diff --git a/cluster-trace-v2026-GenAI/lora_request_processing.ipynb b/cluster-trace-v2026-GenAI/lora_request_processing.ipynb
new file mode 100644
index 0000000..a74bc0d
--- /dev/null
+++ b/cluster-trace-v2026-GenAI/lora_request_processing.ipynb
@@ -0,0 +1,425 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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+       "<style scoped>\n",
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+       "\n",
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+       "\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>gmt_create</th>\n",
+       "      <th>gmt_modified</th>\n",
+       "      <th>predict_type</th>\n",
+       "      <th>predict_status</th>\n",
+       "      <th>exec_time</th>\n",
+       "      <th>exec_time_seconds</th>\n",
+       "      <th>groupId</th>\n",
+       "      <th>prompt_length</th>\n",
+       "      <th>negative_prompt_length</th>\n",
+       "      <th>num_images_per_prompt</th>\n",
+       "      <th>num_inference_steps</th>\n",
+       "      <th>checkpoint_model_version_id</th>\n",
+       "      <th>num_lora</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>2025-02-01 09:57:50</td>\n",
+       "      <td>2025-02-01 09:58:22</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:32</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>G0000</td>\n",
+       "      <td>63.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0000</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>2025-02-01 11:16:14</td>\n",
+       "      <td>2025-02-01 11:16:57</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:43</td>\n",
+       "      <td>43.0</td>\n",
+       "      <td>G0001</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>M0001</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2025-02-01 11:17:06</td>\n",
+       "      <td>2025-02-01 11:17:42</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:36</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>G0001</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>M0001</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2025-02-01 11:17:16</td>\n",
+       "      <td>2025-02-01 11:18:09</td>\n",
+       "      <td>IMG_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:53</td>\n",
+       "      <td>53.0</td>\n",
+       "      <td>G0001</td>\n",
+       "      <td>93.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>M0001</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2025-02-01 11:21:34</td>\n",
+       "      <td>2025-02-01 11:22:25</td>\n",
+       "      <td>IMG_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:51</td>\n",
+       "      <td>51.0</td>\n",
+       "      <td>G0001</td>\n",
+       "      <td>79.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>40.0</td>\n",
+       "      <td>M0001</td>\n",
+       "      <td>0</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",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26818</th>\n",
+       "      <td>2025-02-24 10:33:24</td>\n",
+       "      <td>2025-02-24 10:33:48</td>\n",
+       "      <td>IMG_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:24</td>\n",
+       "      <td>24.0</td>\n",
+       "      <td>G3974</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0004</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26819</th>\n",
+       "      <td>2025-02-24 10:33:25</td>\n",
+       "      <td>2025-02-24 10:34:09</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:44</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>G0287</td>\n",
+       "      <td>7.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0001</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26820</th>\n",
+       "      <td>2025-02-24 10:33:45</td>\n",
+       "      <td>2025-02-24 10:34:00</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>SUCCEED</td>\n",
+       "      <td>0 days 00:00:15</td>\n",
+       "      <td>15.0</td>\n",
+       "      <td>G2054</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>1.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0010</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26821</th>\n",
+       "      <td>2025-02-24 10:33:46</td>\n",
+       "      <td>2025-02-24 10:34:18</td>\n",
+       "      <td>TXT_2_IMG</td>\n",
+       "      <td>PROCESSING</td>\n",
+       "      <td>0 days 00:00:32</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>G0263</td>\n",
+       "      <td>45.0</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0003</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>26822</th>\n",
+       "      <td>2025-02-24 10:33:57</td>\n",
+       "      <td>2025-02-24 10:34:18</td>\n",
+       "      <td>IMG_2_IMG</td>\n",
+       "      <td>PROCESSING</td>\n",
+       "      <td>0 days 00:00:21</td>\n",
+       "      <td>21.0</td>\n",
+       "      <td>G3974</td>\n",
+       "      <td>16.0</td>\n",
+       "      <td>26.0</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>30.0</td>\n",
+       "      <td>M0004</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>26823 rows × 13 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                gmt_create         gmt_modified predict_type predict_status  \\\n",
+       "0      2025-02-01 09:57:50  2025-02-01 09:58:22    TXT_2_IMG        SUCCEED   \n",
+       "1      2025-02-01 11:16:14  2025-02-01 11:16:57    TXT_2_IMG        SUCCEED   \n",
+       "2      2025-02-01 11:17:06  2025-02-01 11:17:42    TXT_2_IMG        SUCCEED   \n",
+       "3      2025-02-01 11:17:16  2025-02-01 11:18:09    IMG_2_IMG        SUCCEED   \n",
+       "4      2025-02-01 11:21:34  2025-02-01 11:22:25    IMG_2_IMG        SUCCEED   \n",
+       "...                    ...                  ...          ...            ...   \n",
+       "26818  2025-02-24 10:33:24  2025-02-24 10:33:48    IMG_2_IMG        SUCCEED   \n",
+       "26819  2025-02-24 10:33:25  2025-02-24 10:34:09    TXT_2_IMG        SUCCEED   \n",
+       "26820  2025-02-24 10:33:45  2025-02-24 10:34:00    TXT_2_IMG        SUCCEED   \n",
+       "26821  2025-02-24 10:33:46  2025-02-24 10:34:18    TXT_2_IMG     PROCESSING   \n",
+       "26822  2025-02-24 10:33:57  2025-02-24 10:34:18    IMG_2_IMG     PROCESSING   \n",
+       "\n",
+       "             exec_time  exec_time_seconds groupId  prompt_length  \\\n",
+       "0      0 days 00:00:32               32.0   G0000           63.0   \n",
+       "1      0 days 00:00:43               43.0   G0001           93.0   \n",
+       "2      0 days 00:00:36               36.0   G0001           93.0   \n",
+       "3      0 days 00:00:53               53.0   G0001           93.0   \n",
+       "4      0 days 00:00:51               51.0   G0001           79.0   \n",
+       "...                ...                ...     ...            ...   \n",
+       "26818  0 days 00:00:24               24.0   G3974           16.0   \n",
+       "26819  0 days 00:00:44               44.0   G0287            7.0   \n",
+       "26820  0 days 00:00:15               15.0   G2054           47.0   \n",
+       "26821  0 days 00:00:32               32.0   G0263           45.0   \n",
+       "26822  0 days 00:00:21               21.0   G3974           16.0   \n",
+       "\n",
+       "       negative_prompt_length  num_images_per_prompt  num_inference_steps  \\\n",
+       "0                        26.0                    1.0                 30.0   \n",
+       "1                         NaN                    1.0                 40.0   \n",
+       "2                         NaN                    8.0                 40.0   \n",
+       "3                         NaN                    8.0                 40.0   \n",
+       "4                         NaN                    8.0                 40.0   \n",
+       "...                       ...                    ...                  ...   \n",
+       "26818                    26.0                    1.0                 30.0   \n",
+       "26819                     NaN                    4.0                 30.0   \n",
+       "26820                    26.0                    1.0                 30.0   \n",
+       "26821                     NaN                    4.0                 30.0   \n",
+       "26822                    26.0                    4.0                 30.0   \n",
+       "\n",
+       "      checkpoint_model_version_id  num_lora  \n",
+       "0                           M0000         0  \n",
+       "1                           M0001         0  \n",
+       "2                           M0001         0  \n",
+       "3                           M0001         0  \n",
+       "4                           M0001         0  \n",
+       "...                           ...       ...  \n",
+       "26818                       M0004         1  \n",
+       "26819                       M0001         1  \n",
+       "26820                       M0010         0  \n",
+       "26821                       M0003         1  \n",
+       "26822                       M0004         1  \n",
+       "\n",
+       "[26823 rows x 13 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "# Read the data from the CSV file data.csv\n",
+    "\n",
+    "# data = pd.read_csv('data.csv')\n",
+    "# load from tar.gz\n",
+    "data = pd.read_csv('lora_request_trace.tar.gz', compression='gzip')\n",
+    "data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "predict_type\n",
+      "IMG_2_IMG     0.066481\n",
+      "INPAINTING    0.005633\n",
+      "TXT_2_IMG     0.737039\n",
+      "dtype: float64\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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mTJmC+++/Hz/88AO2bduGTz75RHl91KhR+PTTT/HWW2/h6quvjnks559/Prq6ujQNwWmI85fIcXk8HoiiqNn2k5/8BGvWrMHo0aMN/3k8HowdOxbhcBgrV65UPrNp0ya0trYqfx988MHYsWMHduzYoWxbs2YN2traMH78+JjjA4D/+q//woIFCzB//nxMmTJFE5FzGlEUsXnzZsPvwigsmJ2LA2bn4oHZujhgdi4OCsnOzEnLAFYyoGPGjFGEL77//nucf/75mve+++67eOyxx7Bq1Sps374dzz33HCRJwtixYzXfc9BBB+HTTz/Fa6+9ptSDmXHUUUfhpptuwh/+8AfcdNNNWLp0KbZv347FixfjnHPOwbPPPpvQcQGRPmmff/45du3ahX379gEAbr75Znz11Ve46qqrsGrVKmzcuBFvvfWWIhwybtw4TJkyBZdffjmWLVuGlStX4vLLL0dJSYkSaZwyZQrq6upwwQUX4LvvvsOyZctw0UUX4fjjj1fq2GJx/vnnY+fOnfjnP/+ZFcGQzs7OjO+TkXmYnYsDZufigdm6OGB2Lg4Kxc7MScsiDz30EPr06YNjjjkGp556KqZOnaqp16qursbrr7+OyZMn4+CDD8bf//53vPjii5gwYYLhu8aOHYtPPvkEL774Iv7whz9Y7vO+++7DwoUL8c0332Dq1KmYMGECbrjhBhx66KGKBH+84wKAuXPnYtu2bRg1apRSG3booYfis88+w4YNG/Dzn/8cEydOxJw5c3DAAQcon3vuuecwaNAg/OIXv8CZZ56Jyy67DBUVFfD5fAAi6aFvvfUW+vTpg1/84heYMmUKRo4ciZdffjmh37SqqgozZsxAeXk5zjjjjIQ+w2AwGAwGg8Fg5BKcXAiNBNKko6MDVVVVaG9vR2VlpeY1v9+PrVu3Kv24kkWWZfT29mqiRQyVnTt3ora2Fh9//DFOPPFEW77zxBNPxIQJE/DYY4/Z8n2JngOiKKK+vh51dXUQBMGWfTNyD2bn4oDZuXhgti4OnLDzqIvUBeTNz50X452MTGGXnWP5BpmCqTtmAI/Hk+1DyBk++eQTdHV1oa6uDo2NjbjpppswfPhwy/5vydDa2oolS5ZgyZIllnV3TsJxHGpra5kzXuAwOxcHzM7FQ6HZel1DG6rLPajpWxr/zUVEodmZYU4h2Zk5aQ7DcRxcLvYzE0KhEP77v/8bW7ZsQUVFBY455hi88MILcXu3JcLEiRPR2tqK++67z1C3lwl4nke/fv0yvl9GZmF2Lg6YnYuHQrL19j1dmH7bBwBYZEePk3YuAH+gYCik65l5Dw5D1B19Pl9BePXpMnXqVEydOtWR79YrUGYaURSxceNGjBkzhqXMFDDMzsUBs3PxUEi2/m7TvmwfQs7ipJ3dApN4yBUK6XpmZ1UGYGV/xYPf78/2ITAyALNzccDsXDwUiq17A+FsH0JO45SdXcxJyykK5XpmZxWDwWAwGAxGAdAbyP/eUPmIS2CZUgz7YU4ag8FgMBgMRgHQwyJpGYPOkmKRNIYTsLMqA3i93mwfAiMD8DyPkSNHgufZZVXIMDsXB8zOxUMh2ZqlO1pjt53DouqkuV35f+4UCoV0PTPhEIfhOC7vCxcZicFxXNZ6aTAyB7NzccDsXDwUkq1ZJM0au+0cDKuppQLP0h1zhUK6nvPfzcxxZFlGT08PEw8pAkgDRVFkNQGFDLNzccDsXDwUkq39wfwfg1PYbedgSFL+zdIdc4dCup7ZWcVg2Egh3BQY8WF2Lg6YnYuHQrE1i6TFxk47B8Oqk8Y6LOUWhXI9MyetQJk5cybOOOMM5d8cx+GKK64wvG/27NngOA4zZ87UbG9qasK1116L0aNHw+fzYdCgQTj22GPx5JNPoqenJ+7+W1pacPXVV2Ps2LEoKSnB0KFDcc0116C9vT2h49+2bRs4jsOqVas0fwuCgF27dmne29jYCJfLBY7jDL3SXnvtNUyePBl9+vRBSUkJxo4di1mzZmHlypUJHQeDwWAwGPkCre4oSSyDx0nodEeWLcVwAuakFQm1tbV46aWX0Nvbq2zz+/1YuHAhhg4dqnnvli1bMHHiRHz44Ye4++67sXLlSixduhQ33XQT3n33XXz88cdx97d7927s3r0bDzzwAH788UcsWLAAixYtwqWXXprWOA488EA899xzmm3PPvssDjzwQMN7b775Zpx33nk4/PDD8fbbb2P9+vVYuHAhRo4ciVtuuSWt42AwGAwGI9egI2kScxwchU53lKQYb2QwUoQJhySJLMuQkHgYVZZluL0uiHIYHNKLh/MQwKUYU//JT36CzZs34/XXX8cFF1wAAHj99dcxdOhQjBgxQvPe3//+93C5XPj2229RVlambB85ciROP/30hFaMDjnkELz22mvK36NGjcJdd92FCy+8EOFwGC5XaqfexRdfjPnz52ucrPnz5+Piiy/GnXfeqWz7+uuvcf/99+PRRx/FNddco2wfOnQojjjiCEdWvXiex9ixYwtCUYhhDbNzccDsXDwUkq1pdUdRkuFiumUKdtuZjqQxhzh3KKTrmTlpSSJBxLK9H2Rl3z8bMBVCGiabNWsW5s+frzhpzzzzDC655BIsWbJEec/+/fuVCBrtoNGk6ii2t7ejsrIyZQcNAE477TT8/e9/xxdffIHjjjsOX3zxBVpbW3HqqadqnLQXX3wR5eXl+P3vf2/6PamOIR4ej8eR72XkFszOxQGzc/FQKLbWRNJYuqMBO+0coCNpzEnLKQrles5/N5ORMBdeeCG++OILbN++Hdu3b8eXX36JCy+8UPOeTZs2QZZljB07VrO9f//+KC8vR3l5OW6++eak971v3z7ceeeduPzyy9Mag9vtxoUXXohnnnkGQMTRvPDCC+F2uzXv27BhA0aOHKlxCB966CFlDOXl5QnXxyWKJEmor6+HxPIeChpm5+KA2bl4KCRb0+qOzHHQYredgyG6Js2Wr2TYQCFdzyySliQ8BPxswNSE3y/LMnp7/Sgp8aUdveGRXt7CgAEDMH36dCxYsACyLGP69Ono379/Qp9dtmwZJEnCBRdcgEAgkNR+Ozo6MH36dIwfPx633357CkeuZdasWTjmmGNw991345VXXsHSpUsRDsdXtJo1axZOO+00fPPNN7jwwgtZoW8MJEnGhfd+ir4VXvzt6mOzfTgMBoPBSAAWScsctLqjyH5rhgMwJy1JOI5LKuVQhgyBEyBwLsdS7JJh1qxZuOqqqwAA8+bNM7w+evRocByH9evXa7aPHDkSAFBSUpLU/jo7OzFt2jRUVFTgjTfeMES8UqGurg7jxo3Db3/7Wxx88ME45JBDFBVIwpgxY/DFF18gFAop+6yurkZ1dTV27tyZ9jEUOht3t+ObdXsBRBYacuHcZTAYDEZsNOqOzG9wFK1wCPuxGfbD0h2LjGnTpiEYDCIUCmHqVGNEsF+/fjjppJPwt7/9Dd3d3Wntq6OjAyeffDI8Hg/efvtt+Hy+tL6PZtasWViyZAlmzZpl+vpvf/tbdHV14YknnrBtn8WEKKoPHJYyw2AwGLmPLMuaSBqL7jgLk+BnOA2LpGWAZKNPTiIIAtauXav824wnnngCxx57LI488kjcfvvtOPTQQ8HzPJYvX45169bhiCOOiLsf4qD19PTg+eefR0dHBzo6OgBE0i6t9p0ol112Gc455xxUV1ebvj5p0iT84Q9/wB/+8Ads374dZ511Fmpra9HY2Iinn34aHMfZrvzD8zzq6uoKQlGIfrhLEiDk/5Bso5DszLCG2bl4KBRb0/VoAFtg02O3nTWRNPZT5wyFcj0DzEnLCLmWLlZZWRnz9VGjRmHlypW4++67ccstt2Dnzp3wer0YP348brzxRkvFRJrvvvsO33zzDYBICiXN1q1bMXz48JSPHwBcLlfceroHHngAP/vZz/Dkk0/imWeeQU9PDwYNGoRf/OIXWLp0adzfIRWCwaCtEcNsQa8KsjQOI4ViZ0ZsmJ2Lh0KwdVdvSPM3u3cbsdPOTII/dymE6xlgTlpG8Pv9GY+mLViwwPTfZrz55puGbYMHD8bjjz+Oxx9/PKX9n3DCCWmF/4cPH675vP5vPYcffrjp6+eeey7OPffclI8jGSRJwvr161FXV5d2pDDb0M929vDRUkh2ZljD7Fw8FIqtu/xaAS3mpGmx2860cIjMfuucoVCuZ4DVpDEYDBPohztz0hgMBiP36fazSFomCbB0R4bDMCeNkRIvvPCCpucY/d+ECRPifv6KK66w/PwVV1yRgREwYqF10rJ4IAwGg8FIiK5eXSSN3bsdhaU7MpyGpTsyUuK0007DUUcdZfpaIjL7c+fOxY033mj6mhO1Ypki30PrBInVpMWkUOzMiA2zc/FQCLbWR9KYuqMRO+3MJPhzl0K4ngHmpDkOx3EoLS3N9mHYTkVFBSoqKlL+/MCBAzFw4EAbjyj7CIKAurq6bB+GLWhq0tjDR0Mh2ZlhDbNz8VAotu42RNLYvZvGbjvTNWnst84dCuV6Bli6o+PIsgxRFFkPjSJAlmV0dHQUhK01kbQCGI+dFJKdGdYwOxcPhWLrLlaTFhO77RwMUemOUow3MjJKoVzPAHPSMkIgEMj2ITAygCRJ2LJlC6QCuFtrmlmzB72GQrIzwxpm5+KhUGxNN7IG2AKbHrvtzCJpuUmhXM8Ac9IYDIYJYYmpVjEYDEY+QddIAWyBzWlo4RAABRG5YeQWzEljMBgGwmGW7shgMBj5RCCkdRrYvdtZDE4x+70ZNsOctAzAcVy2D4GRIQqhwz0AiBJr0hmLQrEzIzbMzsVDIdiaTr8DmLqjGXbaWf97F0B2XcFQCNczwNQdHYfjOJSUlGT7MBgZQBAEjBs3LtuHYQthqiZNZKuDGgrJzgxrmJ2Lh0KxtSGSxpwGDXbbOcgilzlJoVzPAIukOY4sywiHwxnPVZ45cybOOOMM5d8cx+Hee+/VvOfNN9/URPmWLFkCjuOU/wYNGoQZM2Zgy5Ytms+9+OKLEAQBs2fPNuyXfEdbW5vm7wkTJkAUtTe06upqLFiwwLBfs/+WLFmCBQsWoLq6Wvn8ggULwHEcpk2bpvnetrY25TM0n376KX79619jwIAB8Pl8GDVqFM477zx8/vnnifykcZEkCfv37y+IYtWwSPd/yeKB5CCFZGeGNczOxUOh2Jql38XGbjsHdL83q0nLDQrlegay7KQ9+eSTOPTQQ1FZWYnKykpMmjQJ//73v5XX/X4/Zs+ejX79+qG8vBwzZszAnj17NN/R0NCA6dOno7S0FAMHDsQf//hHhMNh/a6ySjAYzPYhwOfz4b777kNra2vc965fvx67d+/GK6+8gtWrV+PUU0/VOFhPP/00brrpJrz44ovw+/0J7X/Lli147rnnTF875phj0NjYqPx37rnnYtq0aZptxxxzjOlnXS4XPv74Y3z66acx9//EE0/gxBNPRL9+/fDyyy9j/fr1eOONN3DMMcfg+uuvT2gM8ZBlGTt27CiIG3VYYjVpVhSSnRnWMDsXD4Via72QBRMO0WK3nXt1aposvTQ3KJTrGciykzZkyBDce++9WLFiBb799ltMnjwZp59+OlavXg0AuP766/HOO+/glVdewWeffYbdu3fjrLPOUj4viiKmT5+OYDCIr776Cs8++ywWLFiAOXPmOHbMsiyjNywm9Z9fTO79Vv+lc8JNmTIFNTU1uOeee+K+d+DAgRg8eDB+8YtfYM6cOVizZg02bdoEANi6dSu++uor/OlPf8JBBx2E119/PaH9X3311fjzn/9s2o7A4/GgpqZG+a+kpARer1ezzePxmH5vWVkZZs2ahT/96U+W+25oaMB1112H6667Ds8++ywmT56MYcOG4dBDD8W1116Lb7/9NqExFBNhWlqYPXgYDAYj59FHdjJ5725u68WKjfsytr9coNvQ8iBLB8IoWLJak3bqqadq/r7rrrvw5JNP4uuvv8aQIUPw9NNPY+HChZg8eTIAYP78+Tj44IPx9ddf4+ijj8aHH36INWvW4OOPP8agQYNw+OGH484778TNN9+M22+/3XJinw5+UcIpH35t+/cmwvsnH40Sl5DSZwVBwN13343zzz8f11xzDYYMGZLQ50g9HYkGzp8/H9OnT0dVVRUuvPBCPP300zj//PPjfs91112H559/Ho8//jhuvPHGlMZgxe23347Ro0fj1Vdfxdlnn214/bXXXkMoFMJNN91k+nkm7GJEZJE0BoPByCuyVSO1e38Pfn79OwCAxX89BcMHVWRkv9mgNxDGVX/7CpMPPwA9fq2TxkS2GHaTM8IhoijilVdeQXd3NyZNmoQVK1YgFAphypQpynvGjRuHoUOHYunSpTj66KOxdOlS1NXVYdCgQcp7pk6diiuvvBKrV6/GxIkTTfcVCAQ0EZ2Ojg7lGEhaH8dx4HkekiRBlmXNf9nCbP8cx8U8Jvq1M844A4cffjjmzJmDp59+WnlNlmXN95D9NDY24oEHHsCBBx6Igw46CKIoYsGCBXjssccAAOeddx7+8Ic/YMuWLRgxYoRmf/rfq6SkBHPmzMGtt96K//qv/0JVVZXlmMyO3Ww7+f8BBxyAa665BrfeeitOP/10zedkWcb69etRWVmJQYMGKWN99dVXMXPmTOV9X331FQ499FDTfZJjpM8Pno8EoemcZ1EUUVFRobyXRhAE5VyKt11/7um367/bajvP8+A4znS7/tj124Mh9eEjRcevf3++jUl/jKmOSRRFlJWVQZKkmGPNpzHpj5GNiVfsTF/z+TwmjuOweXc7hg0sB89zBTEmu849WZY1ts7XMfmD2tdDYdHxMcmyjKse/1J5ffe+LtT2L7VtTPG2JzMm8ozWvzcZO728ZDOWfN+IJd83YmC1VkGQqCIX+/WU7THpn9Gpjkn/ejbIupNWX1+PSZMmwe/3o7y8HG+88QbGjx+PVatWwePxaIQiAGDQoEFoamoCADQ1NWkcNPI6ec2Ke+65B3fccYdh++rVq1FeXg4A6Nu3L4YOHYqmpiaEQiH4/X7IsgyXy4X3Tz4agYBfc7K53R64XC74/b2ak8fj8UIQBPT29mj25fX6wHEc/P5ezXafrwSyLCMQ0NZ6lZSUwg0Zvb3q+4lypCiKmro3+kTr7e1FOBxW3nPfffdh8uTJuOqqq5TPhMNhuN1uhEIhAEBtbS1kWUZPTw8OO+wwvPDCCxBFEYsWLUJ3d7ci1FFWVobJkyfjqaeewpw5czSSp729vfB6vYozLMsyzj//fDz44IO46667lN9flo1jMttOxkS+G9DW+l1//fV46qmn8I9//EOTEhsIBCCKIjiOQ29vLzyeiJ2OP/54LF26FLt378a0adOUsdP7jNgjMqZQKIQNGzYox1dXV4dgMIj169cr7xUEAXV1dejo6NCIrfh8PowbNw6tra3YsWOHsr2iogKjRo1Cc3Oz5nwl597OnTvR0tKibCepn9u2bUNnZ6eyvba2Fv369cPGjRs1NYIjR45EZWUl1qxZo7nZjB07Fh6PB/X19Zqx0mPasUvdrywBnZ2deT8mArFTumNqbGwsuDEVop1SHdOWLVvg9/uxZs2aghjT29/ux19eWIkpdVW48qSaghiTXedeKBRCd3e3Yut8HVNrW4dmbJs2b0FZeI+jY9rTHsT3W9Sx7djZiNKQqh2Qi/eIpqamlO3UsEN9vatXqzfQ0dmFPhW+or+ecmVMHR0daY2pq6sL2YaTs1xZFwwG0dDQgPb2drz66qv417/+hc8++wyrVq3CJZdcYqhh+tnPfoZf/vKXuO+++3D55Zdj+/bt+OCDD5TXe3p6UFZWhvfffx+/+tWvTPdpFkmrra1FS0sLKisrAaieeU9PD7Zt24YRI0YoE3ar6JXV9nA4DEEQ0kqrS3afl1xyCdra2vDGG29o/s1xHKZPnw63242LL74YZ511FiRJAsdx+PTTTzF58mSsWLEClZWVGDhwICorK5XvP++88/DKK69AENSUS0mSMGTIEGzduhU8z2PJkiWYPHkyWlpaUF1dbfj7lVdewSWXXIINGzZgwoQJePjhhzURLf2x0zz77LO47rrrFPGTBQsW4Prrr0dbWxtkWcZf//pXPProo1i2bBmGDBmCTz/9FMcffzweeugh3Hjjjdi9ezdqamo0v9m2bdswcuRIfPfdd5g4caLpb+n3+7F161YMGzZMOQfMVouIotCAAQMM35FvK2BPvbcOD7z6IwDg7bknY/ywaraqF90uSRL27t2LgQMHwuVyFcSY9MfIxsQjFAph7969GDBgAHiez/sxHfb/3kBPtIZmw/yzlWPM5zHZde5JkoQ9e/Yots7XMf3mrk/x3ab9yuvP/OE4HHdIjeYY7R7Txl3tmH7bR8rrT15zDE6ceIBtY4q3PZkxkWd0//79NfOxZOz04qeb8efnVkaOidPWoX3z+GnoX1VS9NdTtsekf0anOqaOjg707dsX7e3tim+QabIeSfN4PBg9ejQA4IgjjsDy5cvx6KOP4rzzzkMwGERbW5smmrZnzx7U1ERuOjU1NVi2bJnm+4j6I3mPGV6vF16v17BdEASNAwKoxiT/EawcLv12WZYRCoXgcrnSrn1KdJ9Wr5F/33vvvTj88MMxduxYzXby/5EjR2p+c47jsH//frz11lt46aWXMGHCBOU1URRx3HHH4aOPPsK0adM030X/ZuTf5557Lh544AHMnTtXsz2V8erHds011+Dxxx9X0jHJ9nPOOQe33HIL7r//fjz88MOm32H2nfR3cBxnen7o/25qasKAAQMM2wFtNDCd7Wbfbfd2CervIEVTRPN9THrSGVNzc7MStS+UMSWyvZjGxPO8Ymf6Pfk6pjA1OYp3H0tle76fe2a2zrcx6Zsry+ANn7F7TLpdIiyZH2eu3CNSeUbT7y0vUbUO9CVoxG9g11P2x0Q/o1M9dqvXM0nWnTQ9kiQhEAjgiCOOgNvtxuLFizFjxgwAEWn4hoYGTJo0CQAwadIk3HXXXWhubsbAgQMBAB999BEqKysxfvz4rI0h16mrq8MFF1ygcWbi8b//+7/o168fzj33XIMjc8opp+Dpp5829Cuz4t5778XUqVOTOuZE8Pl8uOOOOwz924YOHYoHH3wQ1157LVpaWjBz5kyMGDECLS0teP755wHkxsWYS9DqjlkOtjMYDBtgKq2Fj76ZdSbu3frebPpjKDRKvNbTZnaJMewmqxL8t9xyCz7//HNs27YN9fX1uOWWW7BkyRJccMEFqKqqwqWXXoobbrgBn376KVasWIFLLrkEkyZNwtFHHw0AOPnkkzF+/Hj87ne/w/fff48PPvgAt912G2bPnm0aKWOozJ071xB2jsUzzzyDM8880zTSNGPGDLz99tvYty8x+d3Jkydj8uTJjvSzu/jiizFy5EjD9quvvhoffvgh9u7di7PPPhtjxozBKaecgq1bt2LRokWoq6uz/VjyGbpPGuv9wmDkP+w6Lnz0kbRM2Fy/T73CZKEh8No5UIlHgFuIpsmxBU2GzWQ1ktbc3IyLLroIjY2NqKqqwqGHHooPPvgAJ510EgDg4YcfBs/zmDFjBgKBAKZOnYonnnhC+bwgCHj33Xdx5ZVXYtKkSSgrK8PFF1+spNLlCtmI0ixYsMD034Thw4cb6v1OOOEEy5W3H374wXJf5557Ls4991zT77D6TrqOMNax08ycOVNTv6b/G4j81qTPnp4pU6Zo1ELthuM49O3bN+201lwgLFK1duy5o6GQ7MywptDszOaP1hSKrUkUy+PiEQxLGXEa9E6Z3mnLJeyws97xLStxo6MnCIgsWp0rFMr1DGTZSXv66adjvu7z+TBv3jzMmzfP8j3Dhg3D+++/b/eh2QbHcSyqVyTwPI+hQ4dm+zBsQaSctGLp/bJ6WysGVvswoLok5vsKyc4Ma5idi4dCsTVJPfR5hIiTlpVIWmadtJ5AGFc9/hVOOuJA/PaXo2K+1w476xedS70udPdG1KFZJC03KJTrGUgj3XHTpk344IMPFMlyVrdiTkROP8B+nyJAkiQ0NDQklUaaq4TE4mpmvWFnO06b8yGOvubtuO8tJDszrGF2Lh4KxdYkqkXqpjKxvmZw0sKZTXf84Nud+OyHRtw2/1sEgrH3bYedDZE0nwuk72Cenz4FQ6Fcz0AKTtr+/fsxZcoUHHTQQTjllFPQ2NgIALj00kvxhz/8wfYDLARyoSEew3lkWUZLS0tBOOR0JK0YallWbEysnhIoLDszrGF2Lh4KxdbEYfJ5IiUWGalJ06c7ZjiS5nOr5SRLfmiM+V477Kz/SUu9qnJ3MSxo5gOFcj0DKThp119/PVwuFxoaGlBaqnaVP++887Bo0SJbD47BYGQHbSQtiweSIdxC/ueuMxiM4kWSZMVJK4k6aZlIVTdG0jLrpIWo/b33TYPj+9NHZ0p9LhAtkUJwChi5RdI1aR9++CE++OADDBkyRLN9zJgx2L59u20HxmAwsodIPYiK4cHjEtT1qlBYgtuVVeFbBoPBSAraWSnxRKZ2Ygbu3XrJ/UxL8NPplYtX7kYgJMLrdk6sTe/3lvlc4DmW7shwhqRnIt3d3ZoIGqGlpYUJZFjgdruzfQiMDMBxHGpqagpCUShMRdKKId2RdtK6/aGY7y0kOzOsYXYuHgrB1rRz5PNGnJSMCIeEsivBT0fu/EERnb3W92877Kx/HpZ6qZq0IljQzAcK4XomJO2k/fznP8dzzz2n/M1xHCRJwv33349f/vKXth5cIcBxHNxud0GcLIzY8DyPmpoa8Hz+R2G0EvyF/+ChJzPd/tj9+wrJzgxrmJ2Lh0KwNe2skEhSZtQdsyvBH9A5ibHGbIed9SmkZT4XOJbumFMUwvVMSHoE999/P5566in86le/QjAYxE033YRDDjkEn3/+Oe677z4njjGvkWUZfr+fXbxFgCiK2Lx5c0EIxdCRNLkIUjjoiUZXnEhaIdmZYQ2zc/FQCLYmkTSvW1AaLmemT1p2a9L0TiL97NJjh51NI2lRL60Ysk7ygUK4nglJO2mHHHIINmzYgOOOOw6nn346uru7cdZZZ2HlypUYNSp2j4pipRBkQBmJ0dnZme1DsAWxyCJp9GpsT5xIGlA4dmbEhtm5eMh3WxNnyePmlfS7jKg7Rp0yT7SON+PpjklE0oD07ax/Hpb6WLpjLpLv1zMhpWbWVVVVuPXWW+0+FgaDkSOEpeKqSaPrOeKlOzIYDEauQe5hHhevRHYy4TMQp6y8xI2WzkAWImna/Tn9vNI7gWVeJhzCcI6UEjb9fj+WLVuGd999F2+//bbmP0b24Tgu5n+333473n//fXg8Hnz33Xeazz744IPo378/Xnrppbjfs2TJkpjH8frrr+Okk07CgAEDUFlZiUmTJuGDDz5IeBwzZ87EGWecofmb4zhcccUVhvfOnj0bHMdh5syZmu1NTU249tprMXr0aPh8PgwaNAjHHnssnnzySfT09CR8LMUGXZNWDKm69Gpsdy9z0hgMRnLIsozte7qydr8kaX90umMmI2nlJZE1/0z3SdOrSYoOe0qGPmk+F0jpUzE8KxmZJelI2qJFi3DRRRdh3z5j81eO4woiB9RuPB5PRvdHGowDwMsvv4w5c+Zg/fr1yrby8nKUl5fjoosuwkUXXYQVK1bA6/VizZo1uO2227BgwQKceeaZmu+59tpr0dHRgfnz5yvb+vbtG/M4Pv/8c5x00km4++67UV1djfnz5+PUU0/FN998g4kTJ6Y0ttraWrz00kt4+OGHUVJSAiCyaLBw4UIMHTpU894tW7bg2GOPRXV1Ne6++27U1dXB6/Wivr4eTz31FA488ECcdtppKR2HGRzHoba2tiBEYsJF1ieNftDHq0krJDsXE7Is46//9wMOGlKFM44dHvf9zM7Fgx22fui1H/HE22tww9l1mH3aeBuPLjGUdEcXrwhZZKQmLeoclvvcmr8zhT69MpZjaoedDTVpPrcaSWNOWk5QSPfupJ20q6++Gueccw7mzJmDQYMGOXFMOY0sy+gNpnATssF5LfEICZ10NTU1yr+rqqoUOVI9Dz/8MOrq6vDnP/8Zf/nLX3DxxRfj1FNPxXnnnWf4npKSEgQCAdPvseKRRx7R/H333XfjrbfewjvvvJOyk/aTn/wEmzdvxuuvv44LLrgAQCRiN3ToUIwYMULz3t///vdwuVz49ttvUVZWpmwfOXIkTj/9dNtXvXieR79+/Wz9zmxBR9KKLd2xJxBf3bFQ7FxMbNrdgX+8tw79Kr0JOWmFame+ACYudmOHrZ94ew0A4KFX67PipCnCIR5KOMTme3cgKMLr0fYgI85heYlbcxyZQp/uGE/dMV076+cNZV6XMi8rgkdlXlBI9+6knbQ9e/bghhtuKEoHDQB6gyLqLnstK/uu/+cMlHpTKiM0paKiAs888wymTp2KrVu3YseOHVi0aJFt369HkiR0dnbGjcDFY9asWZg/f77ipD3zzDO45JJLNOmX+/fvx4cffoi7775b46DR2L3KIooiNm7ciDFjxkAQnGummQlEjbpj4T956Ad9vHTHQrJzMdHRE4mQtncHIcty3Ou/UO1MJvAMlUKwNS3g4URk54Nvd+L3j32JuRcfgQtOHG3YL3HSMp3uqN9fPHXHdO1sjKS5QC6pYnhW5gOFcD0Tkq5JO/vss+PWIjHyh8mTJ+Pss8/G//3f/+Gxxx5zdPXhgQceQFdXF84999y0vufCCy/EF198ge3bt2P79u348ssvceGFF2res2nTJsiyjLFjx2q29+/fX0n3vPnmm9M6DjP8fr/t35kNQkWn7ph4uiNQOHYuJnqjEdKwKCe82l+IdhYE5qSZke+2piX4nVB3vOrxrwAAc55dodmuCodEa9KyLMEfb8zp2tmg7siaWeck+X49E5IOy/ztb3/DOeecg//85z+oq6uD2+3WvH7NNdfYdnC5SIlHQP0/ZyT8flmW0dvbi5KSkrQjNyUe+1cEdu3ahUWLFqG0tBT/+c9/0nagrFi4cCHuuOMOvPXWWxg4cGBa3zVgwABMnz4dCxYsgCzLmD59Ovr375/QZ5ctWwZJknDBBRcgEAikdRyFjMjUHRkFBm3Xzp4QfB77shLyCRZJK0zUmjRBVXe00V/yunnTUo9A1CmrKMlSTZo+3dFhR8mg7uij1B0L/1HJyDBJP6VefPFFfPjhh/D5fFiyZInG8eA4ruCdNI7jkko5lGUZnORCCZW3nEtcdtllOOKII3DrrbfipJNOwtlnn43jjz/e1n289NJL+K//+i+88sormDJlii3fOWvWLFx11VUAgHnz5hleHz16NDiO0wimAJF6NACK6AjDnGJWd0ykTxoj/6BrDbt6wxhQnb1jySY8c9IKEjWSRvVJs/He7fMIpk5a7qU7ZlbdsarMowi1FMOCJiOzJO2k3Xrrrbjjjjvwpz/9CTyfkoJ/0eH1erN9CKb861//whdffIH6+noMGzYMV155JWbNmoUffvjBso4rWV588UXMmjULL730EqZPn27LdwLAtGnTEAwGwXEcpk6dani9X79+OOmkk/C3v/0NV199tW3jiQXP8xg5cmRBXBfFrO7YHSfdsZDsXEz0Uk5aZ28w7vsLyc70QouLOWkGCsHWSk2aW1Ak4e0UDtELhij7pfqk0ceRKfSRu3jCIenamXx/VZkH1884BP2rfIpTXAwLmvlAIVzPhKRHEAwGcd555xXE4DMBx3EQhMRUGTPJ9u3bccMNN+CBBx7AsGHDAAD33XcfOI7Dn/70J1v2sXDhQlx00UV48MEHcdRRR6GpqQlNTU1ob29P+7sFQcDatWuxZs0ay8LQJ554AuFwGEceeSRefvllrF27FuvXr8fzzz+PdevW2V5QynEcKisrc87WqUCvRtqtEJaLBKjV2K44kbRCsnMxoU93jEch2Zle4WeRNCOFYGs6kiZw9qs7et0JOmmZVnfURdLiSfCna2fym5569FD8bsoYAHDk92akTiFcz4SkPa2LL74YL7/8shPHUpDIsoyenp6cWmGRZRmXXnopJk2ahMsvv1zZXlpaigULFuDJJ5/EZ599lvZ+nnrqKYTDYcyePRuDBw9W/rv22mvT/m4AqKysRGVlpeXro0aNwsqVKzFlyhTccsstOOyww3DkkUfi8ccfx4033og777zTluMgiKKI+vr6gugVqI2k5c656xT0amy8SFoh2bmY6NWlO8ajkOwcoqIbLoEtsOopBFtratIcEA6xdNL0zawzHEkzNrOOre6Yrp3J99Pzf45nNWm5RCFcz4Sk0x1FUcT999+PDz74AIceeqhBOOShhx6y7eAY6TNz5kzMnDlTs43jOHz88cem7z/uuOMQDhsnMAsWLEh63+mqgOr3Ge8Y3nzzTcO2wYMH4/HHH8fjjz+e1rEkSiHcFIBijKQlJxxSKHYuJjSRtATSHYHCsHMgJGpqiVifNHPStbXAc1mrSXrlsy144p1Inza6Js3OBTafRbpjQNcnLRiWIElyxiK2eqcwng3StTP5TWkBHkWCvwgWNPOFQrh3Ayk4afX19Uoj4h9//FHzWiGEFhkMhvZBVwQ+mibdkQmHFCY9mpq04rBxZ28IZ93+Efa2q3LUrFLBGQQhe07an55ervzb4xZAZmJ2LrD5LCNp2nRHIBK5taphsxt9eqUYo0+aHZDflF7scKIvHYMBpOCkffrpp04cByMPmTBhArZv32762j/+8Q+l2bQZDQ0NGD9+vOXra9aswdChQ9M+RkZq0H3SikGxKsgk+Aserbpj/Jq0QuDxN37ElsZOzTYps9loRYNb4DOubAgYozdet6Dcv+28ddPpjnQzeDLmcp/qpAXDYuactGgkjec4SLLs+POKfD3Pmzhp7Npi2ExxNorJMD6fL9uH4Ajvv/8+QiHzyc6gQYNifvaAAw7AqlWrYr6eb/A8j7FjxxaEqA69GlkMKRxa4ZD46o6FYudiokcjHJKYumM+23nn3m48+9FGw/ZiuJ6TxQ5bZ6v/nN4p8bh4JaIj2eg10E5Xb1BUWhHpa9KASO+0Ctv2HGFvWy8+q2/Cr4+q1fQ4JPsv9Qro8ofjqjuma2fym9JOGkfUNNm1lRPk+72bJmkn7Ze//GXMtMZPPvkkrQMqRAo1DZSoQqaCy+XC6NGjbTya3MDj8WT7EGxBU5NWBA8eOpIWDEkIhSW4XdY3+EKxc7b5as0eHNivDMMGlTu+r96AauNE0x3z2c7rd7ZpBIAIxRAZT4V0bZ0pQZZVm/fD6+Zx8NA+AIzpfV63oDgudpraQ90Pe/xhykkjqpICPC4ewbDkSETxnDsXY8febmxt7MQfzz1U2U7u3SVeF7r8YYTjOKbp2pn8poJJJI0tgOQO+Xzvpkn6rnL44YfjsMMOU/4bP348gsEgvvvuO9TV1TlxjDlBOhdfb2+vjUfCyDSJ2l6SJNTX19u6epktNOqO+T+cuOiLz+nUOD2FZOds8sOWFvzu3iWY/Mf3MrK/7oAaIU0k3THf7WzmoAHFseiSLHbYOhORtPbuIGbc8TF+fduHSsRI75S4Xbwj6o70eUNSwmVZplQlecWR0/cus4Mde7sBAEu+363ZTu7dJd5IpC/WmO2ws6ruaHTS2AJIbpDv926apCNpDz/8sOn222+/HV1dXWkfUK5BemkFg0GUlJRk+WgY2aCnpwcADEqmhYokyZoHcrGpOwJAd28IVWWFsRKXq6zctC+j+9OkOxZBTZrVhLEYrudsIAjqpJ2u2bKTti41TTcQElHidRkiaU0tPSj1uZTjsAva6e+JLnjQtcsetwCPWwD8YUdr88jYCGRfJdHIntPnt2yi7sgk+BlOYVtN2oUXXoif/exneOCBB+z6ypzA5XKhtLQUe/fuhdvtTjrHVZZlBAIBcBxXsGmPhQrpcdfc3Izq6mrbm1/nKvqV2WJYedc7abRkOcMZMt1PqYdKd+xKoJl1vhO2+H3ZRNIZXNTcICzKcLvsf97TKdg9gXDESdMZlOc5xYGwNZJGfVd3NF2YdsacjqQRyiiBkrAoKc+nkmjNXNjhE1xU1B3VbaSZtcwuLobN2OakLV26tCAFMjiOw+DBg7F161ZLJcNYyLKMUCgEt9vNnLQ8pbq6GjU1Ndk+jIyhT5MqdCdNlCRlzBwHyDJLW8kEoYw7acUVSbOqzSn06zlb0JG0QEiMWdOaMpTtSI0lfa+a8pMDcdkp4/Dip5sB2Gtr+nzqjl5L9EKLx83D446MOeBgJK2MiqTRi2tETMTpSBr5TTXqjkw4hOEQSTtpZ511luZvWZbR2NiIb7/9Fv/zP/9j24HlEh6PB2PGjEEwmFgDVBpZliFJEnieZ05aHuJ2uxOOoPE8j7q6urxXFBJFXSTN4YdeIChi3ttrcOLEA3DYqH6O7ssMejW41OtCtz8MMUYue6HYOdtkOpLWm6QEf77b2bImjS1AGLDD1nT6WyAkavqG2YVIO2nByPlMRJ7cAo9/XHec5ljstDWdVklSh4loh8BzEHhekenX9y5LFzptk3bS9PduIPYCmx12NuuTxrE+aTlFvt+7aZJ20qqqqjR/E6nLuXPn4uSTT7btwHINnudTihTKsgy/3w+fz8ectCIgGAzmfUQ5ZIikObu/fy1aj3lvr8G8t9dg83PnObszE+jVWNVJiz3oQrBztslkJE2S5JQiafls57BoEUljTpop6dqa/l2diiTR9yWy6EC20ZE8J/p20WmE+kgaSXNU0x3tHb8/qL1HE8h+BJ5Tonj6RUY96dsZyj4JajPrlL+WYTP5fO+mSdpJmz9/vhPHUbBIkoT169ejrq6uaGqaipVCsXWmI2kbdrY7+v3xoJuhqg/62AphhWDnbLFtTye+WdscU0HTbvwhkc4UU6KlQoyV1ny3s9VCg8hW+w3YYWtR46Q5U5NF34tJ3SyJmLo06XdO16RFFjkUZcdoBM3jEjTb7aK9W81ioptqk9o3j4tPSGHRTjtr1R0j/2c1ablBvt+7aVgzawaDoUFfeO10Cke2msASyITK6+aVSTurSXOOE//4PgBtupDTmDmE3b1hVBawgqeVcIic/6rUOQmdXmp3uh+Bvi/1KJG0aDSJ6tNG1h7sVXdUT5weJZKmOkkAlEUuu4VDOiihH9pZpJ1EJ1I8zTBTd+R5lu7IcIaEnLQ+ffoknKrX0tKS1gExGIzsok+Tcvqhl+0s4EAwMl4v9aBnTprzZHJCQ2poSjwCxGhvp87eUGE7aVaRNHZuOwJdx+pUJI2O8PsD2kga7TQIDvTtor+L9Ekj4yTOmRJJszndsYOKpNHnNe0kknRPJ9Qd1za0wi0IGH1gpam6I8fSHRkOkZCT9sgjjzh8GIVNvodbGYlTCLY2qjs6u79sR9KUB72bh0tIbHJTCHYuJkj9DumxtD8UQGcCMvz5bGerlF222m9Ouram75uZqEkzRNJM+3bZKRxiFklTF7gAKpJms5MaP5LGJxxJS9bObV0B/Pq2DwEAGxeca67uyBmPjZFd8vneTZOQk3bxxRc7fRwFiyAIqKury/ZhMDJAodjaEEkrmnRHQa3liFF8Xih23r6nCzV9SzQ1Hk5jpZrpVPNfAln5L/W64BJ47O8IxBUPyXc7h2Kcw5IkayaZxY4dts5ETVqiwiF6h2X7ni4M7leiRLrS3be+T5peOMRuJ7W9h46kqd+tCpcklgWRip23NHZq9q2oO/ImvzdbAMkJ8v3eTZOSPqUoinjttdfwl7/8BX/5y1/wxhtvQBRZ81czZFlGR0eHrbnhjNykUGytX4F3enWQftgt+b4Rt85fDn8wc6ISZELhdQtK8X2sB30h2PmHLfsx+Y/v4Zanl2d0v21d5m1MnJ7c9FCRtMrSiDR6R0/slir5bmdyDptJwbPJpBY7bE0v7DgmHKKR4I/2SVOEQ6iaNCr97vMfGjH5j+9h5v2fpbVvsyiemoUgaP5ve00ale4oikZnONF64lTsTN+zJElWMks0kUsuM/VwjMTI93s3TdJO2qZNm3DwwQfjoosuwuuvv47XX38dF154ISZMmIDNmzc7cYx5jSRJ2LJlCyQ7tXAZOUmh2Fq/Au/0hI4WkLj0wc/x0qdb8M/31zu6TxqSmuNx8QmpohWCnYmi5o9bM1tD3NIZMN1u1dPLLhQnzeNCZWmkDq0jTrpjvtuZRMSJU0rD6tK02GHrsCaSljkJ/rBJJI2+j72weBMA4Jt1e9PaN32NdvvNI2leJd3R5po06lrVCrQYhUPsvne3dKn3LFGSzdUdeVaTlkvk+72bJmkn7ZprrsGoUaOwY8cOfPfdd/juu+/Q0NCAESNG4JprrnHiGBkMRgbRP+ScXh00S3fc0tjh6D5ptJG04lB3bI2uDje29GZ0tdHKSXP6HCPCIaU+FyqiTgst612IkMmsmZNWCCvMuYZG1MOhTAAzCX4SwXOZ1EjJsmzoe5kqdKqyUd0xEkFzC870SaOvVVGT7pjcAlsqtFFOmiTJ5uqO1O/NYNhJ0hL8n332Gb7++mv07dtX2davXz/ce++9OPbYY209OAaDkXn00t1OP3fMapHo5qVOoyiUeQRl7LH6pBUCJIWnJxBGV28IFaWZUTls6TB30px2ismkssTrQlVU0TER4ZB8RlQiaUbbFvgaRFYIa9QdsxFJU9fc6aiSVVPzdPZt7JPGa47B7uuZTk02jaS5qFR1m8ZLaO2kHUTZVN1RTS9lFxbDXpKOpHm9XnR2dhq2d3V1weMpXDnjdCiErueMxCgEW+sljJ2eQJvpFzg1yTGDXo1V1B3jPGzz3c5t3aqz1NjSm7H9ZiuS1huVKy/xCGpNWgKRtHy2M7mOWbpjYqRj60iERf3bOQl+9b5IzmnRpJk1RzkNtjlpdLqjTt3RHU13dMpRau9WF1Toc5dW5k00kpasnel7lijJpuqOak1aUl/NcJB8vnfTJO2k/frXv8bll1+Ob775BrIcCf1+/fXXuOKKK3Daaac5cYx5jSAIGDduXMHIgTKsKRRb54K6o9+hSY4ZdLojefDGmtgUgp3pYvimlp6M7dfKSXPaaSD2dLv4hGvS8tHOKzftw8ZdkXpDMuZys3RH5qRpSNfWYd3sPBPqjj1KJC2yb1O1QUmOqfKZDPTiHXHYVHVFZyNpnT20cIiZuiOfsLpjsnam71mSJKvqjpqatMj/WbpjbpCP924rknbSHnvsMYwaNQqTJk2Cz+eDz+fDsccei9GjR+PRRx914hjzGkmSsH///oIoYGTEplBsrRdxcPrBw/PG21Ago+qOqkIYqUmLFdkpBDtrnLTWzEXS9nf4TbfHi1ymC5m4uQQOlWWJqTvmm52bWnpw9tzFmHbLIgB0TZoxw4VF0rSka2t9erTdwhnKfmh1RyLBL6rnNoHn6HRHm2rSKOeIOIYhfSQtwT6TydJu0cw6QAuHJOAgpmLn/e3qPUuUZCVapu2T5sy4GamRb/fuWCTspJ199tlYtGgRqqqq8NZbb2HDhg149dVX8eqrr2L9+vV44403UFVVldTO77nnHvz0pz9FRUUFBg4ciDPOOAPr12tV3fx+P2bPno1+/fqhvLwcM2bMwJ49ezTvaWhowPTp01FaWoqBAwfij3/8I8LhzE3yYiHLMnbs2MFWWIqAQrG1Pork9IPHLJKW0XRHqq5BiaTFkXHOdzvTxfCZjKTtt6hJczrdUeklxfNK/V28SFq+2Xnzbq3YDhFYIDV4NKx2Rku6ttbfLxyT4DcVDlHPbQKtNqivMU4V0SSSRqJ0JJJGnBW7UiwJ9LVKO8Qk3dGbYDPrVOy8j1pYkiRZcZTpSBrHatJyiny7d8ciYSettbUV06dPx9ChQzFnzhwIgoBTTz0Vp556KkaPHp3Szj/77DPMnj0bX3/9NT766COEQiGcfPLJ6O7uVt5z/fXX45133sErr7yCzz77DLt378ZZZ52lvC6KIqZPn45gMIivvvoKzz77LBYsWIA5c+akdEwMRrFj7JOW+WPIhnCI16PWpBV6vxs6kpYLNWmZSnd0CVxSNWn5RE9AvWZkWY2glPmM+mCFfn5nGn0NVsCh+5dpM2vZJJLmQLqjxkmL/luJpAnaSJrd5xdRZwV0zaypBTZBWWCz94FFLyyJsqykCgsm6aUF4BMwcoyEnbTFixdjy5YtuPTSS/H8889j9OjRmDx5MhYuXIhAwPzBG49FixZh5syZmDBhAg477DAsWLAADQ0NWLFiBQCgvb0dTz/9NB566CFMnjwZRxxxBObPn4+vvvoKX3/9NQDgww8/xJo1a/D888/j8MMPx69+9SvceeedmDdvHoLBwnoIMxiZQP9Qd3o1ymyCnkknje6hlUhNWiHQ1k2nO2a/Ji1zkTTKSSswdcdeKkWYFowgqWg0zEezl2xG0oid6UiaQDVXtivdkf4esk99uiNJOYyViZDSvqnvkzTpjqpwSCKRtGTpCYSV5wOgV3c0SvCzxQ+G3SQlwT9s2DDcfvvtuP322/HJJ5/gmWeewWWXXYarrroKv/3tbzFr1iwcccQRKR9Me3uk4JnI+69YsQKhUAhTpkxR3jNu3DgMHToUS5cuxdFHH42lS5eirq4OgwYNUt4zdepUXHnllVi9ejUmTpxo2E8gENA4lh0dkTQRURQhipGLnuM48DwPSZI0k1Synbwv3nZZllFRUWHYziu1L1JC2wVBgCzLptv1x2i13a4x8TwPjuPYmHTbRVFERUUFZFk2fE8+jSkU1r5figoEOWUnMyUw8vDNxLlH5KR9Hl5RJwuLkmYf9JhEUURZWRkkSYo51ly9nvxBUeME72nptf2+ZzUm62bWkuWx23HukQkmxwHl0cgSqUmLNaaysjLldbvs9OZXDQCAM44ZmtaY9HYi5zEABINhdfJuop4aCoUhiiK7l0e3y7KssXWyYwrqamj9wchcwu4x0ffmnkA4GjElThqo6zjyHlGSTBfdUrGT5lknRf4OhCLjdglc5H5I0h3DkuGeko6d6GdEiLo3k9plj4sHh8ixk3u32ZjIM1o/fis7NesWsEIhUfkszxuPnaQ7Fvv1lO0x6Z/RqY5J/3o2SLpPGmHy5MmYPHkyOjs7sXDhQvz3f/83/vGPf6RcCyZJEq677joce+yxOOSQQwAATU1N8Hg8qK6u1rx30KBBaGpqUt5DO2jkdfKaGffccw/uuOMOw/bVq1ejvLwcQMRRHDp0KHbu3ImWlhblPTU1NaipqcG2bds0rQhqa2vRr18/bNy4EX6/msM8cuRIjBo1CvX19RqDjx07Fh6PB/X19ZpjqKurQzAY1NTmCYKAuro6dHZ2YsuWLcp2n8+HcePGobW1FTt27FC2V1RUYNSoUWhubtb8BnaOqbKyEmvWrGFjMhlTR0dHXo9p89btmu2iJDtqJzPRCPLwzcS5t3vPXgBAd2cbeD4SZdmxYxfq63tijqmxsTHnzr1E7LS/UxtB2rW3U9mHk+eeJMtotXLSwiL8fr9j9wgyyWvdvx+7tkf+3dkbgiTJlmPasmUL/H4/1qxZYzkmIDk7+cPAn/61ATwH1Ja0KrU8dlxPm7e1Kq9v3roNLa2RRc+mxt2G33vNunXYV+lm9/LomEKhELq7uxVbJzumXklb97dn737U19fbPqaGHTuVbV3dfvj9fqXmrKe7Sxkbx/UDAHR396C3VzsnS9VO2kiajJ07d6Ipeu9sbdmH5uZmCNEVgX37W5RjscNOdGZDZ2e38trmHc0AgBK3jL3Ne6L7bsXGjRtjjqmpqSmhc29foETz261bvx5d3ZHnAs+rz6fWlv0AAL8/cn8r9uspV8bU0dGR1pi6urqQbVJ20gBg69atWLBgARYsWID29nZNxCtZZs+ejR9//BFffPFFOoeUELfccgtuuOEG5e+Ojg7U1tZiwoQJqKysBKAWgg4ZMgQHHnig8l6yffjw4ZrvJNvHjBlj2F9TUxPGjRunUbEj/66rq9O8l+d5+Hw+w3YgcuKabe/Tp4/BkQWAgQMHYsCAAYZjTHdM5NjHjx9vur1YxyRJEpqamjBgwIC8HlN1v0EAVHEeWXbWTqK4y/D53qAIWZYzcu75/tMNoAO1B9agbWtkojuopgZ1dQeZjkmSJOzduxcDBw60HBOQu9fTuh1tALbA6xYQCInoCkgYM3Y8fB7B0XMvEBIhShsMxwYAMjhH7xGivA8AUFMzED874mAAmyHLQLc/ZDmmUaNGYe/evRgwYAB4nrfFTht2tkOS10OSgTFjDzYoL6ZzPX25fR2AyKS1tnYoSssaAXRh2NBa0NczAIwZcxCGDixn9/Lodo/HoxwP/ZxOdEwNzV0A1MlqSVnkc3aPqWbwAQAi98uQFLlmyCJXdXWVcqyf/RCZ2Hp9JeB7ewGojloqdurXrz9kqJNuUZIwZMgQVFY1AWjDgYNrMHDgQLj4yMJAZZV6LHbYSZLV+4bXV6K81v1uxDkaeUBfNJeWANiLysoqZV/6MZFndP/+/RM69xav1C5wjBo1Bl5fOwA/eJ5T9jOgXgTQBpfbnfCYyPZCvJ6yPSbyjCZihqmOiWTZZZOknTS/349XX30VzzzzDD7//HPU1tbi0ksvxSWXXILa2tqUDuKqq67Cu+++i88//xxDhgxRttfU1CAYDKKtrU1jwD179qCmpkZ5z7JlyzTfR9QfyXv0eL1eeL1ew3ZBEAx9Fczkwcl7E9kuiqIycTf7TKLfA0RORLPtVseY7PZkjsWu7YU2pli2zpcx9QaNfdKctJNZTZokA93+MMpLjD2eAHvPPVLbUe5zK3UGkmwcL33szc3NSsQ+V849ILHrqaMnMmE7sH8ptjZ1QpYjohNlJR7T99t1jBJ1XvEcp1FCk2TrY7fj3CNiOG6XgFKfR3FQO3pCitqj2fcQO9P7T+c3aG6nei7FOceS3e6nFFFlcMp15XGb/KY8b9uYlO/M83u5ma0TH5P272BY1nzOrjHJUHNXSa0UyR5zu1SbktowOh2SkIqd9DVmYTHyTCDbfR4XeJ6nZPCNY0jVTrIsG0RLyGuNUWXaA/qXKanUkqx+1mxMyTyjaTEeAADHKWl2PPU7knpAcktj11P2x0Q/o1M9dqvXM0nCwiHLli3DFVdcgcGDB+Oyyy5DTU0NFi1ahC1btmDOnDkpOWiyLOOqq67CG2+8gU8++QQjRozQvH7EEUfA7XZj8eLFyrb169ejoaEBkyZNAgBMmjQJ9fX1aG5uVt7z0UcfobKy0uAlMxiM+JCHf4kncoNyWnlP1OWoEzIl7EBU0kq8rqJQdyQ9h/qUexUnuLPX+d+aPo8qdQ2Wnf69ieIbERcg+2/PsMLjHqonXcgmaXRCb4BWwFMFIwSBx4UnahWY5cLWxckIkiRj6Zo96OwJZqyZNX2dyHJE3ZA4YVohC7Vvlx3nmdn1KcmyUTgkgYbSSe9b1juIkvL/pqgy7YH9SuFyoJG23sENi7IiukOrO3JUywMGw04SdtKOPvpofPPNN7jzzjuxe/duLFy4EFOmTFHCjKkwe/ZsPP/881i4cCEqKiqUPOHe3siFV1VVhUsvvRQ33HADPv30U6xYsQKXXHIJJk2ahKOPPhoAcPLJJ2P8+PH43e9+h++//x4ffPABbrvtNsyePds0WsZgMGJD5I4rohNZ2ekJtIX6WGdvZibQirqjl1J3LIAmmFa0RuX3q8s9qCBOWgYcYnrCQxpKK685/HvrG/5mS+GR7klnl+oeoduvjkWiVOjcAoc7Lj4CP/5zhtIzjTXdTZ8XP92MC+9dgt/e/amhbUkmJPiByL2LbtROoPukhWw4z8zO1bCYGSdN/13k7+bWXoiSDLfAY2B1iTJmO/et/+0kKqrHmTjFhdA8mZFbJJzu+O233+InP/mJrTt/8sknAQAnnHCCZvv8+fMxc+ZMAMDDDz8MnucxY8YMBAIBTJ06FU888YTyXkEQ8O677+LKK6/EpEmTUFZWhosvvhhz58619VhTheM49O3bNy1nlpEfFIqtu6NOWnmJG81tfsdXB62iKJ3dmYqkRSZUJV5BUXeMFdnJdzuTRtbV5Z6II74/s5E0gedQ5stwJE3X8LdSaWhtvRDghJ3pnnR29a8idFECEWFRVgQlyJhLvC5Vppw1dNKQiq1f/c9WAMDahjbDIkNLV2ptieKhv056g6KmUTuBloS3o52ImeNDR+n0fdLMFHtT3rfOUSLX8u79kQWPwf0iDloiEvzJ2ln/24mSrKQ70pE05fdml1VOkO/PaJqEnTS7HTQgsf5LPp8P8+bNw7x58yzfM2zYMLz//vt2Hppt8DyPoUOHxn8jI+/Jd1uHwhL8wbCyIk+iLE5P6Kx66mQqymEaSYux+pzvdm5TImnezEbSiNMgcCj1ah89mUqpVSJpZcRJsx63E3ame9LZne5I21CUJMVxoCMsHDV5Z6ikYmvafnSkNizK2Lm3G8GwCI/L3poW/XXSGwgbosQANM64HdeWmaMnihKCul58aiaCk5G0yD537e8GAAzuVwYACTWzTtbOYd01SkeoKR+Nilyy6yoXyPdnNE3C6Y6M1JAkCQ0NDSwMXgTku63Puv0jHH7FG1GlMij1Sk5PoC0jaRlKd9TWpEX7pMR42Oa7nUnUrKLErTppGYikkYmbi+dR6susk0acbl5Xk9YRoybNCTs3UZE0uxumd1E2DIsyNXmnmhyzyaQpqdiadtLIuX1Av1KUel0QpYijZjcGJy0YVustBWP6nV3Xldk92izd0RWN5umjX+lgcNKi371rX2TB48B+pQCQUCQtWTvrnc1IfzjtvQSg0x3ZdZUL5PszmoY5aQ4jyzJaWloSihoy8pt8t/WahjYAwLodERllpSbN6UiaxWQ1c5G0SLpjopG0fLcz+b09Ll6xcSYiafSKf5nOSbN7ciNJMp7+93qs2hyR6CZOCUln9UVFcYIh64e4E3ama9LsjqR16WrSSDqlk5P3QiEVWwc1kTQSteQxoibSa/Xfy3fi7++stbU+zZDuGBDV60rT4idiZ/14Uj2XibPiphx+Ot2R9Psj55pZ78tU0Z+r5FhIuuOB/SORNH1N2guLN2HpGm3riWTtbJbuKFHqjgT1907oaxkOk+/PaJq0+qQxGIzCRUl3dHgxymqCngknTZQkRYlNW5OW/ytwVoSpCEsm1R1D1ETW6XTHN77chrtfXAUA2PzceRqlw8j/My8Q0+0Pac5pu2vSaEc7LEmqoARvNpnM/8lLtjGLpAk8h+E1FVi9vQ0PvRrpm9av0otzjh9pyz7152tvIKzu20Q4RH9dSbIMIYU6HVFU9yEjktIZFqUYkTQ7a9KMKYeAmu54QDSSpqg7ijK+XtuMOc+uABC5/lNFv1gnSbLyPDSvSWPXFcNeko6k/fnPf8b27dudOBYGg5FDKOmO2apJy4A8ei/VB0er7li4D9swFWFRa9Kc/61JLUlEOMTZSNraaFRY2TdxEKP2dSItKx60/D7gQCSNcrRFUdY44wQWSbOPYFi9d9CppSNqKjTva7PxPqa/TkRJNpzbgGpnfaQ4Vbsr9Y08pwiUmAmHKM6hg+mO5P5FrqfBfaPpjtS5vXm3PU2I9deoKJmrO5J/MyeNYTdJO2lvvfUWRo0ahRNPPBELFy5EIOCMilGhwHEcampqCkJlhhGbQrM1mcA7LcFvNXHwOyRjTUPq0TgukgKn1KTFUQjLZzuTybtboNIdM1GTRk1knY6k6SdX+mgD+X+saJbddqaVHQF7JfglSUaXX1V3FClVP600e/T9bC6pIRVbayNp6gKE3kmrLjNvlp4KRodFVs5tusEvifLQvfOA1J0nSbl+eOV8CotqSq0SSXMg3dHMMQXUNgekn6dA9bi06lOXrJ316Y6SlbqjkoGR0NcyHCbfn9E0STtpq1atwvLlyzFhwgRce+21qKmpwZVXXonly5c7cXx5D8/zqKmpseyQzigcCs3W5RlSd7SaONidDmYGqUcr8bjAcaqMczx1x3y2M1l5F3guK33SXAKn9OtSjsnmc0x/7ujrdlwW6WA0dtt5D6XsCNgrHNKtn4xTK/5aaXYmcGBGKramnTTye7oEDiMHa500O6PyeruFRYmqhzM64z0BrbOSciRNVB0TtReapNTlGfqk2Xhu638/cixK+rRu32FJslzgS9bOZsIhiroj9RXEX2NpxLlBvj+jaVIawcSJE/HYY49h9+7dePrpp7Fz504ce+yxOPTQQ/Hoo4+ivb3d7uPMW0RRxObNmyGKzkcFGNkln21t9nAhURbHnTSL77db/c4Mf5AoO0ZXYxOYvOeznQG1QavLldlImkhN9E4/Zhh++8tRyiq43U6DMU1JK6IhCPFrZ+y2c5Mukha0Md1R72SHRUl1il1mTY7ZZJImFVvTCwF0Hz59JM3W+iwTEQ26/yDBys6pXmd0qjLJNqDVHT0GR8l5CX46IwCgo1naSBo95mTtbBZJU4RDTNJLWRpxbpDvz2iatNxMWZYRCoUQDAYhyzL69OmDv/3tb6itrcXLL79s1zHmPZ2dndk+BEaGyFdbm03aVOEQpyNp5pMYO9PBrKB7pAHQrBLHIl/tDFA9w3gOFSWRiFZXBiX43S4eNX1L8ZdLjsS4odXRY3I43VEXSUt0MmmnnWllx8gx2Td519sv0sTYqPqXiEx5sZKsren7k0hF0ipKPbj1/MOV10IO1meJIiUQY1J7qCdV5ylMCYfQ90i9cIhAiXfYhVkza1lWHUSyCOGirmk6kkbXDgLJ2VnfJ02UKQl+VpOW0+TzM5omJSdtxYoVuOqqqzB48GBcf/31mDhxItauXYvPPvsMGzduxF133YVrrrnG7mNlMBgOoXeI3AIPrzsa5XD4uWOZ7mizsIIZSrojcdKEwl8RDVG1YZmU4A9TaZYEp5wGsxVwQF39djkwmbTi4+924cFX6xXJcIKd57feSQtTghKCYDKZLODzOxuo53bkvJo1bSzOOGYYgPgLPslgSHeknHGz6yre55Pdr4vnVWVUuk+aIERft//+KcrGdE5JVuvhPNF9W0XSYrXZiIfewY5I8Ef+bfZ7Mx+NYTdJS/DX1dVh3bp1OPnkk/H000/j1FNPhRC9SAi//e1vce2119p2kAwGwxnCogSXwBseqqU+l+ah5yT6dEee4yDJckYcpV4lkhZNdyRpKxlU/cs0dA1LRptZ62TwgcTSS1PBKByinei5MijB//8e+ULzt8BzGmEPO9DbT6QEJdymzaxt2zUD6vlLO8SKMxN2OpJm7YzrSfWco4V3OI5SdxT1kbTEMhGSgdyLPS4BYTFyvw6LshLlIpE0+l5Cq/amk1asH4dEtbagf2NFgp9dWAybSTqSdu6552Lbtm147733cMYZZxgcNADo379/QfcZSgaO41BbW1sQKjOM2OSbrR99/UdMvOINbNzVbnTSvK6MPXj06Y6lUXn2TNSkkXRHNZKmTkCsyDc761EFPDJckyaRVXeTfk42O8WGFXBdtCERCX6n7Ez6OtmZBqePpNFOoFk/p0KOFKdCurY2k8FXarfsdFhMRDTMmlnbHUmjxYZUcSWTdMcEhJeS3rdEnDRtI219iwmBqpWjG7sHqahasnbWj0O0UHfkWK1nTpHvz2iapJy0UCiEBQsWoKPDnh4UxQDP8+jXr19BqMwwYpNvtn7szdXoCYRx30vfGxyl8hJXxkQG9BMP0kMrE+qOJJJW4tHXpMVW/csnO+uh60tIJC0Ykixlq23bb9ioNqj83narO1pK8OuaWcdR8XTCzkMGlJkeYzp0+7XqjhHhEJNaJdbM2pR0bW0WJXY5sABh1jPMtJm13TVplDgJLRwSNAiHxG9hkiyKk+ZWf9twWDJG8ajMDzp9O0g9R5K1s0GASKTUHTnj780uq9wg35/RNEmNwO12w+/3O3UsBYkoili3bl1BqMwwYpOvthYE3vDwLvW6qGJoZ/evn3gQxT8704SsUGvSklN3zEc7E0iExS3wKCtRM96djqbpUw4BKpLmcE2aXqZcrZ2Jre5ot529bgEDqnymx5gOegebnly6TCbvLJKmJV1b08IhBCINb+diU6xm1mbqjlbHmep+XYJak0afc/o+aU6oO3pcataWZt9E3ZE6tzt61AbidE1asnY23Ecs1R0j/2eRtNwg35/RNEm7mbNnz8Z9992HcDgc/80MAGCObRGRj7Z2CZxhtbfU56KKoe1/8Kze1opd+7oBWEfSMpHu2Gul7hhn3/loZwIt2S3wPMqjv7cT4iH72v34fvP+yH5NIjuCQ0IWtJMiSpImEgBoU6NiYbeda/qWKBNaOyNp+u+iJ7GCSSSNTSaNJGNr/T3RLLXUERGNGM2szdJaDZ9PMapHi5OQcfkDRieNT/D+mQyiLmIGAH7q/NbXmYqSpI2k6dQdk7Gz/v4gadQd1e2Zqt9mJE4+P6NpkhYOWb58ORYvXowPP/wQdXV1KCsr07z++uuv23ZwDAbDeVwCb3iolvncjtWvbNrVgdPmfIgynws/PDXD8CAs80VS8DLTzFpfk+ZM+l0uoSqyRSY95aVudPnDjjhpR1/zFmQZeOP2kxR7asQVnBIOoXtYhWWDg+jKkIqnfjJf07dUOQY7z2+9gp020mCMpLHJZHoYmqWbyOArCwE2OuNmPcNMFz+sImlyasdC90mTEfnu3qC6UE/uJaQuzolImkvg4BI4hEWtxL6hkbYka7IC0lF31NcTipIMsklTk5ahrBNG8ZG0k1ZdXY0ZM2Y4cSwMBiMLuHjO8FAt87kcm9C9tXQ7ALWORv/9mRQOsY6kFe7TVq9EV1HiRhN6HUl3JD7Kig17URatf9MIHAj217AAOieNUmQj5zQtfmA3S9fswctLtuC2CyeiusyjeW1wnxKlfsfWSJpuHPQklq4BVCNptu26KNFEkQTeVAZfFQ6x78c2SPCL5s2sOSsnLcX7Gn3PINd0b9AYzSL3FCdq0kjkPyyKWifNpJk1XaOZjrqjPuWeTnfkzNId2YXFsJmknbT58+c7cRwFC8/zGDlyZEEUMDJik6+2FszSHb0uxyZ0323cp/lbv1pJHKZMOErGmrT4E6t8tHN7dxCVpW5wHKdM6MkksjwauezxO5fCXlbiVlPCMhBJo6MXkYmstiYtkXTHVO184b1LovvicefMIzSvDepTokwa7VTA09ekBajogVkNIJtMaknW1rSDwvEwnF8ALRzipLqjZLpvwUI4JNXrjFaQJN/gjy5weVy8EklSGko7IJYSES3hEAipixAugaP2HbFdT0DUOGa0umOydqbrd0OipFnUoX9jtbUFu65ygXx8RluR0gjC4TA+/vhj/OMf/1C6eu/evRtdXV22HlwhwHEcKisrC0IKlBGbfLW1wPNGR8nBPmkrN+3X/K3//myoO+ojabHGnG92/mTlbvzkyjfw1//7AQBdGxad3LiIw2Lv7+2n0qFKvS5l4uY2qZFyNN2RUjoUkhAOSdfOe1p7NZPFw0b2xamThqo1aTb+3vqoHKnDEXiO9XNKgGRtTUdyJE1DaUrdUbGznQ6LMf3ObN9WwiGp2p1WkCT3SOKo0rVifALXVbKIlHIm2bfqpBn3rV+woK/BZO2sNMx2k9RV9ffjTdMd2XWVC+TbMzoWSTtp27dvR11dHU4//XTMnj0be/fuBQDcd999uPHGG20/wHxHFEXU19cXhMoMIzb5amsz4ZByn8sRxarmtl7NQ1SWZcOqK6kPs3M11opei5q0WA5Lvtn5jv/9DgDwj/fWAdD2SYv8PzJmO9PvAKC9W02f9HkEUxW6RJziVKAn0XRKGFltTySSlq6dS72C5jd97c9TcPDQPmpNmo2/tz6li4yfjloCbMXfimRtTS9AiJIMU3VHJxwWXc8wzbltEjHVk2rqJX3tkv0oThrddiCBPpNJ75s4iJwq/2/mpFnV4dHXRrJ2JvdKrzuSaUEvrGjUHYnIFmsPnBPk2zM6Fkk7addeey2OPPJItLa2oqSkRNl+5plnYvHixbYeXKFQCCcKIzHyxda0oIHAc4ZIWv8qnyNKcN9u0KY60hMcQibVHUm6Y6lOgj+e05Avdga0Bf6AOlEjDosTQhZAJMWSINIqdBmQhKfT0URRUieZhkiac3b2eV2aPlJkVdfjQOTSEEmLLoS4dOk+HJPgtyQZW9Pnlyyrv79ZTZqdaduSzkkTqRQ8TSTNIoCQcjNrJeWQV/ZD0h3pSJqqCGzfwosiWqKJ4qmplsq+BQsnTRdZS8bOxHYkkkZfZxp1RybBn3Pk0zM6FknXpP3nP//BV199BY9HWxA9fPhw7Nq1y7YDYzAYzhHU9FHilYeRW+Bx2wWH4/RjhmH7nkj6sp1Rjsb9PZq/6eagBJJ6mIl0RxLV87lJuqP9xf7Zho4qAWq9lsvlnNMAAB2UkxamVOjcJqvftkfSKGGHEOUg6h1TJxcC6EgaPZF1InKplxkn17fLIpLGmlmnB4nAE8h9RBCMToOd9zG1sbMA+MMIiZJpJM0qqpTq+W62D7N0R3q/YUmCh1d7m6WKVjgkmtJI1aSZ7ZsmnessFCOSZq7uyK4rhr0k7aRJkmTqoe7cuRMVFRW2HBSDwXAWenVRoNQdD+hfigunjAFAyXXb+NzRTyYjk3djPRyQmXRHfc2BU05DNunRTSjpVXGAdljsHXN7jzaSZibBr9Sw2Di5CYUlzWRKlCTFnkokzSEJfjq1rcTrUiaIHpcxJczJmjSzdDCANbO2C/3Chxq5dLZPmiGSRjWzNquRsvp8spj1gSPRLLdFNEsU5RRmmEZEquZO0KdaWjiINGmpO0b3TZy0sK6+jeDEs5LBAFJIdzz55JPxyCOPKH9zHIeuri78+c9/ximnnGLnsRUEPM9j7NixBaEyw4hNPtmaVn/jec60XoiLDsNOhyWg61kjirJhgl6mqDs6H0kjkyul104CNWn5ZGdAlcEnEOfArXNYnEx31Kz4885G0vy69KYQJRxCJs6JNC1Pxc5dvapDXOJxISQaJ5Nul/1OsX4iqkR2dBNXJsFvTrK21jtp5L4mmNRnOdEnzUOcBk2UOIFIWtrpjsa6MM0CBPX72eWckucDkeAH1PM7oZo0nbpjMnYmzwGPidiPpnm4UpPGLqxcIN+e0bFIegQPPvggvvzyS4wfPx5+vx/nn3++kup43333OXGMeY8+NZRRuKRr661Nnbji0S/w/eb98d+cBrR4hyhR9UL0gz7qpdmZGqWvDwiJkqFmo1RRd8xAJE2Xjpao05Cv17QkyYrTRiaUbodS/2jhkIgKnYlUuAP9yvy6yGEoLClpSGQyJSTYwypZO9MNwTnOeH4B6u9ta580g7qjVhyGwNQdrUnG1vo6T5IhoImkkQUfO0U0ZBLZIZE0OkpM16TZG0kTqX0odWEBo3CIJpJml5NGReDJb+o3ES1JNJKWjJ1jpTvyJqqpLEKdO+TrM1pP0k7akCFD8P333+O///u/cf3112PixIm49957sXLlSgwcONCJY8xrJElCfX09JBsVnhi5iR22vvEfX+OjFbtw1h0f23hkRjROGuUoaSWNo6/bGknTpTvGqEnLhHBISLdSqjgNMcacz9c0PclQI2n2Ow2ANpKmlcF3VoK/1yLKARgVLWOJOqRi544eeswygiG1zxLB7UANINmPzxOZTPpNanYApu5oRbK2to6kZVY4JCzKhigxYFR3VBdD0u2Txilj9JulO9I1aTad32Y1aX6zdEfBfDpLO2nJ2lnUpTtqhENYTVrOks/PaD0pZQy7XC5ceOGFdh8Lg1H0NLb0ZmQ/QWriSissmhdD27hfnSNg5hiUZlDdUZlEJxlJy1doZ0iJpDmQfgfonTS1dsYsLcvO31sf5Qjo6i/p/9t9jnX2qpG0sCghKGrPL0B1nNKpldFD9lPiEeAPipbpjkzd0R56A3onzaimKThQexhW1AZJuqOkUT+k4Tg11XlQnxLs3t+TRp80te6NRJDM6sI4LvK6JBsX31LFPNUyco0n0sBbvzCYDKoEv3YhSx+pZII8DKdI2kl77rnnYr5+0UUXpXwwDEaxU1nqxp5W5x01+sEViWZZp6LZ+eDRPzDNHqClVJ80WZYdbUgZNKQ7OuOw5AI8x2nqY1z6mjSbI2kdGgl+Sa2dcTqSpp9AU1EPly56aLed6XTHsCiZCoe4XeoE2y5IGrHP4wIQVK4regINsNoZu9DXPQZNImluqr712Q83YPSBVTh2wqC09qtE0qJOmlUza0BbizqoOuKkpSrQo2ZaqM3Re00k+Ml7gmFnnDQlkmZSk2bVGy6dxRCScu/1aCNphlpPJhzCcIiknbRrr71W83coFEJPTw88Hg9KS0uZk8ZgpEF1uTcj+9HWpEmmD3onlOCCOuEQMyeN9EkDIpNot8s5J01JdxR0fdIKcEW0xCto0jjJqr9zNWm0cEjsmjRbI2kW8uiR/enTWm12THXpjuY1afY7xeS7SqL9/pT0O4u0NzaZTA+rc0wbJY7Y/NsN+5T+kJufOy+t/ZJ7MYnsWDWz1uPzprcwQCvCkiGapRxG3hM/lTilfQu8WpMWMIqW6M/1cp8LXf6woQ46GYzNrCPHwukyK50Q2WIwgBRq0lpbWzX/dXV1Yf369TjuuOPw4osvOnGMeQ3P86irqysIlRlGbOywdVWpW/m3k6kTdJ2O1YPeiQadeqfMbJWTRNIAraS5ExCnkUjwuxJUd8yXa5qOIvk8gjIunuOUlWeXQ33SNBL8knlNmjKhs/EcM9YLGdMdE6lJS8XO1pE0tV+UEz3agoqTFrl2giZ9u4BIChzA0h31JGtrgwR/2Ph7x3KaUkWtSYtG0uhm1hb787oFZUEmXeEQl8ApYyTpjh7B3EmzawFEleBX1R2tIml00kXfysiCZ1BTR5acndWaNG26oz61kixosnTH3CCfntHxsGUEY8aMwb333muIsjEiBIPB+G9iFATp2rqiVFUkoiMRdkNPXCVKeY+OpHFKapR9+9U7ZfrJjlvgUVaiOqpOKzzqIx18gpGdfLmm6Ropr1tQRQao6KTat8ve37qjm3ZYzFNqlTQhB4VDyDlGO6bkPI/nrCRrZ21NmkUkzWX/761E0jwkkkbU71jtTKIkY2tj3aPx3NYrawLpLzqRxQxaOERxYvThnSh9K7zKeZ+q0qSyuMNzSrTQb5HuSJy43z/2JX7/2Jdpn2vamjSdsqRFFA8A+kSzUgzKpwnaWZZlg7oj/TvQsHTH3CNfntHxsM3NdLlc2L17t11fVzBIkoT169cXhMoMIzZ22Jpe+NnfEbDhqMzR1KTRwiFmqWi2SvBbpzve918/xX2X/RSlXjXqYGePIT2ipEqzk5Q/suIcT90xX65p2mmgnXFa4MCJ9DvAWt3RrE+avTVpiUyg40dMU7FzR08iwiH2q2mSSE6JJxJJU9MdWTPrREjW1lbNrDUtTEwiW929YcO2ZFD7pJH7lFrraRVJ61vpVc73tCNpvEkkzS1o3kt+g/U72vHBtzuxcVdHSvtU962m7hLnyCySFnmP+nefCmMkLRk709eIR6fuaHTSot/PFj9ygnx6Rscj6Zq0t99+W/O3LMtobGzE3/72Nxx77LG2HRiDUYzQE7d9HX6MOqDSkf0YJfiNyntOTOgM6Y7RySTHAWf/YiQA7Sq/kwqPtMNIJj2JRtLyBU36nSRrBAAITkjCA/p0R9k0LYv8285zTD+BViJpvDHKYbezQv/eomQeSfM48HuT/ZDao4CFBD/vwMJLMRJIoJm12ySS1tUbQmVZ6v2bjOmOlGqqlZNGR9LSrUmj+qSRbfpx6mvDNu3uwEFDqlLaL72fSBQv2syayP9bRIqByLgBY2/ORKF/K30za726I1dgzw1G7pC0k3bGGWdo/uY4DgMGDMDkyZPx4IMP2nVcDEZRQqvN7Wv3O7YfTU0arRBGPXDp55BdKotkxV89DqN0NcdxcAs8QqLkaLoj7RCTSbQaYSmMh60m/S4sKZMMl2AS2bGzoXQwrHGC6bpHswa0mZDg1zQaTrNvlBVd1O8dEiVlgug2qVWyNZIWMk93NDazZpNJO9Dfl8yFQ4z3y05/yLAtGQzCIZKkpEDqo6aEfhVeJfKUciRNVKNZ+nEZ0x21r6/f0YZTflab0n4j+zb2aDOT/we0CzFmkbRkoG2s75Nmqe7IriuGzSTtpBVC+DDTCIIQ/02MgiBdW9MPlEylO4oWwiH0g0iSZcs+NMnt1zzdUf9gdwkcQqLDkTRNY+fkImn5ck3TTkNYMldYdEKOvr1bOxkNi5KSukqfVxmR4DcR0RCUSFrs8ytZO2vUHSmn2GNak2a/cIhPn+5o2czatl0XDMnYWn9fIr+/YLL4QdOVbrqjrkZKFM2j4zR9K7zY0xZp65JqTZpZrzKCQYJf5yyua2hLaZ/6fWvq4YLmixC0k9y3nETStLZK1M4iZWN9TZr+UaimOyb01YwMkC/P6HikXJO2b98+dHSkl2tcDAiCgLq6uoI5YRjW2GFr+uHvbCSNrkmjFMJM0h0B+ybR+tQTq6a7TikOao9FnUCTKKESYYkxec+na1rfXNms1YI7gfqsZNGnHIY1fdKcleA3qDsGreuFSC8+M1Kxsz691FyC3/6aNPJdpJ5TX2tJYOqO5iRra4OTZhatNXGa6EWTVFBr0uhm1qoDZUbfSm/a15lST0qlOxLiRdLW7mhLaZ8EdQGRV5zggEUkjVaJ7VMRSSulszeSsTO9aKUsrFhF0lgacU6RT8/oeCTlpLW1tWH27Nno378/Bg0ahD59+qCmpga33HILenp6nDrGvEaWZXR0dDA1rSLADlvra9Kcgl5d1EbSjOqOgH0Kj8ZImvlDz+1AdEeP2QRaafYrW09o8uma1tRIUb3K3CbqjnaKtOgdkLBmxZ+KaDlQ9+i3Sneko4e6KLEZqdhZ7xSbnWN2Ry4lSVWhK/Fqk2OsJpP5cO5mkmRtbVAMDBsjl2ZCHuk6aZJO3ZG+n5pF7gDgp2MHJKxmaoWmobRuXJ4YCosAsGtfj6axfar75ulm1kFjGjGgrRUkPUfp7JRk7EyuKTflmJIUSH1NGpPgzy3y6Rkdj4SdtJaWFhx11FF49tlnMWPGDDz44IN48MEHcdppp+Hxxx/HL37xC/j9fixbtgyPPfaYk8ecV0iShC1btrA00SLADluHspDuSNek0Q8ffbqjHZBVTV+0dsZMFQ1ITH0vXZQJtEWKktWEJp+uaX2NlFmrBRK1DNr4W+vtJkpq6h+dEuZEuqO+BsVM6ZA+BitnKRU7651icixm6Y52ndt02iS5rggG9Tum7mhKsra2SlXVqqYap1fdfnvVHc16ABLev3sq/n7tcTjyoAFpN5hWFBYFzpDOGE84BADWpRFNo0WtlGbWJgsvgPbaL9X1DASSszOdGq44aVbqjkqkMsFBMRwln57R8Ui4Jm3u3LnweDzYvHkzBg0aZHjt5JNPxu9+9zt8+OGHzEljMFKEfvjvdzLdMUjXpEkWPazU99vlpJEJc6nXBX9QNK3lANQJtaPpjmEiIW10GoDCKALv1K3ck9+btrNHiaQ55yhpGqabiCvY6qTporVmEzr6GMKipNScpEunzilWI2nGZtZ2pTuaTUzVfTEVOiewcuy1LUzM1R3TQRUO0QrERPantfXYIdUYO6Rac1ypNo3XNJTWnVOGmjQT53RPW+rPMnLMPN3MWkl3tL5uyX09VeEQcj8UBN6gjmmMpEX+z9IdGXaTcCTtzTffxAMPPGBw0ACgpqYG999/P1577TXccMMNuPjii209SAajWNBE0jozU5MWSYMz9tqh1RztmtQRx4hMJq1q0kg6XibUHTWpaPTkvQBW4fSTQrOCeyfq//SRhjAdxaMXAhyJpMWX4KePIdXogh5ZlrURalGNHppJ8IdEyZZ0HPqeoY+k6R0F1szaHqxSg+n7h14eHrAh3VGR4Nc6K4B1nzSAWgxJV4Kf5zVjBGIrLBL8gdQjiHSatH7RwUosBaCus1SdNIlkWsSPpHFKM2t2XTHsJWEnrbGxERMmTLB8/ZBDDgHP8/jzn/9sy4EVEj6fL9uHwMgQ6dqanijrVersRCvBL1FRDiqqRDtpNjx7ZFlWohylvqiTZiLqANB1O5lNd0w0kpYv1zSdfgfQTppR4MBOtUGzmrSwaPy9nRAOMaY7mknwU+mONtk54nSpf4uirBGnUfYtqHWPdjinQSpSqE89M/RJY+mOliRrazO0CwHORdI8SiSNqkmzkOAH0o9Y0+q/+nEZ1R2NjlNPOk5ajHo4s5RSAuklp78fJGpnNd3RLJKmfa9ak5bQVzMyQL48o+ORsJPWv39/bNu2zfL1rVu3YuDAgXYcU0EhCALGjRtXECozjNjYYWt6cqtv/GwnVhL82nQdeyNp9MOyLE4kzQkxC8PxEHl0N52KRqfBWav+5cs1rZ8c+U360rkdcIiNNWmyJmWK4ES6o76Rs7IQoHPGFaVDi3Ena2d9mqUm3ZFuckxNau34zTUCB4ZIg3mUg/loWpK1tVV0xupeQuhMW4JfG0kjUWOOM49gEdK9zmj1X0MkTZ+qbjLudBYclXo43qQezhXDSSPpjnRKaBJ2DoWNipZB6negIYfF0ohzg3x6RscjYSdt6tSpuPXWWxEMGlV6AoEA/ud//gfTpk2z9eAKAUmSsH///oIoYGTExg5b0+l9/gw5aWFJ1hRnE+i0+1RrGWjoh6USSbNUdyRS+M499MikWqPuSLcdsBhzPl3TesdBcWAcVBsEzCJpqgS/mXCIE5E0fUqtfnJJJnxW51iydtYvqoiU6qKZuiNgTzqvEq1zC4ZJrDGSFvk/m0xqSdbWYZMFB8BahIiQdiRN1takkVtUrCgaYF8kzSyaVeLVidWYHItdkTS9I2qlaOl1C6aRtGTsTCvhxhUOYRHqnCKfntHxSNhJmzt3LtavX48xY8bg/vvvx9tvv4233noL9957L8aMGYO1a9fi9ttvT2rnn3/+OU499VQccMAB4DgOb775puZ1WZYxZ84cDB48GCUlJZgyZQo2btyoeU9LSwsuuOACVFZWorq6Gpdeeim6urqSOg4nkWUZO3bsYDUARYAdtqYnt8GQPTUrZgQ0EvzmE2iOU6MNsg0PnwA1thKPtvA9m+mOHt2Y4ymh5dM1rXcceqPy9PTvraQ72hi1NBUOUSI+DguHECfNp4vWWtSz2GVn45jNJfjpibwdvzm9D/3kUX9dqc2sc//czSTJ2prcl/Q1gF5KhMhM5bDLb09Nml7oJlY9WuT1qAR/ujVpAm9wwsq8bs3fpjVpwfRr0iLKkrHr4QglHoGKpGkl+BO1M62Eq9ZyRl6zqknLh2dCMZBPz+h4JOykDRkyBEuXLsX48eNxyy234IwzzsCZZ56JW2+9FePHj8eXX36JoUOHJrXz7u5uHHbYYZg3b57p6/fffz8ee+wx/P3vf8c333yDsrIyTJ06FX6/KqhwwQUXYPXq1fjoo4/w7rvv4vPPP8fll1+e1HEwGLmC3ilxKuVRk+5IRdKsJ3Xp7zMYVNUU3UqfH2MqWuTvaCTNRsVBAGhs6cG8t9dgf4dfiXLQ6o6AM45DtrAS0TBLv3OyJi0iwW8WSYtOHm18mJKIrZpSS6LE+nOMRNLsGbf+Wg1TEvz6XnzkHLNjEUJRKXWZCSvom1kXzrmdTYhd9c6SlTNOsK8mLX4dGE3akTQi3mESSSOLIcqxmDiMPWmlO0bvG5xJPZyFc+rzChqBnlQix2ThkpbgJ+jVHV0ZyPxgFCcJS/ADwIgRI/Dvf/8bra2tSkRr9OjR6Nu3b0o7/9WvfoVf/epXpq/JsoxHHnkEt912G04//XQAwHPPPYdBgwbhzTffxG9+8xusXbsWixYtwvLly3HkkUcCAB5//HGccsopeOCBB3DAAQekdFwMRrbQT279QRE+T1KXaUIYnDSTZtYAeRjJtqy8k0iaxyUoD1tFgt8ibchOxwEALvnrZ9i4qwOrNu3H9KNqI/uyaMYqFkCqhD664w8ao0pO1KTp7RYSZbXNg0lNmiPpjtHJo9mY6eOwS91Rn1pKR9L0DX9dAg9REm2JpNGOoF7N0dAnjak72oJVJM1DScKbN7NOryZNr+6o7svZdEeykMGb1IXpnTSz1gO9dqQ7mqo7WkXSXJrfKBSW4PUkV58UpupJrfqiEcxaIjAYdpDS7K9Pnz742c9+ZvexaNi6dSuampowZcoUZVtVVRWOOuooLF26FL/5zW+wdOlSVFdXKw4aAEyZMgU8z+Obb77BmWeeafrdgUAAgYDaKLijowMAIIoiRJEU4nLgeR6SpE05I9vJ++Jtl2UZFRUVhu1kBVmfM2u1XRAEyLJsul1/jFbb7RoTz/PgOI6NSbddFEVUVFRAlmXD9yQ6Jv3ktscfQkWJy/YxGaTCFWcJmvfT4gqpjokcI4lweN28UhtDqzvS308mOMFQWLM9XTtt3BW51v9T34STjogs4rgE9fsEQVAewKGQqNlOxiSKIsrKyiBJUsxzMheup6A+3TGgTXeUJAk8Fz33wlLkbxuup5AughcOi5o2D8r7o/sQo3L0dtwjyDllllKbyDlGj6msrEx5LZ6degPaKElIlJXfwUVdV4IgwO2KXIOBYNj0HIs3Vvq+R+TNPS4eHKf7bHS/5P1A5PVw9Hpm9/LIdlmWNbaONybipOkjaS4BhnObpqs3pLFH0mNSVHi136s/t/VjJS6FKMkp2YlWNdT7YD43pxkT7b/wXCQLoycQTtlO9L6NmR6R/+vH5PMIGoe5NxBSbFNRUWEYv9m5FwxFriuXiwcH7e/CK89FkpmA6GciUTtZTuy6KdTrKdtj0j+jUx2T/vVsYP8SvU00NTUBgKEv26BBg5TXmpqaDIqSLpcLffv2Vd5jxj333IM77rjDsH316tUoLy8HAPTt2xdDhw7Fzp070dLSorynpqYGNTU12LZtGzo7O5XttbW16NevHzZu3KhJxxw5ciRGjRqF+vp6jcHHjh0Lj8eD+vp6zTHU1dUhGAxi/fr1yjZBEFBXV4fOzk5s2bJF2e7z+TBu3Di0trZix44dyvaKigqMGjUKzc3Nmt/BzjFVVlZizZo1bEwmY+ro6Eh5TPpJ9Q8/rkFNtcf2MdFOmj8QxN59+wEAsiTpxhq5EXZ2dmHfrk0pjQmI2CkQjlxbnCyiq6MNANDVEznecCio3a8UOb5du5tQX9+R0JgStRMAeD0COrt6AQC93V2or69XxkQe/GvWrUNHs9dyTI2NjTl37umvp+7egOazu5uaAQABf2Tszc3N2LplOwDAHwhh586dtoypsyvyaCGTtI7ObvijTgwPKGPatTNSPyxKMvx+vy33COIsicGofaN/h4Lac4xMvHbs3IVAa4NhTFu2bIHf78eaNWsAxLfT2vXaemlRlBCI1uLs3rUT9fXtypjIJHv12sg5ls59b+OmyPvDoQC6OtVrBQA6Wveivr5eGVPL/sh13tLSivr6enYvj44pFAqhu7tbsXW8MZFFLVnUCqm1t7agqWG/+tvwnCZ61d7lR319fcpjIt+1fat6TAAgSWHNuPR22he9v4uSnJKdOju7AQC7djSgT3WlZt87tm1GqM2jjCkQ6FVeK/cJ6OgV0RsUU7ZTa1s7gIhzKEva5+OepkYAowxjghTUZEh8X/8jqkpdypiamprinnubt0Ts4hI47NvbrNkvOQ4ypt6g6ngEQiI2bVhb1NdTroypo6MjrTHlgr5FzjppTnLLLbfghhtuUP7u6OhAbW0tJkyYgMrKyA2I5O4PGTIEBx54oPJesn348OGa7yTbx4wZY9hfU1MTxo0bp3jpgOqx19XVad7L8zx8Pp9hOxA5cc229+nTB9XV1YbtAwcOxIABAwzHmO6YyLGPHz/edHuxjkmSJDQ1NWHAgAEpj0mUtM7E8JGjMebAKtvHRKdmcbwLlVXVANrh87pRV3eQ8ppL2IxAKIyS0jIcNCw9OzVvjEwUykt96N+/H4AOSNGy2NIS7W9Z8ulXAIB+Awagrm5kQmMCErFT5Pct8QjgXZGC9/79+mg+R1KHRo8eo/z29JgkScLevXuVBaJcOPcI+utJxnYAaoSnrKIaQDuqKsuVMR08zgdgG8DxGDJkiC1jWrUn4tCXeF3o9ofh9ZWA65QAiHC7BYyNHuM+qRHALkiybNs9gmQvDhrQB9jardTClZVqv9/j3gEgiIGDalA3Qk3ZJ2MaNWoU9u7diwEDBkQiBHHsNKR2OIAGlHgE9AYjkUOSzTh61HDU1anp9xGp9hBGjByNg4eqY0jlvnfAHg7ATlRVlKFf3z6az40YNgR1daOV9w8cOABAIyorq1FXV8fu5dHtHo9HOR76OW02JlmWldqj6soyYK+6EHLA4EEoHa7a2SVs1DhpvUFJ6Smb7JjolOBDxo8FsE352+fxaI5Tb6evGtYB2AdRlFOyk8fnA9CLkSOHR8/ddcrrPzlsAvpV+pRjrywvA9AGAOhXVYqO3k70BsIp26lscTuALrgEHl6dSMmIYZGUdXVMkft7n8py8DwHt8AhJMoYPWYsavqWKs/o/v37xz33dvp3AtgNF89jcE0NAHWR0u2OHAcZUyTaF1mk6Q2KRX89ZXtM5BldVVWV1phIll02yVknraamBgCwZ88eDB48WNm+Z88eHH744cp7mpu1KxzhcBgtLS3K583wer3wer2G7YIgGPoq0Dds/XsT2S6KojJxN/tMot8DRJXnTLZbHWOy25M5Fru2F9qYYtk63rGLkqQIdPg8AvxBEcGwcR92HLu+Jo3s1yXwmvfzSg2L+fckYw+lJs0tKHVQpJ5Gv1+yCipJ5vtN9zfweQSlD06kRo7qbxQ9dhmc7rdQx9Tc3KxE+XPl3AOM15OxsbNaZwFEjt0brXkMhSVlLOmOiThGxEkTJXVi63aptnZHU5IkSba8FyR7jyALEOUlkYkUSbPUn2OkvkWSrb+f2Jl+3eo3ID91qc8VcdIkNY3Y63bp9s2b7juV+x5xSj0uwVCjU+Zzm+5X1o2D3cthamuzMYWppuX6emGfx6WpD3MLvEZJV5KBoAiURu9vyRxjiFrxL9E5K/pzW/895DoTY1xnsexB7pU+j9tQa1dR6tWeY1SaYZ8KD7Y2RdKsU7UT/WzSn98et1oKIAgCpkw8AB+v3I3LThkXfV1ASAwjLKljTvQZTbLyXAKv/H7KsUWfi+Q7BCHyTAuJEvxBEX0rjPPLRMZKk+/XU7bHRD+jUz12q9czSexq0ywyYsQI1NTUYPHixcq2jo4OfPPNN5g0aRIAYNKkSWhra8OKFSuU93zyySeQJAlHHXVUxo+ZwUgHWsmQTDD16Y92YZDgt2rSydkn2U3XpLl06o5W0uF29JEiiLqahWJQd9S3OFB6hpmoOzrRJ6002kMpTJ1jtPCAI82so2Ms8eoEDQwiGmRxxJ59k/2WRYUUwmHzPmmA+vvbIYxDriuP2ziJ1TsRajNr67YDTS09aR9TIUML7OiFQ/TCFmaCHqkqPNKRNI9uv3El+NMUQ1IEcNy8oZem/jegnyHVZRFnJS11R6onnaEPoEs77nnXHIv/PPRr/OLQyMK+R/ecSQZybbpcxv5senVHAIowCamJZTDsIKtOWldXF1atWoVVq1YBiIiFrFq1Cg0NDeA4Dtdddx3+8pe/4O2330Z9fT0uuugiHHDAATjjjDMAAAcffDCmTZuGyy67DMuWLcOXX36Jq666Cr/5zW+YsiMj7whSD/+KqJPmVENrQzNrqmEojZ19lZSmuy5BedCTbfrJjROKg21dav2IzyOok1uDUpq9qn/ZhPy+xGGJpe4YEu3ry6eq30UdFlHW9Dsi8A44afpm1gSjMpx9Mvhm+5VkWbnO9E6ax2Xf+R2iVOj016++0bCy6GLxe//93bU49rp38OKnm9M+rkKFXjiiHRSPm1fSrghmcvSdPak5afQ14tU7/XEk+NO9zkibB7fAaxzPMq/LMGaNk1YeqafuTadPWvSYeZ43OKMewbj4cUD/MuVvIuyib0WSCEoza5PryqwXHDkX/KH0FDwZDJqspjt+++23+OUvf6n8TerELr74YixYsAA33XQTuru7cfnll6OtrQ3HHXccFi1aBJ/Pp3zmhRdewFVXXYUTTzwRPM9jxowZeOyxxzI+Fis4jkPfvn0NNzJG4ZGurcNUalp5ibYRr53I1OQRiDgjYZMeVoCq7miLBL8SSVMl+InToH/oOdHMuqVTrR0JhiXN5JYmXnQnX67psCgpdivzudDVGzLtk0ZPJEVJNp1YJgtxWIjCoihJiow3vW+7I2miJCnfVWaQBjefTNplZ3J+05LkvQGyEGAecbFTgt/jFkycNPPfwOrnfuCVSMH8bfO/xW9/OSrtY8sXkrE1fZ+m1R31NgbMJeJtiaTp0+/iSPC70nXSQmokjV680svvA9r7SXVZ1EmzoU+aizc2s3ZZNLMmkOgWue8lZWcqTTqRSJrPrd0XI3vkyzM6EbLqpJ1wwgkxV245jsPcuXMxd+5cy/f07dsXCxcudOLwbIHn+aSbfDPyk3RtHVKkhjllNd6JG34wLGnUocOSpDSz1j8E4628J7dfY1qWkn5nkcZiZwoe7aT1+MNUCo8+XSd2Gly+XNN0PZpyPoWMkTR6IhkWJcveQ8lAfltfdL/BkHrO0Y6EYHNzZVoQxxhJ00dMY6d5JmtntYm2Wi/US8nj09jZQFzTJ03nYJfoUtGUlhpxfu+aPiVpH1c+kYyt6fs0veCgtzFgHknrsCGSJggceI5TF2G8sady6UfS6LRd62uM3hcAVEdrs9Lrk6b2aLNazLNC7V9GviNxO9MlAFYLPDQ+D3PScoV8eUYnQs7WpBUKkiShoaHB0BuCUXika2sysXW5ODW/3YFImr7OTZbViYd+kqf207Jhv1RjXyXdMaw+gGmcSHds6aCctEBYN/FQiRdhyZdrmrYzqQ0j9RKamjTq33bVAJLzqcRk4uIySXe0q5k17ZjqI2n61W83SWu1sGOydiYTQU0kLWie7lhdHpm8PvLaj9jX4Uc6KIsfLt6w2FHiMY+kmS2O0ttq+haXk5aMrcPUfZq+X5o5aXRjZ/J6Z4qRNI2TxnOaeix9xFSPIlSTppMWSVWn0h3NImnU632i6Y7BsJTyvVxUIlqcwSnTZ0Ho8enqxJKys0gJHemeT5zJbtV0R+akZZt8eUYnAnPSHEaWZbS0tNhW68HIXdK1tSJkIfDKCqATq3Jm30kmmPpJHkkXsCXdMUinO2odIWO9kP1iFnQkrTcgWjtpSk2a+Q0+X65pxQHmOEPaDx0xpSd7dqTf0d+jbygNaB1Eu9MdyX44zhghNYg68LHPsWTtTJwlOrpAxqU/x26YcQj6lHvw47ZW/Ot9bduNZAnFiKT5LGrSzH7vVqpmc1Cf0rSOKd9IxtZkIcMtaEU09AJEgPac61sZccw7uoOG9yUCcbA4LnJfpu/VpV5jqiUNWQxJ9X4aohbY6HOs1Oc2vJd+vSqa7gioCxbJotakcUqtNsHtMka0aNRIWmTfydhZEToSjBE8wSzdkdxj00jtZNhDvjyjE4E5aQxGjqBE0gReyW9v7Qrim3XNKatymWG20hc0SYMDIg1EAbvSHWmFMO2tRx/lUNUd7Rv3fipi0RMIWwuH2JyCly3oOhKy4uw3UXcUeF75/e2KXJLvKdGlWQLmwiG2RdIocRpDraGFcIjdqZY+j2CM2unOsUNH9sN1Zx0CANi2p9OW/XpMVvz1kbRY6o7bqeMogFIOx1An79paJbOoDn2d9a+M1NKnm+6oyr/TzlKcSFoa15ksy5bRWrN0R9pxLS9xK9dCqimPak0ajwMpURAAcMeRSFfqxNJRd0xaOIQ5aQz7YE4ag5EjhCm5brIC+NCr9Tj/7k/xwbe7bNsPiabQD1ir2jA7Jfhp4RC9dLJB3dFG9TsCHUkD1LQjy0havjtp1MSKRI380YmSIXJJagBtiqQRh5xMXOjTx0qCf29bLy554DMsXpn6uU7G7DWRo9ef22okzZ4xq+c3b3k+0wyM1n01t/amtV+tcIh2P/oISyynePueLuXfTEbcGjpySZ9j+sgtoHVY+ldFnLR00x2JDenvjpfuqETSUljsEyVZuX710VqzdEe6h5XPIyjnYE+aThrPc6gdoHXS9M8RPd5odDOV81kRDjGphTN10phwCMMBmJPmMBzHoaampiBUZhixSdfWmkiaruB/x94us4+kBHmI0A9YMtEzRtJiq8ElA12Tpp9M6v9W0h1tchoAYH+H1kkjkvyGSFoCqn/5cE0HlP5ZqlNsFkkDaBl+m2rSdOmOBJ7TTnjo3/qO//0On//QhMsf/iLl/arRQ8GkZ5X533bZOUj/3vqmuyZRlkHVUSetLb2atBAd5dCnO+ojaUSt1eSy0jhpIfuuu3wgGVuHLNLgTIVDqG39oumOnT2ppTvSESUABin8WKRTk0bXeXrcgsY5NI2kUeeg1y0oDmTKkTTq964u92ieW/Fq0ry66FYydlYipia1nrH6pDEnLfvkyzM6EZiT5jA8z6OmpsayQzqjcEjX1iGqUNmrq2/o8dvXe4WsKtIpMgGrdMfoTU62wUuja9KM9UHmkTU7m1nrI2nt0doQowR/VN0xhupfPlzTdBqcW1fjZ0z9szeqpDhpcXqV0ZGdzY3ppf0BlGPqMoukcaZ/W9UeJmtnMpmlay4JsSJpe9t700r3pBc/aKfBJXCG/ZKxiCaRcTrtMpW+UvlMMram+2fR55SZjen7Wj+b0h2VSBp1jsWLpAlKOnPy5xldp6rvk2aWZkmP2evmlV59qcrwK2meHAeO4zQpj2a/OY2+Ji05O1tL8MdSd2RR6OyTL8/oRMj/EeQ4oihi8+bNEEV24RY66dpa7dvFwatbAbfTSSOrij6P2lfJSjiEPIvMJnXJQqdlGeXQM6DuaOGk6Qv+leiOxZjz5ZrWRi7Nf1+C3Y2d1Uhagr3KZBnd/tQmrzRBC4EDwNhLSogTPUzWzrSDqP99zUQl+lf6wHGRyWBLV8DweqJo0u+o31cfRQPU69ls0UUbScvtc9tukrE1PXmnzymzPmluk5q0VJtZS7qatHi1YTTp1H4GKTEel8DFTXcUNNFFGyJpknZh6cB+qqhNPAl+veOUnJ2tm1mbBWjIvY7VpGWffHlGJwJz0jJAZ2f6K8SM/CAdW2tr0rSXZncafWb0kHQMH7XibxlJs1HYQVOzE2dl0om6MP3kSImkGRrDxndY8uGajpV+Z+W0BW1KLyUTWb26oL75LH1+2bEQQcbs9ZgIh1hEa60iaUBydqaFWuh98RxnSOcFItd532gfqb1tqdel0fLotNOgT5kG6GbWxutq575u5d/Flu4IJG5rTV+6OOqO9P2UpDt2pJnumJJwCLmnpVCTRi8CRFQl6YUAk3OMOge9bgGlUeelJ91IWnS/g6j2EIlH0tRxJ2pnWt0xkT5pLN0xt8iHZ3QiMCeNwcgRYtWk2RpJC6qRNLIaqwqHZKImzZgOZpxAR6McNtakkZVcsi9lsmUxmbdLcTBbaPrSxUm/s1uoJajrk0YwphyqjcO77XDSYkQPrf4O2yz/79U5xbEmkgOjdWl7WlOvSyOOqd5pMKvX4SyUS/3BsKZms9giacmgRli0k3czO9PRrnTTHaUYwiGJSvCnck8LUPdtwOiE6aHl6SPpjjZF0qK/JanlBNReh1aoDaaT33fIQsUTMK9JU4VD7HtWMxjMSWMwskhTSw9+eeN7+Me7a5WHAq3uSEhVGcsMPxVtIM4SiQIYUsLIpM6GybtW/S6xyI6d6Y7kNyQr2gRjumN03/nupIXUGql4v7fdfemImIUh3VGwjqTZEcWjJfgNNWkWf1vVHia9b8pBpPs3JeKkpRNJ61XUWoW4ToNVM+vG/dr9MyfNmrCFNLupcIig1o+RnmH2RdLU/cVtZp1GP0K6Rxr9XYC5k0bjddun7qhE0vqoTlq8dEezSFrC+6WaaCclwc8iaSnz+Q+NeGbRevywpSXbh5IzMCfNYTiOQ21tbUGozDBik4qt71q4Cg3NXbj//37QPAx9uoefHVEGAll59+mUugBjpIOk0djhJGqV98zrg5TjUFIO7VMbJJNoUhtCMEjwx1l1zpdrOkBU/8zk6C1+b7v60lkKh1hFs2yys6poaYweWkfSzMecrJ3pSBqd3mhWt0MYWB05F/ek46RFr02fx6VT1jM+3q2aWe/a3635O1hk6Y7J2DocpmvStPVXesh9zS3wqCyLNGLuSlc4JHqM7iTSHfk0nDS6lQegTbM0O8foe4jHzcNHImmpNrOOfl9neB++b/kPqivV18zSDmm8Oln8ZOxMZ34kFEljTlravL9sB+5auApfrm5K63vy5RmdCMxJcxie59GvX7+CUJlhxCYVW/+4rVX5N71C62gkjUp3NIopaG9qZb7oxMIGJ1FTCxcnFU1Jd7TJaaBTbfpVaZ00vTx6vJq0fLmm1WbdRjVNQ/qjzS0PlJo0fbqjVWqpLrKjj/QkijqhjC9Oo9akWat4JmNnK/n/2E5a+r3Seqm+h7RzaJbuaJW+vHt/DwBg+KByAOq5UywkY2s644FOZzSLXBJHyuMWUFkaiaR1+cMpZQiI0cUEs0haPOEQJWqcknCIOl5Am8JpFkmj9+FxqZG0dNMdG3rWoifcgb6Dm8BxwMjBFXEn4UqfNErdMVE7a56Tuv3kSjPrtq4ANuxsz9j+nIakAleUuNP6nnx5RidC/o8gxxFFEevWrSsIlRlGbFKxdUOzqqhGF2h7M1aTFttZIhPMrhQbsNL0RnP1ExF1sDvdsYdq4lwdTTsiWKk7WkXS8uWaVtU0E4ikKTVp9vZJ09dJWQnT6Ek1kqPK4BsjaXrl0ngT12TtbJXOG8tJI6lbze2p16QpkTRduqOZkIXaJ00XSYuKhoyoqQBQfMIhydg6RKn+8ZrUPzPhkMg2j4vXTDxTuZ/qVQ5pWyeq7piSBL+oTXfk46Q70vdsnueUaHqqC42qqmV0n14Zq/5+Ft658+S4n1XUHUOqumOidibPSa/HuKhoNvfPRiTt949/hV/99yK8+vmWjO3TSYi4V0Vpek5avjyjE4E5aRnA70+vWSkjf0jG1voC4xAl7ax/+NmZ7uin+pUZBTy0t4TyEpdt+w9oIngJqjva5DSQCUKJ12VIDTKIaCQgWpIP13SA6pOmd8b3BhoQEHuUv5V0R5siabQCHu2wxFsUIPSmWHwfiJlSa5VqaY+d6fQobSTNesIxIJrumFYkLaBG0rTNlRNXd9y1L3IujBwccdJCopT3wjnJkqitw4rAE6exc6yaNLeLh9vFK0I6nSk4aQYJ/mQiaWlJ8KvXlJ54kTT62FKNpIUVwZTI3wLnQnmJG93yPmzprIckW1+/+j5pQOJ29lNlAYY+aabpjpFxZrJP2jdrmwEAN/9rOTbuyv+IWmdvpF6TRJ3TIR+e0YnAnDQGI0us26HeVD1uXluTpo+kOSAc4vO4DE6ZPvpQHp1gdtsQSaP7sxlq4SwiPXalOxIns8zrMkxo3IL2t1ZWfvO8tkCT+qebQHaL+7HXv0v5m7QhsLsmzS1oI1pWEvx6Uq1foetn4jazTiMFzAxtiwl13+UxImkDoqm3tLJisqgLENrz2Cz9jrOYrO9uiaY7RiNpQPE1tE4URfVPr6Zp4hST84A4cJVEPKQ7jUgaSXek9h1POESJpKUpwa+nrMS4X73IlBpJS+18kkycNADY0bUBe3ob0BlqtfpoWtGtQJDUeppF0mKoO2Yo3VGWZU2/tlc+y/9oml3pjoUEc9IYjCzx41ZVwSgYklQZfIEzpM6QdMdv1+/FP99fl9YqdyBIp2XFjqSVRW+WdqQ7kgdlicfoNFjWSNlck1Zi4qTp08IUNTIbo5fZwKpvFxBJHQpLqk3dcerwkoVOkaL3nWgkzZ/ihI4es+HctkixtSvFU1OTRp3fZTEmHBUl0TqlNK4v9bqKHSEGVMEDg5MWTXccOVhVZSi2lMdEIeeLvsmxWSRNoGrSAKAymsaVisKjXoKfJlZKLZBeWxG9cAgAXDrtIJw48QD89KABhvfrVXHJsaXarJ783uTRpLSRkCPfF5atv9cskpYodFmAQTgkRp+0VCOGydLtD4MOiG/Y2QFZlpXaxXzErnTHQiL2lc1IG57nMXLkyIIoYGTEJllb6wt+1ebKxkhaSJQQDIs4765PAADDB1XgpCMOTOk4NQXRFg1+CeoD1j7hEK9HMMitl+smsuQ46re24r1vGjD9qKFp7Zs0Ay/1mUTSdJOr0mj00Cp6mS/XtEYS3pD6B4iyOnFx2ewUh63SHS1aPOhJPd0xhnCIVSQthkBMMnbW1qQlJhxC0om7/KHoynhyamSyLCu/lWHxIYYEPx09FCUJTS2RdMuhA8vBcxwkWS4qGf5kbK2pt6TOMbMaQHLdkXsMuc+lku6oRNKi5wgd6dRHUfWoYkipOGnGSNp/nz/R+jh1+yhP4xkiy7KSmqucu3I4+v/I+CXJ+nv1DaaTsXMsoSv9YhNgrH9zGjJfIKzb0YYzb/8IkiTjzTtOtsxSyFVkWVYWqyrSTHfMl2d0IuT/CHIcjuNQWVlZEFKgjNgka+uWTm2KE1lFMqtJA4CuXvVh1NTaY3g9Uehc+3gqi2RSYYe6Y0DZr8swgdanN9CRiGvmLUVTS+rjBbR1O/HSwuKpkeXLNR2kmysb0gzVyQ5Ap5faJBxCKZXSDou+1sD+dEeqN1yCzaytUjyTtbOmJk0jwW+9Kkyur7CYmlPkD4rKarp+YceshogMhQ527GsPICRKEHgOA6t9BkW8YiAZW6sqvPGbWSuRNJLuWEp6paXgpMnaSBotrmNWf6g5Di6y/5bOAN75uiGpiFpQ18w6HvqUSnL+p+Kk0YsJ5JISo06ZFHXS6PuYHn2ftGTsrOknqrt3VJYZnYiSDAuHtHVFnDSyOLO33Y/6ra1Yvb0NrV2pp09ni0BIVM61dCNp+fKMTgTmpDmMKIqor68vCJUZRmyStXVrl3YljKyMmfVJA7RKkJVp3MQ0qlVxVP/sUneUZVlxlHweoyS8/qasr+MhEuGp0hNNtSn1ujSRDY5TH64EUkNhNanIl2taVXc0qwHkIFGTG9vTHTXqjuo5pbezdbpjaosCatsB3uCY1g4o0/ytSPDHUHdMxs50n7REI2l09ItehEkU2pk1LD6YSPCbNbMmCyADq0s0C0SBYP6mTSVLMrYOWTazNqlJI+qOunTH9q7k0x1JhIrsMxknmhbNue6Jpfjsh8aEPxurJs0MfSRNycZII3oIqMqkohyGLEuQIUX/tv4dfLp0x2TsTAtdcRynqf/qU+417ivTTlp0vjBkQBkG9y3VvGan0FimIIvUHBepHU+HfHlGJwJz0jJAIZwojMRIxtZtutWuDiqS5vEYH/ibKPWmdJrNBpKQ4FeEQ1KsJyCERElJW4nsN3Yk7ZDhffGHs+uUv/e2pafURIrWy3wuRYULAM47YaQh0lGWgBpZPlzTAdphMU13pJw0V3xFy0SRZVmbaumiImll2t/aKpKWqshAwKIOr2+FF0fq6mcEJcXTOqqQqJ1lWdbWAFK/dyzhEJ7nlNdTSYEj52hkvFobm0vwGx1TkupY0zfSDoCkiBWbcEiitibni77e0lTdMfo66cVIhGKaU2herpfg16eMx0J/X9+4qyPhz9ILH4lwydSDAACn/KwWAFXXbFckTQ5rHLNEImm045SonemyAEDbwqPKJJKWaeEQsqhbXebBQUOqNK/ZUUOeacj9r7zEbUuqZj48oxOBOWkMRpZo062mdtA1aSaRtA3Ug7U7jeLkAK3uGKfJsV0S/LQssc9E+l8fYeF5Dr8/bTxOjtbd7W1PXaIcUEVASrwCxtZWgeOAQ0f2xZwLf2J4b8GoO2qcBu3vXVrCmaY73rVwFV5esjmt/dJOjz6SFk9a+eCh1QBSr0mjFS3pSNKMn48wPPhdSn1W+o5pWFRrZ7xuQYlMArGFQwAqpTglJy2axusxOoJmk2qeNzppjdHUabIa70S64/wPNuC6J5baFqlNh2BYxDXzvsLCTzal9PlQmErljdPMWo2kRf4/KOoIp+KkqRL8ke9KZqFOvxhXbqLKaIW+T1o8xtZWY9U/zsJjsydF9pWGcIiVkyYl6KSlWicmy7KmLCCyf/U37FNuvI8pixuhzLSvIIu8VeVGJy0fI2lkkTqdLKFChDlpDEaWIOmO5CFGFL/cglE4BICmD0o6yoP0w0cf0dKnP5IoU7orc2RVkuPMmysTlTs9A6vJpCa9SJoiHOJ1YcyBVfjq0dPwyv+caFr7R1LQetKMHmYbK4cFACrKOFPhEAC4+8XvsWLjPvzxqW+UhYNkoCfi+l5SsR7AAs8pjkKqKUO0Y8rzHIYPKgcAzDx5jHF/Nvbio6NO+shlPOU94qSlMrHqoRpZ6zGbVJs5hCSSRhprk7Q9u9QdZVnGw6/V452vG7Bq835bvjMd3vhiG977Zgf+Z8GKlD6vSXek+6SZ3Etcupq0QX0i5/eeFPriiTp1x2QinfoFimTONfqaSpSKErdSD6Q+Q1KIpFH3EkETSVO/K3YkLfKhSO1mcnV4+lpPOhpZZeKk0c/sTNRzkkXeSCStUvNaXkbSmPy+KcxJcxie5zF27NiCUJlhxCYZW/cGwsqNfHC/yIO7PXqT0iviETZRkbR0+qZpa9JipzuW2RRJox1DjuPi1qQR+kfTg/a2p+ek9VJOGqDW35hBml33WqTc5cs1rYpoaMU7OA4o9enSHanXu3pDOPfOxXj9i2144p21Se+XTpnUn8tmaUKEg4dWKxOdVGWsaeEQAHh1zhR89ehpqNHVbABqREIvGU5Ixs60Q6OPXOqVS/UoCo8pTKz8FsqOgHnfruro79/tDyuTfFKTpqQ72hxJa9zfo9w/du7ttuU704E4pTTJ2NpKOMRcgl+r7lgTdYSbUnDSJIO6YxKRNN29Lplzje55mApkkSIQEpOOpJpF0gAgJKmlAlKsmjTKcQqGpYTtTGd+kAiZNpJmXZMGpC58FIvXv9iKx99crfxNatKqyjyY9tNaTD+qVnktldTpbNNpk7IjkD/P6ETI/xHkAR5P+icdIz9I1NatUWVHl8BhQFXkwU1H0sygxTPscNLMasOM6Y7qKn86KRz6/H59/YxV+s3A6qiTlkJ6EA2ZJJbGiWrIsqwIicT6jfPhmlZWwHVS4RWlHHhel+5okcrU2Zt8JC1ITcT0vaRiPYDHD6tWxC9SjqTpejr1qfAqESI9biWSZj1xTNTOQarHocBrWx4kGklLxUkjtXtmzYzNrim6JpA0VCYOQ000ykMiQunUvdLQado792XfSaOvazq6kqitw1S9ZTwnbWB0kYlkBJD/72ntTSqyA0TaNADqPSwZJ1ofSUvmXKMFiFKBbnid7GIfcdI4DhqlviDlpMWMpNHRreg9JRE7k0VFnuOUa5mOXFabRNIEnlfOAbvFQ8KihD8+tQyPvP4j1jW0AVDFZ6rLPSj1uvDY7GMw5SeR8oBspTuGwlLS5zWBZG3Yle6YD8/oRGBOmsNIkoT6+npIedxgkJEYydiapDr2Kfcqku9kUuSKCi1cdNIYHH3wQEw+/ADD59NJdwzQEvw6p4zXSdbSogfp1MGRqBR5aOrV7/ROG4E4sHZF0mKpRsmyjLVty7CtN5IGZfUb58s1rTgsuhqp8qjIoSSrKUBWkwq9E58I9Mq7Pmoa6wE8YVgfpSFzqivRgVDiE0pFOMRi8SEZO5P9kgieJpIWQ4IfSM9JI5E0WqH0hrPrUDeiD343xSTFk+cVG5B0KWMkzd5+T5t2q2nau3LASaOjtOS8T8bWpE2FUd3ReK2cfuwwPHX9cbjqjAkAgEF9fMp+O5OU4e/U1ewkI/KjV7BNJvWQLEAkqu6ox+MSlN8mWYVHNcVTuz2UoJMWuQdF/h0IiQnb2a9TdgS0ixZmkWtAfb4FbHTSZFnGjmb1uiHy+nQkjZBOVD5dOnuC+Pn17+CKR75I7fO99qU75sszOhGYk8ZgZAFS9Ftd7jGsgpOVuz//7id44ZZfmk5s01kp81uoO7oEztBXxEv1UktFQpkQ0BVhJ1qzM6DannRHsnpuFnEgtAb3oD20D7w7YpueFMUrcgUyqfC6BI0TXF6m2phMcH7c2mL6Hfpefomgl+ymbW12Lp913HCMq63CWT8fkX66YxJKdIpwiI01aWS/mkhaHJGG8jRqdszO69mnjcebd5xsmWZJogBt3QFIkqzUR5F6QI/N6Y50mvaOHEh3pFUGU5nM0sIh2mbWZnWBAk6ceKAy8fR5XErKabIpj+3UpHx711qYBSxEWcSe3gYERe39ssTrwv/+6QScevRQAGpULhGSFQ4xQ2nlkmwkTWk7EPnbw0eeB0FJHV8sCX6O41JSXdRnfph9rxnqvux5dnz5YxOO+P2bePj1emXbvo7IPVlRd6RSLyvSWPBJl2/W7cXedj8+Xrk7pUwfpSaNCYdoYE5aHvHNumb88sZ3k+pxwshN6EhavObKZo6FLTVpbm2fNDPZW47jqJV+exxDQKs2FstxIpLV+9r9pumWn//QmFAqJPm9rNIdZVnGru6IqqHXo66c5oIaXaooEvxubfpdhYmTdvDQPgAiNUv0qnsqThpdswNoxWiIuqMsS9jvb0RYCuGvlx+F9+6aFm00HrFP6umO2ohWLEi0S998NxXoHml6ynxutAT24Lt9n6IzZHSGldXvFIRqSIRaHymJBVl5b+8OoqUrgGBYAsepCyK2R9IoJ42OpO3a142Pv9uVcnpUquyjFnxSkYUn57db4DT3sUQjTQP7qCmPyUCr3+3u2WL6nl3dm7Clsx6r277G9q51+LF1qXKNHzN+EI4/bDCA5CbxJEqcaiQNoBtapx5J4yHAxUe+R5PuKMW2YSp9/+hnZDxkWUZLoAkhKagsgOzvsKeZ9J0vrER7dxDvfbND2bYv+rxT1B2pSFo6jcPj8e36vVizvdXydfqeHet9VpByDztq0goJ5qTlEYu/24WG5m58uGJntg+FkSaJRNIIZo5FqpEGWZYpCX5Bk65jldpGVkGX/LA75dowQ00alQ4Wa4LZr9IHjos8rFt0feW+XL0HlzzwOSb/8f24+yepi1ZpKj1iJ7rCbQAAL/WMSPV3zgXoXmUuqleZmZP2x/MOxTVnTMA7f5mKedccizOOGQZATa1JBn0kjfb9SSRta9cabOj4Dju6N2g+S86FVCX46VYL8SARPjtUDPUKeLSoQ5nPhfXt3yIg9WBt23LDZ9OS4I8hHGJFdVlk5b2tK6ikOvav9CmqjqqTZk/PvI27VSdt9/4epeXBn/61HP/vkS+wYuO+tPeTDLT8fSq/ueKkuXjNwlaikSZSI7knyXspiZyUl0bsc8VvI3a865Ijlfe0BpsBAH6xG409W9EZakF7UFXULE9BrTek3EdSq0kDUhegIucKzwMC74LARb4nJCaW7ghQTaaTiG7Rz0ir7yNs6liF9e0rsKN7PYb0j+SS2yWQY3ZdN0cXGeg+aQSn0h3bugK48N4l+N29Syxr0+nrqn5r8k6anemOhQRz0hyG53nU1dXZojJDcpBJwTcjt0jG1q1daqqC/kasF3Gg66jGHBiR2k11pYxeHfd6BE29kL4+Tdl/1Em758Xv8bv7lqS0Xz/Vmw3QpsDFiqS5XbyipLVPJ8O/clNkctcTCGtWx82IF0nzh9WHqtulpteYNVW285p2EiX1z61Nd9Q6aZH39K/04dqzDsEB/Upx/KGDMWvaWABASworwkGdk0afc5WlHsiyhD292wEATb3bNJ9V0x1Ti+KoKUDxV2MPiKb37baok0rGzooUfvT81qjDUavxohzG1s4fsbVTVWkjq9+pNbOOXlcJOKUE8tu0dwcNjawjx2sUSkiVptZedPWGIPARAYawKGNPdJ8NzV0AtJG2TEDfK8h9NBlb0zVp9P0zUSemJsVIGkkHK/FFrq/jjnDjw0cn4je/HKW8x82p572MyPu6Q+3oCXdClMLUJD6JmrRwejVpgPoM6U4yG0OJpHGAwKlOGp3uKMVx0jzUokOidu5VrmejTStK3OgOdyAo+tET7sS+wG4AQHPvTgwZEHXSbKq9JOrGND9sacHv7l2itKWh73XptPOIxY693QiJEtq6g5aLC3SbnB+3mafPx6LLxnTHfHlGJ0L+jyAPCAaTV0gzoz3qnOmbIGeCxp6t2NL5Y0ZTU77dsBdXPvqF5SQqF0nU1iRC0SeBSBrNucePBJB6uiO9Ou7TTd71DU8JdG3LxhQnVIGg9qFHT25oJ1WSRfjFHs1nicKjvgEs/QBd8v3umPvvCcSOOPhF9RzjOA4+T+R3sRIPseuadhLFWRI4SFCdrYpS9be3muD0rYw4xq1dgaSv+VBYW8NC/4Zej6Cs9gMAzwma708n3VGSZKp3kFEiW8+waA+1Xft68M7XDbjl6WWGyGmidm5T0pcjE6ZYqYJNvdvR1LsNYSlyP09l4kxQWkuYNLO2QqlJ6woq1xRRHQRUpzJVdcf5i9bjwVfrIcuy4oANH1SutBohE1iSTdDY0mP+RQ4QDIvKAhmgjTgkamulJk0XSUs43ZEoPCY57vZoOpjHq54ngkt7zgi88TzY2bMR37d8jq1dq9WobTI1aVQrj1RReqUlm+5IatIELuqkGdMdJUiQZetzVYmkRe8pidhZ38iaprxUwA8t/8GK/YvxQ4sqklHqKledNJsiae0mfSq/XtuMr9bsUf6mnTTiDNstwU+3rSCLK3ro5/PqbamkO9rbzDofntGJwJw0h5EkCevXr7dFZYZcsO3d9uQ7J4osy2joWo89vdvRK5pfoE4w64HP8eGKXbh63lcZ22c6JGNrZVJX4UWpbrVO70jQqVM/HTsAQOrqjuRBJfBctIcVHUkzvx3o1enEFM5lfbojrSJJpztu6vgeK/d/iq6QqghHFB71kzl6sWLxyjhOWpx0R71j6PNGHQwTZ9jOa9pJyHnTI+/H1u7vle1mwiF6+kajl2FRTlqFTq3ZMf8N9/p3Kf+WZBFhWbWjL410x25/CFLU4asqi/+g71/lQ6nXBUmWcfM/l+H/PtuKt77arh5bEnZu1ymt6Z1MDsYFkJAUTV9LS4I/viCOHk1NWrTmsF+l6tR6TCKgiRIIifjLwlV44u01WL5+LzbuilzHY4ZUoZaKMgRColIPRrcWcRJRkrBld6dmG/nNk7G1tiaNFg5R/93YsxW7ujeZfp5ELRtN+rXFgkiUe33qeUJfOwAUx9+Mvf6dKdUXB9PskwaoKsGpSvDrI2mirB1nLPEQJTIcVXdMxM50L1E9ZT71dyDRSgAISSE13dGmheVEFuTpZ1o695JYNLWq1+gOnZP29dpm3PL0cmxpVBdwN+/uTHoh2W51x3x4RicCc9LyCDIRaM1wJE2CCAmRm1ZATK9fVTKQG/qqzeahc1GSbEnJyQaxImlkNY5wybSD8PNDavDP63+uOEypyuEbnCVqJZieqNHoH1SpnH9EUp2sTNLqWPT4O0NtAID2oFqncsiIiKjFV2vUCAygTloA4Isf98QU+SBpi1ZKkoGok+YTIr89iaTldU1adJK9N7BV44xr0h0tiu69HkH5rZItgqcjDYAxZbQ3rH3I91B/Ewl+fwrpjiQd3Ofh0RTYEPdexXGcEk0jDsknq2I7+/H2Xa1E0rTnIplc0pAJdoWSopSKBD/pk5ZEumMZUXdUnbS+FWpalSq0kLwN6NX0L1fvUSLvow+oVO5rDc3dmsmnU5G0rU2duHvhSmxtjDhmc55dgem3faB5D3nGJBO5VYVxeHDUDIo4t6IsYlvXGjR0rzc9Bw86sAoA8P2W/UlFqUmkweVRr0fi6CvHJsW+N9PnWqJ9L5XIuA2RNPoc9yewEEOuS5cr6qSZRAqB2HVpJAU5GRsHYqg7lpVEfocSoQKH9v05JvY9AUDktz8w6qTZ1WqCFm7SLzCWeARcc8YEzbOU/M7b93Rpzv100UbStGO74J5P8X+fbdHUoUmyjE272pEMTN3RHOak5RFqJC2zThr9IAhKmXPSaPTRG1mWMeOOj3Hyzf/OS0etLUZNWq3OSetf6cOCm47H5IkHKDVVvYFwSqmnpHiaTMToFEeyCqhn+x7tjX5/CnL4sVYmiZMmyZJyfnWH1VW5X0b7xH32Q6OmN1AbdR30BMKWzoQoScrD3iriQCJpZa7IBMob9VfT6Q2XbcgKOCeENX2GzIRDzCC1gFNufh8X378k8f3qI2m61XNST+LlIxEFOjpPnI1UImnkmior4dDYuxVr25YZ3rO3dyf29DagNbAHu7o3Y+hA7Tn/5eo98AfDWLxyF17/YlvC+25XlNYiv5lepMBspT9siKTZI8EfjypSk9YVVK4ZeoFGSXdMog8XgZ7MfbJyt9IjbfSBVRhRUwEg4jy1UpPPRociaU+9txZPL9qAKTe/j2837MVLnxoVEbt6Q/hu4z785Pdv4pWvExMwCVHCIXSWHXHSgpRj1hM2TpLrRvaFx81jf0cAW5sSm0TLsqw8911e9fv1kbOQHGtuwKHMJ0S/L/GUebXGNP5CQEDsxc7ujZo+ZoAqHELO8ZWb9uGw//c6Hnvjx5jfR5yUyjIOAu+Cy2SxA9Dex/TPRW8KLSX8MYRDSksi989KTx+UuSrh4iPXkwQRg/uT1Hw/nnxnDdbvaEt4n3pom//92uPwf/8zWfP6+3dPw7VnHaLZVhH9nVs6A3h60QY88c6alPdP00QtpOzYGzubijhZjfuTmysSW/epiJ+qXkwwJy0DCELqqkg05ILt9ocz6pjQq3OZjKT1pS7WTZRCGBCZkNVvbcWOvd3YtTdzNQ3xSNTWRJBBr+44oMoXc8JFnLSwKKc0idKvENIpjgdaOGkdunS3VHqWxVLLIhNzuhi8J6yuwh0+qi/6VnjR2RPSKMHpBXSsxEPoSI5ZM2tJlhCI7rvcXRU9zsiD2CqSZtc17RT+YFhxjEtLAfpwy02EQ8zoS03cv/hxT8KRFb26Iz0ZFGVRmVBVefoD0EbW1HTH5O9v5P5YVhqZpOlTs3vDXdjU+T22dNZjXfu3aOhehwH9tNeQPyjis++bcPXfluJPT3+L9t7ErrE2ndIaHUkTZVGTFkUIGWrSMiPBr6g7dgeU+xB9r01Hgp+Oiq1paMN3GyPKggcdWKlx0mil1saWXkdqnX+kVvbvfH6l6Xs6e0O4+V/LEBZlvPTVftP36KGbtYtUNIoIhwSk2E6a1y3g8JH9AADL1+9NaJ89gbCyL5dXvc/RTpksy4ZIGll0ir4DgktSouqJnm8hXQ/AWOzq2YQd3Ruwp7cB7cH92OvfBVEOqxkg0Ujan/61HGFRxqNvrI71ddjfERlrZTmnSXfUQ+5j27vWYfm+D7X3FNK7jKT6J3Dv9usyP2iIk+bmIteMwLmUdObyEjW184FX6nHdk1/H3ZcVnT0hxea/qKvB2CHVmtfNFlX1vRHTcRJpGimRmx3NsaOE5NzenUSEvCcQVp4T/SuNYimpkOvP6ERhTprDCIKAurq6tE+YQFDUhOszqfBIR9ICUnpNhRNFlmWlbwYArNqkfYDSTVGb27MT3dOTqK1lWVaOeVCfEpRSqUq11Mr+po7v8UPLfyBRE2n6vanUpcXqV2YVSbtz5hGam388JcWY+zV76EUdpwBVF9YrdiuTeYHncfyhkf4+n6xU65nadLWZ+zosnDSi4MZxpik7EedQBgceJUIk/c0TrcXuCYThF3vQGlBTLe26pp2EONIeN49SH0AHopONpBESrR3SC4fQkCa7PASUu6sB6CJpKaQmEUgkrbyUqhmhJv+9onFyMai/+luQa+KZD9YrDkpp39qE7Nwe3TeJUh15UMQB9bh5yzohku6oryNZv6MN029dhOueWBp3vyTiWOJ1QZIl1Ld8iQ3t38X8TFU5XZMWsYfWSUu9Jq3JpM6K5zgMr6lQnLRtukhaICSmncL/f59twS9vfFdJ75JlGQ3UM+JHCyGDbr9WGTYRW4cpdUfaSXMrkTT1+3pF80gZqS1evj6x6B0RDXMJHDzUPJx2yiRZhAz1eFycGwdX/xQjK+rAgaRihpJunh5Mok8acUp7wl1Y17YMmzpWYcW+T+D1Spp9JvoMIZHeygoOrhhOmiSH0Rlqxe6ezRDlMPYH1F6yRN1xa1Nnwvdus8yPK359MPpX+fCbaRGFZXc0gsZxnBJNE+UQ+lJOxoadyaX80ZBrotTrgtcjGPqYmvU1LdPVj2/a3ZlSDbkeOpLWQEXSQrqFYoHnFAXqZNKYiTPudQuWJQnJkA/P6ERhTprDyLKMjo6OtFcK23u0D7FMKjx+v3k/9rdFLsZghiJpnT0h5WEIAKs2a500Oud7b1tmHMd4JGrrjp6Q8uAbWFWiiZwNHVAe/S4Je/070R3u0KzGCjyvrHSnovDYo1t5pyNp+lo4wokTD8Sqv5+J06O9s1KJpKm1M8YbsKLopxPvoMd93CGDAADfb1HrE8nEhTh5+y2ctG3RdM2BfXya/H3l2JR6tFLlYetxR2zY4w9jfdu3WNe+XBEzseuaTob27iC+XL0n4X2Sa2JAlRccx6HXr36ulFqojOmkVWhl7HfvT6zOgu4jpYdESz2CT3GIe6n2BySquqe1F+f9ZbGiAJgIJJJWUaY+mOmoBlkE6OutwfDy8QCAgf3U8+GMYyPn97cb1Inz5p37EvrN9ZG0P5xdh5vPOwyL7v6VQeSAoAiHRCdWvUERaxtaccqtH2Ddjna883VDXEeJRHpLPC50hlrQFW7D/kCjZmFHj1KT1kXVpNHCIWn0SdsTFRgYNbhC2SbJMrxu4f+3d97hcZTX/v/OzPYqrXpzkWxsbNwBYwPBBNPCpSUXDAGCHSAQSMAXAvfmB8FAuJQbX0roJGC4VAcwHRdwAxcw7pYtyWqW1dtqe5nZmff3x+zM7mjVMVi23s/z6PF6dnbamfd9z3nPec9BUbYVHMsgGImhol6rvA703eoJQgie/+SAXEN0p1xDtM0T6dFTVJRlxX8umIaF540HIBvGyZECA5F1crH25ELCitLcnycNSDbS2gd0Tn98/HdY9GAYRs1yKJIYpHjMpeJVY8Gh2D4F450zoWeNyDGPgpGTQ4sFKTroDI98H5MuyRBCVA9WQOiCFPcei0QAo5PbveJJ8wxwyUZ3T5qRs/S4n1zaIuGVS474mRWfMPnnygq8vubggPruniI/7r5yKr79+yVw2OP9G5toM7p46QOBCJpxiGEw4LV/3Umupdqd5NpoySheeYWoIKasIRsshBDN5EunL6rKsfuYK0pEzeI6mDBmxWjPjI9XP5SjMUb/WFAj7UdGkiTU1NQMOctM2eEu+MNCilHW3YvwY1HZ6MUNj+3FnY/KDe6n8qR1L1zcPfV7g8ZIGx6etIHKWqmP47QaYDRwmjVpRdmy4poc+tf9mVuHmCkLSMyIKWmgkxNK9OZJA+TZwsy4IvdDPGnGnjxp8YGweyhtMCnD44QiOWznYINX7XgVpbw4rhB2eHtuE4oXdnpJRo/fK8q7kbNAF1d+jEb5HL5IGKH4bHgwHoL5Q9v0ULjhf7/Gbx7fgFXfD6yQvWKkuRzy/RSP4sCxQEG2XjMI9mWkmbuldW8cpCdNqYWXHx+0xxc4IChGGmuEKa5w8VJYVTSTPbbbD3bgs28PD+icQELxs5oTA3Py2kbl/TKyZhhY2VLNypT3ZRjg2nPGpRxzf1XToLI7Ws1yzT2rSY/fXTQRo3NsvSZzULZbkxSrFz4t0+zTk2cqGSUs1GLkNJMcUbH3Nqp40nwhQW0z2sQhP8CTFu/brjlnnCr3U+MGiUHHqRNBO6u0HqTBrl9JpqrJp0ZWNMb/rW5OpP4/cVSauu/kMen43UUTUZIvz/Z3X8caGoDhkhzOOzrHhgd+MxN/v22OrBjybk0/Fo4FelQUZ47PgEHPoqEjOCBvS/dC1hZdwgiOxScBlPdJxxqQYx6FtHg4MZDw+ggSn7Q+bJBGWg99dzIxwqvXEu22dp3Ty9dW3eTDvlptIrC+kjMp8rFbZSPN1IuRFo4F1f4Z0Hrnrz93PH530UQAwDvrqwfUd/cW+cEwjLreLtlI07NyvxWTeNz571PU7YSk6jIDxZ2UXExByYp8xpTcHn/TU/biH+LNA+TJHKUvUEI5lRIDPa0Dz4vXnxyMJ03ph45UqOPRGKN/LKiRNoz5tqwN/3bfGjzw+g5NJjvgp0sesjO+BkgUgbZOCbwY+UlmJ7oX0e2eLUnjSRuC0TAUPIHoETEI29XaRHKHlOxdUpKGJA/03b2XSkc8lMyDiqKtKFDJ69qSPWmEENQFyjVppDPjqfCHZqSlFgdVMuvNn1UAIHHPLCPvE4z5IEg8eDGC4lwHOJaBLySgzROBJCXCYRWFq7dwR8UL25uRpsx2mzkrdPHBVvGkeUKJmfDunr6fCj4mYlfc0Hz/m9oB/aY9Hk6b7ogrdSYGLz5kxZP/KStuysxvX0Za93o4A81YpoYoxReQv37PWbj67BL8886fJTxprAl61qiGYSnbs9PMuOPyyVDsyHW7m9Gd2hZ/SpgNAHjiXiFLkpEWEhJGmpqwhDPDwMkKlt0m4O4rpmLJdTMxsSgNWd2Kx7b7BqbIKpNoHaQMe7s2aRInKIqrRWdHjnk0XMbc+PZ43Ssdp7aLNdsbkw+Lxn48TOGkxCHJBmlfCZ6cloTSp5QsyLCnetIGUyeNEILywx71HcnLsOCDJfNx7Tnj8JdrZ6j7KSGPyWtLAeDDzYeGXNtpXVL5jfr4+aubElklTyhMrMsaHZ8EUya69nSL0BjIWKJEeCiJca6bPx4XzR6FhmAl9nu2oj2SmEiRIPXYb1hNesyLh3B/OoCJCMXbp4TyGlmTOqGkGGeKZ1bP6tERicKflLwm2UhLhDsO1EgTNffbG6FuWVuTYfXyc61u9uOyJV9qvuvrmat9iU1OHGJgTWqfAST6MZ+glWOyccwwDG64YAIA2aDvnm22J5KXBYRjQU3IcuI5J9qRLun5Xn/ueOx+8XK1L2kZYvbS5ORiCv/6y9m49MxsXHMpAw+fGirbkxfqhxppSvp9l92I4vhYqyS86T7m2kw6VbcYlJHmUzxpR8ZIO56gRtowJSqK+OB7uWbPd+XtKeEBP1W4Y3IK2P2V8gL4vjNIHRmUFPVK9rU2T0STslezJu0nCHckhOCq/16HC/686gcbyG3ehEIqERHtQqX6nWqkacK0uhlpiidtCEaaUhhcSRLSmrQgODl0JywG0BSqxuFghapwZsWNyh8S7phspH3x3+dj698vQVE8xDMqyZ16uiEbgOy52t+1FbvdX4PTSRgTN+oONnjhDwtQ5goUT1pP4Y6EENXAKS4CDvkPpBQ+VWZgrTpHwpMWTxzSFUq8Z5Ee1jT9FOxJKkGhG2CtIqVNOBMT7jCbGIiQ5W2IzwL3lTjk2vlaz9JA16QpSsG4eKrx4jwHHl50MgqzrOBF+V0ycHLoqRKGlbwe8fbLT8LKRy4AAGwta9WE9a7cVo/593yBFz/TepyAJE9aUrHunjxpBs4MfdyTxktR3PxvE3Hd/PFgGAbTuhnyHf7+21hyFja9MQqRxOATEmugFAXPwJpQbD8JmUY5W6mQpPidF5+oEEQJLrsRp50ot4H+nrmaOMTIIZR0rx6+HZXe3SnhdrwUhY5j1BlxQFasktfeDDZxCCEE9y7bjovuW62m4c5NtyA7zYwHr5+FSaPT1X0VI00xABVP/urtDbjlqU0YCsk1ElVPWtxIK8l3qCnvgcTEkOKx7T6uDmQSThC1nmIgvs44Ut/j/skenmQumj0KAPD5d4f7nfhMeGrl52XgTBrDoCVch0MBOdwvJOix8OtduHtbIvxPSXIhkOiga2kl1pgyvU7SClIUgXj5lGQcehcAgNX1Pma09fHMlTWTTpsc4skwDGKSBcpKCMWb5ePlPj7DKBu+MSKokyCEENhtBIWZVhACVLX2P36pa2LZKHa7N2BHx1o0Bqs1iY80nrS4sRiTeDAMA7vFoNbDq28L9jqB2BeeHrId2rObcMWlIYj6TtQHKgZ0nKdWlOKRd3b3WaKmLxRvfp7LjJI82UhTErkpE7bFeXZceEohXrvnLDXcsa0rMuBzKmN3b2WARjLUSPsJMJkGPzvwlx3l+KJUnlVtdodSBuufypOWHM9cWil3XD/mujRFIVM8aWNzHapCkfwMkmf1h+LZGSytXWFUNvrgCfIp4RrJDETWbV2KJ82MjkgzfFJi9jw3Hiqg8aR1C3dUkockJw7p8kfx1zd39pvSWXmG+ZlW+IUuHGrveeF68oCrfFZCEYYy4KgpjeMKoEhEGPWcGnYJJO7ZZZTXnwVjPoTFAEQiIBjzqjPiBxu86vtvNnBqeEVnD+GOzZ0htHsj0HEMTBn1aA7Xwh1tVb8nhCAY97ZY9c74eg8dTEZZGfKFQ9hTHsMHq6MICol3bihtui+ivIjHl+9JmdkH5LTwCskFQ/tCMaQtNm0/oSgYytqOUMynhhp259yZBfj0r+fhkd+eDGDgnjSlgHGycqyQ7EkDoIYvdfc2jMt3oCjLCl6Q8M2+FnX7N6Xy502lLehOIiQsYaT5hE7VEFUmPuRwR1kZIJBUTxcATCtJGBTAwIy0MC+qHmnl3MntRzm+MgGgY7UeEAC4Z8E01UP+i1OLMCru8Wnq45kLMSmxDs+s1xikTaEadEQbUebZpk6ydEaasaPjKzSFatQZcUC7Hg1IGGkDqWMFAO9uqMHyDdr09oqC2h3FSFP4zfzx6uTLtvL2QXvT3P6oOgkDAA0dIRBCVCWypLsnLUc+f/cECwrtvYRMJ5OoA5h4z/xCV0o/rXhMkz1ryfx8Rj7MBg6H24KatbY9oUTSKOtJZU+0bBjwYhi1/lK1DdWHOARjIiq8AXj5+LuX7EmLhzv6B5o4JH6/QakDOzrXYlfnenTF+1BB4lHu2Y6n93+Nz+urU37rMGSAZThkuoDelhr1NX5rPGmMDvvcPty/U4fVDab4c5DfXWX9m13vUkt7KJ692sB+7Oxchwlj5H1r2gden01kg/HjizgcLFdD8BmwmiQmyvNNLi6ujOV/eHYLzlz8aYr3uD+UxCFKuGM4FtC8S4GYp8/i5cm8srICb3zVc3H1/ig77AEAFGbZMC7ebyiTIIp8po514dk/no4Z4zKR6TBBz7GQCFF1nf5Q3oGMIxTuCBz5MfpoQY20HxmO4zBx4sRBZ5mZnGYH7040wO6JM34qT1pyTYz9lTFIEtGskWrqCOJ/3983ZJd+Muv3NGHKTR/g+U8OqPHYLrsRBXHvkhIHTQhRPwM/TXbH5JABpdPqzkBl3ZYU7hiIdcFsYnDWqXpcfsbopHDHpDVpKeGOsoKRbKS9sqoCr62pxKPv7O7z3Er4VH6GGdW+vYjGeh4g/UmeAKXAtBK+MZRELcnZsiJiCLs61mG/J5GeOCqGVSXHoc9IyeIVivk1RponKZueEiLRk/G4I67AnVDoAKuL1xkUEoNlWAxAggiW4dREFjpGD2PcqegNxPC3f0bw4ZcCvtnlASFkyG26O4QQdVH5B5tq8fLn5bj/9R0p+yUbJHWtgQGV31A8AjZrDCzDqQqjQroxG3rGAEGKwsO3qdfTFKqBNz4rzTAMJo1OR2GO/DBq2jrUd/Hz7w73uF5MlCRUxgfwZOVYobuRlvCkad9xhmFw7kzZu/T48j2qMaK0w+S1iQpqnTQLA4vOASNrljO9ReREGoqxYuTMYBlOTb6gbO+INMGRJyuaOenx0F5/DCzb9zCpnFfHMep7E+jBk6YYZ8kKs0Key4L/XnQypha7sPD88SjIlBW8xo7e+9WaZh/4mASbSQeXEz0mC+GlCA56d0Iikurp6eJbNaG/rm51iZQ+qLrZ3+9MeFQQ8cT7+1K29zYjPq3Epfn/3Mk5WPu3i1CUZYVECHYNUpHduLcZEiEYl+8AyzCICiIONnhVw82Z0YWx+QllLeFJ6zmDXKe/byNNiElqwg2rMWHodUZTi6AXWuXkJB6+vceQR4tRh/NPLgSAFCO3O0q4oxLKa2BNaqift1uoX2s48b5W++T+XvH6aBKHDNKTFpTk80SlMKp8e0CIhPrgQRzwtOPzegveq7Wge4SskTXDwtmRncFi2Z+n47tnLsXk0WmafXqLhJEkkqiTFjfStra5QQDsdRtASKKMh4JN74RZJ8s4GPPCy3egNSxHJOUVyLpMo5cdcHZHidX2S0ob0rMGTWhhIpw08Uxz0xMTFXxMwl0vDi4df5dae9GAxmAVKn27AciRJspY1V32yZw7qwDzZ+RjWrHc5p5aUTqk5RpKOPEZJ+WoSwuqm7XhjhlJYYosy6j950DT8CvG3pEKdzxSY/RwgBppPzKSJKGzs3PQCxjzGAMkPvGbnd0GL0Vp+bHXhyXXxAiEgE/XCZoaJP/7/j48/8kBXLrkyyFlG0zmw3jx2Bc+LVNTKbvsBjWhhZIspNMf1dRRSjYabv37Zpz5H59qwjSHwvrdTfh6b2I9zMHGhJFWHjfSFCVbkcFAZa0MStnpZtUAuulKIx5YdCIkIqIpVINAzKPun+JJ6yHcUVFKlGK8PRETJTV0IT2NoD4YwvSzbMjP0uHZP8zV7Jt8ftWTFu9A3f4onv14/6ASCyg1tswGDrX+UgiEh19wgxcjkIiICq9snNh0adCzRlh0Ds3vNUZao1ddj+a0GlQPX0/hjmu2yzOPsyYmZvAVIwRIJCex6hzqoKtj9Wq44/f7Evd4sC4GgfBDbtPJdPmjOOM/PsWipRshSpIqv/11XZr05F9sq9d4CkSJ4O8f7se28raUYyajhNSmORhkGQvU2WUFHaNHlrkIANAalo2t9kgD6gJlqPTuVN/pmCTAr5MLoro9BJ2RNjS0B3H7c1ux+IWtmnBZADjcGgQvSDAZOBRmWkAI0fRRSnpyZU2YkU31HCv8/pJJKMi0oK41gP/65zYQQtQEQr6QkHLuhCdNnmHPMY+K319dYr0jONWjpczCK+2rI9KIklEcHvljLt7689kAZC9Zb1lDE+eNJzewcOo7FBC8alitMruuKNVqaBQRNM/mkrmj8cqfp6CV3QyjVX4v+wp3VCaLJhSloVNINRIAecbfJ7hR69+P9nAnNrUY0RLyY3qSsZScNASQvV12ix4RXkzJwtidL3c0wu2PIjfdjDOTkhlwvRi2k0enqwockAjlOvmEeLbDg4Mz0hQF8ryTC9XjPvzWbkR4EWMLWVgymgBLC+bPlBXWLKceTaFqmIzacXPuZDm8tL+Z//J6D3hBgsOqB8zNiEmyDDujqZ5dq84Bp142htvC9Sj3fI8dHes0xvlVZ5cAAD779nCfXkQlu7PJlMgsqBj93m5rk5qCiXur9itGWrInLR7qOcCEFkpoapQkPLUxIsAdbUVbuB6Hg/HanYRBcyjRvgB5QsQa78tHFUrIdJrw1v/7OV6443Rc83P53nsLn/cGebXEgZI45KBX1j18AosunkW2uVCzRs2ic6gGTF2gDAc83wGQ+7txo2SFffvBVoT7SRCjGGmEk68t1xzPbBz3ZCWHOirHBxLecUKIGuGhUN8exN6agdXiAxKTPyazgMPBCjVstsA6TjVOu8seAP5y7QyMy3dgyXUz8dJ/nIn37j8HU4tdCIQFvNBDmHhfdPgi2B2/5p9Pz0dJvjyOVjf58Pa6KnUCsXvCjxyX/P/kNbWrv2/AxEXvYeW21LBgNbvjEUwc8kPH6OHCcWOkPffccxgzZgxMJhNmz56Nbdu2He1LAiA31vr6+kEbU/4O7eCorMEyxfsGT5DHuzUNuHztNqxp7FthGypCTFKVhCsukDv591fz+Gaf3MhiooSPtsizVB3eCP76Zt/1efpCkgi2HpDvIxSN4cPNhwDICoSyfkrxntXHExoo65vc/iiEmITaFj9Wb29AU2cIq7c34MPNhwYcopVMQ3sQNz35DW584hvUtQbw7vpqtSgrAJTVe9Dlj2L+PV9g/MJ/4ay7PkOHNzJgWSuetEynQbOOJBTz4VDgAOoCZZrtvBTRrKNSFr0rSQNESVJDMCO8qD7HlPN2hSFKRF4AbujAG1VWfMc78O+LnDj35ISCJUoxzVoWr9CB7R1fgRi61JCsJz8oxRtfVaacozeUcMcYG4CHTxRw9QlutEcaEYx5oWP0GO+cAYZh1IE98Wz8ajHP8nqP+l6mWQ3qrH2nL6pJdxyMCFi3W1biTp+RGDAjYlBdAxVQ16MlvD46Ro/xY9iU8JyKGhEfbq5CdZNvSG06ma92NqLFHcam0lb8a2Ot6iknBNhaJsuvprUTf3pZrpV144UTMGWsHIr3wqdluOnJTX2Goykzpk47g2zzqBSlgmU4ZJtkI83Dt6Mj0oTGkOxFEgivGukevh02mwCWBUQJqOtow+fbDqvXunm/VjlV16Pl27HPswnftn+BnZ3r1LUsfNxr1d2TVukL4ovDLWgJNapeB5fdiOdvPx06jsGaHY14e121Zva/e8bX5DVpetaILFMhGDAIxDzY37U1fr5EGQblGjoiTfDxbvgEuQ2NGRPGmByrms20r5BDILk+W+KFkSCq4VYxSZZTwpOmKLEE1f692N7xFfa6v8HhQAUqfbtBIIGzyspXX4lDFCNtdD6LhqDcFhsCLhwOxMtrMDqMd0wHALRFDmN9swFfNJjx8WEDJo5JKEPdvUosy6gFabtHcHTnnfXyO3PFWcV49IZTUJxnx+8vPrHX/RmGwdnT89T/K+nFT5kgK50DLe4MyAktvo6Hwp4zI19NfLTlgByKd+l82dvh5Tvw0uIz8NJ/nImGUCXqAuVoEw6qx8lNN+OUeJr2vtZHAYnnUVLEoj5UgUrfLniFDghSFDpGjzG2yQAANq5aZasTIXXo4tvAS2G0hRNK6sknZKIkz45QNIZPt9b1el5lstRikVDl06HSF0uZZFBoSCopUO2T25LS/v2CG6Pij/+z7+r7LVAvSpKaXIaw8fA7gxyOftC3EwQSWkKJvrUzUoS97nQohzWwJtj0cr+lGBR2sx7nzSpETtyI6c27o3hXrGY5tJRjOBz0JdrDIT8HjtGhyHoCANlrxzEcmkMO/PduB3Z0GNTtU11nYlZxIdIdDHwhES99caDP+47Ek64Y9PLvc+JGmkJyf3qgy4+bNjXguzY5MqEuUIbvO76E3ZH6bF//cuBjpjI5pDcl5DvBOQt2fbpqpHVGmtAa1q5pXHjeCVj92IWqkcixLP4Uzzi5fENNn8sVth5oxazff4hXV1Vgd3Unrn10PQiRs6LmuiwYlW2DnmMR4UX85bUd6iROplM7vqSlybLbejARAvt/X1VCEKUe9QblXlvF/agLlP3gJF1D1buHI8eFkbZ8+XLceeedWLJkCXbu3Ilp06bh/PPPR1vbj2O8/BR8q7zc3SSUkyFvcPsj+EdFHbx8DI/uqcSKQz3PpA6VZz/ej6k3fwCJEOh1wCXn6HH5zwpACPDcex0I87xmhh8A3v/6kFqTarCU13s03i8lg1a63aCG37z0eTkuuncVXl8jN/I5J2aDi9em6fRF8Pl3ifCrR97ejT+99B1ufmrToBuqvJBb9lpc+fBa3LtsO1ZvT8SCVzf58Mg7u3GoNR4+0RHC8o19h6skoygCdpu2E+/i23pdv8AnZYtTDCXleVU1+jTp+JMX0iejGDa5LjO+bm1De0RW5na79fDwbaj27UVp1xbs6jyEJ0vteLPKrip8ghTF4eABPPvHOWqIzrvrawb8bJUEBwFRq9T7BDc6I/L15luK1TVKyUYTIIcljs6xYlS2DbwgqV5Xh9WgxrGLEtEkAli7qwkRXsToHBsK8rThwe6oXHPMGzcYIzErfrdpN54srYaeNWJ0PoerLtLWoqltkPD//lGK6//2NcL84GboREnCLU9vwq8fWQd/iMfa3QkZ/c/yPahpTrQbxfB59cu9iPIE48ewuP1X45Gfkci+GQgL2LAnNfOhci5l0MtNs8Gqc2gykQGyAm/WWZFnHgsAqPTt0iRGUdacdEVbwXEMstLl92BXVQc+TwpzTF4vByQ8zqPy9AiLfnxeb8ITpToc8NTAw7eBQIKO0eNAVxRXr9+O9c0RvFVtwd/2AX8rrcbLFeXY6/4Gnqgsl5PGuLDwPFkJe/itXdpzJYUgE0LUgtI2CwMDa4SBM8UL+TKo8otYus+OHZ0J40Tx5rVHGrDfs1VdrycREcGYD/nxkMPkosg9oSZ1iOuqSnbSLr4VPt4Nf9z4U2bbWYZT96nxN+KZ/Xq8XhlDjb8KEhHBgEVmutyvNXWGeq2zVF7vAQBkZse9C/wYPF8u4ZWDNvgFBhadHRmmPBRYxoEQYI9bPn+5Rw+jLdGfdPdIAsD0cbKR1r2PT6ai3oNvy9rAMMCVPxuLPJcFXz7+C/zpiql9Pq+Tk7zaJrNsUJw6QfZk7anpVGsw9cc/v6hAICwgw2FEdo4PFnuiDY3KYzFzkvyMw6IfghSNe7zkNiNwifuaXGxDVlzJ7C8pklLOY+yoePZXvh1lHnlC2GXMRa55NErsUzHFdQYAIN2YAxacZt1jWyShVDMMo3rT3llX3WN/6g/xqscid7QOyw5a8efvq8BLaZr9LJwdBByaQ4ljVPm0njQAGD2hAbkuIzq8ETz45s4e18EqhJMyIeo42VOVacrX7NMQTBz7vUMevFnNY2WDPPli4MxIN8pe0mDMp4bxE0Jgscjtprdwx05/okbae7UWXL1hryZjZW1ABwYs8i3FKLZPwYQ0ee3sijovgjEW37Sk4ZTMCzEj42wYOTNOdM3AwkvlceXlzw9qlkx0RzFeDTrAbnDBzNk0NdqSn+eb1fXwCiLWNpngF/xoCtVAJAI4c2LCQUkM9NWOxn4NY0BeZqLUa8zKlp/DeMcMNWzdqc+AibMiRgTU+PehI9LY43EIkXDQuxP2vCpMLU5HhBdx+7NbepX50vf2whPk8d9v78YVD61VJ8LOmS7LXMexKMpOLdWTvJYsJgmYOkmW0+rvOrGlrBHbytuw/aD8PLYf7EjJqaC0u/ebjdjSWoem0MD1qeOd48JIe+KJJ3DTTTdh0aJFmDRpEl588UVYLBa8+uqrR/vSBs3Ln5dj8/5WrN4iK9TW0VqXuVJ8tarVh679PrSsaUWkNYKXymvRHBra2qzaZj/W7CvFro5v0BlpRukhN55esV8Nc8hyMWAYBn+5+hQ47Qya2yU8unwHvtwpdwynzcjEGVOyIRGCFz4pG9LshZIQ4GdTc9VsfYAcDlOQVL9LKfIKAAvmlagheK1dYc0aGSX0suywB+t7SOOtIEkE35a14ZMtddi8vxWiJGmMve6LmhlGNiBXxI2Eq84uBgAs31A9oKKVhBB1UDJY/IhJQK1Pj64oC3e0BQTaYygzdlExDL/QhWDMhzH5cjjHstUVeHNdGV5dJc8KKwlWPv32cI8JRJRZ+fQ0FqsaE02/LsBhZ8c+tEXq4eW78MyBRrRHOBzwcPhnRcJQ46UIThwv4n9uOhUWow61LX7V69MfSmhkBPJanVFWOSWyO9KsxtVnmPLRHIpgd6cXFp0LHKODy5gLBgxEEkMg5sFp0+Vr2RafcU+zGqDXsWpxT8U4CUVjas2pi04tUmudKYPc4WAF6oMHERaDECQdntrvQaUviE8Ot6A+KCuovzhLj+svN+LZP8yFQZ/wkrR2hfGvrQMrcqzw5tqD+HJHI74rb8etz2xSw7QynUZ1vYniuduwpxnt3hC+2NIevw4D3EKTpt4TAHz+Xc/Z5LoCPERJPl5JViEYhtEoFQwY1Pol3LZlL9Y2WbCxOQMvltnQEORg08nncEfbIBEJXXEj9henykrG/77uw/46j3qsLUkFtkPRmNp2srN5VPl02NxqQlNIh2WV7fi6pRbuKIs0QwGWltagJRzF82XN2N+VuLYtbUZUeIH1zTvVMNs/XjYZOelmTbkIQGukNXWG1Kx7VjODphCLP2zZi+fLguDFk/BRnR3uKIf3aiS0R6LoivI46GXRGWHxf5VWvF1tQSiWnHDEjSlj5JDAFz8rx7WPrceN//s13t1wECu+PQBvMNHXKp40i1lCS4hFJDYahACNwWrs92xFY4jHIT8HJK2z7IwQ1Ph0+LzejMNBHXZ2GvBSuQtV3kKc4JyLjDQdGEaOZuhp5psQggNxORTkERBixDs1suElSAw2txpVpbLIegJ8Qha6eLntxAiDLe2JRBXF8Yxt1T43trbWIyaK6pq13dWdvb7nSvu64ORCZLsM8PAdKYkMCCHwC27VMy8REYVj25CXxWB0AYuOWDkkImFMrg2jc+QJmO614nriky11eOIDeS3c7b+cgMOhchhNCeX3N5cZkWcZrYZNe/lOTXIPfZLzkE33I6qX+7H+klDtrJLbw7jRrJrgKCYBnx824YnSGGr9IWSbi9Q6ZhyjQ7oxW3OMiBjSrGG7/PQxMOhZHDjsUbNjJrNmRyP4mISSfBsqJSsIGAiEYGV9SB0fGoMcGkNjUOc/CTFCVMWuLhACL0rawsscg4vmyW1u+YYa/PLBr7Bmh3Zy8J311bhsyRr85z9lAzTDqYPRANj1aUgzZKn7OfVj0BhKXR+/o8OAkGAAx3DQs0a1X2kKVcMvdKE2UIqIXvYctveyplzxpHEmDrs6DXBHhfgzldtptc+Cb1rdkAiQYx4Fq86BplAE2zs8AIC2CI/tHR7Vc84wDC45bSxOLOEQFSQ8/Pau1JPGCcejFPR6IN2QBYZhMN4xXY3wsMe9g23hKL5rk2UWiLEo8+oREBhU+XSAKbEs5MZfjEeOy4hAJIaXvyjvs12RuB4lSgTTJhiQnR1GVAReKvfh7m370RqOgmN1mJp+hjrJVhcshyDxCAjeeKi1HGZ+KFCGzmgzgqIX11zkBMcy+K68HVc/sj4lAVptix+7kzIJS4TgrKl5uOHCCbj+vPHwCx4EBZ/GcFdIDlN0R1sw7UQOaQ4GvgDBdY9uwtWPrFcn3kWJYOOeZjS7Q9hyoBX+pILyER2HXEuaGl5KARhyjPsDeZ6HxWLB+++/j8suu0zdfv3118Pj8eDjjz9O+U00GkU0mphJ9Pl8KCoqgtvthsMhN0KGYcCyLCRJ0jQmZbsoal/U3rYTQlBXV4eioiLNIkZlMXpyzGxFvRcX35+oIVKUr4c4KwNNnya8D6PnOHD4Ox+SE7IxDKBz6MEyBOwgi7UTCYh44x2SmYXOxEIISYhFEycwWFhMX5ALM2dDY2UHqjZqG3fGHBdMNhaNX8ozPwYbB04/iAshQNgbAwgw6lQndAYGNZs8AIBJv8gEq2NQ+ok2DEZvZjHjylzs/6wdwc6EYsCwgM7IQggnrl9nZKC39LyANBaVIISSH6Z8Peq/3bDnGOBvlQelrPEWjDktDTuXN0PkCUxOHZj+pj0IEPbIz/vk63IRICxCMRYMCLJMElhGnmlXkgAkf47/HB0hBs0bOhFp1a4pyDvJBn8bj0AbD52Rhd6ivZhYRIIQluAsNsN5agYsOga5JiNqAhGkGSSYOAKRAO0RDgaWYHKaA7vcflh0HDKMiSKeDFjUbO5C+8EQGBYwOXTy8+qDcJd8z1N/lQWL0wgDa9J4bhiGhYGx4HAwDALAqdfBZTIAhCAihkDi2btCXQJKP0rE4edOtmH0qU7sWdGKiDcGo50Dq2Mg8gR8UITezOKkS7LUZ2HmbIhKYc0z9fAcIknN1qrj4IrfL8foYWBN2Le6Ae56bQjGYN7zqE+EJHYzwC0sSs5KQ/lKuT2ljzLC3yogFpXA6RmIAoHezGLaldlgWQZiFGjY5YM1Q4+aTR752TtTEyAQEYj4YtCZWMy9thgsw0IkohriqWP0aA0TCKT7hACDAosJkaRCsDIMON6IrW/Xqm3CWWiErzkKIgLmNFn+yjPXmVicdGkmQjo9IiLT7UgEmSYD2rt5S64qDmJdkwltkUQ7zTBKMCie8poQqjbKypDFpUfILYDVMTDa4xMIQTHeBjlMuTwLXbwefC+TJhlGPXx8LOX+rToJdr2yjYEQkrBnRSskIfU4yedW2pWrxAzbKbJxk2YgMHESYgToiN9TuoFDmsEICQSHAyGQeKNhADj0OnjjXgL5/QO+f7dBfYd1pm4di9KPMMCsa3MRJHqEYgR6RlbgdQxBrplTSw34BAGdUQEcA4gEsOgk6PwxtB8MomC6HZyRQ2tEvh6bjsAkitj5jjzuGKwcOEPqex72yH32SZdkwZKReA8ZzdwvUSeeGDDxTwSSSMCwSl0nBgwYuOvCqFznBsMAprSeE3to7h1A9gQLxsxNA0DgbYqiYrUbWSeYMfb0NDVxjOzFYtQfK31q6SftCHXFUHBJHrhIDIdXtffaptR7jvdjJ1+TD6vZCpHE4BWi8PLyPZs4Fnlm7boaETE1IzLH6CHGvWrJz6lqoxudNeEeZS2ERMSiBIUz7OAmONT3RscwyDYTREQR7qh2fJvgtKEhGEYwJiLDqIdDr4+vjSQQJB6SSNCww49Au4BAGw+WY2CM11RM1gkUis90InOcBfp4fTaRCCCQIBIdmkJRZBj16Ixq23SagSDdIE+wxgivqR0IAMEOAfs/7ej1mStjs63IBNfpiQQhszKcKPcGEIwnUEo36JFu1IMQIBCLoT3Cq8O3U6+Dy5iYBJKIiK5OL/Z/3AFCEn1XdyLeGIgETP63LGTlpSPRVcjvMwM5HN4vaM/n0HMIxyQIhEBPJDR83gowwJRfZqFhhx8tpYkxr7d2JQkE0YB8bxMvdMGRa0QwxsIvyPtadRyylXUv0I6PCsltLZmwR0Tdt174mqPgDAwM1sR7ozxvR54R9hwDjDYOmeMs8TaaaMftFSHUbvEie4IFbRXymDJjQS4McR1L3o+gcWcAjXu0k8WsjoEUI8pFai+PAW7/02T8YZIcLs1xXK/6d396uSiKqKurw5gxY6DX61P0cpZlwTBMj9uBhF7u8/ngcrng9XpV2+Cnpo+e8Nigo6MDoigiJydHsz0nJwfl5eU9/ubRRx/Fgw8+mLJ9//79sNlkL4XL5cKoUaPQ0NAAtzthlOTm5iI3NxeHDh2C3594AYuKipCRkYHKykpEIonZuOLiYpSUlGDfvn2aF2LChAkwGAzYty+RGauhM4oLTynElzsaARD8/lwX3PlRvFJrR7idB2fhIBbYkXmmAR1bOkFiBOPHcKisFSF4h1YIFADAAIyOgRCWVOOG0TOwjrYgUBWEeZwNLWEWQAjIs8B1igT3dg8AwDLKgowxRkQIB8dkO/zlAfCBgSeUSMaUZ4JUZIXAMdA5AhCDIrwGPRgdA9YgNx5LkRmB6iAs421oibKA0wDEjTRGzyB9uhOxgAihzA/nSQ74yv2IRQlifSQ1YfQMDC4DhC4eEi83fHOBGUQiiDRH4JzigLfUB1OWEZYpDkjmIEz5JpgKzWgVGFiKrfCXB1IGtr7Q2XVoE+TmZ+VYBEVJo6ACvX0GwACFZ6ajZZcfgj8GvpMHEQmkHDOcJXaE17QhFhY1hnYybJoR6QaCG5wmNAgSagB4eK1icIFDhzkGEa16Fk2CiFBMex36E50wumOIdvCqwtQfjI6Bm9HDEwKASOp9xWt4WRjAK8RUpVXuzeP7mjgYXHo18ylv1aM5zIB16gFvDFF/0rvHAq65Gehk9MqhkfigPXe2jsGCTBv+5eHRGokiqN6vBCAE40l2WFjAOdmOYF1oSO+5IV0PxyQHunZ5IIZEmEdbEXJaYB0bQbA2BLbAisxJOrR/3QkxJB/bUmJDWzTRTRunpcsKQFoQgkdQlcae0Dn1OBRI9gwo9yy/F1PTHSjz+AEQFOpZ1PISDgXCKc9GRoBjoh2+Mj9M+SbYZ7vAf9eFcENYK//4M3czBkAEHCyDCXYR33tZmDkJYZFVDbSr0wxoEiTk2ATMyCBgEME7NVYYGEAEQWc0qQ5VrgWm3BAiLVGYJ9oR+tYNKUY0969z6JB+RiZaIzoABOMNLLJ0LHZEREQlgl9k2rG6w68qk1aOQVAkyDISCBKBR2Djco/DsHBOdaJrhwf6dD1MOUYIXQJiQRGxQCzl2Us2AziGQAcGHj7xzjIgMLJAFy+ii1cMfQZmliAsMTjdqsNlmXZUmh34sLYJbVEBwRhgm+yAZ7dX0y93x+AyoF2Q7zedY3DL2Fy81dyMw0EGDSH53U3mV5kmfNARRijGAmYDjNMM6CAAIvHr5IBAjEEAOrk/rwiAD4pAL5Fh5gITfBYjfL0GcQx8so5kmWHONyHcFOnzvVawT7TBONWJlnD8HOkWFFxqBGti49sUD09P7zMH19nZSBcJHFYOfpYBo2NAur1TPWHIMKBNZIGActMsTCyDsQ4ryjwB1AZ6Wk+T3PZSr0dXbANqwr3LmgXEfCtYMJhkkxDmdajlJTSF5GNzDMFYPYcOkcAjEszKcGB+TjqWVdajMyp0M6Dk8xumpCNdIhA2dCDaFk25b1OOEZHWKIzZRgj5tvgzFeJ/CnFjgiPosplQGYri31wWfNgRhIdn4OGTn4X2viXDwJ455zQg0yBhsisTG1vcmCpFcFGGAVuCMXwbiqGLF9DFa/WfX7ks+Kgr3G0cUW7MBNsEG/zlgb7HLgbw6HTw+/tfH3WJw4DPfTx88YgRCwuEJBZZF+QABGiLskChDTggNySGZfpsVwzHwD7BhqDDjFD8/XZwDDItZtT4Q93esaTxsT+MHBxzMhD6qg0xX0z1GGp2GW8Dl29GDECLOnwk2jEpsqHgUgs4M4c0ix6QCDoZXdIYG9+32AaLR4Qpxwh/hR+CL4a0mWlwb4t7iwnAGlg1QZ45XY/ZAo99+/bBbrejpKQEbW1taGlJOCkGq5f7fL5e9XKHw4EDBw70qZcHAr0XaP+pOOY9aU1NTSgoKMCWLVswZ84cdfs999yDjRs34rvvvkv5zU/pSQOA9vZ2ZGRkaFI59+RJU7Z3eCMIRQUUZloRjgXgFzjUh3kIYgR61gReDMPtDyKN4zCzKAM19TGUd7jRHkk0XIZhAZKY/QDk2RUwTMr2vGwzXHYbDtWHEREiEEkMuZkmZKSb0NIeQYbLALvBLq+jIAS8FEaLOwiGAcZnO3CiMxP7PG3wxwSEwjHUNgRTnhmQmomSYVgAsls+I82InEyT+gyCIQGRqIh0ZzzNsJ+HTsfBauZQ3xxCQY4ZLMsgJhLU1gchSQRjCi0wGjjERAntnVEU5FrR7g6jtSPROJVnoCTiYFkGYwutMJt04AWCqjofQICxRXLhS38whpxME9o6I7BZdDDFa5Sx8Rl+SSKIiRJq64MQBBGRSBSmbjOpPcljVL4V6TYrnEYbJjgsaAz50RyKQscawMSfgSRJkIiEiBgAAWDmrAAD6JgIim1GNIcN6IqG4A2FEAyLyEyXn1UkKqKmPqDOUicnHTEaOIwbZcfMzBxYdQYQQlDhDSIoimDjcjKyDE502sAwDHhJQrkvCFEikAiBIEbVkCGWZdHYEkSXTxvu0tu7l59jQYbTBCMnz66KUgxRKQSO5WBkLADDIN9sRJbJgHJfEDEir68iREI47t2x6BwIhqMoq2uDycBiTKFVLnAqElQf9kNM8lblZ5vhSjMCYGBkLeo6IEBeTC0nswCcBjMmOOTj+GMSKr3+FCcqF5cHL0bAixG0dXrR6WUBpLan7u+Y/EwYnDg6GzaLEb6IFy0dYYzOyQDLEkTFMNraYxiT54JEBHhCAdQ2BGHUc5g8JhcSE9NkP2RZBsFQDIcaAtqJyKT2JJ8vC1azSb12QeLl+j6sDlaOw4kuBzrCUQAE6QY9KrwBhEUJLMsiJgoIxz2dZs4GNn7s2pZ2ZLqMMOssiPISyuvaIJHEveZnm5HmMIBlWVh0doy1muHQc9jvaUOBVQ9esqIlLMCm4zDekQhjJowkP4cQiwyTHlFRxAFPWzwGVM6iGotJ6OiKIjfLjI4uHu2dEfW5syyDkiIbjEYddNDDYbBggtMGjmEQjInwCDEUWkyoD4TQGuHhMugxxm5BudeN0VY7CJFQ6vFCxxohiBHEIEASRQSCAQTDOmS4jDDoOehYA3TEgLLDbQiGeVW2RgOLsYU2nJSeBbPOgIPeAMJSGAbWjNFWM+x6Hcq9AcQIAceyyDMbkWHQ4VAgjGK7BSzDgOM4CKKIco8fYVGCKMXgjwZwqCGIWExKeccYlsHoAgucZot6vzqWhV/gUdrlVr1o8v5AusmIsVYTqv1uNAYD6nMDGEiShLF2J7JMVuzqbIEYP1cgJKCuMaRZQwXIfTnLMBhbZIXRwMHAGWBgzQiLQYhSQvHjWA5GzgxREhEVw2AZFmbOCo7Tafo3Kf7OCjGC6jo/xKRxsaf25LTrUZgrt1lJkmBgjdCzRkTEIAgjwcRZwcQV16gYQkwSwLJM3DMur5cSpRhcRg4lznTs6mhBWV0z/EFWjTtObk+adjwmFzaTXtP2SuwWpJmMOOD2IZykAyT35QlnDJG9+RA1439jawg+fyzlXgEgy2VCTqYZDAimp+cCDIOD3iDAMBAkHuPsVriMZoiEoCEYQaHNDD3LIiQIKPcG1OLPSl8QivnV+oiSRFBTH4QgJN4xZTxud/NwOfUw603Qc6Ye70nHMDgxzYYYIQiKErIMetT4g+iKGwDK/hFBlj/DsBCkKMw6K1q7/DjUrI3MSX7H9DoWJaPtmJaejTSzGYcDYYyyGNV9eEnCQb8c6qwkOHHodRjvsKI5wqM5HpmhPnpJgtfnAWdmUX04oJYX6Ek3ys90oDArTdbrpO6eKqjb7ToOJzhtaApF5L7FaMAoixH7ujoQEeV3SIIIA2tCfXsndHr5vg41BNVr6/6OjSmwId1mAwcdolIYRtaEiWl2mPV67Hf7wHfXGxkG0VgYbDykOiqFwDCAWecAQ2QPYlgMqmNDLEZw8JBPe14wsNv0KMzVZgJmWdnTbWAsIJAQkcJgIR9bJDwisXDK/nrWCF28gHpM5OGLBOD1x5CbZUJDSwgeHw+X04Aslwl1jSFEeRHnTipEsStNPc4P8aRJkoT29nZkZ2dDp9Md0560Y95IG0q4Y3d8Ph+cTuePIghRFLFv3z5MmTLluKjZQOkdKuuRAZXzyIDKeeRAZT0yoHIeGRwpOf+YtsFAOeYThxgMBsyaNQtr165Vt0mShLVr12o8axQKhUKhUCgUCoVyLHDMr0kDgDvvvBPXX389Tj75ZJx66ql46qmnEAwGsWjRoqN9aRQKhUKhUCgUCoUyKI4LI23BggVob2/H/fffj5aWFkyfPh2rVq1KSSZyNGAYBi6XS42hphy/UFmPDKicRwZUziMHKuuRAZXzyOB4kvMxvybtSDAc4k4pFAqFQqFQKBTK0Wc42AbH/Jq04Y4kSTh8+HBKFkfK8QeV9ciAynlkQOU8cqCyHhlQOY8Mjic5UyPtR4YQArfb3Wt1ecrxA5X1yIDKeWRA5TxyoLIeGVA5jwyOJzlTI41CoVAoFAqFQqFQhhHHReKQH4pibft8viN+bFEUEQgE4PP5aF2O4xwq65EBlfPIgMp55EBlPTKgch4ZHCk5KzbB0fTIUSMNgN/vBwAUFRUd5SuhUCgUCoVCoVAowwG/3w+n03lUzk2zO0JeZNjU1AS73X7EU3b6fD4UFRWhvr6eZo48zqGyHhlQOY8MqJxHDlTWIwMq55HBkZIzIQR+vx/5+flg2aOzOox60gCwLIvCwsIf9RwOh4N2CiMEKuuRAZXzyIDKeeRAZT0yoHIeGRwJOR8tD5oCTRxCoVAoFAqFQqFQKMMIaqRRKBQKhUKhUCgUyjCCGmk/MkajEUuWLIHRaDzal0L5kaGyHhlQOY8MqJxHDlTWIwMq55HB8SRnmjiEQqFQKBQKhUKhUIYR1JNGoVAoFAqFQqFQKMMIaqRRKBQKhUKhUCgUyjCCGmkUCoVCoVAoFAqFMoygRhqFQqFQKBQKhUKhDCOOGyPt0UcfxSmnnAK73Y7s7GxcdtllqKio0OwTiURw2223ISMjAzabDb/61a/Q2tqqfr9nzx5cffXVKCoqgtlsxoknnoinn35ac4wNGzaAYZiUv5aWlj6vjxCC+++/H3l5eTCbzZg/fz4qKyvV7w8dOoQbbrgBY8eOhdlsRklJCZYsWQKe5/u99w0bNmDmzJkwGo0YN24cXnvtNc33X3/9NS6++GLk5+eDYRh89NFH/R5zOENl3busH3jggZTrnThxYr/HHY5QOfcuZ7/fj8WLF2P06NEwm82YO3cuvv/++36POxwZqXJubm7Gr3/9a5xwwglgWRaLFy9O2WfFihU4+eSTkZaWBqvViunTp+ONN97o87jDGSrr3mU9b968Hq/5oosu6vPYw5GRKucVK1bg3HPPRVZWFhwOB+bMmYPVq1dr9jme9DEq597lfMR0MXKccP7555Nly5aR0tJSsnv3bvKLX/yCjBo1igQCAXWfW265hRQVFZG1a9eS7du3k9NOO43MnTtX/f6VV14ht99+O9mwYQOprq4mb7zxBjGbzeSZZ55R91m/fj0BQCoqKkhzc7P6J4pin9f32GOPEafTST766COyZ88ecskll5CxY8eScDhMCCFk5cqVZOHChWT16tWkurqafPzxxyQ7O5vcddddfR63pqaGWCwWcuedd5IDBw6QZ555hnAcR1atWqXu88UXX5B7772XrFixggAgH3744WAe7bCDyrp3WS9ZsoRMnjxZc73t7e2Der7DBSrn3uV85ZVXkkmTJpGNGzeSyspKsmTJEuJwOEhDQ8OgnvFwYKTKuba2ltx+++3k9ddfJ9OnTyd33HFHyj7r168nK1asIAcOHCBVVVXkqaeeSnkXjiWorHuXdWdnp+ZaS0tLCcdxZNmyZQN4ssOLkSrnO+64gzz++ONk27Zt5ODBg+TPf/4z0ev1ZOfOneo+x5M+RuXcu5yPlC523Bhp3WlrayMAyMaNGwkhhHg8HqLX68l7772n7lNWVkYAkK1bt/Z6nFtvvZWcffbZ6v+Vl6Wrq2vA1yJJEsnNzSV/+9vf1G0ej4cYjUbyzjvv9Pq7//mf/yFjx47t89j33HMPmTx5smbbggULyPnnn9/j/sd6p9ATVNYJWS9ZsoRMmzZtwNd7LEHlLMs5FAoRjuPIZ599ptln5syZ5N577x3wPQxXRoqckznrrLN6VNx7YsaMGeS+++4b8LGHM1TWvfPkk08Su92uUXiPVUainBUmTZpEHnzwwR6/O970MSrnhJyPlC523IQ7dsfr9QIAXC4XAGDHjh0QBAHz589X95k4cSJGjRqFrVu39nkc5RjJTJ8+HXl5eTj33HOxefPmPq+ltrYWLS0tmnM7nU7Mnj17SOdOZuvWrZrjAsD555/f53GPN6istcetrKxEfn4+iouLcc011+Dw4cN9HvdYgcpZPm4sFoMoijCZTJp9zGYzNm3a1OexjwVGipwHCyEEa9euRUVFBX72s58d0WMfLaise+eVV17BVVddBavVesSP/VMzUuUsSRL8fv+P8n4MR6ictb87ErrYcWmkSZKExYsX4/TTT8dJJ50EAGhpaYHBYEBaWppm35ycnF7jWrds2YLly5fjd7/7nbotLy8PL774Ij744AN88MEHKCoqwrx587Bz585er0c5fk5OzoDPXVVVhWeeeQY333xzn/fa0tLS43F9Ph/C4XCfvz0eoLLWynr27Nl47bXXsGrVKrzwwguora3FmWeeCb/f3+exhztUzgk52+12zJkzB3/961/R1NQEURTx5ptvYuvWrWhubu7z2MOdkSTngeL1emGz2WAwGHDRRRfhmWeewbnnnntEjn00obLunW3btqG0tBQ33njjET3u0WAky3np0qUIBAK48sorB/W7YxEqZ62cj5QuphvU3scIt912G0pLS3/QrHJpaSkuvfRSLFmyBOedd566fcKECZgwYYL6/7lz56K6uhpPPvkk3njjDbz11lsaAa9cuRIcxw3q3I2NjbjgggtwxRVX4KabblK322w29fO1116LF198cSi3dlxBZa3lwgsvVD9PnToVs2fPxujRo/Gvf/0LN9xww6CubThB5azljTfewG9/+1sUFBSA4zjMnDkTV199NXbs2DGo6xpuUDmnYrfbsXv3bgQCAaxduxZ33nkniouLMW/evEFd23CDyrp3XnnlFUyZMgWnnnrqoH873Bipcn777bfx4IMP4uOPP0Z2dvagznksQuWslfOR0sWOOyPtD3/4Az777DN8/fXXKCwsVLfn5uaC53l4PB6NVd/a2orc3FzNMQ4cOIBzzjkHv/vd73Dffff1e85TTz1VfTEvueQSzJ49W/2uoKBAnd1ubW1FXl6e5tzTp0/XHKupqQlnn3025s6di5dfflnz3e7du9XPDodDva/kTDnKcR0OB8xmc7/XfixDZd2/rNPS0nDCCSegqqqq33sbrlA5p8q5pKQEGzduRDAYhM/nQ15eHhYsWIDi4uJ+7224MtLkPFBYlsW4ceMAyOE+ZWVlePTRR49pI43KuneCwSDeffddPPTQQ4P+7XBjpMr53XffxY033oj33nsvJXT9eITKuX85D1kX+8Gr2oYJkiSR2267jeTn55ODBw+mfK8sYHz//ffVbeXl5SkLGEtLS0l2dja5++67B3zu+fPnk8svv7zPa8vNzSVLly5Vt3m93pQFjA0NDWT8+PHkqquuIrFYbEDnvueee8hJJ52k2Xb11Vcf14lDqKwT9CVrQgjx+/0kPT2dPP300wM6x3CCyjlBf3J2u93E6XSSl156aUDnGE6MVDknM5jEIYsWLSJnnXXWoM8xHKCy7l/Wy5YtI0ajkXR0dAz62MOFkSznt99+m5hMJvLRRx/1u++xro9ROQ9MzoQMXRc7boy03//+98TpdJINGzZoUl6GQiF1n1tuuYWMGjWKrFu3jmzfvp3MmTOHzJkzR/1+3759JCsri1x77bWaY7S1tan7PPnkk+Sjjz4ilZWVZN++feSOO+4gLMuSr776qs/re+yxx0haWhr5+OOPyd69e8mll16qSQXa0NBAxo0bR8455xzS0NCgOX9fKOm67777blJWVkaee+65lBTNfr+f7Nq1i+zatYsAIE888QTZtWsXqaurG9QzHi5QWfcu67vuuots2LCB1NbWks2bN5P58+eTzMxMzX0dK1A59y7nVatWkZUrV5KamhqyZs0aMm3aNDJ79mzC8/ygnvFwYKTKmRCi9suzZs0iv/71r8muXbvI/v371e8feeQRsmbNGlJdXU0OHDhAli5dSnQ6HfnHP/4x4Oc7nKCy7l3WCmeccQZZsGBBv8cbzoxUOb/11ltEp9OR5557TvMbj8ej7nM86WNUzr3L+UjpYseNkQagx7/kGiPhcJjceuutJD09nVgsFnL55ZdrhLFkyZIejzF69Gh1n8cff5yUlJQQk8lEXC4XmTdvHlm3bl2/1ydJEvnLX/5CcnJyiNFoJOeccw6pqKhQv1+2bFmv99Af69evJ9OnTycGg4EUFxen1FVR0pd2/7v++uv7PfZwhMq6d1kvWLCA5OXlEYPBQAoKCsiCBQtIVVVVv8cdjlA59y7n5cuXk+LiYmIwGEhubi657bbbNAPEscRIlnN/13zvvfeScePGEZPJRNLT08mcOXPIu+++2+9xhytU1r1fMyEJL8OaNWv6Pd5wZqTK+ayzzupX1zqe9DEq595leKR0MYYQQkChUCgUCoVCoVAolGHBcZmCn0KhUCgUCoVCoVCOVaiRRqFQKBQKhUKhUCjDCGqkUSgUCoVCoVAoFMowghppFAqFQqFQKBQKhTKMoEYahUKhUCgUCoVCoQwjqJFGoVAoFAqFQqFQKMMIaqRRKBQKhUKhUCgUyjCCGmkUCoVC+clZuHAhLrvssqN2/uuuuw6PPPLIUTt/TzzwwAOYPn36gPdftWoVpk+fDkmSfryLolAoFMpRgRppFAqFQjmiMAzT598DDzyAp59+Gq+99tpRub49e/bgiy++wO23365umzdvHhYvXpyy72uvvYa0tLSf7uIGwQUXXAC9Xo+33nrraF8KhUKhUI4wuqN9ARQKhUI5vmhublY/L1++HPfffz8qKirUbTabDTab7WhcGgDgmWeewRVXXHFUryEZQghEURzSbxcuXIi///3vuO66647wVVEoFArlaEI9aRQKhUI5ouTm5qp/TqcTDMNottlstpRwx3nz5uGPf/wjFi9ejPT0dOTk5OAf//gHgsEgFi1aBLvdjnHjxmHlypWac5WWluLCCy+EzWZDTk4OrrvuOnR0dPR6baIo4v3338fFF1885Pt74YUXUFJSAoPBgAkTJuCNN95Qvzt06BAYhsHu3bvVbR6PBwzDYMOGDQCADRs2gGEYrFy5ErNmzYLRaMSmTZs05/j666+h1+vR0tKi2b548WKceeaZ6v8vvvhibN++HdXV1UO+HwqFQqEMP6iRRqFQKJRhweuvv47MzExs27YNf/zjH/H73/8eV1xxBebOnYudO3fivPPOw3XXXYdQKARANn5+/vOfY8aMGdi+fTtWrVqF1tZWXHnllb2eY+/evfB6vTj55JOHdI0ffvgh7rjjDtx1110oLS3FzTffjEWLFmH9+vWDPtZ//dd/4bHHHkNZWRmmTp2q+e5nP/sZiouLNQagIAh466238Nvf/lbdNmrUKOTk5OCbb74Z0v1QKBQKZXhCjTQKhUKhDAumTZuG++67D+PHj8ef//xnmEwmZGZm4qabbsL48eNx//33o7OzE3v37gUAyxzrUwAABClJREFUPPvss5gxYwYeeeQRTJw4ETNmzMCrr76K9evX4+DBgz2eo66uDhzHITs7O+W7559/Xg3FVP5uueUWzT5Lly7FwoULceutt+KEE07AnXfeiV/+8pdYunTpoO/3oYcewrnnnouSkhK4XK6U72+44QYsW7ZM/f+nn36KSCSSYoTm5+ejrq5u0OenUCgUyvCFGmkUCoVCGRYke5M4jkNGRgamTJmibsvJyQEAtLW1AZATgKxfv15jVE2cOBEAeg3/C4fDMBqNYBgm5btrrrkGu3fv1vw99NBDmn3Kyspw+umna7adfvrpKCsrG/T99ufNW7hwIaqqqvDtt98CkJOYXHnllbBarZr9zGaz6l2kUCgUyvEBTRxCoVAolGGBXq/X/J9hGM02xbBSUs4HAgFcfPHFePzxx1OOlZeX1+M5MjMzEQqFwPM8DAaD5jun04lx48ZptvXkcesLlpXnPgkh6jZBEHrct7ux1Z3s7GxcfPHFWLZsGcaOHYuVK1eq69qScbvdyMrKGtR1UigUCmV4Qz1pFAqFQjkmmTlzJvbv348xY8Zg3Lhxmr/eDCClDtmBAweGdM4TTzwRmzdv1mzbvHkzJk2aBACqsZSc4TI5ichgufHGG7F8+XK8/PLLKCkpSfHiRSIRVFdXY8aMGUM+B4VCoVCGH9RIo1AoFMoxyW233Qa3242rr74a33//Paqrq7F69WosWrSo15T2WVlZmDlzZko2xYFy991347XXXsMLL7yAyspKPPHEE1ixYgX+9Kc/AZBDD0877TQ1IcjGjRtx3333Dfkezz//fDgcDjz88MNYtGhRyvfffvstjEYj5syZM+RzUCgUCmX4QY00CoVCoRyT5OfnY/PmzRBFEeeddx6mTJmCxYsXIy0tTQ077Ikbb7xxyAWgL7vsMjz99NNYunQpJk+ejJdeegnLli3DvHnz1H1effVVxGIxzJo1C4sXL8bDDz88pHMBcvjkwoULIYoifvOb36R8/8477+Caa66BxWIZ8jkoFAqFMvxgSHLgPIVCoVAoxznhcBgTJkzA8uXLjwkP1A033ID29nZ88sknmu0dHR2YMGECtm/fjrFjxx6lq6NQKBTKjwFNHEKhUCiUEYXZbMb//d//9Vn0ejjg9Xqxb98+vP322ykGGiAXzn7++eepgUahUCjHIdSTRqFQKBTKMGTevHnYtm0bbr75Zjz55JNH+3IoFAqF8hNCjTQKhUKhUCgUCoVCGUbQxCEUCoVCoVAoFAqFMoygRhqFQqFQKBQKhUKhDCOokUahUCgUCoVCoVAowwhqpFEoFAqFQqFQKBTKMIIaaRQKhUKhUCgUCoUyjKBGGoVCoVAoFAqFQqEMI6iRRqFQKBQKhUKhUCjDCGqkUSgUCoVCoVAoFMowghppFAqFQqFQKBQKhTKM+P+1wxovCDco6wAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "data_online = data.copy()\n",
+    "data_online['gmt_create'] = pd.to_datetime(data_online['gmt_create'])\n",
+    "\n",
+    "qps = data_online.groupby('predict_type').apply(\n",
+    "    lambda grp: grp.set_index('gmt_create').resample('Min').size().mean()\n",
+    ")\n",
+    "print(qps)\n",
+    "\n",
+    "plot_data = data_online\n",
+    "\n",
+    "qps_hourly = (\n",
+    "    plot_data.groupby('predict_type')\n",
+    "    .resample('H', on='gmt_create')\n",
+    "    .size()\n",
+    "    .reset_index(name='count')\n",
+    ")\n",
+    "fig, ax = plt.subplots(figsize=(10, 3))\n",
+    "# Plot the time series with hue based on predict_type\n",
+    "sns.lineplot(x='gmt_create', y='count', hue='predict_type', data=qps_hourly, ax=ax,palette='YlGnBu')\n",
+    "ax.legend(loc='upper left', ncol=1, title='Task Category')\n",
+    "plt.xlabel('Time (Hourly)')\n",
+    "plt.ylabel('Query Volume')\n",
+    "plt.grid(True, linestyle='--', alpha=0.6)\n",
+    "plt.show()\n",
+    "\n",
+    "# fig.savefig('qps_hourly.pdf', bbox_inches='tight', dpi=120)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_1820367/1190207994.py:3: FutureWarning: \n",
+      "\n",
+      "The `ci` parameter is deprecated. Use `errorbar=None` for the same effect.\n",
+      "\n",
+      "  sns.barplot(x='predict_type', y='exec_time_seconds', data=data_online, ax=ax, hue='num_lora', ci=None, palette='YlGnBu', alpha=0.9)\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(10, 3))\n",
+    "\n",
+    "sns.barplot(x='predict_type', y='exec_time_seconds', data=data_online, ax=ax, hue='num_lora', ci=None, palette='YlGnBu', alpha=0.9)\n",
+    "\n",
+    "ax.set_ylabel(\"Generation Time (s)\", fontsize=12)\n",
+    "ax.set_xlabel(\"Workload Category\", fontsize=12)\n",
+    "ax.legend(title='Num. LoRA', title_fontsize='12', fontsize='10', loc='upper right')\n",
+    "for p in ax.patches:\n",
+    "    if p.get_height() > 0:\n",
+    "        ax.annotate(f'{p.get_height():.1f}', (p.get_x() + p.get_width() / 2., p.get_height()), ha='center', va='bottom', fontsize=10, color='black')\n",
+    "ax.grid(axis='y', linestyle='--', alpha=0.6)\n",
+    "\n",
+    "ax.set_ylim(0, 60)\n",
+    "plt.show()\n",
+    "# fig.savefig('..predict_type_exectime.pdf')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/cluster-trace-v2026-GenAI/lora_request_trace.tar.gz b/cluster-trace-v2026-GenAI/lora_request_trace.tar.gz
index c2c19ef..154f9a2 100644
Binary files a/cluster-trace-v2026-GenAI/lora_request_trace.tar.gz and b/cluster-trace-v2026-GenAI/lora_request_trace.tar.gz differ