From 5d224d11024875e6b97eec465ab34236bab387c8 Mon Sep 17 00:00:00 2001
From: Miguel Moraes <miguelmoraes94@gmail.com>
Date: Mon, 27 Nov 2023 08:59:23 +0000
Subject: [PATCH] Solved lab

---
 your-code/main.ipynb            | 3416 +++++++++++++++++++++++++++++--
 {data => your-code}/website.csv |    0
 2 files changed, 3301 insertions(+), 115 deletions(-)
 rename {data => your-code}/website.csv (100%)
 mode change 100755 => 100644

diff --git a/your-code/main.ipynb b/your-code/main.ipynb
index a5caf8b..f2038a4 100755
--- a/your-code/main.ipynb
+++ b/your-code/main.ipynb
@@ -21,7 +21,9 @@
     "%matplotlib inline\n",
     "\n",
     "import numpy as np\n",
-    "import pandas as pd"
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import matplotlib.pyplot as plt"
    ]
   },
   {
@@ -39,9 +41,224 @@
    "cell_type": "code",
    "execution_count": 2,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "websites = pd.read_csv('../data/website.csv')"
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL</th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>WHOIS_STATEPRO</th>\n",
+       "      <th>WHOIS_REGDATE</th>\n",
+       "      <th>WHOIS_UPDATED_DATE</th>\n",
+       "      <th>...</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>APP_BYTES</th>\n",
+       "      <th>SOURCE_APP_PACKETS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>700</td>\n",
+       "      <td>9</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>AK</td>\n",
+       "      <td>7/10/1997 4:00</td>\n",
+       "      <td>12/09/2013 0:45</td>\n",
+       "      <td>...</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>3812</td>\n",
+       "      <td>39</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>None</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>12/05/1996 0:00</td>\n",
+       "      <td>11/04/2017 0:00</td>\n",
+       "      <td>...</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>4278</td>\n",
+       "      <td>61</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>5 rows × 21 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "0   M0_109          16                          7  iso-8859-1   \n",
+       "1  B0_2314          16                          6       UTF-8   \n",
+       "2   B0_911          16                          6    us-ascii   \n",
+       "3   B0_113          17                          6  ISO-8859-1   \n",
+       "4   B0_403          17                          6       UTF-8   \n",
+       "\n",
+       "                  SERVER  CONTENT_LENGTH WHOIS_COUNTRY WHOIS_STATEPRO  \\\n",
+       "0                  nginx           263.0          None           None   \n",
+       "1          Apache/2.4.10         15087.0          None           None   \n",
+       "2  Microsoft-HTTPAPI/2.0           324.0          None           None   \n",
+       "3                  nginx           162.0            US             AK   \n",
+       "4                   None        124140.0            US             TX   \n",
+       "\n",
+       "      WHOIS_REGDATE WHOIS_UPDATED_DATE  ...  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0  10/10/2015 18:21               None  ...                     0           2   \n",
+       "1              None               None  ...                     7           4   \n",
+       "2              None               None  ...                     0           0   \n",
+       "3    7/10/1997 4:00    12/09/2013 0:45  ...                    22           3   \n",
+       "4   12/05/1996 0:00    11/04/2017 0:00  ...                     2           5   \n",
+       "\n",
+       "   APP_BYTES  SOURCE_APP_PACKETS  REMOTE_APP_PACKETS  SOURCE_APP_BYTES  \\\n",
+       "0        700                   9                  10              1153   \n",
+       "1       1230                  17                  19              1265   \n",
+       "2          0                   0                   0                 0   \n",
+       "3       3812                  39                  37             18784   \n",
+       "4       4278                  61                  62            129889   \n",
+       "\n",
+       "   REMOTE_APP_BYTES  APP_PACKETS  DNS_QUERY_TIMES  Type  \n",
+       "0               832            9              2.0     1  \n",
+       "1              1230           17              0.0     0  \n",
+       "2                 0            0              0.0     0  \n",
+       "3              4380           39              8.0     0  \n",
+       "4              4586           61              4.0     0  \n",
+       "\n",
+       "[5 rows x 21 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites = pd.read_csv('website.csv')\n",
+    "websites.head()"
    ]
   },
   {
@@ -67,18 +284,111 @@
    "cell_type": "code",
    "execution_count": 3,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                           object\n",
+       "URL_LENGTH                     int64\n",
+       "NUMBER_SPECIAL_CHARACTERS      int64\n",
+       "CHARSET                       object\n",
+       "SERVER                        object\n",
+       "CONTENT_LENGTH               float64\n",
+       "WHOIS_COUNTRY                 object\n",
+       "WHOIS_STATEPRO                object\n",
+       "WHOIS_REGDATE                 object\n",
+       "WHOIS_UPDATED_DATE            object\n",
+       "TCP_CONVERSATION_EXCHANGE      int64\n",
+       "DIST_REMOTE_TCP_PORT           int64\n",
+       "REMOTE_IPS                     int64\n",
+       "APP_BYTES                      int64\n",
+       "SOURCE_APP_PACKETS             int64\n",
+       "REMOTE_APP_PACKETS             int64\n",
+       "SOURCE_APP_BYTES               int64\n",
+       "REMOTE_APP_BYTES               int64\n",
+       "APP_PACKETS                    int64\n",
+       "DNS_QUERY_TIMES              float64\n",
+       "Type                           int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.dtypes"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 4,
    "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                            0\n",
+       "URL_LENGTH                     0\n",
+       "NUMBER_SPECIAL_CHARACTERS      0\n",
+       "CHARSET                        0\n",
+       "SERVER                         1\n",
+       "CONTENT_LENGTH               812\n",
+       "WHOIS_COUNTRY                  0\n",
+       "WHOIS_STATEPRO                 0\n",
+       "WHOIS_REGDATE                  0\n",
+       "WHOIS_UPDATED_DATE             0\n",
+       "TCP_CONVERSATION_EXCHANGE      0\n",
+       "DIST_REMOTE_TCP_PORT           0\n",
+       "REMOTE_IPS                     0\n",
+       "APP_BYTES                      0\n",
+       "SOURCE_APP_PACKETS             0\n",
+       "REMOTE_APP_PACKETS             0\n",
+       "SOURCE_APP_BYTES               0\n",
+       "REMOTE_APP_BYTES               0\n",
+       "APP_PACKETS                    0\n",
+       "DNS_QUERY_TIMES                1\n",
+       "Type                           0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.45592363840539024"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(websites['CONTENT_LENGTH'].isna().sum())/(websites.shape[0])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "# I think that the columns we will use as features are the numeric ones. The column we will predict is \"Type\". I would only change the \"WHOIS_UPDATED_DATE\" to datetime."
    ]
   },
   {
@@ -102,21 +412,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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l0dvb2zhlyhRjQkKCJL/+/fsb27RpY3Gdql0H33rrLas6IiIijPfcc4/R19fXqFQqjf7+/sZBgwYZP/74Y3Mca7sOJiYmGu+++26jh4eHUavVGocPH27866+/rO6at2LFCmNoaKhRoVAYAeP69euNRqPlroNGo2nnwIULFxqbNGliVCqVxoCAAOMjjzxizMnJkcRr0qSJcdSoURb3079/f2P//v2t3uv1ULnroD2s7Rx48eJF4+23327UarVGDw8P44QJE4zx8fFWd9ZbtGiRsVGjRka5XC4pP1vaq85VlV9hYaExPDzc2Lp1a2NRUZEk3qOPPmpUKpXGY8eO/e37tLUjZF1sQqfTGZ966iljYGCgUaPRGDt37mzcunWr1TrdvXu3sVOnTka1Wm0EzPdXtetgRkaGJP706dONzs7OFnqt2fjrr79uDAkJMarVamOrVq2Mn332mTlfa+Xw4YcfGps1a2ZUKpXG8PBw49dff22v+AQCwS1CZjQajbfEwxMIBAKBQCAQ1BmZTMajjz7K+++/f6ulCASCOiDWaAkEAoFAIBAIBAJBPSMcLYFAIBAIBAKBQCCoZ8RmGAKBQCAQCAT/AsRqD4Hg34UY0RIIBAKBQCAQCAT/bzl48CB33HEHjRo1QiaTsXXr1lrTHDhwgC5duqDRaGjatCkff/zxDV9XOFoCgUAgEAgEAoHg/y1FRUV06NChzhvJxMTEMHLkSPr27cuZM2d47rnnmDt3Lps3b76h64pdBwUCgUAgEAgEAsF/AplMxpYtWxg7dqzNOAsXLuTnn38mMjLSHPbwww8TERFh8UFze4gRLYFAIBAIBAKBQPCvQafTkZ+fLzl0Ol295X/kyBGLj78PGzaMkydPUl5eXud8xGYYAoGgVn5VtrzVEqwSOND3Vkuwybfjd91qCVY5te/CrZZgFaPRcKslWMVgaJiTPlSO6lstwSoVurJbLcEmcoXiVkuwilKtutUSrKLX62+1BKs0VBvTFZXcaglW+WNb/1t27X+y7XDi+cksXbpUErZ48WKWLFlSL/mnpqbi5+cnCfPz86OiooLMzEwCAgLqlI9wtAQCgUAgEAgEAsG/hkWLFjF//nxJmFpdvx1QMplM8nfVaqua4fYQjpZAIBAIBAKBQCCoV2TKujskN4para53x+p6/P39SU1NlYSlp6fj4OCAl5dXnfMRjpZAIBAIBAKBQCCoV+QO/5yj9U/Tq1cvtm3bJgnbtWsXXbt2RalU1jkfsRmGQCAQCAQCgUAg+H9LYWEhZ8+e5ezZs4Bp+/azZ88SHx8PmKYiTps2zRz/4YcfJi4ujvnz5xMZGcm6detYu3YtTz311A1dV4xoCQQCgUAgEAgEgnpFpmw44zknT55k4MCB5r+r1ndNnz6dDRs2kJKSYna6AEJDQ/ntt9948skn+eCDD2jUqBGrVq3i7rvvvqHrCkdLIBAIBAKBQCAQ/L9lwIAB2Pt08IYNGyzC+vfvz+nTp2/qusLREggEAoFAIBAIBPXKv3mNVn3RcMb0BAKBQCAQCAQCgeD/CWJESyAQCAQCgUAgENQr/+T27v8WxIiWQCAQCAQCgUAgENQzYkRLIBDcEAoXZ1o8PwfXDuG4dmyN2seTy8tWc+Xl9+uUXuXjSfjrT+M3ciAKJw355y4R9dIKsvYdtYjrNagXLZc+gWv7cPTFpaT9to9Lz75FWUa2RVy5xpGAGQ/g3n8QCq0WXUI8aZu+Jnf/nlo1abt0x2/KDJyah2GsKKfwfAQpaz+mNC62On8nJ3zuvBtt526ogxsjd3SkLDWFnD27yNjyA8byMuv36wDDuilp31SBoxoyco3sj6gg4preriY3Z+jXXkkjLxkBXnIc1TK+21/GqcuW6YZ1c6BlsAIPFxlKB8gvNnI1ycDeMxXkFtpe/FuFQiHj3rH+DOvvjae7ktR0HT//nsHWnem1pgXQqOXMnBhI/54euDo7EJ9cysafU9h/JMduundfakn7Vlq27kxn9fpYG7oCGD7Ax6zrp13pbN2ZVmdd908Mon9PT1xdHIhPLmHjTynsO2JpP9fz3uJw2rdyZevONFauta7rvnGNGDHAB08Pk66tO9PYsqPuumZNCmJALy+zrm+2JrPvsFTXwjlNGT7AxyJ9fFIJs5+Lspq3QgGT7vBj6G1eeLo7kJZRxs97Mvl5d2adtc24O4B+3d3ROitISNGx6dc0DhzLlcS783ZvBvb0oJGfGkeNnNz8Ci5eKeKLHxKJSyyxouvW1+UHXyRa0QWT7wxgWD8vk66MMn7+PZ2fdmXUWdfMCY3o39MDrbMDCSmlbPw5lf1HpbY/dpgPg3p70shPYyqvvAouXCnk6y0pJGcarOqaOMqX22/zwNPNgdTMMn7Zm822PVl11jXtLj/6dnMz1+P3v2Vw8HieJF7rFk7c3seDpo0dCQlUo1TKmfH0JdKzyq3me6vt65uf07gWbfmsbQj29fb7l6zqmjahMSOH+OPlqSIlrZQff01i8y/JddLlqJEze0oog27zQatVEp9YzFc/xLPnkNQ+/9jWv075/a8Ra7SEoyVowAwYMICOHTuyYsUKSfjWrVsZN24cRqORDRs2MHPmTPM5X19funfvzuuvv06bNm3M4TNmzCA3N5etW7fesI6QkBDmzZvHvHnzLM7FxsYSGhpqNd2RI0fo2bOnWeOwYcPYsWOH+Xxubi4eHh7s27ePAQMGmMP37dvHO++8w7FjxygoKCAwMJCuXbvy6KOP0rhxY5vXq2Lx4sXMmDGD0NBQzpw5Q8eOHSXnbZVrXVF5udP4gXvIP3eJtJ9303jWPXVOK1cp6bFrA0o3Vy7Mf5Wy9CyaPHIf3X9dw7FhM8k+dMIc17NvN7r/8hnpvx3g5F1zUPl6Eb78KXrs2sCfPe7GUCZtCIQsfgWnsFakrPsYXWICHgNvJ+S5JcTKZOTu221Tk2uv2whd/Cp5R/4gZtkLKJyd8Z86k+bvfMDlx2dTlmJ6Iap8/fAZdw/Ze3aSvnkThtISnNu2x3/q/Wg7d+Pas09azX/qUBVBPnJ2HC8nI9dIp+YK7h2sQkYZZ+04W16ucjo2V5CSZeBSgp5OzW0/rjUqGRHX9KTnGNCVg6+HjMGdlLRuouDd70sp1tlMCsAT9zdmyG1ebPg+iahrxXTt4MqcacE4auR8+1Oq/cTAkvnNaNnUmTUbE0lM0TG4jycvzG2GXBbN3sPWGyp3DvWhkb+6Fl1NuL2vN+u/SyQquoiu7d14dHpjnBzlfLM1pVZdSxe0MOn6NoHElFIG9fHihSeaI5NfY++f1husdw7zpZGfxm6+8x4IYWhfb9ZtSuTStUK6dXDnsRlNcHJU8PWW2htQy54KI7yZM599k0BCSimDb/PipXktkMuusqeGrlKdnvnLpA24sjLLhnkVj08LZnBvDz7/MYXLMSV0aaflkfsCcdLI2fhL7Y7zS3NDCAt1Yt13KSSl6hjYy4Pn5oQgl8Wy72iuOZ6riwMnzucT/WsphUUVBPiquWeULx+80pqHF10gMaVUkm9Drcu5MxszpI8XG35IrtTlypypwThpFHz7cx1s/8lmhDV1Yu3GJBJTSxnU25PnH2+KTB7NvsPVzpariwPHI/KJjkulsEhPgK+aiXf4s3pZOHOXXSUpVeo8PDolkEG93flyS5qpHtu68NDkABw1cr77tXYn8IVHG9Mi1IkNP6SSlKZjQA93nn24MXJZPPuPVTtbHVu50LG1C9fiSygu0dOhlYvdfG+1fa18qcW/yr4WPNKCYQP9WPNVDJeuFNC9sydPzG6Ok6MDX34fbzctwKvPtaFVCy0ffx5DfFIJt/f3ZekzrZHLI/n9QHV5P/SU5c54rcNceeLB5rVe459ETB0Ujpbg/wGurq5ERUVhNBpJSkrimWeeYdSoUVy+fBmVSvU/0bB7926JYwfg5eVl/r+DgwN79uxh3759ku841OTDDz/kscceY+rUqWzatInQ0FBSUlI4ceIETz75JMePHyclpfql8fbbb7Njxw527652JFxcXMjMrFvv4t+hJC6JXT7dAFB6edyQoxV8/wRc27bkz74TyT16FoCs/cfoe+onwl9/msN9qvNq9cYzFF2O5fTEuRj1JoekJDaR3gc3EjRzPPGffGuOq+3WE9cu3YldvsQ8glUYcQalnx+NZs8h98BeMFhvnDZ64GFKY6KJXfq8Oazo4l+0WvcN/tNnEf/6ywCUpaZwcdoEDKXVL/jCs6cxlJYS+OCjOLdpR9GF85K8WwbLCQtS8M2eMvMIVnSKAXetjJE9lURE67G122xMioGXvzRdK9BbZtfR+ulPqdMZnQI5BUbuH6GmdYiCk1G2HbomQRqGD/Bm/XdJfPeLqfc3IrIAVxcH7hsXwC+7Mygosp2+e0c3urZ349XV0eYRmYiLBfh6q3jwviD2H8nGUOMe/bxVzJoUxBsfxrB0gfWGQJMgR0YM9GHdpkS++yXVnK+r1oH7xjVi2+/pddL1yqqrZl1nLxbg56PmofuC2X84y1KXj4oHJgXz+ofRLFvQwmq+IUGOjBzow9qNiWzalmLW5aZ1YMpdjfh5V5pdXT06udGtgxsvr7xqbsCdvZCPn7eah6Y2Zl8NXUYjRF4ptMhH5WjppDYJ1DCsnycbNqfww3ZTY/zcpUJcXRRMHuPPr/uy7Grr1l5Ll7auvPZRLPsrG70Rlwrx9VbywKRGHDiWa9b25RapE3I+qojIq0Wseb2V2Wk362qgddkkUMPw/t6s/z6Z73812f65yEJcXRy4d2wAv+ypxfY7uNKlnSvL349mX+XobcTFQvy81Tw4OYgDR3LMur7YLG3sn7tUSOTVIta+1YaBPd35amt1o7lxIzVD+3rwxY9pbN6RaS5frYsDk0b78tv+bArt6OraTkvntlre+CSeA5VO1blLRfh6Kbn/ngAOHs8z6/p2Wzrf/Gy69l3DvO06WsK+qqmLfYU2dmL07f58+mUM324xjaae+SsPN60D0yc2Zuv2ZAoKK2zq6tnFk+6dPFny1kV2HzSV95nzufj7qpkzsyl7DqWbX2sXogos0o8Z3giDwYhcLpydW4lYoyX41yOTyfD39ycgIICuXbvy5JNPEhcXR1SU9ak1/wReXl74+/tLDqVSaT7v7OzMzJkzefbZZ23mER8fbx45+/zzzxk0aBChoaH07t2bJ554gpMnT6JQKCTXcHFxwcHBwSKsoeJ35xAKL0WbnSwAo15P0jc/49G9A+pGvgCoG/ni3q09SV//ZHayAHKOnKEwKgb/O4dI8nXv0w99cTG5B/dLwrN3/obK2wen8NZW9Si0rmiCm5B/QjptsTw9jdK4GNx69wW56TFpKC2VOFlVFEdFAqD08bU41zZEga7MyPlo6Uv+ZJQeN2cZjX1tP4Jrn/Bnn8ISUw42/Eszfbp6IJfL2LFf6pzvOJCJRq2gWwc3u+lv6+ZOcYmeA0elI1c7D2Th7akivLmzRZonZzfh1Pl8/jyZa0eXu1VdO/dX6uroXosuD6u6duzPMOlqYfk7mT87lFPn8/jzhO0pj326mcpr+z7pqML2fRlo1Aq616aruyfFJXr2H5H2ku/Yn4GPp4pWVnTVld6d3ZDLZew6JL3nXQez0ajldG2ntZu+TxdTXR48nitNfygbbw8V4c2c7KbPKzA1GvV6qfU22Lqs1LXzQA1dB7JM5dXB1a6uPlW2f0x6jZ0HMm3a/vXk5ps6SPQ1fIBenV2Ry2X8/oc039//yDHpamvfRnp3dqW4VM+hE9Jpgr//mYO3h5KWTavr0c5nhazkK+yrirrYV9+e3sjlMn7bLXUaf92dhkatoGcXT7u6+vXypri4gn1/SJ81v+1OxcdLTesw2/bp6KhgYB8fzv6VZzPO/wK5g+wfO/4tCEdL8P+K3NxcvvnmGwCJo9MQWLJkCefPn+eHH36wen7z5s2Ul5fzzDPPWD0vk/17Hiy20LZpQf55Swe4oDJM27pFZbwwAJtxq85XoQkJpTQ+FgzSFktpzDUAHEOsT7eUVdqIsdxyPYKxrAyFxhF1QKC9W0LbsbPpWtet56rCz1NOeq7Rojc0Ndvk/fh51G+dymXgoIBGXjLu6K0kI9fAXzH214KFBGvIySsnJ0/asxoTX1J53tF++iBH4pNKLRy66PhiAEJrpB8x0JvwZs68v8H+tJnQYKdKXTVG62zkay19fFKJFV0lVtOPHOhDeDNnVq+Ps59vY0f7uhrXpsuROGu64qzfl0olZ/Onndi9sTvffdSJufc3QeussJp3kyANufmWdRmdYOogCAmyr61JkIaEFMu6jKlM38RKerkMlA4yggPUPHl/Y3Jyy9lRw3FpqHUZEuRo3fYTKvOtpbxCghyJT7Zm+yXm8zW5vrzmzw4hJ6/cwqFqEqghN7+CnHzrupoE2p+u1iRQQ0Kyzk492p+yazPfhmBfef8e+2ra2Jmc3DKyc6W6rsWaRqhDG9t3xJs2cSY2sRh9DV3XYovM520xpK8PTo4Ktu2qfdqk4J9FTB0U/OvJy8vDxcUFo9FIcbHpwTpmzBjCw8P/Zxp69+6NXC7tt8jLy0OhqG4QNWrUiCeeeILnn3+esWPHWuRx+fJlXF1d8ff3N4dt3ryZ6dOnm/8+cuQI7dq1uyldJSUlFuu2rken06HTSRf1lBsNKGU33y+j8nKnPMeyh62sMkzl5S7513rcXJSV56tQuLqZ11JdT0VBgfm8NSpysqnIz8O5jbRMFc4uaEKaVqZ1hSRrqUET2gzfCfeS+8cBs1N3PU5qyC6w7DIuLjWFOWnqz9FycYQXp1Y3COLTDHzyi44y2zNTANNaCGvTV0p1BsrKDbi62H9NuGodSEm3XARWUKg3n6/Cy0PJQ/cF8dk3iWTlWF9sf32+N6srOc1yBLIqz+vTe3soeWhKMJ9+k1C7LhflzelysV5e+VW6tNUdRNfiirn2ZTwxlQ3GDq1dGT/Kn85t3Zi77AqlOmkLzNVFYS7369GVmbRpXaw7aNenT0233Gigusws0//0aXtUKtOzISGllPnLIsnIkubRYOtS62B1SlmVLu3frMuCoqq6tEy/bV2n6vJKLuWpVy6TmVOjHp0V5jyuR1dmpLyO9ZiSYaUeK+/V1fnvNf0agn09/drVf499uTqYf9fWdLm52tflpnUgOdVSV36BbfuqYvTtARQUlnPgcAbQyu51/klkin9/B/HNIhwtwb8erVbL6dOnqaio4MCBA7z11lt8/PHH/1MNmzZtolUr6cPseierioULF/LJJ5+wbt067rnHcm1TzVGrYcOGcfbsWZKSkhgwYAD6mnNM/oau++67z26a1157jaVLl0rCJss8uU/hfUPXtomduSrGmudsxbUabmcOjJ18Mn/egv+UGfjdN52sX39C7uRM4MNzkWvUdtOq/Pxp+vIblGWkk/DeG3aubfvUTc8PvI7iUlj1YykOChm+7jL6d3DgodFqPtmmo6ByEzi5zDwTEqieVmhfYu0i7U0/uv7cvFlNuBZfwq97pT3Ssr+j6ybLTqLrgRCuxRXz6x7pFB2buuzd7w1e2/Jc9ckffpVOOTp1Pp+rsUUsXRDGyIFebL1uZ7y6lFldxN1omT/5yhUcHGQE+Kq5a5gP77wUzjPLo8w7Dzb0urzZi9u/L8uzTyy9hNJBToCvmrtH+PLW82G88G4M8ck6iS67sm62vOoQRy6Xamgo9vXms815ZvmlBmlfiuvsS2+uR3vvuzpc+0aEVhLa2Ik24a5s/iWJsvJ6fMkI/hbC0RI0WFxdXcnLsxzRyM3NxdW1em6yXC6neXPTgvrw8HBSU1OZOHEiBw8e/J9pDQ4ONmuwh7u7O4sWLWLp0qWMHj1acq5Fixbk5eWRmppqHtVycXGhefPmODj8vZ+qNV2OjvanUSxatIj58+dLwvZ6dvlb169JWVYuSk93i3CVh2nEqTw7zxwPsBHX3RyvCn1+Hgqt5Xx1B61pzYC+IN+mptSvNiB3dMRv8jQCpj8AQN7Rw2Tv3I7XyDsoz7Tc4Uvp60ezt1Zi1Ou5tnAe+gLLhcgAxTrro1ZVYcW6+nsJGoyQlGkEjMSlweVEPQsnaxjQUcm2I+V4uMh49l4NzO5qTrNgWRT5hRU0a2K5NkKjlqNSyq32YF9PfkGF1R7jqt7tql7hvt096NbBlXlLonB2knZC3DnUlzuHVq9xm78skvyCWnRZ6fGvmy5TWFX6fj086NbBjSeWRFrR5cedQ/3Mf89bcpH8wnKah9grr1p0FVZY7Ymu0lpb+kPHcyjV6XlociAPTa6e1vr0a1fJL9TTrLFlB49aVVVmtdRlod7qqEJ1mVmmvxpnavBeulZMdHwxny5vxZo3q0eIG2pdLnglivyCCppamep5Q3VpTZdzVV1aKa9YU3lFXi3iWlwxa95sw4fLqqdCL3wjmvwivVVdapUMZR3r0dr00qqw2srb20PJhrekM0KEfd2YfT2+6Cz5+RW0CLVc31Wlq2pkyhZ5BTaeFZVhttKPuj0AoEFMG5SLES3haAkaLuHh4Wzfvt0i/MSJE7Rs2dJmuieffJJ3332XLVu2MG7cuH9S4t/i8ccfZ9WqVaxcuVISPn78eJ599lneeOMN3nvvvVukDtRqNWq1dA5/fUwbBCj46zKubcMswrWVYQUXrlT+e7kyvCUZOw5axK06X0VJbDQeA4aAXCFZp6UJbVZ5Psa2KIOe5E/eJ/Xztaj8A6jIz6MiO4umy99Bl5Js4Wgpff1o/vYqZMi48vTjVh2xKlKzDXRspkAuQ7JOy9/TVJ5pOf9cb2NeEeQXGfFxM73o8ouNrPqxlEunos1xEpJLaR3vzKDeXni4OUjWXlStS4hNsPwm0vXEJJQwsLcncrl0442q9Ob1LsGOODjIef8V29NYPv4yjojIQhKSS4gJK2ZQHy883JSStRc187VFdEIxg3p7WehqWiN9SLATDg5yPniljbVsAPjwizgiLhaYdMWXMLiPt6WuxqaGXtXaNlvExJcwqI+lrqq1XbXdF5h6wk+ez2fDD9UNqcRUHbEJTgzs6WGlLk1remKtfN/qemITSxjQw8NCW0iQKb2172NdT1JqGZejC9G6OLBshWkqbUOry0++TuBcZCEJKaVm27Vl+zG13G9MQgkDe9m2/drKOylVx5UY026Cr32UAFTWY2IpA3q44+HqIFmnZa6HJMvpZNcTm1RK/x5udurR/vcecvLLeWLZVckMioZiX1dii3FxkjdY+3p/3VXOnM8jPqmEtnFFDOnvi6e7UrJOq1mIaW1VTHyRfV2xhQzp54tCjmSdVtXarOg4y/QODjKGDfTl0pUCrsbYz1/wv0FshiFosMyZM4dr167x6KOPEhERweXLl/nggw9Yu3YtTz/9tM10rq6uPPDAAyxevFgybJ+Xl8fZs2clR3x87d+xAEhKSrJIm51dvUNRVlYWqampkqPUyg51ABqNhqVLl7Jq1SpJeOPGjXnnnXdYuXIl06dPZ9++fcTGxnL69GlzXGvTEf9NpP60G5dWzXDv3t4cJlMoCLx3DDnHzqJLMW0zrEtOJ+d4BIH33SGZ7+PeowMu4U1J3fq7JN+8Pw+icHLCva/0o42etw+nLDOD4ksXa9VmKC2hNDaaiuwsHJuHoe3UmYwt30viKH18TU6WXMHVZ56gPN3+xzAvxOpRq2S0DZXWW5cWCvKKjMSn17Il4E3g5SrDzVlGZr7pN6A3mEa8LkcXm4+SUgOHT+ViMBgZ2k86NXRofy9KdXpORNjfteqPEzk4OSro191Dmr6fN5nZZVy6anrZ7zyQyYJlURZHVR7zl0Wy82AWl6OLKCk18OdJk65h/aW6hvX3Mek6m2tX159VunpId/Ya2r9SV+WW6TsPZDB/WaTFAfDH8WzmLbnIzgOZ1bpO5Jh0DZDqGj7Am1KdnuO16Dp0PBsnRwX9a+ga1t+HjOwyq1u5X0//np44ahSciMjnSmyJ+SgpNXDkTD4Gg5Hb+9S459s8KdUZOHne+shrFX+eysPJUUHfru6S8Ntv8yQzp4xL14rtpndylOPvqyE2oYTL0UUNri4XvBLFroNZXI6pYft9vaT59vMylVeE7ZFwgD9P5prKq4bt397PS2L7tnBylOPnoyYuSSepx6OV9Ti4j7s03z4eJl1/2beRI6fzcNIouK2LdG3qkD4eZOaUExVtvx71eiS21aDsy1vVYO3r8UVn2b4njairhZSU6PnjWCYGg5ERg/0l+Y4Y7E+pTs/RU/Y/hnzwaBZOTg707y39aPmIwf5kZOm4eNnSPm/r7oWHm4pffr/1o1kAMrnsHzv+LYgRLUGDJSQkhEOHDvH8888zdOhQSktLCQsLY8OGDUyYMMFu2ieeeIJVq1bx/fffm9dC7d+/n06dOkniTZ8+nQ0bNtSq5e233+btt9+WhK1fv978oeEhQ4ZYpPn222+ZNGmS1fymT5/OO++8w8WLUgfg8ccfp1WrVrz77ruMHz+e/Px8vLy86NWrFzt27LihjTD+SXyG9UPh7IiD1tSz5tKqOf53DQMgffsBDCWltP/0VQKnjmV/y9spiTdtVJG4/gdCHr6Xzt+u5NLz76BLzyLk4XtxbhnKsWEzJde4tOhteuxYR5eNK4n9+BvUvl6Ev7qA/L+iSNywWRK34MQx8k8dJ+jxBcidnClLTsR94BBcu/Uk7vVl5m7K4PkL8bx9OBenTzI7SS7tO+LYshWl0ddABk4tW+M78V7yTxwn8+cfzddwcHen+VurUHp6kfDuGzi4e+DgXt3AKs/MsBjdikowcDlRz7jblGhUkJlnpGNzBS0bK/h2b5l5jv74fko6hyl4c6OO3MLqzoF2oSYn09PV9G+Qj9w85/58jOme/D1l3NFLyfloPdkFRoxG04jZbe0UFOvg4Dn701PiEkvZsT+T6eNN31yJii6iSzs3Rg3yYf13SZLpPFPuCmDqXY14+tUozkWaGh8nIvI5eS6PubOa4OSkIClVx6DennTv6Mby96PNI3lpmWWkZVouhAfIzC4n4qK0kRaXWML2fRlMHx+I3mAk6prpI6SjBvuw/rtEia6pdzVi6t2BPPXKJc5FmvI5fjaPk+fyeGJWCE6OCpJTSxnYx4vuHd1Zvvpata6MMtKsbBwAkJljqSs2sYTf9mUwc0KQqbyuFtG1gxujB/uybpNU17S7A5k2PpAFyyKJuE7XiYg85s0ONZfX4D5e9Ojkzqurrpp1+XmreGFuc/YeziIptRSjsXozjJj4YrYfsGykxSWVsvNgNlPH+WMwGomKLqZLWy0jBnjx+eYUibb77vTjvjv9WfjGVc5HmRyCk+cKOPVXPo9PD8LJUU5yWhkDernTrb0rr38cZ9bm5Cjn9Wease9ILklpOnRlBoL81Ywd6oPSQcYXm6Ub0zSUuqyy2evLa8eBTKbd3Qi9AS5HF9GlnSsjB3qz4ftkqe2PC2DKuACeWX6Zc5eqbf/U+Xzmzmxs0pVWysBennTv4MZrH8RIyuuNRWHsPZxNUmopZWVGggLUjBvmi9JBZv6OVRXxyTp2Hcphylg/DAa4HFNC57YuDO/vyRdb0iTf0Jp8hy/3jvFl0Vsx/HW5sh7PF3L6rwIendoIR0c5Kell9O/hTtd2Wt78NEEyuu6qVdAuzPQcrxpZ6tpOS15BBTl5ZWbbaDD2pWy49nWmxlbqMfHF/PJ7KvffG4LBYCTySgHdO3kwZlgAn30VK5maOmNSE2ZMasK8FyLMW7IfPZXN8TPZPDWnBc5OChJTSrm9nw89u3iy9O1Iq5/uGD00gFKdXvIx41uJTCHGc4SjJWjQdOnShR07dtg8P2PGDGbMmGER3rhxY8qv27J7w4YNdXKorBEbG2v3vL3FrmBdo0Kh4MKFC1bjDxkyxKrjZo0lS5awZMkSi/CQkBCbuvbv31+nvO3R9v3FOIUEmf9uNGEEjSaMAGBv80GUxCWBQo7cwcG0SrgSQ1k5R4fNoNXrT9NmxQsonBzJj4jk+OjZZB86IblG9sHjnLjjQcKWzKXb1o/RF5eQ/tt+Ihe+iaHMcren2KUvEDBzNgHTZqHQatElxEs+YAwgkyuQKRwkm44YKipwv60/mnunIVMq0SUlkvr5WjK2/iCZR6JpHIK6kWlNTJNnX7K4fuqX60j9cr1F+Je7yhjWTcntXZU4qSE91yj5gDFULaSWUbOPbsrt0imcvds40LuN6bG98FPTdJbCEiP5xUb6tnfA1UmGXA55RUYi4w3sO1NBXlHt0xNXrosnM7ucscN88XBXkpZRxodfJLB1p/RlLZfJUChk1FS65N1r3D8xkOnjG6F1cSAhuZRXVl1j/xHb35ipCyvXxZGZU864YX6VunR88Hk8W3dKRxJl8kpdNQpw8TtXmDUpiBkTAqt1rbzKviP2e5JrY8WaWDKzyxg33B9PdyWpGTre3xDHlh01dYFCIaNmxb709mUemBzMzHuCTLqSSli24or5Y6kARSV6svPKmTDaHw83JXK5jLQMHT9uT+XrH5Mpt/H6Xv1FApk55YwZ4oOHmwNpmWV89HUSP++uuQFJVZlJxS1bFcuM8QFMvSsArbOCxBQdyz+M5cCxXHOc8nIj0fGljBjghY+nEpVSTk5eORGXClnyTqLVqW0NtS5Xra+yfR883BqZbP/LBH7aZWWzAyt1ueS9a9x/TyOm390IrYuChORSXl0dzf6j1bZvKq9iRg3yxsdThUopJzuvnHORBSxdGU1KpmWL+YOvksjKLWfMYNO03rSscj75NoVte6TfX5NX2ljN8nrlg3im3+XH1LF+aJ0VJKTqeP3jeA4elzoDTRppeP7RJpKwx6aZnnMRkYU88/pVyblbbV8vr04j2sqUuIZqX+98dIXMLB13jw7E00NFalopKz+7yuZfpM6i6dMclu+A55df4MGpocy6LwRXrZL4xGIWv3mRPYcsp6z7eqvp1tGDXfvTKCq+sY2zBP8cMmNtrUSBQPCf51el7TVxt5LAgZYfCW4ofDt+162WYJVT+6w7+Lcao/Gfm0Z5MxhqfgStgaBy/HvfQvqnqdBZ7/FvCMgb6NRrpVp1qyVY5UZ3uf1f0VBtTFdU+/rKW8Ef2/rXHukf4miP7v9Y3j2PHf/H8q5PxJie4D/N119/jYuLi9WjTRvbC14FAoFAIBAIBAJ7iKmDgv80Y8aMoUePHlbPKZVKq+ECgUAgEAgEAvv8mzat+KcQjpbgP41Wq0Vb+a0lgUAgEAgEAoGgvhCOlkAgEAgEAoFAIKhXxAeLxRotgUAgEAgEAoFAIKh3xIiWQCAQCAQCgUAgqFdkYkRLOFoCgUAgEAgEAoGgfpHJxcQ5UQICgUAgEAgEAoFAUM+IES2BQCAQCAQCgUBQr4jt3cWIlkAgEAgEAoFAIBDUO2JESyAQCAQCgUAgENQrYnt34WgJBII6EDjQ91ZLsErSvvRbLcEmQU9obrUEq5y61QIEgluEWJgv+CdxUKtutQRBA0Q4WgKBQCAQCAQCgaBeEWu0xBotgUAgEAgEAoFAIKh3xIiWQCAQCAQCgUAgqFfEdF3haAkEAoFAIBAIBIJ6RkwdFFMHBQKBQCAQCAQCgaDeESNaAoFAIBAIBAKBoF4R27uLES2BQCAQCAQCgUAgqHfEiJZAIBAIBAKBQCCoV8QaLTGiJRAIBAKBQCAQCAT1jhjREggEAoFAIBAIBPWK2N5dOFoCgeAGkWscCZjxAO79B6HQatElxJO26Wty9++pNa22S3f8pszAqXkYxopyCs9HkLL2Y0rjYqvzd3LC58670Xbuhjq4MXJHR8pSU8jZs4uMLT9gLC+zmrfCxZkWz8/BtUM4rh1bo/bx5PKy1Vx5+f063ZfKx5Pw15/Gb+RAFE4a8s9dIuqlFWTtO2oR12tQL1oufQLX9uHoi0tJ+20fl559i7KMbIu4Zboijv22kisR29EV5+Hh25TOg2cT1mmUXT3Xzu3iasQO0uP/ojAvDSetFwGhnek+7DHcfUIkcWMu7ONqxA4yEi+Smx6DwVDBY+9eqtN9AygUMu4d68+w/t54uitJTdfx8+8ZbN2ZXqf0GrWcmRMD6d/TA1dnB+KTS9n4cwr7j+TYTffuSy1p30rL1p3prF4fa0NXAMMH+Jh1/bQrna070+qs6/6JQfTv6YmriwPxySVs/CmFfUcs6+l63lscTvtWrmzdmcbKtdZ13TeuESMG+ODpYdK1dWcaW3bUXdesSUEM6OVl1vXN1mT2HZbqWjinKcMH+Fikj08qYfZzUVbzVihg0h1+DL3NC093B9Iyyvh5TyY/786ss7YZdwfQr7s7WmcFCSk6Nv2axoFjueY4chmMHepDl7ZamgRp0Do7kJ5VxpHTeXz9YyJFxXorum59XX74VbIVXTB5jD9D+3ri6a40ldfuDH76/QbKa3wA/Xt4VJZXKZt+SWP/0VxJvLFDfRjYy4NGfmocNXJy8yq4eLWIr7emkpReYVXXxFG+3H6bB55uDqRmlvHL3my27cmqs65pd/nRt5ubuR6//y2Dg8fzJPFat3Di9j4eNG3sSEigGqVSzoynL5GeVW4131ttX5t+TSdPZ03XrbevFZ9FW9U15a5ARgz0wdNDRWq6ji07UtmyPbVOuhw1cmZNasyA3pXPiqQSvtmaxN4/pXbw7KPNGD7Q1yJ9fFJJna4j+OcQjpZAILghQha/glNYK1LWfYwuMQGPgbcT8twSYmUycvfttpnOtddthC5+lbwjfxCz7AUUzs74T51J83c+4PLjsylLMTWCVL5++Iy7h+w9O0nfvAlDaQnObdvjP/V+tJ27ce3ZJ63mr/Jyp/ED95B/7hJpP++m8ax76nxPcpWSHrs2oHRz5cL8VylLz6LJI/fR/dc1HBs2k+xDJ8xxPft2o/svn5H+2wFO3jUHla8X4cufoseuDfzZ424MZdIGyvb1j5Oe8Be9Rs3H3SeEy6d/ZdeXCzAaDLTscodNTaf3rsFJ602X2x/CzTOYwtxUTu75hE3v3sX4Jzbh5d/CHDf6/G5S487iE9gahYOKjMQLdb53gCfub8yQ27zY8H0SUdeK6drBlTnTgnHUyPn2p9obBEvmN6NlU2fWbEwkMUXH4D6evDC3GXJZNHsPW2+o3DnUh0b+6lp0NeH2vt6s/y6RqOgiurZ349HpjXFylPPN1pRadS1d0MKk69sEElNKGdTHixeeaI5Mfs2ioWLWNcyXRn4au/nOeyCEoX29WbcpkUvXCunWwZ3HZjTByVHB11ssG/M1WfZUGOHNnPnsmwQSUkoZfJsXL81rgVx2lT01dJXq9MxfJnWay8oMNvN+fFowg3t78PmPKVyOKaFLOy2P3BeIk0bOxl9qd5xfmhtCWKgT675LISlVx8BeHjw3JwS5LJZ9lc6DSiVnyjh/9h/NYfuBLPIL9TRv4si9Y/zo0UHLI89doKzcKMm3odbl49ODGdLHk883pxAVXUzX9loemRKEo0bBxm21N9IXPxFKWFMn1m1KJrGqvB4NRSaLZd91HQ1aFwUnzuUTHV9CQZGeAB8VE+/wY9WSMOYuu0pSqrQD6dEpgQzq7c6XW9JM9djWhYcmB+CokfPdrxm16nrh0ca0CHViww+pJKXpGNDDnWcfboxcFs/+Y9XOVsdWLnRs7cK1+BKKS/R0aOViv7xusX317OTKw8/+9a+xrydnhzK0nw9rNyYQVfmseHxmiOlZ8WNSrbqWPd2S8GYufPp1HAnJpQzp681LT4Yhk11hzx9S57ZUp2f+kouSMF2ZgbXvdKj1Ov8UYo1WA1ijNWPGDGQyGa+//rokfOvWrchkpgrasGED7u7uVtO7u7uzYcMG898ymQyZTMbRo9JeaJ1Oh5eXFzKZjP3791vEl8lkODg40LhxY+bPn49OV91lsmHDBkm8qkOjqf6BVd3H9fk88sgj5OTY79G9njNnzjB69Gh8fX3RaDSEhIQwceJEMjNNP6bY2FjJ9T08POjXrx8HDhywquP6Y/jw4RbXmjBhAn5+fmg0GsLCwpg9ezaXL1+WXOvs2bMWOocOHYpCobAo46rrjx07ts73bK0M/q6uAQMGMG/ePIvwb775BoVCwcMPP2xxbv/+/ZJy8vLyYtCgQfz5559W9T344IMoFAo2btxo9fzVq1eZOXMmQUFBqNVqQkNDmTx5MidPnrRpR9cf+/fvr1d7q82mbhRtt564dulO4up3yPr1ZwojzpCw4k3yTx2n0ew5YGeaQKMHHqY0JprYpc9TcOIoufv3cG3RAuQaDf7TZ5njlaWmcHHaBJI/eZ/8o39SePY0aV9tIOXzNWg7d8W5TTur+ZfEJbHLpxtHB0/l0vPv3tB9Bd8/Ade2LTl97zySv91G5p7DnJ44l6LLsYS//rQkbqs3nqHociynJ84lc89hkr/dxpl75+HatiVBM8dL4sZePEDC5cP0v/sl2vaeRFCLngya+DLBYb05vO0tDAbLnv8qRs36iFGzPqR197sJbN6dll3HcOfD69BXlBNx4HNJ3EH3vMzURTsZPu09/Jvc2Eu1SZCG4QO8+fLHZL77JY2IyALWbkxi+75M7hsXgNZZYTd9945udG3vxqr18fy6J5OIiwW8+1kcJ8/l8eB9QVh7z/p5q5g1KYjV6+Lt6HJkxEAfvticxHe/pBJxsYC1GxP5bV8G941rVGddK9fF8sueDM5eLODdz2I5eS6Ph+4Ltq7LR8UDk4JZtT7OZr4hQY6MHOjD5z8ksWlbChEXC1jzbQK/7c1gyl216+rRyY1uHdxYsTaWbbvTOXshn3c+ieFERB4PTW1soctohMgrhZLjWlyx9TIL1DCsnydf/ZTKD9szOHepkPXfp7DjYBaTx/jXqq1bey1d2rry/heJ/LY/i4hLhaxYn8Cpv/J5YFIjs7ayMgPTF1xk1YZE/jiZx7lLhfy4M4MV6xMICXaiXw9Pqa4GWpdNAjUM7+/FV1tT+f63dM5dKmTddynsOJDFvXfWobw6uNKlnSurNyTy674sIiILWbEugVPn85l9XXkBfPljKl9tSeXwqTzOXypk16FslqyIxlGjYGBPd0m+jRupGdrXg29+SmfzjkzORxWxYXMaOw/lMGm0Ly616OraTkvntlo+/CqJ7QeyOXepiFWfJ3H6rwLuvydAouvbbenMfCaKV96P58S5Arv5NgT7ahLo+K+xr5AgR0YO8mXD9wls+jmZsxfy+eybeH7dk87UuwPRutgf6+jRyZ1uHdx577Notv1uela8/XE0JyJyeXhqE4vXrdEAF68USg5bz4r/FTK57B87/i3cckcLQKPR8MYbb9yQU2KP4OBg1q9fLwnbsmULLi7We2rWr19PSkoKMTExfPjhh3z55Ze88sorkjiurq6kpKRIjrg46Q9s+PDhpKSkEBsby5o1a9i2bRtz5sypk+b09HSGDBmCt7c3O3fuJDIyknXr1hEQEEBxsfSHsnv3blJSUjhw4ACurq6MHDmSmJgYCx3XH99++635/C+//ELPnj3R6XR8/fXXREZG8uWXX+Lm5saLL75oV2d8fDxHjhzhscceY+3atXW6t7pyM7rssW7dOp555hk2btxoUZZVREVFkZKSwv79+/Hx8WHUqFGkp0t754qLi9m0aRNPP/201Xs/efIkXbp04fLly3zyySdcvHiRLVu2EB4ezoIFC5g4caKkTnr16sXs2bMlYb179wbqx95uxKbqinuffuiLi8k9uF8Snr3zN1TePjiFt7aaTqF1RRPchPwTUue8PD2N0rgY3Hr3NTtphtJSDKWlFnkUR0UCoPSxnB5xs/jdOYTCS9HkHj1rDjPq9SR98zMe3TugbmS6prqRL+7d2pP09U8Y9dVOUs6RMxRGxeB/5xBJvtHnd6NUO9G8g7Sjo1X3uyjKTyctLsKmJietl0WYi5sfLm5+FORKe2hvZh58n64eyOUyduyXOt87DmSiUSvo1sHNbvrburlTXKLnwFHpyNXOA1l4e6oIb+5skebJ2U04dT6fP0/m2tHlblXXzv2Vujq616LLw6quHfszTLpaWL4P5s8O5dT5PP48Yftd1Kebqby275OOKmzfl4FGraB7bbq6e1Jcomf/EWkv+Y79Gfh4qmhlRVdd6d3ZDblcxq5D0nvedTAbjVpO13Zau+n7dDHV5cHjudL0h7Lx9lAR3swJAIMRCoosOwmiok3PFR8vlTTfBlqXvbuYymvnQWld7DyYZSqv9q52dfXp4lZZXtJr7DyYbdP2rycv3zRlUF+jKHt1dkUul/H7H9J8f/8jx6SrrX0b6d3ZleJSPYdOSKcJ/v5nDt4eSlo2dTKHGY01U9vLV9hXFXWxr9u6e5p0WTwr0uv0rOjbw/SsOFDjWbF9bzo+Xjf3rBD872gQUweHDBnC1atXee2113jzzTdvOr/p06ezatUqVqxYgaOjI2BqbE+fPp2XX37ZIr67uzv+/v6AyUkbM2YMp0+flsSRyWTmOLZQq9XmOEFBQUycOFEy2maPw4cPk5+fz5o1a3BwMFVLaGgogwYNsojr5eWFv78//v7+fPLJJwQFBbFr1y4eeughCx01KS4uZubMmYwcOZItW7aYw0NDQ+nRowe5ubl2da5fv57Ro0fzyCOP0L17d1asWIGzs/2XSV24WV22iI2N5fDhw2zevJl9+/bxww8/MG3aNIt4vr6+Zjt44YUX+O677zh27Bh33FE9tev777+ndevWLFq0iICAAGJjYwkJCQHAaDQyY8YMWrRowaFDh5Bf1/Dt2LEjTzzxBI6OjmZ7BFCpVDg5OVmtq/qwtxuxqbqiCQmlND4WaozElMZcA8AxJJTii39Z3o9SCYCx3HLev7GsDIXGEXVAILqkBJvX1nbsbLrWdeu56gttmxZk/3HKIrzgvGkdjLZ1C3TJ6WjbhAGQf95yfUzB+Sg8eneWhGWlXsbDtxlyhfRR69WoZeX5KwSEStPYIy8rgYKcZELbDa5zmtoICdaQk1dOTp50nUhMfEnleUdryarTBzkSn1SKocZstuh4U6MoNNiRi1eKzOEjBnoT3syZWU/bn94YGuxUqUtqM9fnW1v6+KQSK7pKqnVdLjSHjxzoQ3gzZ+5/6rz9fBs72tfV2BGsD4ibrxtnTVdc9X1duE6XSiVn86edcHNVkp1Tzh8nslm/KRGdldmDTYI05OZb1mV0gqnjIiTIEci1qa1JkIaEFMu6jKlM3yTIkYtXbXfSdGxtamjHJkrXhTTUugwJcrRaXjHm8rI/LSwkyJH4ZGvlVWJOf73tg2n9kUIhw99HxayJjcjJK7dwqJoEasjNryAnv6auEvN5kDpRNdMnJOvs1KOayGs33tkm7MtE3Z8VJl3ZuTV0xV33rKhFV1xiCXqbzwonLkRJnxU/ftbF9KzILeOP4zms22T7nfq/4N808vRP0SBGtBQKBcuXL2f16tUkJibedH5dunQhNDSUzZs3A5CQkMDBgweZOnVqrWkvX77Mvn376NGjx01piI6OZseOHSgrG5i14e/vT0VFBVu2bMF4A11MTk6mHqByKw1Ya+zcuZPMzEyeeeYZq+dtTdEEkzOxfv16pkyZQnh4OGFhYXz33Xd11vpP6bLHunXrGDVqFG5ubkyZMqXWUbji4mLzaGjNulu7di1TpkzBzc2NkSNHSkZNz549y4ULF1iwYIHEybpZ/XXFmr39XZuyh8LVDX2B5fSSisowhav10Y+KnGwq8vMspv0pnF3QhDStTGu791gT2gzfCfeS+8cBs1NXn6i83CnPsWy4lFWGqbzcJf9aj5uLsvJ8FaXFuWicLMukKqy0KLfOGg36CvZufB6l2omO/WbUOV1tuLo4UFBouRi/VGegrNyAay3TW1y1DhQUWaYvKNSbz1fh5aHkofuC+OybRLJy7D+zXLU3ryvfSvqqPK9P7+2h5KEpwXz6TULtulyUN6fLRnlXaXXVVv+Gr8UV8/GX8SxffY2Fr15ix/4Mhg/wYfXLbdCoLZ8zri4Kc7lfj67MpE3rYn8Kla301WVmO72Xh5L7JwRw6VohR0/nSvNtsHVp/X7rXpcKqyMv1nRV8fOaDvy6viNr32xNcCMNTy2/QmYNna7OCqu/KV2ZkfK61qM1XZVhrs5/r4+9IdhXVHTxv8e+atVlv31oK331s6Ja19W4Yj76Mo5XV1/lmVcj2bEvg+EDfXj/lTZ2ryH452kQjhbAuHHj6NixI4sXL66X/GbOnMm6desA0yjMyJEj8fGx3L0JYPLkybi4uKDRaGjZsiVt2rRh0aJFkjh5eXm4uLhIjqFDh0ri/PLLL7i4uODo6EizZs24ePEiCxcurJPenj178txzz3Hvvffi7e3NiBEjeOutt0hLs70Yt6ioiEWLFqFQKOjfv7+FjuuPqpG8K1euABAeHl4nXdeze/duiouLGTZsGECdHJe6cqO6evfubXGPhw4dksQxGAxs2LCBKVOmADBp0iSOHDnC1atXLfILCgoy5/Pee+/RpUsXBg+uHjW4cuUKR48eZeLEiYDp3tevX4+hsgvsZsrVGvVhb3/HpsC0njE/P19ylEm6+uw4bbYcOqORzJ+3oO3cFb/7puPg7o6qUSCNF76IXKO2m1bl50/Tl9+gLCOdhPfesKv9prDjjFo4qnbu0wKZ7R49mZ1zNa+/Z9PzJMecYsi9b6D1CKhTOmtS5PLqw5y/vWvbPVulr27n5s1qwrX4En7dK53i87d03WTfgUTXAyFciyvm1z3SKT42ddm73xu8tuW56pM//JrKD7+mcup8PqfO57NuUyKvf3CNJkGOjBzodcNlVhdxf6fMtc4KXpnfFJkMlq++Jim3m8m3rvxjdVmnyryx9POWXWbukihe/yiWkhIDby1qQUiQ+oZ01cnIbjL59WXVkOzr9Y9jG6x9KeTVR3Xam6tIu8/f60798EsKP/ySwqlzeZw6l8fajQm8tvoqTYKcbKf/HyCTy/+x499Cg5g6WMUbb7zBoEGDWLBgwU3nNWXKFJ599lmio6PZsGEDq1atshn3vffeY8iQIej1eq5evcr8+fOZOnWqZMMDrVZrMZ3w+mlgAAMHDuSjjz6iuLiYNWvWcPnyZR5//PE6a3711VeZP38+e/fu5ejRo3z88ccsX76cgwcP0q5d9UhA7969kcvlFBcXExAQwIYNGyTnq3Rcj6enafHozYxsrF27lokTJ5qnoU2ePJmnn36aqKgoWrZs+bfz/Tu6Nm3aRKtWrSRh9913n+TvXbt2UVRUxIgRIwDw9vZm6NChrFu3juXLl0viHjp0CGdnZ86cOcPChQvZsGGDZHRo7dq1DBs2DG9vbwBGjhzJrFmz2L17N0OHDjXrr2vDuTbqy97qalPX89prr7F06VJJ2ENNg3m4WRP0+XkotJYjTw5a05QOfUG+zXtK/WoDckdH/CZPI2D6AwDkHT1M9s7teI28g/JMy520lL5+NHtrJUa9nmsL51kdTasPyrJyUXq6W4SrPEwjT+XZeeZ4gI247uZ4VWic3K2OWpUWm+KprYx21cRoNLJ30wtcPrWNIZNfp2nbvzdtUOsIMwbJeGxkV3PYgmVR5BdW0KyJ5ctYo5ajUsqt9kBfT35BhdUe46re7aoe2b7dPejWwZV5S6JwdpL2XN851Jc7h1avvZu/LJL8glp0Wenxr5suU1hV+n49POjWwY0nlkRa0eXHnUP9zH/PW3KR/MJymofYK69adBVWSHqiq6jSWlv6Q8dzKNXpeWhyIA9NDjSHP/3aVfIL9TRrbDkqoFZVlVktdVmotzqqUF1mluldnBS89kwzvDyUvPlJHF+skG7G0lDr8qlXr5jKq4nl/dZZV6He6ihOTV3XczXONB3t0rVirsUV89nrrflwWZj5/MI3oskv0tPUyrQytUqGso71aG0DiKqw2u7L20PJhreknYYNxb7WvyldB9xQ7Wve4gvkF1TQPMRyaUWVLmujaJa6LEe9qrTWlv7Q8WxKSvQ4OtofaRT8szQoR6tfv34MGzaM5557jhkzZpjDXV1dKSwsRK/Xo1BUG4xer6ewsBA3N8vGipeXF6NHj2bWrFmUlpYyYsQICmw00vz9/WnevDkALVu2pKCggMmTJ/PKK6+Yw+Vyufn/tnB2djbHWbVqFQMHDmTp0qVW14XZwsvLiwkTJjBhwgRee+01OnXqxNtvv83nn1fvMrZp0yZat26Nu7s7Xl6WC+av11GTsDDTA/3SpUv06tWrzrqys7PZunUr5eXlEidOr9ezbt063njj5kYablRXcHCwxT3WdETWrVtHdna2eXolmEa5zpw5w8svvyyxpdDQUNzd3QkLC6O0tJRx48bx119/oVar0ev1fPHFF6SmppqdTDDd+9q1axk6dKhZf2RkJB07drzh+69JfdpbXWzqehYtWsT8+fMlYZfuMjmrJbHReAwYAnKFZJ2WJrRZ5fkYbGLQk/zJ+6R+vhaVfwAV+XlUZGfRdPk76FKSLRwtpa8fzd9ehQwZV55+3KojVl8U/HUZ17ZhFuHayrCCC1cq/71cGd6SjB0HLeJWna/CKyCMK2d+xaCvkKzTykoxxbt+i3ZrVDlZkSd+ZNDEV2jZdcwN3lk1RaWw6Q8jB7ZHmsMSkktpHe/MoN5eeLg5SNZeVK1riE2w/x2WmIQSBvb2RC5HssahKn3VupLQYEccHOS8/0ora9kA8PGXcUREFpKQXEJMWDGD+njh4aaUrL2oma8tohOKGdTby0JX0xrpQ4KdcHCQ84GdKTYffhFHxMUCk674Egb38bbU1dj0nKla22aLmPgSBvWx1FW1XqO2+wJTD/vJ8/ls+KF6U5TEVB2xCU4M7OlhpS5Na41qrm2pSWxiCQN6eFhoq1qrFFcjvYuTgtcXNsPfW8XCN64Rl1TKI89J1941tLr89JtEIi4VkpiiM9luL8vyqrrf2ETLTXmuJzaxhAE9Lcururztp09KLeNKbBFaZwde+8i0liYxVUdsYikDerjj4eogWadlroekWnQlldK/h5uderTyIarryMkv54llV9Fft0tHQ7GvxxZHoS+vvnZDs68PP48l4mI+8UkltGmpZfBtpm8TXr9Oq2kdnxXR8cUMvs0bhRzJOq2mlU5lTEId1tnd4iVScoVYo9Xgxt5ef/11tm3bxuHDh81h4eHh6PV6zpw5I4l7+vRp9Hq9zdGU+++/n/379zNt2jRJo7o2quKWlNzch94WL17M22+/TXJy7d9VsYZKpaJZs2YUFUkX0wYHB9OsWTOrTlZtDB06FG9vb5ubjtjadOLrr78mKCiIiIgIzp49az5WrFjB559/TkWF/Z6Vf0qXLbKysvjpp5/YuHGjRO/Zs2cpLCxk+/btNtNOnToVg8HAhx9+CMBvv/1GQUEBZ86ckeTz/fffs3XrVrKysujYsSOtW7fmnXfeMU8nvBn9f4e62Jstm7oetVqNq6ur5FBVDtPn/XkQhZMT7n37S9J43j6csswMii9dtJalBENpCaWx0VRkZ+HYPAxtp85kbPleEkfp42tysuQKrj7zBOXpdfvo5N8l9afduLRqhnv39uYwmUJB4L1jyDl2Fl2KaQdKXXI6OccjCLzvDsm8FfceHXAJb0rq1t8l+TZrdzvlumKundslCb90YivOrr742dmK3Wg0su+7F4k88SMDxy+ldfe7b+oeDUZIz4PL0cXmo6TUwOFTuRgMRob285bEH9rfi1KdnhMRthfdA/xxIgcnRwX9untI0/fzJjO7jEtXTba280AmC5ZFWRxVecxfFsnOg1lcji6ipNTAnydNuob1l+oa1t/HpOtsrl1df1bpqrEV9ND+lbquFFbqymD+skiLA+CP49nMW3KRnQcyq3WdyDHpGiDVNXyAN6U6Pcdr0XXoeDZOjgr619A1rL8PGdllRF4ptJHSRP+enjhqFJyIyOdKbIn5KCk1cORMPgaDkdv71Ljn2zwp1Rk4ed7+iPCfp/JwclTQt6u7JPz22zzJzCnj0nUbKJgbwT4qFr11jWvxJVTojVyOLpIcDakun3r1CrsOZXMlprK8TueZyuu2Gvn29TKV1znbI/QAf56sLK9uNcvLS2L7tnBylOPnrSYuSSepx6OV9Ti4T418+3iYdP1l30aOnM7DSaPgti7STughfTzIzCk3795nC70eiW01JPu6ElvSYO1r3uIL7NyfQdS1Sl3HsyufFdJlK8MH+tzQs6JfT2lbb9gAHzKy6vKs8MJRI0azbjUNakQLoF27dtx3332sXr3aHNa6dWtGjBjB/fffz7vvvkuzZs24du0a8+fPZ8SIEbRubX1L6eHDh5ORkYGrnUX2YGoEp6amYjAYuHLlCsuWLSMsLEwyNc1oNJKaavnhTl9fX6ubH4Dpu05t2rRh+fLlvP/++3Y1/PLLL2zcuJFJkyYRFhaG0Whk27Zt/PbbbxZb1deGTqez0Org4IC3tzfOzs6sWbOGCRMmMGbMGObOnUvz5s3JzMzku+++Iz4+3uo3otauXcv48eNp27atJLxJkyYsXLiQX3/9lTvvvBMwrS+q+Z0rT09PGjdubFPz39Vliy+//NI8klOzfkaPHs3atWsZPXq01bRyuZx58+bxyiuv8NBDD7F27VpGjRpFhw7SRnGbNm2YN28eX331FU888QTr169nyJAh9OvXj+eee47w8HAKCwvZtm0bu3btknzvrDbqw97q06aqKDhxjPxTxwl6fAFyJ2fKkhNxHzgE1249iXt9mbk7MHj+QjxvH87F6ZPMTpJL+444tmxFafQ1kIFTy9b4TryX/BPHyfz5R/M1HNzdaf7WKpSeXiS8+wYO7h44uFc34sszM2yObvkM64fC2REHrWm6hkur5vjfZVpTmL79AIaSUtp/+iqBU8eyv+XtlMSbnNLE9T8Q8vC9dP52JZeefwddehYhD9+Lc8tQjg2bKbnGpUVv02PHOrpsXEnsx9+g9vUi/NUF5P8VReKGzZK4TVr1IzisN/t/WEpZaSFu3o25fOZX4i8d4vb73kIuN70E92x8nksntzL1uV24epqmgx3c8goXj/1Aq+534xUQRmrsWXO+CgcVPkHVz7387CTSE0w7YOVlmXrGr0bsAEDrGYhfsPVpogBxiaXs2J/J9PGNMBiMREUX0aWdG6MG+bD+uyTJdJ4pdwUw9a5GPP1qFOciTS/5ExH5nDyXx9xZTXByUpCUqmNQb0+6d3Rj+fvRGCpnBadllpGWWWZNApnZ5URclDbS4hJL2L4vg+njA9EbjERdM32EdNRgH9Z/lyjRNfWuRky9O5CnXrnEuUhTPsfP5nHyXB5PzDJ9HDQ5tZSBfbzo3tGd5auvVevKKCMtw4auHEtdsYkl/LYvg5kTgkzldbWIrh3cGD3Yl3WbpLqm3R3ItPGBLFgWScR1uk5E5DFvdqi5vAb38aJHJ3deXXXVrMvPW8ULc5uz93AWSamlGI3QobUr40f5ExNfzPYDlh+CjksqZefBbKaO88dgNBIVXUyXtlpGDPDi880pEm333enHfXf6s/CNq5yPMjkEJ88VcOqvfB6fHoSTo5zktDIG9HKnW3tXXv84zqxNpZSx/OmmNGvsyMffJKFQyMxbc+vLlOQWVJCSVj1q0lDq8twlacM0LqmUHQeymHZXAAYj5vIaOdCLDT/UKK+x/kwZ688zr1/lfGU+J86Z1s49PiPYpCvN9AHebh1cef2jWLMuJ0c5ry9szr4jOSSl6igrNxDor2bcUF9UShnf/Cz9lEh8so5dh3KYMtYPgwEux5TQua0Lw/t78sWWNAqv0zX5Dl/uHePLordi+OtyZT2eL+T0XwU8OrURjo5yUtLL6N/Dna7ttLz5aYJZF4CrVkG7MNPzsmpkqWs7LXkFFeTklZlto6HYF0BWlqxB2tfZC1LHPDaxhN/2pjPznmAMBiOXqp4VQ/xYuzFBMk142vggpk8IYv7Si0RcNOVz/EwuJyJyeXJ2U9OzIqWUwbd506OTB6+svGIeffPzVvHCvBbs/dP0rMD8rAggJr7YPNp+KxC7DjZARwvg5ZdfttjNbuPGjSxZsoRHHnmExMREgoKCGD16NEuWLLGZj0wmM6+pscfMmTPN8f39/enXrx/Lly+XTBPLz88nIMByAXpKSordbbjnz5/PzJkzWbhwIcHBwTbjtW7dGicnJxYsWEBCQgJqtZoWLVqwZs2aOu2WeD07duyw0NqyZUsuXboEwJ133snhw4d57bXXuPfee8nPzyc4OJhBgwZZfD8M4NSpU0RERPDZZ59ZnNNqtQwdOpS1a9eaHa39+/fTqVMnSbzp06fXutX9jeqyx7p16xg3bpxVp+Tuu+9m4sSJdjeFuP/++1m8eDGrV6/m119/5ZtvvrGII5PJuOuuu1i7di1PPPEE3bt35+TJk7z66qvMnj2bzMxMAgIC6N27NytWrLgh/fVhb/VpU9cTu/QFAmbOJmDaLBRaLbqEeGKXLyF3/x5zHJlcgUzhIFmzZqiowP22/mjunYZMqUSXlEjq52vJ2PqDZL6GpnEI6kYmZ6PJsy9ZXD/1y3WkfmndUWz7/mKcQoLMfzeaMIJGE0zTHvc2H0RJXBIo5MgdHCSbVBjKyjk6bAatXn+aNiteQOHkSH5EJMdHzyb70AnJNbIPHufEHQ8StmQu3bZ+jL64hPTf9hO58E0MZZa7UI2YuZqjv63g2I7VlBbn4uHblKFT3yGs0yhzHKNRj9Gg5/rVzbEX9gEQeXwzkcelDpzWoxHTX9xr/jvp6jH2bHxOEmfH5/MACO82Fr/J0g/C12Tlungys8sZO8wXD3claRllfPhFAlt3ShuAcpkMhUKGrMZ8lCXvXuP+iYFMH98IrYsDCcmlvLLqGvuP3Ny3EVeuiyMzp5xxw/wqden44PN4tu6U/nZl8kpdNd7pi9+5wqxJQcyYEFita+VV9h2xdFJuhBVrYsnMLmPccH883ZWkZuh4f0McW3bU1GXayrvm9J2X3r7MA5ODmXlPkElXUgnLVlxh3+FqXUUlerLzypkw2h8PNyVyuYy0DB0/bk/l6x+TKbfx+l79RQKZOeWMGeKDh5sDaZllfPR1Ej/vrrkBSVWZScUtWxXLjPEBTL3L9LHqxBQdyz+M5cCxXHMcDzclLZuaGudzpgRRk50HMnjzI+k04oZal6s/N+0ed+ft15XXV4n89Lu0vKq2Za/ZbFy6MoaZEwKYdrepvBJSdCz/IIb9R3PNccrLjUTHlzByoBc+nipUSjk5eeVERBaybFUayRmWM0I++CqJrNxyxgw2TetNyyrnk29T2LZH+k0leaWN1SyvVz6IZ/pdfkwd62fSlarj9Y/jOXhcOkLdpJGG5x9tIgl7bJrp+RsRWcgzr0s3jxL2dWO891mM6VkxIsD0rEjXsXp9LFu2SztSbdXjS29FMWtyY+6fGIzWxYH4pBKWvXeZvX9W20FRiZ6cvHLuGR2Ah3v1s2Lz9hS+/jGJX7/oflP3cDP8mzat+KeQGetr32eBQPD/lrND+95qCVZJ2pdee6RbRPTWS7daglV++srye2ENAaPRyoehGgAGQ8N8Raoc1bdaglUqdNZ7/BsCijp+buV/jYOyQfZ5S9ZoNSQaqo3pKxpmee3/oe7r8eubmPv//rri2ghd9/M/lnd90jB/3QKBQCAQCAQCgeBfi5g62AA3w/j/ytdff23xXaSqo02b//8flPuv379AIBAIBAKB4L+FGNH6HzFmzBh69Ohh9ZyygU5nqE/+6/cvEAgEAoFA8F9CjGgJR+t/hlarRVv5Udf/Iv/1+xcIBAKBQCAQ/LcQjpZAIBAIBAKBQCCoV8Sug2KNlkAgEAgEAoFAIBDUO2JESyAQCAQCgUAgENQrYo2WcLQEAoFAIBAIBAJBPSOmDoqpgwKBQCAQCAQCgUBQ74gRLYFAIBAIBAKBQFC/yMTUQTGiJRAIBAKBQCAQCAT1jBjREggEAoFAIBAIBPWK2AxDOFoCgaAOfDt+162WYJWgJzS3WoJNmo4Nv9USrNLs5SO3WoJVUuMybrUEq8ga6NQXV6+G+QF4taPqVkuwiUqluNUSrCJ3aJiTi3IyCm+1BKs4OqtvtQSrXD179VZLEDRAhKMlEAgEAoFAIBAI6hWx66BYoyUQCAQCgUAgEAgE9Y4Y0RIIBAKBQCAQCAT1ilijJUa0BAKBQCAQCAQCgaDeESNaAoFAIBAIBAKBoF4Ra7SEoyUQCAQCgUAgEAjqGTF1UEwdFAgEAoFAIBAIBIJ6R4xoCQQCgUAgEAgEgnpFjGiJES2BQCAQCAQCgUAgqHfEiJZAIBAIBAKBQCCoX8RmGMLREggEN4bKAYZ1U9K+qQJHNWTkGtkfUUHENb3ddG7O0K+9kkZeMgK85DiqZXy3v4xTly3TDevmQMtgBR4uMpQOkF9s5GqSgb1nKsgtNFrNv0xXxLHfVnIlYju64jw8fJvSefBswjqNsqvr2rldXI3YQXr8XxTmpeGk9SIgtDPdhz2Gu0+IJG7MhX1cjdhBRuJFctNjMBgqeOzdS3bzV7g40+L5Obh2CMe1Y2vUPp5cXraaKy+/bzddFSofT8Jffxq/kQNROGnIP3eJqJdWkLXvqEVcr0G9aLn0CVzbh6MvLiXtt31cevYtyjKyLeKqlXBnPye6hKtwdpSRmqVnx9FSTkaW1apJ6yTjroFOtG+mRKWUkZiu56eDxVyKq5DEc1DAoC4aerZT4e2mQFduJD61gl8PlxKdVGEj92oUchg/wovBvdzwdFWQllXObwdy+XV/bq1pATRqGfeN8ea2zq64OMtJTC3jx13ZHDpZYBG3abCaGXf5EBbiiN5g5HxUMet/zCA9q0Ka3x3e9OmsxcVZTlJqGZt35fDHKcv8auLmomD6OG+6tnNBrZIRk6jjm22ZnIsqsYjbvqUT997hRWiQGl2ZkZPnC/l8SyZ5hdZ/Y2qVjPGDtXRvq8HZUU5KZgW/HCrk2PnSWnVpneVMGqqlY0sNKqWMhNRyfthTwMVoqR0sut+TVqFqi/TnrpTy9hc51nUpYWx/J7q2UpttbPuREk5crJuNjR/kRLvmKpONpVWw9WAxl2Kr68PLTc7rj3rYzOOva2Ws3GRZN2oljL7Nkc4tlThrZKRlG9h1rJRTUeW16nJxkjGunyNtmzqYdGXo+eWPUqLipfaskMPwXhq6t1bi7iInv8jIicgyth8ppdyG6auUMLq3ms4tlDhpZKTlGPj9hI7Tl+3/VtxdZAzqoiLIR0GgjwIntYyvdpVw7KL1+2kZrGBUbzWB3grKKoxciKlg6yEdhSXWn61qlYwJQ7T0aOdotq9tBwo4Wgf7cnWWM2m4K51aqlEpZcSnVvDD7/lcqGFfz8/yolVTK/Z1uZQ3P7d8fpm1NVAbq0KhkHHfuEaMGOCDp4eS1HQdW3emsWVHWq36ADRqObMmBTGglxeuLg7EJ5fwzdZk9h2WlsnCOU0ZPsDHIn18kuXz5b/Mhx9+yFtvvUVKSgpt2rRhxYoV9O3b12b8r7/+mjfffJMrV67g5ubG8OHDefvtt/Hy8qrzNYWrKSA1NZXHH3+cpk2bolarCQ4O5o477mDPnj3mOIcPH2bkyJF4eHig0Who164d77zzDnq99MUvk8nQaDTExcVJwseOHcuMGTPMcewdtcXbuHEjAPv370cmk9G2bVsLHe7u7mzYsMEcx96xYcMGu+VTlUdubq7V80uWLLGab3h4uDnOgAEDJNqrWLFiBSEhIZKwsrIy3nrrLTp37oyzszNubm506NCBF154geTkZJvXu/6IjY1lyZIldOzY0UJvbGwsMpmMs2fP2r1vW0wdqqJzmILdp8tZt72MxAwD9w5W0bGZwm46L1c5HZsr0BvgUoJ9p0yjkhFxTc93+8tYt72Mg+cqaNVYwWNj1ThZvosB2L7+cS6d3Er3oY9yx+xP8Q1ux64vFxB1apvda53eu4aKslK63P4QYx78jJ4j5pGRFMmmd+8iK/WKJG70+d2kxp3F0785Xo1a2s23CpWXO40fuAe5WkXaz7vrlKYKuUpJj10b8B7YiwvzX+XkXXPQpWXR/dc1ePbtJonr2bcb3X/5DF1aFifvmsOF+a/iPag3PXZtQK5SWuT98F1aerZT8cufJaz6roDYlApm3+lCt9Yqu5ocFPDkJC3hTRzYtLuYDzcXkF9kYO49WloES/vupoxwZtwARyIul/PB5gK+3VWE1knOU/dqCQmwby8AD0/2Y/wwT7YfyGHJ6kSOni3kgQm+jB/uWYfSg2cfDGRQTzc2/prJsvcTuRpXylOzGtGvm1YSL9BPxatPBuOgkPHWmmRWf5lKIz8Vry0IxtVFcV1+jRjY05WNv2Wx7IMkrsTpeGpWAP26amteWlpmDjKWPRFE+3An1nyfzvKPk8kr0PPSY0G0aeEoidumhSMvPRZIXoGe5R8ns+b7dNqHO7HsiSAcHKyvd5g72YPbOjmydV8h73yZTUxSOY/e40Gv9hr7uhTw7ExPWjdT89Vveaz4Jpu8IgNPTfOkZYilHaRlV7D0k0zJ8fVv+Tbzf+RuLb3aqdn2RzErN+UTk1zBg2O1dK+Djc2/15XwECWbfi/ig+8LyC8y8sREV8IaV9tYXqGB1zbkWRzbD5sal2cuW29sz77TmZ5tlGw/XMoHm4uIS63g/juc6Rpu+TupqWvuBBdaNnbgh30lfLK1iIIiI4/e7UzzIKk9zxztxJCuav6MKOPDzUX8eU7HoC5q7h/tbDP/B0Y70aOViu3HdHy0tZj4VD0zRzrRpaX9PnFvdzldWyrR6+FijH2nrHmggkfGOlFQbOTTbcVs3l9KWLADj9/thIONn+S8ez3o29mJLXsLeOvzLKITy3hskie92jtaT1CJgwIW3e9Fm6Zqvvw1n/e+yiGvUM/TM7wIt2ZfWRUs/jhDcnz5q237goZrY1XMeyCE+8Y2YuvONJ559RKHjufw2Iwm3Deukd10VSx7Koxh/X344ockFr4WxaVrRbw0rwWD+1g29Et1euY8f0FyLFtxtU7X+aeora1yM8eNsmnTJubNm8fzzz/PmTNn6Nu3LyNGjCA+Pt5q/D/++INp06Yxa9YsLly4wPfff8+JEyd44IEHbui6YkTrP05sbCx9+vTB3d2dN998k/bt21NeXs7OnTt59NFHuXTpElu2bOGee+5h5syZ7Nu3D3d3d3bv3s0zzzzD0aNH+e677yRGL5PJeOmll/j888+tXjMlJcX8/02bNvHSSy8RFRVlDnN0rH54r1+/nuHDh0vSu7u7S/6+du0aX3zxBTNnzrS4Vu/evSXXe+KJJ8jPz2f9+vXmMDc3t1pKqXbatGnD7t3SRrSDg/TnpdFoeOGFF7j77rtRKq2/0HU6HUOHDuXcuXMsXbqUPn364ObmxrVr19i6dSurV6/m+eef5+GHHzan6datGw8++CCzZ882h/n4WPZs1Qctg+WEBSn4Zk+ZeQQrOsWAu1bGyJ5KIqL1GK13ihKTYuDlL009oIHeMjo1t/34+elPaU9sdArkFBi5f4Sa1iEKTkZJHbXYiwdIuHyYoVPeJqzzaACCWvSkICeJw9veokWnkcjl1lsRo2Z9hJNW+tIKbNGDL14ZQsSBzxk08RVz+KB7XjZ/F+TA5mVkJF6weQ9VlMQlscvH5BQpvTxoPOueWtNUEXz/BFzbtuTPvhPJPXoWgKz9x+h76ifCX3+aw32q82r1xjMUXY7l9MS5GCs7HkpiE+l9cCNBM8cT/8m35rhtmyppHapkzU+FnKgcwbocX4GXm4K7BzpxMrLMZj32aa8m0NeBN77IJzrZ1KiLiivkxftduXugE69/YWoYOSige2sVxy+W8dOh6l7Vq4kVvPW4B93bqIlNKbZ97wEqhvR246ufM9nyu2nE5K8rJWidFdwzwosdB3MpLDbYTN+ljTOdWjvz9tpk8wjW+csl+HgqmXGXD3+cLMBQeY/33uFFeYWRlz9MoqTUlOe1+FI+WtqUsUM8+GJrJl3aONOxlTPvrEsx5/fX5RJ8vRyYfpcPf5yqzq8mt/d2pUmgmoVvxRMVU1qppZgVzzVh+lhvnnkrwRx3+jgfktPKeOOzZAyVt5eWVc4bTzVmSC9XdhzKk+TdvoWads3VfPhdjnmEITKmDC93BROHuXL0fKnNuuzfxYlgPyXLPs3kakK5Oe0rj3ozaaiWpZ9mSeKXlxu5llj7qA9A22ZK2jRV8dnWAo5Xji5ExVXg5SZn/GBnTtixsds6qAnydeC1z/PMI59RceUsfsCNuwc68drnJhur0GO2wesZN9AJXZmR4xcsG8FtQh1oFaJk3S9FnLpkupcrCRV4usoZ19+RU1HlNnX1aqci0EfB218XEJNi+o1djq/guelaxvV35K2vCwEICVDQKUzF5n0l7D2lM+mPr8BggDv7ORLexMFi9Ld1iAOtmjiwYXsxp6JM564k6vFwlTO2r4bTlwtt6rqWqOe5T03XDvaV23UYx/bVkJ5rYO0vJWZ7zcovYf5Ek/P5xzlp/XYIU9OuhYYPNuVw5JzpdxwZU4a3u4LJI1w5er7Epq4BXZ0I9ley5OMMs31djNGx/DEfJg13ZcnHmZL4ZRVGriXUzb6g4dpYFSFBjowc6MPajYls2mZqh0RcLMBN68CUuxrx8640Copsdzr26ORGtw5uvLzyKnv/NP0Wz17Ix89bzUNTG7PvcJbkmWM0QuSVQtsF9h/n3XffZdasWWZHacWKFezcuZOPPvqI1157zSL+0aNHCQkJYe7cuQCEhoby0EMP8eabb97QdcWI1n+cOXPmIJPJOH78OOPHjycsLIw2bdowf/58jh49SlFREbNnz2bMmDF8+umndOzYkZCQEB544AE+//xzfvjhB7777jtJno8//jhfffUV58+ft3pNf39/8+Hm5oZMJrMIq8Ld3V1yzt/fH41G2kv7+OOPs3jxYkpLLacxqFQqSVpHR0fUarVF2M3i4OBgodPb21sSZ/LkyeTl5fHZZ5/ZzOe9997jjz/+YO/evcydO5cuXbrQvHlzhg0bxkcffcTy5ctxcXGRXEehUKDVai3C/gnahijQlRk5Hy19OZyM0uPmLKOxr+1Hio33XZ2pmtZisNK2jj6/G6XaieYdpE55q+53UZSfTlpchM18azpZAC5ufri4+VGQmyIJ/19/fNHvziEUXoo2O1kARr2epG9+xqN7B9SNfAFQN/LFvVt7kr7+yexkAeQcOUNhVAz+dw6R5NsxTEmpzsipS9JGwuFzOjy0ckIb2XaCO4apSM3SSxofBiMcu1BGaCMH3F1k5jCjEUp00povLTNiMBipqLBvET07uCCXy9hzROpY7DmSh1olp3Mb2yMDAD07ulBSauDP09JpPXuO5OHlriQs1PQckcuhWzsXjpwpNDtZABnZFfx1uZgeHVwA6NHBVn75eLk70CLU9uhRjw4uJKaWmZ0sMNnxgRP5hIU64ulmKm9PNwfCQjTsP54vsfOo6FKS0sro2dHFIu+urTWU6AwcvyB9/h06XYynq4JmQbYb3V1aaUjOqDA3gqt0HY4ooVmwCg/t37f3TmEqSnVGi6moVTbW1I6NdWqpIiVLL5leajDC0b90NA00TcWzhY+7nLDGDpyM1FFaZmljHVooKS0zcqbGNMEjf5XhrpXbHWnt0FxJapbe7GRV6Tp+sYyQAAfcKm2/WaDp3i7ESK/xV7Tp744tLOukQzMHk64a0wSPXSzD3UVOiL9tXXV9tro5y2jir+BEZLmkgR6ToictW0/7Zpa6quzr2F/SKWgHT5fg6aqgebAd+2rtSHJGuYV9/Xm2hObBKjxcb+552lBtrIo+3TyQy2Vs35chCd++LwONWkH3ju527++27p4Ul+jZf0Ta4bFjfwY+nipatbB8HjQ0ZHL5P3bodDry8/Mlh06ns6qjrKyMU6dOMXToUEn40KFDOXz4sNU0vXv3JjExkd9++w2j0UhaWho//PADo0bZX45QE+Fo/YfJzs5mx44dPProozg7WzZa3N3d2bVrF1lZWTz11FMW5++44w7CwsL49ttvJeG9e/dm9OjRLFq06B/Tfj3z5s2joqKC99+v25qXW4WrqyvPPfccy5Yto6ioyGqcb7/9lttvv51OnTpZPf93hsvrEz9POem5Roue+9RsU6vQz6N+9cllppGRRl4y7uitJCPXwF8xlj2AWamX8fBthlwhfbFWTe+rOQWwNvKyEijIScbTv/nfF18PaNu0IP98lEV4QWWYtnWLynhhADbjVp2vItDHgZQsvUU9JmaYyjbQ23ajLtBHQWK6ZQ9vVdqAyrQGAxw4raNXWzUdWijRqEzrHaYOd6ZEZ+TQWesvxCoaN1KTW1BBbn6N0csknfl8bekTUnUWjnnN9AE+StQquTm8ZtwAHyVKBxmNG6lISC2zmV+TANt6GjdSE2c1/7LK8yrJv3FJlr3ksUk6Glu5RpCvA8kZFRa6EtJMdRTkZ7uxGeTnQEKa5QhCQqopbaCvNK2vpwMfLvJj/RJ/3nrSh/FDtChtZB/oo7BuY+mm+mzkY9vGGvk4kGTNxuqQtk8HNXKZjEMR1u0rwFtBqhVdyZX228iO7TfyVpCcafn8SaoMC/AypVVUtqwqakSt+jvQiv4Abzlp2QYLXUkZhsq8b765FuAtr9Rr2VuVnGmgkZVrBPkprdpXfGq5+bwtgv0czLZ0PVU2F+grTevn6cDHz/vz+bIA3pnvy4TbbdsXNFwbqyK0sSM5eeXk5NWYoRFfbD5vN32wI3FJJRZlHx1XbD5/PSqVnM2fdmL3xu5891En5t7fBK3zP9PpWldkctk/drz22mu4ublJDmsjUwCZmZno9Xr8/Pwk4X5+fqSmplpN07t3b77++msmTpxo7rR3d3dn9erVN1QGYurgf5irV69iNBola4lqcvnyZQBatWpl9Xx4eLg5zvW89tprtG/fnkOHDtldaFgbkydPthidOXfuHE2bNjX/7eTkxOLFi3nuueeYPXt2vUwFvFHOnz+Pi4u0d2nSpEmsWbNGEjZnzhxWrlzJu+++y4svvmiRz+XLlxkwYIAkbNy4cfz+++8AtG/f3mbvS111GW3NpagDTmrILrBMX1xqCnPS1J+j5eIIL06tfpHEpxn45BcdZVaWIJQW5+LmGWwRrnEy2UJpUW6dr2vQV7B34/Mo1U507DfjRmXXKyovd8pz8izCyyrDVF7ukn+tx81FWXm+CmdHGZm5lg3GohKD+bwtnB1lFJVasYHKEUcXx+rG2nd7iinRGXl4nGl0CiArT8+73xaQkWt72h+A1llBoZVpNboyI+XlhlobEFpnBWmZlk5EVZ5V6av+LSy2vFZBkR65XIaLk7z2/Oz0gGudFRRYyb+mFtfKf61NJyos0qN1tryGi5Oc9BzLH0XVtEoXJ9u6XBzlFFmZflllB9envRxXxrHzpaRkVqB0kNEhTM3I25wJa6zktfXZFlO0XBzlZNixMRc7NubiKKPIysYMVXZnK61MBr3bqUnJrOBaovW1Ss4aGVl5Vu65Mm9nO88wZxu6qmy/6neTmmW676aNFJJrVY10Wft9OWtkZObZfrba+03Wlap7K7by+y3SGa0+v12c5GRkW5ZldT3at6/CEsuyrrJN7XX2FRVXxtHzJSRnVKBSmuxrVF8XwpqoWL42y+oUwIZqY1W4uigpKLSMU6ozUFZuwNXFfhPc1cWBlHRLZy6/Mk9XbbWjei2umGtfxhNT6cR1aO3K+FH+dG77v28P/a9YtGgR8+fPl4Sp1fY74Gp2VhuNRpsd2BcvXmTu3Lm89NJLDBs2jJSUFJ5++mkefvhh1q5dW2edwtH6D1PV4K7LKImtxrktI23dujXTpk1j4cKFN+QY1OS9995jyBDptKfgYMsG9axZs3j33Xd54403WL58+d++3t+lZcuW/Pzzz5IwrdZygbxarWbZsmU89thjPPLII1bzqlmeH374IUVFRaxatYqDBw/etK6kpCQLZ+56dDqdxfB7RbkBB2XlA8yen3az8wOvo7gUVv1YioNChq+7jP4dHHhotJpPtukosLaRkh07rutIoNFoZM+m50mOOcWIGavQegT8TfX1iB3H2OJ3aSuulXB7/nat1VjHtCN7a7i9u4Ztf5RwNbECjUrGwC4a5k3SsnJTAQlppkaSXCbdBbiqB9dun0AdbM1YV6G1XMtY41+rcWrRYzf/mlpq0XFD165NVx3Pbd4jXftx7oqOjBw9945wpXO4mlORlg3Cm6m+v5O2bVMlHq4Kvt9jfcZAfeiqS8YXYipIz9Eztp8jBcVG4lL1hAYoGNNXg95grNVW6l/YzWV1M5e2b/fVJ3/YLZ2SG3HZZF/3jXSjSysNJy9a3+GwodjY33mG1aVc61x+v0pHZU6dz+dqbBFLF4TVTPa/5R+cbq9Wq2t1rKrw9vZGoVBYjF6lp6dbjHJV8dprr9GnTx+efvppwNTR7ezsTN++fXnllVcICKhb+0BMHfwP06JFC2QyGZGRkTbjhIWZfqS24ly6dIkWLVpYPbd06VLOnDnD1q1b/7ZGf39/mjdvLjmsbSTh4ODAK6+8wsqVK0lOTv7b1/u7qFQqC522frxTpkwhJCSEV155xeJcixYtuHRJul14QEAAzZs3x9Ozbjut1aarSZMmdtNYG44/uuMtAIp11ketqsKKdfXXGjAYISnTSFyagRNRej77VYenq4wBHS3rX+PkbnXUqrTYNMKjdqq9V89oNLJ30wtcPrWNIZNeo2nbwTd9DzdLWVYuSk93i3CVh+l+yrPzzPEAG3HdzfGqKCox4mylJ7oqrNjGNs/Vaa3YQGVYVW+yv5ecO/o6su2PEn47XMrl+ArOXS1n9fcFFJcamTDICTBNJ/xooSdbPmhpPtq2cKSgSI/WxXLUSq2SoVTKrY4QXU9Bkd7qqJdL1ahRZfqCGqNK16N1VmAwGCkqNtSaX2GR7RG6giK9ebTKatpKLfmVWmzFtXaNwmKD1VGrqjBrIwrmtCXW01bZgbXRrus5HGHq8WgWbLnDW2GJwepohzlvOzZWWGK0OqJQNSJjK+1tHdVU6I0cOW97SldRqdHqqJW90R5z2tpsvzKt3gAfbi4iu8DA4xNcePtxNx4Y48zOo6UUlxrJLbQ+omZNV9Wz1doo8o1ib9TOWS2zeu+27KuqHmuzL61d27R/T3+erbIv69MTG4qNebnJ+WSRF3s29jAfHVpryS8sx1VrOZ6hUctRKeVWR7uuJ7+wwmr6qpGw2tIfOp5DSan95+R/BZVKRZcuXcyzg6r4/fff6d27t9U0xcXFyGs4ilUzrG5kZpBwtP7DeHp6MmzYMD744AOra4Zyc3MZOnQonp6evPPOOxbnf/75Z65cucLkyZOt5h8cHMxjjz3Gc889Z7H9+j/BhAkTaNOmDUuXLv3Hr3UzyOVyXnvtNT766CNiY2Ml5yZPnszvv//OmTNnbo04TMPxeXl5kqPncFOPTmq2AV93GfIa7yd/T9OjJC2nHrtda5BXBPlFRnzcLF+OXgFh5KRfw6CXvniyUkzTWr38rXcGVFHlZEWe+JGBE1+mZdcx9Sf8Jij46zKubS17JLWVYQUXrlT+e7ky3HLLeW3bMPP5KpIyKgjwUljUY9XakSQr61Cq0+oJ9LF8+VelrVrDEuTrgFwmIzZFWicGg2kdRNUaiNwCA8s35LHgtVjzcS2+lLhkHe5aB9xdpU5Hk0BTD2Z8sv31EXFJOoL91RYdqiE10qdklKMrM5jzlVyrkZqUjHLKK4zEJ+sI9ldZ5Nekcq1XXIptPfHJOhoHWjojTarWZFVqiU+WrtmqeZ14K9dISKugkY+Dha6qtVmJabYbYwlpFQRbWWMTXJXWyhoWa1hrcyRl6K3bmG+lnWTYsbH0CqvrmKrSJmVY6tI6yWjfXEXElTIKim0/h5Iz9Phb0VW1NsvaGixz2ky91TVcVWEp16XNyDXwzjeFPPdxHq9uyGfhh3mcvlyO1knOVStTzpIzDfh5yq3oMlVsSpZ9p7cupFSuzarKs+Z1kq1cIyGt3Kp9mW3Eyho/c9rUcqtrBKtszl7a67HVpm0oNpZbYOCVdbk89Oxf5uNydBEx8SV4uCnxcJP+xkIbmzqZYuLtf+MqJr6EJoGOFmVftbYrJqHhfyPrn1yjdaPMnz+fNWvWsG7dOiIjI3nyySeJj4837+K8aNEipk2bZo5/xx138OOPP/LRRx8RHR3Nn3/+ydy5c+nevTuNGtVte34QjtZ/ng8//BC9Xk/37t3ZvHkzV65cITIyklWrVtGrVy+cnZ355JNP+Omnn3jwwQc5d+4csbGxrF27lhkzZjB+/Hjuucf2dtWLFi0iOTnZYuvzupKbm0tqaqrksLWRBMDrr7/OunXr7Mb5u5w/f56zZ89KjioqKiosdKal2f4g4ahRo+jRoweffPKJJPzJJ5+kV69eDBo0iJUrV3L69GliYmLYuXMn27dv/8d2E7wetVqNq6ur5KiaNnghVo9aJaNtqFRHlxYK8oqMxKfffGPAFl6uMtycZWTmW751m7W7nXJdMdfO7ZKEXzqxFWdXX/yadLCZr9FoZN93L5qcrPFLad397nrX/ndJ/Wk3Lq2a4d69vTlMplAQeO8Yco6dRZeSDoAuOZ2c4xEE3neHZKqGe48OuIQ3JXWrtBfvzOVyNGoZnVtKG/S92qrIKTAQY2U74+q0ZQR4KyS7s8ll0KONiuikCvIqPyidV9lrX3PnLwcFNPZXkFNgOq83QFyqnqvxOvNRojNyLKIQg8HIoJ7S0cjBPd3QlRk4fcH+b/xoRCGOGjm9O0mn8A7s6UpWbjmXK3cANBjgxLlCenV0wVFd/fL29nCgXZgjR8+apswdPWvKr1cnFyv5VXAlxvbHW4+eLSTYX02LkOqdCeVy6N/dlaiYEnLyTA3C7LwKLseUMKC7q6TxGBaiIchfxZGzlls3n4osxVEtp1tr6a6Ht3V0JDtfb3c79lMXS2nk40DT63YmlMuhdwdHriaUkVtg//d8WydTg+9aguXmHWeiykw2Fl7DxtqpySkwWN0y25z2chkB3g6S3S/lMujZVk10UrnZxmrm66CQ8Uctm6xEXC1Ho5LRMUza+O3RVkVugYHYFNuN84gr5fh7KSQ7AMplps8YxCRXkFdkqSuv0EhypoHyChjSzfQB6sPnLcvr3DXT1NqOLaS/lx6tVeQWGohNvfnOyrwiI7GperqFKyUzrUP8Ffh5Koi4amkrJy9W2lcbqX317exEdr5esqOgtbSBvkrJzpdyOfTu6MjV+Nrtq29nk0Ni6xoNxcaqnmGXo4vMR0mpgT9P5GAwGBk2QLoD8fAB3pTq9Bw/m2v3/g8dz8bJUUH/HtLZLMP6+5CRXVbrVu79e3riqLm1m2E0JCZOnMiKFStYtmwZHTt25ODBg/z222/mWT4pKSmSb2rNmDGDd999l/fff5+2bdsyYcIEWrZsyY8//nhD1xVrtP7jhIaGcvr0aV599VUWLFhASkoKPj4+dOnShY8++giA8ePHs2/fPpYvX06/fv0oKSmhefPmPP/888ybN8/u+hdPT08WLlzIc88997f0Wfs21muvvcazzz5rNf6gQYMYNGgQu3btsnr+ZujXr59FWNXw8YULFyzm66rVaqtbzlfxxhtvWAxZazQa9uzZw4oVK1i/fj2LFi3CYDAQGhrKiBEjePLJJ+vhTv4+UQkGLifqGXebaRe5zDwjHZsraNlYwbd7q79ZMr6fks5hCt7cqCP3uhdWu1CTE+BZua1vkI+csnLT+fMxlVPOPGXc0UvJ+Wg92QWm9Qz+nnJua6egWAcHz1m+PJu06kdwWG/2/7CUstJC3Lwbc/nMr8RfOsTt971l/obWno3Pc+nkVqY+twtXz0AADm55hYvHfqBV97vxCggjNfasOV+FgwqfoNbmv/Ozk0hPMH22IC/L9O2jqxE7ANB6BuIX3M5qufkM64fC2REHrWl3T5dWzfG/axgA6dsPYCgppf2nrxI4dSz7W95OSbxp+mvi+h8IefheOn+7kkvPv4MuPYuQh+/FuWUox4ZJfxuXFr1Njx3r6LJxJbEff4Pa14vwVxeQ/1cUiRs2S+JeiC7nYkw59w5zQqOWkZ6jp3trFW2bqVj7c/X3eqaOcKZXOxUvfJxHdr6pfg6f0zGgs5qHxrrw44ESCooMDOiswd9TwXsbq9dZXE2oICa5gtG3OaJSyriSUI6j2rRGy8ddwbpt9hsJCSll7D6cx+TRXhgMRq7EldKplTNDb3Pj622Zkm9oTRzpxcSRXry4MoELV0y9vKcvFHHmYhEPT/bDUSMnNaOMvl1d6dLGhXfXJUt2KvvmlyzeedaFF+YEsXlXNioHGZPv8Ca/SM9Pe3JM+V0s5mxkEQ9P8sNJoyAlo4x+XbV0aePMu+tTzPk9NsWPgT1ceXhxjHkTgd1H8hnR351nHgjgy62Z5BboGdHfjUA/FYtXJUru+4utmSyZG8TTswPYfiAPd62CqWO9iUvSseeI5cdbz13Rcf6qjul3uOGolpGWradnO0c6hGn46Pscc13OGuvGbR0deeq9DLIqHbuDp4sZ0sOJxyd68N3v+eQXGhjcwxl/bwfe2JBtvkZYEyVj+rtw6qKO9JzKzTBaqBnQ1YkL13ScibJ0bv6KLudCdBlThjvjaLYxNe2aqVjzU4FZ1/SRzvRqr+a5D3PNNvZnhI6BXTQ8NM6FH/cVU1BsZEAXNX6eCt771voHbG/roCYrT8+FaPujJBdjKoiMLWfSEEc0KhkZuQa6hitpE6pkw69FZl33DXOkRxsVS9bkk13ZuXPkrzL6dVIza4wzPx0soaDYSL+OKvw85Kz6XmrPQ7qpyS8ykFNgROsko3NLJR2aK/n8t2KrjfiLsRVExlVwzyBHNKpSMnINdGmppHWIA59vLzbruneIhu6tlSxdX0jOdRsTdaz8LqGXm+nZ2tjX9CkOgLNXq5+ZP/1RymPjnJg1ypFDEWW4OMkY00dDcqaeYxcty+7cZR3nr5Qyc4w7jup80rIq6NXBZF8ffldtXw+Mc6NvJyfmv5tOVuUGFQdOFTOkpzOPT/Zg084C8ov0DOnhTIC3A6+vq96yvGUTFXcOcOHkxVLSs/UoldAhTMPAKvu6ZP092lBtrIrYxBJ+25fBzAlBGAxGoq4W0bWDG6MH+7JuU6Jk05tpdwcybXwgC5ZFEhFpeo4eP5vHiYg85s0OxclJQVKqjsF9vOjRyZ1XV101P3P8vFW8MLc5ew9nkZRq+m5e1WYYMfHF5hG0W4FM1rDGc+bMmcOcOXOsntuwYYNF2OOPP87jjz9+U9eUGW9mCzKBQPCfYOGn1VMUVA4wrJuS9s0UOKkhPdfI/rMV5g8YA0zor6RrSwde/6aUnOsaFW88aHs726pruDjCqJ5KGvvKcXWSIZebemIvJxrYd0baaxwUWN3LWqYr4uhvK7h6dgelxbl4+Daly5AHCetU/c2L3d8+y6UTW5n2wm5cPYMA+PzlQRTkWF/Xp/VoxPQX95r/jjz+I3s2Wu80CO82liGTXzf/3XRs9W6eA6/swSkkyGq6vc0HURKXRPu1rxE87S7z31WofL1o9frT+I4cgMLJkfyISKIWryRr7xGLvLwH9yZsyVxcO7RCX1xC+m/7iVz4JmUZ1Y3mn182pVMr4c7+TnQNV+GkkZGarWfHkVLJN2mmj3Kmdzs1z32UK9k9Tesk4+6BTrRrrkTlICMxXc9PB4stPsKqUcsY1l1Dx5YqvFzl6MqNpGTq2Xms1KKxkhon/dYMmLbJnjDCi8G93PBwVZCeXcGv+3P4dX+uJN6kUV5MHu3N8+/G89eValvVqGVMGeNDny5atE5yEtPK2Lwz2/zB4etp1ljN9HE+tAx1RG8wcj6qmPWbM0jLqpDkd98Yb/p0rsqvnM07s/njVHV+c6f6MaiXGw++EE36dbu1uWkVTB/nTde2LqhVMmISdXyzLYtzUZYfbe4Q7sTk0V6EBplGQE7+VcjnP2aSV1j9G3P1qh6pU6tkjB+ipUdbDc6OclIyK9h2sJBj56sbqLPHudG3sxPz30mX7Djp6ixn0jAtHVtqUCllxKeUs3lPAReiq+3A11PBlJGuNPZXmtfXpGZVcOx8Cdv/LJJsY652rB5dUCth7AAnurZS46yRkZqlZ/uREk5crM575mhnerfX8OwHOVIbc5YxfqAT7ZurUCllJKRV8NPBEiJjLRu5zQIdeHa6G9sOFfPzIdvTqVQqhVnXHbc50rmlEieNjLRsA7uOlXLqum9rTR3uRM+2Kl78NN/cOAeT7Y/t70jbpg4m28/Q88sfpUTFS21/RC81PVqrcNfKKa8wEpOiZ+fRUq4lWY5MyR1MZapSwh291XQKU+KklpGeY2DXCd3/sXfW4VEd3+N+dzfursQIEQjuBKd4ixSnpWgpFC+UUgqlSJFiBVoKLU5b3K24u3sgWBKIkBC33cju749NNll2k0ALH8L3N+/z3Ad29Ny7J7P3zJk5w9VCZ2v1amlCnQpG/LAyVWMAAvwyyqrI+x6+QNtwCPCU8WE9Y9wdZWRnq7j9JIcdpxQ6e6YS49TGo7GRhG4tLKlTyRRzUylRcTnsPpGqOSAb4IvONjSqbsaoOc919KtnayuqBppgbCghPDqbLYdTuPOoQAec7WR89pG1jn6dv5nJvtNpOmHyTc0LlvmWJh17eP2hTppMJqFXJzdaN3HEzsaQmDgFO/Y/Z/t+7RUvfbq607drGUZNvsuNuwXjiYmxlM97etCknh2WFgY8jczk7x1RHDtbMKZbmMsYO7gsfj5m2FobIpVKeB6n4PSlRP7eFsWeNTX1yvu/IHG6/qBfbwLbCUveWttvEmFoCQSCEilsaJUmChtapY3ChlZpIt/QKm3oM7RKA+/67LqiKGxolSYKG1qljXxDq7SRb2iVNvINrdJGYUOrNKHP0CoNHNtU5531nThTv/foTWA7/re31vabpHT+dQsE/0PatGmDhYWF3utdhIoXCAQCgUAgeN+RSKVv7XpfEHu0BP/fs3z5cjIz9Xts/k1IdYFAIBAIBAKBQBhagv/vcXd3f9ciCAQCgUAgEPyf4t+EYf+/xvvjexMIBAKBQCAQCASC9wTh0RIIBAKBQCAQCARvllIW3v1dIJ6AQCAQCAQCgUAgELxhhEdLIBAIBAKBQCAQvFHEHi3h0RIIBAKBQCAQCASCN47waAkEAoFAIBAIBII3y3t03tXbQhhaAoFAIBAIBAKB4I0ikYilg8LUFAgEAoFAIBAIBII3jPBoCQSCErly7M67FkEvV961AMXgO+3cuxZBL+2/r/euRdBL/YtL3rUIejkvafCuRdCLr2X0uxZBL6GBTd61CEUiMy2dc8sBXfzetQh6yZ2w8F2LoJf7gU3ftQh6Mbt6/V2LUPoQSweFR0sgEAgEAoFAIBAI3jTCoyUQCAQCgUAgEAjeKCK8u/BoCQQCgUAgEAgEAsEbR3i0BAKBQCAQCAQCwZtFIvw54gkIBAKBQCAQCAQCwRtGeLQEAoFAIBAIBALBm0Xs0RKGlkAgEAgEAoFAIHizSMTSQbF0UCAQCAQCgUAgEAjeNMKjJRAIBAKBQCAQCN4sYumg8GgJBAKBQCAQCAQCwZtGeLQEAsG/RiaT8ElHF1o1dsDOxpCYWAW7DsWx40DsK9U3MZbSr7s7jevaYmVuQESUnA27ojl+LrHYevMnBVC5vCU7DsTy6+qIUinXP9fUacaG0KGRGTUCjTA3lRATn8v+83Iuh2SVKIelmYROTc2o7GuIkaGEZ7G57DyZwb3wHK1yBjJoVsOEupWMcLCWochWERGTw96zch5H5uhtW2Zhjt+EIVhVCcSqagWMHe0InfoLD6b9+krPyMjRjsBZY3Fu2xSZmQkpN+9xf9IC4o+d1ylr36weAVNGYlU5kNwMOc/3HePet3PIikvQ23aGXM7Sjbs4cv4qKWnpeLm50LtDS1oG1ypWpj3HzzFt6Vq9efuWzsLexlorLVOuYO2ugxw6e5mYFwmYmhhTztOd8QM/xdPVSacNhTyDvRt+4dr5A2SkJePs5kPzDgOoXr9NsXLdv3mOw7tWEvPsEempSZiaWeLqUY6m7foQVK2R9j1sWMTda6dIjIsiK0uOta0j/pXq0vLjL7BzdNPbfmZmJn+uXc3pUydITU2ljIcHXbp2p3HjpsXK9TJ/rlnFxo3r8fTy4rcly3Ty5fJMtmzexMkTx4mNjcXU1ARvn7IMGz4Kd3d3nfKlVcdk5mb4fT8Sl49bY2hrTXroYx7/vJyYrftKlMnhg/r4jhuCVZUKKLOySTx7mdAf5pN276FWOYmhIb7fDMate3tM3JxQxLwgevMeHv70G0q5Qm/bEmMTbDv1wrxWfaTmlmRHPyN531bSL54qUS6TwErYfNgVIw9vJEbG5MQ9J/XUQVKO7AOVEgADeyc85iwvso2MW1d5/vNknXS1fq3h1KmTGv3q2rUbjRs3KVGuwqxds5qNGzfg5eXFb0t+18mXy+Vs3ryJkydOFNIvH4YPH/le6ReAPDODXRt+5crZQ6SnJePi7k2rjv2p1aB1sTKF3DzPgR2riH76OG+ssMDNsxzN2/emUvWGWmXnTRrAg7tXdNqoUDWYERN/e6Vn8LaRSIU/RxhaAoHgXzOyvyfNG9izenMk9x9lULOKFUN6e2BqImX9zpgS608e7UtAWXOWb3jGs2gFH9S3Y+IIX6SSxxw9q/8HrENLR9xcjN8buQZ3ssTLVcb245k8T8ildgUjBnawQCJJ49Ldoo0tAxl81cMSUxMJGw9nkJqhpEl1E0Z0s+TnDak8eFpgQPVqY06dCkbsPyfnXkQG5iYSWtc15etPLJn9Vwph0bk67RvZ2+D5eTdSbt7j+a7DeA7oVuJzyUdqZEidg6sxtLbizujpZMXG4/Xlp9Teu5wLrfqRcOqSpqxdw1rU3rOM2H0nuNxpCEZO9gTO+Jo6B1dzpk5nlFnZOu2Pm/cHIY/DGNLzYzxdnTh45hLfL1qJSqmiVYPaJcr3/eDeeLk7a6VZW1hofc6QyxkydQEvEpPo3aEV5TzdScvI5FboY+RZ+r+XFfNGEfHoNu16jsLJ1ZsrZ/axZtE3KFVKajb4sEh50tOScS1TjnrNOmNlY096WgpnD23ij1lD6TVsBrUattOUzUxPoUZwG5zLlMXYxJyYZ484uP0Pbl8+zvh5OzC3tNFpf8aPUwh9EErfvv1xdy/D8ePHmPPTTFRKFU2aNivxeQE8fvSIbdu2YGNrqzc/MzOT774dS3xCPF27dsfbpywZ6emEhNxFoZDrrVNadaza34uwrlaR0MnzSX8YhmvXj6i6ah43pBKiN+8tUiants2otu4XYvce5dpnIzG0ssD326HUPvAn55p0I/PJU03ZKivn4tiyEY9++o3kq7exqV0V37GDsShfjqs9hupt33noeIx8/Ejcsobs51FY1GmE0+CxxEokpF84WaRcJhWq4DJ6MvL7d3ixejHKLDlmVWtj/8kXGDi6kLBebVzlJCcQ9eNYnfpm1etg07YLGVfP6W1/+o/TCH0QSr++/XBzL8OJ48eY/dOsPP16NWP+0aNHbNu2tVj9Gv/tNyQkJNClazd8fHxIT08nJCQEhUK/YVpa9Qvg9zmjCX90h46fjsTZzYuLp/axYsG3qFRKajdsW6Rc6anJuHn40uCDTpqx4tTBzSyeMZx+I6ZTp5H2OOPgXIb+I2dopZmZW77ycxC8fd6ZqSmRSIq9+vbtC8C1a9fo2rUrzs7OmJiY4O/vz8CBAwkNDQUgLCxMq56trS2NGjXixIkTryxLTEwMw4cPp2zZshgbG+Ph4UG7du04cuSIVrmzZ8/Stm1bbG1tMTExoVKlSsybN4/cXO2XGIlEgomJCeHh4VrpHTt21NxXu3btaN68uV55zp07h0Qi4erVqzr3V/g6f14967J69WqtdGdnZ9q1a8edO3e02o2NjWXQoEF4enpibGyMi4sLrVq14tw53cH17NmzyGQyWrcumH3p27dvid9bfrmOHTtqtff06VMGDBiAm5sbRkZGeHl5MXLkSOLj47XKNWnSBIlEwoYNG7TSFyxYgLe3t97n9TIvP4/8y8TEBIDc3FyCg4Pp3LmzVr3k5GQ8PDyYOHGiJm3r1q00adIEa2trLCwsqFy5MlOnTiUhIUHTl42NjV45JBIJO3bs0En/4osvkMlkOvcIMHnyZCQSCYMHD9ZKv379OhKJhLCwMK30rVu30qxZM2xtbTEzMyMgIID+/ftz7dq1V34e/xavMia0buLAn9ui2LTnOTdCUlmxIZJ/jr3g049dsTSXFVu/dlVrala2ZtGqCPYeecGNu6nMXxbO5ZvJfPFpGb1Lu50djBjQowy/rNT1YpVGuSqWNaSCjyHrD2Rw6rqC0Igc/tqfwd0n2XRuaoakmOXr9Ssb4+5kwLId6Vy8m0VIWA6/b0/jeUIunZuaacoZyKB2BSMu3s1i56lM7ofncPV+Nr9uSUUmk1A7SL9RmhkeyUHHWpz/4DPuTZhf7DN5GY/+XbGqGMDVT0YRtX43L46c5Wr3EaSHhhE4S/tFrvxP35AeGsbV7iN4ceQsUet3c+2TUVhVDKBMvy46bZ+5dpuLt0IY278nnZo3pGZQAN990Yvalcrzy9/byFUqS5TP18ONSn5ltS4DA+3vfenGXYRFxvD75DF0a92U6hX8aVSzCkM/+Rh/rzI6bd65dpL7N8/RdcBE6rfohl/F2vQYNJmAyvXY9dd8lEpdYzaf6sGt6dR3HNWDW1OuQi2q1P6AL8b9irWdE+cOb9Eq23XARD7o0J+KNZrgF1SLhq160HPQFFKT47l1+ZhO25cuXeTatasMGTKcNm0/onKVqowY+RXVqlVn5cplOr9P+sjNzWXBz3Np3eZDypTx0Fvmz7Wrefo0gtmz59OufUcqVapMnbr16NtvAGXL+uqtUxp1zKFlIxya1efumKk8XbWJhFMXuTNiEi+OniFg2lgoZgbef+oYUu+Ecu3T4bw4eJLoLfu4/PFADMzM8JswXFPOulYVXDq05MHUBTyev4z44+d4NHsJD2f+ilPbZtg3DdZp27RSDUwrViP+r6WknjiA/N4tXqxZTObta9h161fswa+W9T9AlZvL84XTyLh+AfndGySsW0bG7atY1v+goGBODorH93UuYx9/lAo5aXqMuQL9Gkqbth9SpUoVRowcladfy19Dv+bTpk1bPMro/m0B/Ll2DU+fPuWn2XNp374DlSpVpm7devTr15+yZcvqrVMa9Qvg1tVThNw8T8+B39GoZRcCKtbisy9/oHzlumz982eUxTyzmvVb0a3fN9Ss3wr/oJpUq9OMoeMXYWPnxKlDW3XKGxkZU9a/stbl4u7zWs/irSKRvL3rPeGdGVrR0dGaa8GCBVhZWWmlLVy4kD179lC3bl0UCgV///03ISEh/Pnnn1hbW/P9999rtXf48GGio6M5ceIEVlZWtG3blidPnpQoR1hYGDVq1ODo0aPMnj2bW7dusX//fpo2bcrQoQWzTtu3b6dx48aUKVOGY8eOce/ePUaOHMn06dPp0aMHKpVKq12JRMKkSZOK7HfAgAEcPXpUxxgDWLlyJVWrVqV69eo691f4qlGjhiY///lFRUWxd+9e0tPT+fDDD8kqNDPbuXNnbty4wZo1awgNDWXXrl00adJEYzS8LMPw4cM5ffo0ERHql8eFCxdq9Q+watUqnbSXefz4MTVr1iQ0NJT169fz8OFDli5dypEjR6hXr55O/yYmJkycOJHsbN1ZolflZX2Kjo7WPGuZTMaaNWvYv38/f//9t6bO8OHDsbOz03xvEyZMoHv37tSqVYt//vmH27dvM2/ePG7cuMGff/75r+TKyMhg48aNjB07lhUrVugtY2JiwooVKzSTCUUxbtw4unfvTtWqVdm1axd37tzhjz/+wNfXl+++++6Vn8e/pX5NW6RSCfuPv9BK33/iBSbGMmpVsS6ippoGtWzIyMzlxHnt7//AiXgc7IwILGeuU+ergV5cuZXCmctJ74VcVf0NkStUXLmn7SE5e1OBraUUH7eiFxVU9TciJj6Xx1EFniulCi7cycLHzQAbC4kmTaWCTIX2GCTPUqFUqsjJ0U5/Ezh3aE7avccknb+uSVPl5hK5bhe2tatg7KZedmfs5oRNrcpE/r0TVaGXi8Rz10i7/wSXDrqTTScuXcfMxJgP6lbXSv+oST3iEpO586Dkcb0k5Iosdh09S7O61XF3dnylOrcuHsXYxIyqdVtqpddp0pHkxFjCH9x6LRlkBoaYmlkhlZW8sMTCyg4AqVR3kuDc2TOYmprSoKH2EsTmLVqREB9P6P17Jba/edMGUlNT6d2nn958uVzOwQP/0KBBI1xcXUts703wtnTM+aPm5KSmE7P9gFZ65F/bMHFzxqZmZb3yGNrZYOFflheHtJfxyZ9GkXr3AU4ffqAx0mzrVAMg7qC24RK7/7hahvYtdNo3r14XpTyD9EuntdJTzxzBwNYe47L+euUCUOXmQE4OqmztcUaZkY6qhN9RA0cXTAIqkn7pNCp5pk7+ubNnMTU1paGOfrUgPj6e+/fvF9s+wOZNG/P0q6/efLlczoED+2nQoCGu77l+AVy/oB4rqtfT/p6Dm3UgOSGOJ/9irDAzt0QmK36SUFA6eWdLB11cXDT/t7a2RiKRaKVlZGTQr18/2rZty/bt2zXpPj4+1KlTh6SkJK327O3tcXFxwcXFhd9//50yZcpw8OBBBg0aVKwcQ4YMQSKRcPHiRczNC16ggoKC6N+/PwDp6ekMHDiQ9u3b88cff2jKfP755zg7O9O+fXs2bdpE9+7dNXnDhw9n3rx5fP3111SqVEmn348++ggnJydWr17NDz/8oHXfGzduZMYMbVdw/v0VReHn5+rqyldffUX79u25f/8+lSpVIikpidOnT3P8+HEaN24MgJeXF7Vr6y7DSU9PZ9OmTVy6dImYmBhWr17NpEmTsLa2xtpa+yXVxsamWLkAhg4dipGREQcPHsTU1BQAT09PqlWrhq+vLxMmTGDJkiWa8j179mT37t0sW7aMIUOGFNv2qzwPffj5+TFz5kyGDx9O06ZNuXTpEhs2bODixYsYGRlx8eJFZsyYwYIFCxg5cqSmnre3Ny1atNDRv1dl8+bNVKhQgfHjx+Pq6kpYWJiOpy4gIAAnJycmTpzIpk2b9LZz/vx5Zs+ezcKFCxkxYoQm3cfHh8aNG+s1/Ev6nl4Xbw8TEpOzSUzW3gP0JCIzL9+0+PplTImIlPOyg+JxRAYAPh6m3H2Qrklv09SBQF9zBozV9tSWZrncHQ2Ijs9F+ZKt8yxO/YPt7iArcg+Vu6OMB091X5Ly67o6yEhKy0GphBNXFdSvbExIWDb3w7MxN5XSsZEpmQoVp67rX3bzX7AM8iPhtO7egNRb6pcuywp+KKJisQxSvxym3NJ9GUu9dR/b4Oo66Y+eRuHt7oLBSy8Vfp7umvzKAfo9KPmMnv0bSSmpWJiZUr2CP190+whfj4I9HiGPw8lUKPB0ceSn5es4dO4ymfIsynm5M7DLRzSorjtmRz99gLN7WWQvGUZunv6afJ+AqsXKpVQqUamUpCUncObwZuKiw2j/6Vd6y+bm5pCbm0Ns5BO2rfkJJ1dvqtTRfakLDw+jjIenzkuYt4+PJr98haAiZYqICGfjhnV8N/EHzfj8Mg8fPkAul+Pm7s7iXxdx8uRxFHI53t4+fNqrN7Vq1yn2vv8Nb0vHLCv4kRb6SOulGSD1tnpiy6KCH0kXr+u0JTU0BECpZ1mpMisLA3MzzMp6kvEwDKmR/rL5S8wsKwbotGHo7kV21DNeHniynqonFozKeKF4pN9oTj2+H/M6jbD/5AuS9m5GpVBgVrUW5tXrkrC1+ElBy4bNkUilpJ48pDc/PDwMDw8PHf3yKaRfFSpUKLL9iIhwNmxYz4SJ3xejXw8L6dcvnDh5opB+9aL2e6RfAFFPH+FSxkdnrHD38svLf4hvYNVi5csfK1KTEzh1aAvPo8P5uNdInXJxz58xum8j5Bnp2Dm6UrN+K9p2HoiR8X9bsfLGEHu0Su8erQMHDvDixQu++eYbvflFLdcCMDNTL6spySOSkJDA/v37mT59upaR9XIfBw8eJD4+nq+//lqnTLt27fD392f9+vVahlZwcDD3799n/Pjx7NmzR6eegYEBvXv31hgx+cvuNm/eTFZWFp9++mmxshdHUlIS69atA8Aw78fBwsICCwsLduzYQd26dTE2LnqPy8aNGwkICCAgIIBevXoxfPhwvv/+e42Mr0NCQgIHDhxg+vTpOoOsi4sLn376KRs3buS3337TtG9lZcV3333H1KlT6dOnj97v5k0wfPhwtm/fTu/evbl16xaTJk2iatWqAPz9999YWFgUaegVp3/FsWLFCnr16oW1tTVt27Zl1apVTJkyRafcrFmzqFWrFpcuXaJWLd0AAOvXry9Wvn/zXb0uVhYGpKbpGglyhZKsbCVWFsUPL1aWBkTH6hoBqWm5mvx87G0NGfRpGZate0Z8YvF/16VJLnNTCS+SdJeJpGcqNflFYW4qIV2u643KyFSnWZgW/IBtOpJBpkLF4I8tkOatbYxPzmX++lTikkpeave6GNnbkJ2YrJOelZdmZG+j9a/+skkY5uUXJjk1HXdnB510Kwv1OJCclq6Tl4+9jRX9Pm5NxXJlMTcz4WFEJGt3HmTAxDn8MfVrzZLAuMQkANbuOoivpzs/DFEvi1639zBfz1nCgm+HUbeK9stjeloy9k66y57MLNSTT+mpuvf4Mr/PGsK9G2cAMDG1oM+ouQRVb6RTLiXpBd8PKtj74lWuMsMmrcDYxEynbGpKil4vk6Wlep9GSkpKkfIolUoW/jyP4OAG1KpV9N63+Hi1d3jL5o14e/swesxYpBIp27dtYeqUSUyeOp0aNWoWWf/f8LZ0zNDOhoywpzpl8+sb2dno5AEoYl+QlZCETR3tF2sDa0ssy/tp6mYAafceAWBTtzqZ4ZGasrZ5Xlp9fcgsLMmOe66TrkxPA0BazL4bxeNQYmZPxGnIOKw+UO/hUeXmkrh1LSkHdhRZD4kUi+BmZEU9RfEwRG+RlJRUXFx1J+ny9Su1BP1a8PPPBAfXf0X92oS3tzdjxnyNRCJh+7ZtTJ0ymSlTp703+gWQnpqEg7PuWGH+GmPFrzOGcff6WQBMzCz4/KvZVKqhPVaUK1+NmvVb4eLuQ1aWnDvXznBw5xoe3bvOV5OXIS0NRs57tMTvbVEKvgX9PHjwAIDAwMDXqpeens748eORyWQaz01RPHz4EJVKVWIf+Uu4ypcvrzc/MDBQ7zKvmTNnsn//fk6d0h8xqH///oSFhXH8+HFN2sqVK+nUqRO2L20YDQ4O1hhL+VfhtdHJyclYWFhgbm6Ora0tGzZsoH379pp7MzAwYPXq1axZswYbGxvq16/Pd999x82bN3XkyjcGAFq3bk1aWprOfrVX5cGDB6hUqiKfXfny5UlMTCQuLk4rfciQIZiYmDB//uutu84n/3kUvlq21F7yI5FIWLJkCUeOHMHZ2Zlvv/1WS+6yZctqDNXX7cvipY33+W2eP39eY5D36tWLVatWodSz56R69ep069ZNS6bChIaGUrZsWQwMCl7658+fr9V/cnLBYP4qzyMfhUJBSkqK1oUqC6kUzZVPcYvSVMXm5pUppkjhvFEDvHgUkcneo9rLASUSSqVcr9xWiYK8WlbbYBNa1DZh9+lM5q1LYfGWVJ4nKBnVwxIP57e03KSYG3vZo1pk2SLSi/tpLm4SoV7VIAZ370CDGpWoVt6Prq2a8PvkMUgk8Mem3QXd5rkYDQ0MWPDtMBrWqEyD6pWY/81QHGysWLFNf/S5Yt8ZXuF9onO/8Yyevp7Pxy4isEowaxZ8zZUzun2ZW9owZsYGRk5ZS48vJpORnsyvUweQnBinp9V//7x2bN9KVFQkAwcNLrIMFDwvAwNDJk+dTp069ahVuw6TJk/D1s6Ojev/Lrb+v+Zt6djrtFuoTsSydTg0rYfvN19i5GCHWVlPKi+bjdRM7T1Q5Y3lcYdOkf4onIApY7BvGoyBtSUOzRvg/8MolDk5mnJ6OilSruLyjLx8cR72HYqwh8QsnEr07Akk7duC7ce9sGnXvch6ppWqY2DnQOop/d6sfCTFaVgx+rV9+zaioiL54jX0a8rUH6lTpy61a9fhh8lTsLOzY8P6dcXW/9e81THs3z2zfLoPGMe3s/7iy3ELqFClHst//oZLp//RKtOh5zAat+pGQMVaVKrekB4DvuXjT0fw4O4Vblw6XmIfgv8NpdajVeRgVwTBwcFIpVIyMjJwdXVl9erVepfs6evjVWf/i5JJpVLpbaNChQr07t2bcePGcfbsWZ38wMBAgoODWblyJU2bNuXRo0ecOnWKgwcP6pTduHGjjrFS2JVvaWnJ1atXycnJ4cSJE8yZM4elS5dqle/cuTMffvghp06d4ty5c+zfv5/Zs2ezfPlyTZCO+/fvc/HiRbZt2waoDbTu3buzcuXKIoN3/BeK+g6MjY2ZOnUqw4YN48svv3ztdvOfR2H0LVtYuXIlZmZmPHnyhGfPnmmW8RX1nb5qX6BenliYFStW0KpVKxwc1LP1bdu2ZcCAARw+fFiv0fPjjz9Svnx5Dh48iJOTbqjpl+Xr378/7du358KFC/Tq1UtLX1/1eYB6gqCwl83Ly0snCMeYqfdJScvB10t3ht3EWIqRoVTjASqKlNQcvd4lSwu1Xud7pRrWtqVWFStGTb6PuZm20dChpRMdWhY8m9Iil6GBBFNjCemZKsxNdeez8tPyvVP6UNfV1UGzvLR8r5iLvZR2DU3ZdiyTQxcLor/dfpzN5M+t6drMjPnrU4u959clKz4JQz2z8ka26hnb7IRkTTmgiLI2mnKFsbY01+u1SslLszLX/W6Lw83JnioBvtx+WLC3y9pSPRFSyb8s5qYFS2xMjI2oVt6PE5dv6LRjbmGtdyY6Iy1Zk18STq5emv9XqtmUpTMHs2XFdKrVa601+yyTGeDpq17uVzawGuWr1mfK8DYc3rmCzn21J18sraxISdX9flPz0vI9Dy8TGxvL33+tpU/f/hgYGJKWpvacKHNzUSlVpKWlYWhoiLGxMZZWVgCUr1BBs2IE1PtJK1WszPnzur9v/5W3pWPZCfrbNcxvV4/nIp9Hs37DwNwM37GD8ZuoXrIdu/84kX9tx6NvV+RRao+UKjubK52/oPIfP1Frp3ovbk5aOg+mLsD3my+RR+keM5GblopMj9dKaq7W1XzPlj7sew0mNyWJ2F9nakK5y+/dAqUSmw49SDt/nBw93jLLhi1Q5WSTdlY3yEo+VlaWpKbqeq1eTb/+pG/ffhgYGGj0Kzc3F6WOfqnbKF+hvI5+VaxYifPn9UdD/C+8zTHM3NKGtLQknfR0zVhhVaJ8zoXGiiq1mvDLj0NZv3wmNYJbFeupqtPoQ7aunc+T0JtUq/NqEUffJiK8eyk2tPz91eti7927R7169Uosv3HjRipUqICNjQ329vav1Iefnx8SiYSQkBCdKHn6ZAkJCSE4WDda0L1794pcozxlyhT8/f31Rp8DdVCMYcOGsXjxYlatWoWXlxcffPCBTjkPDw/KlStXpIxSqVSTHxgYSExMDN27d+fkSe3NuCYmJrRo0YIWLVowadIkPv/8c3744QeNobVixQpycnK0zqxQqVQYGhqSmJio42kriXLlyiGRSLh7967eZ3zv3j1sbW01xkdhevXqxdy5c/nxxx9fOeJgPoWfR1GcO3eOn3/+mX/++YfZs2drjB6JRIK/vz+nT58mOzu7RK/Wq/SVm5vL2rVriYmJ0fJC5ebmsmLFCr2Glq+vLwMHDuTbb7/VCZzh5+enI5+NjQ02NjY8e/bsX8mYz/jx4xk9erRW2uBvbyCVFTyHp1FyKkSY0yzYHltrA639UD55e6DCnupurC7Mk6eZNA22QyrV3paQX/9JXn0fD1MMDKT8+qN+ryjA0r+ecjMktdTI9eEHjnz4Adx5koWvmyFSCVr7tNwd1YZZ5Iuijb7IuFzcHXWH6Py6UXl1yzgZIJVICIvWXi6pVMKz2Fz8Pd/8MJ96OxSrirqb8y3z0lLvPMj7NzQvPYC4/Sd1yubnF8bXw51DZy+Rk5urtU/r4dPIvHz9Z0kVhwqQFpqYKOepeyaPdlndlwNXTz+unvmH3Nwcrb0X0RHqe3X18NOpUxKevpUIuX6GtJQErGx0x8B8bOxdsLZ1JC46TCfP29ubkyeOk5ubqzX5FhamNiy9vLz1thkTE41CoeCP35fwx+9LdPJ7dOtE+w4f88WgLzX7cfSh4tUnpV6Ht6VjqXdCce3yIRKZTGuflkXeXpy0uw+KlEmVm8u9737iwfRfMPVyJzs+CcXzOGpuX0bGk6coogqMmYzHEZxv3hNjVycMba3JePIUQytLys+eQOLZyzptZ0WGY1GnIS8PPEZlvNX5z4oOXmTk6aMO/67S9pQpwh4gkcowdPXQMbSkltaYValJxvWLKItZyubl7VOEfoWp80vQr99/X8rvvy/Vye/erQsdOnTki0GD/0/pF4C7Zzkund6vM1ZEhqvPWnPzeLXf4sJ4+wVx5/oZ0lISsbIp+R1XGDilh1L7TbRs2RIHBwdmz56tN//lYAQeHh74+vq+spEFYGdnR6tWrVi8eDHp6bozqPl9tGzZEjs7O+bNm6dTZteuXTx48ICePXvq7cPDw4Nhw4bx3Xff6Q2D2q1bN2QyGevWrWPNmjX069fvjQwqX331FTdu3NAKJKKPChUqaO49JyeHtWvXMm/ePK5fv665bty4gZeXl1aEvlfF3t6eFi1a8Ntvv5GZqf2CGxMTw99//0337t313rNUKmXmzJksWbJEx6PyX8nMzKRPnz4MGjSI5s2bs3z5ci5dusTvv6sPUfzkk09IS0vjt9/0H/r3usEw9u3bR2pqKteuXdN6tps3b2bHjh06Ye7zmTRpEqGhoTqh4Hv27FmsfP8FY2NjrKystK6H4dmEPs7QXJlyJWevJKFUqmjZSPsFsWVje+SKXC7dKH4d+ulLiZiZymhUW9t4b9nIgRcJWdx7qNbLAydeMGbqfZ0rv40xU+9z8GR8qZNr3roUztxQYGIsoXqAkVZb9SoakZiq5EmU/kAYANdCs3B1kOHtWvByI5VAnSAjHkfmkJymttyS09QvV2VfimBoIANPFxmJqW9+j1bMzsNYlPfFpnZBhDaJTIb7J+1JvHAdRbR6xl4RFUvixRu4f9pOa22nTZ0qWASWJWaH7pKlJrWqkCFXcOzCNa30fSfO42hrTZDf64Uujop9wc37j6hYqJ6DrTWV/MpyM/QRaRkF45JckcW1kAdU9PPWaadyrQ9QyDO4ceGwVvrFkzuxtnXCy6/4FRQvo1KpeBRyGVNzS71nYxUmLiaCpPjnODh76uTVq1efzMxMzpzWXqJ+9PAh7Ozt8Q/QvzS+bFlfZsyao3P5lC2Ls7MzM2bN4aN27QGws7MnsHwFQu7eISOj4LdSLpdz+9ZNAgKLngT5t7wtHXu+5zAGluY4d9Ce3HL/pAPyqOckXdZdTv8yuekZpN19gOJ5HFZVKmDXuC7hS/UHnVBEx5J29wHKTDk+I/uTk5bOs7VbdMplXD2H1MQM8xrak7kW9ZuRkxiP4nHRUWhzkxIw9i6nEwLexFf93ecm6i5ttghuisTAsMRlg8H1gvP0Szsa4pHDh7G3tycgQDewB6j1a+asn3SufP2aOeunl/SrPCF37+rRr1sEvOYWklfhbY5hVWs3QyHP4Np57S0X54/vxtrOEZ9/MVaE3rmCmbkl5pbFe87PHd8F8Np9vDUk0rd3vSeUWo+Wubk5y5cvp2vXrrRv354RI0ZQrlw5Xrx4waZNm4iIiNB7DtHr8ttvvxEcHEzt2rWZOnUqlStXJicnh0OHDrFkyRJCQkIwNzfn999/p0ePHnzxxRcMGzYMKysrjhw5wtixY+nSpQvduhV9UN748eNZtmwZT5480QqYAeogFd27d+e7774jOTlZ41l6mfj4eGJitA9atbGxKfIsJCsrK423qmPHjiQkJNC1a1f69+9P5cqVsbS05PLly8yePZsOHToAsGfPHhITExkwYIBOdMEuXbqwYsUKhg0bVtIj1eHXX38lODiYVq1a8eOPP+Lj48OdO3cYO3Ys7u7uTJ8+vci6H374IXXq1OH333/H2dm5yHIvo1KpdJ4XgJOTE1KplG+//RalUslPP/0EqKMgzps3j9GjR9O6dWvq1KnDN998w5gxY4iMjOTjjz/Gzc1NE5q+QYMGWtEIS2LFihV8+KH6DJLCBAUFMWrUKP766y+97Tk7OzN69GjmzJmjlV6vXj3GjBnDmDFjCA8Pp1OnTnh4eBAdHc2KFSuQSCRaywtKeh7/hvBncvYff0GfLm4olSruP06nRiVrPmzmyKpNkaSmF0ws9Orkymed3Bg7/T43Q9RLSC7dSOHyzWRGDPDCzExGZIyCZsF21K5qzYxfH2s8QM9fZPH8hf4DZF8kZHMjRHvZVGmRKzRCXfDuk2w+aWWGibGE2ET1gcUVfY1YsStNs7z/szbm1KtkxMSlySSkqA2jszcVNKluzKCOFmw7kUlquvrAYhc7GT9vKLjnh09zeBKVw0cNTDEylPDgaTamxhKa1jDB0UbGyt1FLzlybNUImbkpBpbqQBMW5cvh0qkVALH/nECZKafyH9Nx/6wjxwNakBkRBcCzVVvwHvwJ1dcv5N6EeShi4/Ee/AnmAT5caKUdIvze+LnU2b+SGhsWErZ0HcZO9gROH0PK7fs8W617LkxwtYrUrlSe2SvWk54pp4yLIwfPXObcjbtMGdYPWZ6+/rj0T/adPM/WhVNxdVRPsA37cQFVy/vh5+mOuakJDyOi+Gv3QZBIGNStnVY/I3p1Ysi0BYyc+Qu927cEiYR1ew6TlJLGoK/a68hVoVpDAirXY/Pyacgz03B09uTK2X2EXD/DZ8NmakKvr1s6iUsndvH9on3YOaq9b8vmDMfdKwB3r0DMLa1JTozj4vGdPLx7mS79J2hmvSPD77N97Ryq1mmBvVMZJFIJ0REPOL7vT8wtbWjWrq+OXDVr1aZater8tvgXMjIzcHN148SJY1y5cpkxY8dpvBALF8zjyOFDLF+xBidn57xzAavotGdurt7/+3LegAEDGf/tN3w/8Tu6dOmWF6xgCykpKfT6rI9OO/mUNh17cegUL46eocLPkzCwtCDjcTiuXT7EsUUjbnw+VuNNqvjrj7h90oGTVVohf6qWya5BLayqVyLtzn2QSLCuURmfUQN4cfg04b9rT0T6jByAIvYF8qdRGDk54PJxa5w/+oCbX4zTvMQXJvPWVTJvX8P+sy+RmpqRHRuNeZ1GmFWqQewf8zTeKod+w7EIbsazb78gJ169Zy/l4E7sPx2E88iJpB4/gDJLgWmFyli37EjmnetkPQ3T6c+yYQty4uPIvH1NJ68wNWvVolq16izO0y9XVzdOnDjOlSuX+XrsNxr9WrBgPkcOH2bFilXF6peFuTnKIvVrHN9PnECXLt1AImH7tq2kpKTw2We9i5SvtOkXQMXqDShfuS7rlk0nMyMNJ1dPLp3+hzvXz9BvxHSkec9s7W+TOX98N9MW78Y+b6z4bdYoynj74+EdoBkrzh3bxYO7V+jx+XjNWPHg7lX+2bacqrWb4eDsTk52Frevneb0oW0EVKxN5ZrFxygQ/O8otYYWQIcOHTh79iwzZ87kk08+ISUlBQ8PD5o1a8aPP/74Rvrw8fHh6tWrTJ8+nTFjxhAdHY2joyM1atTQCjnepUsXjh07xowZM2jUqBGZmZmUK1eOCRMmMGrUqGK9UHZ2dowbN07nbKN8BgwYoFk+5umpO2MJ6N0ftX79enr06FFkvyNHjmTRokVs3ryZDh06UKdOHX7++WcePXpEdnY2Hh4eDBw4UCPXihUraN68uY6RBer9XTNmzODq1ata53u9Cn5+fly+fJnJkyfTvXt34uPjcXFxoWPHjvzwww/Y2dkVW/+nn37Su2SzOFJSUvSexxEdHc39+/dZvHgxx48f14poOHDgQLZs2aJZQvjTTz9Ro0YNFi9ezNKlS1Eqlfj6+tKlSxf69Cn6xeJlnj9/zt69ezWRIAsjkUjo1KkTK1asKNJwGzt2LEuWLEEul2ulz507l9q1a7NkyRJWrlxJRkYGzs7ONGrUiHPnzmFlVbAOvLjn8V/Cvi9cGcGLhGw6tnLC1saQ53FZ/Lb2KTsOaL9ISCUSZDKJzgbhyfMf0b+7O326uGFpYcDTKDk/LnrE8XOJ/1qm0ibX0m2pdGhsRvuGppiZSIhJyGXZzjQuhxQYaVIpyKQSrT3SObnw8/pUOjc1o0cLM4wMJDyLzWXRplQePC3whKmABRtTaVXbhOqBRrSobYIiW0X0C3XZO4+LjtJY8dcfMPMuiI7l1rUNbl3bAHC0XDN1xDSZFKmBgdYGbmVWNudb9aX8rLEELZiIzMyUlBshXPxoIAmnLmn1kXDyIpfafYH/5BHU2rGU3IxMYvcdJ2TcbE2465f5acwXLNmwiz827yYlLQMvN2emjehPy+CCCJxKpZJcpVJrL7qvhzuHz13h7z2HUWRlYWdlSY2gAAZ0aounm/ZETeUAX36dOJLfN+5i0q+r1M+jnA9LJn1FJX/9B6QOGLOAPRsW8c+mxaSnJePs5kOfEbOpXr9NwfehzEWpzNXaI1nWvxrXLxzi1P71yDPTMTW3xKNsEF+MW6wVddDS2h5rW0eO7VlDStILcnNzsLF3Jqh6Y1p0HIitg/6/1e8m/sDaNav4+8+1pKamUsbDg7HjxtO4cUHkQqVSqQ4Z/QrBYPRRvkIQ02f+xJ9rVzN3ziwAAgLLM3PWHMqXLzq8d2nUsWufjsBv0kjKTRiOka01aaGPud5vDDFbCwKTSPJkKvw3qczKxqVDS8zHDkZqbETGo3AeTv+F8KV/6YRll5oY4zvuS0zcXFBmykm6fIOLbfuQeE43pHg+zxfPxLZTL2w6foLM3JKsmGfELp1D+sVC3kqJFIlMRuEQKClH9pKTmIB1y/Y49BuGxNCInBexJO3aQPLBnTr9GPsGYuTmQeLO9cVH68ljwsTvWbtmNX/9uZbU1DQ8PMrwzbhvady4ScGz+Y/6VaFCBWbMnMmfa9cwZ456AjQwsDwzZ81+7/QLYNDY+exc/wu7Ny4hIy0ZZ3cfBoyaRa0GrQtk0DNW+AZW4er5wxzfvwF5hnqs8PKtwNDxi7SiDlrbOiCVStm35Q/SUpOQSCQ4uXjSrvuXNG/fu3REHAT1Moz/z5GoXjfqhEAg+P+O5j119xQIise3iv6X9XdN++9L3vP6Lqh/UXefUGngvKTBuxZBL76W+g+If9eEBuqPZloakOkJTFMaCOjy+vv7/hfkTlj4rkXQy/3A1iUXegeYXb3+rkXQS9NKxZ8d+TbJXDfzrbVt+sn4t9b2m6RUe7QEAoFAIBAIBALB+4fkPdpL9bb4P/0EIiIi9J5vlH9FRES8axEF/4KgoKAiv9N/E7BDIBAIBAKBQPCGkUre3vWe8H/ao+Xm5sb169eLzRe8f+zbt4/sbP3rol8nYIZAIBAIBAKBQPC2+D9taBkYGLzy2UGC9wcvL6+SCwkEAoFAIBAI3h1i6eD/7aWDAoFAIBAIBAKBQPAu+D/t0RIIBAKBQCAQCATvgGKOPvr/BeHREggEAoFAIBAIBII3jPBoCQQCgUAgEAgEgjdLaTk4+R0inoBAIBAIBAKBQCAQvGGER0sgEAgEAoFAIBC8WUTUQWFoCQQCgUAgEAgEgjfMe3Sw8NtCmJoCgUAgEAgEAoFA8IYRHi2BQFAiKpXyXYvw3hETHveuRdBL/YtL3rUIejlT+8t3LYJeHm67965F0Eud2z+9axH04nRh8bsWoUgMFGnvWgS9HDX66F2LoJcGm0a8axH00qCU6tjOBNN3LULpQywdFB4tgUAgEAgEAoFAIHjTCI+WQCAQCAQCgUAgeLOIA4uFR0sgEAgEAoFAIBAI3jTCoyUQCAQCgUAgEAjeLOLAYuHREggEAoFAIBAIBII3jfBoCQQCgUAgEAgEgjeL2KMlPFoCgUAgEAgEAoFA8KYRHi2BQCAQCAQCgUDwZhHnaAlDSyAQCAQCgUAgELxhRDAMsXRQIBAIBAKBQCAQCN40wqMlEAj+NTKZhE86utK6iSN2NobExCrYeTCWHQeev1J9E2Mp/buXoXFdO6wsDIiIymTDzmiOnUsott7PPwRSubwVOw4855dV4aVSrlU7knTlkkKXNvZ8UM8aOysZz+Oz2Xciib3Hdcvql0vCp+0daFDdCgtzKc9isth2MIFTl1N1ypb1MKZvJ0f8vU3JVaq4dT+DVdviNPkZcjlLN+7iyPmrpKSl4+XmQu8OLWkZXKtYGfYcP8e0pWv15u1bOgt7G2uttEy5grW7DnLo7GViXiRgamJMOU93xg/8FE9XJ502ZBbm+E0YglWVQKyqVsDY0Y7Qqb/wYNqvr/KIMHK0I3DWWJzbNkVmZkLKzXvcn7SA+GPndcraN6tHwJSRWFUOJDdDzvN9x7j37Ryy4vR/z9mKdC7sX8jDG/+gyEjGxqks1ZsOxK/ah8XK9OjWQR7d2E/s09ukJz/HzNIeF+/q1Go5DBtHb62yYXeP8fDGfl5E3iUp9glKZQ5D5t4r/qYNjTFt3A6jwOpITM3JjY9Bfu4g2SFXiq1m8ckoDL38i8xPWvQtqvQU9QeZAcY1m2BcqS5Sa3tU2QpyY56SeeYfciMf662v1rE9HD5/lZT0dLzcnOnTviUtg2sWK9eeE+eYuvQvvXn7lszAQZ+O7T7EwbNXNDrm5+nG+M8/0atjGXIFi7ce4NClm6SkZeLt6ki/D5vQqm7VYuXadeoyk1ds1pt3cMFEHGwsNZ+zc3JYvusoe89eJTYxBQcbS9rUrcrADs0xMTLU24ZCns7+TYu4cf4AGenJOLn50LTd51QLblusXKG3znFs9wqeP3tIeloSJmaWuJQpR5MP+1G+WiOtsnevHufG+QNEhocQG/UEZW4Oc9fdKbb90qpfUHp1LEuezvGdCwi5/A+Z6cnYu5QluPUXBNUufqy4d/UgIVf2Ex12i9Sk55hbOVDGtxqN2g3Hztlbtx9FBuf2L+PupX0kJ0RiZGyOk7s/bT+bprf8/xwRDEMYWm+Svn37smbNGgAMDAyws7OjcuXK9OzZk759+yLNc6F6e3szatQoRo0aBcC1a9f4/vvvuXjxIikpKbi4uFCnTh0WL17Mr7/+ypQpU4rt98mTJ3h7exeZP3nyZE0bEokEFxcXmjZtyqxZs/Dw8NCUa9KkCSdOnNCpP2jQIJYuXaqpD3Du3Dnq1q2rKaNQKHBzcyMhIYFjx47RpEkTTd6ePXuYO3cuV65cITc3l6CgIIYOHUrfvn115CvuHlevXq23XEBAAPfuFf0iEhYWho+PT7Ht//DDD0yePJljx44xZ84cLly4QGZmJt7e3rRp04bRo0fj7u7O8ePHadq0qaaeg4MDNWvWZNasWVSpUqXYPkD7GRsZGeHl5UXfvn0ZN24cMpkMgNzcXBYtWsSqVasIDQ3FxMSEevXqMXHiROrXr69pa/Xq1fTr10/z2cnJidq1azNr1iyCgoI031VR9OnTh9WrV5coc3GM7O9Fi4YOrNr0jPuP06lZ2ZqhfTwxM5Wybkd0ifWnjPEjoKw5y9c/5Vm0nGb17Zk4shwS6SOOnonXW6dDKyfcnE3eS7kG93SmSR0r1u1+wYMwOdUqmPN5VydMTaRs2V+8EQfw7Rfu+HmbsHZ7HFGxWTSqZcXXA9yQSKI4eanA2HJ3NmL6Vx48eaZgzvIoDA0lfNLOgZljPJA8jUSVk824eX8Q8jiMIT0/xtPViYNnLvH9opWolCpaNahdoizfD+6Nl7uzVpq1hYXW5wy5nCFTF/AiMYneHVpRztOdtIxMboU+Rp6VpbddI3sbPD/vRsrNezzfdRjPAd1KlCUfqZEhdQ6uxtDaijujp5MVG4/Xl59Se+9yLrTqR8KpS5qydg1rUXvPMmL3neBypyEYOdkTOONr6hxczZk6nVFmZeu0/8+a4cQ9vU3dtqOxcfQm9NpeDv09BpVKiX/1dkXKde3ocsysHKjxwSCs7D1IS4rh6pHf2bygE52Hb8TOxU9T9vHtwzwPv46DewVkBkbEPSvhJRiw6PwFMhcvMo/vQJkQi1FQTSw6DiBNIiH77uUi62Uc2IDEWFtnJYZGWHQfRm5MRMFLMGDW5lOMgmohP3eAnPD7SEzMManXEstPvyL1z7nkRutOeIybv4y7j8MZ2qMDnq7OHDhziYm/rEKpUtG6fvEGPcCkwb3wcnPRSrPRo2NfTlvIi8RkerdviV+ejt18ULSOff3Ln9x58ozhXVvj5eLI/nPXGL90PUqVijb1qpUo1+QBXfF2ddRKs7Yw0/o8fsl6zty8x8AOzQnyKcPNh+Es332UR5HPWTCqr9521/w8iqePbtO251c4unhx7exe/v51LCqVkur1PypSnoy0JFzK+FKnaWcsbRzISEvm3OGNrJjzJT2HzKJGgwLdvH35COEPb+DuXR4DAyOePXl/9QtKr45tWTKc6PBbNP14DHbO3ty5uIcdy0ejUimpWKfoseLc/mWYWztQv+1gbBw8SEmM5uw/v7Pix4/pO34Tjm4FY0WWPJ2/5vUmNTmW4NZf4OQegCIzlWePr5GdJS/x3gX/G4Sh9YZp3bo1q1atIjc3l+fPn7N//35GjhzJli1b2LVrFwYG2o88NjaW5s2b065dOw4cOICNjQ1Pnjxh165dZGRk8PXXXzN48GBN+Vq1avHFF18wcOBATZqjo/aAr4+goCAOHz6MUqnk0aNHDB06lG7dunHu3DmtcgMHDmTq1KlaaWZm2j8gHh4erFq1SsvQ2r59OxYWFiQkaL8s/vLLL4waNYpx48bx22+/YWRkxM6dOxk8eDC3b99m7ty5r3WP+fdRmJef6ct4eHgQHV3wcj137lz279+v1Y6FhQW///47Q4YMoU+fPmzduhVvb28iIiJYu3Yt8+bNY/78+Zry9+/fx8rKioiICEaMGEHr1q25d+8e1tbas2D6yH/GcrmcPXv2MGLECGQyGePGjUOlUtGjRw8OHz7MnDlz+OCDD0hJSWHx4sU0adKEzZs307FjR01bVlZW3L9/H5VKRWRkJN988w0ffvghoaGhWve8ceNGJk2axP379zVppqamJcpaHF5lTGnT1JGVG5+xaU8MADfupmJlacCnH7ux+1Asqem5RdavXdWampWt+XHRQ46dVevN9bupODsaM+hTD46fjUep0q7j7GjE5z08mPXbY6aO8dPTaumVy8PViObB1vy16wXbDyUCcPtBJpbmMrq1sWf/ySTSMpRFylUjyJxqFcyZuyJK48G6FZqJo50hfTs5cvpyqkauT9rZk52jYtpvkWTK1W0+ipCzZEpZcp08ObJ3JxdvhTB1eH9a5b2M1AwKIDougV/+3kbz4JrISlhb7+vhRnlfr2LLLN24i7DIGP6ePQF354JxqlHNoiclMsMjOeiolsnQ3va1DC2P/l2xqhjAmYbdSTp/HYD44xdoeGUngbPGcrZ+QVvlf/qG9NAwrnYfgSpXrQ+ZYc8IPrmBMv26EPH7eq22w0NO8Cz0LC0+nYtfNfVLr3u5uqQmRnJuzxzKVW2LVCrTK1fb/ksws7TXSitTrg5/zmjOjZNraNrtR0160y7TkOQ9+5PbppZoaBn4BmHoU560nSs1L705EaFIre0xa9aJ5JAroFLprauMj9FJM6pUB4nMAMX1swWJMgOMgmqSdfcS8pO7Nck5zx5hM2IWRkG1yXzpRfjMtdtcuHWPacP60aq+2rtQM8ifmBcJ/PL3dlrUq1GijpUt40aFEnVsD2GRMaz7aQLuzg6a9EY1K+stf/rGPc7fecCMwT1pnefBqlXel+j4JBZs3EfLOlVKlKtcGRcq+JQpMv/mw3COXrnN6B4f0qu12qNUJ8gPmUzGr1v2c/52KHUrant6Qq6dJPTWWT4dNptqwWqvR7mgOiS+iGbPunlUrdemSP2qWq8NVeu10UqrUK0xM0a14vzRzVqGVpfPp2gmfbet+rFEQ6u06heUXh17eOsET0LO0PHzeQTVVo8V3oF1SY6P4sjW2VSoVfRY0W3YUsyttMcK78C6/Dr+Ay4cXs1Hvadr0o/vXMCLmMcMnLQLW8eCSXP/qh8Uez//U0QwDLFH601jbGyMi4sL7u7uVK9ene+++46dO3fyzz//6PUenD17lpSUFJYvX061atXw8fGhWbNmLFiwAE9PTywsLHBxcdFcMpkMS0tLnbSSMDAwwMXFBTc3Nxo2bMjAgQM5f/48KSkpWuXMzMy02nZxccHKykqrTJ8+fdiwYQOZmZmatJUrV9KnTx+tck+fPmXMmDGMGjWKGTNmUKFCBcqVK8eYMWOYM2cO8+bN48KFC691j/n3UfhycHCgOGQymVZ5CwsLnXaSkpIYMWIEI0aMYOXKlTRp0gRvb28aNWrE8uXLmTRpklabTk5OuLi4ULt2bebNm0dMTAznz+suTdJH/jP29vZm2LBhfPDBB+zYsQOATZs2sWXLFtauXcvnn3+Oj48PVapU4Y8//qB9+/Z8/vnnpKena9rK91C6urpSs2ZNvvrqK8LDw7l//77W/VlbW2vKFk77L9SvaYNUKmH/8Rda6QeOv8DEWEatqjbF1m9Qy5aMzFxOnNc2zvcfj8PBzohAPwudOqMH+nDlVjJnLiW+d3LVrWKBVCrhyLlkrfQj55IxNpJSPci8WLnqVrUgU67kzFXtZYJHziVjb2OIv4965lgqhVqVLDh3LU1jZAHEJeRwOzQDQ2tHTly6jpmJMR/Ura7V1kdN6hGXmMydB0+KleVVkCuy2HX0LM3qVtcyst4mzh2ak3bvscbIAlDl5hK5bhe2tatg7KZe4mPs5oRNrcpE/r1TY2QBJJ67Rtr9J7h0aK7T9uPbhzE0NsO3cmut9PK1OpGeEsvziBtFyvWykQVgbu2MhbUzaUnaHlbJa24eN/KvgkohJzvkqla64uY5pJY2yNyK9+brtFc5GJVCTlbhZWEqJahUqBSZWmVVWXJUSiXk6Hr/jl+6kadj2h6ijxrn6djDsNeSSx9yRRY7j53hg7rVtV6Ai+PYlduYmRjRvFYlrfT2DWsSl5TC7UcR/1muGw/URkH9yoFa6Q2rqD8fuXxbp87ty4cxNjGjcp1WWum1GnckJTGWiIc3X0sGmYEhJmaWOi/00v8j+gWlV8fuXzuEkbEZ5WtojxVV6nciLSmWqCdFjxUvG1kAljbOWNk6k5pQYLhmKzK5fnoL5Wu01jKyBKUPYWj9D2jWrBlVqlRh27ZtOnkuLi7k5OSwfft2VEXMCr1pYmJi2LZtGzKZ7JWMtJepUaMGPj4+bN26FVAbVCdPnuSzzz7TKrdlyxays7P5+uuvddoYNGgQFhYWrF+/XifvXbB582aysrL45ptv9Obb2NgUWTffM5Sdrf/HoCRMTU01ddetW4e/vz/t2ukuLRgzZgzx8fEcOnRIbztJSUmsW7cOAEND/XsA3iQ+HmYkJmeTmKx9348jMvLyi/eY+XiYERGZifIlJ87jiEy99ds2dSTQ11zvnqz3QS5PN2OSUnNIStH2poVFKjT5JdV/GqPQkevl+q6OhhgbSTXpL5eVGpvy6GkU3u4uGLz09+/n6Q7Ao6dRxcoCMHr2b9TrOYQWA8Ywbt7vPHoaqZUf8jicTIUCTxdHflq+juYDRlP/02H0+W4mp6/eKrH9f4NlkB8pt+7rpKfmpVlW8Msrp/YmFFU2P78wCTGh2Dr5IpVpe9DtXQPy8h+8lqzJ8U9JTYzCzqXca9V7GZmjG7nxMeqX1ULkxkbm5bu+cltSW0cMPf3ICrkM2YX0R6lEcfUkxhXrYuhXBYxMkFrbYd7mU1SKTBQ3zui09ehZtF4dK+fpps5/FR2bs4S6nwyj+edj+Wb+Hzp1Qp5EkKnIwsPFkVkr1vPB518T3GsEvb/7idNXdY0ZgIeRz/FxddLVfQ8XTX5JjPx5FTX7fUuToZMZ88taHj7T9txk5xnvRobaupL/+cEz3eXLMU8f4uRWFtlL+uXqGZCXX7J+KZVKcnNzSE6M5cCWX3kRHUbjD/uWWK84Sqt+QenVsbioB9i76o4VTmXU32Vs5OuNFYlxT0mOj8LBrWCsiI64Q7YiAzsnL/75+wfmjarFzC8rsmJ6Jx7cPP5a7b9VJJK3d70niKWD/yMCAwO5eVN3Rqpu3bp89913fPLJJwwePJjatWvTrFkzevfujbOzs56W/h23bt3CwsICpVKp8USNGDECc3PtWfTffvuN5cuXa6UtXrxYx1vVr18/Vq5cSa9evVi1ahVt27bVWcIYGhqKtbU1rq66A7GRkRFly5YlNDT0X91HYXr06KEj8+vy4MEDrKys9MpaHPHx8UyZMgVLS0tq1y55X0thlEolBw8e5MCBA5r9eqGhoZQvX15v+fz0ws8sOTkZCwsLVCoVGRlqQ6J9+/YEBgbqbeNNYmVpQGpajk66XKEkK1uJlUXxw4uVpQFRz3XXkee3Wbi+g60hg3p58Me6p8QnFm/Qlla5LM1lpOlZsqjIUpGdrcTSvPhJD0tzGc9f6PaR32Z+/fx/0zJ0+0pNz0UikZCcloG7k+7MqZWFejxITkvXycvH3saKfh+3pmK5spibmfAwIpK1Ow8yYOIc/pj6Nf5e6iVVcYlJAKzddRBfT3d+GNIXiUTCur2H+XrOEhZ8O4y6VSoUe8+vi5G9DdmJyTrpWXlpRvY2Wv/qL5uEYV5+YeTpSVjZ684cG5tZa/JfFWVuDsc2TcDQ2IzKjfq+cj19SEzNUSa90ElXZaq/Q6mprge2KIyrBAOguHFWJy/z8BZUikzMOw3UeN1yk+NJW7cQZWKcTvnk1HS9Omadr2OpxeiYtRX9Oramop835qYmPHoaxZqdB+n//RyWTRlToGMJSQCs3XWIcp5uTP6yDxKJhL/3HmHM3KUsGDeEei/pWHJaBu6Odjp9WpmbafKLlsuSAe2aUcnXE3NTYx4+jWH1vuP0mbaYVRO+xD/vBb9snuf0+oMwrb6uhYYV2Ud6WhL2TrrLEc3MrfPydXX1ZVbMHsz9m2qjxMTUgl4j5lGhWuMS6xVHadUvKL06lpmWhI2j7ndpkjdWZL7mWLF3zXcYGZtRp3lfTXpqonpC4Nz+ZTi6+9Ou309IJFIuHFrJpsWD6TFiGb5BDV+5H8HbQxha/yNUKlWRwQmmT5/O6NGjOXr0KOfPn2fp0qXMmDGDkydPUqlSJb11XpeAgAB27dqFQqFg586dbN68menTp+uU+/TTT5kwYYJWmpOTbkSdXr168e233/L48WNWr17NokWLXlum4p5JUeTfR2EsLS2LKP32ZClTRj2Ipqen4+fnx+bNm/U+J33kG7NZeZtoP/vsM3744YdX7ruwnJaWlly9epWcnBxOnDjBnDlzNIFL/i0KhQKF4iVviCoLqcxI8zHfq1KcD/a/OmgL1x/1uTePwjPYe0T7B1ci0T6mo9TLVaxgr9B3cYVeyirpPovT9uL+FupVDaJe1SDN52rl/ahfrRKffjONPzbtZu7YL9X9520YMzQwYMG3wzA3VS9trBkUQJdRk1ixbd8bN7TUHRd94zqrBooqW0S6pJin9qrjh0ql4timCUQ/uULr3ouwtHm9yR39jRbf3yshkWJUqS65cVHkRoXpZJsEt8akdnPkp/eS8/QhEiMTjGs2waLncNI2/ELu82e6TRbzTF5Hx6qX96N+tYp88s10/ti8h7lfq/f0KlWFdGzc0EI65k/nryazcvs/Oi/B6r6L7LrYv4v6lQOoXzlA87lGQFkaVgmk2/c/s2T7IX4e2UdTzsPZnkWb/sHeyoIgHw9uPopg8Zb9yKTSou+92OdVjGB5dOwzgcyMFFKT4rhyeg9/LRpDjy9naPZ8/WtKqX5B6dWx4jSpuHGkMCqVij1rJxDx8AqdBy/Cys61UJ76R0VmYEiPkcswNlEbvN4Bdfjt+5ac3vNb6TC0xDlawtD6XxESElJs5Dt7e3u6du1K165dmTlzJtWqVWPu3LmaKIb/FSMjI8qVU7udg4KCePDgAV9++SV//vmnVjlra2tNueKwt7fno48+YsCAAcjlctq0aUNqqvbeEX9/f5KTk4mKisLNzU0rLysri8ePH9OsWbN/fR9vknxZo6OjX8mrderUKaysrHB0dNTZw1YS+cassbExbm5uWss3/f39uXv3rt56ISEhAPj5FQRbkEqlmucRGBhITEwM3bt35+TJk68lU2FmzpypFd3Ry8uLsLAwrTKjp4aQkpqDr5cZL2NiLMXIUEpquq5XqTApqTl6vUuWeWn59RvVsaVWFWtGTg7B3Ezb69OhpTMdWhZ4fkurXBPmR5CanouPh+7yQGMjCYaGUlL1eKAKk5qeq9frZZGXll8/9SUPl9Y9mMtQqVRYW5jp9Vql5KXlz+6/Km5O9lQJ8OX2w4K9XdaW6h/+Sv5lNS8nACbGRlQr78eJy0XvU/i3ZMUnYWhno5NuZKueSc5OSNaUA4ooa6MpVxgTcxvkGUk66YoMddl8z1ZxqFQqjm2eSOjV3TTrMQufiv9907oqMx2Jqe7+vvw0lbzoWf3CGPoGIbWwJuP8QZ08qb0LJo0+IvPoDhQXC4IIZT++g9XASZh+0IW0dQu06lhbmuvVsfw0K4vX1DHHPB17EFbQR57norK/zyvrmFr3dT1KKekZ/1IuO6r6eXOr0N4uQwMDfhndn+//2MiQuSsAMDU2YliX1izbdQQnW11dMbewISM1SSc9I12tX/mereJwdC0I6hBUoxnLfhrEtlU/UqVum9fem5VPadUvKL06Zmpho9drJc8bK0xe4btUqVTsXTuB2+d30a7fLAKqau8bNbWwAcDdt5rGyAIwNDbFy782969pBw17V6jeoyV+bwthav4POHr0KLdu3aJz586vVN7IyAhfX1+toAdvmu+//57169dz9erVkgsXQf/+/Tl+/Di9e/fWu9erc+fOGBgYMG/ePJ28pUuXkp6eTs+ePf91/2+SLl26YGRkxOzZs/XmJyUlaX328fHB19f3tY0sKDBmPTw8dJ5bjx49ePDgAbt379apN2/ePOzt7WnRokWRbX/11VfcuHGD7du3v7Zc+YwfP57k5GTNdfPmTQaNu86X393RXKGP03nyNANba0NsrbX3g+XvYXryNFNf8xoeP83A091UZ8Kr7Ev1vT3MMDCQsvjHIHatrKG5CrP0z/BSKdfKrbGMmRnGowg54VEKbCwNsLHS/s693NXGV0SU7p6qwoRHKvBwMdaRy/ul+tFx2SiylJp2tfpyM0apyMTXw52wyBhycrWNu4d5+6x8Pdx06paECpAW+lEtl7ffq+iyb/7nJ/V2KFYVdfdXWealpd55kPdvaF56gN6y+fmFsXfxJzH2EcpcbUM9PlpdtnCIdn3kG1n3Lm2jSddpBNRo/wp3VDK5sVHI7F10onvJHNXfYW5cyccZABhVCUaVk03W7Ys6eTIndyQSqW6IbaWS3NhnevfplPNw06tj+Xtg/pWOqVRIpAU65leMjqFSaemjRq4yLjyJjtWj++p9VuXcX3/JvkqFTl+ezg6s+X4o+3/+jo3TRnF40fc0r1WJpNR0qgfoTrq6ePgRG/WY3Jf0KzoiVJP/unj6ViIzPYX01JKPjiiK0qpfUHp1zNHdn/ho3bEi9pn6u3RyL3ms2Lt2AjfObuPD3j9SqW4HnTJO7rpjl/Y9iNf70oL4Jt4wCoWCmJgYIiMjuXr1KjNmzKBDhw589NFH9O7dW6f8nj176NWrF3v27CE0NJT79+8zd+5c9u3bR4cOun9cb4qyZcvSoUMHnWh6GRkZxMTEaF2JifojqbVu3Zq4uDidcPD5eHp6Mnv2bBYsWMCECRO4d+8ejx49Yv78+XzzzTeMGTOGOnXqvJbcOTk5OvI9f/5qh9AWh4eHBz///DMLFy5kwIABnDhxgvDwcM6cOcOgQYOYNm3af+7jVejRowcff/wxffr0YcWKFYSFhakNnUGD2LVrF8uXL9fZV1cYKysrPv/8c3744Yd/HVzF2NgYKysrretheBahj9M1V6ZcyZnLSSiVKlo11o7E1KqxI3JFLpeuJxXbz5lLiZiZymhUR3u/RMvGDrxIyOLegzQADpyIY/TUEJ0L4PTFBEZPDeHAyfhSJ9eE+REcPZfCwwgFmQoVF26koVSqaFZXezbzg7rWKLKUXL1T/MTK+RtpmJpICa6mvVS2aV0r4pOyCX2i3lemVMKlm2nUq2qBqXHBS4CDrQGV/E3JTo6jSa0qZMgVHLtwTautfSfO42hrTZDf60USi4p9wc37j6hYqJ6DrTWV/MpyM/QRaRkFxq1ckcW1kAdU9PN+rT5ehZidh7Eo74tN7YKwyxKZDPdP2pN44TqK6FgAFFGxJF68gfun7bSWttjUqYJFYFlidugGnPGp2IJsRQaPbmnPyN+/vANzKyecPYsOWa9SqTi++Xu1kdV5CuVrv9qk26uQFXodibEJhoHakdeMK9VFmZpEblTJESQl5lYY+lYkO/SmZu+Nlvx5+4Nk7t7aGTIDZM6eKFOSdOpodOzida30vScvqHWsnLdOneKIjH3BzdDHVCz3so75cOP+Yx0duxryUEsf82lWI4gMeZZO5L/dZ67gaGNFRV/P15MrLoEbD8OoVEQ9J1tr/DxcMTU2Yu0/JzA1NqJjI93znSrWao5CnsGti9q6d/nUTqxsnfAspz+UeFGoVCoehVzG1MwKszzvx7+htOoXlF4dC6janCxFBveuao8VN89tx8LGCTef4seKvX9O5MbZbbTtNZUq9fWPFZY2TriXrcazh1dRZKZp0rMVmUSEXsS9mD7+p0ikb+96TxBLB98w+/fvx9XVFQMDA2xtbalSpQqLFi2iT58+el33FSpUwMzMjDFjxvD06VOMjY3x8/Nj+fLlOlH83jRjxoyhfv36XLhwQWPwLFu2jGXLlmmVa9WqFfv379epL5FISgyt/tVXX+Hr68vcuXNZuHCh5sDiJUuWaB22+6rcuXNHZ2mfsbExcvl/P5xvyJAh+Pv7M3fuXD7++GPNgcUfffQRo0eP/s/tvwoSiYRNmzaxcOFCfv75Z4YOHYqxsTH16tXj2LFjNGjQoMQ2Ro4cyaJFi9i8eTPdur36GUSvS/izTP45FkefLu7kKlXcf6Q+GPjDDxxZtemZ1llVn3Vy47PO7nz94z1uhqiXmF68nszlm8mMHOCNmamMqBg5TevbU7uqDTN+eaQ5E+p5XBbP4/QfCvkiMZsbd7WXrJYWuW4/0PacPY3O4vDZZHp+ZI9SqeJBuJxq5c1p2cCav3e/0DpDq3tbe7q3tef7hU+5k9fO1TvpXLubzuCezpiaSImJy6JhTStqBFkwf2WU1tle6/bEM+9bCyYOKcPWgwkYGUjo2c6BlPRcDGIjCK5WkdqVyjN7xXrSM+WUcXHk4JnLnLtxlynD+mnOnvlx6Z/sO3merQun4uqo3nQ+7McFVC3vh5+nO+amJjyMiOKv3QdBImFQN+1omSN6dWLItAWMnPkLvdu3BImEdXsOk5SSxqCvivboOLZqhMzcFANL9aSCRflyuHRSh72O/ecEykw5lf+YjvtnHTke0ILMCPUM9rNVW/Ae/AnV1y/k3oR5KGLj8R78CeYBPlxopT3e3Bs/lzr7V1Jjw0LClq7D2MmewOljSLl9n2ert+rI5FW+EWX8gzm5dQrZ8jSsHTx5cG0vEfdP0fyTOZow2kc3TeD+5R30+vYglnbq2fDTO34k5OIWAmt3xs7Vn5jw65p2ZQZGOLoX7PFITYgk9qk6KmNK/FMAHt1Qj7+Wdu44eWjv2815fJfsJyGYtepBppEJysQ4jCrUxNA3iPRdqzT7zcza9sKoUh1SlvyAMkXbw6E+20hWZHS3nKePyIkKw7TBh0gMjciJeIjE2BTjmk2Q2TqQvmu1Tp3gqkHUqRTITys2kJ6Rp2Nn1To2dWgfjY5N+/0v9p28wLYFkzU6NnT6IqoFlqNcno49ehrFn7sPIZFIGNxN++Dekb068eW0hYyYtZje7VogkcDfe4+QlJrGoK66h/zWrxxI3SA/Zq7dTnqmHA9nB/afv87ZW6H8+EUPjVxTVmxmz5mr7Jz9DW4OtgAMnr2M6gE++JVxVQfDeBbDmn0nkCDhy04ttfpZve84DtaWuNjZEJ+SxqGLNzl+9Q7Tvuiud+lg+aoN8a8UzNaVU5FnpuHg7Mm1s/u4f+M0nwz5SaNfm/74nssnd/Ltz/uxy/MqrZo3DFfPANy9AjGztCElMZZLJ3bwOOQSH/ebqBXJMCEuiqeP1foVH6vWrxsXDgBg5+iOR9mK2t99KdUvKL06Vq5SY3zK1+efvyejkKdh6+jJnUt7eXznFB0GFIwVe9Z8x81zOxg6/RDW9uqx4uCGH7lxegtV6nfGyd2fyMfXNe3KDIxw8SwYK5p3/Ya/5vVm/cIB1Gs1ECRw4dAqMtKSaNxhpN5nJvjfI1H9r2KKCwSC95YPeugu9wCQySR8+rEbrRs7YGtjyPM4BTsOxLLjgLaXsXcXd/p0cWf01BAtw8jEWMqAHmVoXNcOSwsDnkbJWb8jimPnSl7qcmRDbXYceK43rHppkGvVjiRduaTQtY09H9SzxtZKRmxCDnuPJ7L3uHbZHh/a0/MjBybMj9Ay2EyMJfRq70j9GpZYmkl59jyLrQcSNAcYF8bX05g+HzsS4GNKrlLFrfsZrNoax0+dwgDIkMtZsmEXR85fISUtAy83Z/p0bEXL4ILZ9qm/rWHvyfNsX/QjbnnRvX5es5kLt0J4Hp+IIisLOytLagQFMKBTWzzddJddXb/3kN837uLuY/X3VLGcD4O6taNygK9WuTO1v9T8v+mDI5h56z8Q9mi5ZmSGR1J5xUw8enfSfM7HyMme8rPG4tS2CTIzU1JuhHD/h4XEHz2n05bDB8H4Tx6BVZXy5GZkErvvOCHjZpMVV/A9P9x2T/P/bEU65/9ZwKMb+5FnJGHrVJbqzb7Ar1pBsIEjG75VG1rfHcbKTn0Pf05vRmqi/lDTlrZufDbhqObzvUvbOLrxO71lA2p25IMeswDofXtoQYahMaaN22NUvjoSEzNy458jP3eA7EJnFZl9+BnGleuR/NtElMnaemz1xQ8gk5GyRHuFgxbGJpjUaYFRQFWkVnaoshXkvohBfv4gOY8L9pVKW3XS/D9DLmfJxt0cPn9Vo2N9O7SkZXBNTZkpS9ay9+QFdiyailveS/D8tVu4cDOE2IQk5Hk6VjPIn/6d2uDlql/Hlm7aU0jHvBncrR2V/ctqlTNQpOXJpWDx1gMcuniT5PQMvF2d6P9hE1rlHWAM8MOyTew+c4U9c8bhlhc5cO663Zy/HcrzhGQU2dnYWlpQq7wvAzt8gJeLdtTdP3YeZs+Zq8QmJGNsZEglXw/6f9RM77LBo0bql3WFPJ1/Ni7ixoX9ZKQl4+TmQ7P2A6kW3FZTdsPS77h8ciffLTyInaP65fzY7hXcvHCQF88jUGSmY2JmiUfZIOq3+lQn6uClE9vZ+PtEHRkAajbqQI/BMzSfGxwcof5PKdIvKL06tjO1YB9Vljyd4zt+5u5l9Vhh71KW4NaDCKpdMFbsXvUtN89tZ+iMI9g4qMeKX8c3Izle+6iMfKzt3Rk286hW2tMHlzm+cyHRYWrj2b1sFRp3GEkZ34IzEnv/t8CT/4nM42/vCB/TJqVj60lJCENLIBCUSFGGlqBoLPTMWpcG1nyh/0f8XVPY0CpNFDa0ShNahlYpovBLcGkj39AqbeQbWqUNjaFVyiitOlbY0CpNCEPr3SKWDv4f4OVzpQrzzz//0LBhKQjx+ZY5deoUbdq0KTI/Le3t/8CWBhkEAoFAIBAISgMi6qAwtP5PcP369SLz3N2LiZjzf4iaNWsW+xz+f5FBIBAIBAKBQFA6EIbW/wHexrlS7xumpqbv/DmUBhkEAoFAIBAISgXvUXTAt4V4AgKBQCAQCAQCgeDNIpG8vetf8Ntvv+Hj44OJiQk1atTg1KlTxZZXKBRMmDABLy8vjI2N8fX1ZeXKla/Vp/BoCQQCgUAgEAgEgv+zbNy4kVGjRvHbb79Rv359fv/9d9q0acPdu3fx9NR/Dl63bt14/vw5K1asoFy5csTGxpKTk6O3bFEIQ0sgEAgEAoFAIBC8WfScH/uumD9/PgMGDODzzz8HYMGCBRw4cIAlS5Ywc+ZMnfL79+/nxIkTPH78GDs79REP3t7er91v6XkCAoFAIBAIBAKBQFACCoWClJQUrUuhUOgtm5WVxZUrV2jZUvtg8ZYtW3L27Fm9dXbt2kXNmjWZPXs27u7u+Pv78/XXX5OZmam3fFEIQ0sgEAgEAoFAIBC8UVQSyVu7Zs6cibW1tdalzzMF8OLFC3Jzc3F21j6M2tnZmZiYGL11Hj9+zOnTp7l9+zbbt29nwYIFbNmyhaFDX+8MQ7F0UCAQCAQCgUAgELw3jB8/ntGjR2ulGRsbF1tH8lIQDZVKpZOWj1KpRCKR8Pfff2NtbQ2olx926dKFxYsXY2pq+kpyCkNLIBAIBAKBQCAQvFneYnh3Y2PjEg2rfBwcHJDJZDreq9jYWB0vVz6urq64u7trjCyA8uXLo1KpePbsGX5+fq/Ut1g6KBAIBAKBQCAQCP5PYmRkRI0aNTh06JBW+qFDhwgODtZbp379+kRFRZGWlqZJCw0NRSqVUqZMmVfuW3i0BAJBiSiVqnctwntHUcsR3jXnJQ3etQh6ebjt3rsWQS/lOgW+axH08sWw/e9aBL0MM9Y/O1waSMx9tdnv/zV3HrxrCfTz54tv3rUIehlq7PSuRdBLO9mJdy1CETR+Zz2rStGBxaNHj+azzz6jZs2a1KtXjz/++IOIiAgGDx4MqJciRkZGsnbtWgA++eQTpk2bRr9+/ZgyZQovXrxg7Nix9O/f/5WXDYIwtAQCgUAgEAgEAsGbphRNOHbv3p34+HimTp1KdHQ0FStWZN++fXh5eQEQHR1NRESEpryFhQWHDh1i+PDh1KxZE3t7e7p168aPP/74Wv0KQ0sgEAgEAoFAIBD8n2bIkCEMGTJEb97q1at10gIDA3WWG74uwtASCAQCgUAgEAgEb5TStHTwXSGegEAgEAgEAoFAIBC8YYRHSyAQCAQCgUAgELxZStEerXeF8GgJBAKBQCAQCAQCwRtGeLQEAoFAIBAIBALBm0Xs0RIeLYFAIBAIBAKBQCB40wiPlkAgEAgEAoFAIHijqMQeLWFoCQQCgUAgEAgEgjeMWDooDC2BQPDvkckkfPqxG22aOGJna0hMrIIdB56zff/zV6pvYixlQI8yNKlnj5WFARFRmazbEcWxswla5cYNKUvrJo469SMiM+nz1c1SKdeI6U/z2pLwaTsH6le3xMJcSmRMFlsPJnL6SmqJclhbyOjzsQM1K1lgbCThyTMF63a/4Ob9TJ2ylQPM+KSdPT5ljFFkqbh8K40121+QnJart22FPIO9G37h2vkDZKQl4+zmQ/MOA6hev02xMt2/eY7Du1YS8+wR6alJmJpZ4upRjqbt+hBUrZFW2T0bFnH32ikS46LIypJjbeuIf6W6tPz4C+wc3YrsI1uRzoX9C3l44x8UGcnYOJWletOB+FX7sFjZHt06yKMb+4l9epv05OeYWdrj4l2dWi2HYePorVU27O4xHt7Yz4vIuyTFPkGpzGHI3HtFti2zMMdvwhCsqgRiVbUCxo52hE79hQfTfi1WpnyMHO0InDUW57ZNkZmZkHLzHvcnLSD+2HmdsvbN6hEwZSRWlQPJzZDzfN8x7n07h6y4BD0tg4mRhB5tbalX1RwLMylRsdlsP5LM2WvpJcplZSHls3Z2VK9ghrGRhPCoLNbvS+T2A7mmjKmxhDYNragcYIq7kyEmxlJi43M4eSWNfSdTyM5R6W1bnpnBznWLuXz2IOlpKbi4e9O6Uz9qN2hdrEx3b5znwPbVRD19RHpqMqZmFrh5lqNlh8+oVKOhTnmFPJP921dx6fQBEuKiMTYxw93bj88GT8TZzUtP+XQObF7EzQv7yUxPxtHVhybtBlK1Xtti5Xpw+yzH96zg+bOHZKQlYWJmiUsZPxq17Utg1cZ6yx/c8gvREfcxNDKhfLUmtO0xBgtre73tGxpAk0oSyntKMDWC+BQ4G6LiboT+55uPpSnUDZTgbCvB2UatD7svKLn5RLuetTkMaycrsp1H0So2nFDqpBsbSejRxpZ6VcywMJMRFZvNjqPJnL3+avrV6yM7qlcwxdhQrV8b9idp6RdAjzY2VCtviqOtAUaGUhJTcrgVKmfbkSReJOofw6D06liGXM7vG3Zy5NxlUtLS8XJzoXfH1rSoX7tYufYcP8uPv63Wm7f3jznY21hrPn85eS7X7obqlKtbJYgFE0YW24/gf4cwtAQCwb9m1OfetGzowMqNz7j3KI1aVWwY1tcLM1MZf2+PKrH+1K/9CfQ1Z9m6pzyNlvNBA3smjfJDKnnIkTPxWmXlilxGT9V+Ec7K0n0pKD1yGQPw7RdulPMyYe2OF0TFZtGophVfD3BFKoGTl4s2tgwMJEwdWQZzMynLN8eSnJpL28Y2TBpWhh8WPePOgwJjK8jPlEnD3LlyO50ZS6OwtpTRu6MDU0eWYcxPEeToeRFeMW8UEY9u067nKJxcvblyZh9rFn2DUqWkZoOiDZr0tGRcy5SjXrPOWNnYk56WwtlDm/hj1lB6DZtBrYbtNGUz01OoEdwG5zJlMTYxJ+bZIw5u/4Pbl48zft4OzC1t9Pbxz5rhxD29Td22o7Fx9Cb02l4O/T0GlUqJf/V2eusAXDu6HDMrB2p8MAgrew/SkmK4euR3Ni/oROfhG7Fz8dOUfXz7MM/Dr+PgXgGZgRFxz+4U2S6Akb0Nnp93I+XmPZ7vOozngG7Fli+M1MiQOgdXY2htxZ3R08mKjcfry0+pvXc5F1r1I+HUJU1Zu4a1qL1nGbH7TnC50xCMnOwJnPE1dQ6u5kydziizsnXa/7q/M74eRvy9J5HouGwaVLfgq95OSCWxnL5a9MuwgQx++NIVM1Mpq7bHk5KWS6sGVkwY5MK0JTHcfaR+GXawNeDDxtacvJzGnuMpyBVKAn1N6NbKhsoBpkxbEqO3/SWzxxD+8A4f9xqBs5sXF0/9w/L541EpVdRpVLRBn56ajJuHLw2af4yVrT0ZqSmcOLiFX6aPoP/IH6nbuEA/5ZkZzJs0kOTEOFp/3A93bz8y09N4fP8GWQq53vb/XDCSZ49v07r7Vzi6enPt7F7WL/4alUpJteCPipQrIy0ZZ/dy1G7SBUtrBzLSkjl/dCOr5n5J98GzqN6gvabs45BLrJwzmMCqjej91a+kp8Szb8N8ls3sz/BpmzEwNNJpv0sDKa52cOyGioRUFUFeEj4OliKRKLkTXrSxZWsJQV4SnifBw2gVFb30L9dKy4RVh3SNlgB3CcEVpNx/pr+Pr/s64ethxLq9iUTH5dCgujmjPnNEIoEzxRjzBjKYNNgFM1Mpq3ckkJyWS+v6Vnw30JlpS2MIeazQlDU3lXLmWjqRz7PJVKgo42xIp+bW1AwyY/ScSNIy9I/1pVXHvp27hJBH4Qz55GM8XZ05cPoi3y9cjlKlolWDOkXKlc/EIX3xdnPRSrO2MNcp5+7swJThn2ulWZibltj+/woVYumgMLQE7w19+/ZlzZo1AMhkMtzc3Pjwww+ZMWMGtra2AHh7exMeHq5Td+bMmXz77beEhYXh4+ODTCYjPDwcd3d3TZno6Gg8PDzIzc3lyZMneHt7a/LWrFnD4sWLuXPnDlKplGrVqvHNN9/w0Ucf6chWFCqVqshyrVq1Yv/+/SU+A29vb0aNGsWoUaN07tfU1JSyZcsyfPhwBg0aBEBubi6zZ89mzZo1hIeHY2pqir+/P4MGDaJfv34l9lesLGVMadvUkRUbnrFxdzQAN+6mYm1pQK9Obuw6+JzU9KJnIutUs6ZWFWumLXzI0Tzj5fqdFJwdjBn0mSfHzsajLPS7r1JByIO090YuawdjagSZU7W8OfNWRnMqz6i6HZqJk70BfTo5cvpKqlZbhWkRbIWXuzHj5kRw/4n6x/xWaAYLvvOiT0cHvpnzVFO2z8eORD3P4qdlUSjz3keex2fz09eeNK9nxf5TyVpt37l2kvs3z9F7xE/UqK+exferWJuEF1Hs+ms+1YNbI5Xqn/muHtya6sHas8UVqzdiyvDWnDu8RcvQ6jpgolY5v6Ba2Du58/usIdy6fIy6TT/WaT885ATPQs/S4tO5+FVT/325l6tLamIk5/bMoVzVtkXK1rb/Eswstb0FZcrV4c8Zzblxcg1Nu/2oSW/aZRoSqXpZy8ltU0s0tDLDIznoWAsAQ3vb1zK0PPp3xapiAGcadifp/HUA4o9foOGVnQTOGsvZ+gVtlf/pG9JDw7jafQSqXLWeZoY9I/jkBsr060LE7+u12q5W3pQqAaYsWBureem981COo50Bn7Wz4+y19CJ1rFldSzzdjJiwIIrQcPVL7+2HcuaOdadXO1u+W6D++4lNyGHItKcosgoauv1QjkKhpHcHewJ9jLn3RKHV9q0rpwi5cZ7Pv5pB7YbqF97ASrWIj4tm69qfqVW/JVKZ/u+xVoNW1GrQSiutUs2GfDf4I04d2qr1Erxz3WJiIp8waf4mHF3KaNKr1m6it+1710/w4PZZeg6ZQ9VgdTu+FeqQ9CKKfevnUqVumyL1q0rdNlSpq/3yXr5aY2Z91ZKLxzZrGVp718/FwcWLXiMWIJOpX7VsHcuwZOqnXDqxjXrNe2i14+sKZV0kbD+r1HiwwmNVWJur+KCKhLsRKlRFfI8RsbBgh/oP39UWKuo6WADIVUJUvG5608oSsnJUeo25aoFq/Vr4V1yBfj2S42BrwGftbDl7Pb1IuZrVscTT1YgJi6J5kKdfdx7KmTPGjV4f2TFhUbSm7Ipt2t7au4/kxCbk8N1AZ2pVNOPYRd0xtrTq2Nmrt7h4M4SpIz6nZQO1B6tGxUBiXsTz659baR5cC5m0+CV1vh5ulPf1LrYMgLGRERX9y5ZYTvDuEIsnBe8VrVu3Jjo6mrCwMJYvX87u3bsZMmSIVpmpU6cSHR2tdQ0fPlyrjJubG2vXrtVKW7NmjZbhlc/XX3/NoEGD6NatGzdu3ODixYs0bNiQDh068Ouv6mVDCxcu1OoPYNWqVTpphe+h8LV+/Xqdfl+V/Pu9efMmHTt2ZPDgwWzcuBGAyZMns2DBAqZNm8bdu3c5duwYAwcOJDEx8V/3l0/9WrZIpRL+ORanlf7PsThMjGXUrmpTbP0Gte3IyMzl+DntX/79x+NwtDOivJ/Fey9XnSoWZMqVnLmq7bk6ci4FexsD/HxMiq37LCZLY2QBKJVw4lIK/j6m2FmrX97srA3w9zbh+MUUjZEFcP+xnMjnWdStqivvrYtHMTYxo2rdltp9NulIcmIs4Q9uvfI9AsgMDDE1s0IqK3nuzsLKDqDIl9nHtw9jaGyGb2VtY658rU6kp8TyPOJGkW2/bGQBmFs7Y2HtTFpStFa6pIQXnTeJc4fmpN17rDGyAFS5uUSu24Vt7SoYuzkBYOzmhE2tykT+vVNjZAEknrtG2v0nuHRortN27UrmZMqVnLuh7Vk4diEVOxsDynkZFylXnUrmRD7P0hhZoNaxk5fT8PMywc5a/R0pslRaRlY+DyOyALC30f3er104hrGJGTWCW2il12/WnqSEOJ68po4ZGBhiZm6JVFrQl0KRyekj26lRr4XWC3Bx3L58BCMTMyrV0X7JrtnoY1ISY4l4qLsUuThkBoaYmltq6X5ywnOePb5F9frtNUYWgLd/NRxcvLlz+bBOOwFlJCiyVYQ81X7ONx6rsDST4Gb3WmK9MjYW4OUEIREqsnJ082tXMtOrX8cvpWFnbYBfMfpVu5IZkbHZGiML1Pp16ko6fl7G2FoVvYwRICVv2XNurn5LrrTq2PGL1zAzMaZZvRpa6R81qU9cYhJ3Hjx5LbneZ1QS6Vu73heER0vwXmFsbIyLi9qdXqZMGbp3787q1au1ylhaWmrKFEWfPn1YtWoV48eP16StXr2aPn36MG3aNE3a+fPnmTdvHosWLdIy1qZPn45cLmf06NF06NABDw8PrK2ttfqwsbHRK0fhe3gTFL7fH3/8kU2bNrFjxw66d++uMUS7du2qKV+lSpU30q+PpymJydkkJmsvZXockaHJ50wx9T1MCY/M1DIOAB6HZ2jy74QWzGIaGUnZ+kc1rK0MSUjM5vSlBFZtfKbjnSotcgF4uhnxNCZLp62wSPWLh5erMfcf61964ulmTMhD3b1YYZFZmrYTknPwdFMvQQrPS3+5n/JldZeRRD99gLN7Wa2XQAA3T39Nvk9AVb1y5aNUKlGplKQlJ3Dm8GbiosNo/+lXesvm5uaQm5tDbOQTtq35CSdXb6rU0TUaABJiQrF18tUx2uxdA/LyH+DqXb1Y2QqTHP+U1MQofCp+8Mp13jSWQX4knL6ik5566746v4IfiqhYLIPUzz8lL/3lsrbBuvft6WpI5PNsHR0Lj87TE1cjQsMUOvUAPFwNCdGjfxF5dcu4GJGQrKuD+VT0U08UPI3R1b2oiIe4lvHR0bEyXup7jIx4hG9g1SLbhgIdS01O4OTBrTyPDqfTZwV7TyIehaCQZ+Lk6snfv0/n0ukDKBSZlPHyo133L6lcU3evzfNnD3By89WRyyVP958/e4C3f7VXkis9JYHzRzfyIjqMNt3HaPJjnj0AwDWvzcK4evoTFnpNJ93RWkJ8CjreodgkdYKTjYTI+OL3av0bqvpIkEgkXH+sf2meh4shkbF69CsqS5NfpH65GHLvsW5evm56uBiSmKI9fkulIJNKcHc2pG9HO6Jis7lwK0Nv+6VVxx4/jcLb3RWDl7xp5bzK5OVHUjnAt1i5xsz6laSUVCzMTKkWFMAX3drj66k7ERwZE0fLfqNIz5Tj4mhH8+Ba9Ov8ISZGuktTBe8GYWgJ3lseP37M/v37MTQ0fO267du3Z+nSpZw+fZoGDRpw+vRpEhISaNeunZahtX79eiwsLDRL8QozZswY5s+fz9atWzVL+UoDJiYmZGerjQwXFxeOHj3KkCFDcHTUDdrwX7CyMCQ1TXcKVK5QkpWtxMqi+OHFysKA6FjdH+GUvDatLAu+10fhGTz6M4InecZSlQpWdPnQheoVrRk8/jZyRcFbQGmRa9y8Z1iay3j+QndPTVqecWhpUfSsnKW5jNQM3SWOmrrm6h9xq7x/9S2HTEvPxdJct4/0tGTsnXRnZ80s1JMF6anJOnkv8/usIdy7obZYTUwt6DNqLkHVG+mUS0l6wfeDmmo+e5WrzLBJKzA2MdPbrjw9CSt7D510YzNrTf6roszN4dimCRgam1G5Ud9XrvemMbK3ITtR95lm5aUZ2dto/au/bBKGefmFsTCTERuvR8fy9rRYmBWjY2YyvXtf0tKVeflF1/V0NaRDM2su3EwnIlpP/6nJODrr0zErANJTk4psO59ffhzOnetnATAxs+CL0T9pvdgmJsQCsH/Hatw9y9FvxDQkEimHdv3J4pkjGTHxV4KqBWu1mZGWhJ2jrn6Zmdto8kti1ZzBhN46DYCxqQWfDJtP+WoFwTDy2zC1sNGpa2purbcPUyNI0rPdSZ5VkP+mkUigko+EF8kqnr3QX8bCXEZsvO54mq83lmZFe6WK1K/8uubada0tZSybXPDdhIYrmLIkRq83FUqvjiWnpeHupPt7a2WhHvOSU4ve12ZvY0XfTm2p6FcWc1MTHkVEsnbnfj6fMIs/pn2Dn3fB86kSWI7mwTXxdnNBkZXN2eu3+WvXAW7ee8jiH8Yg/R967YvkPfI8vS2EoSV4r9izZw8WFhbk5uYil6tnYufPn69VZty4cUycOFGnXpMmTTSfDQ0N6dWrFytXrqRBgwasXLmSXr166RhtoaGh+Pr6YqRndsjNzQ1ra2tCQ3Wj/rzKPbws8/fff/9a7bxMTk4Of/31F7du3eLLL78E1M+mS5cuuLi4EBQURHBwMB06dKBNm6I3CSsUChQKbUNDospCIit4Bvmzm0WtzQd4lbnXYusXytyyV3uz/ZVbKTwMS2fKGH/atXBi676YUidXi/rWJfZXXD8ly/HS56LKFZFe7PEmr7B/uXO/8WSmp5KSFMflU3tYs+BrPh06XbPnKx9zSxvGzNhATnYWzyMfc2T3Kn6dOoBhP6zE2la/8S8pRgDJK57LolKpOLZpAtFPrtC69yIsbVxfqd5bo5gvU6XzZRZRtoj0/+Tn+Bd/K462Bowf6EJ8Ug5LNxbxhg7F69ErfI89Pv+GzPQ0khLjuHByH3/MH0e/4VM1+3FUeZvPDAwMGPn9r5iYqoMFBFSqyfdDO7Bn8zKdl+AS5XoF5e/Q5zsy01NJTYrj6pndrPt1NN0GzdTs+SqppSJ1+D+OW6+LrwtYmUk4fE2/N0vTd3G6W0IfqmJKvNxsanou3/4chaGB2qPVvqk1P3zpwuTfYkhKLWJf7XuoY8WJVa9qRepVraj5XK2CP8HVK9Hr6yn8sWkXc74Zqskb3KOjVt3g6pVwdbTnlz+3TKkrIAABAABJREFUcPLyDZrULt4zK/jfIAwtwXtF06ZNWbJkCRkZGSxfvpzQ0FCd/Vdjx46lb9++Wmn69l4NGDCAevXqMWPGDDZv3sy5c+fIydGzSL0YVCrVK7/4vXwPhbGz+/cL8PMNS4VCgZGREWPHjtV44CpUqMDt27e5cuUKp0+f5uTJk7Rr146+ffuyfPlyve3NnDmTKVOmaD57eXkRFhamVWbU5LukpGVTzlvXK2FiLMXIUKrXq1SYlLQcrCx1h6B8j1NJ9UOfqGcFh/T2Ykhvr1Ij16mLiWTKcwnwMSU1PVdn1hbUs8RQ4DnQR2p6rsZbpbdunrcrJc+TVVRZfX2YW1jr9VplpCVr8kvCybVgx32lmk1ZOnMwW1ZMp1q91lozqTKZAZ6+QQCUDaxG+ar1mTK8DYd3rqBz32912jUxt0GekaSTrshQy5bv2SoOlUrFsc0TCb26m2Y9Zr3TZYMAWfFJGNrZ6KQb2arvJTshWVMOKKKsjaZcYdIycvV6FfI9WUVFawNIzcjFQo/HMz9NX10HWwMmD3UhV6liym8xRbZvYVmUjqUAr6ZjhcNmV63dhIXThrJu2Sxq1m+FVCrFwlLdhm9AFc0LMICxsSn+QTW4duG4TptmFjYaPdeSK89TavYKcjm4eGv+X6FGM1bM/oIda6ZRuW4bpFIpZnmeLH2eq8z0ZEzNdfvIzAJTPdudTPLmt+S6qzP/M1XKSsnNVXErrGhjKK2oMUyjX0UHFkotUTe16yqV8PiZ+kbvhym4fi+TXyeUoWMza1bv1D3aoLTqmLWFBSl6vFYpaeqVD1Z6ogcWh5uTA5UDy3H7weMSy7ZuWJdf/tzC7dDHpcLQEgcWi2AYgvcMc3NzypUrR+XKlVm0aBEKhULLKABwcHCgXLlyWpepqe4+lYoVKxIYGEjPnj0pX748FStW1Cnj7+/Po0ePyMrSswchKoqUlBT8/Px08l7lHgpf/8XQGjt2LNevXyc8PJy0tDRmz56t9aIrlUqpVasWX331Fdu3b2f16tWsWLGCJ0/0b8gdP348ycnJmuvmzZt88c01Bn17W3OFPk7nSUQmttaG2FprewF9PNVGzpOIovd25Od7uZvy8uoGH0/1d/XkafH14xOykStyuXgjqVTJlY9SqSIiSoGHi5FOW15u6jeq8Gj9exsAIqIUeLrrelK98vdkRSnyyhXs2dIta0yEnj5cPf14HvmY3FxtozE6Im9vicfr6TSAp28lMtJTSEvRf9ZTPjb2LljbOhIXHaY3397Fn8TYRyhfki0+Wu05LhyiXR/5Rta9S9to0nUaATXaF1v+f0Hq7VCsKuru17HMS0u98yDv39C89AC9ZfPzCxMRnYW7s6GOjnm6GmnyiyIiOltTTl/dpy/VdbA1YMpQF5DA5MUxJCQX/ZLt7uVH9LMnOjr2LE/H3D2L36OiDx+/imSkpZCWkqjpoyhUKhVSqe5LnouHP7FRj3Tkinmqlsu5zOvrvodvJTLTU0hPVeu+S14b+W2+3I+Lnj7iklXYW+l6O5xs1An5e7XeFGbG4OcGoVGQUfQwRER0Nu5ORevX0xjdZaOF63q46i7tf5W6AAnJuSQm5+LqqN8nUFp1zNfTnbDIaHJytf8+HkWo9+6W9dCd+C0RFUhfw2jRJ9e7QATDEIaW4D3nhx9+YO7cuURFlXw2kj769+/P8ePH6d+/v978Hj16kJaWxu+//66TN3fuXAwNDencufO/6vtNkW9Yurm5vZJ3rUKFCgCkp+tfJ25sbIyVlZXW9SAsi9DH6ZorU67kzKVElEoVrZo4aNVv3cRBbQBdTypWjlMXEzAzldG4jraR2aqxI3EJWSWGcq9fyxYTYxkXryaVKrka17XD1ERGaJic89fTMDWRUq+a9lLRpnWtiE/K4cET/YEwAM5fT8PDxRg/74LIhFIpNK5txf0nmSTmveQmJOcQ+iSTJrWtKPzb6u9tQhkXI85d15W3cq0PUMgzuHFBO/rZxZM7sbZ1wsuvUrH3+DIqlYpHIZcxNbcs8mysfOJiIkiKf46Ds6fefJ+KLchWZPDo1kGt9PuXd2Bu5YSzZ9HBXFQqFcc3f682sjpPoXztd/u3mU/MzsNYlPfFpnZlTZpEJsP9k/YkXriOIlq9D0QRFUvixRu4f9qOwm+2NnWqYBFYlpgdh3TavnAzA1MTKXUra8+SN6llQUJSDg/Di36LvngznTLORpTzLHClSKXQsIYFoWFyrUAFDjYypgx1QSqVMOW3GF4kFu/ZrVqnKQp5BlfPHdFKP3dsNzZ2jvj8Cx0LvXMFM3NLzPO8DDZ2jpQNqMzDezfIzCjQc4Uik9A7V/Dx1+0jqOYHZMkzuH1J+1leObUDK1snPMtV1qlTklxPQi5jamal8WRZ2znj4VuJa2d2o1QWPMPwhzeIi35CxVq6gWDuP1NhbCghsIz2GF7ZW0Jqhoqo4ucvXptK3hJkMgk3igiCkc/F22r9qlNZe5VA45rmJCTnaEUU1Kl7KyNPvwqMeakUGlY3JzRcoRMI42Wc7Q2wt5ERo2ePGJReHWtcuyoZcgXHLlzVSt974hyOtjYE+fm8llxRsS+4ef8hFf1KDuO+74R6v9mrlBX8bxBLBwXvNU2aNCEoKIgZM2ZoQq2npqYSE6O9d8bMzAwrKyud+gMHDqRr167Y2Njobb9evXqMHDmSsWPHkpWVRceOHcnOzuavv/5i4cKFLFiwAA8P3Y3VxaFQKHTkMzAwwMHBoYga/54uXbpQv359goODcXFx4cmTJ4wfPx5/f38CAwP/U9thzzLZdyyOfl3LoFSquP8wnZpVrPnoAydWvhQNsHdnd3p3cWfM1BBuhKhDnV+8nsylG8mMGuiDmZmMyBgFH9S3p041G6Yveqg5+8fZwYiJI8px9Gw8kTFyVKqCoBNPIjLYezSuVMp16EwyiiwV10PSGdzDGTMTGdFxWTSqaUmNIHPmr4rWtDWslzNN61gx+IcnxCWoXyoOn0uhTWMbvvnclT93vCApNZc2ja1xdzbih0XPtO557Y4XTB5RhrEDXfnnRDI2ljI+6+hAeKSCI+dSdL67CtUaElC5HpuXT0OemYajsydXzu4j5PoZPhs2UxN6fd3SSVw6sYvvF+3DztENgGVzhuPuFYC7VyDmltYkJ8Zx8fhOHt69TJf+EzQRwCLD77N97Ryq1mmBvVMZJFIJ0REPOL7vT8wtbWjWrq9evfIq34gy/sGc3DqFbHka1g6ePLi2l4j7p2j+yRyNbEc3TeD+5R30+vYglnbqGeLTO34k5OIWAmt3xs7Vn5jw65p2ZQZGOLpX0HxOTYgk9qk6/HNKvPpMskc31GfZWdq54+Sh+wLl2KoRMnNTDCzVRo1F+XK4dFKHCY/95wTKTDmV/5iO+2cdOR7QgswI9QTQs1Vb8B78CdXXL+TehHkoYuPxHvwJ5gE+XGilfZ7dvfFzqbN/JTU2LCRs6TqMnewJnD6GlNv3ebZ6q45M1+9lcuN+JgO72GNqIiXmRTYNqptTrbwZC/+M1ejYl90daFzLgmHTn2mMpKMXUmnVwIoxfZ34e4/6QNlW9a1wczLUOoTYykLKD0NdsbGSsWTDC6wtZFhbFCwJi0/K0fFuVaregPJV6vL3HzOQZ6bj6OLBpdP7uXPtLANGTtecb7Rm8WTOHdvD9N92Ye+k1rHFM0dRxtsfD58AtY4lxHH22G5C71zhk4HjtaLMde3zFfMmfcHCqUNo9XE/JBI4tOtP0lKT6NBT++gPgMAqjfCrGMz2VVOQZ6bh4OzJ9XP7CL15mh5f/qTRr83LJnL11E6+mb8fWwe1fq2ZPxRXz0DcvAIxs7AhJTGWy6d28PjeJTr2+V5Lrjbdx7D8p8/5a9FX1Gveg7SUBP7ZOB+XMn7UbNRJR65H0fA4RkWbmhKMDSExTX1gsa+bhB3nlJr9TB/WllDZW8LiPUpSCgXjC8yLCWFjoTbUXG0h/2zre9rDBQBVy0pITlfxKFo3rzAa/epsj5mxlJgXOdSvptavRX/HaeQa3M2exjUtGD7zGS8S1bpw7GIqrepbMrq3E3/vTSQlLZeWwZZq/VpaoF+erob06WDH+RsZxCZko1SBp4sRHza2IjVdye7j+oPzlFYdC65WidqVyzNn2d+kZ8jxcHHk4JlLnL9+h8nDB2jO0Jq+ZA37Tpxjyy/TcXVUH00xbNp8qpX3p5ynO+ZmpjyKiOSvnQdAIuGL7h0KvpeQB6zeto/Gtavi5uxIVlY2567fZufhU9SsGEiDGq83YfDWEEsHhaEleP8ZPXo0/fr1Y9y4cQBMmjSJSZMmaZUZNGgQS5cu1an7KgbOggULqFy5MkuWLOH7779HIpFQvXp1duzYQbt27Yqtq4/9+/fj6qq9MT8gIIB79+69dlsl0apVK9avX8/MmTNJTk7GxcWFZs2aMXnyZAwM/vuf/4LlYbxIyOLj1i7Y2RgSE6fg19XhbN//XKucRAoymURng/CkuaF83tODft3KYGlhwNPITKYueMCxswXTt+mZuSQkZ9P1IxdsrQ2RSiU8j1Ow7Z8Y/t4WpRVxsDTJZWCuNuxn/RHFp+0d6PmRPZZmUp49z2buimhOXyk4W0sqUctRWIycHBWTFj6jz8cOfN7NCWMjCU+eKZj6ayR3HmgvX7z9IJNpiyPp+ZE9E750Q5Gl4vLtNNZse0FOjv4lRwPGLGDPhkX8s2kx6WnJOLv50GfEbKrXLwiUolLmolTmam2GL+tfjesXDnFq/3rkmemYmlviUTaIL8Yt1oo6aGltj7WtI8f2rCEl6QW5uTnY2DsTVL0xLToOxNah6CMO2vT5hfP/LODigV+QZyRh61SWFp/Ow69aQbABlTJXfRXabB929xgA9y5u5d5FbaPE0taNzyYc1XyOfHSBoxu/0ypz4M9RAATU7MgHPWbpyFXx1x8w8y6IcubWtQ1uXdXP62i5ZmSGR4JMitTAQOsFQ5mVzflWfSk/ayxBCyYiMzMl5UYIFz8aSMKpS1p9JJy8yKV2X+A/eQS1diwlNyOT2H3HCRk3G2WW/qVWc1c+p+eHtnRvY4OFmYzI51n8vDaWs9cKvNZSqR4dy4Wpv0XTq70d/TvZY2woISwqixl/xHD3UYG3tYyzES4O6iVgIz9z0ul/0/5ENh9I0kn/8pt57Fj3KzvXLyEjLRkXd28+Hz2T2g0KzkhTKpVqHStUzzewKlfPHebYPxuRZ6h1zNu3AsO+W6QTTts3sCpfTfmdnesWs2KB+vss61+Zr6cuwzdAv/fzs1ELObBpIYe2/EJGejJObmXpOXQuVesVBHJR5ctVSDAv/+rcuniQs4f+RpGZjomZJWV8KtJ3zBKtqIMAvhVq0+/rpRza+gur5w3FyNiEwKpN+LDn1xgY6g8huOW0kiaVJDSuJMHESB3uvfABxqBWK6lUovP+2rmB9l6omv5SauatVp2+QdsIdrcHB2sJp24X783KZ+7qWHq2saVb6zz9is1mwZ9xnL1eWL8kefpVIFhOLkxbGkOvj+zo/7EdxkYSwiKzmLnsOSGFwr4np6qXCLZrYoWNpQyZTEJ8Ug5X72aw/Ugy8UlFe75Kq47N+vpLlq7fwbJNO0lJy8DL3YVpIz+nRf3amjK5SiW5SqXW+FrOw53DZy/x9+6DKLKysLOyokbFAPp3/ghPN2dNOXtba6RSCSu37iU5NQ0JEsq4OjGwW3s+adeidEQcFAAgURUXTkYgEAiApt0uvGsR3jusHWzftQh6GfyF97sWQS/3n77+MQ3/C/4fe+cd32T1Pf53kibpSPeetNBCWWXvjUxFQGWDMgQFRFFkCIrspaKgIoLsPZStIEP23hvKKquT7pm2SX5/pE0JSVpG+VB+3/t+vfKC3vWc5+npzXPuOffc4HdfzPP7slgyZMerFsEsQ/p7Ft3oFZGYYflw3VfJ5VuvWgLznD95/1WLYJZP+pka+yWBsNyTRTd6BThXaVJ0o5dE/KUjL21s10pmsj2WQITJKxAIBAKBQCAQCATFjDC0BIISwsqVK1GpVGY/FStWfNXiCQQCgUAgEDw1OiQv7fO6IPZoCQQlhPbt21OnTh2zdU8epCwQCAQCgUAgKNkUm6GVlJRkMXObQCAoGnt7e+zt7V+1GAKBQCAQCAQvzOt03tXL4rmewIwZM1i7dq3h5y5duuDq6oqvry/nz58vNuEEAoFAIBAIBALBa4hE8vI+rwnPZWjNmzfPcHbQrl272LVrF9u3b6dt27aMGDGiWAUUCAQCgUAgEAgEgteN5wodjIqKMhha27Zto0uXLrRq1YrAwECLe0wEAoFAIBAIBALB/w10Iufe8z0BZ2dn7t/Xn6+wY8cOWrRoAYBOp0OjsXywnEAgEAgEAoFAIBD8X+C5PFrvvvsuPXr0ICQkhPj4eNq2bQvAuXPnCA4OLlYBBQKBQCAQCAQCweuF7jXaS/WyeC5D66effiIwMJD79+/z3XffoVKpAH1I4eDBg4tVQIFAIBAIBAKBQCB43XguQ0sulzN8+HCT8s8///xF5REIBAKBQCAQCASvOSK9+3Pu0QJYvnw5DRs2xMfHh7t37wIwa9YsNm/eXGzCCQQCgUAgEAgEAsHryHN5tObOncu3337L559/zpQpUwwJMJycnJg1axYdOnQoViEFAsGrRWGjfNUivHY4uJbMw6fL2Ee9ahHMUufSjFctglk+GrLjVYtglj6/tnnVIpjFa8juVy2CRfyts1+1CGb5e5fTqxbBLL1/bv2qRTCL1+CSqWMfzvZ91SKYZcPPr+7aOsQerefyaP3yyy/88ccffP3118hkMkN5zZo1uXjxYrEJJxAIBAKBQCAQCF4/dBLpS/u8LjyXpHfu3KFatWom5UqlkvT09BcWSiAQCAQCgUAgEAheZ57L0AoKCuLcuXMm5du3b6dChQovKpNAIBAIBAKBQCB4jdFJJC/t87rwXHu0RowYwSeffEJWVhY6nY4TJ06wevVqpk2bxoIFC4pbRoFAIBAIBAKBQCB4rXguQ6tv377k5uYycuRIMjIy6NGjB76+vsyePZtu3boVt4wCgUAgEAgEAoHgNUIkw3gOQys3N5eVK1fy9ttvM2DAAB49eoRWq8XDw+NlyCcQCAQCgUAgEAgErx3PbGhZWVkxaNAgrl69CoCbm1uxCyUQCAQCgUAgEAheX16n7IAvi+d6AnXq1OHs2bPFLYtAIBAIBAKBQCAQ/H/Bc+3RGjx4MF9++SUPHjygRo0a2NnZGdWHhYUVi3ACgUAgEAgEAoHg9UPs0XpOQ6tr164AfPbZZ4YyiUSCTqdDIpGg0WiKRzqBQCAQCAQCgUAgeA15LkPrzp07xS2HQCB4DZHJoNvbnrRq6IqLkxUxcdls2fOILbsfPVV/a6WUPu9507i2E/Z2Mu5HqVn7dwz7jycZtevQ0o1mdZ3x8VRiYy0lKSWXKzfSWbUlhrsPs16JXFIJdGzlTo1K9pTys8bezorY+GyOnklm7d+xhnZKhYROb9hTu5I1djZSoh7lsu1gGscvmsr9JPZ2Urq1sqdqOWsUcgn3o3P4c08qV25nG7Ub3c+F8kFKk/4XbmTxw7JEs2NnZmayfNkSDh3cT2pqKn7+/nTq3JUmTZo91TPKZ/nSxaxdu5qAUqX4be4fJvVZWZn8uX4dB/bvIzY2FhsbawKDSjPk08/x9fU1P6hciU2Tt1GEVkdiY4cmPpqsozvJuXq6UFlUPT5HXqqsxfqkn79Cl56i/0FmhbJmU5SV6yJ1dEWXo0YTfZ/Mw9vRPLxttr+1QkK3N52pV9UOla2UyNgcNu5J5sjZ9ELlAnBQSXn/bReqV7BFqZBwNzKb1f8kculGgR7YKCW0beRAWDkbfD3kWCulxMbncuB0Gv8cSCEnV2d2bJnKjpCvB+NQJRSHqhVQursQPvEXbkz6tUi5ABTuLoROH4Hnm82Q2VqTcuEa17+dRfzeYyZtXZvXo9yEoTiEhaLJyCLmn71c++p7suMSTNpmZmayYtliDh/cT2pqCn7+AbzXuRuNn1HHVixdxLq1qwgoFcivc42PkBkzahiXLl4w6VOtRk0mTJpudrzMzEyWLlvGwYMHSU1Nxd/fn86dO9O0SZNnkmvp0qWsWbuWUqVK8fvcuYbymJgY+vTta7FfjRo1mDxpkkm5Ug4dm9hSs7wSOxsJ0fEath/N5OSVbDOjGGNvK6FTc1sqBytQyCU8iMll04EMrkXkGtq4OkqZ/omzxTEu3cpm9tpUk/KSql9QcnXMWiGhRztX6ldTobKV8jAmhw27Ezl8Jq1IWRxVMt7v4ErNinYoFRIiHmaz6u94LoZnGrWrUdGWBtVUBPkp8fVUYCWT8O5nN5/hrl8+Yo/WcxpapUqVKm45BIJi58iRIzRq1IiWLVuyY8cOQ3lERARBQUGGn52cnKhcuTKTJk2iSd4XbZ8+fVi6dCmgTwDj7+/Pu+++y4QJE0xCZZ/kyfHlcjkBAQH06dOHr7/+mhUrVjBw4EDOnz9PcHCwoV1kZCQVK1Zk/PjxfP7554VeY/HixQQGBtKsmfkvk6ioKLy8vEhPT2fixImsX7+eyMhI7O3tqVixIsOHD6ddu3aFXuNp+PQDf96o78zSDVGE38mkRmV7BvX0xdZaypptsUX2//azQMoG2bJoXRQPo9U0q+fMmMGBSCUR7D2WZGjnoLLi5MUUbv+dRVp6Lt4eSrq85cHsb0MYMi6cB9Hq/7lcCoWUXu94se9YItv3x5OSpiG4lA092ntSt5oDExckkZMLn3V3prSvnHU7U4mOz6VemA2fdHFGKknk6AXLxpaVDL7q64KttZQV/ySTkq6lRR07hn/gwowlCVyPMH75iknI5ff1SUZlGVlai+NPnTyB8Bvh9OnTD19fP/bt28v3M6ah0+po2qx5kc8I4PatW2zY8CdOzuZf3jIzMxnz1QjiE+Lp3LkrgUGlyUhP5+rVK6jVlu9d9d5HyLxKkblvE9qEWBQVa6Lq+CFpEgk5V05Z7Jfx7xokSmujMolcgarrEDTR9wqMLMC2bU8UFWuRdfRfcu9eR2Jth3W9Vtj3/ILU5T+gibprMv7wfp6U8VewclsiUXE5NKyu4osPPJBKYjl0xrKxZSWDcYO8sbWRsnijXldaN3Tg64+9mDQ3miu39M/CzdmKt5o4cuBUGtv2pZCl1hJaxpourZ0IK2fDpLnRZsdXuDoR0L8LKReuEbNlNwEfdrEoy5NIFXLq7FyC3NGBy8OmkB0bT6lBPan99wKOt+5LwsGThrYujWpRe9sfxP6zn1PvDkbh4Uro1OHU2bmEw3XeQ5udYzT2tMnjuXHjOr379MfH148D+/bww4wp6LRamjR746nku33rJhs3rLeoYwBeXt4MGznaqExlp7LYftLkydy4cYO+ffrg6+vLvn37mDFjBjqt1uKc+iS3bt3irw0bcDYjl7OLCz/++KNJ+dGjR1m/fj3169UzO+ag9+wJ9LZiw74MYhI01K6g5KOO9khI5UQhxpaVDIb1cMDWWsLaXemkpOtoVsOaoV0d+Gl1CuH39MZWcpqWaUuSTfpXLaugbX0bzoabv0ZJ1S8ouTo2sr83wQFKVmyJJzIuh0Y1VHzZxwupJJqDpy0bW1ZWMH6ID3Y2UhZtiCM5VUObRo6MHeTD+DkPuXKzYN6sE6aibKA1dx6oycnVERxgbXHcV4UIHXxOQ2vZsmWF1n/wwQfPJYxAUJwsWrSITz/9lAULFnDv3j0CAgKM6nfv3k3FihWJjY1lzJgxvPnmm1y6dMlgJLVp04bFixeTk5PDwYMH6d+/P+np6cx9bOWyMPLHV6vVHDp0iP79++Pt7c2HH37Ixo0b6d27NwcPHkQq1a/4fPTRR1SrVo2BAwcawnMBhg4dSkpKCosXLzaUOTo6cvz4cQCuX7+Og4OD0bXzj1sYOHAgJ06c4Ndff6VChQrEx8dz5MgR4uPjn/FpmlLK15rWjV1Y8lcUf26PA+DCtTQcVDK6t/fi773xpKZbDiOuFWZPjUoOTJsbwb484+X8tTQ83OT07+bD/uNJaPMW8JdvNH7BvHg9nas301kwvTzN6zmz7LH6/5Vc2dlaen95xWisC9fSiI3PZuynQdSqqCYtQ0vlYCW/rUvkWJ4H6+qdbFydZHRt7cCxi1nozDspaFLDFn9PORPnP+Lm/RxD38mfuNGtlT0T5hv/DnNydNx6YPoiYo6TJ09w9uwZRowcTZOm+hfLsCpViYuNYdGiP2jUuAkymazQMTQaDbN++oE2bd/izp3bpKSYvsAtX7aE+/fv8euceXh5exvK69Q1/6IJYFWmIvKg8qRtXmQwqnLvhSN1dMW2+bskXz2NpYemjTc1RBSV6yCRWaE+d6SgUGaFomJNsq+cJOvAVkNx7oNbOH02HUXF2mQ+YWhVK29DlXI2zFoWy+E8D9blm1m4u1jx/tsuHDmbbtDXJ2le154AHwVfz4ok/K5+UeDSzSx+GOFLr7edGTMrCoDYhFwGT7qPOrtgoEs3s1CrtXzQwZXQICXX7qhNxs+8+5Cd7rUAkLs6P9OLsH+/zjhUKsfhRl1JOnYOgPh9x2l0ejOh00dwpEHBWOVnjCQ9PIIzXT9Dl7dFIDPiAfUPrMGvbyfuzVttaHvq5HHOnT3NlyPH0KSp3nAPq1KV2NhYFi+aT8PGTZ9Kx2b/9D1t2rbjzp1bpKSkmG2nUCoJDa3wVPd74uRJzp49y6iRI2natCkAVapUISY2loWLFtG4ceOnkuvHn37izbZtuX3njolcCrmc8qGhJv2WLFmCUqmkSd51H6dSGTkVSyv4Y1OBUXX9bi6ujlI6vWHHyavZFueKhlWU+HlYMW1pMrcf5ub1zWFcf0fea2bLtKV6+XI1cDsy16T/O81sUWfrOHHZvKFVEvULSq6OVa9gS9VQW35cEs2hPA/WpRuZuLvI+aCDG4fPpFmcK1rUdaCUj5KvfnxAeIT+O+PijUx+HOXPB+3d+OrHB4a2c9fEGnSifye3EmloCZ4z6+DQoUONPoMHD6ZPnz589NFHRa7ECwT/C9LT01m3bh2DBg2iXbt2LFmyxKSNq6srXl5ehIWFMW/ePDIyMti5c6ehXqlU4uXlhb+/Pz169KBnz55s2rTpqWXIH79UqVL07NmT+vXrc+bMGQDmzZvHzZs3DaueS5Ys4eDBgyxevNhw3fyPjY2N2bJ8PDw8jOq8vLwMxtvWrVsNRmRgYCA1atTg008/pXfv3s/xVI2pX90RqVTCzoPGIR07DyRgrZRSs7J9of0b1HAiI1PDgRNJxv0PJuDmrCC0jG2h/ZNT9S8Mmie+sf5Xcml1mDXYrt/OAMDFUUrNCtZkqrWcuGzsvTl4JgMXBxll/OQW5ahR3prIuFyDkQWg1cKR85mU8VfgbP/8IRlHjxzGxsaGho0aG5W3aNmahPh4wq9fK3KM9evWkJqayge9zYdIZWVlsfPf7TRs2NjIyCoKRdkq6NRZ5Fw9Y1SuvnAUqb0TMp8gCz0tjBdWH506i+zHww51WtDp0KmNQ3F02VnotFrINTVYa1e2IzNLy9Hzxp6rvcdTcXGyIriUaehmPnUq2/EwJttgZIH+d3ngVBohpaxxcdS/DKqzdUZGVj437+lfgF2dnmtttFA8O7Qg7dptw0swgE6j4eGqLTjXroLSR79oo/TxwKlWGA9Xbja8BAMkHj1L2vU7eHVoYTTusSOH8nTMOBzvjWfQsT/XrSYtNZVevfu9wB0ac/TIEWxsbGjUqJFReauWLYmPj+f69etFjrFu3TrSUlOfaR6NjIri4sWLNG7UCDtb07mtWlkFWWodp64aGztHLqhxtpdS2sfy775aOQVR8RqDkQX6+enYJTWlfeU4qSzPFe5OUsoGWHHqqposM7r3orws/YKSq2N1wvRzxZFzxp6r/46l4OpkRUigZYOoTpiKBzHZBiMLCuaKsoEFcwVYXG8qUegk0pf2eV14LkkTExONPmlpaVy/fp2GDRuyevXqogcQCF4ya9eupVy5cpQrV45evXqxePFidIXMSrZ5X3w5OZY9AjY2NoXWF8apU6c4c+YMderUAcDd3Z158+YxduxYdu3axRdffMHs2bOLPSzXy8uLf/75h9RU07j7F6WUnzVJKTkkJhuvkN6+r/+CCPSzMdfNqP/9qCy0T0S33cnrX8pMf6kE5FYS/L2VfNEvgMTkHBOD6lXI9ThVK+gNuYexufh5WBEZl2sy1v0YvWx+npZfnvw8rbgfY6pv96P1fX09jPt6uFjx22hPFo/34vsv3OnUwh65heHv3o3Azz/AZLU3MM+be/duhEW5AO7du8vaNasYPOQzI6P/cW7evEFWVhY+vr7M+fVnunZ5l47t3+Tzzz7h5InjFseWufugiY/WG0OPoYl9mFf/9Eab1NkdeUAI2VdPQc5jniCtFvWZAygr1UUeUgUU1kgdXbBr2xOdOhP1+cMmYwV4y3kYk2Pyu7wblZ1Xr7Aoh7+33NDuce7llfl5We4LUClE/2J2P7rovTrPin3FEFIumhoXqXll9hVC8trp975Zaptfn48lHQsKKp1XX/he73v37rJuzUoGDRlqUcfyiY6KpEeXd+jYrhUf9Xuf5UsXoVabev4AIu7exd/f34xcQYb6wrh77x6r16zhkyFDipTrcXbu3IlOp6N169Zm633dZUTFa0w8HQ9i9UaHj7tlz4yPuxUPY009VU/Tt0EVJVKJhIPnzT+vF+Vl6ReUXB0L8FbyICbbdK6ILHquCPBWcDfSdNy7D/Vl/oX0FZRMim15LCQkhOnTp9OrVy+uXSt6FUEgeJksXLiQXr16AfoQwLS0NPbs2UOLFqarYunp6YwePRqZTGbYo/UkJ06cYNWqVbzxxtPFfAPUr18fqVRKdnY2OTk5fPTRR0ZhtR07dqRLly60adOGdu3a0adPn2e7yTz8/PyMfvb19TWsys6fP5+ePXvi6upKlSpVaNiwIZ06daJBgwbPda3HcVDJSE0z9eios7Vk52ixVxUesuGgkhEda/rimJqWa6h/ks3zw1Ao9OtD96OyGDHtJnEJxsbIq5ArH1dnOf06e3P9dgbnrqvp3tqB2ETTF6C0DP03sMrW8lqXykZKeobpHqv0TNO+4XezOX4xi6hHucitJFQpq+TNhnaUDZAzbXGCycpnakqKWS+Tvb3eSLQUPgOg1WqZ/dNM6tdvSK1atS22i4/XJx75c/1aAgODGPblCKQSKRs3/MnECd8yfuIUatSoadJPYmOHNsk0aYkuU+9JktpY3hfxJMoq9QFQnz9iUpe5+0906kzs3h2AJM8DrEmOJ23VbLSJcSbtVbYyYuNNDd+n+V3a28oM7Yz6pmvz6i33DfCW06G5I8cvpHMv6vkWegpD4epETqJp2Gd2XpnC1cnoX/Ntk5Dn1eeTmpKCpxkdU+XpWGoROvbzT99Tr35DataqU6j8FSpUomHjpvj5BZCdreb0qRNs+HMtVy5fYsr0Hwze/cflKkz3i5Lrp59+okH9+tSuVatQuR5Ho9Gwe/du/P39qVixotk2KhspcUmm85bh793G8l4XlY2E9EzThcT0LF2hfSUSqF9ZSdSjXG49MJ2nioOXpV9QcnXM3k5KjNm5QpNXb/k7RGUnM8wLj5OakT9XFP79VdIQe7SK0dACkMlkREZGFueQAsEzc/36dU6cOMGGDRsAfTKLrl27smjRIiNDK98QysjIwNvbmyVLllC5cmVD/bZt21CpVOTm5pKTk0OHDh345ZdfnlqOtWvXUr58eXJycrh48SKfffYZzs7OTJ9ekKVo7NixLFu2jLFjxz73/R48eNDwkpB/v/k0btyY27dvc+zYMQ4fPsx///3H7NmzmTBhgsVrqtVq05U6XTZSWcFKWv5KXaGRC08R1lBYE3MOyC8m38DKSoK3h5J3W7vz3VfBjPnhliHz4KuSC/RfnpOHlUYigam/RaCzcS60/dPI8rRd/9pjHKJy4YaauEQNPdo6UD1UyemrpiukhX39SSSWazdt/IvIyIeMHTehkBFAl7c0b2UlZ/zEKQavceWwKnw0oC9rV680a2jpOxcy7tPGy0ikKCrXRRMXiSYywqTaun4brGu3IOvQ3+Tev4lEYY2yZlNU3T8lbc0vaGIemPR5oUidwu7JQrm7sxWjB3gRn5TL72ufLmPmc1HIMzV53pbamimXFKJlhenY5o1/EhX5kG/GmWbme5InQ75q1qqDh6cXixfM4/ixI9Sr39CMXJYpTK4NGzcSGRnJ+HHjipTrcU6fPk18fDwdO3YstN0LTBXP1bdSaTnODjLW7yk6a+YL8ZL0C0qujhU2TRU1h72IHghKHs9laG3ZssXoZ51OR1RUFL/++muxrJQLBC/CwoULyc3NNUodrdPpkMvlJCYWpLpeu3YtFSpUwMnJCVdXV5NxmjVrxty5c5HL5fj4+CCXW95PYw5/f39DVsHy5ctz+/Ztxo4dy/jx47G21ocC5RtFjxtHz0pQUBBOTk4W6+VyOY0aNaJRo0Z89dVXTJ48mYkTJzJq1CgUCtMwhGnTpjFhQsFLdKlSpYiIiDBqM2LaTVLSNJQJMF1dUyqkKOTSQhNOAKSkacx6h+xV+mdhrv/Nu/o9NdduZXD7Xgbzp5bn98kFm85flVwqWxnTRpbB1VnOqBk3iY7LxjNA7+0w5+nIL0vLtJwVMC3TfF87G32ZOW/X4xw5n0mPtg6U8VeYGFr2Dg6kmAknzQ8xfdxwf5zY2FhWrlhG7z79sLKSk5amN/C0Gg06rY60tDTkcjlKpRL7vAQt5StUMBhZANbW1lSuFMaxY6ZeJtB7riQ2ppk988t0WU/3UigvUxGpypGMYztN6qSuXlg3bkfmf5tQn9htKM+5fRmHAd9i80Yn0lbNMuqTlqExu5ps+F0W8vtIzdCgsjOjB3aW+7o5WzH+Ey80Wh0TfosudPwXITs+CbmLk0m5wtkRgJyEZEM7wEJbJ0O7fOwdHEhNNfUopOXpmMqCjsXFxrByxVJ69+lvpGMajQadVmukY5Zo2qwFixfM4/q1qyYvwUXpviW5YmNjWbFiBX379MHKyspILm0Rcv27cydWVla0KCQiIi1Ti8qmkL93Mx6rgr46s14rO2tJoX0bVlWSq9Fx9OLLCRuEl6dfUHJ1LDVda9ZrpcqbPwr7W05L12BvZq6wN8wzr9c5tbpCjN3/KzzX292TqzISiQR3d3eaN2/OzJkzi0MugeC5yM3NZdmyZcycOZNWrVoZ1b333nusXLnSkNbc39+fMmXKWBzLzs7OKP36iyKTycjNzSU7O9tgaL0KKlSoQG5uLllZWWYNrdGjRzNs2DCjsk/GXkYiLZguHkSribhvS7O6zjg7Whnthwry199bxAPjRANPEvEgk6Z1nJFKMYplD/TT979bRP+H0dnciMjQe5J+jXhlcqlsZUwfVQYvNwWjZtwy7OUC/V6sumHWJmPl7816EGM5XOd+TC7+nqbGvX9+XzN7MsxhbvE0MDCQA/v3odFojPY3RETo9zSUKhVodqzo6CjUajXz581l/jzT7JvdurxL+w7v8NHHg4yOODCRCZ3F1WZNbCSKCjVBIjXapyVz99HXx0VZHPdxFFXqo8vNIfvSCZM6mYcvEonUNIW7Vosm9gFWASEmfe5FZdOgmsrkd5m/3+KemT1YBX1zzO7LyC+7/0RfN2crJnziBRIY/2s0Cckv7+Uq9VI4DpVM97/Y55WlXr6R9294Xnk54nYcMGmbX59PqcAgDu7fW4iOmdeP6OgostVq/pg3hz/mzTGp79GlI293eJcBHw8u8t7M6VhgYCD79+83ketO3mJSoIV9stHR0ajVan6fN4/f580zqe/cpQsdOnRg4McfG5UnJSVx4sQJ6tSpU+iC2MM4fTp3qQSjfVq+HnoZI+Ms68DD2Fx8zezDyu/7MM50rrC3lRAWrOD8jWxSM16en+Rl6ReUXB27G6mmUQ1707nCp+i54m5UNqW8TQ08Q9/I4t+nKXi5PJehpX1yh59AUELYtm0biYmJfPjhhzg6OhrVderUiYULFxbL+VFPQ3x8PNHR0eTm5nLx4kVmz55Ns2bNTFKxvyixsbFkZRlntXN1dUUul9O0aVO6d+9OzZo1cXV15cqVK4wZM6ZQOZRKpclK3s17OYBxzPnRsyn0fs+blg1cWPdPwdlUrRq6kKXWcupi4Qk4Dp9O5s2mbjSq6cT+xzL8tWzowqPEbK7dyii0v62NFC83BZdvpHMjosD4+V/KZTCy3BWM/u4Wt+4ZG2Gnr2bRrJYttSpYc/xSwe+oYVUbElI0haZjP30liz7tHSntJ+d2XjupFOpXseHm/WySUgufhxtW02/uvnXf9Iu5Xr0G/LtjO4cPHaRxk6aG8v9278LF1ZWy5UxTUwOULl2GqdO/Nyn/Y/5cMtLTGfrFcNzc3ABwcXEltHwFrl65TEZGOra2eo9UVlYWly5eoFxoebPXyA4/h7JaQ+Sh1YwOKFZWros2NQlNZOEb3AEkdg7Iy1Qi5/o5w96ux9Gl6VfHZb6B5N6/UVAhs0LmGYA2Jcmkz/ELGbSo50DdMDuOnCsYs2ktFQlJudy8a9krcOJCOgM6uxEcoOTmPX07qRQa1VARHpFFYkrBS7Sbk4wJn3ghlUoYNyeKR2b2+BUn0Zt3U/nX8TjVDiPphP5QVolMhm+P9iQeP4c6Sv83pI6MJfHEeXx7vs3tHxca3iCd6lRBFVqaO78sNRq3Xr2G7NzxD0cOHaDRY4fH/rd7Z6E6FlQ6mCnTfzApXzB/Lul5Oubq5l7oPf23W+/FNKdj9evVY8eOHRw6dMhoT+6e3btxdXWlXLlyZscsXbo0Mx4L+85n3vz5pKenM+yLLwy6/zi79+whNzeX1k8s/D3J2evZNK5mTfVQhVHmwXqVlSSmas2mZTf0Dc+mVxsVQT5W3MlrJ5VA3UpKbj/MITnN1JCqV1mJlUzCoXMvz5sFL0+/oOTq2PEL6bRq4Ei9KioOny0I625W2574pFxuRGSZ9Cnom8bHXTwIKaXkxt2CuaJJTXuTueJ1QKcTHq3nMrQmTpzI8OHDjcJBQH845ffff8+3335bLMIJBM/KwoULadGihYmRBXqP1tSpU0lIMH/CfHGTvx9MJpPh7e3Nm2++yZQpU4r9OuZeDI4ePUrdunVp3bo1S5cuZcyYMWRkZODj40O7du2K5W/07sMs/j2QwPvveKHV6bh+O4Malexp29SVpX9FGYXY9ezgSc8OXoyacZOL1/UvqacupHL6Ugqf9vbD1kZKZEw2Tes5USvMgem/3zWs6traSJk+sgx7jybxMEaNOluLn5eSjq3ckcslrNgU/UrkUsglTB1RmjIBNvy+6iEymcQoJb1cJePCDTUXb6rp/bYjNkoJMQka6la2oUpZa+auTzR4mz7s6EjDqjYM/ymO+DzvxYEzGbSoY8unXZ1ZtyuFlDQtb9Sxw8vNihlLCnS4bCk57ZuoOH1FTWxiXjKMECVNa9py+Zaas9dNX6Rq1qpNtWrV+W3OL2RkZuDj7cP+/Xs5ffoUX44YZVgdnj1rJnt272LBwqV4eHqiUqkIC6tiMp6dnQqNRmNS9+GHAxj91UjGfjOGTp26IJFI2LjhT1JSUuj1vvnU2Lm3r5Bz5yq2rbuRqbBGmxiHokJN5GUqkr5lscFFZ/tmLxSV65AydxzaFOO/af3ZWTKz2QMBcu/fIjcyApuGbyGRK8i9dxOJ0gZlzabInN1I37LEpM+5a5mcv57JgE6u2FhLiX6UQ8PqdlQrb8vs5bEGvRjU1Y0mtVQMmfLAYCT9dzyV1g0d+LKPByu3JZCcpqF1Awd8PORGhxA7qKSM+8QbJwcZc9c8wlElw/GxMNb4pFyL3i331o2R2dlgZa83aFXlg/F6V5/hLnb7frSZWYTNn4Lv+x3ZV64lmff0+6kfLP6TwIE9qL56Nte+nok6Np7AgT2wKxfE8dbGqfuvjf6BOjsWUWPNbCJ+X4XSw5XQKV+Scuk6D5b8ZdS2Rq3aVK1Wg7lzfiYjMwNvb18O7P+PM6dPMmzEaIOO/TzrB/7bvZP5C5cbdKxyWFWT+7Ozs0Oj0RjVXb50kXVrV1KvXkM8vbzJycnm9KkT/Lv9b8KqVKN2HdPz2mrVqkW1atX4dc4cMjIz8fH2Zt/+/Zw6fZoRI0YY5Ppp1ix2797NooUL8TTofphFuczVgT7boLu7OzVq1DBbn8+l2zlcvp1NrzZ22CglxCbqPVyVyyhYsDnVMFf0ftOOemFKxvyWREKK3hg5fF5NsxrWfPyOig17M0jN0NG0hhJPFxk/rTafEKJhFSXxyRou3366BCslTb+g5OrY2asZnLuWwUdd3B+bK1RUr2DHrGXRhrlicHcPmtW2Z/DEu8TlzRV7jqXQtqEjw/t6sWJrvOHAYh9PBePnPDT+nTgXHCvh5aaPfqhXVf/7iY3P5db9l2tEPw2650tu/v8Vz2VoTZgwgYEDB5oYWhkZGUyYMEEYWoJXxtatWy3WVa9e3bAJtajNqObO3XpaAgMDn3rD/tO0tSRL06ZNi+w7evRoRo8eXWibF+GXZfd5lJhD+xbuODtaEfMom7krH7Jlt/HGfYlEgkwmMQmzmPhzBH06efP+u97Y28l4EKVm6m8R7D+eZGiTk6Pj9r0s2jZ1xd1FjkIuJTE5h/PX0pj0Swz3zKTC/V/I5ewop1xp/Zfa4F7GmR9Bf1bWHxuT+Xl1Ip1a2PPuG/bY2UiJepTLnHWJHL9YsKoplZAnR0H/XA1MX5xAt9b2vP+WIwq5hHtROcxclsD1iIIV76RULVotdGiqMuwXio7PZcN/qWw/nG5xU/aYb8axbOliVi5fRmpqKn7+/owYNZomj60Ma7VatFotuufcgl2+QkWmTJvB8mVL+OF7vTegXGh5pk3/nvLlLR/+mfbXfGyatMemcTsk1rZo4mNI27TQyMOFRIJEKjOb2UAZVh9N0iNyIyxlwNWRuuZnrOu0RBFaHevaLdDlqNE8iiZ17a/k3r5ittcPi2Lo/pYzXds6obKV8TAmm5+WxXLkbIGHSyrN+10+1i9XAxN/i6JXexf6veuKUi4hIjKbqfOjuXKrQA/8PBWGF6ah73uYXH/djkTW/5tkVrZKv47DNrBAD306t8Wnc1sA/gtuTubdhyCTIrWy4nFF02bncKx1H8pPH0HFWd8gs7Uh5fxVTrQbQMLBk0bXSDhwgpNvf0TZ8Z9Ra9PvaDIyif1nH1dHfYc22/SFffQ341mxdBGrli816NjwUV/TuJh0zNnFBZlUytrVK0hJSUYikeDt40uP9/vwzrudTLLB5TP2m29YunQpy5cvJzU1FX9/f0aNGkXTxzxc+XK9CFeuXOH+/fv06NHDoiyPM/evVDo2taV9Y1vsrCVEx2uYvymVk1cK/t6lUpBJTeeKmatS6NTMlu6t7FDIJdyPyeXntamE3zP1hJXxtcLbzYqtBzOe+qmXRP2Ckqtj3y2Iokc7V7q/6YLKTj9XzFwSzeEzBR6u/Lni8ckiNxfGzYnkg/au9O/kjkIuIeJhNpPnRnLlprEnrFKIDZ/28jQqG9FPn4Xxv+Mp/LoyFsGrR6J76hROBUilUmJiYnB3N3at/vfff3Tt2pW4ONPUuAKB4PWlde9zr1qE1w7PAM+iG70CxvYpmTH+butmvGoRzPJR7IhXLYJZ+vza5lWLYJbga7uLbvSKkFMydX/aWqdXLYJZOo6r/6pFMEtJ1bHRs1+9B8kcG34uvr3mz0r4rXsvbeyyZQJe2tjFyTN5tJydnZFI9Ku/ZcuWNVoF1mg0pKWlMXDgwGIXUiAoSQwcOJAVK1aYrevVqxe///77/1gigUAgEAgEAkFJ45kMrVmzZqHT6ejXrx8TJkww2gejUCgIDAykXj3TeFWB4P8n8vcomqO4E10IBAKBQCAQvI6IA4uf0dDq3Vu/eTkoKIj69es/87lCAsH/D3h4eODhYbp/QiAQCAQCgUAgyOe5kmE8nhI1MzOTnBzjTYpiVV8gEAgEAoFAIPi/i/Bo8Xx5FzMyMhgyZAgeHh6oVCqcnZ2NPgKBQCAQCAQCgUDwf5nnMrRGjBjBf//9x2+//YZSqWTBggVMmDABHx8fli1bVtwyCgQCgUAgEAgEgtcIHZKX9nldeK7Qwa1bt7Js2TKaNm1Kv379aNSoEcHBwZQqVYqVK1fSs2fP4pZTIBAIBAKBQCAQvCbodK+PQfSyeC6PVkJCAkFBQYB+P1ZCQgIADRs25MCBA8UnnUAgEAgEAoFAIBC8hjyXoVW6dGkiIiIAqFChAuvWrQP0ni4nJ6fikk0gEAgEAoFAIBC8hojQwec0tPr27cv58+cBGD16tGGv1hdffMGIESOKVUCBQCAQCAQCgUAgeN14rj1aX3zxheH/zZo149q1a5w6dYoyZcpQpUqVYhNOIBAIBAKBQCAQvH68Tp6nl8VzGVqPk5WVRUBAAAEBAcUhj0AgKIHkqrNftQivHUobxasWwSzhoU1ftQhm8Tg+51WLYJYhSs9XLYJZvIbsftUimOVmaItXLYJFZDbPFcTz0vmmW7lXLYJZsq4JHXsWxl45/KpFEJRAnmvW0Wg0TJo0CV9fX1QqFbdv3wZg7NixLFy4sFgFFAgEAoFAIBAIBK8XYo/WcxpaU6ZMYcmSJXz33XcoFAWrtpUrV2bBggXFJpxAIBAIBAKBQCAQvI48l6G1bNky5s+fT8+ePZHJZIbysLAwrl27VmzCCQQCgUAgEAgEgtcPnU7y0j6vC8+1R+vhw4cEBweblGu1WnJycl5YKIFAIBAIBAKBQPD6on2NQvxeFs/l0apYsSIHDx40KV+/fj3VqlV7YaEEAoFAIBAIBAKB4HXmuTxa48aN4/333+fhw4dotVo2bNjA9evXWbZsGdu2bStuGQUCgUAgEAgEAsFrxOuUtOJl8Uwerdu3b6PT6Xj77bdZu3Yt//zzDxKJhG+//ZarV6+ydetWWrZs+bJkFQgEAoFAIBAIBIJn5rfffiMoKAhra2tq1KhhNjrPHIcPH8bKyoqqVas+8zWfydAKCQkhLi4OgNatW+Pl5cXNmzfJyMjg0KFDtGrV6pkFEAgEAoFAIBAIBP9/UZKSYaxdu5bPP/+cr7/+mrNnz9KoUSPatm3LvXv3Cu2XnJzMBx98wBtvvPFcz+CZDC2dTmf08/bt28nIyHiuCwsEAoFAIBAIBALBy+bHH3/kww8/pH///pQvX55Zs2bh7+/P3LlzC+338ccf06NHD+rVq/dc132hY9KfNLwEAoFAIBAIBAKB4GUeWKxWq0lJSTH6qNVqs3JkZ2dz+vRpk8i7Vq1aceTIEYvyL168mFu3bjFu3LjnfgbPlAxDIpEgkUhMygQCwf9NZDIJPTp606apOy5OcqJj1WzeGcumf2Oeqr+1Ukq/rn40qeuCg8qKe5GZrNkcxd6jCYX2+2lcKGHlHdj0bwy/LL5bIuX6+7S+TCmHjk1sqVleiZ2NhOh4DduPZnLySnaRctjbSujU3JbKwQoUcgkPYnLZdCCDaxG5hjaujlKmf+JscYxLt7KZvTbVpFymsiPk68E4VAnFoWoFlO4uhE/8hRuTfi1SLgCFuwuh00fg+WYzZLbWpFy4xvVvZxG/95hJW9fm9Sg3YSgOYaFoMrKI+Wcv1776nuw4888zIyuL39duY/exM6Skp1PKx5Pe7VvRqn7NQmXatv8oE39fYbbun7lTcXNyNCrLzFKzbOsudh45TfSjBGyslYQE+DC6fw8CvD1MxsjKzGDzqjmcOrKT9LQUvHwDafNuX2o3bFOoXFfOH+PfjUuIvH+L9NRkbGxV+AQE06rD+1Su0cikvTorkx0bF3Py0L8kxEWhtLbFNzCE9wd+g6dPKZP2mZmZrFi2mMMH95OamoKffwDvde5G4ybNCpXrSVYsXcS6tasIKBXIr3MXGNWNGTWMSxcvmPSpVqMmEyZNNzteSdUxmZ0tIWOH4vVOG+TOjqSH3+b2TwuI/uufImVye6MBZUYNxqFKBbTZOSQeOUX4uB9Ju3bTqJ1ELqfMyIH4dG2PtY8H6uhHRK3fxs0Zv6HNMv8yKFFa49ShJ7Y1GyCzU5ET/ZDkHX+RcfJQkXIpy1XCsW0nFH6BSBRKch/FkHZoF6l7t4NOa3wdhRKHNu9iV6shVi4eaNWZ5Dy8S/zy38iNjTIZW+jXs89hWZkZrF0+n2OH/iMtNRUfvwA6dHqf+k1aPJVs+axdPp+Na5fiFxDED78Zz22nTxzm2MH/iLgdTuSDu2g0GtZsO/xM47/OTJs2jQkTJhiVjRs3jvHjx5u0ffToERqNBk9PT6NyT09PoqOjzY5/48YNvvrqKw4ePIiV1XPlDgSe0dDS6XT06dMHpVIJQFZWFgMHDsTOzs6o3YYNG55bIIFA8PowtF8pWjZyY/G6B1y/nU7NMEc+6R2ArY2UVZtMv7CfZMKXIZQrbceC1fd5EJVF8waufDM0GIn0Fv8djjfbp0NrD3w8rV8buQa9Z0+gtxUb9mUQk6ChdgUlH3W0R0IqJwoxtqxkMKyHA7bWEtbuSiclXUezGtYM7erAT6tTCL+nN7aS07RMW5Js0r9qWQVt69twNtz8NRSuTgT070LKhWvEbNlNwIddinwu+UgVcursXILc0YHLw6aQHRtPqUE9qf33Ao637kvCwZOGti6NalF72x/E/rOfU+8ORuHhSujU4dTZuYTDdd5Dm2169uKoH//gyu27fNKtAwHenvx7+CTf/LIYrU5Hmwa1ipTv24G9KOXjZVTmpFIZ/ZyRlcWgSbN5lJjMB+1bERLgS1pGJhdu3CYr2/wzm/vdl9y9eZl3en2Gp08pThzczoIfR6PT6qjTuK1FedJTk/HxL0PDFu/g4OxKRmoK+3f+yS9TPqPf0MnUbfKWoW1WZgYzvx1AcmIcbd7pi29gCJnpady+fp5sdZbZ8adNHs+NG9fp3ac/Pr5+HNi3hx9mTEGn1dKk2dPtK7h96yYbN6zHydmy0e7l5c2wkaONylR2KgutS66OVVv5M47VKhE+/kfSb0bg3bkdVRfP5LxUQtT6vy3K5PFmc6qt+oXYv//j7PtDkTuoKPPVJ9T+dzlHm3Yh8859Q9sqi37AvVVjbs34jeQzl3CqXZUyIwaiKh/MmW6fmB3ffdBXKEoFk7RxGTkxkdjVboz7gOHESaRknDhgUS7r8mF4DB2H+sYV4pf/hi47C5uw2rh0G4CVuxeJaxca2kqU1nh+OQmZowspOzaQ/TACqY0tytKhSBRKs+ML/Xr2OWzm1DHcDr9G9z4D8fb15/C+Xfz8/Ti0Oi0Nmz5dPoOI2+Fs27AaRycXs/Unjx7gxvXLBJYJQS6Xc/vm9ae+//8VL/Ng4dGjRzNs2DCjsnz7xBJPOod0Op1Zh5FGo6FHjx5MmDCBsmXLvpCcz2Ro9e7d2+jnXr16vdDFBcbExsYyduxYtm/fTkxMDM7OzlSpUoXx48cbYkOPHDnC5MmTOXr0KJmZmYSEhNCnTx8+//xzZDIZABEREQQFBXH27FmTDCkdO3bEycmJJUuWANC0aVP2798PgFwux9/fny5dujB+/Hgjhb158yZTpkxh165dxMXF4ePjQ926dfnyyy+pWVO/ymzJu7l69Wq6dev21M+hXLly3Llzhzt37uDr62tU97i8CoWCUqVK0adPH0aNGoVMJmPfvn00a1awyubm5kbNmjWZPn06VapUKfLaRY2fT6tWrdizZw+HDx+mbt26JuOcPXuWqVOncuDAAZKTkwkICKBJkyaMGDGCsmXLmv0dpaam8vbbbxMdHc2uXbvw9/cv9Jnu2LGDpUuXFno/Op3uqfTqeSjlZ0PbZu4sWvuAddv0K0Lnr6TiYG9Fz3d82LorltR0jcX+tas6UjPMkck/32TvEf2q4LkrqXi6K/m4pz/7jsSjfSI62dNdQf9u/kz/7TYTvwwp8XJVKiOnYmkFf2wqMKqu383F1VFKpzfsOHk1G0sR2A2rKPHzsGLa0mRuP8zN65vDuP6OvNfMlmlLUwDI1cDtyFyT/u80s0WdrePEZfNGQ+bdh+x01xstclfnZ3pJ8e/XGYdK5TjcqCtJx84BEL/vOI1ObyZ0+giONCgYq/yMkaSHR3Cm62foNPrnnhnxgPoH1uDXtxP35q02Gvvw2Uscv3iNSUP60rqBfm6pWbEs0Y8S+GXlRlrWq4FMWnjUe2k/HyqUMfX8PM7va7cR8TCaVTO+xtfTzVDeuGaY2fYXTx/k6vlj9P9iKrUb6Y2q0Mq1iI+L4q9lP1GrQSukj80Rj1OrYWtqNWxtVFa5ZiPGDGzHwV1/GRlam1fNIfrhHb79cR3uXn6G8qq1m5od+9TJ45w7e5ovR46hSdPmAIRVqUpsbCyLF82nYeOmRnOXOTQaDbN/+p42bdtx584tUlJSzLZTKJWEhlYodKzHKYk65taqMW7NG3C+35dE/an3YCUcPIFNgA/lJo0g6q/toDX2AOVTduKXpF4O52zPTw1licfP0fjMdkK+/pQL/UcC4FirCl4dWnFt9HQi5izNk/0outxcyo4fhmuz+sTvNQ5Xsq5UA5sKVYn7YyYZJ/WZ0NTXL2Hl6oHze731Xi2debns6jUHjYbYXyajy9Z7y7KuXkDu5YuqfnMjQ8upQ0/kXn5ETfyc3EcFHv7M8ydNxgWhX/Dsc9jZk0e4ePYkn44YT4Mm+kzcFcNqEBcXzcpFc6jf6A2Lc0U+Gk0uv8+ayhttOnD3zk1SU5JM2nz06SikeXPhorkzS6ah9RLTuyuVyiINq3zc3NyQyWQm3qvY2FgTLxfo38dOnTrF2bNnGTJkCABarRadToeVlRU7d+6kefPmT3XtZ9qjtXjx4qf6CJ6P9957j/Pnz7N06VLCw8PZsmULTZs2JSFB/7K3ceNGmjRpgp+fH3v37uXatWsMHTqUKVOm0K1bt+feMzdgwACioqK4efMm3333HXPmzDFyvZ46dYoaNWoQHh7OvHnzuHLlChs3biQ0NJQvv/zSaKzFixcTFRVl9OnYseNTy3Lo0CGysrLo3LmzwRi0JO/169f57LPP+Oabb/jhhx+M2ly/fp2oqCj+/vtvEhMTadOmDcnJpqv+zzP+vXv3OHr0KEOGDGHhwoUm/bdt20bdunVRq9WsXLmSq1evsnz5chwdHRk7dqzZa8bFxdGsWTPS0tI4dOgQ/v7+hjpLz3T27NlGZebaQtF69bw0qOmEVCphx75HRuX/7nuEtVJGrapOhfZvWMuZjEwN+48Zy7FjXxxuLgpCQ0xXMocNCOL0xWQOn0x8LeSqVlZBllrHqavGxs6RC2qc7aWU9rG81lWtnIKoeI3ByALQ6uDYJTWlfeU4qSxP3+5OUsoGWHHqqpqs7OLfS+vZoQVp124bXlAAdBoND1dtwbl2FZQ++rA7pY8HTrXCeLhys+EFBSDx6FnSrt/Bq4NpGM2+k+extVbyRt1qRuXtmtQjLjGZyzcjXlj+LHU2m/ce5o261Y2MrMI4e3wvSmtbatQ3PsKkQfP2JCXEcefGxWeSwcpKjq2dPVJpgQ6o1Zkc2rORGvVaGhlZhXHsyCFsbGxo2KiJUfkbLVuTEB9P+PVrRY7x57rVpKWm0qt3v2e6h5fJy9Ixz3YtyE1NJ3rjv0blD1dswNrHEycLhrbcxQlV2dI82mWcDjrrfiSpV27g8dYbkPfS61xHr7txO429ULE79ullaG96DI5ttTposzLJOG0c+pV2eA9Wzq4og8wvLAGg0aDLzUWXYzzPaDPS0eUUeFskCgWqhi3IOH3EyMgqDKFfzz6HnTx6AGsbG+o2NA6tbNriLRITHnEj/EqR8m1ev4K01BS6ffCRxTbSIhacBAUoFApq1KjBrl27jMp37dpF/fr1Tdo7ODhw8eJFzp07Z/gMHDiQcuXKce7cOerUqfPU137+oENBsZKUlMShQ4fYt28fTZroJ7RSpUpRu3ZtANLT0xkwYADt27dn/vz5hn79+/fH09OT9u3bs27dOrp27frM17a1tcXLSx9mExAQwKpVq9i5cyfTpk0zhIuGhIRw8OBBoz/sqlWrMnToUKOxnJycDGM9DwsXLqRHjx40adKETz75hDFjxph4dR6Xd8iQIWzevJlNmzYxatQoQxsPDw+DLDNnzqRhw4YcO3aM1q2NV5WLeh7mxl+8eDHt2rVj0KBB1K5dm1mzZhnCZzMyMujbty9vvvkmGzduNIwZFBREnTp1SEpKMrne/fv3admyJd7e3mzZsgV7e3ujekvP1NraGkdHx0LbFqVXL0KQvy2JyTkkJhuHTdy+l5FXb1Nk/3sPM00Wj2/fyzT0vxKeZih/s5k7oWXs6De88BfakiSXr7uMqHiNiQfsQaz+C9vHXcath6beKH2dFTfvm4akPN43Kc38CneDKkqkEgkHz5vfC/Ki2FcMIeHQaZPy1Iv6FVX7CiGoI2Oxr6gPuUi5aLrSmnrxOs71q5uU33oQRaCvF1ZPrPgGB/jo6+9HEla2dKHyDft+LkkpaahsbaheIYSPO7ejjL+Pof7qnXtkqrPx93Jn+sLV7Dp6msysbIIDfPmo01s0rF7JZMzIezfx9gtCJjP+2vQrpb/Hh/duUSa0aqFy6VdEtaQmJ3Bg51/ERN3l3fcL5tB7t66izsrEwzuAlfOmcPLQv6jVmfiVCuHtroMIq2m6n+vu3Qj8/ANMvApBQaXz6u9QvkJFizLdu3eXdWtWMvqb8djYFP63ER0VSY8u75CRkY6HhyeNmjSjS7eeT72q/Cy8LB2zrxBCWvgto5dmgNRL4QCoKoSQdOKcyVhSuRwArZmwUm12NlZ2ttiWDiDjZgRShfm2+SFm9pXKmYyh8AkgJ+q+iTct50EEAHLfUqhvm/dYpB7YgV3tRjh360/KP3+izc7GtkotbKvVIXFjwb4eRUAwUmsbcmKjcOnxMba1GiFVKsl+cJfkravJvGj6vIV+Pfscdv/ubXz9Ak3mioDAMob6cuUrW5Ttwb07bFy7lGFjpmBtY/v0N1UCeZmhg8/KsGHDeP/996lZsyb16tVj/vz53Lt3j4EDBwL6UMSHDx+ybNkypFIplSoZfw94eHhgbW1tUl4UwtAqIahUKlQqFZs2baJu3bomE8vOnTuJj49n+PDhJn3ffvttypYty+rVq5/L0Hqc8+fPc/jwYQIDAwE4d+4cly9fZtWqVWZXT5ycnF7oeo+TmprK+vXrOX78OKGhoaSnp5uEAprDxsaGxETLHo78yT0nx/Sl9Wl4fHydTsfixYuZM2cOoaGhlC1blnXr1tG3b18A/v33Xx49esTIkSPNjvXk87p+/TojRoygevXqrF27tti/UIrSqxfBwd6K1DRTIyFLrSU7R4uDqvDpxcHeisgY0z0n+WM+3t/NWc7HvfyZv+o+8YmF/x5LklwqGylxSaZhiumZ2rx6y19CKhsJ6Zmm3qj0LF2hfSUSqF9ZSdSjXG49MG/EvSgKVydyEk09xNl5ZQpXJ6N/zbdNQp5X/zjJqen4erialDuq7Az1lnB1dKBvxzZUCgnEzsaaW/cjWbp5J/3Gfs8fE76kbCm9lyguIQmAZVt2ERzgw/hBvZFIJKz8ew9f/vA7s0YNpl4V4xCmtNRk3D1NvUy2KgcA0lOTLMqVzy+TP+XyOX3ImLWtio+GzTAynhITYgHYsWkJvgHB9P1sEhKJlF1bljNn2lA+++ZXKlYzXn1NTUnB09vb5FqqvAWbVAthWqA3/H7+6Xvq1W9IzVqFr9BWqFCJho2b4ucXQHa2mtOnTrDhz7VcuXyJKdN/KPbV9ZelY3IXJzIi7pu0ze+vcHEyqQNQxz4iOyEJpzrGL9ZWjvbYlw8x9M0A0q7dAsCpbnUy7z40tHWuW93iNaQqe3LjTL1M2gz9oo7Uzt6kLp/sOzeImTkWt49H4tBMH4aq02hI2ric1F2bDe1kzvq9Po5t3iH74V3iF88GnRaHlh1w/+RrYn+eSNaVc0ZjC/3S//ssc1hqagqeXj4m5Sp7/VyRlmI5ukar1fL77KnUqt+EarVMPS2C56dr167Ex8czceJEoqKiqFSpEv/88w+lSunDzKOiooo8U+t5EIZWCcHKyoolS5YwYMAAfv/9d6pXr06TJk3o1q0bYWFhhIfrV9vKly9vtn9oaKihzbPy22+/sWDBAnJycsjOzkYqlTJnzhxAn3Ulf/ynoXv37iYrXxcuXKB06cJXoAHWrFlDSEgIFSvqV8e6devGwoULLRpaWq2WnTt38u+///L555+bbRMfH8+ECROwt7d/Zi+OufF3795NRkaGwTPWq1cvFi5caDC0nvV5ffDBB9SvX5+//vrLYpz7izzTovTKHGq12jRFqi4bqUxh+DF/0bWwoLQXPf3h8f6f9w/k1t0M/t4TZ9RGIjFE65QouYzaFzZWUdd6jrpKpeU4O8hYv8eyQVIsFPIgTcKYLbW1UF5YNtvC6upVrUi9qgWr69XLh9CgWiV6jJzC/PXb+GG4fuVSm3dduZUVs0Z9gp2NPolJzYplee+L8SzauN3E0NJf3OKl9cpYBN36jyQzPY2kxDiOH/iH+T+Oou+nEw17vnR5rk8rKyuGjv0Vaxu9cVmuck3GftKBbev/MDG09GI93/PavPFPoiIf8s24SUXK/mTYV81adfDw9GLxgnkcP3aEevUbFjnGM/OydOxZxn2sz70/VhE8ajBlRg7i/qK1WDmoCJ0+GqmtXn90eRNQ3K6DpN+6S7kJX5IdG0/ymYs41apC2XGfo83NNbQzcxGLchVWpwgog/vg0ajvhJOwYi7a7Cysy4Xh1KEnErmC5L/X6RtK9JOlLjeX2NkT0eUlV8m6fhGfSXNxbNfFxNACoV+FtrVU/pxz2N+b1hAd+YARY7+z2OZ1wpKmvyoGDx7M4MGDzdZZ2q6Sz/jx481mNCwKEeBZgnjvvfeIjIxky5YttG7dmn379lG9enWjX76lLwFLmVOehp49e3Lu3DmOHj1Kly5d6NevH++9957R9Z527J9++skopvXcuXNG+40KY+HChUYJVnr16sWGDRtMwu1+++03VCoV1tbWtG/fnl69epmcceDn54dKpcLNzY2rV6+yfv16PDxM0zWbo7DxFy5cSNeuXQ2pPrt3787x48e5fl0fVvCs++Q6dOjAoUOH+Ouvvyy2eZFnCk+nV48zbdo0HB0dDZ+wsDD2rG3IrlW1DZ8qFexJSc016x2yVkpRyKWkphfuTbHU3z6vLL9/4zrO1KriyPxV97GzlRk+AB1aeZZIuaysJNgoJaRnaVHZmE6zdnll5jxW+aRl6sx6reysJYX2bVhVSa5Gx9GLLydsECA7Pgm5mVV5hbM+lDUnIdnQDrDQ1snQ7nEc7e1ITjM1EvPLHFTPFkrj4+5KlXJluHQjouAaed6xsLJBBiMLwFqpoFr5EK7dMfV4qOwdSU81lTcjTb+ib6dyNKl7Ek+fUgSGVKRq7aZ8PPw7QivXZtUf09HmvXir7PVjlClXxWBkASiVNpStWIN7t033w9g7OJCaaupVSEtNzRvTvCckLjaGlSuW0q3HB1hZyUlLSyMtLQ2NRoNOqyUtLc3imTT5NG2m359y/drVIu/9WXlZOpaTYH5cef64ZjwX+dya/hsRvy6hzIiBNL99mMbn9Pu8Hq7Qh4lnReo9UrqcHE6/9xFZD6KotXkhLe6foOqyWdyeOZ/cpBSyImNNxtampZr1Wklt9XtCtelpJnX5uPT4CE1KEnG/TSfz4inU1y+RvGUVyTv+wvHtrli5eeZdQ68n6lvXDEYWgC47G3X4ZRQBZUzGFvqVBDzbHGZv72DWa5WW9xzt8jxbT/IoNpr1KxfwXvd+WFlZkZ6WSnpaKlqtBp1OR3paKtlFPDNByUN4tEoY1tbWtGzZkpYtW/Ltt9/Sv39/xo0bx6xZswC4evWq2Y17165do0IF/Qps/r4dc8kfkpKSDG7SfBwdHQkODgZgxYoVVKxYkYULF/Lhhx8a0lpevXrVJIOhOby8vAxjPQtXrlzh+PHjnDx50mivlUajYfXq1QwaNMhQ1rNnT77++muUSiU+Pj5mPUEHDx7EwcEBd3d3HBzMT2qWsDR+QkICmzZtIicnx+gkcY1Gw6JFi5gxY4bheV27du2pMvqNGTOGsLAwevbsiU6nMxv6+bzP9HEs6VWfPn1M2ppLmfrxqHNIZXLDz/cjM7lTNoPmDVxxdpQb7YfK3wN1535moTLdvp9B8/quSKXG2xJKP9E/0N8WKyspcyZb3gfw+/K7nL+aVmLkaveGB+3egMu3synja4VUgtE+LV8PvU5FxlnOfvgwNhdfd1Pdzu/7MM7UYLS3lRAWrOD8jWxSM17egfKpl8JxqGSa8tY+ryz18o28f8PzyssRt+OASdv8+scJ9vdh55FT5Go0Rvu0bt2PBDDaa/W06HQ6JNICozUkwLewxkjNLCz5lgrhxMEdaDS5RnsvHtzT36uvmZfUoggKqcTls0dIS0nEwckV31KWEx7odDqkUlO5SgUGcXD/XjQajdFcGBFxR19fKsjseNHRUWSr1fwxbw5/zJtjUt+jS0fe7vAuAz42v/r7OC/jPM2XpWOpl8Px7vQWEpnMaJ+WKm8vTtqVGxZl0mk0XBszgxtTfsGmlC858UmoY+KoufEPMu7cRx1ZEPqXcfsex1p0R+ntgdzZkYw795E72FP+u69JPHLKZOzsh/ewq92IJyceuZ/++zrnoel5gfko/INIP3HQJCthdsRNJFIZcm8/ch/FFDoGEsxmWxT69exzmH9gGY4c2GUyV9yPuK2vL2U+GiUmOpJstZql82exdP4sk/oPu7WhbfvO9P7o86JvsIRQkvZovSqER6uEU6FCBdLT02nVqhUuLi7MnDnTpM2WLVu4ceMG3bt3B8DZ2Rl3d3dOnjRO15qZmcnly5cpV850I24+crmcMWPG8M0335CRkUHVqlWpUKECM2fONKy6Po655A7Pw8KFC2ncuDHnz5838tyMHDnSJLNfvmHo7+9vMdwuKCiIMmXKPLORVdj4K1euxM/Pz0TGWbNmsXTpUnJzc2nVqhVubm589515t7+55/XNN98wadIkevbsyerVq007vQTy9cocSqUSBwcHo8/Nu9mE3043fDKztBw+lYRWq6N1E+Osba2buJOl1nDyXFKhMhw+mYitjYzGdYzPCGnVxI1HCdlcu6Ffwf13fxzDJl41+QAcOpHAsIlX+fdAfImT6/sVyRw6r8ZaKaF6qMJorHqVlSSmas2mZc/nbHg23m5WBD2WmVAqgbqVlNx+mENymqkhVa+yEiuZhEPnXu6qZ/Tm3ajKl8GpdkH4qUQmw7dHexKPn0MdpV+xV0fGknjiPL493zaK8XSqUwVVaGmiN+0yGbtprSpkZKnZ+0RCgr8PHMfd2ZGKwYHPJOvD2EdcCL9NpeCCF0I3Z0cqhwRx/vpt0jIKDO8sdTZnrt6kUojpy2PVOs1QZ2Vw5ugeo/Kje7fi5OJOUIjlze3m0Ol0hF8+ja2dPXZ5niwnF3dKlwvj5rXzZGYUeDDU6kzCL58mqKzpNerVa0hmZiZHDhm/BP63eycurq6ULWc+jDmodDBTpv9g8gkqXQYPTy+mTP+Bt97uUOg9/Ld7JwDlQs2HtL8IL0vHYrbtxsreDs8OxmcZ+fboQFZkDEmnTA/NfRJNegZpV26gjonDoUoFXJrU5e7vy822VUfFknblBtrMLIKG9iM3LZ0Hy/40aZdx7hhSaxtsqxsv0KnqNSM3MR71HcsGYG5SAorAYENoYD7KMvrv+txE/dl/muREsm5dQxlcHol1QWIKiUKBsmwl1HdMjQahX88+h9Wq15iszEyOH95nVL7/v+04u7gRUtZ8CvvA0iGMnfqLyadUUDDunt6MnfoLrdt1Koa7F/wvER6tEkJ8fDydO3emX79+hIWFYW9vz6lTp/juu+/o0KEDdnZ2zJs3j27duvHRRx8xZMgQHBwc2LNnDyNGjKBTp0506VJw7sPw4cOZOnUqnp6e1K9fn8TERGbMmIGVlVWR55/16NGDMWPG8NtvvzF8+HAWL15MixYtaNy4MWPGjCE0NJS0tDS2bt3Kzp07DedOgd6QePKcAnt7e5NDrR8nJyeH5cuXM3HiRJNsLv379+e7777j/PnzT3UO1stk4cKFdOrUyUTGUqVKMWrUKP7++286dOjAggUL6Ny5M+3bt+ezzz4jODiYR48esW7dOu7du8eaNWtMxv7qq6+QyWS8//77aLVaevbsaah7nmeaT1F69SLcfZDJ9r1x9O7ki0ar4/ot/cHAb73hzuJ1D4zOqnr/XR/ef8+X4ZOvceGqPuTkxLlkTl1IZuiHgdjayIiMzqJZA1dqV3Vi6i+3DB6gmLhsYuLMnwX1KDGH81dSS6Rc4ff0DRtWyaZXGztslBJiE/UHFlcuo2DB5lRDeH/vN+2oF6ZkzG9JJKToFzQOn1fTrIY1H7+jYsPeDFIzdDStocTTRcZPq81vQG9YRUl8sobLt58u8Yt768bI7Gywstfrkqp8MF7v6vcfxm7fjzYzi7D5U/B9vyP7yrUk857eq/Rg8Z8EDuxB9dWzufb1TNSx8QQO7IFduSCOt+5rdI1ro3+gzo5F1Fgzm4jfV6H0cCV0ypekXLrOgyWmIbP1q1akTuVQZixcQ3pGFn5e7uw8coqj568w8ZPehjO0Js1bwT8HjrNh1ni83fXJMz6Z8jPVQoMJDvA1JMNYvnUXEomEgV3aGV1naK93GTRpNp9Nn8MHb7dEIoGVf+8hKTWNjzu3M5GrcvWGlK9Sl5Xzp5KVmY67lz8nD+3g8tkjfDh0iuFcnKVzxnN07zam/LYFVw+9923OtM/xCyyLf1A57OwdSU6I48jerYRfPk2PAaONVr079/6Cmd9+xOyJg2n9Tl8kEti1ZTlpqUl06G66+l+jVm2qVqvB3Dk/k5GZgbe3Lwf2/8eZ0ycZNmK0YbHo51k/8N/uncxfuBwPT09UKhWVw6qajGdnZ4dGozGqu3zpIuvWrqRevYZ4enmTk5PN6VMn+Hf734RVqUbtOpa99yVNxx7tOsij/w5T4advsbJXkXH7Lt6d3sK9ZWPO9x9h8OpU+nUyPj06cKBKa7LyvKkuDWvhUL0yaZevg0SCY40wgj7/kEe7D3F33kqj6wQN/RB17COy7kei8HDD6502eLZ7gwsfjTK8xD9O1qUzZF45h0vPgUitbcmJi8KuVmNsKtXg0YIfDd4q1w+GYFevGQ+/HogmQb83NHX3Vly6D8BjyNekHvgXXbYa69AwHFp1IPPKOUPmQoCk9Yvx/HIynkPHkfzvRtDpcGjZAZnKnrjNq0zkEvr17HNYtZr1qFytFgt/+4HMjAy8fHw5vH83508fY8iX3xrmit9nT+PAnu3MXrAOdw8v7FT2VAwzzWJoa2ePRqMxqYuLjeZWuH5xLyZaf1/HDu3VPxdPL8qEFL+B+qy8zHO0XheEoVVCUKlU1KlTh59++olbt26Rk5ODv78/AwYMYMyYMQB06tSJvXv3MnXqVBo3bkxmZibBwcF8/fXXfP7550bu9eHDh6NSqfjhhx+4desWTk5O1K1b1xBSVxgKhYIhQ4bw3XffMXDgQGrXrs2pU6eYMmUKAwYM4NGjR3h7e1O/fn1DSGM++UkhHmfatGl89dVXFq+3ZcsW4uPjeeedd0zqQkJCqFy5MgsXLuTnn38uVO6XyenTpzl//jx//PGHSZ29vT2tWrVi4cKFdOjQgQ4dOnDkyBGmTZtGjx49SElJwd/fn+bNmzN58mSL1xgxYgQymYzevXuj1Wp5//33ged7pvk8jV69CLMX3eVRYg7vtPbE2UlOTJyaOUvvself4+xZEqkEmUxisj943MwbfNjNjz6dfbFXWXE/MovJs2+y9+iLnfFVkuSa+1cqHZva0r6xLXbWEqLjNczflMrJKwVGmlQKMqmxHLkamLkqhU7NbOneyg6FXML9mFx+XptK+D1TT1gZXyu83azYejCjyCQb+VT6dRy2gQWZ9Hw6t8Wnsz4xw3/BzfUZ02RSpFZWRpu7tdk5HGvdh/LTR1Bx1jfIbG1IOX+VE+0GkHDQ2JOecOAEJ9/+iLLjP6PWpt/RZGQS+88+ro76zpDu+klmDBvA3LVbmffnNlLSMijl48nkT/vSqn7NAhm0WjRardG9lvH3YdfR06z8ew9Z2dm4ONhTs2JZ+r3bllLexodShpUtzZyvP+X3ddv4ds4S/fMIDuT3bz+3mD5+0MiZbFr1K5tXzyUjLRkv30D6D5tG7YZtjOTSajXGcoVW5czR3ezdvpasjHRs7OwJLFOBIWN+NknZXia0Kl9MmMfmVXNYOEv/N1q6bBjDJ/5BmXLmF5tGfzOeFUsXsWr5UlJTU/Hz92f4qK9p3KQgkZBeLi26p9aOApxdXJBJpaxdvYKUlGQkEgnePr70eL8P77zbqdCMcCVRx872/IyQb4cS/PWnKJwdSQu/zbm+XxL91z+GNpI8mR7/m9Rm5+DVoRV2IwYiVSrIuHWXm1N+4e7vK0zC7qTWSsqMGoS1jxfazCySTp3nxJu9STxqmlI8n7i503Hq2BPHDt2R2dqTE/2AuD9+0B9WbBhYikQmM3pWqXv/JjcpHocW7XH94BMkcgW58bEkb11Lyu4tRtdQ375OzE/f4tShJ24ffpFXFk7MD9+QbSF9vNCvZ5/DvhwzlTXL5rN+5QLSUlPw8SvFZyMmUL9JwblbWq3GsP/qebh84TS/z5pqVDZr+jcANH6jLYO/+Oa5xi1OROggSHTP+xsWCAT/Z3ij24lXLcJrR+mwZ9+z87+g47iSmTK44XHTfRwlgXPKkvm8vKzjX7UIZrkZanqAa0lBZiYxTUmgfDfL4fyvkqxRv7xqEcxSUnXM58rhohu9AqqFPN2h7C+Dw1csJ3F5URpUUL20sYsT4dESCAQCgUAgEAgExYoIHRTJMAT/I9q2bWs4PPfJz9SpU4seoBg4ePCgRRlUqtdjZUQgEAgEAoFA8HogPFqC/wkLFiwgM9N8Wm0XFxez5cVNzZo1OXfu3P/kWgKBQCAQCAT/l9GKzUnC0BL8b/D1LeTcmv8RNjY2L3welUAgEAgEAoFA8DQIQ0sgEAgEAoFAIBAUK2KPltijJRAIBAKBQCAQCATFjvBoCQQCgUAgEAgEgmJFnKMlDC2BQCAQCAQCgUBQzIiTekXooEAgEAgEAoFAIBAUO8KjJRAIBAKBQCAQCIoVrUiGITxaAoFAIBAIBAKBQFDcCI+WQCAQCAQCgUAgKFZEMgxhaAkEgqdAKpO9ahHMIpGWXKe8QlEyn5nMpmQ+Myt12qsWwSyJGuWrFsEs/tbZr1oEs5RU/QLQZGpftQhmUadmvWoRzKJA/apFMEtJ1bFktd2rFkFQAhGGlkAgEAgEAoFAIChWRNZBsUdLIBAIBAKBQCAQCIod4dESCAQCgUAgEAgExYpOZB0UhpZAIBAIBAKBQCAoXrQidFCEDgoEAoFAIBAIBAJBcSM8WgKBQCAQCAQCgaBYEendhUdLIBAIBAKBQCAQCIod4dESCAQCgUAgEAgExYpI7y48WgKBQCAQCAQCgUBQ7AiPlkAgEAgEAoFAIChWtCK9uzC0BALB8yOTQfcO3rRu7IqLk5zouGy27Ipl8864p+pvrZTSt7MPTeo6Y29nxf2oLNZsiWbfsUSjdh1bu9O8vgs+ntbYWEtJSs7l8o00Vm2O4e7DLPNytfeiVSMXXJzkxMRls2V3HJt3PXpqufp08qZJHWfs7WTcj8pi7bYY9h1LMparlTvN6jnj46k0yHXlZjorN0Ub2ijl0K6hDdXLybGzlhCToGXn8SxOX88pUg6VrYR3GttQqbQVCrmEB3Eath3K4vq9XOP7lUKbetbUriDHSSUlJV3HyavZbD+aRU6u+bFldraEjB2K1zttkDs7kh5+m9s/LSD6r3+KlMvtjQaUGTUYhyoV0GbnkHjkFOHjfiTt2k2jdhK5nDIjB+LTtT3WPh6oox8RtX4bN2f8hjZLbXH8jCw1c/76l10nL5CSlkmgtzt932pK67pVC5Vry8FTjF+43mzdzlnf4OZkb/g5JzeXBVv+4+8jZ4hNTMHNyZ62dasyoEMLrBVys2Oos9L5d/3PXDi+g8z0ZNy9g2j69gCq1nuzULluXDrCvm0LiXlwk4y0JKxt7fHyC6Hxm30IrdrEbPudf/5C1L3ryBXWlK/WlDe7fYnK0dXs+JmZmSxdtoyDBw+SmpqKv78/nTt3pmkT07ELY+nSpaxZu5ZSpUrx+9y5hvKYmBj69O1rsV+NGjWYPGmSSXlJ1TGZyo6QrwfjUCUUh6oVULq7ED7xF25M+rVIuQAU7i6ETh+B55vNkNlak3LhGte/nUX83mMmbV2b16PchKE4hIWiycgi5p+9XPvqe7LjEkzaSpTWuHXtjX3dxkjt7MmOvE/ilnWkHt1fpEw2FcJw6dgNZUBppEolObHRJP+3g6SdW0GnLbiGlRynNh1waNwCubsXWnUm6js3id+wiqwbV82Ordev5Rww6JcfXZ5Dv5YsXWbQr3lzfzOUR8fE0KdvP4v9atSozhQz+gUlV8eyMjPYvPpXTh/ZRXpaMl6+gbR5px+1GrYpVKar54/x76bFRN6/TXpqEja2KnwCgmnZ/gMq12hk0l6dlcm/Gxdz8vAOEuKiUFrb4lsqhF4Dx+LpU6rIZyB4+YjQwRJAnz59kEgkSCQSrKysCAgIYNCgQSQmFrxsBgYGGto8/pk+fToAERERhv4PHz40Gj8qKgorKyskEgkRERFGdUuXLqV27drY2dlhb29P48aN2bZtm1nZLH0Ka9emTeGTypNMnToVmUxmuK/HWbJkidHY3t7edOnShTt37ph9Tra2tlSqVIl58+Y91bWfZnyAVatWIZPJGDhwoNlxUlJS+PrrrwkNDcXa2hovLy9atGjBhg0b0OUFLDdt2pTPP//cqN/s2bNRKpWsWrUKKPyZ7tu3r8jfy5IlSwCYN28eVapUwc7ODicnJ6pVq8aMGTOe6pkUxWd9A+j+thdbdsUxesYNDp9KZPD7/nRv7/VU/cd/UYaWjV1ZviGKMd/f4PrtdL7+tDTN6jsbtXNQWXHifAo//hHB6Ok3WPZXJMGlbPl5fFn8vJQm437a259u7TzZuvsRY767xeHTSQzq5Ue3tz2fSq5xQ4No2ciFFRuj+PqHW1y/ncGYT4JoVs9YLnuVjJMXUvhp4T1Gf3eLZRuiKFPKhp/Hl8XDWT+9DuhgR92KcrYfyWLOX+ncjc6l39t21Aw1/zKfj5UMPuusolyAFX/uzWTepnRS03V88p4dwX4yo7Z929nSoqaSw+ez+e2vdA5fUNO8hpJ+7ewsjl9t5c/4du/ArelzOP3eRySfuUTVxTPx7vxWoXJ5vNmcGn/NJzsugbPvD+XKF+OxLVOK2v8uxybI36htlUU/EPRZPx4sWcfpTgN5sOxPAof0oeqSHwu9xvBflrPt8Bk+6tCCX77sR8UgP0b/vprtR88W2i+f8R92Zsk3g40+jipbozaj565m2fb9vNu0Dr8M68s7jWux4t+DfPXbSovjLp81lDMHN9PincH0GzEPv9KVWT1nOGePbLPYByAjLRlP32De7vUV/Uct4N2+45HKrFj8wyDOHNpi1Pb21ZMs+n4gKkdXPvjiV9q/P5obl47yx7R+5OZkmx1/0uTJ7Nmzh549ejBp4kTKhoQwY8YM9u7d+1TPC+DWrVv8tWEDzs7OJnXOLi78+OOPJp/OnTsDUL9ePbNjllQdU7g6EdC/C1Klgpgtu4t6NEZIFXLq7FyCW7N6XB42hVPvDkYdE0/tvxfg0qiWUVuXRrWove0P1DHxnHp3MJeHTcGteX3q7FyC1Iwx7zNsLA6NWhD/10oezvgG9e1wvD8bjX39poXKZFupGn5fT0MilRHzxywiZ04k48oFPPoMwv39j4zaeg4Yilv3vqSdOsrDH8YRu2gOMgdH/L/9HusyZc2OP2nyFHbv2U3PHj2YPHECZUPKMn3Gd+zdu++pn1uBfjmZ1Lm4uPDTjzNNPl06dwKgfr36FsctqTr2+/fDOLZvK+26fMxnX88hMLgiC376ihMHCzcA09KS8fYvQ+e+wxn67Vx6DhyLTGbFr1M/5dj+v43aZmVmMPPbDzn830aavdmdod/OpfeQCQSFVCY723QB8lWg0728z+uC8GiVENq0acPixYvJzc3lypUr9OvXj6SkJFavXm1oM3HiRAYMGGDUz97e3uhnHx8fli1bxujRow1lS5cuxdfXl3v37hm1HT58OL/++iuTJ0+mY8eO5OTksGLFCjp06MDs2bMZMmQIs2fPNjJ6vL29Wbx4sVkDKv8eHkepNH0JLozFixczcuRIFi1axFdffWVS7+DgwPXr19HpdFy7do2PP/6Y9u3bc+7cOWQy/ctn/nNKS0tjyZIlDBw4ECcnJ7p27Vrk9Z9m/EWLFjFy5Ejmzp3Ljz/+iK1twQtcUlISDRs2JDk5mcmTJ1OrVi2srKzYv38/I0eOpHnz5jg5OZlcd9y4cXz//fds3LiRN98sWB239Ezt7OyIiooylA0dOpSUlBSjto6OjixcuJBhw4bx888/06RJE9RqNRcuXODKlStFPouiKOVrTZsmbixeH8n6v2MAuHA1DQeVFT06erNtTxyp6RqL/WtXcaBGZQem/nqbvUf1iwrnr6Th6abko+5+7D+aaDjscNlfUUZ9L1xL4+rNdBZ+X5Hm9Z1ZtqHAg6SXy5Ulf0ax/p9YQ3sHlRU9Onjx93+PCpWrVr5ccyIMnrXzV9PwdFMwoJsP+48VyLX8sesCXLwGV2+ls3BGBWpVUBARmUv5QDmLtqVz+preg3Xjfi4uDlLeaWLD6es5Fr8w6lVW4Osu44eVqdyJ0ssbfi+XMb3teaeJDd+vTAMg0FtGtbIK/tqbyX+n9aur1+/lotVCh8Y2hJay4tpdY7eWW6vGuDVvwPl+XxL1p/6LP+HgCWwCfCg3aQRRf20HrRZzlJ34JamXwznb81NDWeLxczQ+s52Qrz/lQv+RADjWqoJXh1ZcGz2diDlLAYjfdxRdbi5lxw/DtVl94vceMRn/0PlrHLt8g6kDu9Mmz4NVq3wZouKTmLX2H1rVqYJMWvgaYbCfFxWC/CzWX7h5l/9OX2JYt7fo1aYxAHUqhiCTyfj1zx0cuxRO3UrGL53Xzu3nxqUjdB/8PVXr61/iylSoQ9KjSP5Z/QNV6rZFKpWZXAugSt22VKnb1qisfLUmTP+iFSf2rqd6w/aG8r9X/4CbVyl6fTYLmUz/Fe3s7sfciT05uX8D9Vp0MxrnxMmTnD17llEjR9K0aVP99apUISY2loWLFtG4cWPD3GUJjUbDjz/9xJtt23L7zh1SUlKM6hVyOeVDQ036LVmyBKVSSZO86z5OSdaxzLsP2emuN4rkrs4EfNil0OfzOP79OuNQqRyHG3Ul6di5vGsep9HpzYROH8GRBgVjlZ8xkvTwCM50/QydRv83nBnxgPoH1uDXtxP35hV8v9tVrYVdWA2ifplO6pF9+rZXLmDl5oF7z/6kHj1g5Jl6HIcmLdHlanj4/bfo1Po5IOPSWRTefjg0aUncst8BvTfLvkEzUg/vI37d0oLnEX6FMnNXYd+gOVm3wo3GPnHyJGfOnmXUyBE0e0y/YmNjWbBoEY0bN3pK/Zr1zPq1OE+/mjY17zkrqTp28fRBrp4/xoefT6N2I/3ffbnKtYiPi+KvZT9Rs35rpBaeWa0GranVoLVRWViNRowZ9BYHd/1F3SYFBuTm1b8S/fAOY2eux92rYL6rUqup2bFfBSK9u/BolRiUSiVeXl74+fnRqlUrunbtys6dO43a2Nvb4+XlZfSxszNese7du7fJi/mSJUvo3bu3UdmxY8eYOXMm33//PcOHDyc4OJjy5cszZcoUPv/8c4YNG8b9+/dxdHQ0uh6Ak5OTSdnj9/D4x9zqqCX2799PZmYmEydOJD09nQMHDpi0kUgkeHl54e3tTbNmzRg3bhyXLl3i5s0CV3/+cwoODmby5MmEhISwadOmp5KhqPEjIiI4cuQIX331FaGhofz5559G/ceMGUNERATHjx+nd+/eVKhQgbJlyzJgwADOnTuHSqUyaq/T6fj000+ZPXs2O3fuNDKywPIzVSgURmU2NjYmbW1sbNi6dStdunThww8/JDg4mIoVK9K9e3cmWQjDeBYa1HRCKpXw737jcLx/98djrZRSs4pD4f1rOZGRqWH/ceMwwX/3P8LNRUFosGVvDEBSit5w0TzxPVq/hqNergPxxuMeyJMrrAi5ajiSkanhwIkn5DqQ8FRyJafojRqtVkeVEDlZ2TrOPhEmePRSNk72UgK9Lb+gVAmWEx2vMRhZAFodnLiSTaC3FY4q/RdYGV/9y/jlO8bXuHRb/3PVENOVc892LchNTSd6479G5Q9XbMDaxxOnmmFmZZK7OKEqW5pHuw4alWfdjyT1yg083noD8owg5zrVAIjbafx3HLtjn16G9i3NXmPv6UvYWitoUauyUXn7RjWJS0rh0q17Zvs9C+dv3AWgQZjxy12jKvqf95y6ZNLn0qk9KKxtqVzH+CWoZuN3SEmM5d7NC88kg8xKjo2dPVJZwXpnckIMD25fpHqD9gYjCyCwbDXcvAK5fMrU+3L0yBFsbGxo1Mg4rKhVy5bEx8dz/fr1ImVZt24daampJt8ThREZFcXFixdp3KgRdra2JvUlWcdeBM8OLUi7dttgZAHoNBoertqCc+0qKH08AFD6eOBUK4yHKzcbjCyAxKNnSbt+B68OLYzGVdWqjzYzg9RjxveSsn8XVi5uWAeXsyiTLjcXXW4Oumxjj6c2Iw3dY15QnU4LOi3ajHTjdpnp6LQao7b5HDlyFBsbGxo/oV8tW7Z4av1au249qamp9On9QZFt89Hr1yWL+gUlV8fOnfgPpbUtNeob19Vv1oGkhDju3Lho4a7NI7OSY2tnb2TQZqszObxnI9XrtTQysgQlD2FolUBu377Njh07kMsLDy0yR/v27UlMTOTQoUMAHDp0iISEBN5++22jdqtXr0alUvHxxx+bjPHll1+Sk5PDX3/99Xw38JwsXLiQ7t27I5fL6d69OwsXLiyyj42NDQA5OZb3u1hbWxda/yzjL1q0iLfeegtHR0d69eplJKNWq2XNmjX07NkTHx8fk7FUKhVWVgUvT7m5ubz//vusX7+e/fv307Bhw+eSsTC8vLw4duwYd+/eLfaxA/1sSEzOITHZ2Fty534mAEF+NkX2vxeZZbLgePtepqH+SaQSkFtJ8PdWMmxAIInJOex8wqAK9LMhKcWcXFl59dbPJVf+fZnrbyRX/wASk3M4eikbbzcZ0fEagwcsn8g4/YuXj5tlQ8vHTUbkI1PP28O8Mm9XfV9Z3iye+0TT/J993U2vYV8hhLTwW0YvgACpl/Sr2aoKIWZlkubNSdps0xcybXY2Vna22JYO0LdVmG+rzdb/LdlXMv/iePNhDEHeHlg9seIb4u9lqC+KoT8tpmbfr2j6yXi+/GUZNx8Yex5z8u5bITcO6sj/+cYDYw8qQMyDG3j4lDEygAC8Asoa6otCq9Wi0eSSkhjLzr9+4VFUBI3a9jHUR+eN4R1gGsLlHVDWUP84EXfv4u/vb+JVCAoKMtQXxt1791i9Zg2fDBlimO+ehp07d6LT6WjdurXZ+pKsYy+CfcUQUi6aGhepeWX2efdlX1H/O7TUNr8+H4VfINkP75t4YNT39KHrSv9AizIl7/4biZUcj96DkDm7ILW1w77hG6hq1Sdx62N7FjUaknZtw6FxC+xq1kNqY4uVmyeeAz5Hm5FB8n/bTcYuLv0aMuST59KvNhb0C0qujj28dwtvvyCTucKvVEhe/U2TPiZy5M0VSQmxbFnzGzFRd2nZ/n1D/d1bV1FnZeLhHcDKeVP44oNGDO5akykje3DxtOki9atCq3t5n9cFETpYQti2bRsqlQqNRkNWlv6F8McfjeN/R40axTfffGPSr+ljYRtyuZxevXqxaNEiGjZsyKJFi+jVq5eJ0RYeHk6ZMmVQKBQmsvj4+ODo6Eh4eLhJ3dPcw5Myjx07tsi+KSkp/PXXXxw5onfB9+rViwYNGvDLL7/g4GDeA/HgwQO+//57/Pz8KFvW9MUkNzeXFStWcPHiRQYNGvRM92JufK1Wy5IlS/jll18A6NatG8OGDePmzZsEBwfz6NEjEhMTCTUTAmGOP/74A4Dz589b7PMizxT0IYnvvvsugYGBlC1blnr16vHmm2/SqVMnpEWEXxWFg72V2RC8LLWW7Bwt9qrCpxcHlRVRsaYbiVPTcw3jP8nWRdVQKPRy34/MYvjUG8QlGBvRDioZqWmW5XIoUi4ZUXGmX8CpabkGuZ9ky4IqBXJF6eWydvfBzlpCfLJp6Ep6lv5bws7acliFnY2E9EzTb5OMvDI7G33f6Hj9vZb2kRldK9/Tld/uceQuTmRE3Dcpz0lMBkDh4mRWJnXsI7ITknCqU92o3MrRHvvyIYa+GUDatVsAONWtTubdgn2jznWrF3qN5LQMfN1dTMod7GwN9ZZwdbTnw7ebU7lMAHY2Sm7ej2bJP/voPWkOi78eRNkA/QJI6Tyvw7kbEUbXOhseYfEaGWlJuLj7m5Tb2jkZ6oti8fcDCb+oXwRT2qjoMeRHylcrCIvKH8NG5WTS18bO0ew1UlNS8PL2NinPDytPfSJM63G0Wi0//fQTDerXp3atWhbbPYlGo2H37t34+/tTsWJFs21Kso69CApXJ8M9PE52/n25Ohn9a75tEnJXY9lk9vbkxEabtNWkpQIgtbfsic+6dZ0Hk0fh8/nXOLXWh6HqNBoerVlM4t8bjNrGLZuHNiMdny++QZIX6poTF8ODyaPIiTFdYNDrl+me23z9SklJtSiXXr9mPad+7cHf34+KFStYbFdSdSw9NQk3T1Mvk529o74+zVQnnuSXKUO4ck7/PmRtq2LAsO+oXKOxoT4pQR8W/++mJfgGBNPn08lIpRJ2bVnOnGlD+fTrOVSsZnlvm+B/hzC0SgjNmjVj7ty5ZGRksGDBAsLDw/n000+N2owYMYI+ffoYlfn6+pqM9eGHH1KvXj2mTp3K+vXrOXr0KLm5FlKPWUCn0xkSXTzrPTyOi4vpC5M5Vq1aRenSpalSpQoAVatWpXTp0qxZs4aPPirYzJucnIxKpUKn05GRkUH16tXZsGGDkcGYb5Cq1WoUCgUjRoww67kzR2Hj79ixg/T0dNq21cdcu7m50apVKxYtWsTUqVMNiS6e9rk1bNiQc+fO8c0337BmzRojb1c+L/JMQb+n7ujRo1y6dIn9+/dz5MgRevfuzYIFC9ixY4dZY0utVqNWP2EA6bKRygqesWHR9QV3pBbWW2dm7KETriG3kuLtoeS9th58PzqE0d/dNGQezJerMLGeSuRn7P/5xHCsrCT4eCp5t7Vert82ZhY1VKF1Tyvj5Tu5xCZq6NjYhtQMHXejNQR5y2jfyBqNVmf5fgt5EOaefX6fe3+sInjUYMqMHMT9RWuxclAROn00Ulu9p0+X90uI23WQ9Ft3KTfhS7Jj40k+cxGnWlUoO+5ztLm5hnbmKOxPqLC/rgZh5WgQVrDCXKNcaRpVCaXL2J+Yu3EXPw3tbWjn7+nKz+u24+qgomKQPxdu3WPOnzuQSaWW/4YL/dMu+u++Q+8xZKankpoUx5nDW1n16zC6fDzNsOerqJEsyVXYlQubjzZs3EhkZCTjx40rQnJjTp8+TXx8PB07diy8YQnWsRfiWe6rkPt8lnELq1MGBePz5bdk3bxO8oKf0aqzsK1YFdcuHyCRK0jYuMrQ1uWd7ji/1Yn4P1eSee0SUltbnFq9je+YqTyc9jXqiFsm40sK0bDC/lY3bNzIw8hIxo/71nIjM5w6fZpH8fH072g5E6GBEqpjhf3dFfY88+n24SgyM1JJTnzE8f1/88ePI+kzZJJhz5cub7+elZWcz76Zg7WNPqS9XKVajB3Snr//nF8iDK3XKWnFy0IYWiUEOzs7goODAfj5559p1qwZEyZMMNpL4+bmZmhTGJUqVSI0NJTu3btTvnx5KlWqxLlz54zalC1blkOHDpGdnW3i1YqMjCQlJYWQEPNu96e5h2dl0aJFXL582cjY0Gq1LFy40MjQsre358yZM0ilUjw9PU32qEGBQWpra4u3t/czGYyFjb9o0SISEhKMkl9otVrOnj3LpEmTcHd3x9nZmatXzafIfZLKlSszc+ZMWrRoQZcuXVi7dq2J5/FFnunjVKpUiUqVKvHJJ59w6NAhGjVqxP79+2nWrJlJ22nTpjFhwgTDz6VKlTLJVvnl5OukpOZSOsA0FMRaKUUhlxo8QJZIScs16x2yt9OXmfNK3YzQGy9Xb6Zz624GC76ryLyp5Q31w6fcICVNQ5lSpuFyBrnSi5JLg73KTLhdnqzm+t+8q5fr2q0Mjp5JZskPFWjfyIb0LJ1Zr1V+WUaW5W+h9EydWW+UbV5ZvldMo4Xf/krngzdt+bSz3vupztax5WAmbepZk5Rm+iKQk5CE3MxKrNxZv+JqbhU+n1vTf8PKzpYyIwYS8s1ngH6/wsMVG/Hv05msSH1ony4nh9PvfUTY/BnU2qwPsc1NS+fGxFmUGTmIrMhYs+M7qmzNepRS0vVlDirz+zUs4ePuQtWQQC4+trdLbmXFL8P6MXb+Wgb/oJfNRqlgSKc2/LFlDx55z+FxbFVOZJhZic5IT8qrN+3zJG5egYb/V6jRnIXffcSmpZMIq9sWqVSKbZ4ny5znKjM9GRs702vYOziQkmrqVUjNK1M9kTApn9jYWFasWEHfPn2wsrIiLU2fXEWj0aDVaklLS0Mul5tNaPTvzp1YWVnR4o03LN5rSdaxFyE73vx9KfLvKyHZ0A6w0NbJ0C4fTWoqMpWp10qm0v/+tGmWPUcefT9Bk5xE5MyJhoQZmVcugE6La6eepB7+j5zYaBQ+/rh2ep9HqxaS+HfB1oD0cycJ/H4+7r0+4sHkUUZjF6VfTybkyic2NpblK1aa1S9dMegXlFwds7N3Ij01yaQ8PVUvj62Z3/OTPJ6avUqtpvw8+RNWL5hGzQatkUql2OXNFWXKVTEYWQAKpQ0hFWpw7sS+Iq8h+N8gDK0Syrhx42jbti2DBg0yu9+nKPr168fgwYNNvCH5dOvWjZ9//pl58+aZeM5++OEH5HI577333nPJ/qxcvHiRU6dOsW/fPiNvTVJSEo0bN+bSpUtUqlQJAKlUWqTh8bQGqTksjR8fH8/mzZtZs2aNUaiMVqulUaNGbN++nXbt2tG1a1eWL1/OuHHjTH5v6enpKJVKI2OyatWq/Pfff7Ro0YLOnTuzfv3659qb9yxUqFDBII85Ro8ezbBhw4zKBo25gFRaINf9qCzu3M+kWX0XnB2tjPZDBfnrja87DzILlePO/Uya1XNBKjXelpDfP6KI/g+j1dyISMfe1opJv+r3MTyIUueN62wiV/7eqogHhae9jXiQSdO6zmbkerr+mVla7kdl4eFuy80HudQsr0AqMY4pz9+bZW4PVj6RjzRm93Dll0U91jcuScvMVWk4qiTYWUuIS9Jio5TQ+Q1bbj4wE555ORzvTm8hkcmM9jeo8vaNpF2xvN9Ip9FwbcwMbkz5BZtSvuTEJ6GOiaPmxj/IuHMfdWTBHqqM2/c41qI7Sm8P5M6OZNy5j9zBnvLffU3ikVNmxw/28+Lf4+fI1WiM9mndvK8Pqwr2fboU/UYy60D6xIJLgKcbS8d+QmxiMslpGfh5uJKWmcX3K7dQvVyQyRhe/mU5d/RvNJpco70X0ff1z8rT79kWpgD8y1Qm/MIh0lMTsHd0wytvjOj7N0zO14q+f8NQ/ziBgYHs378fjUZjtI/mTt7iSGAp82fpREdHo1ar+X3ePH43cwRG5y5d6NChAwOfiAZISkrixIkT1KlTx2wG1XxKso69CKmXwnGoZBqqbp9Xlnr5Rt6/4Xnl5YjbccCkbX59Pur7d3Co35QnJ578vVnq+xEWZVKWKqPPVPhEVsKsW+FIpDIUvgHkxEajLFUaiVRK1u0ntgVoNKjv3camvHECGoCgwFLs23/ARL8iitCvqCL0q1OXrnTs0IGBHxunn9fr10nqFqFfUHJ1zDcgmJOHdpjMFfl7s3wDnv39JDC4IpfPHiYtJREHJ1f8AguZb3QglZaMbH86cWCxSIZRUmnatCkVK1Zk6tSphrLU1FSio6ONPk+mSc1nwIABxMXF0b9/f7P19erVY+jQoYwYMYKZM2dy69Ytrl27xjfffMPs2bOZOXMm/v6m+xEKQ61Wm8j36FHRB8QuXLiQ2rVr07hxY4PnpVKlSjRs2JB69eo9VVKMl83y5ctxdXWlc+fORjKGhYXRrl07g4xTp07F39+fOnXqsGzZMq5cucKNGzdYtGgRVatWNazqPU5YWBh79+7l6NGjdOrUiezHNt0+7zPNZ9CgQUyaNInDhw9z9+5djh07xgcffIC7uzv1LJx9o1QqcXBwMPrcvJtD+J0MwyczS8uR00lotTpaNTI+RLVVY1ey1FpOnbe8NwTg8KkkbG1kNKptnJmyZWNXHiVkc+2meUMwH1sbKZ5uSiIeZnHjTiY37mSSmaXl6JlktFodLRsah1i2apQn14Wi5ErWy1XLyViuhk8nl4NKRqCfDXFJWs7fzMFaIaFqWWPjuU4lBUmpWiKiLBta52/k4OUqI9Cr4OVGKoHaFRTcicwlOd3UG5acpiPykZacXGhRS4k6W8eRi6b7zWK27cbK3g7PDq2Myn17dCArMoakU0Vn0NOkZ5B25QbqmDgcqlTApUld7v6+3GxbdVQsaVduoM3MImhoP3LT0nmw7E+zbZvXqEhGVrZJ5r+th0/j7uRApTIBRcr2OA/jEjh/M4LKFvp5ODsS4u+NjVLBsu37sVEq6NjYdD9JxZpvkJ2VwaWTu4zKTx/chIOzBwHB5jOcWUKn03Hn6ilsbB0MnixHF0/8y1Tm7OGtaLUFunH35nniou5QqVYLk3Hq16tHZmamIQFSPnt278bV1ZVy5cwnhChdujQzpk83+ZQuXRpPT09mTJ9O+yeSKAHs3rOH3NxcWrdqZWbUAkqyjr0I0Zt3oypfBqfaBb9viUyGb4/2JB4/hzpK7+FQR8aSeOI8vj3fNmSwA3CqUwVVaGmiNxnrUdrJI0htbFHVNk6K5NC4BbkJj8i6aTm7X25iPNalQ0Bi/EpnHaL39ufExxnaAVgHG+8JlljJUQYGk5tg+t1Sv179PP06bFS+e/eeQvWrTOnSzJg+zeRTunRQnn5No/3b7Uz6Pa1+QcnVsWp1mqPOyuDMsT1G5Uf3bcXJxZ2gEFODtjB0Oh03rpzG1s7esM/L0dmd0uXCuHntHJkZBe8V2epMwq+cJijk2eYjwctDeLRKMMOGDaNv376MGqV35X/77bd8+61xrPPHH3/M77//btLXysoKNze3QsefNWsWYWFhzJ07l7FjxyKRSKhevTqbNm0yyVL4NOzYsQPvJzZllytXjmvXrlnsk52dzYoVKwz3+CTvvfce06ZNK7YDdp+XRYsW8c4775jd0/Tee+/RtWtXYmJi8PT05NixY0yfPp3Jkydz9+5dnJ2dqVy5Mt9//z2OjubDiypWrMjevXt54403eO+99wwZH5/nmT5OixYtWLRoEXPnziU+Ph43Nzfq1avHnj36L8kX4e7DLHbsf8QH7/mg0UL47XRqVHbgzWZuLFkfaZQoo9c73vR6x5uRU8O5cE3/pXDyfAqnL6bwWd8AbG1kRMZk0ayeC7WrODJtzh2DB8jWRsqM0WX570gCD6OzyM7W4eet5J3WHijkEpZvjDIjVzwfvOuNVgfXb2dQo5I9bzbTn631uFw9O3rRq6MXI6ff5GK+XBf0cn3axz9PLjXN6jlTq4oD0+dGGMk1fVQwe48m8jBaTXaOFl8vJe+00sv1z5FM7sVouBqRQ7cWNlgr9J6mmqFyKgbJWfJ3uiF+vWdrG+pUVDB+QQoJKfrCo5eyaVxNyYft7dh8IJPUDB2NqyrwdJby83pjg71FLSUp6VoSU3XY20qoXk5OlWA5S//JIDnN1CB7tOsgj/47TIWfvsXKXkXG7bt4d3oL95aNOd9/hGFFvdKvk/Hp0YEDVVqTdT8SAJeGtXCoXpm0y9dBIsGxRhhBn3/Io92HuDvP+LDfoKEfoo59RNb9SBQebni90wbPdm9w4aNRhhfSJ2kQFkrdiiFMW7aR9Mws/D3d2HHsHEcuhjP5o26GM7QmLFzPtsNn2PzdSHzc9Mb6wO/+oHq5IEL8vPXJMB5Es/Sf/UiQMOhd45exJf/sw83RHi8XJ+JT0th14gL7zlxm0kddzYYOhlZpTEil+mxcPIGszDTcPAM4d/Qfwi8cotugGYYztNb/8Q1nDm5m5I87cHbT76Fd+uMneAeE4lMqFFuVEymJsZw6uInb107SsfdYo1Xvtl2/ZMGM/qz4+QvqtehGWkoC29f+iJdfCDUbv2siV61atahWrRq/zplDRmYmPt7e7Nu/n1OnTzNixAiDF+KnWbPYvXs3ixYuxNPTE5VKRViY6cuYnZ0dGo3GbB3os8G5u7tTo0YNs/X5lGQdA3Bv3RiZnQ1W9vqwK1X5YLze1We4i92+H21mFmHzp+D7fkf2lWtJ5j29bA8W/0ngwB5UXz2ba1/PRB0bT+DAHtiVC+J4675G17g2+gfq7FhEjTWzifh9FUoPV0KnfEnKpes8WGKc1Tfj/CnSL5zG88NPkdnakh0diX39pthVrUXUrzMM3irPj77AoXEL7nzel9xH+vtL2r4Rjz6D8R0xnqQ9/6DLVmNbsSrOb71H+sUzZOdlLsy8fpmsm9dx7dQLqVJJxtVLyGztcGrdHoWnN1FzvjN5TrVq1aR6tWr8MmcOGZkZRvo1csRwg379OGsWu3fvYfHChXh6eqBSqahiVr9UaDRas3WgDxvU61d1s/WPU1J1rFL1hpSvUpdV86eQlZGGh1cAJw5t5/LZw/QbOsVwhtayOeM5um8rk+dsxdVDHwHz2/TP8StVFr+gcqjsHUlKiOPo3i2EXz5N9wGjjeaKTh8M48dxA5g9aTBtOvYBiT4ZRlpqIu27Dy7y+f0veJ2yA74sJDqLuwUFAoFAT8uep82Wy2TQo4M3rZu44uwoJyYum827Ytm8M86o3fvvevPBez58Ofk6F64WGAnWSin9uvjQuI4L9ioZ9yOzWLMl2nBQMOjTpg/p40/FsircXRQo5FISknO4cDWVNVtjuRdpGsonk0GP9l60auyKs6MVMY+y2bIrjs27jFds33/Hi/ff9Wb4lBsGAzBfrr6dvWlcxxl7Oxn3o9Ss3RrNvmNJRnJ98oEfFcvaGeRKTM7h/NU01myNQemuN5CVcni7oQ3Vy8mxtZYQk6Bl5/EsTj92ttb7bWypW0nB2PkpJKQUhP/Y20ro2MSGSqWtUFhJeBCnYduhLK7fM94n1raekjoVFDjZS8nJ1XEnSsO/x7K49dDUY/b2RL0nU2ZnS8i3Q/F6py0KZ0fSwm9z+8c/iP7rH0PbynOn4tvzHfZXesPwoulUuyqh077CrmxppEoFGbfu8nDlRu7+vgLdE0l3yowajE/39lj7eKHNzCLp1Hlu/zCfxKOm+tTo32mG/2dkqZnz17/sOnGB5PQMAr096PdWU1rnHWAMMO6PdWw9fJpt34/CJy9z4A+rtnLsUjgxCcmoc3JwtldRq3wZBnR4g1Je7kbXm795N9sOnyE2IRmlQk7lMv70a9fcJGxwl1XBopM6K51/183mwvEdZKQn4+FTmqZvD6BqvYLz79bNG8Ppg5sY9dMuXNz1hta+bQu5eGIn8TF3UWemY21rj19QJeq36mmUdTCf8ItH2PXXL0TevYZCaU1o1aa81X04KseCxZEwlwjD/zMzM1m6dCkHDh4kNTUVf39/unTpQtMmBWPP/PFHdu/ezZLFi/H0tBx+OXLUKFJSUvjdTNj5lStX+HL4cHr06MH7vXqZ7R9ercBLUdJ0TJNZ8LfV7MYebAPNnz/0X3BzMu8+JGzhNPw/eNfwcz4KD1fKTx+Bx5tNkdnakHL+KtfHzSb+v6MmY7m9UZ+y4z/DoUp5NBmZxP6zj6ujviM7LsHQJqSTXuckSmvcuvbBvm5jpCoVOZEPSNi8ltSj+w1tPQd+iWOTltz+tDe5jwrC21S1GuD05jsofPyQKpTkxMWQenQ/if9sMBxiDCC1scX57c6oatVH7uaJVp1J9oN7JGxdT8Z54zA4+eRfAb1+LVm6jAMHD5KWmoqfvz9du3Q20q8ffvyR3bv3sGTxIrwK0a8Ro74iJSWFeXN/M6m7cuUKw4aPoGeP7hb1C+B6tYK/yZKkY9ZHzhj+n5WZweZVv3DqyC4y0pLx8g2izbv9qNWwjaHNkl/GcnTfVqbM/Rs3D/1c8e+mxZw5upvY6PtkZaRjY2dPqTIVaP5mN6Osg/ncvHqWzat/JeLmZQCCyobRodtgyoRWNbRpWunp0+oXN38ef0kJaYBOdV6PoDxhaAkEgiKxZGi9aiQvmKL+ZRJSxXSfT0kg39AqaTxuaJUkHje0ShKPG1oliccNrZLG44ZWSSLf0Cpp5BtaJY3HDa2SxOOGVkniVRpa64+9vL+5znVL7vf/47weUgpea1auXIlKpTL7sXQGy8ugYsWKFuVYuXJl0QMIBAKBQCAQCJ4Kne7lfV4XxB4twUunffv21KlTx2zdy86w9zj//PMPOTk5ZusKC6URCAQCgUAgEAieFWFoCV469vb2Fs/a+F9SykIaWoFAIBAIBAJB8aLVifTuInRQIBAIBAKBQCAQCIoZ4dESCAQCgUAgEAgExcrrtJfqZSE8WgKBQCAQCAQCgUBQzAiPlkAgEAgEAoFAIChWhEdLeLQEAoFAIBAIBAKBoNgRHi2BQCAQCAQCgUBQrGiFR0sYWgKBQCAQCAQCgaB40Yn07iJ0UCAQCAQCgUAgEAiKG+HREggEAoFAIBAIBMWKSIYhDC2BQPAUyJWKVy3Ca4fUqmQGDJTrFPKqRTDLf4p2r1oEs1y+8aolMM/fu5xetQhm+aZbuVctgkXUqVmvWgSz3PjzzqsWwSybKju/ahHMUlJ1bOs961ctglmaVnrVEvzfRhhaAoFAIBAIBAKBoFgRyTDEHi2BQCAQCAQCgUAgKHaER0sgEAgEAoFAIBAUK2KPlvBoCQQCgUAgEAgEAkGxIzxaAoFAIBAIBAKBoFgRHi1haAkEAoFAIBAIBIJiRiTDEKGDAoFAIBAIBAKBQFDsCI+WQCAQCAQCgUAgKFZE6KDwaAkEAoFAIBAIBAJBsSM8WgKB4LmRyaDrWx60bOiMi6MV0Y+y2fZfAlv3xD9Vf2ullA/e9aRRLUfs7WTcj1Kz/p84DpxINmpXIcSWlg2cKR1gQ6CvErlcSp8R14iNzynxcink0K6+kuohcmytJcQkatl1Us2Z8NxCZXBSSWheQ4Gfuwxfdxm2SgkrdmZy/Ir5ey7nL+Ot+kp83WRk5+q4fCeXTQfVpGWaX1KUKK1xfrcXdrUaILWzJyfqAcn//EX6iYNFP5/Qyji91RmFfyAShZLcuBhSD+4kZc8/oNMCYOXqgf/3CyyOkXHxDDE/jTdbp85KZ8e6nzl/7F8y0pPx8Ami2dv9qVb/zULlCr94lL1bFxLz4CbpaUlY29rj5RdM07f6Ur5aY6O2V87s4/yxf3l49yqxkXfQanL5YdXlQseXW0HTyhLKB0iwUUB8Chy5quPKvcKXbe1toG6oBE9nCZ5OYK2QsPW4lgt3jPs52sGQt2UWx7kVpWPNfq1JuVIOHZvYUrO8EjsbCdHxGrYfzeTklexC5QKwt5XQqbktlYMVKOQSHsTksulABtciCvTT1VHK9E+cLY5x6VY2s9emmpRLlNY4deiJbc0GyOxU5EQ/JHnHX2ScPFSkXMpylXBs2wmFX56OPYoh7dAuUvduN+iY4ToKJQ5t3sWuVkOsXDzQqjPJeXiX+OW/kRsbZVYut669sa/bGKmdPdmR90ncso7Uo/uLlMumQhguHbuhDCiNVKkkJzaa5P92kLRzq5FcEis5Tm064NC4BXJ3L7TqTNR3bhK/YRVZN66aHVumsiPk68E4VAnFoWoFlO4uhE/8hRuTfi1SLgCFuwuh00fg+WYz/h975x3eZPU98E+SNmnTdO9FyyiUVfYqW5kOQEFkDxkCgigCCqgMWSoooMiQspStLAVZyt57Q1lldNOZtmnaJvn9EZoSkpSiIPj93c/z5OnTO8/75uS+77nn3HtlSgcyz13h6uezSNl9xKKs50sNqDBxOC4R4ehyckncupsrn3xNXnKqRdlnrV8AdjJ4qbYDkREKvFxlaPMN3E4oYMsBDTdibY+VL6qO5WmzObJ1NtfP/EFuTgbuPmWo9fIAytd8tViZrp/bwfUz20i6e4GsjESUKk/8S9ekXpuhuHmHFrWfm8XZ/T9z9+pB0pJuka/NwcUzkAq12lGtSS/s7BWPvf5/A73lcPX/DmFoCQSCv817PQJ5KdKNnzYkEn1LQ60qKt7t6o+jg5S1W5IfW//T90oRVlrJ0l8SiE3U0qyeG58MKoVUcoc9R4uMmuoVVVSvpOLGHQ05Gh3VKqr+M3L1f01JiK+MzQdzSUrTU7uCPX1fUSKR5HDyqu0XCC83KbUr2BObrOfSrQJqh9vbLFsuUMbgDkouxhSw8LccnB0ltGvkwLCOMr5elU2BzrKO73tjkJcOI+2XZeQnxqGq1wSfQaNIkkjIPrrPZl8OlarhN2ICuVcvcn/pXPR5uSir18Wz20DsvP1IXWU0rgoyUombPMqivrJmPdxe6UTOqcM2+1j27QfcvXGBV7p+iLdfCKcPbWHF96MwGPTUbPiazXo5Wen4BZWlXvOOOLt5kZOVweFda4j6ejBdh0ynVqPXTWUvnPiT29fPEhhaETs7OfduFW9kAXRqJMXfA3afNZCqNlA5RMIbkVIkEj0Xb9s2ttydoXKIhMR0uB5voEqIxGq5LA0s2Wn5ZVUIlBBZScrVe9b7GNzRmVB/O9bvySExVUfdSgoGdnBGgppjxbwM28lgRDcXlA4S1uzMJjPbQPNaDgx/24VvV2USfceonxlZeqYtzbCoX728nLaRjpyOtt6H9+BPkIeUI33DcvIT43Cq2wTvASNJlkjJOVaMjlWMwGf4eLTXLpHy0w8Y8nJxjKiLR5cB2Hn7kbYmylRWonDA96MvkLl6kLltPXmxMUgdlSjKhCORW3/ZDBjxGQ5lynN/9RLy4u/h0rA5/u+PAYkE9aE9NuVSVqlB4JjJaC5fIPHHWRi0Wpxq1cenz2Dsff1JXj7fVNZ3wHCcGzUnddNaci6eQebkjEf7zgR//jV3J4wg90a0RftyTzdK9e9M5rkrJG7eRal+nW3K8ihSuT31dizF3tWFiyOmkJeUQsjg7tTdsoijrfuSuv+4qaxH4zrU/f1Hkrbu5cSbQ5D7eBI+dST1dizlYL2O6PPMJ3OetX4B9HpFRb3Kcv44rOFKTD5KRyltGzgysocLXy7PJCbe+lj5ourY1sXDSLp7gcjXRuDmHcrVU1vY/tNHGAx6KtR63WodgFN/LkLp4kXtFu/i6hmMOj2BE7sWsHrmm7w1fA2e/mEAqNPiOLN3GeG121G9WV/sFUribpzg6PbvuXP1EB0GL0YisT7OCP5dhKH1P0hSUhKfffYZf/zxB4mJibi7u1OtWjUmTJhAgwYNADh06BCTJ0/m8OHDaDQawsLC6NOnDx988AEymXFGNSYmhtKlS3P69GmqV69u1keHDh1wc3Nj6dKlADRr1oy9e42zgfb29gQHB9O5c2cmTJiAQlE0EF2/fp0pU6awc+dOkpOTCQgIoH79+nz00UfUrl0bwObgsGrVKrp06VLi+1ChQgVu3brFrVu3CAwMNMt7WF65XE5ISAh9+vTh448/RiaTsWfPHpo3b24q7+XlRe3atZk+fTrVqlV7bN8Pty+RSPD29qZJkybMmDEDJycnqlSpwvvvv8/YsWPN6nXu3Jlbt24RHx9PbGyszfabNm3Knj17CA0N5fbt2xb506ZN45NPPgHg119/5auvvuLKlSvo9XpKlSpFmzZtmDlz5mOvozhKBSho1did5esT+XXbfQDOX83GWWVHl9d82LonlaxsK2/4D6hd1ZmaVZz5csEd9j4wXs5dycbH0553Ovuz71iGaceiVb8lsXJzEgBvtvYq1tB6keSqFGpHxRA7lv5RZFRdu6fD3UVKh8YOnIrOshnDfuOejrELswAI9pEWa2h1aOxAUrqeqN81JtlSMjWMeNuJ+pXtOXDO/MXJsWotHKvUIGnBDJNRlXvlPHaePnh07kv2sQMWM7qFODd8GYNOR+LsLzDkaY11L53F3i8Q54YvmwwtCgrQ3rxqUd+9Y0/02lyybBhzl0/vI/r8IboP/YoakcbZ33KV65F2P57fV86keoO2SKXWvT7VG7SleoO2ZmmVajRl6getOfLXOjNDq1P/iUilxuj59UsmP9bQKusPZfwkbDikN3mwbicZcHUy8HI1CZfuGGx+l3eSYNZG4/30d4cqIdbL6fQQZ8Xp2jxCYvRSWjHmqpS1p3IZOT9uLHrpvXq7AE9XKZ1eduL45TybcjWqpiDIx45pyzK4+cBrcPV2PuP7u9KxuZJpyzIBKNDBzTjLF903mivR5hk4dtHyZduhSi0cK1Un+ceZ5Bw3ekm1Vy9g5+mDe8feRo+DDR1zavAS6HQkfTe5SMcun8PeLxBV5EtmL8Fu7btj7xdE/KQPKLifaErXnD1u0S6AU/U6OEXUIv676SajSnPpHHZePnh374/68D6bcrk0bYmhQEfs159j0BrlyrlwGrl/EC5NW5oMLYmdPc4Nm6M+uIeUtcuKZIq+RNl5K3Fu+JJVQ0tzO5Yd3nUAsPd0fyJDK/idt3CpUoGDjd8m/cgZAFL2HKXxyU2ETx/FoYZFbVX8cjTZ0TGcevt9DDrjWKiJuUfkvtUE9e3EnQWrTGX/Df2yk0HdynKOXsxj416Nqf6Nu/nMGO5BvSpyq4bWi6pjMZf2cjf6EK17zqB8TePEUFBYfdSpsRz87WvCarxicwx7rf88lM6eZmlBYfVY9kULzuxdxstdJgPg4hFEn8/+xF6hNJULDquPvcKRg5u/Jv7WKQLK1LLax7+JWKMl1mj9T9KxY0fOnj3LsmXLiI6OZvPmzTRr1ozUVGNIwIYNG2jatClBQUHs3r2bK1euMHz4cKZMmUKXLl0w/M1fxoABA4iPj+f69et89dVXzJ07lwkTJpjyT5w4Qa1atYiOjmbBggVcunSJDRs2EB4ezkcffWTW1pIlS4iPjzf7dOjQocSyHDhwgNzcXN566y2TMWhL3qtXr/L+++/z6aefMmPGDLMyV69eJT4+ni1btpCWlkabNm3IyLCc2S2u/djYWDZt2sTdu3fp0aMHXl5eLFy4kIkTJ3L+/HlT+V9++YXffvuN5cuXc/r0adN1//rrr2ayxMfHs379elO9SZMmWdyrYcOGAbBr1y66dOlCp06dOHbsGCdPnmTKlCnk5T0+5ONxNKjpglQqYeeBNLP0nQfScFBIqV2leK9TZE0XcnJ17D9ufj93HkzDy92eCmWKHiBPopIvklzVytqRm2fg9CNhgkcv5eGmkhLqZztMrKSX7OokIcRPxvHL+WZb6d6K15GYqiOirKWB5lSzPvrcHLIfCa9RH/wTO3dPFGXK25ZLVwAFBRjyzXVIn5ONId96WGMhdt5+OFSoQvbxAxhyNVbLXDixC4WDkoh6rc3S6zTtQGZaEneunyu2j0eR2dnjoHS2eLEpNLJKSoUgCdp8A5fvmn8zZ28acFZKCPB4ouZKjJsKQnzg8h0DeVYm9WuUl5OrNXDisvn3ceicFndnKWUCbM+n1qggJz5FZ3oJBuN2zEcuaCkTaI+byvY98naTUr6UHScua8nNs9RWZY166HM15Jw8aJaeVahjpcNsto1Oh6EEOiaRy1E1akHOyUNmL8DFoaoTiV6Tg/qIuaGfuXcndh5eOJSrYLOuoaAAQ0E+hrxH5coyk9Vg0INBjz4n27ycJhuDXmdxXU8D3/YtyLpy02RkARh0OmJXbsa9bjUUAT4AKAJ8cKsTQeyKTSYjCyDt8Gmyrt7Cr30Ls3b/Df0yGIwfjdZcjzR5BvR6AwU2HP8vqo7dOL8Le4WSctXamKVXqvcm2RlJJN4+a7Puo0YWgMrVF5WrL1npRSGK9gqlmZFViG+pCACzsoLni/Bo/Y+Rnp7OgQMH2LNnD02bNgUgJCSEunXrApCdnc2AAQNo164dCxcuNNXr378/vr6+tGvXjrVr1/L2228/cd9KpRI/Pz8ASpUqxcqVK9mxYwfTpk3DYDDQp08fwsLC2L9/v9lLTvXq1Rk+fLhZW25ubqa2/g5RUVF069aNpk2b8t577zF27FgLT9nD8g4dOpRNmzaxceNGPv74Y1MZHx8fkywzZ86kUaNGHDlyhNatzV8CH3c//P39ee+99xg0aBAA7dq1o1u3bvTq1Ytjx46Rnp7OkCFDmDZtGhUrVjRrx8PDw0yWR3F2drZ5r37//XcaNWrEqFFFIVzly5d/IqPVFiGBDqRnFpCWaf4UvHVXY8oH20ZpSKADd+O0FjHct+7mGvODFFy+kfOflsvfS0piqt7iLJHY5AfeDU8pt+Jte9dK2gdA7H3Lmdu4+3rKBFgac/aBIeTH3bMIoM+7ewsAeVAI2htXrPan3rMNp3pN8Ow2kPQt6zBotSir18GpZn1Sf/2pWFmdG7dAIpWi3rfTZpmEu9fxCSiDTGb+ePIvVeFB/jVCy9coth+9Xo/BoCcrM5Ujf67lfnwMr3YdUWydx+HtKiEl09K4Tko3Jvi4SYhNefrTt9VLS5BIJJy5aX1mPtBbRnyKzkLH7iUZ9SrAW2ZzjUuAtx3X71oaxw/XTc+y3m/DagqkEgn7z2qt5ssDSpEff9dCx/LvxQBGHbTm8QRQ79uGU93GuHfpT+bWX9Dn5aGsVgdljXqkbfi5qI9S5ZA6OJKfFI9Ht3dR1mmMVKEg795tMn5bheb8SUu5gkLJi7WUS3vHqPuK4FCba6gydm3BObIZPr0Hk7JptTF0sGZ9VHUiub96SVFBnY70nb/j2qw12RdOo7l4FqmTM15d+qDPySHjrz+stv9PcK4cRuoBy+tVnzfeY+dKYWjjknCubJxEyTxvee/V56/iHlnTLO3f0C+dHvaczKVRNQcux+RxJaYAJ0cJbzRTotEa2Hcm12r7L6qOpcZH4+5bFukjY5inv3EMS4m/hn/pmhb1bJFx/y7qtDjKVH35sWXvXTOux/PwK8bI/BcRHi1haP3PoVKpUKlUbNy4kfr165uF7QHs2LGDlJQURo4caVH39ddfp3z58qxatepvGVoPc/bsWQ4ePEhoaCgAZ86c4eLFi6xcudLqTLI1A+LvolarWbduHUePHiU8PJzs7GyLUEBrODo6kpaWVmw+QP5jZu2tkZqayrp166hXr54pbfbs2VStWpUvvviCy5cvU6VKFQuD85/i5+fHypUruXDhAlWqVHmqbbs4yVBnWz5gtXkG8vP1OKtse2sAXFQy4pMtZ3bVD8L6XJz+3vD0Isnl5CDhfoblkyYn15jm5PjPY+idHCRmbT5MttaA0sGyD5nKmfxky9lZfbYxVFHq5GyzP+3NaBK++hSfIR/j8rIxtM+g05H263Iyt2+0LahEiiryJfLi7qK9bv1FFiA7Kx1PnyCLdKWT64P8x3uUo74axNVzxlluB0cVPd6fSaUaTR9brzgc5ZCebZmem1eU/7SRSKBqaaMO3btvvYzKUUpyuqWxnq3RP8i3rWMqRwnZVjZLyX6gS7bqSiQQWVVB/P0Cbtyz/pItVTlTYE3Hch6vY3m3rpE48zO83h2NS/MiHUvf8BPqnZtM5WTuxkko1zZvkBd7m5Qls8Ggx6Vle7zfG0fSnEnkXjpj1rbM2Zn8pASLPnVZxs08pM4uNuXKvXGVe5M/JuCDcbi1bmeS6/7qJaRtWW9WNnn5AvQ52QR8+CmSB97U/ORE7k3+mPzEp+9tkHu6kZ9m+dvIe5Am93Qz+2u9bDr2D/IL+bf0a82uHDRaA4PfdEYqNaanZOiYuSKT5DTrxv6LqmO5Oem4eAZb9OmgdDXllxS9roA/14zDXqGketM+xZa9H3eVU39FUaZqS7wCbHtm/03EgcXC0Pqfw87OjqVLlzJgwADmz59PzZo1adq0KV26dCEiIoLoaGNc+KNek0LCw8NNZZ6UH374gUWLFpGfn09eXh5SqZS5c+cCcO3aNVP7JaFr166mtWKFnDt3jjJlyjy27urVqwkLC6Ny5coAdOnShaioKJuGll6vZ8eOHWzfvp0PPvjAapmUlBQmTpyIs7OzyTv4OArvh8FgICcnh/Lly7N9+3ZTvouLC0uWLKFVq1Y4OTlx7ty5v7V49eOPP+bTTz81S/v9999p1qwZw4YNY//+/VStWpWQkBDq169Pq1at6N69u4URXohWq0WrNZ+lNhjykMmK3iQLJxCLna36hwNsSao/arO/KHI9j8aevKm/d5PkIWXxHTqW3JtXub98LgatFoeKEbi/0QOJvZz039ZYredYtSZ2Hl6krFn8eNGK+R2U5CfSofc4NDmZqNOTOXngd36e8xFdBk81rfn62xRzy57F+0RZP3BRSth1uvitu/6Juv+dulXK2OPuImPdn1Ysz3/cOshLlcV7yBi0t6JJ/Xke+rxcHCpE4Na+OxJ7ORlb1hoLSh6EnhUUkDR7Egat0fORe/U8AV/Mw/W1zhYvwcYKxX2RtvMUpcsR8NHn5F6/SsaiOei1uSgrV8ezcy8k9nJSN6w0lfV4oyvur3Yi5ZcVaK5cQKpU4tbqdQLHTiV22ji0MTdsy/B3KUZ2iyUBtspaSf839OvVho60qufI5v0art3Nx1EhoXktBz7sZtw4426iLc//C6pjFDdQlew5bzAY+HP1OOJunuSVPnNwdve3WTYz9R6//TgIlZsfL7/9RYnaF/w7CEPrf5COHTvy6quvsn//fg4fPsy2bdv46quvWLSoaKtlW+uwDAbD396ppnv37owbN47MzEy+/PJLXFxc6Nixo1l/JW3722+/pUUL81jx4GDLGSJrREVF0aNHD9P/PXr0oEmTJqSnp5t5zgoNocL1Sj179mT8+PFmbQUFGWfWs7OzCQsLY926dfj4+JRIjsL7AZCYmMjUqVNp1aoVJ0+exNnZONP20ksvUb9+fapXr05IiI0V8o9h1KhR9OnTxyytcPMPJycntmzZwo0bN9i9ezdHjhzho48+Yvbs2Rw+fBil0jLGe9q0aUycONH0f0hICDExMWZlPv7yJpnZOsqUcrSor5BLsLeXmjxAtsjM0uHsZOldKkyz5pV6GC93e5Z+bW64vwhyPUx2rsHkcXqYQi9TthUv1JNS2Ia1fpwUEqueLl2WGpmV2V6pk3H9WqFnyxqePQahy0wn6ftppoXmuVfOg16PW/suZB3ZY3WW2blxSwwF+WQd2l3s9Tip3MhRp1uk52QbZ+ALPVvF4e1f9FuqXOslfvzyXdYvmUy1+m2feG1WIZo8cLQyN+HwYP4h9+kvu6FaGSk6nYHzMbb1JEujR+VoeU1OD9KseRSK6hqseiQKdclW3UbVFRToDBw+bz1sEECfpbbqUZAqH69jHt0GostMJ/mH6SYd0169AAY9rq+/TfbRvRTcT0SfZdxMQXvjiukFGMCQl4c2+iKONepZtK1Tq5GpLL1WMpWzSW5b+PR9D11GOnEzJ5nk0lw6BwY9np26oz74F/lJCcgDgvHs1JP7K6NI2/KrqX72meOEfr0Q7x4DuTf5Y1vd/C3yUtKx93CzSJe7G38v+akZpnKAjbJupnKF/Bv65ecpo10TR379K4cdR4u+xws38pk40I3OLZyYuSLTop0XVccclG5WvVa5ORkP8h8/hhkMBv5a8ylXT/5Gi27Tiw0bzEyNZcPc3kilMt4YshQHJ7fHtv9v8XfX/JeM/8auimIzjP9RHBwcaNmyJZ9//jmHDh2iT58+jB8/nvLljfHZly9bD925cuUKYWHG2F5XV+NgYG3zh/T0dFN+Ia6urpQrV46aNWvy888/s3fvXqKijDv3PK7fR/Hz86NcuXJmH3t727uuFXLp0iWOHj3K6NGjsbOzw87Ojvr166PRaFi1apVZ2e7du3PmzBlu3LiBRqMhKirKwvDYv38/Z8+eJSMjg+jo6BKtzSqk8H6UK1eOhg0bEhUVxbVr11izxnzGv1DOv4uXl5fFvSoMcyykbNmy9O/fn0WLFnHq1CkuXbpkIUchY8aMISMjw/Q5d+4cQ8dfZvik66bP9dsaYu7l4uZih7uLueyhQQ4A3I61HldfSExsLsEBCguvlKn+PdsvcQBpmflmMr0ocj1M3H09vh5SpI88DwIerKuKT/nnh4zEP1ibVdjmo/3EWekjL/Y29gFBFi5BeVCoMf+e5U6WpjKlSqO9fd1iNy9tzDUkUhn2/pYTIlJnV5TVapNz5hh6dfGhf37BYSTF3USnMzdo4+9Em/KflFJlq6LJziRbbXlGUElJzjDg6WLpUfNxMyYUrtV6WigVEBYA0XGQU4zKxSbr8PeUWehYoI9xYiAu2fbEQmxSAYHelpMKhXVjky0nFZyVEiLKyTl7LQ91ju1rzou9Y9SFR3TMPshoBOfHFqNjwaXJu33DQsfyYq4/0LGgx7aBBKuH+Gjv3kIeaCmXIjj0QX6MzSYVIWXJvXnNQq7cG9FIpDLkgaUelCuDRCol9+Yj0SE6Hdo7N5EH/71JteJQX4jGpYrlJjbOD9LUF689+Bv9IN0ytMy5SnlTfiH/hn4F+8qQSiQWOwvq9HDPRhvw4uqYp3950hJvoH9kDEuJj36QX/wYVmhkXTq2npfe/oLw2u1sljUaWb0wGAy88d4yVG5/f2274NkgDK3/J1SqVIns7GxatWqFh4eH1a29N2/ezLVr1+jatSsA7u7ueHt7c/y4+RamGo2GixcvUqGC7Rhge3t7xo4dy6effkpOTg7Vq1enUqVKzJw5E72VgSk9Pf2fXeADoqKiaNKkCWfPnuXMmTOmz+jRo01GXyGFhlBwcLBFmGIhpUuXpmzZsri42I7bLymFfWg01ndb+7cIDQ1FqVSSnW097EehUODi4mL2uXm3gGsxGtNHk6vnyOlM9HoDLzd0M6vfsqE7uVo9Jy7Ynk0EOHwqA6WDjEa1zA32Fg3duZ+Wz9WbxW84odNhJtOLItfDnLtRgINcQvUwc6OvXiU56Vl6YhL+2UYYABnZBmISdNQJtzczAkL9ZPh6yDh73XJNYc6pw0gdlDjVijRLVzV8iYK0FLSPviA+hC49FUVoOVNITSEOZY3eRV2a5WIiVWRzJHb2qPfb3gSjkCp1WqDNzeH8MfOyJ/ZvwsXdh1LlIh7bxsMYDAZuXD6Bo9IFpcrtieo+zNV7BhT2EsKDzN84I0IlqHMMxP19G84qVUMlyGQSztrYBKOQ01fzcFBIqBluvkisQVUFaWq91W3ZTXWj8/D3sqP0QzvHSSVQv4qCm7H5ZGRZGlINqiqwk0k4cKb4CYecM0eQOjiirNnALF3VoLlRx25ds1m3ID0VuRUdU5Q1PnMK0ox74Osy0si9cQVFuYpIHIomlyRyOYryVdDestTjrOOHkDoqUdVtZJbu0qQFBan3yb1uffOEwn4dyoRZ6n6YMRQ/PyXZTD6HcuYed4mdPYrQchSk2lhw9w9I2LQLVcWyuNUt+n1IZDICu7Uj7egZtPHGYyi0cUmkHTtLYPfXzQwUt3rVUIWXIWGj+e/u39CvdLVRxx/dwdBOBqV87UjLtP4beFF1rExES/K1OVw/t8Ms/fLxjTi5+uAbYvuIGKOR9RmXjq2n+VsTqVSvo82y6rQ4NszthV6v540hy3DxCLRZ9nlRuKPks/j8VxChg/9jpKSk8NZbb/HOO+8QERGBs7MzJ06c4KuvvqJ9+/Y4OTmxYMECunTpwsCBAxk6dCguLi78+eefjBo1ik6dOtG5c9F5GyNHjmTq1Kn4+voSGRlJWloaX375JXZ2dmbhedbo1q0bY8eO5YcffmDkyJEsWbKEFi1a0KRJE8aOHUt4eDhZWVn89ttv7Nixw3TuFBgNr4QE8wXLzs7OODk52ewvPz+fn376iUmTJlls/NC/f3+++uorzp49W6JzsJ4GOTk5pmtITExk8uTJODg40KpVq6faj1qttrhXSqUSFxcXJkyYQE5ODq+88gohISGkp6czZ84c8vPzadmy5T/q906clh370+jRwRe9HqJvaahZRUWbph4s35BodlZV19d96NbOhzFf3+JCtNHAO3E+i1MX1LzXMwBHRynxSXk0redG7arOfLXwrtkiWhdnGVXLG7/7Qs9S7arOZKgLyFDrTG2+SHKpfGRciing8u0COr/kiIM8l+R0PbUq2FMp1I5lf+SYHhbdWjhQt5I9E5dkkaYu6qB6OeMQ7elqfBko5SND+2Ar7TPXi15wNh3IZegbSvq96sj+s3molBLaNXQg7r6Oo5csDS3N+VNoLpzGs+dgpI5K8pPicarXBGXVWiQtnGma5fXqOwxV5Evc+2QgBQ9eIjN3bMKz+7v4Dv8U9Z7t6PO0OFaKwLVVBzQXz5BnxSPg3LglBSnJaC6ctsh7lIrVG1O+aiS/Lp5EriYLL99SnD60latnD9BtyJembdrXLvyME/s28cm32/DwDgBgycyh+JeqQGBIOEpnNzLTkji+dyM3Lx/njb6fmu1kmJocx92bxuMVUpLuAnD2qHENpYd3IMFlzMeQG/FwM8FA29oSFPaQlmU8sLhsgISNh/Wm7/LVuhIiQiXM/V1P5kM2efiD/T3cVEZDzd8dCs+FvXLP8j5ULyMhI9vAjcfsm3DhZj4Xb+bRo40TjgoJSWnGA2WrlpWzaJPaJFfvV5xoEKFg7A/ppD54cT14VkvzWg68+4aK9btzUOcYaFZLga+HjG9XWYZqgfFspJQMHRdvFr8pUO6FU2guncGj+yCkDkryk+NxqtMExyq1uL/oG5OOefYailOD5sSOG4Qu1ahj6l2/4dF1AD5Dx6Hetx1DnhaH8AhcWrVHc+mMaVc5gPR1S/D9aDK+w8eTsX0DGAy4tGyPTOVM8qaVFnLlnD1B9rmT+PYbhkypJC8hDufIZjhVr0P891+a5PId+CEuTVpw64O+FNw3Ginpf2zAp88QAkdNIP3PrRjytCgrV8f91Y5knz9F3oOdCzVXL5J7/SqenXogVSjIuXwBmdIJt9btkPv6Ez/3K5v3zbt1E2ROjtg5G8cVVcVy+L1pjKRI+mMvek0uEQunENizA3sqtERzJw6Ae0t+IXRQN2qums2VcTPRJqUQOqgbThVKc7R1X7M+royZQb1ti6m1ejYx81ei8PEkfMpHZF64yr2lv5qV/Tf06/rdAm7FFfB6YyVyewnRd/NxVEh5qbYD3u4yFm2yHs75oupYaMUmBJePZM8vE8nLzcLNqxTRp7Zw58p+WvX42jSG/bl6HJePb6TXuB0mI2nf+slcOvoLlep1xMu/PAkxZ0ztyuzkeAdVAiBHncL6ub3Jzkzm5S5T0GSloMkqOoRP5eYnvFsvCMLQ+h9DpVJRr149vv32W27cuEF+fj7BwcEMGDDAdDhup06d2L17N1OnTqVJkyZoNBrKlSvHuHHj+OCDD8zWUY0cORKVSsWMGTO4ceMGbm5u1K9fn/379z/WyyOXyxk6dChfffUVgwYNom7dupw4cYIpU6YwYMAA7t+/j7+/P5GRkcyaNcusbt++fS3ae/gQXmts3ryZlJQU3njjDYu8sLAwqlatSlRUFHPmzClW7qfFjz/+yI8//ggYvYMRERFs3bq1WE/g3+Hzzz/n888/N0t79913mT9/Pk2bNmXu3Ln06tXLdHh1jRo12LFjx1ORY+7PsaSk59PuZU/cXe1ITMlnwap4fvvT/NRVqRRkMolF2NXkuXfo/aYvPTv44uwk426Clunz77DvmHl4WUiAA+PeMw+3GdrL+GA6dyWLT7669cLJde1eAXN+yWHR7zm8HqnglQYKlAoJSWl6lmzN4dRDZ2tJpSCTWsrR7zXzUNYm1eU0qW6cWR4266EXlXs65m3K4dUGCga2V5Kfb+DCrQI27tdSYMNpljh3Gu5v9sCtQzdkTs7kJdwjaf7XZB/bX1RIIkUik/FwLHzmn1soSEvFtVU7vPoORWIvp+B+EumbV5OxY5NFP4qy4cgDgknbtKrE05C9P5zFH2vmsP2X78nJysAnoDTdh35NjchXTGX0eh16vY6HF7yHlq/BuaM7OLhjJVpNNg5KZ4LLVOadUT9Y7Dp449JR1iww30Tmp9nGLeBrN2lPl0FTLeT65YCeZlUlNK0qwUFu3O794QOMwRhaKLXyXXZsZO41r11eSu0HkV5TVpt/SYGe4OUqYf+FkoWWzvtVTYdmSto1UeLkICEhRcfCjWqOXypaOGZNxwp0MHNlJp2aK+naygm5vYS7iQXMWaMm+o6lp6JsoB3+Xnb8tj+nRJt/JM+bjluH7ri274pM6Ux+wj2Sf5xhPEj2IcEkMplZTKZ69xYK0lNwadEOz17vGXUsJYmM39aQuWuzWR/am1dJ/PZz3Np3x6vfhw/Sokmc8Sl5Nrb2jvvmC7ze7oNnp15IVSry4+4RP2ca6sNFk30muR7S/fTtmylITcHtlTfwHfgBUrmC/OREUtavIG3rQ7sOGgzcmzoG99ffQlWvMe6vdkKv1ZB37w73pn9KztkTNu9Zle/Howwt2nUz4K22BLxlPIT7r3IvobkdCzIpUjs7s3umz8vnSOs+VJw+isqzPkWmdCTz7GWOvTaA1P3mUSmp+45x/PWBlJ/wPnU2zkeXoyFp6x4uf/wV+jxLA/pZ65cB+HZVJq3rO1CropxW9RzR5huIu69j9upMLhRj1L+oOvbKO99xZMssjv7xHbk56bj7lqF1z5mUr1m0IY9er8PwyBh266JxDeulo79y6ai50evsHkCfz/8CIDXxOpkpxgmiHT+P4lHqtn6Pem2G2bxv/xZWApj+3yExPNuVagKB4H+AV945//hCAjPKRjz9dRhPgxHnivdEPy8uvLf+8YWeA+euvZgLrmNupj9vEazyaUy/5y2CTbTq4tdnPi+u/XLr8YWeAxsnHnreIljlRdWx3zpseN4iWGXoK89vDJv927MzMYa//uTX9cMPP/D1118THx9P5cqVmTVrFo0bN7Zadv369cybN48zZ86g1WqpXLkyEyZMeKK1+iDWaAkEAoFAIBAIBIKnzIu0RmvNmjV88MEHjBs3jtOnT9O4cWPatm3LnTt3rJbft28fLVu2ZOvWrZw8eZLmzZvz+uuvc/r040PgH0YYWoL/FG3btjUdyvzoZ+pUy1CfZ8H+/fttyqBSqf4VGQQCgUAgEAheZPSGZ/d5Ur755hv69etH//79qVixIrNmzSI4OJh58+ZZLT9r1ixGjx5NnTp1CAsLY+rUqYSFhfHbb789Ub9ijZbgP8WiRYts7trn4eHxr8hQu3Ztzpw586/0JRAIBAKBQCAwR6vVotWa736qUChQKCwPPMzLy+PkyZMW6/xbtWrFoUMlC5HV6/Wo1eonftcUhpbgP0XhQbzPE0dHR8qVK/e8xRAIBAKBQCB4YXmWu0BMmzaNiRMnmqWNHz+eCRMmWJS9f/8+Op0OX19fs3RfX1+LXZttMXPmTLKzs8125i4JwtASCAQCgUAgEAgE/xnGjBnDiBEjzNKsebMeRvLIdrAGg8EizRqrVq1iwoQJbNq0CR8fnyeSUxhaAoFAIBAIBAKB4Kli+DuLqUqIrTBBa3h5eSGTySy8V0lJSRZerkdZs2YN/fr1Y926dbRo0eKJ5RSbYQgEAoFAIBAIBIL/SeRyObVq1WLnzp1m6Tt37iQyMtJmvVWrVtGnTx9WrlzJq6++arNccQiPlkAgEAgEAoFAIHiqPEOH1hMzYsQIevbsSe3atWnQoAELFy7kzp07DBo0CDCGIsbGxrJ8+XLAaGT16tWL2bNnU79+fZM3zNHREVdX1xL3KwwtgUAgEAgEAoFA8D/L22+/TUpKCpMmTSI+Pp4qVaqwdetWQkJCAIiPjzc7U2vBggUUFBTw3nvv8d5775nSe/fuzdKlS0vcrzC0BAKBQCAQCAQCwVPlWe46+HcYMmQIQ4YMsZr3qPG0Z8+ep9KnMLQEAoFAIBAIBALBU0X/IsUOPifEZhgCgUAgEAgEAoFA8JQRHi2BQPBYdDrd8xbhP0dactbzFsEqunGzn7cIVmm09v3nLYJVfro/+nmLYJXec1o/bxGskntl1/MWwSZytM9bBKtsrOr+vEWwSofxtndje568qDq2Z86t5y2CVYa+Uua59f2ihQ4+D4RHSyAQCAQCgUAgEAieMsKjJRAIBAKBQCAQCJ4qwqMlPFoCgUAgEAgEAoFA8NQRHi2BQCAQCAQCgUDwVNELl5bwaAkEAoFAIBAIBALB00Z4tAQCgUAgEAgEAsFTxaB/3hI8f4ShJRAIBAKBQCAQCJ4qBhE6KEIHBQKBQCAQCAQCgeBpIzxaAoFAIBAIBAKB4KmiF6GDwqMlEAgEAoFAIBAIBE8b4dESCAR/G5kMurzuS6tGnni42ZGYnMfmP++zedf9EtV3UEjp09GfJnXdcHaScTdey5otiew9mm5Wrn1LL5rXdyfAV4Gjg5T0zAIuXctm5eZEbsfmPhe5pBLo0MqbWlWcCQlywNnJjqSUPA6fymDNliRTOYVcwlstnKlX1REnRynx9wv4ba+aI+ct5X4UFycpXdq4UKOCArm9hDsJBfyyM5OLN/PMyo3r50nFMgqL+ueic/lqWarVtjUaDT8tX8b+/ftQq9UEBQfz1ludadq0WYnuUSHLly1lzZrVhISE8MO8BRb5ubm5rFu3ln1795KUlISjowOhpUszbNhwAgMDrTdqr8Cx6evIw2sicXRCl5JA7uEd5F8+Wawsqm4fYB9S3mZ++pxPMGRnGv+R2aGo3QxF1fpIXT0x5GvRJdxFc/APdLE3rdZXyCV0aetOg2pKVEoZcUn5bPwrg0NnsouVC8BFJaXHax7UrOSIwl7C7bg8Vm9L58I1cz3o0taNGhUd8Xa3Q24vJS2zgPPRuaz/M537aTqrbctUToSNG4JLtXBcqldC4e1B9KTvuPbF94+VC0Du7UH49FH4vtIcmdKBzHNXuPr5LFJ2H7Eo6/lSAypMHI5LRDi6nFwSt+7myidfk5dsqWcajYafly/h4P69qNWZBAWXouNbXWjStHmJ5Crk52WLWbtmJaVCQvl+3iKzvLEfj+DC+XMWdWrUqs3EL6ZbbU+j0bBs+U/s278ftVpNcHAQnd96i2ZNmz6RXEuXLWf1mjWEhISwYN4PpvSExET69H3HZr1atWoy5YsvLNIV9tChqZLaFRU4OUpISNHxx2ENxy/lWWnFHGelhE4vKalaTo7cXsK9xAI27svhSkyBWTk7GbxU24HICAVerjK0+QZuJxSw5YCGG7EFVtt+UfULXlwdc5BL6PKqB5E1nFAppcQm5rNxVzoHT5dsrOjZzpNalZUo5BJiYvNYvTWV89FFY4WjQkLbJq5Uq+BIgK89DgopSSkF7D+hZsveTPILXoy1UWKNljC0/qfo06cPy5YtA0AmkxEQEMCrr77K1KlTcXd3ByA0NJTbt29b1J02bRqffPIJMTExlC5dGplMxu3bt81ehOLj4wkODkan03Hr1i1CQ0NNecuWLWPu3LlcvHgRqVRKjRo1GD16NK+99pqFbLYwGAw2y7Vu3Zpt27aV+F5MnTqVzz77jClTpvDJJ5+Y5S1dupS+ffua/vfz86Nx48Z8+eWXlC5dGjC/T46OjpQpU4Zhw4bx7rvvPrbvR9t3cnKiQoUKjBs3jjfffJN+/fpx7NgxTp48iVwuN5XbunUr7du3p3Xr1mzZsqXYPm7dusXSpUuZOHGiRV6FChW4cuUKADdv3mTcuHHs3buX1NRUvLy8qFWrFl9//TXly9t+IS0pw3oF83KkO8vWxxN9S0Otqs4M7h6I0kHK6t+THlv/8/dDKV9ayeK18cQmaGnewJ2xQ0KRSmLYfSTdVM5FZcfx85nc3JJLVnYB/j4KOr/qw+zPwxg6Ppp7Cdp/XS65XEqPN/zYcySNP/amkJmlo1yII93a+VK/hgsTFqaRXwAfdHOnTJCcNdszib9fQGQ1R4Z28UAiSePwOY1NGexkMOYdT5QOUn7akklmlp4W9ZWM6uPJ9MUpXIkxf/lKTCngh3VpZmk5GtsPuSmTvyD6WjR9+/QlIDCIvXt289WX0zHoDTRrXrKXlBs3brB+/a+4PRhfHkWj0TDmk9GkpqbS6a3OlC5dmuzsbC5fvoxWq7VaB0DVcSAyvxA0ezaiT01CXrk2qg79yJJIyL90wma9nO2rkSgczNIk9nJUbw9Fl3CnyMgClG27I69ch9zD2ym4fRWJgxMODVrh3P1D1D/NQBdvOU6O7OND2WA5K7ekEZ9cQKOaTnzQ0xuJhGJfoOxk8PkgP5SOUpZuTCUjS0ebhi6MHeDLF/MTuHyz6F44OUo5eDqb2MR8NFoDQb72vNnCldqVlYz4OpasHMtYHLmnG6X6dybz3BUSN++iVL/ONmV5FKncnno7lmLv6sLFEVPIS0ohZHB36m5ZxNHWfUndf9xU1qNxHer+/iNJW/dy4s0hyH08CZ86kno7lnKwXkf0eflmbU+bPIFr167Su09/AgKD2LfnT2Z8OQWDXk/T5i+XSL6bN66zYf06mzoG4Ofnz4jRY8zSVE4qm+W/mDzFpPtBgQHs3rOX6V9+hUFvoHnzZiWS68aNG/y6fj3u7m4WeR4eHnz7zUyL9MOHD7N23S9ENoi02ubgjs6E+tuxfk8Oiak66lZSMLCDMxLUHCvG2LKTwYhuLigdJKzZmU1mtoHmtRwY/rYL367KJPpOkQHV6xUV9SrL+eOwhisx+SgdpbRt4MjIHi58uTyTmHhLY+tF1S94cXVsVD9fypZSsOK3VOKS8mlcS8WHfXyRSBM5cLL4sWL8ewE4OUpZsj7FOFY0cmHcIH8mzY3n0g2jseXlYcerzVzZd1zNb3syyNXqqVjWgbfauBNRwZFJPySU6NoFzx5haP2P0aZNG5YsWUJBQQGXLl3inXfeIT09nVWrVpnKTJo0iQEDBpjVc3Z2Nvs/ICCA5cuXM2ZM0cCybNkyAgMDuXPnjlnZkSNH8v333zN58mQ6dOhAfn4+P//8M+3bt2f27NkMHTqU2bNnM3160cyPv78/S5YsoU2bNjav4WEUCsvZ+uJYsmQJo0ePZvHixRaGFoCLiwtXr17FYDBw5coV3n33Xdq1a8eZM2eQyWRA0X3Kyspi6dKlDBo0CDc3N95+++3H9l/YPoBarWbJkiV07tyZixcvMmvWLKpWrcr48eOZNm0aAOnp6QwcOJBx48YxcuRIsrKyTG3VqVOHgQMHmn1n3t7eAFSuXJldu3aZ9W1nZ/xZ5+Xl0bJlS8LDw1m/fj3+/v7cu3ePrVu3kpGR8SS30yohgQ60buLB0l/j+eWPZADOXcnCRSWjazs/tuxOQZ1tfQYeoE6EM7WquDBtXgx7HhgvZ69k4eNlT/8uAew9mo7+gZ3w0wbzh8b5q9lcvp7NoukVeamBO8sfyv+35MrL09P7o0tmbZ27kkVSSh6fDStN3cq5ZGn0VA1zYO6aIqPq8q08vNxkdG3rwpHzGmxN+DWrrSTYz54J85O5ftf4gnHplpapQ73p0saFCfPNvXN5BQZu3LV8EbHG8ePHOH36FKNGf0yzZkajqlq1aiQlJbF48SIaN2li+h3YQqfTMevbb2jb9hVu3bpJZmamRZmfli/j7t27fD93Hv7+/qb0+vUb2GzXrmxl7EtXJGvTYpNRVXAnGqmrJ8qX3iTj8kls3TR9iuXLhbxqPSQyO7RnDhUlyuyQV65N3qXj5O77zZRccO8Gbu9PR165LppHDK0a4Y5Uq+DI7J+TTUbVxRu5eLnb0fN1dw6dybb5Xb5Uz5lS/nLGzYnn2m2jUXXxei5ffxRAj9c8GDcn3lQ2ar35zP2lG7kkpRYwdoAvdaoo2X0si0fR3I5lh3cdAOw93Z/oRTj4nbdwqVKBg43fJv3IGQBS9hyl8clNhE8fxaGGRW1V/HI02dExnHr7fQw6o95rYu4RuW81QX07cWdB0XPmxPGjnDl9ko9Gj6Vps5cAiKhWnaSkJJYsXkijJs1KpGOzv/2aNm1f49atG1Z1DECuUBAeXqlE13vs+HFOnT7Nx6NH0bxZM6BI9xctXkyTJo1LJNc3387ilbZtuXnrloVccnt7KoaHW9RbsnQpCoWCZs0sPWdVytpTuYycHzcWGVVXbxfg6Sql08tOHL+cZ1O/GlVTEORjx7RlGdx84JW6ejuf8f1d6dhcybRlRvnsZFC3spyjF/PYuLdokufG3XxmDPegXhW5VUPrRdQveHF1rEYlR6qFK/l2WSIHTz0YK67n4u1hR892nhw6lW16tj3Kyw1cCAmQM/bbWKJjjGPFhWsaZo4Oomc7D8Z8GwdAUkoBQybeQZtX1NCFa7lotQZ6dfAkvIyCKzdtT2b9W9i6zv9PiDVa/2MoFAr8/PwICgqiVatWvP322+zYscOsjLOzM35+fmYfJycnszK9e/e2MHaWLl1K7969zdKOHDnCzJkz+frrrxk5ciTlypWjYsWKTJkyhQ8++IARI0Zw9+5dXF1dzfoDcHNzs0h7+Boe/rgXM9P0KHv37kWj0TBp0iSys7PZt2+fRRmJRIKfnx/+/v40b96c8ePHc+HCBa5fv25xn8qVK8fkyZMJCwtj48aNJZKhsH0/Pz/CwsKYPHkyUqmUc+fO4ezszNKlS5k5cyZHjx4F4IMPPsDf359PP/0UlUpldu0ymcziOyt8eNjZ2VncKy8vLwAuXbrEzZs3+eGHH6hfvz4hISE0bNiQKVOmUKdOnRLfT1tE1nRFKpWwY7/5i+GOfak4KKTUrupso6aRhrXcyNHo2Hcs3bz+/lS83OWEl1UWWz9DbXwh0D0ykv9bcukNWDXYrt7MAcDDVUbtSg5otHqOXjD3XO07pcHDRUa5YHubctSq5Ehccr7JyALjwuKDZzSUC5bj7vL3h+/Dhw7h6OhI48ZNzNJbtGxJSkqKaZKgONatXYNaraZX7z5W83Nzc9m+fRuNGjU2M7Ieh7x8NQzaXPIvnzJL1547jNTZDVlA6RK3BSCPiMSgzSXv4bBDgx4MBgxa8+/FkJeLQa+HAkuDtW5VJZpcPYfPms9G7zmehYerHWEhtieD6lZVEpuUbzKywPhd7j+ZTViIAneX4l8GM7OMeqbTPf23Ft/2Lci6ctP0Egxg0OmIXbkZ97rVUAT4AKAI8MGtTgSxKzaZXoIB0g6fJuvqLfzatzBr98ihAzg6OtKosblR8XLL1qSmpBB99cpjZftl7Sqy1Gp69LYdhvekHDp0GEdHR5o0bmyW3rJlixLr/pq161Cr1fTp3avE/cbFx3P+/AWaNG6Mk9JybKtRXk6u1sCJy+aeq0PntLg7SykTYHtevEYFOfEpOpORBcbx6cgFLWUC7XFTGccKg8H40WjN9UiTZ0CvN1BgPXLwH/Gs9AteXB2rV9XJOFY8ElL811E1nm6PGSsilMQm5pmMLDCOFftOZBEW6oCHq3Gs0OYZzIysQq7dMdbzdBN+lBcFYWj9D3Pz5k22bduGvb3tlzlbtGvXjrS0NA4cOADAgQMHSE1N5fXXXzcrt2rVKlQqldWQuo8++oj8/Hx+/fXXv3cBf5OoqCi6du2Kvb09Xbt2JSoq6rF1HB0dAcjPt+0RcHBwKDbfFjqdzhQOWbNmTQCaNWvGkCFD6N27N+vWrWPt2rUsX77c5I16Gnh7eyOVSvnll1/Q6Wx7cP4uIUEOpGfmk5Zh/nS+edcY2hAa5PjY+nfjcy12Jbr1oH6IlfpSCdjbSQj2V/DhO6VIy8i3MKieh1wPU72S0ZCLTconyNeeuOQCi7buJBj1KMjX9m8z2NeOuwmWbz53E411A33M6/p62DF/nB/LJvkzc4QPb7V0xt6GOt2+HUNwcLDFbG9h6Ozt2zE25QK4c+c2q1ev4r2hQ02/nUe5fv06ubm5BAQGMvf77+jcuRPt273G8PeHcezYUZtty7wD0KUkWJx0qUuKfZBfcqNN6u6Nfakw8i6fgPyHZnf1erSn9qGoUh/7sGogd0Dq6oFT2+4YtBq0Zw9atBXsZ09sUr7Fd3k7Ls+Ub4tgP3vuxFmGft2Ot11XKjXqemignD4dPIhLyufo+ZySXPYT4Vw5jMzzlsaF+kGac6WwB+WMoca2yhbmF3L7dgxBwaWs6FiZB/m3ipXrzp3brF29gsFDh9vUsUIS4uPo1vkNOrzWioHv9OSnZYtthqbG3L5drO7HWAmtN7uuO3dYtXo1Q4e+91i5HmbHjh0YDAbatG5tNT/QW0Z8is7CA3AvyTh2B3jbNsYDvO2ITbIcKx6tq9PDnpO5RFZVUL28PQ5yCZ6uUnq9okKjNbDvzOPXjT4pz0q/4MXVsWB/OfcS82yPFf5yK7WMlPKTm8qZ1zX2Fexnuy5A1TDjddxLePJ3lWeBQW94Zp//CsLk/R/j999/R6VSodPpyM01DprffPONWZmPP/6YTz/91KJeswdhFAD29vb06NGDxYsX06hRIxYvXkyPHj0sjLbo6GjKli1rttaokICAAFxdXYmOjv5b1/CozJ999tlj62ZmZvLrr79y6JAxTKhHjx40bNiQ7777DhcXF6t17t27x9dff01QUJDVdUsFBQX8/PPPnD9/nsGDB5foGjIyMkzXoNFosLe3Z+HChZQtW9ZUZtq0aWzfvp0uXbowc+ZMKlasWKK2H+b8+fMW96pLly4sWrSIwMBA5syZw+jRo5k4cSK1a9emefPmdO/enTJlyjxxX4/iopKhzrI04LR5evLy9Tirip+ld1HJSEiyfKCoswpM+Y+yaWEEcrlxfuhufC6jpl0nOdX8gfI85CrE092ed97y5+rNHE5f1dK1rSvJqZYvQNka4xNY5Wh7rkvlKCVLY7kep3CNjrOyqO7V23kcOa8hLrkAub2EauUVvNpYRfkQOVOjUixCjjIz1fj5+/EohSHEahvhMwB6vZ5Z335LZGRD6tSpa7NcSooxtPGXdWsJDQ3lo49GIpFI2LB+PZMmTmDipC+oVau2RT2JoxP6dMtNSwwa4+yw1NH2uohHUVQzroXRnj1kkafZ9QsGrQanNwcgkRrvpS4jhayVs9GnJVuUVznJSEqx/C6Lvg/beuGslFldW2Wq62Re19VZxo8Tgk3/R9/WMnFegtUZ7H+K3NON/DTLUOK8B2lyTzezv9bLpmP/IL8QdWYmvlY8maoS6ticb7+mQWQjatepV6z8lSpVoVGTZgQFlSIvT8vJE8dY/8saLl28wJTpM5BKzX9j6szMYnU/M1NdrFzffjuLhpGR1H2CqACdTseuXX8SHBxE5crWw89UjlKS0y3HraKxQmKzfZWjhGwr6zGzcw0WddfsykGjNTD4TWekUmN6SoaOmSsySU57+ntxPyv9ghdXx5ydpCQWN1Y42R4rVE7FjxUqJ9vPjJAAOe1fduXo2WyrxtrzQOyFIQyt/zmaN2/OvHnzyMnJYdGiRURHRzNs2DCzMqNGjaJPnz5madZ2/+rXrx8NGjRg6tSprFu3jsOHD1PwhLEFBoMBicT2A6K4a3gYDw+PEtVduXIlZcqUoVq1agBUr16dMmXKsHr1agYOHGgqV2gIGQwGcnJyqFmzJuvXrzczGAsNUq1Wi1wuZ9SoUSXaDAOMD+1Tp4yhTzk5OezatYt3330XT09Pk1fQ0dGRjz76iA8//JDhw4eXqN1HqVChAps3b7bou5D33nuPXr16sXv3bo4ePcq6deuYOnUqmzdvpmXLllbb1Gq1ljN1hjyksqJ7UzhTV+wYWoIBtrgi1gboDydfw85Ogr+Pgjdbe/PVJ+UYO+OGaefB5yUXGB+ek0eUQSKBqT/EYFC4lbS7J+7LmFeU+csu85fDs9FaktN0dH/FlVoVHThxyXKmWkIxv8tifrMbNqwnLi6Wz8dPsF0fTDOOdnb2TJw0GeWDcKmIiGoMHNCP1atWWjW0jJWLabekT26JFHnV+uiS49DFxVhkO0S2waFuC3IPbKHg7nUkcgcUtZuh6jqMrNXfoUu890R9P04qQzElHm1Wna3jk2/jsLeTEOhrT7vmrowf7MeEHxJIVz9973RximZxzbbKWkkvTseKey5s2vAL8XGxfDrecme+R3k05Kt2nXr4+PqxZNECjh45RIPIRk8ol+2+1m/YQGxcHBPGf/5YuR7mxMmT3E9JoX+H4sPTih13HtNHSeu+2tCRVvUc2bxfw7W7+TgqJDSv5cCH3YwbZ9xN/O/oF7y4OlbsGPaYb7PYIc5GnreHHZ8M9ON+WgHzVltOFAmeHyJ08H8MJycnypUrR0REBHPmzEGr1VrsTOfl5UW5cuXMPtbc5lWqVCE8PJyuXbtSsWJFqlSpYlGmfPny3Lhxg7w8y9mTuLg4MjMzCQsL+1vX8PCnpIbW4sWLuXjxInZ2dqbPxYsXLcIHnZ2dOXPmDOfPnycrK4uTJ09arFsaNWoUZ86c4fbt22RlZfHVV19ZzFzZQiqVmmSPiIhgxIgRNG/enC+//NKsnJ2dHTKZ7ImN0ULkcrnFvfL19bW41nbt2jFlyhTOnj1L48aNmTx5ss02p02bhqurq+kTERHB9uV1+WNJddMnIlxFZpbOqndHIZcit5cWu+EEYLO+s8o4/2Ot/vXbGq7cyGH34TRm/HgbDzd75k8Of+5yqZQypo0ui6e7PWO+vkFCsvH3kJWjR6W01BmnB54sax6rQrI0ejOvVVFfhXWLf1gfPGNcf1TWyjowFxdn1GrL2V612miwPbo5TiFJSUms+PknunXrjp2dHVlZWWRlZaHT6dDrDWRlZZmMdGcXYxsVK1U0GVlgDMGtUqUqN27csNqHQZONxNHJIr0wzZD7+O2RAezLVkaqcrUaBij19MOhyWto9m8h9+AfFNy5Rv7182StnYshV4Pjy50s6mRl66zORJu+jxzbeqXO0Vn1eNmqq9fDzXt5XI3R8tfRLCbNS8DH044OL7kWf9F/g7yUdOw93CzS5e7GvvJTM0zlABtl3UzlCnF2cbGqY1kPdExlQ8eSkxJZ8fMyunTrhZ2dvZmOGfR6Mx2zRbPmxvU8V69ctshzdnEhU23ptSqJ7v/08wq6d+tmofuPk2v7jh3Y2dnR4mXbu+BlafRWPdyFY4U1j1VRXYNVj5eTg8Ssrp+njHZNHNm8P4ctBzVE3yng7LV8vlurJifXQOcWlr+7f8qz0i94cXVMna236nky/d6zixn3s3U4F1fXirfLy92OCUP90esMTJwbb7XM80KvNzyzz38F4dH6H2f8+PG0bduWwYMHExAQ8MT133nnHYYMGWLhYSqkS5cuzJkzhwULFlh4zmbMmIG9vT0dO3b8W7I/KefPn+fEiRPs2bPHzDBLT0+nSZMmXLhwwWQsFhpCxVFokD4tZDIZGo3t7bz/DSQSCeHh4abQSmuMGTOGESNGmKW999lFJNKi4eJegpaYu0qa13fH3dXObD1U6WDj9tox94q/1ph7GprVc0cqNT89PjTIWP/2Y+rHJuRxLSbH6En6Pua5yaVSypj+cVn8vOR8/OUN01ouMK6nahDhaNFWsK/xXt5LtB1HfzchnyBfyyE6+MG6ruLqPoy12dGQ0NLs27sHnU5ntr4hJibGmB8SarWthIR4tFotCxbMZ8GC+Rb5b3fuRPv2HRj47iDTmherMmHb061LikNeqTZIpGbrtGTexvFLlxxvtd6jyKtFYijIJ+/CMYs8mU8gEonUcgt3vR5d0j3sSllODt2Jz6dhDSeL77LUg/UWd4tZE3EnPp9gf0uDtyR1AVIzdKRl6PD3fvqPbPWFaFyqWIZMOz9IU1+89uBv9IP0CiRv22dRtjC/kJDQ0uzfu9uKjhnXzYSEWNePhIR48rRaflwwlx8XzLXI79a5A6+3f5MB7w557LVZ07HSoSHs2bvPpu6HhoRYbSs+IQGtVsv8BQuYv8DyvLhOnd+mQ/v2DHp3oFl6eno6x44dp369eri5udmUNTbZuJ27VGK+U1ugj1HGuGTbhnxsUgGBVtZwFdaNTTaOg8G+MqQSicXOgjo93EsqoHypJ1/P/TielX7Bi6tjd+LzaFRTZTFWhBT+3uNth/Xdic8zjQsPUypAbsp/GC93OyYO80cCfP59PKkZz8AjKfhHCEPrf5xmzZpRuXJlpk6dyvffGw8XVKvVJCSYb4OsVCqtrmEaMGAAb731ls0HRIMGDRg+fDijRo0iLy/PbHv32bNnM2vWLIKDg63WtYVWq7WQz87OzrSbni2ioqKoW7cuTZo0schr0KABUVFRfPvtt08ky9/FYDCYrkGj0bBz5062b9/O558/WcjJ4ygoKLC4VxKJBF9fX86cOcP48ePp2bMnlSpVQi6Xs3fvXhYvXszHH39ss02FQmGxnf71O/mA+cvg4dOZ9O7oT8uGHqzdWnQ2VatGHuRq9Zw4b3utA8DBkxm80syLxrXd2PvQDn8tG3lwPy2PKzeKX/ivdJTi5yXn4rVsrsUUGT//plwmI8tbzpivbnDjjrkRduJSLi/VcaJOZQeOPnRAceOaSlIzdWY7Cj7KiUu59G3vRtkge27cM5aTSiGyuiPX7+SRri5+1rJxTaMXyVofkQ0i2b7tDw4eOECThw5p/XPXLjw9PalQoYLVNsuUKcu06V9apC9cuICc7Gw++HAEXl7Gowc8PDwJr1iRy5cukZOTjVJpnC3Pzc3lwvnzVLCy/TVAXvQZFDUaYR9ew+yAYkXV+ujV6ejiil/gDiBxcsG+bBXyr54xre16GEOWcXZcFhhKwd1rRRkyO2S+pdBnplvUOXYhhxYNnKkXoeTwmSIdaFrbidSMArMdBS3qns9hQCdPypWSc/2O8UVJKoXGNZ2Ivq0lLbP4lyNfTzs83WScuPT0t4VL2LSLqt9PwK1uBOnHjIeySmQyAru1I+3oGbTxxt+QNi6JtGNnCez+Oje/iTK9QbrVq4YqvAy3vjM//7BBg0bs2LaVQwf20fihw2P/2rUDD09Pylew/v2XLlOOKdNnWKQvWjiP7Oxshn84Es8HOmaLv3YZd9qtEG657jWyQSR/bNvOgQMHadq06Fmxa9efxep+2TJl+HL6NIv0BQsXkp2dw4gPP8DbyjNq159/UlBQQOtWrYqV+fTVPJrUcKBmuNxs58EGVRWkqfXcjLP93Z+OzqNHGxWlA+y49aCcVAL1qyi4GZtPRpbRciscM8oE2JmdrWUng1K+dqRlPn1PyLPSL3hxdezYuWxaRrpQv5oThx46X69ZXWdS0osfK46ey2ZgZ2/CQhSmclIpNKntTHRMrtlY4eUuY+Iwf6RSCeO/i+N+2jPYNvIfIg4sFobW/wtGjBhB3759TS/Xn3/+ucUL/7vvvsv8+ZYz1CUxcGbNmkVERATz5s3js88+QyKRULNmTTZu3GixS2FJ2LZtm8V20A8fwmuNvLw8fv75Z5sGRMeOHZk2bZpF6N6zIjMz03QNCoWCkJAQJk2aVKyB83e4ePGixb1SKBTk5uYSFBREaGgoEydOJCYmBolEYvr/ww8//Md9347NZfu+VHq+4YfeYODqzRxqVXGmbTNPlv0abxZi1729L93b+/Hxl9c5f9X44DlxTs3JC5kM6x2E0lFKXGIezRq4USfChenzb5tmdZWOUqaPLsvuw+nEJmrR5ukJ8lPQoZU39vYSft6Y8FzkkttLmDqqDGVLOTJ/ZSwymcRsS3qZk4xz0VrOX8ulbzs3HBWZJKYU0KCaI9XKO/DD2jSTt6n/G640rqFkxDdJpDxYEL/3ZA4t6jsxrKs7a7aryczW0aKeE/5edkxfnGLqp0KInPbNVJy4lEtSqg57e6hW3oHmtZVcvKHl9BXL9Vm169ShRo2azJ37HTmaHPz9A9i7dw8nT55g5KjRptnhWbO+4c9du4iKWoKPry8qlYqIiGoW7amcnNDrdBZ5/foNYMwnH/PZp+Po1KkzSCRsWP8rmZmZ9OxpfWvsgpuXyL91GWXrLmjkDujTkpFXqo192cpkb15ictEpX+mBvGo9MueNR59pvvOk8ewsmdWwQYCCuzcoiIvBsdGrSOzlFNy5jkThiKJ2M2TuXmRvXmpR58wVDWevahjQ0ROlQkrC/QIa1nCiRkUlc1Ykm77LQZ09aVpbxbBp97ifZvwudx9T07qhMyN6+bBiSxqZWTpaRToT4GPPF/OL9LeUvz2923tw5GwOSan56A3GXchebeqCOlvPb3tsn3/n3boJMidH7JyNBq2qYjn83jTucJf0x170mlwiFk4hsGcH9lRoieaO8Tyee0t+IXRQN2qums2VcTPRJqUQOqgbThVKc7R1X7M+royZQb1ti6m1ejYx81ei8PEkfMpHZF64yr2l5rvL1qpTl+o1ajFv7pwHOhbIvr1/cerkcUaMGmPSsTmzZvDXrh0sjPrJpGNVI6pbXJ+TkxM6nc4s7+KF86xds4IGDRrh6+dPfn4eJ08cY/sfW4ioVoO69SzPa6tTpzY1a9Tgu7lzydHkEODvz569ezlx8iSjR400yfXNrFns2vUnS6Ki8PX1QaVSUS0iwopcKnQ6vdU8MIYNent7U6tWTav5hVy4mc/Fm3n0aOOEo0JCUprRw1W1rJxFm9Qm/er9ihMNIhSM/SGd1AeG0cGzWprXcuDdN1Ss352DOsdAs1oKfD1kfLuqKLTu+t0CbsUV8HpjJXJ7CdF383FUSHmptgPe7jIWbbI9CfWi6Re8uDp2+rKGs1dyGPCWF0oHKfHJ+TSqpaJGJSWzlyeZniGDu3rRrI4z731x12Qk/XVETZvGrozo68uK31LIUOtp08iFAB97Js0t8ua7qKRMGBqAu4uMeavu46qS4fpQyHtKeoHwbr0gCEPrf4ilS5daTe/WrRvdunUDisIjbBEaGlrsDET16tWt5r/zzju8807Jz6Gw1cfSpUttXkdxyOVy7t+33KmskBEjRpjC4fr06WOxGcijPO4+FUdJ2n+SsrZkmTBhAhMmTLBZz8vLi9mzZ5dIjr/Ld8vvcj8tn3YtvHF3tSPxfh7zVsSyeZf5dyGRSJDJJBZhFpPmxNCnkz893/TH2UnGvXgtU3+IYe/RdFOZ/HwDN+/k0raZJ94e9sjtpaRl5HP2ShZffJfInTjL2cF/Qy53V3sqlDG+dAzpEWQhw75TOSz8NZ1ZK9Po3NKZTi2ccXKUEpdcwPerUznykIdLKn0gx0P1C3QwLSqFrm1c6PW6Kwp7Cbfj8/l6WQpXYopmvNPVxi2hOzR3NsXxJ6QU8OufarYeyLK5sHrcp5+xfNlSfv5pOWp1FsHBQYz++BOaNm1mKqPX69Hr9Y9dvG2LSpUqMXXaNH5avoyvvzZOcoSHV2Ta9K+oWNH24Z9Zvy7EsWk7HJu8hsRBiS4lkayNUWYeLiQSJFIZ1tbCKyIi0aXfpyDG1uSMAfXqOTjUa4k8vCYOdVtgyNeiu5+Aes33FNy8ZLXWjKVJdG3rTuc2bqiUMmKT8pn1UzKHHjovp+i7LBKsQAdfzE+gx2sevPOGBwq5hJjYPKb9mMjlhw4VzVAbQwRfb+aCm7MMmUxCSnoBpy7lsOHPDJMRbo0q349HGVqkhwFvtSXgrbYA/FXuJTS3Y0EmRWpnZ7bjgz4vnyOt+1Bx+igqz/oUmdKRzLOXOfbaAFL3HzfrI3XfMY6/PpDyE96nzsb56HI0JG3dw+WPv0KfZ+k5HfPpBH5etpiVPy1DrVYTFBzMyI/H0eQh78M/0TF3Dw9kUilrVv1MZmYGEokE/4BAuvXswxtvdrK5pvazT8exdNlylv/0M1kP5Prk49E0e8i7+091H4xnGd69e4/u3bqWaH3vvF/VdGimpF0TJU4OEhJSdCzcqOb4paLfu1QKMqnEbNOOAh3MXJlJp+ZKurZyQm4v4W5iAXPWqM08Vwbg21WZtK7vQK2KclrVc0SbbyDuvo7ZqzO5cNO2h/1F1C94cXXs66hEur7mwdtt3VE5yYhNzOPbpYmmw84BpKbnT1G9Ah1MnBtPz3Ye9OvohdzeOFZMmZ/ApRtFz4xgPzl+XsZQz+G9fCz6X/tHGmu3pT3x9T5tDC/OcrHnhsQg/HoCgeAxtO595nmL8J/DO8jy4fciMOGd4hd5Py881379vEWwyrv3Rz9vEazSe47185ieN+Wu7HreIthEzoup+1PXuD9vEazSYXzk8xbBKi+qjo2b82KcXfUov8z+58e5/F1Gz39269K/GlTyc+yeJ2LXQcF/hhUrVqBSqax+Kleu/K/JUblyZZtyrFix4l+TQyAQCAQCgeBFRW8wPLPPfwUROij4z9CuXTvq1bN+sOCjByk/S7Zu3Up+vvWZq0e3VhcIBAKBQCAQ/P9EGFqC/wzOzs42zzj5Nwmxsf2vQCAQCAQCgcCIWJ0kDC2BQCAQCAQCgUDwlPkvHSz8rBBrtAQCgUAgEAgEAoHgKSM8WgKBQCAQCAQCgeCpIiIHhUdLIBAIBAKBQCAQCJ46wqMlEAgEAoFAIBAInioGsUZLeLQEAoFAIBAIBAKB4GkjPFoCgUAgEAgEAoHgqfJfOlj4WSE8WgKBQCAQCAQCgUDwlBEeLYFAIBAIBAKBQPBUEWu0hKElEAhKQIE273mL8J/D0UnxvEWwytXw5s9bBKs0Ojr3eYtglfcUPs9bBKv4Ddn1vEWwyvXwFs9bBJvIHF/MIJ5Pu1R43iJYJfeK0LEnYdylg89bhBcOYWiJ0EGBQCAQCAQCgUAgeOoIj5ZAIBAIBAKBQCB4qgiHlvBoCQQCgUAgEAgEAsFTR3i0BAKBQCAQCAQCwVNFrNESHi2BQCAQCAQCgUAgeOoIj5ZAIBAIBAKBQCB4qhjEgcXCoyUQCAQCgUAgEAgETxvh0RIIBAKBQCAQCARPFb1YoyUMLYFAIBAIBAKBQPB0EaGDInRQIBAIBAKBQCAQCJ46wqMlEAj+NjKZhG4d/GnTzBsPN3sSkrRs2pHExu2JJarvoJDyzttBNK3vgYvKjjtxGlZvimf34dRi6307PpyIii5s3J7Id0tuv5BybTlpTFPYQ4emSmpXVODkKCEhRccfhzUcv5T3WDmclRI6vaSkajk5cnsJ9xIL2LgvhysxBaYynq5Spr/nbrONCzfymL1GbZEuUzkRNm4ILtXCcaleCYW3B9GTvuPaF98/Vi4AubcH4dNH4ftKc2RKBzLPXeHq57NI2X3EoqznSw2oMHE4LhHh6HJySdy6myuffE1esvX7mZOby/w1v7PryCkys7MJCfCld7tWtIqsXaxMv+89zKT5P1vN2zpvKl5urmZpmlwty3/byY5DJ0m4n4qjg4KwUgGM6d+NUv4+Fm3kanLYtHIuJw7tIDsrE7/AUNq82Ze6jdoUK9els0fYvmEpcXdvkK3OwFGpIqBUOVq170nVWo0tymtzNWzbsITjB7aTmhyPwkFJYGgYPQd9im9AiEV5jUbDz8uXcHD/XtTqTIKCS9HxrS40adq8WLke5edli1m7ZiWlQkL5ft4is7yxH4/gwvlzFnVq1KrNxC+mW23vRdUxmZOSsM+G4/dGG+zdXcmOvsnNbxeR8OvWx8rk9XJDyn48BJdqldDn5ZN26ATR478h68p1s3ISe3vKjh5EwNvtcAjwQZtwn/h1v3P9yx/Q52qtti1ROODWvjvK2g2ROanIT4glY9uv5Bw/8Fi5FBWq4Nq2E/KgUCRyBQX3E8k6sBP17j/AoDfvR67Apc2bONVphJ2HD3qthvzY26T89AMFSfEWbQv9evIxLFeTw5qfFnLkwF9kqdUEBJWifaeeRDZtUSLZClnz00I2rFlGUKnSzPjBfGw7eewgR/b/RczNaOLu3Uan07H694NP1P6zRmzvLgwtwQvGoUOHaNy4MS1btmTbtm2m9JiYGEqXLm36383NjapVq/LFF1/QtGlTAPr06cOyZcsAsLOzIzg4mDfffJOJEyfi5ORUbL8laR/g3r17lClThjJlynDlyhWLdgwGAz/++CNRUVFcvHgROzs7ypUrR48ePRg4cCBKpZIJEyawceNGzpw5Y6q3f/9+Xn/9dXr27MmcOXNYtmwZffv2tWhfoVCQm5uLRCIp9np69+7N0qVL2b17N5MmTeLs2bPk5uYSGBhIZGQkUVFR2Nn985//8HdCaNnYiyVr73H1Zja1I1x5r3cplI5SVm60fGA/ysSPwqhQxolFq+5yLz6Xlxp68unwckikN/jrYIrVOu1b+xDg6/CfkWtwR2dC/e1YvyeHxFQddSspGNjBGQlqjhVjbNnJYEQ3F5QOEtbszCYz20DzWg4Mf9uFb1dlEn3HaGxlZOmZtjTDon718nLaRjpyOtp6H3JPN0r170zmuSskbt5FqX6dH3tfCpHK7am3Yyn2ri5cHDGFvKQUQgZ3p+6WRRxt3ZfU/cdNZT0a16Hu7z+StHUvJ94cgtzHk/CpI6m3YykH63VEn5dv0f7H3/zIpZu3ea9Le0r5+7L94HE+/W4JeoOBNg3rPFa+zwf1ICTAzyzNTaUy+z8nN5fBX8zmfloGvdq1IqxUIFk5Gs5du0lunvV7Nu+rj7h9/SJv9Hgf34AQju3/g0XfjMGgN1CvSVub8mSrMwgILkujFm/g4u5JjjqTvTt+4bsp7/PO8MnUb/qqqWyuJoeZnw8gIy2ZNm/0JTA0DE12FjevniVPm2u1/WmTJ3Dt2lV69+lPQGAQ+/b8yYwvp2DQ62na/OXH3i+Amzeus2H9OtzcbRvtfn7+jBg9xixN5aSyUfrF1bEaK+bgWqMK0RO+Ift6DP5vvUb1JTM5K5UQv26LTZl8XnmJGiu/I2nLX5zuORx7FxVlP3mPutt/4nCzzmhu3TWVrbZ4Bt6tmnDjyx/IOHUBt7rVKTtqEKqK5TjV5T2r7XsP/gR5SDnSNywnPzEOp7pN8B4wkmSJlJxj+2zK5VAxAp/h49Feu0TKTz9gyMvFMaIuHl0GYOftR9qaKFNZicIB34++QObqQea29eTFxiB1VKIoE45ErrDavtCvJx/DZk4dy83oK3TtMwj/wGAO7tnJnK/HozfoadSsVYlkjLkZze/rV+Hq5mE1//jhfVy7epHQsmHY29tz8/rVEl+/4N9DGFqCF4rFixczbNgwFi1axJ07dyhVqpRZ/q5du6hcuTJJSUmMHTuWV155hQsXLpiMpDZt2rBkyRLy8/PZv38//fv3Jzs7m3nz5pWo/8e1v3TpUjp37sy+ffs4ePAgDRs2NKvfs2dP1q9fz6effsr333+Pt7c3Z8+eZdasWYSGhtKhQweLPrds2cJbb73FqFGjmDhxoindxcWFq1fNB85CAys+vshYWLNmDZ9//rlZWUdHRy5evEjbtm15//33+e6773B0dOTatWv88ssv6PXmM5x/h5AgR9o292bxmnus/T0BgLOX1Lg429H9jQB+25mEOltns37d6q7UjnBl8pzr7D5knBU8c0mNr7eCd7sHs+dQCo9Ohvl6y+nfJZjpP9xk0kdhL7xcVcraU7mMnB83FhlVV28X4OkqpdPLThy/nIetEPZG1RQE+dgxbVkGN2MLHtTNZ3x/Vzo2VzJtWSYABTq4GVdgUf+N5kq0eQaOXbRuNGhux7LD22i02Hu6P9FLSvA7b+FSpQIHG79N+pEzAKTsOUrjk5sInz6KQw2L2qr45Wiyo2M49fb7GHTG+66JuUfkvtUE9e3EnQWrzNo+ePoCR89f4YuhfWnd0OjBql25PAn3U/luxQZaNqiFTFp81HuZoAAqlbX0/DzM/DW/ExObwMovxxHo62VKb1I7wmr58yf3c/nsEfp/OJW6jY1GVXjVOqQkx/Pr8m+p07AVUpnMat06jVpTp1Frs7SqtRszdtBr7N/5q5mhtWnlXBJib/H5N2vx9gsypVev28xq2yeOH+XM6ZN8NHosTZu9BEBEteokJSWxZPFCGjVphsyGXIXodDpmf/s1bdq+xq1bN8jMzLRaTq5QEB5eqdi2HuZF1DGvVk3weqkhZ9/5iPhfjB6s1P3HcCwVQIUvRhH/6x9gY3wsP+kj1BejOd19mCkt7egZmpz6g7BxwzjXfzQArnWq4de+FVfGTCdm7rIHsh/GUFBA+Qkj8GweScruQ2ZtO1SphWOl6iT/OJOc4/sB0F69gJ2nD+4dexu9Wgbrcjk1eAl0OpK+m4whz+gty718Dnu/QFSRL5kZWm7tu2PvF0T8pA8ouF/k4decPW7RLgj9gicfw04fP8T508cZNmoCDZu2BKByRC2SkxNYsXgukY1ftjlWFKLTFTB/1lRebtOe27euo85MtygzcNjHSB+MhYvnzXwhDS3h0RJrtAQvENnZ2axdu5bBgwfz2muvsXTpUosynp6e+Pn5ERERwYIFC8jJyWHHjh2mfIVCgZ+fH8HBwXTr1o3u3buzcePGEstQXPsGg4ElS5bQs2dPunXrRlRUlFndtWvXsmLFClatWsXYsWOpU6cOoaGhtG/fnr/++ovmzS3DLFauXMmbb77J9OnTzYwsMBpVfn5+Zh9fX18AszRXV1eLsq6uruzcuRN/f3+++uorqlSpQtmyZWnTpg2LFi1CLpeX+J7YomFtN6RSCdv23DdL377nPg4KGXWquxVbv1Edd3I0OvYeMQ+92LYnGS8POeFhljOZIwaU5uT5DA4eT/tPyFWjvJxcrYETl82NnUPntLg7SykTYHuuq0YFOfEpOpORBaA3wJELWsoE2uOmsj18e7tJKV/KjhOXteTmPf0HnW/7FmRduWl6QQEw6HTErtyMe91qKAKMYXeKAB/c6kQQu2KT6QUFIO3wabKu3sKvvWUYzZ7jZ1E6KHi5fg2z9NeaNiA5LYOL12P+sfy52jw27T7Iy/VrmhlZxXH66G4UDkpqRbY0S2/4UjvSU5O5de38E8lgZ2eP0skZqbRIB7RaDQf+3ECtBi3NjKziOHLoAI6OjjRq3NQs/eWWrUlNSSH6qqXn/VF+WbuKLLWaHr3feaJreJY8Kx3zfa0FBepsEjZsN0uP/Xk9DgG+uNkwtO093FCVL8P9nfvN0nPvxqG+dA2fV1+GBy+97vWMupu8w9wLlbRtj1GGduY6BKCsUQ99roack+ahX1kH/8TO3RNFaesTSwDodBgKCjDkm48z+pxsDPlF3haJXI6qUQtyTh4yM7KKQ+jXk49hxw/vw8HRkfqNzJ/5zVq8Slrqfa5FX3qsfJvW/UyWOpMuvQbaLCN9zIST4MVAfEuCF4Y1a9ZQoUIFKlSoQI8ePViyZEmxO9YolUoA8vMt3faFODo6FptfHI+2v3v3bnJycmjRogU9e/Zk7dq1qNVFa19WrFhBhQoVaN++vUVbEokEV1fz9SFz586lb9++REVF8f777/8tGYvDz8+P+Ph49u2zHXLyTygdrCQtI5+0DPP7e/NOzoN8x8fWvxOrsZg8vnlHY7X+K829CS/rZHVN1osqV6C3jPgUnYUH7F6S8YEd4G17VjPA247YJEtPVUnqNqymQCqRsP+s9bUg/xTnymFknrecPVU/SHOuFPagXHkAm2UL8x/mxr14QgP9sHtkxrdcqQBj/t24x8o34ut51O82lBb9RzH6m4UWdS7fuoNGm0ewnzfTo1bxcv+RRPZ4n15jv+TAqQtW24y7cx3/oNLIZObGcVCI8Rpi79x4rFx6vR6droD01CQ2r55HYvxtWrbracq/c+My2lwNPv6lWLFgCh/0bMLgznWYMqob507st9rm7dsxBAWXsvAqlC5d5kH+rWJlunPnNmtXr2Dw0OE4Ohb/20iIj6Nb5zfo8ForBr7Tk5+WLUar/W/pmHOlMLKib5i9NAOoL0QDoKpk3aCR2tsDoLcSVqrPy8POSYmyjDECQyq3XrYwxMy5SgWLNuQBpciPv2vhTcu/FwOAfaBtD6163zYkdna4d+mPzNUdiaMTTvWboaxRj4ztG4r6KFUOqYMj+UnxeHR7l6Bvf6bUD+vwGzsDx6q1rLYt9OvJx7C7t28SGBRqMVaUCi1ryi+Oe3dusWHNMvoNGYmDo7IEV/PiojcYntnnv4IIHRS8MERFRdGjRw/AGAKYlZXFn3/+SYsWljNG2dnZjBkzBplMZraG6mGOHTvGypUrefnlksWQP679qKgounTpgkwmo3LlypQrV441a9bQv39/AK5du0aFCpYPUGtcvnyZoUOHml3zo2RkZKB6ZF1JZGSkmQevON566y22b99O06ZN8fPzo379+rz88sv06tULFxcXm/W0Wq3Fw02vy0MqM/eCuTjboc6yNARytXry8vW4qIofXlyc7YhLtFxzUtjmw/W93O15t0cwC1feJSWteMP5RZJL5SglOd0yTDFbo3+Qb3utncpRQrbG8mGSnWsotq5EApFVFcTfL+DGPcv78DSQe7qRn2a5LizvQZrc083sr/Wy6dg/yH+YDHU2gT6eFumuKidTvi08XV3o26ENVcJCcXJ04MbdOJZt2sE7n33NjxM/onyI0UuUnJoOwPLNOylXKoAJg3sjkUhYseVPPpoxn1kfD6FBNfMQpix1Bt6+ll4mpcr4W8pWp9uUq5DvJg/j4hljyJiDUsXAEV8SUbtoM4y01CQAtm1cSmCpcvR9/wskEik7N//E3GnDef/T76lcI9KsTXVmJr7+/hZ9qZydTfm20Ov1zPn2axpENqJ2nXrFyl6pUhUaNWlGUFAp8vK0nDxxjPW/rOHSxQtMmT7jqc+uPysds/dwIyfmrkXZwvpyDzeLPABt0n3yUtNxq1fTLN3O1RnnimGmujlA1hWj0e1Wvyaa27Gmsu71a9rsQ6pypiDZ0sukz8ky5js5W5ULIO/WNRJnfobXu6NxaW4MQzXodKRv+An1zk2mcjJ341of1zZvkBd7m5Qls8Ggx6Vle7zfG0fSnEnkXjpj1rbQL+PfJxnD1OpMfP0CLNJVzsaxIivTsq1C9Ho982dPpU5kU2rUibRZTvDfQRhagheCq1evcuzYMdavXw8YN7N4++23Wbx4sZmhFRkZiVQqJScnB39/f5YuXUrVqlVN+b///jsqlYqCggLy8/Np37493333XYnlsNV+eno669ev58CBot2fevToweLFi02GlsFgeOwmFYUEBQXh5ubGV199Rdu2bfG38iBzdnbm1KlTZmmPmxF8GJlMxpIlS5g8eTJ//fUXR44cYcqUKXz55ZccO3bMap8A06ZNswhjLBsxkNKV+5n+L5x0LW5O6Z9OOD1c/4P+ody4ncOWP5PNykgkpmidF0ous/LFtfW4vv5GXpUy9ri7yFj3p7l9YSUAAMe7SURBVG2D5KlQzI208ETbKmsjvbjfUXF5DapXpkH1yqb/a1YMo2GNKnQbPYWF635nxshBAKbZUHs7O2Z9/B5OjsZNTGpXLk/HDyeweMMfFoaWsXObXRuV8TF06T8aTXYW6WnJHN23lYXffEzfYZNMa74K1zPY2dkx/LPvcXA0GpcVqtbms/fa8/u6Hy0MLaNYf+9+bdrwC/FxsXw6/ovHyv5o2FftOvXw8fVjyaIFHD1yiAaRjR7bxhPzrHTsSdp9qM6dH1dS7uMhlB09mLuL12DnoiJ8+hikSqP+GB4MQMk795N94zYVJn5EXlIKGafO41anGuXHf4C+oMBUzkonNuUqLk9eqizeQ8agvRVN6s/z0Ofl4lAhArf23ZHYy8nYstZYUGIcLA0FBSTNnoThweYquVfPE/DFPFxf62xhaIHQr2LL2kr/m2PYlo2rSYi7x6jPvrJZ5r+EWKMlDC3BC0JUVBQFBQUEBgaa0gwGA/b29qSlFa17WbNmDZUqVcLNzQ1PT8tZ7+bNmzNv3jzs7e0JCAjA/kG4R0mx1f7KlSvJzc2lXr2iWTmDwYBer+fSpUtUqlSJ8uXLc/ny5RL14+zszK5du2jVqhXNmjVj9+7dBASYz4BJpVLKlSv3RPJbIzAwkJ49e9KzZ08mT55M+fLlmT9/voUxVciYMWMYMWKE6X+JRIKzs/ls6ohJl8lUF1A2xDKswUEhRW4vRZ1dvDclU11g1bvk/CCtsH6Teu7UqebK8AmXcVKah6+0b+VL+1a+L5xcdnYSHBUSsnP1qBwtZ2KdHqRZ81gVkqUxWPVaOTlIiq3bqLqCAp2Bw+efTcgNQF5KOvZWZuXl7sbw2PzUDFM5wEZZN1O5h3F1diIjy9JILExzUT1ZKE2AtyfVKpTlwrWYoj4eeMciypc2GVkADgo5NSqGsffEWYt2VM6uZKst5c3JMs7oO6lcLfIe5eGt2avXbcbsL95j5Y/Tqd2wNVKpFJWzsY2yFaqZjCwAhcKR8pVrcfroHos2nV1cUKstvQpZD8KaVc7WPSHJSYms+HkZvfv0x87Onqwso+dEp9Nh0OvJysrC3t4ehcL6TnQAzZq3YMmiBVy9cvmpvwg/Kx3LT7Xern1hu1Y8F4XcmP4Ddk5Kyo4aRNinxnDvpG17iP15A8F93iI3zuiRMuTnc7LjQCIWfkmdTca1vAVZ2VybNIuyoweTG5dk0bY+S23VayVVGqMa9NlZNuXy6DYQXWY6yT9MN22Yob16AQx6XF9/m+yjeym4n4j+ga5qb1wxGVkAhrw8tNEXcaxh6XUS+pUOPNkY5uzsYtVrlfXgPjo5W48ouZ+UwLoVi+jaezB2dnZkZxnvsV6vw2AwkJ2lxt5ejryYe/aiIQ4sFoaW4AWgoKCA5cuXM3PmTFq1Mt/2tGPHjqxYsYLXXnsNgODgYMqWLWuzLScnp39knNhqPyoqio8++og+ffqYpb///vssXryYGTNm0K1bN7p06cKmTZss1mkZDAYyMzPN1mm5u7uza9cuWrdubTK2HjY0nwXu7u74+/uTnW3b26FQKCwefoPHXjT7/26chlvlc3ipoSfurvZm66EK1zDduqspVpabd3N4KdITqdR8WUKZR+qHBiuxs5Myd3Jla80AMP+n25y9nPXCyPXayz689jJcvJlH2UA7pBLM1mkF+hgNs7hk27sfxiYVEGhlHVZh3dhkS4PRWSkhopycs9fyUOc8uwec+kI0LlUs1yY4P0hTX7z24G/0g/QKJG/bZ1G2MP9hygUHsOPQCQp0OrN1WoXrrMoGW4bkPA6DwYBEWmS0hpUq5ndmMCC1MuMcGBLGsf3b0OkKzNZe3LtjvNbAUrbHJVuUDqvCxdOHyMpMw8XNk8AQ2xseGAwGpFJLuUJCS7N/7250Op3ZOpqYGOPamZCQ0hZ1ABIS4snTavlxwVx+XDDXIr9b5w683v5NBrw75LHXUVJP/pPwrHRMfTEa/06vIpHJzNZpqR6stcm6dM2mTAadjitjv+TalO9wDAkkPyUdbWIytTf8SM6tu2jjikL/cm7e4UiLrij8fbB3dyXn1l3sXZyp+NU40g6dsGg7L/YOTnUb8+jAYx9kNM7zY22vTZUHlyb72H6LXQnzYq4jkcqw9w+i4H5isW0gwepui0K/nnwMCw4ty6F9Oy3GirsxxrVZwSFlrMqUmBBHnlbLsoWzWLZwlkV+vy5taNvuLXoP/ODxFyh4YRCGluC58/vvv5OWlka/fv0sNozo1KkTUVFRJkPreXDmzBlOnTrFihUrCA8PN8vr2rUr48aNY9q0aXTu3JkNGzbQtWtXPvvsM1q2bIm3tzfnz5/n22+/ZdiwYRbbu7u6urJjxw7atGljMraCgozrQAwGAwkJCRby+Pj4lChefcGCBZw5c4Y33niDsmXLkpuby/Lly7l48eIThVMCRN+0NMwOnkinb+cgWjf1YvXmou3mWzf1Jler4/iZ9GLbPHg8jdde9qFJPQ/2PHQQcKumXtxPzePKNeMM6Pa9yZy9ZDmj+s3nFTlwLJX12xK5dVdDprrghZLrcLQMFycplcvIqRkuN9t5sEFVBWlqvdVt2Qs5HZ1HjzYqSgfYcetBOakE6ldRcDM2n4wsS0OqQVUFdjIJB848O28WQMKmXVT9fgJudSNIP2Y8ZFQikxHYrR1pR8+gjTfO2Gvjkkg7dpbA7q9z85so04ucW71qqMLLcOu7ZRZtN6tTjY1/HWT3sTO0bFC0QH/LvqN4u7tSuVzoE8kam3Sfc9E3qVOl6Lfr5e5K1bDSnL16k6wcDSql0YjO1eZx6vJ1qoRZvjxWr9ec/TvXc+rwn2ZbtR/e/RtuHt6UDqtqUac4DAYD0RdPonRyxumBJ8vNw5syFSK4fuUsmpwsHB94M7RaDdEXT1K6vGUfDRo0Yse2rRw6sI/GDx0g+9euHXh4elK+QrhFHYDSZcoxZfoMi/RFC+eRnZ3N8A9H4unlXew1/LXLuF60QnjFkl30E/CsdCzx910E9+2Mb/tWJKz/w5Qe2K09uXGJpJ+wPDT3UXTZOSaDzKVaJTya1ufqOOuhXtr4JJOspT8bTkFWNveW/2JRLufMEZybtEJZswE5J4p2HlQ1aE5BWgraW7YNwIL0VOSh5YyhgQ8ZW4qyxjXDBWnGs/90GWnk3riColxFJA6OGHKNk0YSuRxF+Spob1kaDUK/nnwMq9OgCX9t38zRg3uIbFK09GHvX3/g7uFFWHnrW9iHlgnjs6mWz+blP84mJyebQcPH4ulleZD6i4xehA4KQ0vw/ImKiqJFixYWRhYYPVpTp04lNdX66ev/BlFRUVSqVMnCyALo0KEDgwcP5rfffuPNN99k5cqVLFy4kMWLFzN58mTs7OwICwujV69etG7d2krrxvOytm/fTtu2bU3GFkBmZqbVdVTx8fH4+flZpD9K3bp1OXDgAIMGDSIuLg6VSkXlypXZuHGjzQ1EnoTb9zT8sTuZ3p0C0ekNXL1hPBj41Ze9WbL2ntlZVT3fDKBnx0BGTr7CucvGcIhjZzI4cS6D4f1CUTrKiEvIpXlDT+pWd2PqdzdMHqDE5DwSk62fBXU/LZ+zl9RmaS+KXNF3jAUbVcujRxsnHBUSktKMBxZXLStn0Sa1Kby/9ytONIhQMPaHdFIzjQ/yg2e1NK/lwLtvqFi/Owd1joFmtRT4esj4dpX1BeiNqilIydBx8WbJdtr0bt0EmZMjds7GMDVVxXL4vWnU06Q/9qLX5BKxcAqBPTuwp0JLNHeMXqV7S34hdFA3aq6azZVxM9EmpRA6qBtOFUpztLX5QdtXxsyg3rbF1Fo9m5j5K1H4eBI+5SMyL1zl3tJfLWSKrF6ZelXD+TJqNdk5uQT5ebPj0AkOn73EpPd6m87Q+mLBz2zdd5T1sybg720M831vyhxqhJejXKlA02YYP/22E4lEwqDO5pM1w3u8yeAvZvP+9Ln0er0lEgms2PIn6eos3n3LcmKnas1GVKxWnxULp5KrycbbL5jjB7Zx8fQh+g2fYjoXZ9ncCRze/TtTftiMp4/R+zZ32gcEhZYnuHQFnJxdyUhN5tDu34i+eJJuA8aYzXq/1ftDZn4+kNmThtD6jb5IJLBz809kqdNp39Vy9r9WnbpUr1GLeXPnkKPJwd8/kH17/+LUyeOMGDXG5IWYM2sGf+3awcKon/Dx9UWlUlE1orpFe05OTuh0OrO8ixfOs3bNCho0aISvnz/5+XmcPHGM7X9sIaJaDerWa2DRTiEvmo7d37mf+38dpNK3n2PnrCLn5m38O72Kd8smnO0/yvQiXeX7yQR0a8++aq3JfeBN9WhUB5eaVcm6eBUkElxrRVD6g37c33WA2wtWmPVTeng/tEn3yb0bh9zHC7832uD72sucG/ix6SX+YXIvnEJz6Qwe3QchdVCSnxyPU50mOFapxf1F35gMKM9eQ3Fq0JzYcYPQpRrXhqp3/YZH1wH4DB2Het92DHlaHMIjcGnVHs2lM6adCwHS1y3B96PJ+A4fb9yR0GDApWV7ZCpnkjettJBL6NeTj2E1ajegao06RP0wA01ODn4BgRzcu4uzJ48w9KPPTWPF/NnT2PfnH8xetBZvHz+cVM5Ujqhp0Z7SyRmdTmeRl5yUwI1o43KFxATjdR05YHx/8Pb1o2zY0zdQBU+OMLQEz53ffvvNZl7NmjVNMb6Pi/W1du5WSQkNDbXZfnHeH29vbwoKirwSUqmUQYMGMWjQIJt1JkyYwIQJE8zSnJ2dzTba6NOnj0WYoi1sla1RowY//fRTidr4u8xefJv7afm80doXdzd7EpO1zF12h43bzXfPkkglyGQSi/XB42deo1+XIPq8FYizyo67cblMnn2d3Yf/mWH9Isk171c1HZopaddEiZODhIQUHQs3qjl+qchIk0pBJjWXo0AHM1dm0qm5kq6tnJDbS7ibWMCcNWqi71h6wsoG2uHvZcdv+3Meu8lGIVW+H48ytGgnvYC32hLwlnFjhr/KvWTcMU0mRWpnZ7a4W5+Xz5HWfag4fRSVZ32KTOlI5tnLHHttAKn7zQ8+Td13jOOvD6T8hPeps3E+uhwNSVv3cPnjr0zbXT/KlyMGMG/Nbyz45Xcys3IICfBl8rC+tIqsXSSDXo9Orze71rLBAew8fJIVW/4kNy8PDxdnalcuzztvtiXE39esj4jyZZg7bhjz1/7O53OXGu9HuVDmf/4BEeWth/YMHj2TjSu/Z9OqeeRkZeAXGEr/EdOo26iNmVx6vc5crvDqnDq8i91/rCE3JxtHJ2dCy1Zi6Ng5ZrsOFpb9cOICNq2cS9SssQCUKR/ByEk/UrZCNatyjfl0Aj8vW8zKn5ahVqsJCg5m5MfjaPKQB8Iolx5DibWjCHcPD2RSKWtW/UxmZgYSiQT/gEC69ezDG292KtbD/iLq2Onu7xP2+XDKjRuG3N2VrOibnOn7EQm/bjWVkTyQ6eHfpD4vH7/2rXAaNQipQk7Ojdtcn/Idt+f/bBF2J3VQUPbjwTgE+KHX5JJ+4izHXulN2uGTNu9V8rzpuHXojmv7rsiUzuQn3CP5xxnGw4pNDUuRyGRm90q9ewsF6Sm4tGiHZ6/3kNjLKUhJIuO3NWTu2mzWh/bmVRK//Ry39t3x6vfhg7RoEmd8St5N6wfeCv168jHso7FTWb18IetWLCJLnUlAUAjvj5pIZNMiD5derzOtv/o7XDx3kvmzppqlzZr+KQBNXm7LkA8//VvtPk3EZhggMYiVagKB4DG83OXY8xbhP0eZiCdfs/Nv0GH8i7llcKOjlus4XgTOKF7M++XnkPK8RbDK9XDL4zheFGRWNqZ5EajYpWTHgvzb5H78ZCHm/xYvqo4FXDr4+ELPgRphJTuU/VnQfUzs4wv9TVZMe7Zr2p8WL+aoIxA8ZQYNGoRKpbL6Kc77JBAIBAKBQCB4cgwGwzP7/FcQoYOC/xdMmjSJkSNHWs0r7vBegUAgEAgEAoHg7yAMLcH/C3x8fPDx+W/t1iMQCAQCgUDwX8X24dz/fxCGlkAgEAgEAoFAIHiqiO3dxRotgUAgEAgEAoFAIHjqCI+WQCAQCAQCgUAgeKr8lzateFYIj5ZAIBAIBAKBQCAQPGWER0sgEAgEAoFAIBA8VcSBxcKjJRAIBAKBQCAQCARPHeHREggEAoFAIBAIBE8V4dESHi2BQCAQCAQCgUAgeOoIj5ZAIHgs2mzN8xbBKnYK+fMWwSbXz1x/3iJYRXnqzPMWwSqbUh2ftwhWeV2293mLYJV+swOftwhW+ezSwectgk0ytE7PWwSr/HbH4XmLYJU9c249bxGsMu4F1bG4Sg2ftwhWqZF/9bn1rTeIA4uFoSUQCAQCgUAgEAieKiJ0UIQOCgQCgUAgEAgEgv9xfvjhB0qXLo2DgwO1atVi//79xZbfu3cvtWrVwsHBgTJlyjB//vwn7lMYWgKBQCAQCAQCgeCpYtAbntnnSVmzZg0ffPAB48aN4/Tp0zRu3Ji2bdty584dq+Vv3brFK6+8QuPGjTl9+jRjx47l/fff59dff32ifoWhJRAIBAKBQCAQCP5n+eabb+jXrx/9+/enYsWKzJo1i+DgYObNm2e1/Pz58ylVqhSzZs2iYsWK9O/fn3feeYcZM2Y8Ub/C0BIIBAKBQCAQCARPFYPB8Mw+Wq2WzMxMs49Wq7UqR15eHidPnqRVq1Zm6a1ateLQoUNW6xw+fNiifOvWrTlx4gT5+fklvgfC0BIIBAKBQCAQCAT/GaZNm4arq6vZZ9q0aVbL3r9/H51Oh6+vr1m6r68vCQkJVuskJCRYLV9QUMD9+/dLLKfYdVAgEAgEAoFAIBA8VfT6Z7e9+5gxYxgxYoRZmkKhKLaORCIx+99gMFikPa68tfTiEIaWQCAQCAQCgUAg+M+gUCgea1gV4uXlhUwms/BeJSUlWXitCvHz87Na3s7ODk9PzxLLKUIHBQKBQCAQCAQCwVPlRdl1UC6XU6tWLXbu3GmWvnPnTiIjI63WadCggUX5HTt2ULt2bezt7UvctzC0BAKBQCAQCAQCwVPFYNA/s8+TMmLECBYtWsTixYu5fPkyH374IXfu3GHQoEGAMRSxV69epvKDBg3i9u3bjBgxgsuXL7N48WKioqIYOXLkE/UrQgcFAsHfRiaT0OutUrzSwg9PDznxibms3xLLr7/Hlai+o4OUAT1K81Ijb5yd7blzL4eff7nDn/uTzcod+K2pzTbuxGroNfyMhVw93gykbXNvPNzlJCRp2bAtgQ1/WF/0ak2ufl1K0SzSExeVHXdiNazcGMtfB1PMyn3yXlnaNPexKlPvD89ZpMtkErq/EUDbZt54uNuTkKRl4/ZENmxLLJFcDgop/boE0azBA7niNKzcGMfuQ6lm5T4eUoY2zbytynXjQdFcTQ6bV3/PyUM7yc7KwC8wlNYd3qFOozbFynD53BG2b1xC/N2bZKvTcVSqCChVjhbtelG1ZmOzsjM/78e1Syct2qhUPZL3P/3BZh95udns2TSLyyf+QJOdgadfGSLbDKRy3VeLle3KqR1cPrmN+JjzqNMTcXLxIqhsDZq8PgwP31DLfrQ5HN72I5eObyUjNRa5wgmfwPK80vMLq+VzcnNZsHoTfx4+QWZWNiEBfvTq0IaWDesWK9fvew4x+YelVvO2LPwaTzdX0/+DJ8zg9KVoi3L1q1Vm1rjhVttwkEvo9ponkTVUqJRSYhPzWb8rjYOnsoqVC8BVJaNne09qV3ZCIZcQE5vHyi0pnI/WmJWrVVlJwxoqSgcpCPSVYyeT8Ob714ttO1eTw5qfFnLkwF9kqdUEBJWifaeeRDZt8Vi5HmbNTwvZsGYZQaVKM+OHn83yTh47yJH9fxFzM5q4e7fR6XSs/v3gY+XatMpc99u8UQLdP2vU/bhHdL9lu15UrdXYorw2V8P2DUs4fnAbqcnxKByUBIaE0WPQZ/gGhFiUz9Nmc2TrbK6f+YPcnAzcfcpQ6+UBlK9ZvN5fP7eD62e2kXT3AlkZiShVnviXrkm9NkNx8w4taj83i7P7f+bu1YOkJd0iX5uDi2cgFWq1o1qTXtjZWw/DcpBL6PKqB5E1nEz6tXFXOgdPZxcrF4CLSkrPdp7Uqqw06dfqramcj841lXFUSGjbxJVqFRwJ8LXHQSElKaWA/SfUbNmbSX6Bbe/Fi6pjMpUTYeOG4FItHJfqlVB4exA96TuuffF9ieSRe3sQPn0Uvq80R6Z0IPPcFa5+PouU3Ucsynq+1IAKE4fjEhGOLieXxK27ufLJ1+Qlp1pp+f8vb7/9NikpKUyaNIn4+HiqVKnC1q1bCQkx/hbj4+PNztQqXbo0W7du5cMPP2Tu3LkEBAQwZ84cOnbs+ET9CkNLIBD8bT4aHEbr5r4s+vkWV66pqVvTg+EDyqF0tOOnddYPAXyYKWMrUzHMmfnLbnEnVkPLpj5MHF0JqfQyO/cmmcq9O/KURd1K5V0YPrAc+49aPkw+HFCaVk28iVp9l6s3sqhTzY1hfUNROspYsT72sXJNGlWB8LIqFq64zd24XFo09uLzD8sjkVzjzwPmuw3lanWMmHDJLE2bZ3227YP+obRq7MXiNfe48kCuoX1CjHJteLxxOmlkecLLOvHjyrvcjc/l5UaefP5BGFLJdf58xAjM1eoYMemKWVpenp7uvcoBsODrEdy+cZEO3YfjGxDCsf1biZr1CQaDnrqNX7EpQ7Y6g4DgsjR6+U1c3DzJzspk/451zJ06jL7vT6FeE/OXQi/fIN4ZPtUsTenkXOx1/jJvGPG3z9P8jY/w8A3l4rHf2bhoBAaDnir1XrdZ7/C2H3Fy9aLhK4Nw8womMy2eQ38sIGryG/QZsxbvgLCie5Gbzc8ze6HOSCKyzUB8Aiug1ai5d/M0+Xm5Vtv/ZMY8Lt+4zZBub1DK35ftB47x2exF6A0GWjeqV+w1AXw6pA+hAX5maa4qJ4tygb5eTBzW3yxN5eRos93R/f0pV0rBz5tTiEvOp3EtFR/18UMqSWD/SdvGlp0dTBgagJOjlMXrk8lQ62jT2JXPBgcwYW4sl64X3Yd6ESrKhzpw656W/AID5Uo5PPZ6Z04dy83oK3TtMwj/wGAO7tnJnK/HozfoadSs1WPrA8TcjOb39atwdfOwmn/88D6uXb1IaNkw7O3tuXn96mPbnP/1CG5fv8gbPYbj6x/CsQNbWfTt43U/KysD/+CyNGzxJq4PdH/f9nV8/0D36zct0v1cTQ7fjO9PRloyrd94h6CQMDQ5Wdy4cpY8G/q1dfEwku5eIPK1Ebh5h3L11Ba2//QRBoOeCrVs6/2pPxehdPGidot3cfUMRp2ewIldC1g9803eGr4GT3+j3qvT4jizdxnhtdtRvVlf7BVK4m6c4Oj277lz9RAdBi+2ush/VD9fypZSsOK3VOKSjPr1YR9fJNJEDpy0bWzZyWD8e0b9WrI+hYwsHW0auTBukD+T5sZz6YbxPnh52PFqM1f2HVfz254McrV6KpZ14K027kRUcGTSD7YnyF5UHZN7ulGqf2cyz10hcfMuSvXrXCJZAKRye+rtWIq9qwsXR0whLymFkMHdqbtlEUdb9yV1/3FTWY/Gdaj7+48kbd3LiTeHIPfxJHzqSOrtWMrBeh3R55V8G/Jnwd85WPhZMmTIEIYMGWI1b+nSpRZpTZs25dQpy/ePJ0EYWv8P6dOnD8uWLQPAzs4ODw8PIiIi6Nq1K3369EEqNUaUhoaGcvv2bQ4fPkz9+vVN9T/44APOnDnDnj17AMjOzmbSpEmsW7eOuLg4nJ2dqVy5MiNHjuS1114rkUwXL15k4sSJ7N69m8zMTEqVKkWXLl0YM2YMSqXSVE4ikbBhwwY6dOhgVv9RmR6+xodp3bo127ZtM7s+AAcHB0JCQujXrx8jR47k2rVrVK9enUWLFtGtWzdTfb1eT6NGjfD19WXDhg02r+dxO9L07t2bpUuXWlxPYb1H77lWqyUgIIDU1FR2795Ns2bNiu1n1apVdOnSBYAFCxbwww8/cP36dezt7SldujRdunTh448/LlbGx1G6lJLXWvqx8KdbrNpwD4DTFzJwdbaj99ul2PhHHOqsApv169fyoG4NDyZ8fYld+4werNPn0/HzUTCkbxn+3J9E4YZFF6+qLeq3axOAXm9g619JZumhQY688pIPi1bdYc1mo/Fy5mImLs529OwYyOYdicXKVa+GG3WquTHp22iTB+vMxUx8vRUM6hnC7kP3eXgjJYMeLl2zfJmVSM0js0ODHHmluTdRq++x5rd4AM5eUuPqbEePNwOMcmXripHLlTrVXPli9nVzubwUvNuzFLsPpfDwM81ggMtW5AI4f2o/l88dod8H06jTqC0AFarUITU5nl9/+pbaka2RymRW69Zu2JraDVubpUXUasy4Ia+yf+evFoaWXK6gTPkIm9f1KNfP7+XW5YN06D+TynWN40doeH0yUuL489evqFTnFaRS67J1HjofJxfzRcqh4fX5fszLHN21lNd6TTGl79k0i/sJNxnw+WbcvYNN6eWrv2y17UOnznPs3GUmvd+fVo2MHqxaVcJJuJ/C9z/9SovIOsikxUfjlw0OoGLZ0MfeA4VcTpXyZR5bDqBmJSXVw5V8szSBAw88WBeuaf6PvTuPqyn94wD+ubd9XxSVkkiLbNmyryGmwY8smSJl7PuWNWNkJ0L2bmUQpcZWsovsW0VJIZVUaE97nd8fdzq63XsrRudc43m/Xl4z556T89E93c5znuf5PtDWlMHEEVq4/aQA4u51rLupwlBPDss83iH+Lf+m91lCETxcDTBxuBaWebyjj9134gP+KbiFKXZadTa0nj68g2dPH2LOkj/Qs+8gAIBFu074+DEdx3he6NF7oNhrrEpFRTn279yAgTYjkJT4Cvl5OULHTJ3jSv/O4u3bXudN8LPHt/Aiin/td+39z7XftgsyP6Yh6Ejt136XnkPQRcS1v2IG/9qv3tA6478H6amJWL09ENo6+vTr7bv0E/l3v40NR0r8HQxx3AaTjvzrXr9VN+RnpeL2ua1oZSn+uredsg+KKoLXvX4rK/its0ZkuB8GjncHAKhq6sNp9VXIyH35nWrQqhtk5BRw++xWpCU+gV6LTgJ/j2VrBbQ3U8QOvwzcfsJvVMW8Koa2pjQchzfCnSefxV5fA7urwlBPFit2pCL+LX99o+cJRdi+VB+OwzWxfAf/8/lDZjlmrk1GSemXv+h5QjFKSihMHNkIZi3kEPdGeH0kSb3GAKAoKRWXtLsAAGQaaXxVQ8vAeQxU25jidu9xyLkXCQDIvHEfvR+fgdmmJbjT88vfZb55KT7Hv8WTcXNBVfB/fxS9fYceN09Af7Idkg/41/u8RMMgc7R+UjY2NkhLS8Pbt29x4cIF9O/fH/PmzYOtrS3Ky7/chMrLy9d5Qz59+nScPn0ae/bsQVxcHMLCwjB69GhkZmbW+nVV7t27BysrK5SWliIkJATx8fHYsGED/Pz8MGjQIJSWlv6rf2P1P/7+gh86VV3IL168wOLFi7FixQocPHgQJiYm2LRpE+bMmYO0tDT6+O3bt+PVq1c4cOBAreeufs6dO3dCVVVV4DVPT0+xX2tgYAAfHx+B1/7++28oKyuLPN7Hx0fo31nVcPP29sbChQsxd+5cREVF4fbt21i6dCkKCuoeUlSX3t20wOVyEHpF8GljyJUMyMtJoVsn0U8Hq/TproXCwnJcjxAcJhh6JR3ajeTQ2kRV7NcqKEihf09tRMXmITVd8Olwr66a4HI5CLsu+PdeuP4B8nJS6NpBvfZ/l5UmCosqEH5X8Pq9cO0DtBvJwryV6PehLj27aIDL5eCCUK6P9crVqys/140aucJufIS25tflirx/DXLyiujYfZDA6z0GjEBu1kckJjyr998FAFLSMlBUUoFUHTc19fHy6WXIyinCvJPgMK72PUehIOcD3idGif3amo0sAFBRbwJVjSbIz/pynZaVFCEy4hTMO9kINLJqc+PBUyjKy2FAd8EbUdt+PfExOwcxCYn1+nu+N6t2SigqrsSdSMGf6Wv38tBIXRqtmotvEFm1U8a7jFK6kQUAlZXAzUcFMGkuD021L+8n9ZUPph/evQl5BQV069Vf4PV+1r8gO+sTEuJjxXzlF2cCj6IgPw/jJ04Vewy3jsZtTZEP+Nd+px41rv3+I5Dzna790pIi3L76Nzp2HyTQyKrN62dXICOnCOP2gtd9a6tR+Jz7ARlJ4q/7mo0sAFBWawJltSYoyPny+0tGTlGgkVWlSTP+g5Dqx1axasu/vu5GCvZcXbufz7++DMVXfevaThGpGaV0Iwv4cn21qnZ9lZRSAo2sKgnJ/K9rpC66T0BSr7F/q8kIaxTEvaEbWQBAVVQg9fhZaHRtDzk9/nB1Ob3GUO/SDqnHztCNLADIvvsUBS8ToTPi64ZPNgRJKYbBJtKj9ZOSk5ODjg5/CEvTpk3RsWNHdOvWDQMHDoSvry+mTOEPW5k2bRr27duH0NBQDBsmekjFuXPn4OnpSe9v3rw5OnXqJPLYmiiKgouLC8zNzREcHEx/oBkaGsLExASWlpbYsWPHN/W+VP83iqOiokIfM2XKFOzbtw+XLl3CtGnTMGfOHJw5cwa///47zp8/j7i4OLi5ucHf3x+NGwvPy6mu+nnV1NTA4XDqzFJl0qRJ2LVrF3bu3AkFBf5wIR6Ph0mTJmHdunVCx6urq4v9u8+dO4exY8fCxcWFfs3CwqJeOerSopkSsnNKkZUjODTh9Vv+DZ9RM+EhUQJfb6iEt+8KUVFjlN3rt5/p/c/j8kR+rXVvbSgqSCHk6gehfUbNFJGdWyaU601S4T/7xQ/BAgAjA0UkvSsSykV/vYEiYl5+uamVleUi+FAnqKnKICunFBEPssE7mYKCQsG/wKiZArJzy5CdWyNXcrVctQz7NzJQQFJqEWouS/IllwJi4gVzBR205OfKLkPEwyz4nOT3ULxPeQ0dfSNISQn+Cmhq2Oqf/a/Q0qyD+DDg9+5SVCXyc7Nw6/IpZKQl4X8OwnOIPma8w0KnPigu/AxNbV107jkEw0b/Dlk50Q2Aj+8T0Ei3Jbg1sjXWNwUAfEhNgH7LjrVmqy77YwpyM9/DpMOXm4605BiUlRRCs7EhLhxbg9iHoSgtKUJjfRP0+XUuWrXrJ/T3vEl5j+ZNdSFdozFpbKj/z/5UtDNtWWuWRZv2ICcvH8qKCrC0MMXUscPRsllToeNS0z9i8OT5+FxUDB1tTVj36ILJo3+BvKys0LHNdOXwLqNU6LpIel/6z35ZvEwUPVStma4sYt8UCb2elMq/wTXQlUVWrvD++khJeoOm+s2FrrFmzVvS+03N24r9+nfJifj7pB8WrlgPeQXhxsG3Sk1+DV0R177+P9d+avLXXfs3L/Gv/VGOX679pNcvUFJchMa6zXDswHo8uh2GkpIiNDU0wfBx09G2Ux+hvzMrLR4aTYSv+0a6/Os+My0Bukb1v+5zP6UgP/s9WrQV3UNb3bsE/rwfTZ1WQvsMdGVrvb4MdGXx8q1wbxMANNORxYs3wtde0vt/ri+d2q+vtq34n9Xv0kUPf5PUa+zfUrFohawI4bmt+c/4PWkqrVuh5P0HqFiYAADyngn3sOU/ewmNHvW/XoiGQxpaBG3AgAFo3749goOD6YZW8+bNMX36dCxfvhw2NjYin+zo6OggNDQUo0aNgopK7XMvaoqMjERsbCyOHz8u9He3b98e1tbW8Pf3/9fD3OpCURTCw8Px4sULtGrF/2XD4XDg4+ODtm3b4tChQ/D29sa4ceOEhi1+b506dYKRkRGCgoLg4OCAlJQU3Lx5E15eXiIbWrXR0dFBeHg4kpKS6Amf34uqqjTyRAzBKy6pRGlZJdRUa/94UVORxvt04V/Cefn8v1NVRfzX2w7SRX5BGW7eE+41VVWRFjk0sCqXqnLtZVlVVaSRliF841D1b62e61VSIV79lYTEfxpLHVqrws5WFx3bqmL68hgUl3y5O1FVlqkjV+3fL1VlaaR9qC3Xl3/X66RCvP4rmc7VvrUq7H7RQcc2akjKBT7n50CrifCTdiVlflGGz/m5tWYBgD0bZiM28g4AQF5RGVMWbBG6gTQ2t0TnnkOg09QIpaXFiHl6G5fO+OF1XCQW/HFI5OdJUUEO1LWFs8kr8rMVfc6pM1uVyopyhPitgKycIqysnejX87P5xUfuhh2CdlMT/Dp5MzgcLu5f5iHAazrGzz2ElhaCxQ1yCwrQtLFwgRFVZf4NWm6++LkqjdRV4TRqGNq0agElBXm8Tk7FkTNhmLJyEw6uW4pWzb/0qrU3M4Z1j85orqeDktIy3Il8jqNnLyI67hW81iwS+p6pKHGRkSl8I1pQWPHPfvG9jMpKUij4LDyfMP+fhwQqit/eQ5mfn4cmOnrC51Th91QX5Im/xiorK7HfcwO69OgLyy6iSy9/K7HXvso/135B3df+7vWC1/7vCwWv/Zws/gOgi6d90bSZMZzmuIPL5eDy2b/gtXEe5qz0goWl4L+ruDAHqo2Ee1errvviwpz6/QPBv+6vnlwJGTlFdOjrVOuxn96/xJNr3mjRdhC09EyF9vOvL+HPraoHSXVeX4XC11fVa8pK4nuKDPVkMWKgGu5HfaYbdTVJ6jX2b8k2UkdZtnD20n9ek22kLvBf0cfmQOaf/Wyq/IbqgP81pKFFCDAzM0N0tGC1tFWrVsHHxwfHjh2Do6Oj0NccPHgQv/32Gxo1aoT27dujV69esLOzQ8+ePes8X3w8v7qWubm5yP3m5uaIiIj4hn8JcP78eaHhdq6urli9erXA9qpVq1BaWoqysjLIy8tj7ty59P5mzZph586dmDJlCpo2bYqLFy9+U5avNXnyZPB4PDg4OMDHxwfDhg2DtrbwTR4A2NvbCw3Zio6ORosWLbBmzRqMGjUKzZs3h4mJCbp3745hw4bBzs5O7HCIkpISlJQI3tBzqDJwpb7cyFf19lC1jCeqz1Cjb+n8N2qmCAszVQSdT0VFBQWpav+M+uSqz1mp2o6ptuvUecGhNo+jc5GQ+Bl/LjHFr4MaIyiUP1ytks71b1LV8fXVdp4KERzO+fhZHl69/Yy1i0xQyuXftHBQyzzCeqx6P87FFUWf85Gb/Qn3b4bg8I6lcJq9jp7zBQAj7GcLfE3bjr3RSFsPQUc8EPXwBiytBogLID5abbmroSgK54+sRPKrxxg9fRdUNXWr7eO/IVLSMhg/7xDk5PmfE81NrbB39WBEnN8r1NCqI1at37LuHdqge4c29LZlaxP06NgWDovX4mDAWWxdOoveN338SIGv7dGxLXS1G2H3X6dw81EU+nW1FPFvFX/u2n8War/u/vXgnFq+KbXNYw05fQLp799hyeot/zbBV5+7PtfXeBdXFBX+c+2Hh+CQB//ar5rzVXV9SUvLYO4qL8gr8Hv3Tdt0werZwxFy6qBQQ6vq7LWkrjMX/9wUrp5YifdvHmOY0y6oaOiKPTYv6x3OHZoOZXUdDBxXy0O8Wj+36ri+vuEC09aUxrKpOviUXY59Jz6KPqiKhF5j/1qtv1upmi989d9BMIfM0SIEUBQl9OGkra2NxYsXw83NTeR8qT59+uDNmze4evUqRo8ejZiYGPTu3fure1/E5ZEVMVymPvr374/IyEiBP7NmzRI4ZsmSJYiMjER4eDj69++PlStXCi1eN3nyZOjq6mLu3LlQU1MDExwcHHD37l28efMGvr6+cHZ2Fnvsjh07hP6dBgb8J6O6urq4e/cunj17hrlz56KsrAyTJk2CjY0NKmuOBfnHxo0boaamRv9p164dbp23RviZvvQfyzZqyMsrh5qKcO+QvBwXsjJcumdKnNz8cpG9VlWvifv6XwbxbxzuPsrE1YDuAn86WKgiL79coHdHKFcthTCqziuq16uqx6mur49P5PdszJxoiKsnrHD1hBXat1ZBXkGZyH9vVa7aCnRUnVfk9+ufXHV9/a0H2SgqroCqIhdKKuooKMgROqbqab6Ssvj5cVWa6BqiuXEbtO/SD1MXbYVZGyv4H94o9rqqUlUsIzFeuPw9ACgoq4vstSou5GeTV6r7Z5CiKIQcWYnn987iV6eNMO0gOFdBQVkdANC0pSXdyAIAGTkFGJp0RXqy8NwONWVl5Inotcor4PcaqoqoHlgbvcZaaGdmjOcJb+o81qY3vzDO83jhY/M/V4rsVVD+pzdKVI9ClYLPFVAR0augosj952vFF2epi4qKqsgehYJ8/nBgJRXR19inD+kIPHYYo+2dIS0tjc8F+fhckI/KygpQFIXPBfkoLRE9VK0+lFTU8Tk/R+j1ql5cxfpc+3rVrv3FW2HWVvDaV/rn+mpp2p5uZAGArJwCWrXuhOQ3cUJ/p7yiusheK/q6V6zfdX/t5Cq8fHwO1vYbax02mJeVir+9JoHLlcL/ZvpCXkld5HH5nytF9jwpV10jInpEq4i7vuivFXFtamlI44/ZuqisoLDWK63W61dSr7F/qzQzBzKa6kKvy2rwr4GyrFz6OABijlWnj2MTmaNFerSIGl68eAEjIyOh1xcuXIi9e/di717Ra9/IyMigd+/e6N27N5YtWwZ3d3f8+eefcHV1rbWhVDVMLzY2Fh06dBDaHxcXBxMTE3pbRUUFubnCHx45OTlCjSAlJSUYGxuLPTcAaGlpwdjYGMbGxggKCoKxsTG6desGa2vBGzNpaWlISzP349KoUSPY2trCxcUFxcXFGDp0KPLzhSvvAfzhgXX9O9u0aYM2bdpg1qxZiIiIQO/evenGZU3Lly/HwoULBV5znncfHO6Xf39yahHaJH2Gdd/G0FSXEZgP1bI5/8YiMbn2NVbevC2AdZ/GkOJCYD5UC0P+179JEv56aWkOhvRvjLiEfDyKysE0V8Gb9eTUIliYqmBgLy2hXC2aKf6Tq/Y5J2+SCzGwl5aIXP98fUphrV+fmV2K4pIKRMflw9ufPycq5X0REpOLMLCnFjTUZATmaRnVM1dichEG9GwELhcC8yWq5pwlptR/Lk3TZsZ4GBGGiopygfkNqUn8dZH0DGq/nkRp3soCMZG3UZCXDVV14cn5NdWsylhFu6kJYh+cR2VFucB8lQ/v+L3fjZsKzyOprqqRFXUnGLYT16NttxFCxzRuKjxEqvrXi8rWsllTXL79AOUVFQLztF4n89/jFgbCc63qRAHcevQeVuFyhY9Nel+C3p1UhK6LZnr8z93kNPHFhJLSSmGoK1zMgP5aMUO26sOgeUvcuXlZ6BpLectvLBoYiq6qmJH+HqUlJfA7uBN+B3cK7XcZb4Ohw8dg0tT535RL7LWf/Ire/7WaG1sg5umXa1+/eS3XKCX6fWyka4L4pyFC131mWvw/++u+7q+dXIXYB8EYOM4dZp2Hiz2W38iaCIqiMGr2ESiri58/nJxWil4dlYWuL0Nd/jWSUsv1lZxWima6IuYVirk2tTSksXaOLjgA3PakISu39oa+pF5j/1b+83iotjERel3ln9fyYxL++W/8P6+b4mPYTaFjq/aziarjwdvPgPRoEbRr167h2bNnIhdjU1ZWxurVq7F+/Xrk5YkuUFBd69atUV5ejuJi0ZOwq1haWsLMzAw7duwQehIeFRWFK1euwMnJiX7NzMwMDx8+FDiOoig8fvwYpqbib57qQ0NDA3PmzMHixYvrHG7DBGdnZ9y4cQMTJ078LtXcqrRu3RoAvyy/KHJyclBVVRX4E/+mGC9fFdB/iooqEHH/EyorKQwdKPhLeuhAHRSXVODe49oXS7x5LxOKitLo20NwSOTQgTr4mFmC2Hjh66xX10bQUJPF+ctpKC+n8PL1Z4E/RcWVuP0gC5WVFIbUWLDXpr82iksq8CAyp9Zctx5kQVFBCn26CTYWhvTTxsfMUrEl06v07KwJeTkpPHiSg/g3nxH/5p9cD7P/yaUlmKuf1lfl6mslWM1xSF9tfMyqO1ffbppQkJdCXmElOnQdgJLiQjy9d1XgmHs3zkFNUxtGrcRPIBeFoijExzyGopIKPddFnLs3zgKA2HOYdrBGaUkh4p5cEng9+u7fUFZvDD2j9rXmCPlrFaLuBGOYw59o31P0wpIq6o3RtIUl3r16gpKiL9+3spIiJMc/QFMR5+jbtQMKi0tw/b7gmioh4XehraEOi1bCD6hq8/7DJ0S/fIU2reou4x4azp8PJOrY+9GfoSDPRff2gsOk+3dVQWZOORLeiv8Mvh9dAH0dWYHKcVwu0LezCuLfFiM779t7tLp074PioiLcv31D4PXwaxegoamFViatRX5d8xatsHrDbqE/hkbG0G6ii9UbdmOIrd0357K04l/7T2pc+3dvnIP6N177CbGC176ahjZamLbDq7hIFBV+ub5KS4oQH/sYRq2Elzto0W4QykoK8Spa8Lp/8fA0lNQao4lh7df9tZOrEfsgGP3HrEVrK/ELquZnv8ffXhNRWVmJ/830g6pm7Q8IHvxzfXVrL9hj26/q+koS3/NzP/qzyOurj4jrS0tDCmvn6ILL5eAPrzR8yq69hx6Q3Gvs30o/cwXK5i2h3vXLdcKRkkLTCcORfT8SJWn8OYAl7z8g+0EUmv72K/8b+w91q/ZQNmuB9NOXGc9OCCM9Wj+pkpISpKeno6KiAhkZGQgLC8PGjRtha2uLiRMnivyaqVOnYseOHfD394eV1ZfFOfv16wd7e3t07twZjRo1QmxsLFasWIH+/ftDVbX2YRgcDgeHDx/G4MGDMXr0aCxfvhw6Ojq4f/8+Fi1ahCFDhmDatGn08YsXL8akSZNgZmaGwYMHo6ioCAcPHsTr16+FhgVW/Rurk5aWhpaW4I1udbNmzcLmzZsRFBQEOzv2PmgBfnn6jx8/1vk9zMnJEfp3qqioQElJCTNmzICenh4GDBgAfX19pKWlwd3dHdra2ujevfu/ypeYXIjzl9PhPKE5KispvEjIR1dLDQwfootDR98KDGVzGm8Ip/GGmL8qCpHP+T2S9x5n4cHTLCye2QpKilJ4l1aMQX200a2TJtZueyFU5QoAbAfrorikQmAx45revitC6LUPmDzWAJWVFOJefUbn9mqwtW4C7xMpArkm2ulj0hh9LFwbi6hYfsPuwdMcPIzKwYLfW0BRUQqpacUY2EsLVpYacPdMoHM10ZLFqvmtcO12Jr/EPFVVdEIXicmFCLn2UTjX9Y+YPEYflZUUXlblGtgYvJPvBNbQmji6KSbaNcWiP18g6gW/J/NBZC4eRuVi/u9G/FzpJRjYsxGsLNWxftcrei2bJlqyWDXXGNfu8HNR1JdiGInJhXifx0Gbjr1g3q4bjh9aj6LCAjTWbYaHERcQE3kbk+eup9eeObL3D9y7cQ7rvM6hkTZ/0vneTfOh39wEBs1NoaSihtzsj7h7/SwSYh9j/JTl9JPlhNgnuBB8GB26DoBWk6YoLyvF86cRiLgcDNM2XdGuc1+R759x274wMu+JC8f+QElxATS0myHmYQjexNzCCJet9FpC5/1WIPruacxafxlqjfg3i5dOuCMq4hTa9xyNxk1NkPomkv57paRlodPsy42X9ZilOLp9Ivw9XdB9yO8AB7h/2QeFBTnoO0K4emIPy7bo2s4cWw8dw+fCYhjoaOPS7Ye4FxmDP+a40Gtord/nh9Dwuzi1ez10tfmN9dnrPGBpbgLjZk2hpKiA18mpOHrmIsDhYOq4Lz1ukS8S4Bscir5dO0CviTZKS8twN/I5zly5hc5tzNCrk/AN+tMXhYiMK8TUsdpQkOci/VMZenVURsfWSth5JJ2+LmbaN0b/riqY+WcSPv5zE3v1Xh6G9lLD4sk6OHouk16wWK+JLP7wElzYW1tDGsb/3DDraPGH1nbvwL/5/pBZjtcpgjfclp27o61lF3jv3YaiwkLo6DXF7fAriHp8D7MXudHX2H7Pjbh59QI8DwdAu7EOlJRVYNFOuFqaopIKKioqhPZ9/JCO1/EvAPB7KgDgXsR1fuYmOmjZSnD+b5uOvWDevhuOH1yP4sICNNZphgcRFxDz9Dac51W79r3+wN0b5+DudQ6NGle79g1NoG9kCmUVNeRk8a/9+JjHsP99uUCvit3EhfBY8zs8182EzUgngMMvhlGQn43h9sILpjY37wMDkx64cWotSosLoK7VDPFPQpAcdwuDHb5c91dPrMSLh6cxceUlupF0M9gdsfdPobXVaGjpmiD9bST990pJy0Jbn3/dF+ZnIthrEj7nfcTA8etRVJCJooIvBYWU1XWEereevihCVFwhfh+jBUV5LtI+lqFXJ2VYtlaE55EP9PU1w14L/bqoYNa6FLqRdO1ePmx6q2Hh5CY4di4TufmVsOmlCr3GMvjT68v8VlVlLv6YrQcNVSns8/8ENWUpqCl/ebiYmVMusndLUq+xKtpD+kBKSQHSKvyfE2VzY+iM4q/D9uFCOCqLitHu4Ho0dRyJG6aDUJTM/7vf+ZxC8+kT0NHfE3Ert6PkQyaaT58AJVMj3B8yWeAcccu3wSqMh04nPPF2/3HINW4Es/WLkPf8Jd75BonMxaQfaYhfQyENrZ9UWFgYdHV1IS0tDQ0NDbRv3x67du3CpEmTxBZJkJGRwbp16wQW8AX4iwD7+flhxYoVKCwshJ6eHmxtbeHm5lavLD179sS9e/ewdu1aDB06FFlZ/J6Q2bNnY8eOHQK9OWPHjgVFUdi2bRtWrlwJeXl5WFpa4tatW0JV9ar+jdWZmpoiLk54fHwVbW1tODo64o8//sCoUaMYXz+jOg6HU2ujsMrkyZOFXtu4cSOWLVsGa2tr8Hg87Nu3D5mZmdDS0kL37t1x9epVNGpU9/Cuumzfl4BPmSUYbdsUmhqySM8ohuehVwg6/17gOC4HkJYSnma+ckMMpjoaweW35lBVkUHyu0Ks2RKLq7eEJ0A31pJDlw4auHQjA5/rmDuy41AiPmWV4n9DdaGpLoP0DyXY7fMWf18QbJByuYCUFEdoPrXb1pdwsW8G53EGUFGWRnJqkcACxgDwuagC2bllGGurCw11GXC5HGR8LEHQhTQcC05FcYnwL5idh9/yc9no8HN9LMEe3yT8HZYhcBznn1w1v2Fu2+Ixxd4Ak8fqQ0VZGimpRfhzZwKu3/nSe/i5qAJZuWUYY6sDDbUvuYIvpONY8HssWswv7z9tiQfO+O/GuZP7UFiQiyZNjeAyfxO69Pqyjk9lZQU9b6FKS7P2eHLvCm6EnUBx4WcoKKnAsGVrzFq+S6DympqGFrhcLkJPHURBfg44HA4a6zTDr+NmwHr4xFp/tuxm7MaN0zsQfmYXigtz0EinBUZO8YBF1y8LwlKVlaBqZEuI5t/8RN0OQtRtwZsMtUZNMXvjNXpbv2VH/LbAFzfOeOKM92IAQNMW7eG4+Aj0WwoXnACATYtnYL//aRwKOIO8gkIYNtXBunlTMKhnV/qYispKVFRWCuQyNmiKK3ce4ti5SygpLYWmqio6tTGF82hbNNNrQh/XSEMNXC4HvKAQ5OYXgAMO9HUb4/exwzHh10Fiv2dbDqdhgm0j2A/ThLKSFFIzSrHdNx23n3zpTeGKuKbKy4E1Xu8xcXgjTLHThqwMB29TS+G+7z1iXwn2hLVppYA5Dk0EXlvizP98vXY/D3uOCT/8WLRiA04cOYjAY4dRkJ8HPX1DzF2yFj36fhmaLeoa+xox0Y+xf+cGgdd2bloFAOgzcChmLlgl9DXTl3jgzPHdOHuCf+3rNDXClAVirn3UuPbvXsH1Gtf+7BW7hCputjTrgAV/HMQZ/z3w9lwBADAyaYdFaw+jpano3qlhzrtxL2Qn7l/YjeLCHGg0aYEhjtth0vHLdV9ZWQGqsgLVK0kkxvCv+9j7QYi9L3jdq2jowcmNf91nZbxCXmYKAODS0SVC5+86ZBasbOYIvb7VOwP2tpoYN1SDvr52+Gbg9tMvoyK4HI7QZ2l5BbDWKw2OwzXhMlqLvr7W709H7Osv15eBjizdeJ83UXjplIAL2QgIyxb5PZPUawwA2uxZA8XmXypc6o0ZCr0x/IIp14wHoCgpFZDigistLVDUo7K0DPeGOMF80xJY7FwFKUUF5EW9wAPb35F1S3BET9bNB3j461SY/DEXXU7vR0VhET6E3sAL1y2oLBVdFp9gFoeShDFSBFFNZWUlXFxccPHiRYSHh9PzuAj29Po1nO0IIknLfVuhFCaIm4PENrfVwr0ikiAlq/b1zdjyq7pkXvsu3t8wJ4wBq+eosx1BrNySrytYwpTnyeIXlWbTjYvsLMJdl5Wz6y5Ywob3reuutMyGX8qE19liysDxDxrs7756omvdB0kAybwTIH5qXC4X3t7ecHV1xa1bt9iOQxAEQRAEQRBfjQwdJBrUrVu3MHToULH7CwpET+DncrmYN094noSkSE5OpotKiBIbG4tmzZoxmIggCIIgCEJyVJI5WqShRTSszp07IzIyku0Y352enl6t/y49PeHV6gmCIAiCIIifB2loEQ1KQUGhzjWefkTS0tL/yX8XQRAEQRDE90DW0SJztAiCIAiCIAiCIL470qNFEARBEARBEMR3RdbRIg0tgiAIgiAIgiC+M4oiQwfJ0EGCIAiCIAiCIIjvjPRoEQRBEARBEATxXZGhg6RHiyAIgiAIgiAI4rsjPVoEQRAEQRAEQXxXpLw76dEiCIIgCIIgCIL4/iiCIAiGFBcXU2vWrKGKi4vZjiJEUrORXF+H5Po6JNfXk9RsJNfXIbkIJnAoiiIz1QiCYEReXh7U1NSQm5sLVVVVtuMIkNRsJNfXIbm+Dsn19SQ1G8n1dUgugglk6CBBEARBEARBEMR3RhpaBEEQBEEQBEEQ3xlpaBEEQRAEQRAEQXxnpKFFEARj5OTksGbNGsjJybEdRYikZiO5vg7J9XVIrq8nqdlIrq9DchFMIMUwCIIgCIIgCIIgvjPSo0UQBEEQBEEQBPGdkYYWQRAEQRAEQRDEd0YaWgRBEARBEARBEN8ZaWgRBEEQBEEQBEF8Z6ShRRAEQXwziqLw4cMHtmMQBEEQhMQhDS2CIAhCLEVFRXz8+JHetrGxQVpaGr394cMH6OrqshGN+A7Ky8tRUFDAdgziOyguLoafnx/27t2LhIQEtuNIjMrKSpSXlwu8lpGRgbVr12Lp0qWIiIhgKRnxMyANLYIgCAkQHR1drz9MKy4uRvVVQG7fvo2ioiKBY9haJcTZ2Rn5+fmsnPtbJCUlITY2FpWVlYyfOzQ0FH/99ZfAa+vXr4eysjLU1dUxePBgZGdnM54LAO7fv48LFy4IvHbkyBEYGRmhcePGmDp1KkpKSljJJk54eDhCQ0NZ+54tWbIE8+bNo7dLS0vRvXt3/P7771ixYgUsLS1x9+5dVrJJGhcXF8ycOZPezs/PR5cuXeDl5YWLFy+if//+CA0NZTGhaGxfY8T3Ic12AIIg/rsWLlxYr+M8PDwaOImgrKwsFBYWQl9fn34tJiYG27Ztw+fPnzFy5EhMmDCB0UwdOnQAh8OhGy0cDgcAvxFT9TqHw0FFRQWjueqjKivT/Pz8sGnTJqioqLByfnH8/PyQnZ2N+fPn069NnToV3t7eAABTU1NcvHgRBgYGjGXatm0bRo8eTW/fuXMHbm5u+PPPP2Fubo6VK1di3bp1jP8sAsAff/yBfv36YejQoQCAZ8+ewcXFBU5OTjA3N8fWrVuhp6eHP/74g/FsW7duRUFBAdauXQuA//M4dOhQXLp0CQDQuHFjXL16FRYWFozmunDhAjZs2EBvHzt2DElJSUhISECzZs3g7OwMd3d3hISEMJrr1atXyM3NRadOnejXrl69Cnd3d/qzdcWKFYxmun37Nvbs2UNvHzlyBOXl5UhISICamhpcXV2xdetWDBs2jNFcVST1GiO+D9KjRRBEg3n69KnAn927d+POnTsCr0VGRjKea9asWQI3lB8+fEDv3r3x8OFDlJSUwMnJSejpf0NLTEzEmzdv6P8qKCjg+vXrQq8TX7DVk1aX/fv3Q01Njd4OCwuDj48Pjhw5gocPH0JdXZ2+qWLK8+fP0aNHD3r71KlTGDRoEFauXIlRo0Zh+/btOHfuHKOZqkRGRmLgwIH09okTJ2BlZYVDhw5h4cKF2LVrFwICAljJ5u/vj9atW9Pbp06dws2bN3Hr1i18+vQJnTt3Zvy9BIDk5GSBXJcuXYKdnR0MDQ3B4XAwb948PH36lPFcS5YswenTp+ntxMRE/Prrr5CVlUX37t2xceNG7Ny5k9FMqampaNWqFb199epVjB49mv4ZnTRpEmJiYhjNVJ2kXmPE90F6tAiCaDDXr18X2FZRUcHx48fRokULlhLx3bt3Dz4+PvT2kSNHoKmpicjISEhLS2Pbtm3w8vKCo6MjY5kMDQ0FtjkcDvT19YVeZxqHwxHosaq5zTZJylIlPj4enTt3prfPnDmD4cOH47fffgMAbNiwAZMnT2Y0U35+Pho1akRvR0REwM7Ojt62sLDA+/fvGc1UJTs7G02aNKG3w8PDYWNjQ2936dIFKSkpbERDYmIi2rVrR2+HhoZi9OjR6NmzJwBg1apVGDNmDOO5uFyuwIOGe/fuYfXq1fS2uro6K0POHj16hKVLl9Lbx44dg4mJCS5evAgAaNeuHXbv3i3Q29vQ5OXlBYY737t3D1u3bhXYz+Y8RUm9xojvg/RoEQTx00lPT4eRkRG9fe3aNfzvf/+DtDT/2dPw4cPJZPJ/UBQFExMTaGpqQlNTEwUFBbC0tKS3zczMWM1XPZu4P0wrKiqCqqoqvX3nzh306dOH3m7RogXS09MZzaSnp4cXL14AAAoKChAVFUXfyAFAZmYmFBUVGc1UpUmTJkhMTATAn2v05MkTdO/end6fn58PGRkZVrKVlZVBTk6O3r57965Az6Cenh4+ffrEeC4zMzO6BzImJgbJycno378/vT8pKUmg8cqUT58+CQzJvn79On799Vd6u1+/fnj79i2jmdq3b0+PULh16xYyMjIwYMAAev/r16+hp6fHaKbqJPUaI74P0qNFEMRPR1VVFTk5OXRv0YMHD+Di4kLv53A4Ejf5ni3Ve/4k0dq1awWG6UkCQ0NDPH78GIaGhvj06RNiYmLQq1cven96ejrjme3s7DB//nysWLECoaGh0NHRQbdu3ej9jx49gqmpKaOZqtjY2GDZsmXYvHkzTp8+DUVFRfTu3ZveHx0djZYtW7KSzdjYGDdv3kSLFi2QnJyM+Ph49O3bl97/7t07gZ5CpixZsgT29vYICQlBTEwMhg0bJvDwKDQ0FF27dmU8l6amJtLS0mBgYIDKyko8evQICxYsoPeXlpYyPuR39erVGDZsGAICApCWlgYnJyeBSql///23wEMHpknqNUZ8H6ShRRDET6dr167YtWsXDh06hODgYOTn5ws84YyPj2e0UIE4kjAsbtKkSWxHqNX48ePRuHFjtmMImDhxImbNmoWYmBhcu3YNZmZmAsUB7ty5gzZt2jCaac2aNXj//j3mzp0LHR0dHD16FFJSUvR+f39/gZ4HJrm7u2PUqFHo27cvlJWV4efnB1lZWXo/j8fD4MGDWck2Y8YMzJ49G7du3cK9e/fQvXt3gfk0165dg6WlJeO5Ro8ejdDQUISEhGDw4MGYM2eOwH5FRUWBSntM6du3L9atW4e9e/ciMDAQlZWVAj1tsbGxaN68OaOZ+vfvj8ePH+Py5cvQ0dERGobXoUMHVhqlVST1GiO+Dw4lqbOJCYL44dUsR96jRw8EBAQIDC0BIDA+nQmRkZGwtrZGfn4+ysvLsWLFCqxbt47e7+joCCUlJezfv5+xTJaWlgINq+joaJiZmQnccALAkydPGMskSn5+vsATaS6XC2VlZVaySElJIS0tTeIaWpWVlVizZg3Onz8PHR0deHh4wNzcnN4/ZswY2NjYCPSiEkBubi6UlZUFGoAAv0qosrKy0M8CU7y9ven3cs2aNdDR0aH3zZw5E4MGDcL//vc/VrJJmsTERAwaNAiJiYngcrnYtWsXZsyYQe8fOXIkjIyMsGPHDsYyOTs7w9PTU+Kqk1ZX1zVmbW2NUaNGsZiQ+FakoUUQRIPhcrkCJcurY7tk+cePH3Hnzh3o6OjAyspKYF9ISAhat24tMBSnodW3qtSaNWsaOImgyMhIrFy5ki4TraKigsLCQno/h8PB3bt30aVLF0ZzAfzrKz09vdaG1qlTpwSKPvysPnz4UOv3qaKiAo8fP2blyb6kNpgBfqGccePGCcyhkQRbtmzBnDlzoKCgAAC4efMmrKys6Jz5+flwdXXF3r17Gc9WVlaG2NhYaGtrC819ioqKgr6+PqND4ST5+iL++0hDiyCIBpOUlFSv49iurCdKamoqmjZtytj5kpOToa+vDy5XsmoUubi4wNjYGMuXLwfAb2gdOHAATZs2BUVR4PF4oCiK8XL4VcrLy/Hy5UvIyMjAxMSEfv3MmTNwc3NDXFwcK/PtAgMDcfr0aZSVlcHa2hpTp05lPEN1NW82zc3NcfHiRTRr1gwAkJGRAT09PVYeetSnwcwWSb1Jr5lLVVUVkZGRdEVXNt9PSSPJ1xcABAQEYOTIkXSP7du3b2FgYED37BYWFmLPnj0C1RyJH4dk/UYnCOI/xc/PD9ra2jA0NKz1jyRJT0/HnDlzYGxszOh5jYyMJLKy1O3btwUKOQBAt27d0LdvX/Tr1w+zZs3CzZs3Wcn24sULmJiYoF27djA3N8eoUaOQkZGBvn37YtKkSRg0aBBevXrFeK6DBw9i3LhxePToEV6+fIkZM2bQDVW21Hym+u7dO5SXl9d6DCG535OauSQlZ+vWrZGVlUVvT506FR8/fqS3P3z4wEp1S0mY7yqOvb09cnJy6O127doJPKTMz89n/fOD+HakGAZBEA1m7dq1mD59Omtlo8XJycnBrFmzcOnSJcjIyGDZsmWYPXs2/vjjD2zbtg0WFhbg8XiMZpKUG6WaUlJS6F4PAPjzzz+hpaVFb+vq6iIjI4ONaHB1dYWRkRF27dqFY8eO4eTJk3j+/DkcHBxw/vx51uZk7N69GytXrqTn/fn6+mLOnDnYuHEjK3nqi82b0YsXL9ZZiXH48OEMpREkyTfpkiYuLk6gAX/ixAksW7YM2traAPifc8XFxYznMjExqfN9rN5AZJKkNpqJ74M0tAiCaDCS+gtjxYoVuHnzJiZNmoSwsDAsWLAAYWFhKC4uxoULFwRK6/7s5OTk8O7dO7rnsXqpZoDfEGOrIf3gwQOEhoaiY8eO6NWrF06ePIklS5bg999/ZyVPlTdv3ggsSOzo6IipU6ciPT1dYJI78UVd1S3ZmssJAE5OTnXO0QoODmYozY9F3PxcpkniMhDEz4E0tAiCaFCS+DQ4JCQEPj4+sLa2xsyZM2FsbAwTExPs3LmT1VyHDx+us4Lf3LlzGUrDZ2lpidOnT4tdZyY4OJi10sMfPnyg59Gpq6tDUVFRIhrJRUVFAu+jlJQU5OTkBIqIMI3D4SA/Px/y8vJ0EZqCggLk5eUBAP1ftkjyHBoVFRW66IQkqf55UV5eDl9fX7q3OT8/n81oEkcSl4Egfg6koUUQRIMaOHAgpKVr/6hhumT5+/fv6XVKWrRoAXl5eUyZMoXRDKLs379fqLR1dRwOh/GG1syZMzF+/Hg0b94cM2bMoIt1VFRUYO/evdi9ezeOHz/OaKYqHA5HoHgIl8uFjIwMK1lqqtlornkjDDDbaKYoSqBYCEVRAg3kqsYXGyTxYUx1u3btkrib9GbNmuHQoUP0to6OjlBBmupDfpnC4XCE3k+231+2z18f1YfOVlZW4urVq3j+/DkACMzfIn48pOogQRANhsvlYtGiRXX20jBdslxKSgrp6en0vAEVFRVER0czWs69JkmujOXq6oqtW7dCRUUFLVq0AIfDwevXr1FQUICFCxdi69atrOTicrlQU1Ojb6RycnKgqqoqVLmR6bkXzZs3r/PmjsPh4M2bNwwlAsLDw+t1HBs9gpJ87Utq1UFJxeVy0aZNG/rhWs31AMvLyxETE8PoMFBJvr4A1KvSLJtDZ4l/h/RoEQTRoJYsWSJxv+AoihKYd1FcXIzp06dDSUlJ4Dgm511I8lPXzZs343//+x/8/f2RkJAAAOjduzfs7e3RrVs31nL5+Piwdu7avH37lu0IQpKSkiRyPSiAPz9LEofmAZI7z3TAgAEIDg6Guro621EE1HxoNmLECKFjRo8ezVQcAPweotpQFIWPHz+y9nuqrnzEj430aBEE0WAk9Wlw9UIFtWHyRl7Sn7oSPzZJ/VkEJHsdofDwcPTs2bPO4c9Mk9TPC0lcD1BRURFJSUn0CAYbGxv4+PhAV1cXAFlzjGhYpKFFEESDkdSbAUm0du1aLFmyROJK4ScnJ9frODbmg1QpKirC5cuXER8fDw6HAxMTE1hbW7PWS7Jr1656HcfkHC1J/lmU5MV3hw0bBn9/f3r+zPr16zFr1iy6JykzMxO9e/dGbGwso7kk9f2UxAZ9ze+ViooKoqKiBK4vXV1d1nqW6rsOYZ8+fRo4CdEQJOsRDUEQ/ymJiYn0U0QAQmPzpaSkYGFhwUa0On348IHRm4WpU6di/fr1WL9+PQCgV69eAlXqpKSkcPr0abrKHlPEzTeqXjyBw+EILX7LlLNnz2LKlClCiz1raWnB29sbv/76K+OZduzYUecxbBQ2kdThqZK8jtDFixdRUlJCb2/evBn29vZ0Q6u8vBwvX75kJVtVFcnaqKqqMpSGT5Leu6/B5s9Gv3796POL+/6ROVo/LtLQIgiiwSQnJ8POzg4PHz4EAHTr1g2FhYX0LxMOh4OLFy/C2tqa0VySOJRk3759AtWloqKi4OzsDE1NTQDAhQsXsGPHDmzbto2xTADw9OlTka9TFIUTJ05g165ddRY7aSh37tyBnZ0dhg8fjkWLFsHc3BwAEBsbi+3bt8POzg43btxA9+7dGc2VmJjI6Pnqi6wH9fUkuRFYvYpkTVUPQsjNueTT0NCAiooKnJyc4OjoKFCZlPjxkYYWQRANxsvLC46OjgKvXb9+HYaGhqAoCrt27cK+ffsYb2gVFxcL3DDdvn0bRUVFAscwfUN19uxZoep98+bNo4e3dOvWDQsXLmS8odW+fXuh165cuYJly5YhPj4eS5cuxeLFixnNVMXd3R2TJ0/GgQMHBF7v0aMHevTogWnTpmHdunUIDQ1lJV99tW3bFqGhoTAwMGjQ80jqelDEtzl16hT9IEaSSNp6gDVLzosqQc+mtLQ0/P333+DxeNiyZQuGDRsGFxcX2NjYSFRO4tuQhhZBEA3m0aNHmD9/vsBr+vr6MDQ0BAA4Ojril19+YSFZ3Zj+Bff27Vu0bNmS3h40aJBAFURTU1PWe0oeP36MZcuW4datW5gyZQpCQ0NZnYtx9+5dbN68Wez+WbNmScQCxnV5+/YtysrKGvw8krgeVBVJXUdIEteFqtKzZ0+JfD8lbT3AqjXkqt63goICWFpa0gU72O6llJWVxbhx4zBu3DikpKTAx8cHs2fPRklJCSZNmoS1a9dKXDEWov7IO0cQRINJTU2lh+MBgJ+fH3R0dOhtTU1NZGZmshFN4pSXlyM3N5ferjmEKzs7m7VKXq9evcLKlSsRFBSEsWPHIjY2lu5pY1NxcXGtc1DU1NQE5tf8zCSlcSDOpEmTBLanTZvGUhJBdS0FQa4vYY8ePZKoBqCkLgMhioGBAdzc3ODo6AgXFxds2rQJixYtksieS6J+SEOLIIgGo6KigsTERLoHa9SoUQL7ExMTGZ+sDUjmUBJTU1PcuXMHlpaWIvffunWr1jkZDWXmzJnw9vZG//798ejRI3To0IHxDOKYmJjg2rVrYsv1X716FcbGxgynkkxsP7WvjSSvIzRx4kSBzwYHBweRxzCtadOmtfYaEV/UbMSLkpqaykCS2pWUlCAoKAg8Hg93797FL7/8gpCQENLI+sGRhhZBEA3GysoKR44cQb9+/UTu9/X1hZWVFbOhIJlDScaPHw83Nzf07t0b7dq1E9gXFRWFtWvXYtmyZYzn2r9/P+Tl5fHhwwc4OzuLPe7JkycMpuJzcnLC4sWL0aRJEwwbNkxgX0hICJYuXYqVK1cynksSeXp6QkNDg+0YIqWmptZZTfPYsWP47bffGEr0ha+vb53HsFFxU1dXF5mZmWjUqBHj5/7RzJs3D56enmL3p6amon///oiPj2cw1RcPHjyAj48PTpw4ASMjIzg5OSEgIIA0sP4jSEOLIIgGs3DhQlhbW6NRo0ZYsmQJPZzkw4cP2Lx5M44ePYpLly4xnksSh5LMnz8f58+fR6dOnTBo0CCYmpqCw+EgLi4Oly9fRvfu3YXmuzFhzZo1jJ+zvubNm4c7d+7A1tYWpqamAlUHExISMHLkSMybN4/llJJhzZo1OHv2LHx8fKCvr892HAGDBg3C7du3xTYEjx8/jsmTJ7PS0Dpx4gTGjx8vdn9ZWRns7Oxw5swZBlPxl12wtLTEpk2bMGfOHEbPXRtbW1vWqpCKc+TIETRq1Ahubm5C+96/f4/+/fsLDGlnWrdu3dCsWTPMnTsXnTp1AgBEREQIHTd8+HCmoxHfA0UQBNGAvLy8KFlZWYrL5VLq6uqUhoYGxeVyKVlZWWr37t2sZAoPD6fKyspYOXdtSkpKqI0bN1Lt27enFBQUKAUFBapdu3bUxo0bqeLiYrbjSawTJ05Qw4cPp8zNzSlzc3NqxIgRlL+/P9ux6k1ZWZl6/fp1g54jNTWV+uWXXyh1dXXqyJEjDXqur9W3b1+qa9euVEFBgdA+f39/SkZGhvLw8GAhGUXJyclRYWFhIveVlZVRI0aMoPT09BhOxRcYGEg1btyYsra2plJSUljJUJOMjAz1559/UhUVFWxHod28eZNSVFSk9uzZI/D6+/fvKRMTE6pHjx4irz2mcDicOv9wuVzW8hH/DoeiJHjgNkEQ/wkpKSk4deoUEhISAACtWrWCnZ1dg5ezFkdKSgppaWkSNWH7R5SdnY2jR4/C29sbkZGRbMf5YR0/fhwjRowQqDLZUHx9fbFw4UL069cPq1atEqpmVnPYKhMKCgrQr18/qKur48KFC5CRkQEABAQEwMHBARs2bGBtCQFPT0+sXLmS7lWuUlFRATs7O9y9exc3btyAmZkZK/k+fvyIWbNm4fLly3B0dBR6Pz08PBjNExoaimnTpkFPTw9//fUXK/NKRQkJCcHo0aPh4+MDe3t7pKeno1+/ftDQ0MDly5clrheO+A9hu6VHEATBNA6HQ2VkZLAd44d1+fJlavz48ZS8vDylr69PzZ07l5UcFRUV1JYtW6gePXpQXbp0oZYvX04VFRWxkqW6oUOHUjk5OfS2u7s7lZ2dTW9/+vSJMjc3ZyEZ3+XLlykpKSmKy+XST8vZfmr+4cMHyszMjBo1ahRVWVlJBQQEUDIyMtSmTZtYy1TFzc2N0tDQoJ49e0ZRFEWVl5dTo0aNoho3bkzFxMSwmq28vJxyc3OjpKWlqV69elH9+vWj//Tv35+VTDk5OdSkSZMoJSUlateuXaxkEOXYsWOUvLw85ePjQ5mZmVFdunShcnNz2Y5F/MeRHi2CIBrMzZs363Vcnz59GjiJIC6Xi4yMDGhrazN63toYGRnVWfmQw+Hg9evXDCUSlJycDB8fH/j4+KCgoADZ2dkICAjA6NGjWckDABs3bsSqVaswcOBAKCgo4OLFi5g4cSIOHjzIWiZAuMdUVVUVkZGRdEn8jIwM6OnpoaKigvFsHh4eWL16NcaMGYPVq1cL9YBUVQhlQ0pKCnr16gVjY2NERETAzc1NYoqZzJkzB0FBQbhx4wZWrlyJGzdu4Nq1a2jbti1rmWJiYuDo6Ijs7GzweDz079+ftSyinDp1CuPHj4eSkpJQhcSsrCxWMu3duxdz5sxBx44dceXKFXrtNjadPXu2XseROVo/JtLQIgiiwdS27lNVo4LD4TBetYvL5WLq1KlQVFSs9Tgmh93UVhXr7du3OHDgAEpKShi/OQ8ICMDhw4dx+/ZtDBs2DA4ODhg6dCiUlJQQFRWF1q1bM5qnOlNTU8ybNw8zZ84EAISFhWHkyJEoKipitVw/l8tFeno63dBSUVFBVFQUqw2tN2/eYOLEiXj9+jX279+PESNGMHbuukRHR9P/HxcXh4kTJ2LkyJFYsWKFwHFsDGusztHREadOnYKysjKuXr3Kap5Nmzbhjz/+wIQJE+Dp6QkVFRXWsojy8OFDujT+okWLhBr09Sm5/r1YWloKfB7ExsbCwMBA6HvGRuVUoPbfk1U4HA4rD2aIf49UHSQIosFkZ2eLfL2wsBCenp7YtWsXawvfPnv2DLKysmL3M32jLqo6XlZWFtatW4d9+/bBysoKmzdvZjQTAEyYMAFLly5FUFCQxN3MJSUlwdbWlt4eMmQIKIrC+/fv6ywX/rNp164dbGxscPr0aWhpabEdR0CHDh3A4XBAURT934CAAAQGBtJLLbB1o7lw4UL6/9XV1UFRFDp06CBU9p3puVCenp4IDAzEr7/+yuh561JeXo41a9Zg27ZtmDVrFjZs2AB5eXlWM40cOVJgW5IeMgCSvY4c8e+RhhZBEA2m5rCMyspK8Hg8rF27FlwuF15eXow+2azu77//lthiGEVFRfDw8MDWrVvRvHlzBAcHC60TxRRnZ2fs3bsX4eHhcHR0xLhx4yRmPabS0lIoKCjQ2xwOB7KysigpKWExlegFsNleEHv//v0iF9stLS1FaWkpq8UAEhMTWTt3XZ4+fSqw3b17d5SXlwu8zsZ7+/z5c6E1tD5//oyTJ0+iqKgIgwcPRqtWrRjP1bFjRxQUFODSpUvo27cv4+cXRZKXqAD4n7GS2CtJfB9k6CBBEIwIDg7GihUr8PHjRyxfvhxz5syBnJwcK1kktepgRUUFDh06hLVr10JeXh5//vknHBwcWL9JLyoqQkBAAHg8Hu7fv48hQ4YgJCQEkZGRaNOmDWu5RA0B9fLygoODg0Ajn+neBi6Xi6FDh9LX97lz5zBgwAC6qmBJSQnCwsIY76Hx8fHBkydP0K1bN/z2229Yvnw5PDw8UF5ejgEDBuDEiRNkAdwfREpKChwcHOj309vbG4MGDaIruyooKODChQuMz3+dMmUKdu7cKVFV/IqLi3Hp0iX0799fqDGTl5eHGzduYMiQIeT3EdEgSEOLIIgGFR4eDldXVzx79gzz5s2Dq6sr6xOQa86hkQQBAQFYtWoVcnNzsWLFCsyYMaPWoY1sSUhIAI/Hw5EjR1BQUIBffvkFdnZ2GDVqFONZ+vXrV68CIteuXWMoEZ+Tk1O9GsdMLpy9fv16rF+/Hj169MDTp08xduxYnD59GvPnzweXy8WuXbtga2uLffv2MZapSkJCAtzc3HDgwAGoqqoK7MvNzcWMGTPg7u7O2jDjvLw8KCsrC82lqaysREFBgVBmJowdOxYpKSmYNWsWAgMDER8fj5YtW8Lb2xtcLhczZ85EZmYm49c+wH8/o6Oj0bFjRxgZGSEkJASbN29GUVERPfeOyYdHnp6eOHv2LK5evSpyv7W1NUaOHInZs2czlqk6Sfx9RHxHrNQ6JAjipzB06FBKVlaWmjZtGpWWlsZ2HJqvr6/ELQDM4XAoRUVFysXFhVqwYIHYP5KioqKCOnv2LDVixAhKVlaW7ThEHYyNjanjx49TFEVRDx8+pLhcLhUYGEjvDw0NpZo1a8ZKtt9//51asmSJ2P1Lly6lpk+fzmCiL4KDg6lWrVpRnz9/Ftr3+fNnysTEhDp79izjuZo0aULdv3+foiiKyszMpDgcDnXnzh16f2RkJNWoUSPGcwUHB1PS0tKUrKwsJScnR/n5+VFycnKUjY0N9csvv1DS0tKMl+zv0qVLre/RuXPnqC5dujCYSBCHw6E+fPjA2vmJhkV6tAiCaDBcLhfS0tJQUlKq9Qkm06V+Hz9+jMWLF+PMmTMin6CPHDkSO3fuRPv27RnLJKm9M/Xx4cOHH+JpbM0y6w1FEocCycnJ4dWrV/Qi4XJycoiOjoapqSkAIDU1FUZGRigtLWU8m5mZGf766y906dJF5P7Hjx9jwoQJePnyJcPJgMGDB2Ps2LGYMmWKyP08Hg8nT57ExYsXGc0lJSWF9+/fo0mTJgAAZWVlREdHs76EQOfOnTFkyBC4u7vD19eXLogxf/58AMDBgwexY8cOvHjxgrFMGhoaiIqKQrNmzUTuT05ORvv27cUWb2poXC4XampqdX7+s1USn/h3SDEMgiAaDJNDo76Gh4cHBgwYIHLIj5qaGgYNGoStW7fi6NGjjGW6ceMGY+f6GvVZ44XD4Uhc9TNRmHquKInPL8vKygTmoMjKykJGRobelpaWZq18dFJSUq2NUi0tLaSkpDCY6Ivnz59j7969Yvf36dMHq1atYjARH/VPhcYqbM/jrPLy5UucPHkSHA4HkyZNwu+//w5ra2t6/+DBg+lGF1PKy8vx8eNHsQ2tjx8/Mr7ESE1r165lfUg90TBIQ4sgiAbDVkXButy7dw+urq5i9//66684fPgwg4kkV83SyFXlt2u+RtZ4kXyxsbFIT08HwL9Rj4uLQ0FBAQDg06dPrOVSU1PD69evxS6W/OrVK1bmQQH8JSpquwkvKytjrSfEzc2NLgRTWlqK9evX0zfrhYWFrGT6/PkzXXCCy+VCQUFBoFiNgoIC41VBLSwscOXKFXTq1Enk/suXL8PCwoLRTDWNHz9eonrAie+HNLQIgmgwDx48QKdOnSAlJQVA+ClsSUkJzpw5g7FjxzKaKzU1tdZSusrKykhLS2MwEdC6dWtERERAU1MTADB16lSsX78e2traAPjD85o3b874DVTNNV5qLr5LiHbx4sU6n1APHz6coTR8AwcOFGgkV61BVn0NKzb06dMHu3fvxoABA0Tu37VrF3r37s1wKr7mzZvj0aNHMDMzE7n/0aNHYhuIDalPnz4CQyl79OiBN2/eCB3DtJpLG4ha6oBpzs7OWLhwISwsLATW3QP4FUHd3d0Zr0xaHdvfH6JhkTlaBEE0mJpzVWrOkWFrHoGBgQEOHToEGxsbkfsvXLiAqVOnMjpcqWblKVHfK11dXdYXt/yRG1pMZa9ZnU4UpnsBk5KS6nUcG42Gp0+fonv37rC1tcXSpUvpeWNxcXHYsmULQkJCcOfOHXTs2JHxbCtXrsTRo0fx4MEDej5UlfT0dFhZWcHBwQHr169nPJskqjnfKCcnB6qqqvTPBEVRyMvLY/wz38HBAcePH4eZmRlMTU3B4XDw4sULxMfHY+zYsfD392c0T3VfW3Xw3bt30NPTq9fnDME+0qNFEESDqfkcR9RzHTae9VhbW2P9+vUiG1oURWHDhg0C8wrYIOr7Qp58/jtMfv8krVzz1zagZs6ciT///BNaWloNlOgLS0tLnDp1Cs7Ozvj7778F9jVq1AgBAQGsNLIAYNmyZThz5gxatWoFBwcHgZv0Y8eOwcDAAMuWLWMl29dgqhCMpM7LPXr0KIYPH47jx48jPj4eFEXB1NQUa9euZXxERU1f+/CsdevWjLyXxPdBGloEQbCKjcbDqlWr0KlTJ1hZWWHRokUCN0/bt29HfHy8xN4wEN+OqUb9f6FBfPToUSxevJiRhhbAH8aYlJSEsLAwvHr1ChRFwcTEBIMHDxaY48M0FRUV3L59G8uXL8fJkyfp+VgaGhpwcHDAhg0bah2GLCmYuva/dl6uv78/hg8fTi/m3ZDGjh0rslFVUVGBc+fOCc1HlVRkINqPhTS0CIL46bRs2RJXrlyBk5MTxo8fT98YUxSF1q1b4/LlyzA2NmY0k6i5DJJ4wy4Jcy6qy8/Px71791BWVoauXbvW2jC4cOECmjZt2uCZ/gs3Qmz8GxQUFPC///1P4LXKykqcO3cO3t7eOH36NOOZAH6xjr1798LLywufPn0CRVHQ1tamfw4+fvxIz6Ukvs60adNgZWXFSu9MXFwceDwe/Pz8kJ2dzcrSBsR/H2loEQTRoCS10lnnzp3x/PlzREZGIiEhgX6C3qFDB1byUBSFgQMHQlqa/7FcVFSEX3/9FbKysgDAWvlhDQ0NgYZVQUEBLC0theYHsLHGS3R0NIYOHYr09HRQFAVVVVWcOnVK7LDPXr16MZJr0qRJUFBQYORc/1UJCQkCN8FDhgxhOxI4HA7doKIoCqGhoTh8+DBCQkIYr6T3X8F0g/7z5884efIkvL29ce/ePfTv3x/r16//YXqziB8PaWgRBNGgJLXSWZUOHToINK6ys7Nx9OhReHt7IzIykrEca9asEdgeMWKE0DGjR49mKg5t586djJ+zvpYtW4ZmzZohMDAQ8vLyWLt2LWbPno24uDhWc1UNO01NTUVQUBDi4+PB4XBgYmKCUaNGMdKr9iMqKipCQEAAfRNcUVGBHTt2wNnZGcrKymzHAwC8efOGbgAWFBTgl19+wYkTJ9iORdTh7t27OHz4MAICAtCqVSv89ttvuH//Pnbt2oXWrVuzHY/4DyMNLYIgGkxiYiLbEertypUr9PAkLS0tjBo1itHz12xoSQpJXQsN4JfWDg0NRefOnQEAPB4PjRs3RkFBAes35nv37sXChQtRWloKNTU1utrakiVL4OHhgZkzZ7KaT5I8ePAAhw8fxsmTJ2FiYgIHBwcEBgZCX18f1tbWrL+XxcXFOHXqFA4fPox79+5h0KBBSEtLQ2RkJNq0acNqtvpi+4EWm1q3bo3CwkJMmDAB9+/fpxtWP0IRE1F+5vfyR0RqQxIE0WAMDQ1r/aOqqorw8HDW8iUnJ2Pt2rVo3rw5xo8fj4CAABw9ehQpKSnw9PRkLZcoUVFR9HpkTMrOzsbu3buRl5cntC83N1fsPiZ8+vQJzZo1o7cbNWoERUVFfPz4kZU8VUJCQjB37lzMnj0bqampyM7ORk5ODlJTUzFz5kzMmzcPoaGhrGaUJD169ICSkhIePHiAhw8fYt68eUKl1Nkyc+ZM6OnpwcvLC2PGjEFqairOnTsHDofzQ5XX/i/MG/xWr169Qp8+fdC/f3+Ym5uzHedf+5nfyx/Rj/MpQRDEf05ycjImT57M+HkDAgIwePBgmJub4/nz5/D09MT79+/B5XIl+hcxG79g9+zZg5s3b0JVVVVon5qaGm7duoXdu3czngvgP9nNz89HXl4e8vLykJubK/QaG43ALVu2YNmyZdi2bRt0dXXp13V1deHh4QFXV1ds3ryZ8Vxfw8HBQeR73hAGDBgAb29v/PnnnwgLC5OoG8mDBw9ixowZuHTpEmbNmoVGjRqxHYmWn5+Py5cvIzQ0tM75rkwVgpFEiYmJMDU1xYwZM6Cvr4/Fixfj6dOnEtMzNHr0aGRmZtb7+NjYWFbWuyO+DWloEQTx05kwYQI6d+6M9PR0BAYGYsSIEXTRCUnGxo1BUFAQpk+fLnb/tGnTcOrUKQYTfVFVwERDQwMaGhrQ1NSki3VoaGhAXV0dGhoajOd6+vQpHB0dxe53dHTEkydPGEwEFBYWYtasWWjatCkaN26MCRMm1Hpzvm/fPsZKu1+6dAkxMTH0zbCuri7mzZsHgP1hUkeOHMGDBw+gq6uLcePG4fz586wVpqkuOjoaZmZmsLGxga2tLYyNjXHlyhWxx/fq1QtycnIMJqwfQ0NDyMjINOg5mjZtipUrV+LVq1f466+/kJ6ejp49e6K8vBy+vr6Ij49v0PPXJS0tDRYWFjh37ly9jjcwMGBldAPxbTiUJD06IgjipxIVFYWOHTuioqKC0fNOnToVAQEBsLCwgKOjI8aNGwcNDQ3IyMggKipKIidHs/W9UlFRQUxMjMAQveqSk5PRpk0bVnqO6jvstG/fvg2cRJCysjKio6PFlqx+8+YN2rVrR1ffZMKSJUuwd+9e/Pbbb1BQUMDx48fRr18/BAYGMpahvi5fvgwej4fTp0/DwMAAdnZ2sLOzY23RYgB4+/YtXQSjsLAQWVlZOHnyJOzs7FjJM2zYMGRnZ2P79u10IZiXL1+yXggGAAIDA3H69GmUlZXB2toaU6dOZTuSkNzcXBw7dgw8Hg9PnjxBmzZtEB0dzUoWiqKwbds2rFmzBvb29ti5c+cPsTYbUT+koUUQBGvYajwAXyqc8Xg83L9/H0OGDEFISAhrE9zraqhER0ejb9++jH+v1NXVERYWhm7duoncf+/ePdjY2CAnJ4fRXJLMysoK48ePx4IFC0Tu9/DwwMmTJ3H//n3GMrVs2RLr16/H+PHjAfALUPTs2RPFxcUS+3S8qgIoj8dDdHQ0K58TNVEUhYsXL4LH4+Hs2bN04Zxdu3YxmqNx48YChWAyMzPRuHFj5Obmslo85ODBg5g+fTpatWoFeXl5PH/+HEuXLsXGjRtZywQASUlJuHTpEsrKytCvXz+Bh2mRkZHg8XiMv4c1xcXFYfLkyUhLS8PcuXPppT6qzJ07l6VkxL9BGloEQTSYun5xpaamYtu2bazfQFWt2XPkyBG6ZLOdnR2jlQe5XG6tw6SqSuEz/b3q378/rKyssGnTJpH7XV1d8eDBA1y/fp3RXADw/v17eHh4wM3NTWg+UW5uLtzd3bF48WLGCyv4+flhxowZ2LZtG6ZOnUrfMJWXl+PAgQN075KTkxNjmWRlZZGYmCgwT0dBQQHx8fEwMDBgLIcolZWV2L59u0AviJubG+Tl5eljnjx5wlqPFkVRePXqFcrKymBiYkK/n1lZWThy5Ah8fHwQFRXFaCYul4v09HQ0btyYfk1FRQXR0dEwMjJiNEt1bdu2xciRI7Fu3ToAgK+vL+bMmYP8/HzWMt28eRPDhg1DYWEhAEBaWhp+fn6wt7dnLZM4hw8fxvTp06GrqyvQ0OJwOHjz5g2LyYhvRRpaBEE0mPr+wpeUMvCVlZUICQmBt7c3Lly4wOgipJI6DC4oKAjjx4/Hjh07MGPGDLr3o6KiAnv37sWiRYtw/PhxVoZQLV68GHl5eTh48KDI/dOnT4eamhorhScWL14MDw8PqKiooGXLlgCA169fo6CgAHPnzsWOHTsYzSMlJYX09HR6wV1AMm7MAWDjxo1YtWoVBg4cCAUFBVy8eBETJ04U+74y6e3btxgxYgSeP38OgD8/Jjg4mNVhjAD//YyPjxdYQNnAwAARERFo3rw5fRxTBU2qKCkp4dmzZ/Sw2YqKCigoKCA5ORk6OjqMZqnSt29fqKqq4sCBA1BQUMDy5csREhKClJQUVvKIkpGRgSlTpiAiIgI7d+6U6GU1iK9DGloEQRA1FBUVYc+ePViyZAnbUcTatGkTpk+fDnV19QY/18qVK7Fx40aoqKigRYsW4HA4dKNhyZIlYnu7GlqbNm2wf/9+9OrVS+T+O3fu4Pfff0dMTAzDyfju3bsHf39/JCQkAABMTEwwfvx4scMwGxKXy8XQoUMFCiKcO3cOAwYMgJKSEv1acHAw49lMTU0xb948em2xsLAwjBw5EkVFRawXwxg3bhwiIyOxZs0ayMvLY+vWraioqMCDBw9YzSWqB7z6AvBs9YCL62mLiooSO2exoWlqauLmzZv0kPDPnz9DVVUVnz59YqVYTk0nTpzA7NmzYWlpCR6Px3oPM/F9kYYWQRASo23btggNDWXkF82nT59w//59yMjIYODAgZCSkkJZWRn27t2LTZs2oaysrM6SyWxSVVVFZGQkYzcvDx48wLFjx/Dq1Su62t+ECRPQtWtXRs4vipKSEl68eFFroQ5zc3N8/vyZ4WSSp77LKPj4+DRwEmHy8vKIj4+n30eKoiAvL483b96wXpJcT08P/v7+dE/yu3fvYGhoiIKCAigoKLCWS1J7wLlcLtzd3QXmibm6umLJkiUCVSyZnG8kqcMsqygpKWHTpk2YM2cO21GIBiBd9yEEQRDMePv2LcrKyhr8PHfu3MEvv/xCr7vUuXNn+Pj4YOTIkaisrMTKlSvh7Ozc4Dn+Daaekbm5ucHNzQ1du3YV2ahKTk6Gi4sLLl++zEie6hQUFPD27VuxDa23b9+ycjOcnJxcr+PE5W4IbDSg6qu0tFTgfeJwOJCVlWV06K446enpMDMzo7f19fWhoKCAjIwMgSF6TGO6AVVfzZo1w6FDhwRe09HRwV9//UVvczgcxgs7xMbGIj09nd6mKAovXrwQmDvWrl07RjNViYyMRKtWrcTuDw4Oxh9//MFaVUTi3yENLYIgfjqrV6/GkCFDsGrVKvB4POzcuRO2trb4448/4OjoyPpwJUni6+uLc+fO4ciRI2jbtq3AvoMHD2Lx4sXo2bMnK9msrKzw119/oU+fPiL3HzlyhJUet+pPyasaxNWvKbaGddVWeY1tq1evhqKiIr1dWlqK9evXQ01NjX7Nw8OD8VwcDgdcruCSo1wul/VFlatKgtdWQIQNb9++ZfX84gwcOFDoPbO1tQWHw2Ht57FKq1atcOjQIVy6dAkyMjKYN28erKyscO3aNSxatAgvX76sdV0+QrKRoYMEQUgMpsbya2lpITw8HBYWFigsLISKigpOnDiBMWPGNOh5vyemvld5eXmYPXs2AgICsGbNGri6uuLdu3dwdnbGo0ePsG3bNkyZMqVBM4hz/fp1DBo0CPPnz8eSJUvo6oIZGRnYsmULPD09cenSJQwYMIDRXNLS0tDX14eTkxN+/fVXoTLNVdq3b89YJkmuvNavX786H25wOBxcu3aNoURfcLlcqKmpCeTLycmBqqqqQAMsKyuL0VySXEBEXJVGtiQlJdXrOENDwwZOItq2bduwYsUKtGvXDi9evADAnxfr4eGBOXPmYNasWYwtHk58f6ShRRCExGCq8VBzzL6KigqePn0KY2PjBj3v98T0BPMzZ85g2rRp0NHRQWJiIrp3745Dhw6xPnH7wIEDmDdvHsrKyqCqqgoOh4Pc3FzIyMjQlRKZlp6eDj8/P/j6+iI7OxsODg5wcXGBubk541mq/AiV1ySRn59fvY5jukqcpBYQEVWlMSgoCJ06dWIt09eaOXMm/vzzT8YaN+bm5liyZAmcnZ1x48YNDBgwAAMGDMCpU6cYKXZENCzS0CIIQmIw1XioXhpZXFlkgPnSyF+D6YZWeno6HB0dcfXqVSgpKeHMmTOM9xTV9Oeff2Lx4sXIzs5GQECAQKEOOzs76Ovrs5oPACIiIuDj44PAwEC0bt0aLi4ucHFxERqO1tAkvfLa12C6EMzX8Pf3x/DhwwUqOTYESS0gIqlVGr8G09eXoqIi4uLi6PdSTk4ON2/ehJWVFSPnJxoYRRAEISGUlZWp169fN/h5OBwOxeVy6T/itpnk5+dHFRcX1/v4oUOHUu/fv2/ARF8cP36c0tTUpAYMGEDFxcVRS5YsoWRlZam5c+dShYWFjGQQhcvlUhkZGayd/2ukp6dT/fv3p7hcLpWZmcn4+TkcjtD3SllZmXrz5g3jWf4tpj4nvoWKigpjn2EfPnwQeE0Svi+6urrUjRs36O2UlBSKy+Wy+jnxtZj+Ptb82ZSE95H4fkgxDIIgWJOSkoI1a9aAx+MB4A8Dq5pn05CuX7/e4Of4WpMnT4aNjY1ACeLahIaGNnAiPjs7O1y8eBEbNmygyw9v2bIF//vf/+Dk5IQLFy7Az88P3bt3ZyRPddQPMCDjzp074PF4CAwMhKmpKby8vFgbDiTJldf+K5i8JiWxgIikVmmUdIcPH6ZL4peXl8PX11do6CLTlRqJ74MMHSQIgjVRUVHo2LEja9WeavPx40doa2szdj5Ra71Igp49e8LPz0/k/LXi4mK4urpi3759KC0tZTwbl8tFRkYGo+9TfaSlpeHIkSPw8fFBdnY2fvvtN7i4uMDCwoK1TFUL3Nb2K5/Nymtfg+0FcGvDVLb6FBABmH+oJCUlhfT0dIGfSVVVVURFRUnEmlX1wfT11bx583oVg3nz5g0jeYjvi/RoEQRB/IOiKFy4cAGHDx9GSEgI4+v4SGJZ+Vu3bomdTyQvLw9PT0+MHj2a4VRfDBw4sM6qZk+ePGEoDZ+hoSH09PQwadIkDB8+HDIyMqioqBBaB4fJ3qPExMQ6j8nOzmYgCfE93Lhxg+0IIlH/zJGs/llWUFAAS0tLVqs0SjJJLYlPfB+koUUQxE/vzZs34PF48PPzQ0FBAX755RecOHGC8RxOTk6Qk5Or9Zjg4GCG0vDVp2hD9aFCTBsyZAg95EZSlJeXIzk5GevWrYO7uzsA4SFlTPceiStdnZubi2PHjsHb2xuRkZE/RI+WJD6QkDTPnj2Dt7c3du7cyeh5JXlhbIJgA2loEQTxUyouLsapU6dw+PBh3Lt3D4MGDUJaWhoiIyPpymxMU1FRgYKCAivnFkdRURFJSUn0UCAbGxv4+PhAV1cXAH/NKj09PdZu0JcsWSJxwy3r03vEtmvXroHH4yE4OBiGhoYYPXo0Dh8+zHaseiEzHkTLy8uDv78/vL298ejRI1bm29WnzH15eTkDSb6dg4MDoxVnhw0bBn9/f3pu3fr16zFr1ix6LmdmZiZ69+6N2NhYxjIR3w9paBEE0WBGjRpV6/6cnBxmgtQwc+ZMnDhxAqampnBwcEBQUBAaNWoEGRkZxstuV7dr1y6JazQUFxcL3Njevn0bRUVFAsewdeMrqT0bbC18Wpd3797B19cXPB4Pnz9/xtixY1FWVoagoCC0bt2a1Wz5+fm4d+8eysrK0LVr11rXMLpw4QKrJcxrY2hoCBkZGUbPGR4eDm9vbwQFBaG4uBhLlizB8ePHJW5dwNjYWHh7e+Po0aPIyMhg7LyFhYVYsmQJTp8+jbKyMlhbW2PXrl1ir7F9+/Yxlg0ALl68KDBMffPmzbC3t6cbWuXl5Xj58iWjmYjvh707CoIg/vPU1NRq/WNoaIiJEycynuvgwYOYMWMGLl26hFmzZqFRo0aMZ6hJUhsN9cFWdknt2diyZYtAY/TmzZsCN1L5+fn0QrNMGTZsGFq3bo3Y2Fjs3r0b79+/x+7duxnNIE50dDTMzMxgY2MDW1tbGBsb48qVK2KP79WrV51DbL+nwMBA/Pbbbxg7diwOHjxY67HPnz9nZBHvtLQ0bNiwAcbGxhg/fjy0tLQQHh4OLpeLiRMnSkwjq6CgAIcPH0b37t3Rrl073L9/H8uWLWM0w5o1a+Dr64tffvkF9vb2uHz5MisLmYtT83NMUj/XiG/EQkl5giAIVh07doyytramlJSUqLFjx1Lnzp2jysrKKGlpaSomJoaVTKLWOZIEda3xkp6ezviaY1Xevn1LVVZW1vt4ptY4qrm+V83zsvE9k5KSohYsWEDFx8cLvM7mNV9l6NChVLdu3ajbt29Tjx8/poYPH06ZmpqymqnKgQMHKA6HQ5mYmFDt2rWjuFwutWzZMrZjUXJycpSDgwMVFhZGVVRU0K9LwvtJURR169YtatKkSZSysjLVtm1bSkpKioqIiGAlS4sWLSh/f396+/79+5S0tDRVXl7OSp6aJPkzlvj3SI8WQRCsOnXqFOPnnDBhAi5fvoznz5/DzMwMs2bNgq6uLiorK1kbB3/9+nVoamqycu7acDgcgR6rmttsMjQ0/KosFENPimueh6nz1ubWrVvIz89H586dYWVlhT179uDjx49sxwIAPHr0CLt370aPHj3QsWNH8Hg8JCQkoKCggO1o2L17N1auXImXL18iKioK3t7e2LNnD9uxYGhoiIiICNy8eRPx8fFsx6Ft2bIFZmZmGD9+PLS1tREREYHo6GhwOBxoaGiwkiklJQW9e/emt7t27QppaWm8f/+elTw1ifpMlZTPWOLfI+toEQTRoKrGl8vIyMDExIR+/cyZM3Bzc0NcXBzjZdRroigKFy9eBI/Hw9mzZ6GlpYVRo0Zh165djGU4cuRIvY5jeqgll8uFmpoa/Ys/JycHqqqq9Fw2iqKQl5f3Q1SrY2p9nJprotU8L5sFRAoLC3HixAnweDw8ePAAFRUV8PDwgLOzM1RUVBjPA4heQ05FRQXR0dGsr72kpKSEZ8+e0e9dRUUFFBQUkJycDB0dHVaz3b59G97e3ggMDISJiQkcHBywdOlSREdHw9zcnJVM0tLScHV1xZ9//gkpKSn6dRkZGURFRbEyF1DU2l6Scn0B/Ot/6NCh9HDYc+fOYcCAAVBSUgIAlJSUICws7If4jCWEkYYWQRANJjY2Fra2tkhKSgIAjBgxAvv27cPYsWMRFRWFKVOmYN68eYzMaaivrKwserHZqKgoxs5b29NeDoeDz58/o7y8nPFftn5+fvU6rj7VxthGGlqCXr58CW9vb/z111/IycnBoEGDcPbsWcZzSElJIT4+nr4RpigKBgYGiIiIQPPmzenjmKwEV0VcI1CSFkwuKCiAv78/eDwe7t+/j759+2LChAkYOXIk44t5b9iwAb6+viguLoa9vT0cHR3Rpk0bVhtaNRsygHBjBmB+6YwqkydPrtdxpHT+j4k0tAiCaDDDhw/H58+fsWDBAhw7dgwnT56EsbExHBwcsGDBAtaeoP9I0tLSsHbtWvB4PAwYMABhYWFsR6qVv78/hg8fLnADIymYbGi5u7vT63u5urpiyZIldJWz/Px8uLm5sd7QqlJRUYFz587RPbpM43K5QkOlKIqiX6v6fza+XzXfS0D4/QSAuXPnMp5NlBcvXtCN56ysLJSVlbGSIzw8HDweD0FBQWjZsiViYmIQHh6Onj17Mp6FNGQINpGGFkEQDUZHRwehoaHo2LEjcnJyoKmpiQMHDuD3339nNdfChQvrPIbD4WD79u0MpBEtPz8fmzdvhqenJywsLLBx40b079+ftTz1paqqisjISIl52l8dU9maN29erzkWP8J6W0wIDw+v13F9+/Zt4CTC6vNecjgcvHnzhqFE9VNeXo6zZ8/SS2xs2rQJ06dPp0uGMyU/Px/Hjh2Dj48PHj9+jK5du8LOzq5en8EE8V9AGloEQTQYLpeLtLQ0NGnSBACgrKyMJ0+eCMzVYkPNBktERAQ6deoksFgwh8PBtWvXmI6G0tJS7NmzBxs2bICWlhbc3d1hZ2fHeI5vJWnDqqqTpGypqakSuxYU8d8jCQ9Anj17Bm9vbxw/fhwfPnxg9NxJSUm4dOkSysrK0K9fP9bXjauuf//+IhvzampqMDU1xaxZsyRqeD3xdUhDiyCIBlNzErKqqiqioqIkYgJydZJwA05RFI4cOQI3NzeUl5djzZo1cHFxEZhQ/iOQhO+lOBEREejSpQujazDVlJ6ejg0bNuDQoUNCCz//rCiKwrZt2wQWlHVzc4O8vDzb0QDw87169QplZWUwMTGBtLQ025G+miT9XJaVldGLOrdt2xahoaEN2pC4efMmhg0bhsLCQgD8gh1+fn6wt7dvsHN+jQULFoh8PScnB48fP8abN28QERGBDh06MBuM+D4YLCVPEMRPhsPhUOrq6pSGhgaloaFBcTgcSk1Njd6u+sO2muuWsKFt27aUoqIi5erqSqWlpVG5ubki/0g6Jr+X5ubmVGZmJr39+++/Ux8+fKC3MzIyKAUFBUayVJednU1NmDCB0tLSonR1dSlPT0+qoqKCWr16NaWgoEB17tyZOn78OOO5JNWGDRsoLpdLDRo0iBo+fDglJydH/f7772zHoiiKohITE+n1s7hcLmVoaEg9evSI7VhfTRI+40RhIlefPn0oW1tbKjU1lcrKyqKmTZtG6evrN+g5v6eZM2dSQ4cOZTsG8Y1IjxZBEA3mR6lYJwlPe6vKpQOi11ChWCwI8DWY/F7WrAhXc3hURkYGvT4ak2bOnIlz585h3LhxCAsLw4sXLzBkyBAUFxdjzZo1rMw1kmSmpqaYN28eZs6cCQAICwvDyJEjUVRUxPp6QuPGjUNkZCTWrFkDeXl5bN26FRUVFXjw4AGrub6WJHzGicJELk1NTdy8eRNt2rQBAHz+/Bmqqqr49OkTa2t7fY3o6GgMGTIEaWlpbEchvsGP1/9NEMQPg+0G1I/k+vXrbEf44Yl6bsjGjXpISAh8fHxgbW2NmTNnwtjYGCYmJti5cyfjWX4ESUlJsLW1pbeHDBkCiqLw/v171uex3bp1C/7+/nTjuGvXrjA0NERRUZHAnE5CcuXk5AiU51dSUoKioiJycnJ+iIaWgoICiouL2Y5BfCPS0CIIosGIKtsM8HseTE1NsXTpUroqFpOio6MFtimKQlxcHAoKCgReb9euHWOZ/iu9HIaGhvT8i5/V+/fv6cn2LVq0gLy8PKZMmcJyKslVWloqVIhGVlaW9YXMAf6cOjMzM3pbX18fCgoKyMjIEFjji5BssbGxSE9Pp7cpisKLFy+Qn59Pv8bk5/3XuHTpEusFpIhvRxpaBEE0mODgYJENrZycHDx48AAODg7w8/PDmDFjGM3VoUMHcDgcgR6QqifqVa8zPUwvICAAI0eOhKysLADg7du3MDAwoIthFBYWYs+ePVi6dCljmb7F8+fPGTsXh8MRur7YHmoGAJWVlQKNTSkpKYlcV0ySrF69GoqKivR2aWkp1q9fDzU1Nfo1Dw8PxnNxOByBYb0A/wHSjzbronfv3j91D9zAgQOF3rPqvahsDssWt3Zdbm4uHj58CG9vb/j6+jIbivhuyBwtgiBY4+XlhSNHjuD+/fuMnjcpKalexxkaGjZwki+kpKSQlpZW63wjPT09xm8GjIyM6rWO0OvXrxlK9AWXy0WbNm3oKnDR0dEwMzOjG6vl5eWIiYlh/HvG5XIxdOhQurrhuXPnMGDAAKHGVnBwMKO5JFW/fv3q1UBmY3gtl8uFmpqaQL6cnByoqqoKNMCysrIYzfVfeTDDxByt+nzeZ2dns1bVr2ZDvoqKigrMzMywePFixh9GEt8PaWgRBMGahIQEdO3aFdnZ2WxHYV3Nwg41b0DYamh5enqK3ff27VscOHAAJSUlrDwNXrt2bb2OW7NmTQMnETR58uR6Hefj49PASYh/S1IL+kjqg5mvdfz4cYwYMYKVHt/c3FwcO3YM3t7eiIyMlPjvFfGDYqHSIUEQBEVRFBUVFUXp6Ogwft74+Hhq/PjxIsul5+TkUPb29oyXQuZwOFRGRga9XbPscXp6OsXlchnNJE5mZiY1f/58Sk5OjurTpw919+5dVnIkJSVRFRUVrJybYE50dDQ1b948tmOIVVZWxvg5JfXzYujQoVROTg697e7uTmVnZ9Pbnz59oszNzRnPVd3Vq1ep3377jVJQUKDMzMyolStXUk+ePGE1E/HfJbq/kiAIggGHDh2CpaUl4+fdunUrDAwMoKqqKrRPTU0NBgYG2Lp1K+O5JF1RURHWr1+PFi1a4Pr16wgODkZ4eDi6devGSh4jIyN8+vSJlXMTDSsvLw8HDhxA165d0b59e9y4cYPtSEJiY2OxaNEi1isjSpKLFy8KFDHZvHmzwLDK8vJyvHz5kvFc7969g7u7O1q0aAF7e3toaGigrKwMQUFBcHd3Z+X3UHXl5eXYunUrOnbsCGVlZWhqaqJbt244cODADzcfkBBEimEQBNFgFi5cKPL13NxcPHr0CK9fv8atW7cYTgXcvHkTf/31l9j9Y8eOxYQJExhMxHfx4kV68n9lZSWuXr1KF5fIyclhPE+ViooKHDp0CGvXroW8vDx2794NBwcH1gtPkBuQ/57w8HB4e3sjKCgIxcXFWLJkCY4fPw5jY2O2owEACgoKcOLECXh7e+Phw4fo1q0bli1bxnYsiVHzZ1ISfkaHDRuGiIgI2NraYvfu3bCxsYGUlBT279/PdjQA/AdYgwYNwt27d2FtbY0+ffrQlXCr1uQ7e/YsEhMTcevWLTg5ObEdmfgKpKFFEESDefr0qcjXVVVVYWNjg5kzZzJacKJKUlKSwLoqNWlpaSElJYXBRHw153lMmzZNYJuNhk1AQABWrVqF3NxcrFixAjNmzKAn4BPE95CWlgYfHx/weDx8/vwZ9vb2CA8PR/fu3TFx4kSJaGRFRETg8OHDCAoKgpGREWJjYxEeHo6ePXuylklSH8xImkuXLmHu3LmYMWMGWrVqxXYcIRs3bkRKSgqePn0qVGI+KioKw4cPx4IFCxAUFARXV1eWUhLfijS0CIJoMJK6CK+amhpev34ttpH36tUrkcMKG1JlZSWj56uv8ePHQ0FBAfb29khKShL79J6N0tsAcPjwYSgrK9d6zNy5cxlKQ3wLIyMjjBkzBl5eXhg0aJDYKmxs2LJlC3g8HgoKCmBvb4+IiAi0b98eMjIyrC92K4kPZiRxyYVbt26Bx+Ohc+fOMDMzg6OjI8aNG8dqpupOnDgBDw8Pket4tW/fHtu2bcO4ceMwefJkzJkzh4WExL9Bqg4SBPHTGTt2LMrKyvD333+L3D9ixAjIysoiMDCQsUzOzs7w9PSEiooKY+esj/qU3uZwOLh27RpDib7gcrnQ19enS1qLwuFw8ObNGwZTEV/L1NQUpaWlmDBhAhwdHekFgmVkZBAVFUUv/swGaWlpuLq64s8//xS4ziQhmySqa2mDkpIShIWFsVLhr7CwECdOnACPx8ODBw9QUVEBDw8PODs7s/q5Ky8vj4SEBBgYGIjcn5KSgubNm5OqiD8o0tAiCOKn8/TpU3Tv3h22trZYunQpTE1NAQBxcXHYsmULQkJCcOfOHXTs2JGxTDXLNRN1q1kSn/hx3b59G97e3ggMDISJiQkcHBywdOlSREdHw9zcnLVcGzZsgK+vL4qLi2Fvbw9HR0e0adOGNLTEcHJyqlcPFttLG7x8+RLe3t7466+/kJOTg0GDBoldOLihNW7cGBcuXECnTp1E7n/48CGGDRuGjx8/MpyM+B5IQ4sgiJ/S+fPn4ezsjMzMTIHXGzVqhMOHD2P48OGM5vlRGg2fPn0Ch8NBo0aN2I5CGqf/QQUFBfD39wePx8P9+/fRt29fTJgwASNHjoS2tjZrucLDw8Hj8RAUFISWLVsiJiaG1Tlajx8/xuLFi3HmzBmhYc65ubkYOXIkdu7cifbt27OS70dRUVGBc+fOgcfjsdbQGjduHMrLyxEUFCRy/+jRoyElJYWAgACGkxHfA2loEQTx0yoqKkJYWBhevXoFiqJgYmKCwYMHQ1FRkfEsXC4XGRkZrN5MipOTk4OVK1fi5MmT9OLSGhoaGD9+PNzd3aGurs5Krh+lcUp8mxcvXtC9DllZWSgrK2M7EvLz83Hs2DH4+Pjg8ePH6Nq1K+zs7MRWWG0oEyZMgLm5OVavXi1y/4YNGxAbG4ujR48ymos8/Ph6sbGxsLKygoWFBRYuXEgPnY2NjcWOHTsQGxuLe/fuwcLCguWkxLcgDS2CIIg6tG3bFqGhoWLH0H8PXC4XampqdQ67qb4mDROysrLQvXt3pKam4rfffoO5uTkoisKLFy9w/PhxGBgY4M6dO6wUBli7di2WLFnCSsOYYE55eTnOnj2LUaNGAQA2bdqE6dOns9bAr/Ls2TN4e3vj+PHj+PDhA6PnbtmyJf7++2+RBRSqso0YMYLx+Ynk4ce3uXfvHlxcXPDixQv6dwBFUTAzM8Phw4fRo0cPlhMS34o0tAiCIOqgoqKCqKgotGjRosHOweVysXPnTrpcszg1K401tPnz5+Pq1au4cuUKmjRpIrAvPT0dgwcPxsCBA7Fjxw5Gc1X38OFD+Pv7Iz4+HhwOB61atcKECRPQuXNn1jIRDUdVVRWRkZEN+vP4NcrKyiAjIwOAmYcyAL+AwosXL2BkZCRyf2JiIlq3bo2ioqIGzVETaWj9O5GRkYiPjwcAtGrVivWFlIl/j5R3JwiCkBDjx4+XuBuU06dP48CBA0KNLADQ0dHBli1bMH36dNYaWkuXLsW2bdugrKyMFi1agKIo3LhxA56enli8eDE2b97MSi6i4Uja8+GqRhYAvH37lpEhjtra2nj58qXYhlZcXBy0tLQaPIco1df3EofpObA/ig4dOqBDhw61HiNpDxqI2pGGFkEQhARge60ZcdLS0mqdG9CmTRukp6czmOgLPz8/7N69G7t27cK0adPoG96ysjLs27cPrq6usLCwwMSJE1nJRxANxdraGuvXr4eNjY3QPoqisGHDBlhbW7OQrO5edw6HQ0qV/wuS9qCBqB1paBEEQUgASf3lqaWlhbdv30JfX1/k/sTERNYqEHp5eWHDhg2YPXu2wOsyMjKYO3cuysvLsWfPHtLQIv5zVq1ahU6dOsHKygqLFi2CqakpOBwOXrx4ge3btyM+Pp61Eupk6CBBfCE5y68TBEH8xCorKyXy5sTGxgYrV65EaWmp0L6SkhKsXr1a5FN1JsTExGDEiBFi948cORIxMTEMJiIIZrRs2RJXrlzB58+fMX78eHTs2BGWlpawt7dHYWEhLl++DGNjY8ZzSWrPPEGwhfRoEQRBSABnZ+c6j+FwOPD29mYgzRdr165F586d0apVK8yaNUug9PDevXtRUlKCv/76i9FMVaSkpEQ2AKuUlZVBSkqKwUQEwZzOnTvj+fPnePr0qcASFVVzfAoLCxmvyCmpPfMEwRbS0CIIgqghJSUFa9asAY/HAwCxxSC+p6r1qUSpqKjAlStXUFJSwnhDS19fH3fv3sXMmTOxfPly+kaKw+Fg0KBB2LNnT4NXWBOnU6dOOHbsGNatWydy/19//YWOHTsynIpoaL1794aCggLbMSSGpaWlQHW64uJieHl5YevWrYzPn5w0aRJ5bxoY6TX8sZDy7gRBEDVERUWhY8eOEjFh+8yZM1ixYgXev38PV1dXLFu2jLUs2dnZSEhIAAAYGxtDU1OTtSwAcP78eYwcORILFy7EokWL6MZweno6tm/fjp07d+Lvv/+Gra0tqzmJ2gUEBGDkyJGQlZUFwK/cZ2BgQPdGFhYWYs+ePVi6dCmbMevl+PHjGDFiBJSUlBr0PKWlpVi7di0uXboEGRkZLF26FCNHjoSPjw9WrlwJDoeD2bNnY/ny5Q2aQ5zU1FQEBQXRSy6YmJhg1KhRaNq0KSt5/kuYWG6E+I4ogiAIQkBkZCTF5XJZzRAREUH17NmTUlRUpJYuXUplZWWxmkdS7dq1i5KVlaW4XC6loaFBaWhoUFwul5KRkaF27NjBdjyiHrhcLpWRkUFvq6ioUK9fv6a309PTWft5HDp0KJWTk0Nvu7u7U9nZ2fT2p0+fKHNzc8ZzLV++nFJVVaVGjx5N6ejoUNLS0tTUqVMpExMTytfXlyotLWU8UxUvLy9KTk6O4nA4lLq6OqWmpkZxOBxKTk6O8vLyYi3Xj6asrIzKz88Xev3WrVtUcXExC4mIb0GGDhIEQUiQmJgYLFu2DGFhYZg4cSJOnDghtuIfE0aNGlWv44KDgxs4iWhz5szB//73PwQGBtK9bSYmJhg9ejRrQxqJr0PVGFhTc5tNFy9eRElJCb29efNm2NvbQ11dHQBQXl6Oly9fMp4rICAAvr6++N///oeoqChYWloiLy8PMTExkJZm79YuJCQEc+fOxfz587Fo0SLo6uoC4C8TsXXrVsybNw/NmzfHsGHDWMsoaUJDQ5GZmQlHR0f6tfXr12PdunUoLy/HgAEDcPLkSWhoaAAAevXqxVZU4huQhhZBEIQESElJgZubG44ePQpbW1tER0fD3Nyc7VhQVVWV+DkB+vr6WLBgAdsxiP8gSW0EpqSkoEuXLgCA9u3bQ1ZWFq6urqw2sgBgy5YtWLZsGdzd3QVe19XVhYeHBxQVFbF582bS0Kpm27ZtGD16NL19584duLm54c8//4S5uTlWrlyJdevWwcPDg8WUxLciDS2CIH46dfXS5OTkMBOkmqp1cBYtWoQePXogISGB7qGpbvjw4Yzm8vX1ZfR8X+PmzZv1Oq5Pnz4NnIQgmFVWVkbPaQP4a8epqamxmIjv6dOnOHjwoNj9jo6O8PT0ZDCR5Hv+/Dm2b99Ob586dQqDBg3CypUrAQDy8vKYN28eaWj9oEhDiyCIn05dNyRqamqML3JbXFwMgP9EWBwOh8N4gQ4pKSmkpaVJ5Bpf/fr1o3vbxPU0sPE9I77exYsX6Z/LyspKXL16Fc+fPwfAzoOPKhwOR6hHV1J6eN3c3Ojy7aWlpXB3dxf6bGP65ryyshIyMjJi98vIyEhMr6CkyM/PF1j0PSIiAnZ2dvS2hYUF3r9/z0Y04jsgDS2CIH46Pj4+bEcQUllZyXYEkST5pkhDQwMqKipwcnKCo6MjtLS02I5EfKNJkyYJbE+bNk1gm63GDUVRcHJygpycHAD+A5Hp06fTVQWrz99iUp8+fQTmhvXo0QNv3rwROIaN75mFhQXOnDkjdijv6dOnYWFhwXAqyaanp4cXL16gWbNmKCgoQFRUFHbs2EHvz8zMZHw9NOL7IQ0tgiCIaiorKxESEgJvb2+cPn2a7ThELdLS0vD333+Dx+Nhy5YtGDZsGFxcXGBjYyMxvQ5E3ST1IQMATJw4UeBacnBwEHkM027cuMH4Oetj5syZmDFjBuTk5DB16lR6zlh5eTkOHDiAVatWYe/evSynlCx2dnaYP38+VqxYgdDQUOjo6KBbt270/kePHsHU1JTFhMS/QdbRIgiCAJCQkAAejwc/Pz9kZ2djyJAhrDS0AgMD4e/vT68/06pVK0yYMEFgKAmTuFwu/Pz86hxuyfTcsZpSUlLg4+MDPz8/lJSUYNKkSVi7di3rxQEI4mezePFieHh4QEVFBS1btgQAvH79GgUFBZg7d65Abw3BXydu2rRpOH/+PHR0dHDw4EH07t2b3t+/f3/Y2NjA1dWVxZTEtyINLYIgflpFRUUICAiAt7c37t27h4qKCuzYsQPOzs5QVlZmNEtlZSXs7e0RGBgIExMTmJmZgaIoxMXF4dWrVxgzZgz8/f0Z76nhcrl1HiNJ86ASExPh4uKC8PBwfPz4kfVFlYm6PX78GIsXL8aZM2egqqoqsC83NxcjR47Ezp070b59e8azSeocRWdnZ5Gvq6mpwdTUFA4ODox/hlV37949+Pv7Cyy5MH78eIGeGoL4GZBHfQRB/HQePHiAw4cP4+TJkzAxMYGDgwMCAwOhr68Pa2trVm5Qdu7ciStXruDs2bOwtbUV2Hf27FlMnjwZnp6emD9/PuPZ0tPTJe5Gs7qSkhIEBQWBx+Ph7t27+OWXXxASEkIaWT+I7du3Y8CAAUKNLIDfcBg0aBC2bt2Ko0ePMp5NUp9FZ2dni3w9MTERx44dw7p163Dr1i20aNGC4WR83bp1I40qggDp0SII4ickLS2NOXPmYPr06QJj32VkZBAVFYXWrVsznqldu3aYP3++2CfV3t7e2LlzJ549e8ZoLkl9og/wG8w+Pj44ceIEjIyM4OTkBAcHB9LA+sG0bNkSf//9N9q1aydy/7NnzzBixAihYg9M4HK5Ev+goaaioiJ6bllAQACj505OTq7Xcc2aNWvgJD+O/v371zlSgcPh4OrVqwwlIr4n0qNFEMRPZ8CAAfD29saHDx/g6OiIIUOGsF48ISEhAdbW1mL3W1tbY/bs2Qwm4qvPs7jIyEh06NCh4cPU0K1bNzRr1gxz585Fp06dAPBLI9fE9vwxonapqalQUVERu19ZWRlpaWkMJhJUvfS8OJJ0jSkoKMDV1bXO9QIbgpGREf3/VZ8d1T9bKYqSqKHGkqC2z868vDz4+/uzVt2S+PdIQ4sgiJ/OpUuX6OIJM2bMQFFREcaNGweAvTLSCgoKyMnJEfukNy8vDwoKCgyn4pfdFnXe3NxcHDt2DIcPH0ZUVBRrN07JyclYt26d2P3kpk7yaWtr4+XLlwI36dXFxcWxWrq/Zun5miTxGtPU1GRl/TEOhwN9fX04OTnh119/JcVo6kFUcZDy8nJ4eXlh/fr1aNq0aa2fcYRkI0MHCYL46V2+fBk8Hg+nT5+GgYEB7OzsYGdnh44dOzKW4ZdffkGzZs2wb98+kfunT5+OlJQUhISEMJZJlGvXroHH4yE4OBiGhoYYPXo0Ro8eDUtLS1ZzET+uyZMn49WrV7h165bQPoqi0KdPHxgbG7Oy/t2POHQQAI4ePYrt27fj6dOnjJ43PT0dfn5+8PX1RXZ2NhwcHODi4gJzc3NGc/zIjh07Bjc3NxQVFWHVqlUCZfKJHw9paBEEQfwjOzsbR48eBY/HQ3R0NKNPqe/cuYN+/fph5MiRWLx4MV118MWLF9i+fTvOnDmD69evo2fPnoxlqvLu3Tv4+vqCx+Ph8+fPGDt2LPbv38/afDbiv+X169fo1KkTTE1NsWjRIpiamoLD4dDXfnx8PB49egRjY2PGs0nqHMXo6GiRr+fm5uLhw4fYsGED3N3dMX36dIaTfREREQEfHx8EBgaidevWcHFxgYuLS70qmf6MwsLCsGzZMiQmJmLx4sVYuHAhvTA28QOjCIIgCCGPHz9m/JzBwcGUlpYWxeVyBf40atSIOnXqFON5KIqihg4dSqmoqFD29vbU+fPnqfLycoqiKEpaWpqKiYlhJVOVGTNmUPn5+fT2kSNHBLazs7OpoUOHshGN+EoPHz6kLCwsKA6HQ1/3HA6HsrCwoB48eMBaLg6HQ2VkZLB2fnGqvk8cDkfoT+PGjaktW7awHZGWnp5O9e/fn+JyuVRmZibbcSTO/fv3qX79+lHy8vLU/PnzqY8fP7IdifiOSI8WQRA/HXFPg2sSVwWtIRUWFuLixYsC688MHjwYioqKjGcB+BUa586dixkzZqBVq1b062xWaKxSs7dBVVUVkZGRdEnrjIwM6OnpSdz8GUK8p0+f4tWrV6AoCiYmJnShgMLCQlZ+BiZPnoxdu3bVWqyDDUlJSSJfV1NTg7q6OrNhxLhz5w54PB4CAwNhamoKZ2dnTJ06lfRo1cDlcqGgoIBp06ahefPmYo+bO3cuc6GI74Y0tAiC+OlwuVxwOJxaK+oxPcH92rVrmD17Nu7duydy0dYePXpg//796N27N2OZAODu3bvg8XgICAiAmZkZHB0dMW7cOOjp6bHe0Ko5f0ZFRQVRUVGkofUfUlxcDC8vL2zduhXp6ems5UhNTUVQUBDi4+PB4XBgYmKCUaNGoWnTpqxlkkRpaWk4cuQIfHx8kJ2djd9++w0uLi6wsLBgO5rEat68eb3Ku7OxvAHx75GGFkEQPx1xT4NrMjQ0bOAkXwwfPhz9+/fHggULRO7ftWsXrl+/jr///puxTNUVFhbixIkT4PF4ePDgASoqKuDh4QFnZ2fWnvaThtZ/Q2lpKdauXYtLly5BRkYGS5cuxciRI+Hj44OVK1eCw+Fg9uzZWL58OSv59u7di4ULF6K0tBRqamqgKAp5eXmQlZWFh4cHZs6cyUouAAgMDIS/vz/dAGzVqhUmTJgAOzs7VvLIyspCT08PkyZNwvDhwyEjIyPyODZGCxAEG0hDiyAIQgIYGhoiLCxMbHWuuLg4DB48uN4Lgjakly9fwtvbG3/99RdycnIwaNAgnD17lvEcpKH137BixQp4eXlh0KBBuH37Nj59+gRnZ2fcuHEDK1aswIQJE8TesDe0kJAQjBgxAvPnz8eiRYugq6sLgN9zs3XrVuzevRtnzpzBsGHDGM1VWVkJe3t7BAYGwsTEhC6eExcXh1evXmHMmDHw9/dnfLmK6sMCq85d8zZTEsvhs62yshK+vr4IDg7G27dvweFw0KJFC4wePRqOjo6sr/NIfDtSL5IgiJ9OQkIC3NzccODAAZHD9GbMmAF3d3f6hp0JGRkZtd5MSktL4+PHj4zlqY2pqSm2bNmCjRs34ty5c+DxeKxlcXNzo+fulJaWYv369fTisoWFhazlIuovICAAvr6++N///oeoqChYWloiLy8PMTExrJe13rJlC5YtWwZ3d3eB13V1deHh4QFFRUVs3ryZ8YbWzp07ceXKFZw9exa2trYC+86ePYvJkyfD09MT8+fPZzRXYmIio+f7L6AoCr/++isuXLiA9u3bo23btnTFWScnJwQHB+P06dNsxyS+EenRIgjipzN16lSoq6tjy5YtIve7uroiLy9P7JpWDaFly5bYtm0b/ve//4ncHxwcjMWLF5Nx+tX069evXk96r1+/zkAa4lvJycnh9evX0NfXBwDIy8vj3r17dCEMNqmqquLhw4cwNTUVuf/ly5fo3Lkz8vPzGc3Vrl07zJ8/H87OziL3e3t7Y+fOnXj27BmjuYiv5+Pjg3nz5uHMmTPo37+/wL5r165h5MiR2LNnDyZOnMhSQuLfIKVfCIL46dy8eRNjxowRu3/s2LG4du0ag4mAYcOGwc3NDcXFxUL7ioqKsGbNGqEn10y4f/8+Lly4IPDakSNHYGRkhMaNG2Pq1KkoKSlhPBcA3LhxA9evX6/zDyHZysrKICsrS2/LyMjQvZJsq6ysrLWnWUZGptaiOg0lISEB1tbWYvdbW1vj1atXDCbi27JlC4qKiujtmzdvCnw+5OfnszqnTRL5+/tjxYoVQo0sABgwYACWLVuGY8eOsZCM+B5IjxZBED8dBQUFxMXFiS12kZSUBHNzc0aHnmVkZKBjx46QkpLC7NmzBRZt9fLyQkVFBZ48eYImTZowlgkAhg4din79+sHV1RUA8OzZM3Ts2BFOTk4wNzfH1q1bMW3aNPzxxx+M5qqvhw8fokuXLmzHIGrB5XIxdepUegiol5cXHBwchBpbHh4ejGezsrLC+PHjxRap8fDwwMmTJ3H//n1Gc2lqauLGjRtii0o8e/YMffv2RVZWFqO5yJILX09HRwdhYWFie3CfPn2KoUOHslp1k/h2ZI4WQRA/HTU1Nbx+/VpsQ+vVq1dCc7caWpMmTXDnzh3MmDEDy5cvp5+SczgcDBkyBHv37mW8kQUAkZGRWLduHb194sQJWFlZ4dChQwAAAwMDrFmzhtWGVkFBAaSkpKCgoEC/FhkZidWrVyM0NJTc1Em4Pn364OXLl/R2jx49hIbIslUMYObMmZgxYwbk5OQwdepUes5YeXk5Dhw4gFWrVmHv3r2M5+revTv27dsndnizl5cXunfvznAq4cIX5Fl+3bKysmr9bG/SpAmys7MZTER8T6ShRRDET6dPnz7YvXs3BgwYIHL/rl27GF+vCuBXHgwNDUV2dja9aGurVq2goaHBeJYq2dnZAjcB4eHhsLGxobe7dOmClJQUNqLh3bt3GDduHO7du0f3BLq7u2P69Onw9/fHiBEjEBERwUo2ov5u3LjBdgSxJk2ahGfPntHl5Vu2bAkAeP36NQoKCjB37lw4OTkxnmvlypXo168fMjMzsXjxYrrq4IsXL7B9+3acOXOGDJv9QVRUVNRa9EVKSgrl5eUMJiK+J9LQIgjip7N8+XJ0794ddnZ2WLp0KT3RPS4uDlu2bMHFixdx584d1vJpaGhIzHC3Jk2aIDExEQYGBigtLcWTJ0+wdu1aen9+fj5rpbeXLVuGgoICeHp6IigoCJ6enggPD0f79u0RHx8PIyMjVnIR/y3btm2DnZ0d/P39kZCQAID/sGb8+PHo1q0bK5l69OiBkydPYurUqQgKCqJfpygKmpqa8Pf3R8+ePVnJRnwdiqLg5OQEOTk5kfvZmgNLfB+koUUQxE/H0tISp06dgrOzs9ACwI0aNUJAQAA6duzIUjrJYmNjg2XLlmHz5s04ffo0FBUVBXr7oqOj6af8TLt+/ToCAgLQs2dP2NnZQU9PD2PGjMGyZctYyUN8G3GV89TU1GBqagoHBwcoKysznEpQt27dWGtUifO///0PQ4YMwcWLF+kGoKmpKQYPHiwwjJZphw8fpt+v8vJy+Pr6QktLCwAYr874I5g0aVKdx5CKgz8uUgyDIIifVlFREcLCwuhheiYmJhg8eDA9KZ8APn78iFGjRuH27dtQVlaGn5+fQAn6gQMHolu3bli/fj3j2aSkpJCamgodHR0AgJKSEh49eiR20WdCMolb0iAnJwcxMTGQkZHBrVu3GF3Xrkp9Fwhv1qxZAycRdP/+fWRlZWHo0KH0a35+fvjjjz/w+fNnjBw5Ert37xbbS9JQmjdvXq/5dGS9LeJnQRpaBEEQRJ1yc3OhrKwMKSkpgdezsrKgrKwsUJ6bKVJSUkhPT4e2tjYAQEVFBdHR0WTI4H9IUVERJk6cCA6Hg4CAAMbPX/16r16gpvprHA6H8YIroqqBdurUCZMmTZL4aqCpqalo2rQp2zEIghGkoUUQxE9n2LBh8Pf3p8tHr1+/HrNmzYK6ujoAIDMzE71790ZsbCyLKX8cp06dgp2dHePn5XK5aNOmDT2RPDo6GmZmZkKNvidPnjCejfh+Hj16hFGjRtW7d+l7kpaWhr6+PpycnPDrr7+KLVrQvn17RnPp6uri3Llz6Ny5MwB+cYzw8HC6+EtgYCDWrFkjUZ9h6enp2LBhAw4dOiSw1hZB/JeROVoEQfx0Ll68KDDBePPmzbC3t6cbWuXl5QLlpn92Vd8PGRkZmJiY0K+fOXMGbm5uiIuLY6WhtWbNGoHtESNGMJ6BaHiamprIyclh5dzv3r2Dn58ffH19sX//fjg4OMDFxYX14amSWg00JycHs2bNwqVLlyAjI4Nly5Zh9uzZ+OOPP7Bt2zZYWFiAx+Mxnosg2EIaWgRB/HTIWi/1FxsbC1tbWyQlJQHgN2b27duHsWPHIioqClOmTMH58+dZyVazoVWX27dvo3PnzozPWyH+nTt37rBWcEVHRweurq5wdXVFREQEfHx8YGVlhdatW8PFxQUuLi7gcrmM55LUaqArVqzAzZs3MWnSJISFhWHBggUICwtDcXExLly4gL59+zKeiSDYRBpaBEEQhFjLli2DkZERdu3ahWPHjuHkyZN4/vw5HBwccP78eaioqLAdsd6GDh2KyMhIVooqEOJFR0eLfD03NxcPHz7Ehg0b4O7uznAqYb169UKvXr2wYcMG2NvbY/r06Rg9ejQ0NTUZzyKp1UBDQkLg4+MDa2trzJw5E8bGxjAxMcHOnTsZz0IQkoA0tAiC+OlwOByhylj1qZT1M3rw4AFCQ0PRsWNH9OrVCydPnsSSJUvw+++/sx3tq5GeS8nUoUMHcDgcke+PtrY2XF1dMX36dBaSCbpz5w54PB4CAwNhamoKLy8vergx09zd3TFq1Cj07duXrgZafW4ij8fD4MGDGc/1/v17tG7dGgDQokULyMvLY8qUKYznIAhJQRpaBEH8dGouEFlcXIzp06dDSUkJAFkgsroPHz7QFcLU1dWhqKhIhv8Q35W4Ut9qamqsNWSqpKWl4ciRI/Dx8UF2djZ+++033LlzBxYWFqzm0tbWxq1bt8RWAw0MDGRl7bHKykqBIYtSUlL05ypB/IxIQ4sgiJ9OzQUiHRwchI4hC0TycTgcgTkoXC6XlbkfxH+XoaEh2xHEMjQ0hJ6eHiZNmoThw4dDRkYGFRUVQsMd27Vrx0q+qsqpNbExnBGo+yFWleDgYDbiEQTjSHl3giAIQiwulws1NTV6aGVOTg5UVVWFCgBkZWWxEe+rqKioICoqiszRklCBgYHw9/dHfHw8OBwOWrVqhQkTJrBS0bJK9eu86meg5m0TG+toSarJkyfX6zgfH58GTkIQkoH0aBEE8VNKSkrCpUuXUFZWhn79+tHzCghB/6UbIjIPTzJVVlbC3t4egYGBMDExgZmZGSiKQkxMDMaNG4cxY8bA39+flfdP3LBGQrT/0ucFQXwPpKFFEMRP5+bNmxg2bBgKCwsB8Bcl9fPzg729PcvJJE/NYZaSJDk5GQYGBvW+AScDOCTTzp07ceXKFZw9exa2trYC+86ePYvJkyfD09MT8+fPZzybJA9rJAhC8jG/+ANBEATLVq9ejf79++Pdu3fIzMyEs7Mzli5dynYsifTgwQOBYVE1GyslJSUICAhgOhYAwMjICB8/fqz38fn5+WTYoATy9fXF1q1bhRpZADB8+HBs2bIF3t7eLCQDtmzZgqKiInr75s2bAsVy8vPzMXPmTDaiEQTxAyBztAiC+Oloamri5s2baNOmDQDg8+fPUFVVxadPn6ChocFyOskiJSWFtLQ0NG7cGACgqqoqsBZVRkYG9PT0WJmjwuVykZ6eTmcjfkwKCgp4+fIlmjVrJnJ/UlISzMzMBBo8TJHk658gCMlHerQIgvjp5OTkCNycKykpQVFRETk5OeyFklA1n8WJejZHntcR/4aCgkKtP3t5eXlQUFBgLlA19bn+CYIgxCFztAiC+CnFxsYiPT2d3qYoCi9evEB+fj79Glslm380bBaZOHz4cJ3rBc2dO5ehNMS36N69O/bt24d9+/aJ3O/l5YXu3bsznIogCOLfIw0tgiB+SgMHDhR6Om1rawsOhwOKokjJ5h/E/v37hRZrrY7D4ZCGloRbuXIl+vXrh8zMTCxevJiuOvjixQts374dZ86cwfXr19mOSRAE8dVIQ4sgiJ8OKdn8dar3/lEUhbi4OBQUFAAAPn36xGY0PHr0iMzR+sH16NEDJ//f3r0HdVXnfxx/fb+gclEIVkRJTFBBTY3VLKUMcwnBUNc2cb2Coq6ZOm7bmJdZ1CHdUdN1MW9DCrqbmLfyQsmul9S8bLZeV827hhfMTbwiKHy/vz/89S0E0oo4B7/PxwwznvM54GuYafL1fZ/zOR98oMGDB2vlypWO83a7Xb6+vsrIyNBzzz1nWL7vT00LCwuVnp6umjVrSlKxCTgA3I/NMAAAZbJarY4p3/2Mnv7dv1EBKre8vDxlZWXp+PHjkqTQ0FBFRUUZ9nyWJNWvX/+hbo3lwxsApWGiBcDpXLlyRXl5eapbt67j3KFDh/TOO+/o1q1b+u1vf6tevXoZmNA8zPwPSD4nfDT8+9//1pUrVxQTE6Nu3bpJkhYtWqSRI0c6/nucNWuWqlWrVuHZzpw588Brzp8//8sHAVApUbQAOJ3XX39dderU0YwZMyRJX3/9tdq1a6eAgAA1aNBACQkJKioqUt++fQ1Oarzc3FyFhYUZHaNU48ePf+BGGDC/CRMmqH379oqJiZEkHTx4UIMGDVJ8fLyaNGmiadOmKSAgQBMmTDA26H1ycnI0efJkpaamGrL1PADzY3t3AE5n165d6tKli+N48eLF8vX11b59+7R69WpNnjxZs2fPNjChebRs2VKtWrXS3Llzde3aNaPjFDN8+HBduXKl2LlDhw6pf//+iouL05IlSwxKhh9j3759+s1vfuM4Xrp0qZ555hmlpqbqjTfeUEpKimEvxb569ap69+4tPz8/BQQEKCUlRTabTUlJSQoODtbOnTu1cOFCQ7IBMD+KFgCnk5OTo6CgIMfxpk2b1K1bN7m63hvyd+nSxfGciLPbvn27WrZsqdGjR6tOnTrq06ePaXaAe/311x1TSem7yeTu3btVUFCghIQE/f3vfzcwIR5Gbm6u/P39HcdbtmxRdHS047h169bKzs42IprGjh2rrVu3Kj4+Xr6+vvrjH/+o2NhYffbZZ/rkk0+0e/du9ezZ05BsAMyPogXA6Xh5eRV7Qernn3+uNm3aOI4tFosKCgoMSGY+bdu2VWpqqnJycjR37lydO3dOkZGRatCggSZNmqRz584Zlo3J5KPB39/f8SzgnTt3tGfPnmLvzbpx44aqVKliSLbMzEylpaXpnXfe0Zo1a2S32xUSEqJNmzYpIiLCkEwAKg+KFgCn88wzzzhuAVqxYoVu3LihDh06ONaPHTumwMBAAxOaj7u7u+Lj4/Xpp5/q2LFj6tmzp+bPn6+goCB16tTJkExMJh8N0dHRGj16tLZt26YxY8bIw8ND7dq1c6wfOHBADRo0MCTbhQsX1LRpU0lScHCw3NzcNHDgQEOyAKh8KFoAnE5ycrJWr14td3d39ejRQ6NGjZKPj49jfenSpXxa/QMaNGig0aNHa9y4cfLy8lJWVpYhOZhMPhrefvttubi4KCIiQqmpqUpNTVXVqlUd6wsXLlRUVJQh2Ww2W7FpmouLizw9PQ3JAqDyYddBAE4nLCxMR44c0Y4dO1S7dm09++yzxdZ///vfOz7FRnFbtmzRwoULtXLlSrm4uCguLk6JiYmGZPl2MpmamqpVq1Yxmayk/Pz8tG3bNl27dk3Vq1eXi4tLsfXly5cbtruk3W5XQkKCY2v5/Px8DRkypETZWrVqlRHxAJgcLywGgAdo3ry5Pv74Y6f9R3t2drbS09OVnp6u06dPKzw8XImJiYqLizP00/19+/YpMjJSN27cUGFhocaOHavk5GTHet++feXp6al58+YZlhGVW//+/R/qurS0tF84CYDKiKIFAA9Qo0YN7d+/X8HBwUZHqXAvvfSSNm/eLD8/P/Xr108DBgxQaGio0bEcLl++XOZkMjMzU02bNi32HBcAABWFWwcBAGVyd3fXypUrFRsbW+KWLjPw8/NT165dS117+eWXKzgNAADfoWgBAMq0Zs0aoyOUKSUl5aGuGzFixC+cBACAkrh1EAAewJlvHRwwYMADr7FYLFqwYEEFpCnuYW4JtFgsOnXqVAWkAQCgOCZaAIAy5ebmlrlWVFSkDRs2qKCgwJCi9e1LbgEAMCOKFgCgTB9++GGp51evXq2xY8eqWrVqSkpKquBU37HZbEpPT9eqVat05swZWSwWBQcH63e/+5369u0ri8ViWDYAgHPjhcUAUIrz5887/jx//nz5+/sbmMY8tm/frueff169evVSbGysTp06pdGjRxuSxW63q3Pnzho4cKDOnz+v5s2b68knn9SZM2eUkJCgbt26GZILAACJogUAxeTk5Gj48OFq2LCh41yvXr0MfV+UGRw6dEidO3dW+/btFRoaqqNHj2rKlCny8fExLFN6erq2bdumjRs3au/evcrIyNDSpUu1f/9+bdiwQZs2bdLixYsNywcAcG4ULQBO5+rVq+rdu7f8/PwUEBCglJQU2Ww2JSUlKTg4WLt27dLChQuNjmkK2dnZ6t+/v8LCwuTq6qoDBw5owYIFqlu3rtHRlJGRobFjx+rFF18ssdahQweNHj1a77//vgHJAABg10EATmjo0KFau3atevToofXr1+vIkSPq2LGj8vPzNX78eEVERBgd0TQ8PDxksVg0fPhwhYeHl3ldly5dKjDVPbVr19b69esVFhZW6vrevXsVExOjnJycig0GAIAoWgCc0BNPPKEFCxYoMjJSp06dUsOGDTVixAjNnDnT6GimY7U++MYHi8WioqKiCkhTXNWqVXX27FnVqVOn1PULFy4oKChIBQUFFZwMAAB2HQTghC5cuKCmTZtKkoKDg+Xm5qaBAwcanMqcbDab0RHKVFRUJFfXsv835uLiosLCwgpMBADAdyhaAJyOzWZTlSpVHMcuLi5Ov9lFZWS325WQkKBq1aqVus4kCwBgJIoWAKdz/z/Q8/PzNWTIkBJla9WqVUbEM6Xly5crIyNDx44dk8ViUaNGjdSrVy+9+uqrhmWKj49/4DX9+vWrgCQAAJTEM1oAnE7//v0f6rq0tLRfOIn52Ww29ezZU8uXL1dISIgaN24su92uL7/8UidOnFD37t2VkZHBi4EBALgPRQsAUKYZM2Zo0qRJWrRokWJjY4utrVmzRv3799ef//xnjRw50piAAACYFEULAErx9ddfq1atWkbHMFyLFi00cuRIDRgwoNT1BQsWaObMmTp48GAFJwMAwNx4YTEAp+Ph4aHLly87jqOjo3Xx4kXH8aVLl8rcMtzZHD9+XJGRkWWuR0ZG6sSJExWYCACAyoGiBcDp5Ofn6/vD/O3bt+v27dvFrmHYf4+7u7uuXr1a5vr169fl7u5ecYEAAKgkKFoAUAo2d7inbdu2mjt3bpnrs2fPVtu2bSswEQAAlQPbuwMAyjRu3Di1b99e33zzjd58803HroNHjhzR9OnTtXr1am3evNnomAAAmA5FC4DTsVgsxSZW9x/jO+Hh4frggw80ePBgrVy5stiaj4+PMjIy9NxzzxmUDgAA82LXQQBOx2q1ytvb21Gurl69Ki8vL1mt9+6mttvtun79uoqKioyMaSp5eXnKysrS8ePHJUkhISGKioqSh4eHwckAADAnJloAnA4vIv7xPDw81K1bN6NjAABQaTDRAgCUadOmTRo2bJh27dolLy+vYmvXrl1TeHi45s2bp3bt2hmUEAAAc2LXQQD4f6dOndKhQ4dks9mMjmIaM2fO1KBBg0qULEny9vbWH/7wB82YMcOAZAAAmBtFC4DTuXPnjsaPH6/OnTtr0qRJKioqUs+ePdWoUSO1aNFCzZo105kzZ4yOaQr79+9XdHR0metRUVH6z3/+U4GJAACoHChaAJzOmDFjNHfuXPn7+2vhwoV65ZVXtHfvXi1ZskRLly6Vq6urxo0bZ3RMU7h06ZKqVKlS5rqrq6suX75cgYkAAKgc2AwDgNNZsWKF0tPT1alTJx07dkyNGzdWZmamYmJiJEm1atVS7969DU5pDo8//rgOHjyohg0blrp+4MAB1alTp4JTAQBgfky0ADidCxcu6KmnnpJ0b5vyatWqFSsSISEhysnJMSqeqXTq1ElJSUnKz88vsXb79m2NHz9esbGxBiQDAMDc2HUQgNOxWq3KyclRrVq1JEk1atTQ/v37FRwcLOne7XIBAQG8R0v3fhctW7aUi4uLhg0bptDQUFksFh05ckSzZ89WUVGR9uzZI39/f6OjAgBgKtw6CMApZWVlydvbW5Jks9m0ceNG/fe//5V07wXGuMff3187duzQa6+9pjFjxujbz+YsFos6duyoOXPmULIAACgFEy0ATsdqffBd0xaLhYnWfXJzc3XixAnZ7XY1atRIPj4+Ja45d+6cAgICHup3DADAo4yiBQAoN15eXtq3b5/jNkwAAJwVHzkCAMoNn90BAHAPz2gBcDpbt259qOteeOGFXzgJAAB4VFG0ADid9u3by2KxSCp7AsMzWgAA4OegaAFwOj4+PqpRo4YSEhLUt29f1axZ0+hIAADgEcMzWgCczsWLFzVlyhTt3LlTzZs3V2Jionbs2CEvLy95e3s7vvDjfTspBADA2VG0ADidqlWrqkePHsrKytLRo0fVokULDRs2TIGBgRo3bpwKCwuNjlhpsRkGAAD3sL07AEg6ffq0EhMTtWXLFl2+fFm+vr5GRzKNs2fP6p///Kfu3r2riIgIPfnkk2Vem52drYCAALm4uFRgQgAAzIdntAA4rYKCAq1cuVILFy7Uzp079fLLLyszM5OS9T1bt25Vp06dlJeXJ0lydXXVokWL1LNnz1KvDwwMrMh4AACYFhMtAE7n888/V1pampYuXaqgoCAlJCSoT58+FKxSREREyMvLS/Pnz5e7u7vGjBmjzMxMZWdnGx0NAABTo2gBcDpWq1X16tVTfHy8WrVqVeZ1Xbp0qcBU5uTr66utW7eqWbNmkqRbt27Jy8tL//vf/+Tj42NwOgAAzIuiBcDpWK0P3geI92jdY7ValZOTo1q1ajnO1ahRQwcOHFBQUJCByQAAMDee0QLgdGw2m9ERKpXDhw8rJyfHcWy323XkyBHduHHDca5FixZGRAMAwLSYaAEAymS1WmWxWErdtv3b80z/AAAoiYkWAKezePHiUs97e3srNDRUjRs3ruBE5nX69GmjIwAAUCkx0QLgdMraxOHmzZuy2Wzq1KmTlixZoho1alRwMgAA8Kh48BPhAPCIyc3NLfWroKBAu3bt0ldffaWJEycaHdMUjh8/rp49e+r69esl1q5du6ZevXrp1KlTBiQDAMDcKFoA8P+sVqtat26t6dOna+3atUbHMYVp06YpMDBQXl5eJda8vb0VGBioadOmGZAMAABzo2gBwH0aNmyoc+fOGR3DFLZu3aru3buXuR4XF6dNmzZVYCIAACoHihYA3OfkyZOqW7eu0TFM4ezZs8XeoXW/mjVrKjs7uwITAQBQOVC0AOD/2e127dmzR3/605/UuXNno+OYgre3t06ePFnm+okTJ0q9rRAAAGfHroMAnI6Pj48sFkuJ8zdv3lRRUZGio6P1wQcfqHr16gakM5e4uDjdvXtXH374YanrXbt2VdWqVbV8+fIKTgYAgLlRtAA4nfT09FKLlpeXlxo3bqwmTZoYkMqc9u7dq7Zt2yo2NlajRo1SaGioJOnLL7/U1KlTlZmZqR07dqhly5YGJwUAwFwoWgCAH7Ru3ToNGDBA33zzTbHzv/rVr/Tee++pS5cuBiUDAMC8KFoAnI7Vai11ovV9FotFhYWFFZTIvAYMGKC//e1vcnV11fr163XixAnZ7XaFhIQoKipKHh4eRkcEAMCUKFoAnM5HH31UZtHasWOHZs2aJbvdrtu3b1dwMvNxcXHRxYsXf3DnQQAAUBJFCwB075mjMWPGaO3aterdu7eSk5NVr149o2MZzmq1Kicnh6IFAMCPxPbuAJzahQsXNGjQILVo0UKFhYXat2+fFi1aRMn6ngfdZgkAAEpyNToAABjh2rVrmjx5smbNmqWwsDBt3LhR7dq1MzqWKYWEhDywbF25cqWC0gAAUDlQtAA4nalTp2rKlCmqXbu2MjIy1LVrV6MjmdrEiRPl7e1tdAwAACoVntEC4HSsVqvc3d0VGRkpFxeXMq9btWpVBaYyJ57RAgDgp2GiBcDp9OvXj+eOHhK/JwAAfhomWgCAMjHRAgDgp6FoAQAAAEA5Y3t3AAAAAChnFC0AAAAAKGcULQAAAAAoZxQtAAAAAChnFC0AAAAAKGcULQAATCQhIUEWi6XE14kTJ372z05PT9djjz3280MCAB6IFxYDAGAy0dHRSktLK3bOz8/PoDSlu3v3rqpUqWJ0DAAwLSZaAACYTLVq1VS7du1iXy4uLlq7dq1atWolNzc3BQcHa+LEiSosLHR834wZM9S8eXN5enoqMDBQQ4cO1c2bNyVJn376qfr3769r1645pmQTJkyQJFksFn300UfFMjz22GNKT0+XJJ05c0YWi0XLli1T+/bt5ebmpn/84x+SpLS0NDVp0kRubm5q3Lix5syZ4/gZd+7c0bBhw1SnTh25ubmpfv36+stf/vLL/eIAwESYaAEAUAlkZWWpT58+SklJUbt27XTy5EkNHjxYkjR+/HhJktVqVUpKiurXr6/Tp09r6NChGjVqlObMmaPw8HDNnDlTSUlJOnr0qCSpevXqPyrDW2+9penTpystLU3VqlVTamqqxo8fr3fffVe//vWvtXfvXg0aNEienp6Kj49XSkqK1qxZo2XLlqlevXrKzs5WdnZ2+f5iAMCkKFoAAJjMunXripWgmJgYXbp0SaNHj1Z8fLwkKTg4WMnJyRo1apSjaI0cOdLxPUFBQUpOTtZrr72mOXPmqGrVqvL29pbFYlHt2rV/Uq6RI0fqlVdecRwnJydr+vTpjnNBQUE6fPiw5s+fr/j4eH311Vdq1KiRnn/+eVksFj3xxBM/6e8FgMqIogUAgMm8+OKLmjt3ruPY09NTDRs21O7duzVp0iTH+aKiIuXn5ysvL08eHh7avHmzJk+erMOHD+v69esqLCxUfn6+bt26JU9Pz5+d6+mnn3b8+fLly8rOzlZiYqIGDRrkOF9YWChvb29J9zb2eOmllxQaGqro6GjFxsYqKirqZ+cAgMqAogUAgMl8W6y+z2azaeLEicUmSt9yc3PT2bNn1alTJw0ZMkTJycny9fXVZ599psTERN29e/cH/z6LxSK73V7sXGnf8/2yZrPZJEmpqal69tlni13n4uIiSWrZsqVOnz6tTz75RBs2bFBcXJwiIyO1YsWKH8wDAI8CihYAAJVAy5YtdfTo0RIF7FtffPGFCgsLNX36dFmt9/a6WrZsWbFrqlatqqKiohLf6+fnp4sXLzqOjx8/rry8vB/M4+/vr8cff1ynTp1S7969y7zOy8tLPXr0UI8ePfTqq68qOjpaV65cka+v7w/+fACo7ChaAABUAklJSYqNjVVgYKC6d+8uq9WqAwcO6ODBg3r77bfVoEEDFRYWatasWercubO2b9+uefPmFfsZ9evX182bN7Vx40Y99dRT8vDwkIeHhzp06KB3331Xbdq0kc1m01tvvfVQW7dPmDBBI0aMkJeXl2JiYlRQUKAvvvhCubm5euONN/TXv/5VderUUVhYmKxWq5YvX67atWvzLi8AToHt3QEAqAQ6duyodevW6V//+pdat26tNm3aaMaMGY4NJsLCwjRjxgxNmTJFzZo10/vvv19iK/Xw8HANGTJEPXr0kJ+fn6ZOnSpJmj59ugIDA/XCCy+oV69eevPNN+Xh4fHATAMHDtR7772n9PR0NW/eXBEREUpPT1dQUJCke7saTpkyRU8//bRat26tM2fO6OOPP3ZM3ADgUWax339TNgAAAADgZ+EjJQAAAAAoZxQtAAAAAChnFC0AAAAAKGcULQAAAAAoZxQtAAAAAChnFC0AAAAAKGcULQAAAAAoZxQtAAAAAChnFC0AAAAAKGcULQAAAAAoZxQtAAAAAChn/wd9s9bUOdCZmAAAAABJRU5ErkJggg==",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "columns_to_correlate = ['URL_LENGTH', 'NUMBER_SPECIAL_CHARACTERS', 'CONTENT_LENGTH', 'TCP_CONVERSATION_EXCHANGE', 'DIST_REMOTE_TCP_PORT', 'REMOTE_IPS', 'APP_BYTES', 'SOURCE_APP_PACKETS', 'REMOTE_APP_PACKETS', 'SOURCE_APP_BYTES', 'REMOTE_APP_BYTES', 'APP_PACKETS', 'DNS_QUERY_TIMES']\n",
+    "subset_websites = websites[columns_to_correlate]\n",
+    "\n",
+    "correlation_matrix = subset_websites.corr()\n",
+    "\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', annot_kws={\"size\": 12})\n",
+    "plt.title('Correlation Matrix Heatmap')\n",
+    "plt.xlabel('Features')\n",
+    "plt.ylabel('Features')\n",
+    "plt.show()\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
-   "source": [
-    "# Your comment here"
-   ]
+   "source": []
   },
   {
    "cell_type": "markdown",
@@ -133,29 +462,403 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL</th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>CONTENT_LENGTH</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>WHOIS_STATEPRO</th>\n",
+       "      <th>WHOIS_REGDATE</th>\n",
+       "      <th>WHOIS_UPDATED_DATE</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>263.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>15087.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>324.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>162.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>AK</td>\n",
+       "      <td>7/10/1997 4:00</td>\n",
+       "      <td>12/09/2013 0:45</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>None</td>\n",
+       "      <td>124140.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>12/05/1996 0:00</td>\n",
+       "      <td>11/04/2017 0:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache/2.2.16 (Debian)</td>\n",
+       "      <td>8904.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>FL</td>\n",
+       "      <td>15/02/1999 0:00</td>\n",
+       "      <td>15/07/2015 0:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>cloudflare-nginx</td>\n",
+       "      <td>NaN</td>\n",
+       "      <td>US</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1/04/1998 0:00</td>\n",
+       "      <td>9/12/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft-IIS/8.5</td>\n",
+       "      <td>24435.0</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Wisconsin</td>\n",
+       "      <td>14/11/2008 0:00</td>\n",
+       "      <td>20/11/2013 0:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 18 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "0      M0_109          16                          7  iso-8859-1   \n",
+       "1     B0_2314          16                          6       UTF-8   \n",
+       "2      B0_911          16                          6    us-ascii   \n",
+       "3      B0_113          17                          6  ISO-8859-1   \n",
+       "4      B0_403          17                          6       UTF-8   \n",
+       "...       ...         ...                        ...         ...   \n",
+       "1776    M4_48         194                         16       UTF-8   \n",
+       "1777    M4_41         198                         17       UTF-8   \n",
+       "1778   B0_162         201                         34       utf-8   \n",
+       "1779  B0_1152         234                         34  ISO-8859-1   \n",
+       "1780   B0_676         249                         40       utf-8   \n",
+       "\n",
+       "                      SERVER  CONTENT_LENGTH WHOIS_COUNTRY WHOIS_STATEPRO  \\\n",
+       "0                      nginx           263.0          None           None   \n",
+       "1              Apache/2.4.10         15087.0          None           None   \n",
+       "2      Microsoft-HTTPAPI/2.0           324.0          None           None   \n",
+       "3                      nginx           162.0            US             AK   \n",
+       "4                       None        124140.0            US             TX   \n",
+       "...                      ...             ...           ...            ...   \n",
+       "1776                  Apache             NaN            ES      Barcelona   \n",
+       "1777                  Apache             NaN            ES      Barcelona   \n",
+       "1778  Apache/2.2.16 (Debian)          8904.0            US             FL   \n",
+       "1779        cloudflare-nginx             NaN            US             CA   \n",
+       "1780       Microsoft-IIS/8.5         24435.0            US      Wisconsin   \n",
+       "\n",
+       "         WHOIS_REGDATE WHOIS_UPDATED_DATE  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0     10/10/2015 18:21               None                     0           2   \n",
+       "1                 None               None                     7           4   \n",
+       "2                 None               None                     0           0   \n",
+       "3       7/10/1997 4:00    12/09/2013 0:45                    22           3   \n",
+       "4      12/05/1996 0:00    11/04/2017 0:00                     2           5   \n",
+       "...                ...                ...                   ...         ...   \n",
+       "1776   17/09/2008 0:00     2/09/2016 0:00                     0           0   \n",
+       "1777   17/09/2008 0:00     2/09/2016 0:00                     0           0   \n",
+       "1778   15/02/1999 0:00    15/07/2015 0:00                     2           6   \n",
+       "1779    1/04/1998 0:00     9/12/2016 0:00                     0           0   \n",
+       "1780   14/11/2008 0:00    20/11/2013 0:00                     6          11   \n",
+       "\n",
+       "      REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "0                     10              1153               832            9   \n",
+       "1                     19              1265              1230           17   \n",
+       "2                      0                 0                 0            0   \n",
+       "3                     37             18784              4380           39   \n",
+       "4                     62            129889              4586           61   \n",
+       "...                  ...               ...               ...          ...   \n",
+       "1776                   3               186                 0            0   \n",
+       "1777                   2               124                 0            0   \n",
+       "1778                  89            132181              6945           87   \n",
+       "1779                   0                 0                 0            0   \n",
+       "1780                  28              3039              2776           25   \n",
+       "\n",
+       "      DNS_QUERY_TIMES  Type  \n",
+       "0                 2.0     1  \n",
+       "1                 0.0     0  \n",
+       "2                 0.0     0  \n",
+       "3                 8.0     0  \n",
+       "4                 4.0     0  \n",
+       "...               ...   ...  \n",
+       "1776              0.0     1  \n",
+       "1777              0.0     1  \n",
+       "1778              4.0     0  \n",
+       "1779              0.0     0  \n",
+       "1780              6.0     0  \n",
+       "\n",
+       "[1781 rows x 18 columns]"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites = websites.drop(['SOURCE_APP_PACKETS', 'APP_BYTES','TCP_CONVERSATION_EXCHANGE' ], axis=1)\n",
+    "websites"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your comment here"
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 800x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "columns_to_correlate = ['URL_LENGTH', 'NUMBER_SPECIAL_CHARACTERS', 'CONTENT_LENGTH', 'DIST_REMOTE_TCP_PORT', 'REMOTE_IPS', 'REMOTE_APP_PACKETS', 'SOURCE_APP_BYTES', 'REMOTE_APP_BYTES', 'APP_PACKETS', 'DNS_QUERY_TIMES']\n",
+    "subset_websites = websites[columns_to_correlate]\n",
+    "\n",
+    "correlation_matrix = subset_websites.corr()\n",
+    "\n",
+    "plt.figure(figsize=(8, 6))\n",
+    "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt='.2f', annot_kws={\"size\": 12})\n",
+    "plt.title('Correlation Matrix Heatmap')\n",
+    "plt.xlabel('Features')\n",
+    "plt.ylabel('Features')\n",
+    "plt.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Print heatmap again\n"
+    "# I removed 'TCP_CONVERSATION_EXCHANGE', 'APP_BYTES' and 'SOURCE_APP_PACKETS'"
    ]
   },
   {
@@ -169,11 +872,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                            0\n",
+       "URL_LENGTH                     0\n",
+       "NUMBER_SPECIAL_CHARACTERS      0\n",
+       "CHARSET                        0\n",
+       "SERVER                         1\n",
+       "CONTENT_LENGTH               812\n",
+       "WHOIS_COUNTRY                  0\n",
+       "WHOIS_STATEPRO                 0\n",
+       "WHOIS_REGDATE                  0\n",
+       "WHOIS_UPDATED_DATE             0\n",
+       "DIST_REMOTE_TCP_PORT           0\n",
+       "REMOTE_IPS                     0\n",
+       "REMOTE_APP_PACKETS             0\n",
+       "SOURCE_APP_BYTES               0\n",
+       "REMOTE_APP_BYTES               0\n",
+       "APP_PACKETS                    0\n",
+       "DNS_QUERY_TIMES                1\n",
+       "Type                           0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum()\n"
    ]
   },
   {
@@ -187,20 +919,385 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL</th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>WHOIS_STATEPRO</th>\n",
+       "      <th>WHOIS_REGDATE</th>\n",
+       "      <th>WHOIS_UPDATED_DATE</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>10/10/2015 18:21</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>AK</td>\n",
+       "      <td>7/10/1997 4:00</td>\n",
+       "      <td>12/09/2013 0:45</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>None</td>\n",
+       "      <td>US</td>\n",
+       "      <td>TX</td>\n",
+       "      <td>12/05/1996 0:00</td>\n",
+       "      <td>11/04/2017 0:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</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",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>Barcelona</td>\n",
+       "      <td>17/09/2008 0:00</td>\n",
+       "      <td>2/09/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache/2.2.16 (Debian)</td>\n",
+       "      <td>US</td>\n",
+       "      <td>FL</td>\n",
+       "      <td>15/02/1999 0:00</td>\n",
+       "      <td>15/07/2015 0:00</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>cloudflare-nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>CA</td>\n",
+       "      <td>1/04/1998 0:00</td>\n",
+       "      <td>9/12/2016 0:00</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft-IIS/8.5</td>\n",
+       "      <td>US</td>\n",
+       "      <td>Wisconsin</td>\n",
+       "      <td>14/11/2008 0:00</td>\n",
+       "      <td>20/11/2013 0:00</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1781 rows × 17 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "0      M0_109          16                          7  iso-8859-1   \n",
+       "1     B0_2314          16                          6       UTF-8   \n",
+       "2      B0_911          16                          6    us-ascii   \n",
+       "3      B0_113          17                          6  ISO-8859-1   \n",
+       "4      B0_403          17                          6       UTF-8   \n",
+       "...       ...         ...                        ...         ...   \n",
+       "1776    M4_48         194                         16       UTF-8   \n",
+       "1777    M4_41         198                         17       UTF-8   \n",
+       "1778   B0_162         201                         34       utf-8   \n",
+       "1779  B0_1152         234                         34  ISO-8859-1   \n",
+       "1780   B0_676         249                         40       utf-8   \n",
+       "\n",
+       "                      SERVER WHOIS_COUNTRY WHOIS_STATEPRO     WHOIS_REGDATE  \\\n",
+       "0                      nginx          None           None  10/10/2015 18:21   \n",
+       "1              Apache/2.4.10          None           None              None   \n",
+       "2      Microsoft-HTTPAPI/2.0          None           None              None   \n",
+       "3                      nginx            US             AK    7/10/1997 4:00   \n",
+       "4                       None            US             TX   12/05/1996 0:00   \n",
+       "...                      ...           ...            ...               ...   \n",
+       "1776                  Apache            ES      Barcelona   17/09/2008 0:00   \n",
+       "1777                  Apache            ES      Barcelona   17/09/2008 0:00   \n",
+       "1778  Apache/2.2.16 (Debian)            US             FL   15/02/1999 0:00   \n",
+       "1779        cloudflare-nginx            US             CA    1/04/1998 0:00   \n",
+       "1780       Microsoft-IIS/8.5            US      Wisconsin   14/11/2008 0:00   \n",
+       "\n",
+       "     WHOIS_UPDATED_DATE  DIST_REMOTE_TCP_PORT  REMOTE_IPS  REMOTE_APP_PACKETS  \\\n",
+       "0                  None                     0           2                  10   \n",
+       "1                  None                     7           4                  19   \n",
+       "2                  None                     0           0                   0   \n",
+       "3       12/09/2013 0:45                    22           3                  37   \n",
+       "4       11/04/2017 0:00                     2           5                  62   \n",
+       "...                 ...                   ...         ...                 ...   \n",
+       "1776     2/09/2016 0:00                     0           0                   3   \n",
+       "1777     2/09/2016 0:00                     0           0                   2   \n",
+       "1778    15/07/2015 0:00                     2           6                  89   \n",
+       "1779     9/12/2016 0:00                     0           0                   0   \n",
+       "1780    20/11/2013 0:00                     6          11                  28   \n",
+       "\n",
+       "      SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  DNS_QUERY_TIMES  Type  \n",
+       "0                 1153               832            9              2.0     1  \n",
+       "1                 1265              1230           17              0.0     0  \n",
+       "2                    0                 0            0              0.0     0  \n",
+       "3                18784              4380           39              8.0     0  \n",
+       "4               129889              4586           61              4.0     0  \n",
+       "...                ...               ...          ...              ...   ...  \n",
+       "1776               186                 0            0              0.0     1  \n",
+       "1777               124                 0            0              0.0     1  \n",
+       "1778            132181              6945           87              4.0     0  \n",
+       "1779                 0                 0            0              0.0     0  \n",
+       "1780              3039              2776           25              6.0     0  \n",
+       "\n",
+       "[1781 rows x 17 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites = websites.drop('CONTENT_LENGTH', axis=1)\n",
+    "websites\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                          0\n",
+       "URL_LENGTH                   0\n",
+       "NUMBER_SPECIAL_CHARACTERS    0\n",
+       "CHARSET                      0\n",
+       "SERVER                       1\n",
+       "WHOIS_COUNTRY                0\n",
+       "WHOIS_STATEPRO               0\n",
+       "WHOIS_REGDATE                0\n",
+       "WHOIS_UPDATED_DATE           0\n",
+       "DIST_REMOTE_TCP_PORT         0\n",
+       "REMOTE_IPS                   0\n",
+       "REMOTE_APP_PACKETS           0\n",
+       "SOURCE_APP_BYTES             0\n",
+       "REMOTE_APP_BYTES             0\n",
+       "APP_PACKETS                  0\n",
+       "DNS_QUERY_TIMES              1\n",
+       "Type                         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your comment here"
+    "websites.dropna(inplace=True)"
    ]
   },
   {
@@ -214,11 +1311,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Examine missing values in each column\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                          0\n",
+       "URL_LENGTH                   0\n",
+       "NUMBER_SPECIAL_CHARACTERS    0\n",
+       "CHARSET                      0\n",
+       "SERVER                       0\n",
+       "WHOIS_COUNTRY                0\n",
+       "WHOIS_STATEPRO               0\n",
+       "WHOIS_REGDATE                0\n",
+       "WHOIS_UPDATED_DATE           0\n",
+       "DIST_REMOTE_TCP_PORT         0\n",
+       "REMOTE_IPS                   0\n",
+       "REMOTE_APP_PACKETS           0\n",
+       "SOURCE_APP_BYTES             0\n",
+       "REMOTE_APP_BYTES             0\n",
+       "APP_PACKETS                  0\n",
+       "DNS_QUERY_TIMES              0\n",
+       "Type                         0\n",
+       "dtype: int64"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.isna().sum()\n"
    ]
   },
   {
@@ -256,11 +1381,62 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['None', 'US', 'SC', 'GB', 'UK', 'RU', 'AU', 'CA', 'PA', 'se', 'IN',\n",
+       "       'LU', 'TH', \"[u'GB'; u'UK']\", 'FR', 'NL', 'UG', 'JP', 'CN', 'SE',\n",
+       "       'SI', 'IL', 'ru', 'KY', 'AT', 'CZ', 'PH', 'BE', 'NO', 'TR', 'LV',\n",
+       "       'DE', 'ES', 'BR', 'us', 'KR', 'HK', 'UA', 'CH', 'United Kingdom',\n",
+       "       'BS', 'PK', 'IT', 'Cyprus', 'BY', 'AE', 'IE', 'UY', 'KG'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 16,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "websites['WHOIS_COUNTRY'].unique()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['None', 'US', 'SC', 'UK', 'RU', 'AU', 'CA', 'PA', 'SE', 'IN', 'LU',\n",
+       "       'TH', 'FR', 'NL', 'UG', 'JP', 'CN', 'SI', 'IL', 'KY', 'AT', 'CZ',\n",
+       "       'PH', 'BE', 'NO', 'TR', 'LV', 'DE', 'ES', 'BR', 'KR', 'HK', 'UA',\n",
+       "       'CH', 'BS', 'PK', 'IT', 'CY', 'BY', 'AE', 'IE', 'UY', 'KG'],\n",
+       "      dtype=object)"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "country_mapping = {\n",
+    "    'Cyprus': 'CY',\n",
+    "    'us': 'US',\n",
+    "    'United Kingdom': 'UK',\n",
+    "    'GB': 'UK',\n",
+    "    \"[u'GB'; u'UK']\": 'UK',\n",
+    "    'se': 'SE',\n",
+    "    'ru': 'RU'}\n",
+    "\n",
+    "websites['WHOIS_COUNTRY'] = websites['WHOIS_COUNTRY'].replace(country_mapping)\n",
+    "\n",
+    "websites['WHOIS_COUNTRY'].unique()"
    ]
   },
   {
@@ -278,11 +1454,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 18,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "websites[\"WHOIS_COUNTRY\"].value_counts().plot(kind='bar')\n"
    ]
   },
   {
@@ -294,13 +1491,57 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 19,
    "metadata": {
     "scrolled": true
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['US', 'None', 'CA', 'ES', 'UK', 'AU', 'PA', 'JP', 'CN', 'IN']"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here\n"
+    "top_countries = websites['WHOIS_COUNTRY'].value_counts().head(10).index.tolist()\n",
+    "top_countries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: >"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "websites['WHOIS_COUNTRY'] = websites['WHOIS_COUNTRY'].apply(lambda x: x if x in top_countries else 'OTHER')\n",
+    "\n",
+    "websites[\"WHOIS_COUNTRY\"].value_counts().plot(kind='bar')"
    ]
   },
   {
@@ -316,11 +1557,303 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL</th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>M0_109</td>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>9</td>\n",
+       "      <td>2.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>B0_2314</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache/2.4.10</td>\n",
+       "      <td>None</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>B0_911</td>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft-HTTPAPI/2.0</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>B0_113</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>B0_403</td>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>None</td>\n",
+       "      <td>US</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</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",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>M4_48</td>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>M4_41</td>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>B0_162</td>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache/2.2.16 (Debian)</td>\n",
+       "      <td>US</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>87</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>B0_1152</td>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>cloudflare-nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>B0_676</td>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft-IIS/8.5</td>\n",
+       "      <td>US</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1779 rows × 14 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          URL  URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET  \\\n",
+       "0      M0_109          16                          7  iso-8859-1   \n",
+       "1     B0_2314          16                          6       UTF-8   \n",
+       "2      B0_911          16                          6    us-ascii   \n",
+       "3      B0_113          17                          6  ISO-8859-1   \n",
+       "4      B0_403          17                          6       UTF-8   \n",
+       "...       ...         ...                        ...         ...   \n",
+       "1776    M4_48         194                         16       UTF-8   \n",
+       "1777    M4_41         198                         17       UTF-8   \n",
+       "1778   B0_162         201                         34       utf-8   \n",
+       "1779  B0_1152         234                         34  ISO-8859-1   \n",
+       "1780   B0_676         249                         40       utf-8   \n",
+       "\n",
+       "                      SERVER WHOIS_COUNTRY  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0                      nginx          None                     0           2   \n",
+       "1              Apache/2.4.10          None                     7           4   \n",
+       "2      Microsoft-HTTPAPI/2.0          None                     0           0   \n",
+       "3                      nginx            US                    22           3   \n",
+       "4                       None            US                     2           5   \n",
+       "...                      ...           ...                   ...         ...   \n",
+       "1776                  Apache            ES                     0           0   \n",
+       "1777                  Apache            ES                     0           0   \n",
+       "1778  Apache/2.2.16 (Debian)            US                     2           6   \n",
+       "1779        cloudflare-nginx            US                     0           0   \n",
+       "1780       Microsoft-IIS/8.5            US                     6          11   \n",
+       "\n",
+       "      REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "0                     10              1153               832            9   \n",
+       "1                     19              1265              1230           17   \n",
+       "2                      0                 0                 0            0   \n",
+       "3                     37             18784              4380           39   \n",
+       "4                     62            129889              4586           61   \n",
+       "...                  ...               ...               ...          ...   \n",
+       "1776                   3               186                 0            0   \n",
+       "1777                   2               124                 0            0   \n",
+       "1778                  89            132181              6945           87   \n",
+       "1779                   0                 0                 0            0   \n",
+       "1780                  28              3039              2776           25   \n",
+       "\n",
+       "      DNS_QUERY_TIMES  Type  \n",
+       "0                 2.0     1  \n",
+       "1                 0.0     0  \n",
+       "2                 0.0     0  \n",
+       "3                 8.0     0  \n",
+       "4                 4.0     0  \n",
+       "...               ...   ...  \n",
+       "1776              0.0     1  \n",
+       "1777              0.0     1  \n",
+       "1778              4.0     0  \n",
+       "1779              0.0     0  \n",
+       "1780              6.0     0  \n",
+       "\n",
+       "[1779 rows x 14 columns]"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites = websites.drop(['WHOIS_STATEPRO', 'WHOIS_REGDATE', 'WHOIS_UPDATED_DATE'], axis=1)\n",
+    "websites\n"
    ]
   },
   {
@@ -334,11 +1867,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL                           object\n",
+       "URL_LENGTH                     int64\n",
+       "NUMBER_SPECIAL_CHARACTERS      int64\n",
+       "CHARSET                       object\n",
+       "SERVER                        object\n",
+       "WHOIS_COUNTRY                 object\n",
+       "DIST_REMOTE_TCP_PORT           int64\n",
+       "REMOTE_IPS                     int64\n",
+       "REMOTE_APP_PACKETS             int64\n",
+       "SOURCE_APP_BYTES               int64\n",
+       "REMOTE_APP_BYTES               int64\n",
+       "APP_PACKETS                    int64\n",
+       "DNS_QUERY_TIMES              float64\n",
+       "Type                           int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 22,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.dtypes\n"
    ]
   },
   {
@@ -350,11 +1908,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "websites = websites.drop('URL', axis=1)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "URL_LENGTH                     int64\n",
+       "NUMBER_SPECIAL_CHARACTERS      int64\n",
+       "CHARSET                       object\n",
+       "SERVER                        object\n",
+       "WHOIS_COUNTRY                 object\n",
+       "DIST_REMOTE_TCP_PORT           int64\n",
+       "REMOTE_IPS                     int64\n",
+       "REMOTE_APP_PACKETS             int64\n",
+       "SOURCE_APP_BYTES               int64\n",
+       "REMOTE_APP_BYTES               int64\n",
+       "APP_PACKETS                    int64\n",
+       "DNS_QUERY_TIMES              float64\n",
+       "Type                           int64\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites.dtypes"
    ]
   },
   {
@@ -366,11 +1958,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 25,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['iso-8859-1', 'UTF-8', 'us-ascii', 'ISO-8859-1', 'utf-8', 'None',\n",
+       "       'windows-1251', 'ISO-8859', 'windows-1252'], dtype=object)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here"
+    "websites['CHARSET'].unique()"
    ]
   },
   {
@@ -384,11 +1988,151 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 26,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['nginx', 'Apache/2.4.10', 'Microsoft-HTTPAPI/2.0', 'None',\n",
+       "       'Apache/2', 'nginx/1.10.1', 'Apache', 'Apache/2.2.15 (Red Hat)',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'openresty/1.11.2.1', 'Apache/2.2.22', 'Apache/2.4.7 (Ubuntu)',\n",
+       "       'nginx/1.12.0',\n",
+       "       'Apache/2.4.12 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'Oracle-iPlanet-Web-Server/7.0', 'cloudflare-nginx', 'nginx/1.6.2',\n",
+       "       'openresty', 'Heptu web server', 'Pepyaka/1.11.3', 'nginx/1.8.0',\n",
+       "       'nginx/1.10.1 + Phusion Passenger 5.0.30',\n",
+       "       'Apache/2.2.29 (Amazon)', 'Microsoft-IIS/7.5', 'LiteSpeed',\n",
+       "       'Apache/2.4.25 (cPanel) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'tsa_c', 'Apache/2.2.0 (Fedora)', 'Apache/2.2.22 (Debian)',\n",
+       "       'Apache/2.2.15 (CentOS)', 'Apache/2.4.25',\n",
+       "       'Apache/2.4.25 (Amazon) PHP/7.0.14', 'GSE',\n",
+       "       'Apache/2.4.23 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.25 (Amazon) OpenSSL/1.0.1k-fips',\n",
+       "       'Apache/2.2.22 (Ubuntu)', 'Tengine',\n",
+       "       'Apache/2.4.18 (Unix) OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.10 (Debian)', 'Apache/2.4.6 (CentOS) PHP/5.6.8',\n",
+       "       'Sun-ONE-Web-Server/6.1',\n",
+       "       'Apache/2.4.18 (Unix) OpenSSL/1.0.2e Communique/4.1.10',\n",
+       "       'AmazonS3',\n",
+       "       'Apache/1.3.37 (Unix) mod_perl/1.29 mod_ssl/2.8.28 OpenSSL/0.9.7e-p1',\n",
+       "       'ATS', 'Apache/2.2.27 (CentOS)',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips DAV/2 mod_bwlimited/1.4',\n",
+       "       'CherryPy/3.6.0', 'Server', 'KHL',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 PHP/5.4.16 mod_jk/1.2.40',\n",
+       "       'Apache/2.2.3 (CentOS)', 'Apache/2.4',\n",
+       "       'Apache/1.3.27 (Unix)  (Red-Hat/Linux) mod_perl/1.26 PHP/4.3.3 FrontPage/5.0.2 mod_ssl/2.8.12 OpenSSL/0.9.6b',\n",
+       "       'mw2114.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 mod_perl/2.0.8 Perl/v5.10.1',\n",
+       "       'Apache/1.3.34 (Unix) PHP/4.4.4', 'Apache/2.2.31 (Amazon)',\n",
+       "       'Jetty(9.0.z-SNAPSHOT)', 'Apache/2.2.31 (CentOS)',\n",
+       "       'Apache/2.4.12 (Ubuntu)', 'HTTPDaemon',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'MediaFire', 'DOSarrest', 'mw2232.codfw.wmnet',\n",
+       "       'Sucuri/Cloudproxy', 'Apache/2.4.23 (Unix)', 'nginx/0.7.65',\n",
+       "       'mw2260.codfw.wmnet', 'Apache/2.2.32', 'mw2239.codfw.wmnet',\n",
+       "       'DPS/1.1.8', 'Apache/2.0.52 (Red Hat)',\n",
+       "       'Apache/2.2.25 (Unix) mod_ssl/2.2.25 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/1.3.31 (Unix) PHP/4.3.9 mod_perl/1.29 rus/PL30.20',\n",
+       "       'Apache/2.2.13 (Unix) mod_ssl/2.2.13 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.2.10',\n",
+       "       'nginx/1.1.19', 'ATS/5.3.0', 'Apache/2.2.3 (Red Hat)',\n",
+       "       'nginx/1.4.3',\n",
+       "       'Apache/2.2.29 (Unix) mod_ssl/2.2.29 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 PHP/5.4.35',\n",
+       "       'Apache/2.2.14 (FreeBSD) mod_ssl/2.2.14 OpenSSL/0.9.8y DAV/2 PHP/5.2.12 with Suhosin-Patch',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8e-fips-rhel5',\n",
+       "       'Apache/1.3.39 (Unix) PHP/5.2.5 mod_auth_passthrough/1.8 mod_bwlimited/1.4 mod_log_bytes/1.2 mod_gzip/1.3.26.1a FrontPage/5.0.2.2635 DAV/1.0.3 mod_ssl/2.8.30 OpenSSL/0.9.7a',\n",
+       "       'SSWS', 'Microsoft-IIS/8.0', 'Apache/2.4.18 (Ubuntu)',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16 mod_apreq2-20090110/2.8.0 mod_perl/2.0.10 Perl/v5.24.1',\n",
+       "       'Apache/2.2.20 (Unix)', 'YouTubeFrontEnd', 'nginx/1.11.3',\n",
+       "       'nginx/1.11.2', 'nginx/1.10.0 (Ubuntu)', 'nginx/1.8.1',\n",
+       "       'nginx/1.11.10', 'Squeegit/1.2.5 (3_sir)',\n",
+       "       'Virtuoso/07.20.3217 (Linux) i686-generic-linux-glibc212-64  VDB',\n",
+       "       'Apache-Coyote/1.1', 'Yippee-Ki-Yay', 'mw2165.codfw.wmnet',\n",
+       "       'mw2192.codfw.wmnet', 'Apache/2.2.23 (Amazon)',\n",
+       "       'nginx/1.4.6 (Ubuntu)', 'nginx + Phusion Passenger',\n",
+       "       'Proxy Pandeiro UOL', 'mw2231.codfw.wmnet', 'openresty/1.11.2.2',\n",
+       "       'mw2109.codfw.wmnet', 'nginx/0.8.54', 'Apache/2.4.6',\n",
+       "       'mw2225.codfw.wmnet', 'Apache/1.3.27 (Unix) PHP/4.4.1',\n",
+       "       'mw2236.codfw.wmnet', 'mw2101.codfw.wmnet', 'Varnish',\n",
+       "       'Resin/3.1.8', 'mw2164.codfw.wmnet', 'Microsoft-IIS/8.5',\n",
+       "       'mw2242.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.5.38',\n",
+       "       'mw2175.codfw.wmnet', 'mw2107.codfw.wmnet', 'mw2190.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS)', 'nginx/1.13.0', 'barista/5.1.3',\n",
+       "       'mw2103.codfw.wmnet', 'Apache/2.4.25 (Debian)', 'ECD (fll/0790)',\n",
+       "       'Pagely Gateway/1.5.1', 'nginx/1.10.3',\n",
+       "       'Apache/2.4.25 (FreeBSD) OpenSSL/1.0.1s-freebsd PHP/5.6.30',\n",
+       "       'mw2097.codfw.wmnet', 'mw2233.codfw.wmnet', 'fbs',\n",
+       "       'mw2199.codfw.wmnet', 'mw2255.codfw.wmnet', 'mw2228.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4 mod_fcgid/2.3.9',\n",
+       "       'gunicorn/19.7.1',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/5.4.16',\n",
+       "       'mw2241.codfw.wmnet',\n",
+       "       'Apache/1.3.33 (Unix) mod_ssl/2.8.24 OpenSSL/0.9.7e-p1 PHP/4.4.8',\n",
+       "       'lighttpd', 'mw2230.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips', 'AkamaiGHost',\n",
+       "       'mw2240.codfw.wmnet', 'nginx/1.10.2', 'PWS/8.2.0.7', 'nginx/1.2.1',\n",
+       "       'nxfps',\n",
+       "       'Apache/2.2.16 (Unix) mod_ssl/2.2.16 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4',\n",
+       "       'Play', 'mw2185.codfw.wmnet',\n",
+       "       'Apache/2.4.10 (Unix) OpenSSL/1.0.1k',\n",
+       "       'Apache/Not telling (Unix) AuthTDS/1.1',\n",
+       "       'Apache/2.2.11 (Unix) PHP/5.2.6', 'Scratch Web Server',\n",
+       "       'marrakesh 1.12.2', 'nginx/0.8.35', 'mw2182.codfw.wmnet',\n",
+       "       'squid/3.3.8', 'nginx/1.10.0', 'Nginx (OpenBSD)',\n",
+       "       'Zope/(2.13.16; python 2.6.8; linux2) ZServer/1.1',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/0.9.8e-fips-rhel5 mod_bwlimited/1.4 PHP/5.4.26',\n",
+       "       'Apache/2.2.21 (Unix) mod_ssl/2.2.21 OpenSSL/0.9.8e-fips-rhel5 PHP/5.3.10',\n",
+       "       'Apache/2.2.27 (Unix) OpenAM Web Agent/4.0.1-1 mod_ssl/2.2.27 OpenSSL/1.0.1p PHP/5.3.28',\n",
+       "       'mw2104.codfw.wmnet', '.V01 Apache', 'mw2110.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37 PHP/5.5.1 OpenSSL/1.0.1g mod_fcgid/2.3.9',\n",
+       "       'mw2176.codfw.wmnet', 'mw2187.codfw.wmnet', 'mw2106.codfw.wmnet',\n",
+       "       'Microsoft-IIS/7.0',\n",
+       "       'Apache/1.3.42 Ben-SSL/1.60 (Unix) mod_gzip/1.3.26.1a mod_fastcgi/2.4.6 mod_throttle/3.1.2 Chili!Soft-ASP/3.6.2 FrontPage/5.0.2.2635 mod_perl/1.31 PHP/4.4.9',\n",
+       "       'Aeria Games & Entertainment', 'nginx/1.6.3 + Phusion Passenger',\n",
+       "       'Apache/2.4.10 (Debian) PHP/5.6.30-0+deb8u1 mod_perl/2.0.9dev Perl/v5.20.2',\n",
+       "       'mw2173.codfw.wmnet',\n",
+       "       'Apache/2.4.6 (Red Hat Enterprise Linux) OpenSSL/1.0.1e-fips mod_fcgid/2.3.9 Communique/4.2.0',\n",
+       "       'Apache/2.2.15 (CentOS) DAV/2 mod_ssl/2.2.15 OpenSSL/1.0.1e-fips PHP/5.3.3',\n",
+       "       'Apache/2.4.6 (CentOS) OpenSSL/1.0.1e-fips PHP/7.0.14',\n",
+       "       'mw2198.codfw.wmnet', 'mw2172.codfw.wmnet', 'nginx/1.2.6',\n",
+       "       'Apache/2.4.6 (Unix) mod_jk/1.2.37',\n",
+       "       'Apache/2.4.25 (Unix) OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'nginx/1.4.4', 'Cowboy', 'mw2113.codfw.wmnet',\n",
+       "       'Apache/2.2.14 (Unix) mod_ssl/2.2.14 OpenSSL/0.9.8a',\n",
+       "       'Apache/2.4.10 (Ubuntu)', 'mw2224.codfw.wmnet',\n",
+       "       'mw2171.codfw.wmnet', 'mw2257.codfw.wmnet', 'mw2226.codfw.wmnet',\n",
+       "       'DMS/1.0.42', 'nginx/1.6.3', 'Application-Server',\n",
+       "       'Apache/2.4.6 (CentOS) mod_fcgid/2.3.9 PHP/5.6.30',\n",
+       "       'mw2177.codfw.wmnet', 'lighttpd/1.4.28', 'mw2197.codfw.wmnet',\n",
+       "       'Apache/2.2.31 (FreeBSD) PHP/5.4.15 mod_ssl/2.2.31 OpenSSL/1.0.2d DAV/2',\n",
+       "       'Apache/2.2.26 (Unix) mod_ssl/2.2.26 OpenSSL/1.0.1e-fips DAV/2 mod_bwlimited/1.4',\n",
+       "       'Apache/2.2.24 (Unix) DAV/2 PHP/5.3.26 mod_ssl/2.2.24 OpenSSL/0.9.8y',\n",
+       "       'mw2178.codfw.wmnet', '294', 'Microsoft-IIS/6.0', 'nginx/1.7.4',\n",
+       "       'Apache/2.2.22 (Debian) mod_python/3.3.1 Python/2.7.3 mod_ssl/2.2.22 OpenSSL/1.0.1t',\n",
+       "       'Apache/2.4.16 (Ubuntu)', 'www.lexisnexis.com  9999',\n",
+       "       'nginx/0.8.38', 'mw2238.codfw.wmnet', 'Pizza/pepperoni',\n",
+       "       'XXXXXXXXXXXXXXXXXXXXXX', 'MI', 'Roxen/5.4.98-r2',\n",
+       "       'Apache/2.2.31 (Unix) mod_ssl/2.2.31 OpenSSL/1.0.1e-fips mod_bwlimited/1.4',\n",
+       "       'nginx/1.9.13', 'mw2180.codfw.wmnet', 'Apache/2.2.14 (Ubuntu)',\n",
+       "       'ebay server', 'nginx/0.8.55', 'Apache/2.2.10 (Linux/SUSE)',\n",
+       "       'nginx/1.7.12',\n",
+       "       'Apache/2.0.63 (Unix) mod_ssl/2.0.63 OpenSSL/0.9.8e-fips-rhel5 mod_auth_passthrough/2.1 mod_bwlimited/1.4 PHP/5.3.6',\n",
+       "       'Boston.com Frontend', 'My Arse', 'IdeaWebServer/v0.80',\n",
+       "       'Apache/2.4.17 (Unix) OpenSSL/1.0.1e-fips PHP/5.6.19',\n",
+       "       'Microsoft-IIS/7.5; litigation_essentials.lexisnexis.com  9999',\n",
+       "       'Apache/2.2.16 (Debian)'], dtype=object)"
+      ]
+     },
+     "execution_count": 26,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites['SERVER'].unique()\n"
    ]
   },
   {
@@ -400,7 +2144,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -418,22 +2162,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here\n"
+    "def label_server(server):\n",
+    "    if 'Microsoft' in server:\n",
+    "        return 'Microsoft'\n",
+    "    elif 'Apache' in server:\n",
+    "        return 'Apache'\n",
+    "    elif 'nginx' in server:\n",
+    "        return 'nginx'\n",
+    "    else:\n",
+    "        return 'Other'\n",
+    "\n",
+    "websites['SERVER'] = websites['SERVER'].apply(label_server)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 29,
    "metadata": {
     "scrolled": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array(['nginx', 'Apache', 'Microsoft', 'Other'], dtype=object)"
+      ]
+     },
+     "execution_count": 29,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Count `SERVER` value counts here\n"
+    "websites['SERVER'].unique()\n"
    ]
   },
   {
@@ -445,11 +2210,413 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>SERVER_Apache</th>\n",
+       "      <th>SERVER_Microsoft</th>\n",
+       "      <th>SERVER_Other</th>\n",
+       "      <th>SERVER_nginx</th>\n",
+       "      <th>CHARSET_ISO-8859</th>\n",
+       "      <th>CHARSET_ISO-8859-1</th>\n",
+       "      <th>CHARSET_None</th>\n",
+       "      <th>CHARSET_UTF-8</th>\n",
+       "      <th>CHARSET_iso-8859-1</th>\n",
+       "      <th>CHARSET_us-ascii</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WHOIS_COUNTRY_CA</th>\n",
+       "      <th>WHOIS_COUNTRY_CN</th>\n",
+       "      <th>WHOIS_COUNTRY_ES</th>\n",
+       "      <th>WHOIS_COUNTRY_IN</th>\n",
+       "      <th>WHOIS_COUNTRY_JP</th>\n",
+       "      <th>WHOIS_COUNTRY_None</th>\n",
+       "      <th>WHOIS_COUNTRY_OTHER</th>\n",
+       "      <th>WHOIS_COUNTRY_PA</th>\n",
+       "      <th>WHOIS_COUNTRY_UK</th>\n",
+       "      <th>WHOIS_COUNTRY_US</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1779 rows × 24 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      SERVER_Apache  SERVER_Microsoft  SERVER_Other  SERVER_nginx  \\\n",
+       "0                 0                 0             0             1   \n",
+       "1                 1                 0             0             0   \n",
+       "2                 0                 1             0             0   \n",
+       "3                 0                 0             0             1   \n",
+       "4                 0                 0             1             0   \n",
+       "...             ...               ...           ...           ...   \n",
+       "1776              1                 0             0             0   \n",
+       "1777              1                 0             0             0   \n",
+       "1778              1                 0             0             0   \n",
+       "1779              0                 0             0             1   \n",
+       "1780              0                 1             0             0   \n",
+       "\n",
+       "      CHARSET_ISO-8859  CHARSET_ISO-8859-1  CHARSET_None  CHARSET_UTF-8  \\\n",
+       "0                    0                   0             0              0   \n",
+       "1                    0                   0             0              1   \n",
+       "2                    0                   0             0              0   \n",
+       "3                    0                   1             0              0   \n",
+       "4                    0                   0             0              1   \n",
+       "...                ...                 ...           ...            ...   \n",
+       "1776                 0                   0             0              1   \n",
+       "1777                 0                   0             0              1   \n",
+       "1778                 0                   0             0              0   \n",
+       "1779                 0                   1             0              0   \n",
+       "1780                 0                   0             0              0   \n",
+       "\n",
+       "      CHARSET_iso-8859-1  CHARSET_us-ascii  ...  WHOIS_COUNTRY_CA  \\\n",
+       "0                      1                 0  ...                 0   \n",
+       "1                      0                 0  ...                 0   \n",
+       "2                      0                 1  ...                 0   \n",
+       "3                      0                 0  ...                 0   \n",
+       "4                      0                 0  ...                 0   \n",
+       "...                  ...               ...  ...               ...   \n",
+       "1776                   0                 0  ...                 0   \n",
+       "1777                   0                 0  ...                 0   \n",
+       "1778                   0                 0  ...                 0   \n",
+       "1779                   0                 0  ...                 0   \n",
+       "1780                   0                 0  ...                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_CN  WHOIS_COUNTRY_ES  WHOIS_COUNTRY_IN  WHOIS_COUNTRY_JP  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 1                 0                 0   \n",
+       "1777                 0                 1                 0                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_None  WHOIS_COUNTRY_OTHER  WHOIS_COUNTRY_PA  \\\n",
+       "0                      1                    0                 0   \n",
+       "1                      1                    0                 0   \n",
+       "2                      1                    0                 0   \n",
+       "3                      0                    0                 0   \n",
+       "4                      0                    0                 0   \n",
+       "...                  ...                  ...               ...   \n",
+       "1776                   0                    0                 0   \n",
+       "1777                   0                    0                 0   \n",
+       "1778                   0                    0                 0   \n",
+       "1779                   0                    0                 0   \n",
+       "1780                   0                    0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_UK  WHOIS_COUNTRY_US  \n",
+       "0                    0                 0  \n",
+       "1                    0                 0  \n",
+       "2                    0                 0  \n",
+       "3                    0                 1  \n",
+       "4                    0                 1  \n",
+       "...                ...               ...  \n",
+       "1776                 0                 0  \n",
+       "1777                 0                 0  \n",
+       "1778                 0                 1  \n",
+       "1779                 0                 1  \n",
+       "1780                 0                 1  \n",
+       "\n",
+       "[1779 rows x 24 columns]"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy = pd.get_dummies(websites[['SERVER','CHARSET', 'WHOIS_COUNTRY']])\n",
+    "website_dummy\n"
    ]
   },
   {
@@ -461,11 +2628,868 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 31,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here\n"
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "SERVER_Apache           uint8\n",
+       "SERVER_Microsoft        uint8\n",
+       "SERVER_Other            uint8\n",
+       "SERVER_nginx            uint8\n",
+       "CHARSET_ISO-8859        uint8\n",
+       "CHARSET_ISO-8859-1      uint8\n",
+       "CHARSET_None            uint8\n",
+       "CHARSET_UTF-8           uint8\n",
+       "CHARSET_iso-8859-1      uint8\n",
+       "CHARSET_us-ascii        uint8\n",
+       "CHARSET_utf-8           uint8\n",
+       "CHARSET_windows-1251    uint8\n",
+       "CHARSET_windows-1252    uint8\n",
+       "WHOIS_COUNTRY_AU        uint8\n",
+       "WHOIS_COUNTRY_CA        uint8\n",
+       "WHOIS_COUNTRY_CN        uint8\n",
+       "WHOIS_COUNTRY_ES        uint8\n",
+       "WHOIS_COUNTRY_IN        uint8\n",
+       "WHOIS_COUNTRY_JP        uint8\n",
+       "WHOIS_COUNTRY_None      uint8\n",
+       "WHOIS_COUNTRY_OTHER     uint8\n",
+       "WHOIS_COUNTRY_PA        uint8\n",
+       "WHOIS_COUNTRY_UK        uint8\n",
+       "WHOIS_COUNTRY_US        uint8\n",
+       "dtype: object"
+      ]
+     },
+     "execution_count": 31,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "website_dummy.dtypes\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>CHARSET</th>\n",
+       "      <th>SERVER</th>\n",
+       "      <th>WHOIS_COUNTRY</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WHOIS_COUNTRY_CA</th>\n",
+       "      <th>WHOIS_COUNTRY_CN</th>\n",
+       "      <th>WHOIS_COUNTRY_ES</th>\n",
+       "      <th>WHOIS_COUNTRY_IN</th>\n",
+       "      <th>WHOIS_COUNTRY_JP</th>\n",
+       "      <th>WHOIS_COUNTRY_None</th>\n",
+       "      <th>WHOIS_COUNTRY_OTHER</th>\n",
+       "      <th>WHOIS_COUNTRY_PA</th>\n",
+       "      <th>WHOIS_COUNTRY_UK</th>\n",
+       "      <th>WHOIS_COUNTRY_US</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>16</td>\n",
+       "      <td>7</td>\n",
+       "      <td>iso-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
+       "      <td>832</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>None</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
+       "      <td>1265</td>\n",
+       "      <td>1230</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>us-ascii</td>\n",
+       "      <td>Microsoft</td>\n",
+       "      <td>None</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Other</td>\n",
+       "      <td>US</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1776</th>\n",
+       "      <td>194</td>\n",
+       "      <td>16</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>3</td>\n",
+       "      <td>186</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>UTF-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>ES</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Apache</td>\n",
+       "      <td>US</td>\n",
+       "      <td>2</td>\n",
+       "      <td>6</td>\n",
+       "      <td>89</td>\n",
+       "      <td>132181</td>\n",
+       "      <td>6945</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1779</th>\n",
+       "      <td>234</td>\n",
+       "      <td>34</td>\n",
+       "      <td>ISO-8859-1</td>\n",
+       "      <td>nginx</td>\n",
+       "      <td>US</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>utf-8</td>\n",
+       "      <td>Microsoft</td>\n",
+       "      <td>US</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1779 rows × 37 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      URL_LENGTH  NUMBER_SPECIAL_CHARACTERS     CHARSET     SERVER  \\\n",
+       "0             16                          7  iso-8859-1      nginx   \n",
+       "1             16                          6       UTF-8     Apache   \n",
+       "2             16                          6    us-ascii  Microsoft   \n",
+       "3             17                          6  ISO-8859-1      nginx   \n",
+       "4             17                          6       UTF-8      Other   \n",
+       "...          ...                        ...         ...        ...   \n",
+       "1776         194                         16       UTF-8     Apache   \n",
+       "1777         198                         17       UTF-8     Apache   \n",
+       "1778         201                         34       utf-8     Apache   \n",
+       "1779         234                         34  ISO-8859-1      nginx   \n",
+       "1780         249                         40       utf-8  Microsoft   \n",
+       "\n",
+       "     WHOIS_COUNTRY  DIST_REMOTE_TCP_PORT  REMOTE_IPS  REMOTE_APP_PACKETS  \\\n",
+       "0             None                     0           2                  10   \n",
+       "1             None                     7           4                  19   \n",
+       "2             None                     0           0                   0   \n",
+       "3               US                    22           3                  37   \n",
+       "4               US                     2           5                  62   \n",
+       "...            ...                   ...         ...                 ...   \n",
+       "1776            ES                     0           0                   3   \n",
+       "1777            ES                     0           0                   2   \n",
+       "1778            US                     2           6                  89   \n",
+       "1779            US                     0           0                   0   \n",
+       "1780            US                     6          11                  28   \n",
+       "\n",
+       "      SOURCE_APP_BYTES  REMOTE_APP_BYTES  ...  WHOIS_COUNTRY_CA  \\\n",
+       "0                 1153               832  ...                 0   \n",
+       "1                 1265              1230  ...                 0   \n",
+       "2                    0                 0  ...                 0   \n",
+       "3                18784              4380  ...                 0   \n",
+       "4               129889              4586  ...                 0   \n",
+       "...                ...               ...  ...               ...   \n",
+       "1776               186                 0  ...                 0   \n",
+       "1777               124                 0  ...                 0   \n",
+       "1778            132181              6945  ...                 0   \n",
+       "1779                 0                 0  ...                 0   \n",
+       "1780              3039              2776  ...                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_CN  WHOIS_COUNTRY_ES  WHOIS_COUNTRY_IN  WHOIS_COUNTRY_JP  \\\n",
+       "0                    0                 0                 0                 0   \n",
+       "1                    0                 0                 0                 0   \n",
+       "2                    0                 0                 0                 0   \n",
+       "3                    0                 0                 0                 0   \n",
+       "4                    0                 0                 0                 0   \n",
+       "...                ...               ...               ...               ...   \n",
+       "1776                 0                 1                 0                 0   \n",
+       "1777                 0                 1                 0                 0   \n",
+       "1778                 0                 0                 0                 0   \n",
+       "1779                 0                 0                 0                 0   \n",
+       "1780                 0                 0                 0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_None  WHOIS_COUNTRY_OTHER  WHOIS_COUNTRY_PA  \\\n",
+       "0                      1                    0                 0   \n",
+       "1                      1                    0                 0   \n",
+       "2                      1                    0                 0   \n",
+       "3                      0                    0                 0   \n",
+       "4                      0                    0                 0   \n",
+       "...                  ...                  ...               ...   \n",
+       "1776                   0                    0                 0   \n",
+       "1777                   0                    0                 0   \n",
+       "1778                   0                    0                 0   \n",
+       "1779                   0                    0                 0   \n",
+       "1780                   0                    0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_UK  WHOIS_COUNTRY_US  \n",
+       "0                    0                 0  \n",
+       "1                    0                 0  \n",
+       "2                    0                 0  \n",
+       "3                    0                 1  \n",
+       "4                    0                 1  \n",
+       "...                ...               ...  \n",
+       "1776                 0                 0  \n",
+       "1777                 0                 0  \n",
+       "1778                 0                 1  \n",
+       "1779                 0                 1  \n",
+       "1780                 0                 1  \n",
+       "\n",
+       "[1779 rows x 37 columns]"
+      ]
+     },
+     "execution_count": 32,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites_final = pd.concat([websites, website_dummy], axis=1)\n",
+    "websites_final"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>URL_LENGTH</th>\n",
+       "      <th>NUMBER_SPECIAL_CHARACTERS</th>\n",
+       "      <th>DIST_REMOTE_TCP_PORT</th>\n",
+       "      <th>REMOTE_IPS</th>\n",
+       "      <th>REMOTE_APP_PACKETS</th>\n",
+       "      <th>SOURCE_APP_BYTES</th>\n",
+       "      <th>REMOTE_APP_BYTES</th>\n",
+       "      <th>APP_PACKETS</th>\n",
+       "      <th>DNS_QUERY_TIMES</th>\n",
+       "      <th>Type</th>\n",
+       "      <th>...</th>\n",
+       "      <th>WHOIS_COUNTRY_CA</th>\n",
+       "      <th>WHOIS_COUNTRY_CN</th>\n",
+       "      <th>WHOIS_COUNTRY_ES</th>\n",
+       "      <th>WHOIS_COUNTRY_IN</th>\n",
+       "      <th>WHOIS_COUNTRY_JP</th>\n",
+       "      <th>WHOIS_COUNTRY_None</th>\n",
+       "      <th>WHOIS_COUNTRY_OTHER</th>\n",
+       "      <th>WHOIS_COUNTRY_PA</th>\n",
+       "      <th>WHOIS_COUNTRY_UK</th>\n",
+       "      <th>WHOIS_COUNTRY_US</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
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+       "      <th>0</th>\n",
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+       "      <td>10</td>\n",
+       "      <td>1153</td>\n",
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+       "      <td>9</td>\n",
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+       "      <td>6</td>\n",
+       "      <td>7</td>\n",
+       "      <td>4</td>\n",
+       "      <td>19</td>\n",
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+       "      <td>1230</td>\n",
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+       "      <td>0</td>\n",
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+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>16</td>\n",
+       "      <td>6</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>22</td>\n",
+       "      <td>3</td>\n",
+       "      <td>37</td>\n",
+       "      <td>18784</td>\n",
+       "      <td>4380</td>\n",
+       "      <td>39</td>\n",
+       "      <td>8.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>17</td>\n",
+       "      <td>6</td>\n",
+       "      <td>2</td>\n",
+       "      <td>5</td>\n",
+       "      <td>62</td>\n",
+       "      <td>129889</td>\n",
+       "      <td>4586</td>\n",
+       "      <td>61</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
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+       "      <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>1776</th>\n",
+       "      <td>194</td>\n",
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+       "      <td>1</td>\n",
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+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1777</th>\n",
+       "      <td>198</td>\n",
+       "      <td>17</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>2</td>\n",
+       "      <td>124</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0.0</td>\n",
+       "      <td>1</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1778</th>\n",
+       "      <td>201</td>\n",
+       "      <td>34</td>\n",
+       "      <td>2</td>\n",
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+       "      <td>132181</td>\n",
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+       "      <td>4.0</td>\n",
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+       "    </tr>\n",
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+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1780</th>\n",
+       "      <td>249</td>\n",
+       "      <td>40</td>\n",
+       "      <td>6</td>\n",
+       "      <td>11</td>\n",
+       "      <td>28</td>\n",
+       "      <td>3039</td>\n",
+       "      <td>2776</td>\n",
+       "      <td>25</td>\n",
+       "      <td>6.0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>...</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
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+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>1779 rows × 34 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      URL_LENGTH  NUMBER_SPECIAL_CHARACTERS  DIST_REMOTE_TCP_PORT  REMOTE_IPS  \\\n",
+       "0             16                          7                     0           2   \n",
+       "1             16                          6                     7           4   \n",
+       "2             16                          6                     0           0   \n",
+       "3             17                          6                    22           3   \n",
+       "4             17                          6                     2           5   \n",
+       "...          ...                        ...                   ...         ...   \n",
+       "1776         194                         16                     0           0   \n",
+       "1777         198                         17                     0           0   \n",
+       "1778         201                         34                     2           6   \n",
+       "1779         234                         34                     0           0   \n",
+       "1780         249                         40                     6          11   \n",
+       "\n",
+       "      REMOTE_APP_PACKETS  SOURCE_APP_BYTES  REMOTE_APP_BYTES  APP_PACKETS  \\\n",
+       "0                     10              1153               832            9   \n",
+       "1                     19              1265              1230           17   \n",
+       "2                      0                 0                 0            0   \n",
+       "3                     37             18784              4380           39   \n",
+       "4                     62            129889              4586           61   \n",
+       "...                  ...               ...               ...          ...   \n",
+       "1776                   3               186                 0            0   \n",
+       "1777                   2               124                 0            0   \n",
+       "1778                  89            132181              6945           87   \n",
+       "1779                   0                 0                 0            0   \n",
+       "1780                  28              3039              2776           25   \n",
+       "\n",
+       "      DNS_QUERY_TIMES  Type  ...  WHOIS_COUNTRY_CA  WHOIS_COUNTRY_CN  \\\n",
+       "0                 2.0     1  ...                 0                 0   \n",
+       "1                 0.0     0  ...                 0                 0   \n",
+       "2                 0.0     0  ...                 0                 0   \n",
+       "3                 8.0     0  ...                 0                 0   \n",
+       "4                 4.0     0  ...                 0                 0   \n",
+       "...               ...   ...  ...               ...               ...   \n",
+       "1776              0.0     1  ...                 0                 0   \n",
+       "1777              0.0     1  ...                 0                 0   \n",
+       "1778              4.0     0  ...                 0                 0   \n",
+       "1779              0.0     0  ...                 0                 0   \n",
+       "1780              6.0     0  ...                 0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_ES  WHOIS_COUNTRY_IN  WHOIS_COUNTRY_JP  \\\n",
+       "0                    0                 0                 0   \n",
+       "1                    0                 0                 0   \n",
+       "2                    0                 0                 0   \n",
+       "3                    0                 0                 0   \n",
+       "4                    0                 0                 0   \n",
+       "...                ...               ...               ...   \n",
+       "1776                 1                 0                 0   \n",
+       "1777                 1                 0                 0   \n",
+       "1778                 0                 0                 0   \n",
+       "1779                 0                 0                 0   \n",
+       "1780                 0                 0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_None  WHOIS_COUNTRY_OTHER  WHOIS_COUNTRY_PA  \\\n",
+       "0                      1                    0                 0   \n",
+       "1                      1                    0                 0   \n",
+       "2                      1                    0                 0   \n",
+       "3                      0                    0                 0   \n",
+       "4                      0                    0                 0   \n",
+       "...                  ...                  ...               ...   \n",
+       "1776                   0                    0                 0   \n",
+       "1777                   0                    0                 0   \n",
+       "1778                   0                    0                 0   \n",
+       "1779                   0                    0                 0   \n",
+       "1780                   0                    0                 0   \n",
+       "\n",
+       "      WHOIS_COUNTRY_UK  WHOIS_COUNTRY_US  \n",
+       "0                    0                 0  \n",
+       "1                    0                 0  \n",
+       "2                    0                 0  \n",
+       "3                    0                 1  \n",
+       "4                    0                 1  \n",
+       "...                ...               ...  \n",
+       "1776                 0                 0  \n",
+       "1777                 0                 0  \n",
+       "1778                 0                 1  \n",
+       "1779                 0                 1  \n",
+       "1780                 0                 1  \n",
+       "\n",
+       "[1779 rows x 34 columns]"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "websites_final.drop(columns=['SERVER','CHARSET', 'WHOIS_COUNTRY'], inplace=True)\n",
+    "websites_final"
    ]
   },
   {
@@ -479,13 +3503,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 34,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "X_train: (1423, 33)\n",
+      "X_test: (356, 33)\n",
+      "y_train: (1423,)\n",
+      "y_test: (356,)\n"
+     ]
+    }
+   ],
    "source": [
     "from sklearn.model_selection import train_test_split\n",
     "\n",
-    "# Your code here:\n"
+    "X = websites_final.drop(columns=['Type'])\n",
+    "y = websites_final['Type']\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=1)\n",
+    "\n",
+    "print(\"X_train:\", X_train.shape)\n",
+    "print(\"X_test:\", X_test.shape)\n",
+    "print(\"y_train:\", y_train.shape)\n",
+    "print(\"y_test:\", y_test.shape)"
    ]
   },
   {
@@ -499,12 +3542,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "from sklearn.linear_model import LogisticRegression\n",
+    "\n",
+    "log_reg = LogisticRegression()"
    ]
   },
   {
@@ -516,12 +3560,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 36,
    "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here:\n",
-    "\n"
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\linear_model\\_logistic.py:460: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
+      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
+      "\n",
+      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
+      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
+      "Please also refer to the documentation for alternative solver options:\n",
+      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
+      "  n_iter_i = _check_optimize_result(\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {color: black;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LogisticRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">LogisticRegression</label><div class=\"sk-toggleable__content\"><pre>LogisticRegression()</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "LogisticRegression()"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "log_reg.fit(X_train, y_train)"
    ]
   },
   {
@@ -533,12 +3604,47 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 59,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.8820224719101124"
+      ]
+     },
+     "execution_count": 59,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.metrics import confusion_matrix, accuracy_score\n",
+    "\n",
+    "y_pred = log_reg.predict(X_test)\n",
+    "\n",
+    "accuracy_score(y_test, y_pred)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 60,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[301,  12],\n",
+       "       [ 30,  13]], dtype=int64)"
+      ]
+     },
+     "execution_count": 60,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "confusion_matrix(y_test, y_pred)"
    ]
   },
   {
@@ -550,11 +3656,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Your conclusions here:\n",
+    "#It doesnt seem like a very reliable model as it got 30 false negatives.\n",
     "\n"
    ]
   },
@@ -569,12 +3675,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Your code here:\n",
-    "\n"
+   "execution_count": 62,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {color: black;}#sk-container-id-3 pre{padding: 0;}#sk-container-id-3 div.sk-toggleable {background-color: white;}#sk-container-id-3 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-3 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-3 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-3 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-3 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-3 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-3 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-3 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-3 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-3 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-3 div.sk-item {position: relative;z-index: 1;}#sk-container-id-3 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-3 div.sk-item::before, #sk-container-id-3 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-3 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-3 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-3 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-3 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-3 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-3 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-3 div.sk-label-container {text-align: center;}#sk-container-id-3 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-3 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>KNeighborsClassifier(n_neighbors=3)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" checked><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">KNeighborsClassifier</label><div class=\"sk-toggleable__content\"><pre>KNeighborsClassifier(n_neighbors=3)</pre></div></div></div></div></div>"
+      ],
+      "text/plain": [
+       "KNeighborsClassifier(n_neighbors=3)"
+      ]
+     },
+     "execution_count": 62,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "\n",
+    "knn = KNeighborsClassifier(n_neighbors=3)\n",
+    "\n",
+    "knn.fit(X_train, y_train)"
    ]
   },
   {
@@ -586,12 +3709,75 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'Flags' object has no attribute 'c_contiguous'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\migue\\OneDrive\\Ambiente de Trabalho\\Ironhack\\week 7\\lab-supervised-learning\\your-code\\main.ipynb Cell 70\u001b[0m line \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/migue/OneDrive/Ambiente%20de%20Trabalho/Ironhack/week%207/lab-supervised-learning/your-code/main.ipynb#Y140sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m pred_knn \u001b[39m=\u001b[39m knn\u001b[39m.\u001b[39mpredict(X_test)\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\neighbors\\_classification.py:246\u001b[0m, in \u001b[0;36mKNeighborsClassifier.predict\u001b[1;34m(self, X)\u001b[0m\n\u001b[0;32m    244\u001b[0m check_is_fitted(\u001b[39mself\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39m_fit_method\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    245\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mweights \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39muniform\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m--> 246\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_fit_method \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mbrute\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mand\u001b[39;00m ArgKminClassMode\u001b[39m.\u001b[39mis_usable_for(\n\u001b[0;32m    247\u001b[0m         X, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_fit_X, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmetric\n\u001b[0;32m    248\u001b[0m     ):\n\u001b[0;32m    249\u001b[0m         probabilities \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpredict_proba(X)\n\u001b[0;32m    250\u001b[0m         \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39moutputs_2d_:\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:471\u001b[0m, in \u001b[0;36mArgKminClassMode.is_usable_for\u001b[1;34m(cls, X, Y, metric)\u001b[0m\n\u001b[0;32m    448\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[0;32m    449\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_usable_for\u001b[39m(\u001b[39mcls\u001b[39m, X, Y, metric) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mbool\u001b[39m:\n\u001b[0;32m    450\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Return True if the dispatcher can be used for the given parameters.\u001b[39;00m\n\u001b[0;32m    451\u001b[0m \n\u001b[0;32m    452\u001b[0m \u001b[39m    Parameters\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    468\u001b[0m \u001b[39m    True if the PairwiseDistancesReduction can be used, else False.\u001b[39;00m\n\u001b[0;32m    469\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m    470\u001b[0m     \u001b[39mreturn\u001b[39;00m (\n\u001b[1;32m--> 471\u001b[0m         ArgKmin\u001b[39m.\u001b[39mis_usable_for(X, Y, metric)\n\u001b[0;32m    472\u001b[0m         \u001b[39m# TODO: Support CSR matrices.\u001b[39;00m\n\u001b[0;32m    473\u001b[0m         \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m issparse(X)\n\u001b[0;32m    474\u001b[0m         \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m issparse(Y)\n\u001b[0;32m    475\u001b[0m         \u001b[39m# TODO: implement Euclidean specialization with GEMM.\u001b[39;00m\n\u001b[0;32m    476\u001b[0m         \u001b[39mand\u001b[39;00m metric \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m (\u001b[39m\"\u001b[39m\u001b[39meuclidean\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39msqeuclidean\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    477\u001b[0m     )\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:115\u001b[0m, in \u001b[0;36mBaseDistancesReductionDispatcher.is_usable_for\u001b[1;34m(cls, X, Y, metric)\u001b[0m\n\u001b[0;32m    101\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_valid_sparse_matrix\u001b[39m(X):\n\u001b[0;32m    102\u001b[0m     \u001b[39mreturn\u001b[39;00m (\n\u001b[0;32m    103\u001b[0m         isspmatrix_csr(X)\n\u001b[0;32m    104\u001b[0m         \u001b[39mand\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    110\u001b[0m         X\u001b[39m.\u001b[39mindices\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m X\u001b[39m.\u001b[39mindptr\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m np\u001b[39m.\u001b[39mint32\n\u001b[0;32m    111\u001b[0m     )\n\u001b[0;32m    113\u001b[0m is_usable \u001b[39m=\u001b[39m (\n\u001b[0;32m    114\u001b[0m     get_config()\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39menable_cython_pairwise_dist\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mTrue\u001b[39;00m)\n\u001b[1;32m--> 115\u001b[0m     \u001b[39mand\u001b[39;00m (is_numpy_c_ordered(X) \u001b[39mor\u001b[39;00m is_valid_sparse_matrix(X))\n\u001b[0;32m    116\u001b[0m     \u001b[39mand\u001b[39;00m (is_numpy_c_ordered(Y) \u001b[39mor\u001b[39;00m is_valid_sparse_matrix(Y))\n\u001b[0;32m    117\u001b[0m     \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m Y\u001b[39m.\u001b[39mdtype\n\u001b[0;32m    118\u001b[0m     \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mdtype \u001b[39min\u001b[39;00m (np\u001b[39m.\u001b[39mfloat32, np\u001b[39m.\u001b[39mfloat64)\n\u001b[0;32m    119\u001b[0m     \u001b[39mand\u001b[39;00m metric \u001b[39min\u001b[39;00m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mvalid_metrics()\n\u001b[0;32m    120\u001b[0m )\n\u001b[0;32m    122\u001b[0m \u001b[39mreturn\u001b[39;00m is_usable\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:99\u001b[0m, in \u001b[0;36mBaseDistancesReductionDispatcher.is_usable_for.<locals>.is_numpy_c_ordered\u001b[1;34m(X)\u001b[0m\n\u001b[0;32m     98\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_numpy_c_ordered\u001b[39m(X):\n\u001b[1;32m---> 99\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mhasattr\u001b[39m(X, \u001b[39m\"\u001b[39m\u001b[39mflags\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mflags\u001b[39m.\u001b[39mc_contiguous\n",
+      "\u001b[1;31mAttributeError\u001b[0m: 'Flags' object has no attribute 'c_contiguous'"
+     ]
+    }
+   ],
+   "source": [
+    "pred_knn = knn.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 57,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "AttributeError",
+     "evalue": "'Flags' object has no attribute 'c_contiguous'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\migue\\OneDrive\\Ambiente de Trabalho\\Ironhack\\week 7\\lab-supervised-learning\\your-code\\main.ipynb Cell 70\u001b[0m line \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/migue/OneDrive/Ambiente%20de%20Trabalho/Ironhack/week%207/lab-supervised-learning/your-code/main.ipynb#Y125sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m pred_knn \u001b[39m=\u001b[39m knn\u001b[39m.\u001b[39mpredict(X_test)\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/migue/OneDrive/Ambiente%20de%20Trabalho/Ironhack/week%207/lab-supervised-learning/your-code/main.ipynb#Y125sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m accuracy_score(y_test, pred_knn)\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\neighbors\\_classification.py:246\u001b[0m, in \u001b[0;36mKNeighborsClassifier.predict\u001b[1;34m(self, X)\u001b[0m\n\u001b[0;32m    244\u001b[0m check_is_fitted(\u001b[39mself\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39m_fit_method\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    245\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mweights \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39muniform\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[1;32m--> 246\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_fit_method \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mbrute\u001b[39m\u001b[39m\"\u001b[39m \u001b[39mand\u001b[39;00m ArgKminClassMode\u001b[39m.\u001b[39mis_usable_for(\n\u001b[0;32m    247\u001b[0m         X, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_fit_X, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mmetric\n\u001b[0;32m    248\u001b[0m     ):\n\u001b[0;32m    249\u001b[0m         probabilities \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpredict_proba(X)\n\u001b[0;32m    250\u001b[0m         \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39moutputs_2d_:\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:471\u001b[0m, in \u001b[0;36mArgKminClassMode.is_usable_for\u001b[1;34m(cls, X, Y, metric)\u001b[0m\n\u001b[0;32m    448\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[0;32m    449\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_usable_for\u001b[39m(\u001b[39mcls\u001b[39m, X, Y, metric) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m \u001b[39mbool\u001b[39m:\n\u001b[0;32m    450\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Return True if the dispatcher can be used for the given parameters.\u001b[39;00m\n\u001b[0;32m    451\u001b[0m \n\u001b[0;32m    452\u001b[0m \u001b[39m    Parameters\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    468\u001b[0m \u001b[39m    True if the PairwiseDistancesReduction can be used, else False.\u001b[39;00m\n\u001b[0;32m    469\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m    470\u001b[0m     \u001b[39mreturn\u001b[39;00m (\n\u001b[1;32m--> 471\u001b[0m         ArgKmin\u001b[39m.\u001b[39mis_usable_for(X, Y, metric)\n\u001b[0;32m    472\u001b[0m         \u001b[39m# TODO: Support CSR matrices.\u001b[39;00m\n\u001b[0;32m    473\u001b[0m         \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m issparse(X)\n\u001b[0;32m    474\u001b[0m         \u001b[39mand\u001b[39;00m \u001b[39mnot\u001b[39;00m issparse(Y)\n\u001b[0;32m    475\u001b[0m         \u001b[39m# TODO: implement Euclidean specialization with GEMM.\u001b[39;00m\n\u001b[0;32m    476\u001b[0m         \u001b[39mand\u001b[39;00m metric \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m (\u001b[39m\"\u001b[39m\u001b[39meuclidean\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39m\"\u001b[39m\u001b[39msqeuclidean\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[0;32m    477\u001b[0m     )\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:115\u001b[0m, in \u001b[0;36mBaseDistancesReductionDispatcher.is_usable_for\u001b[1;34m(cls, X, Y, metric)\u001b[0m\n\u001b[0;32m    101\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_valid_sparse_matrix\u001b[39m(X):\n\u001b[0;32m    102\u001b[0m     \u001b[39mreturn\u001b[39;00m (\n\u001b[0;32m    103\u001b[0m         isspmatrix_csr(X)\n\u001b[0;32m    104\u001b[0m         \u001b[39mand\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    110\u001b[0m         X\u001b[39m.\u001b[39mindices\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m X\u001b[39m.\u001b[39mindptr\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m np\u001b[39m.\u001b[39mint32\n\u001b[0;32m    111\u001b[0m     )\n\u001b[0;32m    113\u001b[0m is_usable \u001b[39m=\u001b[39m (\n\u001b[0;32m    114\u001b[0m     get_config()\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39menable_cython_pairwise_dist\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mTrue\u001b[39;00m)\n\u001b[1;32m--> 115\u001b[0m     \u001b[39mand\u001b[39;00m (is_numpy_c_ordered(X) \u001b[39mor\u001b[39;00m is_valid_sparse_matrix(X))\n\u001b[0;32m    116\u001b[0m     \u001b[39mand\u001b[39;00m (is_numpy_c_ordered(Y) \u001b[39mor\u001b[39;00m is_valid_sparse_matrix(Y))\n\u001b[0;32m    117\u001b[0m     \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mdtype \u001b[39m==\u001b[39m Y\u001b[39m.\u001b[39mdtype\n\u001b[0;32m    118\u001b[0m     \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mdtype \u001b[39min\u001b[39;00m (np\u001b[39m.\u001b[39mfloat32, np\u001b[39m.\u001b[39mfloat64)\n\u001b[0;32m    119\u001b[0m     \u001b[39mand\u001b[39;00m metric \u001b[39min\u001b[39;00m \u001b[39mcls\u001b[39m\u001b[39m.\u001b[39mvalid_metrics()\n\u001b[0;32m    120\u001b[0m )\n\u001b[0;32m    122\u001b[0m \u001b[39mreturn\u001b[39;00m is_usable\n",
+      "File \u001b[1;32mc:\\Users\\migue\\anaconda3\\Lib\\site-packages\\sklearn\\metrics\\_pairwise_distances_reduction\\_dispatcher.py:99\u001b[0m, in \u001b[0;36mBaseDistancesReductionDispatcher.is_usable_for.<locals>.is_numpy_c_ordered\u001b[1;34m(X)\u001b[0m\n\u001b[0;32m     98\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mis_numpy_c_ordered\u001b[39m(X):\n\u001b[1;32m---> 99\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mhasattr\u001b[39m(X, \u001b[39m\"\u001b[39m\u001b[39mflags\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mand\u001b[39;00m X\u001b[39m.\u001b[39mflags\u001b[39m.\u001b[39mc_contiguous\n",
+      "\u001b[1;31mAttributeError\u001b[0m: 'Flags' object has no attribute 'c_contiguous'"
+     ]
+    }
+   ],
+   "source": [
+    "pred_knn = knn.predict(X_test)\n",
+    "\n",
+    "accuracy_score(y_test, pred_knn)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 56,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "NameError",
+     "evalue": "name 'pred_knn' is not defined",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[1;32mc:\\Users\\migue\\OneDrive\\Ambiente de Trabalho\\Ironhack\\week 7\\lab-supervised-learning\\your-code\\main.ipynb Cell 71\u001b[0m line \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/migue/OneDrive/Ambiente%20de%20Trabalho/Ironhack/week%207/lab-supervised-learning/your-code/main.ipynb#Y136sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m confusion_matrix(y_test, pred_knn)\n",
+      "\u001b[1;31mNameError\u001b[0m: name 'pred_knn' is not defined"
+     ]
+    }
+   ],
    "source": [
-    "# Your code here:\n",
-    "\n"
+    "confusion_matrix(y_test, pred_knn)"
    ]
   },
   {
@@ -605,7 +3791,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -622,7 +3808,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -645,7 +3831,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -655,9 +3841,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "ironhack-3.7",
+   "display_name": "base",
    "language": "python",
-   "name": "ironhack-3.7"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -669,7 +3855,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.3"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/data/website.csv b/your-code/website.csv
old mode 100755
new mode 100644
similarity index 100%
rename from data/website.csv
rename to your-code/website.csv