih1sovHAyUiIOmMfJyzloumy1TswX9DpTa5Zr58NYPm7ywh3WowyjSH582/uc+K8ikhA6n9Q2U1ZiduMoFUuY4Y4YzOGE20qGw7V0mL5yuvz6mnx2QqJXIvKVW6QslK+G+fjKHp6Jl7sQgdTYOYjp9RtfMgOUlqIkz/D5xwXCAQNNmt/bloCAi1O2M1BGsOn+NwQjKBPiburF3OaV8hi9Vg7eFznLh4lVphQTSrXJqNR8/Tf9IGl0+TrsHGV+6iTJDjeTOsBl8sO8zUtcdsSkewnxdD2lTmqTuq4ZWjW/vy/Qk8OjX/TVmrhAaw7PmOWAyBxSrw9bKPDfplYyyv/LnbxQz2LHi2PbXCsj9LUjOsfL/mGNPWxdhcVO2rhzKqU7Vc9YcKiqvpVu7+cg1Hz13JlX1l0jUqh/gzd3Q7Wzq4QlEUycv9+6a/0ydOnMhHH31EXFwcdevWZcKECbRv397h2Li4OJ5//nm2bt3KoUOHePrpp5kwYcKNFVhxQzhy1nHp95fNMxhpnneNhcAAdJmp1W8yzH6MXIoNZD+e+ww8uSlX34BgPy+e71qD9+dHM9i8CN2DEF+e3AhB4XKuzd/DP885GwlAJe0Ms7z/R6/094gV5QjlMr97v0UpkuxlBHyOLeG0fy0udf+eiIM/w6ktCN2MuWYPaPkEVbOCuK0ZMK2PdEM5RUjFa/tP0G6M3RmTrtGxRhk61nCddvz1isNMWHLILsA2yMfMnbXL4qLQLiCtK4cSkhwqN1ZDMPLnrSzbn2A3x+WrGXy+9BD74hL55pGmNlfY3J2nMemay5oyjoJrs6obf/NIUzRNw8uk4agWYFiwZ+4bme0WYqfYAPh6mXiyczWe6FiVpDQLPmbdbdFBT0i3GKSkWwj0MWM22bf48PM2MfOxVjz3605WXtMbq01UCOP7N1KKjeK24qa+22fNmsWzzz7LxIkTadu2Ld9++y09evQgOjqaihVz10hJS0ujTJkyvPrqq3z66ac3QeLbECHg5GY4vFQG6FZoJuvY6IWbTRHgnXv+GtoJRprnAThoCWDAxWOwYzpcOOx8YmHAuYNwahtUyO0meaxDFMHiMuVWXHIvZMmK0kqURfNhMsZl4auQlujwErNm4CfSeNw0j1ctwxhsXkhpkjBpuV1dJgwiU6J5/O89+NR/g/eeq0+gj4M/2R2/uFFsMhECTm5xP84BHy3Yz1crjuQ6npRmYc4O5+nMOXGWgbNobzxL9znOchLAougzLNl3hq51ZffySynpbovlGQJe71Wb6RtjOXnxKiX8zNzXtIKtNo0r2lcvQ+kAby5ccR1XVSssiM8fdF7bR9c1gv2cN/j0lMMJyXy1/DDzMoPq/b1N9G8eyROdqtrFMYUE+jBtaAuOnbvCxqMylb95ldJULeNB1WyFophxU5Wb8ePHM2zYMIYPHw7AhAkTWLhwIV9//TXjxo3LNb5y5cp89tlnAPzwww83VNbbkqR4mPmQ7GKtZ75VDAuUKA8DpkNE40JbumnlUgT7ednFPgwwLccidLtu23YIA/bO8WyBi8ccKjeapjGgVTVY4cEcUZ2yf09NhL1/ynlDq8Op7eAkNsesGfQzrWaytQdDTfMdKjZZWITOPaY1PLGzObtPXWbOqLa5yumzZoIHwoJMecq7UnrxSjoTHSg2eaG0v7fTrK5f3KQxmzSN6Rtj6Vo3jJR0C4fPuqkCDUSU9GVY+yiGtfe8gGMWXiadN/rU4ZmZO5yOefrOaoy+o7qdu6ww2HniEgMmbSDdatgUupR0Kz+uP8783fH8+WQbwoPtCzZWCQ2giuoJpbjNuWldwdPT09m6dStdu3a1O961a1fWrVtXYOukpaWRmJho96PwAEsaTLs72yJgWLJbDCTFSzeIrSpxweNjNjH6DtlaoDxn6auvoYW+z30w79Xzni3gV8r5Od8SMvjYXdfzOn3l/9t/ho9rSHfXui/h1FaEGzn9tHQWeL+Mv+Y6bdisGYRo8j0bc+4K7/4bnXvQ5ROu5bRhQNU7PBybzS8bY/PcgPJanuhU1akicPTcFZdpzFYhOHbuCukWg0HfbyL2wlXngzNpWun6Wgf0bVSeiQ83IaKkvZUnqkwAPw9ryXNdaha6YpMVqJ1mseayVFkNwdnkNN78e2+hyqBQFFVumuXm3LlzWK1WypUrZ3e8XLlyxMfHO7kq74wbN4633nqrwOa7bYj+G845LmiHsEJ6Cmz8Frq9W2giDGtako7bJlH1wgqbG8pt+Lt3oHQNuSre5x8ClR3Hddlo/zz88oDjc7oJQmtBVGfYNw/+ejL7XGZAsbvSdYaQqebuxlmEzgkhO6sL4M/tp3i1Zx2C/b3Yc+oyP66P4T+WKJpqB90HP/uHyIaneeRgQt4q/mbtSc+MixnWrgrD2zvPtirl58Xpi1edKlAaUMrfizk7TrHluGdFGQ3DjRLsAT3rh9O9bhhbYy9yPjmNsGA/GlYIvmGFCdcfPc/x887bSFgNweLoMyQkplK2RMGl2SsUxYGbHmF27QeFEKJAPzz++9//8txz2UGeiYmJREbmrUtxoZFyQcaIHFokLSUVmkOzoRDiuPJrgWNJhz1/wPYf4fIpCCwHjR+BBg/A3tn26cTXIqywa1bhKTcZqWjT7qb6pWg7TcHlW0PTpezl6sI/zzsfd8drYHaTjlujG/T4KLMxqCafB02X+y5dDR75XQqz7H/gUeOEbAyhoXvYm8qsGcyydLI9zrAKDiUksePEJd75Zx8mXSOZbrTwdqKIZqGZYOCf4J13d0VZJxlOrigV4EW/xhUY0KIi1coGEnf5KjM2xrLp2AV0XaNttVAeaBZJmSAf7mlcnr2nXVtU72ksawC5C1zOwnr9ug0gFTSzrvHv7njWHj6HQAYRP9q2Ck0rubD+FQAH4pM8CtQ+fDZZKTcKxTXcNOUmNDQUk8mUy0qTkJCQy5pzPfj4+ODjcwsWrzq5FX6+VwaeZn16ndwCG76C3hOg6ZDCXT8tCX66VwYLZykxl07AyU2waRJ4+TlXbLJw1wH7etj9G5zxPB0XkPImxkPPT6TitvRtsFyV8UKGBcx+cNcbUoH0hJaPQc0esO1HOLsPvPyhdh+o0QNMZjh3CM7uz5OIFqFzFR98RRpeLmJtQN64/jLasknUsju+Pz6Jd/6RReashmAhzdlorUUz/aDz+J17v4WAMnAmWgZB+5X0WOahbaswefUxj8cL4MKVDBpGlqRa2UAW7Ilj9IztWA1hcz9tOHqeL5cd5vvBzbi/WSTfrzlGQlJa7jRmTaNcsA//aVqBicuPeKTY6BrUiSiYMg8/bTjO/83ZY7NCgezjNG9XHG/dXZfBbSoXyDqO0PBMkSuITCyForhx02JuvL29adq0KYsXL7Y7vnjxYtq0yV2DpFiRehl+7gdpyfafXsIqH899Fo6vL1wZ5r8kM4YghxKT+X/CPhlXo7vSfbU8ddvOM9t/dh/z4oiD/8K2qdB6FLxwCO75Gjq/Kv9/4RC0eiJv85WMhDtehf4/Q79JUrkxZT4vqe7jt3K+vBah86/RknnWlrh3XMEka2+ez3jCbmzpAG+W70+wa1hpxcSjGS/yu7U9GcLBjS6isVRYx9eGr1vDR1Hw+1C4eNytDADhJf24q3ZZj8ZmoWuy39HhhCSe/GU7Fquwi6sxBKRarAydtpnUDGtmA8rcWT1WIYgKDSQp1ULpAG8PnjVpDe7f/Pqts9GnE/m/OXsQYKd0Zf3+xt972X3y8nWvcy07T1zi0ambeHOug/iqawgN9KZB+Ty231AobgNumnID8Nxzz/Hdd9/xww8/sG/fPsaMGUNsbCwjR44EpEtp0KBBdtfs2LGDHTt2kJyczNmzZ9mxYwfR0e4/BG4pds6UCo6ztgG6CdZ/WXjrXzknXUrO1hdWGaRquKn22nx4wcuWRXK8e8uRQzTY8LX81ScIGj0E7Z+Tncu9/AtUREpVwp2SommQIXQGpb9Iy7SveDpjNItEc7w0Z00rZVXfaKMi71sewrjmT3Rkxyg2HD2P1RA00A4z3vwV33p9wiDTIt6wDKFV2pc8lj6GCRn3gskHqneHuJ1wKkcKuGGF6DkwuTNcjPFoq5MGNqNhec+tIYaAk5euMmWtnN+RAUIIWbvll42xRJb2p2sdxxbb9UfPc89Xa+lezzOL7gf3NaBcAbhpflwfk6vNRE5MusaP62Oue52crD50lvu+XseqA+fcDwae7FwtV80bhUJxk2Nu+vfvz/nz53n77beJi4ujXr16/Pvvv1SqVAmQRftiY+0zcho3zk4/3rp1K7/88guVKlUiJibmRop+fRxe6vq8YYEjbsZcDye3uFdcAKre6VgOTYeKbaDRIwUvWxbBFWQ2Vp4VHCHr2KRfkW6onTNgw0Q4s0fKXaUjtH06X1lDuQgIhZBqcP6Qy2FemkE7fQ/h2kUWW5sSF9KGK6IKfsmx6A4UTJMGEzP62h5npUk/0qoiw9tF8d2SHfzt/QpVc3QI72bayljzr/xfxmB+MbpwJaIFDP0Qvmxuq3hsh2GVndUXvQ79f3K7VV3X+Gt0e975J5rvPHBRaRqUCfJh2f4ElzVpDAHL9ifwQPNIPl/muD6R1RCcv5LOmcQ0KpTy4/TlVIdzBnib+OaRprR3U4zQUzYeu+BSdqsh2HDMw+w8D8iwGjw7awdWIVz2iNJ1DcMQPNGpKkMK0S2mUBRlbnpA8ahRoxg1apTDc1OnTs11rFh0ixBW3AagGs6/2d8w6j8gY07WfpadbuwbDM2GQceX3AflXg+NB0HMmuuYQIe/n5QF7rKsH8KAY6vg6HIZLNzyseuXs0Y3WO9auQEY4bUAhOBdrx/YfaU2/5ga08OcSFDGeaxCw6QJWw2f8Rn/YZ7R2nZtt7phPHVHNepGSPfDfPOLlLbm/mZvwuBdrymczwimXt1H5POXesm5UMIqm2wmn4VAzxSC13rVoXvdMN6au5fdp5y75YSAB5pG8vEiN4HOgMUwmL31pMuwbKsh+GvHaRaOac9zs3ay5fhFm81MAO2rhTJhQCNCCrA5pMmF1cY2pgCTH5buS+B8suvCgQIY1rYKA1tXIrJ0AVsiFYpixE1Xbm5LKjSHI8ucWyU0k6wEXGjrN8sOsnWKBpVaS9dLs2FwfB0kxUFYPShbu+BlOncIjq0Ew5CNLeveC5u/kwUEnbnPHIqty+f34L+Zig3YFdPLmmv+i9J6E1rt+uRu/IhHLkQt87U2Y6WRZQ8NLXvQNThhlCFWlMGEwQERyS/WOzkgZHVuk6ZRvVwgEx9ukp1BuOs3QoxzDr1hWZk1b3j9hLnFf2H7HPevs7BKC5mHyg1As8qlmfV4a+7+ci3HnPQyqlYmkLsbRbD8QAKLos84tYDoGjSKLMmpS1fRNdlc0hlXM6z4eZn5/Yk2RJ9OZOvxC6BptI4KoVrZgq/C26lGGYf7y8Kka3SqmbdYJFccTkhy21YC5OusFBuFwjVKubkZNBkMqz527C4AecNp5diaVSAEhEKFFhDroliiXymp2MTtku0EYlZlnwtvCF3etq/Qm19SLsheUIcXQ87v4hWawd1fwbovYNfM7Bu0bgbdS6bOOyqUJwxo+4y0Nmkm54qRpsPWKdefyl62tsyeOrTIYyVM07J3Gq6dR8egZ/oHXCb7hmXSNQK8TXw2oLF9aYS1ExDCeUq8pkEE58GUAj7Bnsnkm/fMIn9vMzMfa8Xz1/Qy0pBKwcf3N8TXy8SQNpWZv8d53SpDwB/bTlKzXAm3yfQmTSPIV35k1YkoUWAZUc4Y2LoS09bHYJD7r1TL/BnUulKBrefnbfbIMj1tfQzP3FVd9YpSKFygItFuBiXC4b7v5A02Z0aSlpnp0moU1OpdeOsLAclnXI+5egF2zIDvu8Lxtfbn4nbLNPIDC65PDku6rIJ8ZFmWYNhuI6e2y4yyrv+D5w/AgzNhwAx4bj88vjLT0pB1iyH7ebzrTajVC+J3u76xCyuc3iF/T0+R7qrDSyDZcY8jl9z3HdYqHeWWMJEhPP+zMmsG4doFxpbbTInMG7evl86A5pH883R7aoYF5ZBZcDHhFMKTnKGUi1C7N64DnjUoU1vGDeWD0MxeRsvHduLD+xrw4X8asOKFTnw/pDmlAqTLsmVUCGO71gCcu3nSLYI9py67tFiYdI0e9cOuK+05NcPK9tiLbD1+kStp7mPOKoUEMPHhpphNml0vM10Ds0njy4eaEFWAfZu61innslJzFqkZBov2uvn7VShuc5Tqf7Ooe48s1rfhazgwX1a2Ld8MWo6UcRyFWQX1UixccNMrSDfJAnXWdAdKggFCk+0Gqu3NTo3OK9FznNeyEVbpBts6VWY71eyRfS6wDIzeCrt+hX1zISNFWpOaDc12mZm85XGnaDJmaNk78jXIqtmjmeRr0+MjCAjJfZk1sw2FV3Y2Tqrux8ArY0lP60Qf0waiOMUd5p15eCIEHa8u4ZE3PiDNYuBj1h0Wssw4tp5FGQ24z7TK/beSEhHg7Sefk83f4yRfSRY0vM73mrteRk/dUZ3GFUvx8cIDbD9xyeGYLOkcxd3oGph1jdF3VM+XfBlWgy+WHmLquhgSU6VS4+clm0++1L0WfplNWlMzrKRbDYJ8zLbnv0udcqx8oTO/bIy1FfFrWy2EB1tUpEKpgnUNRZb2p2ONMrm6el+LSdM4k5haoGsrFMUNpdzcTMLqwz0Tb/y6VtdBi4BUXhJPuRog07WPLofqXfInx86ZbqogG7KCc/vnHJ+v3hUaDnBcdbdWb3t3Vu7J4fLJHFajrMNW2Xzz0GIpmzUDwutD5Q4ynfrIcnlt6Sho+QQ0G8qnSw6xNfYShqhGZSOeQV4LXbqOrkXXINCaiKZpLi0Tizds5WdrF/qbV7qczwiMQPfObKbY/X0ZnL51aqY/zCQVabMf9Po407pT+LStFsqszSfY5cZCE+znRWJqBobIzhIrX9KPCQMa21uxPEQIwdMztrNgT7yd0nQ1w8qP62PYe/oyz9xZnUmrjrL6kFReygX5MKhNZYa1q4Kvl4mIkn6M7VaTsd1q5n3jeeSVnrXcKjdWIShb4hYsTKpQ3EIo5eZ2JDhS9mByVWFYeJAqjuZxnRSHXDnrPtU75ZpU24R9sHwc7J8nFRHdC+r1g04v2xcVbD1KKjeObAGaLg+dO+h4TWGVlaOziN0IsRvs57pwDOa/iPXwUmYeHIwhoKW2j0+9vgZEnowhhtBIDaqIYQii4xK5kmahSmhArpL6Oy/7YsJ1VWghwKKZ8M7Srkxe0GeCVBD3zpHZU6Uqy4Btn7wrC9dDzHnnwblZWIVgwyt3smxfAlczrNQoF0TrqBCX9WZcserQOacxP4aAzTEXGfj9JnQt+11yJimNjxcdYMWBBH4a1vKGVgCuGVaChhWC2XXystMYJD8vE13rhN0wmRSKooiKubkd8fKV7R00Jx/amg4+ngRrCtfdtd1RqrJzGaQgULJi9sNT22DyHdmKDUgrxO7fYVJnOJsj7bhcXVlV2OyTabHQs9cSAofByE4R1/yf9btAP7SQXpYlAIwy/4WBfXyGJ+iaIDA1nu4fzKX3F2voP2kDrcYtZcSPWzhxIdu15l0ijDtMO7C4iOnRNPBOOpHb6layoqzv0/55uf8/R8L0+6WieNmVha7gKB3g7fa5CfbzomyQLwNaVOTRtlVoWy0034oNwIxNsW5TugWycKLdMQFbjl/k+zWet50oKF7tVQddd/4+erF7TQJ81PdShcIVSrm5Xen0XwhrkLvFgW6S3/YHTLdXLBzh5Sfjg/JLk0Hus3maPir/z7ohW9JyXyOsslfWvGftj9fsAc/tgy7/gzp9pYWnWhc8aX2QFwabFuJDOu31XZjd9Ityhv/V0zyb8oXtcVZxu3smruX0pasAdGrTGm8sngUUW9JyHzsTDZ81Qsx9GrH/H8ShRYhVHyI+awA7Z+VL7rxwT6PyLgNmdQ3ua1KhQNeMcZHK7Q4h4Md1MTe8tlaLKqX5aWgLKl6T7l3Sz4v/3VOPR9s677CuUCgkSv2/XfEJhEf/gY3fynoyiadkuf56/WQqddnaMvPodxdNJju8eH2ujap3Qs1ecOBfcruOTLInUsMH5eOTW+Cci4Jwwipr8Zw7BKE5Ak/9S0Ob0dmPP6pG3qw2rtEQ1NRP4kO6W6uEwLlaZdYE3fXNlOcsp5A1Z6yG4FJKBhOWHOTD/zSkSeUQVuLjsnUDIBXUEuVJtxjM3XmamZtjOXUxhZDkQ/xHa8T9ppX4a5nKjzAwhAF/Po5WOgoim+dp/3mhR/0wvlkZxKGEZIe1cUr5ezGwAFOrAUICvW2xO/nhTFIaSWkWSvh6Fahc7mhTLZTlYzuxLfYisRdSKOnvTduqoXib1fdRhcIT1F/K7Yx3gIzFeC4aXj8Hr52Be7/Jzjiqdx/0/UrG54C8aYLMROr8GrQbc33r6zo8MA3aPWsfFGzylladQX9lZyW5Umxy4iyOJovUgm90aNXMJOJPvCjlsouzO3uLrgla6vvs5zYEc7af5mq6FU3TeMRrFYnCD0M4nk0ISPGvQIow89DkDTz/2062Hr/I6ctp7LFW4E3LYPqkv8NZke121AGr0Ehc/qmHO84fPmYT04e3pGWV0nJdDZtCWK1sIL8+3ppQDyoMp1msrDx4lrk7T7P75GWXlpV7G1fIt2ID8jXzvkm9mzRNo2ml0tzbuAKda5ZVio1CkQeU5UYhMTn5Ztr4EajbT5bpv3xCFgCs3ef6Ym2uXfeuN6HDC7LBo2GVWWR+Je3HOcqIckTCPmlNqtDCLl3bRnAFuHD0eqW2Q/fy47F6ofy4rSvPm3/F5LYcnYu5tNzXplsNziWnEVnan7I1W2HZPx8EtrYNgF121ocXO3Bg6ma2xV4Esq0WIvO7TIwI47mMJ/jJ+wPbGmbNwPfY4twCpSXLwHP/EOfvkTwQEujDLyNasT8+kTWHzmE1BE0qlaJZpVIO099zIoRg2roYPl1yiMtXM2zHa4UFMa5ffRpXzP2e7N0gnG9XHuGoA/eUO4uOSZNZXjcyoFihUBQMmigWzZo8JzExkeDgYC5fvkyJEoVb4VRRgKReho9rgMXT+h4aBIXJ2KIGD8j4IJAVjxf/Xz47jrvAO4A079Kkpl4lyHIuZ3nB7ErJrtLeM+mc9gnHRPi1O2HHG10J9vOSmVs/dEM4iLyxCo1LBNAu7XOu4r4r9lLv56mqx9keW4TOlZcT5Dont8DKD2XlZYS03jUZDB3GSlffTeCblUd4f/7+XMd1DbxMOn880YZ65YNznT+XnMboX7az/uh5m6XIEFAnPIgMq3Co+IBUFmeMaEWrKAf1jhQKxQ0nL/dvZedUFA18g6H1U3geDCxkEcC5T8PXbSEps6Jrs6FQtq7zLK3wRvmTL/0KPsknCLZeRNdMaDbLlibbVAz5B+rf73Rdi9BZZa2fS7ExaRqda5WVCgdAxZak9/4CQ2hYMl1ThpA/lwhkYPorHik2AJuN7LotVqGxR1Th4pV0OLgIfugqKzZnWaHSk2HjN/DdnXDl+jthCyHYcPQ8r8/Zw7MztzNhyUFb4LQjLqWk84mTJpyGAItV8OGC3IoPyErKMx5rxYJn2/Nqrzq80rM2f45qwz9Pt2f6iJbULCfjxsy6hikzS8nLpDH+gYZKsVEoiijKLaUoOnR+Rdaf2TQ5M7Vbl6ng7rhwBKb0gCfWSvfWo//AvOdg7+xsS4rZD5qPgJAoWPwGpOUzNkdYAU1amJ7ZCYFh0j127pAsKJjLcqNhALGiLM9nPGF3RtdkWNKzd+UIkLakcTVuPyZ8CNSkFcuCiVVGA57PGEka3nTQd7LKaOhW1JxqokkTTLN04y0fAbNHyAam17rXhBUuHodlb0Ofzzx9RnKRmJrBiGlb2HjsAmZdQwiBAD5feoj/9qjNiA5Rua6ZtysOy7X52jmwCsHqQ+dISEzNVR8oi1phJagVZv9tr2yQL/NGt2P14XMs2htPaoZBzbBA/tM0ktIBhdj1XqFQFCpKuVEUHkLISr+bJ8teT17+srVBs2EQXD7v8+km6PmR7L21+zdpjdn+o2cVly8cgfF14P5pMjMs+i/789Y0WP955oPrTRUXUrmJ/lvWljm9XSpXljRyKQy6CdH2OaZfuovzW86hZcbOGELeeMf3b0iDCiUzZbTAL/0pcWwlWo6Uc2/Nyh36dr70+px6+nF0YdA8/WvScR0j00Lfb4vb+d3akbTa91EiZoEs9Od0a1bYOQO6vuM8U+5iDJw7LBXJCs1yxeqM/mU7W2JkPJDlGnfQu//uo1ywL3c3jLA7npCUhknXco23Ey1znDPlxhm6rtGxRhk61vC8M7ri1sEwDNLTPfgMUBQJvL290fXrdyop5UZROAghe09tm2bfnXvNBJl+PugveePLD6WrQMcXITURtnzn+XVXL8CPfZzIm9OiUgBhaELIruuNHoapvSDDictFCEwJe3n9wVd5vGsqS6ITSEm3ULVsIB2ql7EvQLd3Nhxd7lD10jVob9orlRVd8IC+nF+MuzAceJ5NWOmg7aKSdoZdIopplm4sMnXgr6612LZ6JT9njGKnUQUfMuiib+Vh81LKapeyJ7CkydYVWVl1WZw/Av88B0dXZB8LKAMdX4Lmw0HTiD6d6LK9gAZ8sfQQfRqE2wUYlwnywepBeGDZINWW4HYiPT2dY8eOYRgFHEOnuGnouk6VKlXw9r4+y6lSbhSFw7YfpWID9kX3hFXe6Kf/R7qB9vwOVy9CULgsutf0USgZ6dkaV84VvNyO0M0yW+jKOfdFB21oUsH57i5Iv+J8mLDKOj+JpylbIoKHWroonLjlB5dByUJgy5561esXDqdXYIOog44VAxMaBgKNqtppPvH+hnTMDEz/L1UqhPNbvwb8syuOTzfXwoQVKzI2aL81ku+sPfnR+32a6oeyF8sK0M7iYoyMx0lNtD9+5Sz8O1a+xh1fZMm+M5g0zamiIoBDCcmcvHiVyBxF7HrXD+ftuXvJcOKaMmnQumponq02iqKLEIK4uDhMJhORkZEF8m1fcXMxDIPTp08TFxdHxYoV3WZQukIpN4qCRwhY/yWOezwjb+hXL8KqD7OPXb0ICdGw+hPZELP7+7Jruiu2/+R8jYLEsEDaFajSXloldLNMWXe3rncgXPQk7VzI1hElIlwPu3DEZbZVzs8BPy2dn7zHscBozkxLZ06KMpTRLnG/aRV9TWvx1WSs0rz+pajUuB2Lo8/w6RJZIyhLsQEwMHEVHx5Nf5F1PqMJ1NKgbB0oeU2xvRXvy3goZ8rfivehySBSM6xSTjdPXZrFfp5SAd48e1cNPlqYO6hY18Ck67zYvfAbWypuHSwWCykpKURERODvX7Ad2hU3jzJlynD69GksFgteXvkvP6GUG8X1c3qHVEy8/KFqZ3nMXTE9VxxaDCc2wvBlEFrN8ZikM7D3TwpdscnCSJONOa9eguQE2bDz8nHHYzVdxptcPonHyte1lhBH+JaSa3uIl2alj2kDfUwbnI6pFCpTpyevPopJy91jCcBAJwl//rS2Y6B5CXR6yV6TSr8i+3sZrqxaAnbOpFb4Ay7jZkA2hixfMvfNalSnqviYdT5feojE1OzGrlFlAvngvvrZsUmK2wKrVb7frtd9obi1yHo9rVarUm4UBYAQmV3CNdmawRPO7JX9nuJ3ZR8z+0BTFy0bPBNGFo9b9Co85KDn0drPYembbm6mBYw1Q7qFHJHTVaTpMvPqod/g76fwSLHxD4XyTd2Pa9gflr1TcDV6NB3C6mMYgs0xF9xUVxZsEHUZ2LO77NOVk5Tz7rPWNBMknqJbq3KU9Pfi8tUMh+uZNI0HmlXAzzt3yrymaQxvH8UjrSqx/sh5ElMzqFjan0aRJa/LfK0o2qjXvnhRUK+nUm5ud4SQ7p11X2a3OAhrIPtL1bvP/ht6Ts4fgR+6QXqK/XFLGmz82qOCda7lssLBhZAUL4vxZbHjF1j8ev7nLQyEAYHl5E+tXtB0CGl+ZSCoEj4Xjrp/Hto/51n136aPwsZJMo4ll/tHJ889s4QhlVGPjF8aokZ3aNEm9ynfku5fb2FAQBl8zCa+eLAxQ6duxhDYFc/TNahaNoDnurp2L/l6mehcq6wnQisUitsUFYF1OyOE7KT992h7N9KZPfDHMFj6tvNrV30EGSnOYywKxLog4NKJ7IeGASvGFcC8hUBGKmLYIv4MfoSeUw5R87UF1Nw/jHtS32CB1YVVploXmdruCf6l4dF/oUzmzV8zZRcFLN9YFiiE3J3eXXFiE7qu0TiypMvGnwKN5tXCHZ/0LQE1ejgvjAjyfVL/PwC0r16GP0e1pXvdMFs2WGl/b57sXI0/nmiTXbBQoSiCaJrGnDlzbrYYeWLFihVomsalS5dutigFhrLc3M4cWgRbp2Y+yPH1PUsxWTNeZjBFtrC/zpLmQYxFAeGbo5x+wl64FFv4a+aHtMvMmjGFl6Mr2Rm7qmmnaKfvtev9ZKNsXRgw3bl1DKQ7bNuPsOlbWQjQ7Au175bVmpPjAQ2qdIQKTaWyWqmtDN49f8j5nDmZ1hsenc+I9lE8MX2bwyG6Bn7eJu5rWsH5PJ1fgSNLwOLsPaHJAoClZYG+euWD+erhJmRYDdIsBgHepjybozOsBgv2xPPHtpOcSUyjQkk/HmgeyR21ytqn0CsUBcCQIUOYNk1mgJrNZkqXLk2DBg148MEHGTJkiC1bKy4ujlKlCqj33g2iTZs2xMXFERycu31JUUVZbm5nNk1y/W1bN8NmB3Vk0pI8qwx8XWgyKyc0R3Xea11gtxAC2HNAWr+yYkl66Bv52HsSAaQ61l9qdJduIWdY0uGXAfDP83D2oFQ6M1Jgz2/S4hbeULq0KmRahjRNWkdCa+BxIULDAgtfoXu9MEZ2lNlpORUDk6bhbdb5blBzSvheY1G5cFS2ZFg+ThYqrNjW9Vp/DJN7yoGXSSfQx5xnxSYxNYP/fL2O0TO2s+rgWfbFJbLsQAIjftzCkCmbSM24gfFYituG7t27ExcXR0xMDPPnz6dz584888wz9O7dG4tFBrmHhYXh41O06i15e3sTFhZWrOKXlHJzOxO/23XdFsNiHyychU8J1zflguLONyDlAuyYIZWsK2e5Vd+yGnCGnH2IBC+bZ2A4sthkse4zaQFz1qtpw1dwdClSdcphWTOsslrxr4Nz19C5cAwO/IOHgTRSYTqxEe3iMV7uUYsZI1rRpU45IoJ9qRwawIgOUSx5riOtq+bYW+xG+KoVfN4Y5r8EK9+XwdNHl7laSAYeH/jXM7nc8PIfu9lzStbUyQrbyYrfWXv4HO/9u69A1lEocuLj40NYWBjly5enSZMmvPLKK/z111/Mnz+fqVOnArndUi+99BI1atTA39+fqKgoXn/9dTIy7L8cvvPOO5QtW5agoCCGDx/Oyy+/TKNGjWznhwwZwj333MPHH39MeHg4ISEhPPnkk3bzXLx4kUGDBlGqVCn8/f3p0aMHhw5lW3CPHz9Onz59KFWqFAEBAdStW5d//5V/j9e6pVyNLSoot9TtjJcHtSEcjTF7Q/3+sHP69bmmND3TzJF5d8qqZOwTBJ1fhy3fw8yHsvs1IcArILPa73XG9OhmqbwVEGl4sdzawPa4rhZDJd1N2rZhkdYM3QsaDpC1fbIy1QxDWkWcpjAZMrtt92/QdEimEEkwtXe+5F++eSedu0XRumqIvSJzLTFrYFpfEPl47nQzJOyTLTiug1OXrjJ/T5zTp8YQMGvzCZ7vWlPF7ygKnTvuuIOGDRsye/Zshg8fnut8UFAQU6dOJSIigt27dzNixAiCgoJ48cUXAZg+fTrvvvsuEydOpG3btsycOZNPPvmEKlWq2M2zfPlywsPDWb58OYcPH6Z///40atSIESNGAFIBOnToEH///TclSpTgpZdeomfPnkRHR+Pl5cWTTz5Jeno6q1atIiAggOjoaAIDHWfG5mXsrYpSbm5n6vSFdV84t95oWu603yw6vgD750HqZc+r9mq6rERsTZexI3X6QosRMnV639/ZlYqProAFL2Fvfcj8PSMFj60SrihAxQYgWq+JJcefU7DmoipxLlkyYMd0OH8YBs+VmVNXL8hMMZdoMuh78/dQuR14B8m+WfngfyvOccjvCI91cFE4MaulRn4UG5BWovjdsOZTCK0pizWa8v4RtOHIeZdp6wBpFoPtsRfpVFNlVSkKn1q1arFrlwMrN/Daa6/Zfq9cuTLPP/88s2bNsik3X3zxBcOGDePRRx8F4P/+7/9YtGgRycnJdvOUKlWKL7/8EpPJRK1atejVqxdLly5lxIgRNqVm7dq1tGkjMxqnT59OZGQkc+bM4f777yc2Npb77ruP+vXrAxAVlbtBbRZ5GXuropSb25kWI2RTy4yrubObNJMM5m080PG1JSvC8CXw99NwfI1n65l95c3bUeXhFiNk6f6JrdzcoG9Q0b48crLKfzBFC9prOxhkWkRD3ZPKxDkQBsSul0pevfs8Sw3PcvWknJc1hzxuDZGNVWhEi0ocFRF8sOAA9zauQBln/ZlObpYKWH4RhnSZHVogLX6B5aDfJIjqlEeZPXsPeDhMobhuhBBO41V+//13JkyYwOHDh0lOTsZisVCiRHZ3+gMHDjBqlH3GZIsWLVi2zN7NW7duXUym7BjJ8PBwdu/eDcC+ffswm820bNnSdj4kJISaNWuyb5900T799NM88cQTLFq0iLvuuov77ruPBg0a4Ii8jL1VuTUDGBQ3huAKMHBOdkaSbpY/IBseDv5bph87I6QqPPoPPOig0N61ePnJZpnOWipkpMreRPm0PNw8NPAOoEWTprzjPYWp3h/RQd9NiJYE5PEGq+mw7Sf5u2+wDBj2lHwoNobQAI33LA/LKYTgz+0nnV9w0UlF5jwvnCnrlbPw83/g1NY8Xd60kvtMFJOuUb9C8cn8UNza7Nu3L5cbCWDDhg0MGDCAHj16MG/ePLZv386rr76aq4v5tYqRcPDBcW21Xk3TbA1DHY3POp419/Dhwzl69CgDBw5k9+7dNGvWjC+++MLhdXkZe6uilJvbibRkWb7fmsOtENkCxkRD369k3EfDB6Hfd/DsLgir79m8NbvLAnPOMnRMPjJWZlpv+LyJLBh4bSDs9p+ur2XDTUNA+hXK/daHB7UlAJi1bCuYpuVBwREGXM6R6m4q2LLy18oRR2mGZrzAeqMuALqmcfKik+7lAH55SW/V7OvwOBTIkD8rPsjDvFC1TCDtqoU4Tfc2aRp9GoQTGli0MlYURZNly5axe/du7rvvvlzn1q5dS6VKlXj11Vdp1qwZ1atX5/hx+y8JNWvWZNOmTXbHtmzZkicZ6tSpg8ViYePGjbZj58+f5+DBg9SuXdt2LDIykpEjRzJ79myef/55Jk+e7HTOvIy9FVFuqduB2I2y6N7hJYAAn2BoOhjaPw9+JcHbHxo/In/yS69PZCXhdV9ktnHIRPeSMSUpmR28LxyFRa/BrlkwZF621WjNp/lf+wYi8DjJ2kaWguM2yzIrJgmkleRk3j7gPJHj24xeHCGCE6IsG4zaiBzfbwRQ0t+FQlWlvVRwrl50s5AObUbLLLCz++DUdpwGgAurrLeUetm+ppEbPnmgEfd/s54TF1NsSlvW01szLJC3+tbzeC6FwlPS0tKIj4/HarVy5swZFixYwLhx4+jduzeDBg3KNb5atWrExsYyc+ZMmjdvzj///MOff/5pN2b06NGMGDGCZs2a0aZNG2bNmsWuXbvyFOdSvXp1+vbty4gRI/j2228JCgri5Zdfpnz58vTtK+Mmn332WXr06EGNGjW4ePEiy5Yts1N8cpKXsbcqSrkp7uz/B2Zlxc1k3gXSLsP6r+DgAhi2KI/fyJ2gm6DTy9DmaRk7kpEKS/5PpibbxfNkynBmLyx6He7+XD5OPH39MtwACrUKhDCyY5xiVpPf+CKR+U9OZcoQGkuMJnxgfRDDicHWagjubuiiM7nZBzq/Cv+OdS1Ap1dkwDnAP2MhbpfM/nIlcWpinpSbciV8mfd0O2ZtOsGvW05wLjmN8GA/HmwRyX+aRjrsTaVQXC8LFiwgPDwcs9lMqVKlaNiwIZ9//jmDBw+2FfHLSd++fRkzZgxPPfUUaWlp9OrVi9dff50333zTNubhhx/m6NGjjB07ltTUVB544AGGDBmSy5rjjilTpthq7qSnp9OhQwf+/fdfmzvLarXy5JNPcvLkSUqUKEH37t359FPHXyrzMvZWRRPOnHXFlMTERIKDg7l8+bJdUFexJD0FPq6e6QJy8DJrJhnI2yNvbgGsGTLjycvfuTkidoPsPeUKkzeMPSTr5rx961X0zGltsQjdzt1UKHgHwYtHZEG8f56TCmAeMQTsExUJ0ZII06SF5ZwowRRLd7619rbL6MqJpsG9jcsz/oFG7hdZ/xUseQusafbHfYLgrrdkG4isJ27dF7D4/1y34zD7wksxnnVGBxkAv/1nWV378gnwKw2NHpbrBrhIY1cUK1JTUzl27BhVqlTB19f3ZotToHTp0oWwsDB++umnmy3KDcfV65qX+7ey3BRn9v5p7yK6FmGVpf3vetOzG8vJLbB6PBycL29WJSKg+Qho9YT99ReOypRhd1jTZd2TyJbux94oMuvfXBG+HBVhVOU0Ao11Rl1OiDIMMS102YPpukhPgtmPw76/yK+NSNfgrfTBbBE1qaidQQNOiDIOlRo9h7vs/qYVeKlHbZdZHzZaPyktTPvmZsZJCah6p2z9cG1qd4MBsORN58qNbpKxXp4qNmlJMK2PVACzah+lXoYV78m6SEMXQKnKns2lUNwCpKSk8M0339CtWzdMJhMzZsxgyZIlLF68+GaLVqRRyk1xJn5XdmE8Z2SkSJeQsyymLPbNlRVxIftGlXgalv1PurcG/SVvUBePw+Q7IfWSZzKavEDXIbwRxO3w7JrCIjgSGg/k6z3w6cmapGOfndBZ385Q88LClSH6T+RNO39WovcyBrBJSN94jHDc6LJ2eBAvdqvF4YRkYs5fYdfJy8zacpJZW05SJTSAoe2q8FCLiq77M/mWgMYPuxcosAx0eRsWvpL7nGaCgLLQ8WVPtiZZ+Jp0cwG5+qElJ8Bvj8Jjyz2fT6G4yWiaxr///ss777xDWloaNWvW5I8//uCuu+662aIVaZRyU1zZOEm2LPAoRViDffNkoGipyvIbeE7/cWoizH4sU6m5xr0lDFn/ZO1nMuZm6duZhf08uDn7lYKwzNoJHV6AWR7cLAuTxFPQZjQ7T+wj41S8bau1tFgGmRbRXN+PReiYMNwHB18XHniKzX5gyZ3Z9IR5LqPNf+KFwWERwY/Wrvxh7YAVGYOiAZVKB9C5Vln2xycxfWOsnSUq5twV/m/OHjYdPc9nAxqjF4SZqvWT4B8qrSsXY+QxzQR17oau70IJJ93Gr+XqJdj5i4tO9FY4vQ1ObYPyTa5fboXiBuDn58eSJUtuthjFDqXcFEe2/ADzX/BgoAZBEfBte3v3VcmK0OdzqNpZPt79a2bLAyc3XWFIRarF49Ly4KlC1fpJ2coBoHZvqeCs+siDawsJYcA/z3FHrVdZsFdWBx5oWsRb5qkIwJR5n7/pUWp3vSUzjI6vzXWqJFdsildtYvnAPJnu+mYey3jO5ppqVrkUB88k8cGC/UB2bybIfoXn7orjrjrl6NuofMHI3LA/NHgAEqJlDFjpKAgIzdscZ/ZIV6ZLNKlsK+VGobitUXVuihuWdGk98QgBSadyx+VcOgE/94MjK+Tj+N0yNsIVV87C2f2e95pq9BC0e87+2B2vQbf3Pbu+sNg5kz5RGuVK+NDCdJD/eU1F17IVG/AgpbuwaT5cumAckFM2kybQNOik72S46V80Dfy8TdzfNJJfNsa6dDvpGkxbF1OwcmsalKsrayvlVbEB1zVzcuLuvapQKIo9SrkpbsSscl+HBGQtEt2Z4U5IK8bP/WDjt2DyMBMhoIwHgzR5c+77lbwJnYmGHb9kdsc+B7V6erZWoSHw++dp5rQ/xRiv32++lSYnmgkqd4DkM3D+kPvxWZchGGJeiI8JJg1sRrC/F3tPX7Z10XaEIWB/fFK+RbUagiXRZ3jp9108PWM7Xy0/zNmkNPcXuiK8IXi7a94noEqn61tHoVAUeZRbqriR4oFiA1D/AVlIzxXCCvNflJkxrhpNaib5bTy0GlRqJ+vcuHJNtX0GLh6TmUEnc9Ry0M1QpYNn8hcmR5cSfnQp4VDIhW3yiLBCy8fhUqz7sTnQNAjjIkseq0uFitJi4u9tzso1coqPOX/ffc4kpjLw+40cPJOMSdcQQjBvF3y6+CDj+tXn/maR+ZoXb3+5/9XjcVraoNqd8n2oUChua5TlprhRsqJn47z9PTff75wJ5eo5dwsIK7TPLOx2x2uOx2QPlinq33fN3VPIsMCRZY4vux3RdHJpV38Mkx3E80GFDW/C3Gfh0BK61injUrEx6Ro963sY6JsDwxAM/mETR87K9hpWQ2AIaQmyGIIXf9/FusPn8iU/AJ3+C7Xvlr9nvR+z/g+rB/d+m/+5FbclFqvh8rGiaKIsN8WNyBZQuqqsDOwonVjTIaQaVGguA489wbBA3X6gzZHp5bo5M6pWyPl6fgzVM9MWK7WGuvfCnt+dz7f4DXldPpo93lZkPcc5saRKF57ZV/6eF/b9Lc04W6cwoFx9fg56loNX/HO5pzRN9md6tG0VUtIt/LblJDM3x3LmchplS/jQv3kkDzSLJMAn98fHykNnXbqzdE1j4oojtKmWj5gbkKUDHpgGR1fAtmky+yqgjKyVU6tPdoC6QuEG+b4XLNgbz7+747h8NYNgPy961g+nR70wQHNdDuEWICYmhipVqrB9+3YaNWrEihUr6Ny5MxcvXqRkyZI3W7ybirLcFDc0DfpMkKnc2jUvr5Z5rPen8tuvl7+HkwpIioPHVsLDf8hqsPX6yVL8Y6Kh2aPZQw0DjrqrMyKUYuMRzmwrIu+KDcjnPNO9aDobzZzgTwkLkrV8zHr2B7m/l4nvhzQjJMCbe75ay5t/72V/XBIXUtI5EJ/E23OjufvLNZxPzh1DsyT6DGYXNwSrEKw5fI7UjOt4/TVNZvLdPxUeWwEP/wb17lOKjcJjDCFYdfAsrd5bxlO/bOff3fGsPXyef3fH89Qv22n13jJWHTyLUQhBd0OGDEHTNEaOHJnr3KhRo9A0jSFDhuRr7jZt2hAXF0dwsOetTG4UU6dOvaEKl7LcFCcsabLYXvwuqH+/rOJ6dn/2+fJNoes7ULGVfNz1f/DP857NHbseEk9CVKdsK40j0i5Dyvl8b0FxgzCs+Jzbw8qHdRalNmHVwbNYDEGjyJLc07g8gT5mRv68lSMJV+xUrKzfY86n8NIfu/hucHO7aVMzDI86YqVbDXy9VFaT4sZjNaRiM/zHLU6D6s8mpzH8xy18N6gZHWqUKXALTmRkJDNnzuTTTz/Fz09W505NTWXGjBlUrOhhaIEDvL29CQsLKygxizTKclNcOLoCPqkpYzLWT4Tdv0nFpnxTeHAmjN4Gw5dkKzaQmbU00UXWVA7O7IEJ9eUaKz+UKeeOMPvdArnStw5C3AJ1cZyhmzEfnE/P+uG8f18DPr6/IY+0qkSgj5nTl66ycG88VifCWw3B0n0JnLyYYne8dniQ22+7YSV8CLrGpWUYgtWHzvLCbzt57MctvDMvmkNn8p+tpVA4R8Z+ucoWBPkef/GPXS7H5JcmTZpQsWJFZs+ebTs2e/ZsIiMjady4se3YggULaNeuHSVLliQkJITevXtz5MgRp/OuWLECTdO4dOmS7djkyZOJjIzE39+fe++9l/Hjx9tZUN58800aNWrETz/9ROXKlQkODmbAgAEkJWX//bmTIyYmBk3TmD17Np07d8bf35+GDRuyfv16m1yPPvooly9fRtM0NE2zax5aGCjlpjgQvwem3y8rAwMYGdnZTad3yMJ4pao4vrbxw9Cgv+drpZyDFeNgxgDZQPNavHyhWlfPa5IUczTtFtf1HFQ5Bth54pJbpUwA22Mv2R37T9MKeJt0p0lmugaD21Sx61+VlJrBgMkbGPj9JmZvP8Wi6DNMWRdDl09XMe7ffdxmvX0VhYjFajB/TzxnHbhUHXE2KY0Fe+IKJcj40UcfZcqUKbbHP/zwA0OHDrUbc+XKFZ577jk2b97M0qVL0XWde++9F8PwTJ61a9cycuRInnnmGXbs2EGXLl149913c407cuQIc+bMYd68ecybN4+VK1fy/vvZNcc8lePVV19l7Nix7Nixgxo1avDggw9isVho06YNEyZMoESJEsTFxREXF8fYsWPz8nTlGaXcFAfWTpDxFI5aHgirzEpyFQdTpmbu+BxXCAOOLIWdMxyfb5/l6rr5d/WifV8s5OfPsELZuo5X9lAj068ZV9Lfm08eaCiDkq8x5WsatKwSwtB2le2Oj5m1g60xFwBs36az/v921VF+XH/cI1kUCneYTTr/7o7L0zX/7o7HbCr4W+XAgQNZs2YNMTExHD9+nLVr1/LII4/Yjbnvvvvo168f1atXp1GjRnz//ffs3r2b6Ohoj9b44osv6NGjB2PHjqVGjRqMGjWKHj165BpnGAZTp06lXr16tG/fnoEDB7J06dI8yzF27Fh69epFjRo1eOuttzh+/DiHDx/G29ub4OBgNE0jLCyMsLAwAgPd1ay6PpRyU9QxDNg7x3VlYN0s06+dUa2LZ72g7CeFTZPlr5Y0mcHz26Mw40Gp+PQe73mn50LklraauMK3JPiVdKJ0FsSmNDB5yywjBzSrXMplYDBIK0zzKqVyHe/dIILfRramU80ytr5VESV9+W+PWkwd2hwfc7ZV73BCMkv2JWB1oYROXHHYrQtBofCUy1cdWJwLcLynhIaG0qtXL6ZNm8aUKVPo1asXoaH2WYRHjhzhoYceIioqihIlSlClirTAx8Z6VuvqwIEDtGjRwu7YtY8BKleuTFBQkO1xeHg4CQnZVdA9laNBgwZ2cwB289xIVEBxUcewSDeUyzFWSHMRv5Cv2jKGjOnZ+ycs+j+4HJvdgfzgQkBAt/fgyHI4VMidtIsjTruqa1CyElw6jkcNNh1OYZLX3jMR/Es7HBIa6MO9jcvzx7aTONIrdA36NipP2SDH1aubVirN94NLY7EaWAyBj1l3aA1acSABXcPhGlmcSUzjQHwSdSJKeLI7hcIlwX5ehTo+LwwdOpSnnnoKgK+++irX+T59+hAZGcnkyZOJiIjAMAzq1atHerq7HmsSIUSuvztHbl4vL/s9appm53LyVI6c82St66kLraBRyk1RRzdn1oxx9QYSEFrd+emtU5yfc4U1HX4bkmMZq/3/C17mVnBNFRsqtoF7v4aUCzC5cz4n0WQV33bPyZpELnirb11iL6Sw8dgFmwJi0sAqoEnFUrxzTz23q5lNOmYX4VfpVkN+CLrxH6arwmqKAsBiNehZP5x/d8d7fE3P+mFYrEahuKa6d+9uUxC6detmd+78+fPs27ePb7/9lvbt2wOwZs2aPM1fq1YtNm3aZHdsy5YteZqjIOQAmclltd64EiBKuSnqHFvhmUupWhfn5y6fKjBx7HFX4L/gEKIIu6A8JXadtMKVbyLbZ+z+jTw/v2P2QrBnnb79vc1MH96SJfvOMGvLCeIupRIe7Mv9zSLpWqdcgXzY140Iduty8jbpRJUJuO61FAqzSadHvTDKBPp4FFRcJsiH7vXCC62Yn8lkYt++fbbfc1KqVClCQkKYNGkS4eHhxMbG8vLLL+dp/tGjR9OhQwfGjx9Pnz59WLZsGfPnz/c4pq6g5ADp+kpOTmbp0qU0bNgQf39//P09rbWWd1TMTVHn7EHPgoFdFX3zyx03UTDcuDiJYq/YgHQn7fpV/n7PRGjzFFbdJ29zuHJPOsBs0uleL5wpQ1qw4NkOTHm0BT3rhxfYt9j21UKpUMoPZ/cOk67Rr0l5SvgWnmtAcbuh8eF/GrhVWEy6xof3NXA5piAoUaIEJUrkdrnqus7MmTPZunUr9erVY8yYMXz00Ud5mrtt27Z88803jB8/noYNG7JgwQLGjBmDr6+HzZALSA6QBQZHjhxJ//79KVOmDB9++GGe58gLmrjN8iwTExMJDg7m8uXLDt9QRY7N33lWiG/4MqjQ1PG5GQ/DgXkFK9cNJutdXKyVHN0LmgySwdqZvDpjLRf2LOYp0x/U0WJd718zwQuHncbZ3Cx2nbzEgEkbSLMYdlYcXYNqZQP57fE2BPsr5UZhT2pqKseOHaNKlSp5ulmDrFC88sBZXvxjl8Nu9WWCfPjwvgZ0rFkmV0ZgUWfEiBHs37+f1atX32xRHOLqdc3L/Vu5pYo6nriUAspCRCPH51IuwOFFBSrSzaCYff44RlhzuZSuav701tdR241iIzQTWq3et5xiA9CgQknmP9Oeb1cdZc72U6SkWykX5MMjrSoxpG1lgpTVRlHA6JpGhxpl2PDfO1mwJ45/d8fn6C0VRvd64bZxRZ2PP/6YLl26EBAQwPz585k2bRoTJ0682WIVOkq5KSpYLXB4icyS8SsFNbqBb7DzWjM5iWjkvAP4jl/cZ1spbh0aPmj3sGfgQe4ybXR5iYGG7u0Pd/5fYUp2XVQKCeC9e+vz3r31sRrilm9YqCj6ZL3HutUNo1eDCNtxi9UoVu+/TZs28eGHH5KUlERUVBSff/45w4cPv9liFTpKuSkKHJgPfz8NVxKyM6PMvtD2WdnQ0iWa6waZ8buRoVfFq5FlsQwwbtAfTm2TcTNlagLQ8cp8LOiYHXWAz8Rq8kUftgRCq90oSa+L4nRjUdz6XBs/VhhZUTeTX3/99WaLcFNQys2tzpHlMPOh7KCSrMwoSyqsfN99GrhuAp8g5+e9fKUWUMwir4qVYuMdIF/jnTOyLXWRLaHPZ3hdPg4uFBsAs9kLytYqfDkVCoXiFqF4qajFkSVvZCoeTrQPIVz3cTIsUPce5+dr9szuQ3W7o+kyPulWwssf0q9AxjU9oE5uge+7yCrQLrLlBKDdgnE2CoVCUZgo5eZW5vwRiNuJ62/mmf4XRzc4zQQRTSDqDueXV7sLytS+XkmLB8KQrr9biYwUx8eFFdJTZPNSF5Y7TdOh0cOFJJxCoVDcmijl5lYm5bz7MbpZBpn6Bmc+9pLHACq2gkf+AN3Fy6ybYOBs8FJF0oocwgqnt0K5eo6td7pJWqKaDbvxsikUCsVNRMXc3MqU8KCSrGGBKh2h1yewby7E75LBxjW6QXkndW1yrRMBnV+BRa9en7yeoGkQGAZJ8RS7QJ/CIKtflzMMK9z9JSx/Fw4vBrTMwtACytWH+6dCQMgNElahUChuDZRycysTXB6iOsOxVc5vcN6BUKsXmH2g/n/kT35o/DCs+hBSEyk0pePeSVCzBxxbCbMeKZw1bgqF1WbCg3k1HUKi4JHf4dwhOLpCKjyRzT1XbhWK2xlrBpi8nD9WFEmUW+pWp+s7UnFxFjTc4wPwLoD+HH6l4OE/XGdWXS9/PgafNYS4XZ61jCgqBIRCiIvGpPnFy891Q0nNBDV7ZbskQ6tDixHQaqRSbBQKdxhWafneNxd+HQw/9pX/75srjxtFuzxG5cqVmTBhws0W46ZRjO4wxZSwejBsEUS2sD9eqrJ0OTQuQAtIZHN4Zid0frXwlI+rF2D1x+BdiEqUybtwlA1H6GZpXWvxGAXeAd2SBj6Bjs9pJrnPzv8t2DUVitsBYcDhpTC+Nvz+KETPkVbP6Dny8fja8rwnTYnzyJAhQ9A0zfYTEhJC9+7d2bVrV4Gus3nzZh577LECnbMooZSbokBYfRi6AEZvg4F/wmMr4OkdUPde99dePgVL/wdft4WvWsBfozMzsJzgXxo6vgjNC7GCpTAg7XLhzW/yhvOHCm/+nBgWaDIQGg6QFhRXafl5RVhlwb5avaUVJyeh1WHIP1CubsGtp1DcDhhWOLQEZg6AZCfZkckJ8vyhJYViwenevTtxcXHExcWxdOlSzGYzvXv3LtA1ypQpU6hdt291lHJTlAipClXvgIjGnlWpO7oSvmgKaz6FM3vg7AHY+Qt82wHWf+X62pYjC0ZmlxRSpb30ZG7cW1sDQ0jlo++XDixe17lHTZev9dhD8MCP0HciDFsCozY4b4SqUChcIODvJ90rLYYV/n6Kwoin8/HxISwsjLCwMBo1asRLL73EiRMnOHv2LACnTp2if//+lCpVipCQEPr27UtMTIzt+iFDhnDPPffw8ccfEx4eTkhICE8++SQZGdmtdK51S+3fv5927drh6+tLnTp1WLJkCZqmMWfOHABiYmLQNI3Zs2fTuXNn/P39adiwIevXry/w/d8IlHJTXLlyHmY8CNY0+2DkrIJ9C1+RgcrOCKkKHV8qXBkLK3DZO6jw5s6FgJ/uhvfKw+9DHX9gegWAb8l8Tm/IAn4+QVCnrwz8jmxezEowKxQ3CGsGRP/t3GJzLclnZAyOtfD67yUnJzN9+nSqVatGSEgIKSkpdO7cmcDAQFatWsWaNWsIDAyke/fupKen265bvnw5R44cYfny5UybNo2pU6cydepUh2sYhsE999yDv78/GzduZNKkSbz6quPs2FdffZWxY8eyY8cOatSowYMPPojFUvQKvapsqYLg2CrY8DUcXy9vOtXuhFZPOA/qFAJWj4cNE7Nr2ZSsBHe8Cg0eyPv6J7fKVOCY1WBNl9/2dbP83Rm6GdZPhCodIGG/lGX/P7KJZngjWTslZnXeZbnZaHrmvm9wmrk1zckJIVtllK4MJSpAwp68zauZlOtJoSgoTF4Q/Vferon+y7MQgDwwb948AgNlPN2VK1cIDw9n3rx56LrOzJkz0XWd7777Di3zS8yUKVMoWbIkK1asoGvXrgCUKlWKL7/8EpPJRK1atejVqxdLly5lxIgRudZbtGgRR44cYcWKFYSFhQHw7rvv0qVLl1xjx44dS69evQB46623qFu3LocPH6ZWraLVwuWmW24mTpxIlSpV8PX1pWnTpqxe7fqGunLlSpo2bYqvry9RUVF88803N0hSJ6z6GKb1gYMLIfWiDJjd+ydMvhO2/ZR7vBCybP6ytyHlHPImLOBSDMweAXPH5G39rdPguzvgyNJsZUYYrhUbkBacYytlU85v2sKO6VKe1Mvy+IavZM2cooRmku0K3O39RiOscGYv9PsGHl8NrZ+SH5Yd/wt3vO7mWgOaDL4xcioUtwOpl/I2/moex3tA586d2bFjBzt27GDjxo107dqVHj16cPz4cbZu3crhw4cJCgoiMDCQwMBASpcuTWpqKkeOHLHNUbduXUym7Bi/8PBwEhIcW6QOHDhAZGSkTbEBaNGihcOxDRo0sJsTcDrvrcxNtdzMmjWLZ599lokTJ9K2bVu+/fZbevToQXR0NBUrVsw1/tixY/Ts2ZMRI0bw888/s3btWkaNGkWZMmW47777bvwGYtbCsv/J3x25fuaOllWCQ3Nk7qz8AE5udj7n1h+g3r3SouKOswdg7jN5l9smpwG/Dc50pRTxgnomb6jdB/b8cbMlcU7CfmhwP4Rnf3hgWOH0Ntj/b+aBzNchq3hf9/eli1ChUBQMeXUR++VxvAcEBARQrVo12+OmTZsSHBzM5MmTMQyDpk2bMn369FzXlSlTxva7l5d9LR5N0zAMx9ldQgibFcgdOefNusbZvLcyN9VyM378eIYNG8bw4cOpXbs2EyZMIDIykq+//trh+G+++YaKFSsyYcIEateuzfDhwxk6dCgff/zxDZY8k43fZLc6cIgOm7+3P7TB8d7sWPKmZ+tv/s6zcY7QTFCyQqYvuQgrNkMXwrDFMuC26aM3WxrXOKpHpJvg/h+lElOqUvbxii3hod9kzRqFQlEwWDNk7FpeqNO3UGNuQCoRuq5z9epVmjRpwqFDhyhbtizVqlWz+wkODs7X/LVq1SI2NpYzZ87Yjm3e7OJLdjHgpik36enpbN261eY/zKJr166sW7fO4TXr16/PNb5bt25s2bLFLko8J2lpaSQmJtr9FBixG1x31BZWiM2xF2uGZybRhP2erX98HflWTIRVpn27KhJXELTNo5stT2hQvpmsAeRX0nlNmFsBL3/ZJsMRJrNUYp7eAS+fgFfj4dH5UKOr4/EKhSJ/mLygzt0QWNaz8YHlpEW4gCsWp6WlER8fT3x8PPv27WP06NEkJyfTp08fHn74YUJDQ+nbty+rV6/m2LFjrFy5kmeeeYaTJ0/ma70uXbpQtWpVBg8ezK5du1i7dq0toNhTi05R46YpN+fOncNqtVKuXDm74+XKlSM+Pt7hNfHx8Q7HWywWzp075/CacePGERwcbPuJjIwsmA2A64aUtjE5LTsevok8LaDn0mrkdHL5X+dXZY+nwqJUFRi+FDq9XHhr1OotFYMswhp61o/rZtDmaffKl6aBb4ncNW0UCkUBosHdX0mrqSt0E/T9isIoWbFgwQLCw8MJDw+nZcuWbN68md9++41OnTrh7+/PqlWrqFixIv369aN27doMHTqUq1evUqJEiXytZzKZmDNnDsnJyTRv3pzhw4fz2muvAeDr61uQW7tluOnZUtdqje58g47GOzqexX//+1+ee+452+PExMSCU3CqdZV1Y5xZbzQdquWIRjeZZZPKxNOu541s7tn61btkFuTLg/WlUhsZxFqpNWz5Afb97fm1HqHJdhEPzYIyNeWhyJYyzqhAq33q0O4aq5Cuwx2vwZwnCmiNrPdUXq1bmvxgFEJayFo8fgPS6hUKhUfoJqh+FwyYKevYJJ/JPSawnGxIW+3OAq/W7iplO4uwsDCmTZvmco5rubbVQs66OCBdU2vWrLE9Xrt2LYAt9qdy5cq2+2kWJUuWzHWsqHDTlJvQ0FBMJlMuK01CQkIu60wWYWFhDsebzWZCQhx3Pvbx8cHHx6dghL6WViNllpFDNDD5QNMh9oc7vQx/P+163q7verZ+00dh3eeyTL87dJNsSTB4XrbFqf4Dsnpx6mXXnacdUbuPTIFPzaw0rOlSeQksC/dPy1ZsANo+AzMfytv8rtC9ZOsJR0XsGj0EVy/C4jcy96Q531uWzI4aVJatDT0/gfkvwZndLoS5RpFpPFBaj5LjpWWsYX8oHZWvbSoUikJC06Xi8ly0rGMT/ZfMivIrKWNsavcBtGLVA+/PP/8kMDCQ6tWrc/jwYZ555hnatm1L1arFM2Hhpik33t7eNG3alMWLF3Pvvdk1BBYvXkzfvo4Dvlq3bs3cuXPtji1atIhmzZrlihy/IZSrC/dNhtmPZd/cQP5BmH3gwZlQItz+miaDIXYT7PjZ8Zw9PoRydTxbP7i8XOOXAS7qrGTeuEuUh4d+tXel+QTKdg4/3pMZCyTsr3FG8xHQ8yPpRonfA4cWSgUrrAHU6G7vKgLZtfzON2DpW9KV5sjSlVWbp3pX2D9PKgzXFsQLLCdTqDu/Kt03zmj9JDR8EHb9ChePQ/xOOL42x9pZz0kE9PkCDvwr+8pY02R9n5aPQ1QnOdfI1XBkmawjdHoniEzZ/UOg/v1SgU05J+dq9JBSZBSKokKWW6pWb/s6NtaMfLr8b22SkpJ48cUXOXHiBKGhodx111188sknN1usQkMTN9HmNGvWLAYOHMg333xD69atmTRpEpMnT2bv3r1UqlSJ//73v5w6dYoff/wRkKng9erV4/HHH2fEiBGsX7+ekSNHMmPGDI9TwRMTEwkODuby5cv59l/m4uJx2DpFBvhqOlS9E5oMgiDHFihAtkZY8iacOyivqdBcWmzK1c77+klnZF2aPbOlkmLyBr/S4OUL/qFQrx/U+4/z7uFXL8KOX2TNG0uqLD5YsbVUWo6vg9REWSE3sqXsOVWxZd5lBKkIbZ0iXWmaDt6B0vJj8pLKRJPBUhk8uQW2TIGz+6USU/deqHcfeAfkb12AU9tg61RZb8YnCOreI5WTvMyZliTT73UTlK0LZu/8y6NQKK6L1NRUjh07ZquTpigeuHpd83L/vqnKDcgifh9++CFxcXHUq1ePTz/9lA4dZI2XIUOGEBMTw4oVK2zjV65cyZgxY9i7dy8RERG89NJLjBzpebpsoSg3CoVCobihKOWmeFJslJsbjVJuFAqFouijlJviSUEpN8UnWkqhUCgUtx232ffzYk9BvZ5KuVEoFApFkSOrr1LOTtmKok/W65mzb1Z+KH4h4QqFQqEo9pjNZvz9/Tl79ixeXl7onhRVVdzSGIbB2bNn8ff3x2y+PvVEKTcKhUKhKHJomkZ4eDjHjh3j+PHjN1scRQGh6zoVK1a87rYQSrlRKBQKRZHE29ub6tWrK9dUMcLb27tArHBKuVEoFApFkUXXdZUtpciFclIqFAqFQqEoVijlRqFQKBQKRbFCKTcKhUKhUCiKFbddzE1WgaDExMSbLIlCoVAoFApPybpve1Lo77ZTbpKSkgCIjIy8yZIoFAqFQqHIK0lJSQQHB7scc9v1ljIMg9OnTxMUFOQ2jz4xMZHIyEhOnDhxW/Whul33Dbfv3tW+b699w+27d7XvortvIQRJSUlERES4TRe/7Sw3uq5ToUKFPF1TokSJIvtmuB5u133D7bt3te/bj9t172rfRRN3FpssVECxQqFQKBSKYoVSbhQKhUKhUBQrlHLjAh8fH9544w18fHxutig3lNt133D77l3t+/baN9y+e1f7vj32fdsFFCsUCoVCoSjeKMuNQqFQKBSKYoVSbhQKhUKhUBQrlHKjUCgUCoWiWKGUG4VCoVAoFMUKpdxcw7hx49A0jWeffdZ2TAjBm2++SUREBH5+fnTq1Im9e/fePCELkFOnTvHII48QEhKCv78/jRo1YuvWrbbzxXHvFouF1157jSpVquDn50dUVBRvv/02hmHYxhSHfa9atYo+ffoQERGBpmnMmTPH7rwne0xLS2P06NGEhoYSEBDA3XffzcmTJ2/gLvKHq71nZGTw0ksvUb9+fQICAoiIiGDQoEGcPn3abo6iuHd3r3lOHn/8cTRNY8KECXbHi+u+9+3bx913301wcDBBQUG0atWK2NhY2/miuG9wv/fk5GSeeuopKlSogJ+fH7Vr1+brr7+2G1NU9+4KpdzkYPPmzUyaNIkGDRrYHf/www8ZP348X375JZs3byYsLIwuXbrY+lQVVS5evEjbtm3x8vJi/vz5REdH88knn1CyZEnbmOK49w8++IBvvvmGL7/8kn379vHhhx/y0Ucf8cUXX9jGFId9X7lyhYYNG/Lll186PO/JHp999ln+/PNPZs6cyZo1a0hOTqZ3795YrdYbtY184WrvKSkpbNu2jddff51t27Yxe/ZsDh48yN133203riju3d1rnsWcOXPYuHEjERERuc4Vx30fOXKEdu3aUatWLVasWMHOnTt5/fXX8fX1tY0pivsG93sfM2YMCxYs4Oeff2bfvn2MGTOG0aNH89dff9nGFNW9u0QohBBCJCUlierVq4vFixeLjh07imeeeUYIIYRhGCIsLEy8//77trGpqakiODhYfPPNNzdJ2oLhpZdeEu3atXN6vrjuvVevXmLo0KF2x/r16yceeeQRIUTx3Dcg/vzzT9tjT/Z46dIl4eXlJWbOnGkbc+rUKaHruliwYMENk/16uXbvjti0aZMAxPHjx4UQxWPvzvZ98uRJUb58ebFnzx5RqVIl8emnn9rOFdd99+/f3/b37YjisG8hHO+9bt264u2337Y71qRJE/Haa68JIYrP3q9FWW4yefLJJ+nVqxd33XWX3fFjx44RHx9P165dbcd8fHzo2LEj69atu9FiFih///03zZo14/7776ds2bI0btyYyZMn284X1723a9eOpUuXcvDgQQB27tzJmjVr6NmzJ1B8950TT/a4detWMjIy7MZERERQr169YvM8ZHH58mU0TbNZLYvr3g3DYODAgbzwwgvUrVs31/niuG/DMPjnn3+oUaMG3bp1o2zZsrRs2dLOfVMc951Fu3bt+Pvvvzl16hRCCJYvX87Bgwfp1q0bUHz3rpQbYObMmWzbto1x48blOhcfHw9AuXLl7I6XK1fOdq6ocvToUb7++muqV6/OwoULGTlyJE8//TQ//vgjUHz3/tJLL/Hggw9Sq1YtvLy8aNy4Mc8++ywPPvggUHz3nRNP9hgfH4+3tzelSpVyOqY4kJqayssvv8xDDz1kayhYXPf+wQcfYDabefrppx2eL477TkhIIDk5mffff5/u3buzaNEi7r33Xvr168fKlSuB4rnvLD7//HPq1KlDhQoV8Pb2pnv37kycOJF27doBxXfvt11X8Gs5ceIEzzzzDIsWLbLzv16Lpml2j4UQuY4VNQzDoFmzZrz33nsANG7cmL179/L1118zaNAg27jitvdZs2bx888/88svv1C3bl127NjBs88+S0REBIMHD7aNK277dkR+9licnoeMjAwGDBiAYRhMnDjR7fiivPetW7fy2WefsW3btjzvoSjvOytRoG/fvowZMwaARo0asW7dOr755hs6duzo9NqivO8sPv/8czZs2MDff/9NpUqVWLVqFaNGjSI8PDyXpyInRX3vt73lZuvWrSQkJNC0aVPMZjNms5mVK1fy+eefYzabbd9sr9VgExIScn3rLWqEh4dTp04du2O1a9e2ZRCEhYUBxW/vL7zwAi+//DIDBgygfv36DBw4kDFjxtgsd8V13znxZI9hYWGkp6dz8eJFp2OKMhkZGTzwwAMcO3aMxYsX26w2UDz3vnr1ahISEqhYsaLts+748eM8//zzVK5cGSie+w4NDcVsNrv9rCtu+wa4evUqr7zyCuPHj6dPnz40aNCAp556iv79+/Pxxx8DxXfvt71yc+edd7J792527Nhh+2nWrBkPP/wwO3bsICoqirCwMBYvXmy7Jj09nZUrV9KmTZubKPn107ZtWw4cOGB37ODBg1SqVAmAKlWqFMu9p6SkoOv2b32TyWT7hldc950TT/bYtGlTvLy87MbExcWxZ8+eIv88ZCk2hw4dYsmSJYSEhNidL457HzhwILt27bL7rIuIiOCFF15g4cKFQPHct7e3N82bN3f5WVcc9w3yfZ6RkeHy86647l1lSzkgZ7aUEEK8//77Ijg4WMyePVvs3r1bPPjggyI8PFwkJibePCELgE2bNgmz2SzeffddcejQITF9+nTh7+8vfv75Z9uY4rj3wYMHi/Lly4t58+aJY8eOidmzZ4vQ0FDx4osv2sYUh30nJSWJ7du3i+3btwtAjB8/Xmzfvt2WEeTJHkeOHCkqVKgglixZIrZt2ybuuOMO0bBhQ2GxWG7WtjzC1d4zMjLE3XffLSpUqCB27Ngh4uLibD9paWm2OYri3t295tdybbaUEMVz37NnzxZeXl5i0qRJ4tChQ+KLL74QJpNJrF692jZHUdy3EO733rFjR1G3bl2xfPlycfToUTFlyhTh6+srJk6caJujqO7dFUq5ccC1yo1hGOKNN94QYWFhwsfHR3To0EHs3r375glYgMydO1fUq1dP+Pj4iFq1aolJkybZnS+Oe09MTBTPPPOMqFixovD19RVRUVHi1VdftbuxFYd9L1++XAC5fgYPHiyE8GyPV69eFU899ZQoXbq08PPzE7179xaxsbE3YTd5w9Xejx075vAcIJYvX26boyju3d1rfi2OlJviuu/vv/9eVKtWTfj6+oqGDRuKOXPm2M1RFPcthPu9x8XFiSFDhoiIiAjh6+sratasKT755BNhGIZtjqK6d1doQghRuLYhhUKhUCgUihvHbR9zo1AoFAqFonihlBuFQqFQKBTFCqXcKBQKhUKhKFYo5UahUCgUCkWxQik3CoVCoVAoihVKuVEoFAqFQlGsUMqNQqFQKBSKYoVSbhQKRYHy5ptv0qhRo5sthkKhuI1Ryo1CcZsyZMgQNE1D0zS8vLyIiopi7NixXLly5brmHTt2LEuXLi0gKZ0zZMgQ7rnnnkKbf+rUqWiaRu3atXOd+/XXX9E0zdZwUqFQ3Foo5UahuI3p3r07cXFxHD16lHfeeYeJEycyduzYfM0lhMBisRAYGJirEeWtTHp6utNzAQEBJCQksH79ervjP/zwAxUrVixs0RQKRT5Ryo1CcRvj4+NDWFgYkZGRPPTQQzz88MPMmTMHkMrKhx9+SFRUFH5+fjRs2JDff//ddu2KFSvQNI2FCxfSrFkzfHx8WL16dS63VJaF5b333qNcuXKULFmSZk89igAABh5JREFUt956C4vFwgsvvEDp0qWpUKECP/zwg51sp06don///pQqVYqQkBD69u1LTEwMIF1f06ZN46+//rJZn1asWOH2upzyjBs3joiICGrUqOH0+TGbzTz00EN2sp08eZIVK1bw0EMP5Ro/d+5cmjZtiq+vL1FRUbZ9ZjF+/Hjq169PQEAAkZGRjBo1iuTkZNv5qVOnUrJkSRYuXEjt2rUJDAy0KaAKhcJzlHKjUChs+Pn5kZGRAcBrr73GlClT+Prrr9m7dy9jxozhkUceYeXKlXbXvPjii4wbN459+/bRoEEDh/MuW7aM06dPs2rVKsaPH8+bb75J7969KVWqFBs3bmTkyJGMHDmSEydOAJCSkkLnzp0JDAxk1apVrFmzxnajT09PZ+zYsTzwwAO2G39cXBxt2rRxe10WS5cuZd++fSxevJh58+a5fE6GDRvGrFmzSElJAaQC0r17d8qVK2c3buHChTzyyCM8/fTTREdH8+233zJ16lTeffdd2xhd1/n888/Zs2cP06ZNY9myZbz44ot286SkpPDxxx/z008/sWrVKmJjY/NtTVMobltubt9OhUJxsxg8eLDo27ev7fHGjRtFSEiIeOCBB0RycrLw9fUV69ats7tm2LBh4sEHHxRCZHcjvra78htvvCEaNmxot06lSpWE1Wq1HatZs6Zo37697bHFYhEBAQFixowZQgjZwblmzZp2nYvT0tKEn5+fWLhwoUP583JduXLl7LrAO2LKlCkiODhYCCFEo0aNxLRp04RhGKJq1arir7/+Ep9++qmoVKmSbXz79u3Fe++9ZzfHTz/9JMLDw52u8euvv4qQkBC7NQFx+PBh27GvvvpKlCtXzqWsCoXCHvPNVq4UCsXNY968eQQGBmKxWMjIyKBv37588cUXREdHk5qaSpcuXezGp6en07hxY7tjzZo1c7tO3bp10fVsQ3G5cuWoV6+e7bHJZCIkJISEhAQAtm7dyuHDhwkKCrKbJzU1lSNHjjhdx9Pr6tevj7e3t1u5sxg6dChTpkyhYsWKJCcn07NnT7788stca2/evNnOUmO1WklNTSUlJQV/f3+WL1/Oe++9R3R0NImJiVgsFlJTU7ly5QoBAQEA+Pv7U7VqVdsc4eHhtudFoVB4hlJuFIrbmM6dO/P111/j5eVFREQEXl5eABw7dgyAf/75h/Lly9td4+PjY/c466bsiqx5s8jK0Lr2mGEYABiGQdOmTZk+fXquucqUKeN0HU+v80TmnDz88MO8+OKLvPnmmwwaNAizOfdHp2EYvPXWW/Tr1y/XOV9fX44fP07Pnj0ZOXIk//vf/yhdujRr1qxh2LBhNlcgOH6uhBB5klehuN1Ryo1CcRsTEBBAtWrVch2vU6cOPj4+xMbG0rFjxxsuV5MmTZg1axZly5alRIkSDsd4e3tjtVrzfF1+KF26NHfffTe//vor33zzjVOZDxw44PD5BNiyZQsWi4VPPvnEZsX69ddfC0xGhUKRjQooVigUuQgKCmLs2LGMGTOGadOmceTIEbZv385XX33FtGnTCn39hx9+mNDQUPr27cvq1as5duwYK1eu5JlnnuHkyZMAVK5cmV27dnHgwAHOnTtHRkaGR9fll6lTp3Lu3Dlq1arl8Pz//d//8eOPP/Lmm2+yd+9e9u3bx6xZs3jttdcAqFq1KhaLhS+++IKjR4/y008/OVWUFArF9aGUG4VC4ZD//e9//N///R/jxo2jdu3adOvWjblz51KlSpVCX9vf359Vq1ZRsWJF+vXrR+3atRk6dChXr161WWRGjBhBzZo1adasGWXKlGHt2rUeXZdf/Pz8XNbv6datG/PmzWPx4sU0b96cVq1aMX78eCpVqgRAo0aNGD9+PB988AH16tVj+vTpjBs37rpkUigUjtGEcuYqFAqFQqEoRijLjUKhUCgUimKFUm4UCoVCoVAUK5Ryo1AoFAqFolihlBuFQqFQKBTFCqXcKBQKhUKhKFYo5UahUCgUCkWxQik3CoVCoVAoihVKuVEoFAqFQlGsUMqNQqFQKBSKYoVSbhQKhUKhUBQrlHKjUCgUCoWiWKGUG4VCoVAoFMWK/wcxAZVCRfGaBQAAAABJRU5ErkJggg==",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Create mapping between values and colors\n",
-    "labels = cancer[\"diagnosis\"].unique().tolist()\n",
-    "colors = list(mcolors.TABLEAU_COLORS.keys())\n",
-    "color_map = {l: colors[i % len(colors)] for i, l in enumerate(labels)}\n",
-    "\n",
-    "# Plot\n",
-    "plt.scatter(cancer[\"perimeter_mean\"], cancer['concavity_mean'], \n",
-    "            color=cancer[\"diagnosis\"].map(color_map))\n",
-    "\n",
-    "# Create custom legend handles\n",
-    "handles = [plt.Line2D([0], [0], marker='o', color='w', label=label,\n",
-    "                      markersize=10, markerfacecolor=color_map[label])\n",
-    "           for label in labels]\n",
-    "\n",
-    "# Add labels and legend\n",
-    "plt.xlabel('Perimeter Mean')\n",
-    "plt.ylabel('Concavity Mean')\n",
-    "plt.title('Scatter Plot of Perimeter Mean vs Concavity Mean')\n",
-    "plt.legend(handles=handles, title='Diagnosis')\n",
-    "plt.show()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 61,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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vetWky7Zv3z7pMf/oRz/Ctu1Jj6WRBx98kFe/+tW0tLSgaRqGYXDhhRcShiGPPfZY/biLL76Y+++/nx07dtQvu+2223j2s5/N8ccfP9uHDMAFF1xAe3v7pKXJz372s7S1tXH++efP+HY2bNjAi1/8Ym699VaGh4f53ve+N+3j/sEPfoCiKPzVX/3VpNdhZ2cnJ5544qT3xmw/51/96ldP+vf27dtxHIeBgYEZP5alTCYUL2GnnXYap512GgC+7/PBD36QT33qU3z84x/n4x//eD2nYfXq1dPeRhRFnH322fT09HDNNddwwgknkEqliKKI5zznOc/4w6+/v5+dO3dOm9h78HpvV1fXrG7/mGOO4Rvf+AaKomDbNhs2bCCZTB7yd4aHh9F1vb5+PkFRFDo7OxkeHp7VGOb7diFOnP7FL34BgGVZrFu3jmw2W79+vp/n5ubmSf82TXPayw/cnt7f38/Y2Fj9+MONq5H5fmwTXvjCF7Jp0yY+//nP881vfpMrrrgCRVGmHDc8PEwQBHz2s5/ls5/97CHH9J3vfIc3vvGNnHfeefzN3/wNnZ2d6LrOLbfcMimvYkJLS8uUyyzLOuz7UNd13vKWt/DZz36WsbEx8vk8X/nKV+jq6uKcc86pH/fP//zPrF69mjvvvJN//Md/xLZtzjnnHD7xiU9MSmA92Nq1a3nyyScPOYYJE6/zRn+H7u5u7rnnnkmXJZNJbNuedJllWZNeR4ODg3R3dzfMOZmwZ88eXvCCF7BlyxY+85nPsH79emzb5n//93+5/PLLJz2Hf/mXf8n73/9+vvKVr3DDDTfw8MMP85vf/Iabb755Ro+xEcuyeOc738lNN93EJz7xCXzf55vf/CZXXXUVlmXN6rbe9ra3cfHFF/PJT36SRCLBG97whobH9ff3I4Sgo6Oj4fUbN24Ejuxz/uDX4sRjmI+AeDHI4GaZMAyDa6+9lk996lP8+c9/BqifZPft28eaNWsa/t6f//xn/vCHP/CVr3yFiy66qH75zp0752Rcra2tJBKJhh/kE9cfqNHJ5FBs264HeDPV0tJCEAQMDg5OCkSEEPT19fHsZz97Vrc337cLcaL4oR7nfD/PR6q1tZWWlhZ+/OMfN7z+wFmKQ93GQj22iy++mL/7u79DUZRJ74cDNTU1oWkab3nLW6adFd2wYQMAX/va19iwYQN33nnnpHEdnCw7Fy6++GI+8YlP8I1vfIPzzz+f//iP/+CKK65A07T6MalUiuuvv57rr7+e/v7++izOq171Kh599NFpb/ucc87hs5/9LL/+9a8Pu6Nu4qTY29s75bqenp4pf6+ZaGtr47/+67+IomjaAOe73/0ulUqF73znO/UZCYDf//73U45tamriNa95Dbfffjsf+9jHuO2227BtmwsuuGDWYzvQu971Lm688UZuvfVWHMchCAIuvfTSWd/O6173Oi6//HJuvPFG3vGOd0y726+1tRVFUfjlL3/ZMICauGy+P+eXIxncLEG9vb0NvxVNTC12d3cDcPbZZ6NpGrfccgtnnHFGw9ua+MA9+I3x+c9/fsqxh4rcp/t2+cpXvpL/+3//Ly0tLfUP/MX2kpe8hI9//ON87Wtf48orr6xf/u1vf5tKpTJpO/BMvjUfye3OtaX4PEM8rm984xuEYcjpp59+yGOXwmvooosu4n/+53/Ytm3btNvrk8kkZ555Jg8++CDbt2+fdlYK4veXaZqTApu+vr6Gu6WeqW3btnH66adz2223EYYhruty8cUXT3t8R0cHb33rW/nDH/7Apz/9aarV6rSznldeeSW33norl1122ZSt4BAH8N/97nc599xzOeOMM0gkEnzta1/jvPPOqx+zb98+7r333mlnIQ7lZS97GXfccQdf+cpXpl2iafRZJoSYdon64osv5pvf/CZ33XUXX/va1zj33HPJ5/OHHMfhZi+6uro477zzuPnmm/E8j1e96lWsXbv2cA9vikQiwUc/+lF+8Ytf8K53vWva4175yldy4403sn//ft74xjdOe9xsPuePFjK4WYLOOeccVq9ezate9Sq2bt1KFEX8/ve/56abbiKdTvO+970PiLfXfuQjH+Ef/uEfqNVq9W19Dz/8MENDQ1x//fVs3bqVY445hg996EMIIWhubub73//+lKljgBNOOAGAz3zmM1x00UUYhsGWLVvIZDKccMIJfOMb3+DOO+9k48aN2LbNCSecwBVXXMG3v/1tXvjCF3LllVeyfft2oihiz5493H333Vx99dWHPenNtZe+9KWcc845fPCDH6RYLPK85z2PP/7xj1x77bWcfPLJvOUtb5n0mBs9rmd6u3NtKT7PEG+j/rd/+zde/vKX8773vY+/+Iu/wDAM9u3bx89//nNe85rXcO655wLTP9cL+di6u7v57ne/e9jjPvOZz/D85z+fF7zgBbzrXe9i/fr1lEoldu7cyfe///16/tUrX/lKvvOd73DZZZfxhje8gb179/IP//APdHV18fjjj8/JmA90ySWX8M53vpOenh6e+9znsmXLlknXn3766bzyla9k+/btNDU18cgjj/Cv//qvnHHGGYdczt2wYUN9Ruikk07i3e9+NyeffDIADz/8MLfeeitCiHqAcM011/CRj3yECy+8kAsuuIDh4WGuv/56bNvm2muvnfXjuuCCC7jtttu49NJL2bFjB2eeeSZRFNUD0Te96U289KUvxTRNLrjgAj7wgQ/gOA633HILo6OjDW/z7LPPZvXq1Vx22WX09fUdMhCckMlkWLduHd/73vd4yUteQnNzM62trZPKFrzvfe+rvx4PzIGarauuuoqrrrrqkMc873nP46//+q+5+OKLeeCBB3jhC19IKpWit7eX//qv/+KEE07gXe9616w+548ai5fLLE3nzjvvFG9+85vFpk2bRDqdFoZhiLVr14q3vOUt4uGHH55y/O233y6e/exnC9u2RTqdFieffPKknR8PP/yweOlLXyoymYxoamoS5513ntizZ0/DXQEf/vCHRXd3t1BVVQDi5z//uRBCiKeeekqcffbZ9WqvB2b0l8tl8Xd/93diy5YtwjTN+hbaK6+8ctJWRUBcfvnlM34eptsKfrBGFYprtZr44Ac/KNatWycMwxBdXV3iXe96lxgdHZ103KEeVyMzvd0j2S11OHPxPB/8N5/YAXLwTqWJHRWDg4OHHavv++Kf/umfxIknnlh/DW7dulW8853vFI8//nj9uKX6Gmq0W0oIIZ588klxySWXiFWrVgnDMERbW5t47nOfKz72sY9NOu7GG28U69evF5ZliW3btokvfvGL9efvQNONfd26deKiiy6a0eMpFAoikUhMu7PoQx/6kDjttNNEU1OTsCxLbNy4UVx55ZX1reKH88QTT4jLLrtMHHvsscKyLJFIJMRxxx0nrrrqqim7KL/0pS+J7du31/9er3nNayZV+xVi+td2o+enVquJj370o2LTpk3CNE3R0tIizjrrLHH//ffXj/n+979ff52tWrVK/M3f/I340Y9+NOmz6kAf+chHBNBwG70QU3dLCSHET3/6U3HyyScLy7IE0PBvs379erFt27Ypl0/nwN1Sh9JoK7gQQtx6663i9NNPF6lUSiQSCXHMMceICy+8UDzwwAP1Y2b6OT/de3vis6DRbtnlSBGiQcMVSZIkSZKm+OMf/8iJJ57I5z73OS677LLFHo40DRncSJIkSdJhPPHEE+zevZuPfOQj7Nmzh507dx5256a0eGSdG0mSJEk6jH/4h3/gpS99KeVymW9961sysFni5MyNJEmSJEkripy5kSRJkiRpRZHBjSRJkiRJK4oMbiRJkiRJWlGOuiJ+URTR09NDJpNZsBL1kiRJkiQ9M0IISqXSYfuQwVEY3PT09Ezbh0mSJEmSpKVt7969h2wYDUdhcDPRyG/v3r2Tui5LkiRJkrR0FYtF1qxZM6OGvEddcDOxFJXNZmVwI0mSJEnLzExSSmRCsSRJkiRJK4oMbiRJkiRJWlFkcCNJkiRJ0ooigxtJkiRJklYUGdxIkiRJkrSiyOBGkiRJkqQVRQY3kiRJkiStKDK4kSRJkiRpRZHBjSRJkiRJK8pRV6FYkiRJWrq8IGKs6uGFEZqqkE+YJExtsYc1iR9GjFQ8BkoOXhCRMnXaMhbNKVM2ZF4iZHAjSZIkLQkDJYddgxUKVQ9QAEHS0lnbnGRNUxJVXfzAwfFDdvSV6C3UMFQVQ1MZqXjsG62xriXJMW3pJTHOo50MbiRJkqRFN1LxeKSniBDQkU2gqQpCCMpuwI6+EqoCa5pTiz1Mnhwq01uo0ZGx0bWnMztqXsiuwTIpS6c7n1jEEUogc24kSZKkJaBnrIYXCFrSFtr4zIeiKGRsg4ShsXekhhdEizrGshswUHRpSpqTAhuAhKlh6Ro9YzWiSCzSCKUJMriRJEmSFlXNCxmuuGQTjRcTsgmDshtQcvwFHtlkVS/ACSKSZuNxpiydshvgBOECj0w6mAxuJEmSpEUVCYGIqM/YHExVFASw2BMiCgoIgRCNByJEnCmkIHNuFpsMbiRJkqRFZekqtqlR8xrPeDh+iKkpWMbinrIytk7S0qm4jcdZcn3ySRN7kccpyeBGkiRJWmS6ptKds6l4AX44Oa8mEoKRikdL2iJjLe4eGNvQ6M4lKDoejj85wCnWfISArrwtt4MvAXK3lCRJkrTouvIJik7A/rEalqZiGRp+GFFxA1ozFse0pZdE0LCuJYkfRuwv1BiuuOiqShBFJEyNLZ0Z2tLWYg9RQgY3kiRJ0hJgaCpbOzM0p0x6CzVqfoSpq6xrydKRtbGNpVHIT9dUtnRm6MzZjFY8/DAiYeo0pUzSizyzJD1N/iUkSZKkJUHXVLrzCbpyNmEkUBVlSRbEUxSFfNIknzQXeyjSNGRwI0mSJC0piqKga0svqJGWDxncSM9MFIFXAhGBngDDXuwRSZIkSUc5GdxIR67UB2O7oTYWBzmGDdluyK+TQY4kSZK0aGRwIx2Zwj7o+xMoKtg5UDXwazC4A9wSdG4HXa5HS5IkSQtPBjfS7AUuDD8BmgnJ5qcvtzJgJKDYA+l2yK9dvDFKkiRJRy1ZxE+aveoIOEVI5Kdep+pgJqGwP65FLkmSJEkLTAY30uxFPihKvCTViGbGszuRbB4nSZIkLTwZ3Eizp46vZk43MxN6oFtxHo4kSZIkLTAZ3Eizl2gGMw3O2NTrohC8arxragmUSpckSZKOPjK4kWbPsKHlGPBdqAxC6Md1btxSnEyc6YJM52KPUpIkSTpKyd1S0pHJrY6XnUZ3Q3X46SJ+rZugaX28LCVJkiRJi2DRZ25uvvlmNmzYgG3bnHrqqfzyl7+c0e/993//N7quc9JJJ83vAKXGFCVeelrzF7D2jPGf50D7tng7uCRJkiQtkkUNbu68806uuOIK/vZv/5YHH3yQF7zgBbzsZS9jz549h/y9QqHAhRdeyEte8pIFGqk0LVWLt4Qnm+Mt4JIkSZK0yBQhFq8Yyemnn84pp5zCLbfcUr9s27ZtvPa1r+WGG26Y9vfe9KY3sWnTJjRN47vf/S6///3vZ3yfxWKRXC5HoVAgm80+k+FLkiRJkrRAZnP+XrSZG8/z+O1vf8vZZ5896fKzzz6b+++/f9rfu+2223jiiSe49tprZ3Q/rutSLBYn/UiSJEmStHItWnAzNDREGIZ0dHRMuryjo4O+vr6Gv/P444/zoQ99iH/7t39D12eWC33DDTeQy+XqP2vWrHnGY5ckSZIkaela9IRi5aBaKEKIKZcBhGHIm9/8Zq6//no2b94849v/8Ic/TKFQqP/s3bv3GY9ZkiRJkqSla9G2gre2tqJp2pRZmoGBgSmzOQClUokHHniABx98kHe/+90ARFGEEAJd17n77rs566yzpvyeZVlYltyWLEmSJElHi0WbuTFNk1NPPZV77rln0uX33HMPz33uc6ccn81m+dOf/sTvf//7+s+ll17Kli1b+P3vf8/pp5++UEOXJEmSJGkJW9QifldddRVvectbOO200zjjjDP4whe+wJ49e7j00kuBeElp//793H777aiqyvHHHz/p99vb27Fte8rlkiRJkiQdvRY1uDn//PMZHh7m7//+7+nt7eX444/nrrvuYt26dQD09vYetuaNJEmSJEnSgRa1zs1ikHVuJEmSJGn5WRZ1biRJkiRJkuaDDG4kSZIkSVpRZHAjSZIkSdKKIoMbSZIkSZJWFBncSJIkSZK0osjgRpIkSZKkFUUGN5IkSZIkrSiLWsRPkiRJWtq8IKLk+EQCLEMlY+kNmxtL0lIigxtJkiRpCiEE+0Zr7B+tUXR8BGBqCi1pi41tadKWPH1IS5d8dUqSJElT7B2psqO/hKVrtGdsNFXB8UN6xxwcP+SEVXkSprbYw5SkhmTOjSRJkjSJ44fsGamSMHSakiaaGi9D2YZGZ85mpOLRX6wt8iglaXoyuJEkSZImKdR8Kl5I1p46ua8qCilTp7fgEkZHVWtCaRmRwY0kSZI0SRAJQEybOGxoKmEUyeBGWrJkcCNJkiRNYmgKCsq0wYvjh1iGhq7KXVPS0iSDG0mSJGmSpqRJNmEwWvWmXBeEEU4Q0p1PoMrgRlqiZHAjSZIkTWJoKse0pVFV6C86VL0AL4gYq3r0l1y68wnaM9ZiD1OSpiW3gkuSJElTtGUstqt59o/VGK64iCjENjS2dSXpyiUwNPndWIpn8hRFqe+oWypkcCNJkiQ11JQyaUqZOH5IGAlMXZVBjYQQgsGyS1/BoegEqEBr2qIjZ5NLGIs9PEAGN5IkSdJh2IYs1ifFhBA8OVRh12AFgJSlE0XxZX1Fh61dGdoz9iKPUgY3kiRJkiTN0GjVZ9dQhYytkzSfDiGyCYPhssvO/jJZ21j0gFjOL0qSJEmSNCMDRQchxKTAZkJTyqTk+g132S00GdxIkiRJkjQjhZqPrTeelVGVuD6S44ULPKoGY1nsAUiSJEmStDzo2vTFHQEiIdDUxQ8tFn8EkiRJkiQtCx1ZGyeIiMTUAMcNQnRNJZtY/HReGdxIkiRJkjQjrWmL5pRBf9HBD6P65TUvZKjs0r1EtoMvfnglSZIkSfPEDUK8IEJXVRKm3NL+TMWFHLM83l9mpOIRCgECLF1lbUuSY9sy0zZcXUgyuJEkSTrKFB2fihsAkDR0sgl9SZyQ5lLNC9k3WqW/6OCFEZqi0JK2WNOUJJdc/JmF5SxjG5y0Js9YzafmhyhAxtbJ2EvneZXBjSRJ0lHCDUKeGCgzUHRxwwgEGLpCa9piU3tmxcxsOH7IQz0FhkouuYRJPqHjhxG9hRpjVY/junM0p8zFHuaypqrKkn4OZXAjSZJ0FAgjwY6+Ej1jNVpSFi3jRdYcP2T/WI0oEjxrVW5FtFfYP1pjqOTSlU+gjs9IGZpK0tTpLzo8OVQmn2iSXc1XsOX/KpYkSZIOa7Tq0V90ac/Yk6rH2oZGVzZBf8llpLL4xdeeKS+I6Cs6ZGyjHtgcqDllMlrxKTr+IoxOWigyuJEkSToKjFU9QDScmdFUBV1RGCq5Cz+wORZEEX4QYRmNT2+GphIKgXfATh9p5ZHBjSRJ0lHAD0XDmYwJmqrgh9MXZ1suNFVB16Z/LEEYoSoK+hIoNCfNH/nXlSRJOgqkTA0/mn62wg1DMvbyT8O0dI32jE2h5iEaFJor1HxyCZ3sCnis0vRkcCNJknQUaElbJA2dQm1qrknZDTA1lda0tQgjm3vdTQnyCZO+ooPjx32O/DBiqOwiEKxvSaGvgMRpaXoydJUkSToKpCydY9vTPNpXpL8YkrJ0FOLABmBTR3rF1H9JWzrHrcry1FCF4bLLSNVDUxRySYN1zUnas/ZiD1GaZzK4kSRJOkp05xNYukpfwWG0Gu+Mas9adOUStKaXbs2SI5G1DU5YlaPkBuMVihUytoEmt38fFWRwI0mSdBRpSVu0pC38MEIIMDRlxVUnnqAoCtklVDVXWjgyuJEkSToKrYRifUeDKBJEQqCpKzcInQ8yuJEkSZKkJabqBQwUHfqKLmEkSJkanbkEbRlLLq3NgAxuJEmSJGkJKTo+D/cUGat6pEwdXVUZqfj0Fx3WtaTY1JGRAc5hyOBGkiRJkhaY44eMVDxKjo+qKOQSBk0pE01ReGKgTMnx6c4l6ktRaVvHDUJ2j1TJJgy684lFfgRLmwxuJEmSJGkBDZddHusrU3A8dFVFCBAIWtMWHVmL4bJHS8qakmNj6RqWptJbqNGZtWXjz0OQwY0kSZIkLZCKG/BoXwnXjybNzISRoL/oMFR2CaJo2oTvhKlRcUP8KMJStYbHSLJCsSRJkiQtmMGSQ8nxactMnpnRVIX2jEWh5lFxw4atIwCiCFRVOWSfMEkGN5IkSZK0YIbKHgmj8aKJrqnYho4QgoobNjym6Pq0pU25lf8w5LKUJEmSJC0QARxqzsXSVTK2TcHxUZS4bQbEy1YjFY/k+JZw6dBkcCNJkiRJC6Q5afJ4uUQTU9tdhJFACMGWjgwVL2D/aI2C44MARYFswmBTe5pcQlZdPhwZ3EiSJEnSAmnLWuwbqzJa9WhKPh3gCCEYKrs0py1aMxZdWoKuXIJCzSeMBJah0pSUy1EzJYMbSZIkSVogWdtga2eWHX0l9o9WsQ0NAbhBSD5psrkjUw9gUpZeX5aSZkc+a5IkSZK0gDqyNklTY7jsMlYNUBRozVi0pExsQ27vngsyuJEkSZKkBZaxDTKyY/m8kcGNJEmSJEnPWNHxGSy6FBwPTVFpSZu0pq1FmY2SwY0kSdIMVb2AwZLLYCnu1NycMmnLWOSTU3e+SNLRpGesxuP9JWp+SMLQESKgt1AjnzTZ1pVd8B1eMriRJGnRFGo+gyWH0aqPpkJryqItY5Mwl17ewWjF45HeIkXHJ2noKArsGqywf7TGsR1pVjclF3uIc8YPI0YqHoWqj0CQsQ2aZT6INI1C1eex/hK6qrIqb9UvF0IwUHJ5vL/ESWvy6Au400sGN5IkLYqesRqP9Zdwg/ibXhQJBoou+TGHrV2ZJTUb4gURO/pL1LxwUj+gfBKKNZ+d/WUylkEuufxzKMpuwKO9RYbLLqqqogBBVCFnm2zpytCcWjp/F2lpGCg5uH5EywGBDYCiKLSmLQZKDiNVj/aMvWBjkhvmJUlacAd+0+vOJWlKmrSkLbpzCcpuwI6+El4QLfYw60arHoWaT2tmaqfmbMLADSIGSs4ijW7u+GHEo31FhiseHdkEnVmbjqxNdy5B1Y+DnqoXLPYwpSVmonJyI5qqIICa17idxHyRwY0EXhVqo+AU465skjTPBssObhBOWYef+KY3WvUYrXqLNLqpKm6AAtM2K0yY2pIa75EarXiMlD06Mjaa+vRjVRSF9oxN0fEZLi//xynNLUWJA5hpHfLK+SGXpY5mXhVGn4JSHwQOqBokmqFpHaTbF3t00go2WvWnbR6ojXc8rrhLZ4ZAUxWmadIMgBDTBz7LSdHxASYFNgeydY3hssea5pWTXyQ9c21pkx19pUkVlyf4YYSqKKQXuBihnLk5Wvk16P8TDO8E3YiDGTsHtWHo/UMc8EjSPFHg0MECSytYSFs6mqrgh1NnNoUQ1PyA9ozV4DeXH+UQbR0VRSFCzu5Kk7VlbdIJg8GSizjgjR2E8XJtW8Zc8Bw6GdwcrYq9UOqH3Cow0/GsjW5BugMQcdATLp1vztLK0paxqPnBpA/CCRPf9DL20plYzifjLd8DJXdSgBNG8W6QfMKkdQUEN2nLIEIQTRN51vyA5iWU6C0tDWlLZ1tnhoSh0Vus0Vd06CvWGKq4dGZttnRmp50NnC9L59NDWjhhAMV9YGVAaRDfJpriwKc2Cum2hR+ftOK1ZSz2j8bf9FozVn2Wxh//pteZtZfUbilNVdjSmQGo17iJCfJJky2dGZLm8v84bU6Z5Me/gbcflDw9XHZJWTqtC7jjRVo+WtIWJ6/TGal4cY6aArmESVPSWNAt4BOW/7tRmr0ogNAHY5oPKXX8ZRH5Czcm6aiSNHW2dWXZ0V+ir+jEy1TES1GL9U3vcGxD44RVOcZqPiXHJ4oESUunObVyOjWbusrWziyP9BXpKdSwdA0FcIKQtKWzuTOz4LkT0vJhGxrd+cRiDwOQwc3RSdVBMyDwwGiQGBiFoCigLv+aHdLS1ZQyOWVtU/2bnqpAJmHQlDSXXGAzQVUVmlPmiq71kksanLQmz1DZZaTiIQTkkwataUt2qJaWDflKPRppOmRXQf9DYGenLk3VRsHKQiK/KMOTjh6mrtKZk8scS41taKxuSq6oqsvS0WVlzKVKs5fthlQ7FHrAq4CIIHChPBBvY2k5Np7dkSRJkqRlRs7cHK2MBHSdACNPQrkfnAIoGiSbIL8eMh2LPUJJkiRJOiIyuDmamSnoPB68DfGsjaqBmQFVTuitOEKAWwIRgmaBKZcbZsrx47LxpqaiLtFcIEmSJlv0s9jNN9/Mhg0bsG2bU089lV/+8pfTHvtf//VfPO95z6OlpYVEIsHWrVv51Kc+tYCjXaHMFCSb4yJ+MrBZecqDsP+3sOfXsPtX8X/7HoqXI6VpDZdd/ry/wG+eGuF/nhzmwb2j9BZqRNEi1JKXJGlWFnXm5s477+SKK67g5ptv5nnPex6f//znednLXsbDDz/M2rVrpxyfSqV497vfzfbt20mlUvzXf/0X73znO0mlUvz1X//1IjwCSVriSv3Q98d4+3+iKd4pF9RgZFc8k9O1Xc7iNNBXcHi0t0gQCTK2joJCqRbwx9IYG1rTHNuelrM4krSEKaJRidAFcvrpp3PKKadwyy231C/btm0br33ta7nhhhtmdBuve93rSKVS/Ou//uuMji8Wi+RyOQqFAtls9ojGLUnLQhjA3v8BvwKpg4oxiggK+6D9WdB67OKMb4ly/JAHdo8ShYKmg7Z8O37IWM3npDV52lZARWJJWk5mc/5etDUIz/P47W9/y9lnnz3p8rPPPpv7779/Rrfx4IMPcv/99/OiF71oPoYoScubMxb/JJqmXqeocRmA4v64oKNUN1LxqDg++eTU3YK2ERe1Gyg6Cz8wSZJmbNGWpYaGhgjDkI6OybtyOjo66Os7dNPG1atXMzg4SBAEXHfddbz97W+f9ljXdXFdt/7vYrH4zAYuSctF6I+3q57mba5Z4FfjJSu57b/OCyIURZnUeuBAtqFRXkIdyyVJmmrRs0cP/gARQkz7oTLhl7/8JQ888AD/8i//wqc//WnuuOOOaY+94YYbyOVy9Z81a9bMybglacnTjLjSdDTNiTh04yrU0wU/RylNVThUznAQRpj6on90SpJ0CIv2Dm1tbUXTtCmzNAMDA1Nmcw62YcMGTjjhBN7xjndw5ZVXct1110177Ic//GEKhUL9Z+/evXMxfEla+ux8vAOuNjr1OhGBU4orVc/TrE0UCYqOT6Hq17dTLwfZhIGlK9S8qWMOI4EbhLRnZVVlSVrKFi24MU2TU089lXvuuWfS5ffccw/Pfe5zZ3w7QohJy04HsyyLbDY76UeSjgqaHleaRokLNQZuHNR4lbgydaotrlQ9D/qLDr/bM8oDT43wm6dGeOCpEXYOlHCDpR/kZG2dVfkkI1WXshswsefC8UP6ijVaMxat6ZXbW0qSVoJFnY++6qqreMtb3sJpp53GGWecwRe+8AX27NnDpZdeCsSzLvv37+f2228H4HOf+xxr165l69atQFz35p/+6Z94z3ves2iPQZKWtExnnDw8uhtqI/ESlW5D84b4Zx62ge8fq/FIbxFNUcjZcRPMqhfweH+ZihuyrSu7pJd1FEVhY1sKVYXegkNv0UdBYGgq3fkEx7ansXRtsYcpSdIhLGpwc/755zM8PMzf//3f09vby/HHH89dd93FunXrAOjt7WXPnj3146Mo4sMf/jBPPvkkuq5zzDHHcOONN/LOd75zsR6CJC196XZItoJXiju+61ZcuHEeOH7Ik0MVLE0ln3x6diNjGyRNnb5CPPOxKp+Yl/ufK7qmcmx7hlX5JCXHRxAnEmdt/bA5gZIkLb5FrXOzGGSdG0maP30Fhz/sG6Urm2gYBAyXXdK2zqnrmmSQIEmLrOj4DBZdRqseqgqtKYvWjEXSXJqbDGZz/l6aj0CSpGXJDyNg6i7ICZau4QYRkQBNxjaStGj6Cg47+ovUvJCkoRMJwUDRJTtqsK0rO6WA5XKzdBe+JUladgwt/kiZbkLYCyMsXUV2LpCkxVN0fHb0F1FQWJVP0pQyaUlbdOcS1LyQHf3LI/n/UGRwI0nSnMknDVKmTtGZWlsnjAQ1P6AzZ8slKUlaREMll5oX0ZScPDujKAqtGYuxqs9IxVuk0c0NGdxIkjRnbENjfWsKxw8ZLrv4YUQkBGU3oLdQozNry55My1gQRrhBSCg7oy9rYzWPhNF4x5+qKGiKQmWZV+GWOTeSJM2pVfkEuqqyd7TKSNVDRGCbKse0pVnbkpTbqJehmhfSV6jRV3Dxo7hCc3fOpiNny7/nMqSiIsT0wYtg+QevMriRJGlOKYpCZy6eoZkogmcbGvY03xSlpa3iBjzcW2So5JKxDSxdxQ0iHuotMlLx2NqVlX/bZaYlbdJXdBq2O5qYlcsllndCsQxuJEmaF5qqkEvIhpzL3VNDFYbLLt35BOr4iTBpQtY26CvWSNs6x7ZnFnmU0my0pi3yCYOBkktbxqr/XYMwor/k0J6xaUou7/euDG4kSZKkhspuwGDZpTn59AlwgqYq4wGOy5pmudy4nCRMja1dGXb0legrOqgoREKgKNCesdnSmUHXlndK7hEFN1EUsXPnTgYGBoiiaNJ1L3zhC+dkYJIkSdLi8oII149oSTUOXBKGxkjNww0iGdwsM/mkyclrmxipeJRdH1VRyNgGTUlj2Qc2cATBza9//Wve/OY3s3v37im1LBRFIQyX9954SZKeJoQgjASqoqDK4jRHHVWJZ2iCMGp4wgsigTa+u0ZafkxdpTNnAyuvy/2sg5tLL72U0047jR/+8Id0dXXJehWStAIFYcRg2aVnrEbNj9BVha6cTXvGJmHKb+hHi4xtkE3oFGo+LempW/gLNZ+2jEVSviakJWbWwc3jjz/Ov//7v3PsscfOx3gkSVpkQRjxaF+JfaM1LF3FNjT8IOKR3iL9RYfjunOkLZmut5wEYUTJCQiFwNJV0tbMGoBqqsLa5hR/7ikwWvHIJQ1URSGMBGNVD11TWN3UuI+YJC2mWX9CnX766ezcuVMGN5K0QvUWHPaNVmnP2PV2CgDZhEFfwWHXYJkTVuXkCW0ZEELQV3TYPVylPBHcaCotGZMNrekZBakdWYtIZHlqqEJfoQaKgkL8etjYlmo4oyNJi23Wwc173vMerr76avr6+jjhhBMwjMnbxbZv3z5ng5MkaWGFkWD/WI2koU8KbCCuXNqcMhkquxSdQG7zXgZ6Cw4P9xQxNJXWtIWmKjh+SM+oQ9UNOWF17rAdoBVFoTufoDVtMVbzCCOBoankEysj8VRamRQxXYe7aajq1Bezoij1YkBLPaF4Ni3TJeloU/NC/ufJYVKmPm1htp5CjZPX5GnPrrwkxJXECyIeeGqEIBJTeggJIegZq7GpI8Mx7elFGqEkzc5szt+znrl58sknj3hgkiQtbYoSz9BE03zniYRAAbkktQyM1TxKjk9nLjHlOkVRSNsG/UWHdS1JOQMjrTizDm7WrVs3H+OQJGkJsA2NlpRJT6HWcLmi5ASkLJ1sQiYUL3VhJEBRphTfm2BqKk4QEkQCWaJGWmmO+BPq4YcfZs+ePXje5Lbor371q5/xoCRJWjzd+QRDFZfhsks+aaKp8bJz2Q2oegFbOzOyYNsyYGgqqhIHOVqDGkVOEGLq6pTcKklaCWYd3OzatYtzzz2XP/3pT/VcG3h6mnqp59xIknRoTSmTbV1Zdg1W6C/WAAUQJEydzR1pVjclF3uI0gzkEwZZ22Ck4tGWmbyjKYwEVS9kfUuyYeAjScvdrEP2973vfWzYsIH+/n6SySQPPfQQv/jFLzjttNO477775mGIkiQttPaMzanrmjh5XRPPWpVl+5o8z17fzPrWtKxUvEzomsrGtjSaBn0Fh5oX4ocRxZpPb6FGZ9aiIyeTwqWVadYzN7/61a+49957aWtrQ1VVVFXl+c9/PjfccAPvfe97efDBB+djnJIkLTBDU2nPyJPfctaWsdiu5tk3VmWk7BF6AkvX2NyRYVVTQi4vSivWrIObMAxJp+Otg62trfT09LBlyxbWrVvHjh075nyAkiRJ0pFrSpk0pUyqXkAk4kRiU5d5NtLKNuvg5vjjj+ePf/wjGzdu5PTTT+fjH/84pmnyhS98gY0bN87HGCVJkqRn6HDF+iRpJZn1q/3v/u7vqFQqAHzsYx/jla98JS94wQtoaWnhzjvvnPMBSpIkSY3VvJDhistYNd612pSyaEmZ0xZglKSjxawrFDcyMjJCU1PTsijsJSsUS9KRcYOQ0YqPG4SoikIuGe/GkY6cH0Y4foiiKCQNbVbJ2sNllx19JYpOgKmpCAR+GJFPmmzrzJJLyr+NtLLMa4XiCTt37uSJJ57ghS98Ic3NzcxBjCRJ0hI1UHJ4or9CwfFRlLh8v61rdOcTbGxLyQq3s+SHEftHq/QVXCp+gEYcLK5qSswoibvmhezoK+H4Ed05u/7FUghBf8nlkb4iJ6/Ny4Rh6ag160+k4eFhXvKSl7B582Ze/vKX09vbC8Db3/52rr766jkfoCRJi2us6vFITxE3COnK2XTnEqzKJ0mYGruGyjw1XFnsIS4rQRixo6/Eo32luO9TwiRl6YxWfP64r8D+sdphb2Oo7FJyAlrT5qQZc0VRaM9YFGoeIxXvELcgSSvbrIObK6+8EsMw2LNnD8nk08W8zj//fH784x/P6eAkSVp8PYUaXhjRkrYmlfJPmjq5hEnPWFxDRZqZobLH/rEa7RmbXMIgjAReEJEwNQxF4cmhCo5/6OdzpOJh6mrDVABVUdAUlWLNn6+HIElL3qyXpe6++25+8pOfsHr16kmXb9q0id27d8/ZwCRJWnxeEDFS9khbjfM3UqZGb9Gn6PgkTLkEMhN9hRqGqhIJwVNDFUaqHn4QoSiQNDUUBTa2JunOy0rQknSkZh3cVCqVSTM2E4aGhrAsq8FvSJK0XEVCEAkwpslzVRQlbs4gU+5mRAhBzYtQFdg1WGG06pGxDNIpnSiK+3cNll32jzqHDG6aUya9BQchxJTZm0gIgkiQTRxZQnEUCcZqPiXHJ4oESUunKWnK2jjSsjLrV+sLX/hCbr/99vq/FUUhiiI+8YlPcOaZZ87p4CRJWlymppKytGmXnbwgQtMUEnLr8YwoioJpKAyWXEarHq0pi4SpoSoKuqaST5roqsL+Qg03mH5pqjVtkbV1BsvupM0ckRAMllyakgbNKXPW43P8kD/1FPjd7lEe7S3xWH+Z3+8d43d7RhmVOTzSMjLrmZtPfOITvPjFL+aBBx7A8zw+8IEP8NBDDzEyMsJ///d/z8cYJUlaJKqq0J1P8MfSGI4fTqqfEgnBUNmlM2eTTcgCcTPVnrW5f+cQKcuYsvW76gXkUwYqMFb16cg2DhoTpsbWriw7ekv0FGpxZ28BgYjIJ0y2dmVnvVMqigSP9ZfoHa3RnrXr3cLDSDBcdnmkt8iJa/KkLPm3lpa+Wb9KjzvuOP74xz9yyy23oGkalUqF173udVx++eV0dXXNxxglSVpEHRmb9a0pHu4p4gYRtq6haaAqKu1Zi2Pa08uixtVS0Zw0ydoGY1WfhKFiGzphJKh4AV4QsrY5CYqCH0aHvp2Uycnr8gxXPArjRfzySZOWtHlEW8DHaj4DRXdSYAOgqQptGYueQo2hsjttcCOEoOgElBwfIcA2NJqShiwTIC2KIwrBOzs7uf766+d6LJIkLUFeGFHzQyKgUPPp92sYmsbG1hQbWlOk5Tf5WUmaGsd0pHlqsIIbRpQcB1VRSFoaq/JpWtImAyUXcwZBgW1orMonWJVPPONxDRQdesaqjI4HSjnbIJ80SZjaeJFBnYGSy7qW1JTf9YKInQMl+ooO3nhytIJCc8pkU3tGFhSUFtyMP5X27Nkzo+PWrl17xIORJGlpCSPBjr4SfWMO65tTbG7PIMYTVgfLLk8NVcjY+rwWi4sigTt+wrSm2f68nCiKwvqWFGUnIJ808PyIQAhSpk7S1MeTjPUFDQgGSg5/3l9g/5hDVy4OlEYrHsmSy/rWFLlEvIQWRlMzx4UQ7BwosWekSkvKwk7Hr4UwipctH+ktsn1NTva2khbUjF9tGzZsqP//RALbgR8yE1n7YSjrXUhLj+OHDJVdBkoOQSjI2gbtWZumpLHsT5bzabTqMVByJi1VKIqCoSl0Zm36ijWGyx7dczBzcDAhBAMll56xWr1mSy5h0J1P0JaxlvXfrS1j0ZoyebS/hOdHoMQ7zjRVoSlt8hfrmxesunDFDXisr4SuKbSkTNKWjqYqgMFo1WP3cIUtnRkqXsCGBrM2xVpAb9GJA5sDcrI0NS4o2FOoMVhyWdcigxtp4cz41aYoCqtXr+atb30rr3rVq9B1+UKVloeS4/NIb5HRqo+lqWiqwp5qlf2FGse0pljXklrWJ8r5NFb1EIJJORgTVEXBUDUGS+6cBzdivAbMzsEyuqqStnSEgJGKz1DZY1NHuuHyyHKhKQqKqhCEEW4QBzcIASo0CRNdXbg8laGyS9kLWNeSouaFjNU8mpNx5eN8wmCoHAeYGVunLTO13EfR8fEDUZ+xOdDEclZ/sfFyliTNlxlHKPv27eOrX/0qX/nKV/iXf/kX/uqv/oq3ve1tbNu2bT7HJ0nPSBQJHu8vM1b16cza9Qq7eeJvrDsHKqQso+GHthQvLaiHCPw0VSGahyI3xVrAk8MVMpYxKYE1YWqU3YAnBys0pcxl27hzoOQyWPLYvrqJSAj8UKAokDA0RioeTwyWySeNhkHlXBur+tiahq6qrGtJ8dRQhcGKi6VpqAoUHB/bUDh5bZ6mBtvLIxGPfToTy1mNavJI0nyZ8Tuns7OTD37wgzzyyCP8+7//O6Ojo5x++uk85znP4Ytf/CJRdOjMfklaDGM1n5GKR+tBrQMAUpaOAPqLzuIMbhlI2wZBFE3bGLfmB/MSYAyVXfwwargzJ23pOEHESNmd8/tdCEIIegs1bF3F0FQsXSNt6aRMHVVRaEqaFGt+PbF3vikKTKTSZGyDTZ1pNrakSJgqhqbQlrY4rjvHmubGMy8JQwMhGubjQLwknEvqMrCRFtQRfS14/vOfz5e//GUef/xxkskkl156KWNjY3M8NEl65qpeQCjEtN+A06ZOoeYTHGbb7dGqOWmSto2GTRiLNR/b0Gidh1mvihdgadPnnJiaSnWZ9rMKIkHNj7CmKXyoqQqCeAfSQmhJW/hhWA9gbV2nM5fguK4c27pydObsaQMbgKaUSS5pMtwg2Kx6AYoSlxOQpIV0RMHN/fffz9vf/nY2b95MuVzmc5/7HPl8fo6HJknPnKIoCKZfNomEQAH5rXIaCVNjc3saRYWesRqFmk+x5tNXrOGGIce2p8kdYZn/QzE0FX+amQCAUEQLsmQzHzRFQR/Pt2lECAFCLFjeTct4cDJQcifNvoSRoL/k0Jq2aEpOX+3Y0FQ2d2SwTI3946+RkuPTX3QoOQEbWlNHVC1Zkp6JGefc9Pb2cvvtt3PbbbcxOjrKX/7lX3L//ffzrGc9az7HJ0nPSMbWsTR1SnXdCWU3YGNbanx3iNRIe9bGMjQGig5DZQ8ErG5K0JFNzNtJqzVtsXekih9ODWLi4nbKsj1hqqpCZ9bi0b4SucTU3XplNyBp6fMSNDZiGxrburLxlv9iDU1R618IWtImWzoyh+0r1ZwyOWlNnv6CE7eEiKAzZ9OZs2lJmfLLg7TgFDHdYvpBTNOku7ubiy66iFe/+tUYRuM33vbt2+d0gHOtWCySy+UoFApks9nFHo40z4QQPNJbZM9Ilba0Xf+QjoRgtOKhqgonrskv2IlkuRNCxJt65jkYDCPBQz0FesZqNCXNeo2UihswVvNZ3ZTguK7svI9jOn4YUajFjSVNXSVrT22lcCg1L+SP+8YYq/m0pOKKwpEQlJyAqhewuSPN+tb0PD6CqbwgYrTqUXLibfdZ26ApZc56hmyhXiPS0Wc25+8ZBzfqAVOkE1H4wb+6HOrcyODm6OMGIY/3l+krOgRhhDq+VJWxDDZ1ZOROqSXKDUKeHKzQX3RwxvNPbEOlK5tgfWtqUbpUCyHoKzrsHq7Wa++oSjyLtLEtRf4QyzcHKzk+uwYrDFfceLcUcZL7mqYEq5uSMjhoIAgjRqs+jh+iqgpZWyezgDvmwkgwUvEo1DzCSJC2DVpSZsNZYWnuzeb8PeNlqSeffPIZD0ySFoOlaxzXlWVVPkHR8QkjQcLUaErKD6WlzNLj5pBrmpNUvACId0otZqXbvqLDQ/uLmJpKe8ZGU+MeUMMVj5ofcsLq3Ix3j2Vsg+2rcxSdANcPURSFbGJ+qz0vZ2NVj50DZUYqce0liCtWd+VtNral5z0Hy/FDdvSVGCjFuysVFIKoEu8w60jTLpOml5QZf0qsW7duPschSbHABbcMCDCSYCbn5GZVVaEpZTas0yEtbSlLXxKdqP0wYvdwFVNTJ72ODE2lM2vTM1ajZ7RGtmvmMwmKosRLojNcFj24OaVlqDQlZ790tNxU3ICHe4pUvLAeVEK8G+vJoQoAWzrnbyY+igQ7+kv0Fhw6Mla9GagQ8UzOo70lbENbtnWXVqLF/8SQJIAohLE98Y9XAkEc3GS7oXkj6EsrKHGDkJGKx0jZIxSCXMKgJW3JJpIrWHF8F1BbuvE39FzCYLDssn6a5PVnyg/Hm1MWnLjXFgqKEt/v5o7Mig7c+4sORSegO2dPSk6emMXrHXPozifmbYmqUPMZLLq0pa1JXc4VRaElbdFTqDJQdGRws4TIT2Jp8QkBQ4/HP3YaMl2AAl4Zhh6DoAYdJ4C2NF6uJcfn0b4SIxUXXVVRFYWesRopS2dzR4aOrJyeXolCIYjG+z81omsKji8mVWwOI0Gh5uMFEaoaByJHuuz0xECZ3cM1WlImrQc0pxwuuzzcW+TENfkVGVwLIegvuqStxoUAJ5qNFp1g3oKbshsQjiePN5IyDQZLHse0ySrMS8XKeydIy48zBmO7IdUcz9ZMsDKg21DYHwc8mc5FG+KEIIx4rL/ESMWjM5uYVPV4tOLxaF8R29Dk7qsVyNI0NFXBC6KGJznHjy+fWCIaHW+jMFb1iUTcfiBtG6xtTrK6KTGrk2DR8ekrODQflCemqQrtWZt9Y1X6Cw7p9oXdYbUQIhEHONohni8FhegQdZHmhDLPty/NqZW9UCstD9VRCLzJgc0EzQBVg1L/wo+rgdGqz3DZoyNjT2nn0JQycfyQwZJs53A4USQYKrs83FvgN0+N8Ie9Y/QWas+oKq/jjy8VVjzcYO53bWZsndaU2bAtQhgJyq5Pdz7unl50fB7qLTJW9WlOmXTlEnTmEggBj/YV2Tdam9V9l5wAJwxJmI1nfTKWwUDJnf8T/CLQVIW0rVMdTyo/WBjFva3mc3NAwtRQFXXawotVL6ApObVmkbR4Zh3cXHfddezevXs+xiIdrUIPDlFqH82Il6aWgKoXIJh+aSJp6AyXF6Yn0HIVRYKdA2Ue3DNGz6hDzQsZLnv8YW+Bh3sKOP7sAhM/jHhioMwDT40c8DPKU0PlafsdHQlVVdjQmiZpavSM1Si7AY4fUhiv2NyZteka747eM1qj4gR0ZO36TI46njxs6xp7R6qzCuSiSKCIQzQwVZS4vswze4hLVmfOJkJQa9ByY6jsxpsFkvM3W9qUNGlJmQyU3SmNYos1H0NT5HL0EjPr4Ob73/8+xxxzDC95yUv4+te/juPIb6nSM2TYcKj6SIEH5hKabj/EGWSlnlzmUl/R4cnhCvmEQUfWpilp0pax6Mza9BUcdg2WZ3xbYSTY0Vfi8YEymhLvWurI2ggBO/pLPDFQnrbp55HIJQ1OWJ1jfWuSMIqoeAGaorC1M8O27iyWruEGIUNll+w0S5PZhEHZDSiM18mZiYSpoapMG6xVvIC0ra/YStutKYsNrSkKjsdA0aHsxM/f/rEaCVPj2Lb0pETfuaapCps60jSnTHoLNQZLLiMVj/1jVfwoYtMKT+hejmb9avjtb3/L7373O7Zv386VV15JV1cX73rXu/jNb34zH+OTjgaJZjAT4JamXheMB8/pjoUd0zRSlo6qcsjp6da0LAo4nSgS7B+rYWnqlGUEbXy7/kDJpew2XoI42EjFo7dQoz1jkbbjhNOJGZLmpMXeseqsgoiZyNgGWzqzPHtDM3+xoZnTNjSxvjVdTxSOojgI0RsEGm4QMlh2eWqowp/3F9g7Um04G3GwfMKgKWkyVHanBGsTs4mduckzB1EkcPxwXpboplNyfPaOVHlioMzekeqM/46Ho6oKG1vTnLg6T2vGIkLEAUd7mhPX5BcksJioS7R9dZ6WtEk2obOpPcPJa5tY3TQ3JSukuTPjCsWNBEHA97//fW677TZ+/OMfs2XLFt7+9rfz1re+lVwuN5fjnDOyQvESNfIkDDwcL0FZWVCUuN6NV423grdvgwVqJHgoYST4w94xBksuHdmn621M1LtQVYWT1ublltBp1LyQ/3lymJSpT5sj0VOocfLa/IyKoj3cW2D/qEPnNEsCPWM1NnWk2di2cDN/QRjxwO5RvCCa1HCy4PjsHqowVvXwwohj2zMYmkrW1tnSmaHlMEFxoerzSG+RsapH0tLRFIWqH6IAG1pTbGxLoShxYm1/yakvnamKQlPSpCtnH/Y+jlQUCZ4arrBnpIrjh2iKSigiEobG+tYUa5uTc5qPEkZxRWdZxfnoMpvz9zM6W0RRhOd5uG78baK5uZlbbrmFNWvWcOeddz6Tm5aONk3roftksHPgFKE2BroFXduhfeuSCGwgnl3Y0pmhNWPSX6zRV3QYKDn0FBx0XWVrV0YGNoehANN9pZroiK0ws5OW5wuMQ5zgdFXBfQZJykdC11S6czYVN6jP8LlByO6hCjUvwNRVVjclWducpDtn4/gRO/pKh53BmVgS29qVwdLjEgRdOZsT1+QnBTZPDJb5074CxVpAQtcxNZXegsMf98VJ2/Ohp1Bj50AZS9dYlU/SmbNZlU9iahqPjRe/m0uaqsjARjqkI9oK/tvf/pbbbruNO+64A8uyuPDCC/nc5z7HscceC8BNN93Ee9/7Xs4///w5Hay0gilKXLAv3Ql+JT77GcklU9vmQClLZ/vqPCMVj9GKRyQEGdugNW1Nu5tFitmGSj5pMlRyGz5XFTckZelk7Jn93ROmymA5IhhvZDlW8wnCiJSlk0+YBJEgYSx8YNyZSzBa8+kdq5E0dEqez1DJxTJU0rbB6nyyvtuuNW3SU3AYrrisPkxF7rhac5p1LamGzSlHqh67h6vkE+ak53eiFswTA+Up1z1TQRixb7SGbWhT6uykbR03CNk/Vps00ylJ823WZ47t27fzyCOPcPbZZ/PlL3+ZV73qVWgH7XS58MIL+Zu/+Zs5G6R0FFHVuL7NEmdoKh3jyavSzCmKQnc+wWDZpVDzydpPF2Zz/JCC47GpPTPjbb2taYudA2Ue7ilQ8UI0VUVTFUYqHrtFlaakTlOqedLvRFFcaE9TlXnbumvqKts6szQnTfaP1RgZ8dBUhTVNSVoz1qT+WIqiYGoqoxVvxrkbihJXJz7YRN+jRsFLPmHQU6gxUvVYZSaO7IE1UHFDyk5AyzR5L9mEwWjNo+IFclZTWjCzDm7OO+88LrnkElatWjXtMW1tbUTRwk4FS9LRwg1CSk6AEPFJ7OBvy4Wqz0DJYbjioRAHAO1Za167J1e9gOFy3C1ZVRWakxbNKbNhsbu2jMW2riy7Bsv0FhxURSEUcQG8ja1p1rXMPDkznzAQEewZrdGZs0lberzkJQRF18eP9PqW66oX0F9w6Cu6hEKQMjW6cgnaMta8zCiYusqa5iTd+QS2odJfcOjON35sAtEwWIE4GButPl2/J2HotKRNcompdVVKtQBrmiq6iqKgKSruLLfaH45ANJxFmqAqCiKafilSkubDrIMbIQRNTU1TLq/VanziE5/gox/96JwMTJKkycJIsG+0yr7RGhU3QAiBZWi0Zyw2tqWxjbj+ymP9JVw/XpoRQvD4QJmeQo2tnVnaMnOfUDpQdHisv0TZDTA1DSEEe0fiNgFbu7INWwKsyidoShqMVDwcP8TUNHJJY9JMzkyU3RDb1DhxdZ6xmkfJiXdGJS2dta1JgjAu3W/qWpyMW/FIWTq6pjJa8RkoOqxtSbK5IztvSyaaGtdA6S86REJMKf4ohCAII5pSU/82fhjxeH+J/WMOINBVFTeosXtEZV1zig2tqUlBhamrVA+RuxOKCH2O89dsQyNhqlTcxu0Pym5A0tRIzGORPUk62Kx3S2maRm9vL+3t7ZMuHx4epr29nfBQ9UqWALlbSlqudg6UeGKwQsqMc1JURaHqBYxWfTqyFmubk/y5p4CmqFPaPwyXXUxd5ZR1TXNaybXo+Px+zxhCQPMByxLh+I6dtrTFiWvy8xY49IzV+NP+At25BGEU4YzP0tiGhqYolN0AP4qwdZVCzacjM7nxohuEDFc8TliVozs/d0s1E8LxWZeBosOf9xcII9jQliRlxn+fSAgGSy5pW+ekNfkpf5snBso8PlCiLW1PmgWrenGdl+MPGnfPWI0/7hujM5uY8pw7fkjJ9Tl1bTO5OS54F4+zTHvGmtSh3A8jBkoOWzszrG9dQrWqpGVpNufvI5q5afTN6g9/+APNzc0NfkOSpGeq5PjsG62RTxiT8jWSpo6la/QVa7hBSM2LWJWfOgMwUXxsuOKxag5P4oNFl6oXsOqg5RZNVWhPWwxV4mJn8zFjVCcm7lMlZapTrqu4ATUX2g4KbAAsXcPSVHoLcYXhudyB4wYhO/pK9Bfj3aQJQ+PJ4Qq9hRqrmxI0pyxCEZFLmGztnJpn5PghvYUaOXvq8l7S1Kl5UxN1W9JxQcS+Yo2W1ESgIaj5EcWax7qWFNnE3Cfpr2lOUvVCesaq6JqKqal4QUQoBGuak6ySdWCkBTbjV3lTU9N4EpvC5s2bJ31IhGFIuVzm0ksvnZdBStLRbqzq4/ghLQ2WLjRVwdY1dg9Vp01wVhQFTVUpOz4wu+Cm6gVUvbieStrWJ3W1Hiq7k4KtA+maSiQY7wk0P8FNytIxdQXHDxvOSJU9n5SpUfOjSTMKB0qYGhU3xI8iLHVuZrWEEDwxUKZnrEZ75ukWDKuakuwdrVKs+aRtnXUtSZpTZsNO4RU3ft47s41nWdK2TsmJXxep8aU/S9fY1pml6o7y0P4xio5PhEJHxmJbd5Zj29PzkkRt6irbujK0Zy36i3FLjXzKoCMT19aRu6SkhTbj4ObTn/40QgguueQSrr/++klF+kzTZP369ZxxxhnzMkhJWq4cPy7FP1hyCSJBxtJpz9qzbrIXFy07RD0XTSWIBIdqpdQo3+NwY39qqEJ/ycHxIxTiYGJ1U4LVTcklccLK2jodWZs9I9VJQQTAWNVDH893eWq4Ou2scxTFybCzeW4Op+QGDBTdA2ZPYoYWJ033Fx2ytk5XrnGgWfUChsouhZpHNqHXl7EORwjBYNnFDUKa0xatWRuEIBIKJSdewpyvWTRd7iCUlpAZBzcXXXQRABs2bOC5z30uhiG39EnSoZQcn0f7SgyXXWxdQ1MVRise+ws1jmlNsa4lNeMAx9TV8V0pjU/Qrh/SmbPxw7BhEDNRTC6fnFmZej+MC8v1Fmo0JU2akxaREJScgEd6S3hBxLHtaVrTFo8PlCZV4j3wPlWFaWd25oKiKGxsSxNEgv5ivA1aRcGPIpKmzpbOLE3JuKVDxQ1JN6ifU3R8NrSmpp3ZORIVN8ANI1oOmk0KI4EXROiawnDFww+jKTkqTw1V6C04FGrxUuRQyaO7KcGqfGLSDE/ZCUjbxqQZq9Gqz87BMmnLoCM7OXAaLrvs7C+TTegNZ4okaSWZ0adOsVisJ++cfPLJ1Go1arXGlS5lkq4kxdt3nxgoM1Lx6Mol6sFGnvjEt3OgQsoyZvwtujllkrZ0CjV/SoAykduwrTNDb8Ghv+jQnonzMIQQDA4NsW9ghLUdzeQTbTO6v+GyR2/BoSNj1xsSTvRsMjSFfaNVOnI2bVkrruNS8aYkFA+UXdrS1qTL54NtaDyrO06sHat6+KEgbek0p8z6cs2qfILH+sugUN+9FUaC4YpLytLoyM3DbMMBs2hBGDFYdhkqe3h+iBtEJC2NTe2Zek+oKBI83l9iz0icW7WuOZ4d29lfYt9IlSAUHNOWQlNVql6AF0Zszk9OHB4sOYShIJWe+tHelDLpK9bqr0lJWslmFNw0NTXVd0jl8/mG3xwnvlEu9d1SkrQQxmo+Q2WPtrQ1ZRYlZemU3YC+Ym3GwY1taGxsS/NIX5GBokM2YaAoUHVDakEQl/LPJ8klTR7rL7Frfz/3fO+b/PDrX2bv3t3129lyzDG86z3v4aKLLiKfz097f/1FJ04KHd/tUnICNFUhaWmoqPSMVTE1lc2dWY5tT7FrsML+sWp9K7gfCVrTJps7MwuyfKWpCq1pa9qmpRMVffeNVekp+PUFvlzC4Nj29JTdZc9U0tAxdAU3CNFVlaeGKwwU46rMCVOn4js4PjzaV0RVoD1rM1bz6RmLd5hNJBB3ZW38IKKv6PBEfwlViXOETF3lmLb0lJ5ahZo/7ZZrVVFQUGbUqFOSlrsZBTf33ntvfSfUvffeO29VPSVppah6AaEQ0y51pEydQi3uPaTPcDmkO5/A0FR6xmqMVT2EANvU2NCWoysXz9RkbYOBh/6Ht77xPGrVKq8HXg80AaPAt3ft4v1XXslH//Zv+ea3v80555zT8L68MKLs+uwdrY7XoYnrp/QWqiAUbENFKFDxQlrTFls6M9S8kKLjH7aI32LQVIVj2tN05W0KNZ8wEli6RlPSmPHzPxvZhE5rOp7V0hWVwbJLc8pE1+JZF0vX2NyRGZ/hq5BPmoxWPEIhJj1nuqayvjVFS9pi10AZVVHY1J6hNW2RTUytCaRrClV3+sSricrMkrTSzSi4edGLXlT//xe/+MXzNRZJWjEURZm0LHGwOC+GWX9RaMtYtKZNan6IEGDp6qST809+8hNe8+pXcY4QfEkIOg/6/fOEoA94e63GK1/xCn7wwx82DHBEJNg1VKEpYdKesfGCiKGyi6VrhELghCFdWZu2tMVAyQVg++oca7XUrB7PQkua+rzmAE1QxoOQIIz49a5h3CDCVFW8KMJQFdY2J8knDaIobpkw0Slcb/B6mFgOXNeaIpcwOKZ9+noxbWmbgWKxYd6VF8QF/GQLBOloMOuvLBs3buSaa65hx44dczKAm2++mQ0bNmDbNqeeeiq//OUvpz32O9/5Di996Utpa2sjm81yxhln8JOf/GROxiFJcyljP71FuZGyG9B6hFtkFUUhaer1SrsTxsbGeOPrX885QvDdKJoS2EzoBL4bRZwjBG98/esZGxubeh9qvKRij9eNKY9vS87aBrauEYTxMvTEDpmhsstI1Zv1Y1nJEqbGtq4sa5tTdGRt0rbBmqYkWztzdOUSKCjjeVHEOTimhn+ItjVOEJKyDp0I3JaxaEoa9Bcd/PDp23L8kIGSQ2fOnvMlOElaimYd3Lz73e/mxz/+Mdu2bePUU0/l05/+NL29vUd053feeSdXXHEFf/u3f8uDDz7IC17wAl72spexZ8+ehsf/4he/4KUvfSl33XUXv/3tbznzzDN51atexYMPPnhE9y9Nwy1BZQiqIxDJ9fkjkbF0OnI2wxW33tsI4ty04XKce/FMklijSDBS8Xi8v8Qf9o7xaG+Rz33hy1SrVb4URYedktWBL0YR1WqV22+/fcr1QghW5xKMVX2KNb++DFYar/jbkop3T0G85KOgUKj6R/x4lgN/vPN4Ybzz+ExYukZbxmJ1U5ItnRlWNyXrO7acIKBUi+vUaGqcNJ4wtHoLiQNVvQBdi/OKhBCMVT12DZZ5pLfIk4NlCjUfIQS2oXFcd5bWtMVwxaNnrMb+QpWS67OuJcmmjvScFiqUpKVq1u0XJjz22GP827/9G9/4xjfYtWsXZ555Jn/1V3/FhRdeOOPbOP300znllFO45ZZb6pdt27aN1772tdxwww0zuo1nPetZnH/++TPuaSXbLxyCW4LhXVAZgMABRYdEHprWQ7ZrsUe37HhBxGP9JfqKDkEYoSkqEREZy+DYjjTtmSMLbsLxnVh7RqpEQmBqKn4Y8faXncEZ+3bzjVm8pc9XFP6wcSOPPP74pCWyB54aoegERJFgoOSwa6BEzY9oy1jkkyZuELGuJVmvTNxfdFjTnGBL58p7TwVhxP6xGr1jDmUvAOIdV6ubEnTnEocNFnYPV3ikt1jfNVf1A/oKDqMVj5IToACnb2xmU0eGYs3nsf4yigIZK04aL7txbtbGtrip6K7BCnvHqvhBvI3cDyMsXWXtAb2mwigOgKpeGN+WPfu+XZK01Mzm/H3EmXSbN2/m+uuvZ8eOHfzyl79kcHCQiy++eMa/73kev/3tbzn77LMnXX722Wdz//33z+g2oiiiVCodsu2D67oUi8VJP1IDXgV6/wiFvWCmILca0q3glaD3D1DsWewRLjumrnJcV5ZT1zaxrSvLMe0ptq/Oc8q6piMObAB6CzV2DVXIJQy6cgla0hZWWGXP3qd4/Sy/q7xeCHY88QQjIyOTLm9Nm3hBSEfW5riuLMevydOZt1nTnCJtGZPq1wghCEU0467jjh9ScvxlsWsnigSPD5R4pLdIEAlakibNSRPPj3hof4Enhyoc7vthRzau0ttbqDFSdXlioEzvWA0/jDA1lXUtScaqAX/aXyBt6Wxfk6M1bVELAqpeQD5pcMLqPBtaU+wfi//2WctgVT5Je8ZmVT5J0tTZOVCid7zWj6YqtKQt1jQnWd2UbNhBfDkou3Exw+Hy5BlQSTqcZ5RZ97//+798/etf584776RQKPCGN7xhxr87NDREGIZ0dHRMuryjo4O+vr4Z3cZNN91EpVLhjW9847TH3HDDDVx//fUzHtdRq9AD1eE4qJn4EFR1SLXFlw8/Ef+/JtfrZ0NVFZpSJk1zVOslCCP2jdZIGtqk4m3VShmId0XNxsTxpVKJlpaW+uVtGZt9Yw6DJZfWtElXNkGhGlCs+fhhRFPKJDu+vDJYdsla5mHr2ZTdgH0jVQZKLn4UYagqrRmTNU3JGQdGC22k6rFv1KE1bU0qfNeUMrE8lT0jFVoz1iHzWGxD47iuLE8OVfj1E0PsGa3SnIoLI3blbNqzNqqi0Fd02D1S5aQ1edrSFm4Q1ZPGVVXBCyL2j9ZIW/qUVhNJU8fxI/aPVunIWEe0A2y6ApGLoeaFPDlUZqDk4vohqqqQsQxWNcXBnFxakw5n1u+Axx57jGuvvZZNmzbxvOc9j4cffpgbb7yR/v5+7rzzzlkP4OA300zfYHfccQfXXXcdd95555QO5Qf68Ic/TKFQqP/s3bt31mNc8UIfSj1gZ58ObA5k58EtQm1soUcmHaTmh1S8YEql3WQq3kEzOsvbmzg+k8lMujxl6WzrzGAbcVPJshOQMDTGah5BFJFLxFvZ949VsQ2NLV1TGz8eqOT4/Hl/gaeGK5iaSlPCxNJV9g7XeGh/kWKDPJOlYKjkokDDir5JU8cNIkYr8W6xKBI4fjgpkXeCqij4QUih5pM0dBShgBIHvxPvuOakyUjVo+gEKIqCbWgkTK1+Ip/o8TVRhPBgGVun5AZUp0lib0QIwVDZ5aH9BX69a4T/2TXM7uHKeD+wxeH4IQ/3FtgzUiVp6HTnk7Slbfww4pHeEntGKos2Nmn5mPXMzdatWznttNO4/PLLedOb3kRn53R7Mg6ttbUVTdOmzNIMDAxMmc052J133snb3vY2vvWtb/F//s//OeSxlmVhWfPYkXgliIL4x5hmqUTVQAiIluYJ6GjTKPTPNzWzYd0Gvr3nKc6bxdLUtxWFLRs3NlzabUlbnLJOZ7jiUXJ81rYkOW1dE34UUXLik9/61iStaateCXg6e0eqFKo+3blE/cuLoakkDI3eosOe4SrHr8od8jb8MKLmh6iKQtLQFuTbe80PD9mWwVBVym7cnbtnrEbNi2cZ2tMWnXmbrG3UT9Z7h6skLI21aRsFhYobsGuwQhgJunIJTF0lCEXD4Ajit6AQjb9/HHjMTAkh2DVY4cmhOFiwDQ1fCB7pLdI7ZrKtK0suufAzaoMll8GSR2f26erLmqqQT5roTsCekRrtWXtBtvRLy9esXx2PPvoomzdvfsZ3bJomp556Kvfccw/nnntu/fJ77rmH17zmNdP+3h133MEll1zCHXfcwSte8YpnPA4JUA3QTAg8MJJTr4+C+BNVm98y+tLhJU2dtKVTcoJJy0CKonDexX/NJ6//CH0w7TbwA/UC3wFueu97p50ttQ2NVfkEs+0kfqCqFzBYcsk3aBaqKApNCZOhskvZDRrOSvhhRM94Qm/FD1CBbMJgdVOS9ow1r0sptqExXJ5+i7sbhvSOVdk/VsXSNJKmThgJnhyqMFB2Oa4rS8UNGCi5dOUTFJwAP4hImDrZhEHZDegvxgX+VCXeGm6ojYOppKWRsDTKTkC2wTLYxPM3XYXigw2VPZ4cqpCxJ9f+yScMBkoujw+UOHlt04IW/RNC0Fd0SBhaw/tNWRq9RZ+xqi+DG+mQZr0sNReBzYSrrrqKL33pS9x666088sgjXHnllezZs4dLL70UiJeUDtx9dccdd3DhhRdy00038ZznPIe+vj76+vooFApzNqajkqZDdlW8W6rR1u/qCCSaITHbjA5prmmqwqqmJG4QTlk6OOe152PZCd6uqhxuUSEA3qGqJJPJQ+5wLDo+Tw3FW46fGCiPbwmfXdKyHwj8UEzbrNEy1PiYBgmjwXgDz4mE3qaEScY2KNYC/rSvwL7Rxj3u5kpr2kIgGiaz1ryQqhdSckPa0nHScMLUSNs63fkErheyc6DE3pEqKSMOIJqScUAz8RymTI2aF1B2AkYrHi0pk0yD5p4QL41152xKrj9lPI4fvx66c/aMG4D2FePn7uAgQVEUWlImo1WP0QWuXSQE47vAGgdUihIv44XREW3ylY4isw59wzDkU5/6FN/85jfZs2cPnjf5xX/wrotDOf/88xkeHubv//7v6e3t5fjjj+euu+5i3bp1APT29k6qefP5z3+eIAi4/PLLufzyy+uXX3TRRXzlK1+Z7UORDpTthuoQFPfHOTZGIp6xqY2BbkHLsfHylLTourI2jheyZ6TCWM1DV+PlDM1M8ukvf413veU8XquqfDGKaLSBv5c4sPmJovDD73ynYY8pIQS7hys8NVTFCeKqukEkeHJYYU1TkmPaUjNOWtU0BV1V8MMIrcFryA8jdC1uHXCw4YrH/tEq7ZnJJ20rrVGo+Tw1XKF1PKiYD80pk1X5BHtGqmQso778VnJ8Kl6AoSpkE0bDgKJ5vFGlQKl3TW/P2pSdgKGKS9YyMHSVIIx7R3XnE6xtPnSy7JrmJI4fL4MpjD+vUYSCwobWNKuaGsy8NhBGglItIDnN86ZrKlHEgu9oU1WFhKkxVvXJNLg+EgIBc9rBXVqZZh3cXH/99XzpS1/iqquu4pprruFv//Zveeqpp/jud78741ozB7rsssu47LLLGl53cMBy3333zfr2pRkybOg8IQ5sij3xbI2qxfVtcmsh1XLYm5CmF0WCqh/WC609kw9nVVXY2JaiNWMxUnap+SGWrtGcMnnJ1teypvmHvPH1r2dttcrriLd713tLKQrfAZKJBD/8znemlGKY0Fd0eKy/TNY2aDmgGaXjhzw1XMbUFDa0Td8G4EApU6M5bdJfcOnMTT2ZjlZ92jNWwyWpvoKDrqkNn6+srdNbdBipeqwy56fLtaYqbOqIk6V7Cw5D5Th5OG3pbO5Is3ekNu2MlK6p9TYcrh8nAicNjfVtKfaOVOkrOPhBRNUP2NyZ4fhVucPuODM0lS2dWdqzNoMlF9ePSJgqrWmLpqQ54zwkhXgW5FAzIEIRi7IrqTNnxzvqwmjK371Q9UlbOk2ppbm7Tlo6Zh3c/Nu//Rtf/OIXecUrXsH111/PBRdcwDHHHMP27dv59a9/zXvf+975GKe0EIwEtG2GpnXjRfy0uObNEtkeuhwJIRgsuewfq1Go+kQIkqZOd86mO5844qaNyni/oUZbkM855xx279vH7bffzs3//M9884kn6tdt2biRm977Xi666CJyucYJvFEk2D9aw9TUKYnCtqGRNg32Fxy6mxLTntgPHuva5iTFmk9f0aE5GTfU9IKI0ao3XoAu2TB3ZiJwm+52GV/GOJgbhAyXPQZLLl4YkbI0OjI2zSlz1jk6hqaysS3NqqZEfSYjZemoikJ/wSOYJkCId35CZy7B7uEyJcenUAsYKjs4foSiCoJAkDD1eFfUDId1uA7oM6GqCu0Zi8cHSg1fQ44fYmnqtEtk86ktbbEqn2DfaJXUeC+wSAiKNR9Vhc1tuRm97qSj26xfuX19fZxwwgkApNPper7LK1/5Sq655pq5HZ20OHQr/pGesf1jNR7tLaEqChlbR1PjXTIP9xYpuwFbOrPzkrCZz+d573vfy3ve8x5GRkYolUpkMhmam5sPe3KvjhfZm672TNrW6Ss4VNzpA48p40maPKs7x+7hCsNVjzAUaJpCS9pkXUtq2jpAlq5S86bfpScUMWU5q+oFPNJbZLAUN/rUVYWxqkfPqMP61iQbW4+sBYGla1Meb3vW4rGBUsPqv2U3qOfZ/GlfwP7RGkEUxSdpRUEA7RmT7atz1LyIh3qKbF+dW7CaP+1Zi96iw0DJoSX1dJ8zxw8Zrnisa0mQOcwuuPmgaypbOjNkbJ3egkPR8VAUhdaMxaqmxDMK6qSjx6xfuatXr6a3t5e1a9dy7LHHcvfdd3PKKafwm9/8Rm65lqQDxIXIKtiGNunbcT5pkjR19o3WaE1btGePvFrx4SiKQktLy6QCfTMhAKXhpvOJJQ1mnVjclDLJJw2KTtxOQNdUMpZ+yEAjXqJwCCMxJQgsuwEJXSOffDowEkKwc6DMYMmdtJUYxv8egxXSlkHnM+jrdfD4Bksu/eMBgqGpCCEoOQFl12dDa4regkN7Jm5Y+bvdo9iGhq1rqJqCoWskzHgGbv9Ylf6is2DBTcY2OK4ry+P9JfqLNVDiJp6mrrC2JcExbZlFK+pnaCrrWlJxYnYQoSqQMLQlU2RQWvpmHdyce+65/OxnP+P000/nfe97HxdccAFf/vKX2bNnD1deeeV8jFGSlqWRqkfFDelucCI1dRVtvCrtfAY3R8LWVdKWTsUNMPWpMyoVNyRhaoetbdOIoihYuoobhIT+eN8ja/qeR61pi85sgt5CjXzCJGlqRCJO6K35Ice2pyfl6hSduFz/gTMRExKmRtmNixJ2ZOdmC3nK0tnWneWJgTIjFY/wgF1QW7uymJrKk8NVOnM2IxWXjvGu3KoCpq4xVPIYrXjkEgZpy2Cg6LKhNb1g26+bUyanrGtitOLFS2VKvM1+qfShMqbJt5Kkw5n1p9ONN95Y//83vOENrFmzhv/+7//m2GOP5dWvfvWcDk6SljM/iOqJm41YhkZ1CfZX0jWV7nyCh3qKJPxwUuVhP4woOD7HtqcOWZF4ghdEjNW8euJqseYzUHKpeiFRJDA0hc5cgmPa0g13PBnjSxQJQ6Ov6FAo+PUlvvWtTzfunFDzQoJQTDu2lKVRcgLcIJrR+GcilzA4aU2eQs2vzzJkEwa2ofHUUAVEXKE4Is6XSRhPf+we2AVcVxWCKCISAm2aWbP5YGjqkguwJemZesYLqqeffjqnn376XIxFklYUTVWIN6425ocRaWtp7vroyiWouiF7RqrjSb8aXhghhGB1U4K1zanD3kZvocZTg1WKjocA+sYcSm5AV87G0hUKTogXRHHBu6LDc49twTamfiTZhsbmzgxrmpPU/BCFOO+n0Tf6OMf4EDuAxiv8zvWkxEQPsSmXK0+/BixNRVUUwihCGy/UFwqBOb49vuaH5JMGeoNZm5oX4oxXZ06P525JkjS9WQc3N9xwAx0dHVxyySWTLr/11lsZHBzkgx/84JwNTpKWs6aUiW1oVNxgyhJOGAm8MKQj16iax+LTVIVj29O0ZiwGSw41L8I0FNrS8Y6jw51c+4sOD/cWMRSVjmwCxw/ZN1rDDUIe3DNKa8aiLW1j6SoVL+KB3aNkbJ1nb5g+NyhhaoetZzPRVLLRcw5xnk4cXMW3E0aCkuMTRAJTVw+5RHYksgkdXYt3hqVtg4ytM1bzaR7PE3L9kO68jRvEPam6DmhPAXFy757hKn1FB7e+bKSzpjlJZ9ZeEktHkrQUzXox8/Of/zxbt26dcvmznvUs/uVf/mVOBiVJK0Ha0lnTlKRQ8yjUfMJIIISg4gb0FWt0ZhO0pJZuEr6qKjSnTLZ0ZjlpbZ7junK0ZabmshwsjAR7RqpoxLMZmqpQcgNcPyQQEI3PniTNuF1BW9omben8Yd8oheoz61+WsnS6cwnGah7OAQ0khRCMVj10VaErH9fE6S86/Hb3CA88Ncpvd4/y26dG+NP+wpw28czaBp1Zm8GyQxBGrGlKYhsa/UWHvaM1DE0hEoKRisfa5iRtmadfD14Q8WhvkV2D5fGlI4uWlEnVDfnz/iL7RqtzNk5JWmmOaCt4V9fUuqdtbW309vbOyaAkaaXY0JrC1BX2jcRbbiFuN7C+JcX61hSmvrySJctu3Cag6gVxd++USS4xuWdU2QkoHDA7ARCGERU/xPVDWlIWFSfEDcL6MlTGMhiruQyWnWfcrHF9a4ogiugZL7qnqyqhiEhbOpu6MnHl4ILDQ70FNOJWA7qm4vghfQWHqhdy/KrctN23Z0NVFTZ1xMUOB0oOXiDI2DpRKEgIQVdTgvaMRVcuMSVwHCg59BUdOnNP7/pSNYWWtEWh5rN7uEpbxp6z3CFJWklm/e6dSCDesGHDpMv/+7//m+7u7jkbmCStBKqqsKY5RUc2Ue8plBifsVhOhBDsG62ya6hCzQvjgCGKa9Wszic4tj1dL0gYCUEUiUm5I6au4fkBCnGbBScQHFj7zg1CcglzTmZNDE1la2eW7lySsZoXJxibGs1Jk4Sp4YcRTw1X0BV1UkVg29DozNrsH6vRO1ZjU8fcLBlausazurOsqSXrj882NLJ2vA1eV5Upy0tCCPoKDrbeuIFk1tbpLdQYrXp05eanOrMkLWez/oR9+9vfzhVXXIHv+5x11lkA/OxnP+MDH/gAV1999ZwPUJJWAlNXaW6wrXq5GCy57OgrkzA0VuUnt2PYPVzB0FSOaY9nKExdjYvv+WE9iEuYKigKI2UXUCZt8fWCCEFcd0VT5mYmS1EUckmj4SxQseZTcnza0lN3CE1Ufu4vuaxrmbuZtUONp5FIxM/LIaszKxCEsoGkJDUy6+DmAx/4ACMjI1x22WX1ppm2bfPBD36QD3/4w3M+QEmSFpcQgp6xWr0GyoHiGQiTnkKNVU0JbCOuf9OWtdgzXMUyVIYrHv1jDkLAQMmjt+CwriVFxQ1QFAUvCOnM2Ri6MinnZL4E47lP0+UOGZpK1QsWtfO0qsTLl6VaQLrBx/REAUVZA0aSGpt1cKMoCv/4j//INddcwyOPPEIikWDTpk2yOrF01AvCiIobIojrrCyXXAg/jOgvOPQUakSRoCllsq45hT2+M8nxIwo1n+w0lXNTlkZvwaPkBPXHvL4lRdUNeainyFDJJWFqrMolqTgBYzWfYHxpaGNbmvWtKcJQ0Ja2aEnPbHYrCCNCITBUtWGFYyEExVpA2QsASJs62US8E8rUVFRFbdiYEcANIkxNa9ilfKEoSlz/Z7A0Vq/mfKBCzSdlGeSfYX6SJK1UR7zwn06nefaznz2XY5GkGSm7AcNll7Gqj6JASzreRbJYwYQQgt6Cw77RKsVagBDxMkxH1mZtS3JJNfkbq8bNJMdqPgqQMFQe6y+xe6QabzVGQSiC7lyCF21pZ01TvPOoUPPHS/PHtVoOpIwXjjmwvkzS1NnckWHPcKXek8nUVF6wqY2y6zNajYv5hVFcu6U9b7GpI3PY56riBvQVHHoLNSpegKlrrGtOsqY5WQ9Ual7I4wMlBstxZ2mIZzja0hab2jNkE3FQMFrxyCaMeiFF21CxdI2y67O1M7PosyITica9hRpZ2yBp6oSRoOjEO++2dWeXTQAtSQtt1sFNpVLhxhtv5Gc/+xkDAwNE0eSOvLt27ZqzwUnSwQaKDjv6S1TcAFuPS/H3jNXIJ022dWUbdjieb3tGqjzWX8LUNFpSJqqqUHVDdg6UqXohx3VnF/1ECbB3pMoTA2XcICJparhBxE92DdFfctjamWNNUwpVUXCDkH2jVb73u32csDpPICL2jlbxwojuXIKuXIKmA3ZCVb0AW1dJHZQk7Y7XdlnfGufiqIoSFzYUgooXMlRyCYXghNU52tLWYZtZFh2fh3uKPDVcoerGu60cL+T3e0bZ3JHhhZvbSBgaO/qK9BYd2tJWPVhyg5D9Y/HM1PGrcqxuSvB4f4k/9YyhKWo9+VnXFE5YladzCSTpGprK1q4MaUuntxjv/FLVuCLymqbkiqoqHEbxVv3hsovjx6/P1rRFPmnIWj7SETmihOL//M//5C1veQtdXV3yhSctmJLj82hfCSGYVHZfCMFAyWVHX4mT1+ZnHEiEkaBQ8/GCCFWFfMKcdQJp1Qt4arhCytQnNTxM2zq2oY73jrIWfUfLWNVj58B4ADbeVbm/UIs7Vxvx7IUYL99r6RqduQS/emKIUMDzN7WyrTPHjr4ioxWfmheysS1NU9IkCCNGqx7rWpJTiuZF0+SFKIpC2tLRVYWqF8S9lg4T2ESRYNdAmT0jFSpOnKvTkrLQ0goVL+CP+8ZQFYVnrcoyUHLpOqhppqVrdGUTDJQchkouI1UPU1fpyCRwgzDe4SVAV+MAp1GV4CNRdnxKToCuKWQTxqxn8Sxd45j2NKubEzh+3NohZR662ehy44cRj/eX2D/mxLvpVIW+YsTukSrrmpMc03ZkXdylo9usg5sf/ehH/PCHP+R5z3vefIxHkqY1NN6TaFV+cqCgKAqtaYv+Yo2RikfHDL7RjlQ8dg2WGa368UlYCDK2wbrWFN25mVd+Ha361LyI5vzUnDNdUzE1lb6Cs+jBzUDRxQsFremnA7D+kkMQQXfOougElN2QXCIORMaqHsZ47RdVUWhJm6xtTtZnEEIRsbYpRSQEXbkEG8ZnZw5kjrcbmC63xfFDLEObUSBRdHz6ig5VN25dcOAMXcY26MwmeHygjKmpKOMzRAfTxrdcPzlcoeKGrG9JY4438QzG+1ypKAyW4+CnPXPkMyNjVY/f7xljR1+Jmh+gKSpdTTbHd2U5tiMzJYfmcCxdQ1OUuFv7eEd2IVgRJ/09w1X2jFRpS9uTvlzUvJAnBsskLX3Ke16SDmfWwU1TUxPNzc3zMRZJOqThikdymhyDiRNX2QnoyB76dgpVn4d7Crh+ROt4AbdICIq1eNkDmPGHaRDG36anEwcIcU+mhZzlLNR8hkouo1UPRYH9ozWS1uTnLhKAEPU+R14QAgZeGFJ0fFKmRiQEYSQwNJU1zUlySZOhkkt/qUbaMtjYnqI5ZTYMXnIJg6aU0TDgDKN4aeq4luSMTvRuEFFy4lm2lgY9nBKmRsUL2D9Wpbsp2eAWYrqqMFb10FS1fiK1dI0DQ1NVURgqu0cc3BSqHvc81MfOwQotaYuObAIviNg7UqO/6OCEIdtXNc04MBmrevQVHIYrHjU/JBzPI8pYBtmkQUfWpjVtLstZdMcP6zlFB8+aJkyNpK+zf7RKZ9aW/bSkWZl1IsA//MM/8NGPfpRqVZb+lhaWqnKIloixmXy+7y9UqXoh7Vm7fmJVFYV80sTSVfYOV+uJqIejaypxjNB4ZF4QkTDUBT3x9BZq/H7PKI8PlKi6IWUnZM9ohcf7y5OK5GWTBgLwo7A+IwBx4BFFAi+IyNhGPXCZqAFzTHua9a1pNnWm6cja0y4DqqrCxtY0tqnRM74E5vhhfLIuOnTl7BnntqiKQhAKBKJhUBBGAktX67NN03GDEENTD3mi1FUFPziybeBCCH795DAP7htDAaquH+ckmSprm5KICP64r8ho1ZvR7fUXHf6wd4w9I9W4kelQhT/sK/BoX4meQo2esRp/2DvGrsHKtK/BpazqhVS9cNpq0Glbp+wGVMd3vUnSTM165uamm27iiSeeoKOjg/Xr12MYkxM4f/e7383Z4CTpQC0pi4FiEZj6zX2iJknaPvRL2vFDhsvetNuas7bBQMmhWPPruSmH0pw0SRgaJSeYUgPGDyO8MFrQ5NSi4/NYXwlVUSblJR3bmuGP+wvsHq6wpTODqWl0ZW2aUxa9Yw7ZhF5vhaCpClUv7gO1oSU1JRCIAwRlRrlNTSmT7atz9IzWGCq7uEG8TX5bS5LOnD3jHKdsQiebMOgvukRCTNmxVfECUqZGR85GRaFQ86cklxdqPglToy0d1+CZjhtEpKwj24W0o7/E/Y8PUXNCMqZBxQ0ZqwWkTZ2uvE0+aTJccekt1A77+nL8kMcHyoBCe9ZmR1+RCDi2LY0bRBQcn65cAl1TeHKoQiahP6OltMUkgEbh5jKM16QlYtbBzWtf+9p5GIYkHV5r2iJjGwyW3EnT8GEk6C85tKbNSf2MGplYZkkYjb+5a2qc1xDO8FM1YWpsaE3yaF8ZP4zIJgxURaHiBhRdn1X5xIxrt8yFwaJLzQ8nBTYAzSmLzpzNvtEanVmbtoxGwtA5cXWWex8dYLTq01KLe0ZV3LhNwqq8TWd+6slyrOrTlrHIHiaQnJC1DbJdRpy4G4GhKUeUc7KtK8OugTIDRYeO8Y7YYRSf5C1dJWHqHNuWRtNUHusr0lcMSJtxgFP2fHRVYXNnlqytM1ByKTn+pCRwiBPEDT3O4TqY44f1woMpS5uSHDxW9djRWyKIBC0Zs55gLYgT1/sKTn25s+QcfiZiuOJRdny6cwkKTlxVOZ+IX/e2ocV9vqoe61pSlJx4i/xyC25SlkbS0ik3+HIAcdmHzPg2eEmajVm/Yq699tr5GIckHVbK0tnameGxvjK9hRq6qhIBURTRkrHY0pk97EnT0FRsXcPxG5e2d4MQXVOwtKnXRZHACyNURZk047C6KYmhaewbrTJa8xBRHPRsbs9Mqr+yEEarHklj6ts6YWoc05qmWPXZO1Idr9ILlqHziu1dhJFg/1iNUAg2tqU4a1s7VS9ksOyST8TLdX4YMVbzSVs661tSs15qe6b1fta3pDnj2BZ+9cQwu4bKJE0tnkHSNdKmwbqWeHu0bWgkDI2+Yo3RSrwMt6opQWc2Ue8ltbE1xWP9ZWp+vCSioFB2A0IRcUxbetKsjxdE7Bmp0FtwqLohijLRfdxm7QEzW4Mll0AIskmDqvv00piCQtY2KDo+hVqcwD6Tppw1L05EVhQF14+IIur5UfHzqVJx4yApZcYBQhhNX3l5KbJ0je6cHZdS0NVJdXuqXoAbhGzqSC+rxyQtDUccDv/2t7/lkUceQVEUjjvuOE4++eS5HJckNdSStjh5nc5wxaNY89EUhXzSoGmapNaDGZpKV97mkd4SKVObFAwJIerJr9nE02+NMBL0Fx16xmpUvRBVVWhNmXTlEuTG63B05mzaMhYVL0BEYJvqohTvU9Wnt2AfLJsw2NiWojVj0ZqOO1BnbIP8+FZsL4iIhKjnpFS9gH0jNfpLDrVagKYqrGlKsKopuSj1hFRV4bT1LeNLNCXGqn68kytl0JVPsLY5VT85NqdMmlPxVnVgStC7pjmJbWr0jjmM1TxcL8TQVdbkk5N2y4WR4LH+EvtGa+Rsg65cnKdUdgIeGyjhh4JNHWkURWG44tGWsiikfB6vFPGCEHP8NaAqCkLAUNmlK2+z6hBJzxM0Ran/LRUVxEHn94nGpRDPNGqqMmlpxw8jRseTkFUlDrAmqjQvJWubk3EdolGHkaqHoar4UZwbdUxbms4VVM9HWjizDm4GBgZ405vexH333Uc+n0cIQaFQ4Mwzz+Qb3/gGbW1t8zFOSaqzDY1V+cQRbw/tyiUYq/r0FhySpoatx52iS2487b+hLTXp5Pb4eAVfS1NJmBpRBLtHqgyUXI7rztaXMDRVmTaXZ7aiSDBW83H8eKYgaxtT6sg00pa2GSgWGu7OCsIIQ1fZ0Jpu2MPp4PyXpKmzuTPD2pYkfhihq/HjX2xrm1OszicpewFRJLB0bdpxTTeTpygK7RmbrK2zo6/EYCBwg4g9I1WGKh7dOZt1LSmGKy49YzXaM9bTidXEgaKpq+wdq9KetcgnzTiwUGBDW5LBisNA2SVnGyQtjTASDJYdWlMWJ67Ok59BcJhPmmjjQWfK1LFUFccLUNR4Oa7mh6xrSQFQdn02tWfqydajFY/H+kuMVb24erQQGLpKZ9bm2Pb0kqqarWsqWzqydGYTDFdcvCDCNjRaUtaSDMak5WHWwc173vMeisUiDz30ENu2bQPg4Ycf5qKLLuK9730vd9xxx5wPUpIa8mtQGQK3FH+1TTRBsgW0Q7+sTV1lW1eW5pTJ/rEatSBAV1WObU/TmUtMWjIYKrvsGanSkjKxNAXVK6JGHjlTo9+z2DlQJpcw5nTpqVDzeWKgzEjFIxQRiDig684n2NCaOuTSW2vaIp8wGSi5tKat8Zoo8dLdYMWlI2PTNMt+REuxT5Y6B4GkH0bs6CvTW3DIJ+IcmUgIyk7A/8/enwdLlp/lnfjn7Fvuefdbe3dXVe8tWQhbAo/BCBCCkQnNDHZMwAgbxciAwSyBYQS2mbCDGY8HNGYZMGMDxh5E/LDMEFhoEBLCg0AISYhudVdvtdfdb+6ZZ19+f7x5t7r3VtfaW+UTcaOqcjnnmyez7vfJ933e53lpfUCaFSR5hqIcLJ62DY3WKKIziqm5JjNlixfWhizWHL7iRINzK31WugHdMKYoZHT76x6Z4aljNzcGXnUMFmo2V9o+DdfCMlReWBuS5zlBklNzDAZhTJxmlB2D2apUOIZRynMrfcI4Y3aXmWGUZlxt+yjAw/OV1xVpUFWFumdSP2DMf4IJbge3TG4+/vGP8wd/8AfbxAbgkUce4ed//uf5+q//+ru6uAkmOBTDDVh/DsI+aNrOWIU3DbOPgund8OmmLr4tCzWHJMvR1IM3sNVeiKYqONkQq30BLWihFKKnOGKUWR7N0mm6zNyliSg/Tjm30mcQJjS9nWrBKEo5vzGkKOD0XPnQ5zumxtn5Mn95tcvTSx16fkJWSIbUg9MlHpgp3bKY982K9khG0mfLey0BKmOyeq3rY2qSiXUYDFUlTKX1NV2xWeqFbAwimiWLdz4wTS+IGUQJnZHkVf2V442b9rdRVYUHZ8ooCrywOuRaJ8CPEvICTE1BVeDZ5T7Hmx5vOV7fJuUb/ZBBmO6rbFq6VENW+yGLNZfqJHRzgjcxbpnc5Hm+b/wbwDCMfTlTE0xwTxANYO3LkMVQXdwxaMlTGKxKFWfhLaC+crVBUxW0Qx6X5YVMaxQBzuY51HRIajcoNBOKDC3qU+4/T9otQ/Whu/LS1vshXT9moers+WbtWTqKAsu9gPmavW/KZzcURRHRs6YxV9XQVPl3nBcsdQIemtVvSaC5lfvT3xbDijnfnbY2wiRjcxix1g9Js4KyozNbtml4r44h3fogRFcPntxyTI22H0FRkN1gcC7JCxxDnl+ydB4eC95X+wGqolIU0jZ7fNHlzFzllhyFtz5/WxWqY02XRxYqXG35rPZChnGGZ6gS8RAkzFZsiqJgbRDhHdKmk2pTTD9MJuRmgjc1bpncfO3Xfi3f//3fz2/8xm+wsLAAwNLSEj/wAz/A3/ybf/OuL3CCCfZhuA7xEKpH9t6u6lCek/v9NpTuTP+lKmPn4+ESatwnKc3vEClFI7PrZMMYo38ZshOg3dlmURQFq/0I1zxYZ+CaOp0gph+mh5KbPC94eX1AlOY8cl3rIUozrrR9qq5x03EQQZzxwmqfjWFEXoCKQlYU1FyD07Pl7emjW8UgTDi30qc9SrB1FV1TWeoELHdCjjddaq5BmOQoytiJ9x5oL6Lk4FiILWiqStnW6QViPnh9a07CW1Uau8bGtwTvHT9mGKaoikLVNaiP9TM3i614kK6f0PXl71XH5LllqerZuoahqfTDjLVBnzjL+c6qjWfpFDn7fIB24/XTjJpggnuHWyY3P/dzP8d73/teTpw4wdGjR1EUhStXrvD444/z7//9v78Xa5xggr0YroNxyLSJqkOeQTwA7ozcKIrCnKewfnGNrFTZZ38cxhmqW6VU+BB075hMiTamuGHWkoI85jB0A2mBHFT9sMYb4ko3ZK7yyvlZW5NCq33xT9kiAnlRsDmMOLfS56mjtZsSOu9GnhecX5dcr/mqvb0RVx2DjUHIHzy3xlTFpGIbFIW0EOcqNg/cZSGsa2l0/WTPbWGakmagKdIiPF53KdsGl1o+rqFRsnWKQshZnOU8NFPap/2xDU3IY/X21rU7HqThmagqbAx1Xt4Ycq094uH5CjV3h1C1/ZCXN4Z86WqHr3pohqqrs9wND/SNyfICRQHLmLQmJ3hz45bJzdGjR/niF7/IJz7xCZ5//nmKouCRRx7h677u6+7F+iaYYD+K/MY5Cwp3zdp0tmQQmAqbYUZFL9A1BQqpaAzjlKN1F0eLpCV2h1BVBc/S2RxEB1ZmsryAQvxNDkOYZGTjce6D4I4zmJKswNRvTG66fsx6P9pDbECqAjNlm6Wuz+YwOpTchEm2rWfabcLWDRI2hzHTJWtPhSFMMtb6EaMoZaqwWKi627dfbvnkBTwyf2utnRthpmyz1AkJEwnOXOuHdEcRnSChNYxQxqPYR+suc1VLoiOCGAUJ6xTvnNsfUx5F6fb1KVk7lamlrsSDbFXXNEXBj7JtE79hlFFxdlyabcPA1HIubvi89XjKTMVmpRcyitI9700xJqV175XNLieY4I2O2/a5ede73sW73vWuu7mWCSa4OXjTsPmiTEddjzwVzY25P6X6duDYDsdm66y0+rTCZNt3xNY1jjVc5ks6BBrorxzVcDOYr9qsD8ID2yCtUUTVlYmSoihIc9ngdrc7ZMMrDg3qzMbPeSV+sKXdGIQJNU/HOCCGzjV0NgbR9jjyFnb748RZjj5ObT9SFxFrkGRkxf6WUDdI6AcJc1WbMM1Jcxk/tw2NmbLNaj/kSN2hdpc25oZrcrzh8uxyj9V+SJ4XBEnKSjcizjLKls5yJ0BTFBxT59S0y0xZKl6Ood22sdwgTLjcEmKYpAW6Jg7SRxsurqmxOYwp2zpBIoTZtTQKxPV6seYQJBlhmuMaGjkFYZyxULXp+DFBnNH0TB6Y9nh5Y8QgSnAMmQLz45SaY3J65tZTySeY4I2GmyY3n/rUp/je7/1ePvvZz1Kp7I1d7vV6vOMd7+AXf/EX+eqv/uq7vsgJJtiD0gz0roiuxt2VUF/k0rJymjISfjeg6XhTxzkVP82s7RHlijjUmjq2ocJgBbwm2LW7crqpksXxhsel1ghdVXFNbVtY6lkS9bA5FO+VIMnRFIW5isVMRfQWFUfHMXRGh4QR9oOYB6acG7a+2qOYq22f55a7XO2E9KOEumsyX7VxdrkfK8pOptcW/Djl2eU+m2NnY8/USbKcpW5AJ0h4bKEy1nzsP39nGGMZGihiRrf7EaaukmY5/SC9a+RGVRVOTXtcaY9Y7hXkRcGFTZ80y7F1mcC7uOETJjlnZstcaflMl23Kt9iG241BmPDscp9ekFB3TCxXnJ/XBxG9INl+f4MkJUkkKNQxNUxdGROUjLwQ8hpnOaMopWRLuyxMcxQUFEXheNOjbBusDUJ6foqpqhxvukyXrUmUwQT3BW76U/7hD3+YD3zgA/uIDUC1WuV//B//R376p396Qm4muPdwajDzCKw/D92rYDhCbNJYyM7sw6/odXNLqCyg+i3K/WXKVlnOl/vQ60mFqPmQWAPfJKI0ozNKiNJsW3BaHrclZPy3RNU1WOlKkraqyCbcLJms9kKudgIsTSoaaV7wwuqAtbGhYMU2WKw5vLQ+RIHttkSeRAw2l5hP1lgwDIgdqCxCaRaMndZKaxjx7HKfKM1peja9IMNQFVZ7IX6U8sBMaZvg+HHGXHVvW2ZpHJC5UHW22yaGpuKaOqv9kIubIx6Y9rA0lSDO9pjvZRSoY63LQtXZEzUAUpXK7vJEZpBkaKrC2dkyn73QpjuKcQyVXFXx0wJTU+iMYq52faqOSWd0eOjqzeBax983DWfpGrNllSttnz99ucXVro+ta0yVLRTGIabjhPYwSSlQGEYJnqHT8EymyyZL3ZATzZ3xbkVRaJYsmiXr0CreBBO8mXHTO8Bf/uVf8r/+r//rofd//dd/Pf/yX/7Lu7KoCSZ4RVQWhFiMNiFoSyvKm5Yf4y7btesWzD0OTgP618amgTrUT8jEllO76UOtD0JeXhsyGGcCFXmBZags1lxOTYtBn6oqzFZsZsoWSSYbvq6pLHUDrnZ8pry9adoVW2dtEHJhfcgTR2qcmPIokKyoXi9BzWLczjma2QaL0008y4DEh5W/hPIszD4OpkueF1xqjUjSnLmKTZrltPyYUZgy5ZlsjmI2BhHHGjq9IMEy1D1BjVGasdYPqdnmgdM6Ddek7cecKkrMVW0utXymVHNbJOyZGi91A5olk6a3t82XFwV5Ac5drjokWUE/TOkHCRvDCNfUmK044/tyhnGCremoikJnFNEPklc44uEIk4yNQbwdfrmFXpCw3g9Z7gW8uN6n6ViEWk7Ds7ANlaqjYuoK64OQjWHMbNXioekSpqFhahrr/RBVhccXawe2yibEZoL7ETf9m2Jtbe1Af5vtA+k6Gxsbd2VRE0xwU7Ar8sOpe38u3YLmKagdFX8dRbtlEtX1Y86t9ClymKvsTAkFccaFzSGqCg/O7Bj0KYqyLfrN84LlboClaftiEhRFoelZbA5jaXd4Jg/OlJmvOlxu+fSvXUT3V/GrC6xnNllmUXfL0krrL4Phwdxj9MOdSSsQQnWi4XGxNaI1isnzgsutESAVoYdmy3u8UpKsIMlyXOfgXyumrpKmOXGWc2q6RF4UrPRDkjRCVRSSLMfSVWbKFqXrEsdbwxhDU0jznI1BRNnW74prsq4pDMOU9ihC11SMXdNYhqZiaRpBKtWrrp8SptkNjnZjJFlOkud72oUdP+bCxog0y1EK0AqVZtlivR9ybqXH8aYnzsk5eLaBbWh4lsHmKEZRIElzaq7F33hw5obmjhNMcL/hpsnN4uIizzzzDA8++OCB9z/99NPMz8/ftYVNMMHrEppx2342y72AKMn3ecw4pka1MFnuhizUnAM1EXGW48fpoXoJQ1PJC8lH2kI3SFjv9CiPVrFLdTLdoDWMafsxxxquTPq4DRiuQXySJNP3TVqVbJ2HZkrb1YVhlHCs4XKs6e0Lz9RVBU1VidOD/WNkMkjF0JTtCIyFmkM/SMnyHMtQGYYpVzsBa33J/coLaI8i+mFKxdZ5drkPRYFn6SzWnD2p3LcDz5BzJHmBbagEEWRFjqbI+rPxaH6c5+N079vX+xiairHr+gzDlL+82qE1TPAsjZ6fUChQd02myxYXN0b4cYamSpDpA1MljjYcTk6XuNzyiZKMqqtzslna47UzwQQT3AK5+aZv+ib+8T/+x7z73e/Gtvd+Yw2CgH/yT/4J3/zN33zXFzjBBG8GxGlOexgfar7nmRor/ZhBeDCBURUFTVH2CXi3UBQFBWxPQQ2jlJfXB1ikNKyC1C6DKgGTfpRyrRNQsnVKhgthF5IQQyujjSsou8nJVraUZ+pkRc7pufKBfjMy1WRxueXjmtq+dkjXT6i5xvY1UBSFmmvuEQgXRUGjZI2dmhPyIgcKPFO8Y2xDoyhEYP3C2pA0L3ho9g4qForCdNlkGCa0i1gqOVGGoeVkmRA9VYH2MGa+ZjNdun1ys3V9LrWkUvPl5T6XNn2aJZMsh81RRDIWCU+XbRZqost5aKaEqau0RjHNskydHbmJVPEJJrifcdPk5sd//Mf56Ec/yunTp/ne7/1ezpw5g6IonDt3jp//+Z8nyzI+9KEP3cu1TjDB6xt5JsJmVd/nw1MgmhHjkCKDMvYyubAx5ErbR1VkcmprusXUVaZKFpfb/r6WDcAgTPFMbdu4rTWMCOKMKdeEvoJSZBTj/+7u2EunO0ooVQFUUCSIsuYadPx4j5YGhHR0g/gVE6UX6w7tUczaQMIobUMS17t+gqpIhMCNKi3KeGx8qmRJK64X8OxSb08ApKIolG0DTVVY6gTMVW8cR3EjaKrCfNUhjCV9/YW1AWT59iSaq8vkVt01eHShesNJrTwv6IcJcZqjqsqBgapHGjIN9RdXuvhxQsk2MHWNIE6Zq9gM44zlbohr6ZiaSrSrClYUxXYC/QQTTHBj3DS5mZ2d5U/+5E/4+3//7/NjP/ZjFGO/D0VR+IZv+AZ+4Rd+gdnZ2Xu20AkmeN0i7Eum1XAV8hyssmReeTPbU1SmJlb+XT85sDKz3PW50h5RUDBVsikK2Bj2WeoYPDxfoe6ZzNccNocR64OQpmehqQpFUTCKMoZRwpm5suhQ8hzfH2EqGblRIrPqaGGL1J3ZPp+hqfhxBqEPdhUsMcc7MeXx7HJPhMGubM5hktH1RcuzULtxbEPZNnh0scqlzRHtUUTbj9FUhZpjcLzpMV2++c1ZVRXW+iGWfrCnjGtKzEHXT26b3MCOt9Cj5QqepbMxjLB0BUNVaI9SHEPj0cUap2fLhxoI9vyEi5tDNkexuAADFdvgaNNlobrjBl2ydBZqDi+s9inQ2RwGGCpUHINmyaTnJ1zYHLHeC5kqW2iqTHQNo4QjdXef0DpMMvpBQjbOsKo6xh216SaY4M2CWxo9OH78OB/72MfodDq8/PLLFEXBQw89RL1+gJnaBBPcDxi1YPUZybqyPAnr9DdEx9I4BVOnQVVRFKkQbAyifQZ9/TDh2eUeTc/mweny9kZYFAZrvZA/v9Tm+LjiUfdMOsOY9UFIIQ/CMUXce6xqyWh87xql9RaVQYKVHSGzqmhhBy3skFlVUFSyLMdMe5CqMH12e3R+qmTx2EKVq22fth+TZWDqCkcbom+5maiFqmPw+GKFlX7IIEjRVYW5qk3pBgQkH8cCXN/KSrLihoZzCoe36m4WUyWLE03xFpoqW5QsMSccRCl1z+Stx2ucmascOgI+GL9/fpxRd01MXSUbV3HOLfcB9iR0K8DRhkfZ1nANnZycqZKNgoKta0RZLvEO3Zz5uk1eFDwwXeL4Ln1RURRc6/hcbgeMxpN3qqJQdw0emC5Rv83MrwkmeLPgtuYq6/U6X/EVX3G31zLBBG8sZAlsPA9ZKJWaLVhlSAJonxcX5bJUNGfKFienPC61fAgSHEMM+i5uDjF1lbPz5T2be5IV9KKE8+sj2qOYZskiz3NcU+dYw6XsGGiKtD8crYD1c9C9BLpNqVRiddhB655Hscok3gJ62MIcrZLlYAYR1doszJ4Rv5tdaJYsGp7JIErJc9Gd3Ep+VBBnnN8YsjEISbKcAoWlXsBC1eHElLfdZkmznI1hxEpXHJlNXWWuajNdtnbGwy2NtV60T7wMjKvHxb7psVuFqio8MF2i6his9AKGUcZ02aLhmszW7H3Vkuux2gvph8ke7xpNVai7Jh0/5vLmiOmStb1OVVUoCihZJg/MlLiwMaQ3rj5pqopn6mgoPLJY4exchamStccPCMQv59zKANfUtyfv0iynNYp5dqXPE0eqd+THM8EEb3RMrConmOB24bdFjFs6oB1rOHLfYHmb3Gxvoq7Bej9iEKbYhow+H6m5e9pVRVFwpT2iNYypOZKKPVexKYqC9ihmYxixUHd2NrDeNehcgvIMaCaVHKqhxtogZCrqoGkW/sxbyIIuncGQ6ekSpZPHwPb2rx2poNzO5hinOc+v9lnth0x51naFahSlnN8YkuY5Z+cqJJmYDy51AyxdxdJVRlHGl5d6zFZsHp6vYBsasxWb1W5IlGb7tD7dIMGzjdtOJt9CURR0/JjNUYQf56jATNVmruq8IqmL05y1fkjJ1A+M2646Bmv9kF6QbLfktvRCSZYzVbJQgNV+SDeIybKCQZTw1NEaf/WBqQNdpiXdPcA19T2kT9dUZis2y92A5U5AZf6NR27SLCcdE+pJe22CO8GE3LxRkWdiYDdcF0M205NYArcprZEJ7j3SQAI6D7vehid6nDzf1t6oqoROzpTtbefYL15p0/f3Bm8Oo5T2KKbumvSCeNsTpwB0XeXC+pA4zTg7X6XhGDi9a2BYoMlGr6lwvOmiKtAdVlFba/SUeXJviunFeU7NlDHMu/85aY0i1voR87sEwCC+OJqqsNQNma86dP2YpW7ATNnaI7rNcoPVfohtDHl4vkpznLl0qeXjGNp4PLxgEKaoKjw8W7kjvxshkT4vbwzJ82I7h+mltSGr/YhHxnqngxCnOdc6Ps+v9FFVFcdQmS7b1Fxjm4htvW9bmWQANcdgpmKx3AmYLts0SxY112QQJmwOI047Zb7ygcahY//9IGUYJsxVD9Y/VWyDzWFEnOZ3XNV6teDHKSvdkLV+SJpLNW6+ajNbse+Kn9EE9x8m5OaNiCwZRw9cFmde3QS/Jf+uHd+joXjVEA3B34RwIJu9O853erXX8WpCURG6cQiKTMjGIQ6xWy2M6ZLNer+3xybfj7NxyKU83bN04izjSiugNZJAy36YkGQFZaPg4bhLo7w3LNTSVR6YLjGs2sStEcmMhdNsUHH0e+Zau96PMA/51m0bGq1RxMYgZGMQU7L0fdNE0s4xWB9EHGuk22aBZcdguSv6EkWBmYrFQs254+mhjp/w8sYQ19D3VEnqrsl6P+TFtQFvPV7ft84ozXh+ZcC1ji8u0rlMV53fGFL3DE5NyVRZkuWoioK5O1VdVTg9Hl9f70ekeY4yztNarLucmS3fMP8pH39ODnKBBjEmjJNiD6F6PWMYpTy33KM9jCnZhuiO0oxzK33ao3i7ijfBBLeCN/HO8yZG5zJ0LkqlZncadRpB+4JUcRonX7319Jdh/QWIB0K08my8vlnJgDLfpJ4cdg10WypnxnWvsSggGsHsiUPJzRamShY1x2R9EDFVGk9BIZtYaxTT9EzKls7lts/6IKThmdi6hqKI03F/FHK5FRKnBYUtOh7LUKk6hkxpmRp4BlQ9cO9tqyLJcnTt8NerqTKlFaQZdefgiohrSrxDmGTbFZ/FmsNcxd7O47J09a4QtPVxGvhB7Z9myWKtH9AZxcxU9mdorYx1RIamcnFzhGfpeJbO5ijC1gNOTpWk+uYZ+zRDtqHx2EKVXj1hEKbbAZl11zzQAHE3LF3ddnQ+6LFBnGEZ2ise5/WCS5sjOqNk29cHxNiybBus9gPKtr7HuXuCCW4GE3LzRkMaQX9JYgf067616paIWbtXRCSqvwoTE0EH1p6VKkbt6M7teSqkR1Fh/qlbCpZ8w8CuyHVuvQxuIaQS5LUPNyRzqvzK9giOqXF2vjwOwAxRkLyhQZRyrO5yfMolSHLaQxHW6qpKN0mYq9hoqkrJtXkpKNHpXMJuaiiqVJQ8Q0aR62oARumWMrBuFyVLxrMPQlEUZLls4tpIppwO+kIuo9T7KxOaqtz1ROtukOxJOr/+fCgKQbI3ciFOc1Z6IWXLQNfEf2gQpmwOIxxDw9FVlnqB+OOULE5NlQ4cIS+Ammvc8mRTxZax8dYwZqZsXSdCz/GTlJPT1TeEZmUYpWwOIuquuY+saqrovlb7EUcb7g39lSaY4HpMyM0bDfFIfkozB99vlWC4Ccno1SE3g1XIon0TN6i6rHG4JsJat3Hv1/JaYOohqcz0rgnRQxFC5zakPWgeLNi9HjXX5C3H6nT8mNF4SqnpmaKb0DT6YUSSF9R0jVGUbo+FF0XB1bbPBk1KepsTao/MbVIoBj0/5vLSMpGdkk89TDYocM2Immves41vpmJzrRMcGBXRD1M8S2Ox5uBHGa1RfGC7oR8mlB1926wwyXI6fixj4WNzvLvVplAVhfwGSeNFUewjWWGaEaYZjXHlydBUTk55lC2dzWFMnGaEccZM1ebsXGVP1SbNcjaHMSu9AD/O0FWF+arNzC1oS1RV4dRUiSjps9wLxiRLIUxywiRloebsS2t/vSJKMuIsp3mI/ss2NDpBTJzmE3IzwS1hQm7eaFAUZCzjkH56UYynNl6Fb215DqMNSec+CLolVYxo8OYlN5oBMw9LOnjYk+tvODICfovCblOXaZctzFZtzq30x+PJKcMoBUJMVeVo3aHqGIzGwmO3XGNQPExir2MGLZQip5rmPN/KuVA+guvWUMIemqIyVTJ5aLZ8S+PdN4u6a3BiyuXixohRlFGydAokeVtT4excBc8yWKg7tPyYji/TYIqibMcqhEnGqWkZGV8fhFzYGNEPkvEnvsAbj8Ifbbh33JqarVicW+lTK4x9x4rSDH1svrgbqqKgoZDmBVv7raGpzNccZio2UZLR9mPOzJb3EZsX1wZc7QSYmjrWluQ8t9JnbSDi5Zt9T6quwWNHqqz2Atb6EVGa45gqD8xUma3Yb5iWlKYq22PsB/kZZXmBdgN90QQTHIYJuXmjwSxJdSbsH0wYor60pg4jHK867pNfSlZZfu4iyrbBE0dqtEYxF9aHbA4iZseTVltVjVGcimhVVbBKDeKpI2RRlywOuNgKuezpVEplHqh5KIjb7bWOT1YUPHGkdtc3QUWRqkLJEs+YfpigoDBXtZiv7giAZ8o2j8wXXNgYsdIPoFBAAcfQODNXZrEmMQ7nlvsUhTx+y5G5H6a8sDZAVZU7zliaLlusdE3WBhHTY70TCLHZHEYcqbv79DKeqVFzjQMrT5qqEKY5jZK5T8ez0gu50vaZKe8lH1XHYLUXcn5jyOOL1ZsmbCVLtCjHmx5ZXmBq6qEOyq9XlG2xOegFCc0DxOHdIGG2YuHeg8m+Cd7cmJCbNxo0Q7Qtq1+W9tTutkc8Ek3O1JlXZ0pJVcFpinjYru6/P4tB0V5HROvVQZYX9INke6S1Yt/+dJJtSBtnvmJTtnXW+hGutesXfSEW/K6l0yyZ4j5sN2ilEav5gFpVowA2ByFtP8GPM4pCjOfKlsHpubsv1FTHjsSzFWs7pfyglst81aHumnT9ZJwYLsZ3jinhmEtdnzgrJL18DGVsWpgXBdfawR1XKVxT5+x8mRfXhuL6XEhN1NCFOD00W9r33imKwmLdpe3HdEYxVddAVXaIV5zlPFQv7alEZHnBSi/ANfZPiKmKQsMzaQ0l/fwgw8IbwdDUA7VLbwRoqsLxpsczSz06o5jKOD4iy8V7yNTkfbhX030TvHkxITdvRFSPQRqLaZvfFiKTZzK50zy9X/9yL1GZF4Fz2JXpoS3kmXjwlOelRfM6QJYXdP2Y9igmyXI8S6fhmXeUS3Q91gchl1s+PT8hy3N0XaXpmpycEvO+24WqKjw0WyYdb5KWrqEpCh0/Js4LHqzaezbFfpCgqZILleVwYdNHUxWccar2xiDhzy62qLrGnlbY3YSiKK+oI7ENjbnq/seEiaSoVw95byq2wcYwZBCmd2ziV3NN3nqsRtuPCeMcRZHj32hkfrps8fB8hYsbI1b7oTAiRVpmZ+dKzF+neYnTHD/O8A4RRNuGRtuPiZIMbpHcvNExW5GIicub/nasiKpIRevkVOmO398J7k9MyM0bEaoqQtbSjJCbNBSdh9sAq/KKo8d3FW5DNCebL4ioVreE2GSpuOVOn31dTErFqegdVnohRVFsO8Q6hsapae+ufDtcH4Q8u9QDFJqeia6pxKkISEdxj8cWq7f8rXw3PEvn8SNVWsN47Hob0/BMsmKcRbRLdJkDcSpiTYDZso21i2g0SxZ5UfDy+vCuCHTzvKAXiPdOnhe4lr6ds3RbxysKoiQjSnLao0Kmwiwdz9JQFAVNVcjz4hVzpbbWleQ5uqoeGiypa+q+JPRXwnzVoeFJ5Skep3fX3IOvpaKMxcuHeM/khYRt3q8VivmqQ9Oz6AUJaT6+lo5xw1yxCSa4ESbk5o0KRZHR3ldhvPcVUZ4bOyZviGuvVYXSNLhTr87E1k3gwsaQa539eod+kPDC2hDb0G8psfp6ZHnB5ZYPKHuM5bZEwsu9gKWuT9U5oH13C7B0bdzCiEkzSPMcS9e51vFZG7Q42XSpuSbDMGEQJTRckwL2EBuQCaQjNZdBmNAexTdO+84SMYlMfJkEsypSjRtvxGGS8eLaYMeQDtHPVB2D07Pl2/rm3QsSrrQDBlEqouSiQNMUpseOxWkuKdi2cfjm1x7FXNwc0hlJaraqKFQdnRNNb59vze3C0jVmKxphktEexVzYGFIgr32qtBM/YRvyvq32wgPH2QehGBZWnPv3V7Kpq3f0f3CCCXbj/v2fNMGdoyikJdW+KELmAtEEbQmaXyfEZhSlrPXDAw3SKo5B2M9Y6QVMlfZ7bdws+kFCz09oHrKR1xyDzUFMOJXdcVzAy+tDlro+FdsgSKQqNVu26PgJa/2Qsm3wyILEBlzr+LjG3mpRP0hwTI3auOoQXefjsgd+WwI5g87WAqQNWl6AmbPkqslLa0OWuwHTJXu7UpMXBZuDiHMrfZ48WjvQJO8w9PyEl9YHVBydNM+puxIoGac5K/0QFCEVi3Xn0ON2/Zhnl3vESU7Dk/c9HY+UP7vcA4VbrtTcaL3nVvv0ghh9XKW82pb35+x8ZZvcLdYcWsOI1jCi7pnbOp1RlDGKEs7OVybjzhNMcJcwITcT3D56V0XYrJviRqxq0iLrL4m4eeEtN+3zci8xjFLxJTkk3blk67LJp/ltE4+sKERjMyZPajxEDzbRw00AFKNBqFRI8zvTH/WChLVBuO2KOwzT8TkLCiBMc5olk8eP1Fjthax2A9YHAShSmQniFFNXOd7wcAydVhEfXvqPBrD6jFRsynM7o+1pJFEfQL96lrVBuIfYgLRgZio2Sx2fjX5IafrmReUrvYAwyXlwpsyl1oiNQYSlqZi6iqrAi2sD3n6yyckp71Ayeq0TEMQZ81WHJMtZH4RsDmLSPCdIMuI052vOzGDeYTsuSjOeX+0zDFPmKs5OBlhRsDGMeH6lz1uO1cV92DN5eL7C+fWxTkeEOtiGykOzZY7e4eTXrSLPC7pBQmsY4ccZtqFKIrxrvuGmriaY4HpMyM0Et4c0koqNYe8VDOu2fKvvXYPeMkw/9NqtcRfu9a9qQ1PRdZUozfDiNlb7ebRkSDaOZdB6qzQMDyNwwZq/7fMMwpRhmDIIZCpnepdDrUwQ+XzxSoez8xXmqjbveHCaz17YBERntFh3aHgWJUsnTDIsXaVymA5ouA5hj6J6lDjLybMMU9PQdEv0XoMVhkyTZsqh2hrX0lkfRJy8SXKTZjmtUUx5nDt1csqj6hpsDiQI0rN0bEPjaN091BPGj1Naw4iaYxKlGRc3R7SHMZahoY/HyZ++1qNsG5ya9rYnulxTp+7ems6jPYrp+AnzVXuPF4uiKEyXLJZ7IRuDkMW6i6YK4au5Jl0/JkplQsw2VIIk57mVHgB1z6Lpmfc0TynLC86vD7nS9skLGSNP8pwr7YDFus3pmfJE7zLBGxoTcjPB7SHoyjf7ygEbtaKAXYbhimRcvcbhma6pYWoaQZzhHOCXMYxSpkoW1h0kKFdsnaZr0u52aQQvQJEQl2VqrSigEzucsH2s1gvgVm67olUUMAgSRlG2TzeiKgo1z6Tnx7SGEXNVh5PTHqPxZt8omdj62B8nSun6MSfKGZV4A1JN4iQMZ9eJVujlFusbQ/phQpGDZYguYqpkoecJSjRA4XAdkYho2RMKesPXB2PBt7wXuqoyU7KZLlnjIFGFlX6AdQOtTZoXpEWBriksdQLao5ipkrVdjfAsHT/O+NPzLS5ujkQjJTIhmiWT07Plm56g6wcJunqwyVyU5nT9mD9+eZPjTQ/X1JivOkyXre33rjOKeWF1QDeIt1um1zoBNcfkzFz5lqMZbhbLXZ8Lm6N9JCpOc660fGxd49QtVNsmmOD1hgm5meD2kKfyp3LIJqOaUt0pMl7rj1nZNpipWFxp+cxq9p5vpKMoJS9gvmrfcPPdKuH3g4S8KORbvmdsayQUReHkVIm0fZlet41eO4KeFcRpxihKqbkmjak6+Msw2rwhuYnSjJ4vPjlbEzhbG59tqgyj7FBvlyTLKNk6gzBlripC1ofnK7y8PmRzFNHOEqDALmIeyFc4EXRQgowkL0g0B7V2DGv6FIqq0R5GXNkMCHWZUtJ0sfi/sDHEj1KO6WDpBYoydpI9oJXhxynHbsFJWFcVyrZUanZXZhQU9PGEm66oODeoapiaiqWp9HwRS1dsg4KCXpgwDFOGUcK1TohtKGgqzNdsGq4JKKwPQp4vBjxxpHpH+hc/Trm4OeJq22e6bKGi0BklbAwijtQdTo/H+l9YGzCKUhaqO6GRMqof8cLqgKeO1e56BSfNcpa6Ia6p7Tu2qauULYOVXshi3ZlogCZ4w2JCbia4PWimVGjyVHKkrkcagO4cfN/dRlFI9EEaiS7EroqweRdOTZdIsoK1foiqyEYZZRmmpvLQjHfDKY0wyXhhbcBGP5JQRwXyAhpGzOlyQs0CNIOq0+BsLaMdemwWEEYJuqZytOEyXbZlsie2xBOI4we8jILlXsilzdE4akECJCuOwbGGi64q9EPxz2mPIqqOvl3hANlQlXH1Zjc8S+eJI1X6QUqQZChJQLlzATfrEFsNlnwx+cuiPua1P8eYH1A78igrgYmWBTRrze1jGbqKk2qs9XzqXkrtSJV6ZrI5jPaFOIoeSLmlySRFkayl9UG0L58qH+tYZsvWDUfqbUNjtmLzF1c7hGmGY6ksdQN6QUKWFVxujWj7MQ3HYBhmaArMVB2O1T1mKzar/YDW8BUmyMaoOAZpLq2d3XqbKy2fla7c7pgaiireOHGac7XjUxlHTnT9eA+x2boG02WL5V5AaxSzeBPruBX4ScYoTg9NZS/ZOuv9CD/KJuRmgjcsJuRmgtuDUxfTPr+9P8QzTyH2ofnQLecr3TLCHmy+DP6mjCwriowq109I3tN407ANjUcXKsxXbTZHEUla4Fka0yX7hmZteV6IP04nYGbLDbco0HuXCJdeYoUYa6qMowOmRylNKNVsZt0KWS6tEXN3laXIxbX5AKz2Q84t97F0lbmKaDiyvODaZpdnXzzPnBVSsXQqmcZLfZUozTlSd7HGWh9NVThSc0BR9rVVFEWh6hpUMaC9AkmLpLTApVbA5jDEMXScUoMiMhiuXuD5URniCo9bBkU8JN/lMq1r4MQdNu069dI0p42CcysS4ugYOqoiG6ihKTw4fesmbNNli1NTHhc3R/RDSe1Os3xbLP3gbPkVBa8LVYfnV/p8caPDxU2Ikpy6Z9INY5IiZ67i4NkawyBF16TSdXFzyENzJXRVpTWKborcNDyTumuwMdghd6v9kC8vdRnEGbausjGICKKMqbLJYt3F1nVWeiG2rmFo6oGfPUVRMDSVzii6ZXKT5QV+LJVV19RvOST1ECueCSZ4Q2FCbia4PWg6TJ2G1aehvyxER9UgCcZanEVxJ76XiIaw8rQQHG9qx0Aw7MmUDwXUjm0/XNdUZir2TVUStkIcW8OYqy2f+Zqz3QoyRivY3RcxS2XWQp2q7uHUHMn7Gi1BnmFZpXGIqQHalo4lF3PDAzLB0izncssft6F2yEDit0lXzpF2+6gVgyN6zqyZ4Xk2zyaL9AKd+arNfFWEqmGSU7b1wwlFUcj7ZXq0/ITNYUjDtdC08QboVnCzIVfDAVfiMg/NPYjTvyDiaN1BKXK0xCe0S7S9B8kVjaqr8OTRGhuDkPWBVLdmKhYzZfu2NCOKonBq2qPmGqwNQgZBimPqPFix93jHHIYky7ncHhGmGUGScaU9wtQ0un6MZarMlx3SoqDIRY/lxwnHyx6tUUxnlGBqKjcICt8DS9c4O1fh3KqQuywveOZan7V+yPGpEkfqDiXLIExSlroS7zBXdfCjFP0mSIdyC1L4PC9Y6Ycsdfxx5U/ypxbrLvMVe5sQuoZGydIZhumB788wkvT2exGsOsEErxYmn94Jbh+laRn37l6VykmeCcGYfQyqi/fe56a/Iv4ruyo0qJqQh6Ar01ylWVnTLaA1jLja9un4MSvdkJV+SF6ITbyjFxiDq+S6TW6WsPOU1pYJnl2R6bHVZ2RazKnI9JjbAG9GSJ83JeaG12FrCmq3ASCJz2j5BaJwwFRzhnahMHB0HDXjdLqMEa1yLncp2QauKQnhVdfk7FzlcGfgIoc8JVcMNocRtq7vEJstKAo1S+WFYcamscDUTBV9tIoW9yjQCMon6FLF9srbl90xNY41PY41787ov6IoNEvWgWGKr4QLG0O+dLWHHydCkPqyUUdpTjBKqDcMekGKa2o0PYsoLchysHWN9iim5hpUd5np5XlB249ZH4SMImllzlZsmiXxz6m6Bk8drdEexXx5qYupK5ycKXG84WKNBdy2IX+2hjGeLZNgVcdgvR8eKLYuioI0y/e1GA9DURRc2Bxyfl0MKWvjltMwTHnmWpdgpsQD05KTpWsqR+ouX77WxYrVPa2/MMkYxcmNP0MTTPAGwITcTHBncBvyE/uycerWPr3LPUGWwmBZCMVBLSW7MiY/XSjP3vRhNwYRzy33SLOCqmsQuRndXof1lTZxK+d0OUcP1ojLR4DrRszDrjj5MnaPJhdCM1gB4zIsvpV85hF6EfjDAICSKa60eVGQFdeJcoMO/qCH4k6j6ypFVJAXgKpj1Rc4O1wnLGIsXWWmYt7cCLGqgemRDjZIUhtDv+7aFWLoV/EczJ5ofOrNBpm9U23Ki4JRL+RE5cYi7NcCoyjl+ZUBXT+mbBucaJYYhClFAa1RRGcUY2oaFdfAMw1cU9+OqFBVhd54rHtqbPCXZTnPLPW4NM7mqjg6g1wSvucqFmfnK9iGCHPnKjaXWyZPHa2z1A1IM9hd/LANnX4Yst6PeOJIlYWaw/ogYn2wV69UFAXrg4iqax5qCnk9xNHZp+aae8hK3TOxY43LbZ+pkrVdFZyv2AQzJa60fbpj88E0Exfok83SHaetTzDBa40JuZng7sC8t78M87wgzQsZu1XHQuatStFBUNQdwfNNIssLLrVGZDnSuipySvEKU6MLlPSCjaFOf9RjOr9EoWokpSOEaca8J4+lew3yRKpFM48A+Zj0ieA5sBq8uFmwMeiQ5jko4o8zW7aZq9pYmrp3XN1vk2s2igJhCqYG5taXaVXHUGFOj1mcLd/a2G5lAa2/gp4npBiwi4tqYYfMrKB7DRqlEX6c0wsSyraOqigSM+BHTJWsG4qw87x4TYzgBmHCal+CRUuWTpRmTJdtigIcQyNJZQN/eLbEIMpYG4TUXGkbrQ0i5ms2Z+YqlCydzijmC5fbfOlKF8fU8UyNNM+Zqzo0DJPVXoBpqDwyL6PwW2PsjqExW7a41BqhKuCMyUaeFwxDcbFeqDnYhsbZuTLPrw5Y6QXbU3xplo8rcOWbnpRqDWOStMAt7f+V7pgaHT9mcxhtkxtVVXhgusR0yaY1isaeRxrNkkl1LHaeYII3MibkZoLXNaI0Y70fsdwNZAxYU5mv2syWDGzdkqmsg4jVFqm5hZZUL0jo+glTW9+Wh6t4oyVs16OX6Nglg5XC5Wi+gdV5GT8z0M0GDdcSR+aoLyPwmgGWJ3+O9TWJX+Pq1cuseTWmatVt/U6UZlxr+2R5Qd0zWekFzBtbTrcFtqXTDlMyDI5XVYxdLaQCBcZj6beE0ixa4yQzg3Nc6eegNVDJ0KI+hW4T1R6kFyucmioxX7VY68djR12wNJXFmsupaW/fxhulGRuDiNVeSJIWOKbKXNVhqmTeM0O4MMmkMoOQijDJGUUZC1V5Dy1do+YYrA0iGp6JHye0Rgm2qeOYOooiqeB5UTBfs/nqB6eYq9q0RzHPXOvy0jhYtFmyiLOcjUHMKM54cLpE3TNZ70cca0j+laYqlGydjX7EbFWSrtf6EYNBiIJM2Jm6ymOL1W2SUXPN7ZZW148Btis2tzICHiTpofYAIOf1470xG9si8ztIq59ggtcrJuRmgtctwiTj+ZU+q/0I19CwDMkXOrfSZ6Nk8Zi7gL35jIx+Xz9y7rfAaYDhivBYM16R6KRZTlEUshHnKfRXsUg4ofXoDdr04oKh1qRVaVAevoyiXOPoA/MSdhikkMZSMaos7mvN9RKF/ihgblZH2bUJWbrGTMVmfRByZq5MnOWs9AJKloGhlsnSFoPIZMbLmfV2vcYio+/HuAvV/eLhoAvDDQja0oYqzYA3vWPQp2ow8zBVrYx7/hzdXpeybZKVjxK583RyjyjLeXi+zJG6y9GGEIh8XJU4yOAuiDPOrfRZH8gUkKmrtEcJawOZ9jkzV77h5nurkKDSEcvdgFGUgqJgaSoo0jaLs3w7LHS6LAaAnSCmUBRA4VJryGzF4aHpEuVxpeKBaY/jTW88yj1iFKU445aToihYusZ0WWNjELHWDzk1XaIbJPhxup1xNVe1WeuHREnOYt2lWbK2r13Xj1moOzw4s7fKZhsaCzXnpqazDoOlS1XpMKR5fkNvoAkmeLNhQm4meN3iWsdntR8yV3G2tSiuKd4iK12fS+icdZvQWxqLeV0hJUF3x1zw6uekVaQako9UO3qogZ4+HstNsxw9HmJ2X8ZMB6CqWCULYxRRCa9QKjxK04tUkk3cYh2CuozERwNoPCDn2UKWQjxk2FpDJ0PVDK6ftN3a9JNgyGPVgg0tZjkoiM0q9ZLDO8spARb9IMbWNYq8oBiuYHgNTh07vlf42b4Iy18Szx+nDqoimh+nLkLvrRR5VcOePs7x8jyX1tqsDRPCQkeNVcqOyoOzJearojuxdA2rdOON8WJryNogZH7Xe1W2ZXLpWsenbOscvwmxcVEUhEkuE/36wWPSRVFwYWPI+Y0hFdtgfuwTEyYZG/2QLC9Y6QXbY9CaqjJfc7BNlaIoONH0eHShgq6pOLponmarNk1PglN7QULLj6m5JuuDiOvfsPI4iyyIUyiKPRNNU57FyfEY+yBUcE0dU1cZRinzNYdH5iv3pIrVLFlcbvlE6X5vmjiVpPbbSWefYII3KibkZoLXJcIkY7UXUrGNfT4dRthmMbhC1GoTTFs4eQZ+B8xYzAW9KSE4ow3ZzI2ybPabL0pFZ/5JsPZrVKqOQc016AYJc0kLc7RMVl6gMGyUArLM5eRMk6N6FwwPtJpUh1QNaseFXG2lZucFDFeFWMQj7LVlbGsOtXeBuHqSQt/5lq5kEeXuSxijLk5J4RiwaHhkM0fQF86itl9iNOzTTnSGYYyeR5RmZ6gcfwteZUwY8kymtF78hARdGq60ySoLUJqTa7H+PBx52544jJJt8uixWYZRSpTmqIpCxdYP3YCLomAQpkSpaINKlkxpbfQjGq65/73SVDxTfF0Wdo3TH3Tc9YG0H/tBAgpUbYP5mrPPHHAQpSx1AurXiWdtQ2Oh7rI+jFnrB6z2xwRHUYizjAI41vB4+8kGjyxUKYqComCfNijLC9K0oFTSKduGjJDvqnoYmoofpwzCFM/SKds7a1BVaedVHIPVXsggTNFUhYdmSsxW7VtKR78V1ByDxbrN5ZZP2TIo2TsxG/0w4VjTpe5OyM0E9w9ec3LzC7/wC/xv/9v/xsrKCo8++igf/vCH+eqv/uoDH7uyssIP/dAP8YUvfIGXXnqJ7/u+7+PDH/7wq7vgCV4VROnYtO26X8j6aAW7fQ6ylHVsYq2MY5qieXGnYOZh6FyUzXz3iLhugVWWxPLOJZh7bN85NVXhRNPj2eUe/c4GumpR5DlRWjAIC6q2ypSng1qXatHso3D8nTstqNGm+O4MViAOoH8NFJUiz4nLR1lLaky3LmIkAcn0YxSaBXmC1TpH3L+MtbBA4FTpBTGjdhd97QvYc2epzrwVr9rC22ozedPys6U1KgpYew6e+x05p12D1IewJa939jGonYDRmpC766bHlLHpX/kV3pO1fshfXutyYWNIlEjb5/Ssx9G6R5jmh6aue5ZOL5CgyIPITVFIi+ml9RGaomwTgPYoYWMY89CMx4mpHTLa8xPCJKPmGrT9iDgR12jP1PFsjWN1h7KlkxUihi4UBVtXcSyDB6bdbfG1oigHDtrpmoKhK8SpBJN2gphhtNN6SrJcJsbilBNT1X3aGFVVmCnbzJRtcbRmP4G6HRRFsR1zcX1FS1UVHpopY+kay72QtbFGyrV0Hpopc6zpTpK+J7iv8JqSm9/8zd/kH/7Df8gv/MIv8M53vpNf+qVf4t3vfjfPPfccx44d2/f4KIqYnp7mQx/6ED/zMz/zGqz4PkU8EoM6kA3VOmT8+i5CUxU0BbKi2P6QKmmI1T1PoWhEThPCBNV0JKTTKsnmPWpKxcRp7F+jokh7ZrgG8ckD21PTZYvH5j06nYSBMUMyGKC7JnMlnfmSjqMrkBVyTZz6Xm2NNyVVofXnYOXLoCj4qsdaWmZZrXMlLFiNCxaGlzDVJu7MCfSgRdRZQqnMk5sez68NGQYJUabhDzVY+iLRgsZbT5/kxJEHD3ab9Vtw+Y/ldTk1ee0UkIQQjWD1yzveOsnott6PpU7A7z+7wvogpmRpqApsDEJeWu0zV3U42nCYLdsHrk8iKxQO21v7geQwlS19j3GcY2oMo5RLmz51bydyIcvFYPEvr3YZRAmGKpNxuibeOBVbZ75uc3q2fKg3zY1QtnSansV6P2KuanOi6bHUCVgfhKgKbA5jFsZTVcebN54SvFV34IMQJiLUXu4GpHmBbajbAZy7X4uuqZyaLrFYdxhFIh4+KD9qggnuB7ym5Oanf/qn+Xt/7+/xXd/1XQB8+MMf5v/9f/9f/s//8//kp37qp/Y9/sSJE/wf/8f/AcC//bf/9lVd632JLIHWefn2nwRSIdAtGXWeeuiejn97pkbdNWmNYmbK8stZD9uoyZDEm2cUyDfp7baEbgt56V4VYa9TP/jAui1ELY0O1d5MlWyaMxVGFYPC76CPNnBMBTID4hTIpfpRObLzpDyTVlgWgVmC6hEGziwXWhGBYdEoG+h2zFI3YH2kwJWX8JQq05t/QWV0mRl9ROuaQapUCQubQZiiGy7lvM/a5hofj22++qFpHl2s7t8wN18SYuM1x975IprFcEHRYbQuFR2nBrfgeLuFNMv580stNkcx02WL9UFElEjcQ8U2eHGtz8YwpO5ZLFT3i2L7QcJU2TpU0Lo5jIiznKkDxphL46pPaxhRdQzyvGC55/O5iy2UcZXHM3Xqnoljqqz1QlpDhbefaDBVsvaaIt4kFEXheNNlEKWs9gOqtklpTmNjENMaRZydK/OVJ5vM1+69z48fpyKgH8S4hsQ1DIKUzWGX+apzoNmepWuTTKgJ7nu8ZuQmjmO+8IUv8KM/+qN7bv/6r/96/uRP/uSunSeKIqIo2v53v9+/a8d+U6MoYOMFaF8At74TGZCG0L0im/j8U/fMhVhRFBbrLh0/ptMfUjcStGCTIksZRBlZXjBbsdnzJVx3ZDRc1YWYHTQdtRX0eaNAT1VDKc1Qil6CuYcgnBbBcBqC64wDQTW5LiD3bbwIYUdIznAdRhu0Ixs/LzNVlmvUKFmYusbIiun0+qRXPs+iep5KSSPII+htYBcrZExRqR1FU1XswuSYZ/ByAc+t9GmUzP0Ga/0VeT1mWYwNd0M3xYNnuA5uU6put4jNsWNz2RJH3bwQjce26ZxScHlzxBcvd3BOqdTHhKIoJEldUWGh5hxKBEZxiqkdvhlbuoYfpxRFwfmNIc8vD4jHOVOuqRMkGcO2z2zVxjVV1vrRjlfQbaLmmjy+UOVqx2dzGJFmBRVH54EZj6N198CJsXuBS5sjNgbRHlF9CZ0ky1nuhlQd46aE2hNMcL/hNSM3m5ubZFnG7Oze/v/s7Cyrq6t37Tw/9VM/xU/+5E/etePdNwg60LsqEQv6riwm3YbKvOhKRhsSs3CPMO1qPO50WLv6EpHfh2gD29/Anoaj8yf2u7fmyc5Y+Ghj79TS9utqgzcr+psboTIvpMHfHEcmjMldEoi2pnpCJrSCLqz8pZAqd0oqJYpC3F0m7j5Pvf4QsLOOkq1Ty2EhD+mhU26ewk1aLI1s2gr4owGeskTqlsBuopCD7mAVGnlRsNwNmK/KRhfEGa1RRNCJsYcFbqNMRbUxwr68vi0yUeRSrSrNHl7RugGCOCfKCiAnSvNtYeqWuLjnpyR5zlo/4PNXO8xVHOqugaqCZxk8PFu5oeGfpatk+eFpjWmej7OhEi63fTRN4YHpMr0wIUhSbF0nzjKutHxmKxZ195VbTzcD8YCpMopS0rzA0JRb9xS6AwyjlPVBJNlfBwi1S5bOSvfGQu0bIcsykiS5W8udYIK7AtM0UdU7///7mguKD8pUuZul3h/7sR/jB3/wB7f/3e/3OXr06F07/h0hS2WzDXpie2+VdwIgXw0UhZCY0YZs2rotQlWnLpt2nu4lNltQNZlKGqzeO3KT57DxAlP+BaqzJQZFkyyaxl75IjbXMCINBhUJycxTaTFlMUw/LH4uYVeqFVu6mCyRa61ZUD/+ypohuyqi443nheQAUMjrbpyC6dNyU+/aWMzc3K7YkITkaYAeRpjBKnF5artSpGQJWtQDXSfSmyS2Rre3ylo7YsMv8GONhpIRb6ygVwt02yIyaxCKw64fZYRJhh9nvLg2YBCmOMU0Ff9loiKhbs5yTFnDCToyDp8nMqJ+4qtEbH0bvzQMXUFXRMi7lXBeFIUETfoxWV7gmgYLNZfpkgWKtJMemPFoeBJ0Gac5HT9mECYoKJQdfZuENDyLK22fJNsvOE7G0QiNksnmMCLLc3RVpeaZVF2ZZBpFGRTylk6Vrbs+FaQo0PNj2iMhAg3PYKps3XOiEyYZUZrT9A6uQrmmRvcGQu3DUBQFq6urdLvdu7TSCSa4e1BVlZMnT2Kad/b/+DUjN1NTU2iatq9Ks76+vq+acyewLAvLepXIwq0gHsH6OSEIFKBoQnDsmlj3e817e/48E61G56KcVx0TgPZFSdJWVFnTYVB12TjvFYKOtL+8KQzdpgHgOaCcgbVzcOkzUpnxGkISWy9L5SQJxMtm7knRC402EaMSRYS2zQeEQN4MStNCcvyWVGYUVd4fuyo7XhKKWZ6mCwkK+6JDMiw0q4QdrcBGj9ybIXOnUFMfNfFJ7SZ5OEAzLAaYtJMq5fwaIaDqFqZm4CRrrPVtBu5j6KpLXkS4poaiSBvnxdUBSVawULVRzJOY4XmqUYd25HLJPsJD1RA97EI4gMW/Aqe/UUheEghBU2++bTNbkXiIz3c6NMcTUWGS0w8SLEOl5ydMl00qts70mFyM4hTPNLANjV6Q8MLqgPYoQlNUirFxTLNkcmauQsMzmas4LHV96q6JY2pEacYwShlFGSeaHnXXZKkTYGmauAAPQpqejFYneU5RSPiobYjY+W4Z1rWGEc+vDhiECfZYx7I6CCh1DM7OlW9L03OzKIrxWPqY0F2PLC9QbyDUPgxbxGZmZgbXdSdRCxO8bpDnOcvLy6ysrHDs2LE7+my+ZuTGNE3+yl/5K3ziE5/gW7/1W7dv/8QnPsF73/ve12pZrw7yTIhNfwUqczv6jyKXb/5rX5YN6QAvlruG3rUxIWjsONeC6Era54UI5GJSdmCVIw3FP+Vewd8Esr2VIwUZ7+5cgHgofi55WTbtmUekStO+IK+pNC1/hj0hbZoxblnd4qanm9KiOghFJgSvvyouyKWZ7WtlNE+iphbx1S+hj5ZAN8k1h7DxMKAQDr5EpWIwjHLi0lGqbhln5QpBr4uSJRRWmY3yw4yyKarDiLonGpeaazIKE4ZRymJtrL1xasSzb6FYf4Zq3Gcw6jPQVep2GcoLsPhW+VytPiNr1i1xUa7cXHK7oam85Vidcyt9rnV8Tk2X8BPxuvHjAlNTOdJw0VQFx9RwTZ1uIFlGlqFybqXPMEz36EayvGBtEFKs9HnyaI3TcyUMTeHl9QFLY9dhQ5X4BktXyPICU1dJ84KmZ7IxjAjiFMfUt/U6A1JGUcpizaF+FwzrwiTjhdWBuA3X9uqcNocRL6wO8I7pd6zvuR5+nLLWC7nWDVhq+yx3fU5Ol2i45h6S0wsSpm8g1D4IWZZtE5tm8x5/gZpggtvA9PQ0y8vLpGmKYdy+tu01bUv94A/+IN/+7d/O2972Nv7aX/tr/Ot//a+5cuUKH/zgBwFpKS0tLfHv/t2/237Ol770JQCGwyEbGxt86UtfwjRNHnnkkdfiJdwe/La0MHYTG5DKQGlWJn6G6/eO3GSp6GkMZy+xASETdlmIg25Le+d6nUbiA+otpW3fMtJQqknXIx5Ka2n+CWlFNU/JZm14Qiz6y1IN86bGot+xVqY4XNNx29AsIYDDNTHLu44E1mpTbIxOsFY0SapPYthlkkJl1G8zbznU7ZwrvRzPNlH0OVy9zrK+SXvzGgP9FC1thsEgZqok1RBNU1ioOVxujXAMHSUeYfirUGTklkey+HaSwRqddouGo1BfmJN22agl77ddFTF0EgjR8dvSeruJNuiZuQrvfWqR3/6LZS61RvhhSpznzFYdTk656IpKxTWojoW2hqoRJCmtcWbSQnWvoFhTFWbLNmv9gPYoZrZi0/Bk854q2Zxs6ni2TlHA+Q2fIMmZLllc6/g4psbRmsPVboA/1twESUZ7FAlRmr07UQ+bw4hBlDJf2d+abXomy72QzWHE0cbdmxochAnPLvfpjmJKtsFsxebl9SHPXOtxvOFyYspDVRS6foKmwmL9cKH2QdjS2LjuJPV7gtcnttpRWZa9ccnNt33bt9Fqtfif/+f/mZWVFR577DE+9rGPcfz4cUBM+65cubLnOW95y1u2//6FL3yB//v//r85fvw4ly5dejWXfmeI+lKlOWxix3RlfLd56t6cPxmJDsM95JubWYZ4TVx3+8tSYbIrgCLkIk+h+dDhz78b0B2puOxbe7jjAlya3r8GsyRtpDwXfYnflvUHban8eHNCyuxbnxraB02XClfs78Q9bKEosNIe07PHUDG5Fg8IkojcqrEwO83RxgOo3UsUmY2iyLRLyTF5bMZkyZznmXwBVSlwTJ2SbeCaGienS0yXLS5v9Kmsf5764Dm0uI1SFOSaTVw5yWju7WT2SfIpB+anYeVLEPf3Ghoajrz+/pKQv8bJm3q5bz3eYKZi89nzm7y4OiBMCxbrQo4rrsHxhoc2riwkeY5taLSGEaamHbgBa6qCqqp0/Zi6a3J+fYRtaCxeNw3mmRorPXEknq86XOsEVGyDMzMarVHMxkBSrd92vMHbTzYoO3dnkqkfJOgHGOaBaAVNTaUXxBzl7hAFiZUY0QuS7ekyU5cq1+og5PnVPkGS0SxZlC2dU9PV226LTVpRE7xecbc+m6+5oPi7v/u7+e7v/u4D7/vVX/3VfbcV9+Ib+GuCG70O5d5UGg5CloxbNxGggV0SYgFSjSjPiRuv3wYK2cyri9KSupe/IL0paTFtRQlsQUGEw4Z9yORPLhNLIE7EGy/Ia7Q8iUTYfF48X2YfE3J0p6guCEEYbQpp0E1pO8ZDUHQsAhaSDtOqxSjTGA00wrjBqlWjpNWxkxWKXgfdMlCKHM0ss3jmMcp6k7V+SJhmvPVYncWau93+WOh+kdHVT0GlRlw+DqqGFg2x2s+iRD206b9JqbIA8UDW5Tb3v1eqLpXB3jWoHt0TyXAjHKm7vPvxBU7PDvizix2qjiF6G8fYbg+FSYamKDQ8i1Hk31AToiJvS9ePGUQJswdUSXRNxdI01vohjy9WsQ2VlV6In+S4ps7D8xYLNYdjDffu5jZJMPuhKNibK3Wn6IcprVFE0zMJ04yVXkjHj0mzAk0Bd5xi/thChamyNfGymWCCG+A1Jzf3JUwPiS/ODtaAJIFsOPcKhieTWd0rQmyikWx+RT5u8bhyfrMkm7U3JcLULYM644AJqjtFEgohKAq5Pk4d6idEF2SEO6PbWSxi7OqRgz1boqFUlaKeCKZ1W7QwW3Dq0vLbOCfHvNPX4k3LFFLQkciDNBpHJMyI782gBdNnGFgzrF55CbV7CTMPCd2jdOxpItUj1CvMlzw0yyO1mxS6jZWLluX0bJkHZ3aNrY82afSeJjJt/FTFC1sUmkmue6SVB8g2nmehepG6dwb87nji7ZBv94YrFbwsumlyAxKn8NhiDUNXudzyMTUNXVXJi4JhmDKIEk40PWqOwcA1WOkF+45RUBAlGcNxonY8nopSDyHMlqERpjmqqvDgjKSVj6J0ez33woW37ppcbfvkRbFvXXkhQt+7oe3ZQpRkJFlBXhScXx/SD1Mqtk7JlMTvrBAdU1EwITa3AUVR+E//6T/xt/7W33qtl3LT+PSnP83XfM3X0Ol0qNVqr/Vy3lCYkJvXAm5Tvu0PN6RFsvsXZ9CRDXf3hny3oelCDC78kZCVXUJYwj60X94Rm8a+VG4Gy0IsVF10QbWjr+wVczPIUqmw9K4JuQHZdCsLQm5MV0jY7srR0bcLGcrTnfiDopB2lOFJtWmwKkTjoMkob0rabX7rzkfZDUeSwDfOyXXUbbm+7UswbEF5gZE9w9rlFzGGK9i1GZQswVAVzJJHr9fCx+aK8iBWYWKnKnEYEaWZWP9PXWfQ1rqA1r6AmldZ3ewQZuBpGSVLRy81KLlV5rIrGEqxM+12GInOk7Evz61vlIdlGXmWzpnZMkcbkmU0VbIoWTrtUUzDMyko6IxbSUvdAFNXtx+T5cWhVhBJlmPpKtr4Ptu497ECDc+k5pisD0JmyvY2wcmLgo1BRNUx72rStqpKHWitH9IPU6ZLO4Ghmqptr+Vqx2eh5kyyosZ4//vfz6/92q8BoOs6jUaDJ554gr/zd/4O73//+7c9U1ZWVqjXb93n6bXEO97xDlZWVqhWq6/1Ut5wmJCb1wKaId/2V78sm7phi2YjDsB0xKvFqd3bNRSFjE4XqUzSaIaQBUWB5oPjya1N2HxZ9D92RchMFss0ld8SUa99B//ptl2Qz8vxKwtyezyUBO80knDK8oLohIpCyFieCpnor8g6FVU2cLsC02fl2m08v18svQVFHV/vcc5Snu8c33D25kXdDBonKcjpr77MoL9OECV4vZdxq3W8xgN0BxHFcBWrOk2hGRR6hh500JSCcuMISmcZzz1FYHqEcU7J0XmoWmaqZO77hu6vn2e5E7FRqmG5CVYywo+hE6TMGl1mZ6pYRSyk0anJ+xP2doTVuxH0hEDeZvXq+iwjBXCtvdb/nqVzerbMC2sDljo+gzDlWtcnzQqaJZNjDY8kzbkyHDGKU8q2TtXZSxjyosCPU040K3e0oed5QZhK5pKta694LEvXODtf4cW1Aav9cA+5qTkGZ+crd5VgVWwDU1e4sBFQto19JG8YpRypybXuhwm1Scr3Nr7xG7+RX/mVXyHLMtbW1vj4xz/O93//9/Nbv/Vb/M7v/A66rjM3dw+nO+8RTNN8Q6779YC72KCe4Jbg1OHI2yRo0WmIiHf6LBz5invq+gtI9lLQhpmz48ToY7L5VY4ImZh5RFoV688LsakujidtxsnalUXZMNsX7kwbFHSgJ142294xiiLnKM+JNsZvSSXErspmremyGc89IRWc6bNiqrf4Fvn31gTXlm/QYSgKITj9FVj6c7j8p3DlT+HKZ8XrJ0sPf16e77kpR+F8PscX8rNcMM/QdU/Q02pc9EtcXu8w3LiKqao7pEnRgAKlyFBNExSVctblLcfqfOWpBm873mCx5uwjNkU44NLmkH5hM5dvsJBd44iywWmrzQmjR9Zfx9+4LLopzZCf+gkhiUFHiCCIBmmwIu2/6hHuFJau0fBM6t5+MgYwU7F5y7E6x5ouvVDEw08eqfH4Ym0cZmkxV3XIc6labBkDAgRxxmo/YKpkMXOAHudmUBTFdqL55y62+dyFNl+80mG5G5DvckbO82KfU3LVMXjySI2njtY40XQ50XR58kiNtxyrbwd53i2Yusp8xWEUp8Rpvq0vzPKCjh/L/TWHrChIsjeL9vDuwLIs5ubmWFxc5K1vfSv/0//0P/H//D//D7/3e7+3rd1UFIXf/u3f3n7OP/pH/4jTp0/jui6nTp3iJ37iJ/Y5Nv+zf/bPmJmZoVwu813f9V386I/+KE899dT2/e9///v5W3/rb/Ev/+W/ZH5+nmazyfd8z/fsOU6n0+E7vuM7qNfruK7Lu9/9bl566aXt+y9fvsy3fMu3UK/X8TyPRx99lI997GOAtKUURdk2XLzRYyfYi0nl5rWE4Yhbbv34q3veIt+ZODLdgyeHsljStUsz+yeBFEVMBocbMvl1u9WbYJzFdFCFRTPkPMP1w0fOrYoQw4Ncd8uzsoEf5NOTJeNjr0nLS9Hl8YYl1ZylL4jWxyyLqNSpS6ssjWA4PqZdH5sITrE+iLiwMaJWqlLKVazWKm7Rp4g79NZ08sEmlm1A3hybH6YUikqhjr95qzpKFstfb1BN6Pe6rOU1jptgDy6QGlXSogAFFNXCyAOC1ia1pxZQtq7JFnlpX5BW3RapcxrisnyvK4RjlCydsm1wpO7u84wBaTNNlU0sXcXUVTYGEQXibbNYczk17d12leRK2+fFtSG6KkGbAMMw5ZlrXfyZErMVm41BxFo/oigKSrbOXNVmyrNQVQVTl0Txg8TOdxvHmi4nmh6tgehrQDblkq1zpOZgGxp+nGFok5bUK+Frv/ZrefLJJ/noRz+6Hc68G+VymV/91V9lYWGBZ555hg984AOUy2V+5Ed+BID/8B/+A//8n/9zfuEXfoF3vvOdfOQjH+F//9//d06e3Dtd+Id/+IfMz8/zh3/4h7z88st827d9G0899RQf+MAHACFAL730Er/zO79DpVLhH/2jf8Q3fdM38dxzz2EYBt/zPd9DHMf8l//yX/A8j+eee45S6WAbkFt57P2OCbm5H6GZMj0U9g5O9k7HQaMKB8cvML49ax08rn2z2BLf3midWbj3tiSQTbq/NDbnM2UDL8/tFc56YxO/wYoQtK2x+zQa63t8WH123OpyRYBcGo+I+21Y+TLMPSz6qPZFOY5dg8YJIQe9qzBYIq8/xNKohqGpeATYredQ0hFR7UHMwVVMs0E/CPEGVzFKdRJvHmO0BoqKFmxA2MOI+9juo4BUKvJCNvXrvVqCNCMtVHTTpOgHKElMoYs4XUnbmFnKyKqTGBW2GxaKIvqo0qx4FuWp+PM4tVs3NLxD+HF6oNPuFmxdp+RoPL5YYxCm5EWBbWjbhOR2MAgTLm6OKJk6JXvnOLahEcQZX17u8/K6tCdLlo6mKGz0heicnHI5NVV6VbUtjqnz+GKNcyt9KrZOjpgoVmwDTVVYH4TUXIPKqxTc+UbH2bNnefrppw+878d//Me3/37ixAl+6Id+iN/8zd/cJjc/+7M/y9/7e3+P7/zO7wTgH//jf8zv//7vMxwO9xynXq/zcz/3c2iaxtmzZ3nPe97DJz/5ST7wgQ9sk5rPfOYzvOMd7wCENB09epTf/u3f5r/9b/9brly5wvve9z4ef/xxAE6dOtwC5FYee79jQm7uR6iqtKCGG2KWt5vAbGltvBmJHNhy970eWSLtleurOrcCw5HN9jAkoehtthD7sPr0jsGhZsoaV/5SdEOzj+3oRwwH5h6XqIbB2vi1jas4aSQj5gpSNSsK0dy0X4Y0ked6jXHmVwGtl+TccvGkUmVXIR6SbLxAlJ7EK82iB0uocZ+kvICSxajpCCdsM7IcstQha13C9jdR8pjUmUYLNokGPZpmgRK2+fLVNq0gJc8LHENnrmqxUHMxdbnGiuFgJD3yNCVqnEGPe2jRACgoTJcwM0lKCyjxUFqPu92HdVNIXp6Poy0ujzVGrhC4e5TuvhumppJe19LbDcmWMsZ5U3dnPe1RTBhnNOv7J8ZMXWWp41O2dJ46Wt/WuJRsnSDOuLjpU3EMZsr3vmKzG4t1h7Yf0/MTaq5EWCRZzuYwwdAUMfKbiIlvCjfKKvyt3/otPvzhD/Pyyy8zHA5J05RKZaeK/cILL+yzKXn729/Opz71qT23Pfroo2i7Uu3n5+d55plnADh37hy6rvOVX/mV2/c3m03OnDnDuXPnAPi+7/s+/v7f//v8/u//Pl/3dV/H+973Pp544okD13wrj73fMdHc3K8oz0vOkt+WqkTYE31Lb0k2u4Unx+PM3YOfH3TArd+ZoNhtCLGKBvvvSwIhT6VdLan2BSFk1UVpFZmerLUyL9NP3b2Gj9hV0TUdfbtoieYfh/rJnQmxLT8fRZHbFF02fU0XgrdxbnzONdHvtC7A2nM73idmCfIMK9igKDL00Sq5KdNNhWYSV08Rl46hmh6l6jRmuEHcX6VrzNPWphhECbbroU+fYenqJbpL57F1jYptkuYFz68OObfSJ06FEJSrDSwNoigkLS0QNh4mnH6CaOpxwsYjdEunKDkORtLnQIOWJICVL5Ff+SzDq08zvPoM4eXPwbU/H0+j3VvUPRNdUwmT/VqoNMtJ8/yuEwlp4Rz8a64fJkRJjqXr+zZAx9RQgNVeeOBz7yVk1L7K0YZDmGSs9yP6YcJUyeSxxds37rsfce7cuX1tJIDPfvaz/O2//bd597vfze/+7u/yF3/xF3zoQx8ijuM9jzso2Pl6XO+iqygK+ZjEH+bLtpt0fdd3fRcXLlzg27/923nmmWd429vexs/+7M8e+Lxbeez9jgm5uV+hqjB1BhbfJtURRQOjJALnhadE1Fs/Jt/sByuiwQGptIw2AEWIwp20NuyqjFFHAzlmGsmP35LNtnFyx6gvHokGyK3vrxapY8Fxf0mqPbuh6UJkGifH4tpQqju6DVxXRVAQDVBvLGR2p0R3Y5bl77Yn1Z3h2jh3C0ynRFUdMQgSlAKKXWPVhWYysOdJph+l8sjfpLp4Fnf+NI7nUdcTZqdnmD75BOvGIolRZkHZxNNyTF2l6hjMli1WegHrA3lNrmUw06gy0Kskoy4kPnmhkGQ5nTBHcWtMueNqmmpQFDJ2/fL6gKevtHnh3NNcuHyRcz2T50Zlvjws8+zQ5erKKuG1v9yZHrtHqDoGR2oOrVHEMEy3f/H7ccraIGSu6tC8i6PVMK4WHbLBxGlOlhfY5sG/Bj1TZxCm+0TGrwZKls4jC1XedqLBV5ys87YTDZ48WqM5ITY3jU996lM888wzvO9979t332c+8xmOHz/Ohz70Id72trfx0EMPcfny5T2POXPmDJ/73Of23Pb5z3/+ltbwyCOPkKYpf/Znf7Z9W6vV4sUXX+Thhx/evu3o0aN88IMf5KMf/Sg/9EM/xC//8i8fesxbeez9jElb6n6GOs6HKs8eLLx16kJ2Wi/BqC3VC0URMW3z1N3JlmqcFLLRuyoeO1vj3lNnZCprS6ORRkJMnANGmmEcWbG5Q14OQxpJm830pK2VBLsEzYqQFr8j+h23IWRne3NUZI1X/kTaeqaHoupMeTNcUTV6hU0tbZObIvCL05xBlHCk7uEYCdge1pG30XBrckzdohNkjDp96uU6SrCBmozINNngdU3FMXRWeiELVfE1OTY3i9Y/Tq/fpZ3YREnMKPPQDIs5zSCOfEbWNA4KF9aHXGr7EjqZDuleWWE1dphy4eyUjqWrRGnGlaBMtLzC0eoK1uyDd/yWHgZFUXhwpoShqaz0AlZ6MQWS4H2i6XFiyrsph+GiKBhGKXkuraUbBVc2PBNtUyFKs32TXNl4OqrmHqxfyYoCTb2bHsS3Du8O9Eb3E6IoYnV1dc8o+E/91E/xzd/8zXzHd3zHvsc/+OCDXLlyhY985CN8xVd8Bf/5P/9n/tN/+k97HvMP/sE/4AMf+ABve9vbeMc73sFv/uZv8vTTT9+SzuWhhx7ive99Lx/4wAf4pV/6JcrlMj/6oz/K4uLidkD0P/yH/5B3v/vdnD59mk6nw6c+9ak9xGc3buWx9zsm/3MmEBwWpeA2wP4KaU9liVRJ7qYYVVHE36Y0Nw7kHOtArj++ogDaXuO+3cgz0ZPEI3mu4R08RWWVoNcV4lZZEAPBPB2THUvITjKCuSdlGisN5XjRQAJNNXtc4cillTdco3asytlpjyvxLO2VZbKkR6pZ6JrKfNVmvmpDd0UCSZ3aHo1TmiUUFGMDt/0VAtuQNk6aF5iqglFf5Pj8Ev1Kiatra3QwKbsGdTNGz0esFnWGYZPyap8rbZ+Ga+GYGkmnxTCLqNglhqnKRlBwtCLCWkt36LR03LWrLFxPbvJcSK2q35W4DV1TeWBGvHEGoeitXFO76U18cxhxre2Px8XB0CWA81jTxTX3H6PqGCzWbS63fKq2iWfJ58qPM/w4ZbZiyZj+ddgiUKdnX11B8QS3h49//OPMz8+j6zr1ep0nn3ySf/Wv/hX/w//wP2yb+O3Ge9/7Xn7gB36A7/3e7yWKIt7znvfwEz/xE/zTf/pPtx/z3//3/z0XLlzgh3/4hwnDkP/uv/vveP/737+vmvNK+JVf+RW+//u/n2/+5m8mjmP++l//63zsYx/bbmdlWcb3fM/3cO3aNSqVCt/4jd/Iz/zMzxx4rFt57P0OpXjzhDXdFPr9PtVqlV6vt0c8NsHrHHkGVz8neUnedZlQWQJrz0pVRreEdOi2jDrPPSlEZusX3HBdNCZuQyo3/VVpdyW+RDf0rgrZOfbXpKJTFNC5CMt/Ia275oOyyTceEBKUZdL6ajxAYDcZ9DqkwxaaYeGWqpQMBSUZCtlKIxHu7jLUa49inl8dMGNGqIA/+zaKXeSnFyRoqsLbTzbQVEXWuPQFNjfXuNIJaShDNKWgUA2UoiCsn+a8eYaNYcSRuretz+itXmT10nPYtQX8TJyAH5vWMccjxWFvE9WwOftXv1HOE4/GU2nLcu1NR6pVpdlbimq4m1gfhDy33CfLCqquga4K8esGkpz+6EL1wCpOmuVcbvms9AL8OKMoCmxTY65iE6UZy92Qumtuk6MsL9gcRrimxhNHa3c0rfV6QxiGXLx4kZMnT2Lbr65Q+s2Ad73rXczNzfHrv/7rr/VS3rS40Wf0VvbvN8//2gne3FA10cwsf0n0OE5NtCVpJNNSnUuioY36Um3JMiEx01+Eh94Fs49IxcedgtoJEQqbjvj1WCUxK/RyeOBrhciMWkKUFKRyobsyCh60hahE/fHCCnlskeE0H8TREmiURQOUZ7LG2sPSwvNbsPKMEC/DBUXaDq6WkQy7qLMP7yE2RVEwDBPOzJWFcABYJfKZx9hYG2IyQrFKZIpOoRmkzgxR4wylROO5lQFHGjvRDalmUgCKkuHoKq0AgrTYJjdmEdHXZ0jzHC0ewsrTIhq3ykJmwh4M1uU9mHn4rhCcYZTSCxLyvMDSVWquuT0Zdj3SLOfS5oiiYI+Zn2fpOKbGSjdgpRdwanq/58fuatEwSikK8CwN19RJshxT01jthXSCGKVQUBQRPz80U3pTEZsJbg2+7/OLv/iLfMM3fAOapvEbv/Eb/MEf/AGf+MQnXuulTXATmPzPneCNg/KcTDy1zouzMAhhGK6BasjfveZOlaS/LEQlHsq/j7xNKjgzZ0WXs/YcdK6MW2OL4nZsjv1/1p6Tv9s1mcjSXDH5C7rQPDkOHl2S49kVqfa4TSFh/RVp4xz5ClmXqo6zsHJZy/o50A0ozWGZHotGysvFAqk+RzkXnUeYZJLHVDKZq+4yOSwKktgnTKGk5ahJTGZVSMrHiKoPgqpi+y30YJOsG4BSgSJHD1qYUQer1SMuHQF2/I3UeECIBuU5+YWw+ZJcg+qRnVaUWRJRefcSOFVxtb5NZHnBxc0hS52AMMkRJTZUXZMHpktMl/eLZntBQi9ImC7trzaoikLZNljthRxtuIdORx2UR2VoKmfnKyzWHfqhjOHbhkbdNe5uwvgEbzgoisLHPvYx/tk/+2dEUcSZM2f4j//xP/J1X/d1r/XSJrgJTMjNBPcWYU+EvmFPNnxvSqont+Oroiiy4XrTUlXIElj7siSWrzwNRQIjIFsbe/TEQniiPgR9EQMfe7s8b7gGFDuxD9EALnxaCI2iylr7V+U8dlVM/qx5mSSrLIj+Jk/BnZZWkaKO4yPGIu3Bmrzm0ox45Cx9UUbVDRumHoKgJe2w6lGmTv9V4qzG1W7ExjAkz4ux1b7NqenSTqulKGDzZbSN5zGzkNBZQLE0tHiAMbhKAWhpgDPaoBGmhOsGtNuQZXilObpenbR3lXz0ZarODKX6NEYSkikGbfsEJ2bm0OKeTK55U/s1Npoprbre0ljsfYjuamvqTVHH13PvcS63Rry8PqLmGDQ8ITJbEQPPrfR4Uqvty01K80JMtQ/Rv5i6ih+npFnB7RgZl22D8sQYb4JdcByHP/iDP3itlzHBbWJCbia4d+hekQDMJJAWT57JbaVpMdwzvVc+xkHQLani5JmQhs3npV1kl4VoDFYgj8XHRtHEmLBzHr74K/DSHwgJQhGS0TglLa7NFyXAs3ZMzP9qR6VK07ooz6+fhMqcnBd20ttB9DrVozsuyFt/xkPIGkKaVp8WYqCosq7SLMw8CqMNlDRmsVlipupujx5bhkrZus5/JehA+zy6W6c8pXCt42PrNqnuoIZdykv/H6kzRcdcYGZaI/F7+GGCa4Cejqg157lMhcGgy2MsY6U2He8UbaVGbWqW2YqN3+vQ6mcMQgVVianbGg1H3bH7Nxx5vVkM6nWxGWkklbDBsrznqibTbfXj2+nsYZKx1A2o2PoeEbE2ThCXKapgH7nRVWkXZePK1vWI0xxdU9EnsQQTTDABE3Izwb3CqDVuv1h7wxnzTISqPCu3jzYlpFM1wGlK1eNmqzp5KlWEOBDdjOEKIdkKt8xjUMydEEy/IynnminVmO5lMQRsPCAEpvmAPD/sSnXIa4r4t3dNWk/hQCo8ZkmqEVkq6zcdIWz71ldIW2z5i9LKcWSDFzfkC/K67YYEhNaOYmjGjZ15Rxvbk13NUkp7FNMaxlQdA4scLdikZ8ziawqPTikE612uJBadUYK5eYHUGVIyK0xNeTjGCTbxCMsnOVr1ONZ06QcJLy75DFtglDJy4HIvY8pVOds08Ex1R0d0vddQGsHqM9IKtCvjMfoURmtCPOceh/Ic/SBhFGUsVA8Ws5Ztg9YwJk7zPfqbqiORA10/3uf1khcFgzDhodnyoS2pCSaY4P7ChNxMcG8wWJHNzZ7ZuS0NhTwEHbj2OSgvgluTastwXR5TOw5H3g71o3uzog6C35LqiV2BqCutqGQkAmDTG08zRTLijQKk8qddhakHpG0U+0I+3GkhVooq7autiSxFkWqFZoomp3dVCFWayMZdPyVmh7urUHkqzysyITG6I8ffglmSNQ1WZdw8SaTScdCI+27Eo+1r4pk6D0yXuNbx6QcJ1mCDPAHyhBNTJWaNAEVZYdpM2MwhsHNse0CjplDRWsTOFLmpoB9xsL0yvSDh3GofdJfFmgOKEMYsL1gd5mhKyuMzBlrYlyrW9e/N1mRVZX6ncqUZcu1Gm6LjcZvkBajKfufXLWiKQlwU5NcNceqayslpj+eW+pKv5Jjo2o42aapssVA7IIB1ggkmuC8xITcT3DliX4iLoshmDUI8zF2TK6NNEaPGPgw3pQWUxjCw5Dml2XEl5ooQkujxvVlR1yNLpMVVFKJrGa7L87eEu3kmE1NpPA4HTcWBOUvkJ8/HfjMFZDn465CMdSLXuyNsTWUZ1s4UVOMEmLZUY7ZeM4wrU2vjHKcMyKUSVeR7qx2aIef2W2N9y01UHDRzT1Bp2dY5PVthGKVkuoVZ2JhzdcyqDYMe+BtUDY9qsyKEzS6gVoU0RA9WwTTAkF8BG4OQMMlYqJZBmRdSpqhohsuMp7IxTOhqHZqeB9WFvevKc6lume4OsdkNpy4aJ7+NbdRRVWVfZWYLfpxSsnXMAyowM2UbZVHacR0/JsvANBROTLkca3g3NPObYIIJ7i9MyM0EO8gzQDnY/O4gJME4MXtVqiaKKtNFW22oLJafJJTNEsCsgtKSNk6ewrAr3+4NZ6fagSLVEachTsjXY7guGpn150XYa5VENzNYkbZRPJR15GNHZa8Jo65svFuj1oqy41BslsTvJmjLeuvHd85VFKIjiYdw9c9kEioeykZempOqUzCe0spzITGlaZh5RK6NVZFzREOpMO2Gqgu5mTp9c/ojb1paabvCTDUVqo4OpRIMAG8cV5Gnsvatke082SGKuj0mpMl2vtbmMMYdEx3K89JSG67AcB1DUcgChVGtTHP+kZ1IjC3k6Tio8xAiqmrjVmFCtWQw5ZmsDSLmKjbqrgpOlGZEWc7pmnOocd502aLpmQzjdFt4fZB53wT3HmmW75kou/7fE0zwWmLyW2EC0ccMVmSjBdlEy3N7zOb2YUtjMRjnPTk12eTCHlz5050gTqchf08jISrRSDZWRRciUJ6XqkLiywZvenK/bkkLqHZ0b7vGb8t581RISBpIHIRdG2t25kXrYzhyLMOV0XA2IQtlM98iNZrJ2MhmTF7+XNoq7csQDoUMDFdlEsvwhCCompwjHknlSNHk3IYrU2BuA9wmhaqDZqFsvcbNlyDaNT1UjNO5vVl5jTfj/us2dya13IYcayvRPEtE1LylL6IQ0ue3IN+Qa6ho8rrjkXgCWc4eIrvdKlJUqB2B0pSQxSJDcQqYXwDvAOMsVRMSlcWAt316IaqqjHoDqCKQfmCmRJzlLHcDPEtHVxWCJCPLC441HGYrh5CkrdOpCpXJZNNrBsnaKvj4s6t87JkVekFC1TH4psfnefdjc4By6FTbBBO8WpiQm/sd3atCBvJk3EYqoHNBQihnH5XN9CAMVuWnsrAzEqwZQjo2XhhXKqqymQ7XZNO1xhEH8VAIVD7+tp/44wqKt5Nxpds7lZ/d5KZ7VYhSZV4qM04D/E0hFvWjon8pz8OVz8rzikJaJmFPiE3jhLSBoqEIdFVdRsU1S/Q/eQbLX5D0cRS2g4XG0z64TVm/osmPvym+N7oD02fphimr6wGdUQKJyVRfZ6biUvVmYXBNzqnb46qSAcf/mrSwbgaaLhUh1ZSqit8Za4JcmH9CCN3mi/LeDdelFRj1x9Nq9o6uyW2AVYVoXFGySjQ9kwsbI6rOrmutS8BomuWoeYzrHKKBUjUZDV/7soSMBp1xEGo4ng6zhHiOKz5l2+DxxRrrg5DVXkiWF0yVLOaqNlMla7Ixvo6RFwX/5cUNfuS3nmZjGO2572PPrDJdsvgX/80T/FdnpvdU5V5vuHTpEidPnuQv/uIveOqpp/j0pz/N13zN19DpdKjVaq/18ia4C5jUEO9nhD3YfEEM5SoL0jaxq7JRKaqQlIOSootCNlBzVwZUUUD3Glz8I9lU455sqmFX2lJFBq2XxxqTmbHD8LiCsRuJLwZ5qibVnV0p2ySBkAm7Kv9WNakGuVOyocYj6IzbNrVjEspZnZNN1a6O9SqKECKrIhWfLJVJrRPvgLknRB+TRkL0rMo4U0kVstO9Jq2maDR+XYE4I4d98FusrK/zpStdLrd9sqIg0z2uBhbnz32BzuoFIX55LIRDt+DM14vb741QFHI9V78Ml/5Ypq+sEsw/BUffLkaBx75SjAnrx2Hxr0BpXipcBaJbOvpXwZ2RqS7LE6LmlKXqtfoMxCNmyja2odLx4z2nz/KC9WFE0zOpuzeY5KrMC2m6+jmpdEV9eW9Hm7Dxoryv6c5m6Jgax5sebz/Z4CtPNXnyaI3Zin1LxKYoCnp+wsWNIedW+lzaHNILEu6zRJlXDVle8EcvbPBd/+7z+4jNFjaGEd/17z7PH72wcdfT1N///vejKAof/OAH99333d/93SiKwvvf//7bOvY73vEOVlZWqFard7jKu49f/dVfnRCu28CkcnM/Y7ghG/TuUe0tuA2pkow29+tB8rFQV9u12fVXYPVLUgkoLwhxcqqi3bArQm40U0iUUxMSohrS9lDUsQ5kNNaszMjz6yf3CorzTO7fbR6n26JZCTtjHUksm/hD7xIiEfSkYtFfgdaL46ykWAiRqkm1Y/GrhAh1LsrtijoWwW6ICLpASJlbB8ZVJU0TjY2/Cd1r+FaTi1EH3ZneHlVWoy6OPcK3PS6nHraa4tiuXAunNj7XDTbzohA35tZL8roNd1wJW5fnzj22X8fjNmQirXpEyNloTYiGXQJ7Uaopw3UhPTMPS4Wle5XqzFnOzFV4cW3AUtfH0jXyvCDJC6ZKJqd3R0BsIY3kXHkq18SpIcGn1li0ncl7WZqVyuDmS7D41j2vWVEUbseaJssLzq8Pudr1ReuhqBIuqo841vA4OeVNAi/vOgp+5LeefkXSkuUFP/Ifn+azP/Y37/oKjh49ykc+8hF+5md+BscRvVgYhvzGb/wGx47dvmu2aZrMzc3drWVO8DrApHJzP2OrgnAYdFPIx/VQNXleNv6Wn4Zi3IYmFY8tHYdZgtqCVGLsmpADVZOqSu2YbIjdq0KIwr5skpVFSGJ5Tu2IVFb89tgPJ9lpY4FsnsN12HheyNJgRTZ/rykVCqcubahjb4eHvwke/q+FELhzcp7maTjxTmkNhR0hHWF3fE1yWU/sC0HKQkCVTXrrdRfjVlviMxj5+Km2p61jDJdQ0wBr4RH88gl61bOw+BSc+CpZ49pz0lra1slch+G6EBurvEMKvSnx5gna8rrz6ypfaSSap941SH0hia2XhdyN1sdTXy6JO01QGIR6ZSwIj5ir2rz1eJ2H5ys0SyZzVZunjtZ44sh14ZHRUMwTv/jv4Qu/Bl/8dXjm/wcvf0rWN/8W8bWZe1wyvcqz0oYcbcj1vQu41vG5sDmibBosVF1mKjYLNQfX1Dm/MWS1H96V80wgSLOc3/vy6qEVm+uxMYj4+JdXSLP8lR98C3jrW9/KsWPH+OhHP7p920c/+lGOHj3KW97ylu3bPv7xj/NVX/VV1Go1ms0m3/zN38z58+cPPe6nP/1pFEWh2+1u3/bLv/zLHD16FNd1+dZv/VZ++qd/ek8F5Z/+03/KU089xa//+q9z4sQJqtUqf/tv/20Gg53fma+0jkuXLqEoCh/96Ef5mq/5GlzX5cknn+RP//RPt9f1nd/5nfR6PRRFQVGUPcnlExyOCbm5n6Fq4wmpQ5BnB4/2KopssLE/FhGPBcFWSaoNsT9ugZSkreTUpeqQpbKZB10R6NZPykY//6Rs3E5dtC+lKZg6IxNTL38CLv5/oqFZ+vxYK7O5M4G19AWZIPLb8vioB/318ehxaxy/MBDxb9CS9tTsGalalGekehQPRUTcuyZkq3MZ1p4fZ0RpsiGnyVicmwGFVFKioRAPRWGUmejOTklbSQOMYJPUktt0XacVa7Qijc76NYLWNbj6WTj/B/Jn98p+ojJYlnNdXzlTVKmIjDalHbf7/Vp/XkwBDVu0R1NnSUoLRJpDjElSPU7bmOVCO+HLyz2e2wi5uN6hM5D2Y8nSOd70eOJIjUcXq8xV7b0j29FAWk8vfxL8DakUlablM7D50rht15f3067sfH50a2dU/w4RpzlLnYDSODRzN1xTx9I1rnX8u94WuZ+hayofe2bllp7zsWdW78n01Hd+53fyK7/yK9v//rf/9t/yd//u393zmNFoxA/+4A/y53/+53zyk59EVVW+9Vu/lfz6/2OH4DOf+Qwf/OAH+f7v/36+9KUv8a53vYt//s//+b7HnT9/nt/+7d/md3/3d/nd3/1d/uiP/oj/5X/5X255HR/60If44R/+Yb70pS9x+vRp/s7f+Tukaco73vEOPvzhD1OpVFhZWWFlZYUf/uEfvpXLdd9i0pa6n+FNy5hznu3PCdoaJT5sYqo0rn70l6RaUuSSnJ2G8rzmyb1mbpoOxqyQIsOR++af2PF4CXtyTlWXHKiLfygEw7BExFueHwtp12Uj7V6B1oWxJgZpRxmeRDCsPSvtmNKsVJH8rqxx6kGpINWOyTRYbwmu/JlMREVdYNweGyxLlch0pOWVxTvj7sM10RolI7YNAe0aeeUo2a69VMkzua6GQZLmrPQCDAXijTWcYAVVd6noBk29jJGGkmyehBIJseV+HPT2egVdD78FK1+Sa2NXZD39Jageh9EGYZLTHcQkoUqseujdId2gDXmCOmNSMg3yOKDlF1xdHfGw7h0YWrkH7UtCKjUDSos7/jyaOSaXAxgsyedmd1WwKMavqbsjMt7K9bpFjKKUUZQdutayrdMJYvw4neRF3UX0guSVH3QHj79ZfPu3fzs/9mM/tl31+MxnPsNHPvIRPv3pT28/5n3ve9+e5/ybf/NvmJmZ4bnnnuOxxx57xXP87M/+LO9+97u3icTp06f5kz/5E373d393z+PyPOdXf/VXKZfL22v75Cc/uU2EbnYdP/zDP8x73vMeAH7yJ3+SRx99lJdffpmzZ89SrVZRFGXSNrtFTMjN/Qx3SqoXgxWpBGxpaNJIWgjlBRHfHgTdlBaPVRYBadAHz9yZYtrteRKPhLjMPS5C2INaYd6UmO5d+RO4/Kci1NUdqUAkgUziKLoQju6yVFmKGGonpLLh1OXx61+WCo1qiNhYNUUInMVSkakuCsGBnXyq7lWZsvJbsrYklEoTqmzi1WM7hnzxeLJra1y++SBYHuWZEyQbBUXYw4paaEELfXiNIuqzHDdojxIea8JM1CGvThOlOW0/xh/BibkmquELaShNy2tRFPnJMyEMQU+0QpopP4M10eOAmB7mmcRDqCqU5wgHmyxtthikOg29hFuE+Bn4m1fI6w9StqroGhjZCGP6FAPF4vzGkJprHB5hEI9kSitLhOBdb0pYnhn7BfVkzVvvc4HEXgxX5Rpq5pgczYyvX/mVP6sH4JV40aRuc3exZ5LuHjz+ZjE1NcV73vMefu3Xfo2iKHjPe97D1NTUnsecP3+en/iJn+Czn/0sm5ub25WSK1eu3BS5eeGFF/jWb/3WPbe9/e1v30duTpw4sU1sAObn51lfX7/ldTzxxBN7jgGwvr7O2bNnX3GtExyMCbm5n6GbIixVnpeKSDGOJ1B1EaROn90xgTvw+RZMn5aN3rBks3OnpXowWt/2SCEaSqTC7GOHa3zyXGIQXvrE2AtnJMfrr+xs8hQyCu2UoTWEyhHZZGvHhASFPWlredOQjmCwIWQoi4XsBJ3xyPSYeEUD0QFZrrgX05IKjWbJjz6uRpiunMutS4XEmxUBcpGLVseqUfdcFjYuE116Ac9MUYxxFMDq00Rhk2PzZ2lqPkqRU6gGbtZCK0+xHuo0woSa60rLbrgp5EbVhHxe/P9AycdTXdpY37S+40XTODkeoc+h9+dSUaodZ0ObJfTPM2OpKHYJbdhFDTbwzFmuWPPEgxEns00yq0ZSWqCum6wPQrp+cnj1Jo2E+KmaXM/r4c3I+x50d+mSCtENrZ+TqlTt2M7r6C8JWVx46pZCVB1Tw7E0RtHBlZlhlOKZOu7txINPcCDSLOebHp/nY8+s3vRzvunxuXtm7Pd3/+7f5Xu/93sB+Pmf//l993/Lt3wLR48e5Zd/+ZdZWFggz3Mee+wx4jje99iDUBTFvoiQg6bwDGPv509RlD0tp5tdx+7jbJ33ZltoExyMCbm5n5DnQjZUfedrr+nBwltEVxIPx7eVdqoHNwO3LhWZ1S/LZl+ZH7sCb8hGVzsuGoyVp+V85bnxtNKuX3pBGy59Rp6jqJBHEKvjVtC6kKLKglRXFFU2V7sqm2PYG5Ob8eSV2xRC5U5BMpSv8OU5qR6h7Gy+fluqEN40zDwmm6/5WamKKKpck6KAxgMU3gxKPHYjTkawcQ76a+P0awXzhf/MmRzWrJOsGqdJUx3NPEVExHx2gUYMmlKCPEX3N8lMj7yySB7DIEyouYZUM9JdmpQ8letiutJiU8Zr3xqrbpzaIQWKKoT06ueIhm02lCbWjEWS9VCTASk6w0AlduaoqjGBn9GvH0NrPkBultCAgoL4RgJQVZc1qqpcvy0CtwXDlmpflghRKwqpKvWWpCU4c3an2qOPH9u7JoSy+cDNfdYA29CYr9i8uDbANrQ9laYwyfDjlBPNysQt9y5C11Te/dgc0yXrpkTF02WLb3xs/p55Fn3jN37jNkH4hm/4hj33tVotzp07xy/90i/x1V/91QD88R//8S0d/+zZs3zuc5/bc9vnP//5WzrG3VgHyCRXlt1AGznBgZiQm/sB0VC0Iv1lqYCYnhCF8tz4W7g6dta9gSPxK6F6RDa+7uVxMncuo8hbTsRhV+4PurKh1Y7LZrel9dl4UXQ0W4nd8VAmlLaSuLNYnJRBtD2aIcJVqyIkxZuSytNWVcCuwsITkhelWWO33k0xubPKsvFGA9Ht6IZUaawZWHwbbDwHdp3QHzBIFdbsh8kLi4odMxX8JaU8G+dPZeNqlwGDNayox5FSn6YeMZh7O6Q5K8MyZubhrX2RAhVV04ibZ0B3MIZLlGKN3JqFwpVJrK3KVhrLNZt5BMK2jKUrCKEqGGuQdCGsiiokwnDAdMm6V/DzB4lw2CxsVH0OrxTSTmfplR7A9qqs+zlubZ6qKa3IoigoCgX9RpuRVd6Zeoq7+7VaUU/ej5mz0m4qciGjRSFE7HqyrChyzP4y1E/s133dAMeaLlGasdQNAAVTU4mzDAWFE02Pxbp708ea4Gah8C/+myf4rn/3+RuKtTVV4V+874lD778b0DSNc+fObf99N+r1Os1mk3/9r/818/PzXLlyhR/90R+9peP/g3/wD/jrf/2v89M//dN8y7d8C5/61Kf4vd/7vUMDXw/C3VgHSOtrOBzyyU9+kieffBLXdXHdyef7lTAhN292BF0xags6O+Z4QVvITv2ETA3dwqZyKBRFyJI3I8SkyEU3k1yVoMUtcbGDkI/2BRH/1sbeFN0rQoR0YzzuHY6dg8fJ0nkqx0x8aWeollRt4kAqG1vOxuFAqj5TZ8bnDIUwdS4JOXIboq9Rxh43/SUhR/1rcj3cGtg1hkHERi+kY84DJkpe0Oq1CH2oTx9hNhlrT8pzQozyBBQVlQJv/Yt40TpYZfIwolfk5FaJvNDQB5dwgk2yylHi2gMYYUJJ3QRTnIK3nZDjoZCv6oL8hD25bpo5dnielarUYJx1FfaBApKIYLRGb2TgayVcQ0NLRowo2LSO02GKGd0ht1K0XZqZfiiBlTfUSSiKXKPRhqxtuCpOx1sTZUkE0w+NJ9HG4kdFFfJy2KagGTueOLfwOTQ0lTNzFabLNhvDkDgpsA2L6bJF3TUnHjf3AJqq8F+dmeb/+o638SP/8Wk2BvsrONNli3/xvlfHobhSOSAKBFBVlY985CN83/d9H4899hhnzpzhX/2rf8Xf+Bt/46aP/c53vpNf/MVf5Cd/8if58R//cb7hG76BH/iBH+Dnfu7nbvoYd2MdIAaDH/zgB/m2b/s2Wq0W/+Sf/JPJOPhNQCnuMzvPfr9PtVql1+sd+p/jTYM8l/Hp0YZ809/9yyaNpBqw+JaDTfxuhKKQnxsFbEZDuPzHQiKs8n6tjd+SCsyxr5RN7c//L9HXpKFsdK3zQsKSQH7S/3975x0mdXXv//e3TZ+d2Z3tbIGlFymCxiiK3sRgx+gTjRLUn+WRezUKETQ3mqsxsZfkggLRa5QkJupNEEtyJWholiiiKALSYdnG9p0+8y3n98fnzMwOW1gUXFjO63n2Yfdbz/nOMOc9n8otE55CWlBNncSOESUh5B/EBU+IhE3FqTywNUjnHviC5lt+Kl0j1g6AURCyEafYoorTAJsbens96r/8F5IWg1o0DpbmhKJHwQAkY2HEJRuGRzZSETF7Do2jdS+lRhsJupZB7q6obmC/4YfXbIcNOtREO6BHoMgKEpofUW85Cl0KHNCBkecDoy+meKOmbcCuf5J7MCV6nLm84u82KpDYXkuuINVGMUOShGhLNb4MedHAfLBkFX6XHbqWg4i9CHsTbkR1C8xiGJTnxEmD/FRsOq4jYZgYVexFeV4fYl/CjUDjNrKCRVvotXDkULuOVAZc52Nr1tMz766sQLSFstzKv9X3hq2WRe+N0AFyEaoOur4rv/cYMQHi8Tj27NmDIUOGwOHovYdXT6SsNm99UY+/b2ro1FuqGOeNo2DYgdhC46abbsKXX36JdevW9fdQBjS9vUcPZ/0WnwQDmXg7WSvc3VTCVe0UBNxRQ7EPfVlYkhFaUEL1FLtj99K57oLs840EBZDWfUaLnqRQXI6nKJMZY/PQt389Rou3K0ALoTOP4lli7bRoySpZBIwETynnBfaSYQoENg1+rSiQ48/0pKr+gISLq4DOsXmAPA9ZQBJhEgQ2D09LtpH1pmU34AognDTR4J8Enz8AiVE6a9xbCSbJcLRuRTTYjngsAqdNzVQ8DtVTvJEzj66bPACoNjgtE4XR/YgkGaJ2LyR3GeyhWijxVmh6BAGHBod9GGDZybrUtI3EaPgAd7HFyOUUaaKg5pxisni1VfO4ENLa2QAAV2tJREFUogAJHQCItaFNLUCLrwIBxcA+lKBJ8sDlcsGmqgjYDASbI/A5NHgcGg4E42Rws2sYUuBGySEaVqbxFNJ9i8fyqtKMYqp4zZ8snHmUnRZt7dpDy9TJ+pY/4jCEjUmiqnUPSJzayd3YsZ9crYVjei9MKfjapITL9LHFuHB8pvecYVoDStQ8/vjjOPfcc+F2u/F///d/WLp0KRYtWtTfwxL0ESFuBjLJCMVBqHZAjlNTw84fPhrvwG3pZPXojc7uLZubREeonhb3vKGZBcpIUmBx0zZa9DQ3CaFQA10jMIwWwlRPqdRimDeMrB8AuadSC5epcIEkkQjSw0AkCkCi+ckyILvp99Y9JID0GAkAm5cWPk8pjyeSyf3kzCW3iR4jkZRq6+ArA4rGINiuo01R4cx1oXNOg5wMgika7LBgRFoAOcbFFqOF2tBpjrJK9zKTkCTAb7TCprqR1JtgRnVoOrnb7A4PHLJJFoecIgq83fEPcv3kVVHQdNtewO2nMYZqaV45gyhGyeQ9uyJNZL2yu9GgDYZD88NltKLCbqFW9qIjlkRH3IAsS/A7bfj20ACGFnqQ0C1EEjqiSRM1LTHsb4nC79JQlONAntvWe3yBrPQtTktRKVC7YRO9Vxw+LlijJM785WRV7CvBWrLqufKyA5pNnVL6Vceh+3UJjggHB2wPtADujz76CI8++ihCoRCqqqqwYMEC3Hjjjf09LEEfEeJmoBJuAho+p0Uw1EiLkTOHvv07/XQMMzPZK7F2Xp/G1rXuiGVSg81EiARAatFz5JBAaN1N1/QW0+ITrKXF2YiTVcPmoYUo2koLkN1L7iJXPq8nA1rkCkZSPRRZouulgmVTDSyZScInVRnYW8wXeIOOSwQpBgcmCQBXLomx0Ge0+OkxCsoNNZCocfgplseIU52eUB1QdTaQjIF1BNPTl4w41FgzlEQ7pEQQjlANZFOnayoqxbuYSRJ9lkHp0JqLrE3Bekh6DG7E4LJ0GMyiWoGaBkmzU3Bw+x5eN0Yhi03BCHrGOaXcfXiA/k6GqWVD/nCg7Fu0XY+Q+03RAFmFs2M3VEhwySbsjjZ4KwoQ8ufAsBgUSUZ7LIk8tw05Dg2NehzVrTHEkibcdhWyBNS1x1EfjGN4gQcVgb6nZ/eKp5Ay8jpqyK3GeJfy4pPodVJ6ifM5+H3YzqsvH5yppWj0ngnWU7C6TQRcCr4er7zySn8PQfA1EOJmIBJpJmFjGVQUTrGRFSTBS+TnjyBXRpyXya/fyFN3DV4nppDqp6SaMsbayL3lKejqdtCcdN2OWhIrwVpa5G1OckO17iFhojroW3usjawnsj1bKDn9tACaOi2CWoQCVm1uQPPynk5SJh3ZU8zjK2yZZpCKCtidNP/gfhJs8TYek8KrCjOTtwCQAWeE5mzo1Aiz9hOg7FR4XYOhyjJ004Ij2QZH6zaokVoo0WYosVawpk1wsgjQ2sCtYQo9A81Fz1qWM81DI038QUmQGIMGntJp6iTMPAG6f7CG5pRUqdkoQPMJDKW0+lgbxZnIdnpOkWayYKgqBUhbFtBejeJgA5oMFxRPHhSmQ2vcCNU3BMmcITAsBjUpwWVTEddN7DwQhmUxlPozQsHr0BCOG9jVFEaOU4O/t07gh0PKypOqZq3YDz8+Ro9yUdqDr93mIetQMiLEjUBwgiPEzUCDMXJlmAmeiSRRt2tIgCOX6rR01JAgMJO0SGoO3tRSowW5aStZBSq/TRYSPcq7cffwdtFcZNUx4jzwl8du5JSSwArzqrWyTBYlTxFQPon+7UxOCQUYt+wCrDi5j5hFwibJ08GTEYqlkVPpzy5Kj463UxyIkeRp4lGyFNn9vIs3F1jBBgpCjrWRy0yz0zW8JZTGvu89+CcMRmGOHQeam1ER3gRH6ybYW3dAjdTBjLXBnuiABp2EnWmSpUmSeVo976XlKSQrAyRQLypGViwjRs+ZMTpHj1LMUiIMBHi6euf4k85p+vEAWXfchZRdpkcAdznNq20vYCVhLxgCubEZsVgEatFEyJoDtvZdMFQ3Go0cFHjsyHPbcCAYRyiuo8R3kAUEgMehItiuoymUOHLiJv1e6Xq/vsOrNvdYe5hvP8pZOgKB4NhHiJuBRiJEi3qqbUJOKQBGrphImBbY6N6MS0iSaCHW40DHXrLQGAmgaQdZI4ZM466rXpLqmMVjX1T6MXVAA23zV2bq1lgmfbsumwLkVtK5qWwogNxPzlyyKpmlZJGINJNrzTJpvLE2Go8RJ+FkGkCsmc63LL6wSRRrJEmAwuOAZJnGkAzyTCuTzlfyuRgKkTCp2QB50BSM8BTDXr8Pyu5VkDu2wdKjSMCCpjpgYwlohgGYMQCeTDq05qR2EEHe7sEToGcTqiVRozp5jI5E7jUjRsLMlc9TphsoeDoRAdx0WBbxMFWNtnQ6JreS92oKp2v+uJmJfKeE5jhDa8yAImlQYzqijfuQVz4Zw4s8UGQJ0aQBWZZ7jKtxasrX6g3EGEMoYSAY08EYYNdk5LpsPbd26Auai6w2sXbA003wcyJE76/e+nEJBIITAiFuBhqWwRdtHscgK2TBcRfwYngGLfx5gylWxl1AYqZlJ4kihxew59H5LbtpQSkYSdaBZLR7c38iTK6uVCfqpi8pNTneRu4iPUqLt6RkGm4aCXJZBevJkgKZ7u3w8/gai7pPJyP0u+YigaJqJMCirSR4LJ2uJavcksNbJ5ghsqowHlNjJnjFYZMsJ5KNW5gYz55Kkmusoxb44i9wuPIxvOEL6MHNMM0EmAzIkKB5cqGGowBTSTTpIRKQMtX4RfM2Go+3iMbtLQRsDnoOqfgmI0HHphpIxjto/OEGQHEADRtpf15VpilosJanPOfT+VaSYm/CPDU8xisCyypyA8VwmoDX70RQ0qCqfpQ5LXhLXLDb6X2hSBKsXqpAWIx9ZSGimxZ2NobQ0BFHwrAgQaJG8k4NI4q8yHV/RWuQLAO+cnr9E6Hs2DA9RtsKRmcshwKB4IRFiJuBhmKjGBM9ni1ENCf9JCO8Noo942oKHcik6koSCQBFBexuEgehegrebd1Di20qCNgyyY2SaqkA0EIfOgDUfUxiSHPSmOK8maLNzYvm8cBjpx9wFvMqxh3AnjVA6z76hp4I8TgTXiRPyyHxE+vgQbw6d4XpgMatRpJCAsfgoijBU6k1N32jZxZvmcCbYqoOfi2V5uMtJsHl8EGWALsR4tYWABKj5wcGMB7/k4hSB3JHHo052kbXsedwd12YnrfdQ93JwXgbCB4AzUwSVP5ycqvZPWSZqP2ERKFlcFeVSsHgjV9Sar+skKXK6SNRKMn0nF0FgMsPR6IDxX43ih0eIKrTsw3XAjGqAJ3jtEORJOim1UXEWIwhbpjIP1SH8B7Y1RjGvpYY8lw25HuoMJ9pMbSEE9hSH8SEcj889q/40eMtAQq5GI91UKyUxd/HgWGUaSb4ZjD17GDwg/8WCPoRIW4GGnYPVa9t30fCorPbgTH6hp87hFxFkkIiKNJIQshI0P5EO4kCRaPA2GgLWREgU0ZRtBVpn4kzl1wlqSBPu4esFvWf0vVNnRZop5+KvDEL2P8hAEYdulNxPJJM109EqMKwJFMAs7+Czok0UdZX8/bMfYL1FItjWYDO+2YpuTQ2Ww6JiWgLxROlqgjbvDyolfHzwiRaEiG6v6mTZctbRK48gLuUuCBMFRSUGKAnkaoKDKkdYLx9QrydLCreQhJzwVbAGSDPnh4FJCdZ0JibjrfnAIOn8hYSjLckqCWhZHPT65VTyjPCuOAzLSC0k+4VaqAYqXATYNtH8TlFJ9G58SA1JLW5gUaNxqs6kOstRaGnEHXBOPI9dthVEiG6aaE5nEDAY0fAbYNlMbRGk2gOJRDXLTg0GfleO/J6qAIcjOto6Igjz2WD05apOKzIEgpzHKhpj+JARxyewq/oOpIkCnZ3Bei11WP0DF28no6Itzn6pJrYbn0D2PIavQcdfmDMDGDMJaDmu8dv09LBgwdjzpw5mDNnTn8PRfA1EOJmIJI3mBbojhoSFYqNYkBiHbz9QCVZMly55C4xDbLQBGv5YuEgIeDwUnE0gBpjFo8lC0O8nQSH6qTrHfxtLRHiTSjdJBYkmcSIrJLQ2fs+72t10Nsv0kSF+Yy8TE8iRy5P8Y5QJowZp4yhRDvvGcWDTJNR+tBNxmm7rAAwAciAu5gXw4tmKhtDpmtZGokihkxskKLy2KMkPRszRv8aSYAlyVJk8bgdWaHAXlj03CQGKBr0aAsMyGCSCg02aHqMXGqxJD/WSRll3hIKrHYF6BlIEo0jWEtBw+Muze6YrdppjA2bKfMtGab7ugtIyOhxSqf3ltIzq/2ExlowkoQoACSjkFt3YaSfQc4tx4FQHLqRgAQJsiQh32PH8CIPVFnCtgNB1LTFyWCnyGgOW9jfFkNZrgPDC71dapuE4gbipomArXurj9euoTGUwJB899drkeDI6TlrSnD0YBaw8x3g9Vvos6MzW5aT9feSp4Hh3824YY8Q1113HZYuXZr+Oy8vD6eccgoeffRRjB9/5HpZrV+/Hm73ESqDIOg3hLgZSKQsM0acYls0N+/5w3s05Q+n9Gs7/9YcGEa9mGKtdB5Ai64eI1HkKSGzf9tespp4S8iq0NuiYpm04Nrc3dTLscgyE23hNWE69RMyDZ5O7QbsSV5bZydZZ/QQz5oyyO2SirWBDihOupbqIPFhc9MHLAPF1tg8QG45BSVDzqS7ywoJBUkhEWDyoGibh65T/xl9G3XlAi1tAItmmowyxuOrLcACna9QurmhaIhJLhiRKIKWAUtVYTc1eJJhOBVAyykmS5ckAbWfZaooH2xxMA2y8ijdxKcoNrLSJLlYSwS5+OK9p5y5NF9m0U/5KRlhA6TdlfZIPcaWl6M8Nw+hBAX+umwK/C4bFFnCvpYI9rVEsyw7AJA0LFS3ROHUFAzOz7bAWBaDxHoWLYokUZPOnt9BgmMVyyRh89IPufWmG8KNtP+HLwHDvnPELTjnnXcenn/+eQBAQ0MD7rnnHlx00UWorq4+YvcoKCg4YtcS9B8Dq6TkiUwiRN/S939I/zZtJcHiLqB+SpWnU7dme6fFyJ0PlE2mIM1QA9VXMZP0gWQmgfa9QO0GiqHZsxrYvZauHWrgXbG7g6dFW0b25mg7cGAz9XgKHaDFt2ETZUOlYCDREmmisdhzyFJCSoWPywASbZkCekaSCvepNooR0uw8hiZB4q3qDCrMVzKeRI+7MBN7YyQovsWIAZJFYkFWeSB0A1mtVBePaZFoznqCApVh8lotqfglE1YihHg0hLAhw5QdcMkm3AqDbBqIxE1EDBmmM0CCsnkXxTIlgpTt1VGT/cwSvJ5Ld99+9RhlZEVbScQGhgOFI3nDylLef8tFr2HppIxVqDM2F6DHIcWD8Lk0lOW6UJ7nQsBjhyJLSBoWatti8Ni1LGEDADZVhtuuoa49jqRhZe1zaAokCT12jY4kqUFnd2X6Q3Ed+1uj2NcSQX1HDHG9hwVU0E8wstj0JGxSWCbw+q3oNcPyK2K321FcXIzi4mJMnDgRd911F/bv34+mJqonVVtbiyuvvDLdkXvGjBnYu3dv+vzrrrsOl156KR5//HGUlJQgEAjglltuga5nMgMHDx6M3/zmN+m/v/zyS0ydOhUOhwNjxozB22+/DUmSsHz5cgDA3r17IUkSli1bhnPOOQculwsTJkzABx98cMTnL+g7QtwMBPQYUL8JCNfTN3TfIF75VaUaN6GGnvvtuPKA8tOA/FG0iFsmd/EYme7hiRC5hIw4NYes/YRq0XQncGSZ4kMS4cz+WAfQsoPcN5oDyB8KuPPI4pHK0pJVun8LjyPxFpGVSdZoLo5cWqxDdXRtRSXrks3FA6gTQDIGyzRgJiMkRiQA9lwgUAWMOJfmaulIt0tIxii+h0l0jUQQ6Kjj2VYmiR/Vnul2rmo85dsFSHYAMrmWVBcgazCTMUSZE6rdDRuLwxZrgBZrgmZTES8/AwfcVUi27gdqPyLrlcNLIss0yRLTUUfPP9ZGFjNXfvfffPUEPTObkwKKbW6KJXIFAH8pAImy1dRuKvl2ppeaMbGkiWjS7DHw12NXEU2aiCWzF7pcl4Y8tw3N4QQO7skbTRpgAIp92dlMpsWwszGEDfvasLmuA9saQvh8fzs+3teG+o5Yz+MXfHOYOrDl9a6uqJ4IH6CYHPOrlxM45C3CYbz44osYNmwYAoEAotEozjnnHHg8HqxduxbvvvsuPB4PzjvvPCSTmUYqq1atwq5du7Bq1SosXboUL7zwAl544YVu72FZFi699FK4XC58+OGHeOaZZ3D33Xd3e+zdd9+NefPmYePGjRgxYgSuuuoqGIbR7bGCo49wSw0Ewgcoo8Y3iASFqdOiaPeS2yXVVLAnd5LDS4Kj/gtKD5d5byczSYu6t4gsHHoY8I/komQHCSl3N1YBTxGJoVADLdDhBrqW5iKXVW4VxauEGyhGpn0/73MVA1r20nHh+swHYzxCoirl8tIcmeBnk1oyxJmCmKkgntSgMwWGwZCrN8JvfgTJiFNBwpwSKmKYiJCbzs7TxlU7TxWPUICy5iDLUSLIrVC8LYVUQOflDaZ9bfvoPFBtHZPJYCqDXQ+CMQNKMgrTkQvDmQ9PZD8SkQ7EHHlwlozKVOpt3Qe07iQR17IDCFbQOPNH0etnJru6ppIhXvW5O8HKg6KNGLkRoy3dv+6WQeJG7UH88HJBJFD6HhujKjKGF3qxtT6IuvYYb+sgIaqbkABU5btR4Mked3VLBDsbI8h1aQi4aR9jDO0xHV/WB6EpMvI9PYhzwTeDolHw8OGw5TVg7PeP6DDefPNNeDxkfY5EIigpKcGbb74JWZbx0ksvQZZl/M///E+6ftPzzz8Pv9+P1atX43vf+x4AIDc3F0899RQURcGoUaNw4YUX4p133sFNN93U5X7/+Mc/sGvXLqxevRrFxZQR+sADD+Dcc8/tcuy8efNw4YUXAgB+8YtfYOzYsdi5cydGjRp1RJ+BoG8IcTMQCNaRmAnWcZeOSQtiqntzLM4zGnoqW+8l60qogQKGNSdZR8INZOkINfJA4g6eYu4msRM+QOImFesT7wBl4zgprqRtN7lbmnfQMWqUjvcW8VokEsXV1G6gb4RGglxRjhz6nXGBlYjQQm/3A2wzFbMzEkCCXEUx2YMWuBGHDc5kBKbqQ0SXYUYSQGgz/A2fQ2r4gubq5AULJZ7KrTno2SWjFAwsyWSx8lUCusGzl3wA2gGWAMCLBkoK73/F09ElGSZT4Yg3QrZ7YbjyoZhJAAosux9ypA62RCtk3QCcMokyxcaDh2sAZz4JrUQQMHIp7dvmIveVt5j3A+OCK95ObRlibTy+qZOrMdpK1i2Zxxc1fsmrHw/NlAZgjLK5nIHsWJxOuG0KPHYVoYSB3G6qFIfiOjwOFS57V8uSz6XhpDIfmkJxNAQTYBZQ4nOgKMeBfE92Q864bqK2Iw6vXYXLlvk4kiQJuS6qpFzXHkPgUI08BUefePvhHR87zOP7wDnnnIPFixcDAFpbW7Fo0SKcf/75+Oijj7Bhwwbs3LkTXm92rF88HseuXbvSf48dOxaKknnflpSUYNOmTd3eb9u2bSgvL08LGwA49dRTuz22c1BzSQk1g21sbBTipp8Q4uZ4h/E05ra99G1cc9GibcQprsVTQGKlNz95qrWBJPFeTm76W3VRUCuigDY807JBc9A3uVA9CZW2/dzSYmT3igqMIKFz4AvenkAmq0/dRrJ4GHFetdhFlpxEkJp7uouoSB0zqeN4w6ZMiwfTpPkYOsB06IqKqKVAZQZyEYPuCkBzFaIo3gTD0NGu5sFmHIC7dgPPcALFycACWacUXu9GQzqOhlk8Loc34IQOtMW4iFHIwsR0HpjMY24sHTLTYEgMiuaCbEQBSYJp9wFmHGq8GYYRhaYywDB4w8t2un7BKDKOqA6Kg9I8wIHPKBbKiAONm0lgufJI5BWMJjddsBZo3ArEO2DYPEiE2mEF68FMC1bxONhLToEzvJ+K/EWaqFGlwhuPOvzUoLOH/k6qIqMs14kvajtgV+Us4RFLmojqJsbku3os9Oe2q3DbPagMuKm2YA+ZUaG4gWjCQHFO94X3vA4VbdEkEoYFh3b8phcPCBz+wzs+1aD3COJ2uzFs2LD035MnT4bP58Ozzz4Ly7IwefJkvPjii13O6xwkrGnZ2Z2SJMGyrINPAUAWxL6K6s7XTZ3T03UFRx8hbo53JIkWyUgzZUOlAlA1Jy3Q4Ub6V+2lamu4kaw8uRUkZuLtFAAcbiQhwyxymdh9VHcmEaJ6M4qNqhgnwxSs7C+j66WK+9V9wrN4DG4diQDxOiDSSgXl7D76AJQUElQOH1D/OYkmXwWdk+rZ1L6HAnHByOJgkPXFkDQgEoaDRRBlDuhyDhyxZkiWAUmSISdCSLIk3LE2XuRPBqRoxhKkx7i1JEGix51P9w/V0cLfvo/mB8YbeCbpR5JIFCUjdA4kyIYJWQ9BjrXCchfAcOTBcBVDjTXAMgzo9gBUxuNpDJkHNUfJ5eUppteMSbzCtI3+LhxFwiQR4p3TR9Hzrf4Xxdu4C5Bs2oXW1gMwgy1gig+Gy4dm2ygoTUlU5FUiUJlPwdyRZsocKxpLrsPOweXdUOpzIq6bqG6Noj2WhCrJMBgV/Rua78Yg/6GbU0qS1GvpGQbKnOppAZEliUoS9VJNWfANYOpUx2bL8r6fM2bGUS/sJ0kSZFlGLBbDySefjJdffhmFhYXIyTkyZQJGjRqF6upqHDhwAEVF1Atv/fr1R+TagqOLEDfHO/EgqGidl4SELCNdREtWaKE0Yl3TsjuTCFEvqtwhQOsuWvCTQbIuODy00FoGpXLv/5gWY8VGcTzhA7TQt+3lhfcK6b6eImD/BnJtSRIJBsVGBQNDjXRtC9yFplGVXm8xFb6LNPGYITfQuJ1XFLaTKHHmUTsDdwAwdcSSCoKqA65YPZJMgaKHICsMps0F1YhBscLQLcBSHZBTLrRoMz03SaGsIknlrieOZidBKDOgvY4sW6qDLCnMRuOzeSgzKdJCosfuhQ0MulGNuG4goeTAJltAMgI9kQCDBpfTBZseIjdbpJlnhrVk0rqdfspu85WSoErw2BpvCd0/Zea3uaiQXeNWWM587M3NQ9jYjxJ5O2Bzw/KWwecrQzAJ7G2NwVbkg7d0PMURlZ3GrVSHRpYlDC3woMDrQGs4gbhhwaHKyHPbkeNUj4ibyKkpsCsy4rrZrWUmmjThsildMrYE3zCKRgX6PIV9Cyr2FAGjL+652e5XJJFIoKGBimu2tbXhqaeeQjgcxsUXX4xTTz0Vjz32GGbMmIH7778fZWVlqK6uxrJlyzB//nyUlZUd9v3OPfdcDB06FNdeey0effRRhEKhdECxcJMe2whxc7yTyuhx5AANn5MA0exkCVG0TBZNb2mZqp3Ss8MHyIWU4BYSWw7FcDATyBtOC2/bbgp+LZtEbismkWsqHqTAZYePp0aDRECwBigYS26o5m28wm+Mu3dCQE4x4B0EVH9ArplBp1B6d7yDV0vuyNR7ySmlAGUzRq6VaCukBBCzcuCGAk2VqUO3EYNkWVBYHAlJgyKZkFSVRFmS39tK0P0Vjf4XKB4Sh8kI3cNVQCnhqg2QckgEaXayGskqiS9vMZ2vuQBnHiQ9Apc3D3IsBKao0PUk1JYvoagq7O4cuFgckqRSppnJ+2HJMrnYFJWePzO5JYjROFM4fJRNFW2lgOPcwYBiQ7hhNyLtNfCrFiTNiYSvAqazEJBk5DhlNIcSaIsk4fXaqNM6M0FdTfuGJEnwOTX4nEfn27fXoSHfa0dNWxTFOc6sFPGEYSKmmxha6O42dVzwTSNRgb7e6twA9H9jxtM4nED0vvLWW2+l41m8Xi9GjRqF//3f/8XZZ58NAFi7di3uuusuXHbZZQiFQhg0aBC+853vfGVLjqIoWL58OW688UaccsopqKqqwmOPPYaLL74YDofoYXYsI8TNQCDUwN0jAco+MmIkLFy51JXbE+i9WqjqJBdS+ADgKqRr6GGq/QJG3/iZQftlldwlLt6HKvXtxe7l7pMggJxMQ8doMwkdM8ndUiFyKWkOQNLoPEUlF0ssyJtI8kU9GaMWB7JGsTY2L7l0FC66jBiclgU7c4NJEhxGO1jShGTqAJMgSSYsU4YTcUi6QX2gUtWVU60hYq28srBKAsKeQyIm0sTbHzgAuGnOpgV4C2h80VYgMCQjcNqpiJhss8PFTNgdGnQ1F1KoBkq4AWoknMmQkjXePqKWxuAOUHxStBkINQHqbrKYlUzMvEaSTM86VQtHkgDfIHToOWgNF8LLqsFiB6DGWqDG22GpThiuQjhUH9qjOsodFiTFdsS/SR8JhhZ4kDBMNARjcKgKVEVGQjdhMYbKgBMlvl7S2QXfHLJClYd/+BLVsQkf6HqMpwi45Ckq4HeEKxT3lrKdori4OKuKcXfXOJjONW0AZNXFAcg19e6776b/fu+99wAgHfszePDgLmUP/H5/l22Cb5Zj75NOcHiYSV7Z1wm4S3n1XAOAxOvT7CcXhtZDfITJs39Mnc5x5ZFVweJxLXqM4jxS9VJcuZRtFG0BwEgcpOJ7GMi6EPqUtofqaXzxIB0rqRTgbCaAWIiLI5XGbPOSBaN5BwmfvCHkKjLjtPgngjw2htfgSUQA2Qa7Q4FTdqElUgzNisKb7IBTioExBRHJDkgynCCxAyNOi7tiz3QHV1VqzGnjTTlzB9Pzk2QSXrJMViJZI3N8/eeZFPu6z+k6Gg+89hQBjmGApUNhBhTTIBHTYQKI0bGSDGg2Ht9TQMLRHSDRZRpkTWqvptgmRydXWeqb8sFp4bICNdkOxWgBU22QLAOmwwvJiMHevgsOWyF09yCwRBRSyUk9BhD3J06bgnGDfGgOJ9HQEUPSYCjIsaM4x5EuKig4RpBkEi4/2ZLpLRVrJ5fqmBnkikoV8hwgvPrqq/B4PBg+fDh27tyJ22+/HWeccQaGDh3a30MT9MKx90kn6B7G04ANXkHY4aN/I41kPejcdVvWeOl9XlHX7u25oWCslYKH/RV0bjJEtWCSUV4cjlf9deby2jId9I0tlbYdD1L8iK+SatG0bOdZWx4KvDV41V+bk8ZqGYDLT+ncZoJEgiwBsKjeTrSNrDgA7wTuBCBRsHO8gywbRjz1UCDZnCgw2wFNwwEzgNakE7lyEH6zBTYpAY/GYFdtJN70GN1DtZFgkRgXZl5er4fRXCUnPQ9Lp/lGWoBoHd3S0EjEpDqb5w3LvB6STLEy+cNIoLXupdfEW8QzvWJ0jGkCiRayzqRq7LTtIcGT6CABkwzSa5MK+o210T1ceVkvn5tF4Y1WI+nKAcsbDVvHHsjJECybB6akQm7bhXwlCblsAsXuHKPYVQWD/E4M8jsPK0NF0A+kLKujLsquY2Pqx6Rl8OsSCoVw5513Yv/+/cjPz8d3v/tdPPHEE/09LMEhGHjvxIFIvIPqwUS5hSVVYyV3MC2avjKK0wjWkNCQAECihdExuPcqtXqMjtccJIKMGFlhUu0PEh1Azad0P7uHAod95RT0qrlogW7eBdT8i8SUp4gEkaSQSyzUCEQOAMine4SbeIyQj4uVGiDC08otRv2sKr/Nm33qZCVq2wOo5RTvEu0gy4vVxONHAE1WUCp3IJe1I+6xwzBVOHUNDlmHqtp5QTqZrsVAVhyFxyXZ/fz5MMrQkhTeqNICkoziWxIhEiA2F/WyirbTNQvHU8yQwrOwjCTFLKV6TZlJbpXpILGoujNiLxkmC5HTT89CsZHIcvooRspIUCq/PYfHKKk0lmSEVx4mf7+PheDXDBwwbMhze8H8MrRoE+REO+JJA6rE4M0tBIrHp8851hHC5jjh4Cyoo5gV1Z9cc801uOaaa/p7GILDRIibY514kFwh8Q5aKFUHb43QRgHERpJ3ly4m60oilHG5OHKo8WRvzetSC4nDT9dTHdSrqL2azo130EIcbaJjLJOsOy27qTCc6gA8+SRAJIkWem8JCQcJdO9YG7lcnPk85iZGcT6agzKmFAXwDyEhxRJUjNDGO5LHOoC8KrKoMIusPkYcYDmA6uEuOAa48uCMtsAp6YDGKABY5a0ZJJAbKzVfZtAHsacQKBhO4qajhlLZFV4p2LJILJoWNR7NG0bHR5tJoBWdRCnVkWYSHnqUhJHqoEBkWSaBAkbPzF9Ox4QbeKPLJM0j3kYCy+6i+Tl8NG7IdK9gPbmvAHrmTdxt5y0BciuhmDGU5HoRT2hoicShyk7ItgoYyIfdLaHcZcIbKDluhI1AIBAcCYS4OdYJ1lI8Rs6gjBCRVVrwIk1k3YibJGxUe3ZJ/mSUFu7eim85fGTFSMZoQQfjFhEGwAKMCFksNBfPWCqguJtEEDiwhRZtSSFBpPKA1ZxSunYsh4SYrJJIs3tIJDCLLDWai9xNqoPOhUJF6eq/AJxeCmx2F1AfKoefdy6X6adtNxCrI4uKauPbeUVjm4dcSnYPNZO0+4D9/+Ldzn0kJswkBQvH2ihTLBXInFNORQPBAKhAeB/vtWWROEnyasl5Q3j7AlvGLRWqp/MiTdx910QxQym3V+0eulaqpZsRBUzGm396AFdRpi+Xww+UjONWJP6aOHPpXnqM6gwlgoDNA6fKMNzvRXssifYo7+7td8Lv1uBJNPde40ggEAgGIELcHMsYCcqEcvi6j5lx5lIGkGqnhdWVz9OwGVlbYu1U2K+ntgsAuT1ySsnd5M6nNT1YS4u+oVPjSX8Zt8CEyI2i2MjlpIepNo5mBw58yd03BrmivIUUH5IIUn8qzUUiqWgMiYuaD2nRVTS6pySTILB0ur4zH/DaaZFPBmk8Ni8waArQ8AXQxFsoOPMBVQF0neas2klwwaIYFs1FFhfNw9sUyFSgz+Yh6xEDCRaHJ1O0MLeCXFc2D10n0kyiJNZKFilZoXgaTyEPPM6hexoxqr4cayP3msFFkZkEEu2ZFHvNAZguOl7mgcJWkuYuyfR6aw4SnEaM3ICe4k6vmZfmFazjxQ41aFYcBR5ndt8mUych6Sn8im9AgUAgOD4R4uZYxjJ4cG4PMTOySm6gghG8SnEjz6phtAgXjKT2Bb0hSXRcx34KFLa56HybC1QckAcoJ0NkxQnV0X1dedy1ZKfjOqp5ELKX6tkoGokaWaNxKRrFkuSU8SDoUlrETQPw5JHbSI+QGGveTm6udOaSAgQbgNJCCgi2OSj+JsFdXIqHxuGv5P2vYiRQTJNaQzRuoXgb1UYWJD3K6+4kM3WAvOW0L9YOFIwB9qyloGFnPv2raiSc8oeTCIs2Ua0cyUZuM9VOYi2nlM8th55ZPEjupVgLubhYkgdTJ7mlDNx6pgHRRkAaS1WEGagqc+6Q7vs/yUomANxXRs/L7uXFGiV6ltE2El2u/K/09hMIBILjFSFujmVkjawYRrz7DtBmkgcX59ICG2vjmUQSLa42d9/uo2hA6WRyh6SqEUsKdatOhEnoJEFCIN5OVhLNTa4ZPU5Wo3SatUpCI9pOFg/NRTEvBSNpoXblUZVhxgWHh9fL0XlMjCOHMpVa95AFKREkEeXKo3EYCbJu5FaQdSPWTmJGc5AFJRWfIqmUDQWDnkPu4EyDUZMH6TKL7uUKkGBReTsFMIqZUVTqmRVvJ4Hp9JK4klXuIlMAG0g0RVspPiZ/GMUPwSLB0bKbx9q0kvDSbHS8zUn3sixu/fFT1pgrQM85VE+vf8pS1B2qg1xauUPo944aGgNAzz1/OL0vjsH0b8HxD2MMLS0tCIfD8Hg8CAQCIhhccMwgPvWOZVQbWQGatvB2AActctEWiuVw+EkgHJQmfFi4AyRWgnWUlRNuzFgWwgdIvDjzyeJhBik2hlkkhmJtQOnJ1Icp2kLixZFHsSeKSsImfzRQcWom6PnAJrp26sOQAYBEsSXxDhIyqo1nNHnonI5aunaq5YSi8aagRiaDyM5dcAqvZxNUKF6JmWQlCtYDMMlakgjyHlI2yv4KNZIga97JiyAGyBKWinOJtdMxDh8JHAdPsW/dg3TLi/wRvMIw6L7F44G6T4HWfSRGnTk0H2bR8YqT3FexVhp7sCaTDp43lDcVtbqvG2Im+DNwkKjylfEsLG5566u4FQgOg/b2dixduhSLFy7Etk7dtkcOHYp///GPce2118Lv9/ffAAUCpCMbBccs/jLKhArW0aJuJsn901FLFo3AcN5P6msiKxR86y3hxfhqMgX44kFeUI938lYdZNmJNJE7qXQiWWCcflrMPTzepngcCSVbDlD/GbDjbYpJSUZpfzJE1huAx6Ho5EYyk1TsL28oWWKYRSIj0gI0bqNKxrLEU+ALKFsLjJ5R42aKU8oZRONMdADJjkxRwWSIRFsiSFaptv3cVRUhl1F7De8d5c4U67N7yN3kDJBFxFsClIwHRl5AGVOBoUDxWCB/ZEbYAGSxcuTQWPKHkYBUbJQN5cyjzt6anYoI8kag0GM8Iy1KotXm5Faig2AWjd9XlhG9Gm/86SkQwkZwVFixYgUqy8owb+5cTNy9G68AWAngFQATd+/GvLlzUVlWhhUrVvTzSI8NVq9eDUmS0N7e3t9DOWJcd911uPTSS/t7GIdEiJtjHc1JgqFgFH0jj7XTQuivIFHxdaw1B2NzA6WTgOHnUqqz5iJLi82d6T0lgYJbcwfzYN8Obo0JklCJtZNI0Zy0WIebqQKyZifREm0G6j8lseTIpbmED/CMJINEhruQig9G28gl1F7LG00aZMHRbCTs/BXUAiGnjBZ0Zx4JhSFnAoNO5hYdJ1laDF6nxuGjwF1Z5o0qA/S/QE+QmyiZag/hpn8Vjc41InQPSJS+7czlMS45ZPHKG0qWJlPv+lz1GAU3l4zngkkmy4/qzAQqKxpZfYrHkcUoMIxieiyeTRVu5AHCjMbZUUfPyVvc9X4CwVFgxYoVuOjCC3FmLIb9jOElxvADAN8F8AMALzGG/YzhzFgMF1144REXONdddx0kScLDDz+ctX358uX94g578803cfbZZ8Pr9cLlcuGUU045ZHuI44m9e/dCkiRs3Lgxa/t///d/HxfzFG6p4wHNSUHDuZW00MoqD/jtA0aSXEXRVvq27/RRgGlP5yu8WNzwcymNufFLHtTsJteY3UOixojQ4txRQ53EQweA9v0kGCSZFuNwI1lP3IU0bs1JVp1khI7PKaHFGiCxkVMG7F1Lbh6dZ4EleSVju5dEQrSNZ2zZyVJj91DhQM1BLrxU/FG8g55XRzUQoT5UcHgoayoeyggFWSWLTriJ+mVR6haNKdTAqzzHSJwZcRJrngBP7d7ArVSBTFZWsJ7GI0sAFIr7SYYBuxPIGU5itHU3iRpZpnGrTrK4uPK4i6yMrsEsstrk8hpA0RZyr6lOLqiG9F6gUSA4QrS3t+OKyy/HdMaw3LJ6XDiKASy3LFwqy7ji8suxr6bmiLqoHA4HHnnkEdx8883Ize0m0P4bYuHChZgzZw7uuusuLFq0CDabDa+99hpmz56NL774Ao8//ni/jS2ZTMJmsx36wK+Iz+c79EHHAMJyczyR6v7dV2GTCAG1n9Ai3LEPCNWSe6hmPQmP3vAWkXVGtpF1oGgcEKiiBZyZVIPGMmnh37WaxJPmpDgUu5e7hHhwrmWStSSVkm5z0zWiLUDLTqrq27KL4l/iHbTo23PoOs5csmh4S3npHZ0sQjYX3U91kiDzV1LcT0oI6DHAP5hcSKE6shopdrKuqDYSfSbvqG7zkuCzu0ns6BFg0GRqXOkrJ+ESauTp6E4gtwqQ7fQ8jQQJIEkmUSUB2LMO2PEOsHsVUPcZuc4Cw+mY0pPJslQynruqCkm4Dj4DGPpvZKXz8WKCqp0LSztQdgpQcRpQcTr9WzxOuJ4E3xhLly5FNBrF//QibFKoAJ61LESjUfz+978/ouP47ne/i+LiYjz00EO9Hvf+++/jrLPOgtPpRHl5OW677TZEIpS0sHDhQpx00knpY1OWn6effjq9bfr06fjP//zPbq+9f/9+3HHHHZgzZw4efPBBjBkzBsOGDcMdd9yBxx57DE888QQ+/PDDrHPee+89TJgwAQ6HA9/61rewadOm9L59+/bh4osvRm5uLtxuN8aOHYu///3v6f1btmzBBRdcAI/Hg6KiIsyaNQvNzc3p/WeffTZuvfVW/OQnP0F+fj7OPfdcXHXVVfjhD3+YNQZd15Gfn4/nn38eAHVYnzp1Kvx+PwKBAC666CLs6hRDNWTIEADApEmTIElSuvP6wW6pRCKB2267DYWFhXA4HJg6dSrWr1+f3p9yzb3zzjuYMmUKXC4XTj/9dGzbtq3b53ukEOJmoGIalAIdayZx4i0ha0DOIFrUD2zmdVd6QLXT4q7ygGGTdxuPtlC8j5Egi0ciQtWMG7cC7Xup/oseofgYO7f2tFeTsEk1gkyG6RrxEFAygWrf2NzknrEkEhr5QzP9s+JBquzbtptESyIIKC4SC4Gh5J7LH0bVi80YCbJIIw/EdgOQyArTUUfWF4O3nAgMJzEExjONakk4NW2nv0smAAWjyTrkLqBYHUMn15ViA/xDycr05d+B3euAfe+Tay6vkrK5XHk0Rk8RiRmA7uHg8UiBYSTgfIPoXp78rplNksQtTDwrzpUnRI3gG4UxhsULF+JykGWmL5QAuAzAogULjmh3bEVR8OCDD2LhwoWoqanp9phNmzZh+vTpuOyyy/D555/j5Zdfxrvvvotbb70VAImBzZs3pwXCmjVrkJ+fjzVr1gAADMPA+++/j2nTpnV7/b/85S/QdR3z5s3rsu/mm2+Gx+PBn//856zt8+fPx+OPP47169ejsLAQl1xyCXSdXNi33HILEokE1q5di02bNuGRRx6Bx0M95err6zFt2jRMnDgRH3/8Md566y0cOHAAV1xxRdb1ly5dClVV8d577+G3v/0tZs6ciddffx3hcDh9zIoVKxCJRHD55ZcDACKRCH7yk59g/fr1eOeddyDLMr7//e/D4okkH330EQDg7bffRn19PZYtW9bt87jzzjvx17/+FUuXLsUnn3yCYcOGYfr06Whtbc067u6778YTTzyBjz/+GKqq4vrrr+/2ekcK4ZY6EiRC5NaINtNi5s6nxbC3RaijFmjaRvVlINHi3DnT5nBIRoC2amobEG2lIFgwWkj95ZRS7Mwla4Ak0djaa2jMdi8tyJFG+puZ5HZSbCRCFCe5WvQwuV8khYSPogLhDrqmr5yESMd+chUloyRmmIPGwRhZO8wkuaMat1KKtL+Mrq3Z+DVyM1lRyQiJpWSEFnZZ4Y35FCAKskTllPJeWNySZSTIIiPJJGTsXppL6SSqUGwYvJigN9MdvHUXxfOkejzpMbpH9Qc0DyNK19R40T1JIStOPEQxPs4cEmXJCGWLFYykFOxUnx3LpGfirwSG/RtQ8wkQruNxSS56zR1eXnjwIJhFMTfC9SToR1paWrBt1y788jDPu5wxvLJrF1pbWxEIBI7YeL7//e9j4sSJuPfee/Hcc8912f/YY4/h6quvxpw5cwAAw4cPx4IFCzBt2jQsXrwY48aNQyAQwJo1a3D55Zdj9erVuOOOO/DrX/8aALB+/XrE43FMnTq12/tv374dPp8PJSVdG9HabDZUVVVh+/btWdvvvfdenHvuuQBIiJSVleHVV1/FFVdcgerqalx++eVpa1JVVVX6vMWLF+Pkk0/Ggw8+mN72u9/9DuXl5di+fTtGjBgBABg2bBgeffTR9DFDhw6F2+3Gq6++ilmzZgEA/vSnP+Hiiy9GTg5Z0FMiJ8Vzzz2HwsJCbNmyBePGjUNBAZXVCAQCKC7uXtZGIhEsXrwYL7zwAs4//3wAwLPPPouVK1fiueeew/z589PHPvDAA2nB+NOf/hQXXngh4vE4HI6jU0G93y03ixYtwpAhQ+BwODB58mSsW7eu1+PXrFmDyZMnw+FwoKqqCkuWLPmGRtoDoQPA/o/JEhLvICtH/edAzcdkveiO2o3AZy8Bu1fT+aE6YNtbwGcv06J/OERagF2rgK2vUSZS41Zg9z+BLa8DDZszIqppGy3cKVJduuMdQO3HdG60mawke9YCG/8IfPFXCmq1eXiGVj1lFyU6KPbF4SNrgzOPFueisUDhGLKmFIwiVxLvgYREmNo1tOyg+i/hBvq9aRvFsbTuIheVaZHAadtDWUtGMhMfY/dzNxQvDBisozkZCbIohZt47y2LXD2phpmySsLJSmYCjBUbDx5OkuWkaCxtd/rJugVQ4HOwgQKIkzwzadBEEq2RA/QcjCQohd2gZxBppnNSyLzJabSVhM+kq4CJPwImXAVMnAlMvJpXe45289o2ZxppCgT9ROrb/+FGuKSOD4V6sRB/RR555BEsXboUW7Zs6bJvw4YNeOGFF+DxeNI/06dPh2VZ2LNnDyRJwllnnYXVq1ejvb0dmzdvxuzZs2GaJrZu3YrVq1fj5JNPTltPDpfuutp/+9vfTv+el5eHkSNHYuvWrQCA2267Db/61a9wxhln4N5778Xnn3+eNZdVq1ZlzWXUqFEAkOVCmjJlStb9NE3DD37wA7z44osASIS89tprmDlzZvqYXbt24eqrr0ZVVRVycnLSbqjq6uo+z3XXrl3QdR1nnHFG1r1PPfXU9PxSjB8/Pv17Shg2Nh4iPOJr0K/i5uWXX8acOXNw991349NPP8WZZ56J888/v8eHu2fPHlxwwQU488wz8emnn+JnP/sZbrvtNvz1r3/9hkfOSYTJ9QOTrBDufPrxldG3/FRl3M601wC73gHAyB2TW0GxLYWjyAKwYyVZBfqCHgfqN1JFX7uX4mFkma7nLaIxxNpJnMRayT3U2URsmsCBrSRwfGWZdgJmgtxN4Sa61uDTSbDYeAYUkyhg1saDeW281ozNRRYdh4+eQ8lJJD4YKLBX0chaEm6k/QUjeaZShKxJehwI7qcYEy2VLp3DqyHbKTjX7iEB4/RnrCOJEKVXF44h0eLy0bg9xWS9atlBjSnd+eS28paS8Ak1ZNoTpNLcnQEai+og95jTS4KoYDgJNdOguB/VRcIllcVkJHn6uJuEV+esKZubXgs9RlaY3Eqau28QBVXnjyBxE6znqfftJEplG7nFuivgKBB8Q6QW+W4KEvRK6niv13tExwMAZ511FqZPn46f/exnXfZZloWbb74ZGzduTP989tln2LFjB4YOpYrtZ599NlavXo1169ZhwoQJ8Pv9OOuss7BmzRqsXr06HV/SHSNGjEBHRwfq6uq67Esmk9i9ezeGDx9+yDmkBNCNN96I3bt3Y9asWdi0aROmTJmChQsXpudy8cUXZ81l48aN2LFjB84666z0tdzurl6CmTNn4u2330ZjYyOWL18Oh8ORtq4AwMUXX4yWlhY8++yz+PDDD9NxQslk8pBjT5FyOR4s5roTeJqW6Rqf2pdygR0N+lXcPPnkk7jhhhtw4403YvTo0fjNb36D8vJyLF68uNvjlyxZgoqKCvzmN7/B6NGjceONN+L666/vv8j0SBMtrAd/s5YkChSNt5M1pDPNX1LMSMo6kD5HpviPUB0txn0h2kwZSpJClol4OwCJL8x53IXDXSbOXO4+4T5YPUZCJNqcqRIM0MKsx0gkqdy64S2mhpfeEnJbWQlAT5IgClSR6ycezBT9U210DbuXRIYZJwuVHiELi+rg9Vk0ChxOhEgoag5e6yVJ1YJtbhJOskpzNA26R6rOTv5woOocoPJ0oOJb1M/K4q4nRSNB5s6nuXtKKDanZAIw9GwSFJ6ijHDQ3Dzbyg/AJOGmOUlguPMo1gbItMRQHSRyLJ276RRyQWlOXugwkXmdLINe3+4K8UkSZT2VTqZnAlB15fwRQNnJPP1cIOg/AoEARg4dir8eZrr1XyUJI4cORV7eESxX0YmHH34Yb7zxBt5///2s7SeffDI2b96MYcOGdflJZRGl4m7+8pe/pIXMtGnT8Pbbb/cabwOQO0dVVTzxxBNd9i1ZsgSRSARXXXVV1vZ//etf6d/b2tqwffv2tAUGAMrLyzF79mwsW7YMd9xxB5599tmsuQwePLjLXLoTNJ05/fTTUV5ejpdffhkvvvgifvCDH6Tn39LSgq1bt+Kee+7Bd77zHYwePRptbdnyNXWsaZo93iP1TN999930Nl3X8fHHH2P06NG9ju9o028xN8lkEhs2bMBPf/rTrO3f+973urxZU3zwwQf43ve+l7Vt+vTpeO6556DrepYyTJFIJJBIZBaaYDB4BEbPibbSgtwdkpQJhk1lzjFGYsTu6b4RpqLSwhY+0Lf7xzoycSiwSFCkFmubi1f2DVLjSU8BHavHKPZFc2diOWT+NkjVkZG5kLB5SAxJEp1vd5NQ0pzkCnLlkUDJKaX7B+vIyhEPAkqcFu0R0ykbKhkmsWOrIYuRmQTgIpHCLN5kMkliR1LJspKM8lTsEP0t28hipNqoTo6/kgRQ6llKCoky0yALDhidlzuEV/o1aa6+MqB4Aj2PYA2JM1eAhEqig9fLCfOaOk7AO4i2x9roXpZB84ebrEOuPLL6JMP0zCQZWd8bYu0kmlLVk7t7r3gK6McyQdWO+91jLBAAoG/Z//7jH2Pe3LloQN+CiusBLAPwxG23HbUaNCeddBJmzpyZtnKkuOuuu3DaaafhlltuwU033QS3242tW7di5cqV6WNTcTcvvvgiXnvtNQAkeO644w4A6DHeBgAqKirw6KOPYt68eXA4HJg1axY0TcNrr72Gn/3sZ7jjjjvwrW99K+uc+++/H4FAAEVFRbj77ruRn5+fzjiaM2cOzj//fIwYMQJtbW345z//mRYGt9xyC5599llcddVVmD9/PvLz87Fz50689NJLePbZZ6EoPbRmAb1uV199NZYsWYLt27dj1apV6X25ubkIBAJ45plnUFJSgurq6i5rcWFhIZxOJ9566y2UlZXB4XB0SQN3u93493//d8yfPx95eXnpZxONRnHDDTf0OLZvgn77BG1uboZpmigqKsraXlRUhIaGhm7PaWho6PZ4wzCyUuM689BDD8Hn86V/ysu7Cdz8qqQyWXoi1e06C76Y94iFPr8sksRv0qk2S3o4Mi3SmgOI8gq9sSBlOEkK787dnblY6nS5g+amuchlo9gyPa8AEhvuQhI5BSPoupXfBspPJWuP5iIB4C7g18gl0RBr5w0kGVlG4h20v3Qi74s0hNx2hWOBwnHkzgmMoODjnFL6u/MHp80FuAq4BavTfFLzSIQztXpyy6kIoD2XLEpGjF6rnDJyFal2EnnuAnKT5Q4mN5Wk8Gdk0RhdAbpmTgltC9V36jhuZeoL+Sv7JlhkRQgbwTHHtddeC5fLhRtlGcYhjjUA3CTLcLlcuOaaa47quH75y192ycYaP3481qxZgx07duDMM8/EpEmT8POf/zwrAFiSpLR15swzz0yf5/P5MGnSpHTQbU/MnTsXr776KtatW4cpU6Zg3Lhx+NOf/oTFixd360l4+OGHcfvtt2Py5Mmor6/H66+/nmUZueWWWzB69Gicd955GDlyJBYtWgQAKC0txXvvvQfTNDF9+nSMGzcOt99+O3w+H+Q+fE7MnDkTW7ZswaBBg7LiYmRZxksvvYQNGzZg3LhxmDt3Lh577LGsc1VVxYIFC/Db3/4WpaWlmDFjRrf3ePjhh3H55Zdj1qxZOPnkk7Fz506sWLGiX+sQAYDEjmSe3mFQV1eHQYMG4f33388KtnrggQfwhz/8AV9++WWXc0aMGIH/9//+X1b9gffeew9Tp05FfX19txHd3VluysvL0dHRccg38CFpr6a6MTmDulpiLJNiOgZNpoUvxZ51wM63KeD24HOMJNC2Fxh3GaUKH4pgPbBzJVkU3PmUIRRrJUsEGO9m7aBFGIwsIZVnkGiweyhgdf9HdG4qfqVlF9C2jwRCMsxrxXBBacRJIBhJ2i9JJGQU3uAzJXzchSRQUlatxi/J1eYrI6tU03YSANEWGm88RO4tU6fg3bJv0XHhJm4N4eZXM0kWEMaoAnHFaV0z0qKt1MvJMkhQte2juBvNRecHhpOFxEjQce37yaKi2XmWmErPlTFyU4HX43Hlk+BJhCkrykhkhFvxSXR+8056T3hLuHsL9HwCQzMuJ4GgH4nH49izZ086ieNwSFUons4YnrUsdM0VIovNTbKMFZKEv/39710s7QLBoejtPRoMBuHz+fq0fvebWyo/Px+KonSx0jQ2NnaxzqQoLi7u9nhVVXtMNbTb7bDbj1JApruAFsRQAwmAlJUmJWxc+V1TuwtGUTZV625eJI+bFc1kZltgaN/u7+LNLvc3U8aRI4eLEl6B1zJJePkqyK1SenK2aHLmUdxJsA7IKSaXjbuAREWogVKnU2nWJrespBZrfyXVgmnfT5YJRw4JFm8RCYjO7rpUb6xIM2U8Obzk3vIWkVElfzi1LwjWAmEHCRZ/JY3f5JlQ8XaqLmz3AqUTSDR2l2rvyiOx0bwjE+yb4N23C0Z16houUeBzAXeNpXpPmQYFFVecRlao9mqg5iOqZ5MKlg4MJxdapBVwaHRulNE8y06lOCEzSS67VDC0QHCcM336dLz5t7/hissvR0U0istA6d65oODhv0oSlgFwOZ3427JlQtgI+pV+Ezc2mw2TJ0/GypUr8f3vfz+9feXKlT2av7797W/jjTfeyNr2j3/8A1OmTOk23uaoozlJLBzYQlYTmdeXAUjUFI3NWERSeAqAkdMpK6p5e7bbKncwMPL8vtc1UW0UO2LolDUVaiCLQqyVhhGo4rVboiQW8kdkny/L1CwTjCwlqUq7NhevIZPgbRVqaGG3+yj+pGgMT/0eQzE88SAJHI2nWR9skXL66Vk0fUkByzYPibFICwX7purb5FZRYG2QF9vzFGSCogNVQNF46iXlK+/aIT3rGReScIu1kcgoHJPpbB6uJ6EjyeTuyh1McUmxNtpvz6G5p6opF4+lubbsonExg0SVI5fEq6KSlUixCSEjGPBMnz4d+2pq8Pvf/x6LFizAK527gldV4YnbbsO111573JToFwxc+s0tBVAq+KxZs7BkyRJ8+9vfxjPPPINnn30WmzdvRmVlJf7zP/8TtbW16RLee/bswbhx43DzzTfjpptuwgcffIDZs2fjz3/+c5eCRD1xOGatPmMkMzViJJmnLwe6CpvOxINU1yV0gPdVGkTWC9tXKNhm6rwCbzUQC/ExeHjGD29+6cztOZbD4q6XWDuJFDs/Lx7kTS0jvBt2EVk+7F+t/gP0GFlvktySIvHgHlnNfmZJnlWVjNK+Q42/LySj9Bp9nWtaJo8zkjKNQQWC44iv45Y6GMYYWltbEQqF4PV6kZeX1y8NLAUDi+PeLQUAV155JVpaWnD//fejvr4e48aNw9///ndUVlYCoNLTnWveDBkyBH//+98xd+5cPP300ygtLcWCBQv6LGyOGqqNvu3nlPb9HEcOxY0cCRSNrAvdVbntC7JC1g5PYfZ2Vx6QN/hrDy+N5uzbGG3uI99iwOYCbBVf7xqyIlofCAQcSZIQCASOaPVhgeBI0a+Wm/7gqFhuBAKB4DjgSFpuBIKjwZGy3IicU4FAIDjBOMG+0wqOI47Ue1OIG4FAIDhBSCVeRKPd9DITCI4BUu0feitQ2BdEV3CBQCA4QVAUBX6/P92w0OVyiSBgwTGDZVloamqCy+WCqn49eSLEjUAgEJxApIqdHs2OzALBV0WWZVRUVHxt0S3EjUAgEJxASJKEkpISFBYWQtf1Q58gEHyD2Gy2PrWWOBRC3AgEAsEJiKIoXzuuQSA4VhEBxQKBQCAQCAYUQtwIBAKBQCAYUAhxIxAIBAKBYEBxwsXcpAoEBYPBfh6JQCAQCASCvpJat/tS6O+EEzehUAgAUF7+FfswCQQCgUAg6DdCodAhO8+fcL2lLMtCXV0dvF7vIfPog8EgysvLsX///hOqD9WJOm/gxJ27mPeJNW/gxJ27mPfxO2/GGEKhEEpLSw+ZLn7CWW5kWUZZWdlhnZOTk3Pcvhm+DifqvIETd+5i3iceJ+rcxbyPTw5lsUkhAooFAoFAIBAMKIS4EQgEAoFAMKAQ4qYX7HY77r33Xtjt9v4eyjfKiTpv4MSdu5j3iTVv4MSdu5j3iTHvEy6gWCAQCAQCwcBGWG4EAoFAIBAMKIS4EQgEAoFAMKAQ4kYgEAgEAsGAQogbgUAgEAgEAwohbg7ioYcegiRJmDNnTnobYwz33XcfSktL4XQ6cfbZZ2Pz5s39N8gjSG1tLX70ox8hEAjA5XJh4sSJ2LBhQ3r/QJy7YRi45557MGTIEDidTlRVVeH++++HZVnpYwbCvNeuXYuLL74YpaWlkCQJy5cvz9rflzkmEgn8+Mc/Rn5+PtxuNy655BLU1NR8g7P4avQ2d13Xcdddd+Gkk06C2+1GaWkprrnmGtTV1WVd43ic+6Fe887cfPPNkCQJv/nNb7K2D9R5b926FZdccgl8Ph+8Xi9OO+00VFdXp/cfj/MGDj33cDiMW2+9FWVlZXA6nRg9ejQWL16cdczxOvfeEOKmE+vXr8czzzyD8ePHZ21/9NFH8eSTT+Kpp57C+vXrUVxcjHPPPTfdp+p4pa2tDWeccQY0TcP//d//YcuWLXjiiSfg9/vTxwzEuT/yyCNYsmQJnnrqKWzduhWPPvooHnvsMSxcuDB9zECYdyQSwYQJE/DUU091u78vc5wzZw5effVVvPTSS3j33XcRDodx0UUXwTTNb2oaX4ne5h6NRvHJJ5/g5z//OT755BMsW7YM27dvxyWXXJJ13PE490O95imWL1+ODz/8EKWlpV32DcR579q1C1OnTsWoUaOwevVqfPbZZ/j5z38Oh8ORPuZ4nDdw6LnPnTsXb731Fv74xz9i69atmDt3Ln784x/jtddeSx9zvM69V5iAMcZYKBRiw4cPZytXrmTTpk1jt99+O2OMMcuyWHFxMXv44YfTx8bjcebz+diSJUv6abRHhrvuuotNnTq1x/0Dde4XXnghu/7667O2XXbZZexHP/oRY2xgzhsAe/XVV9N/92WO7e3tTNM09tJLL6WPqa2tZbIss7feeusbG/vX5eC5d8dHH33EALB9+/YxxgbG3Huad01NDRs0aBD74osvWGVlJfv1r3+d3jdQ533llVem/393x0CYN2Pdz33s2LHs/vvvz9p28skns3vuuYcxNnDmfjDCcsO55ZZbcOGFF+K73/1u1vY9e/agoaEB3/ve99Lb7HY7pk2bhvfff/+bHuYR5fXXX8eUKVPwgx/8AIWFhZg0aRKeffbZ9P6BOvepU6finXfewfbt2wEAn332Gd59911ccMEFAAbuvDvTlzlu2LABuq5nHVNaWopx48YNmOeQoqOjA5Ikpa2WA3XulmVh1qxZmD9/PsaOHdtl/0Cct2VZ+Nvf/oYRI0Zg+vTpKCwsxLe+9a0s981AnHeKqVOn4vXXX0dtbS0YY1i1ahW2b9+O6dOnAxi4cxfiBsBLL72ETz75BA899FCXfQ0NDQCAoqKirO1FRUXpfccru3fvxuLFizF8+HCsWLECs2fPxm233Ybf//73AAbu3O+66y5cddVVGDVqFDRNw6RJkzBnzhxcddVVAAbuvDvTlzk2NDTAZrMhNze3x2MGAvF4HD/96U9x9dVXpxsKDtS5P/LII1BVFbfddlu3+wfivBsbGxEOh/Hwww/jvPPOwz/+8Q98//vfx2WXXYY1a9YAGJjzTrFgwQKMGTMGZWVlsNlsOO+887Bo0SJMnToVwMCd+wnXFfxg9u/fj9tvvx3/+Mc/svyvByNJUtbfjLEu2443LMvClClT8OCDDwIAJk2ahM2bN2Px4sW45ppr0scNtLm//PLL+OMf/4g//elPGDt2LDZu3Ig5c+agtLQU1157bfq4gTbv7vgqcxxIz0HXdfzwhz+EZVlYtGjRIY8/nue+YcMG/Pd//zc++eSTw57D8TzvVKLAjBkzMHfuXADAxIkT8f7772PJkiWYNm1aj+cez/NOsWDBAvzrX//C66+/jsrKSqxduxb/8R//gZKSki6eis4c73M/4S03GzZsQGNjIyZPngxVVaGqKtasWYMFCxZAVdX0N9uDFWxjY2OXb73HGyUlJRgzZkzWttGjR6czCIqLiwEMvLnPnz8fP/3pT/HDH/4QJ510EmbNmoW5c+emLXcDdd6d6csci4uLkUwm0dbW1uMxxzO6ruOKK67Anj17sHLlyrTVBhiYc1+3bh0aGxtRUVGR/qzbt28f7rjjDgwePBjAwJx3fn4+VFU95GfdQJs3AMRiMfzsZz/Dk08+iYsvvhjjx4/HrbfeiiuvvBKPP/44gIE79xNe3HznO9/Bpk2bsHHjxvTPlClTMHPmTGzcuBFVVVUoLi7GypUr0+ckk0msWbMGp59+ej+O/OtzxhlnYNu2bVnbtm/fjsrKSgDAkCFDBuTco9EoZDn7ra8oSvob3kCdd2f6MsfJkydD07SsY+rr6/HFF18c988hJWx27NiBt99+G4FAIGv/QJz7rFmz8Pnnn2d91pWWlmL+/PlYsWIFgIE5b5vNhlNOOaXXz7qBOG+A3ue6rvf6eTdQ5y6ypbqhc7YUY4w9/PDDzOfzsWXLlrFNmzaxq666ipWUlLBgMNh/gzwCfPTRR0xVVfbAAw+wHTt2sBdffJG5XC72xz/+MX3MQJz7tddeywYNGsTefPNNtmfPHrZs2TKWn5/P7rzzzvQxA2HeoVCIffrpp+zTTz9lANiTTz7JPv3003RGUF/mOHv2bFZWVsbefvtt9sknn7B/+7d/YxMmTGCGYfTXtPpEb3PXdZ1dcsklrKysjG3cuJHV19enfxKJRPoax+PcD/WaH8zB2VKMDcx5L1u2jGmaxp555hm2Y8cOtnDhQqYoClu3bl36GsfjvBk79NynTZvGxo4dy1atWsV2797Nnn/+eeZwONiiRYvS1zhe594bQtx0w8HixrIsdu+997Li4mJmt9vZWWedxTZt2tR/AzyCvPHGG2zcuHHMbrezUaNGsWeeeSZr/0CcezAYZLfffjurqKhgDoeDVVVVsbvvvjtrYRsI8161ahUD0OXn2muvZYz1bY6xWIzdeuutLC8vjzmdTnbRRRex6urqfpjN4dHb3Pfs2dPtPgBs1apV6Wscj3M/1Gt+MN2Jm4E67+eee44NGzaMORwONmHCBLZ8+fKsaxyP82bs0HOvr69n1113HSstLWUOh4ONHDmSPfHEE8yyrPQ1jte594bEGGNH1zYkEAgEAoFA8M1xwsfcCAQCgUAgGFgIcSMQCAQCgWBAIcSNQCAQCASCAYUQNwKBQCAQCAYUQtwIBAKBQCAYUAhxIxAIBAKBYEAhxI1AIBAIBIIBhRA3AoHgiHLfffdh4sSJ/T0MgUBwAiPEjUBwgnLddddBkiRIkgRN01BVVYV58+YhEol8revOmzcP77zzzhEaZc9cd911uPTSS4/a9V944QVIkoTRo0d32ffKK69AkqR0w0mBQHBsIcSNQHACc95556G+vh67d+/Gr371KyxatAjz5s37StdijMEwDHg8ni6NKI9lkslkj/vcbjcaGxvxwQcfZG3/3e9+h4qKiqM9NIFA8BUR4kYgOIGx2+0oLi5GeXk5rr76asycORPLly8HQGLl0UcfRVVVFZxOJyZMmIC//OUv6XNXr14NSZKwYsUKTJkyBXa7HevWrevilkpZWB588EEUFRXB7/fjF7/4BQzDwPz585GXl4eysjL87ne/yxpbbW0trrzySuTm5iIQCGDGjBnYu3cvAHJ9LV26FK+99lra+rR69epDntd5PA899BBKS0sxYsSIHp+Pqqq4+uqrs8ZWU1OD1atX4+qrr+5y/BtvvIHJkyfD4XCgqqoqPc8UTz75JE466SS43W6Ul5fjP/7jPxAOh9P7X3jhBfj9fqxYsQKjR4+Gx+NJC1CBQNB3hLgRCARpnE4ndF0HANxzzz14/vnnsXjxYmzevBlz587Fj370I6xZsybrnDvvvBMPPfQQtm7divHjx3d73X/+85+oq6vD2rVr8eSTT+K+++7DRRddhNzcXHz44YeYPXs2Zs+ejf379wMAotEozjnnHHg8HqxduxbvvvtueqFPJpOYN28errjiivTCX19fj9NPP/2Q56V45513sHXrVqxcuRJvvvlmr8/khhtuwMsvv4xoNAqABMh5552HoqKirONWrFiBH/3oR7jtttuwZcsW/Pa3v8ULL7yABx54IH2MLMtYsGABvvjiCyxduhT//Oc/ceedd2ZdJxqN4vHHH8cf/vAHrF27FtXV1V/ZmiYQnLD0b99OgUDQX1x77bVsxowZ6b8//PBDFggE2BVXXMHC4TBzOBzs/fffzzrnhhtuYFdddRVjLNON+ODuyvfeey+bMGFC1n0qKyuZaZrpbSNHjmRnnnlm+m/DMJjb7WZ//vOfGWPUwXnkyJFZnYsTiQRzOp1sxYoV3Y7/cM4rKirK6gLfHc8//zzz+XyMMcYmTpzIli5dyizLYkOHDmWvvfYa+/Wvf80qKyvTx5955pnswQcfzLrGH/7wB1ZSUtLjPV555RUWCASy7gmA7dy5M73t6aefZkVFRb2OVSAQZKP2t7gSCAT9x5tvvgmPxwPDMKDrOmbMmIGFCxdiy5YtiMfjOPfcc7OOTyaTmDRpUta2KVOmHPI+Y8eOhSxnDMVFRUUYN25c+m9FURAIBNDY2AgA2LBhA3bu3Amv15t1nXg8jl27dvV4n76ed9JJJ8Fmsx1y3Cmuv/56PP/886ioqEA4HMYFF1yAp556qsu9169fn2WpMU0T8Xgc0WgULpcLq1atwoMPPogtW7YgGAzCMAzE43FEIhG43W4AgMvlwtChQ9PXKCkpST8XgUDQN4S4EQhOYM455xwsXrwYmqahtLQUmqYBAPbs2QMA+Nvf/oZBgwZlnWO327P+Ti3KvZG6bopUhtbB2yzLAgBYloXJkyfjxRdf7HKtgoKCHu/T1/P6MubOzJw5E3feeSfuu+8+XHPNNVDVrh+dlmXhF7/4BS677LIu+xwOB/bt24cLLrgAs2fPxi9/+Uvk5eXh3XffxQ033JB2BQLdPyvG2GGNVyA40RHiRiA4gXG73Rg2bFiX7WPGjIHdbkd1dTWmTZv2jY/r5JNPxssvv4zCwkLk5OR0e4zNZoNpmod93lchLy8Pl1xyCV555RUsWbKkxzFv27at2+cJAB9//DEMw8ATTzyRtmK98sorR2yMAoEggwgoFggEXfB6vZg3bx7mzp2LpUuXYteuXfj000/x9NNPY+nSpUf9/jNnzkR+fj5mzJiBdevWYc+ePVizZg1uv/121NTUAAAGDx6Mzz//HNu2bUNzczN0Xe/TeV+VF154Ac3NzRg1alS3+//rv/4Lv//973Hfffdh8+bN2Lp1K15++WXcc889AIChQ4fCMAwsXLgQu3fvxh/+8IcehZJAIPh6CHEjEAi65Ze//CX+67/+Cw899BBGjx6N6dOn44033sCQIUOO+r1dLhfWrl2LiooKXHbZZRg9ejSuv/56xGKxtEXmpptuwsiRIzFlyhQUFBTgvffe69N5XxWn09lr/Z7p06fjzTffxMqVK3HKKafgtNNOw5NPPonKykoAwMSJE/Hkk0/ikUcewbhx4/Diiy/ioYce+lpjEggE3SMx4cwVCAQCgUAwgBCWG4FAIBAIBAMKIW4EAoFAIBAMKIS4EQgEAoFAMKAQ4kYgEAgEAsGAQogbgUAgEAgEAwohbgQCgUAgEAwohLgRCAQCgUAwoBDiRiAQCAQCwYBCiBuBQCAQCAQDCiFuBAKBQCAQDCiEuBEIBAKBQDCgEOJGIBAIBALBgOL/AwZlNDkT4GgjAAAAAElFTkSuQmCC",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Plot existing data\n",
-    "plt.scatter(cancer[\"perimeter_mean\"], cancer['concavity_mean'], \n",
-    "            color=cancer[\"diagnosis\"].map(color_map), alpha=0.2)\n",
-    "\n",
-    "# Create custom legend handles\n",
-    "handles = [plt.Line2D([0], [0], marker='o', color='w', label=label,\n",
-    "                      markersize=10, markerfacecolor=color_map[label])\n",
-    "           for label in labels]\n",
-    "\n",
-    "# Add new observation\n",
-    "new_observation = {'perimeter_mean': 97, 'concavity_mean': 0.20}\n",
-    "plt.scatter(new_observation['perimeter_mean'], new_observation['concavity_mean'],\n",
-    "            color='red', edgecolor='black', s=100, label='New Observation')\n",
-    "\n",
-    "# Add labels and legend\n",
-    "plt.xlabel('Perimeter Mean')\n",
-    "plt.ylabel('Concavity Mean')\n",
-    "plt.title('Scatter Plot of Perimeter Mean vs Concavity Mean')\n",
-    "plt.legend(handles=handles + [plt.Line2D([0], [0], marker='o', color='w', \n",
-    "                                          markerfacecolor='red', markeredgecolor='black',  markersize=10, label='New Observation')], \n",
-    "           title='Diagnosis')\n",
-    "plt.show()\n",
-    "\n",
-    "                                    "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 16,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#new observation\n",
-    "\n",
-    "new_obs_Perimeter = 97\n",
-    "new_obs_Concavity = 0.2"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 21,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0      25.800194\n",
-       "1      35.900178\n",
-       "2      33.000000\n",
-       "3      19.420044\n",
-       "4      38.100000\n",
-       "         ...    \n",
-       "564    45.000021\n",
-       "565    34.200046\n",
-       "566    11.300511\n",
-       "567    43.100266\n",
-       "568    49.080407\n",
-       "Name: dist_from_new, Length: 569, dtype: float64"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#distance calculation\n",
-    "\n",
-    "cancer['dist_from_new'] = (\n",
-    "(cancer['perimeter_mean'] - new_obs_Perimeter)**2 +\n",
-    "(cancer['concavity_mean'] - new_obs_Concavity)**2 \n",
-    ")**(1/2)\n",
-    "\n",
-    "cancer['dist_from_new']"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 22,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>perimeter_mean</th>\n",
-       "      <th>concavity_mean</th>\n",
-       "      <th>diagnosis</th>\n",
-       "      <th>dist_from_new</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>291</th>\n",
-       "      <td>97.03</td>\n",
-       "      <td>0.05940</td>\n",
-       "      <td>Benign</td>\n",
-       "      <td>0.143765</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>138</th>\n",
-       "      <td>96.85</td>\n",
-       "      <td>0.15390</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.156924</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>96.73</td>\n",
-       "      <td>0.16390</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.272403</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>514</th>\n",
-       "      <td>97.26</td>\n",
-       "      <td>0.07486</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.288548</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>54</th>\n",
-       "      <td>97.26</td>\n",
-       "      <td>0.05253</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.298910</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     perimeter_mean  concavity_mean  diagnosis  dist_from_new\n",
-       "291           97.03         0.05940     Benign       0.143765\n",
-       "138           96.85         0.15390  Malignant       0.156924\n",
-       "15            96.73         0.16390  Malignant       0.272403\n",
-       "514           97.26         0.07486  Malignant       0.288548\n",
-       "54            97.26         0.05253  Malignant       0.298910"
-      ]
-     },
-     "execution_count": 22,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#take the 5 nearest neighbours\n",
-    "\n",
-    "nearest_5 = cancer.nsmallest(5,\"dist_from_new\")[[\n",
-    "    \"perimeter_mean\",\n",
-    "    \"concavity_mean\",\n",
-    "    \"diagnosis\",\n",
-    "    \"dist_from_new\"\n",
-    "]]\n",
-    "nearest_5"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 26,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<module 'matplotlib.pyplot' from '/Users/juliagallucci/miniconda3/lib/python3.10/site-packages/matplotlib/pyplot.py'>"
-      ]
-     },
-     "execution_count": 26,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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VaiUXLlwgAMjWrVv59x577DEil8sdBFl6ejoBQD788EN+W1ORR0jL7tqcnBwiEAjIu+++y28zGo3E39/f4SG3JXrz+dMU7t7w0ksvEX9/f4d7TVRUFJHJZA6/c6PRSPz8/MiiRYv4bbfddhuRy+WkpKTEYZ8SExNdEnnZ2dlk4MCB/L1PLpeTSZMmkY8++oh/IODmGhsbS2bNmuXw+WnTppG4uDh+7pzIGzJkiIO797333iMAyPXXX+/w+UcffZQAcLgWRUVFEblcTgoLC/ltqampBAAJDQ11cJtu2bKFACA//vgjvy0xMZEMGzas2bKSmTNnktDQUH5erblrr7zySgKA/Pbbb07fGzp0qMO2Bx54gGg0GoffujM4kUdIw+8qJCSEWK1WUllZSaRSKVm/fr3Ta7er1/2meOIcc4V2uWufeeYZHDt2DD///DMWLlyIxYsX4+2333arD9LEPNkSo0aNQnZ2Nnbu3IlnnnkG48aNw2+//Ya5c+fi+uuv5/vZsWMHZDIZFi5c2Gp/J0+exPXXXw9/f38IhUKIxWLMnTsXdrsd58+fd2sfGmMymfDbb79h9uzZUCgUsNls/N/06dNhMplw+PBhh8/cdNNNbo2xatUqiMViSCQSJCUl4eDBg3jppZfw4IMPtviZ33//Hf3798fo0aMdts+fPx+EEPz+++9uzcHb/QLA9u3bIRaLIRaLERMTg2+++QYPP/wwXnnlFa8fZ4ZhMH36dP61SCRCfHw8QkNDMWzYMH67n58fgoKCHFzI27Ztw8SJExEWFuYwr2nTpgEA9u3b1+rYnXEOcfs4f/58fPnll7DZbPj8889x6623QqVSNWt78OBBVFVVYd68eQ7zYVkWU6dOxbFjx6DX6wEANpsNr732Gvr37w+JRAKRSASJRIKsrCxkZGQ06/v66693eD148GAAaHP5QUfR6/U4cuQIbr75Zod9FgqFuOuuu1BYWNjM7dfWXHft2gW73Y6HHnqo1bHLyspw//33IzIyEiKRCGKxGFFRUQDgcIwWLlwIo9HosAB83bp1kEqluOOOO9qx1w2BcDNnzsSqVav46+ZXX32FyspKLF682OV+euv58/vvv+Oaa66Bj48Pf2944YUXUFlZ2cxtOXToUPTp04d/LZPJ0K9fP4ex9+zZg0mTJiE4OJjfJhQKcdttt7k0n7i4OKSlpWHfvn1Yvnw5rrnmGhw7dgyLFy/GuHHjYDKZADS4bhcvXoxt27ahoKAAQEMQ0s6dO/Hggw82i76ePn26g7s3KSkJAHi3btPtXJ+N9z08PLxZu6uuusphOQS3nTsm2dnZOHfuHP71r38BQLPrW3Fxscvudq1Wi6uvvrrZ9n//+99ITU3FgQMHADRE23/55ZeYN2+e0/OzJRYsWIDS0lLs2LED//d//weJRMK7kJviznXf0+eYK7i+kK4Rffr04QfnbohPP/005s2bx683agtuomFhYW22FYvFmDJlCqZMmQKgYa3CzTffjG3btmHHjh2YPn06ysvLERYW1mydXmMKCgowfvx4JCQk4P3330d0dDRkMhmOHj2Khx56CEaj0aW5O6OyshI2mw0ffvghPvzwQ6dtGq+7AdDieouWuPXWW/Hkk0/yYd5xcXEQCoVtzis6OrrZdu64V1ZWujUHb/cLAFdccQXeffddMAwDhUKBuLg4SCQSAEBRUZFXj7NCoYBMJnPYJpFI4Ofn16ytRCLhL7QAUFpaip9++glisdileTWlM84hjgULFmD58uV47bXXcOLEiRbHKy0tBdAQ2d0SVVVVUCqVeOyxx7By5Ur85z//wZVXXgmtVguBQIB77rnH6W/L39/f4bVUKgWAdv0OuetRXl4eEhMTW21bXV0NQojTY9fS+dvWXMvLywEAERERLY7LsiwmT56MS5cu4fnnn8egQYOgVCrBsizGjh3rsN8DBgzAqFGjsG7dOtx3332w2+343//+h1mzZjk9F13l3//+NyZNmoRdu3Zh8uTJWLlyJcaNG+d2lHlvO3+OHj2KyZMn46qrrsKnn37Kr63asmULXn311WZ9Nh2bG79xu8rKSoSEhDRr52xbSwgEAkyYMAETJkwA0PCAcvfdd2PTpk1Yu3Yt/4C/cOFCvPDCC1izZg1ee+01rFy5EnK53KnRo+n5w11bW9re+BrXkc9z58ITTzyBJ554wun+tnWN5Gjpujdr1ixER0dj5cqVSElJwfr166HX69t8+GpKVFQUJk2ahLVr1yI/Px+33347FAqF0/V+rl73vXGOuUK7RF5TRo8ejTVr1iA3N9dlkffjjz+CYRj+5HUHf39/PProo9i7dy/OnDmD6dOnIzAwEH/++SdYlm1R6G3ZsgV6vR6bN2/mn56Bhvx/HUWr1fKWgJZOqJiYGIfXTZ+w2iIwMBAjR4506zP+/v4oLi5utp1bNB4QEOBWf97uF2hY3N3SfnbGcW4vAQEBGDx4MF599VWn77f1QNOZ+xYZGYlrrrkGy5cvR0JCApKTk522477HDz/8EGPHjnXahrNU/O9//8PcuXPx2muvObxfUVEBX1/fds3TVaZMmYJPPvmET9XUGpx48OT5y133CgsLERkZ6bTNmTNnkJaWhvXr12PevHn89paCZRYsWIAHH3wQGRkZyM3NRXFxcYsLv13l6quvxsCBA/HRRx9BpVLhxIkTTvOctkVvO3++/vpriMVibNu2zeEhb8uWLe3u09/fHyUlJc22O9vmKkqlEk8//TQ2bdqEM2fO8Nt9fHwwb948fPbZZ3jiiSewbt063HHHHV4/bu7AnQtPP/00brzxRqdtEhISXOqrpeueQCDAQw89hGeeeQbvvPMOVq1ahUmTJrncb2MWLlyIO++8EyzLtpq+y9XrvjfOMVfwiMjbs2cPBAIBYmNjXWq/bt067NixA3fccYeDObIpVqsVdXV1ThUtZ77nDuC0adOwceNGrF+/vkWXLXdicE98QIPb+NNPP23WtiXF3NLTokKhwMSJE3Hy5EkMHjyYf4rpaiZNmoTXX38dJ06ccHha37BhAxiGwcSJEwG4/xTsar+eprseZwCYOXMmtm/fjri4OGi12hbbdZdz6PHHH4dcLm/RDQE05Cz09fVFenp6my49hmEcflsA8PPPP6OoqAjx8fEemXNLzJo1C4MGDcLrr7+OmTNnOo2w/eWXXzB+/HgolUqMGTMGmzdvxttvvw25XA6gwdL2v//9DxERES1GibbE5MmTIRQKsXr1aowbN85pG2fXHwD4+OOPnbafM2cOHnvsMaxfvx65ubkIDw/H5MmT25xLW0/7jzzyCO6//37U1tYiODi41e+/NXrT+cMwDEQikYNnxGg04ssvv2x3nxMnTsSPP/6I0tJSXsja7XanOdicUVxc7NRi1fTex/HII49g1apVuPnmm1FTU+OWC74zSEhIQN++fZGWltZMyDelI1bZe+65B8uWLcO//vUvZGZm4s0332zXfGfPno3Zs2fDx8enxQcUwPXrvjfOMVdwS+Tdd9990Gg0GD16NIKDg1FRUYFvv/0WmzZtwpNPPtnMimc0Gvk1REajEbm5udiyZQu2bduGK6+8EmvWrGl1vNraWkRHR+OWW27BNddcg8jISOh0Ouzduxfvv/8+kpKS+CeCOXPmYN26dbj//vuRmZmJiRMngmVZHDlyBElJSbj99ttx7bXXQiKRYM6cOXjqqadgMpmwevVqVFdXNxt70KBB2Lx5M1avXo0RI0ZAIBBg5MiRUKvViIqKwtatWzFp0iT4+fkhICAA0dHReP/993HFFVdg/PjxeOCBBxAdHY36+npkZ2fjp59+6tA6tfayZMkSbNiwATNmzMBLL72EqKgo/Pzzz1i1ahUeeOAB/mbW2n51pF9v0B2PM9CQ8X/Xrl1ITk7GI488goSEBJhMJuTn52P79u1Ys2YNIiIius05NHny5DZFg0qlwocffoh58+ahqqoKN998M4KCglBeXo60tDSUl5fzT7kzZ87E+vXrkZiYiMGDB+Ovv/7CW2+91aoLsy327t2LiRMn4sUXX2w1y7xQKMQPP/yAyZMnY9y4cXjggQcwceJEKJVKXLhwAd999x1++ukn/rf++uuv49prr8XEiRPxxBNPQCKRYNWqVThz5gw2btzotoU0OjoazzzzDF5++WUYjUbMmTMHPj4+SE9PR0VFBZYvX47ExETExcVh6dKlIITAz88PP/30E3bt2uW0T19fX8yePRvr169HTU0NnnjiiVaXo3AMGjQIX3/9NTZt2oTY2FjIZDIMGjSIf//OO+/E008/jf379+O5555r98NEbzp/ZsyYgRUrVuCOO+7Afffdh8rKSrz99tvNRKc7PPfcc/jxxx9x9dVX44UXXoBCocDKlSv5NYhtMWDAAEyaNAnTpk1DXFwcTCYTjhw5gnfeeQfBwcG4++67Hdr369cPU6dOxY4dO3DFFVdgyJAh7Z67t/j4448xbdo0TJkyBfPnz0d4eDiqqqqQkZGBEydO4NtvvwUA/iHtk08+gVqthkwmQ0xMjFODT1N8fX0xd+5crF69GlFRUbjuuuvaNVeZTOZS0mlXr/veOMdcwp0ojbVr15Lx48eTgIAAIhKJiK+vL7nyyiudpkHhImC4P6VSSWJjY8nNN99Mvv32W5eSOZrNZvL222+TadOmkT59+hCpVEpkMhlJSkoiTz31VLN0EUajkbzwwgukb9++RCKREH9/f3L11VeTgwcP8m1++uknMmTIECKTyUh4eDh58skn+UjfxpE8VVVV5Oabbya+vr6EYRiHCLbdu3eTYcOGEalUSgA4RLPm5eWRhQsXkvDwcCIWi0lgYCBJTk4mr7zyCt+Giw779ttvXTnshBDnKVSc4SwZ8oULF8gdd9xB/P39iVgsJgkJCeStt95q9h20tl/OcLVfd6NrXWnb0ePcUnQtF13VmJYixZ3Ntby8nDzyyCMkJiaGiMVi4ufnR0aMGEGeffZZotPp+Hbd9RxylgKDkIb0FjNmzCB+fn5ELBaT8PBwMmPGDIfxq6uryd13302CgoKIQqEgV1xxBfnjjz/IlVde6RDt2dLcueg/LpUCIQ2/VwDNUjS1RE1NDXn55ZfJ8OHDiUqlImKxmPTp04fceeed5MCBAw5t//jjD3L11VcTpVJJ5HI5GTt2LPnpp58c2nDRtceOHXPY7uz8IaQhyn/UqFFEJpMRlUpFhg0b5rA/6enp5NprryVqtZpotVpyyy23kIKCghajrX/99Vf+Gnr+/Plm7zuLrs3PzyeTJ08marWaT5nRlPnz5xORSOQQJdkWvf38Wbt2LUlISCBSqZTExsaS119/nXz++efN9qela1TTeRJCyIEDB8jYsWOJVColISEh5MknnySffPKJS9G1H3/8MbnxxhtJbGwsUSgURCKRkLi4OHL//feTixcvOv3M+vXrCQCHNEAc3PF56623HLa3dDydnfst7buzc6Ol8dLS0sitt95KgoKCiFgsJiEhIeTqq69u9h299957JCYmhgiFQofvta3MHYQ0pEgCQN54441W2zWmpet/Y1rKjODqdd8b51hbMIS4GOZKoVAoncxTTz2FjRs3Iisrq1lADKV9WCwWREdH44orrnBIQtsbudzOn5tuugmHDx9Gfn5+i4EAlwOPP/44Vq9ejYsXL7pk/evNeGRNHoVCoXiDPXv24Pnnn78sbtDepry8HJmZmVi3bh1KS0vbDFDpDVwO54/ZbMaJEydw9OhR/PDDD1ixYsVlK/AOHz6M8+fPY9WqVVi0aNFlL/AAgFryKBQK5TJg/fr1WLBgAUJDQ/Hiiy86LXFG6Xnk5+cjJiYGGo0Gd9xxBz766KM2U2v1Vri0W9OnT8e6devcyo3XW6Eij0KhUCgUCqUX0q6KFxQKhUKhUCiU7g0VeRQKhUKhUCi9ECryKBQKhUKhUHohVORRKBQKhUKh9EKoyKNQKBQKhULphVCRR6FQKBQKhdILoSKPQqFQKBQKpRdCRR6FQqFQKBRKL4SKPAqFQqFQKJReCBV5FAqFQqFQKL0QUVdPgEKhULojdrsdVqu1q6dBoTggkUggEFD7DMU1qMijUCiURhBCUFJSgpqamq6eCoXSDIFAgJiYGEgkkq6eCqUHwBBCSFdPgkKhULoLxcXFqKmpQVBQEBQKBRiG6eopUSgAAJZlcenSJYjFYvTp04eem5Q2oZY8CoVC+Ru73c4LPH9//66eDoXSjMDAQFy6dAk2mw1isbirp0Pp5lDHPoVCofwNtwZPoVB08UwoFOdwblq73d7FM6H0BKjIo1AolCZQNxilu0LPTYo7UJFHoVAoFAqF0guhIo9CoVAoYBgGW7Zs6eppuMXevXvBMAyNhKZQWoCKPAqFQunFzJ8/HwzDgGEYiMViBAcH49prr8XatWvBsizfrri4GNOmTevCmbpPcnIyiouL4ePj09VToVC6JVTkUSgUSi9n6tSpKC4uRn5+Pnbs2IGJEyfi3//+N2bOnAmbzQYACAkJgVQq7eKZuodEIkFISAhdp0ahtAAVeRQKhdLLkUqlCAkJQXh4OIYPH45nnnkGW7duxY4dO7B+/XoAzd21//nPf9CvXz8oFArExsbi+eefb1YB5JVXXkFQUBDUajXuueceLF26FEOHDuXfnz9/Pm644Qa8/fbbCA0Nhb+/Px566CGHfqqrqzF37lxotVooFApMmzYNWVlZ/PsXLlzAddddB61WC6VSiQEDBmD79u0AmrtrW2tLoVyO0Dx5FAqFchly9dVXY8iQIdi8eTPuueeeZu+r1WqsX78eYWFhOH36NO69916o1Wo89dRTAID/+7//w6uvvopVq1YhJSUFX3/9Nd555x3ExMQ49LNnzx6EhoZiz549yM7Oxm233YahQ4fi3nvvBdAgBLOysvDjjz9Co9HgP//5D6ZPn4709HSIxWI89NBDsFgs2L9/P5RKJdLT06FSqZzukzttKZTLASryKBQK5TIlMTERp06dcvrec889x/9/dHQ0Hn/8cWzatIkXeR9++CHuvvtuLFiwAADwwgsv4Ndff4VOp3PoR6vV4qOPPoJQKERiYiJmzJiB3377Dffeey8v7g4cOIDk5GQADeIxMjISW7ZswS233IKCggLcdNNNGDRoEAAgNja2xf1xpy2FcjlA3bUUCoVymUIIaXE923fffYcrrrgCISEhUKlUeP7551FQUMC/n5mZidGjRzt8pulrABgwYACEQiH/OjQ0FGVlZQCAjIwMiEQijBkzhn/f398fCQkJyMjIAAA88sgjeOWVV5CSkoIXX3yxRVHqblsK5XKAijwKhUK5TMnIyGjmXgWAw4cP4/bbb8e0adOwbds2nDx5Es8++ywsFotDu6YC0Vkp9KaltxiG4aN6Wyqd3lh83nPPPcjNzcVdd92F06dPY+TIkfjwww+dfs6dthTK5QAVeRQKhXIZ8vvvv+P06dO46aabmr134MABREVF4dlnn8XIkSPRt29fXLhwwaFNQkICjh496rDt+PHjbs2hf//+sNlsOHLkCL+tsrIS58+fR1JSEr8tMjIS999/PzZv3ozHH38cn376aYt9utOWQunt0DV5FAqF0ssxm80oKSmB3W5HaWkpdu7ciddffx0zZ87E3Llzm7WPj49HQUEBvv76a4waNQo///wzfvjhB4c2Dz/8MO69916MHDkSycnJ2LRpE06dOuXWOri+ffti1qxZuPfee/Hxxx9DrVZj6dKlCA8Px6xZswAAjz76KKZNm4Z+/fqhuroav//+u4MAbIw7bSmUywEq8igUCqWXs3PnToSGhkIkEkGr1WLIkCH44IMPMG/ePAgEzR06s2bNwpIlS7B48WKYzWbMmDEDzz//PJYtW8a3+de//oXc3Fw88cQTMJlMuPXWWzF//vxm1r22WLduHZ+zz2KxYMKECdi+fTvv5rXb7XjooYdQWFgIjUaDqVOn4t1333XalzttKZTLAYa0tCiCQqFQLjNMJhPy8vIQExMDmUzW1dPpcVx77bUICQnBl19+2dVT6bXQc5TiDtSSR6FQKBS3MRgMWLNmDaZMmQKhUIiNGzdi9+7d2LVrV1dPjUKh/A0VeRQKhUJxG4ZhsH37drzyyiswm81ISEjA999/j2uuuaarp0ahUP6GijwKheIVuJUgtK5o70Qul2P37t1dPQ0KhdIKVORRKBSPw7IsLBYLjEYjxGIxRCIRhEIhhEKh04X+FAqFQvE8VORRKBSPQQiB3W6HzWaD3W4HIQRWq5UvSM8wDEQiES/6RCIRtfRRKBSKl6Aij0KheARO0NntdgCAQCCAQCDgS1oRQsCyLC/6qqqqIBAIEBgYSEUfhUKheAEq8igUSoex2+2wWq1gWRYCgYAvXdVYsDEM41DDtLq6GgzDwNfXFxaLBQzD8KJQLBbz7l0q+igUCqV9UJFHoVDaDSEENpsNNpsNAHiB5woMw/DuW64vztLXWPQ1du/2JNFns7MQCQUtvqZQKBRvQ0UehUJpF5wg44rNc6LNVZq2bWzp4yJzuQAOs9ncY0SfnSUACHaeLcH208WoNVrhIxdj+qBQTBsYAoCBUNC95kyhUHonVORRKBS3aGxxI4S4Le6a9uUMrr+eJvpYQrD/fDme+u4UynVmh/e2ny5BoEqK/948GFcmBELQzcRpY/Lz8xETE4OTJ09i6NCh2Lt3LyZOnIjq6mr4+vp29fQoFIqLUN8BhUJxGS64wmKxdFjgMQzToshz1paz9DUWdYQQmM1mGAwG1NfXo66uDnq9HmazGTabzeX+PYGdJdiXWY57NhxvJvA4ynVm3LPhOPZllv9t8fMc8+fPB8MwuP/++5u99+CDD4JhGMyfP79dfScnJ6O4uBg+Pj4dnKXnWb9+PRWeFEoLUJFHoVBcgrOi2Ww23orWEatZRz/LiT4uSEMgEDiIvnPnzqGsrAwGgwFms5lP6eI9CJ767lSb4s3OEjz1/SmvzCAyMhJff/01jEYjv81kMmHjxo3o06dPu/uVSCQICQnpdq5xCoXSOlTkUSiUVuGCKywWC+x2e4fFXdO+PYGzyNyLFy/CZDLBZDJBr9ejrq4OdXV1MBgM/L54anybncWOMyUtWvCaUl5vxs4zxbDZWY+MzzF8+HD06dMHmzdv5rdt3rwZkZGRGDZsGL9t586duOKKK+Dr6wt/f3/MnDkTOTk5Lfa7d+9eMAyDmpoaftunn36KyMhIKBQKzJ49GytWrHCwqC1btgxDhw7Fl19+iejoaPj4+OD2229HfX29y/PIz88HwzDYvHkzJk6cCIVCgSFDhuDQoUP8vBYsWIDa2lpe+C9btqwDR5BC6V1QkUehUFqEEILq6mpUVVWBEOJRgeeOu7Y9fTe29IlEIt7SZzKZoNPpPCr6REIBtp8udusz20+XeCXadsGCBVi3bh3/eu3atVi4cKFDG71ej8ceewzHjh3Db7/9BoFAgNmzZ/NBNG1x4MAB3H///fj3v/+N1NRUXHvttXj11VebtcvJycGWLVuwbds2bNu2Dfv27cMbb7zh9jyeffZZPPHEE0hNTUW/fv0wZ84c2Gw2JCcn47333oNGo0FxcTGKi4vxxBNPuHO4KJReDQ28oFAoTuFy3xUWFsJqtWLgwIFdPSW3aVw/t3EwByGE/zOZTHwbu90OlmXBsqzbtXdrjVa35uZue1e566678PTTT/NWsAMHDuDrr7/G3r17+TY33XSTw2c+//xzBAUFIT093aXv+cMPP8S0adN4QdWvXz8cPHgQ27Ztc2jHsizWr18PtVrNz+23337jBaGr83jiiScwY8YMAMDy5csxYMAAZGdnIzExET4+PmAYBiEhIS4eIQrl8oFa8igUigONgyu45MbtsXBVVVUhNzcXlZWVfBWMxnjTktcWTd27nKWPsyCxLMsLPu5fThS2hI9c7NYc3G3vKgEBAZgxYwa++OILrFu3DjNmzEBAQIBDm5ycHNxxxx2IjY2FRqNBTEwMAKCgoMClMTIzMzF69GiHbU1fA0B0dDQv8AAgNDQUZWVlbs9j8ODBDn0AcOiHQqE4h1ryKBQKD8uyfN1Z4J/kxu6IMZZlkZOTg7y8PPj7+6OsrAxmsxkajQZarRZarRYajcZbu9AuGrt3udfAP5bApla9xpZBhmFgs7OYPigU20+XuDzm9EEhXkuQvHDhQixevBgAsHLlymbvX3fddYiMjMSnn36KsLAwsCyLgQMHwmKxuNQ/F1nddFtTxGJHIctVQnF3Ho374cZ11bVMoVzOUJFHoVBazX3njsgzmUxIS0uDxWLBmDFjIJVKIRAIYDQaUV1djerqaly6dAk2mw0SiQRCoRC1tbVQq9UQCLqXY8GZiGks+qxWK8RicUONXgaYNjAEgSqpS8EXgWoppg4M9VpS5KlTp/JCacqUKQ7vVVZWIiMjAx9//DHGjx8PAPjzzz/d6j8xMRFHjx512Hb8+HG3+vDEPICGyF9nlmIKhUJFHoVy2dO0NFnT3HeuumvLyspw+vRpBAUFYcSIERAIBLzQkMvlkMvlCAsLAyEEBoMBOTk5qK+vx6lTp8CyLHx9feHr6wutVgu1Wt3hAA9Pu4ObzsdisTgIU0YgwH9vHox7NhxvNY2KUMDgvzcNbvF9TyAUCpGRkcH/f2O0Wi38/f3xySefIDQ0FAUFBVi6dKlb/T/88MOYMGECVqxYgeuuuw6///47duzY4dZ35ol5AA0uYZ1Oh99++w1DhgyBQqGAQqFwux8KpTfSvR6dKRRKp8LlvrNaG4IAnEXPtiWWWJbFuXPnkJaWhqSkJAwaNIivR+sMhmGgVCrh6+sLHx8fXHHFFRgxYgT8/PxQW1uL1NRU/PHHHzh16hQuXrwInU7XZWv32oITxAzDAITgyoRAfDZ3JALVUqftA9VSfDZ3JK5MCPR6aTONRuPULS4QCPD111/jr7/+wsCBA7FkyRK89dZbbvWdkpKCNWvWYMWKFRgyZAh27tyJJUuWQCaTudyHJ+YBNCRqvv/++3HbbbchMDAQ//3vf93ug0LprTCku149KRSK1yCEwG63w2az8cEVLVlhLly4gMrKSgwfPrzZewaDAWlpaWBZFkOHDoVSqeTf4wRkS27YgoIC1NbWYtCgQc3mVl9fz7t3a2pqIBQK+fV8Wq0Wcrm8TavRwYMHkZSUBK1W29bh4LFYLCgpKUF0dHSbgqW+vh4KhaKZpQx/z2vnmRJsP13SqHZtCKb+XbuWQceqhXRH7r33Xpw7dw5//PFHV0+lV2MymZCXl4eYmBi3RDXl8oS6aymUywxuPVnT4IqWaMmSV1xcjLNnzyIsLAwJCQnNxU4btDQmwzC8FSoqKgosy6Kurg7V1dUoLS1FVlYWxGIxL/h8fX0hl8vdGtur/L2mcfKAEMwYHMZvttpZgBAQwoI7mk3XPvYk0ff222/j2muvhVKpxI4dO/DFF19g1apVXT0tCoXSCCryKJTLCM661pb1rjFNRZ7dbse5c+dQXFyMQYMGITg4uN3zccWRIBAI+PV6MTExsNvtqK2t5YM4zp07B6lU6mDpk0qdu0s7C0IIBIBDQABnz2wcuds0LUtPEn1Hjx7Ff//7X9TX1yM2NhYffPAB7rnnnq6eFoVCaQQVeRTKZQDnnuWiZ92pXNFY5Ol0OqSmpkIkEiElJaVDFrT2ChihUAg/Pz/4+fkBAGw2Gy/6Ll68iPT0dCgUClitVtTU1EClUjVL5dEdaCl6lzvWLMs2S+vSnUTfN99809VToFAobUBFHoXSy3HXPdsUrhJEYWEhMjIy0KdPH/Tt29cjKU88sSRYJBLB398f/v7+AMCLu/T0dBQXFyMvLw8qlcrBvdtaYEhX0VL0buPtDoEeTj5DoVAojel+VzoKheIxOOudO+7ZprAsC71ej/Pnz2Po0KEIDAz0yNy8VfFCLBYjMDAQEokECQkJUKlUfBBHVlYWTCYT1Go1L/p8fHzcXk/YWTQWdK25d6noo1AozqAij0LphTTNfddegVdXV4fs7GywLIvx48d7NJqvs8qaSSQSBAcH82sHTSYTL/oyMjJgsVj4ahyNS3C5QmeKqrbcu1wbKvooFAoHFXkUSi+Dq1zBlX1qj1uVEIKCggKcP38eQUFB0Ol07RJ4nJDrTmJDJpMhNDQUoaGhIIQ4iL7S0lL4+/vDZDKBYRi+pm13mj8HFX0UCqUtqMijUHoJjUuTdcQ9a7VacebMGdTU1GDEiBGw2WzIyspq95xaS5XiTUueq5HDjatxmM1mlJSUQCgUgmVZGAwGAA3BHiKRCEKh0CXXLsMwYIgdjPCfgA9it4IwQpf32d1jQ0UfhUJpChV5FEovoKPBFRzV1dVIS0uDWq1GSkoKJBIJysvLu23FCU/DCSCxWMxbLu12O5842mxuqEvLBW5wYroxAoYAIEDGT0D6VsBUA8h8gf6zwPS/HgwDsMT74qrx99+45i4VfRTK5QMVeRRKD4ez3tnt9naLO0II8vLykJOTg759+yIqKsrhxu8NkdcZa/I80T9nvZNIJLy1lFvraDQa+TQnYrEYEokYyPoNzI8PAboyh36Y9C2AKgjk+pUQ9L0GbCv1bT1NS1Y+nU4HpVLZLDdfa6IvOjoajz76KB599FGvz5tCoXQMWruWQumhEEJgNBpRW1vbIYFnNptx/PhxXLx4EaNHj0Z0dHSztB3eEnk9DU7QccmWFQoF5HI5BAIBJCIhkLUbzNe3NxN4PLqyhvezdv9t8Wt7PFdZuHAhRCIR/xcUFITp06fj1KlTrfbb1OLHsixvvbTb7WBZ1sECeOzYMdx3330uz4tCoXQdVORRKD0Qzj176dIlnD59ut0Cr7KyEgcPHoRYLEZycjJ8fHyatWEYhg/i8CSdFV3rTTjRJ5PJAAYNFjzW3vqHWDuYHxfzn/ckU6ZMQWFhIQoLC/Hrr79CJBJh1qxZrX6msfWuacLlxqKP+9ff3x9yubzHf3cUyuUAFXkUSg/DbrfDbDbDZrNBIBC0K3qVZVlkZWXhxIkTiI+Px5AhQ1qsCtFeMebKnLo68MJjYxE7kP5jyxa8puhKgYyfGj7nQaRSKUJCQhASEoKhQ4fiySefxMWLF1FeXg4AKCoqwpw5cxAQEICQkBDccccdyM/P5z+/cOFC3HjjjVixYgUiIyMRHByMRx55hK+UQghBbGwsVqxYwYu+9PR0XHHFFZDJZOjfvz92794NhmGwZcsWAEB+fj4YhsHmzZsxceJEKBQKDBkyBIcOHfLovlMolOZQkUeh9BA4653FYuFLkwkEAretbCaTCceOHUNJSQnGjh2LyMjIVgURJyTbQ2v99iR3Lbcur/Gfr68vxGIxhEIhGKEYTPpWt/pk0reCEYqd9i0UCt3O2dcUnU6HjRs3Ij4+Hv7+/jAYDLjmmmugUqmwZ88e7NmzB0qlEjNmzIDFYuE/t3fvXuTm5mL37t1Yu3YtvvjiC2zYsMGplc9ut+PGG2+EXC7HwYMHsXr1ajz77LP8+4159tln8cQTTyA1NRX9+vXDnDlz+LWNFArFO9DACwqlB9A09x13w3VXgJWVleH06dMICgrCiBEjXCrv5U23ak8IvHAZU4177Y1utneBn3/+mXe56/V6hIaGYuvWrRAIBNi0aRMEAgE++eQTvlTdypUrER0djb1792Ly5MkAAK1Wiw8++ABCoRCJiYmYPn06fv/9d9xzzz38ONz5t2vXLuTk5GD37t0ICQkBALz00kuYOnUq7+rlztnHH38cM2bMAAAsX74cAwYMQHZ2NhITEz1+HCgUSgNU5FEo3ZjGue84t2zTRfOuWPJYlkVmZiYKCwsxYMAAhIWFuTwHGngBPjVNY+rr66FUKiEQCBpy58l83etU7tusb84F2rhaidVq5fP0tbX28qqrrsLKlSsBAFVVVVizZg1mzpyJQ4cO4cSJE8jOzoavr+M8TSYTcnNz+df9+/d3yAUYGhqK06dPOx3v/PnziIyMRGhoKL9t9OjRAP6pumI0GgEAAwcO5M9VThCWlZVRkUeheBEq8iiUbkrT3HdNBR7gmivVYDAgNTUVAJCcnAylUunWPHqyJa+zIHZrQx689C2uf6b/LMBuReNVM5wLXiwWQ6/X8+sk7XY7jEYjCCG8O9eZ6FMqlYiPj+dfjxgxAn5+fvjss8/AsiyGDx+OL7/8ku/TbDZDoVA41CNuujaztQcJV5Jdc+evSCTi++H+tdlsYFnW6blNoVA6DhV5FEo3xNXcd22tySsuLsbZs2cRFhaGxMTEdpU468l58joLwgjB9L8eUAW5FnyhCgaSrgOBAGjlGAgEAgeXeuPUJlw1Dq4Sh7Njybn0jUYjhg0bhm+++QZBQUHQaDS8cFSpVO7v8N8kJCSgoKAApaWlfG3gY8eONZsD96+zfH1NlyC01JZCobgPDbygULoRnIvLYrG4lPuuJSuL3W7HmTNnkJ6ejkGDBqF///7tEnjcGD3RXduZIoGvKHH9SkDQRtkzgRBk1kqHz7kKl5RZLpdDrVZDoVBAKBTy7l2DwYD8/HwUFBTg7Nmz+Pe//w2dToeZM2fijjvuQEBAAGbPno0//vgDubm5+PPPP7FkyRIUFha2a7+vvfZaxMXFYcGCBTh16hQOHDiA559/HoDrQTfc/zdew9c4Rx+Xp49CobgPFXkUSjeBc89y6+9cyX3nzF2r0+lw6NAh6HQ6JCcn8xaW9sKJPG/caHvTzZslDND3GpDbv26w1DlDFdzwfvwkj5Q240SfQqGASCTC7t27ER8fj9jYWFxxxRU4cuQIvvzyS6SkpEAmk2HPnj3o06cPbrnlFgwdOhSLFy+G0WiERqNp9/jff/89dDodxo4di0WLFuGZZ54B0JDOxdXv11mePir6KJSOQ921FEo3wG6389Gz7iQ2buyuJYSgqKgIGRkZiIqKQnx8fLutd43xlkWsp5Q1cweWJRDEXw3yWHpDHrz0rQ1RtHLfhjV4Sdfx7TzNunXrsG7dOv41tx6OO7dMJhNUKhVWr17NB1ZYLBaHNZpr165t1u+KFSscXufk5Di8TkxMxP79+/nXBw4cAAB+bWB0dHSzVCm+vr6tpk9pqQybs7q7Tf+fQqH8AxV5FEoXwrlnbTaby9a7xnDuWpvNhrNnz6KyshLDhg1DQECAx+bY2LJCb6Rtw5K/LVKJM4EBs/95w24FQftzDroLwzB8iTPAUfRZLBb+4cBkMvGBHO35frds2QKlUom+ffsiOzsbjz32GJKTkxEXFwer1eqxfWlMU9Fns9kgFovbrLtLoVxuUJFHoXQRnDjjog/bU5qMc9cePHgQcrkcKSkpfF1VT8HNibMyerLfnup2a2vehJCGoAqH1CutB1m4O4a7NBZ9UqkUVqsVZrMZQINFz2Qy8elguGAOV87H+vp6LF26FBcvXkRAQAAmTZqEt956yyv70HhfOAghvFBtutaPij7K5Q4VeRRKJ9NW7jt3+ikqKgIAhIWFIS4uzis3Mk7YeUN0ULoWhmEa6u7iH6syl1qFE/Wc4GtJ9N1111246667Wh3Dm3DnZeMHkNbcu1T0US4nqMijUDqRxu5ZoP1riSwWC86cOYPa2loAQExMjFfXzgHtE3ltWet6eu3anh4h3NTyJRaL+Tx5jQMeTCaTQ46+1kRfd8CdNX1U9FF6MzS6lkLpJFiWhcVi4dcptcc9CwDV1dU4ePAgCCEYM2YM37e36IjIa6vfnuquvRzgkjLLZDKoVCoolUqIxWKwLAuTyQSdTgeDwQCz2Qy73e70u+yM79eVMVqL3m2ce5CL3KXnJaW3QC15FIqX4Ra8c9n92yvuCCHIzc1Fbm4u+vbti6ioqGYVBLyBN0Wet6E3a8/RuBoH4LimtHE1jsbuXaB7WlSbrunj/qWWPkpvg4o8CsWLNC1N1l6BZzabcerUKRiNRowePZovQu+t9XKN6YjI0+v1kEqlDlUbGtObRRghBJWVldDpdFCpVPD39+9WQqGjx14gEEAikfCvG1vEuIAOTiTZ7XaHerjdCWeuXe5fKvooPR0q8igUL8G5ZztivQOAiooKnDp1Cn5+fhg2bJiDYOJuOt605HHjuCMKWJZFRkYGX0nBx8cHWq0Wfn5+UKvVHToe3Z2amhps2LABH69cicxGOeUS4uKw6KGHMHfuXPj6+nbdBBvhye+gsfUOgEMAh8FgAMMwzeruegJPp/ZpSfSZTCYwDMMLWyr6KD0BKvIoFA9DCIHZbMalS5cQEhLSbkHDsiyys7Nx4cIFJCYmIiIiwmk/nSXyXB3DYDAgNTUVADB27FgQQlBdXY3q6mpcvHgRhBBotVooFAp+DZQ3bpBdcdP95ZdfMOfWW2EwGHATgJcBaAFUA/g+NxdPPf44lj3/PDZ+8w2mTJnSal893copFAr5lCwSiYR379psNpjNZl70ce5dT6bn8SQtnUeNLX3OkjJT0UfpDlCRR6F4EM49azQacfr0aYSGhrbrYm80GnHq1ClYrVaMHTsWarW6xbbOSpt5GlcteWVlZfx+JyQk8AvyFQoFwsPDQQiBTqdDVVUVysvLwbIsDhw4AD8/P97S5+k8f53FL7/8glnXX48phOAzQhDS5P1bCEEJgHuMRsy6/nps/fHHNoVeb6GxFQ/4Z53qnj17MG3aNOTn58PX19dhPZ+roq+zxHBLycobiz1CCBYuXIja2lps3ryZij5Kl9M9H50olB4I556y2WwdskqUlZXh4MGDUCqVGDduXKsCD+gcS15b+8OyLDIzM5GWlob+/fujf//+Tj/DMAzUajWioqLQv39/MAyDAQMGQCqVoqioCAcOHMDhw4dx/vx5lJeXt1r6yhU6SwDU1NRgzq23Ygoh2MKyzQQeRwiALSyLKYRgzq23oqamptV+3REGCxcuhEgkwptvvumwfevWrU7XRHr72Gzbtg1Tp05FcHAw1Go1xo4diy+++ALAP4mZuSAOpVIJmUwGhmFgsVig1+uh1+thMpn4fJKt0RUCKj8/HyKRCGlpaQ6u23fffReff/65Q/Ru439p9C6lM6Eij0LpIJz1zmKx8E/73E3V7lDxoHW4dWxpaWlISkrCwIEDXVqs3lmWvJaEpMlkwrFjx1BeXo5x48YhNDTUrb61Wi3i4uIwcuRIjB8/HnFxcSCEICcnB3/88QeOHz+O3NxcVFdXe13MtpcNGzbAYDDgM5Zt0z0iAvDp3+vUvvzyS4/OQyaT4a233kJ1dbVL7b0ljj766CPceOONGDNmDPbu3YuTJ0/i1ltvxYMPPognn3zS6Ty4ShxKpRIqlYq36FosFuh0Ol70cSUA24vFYmnX51xdVuDr6wutVtssXUtT0cf9UdFH8SZU5FEoHYALruAsTpw7h7NiuSpK9Ho9Dh8+jOrqaiQnJyMsLMzlOXRl4EVlZSVfUm3s2LFQqVTN2rR0A3N2wxSLxQgMDERCQgLGjh2LcePGITw8HEajEWfPnsX+/fuRmpqKgoIC1NfXd87NkRBAr2/xj+h0+PjDD3ET0KIFrymhAG4EsOaDD0B0upb7d3P/Jk2ahJCQELzxxhuttjt48CAmT56MgIAAREdH49FHH4VerwfQINCGDh3Kt+UsgatWreK3TZs2Dc8884zTvi9evIgnn3wSjzzyCJYtW4b+/fsjPj4ejz32GN588028++67OHLkiMNnDhw4gOHDh/PW6zNnzkAkEkEmk6GiogJ33nknoqKiEBQUhKFDh2Lz5s3Q6/Uwm804c+YMbrrpJvj4+CAsLAzz5s1DRUUF3/fVV1+NRx55BI8//jiCg4MxZcoU/Otf/8Idd9zhMAer1Yrg4GCsX78eALBz505MmDAB/v7+CAoKwi233ILc3Fy+fXx8PABg5MiREIlEuPrqqwE0WFRvvPFGvp3FYsGSJUsQFhYGlUqFK6+8EkePHuVF3u+//w6BQIBdu3Zh+PDhUCgUSE5ORmZmZqvfIYXiClTkUSjtgFtTZLFYYLfbHYQd4FjvtS2Ki4tx6NAhaLVajB07Fkql0q25CASCThd5nKXtxIkT6Nu3LwYNGtRimpTWaEukyWQyhIaGYsCAAUhJScHIkSPh7++P6upqnDhxAn/++SfOnDmDS5cuwWg0uj2+SxgMEPr4OPyJfH3hGxEBka8vanx9kZmXh5vcFGQ3EYLMvDzU+vo261/o4wPfiAjAYHCrT6FQiFdeeQUrV67kI5ubcvr0aUyfPh3XX389Dh8+jK+++goHDhzAI488AgC48sorcfbsWV4o7du3DwEBAdi/fz8AwGaz4dChQ5gwYYLT/r///ntYrVY8/vjjzd677777oFKpsGnTJoftS5cuxZtvvonDhw8jKCgIs2fP5pOGP/zwwzCbzdizZw9SU1PxxhtvICAgABKJBMXFxZg6dSoGDhyIffv24YcffkBJSQluv/12h/43bNgAkUiE/fv3Y/Xq1ZgzZw5++ukn6HQ6vs0vv/wCvV7PCzSDwYAlS5bg8OHD+PXXXyEQCHDbbbfxv7VDhw7xnyssLMR3333n9HgsXboUmzdvxtq1a3Hs2DHEx8djxowZqK6udnjQee6557Bo0SIcPHgQIpEICxcudNofheIONPCCQnETV3LfcaKvNfFlt9uRkZGB0tJSDB48GEFBQe2aT2cHXlgsFpw+fRo6nQ5jxoyBRqNpd5+A624whmGgUqmgUqkQGRkJlmVRV1eH6upqFBcXIzMzEzKZjA/g6CwXGCcTtG5+jmtfD8Dfc9PBDTfcgCFDhmD58uX49NNPm73/zjvvYM6cOXjooYcANAjpd999F1dffTVWrlyJgQMHwt/fH/v378eNN96I/fv3Y8mSJXj//fcBAMeOHYPJZMIVV1zhdPysrCz4+PggNDQUhiYiVSKRIDY2FufPn3fY/vzzz+Paa68FAKxbtw5RUVHYsmULbrnlFly8eBGzZ8/GoEGDAACxsbH859atW4ehQ4fipZdegkgkgs1mwwcffIABAwYgLS0NiYmJAIC4uDiHtYpxcXFQKpXYsmUL7rzzTgDA119/jZkzZ/Lnc2NrHNBg4YyLi0N6ejoGDhyIwMBAAIC/vz9CQpzbcPV6PdasWYO1a9di2rRpAICPP/4Yu3fvxtq1a/HEE0/wbZcvX46AgAAMGDAAS5cuxYwZM2AymfjawhRKe6CWPArFDRq7Zzkh15JAaU3k1dfX49ChQ9DpdEhOTm63wGtrHE/BibyamhocPHgQDMMgOTm53QKP67MjCAQC+Pr6IiYmBiNGjMD48ePRt29fCIVC5OXlob6+Hjk5OcjOzkZVVZVb6yMdUChgr611+LPV1KCmsBC2mhrI/3bhubYK7h+49oq8vGb922trUVNYCCgU7Zry66+/jg0bNiA9Pb3ZeydOnMAXX3yB4OBgBAcHw8fHB9OnTwfLssjLywPDMBg/fjz27duHmpoanD17FosWLeIfSvbt24dhw4Y5dc07w1k0atNtY8eO5f/fz88PCQkJyMjIAAAsXrwYr732GsaPH49ly5bh1KlTDvuyf/9+hISEICAgACEhIRg9ejQAoKCggF8DN2TIEBgMBt7yLhaLcfPNN+Orr74C0CDGfvzxRwcXbk5ODu6880707dsXWq0WgwcP5vt1lZycHFitViQnJ/PbxGIxRo0ahXPnzjm0HTBgAIAGayy3rrWsrMzlsSgUZ1BLHoXiAu0pTeZMfBFCUFhYiHPnziEqKgrx8fEdzg/WWTVgS0tLUVRUhPj4eERHR3ts0b6n8uSJRCIEBAQgICAAQIPFSaPRwGq1IiMjA1artVlSZpfGZRigqQudkIY/pRL+SiUS4uLwfW4ubnHje/ieYZAQGwu/iIiGMRy6JwDLNtvuKhMmTMDkyZPx3HPPYd68eQ7vsSyL++67D/fee69Dcl8A6NOnD4AGl+1nn32GP/74A0OGDIGvry/Gjx+P/fv3Y9++fbjyyitbHLtv376ora3FpUuXmiV9tlgsyM3NxcSJE9vcB+67ufvuuzF58mRs374du3btwptvvom33noLixcvBsuymDZtGl5++eVmqXdCQ0Mhl8shFAqh0Wh4Sx9XjePGG2/EtGnTUFxcjD179kAmk2Hq1Kn852+44QZERERgzZo1CAsLQ319PZKTk3k3sis0zaPXeHvTbUKhsFmC5e4aaETpOVBLHoXSBpx7lkvl4Gpy46Yiz2azIS0tDVlZWRg2bBj69evnkQSw3rbk2Ww2WCwWFBcXY+TIkYiJifGIKPNWTVwOgUAAHx8fJCUlITk5GaNHj0ZgYCDq6+uRmpqKP/74A6dPn0ZhYSEMBkO758EwDBY99BC+B1Di4meKAWwGcP/ixa0ey44c59deew3btm3DwYMHHbYPGzYMZ8+eRVxcHOLi4hAfH8//cYKPW5e3efNmfu3dhAkT8Ntvv7W6Hg9oEE8ikQgrVqxodkw//vhj6PV63HbbbQ7bGwdiVFdX4/z587yrFQAiIyOxaNEifPfdd1iyZAk+//xzfl8yMjIQHR3tsB/x8fEOa1u5EmwKhQIqlYoPboiIiMBXX32FL7/8EjfccAOABmFVWVmJjIwMPPPMM5g0aRKSkpKapbvhjlVrFmLumB44cIDfZrVa8ddffznsH9dPd00ITem5UEsehdIKdrsdVqu1XaXJBAIBfwOora1FWloa5HI5UlJSPJrw15vRtfX19Th58iQIIUhKSoJW6+7Ks5bpsFC0mcDoSgDWDsi0IAq/VsdSKBRQKBSIiIgAIQT19fV8Uubs7GyIxWJotVrI5XK3j+fcuXOx7PnncY/RiC1tpFGxAbhXIIBCLsddd93l1jjuMGjQINxxxx1YuXKlw/Ynn3wSKSkpWLJkCRYsWACtVotz585h9+7d/Lo7bl3eV199hc2bNwNoEH5c+pOW1uMBDdbAN954A0899RSEQiHmzp0LmUyGH3/8Ec899xyWLFmCMWPGOHzmlVdegZ+fH4KDg/H8888jICAAs2bNAgA89thjmDJlCvr164fq6mrs2bOHF0gPPvggPvvsM8yfPx9PPvkkAgICkJ2djW+++QYff/yx0xREjRMzz5kzB1988QXOnz+PHTt28JY+sVgMPz8/fPLJJwgODkZhYSGee+45h36CgoIgl8vxyy+/ICIiAjKZjK8pzaFUKnH//ffjP//5D7RaLfr06YO3334bBoOhWWAFd42hUDwJPaMoFCc4y33nrigRCoWw2+3Iz8/H0aNHER4ejpEjR3q8ooO3Ai+Kiopw+PBhhIaGQqFQeK3AfHvmztRdguj8doiyfoEodxeE57dBUHSsQfC58nmGgUajQXR0NIYNG4bx48cjKSkJYrEYdrsdRqPRrbxsvr6+2PjNN/iFYXCDQIDiFtoVA7hBIMAvDIOvv/3W6zVsly9f3mzugwcPxu+//46cnBxMnjwZI0eOxIsvvugQPMAwDG+tGz9+PP85Hx8fDBs2rM21mI8++ii+//57HDp0CMnJyRgyZAi+/vprrFy5Em+99Vaz9q+++ioee+wxjB49GsXFxfjhhx8cLGWPPPIIBg4ciBkzZiAhIQEfffQRACAsLAy7du2C3W7H9OnTMWTIEDz22GPQaDQuCaY77rgD6enpCA8Px1VXXeVg6fviiy9w4sQJDBs2DEuWLMFLL70E4B8XqkgkwnvvvYdPP/0UkZGRmD17ttMxXnvtNdx4442YP38+Ro0ahezsbGzfvr3ZAxMhhHfZUiiegiE0CyOF4gDLsrz1DnCsR+kOBw4c4DP4DxkyxKNWsMb89ddfCAgIQFRUlEf6axz1O2TIEAQEBODQoUOIjo52O9ExF4Xs7IZrs9mwf/9+TJgwwb30K1YDRFnbAVMtiDocEAgBUy0ExkrYY64G698XQMOi/NDQULfmbLFYUFJSgqioKIhEIn4dJncD5mqtMgwDvV4PlUrlcG40rl17IxrSpPC1axkGmwEoFAp8/e23mDx5covz4Mq/Ne3fkxiNRr6urLfQ6XSQyWTtSq/jKt7eD0IIbDYbTCYTvzSCq8nb+HzoKDU1NSgtLUX//v1bbWcymZCXl4eYmBgaeUtpE+qupVD+hstIz629a6+4AxrWFel0OqjVaiQnJ3v1RupJS55er0dqaiqEQiGSk5Mhl8s9PkZT3O2XqS8GY6gE6xsNMH+LR5kPiEUHpioH+FvkdQSGYSAWi/myW1yUps1mg9Fo5OdstVodarJOmTIFuRcu4Msvv8Sajz7CNzk5fJ8JsbF4a/FizJ07t5lbrzfjbctUZ6QP4r5fpVLpEIRlsVh48ccJvvZa4+iaPIo3oCKPQkHz3HftFXiEEOTm5iI3NxdyuRyRkZFeFXiA5wIvSkpKcObMGYSHhyMhIaFZcmdP30zbG3jB2C0AwT8Cj0MoAWN1L3mwqwgEAggEAl70cWKPW8PFCQGRSASNRoOHH34YixcvRlVVFerr66FWq+Hn50ddcV6iM48rV4KNs05yDwB2ux0mk8mhtCH3AODK/OiaPIo3oCKPctnDWe+4J+n23jDMZjNOnToFo9GI0aNHIzs7u1NSm3Q08IJlWWRmZqKoqAgDBw50mtjVmyLPXYjMBxCIAKsREMv/3kjAmGvBamM8OMOW4W7GCoWCt+xwFVAau/M0Gk27xF1nnDe9ZYzOoLU0P00fABpbfTmvACf2WhN9LMt6bd0r5fKFPjZQLlu4tTZcgtSOCLyKigocOHAAEokEycnJ8PHxcYiu9SYdcaWaTCYcPXoUVVVVGDduXIuZ+72Zi8/dfokqBKx/PAT1RWB0pWCMVRBU54HI/cD69/PKHFuDs+xIpVIolUqoVCo+uMZisUCn0/F1Vl0J4mjatzfpDAtYZ7hru5OFlBN8crkcKpUKSqUSIpEILMvCZDJBp9PBYDDAbDbDbrfz50NHLHmrVq3i1+iNGDECf/zxR4tt//zzT6SkpMDf3x9yuRyJiYl49913m7X7/vvv0b9/f0ilUvTv3x8//PBDu+ZG6VqoJY9yWeJKaTJXYFkW2dnZuHDhApKSkhAeHs73IxQKOyWZaXvdtRUVFUhLS0NwcDCSkpJatSK0V+R5JQccI4A9YiyI3A+CqmzAbgEb1B9sQCKIwjMFwjoiaFty5zW17DR251G6Nx0RklyOPg7O6mu322EwGGAymVBTUwOhUMg/sLU2VtNzc9OmTXj00UexatUqpKSk4OOPP8a0adOQnp7OJ7dujFKpxOLFizF48GAolUr8+eefWLRoEZRKJe677z4ADXV5b7vtNrz88suYPXs2fvjhB9x66634888/m6W/oXRvaHQt5bKjI7nvGmM0GpGWlgabzYYhQ4ZArVY7vH/mzBlIpVL07dvxQIDW4Mo/JSUludSeEILs7Gzk5+cjKSkJERERbX7mxIkT8PPzQ3R0tFtzay26lhCCPXv2IDk5uf1RgoRt+BM0f149efIkgoODERYW5nJ3drsdRUVFCAoKgp9fy3n3WJaFXq9v9p27AsuysNlsvPADwAs+kUjEi/b29u8qBoPBIbikxfkSAqudgAEgFgngzq+lvr4eSqXSq2vNOiOCl1t7qWxa+cQDmEwmVFVVoa6uDiaTCUKhECqVChqNBoGBgc2uT1w1kfj4eIjFYowZMwbDhw/H6tWr+TZJSUm44YYb8Prrr7s0hxtvvBFKpRJffvklAOC2225DXV0dduzYwbeZOnUqtFotNm7c6IG9pnQW1JJHuWzg3LOcy6wjAq+0tBRnzpxp1QrWGTVluXFcdQtbLBakpaXBaDRi7NixLosIb7jDPFLxghE0D8DoAEKhEEqlEuXl5QAAuVze4vopLrKyvXAWP25NKOe+42oic/n6vOWKNJvNvJWxJQwWO+pMVthYNIg8IQNfhRgSYdvHnBACi8XisRQjLWGxWMAwDC+YvQF33ejI990afn5+MBqNUKvVUCqV0Ov1qK2tbVZ6j2VZlJeXQ6FQQCQSwWKx4K+//sLSpUsd+ps8eXKzSictcfLkSRw8eBCvvPIKv+3QoUNYsmSJQ7spU6bgvffec2u/upsr/XKEijzKZQFnPTl69ChiYmLg7+/fbvcsF6QwYMCAVnOwdZbIczXworq6GqmpqdBqtRg2bJhblg9vrcnrjjcAzoLXWnF4QgjMZrNX8pQ1jtYE/lnYz/15CovF0qq72GonqDNZQQAI//6e7CxBkYCBj1wMgQtfnclk8nouN7PZDIlE4tVzifs+vBkpX1FRAZlM5pBoOj8/v1k7gUCAPn36gGEYVFRUwG63Izg42KFNcHAwSkpaL7IXERGB8vJy2Gw2LFu2DPfccw//XklJSbv6bEp3/H1fblCRR+nVNM19xwVZtOfio9frkZaWBgAYN25cm64bgUDgVjHz9tJW4AUhBPn5+cjOzka/fv34G4S7Y3hLsHa3FSMMw8Df3x9arbZF65DJZEJqairGjh3rlTkYDAacOXMGQ4cORV1dHerq6lBbWwuLxQKVSgUfHx/4+Ph0yBV66tQpREZGtpik+39Hi3DiYj0itXJ+m50lKKox4ebhoUiJbdmdDTSIyBMnTmDUqFFeXXd49OhRDBw4EAqFwmtjFBcXQ6/XO13j5imWLVuGmTNnNqvr2xSJRNLsO2/6e3bFgvbHH39Ap9Ph8OHDWLp0KeLj4zFnzpwO9dmY48ePIzc3F0ajETKZDGq1GhqNBhKJBMOGDWtzmQDFM1CRR+m1NHbPAv8kNW1PxOulS5f48kdNc8i1RGe6a1sax2q14syZM6itrcWoUaPaXUbLm5a87ibyOJoumG+Mty073MOISqWCSqXi1xUajUZUVVWhuroaRUVFYFkWWq0WWq0Wfn5+UCgULt+I7XY7RCJRi/twvtIMg12AWkvjrQwqjQQlOrbNfed+fzKZzGsWHe7BTSqVetXKxgkcb46Rl5cHsVjsluUzICAAQqGwmYWtrKysmSWuKTExDemGBg0ahNLSUixbtowXeSEhIe3qk+OHH37A008/jcrKSkgkElgsFn55gMFgwMWLFxEeHu7qblI6ABV5lF5J49x33BonwP2I18YlvgYPHoygoCCXP9tZKVRactfW1dUhNTUVCoWiw1U3eqK7tqe7ipzNXy6XIzw8HOHh4Xzps6qqKlRWViInJwcikQh+fn686GutTnJblpkwHykuVDoml7azBIQB/JVtW2FYlu1Q1RhX4M5Jb0cod0YOO4PB4HZgh0QiwYgRI7Br1y6H2rm7du3CrFmzXO6HW37AMW7cOOzatcthXd6vv/6K5OTkNvthGAaPP/44Jk+ejCeffBIhISF8ZLnVaoXRaHQrGIrSMajIo/QqGpccchY9644lr76+HmlpaRCLxQ4lvlylMy15jQUYIQSFhYU4d+4cYmNjERsb2+EbbXfKk9cd+va29dGV/hmGgVqthlqtRlRUFOx2O+rq6lBVVYWioiJkZGRAoVDwok+r1Tqsw+REWEtc1dcfqYV1KKw2IVAlgY0QlNaZEeYjw6go3zbn11b/noD7fXm7UoS3S44RQvhayO7y2GOP4a677sLIkSMxbtw4fPLJJygoKMD9998PAHj66adRVFSEDRs2AABWrlyJPn36IDExEUBD3ry3334bDz/8MN/nv//9b0yYMAFvvvkmZs2aha1bt2L37t34888/W50L932Xl5dj6dKlbkfjUzwPFXmUXoMrue9cEV6NRVJ0dDTi4uLadYHvrDx5jS15NpsN6enpqKiowPDhw+Hv75m8cd7Ik+fK+5cr7YlKFAqFvJgDGlz1NTU1qKqqQk5ODh+9yYm+tkTY4HAN5o+NxA9pJSjXWSAQMEgIVuHOUeHQKtq25HER7N6ks0Qey7JeTdECoN0i77bbbkNlZSVeeuklFBcXY+DAgdi+fTuioqIANKwnLCgo4NuzLIunn34aeXl5EIlEiIuLwxtvvIFFixbxbZKTk/H111/jueeew/PPP4+4uDhs2rTJ5Rx5Tz31FLZv34777rvP68eN0jr06FN6BVxKi7Zy37VlybPZbDhz5gyqqqowbNgwBAQEtHtOnW3J0+l0SE1N5S2Pnoxq7KmWPG/S3atRiMViBAYGIjAwEEBDsEh1dTWqqqpw6dIlWCwWZGdnIygoCFqtFiqVqtmYE+L9MCrKBwVVRoiFAkT5ySF0JawWnVOLlft9efu78HZkLdDgrm2PyAOABx98EA8++KDT99avX+/w+uGHH3aw2rXEzTffjJtvvtntudjtdpSWluLNN99EUVERBg8eDD8/P6jVan6NKbXwdR5U5FF6NJx7louebSv3XWsir7a2ll/DlpKS0up6JlfoTJFnMplw6NAh9OnTB3379vX4zfVyDLzoSrxxTGQyGUJDQxEaGgpCCP744w/4+PiguroaeXl5EAgE/Fo+rVbLL0+Qi4VICHZffHRGjrSOJjR3ZxxvrsnjciJ6I9lyZ2MwGLB7924MGzYMX331FT755BOYzWY+F6Svry+qqqpoDr1Ogoo8So+lPaXJnAVDEEJw4cIFZGVlIS4uDjExMR65+HSGyGNZFkVFRdDr9Rg+fLhbgSHu4GouPmef68j7HaEzFvx7s//OODahoaFQqVRgWRb19fWoqqpCcXExMjMzIZVK4efnBz8/P/j6+rptyeosS563xwC8vyZPp9MBgFcrnHQWarUahw8fhsViASGEv05brVaHZNJU4HUOVORReiTtLU0mFAodcp9ZLBacPn0a9fX1GDlyZIs5w9qDt0We0WhEamoqnzvNWwIPaL/Ic4WeGHjhbTrDytF4DIFAwOfei4mJgc1mQ01NDaqrq5Gfnw+dTge1Ws2v+fP19W3TstVZgRedJfK8acnT6/UA0G53bXejvamaKJ6HijxKj6Jp7jt3XTWN3bVVVVU4deoUNBpNh1OMOMObIq+srAynT59GSEgIAgICkJWV5ZVxOHpiChVXuVRrwta0Upy+VAdfhRhTkgIxId6v1weNtCYkRSIRAgIC+DWpFouFz8937tw5WCwW+Pj48Ja+puW3uP57etQrh7fdtQaDAVKptNckCDaZTNi7dy8uXbrEXze0Wi1kMhmCgoIwcuTILp7h5QMVeZQeA5f7riMRdQKBADabDTk5OcjNzW13BQhXx/J0njyWZZGdnY0LFy5gwIABCAsLQ0VFhdfdwm1V1WiJiooKGAwGBAQEtLjGsSutbbkVBjz2fToqdBYwDEAIcCCnGrePCMUDE6K7bF6dbclrC4lEgpCQEISEhIAQ4pCUmYvc9PX15dfzKRQK6q51A51O51Yi6+6MwWDAypUr8dFHH6G+vh41NTXw9/dHZWUlAGDixIn47bffYLPZaORtJ0CPMKXb07g0WUcXWrMsi5qaGuj1eowePRo+Pj4enu0/eDqFitlsRlpaGsxmM8aNG8e7dtorwNzBXUsey7LIyspCQUEBFAoFMjMzoVQqHdZ4CYXCLg+8+PRAAcp1FvgpxRD8fU7pTDZ8d7IEU/oHITbAeamsnr4mj1sr1Z4xGIaBQqGAQqFAREQECCH8er7y8nJkZ2fzlRu4xfYdDWJqic4Sed625Ol0uh4fdMGdT8eOHcMnn3yC9957DyKRCM8//zwOHDiATz/9FLt378b7778PAFTgdRL0KFO6Ne0JrmiJiooK5ObmQiAQIDk52esXGU+6a6uqqpCWlgY/Pz8MHz7cYe7eXC/XeAxXhY3FYkFaWhpMJhNGjx4NiUQClmVRXV2NyspKnDt3DlarFT4+PrDZbDAajfD19fW4qGmrP5PVjr8KaiETC3iBBwBKqRBVBiuOXahpUeR1Bp0ROOIJgcQwDDQaDTQaDaKjo2G321FbW4uLFy9Cp9PhwIEDUCqVfOSur6+vx357erMN2bUEpuwqhGikiA9UOHyXnsLbljwufUpPtuRxIi87OxsBAQGYPXs21q9fD6lUCqVSiUcffRTFxcVYsWIFVq5c6fV1jpQGqMijdFsalybrqPWOsyqFh4ejurq6U54iPSHyCCHIy8tDTk4OEhISEBkZ6TTBc3ex5NXW1uLkyZPw8fHBuHHjADQk5RWLxQgKCkJQUBAIITAYDKiqqkJtbS3Onz+P3Nxc3sqn1Wq9ZvlpDMMwAAOghd1q63Tr6dG7gHf2QSgUws/PD0ajEQDQv39/VFdXo7q6GllZWTCZTNBoNLzo02g07RJQuRUGrDlUioJKG1RlhZAKBRgcrsZdYyKgkHhWPHjbkqfX63uFJQ9oEKyNc3RKJBKUlpYiODgYer0epaWlDu0p3oWKPEq3o63SZO5gNBqRlpYGm82GcePG8WuJOgNOfLXXLcZF/up0ulZdy52RqsUVkVdYWIiMjAyHNDSNI5kb96VUKqFUKlFUVIS4uDiIRCJUVVXh4sWLSE9Ph0ql4kWfj49Pu2+wrc1ZKhJgbLQvfsushEJMIPg7yW+92Q6ZSICx0Z6LtHaXznDXAt4Vqlx0bWOBDzT8JjnR91fqKVjtBCH+/wRxKJXKNudltrH4v2NFKK63IFgpQGigAjqzDUcu1CBII8XsISEe3ZfOWJPX00Ued3xiY2MRFRWFoqIiDB8+HB9//DHeffddDBw4EL///jvuvPNOAD0/cKmnQEUepVvhSfdsaWkpzpw5g+DgYCQlJUEoFMJisXg8GKIluItee6wAnEWMi/xtLequM9a1tTYGy7LIyMhASUmJ26XUGIbhk/BqtVrExcXBarWiqqoKVVVVyMjIgNVq5Rf1uyoCXOXelD5IL9GhpNbMW/XEQgZ3jolAH7+WaxV3hhWip4u8lqJr5XI5bIwYxyqESDWIYTJboTXakVRfAc3fSZk5i66fn5/Tyi2ZpToUVpsQqhKDtTXsi0oqgo/MjqP5NZjWPxAysWcsbyzLghBCLXltwJ1LycnJUCgUMBgMGDx4MObOnYsXX3wRNTU1uPPOO3H33XcDAHXVdhJU5FG6De3NfdcUlmVx7tw5XLp0CQMGDEBoaCj/XltlzTwJd4NzZ+0JIQQXL15EZmYm4uPjER0d7VKC566y5JlMJpw8eRKEECQnJ/NVEtyhab9isRjBwcEIDg52cO1WVVUhNzcXIpGIF3x+fn4dSn0TqZVjze2D8POZMpwprodWLsY1iQEYFeW9gBxX6MnuWo6W8uRZ7Sy+/usS0orqoJWLoZBKcMlggQ5SzB3dDwESm0NSZplMxos+rVYLsVgMo9UOG8tCyBCQRmNIxQKYbSwsdgKZh7KRcL8tb6dQ6S058rRaLSZOnMi/fuCBB7Bw4ULY7XYoFF23xvVyhYo8SpfT0dx3jdHr9UhLSwPwzxNlY7yR1qQlGlvyXIGrm1tdXY0RI0bAz8/P5XE64hZ2BWcir7KyEmlpaQgMDET//v2d3gQ7mmuusWs3MjISLMuitrbWo67dAJUE88ZGuPUZV+beEbztru2Mmq8tRb5mlemRUaJDH60c8r+tbT5yEXIqDDicX4M7R0fwyXS5pMxVVVXIy8vDmTNnoFarYZNoIGFY1JntUIr+2YdqvQ19gxRQST0nyDqSsslVeoO7FvjnvC0uLsaRI0dQWFiIlJQUDBs2DPX19aivr+8VVT16ElTkUbqUprnvGIZp943n0qVLOHv2LCIiIpCQkOD0ouzptCatwYlVV8arr69HamoqpFIpkpOT3Qo84I6XN4VBY2shIQT5+fnIzs5GYmIiIiIiOjSuO1arpq5di8WC6upqp65du93eYxd3d8aavI781lwdw9lvsFxngY1leYEH/B2hKxMhv8rosO9NkzKbzWY+SjtMpENqOQuZiIHOxsDICqCRS3FNYqBHI2ztdju/rMBb9AZ3LQBe4D3zzDM4evQoMjIysGzZMgwbNgzfffcddu3ahRdeeAGJiYldPdXLBiryKF0Cl/uuoKAAhBCEhYW1+4Zjs9mQkZGBsrIyDBkypNXyXkKhkB+7M/JrueJKLSoqQnp6OqKjoxEfH+/2cWhsMfTWPnGWvMbWxlGjRnW4fFFH1xNKJJIWXbvV1dWoq6uDTqfziGu3Mb1hTV5nlBxzNgYX+WpnCYSCf943Wu0I1khbnZdUKuWTMsf3s+P/9p7CiUtGmK1W+AmsGCzXQVjNoohpcO/K5fIO72dnVNXQ6/UICwvz6hjehluW8u677yI7Oxu//fYb5s6dy7uhp06dik8++QQXL15EYmJip5yDFCryKF1A4+CKuro62O12hIeHt6svzgImkUiQkpLidJF2YzhXXmeVQ2pN5NntdmRkZKC0tBRDhw5FYGBgu8bgLpTetFBykbKHDx+GRCJx2drYmaXBmrp2T506BYlEApFIhIKCAqSnp0OtVvPru3x9fTvlHGgPPT3ZMjeGs+ObGKxCqEaGC1UGRGrlEAkYVBmssLPErbWQUrEQKX0UuCJajT7RMRALGtye1dXVKC0txfnz5yGVSnnLb3tFvrfTpwC9a03erl27sHjxYoSEhKCiooK3UIaGhqKsrKyLZ3f5QUUepVNpmvtOLBbDYrG43Q8hBIWFhTh37hyio6MRFxfn0g3b3XVyHaUlkWcwGJCamgqGYdodsNB4DMC7woCziEVHR6Nfv34eFUfemjdXmaFPnz4A/qm/WlVVhfT0dNhsNv7m7+fn53ZZqZ5saessS54zcaSWiXDL8FBsTi3BxWoT7IRALRXimsQAjOzj69YYdrsdcomEj6T18fGBj48Pn5S5pqaGL73Grd/kvnMfHx+X8mV2liWvN7hrgYbfhdlsBtDwm9NqG1IRlZSUwGw2d9j6T3EPKvIonUJLue/aE+1qtVpx9uxZVFdXu52ygxu3M4Mvmoq80tJSnD59GuHh4S2uHXQHb1ryCCHIzs5Gfn4+ZDJZu9bStCYmOrOsWdP6q3q9HlVVVaisrEROTg7EYrFDQmZPuXbbS28QeS2d2/GBSjxyVTRyKgyw2lmE+cgQpHY/AXZrYwiFQvj7+/PXB4vFwgdxZGZmwmw2Q6PR8N+5Wq122ldnWPJ0Ol2Pt+Rxx2jBggX46quvMGHCBOh0OpjNZuh0Orz00kvo168fIiIagpyoq7ZzoCKP4nVay33nrsirra1FamoqFAqF2wEKHJ2dRoUbi2VZnD9/HoWFhRg4cCBCQjyTsJVbQO9psWSxWHDq1CkYDAYkJibyhehdQWey4eiFalyo1EMqBEb08UWMf/dJn8AwDFQqFVQqFfr06cOX4qqqqsKFCxdw9uxZ3rXLWX0aC4Ce7k5tab2cJ2nJXcshEwsxILRjkZburEOVSCTNkjJzazcLCwvBsqyDa5ez7HaGJc9gMPSaqNN7770Xf/75J5566imUlJRg/fr1WL16NTIzM7F582aHlFYU70NFHsWrtJX7TigUOq2K0BRCCC5cuIDz588jPj6er6jQHjojrxwHF81rMpmQmprKV97wtGvG0/tUV1eHkydPQq1WY9y4caitrXVZ2FTozHj/91ycL9U1WHBZFrvPVWLOyDBc2dfR6upNS5475wdXiotLW9PYtXv27FnY7XaHhMydlcfOm/13VeCFp8dorwCTy+UIDw9HeHg4CCH8ej7OsisSiaDVajuU0slVeoO7lotml0ql+Oqrr/Dpp58iIiIC5eXlGDp0KL766itER0d39TQvO6jIo3gNzoLXWnJjkUjUplWNK+9VX1+PUaNG8Ws82ktnW/Jqa2tx9uzZVvPJeWIcT4k8LhVNbGwsYmNj3bYU/nSqBOdK6hHtr4BI0GAJKak349uTxRgQqkaA6h83aHd12bTl2uXOodLSUvj5+bVakaQ99IY1eW1Z8jyBpyLKGYaBWq2GWq1Gnz59HPIxlpaWwmQy4fDhww5BO576zrnzq7e4a7n/v//++7twNhQOKvIoXoMTB609CbcluKqqqpCWlgZfX1+kpKR45MLaWSKPEAKz2Yz8/Hz079+fX4viDTxhEeMqhRQXFzeL9nU135/FxuL4hRr4yMUQCwW8mAjRSJFXaURGiQ7j4x2TPHvTauWJvp25di9duoTc3Fzk5+dj55GzKLTIQERyJIT64Kr+YQhUtx7l7eq43qKzBFhXBXd0lMb5GMViMaqrqxEWFobq6mrk5OTAaDRCrVY7BHF05Hj2BkveCy+8AIVCAYFAAIVCAbVazQfC+Pj4QKPRQK1WIzg4uKunellBRR7Fq7R1kW9JcBFCkJOTg7y8PPTr1w99+vTx2A2jM6pecOvZzGYzYmJivCrwgI5b8kwmE9LS0nh3ctNKIa6KyAb3LIGgyVfFAABpyI3Wnn67E0KhEGq1GiKRCLWaWBzJK4bOaAaxmXCysB67T1/ErQM06BcR0K6oXaD3uGt7iiWvrTHEYjECAwP5Bx+TycQn4T579ixsNht8fX150adSqdw6vj19TZ5er8crr7wCAOjfvz+kUinKy8tRV1cHi8XCVzSSSqUwGo1dPNvLCyryKF6lrZu4SCRqtibPZDLh1KlTMJlMGDNmDDQajUfn5O2qF9XV1UhLS4OPj49HE/C2hquWNmdUV1cjNTUV/v7+GDBggFPLCFc6rS2kYiEGhWuw93wF/JQScLe5Sr0VapkI/YIdrRXd1V3rCrVmgt8zyiETixDl17BfNpbF+ZJ6nKkVwU9W4RC16+/vz1uG2oK6a12jM0Ses8ALmUyG0NBQhIaGOiThrq6uRn5+voMl0M/Pr9UUSVarFWazuUdb8oRCIebOnYvs7GyEhobimmuuwciRI9GnTx/o9XrU19fDaDT2uAe63gAVeZQuhbPkcTed8vJynD59GgEBARg+fLhLeazaO6an4YJDsrKy0LdvX0RFRSEtLa1TgjxcFWGNIYSgoKAA58+fb9Na6o7FbeagEGSX65FTrodMJIDZZodYKMDMQUEI82nuxuwOgRftodgA1BhtiAv4x+opEggQpJGjyAgkDewPsQDNaq82Ttuh0WicipTeEF3b3QMv3BmjNZews/rK9fX1/Ho+Likzt56vaXoenU4HAD3akieTybBy5Ups374dW7ZswbfffovTp0/j6quvRnJyMg246EKoyKN0KdzF02azITc3FwUFBUhKSkJ4eLjXbhDeEHlWqxVnzpxBbW0tRo4cyQeHdFYkr7vj2O12nD17FpWVlQ7zbQl3RF6UvwL/mdwX+7MqcK6kHiqJAGNitBjZp3k1g86wJnmrX4b5xw2NRrtBQCD4ez2qUChwyNVmNpv5qN3Tp0/zaTs40eeJMlyuz59a8lzBbre7tRZYIBDw69BiYmJgs9mapedRqVTw8/NDSUkJ7wJuT+DFqlWr8NZbb6G4uBgDBgzAe++9h/Hjxzttu3nzZqxevRqpqakwm80YMGAAli1bhilTpvBt1q9fjwULFjT7rNFobLOakFKpxC233IJbbrkFBw4cwDfffIPXXnsN4eHhuP322zFnzhy394/ScajIo3iVtm4knKXu2LFjYFkW48aN83qUmTfSjTTO3df4Kb0z1v8B7okwg8GAkydPQigUYty4cW1evN3tHwBCfGS4dWQEWJaFxWJp9UbcU1044UoGvhYxSurNCP275qrNzqLKYMWkhABIRc33WSqVOrj5dDodqqqqUF5ejqysLN7i40paoY5A1+S5N0ZHgjtEIlGzpMzcer5///vfyMvLg1arxZtvvolrr70WI0aMcMmDsWnTJjz66KNYtWoVUlJS8PHHH2PatGlIT0/nq7w0Zv/+/bj22mvx2muvwdfXF+vWrcN1112HI0eOYNiwYXw7jUaDzMxMh8+6co3gatcCQEpKCpKSkrBt2zY8/PDDyMvLw5w5c2i92i6AijxKl8LVMlQqlRg4cKDXM8sDnrXkFRYWIiMjAzExMYiLi3OaB7A7WfLKy8tx6tQphIaGIjEx0eUbpLcCJHryBV8tYXD9oGB8n1qMrHI9hAIGLAHiApSYnBjQ5ucbp+2Iioriy3Bxos9qteL48eNtunbbQ2+Kru0MS54nr0sSiQTBwcEIDg7GsWPHsHXrVjz22GNITU3FihUrwLIs/u///g8zZsxotZ8VK1bg7rvvxj333AMAeO+99/DLL79g9erVeP3115u1f++99xxev/baa9i6dSt++uknB5HHMEy7ErULhUKcPn0ahw4dwpkzZ3Du3DlcunQJM2fOxPz5893uj+IZqMijdAl2ux2ZmZm4dOkSBAIBYmNjO0XgAZ4ReXa7Henp6SgvL8ewYcMQEOD8pt6ZlrzWRB4hBLm5ucjNzcWAAQMQFhbWYtvCaiP+yK5EvcmG2EAFUmL9vSryeqolj2EYjI/3Q7ivDGlFddCZbIjUyjG8jw80MvcvrY3LcAmFQhgMBvj7+7fo2m0aAe0OvcFdSwjp8dZCgaDBna9UKvHtt9+CZVmkpqYiMjKy1c9ZLBb89ddfWLp0qcP2yZMn4+DBgy6Nza0d5BKAc+h0Ov6hY+jQoXj55ZcdRKAzsrKy8OGHH6K+vh56vR4+Pj54+OGHcd111zm068kPdT0VKvIoXsXZj1qv1yM1NRUCgQDJyck4cuRIpyUnBjouvPR6PU6ePAmxWIzk5ORWXRkCgQBWq7XdY7lKa4EXVquVTybdVrTynsxyvPtbDuqMVoABGDBIDFHh2ckxIIR4RRz0RJHXeM6xAQrEBni2ZBshBCKRyCXXLreg3511Y73BXcs91PQ0S15TuETIXC3vESNGtPmZiooK2O32ZjnngoODUVJS4tK477zzDvR6PW699VZ+W2JiItavX49Bgwahrq4O77//PlJSUpCWloa+ffu22NeePXvw0UcfwdfXF7fccgsmTJgAo9GITZs2QS6XQ6vVQqFQIDw83GPlHCmuQUUepVPhqilERkaiX79+EAgELpc28xRCoRAWi6Vdny0pKcHp06cd5t8aXR14UV9fj5MnT0KhUGDcuHGtpnOp0lvwwZ5c6M02hPrKIGAYWGws0ovr8dXxYgxubQKEAMYqgNgBuR8gcO3S0l3KmnU3moqw1ly7eXl5DrV2/f39oVarWz03e0N0bWeKPG+O0ZFEyE2Pr6vifePGjVi2bBm2bt3K1/IFgLFjx2Ls2LH865SUFAwfPhwffvghPvjggxb769+/P66//noIhUKcPHkSv/32G0wmE58ehhCC+vp6LFq0CKtXr4bNZvNK5gRKc+hRpnQKNpsNGRkZKCsrw5AhQxwuLK6UNvMk7XHXsiyLzMxMFBUVYfDgwS5nbe8skefMXVtcXIwzZ84gOjoa8fHxbV78j+ZXo9pgRYhGCsHfbSUiAZQSIQ7kViMxqoWbiL4Mgvw/wNQUAIQFUQWDRI4D8Y/z6D62B29aCb0tklrrv7FrF2jILclF7RYVFYFlWd7K1zRPGyEEeVVmpF00I91ShCh/BYZGaCAXe9Za5W13bWeJPG9V1eDQ6XRui7yAgAAIhcJmVruysrI2r02bNm3C3XffjW+//RbXXHNNq20FAgFGjRqFrKysVtuNGzcO//vf/wD840a32+2w2WywWq2wWq3Q6/X8+UoFXudBjzTFqzAMg/r6eqSmpkIikSAlJaWZe7Mza8kC7rtrjUYjUlNTQQhBcnKyW2uhOmtNXmN3LcuyOH/+PAoLC5sJ6tYw2VgAzatVCAUMbCyBnThxwVn0EGRuB1N7EUQdBjBCMHWFYM5vh33ATYCqdddMT16T503cPSYymQxhYWEICwvjrSaN87TJZDLerXus1I7NJ6uhM1mhqqkAA2BAmBr3JPeBuh1rCVuiMyx5XNlEb9IdLXkSiQQjRozArl27MHv2bH77rl27MGvWrBY/t3HjRixcuBAbN25sM7ADaDgPU1NTMWjQoFbbCYXCHl97t7dCRR7Fq5SXl+PYsWOIjo5GXFyc04tlV7hrXbWucdGowcHBSEpKcvuJvrOja81mM9LS0mCxWDBu3Di3bh4DQtWQiYWoN9mgkTes7yKEoM5kw/BIH8iEdc3EB1OVC6a2EMQvHhA0HBsiiQVTkQmmLN0lkdddMVjsOF+mg9nGIlIrd0jk3J3LjjEMA41GA41Gg+joaNhsNt61e/hMDr7ONEMkECBUIYTWRwyWEeJ0UT32Z1dixkDP1BXljo+3LXneFnjcON605BkMhnYJpMceewx33XUXRo4ciXHjxuGTTz5BQUEB7r//fgDA008/jaKiImzYsAFAg8CbO3cu3n//fYwdO5a3Asrlcvj4NOSwXL58OcaOHYu+ffuirq4OH3zwAVJTU7Fy5UoP7S2ls6Eij+JVfH19MWLEiGYRXI3pju5aQgiys7ORn5/fZjRqa3Smu9ZoNOLQoUPw9fVtV7WQ+EAlrk0MxM9nSqG32CERCWC02OEjF+PO0REoP3epubix1Df8K3C8CRKJEoy+zKVxu6MlL6NEh6+OF6G41gyWEKilIqTE+eHGoSEQNTV1ukF5vRkHcquRXa6Hj1yMUVE+GBKucSroPCWARSIRAgICEBAQgAK2ApLCi/ATmmCz2lBeUQEAsNtF2J9xCVfHaVotweUqneFK7SyR1x0teQBw2223obKyEi+99BKKi4sxcOBAbN++HVFRUQAalmsUFBTw7T/++GPYbDY89NBDeOihh/jt8+bNw/r16wE0VGe57777UFJSAh8fHwwbNgz79+/H6NGjO7aTlC6DijyKV+HqdrZGZ7tr2xqPs4aZzWaMHTu2Q+WGOkvkGQwG1NTUoF+/foiOjm6XQGAYBo9cHYe4QCV+SS9Dld6KlFg/3DQ8DInBKvx6zokgEysBEICwAPPPjZCxGsAqXcsV192oNVqx4UghynUWRGplEAkYVBus+DWjHCFqCSb0bVhX5O7ci2pM+HBvPi5WGyERCWC1szicV41Zg4Nx/WBHi6e3hK/973VyYrEEIqEIWq0WFosFpioddAYjDh8+zLt2Ofdue9ZPcee8t9213hZ53Poyb6/Ja6+r88EHH8SDDz7o9D1OuHHs3bu3zf7effddvPvuu+2aS2M6S4BT2oaKPIpXceUi3xVr8loSXlVVVUhLS4NWq/VI7Vxvizy73Y6MjAzU1tYiKCgIMTExHepPLBTghqFhuGGoo+WSEx1NxQfxiwNRh4GpygFRhzdY9HSlgEQFEpjU5njejq5tT9+nL9WjtN6MGH8FhH9b7fyUEujMdhzMreZFnrv8fLYMBdVGxDbqt1xnxs70coyO9kWIxtEd7A2BFBeggEIshM5sgfLvQGuBSAy7QIpJgyIxfmAg79rNycmB0WhsVmvXlXn1FnctlzbI2+5aLiChp1NaWorg4GD+e6EVLroeKvIoXU5XrMlrKioJIcjLy0NOTg4SEhIQGRnpkYuTN0We0WjEyZMnwTAMwsLCvHoj4o5FM9EkVYFNmA5B3j4wdYUAy4IoA8D2SQZ8ImGzWFBVVQVfX98WBXN3c9fqLQ3nhrCJW1YmFqDGaOVv/O5gtrE4U1QPrVzs0G+AUoLcSgNOFdbhBKnDqaI6SEQChAnMGBnpet47V4kLUCAlTovtqTrUmIB61giTjUVcgAIT4v0dXLtAwznGleC6ePEiADSrteuM3mLJ464T3nbX9vSgBe67WL58OUQiEW699VYMHz68Qwm7KZ6BijxKlyMSiWA2mzttvKYij0sWXFdXh9GjR/OLkD2Bt6JrKysrkZqaipCQECQlJSErK8vrQrlFy5g6FOygWwF9OcDaAWUAIJTAYDDgxIkTMJvNsNls0Gg0fNoPLvlre0WAyWoHSwCFxPPCNkQjhUjAwGi182lFCCGoM9owIFbbPlf43/8haGIJBWBnCf7v2CWU1JsbPN8AiN2KrBoWz8V61hLCMAxuHR4GqakKmZVWyDUqJAYrMTZaC19Fc1Epl8shl8sdonYrKytRUlKC8+fPQy6X84KvsZDnIl97usjrjLWFvUHkcd9zYmIiNmzYgCNHjmDkyJGYNWsWhg4d6nKEP8XzUJFH8Srd3V1bW1uL1NRUqFQqJCcnt5osuD0IhUKPWqoIIcjPz0d2djaSkpIQEREBwEnFC5sZTPFJMLWFDda2sBGAMrBDY7dqlWQEgOqfyExOhIaGhiI6OhpWq5XP43bhwgUIhUL4+fnBYrG4VPyco6zejI3HL+FwXjVYAvQPVeH2EWFICPbcTbJ/iAr9Q1RIK6yHj0IEsVCAaoMFPnIRJsT/s77UHQEjEQkwPFKDXzPKoZWLIRI2fF+l9WaYbCzKdRaEaKSQiBrERFmNDX8WGHGysA7DIz330AE0WCgHBEowJFSBuDjX3fuNo3ZjYmJgs9l4K19WVhZMJhN8fHx4C5+33XTeDojgxvB2mpaOJEPuLnAPgI888gjuvvtubNq0CevWrcPPP/+M5ORkzJs3D6NGjYKvry9dq9fJUJFH6XK6yl1bUFCAzMxMxMXFISYmxis3JU9a8mw2G06fPo3a2tpmFkcHAWasgfDQe2CK0wBiB0MIBKoQ2EcvAgkf2e7xXVnjRgjBhQsXkJWVhaSkJISFhfFCLjw8HOHh4WBZFrW1taiqqkJlZSWqqqqg0+narNagM9vw8o5sZJXpoJKJIGSAQ7nVyCrT4+XrEhDj/49ryGCxY3+BCWcr9BCfNGFIhAaTkwIRopG2uZ9ioQALk/tgZ3oZjl+ohdXOYmCoGtcmBXZITM4YEITcCiNyK/RgwIAlBCqZCFKRABaRgBd4AKAUMyg3EJwoqPW4yAM8s1ZKJBIhMDAQgYENDw9Go9FByLMsizNnzvCWPnfEvCt0liXP2zW19Xp9h4K7ugsMw8BisUCpVGLhwoVYuHAhjh49imeffRbTpk1DYmIiFi1ahHnz5sHX17erp3vZQEUexeu0JQ4625LHzSU7O7vN9C4dxVNr8nQ6HU6ePAmZTObU4ti44oUg4wcIio6D+EYDYjkIYcFU5UF4/HPYAhIAaftuKG19j3a7HWfPnkVlZSX/1O5s3wUCAbRaLbRaLQghsFqt8PX15YNeAPDCwN/fH1JpgzD7M6caOeV6hPpIIRY23Nw1MhEKa8zYfqYMD10ZDQCw2lms2p+P/dlGSIQMlHYLfjxVitTCOjx1bZxLQk8jE+HW4WG4flAwLHYCtVToIIraY50NVEvx+KQYHL9Qi/wqA9RSEYb38cE7v+VCZ3b+kMN6abmiNxbEy+VyXsjX1tYiLS0NSqUSxcXFyMzMbNG12146a02et8foDZY8Du66VFhYiOzsbJw9exZxcXHIz8+HSqXC22+/jVdffRWff/45rrvuui6e7eUBFXmULqcz8+RxYgkARo0a5fUnaE7kdeSmWlpaytfL7du3r9ObDu+utZkguHAARKYFxH8vimcEINoooCoXTOlpkD7J7ZpHayLPZDLxx3XcuHFuWW0EAgFCQ0MRGhrqsO7r0qVLyMzMhFKphJ+fH84V2cASwgs8bk5SEYOMEh2/LbWwDn8V1MJfLoBCIoRKJYWdJcivNGL3uXLcOTrC5bnJxELIPBj/4CMXY1KiY2qZcTFa5JQbYLOzEP29b0YbgUjIYGiExnODN8Lb1Si4iNSYmJg2Xbt+fn5Qq9Vuz6c3WPIIIb1iTR7H1q1b8ddff+HUqVM4f/48CCGYPn06vv/+ewwe3FD9evny5bj//vsxdepUiMWeDy6iOEJFHqXL6SxL3qVLl3D27FlERUUhNze3Uy4wHUklQAhBVlYWLly4gEGDBiEkpOXqEbzF0G4DWCsgbLJvjBAMWMBmcnsf+C5aEHk1NTU4efIkAgIC0L9/f7duik2PSdN1X43X8tVVVsBkYlFXZ4NEIoFEIoZAIIDVThyCBnLKDbCzBDLJP30LBQwUEiFOX6pvx567Nvf2MnNgEI7k1yCrXA/h38fYaiUY10eB4X0876oFvJ/aoqkAa+raNRgMvOi7cOECb911x7XbWZY8b7trDQZDr7HkffTRR9DpdBg9ejQee+wxTJgwgX+PO+fuv/9+LF++nAq8ToKKPIrX6Wp3rd1ux7lz51BSUsLXcs3Pz++0mrKA+zcki8WCtLQ0GI1GjBs3rs0nfd5dK1GC+PWFoPAoiNwP4G7kxkoQiQbEL67d++LseywsLERGRgb69u2LqKgop6KtLVo7N8RiMYKDgxEcHIw7A/RI+yEddWYrVMQMvd4AE8vABiFGhkr4G7JExDREqDbp18ayfLRsd8JPKcGr1yXg13PlOHmxDjKRABGielyd6N+h6hqt4W2RR/5OutwSCoUCCoWCX6PJ1dp15trVarVOhVZnWfI6w13bG9bk6fV6hIWF4d133+WXwHC/wcaR1oGBgcjLy+uyeV5uUJFH6XJEIpHXAi8MBgNSU1PBMAySk5P5vF6dZT1sLPJchYv4VavVSE5OdmntEu+uZRiw/W8AU5UDVGQCMh8wViMIYcEmXgf49Gn3vjQWeSzLIjMzE5cuXcLw4cNbTebamphwJ2FxbKAS90+IxtqDF1FrsoEICCQi4IowEQLMl/DHHxfg6+uLIKEKcjGDahMLf0XD8deZbbCxwNgYrRt73DKezu3nqxDj1uFhuHV4QxLqU6dOeU3gAW2LsI7ijjtYIBDAx8cHPj4+vPWWS8h8/vx5mM1m3rXbOP1OZwRFeNuSZ7FYYLVae4W7tq6uDn/++ScIIbBYLBAKhU6PnUAg4EuvUbwPFXmULocTXJ62LpSVleHUqVMICwtDYmKiw02ts8qNcWO6KiiLioqQnp6O2NhYxMbGunw8GgdekOCBsF+5FIKsX8CUnwPrGwUScxXY2In/WPbcxWaCti4DsvN5YNVanKoUQyfQYNy4cR1KeOru931tYiCGRfjgZGEtrHaC/iEqRPsrQAiBwWBAVVUVSEUFBsrrcLiOwQWTHVI9gUwiRkqsFhP79YzKAp1haetKS15riMXiZq7dxlG7AoGAT7/jiTq7reHtwAudrmEtaW8QeQAQFBSEkpKSXlPBozdARR7F67R1M+Ge9jz1ZM6yLLKyslBQUICBAwciNDTU6ZidYcnjcmy1JShZlsW5c+dQXFyMYcOG8RUHHCAETNFxCAqPAEIp2LhJIH6xAJrnySMBCbAHJHhmJ0y1EB5ZhZiifZBUSqA3GhEr94fqysUQdDCjPSEEOdVW5J0tg0oqwohIDZTS1i9LASoJrk10zPnHMAyUSiWUSiUiIyMxeLAduw6n4Vy5GRa7Df4iAwarCYoLGQdrUEfwdh64nizyPOnm5Fy7ERERYFkWdXV1vOirrq5GbW2tQ9SuJy1v3rYW6vV6AOgVa/LkcjmGDh2K559/Hs8++yw0Gg0UCgUkEgnEYjGkUqnXRTmlOVTkUboczh1ps9k6fEE1mUxIS0uD1WptdS1bZ6ZtaUvkmUwmpKamgmXZli1jdgtEO/8DQfbOhqoSIBAe/gC25CVgRyz0qmVScH4HmOKT0EsCUcMK4RvoAz/UAmc3wRYyAJC3zwVqsNjx2YkanC4xghGZwTAMQjRSPHxlNAaGdWyNklAoREyAEvHBGsTHx/M53CorKx2SMfv7+8PPz6/bLQLvDBHWE/sXCATw9fWFr68vTCYTpFIp1Go1qqqqkJmZCbPZDF9fX170dVTMe9uSx6VP6ckJgrlztaysDLt370ZBQQGOHz+OhIQEyGQyyGQyWK1WDBkyBMuXL6f1bDsZKvIoXQ63KLejoquyshJpaWkICAjAiBEjWl3L1lnu2rbGqqqqQmpqKgIDA1uNTBWc2gjB+Z9BRDJA8ndaDXMdRAdWwBo+Eoww1Ds1YFkbmIuHUW8VwkIE8PXxga+fFoTVgKnMAlOWDhKV0uxjNjsLG0sgFbV889qcWoyTxSZoxAwCtTLYWYJLtSZ8uC8fK25MatOi5w6Nc7g1TsZ84cIFnD17FhqNhhd9Go2mzZuQt+vtdkb/3dVd6yosy0IsFiMoKAhBQUEghDgkZM7Pz+ddu9wfl3PRnTG8acnT6XRQKBQ9WvRwc/f19cWjjz4KhmF4C6vBYIDZbEZlZSV/HKnI61yoyKN4nbZ+0AzDdMiyRghBbm4ucnNzkZiYiIiICJdcxF1pyWtcGSIhIQGRkZGtzlmYvqXhf8SNrHxSDWCsguD8dggG3OsV0WqzmFFbXgqb1QqJVAWJ9O8kzIwADAFgtzi0rzfZ8P2JIuzNqoDFxiIhWIXrBwaif6ijZc5qZ7E3qwoykQAyccNFXyRkEOYjRXGdGScu1mF8vHeSVDdOxhwXFwez2cxb+QoLCwHAwcrnrjDwBD19TR7LsnyEs7fGaWplYximRdduUVERMjIy+JyLrrp2vW3J603pU0QiEW644QaEh4e32q4nWy17IlTkUboF7S1tZrFYcOrUKRgMBowZMwYajWvJY90SeaZaCP98G8Iz3wI2I9joK2Ef/xRI8ECXPt5U5NlsNpw9exZVVVUYOXIktFoX3J2mWhCmyQ2JYQAQwKzzimVSr9fjxIkTiFXFoI/lPIrtDMAZmAyVIDK1Q0oWq53FW79m4diFaiilIogEDA7nVeNcST2WTo5DUsg/Qs9iY2Gy2tE0o4lQ0FDuq6UKEO7gqriQSqUOyZjr6upQWVnJCwOVSsWLPh8fH/4m5WnxYrWzuFRrhoAB2B5saTtbXI8tJ6uQX2lAn0vZuCLOD+Pj/TweLdzWur/Grt3Y2FhYrVY+N9+5c+dgtVodEjI7c+3a7XavinydTgelUtmjLVtcBPIPP/yAbdu24YcffoDZbObXCUskEvzvf/9DRkYGXn311U5JS0P5ByryKN2C9lS9qKmpQWpqKnx8fDBu3Di31lW5XFPWZoL4/2aBKc8EQxraC7J3QZC3F9Z5O0CCBrg0FifADAYDTpw4AbFYjOTkZJdvICRiFARnv+fTpAAA7FaAYUBCBruVisQVysvLkZaWhoiICIT1vwfMkQ+hvJgOodAfjPnvtDAJMwCfSP4zJy/W4mRhLUI0MsglDepNKxchr9KAbWfKHESeQiJEpFaO1AIjGue91VvskIoEiPbvWEBHe2EYhk/nwQkDzsp39uxZ2O12aLVaiEQij4rqtKI67DxbhtJ6CxgGEJssuFFpQSv5rzuEtyxsp4rq8OmBi6ioNUEuZFBYbcSXRwpRWm/G7SPCPDqWu2KhLdeuUCh0SMgslUq9Lkh6Q7ULzhpaUVHBB5I0va4dP34cFy5cANA5uQcp/0BFHsXruHIzccey1tjVGR8fj+joaLdvWEKh0KWbtCB9CwRl6Q7bGGIHsQPCP9+B7ca1bffxt6DkhFN4eDgSEhLcutDZRywEk/s7GGMliFAKgICxW0ACk8AmTIfAxHpEdBBCkJ+fj+zsbAwYMABhYQ03ZlvK4yjfsx7BqAQJCAcbOQ4kcqxDSpbccj1YlvACD2j47lVSkUPZMW777CEhyCyuQanBBiKxwmJjYbCyuCLOD4nBnnFhdVT4Nk7GTAiBTqdDZWUlSkpKYDAYcPjwYd7K197IztwKA74+XgSDhUWwRgqWJThXYccPZ6sRHxkCi51gX1YlSuvMCNFIcVU/fwSpO2Zd8obIYwnBzvRy6C02RKgbfl9arRxVegsO5FThyng/hPq4Xu6uzfE6IBacuXa5dZpcgm+lUsmvyfNWvjxuTV5P5rvvvsOmTZtQUFAAvV6PFStWQCwWQ61Ww9/fH3V1dTh27BgmT54MwPtR6RRHqMijdAtcFXk2mw1nzpxBdXW1667ODownuPAnCCPkrXgcDLFDkLfPpbEEAgGKi4tRUVHhIJzcgQQkwHbjWggPr4Tg4iEQoQT2frfAPnYxIFGBMdd3WOTZ7Xb+2I4ePRo+Po1KavlEoDx8CkShoZBHOK/9qpSKQNBwsxc0upBb7CyC1ZJm7UdH++LuEf7Yll6BegJoZGJcP8gPs4eGdvqNIK/SgOMXamGw2BGplWFMtG+zwA+GYaBWq6FWqyGTyVBYWIioqChUVlby7j9fX19+LZ+rC+r/KqhBjdGGvoH/uO1CFAzK9DZsPVWKX89VoFJnQYOvnMHWU6V4Zko8BnQgAtkbIq/eZENhjQl+CjFgtfH9axVi5FQYUVBt7DYirylN12lyFtzs7GyUlZWhpKQEPj4+/HfrKRerwWDo8ZY8i8WC2tpanD9/HiaTCevXr0dtbS0sFgtsNhv0ej2mTp2KOXPmAKBr8jobKvIo3QJXql7U19fj5MmTkMvlSElJgUTSXDi4isvuWomywVrlzCD0/+y9d3xcd5n9//7ce6cX9WrZcu+92+kFkkBIISFZWEKHDYFlWXZh4QssAZYFNgsE2KV3WJIAKRAI6b06sS1X2bJsq/eRNH3mts/vj6sZS5Zsy47lOPzmvF6J7dHtM7r3zPM85xz3ib+BG4ZBMpkklUqxcePGVxVfJKuWYV79A8dCRQgQY82dX03VKp1Os337dhRFYdOmTRO2kU/UEl4/s4S7XumgczhDbZEXRUA8Y2BakguPYUK8osbHNJePeYuW4tYUXOqZfwA8vn+A37zcSSxtggBFwONNET5+0SzKg8f+jCmKkjftHW3GHIlEOHjwIG63O1/ly7V4J0JPTMfnUseQBmXkWv9pVy8p3aKmyIMinHnF7miW7z3TynfetgT1FOfcpsLixKUquBSBYUlco8YKDFuiKuA9zZFyU9n2y1VwOzo6qK2tJRwO51u7hw4dQtO0MardU70X/S20a2+44Qbe8Y538IMf/ACPx8N73/tebNsmkUiQTCYpKSkZk0VcqOSdWRRIXgFnBU5UWcu1UGbNmsWcOXNe9Y1CVVUMwzjhctaSt6Ju+/m416VQsJbdeNx1c6RUCMGsWbNOXz6lMnFU0KlW8oaGhti+fTuVlZUsXrz4mA/OE5G8qrCHWy6YxfefbqFjKI0EvJrCxfPLuHxRxYTr5OxzRlfNpJQMDg6SSCTyoodX835LKWkZTHNoIIWmCBZWBakKOyR2IKFzxytdGJbNrHIfQgh006axJ8GfdvXyvk3Tj7nNo89jtBmzZVkMDw/nCV86nZ4wmgugOuxmb098THXNljZpwyaadqqgucqoIgSlARdtI+czr/LEbe2WSIonD0Ro7k9R5NPYNKsE2zr9JM/vVllTX8SDe/oJKzY+l4JpS9qHMkwr9rJgEsd6MjgTsWa2baNp2pj3dnRrt729nb179+Y/p6WlpRQVFU36uHI+ea9n5L683HzzzQAcPHiQjo4OFi9eTE1NDalUinQ6XTBCfo1QIHkFTDlezUyeZVns3buXvr6+YydBnAJUVSWTyZxwOVm3AXPTx9Be+A5ScX5dhG0iq5djbfr4Mdfr6upiz549zJo1i1gsNu4aiK7tKLvuQKSHnW0tvAqKX12uLJx8G66trY39+/dPysZlMkRy85wyFlaH2NY2TNqwmVvhZ3bp8efHcoRpeHiY3/72t/z0hz/kwKgA83mzZvH+f/gH3vGOd1BcXDzpcxNCYNmSu7Z180zzICndBATFPo1rVlRzwbwydnXFGU4b1Jf68ufu1hTCXo0tLcPctH7aKVUXVVWlrKwsH+90PDPmFbVBtrVHaR1M52fyuhKS4pDGUMYY0/oG8hU9wzoxqT/Ql+T7z7QykNAJeTV6ohn29SSY7bZZsfz0V1SuXFpFbyzLy8292Gkbn5GmOuzhpvXTXleVvBwmslA5urWr63petdvY2Jhv2+dI3/Fau7kvMn8LMAyD22+/naeffprHHnuM2267jY985CM89dRTtLa2cv3115+2+3cBk0eB5BVwVmAiC5VkMklDQwOqqnLOOeeMKfmfjv1NVuhhXfg57HmXo+y9F2GksWee5yhL1fEtGtu22b9/P52dnaxYsYLKykp27NgxhhwpT/0n2is/ATPrtLSaH0HZ/XvMN38HWbPilM4n9yCabHXDtm0aGxvp7e1l9erVk8qanKyCtzTg5tJFlYBD4AzDOOZ6uW0++uijvOemm0ilUlwHfAUoAYaAu1ta+NxnPsN/fvnL/OLXv+bSSy894THksKdf57HWAYp8LmrCHtKGRVNfktsePci29ijBkQri0c9gRXFmC+1JdsAPR1I82RQhmjGZU+7novll+W3DxGbMOcKXTCZZGfCzw3DRPWTidruYHlK4Zk0l33vJmcerDLnz12ooZVAVcjOn4vgVICklD+7tYyCpM7fiyHzgYFJndz/0xA1Gj12eDoS9Gh+9YCYPuOPELY3Z02tZVhsi5D39j5ozQfIm8/vkdrvHiHNGZ+2eqLWbSqWonioJ9RlC7n34xS9+wc9//nNuueUWGhsb87/zpaWl/Md//AcrVqygvLy8YIZ8hlEgeQWcFTia5PX09LB7927q6uqYP3/+ab+Zn2x7U05bizVt7XGXyWazNDQ0YBgGmzdvzqvmRs//iUOPo738I7BMcI20L0wdMXQY9dn/xrz+V+MZxyTPByb3UMod54GITqus5o4H2igJdHPRggouXVhxzMrV6bZpyW1zy5YtfObTn+YyKfmJlBz9yHublPQAH0inueFtb+N3v//9pIne7r4sEhclfhdJ3aSxJ0EiY5IxbZ4/NESJ30XWtBlKGZQGnIevLSXDKZML5pYeN7Ej96B6uLGfbz/RQlJ3Pr8Cwb07evjPqxZQHR7/xWR0JQjImzEv6B+guXsIBSgplZSraf5uVSU/eqGTrmgWt6agmzZ+t8pNG+qOe2wAacPm4ECKMr9rzEO1xO/isAltw1kWTKyheVVwqQpzilVCoSD19acmjJoMzlQl72Rawke37Y/V2k2n08RisbxP3snie9/7Hrfddhvd3d0sWbKE22+/nfPOO2/CZe+55x6+//3v09DQQDabZcmSJdx6661cdtllY5a7++67+fznP8/BgweZM2cOX/nKV7j22mtPeCy5e8KPfvQjPvShD/HRj36UX//61/n27KpVq+jv75/UeEwBpx8FmUsBU47JfGvL+eTlKky7d+9m6dKlLFy4cEpu5Kc78WJ4eJjnn38er9fLxo0bx9gijLZrUbf/yvG3c/tB0Zz/XD6QEqVnJ8Q6Tmn/o9u1x0M0GuWFF17gcELhoV4fr7TFyVoWLZEUP3m2hV+92HbcfZxukheLxbj185/nMim5z7bHEbwcqoH7bJvLpOQ9N93E8PDwpLafNiUu1bk2ncMZElmLYr8Lr6ZQFnBTHnDjcylE0yatkTRd0QwtA2lqizxctbzqmNvNXYfBpM73nm4lY1pUhdxUhz2UBVwcHEjxs+fbj7tuDjkz5pXLl/HWN5zLJRtXoCqCSCSCb2Af19WbTA8JpG0xrdjD+zZP5+JjCFlGQ1MEmiIwjypHWhIEEo82dfNsUx1rZtv2GYtOezX7yBH6OXPmsG7dOs4991xmzJhBY2MjH/vYx3jwwQf59a9/ze23387evXsn9ft111138fGPf5zPfvazbN++nfPOO48rrriCtraJf3effvpp3vCGN/DAAw+wdetWLrroIt7ylrewffv2/DIvvPACN954IzfddBM7duzgpptu4oYbbuCll16a9LkODw/n0y4GBwfzbWgpJcPDw4WZvNcIBZJXwBnBZGLGdF1ny5YtDA4OsmnTpiltY5wukielpK2tjZdffplZs2axfPnycSpKIcSRqmG8a3ylLvdv24RTJFGjK3nHQldXF1u2bGH69OnsTgRIZC1mlfuoCHqYXuIj7NV4cv8A7UPpCdd/NSQvljH51UsdvP83O3jnL7bz7ScO0z6U5r777iObzfIT2z5hW0EDfmzbpFIp7rjjjkntt75II6VbGJZTrfNqCpY9Yofi1SgPuin1u7l8cQXr6ouYVernmhVVfPqNc09oyCylZEvLMNG0QemoapmmCgJulRcOD5McSe7QTZv7d/XyL/fs5UN37OJbjx9if29i3DYVRaGoqAhN01iwYAFrNmziYCZAX8LANHQ6B6L84plmfvZkI6lU6rjH59YU1swoZjhtkjGcz7otJZ3DGcJuWFg1df5sU6HePXr7MLV2HFLK0+6P53a7qa6u5uabb+bgwYOsWbOG5cuX89BDD7F27VquuOKKE27jm9/8Ju9///v5wAc+wKJFi7j99tuZPn063//+9ydc/vbbb+dTn/oU69atY968efznf/4n8+bN4/777x+zzBve8AY+85nPsHDhQj7zmc9wySWXcPvtt5/weHLvwfnnn8+9994LONcuN3/3y1/+kurq6vz9vNCqPbMotGsLOCuQTqeJRCJMmzaNRYsWTblqbtIWKsdBThTS39/PmjVrKC2dOGt1tJJXls2H/n1O5qvqcQiebYO0kEXToejU+md5VeYEJE9KSVNTE+3t7axcuRLVX0Tb07soC4xv4x0aSHGoP8n0kvHfuk+V5GUMiy//9QCvtEYxLBsbaO5P8UzzIE13/4XrJmjRHgs1wFuBn/zgB9x8880nfGCsqvbQpSscGkiRMW0sSyKERWXQTWXQjZSgKILl08Ksqy+e1DFE0wa/2zXI0wdTJK1DJHSLIstGHaV6zkWTmbZESskPnm3lqQODuFSBW1V4unmQ3V1xPnnpHBZWH3vw/ulDMXb360wrC+N3O5+jvliaP+8dxJvsZU65L+/dNpEZ85uWVNA5nGZvTwJrpKJXFnCzKGAR8k4+IeZkcSYqeTC1JG+q96EoCqlUire+9a287W1vI5PJ0NnZedx1dF1n69atfPrTnx7z+hvf+Eaef/75Se3Xtm3i8fiY+9ULL7zAP//zP49Z7rLLLpsUycv9Dv7bv/0b733ve/nwhz/MoUOHeOCBB3j88cf58Y9/zOc///lT8gct4NWjQPIKeE0hpaS5uZn29nZ8Ph9Ll04uD/bVYrKJF8dCKpWioaEBIQSbN28+rihk9PyfXHQNsuMlRKIXzJGKmW2C5sM8/zNjvO9OFhN55WV1nbse38r27jRlFTUYfTbr6p0W5tHqTNN2TIy9rtM7k/f8oSFeHiF4qiJwCWffLZEUsVnnc92+hpPa3nVS8rvDhxkcHDyuYEQIQalP5ZbzZ/BQYz/37ehlQNeZV+5nQXUIVRF0RjOUBVzMO4GIIYesafPlvx5gW1sUBYnLJTBMm/ahDPWlPtya8x4kshar6sKEvRr7e5O8eHiYUr8rL0AoC7hoGUxz/67eCUlebjj9+UNDaIqCfyRFxOVyUVuq0TKYRq2eyZx6D5FIhF17GtnZb9Kpe/F6vaybXc5FC6sp8rn4xwtnsasrRtdwFr9bZfm0ELtf7plygvR6r+TlRyym6AunlHKMT57X62XOnDnHXWdgYADLsqiqGjtKUFVVRU9Pz6T2+41vfINkMskNN9yQf62np+dVbRNg/vz53HbbbXz9619n48aN3H333Xg8Hj7/+c/zj//4j5PeTgGnFwWSV8AZwUQEIZvNsnPnTtLpNAsWLKCj49Tm0U4Fk27XShsQY1qsAwMD7Nixg5qamknNDI4mefacSyD5CZRtP0eJdYBtIUPVmBd+Fjn7gldzSuPEJLF4nC/d/TJbegFVg8ggjzYNsrKumBXTi3hsXz9Bj4bXpWLZko7hDLXFXpZNm1hyeTySZ1o229ujHBpIEvK62DirJC9k2NEZI21YeF0qbjXX0lTJmjbe+pUEVc0RokwSuVH+RCIxKVXwUMpgV1ccl+rMqDUPpIhmDCqDHkoCbq5cWkWxf3JVrecPDbGrK06JT0XYEAh4MCyb/oRBx3CGYr8L3bQJezXevdGxpDk4kCJjWpT6NSebVxVoqkKRV6OxN4Fh2ePELjmSlzXtcYbHQggEYElBRUUFRSVl/LnDxYuRQUzLwjITbGmN8vD2w7x/XQW1lWWsrC1h7Yxi4Ah5mWoSdiZI5FSeQ+7+MJXncaoWKkef92QVq3fccQe33norf/zjH6msrDwt28zBsiw2b97MH//4x1Nav4CpQYHkFfCaYGhoiIaGBkpKSli1ahXRaPS0CiFOhBNV8kTXdtRn/gul7TlQPdiLr8U491853Jfg4MGDLFq0iLpjxHsdjTHkSwjsFW/HnvdGxGAzqF5k5WJQX33rbDQJ6+vr495ndvLKgEY46CE80prLmhYN7cMsqQ2xsq6IPV1xLCkBSWXIy4fOnZmvGh1v+6MRz5h85a/7aWiPYtoOKS4LuPnXN8xlbX0xWdPGlpKjxaCq4qR2tAdKINYPwKAvTF+ghKJsgpp4ZMLjGBr5czIPx+GMxa+2t9KX0Kkt8lJb5KVjKE3KsFlcG+K6lTVMK568Nc++3gS2LUEKBlI23akUAonfraAqClUhD4urg1y7onpUhU4SSRj0RLPY0hFEVIfduFWFYr9rnA9eDkIIVtWFubuhB8uWebKX1C00VbBgJN/3xZZhtrRGqSry5d+7tG7SPpRmR69OOn7EjDmXsZvb/lThTLRrz5ToYiqv08nGmpWXl6Oq6rgKW19f37hK3NG46667eP/738/vJ1CnV1dXn9I2R0NVVfbv309ra2veQNrtdhMMBgkEAoV27WuEAskr4IxCSklLSwvNzc3Mnz+fGTNmIISYVKzZ6cTxZvJE7y5cd14PxohZsp1C2flb7ANP0rn4S6xfv2lsris4UWPJPnAHwTM22WJCuxZ/GdJ/4irUySB3TgcPHuTQoUPEvFVIEc0TPACPpqIqgpdbhvifv1vBjo4o7UNpwl6NNfXFlPiPHc90LJL3fy+1s6VliIqgB5/bqQp2RzN867FmfvCOlaydUcy9O3rIGE4KghBHWsUuPcaDps67VY3fLXsDT81eQ9wTwGtmWdvRyLu2/ZmibHLM/u4WgnkzZx5zBnI09vTr9MZNZpT48iRpTkWA1sE08Yx5UgQPnFQHS0JnTMewJJpmIyUYlqQqpPKzdy4fV5V7pTVKQjcRCDyakwLROpgh6FF5y/KqCaPJctf5ssUVbGuPcjiSzl9by5ZsmlXCimlhAHZ1xrClHEPOfW4Nl6bSZwd418bl+ZnXwcFBDo8YTTc1NVFeXk5paSku1+mdzzsT7drXwgj5dOLodu1k4Ha7WbNmDY888sgYe5NHHnmEq6+++pjr3XHHHbzvfe/jjjvu4M1vfvO4n2/atIlHHnlkzFzeww8/zObNmyd9Ln/4wx/45je/iWmapFKp/P3VsixCoRDbtm2b7GkWcBpRIHkFnDEYhsGuXbuIxWKsW7duTHrB6bY0ORFylbyJWgrq899xjIoVLd+mtUwTb7Kdc4t7EUcRPKXxj6gv/xAR60KqLuy5l2Gd888wQuJetchDT4DiAu34yREABw4cIJVKsWHDBvZvGwCi45YRwrHVcGsK62aWsG7m5LzMRquEe2NZHtvXT/tQigf39uFWBb4RkqEqguoiLz3RDFtahrhwXikrpoVp6IiR0G0EzmUNeTXmV6jcn47xy6WX8OCSiyjKJKiN9ZF0+3hs7jqyqot/efY35N6hbuAe4CuTEF0AxLN2/phGw+dS6Ivrkzrv0Thndgk/fb6djCnxqI4nnGlLFNsRWTR0xMYIOFoiKRo6Y1SHPAynzTy5tUdI3CULJk4AyH0uK0MePnPZXB5p7Gd7RwyfS2XT7BIunl+WJ5OKMnG2soR8ldDn81FXV0ddXR3ZbJbnnnsOt9tNa2sre/fuJRQK5RM6QqHQqyZoZ2slzxp5n9zqiVu9Ux2blslksCzrpNu1n/jEJ7jppptYu3YtmzZt4kc/+hFtbW35WLHPfOYzdHZ28qtf/QpwCN673vUuvv3tb7Nx48Z8xc7n8+W/rP7TP/0T559/Pl//+te5+uqr+eMf/8ijjz7Ks88+O6ljGhwc5BOf+AQXXXQR11xzDV6vl2w2SzabJZ1OHzO3uYCpR+HKF3BGEIvF2Lp1K8FgkM2bN48L9M6RvDM1x5G7eVuWNe4GpLS/4FiZKE7lyrZthKIiAFfPNkzefWTZ/X9Be+zfwdKR7iBYBuqePyCGWzCv+yUo6imLPET7i2hPfBnRtQ0UBXvu5ZiXfHFCBW4qlULXddxud/76rqwzuHd7Fyndyld5TNvGsGw2zT5xFexoKIqCYRjs6YrxyXt20xPNYlo2hi3RFCd/Nlc1VAVIJCndQlMVPn/5XP736VYae5PYtk3Y62LNjDAX1ZTx6P8W8d2561mVTVGZdJqx7nQcxbbZUTuf1uIaZg53YwIfVBT8Ph9vf/vbxxzbnu44j+4boCWSpjLk5sL5ZVQA5X4VgT1m7k1KSVK3WFEXPulrMLciQEXQTTJrYNhgGTaKgIqgG7cqONCXHEPyuqIZMoZNTZGH8qCbWMbEtmW+KprSj03+c78HlSEPf7++jr9fP/FyK6aFeLIpQjJr5jOAU7qFELBq+rEjLebMmYOiKGSz2XyVr7293RGsjEpo8HhO/OXiaJyJSt7JELCsafNwYz9PNw+SzJrMLPNz2eKKfDV0Ipxu+5SjkbPAOVmSd+ONNxKJRPjSl75Ed3c3S5cu5YEHHqC+vh6A7u7uMZ55P/zhDzFNk4985CN85CMfyb/+7ne/m1/84hcAbN68mTvvvJPPfe5zfP7zn2fOnDncddddbNiwYVLHFIlESKfTeWJZwNmDAskr4Iygq6uLuro6Zs+ePeHN/3ikaypwPF856Qkj0oPYtkTKkbkcAOn87MiCEmXrTx2CFxgZYnaBND0o3Q2ItueQM88/6XQNANHdgOvOtx0RJNgWyoG/4u7ehv7+J8F75OEdiURoaGhA0zTmzZuXJ9AbZpVwzpwynmmOEE0bKMJR0M4uD3DNipqTOh7IZcHafPnP+2iLpFGEUyHTLYluSQ71J1leV4QiBEMpg6xh8+T+Phr2H2JjnZ+PbaqkK1NNUrcpC7hZUBUgNjzEx/7ts/xsV5aGdIwiIOfeFsqm6A+WMhAoxjPczQcVhYeE4Pe/+c2YKvDLrcN8/5lW4hkTv0elK5phd3eci+pU1ta42Dns4kB/irKAC00RRJIGQY/GGxZWnPQ1AJhd7iOd0RHSwuP1EvJqhDwqbUPZccrksoAbt6aQMZykirIRMcpQykBTFEqOIfg4GRXzuvpizpldwnOHhpzqpHAqeOvrS9g8e3yVNrft3O+hx+OhtraW2travL1GJBKho6ODxsZGgsFg3qalqKhoUhW0MyG8mOz2pZT84sUOnjwwgNel4tUUGjqiNPcnueX8maw8Btmf6nZtIpFACDHGOH2yuOWWW7jlllsm/FmOuOXw5JNPTmqb119/Pddff/1JHwtAOBzmiiuu4L777uOaa645pW0UMDUokLwCzggWLVp03JZljtidaZI30TEZi6/H9dx/gzRR1ZFjsU1HNLH4rUcW1JMow61I7aibtOaFbBwxcOCUSZ76wredOb/Ryl4pId6DuvNOrPX/kDdibmpqYuHCheMc712qwmevmM+De/t4+kCEjGGxbmYJb1lWTVnw2LN3x4IQgpYhg+a+BIoCXpdT3RSKIJm1SBs2XcMZpJT0xbOoiuDZA/0oiuDpdp1ruoaYHzYpLS2lxF/GcBz2dKeYNm8p61SdrQ27uNPIMBOYKSWWx0/cyPDlVJQHhMDv8/H73/yGSy65BICO4TQH+lLc+UoniazJzDJfnrj0xrM81ZpmRaWLj188i9++3MXurjgZw2ZWuY+3rqhhaW3omOd6PJw7p5S9nVFCLkFlic8534RO2KuyZkTBmsP8ygCLqgJs74gBbrwuhWTWIpk1ecvyKop8xyZ5k62EuVSFD59fz9r6InZ0xpFSsnxamPX1xbgniD7LbXui7efMmIuKipg9eza6rudzWHfv3o1t2/kKX1lZ2TGtg86mdu3hSJqXWoYoC7jz17vE76IlkuaB3X2smDZxe3qq27W5eby/BQVqdXU1H/zgB/nUpz5FR0cHtbW1hMNhwuEwfr+f8vLy131G7+sVBZJXwBnBiW5kORXbmZrLE0JMOAcYjUbZoS9lbdkqigcbRixUJAiBdd6nkLWrjizs8jkt2vTg2I3bprPOqJm8kyV5SscWZ99i1ENGCJAS0bUN27bZs2cP/f39rF27lpKSEjo6OsbsRxx+isC2n3P9QBPXlczEXvsu7HkrHLKYGnC276+YdFauEIKepIlpSzyqkp+TcykCn8upVpmWRcaUuBRBmcci4PPicrnoi+s8EfFw7XmzSUaHuGdbB48ezpCyHDuQgM/PwtUbMOMDtB9opEW30AIlpFu2UVHs4Suf/hrveMc7KCoqwrBsfvxcO4/vHyCaMRlKGfjdTkxZzoeuPODmYDxNR8xgXdjLJy6ZzUBCR7dsKkMetAnEDpPFZYsq2Nrcw9bOBOnBFEhnvvAd66ZRXzrWRFoIwT9fPJtvPX6Ixt4kQykDn0vhovllvGfD8dXZJ/Pwd6kKm2eXsnkSbfiTIZC5hIbq6mrH/y+RIBKJ0NPTQ1NTEz7fxGbMU92uPZkqW9tgmoxhUR0+0nYWQlDid9E2lCapWwQ94x+FZ6KS5/f7/yZI3uDgIA8//DAtLS188YtfxOPxYJomUkr6+/t585vfzP333z/lLfACxqNA8go4a3CmxRdHCyJy7am5c+fhu+hPGC1Po7Q+Cy4/9sIrkeULjtqAir3kOtQt30fqSXD5wTYR6SFksBJ79sX5/ZwsyZO+MkTqKAsRKUEomO4wW7ZswbbtMUbMo/ej7Lkb7aF/G6lAKoh4F0r7S1hr3w9GGtG7G5DIikXYq96FrFg07hhMy+ax/f08vm+AoZROjdeixucQCt2SqMqopA0JHpfCp94wl9sebsKLRSgQwOVyIaWkNOBiIKFzcNjGlkU80T2A4glQqVqk0hmiySwgqS4qoWjD+XhdCgvLXNyw+hrqayry+zFtyZ2vdPHnXT0EvRrTijwksiYp3aKxJ8HqGUX5vFZFOAQ0h/JTqF5OBK9L5X1rSllWYmOFqvG4FNbOKJowJQSgKuzhq1cvpKkvSSSpM63YN44MHo3TnRF89LZPhVgIIQiFQoRCIWbOnIlpmvkq3759+zAMg5KSEkpLS88qda3frebFRrkcY3Dm9AJuFc8E1c7cPqZ6Ji8QmJwJ99mK3Pvw1FNP8f3vf58vfvGLXHTRRViWhWEYGIZBIpHIR5wVCN6ZR4HkFXDW4EzbqOQEEbZt09jYSE9PD6tXr84b7MrZF2HNvui427DWfhAx3Ipy8FHHQkUoyFAN5mVfB68z63MqJM9e8Q7Ux794xIwZ8n/fZs3H7/ezZMmSMTfNvMWJmUV9+usOwXMHj1TqsnHUl76HLJmNDNUAAqX9JcRwG+ZlX4Oi6fltSSn57VM7ie78CxdYhzBUP8+ZC3nItYhZ5QGaehNkTFCExJaOWnRxVQii3RimSVHAj9vttMZyKk8pHfuPR/cPoJs2dSU+TNPAMnTmlhbRPpRi00w/090Z0OPUlgSw0nFiMQ9ef5B7dvTy4N4+9vU4ma8+t4pLFYS9GkNJnZRuMZjUKQu4aY2kyZo2f2hMsm24iYvml3PunJIjxMPMIOJdzvGFpk1KuTwaqiJYUKaxfPnkvL+EEMwq8xPyahNWjY7GVAqQTte2NU2jsrKSyspKR0SSShGJRBgYGEBKSUNDA+Xl5XlvvtM5hnEyJG9pbYiasIfOoQx1pT40RZDImiSyJm9YWD7O8iaHM1HJCwQCr+tKXu7LSEdHB8uWLeOjH/3oa3xEBRyNAskr4IxgMjey18JGJZ1Os2/fPqSUbN68GZ/v+BWWcXD5MC//b0R/I6JvD3iKsGee61T1RnAqFirWmvcjOl9B2f/nkagzCQgap91I6bI3UF9fP+6a5sik6G9EpAac2cDRywgFLAPpLQafM5AvvWFEpBnl4GPYq9+TX7Sjo5XF27/EDKsNFBXFtFknX+b+zLk0Vt+ESxEcHkihWzYeTWF6iZdrZ+gUayrzako4OJAi6HWOGSmJJHVURdA2mGJvdwJXvnoiRo5doCgK/lAJ12yejq7rRCIR9rb181JTJ1t6YNewgltTsaRDLNsGM9gSqsMedNMmmjHpGs4wkNAZTBq4FUl/ymKgNcq29hgdQzW8fd00lL69qIceQ0n2AWAHq7DmXIpdvvCk3qPJPpyllDyyb4C/7ulnKKXj0RQ2zCzmhjW1ExK+o4URpxtTUWUTQhAIBAgEAtTV1fHkk08ye/Zs4vE4Bw4cIJPJUFxcnJ/le7Xk5mQree/bNJ2fPN9O+2AaicStKmycWcyVSyuPud5UtxZP1iPvbETu+lxyySW0t7fz+OOPc/HFF7/GR1XAaBRIXgFnDc40yZNSsnfvXqqrq1m0aNGp39CFQFYudpIrJkDeQmW41Wn/al7sOZeOUciOX8mFec2PES1PI/b9iaF4lj3+TczfeFm+9TH+MEZ87FQ3Dnk6quVnWw7pU0f92gsFVDci0jxm0ey2O6kzW4h4pnHIqmKXWYdqprFsm52HOqkoL2d5XREzy/zMLXXhi7Yyq6aMJUuWIKqifPmB/XRFs7hVQVq3SBsWFUE3DzX205/IktJtwh4VR4zqVPhA5OemBjOSn+1I0Nhjkdb9dAxnCLggqJoMY6NLgY2kN5alLOCitsiDogguXVjOnu4EpiWp9EmklAQCXiJJnft29XLxNIvpB/8EZgZ7pHIpYp1o+/6EsbIYGTz9w+GP74/wyxc7UBQo8rrImBZ/3dvPcNrkny+edUyyc7ZX8o63fXDSGWpqHBV3KpXKt3YPHz6Mpml5X76SkpKTNmM+WfXu4poQX7pyPjs7YyR1i2lFXhZUBSc0oh69j6kkebmZvNczcu9DR0cHd9xxB/fccw/vec97qKqqIhwOU1xcjNvtZuHChfnPQgFnFgWSV8BZA1VVz0i7Npe6kUqlqKurY+nSpae2oUwUZecdqLt+h0gNYNeswtrwYeT0jWMWUwQsbv8N7obHjhAtzYf5pm9iL7524m1LibL3XkTDb8gMduFBsHmajmAtkolJnqIoSCmRFQuRpbMRkaYRQ2fFmeezTeff3qOG820dAqMqGlJSFXmJPunnd+n1PKIvQZcaWalhoKKZNv6sxWDSoDeapDSV5vLVc5g1yyEsm2aXcttbl/DHHV0c6E3QG9cpU9wsrw2hKhD0qGxpjXFwIEV9sZuUAbHhDHUlXs6dU0JKt/i3exvZ15dAEQLblmRMG4FCSdBPTYlN+1AG05ZkDJO2vigmCstrgty0toaP37Of0oAbIfU84Sjxu+gcztB44AAz9OExVTtZMgulvxGlfx/WJEneZGfmDMvmwcZ+hIDaImd2MuBx5sAaOmI096eYVzl2Lmsq5/Fy25/qeTkYS1L9fj9+v5+6ujps22Z4eDhP+Pbs2UM4HKa0tJRAuISGPoOGDifFY2VdmHPnlI6reJ6KRUvQo01KmPJq9nEyONlIs7MZbW1teUXtb37zG1KpFJlMBtu2GRwc5Ktf/Sr/9m//VhBevAYokLwCzggm81DRNG3KK3mmabJ7926Ghoby3zRPFqJ3N8rOO1Eb74VUZKQa5kI5/ARK23MY1/4EOevC/PKePXcxp/9hh9zl1LJmGu3+j2JULkGWzx+/j8NPwgv/QzKVxvKVEQ74UAYakU98GfMt/zthFTBfyRMK5hu/huve90EmOiLYEOAOYodqEPEuZNiZJRPxHnCHsGc7x2taNmndwu9xs4dZPJhdiookRJoUYRRsLOFEo5V7pZOPGi7i5plHKlJSShZU+vnXS2bTMpjmvx456PjFuZxzry32s0SXHOxP0h/P4FIEy2qDvG/jNPwafP/ZVvb2JHBrCh5NIWtaSAMyps1QymBGiZeaIid1w7Qlfq+b5ZUa51dm2PbKFtJpF5qmompHPnPOJRC4reRIpfMoqC5EZnw6yKtFPGMSSep51W8OAbdKf9ygJ5Y9Jsl7vVby8uKfYxAkRVHyNixz584lk8kwODhId98A33mqnYMx8Lg0XC6NHR1Oq/1jF84cQ/TOVKzZ6Y57G42/hXZt7j14z3vew/XXXz/GtSAnvEilUgXhxWuIAskr4KzBVLdrk8kk27dvz6dC7Nmz56T3JwaaUB/7AmK41SF4MFIls505PCOF9vTXMGZekJ+HczX8ColAjLZDkSORVDvvwLr4C+P2k93+e2RiGEpmUzTyIJAuL2K4DaX1GewFV45bJ1fJA5DT1qC/+0HU3b9HDB5CFtVhLbkeJdKMsu1niKEWQCIDFdgrb8KsXMa92zr5084ehpI65dY7EGYnJgohkSIl3UgELkwM4aJnOEltAKpKgvQmbfoTOpUhtyOuGLmmiqJg2k6U1GjLEiEE1UGNdMLkynkBzlu1kOkjfnO6afF08yAgnZxbwOdSSRs2hiUZTulkTXukvQubZ5fw5SsXUDxiKpzJZHgxvp/nW+MIzUJVQMoEQ1koDnhYUlsMbdkRe5oRkiBtsA1k8OTMkSdDlAIeDa+m0B3NEk0beDWV0oBrJIFDUOw79i14KkneVGeywuSP3+v1Ultby+G0lwEsZlcpCNsgk82SzqR46UCKez0Z3rKyjnA4nJ89nWrCcKaEF38L0DQt/4U5l1yUs8V6PQtL/hZQIHkFnDWYSpLX19fHzp07qaurY/78+SiKcmr+dY1/RCR6HdUqHKnM2SZI05lvG2hyvPNyPnmJHuTR83FCgLQR8e4xL0spaW5uprJnP+FgGa7R3/SVkV/XRN/Ex3b0+YRqsDZ9bMwydslM7Lr1iL7dIKUzR+gr4ZfPtfJ/W9pRFSeDtkMvIWI59idexcRCQUiQQgPpWJkUF5cQy1iowskCzSmVndNzbu51JV5K/S76Elnqih1RSyaT4WB3hLoSP393yRo82pGHddLIYlgSVVGwpcxnr4Y9GpGUgWlD1rRQhMCtKsQzJp3DmTzJ83q9fPiSBQw+2MyBniiWYZFNm2RNSSyt895H4ZrwPN5p7sNdUosAlEQvdqgOq3y8jcyrRX8iS3csS+tg2hmHVAQ+l0qxX2N5bZiF1eMrOX8L7dpTebjv701gSwgHvICXUCiEbdtk++Ls70sxc9euvBmzruuEQqdmZj1ZnAkLlaKi48zlvo5gGAb33XcfTz31FMPDw7jdbkKhEOFwGNM0+eAHP8js2bNf68P8/yUKJK+AswZTMZOXI00tLS0sXbp0zPDvqZBK0bsL6QkiLGPUiyMB8bmECkUF9Yglh121FNHyzJG2qXNgzh+jxBqmabJz507i8ThzZizH3bttLDW0DEdPEZp4bmzSpNUbRs7YnP/nYFLnjzu6cGuC8qBz3GGvRkq3GUobmJ4wAUWgpVX0kVMsC/mwJETTOhcvqCDkcRTEQogx1Y+ATPG+0l00NLXQnqihSZtPXzRNWVGAvz93PgLB7q4YAsG8qgAhn4uaIi+DKYOsKXGrDmFMm877VB12Uxl043erFPs02oayPLJvgCWj0itqi7z851ULuPfF/Tx9OEHTkE3QKwh6VGJZk5/2zaMlqfHh6Mv4/D5clQtxLbwMxTc+AuxYmAwRk1LynSdaiGdMygIukrqFYdnEsyZ+t8rN582Y0L7j9aiuHY1TrRRqE1wLRVHQNDc1VcWce2498Xg8n7EbjUYZGhrKK3aLiopOKymb6kpeKpVi2rRpU7b9M4Fc2/znP/85X/va1ygvL6e8vJxEIkE8HiebzdLU1MQVV1zB7Nmzz0ibvYCxKJC8As4IJjuTZxjGCZebLHRdZ+fOnaRSKTZu3Djum/8pVQ5dAWeOLVdVsy2H1AFOuK2NPeeN4DlSobE2fhSt5ZmxnndCgLcYa/nbgSOtZI/Hw6ZNm1C7FIjsQUTbkf5yx2Q52YssmY1df96Eh5b3yTsJDKcMvv5QE839KRQBwymT6iIPQY9GdbGPuG7RbxfhVUBVDKQl0BSBYUt6o1nmVQZ514Zp+Zv36PdZ6W7A9cQXWRnvYpFpk9BtmmQ9Ly34JOevXkwkqfOh3+6gN5ZFANVFXj50bj1XLqumYzhDUrcwLRvTtjEtp327anoRjqGMBAlBt0JTXxzDMPL7VxSFIp+LjXU+/tgYI+BRKQ+6sWyJaUPSkDyYnMesBatYV5ZlMGGgNxykpGQwr/g8kZWOlPKE17plME1jb4KSgJuAW0U3bbKmjW7ZICFrHn/91/NM3qk8yJfWhnh8v5OznIsfS2RNhICVdWGEEPmorHg8TigUwu/3E4lEaGxsHGPGXFZW9qqVq2dCXft6b9fmfge+853vcMMNN/C1r33tuMsXCN6ZR4HkFXDGcCISoqoqmUzmtOwrFouxfft2QqEQmzZtmnCA+mT960TkIKLjRUSihzxZw3biHoQA20aWzMS88PNj1pOzLqBh7sdY0fs7lESv81r1Sswr/hsCFQwMDLBjxw5qa2tZsGCBM1tXfy7Wpn9C2fF/iEQfKBpy2jqsjf8InonbVCd7Prpp88m7d9PQEcWWjoVJNGOS1C3mVviREqrDXpaUq2zviFPsc7GqUrJh8SzUkVbshplF+DRlHMHDSON66iuIeCd2qJZsKoMmUmwUbawPPsEusYxvPnaQVNaiLOjM8rUPpbntkWa+du0i3rm+jgf29DKUNByRR9DNcMoYIXE5gQdkLElNsSOkyJ17juj1JU1iWZviEYLXPpQhbTjzQraEn+5M0bu0ko9fNItsJk0kEqGvr48DBw7k47pyRr65h1NPLMMftvfw5L4epGVz6XAr16+spiI03kw5kTExLYnb6xyvW1NwawqGZTOYNEhkJ65a/y0IL05l+yumhbl4QRlPNEXoT+iAwKUKzplTyvqZxeP24XK5xpgxJ5NJBgcHGRgYoLm5Ga/Xmyd8p2LGPNWVvGQy+bonebn3uaysjGXLlr3GR1PARCiQvALOGpyumbyuri727NnD7NmzmT179jEfOCfbHtbuv8WZoZOjW6IChII96wLsBVdiL7p6QhLWV76JgUv+gZLobkS0DVk0HbtoBi2HD9Pc3MzixYvHtm6EwF7wZuzZFyGGW5GaF4pnHjdnNq+unSSePjDA7u4YJX4XtpRkDBtNgGnbdEezuDWFBSVwVa3OrVeuz7dezjmn3iFKIzN44wgeoHS9goh1YPmriCdSCCEIllRAZhil5UkeNq4lnrGoK/bk151WpNAxnOHJ/RE+eG49b15Wxb6eOM39SaIpg8ebIjT3JZld4UdTBIMpAwlcvLASt/uI6MO2bSzLQrMNVOGQ2UTW8epzKQKJwLIlQbfKE00RLphXxrr6YgKBADNmzMjHdUUiEfbu3YtlWVjeIhpjLh5sThLPWvhVGykl9zb0sKszxn9etTA/F5jDjFIfYa9GLGNSFjii6I1lTEJe7ZjRZq/3mbxTbdeqiuCd66exsi5MY48zn7ewKsCyaeFxWcNHEzAhBMFgkGAwyIwZM7Asi6GhIQYHB8eYMedydidjxnwmZvL+VtS1t912G/fccw9PPvkk8+fPx+Vy4XK50DTNMTl/nfsBvp5RIHkFnDV4tbFmtm2zb98+uru7WblyJRUVx1dLngypFPv+hOjeAUinVSvlEYWmy4e9+n3Y897oLJyNO21cX/GRfQmJb9sP0FofBT0BKCSUMMPVb2XdBW8/tpWLyz9hruwYRNtRurZT1DdAJDR58cDe7jhI8GgK5UEP/fEsWdNGSoeILCtXuGqmm02bNuH1evNxVaMFFhMRPAChJ7Atg1gijcvtxh/wIxCOMMXM0DWYQlPGVquEEChC0BV1qrmJjMnvt3bTMphCSkgbFomsiWE7rduw18WVy6q5cH5Z/mGjqmp+DtNMDLJmRgkvtiVIG1a+9mpaEq9LoTzopiuaZVt7lHX1R67/0XFd92xt42cvdjKQNEmbjlLYdkFVQMHv93BoIMUTTRGuXTl2VrLI5+Lq5VX8eksnvbEsPrdKWnc+b1evrsy3JI/GmajkTWWF6mTatRnDYkdnjM7hDD6XyvJp4fx/r2Yfqqrm58PgiBlzJBLh0KFDuFyufJXvWGbMhcSLyWP+/Pncf//9/PjHP2bt2rUUFRXh9XoJBAJIKfnmN79ZIHqvEQokr4Azhsm0a0+1kpfJZNixYwemabJp06ZJ3VBORl2r7rwTkCO2G2LE8044ZM42wczA0GG0p7+G0vIsILGrl2Od8y/IunVUR17E13Mf+MJYoekkYkN40n2sHfoTluu6UzpnpI36wndQd/wf6ClqbItyLYwS+jL2vMtOuHrQoyFxHvpuVVBT5CVtWAyndMKazSc3l7By+bL8g04IQVo3+c1LbTy+P0JCt1g9vYjrV9cyt2Js26mfMsKGwO81cAeOCBpEZhi7dC51ZcW80t07pqqUa6PWFTumwXdu7eRQJMnMUh+a6tjDtA6m8WgK7900g0U1obzBcA6WZbFnzx6i0Sjr1q1jKS6+cP9+Xjg8iGk7Gmcnhs2DM9knxwWDjEbrYJpfb+1HKhoeFxi2iSoEcUPiTlvYVgzdUHj5UC9vXlyK2z3Wg+/v1tYS8mr8aVcvkYROXYmXq5ZV8ebjxGnlr9XfeLs2mjb48XNt7O1JYNvOu/Hg3n5uXFPL5tnHF8Gc7NzfaDNmy7KIRqNEIpFxZsxlZWWEQiGEEFPars21l6daIXym8OEPfxghBNde65i7p1IpotEoPT09DA4OFmxUXkMUSF4BZw1OleQNDQ3R0NBAWZkTqzXZb98nVckbbncEFraNQ/YER0QUCnbpbFx/eDci1uEoa4VA6diCct8HMG64g+rI84DAcIWJR6O43V48RXMQsQ7k4aexl15/0uet7P8L6rafIxUXhKqwMhnUzCDqY1/ALpsHpce3LLhoQTm/fqmdoZRBsd+FZUviaQPdtJhR6ae4bm7+WkopUVSNO5os9g4exKU5ObJ/3ZPl5dZh/v1N86kv8xP2qLS2tnK4PcG58y/H0/owxLsxVQ+KnkC4vFgrb+KycBWPNw3SFXViySQQSRoU+zUuWVjBUEpnT1ecsoA7r7oUQjCt2EvncIYin2scwdN1nR07dmDbNuvXr8fj8RAEvn3DUr720AHu39VL0K1SEXTjcSkkMqZjxFzjR9f1/CzfaIXwU82DDKUcD8C0LkbMXhUMw2IwK3C53djSxEonePbZZwmHw/lZvlAohCIEbxkhdRnDxutS8rYwx8LZQsJOFZOtFD7c2M/Ozjj1pT48mkPiO6NZ7t7ezcKqAKWBCUyrR/BqVJqqqubNmIG8GXMkEqGtrS1v1pxr/U8V/hZm8nK46667eOSRR7jkkkte60Mp4CgUSF4BZw1OdkZOSklbWxtNTU3Mnz+fGTNmnNTD62RIniyqcwiczACOOjJXAbLr1qO2vYCId4Kn6IjaVvNBZhh1+y9xG1EMVJKxKH5/AK/X61BEIRDpoUkf82goe+91KomBkba0omG4S3BnY6gH/oq14SPHXX9WeYB/umQO33n8IH1xnUTWREqJpgoODJrccsdOPn3ZPC6sA7H7buTBV7g6blEd2EijshDDshCmxaE+nQ/9ZjsVIQ81Psm5lQbXnr+WfmMtX+1ezYtdJprUWe7qZM6MOi4sPod55QH+9Q1z+OlzbXTHMggEs8r8vH/zDCpCbhJZE1uC+6i3UxECe8SnbzRSqRTbtm0jGAyybNmyMUS/J5YlktSRQH/SIJIy8LpUirwaly6sYP2sMgQyP8uXw+MHhvj5C+0MpU1iGctp00pJ2rCwpaO36YkbKALmzZzBueuqiUQiRCIR2tvbEULkCV9paSl+9+TSE17vM3mTIZGmLXm5NUqRV8OjHSHxtUUeDkVSNPYkOGfOsSPITqcVR86Muba2Ftu2icViRCIRpJRs3bqVUCiUr/LlzJhPB/5W2rWmaXLhhReeUnpQAVOPAskr4IzhRDf+k4k1y7XlIpEIa9eupaRk8h5nOZwMybOX3YDS04BUXY5HnpUFQHqLMC//b7TnvuHM6CmjqojCEWWIrm1EvXWURXcRKqs80tIzs4BAlsw66WMHJ5JMqqOIg8j9Tx5J4zgBrllRw+q6MB/61ctkdagIewj7nOPrT+j89pHnucT/v6ixdopMizdaNpdkX+R+79XcG3grvekkhrSwTEk6lWZvHDrjGuU1A3zvxT7ahkpGSAW06LVohxWeeaCJr12zmM2zS1lbX8zB/iRSQnN/kt9s6WAoZVAedONSnWMIebX8Z2cgoVPidzF/VBTYjkPdfPWv+2hJCDQ1wZqmvXzi0jnUl/rRLZv/fuQg+/uSzK8IkMiaDCR0TFty/rwyPnHpHLSRh7Zt23nxxrb2KF9/5BBpPTfLJ9Et6YxijrrcblXgdSk8c3CQG9bUUlNTQ01NzRiy0NLSwt69e/NVvvLy8hMO/k91pe21tlCRUmLaEvUoQYWAvNn2q93HqUBRFIqLiwmFQrS2trJhwwbi8TiRSIRdu3YhpaSkpCRP3L1e74k3OgFy7dq/BZInpWTdunV87nOf41Of+hSVlZX4fD7cbjdutxuPx/M3Y/r8ekSB5BVw1mCypCuVSrF9+3ZUVc2LAk4FJzOTZy+6Gmu4FXX7L0FPguZBBiowL/kSFM9A+ssAMdbwGEBaDBku2svPoUJvw53qBlnizPFlosjq5dj155zS8cuqpSjDrU7lR4iRB6QJQiDL5k28UrwbMXgQfCXIisVkdZ3dO3eQyFpUFXkJeR3SKIGSgIs3R/+AzLYgQ1VksjYRQ6dYJnlz5n4ek6vJmGWoQqAKSdin4ZUqA0mD259spS8tkbbArTltTltKLFvS3J/k8f0DvH3dNNyqwqLqEHe+0sGdr3ShCoHfo9I6mMqrfXd3JTBtJ8qsyOfibatreKJpgN1dcZLJJI83D5OxBAIJGDy2f4CGjhh3vn817UMZDg0kqQl78GgKIa9GTZGX3liWlkiK0UWz0eKNP+7qR7ckZQEX/UkD3XSqt47RDGgKlHkFtWVB3KpCTyzL7q4Ym2eX5rdVXFxMcXExc+bMIZPJ5Kt8ra2taJqWr/KVlJSMsfc4E+rX13r7LlVhUXWQZw4OUhpw5VvYQ2mTgEdjdvnxZ2qn2lQ3dx/KiQeqq6uRUuYJX3d3N/v378fv9+cJ32irnRMhlUohpfybIHnJZJKHHnqI/fv309jYyOzZs/METwhBdXU1P/zhD1/rw/z/LQokr4CzBjmSd7yHRH9/Pzt37qSmpoaFCxee3I0+1om68w5HJRsox1d3KZY5yZkYoWBt/jjWsr9D6dqK1HzIGRudvFrAXng16s47IBsbsVARSD2BZdkM1r0BUbWJgWlV1Hb+FTF0GBQNe+FbsNbfDK5RVhpGCtLDECh3lKjdO1D2/AERaYaiOqxFVyPrzwXAWvH3iJannYqeJ4ySiePV48iS6dizLx57/JaO+uw3UPbdjzBSSNWFUbqQ7cVXoQZn43bbqCPXUgJIics22cQOTNWLpqj43YIhRRC1/ZQTZZm+kxftC5FA2KPQnRLopolpQ8IAgUBRyCtyEQIpIWtYHOhL5A9tOGXwwO4+vC6FipHEjWKfi+5ohv5EFt2S6Kadr/rc09CNKgSKNDkcSZMyBS4FPC6nimrZksGkzv8+1cI5c0qxpMy3BHPwuVViI56Axb6xP7OlpLEnAUhiGQvLkqO782iqYGZYEHRr+FxK3hhZN4/9hcHr9TJt2jSmTXOMo4eHh4lEIhw8eJB0Op239ygrK5vSOTA4e9S1ly2q4GB/kub+FEGPSta0EcAbFlXkxTevdh+nitH5yzmMNmOeNWsWhmEwNDQ0zow5354/jvgrlUoB/E2QPLfbzUc/+lEAhoeHicfjpNNp0uk00Wg0byw+1V8uCpgYBZJXwFmDXDXDsqxxxqVSSg4dOsShQ4dYsmQJtbW1J7Vt0b8P7e53I5ID5B7XJfv+zIyqK4ELJ7+hUDX2gjePe1nWrMC84P+hPf11p0InbQypEJ97LfWL1uDdeidet4a99G3YlYvBWwzeUS0MI4X63LdQ9t6DMDJIfyn2jHNQWp4BIwGqB9HfiGh5BuucT2Avu8HZ5xXfQH3umyhd29DMLJZwgZ5Ge+CfsS75MrJsDgDq1p8idtyBqfnRAhWYmRSy7SVWp6KoN/2BO5p30dSbxOtS8ilt8YwxkkvrvBduVaE04GIwoWNLiWEYWFIS8qjotsCwbIdMmTbYR1puueguKSUWEtuyifZ10bAjQ1VlJS0pjc7hDGGvRlo38blHPge2ZDhtMr3ER3nAjWnZHBxIsb83SYlX4FckhnTyL2zpLK8oAlVxanpb26Jcv6oWl6KQNix8riOt9ETWpK7ER9AzVqTT2BPnZ8+30RPLEM84D3pVEXhUBVva6JazH4/iKDYFjmAk7NVYUOEdl7wxEXKD/aWlpcybN29Cew/btolEIhQXF592G4+zxSdvRqmPj100i2eaB2nqSxL2aqyrL2bDzOLjHl/uS8NUE1VVVY97HMcyY+7v7+fAgQN4vd484SspKRnzPiYSCVRVPeUuxNkEt9vN+973vhO+HwWC99qgQPIKOGM40S957iZ4NMkzDINdu3YRj8fZsGED4fDxPbQm3PbTX0Mk+x1iJUZuRpkYs7r+BMMfh+L6k97m0bBX3kR29qUMvHgngwN9VKy9ioq+51Ee/wLlyRhCUVB7n0XUbcS65NYx62oPfRql6a9IVUMqbkj0ojb8ClwBZPl8pwoGzusv/4jemovYP6zg0RaztmIZ7qFD6K5iUrZGccCHGGhCfeJLmG/9KV2DcVzP/xY1IxlSXLiSGQKqpCxcRTDVgdH1Cv+wupRb/9JNX7+NS9iYig/N4yNWvZHaoaeRMgRCocjrImAnSWc9ZIOLqE66MWyIZ0zcmoJp2yCgMuSmJ5Y9Qr4EWCOlMI9b43DWxa3PJtDkEIejNmlL0B3LogryLdW+hDP3GHCrdA6n6U/o6CMbGUpLsm7FiQjDEUFkRyppyghLdasKy6aFWVwTYntHlGKfM+QfSzvinrcsq8rP4wH8eVcvX3voAPGsOWKa7MC0pSPMkKAKp13bm9XIjrRxDcumKqTxlYcPM7fczyXzS1lQ5VSIFUXJ/3csHG3v0dXVxcGDB9m/fz+6ruerQ5OJW5sMplpdezLbry3ycuOak/vClhOmTKWH3cmSyKPNmE3TzFdrm5qayGaz+Wqtrut5Ze3JEtXvfe973HbbbXR3d7NkyRJuv/12zjtv4pjD7u5u/uVf/oWtW7dy4MABPvaxj3H77bePWeYXv/gF733ve8etm06nT0hAc18Wdu/ezbvf/W7e9773cfHFF49JvjBN84Sf/wKmFgWSV8BZg1wFZPRcXjweZ/v27fj9fjZt2jTOh2xSyMRQOraA5jlC8ADpCqAYg9DyNPbKm1718RuGwc4DXSS9a1h91WpCQ7tR9v8Z6QmRFUUoioLLo6K0v4BsegB76dsAEAP7UQ4+inR58+1foahO69dMc2QSDKS3lNRQDz+46488Zy2mhDjf0B+mIliE5gkjUynnPIPViMFmkq0NfOvpYf41E8MQHrBt0lJi2CphxYfbjiJ6d3Ne04N822fyB2UDTUYl1cowV1ZlqL/kH7EfOOBEuQnVEZdYNgPVl/BP11zHhvYUX3/4AKQHOcfajV9mOKTNJu5dRNrQiKbNMUP0blU49oIoZKXkwKBEIlAAG7CkU72LpRNInCiw/oROf0LHHrUdh84J3KogY8qRFrMzDpnb34KqAKoi+OQb5vCT59p4pW2YWMak2O/i6hXVXL74iFfdX3b38qUH9pPSHRVt1hrbMjVtcCkwLayRshSWTwujqQp9cUe5a9qSlCF5riXKnp4kH72gniXVjhGsaZqkDYtd3UkMS7KoOkh10cRkTVVVioqK8vOmqVSKSCSSrw4dK27tZHB0Ja8vnuVPO3t5pS2KR1O4YF4pb1pSidd1aiTqTFTZYGpzUF+tEbKmaROaMQ8MDPDWt74VKSWBQIC7776bSy+9dFLK1LvuuouPf/zjfO973+Occ87hhz/8IVdccQV79+5lxowZ45bPZrNUVFTw2c9+lm9961vH3G44HGb//v1jXptMhTH3GSovL2fVqlX8+te/5i9/+QvnnXceb3rTm1i4cOHfjEXM6xkFklfAWYXRCtvu7m52797NzJkzmTt37mmvPuRNeO1XH6WWSCTYvn07Pp8vn5Wr7H7ZUdAWTQcj7hARlw8UFaXlmSMkr3+/o9Z1l40kaVjkqY9tOdsYmduLZXQyuoXhVphR6qNUH0T26XQkNKZ5RqkINC9YOs8cjrJrUCOjhglbg2SEB1U4FbCOgUGKhc2Pnx2i2pzBVeW93CqfRFhZJAKRyKAnN6Bf90vU3b+HjlfoS9ps8Wzi+cDF8Fgb62eW8NUlnZS/fBvFxAEwcPH00ApuF+9mzYwSFlSFGEzqBNwqLx4eojLswedSaeyJ5w9XUcQIiXPeExvQBOimRX98/IyaAFKGRZFXJWM6759j7Oz8zKWKkfQOSWnAzafeOJf+eJZ41qQ67MXvPvIAz5oWP362FcOyUYTTnrXMo9WdTls64PdhZ0zetXE6lSEPn/tTIzVFXkr9zpePiqCblsEUf9kzwKoZjrJ4y+FBvvNkC71xp80d9Ki8ZWkFN62fhqaq48hKjoQJIQgEAmPi1oaGhhgYGGDn7j1E0jZVpUXMqq2grKxs0q2/0SSvN5bl03/cR9tgGpemYNuSvT1xtrfH+Pc3zcu32k8GZ0K9C1NP8k7n9kdXa3ft2sUPfvADvv/97/OFL3yBv/u7v2Pjxo385Cc/YeHChcfcxje/+U3e//7384EPfACA22+/nYceeojvf//7fPWrXx23/MyZM/n2t78NwM9+9rNjbjcnjjgVSCmpq6vjF7/4BTt37uQ3v/kNv/vd77j//vu58sorueqqq5g9e/YpdV8KOD0okLwCzhgmc+NXVRXDMNi3bx8dHR2sWLGCysoTpwMcF94w9rS1KK3POuQnV80zktjChTXjPF5N46e/v58dO3Ywffp05s+ff+Q85ci4fqIPX7TDeU1Md/7MxFC3/BBS/fl4NJEaAGOkciecWTOkDYl+hB4H2yBgSQapZbB4KYoQJNyVZNwl+PUIsWwIT04umhkGd5A2qxRdJnhYnMON/JGgHSNm+/CjEyZFgzWP+zOzqRalrO7ZTpl6GAUbMZLsobS/hDn7EiJL3sfL2VXcl/GwfwDoj2FJyY7G/Xyf/8Ivk/RRghQCPxkuEa/QbNdRs+jDvHO9c86/fqmDl1qH87NxGcM+qiXqEDQbpy26sDrAvt4kpg0KI9U6JxwtX7lL6s4Dv8irkiOIZQEXfo9GZzRDNG3mM2UTWYuHG/uJJHXmVQS5fEkFYa+LQwMpIkkdr0slpVuYttOaPQKJKgQxXSKjGTbOKmFFXZhnmwdJZi1mlnmQUmJYjiVIic/N4YEU8axJImPxHw8dZDhtUO53YdiSwaTBz1/sAgTvXFudJ3SjI+Im+l3JVYd2Dyn8qc+mJ5qGtiwzm1vZWNpETUkgX+U7np/baBJ2384e2obSVIU9eWFL2rB4qWWYl1qGOfc4XnXHwpkSRUw1kZyqdnAgEGDevHnU1NTQ0NBAe3s7Dz30EDU1NcdcR9d1tm7dyqc//ekxr7/xjW/k+eeff1XHk0gkqK+vx7IsVq5cyZe//GVWrVo1qXVzedmWZbF8+XL+67/+i//6r//itttu4wtf+AK33nor1113HR/84Ae5+OKLx81aFzD1KFzxAs4qKIpCY2MjUko2bdp02sr91nmfQvTtRaQHyZEBoSgcqryMaaG6iUmemUXZdz/K4ScBiT3rIuyFVzqJFtJCCpXDhw9z8ODBCcUgduUS1HgPYvAQ7hydSfeD4nbmAztfcl6TErIJkKMqivJI9Uoke/J/dwH1dLA++RTPB9+AKdw8G7yMywb/D1+qB0VzQ0IHM4O9+Fo06SObHeCxosvx6IJzU49SJJLoUuUpeyXfV95OWMT4V/VOZsguhuwg5W49H9Wmtj5LR08Pe/fupVerZv9QlJDXUaYOJg0uZCtBNUEPJQ5RBVL4CIgsb1Ff4CX7w/lj97tVh7fmK1VjL/doBatHUwh4XARdCnHdcpYfuVSaApbt/N2tONW/2eUBAp4jt7NIUsejKXhcDtl4aG8fX3nwACndwhohlL/Z0s7/3Lgcr+YM2Hs0Qdaw87N9OTIpcFIubCmZVebnc5fPR1OUvGK3J5qhJ66TMZ1Wr8+lUFvkYyCh86W/NNExlEZVBIczJlI6lULTsvnZCx0U+Vxcu6JqjBGzruvO52cCsvTC4WF+/FwbtpQUBzzops2+uIEWKOXm6cVEhwbzfm45A9+ysrIxYw5SyjyB2dIyjFtVxvjV+VwqQymDXZ3xUyJ5Z0q9O5UkbyojzcAhVjll7fTp0/PVuWNhYGAAy7Koqqoa83pVVRU9PT3HWOvEWLhwIb/4xS9YtmwZsViMb3/725xzzjns2LGDefOOYcN0FHIzd7qu88orr7B7924GBgY499xzGRwcpLu7m+uuu47LL7+c7373u6dcNSzg1FAgeQWcNRgeHiadTlNUVMTatWtP67c+WbUU4x13o+74P0TXdgiUYy++jgPNJtUTefOZGbQ/3YJy+CmwdECi7Psz8vnbwRsGPUXEPY1oyQWsP//GCc0+RecrjiXKmHBUCXYWsjYyVAeqC8zsCPmcxHkgULC4ceiHvBC4GClUnvZcxLAryYfVP+FLtSN0DbtuAy1lFxFqaaeyyM+gAb8RV/JDcxPT6KPfCjLkqkQTgmWii7lKJ1EC2FKjnOxI31PDinVzePtTLFt7MS+8MoRu2XRFDRJZCykhpKZGyJlD8IQQeDUFbDfFMokYZUS3cVYxd23tpDeepTTgJmsc2yqkIugmnkyiYjO33E9XzMDrUohnDKfShkP2bBtUIWnujTI9pOL1uBnOQndcx+9W+cQf9nDZ4nK++0QL0bSRn+uTEg4NpPjcnxr55btXMb8ywO6uOMV+jf64nheJKALmVwYIezW6olkunF+erwwumxZGUwSNvQncqoJ7hCRG0wa1RV5+9WI7rUMpFCFQhMAaaTO6hMCtKRi25N6dfaybVcrMUp9jw6LrdHZ24vV68+kvo5W6f93bh2FJZpQ6rdmAW8XnUtjfn6LHqGHN4sV5P7eBgQE6OjpobGwkFArljZhHCyM8mkNex3zGZE4VfWokaiqrYLntT/Ug/1SfQyqVOqUvsEcT21fbGt+4cSMbN27M//ucc85h9erVfPe73+U73/nOcdfN7Xv//v384Q9/YPfu3Rw+fJhEIsGCBQu4+eabueqqq9A0jf3793P11Vfzgx/8gFtvvfWUj7eAk0eB5BVwxnC8m1F7ezv79u3D6/VSV1c3NWX94nqsC/7fmJeUw49MaMCsNP4R5dDjI6kUIw9BqSMiTUhvMSkRImRvZ122DSu+Elm0ftw21F13MZbgjYJlIIZbxr+eEzccY72c5jMoY9TFd7BLW0YmNcx14nECegQ7l6nb9iIVvf/EZTfeSf3SYu59+Ak2Re5hsbqfKCHuYzMPKRchUdCEjYqNLjVc2GDqIBSyriJsy2Llgnp8FRXA0EjcmHMMioBmpiMReNAxcOftLdwywy5lOYtrQ/mHwbRiHx86t54fP9vK4f5UvkXLUWcrgKyeJZGWLJ5WzKcum89XHjzA/t4EmqoghES1JX63SlXYi27ZdEcztCdAJLIkdIfEGKbNM80Rnm2O5Nu7qnKkgmjaku0dMQ4OJPnkG+byqXv20hfPOuTRcvzwFlQFKfW7iKYN/G6V1dOPkHmn2qjlLVuyppPsUeJzM5AwiGdNasNeYukEWdNyAlBwjktVHDuaZNZke3uU2eWBvIpcCMGKFStQFCV/PS3LQjdtOobSBN3KaC0OXpeKZet0xzJA0Rg/t9mzZ6Pret6IuaGhAdu28fv9BAIBzpldTFNfkqxp5/NjYxkTj6awbmbxxJ/dE8C2bVyuyUW4ner2p5rknYlK3smQvPLyclRVHVe16+vrG1fdezVQFIV169Zx4MCBEy6bI8IPPfQQv/71r9mwYQO33HIL11xzTX4GT45YLS1YsIC1a9fm/QELOHMokLwCXlNYlkVjYyN9fX2sXr2alpaWKTeDHQ1VVSfcn9L0V2c+TgiHeOXm4wCZTSBLZuDy1aLE2mH7LzHrxpI80bcXEe8+wd4nInIjEtET5JcKYH3iCXb4Z/OPwaeYNdjitEulxLYsLKESNvqwWv7Mhvrz2Kx/GUsdJotEpZdl4iCr5GG+wvs5LGtIiQB+YeDzeLA9laQsDdVK4w6WQK0zDD6nIoCVj6JyFA7P24tpUOayRmkiI90YqITtDDF83MWlHP5zE3XFHtyawt7uBELAxlklzK0I8JfdvQS9Gm5VIWNYGJbEsGxMS6IhuWrNdP5+/XQqQh6+93fLuOPlTpr6knRF00SSOnMrgvmkhPKAm+5YmpRu48PKt1xVwBgl6NDy0W+gCIktJc8fHOJdG6fzgxsX8cOHG+jPuIiYXoZSBvGMmbeHuWJJJcunhdjREWVPdxzdtElkTZbUhNBHjtvvVin2aeztTmBKhaU1fjqGM0SSev79taWj1K0p8jKcNjAsSSaTYdu2bfj9/nz2rm7atA6lAZsZJT68ikWJT6MzmqVY2iNvgcCwHRPhEt/ExMrtdo+JW9uxYwdSSlpbWymLJZkVdHMwmkYKBUUReDSFa1dUs7w2dILP78Q4W8yWXw1erbr2RDjZSDO3282aNWt45JFHuPbaa/OvP/LII1x99dWn7biklDQ0NIyxQTkWctfn0ksv5ZJLLmHJkiXjlhFC5An/9773vYKVymuAAskr4DVDOp1m+/btCCHYvHkzXq+X9vb2SefJng4cK0pNJPtwnqIjvyKjSJciLQJeFygC6Qkhevc4FT/Nc2SZ7b8i7yp8MhgRYUwGl5mPsdk8QMlQ74jVykjQu8x5xSmIQ0+idm5FyQyjqAqanRqJQZNcy5P8yVjPdmUZjymbeat4Arei0pMUeEjhdwn0Rdc5xs3AuvpiAh6NZNaZLbMlSKHx7/YHea94gEuVbbgx2Ksu5JfW5TS7FiNsyfOHhhxiowoURfDA7j6qwh6CXg3TtDFMZw7OtiWWBJcKPr+f3d0JnjoQYdPsEv79/v009SWQEmIZE7cmqAn7CHmd96c04KYnlsGwJKblVA41JSdicEyM4YiHm5QjAg9FMJTS+fFTzTyxpx0DF8XhIAvLfcws8xHPmrhVhTUzillSG+RrDzfzbPMghmVjS4hlDKrDHhZWHSFEWcPC61Yd8mpK1swo4sXDQ0TTJgjnOsyrdOxd3KrCzCKVLVu2UF5enk9x2dIyxO+2dtETyyIEzCjx8ffr67h8aTU/fraVoZRJsVcja1l0x7LMKPGyrNqPZVknNGJ2uVyEQiHq6+vJZDIs7Bvg8X297OlO4NEU1tcXsXmed0JT8sngVH34DvQlebixn4MDKSqCbi6cX8bGCYyRz1S7dir3kfPJOxl84hOf4KabbmLt2rVs2rSJH/3oR7S1tXHzzTcD8JnPfIbOzk5+9atf5ddpaGgAnMphf38/DQ0NuN1uFi9eDMAXv/hFNm7cyLx584jFYnznO9+hoaGB//3f/53UOXR2dua3Bc49fdeuXUQiEWbOnMn8+fPzZLCgsH1tUCB5BZwxjL5Z51pH1dXVLFq0aExuaG4W6UzgWCTPLl+A2vnKqCzaUWxNKEeEEZYBvqAzWzcKSufLSHcIkRk6+YMaJbpAaE4e7QTQsCgx+5xjcI7aqTrmjs82nbZwx8vOv820o01VnGE2jzD4avD3/GzRGymt/RRbtpcxvechgmQYIsxfuZDDHedya9Yk6NGYWeZn/cxidnTEMCzbMRUWEJUBvmvfyP1F7+Ty+SF+tytGMOCi1KXmDZFzogqfS8W2JT2xLBtnFvNiyzCG5VSicsuZNgwmDdKGzQ+eaeFXL7UzkNAp9rlwa07VL2tI9nTHWT+zGGUkFzf36bKkzJscS+nMMebeP1seEXAgQJGS37/SRkKX2FLgdtnUawYJ3aI3nuVfLp3D3ArnYXz39i6ebIpQ5NUIeDzYUpIdsOgYylDic1MacNEbz9Ibz1Jf4mPptCJeaR2m2KexvC5MQ3uUjGFTEXSTMWxSus2m+iDJ9kZm1s9g9uzZCCE40Jfgh8+2ksqaVIY9SAkH+pP871OH+ezl87lmZQ2PNvbTEcuiKQrzq4J8YFMdPvfYz/KxjJhHz3F5vV5mzqjjfTPqxsStHTp0iD179oyJW/P7/ZMib6dSyWvoiPHNxw4xlDbwaSoHB1Jsa4/yjrXTuHbl2EH9v5VKXllZ2Umtc+ONNxKJRPjSl75Ed3c3S5cu5YEHHqC+3jFy7+7upq2tbcw6o1WyW7du5be//S319fW0tLQAzhz0hz70IXp6eigqKmLVqlU8/fTTrF8/fvzkaPz+979n9+7dfPSjH2XmzJkA/PCHP+Tb3/42w8PDlJSU8N3vfpc3v3l8QlABZw4FklfAGYWUkpaWFpqbm1m0aBF1dXVjfj7aJ++EsC1E+4sovbuR3rCT1xqc5HyKlGBlUQQTtmutdTej7v6DI7o4uhqn+UB1g5FCWFmsBW8eV32TvlKUeJdjbmyc/ByKDNaAy49IDUL2OETRtpG2mSc4eaO43I/D01CHDjk+fIi8AtYhgpIZSh+fWSN5qDXF53rOo9hzHvV+g7gSJmFpRDqS3Lejh3eur0NVBO/eMJ1vJg4ymDIIeTSG0gZSSlZNL+b9m2fQ3J/EkvG8TUoi6xBURTjJF0jHE09KSVK3mFHioz+eQTdNLCmQONUtw5bUBd3E0waHI2nK/A7BAycRw0jqJHWTaNqg2OeiJ5qlKuyhyO9md1cMS9rYtnD2OQqK4nzZcKtOfJtp2ViWDQjcisSyLFoGkqyZHmYoqfNk00Ce5D22bwBFkFfxKkIws9RPU1+SjuE0+3oTGJaNS1XojmUJeZOcP6+UvV0JMqbFhpklhLwaKd0i4NFYVqFRnGhj/rx5TJ8+PX+MTx2IEEsbzC53SJVu2thSsqVlmA/fuZO3rqzhC2+ez2DSwO/WWFAdQFMUbNtJ39jaOsRQyqA27GZBpX+cRcuxSNjRcWvpdDo/y3fo0CHcbnee8B0d0zX2I3lyJMyWkju3djGcNqgv8eWJZH88y707ejh/XillgSPq4DNVyZtKu49kMpknZyeDW265hVtuuWXCn/3iF78Y95o8wdjHt771reMaJR8P99xzD/PmzcuT1b179/KNb3yDq666ig9+8IP8x3/8B7fddhtLly49pXMt4PSgQPIKOGOwLIsdO3YwPDzM+vXrJ1Sk5nzyTohsAu3Bf0Vpf8GZkgfkC9/FuvgL2PMuO/Z6UqLsu9/Jch1uZZ3tJpu6Di7+xNhqXMUCkiveg6fhl6jScBIowCFVLg/EOhGKhl1/Ltaq94zbjb3oapSehhHfu5OHSPSCojpk8tgnA2YqN2EG2AjsI6RU9WDWrgMzi9b0F/KKAylxqn4KoNC553keb61HqC6CQR+DeeWlo2B9qmmAd66vQwy3sVob5MuXVvBIq83hSIrqkIcL55ezbJrTinGG/2V+dk8ZVfkRQuQJqBBOxiyWweyARbi4iFc6kgicFqphO21Xj8sRA1ijHlYhr0bGsEhkLTqGMwylHKL3nk3TqQ57eN+vGxhOm+QuhBDO1VEUQWXQjd+t4tZUDD1LX8wk4POQThro0rFmAcmO9mFqg4LtzQYDCwJovhD9ieyIhvgINFUh7NVwqQpSQkXYT8ijMZjU2d4ew5bwxSsXYNqSUr87T1Q7OzvZt28fS5ctHTc43zWcwaM5hMywbLa1R4mmTSxb0hPN8LPn23jh0CC3vXVJvl0N0DaU4RuPHqQlksKyJW5NYfm0EB+7oJ6g+0iSjGVZ2LZ9QrLk8/moq6vLx62Njuk6XtzaybZrBxI6rYNpSv3uMeuVBtx0DqfZ35tk8+yxJG8qq2zgXKNTSteZJE6lXXu2obm5mbe//e2EQs6owu9//3sWLFjArbfeSkVFBf/zP//DRRddRF9fH/X19VNukl3AxCiQvALOGBRFIRgMsnjx4mPeQFVVJZPJnHBb6taforQ+g/QWO2kQ0oZkP+rjX8SuWXnMip6y+3doj38JbAOpeXHrg/h2/gQpEliXfjm/XFdXF3vEuazaUEd139OQ6EFWLcda8GanBZuNISsWI+vWO2TsKNjLbkS+9D1EJjqpazMetuMPYk+C8OaWFxqGcKN5AyAUpDuInHke5vR1aAcfHmnr5siSQHqL0W0F0dXArFgPWzKL8EWiWP4Ksr5KYhmTaNqks3+ILXd+lXNjD6DYWRa4A8xZdA3mm28Z16Y+d04pP3++nYFElvKgh2KfNqLIBa9K3jRYAEuLDJ4d1nEXhfF6vSgi5czl2aAKgaYKpFRQhMCwjpA8RQj8bg1NVbh+VQ01RV7W1hdTW+TYinzzuiXcfMdOJ95MOgTP51apDnuwpOSrVy9CRrv4zyfi+H0eMtbIMYkjyRspS9CfVVngUfjvv+5ma6/NkC7IWmBYFjXFPhQhyBoWlpQI26a+zOe0VvsSZAwby5a8cGiIW//SxGcvn4d7RL3a0tJCS0sLq1atorR0vA9dbbGXXV0xpJR0RbPE0iYeTWBYUOx3EfRo7OtN8NDePq5f7XgzmrbNtx47RHN/kuqwB7cqSOkWW1qj3Lmtl1vOdx6ynZ2dRKNR6uvrx1m0HG+WT1XVPKGbN2/ecePWTrbS5nwZYJyViy3HzlbmX///sYXK2QTTNMecwxNPPMGGDRvyyStlZWUMDQ1NKVku4MQokLwCzhiEEMybN++4LYRJzeRJG2Xfn5CqOx/3hVAgUIFI9KIcehx7+dvHr2fpqFt+ALaJ9DuZkpbUEFYGrfE+rNXvxS6eSVNTEx0dHaxctZryissw+YeR/UpEdwNi6DDS5UUWTT9C8IZbUffcgxg6hAxPw15yHcLMgDvotGvlVCqGj8ycWYobVSgIlw9z1buhdLYz57b8nWg7fzOG6MlMDMtXyczh5znPnMYi9QWWy0OQhKeTq/mecRUpu4yYmeSzzfN5k9/iU2XPoupxtIZfgebDXPeh/FE09ye5t6Ebr0tBtyRd0QyaIpx/m05LNGM683frqxU2V9l4QtN5onkIRTUoDbjoGs6gCCgPeVAE9MYNqkJuMqZNbzyLS3FasEIIrllZzT+cN3Pc1SjyuygLaAynTLKWk5RhSYluOsRrZ2MT071ZNi2s4+4dfaSy5hFjZumQPVURpExJHB97ByzcbijVLHriJt2xLLG0TpFXw5SCWeUBemNZNFXhYH+SjGHjdTmVvaxlc7A/yS9fbOdTb5hDU1MTvb29rF27Nl8BORoXzCvjhcNDtA2m6RuJQjMscKkKQY+Wjxrb2hbNk7w9XXEOR1JUhdx5k+aARyNr2jx3cJB3baxjsKeTw4cPs2rVKoqLi7Esa4xFSw7HmuXLf9qOEbcWiURobGwkm83mtzmZuLWygJulNSGePzREwKOhjbTz++JZKkNulh6l8j0WyRtI6ByOpPBoCguqgvnrcCqYaguVk1XXno1YtWoVv//97znvvPOIxWI899xzfOpTn8p/rnt7e1EUJd+xKVTxXhsUSF4BZxS5maBjYVIzebYJehKUoz6+I1FcIhufcDUx3I5I9iHdo79BC2zND0YUu6uBrQcjZDIZNq1fQ8DFEbWrpaM98lmUAw/mhQ7y+duxzv0ksnQ22p9uQWSGyRmYqTvvdP6uuCBQAcmBsYkWpxUjooJQNVHfPOLSR7zmHNwlF1ARjxMMBpGaF6wjLUwARRr4M/3YwSpW2ztJKYK49OKROleKp1mmNfER+W8UyygJfDyQWcp5ejfn+NsRyX7UvfdgrnwnuPw80xzh//2xkbRujQSQOa3ay1dU8+allaR0i2cPDmGZBpXWAGunh1i2bBnLLYnH4+KFQ0ME3SpBj4ZpSyxL0hPNUuJ38ZELZvLbVzrZ2hYlYdqoimBhdZCb1tdNeDX29STojRtjosnShk3HcIYij6BIc7zAZqYsHj8wxEBCRxUCSzr2JkKARxMIodDYkyDgVigasScJ+mw6h9OOr5wqWVdisqJsmN/GNLoGLVK6hUdzqo9p08KrKVSFPOzuivHUyztwGUnWr18/pr15NOZVBvnQOfX8flsXncMZJI4XXnnQfSRLVoJbO/LQjGVMDMseR2w8mkJKt9m1rxljuJc1a9bkVY45EmPbTsbv6Dbu6HzY0TN9E0HTNCoqKqioqEBKyYsvvojf76enp4empib8fn++yldUVDThdt65fhpd0Qxtg+m8SKfU7+L9m6ePyRmG8QTMlpI/7ujhocYBohkTTYHaIi/v2TidRdWnRqTONguVsxGf/OQnefvb385VV11FZ2cn5513Hueff37+5/fccw/Tp0+npKTkNTzKAgokr4CzCsdSu45dyI2sWobS9hzSEz4ya2akQVGxK8f7NQFIT9BRn9pHKoUCQJpIobD3UCdadTXnqQ247v0KZBNOVW7lOyE9hLL/z0jND55iQEJqEO3Rf0eqLidb1leG1NxONSg95FT5pAnCjx2oRCR68mbGpx1CRckMU1ZXin/1PyDsIox9D5F++mmkFaM8ugvHNCSHkWxcW0fJDINt4BcKPoZx5A+SxUord/NpbjevZ7e6mJjp54X0dM7xtzvD+4PNeH91OdnShXy97e2ksxAkhSItJII4Pp5rHuBTb5iLW1NYUqbS0NBATU1NPuM3oMIHz6nn2hU1DKV0wl6N/b1JDkdSFPk0zplTyv9t6aAlkmZmqQ+vS2U4pdPcl+TGn27l0gUVXLuyhiUj1Z6+eJYfPdM6xmYwp6a1Rv68ePNa3C6NaW74/BUL+MhdOx1ypir4XCqlAReaIhhOO+kagVEkw+dSqC/1MZQy+c/rFrOsNkw0GqXTPsS9e6NkdImtOldQVQR1xV68mqAzkiSWdHHFuesn1b7aMKuE+ZUBbnu0mYf29gNyJK1DktItFEVw7pwj6swZpT4CHidurmiUX14sYxJQTPRoP+vXrZuwRTha2Q7kq3A58pcjfJNp6+Z+Vl1dTVlZGYZhMDg4SCQSYffu3ceMW5te4uM/3rKA5w8N0TmcocjnYvPsEqYVj68CHl3Je+7gEPfs6MHnUplZ5sO0JB1DGX70bCtfeNP8fELJyWAq27VSSpLJ5DErua8XrF27lu985zs8+OCDrF+/ng9/+MNjiOvOnTu54YYbXvfn+XpHgeQVcFZhshYq1roPIHp3IuLdTmXONhGWjl23EdG3B/XF7wIgZ12ItexG8JVAsAp75nkozQ87rV7VDVgo2RhxVxneeRexov23qE0POJUvzYMYbEZ98j+OeOC5AyNZs3FEZhCkfWQUP9mDcIedCqOiga0ji2Ygoh2IXEVwKqp5QhlR+6bRGu8j2PkKQVVDZGJIJNLMoFiOAMSZhhNjyaaRcl6TOnmv4JEflxLjn9Xfcbt8B52sxZIKIjmAiLU7yyR6aRzy0pdK4xOOpYouVISU+GSKSNRiz4M/YkEgxf50JXOWXTBGSZpDedBNedB54FeFvaypL+KVlmEe3dfPw3v7CbicdImeaIbekRZmJqHzx509PLKvny9euYAL55fzwqEhBlP6mG3nzlQBvB43saxFhcu59a2aUcS1K6r5y54+in0uirwaacMmktSZXxGkdShNxrQJqkdIRcawcWuCsoAHIQTFxcX805tWMb22m289dpCsYeHXoMhloepxWmNQ6lW4eMPKSc8nDacNvvZwM3u6YrhUQSxjEc+k8WiO0OPiBeVcOP8Iyasv9XPunDIe3ttH1rTxuVRiWRM9k+XCGbBx/brjVg9HY3Sr9ugq30Rt3dzfcxgtvHC5XFRVVVFVVZWPW4tEInR2do6JWysrKyMcDnPFksoTHt/RJO/p5ghIqAg5v6NuTTC91EdrxLFhuXhB+aTO+3j7ON34W5jJA7jiiiu44oorJvzZT37ykzN8NAVMhALJK+CM4kRzGZO1UJF1GzCv/A7qKz9F9OwEXxhr7mWI7m1oL3wbOdK6VXp3IQ49gXnNj8BbhHnh53BFOxAD+wCBauhk1DCpS77CvAo3ytNPIL1F4Bkx7vSEId6FGB7V5s3GEMne8XN2tgWZobw9CUJgz74YWbEQGv4Ptf2Fk79gJ4KigeoBc0SsIhQkoAwddohf6RxEsh/0hPPjfDNs9MV05uXGvESO6wmCIs3l8jkeYSVrXYdHCJ4Edwg8ISwRhJRESpsBGSJHewUSrzSQTQ/iVw6yylfFU65S7mt2IsI2zS5lcc34b/k7OqJ8/eFmemNZdMsmOiI8YDhNypD5Y1MEBNwKadPi208cYvOcUhJZk4xp55dxwkMk0tEd49aUfPuvP57l/l09tA6mcasKffEsQymDgFtlRV2YT75hDt99soXnDw2iCIHPpZAybGJZkwvmlY+pMqmK4G2ra1Fw7EBsKfGqgr5oArci2FgFW158Pp8fW15eftxZtb/s6mV3V4xpxT7qy/wMpQy6oxlsCTefV89bV9WOJI8cwc3n1VMecPHovgGSuklY0dk0S+WDV6zF4/EcY0/Hx4mqfBOJN45l0TI6bm3WrFlj4tY6OjoQQoyp8h0rGu1oAjaQ0PEe1dLNxddFM6fmuVlo1xbwt4ICySvgrMKk2rUjkHUbMOs2ODNyioqy63eoDb9C+svy1iPSMlD6dqPsvRd79XsgVIPxd79DNj9G795nGdLd6LMuZsWy8xH77ndavr4yZ5vSdrbjCUMm6ggpkgOQjnDcKAtJvoWs7LkHWbHIsXo5ra1agfRXgNuPiPcciULTPAjbGpkjNJHZBIZhcrxHvI2CwthrnuPi9kjzdpoY4ALXPi6wXnCui8uP9DgEbanWSYlIMCDDKFjYI7cViSCNG822iJUu5tbec9m9JYvl7wRF5b6dPbxrw3TeNiIeAMdX76sPNTtD90E3EohlEiR1G2VUgIjEMU9WFIWAW6E3ptPUm8CljpCMkcuRI3g59MWzfOj/dvLO9dPY2hqlqS9BWdDNstoQHSPWJdesqEa3JH/Y1s28ygDxrElTb4KhtIFXU9kws4SPXzxrwmv51lW1lAU9PLCzi4NdEZZU+blx8zzW1xeTTCYZGBigu7ubffv2EQwG84SvqKhozBeg5w8N4nOrecuV0oCbEr+L1sF0vhV8NLwulXdumM41yyt5cWsDIbeXNatXnVa/t6OrfKP/ywk5JmvRcnTcWiwWIxKJ0NbWRmNjI+FwOE/4gsFg/vocnY07q9zPC4eHqQgesejQTaeaWB0+NXI7lcIL27YLJK+AM4YCySvgrMLJkLwjKzk3fKX9BefJPtpbTnUBAqXtOYfkASndYttAGHfdNZSUlJBNJgGQ3iKnrTqw/4iBseZBesJIfxki0QfZgQkO4KhEjBGvOukrRaQGEIcePbnzOSEUEAJhJEGPjxgd48wjBqsRZja/pJ5JoqguRwAygR2LVH3YrhCxrE6xHB71A7BG2rqWUAhrFv92xSrQ6+DJLyNdvnzxzyMsPqLex1fNd5BlfDvy3al/ZGVfLy1mEdNEBM0bQPrKiaQMfrOlg3X1xcws8wPw4uEh+uNZKkOevHWGpjgWKvbRBUjImw87FnyCqrAHn1slrVtY+bSLI/C5VJr7knzxL03UFHlYPi2cFzMU+100dET5n6daxth5VAY9/OOFswHHu29JTZDiY+TECiFYXq4gyyLMXDOTmTNn5olHKBQiFAqNqWINDAzko/1yhK+srGwkwWM8kXOSQY79ZSGbzbKrYRvlQV8+A3eqMBHha2xsRFVVfD7fSVm0KIpCcXExxcXFzJkzh2w2m6/ytba2jrFwMU1zTGXykgXl7O6K0zqYpizgxrBsBpMGi6qDrKo7tSitqZzJS6Wce0uB5BVwJlAgeQWcVci1a0/JOPNotW0OckTlypE4tdraWhbMqaejrZX4yGC5LJ8P2bhD8JSReDAjhTBS2DPORWRiI+Tv6IfsxA9dkR468rPRUWivGjZSCyGwnESOnCWK5gdfCVJPIhLd2NJGcXmxtADDGZ0QUQQSRdFGrokKJfUkYlG6ZRlB4mijKnoKTsvZg42qWKR2/4HoG79GWdHPUYbbnLb2SHvuSvVF3Bh8wvzwuKPNovFKphYVGyjCiCr49Cylfo1IymBLy3Ce5EXTJhKO8kY7NqkxTBvdkkwv8bKgOkBwSKHSB1HAQCVt2HkPPI/mWJBIJH1xnZ5YlsU1kv6EY/VS4nfRHc2SNW3mVgRQhGPX0hvP8p0nDpHWTRK6jSpgdnmAr1y9kHmVYx/UPT097Nmzh0WLFlFbWzvxQTO+ihWNRhkYGODw4cPs3r2bWtXHwaSk2KvgcWkgBPGMiUdTxlmK5JBKpdi2bRvFxcUsXrz4jIfB7927l0Qiwbp163C73eOqfDmcyKIFwOPxUFtbS21tbf765JI3UqkUXq83T/wWVwf5h3Pr+dOuXrqGM6iK4MJ5pbxtdS1e16kRtams5CVHvlQWSF4BZwIFklfAGcWJiFvu2/OphKPbsy9GaX7YsVfJzc8ZKVAUrDmX0NLSwoEDB1haX05dx+9Rnn+cGdkMYd9MRM1nEL07nT6l6nYEErlZNaEgUgNIPXGS6tgpUtICwkg4BMsVBE/YUe4aSYj3oEsFzRaoQsHKJEibCQQ2vbIEDwaG7aHanUEGKpGKG78+wEIcexWZE2UIEBIyuDiozuUh9RJW9Dbjevo+/JU3siL+v2gZhzQKoZDAz+/sCzl6tg+OzAHqqPRThGIoRM0sA0mdkEfDHBUrN7vcj6Y4Rr5+tzpinuz8TBGOEbI5qqSXNm3KAm7+5ZI5YNsMtjWxrBR2DvvwuVWGUgY9sSyqIpzcW9PCrSq4VYc0PdLYh2U7R+3RFJK6SZHXlU/qUBUnF7djOIOmODN9tg37ehN8+I6d/PHm9fmYs7a2Npqbm1m+fDkVFRWTfi8VRaGkpISSkpJ8nFh5Ww8Hhjto7hlGUwSKquHWNC5fWsWSCeYY4/E427Zto7q6Oq9cPlOwLIudO3eSzWZZu3ZtXlwykXhDSnnMWb7jVfly12fu3Lls374dTdMYGhoaE7d2y7pSbHcAv8c1RmF8ssgd71RV8pLJJC6X65TnJAso4GRQIHkFnFV4VSRv7huxDz/leNnlkiYUFWvmhew0ZjJwNz7LrQAAqbdJREFU+DDrVy6m7PF/QelvRLoCCKBocAfaA/+MrFwMiooMVCKMtEP0VBfSzEJqAGFlj7v/4+JUq3jChdP+PbqFLR2rFj2GVFRkeBoi1gnxblyAUDUMxUPGsOlUp7PVdw6NrsV8YPjbFMkoCV8Nfk1FGWjENULwbFQENhJBCg8qNu2yik9YH8EwVR6x53C1q4Yr1ixkX9U8vE1/wpvpwy6azi3Na9lrlzMRsXVjYeC8rwJwacqIwa9NPGuMEV+sqAuzanoRW1qGyZhW3vwYnBm80fN2AEtqQvzHVQuZFtJ45ZVX0DSNz123gb82Rnh0Xz/RtEMmbFuSyFgksMhxCSnBsCR+l4otIZ61sGzyubvOVZZE006b2+tS861d07LpT+jc+Uon79s8g4MHD9LR0cHq1aspLi4+tfd6BD6fj5ULZnF73TQebezjlcMDYGao92ZZYLWwY0eMiooKysvL8Xg8DA8Ps337durr65k1a9YZJXimadLQ0IBt26xZs2ZCscSxxBunYsQMDjEsKyujtrZ2TNzaweYD6LpOcXFxvrXr9/tP+pxGewROBRKJBIFAoGAOXMAZQYHkFXBWIfet/qTn8gBUF+Yb/xNl3mWI1mcBSbZ6La8MFSHTOps2bcJ/6EGU/v3IYLVD4AyDjO3GnYpAtJ1cJUq6jzwchJ7ELluASPblXmHiKt2xXn8VkKajYjVSzt8n2J/IDGOFarG0AJqZgmAVMlhJ73Aal9FPWKR4xbsJG8FW/7msSD6Plk4SMJ1Wr6F40ezsiDuegoqNIiVx6SeoZJnmyeAz4kwXbRgH9mPVmcxdfT5yzUXEYjH+78XD7M/mWtPj26yqkOgjl8XGSb8YSRzDsCRPH4iwtDaEpjgmwp+7Yj6/fLGdJ5oGSI6kUeRIneTI370uhbetrqXKBy+//DJFRUUsWbIERVG4dGEFPdEshwZS+Vk+VTgE0bIdwuhRBT6Xim5JbClRheOlF80YlAacapRtk6/0jW4ha6qCNGyaehPs3buXwcFB1q5de1pbcKUBNzesreOGtY7ps5SSRCLBwMBA3oLE6/WSyWSYMWPGGSd4hmGwfft2VFVlzZo1k658Hc+iZTJGzKMFHUfHraXT6fysY3Nz85i4teLi4kkRt9z+p7KSdyrks4ACTgUFklfAGcVkHkKapk3KK29CKBr2nEtgziX5CkdZmfPwV1UVMbAfsB1BhpQomSj+dJ/jEWdmQNEQ6UEnE1cojvWIULDXvAdl6CCkBjg2kZuK9qwEI3kCfz2JNdiCy86A4kJqbkSih4BhEiFAiRnl/dH/YY7ZjJssNgLDDmBXLUPtakBTXIhUFkZoHkh86CCgkWnM1Ju5Sf6RSoYhI9Ee+S1a0zr0N32bcLiEZ1uSIzbLRxO8ETWk6gHTIVguRUG3Rh7iI0vetbULTRHccoGjWA15NT564Sw+cM4MfvpcGz95rpWsNf7a2rZkRYXKyy+/zLRp05g7dy5CCEzb5qsPHWBrW5RU1hzJRWVEiDHyGZQSlyqoDHnoGEqTMez8uxfPWBwcSFLsc42oNHN2LEfOz8rNcaaHiUYF69atO2F816uFEGKMeKOjo4N9+/YRDofp7Oyku7t7jHjjdKpqj4au62zbtg2Px8Py5ctPmRCdihHzsVS7Qgj8fj9+v5/p06ePi1szDGOMRcux3i/LsvLkciqQU9YWKnkFnAkUSF4BZx1OSWF7FDo6OmhsbGTevHnU19cfuaF6w8BIaSjZhxbvQtojpRojCe4wqG5EZshhBC4v1sp3gZHCDtagpCZS104lxHEI3hHi47acYW4sCzF0CIRKEYIgjg3KUmMnGeElTggbmyIrRbplK3+2N3NuqJs6dRjNGmUiLCR+shQR413yT0ynFzEys6eYWcShJ9Ae/n+8Un8zXTE9d6RHrFfkkQeYbTsaV5fikKNcIL1pSzyags8luH9XLzesmZY3RLZsyW+2dPCLF9snJHjOPiR3Pb2bd547b4zB8ra2KDs7Y1QE3bQbFpoicKmCjGHjcanUFXlpGUxh2NATy5I2jvjq5faUMSxsr8bGWSVEMybPHxwkYzjzfLaUzrZUyTk1KuvWTdymnEp0dHTQ1NTEihUrqKioyIsT+vv7OXjwILt27aKkpCRP+k6n8W4mk2Hbtm0Eg0GWLl16WtuaJzJizs3zjSaAk41bSyaTRCIRent7jxu3lhNdTCXJ+1swQi7g9YECySvgrMOrIXm2bbNv3z66u7tZvXo1ZWVlY38+5w0oDf8HsS5EesCpWwnHggN/eX6WT/rLIFSLuepdKN0NqM98A8w041uyAoQGcrw9yemAFCpCUZH+ckSid4KW7QTrIDClQBEuwMCDgYmGKVXAwpIKg9JPmCT9lp8bBz7Abb5fsJmto7bhtFZn04FEQSAxRm4XbkWANFCb/oosv57yojCRTDLfSh39bHSrgg+eMwPL0LljWy+xrI2QNjYCRYHyoAu/W2MwaXCwP5kneXdv7+Y3L3VMmHOcm9MTUtJqhsclaByOpLBsic+l4nc5UV/gzAJKKfG4BD63imlJEllzTJM5RxdM2zHZPRRJ8bZVteiGyfaOOCndAgFeVXLDIh9XXrBuSm1KjoaUkpaWFlpaWli1alU+F3S0OGH+/Pmk02n6+/vzbUuPx5Of4yspKTllYpZOp9m6dSslJSUsXrx4SqtRR1f5LMuiubkZwzAIBAInJd4QQhAMBgkGg9TX12MYBkNDQwwMDLBnzx4sy8pX+dxu95S+p4lEoqCsLeCMoUDyCjijmMxDYbLRZkdD13UaGhrQ9ZH5uwnmXmTZXKzzPoX6xJfAMka0pAJcPkj2573kRNIGS0d76mtOfJmZcRItjm7JCvUI8RKq8/PTZpUCQpogc0Ty+MTXlgIdDV1qIOCHxpWcq+xhk7oXDZNiokhAx0VMhFCQ1IoB4tLLrekbuN+9E48wnH0pLgxL4iaDioU+cqtQHYkrtqmgYLK6LMO6+noO9qewcap2tjySSPGW5dV85MLZAMyrLeXz9zdi2+DVwK9KpJ4hmhVIVISZRspiJHDvjm5nwD7oJj2UGVNps6WzA69bw1bGV9DCXudYLVtSFnQTSRnoplOt1RRBT0ynJuxlWW2Iuxu68+vlRu5yhUOJU+n73jMtfPLSOXzoPDfPHegjOtDNRfPKOH/N6a1inQhSSg4cOEB3dzdr1649biaoz+djxowZzJgxA8uy8nNqe/bswTTNMckbk1V5JpNJtm7dSlVV1RlX8EopaW5upre3l3XrnIi2V2PR4nK5qKyspLKyckzcWldXF7FYDCEEhw79f+ydd3xUZdqGr3OmpPdGEnoLNZCEjoAVQRBi76urn2XVXdDVtay761rX1V11dbGuDV0bTeyANAEVSAMSCAFSIL0n08t5vz8mc0hIgASSDK7n+v1c18mcOe9MJnPued7nue9Datxadz5Xi8Wi9eRp9BqayNM44+hstFlrvBYSoaGhpKamnrAfSUm6CBqK0G99HmEIwO5UCHA2g+IVlpLn/zstIEwtkWDHGapoXVnzTgictieex7YFqWUdihOpuazj86vraIkRw4m/5BGq8+QfKBQJanVNatlw9ZOchNGEW+goEbGEYKVKRJChDGOaLg90BiRZh58swOl53jpA0skeM15FQUYBWUYyBLBgXB+2Hqqj1uzA4VKQJQl/vUxEkJFLxvVRlzhnVAzr9lWzvaieiEADRr1nCKO62UZcgMSX2/NZl5FPWv9wapqsGHUeCxW9zmOG7H32ioAQfx16WWbigPA2L0Oj1cnmgloqm+yUNdiIDDKQEOZHZZMdi9OT6TomIYTbZwzEXy+zYX8NDVYnBp2nymd3Ce9vAD+9TEywkWqTnY8zynh+wUCsxnL6TurLkCFDelXkeI2G6+rqmDhxYpdEgk6nayNoTCYT1dXVbfJjvYLveIKmubmZjIwM+vbt/ecuhCA/P5/q6momTJigPvdjt3W9gq+rFi3Hxq1VVlZy4MABrFYrOTk5nY5b6yxaJU+jN9FEnsYZR1e3aysqKti9ezeDBg066QVIqspDt+4R5LpD4LYjuWz4CQlQaBuaJYHThiTr2t52QqGleKp5su5olmxX8Gbeyq23imTP2rzbwS3edW506HHjh1Pdazz2WQ+WyxlKBTaMnkEKFITwPAcjTo6IcD5ynY0VP0Bq+Tceg2XZH0m4PY8q69EJN0K4PIEiQvGsSTIiV2QxctwY7pw1iPd/OkK92YHAkx5xZVoCKf3Cjj49SeK+84fwp8/3caDa7Jl6FQKDXkedU2J9hQFFEawva8buctNgdwBSu6SLIKOMTpbpHxlAeisRWd1s5/I3dlJjcnhfKqpNTuosThLD/LlwYAS/ntqPAVGByC0mzlMHR7JmbzVOt8cT0XsqWUL1Wgsw6CitN/PDjiySRw5rtz3c07jdbvbs2YPZbD7tAY/WwxuDBw/G4XBQU1NDTU0NJSUlyLLcbnjDO8A0cOBABg3qOM6tpxBCqOJ2woQJBAQEtLtPT1i0GI1GRo8ejRCCpqYm9fXximJvJfRUBii0SDON3kQTeRq9Sme3azsj8rxbOEVFRSQnJxMXF3fiA+wm9F//HqnxMCIgEnT+SE2Hkdv100lHI8CkLm7HCQVcp9mfJ7xbvm3VTYMIxA8XjQRiQFG3UYOFtZ3A80hSCQNuzPi1iDwJGU/PnhuJ11zzqCYcAH+cJMuHWg52e0SqEGAMwjn+BnSZ7yK5rC09a4p6P8P2V9Hv+YS56W8x6cox7C5tQhEwJjGEmOD224DxYf4suSaZHUUNlDXa2FvRzNq91QT76QgwyAig3uykyangFqCTQC97tl6VluekCBAtwxw/FNYzf2wcsiTx16/yqTE50Mmgkz2VOVfL9nFyYih/nZ/U5v0nSRIPzRmGTpb4bl+1p98O0EsQE+Knbvta7U78JRcpY0eREN+n3XM6+a9TUNpgw6UI+kUEdJg7ezxcLhc5OTm4XK42RsPdhdFobJMs0dDQQE1NjTq8ERwcjMlkYtCgQT4ReHl5eTQ0NDBhwoROi9vjDW901ojZ7XarglGSJMLCwggLC2sXt1ZSUtLGwiUyMrJTE83adq1Gb6KJPI0zjs5YqHgvfmazmSlTppywP8mLXLgBqekIIijWE4Gm90cYhiOq8zwRXoBnq9RrzCYQwt1KQB1bxZPAL9Rzf1vD6ffiiaPi6VgUIfEnx838wfAxiVItUivTEqtaqWuzMrwr98PpuUXvT43LH0lxI0uCnSKpTbbrj9I4ZvNDS/yYHndIIsqsB9hjT8QwOICRtgz8jmzxvAzGUIQxwGPIbKnFuP7PRF69nFnDo0/6NI06melDIgG48d1MZEki0HjULDnYX0eN2UGgQcalCNyKQJYldBK43CALBaOkUFJr4p/rCqgz2blyQl92FnuGZnQtF2xJktDL4FQEu8uaOvyCER5g4KmFI6k8ZzDZRxr514ZCGqxONW2jwWzH7nRzzeTEUxJ4uWXNPLfuAPurPNPP/SL8+d05g5k2OPKkxzocDjXdIS0trUctUcAjjiIjI4mMjGT48OGqRUtgYCCFhYVUVFQQHR1NTExMpz3nThVFUcjNzaW5uZm0tLRTrl52tsrX2o/vRLm1x4tbKywsJDc3l7CwMFX0Hc/w2Gw2dykRRUPjdOjdcEMNDToXbXaiSp7ZbOaHH35AUZROCzwATFV4tx+PnsyAIrVUR2S95+etqmgSqLm37ZB1iIBwcJ7C1mwX2S0G8YMYTamI8gw4IOFGxiz8UJCw036NegRWjBhbEi1cCkjCjZ/kJEMZToFIRIcbAy4U4GX7fOY7nuIq11+5QfcMl9se5o7Pq1j0RTH35vbn5erxNEmhiMCYFrNoT++g0PsjV+9Faiju8vNqtLrQ69q+H0SL/YqfXiLWX5AQoqd/ZCAtUbrEhgcQHRpIVIAOxeVi6baDbPghE7db8VpZq1UbITzmeLrjCJImm5MV2eV8klGKye7iL/OGMzAygCabi7IGK06ni3ljYrll1rAuP7eyRhv3LNvDnrLmloqkxMFqCw+t2kteefMJj7XZbOzcuRN/f39SUlJ6XOAdS2VlJfn5+YwdO5Zp06Zx9tlnM2zYMNxuN7t372bjxo3k5ORQVlaG3X4aSTAdoCgKe/bswWQynZbA6whZljEYDBiNRvWf1gLQ5XLhcDhUQ3avTcvxHssbtTZ58mSmTJlCXFwcjY2N7Ny5k23btpGfn09NTU2bzzOTydT5z6xWLFmyhEGDBuHv709aWhrff//9ce9bXl7OtddeS1JSErIss3jx4g7vt3z5ckaNGoWfnx+jRo1i5cqVXV6XxpmNVsnTOOPQ6XQ4nR1veVZXV5OTk0Pfvn0ZPnx416oJYS29VG6HJ5+2BY/m1LWIORcgH+2tU9wI/1Aka8PRLVwv+gAkaz24OyfyBHokTs3kuV6EECfVMVI+TDOBqqgTSBiEiwjJ1O4YAy4KRAKjpBLP81ScyOj5XknmGfc1xEpNzJV/YqqUy24xiG/dE6kmCpvRjzA/IxU19RygLzKCBiT+Uz+OH6W7ec/wOv6tX3ZJ9kweK452azgZyYmhrM+vQfiLtlupgMPpIjYiAKPBgMXhRhEeoeSv16HXyR4fNKMfdWYHwj+Y6AAzxU6BvYOX+JxhUe1uy680cf+KXCqbW9YtBDEhfjxxcRJ79x+kutHMhZPHkZR48qpbR3y+q4IGq5OwAL2ahWvUSTTaXHyaWcZf5iV1eJzZbCYzM5PIyEhGjhzZqxO8AGVlZezbt69NBq9er283jVpTU8Phw4fJy8tThzdiYmIICQk55cEMRVHYtWsXNpuNtLS0bt+ebk1HVb7m5mZKS0vp27dvmyrfyYY3wDPRnJiYSGJiYpu4tYKCAmw2G7W1teTn52OxWLrsk/fxxx+zePFilixZwvTp03nttdeYO3cueXl59O/fv9397XY7MTEx/PGPf+T555/v8DF/+OEHrrrqKh5//HEuueQSVq5cyZVXXsmWLVuYPHlyl9anceYiiY6MqDQ0ehCHw9Gh/5mXgwcPYjKZGDdunHqb1x/swIEDjB49moSEhK6f2GVH/+l1yFV7EX6hntQLexNOqwmDTgK/EI/4a+nDk0yVLQMULVEJLXmxyDrQ+SGih4HDjFR3sGWLtaPBDLnlZo+RsHebtauUiigeddzIP42vqIMXAIqQ0Ulu4mjo+PSSHnQ6cDspCU7m941XsNvVj2Bh5mnjW6RI+bzjnM1Hynm4PIFmWKVAZOFEQhCAnRbXFFyKp2L4hPEdLgkr8Dy+EEj2RkT4AGw3rmlbJe0EeeXN3Lcilyari0CjDrcisDicBMluXJIBJBl/g4zZ4abB4iQ80EBi+NHme4vDjc3p5t9Xj6Wk3so9n+7BdcxLLAGLZ8Rz88xhRy/oQnDTe1nklTUj8Bgze8eQE4MkHplsZMJpiow/rMxjQ34NEYFtq6xNNheDowP5781p7Y7xTonHx8czbNiwXk9FKCkp4cCBA4wfP57IyM6JW+/wRnV1NXV1derwRkxMTKf71MDTC7dr1y4cDgepqam9bjBtNpvZuXMniYmJav9h6/QNL50Z3jgWi8XC2rVr+de//kVWVhYRERFcffXVXHTRRcyaNavDgZLWTJ48mdTUVF555RX1tpEjR5Kens7TTz99wmPPPvtsxo8fzwsvvNDm9quuuoqmpia+/vpr9bY5c+YQERHBhx9+2OnnpnFmo1XyNHodqWWy8Xgca6HinS6sr69n0qRJhIWFHfdYABxmT/9dTQHCLwQx+FxE5GDQ++Ga9yL6jU8ile4Ehx0CozkQu4D+wW6CD34BzkZaElIRwTFI9UWeqp7EUZ88xTMC4Lz43+j2fILupyWegNOOJm/9QhA6PyRbPRLSKVW7ABKlWkbIxdgxYhAuXOjVfrpQzEdHa9tpAhe4PaWtRPtB4uQmCnBwoW4n06VdHFaiWabMQoebcMmEQKIeQQOByLiREchCAeH5sLBhYId7GJfadiBkPZLiBr0fzrMe6LLAAxgVH8Lf0kex9KfD7C5tQsLN1FiFxXPGkV+vsCK7jMN1NobHBtBsc1LRZMfpVjDoZJxuhUark7EJIQyJCUIIWqxQPNm4SJ58WiEEH2aUM8BVSkx0JDExMdSLQPZXmlsi1jwJHEKScLkFh5sFurjhyDo93+RWsa+ymfAAAyn9wkhO7LxnWlyIX0t7Z9sqpSIE8WHttyDr6+vJzs72yRQrQGFhIUVFRaSmphIeHt7p4zoa3qiurqagoACr1UpERIRqxHy8gQO3260OmPha4LWe0D9e3FpXLFoAAgMDWbhwIQsXLmTWrFmce+65mM1mbrvtNiZMmMCKFSuOe6zD4SAjI4MHH3ywze2zZ89m27Ztp/ycf/jhB+655542t1144YXtxKDGzxtN5GmccbTuybNarWRlZSHLMlOnTj25cau5Gv039yFV7vFUmQCRvRT3WfehjLgYQhNxLVgCjUeQ7E2IiIFU/JRJ6LCh+I2+CN3uj5GKt4DTgtRc1TLp6ulpa4PiwPDfy1CSrwZZj2gRUlKb+0meKV63A1fiZGRLFXLt/lN+XX6rX0WuGMhwqRRZ2HBKOoKx4oerY2eX1lpE749OcfB0xGp+ozzM9Q3r8MfBj2IUdoxE0eiJJUMQINlpFAEoyB4/vBZEy88DsXuelzEId8xIXCk3ofQ99e2d5MRQ/rZwBJnZu7DbLKSlTvGY+faBC0bGoAiBLEmU1Fn58xf7KK6zqs93QGQA910wFFmSyKvw9LlFBRnU2A0JCYdLwawI+o8ciZ+zmbKyMrKPNGF16FAUMOg99xSKgk7yzA6v3FXJQ6vzqW62I/BsE0cFGZk/No7fnjOIGpMDk91NYrg/AYaOm/TnjYljVU45TXYXwUY9kgRmuydmrbX1C3jaEHbv3s3w4cPp27fvKb+Wp4IQgoMHD3LkyJGTmiyfjNbDG0lJSVgsFrXK540S81q0eIc33G43WVlZCCFO6nHZExxP4B37vFpP7J6OEbPNZmPGjBksXLhQ3fo+Ed6evmPdA+Li4qioqOjKU21DRUVFtz+mxpmHJvI0zji8iRd1dXVkZ2cTGxvLqFGjOrU9ost4C7l8FyIkHvRGT8XQVIFu2wsofSdBcMuHWlhfVRfpdDqPLUfUUKSqPUhuOyIwCmGtR3KaOZ6Ckiw1SHs/pylwACFN+z2aSnD0/rIebA0IfQC6yhwkR0vfnDjqutfq4U6KUXKTIh1siSzDMxHsPa6jJaoDwxIiIAJcDkIsh3lz4HIMTUeQEOgk70N4/1d4qnOADgUnOgy4EYAdIzKC2bodSNY6rDdvAOPx/b6EEByoNpNR4pl6TesfztCYwHYXUW9SiSRJTJ40qV0Vx9vP1j8ygFevSWbboXoqmmz0CfVn2uAI/FtEVqi/wRNgLyR0rc7hFp7n2ScyjPDAaAYNGsTQkRaW7N0OiFbN9Ucl+pq8KhxugSyBTvLEqNWYHazeVUFeeTPVJgcuRRARaOCK1AQuHhvX7nmN6BPMw3OG8c/vDtFo9fRzBhp13DJtAGcNOboVWl5eTl5eHmPGjDm5DVA34zUarqqqYuLEid2eqRoYGKgmb3j/pr2CVlEUIiIiMJvNGAwG0tLSejUiDjon8I6lI4uWzhoxCyGwWCyqkPYaMXeGY9d2bIX4VOiJx9Q4s9BEnkavc7IPEb1ej81mIyMjg6SkJPr169e5Dx63A/ngOoRfEOiN3pN5hF3jEeTirSijL213mLdyKO9fg2SqQgT3OWpMbKmjQwUleYYyqC9EFzwA9/C56I/8BLYmMASgBER6RKDbjmRvVO1RRMs/Xrmq6rB2qu8YWi3BiYxDGAiWbJzskqggISOQHGbPFLDiwL/gC8Aj5GbIu3iZhTQTQCgWAOzoUZDpTyWVROBsGfKQUfiVbg2TpP3gFMgHv0MZubDj8wrBm1uLWZVTgc3pee7+hsNcOj6em6f1V4WbxWIhKytLDbs/2UXe36Dj3KSObVqmDY4gJthIVbOdYKMeWZZwuhWcboULRsYQ3qo3LjIkkKExQeyrNOFWjr4nvdVKR8vOvF7X0p8pg0sIas1Omu2NDIgMJMAgU2t28Or3RQQYdFwwsr0txtzRcZw1JIodxQ24FIW0/uFEBR3t82vdA3dsznJP4/Whq6+vV6PCepJjhzfq6+vZs2cPLpdLzcT1VvlOZ3ijs5yKwDuWUzFiNpvNXRLT0dHR6HS6dhW2qqqq0/pS0KdPn25/TI0zD81CReOMQlEUDh8+jN1uJy0tjf79+3f+w1dxef6RjhUKkkc/uTvuh/OKPKnxCB6fDvno4x0v4UK48EgohSBrGfrSHbim3YP9/zZjm/NPJKF4tnH9w9v450ktxTdvB59EK23XiREoAQTgJswr8Do1NiV5otkUjyEyxqMXmAFSJdfp1qIgUyPCqBFhNEmhSEAYZp7XL+Eq3Xqu063lLcPfWaz/FEnyvEa6sozjnvGHQ/UsyyxHliTiQ/2ID/VDliQ+zSzjx8J6ABobG9m+fTvR0dEkJyefdhXH36Dj6YUjiQwyYna6Mdld2F0KI/uEcP8FQ9vd/7JRoQTpBUa9jE6WCDDqiAw0YNTJngqnBG7lqI2GEJ4BDT+9TKi/Hn+DjrgQP9wKrMopP26faYi/nnOTopk9MlYVeN4t0oMHD5KamtrrAk9RFHbv3k1jY+NxkyR6EpfLxf79+wkJCWHWrFnMmDGDxMREmpub2blzJ99//z15eXlUVVV1OeKwM3SHwOuI41m0SJKEoiiYTCYaGhqO6x7QEUajkbS0NNauXdvm9rVr1zJt2rRTXuvUqVPbPeaaNWtO6zE1zjy0Sp7GGYPdbic7Oxu73Y7BYOj0dJ+KIRDRZxxy4SaPuPJ+cNubEIYARJ/kDg/zGqCKkARUnzxJRrIep4rXCkmSISDMk7G66Ul03//dsy2ruDyTraK+/TG0LdodW9074fk6cZ/WyFLL+r0CRGdE+IUiOS2qJczVuu8YJFeyyZ1MiZRADsMRbshhCBN0+cxmJ0qrTV0FkIVAV7QRd3k2Svz4dufdVFCDUxHEBhytnoUHGChtsLG5oJZhIR6/tSFDhjBgwIAuPitPpXBHUQM7SxqQgIkDwkkbEM74fmGsvH0i6/NrqDE5GBoTxLQhEeiP2eovKSkhxl7KVSlxbC4yY3a4kYHIYCNBRh1Zhxs9ObyyDoRA8XruIREgC5xOFwZPMx9BRpnyJjs2l3Lc/rzWeLdIKysrmThxYq9HXHmnWO12e4+kaJwM7yBBQEAAycnJyLKMTqdT7UcURaG+vp6amhoKCgrYvXs3ERER6sTu6QrSnhJ4x3Jslc9ms3HzzTcTHR3d5b7Le++9lxtuuIEJEyYwdepUXn/9dUpKSrjjjjsAeOihhygtLeW9995Tj8nOzgZQs4qzs7MxGo2MGjUKgEWLFjFz5kyeeeYZFi5cyGeffca6devYsmXL6T51jTMITeRp9Dodfag2NjaSlZVFeHg4I0aMYPv27af02O60m5GqcqGxBPQB4PZkuyojFyJiRnZ4jLeSpyRdhMh+D8lU4RkscFq8K+b4Yk8gjEFIphqPnUprGSY654l32peYkw1dtEZnxC3AqQsBxYKfsKOXYDwHsOgC+ElKw+0EWkLE3nHN5i796hZzFYENA3ahJ1znQDjMGDY+hmPOPxARbadBm22uDkWrLEFFbSO7dpW06UFzuBVyjjSy7VA9RTVmHG5BSr8wLhoTR8Ixk6hOt8Lf1x5g/b4aj/UJsCK7nNkjY7j77EEEGnUsSO44naLNkEFaKueHh3NZnYW9FSb8dDKp/cPIrzTx++W5uBSBq8Vg2ZsvYpAhyChhNpsQQmAwGDA5JfpGBOKvP7lMVxRFjeqaOHFir8dbeZNi3G43aWlpvT7FarfbycjIULfnO+qzlWVZTY1ISkrCbDafdHijs3gFXkJCQo8KvGNxOBzceOONVFVVkZub2+UvsFdddRW1tbU89thjlJeXM2bMGL766iv1C1J5eTklJSVtjklJSVH/f0ZGBv/9738ZMGAARUVFAEybNo2PPvqIRx55hD/96U8MGTKEjz/+WPPI+x9D88nT6HXcbneb2LKysjJyc3MZMmQIgwYNwm63s3HjRi688MJT+hCWqvci7/4EuTwLERCJkjQPZcQCjy9eB+Tm5mIwGBg+fDjSkR3oNz6O1FAC5ipPRU5npEX50EZRSTrPUENgjMdTD8VTvYPjC7yT/bUd7+l29a/0uC+bhM0QgVsfgM1qRkbhj+JOMh39qZMicCoKMkpL5U4iDBNLDC8yWi5CwuP1J5CRQ2IJih2C3FCIK/laXJN+0+YsH2w/wpvbSugT4qdmtboUhdI6C+cluFl00XgiIiIA2FFUz3PrDnKg2ozdpaCTJaICDRj1OvpG+PPX+SNIDD8q9NbsreJv3x4g0KgjqCUOrcbsoNHiZEhMEENigpg1LIrzRkS3qeApiqKG3aekpJywgrY8q5xXNxdRa/YMWOhkiXOGR1Hd7KCiyU50sAEZQZ3JhsXhZnaim9nDQtVqU0eRVt4Kms1mIzU19eST4t2M0+kkKysLnU7HuHHjen2K1WazkZmZSUhICKNHjz4lk2eXy0VtbS01NTXU1NSgKApRUVGq6DtRVbK1wBs6dGivCTyn08nNN9/M/v37Wb9+vRZpptGraJU8DZ8hhGD//v0cPnyY8ePHqx9+3u0Nt9t9ShciETMS97l/obOdPF4bBwDRdyLOa5YjVe5G3v4Kur2ft4k5O4rkEX+Kq0UAtvTdybqWXr5e5JhrVdsZDgkhyUhqHq7A392MWXHjh5NNxpkc9J+Kw+RAaomKEEiEyXaaFH8aCeZ25z1cpNvOFCkPl6RnjzyCe6MPg+xG6IweM+hjmDM6ljV7qympsxBg1IGAJoudGH+Fmy84KvBKG6z85ct8ak0OHC6PtHQrgmqzkyHRBo7UW1m9q4LfzByoPvbmgjrcilAFnsnupsnmwuEW1FkcBDbqeO+nw9SaHVw70bMt5o3jslgsTJw48aRRWZelxDOhfxj/3lzI3nITfnqZID89F4yM4YvdlRTVWnC6BSEB/lw+MZarxsfSUFdLdXU1hw4dws/Pj5iYGDXn1esDpygKEyZMUCtoihBs3F/LN3lVVDXZGRYbxILkPoxN7NzEZWdxOBxkZmbi5+fXLf2PXcUb0xYREcGoUaNOWWDp9Xri4uKIi4tDCEFTUxM1NTWUlJSQl5dHaGio6skXHBysnsdXAs/lcnHHHXewd+9eNmzYoAk8jV5HE3kavY4kSTidTnJycrBarUyZMqVNVeV0RV5XaRejpjMgElJxX/AUojQbuekIsrplK3uEnCSrgxyS244qq8RJEi1OtPN7ouvO8Y7r4Ji21iySZwikNYoTB7CKC1gVcD2yJBEX6ofLKVFaZ8ItZPobmil0yFiEARMBfOKexbdMwiALrg3dR7De7fEhdDs8djXHEBVk5KmFI/lo5xG2HKjDZrMyOU7i7rmp9I89amb9TV41jVYXQgjcotXTFILCGgt9I/zZWdzQ5rFtTncb55gGq9MzCStL6GWZvhEB1JocbCqo5exh0WwuqOaTHw/R5BSkDowmqMbOuL4nFnk2p5uXNhayp6yZYD8dOlliR3EDB6rMPDJ3OAKBye5mSEwgMcGeilxwYF81Dstbbdq9e7dnqEeS1Bza1lukH2w/wgfbS3ErCka9jsP1VnYUN/DghcOYMijihGvsLN4K2om2SHsS7+SsN6atuwSWJEmEhYURFhbGkCFDsNvtaoWvsLAQvV6vTuoePHiQxMTEXhV4brebu+++m4yMDDZu3KhNrWr4BE3kafQ6zc3NbN++naCgIKZMmdLeF63FW8rlcvXKlpZOp8Nma58/W1JrpSLxFtICPyegqRBsHr83ERjp2ZZ121EiBiH6T0Pe9zly/aH2+bYdcay3XWevOadybWoj8DxbsDa/SD6zT+dF12WE2wR+Rs8WrWxvwh8n0XIzta4g/GUXTreMCxk/HIRKZs6Vc7hd+QbJPtAz0GIMwT3k/A5PnRjuz90z+jE1qBqDIYiU8ePbifaKJhtuRWB1eV4MSVJT4HApgjqLkwFRbfvW0vqHeyxJ3AoCj02K97odFezZrosIMnCoxsLT3+TzU2EdSOBvNPL9gXoyDjfx9MKRTBp4fBH1U1EDeyua6RPmh19Lr11YgJ6Sehtf5VZ2OK3rRafTqVYhFouFnTt3qs97y5YthIeHEx0dDQFhLM8qx6CTiAv1DBMIIShrtPHej4eZNDBctZo5VbwC63QraKeKxWIhIyODmJgYkpKSevT8fn5+7YY3ysvL2bdvH5Ik0dzczJEjR4iOju7xaWJFUVi8eDFbt25lw4YNpxbDqKHRDWgiT8MnxMfHn/Bb9bHRZj1J6+1a8HxA79u3j/LyclJmXoku7BacFbuQavKRqvOhvhAluA/u4XMRA2Yg1RdizP+6ZZq2/VatQEKS9S1jtK1EYK97jgrQGTDEDOXi5kOstlo5aDWgszZjdJlwCpn+UjUvGv5NDsPIkUfh5zLTV6qgj9HBoEg/BpqyPEkhNQ5EzEhcaTcj+ozr8Gwmk0nN6TyemXVimD9uxTO56hV3XmTJk0075RgxNndMLN/lV1NQZUaWwekSCAQRQUb6tvTuOVwKDqeTnwqbMOplwoM8twshqDM7eWNrMRMHhB/3/Vdca0ERqAIPPJWjQKOOvRWmTr3aZrNZFTgjRoxAkiSsVqs6RLD5wAFqGnXEhRhwOiX0ej2SJBEeYOBwvZWKJnu7oZOu4D1/bGxsjwusE52/T58+vZ7DK8sy/v7+1NbWMmDAABISEqitraWyspL8/HwCAwPVbd2wsLBurW4qisL999/PunXr2LhxI/379++2x9bQ6CqayNPodUJCQhg2bNgJ79M62qyn0el0qhea0+lUbVymTp2qTj+KxDSUhFQ1v9JbbQTQFW5AcllQ4sYhV+eC21MVVH3wJBlhCDyaeNFL2OQQ/JVjIpPcDnRlGUQag3hxQi3v2UezOTsf4bIwLaCIK/1+IN5ppp/7BxawBQwywj8cJXYMBAShREyBhmIkwD7vJQjpeIrVm8Par1+/E04xXjgqlnd+PIzF4UYng6t14VFAgEHHhaPa9jGFBxj4+yWjWJldzuYDdRh1Npxuwej4EDXTtrjGhMNqRZJkwgKPVoMlyeOHd6DaQqPNRXhAx8M4QX6ej8ZjEwAcLoWIwJNPpHqnxfv27dvm+QcEBNCvXz/69euHOaSa1aX5uBWB2WwGwGDQY1d0SLIOo+7UhUdzczMZGRntzt9bmEwmMjIyer0HzktHPXjBwcEMGDAAp9OpJm/k5OQghFAHN6Kiok7LUkZRFB5++GE+//xzNmzY4JMMYg2N1mgiT6PX6cwHvjfarDfwCkqz2UxmZiaBgYFMmTJF3WITLR5p3uii1gIPALtnG1ey14NQUHSBKEKgw91irKy0CLzeG2R3YcRPOs7WseJEsjXQN/8d7p2XxsXFK9mjCyQgIICYwBAQw3CY6zGYy3BLOpqDhmIUfvi73cg6PfiHARL4dZxxWllZyZ49e0hKSjqpH1h8mD+PzB3OH1bm4XR5tl1FK8PoUH99h1uWkUFGbpk+gFumD6DB6uS174vILW/2TMO6nAQqFiYPj2JZbpPn8Vo9hCIEelnCoDv++3Da4AiWZZZR1minT6gfsgRNNhdCcNzEDS91dXXk5OQwePDgE3oApg2IJD48gOpmB3FhgShuBZvdTp3ZzogwheL83ZhbpnW7YrXS2NhIZmYmAwcO9InI8ArMfv36MXjw4DNC4LXGYDC0G96orq6muLiY3NxcwsLCVNHXenjjZAgh+Otf/8qnn37Khg0bTvpFVkOjN9AsVDR6HSEEDkfH6RNefvjhBwYNGkSfPh1XirqTiooKCgoKcDgcJCYmttnaai3uwCNQJUkCpxW5eAtybQFS/UF0hzZ4BjFsjbglAzqd7BlKCIhEsjeBy9vz1zt/bm5DMMWOMA4rUcRLtQyTSml7rZJxGMN4XL6Ddc0DcSgSSDKhOjsPRG1ldtBBpMZiFJ0/dkMYJjkMp9OJQa8j1FGBe+iFSOf+sd0FsLi4mIMHDzJ27NguTRJ+sP0w/9pQiMnubql+gixLBBh0jO8XypKrk0/Yn+ZSFPaWm9hbXE5dxRHmTBpJaEQ017yVgcnuqdhJkoTLrdBodTFndCx/mZd0wjVtOVDLq98XU2d2eJJGjDrOS4rm9hkD2pkre6mqqmLPnj2MGDGiU31YPxyq47l1B2m0OtXKb//IQB46fwB+zmaqq6upr69XtxdjYmIICws7rvDw5j0PHTrUJ9uETU1NZGZmMmDAAJ8IzNOdorXZbOrwRl1dHQaDQRV8kZGRx51KFkLw9NNP8/rrr7N+/XrGjBnTHU9HQ+O00USeRq/TGZG3fft2tYm6p8nLy6OkxGPO27ryJIRQcyjhqIM91jqMax9GrtztGWwQiifj1mlBajERBjxTupFDkGryWwYgTjRa230oOn+etF/J567JODFgwEWavJ/HDW8RLTV51iHrWCot4EXLhQQYdQQ6GxCygTolkCDZydLo9+gnVeMacyW6wvVIDjMKEi6nHZMhhj1RF6ELCCO07wii4xIICwujoKDA08eYkkJYWNhJ19kaq8PFgld3UGd2oNfJ+OtlQvz1uBUFi0Ph+ctHk9o//LjHCyEoKiqiqKiIcePGERkZiSIEa/KqeXbdAayOo1v/g6OD+Mdlo4kLPflQT4PFScbhBuxOhaS4YAZHBx5XOJSVlbFv3z7GjBlDbGxsp597WaMnBaTO7KB/ZCAzh0US6n90S9jrDVddXU1NTQ2A6scXFRWlVpyrq6vZvXs3SUlJvfJ3cyzeCuKgQYMYOHBgr5+/u21SvMMb3tfdbrcTGRmpij7v8IYQgn/84x+8+OKLrF+/nnHjOu5R1dDwBZrI0/AJdrv9hD/3Nqz3ZDVCURTy8/MpLS1Fp9NxzjnnqD/zCryOtmf1P7yIfteHiNAE0PvhdjqRyjLQK+0ndJENJ87A7XYkCgLGcUXDXQQIG/44sGPAgj9T5VyWGF70PBedgSscj1LkiiQyNBjJ1gAuO4qAWhHC3cEbuH5SIq6p9yBV7UZX/D2StQElrC9y9V7k4u9RHDYc+hAORp5NUfhZyDodw4YNIyEhQa14FFSZKKy1EBloJKVfmGqMfCxljTaufzsTo15qEw0mhKDa5OShC4cxf2zHFhRev8WKigpSUlJQDAF8tLOUDfk1ONwKw2KCiA42YtDJDIsN5pykKIKM3dup4q1gjh8/vutxfF1ACEFDQ4M6vGGxWIiIiMDf319NQuiN6vexNDQ0kJWVxZAhQ3xSQexpHzwhBBaLRRV8DQ0NrFixAp1OR2BgIO+//z5r165lwoQJ3XpeDY3TRevJ0/AJkiQdN9Ader4nz+vTZ7PZGDNmDHv37lV/JoRQz92u/05xoTu0HmEMAqHgrjuMMFWhFw486bPeJFrv/TsfRN4duIyhPO68Fr+AEAJtJhCCABwgIENJ4oBIZJhcgfALpd4WgF4WYAxEMQSg2E3ITiu4jdQNuhjXtFkgyYg+43D1GQdCwfj5ncglW0EfgM4YSICziaTSZej0BmwjLqO4uJj9+/cTEBrBRwUK2eU2HG5PD9zg6EAeu3gEA6Pa95dFBBoIMuow2V1tRJ732D7HqbopikJubi6NjY1MnDgRndGPB1buZVdpE/56GVmW2FHcSHSwkWcuGcng6KBufb1bx6SlpaV1uYLZVSRJIiIigoiICIYNG4bFYuHAgQOUlZUBUFhYiMlkUqdGe6MfzrtFPHz48C5nsnYH3inenhzykCSJoKAggoKCGDhwIE6nk+rqat5++2127NiBv78/zz//PPPnz2fOnDmq2beGhq/pXVdMDY1O0pMWKhaLhR9//BGAKVOmEBgYiKIoav+dd4tW7b9rjeICtx3JWotUno2h8RBGd3OL4bA3GaP1MTJd+zOT2x6v96ezXitCH0DuWa+wRxmE0WhsqTT6gyRjxIkTHWVEe1IqXFbG6oqxy8FYHILSJhdFZiOFjjDMih+x/ZNahkZaraxiF3LpDvALBf8wFL0/JuHZshrRvI2Rw4cyffp0Jk+ezJdFgh+Km3E5HQTKLoyyYH+liUdW78OltDeMDjDouHhsHE63oNnmwqUIrA43jVYXw2KDSOnXXjy5XC6ysrIwm81qDuzWg/XsKWsiJthIVLCRiEADieF+1JodrMgu7/RvoVOvtxDs27ePsrIyJkyY0OMCryO8pstpaWmcffbZDBo0CKvVSlZWFps3byY3N5eqqqoe+1uqra0lOzu7U0M2PYFX4J3Mkqm70ev1WCwWdu3axbfffss333zDoEGDeOaZZ/j66697ZQ0aGp1Bq+RpnJH0lIWK96KUkJCgepd5z9V6wKJdBc+L3h9hDEUy7YHW/XdttmOFJ9dWKB6hJLUIN+XEW9QeWgkgfQBKxGDk+oOtBjc6RviFg95IdLAef2HH0WzFKFlB54fwC8Xm1mNwO+hvNCEpThB6rjd+zzbrKEobPZUzSQJFgJAllmeVM3dMbJttTUvVAb63DsfuF8V4DhNir8Kg16M3hiNZapAstRDSB6H356cyB4F+RoKNOlxuF263GwNu9lc0snpbLueO6deu0nTT1P402118k1dNg8WJXpZJ6RfGw3OGtdvm9cZ0GQwGJkyYoPal7a80oQgwHuNv56+X2XWkqROvf+dQFIU9e/bQ3NzMxIkTe9xctyOKioooLCwkNTWV8PBwAPr06UOfPn1QFIWGhgaqq6spKChg9+7dREREqMMbJ4t16ww1NTXs2rWLkSNHEh/fPvWkp/GVwBNCsHTpUtUq5eyzzwZg6tSpPPHEEyfcodDQ6G00kadxRqLT6U46nNFVDh8+zL59+xgxYgT9+vVTb5dlGUVRsFqt+Pn5tTNGlcsy0R1YA+ZK3BHDMDfWESyB7P0w72iewvsznQGEQPiHIVlqPHm3Lmun1isCIkBv9Ai9mnwQHYlez4VNclnBbSf+x8e5SJnEMvcUhGTA323D7nRj04VxgV8BAwNsKKHjQZJJcTsYceQwde4kT76tJBHkpyPYT0dxnYUN+bVqH9yG/Bqe/i6KBtOvUMwS/ji4IWg7vw36CclWD8ZAhJ8nb7Xe4sThVvDTy0iyhEE2YDAYMBoV7CYH1c12srOzkSSJ6OhoYmNjiYyMxKjX8fvzh3LD5H4U1liIDDIyNKb9oIPFYiEzM5PQ0NB2MV1BfjpP/5TdhcWpIEseGxanItoMM5wO3hxah8PBxIkTT8tX7VQ4dos4NLR9zq0sy0RGRhIZGUlSUhJms5nq6moqKirIz88nODhYNQMODQ3tskCqqqpi9+7djB492ic9gL4UeB9//DH33XcfK1euVAVea3rbMkZD40RoIk/DJ5ysJ0+v12O1dk4MnYzW22qpqalERUW1+ZlerycyMpKtW7cSGhqqRlIFBgaiy12O4aeXwWlBIOPav55Al8njFWdrbDFgk0D2Ztl6n5MAWQ+KAnoj6PSI4Fgkp9Uj/OzNtFeGbZGs9YigGNAZEf7hSNbajp6d519uJ0gScnUe9xkOI+n9+dI6GjMBGISTeYadPOj3GSI49ug2rM5ImYgiQjYTGBaNJMnIigOEE5OQ2F9pgrFxFNdZ+MuX+VgdMkGyA1lxYpUCeMs8nSG6Ki7WVeBKugqMnl672BAjof56GqzONokRdrfA36BnxvgkRsQFqZWm/Px87HY7UVFRxMbGEh0dzeTj5LY2NzeTmZlJXFxchykOkwaG8+9Nheyvcnhye/H8ikL89Jw34sT+dp3Ba5YNkJaW1i6Sr6fxDplUVlYyYcKENpnPJ6J1P5nD4VCndUtKSpBlWa3wncgmxIvXB3Hs2LFdmiLuLnwl8ABWrFjBb3/7Wz755BMuuOCCXjuvhsapook8jTOS7tqu9Q5YWK3WNgkW0NYiJTU1FYfDQXV1NVVVVRw4cIBwg4sJ+S8j40QJTsRkMqEPCsPfdBDhsnnEmmwEWdeqyiY8wg7h0V8Go2dIwxiKc8L/oc98G7mxuBMr95QHpeYKz385mk98dxS8vX/+ioWHg1dzW/AWSt1h9FGq6eMuQ+CHkNtOfkbqrNS6g9C5bZ4JW7ezxYw4hAjTfmAIX++pwupwE6AHN4Ho3RaChI0mJYBPLanMTQnBOeku9TH9DTquTE3gtS3FNFqd+Bt0ON0KdqfClMERjOzjMZj1VpqGDx+OyWSiurqaw4cPk5eXR1hYGDExMarYhqMmwwMHDmTgwIEdXtyzDjfhVmgxVRYIPFvQDrdC2oDT65mz2+1kZmbi7+9PcnLyScVQdyOEYO/evdTV1TFhwoQuGSS3xmg0Eh8fT3x8vGoTUlNTo4rtyMhIVfQdmx1dXl5OXl4eycnJXfJB7C58KfBWr17NHXfcwQcffMC8efN67bwaGqeDJvI0zki6Q+R5w9EDAgKYMmVKm6qLt/+utUWKn58fffv2pW/fvjidTizZK5DtDTToIqCxEb1ej59/AIqIQ24uRchGJLcN3Hi2Z2U9StQwHOc9jj5vJfKRnzzTqREDcY27HmXQ2biHzEafvxrdrg+Rq/acYPUC1/CLQW+Aqr3ozVUnf8KS7BkMEQ5wWogO8CNaZwaHGTCCMchTfQxoqZIJQbphO393zsdibiZQOBCSngYCCMDO3Ip3kEvCqGyOwq0oKG6B0S8QIQUhue3IDoUjQaNwXnh720gJ4LpJfVGE4JPMMkw2NwadxLyxcfzunEHtLsySJBESEkJISAiDBw/GZrNRXV1NdXU1Bw4cIDAwkMDAQGpqahgxYsQJG/w/312Jv0EmNsQPi8ONQOCnkzE53Gw5UMe1E09NGFmtVjIyMggPDz9uDm9P0roHcMKECd3SUweebd2oqCiioqIYPny4uq3r9fwLCQlRPfmam5vJz89n3LhxREefflW0q/hS4H311VfccsstvPPOO6Snp/faeTU0ThdN5Gn4hJN9QOv1+tOyUKmrqyMrK4uEhASSkpLUi7I3oswrII83YGEwGIiIiFSP8w8IQFEUTzXPpeBvjMQVPYqApgJkawPCGIh76BxcabcgIofg7DsJXHbPwIRQkCt3IRdvQYlPxZV6M67Rl+P33nzk+oLjvULoSr4HhwmXyzu1ewICWip0tgYQCpLT4unpU9xILgvu/mehxI1Bn/NfcJYh9P5ITguXhzaxL2QyX1eGU0coQkCI7OCB6G0MVEpx5a7AaLschEBvNCC1DEAoOiNuyc3whMh2Ag9AJ0vcNLU/V6YlUtFkIzLQSHgnMl8B/P391XxXl8tFfn4+5eXlyLLMwYMHaWpqOu7WYr3FgUEnY9BJhAUc/Xgzt0zqngomk4nMzExiY2M73CLuadxuN7t378ZqtfZoD6A33zU4OJhBgwbhcDhUP76ioiIURVGrd263u1crmb4UeOvWreOmm27ijTfe4Iorrui182podAeayNM4IzmdSt6RI0fYu3dvuwGL4yZYdICiKOxvDmIg/oTr7cgBUSBJCMUN9XU0RCSTEX8TRDYQER1PdEJ/oqOj1SlPAPR+6PJXY/hpiUd8ISGCYnCe9QeUIefhmrYY41e/bUnDaE3LVq2pAoGEXu5s35cEOj+PsHTbkSzVgIQS2g/njAcREYMQof3Q7fsMyVSFOyENJfka/lS0matsy8jSj8NfcjMjsJhovRXFZMR0eDeTR1/JpjJ/asxO/PUeTWdzKhj1MtdOOHGyQqBRd8redN4Ui+rqaiZMmEBoaKiaQLBv3z6cTidRUVHq1qLBYGB0fAhbD9YR4qdThYDT7Xl9h8Z0fR1ek9/+/fv7JIfV7XaTnZ2N2+1mwoQJvdoDaDQaSUhIwO12U1NTw7Bhw7DZbOzduxen06lu60ZHR7fb1u1OfCnwNm3axLXXXsu///1vrrnmml47r4ZGd6ElXmj4BJfLdUIRV1dXx+7du5k1a1anH7P1gMX48ePbDVh4PfCOa4/SgtPpZNeuXTgcDiYFlhCU8Ro4TGrvnQiJx3HBMyjRSTQ3N1NVVUV1dTVms5nIyEhiY2OJiYkhoDID49f3gOL2VNWE8AxPGIOwX/I2IiQe/zfOQjJX4bFdkVtEWuuBk05Goen8POuT9QidASQ97hEXo0Qn4R4+7+gWbUeH5ryP4YcXECGJ6lCG2+3CXVtEU+xkgq5+nYM1Fv625gB7y5sRAuLD/Lnr7IGcl9QzfVmKorBv3z5qampITU1tN2AghMBkMqmvvclkIjw8nEolhH9uq8HqVAjy0+NWBDanmxF9gllydTL+hs5Xn2pra8nJyfFZDqx3yEOSJMaPH9/2C0QvUVxczKFDh0hJSVFtWryvvXdLvbm5mdDQUFXwBQcHd5sQ86XA27p1K5deein/+Mc/uPXWW7WpWY2fJZrI0/AJbrf7hNuxjY2NZGRkcO6553bq8VwuFzk5OVgsFlJTUwkKOlq1OVFE2bFYLBays7MJCAhg7Nix6PV65PJsj4WKpRoRNRz38IsQoe0rWN5+pqqqKpqamkir+C+xdduRQhORvFVDIZBMZbhSbkKuL0Iu+BrJYWml5Y6t6skd3NYe4R8BAeEIfSCStQ73iItxnvvXkx4HgKkKv5W/RjJVIgKjcCkCV1MlOoM/Yv4LiP5TW5YuKGu0YXcp9I8MQN9DfWne7Unv77Iz/WdWq1UVHT8W1rOp0kClVcJo0HH28BhumzGAmODOV5u8E6SjRo3yiQec1wfQz8/PJ0Me0NaH70RGz3a7Xd3Wra2txWg0qtXViIiIU+5f9KXA++mnn0hPT+fJJ5/krrvu0gSexs8WTeRp+ISTiTyTycS2bduYPXv2SR/L65vm7+/PuHHjTjpgcTzq6+vJyckhPj6e4cOHn9YHu91ux/DJdejr9mPVhSDLMgaDAYNBj85cidJnHHLlbtAHgtPs8ZpT3OqUrtAZkdzeSLRO/IlKOoR/OOj9EOEDccx9HhHe+eqTVLELw9bnENX7sdttyCFx6Kb/FnfS/K4/+dPAW70SQpCSknJK25PeyKnCsiqaGuoJMuraWIScTHQcOXKE/fv3M3bsWJ9MkNpsNjIzMwkODm7nA9hbHDp0iJKSElJTUzv04Tsebreburo6NePV5XKpW+rR0dGd7if0pcDLzMzk4osv5s9//jOLFy/WBJ7GzxqtJ0/jjESv16tRYyf6kD3dAQsvZWVl7N27t9vimfz8/DD0HYuuqQB9UDAutxuX04nJZiXQ5cBmMhHsdkJgAJIxELd/GA5zE/62Co+3m2jlt3cSRFA8kr0RZB2uSXfiSroYgrvmXyb6JHNw4uNU7N7IsEEDCB82Gbehd1McbDYbWVlZp21RYjAYSEhIICEhQbUIqaqqIi8vD5fLpU6LRkdHtxOR3upVSkqKT/JHvVO8ERERjBw5stcFntdoubS0lLS0NEJCQrp0vE53VFALIWhublb9+LzWON7XPygoqMO/SV8KvJycHBYsWMCDDz6oCTyN/wm0Sp6GT1AUBafTedyfO51OvvvuO84///zj9iJ5ByySkpLa9EwdO2DRYQZtq/seOHCAI0eOkJyc3KaP73SRKvfg9/lvwN7kqbIJgWRrwOkfSU3UZKILV2E3RKDT63G5XehlHYHm4uMkW+DplxOCNsJPNiJikjw2KYoT+7WrECEJXVqn9zUoLS1l/Pjxau9Vb2I2m8nMzCQyMrLHxI1XdLTuoWwd9XXkyBFKS0u7XL3qLrzixldTvN73QVlZGWlpaZ02Wu4sNptN3datq6vDz89Pfe3Dw8ORZdmnAi83N5e5c+fyu9/9jj/96U+awNP4n0Cr5GmckXirOC6Xq53IE0KQn5+vXpCPHbDobP+d2+1WvccmTZrUpo+vOxBxY3Bc8BSGH/6F1FgCgBI/HmX674k0hmCo2oDssGJx+nvSGewNLXm3OjxmyscKupYEDeHd5pY8aRrg8ceT9QhD13zgFEUhNzeXhoYGJk6c2O2vQWdoaGggOzubvn37MmTIkB67uEqSRGhoKKGhoQwdOlTt46uqqiI/Px9JkkhM9PRanqyC3N14kzwSEhJ6XdxA+ySNnngf+Pv7qz6Ubreb2tpaampq2L17N4qiEBYWRmNjo08E3r59+5g/fz533HGHJvA0/qfQRJ7GGYksy8iy3G4Ct/WAxZQpU055wMJms5GdnY1Op2PSpEk95j2mDJiBvd80pPpDHhEWPlD1laseeRPBma8SJDUjy3oQVoSkw+LfB9llRY8LWadHVuye4QzFhTer1oPkyYt1ecyP3UnzwT+802vzThE7nU4mTZrUozYYx6O6uprdu3f7ZII1ICCAvn37Ul9fT2BgIP369aOhoYGdO3diMBi6ZXigMzQ2NpKZmcnAgQMZNGhQj53neHin0mtqak4rSaMr6HQ6NT5QCEFlZSV5eXnIssyRI0dobm5WX/+e/uJRUFDA/Pnz+dWvfsVjjz2mCTyN/ym07VoNnyCEwOFwnPA+3333HRMnTlS3zrwDFn5+fowfP/6UByyamprIzs4mKirKZ31PamN7/yCiajPAaUGuykM+8iOExKO4FZwuF26XC529HkUfgFFyIbsdSAgkl8UzbOEXCpKMEjsKx9wXOt2L5+1/805v+sKew9sH6auQe+8XBpfLRUpKiir0FUVRhweqq6txu91t+vi687Wqq6sjOzvbZzYtraPS0tLSCAjo3T5MaN+Dd+y2bkBAgPrae7d1u4vCwkLmzJnDpZdeyvPPP++TIRcNjZ5EE3kaPqEzIm/jxo2MGzeOiIgI6uvryczMJD4+nhEjRhx3wOJE/XcAVVVV7Nmzh0GDBh03/7QnURSFvLw86uvrSUlJadP3JB9Yi/Hb+8AYDN6hB7cTLLXUJF1Lif8o/I9sIUAvoeszgogAHf7CiogcijJwJug7V4nzJjj4UuQWFxdTWFjY7X2QncXpdJKVlYVOp2PcuHHHFW5CCJqamlTB5/VC9FaZTiderKamhl27dpGUlKRuE/cmQghyc3NpbGwkLS2t26LSusLJevBcLlcbwS2EUAV3VFTUaZlDl5SUMGfOHObOncu///1vTeBp/E+iiTwNn9AZkbdlyxaSkpKw2+3HHbDwGhx7xd2JBiy8xq6jR48mLi6uW59PZ/DagyiKwvjx49tvj7qdGL+9D92hDS29eS0RYtFJ2Be8BoFRqj2I16LCz89P3fYKCws7qWitq6sjJyfHZwkO3t6viooKUlJSfDLg4LUoCQoKYsyYMV2a4rVYLOrr39DQQHBwsGp+3RUTYK8Pn6+qmN4sXJPJRFpamk+26rs6ZCGEoLGxUX3vewdnvKKvK9vMZWVlXHjhhZxzzjm89tprPvEh1NDoDTSRp+ETOiPytm3bhr+/P/X19R0mWHj77yRJOmlE2d69e6mtrWX8+PE+ERYWi4WsrCyCgoIYO3oUhvKdyBW7wOCPe8AMROQQzx1ddnT5X6A7tA5cdpQBZ+EaeUmHiRXe5vWqqipqamqQJImYmBhiY2M79IMrLy8nLy+PESNG+KRy5B3yaGxsJDU1tVd6v47FYrGQkZHRLVO8rbNda2trMRgMquA70baid5s6OTnZJz58iqKoZtNpaWk91o96Irpjira1Aba3r9JbYT3RF56Kigrmzp3L5MmTefvtt3tF4C1ZsoRnn32W8vJyRo8ezQsvvMCMGTNOetzWrVuZNWsWY8aMITs7u8fXqfG/hybyNHyG3W4/7s9cLhebNm1CkiQmT558ygMWDoeDXbt24XK5GD9+vE+2pLzTo/Hx8Qwf1A/jhr+gK9rcMkghwBCMc9JvcCefejamoig0NDRQVVVFVVWV2kfmFXylpaUcOnSI5ORkoqOju+/JdRKXy6VGxaWkpPikcuSdYI2Pj2fYsGHdWsVsbQJcXV2Noiiq4IiKilK3gw8fPkxBQQHjxo3zyTa1oijk5ORgt9tJTU392Qq8Y3G5XNTW1qpVPqDNtq739a+uruaiiy5i7NixvP/++73Si/rxxx9zww03sGTJEqZPn85rr73Gm2++SV5e3gn7ML1fhoYOHUplZaUm8jROCU3kafgMh8NBR28/74CF3W5n8ODBbSYOuyLwzGYzWVlZhISEdHlbrruorKwkNzdXbazXZS/F8MOLHt88Y6DHO89SA7Iee/qbiOik0z6nt4/MK/gsFguSJDFw4ED69+/f6xd2h8NBVlYWer3+hP1vPUlDQwNZWVkMHDiwx3sxW28rVldXY7FYiIyMRKfTUVtbS2pqqk+8CN1uNzk5OTidTlJTU0+rn+1U8Qq8Pn36dLvQ9iKEoKGhQRV85eXlvPzyy8yaNYtvvvmGYcOG8dFHH/Xa8588eTKpqam88sor6m0jR44kPT2dp59++rjHXX311QwbNgydTseqVas0kadxSmgWKhpnFPX19WRlZdGnT582IrCrCRbe3rO+ffv6zHfM2wPYOh5LX/C1x9TY2LJVKUmIwGikplJ0RZtwdYPIkySJsLAwgoODsVgsKIpCXFwctbW1FBUVER4erm4r9vQ0pTfBITQ01GcRXd4Bh2HDhtGvX78eP58kSYSHhxMeHs6wYcMwm83s27dPHRzIz89XX//jpT50N263m+zsbNxu9/+0wAPP6x8REUFERATDhw+nrKyMnJwcVq1axYEDBxBC8Oijj3LxxRczadKkHn1POhwOMjIyePDBB9vcPnv2bLZt23bc495++20OHjzI+++/zxNPPNFj69P430cTeRpnDKWlpeTl5akDFnv27FGTK7z2KHDyCdojR46Qn5/v094z70V9woQJbXsAHWaPqXFrJMnzj8PcbWtwOBzqN//Jkyer1TubzaYaAO/fv18dHIiNje0eweF2INXkg6ynyRhPZnYOcXFxPklwAE//VW5urs8GHIQQHDlyBJPJxJQpUzAajWqF79ChQ2rqg3dwpicEh8vlUvOAU1NTfVJJ7S2B1xHBwcFs3ryZwYMHs3nzZjZu3Mjnn3/OlVdeyf79+3u0haOmpga3291u0CsuLo6KiooOjykoKODBBx/k+++/98nvSuN/C+0dpOEzJElSK3T79+/n8OHDpKSkqD1jOp0Ol8vVJqLsRBdBIQQFBQWUlZWRkpJCZGRkrzyP1nh7z+x2O5MmTWpXKVMSJ6LLW94yPdvyXFw2j9dd3NhuWYN3yMMbcN96m9rf359+/frRr18/dVK3qqqKwsLCLk/qHot8cB2Gbc8jmSpQFIFOjiBpwu+IS5rpE4HXuv/NF32IXg+62tpaJk6cqA6aJCYmkpiYqA7OVFdXk5OTA6D2UUZFRXVLe4HL5SIrKwtZlklJSfFJy4IvBZ7JZOKyyy4jJCSElStXEhAQwNVXX83VV1/dq6kmx57neOd2u91ce+21/PWvf2X48OG9sjaN/200kafhU7yiyFvpaO0bp9PpsFqtneq/c7lc7NmzB7PZ7LN4rtYGwxMnTuzwW7gr+Rrkkq1ITaVgCATFDW4HSt9JKANOPm13MhobG8nOzu5U9cxgMJCQkEBCQkKbSV2vKPAKvs4kPsjl2Ri/ewScVlz6YGxOG+HuCiJ3/RP7sBREeO8Z/QohKCwspLi42Gf9b95J4qamJiZOnNhhtejY1IfGxkaqqqooKChg9+7dbfz4TmVQxel0kpmZicFgYNy4cb84gWexWLjiiivQ6/V89tln7b5w9cZaoqOj0el07ap2VVVVHdo4NTc3s3PnTrKysrj77rsBz3tJCIFer2fNmjWce+65Pb5ujf8dtMELDZ/R1NTEjh078PPzY9y4cW0GAoQQVFRUsHv3bgICAoiLiyM2NrZDLzKvuDIajSQnJ/uk36i5uZmsrCyio6PbmDV3hFRbgD57KfKRn8AQgHvYHFzJ14FfyGmtwRsRNnjwYAYMGHDKFzFFUaivr1erfK0ndb0XrWMxfPcIur2rcRgjsTnsBAQEYNDJYKrENfEOXJPvOq3n1lla+/ClpqYSEnJ6r+mpoCgKu3btwmq1nrJFidlspqqqiurqapqamggNDVW3dTvzBcbhcKjpMOPGjfNJL6QvBZ7VauXKK6/EarXyzTff+MQ2ycvkyZNJS0tjyZIl6m2jRo1i4cKF7QYvvGbprVmyZAnr169n2bJlDBo0yCdfYDV+vmgiT8NneH3wWvuVebdvW8eU1dbWUllZqZr/egVfaGioGlEWExNzUnHVU1RXV7MnJ4vRwQ3EBzggMBp3/+mnLdq6grcPsbt7z46d1LXZbERFRamCzytgjJ9cg6jIxSIHERAYiL5FCErN5biGzcF54bPdtqbj4fVDrK+v95kPn3fAweVydduAg91uV/v46urq8Pf3b9PHd6x48jb7BwYGMnbsWJ/8TVgsFnbu3OkTgWe327nmmmuoq6tjzZo1PqnktsZrofLqq68ydepUXn/9dd544w1yc3MZMGAADz30EKWlpbz33nsdHv/oo49q07Uap4y2XavhM1JTU9t8+B87YCHLMjqdjj59+tCnTx91S7GyspLMzEwkScLlctG3b1+GDx/uk4vZ4cOHKcndzqzGzwgsPAR4vjPpQxNxnPtXRMzIHj1/6xzcnuhD9E7qhoWFMWzYMEwmE9XV1Rw+fJi8vDzCw8OJiYkhQgkmwuUgMDzmaKVPCAQgQvt265o6wu12s3v3bqxWKxMmTPCJH6I30USSJNLS0rqtad7Pz4++ffvSt2/fNtvq3ot+az8+l8tFRkaG2o/5SxN4DoeDX/3qV1RVVbFu3TqfCzyAq666itraWh577DHKy8sZM2YMX331FQMGDAA8JuUlJSU+XqXG/ypaJU/DZ3iHKuCo/11nBywOHTqk2oE0NzcjSVKXeshOl9ZDHjMtXxN4eCMiNAH0/uB2IjWVokQNw5H+H9D1zPaxt3JVV1fXLge3N7DZbFRUVFBUVERIfS4TSl5HLykQGIksgWSrB2Mo9svePZro0QN4p0cVRSElJcUn2/Xe7VGj0dhr/W+Koqh9fNXV1djtdiRJIjg4mHHjxvnEcNqXAs/pdHLzzTdTUFDA+vXrfTJso6FxpqGJPA2f0XpytrMGx96eFW/UWUhIiNpD5t1SFEKo21lRUVHdLvjcbrea+5ma1I/wL2/1WKC0jh5z2ZAstTjmPo+SkNat54e2U7wpKSk+rVwJIRgzZgyu7E8IyXkD2VaPJEm4g+KwTbsf/1Fzeuxi7zVa9uVwgd1uJyMjwxNZ5+PtUaPRiCRJNDc3ExYWplb5eqOPy5cCz+Vycdttt7Fr1y42bNjgk2xqDY0zEU3kafgMt9uN0+nsUkRZTk4OiqIwfvz4DisVXrd7r+BzuVxER0cTFxfXLbYUdrud7OxsZFn2VEvMZfituhlhDAZjqwupUJAaDuOY/TTKwFmndc6O1tBa2PjCS8s77OLv709ycvLR19VhgfJsGpqaKVViqKprRKfTqaK7O6usNpuNzMxMn25Nes2ew8PDGTVqlM8EXkZGhjr0I0kSNpuNmpoaqqqqqKur63Su6+mswVcCz+12c9ddd/Hjjz+yceNGEhISeu3cGhpnOprI0/AZO3bsYPDgwRiNxpMKPJPJRHZ2NqGhoYwePbpTYq2joQGv4IuOju6yODKZTGRlZakXdJ1OB24HfstvRGo+0rb3zFILSDgufQcREt+l83RmDRERET4TFWazmczMTCIjI9sMzXTEsVXW1pmux5vU7coaoqKiGDlypE98+LxraC2ufLGGjIwM4uLiGD58eIdraJ3rWl1djSzL6u/AG7d2OvhS4CmKwqJFi9i4cSMbNmw4YRashsYvEU3kafgEIQTJycmUlJQwZ84c0tPTueCCCzqciKytrWXXrl3069ePIUOGnNJFRAiByWRqk+caGRlJXFwcMTExJ+3j8sakdbQG3f4vMWx9DlwOhF8wktMKQsE15mpcU+7u8lqPR319PdnZ2T6LagOPD19WVhaJiYldXkPrTNdjJ3U78zvw0tTURGZm5imtobtobm4mMzOThIQEn63BZDKRkZFBfHx8p8WVoihqrmtVVRVOp5OoqChVdHfV7sXXAu/+++/n66+/ZsOGDW0yrjU0NDxoIk/DZyiKwk8//cSyZctYtWoVlZWVzJ49m/T0dC688EJCQkJ4/vnniY+PZ9asWcTHd19FzOtDVllZiclkIiIiQhV8x24Dl5WVsXfv3uPHpAmBXLge/Z5PkRpKEIFRuEdcjHvUpe0jzE6RyspK9uzZw/Dhw3slf7UjvBmwQ4cOPe2KiRBC/R1UVVWpvwPvtu7xegy9YnvQoEEMHDjwtNZwqniFbv/+/Rk0aJBPBV5iYuJpf/HxCj6TyURYWJgquk9mQeNrgffwww+zcuVKNmzYwNChQ3vt3BoaPyc0kadxRqAoCpmZmSxfvpwVK1ZQXFzMyJEjOXToEP/5z3+YO3duj11ErFarKviampoICwtTBV9ZWRklJSUkJycTFRV14gcSAhQnyAbPIEY3UVJSwoEDBxgzZgyxsbHd9rhdwSt0eyoD1mq1qmKjoaGBkJCQNpm6cNTsOSkpySeZxHC0muo1nPYFzc3NZGRk0L9/fwYPHtxtj+vNNfb68QUGBqqCLzQ0tM3fn68F3qOPPsoHH3zAxo0bSUpK6rVza2j83NBEnsYZR2NjI/Pnzyc/P5/+/fuze/duzj33XBYuXMj8+fOJiIjosYuK90JXWVlJfb1nStSb9drb5rre9Iby8nJSUlIICwvr1fN7KSoqorCwsHNCtxtwOByq4POa/wYGBlJbW8uYMWN6RGR2Bm8lc/jw4fTt2/Pefx3R2NhIZmYmAwcO7NHtSafTqfbx1dTUqMMzMTEx+Pv7k5mZ6ROBJ4Tgqaee4s0332T9+vWMHj26186tofFzRBN5GmcUFouFyZMnk5CQwCeffEJoaCj79u1j2bJlrFixgtzcXGbOnMnChQu5+OKLiYmJ6faLjNPpJCcnB6fTSXx8PHV1ddTV1REcHKxWl3rak87tdqvZpykpKT6JMmodEZaSkuKTaCiXy0V+fj7l5eVIkoTBYFCrS73hh+ilqqqK3bt3M2rUqG5tG+gKDQ0NZGVl9XoV8diYO7vdTmBgIIMGDepSL+XpIoTgH//4By+++CLr169n3LhxvXJeDY2fM5rI0zjj+Pzzz5k7d2676VchBAcPHlQFX1ZWFtOmTWPhwoUsWLCA+Pj40xZ8FouFrKws1fPMO3nodDrVi1xtbS0BAQHExsYSFxfXYZ7u6eD1n/Oa+55K9unpoigKubm5NDY2+iwizGt6ffjwYVJSUggJCaGurk41//VO6nr9EHvKI6+8vJy9e/f6dLu8vr6erKwshg0b5rOeTIvFwo4dO4iKiiIgIIDq6mpMJhPh4eGq8A4ICOiRcwsh+Ne//sWzzz7LmjVrmDBhQo+cR0Pjfw1N5Gn8LBFCUFxczPLly1m5ciU//vgjkyZNYuHChSxcuJB+/fp1WXg1NDSQnZ1NfHz8ce0owFNd8nqQ1dTUYDQaVcF3bO9SV7FarWRlZREQENDWf64X8RotOxwOUlJSfJKcIIQgPz+fqqoqUlNT21VOvZO63sENu91OdHS0uqXYXdWlI0eOsH//fsaNG9crW9UdUVdXR3Z2tk+3iY/Xg+ftpayurqa+vp6goCBVeIeEhHTLlx8hBK+++iqPP/4433zzDVOmTDntx/y54/UVPdltGhqayNP42SOEoLS0lBUrVrBixQq2bt3K+PHjSU9PZ+HChZ2agKysrCQ3N7fLk6Ots0Srq6vR6XRt4tW6cpHz2nLExMQwYsQIn3xgexMk9Hq9z4yWW1cR09LSTlodOt6krre6dKppIN5exJSUFJ9loNbW1pKTk8OIESN8ZvLb2SELp9NJTU2N2sen1+tP2wRbCMFbb73FI488wpdffslZZ511uk/nZ09rMbd7927sdjvJyck+qfhrnPloIk/jfwohBJWVlaxatYrly5ezadMmRo0axcKFC0lPT29XofNWBA8dOsTYsWOJiYk55XMriqJuJ1ZVVSFJEjExMcTFxZ30Iuf1Ahw4cCADBw70iS2H1WolMzOTkJAQnyVIuN3uNnFtp1JF9E5LV1VV0djY2OGk7olovU2cmprqk15EODpNPHLkSJ/1AZ7qFG1rE+zq6mrcbncbP77OVFqFECxdupT777+fzz//nLPPPvs0n03nWLJkCc8++yzl5eWMHj2aF154gRkzZnR43y1btvDAAw+wb98+LBYLAwYM4Pbbb+eee+7p8XX+5S9/4ZVXXkGn0xEQEMC7777LWWed5ZPPDo0zF03kafzPIoSgrq5OFXzfffcdw4YNY8GCBVxyySUMGTKEu+++m6lTp3LFFVd068XcazrrFRtut1sVfMemDHjtSUaOHOmzao23ihgXF0dSUpJPLhTeXkSA8ePHd8uWa+tJ3dra2hPagoDnPVNQUEB5eTlpaWk9PmBzPLyDHmPGjPFZDmt32aQIIWhublYFn9lsPqknohCCjz76iEWLFrFq1SrOP//80306neLjjz/mhhtuYMmSJUyfPp3XXnuNN998k7y8vA4r/FlZWezbt4/k5GSCgoLYsmULt99+O88//zy33XZbt65NCKH+DjZu3MjNN9/MSy+9REREBC+99BJfffUV7777LgsWLNC2bTVUNJGn8YvA28O1evVqli9fzrfffktUVBSyLPP8888zZ86cHvtgbN0/VllZidPpJDo6mtjYWMxmc+d9+HoIr8GwL6uI3jxePz+/HutFPLaX0mAwqEIjPDwcSZLYu3cvtbW1pKWl+WTYBKCiooLc3FzGjh3rs0GPnvTBO9YTMTg4WI1YCwsLQ5Zlli9fzm9+8xs++eQTLrroom4798mYPHkyqampvPLKK+ptI0eOJD09naeffrpTj3HppZcSFBTE0qVLe2SNy5YtU3cMHnnkEfX2W265hY8//pj33nuPhQsX+qSfV+PMQxN5Gr84jhw5ol44hg4dypo1a4iNjVUrfGlpaT0q+Jqbm6msrOTIkSO4XC4iIiJITEzs9DZWd+LtRfSlwbB3m9ibS9wbVYjWW+veSV29Xo+iKEyYMMEnljVwdJL3dFsHTofeNDr29vFVVVXxySef8N///pe0tDTWr1/PBx98wGWXXdZj5z4Wh8NBYGAgn376KZdccol6+6JFi8jOzmbTpk0nfYysrCzmzp3LE088wf/93/91+xqdTifTpk0jIyOD6667rp2QvPPOO1m6dCn/+te/uPHGG7WKnoYm8jR+WdjtdkaMGMH555/PkiVLMBgMmM1mvv76a1asWMGXX35JWFgYCxYsID09ncmTJ3f7N2Jv35nFYiEpKUmt8pnN5jZZrj3dSH348GEKCgp8ag1iMpnIzMwkNjbWZ9vEbrebzMxMzGYzOp0Oh8OhVlp7U3iXlZWxb98+n07yegVeXFzcCSfMewKz2cwLL7zARx99RF1dHQAXXXQRl156aa+IvbKyMhITE9m6dSvTpk1Tb3/qqad49913yc/PP+6xffv2pbq6GpfLxaOPPsqf/vSnbl+fd7u2oaGB2267jQ0bNvDFF18wefLkNve76aabKCkpYf369d2+Bo2fH5rI0/jF4e116ugCZrVaWbt2LcuXL+fzzz/H39+fiy++mPT0dKZPn37a06be6VVZltv1nVksFiorK6mqqqK5uVmdEI2Nje1WGxPvYEFJSYlPJ0e9GbD9+vVj8ODBPhN4XuPr1NRU9Ho9JpNJ7aX09o+d7qTuyfBatYwfP57IyMgeOcfJ8KXAA1i3bh3XXnstb7zxBldddRU7duzgs88+o7y8nLfffrvHz+8Vedu2bWPq1Knq7U8++SRLly5l3759xz22sLAQk8nEjz/+yIMPPsjLL7/MNddcc1rrad2Dd+x/m81mLrvsMnbv3s3KlSuZNGlSm2O9E7jHPobGLw9N5GloHAeHw8F3333H8uXL+eyzz5AkiXnz5nHJJZcwc+bMLlfaLBaLui15sunVYydEvcHxsbGxp2U4K4Rg79691NTUdOg/11t4vd+6alnTnbhcLrKysgBISUnpUMBbLBa1f6yxsZHQ0FC1j6+7tnRLSko4ePAg48ePJyIiolses6v4WuBt2rSJK6+8kn//+9/ccMMNPhEm3bFdC/DEE0+wdOnSE1b+OoNXoH377besX7+ew4cPc80116hG8Xa7ncsuu4yMjAxWrFjRRpi2Pl7jl422Ya+hcRyMRiNz587lzTffpLy8nA8//BA/Pz9uv/12Bg8ezO23387XX3+N3W4/6WM1Njayfft2YmNjGTt27El7ZQICAhgwYAATJ05kxowZ9OnTh5qaGrZu3cpPP/1EYWEhZrO5S8/Hu03c0NDAxIkTfTo5mp2dzYgRI3wm8BwOBxkZGeh0OrWC1xGBgYFtfg8JCQk0NDTwww8/sG3bNg4cOEBTUxOn+l25uLiYgwcPkpKS8osVeFu3buWqq67i+eef95nAA8/fe1paGmvXrm1z+9q1a9ts354MIUSnPhNOhiRJfPzxx1xzzTUcPHiQoKAgFi5cqNq7+Pn5sXLlSqZPn8706dPJyMhod7yGhlbJ09DoIm63my1btrBs2TJWrVpFc3Mzc+bMIT09nfPPP7/dVGZVVRV79uzplqrVsZYgQUFBatpGUFDQCY1qs7OzEUIwfvx4nxmnlpaWkp+f79M+QLvdTmZmJoGBgZ0S3B1xskndzjxmYWEhxcXFPvXi87XA++mnn0hPT+epp57izjvv9Lkw8VqovPrqq0ydOpXXX3+dN954g9zcXAYMGMBDDz1EaWkp7733HgD//ve/6d+/PyNGjAA8vnmLFy/mt7/9LU888cRprWX79u1ccsklPPXUU9x4443U1dXRp08fFEXhrrvu4sEHHyQ+Ph63283999/Po48+6rP3kcaZiybyNDROA0VR+PHHH1XBV11dzezZs0lPT+fCCy/klVdeoaCggMcff7zb/c5aTybW1NTg7++vCr7WkVI2m42srCz8/f19FpUGRxMkxo0b57O+M6vVSkZGBuHh4YwaNapbpg8VRaG2tlYV34Aq+I71RIS2ZstpaWmEhISc9hpOBV8LvIyMDBYsWMBf/vIXFi1a5HOB52XJkiX8/e9/p7y8nDFjxvD8888zc+ZMwDPUUFRUxMaNGwF46aWXeO211ygsLESv1zNkyBBuvfVWbr/99tN6bymKwrJly9izZw+PPfYYBw8eZObMmdx6660kJSVx/fXX8+CDD3LbbbcxYMAA9TiXy+WTlBqNMxdN5GlodBOKopCRkcHy5ctZvnw5lZWVKIrCokWLuPvuu0871/ZEuN1uVfBVV1djMBiIjY0lNDSUgoICoqKiGDlypE8sFYQQHDx4kCNHjvi0amU2m8nMzCQ6OpoRI0b0yO9CCNHGBNvpdKoT09HR0ej1eg4ePEhpaalPzZZ9LfBycnKYN28eDz74IPfff/8ZI/B8Tes+ukOHDtHU1MTIkSNZuHAhAwcO5OWXX8ZqtZKcnExxcTEPPPAATz31lPb6aRwXTeRpaHQzDoeDm2++mfXr15Oens6mTZs4cOAA5513HgsWLGD+/PldzrXtCm63m7q6Oo4cOUJNTQ06nY74+Hji4uI6vZXYXXgHPWpra0lNTfWZ/5zJZCIjI4P4+Pge937zIoRoN6nr5+eH0+n8Rffg5ebmMnfuXBYtWsQjjzyiCRSOTsM6HI52rRTV1dXMnTuXRx55hPT0dBobG3n00UeZOXMmkyZN8pm/pcbPA03kaWh0M3fffTc//PADX375JX369FGFzrJly1i5ciW5ubnMnDmT9PR0Lr74YqKjo7v9QldTU8OuXbsYMmQIwcHBVFZWUl1djRBCndKNjIzsUcGnKAp79uyhubmZ1NTU05oKPh28Vi39+/dn0KBBPhEVQghyc3Oprq4mICAAk8lEaGio+rvorXQNXwu8ffv2MXfuXG677TYee+wxTeBxVODt2LGDZ599loaGBiRJ4m9/+xsjR46krKyMcePG8ec//5mLL76Yt99+m88//5yMjAwCAgJwu91auoXGcdFEnoZGN1NeXk5wcHCHvVZCCA4cOKAKvqysLKZNm0Z6ejoLFiygT58+p33h82bhjh49mj59+rQ5d0NDg+rF583TjY2NJSoqqlsvFF7/OYfDQWpqqs8GPerr68nOzmbw4MFtepd6k9bVzAkTJhAQEIDdbld7+Orq6ggKClJ/F637KbsTXwu8goIC5s6dy/XXX8/f/vY3LY2hFRkZGZxzzjncdNNNzJw5kzfeeIMdO3awfv16xo8fz0svvcSiRYsYPHgwFouFNWvWMGbMGF8vW+NngCbyNDR8hBCC4uJili9fzooVK/jpp5+YPHkyCxcuZOHChfTt27fLF+KioiIOHTp00tQEIQRNTU2q4Ds25eF0mredTmcbw2dfNYLX1taSk5PD8OHD6du3r0/WIIQgLy+P+vp60tLSOqxmegdoqqur1Uldr/lyd23r+1rgFRYWMmfOHC677DL++c9/agKvBSEETqeTK664ggEDBvCvf/0Lm83G1KlTGTFiBO+//7765Wvnzp04HA4GDhxIQkKCVsHT6BSayNPQOAMQQlBaWsqKFStYvnw5W7duJTU1lfT0dLXp+kQXZiEEBQUFlJWVdXm4wds75hV8Vqu1TbxaV2K9vPYkAQEBjB071mcXoaqqKnbv3s2oUaOIj4/3yRoURSE3N5empibS0tI6lZbh7af0DtDAiSd1O4PFYiEjI4PY2FifCLySkhIuvPBC5s2bx8svv/yLFXjHE2Uul4uZM2fyz3/+kylTpjBy5EhGjx7Nf//7X4xGIx988AHz588nLCxMPca7xauhcTI0kaehcYYhhKCiooJVq1axfPlyNm3axJgxY1i4cCHp6entBgcURSEvL4+GhgZSUlJOe7ih9bCAyWQiMjJS7R070barN9GjO+1JToXy8nLy8vIYO3asz7z4vP2IJpOJtLS0U4ql62hSNzo6mpiYmE5n6vpa4JWVlXHhhRdy7rnn8tprr/3ihYmiKFx66aXceeedzJ49W739/PPPZ+LEiXz33XckJCSwdOlSQkJCMJvNXHvttVxwwQXcfffdPly5xs8VTeRpaJzBCCGora3ls88+Y9myZaxfv57hw4ezYMECLrnkEuLj47npppu4/vrrWbBgQbdm3IJHJHhFRlNTE+Hh4arga12Zam5uJjMzkz59+vhETHjxZsCebLu6J1EUhd27d2OxWEhLS+uWfkQhBM3NzWqFz2w2q+I7Jiamw9+7rwVeRUUFc+fOZcqUKbz11lva1iJw33338c9//pPo6GjeeecdLrroIgCee+45/vGPfxAbG8uOHTvU98zzzz/Pyy+/zOeff86oUaN8uXSNnymayNPocZ5++mkefvhhFi1axAsvvAB4Llp//etfef3116mvr2fy5Mn8+9//ZvTo0b5d7BmMt7KzevVqVqxYwbfffktYWBhRUVG88MILTJs2rUcrJTabTRV8DQ0N6nRoQEAAeXl5DBgwwGfTq+CJCDt06JBPM2C90XF2u520tLQubXV3hWPFd1hYmLqtGxgY6HOBV11dzUUXXURycjJLly7VDHpb+Omnn3jooYcAT5zbBx98wOWXX05lZSWLFy8mPz+fiRMnkpqaSm5uLv/5z39YtWoVF1xwgZZFq3FKaCJPo0fZsWMHV155JaGhoZxzzjmqyHvmmWd48skneeeddxg+fDhPPPEEmzdvJj8/32cJAD8nioqKuOCCC4iKiiIxMZFvv/2W2NhYFi5cyCWXXEJqamqPCj6Hw0FVVRVHjhyhubkZPz8/+vXrR2xsbK974bVOkPCl2bJ3otjlcpGSktJjAu9Y7Ha7WuGrq6tTp3djYmIYPXp0r2+R1tbWMm/ePIYNG8ZHH33Ua6/Dz4GysjIuu+wyLr30UmRZ5oEHHuC9997j2muvpaqqijfeeINvv/2Wuro6xowZw+23384555yj9eBpnDKayNPoMUwmE6mpqSxZsoQnnniC8ePH88ILLyCEICEhgcWLF/PAAw8AngtVXFwczzzzDLfffruPV35mYzabGTFiBAsXLuTFF19Ep9NhNpv5+uuvWb58OV9++SUREREsWLCAhQsXMnny5B7ZKqusrCQ3N5dhw4ah0+morKxURUZcXByxsbEEBwf3aPXBO3BSXl7u0wQJt9tNVlYWQghSUlJ8VrlqamoiMzMTvV6vGuu2ztTt6UpQQ0MD8+fPp2/fvixbtsxn1jm+5kSi7NNPP+Whhx7i008/ZdmyZTzzzDO8+eab3HTTTepxVqsVg8GAXq/XKngap4VWQ9foMe666y7mzZvH+eef3yasu7CwkIqKijaNx35+fsyaNYtt27ZpIu8kBAUF8dlnn5GSkqJ++AcFBXH55Zdz+eWXY7VaWbNmDcuXL+fKK6/E39+fBQsWkJ6ezrRp07pFgHh738aOHUtMTAwACQkJuFwuampqqKyspKioCD8/P1XwdXesmxCCffv2UVNTw4QJE3yWpuFyucjKykKSJJ8KPIvFQk5ODvHx8QwfPhxFUdRJ3ZycHCRJIiYmhpiYGKKiorq9MtTU1ER6ejpxcXF8+umnv1iBB6iv7Y033sj06dMZOXIkM2bMAOCcc84hOTmZQ4cO8eSTT6IoCrfccgvgycYFCAgIwFt/0QSexumgiTyNHuGjjz4iMzOTHTt2tPtZRUUFAHFxcW1uj4uLo7i4uFfW93MnNTX1uD8LCAhQvfbsdjvfffcdy5cv5/rrr0eWZebPn88ll1zCzJkzT2krrbCwkKKiog6jufR6PX369KFPnz643W5qa2uprKxUq0veoY3TrSp5J4obGxtVg2Ff4PUE1Ol0jB8/3mfDBR314Ol0OlXUKYqiTuru27dPndTtDl9E8FTtL730UkJDQ1mxYkW3DwD9HPnnP//J0qVL+emnnwgPD2fAgAHcc889pKSkcO655/Lwww8zb948nn76aQIDA7n55puxWCzceeedgCbuNLoHTeRpdDuHDx9m0aJFrFmz5oTeYMd+iGnbEt2Pn58fF110ERdddBGvvvoqmzZtYtmyZdx66604nU7mzZtHeno655xzzkkvzK23RidMmHDS3kmdTqeKOkVRqK2tbVNV8v4sIiKiS1Wl1tOrEyZM8JmgcDqdZGZmYjQaSU5OPqME3rHIskxkZCSRkZEkJSWpk7qHDh1iz549J53UPRFms5nLL78cg8HAqlWrfCa4zzSuv/56Nm7cyJYtW3j88cd5//33efzxx6msrOQPf/gDOp2OFStWcO211/LHP/4RRVGIjo729bI1/sfQevI0up1Vq1ZxySWXtLnoud1uJElClmXy8/MZOnQomZmZpKSkqPdZuHAh4eHhvPvuu75Y9i8Kt9vN999/z/Lly1m5ciUmk4m5c+eSnp7O+eef3+5CrSgKe/fupa6ujrS0tNPKWvVWlbzmy0KINvFqJxJ83uEGp9NJSkqKz7YEHQ4HmZmZ+Pv7k5yc7LOm+O6YojWbzWrEmndS1yvATybYrFYrV155JTabjW+++aZXh6aWLFnCs88+S3l5OaNHj+aFF15Qt0SPZcWKFbzyyitkZ2djt9sZPXo0jz76KBdeeGGPrrG+vp709HRMJhPvvPMOQUFBfPDBByxfvpxdu3bx3HPPce+99/boGjR+2WgiT6PbaW5ubrft+utf/5oRI0bwwAMPMHr0aBISErjnnnv4wx/+AHgumrGxsdrghQ9wu938+OOPquCrqanhwgsvJD09ndmzZ6PT6Vi0aBGXXXYZs2bN6lRyQ2cRQtDY2KgKPpfL1WYbsfUXBW/vG+DT3jdvqkdgYCBjx479WQu8Y7HZbKrgq6+vJygoSBV8xw7R2O12rrnmGurr61mzZk2bRIae5uOPP+aGG25gyZIlTJ8+nddee40333yTvLw8+vfv3+7+ixcvJiEhgXPOOYfw8HDefvttnnvuOX766ac2XzR7gubmZubPn09JSQnLly8nNTWVoqIijhw5wllnndWj59bQ0ESeRq9w9tlnq9O14LFQefrpp3n77bcZNmwYTz31FBs3buy0hUppaSkPPPAAX3/9NVarleHDh/Of//yHtLQ0QPPhO1UURSEjI4Nly5axcuVKDh8+TEJCArIss3z5coYOHdpj5/bm6Xr932w2myr4wsPD2bVrFwaDgXHjxvlsa9Rut5ORkUFISIhP7Em89IYPnjdTt6qqipqaGvz8/LDZbCiKwllnncWvf/1rSktLWbduHZGRkd1+/hMxefJkUlNTeeWVV9TbRo4cSXp6Ok8//XSnHmP06NFcddVV/PnPf+6pZaqYzWYuu+wycnJy+Oyzz5g0aZL6M61NRaMn0XryNHzCH/7wB6xWK3feeacqwtasWdMpgVdfX8/06dM555xz+Prrr4mNjeXgwYOEh4er9/n73//OP//5zzY+fBdccIHmw3cSZFlm4sSJTJw4kfvuu49zzz0Xs9mMv78/kyZN4rzzzmPBggXMnz+/2y05JEkiLCyMsLAwhg4dqsarHTp0CIvFgtFoJDExEUVRfCLybDYbGRkZhIWFMXr0aJ9dmHvL6NhgMBAfH098fLw6RLN06VKeffZZdbBjyZIlvT7V7HA4yMjI4MEHH2xz++zZs9m2bVunHkNRFJqbm7tNnB5rmXKscAsKCmLlypVceeWVXHrppXz88cdMnz4d0AYsNHoWrZKn8bPjwQcfZOvWrXz//fcd/lzz4Tt9GhoamD59OiNGjFCD0vPy8tQKX15eHrNmzSI9PZ358+cTHR3dIxcrr7AKDAwkLCxMzdONiIggLi7ulAYFTgWr1UpGRgaRkZGMHDnyf17gHQ+Xy8Wtt97K3r17mTRpEmvWrKGxsZGrrrqK119/vVfWUFZWRmJiIlu3bmXatGnq7U899RTvvvsu+fn5J32MZ599lr/97W/s3bu3W/ON16xZwwUXXHDc34vD4eDyyy/nyy+/pKSkhMTExG47t4ZGR2gW2ho/O1avXs2ECRO44ooriI2NJSUlhTfeeEP9+cl8+DROTlhYGA899BAff/wxfn5+SJLE6NGj+ctf/kJWVhZ79uzhnHPO4Z133mHo0KHMmzeP119/nYqKCrrre6PFYmHHjh1EREQwfvx4Bg8ezJQpU5g+fTrR0dGUlZXx/fffs2PHDkpKSrDZbN1y3o7WsXPnTqKjo3/RAs/tdnPXXXeRnZ3Nt99+y5tvvklxcTHfffcd55xzTq+uBU59Ov/DDz/k0Ucf5eOPP+5Wgff888/zwAMPqGvo6O/AaDSyfPlyVqxYoQk8jV5Bq+Rp/OzwNv7fe++9XHHFFWzfvp3Fixfz2muv8atf/Ypt27Yxffp0SktLSUhIUI+77bbbKC4u5ttvv/XV0v/nEEJQVFSkXri2b9/OlClTVJ++xMTEUxIjJpOJjIwM4uPjGTZs2HEfwzsoUFlZSUNDAyEhIar58ulMAHsxm81kZGQQFxfnE2HlxdcCT1EUfve737F582Y2bNhAv379evX8rXE4HAQGBvLpp59yySWXqLcvWrSI7OxsNm3adNxjP/74Y37961/z6aefMm/evG5dV1FREePGjePpp59Wve5OhhZXptHTaO8ujZ8diqKQmprKU089RUpKCrfffju33nprmyZs0Hz4egNJkhg0aBD33XcfW7dupbCwkCuuuIIvvviCUaNGce655/Liiy9SVFTU6QpfU1MTO3fupG/fvicUeOAR/P369WPChAnMnDmTxMRE6urq2LZtGz/88AOHDh3CZDKd0nMzmUzs3LlTTZD4JQu8++67jw0bNrBu3TqfCjzwVMPS0tJYu3Ztm9vXrl3bZvv2WD788ENuuukm/vvf/562wHO73W3+2+l0MnDgQO6++27Wr19PU1NTp97vmsDT6Gm0d5jGz474+HhGjRrV5raRI0dSUlICQJ8+fYCjyRpeqqqq2qVsaHQfkiTRr18/Fi1axMaNGzl8+DA33ngj69atY9y4ccyYMYNnn32WgoKC414AGxoayMjIYODAgQwZMqRLgsZoNNK3b19SU1OZNWsWAwYMoKmpiZ9++olt27Zx4MCBTl98m5ubVaE5dOjQX7TAe+ihh/jyyy9Zt24dAwcO7NXzH497772XN998k7feeou9e/dyzz33UFJSwh133AHAQw89xK9+9Sv1/h9++CG/+tWv+Mc//sGUKVOoqKigoqKCxsbGUzq/d/Bn165dAGpyzIwZM/j222/JyMjQvlBqnBFoIk/jZ8f06dPbNVfv37+fAQMGADBo0CD69OnT5pu+w+Fg06ZNJ/ymr9F9SJJEfHw8d955J+vWraOsrIw777yTH374gUmTJjF16lSeeuop8vLyVNH11VdfsXHjRoYNG3baYsJgMJCQkMD48eOZNWsWgwcPVnvrtm7dyv79+2loaOhQ8DU1NZGRkUH//v27LDS7kzNB4D366KMsX76cdevWMWTIkF49/4m46qqreOGFF3jssccYP348mzdv5quvvlI/A8rLy9UvfQCvvfYaLpeLu+66S50Yjo+PZ9GiRZ0+pxACl8ul/vfSpUuZNGkSN998M6tXr0YIwZw5c7jhhht48sknqa2t7b4nrKFximg9eRo/O3bs2MG0adP461//ypVXXsn27du59dZbef3117nuuuuA0/fhc7lcPProo3zwwQdUVFQQHx/PTTfdxCOPPKJusWhefF1HCEF9fT2rV69mxYoVrFmzhoEDBzJhwgSWL1/Oiy++yPXXX99j5/dagVRVVVFdXd0mei0iIoKmpiYyMzMZNGiQT6tWvhZ4Qgieeuop3nzzTTZs2NCucv5LpKioSH1PvPHGG4SHhxMdHc3jjz+OyWTCZrPx2GOPkZeXx+bNm/n73/9OcnIybrfbZ76OGhqayNP4WfLFF1/w0EMPUVBQwKBBg7j33nu59dZb1Z97Bdhrr73WRoCNGTOmU4//5JNP8vzzz/Puu+8yevRodu7cya9//WueeOIJ9dv/M888w5NPPtnGi2/z5s2aF18XaGxs5I9//COvvfYagwcPxuVysXDhQtLT00lNTe3RniVFUairq1PNl4UQuN1uEhMTSUpK+p82Oj4RQgiee+45XnrpJdavX09ycnKvnv9M5Mcff2TatGl89dVXLFu2jLVr17Jjxw5iY2Mxm80UFRXxwgsvkJ+fT1NTE7t27eLaa6/l/fff9/XSNX7haCJPQ6MD5s+fT1xcHP/5z3/U2y677DICAwNZunSp5sXXTbz55pvcc889LFu2jOnTp/P111+zfPlyvvrqKyIiIliwYAHp6elMmjSpR6shtbW1ZGdnExoaitVqxe12ExMTQ1xcHJGRkb1WiTkTBN6//vUvnn32WdauXasmyPzSKS4u5uWXX2bJkiUEBgZSVFREUFAQDoejTX7yrl27OHToEM899xw1NTW89957TJo0SRv60vAZWk+ehkYHnHXWWXz33Xfs378fgJycHLZs2cJFF10EaF583cXBgwf56quvuPDCCwkODuaKK67go48+oqKighdffJGGhgYuv/xyRowYwe9//3s2b97cpi+qO6itrSUnJ4cRI0YwceJEZsyYQUpKCkajkX379rFp0yZ27dpFZWVlu6nK7sQr8GJiYnwm8F599VX+/ve/8/XXX//iBd7ChQtZvHgxAAMGDCAhIQGr1YrVauXLL78EPMM+iqKo74vk5GTS09NZuXIlBoOBL774AtBSLTR8h1bJ09DoACEEDz/8MM888ww6nQ63282TTz7JQw89BKB58fUiNpuN7777juXLl7N69Wp0Oh3z58/nkksuYcaMGepk46lQU1PDrl27GDFiRJvfoxchBM3NzVRVVVFZWYnNZiMqKoq4uDiio6NP69ytaS3wkpKSfCLw/vOf//CnP/2Jr776So3c+iXz448/kpycrPoteoc5vvjiC1588UX+8Y9/cOutt6pVOq/nnfe/n376adatW8fq1at7PfpNQ8OLll2rodEBH3/8Me+//z7//e9/GT16NNnZ2SxevJiEhARuvPFG9X6aF1/P4+/vz7x585g3bx5Op5ONGzeybNky/u///g+n08n8+fNJT0/n7LPP7lLEWXV1Nbt27WL06NGq7c6xSJJEaGgooaGhDBkyBLPZTGVlJUVFReTm5hIZGanGq7XetusKZ4LAW7p0KY888girV6/WBF4LU6ZMAeDll1/mww8/ZOvWrcTHx9OnTx/cbje///3vURSF22+/HbfbzYMPPshVV13FhAkTAE/fcEREBAEBAb58Ghq/cLRKnoZGB/Tr148HH3yQu+66S73tiSee4P3332ffvn0cOnSIIUOGkJmZSUpKinqfhQsXEh4ezrvvvuuLZf+icLlcbNmyhWXLlrFq1SpMJhMXXXQR6enpnHfeeSe8uFZWVrJnzx7GjBlzyt6JFouFyspKqqqqaG5uJiIiQp3U7azYPBME3kcffcTixYtZtWoV5513Xq+e/0zk2C9qmzZt4oorrmDcuHF8++23yLLMkSNHeOONN3jmmWe47rrr2LNnD263m507dwKe9+aCBQt45513ujU6TUOjq2g9eRoaHWCxWNpNV+p0OhRFATQvvjMBvV7P2Wefzcsvv0xxcTFffPEFcXFx/OEPf2DgwIHceOONrFixArPZ3Oa4gwcPsmfPHpKTk0/LHDswMJBBgwYxefJkpk+fTkxMDBUVFWqebnFxMVar9bjH+1rgASxfvpxFixbxySefaAKvBe/v4T//+Q9vvPEGs2bN4vPPP+fAgQPMmjULl8tF3759ufvuu3nllVc4fPgwKSkpqsBzOp3o9Xq++uorTeBp+Bytkqeh0QE33XQT69at47XXXmP06NFkZWVx2223cfPNN/PMM88Ap+/Fp9EzKIrCzp07WbZsGStXrqSsrIwLLriAhQsXUl5ezosvvsiWLVt6LCDebrertiz19fWEhISoFT5vb5bVamXnzp0+FXirV6/mlltu4cMPP2TBggW9fv4zGavVym9/+1sqKyv55JNP8PPzIyMjg2uuuYbo6Gg2bdqkVmtb58+6XC70eq0LSuPMQRN5Ghod0NzczJ/+9CdWrlxJVVUVCQkJXHPNNfz5z39We6+66sW3efNmnn32WTIyMigvL2flypWkp6erP++MubLdbue+++7jww8/xGq1ct5557FkyRL69u3bo6/HzxVFUcjJyWHZsmW8/fbb1NTUqIJv3rx5hIeH96jAcjgcVFdXU1VVRW1tLUFBQURGRlJRUUFsbCwjRozwicD76quvuPHGG3nvvfe47LLLev38PwdWr17NjTfeyKpVq5g1axaKopCdnc11111HWFgY69atIzg4WL2/1o+rcSaiiTwNjV7i66+/ZuvWraSmpnLZZZe1E3mdMVf+zW9+w+eff84777xDVFQUv//976mrqyMjI0Nz1T8Br776Kn/4wx948cUXKS4uZuXKlezdu5ezzz6b9PR05s+fT1RUVI9epJ1OJ2VlZRw4cAAhBAEBAWqFLzQ0tNcEwrp167j22mt58803ufrqq3vlnD9Xfv3rX3PgwAFWr15NREQE4PHCO//885kzZw7vvfeej1eooXFiNJGnoeEDJElqI/I6Y67c2NhITEwMS5cu5aqrrgKgrKyMfv36qV5zGu3Zv38/U6ZM4YsvvlD7JYUQ7N+/n+XLl7NixQpycnI466yzSE9P5+KLLyYuLq7bRVfrLdqhQ4e2iVczGAzExsYSFxdHWFhYjwk+7xDBkiVLuOGGG7TKUys+//xzQkJCGD58uGqn89VXX/Hwww/z0ksvMWPGDPW+Bw8epF+/fqc8Ua2h0VtoIk9DwwccK/I6M627fv16zjvvPOrq6tSqAsC4ceNIT0/nr3/9a28/jZ8N9fX1bV6z1gghKCwsVAXfjh07mDp1KgsXLmTBggUkJiaethg6UQ+e2+1uE68my7Iq+MLDw7stXm3Lli1cfvnlPP/889x8882awGuF0+nkmmuuYfPmzYwdO5ZLL72U22+/Hb1ezyWXXEJ9fT0bN25sd5yWS6txpqNN12ponAFUVFQAtJv2jIuLU39WUVGB0WhsJ1Za30ejY44n8MAjuAcPHsz999/Ptm3bOHToEJdddhmrV69m1KhRnHfeebz44osUFRVxKt+JTzZkodPpiImJYfTo0cyaNYsxY8YghGD37t1s3ryZ3Nxcampq1MnuU+Gnn37iiiuu4G9/+5sm8DrAYDCwbNky3n//fWbMmMEDDzzAnDlz+Nvf/sa9995LQ0MDK1eubHecJvA0znQ0kaehcQZxKubKWsN39yFJEv3792fx4sVs2rSJkpISbrjhBtatW8e4ceOYOXMmzz33HAUFBZ0SfF2dopVlmaioKEaNGsXMmTMZN24cOp2OvLw8Nm3axJ49e6iqqupSvFpGRgaXXnopjz32GL/5zW969b2yZMkSBg0ahL+/P2lpaXz//ffHvW95eTnXXnstSUlJyLKsRor1BF7BXFpayv79+8nPzwdg9uzZPProo+zevZsJEyawYsUKLrjgAnbt2sWOHTtOSeRraPgSTeRpaJwBeBMXjq3IVVVVqdW9Pn364HA4qK+vP+59NLoPSZJISEjgrrvuYt26dZSVlXH77bezbds2Jk6cyNSpU3n66afZu3dvhxf/07VJkSSJiIgIRowYwYwZM0hNTcXPz4/9+/ereboVFRUnzPLNyclh4cKFPPzww/zud7/rVYH38ccfs3jxYv74xz+SlZXFjBkzmDt3LiUlJR3e3263ExMTwx//+EfGjRvXY+vyWp6sXbuWhQsXcu6553LLLbdw5513qvcZNGiQOvj0+OOPc/HFF7No0SLty5TGzw+hoaHR6wBi5cqV6n8riiL69OkjnnnmGfU2u90uwsLCxKuvviqEEKKhoUEYDAbx8ccfq/cpKysTsiyLb775ptfW/ktHURRRW1sr3nrrLTF//nzh5+cnRowYIR544AHx448/iubmZpGZmSl+/etfi507dwqTySTMZnO3/WMymURFRYXIyckRa9euFatXrxZbt24VBQUFoqGhQb3f9u3bRVRUlHj88ceFoii9/jpNmjRJ3HHHHW1uGzFihHjwwQdPeuysWbPEokWLemhlQmzZskWEhISIv//972Lv3r3in//8p5AkSVx55ZXqfRwOh/r/7Xa7EEIIp9PZY2vS0OgJtEqexi8SIcRp9TidCiaTiezsbLKzswEoLCwkOzubkpISJEli8eLFPPXUU6xcuZI9e/Zw0003ERgYyLXXXgtAWFgYt9xyC7///e/57rvvyMrK4vrrr2fs2LGcf/75bN68mYsvvpiEhAQkSWLVqlXquZ1OJw888ABjx44lKCiIhIQEfvWrX1FWVtZmjXa7nd/+9rdER0cTFBTEggULOHLkSG+9RD8LJEkiMjKSX//613z++edUVlbyxz/+kf3793PuuecyZswYZs+eTU1NDcOGDev26o8kSYSEhDB06FCmTZvGlClTCA0NpaSkhGeeeYZzzjmHv/zlL8yfP58777yTP/7xj71egXI4HGRkZDB79uw2t8+ePZtt27b16lqOpa6ujmeffZb777+f+++/n759+/LSSy9x/vnn88MPP6jDUAaDAYfDAaBO0WpGxxo/NzSRp/GLw+FwIEmSOrXYW4Jv586dpKSkqNOz9957LykpKfz5z38G4A9/+AOLFy/mzjvvZMKECZSWlrJmzZo26RnPP/886enpXHnllUyfPp3AwEA+//xzdDodZrOZcePG8fLLL7c7t8ViITMzkz/96U9kZmayYsUK9u/f3y7pYPHixaxcuZKPPvqILVu2YDKZmD9/fpd6wH5phIWFcf3117NixQq2b9+OxWIhNjaW9evXk5yczIMPPsiPP/7YY69hUFAQgwcPZsqUKVxzzTVMmDCBjz76iJqaGr7//nv+/e9/U1pa2iPnPh41NTW43e4TDhL1JqLVdnpkZKS6ddzc3MysWbOYNWsWq1at4qabbmL16tXMnDkTQLNI0fj54+NKooZGr/PAAw+IqVOniocfflgcPHjQ18vpEThmO7gjtm/fLgBRXFwshDi6HfzRRx+p9yktLdW2gztJYWGhGDBggLj77ruFoijCbDaLFStWiOuuu06Eh4eLxMREcccdd4hvvvlGNDY2dusWrvefPXv2iL59+4rFixeLkpIS8dJLL4mzzz5bREREtNl+7GlKS0sFILZt29bm9ieeeEIkJSWd9Pju3K51uVxCCCEqKytFfn5+m5+999574txzzxVHjhwRQgixdOlSMWXKFDFr1ixRVFTULefX0PAlWiVP4xdFdXU1+/btw2w288MPPzB69GhmzpzJli1bfL20XqexsRFJkggPDwc8U5hOp7PNFltCQgJjxozx+Rbbz4HAwEB+85vf8K9//QtJkggMDOSSSy7h/fffp7y8nFdffRW73c61117L8OHD+d3vfseGDRtwOp3dcv6SkhIuuugiFixYwD/+8Q/69evH3XffzYYNGzh8+DAGg6FbztMZoqOj0el0Jxwk6g28PnZ79uxh3rx5vPXWWxw+fFj9eUFBAUVFRWqOcUFBAdOnT+fLL79kwIABvd7SoaHR3WgiT+MXxY4dO6iqquLee+9l/fr1FBQUEBsby5NPPonVavX18noNm83Ggw8+yLXXXktoaCig+fCdLrGxsTzwwAMd9r/5+/szf/583nrrLSoqKnjvvffQ6XTcfPPNDBkyhDvvvJM1a9aoPWBdpaysjHnz5nHhhRfy0ksvtTNQDgoKOqXHPVWMRiNpaWmsXbu2ze1r165VU0d6A51OR2FhIWeffTazZs3izjvvpF+/furPL7jgAnQ6HbNnz+bWW2/l73//O9ddd536enWXEbWGhq/Q3sEavyh+/PFHZFlWLRr69u3LrFmz2Lp1aztHe0VR/id70ZxOJ1dffTWKorBkyZKT3l9oPnzdisFgYPbs2bz22muUlpaybNkygoKCuOuuuxg4cCC33norX3zxBTabrVOPV1FRwbx585gxYwavvPLKGSNM7r33Xt58803eeust9u7dyz333ENJSQl33HEHAA899BC/+tWv2hzjHUwymUxUV1eTnZ1NXl7eKZ1ftPTaLlmyhPPOO4/nnntOFXjev+vk5GT+9Kc/odfrqamp4bvvviMlJUWr4Gn8z6CNCmn8Yqirq2PPnj0MGzaM8ePHq7fr9XocDoe6ZdPQ0IDBYOj16kdv4HQ6ufLKKyksLGT9+vVqFQ/a+vC1ruZVVVX1avXll4Rer+fss8/m7LPP5l//+hfbtm1j+fLl3H///dTX1zNnzhwWLlzI7NmzO3w/VlVVMX/+fNLS0njzzTfPqASGq666itraWh577DHKy8sZM2YMX331FQMGDAA85sfHeua1jvTLyMjgv//9LwMGDKCoqKjL55ckCUmSKC4uVr+keP/tfZ1cLhc33HADN9xwAxaLhcDAQNVHT0PjfwEtu1bjF8O6dev43e/+v717j6o53/8H/ty1M5VMZ3ZiVEoZIdFkU9GFzVEujcqQ45ZzMohIRZaGONIxGPf7NY3JbTqKYh9yKEKoVDKlFLuLSii0dd3t1++Pfn2OrVxmvpHyfqzVWu3PbX/2qtbn1fvyfHshPz8fnp6ecHJywqNHjzBv3jzo6+vj2rVrCAsLw7Fjx5CWlob27dtj/vz5cHNzU4hOICIQEZSUlLhWrsrKSqipqbXgp1P0+tq4wP8KvHv37iEmJgba2toK5zx//hza2toIDQ2Fq6srgPoHsZ6eHsRiMRwcHD7mR/isyeVyJCQk4N///jciIiJQVFQEe3t7ODk5YdSoUejQoQOePn2KMWPGwNjYGEePHv2oY+5aA5lMBiLCjBkz8OTJE4jFYq6AIyK8ePEC69evh7OzM4RCIWuxZtok9u8K89m4evUqvvzySyxbtgwSiQT29vb44YcfYGNjgz179uDXX39FYGAghEIhwsLCMH78eOzZswenT5/mriGTyRrFrwBAfHw8zM3NER0d3SKfDXh7Dp9MJsP48eORmJiIw4cPo66uDsXFxSguLubGgb0rh6/B2/L4Xjd79mzweDxs3rxZYTvL43s7JSUlWFpa4ueff0ZWVhbi4uLQu3dvrF27Ft26dYOLiwtsbW1haGiII0eOsAIP4Fb+eHWIhYqKCmbNmoWzZ89i5cqV3N8tj8dDeHg4jh8/DnV1dW4bw7Q5LTSrl2E+qrKyMnJ1daW//e1vCttzc3OppqaGSkpKyNzcnExMTCgpKYnbv3jxYrKxsSGi+rT7FStWkKOjI5WVlVF+fr7Cte7evUtSqZSIqEVWGIiJiSEAjb6mT59ODx48aHIfAIqJieGuUVlZSfPmzSOBQEBqamrk6OhIeXl5Cu8jFotp6dKldOLEibdGtURERJCZmRnp6OjQpk2bFPZ5eHiQrq4unT9/nm7dukUikYjMzMy4uAumaXK5nNLS0mjWrFlkZGREVVVVLX1Ln4S6ujoiInr+/DlNnjyZnJ2dyc/Pj7KysoiIaNeuXaSiokJOTk7k5eVFvr6+pKqqSkePHm3J22aYD44Vecxn4cyZM9S3b1+u2Hh9eaKYmBhSVlYmFxcX6ty5M2lra9PMmTPJ09OTRowYQfn5+VReXk4jR44kPp9PS5YsIR6PR9OmTaP8/HwqKSkhov89bF7/vq16U5FXUFBAurq6dOfOHTIwMFAo8lgeH9OcGv4xqK6uph49epCjoyNNnDiR7OzsyMzMjNLS0oiIKD4+npycnEgkEtGUKVMoMjKSiFrmHzKG+VhYdy3zWejUqROsrKxga2sL4H/RCA1dO5mZmdDR0UF4eDhycnIQEhKC6upqiMViPHv2DLq6utxYtkmTJmHcuHGQSCRYvHgx4uPjYWNjg99++w1KSkpcFMurg7fb4izdN5HL5Zg2bRr8/PzQp0+fRvtZHh/TXIgIysrKkMlkuHbtGkaMGIGoqCgcO3YMQUFB0NfXx/jx45GQkAArKyscO3YMFy9exIEDB/Ddd9+19O0zzAfHZtcyn4UBAwZgwIAB3OuGAqxhlp2uri7kcjnEYjFGjx7NfVVUVODx48fg8Xg4c+YMNDU1sWvXLoWZjmfPnoWKigo3A3X16tUoLCzE7Nmzoa2tDUNDQ4VZjw3xDG11Bt/atWvB5/Ph5eXV5H6Wx8c0l4ZxdAsXLkRoaChsbGy4fba2tuDz+Vi3bh2mT5+Offv2wdraGoDicmVsLB7TlrXNpwzD/EFjxozBsGHDEBISgtTUVNTU1KCwsBAAYGBggBcvXiAqKgouLi5o3749t0pBUVEREhMT0b17d+jp6eHly5fIzs7GyZMnsXPnTjg4OKBr1644e/Ys915KSkpttsBLSkrCli1bEBIS8ocfnsRmNzJ/AhHBzMwMpqamSEhIwOPHj7l9gwYNgr+/P4yNjTFu3Dg8fvyY/Z4xn5W2+aRhmD+Ix+PB398fVVVVsLS0hIWFBZYuXYqwsDAAgEQiQXJyMhfe2lCkpaenIysri4sXSU5ORkpKCiwsLODl5YWEhASIRCL8/PPPKCgoQGBgIObMmYOkpKSW+aAfWFxcHEpKSqCvrw8+nw8+n4/c3FwsXLgQ3bp1A6CYx/eqj73kFdM6vT70gcfjwd3dHQsXLoSuri4mTJigkKtnYWGBJUuW4MiRI9DW1mYFHvNZYUUew/x/vXv3RmRkJMrKyhAQEABbW1sMHz4cABAREQENDQ2uS7ah+zUlJQWVlZUYPXo0AODatWvQ0NDA8uXL0b9/f2hqasLU1BQxMTFYunQp1NXV8ejRI0yaNAk3btx4473U1dU1mbpPn3is5bRp03D79m0uyiUlJQU6Ojrw8/PDuXPnAABCoRAqKioKS14VFRXhzp07LHSZeSuZTMb97YWFhSEkJISL8Bk7dixWrFgBJSUluLm54f79+9x5VlZW3N/yp/43xDDNiY3JY5jXqKmp4fvvv+dey+VyLkgYqH/Q8Pl8FBcXIzU1FT169EC3bt1QUVGB27dvQ09PTyG5PyMjA3379sXixYvRp08fEBGMjY1x8uRJWFpacseVlpYiNzcX5ubmTa5c0JDI39KkUimys7O51w15fAKBAPr6+tDS0lI4XkVFBV9//TV69uwJQDGPT0tLCwKBAIsWLWqUx8cwryIiLpRcJBKhoKAAfD4fOTk5GDVqFFatWgVHR0fweDxs374dkyZNQnBwcKPJP6wlj/mcsJY8hnkHJSUlBAUFYffu3dxrAEhNTUVcXByGDh0KoL5Vr6CgAP3794eqqiqA+i7Iu3fvwtHRkXvY8Hg8yOVy/OUvf+Hew9/fH66urhg/fjwEAgHmzZuHkpISrtWhuLgYY8eOxbp16z7Sp36zxMREmJubc4Wsr68vzM3NsXz58ve+xqZNm+Ds7AxXV1dYW1tDXV0dUVFRXHH7PoHLGRkZGDt2LDQ1NdGhQwdYWVkpLJPFApfblobizNPTE+Xl5bh+/Tpu3ryJW7duISMjA4sWLUJJSQnGjBkDDw8PKCsrIzk5uYXvmmFaFivyGOYPaijyTExMMHHiRLi4uACoXzatvLycK/oA4OLFi6itrVVo2UtLS0NlZSW6d+8OANi2bRvCwsIQEBCAxMREREZGIiEhAUePHgWPx0NKSgp2794NqVSK3r17f7wP+gZDhw7llnZ79SskJKTJ4yUSCby9vRW2qaqqYtu2bXj69CkqKioQFRXFLR4PAC9fvoSZmRm2b9/e5DVzcnJgY2ODXr16ITY2FqmpqQgICOCKawDw9vZGREQEjh07hitXrkAqlcLR0fGzirNpSxp+brm5uRg9ejS0tLSgrq4OU1NTREdHIykpCWvXrgUAODk5ITQ0FFOnTm3JW2aYltcS4XwM09bI5XI6cOAATZ48mSorK7ntM2fOJCcnJ8rJyeG2rVixgvr370/Z2dl09+5dGjRoEHXo0IFCQkLowYMHREQUHR1NOjo6JJPJ6PLly9SxY0fi8XhkbW1Nhw4d4gJgG4Jc6+rq2uxqEWgicHnixIk0derUN57DApdbr1fDiZOTkyk8PJyKioqIqD7weMCAATR//nzu2OrqaiIiCgwMJKFQSOXl5W+8HsN8blhLHsM0g4YZfocPH+Zak0pLSxEXF4cuXbrAyMiIO/bcuXMYOHAg9PX1kZaWhufPn2PixIk4cOAA+vXrB0tLS2zcuBE8Hg8ymQw9e/aEpaUlvv/+e9jZ2SEoKAhXrlzh3rdh0fWmxvG1RXK5HGfOnIGxsTEcHBzQqVMnWFpaKnTpssDl1quhW3bz5s2YM2cONm/eDLFYDKA+3+6HH37gJlzweDwu805JSQkCgQBffPFFk9djmM8RK/IY5gMRCAQ4ceIEZs+ezW37/fffkZmZCWtra6ioqEBdXR1FRUXYt28fLl++jLS0NLi5uaG2thYODg6Qy+WIj49HSUkJXFxcsHr1amRmZmLIkCF4+PAhtm3bhlGjRkEkEuGXX35BTU2Nwj0QUZOzdFuzkpISSKVSrFmzBiNHjkR0dDRcXFwwbtw4XLp0CQALXP4jdu7cCUNDQ6iqqkIoFCIuLu6tx1+6dAlCoRCqqqowMjLixqo2p/Xr1yMwMBArVqxAREQE3N3duX2Ojo6YMmUKfH19ERwcjNzcXCQlJWH//v2wsLCAiopKs98Pw7RWbHYtw3xAJiYmCq9LSkowePBgbqZply5dUFNTg8OHD2PKlCkwMDCAp6cnPD098fLlS6ipqeHq1atQU1ODlZUVd52cnBwsWLAA5eXlmDBhAp49e4a1a9ciOzsbq1at4o7j8XhcS4ZcLueWgWrNGopWJycn+Pj4AAC+/fZbXLt2Dbt378aQIUPeeC6xIFwFx48fh7e3N3bu3Alra2vs2bMHo0aNQnp6OvT19Rsd/+DBA4wePRozZ85EaGgorl69irlz50JbW1thRvr/xZUrV7B7924EBwdj5MiR3PaGn52uri68vLwgEAjg6emJr776Cl988QWGDh2KoKAghWMZ5rPXop3FDPOZqqur475fvXo1CYVCOnToEBUXF1NiYiI3hu/hw4f03Xff0YwZMxTOX7ZsGXXs2JEuXbrEbbtx4wbp6enR1atXiYjo9OnTtHDhQkpJSaGKioqP8Kk+DLw2Jq+6upr4fD6tWrVK4bjFixfT4MGDiYjowoULBIBKS0sVjunXrx8tX778g99za2FhYUEeHh4K23r16kVLlixp8vjFixdTr169FLbNnj2brKysmu2e9u7dS+bm5lRUVNRoPN3rr3NyciguLo4SExO5bW11bCrD/Bmsu5ZhWsCry5p5eHjAyckJS5cuhVAohLe3N27dugUAyMrKQmFhoUKenkQiwc2bN6GhoQEXFxd07doVnp6eaN++PaRSKbfkWnJyMg4dOoSgoCA4OTnByMgIqampje5FKpXi5MmTuHr1KoBPPyy2Xbt2GDhwIDIzMxW2Z2VlwcDAAAALXH4fNTU1SEpKUhi3CAD29vZvHLcYHx/f6HgHBwckJiZyv3f/V/Hx8QDqV0bh8XgKv48NrXMxMTFISUmBkZERbGxsIBQKAdS38rb2lmqGaU6syGOYFvbVV18hICAAeXl5iIuLQ0BAANdN9fXXX6OsrAydOnXijq+urkZBQQGWL1+Op0+fYsOGDSguLoa1tTXq6urA4/Hw8uVL3Lx5E3V1dbCwsMCmTZswd+5chZiSBg8ePMDKlStha2uLgwcPvrGb62MWf1KplFsxo+EeU1JSuBw8Pz8/HD9+HPv27UN2dja2b9+OqKgozJ07F4Bi4PKFCxeQnJyMqVOnNgpcflcen1Qqxbx586Cnpwc1NTX07t0bu3btUjimtebxPXnyBHV1dY2WknvbuMXi4uImj5fJZHjy5Emz3JeJiQny8/O5n/3rv491dXUICQnB6dOnG53bVteEZpg/i/1FMMwnxNDQEPb29tDQ0OBei0QiTJkyBXZ2digoKEDPnj3x7Nkzbu1XV1dXnDhxArm5ubhw4QIGDRqE5ORk5OfnY968efDz84OJiQkWLVoEgUDQ6D3v3buHsrIytG/fHl9++SWA+lU9AKC8vBxpaWkAPu4sxXcFLru4uGD37t1Yt24d+vbti/379+PEiROwsbHhrvGuwGXg3Xl8Pj4+OHv2LEJDQ5GRkQEfHx/Mnz8fp06d4o5p7Xl8r/9c6R3j2Zo6vqntf5ZQKMTTp0/x66+/KhSODe/z6NEjFBcXw9jYuFnej2HatJbsK2YY5v1IJBLas2cPPXz4kIiINmzYQP3796cbN24QEVFNTQ2XF0ZEtGrVKho0aBA3VunVMYCvkkql5OPjQ4aGhrR06VIKCgpS2P/TTz8Rj8cjDQ0NysvL+xAf7ZOBJvL4+vTpQ4GBgQrb+vfvT8uWLSOi1p3HV11dTcrKyhQeHq6w3cvLi+zs7Jo8x9bWlry8vBS2hYeHE5/Pp5qamma7t6CgIOLz+eTn50eZmZlEVD/WTiKRkKWlJTk7OzfbezFMW8Zm1zJMK2BgYIBZs2Zxr6dPn460tDSIRCKYmprCzMwMnTp1wsqVK7k1dLt27cqNVXpTN1ZhYSGio6MxZ84cVFRU4O7du9y+//znP9i4cSP69esHImrU1UufwQxGGxsbREZGwt3dHTo6OoiNjUVWVha2bNkC4N15fA4ODi116+/Url07CIVCnD9/nlu1BQDOnz8PJyenJs8ZNGgQoqKiFLZFR0djwIABzRpd4uvri9raWgQGBuLUqVMwMzODVCpFSUkJNDU1ERERAaC+65aNwWOYN2PdtQzTCmlpaeHgwYPIy8vDP/7xDy5iRVlZGdevX0dBQQE3WeNtOXkZGRmQSCRwc3NDfn4+N3Hh1KlT2Lt3L0QiEbp3745hw4Y1ulZDgddauiX/jK1bt8LExAR6enpo164dRo4ciZ07d3Ldwq09j8/X1xf79+9HcHAw1x2dl5cHDw8PAPVrKru5uXHHe3h4IDc3F76+vsjIyEBwcDAOHDiARYsWNet9qamp4Z///CfOnj2LwYMHo7CwELq6upgxYwYuXLgAoH5IASvwGObtWEsew7RiWlpa3AO5QWlpKYhIIVevKRUVFbh8+TL09PTQuXNnGBoaIjc3F1VVVfjxxx/h5uYGbW1trFmzBgsWLABQ3yJYVlaG69evQyAQwNLSsk0/aLdu3Yrr168jMjISBgYGuHz5MubOnYsuXbooTOB4XWtp5Zw4cSKePn2KwMBAFBUVwdTUFGKxmCv2i4qKuMkuQP0YUbFYDB8fH+zYsQM6OjrYunVrs2Xkvc7e3r7RbF6g/h8LPp89vhjmnVq2t5hhmA/hfcZHZWdnk1AoJG9vbyIi2rhxI33zzTcUFBREAwcOpOrqavL391fIRROLxfTNN9/QsGHDSEtLiwwMDOjo0aNNXl8mk7WqzDK8NiavoqKCVFRU6PTp0wrHzZgxgxwcHIiI5fF9DGztWYb581h3LcO0Qe8zPio9PR0PHjzA9OnTAdTPNM3JyUFGRgZ27NiBly9fIi4uDnZ2dgCA2NhY/Pjjj/Dy8sKFCxdQUlICHx8frF+/HkVFRdx1S0tLAQDKysqtupWvtrYWtbW1jcYzKisrc93WLI/vw2sNLaIM86li7d0M8xmqra1FQkICZDIZvv32WwD1kzlKS0vh7u4OU1NTREVFQSKRICAgAAAQEhKC1NRUHD16FGpqapgwYQJmz54NsViMU6dOwcPDA8+fP8e//vUvxMTEwNDQEHPmzGmyW1Mul38SmWZSqRTZ2dnc64Y8PoFAAH19fQwZMgR+fn5QU1ODgYEBLl26hEOHDmHjxo0AFPP4tLS0IBAIsGjRokZ5fAzDMC2BR/SJx9szDPPBZGVlwdjYGDKZTGGMU1VVFdasWYPffvsN6enpAOpnjU6YMAFaWlo4deoUsrKy0KtXLyQlJWHjxo3w9vaGRCJBcnIy2rVrh6ioKFy8eBELFiyAp6dnk+/f0uvpxsbGQiQSNdo+ffp0hISEoLi4GP7+/oiOjkZpaSk3y9nHx4drYaqqqoKfnx+OHDmCyspKDB8+HDt37mwyeJphGOZjYkUewzCchha2zMxMTJ48GX379kVISAgKCwvh6uoKZ2dnbiblvXv3EBkZidOnTyM4OBiGhoYA6oseVVVVAEBQUBDOnDmD48ePQ19fH6WlpTh8+DAsLCwUlmpjGIZhmh8r8hiGaeTZs2fYsGED/vrXv2LIkCGQy+Vwd3fH7du3ERMTA01NzUbn3Lt3D5s2beLWxx0zZgxMTEzg6emJ2NhY9OjRAzdv3oSLiwsGDhwIoVCI//73v/D29oazszMbe8UwDNPMWJHHMMx7ycnJwcyZM9G+fXu4u7vDyMgIDx8+hEgkQmVlJf7+97/j999/R0BAAF68eIHw8HAuoiUvLw9EhEOHDsHDwwMikQgeHh6Ij4/HL7/8gmPHjnETPBiGYZjmwYo8hmHeW3p6OjZv3oxz586hY8eOGDx4MIKCgiCTydC1a1eEhoZi3LhxAOpbA4cPH45+/frh4MGDePLkCby9vZGeno5bt24BqM/qGz58OPr27Yu9e/e25EdjGIZpc9jsWoZh3puJiQlXjEkkEgD1M0zLy8sxYMAAiMVi2NnZ4fnz59ixYweSk5Px008/AQAKCgoQHx8Pb29v7np1dXXQ1dVFeXk5gE9n1i3DMExbwIo8hmH+lG7dunHfd+jQAf7+/vD09ESfPn1gb2+Pc+fOQUdHByNGjAAA3LlzB48fP4arqyt3XlFREWJjY7F+/XoALBONYRimObEij2GYZjFq1Cjcv38f9+/fR1VVFQQCAXJycsDj8fDkyRPExMSgX79+6Ny5M3dOUlISSktLucKPFXkMwzDNhxV5DMM0KyMjIwDAli1bUFVVBQAoKyvDuXPnMHPmTO64iooKiMViWFlZQV1dnXXVMgzDNDNW5DEM88E05OX16NEDSUlJ0NDQ4Pbl5eUhLCwMmzdvBsBa8RiGYZobK/IYhvkoXu2mBYB27dph4MCBmDRpEgBW5DEMwzQ3FqHCMAzDMAzTBrEBMAzDMAzDMG0QK/IYhmEYhmHaoP8HFdFl1TyRlrUAAAAASUVORK5CYII=",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "# Create mapping between values and colors\n",
-    "labels = cancer[\"diagnosis\"].unique().tolist()\n",
-    "colors = list(mcolors.TABLEAU_COLORS.keys())\n",
-    "color_map = {l: colors[i % len(colors)] for i, l in enumerate(labels)}\n",
-    "\n",
-    "# Create a 3D plot\n",
-    "ax = plt.axes(projection=\"3d\")\n",
-    "\n",
-    "# Plot data points with color corresponding to diagnosis\n",
-    "sc = ax.scatter3D(cancer['perimeter_mean'], cancer['concavity_mean'], cancer['symmetry_mean'], \n",
-    "                  c=cancer['diagnosis'].map(color_map), marker='o')\n",
-    "\n",
-    "# Define the new observation\n",
-    "new_observation = {'perimeter_mean': 97, 'concavity_mean': 0.20, 'symmetry_mean': 0.22}\n",
-    "\n",
-    "# Plot the new observation\n",
-    "ax.scatter3D(new_observation['perimeter_mean'], new_observation['concavity_mean'], \n",
-    "             new_observation['symmetry_mean'], color='red', edgecolor='black', \n",
-    "             s=100, marker='o', label='New Observation')\n",
-    "\n",
-    "# Add axis labels\n",
-    "ax.set_xlabel('Perimeter Mean')\n",
-    "ax.set_ylabel('Concavity Mean')\n",
-    "ax.set_zlabel('Symmetry Mean')\n",
-    "ax.set_title('3D Scatter Plot of Perimeter Mean, Concavity Mean, and Symmetry Mean')\n",
-    "\n",
-    "# Create custom legend handles\n",
-    "handles = [plt.Line2D([0], [0], marker='o', color='w', label=label,\n",
-    "                      markersize=10, markerfacecolor=color_map[label])\n",
-    "           for label in labels]\n",
-    "\n",
-    "# Add custom legend for new observation\n",
-    "handles.append(plt.Line2D([0], [0], marker='o', color='red', label='New Observation', \n",
-    "                          markersize=10, markeredgecolor='black'))\n",
-    "\n",
-    "# Add legend\n",
-    "plt.legend(handles=handles, title='Diagnosis')\n",
-    "\n",
-    "# Show plot\n",
-    "plt\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 27,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#new observation, 3 features\n",
-    "new_obs_Perimeter = 97\n",
-    "new_obs_Concavity = 0.2\n",
-    "new_obs_Symmetry = 0.22"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 29,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "0      25.800203\n",
-       "1      35.900199\n",
-       "2      33.000003\n",
-       "3      19.420085\n",
-       "4      38.100020\n",
-       "         ...    \n",
-       "564    45.000046\n",
-       "565    34.200075\n",
-       "566    11.300676\n",
-       "567    43.100270\n",
-       "568    49.080446\n",
-       "Name: dist_from_new, Length: 569, dtype: float64"
-      ]
-     },
-     "execution_count": 29,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cancer[\"dist_from_new\"]=(\n",
-    "(cancer['perimeter_mean'] - new_obs_Perimeter)**2 +\n",
-    "(cancer['concavity_mean'] - new_obs_Concavity)**2 +\n",
-    "(cancer['symmetry_mean'] - new_obs_Symmetry)**2\n",
-    ") **(1/2)\n",
-    "\n",
-    "cancer[\"dist_from_new\"]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 30,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>perimeter_mean</th>\n",
-       "      <th>concavity_mean</th>\n",
-       "      <th>symmetry_mean</th>\n",
-       "      <th>diagnosis</th>\n",
-       "      <th>dist_from_new</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>291</th>\n",
-       "      <td>97.03</td>\n",
-       "      <td>0.05940</td>\n",
-       "      <td>0.1879</td>\n",
-       "      <td>Benign</td>\n",
-       "      <td>0.147305</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>138</th>\n",
-       "      <td>96.85</td>\n",
-       "      <td>0.15390</td>\n",
-       "      <td>0.1957</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.158795</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>15</th>\n",
-       "      <td>96.73</td>\n",
-       "      <td>0.16390</td>\n",
-       "      <td>0.2303</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.272597</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>514</th>\n",
-       "      <td>97.26</td>\n",
-       "      <td>0.07486</td>\n",
-       "      <td>0.1561</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.295539</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>54</th>\n",
-       "      <td>97.26</td>\n",
-       "      <td>0.05253</td>\n",
-       "      <td>0.1616</td>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>0.304562</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     perimeter_mean  concavity_mean  symmetry_mean  diagnosis  dist_from_new\n",
-       "291           97.03         0.05940         0.1879     Benign       0.147305\n",
-       "138           96.85         0.15390         0.1957  Malignant       0.158795\n",
-       "15            96.73         0.16390         0.2303  Malignant       0.272597\n",
-       "514           97.26         0.07486         0.1561  Malignant       0.295539\n",
-       "54            97.26         0.05253         0.1616  Malignant       0.304562"
-      ]
-     },
-     "execution_count": 30,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "nearest_5 = cancer.nsmallest(5, \"dist_from_new\")[[\n",
-    "    \"perimeter_mean\",\n",
-    "    \"concavity_mean\",\n",
-    "    \"symmetry_mean\",\n",
-    "    \"diagnosis\",\n",
-    "    \"dist_from_new\"\n",
-    "]]\n",
-    "\n",
-    "nearest_5"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 31,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sklearn import set_config\n",
-    "set_config(transform_output=\"pandas\")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 32,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#import our classifier function\n",
-    "from sklearn.neighbors import KNeighborsClassifier"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 49,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>diagnosis</th>\n",
-       "      <th>perimeter_mean</th>\n",
-       "      <th>concavity_mean</th>\n",
-       "      <th>symmetry_mean</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>122.80</td>\n",
-       "      <td>0.30010</td>\n",
-       "      <td>0.2419</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>132.90</td>\n",
-       "      <td>0.08690</td>\n",
-       "      <td>0.1812</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>2</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>130.00</td>\n",
-       "      <td>0.19740</td>\n",
-       "      <td>0.2069</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>3</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>77.58</td>\n",
-       "      <td>0.24140</td>\n",
-       "      <td>0.2597</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>135.10</td>\n",
-       "      <td>0.19800</td>\n",
-       "      <td>0.1809</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>...</th>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "      <td>...</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>564</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>142.00</td>\n",
-       "      <td>0.24390</td>\n",
-       "      <td>0.1726</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>565</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>131.20</td>\n",
-       "      <td>0.14400</td>\n",
-       "      <td>0.1752</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>566</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>108.30</td>\n",
-       "      <td>0.09251</td>\n",
-       "      <td>0.1590</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>567</th>\n",
-       "      <td>Malignant</td>\n",
-       "      <td>140.10</td>\n",
-       "      <td>0.35140</td>\n",
-       "      <td>0.2397</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>568</th>\n",
-       "      <td>Benign</td>\n",
-       "      <td>47.92</td>\n",
-       "      <td>0.00000</td>\n",
-       "      <td>0.1587</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "<p>569 rows × 4 columns</p>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "     diagnosis  perimeter_mean  concavity_mean  symmetry_mean\n",
-       "0    Malignant          122.80         0.30010         0.2419\n",
-       "1    Malignant          132.90         0.08690         0.1812\n",
-       "2    Malignant          130.00         0.19740         0.2069\n",
-       "3    Malignant           77.58         0.24140         0.2597\n",
-       "4    Malignant          135.10         0.19800         0.1809\n",
-       "..         ...             ...             ...            ...\n",
-       "564  Malignant          142.00         0.24390         0.1726\n",
-       "565  Malignant          131.20         0.14400         0.1752\n",
-       "566  Malignant          108.30         0.09251         0.1590\n",
-       "567  Malignant          140.10         0.35140         0.2397\n",
-       "568     Benign           47.92         0.00000         0.1587\n",
-       "\n",
-       "[569 rows x 4 columns]"
-      ]
-     },
-     "execution_count": 49,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "cancer_train = cancer[[\"diagnosis\",\"perimeter_mean\",\"concavity_mean\",\"symmetry_mean\"]]\n",
-    "cancer_train"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 55,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<style>#sk-container-id-9 {color: black;background-color: white;}#sk-container-id-9 pre{padding: 0;}#sk-container-id-9 div.sk-toggleable {background-color: white;}#sk-container-id-9 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-9 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-9 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-9 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-9 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-9 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-9 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-9 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-9 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-9 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-9 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-9 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-9 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-9 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-9 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-9 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-9 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-9 div.sk-item {position: relative;z-index: 1;}#sk-container-id-9 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-9 div.sk-item::before, #sk-container-id-9 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-9 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-9 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-9 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-9 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-9 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-9 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-9 div.sk-label-container {text-align: center;}#sk-container-id-9 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-9 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-9\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(metric=&#x27;manhattan&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" checked><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier(metric=&#x27;manhattan&#x27;)</pre></div></div></div></div></div>"
-      ],
-      "text/plain": [
-       "KNeighborsClassifier(metric='manhattan')"
-      ]
-     },
-     "execution_count": 55,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "knn = KNeighborsClassifier(n_neighbors=5, metric=\"manhattan\")\n",
-    "knn"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 56,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "#define our predictor variables (Xs) and our response variables (Ys)\n",
-    "X = cancer_train[[\"perimeter_mean\",\"concavity_mean\",\"symmetry_mean\"]]\n",
-    "y = cancer_train[[\"diagnosis\"]]\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 57,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/juliagallucci/miniconda3/lib/python3.10/site-packages/sklearn/neighbors/_classification.py:215: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
-      "  return self._fit(X, y)\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "<style>#sk-container-id-10 {color: black;background-color: white;}#sk-container-id-10 pre{padding: 0;}#sk-container-id-10 div.sk-toggleable {background-color: white;}#sk-container-id-10 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-10 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-10 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-10 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-10 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-10 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-10 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-10 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-10 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-10 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-10 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-10 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-10 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-10 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-10 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-10 div.sk-item {position: relative;z-index: 1;}#sk-container-id-10 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-10 div.sk-item::before, #sk-container-id-10 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-10 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-10 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-10 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-10 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-10 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-10 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-10 div.sk-label-container {text-align: center;}#sk-container-id-10 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-10 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-10\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(metric=&#x27;manhattan&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" checked><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier(metric=&#x27;manhattan&#x27;)</pre></div></div></div></div></div>"
-      ],
-      "text/plain": [
-       "KNeighborsClassifier(metric='manhattan')"
-      ]
-     },
-     "execution_count": 57,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#fit our knn model\n",
-    "\n",
-    "knn.fit(X, y)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 58,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<div>\n",
-       "<style scoped>\n",
-       "    .dataframe tbody tr th:only-of-type {\n",
-       "        vertical-align: middle;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe tbody tr th {\n",
-       "        vertical-align: top;\n",
-       "    }\n",
-       "\n",
-       "    .dataframe thead th {\n",
-       "        text-align: right;\n",
-       "    }\n",
-       "</style>\n",
-       "<table border=\"1\" class=\"dataframe\">\n",
-       "  <thead>\n",
-       "    <tr style=\"text-align: right;\">\n",
-       "      <th></th>\n",
-       "      <th>perimeter_mean</th>\n",
-       "      <th>concavity_mean</th>\n",
-       "      <th>symmetry_mean</th>\n",
-       "    </tr>\n",
-       "  </thead>\n",
-       "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>97</td>\n",
-       "      <td>0.2</td>\n",
-       "      <td>0.22</td>\n",
-       "    </tr>\n",
-       "  </tbody>\n",
-       "</table>\n",
-       "</div>"
-      ],
-      "text/plain": [
-       "   perimeter_mean  concavity_mean  symmetry_mean\n",
-       "0              97             0.2           0.22"
-      ]
-     },
-     "execution_count": 58,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#new observation\n",
-    "new_obs = pd.DataFrame({\"perimeter_mean\":[97],\"concavity_mean\":[0.2],\"symmetry_mean\":[0.22]})\n",
-    "new_obs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 59,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "array(['Malignant'], dtype=object)"
-      ]
-     },
-     "execution_count": 59,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "#predict diagnosis for our new observation using our trained knn model\n",
-    "\n",
-    "knn.predict(new_obs)"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "base",
-   "language": "python",
-   "name": "python3"
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