code/graph/generate_graph.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "47642fff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Author: Dr James K Ruffle\n",
    "# Email: j.ruffle@ucl.ac.uk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "e1413333",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/Users/jruffle/Library/CloudStorage/OneDrive-UniversityCollegeLondon/PhD/WIdeathonRetention23/code/graph\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import glob\n",
    "from graph_tool.all import *; import graph_tool.all as gt\n",
    "import gravis as gv\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "from bs4 import BeautifulSoup\n",
    "import seaborn as sns\n",
    "\n",
    "import os\n",
    "print(os.getcwd())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1b2cc874",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/sw/h3fq4qtj0jj9kh01vd62l8980000gn/T/ipykernel_87010/571048350.py:1: DtypeWarning: Columns (17) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv('../simulated_data/simulated_data.csv',index_col=0)\n"
     ]
    },
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       "      <th>Longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Forum User</th>\n",
       "      <th>Symptom Logger</th>\n",
       "      <th>Frequent Check In</th>\n",
       "      <th>Diamond Forum Contributor</th>\n",
       "      <th>Big App Engagement</th>\n",
       "      <th>Appointment Attendance</th>\n",
       "      <th>7 Day Symptom Logger</th>\n",
       "      <th>Has Logged Symptoms</th>\n",
       "      <th>Checking In</th>\n",
       "      <th>Ruby Contributor</th>\n",
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       "      <th>0</th>\n",
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       "      <td>MindfulAI</td>\n",
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       "      <th>2</th>\n",
       "      <td>yearningBaboon5</td>\n",
       "      <td>../../assets/icons/lion_2298426.png</td>\n",
       "      <td>MindfulAI</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Swarey</td>\n",
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       "      <td>Jeremy_Swarey@mindfulai.com</td>\n",
       "      <td>53.69786</td>\n",
       "      <td>-2.68758</td>\n",
       "      <td>...</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>../../assets/badges/frequent_check_in.png</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>../../assets/badges/7_day_symptom_logger.png</td>\n",
       "      <td>../../assets/badges/has_logged_symptoms.png</td>\n",
       "      <td>../../assets/badges/checking_in.png</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pacifiedTuna1</td>\n",
       "      <td>../../assets/icons/cow_1998610.png</td>\n",
       "      <td>MindfulAI</td>\n",
       "      <td>Norman</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>1988-09-17</td>\n",
       "      <td>7 Megan lock\\nKarlside\\nL3 8HY</td>\n",
       "      <td>Norman_Kearney@mindfulai.com</td>\n",
       "      <td>55.82737</td>\n",
       "      <td>-4.05730</td>\n",
       "      <td>...</td>\n",
       "      <td>../../assets/badges/forum_user.png</td>\n",
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       "      <td>NaN</td>\n",
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       "      <th>4</th>\n",
       "      <td>emptyChough6</td>\n",
       "      <td>../../assets/icons/elephant_10197317.png</td>\n",
       "      <td>MindfulAI</td>\n",
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       "          username                                      icon Trial name  \\\n",
       "0     enragedBass3      ../../assets/icons/sharks_235052.png  MindfulAI   \n",
       "1  thrilledCaviar1      ../../assets/icons/bunny_1469202.png  MindfulAI   \n",
       "2  yearningBaboon5       ../../assets/icons/lion_2298426.png  MindfulAI   \n",
       "3    pacifiedTuna1        ../../assets/icons/cow_1998610.png  MindfulAI   \n",
       "4     emptyChough6  ../../assets/icons/elephant_10197317.png  MindfulAI   \n",
       "\n",
       "  First name  Last name         DOB  \\\n",
       "0    Shannon     Clarke  1993-01-10   \n",
       "1    Richard     Hayden  1973-11-20   \n",
       "2     Jeremy     Swarey  1996-02-19   \n",
       "3     Norman    Kearney  1988-09-17   \n",
       "4     Donald  Hernandez  1985-04-05   \n",
       "\n",
       "                                          Address  \\\n",
       "0      792 Jones shoal\\nWest Bryanmouth\\nCW6M 0RR   \n",
       "1       613 Wood viaduct\\nStanleyborough\\nG6U 3QH   \n",
       "2             9 Miller fall\\nLloydmouth\\nDD8B 4WF   \n",
       "3                  7 Megan lock\\nKarlside\\nL3 8HY   \n",
       "4  32 Norris corners\\nNew Alexandraberg\\nHU01 2FE   \n",
       "\n",
       "                            email  Latitude  Longitude  ...  \\\n",
       "0    Shannon_Clarke@mindfulai.com  52.66277   -2.01111  ...   \n",
       "1    Richard_Hayden@mindfulai.com  51.40148   -1.32471  ...   \n",
       "2     Jeremy_Swarey@mindfulai.com  53.69786   -2.68758  ...   \n",
       "3    Norman_Kearney@mindfulai.com  55.82737   -4.05730  ...   \n",
       "4  Donald_Hernandez@mindfulai.com  52.68333    0.93333  ...   \n",
       "\n",
       "                           Forum User Symptom Logger  \\\n",
       "0                                 NaN            NaN   \n",
       "1                                 NaN            NaN   \n",
       "2                                 NaN            NaN   \n",
       "3  ../../assets/badges/forum_user.png            NaN   \n",
       "4                                 NaN            NaN   \n",
       "\n",
       "                           Frequent Check In  \\\n",
       "0                                        NaN   \n",
       "1  ../../assets/badges/frequent_check_in.png   \n",
       "2  ../../assets/badges/frequent_check_in.png   \n",
       "3                                        NaN   \n",
       "4                                        NaN   \n",
       "\n",
       "                           Diamond Forum Contributor Big App Engagement  \\\n",
       "0                                                NaN                NaN   \n",
       "1  ../../assets/badges/diamond_forum_contributor.png                NaN   \n",
       "2                                                NaN                NaN   \n",
       "3                                                NaN                NaN   \n",
       "4  ../../assets/badges/diamond_forum_contributor.png                NaN   \n",
       "\n",
       "                           Appointment Attendance  \\\n",
       "0  ../../assets/badges/appointment_attendance.png   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "\n",
       "                           7 Day Symptom Logger  \\\n",
       "0  ../../assets/badges/7_day_symptom_logger.png   \n",
       "1  ../../assets/badges/7_day_symptom_logger.png   \n",
       "2  ../../assets/badges/7_day_symptom_logger.png   \n",
       "3                                           NaN   \n",
       "4                                           NaN   \n",
       "\n",
       "                           Has Logged Symptoms  \\\n",
       "0  ../../assets/badges/has_logged_symptoms.png   \n",
       "1                                          NaN   \n",
       "2  ../../assets/badges/has_logged_symptoms.png   \n",
       "3                                          NaN   \n",
       "4                                          NaN   \n",
       "\n",
       "                           Checking In  Ruby Contributor  \n",
       "0  ../../assets/badges/checking_in.png               NaN  \n",
       "1                                  NaN               NaN  \n",
       "2  ../../assets/badges/checking_in.png               NaN  \n",
       "3                                  NaN               NaN  \n",
       "4  ../../assets/badges/checking_in.png               NaN  \n",
       "\n",
       "[5 rows x 8068 columns]"
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     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('../simulated_data/simulated_data.csv',index_col=0)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "647b8d4e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
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       "      <td>../../assets/badges/7_day_symptom_logger.png</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
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       "      <th>2</th>\n",
       "      <td>yearningBaboon5</td>\n",
       "      <td>../../assets/icons/lion_2298426.png</td>\n",
       "      <td>MindfulAI</td>\n",
       "      <td>Jeremy</td>\n",
       "      <td>Swarey</td>\n",
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       "      <td>9 Miller fall\\nLloydmouth\\nDD8B 4WF</td>\n",
       "      <td>Jeremy_Swarey@mindfulai.com</td>\n",
       "      <td>53.69786</td>\n",
       "      <td>-2.68758</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>../../assets/badges/frequent_check_in.png</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>../../assets/badges/7_day_symptom_logger.png</td>\n",
       "      <td>../../assets/badges/has_logged_symptoms.png</td>\n",
       "      <td>../../assets/badges/checking_in.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>pacifiedTuna1</td>\n",
       "      <td>../../assets/icons/cow_1998610.png</td>\n",
       "      <td>MindfulAI</td>\n",
       "      <td>Norman</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>1</td>\n",
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       "      <th>4</th>\n",
       "      <td>emptyChough6</td>\n",
       "      <td>../../assets/icons/elephant_10197317.png</td>\n",
       "      <td>MindfulAI</td>\n",
       "      <td>Donald</td>\n",
       "      <td>Hernandez</td>\n",
       "      <td>1985-04-05</td>\n",
       "      <td>32 Norris corners\\nNew Alexandraberg\\nHU01 2FE</td>\n",
       "      <td>Donald_Hernandez@mindfulai.com</td>\n",
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       "      <td>0.93333</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>../../assets/badges/diamond_forum_contributor.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>../../assets/badges/checking_in.png</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 8069 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          username                                      icon Trial name  \\\n",
       "0     enragedBass3      ../../assets/icons/sharks_235052.png  MindfulAI   \n",
       "1  thrilledCaviar1      ../../assets/icons/bunny_1469202.png  MindfulAI   \n",
       "2  yearningBaboon5       ../../assets/icons/lion_2298426.png  MindfulAI   \n",
       "3    pacifiedTuna1        ../../assets/icons/cow_1998610.png  MindfulAI   \n",
       "4     emptyChough6  ../../assets/icons/elephant_10197317.png  MindfulAI   \n",
       "\n",
       "  First name  Last name         DOB  \\\n",
       "0    Shannon     Clarke  1993-01-10   \n",
       "1    Richard     Hayden  1973-11-20   \n",
       "2     Jeremy     Swarey  1996-02-19   \n",
       "3     Norman    Kearney  1988-09-17   \n",
       "4     Donald  Hernandez  1985-04-05   \n",
       "\n",
       "                                          Address  \\\n",
       "0      792 Jones shoal\\nWest Bryanmouth\\nCW6M 0RR   \n",
       "1       613 Wood viaduct\\nStanleyborough\\nG6U 3QH   \n",
       "2             9 Miller fall\\nLloydmouth\\nDD8B 4WF   \n",
       "3                  7 Megan lock\\nKarlside\\nL3 8HY   \n",
       "4  32 Norris corners\\nNew Alexandraberg\\nHU01 2FE   \n",
       "\n",
       "                            email  Latitude  Longitude  ... Symptom Logger  \\\n",
       "0    Shannon_Clarke@mindfulai.com  52.66277   -2.01111  ...            NaN   \n",
       "1    Richard_Hayden@mindfulai.com  51.40148   -1.32471  ...            NaN   \n",
       "2     Jeremy_Swarey@mindfulai.com  53.69786   -2.68758  ...            NaN   \n",
       "3    Norman_Kearney@mindfulai.com  55.82737   -4.05730  ...            NaN   \n",
       "4  Donald_Hernandez@mindfulai.com  52.68333    0.93333  ...            NaN   \n",
       "\n",
       "                           Frequent Check In  \\\n",
       "0                                        NaN   \n",
       "1  ../../assets/badges/frequent_check_in.png   \n",
       "2  ../../assets/badges/frequent_check_in.png   \n",
       "3                                        NaN   \n",
       "4                                        NaN   \n",
       "\n",
       "                           Diamond Forum Contributor Big App Engagement  \\\n",
       "0                                                NaN                NaN   \n",
       "1  ../../assets/badges/diamond_forum_contributor.png                NaN   \n",
       "2                                                NaN                NaN   \n",
       "3                                                NaN                NaN   \n",
       "4  ../../assets/badges/diamond_forum_contributor.png                NaN   \n",
       "\n",
       "                           Appointment Attendance  \\\n",
       "0  ../../assets/badges/appointment_attendance.png   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "\n",
       "                           7 Day Symptom Logger  \\\n",
       "0  ../../assets/badges/7_day_symptom_logger.png   \n",
       "1  ../../assets/badges/7_day_symptom_logger.png   \n",
       "2  ../../assets/badges/7_day_symptom_logger.png   \n",
       "3                                           NaN   \n",
       "4                                           NaN   \n",
       "\n",
       "                           Has Logged Symptoms  \\\n",
       "0  ../../assets/badges/has_logged_symptoms.png   \n",
       "1                                          NaN   \n",
       "2  ../../assets/badges/has_logged_symptoms.png   \n",
       "3                                          NaN   \n",
       "4                                          NaN   \n",
       "\n",
       "                           Checking In Ruby Contributor  focus_on_user  \n",
       "0  ../../assets/badges/checking_in.png              NaN              1  \n",
       "1                                  NaN              NaN              1  \n",
       "2  ../../assets/badges/checking_in.png              NaN              1  \n",
       "3                                  NaN              NaN              1  \n",
       "4  ../../assets/badges/checking_in.png              NaN              1  \n",
       "\n",
       "[5 rows x 8069 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Implement focus on one specific user\n",
    "initial_user = 'boastfulMare6'\n",
    "user='grizzledTuna9'\n",
    "df.loc[df['username']==initial_user,'username']=user\n",
    "\n",
    "print(user in df['username'].values)\n",
    "\n",
    "df['focus_on_user']=1\n",
    "df.loc[df['username']==user,'focus_on_user']=2\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9021cb7c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# #simulate award badges for users\n",
    "# #similar to git achievements\n",
    "badge_list = []\n",
    "badges = glob.glob('../../assets/badges/*png')\n",
    "for b in range(len(badges)):\n",
    "    png = badges[b]\n",
    "    badge_list.append(badges[b].split('/')[-1].split('.')[0].replace(\"_\", \" \").title())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8aea9a1f",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nodes primed!\n",
      "\n",
      "<Graph object, undirected, with 150 vertices and 0 edges, 11 internal vertex properties, at 0x2b175c190>\n"
     ]
    }
   ],
   "source": [
    "g = Graph(directed=False)\n",
    "username = g.new_vertex_property(\"string\")\n",
    "icon = g.new_vertex_property(\"string\")\n",
    "trial_name = g.new_vertex_property(\"string\")\n",
    "online_status=g.new_vertex_property(\"string\")\n",
    "total_points=g.new_vertex_property('int')\n",
    "total_attendance_points=g.new_vertex_property('int')\n",
    "total_log_points=g.new_vertex_property('int')\n",
    "total_check_in_points=g.new_vertex_property('int')\n",
    "total_answered_question_points=g.new_vertex_property('int')\n",
    "total_spoke_to_bot_points=g.new_vertex_property('int')\n",
    "badges = g.new_vertex_property(\"string\")\n",
    "user_focus = g.new_vertex_property(\"double\")\n",
    "\n",
    "for v, row in df.iterrows():\n",
    "    node = g.add_vertex()\n",
    "    username[v]=(row['username'])\n",
    "    icon[v]=(row['icon'])\n",
    "    trial_name[v]=(row['Trial name'])\n",
    "    online_status[v]=(np.random.choice(['No','Yes'], p=[0.3,0.7]))\n",
    "    total_points[v]=(row['Total points'])\n",
    "    total_attendance_points[v]=(row['Total attendance points'])\n",
    "    total_log_points[v]=(row['Total log points'])\n",
    "    total_check_in_points[v]=(row['Total check in points'])\n",
    "    total_answered_question_points[v]=(row['Total answered question points'])\n",
    "    total_spoke_to_bot_points[v]=(row['Total spoke to bot points'])\n",
    "    user_focus[v]=(row['focus_on_user'])\n",
    "    \n",
    "    badges_won = row[badge_list][row[badge_list].notnull()]\n",
    "    if len(badges_won)>0:\n",
    "        badges[v]='<br><center>'\n",
    "        for b in badges_won:\n",
    "            badges[v]+='<img src='+b+' style=\"margin:10px;max-height:40px;max-width:40px;\"></img>'\n",
    "        badges[v]+='</center>'\n",
    "    else:\n",
    "        badges[v]=''\n",
    "    \n",
    "g.vp[\"username\"]=username\n",
    "g.vp[\"image\"]=icon\n",
    "g.vp[\"trial_name\"]=trial_name\n",
    "g.vp[\"online_status\"]=online_status\n",
    "g.vp[\"total_points\"]=total_points\n",
    "g.vp[\"total_attendance_points\"]=total_attendance_points\n",
    "g.vp[\"total_log_points\"]=total_log_points\n",
    "g.vp[\"total_check_in_points\"]=total_check_in_points\n",
    "g.vp[\"total_answered_question_points\"]=total_answered_question_points\n",
    "g.vp[\"total_spoke_to_bot_points\"]=total_spoke_to_bot_points\n",
    "g.vp[\"user_focus\"]=user_focus\n",
    "\n",
    "#force highlighted user to be shown as online\n",
    "for v in g.vertices():\n",
    "    if g.vp['username'][v]==user:\n",
    "        g.vp['online_status'][v]='Yes'\n",
    "    \n",
    "print(\"Nodes primed!\")\n",
    "print(\"\")\n",
    "print(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7d3174a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick point comparison heatmap...\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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lm6jw7HDZ/hclVA95Bs2l8F5NdU/9JXKdihcLzR5tpu6ZU0XOY/Z/5PxaP6z2u+gOacvoqN4lCV1JrNqqQ7Bc9Lb2s/FkDMadIWFkp74SUG+79rGgrdL9fwuW9z2t3kvzp0uIuu3dEhqOzVdi3/hBItD1d0j4cM8wZceQ3E/CwP5u9YwUzxVfjj0L5RlNf12Jw4teeSJoK//wxzjcKFw398ArHQTia7c48Er/I7BMiIWFhYWFRVngKIVjjmUcs0zI7hvF/TT+2v8Ey0aIuPM/TwZtlcYoN83iX8V50F8wJ1h2KqqZcWyupHFG+8kszV+nZ1oplYK24k8+kXU7qtmh04S+1LeREHCrFqlVlfRCVzsiegvF0Y8HsBGQFT4vs4voCTKb9nPUzHTBo8KOtJj4D/wefhGlLJJwzIjVnARxGeTUU+zbo36vKWKw0tLivKkiAHabq9mT7xMjxELDtCr6vyQEJAGwn6fYIW+SzFgifcSZ1tHpvCyW9ZfNUQt0b1AobpRuEy24pOscOIoCQUqpS2JUj1N0FyqGwWkubpLYsyNYLHr7LXXItcKkVHjqUdlepxWGRMd71MzTbS4izlCqsj6+EYMClFYLwNusRHd5d8kYT75XUpn93/S5VhV2xs2S9HKYNFsScca+U+PZaSizYeSskuMb8TWnX+dIumrxN+qYkSYZcpheF8q6+Tq9ktK7zbUFAH+vXL8A1OY0VEJMp7rs36TOuvWFnWFBqFNJPW/Tu4iDbYcJ4vBrqHPvv8J6Os1JaF1eM2bFdM6cuqrFm0Wj3wzaoqeoNPVIG3Fpjf04NliOdFLvLdYO5P1HGICks9UzXjxDxkvcFcR4rZyn/ysMgEdMTfRvf1e/58u9ddOFEfM2qnvG6eEmXdhbK+8/fysJyo8jl1pzTl8I6+pt1m6414mZFp+z21YzRSycZ0G67l/sC7mOToqwoe7xOm2aQh3mveZvFhaIUTRmHAAg7nxJE0/qdfj1h4WrZx14pYNAfL02B17pfwRHzTE1JycHl1xyCdLT05GUlIQWLVrgl19+OfCGFhYWFhYWFv8TOCpMyI4dO9C6dWucdNJJuO6661ClShUsXboUWVlZyMrKOvAOAOybLCZepRnz+L/9V9pqqRlLtJXEbosXfB8su2kqPskzATan2n3rgwCA5BuolsZqmYk4GYot4NlmMPMDZPZHaZgmdu5z+h3NdgODJGZHajSU7QMTLJpxHE/1GrbrGeFWMiBLFS2EYQNMHZPfI0jJXErqac3khMy+OC25ovqdzcSKP5L6KJGuXdV6VWVmxqyFYUg4fRFxlLqanKoX6NtZpxUWPf+sNF0tOhoz289/WsZL0lAxwzMpk5wSyPAXq5mN06JL0BYbSzUyTA0NzRypzsjM2ami2S++97rPoWvPgrZdepZIrEGI6dmmmZrdxDI1FT2PSZXkMRiweRCjKmbrnMrKQK1ghMTQk+6WWhuGJTMmeACQd+f9su6larbq1KX6Q+QeaRghTqcNsXDb9Zgh1oHXLXhZsZmJ/xbWwLBHIXM5YgDM8+T9IFqsyEmSdgw9nopfFabE7Sz32a3XTG2/idgPetcUf6aevciZMtsO7j3dO5NSDQD+hhWhvgMIs4U6XTb0XuBrVkWny2rDOgAoGiPvgPgrFHPoJMt48RaLsZlTRzEg3uwfpU3rTLheTIiZM6wFvYucRBkHQQowP8vVMmRfOhU8dMzGYi4YtCWnyf/Q8+Iv0mxkIxnjgfGZeScA8JcQC6HrCjkVRcOTeLxo7g4XCleVzUQ6PqPdgVf6H8FR0YQ8/PDDqFOnDl57TYqOZWZm/sEWFhYWFhYWf3LY7JhDxlEJx4wfPx7t2rXDBRdcgKpVq6J169Z46aWXjkZXLCwsLCwsLI4SjgoTsmLFCowaNQqDBw/GbbfdhhkzZuCf//wn4uPjMWDAgBLrFxQUoKCgINTmJ5RHQrwS2HnfS/2VwAmVUnCNCLWYqP1o067BcmyxcnNk0VtADwOYN0vRuh23kTtfmoQ2DJ3KYYRQiCixXIk2TztxIoXSRXfnyrIO97hdpEaOEW6qk1F0r1OPXCVJMOmv1O6GO8mtcaXQyhHjvrqGXDuZIj4uTf03Wajg2KcqLTrSXa6d21AoUuM66i+VNMjidXJOkQ1KROYXiODQXy5Ww047JSJ1q0tIzpsrFK6nUyqdTBHLmjDFgvFSa6LVZRIi8jcrqnjRd3Kds/9DvxtH2Y1SH8RpSSJUff7+L+Jemj9TwhjJfXToY7uEBGJThf6OtM1W+6SUy6CE/JdSdyfSgJhA7czrrSi9TLmTqihon9LAsXsHrav7lEsC3vVUQ0iHDPytkrJtQmy75kl0NmGjCE99E3ajcMmKGXJNm12o2/dSCIhEnLGZc9R5ZhPl30Bq47g11fUxdXPU/8iscvssleJbg11gN67SG9NcisS0fhWdBk9OnOFnSL1TYhtzpR/83jAuuSyopBRkb7sKwUV2yT6DMG2cOJZij+wf21UIzt9G96s51T0yom4WYa6R94oZrxw68feS2HelSr31q5EYdY48jxEdjvG3yHkYOwGf6vKEwjHr9ThgUTI53yJH3Wd/K4UXOQysr0X+5xIuSdyRK7+n6tBOPXIFLk/vRX3NoEW5AIDdOhzDaoJ0CWebel1HWmtwtMzKjmUcFSbE8zy0adMGDz74IFq3bo2rr74aV111FZ5//vlS1x8+fDhSU1ND/x59Y2yp61pYWFhYWBwVeF7Z/PsL4agwITVq1EDTpk1DbU2aNMFHH31U6vpDhw4NvPAN/BkfAgVKCGWq4AIkTCMDMmP5ZASogLAfABBppGa+saUygwXN1nc66kve3yuzMJ4pGFbESSOjI65RoUVWoVohRlxpvugBOA1lZhgI27iWBdc0McZl+ZTayEzGHt3XiJg78Ww62D+LPCtRvZu8XPXfdZK2G+nYtsQxWRQYVOmtxfoeEgib/hWTaK+RjAOTShgSphbLbN+ppA3HSERq0gvjo5QWzDPjPWpmHvOojcttmwee0lnNuAIA71dVH8TtKOxI8W4Sn+nrF6q1UYfSBgvVbJvvnRHbRrKkFhCobLe3apXaJolqeVBVUZPO6tSh61zKDIyZN7+A3LHMLHYL1RXSNW727iYBLQkioRklp77M2vcV03hLVrPZkLh6nbBcLp+rOSalIHvzFePlrxdGyj1R0vDzdutrwVV6NRvgLRfxNJ+nUz5N90Puh5NJ48BU4U2g89glDAWMEeB2YkBryWw9b6EamxUHkRh3i34eqM4U18sx4xEV01AqVqmx72Z3D5o8Ej0bwSfXyAlBM6sO1YFhxsywpU48vb8S9fNE48WlNPrYJv0O4PpElYQ18fTYc8is0aQiA1IDKS5TxKxOM2LEdMXuUNowid+9GTqJII2eITPe6V3i/SymbpG+ymKBLQQs/pw4Kh8hXbp0weLF4ZLHS5YsQb16JV9UAJCQkIAEekkDQH58XKnrWlhYWFhYHBXYcMwh46h8hNx0003o3LkzHnzwQfTr1w8///wzXnzxRbz44osH3tjCwsLCwuLPCGZZLQ4KR+UjpH379hg7diyGDh2Ke++9F5mZmRgxYgQuvvjig96HU02o6IJX3wiW4y+uU2LdwAm1ooQbWIRqwjCRhuJIWvT2I8HyN4nq6/aEL0TgVe7mgXIAI/SbLd4jfoPmcixDjeaKcMtbqqhqt6n4kbCQz9DSXLrcLyxFUMmhh81UTn6d+n3vHBEKJrcnn5C6Wri1K1faiEI2wjB/j9C+BT8oF8e4RhLWirY4Uc5Jh1GKP/s8aJv1tVConU5S1Kn3q7hBenkS+oh2VdfRbSpeDUXfS00YU7vCSZEQUfQ8dR+mQEIHTdn9dJ26jl8mSpihDYkLzcyFa3GgJZUR35yrfqd+/LRI6PXTtPuoR/4UeyeI30xSOxUWdDtIiWxTmrxgkoQR4lrKuHUSVF/3fSsizYTGErqINFe0tVODRMmLpTS7n6rHOQmxC2dIKDDeCBELyYdEn8e3eVJj57K9Eio04bvAVwXAmEQJ9bUzglU6prdQ2M68/6rxVq6d7N9tRrWcdNjK30hi2gIJQ6zLU6HELPI78Y0vBcXQi36Wax+n6wI59UsXb5vnMVKPfG+I3veXayEk+eswCveq83ccuQ6+Dn/GZogIM9JW+hf7TQlHY1vk3BKuJMfXrTqck0jhHArZBiEkCpdEG5Og1LyLaIznTZPl1P5qu7xvRHSc2DJX9bMSPTf8Xtmr+uotIdEwo6rymPHWkUv0PHkXenPV816wWETykQwZG94GJZB2jssO2vx1IvYtnr8KABBXTc7Zz1X30dSdAYBIMwmV+Vt0CK6QxNtHApYJOWQctdoxZ511Fs4666yjdXgLCwsLCwuLo4xjtnbM3mfEFdPtKh8zjq5FUjhKXBDjBqoqlk4cpchSCq4RofqLJAUs7uJbguXC5+8CAER6ktjqC3IqbalYjxBrwRVvTVpdE5756doHNLMMzdK0mNWfQ26Hzan+h57xFLw1LmhKvEVq6Dhmhr6VUjPZxVE7ZIZqeVCfg+q8XDdDp4FGjpMKmzGa8RjHWOOOCQD+rCly/DpqRuo2EDdAfzOloWqXR2+J1BRxmwkrEszGyU3SX6MYDD9H2BGnrsyIjHgxNoXqd5x8gWyvaw2FaFQS9ZXqzGhcLwH4a3X/d8k5u91Ol75oVsZb+avsU88yjRi0BAybwEJjFhrmKBat8EOpeJtwzVUlduPnkei5HLlu6ll04MoLmjmzeyeJbU2VYE5x9aZ/S/1T482pJixZ6HnQx2IG01srlVyNwDh0neeJeBz56nlx2kn1VuM4y06bTiKdpxbW5j9we9CWcJM810Z4W/y6uMRGzhBHVadyPX0cYme4JpRmUvw1JHxtpsTlbt1mcp40xo34mms6xSZIrST3eFVPyJ87k9ronM2ztU2e1eIpUhfJVENmYae/T+6pcTXlZ9Ssu7/3Y/A71XnylhHzptO/3ZbHSxuLklsrJ2fvZxKJVpFxEoht+X6TdUHgOszPg2G/iDHi8ex9p8Sw0b9J3Z2EZuIofbhQMH9ymeznSPT1zwJbRdfCwsLCwqIsYMMxh4yjVsDOwsLCwsLC4q+NYzYcc1PG34LlB++WAlGxuYqeb/eWlPSe/ZKi3/OeF8GkcUEFxAfECFAB4MErhSSKv/ZeAEDRu48FbcMel9BJH+1N0PIS2T73e6HCV69WYYYWvYUWjbZXdO3ON+cEbbu2iiCy5mnq+IPGidCv/z5JS67gqNDEBfnzg7YV93QLlp2Kms6sTkLdzVRY7icliozUET+VrWOEVnYjalhUukBEfdA+AE4tEWZ+828JTXTpoSjiuPoicHPbiaNq0RfaL+D07rLPPUILF09VfXr7c9l+wOPkNGoElVS47ae71X3u/KGEylZf9U6wXPe2bNXnliR2ffm5YNnLU/cuLltcWGMLVwXL5vGIZks/Il37BMtDzlTlBmYXS1jty+fPkO01VT13mISLEuLUvWv0jDjP+hspPGh8QCqTL0K8UOHFPyo/hOPfF8fTaWdLGGPxF4qijiPvlEavUJ/mz9EdkX1+fK8Kx5w/RkJJ8/qPCZaPO1OFD/YulFBY2tMS/vtXHyUObx6TfV75PBXh0mE9f6UICf87PDdYbpKhzqVcTenzF9Nl7PZ9QI252HwRNO6drbZPPlHGo9uGHHyXqXVThkgBuy29pQhkfGMl4J34ijxXXVvLfUhsop1pScA79yMJWbR+90wAwLWXyXvlgWrqvZD+D/GVmf5vEXR2fEiHo5LFs6fvf34Klp+rpMb4bTvk9+dOkHfJiu9VCGm2L2GnFVF579zURPefJuTl75MS9puvV4aQVe4UobQRvhZ9Kz4bSyZKmKPx35XYln1tvrtdwlJjk9Q9G3G3hNomDpXQSK9H9HYJ8n7b9444ECeepHxWRj0h4u5qpJnue696V8cWk3B/nxqHbnUq7EieSH9/Xt2HN/vKz+WfGI/DjYLfJh54pYNAQsteB17pfwRlzoR8//336N27N2rWrAnHcTBu3Ljgt6KiItx6661o0aIFkpOTUbNmTVx66aVYv379/ndoYWFhYWFxDMD3Y2Xy76+EMmdCvvzyS/z3v/9F27Ztcd5552Hs2LHo06cPAGDnzp04//zzcdVVV6FVq1bYsWMH/vWvfyEWi+GXXw6tBPL2c2TWX27ItcGyv0bNOrY8KoLJKo8qsRaL7kB1YIwT6j5KwU2+XYSv3gyVnhl3ocz8lnb8R7BcrbFKYUu+7WrZ5w5xowzqktQQxsbMDGM/iKOok54my0lq1lBMs/JofXJeTFQzzl0fSWopz0z9TWo7t544E3o/fiLbZ6iZfTArBhBbKkyISVt0jiM3SC0Mc9LJefYbEZu5TdS6biMSJJKQsfi90eo8Bsj9AotYtZCy8PX3g7b4KyhtW9dnCaXwvjJCtdWvLfvZJKxE5Gx1773/TgjaQrVntms2IZFq/XB6onGBTJPUUi4zHvtK7XfHNzJbrXyHzGJMafbYF+Nk9x319WGhXbK4SWKZFkjzeInKut4vasb63dMiGj7paUr1XqNYFzNbBIDI6efJvlw1Y/Tni+jZW6yEhE5tSlfl9MYkdX0cNg2kmWfBp0oc6ZZnBpGeSyOSpXLv3kw5vttUCzm1yykAFI8dJ9sXqKlx/GVSW8pfpFOcq8lzwaXbjXhx5gUy7ts8my3rNlDL8856OWhrNoyYv+pqTBlGBQCK5wrzF22h1t09Tn5PqKXGTuK1ksLvTZVZv3OcdgVNFAfc3AdENJ16oboOu94XkXxKf0n3N2ObnWEnvyEMQ8/rlT+0U1VYNKehiGT92WrsONnEUukUXFRIk/UWiZDaSVNsg9tSmDvvJ3nuc19TItXUS8Tx2d8sz6CbrQTr3iwRs3JtHTdbpSgXf/lV0Mbpts5x+h1GTC7y1HvDad9TjrlY/obsfUMJRMtdJH1Ouvg+HG7k//rFgVc6CCS2OuPAK/2PoMyFqaeffjpOP/30Un9LTU3FpEmTQm3PPvssOnTogDVr1qBu3bqlbmdhYWFhYfGnhxWmHjKOenbMzp074TgO0tLSjnZXLCwsLCws/u/4ixWfKwscVmGq4zihcMzvkZ+fjy5duqBx48Z4++2397ufgoICFBQUhNr8GR8iQdePKRoj9H20pRYQVhd6vvhr5WcQaSjCKlN0DgD8PEVHOo2lOJf3tdD397ypKM7LIhLOaTj9GVlXlzwv/vQt2X85ofedWprW3U5Onfv2hX4Dwr4MQZ59MhURS6ICdKtU2MlbS/n8SULL+vphWP6ChEOyLhWxmdtWuzRupeJcTUnUt0Xt118owtf8nxQVHd9YqN7oOf1kG13oatPdwna9vUMEwINfVSG04jHii1C0QfwSkvqoMIXTrH3QFvuKQkgaBTPF+6Tcbf8EAMzo/W7Q1u6N7sGy96MKy015UUIHPV6R/ZuQiL9KHEVLo6+Ll8l1/mq8nP+Z92n6n8Zb4RgRKsa1UUJIpzm5Yi5RDpL5EyT8l9hNhK9mTLDrJo8nt52i0gP/BIQdMk1BMKeBjOf8x56SPjVQgkx260UN9Wz82F+EdV3uozCHLpYX+McAGHWhUPLXva9EmvwSLnjx1WB59yItdD5PnkG35znBsvezos/ZATPuEgm97BwyCgBQ4SwJpTlpOoRFobS97/8YLCedoMIlQQgECIW9/BUqjOI0oOtAvjmmHDyqkiMphZPyRqqxmXwViQhTVOiieLx4uES7iz+Qt1D72uRKGDJyxpmyvQmNUPiNw3+Bw+9iCdc4TbNL9i9Bwj15w8VRuvyDN6m2u54M2pJOVmPPSSXfmnoUssxZBQCI/Sq+LkiQcEr0jD7q9+/luXcqkd/LehWaLl4lYzT+XPHBMOFDJ5vCuEvIVXmlChNHOtBzq4tY5r86Trp0vITSnJr6nhEzkXTJAzjcyJ857oDrHAwS2/Ypk/0cCzhqKbpFRUXo168ffN/HqFGj/nDd4cOHIzU1NfTv0bc+PUI9tbCwsLCwsDgcOCrhGPMBsnr1anzzzTdISUn5w/WHDh2KwYMHh9q8aW8HzpkB+wGZRXu/StpbtKOehZILX8gZ0rAiXKq6pYjB+hQoAVy1NlLvwbAfAOBWVyIql2pU8L6C49SnGZn+knery4zDZ5dCPYv1F4mYy6kms0hfz/4KfpXMoqQ+khboVFSz9dqt5WPNbSdiXuPK6bQW4ZabTuJO415KjqkJepbrZmTIelTPxqmqUiortXeCti7j6ZrWaQoAiDSbE7RFsmRmiapq5u0kynhwW2bL7zrFLz6PjpmqmIgmrSVd1TgwAoDbSM1mW9aV8WD6CQBOuTQAgBcvLJJTgViy8jrdtb2wIycuFobCz1NMlUP3O74rOdtWUUJPM0YAILZUsUuJnWnmVlUYI6e2GhMRHkMVZGbp1FPX0d9JLJapFwPA17NgJ0X2GddcztmtqcWnNYgZ1A677XvSdawl48k4z7LT5gkxSan0t2/SfZdn0bBAAJBWRd2HECvhyBzI0SnIblW69uQgXKGPrpdD9UPMNeFzT+wsqaFOS+3gu1jYvEgPEeh6+9Tz7NYmUS87GGvm0a0qDKUR9QJAue56tk5jx83MBgBE266SbSpTCnE7Pba3y3XGDrmPhklhRoZL3Pv5+vpvl23cKlR9XLvA8vZJ3TNk3YqqL4md6BloooWfu3OlLYkY2CaKIXV3yP3wd8m70LxL3C7dpW0DORhrFi2+Pjky15TnwbBTDjsVlxMmx6QGO7VoG+3eGlefnFXpGTJp/E5TehaPBGwBu0PGEf8IMR8gS5cuxbfffov09PQDbpOQkIAEVuUD2Bcft5+1LSwsLCwsjgKsMPWQUeYfIXv27MGyZVI3YOXKlZgzZw4qVaqEGjVq4Pzzz8esWbPw2WefIRaLYeNG9XVcqVIlxMfH72+3FhYWFhYWFv9jKHNh6pQpU3DSSSeVaB8wYACGDRuGzMzMUrYCvv32W3Tv3v2gj7Pv4weDZae+5KebwnDG2wMA3C6nqfWouJUpOw8ATpqi8fzZVIzteEkzLnpDOWxG+5wftMW+l5x2E4aJnvx3+X0xFWMqrylD/krWVLS/fE7p56Fpb38DFXirQu6nOjTBws1oH/JQoGJ00lGiv01BMi5ixiY5hs4lLwunvKKKnXgqdEUF8gJamM7TmyUeCail7j2HJvwCofTN9rGp46StCRXF0v0LHX+9EpR6P4vfSuQE8Q5wUtW9LR4/Omjj62T679YkZ1YKMXmrFZXvNhRfBe97EdYiXY+dTeLQ62ZToUJdYMvPJfpcF3Hz91KJdrrO/molAOSwEYsT/fUqFOjNni0/X3Cl/L43V/2XC9ilUbhHF9Xj4oGmOKG/QPwh3PYSqgvCdxQqKx73pqybodPr08Wng0MzJtzDIRgOfQTFCVlgS0Jsb5ISwcZdcbNsb0SaW4T6DxVp1GO88JlHgrb46ymsm5Csf5d3SfT0U+WcdKFGb+Uc2WavhCH8JUpk6tQi4ao59nEUBqDxFNxHLkj4C/mI6NCH8Tva3778HAkH57//dbCceMOlahu636Gie2ac0TNqQi9Ouow3M4YAAOaekCiZz8k34cm6En4z7wpAnlfvV3m/OvWbyr5MsU669xwSNfc01D8zdvi5Id8b42uDinIdkk6SZ+RwIf+n9w+80kEg8fj+ZbKfYwFlzoR0794df/Rdc4y6xFtYWFhYWPwxbDjmkHHUfUL+z6BUQJ7NByK1InF7DGYC6ZRySLNpR8+I/AbkTEhMgqkDk95NXFA5ZdKIUJn9iDQSUV8sR7ua7iZh104tTNtL4r7N4lgazOjoS55nIv5aPQtLFFEcw1+vnR3jE0r93TAELDQMiXW106e/VcSyvhbQ+STECzl9mnTXbcSubJXZrqOZGJ/Kbwdl60HXnNwUvVVzS65LwlPTlj91lXTpJNqndmzd87X0Ke18+d2UkPfWUMpjFTHN89do1oHOM7ZcZt6R4xR75ezKlW2Wy75QWTED7ORp2B9/JR2T0rNRkF9yP8QwBM61adKnELOXrEWs9EIMzRKbq7HpbyTxYKYa+3selZlchY7dZXs9dp1kmeHu/lrGRurVGWqBnEBZOOsboSKlnIeE1jq925w7gJDgc89/1fOS9neagW/Rz0sypYOupjRSM0uOipg0JKTW7xCH0k2ZffE1yxYSmYfOT4sfW0r6tXH19PNypW0bsZJuyYRE36OJ2Sr9riCH3hCToY/v1BbWwS33rfyuxbY+H2eluCo7LfW9X7VQ9l9OnbNTSRgdJ0pMjUkXZubOK8nqIpdEvfIrfN1urBAAAJuFQQ2uKbF9PM68heq96u+ld1X+3vC2QKgWUtCn9cSSWfwpcex+hFhYWFhYWPyZYM3KDhn2I8TCwsLCwqIsYD9CDhll/hHy/fff49FHH8XMmTOxYcOGEo6pe/bswZAhQzBu3Dhs27YNmZmZ+Oc//4lrqdjVwcBpSA6UC4RqNk6hbtsTpM2EJkisFaLxNA3Ieer+NhEarl6tqMH0jRT2IafTAOVFTBWEYABEaqnCbsU7psi6muL1ddl2AIiQYNNbMkOdRxZRvUXkGltHF5ajcIZHAj1/sw4dUVjKqUhiL4Nd4qiKNHECDWhrCjMEBcvIQsCtK/4Zxq2Ri/cVz18VLMfVVfQ7h3iY6naa6cJ0KULFsh9CsH8Ov+kQW+5Koe6TKdTmr1eZWttz5H6n5lFYzPSFxkMgogTgVNAhjz25QVveNBHQpV6g+urXFs8Pfy55uxiKmEI8hmr2d8o+/QrUJ3bWDfpEj6oJIzSSa++kiVeG8VDgbUL0uAmTsIhTb7MzR65jBX6hmtAO0fxb1spASNWiY4eeAX+1UP5BmIXcTVm8iErqOfBXiKeH8ZUBgN2bVf/SWFBZUXmGeJtIYLtcMvOgwwzRthJmDYWotM8QF/ozRRIBAMbLIl+eUQ4RFS5Q1zGpj4R5/TX6+DkkKK8rAl1/JYWLNNwWHeT3fBWqC11HFmyadxQ/N1EKvZixQe+y2BoJ50SaaQHwBmlzqupQX4zeFRTiMuGQkB9Klohl/eo6pLxGrr1bn9ynN6vn1TifAkCkFnmbaH8St/mJcnx6hqGfExMyBOgdQB4r/ia5d5Fuyo3XmzMFFn9ulLljal5eHlq1aoWRI0eW+vvgwYMxYcIEvPXWW1i4cCFuvPFGDBo0COPHjy/rrlhYWFhYWBwx+H6sTP79lXBEq+gCwNSpUzFgwIAgHffqq6/GCy+8gJ9//hlnn332QR/HCDMBhER7xrGw+G2p7eJ203UKWPjEaZ4btACNhFVuc0lPbNFbp+NSaXU/h0R9xgmVldEkQjUMSLR596AttlKlV/LXvUcpk0Yg5/02RY5DQj5TW8KbRqmpumw9ADhtFKvgswCsFFFcaHaxi86/tnblpFQ5b5aqyxFpJ2mMfi65IBphG4n7IvVryMHS1czVzGCBsJDQpKyyAyYqySwTJp2XRclaAFilC50Uz+hqKvfRWj2kJoqTTIyQEeDmi0CY4WTp61MsrEHKJcTCmXGYK4ySk0llyI3glFKRve16FlqBRL10Tm4bxeIxo8SzUDML9n6eGjRFep0rxyynZrEh0XEVuQ9m7Pskeva0W2/Na0ggS66ZJn3a3yl9qncqCTZ1LSO/LtV2oZRzf9kc1WYYPPxu7FTWzCKJr72lUpq9xsVmti73wfQ5lH7cRWqSmFTk4hnkntyWRNFakM4urU4dcSc145kZGxasJ56nZu7+whmyT/OO4Bo1nCrdQF2TQJgOwJ8v2xsHY3+ZpEo7NYll02wov7/cyiT21YyYkybPmNtBmBboseHUoYrlehxwunzIjVe/I/zdMsa9dcRyrdcMB917Tsd12/RQ2+cIg4k9JHKtplJvA8YFCDPVtTPUfznVOaGkmNUlR9XY5+8AACJnXYIjChuOOWQc8doxnTt3xvjx45GTkwPf9/Htt99iyZIlOPXUUw+8sYWFhYWFxZ8Vvlc2//5COOLC1GeeeQZXX301ateujWg0Ctd18dJLL6Fr164H3tjCwsLCwsLifwZH5SPkp59+wvjx41GvXj18//33uOGGG1CzZk307Nmz1G0KCgpQUFAQaostmIcEnf8fOYucQrWTXmyDUIdRE1qgonPeagrn6JxybykJq46TstFRU7yMirlhH1GDhipnN0iiWwMfkZXicBnJVMKu2DKiYon+dnTRquJ3X5A+dSCKMk9R7Zs+EtFazTMpDKFFrixqM0XIAAl9mIJWAODHkaDTXCuiRd1W2r2Uinj5a8SfIqDv2W8kSQRyoUJbQacpdKGP780W34NI936yrj4uXzMjGow7r7f0iYSvRjgb15vKrdN9NJR9yMWVwhgB/Z0iol0OyxVPmqz7Lo9S3NXi6mnEobHFEhIwQjwnS8IVDl37wAeEHCIddkzdre5p8XopThhNIs8QLWoOFeojbxXHUdfRofvhTVP7clqKM6wJoQCA07rksxnXQ5xhjdDR2UjhPwq7OZnqPhh/GtXPn2V7EzakcAt2yziKdD1FrcdOnmbf5cgnhMTbRtyZ9630KZU8YowrsduYiuoxDP3PzzWFLIwDsPeNuCdHzspWm6RJ+MvbSO8VM85ovBX990fZvpHqk7dQ3k/RdjJ2/eXKndSbRo7Qdcn/SI/nUHgvU0SixjfHFEEEALeyGs9BWBrh95dbQ3uSVCDvjrkSKjO+PhEqtOfxONCiZ7eThMpMKAwAXD0mYhuoMjoJ4t22ejt+P+rzYzdbn0Lg3nb1fovweDoSOIrhmJEjR+LRRx/Fxo0b0apVKzzzzDPowKE4QlFREYYPH4433ngDOTk5aNSoER5++GGcdtppwTq7d+/GnXfeibFjx2Lz5s1o3bo1nnrqKbRvL38bL7vsMrzxxhuhfffq1QsTJkw46H4f0XDMvn37cNttt+GJJ55A79690bJlSwwaNAj9+/fHY489tt/thg8fjtTU1NC/xybPOXIdt7CwsLCwOBCOUjjm/fffx+DBg3H33Xdj1qxZaNWqFXr16oXNmzeXuv4dd9yBF154Ac888wwWLFiAa6+9Fueeey5mUymIK6+8EpMmTcLo0aMxd+5cnHrqqejZsydycnJC+zrttNOwYcOG4N+77757SH0/okxIUVERioqK4P5OIBmJROD9wRfk0KFDMXjw4FCb9/HwYPbpzRDRoRFBORE5hrdQC/gqpMkOUkicuFuzAk1LL+m98805avPjV0ifj5evQbe6EmR580SMFXJC1Wm4LAI1s/lIA9lP8VSqSaLhpIjIMyTW0qXAI3Ek0lz2myzXUjOq2DfkpngiMTk6tdenejqh49ZUsx9vOZWt/1XNfpw2Us/FCGQBBDNLb764nG7/WMRoVbppp1B2tdxOLotV1YzOaSTpf7EVcnyTRur/JrMwt6OqU1Qw8sWgLeF6qRHhLVPpsntf/jxoS76dnCHLpanjMFNBwlosV331y8nMzftNnEwjNdTM00lnAe8k2V6Lpp10mhnPV/fJ30LivwQSTTfvqH6fL6JjTp824sNIS0n9NDV0AGJAaOboTf2SttczWnLlNMJVbyoJCk/sIb+bOi0kstzyqKxb+e9qvITSUVfJdfIWK8bMbSPjndPLsU0LXmOlZwYEqbss5jW/UUo111zxNANZrnWa/M7iy02r1EK6MDahFF79DmBGyq0n7JU3VWX0uVkZQZuTomb1wTsHCD233lol6AzVhEqT+2QYCLcBiVFZwGuEu43lXcXizOCaEnvj/UJ1rtoqRiv25Tuy/5aqXg0L80PvSuOEPFPOybjFAoDbuHGJfvpbSXi7Q7vIziXX3upicRAz9yFCDCsx395MxTay8DXo0zz5o8mCcH+ftkAoIJfW/2E88cQTuOqqqzBw4EAAwPPPP4/PP/8cr776KoYMGVJi/dGjR+P222/HGWecAQC47rrr8PXXX+Pxxx/HW2+9hX379uGjjz7CJ598Ekglhg0bhk8//RSjRo3C/fffH+wrISEB1atXL3GMg8URraJbt25ddOvWDTfffDOSkpJQr149fPfdd3jzzTfxxBNP7HefCQkJSGBLXgD74o54JMnCwsLCwmL/KKNwTGkShNL+DgJAYWEhZs6ciaFDhwZtruuiZ8+emDZtWon1zf4Tf1fyIykpCT/+qEKDxcXFiMVif7iOwZQpU1C1alVUrFgRPXr0wP3334/09HQcLMr8L/kvv/wSqqJrGIwBAwbg9ddfx3vvvYehQ4fi4osvxvbt21GvXj088MADh25WxjMuTn/UtUaif6MqhNrQhuPRvo7LA4DTUKfN0ezE3yPxxV1b1Y1ISU+TbajWh29SBTklkerAGBMyTsE1+g9mP6KdzwuWDVPitJaYHqe2mlTGKlfRlz7PbM05VyD2JI7T2RqV6BPrIrxVmlXJWSXH5xoZpo3O2XHVjNStI7OcuCSq3eDpWW4C9SklTY6vDZBKrRcDiAlXDUrb1bVfnHI0lCmd1syYopXjSmwD0Gy3usw8uW6GZ+p+EBNRuEjYpcRL9cyea/zsYIZDH4tj9N1UCnsofZpmnoGmJbnkrB8A/C1mvEkMnk3jzIw0ZLpWhWrPVFX3x+EaPjrls3DOh3JuneU6mtTcSIbc73LpEgt2T9CxZDZV2yT33m2qNSFkwuWkyzgxrEWQ7gnA7S5VqwufUjOvuAvkuTY1fljLgHzSamlEsoWB5Gtiakn5c+Sl6pt0UMiY8Mh40BjmAUDxTMX0RM/tI9ubukl8v+neBDV+Ksl4cblukGEo6d47pJ+AZi79hWKIx4aHvmbBnFS633RN/D1aK5dEf1w0axJ6livIePcMG0nshZspqdZGL+WvExYqcpKkjHvb1Dj3ieWKsNmZrgHk1CmdiTa6M7cumc7plHovqyGttypYjrtE6QT5PX5EUEaZLcOHD8c999wTarv77rsxbNiwEutu3boVsVgM1apVC7VXq1YNixYtKrE+oHQbTzzxBLp27YqsrCxMnjwZH3/8MWL6HlWoUAGdOnXCfffdhyZNmqBatWp49913MW3aNDRoIIzUaaedhvPOOw+ZmZlYvnw5brvtNpx++umYNm0aIsRs/RGOeBXd6tWr47XXXivrw1pYWFhYWPxPoDQJQmksyP8VTz31FK666io0btwYjuMgKysLAwcOxKuvvhqsM3r0aFx++eWoVasWIpEI2rRpgwsvvBAzZ8oH8N/+9rdguUWLFmjZsiWysrIwZcoUnHzyyTgYHHGfEAsLCwsLi/9JeF6Z/EtISEBKSkro3/4+QipXroxIJIJNmzaF2jdt2rRfrUaVKlUwbtw45OXlYfXq1Vi0aBHKly+P+vWFEc7KysJ3332HPXv2YO3atfj5559RVFQUWuf3qF+/PipXrhySZBwIx6ywwptBArrukp5pnCmLP/4gaIq74ka1zRqpS+GvFpGpSQv011NNkmYSeqh5mk6ZJArTXycX2WmgU+DYoZKdHXXKJAsenVol0wI59dQIVoteEwEQ2lM9nDlK5LXmOaH0M14jwaimvd3dIiR0j6MaFToFN5Q2y1S1Fg87DSSt1wjsOO3XXyxfxainKVqqV5Pcht0ca5TY3qlEJe6LNG2cS7/rsvMAOX1y7RktlIzrTPQul2uvoR6YuDYSvjNhI/W70LkGHlPBm1QNIZfSXRN6kMB4qhK0cipy9AIRxgbnRH3yV2jBZg259qEUYOOGySmJTMmbY39KqXE1mZbWlH8m1fVhYas+FqcFG7fKxLNoDHH9k2ztmEr3LrElOYnO1s8jUfYhcaMJt3CtI3Ld9BeqEJyfS8/Qr98Ei9HTlZlhSFiqwzAu3UOPaiEZF9YdQ2V2V+lVcXMOwqjNWCxLL3qdys1hXH7GoydpZ9vZIrh09LvIbdhW+kSi4UDYSuOh+J3n5femWuTJouU+2bIvI2zdRWnwWTS2TWowv4tY0KnHltNM+hcI6ynsxI6pxoWaf/emiPjabaSO71IqsbdMxONGlO10PEXaOBRowtULSGtAwn6nke4r1zoytW3o/ca1sbxvv1Bt2XKeRwRHIUU3Pj4ebdu2xeTJk4M6bZ7nYfLkyRg0aNAfbpuYmIhatWqhqKgIH330Efr161dineTkZCQnJ2PHjh2YOHEiHnnkkf3ub926ddi2bRtq1Kix33V+j2P2I8TCwsLCwsJCaS8HDBiAdu3aoUOHDhgxYgTy8vKCbJlLL70UtWrVwvDhwwEA06dPR05ODrKzs5GTk4Nhw4bB8zzccsstwT4nTpwI3/fRqFEjLFu2DDfffDMaN24c7HPPnj2455570LdvX1SvXh3Lly/HLbfcggYNGqBXr14lO7kfHLMfIZEzpCZA4XOPBsumYmbcgOvl9+eVB0n0dLkwbhcxZTGzfrdxx6ApNvG9YHnQODV7e6bXqqAtroEwGf4izQYkkeEUCRVNJVyuA2NMyDgFl0WohgGJG3hH0Oax2Vq2+m/GW2IixSlwRVNV7YmCNZKWmzhV0l2jvdWMMDbpM+lnI5lRIVnNwmMzxFDK26FEsG5F6XP0b9fI71p05+VIhc5FY2SINautZqTeFpmt+gXCmkR7qZmSEQoDQPFbL0mftGjKrUm1QuqqmePIO4XFGvSBsCLet+r8HnxWxHu316e6F1uViNPfIuyH0yJbtl+t9utvlt8/GyWb9/nmH+p3Yk92D743WE7qombjkVOlLpKTqYyi8h9/LmiLbyfixFiOSm+MbZHZYKSKzBxNWrDbTcawt5Qq9+oaGpxOW/Q+CaDbqLHrrxf6Ntr/KgDAS6cLu3LF6+Ji7M1SrERQSwfAvWOEGbznTXXPmDUoHi1Ge0WrVV/im8kMKXLu34NlNFBjy/9tTtDkNhEWbMzJrwAA+r5C5kvaqM6bLunH+8ZJNkBiN/W8pN0jNZW8tZQerisjF46XWX1cZzH2QnktAqV0UxZF/zpIzfZbT5BnoPjTt9U2O+TaR04RBqBo1EOqH3mS+RB/3T+CZWMQFzlFZqSxH8dKn6orRo6Nvwpfkmck7kTdVxKpb71Prk/lR9S12DditGxTT52nYZsAwCWRaOzLt1TfdosIPnLKWfg9jHgYAOL6yzWPfaJY6a1fiki0ykBKLNim2plBZIGzeb9Huwhj5e9Q7xB/rbxruBpy3GU3AACKP5dUZBz838X/O46S5Xr//v2xZcsW3HXXXdi4cSOys7MxYcKEQKy6Zs2akDVGfn4+7rjjDqxYsQLly5fHGWecgdGjRyMtLS1YZ+fOnRg6dCjWrVuHSpUqoW/fvnjggQcQZ8zpIhH89ttveOONN5Cbm4uaNWvi1FNPxX333XdI+pUy/wgZPnw4Pv74YyxatAhJSUno3LkzHn74YTRqVDL84Ps+zjjjDEyYMAFjx44NqCQLCwsLC4tjDkfRMXXQoEH7Db9MmTIl9P/dunXDggULSl3XoF+/fqWGZwySkpIwceLE/f5+sChzYep3332HG264AT/99BMmTZqEoqIinHrqqcjLK1mldMSIEXAcp6y7YGFhYWFhceRhC9gdMsqcCfm9Z/zrr7+OqlWrYubMmaEidXPmzMHjjz+OX3755ZBELAam9gkARLuKmM6Uu+eS29ETVJiFBWymhgIgOfEhQWNzofT775ui9lOf/ClYZKqPaehhAKGS5DD1R6qJEDGoA0NuiiEfEC1C5RBMyMdjq869XyQhFtQTAVqcpsPcX+VrN+SXoEvYu5260HlkyLIRb5JI1DUUKbukkljMNeLIOuL1UKseifbanqn6wXUlCE7NBiXaIu3lPgSixkKhXV3tNdGv6gbZD5UxN6GVvh4J6diPoJY+5jahdbk0vFtdl0bPEEV41yyhtwOXSCqtXu4sEYQ69RXtzHVajOgv/iTyZagj4ZhobU1Ps+dFMrm4pmpBKNGr7Ftj+uKSD0e0kdS7cY5TYmOnujjHGhHsOdXpOlYmkakWAvK1PSufhIJ6ey57H2kh19mtpn1rjiN/Ce1WCwAmqd+tRbWM6Hk8rZUeM8kSfnSMiJTcaBO7UFgtW4dXN8l4c1t1l/3vUn2K6yk1cJwM6V+AdBFP8zVpcop28qT74HbU+yL3UX7v4EQV0ojkkXA0nyZoWkAcCJoBOE0lTGyuM7uTxnVrX2JdrqdTsYc4nZq+JByfIW1Z6r3iVKTzJD8Xt92J6pjso0T3xuwz2l2uIyrQ9q3UeKuStkra2sh7x9Rq4tpZPtV3irbT47UejR39OPkVxJXXp3ozfr4S7rot6f1h8afEYdeE7NypPhYqVZKX0969e3HRRRdh5MiR/192rxYWFhYWFn8aHMVwzLGKw/oR4nkebrzxRnTp0gXNm8ss/KabbkLnzp1xzjnn/N93zs6MO3ODRd9UtE2gdNocLVok4Sm7ahrWxN9BedaUSljB0esmkthmlbgD+ok67Y0Elf5acqqro7/gmUEwM6HtVG2X2BOTgmsEqICwHwAQbd5dnwbVg6H0xMBF0ZVwF1cJjhiB4SZJd/WJyfE10+Nvp33uU26RbnsRDPKMLXBETSJ2hwN+a/Txqf6Hqb4KAI5mt3yeGVK6b2l1RWJr1EyocK9cW3aBxUZ17xMTZD/MLmGDZm2IafCZYailZ74F4pTpxSiEqOt2+LvpOm0TAZ5TVZ2Tt0hq05i0YbAt82a5DoZd8rZQqnI5Scn0l6ix52YS+1GN6uFUViJWfwftkx0yjaMrHd+kq+7bQ2naBH+bZkiIKk5LlGvia3dUrkCMeHleHDMJiad+0LpObcUY+ZzWS2zn1uXqnMpzGrlJ2f6N6rTweW7V519eWAFOCzZ1WPa+MyVoK9eHUkMb61n0FmGHfGI49q1U4zGenkusV9eBxdlOXRKxr6axaX5vJGPXsJ0hx9AtlJJurtNGcaPd84aktpa/Sl9zOqYTT8/GSiVYj60gxitFs1h1KNWZ68AYd9Y0mUiG0qL1NfWX03PFDsL6XZw/VX5Pokmpr59xj5lgqobsrViljlmXGCXDblWqIm15IpwN3iH0d+CI4C8WSikLHNaPkBtuuAHz5s0Lec2PHz8e33zzTaha34FQmo++X1iEhPjSX5gWFhYWFhYWf34cNsfUQYMG4bPPPsO3336L2rUljvrNN99g+fLlSEtLQzQaRVSzA3379kX37t1L3dfw4cORmpoa+vfoKx+Uuq6FhYWFhcVRQRk5pv6VUOZMiO/7+Mc//oGxY8diypQpyGTKGMCQIUNw5ZVXhtpatGiBJ598Er1790ZpKM1H35/xIaDdGzeMkBL2lZoq6jDxxquDtvmPKmqxqSv59k49sp41YQii4Qve/yJYviBfUZdzPhLhVoUeIoYr+FVRrwltyWGSqw/q0I43TUqzb/pI9T0SJwOOi9EZJ9SQDwiJUE0YJpotuf35wyQ9a/UX6lx27JV+5FFNn64VVRG2taOE1q3WSuj1aB0VMtn6tYRoduWqfdWa+m7QVu7Gi6V/s5WnSNGvch3eWSNhggueUY6wSRUlFLZ1lfhf1L1c0fNuFQlLbXpWitnt2aWo5jpdJAQU106F0K6lKMD46eKmu2eCooAv3yv39uvvpADdvlkqNBHbJyGW8icKlVy0RIXLirbLfbp1vfTvlSR1ndjFddLzsq9OjdWxyneX8eKeqMJVCx4VyjujmYQJtq9RYYYtOyREFB+RcExCnLp+Df4t4RrvN3EDNoJQb5Xc29WvSYioZju17u4Vck0q362EhFfukrDVxFlTguWCCerexXcWmv+GIhkbXxlH1OUihN72vLhm5m5R51yjmbgCl7uGwrF71djnkKHbpl2w/Pc96vfvfvxatklQz9XuTyT0uXmVhPqqN1Bjp8Jd8r4p/kzeAW7lNADAlzPFDffMeOlz3CI1dvJmyLVLqCb39s41KhTwNIVBNzyq3j+5uSJUbpzwVbC8eIQeb57sp3lHCanGpmqnz3oiQs8fLV4+CV309U+QcPE382SS1/055edS/kQRbI57Rdbt4/0AAPjuUxnDGV+rcZJ1IwmN64iQecvzKoRToZ6EQ5NuJKfl1eqeTXtCxkPnByVcvWWUYr1f2Crvgn9sk+u8Z6t6rmsNJ6E0he1WvKHufb0N7wdtRevVuyq+llzn3b8JW17pYeXNlP+aTFaTeh5akdT/E/5iHxBlgTL/CLnhhhvwzjvv4JNPPkGFChWwcaN60aampiIpKQnVq1cvVYxat27dEh8sBqWVMM63oRgLCwsLC4tjGo7/RyVv/y873I/vx2uvvYbLLrtsv9scqlnZ3pEy63dPOEN+0MKgolelHkP8NTepn/bmympc4lnPwlgc6LTpHix7U8ar43QTl0Bv4keybnXFkLhtS68a6G1RM41QDYqYmnH6y4TFYZdDI5rzF5F2hlJwjQi1+BvR2yQOe1Z2rwWbzO5wKqCTrmZ/Pok0QzVZdKqgU4lSJnVqKZ+Hv1WcSgNRHaU/B4JGIBATm1oUAMI1LgxjNGeK7LOZpP35BdqxNV1mrrHFSvDpryUWqqGkyEbqqxlR8WdSPyRy6kWyT9NXUtA6lG5r6g2ZsvEAQiXLTe2K2Gy5j9FzxeDHpLQGJdwBOGlaTMe1MKrKB7ivx0tI5Ea1Y/xdSrRY+Mrb8vNN/5LfN63C78Hpz65OSQ+JD/U5+WtlW5NeDEj9D0RlMuD9IGwh9GuE63e4neR58Tfp+5MsIlFOow+E4DyT3CrPo7dY9S/aT2az3jrFuoRS70nMaurt7LpRHGwrPHar9E9fh8IXHgraouf2l+Ob+ia75V3hr6F7X0Gdi79Y2B+nqno2+F3gzRfhrHHL5TpNsXHi6ume2F3t8zdhPd0usi9/uxbP5wkzVvDJlGA5YcD56jiU7hp6BxhBf1x4UgcATjLVXiFxt3nezfUCgBjV9fG06VWku1iScjqvEeb6m0nAS4kFTlX1bPnzJZ2f06JNSr15/tX/6HFCzyo/T7GvFOMVOUGY5MQTyaH3MGHf+/eUyX6S+t9dJvs5FnBYwjFHYhsLCwsLC4s/FWw45pBx2ISpFhYWFhYWFhZ/hGO2gJ23Uqi9yCnkO6Gp7MLlQvMbWZa/nfL9V0p5bexRYYrYOvEJiW9PZac1xcw0t09fvE5F7XJI9LK/foUsb1b7dcgl0DGhi1oUjjD+DQCgHQtNITpAXFAB8QExAlQAaHC5iNEidZUPSPFMocydSiKO9Lfp60fOhlxePAhRVaQv+0IlBnOIkvdXUvlv49vAzorryK2ys6JGOVzDVLehjf1ccrNl59l96k7GlkpRPePo6raQwmb+CqHHfX2dncbk4ZJLHgna4ZMdILmMORLKlWwjL4viCco109st4sI4dmxN0RT2TBFU+sYxln0P9tA5p5XUTMGNyLLua/5aEQqGyHXtjRIq4U5+Mp6+9w7R654Ow7jZ5AGzRMYetJsuXwcu5uYZjwhPxLL+Tnme/AL1jLnkOOovpVBjRJ9fGvVpsYQ+Ij1UwUVvBTkE79RFzNhfgsewdg3N20KePxTiMuGoSFMq3Mgl5o1XBYWQQi61VVVYsHCMOOjGX6bdm3lGnCT7dNJqlOhnbGMu7V7tv3ihiIoTTiVPDf1sxWbItYtvKSLRIAxTjsIxUTn/IKRaJOPBraXCJTG+tuSNYvrskXeJ94sUTESc/jNC1449Q5wG2fp38g+i8KKTosI93mbyTNpAobqMFrqj8gw4iWlqmy1ynRwKMRXOUu3lziaX6yMBy4QcMo7ZjxALCwsLC4s/FaxZ2SHjmP0I2flfYRDS+8ps27iezv1FxJPHG1fPreSIulOEXWYWtneO7DPKLoimfHZdETwuvUaqB9Zu/SkAoNxgSj0mt0jj+snCLF+nF8e+kXRRp4LMFFwteCxYQzMWqgNjnFA5BZdnaYYBibY9o0RbCCtln7E5kg7rpKmZlJssLJP5ymcmI7ZIZjwR7ajoNJLUSre1CMOKP1Bi4WifAbLPiiR01LOaveNF5Fme0p59zZq4WmwKAIWfqvLhURKleavlOjtN9D3dRiwVresv1KmC1UXsyjWA/I1KrOs2k3MC1dWI7VSz5aVTZLbc4nphC4w7q7dK6um4NZXozuFZNwkqvbk6lbsGzXBpZuvNUr9PWSwpjWcvlpmpt147AC8Qti9uwPVyTloU7S2UsvexuSrN0qkmrIK3VoTKbkSvy661VWWWueV9JSJNyZTxmnzGJfg9jNAXALzfhLlz6qh9OeR+HFtFs+EvtNDwzL5yHprxYYaS6x/529TvH20XkeP1JH506ioGZNX9Mt7q/VPeC04D5XTMoufYbyIwjmpmcsdcee4qvTMGABD/z5uCNsOWAUA0RT8jNGtf8qU8902qK8EnZbCi2n8lRddbpe8J/bGb/KSk1vfwFOPmlBPBpnuivAN8nb7u9hIBbiBiZ8YkR+69V04xYm5mK+lUeenzypfUuyyro4xxfxe5l2ohNbMrHu3faaae64Jpkp4d30rGtmHusFlE8AFb2kCcuJmB3bVc/WlL+H6c9LlZ6YkDZQrLhBwyylwTMmrUKLRs2RIpKSlISUlBp06d8OWXQlfm5+fjhhtuQHp6OsqXL4++ffti06ZNf7BHCwsLCwsLi/9FlPlHSO3atfHQQw9h5syZ+OWXX9CjRw+cc845mD9fzYBuuukmfPrppxgzZgy+++47rF+/Huedd15Zd8PCwsLCwuLIwvfL5t9fCGUejvm96+kDDzyAUaNG4aeffkLt2rXxyiuv4J133kGPHj0AKP+QJk2a4KeffsLxxx9/0MdJaUthCBY5aT+Dxo1E5ORq4VMsVWh0fyXlsacoZ8rk9iTSJMoemxV16K0RujDrUjmm266bXij9my7wTuCS30ZsdSIVoKOiee5xSmiZOFXEYpFsoR6NsyS7oIZ8QLQIlUMwodDMr4q2dbO7yzZUxjwomhUS4mmvDBKTulnin4GqSnTozxVnWG+HrBvtrdxVTQl1AKE8fxOeSOqaIb/TvXUrKorWW02eHCd3VQt87SpKUSsjovWpeKCTTmI1LZR0SQwa0L8g3wwuM75Cju8XKvo1syUJSyuTm6QOXbltpdy6v0rdO5fK3ocq/ZniglSO3Q2JXdV47vXj/dKW1UfWNcURW5AYt4CKAmra3aWCjpE1q/QCXaeKcnyniQ5HFVIhv/kSM0jvrLaLtKAxREJGI4xlobHbQLxRTME3b7eEwqJtqAib9n5hAbEJB3GYlIsTOlqw2rpAnjGncVvpnw4TZNwr94b9KRwtSHWyRdDtVKaxVUP1P72r+IBEz1beKCy8jLZvESwbLx326chsRQUPq6t1K3eSsJDb+XT5vZJynPUWiiD85H9T6OUUNaHzc+kZIzjtT1C/e+KM61ZT5xHyssnIkN91GMYjQbe/LVf6f7EKzUSaniAH2iihEyPOduvJeGSPGuPLk3CihOpCfdbbO+QPZMJR3q/ijswFQtNaaN+amrTNkYANxxwyDmuKbiwWw3vvvYe8vDx06tQJM2fORFFREXr2FJ1A48aNUbduXUybNu0P9mRhYWFhYWHxv4bDIkydO3cuOnXqhPz8fJQvXx5jx45F06ZNMWfOHMTHxyMtLS20frVq1QJ799JQWhVdr9cpUkWXZ0d6xppySWtZ16Qk1pZUvEg1mq1q1sOpS2lplEpYNHYcACDa5+ygza1CaYF6Fs7uoiF31FIQODvyDL4WlfzWM7pob5oFVRaxVkTPlk0NGCA8U/BpNm9g2A8AiLZSH4KxZVLLg7/inVo6vTMmMyZ/g0o7DkrRA3DbdZdtKqn++eQG6e+Uj0szMy7NhRUA3Go6bbkNzUxJgGdSa112F01S+4xNEvFepDe5XppTmyPsRVy2fAR7mpXh9EPeP7L1zL+Yyt6vl1le4lXaHXWjXG9v5RzZl5n5ViIHyHpq5s7phewCa9gITvn2SLiKYjVe448npiBNZutoqdNsuew93UdHMyzMjridVUp67PMPpRuniOOp2ZdTnQSDn30cLEdP0WwgpS/zbN8IsZ00eS7YVdRpowWvuyTFl9NMiz8crXZ55c3ye56+JpRuGmJyNAvW8Qa5DuwK6qarZ7xoqsymIw1ktu6kqnvGTssgobZJYY52JQa3QI2XENuXIe+doJ36XG4g2QHUU+6gTk15/4ScdesppslNIXE0i9s1u+NWkfebt07qEhnhrr9ZRKTQDGekgYivfXIy9nX6uFtJ7r3T92/y+yrFysSIoUQdqs2l+x/7QVymQ+npmgF1WghLxULsgHmtTCnA+9TYdRrK/eLrFN9bJRsYtuqIwTIhh4zDwoQ0atQIc+bMwfTp03HddddhwIABWLBgwYE33A9KraL7/qQy7LGFhYWFhcX/J3yvbP79hXBYmJD4+Hg0aKBm0m3btsWMGTPw1FNPoX///igsLERubm6IDdm0aVOpRe0MSqui6333yuHouoWFhYWFhcURwhHxCfE8DwUFBWjbti3i4uIwefJk9O2r8v0XL16MNWvWoFOnTvvdvrQqunvXLIeRZDptSSxWLg0AUDh5TtCWdPxpqh8krMIackzVokB/V640UcghUkfTsvNln055KbPutFbiSC7mxnSmKTbnZIqw1K2oQhJ+Ivk/UNEoQ6dymMHtJI6r2KSEo2tHCaVfr42I8gInVPIBYRGqCcNEGkjow9skx/dN+IFo/BDtbdZbS2I24z5Kx/TWyTWPnKyFqyxYpH0GglAqzuXEkXBVizNj86Von6HHnZqlu2YGY6QKuU5SGCLYP9H4XATNeLs4tYU+dlJFsOl9p6lwVwo3RlrKfQoEgETTetO1x0xD8jgg7xUjPA0V1StFxOrvnCDbs2hwrxp77EPi51E4R/eF9+mt1sXgGlHoIFfE3RFdJM7bQUUeqZy8KWLmNm0qx6GwW0CV0zl5G+gZNB4+xTTeohJGiZxwouoTPSO+djTl0EOIDtf3dM+38lymnUfjTYeA3WzxnQk502qhtxG2A4DHHjNJ6h3gzxWBbuREJcz3ffJTySGxbK3GoX0DQOyLcXJ4PZ79deQr00TejV4pnhssBg6uBYdwUksRaseLsN/R7yC+Hz71z9V99taSE/GvFMbV78IoCU9jUz6Q/Zv25vSO5xC6EadvmCP7L6JxkKmOzy6v5jw88sdhUXFsumqP1pWQ5ZGA7/21MlvKAmX+ETJ06FCcfvrpqFu3Lnbv3o133nkHU6ZMwcSJE5GamoorrrgCgwcPRqVKlZCSkoJ//OMf6NSp0yFlxlhYWFhYWPzpYDUhh4wy/wjZvHkzLr30UmzYsAGpqalo2bIlJk6ciFNOUeKrJ598Eq7rom/fvigoKECvXr3w3HPPHfJxjJshgMAllZFwqoicAgEgiUB55otKaqbglKOZI4kCt45Rs5KKxwsbE3exlIU2ArcY1f/g2byphxE4BwLwaYYf7MeIGIFACMgz05AbpHb1rNZKUib9reJCaGYaIRdUSsE1DwuzHyZVDwC89WpW5JELYeCYyqXiK8os0aRP+htklrZtoszAa1yjrq+3QFJ4QTMep4F2ZKxMwtXtMvP289UM388R9idyohILF44bK+fR7iTZRve16BdhbNyuMgtzjHiT47DM+Gh2zCfBZNG3Ursm2lLXpsmUOi0h0Z+ul8GiPr+iZiCoVL3PzrRaeBpKq6XaLyZ11z2eahEl0va6/yGh8pI5smzcYUk4akTPxSQ2jZwsgknjMusQc7f7G7nPqXcogW5ojC6g0uz5+ppTqnNo3fXqmvlUP8Ttdlqw7M3RabCcMq7T8UPM2nKarWtxY/mexJRQSrhhK53q0o+gXgwA3ziIEqsZKnf/3eeqrYmk4DraTddbJuwIM6Cmng4zpW4HEmLr8cLvN2a03Mrq3nnE5DqZxD7p83PI/dSbKY6tTictNubrpPfP7EdQ8wgkzN1MLqcpdB9bqXHobaVxX48Yta3qefW3yXhxG8mk07B4ThNKY98gtbeCmlo1qcaPYQO3y3Pp5Mk1jbTLLnFOFn9OlPlHyCuv/LFWIzExESNHjsTIkSPL+tAWFhYWFhZHD38xUWlZ4JitHWOqmwIANlCqo/7CLvpWTLrcarouRUWqKnpcWrDo5+Wq36kmCChm6kZUnC9ST3QHgZkXAD9Zz2w5DkvptIYhcGvLjMWk4Do1RWvgraIUNzPjS6YZh0uprzoeHa1DM2CqQGqq4JoaML/vs0nB9Sn11LAfAODqfoXixMtUKp7TNFv2w2Zj2qDJqSax2fK1JB7u6VoeSCF9wzZiscx1ItaAmRqjT3GqyP4NO5M/X5ineNI6GCZl9yKJ1SaWMhsOVYetWIpIml4uTgWKpxsGhFk2StcNatLQzDRY3kJp6cVkjmdMyiju71M9G8foKoht87ZTnRejO2BdEsfY9bnwbNMYfvk75TicMm6uPbMzu7bIdUjVfeXx7KeJMZm/ZEGJPoXSMGtlqLY0une0rrdczbKj2Z1lG50OiwQyLqxEz4Bhb6jOScjQT5uR+cukWjCzCo6j9SHMmhJ7hDj9PBKLFZhwFTJDKZqUYF9bhAULmRwaOp/3SToYY97nkL7CnytmaYEWjCokl5bCbKpwAwA0Q+GkiXaEx6thC/0I6WXSiQHdqdgrNmgLVQSvpRleMjDz8FOJPiFJdHb8/sU2tS+fNWtac+Ok0TubzSjXqb8Jbj1if48ErCbkkHHsfoRYWFhYWFj8mWA1IYeMw+qYamFhYWFhYWGxPxyzTIj34zfBsttBKFrjgLlnooRoUnupdGB/6WzZAYU5DHXn76G0tC7i5ljpApWu6zQksdVCKkluRIMsqGSRqBE3ViDqUAvQvOVSGwY5q4JFp4ESu8VmiAgSuSLC8rcrEezWr4VWrf53SomsqL7IXRY8Mu1rUm8pBZdFqCYME6o3s1Y7pnLq51pKszSzADpOuf5ST8LfrVOVkyXF1WeqWIckvPlCL7stu8q6mtb2KZzjzZkCAEg+Xe6Nt1REgW4d5UBZ6UIKE3B6oAmzRPbzKNTV4ZbduUFT9KQT6fhqTO2bJlRz8q0DgmUTcvCWUEqjuY8khHZqkSjZOPDWpvAh3zvd193PSnXqlEf/LX2a/XWJbZzG4iActFO6bOxbJeyN9hJRb+y7cbJJB/U8cGih9uUy3mKzVSjRX09hoW7i9ouKmvKnZ8BfOU9+N1Q8p8DOFmGrERryOfnrVA0ep5GI0FkobUIXa0aKYDKjs5SYN8fyN1DacX0SkZpQZRGlfFOfnRbKYbTojbeDtrgT1HU2afsA4H09Llh2e/ZRCyTQ3ff4qGA58e9KOFr8zXeyzwvInXSuviZxEpqNLZJnMKLr6YTE45kk4tehHfdEea4DwTkL6+dRGQ0tGOUxGpvwiSyvV46m8Tf8Q3b5raSPR4xrKYXasJPq5dRVz26MtuEQWuRUJXr2tlKY04yDQgknO+SCve8V1b+kRiIaPiKwTMgho8yZkFGjRqFly5ZISUlBSkoKOnXqhC+//DK0zrRp09CjRw8kJycjJSUFXbt2xb59+/azRwsLCwsLi2MAtoruIaPMmZDatWvjoYceQsOGDeH7Pt544w2cc845mD17Npo1a4Zp06bhtNNOw9ChQ/HMM88gGo3i119/hbufCrT7Q/FiEe0lnisCOm+eMrJKqEWzQC1E9KuK4DH26fhgOdJRzaQKfpB01oSWZGAU08ZDNFvO/0lEfQn66zeSQbMoFmZpQZc3S0y23FZKQOv/Sql8fEzDlOyQmZvLhlr7lPBtV64IuKqRuDIQxnE9GFMFFyRKZCaC1jUiVMN+AEC0zyDVRpV5TTVfAHDLqdmsQ2Iwb6EwPY5JSaUZlanQCQB+npodFX4mtTziq0maqVNBzaQcEoH6hXo2nCn79NeIGNbXaZxBJWMA/kZK/zP9qCczJm+lCBVj36sZafRvV8j2s6bI72uVKC+aRhWSOR3XmJBto3ujRX1uY0pTpPok/i+K5XOaUeomVdT1FylWxSWta8gob502WKtGAltmRbT5FteuCbZdSYZ3iTK2AhaRDKH49wAkXjSmaQDgtj9VHZPEz5xeGTCCJOxzM+g6rlpV8vg11MyXU9+xJ1eWNeO2bZfMquvtkRm4eZ5jK4i1LCfPqFNLz6w3Uyr1Lkq9X6nGkZtK6fZcfdvshxjUoN4NsYEOGd15v81Rx8mjVGFm7sorBqXoK+ln4Tp5hpNP8Er2g0Se/iJ9H+sKyxYIhEn8zCydEXeHTM+qC+MU0aZ1zKS4nYUtNEZ5zFRwbS3DOPE+nQokzNUMiHn+AQSp1H6WCIlj498PlhNaaUZoKVXmFZLP4k+EMv8I6d27d+j/H3jgAYwaNQo//fQTmjVrhptuugn//Oc/MWTIkGCdRo2OrKudhYWFhYVFmcOGYw4Zh1WYGovF8N577yEvLw+dOnXC5s2bMX36dFStWhWdO3dGtWrV0K1bN/z4448H3pmFhYWFhcWfGZ5fNv/+QjgswtS5c+eiU6dOyM/PR/ny5TF27Fg0bdoUP/2kcsOHDRuGxx57DNnZ2XjzzTdx8sknY968eWjYsGGp+ysoKEBBQUGozWuViYSopn7Zn6OxFlERpe8bfwnyf4h0F+GYoSHjGkk59MhxHYLlmHYKNA6NABDfWPLw3YwM9Tv7T3Ceu2Y7I+1OlTZdo8JpU7pdvXHodCtS7nxUbpfbXvkE1Jr6btDGFGdQI4JqkgQlsYFQbZzgmCRmM14gLEI1YZiQWJUo3MBrIp9qv5QjjwbtY+JWk9BJyANBX7/4nhKGcNkl0fRzH1HihrZlgVodcX4N6tkQvevWIJGqDmGF6snQtYmep0ICgWcEAJ+EflHt8Oltkesc1IsBgno3fmoanYBX8jyIcnfa9yzZFiGPmPLaMZWGmFORwhSt9PUjl1WH6p+Y5yXkx1Jdj+0k8nog/w1zzULjicI9zs5duh8S9opkSC0RT19nt66ELD0aO9GW+jngkOM8clzV9XqcKhJShHGxTZQx5rDrsEajVuLCyk6g5t448XJvnXocKsxW/ahB57xsDvVJhwdzRURq/E5CM2L2iNFeRDyeovUlzBDp1kstTPpc+sTvFe29Em0vYQhvD/kLVUhT25BXjkOhvKD2DYU0HeNzRGJZP0fCrMY/ySHvEQ71+TtyVRsL1smRNdJDCWtjs76S3yksZpxzOSzFYWJHe7NwHSnjhOokp8lxzu4fLBe/+wYAINr/bFj8uXFYmJBGjRphzpw5mD59Oq677joMGDAACxYsgKcfzGuuuQYDBw5E69at8eSTT6JRo0Z49dVX97u/4cOHIzU1NfTvsa9n73d9CwsLCwuLIw7fK5t/fyE4vn/4pbg9e/ZEVlYWhgwZgvr162P06NG45JJLgt/79++PaDSKt99+u9TtS2NCsHYWEuLV13zsq3eCZqeZEnc65Gzo/aYYGLetsB/8Ve9rl0MzMwIAb7l85HxzhRICdv8nVfU8+UzZ3sxYefZDQkBX1/DgGhf+Gl3LhNgNp77MHH1dHdJtLimuofRFnTbo55LgkbFSCUtji0Ro6GbJLNJt111tT1VwOb0xEPNSBVAjQnWby2w22uV8+V2LDmPfSP2RLW/K9lXv1QwKpxrniOjP7aqYIqeipH56M7+W/hm2I17urdumBwBgxdmPBm31P/qXbK/v49KbpF7NceOukeNv08cnQaPDAuOlWjCZJwLhTU9K5c7qr6tjsTDU+1Fmxm5zxQ45DbLlPPQszvthohzzuJJ1ffxlS+T3imnyu3EFLZ9GvxMTYmbO9DLzfhAxsVNbjwOaDbtZKrV05TlyHTPekPpIJp2Xn5s5p0jphVbjLlS/Uw0bkz4NAN4aJS50W8gYj7ToLr/r1Hp/hczquXrs1svvAwCkPyn3zsyWmcUKVbqum6EWKE3dqVxbttcMqTeFWAcShxsGgV2F2Qm18C2V1pxw7eVy/E063X+TCOedJpIe7S8S0bOBSX8Ogf8QkcAXRkRKNW5ik6X/7vHqfcGp0LFPxwTL0YuuAwAUv/+ibFNbi7dbyvXm++wt1eOd6xfxu0IzIN5csRNwGjaTddera1I8Xd6p0e7kfLtbsWhua6r5RGyqqRvkNpF7E7jprhHGhl1cka7f5cSoJJ18NQ439j48sEz2U+7W18pkP8cCjohPiOd5KCgoQEZGBmrWrInFixeHfl+yZAlOP/30/WwNJCQkICEhIdRWEB+/n7UtLCwsLCwsjgWU+UfI0KFDcfrpp6Nu3brYvXs33nnnHUyZMgUTJ06E4zi4+eabcffdd6NVq1bIzs7GG2+8gUWLFuHDDz8s665YWFhYWFgcMfg2O+aQUeYfIZs3b8all16KDRs2IDU1FS1btsTEiRNxyimqLPiNN96I/Px83HTTTdi+fTtatWqFSZMmISurpKDsj+CtEedCt323YNkI8GLfj5PfmyuRqVORfAd2URhDOyt6OVTuPUso1C49PlVtTai0+SbxWHCq1gkdG0DYgVNTuA4JAQMRGBf0ogJ10F4boT5RcTB4yrvEny0UaOT0C6V/mpKPsEthVaGiTV9YwMZ+BEExKnqojA+IEaAC+yl610IcLCufSQI0fZ1Qh8qUZ9LvlbXvA4lVncayLyNMY6rW9LlOnzBTFmyjQ1yZZ5NHS2XxK/DNNa9CHgYpUngtpl1w3ePk3lW9hMJqm7UbJwt0uwm97lTSoSWm143QjkTJThqNHX1vA0oZ4fBicOwlRO1rcR8AOEkq/MDCVy4NHwiIKYxhaOs6/UUIHQgWARmvFGZs0pvCILla/FmR/EhadpFjVlfXyTjYAoDP9L4pLFeJBI/kO5F2iro+Trr4xhjhrsNhShJXmmsf+1LCtW7vbNnenEsF2qa6iJJdLfRmESVf0/huyuMm9NzUVO8xpw7ZDrBA2BTgY+fXVeTCqserv5XClKFCgtrllUI0TjyFdNN1sU66d+7xFPrQgnW3XXvaRoVjWDDuF9B4rq/Pk4XUdE6+Fry7LUlkz8LSFipEFE2iYpc1RDyOOtpnhLxyQr42WWrMhIT35t6wA6/xYAGAbTrEnimh1SOCv1hmS1mgzIWpr7zyClatWoWCggJs3rwZX3/9dfABYjBkyBCsXbsWeXl5mDp1Kk444YT97M3CwsLCwuIYwVEUpo4cORIZGRlITExEx44d8fPPP+933aKiItx7773IyspCYmIiWrVqhQkTJoTW2b17N2688UbUq1cPSUlJ6Ny5M2bMmBFax/d93HXXXahRowaSkpLQs2dPLF26FIeCY7Z2TOxLEWNFz+0XLHurletpwUQRQSU21q6cO8QZ0V9KaW211Fd58Weyz7hLRRwZV1+nljbqGLRtuPihYLlSe5ValvCvm2X/20So6O/Q5eq5VLUuw+7NF5dWtw6J5nTpdY+Em6gjNTCQpNISi34V1sDtSmmiug6M06idtM0VcaZvynOvXEDbkJiumhY68oxEszMh0dhUEY4aBiTaqmfQVkzix9iEcer3viLkAzsnauFu0Zj3grboWSQA1v+NNJBzKv74Bf0jiTB/JsFnE9UnTsOMLaa6GOu0e2oNSv1cIy6L/nIlDvW7nSX7rCOzcX+FYqpiC0SAG+0l5+/na+Ec1wVqpOuLcErjRvndX6yO79QlxoZLu89QqavbP90YtFW+WdJUfZ2y6q8WZ1g3W0SHwXrk/Oob5o7qyXh0HbBdMx3kWBqpIbPtovd17ZnGcm3cU84Llo0g1Fu7UPa5gcZzsn42aLx488Vtd990NTYrnC8MgJerxyu5EzuVie3cq2bGa1+UZ7FuA6lL5NRV43nZQ3KdGtwkTsp+K8WghsSk+SJM9dbp2fYaclTdpwSj0T4i2A4xVlWpvpNG4djJwXJca/Xc+ttyZft6woY6xqW2SNLApzwmrEX3RCVADrnl0tgxIn6nTobsf6NidT1KJfY3U50WzYqEBNvE4BaNGaf63lOYLySSi6wW3/v8x2k7udxW0Wnsy+V3p5k4KWOneq95+6juzxZ17d22wjp606dI/3apdV12Ks6WZ/h/De+//z4GDx6M559/Hh07dsSIESPQq1cvLF68GFWrVi2x/h133IG33noLL730Eho3boyJEyfi3HPPxdSpU9G6tXo/XXnllZg3bx5Gjx6NmjVr4q233kLPnj2xYMEC1KqlnrNHHnkETz/9NN544w1kZmbizjvvRK9evbBgwQIkluaoXApsFV0LCwsLC4uyQBmZlRUUFGDXrl2hfyUyRAlPPPEErrrqKgwcOBBNmzbF888/j3Llyu3X+mL06NG47bbbcMYZZ6B+/fq47rrrcMYZZ+Dxxx8HAOzbtw8fffQRHnnkEXTt2hUNGjTAsGHD0KBBA4wapQou+r6PESNG4I477sA555yDli1b4s0338T69esxbty4g75k9iPEwsLCwsKiLOB5ZfKvNG+s4cOHl3rIwsJCzJw5Ez17CgPrui569uyJadOmlbpNQUFBCaYiKSkpcC8vLi5GLBb7w3VWrlyJjRs3ho6bmpqKjh077ve4peGwh2MeeughDB06FP/6178wYsQIbN++HXfffTe++uorrFmzBlWqVEGfPn1w3333ITU19cA71Pj2LaGfe7ZeFCybUuKPzxTa83Yd+ij+XKjW4nW5tDcVppj1teTGd2o+JVh22ylKn90i394hFFeX8UqE1fHEb6QfW4VuLJ6/CgAQqS+Oq06SEoht/1io4rgkEbsmt1FiuUVj5BbVqicOkoY1f2eN0M/XXyThFFPEzG0tA8TbQQK7nWqQeOtkm20TRdhVvpYKL5TrL3odU4yOXVDZB8SIUDkEE20q3iy596nc9/InkksqF81brqj6394TEWab9hRC034CHhXSWveSOs9a5wvlvO9T8fFI0mEWt5qITVnMG1unQmURujYoEFFdbIO6j066PFROprhVrrn7LQDA+/skNHFzB3Ho9PV+94yT0Ea5Nur8I23EM4M9YExBtQilpTvlhYqOrVYU822b5Xl5/lcJ6xXMU7/vWi33odrT4gDsr1LreiuFcl/3kdp/neskBJT3jJRrT8jS95yEd9ETRdz41ssq3NX0cwnVtWtPVLj2YfGXSDhm6zsSBqnYWdH3TpL0ed1YCX1U1ppJb5nc29iP2v+H/G9CXj17ldj1qt1yP7/4QUKSkaaqf5M8uY71fpGQQFyh2q54iTyjW3+S3VcfqK7V549KOCRDP5fNe4gXzpqH5d7U/Y++z+R189z38l4YuFod/7ul8lz36j4nWN65WF3ncukSjhmTJO+tDp+pceaWk/GWdJmENPd9ofpS7mby3Fii+0ehi/wvJRQW30r1xaVwcuF7MjZe+lb1//rm8i7ZPVbeySkDdbHOPBHw7vte7n3SSUrQPudxeQabdJZsycTzVeKBR3/YYlvVOCMpfxCCAYCJz6lx2uPkOXKcK3HMYOjQoRg8eHCo7fc2FQZbt25FLBZDtWrVQu3VqlXDokWLSt2mV69eeOKJJ9C1a1dkZWVh8uTJ+PjjjxHTxVorVKiATp064b777kOTJk1QrVo1vPvuu5g2bRoaNFDFDzdu3Bgc5/fHNb8dDA4rEzJjxgy88MILaNlSXrbr16/H+vXr8dhjj2HevHl4/fXXMWHCBFxxxRV/sCcLCwsLC4s/OcooHJOQkICUlJTQv/19hPxf8NRTT6Fhw4Zo3Lgx4uPjMWjQIAwcODBUzX706NHwfR+1atVCQkICnn76aVx44YWHXPH+QDhsjql79uxBmzZt8Nxzz+H+++9HdnY2RowYUeq6Y8aMwSWXXIK8vDxEowdHzux7c6j8T3Uu965StorHkUtgnwsAAP72TbINi+KMKI/LX9eRVL2iDxWD4lYQaipypoic3DpqZuytFZEnNlCZdCPSopRLV6eEhtIkTWomACdNzS5in0hMz2lLKXDaKXDLM6JWrvJgX1lXp5mym2K098XBshGBOumUtktCSU8La/3dVDfDpA2mycyLU1NNCq4RoALA3h9kFpn2rmJCin+S37FXZi9OLTXd5VQ7k3KoTkCn8s0QMaxxefR+lLoUbmcShur0Se8bEatGzpZU5iAVmVMmKeXSn6dnX9Wozsr3U6RPeubgpKfJ8dtTXaKEkuIsf76+Z+TwyHWJTH0RTt8OCYR1Krj330/l5+PF7M/TTIdTPUOOuYZmRLq+CKd+eosUy+ZvFObJSRfGyc1WzrTs+lsw4plgOaj3wwLfPErp3K3LuR+XLX3Kp7G/TKWp+tsoZbulpMkHKZ+c+q5TxrkejL9cBOdOhkrtLBj5fNCWeLNU7/Y2KhaPa0qFYFxiuabKTmEL/PVqe3ZHjXTtE9o3gHCKrkkBpnvL4m5H1/0xrCAARE6Wmigmfd37+TvaRliuoNYSvUu8eT/I79qF1ltMrKpJC6Z6MebaAnJ9/CXCjniLyDqgRQv13+OEGfN+k9pdTpYWtHKNL3as1o60/jpxCPbXkQWCTixwqS6QcXQu/kpctp3KMl49zQBEekpV98Tj5ToeLuTd2e/AKx0Eku/74KDXLSwsRLly5fDhhx+iT58+QfuAAQOQm5uLTz75ZL/b5ufnY9u2bahZsyaGDBmCzz77DPPnzw+tk5eXh127dqFGjRro378/9uzZg88//xwrVqxAVlYWZs+ejezs7GD9bt26ITs7G0899dRB9f+wMSE33HADzjzzzFC8aH/YuXMnUlJSDvoDxMLCwsLCwgKIj49H27ZtMXmyZFl5nofJkyejU6eSWXGMxMRE1KpVC8XFxfjoo49wzjnnlFgnOTkZNWrUwI4dOzBx4sRgnczMTFSvXj103F27dmH69OkHPC7jsPzVf++99zBr1qwSOcWlYevWrbjvvvtw9dWH39ffwsLCwsLisOEomZUNHjwYAwYMQLt27dChQweMGDECeXl5GDhQ1bK59NJLUatWrUDcOn36dOTk5CA7Oxs5OTkYNmwYPM/DLbfcEuxz4sSJ8H0fjRo1wrJly3DzzTejcePGwT4dx8GNN96I+++/Hw0bNgxSdGvWrBliZA6EMv8IWbt2Lf71r39h0qRJB8wT3rVrF84880w0bdoUw4YN2+96pRWwK160DAlRJdKKtiX6XYc38n8TYViFyzTdynnw5AiIYkUTeiTui54ktFrc6bpMeVZ20FY06ulgOdJsjvpvDwmH+OwBsVVR3KXRvv5qCuEkkNeDLlPOJeIjGyl3X5emT6ooFKcpPQ6IiDbaZwDtk/wUtJsk0+veAhHtIUWXKU8msbAOl7CzYmwqUX3aCZV9QFiEasIw0eP7yDG3UNhK07XetG/lnM6iQlimredFssl3SsAW8tRYRy6uLburhVYilOLS6N42LeBNo3AIo6baryllDwDOWSJy9b77EgBQvFjCewk9SzrnMj2NmlosW5vdQ2l8G6qe+ulEqSCjFmfuGv1L0JbaVJxlTeiGQxNuS3EVNo6t/nYJvSBPHdOpTq6+8fL8BuuSE2b8+b2C5dhULRLdJSGY6NmiBAx8JcjPxV9PCvosFdJ0G8l5+ovF68fXvhgm3AEgKDzJiLQ7TX7X4yl3rpSIr0bj3a2nwhD5998p5/Q3mQkad1d/O/mALBd3UxOi81bJfXBSpqhtdWFFAPBmiWAdOhzDTsWxJfJcR49Tx/SWUzgiizyNTKHFeJFk7rzrzWA59T8qTMzhPbf5idIXXdAx5Oiqw05uRgtZjz1idHiSry37ucR+UN4rJpyqtpHxbJyqvSUiCPe3kSdRDXVN/GXkh1JZwjWOLtrH7y+/QImWI936SJ/pXeJ9r8ajuAMdGRwt2/b+/ftjy5YtuOuuu7Bx40ZkZ2djwoQJgWh0zZo1IS1Hfn4+7rjjDqxYsQLly5fHGWecgdGjRyMtLS1YZ+fOnRg6dCjWrVuHSpUqoW/fvnjggQcQFydj75ZbbkFeXh6uvvpq5Obm4oQTTsCECRMO2iMEOAwfITNnzsTmzZvRpo2or2OxGL7//ns8++yzKCgoQCQSwe7du3HaaaehQoUKGDt2bOjEfo/hw4fjnnvuCbUN7doMt3c7wpa8FhYWFhYWf0IMGjQIgwYNKvW3KVOmhP6/W7duWLBgQanrGvTr1w/9+v2xxsVxHNx777249957D6mvjDL/CDn55JMxd+7cUNvAgQPRuHFj3HrrrYhEIti1axd69eqFhIQEjB8//oBfTaWlKxX++3x4m3PV/5BYzdSbiO2T2Y+pl8BluP3lIsJyGmlhaR79TvVLsEfP4tglcIOIFyNZaruQyJRmCkHJcWY9dI2JkHNgSpr0qVI1vU9JxWP4G9TsbOsqYVxSWMio6zmgIimqaWYdCOxoZssujNimRLw+/e5mKoGYR9fGJ0fXoA4MuaCGUyaVCJVnLC7VbDF1aGKrqG7GXhKpahGpT/cx2P/+ZiBG/JhLbrJco4LFyAa7hEXzZ2sBH4nifPrd26765+XSdSQEad0RmpOZvrLY1JHfPS14NHVIAITuXZCf7Qj1GxJdb9UMAaWB+nwdTd0NrrVhmMZ8Gdc8Hn3DYJD7pnGtBABvu3aorEI1ReiYps/+VhEqmxRaAPBXaWEsZwDQePT36WeMGaPg3pMIcysxCLp+yvIcYR2qFtD5GXE2uemymNYz7A85soawVV9zl9415voRc8WsgGEVfHo9FObQu2SRekeEnnu28TbPI6Wj+h4d37BgO2g8ECsbnJ9L52zq0ZAgO/RcmHvH93O3LPsmBMFjlMeOdrZldoYdV4P759B5kOOqqZPjJFCb6Sv3aQ05rupUb38ZsUhHQJhqa8ccOsr8I6RChQpo3jzMUCQnJyM9PR3NmzfHrl27cOqpp2Lv3r146623Ajc4AKhSpQoikZIEWkJCQon0pN0R67NmYWFhYfEngv0IOWQc8XSUWbNmYfp0NesxpicGK1euREZGxpHukoWFhYWFxf8//o/F5/7KOCIfIRyP6t69O8rCmiTamwRoFAYxgi/j0gcIJe6kUWn0dlLe2tXlwaNdKZ+fSmEXTVVirmgtKT+d1EeK2ZmiVBxa8HeQELKZKuwUosRNWXoqaOVmiS+CX6ToxmgvqUDs1JSPNkfvq+7lRGtyCEjTshz6YB8QIy41wkwAcBpQ0ShDdxZTmfQ8HW4h2tXteqpsX1l7n5D4j/0O3Ga68BxRvSYEAwBuTSX+jJ4sPhssyCwtdOI0U94EscmfBW2RU8+VFcx1WLEqaIrrJsXFvKi+T1wCnsS4TqNtJY7tzxPBZOQEJfqLNKcQDp0/9L6cLDHsc5IrlljPKZcm25SnZbNPDvXpkEiFfrJPU24dAPyqVO7egMIYjvG/qCBjHMF1FF+ZSDPxfYAOhXE59aIvqODjWVocniL7DFHu5vgpIup1W8p9LrUYHZV7j32ifBNc9pfQz3povG2j8KD2U+nwdzn3wEcDCMK4ISdjOqZTVS37cRTWonvjz1O+GZHS0hH5ndSc3hVmX/THqtxF3eV3/Y6JHkcCWg4FGrdgEg1XIPG6CXmYcwfCIlMnUwm9/V009vQ9davKufup4oIZGs9mG/J7iaaW9LUx3iNqB+pcWTDuZJbU87kdSDxNz6PZr3m/AICjr6+/j7xoKPwY6aGFwST2t/hzwhpzWFhYWFhYlAVsOOaQccx+hHA6WdFbzwXL0TP6qIUKVPp80scAAKeVlIDn2YWXo1LD3KZSippdBt/+XM2+Lsx7P2hL+Me1wbKTqI4VmzpOOsjZPibdlWqeeLNVGqop6w6I0yUAIFfNrJ2GNKMgGLdJtwqli86ZIr9rIebe8SLMSuqaIb+30bNcdrWsTKxMJZ1WN19Knxd+ptJMA3dMAG5Hceo0Yt6iMe8FbaE6MG8qpoNTcFmEahiQ6ImiyC76WFw5jVCRXTWj/ZS/zNQRIlbterbMoryfVArtxJdkqJ9xqqQCBm6NsymFNktqw/hr1TkVzxG3yNWvCuuR+Yqe5SbKjKvo7bekf21UyqXbSep3eL8pt8vCL+WYcc0ygmWnvkpZjH0n18lJI6amgZrNO01o7ORweqN2wXVEN1X8hriGmlorXAPIaaVqBK15XWa9mZJlCsT0tScn0PffFWbtop5qX8wGxr58N1gu+EnVCkk8S9w9HSrDHgguWUBcUWbzeT8phqRChymyjU7TZHdPbzoVd2msWL7ISSfJPneKYNOUq3friGtwyC13tXp22DGV0+wLdZ2Z+JbyXjEOwsWfjA6a3HZUt2eZcvL0Nwrj455yhuw/ot8btYT19DaJENw4Qju1hdGJtCZxphbr+vnCShR+IDWzEm9V6ciFz8t4iLbQKbKU5s6MkBE9ewvIjZbKwzv1FbvizZF3hUPvX+MqXPCVpOjGdyPhrGYZ3Wxhp9m91ftNMY9uM3nnGxfa2AypJRTJpnflFs2s1ZBzOhLw7UfIIcOqOy0sLCwsLCyOCo5ZJsTCwsLCwuJPBcuEHDIOWwE7g4ceeghDhw7Fv/71r6CA3caNG3HzzTdj0qRJ2L17Nxo1aoTbb78dffv2/eOdEfLuvyRYjvaT0IjxCdn3wBNBW7mHHgQAeOvIp2M9OXUWK6o5tojKeF8qpi/eXB2aqSq0rfejuCC6LbPVf9lxkEMrmqJ1GmTLNrpwXGyF0Pzs2eFUy1Bde+uloC3Sngt6qT5velTo5xpv/ke21wJA9vQw4kIAgVjMCGSB3zlDalraiEUBoYVZ3OfNkMJwTmPl2smiXGzKKfG7EWYCvxPrahFq7KcJQVvcef+QY2lvE5/Etv4aHYbgonrkI+Iep6hwb7lcZ+OECUg4JiQMpcJqgc8HXzvy1yj+bKza/3bxbUi4+S5Z1zimzqNwj6bMnbqNgyYnkYR4mp52ytN1YqdR7V+x935x7U1+UI4ZlLunEJFbj6hsI7Iln5LYD7pIY0sSdK+U58VtpqjykAh0q9xbb4ESPzoV04K2yAlS5NEICJ1KVAiQr4lxM6b6Uf4KCjEdp/rvpEkYwIgrjfuvapTr5Gpx5obzbwvaqr0mfkPGmyX2nbj+usdLiMgUWeMxyl4/TmV1LkUfSbExIyQ34+735xlp0V3th/pZ+KQYPUX7nqf69LkUJ4y7jN5FK35V2y+RgoT+TgmpRk7VBdvKUQipnAitjU8Lh5WcCvpdsUlCbf4Wem4p9BP043sRgpvwaLS/lN7wpopo2T2xj2rbSN5M5IvjVFOhn9hkCXdzKDHSXV2T0oTpIcdlGs/F76l9xV19Q9CWmC3j8XBh96AzDrzSQaDCs1+UyX6OBRzWcMyMGTPwwgsvoGXLsK7h0ksvxeLFizF+/HjMnTsX5513Hvr164fZs2fvZ08WFhYWFhYW/2s4bOGYPXv24OKLL8ZLL72E+++/P/Tb1KlTMWrUKHTooGYLd9xxB5588knMnDkTrVu3Lm13JcG0l/PH31KOno1y6qW3XcSFTqX0kvvkr27j3Li9ZK0KAEG5dt8X58ZQuqyZmXOapXYsDKWg0nJQ3yS2n33q9j27KH2wQGbj2KcdA3eLiNOtKLPQwMWQ0pZZzBYIEcnhMpTSacA1IkzaMf3s75ZZmkO1e4I2ZhjMNSenTI9Kp7s6lTDGZdLNbJ/z87nce5HuHzuqluKu6lAqn0dpf0aUx+nTHjNG+xR75VaQlEneV1CjiM99l7onIUaIx4Y5Fy4Bz3Vc9H+jVene870z58/b0O8B60KumY42A2Q3WHatLG2f7HiKAtVXJ6mUbfA7pqk0bDPuo+QiG59Qcr2YjA2Tch6IOfE7108NL+aUaAOIBUui68Rppqa+C48ncoz1dV/cStLmVNSprTzG+JqZ9Xg88HtHuwo75Uq/jqiQpv4bei+wCF6E6nIwuabBO4pdg43wlt+jxEiZ6xu6tnRMJ0ULg9kxtTwxMfp5cIkF8+k+muM65ehdUIo1AD8vpfpxcHp3OX19SxkPhxU2HHPIOGxMyA033IAzzzwTPXv2LPFb586d8f7772P79u3wPA/vvfce8vPz0b1798PVHQsLCwsLi8MLzy+bf38hHBYm5L333sOsWbMwY8aMUn//4IMP0L9/f6SnpyMajaJcuXIYO3ZsCQfVPwTNNPwdOaW2B02m+iJ96TuZdCw9U3FSSGtA5k5mNh+har37RosWIj5PfW3HXUoVX7WmAyA2gfoWW6aujf8bVeCsUZO2Uefk1qQ6LFyDQqNOF/nSN6ZrABBbqtLh3PpSSNBbTVVVtTFRbP6PcswcMjaromvXkPmUo5mY/RkE+fn6OjWQlEWP0pL9GV+rY1MV3FAdGNNGKbis/zAMSKSRmEMVf/q83oYMm7Lo3ppaGgul+qmvq3YCgL9exak90oGEsGOLPjgzY8JQRFspXUfR1F+ln6TzCRitPaR9yVDbhNgLHs8r1H3yadbt0AzXaDX2LpZ+xJFJV4BVS2R7GhvQM1tvmYw9cx/936jvTcRQKtA4UTqsT2yit10bSqXJvWOWy9+j2r0c0TIEKbZAUJE2VMtom8xsi95T1ZIThwqr6m1QGq6QmRbpH8xzX1hAOhNi9tw6KhV7+6sSBq54PWmk9L3zN1CtpPXEDJqaV8XCShizt8iZkmburxbmLqaZO67k7BcRq7FZ30ea6Xvzqbq1ZgmdWvKuWHybjO3GGVq/lkaMSBWqjLxRV3uuQ1qvNWr7kCka1Z7xtupU5lqkYWoguqriD8eptpVz5DjElBhdWqiOC8Gvqvrn5+bK/rNEh2K0P/5uecaxU7WFGEpTYRjCJAWaMQAQmY7Fnwhl/hGydu1a/Otf/8KkSZP2W5juzjvvRG5uLr7++mtUrlwZ48aNQ79+/fDDDz+gRYsWJdYvKChAQUH4D3BxcQwJ0SNdqNnCwsLCwqJ0HOY8j/9JlHk4ZubMmdi8eTPatGmDaDSKaDSK7777Dk8//TSi0SiWL1+OZ599Fq+++ipOPvlktGrVCnfffTfatWuHkSNHlrrP4cOHIzU1NfTvsR//uAyxhYWFhYXFEYUNxxwyyjxFd/fu3Vi9enWobeDAgWjcuDFuvfVW+L6Pli1bYsGCBWjSRCi9Xr16oV69enjxxRdL7LM0JgTL/4uEeBUe8H6ZFDQ7zVWKoZ9L5be1YIlTZEO1E4zAjepSeEvFiW/aVSq00eFSEVNF+0mKsKPrLHhr6cOIRKROcpo6Zl6u/K6dSgMhG/C7kts7S7SZtF4AiGkK1Z8tKbrOceL0aRxXi/8rIbFQTRZdX8QvkuvqVhOXRBMeYBfWIBxEbohuM3GZNcI1b/LYoG3dS1Kbpu4bV6j1Fsq15TCEqQMTqnuh3UUBiAiVaPpob5WevenMK4O2qu8/EizHflP9X36jnEeDjyWlO+g7jwd9vwDA+1alIjp1JJyx7QnpU/pDKrTE9Lr3i7jtmrBfpLXUAApCcYsljdupSeESE0JavYJ+l3vvVNcukBR6CJU012EQdi8t/niUbF83Qy1QuMfNUmG7jRfcEbRVf/3mYNn3dBiAUol/7CZOxZ3f76XOMzM7aIt9NyZY9nJUmMGtL6Ewt41cE5PG6q+W0Eekx3nB8r6HH1andhU9d6YOCwk/vSmSGuo0133JlbCR21psYP0dqk8hMS6LSI1gkmsJlZfwZOGoxwEAcVdcL9toMbG/UJ47p7mED/1lc9QCC7abtJXftTCWQ6shaBGpT6n3nCrtNtIOvhTOKR7zcrAcd+lNAICiVx+TbZrr90a6iNRNqAqQcJe/hLIXSURqjumtlJAkv9dMOItDWW4bem/odGC32QnStp3Sv2eqseEeL+PFpNF7syWc7KSkye91dGhJ2yMAQNKpdJ8OE3ZdccqBVzoIpLwy6cAr/Y+gzMMxFSpUQPPm4eJEycnJSE9PR/PmzVFUVIQGDRrgmmuuwWOPPYb09HSMGzcOkyZNwmeffVbqPhMSEpCQEFbKF8SXzLSwsLCwsLCwOHZw2M3KAFU5Nzs7OzArW7p0KYYMGYIff/wRe/bsQYMGDfCf//wHf//73w96ny/UlhnRgDFSl6Po3bcBACM+kdnLf15SX93FH0sNhQXjJY0yPqqEYVMgs7xrhko6mNtcG17Nk9oHM+/ZECw3aa3Ei1ybJX/qqmA5d6WaXVWRj3/EnadMhQrfEtbAKSffhHGdleBq5J0ye+hXVY5ZuFetey1pG8ffKbMXt4Xqs79cRGssVvN+UTM1p6bMfmILxEwof76aqSWfLgIxJ1PPLkggu+qO6cFynT4lK4Q6SZR2XFFXlKUaFcyEeMuVgI/rwJwwmiprmmqcc+cETdvHKLag2ucy29tw2lXBcpU79Qw9W0TFRaPFyM5J17U4iInwfpUZHSI6lZpq9BjjLAAYeakyrSuiLNCbxpwj/6PFl+uvl1oiFaqr61f+5v4oFVoM69QTIWCopolmv255UkSgj9yYFiyveFrNImt3kllgwgCpHIzNepZZXc550eWqxk6TD0Q0vGbga8FyrYsVS+htzg3a4i4XRmneWer6F8ZEp9X6MWLmTKVVEp5ufVBme/HllfA36ThhIpZ8LuxS83eVkSEbg3nb1PnFdZFJj5Oaht/jgltFgPv+NXQfy6t3wL6vpNJzYidiIIyQncbzpveFhavx2NkAgGeuFjby+gvUA8n1agrfE+Ox+L+p595JE8H2y3/7Mli+9DS1/6e+kt//fTvV0BmjhMNjFkk/eySJYLNOfy0cJko/0lvufcEoxTTHn9dLzjNV3dvYZ2LatvsnYWpS+yvG2qldN2ibfb0wPYWeuk4dn5Dxun64vCtr3qSfl9oZcsy1wvKZWk1LB8rxC4tlHDV7VVXq9ldRFV59n/2duUGbv3lLsDz6BfXfS2+X+13u2qdwuLFzYMls0P8LUl/7ukz2cyzgiNi2T5kyJfT/DRs2xEcffXQkDm1hYWFhYXFk8BfTc5QFbAE7CwsLCwsLi6OCIxKOORzI/1W89Y3/BAC4XRTd6c34SlaupKhNpyb5R7CTnhYChoSpK4SSX/Nv5QlS+29pskknia2YOi8gd9KQu2ngfirCViMmY1o25BKo+xcSxZG7aZB7P13qUjjtpBS2qY3jrRKRsJstniFOdd1nvg7k62AEeN5SobL9NSpc4tQRAatbl7xRTN9+Fg+VfZ+KCLXcUCUM89ctpZUpdJOl7P1Z/Mhit8A5ksRmkdaK/tx4/q1BW40JUm+neKYaJyuvF8o765Mb5Zy0c6RP9WC4roY3RVHpToNGck6vCG2c9K8BamEXlaBfu0r2pb1fIm1PC9pixp9jHVHSleWYgTB1Bfl8sDBVl1n3ydvESSC3Si1YZTde7yc5f1TX+yJXTLe2otxzB0kdk7RnRKQajEcS4P7WS4SpzR9RIRE3u7sck+6dv3yJ7rv4W7Co2Vujas8w5e62k33lP/YsACBx6L/lPMz5k6NoSKhYT4UPOXwXOfUC6ZP2tfEXUf2mWjK2HVN/hc6ZvU+Kx72h9tnrXNmncVw1fhxAuK6R8bLYQ3HUdBKn6/eGk071cNglVjvPsuOoN1XubaSLqo/C7s0sFI/0Hqh2+fkbsk8dHnWqSIjHqSzjzdTj8ldQaLc8iaJJ4CwbkV+TCcGtkXAvakhoxzhKcy0lfi95c7XnUTsJcZk6V/4yCaWFxN3m+FQ/KamX1OA5XNj595MPvNJBIHX05DLZz7EAW0XXwsLCwsKiDODbcMwh45hlQvLuvThYjvaT6o2mzkDBiGeCtsRhD6jfOK1ts6SOmlmJv05EoJGzRPjqzVRMC6faxca+FSy7jZT7oNtSUmCD6qsA/G26TgsxMWZGFVQ8BcK1NrSrp0kRBQCnRbasu1H1dfeb04KmtFeflGPqlM1QLYxoOMMIAPwiEjxuptmbnpEZZ1W1z1y1H0pT5FRmp74uVLiHHE9zRSxm6l641YmRYqdSzQB404VJMRU4AUgdGKovEhyfZ140+4m2VVUtiyfJzI9n66U57LI7qmGcQjNDqhLs/6zcLIuXSUph/HUy43I1exVbIDP0YLZbqYasR+m0wTG53gq7j2qH4L0PPBu0lbtXmCB/qZ7ZJ4m7qVu/lezLOIHuoTH6q04rThVBdqiqs0lv5wrDS+ZIn9dqZo8EvJHuUhXb36aetxDbuEhEzcFsmu4t1q2SZV2LxG0iVX69tWoW7Damyr+5cm9MqvfG/lJhuPrbt8s+tXNsbOwrQZPbgyqtmhRgeob8FZSGr9NAY5+L4D2SrUSYbofTpZ+/UsXtpqRO1yh87tFgOXqqSiGOfTNF2i6+XI5vqvhul5Ty4nnCHkX7KFYmxIxxTRfzDCUJ22gq2po0bADwN62SPtdqVGI/3g/jZDlHvd8iZ18o288mhra1fi8SU8yO1MaJNTZFdIIsMHbbKRGtT3Wkgncl11yi8Vo05j0AQNxFlwZtiR2EBTtcyL24x4FXOgikvf3NgVf6H0GZa0KGDRsGx3FC/xo3blxiPd/3cfrpp8NxHIwbN66su2FhYWFhYXFkYc3KDhmHJRzTrFkzfP216DSi0ZKHGTFiBByn9OqWFhYWFhYWxxxKIVYt/hiH5SMkGo2ievXq+/19zpw5ePzxx/HLL7+gRo0a+13vjzDqZfmAuaGziJNMMaWhPwgt/PjCqQCAgrclX3/Rd0I7x3Se+5eJIia9rbyIudwuSlTo/SBi2CkvSh57y7rKJ6DSOSIC3fO1hHa256jwQK0eEmaI660oxr0vi8NjtLIUfYpro/w5HnxWRJh9PfFVSExQ1Onle4XMmvzZq8Gy01iHRrZR6IA+Br05qpiUU0VCK0W/SLGn3YvU13ilC6XQlVNRXTOfHFOXDpZwUObZKuTgxMu1catR4TVd6A+tpE/IlZCAt2IVAGDiS9LP018j0aAOnXAxuhXPqX0d960IKpf1uFP6dL8KB0VPGRC0FT59m+xT1x9yG4vw1Fsk18FJ1Q6VCTLG3GwRAA8fpSjgXMh4euQqoZpNIcFl//g2aEtNV/e0ygMiaIyxWHevppjrUhEvop29qSp0cuUcEQe+9dWHwfKykeqcq2eJ10OF2yREFQhiq4r4cerNqq3LZ1J4bd654m3S5EolHI3liLto4u0PBsvfdlQOnDFH7m3Pp4lS1uEWf6M8I2vvlBBVpbpqbMTXlmdw3hcyzlq/q7yACl+WMGtsk7om8R3nB21OloxXf7fysrhok/xlmPi6bO9WUtdv41sSSqu6iQSbVfQ93Sf3c8VouQ8NXlDvrrvelz4P26reNXHkKLp7pDz3Ff6lQ3HkKPrweDnP/2xT4dd7/yveIPdXEyH01jEqZDp2s7w3mxfIve1QLOPAgP1c8h5QYuJy15KYVocHY5Pk/bLlqz3BctULVF9dYrSn3yb3cZUO8/avIyGYRXfLM9T4Qf1eS5YQkL9Efvcaq3fAf+/kIoyyfMKr6j75y6T4oZOsztnfQ+FBWh4xVl3Tf2eQ38YRCMdYHDoOS4ru0qVLUbNmTdSvXx8XX3wx1qwRrcHevXtx0UUXYeTIkX/4oWJhYWFhYXEswff8Mvn3V0KZC1O//PJL7NmzB40aNcKGDRtwzz33ICcnB/PmzUOFChVwzTXXIBaL4eWXlcOi4zgYO3Ys+vTps999llY7xpv8PBLi1IzZodLsJo019qm4PbrdtUuhK0wDCzLhqXQ2riERiLEAFD6r6lZETyvdDc/UYQkJCaMyOzJiWSeZRH+mxgSJA7lOjOmrEd8BgFtHau14uqy9953MsKOX3STHzFViMS7JzWl/bkW1zDNsduU0qZghp86Narbs1qDZJonZ3MpKXBlbLOyIP1ucE90eZ4f2DYjYlbf3coiJoHTZgAkhUZsRMsY+ey9oivYR1sMI2IrffSFoiv+nzOA9I3bjdNcUEU/Gls8s0ebPmiL7r6L7R4yOc5yIQFmIGWxvUh7pmCxMDZxh6do4iZQGac75RxEtR7r1kc3NPWOxLokCHVMjiEWm+pqalGQAcDuJyM7RAmWHxnXhs/fJ8U9UgkuHy8ZTbRt/vUrPDImzSSjt71L3wed+VpDnxftZ1euJnHWZbKPvnZMqrIG/RWbojq6/UvSy1EmJv05YMF8LkL2fhI1028ozHjwDJFQ2zxUgNVFYyBy8C0pJpwekJkxIBMoiTj12Sq0HA6njwmnq3m8i8I2cqN51/C7x1kuqd6SuSqX2NpD7qB6jTnm53vxegL5PPB79dbLPIMXWCNMB+Ftk4mnE7aFjEhNkxra3TZIFQiL6BOWi6yQLa2vGtreVtiExrr9UM72UTJDY5mwcbuzo271M9lPxoyllsp9jAWUejjn9dFGFt2zZEh07dkS9evXwwQcfoEqVKvjmm28we/bsP9hDSQwfPhz33HNPqO22C0/FHRf12s8WFhYWFhYWRxZ/NRajLHDYHVPT0tJw3HHHYdmyZfjmm2+wfPlypKWlIRqNBoLVvn37onv37vvdx9ChQ7Fz587Qv5svKBtTGAsLCwsLC4ujg8NuVrZnzx4sX74cf//739GvXz9ceeWVod9btGiBJ598Er17997vPkqroruPHCpRjajsPOOPIUXQTCGqgMpEOEwReEUQfW1CKADg5en88+3keVFFhGEmDBOiBokODajVykJVBxQohXC4f44JeWwlYWkt8tfYoOjOfbMkd778BRQS0F4e/kJxPAV5XXia/nbiyA0yQuEq443AlL75jfL1Q+EaE+4iJ9DYOrnOEeONQrRryJMjqs41FG4pDofhAKH2AcCprcSbphAd8LswhqFwoyKW9aj/rqbyY3tE9AYOke3QYYICob/9AvEjwDpNO7PzKznfmrCcn09eE5t0yIB8YXwKO5Xm5xLykDEeD0VC6fPxDVXO3iDeBnJn1T4qTpKEeIJ7Ss8Ze7w4OlRm/GcAwM+jZ8yEFwsozMkeMFt0GINLvPu0rxwVXgSFXf19Io506mao88ih+6TfAW46jWvy/zFhGm+77Ac8xrWniNNQwgj83HrblLjc+I2og8k4ClyRN5OgUockeAyH7mfgbyF98vdQ/7THjr9Jwj5OK/aI0U6hGyTEE4jQAcA4LNNzBbqOgRsvOwRXUqFZDpfweDPhV38bjeHFJcXAxm8EAPzt9I4w4zVeihOGwovm90IZT/7uXFnXvPf4XWR8c7bKtferkpfPJvXeccIF3Q8/bHbMIaPMP0L+85//oHfv3qhXrx7Wr1+Pu+++G5FIBBdeeCGqVKlSqhi1bt26yMzMLGVvFhYWFhYWxwZKmbNZHABl/hGybt06XHjhhdi2bRuqVKmCE044AT/99BOqVKly4I0PAf5eEvWR+M8I3LBnb4nfPa6TslFSaE2qor+EUsBqZgXLcdn6SzyRhE9U48LTX/huHSld7q2hOgt65hkSIlbXbouLpQy4U10EtsFxtgg7gm0040pWbpixfeS14kh0LWAoqFy7y2I5w7rQjCfEBJmZMc+I6ik3yJBobRWdpxFXUl2IyA6qp6NnYW7aftKy9YwoJNQ7UdICnQR1HT0WVO5S58F1I0KzPM2EcAouz9ANAxKpJcfxSNxoZpRuZrb8vlXYHW85MQzmmDVFuGscKk0/AQROpm5GS5QGf7t2HyXBJdcs8fQM3t9G1zZS8lEOuYeyIFQzICwyRa6+jpXpOaWZaciZ0hyyJaUQb9YzTxqDTj15HoxIlGsqeetp5q0ZED+P2I80Se82s3knOU3a9PXxyaGXBY9GUFmwSliJhLxc+d0wpFrECACxvTLbN2Lh4J0CwOdnUF8fZsYc3ReH2BkfIng3glGXakLFKLU0eJr3EvPGrIZm2XzKOAQvm2eQnGcdYmADN16+TkYoTi6qIZfYnVtCfQcApyqxQ7t3lty+iojgg2tBYygkgjXnxwwi/zXXY9upkF7y93Sa1G6md3p53Vd6F1j8OVHmHyHvvffegVciHKOu8RYWFhYWFmFYJuSQYQvYWVhYWFhYlAFsOObQccx+hDhZ4pkRop2N4LOO0IEe/R6s11Lyx1GgaeeWIpwKilcBiC1cBQCI1qJy6g2lhH3gZ8A+G1UkJMGCz6DPhu6kImOh0us6XMJF65w08kPQdGv5E4myZ/+NwP+C/ARIEGpy91loGCpYVrGkdseUZg/5smSI8stJ0XTpGhGtgahqFrEGIG8Wx1DUWULjc+jE2ycOoLJNGgAgNkXcHrmQlgmnsAtqpNM58rsWoXIIhj07/NpamMr+EFtFsOk21+NgBxWD4zCDvibsM4I4de+9tVIMza1GmigTltpZirgPMk7c2iSO5nLz2qsiVLiM6PXA94FLxNfQXg7fTZC2dvSM6OM7FPbxVsp4inTRLrJctp7eyEb0yB4zfM6+eYZYWFo9Q7b/UfXLbdldtjHjgcc9P4NaHFruePKk4GuiRaY+9TM07nX4waF3QchbRQtjnRryrgm8bFiIzOJq4xFDx3Tr0/NkihrWIzFpEW1vih/Se8FfIWPb+I848eROupPGaz0VAvQ2iM+Ho8cGh2t9vk5G9MzFHtMpnJOn7gML61kYa64Fe4t4nExgrm8yiVW5kKEJaRaTINzc570UvqtBz5ARbSfQO93iT4lj9iPEwsLCwsLiTwXLhBwyjtmPEG+GCDrd7DbBsr9aCQ2LZ8gsM87UOmGujOoYeL+qGb63OVe2ufgS2afRrcRi0kZOoL4WQTl1Rczqr1keLDv6+E6WsAa+md0sl356XOdFp+h5q0Vs5VYX0aCjWZmiJTTLYQZCizj9jeK86K9dJb9na1EdzTyxKxclUFcEjbHvlWtl9DwRuvmrxdE1VlkLfJfLjCe2gdKO52kn1ZrENMwWt0en0TbdT0k/9FvRLHe7FoTukHP2N+q2CKXgkuun07y1+m+q3G/jgqr2pdkGnrnVFgYi0qA9AKD40+dlG6rBE/tRjcPYDmGc4ssTa6FnYrFJ5ERaTbEFLGj0OB1ViwZDzNEmYWp8LQTc/sqcoC29WXv5fZE2A6RrwinlQcp4ijhQ+tPUvUUqpe3+Qs63embsbRdGyK1NM+ec1XobSQl3O0mNHaxX4km/WoZss1Dug9OorfovsWzeD1/K9nHaQXiRPPcmNdZP5xRamUEb4WvxGnJCXiG1iEyqc+FkGYPxNWiGbtKOt8oz6E37r+yrvjqXfWOnBm2JPRQzZlKKAYTcdH3DTBKjFJsjwthoQzVeCz78KmhLuERqw5jUWC9HxmjxemEzE7R43q8urC0LjL25U/RGlBpv+kQptPxeMtc+9NzOmyP9X6nGRGSLCLZj8+X9Fz1T1d6KffdD0ObWpTT7RtrF9We5jiiWd63bTXlChd5V5hncJaJkn1iPgnFK3J54m7jNHgnYcMyh47CYleXk5OCSSy5Beno6kpKS0KJFC/xCLyff93HXXXehRo0aSEpKQs+ePbF06dI/2KOFhYWFhYXF/jBy5EhkZGQgMTERHTt2xM8//7zfdYuKinDvvfciKysLiYmJaNWqFSZMmBBaJxaL4c4770RmZiaSkpKQlZWF++67L5RMctlll8FxnNC/00477ZD6XeYfITt27ECXLl0QFxeHL7/8EgsWLMDjjz+OihWpyugjj+Dpp5/G888/j+nTpyM5ORm9evVCfn7+H+zZwsLCwsLizwvfK5t/h4r3338fgwcPxt13341Zs2ahVatW6NWrFzZv3lzq+nfccQdeeOEFPPPMM1iwYAGuvfZanHvuuaGSKg8//DBGjRqFZ599FgsXLsTDDz+MRx55BM8880xoX6eddho2bNgQ/Hv33XcPqe9lHo55+OGHUadOHbz2mhSQYyMy3/cxYsQI3HHHHTjnHCUQfPPNN1GtWjWMGzcOf/vb3w7uQCzsosJuRszn7ZkStHERo2C9X6TMuNtR/e7rcAMAcR4EEM3WfgjkW1D8jVCHce0VBes2bBe0eSyy2pOrN6JCV1qo6FPJbxb1uVpc6G+mcEYG+YhoMW3RdrkOiSSGNdfBbSZ9CuXxa7GcU5uK0ZFINLi+5FwY/dsVaht2RiRfB/c4Fabxu50lfU4XSh/V1O8sTkR1CWGZkEjxHKHMQf4Yblbr0HoA4M3T5eB3Sj/ZM8TRLrF+goSNQsXotBMq+4CwCNWEYaK9pRx68dSPZV+7lOgumiTiRbeZhCGMp4rblMS2FdIAAJF6VPCLvShydLE3dsjlPq9WVHn5BuQRw6LBOnqcbJHzcNIolGdEyeyHUlePnXwKAbWWEE+wbSUK66wTfwp/kxqnbgN51t26It5Glg6ZksjSZ9+deTROzLFqy330FmsX2BPIeyRD+9aQgJe9VYyIcxdFFqrwM6CfcTeJhOMUEjV+L37xKjmnpiyIV6GAxO7SZsKkLNj2l1IIqKq6zg4V9yvO+4LWVX8E4ltK6IM9NaDDi26c+PMUz5NwT0JNvf/U0n2ZTCjOqUbCUhPC4oKD9UmsawTzLPJsnh0sRrTfitvxFNmGhPtubX19ess7kd8hwX2oQyGklDRZ1vvnUF0gTCUXaPYXim+Todq40F6rM3C4cbTCMU888QSuuuoqDBw4EADw/PPP4/PPP8err76KIUOGlFh/9OjRuP3223HGGeqaXHfddfj666/x+OOP46233gIATJ06Feeccw7OPPNMAEBGRgbefffdEgxLQkJCqSakB4syZ0LGjx+Pdu3a4YILLkDVqlXRunVrvPTSS8HvK1euxMaNG9Gzp1SrTE1NRceOHTFtWskXkYWFhYWFxTEB3ymTfwUFBdi1a1fo3+8ryRsUFhZi5syZob+pruuiZ8+e+/2bWlBQgMTEcOZQUlISfvzxx+D/O3fujMmTJ2PJEvUh9+uvv+LHH38MFakFgClTpqBq1apo1KgRrrvuOmzbtg2HgjJnQlasWIFRo0Zh8ODBuO222zBjxgz885//RHx8PAYMGICNG9VMoxp/iev/N7/9HgUFBSVuwGfPFiNOf02f1YlmdKvUBbtjusyIHtMuhrFJUvo8f6Y4HxbvVnqVnxZJqt2pXcUJM9K1DwDA2yhiq6/Gy8z0xMVqpkPcB2LLpU9509RNSblEBLTGVdT7TWY0hYu+DZYTeqiZ1GejZJOuWSLU82JqFnzremFnXuKvfj3bBjsTrhABnL9e18VIldlP0bfyhetUUAM0etKJso0uYe9nirvopidFXFj1Ep1WXIeYiEyZucYmKnGmc5b0mdkXf56aBa5+VdrqdxXRnbdd3zNKJd72hGKv0h8WIfG+p94IlpP++XcAgJtN7IQ+D0DEoeyCyim4RgDH7Ee083nB8qSr1NhZQDVXBp2TW+L89r4s987RpqFJ19G0aY9sE7hisrsn14ZZpYS7//5B7u3TreWcCv6r9FVeocRuk4eIu6m3RN/nXLnOa+9V4sx6798UtOXd+WCwnHiaYm1ii1cFbXEDrwuWJ586GgBQt5yM54bvk2Dc1KGhe7fzcWEAkrNVqnokQ5iW5c/I+6DBE11U36dLKnbsN5WaGu1CjE0FGu856jpdv0kYl/enyTPm1FDHWi+kKOrUE1G0V6hTQ8n1d99XIv5Ovk2xY++e/3nQ1veMKQCA+CuE4ds9Svpc4Tbt8kr39tlP0oLl63eq2fwHk+U6XFQs2+f/pN4rO1fJeFu0WdbtZthcEiVHL5L7VPSWejbiLh0YtJkx6v8sTPC+r4Q5LHdJd7VAabnbho0Lln9Yq47fp7GITTcMFX1BjSf180L1ZIp/lvdG5GQlPP1tqLy/qlWVFOdqj18AAPB+kPECrUtwqtEMPF6uyQsjVYruNXfQ34ZjCKVVjr/77rsxbNiwEutu3boVsVis1L+pixYtKrE+APTq1QtPPPEEunbtiqysLEyePBkff/wxYpR8MWTIEOzatQuNGzdGJBJBLBbDAw88gIsvvjhY57TTTsN5552HzMxMLF++HLfddhtOP/10TJs2DREWxv8ByvwjxPM8tGvXDg8+qF5grVu3xrx58/D8889jwIAB/6d9lnZDzk9ujn4VSre9trCwsLCwONIoq3DM0KFDMXjw4FDb74u4/v/gqaeewlVXXYXGjRvDcRxkZWVh4MCBePXVV4N1PvjgA7z99tt455130KxZM8yZMwc33ngjatasGfwtZ/lEixYt0LJlS2RlZWHKlCk4+eSDq3Tv+GXsm16vXj2ccsopePnll4O2UaNG4f7770dOTg5WrFiBrKwszJ49G9nZ2cE63bp1Q3Z2Np566qkS+yyNCcGyH5AQr6aUhc8/GTRHT9QpWfTVXvzxJ+q3fhcEbWz8FcQcyVQsNlW+um9/UMXW7+svs7hIw4xg2c9TuoJQWh7VNAgq2q6Vr9Lib1W6WqSGMCpOY4ktx6aqVMS4y/4hx2HTNV33gyuher9KTLT4v2qGHttJMfhC0o9c1U9t8x3NDKsKQ+FkKj2CN0eESrG1ajYbbSApum6vvrL/zToNk8yT1o6Q2U3tvmq266RRevR2YToiJ2jWhfQ0sS+FvfL3qesfbSVMDOqr5ZEDpgRNN7zZQ7aZrq7zQ6Pk3g19SqrLGl0D12EJDMggKbhOFZlhfzdCrukp89XHdmyx0J4773gxWC7fWY0z9yR5II2RXf5DjwZtcU3IXG+z6kvBcjHGiqtKNXwqqJdR9OSuQRungTqtTtDnJte+8CNhYuLaqTo6seWS8hh/jXrhPd/rlaDtmvHygvGmTVT7plj/sCtl5jzsaZ1imy6z8tiUicFy8SKlRYg2lOcico7MqPyNmnlcLzoTp7mkVz7bdywA4IaXKe3XbPubaC5iKyQlPZKp+uI0pclKHhnelVPjcdt9MsYq9RcGw8yy/U2kEyFjshk3KbFJhwkyuSp+V73E/Z2Ssh3tJudRNEWNJy9XxmPijVfLuazR2peWcm9jE6UUhpOt9sW6pk1XPh0sV7lQa0KyRE+07eGvg+X025UGYNeTkjKe1ECNp7j+wvCx2aL37Sd6Qd4fkZ7ny++r5qpz+1wYm7i/ybvW+24yAGD1aLn29S6md8BW9Q5gWwTW9uQ//JD6/UTSUG1R7I1TiXQsG4TBjPTW7Mk3cm/L3So6xcOFDSecVCb7qfHjtwdeSaOwsBDlypXDhx9+iD59+gTtAwYMQG5uLj755JP9bpufn49t27ahZs2aGDJkCD777DPMn6/Yvjp16mDIkCG44YYbgvXvv/9+vPXWW/tlWACgSpUquP/++3HNNdccVP/LXBPSpUsXLF68ONS2ZMkS1KunhFaZmZmoXr06Jk+eHPy+a9cuTJ8+HZ06lRSQAuoLMCUlJfTPfIBYWFhYWFj8VREfH4+2bduG/qZ6nofJkyfv92+qQWJiImrVqoXi4mJ89NFHQbIIAOzduxeuG/5EiEQi8Lz90z3r1q3Dtm3bUKPGfoqUloIyD8fcdNNN6Ny5Mx588EH069cPP//8M1588UW8+KKaHTqOgxtvvBH3338/GjZsiMzMTNx5552oWbNm6CvOwsLCwsLiWMLRyo4ZPHgwBgwYgHbt2qFDhw4YMWIE8vLygmyZSy+9FLVq1cLw4cMBANOnT0dOTg6ys7ORk5ODYcOGwfM83HLLLcE+e/fujQceeAB169ZFs2bNMHv2bDzxxBO4/PLLAQB79uzBPffcg759+6J69epYvnw5brnlFjRo0AC9evU66L6X+UdI+/btMXbsWAwdOhT33nsvMjMzMWLEiJCY5ZZbbkFeXh6uvvpq5Obm4oQTTsCECRNKqHX/COwm6ReRk+kGJV50tfMgABSuVdRolFwp/e1Mseq6GVQXArtEGDW7WAkud3wjkavKJ1IdGS22My6nAOCQ+6hfW6eWMWUep8tTp1P6XUWqA6NTPkP1GLhGxm5dg2Kr0M+x2SI89XarPi2dInRlZks5PjZqKt6VNE8TggEQpDfumyZukdE09VXsbaHzIDdJU6cmtkAEvO/vE1fO/6Qr58fixUK5My0daa6FkoniEOltpxRgLZYtmvpr0BbfWN3nIspWxS7pX/EydX1yQdeZ7gNK+6qnOjDGCZVTcFmE2kOHYSKNZMbhxyQbzDfOjyws1WGS4lxKM19N+fxRnfJIjwOH0oJtGraVfv4otLNjSqaTI+pOMtNNr61p60Iqna5RxP9Dz4NjXDMpPXqNT3VadDqxkyzXuXCW3OeiXPXsRDPlWeU3tgnh+etFIBzRYSUAqKo38xfIvXcaqLCSv1No/n2LJQySXEv11a0tolx/sZgmYpN6V6R2lPEWqlkSK3l9OE0/x9Uh0XJp0udmqk/sohpH4mznOyUA9uh+OlyzZZWmuR3ph1OBHHjL6bpCq0QAnH4Kpb5W1mEaepfkbpHzS9fXfMMKei/U1fd5rYjxQ6mv+5QdQPESedc4LUXA6zY+Xp3T+yQcJUdYdgYOtue6R/p3p5KEujjtet9qdfPju9FDnqbO2V8n7/G9P8s2Ffrqd+VBiiPLCr7vHHilw4D+/ftjy5YtuOuuu7Bx40ZkZ2djwoQJgVh1zZo1IVYjPz8fd9xxB1asWIHy5cvjjDPOwOjRo5GWlhas88wzz+DOO+/E9ddfj82bN6NmzZq45pprcNdddwFQrMhvv/2GN954A7m5uahZsyZOPfVU3HfffYekXzkstu1nnXUWzjrrrP3+7jgO7r33Xtx7772H4/AWFhYWFhZ/KQwaNAiDBg0q9bcpU6aE/r9bt25YsGBBqesaVKhQASNGjMCIESNK/T0pKQkTJ04s9bdDQZkLU48UtvXuFixXeEoEfrGlKv0w5yYRXtX97D712zwRbsa+pzoGddRX+d4JkpZW/t5/Bsu+qdtBM6PCj+Xix3fV9Um4fsdyman4W9QXupMpoje3qZrlebNEzAUyb3IbqFnu7sHyoVbuLBEFGiHlpOfly/u0j84Mls3sik2wnMpigOStnKPaqpLB2WaZuQZMSV2qelpJm5F5Ml+OjXtbftc1HriyJdd5ceopEWnIUIpgWJ+it98K2uJvvF221/VwYlT/w/9NzWzdTiL89GaIYNLtdKpa4EqmPMPV6bDGmApAqAquv17NDkMGZHtzg+Wdtz6r2mJyH9I/FoW5qc4b+2F8ieNHuosQ0JiaAQB2q3vLJnzMpMT0vds4eEzQVuO5y2TVWaq+Cadfs2GfqZnC16H4fcXeRM7uL/shUZ/bWYl9Q1WXo6LLKh6jUpjdqmlBW6TPRXJMw+JxzZQpkvbs5+7SfRP6x99FLFh3bYRFbGZw70gMayrfAoCTrJigr08Qh8eTPxTDKlNF2P9FWAunCVWF1lV8/R0kCF8taahGFL1vxOigKely9Qy6zUVY6n0v5xnpdn6Jfm4+V8Tnla5Qoul9n8oYT76L3kUL1Xgv/HZG0OYmy32I9tVjisaLW6uR9OU39Wy4LST13jCs5p0AIMSKBO81YmeKP5Tn3ohw428cGrTxvY2ceLZekZgvqojtpKn7V/w2OXHGSZJAtI8S/nJlYjP2AkEzAGwUVnbfx4qhTLr63KAt6cwbcbixrmOPA690EKg9/ZsDr/Q/gmO2gJ2FhYWFhcWfCb53dMIxxzIOSwE7CwsLCwsLC4sD4ZhlQhI7iisni8lMTYZqPai+yT5F4zlVxN8i0jZbttfOiEntxFvEqSB5+N5sZWXLdVji2lD9kypaWEYUKyrTvrRIxwhgAcAxtHQ6ryfb+0VK9JfUhQSw9UVg51RVtHinxuTzQQI34yPALq/IE8Glq2u2cGiFBaGorq6vEcIBgK+35+Owp4YRlvn5Qlmz26RznKbaWbRGfTI1JKJtKAwRErhpPxYS6MKIaQuk+CF7Obi6ryZMB4Tp6SCkQDVNkEJ+KbpeBodL2OXV+ID4VHrco5osbhUVAvPSSBirfVBYdOyk03iOo/Mzx6TQiaNdQSs2pTa+91X1mOKy9G4p8w2uy9NYizy3k7iaaj4FITQaI/5qCV9GO2WX3D8d05yrW418OOrScoZeN6m8tK0mB2Bdjt6he2PuAz+rIcpe4/gO4o7M/heOq94RXpqETkMhMDP2Ukn4Xk6uj0F8Y+kTyqfp/lINHnIYDgT1FJqoeCrVjNLvmIRF8tyGzk+/L6KZ/N6QcEwQaqMaOTx2nbr6PvPYq6jei1xvJjTeErXwNU6O42bIuxSeX3KfSSSi1+8yDmuxz4mj35tuA6oNw4LxOP3+BMG8ayuL6NVPkLEZf5wSOrv1W+FI4tgUNxxdHBYmJCcnB5dccgnS09ORlJSEFi1a4Jdffgmts3DhQpx99tlITU1FcnIy2rdvjzVr1uxnjxYWFhYWFn9u+J5TJv/+SihzYeqOHTvQunVrnHTSSbjuuutQpUoVLF26FFlZWcjKUjOf5cuXo0OHDrjiiitw4YUXIiUlBfPnz8fxxx+PqlVLFy3+HvkzxwXL/m8iLHM7qPzkoLoqAJRXM2ynKs02C2nmbGYa9KVvXAAB4LcrpgAAmg8UdsXtIRUjDavAM2BmEGCqUPJsWtfSCInq+OvfzCKpzalCwtJF2nlxxnTZpDOJzbSw1FslH3ZuWxHOOpWqldw/C0Y1Q+AtEQEctmmRa2qabFO/pHU+Vyje/a7UiEgZrpTbLNrlFDonS+3LSSQ3xWWyfcBa7CGX1c59AADrzrg5aKv92UPBcmzuFADAsn8IY3TcpyT004JVfxfN4miWFvv8AwDhKrhcB6bcTRfqjnJtFxG2OpoBifYQN8jiWbquxhoSOabTtdf3PpTyXV1mnqFxHByU7qMWZCJeRJ6xbz+U3zM0i0d1XEy6b+71w4K21Mf/LduYMUzPyPSTnguW249S27stuwdt3syvpHsrV+pjZ8gxyRXUm6uE4t5SuSaR08WVs+BJ5aSccIO4iwaIk3RA7ydxB3Waqdo1LDyNnEkurTq93N9JtYIMkwGZoXNqvEtppIWjlFtutN+lsr1Oa+bUeaTKeAqEtdvpmBVEQIxina7KzxWxdEE6MN1vb4G49botu4X2AwCxz98JlqMXqDoyxZ+/LvusrdkhSut1a1JasxaRhiodE9Ph1NSsKrE/DrHCQd0gHu/H0fnlapZMV0UG5LkEAP9X9S53WpI4XNfe8WdJn4L0ZEAY5nxJ2U46t2Q12bLGquxTDrzSQSBjzqQDr/Q/gjIPxzz88MOoU6cOXntNLHIzidYFEJQQfuSRR4I284FiYWFhYWFh8ddAmYdjxo8fj3bt2uGCCy5A1apV0bp1a7z0kpg3eZ6Hzz//HMcddxx69eqFqlWromPHjhg3blxZd8XCwsLCwuKIwffL5t9fCWXOhKxYsQKjRo3C4MGDcdttt2HGjBn45z//ifj4eAwYMACbN2/Gnj178NBDD+H+++/Hww8/jAkTJuC8887Dt99+i27dupXYZ2kF7LytG5AQr3PJq4t4MwgfkOAT27QLYy1yBCWazlDM3lKi/hOEyk6I086LHYkOXCLhmthSZUcZ6dZHfmcxmKbHg1L0ALA7V7XNF5dTt9vpsv0KFbJwyG2RXQSdGkrE5Z4oYiyHy5jrcIxbU66Dv0roULeeEpR608XvxK8oDptB6IPKvQchA/YmZpdZIyBrJG615dqIs6I/X9+bmiIODIWDtNum8TJQ+6QaQbuUyNXJEKFfbJnaZ4XqBdRG+iO9fWq63G9/j4hhAw8YEkQiTsSNbjVN8VZIk35Sl4zQkYvFhXxItAg1CMEAiLY5TbVtlmJxSCPx4a/qnNjnAzskXOStXaX7KV4KLJo2Yl9/s4StnDS5t05FNSb81VKEyvh/FOeTw+Q+uQ5ezhy1bSM5TkZtEhVrd1ZvufhbhATjhunk68zXqap6ht1y9DuNsw3T1djKvJXGqB473kpxUQ05ZJqQBHuPcBFILXLNHyH3IfGS06hPKuxlwgEAEKP9589Rz0byaXJv/Jm64GEdCZk5lSVc5K/RoToSXIcE4XFpaj32JqHQsXlvcbhn1yipGZJyhX4OyN+HHUtji1X/EKXrtFc9w+5xJGT2SIy7yDy38rtbS55Bb4kSffurxbPD7S7+HP5KZYpVPE/ClNGqEtYy98kIWAHASZHQkB+vr99eEh3rsJZ7vPhyeFMlFOdqXxx/voSrjwT+anqOskCZMyGe56FNmzZ48MEH0bp1a1x99dW46qqr8Pzzzwe/A8A555yDm266CdnZ2RgyZAjOOuusYJ3fY/jw4UhNTQ39e/SdL0td18LCwsLCwuLYQJkzITVq1EBTEvEBQJMmTfDRRx8BACpXroxoNFrqOj/++CNKw9ChQzF48OBQW/7156Dw9XcBAIn/lqI73gb1tb3jrveDtvSX7lC/bZPS5bEvxVE1kqW+8AsmSdn6xEGXB8uNntECOpq95E8QBiOxs2Il2E3SX0mOqTtz1UIFqvGgRZjGTRUA/M3SP5Nemf+4iP/iTyIxl2aGFjwqM6bmY8Tt0syEWCDmlpdZZCCibSgOkdhKTM0Wvd9ynMapakSw26H3FQke2xxf4piRNtTnZCU4dWtTGmQpaZyFX4qzbQLZEBumhNMw/V/VzK78zXTu68jtsakS41Z5gGZmzN7oe+pmSD+9tWJnbGaRkXrye9J1MkPPf0i59XIdmApPDCtxTv5vIqAzDEj0tCvkmOTS6jVUszxOKQ+ljC9U+9r+qMz8Kt0v19TXzJxD9Rvc9qUI5qi+kjdFPQ+VBnWR/SwkZrCGZny2iNC5yp1SpKrwdfW8RRtLn6PnDZT+69R583wC4Xo3yNezfRb4LpNq3HUHq/HsbSfBp9l3JapDQnVijMPnj/eKKPmE18nB19z7FEoD30j7T9dpz5WIpVou/U++Sl3Tonc+CNrieqgZuNOY3JNnTZFjNu+o/kv3c/dNdwXL5U5T97HwZ2HWEgb2k31tUMxi8Tciti3aS6yGqW2jmVYAiPaVd5n3ixI8us07yDY6NZ6F9dhE76LK6vq6lEYemyzv19hC1ae4y6+V48wWcboRIMfReGOWzQiova+p5HyijF2nWXaonwAAXzM1nEpcUZjgoueVk3G0V3ccSRyt2jHHMsr8I6RLly5YvHhxqG3JkiWoV0/9UY2Pj0f79u3/cJ3fIyEhoURBHD9ifdYsLCwsLP48OFpVdI9llPlHyP9j77rjs6jS7pl53zQCSQglhZbQi0CQJogSFEVUBAvYBXtZd0VcXVlRWNRFxYIiih0Ve8MOUgRFEakqSodQAqGHQICUd+b74947zxkTxOyXqOg8/vJzvO+UOzN3xrnnOc85N998M7p3747//ve/GDRoEL799ls8/fTTePrpp711br31Vpx//vk48cQT0atXL0ydOhUffvhhGZOdIIIIIoggggjizxuV/hHSuXNnvPfeexg+fDhGjx6NzMxMjBs3DhdfLPX5Z599NiZOnIgxY8bgH//4B1q0aIF33nkHPXr0+IU9/6zjzco3rTKEyhqdqM2kUQjqDTWlsmGNskS1K0d/AQLRWs2ljj22J6uX1vUfB351VLfGnjLHt7QqJqsd+siPWqsiuhOpVjagPm9XqZOMNqJaadWl3w35kg3HyIDKQKusWOrGS7rIMwerJ6XTnnEb6wE0F4KalaTVQ/NyZD8Ml2pNFNYAsCzSCdEaCFFtMqQtthzlR76O6eXcs9qk6Kq1VSKbBUbndJBbU9b1fk+R6+hoAhwbAWJ/vrcY1UoR7OwNlFZjUrK5zrVIuVaTUDkFY7OB3iFt5hZPJMyQkFCtBkr1Mr4xEfG4zzkayifCti+0UqpFqpreGC4mAjjbySdpNU1W4swTyD7qOH1NibjpU5k145E0N6z6hHwa00M+PpM3D6kxxxou7i71DFhs0EYKwZa+t83rCbnaShdyuqWvaVRbuXZ2lpDPzfm7CXQfiORqnle7NmkC6fNnVV+XdHW8+0j3M7aN/G5pBeDwBkmN2vRcOwXqOtrpotKaVI1SG+YZPpwqsVFvZVVgowGTRKlR0hnxVGpJd4bHRqieHhusOhxN2i35Su+Gx5vPaFCnpqw0ehZZndU8r6yFo/flIxo3EMVVO1dfPyJ8/xbhBOmYCkeVyLafeeaZOPPMM39xnSuuuAJXXHHFL64TRBBBBBFEEEdLBJyQisdR6x3DCIKzRUhcZvZTskFmB1Hma7mAZgREuHRycsrs01caekCXd64RsqlVjzxd6qvZi7tBCI3sZeLuVjMx+1hCevRMxRDVgJ+pLOqZVCRXiHTh+uLDYhCG3RtlxlWdFVu1l4jzw1eyTRMioZrjUymcQT8AAJpIyNfBKKFanXvLeqzyqsv63JU/SjfXyTlFtdWkRy793EIIgVartBqThwSXceqZkLtOSMFeeeMeUqBMEIKas12XCB8gMirPqPQs0GXCIyMEppw1l9Qe6To52/U9CRNHaR/dJ+MDwwRcXYJrCKiAoB8AEGqs1Ecjq6m8sJqQ8gxiZEXTPoksbMa2VZ2uA5MO9TW1M7OkzdzHeCqRPShlzVYtNd7dXWKX7u4ShME9oJAKO5VK4+k+G5Vcq8WxZY8JyAw+Vq6tm0vjWaOQ7laybjeqo4QCWYQwGMSuWi3yR6IZvlH4tJqQDxT56ZjtmZQcoXeIlZKh9rOXrpMmnPuu90HykTHHJpK8L8qZufv8ncxzS+8quw2hsgYpIqQCEdne0uR0Lim3tFKpuy1HttlL70pThk733lkrBGUrWd87W1CwyKKl3nJ4kCbhc9kxqfV6iBP5TLm78uX3eur++pAUfSw3R8rM7Q5SrntwkSpaiB8kSG0Qf8w4aj9CgggiiCCCCOKPFIFOSMUj+AgJIogggggiiEqIv5raaWVEpX+EZGRkYMOGDWXab7jhBtx9990YOXIkPvvsM2zcuBF16tTBgAEDcPfddyOR1SF/RRQvFiXOagNv8JYj36mUQcle+SL1IMitso2zTpatOAXJH/xcIMp4Ui/1jJFqitV15HPRHghpaNGidIfPpM207dkm+zSExR8pXcLEUA09RnZIGiF8SGBdZ4eCwnfsEfi8YXn1YWznTpC+B40SbMtEQuzQZLL6RORro7UPiJjqriGlUK2rYDWUY4a4tNrA80xOTC/rGRSZQ9c2i1I/RlmRrpO7Th3f7ijmfc6iL71lz5q9IRlyGYItBZv3sTKtB9mT2q4xzwKAorVKrdImzl4s28GbbdiMTo91nw4IkVBNGibUTFJ1rLbrblNjd99Pcr9jKA3h7tRpCibwNs+SZWOCRnopzrocdcx+orfCug2GAOgWkgprK0lTuAu0oWKu9DPUVIjc5tmwkuWcWTvFLSnRfSP10AJJV1laI8Jl9VCddmIFXE4fWkmKCL15ZZLX1opSEyYl4G6m1AIRyr1ncJ2owLpbKI2iCaslWyUdE9YpWbttttfm5NH+9TizKO1TtDxfTqm7un5FK+U6hzm1slONzZIV0o9wI7kmdob6nYmxYCVl07/momPiPY9hSkEzQXi/TpNQShG2vF/d3ZQKND/XL0v45vQg78uQx51DRFiPl/6H6itNKWfPFvpdawbVkQIFZ6EYJtrRxgRS3vNo/usLH/7XCJCQikelf4QsWLAAkYhI/i5btgynnHIKBg4ciC1btmDLli148MEH0bp1a2zYsAHXXXcdtmzZgrfffvsX9hpEEEEEEUQQQfzZotI/QurUqeP77/vuuw9NmjRBz549YVmWp5wKKOfce++9F5dccglKS0sRDv/67oTTqFSQSE5mZh2VKLiYN8ulUjsrQRAEM/uKaUmleGQP7pWbUf+sajzT0AgDzyTIu8YoM3KJm2XWPUwJmZkpheoQUS6e+6xmH9EhmoUwqU4Tt6xqcp3sJJmdOLp01yIVVR9pz3jr8OxHIylM/rNqJsmyvmaMVFjVZTZr9uWVBAI+VMQgMVYS3VsmkerrZ1F5IdI1YZLLhtOpNFVfE0Z5bEI9hOhH1uNMgDPeMlQayghDVN2wPr5T7u+uJoFaqYIAGB8YVs3kkk1znRn9YAt5RyMY1dLlY5/Dqq7HSUr5iqse2ZfGuJWuxoabT/5EtWjmqq8Jz/MYWYQmplqNiLBN5c/m/vhQi1hCxMwCz8Cr03g2aGOSvF/c3QpZ9JWwbiOis9m3Re8CgwJRn6wadL+JUG5QQouuPVLz5Wc9JqLqUT9raqSDie3kDeM991SmHq5N7z2thBxVn94VjHJpf6dwI3rPEknVu+ZcBk/nDKMuy+9M/Q7wlRXHEznbvDe43L4GIVaOur5McmdEyyuz53J78onxfGoSCQlmIrd5V8XTeDTvBSa4EipiJ6hr5rrlPyNVFUGJbsWjSjkhxcXFmDx5MoYNGwbLKv/m7N27FwkJCRX6AAkiiCCCCCKIP1oEJboVjyrVPp8yZQry8/MxZMiQcn/fuXMn7r77blxzzTVV2Y0ggggiiCCCCOIPGFUKPzz33HPo27cv0tPTy/xWUFCAM844A61bt8aoUaN+cT9FRUUoKirytUXqpSBG21E765d67VZdVdMeShYI09OK2CV16myT7modkNAxorzIuhClc5VVtZ0iqQu7k1iaW40UccrNITIqqz06ZaFDd58ilvrg5R1lzblCaQSjJ8rx3VWKkBkTRboKBWIpbsijzmIhvparCWKVTbcAgGXaWXlRW3q71YlEnFw2neQsEH2LCCmJxnRVZF9nDRmj8fF1GsdqSiRS0u8woLqxBgeE8Oh8O8drs7v2km32qO2dr4mseo6QYY32gEPKi5wucvcpKJg1YNwcSUPYNfyeRgAQ4fGoSYFWXVF2dTblqH8vF2KmUUEFBD5nUp1DJFKjrhrTiUjHBL+b9KGVKGPLb3cf9u0HAKwkTfRb9YO0RVHazeiphARGL50u1zyUqaBwqzYdc5Oo+bobVJrEakRE5EQiTBbkq3/vkHSN3UiumWvIkazauZ/UgM16634q01Y7lVKCTMTWBGSrjRCAOS3n7FTkT7sBmW3WpmPqZ8ymZ9SkaBzS1EAh6eIYciXdz1BdSkNoxdVQA0q3MMnUpIjSJdVlNaaxY5RE98l4cNYKsdbObK/ayEjQ1qkPt0B0X3zXWaftnLVi8OlskXVD7fTzSqRfd79cc/P+ZbVbVlc114pTOO5eMgM1JHoysDOpI3fZUmnTBpoAYEVpzRLWGfoNIqiOqXhUGRKyYcMGzJgxA1dddVWZ3/bt24fTTjsNNWrUwHvvvYcoetmVF2PGjEFiYqLv70FyvA0iiCCCCCKI3zsc16qUv79SWK5bNd9uo0aNwlNPPYVNmzb5+B4FBQXo06cPYmJi8Mknn6Aal+QdJspDQrDmS8REK0JW/t/v8ZprnK5mWjaV2Bb+R9k6VzuH7LVLSEVQe7JYaaLUWTT+MW+5+ydqJjMWQoA7aUp/2pfqmzNrmuwziciZLdqo3xd967WZmYQ3i4B/RuN+t1Cdxwlil+4ja61WqqFGjRUASr4VZ+JDmxQha/ZKISf2yRaiY/Rx6ljuXpml2ceJjTsKFeF13+Ofyu+a/8blqHHXS0kntqpSxJ2PL/Ca/r1dZi9P36Wub8HLC2UbIg3W0MqKViux/D74yIvecriumpEdWCmIUtL42wAA/+wv642dJNfMbH/VUunH5OFUhqnHgbtL1Brt+kJw2/3cUgBA9abyYrjlS5nBj39EIWJ2s45e25aLH/CWa7ZWM7HYm8jm/HtVzrrnBUEn4kkk1iihcgkuk1ANAhJ97Sg5jdcelO21/4hRewWADVdO9pZTu6lztmvIjYwarCYLw8591Wt76FFB+9yt2j+J/IuOv0oq2r6adIHaZyMpy915+X+85f171L1L6SjPceyNV3vLpe+8DgDY+5WMx1qP/c1bfn3AewCAgdfKeLGbqfN0Vgtque4FIWpnnKGuWfgsspDYIaXSZjurjhCd3XzZ3orW761YIokeI4qvH1ykSskHzLle9rloOgCg4OnZXlvCLfKuKHrlQwBA8Xa5twkP3Srbz1a/h06/VNrmfSTHb6zeJe4WUo7dR+iMQSaJJL/wmm+85U4vnAgA+P5K6V+LE9TYj8pq6LWFsk/zliMzPwYA7J8pZcHmWQWA0MnqHVD00N1eW9Q5/bzlkjdVqXf+d3LOda6XZ7zka/UcxPzz316bs1FUl7f9S22f8vf2XptBWvLfkHeeHZaxkfSgGjslr74kfR73Iao6ljY6q1L2k7Xhg0rZz9EQVZKOcRwHL7zwAgYPHlzmA+TUU0/FgQMHMHnyZBQUFKCgQD30derUQYjMrzhiYmIQE+OHvYuio8tdN4gggggiiCB+jwiIqRWPKvkImTFjBjZu3FjGoG7x4sWYP1/xBZo2ber7bf369cjIyKiK7gQRRBBBBBFElUfACal4VFk6pqrj4EcPe8tM+vNUEFcJ1G210/bcrPTJJmOm5twYYgGwMoWMVvzccwCAqN6UrkgiK2xNAGQtBidXYEKPfMrW6HEqXeOzc2/YRvavNTuc1ULiZDVHQ9SLTBeVwPD5Q/DzcFfS9qToatQk3XxS8oyVFJKjCaE+6/SdmkBGML8vDFlspaRbnO+E6Bi+SKUk3AJSJN0tKrJ2Y02ao2tnp7HFvYLqjYU7IMRPZ/5s2aZrtvTJaG58JqmD0JkCdXukYSLgsl6CpztB2h98LKumJnRSutBu20V+1xoLfM5mXy6TTcmEzTOjCx2GK6VJqM58UZaNuvCf8vN3M3TfSLWSxr6n+cEkTE1cdXNkPLK2iaewSdoipS9LytLurtUoWR+DydkHFHxuZ0i6xtxP9bu+t7tpPNJz7a5QHDA2fPTWi6NxS2RY8zyVvjrRawtfcYtsqBV8nR+/ln01FcjfELndfUL49pm86dSOe0i0RawmSi2X9Xl8QeRvb5/LiKDcSl1n9wfpk91dIH53p9KtMelYAD5tFevYbPVv0rpx1sm70G6kU8M7JbViFEt9ismsvlzys1Q4AHejPKPmnvveT0Ry9UwgN9O7romkY8z2DqubFokKrV1PpY59iqv6GYr8MFvaSI8F2/T765hu8vOxlZMq+aVY3KD/kVf6FXHspvePvNKfJAJxjiCCCCKIIIKohPirkUorI47ajxCrPpVxLprtLdtdFSnRJX6J+72aVdhdhLDoK1c161FJI8fKT9SMsU1zshbn7WL0FzjPpqmcDLq80aJZkLNKkTd9sz0qEzUzDaselTSy50ptrajaVnxKfLO0PIVaOFtknzaVCqKdmiG4B6iNSojtesoC21kyQ/a/Wc+e2gvB16pNCpl6RurSjKRomSAAdo5GRViFdSeds74WvE9fOW+onOGqZ/PrHpNS3qbvUfn1alWeuGaCoFzNTyVEjCzNvfMoZwaOBkRa/kpmdHF3DFPb0CzSWSjlwFZdNQu0W0n5oFu4W/dNyHdODvXDeKLsJGSuuqjleiW4mZLSNOgHAITbK7+dyBohCLOfjpWhtnP3yP7tTqcCAPY+KIrGiU9fLH02Y5NKgVdOkuVWx6qZK6N5XNJpPFcc4ojxup7iLd9jQmr2vqBI3UmPnSjnEaWeBydH0DYu2zWlofYxgmq6u8j7RUdkqaAKIVYKNcc/KM+IlS7XvOhNRR6MuWmo7H/rOv1v8s9i/6ZcjaztzZc2GltGUdbueLKcxwbpn0EGrS5CHC2eKKTkcKZ6bn1l5stFOsDV5Hvnq9l0fIV4MWrgQ3U36bLn7fKMWS2EiO1qZV9GOnwePBrVjXwtpfs+pVPticX+RlyOG/nsTfU7vXcMcd6ncLuT0MZ0RbI16O1vFQEnpOJx1H6EBBFEEEEEEcQfKQIkpOJx9H6EsAhNbXJANTPS1HJ4IpSD9nlkGISB8tnsFhoVVqV+7kHK+5eTO3ZyV8gx2fNEz+5cnlGZ2TblbtkjApltyvTDriUIgatFj5ycDfQ7cTUa6tnuTzI7QVspqzN8AytWZpvG2ReAzP4ItbBSjC8FzWLoPA2Xwd0g5YMFG+SaVkvNUL+vpXx2tL/qSR2IkBLO8xoBJUIN7PZqxli/m+SQfbPAOIUgpDYhjx3qs+GhMArlE4cyiBqXdhYLjcpDUtiXiB2hzSyYxJ/c7doLgyu+UglRMrlv4qH4fGAMYseOsjSODAISakol6StJV0efP/OeTFuYdLNYKM6KqV7mONWrE1dAOyj7PJcYeTMl8aX03LJw2C59fXfRbJYQqRonqHP2hKsA7z5xab3z1VTZvbn27CZcqyzyGDqVHLNpBu6JmbHXEPXZ828hfpnhvDgHRazLcBoAwOFnx+ySvZCMcBjxUOyGx/x8EzirpNw/3LdPmXUtRpTIkdb4R0XIBRcNFNrK7tHMKTHcIrdQniF3HaEzrRSCwh7eLvNI9Di1m0gJsNU0S9bVIosWeVu57JirXcztVEGFjfeMu+QLOQ4LJxqfKnIQDuKPGZUuVpaRkQHLssr8/e1vqm47Ly8Pl156KVJTUxEfH49jjz3WZ2oXRBBBBBFEEEdjuJX091eKSkdCFixYgEhEhJWWLVuGU045BQMHDgQAXHbZZcjPz8cHH3yA2rVr49VXX8WgQYOwcOFCdOjQ4XC7DSKIIIIIIog/dATpmIpHlZfoDh06FB999BFWr14Ny7JQvXp1PPnkk7j0UimTrFWrFu6///5yJd4PFwXXCgQZfa0oKxqSVP6oN7y25GdHAQCclUKMMkQ5AECRgkiLF0jqgtUcTUqEvTgOPfy4txx1jIJ4Q2cMkm1+JBKWCbKatlIyVJ++FkVSqw6lU5IUtFjyxrteU7iFwJmIU/B+zsNS1tb4XbkOJmXis6jnEjzt8+ArVc6lEjkNn1st6cPQQJxE6o3MEhTLaqpJcVRK57PS1t49Br4F4Nl0qz4rCLf09Ze9pqhrpKTSpNMsW9JWkc+VkqbVilJNmyQdZHc/A4C/FNpnWa5LnZlwyEREd48qIWaPH4b3i55+HgCwVzimqPv0TfIf+po581hNV6Vu7LY9UF44O1SKja+jjyioy2k33ixjp9GkIfK7JqEymTV8hphERjZroiGlNCMfv6X61FlKYN0fBXK32maV7SilmA49oRRZozKkz1FXDpV19bE47eUj8DbMUAsHZIy6m4VUaNVX6SqrJREiNQnUSmEPHUp36Pv89emiAtvt9VNlnzrNcOj+h7y2mLOE+Ip6mlx5SFJ9zrdUOtvjJABA4f2i1lutj3oGQied47VFvv5EtjnuFHVsGsP7h/9Xtr9IHf/Aq5JmqHbjud6yu0rdO2eDpCv2fCnXrPatPdUCpZbtNjLOjKKr1Zr8cnT60mHSbg6V4OpUIBOJI5/KNTVE7bh/XivHmTtdjn/qearvTJyndJW5f5EPpYzeSpJ0kH3yAPw8vNQRpyxpPB96SpFZY6+S+xDX9x9l9lPZ8XXauUde6VdE961/nexAlbroFhcXY/LkybjiiitgWeoLsXv37njjjTewe/duOI6D119/HYcOHUJ2dnZVdiWIIIIIIoggqjRc16qUv79SVCkxdcqUKcjPz8eQIUO8tjfffBPnn38+atWqhXA4jGrVquG9994ro6B6pAg3FmdeH3FMz/ard6KSRkPCbEREPC4Rq632Fc1+MkSSMg6tVg8pi4tqKjNjWzta8mwVVO7mEdy4xNYK6eMIoRF1iZyoRcLCx5JDZnMResIetc/0TjIFt3m2rGc1Ljlbsp+EVy5MMwmXybyGvMnEVIOA0IzDqi/ojE9szeyGyydrJKl/E3mR751x7mUCm+9YsXp2RARebwZN5YNM8vRIppsFHbG6kZeIJr6y4BWY2LpTix7VlZJDJgVGdVL3p1Z9KqclUp/XlkGOteWJvRFiZc7ZuOlyGwCvjNV4wADwE5x1CS4TcD30A0CovnoOIhuldNNurUu9iYBrNSNfI0OepDJzd/Fs6f6Jap9GvO3nx/f2Q+Rqq02W/GBIj9XpPJqRUN0m5Utkx9P+9QzaI80CcKMFeTMkzFbNqBS5DqEmemyEM4hUXF/eQ6ZU3CeeR32CLsOtdhK5MmvyNpNN2TnYI03T/Y5pTe8Aff5x2bRNXXoe9PMYSpDxmrCDythT1bo+tG/vNvpdl8EzCV6PLTuNZA/4d0Ne5+euqbyXvKeF3y/saKvfdS4hZ77ro++T3Y4IuESy95yBSXDPSi7rzO6uXSp9OkH3j8XzfoMoO+KDOFJUKRLy3HPPoW/fvkhPlwFz5513Ij8/HzNmzMDChQsxbNgwDBo0CD/88MNh91NUVOT5zJi/otLIYdcPIogggggiiL9STJgwARkZGYiNjUXXrl3x7bffHnbdkpISjB49Gk2aNEFsbCzat2+PqVOn+taJRCK48847kZmZibi4ODRp0gR33303mMHhui7uuusupKWlIS4uDr1798bq1at/frhfjCr7CNmwYQNmzJjh43msXbsWjz/+OJ5//nmcfPLJaN++PUaOHIlOnTphwoQJh93XmDFjkJiY6Pt78PPvD7t+EEEEEUQQQfzW4cKqlL+KxhtvvIFhw4Zh5MiRWLx4Mdq3b48+ffpg+/bt5a4/YsQIPPXUUxg/fjx++uknXHfddTj77LOxZImU8t9///148skn8fjjj2P58uW4//778cADD2D8+PHeOg888AAee+wxTJw4EfPnz0d8fDz69OmDQ2RlcKSosnTMCy+8gLp16+KMM87w2g4c0KqKtv/bJxQKwXEOD2QNHz4cw4YN87VFJg4FwlrDgbQ0vPp0Rkp0ioY9R1iNEjsUXOkWl9LvpLSn9RyYbOrB14CnBeFuF2Knm0eKiYaUV5NSDwYWZg8a1uzQapDuFoFS2csD2qtk3zq5lrFE+jOpIWe5+FLYLYl0qK+JVZ2gYEqTGNIf6yIYwqSdTP1gbRVznQmmd9YL2S18yQ3qd9KfYB0Uq4bqi1WNtEF4rNjqfjtrxJsG8RqWNqkewJe6MAqUqEvwLXm2mDSMRVCyL4Wl9T/cHXQ/88UXI7JWnx+NHV/qxMDulP5zN2g9mWZC+uUUjp2ZVaaffG/sdJUSsGsQvM0EZK2E6tMBYRKqTsOESH+i1PiXxJJGym7RqrC01wdD4oiKKrtMKU3v2gMeudMHo5dHKjzA50zwviYeO9uZPK3J16lJcsxdkk4ye7ej6DicfjyQDwAIdRaya3nj2eZU3C56HnXqJrKU/JF69tXr0fvDKf/43n5iKc1RWz1bkW/kXRNi/Qz9XoqsWitd7i732Utv8hjkY2kdFJ8miD4/3/trD52n1mHh++kuJyZ2gkqH+dJiG6kIoKZJUVG6mnVM9HPNGjLucplkunV0ionfVTqcFd9IP4mgHFmgUlThXg3LbFOV4fxO9bUPP/wwrr76alx++eUAgIkTJ+Ljjz/G888/j9tvv73M+i+//DLuuOMOnH766QCA66+/HjNmzMBDDz2EyZMVyfzrr79G//79vf+HZ2Rk4LXXXvMQFtd1MW7cOIwYMQL9+yvPnJdeegkpKSmYMmUKLrjggl/V9ypBQhzHwQsvvIDBgwcjTDLNLVu2RNOmTXHttdfi22+/xdq1a/HQQw9h+vTpGDBgwGH3FxMTg4SEBN9fjPkACSKIIIIIIog/UZRLQSCTTI7i4mIsWrQIvXv39tps20bv3r0xb968crcpKipCbGysry0uLg5z5871/rt79+6YOXMmVq1Sgozfffcd5s6di7591Yf2+vXrkZeX5ztuYmIiunbtetjjlhdVgoTMmDEDGzduxBVXXOFrj4qKwieffILbb78d/fr1w/79+9G0aVO8+OKL3hfZr41Q34u85chsKWO1s5RjbtT5F8rvc5Qjod1DjsEOox5Jk4hXTD58d7Sa+Z59uSAp9imksqi343JXK5Mca00JHCEAzrwP1QKV7bJSp0EwwudLqTCTDw2aUHsklcOSD4qzKQcAEPlhjdcW2pgj/e+uSgWdDUJYNLMwQEimpgSWw0mVPtvtqKTRKNPSLGfzO1KK17CTnh2xkiY/WG2UwqfVXkoKI19+IP0zCqOksmp3Uffhp15jvLbWn0opnrNIeap8fasQU4//NMNb9maE+TTrZzfQeXN052VGtWm0zPIavfsv/DxKX31S+tdSEeTsY0+SfeqyZGf2h3LMukSu1rNlZ12O/J5O4zVJ3fOowZLqNGW7gPjAMDG09K1n5XeN4pWSe2v4dDXOFrcTN96sObJs1IBZtfKjW6V/Z76nHErZ9Tgy63XZfpMar3YjIT+Hep4n667UM9p9osppdxH/lHVnqDLWzOfluUaSVireKLNyd9lS+b2JQioShp8vvxfJePQQyhxCV4g8Ca226zI5m9Cr/Xeo0t6ECWNll+vV8d1Vgo7YHWg8m3LdffIMhM4bIv3bop7XqKtu9dqcHFIn1SiZVUfGY+RTKW01EgU2KcMWPy9yAtFX3KjaJo2T42epsmLz7gSAUNts2f9q/S7cJu8v+yQhd3uO4POpDD1Lztk4eZfOX+y1hU+Re+tu133uMcBrA6GRpa9M0MeU8mqPyLxX3rnOJrmP4QuuVPsmsiraV+z/Mf9LOP9DKqW8GDNmDP7zn//42kaOHIlRo0aVWXfnzp2IRCJISfET3lNSUrBixYoy6wNAnz598PDDD+PEE09EkyZNMHPmTLz77rs+ja/bb78dBQUFaNmyJUKhECKRCO69915cfLHylMrLy/OO8/Pjmt9+TVTJR8ipp56Kw8mPNGvWLFBIDSKIIIII4k8X/wufo7woj4IQwzYP/8949NFHcfXVV6Nly5awLAtNmjTB5Zdfjueff95b580338Qrr7yCV199FW3atMHSpUsxdOhQpKenY/DgwZXWl6PXOyaIIIIIIogg/kBRWSW6MTExv/qjo3bt2giFQti2bZuvfdu2bUhNTS13mzp16mDKlCk4dOgQdu3ahfT0dNx+++1o3Fh8mG699VbcfvvtHrejbdu22LBhA8aMGYPBgwd7+962bRvS0gQd37ZtG7Kysn71uR61HyFvnfyct3zuC1KT7nzxGQDgtidF5XDs00pFsGjcw15bwTJBag7sU2S0zwuFJDr4IamZP+8tTTb7XkhQc88X6LFzb0UEjO4sUPT+saLYujdXQbzp1wrMb7XrpPb5tSgjFi8VWDX2THVOz/QVNcb+qUK6O7hfpYCuKhDYcuq/hSxrZymdEs90DvCRwSIfq2PZLeQ8Sz+StJa7V12/cJ9e0rZek+HihAS5vr9A0Q3O18Q0IrM2uF7IYm6e1txggu0hITpGZn4MANg4SVIjmS/LF7dboNJi7vcC6+YNHAEAaPWmpK3ybxztLScMVaSq4z8SNVtOgxjSsVVbdF+cOVSqlphQpp+N3rjZW57YR41DorLixncI/t+t7ln+DaO8ttJDis+UfOPxslExpaXi1XUM9aP9kOGigfpvuU1UKx/8l0Ciex9USCOb0cVdQ0qORguESKgmDXPs92ILn9tbFDDr3qDSi0Wvybg+8z1Jt37ZX42dmlFyHm0ektSF3ThDLZD+Q955kspK1BIzofQkr+374fK8tv9UpRFKX5fnPrI5HwAQdYKo5VqtSTlX89EGXvWx1/TmPyj9qU3cDs2RNGZsSLhmRvPELZQUzoFPJDVSfYRSoR3X6zGv7fqzVaot3K+fbDPmCW+52nBFzmai8iNnyX28sa8a+09/Iung62+VG5l/t1p3zQoheabVkRRWSuRzAIBDBnVRF1ziLRdPHKf6d4GMLZP+K31L+lHwVb63nDQkCwBg0T4X9XvNW94B9f7s8/SxXtvq8+Q+NZ2o1K3D3cVQ0Vm0wFu2u58AAFh4gtzvsC3/O2/3ukr1uUuIhKp1UpxcSZGD7t1/+78CABj+H9I++pNGdHQ0OnbsiJkzZ3rcSsdxMHPmTNx4442/uG1sbCzq1auHkpISvPPOOxg0SN6TBw4c+MUikszMTKSmpmLmzJneR0dBQQHmz5+P66+//lf3/6j9CAkiiCCCCCKIP1JUVjqmojFs2DAMHjwYnTp1QpcuXTBu3DgUFhZ61TKXXXYZ6tWrhzFjFHdu/vz5yM3NRVZWFnJzczFq1Cg4joPbbrvN22e/fv1w7733omHDhmjTpg2WLFmChx9+2ON6WpaFoUOH4p577kGzZs2QmZmJO++8E+np6b9YaPLzqHLvmKqKQ9++5S27PwhR0Opwom4TjwfzpR/qRbPhPClx8wifPh8TKRdbdqGaWba+lVCFOFI/raeVG9lfhL8gTVkeE0vXLFULqeWrg3o+LmmCJBgFRw4uh/UpheapUj5DCAQAq6aoXdrHqlm4m0+lyjFCyjP245E5U8oc08ok9U9WPoxXJXRMFCwc/763HH+lJqPF0xSd7MGtBqRGqcPNIWKVmbkTedBuoNCfDec/4rU1ekv8ZpwVamz8OFTKeo95ixEGff7FVNdePUl+X6jIm1YHmcUdnCBoQLX/aAIhldMykmJlKvSLrcuNN427nJQuCT0yM3g3j8oka5VjSV6HxiOVftrtstX2TISeQx5FRgmVSnANKXDrwJFeW70ZT3nLpT8pxM6iUuFvzxbkrPNjSs3XbiPojrNWNAc8FIwQJ7uplMY6W7XAEfm0MFE672+TAACpE8lfSpe0uxtpjOyjZ9iUv1NJtZXRssz2pa9IHjzUVfpkSnCNv5DqkzxjB+8bBwCodufwsudB/kVoTujM6mV6n+SdwsqxRi1Xe0sBgJsr5HK7eRfVViDIWPFEQVqiLjivTD8jHwlBOHSKQmhKJgvCGmqlxqjdjlROqZTa2abfRTsFdbCaCeoBg1Buln7ydTaE/chngh6HOtP2GmW0jpHj8/MQ+UChLgYxAQDsz1f/5nfJlo2ybN6F9B6O6/PLqEBlxNSUX1eWeqQ4bdvrR17pZ/H4449j7NixyMvLQ1ZWFh577DF07apkGbKzs5GRkYFJkyYBAObMmYPrr78e69atQ/Xq1XH66afjvvvu8wmL7tu3D3feeSfee+89bN++Henp6bjwwgtx1113ITpaoV+u62LkyJF4+umnkZ+fjx49euCJJ55A8+bNy/TvcFHpSEgkEsGoUaMwefJk5OXlIT09HUOGDMGIESM8/xiO6667Dk899RQeeeQRDB06tLK7E0QQQQQRRBB/+rjxxhsPm36ZPXu277979uyJn376qdx1TdSoUQPjxo3DuHHjDruOZVkYPXo0Ro8efdh1jhSV/hFiVNZefPFFtGnTBgsXLsTll1+OxMRE/OMffhfD9957D998843v6yuIIIIIIoggjsYIvGMqHpX+EXIklTUTubm5+Pvf/45p06b5VFV/bbhbqba/GWlyaFW9yCZRLAydqtTcHFK99Ck/bteql5QOsZsL/N78DL0up2AaCMnUzlBQtLtP4G3WDDF6DWyeZXXo7fsN8BtNWVlqXWfxLNlPPJmHaWXIoqlC8Iq9RfoMDefaIdGCsFp1kt+1tkmIdB1cTgfpOn3WanBXK3idtSCM6iQASTftlhRPTBNRP7WzlFaGTzGVTc6M6idpBNhtRLvAEGsdMsVzHbVuvYuFqOczutJpkFZXSYqIzeis2vqeFJFSJ6fNSLvFROxpAq878xTEbJF6qN1dNEF85opmm9ylaiFNUnGcyjMmb2x77zOo07ozrKESOuEs6bPejhUsrbZZsqxTaEYFVfVJpTQMARWQFAwAhFurNKezRXwhOgyiZ0jD3txnqy6RAnW6i58r96Ck4rwUG6VjWE035a5evuMAgFuws8w+WVHVPG+s2xJ1fH/aXqURQmeI5oWdImPDjEe7vhC+3X2S2okdMkAdc+ls2b6jeq7dZCLAcorpOEVydw+JToi7VASirHaKUO5TZz5O3o/m+rp5OXJOZ5JIVYYamxaR0N3jRLPDqL+G+8g2RhHV/y6SdI9dT6VW+H+w7kJ6L9VWY5yfVWcVEU9Niu5kMqOsJdfHitUkU06RU5o2dIq6P2wqasaB88OXsp+mYvDpfKMIuqF+lVdK+mvi9+KEHM1R6YqpR1JZAxRz99JLL8Wtt96KNm3KOq8GEUQQQQQRRBB//qh0JORIKmuAStmEw+Ey6ZnDRVFRURnJWjehLmKio8qsa2bmdhYRn4zHBM9KS6VEzmrcXm3LSEah+CQcWK6OndidLOiJkOlqoqH5ogeEpKk6o2eJbKntHUdme6EMmWGbWZrVhFAengnoWUt0d7HU9lnQm5kMKeAx+dKUyTp7iGwWSwiA8YFhDx1dXsnXxkqga2pmqVSGyWYK3vWl8kQmlpn749KMyGXCqJktV6MZvu6zsz3fawuzjbn2u4jkygw2in1imIxs9kmzSEeX2Fo0s42szJFjnalnqexXw/uMVUgQ+15YLRQi5e4gIh2jL9p3xOerQ/1zQ5rIR2gce8ugtKjMPn2hFYIZMTJKqFyCG922i7dsEBDjWwMApblCrgzXVeiN8SwCAGeX+AYZTxZ+xhiR8s61SO43IxwlLynVz6gW4n/kPWOM4O0i9CgpTR+HPEvYu8X4xOyU0neXlZQ1OdI834BfcdVdvVytd2w3aSt3jBOCaQilRHxHA9FmMM+oj0BbIu8+M95degbc1eTj0kSTnslLiK+J21D3q0jQGYM8Wony3FpE/na0Cit7W7mNW9K62ueK721jepeZd5GPhE7oknlnkxqv68p7y92Wo7ah8QIzdskzyud301mhP75njC5pVYUTACEVjkpHQlhlbfHixXjxxRfx4IMP4sUXFRt70aJFePTRRzFp0qRyiarlRXkuumNf/uDIGwYRRBBBBBHEbxQOrEr5+ytFpSMhR1JZ+/LLL7F9+3Y0JC+OSCSCW265BePGjUNOTk6ZfZYnYesuerfMekEEEUQQQQQRxNETla4TUqtWLdxzzz0+xbQxY8bghRdewKpVq7Br1y5s3brVt02fPn1w6aWX4vLLL0eLFi1+vstyY0SGGNjd8bgQLovfUuqI188WmP+5sYqAd/C1mV7bugWiu3CwVH2LvRUrinv33SLpFvsEZXzkkuHXxH8LybVHRKUuWl8rJMx9M4R8uWOTglAbnSoQbdRJisS1Y6yQ/6rVEog2tp2Cmke/JbDomYfk96RYBdv+rURg1Wm3kX5Hmq44onSHmyt9dtYrmNKKkdTEvllyXwp2qOPWv4Iql7TrIquwfj90qbfcqp+6DqE0ST3YzZp6y8VTlXZL9Hl9ZJ87BCqOrFSkwjdeE9j3ogmksaBt3t3dklqZN1qRYI+fdqnX9sMZotZ4zBiFwYZOFMXQ4gn3estuobqOoXZS1+6slzSCXV+fKxEi2QhxZP+XAQAbXUltPP88GWXtUVD0ghvFYC6jvkoR1bmTrgPpW7i7dCquFZ07Qdml05WpXs/3JE3w5VVyn1ZOUvB99eoC4zd4QszikKMVQolM+7E2ozNGdADw7QBR8DUkVE7BVH9K9DUmt79L/U6TuEseJq0AA5sXCGF7+T9F+Tbj2HzVpQZy7798S8Zur8cUfB9ZINsULVfbxHYVTQy7fXs5ptZBOfZfs+WczqGx2UilH+aMk+t0/OmSUghnqt+dLTLevn1PUivdJ6r3ynU3Cwnzv2nq/JJvFeJn3n8+95ZTb9UprrqigXLLNdK/ezqolMLNSySFNOEcIWqve1e9rmc60o8SuuZXZamxa4WlMe7fQ73l7deOBwDUuW+gbFSgU5ZfCxl2/TuStso4Q6VGwieKjseSm2Q8z9Cpm3/+XdKgix7M95Y73aMmnG4JmdItFZXaqBPU+/vd2+T9VItSbD2f0erSi0lXR4eVRO+3XTK27nxZPa93XyXz7PgRk8tsX9kxJfWiI6/0K2JA3qtHXulPEpWOhBxJZa1WrVqoVauWb5uoqCikpqb+6g+QIIIIIogggvijRVCiW/GodCTk16is/TwyMjIwdOjQComVHfxcrMndhV+X+d0+VWZ+JU8qb4dwn2xZoTxyJJFV3a2CZNx8nyJm3d9VZkmxQ6+RdXdrQtQuIp6yYmo9TajKka9/d6+e+RIvxu5xmvy+RCMkpLZoMXlx24Yy5+FukPJE96Ca4e94Q4intbrLN2f4FOWn45Bgjd2ZFAu1v0hkiXhleP1Ikn6Y8mdA1EdL3njPa3ttmpDdLrtXzVgjP8l1cHbLzNorNYwVRMlZLLNMFBXrbQQBCJ9zDgDgx0uEI9TmfirVy1HXac5jcp16PUOlyvqeu9uJ1JYupaUGPXK3yb2fLRWfOOkZpbBp1RPEp+SZidK/bllqISFJNkpQs/HiSUICjTqOiHoF+vyI1IsDVHasr7/VjsjXTLg0JaG1BLE6NH6StxxzYmt9UCor1jbuxgMGAHqMp8o1M57rCurw+oUzvOVLvlNiRZF1MlstfuppbzmiPY6MJxIA2B2l/NuUoru7hfRsHy/W7esvUuhWo6FC4rTqaCLzNkHTSr5d6S1HHa9I3XZ7OaZ7QMaOIWy6mwX5sprSREjPxo3aKwBY8UIIXX2XUj9t9rRU/nnPzTJ5rsLnyOw48mnZNHLoTPYa2uI7tlohXGbZ/Y6eC0IzrSQ1tozaKwDsvVOQwYQRKk1+cLx4v8R0UaXMduvWsp80IYE6i1QZrDcuAdgNCH1qp8q3jS8NAITPPdtbjkxVar375wtSkfhPKYs2aKjdVZBBT6UVgPPl5/o48lwjTt0H93tR5Y1skHEQddkQ9fsaeX/FXSIIaFXF22kXH3mlXxHnbX2lUvZzNESlIyG/RmXt51EeDySIIIIIIogggvhzR2BgF0QQQQQRRBCVEEelEdvvHEftR4hNNeMRiyyeu2h1wAIhk4VaZajfGlKhOMGynn5IlMCaDsHbx0TUvuzqdLnod6u+IuD5BiClFKzq2hK8oUCkVp4mkDUk8h7DrtqAibVNWGvC0y5YK7CvsR5X/VN9TsiUNESoLZ2/Jgr6IFgyzbK0HoS7RaBoY5XNx2FtFNRUkH24paQzWn9MqphaIdQukDa7DqXFdJqClWXd9aLQaWnFWitJYN1QZhYAoDgidu12VrZsX/gRACBikZJnHSEFukVac4MN5JJIfXWhMr6zm8p4a1htmexLKz9a8XJN7LpJ+HkYUzkAcNYqcmW4pfSDbcjtVE2IJJtyq5HA38YEzm5EaafNy2X7hjqNQtohURl0z8z9I6KgUcGtGSUkTTaj81RYSQeESagmDRNqLAZw4TYZsq8tWiuC00asZWHME6lPfKzqSapfVgY9Q0ZllsjXYSInWnW1rg0/66QDYtR6LTqmL/R4tBKIzEo6KSmZKg1s6zEIAK7WD7J3kjEk3QcrVT/PlNrwpW4PqPSk3UrUR1k3x3suOTW7lsZjc0WWZc2fai3J8FHf53BtSuEka5Irv7NY3bmlTh3/tFT6ScRa834LH5clbUny3gplqbRY9YiQWX3Gc5qsbPYDABapJhutI6sOpUmNFk+UvDPtBuVoFlWjMfYbRMAJqXhUuk5IEEEEEUQQQQQRxK+JSiem/laxf7iUXIYHij+AUe/bdc1/vbZaz48C8DNF1PWkMqi/tJ3lQmoLX3itt+ysU1/w7IVR9DjZZx+rZhd2Nvl3kPcCtisFTFYR9NbLkVmMb5aokYrI9OleU6itkBcRrWZXu8aJd0Kdl8XJ0Kiz8mySz9+bndEx3ZVUAqdt0NnjwcwoWdk18sU73rLVTmbO3jb5dB10uWroWCEcsrqoQXecmVO8tlDfC2V7jRRZNIOOzH3P9xsAIJFQCW197iwVrwujWAoIEdCnpsseGttVKbOHLsCvGBuZ/iEAoHixKDPG3UGaNkYtd9XiMm0+pIG9awzKRaqaPIN3NinUY/foKV5b8n+pNHBfvvp3IREJO4ifjTk/oyYLAO4yXZ7JM8c4WTZjn9VDsUOQmpJpahwy+hF1GVnc69k8q7T6xluyeOd4v69ZUaYtdJI890bFla8Nj3dzHVf1f9xravbSIFlX+8Qcunuk1xZ9zinye6PWvv2oPolvETIVshiZImTT0LEKneLrzR4/nhcToR+HxjzkLceckw0AKJ230GsL96VS7r36nhXke027n1vqLSeP0O+gGEI/GorqsrNa7ZfRQOMjBVYSpveS1UCdJz8jzrefessls5R0QfT1N9LvIocQOlkRb50NRHIvINVlTYKNzJ4qfU4l9VbjCUNItbtfoyeJNG6IzFv01DOqT5df4rXFnTgEVR2vpVcOMfXCLX8dYmqVICH79u3D0KFD0ahRI8TFxaF79+5YsEDY3K7r4q677kJaWhri4uLQu3dvrF69+hf2GEQQQQQRRBB/7AgUUyseVcIJueqqq7Bs2TK8/PLLSE9Px+TJk9G7d2/89NNPqFevHh544AE89thjePHFF5GZmYk777wTffr0wU8//YTY2NgjHwBA6UbJ/UbRzNhZrr7KXVdupHGs5FlcZNFSb9luovKfhV+JWFfCKeSZYso4yctj3woBkJLqqO1CISl5dLeK8I7xw3DXyDGtTDWzdlYK+mK3ppJIXXpbskGOaacIqmAlqzx1/g7J49amsjbfzPpn5wGIN42vFPAQzVJXaa5JTbkmdmeFYDiE8jgbSdgrVQug1Rb+Avbny7IW5PLNppmLoT1Pir5Z5zXFZZPfRLUktf1+ufeGN2G3FZEqdy2VQhskh0XbtqyRY+qSSquWoFzOVvog3qIRjiZSDmtKkQGgdIXizJTky3ioxt41Gn1y18u9sZo00edDniKMSugcP/sG+RCEDQpV2L9HuAbJB8jTZIu+J8x14PtsgtxdnU3qPOzGGbKfvfmyrvHwodko+3aYElyP+wG/K6rxBYnQbJjLopGvz5/dX4k3YZXn0qu9TNytMl483xy1EQBg+wF5RpruJqFEfS6FawX5ilpLY6OmnvlvoJLy9fJcW9rPKrJDnjV7p77f7K8UQ55O+j7bSYIwlubL8aP1NY9sJV8e8tNBoWov/lL4FVs3ydhO3qPHZiy5P9eV/nnoEns2eagoPZcsnrdO3zPtSK06SF5JxQpJdvfQvalBz5u5Foz0xkmps4f4kc+Ve4C8bYw3VxTpS5nj0zvX+VpQYztOt/N7OIg/ZFQ6EnLw4EG88847eOCBB3DiiSeiadOmGDVqFJo2bYonn3wSruti3LhxGDFiBPr374927drhpZdewpYtWzBlypTK7k4QQQQRRBBB/CbhVtLfXykq/SOktLQUkUikDKIRFxeHuXPnYv369cjLy0Pv3iJrnJiYiK5du2LevHk/310QQQQRRBBBHBXhWJXz91eKKhEr69atG+6++260atUKKSkpeO211zBv3jw0bdoUeXkKsktJSfFtl5KS4v328ygqKkJRUZGvzW3bCDFhXdbINua1lYdGQgdq09AdK46Gskh9T0e1TgL3GdIaADiL5qq21gIhJp9DJWzNtcoipxbiyUZdQ6OG4AUIycs+VuzKuUTNQMXRbQS2tZpTia32a0hrQ8qJZBlu65SIs1EIuFYCnZ8poeM+s/W7gUBrSJ88O3ciutlthaRqa3tuQ5wEAHcVlY521x+eTPzcSWkv3b/YM8VC3komAp3pR64QFu3GWkGTlGM93xwIUdHNIxidCcI19TikNIMpYwQA15Qtk506HyvcTJEiw5kCJXNKwU5RaQg3I0N+11C0L+1DKRyrhUr98LlzusZqpPaZ0lFIknYGleuG9fGJ2OpLY9TS5d/Jcp3sRjodVYsIgdUkJWA3V+PUR+7eKGkKTwmVic6UQjJpmFAjsnjfJcRWQ9Rk0rG7gYip/Dz9LLxSXfhLxs3z1DGb0piNqCQ9rN4Rif3ETNM+XlRczThw6P1ic5pDl1WHM+i5aqXvA5cfU2m+be4pPWtxXeUZtzsoiYGozZQGbSypRidepfWiWktKsGWqpE7QUPWZSaRuCanttlfPlkVpDJj3Dj2XqEPvHXpvlBdRndT7z6THAMANyzNg7qlbLGklqyaNMz0e7Qx5p3JqxpRFu1S2a+vz8z0XTUTuwN6p015azTWIP25UCTH15Zdfhuu6qFevHmJiYvDYY4/hwgsvhG3/b4cbM2YMEhMTfX8PzvruyBsGEUQQQQQRxG8UTiX9/ZWiSkt0CwsLUVBQgLS0NJx//vnYv38/xo8fjyZNmmDJkiXIysry1u3ZsyeysrLw6KOPltlPeUgINi5EjPaicZZIOZhP/EuHIfrxV7FbJLM8TwSMZrjODpk5z71I7b/7UEkxhU4VbwQPTaCZH8+Gzf55NuqRG3kGXl9KcI34lFVHZmmGmAnAQyoY6fCRvXaqmZTzvZTaseCW8e3g2TiLlXm+Getle+Nea9WTGUuIRZU08dWZ95HXtmO8IDV1HtTla7sJ8TpApL5yZi3O+nI+NomoZ3dQ6Mr2i+702upO+rdsr4nKm+6c67U1evtW6XOBmiWzoJXNKNiP2peIZsB7H/rEW04af5vekbw6nHnTvGWroUIteDZrrm1krlwnqz7NAg2aQA7DPqKhLkHm8mkfkmIIr4RyRaaJV4jVJst/HAAhXcqcd96/vLaU52/zls3zwujMj9ljvOU2n+ryTCaJL5TrYEio7AwcPla8kiLLv1LrbZPnzm4vZa4FN6hy3xr3ShmoeR6YAOuuE6K31UQ/T0TI9qFcGiHwfJoAv1dTgi733SdEaFQTBKNonHKkjb1VrpOTrxGMjfRcHdNNjmnKkhm5o9891JbE77iM3SAcLGDmLJU0tt3xBN96AFD67gvecvicy1XblEmyTTONnjQT8rVN20fWL1ULpvQbfrkC7z4sF9FIu5X49Tg5CrFzFkrZsd1b7r1Xut8222vic3a+UeXAVgd6P+jn1d0qhG+f0J2+pp4XD4C4XlehquOFepcceaVfEZfnVr3j7x8lqlSsLD4+HmlpadizZw+mTZuG/v37IzMzE6mpqZg5Uz4cCgoKMH/+fHTr1q3c/cTExCAhIcH3F3MYM7wggggiiCCC+D0i4IRUPKqkRHfatGlwXRctWrTAmjVrcOutt6Jly5a4/PLLYVkWhg4dinvuuQfNmjXzSnTT09MxYMCAquhOEEEEEUQQQQTxB4wq+QjZu3cvhg8fjs2bNyM5ORnnnnsu7r33XkRp6/DbbrsNhYWFuOaaa5Cfn48ePXpg6tSpv1ojBACcTeKZ4tO30Foe7hohRBrSm7NbfFDsdEnbOD9qqL5YUj5shd0qQ6VO7NYCIbIioKXVS62WHaQfBCsjWdW8s36Gu11rOewSrQSHIFp3uSYdNiX9B9mj51cD0ocAeVx4Pi8NhHzo8yI5VhO/dsrxXaOJAQD1MtS/KcXjeZ60I6i1gBRRD+nUCtmd1+xOaYQ1OrXTRMiBbs582ZeBsuk6sIqjd61SJCXgLFNQenR1IWH6UlRaDyG5IY0R6rObq2FtSve5RMa1WigvFHeZQN7xWXJ+bp7SqOA0gJtP2iYZeuz9IMq2qKvHwSHSf+D7qPvsMrwsv8LVapmR2XO8tnD/8+R3nRZ0dwm50WqYITso1P0jrYfISgWlJ5JUjZ84q55N1srJODZf1l2sFWlJqdOngmp0QIgXZlIwABBqpdRjHXpGnFXfSv/Nm4pSSM6GH8uch5VE5G5NhDS6KgDgRJOSqPaf2v+OKLfGX0PKuZo86lP1XSZ9CjdUz1tkzvuyjSFUVhNtEqwTbRRPM4jvPekH2S27qn7OEy8kfp48wic9F/veFoJygj6umyHvN6uOEEsNadyKoefKjH3SFvJSMACQq1MeqeTdQlo/zjf63pcKmTRC3jlWY9WX4uWSXoyJl7FrpSlyd2Q+nTOnH/X71Udi3633z4TlOknSp9lKpdbuLgq4v0X81fgclRFV8hEyaNAgDBo06LC/W5aF0aNHY/To0YddJ4gggggiiCCOpgg+QioeR62LrvuDzF6sRkIkNLO80iVS3hfuqGfeRFBztpCq5hb1he3myQw51ELcQKul6y/86kleW+TH2d6yXVfNvux0IZEyedJdp2dsCeUo/lEpGgiJcPM18er7pXKceoJquFqt0lktCo92XZlFGidYi1QvnX2kQmgUU0tltu1up9lLUrK/nwDgaCyGVS15lpesPTyIbGvFkd+Ddji1W5CCJKlJGoKaN2sGPDdhtaGeRTNitEHN0uKaywzXzSFSYGNVPhhdn/rBREM9C3QLCYkwKBUAK60xfh6hDCKE6nvmbhFEyapFs3FTjruYSHnV9MyWFSQJhUOsJifybJp+d3eo67P3K5mNJp9ASqDm/uwilCrMJZl69kikYOxTz00oPUnaSFHVW6ZxHdWASjJ363vG6E0SjfdyfH8YLTQICDsoRz54SbqfoBVT95DK6naN7JEDMZeWegjoBplBh9Ko7FmTLw/skPEcz2PbzPZ3y3Nhrj0f11kv+7dqJalD16AZ+n5SItV1AJYt2JZDlhVWQzVeI6sEvQm1FDKtt5v8fG953zYZ+zV2qf5ZqXLvWLHVKAT73jvGS4ifi+3knm3WZX+mPTK2nFy1bCXSvaXrFGqkniG3VLBch9DCUEP13nQ3EhKbIOiPZZCgbdQncx0zRLaAUbrSn9R7IfoEGvdB/CHjqP0ICSKIIIIIIog/Urh/MVJpZUTwERJEEEEEEUQQlRBBOqbiUaU6IVUZRcvErCgyk+zkMxT0Z6U38dqcrz4DANidqc6coHCv9p60Q9yVYr3+zm0KNu5/jkCMUZcMlnWNoRqTKCmNYTdQ6SBjow0A2FlWHdbuMUC6950ie9mtSGOAdUg0WY7N1DzCIQBnpUo3RXLkOOFjW8ixtKW4u4LSWmyYpqFod4kQR6FhXU4T2Mf1lW20eqHz7ede28ZHxVys0aOa2JubQ9uQTohWVHUPSZv7I/VPE9RAaox2h14AgB9Of9JrO+a9S2X77xWhdMkI0RM49l0icZrUC907KzXDW3a+1BoF9YWUt+ZWuSbN3hyiFkiBMvLRG9I/rURqtRU9FQN/m30DgJUidvSuSUcVUIqoukDdVnUFT1utRW2XU42eVgeZuTmfi7aJpXUhOHVid1DjYWn2w15b+7fOlT5pqNuo4gLAzOynvOWTPhqo9q0VagEgMvMt2V6b0dkNJL1mdz1D+qdJqO4y0YWJulK0X9Z0U/ogGc/IvTPqo84aGSPOMiEl2y31eCejPVZXdYvU8+TMnSXbZFJqt4F+h+SLSiyqSZogf5S6z8lP3C7HX7tE7XuDjDe7Yw/5fbl+rxAR2j7hdOnTthzVVk+e7kuePwAAsvBJREFUVdZBMeR2Jmk6X8yWfXXrrteTtFPJC896y1GXDQEAlL7zumzTRKVD7PZCODdKvwARRgvJULAdySnose8sErJp6Dgi8f+giP+l85d4beH+Z8n2m9U7wu4q7xIez5GPX1W/95R9GgNOdy2pM++WdEx4wGDdpxleW9xlomtTVfFEg8rRCblhU6AT8v+Kffv2YejQoWjUqBHi4uLQvXt3LFiwwLfO8uXLcdZZZyExMRHx8fHo3LkzNnJOMIgggggiiCCOoggUUyseVYKEnH/++Vi2bBmefPJJpKenY/LkyXjkkUfw008/oV69eli7di26dOmCK6+8EhdeeCESEhLw448/4rjjjkPdunWPfAAA01PO95Z7TKTS2PVq1vDkOEENbniyEwCg+G1RqNy9WJJ3hfvUDHtzocxyet4rJFBDyCr5eqnXdHC1fKnXGKBmLUzG2v+VIBT7tqv9p10sfgmhE1XpmEdaBVC6SNRJw31PBQC8c6WUBJ7WXgiTO9eq2e6l+2W2PPtvGbL/k9SsIvLJe16b3VMUKCMzFZIU6nGC1+Zuktmbs1Z9EIY6ZcnvOTkAAIsIsrsnSOlq0inq3h2cTyRJttO5vp/aT64QErmcFfsVma7wGyG91fj3xfh5lLz+tvTzgEKcYq+73Gs79Pjz3nLMOdlqIYXKC7+j0k9TusrW5LlUCqhRF+6n3VpKjCfcpO5ZXeL5DXxNzBlNmWjxi4IKbJ2vxkPDYUI49JEHtdeIRV5APjKuRt7euErO4/x75J7sfUG11zhBZv12ayLw6fJJVi/N+Zt6NjLfFkXSvMGPeMspdynEKbJAUIdQFm0/QqFD1ZNkhl9riKAm0IiX57MEYP8ThASZytMEGTBbF0uZZtN5jwMADt5xvdcW2amOFXu+jGvo8mXVATUeb7lZUM2HRmZ4y84WhRLaqfTOofvg6mfLShGya+kcKSuOuvRKAMAr/WU8XvQfjWilyP0o/WQ6bXOZ2jd5Eb1zgczWB1ygxtm7b4gHzsDHBaEselOp0P40W8rx298oKJndVHsVcYlsS/LrWaxKsa2mVMKrUZPiyTL7PrRGCMg1rtWo6WZ5/3w8Voivx1RX4zFjwple2/rrpdw2836NmrCEAKGhpmQ/9zpR9d2VL+fU7mWNgGwWVNXc2+J3BOGLaiso1hP6/f+3h2Xcx503AlUd4ysJCfn7XwgJqXROyMGDB/HOO+/g/fffx4knqvTHqFGj8OGHH+LJJ5/EPffcgzvuuAOnn346HnjgAW+7Jk2aHG6XQQQRRBBBBBHEnzAqPR1TWlqKSCRSRngsLi4Oc+fOheM4+Pjjj9G8eXP06dMHdevWRdeuXTFlypTK7koQQQQRRBBB/GYRyLZXPKokHdO9e3dER0fj1VdfRUpKCl577TUMHjwYTZs2xZw5c5CWloZq1arhnnvuQa9evTB16lT8+9//xueff46ePXuW2V95BnbO9CcQE6W1B9gWWhO32KDJmM35NApIHdAYfbmbRTvEaigwXunkZwAA4bNFgM2ZJ+RLq56CM0NEtPORSI25GUP+B/L1MUkjoA6lDEz/WD00nmzKDRlsrkC5oXOulv6tUxC0lUhEPOqTXU+dn7tdUjBMcvWuKSlcGjIYm+qBlBOtWg3KtDFpEDGK0Mq28y6RJ21Naoz8MFv2WV9gY2grb7s2aUlsVOmQ0imSdooacq1sb6vrVPzseK8t+iaBZZ1cpSdjxSfJNkSudFZo+Jos4J35Aq9bGdpm/CchVHp27iAbdDKTM4aGrODrmaUBcLcS7Gx+Z0KlNu9yviIiYN9zZGVtPe/uEVIy79+Yozl07y1LaV6UfjLFawv3J8FBPQ6seIHUS154TH7O1ATcDLKtJ9M+Nm+UThMQq4niPh0QUusteU2RQOPuFQKys031n63qfWZzWvm2eLyYYkb/42Zv2dyH4rGjvLbweQOk/9rszmc8afR1IOlLK5n0ULT2itWmq6xH7xXUVGkEi4jMzvdi/GY105K1BWRRz+8F/bxYZFhYeN/T3nK1my5Uv1Mqj/UzrOrqmvC7wNx7u6HI5bp7SRtFv6uMgiwAn7qqs0ipFtvHdJFtXMlPmrHnLideYA1KNZr3GunSsDmj6b+VTDpJ2pjOio0vsx4A0RSpLf9viOsjqcaqikcaVk465uaNf510TJUQU19++WW4rot69eohJiYGjz32GC688ELYtg1Hv2z69++Pm2++GVlZWbj99ttx5plnYuLEieXub8yYMUhMTPT9jX17VrnrBhFEEEEEEcTvEQExteJRJTohTZo0wZw5c1BYWIiCggKkpaXh/PPPR+PGjVG7dm2Ew2G0JnIfALRq1Qpz584td3/Dhw/HsGHDfG3OvFeAaDWb8KEa+gvZpy6qy9ks/tLPy/GWzczcLSaV0wIpyzuwJB8AUKOVlJhZSYJKmK96l+zc3R1S6WPVVGQ1nvmWF4wwuMa3g2cHUUReNDMh8oBwNpOfzl41k3LziGRZl8i2xmOHCHI+a3jjcbFZFFmRphEImg36Qs+uPA8YAJG5MssL9VNleb5ZMZVKu3pm6lObpftgZj3saWKuibOL1T1plqb9UyLbqOx3LymJmhknWZe7B4ksq1U5LUJvIt+LT0xYIyFWUyFcopQQL4MeESLlU0o16+0SXx9PobMaK5ISQrBfl8s2E9SBw4rSY4Nmyz50JUXfR0bZktT5Rzbne01hnmXq+8BISNFyWbdaF6UwzIiNs4XuE+3La6PSWc8HZrtcB7vjyd6yIaEa9AMA7BRFRCxdIIRzPidLK/eGGtO4JpTOPK9WNSqt30Gk6lRN8uQZdqyUp5cuUs9b1MUXyu8F5rnLkX4k06zelNYzMpYq5bReG6EfvpJ08y5ZS+WuSfQaN+gSoxbr5L3gmt83ynPtalVi9sjh7b130X5BmYzvDkBoIL2H7YZU7r9PP8Ok0OuTA9ih3otWXTpnQoqMd41FxzRj25RZA4C7TK6JkWNwSf04iD9mVKlYWXx8POLj47Fnzx5MmzYNDzzwAKKjo9G5c2esXLnSt+6qVavQqFGjcvcTExODGK4eAHAwOpDjDSKIIIII4o8TR6Xo1u8cVfIRMm3aNLiuixYtWmDNmjW49dZb0bJlS1x+uSqjvPXWW3H++efjxBNP9DghH374IWbPnl0V3QkiiCCCCCKIKo+/Gqm0MqJKPkL27t2L4cOHY/PmzUhOTsa5556Le++9F1FRCr04++yzMXHiRIwZMwb/+Mc/0KJFC7zzzjvo0aPHEfYs4a4mZcROvbxlS8OIpR+967VFddP6FDtFn4IJlx60ySqqRFSMP0GnMaj2H/mSkjBQu7uD9k/EMAMhW0kC+VvVdAqHCWqUZjCkOGe+aCmAyVrffw0A2Pe+GPUlnXaR/K5hW6PACPiJZwa2ZsMwDzYFPEt2i4z8vNQIQdJMYLMM8ZbMrYwaI+AnR3rhCIHNOz6pUjIZzZD5fP3USqdRxwu8y4RHu6VSgYzuKuPFotSLXUtD0QQ1+9IYWo+AUzjh40Wp1P1+sf6dDLnOEKVRQ3J1DxFZd/13+tzkflqkkAmdZjAKtIAf/jZRMlkIl+G2pMqZo6zd2XzPIgt7K0YrrqYmyTYb1fWJOoE0JTbK2LKb63MmcnVsV1E/dbfpFBuTp+n4Jh3kS9eQEqi3XzKjY1Kz0QJhEqpJw4Q7iz5F6dLP5PhaUfXgF/JcJlwsUgBGFTh0UracJ6dsdXqB25jMG32JIiE6S0Urx85SmhiGIA8AzjohLXupXyJkRz58lbY/Vm1DqYXQKUSIN9eM3lXRJ8kzapsUEhPGG0vq25DHXXo/eWOUxhungUPNFOHUKZBnIPLlh7K9TgnbPfpLP5fMlN+bKoKy1VbIukzUtpsonSdnuVxHnwlm2+P1ipTCStLvt1VCdjWKywAQmTpF9f1kUaP9s8eECRMwduxY5OXloX379hg/fjy6dOlS7rolJSUYM2YMXnzxReTm5qJFixa4//77cdppokqbkZGBDRs2lNn2hhtuwIQJEwAA2dnZmDNnju/3a6+99rD8zvKiSj5CBg0ahEGDBv3iOldccQWuuOKKqjh8EEEEEUQQQfzm8XuRSt944w0MGzYMEydORNeuXTFu3Dj06dMHK1euLFcAdMSIEZg8eTKeeeYZtGzZEtOmTcPZZ5+Nr7/+Gh06qI/CBQsWIEJuy8uWLcMpp5yCgQMH+vZ19dVXY/To0d5/V2P3718RR62BXcmXYiEf0048D8zsZd1rQlBrfo4im7Enic+/pEitW/Kt+BDE3na8t2wfq0l3VApc+NT7sm53Rf4MnXiq7HMDkcHWKhKYdbwQ7Qwh1N1I5XuHZJbnaILbwSkyO4g9nhCAODWz3Z4jM89EJpZpkqiVkiH75JmnQQuYJLmWiK3JGrWoSQN4f77aZyr58nwt5aquRqHYt8JHPF2r7lmoE/lKEDplyJnOfCKzUomuV1ZYjVCmz5RaJXu7OEuE4Gx3VCXfVhNRJ2XEytHENb63vvJqU5pK6Ikp/QSA0i+VOunBlTJzTDiXCJ0aAXG+kVJqM9vn8mOfP4hBx2g26GyT311NNFz3gqAvTTvL2DXEVeerqXIanUgZN1q9WNxdQsJ0ly1Vx24tSAijfR4CsEtIxXZ7KcEtflspeYZ3CaIUvphmYaa0NFbGq/OjeClZSfqa1hF0yFkgHj12ur4/XIKr0TxGP8JZ8gxGdPn1xp+SvLZWP8rYMB5Bh174wGuLHUQIgp7BOxt+8NrcVfSMNFb3r2i2tMUm6POrRsTOn+Rd5Sbr8yC0be8nQlivqb11iufJeyGmEZW2anKnQxYXO94QMm+Ksb0nRMpu1slbdhap59WqL6Rmt0i9v7isFqtFvdl7ghOoFJnI14dmq3XjWgki46yR8Rpup0iizmoq198j7zI3U8kFRL782muzkuT62dWTdD+JfK7J61Z9eq4Jzdw/S13TxF6/7WfB78UJefjhh3H11Vd7lIeJEyfi448/xvPPP4/bb7+9zPovv/yyJxoKANdffz1mzJiBhx56CJO1cm6dOnV829x3331o0qRJGRmNatWqITU1Ff9rVEmJbhBBBBFEEEEE8b9FUVERCgoKfH8/18oyUVxcjEWLFqF3b0lH2baN3r17Y968eeVuU1RUdFhB0cMdY/LkybjiiitgWX7iyyuvvILatWvjmGOOwfDhw3HgwIFy93G4CD5CgggiiCCCCKISwoFbKX/laWONGVO+C/DOnTsRiUSQkpLia09JSUFeXjkigQD69OmDhx9+GKtXr4bjOJg+fTreffddbN26tdz1p0yZgvz8fAwZMsTXftFFF2Hy5Mn4/PPPMXz4cLz88su45JKKCbZVOB3zxRdfYOzYsVi0aBG2bt2K9957DwMGDPB+d10XI0eOxDPPPIP8/Hwcf/zxePLJJ9FM24fn5OTg7rvvxqxZs5CXl4f09HRccskluOOOOxAdHX2Yo5aNqA5CemPSnqNJi5nSJY+gxrXnbh1SJNRwX9RB0aewuE5+jSonZsg+rgeR/tp10Mcpa3oHwCNashKnUS50WKuBwhDbYnsSTJ9FxK6dCoJNbSpQMSvCmpSFu0t0QoxeCQBY4Zgy/XQJQvaIgrxPNlQz+zEGcJDz9+kNsDZAMwX1u0RuZN0JK0GnPFpKbb+dUDafyQQ565gstcBE4UaSLjL7dPcJpG21ltSNl2YJSwm4RaRBT+uCUiNurpATQ5kqfRBfr/xz8traHCv/YWzKWSuC7o2XSksifYtyIuMMgbfLI09aaVTyTvC/rUl9PqC6iYbnSZMCSQK/ewRm6pOzSMiHhhhs1aUXIZEjzbmacQ8AVhMyuDMaPUQ+tFsSWddcf0qFGR0Q7/mGpGAAIKRVgRseky/7bE4pIq0TEtNHDDCZiO09r3SfQARfFKp0WMxx8i5AfbVsCM8A4HYW0rCdrs0uyao+sRcRttMUkTu6s6QrPFIwAEenEm3SJKozUJIAVtMs9W8mVxvFU5A+Bz3XVrUktUDrobmk2nzvNdNG9znmZPXsGLIoANjts2RdcywysLPqkbKuuVbHkYs6p5M0UZtJ0ea95dMcOiBmntVP0YR4fqf9BlFZyZ/ytLF+LlPx/4lHH30UV199NVq2bAnLstCkSRNcfvnleP7558td/7nnnkPfvn2Rnu4fC9dcc4233LZtW6SlpeHkk0/G2rVrf7UfXIWRkMLCQrRv395jx/48HnjgATz22GOYOHEi5s+fj/j4ePTp0weHDqmXzIoVK+A4Dp566in8+OOPeOSRRzBx4kT8+9//rmhXgggiiCCCCOJPFzExMUhISPD9He4jpHbt2giFQti2bZuvfdu2bYflatSpUwdTpkxBYWEhNmzYgBUrVqB69epo3LhxmXU3bNiAGTNm4Kqrrjpiv7t2VRPlNWvWHGFNif+Xd4xlWT4kxHVdpKen45ZbbsE///lPAKpcNyUlBZMmTcIFF1xQ7n7Gjh2LJ598EuvWlfXMOFwc+las0XMuecFbTuumZrExN97gtX3b73UAQKfhMrPjL3l3t1a1TJOvvJKPxRsm+WVFPJuT3M1rO/ZJIXu5G9TMM7KKvuTDUmoY7qhmH84mQSUKP1ez/Wodkry2UJaUmeZPVCStpP+QGuNOgsqqK1TCIrLYvtHPyv53qFniO7vlPDsUyeyr698UKrT/c+lT9d4yc7aqK4bzxglyTrsKVFuL9lKWG3/L+d6yUSzc9LTs8+p9cswPdcoy/wfJKa7NldlRl0vVvQv1kpLr7XeKGqYTUdsVF8lsveFINbMd+C8hOb75D5mt73g1BwBw0TaZo0y7JEn2uVvNnopyBP2odpxcs9KNamwUEB/xhm0yy3zzSXVSTDKdeerL3vJxXRRiFddTCHSGVPzVaLmOzesJklOtlvLI2bxS+mlZ8pjWTlV9rnX3eXIec2S82sfokkwiBc8bJuKArZqp49pR8nvCcHUfB14lFuxvjRH0xlmh0cC6MmvveLdc8yXvK08W42sDAGuukjLO7QfU2OmYLShWzBVSyuyuV4iTs0HGTuhEIcDdcr3KVd93spAPjRIql+AyCdUgIIkvy/uh+Jn/eMvYr3LXBXMEdaieRYhRoprBR3ZS+XVDGRsjnlFj+79Pn+i1RWYqAvL3L8kY7zBekJYN//5aH1qQtbaz/uktO0u1HUVdQVIin8ozEDpWIRRuTo7XduhreW9GNVIz/3B78b6acqe8N/rfoZCk5+/L99p6xylUuP65cu6hjtLnAy8oMuvBnfJOq3WDIEpWU1V2/N3Ad+Sc/invpb3vqv8hTdokiNX1PYRMe2C9Gts1773Ya8MmQYB//LciXbc4j4izh9QzUrxJSOS+/t2l1Jmdb4TsGn/3m6jqGN3o4iOv9Cvirg2vVGj9rl27okuXLhg/XnlkOY6Dhg0b4sYbbyyXmPrzKCkpQatWrTBo0CD897//9f02atQoPPXUU9i0aRPC4V9Onnz11Vfo0aMHvvvuO7Rr1+4X1zVRqZyQ9evXIy8vz0eQSUxMRNeuXQ9LkAHUh0pyclkIO4gggggiiCCOlvi9vGOGDRuGZ555Bi+++CKWL1+O66+/HoWFhV61zGWXXYbhw4d768+fPx/vvvsu1q1bhy+//BKnnXYaHMfBbbfd5j8fx8ELL7yAwYMHl/kAWbt2Le6++24sWrQIOTk5+OCDD3DZZZfhxBNP/NUfIEAll+gaEkxFCDJr1qzB+PHj8eCDD1ZmV4IIIoggggjiN43fSzH1/PPPx44dO3DXXXchLy8PWVlZmDp1qvf/4o0bN8ImvtWhQ4cwYsQIrFu3DtWrV8fpp5+Ol19+GUlJSb79zpgxAxs3bixX0ys6OhozZszAuHHjUFhYiAYNGuDcc8/FiBEjyqz7S1Gp6Zivv/4axx9/PLZs2YK0NIHEBw0aBMuy8MYbb/i2z83NRc+ePZGdnY1nn30Wh4uioqIy5UnOnOcQo/1jWJ3QkKCcH0gPoJUidhlbdwBwC0kdUBPPuM7cJi2MAyPvBQDEXigID5OsvHXZ9p61JoxRFpM8tdInmz6xvbchEjqbJA9gk6qms1lBlJHppJFwEeXs9DHdH0VrwWpJpDtt5w4iyDF50ZjAuUVC9jLXx6d8yuRKTeRzlgsEGvnyK285arBKkbHiKRtQ2ekqpeHupdwm98lss1Mge3NNSt95zmsL9yNIVJMXSyaNl11eT/wjo8JamC/nQceMrFOKqExUduZJ6sNqKIqwXlsamXsZU0I2N9RkOjef1GbTyYzO3JNIifxuyIOAd82dpbO9Jvu4M2T/u7T2SS3STtkoug8eyZQ1XPR9duaIQq/dTdJi3tijbYoeuMtbDg88Rx2TCbZk/ObuVikBqxGpd9Lz6Og++yzsydDMXaFSfdax2bJ/TXzlZzVCOiCGhFr69lNeW/TVI+WY2uzSd20a0QzO3DNW9aXn1V2m0d3qMja8tFyYFD/5uTbvGt5Pjhzf6F64eZJiCnU4RfqsrxMrIfvUTdtm6xOR5zKy7Isyv0dWfyvH1GPUsiSd4SPWG7O4PaJn4m4WdWckq3vO7wVWXzXq026u8ASMSioAQJtQ+pSQaewb0jhr9Vj6OkZWiqYQk8exW6X9rOaSUozNEmXdqoq7MionHTM6p2LpmKM5KjUdY0gwv4Ygs2XLFvTq1Qvdu3fH008//Yv7La9caewb039xmyCCCCKIIIL4LaOySnT/SlGp6ZjMzEykpqZi5syZyMrKAgAUFBRg/vz5uP766731cnNz0atXL3Ts2BEvvPCCDyYqL8orV3I+e1xmADTrMGHIpgBgmdlbDSoxpTJMmFlJPn2JZ2Z5i9EtlXKcKX8DAOcb+QhyDqpZpN1aSvEsnmWaYzESomdxvhlNLSHGurv1rEOrlAKAy6WpmpBq107y2mwqAXb0bNtqSIqjBVT2p8viHEqT+fwmTDluOWVxXIrn9RMQddGGQooLtZY+G1VQ32yTZz+m7I7st+0GUsZprqPdQGbT3qy/OvnZHBIioRWrEDk7We49lwh7JX5chmnLjNBDQNhrg1A+z+dmmxDt3LqEYOh9uduItKzvnUWzTZ4teygalW8zsmZ8bJzVNLNsT+WwPz83/AyhMDNbLsk018QmPDmWlF8L9PNEs027EaVdtZKqS4gP27mb7SwqhfZZv+sye5dmuzxenS1q/+ETBYE0x/KNW62Cqn7QfdkvSIFBPwDA1qWnpZMfl+37EKphfIUKBSF183LK7n8fIT7b1X1mpWJfyXqonFculbF747BAjsl+NdBKy6xYWjqNkDmNHvnkAEhawNkj5++FGVuJRNY/KM8QtF8PI2v8XnBzVFm0y+9xU3INwErS462Q/JNItdh4arn59H4rTy6AngFHX1Of1w+h265WxGa07beIv9bnQ+VEhT9C9u/f7yu/Wb9+PZYuXYrk5GQ0bNgQQ4cOxT333INmzZohMzMTd955J9LT072UTW5uLrKzs9GoUSM8+OCD2LFDIOnDlRPFxMSUKU86GHXUKs4HEUQQQQQRRBD4Hz5CFi5ciF5UQmkQisGDB2PSpEm47bbbUFhYiGuuuQb5+fno0aMHpk6d6knETp8+HWvWrMGaNWtQv359374rQk+JfENchx/Em8FOUx8yxV8LlyJaoxJunnzwRPLyZfsYdRlCjeQjqPQ72ee059TXdMMXhbfSZpL4n9j11Wy9eLyUNlkxNLM9qGfwdUVoyRNiqkWowlLisbRRPJbiDwRxierd3Vs+8OpsAMCni2R2MmDnfd5yqLVCQHLukfPIGC2iRyVfqzyxce0E/LNId41y/nS3yswpsk6hHla0IAV2CvlJ1FCzlzX3ScngdEcQhL+9p/p/6J475Zi0L1NyaTeg8sR14qFh6dLW3c+Lw2jNkarM8+Bn4p1SraZcZ2ermkHnTRbEJq2+lKF6Amqryd+DZvPFM9U4s+Pkfm6Z5S0iPlHd28SugsSE9uTL8ZN0vj9VzunQOMVfsRPk8YtqSzwS7XPjbhb0xKpBM/Q2qhbfqiPX3vmReDhLtUfPqX29tqKnJccczlBoQqgzOSTnqNn2oTlyvaM3S1o1dIbOp1OZ+JxxgiZm/0sjUiWCAh16UcroC9eqa5rYTzg0NvV//ztKeO3ADrkmtQYI4uQ912NHeW1WNYWusAsu+8AYETIuwU3qJfwLg4BE/0OeW/ahcaYrDpvVOstrM+7SAOCsywEAuPkyww9frJ4xZza5zCbQrF6jse52ubaR5YJ02Dkbyu6zKTkbr1oKACj5khyG//OI9Ek7cTub5HkoeVdKfKOvUNUSpR/JMxDuqt4BJfMXe22hDHKvbq3KgosnPOa1bZwpiFiT0VrYjHyFSucIF8yuo55Huz4JXREXzV2nxqu7TcZWyVIZh+FWGaof6eRJVUfta/u1wvWq1UdQsqKfFKoSx2KQ7fqgquP3MrA7mqPCHyHZ2dm/+LFgWRZGjx7tc9XjGDJkSBnp1yCCCCKIIII42uOvxueojAi8Y4IIIogggggiiN8ljlpihZ1JsG6bTvSD+q6KIuVF6xgFN1qN99Nq9P1lSGBE9rIbC/nxxIUTAQDx5wp87SNmaXJluK/YiCOuuizv1iTRBuSF4W1MBNb6GdKuy9aiupOHQ4YQPqsNUGS2M6JFtTJ8tpB/Damw0T+IYFZLiGchA/ESCdMjvQGwMtX5W42JXFhNpYvYm4XDSlWSv01vFki80cLVZdaLvqC//EchkUh1aSuTMO0Wki4yBMSaN1DZrvbyiO1GpLl6ktqwW6mxUXfbi9LWUUqtLX2dIqT0ySTOaOO/QlBzg0ZEFDTcJBpPVjMh0xpirUME3thLVCrPzZM2O0tSbYbAzKW+xrockFJvN1+unX2cnFMoXsH/FpFpY84SVU/Pxp1LGs11DBEpN5XSIdq/w6Vrc/zpX8q6TekZNLs8R0pLo9YqHpl9/Mlem0vjLf4aRU6MZ+ImET7NcxI+b4C07VDwPZMTYwfRfdQ+MNW/F7VYJkUbEiqnYMJZ8gxH9LlaUTLemFBpH6OO626StJkh09rd5X64e6kU28gJpOV7baFDdG+1z4z7HZXQMhFcP8NRPSW1GlkiKVuTUuWS76hs8Zwy+wr3kXtj1VZpjjA9N1yKbWtvnqgBp3ttmY3kveORaZOEDBtqSd5a5n1BZFsm6NpNO+pDir9TVDb5zDRXaTUuozd9qnOLFAPw+y0mpNLNVgcZ979FBDhIxeOo/QgJIogggggiiD9SBJyQisdR+xFipVCZJJUSmlmLFS+zF+PcaRmRJkiZIwCvZNJdS6JBtWXd2FZ6RknkQjMLAwBXox7s0OluIQQgXc0E2O3TlJuxQI9BEgAIcYuEkDislmp2ELVCPBb4OhhUw2oq6AnPjC1TjneIRJNYYEkLF7lUymzVU9fEpvJldxuR6nR5pdterkNUMRHD9IyJy24ZIbBMmeYGIYn6nYfV7Mhlh1DTfxZN4/I+jShZdch9lbZ3tMuwTWPDdx31fbDSxfvFKabybnNcdgbmMlFT1sz7NCJcREr2lQgbJIgE0vh3Z6cmgUZTiS+5DXtICY9xmuWa2TiXyBrkziJSr4eYAILOUD/CmVSia86fnVK5LLim6p+dRteRHVD1uXK5Lc+s3Z8UGTlE20OLlPkE/5oScqjHjvGAUSvL/yZMCa4hoAKCfgBASKMm7MzL99HdqlARq3Yd2b+5PvxOInKkFatRKirXjyTSc2kEvwiF8o0tPXZ4xu0sJULpaRlqPRK3c+nee9eKXGrNM2KTQ7JPUFC/A6w68v6yjyM3Yf0uZIdkNCU0UF9HZ8kMOQ9+HkzQ2GFk0YjF+Z5Rc00YvSFU1W6oSbDlyDdUZQSckIpHhTkhX3zxBfr164f09HRYloUpU6b4fnddF3fddRfS0tIQFxeH3r17Y/VqPyS/atUq9O/fH7Vr10ZCQgJ69OiBzz//HEEEEUQQQQQRxF8nKvwRUlhYiPbt22PChAnl/v7AAw/gsccew8SJEzF//nzEx8ejT58+OER5zzPPPBOlpaWYNWsWFi1ahPbt2+PMM888rL9MEEEEEUQQQfzRw62kv79SVDgd07dvX/Tt27fc31zXxbhx4zBixAj076/Ihy+99BJSUlIwZcoUXHDBBdi5cydWr16N5557znPau++++/DEE09g2bJlhxUsKxNE1GMvEUOQi2wldVANqTuUOmBY1vgMIFHgRFYndYsV9OeuEYKbqZ0HRO3RWb9U9sn16VrZ1aQT1H9odVH292DY16Q2dgqpjYlXBgItXCBkr8SziPilUy/uJjlnK4vgVq2WaROMD4bCDXGshDxwtivNEDeNlAkpXWO8ZdwV33ltpavk3sScqSF3Uq3EHrrOJnVCaYjy1CbdrXRO2mvDdz/Zb8ac00HqJ8Pb+vx9arRRpOqpx5ZbmiNte+g6ky6GnBN9TCdGyvTJ/U7rwSRTuoGgaC8NsE5gditZNBaMYmzkByEH+nw39Dmz1wanB51cNY7NuAVE7dItFPI22EtJa+FwusTZQqrEdbSGDEPqPJ42KN0Hh66tz7vG3OfdNN7jSRtFp19ZBdYtLKua6Wz4QbY3/iI7BaYPsw+MVkJlHRAmoZo0TKheyzJtAID6Oh1E4z1kCLw0xpmY6qV+OVV2kNRwzdhhFVUOoxJNY9huTX48xhOKvVc4BaVTVO4G0VGydBrGzZPUruvKdbJTVVqOPXbcpTL2rLpaUZpSQM4i8asxaTMk0tigIgBPuZcVq2kcumac8HNtzmk1pdDbdZPdfzEHABDVhYj3v0EEnJCKR6WW6K5fvx55eXno3VuY4YmJiejatSvmzVNmT7Vq1UKLFi3w0ksvobCwEKWlpXjqqadQt25ddOzY8XC7DiKIIIIIIogg/mRRqcRUk04x9sEmUlJSvN8sy8KMGTMwYMAA1KhRA7Zto27dupg6dSpqEinuiMFKo2tFHRB6xhaqTz4IeuZs1SFXzgKaxdUrW3Lq7pKZzA/vqC/wY04XJdCoplRua8pcD9AsMlYUNE35o0szZEMQ8/mokN+CN5tNI+VCcgt29awhJkW8PtyNojJoiF0RKk/0Eeg0Mc1hVCCerr9xtlxPs58CPaNcs1TWo9mN5zdBqbedZHKZrmd/TADmcKsnqX4QOZBnbKbP7hZy0W2pyg+3vSEzy3oDhPTmrFDKkutelplls35CKjb3ju83k3WdeUr50W4tRLuDn/3oLVe7KFstJJFy7AaxNXCrqWOFuvXz2iK6DNZdS1ypOCH6RbSTrLtFPHSQmi/LtRUCYErPAfg8iLzyTCazfiuKqnYzhR45u0S102qmiM4HPhFScPwoKqfdp54XdlX+9j0hVHbvrsnZTOD9dposr1ckTjuWCONEInWXqZJUd4egbHb3E7xlo/DJpaXmGWNvFXcVjRf93IUa0ruA3WuNDwyroLKniSnfJvSDUZGiV5WCcvisc+WYGgFltM6QctUx9Tskj9DbuvS+3K4RpVakZkueKB4iRuXV7k7yb2KvJ3NO30gptSEGO6Qy7SFS0XIdfOrJ+rl2VxLqUDNJts9Q70JGf6xMGgcagXbXybsIzdvKsu6/1UC2cdmBeZlWSOZ3qn5XGkVkALCKZ3vLoZb6PNcLSvVbKKa6f7lkyv8/fvPqGNd18be//Q1169bFl19+ibi4ODz77LPo168fFixYgDQ2B9NRVFSEoqIiX5tTXIKY6N/WnCiIIIIIIoggDhdBOqbiUanpGMPn2LZtm69927Zt3m+zZs3CRx99hNdffx3HH388jj32WDzxxBOIi4vDiy++WGafADBmzBgkJib6/sa+NrUyux5EEEEEEUQQQfzGUalISGZmJlJTUzFz5kxkZWUBAAoKCjB//nxcf71S8zxwQBGrfIql+r8dp/zvyOHDh3tGeSbWtD8fa+cqZc4mj4gqnoHfnnpMUgLXv6HIYqVTxFDL2S2wcuFyReIqPiAkprq3yz47vHYGAMBdKqZ5hRPe95arZWsyHKlNunuFDFeszZRizxF42dS3O1+LumjpIoE7w72UEuB3NwoBrNUpM73lg+sVcezOjZJieexi0hvQegJhch9mBU53lTaoI2VXZ46YWiFKoUxWW1LCXK+hZErBFE9+z1uO7qngdWezQKSpl5M2yxZNfEshvZSd8sHqLlNEzGJSWY25Zoj8rsl2VqzAxsVPPgQASHvwLK+tdAqpo56o+ElNnyJSLkPlBtamVJhbQCmBxhmqLV9ImvH/vs5b/vbsdwEAubbA4wNeEYNH6aeYpB1aqlIb8VdTaqFGkrfo2cCz5kaCkFiNjsgHg+RD/Kz7RUG46E01psKNZGzY2XQso29BOiD771DXsfqIa7y2g/eN85ZjhwwAALirJfXZfWIHb3n1zSptlZIpaZ+E/1wu/TdIJj0jRePEfCzcMLnM7/mjRL+j5qM3AQCcRXO8ttJFKvUSfcklcm6Nm8uy1o0Y8YyQxP+bMU9+1+RGY0QHiAoqIDoghoAKSAoGAGJufRAA8GWb272240al6P2IVs5BbVgIAHH/vFbtO0ZSCzMuEMXTk65U6ZT5Q+U6dxsnqcCiqYrUXJInaZeoVHmNR5+i02b75f0WOvVsb9n5ShnrhXpSakKno5x58n4peVfeBVEXqnSTlSJp0rW3SZ61pFQ9r63evMhry71ZDPzqPaJSkXa746Qf82d7y1Y7lXracs0L0mZLWiP14YFqYSOlL6P1e61UCLRWKxmPr1+sXCYveILIsL9BBDohFY8Kf4Ts378fa9ZIznv9+vVYunQpkpOT0bBhQwwdOhT33HMPmjVrhszMTNx5551IT0/HgAEDAADdunVDzZo1MXjwYNx1112Ii4vDM888g/Xr1+OMM84o95gxMTGIof+ZAkC09duynoMIIoggggjilyL4BKl4WO4vWeKWE7Nnz0avXmVneoMHD8akSZPgui5GjhyJp59+Gvn5+ejRoweeeOIJNG8uM5SFCxfijjvuwMKFC1FSUoI2bdrgrrvuOmzpb3lR9KN8tRdPeNBbDvfUX9tpMgMvfV3NqMIXnC87oNmu1UCRzSz6sIl8JqjJ9Y+rWfADGUJmTfgH+cQYQhd7XVA5rVVLkcnc5eKN4KxSqIDdJEO2aSgzU3eJQl1Cvc+T3wk9MqqZfB7uSiHllXyvZnF7fpBtap0oH3LhE9V1crcRsYtnkZoEWvKiWMDbiVqNNk72Ezp9gBxfz9Cdz0UZ8ZNn5JqecZealTg5RKSzhVgb6qZL7AgVKH1fECc7Was80uwndO5lAIDHznrVa/vH2zLzK31b9f+uNwSpuPeRLDn+Lk2WLSJVSyIDH3xZkStjs2U2+sYDMsu88OML1DZUnlh46x3ecnRLRVgND7rMazP+IiWvvinnVpvKkvcqtLBk6wGvLaqekG3tNIWKhAcKahGZ/Y783kUTSvcJerP/vzKDr3aSmtk7O/Oln9eq2fy4XmLXftOHl3rLztLZaiFDCNnXXSaz3YlPq2Oymm7Jk/dJ/3YoQmg4Qwi84YFXyu9z1H121gthM2rI37zlyae/DAC4aJwQQ1FXK7+Sz0rRbHkGYo5TCsRWe0LzDhJ5XD+vkcVS1ms3YiK4QpLcfaTE2VYQjq/PUX0+4Uc5z9KpCvUo/VrKq8P9ZXJV+uk0vU9B3qL/fpO37C6aDQAI9RnstUXmyDix2mgfGCJulrz1uhyrmz7X2oL8bbtF3mUpDylUYeftgjIldVbPRriPvNftFuI348xV5xn5SSaf4YEXSp902W/pG894baGzBZ2KfPo2AODAbCH9Vr9I9h9ZofYbdSWh3eQrtO+fypE9/hJBp809cXOFZF6yRkqh40aOUn16faLXFj/qNVR1XJ8xqFL282TOm0de6U8SFUZCsrOz8UvfLZZlYfTo0Rg9evRh1+nUqROmTZt22N+DCCKIIIII4miLIB1T8ThqvWOCCCKIIIII4o8UQXVMxaPC6Zg/ShycLJC3R1KC1JpHPnrXa7M76Zp7Ivq5K8gkrZomiREpDnUEztw1agoAoDr7eV0usJuBoJ1vP5UVuF7/kFZETBPyoDGDYuMxd5dA0cbQy0CZAGB3Jbv3LQra3Dp2kdeU9k/RjUB9BUWXvCpQrCGYAfAUZ9lMjg2ojLmYp+7J51QvQ9oI3ra0UV/pOwIPL5csCdp9dqPat4H2Abk2AFBHE9/YYp7CqqlSXJGZQpoLnXaOOuZrQmoLnSXpGOQqEmrJDCFMRl8xRH4350zqoKzk6SxVREarnmi0lHwq/beTFbE31IZ0Y0h5F0b7hAy7nHmf630SQZfGntVEacf4NFJIa8KQVN1VS+T3umyOqO9thmgxRKbJPTEEQ6vJMV6bq1M3pR9KiiXcV8iLnmIqKbPuuvkpbzn5xuPL7nONPGPuTrWd1Yr0IYgU7S5W19ktlPHASqDYrY8bRWX5yVqpM1EIuO460XAxz0DkMyHw+tJi2zeq7evKc2lSZeoHbbiYQiZppIQc+eojtVoNMYMLn6ZSTKWzJss2qbJ/b3syWzNKxACAujodlC+pX7ujiD8ahWJnthDarQ5C+LTTdEqVFFOdhZ/J7+1USqP0g5el7fhstbCD+pFM480YHtK7wOi+AIDdU6XifErHK2lsmjQzp8DrS+rXLcxXC/Qu8WmKmOOYNCMFk+mZOOvkqP6FTpIUf2w3SSFVVVyVcd6RV/oV8WzO20de6U8SlVqiG0QQQQQRRBBBBPFr46hNx5R8KaWrMf8c6S27+YqotP9rUdCseY0ikUZWknwnz6iqaWXEBUImi7pcZh+1/q7KSK1GQooreUuIXeGOOer3Y2RG4n3dA95snO2zjV+Ds1xm6DwDt5sp9MbdQ2RX8lZwctWsJT9fFCjrdaSZgt5X9D9ulmOSfbjxSmGPCGeNXFMzm7Y6CBmsvH4686W80Gqg0IDwAJkNHHOSzOgc7U1hH3uS7CtMVU9azbL0fZmlhS+4ocxxQ2cICuUuUzPoEJOl8zZ6i3YXNROKqkbW6kmkyGpsymuRGu0h8TyxGmaof2fIDD/6SinZLJmkEJiD78l9jH/wfumLIeuuElKy1UCVT1stO0sb+WIY1U67bbb8TuiQoxGzgqdne22J/5WyYVNa6tDMMnTSObIv7V/iEPLmrlLkzHA/UXbFelEKdZM1MkhIQPKt8oxEFihEziavo1DvgbK9Uf3kMfjDV3IsjUbaNWg2vYE8grRCsZXWWH7XiqesJIxqsr2t7+mSl4R/duxFch1NKbQzW9Afu7ucEzR65fOBofJuU4Zb8hrBfRqVDZ8kxExDVgWAUA+N0pGa7b4b5Bmtpn8umS/l+tHHiCeK+5OWCSAAOzJFUF8M0PeZ3yVZ2d6yUS+Nuugfsk+NcLpUBu5uFvVlK00T0jtJmbebJ0hP5GN1/aKuEmKpS8f3VF7Jy4h9hQx6E/mQSnRrCYHZ7nam2ude0p8yPlPtyOpjX770aZ36/4DdSd4/v0UE6ZiKR4WRkC+++AL9+vVDeno6LMvClClTfL+/++67OPXUU1GrVi1YloWlS5cedl+u66Jv377l7ieIIIIIIoggjqZwK+mfv1JU+COksLAQ7du3x4QJEw77e48ePXD//feX+zvHuHHjYFnWEdcLIogggggiiCD+fPH/IqZaloX33nvPEyLjyMnJQWZmJpYsWeKpp3IsXboUZ555JhYuXIi0tLTD7udwcXDm0/IfpQIRG8KXlUJKnTkKVvZq7AG468jAqbaGC3MFakWqmN3Nv0DBuV2GCZHOaiZmS2Z7nwV8HhlhafVSNmXyzJgIMvdZkhvrdTo3Yz4FAO4hdZ7OXCGdMXkScQpKLp0qeirhzkQKzNDEMErxWJlEKjQW9mzZ3UxvEybiKKeYYhRs664QUtrG+0WDoeGjWi+BVFJRLHoA1jHq/ri7yWDOWJcDYgS4QSzH7eMURFz00COy2qVEwN2fDwDYN0Eg+RojRP/C4nSQDpOiUSegtRHi5d7ve1JSUDWuylb7yRQSpbtcyMLIJF0Lc0xjDriKzLUSk2TZWLtzypDNuwo1lF2DFHJrkSLsAfW7XU/IspHZAtlbjXQ6iSFzvf2BMU94bXG3kOKp0dCJl2NuvVwUT9Oe1ekgegacbyhVZ8QGSQvH6OcA9Dzup1QYXVOT8mAtC0uniNiM0v2JCOedleowdko6xRgeAkKydX+UVBkaSLrHqqbO1d0rKSYm0x56QvUp9przyv5O6p6GrAoApV9pwmGR6IRYDYnUrFVcfQabqdInE87cT+Q/iNRsd1TpUytRdIoi70k6yO6uUqGln0yRzbvotCA/y0zWzdXPAGus0LqGAO18TSTRtnSddQrLWSjvEtYRcferVJ1dlxSd88nsUz9PvtSw1hFxN8t1dn4gvZcTdWqatJXiThyCqo7BGeceeaVfES/mvHPklf4k8btwQg4cOICLLroIEyZM8DxlgggiiCCCCOJoDufoLDb9XeN3+Qi5+eab0b17d/Tv3/9XrV+ei27Jhx8gJqxmAD5ClJ7dFI4W5ccaj44F8DNi6m4qxdOzr8j3UhIZdZmUw3a9T3+hJ0mJr/OTrGt30rMCKlHjL3B3vVrXatpOfk7VqpWbxCPCyZWyNLuRWpdVJ3EClbBp0t7KcULAbfW2qLga4muYypLNMQEhplpkTe4jfoXU0LB7D5A2g+RwKe88QRisLH3N6soMt+E/pVTZm9HxzK6YSnQNQrBGCJHhvlJSaSJCqIC7ZikAIPoCIlRq9AMA7NaqdLTGTYLe2LUE5TLnCSqhxX5SodVIDM8Ma/xbCHYlb6oZizVHfIVibhOhPk9FlizFXT1LNsiP6kdZR2iLiHwWoU/OHjWzP3T/Q15b7O23yoa5CilyGEU7TkiFHvpDSEjkazWzrjZciMCMEFjHKYKvGTcAkHqrqIdGPlVIi5UqfeaSSm+2myylxM6PRMo2yAC9xJ3lRBS/VI0Dl5Q03QNqPHIpspssCICdrhCGdddIuWPme0Ly9O49I0pEcrVi9fOcICRJN2+dt2x8YEreEGKqIfZ6BFQQ+gEgfLxCTbgU+ODI4d5ydL+eapu5ogIbfdXfvWWP4HyAEELyUvL6eSDfW7ZPoZJ1TQiNuliIzFYNTVTeKOXN7kZ5Bu0mypOFy7Mjn0mJsLNAjf3wxdTPz0kNuKc6Z1PCrxrl/RhqqBDY0o8nye+EAoZOHKAWyN8JmsDshogo3FbGQcnLSh3VV44fxB8yfvMS3Q8++ACzZs3CuHHjfvU25bnoPvTt6iNvGEQQQQQRRBC/UbiV9PdXit/8I2TWrFlYu3YtkpKSEA6HEQ6r2ci5556L7OzscrcZPnw49u7d6/u7pUuzctcNIogggggiiN8jHLiV8vdXit88HXP77bfjqquu8rW1bdsWjzzyCPqxRgFFeS66BQdL4MBYu5MapU5puMRVdTXZy4NfAbi7SCGzZhIAILJD0h3hEkoTGFIipwHyhUCH3Zq4ZizYDxM+gptOjfhs5Uml0NOXKBT4OVRIx9QRcai6iCF9vT2TZZk06Ok9HCqU/lHtvqeeyCkmTUq0DudgbJfzTUtqtgYKtqqTci2LoxpSXp5A/t69g6QkWFPDGFlZaURqWysaC962NQWmdx1Rk0SRuuc2ES75mGbMGJIi4NeAcfLVdXSKZZsYTu2Yfe2me2/2WaM2tcm9c3cpc0LWdQGTZfU9K94ux/QB8nvz8fOw0mhs8H5N7NP3nnRA2A7e004pJSVgVmldl6P+XUBjiMaDrdODvvHExzqkdWnI0BCUgjVpGIuvk9ba8BGJeWzodNT+AzLI3CIZ717bdkpDpuV7i+b6u3tlPCKPtFVi1PuAzeg8JVTSAWESqknDWKTJ4RwQrR5zzZw9B8u0AQBK1Nh1tlI6OUauiW1SFkTo9nQ6ADg7jEosqcAaJWRWKqbUh6fxwuOa1aUP6L76Uqu0L33NrTghs/rumQkeW5Qq9N5bXIBgopoQhbGb7lNYj42Sco4TxB8qKvwRsn//fqxZI26K69evx9KlS5GcnIyGDRti9+7d2LhxI7ZsUf8TW7lSfRSkpqb6/n4eDRs2RGZmZpn2IIIIIogggjga4q+m8VEZUeES3dmzZ6MXq1PqGDx4MCZNmoRJkybh8ssvL/P7yJEjMWrUqPI78QulvoeLorVCMj00WnxkotqqD5lQ/yu8tsLbFPEr7jLxETDlnr5+EAEt8oWUFw58Ss06nmsoX/pJd18sG+7RX+BEdnUduazG/puJfs5G9ZFmJZHCY2cpQYtMVcSv0ECx9GbUwkN1aHYQ+eQ9Wc7LBwCs+lTQm8z2gv5Uu1wRFZ0lQpi0u4iCp5mlHnpjhtdkZqnhxoJkhKl/bo5CIIrfk7LgJ76Q0tGbblKz1MiqTV5bca5c02oXZauFevIxWvomWVrra+qWyMwx+kpV/vjsQFG9vHKiWLeXTlP9v/8DmYXdMZLUUfVs390v19ZuLMTZyFJV8ukSIvX4+0ne8s2vq7JjVmHdMeRub7nmqWrGa3cWEqdB1AofEdXd2DayTxNFy/O95XBtmS+E6qpzCV8spZ/uj0KMNb5HPJ4L75bS25jW6v5ZsUT+O28IAOCRs4RkOfS5HrLPDXriQSWst1wz21t++F1dckmz9kNjhDhbmq9mtnFdZTyEzqEyTU0wdlYL1yvUVxRX3z5ded+cc6eQoq1UhcQ4PwrytfeTXG85sZe69uHBN3ltzrIv5JwOaIXer4UAG8qU/iFRo18HZYxadQVRm3GzUhU9Zaq8C9yFs9Su35My7fg7hexbNEFJCzD6Uf2p573l0u/UeLXriMSA8z31uaFOQ68VYnzkByKRtlQIq9VYyn433vi+bP6geu7X/P1zr63RqepZjzpevKeslrIceV89g06hoCPhM8+QY+pS8AN3/cdri71CFHpLp6l36dr3BOVqfpsQvZ21Cp2JuuYWr83dIarH++95FgAQPyRbfs/f7dsWAJy9cp9i/q72FflS3gvV/vY4qjrObzSgUvbzxoYplbKfoyEqjIRkZ2fjl75bhgwZgiFDhlRon0eph14QQQQRRBBBePFX43NURhy9LrpfTJL/2CXCNh7CUUCcD+3UajWlUj7yTEHOStMobfVlxrftFuVEW/dqmV1YGWypq47pc5HMkdkJ0tWshvPA0IJSzBOxakuO3eM1MBcmSbY35bamtFL1ici6Jrc8Z5b87iufVGiWu1Nmjj5BLJOTJbdP5/ulAIBQT3FXZfEq75izZOZVMEVmtokjL1IL7Ja5QmZ0Vhc18/bl/TnPfEBvx66jWnSt5FVBTKIGDpDfdW676LWPvKbYGwhBYPdc049kmg3rvrirRYCt+BOZmUafrtErymEbngoA2G0UKuNuE/E644jrfk9CcJk0nsx9JpEt5keYfLy7Re6dfaLMTE05LHOl3NUkzlddjVPfeNPiWKXvy3gKn32m9M9cE+IKHHhQBAPj/qYdSg/IvcVB4htpnordgdAVm5yDDf+CSkvdPcLViExTonyh009HmWBBu13ECzCu1SzIlyGu0Ya3EZkmCKLdQ3yNPLfiPfR+2S7X3Fmmxq7dWFALzwmaxqjVRhBGd5N+HpjnQQ7J4fbKu6Z0+ouyPZX2G96W+6MgLe5WeYfY3VSZPHvssGic3V75WzlfkMhhc/1eq0VpcnYBN/ywGEKPmfNi+pEn18bismGNzEWmC6oaOk7QSk/4jN8/O0mwUI93qx6V+Ornzff+YhFFff3tLvKuimlT1oW3smNgo18nO3GkeGvD+0de6U8SR62BXRBBBBFEEEH8kSLghFQ8go+QIIIIIogggqiECFx0Kx5H7UdIqL74Shx6Wch0UX2zAQBWw+ZeW8krynY6nCFt5VpdE3wd+UTs5P+9R5WBPfyGEOAS7yBPEGOFvVHsr5EkpEBLK4y6a4QE6ixX6Rq7KVmTkx+Du0PByqFTyLaeyoaNeqHnAwLA/V4IdqXLFfy/SxB/1O4maQIrXZEz3c1C7LKa0jnpvpTOmiP7N+TM6eIREep/gfyu0wfurnyvbc5qgfz7rVXqsM5aSU24RVIuG26uYfN6kpqIvCdpFquaLr+kEtpwRwWxPvpZHa/t1uukJLH0FUX6G/2VQN73DhII192mYV9WoGwkKYWitxVsHd1OIPc3Z0q65rLbdTqG4On9t97lLcesUOql4cuukWNqeL/4Wxkv4Q2UejHHXileQ1H1Bd4ONVDnGh4kqpfOPEk32fqasMLlgVclhRSXrVN53wiZNeoqpbj69Cei1Pm36zKkz5r4amXIGLl5iaQHJ+pnwG4lSsPFE8Z4y5Gt6ppGbRaYPXzR9dR/NaYiq8QXiFU933pDEdEH9hA1W6uOUr51llGqbJ5c0+jO+hnpJH1iTyeTsuVye/c7OX+k6vt8QNJKViuxjp8/VI3nHouEnB2Zpd5FJfPlXRFFZF6jhMoluLG33ia/6zRM+BTZZ+lU8n5pp8ab2ynbayt5ZZL8ru3s3WgZTzuflb7UGatS0jvfkue+5nEq7RU+WYjx7LETWaHeW0wCDZ8t7yWjoByZN09+P+cib9mZpcZmwTdynZOaizdO5GtF2I++lpSvSbm2cIQyQ612AZVs56t7Zwj+AODky32K+Ye6pqUfvCRtv0E65veMCRMmYOzYscjLy0P79u0xfvx4dOnSpdx1S0pKMGbMGLz44ovIzc1FixYtcP/99+O0007z1snIyMCGDRvKbHvDDTd4BraHDh3CLbfcgtdffx1FRUXo06cPnnjiCaSkpJTZ7nBRYbGyL774Av369UN6ejosy8KUKVN8J/avf/0Lbdu2RXx8PNLT03HZZZd55bomdu/ejYsvvhgJCQlISkrClVdeif2kSRBEEEEEEUQQR1u4rlspfxWNN954A8OGDcPIkSOxePFitG/fHn369MH27dvLXX/EiBF46qmnMH78ePz000+47rrrcPbZZ2PJEvmgX7BgAbZu3er9TZ+uuEUDB0rV2s0334wPP/wQb731FubMmYMtW7bgnHPOKXO8X4oKE1M//fRTfPXVV+jYsSPOOeccX2nt3r17cd555+Hqq69G+/btsWfPHtx0002IRCJYSA6Kffv2xdatW/HUU0+hpKQEl19+OTp37oxXX331MEctGwff/a+cRIa4vxpRJ2fxXK/J7qxLitl3YqP4tHiCN/tk5skOnofGPwUAiO4ubVZL8oHRJWpuoZAc3V304WXEqUhIyUpXJFJ2i2RxKoOeROYKac5qTc6Um9WM79DLMgOOG3atrBuvyjAjX9EMuTuVKOuZK4tw+UTftmsRNRaUMgJodB4+J1Y9e4l8Kb4SxZ8vlf7do2bGTg6RJAnV8Px0tpEfRAppx+jr6Pz4lfzeXJH+It9Mlbas7rSNIpY6M4ToFeo/RPqsz9llIh6NE+P5YpFfDpdvW/HqWlg1hJRstRN/EiNIxqiE5xJM4nk+B1EjpkboCpN1jSCXD/3ofpb0eYO6vnZDeS6ctYKSGR8cLis298T9aams11iQQ7ulIjTytSl5WkpwDWGUx7DxdgHgCXbZjdvL70Q6NiW6OEiIVL0MWdYzfCbTQqstWwmCcnneKpCxUfLSBK8t+saRsq43xsnJOekw5EzTz0JBYjzyeDmoqk8Uje6zJ/RHxFRn6Wz5vYUqjXVXyv1iF97IRnVMZ6GU2HI5bqix3p6eK2eFyBnYzdXM2Fkn+7frK7Iuj1Ffn7W4ID+X7gpBda2W6p5aNeXacYmthwTT/WYk2zx77k5CSHcJYmZItnZNQTjNMxD5Vkpwuc/QJbxWeyFCx2YJ0bqqon/DyjnG+xs/OvJKFF27dkXnzp3x+OOqDNlxHDRo0AB///vfcfvtt5dZPz09HXfccQf+9re/eW3nnnsu4uLiMHny5HKPMXToUHz00UdYvXo1LMvC3r17UadOHbz66qs47zzlD7RixQq0atUK8+bNw3HHHfer+l7hdEzfvn3Rt2/fcn9LTEz0vpZMPP744+jSpQs2btyIhg0bYvny5Zg6dSoWLFiATp0UQ3r8+PE4/fTT8eCDDyI9Pb28XQcRRBBBBBHEXyLKM20tTzkcAIqLi7Fo0SIMHy5GiLZto3fv3phHKbKf7z/2Z8aHcXFxmDt3brnrFxcXY/LkyRg2bBgsS+m9LFq0CCUlJejdu7e3XsuWLdGwYcMKfYRUuXfM3r17YVkWkpKSAADz5s1DUlKS9wECAL1794Zt25g/f/5h9hJEEEEEEUQQf+xwKumvPNPWMWPG/PxwAICdO3ciEomU4WGkpKQgLy+v3G369OmDhx9+GKtXr4bjOJg+fTreffddbN26tdz1p0yZgvz8fJ8GWF5eHqKjo73/t/+a45YXVUpMPXToEP71r3/hwgsvREKCIjrm5eWhbt26vvXC4TCSk5MP2/Hyvgrd9BaIidYaDusE3rcaKmjSShe7dne9gjDtDvLFxhoElvF8IQiVfVTWfaGg9hZNSG+gBelCGF8N1rSgmnfj3+KzIdfwOKtaIlYgfWeTIr0hVc6DdUhQX0HlMccLFOvulnMynjRODtXuJ5M1eyNFMHTIUtyuTRb3RrfhB/ow1PoSLpNuiUDmpXjoC3vvStGCiDXw9/582YbTPYmKcGnVkNSHs05gX9RI0tuQ94u+JoVvCbyc0F20JAw8z0S8uidRamSPTpuxbwX5Xrgrtb35MR28tkPfCGxc7RZFILSqkUbMckk9urXUi4Ht5o2uBfsGOQUC83uw8k7y0KkpKrUmTWM1biO/E5Rtp5U1d3RXiR6LSQW4O8UHxc7MAgDk3y0p0aRnSNFUpw0tGqPr3pVMbrN+OjWSLsd2F4kWBQoV58uJp1RbBulfhMu+inhsHXpOqcvGXCPqpLaG/508IbMyidTZoa5J6FhJATm7RK3XpGHcVUulH7XkRW7V1c/DYXxYiqaqWWPMzTfL9jod7P4kz43V9ng5vkkX8RhuSNdMv3cMARWQFAwgtvd879zVP8qySeuxRswa0ixqpMaM84UQztEhX/WT/JesZNKQ2a3fIXvp/ddangdbr+u9swBY6UIuN311l8kz6rDHj0692M1IO4RSK843Wl/keCFNGh8qXwqGFKvRRKV73PzyORFVFZVVojt8+HAMGzbM11YeCvK/xqOPPoqrr74aLVu2hGVZaNKkCS6//HI8//zz5a7/3HPPoW/fvlWSqagyJKSkpASDBg2C67p48skn/1/7Ku+rcOwLb1dST4MIIoggggjijxMxMTFISEjw/R3uI6R27doIhULYtm2br33btm3l+rQBQJ06dTBlyhQUFhZiw4YNWLFiBapXr47GZFlhYsOGDZgxY0YZ49nU1FQUFxcjPz//Vx+3vKgSJMR8gGzYsAGzZs3yUBBAdfznjN3S0lLs3r37sB0v76vQXfA2UKiIb6VzqdTwYk2yWkVf/5qk5SQt9Zp4ZmpIZExKc4n8uMRVs7/mRTIjcleSU6txbySymVWfZqN6ts+ETmeenom0FAVHdzmpIBaoclq7m5SVMYnVKzWMIZVAUjeNLNAsZyaoLSePiQSNNuwQ+M3ZKOqm1jGaXBklhMiSz9TML9yZCLqJUhrrHjBOrDLLq1ZLlp1v9TlHE8mygKqitNqtVV8Ikb77GFEqt1Y9+Rp3Nbry1gpBca6I0CxTz47e2y5ltdfSzNagEe5GItK1zZI+56p7a0eRP0mOvAzijapmjvxe/LkgTuFMjYQ0YtRCzSxLZ33ttdnphC7pe1qyQmbt4UZyna10PU6LCR0kp1ari5oxOquk3NShEuCQfh65HNaqo8iqa1ZI2W3HAkJi8nLUv8m1dKYjpOam36lzdhmtK8j3Fou/VIhWVGtR93TZlVWrXbr8QqPZ/k+zFRJ07I30DK3VY5yIoQ7dR9u4MucSSZxQPIN+lXwpz11UT1I3NQuR8lGykjzVHlMoBFxn4Zd6Y5kRu3NFhdaUgrMLbugQEXT1MpfgOkskT29QhfCxggoUvigTsphaepzQfSpZLM+13UUdl31g8L1GihMIbYsmVFWr/bqrpfzZaiXXwVmvnlGXUCh+FxkUrOgLeZaj9xBpWT/XfJ2tOoLEOOu1q3TsbOnTboUcuvsIpUqjZ8T0icdTtviJVVX8HrLt0dHR6NixI2bOnOkViTiOg5kzZ+LGG2/8xW1jY2NRr149lJSU4J133sGgQYPKrPPCCy+gbt26OOOMM3ztHTt2RFRUFGbOnIlzzz0XgDKs3bhxI7p161ZmP4eLSv8IMR8gq1evxueff45atWr5fu/WrRvy8/OxaNEidOyoau5nzZoFx3HQtWvX8nZZLiHnEP+PLIgggggiiCB+5/i9XFCGDRuGwYMHo1OnTujSpQvGjRuHwsJCz0z2sssuQ7169Txeyfz585Gbm4usrCzk5uZi1KhRcBwHt912m2+/juPghRdewODBgxH+Wco0MTERV155JYYNG4bk5GQkJCTg73//O7p16/arSanA//ARsn//fqxZs8b77/Xr12Pp0qVITk5GWloazjvvPCxevBgfffQRIpGIx/NITk5GdHQ0WrVqhdNOOw1XX301Jk6ciJKSEtx444244IILgsqYIIIIIoggjtr4vRRTzz//fOzYsQN33XUX8vLykJWVhalTp3pk1Y0bN8Jmh+tDhzBixAisW7cO1atXx+mnn46XX365DMl0xowZ2LhxI664onwU6ZFHHoFt2zj33HN9YmUViQrrhMyePRu9evUq0z548GCMGjUKmZmZ5WwFfP7558jOzgagxMpuvPFGfPjhh94JPPbYY6hevXq525YX+4ef6y07uwXSD2UoqDqyTtIMdg0F8ztkx+4eKKsBEG5JECDBpfd9lAQA6EII5qmvidGVsd0+8J97pa0amXOF1c23awtUbTdUH1xshOfmyMed1Ujl5kreF/0Lhor3v6gg2lnLhLzX5yQ5Z6PwOfMR6fTJtxCUvV1pmoTaigIma6O46xTZLbJCoNxDi9U1CSfJYI5qR8TZaPVNO/tBgUjfipPUyBOTFJy39y5RMXQdsfeucZxKE4Q6CGHRWUF6Ljo1tOpZud8txyvS34ZbZ3ttDW8WFdnIyhwAwLevCVG4210E22q9F3cJKWXGy3UqnquuQ+luMTz8drGkdtrUU9ek1imkdktQd6iBeglY9FwUPDkTAFByQMZI0vEy9kNtVDrK2UTmXJR2sztrqDOHFHopSpepexbuK+ZdO0eI3kyCvuVRpHvj7lbw+LbXJeVXmyYzUWcqUrenMAvg8XsltXLj7Sq9ZyUkeW27H5eU5tZN6vq0vFjGjnkGAGDf2z+of28TUnPaeUJQNufPpOBwkhpv0SeJium2R0Vsqc5AdZ+KvpVt4q4QSLl0mtLaiBnxoNcWWSISA85SRaS0W8t14nRM8VtK5dWuKWMrfI56L0WmvCvn2ZzeiTpV6Wyh/D2pBlvV1b6cAklthM8kc0JNQjXjEgDiH31WzuknrYxLpp75D03zlpPuVsTewgdEEbraKWq8FS8itdpj5Lm2MzIAAPufn+21rftREO52D6nUtrtTxkPJYhmbdpx6bu2aMsbtDkIWNpoebpGQ1Eu+EZJrqH6S2qaRvOtM4cHKv4sScOZJ8t4p3amuadzJ8n6rNvQpVHX0aVC+fEVFY9qmTytlP0dDVBgJyc7O/kXI6dd80yQnJ1dImCyIIIIIIogg/ugRGNhVPI5e75jOMvsJJQqZzqqlEYbZoqRnd5fSXBPueipZNCRNKhcNnSilejevVTONuG5UjkqW5qZMNPZvl0kb2dUb4pyVRDNwraTpKwetS6hCkprFRZ0gswtWTK1+teLIZD8xy2uLGSykIlPOe5Ij9tn2KSKna+nSXIPiAPBUCAEAukw2VFdmq/E9NNhoSmUB3zUz1z47Voh4XT6SGZudrmZcif8kVUEm89bSCAMRDUPkAQRdztwy40vZvIW6Jg3Ol7LY0PFkQd9KoQldSoW8FzqBoMV4Ta6k6+AplgKIiVXXJCa9odfWk8obrSStPlpbxiDIo8jcByY9J1ypETkmSZJvkLGQtzOEGMpqlGafXNbLqsHhTDX7Y8XU2rdSCXCq7nOilMq7uxV5MyUiSpz28T1l2ZTTNpHS9auy7pHjJyn0yWoupZvJI+T8kvfocUzlqEzUTqimEIAau+ic2ggiZnxeqnVlNVz1+jJKuwCQEi+zbatpFgAgatvTsknbbPldP2/OViJkp2bIuqepZSueEBkiT0afov1P6Bm20/S9H0DPGpN1zXr0/nB+lLFrNVCoifGAAUQFFZASXI+ACkI/AIRbq9JeZ7eQcZNuoeNqpdL4y7LlmBoBjWkj6AQTzs3YrX6TEJHbrhKkAmnq2Qm1kXtjNRUE0zzXHnEd/veO8cSyiOAbXV+eNyN3YDeiMndNOm5xJ5GOa8l4jtqiCLx2ZxnDv0X8HsTUoz2qXKwsiCCCCCKIIIIIorw4apGQIIIIIogggvgjxe9VHXM0R4U/Qr744guMHTsWixYtwtatW30GdiUlJRgxYgQ++eQTrFu3DomJiejduzfuu+++MpUvH3/8MUaPHo3vv/8esbGx6Nmzp8+R94iRTPA0mXtZtlq26hDUfEiRvOxapKKaQqkPo2haIPbSDH8byrNVlyD3GCGjeUqhSXRMTjPo/fvMsUzKgU3KEkl21ygCsjopmc1BK8NWP0H0KXywr1bwtKqRMiGpB3pwKNfmh0lzxBivbcuRNnOe1UlPoJTMv7RpnpUi52lXk3QMHK3zUUuInT7lWm1E5inQHi44jWF0UBzSZXCFRGrFUIrJBOtTmPPn+xVN6qepKgXH8DRCRDpuoonFNUkFmNJJJlWHUklbeSkJgtx9yo9GEZXTY3Sd3X16me4X33srrMcb75NSBt5+6d6bZ8OxhSjMiqVmXy6bLIZp3frqOrCiqhtD3hQ6rcUpID4/V6ewrFTSfSCzOmedIjranJ7T58zqxr60lt5/uL2QE333WY/xwyl9WtWS1ALrzlC42vnbaiYaMN66bOxIz7V7IF8tsAorGdCZa+5GS5qBzei8sUs6IExCNWkYm5RdHdY5MefPGjPGYLOOpEB87xIzdlkFuoWcs1Uj2X9ugO8+GPVlrJV3FVid2bwDeQwn0ztivzYGteW5A/RyQ7lfvmuaptPy8fSu+g0iSMdUPCqcjiksLET79u0xYcKEMr8dOHAAixcvxp133onFixfj3XffxcqVK3HWWWf51nvnnXdw6aWX4vLLL8d3332Hr776ChdddNH/fhZBBBFEEEEEEcRRFxUu0fVtbFk+JKS8WLBgAbp06YINGzagYcOGKC0tRUZGBv7zn//gyiuvPOx2R4rtJwvhKOGhW71ld4+aFSy5SEqcOs64AQDgrBRlVWep+M24umyucJ4gIYlj/y4HM8qL+/Z4TYUPvOItx2VnAADsLuIRgfWiDuhs1LOTLl28NjtTkcCcJUIsBSknmi/8nXe84zXVPEmQEFMOO+U5meGe+xaVhxnr+XLsyAF4Vts+xdOVUt7oEU4zy84i2Zuk9BX5GLWPI9KgtwIhAHqf9jEnyDEL5Zq621Wfit/8wGuLve0O2V7PmDy/FwCR6cryOnQqWdl/TWTcnmf4tgUAl/xyDIGYZ93uXiEDG+VHK0WIdIxo7Rj8HwBA/g6ZJTb7hMajVuN1pr5Fbeo6hM8VgixbxHt9jRKBPm9WDsDRvkMLLxdCYqfnxLLcXa5nnFRqHDr5fDo/jT4Rgljy0jPqkBeIX0xk5sfesn2c3j/Nuq0mQhzde8s4AEC1loJ+RA8bIeek0UhDQgSAyFQpY7XqKHTLIlHC0vniGxQ+92zdeUIFtinSsdWYFHwZ7dQz8/dOf81rG/C0ENqtmgqhKJ70otcWlU2CifUyyxzT+UZI0aFTVZ/yrpRnIOWf6hm3s7LlPD+WSkD7lLP1eQqilHOulAg3GKqQnp3PCmpQ5z/95Jy0DwyroB5YK/1LukWXZdNzH86WCV7px4qka7UlEqnui5PzgxxnOSGsndS6NvnJFD87Xo7/g0KiEh8UD53SV8SDJOrKm9Q+WYF3E5GBMxWqUvSE2HvYMYLiRQ1W/kzsveUR/+m5ZpRr09+nAAAaPC4E4biTr0FVR3b9skUQ/0vM3jzjyCv9SeI3d9FdvHgxcnNzYds2OnTogLS0NPTt2xfLli375R0FEUQQQQQRxB84HNetlL+/UlTpR0h5Lrrr1q0DAIwaNQojRozARx99hJo1ayI7Oxu7d+/+pd0FEUQQQQQRRBB/oqiydExJSQnOPfdcbN68GbNnz/Y+Ql599VVcfPHFeOqpp3DNNQoeKyoqQv369XHPPffg2muvLbOvoqIiFBUV+drcJVMQo/1j3O1i9GV0I5xvRWnUwKpWgt/HxtuXJj75yKhUs779JgUt1r5AlA/tXqJFYddUJCi23GZrdw8aZWKpMc2rIWRXdz99hGlSnUv1/pwGcdYrqNqZS/Bwv/NkX8XaCGu+QPZWZ4HsDYnWkBj5mGpnmoi4XazX3RU6XdNAnBbtekKqg95X5DOBnw9+IhBv9QfuUn0m2JeNrgws67smO8SQzCOc5klbqMvp6jgj/+W1xY64W7bR1u2F94qUcI1Hx8rxNYTr0HlaNYkQ+cNstRAtaYbSqQKVhk/VyrmcJmAzOU0gtuvK2Ims/EYtbCeNA0p7GeKvu0lSekzUMwRCMwYAwG5ARoj63tuUNorMl9QKUlXKwoqn9F6sej6LJ47z2qKGSLrI9N8lXZhtF97pLde5b6Baj8cow/s6jWC1p5RkilwTjxxKhopWE9E5cb5Uqp/2CaIC69ne15Nr5ywSxVOzvbNAdF3CZ8o5OSatR8RWn4llOc8oKCXgfKW1iEgXxhC+nR2i0uojGOvx5pEtgZ9p7WhNjUOimGq0PQB47w13n6QUy12XUhPO3CnecvgM9c4t/eQZ2WdGizL99JHPdbtJAwIAdhGh3Cgts+bRDlL7NSTV7WJIaJ4LAPJ+pGfMd3004dRHGtapRGe+qMGiCV2nXPU8W82zvKbYzqKyXVVxQr2Tj7zSr4gvc2dWyn6OhqgSJIRddKdPn+5z0U1LUw9Za5JCjomJQePGjbGRHDA5xowZg8TERN/f2Jfer4quBxFEEEEEEcT/FA7cSvn7K0WlIyE/d9GtU6eOb5uCggLUrVsXEyZM8IipJSUlqF+/Pu6++24PHeEoDwnZc/qZiNFf+0mP/dNrdzerUr4VN8jsp/VnwwAAkS+myHo7qBxXkzwPzBLvhPhbLpSDmdk6lZ0deETIbrHd1MzSPj5bttlBJXZb1bLVgErgGqmPMGcOzVDjZCZgtVEEuoMPveC1xRyX4S0bb5w5Hwq6c8rHQj6EVif0qWKSEqghgfLsA2tFRdbVluP2CadL2y59TjTjcWbJTMTupL1tuESV7cF3K1Kj1YBmQVR2ZwijJZPf8NpibhZXR68EkEh3kU/Vx6jdkVQl18t9tHv1V22byYaclGtdjXgZkiLws5JPjbpY9USVk89/778eBwBsXSeoQqupQtAzM1ZnviiRIqzO2T5GUAEQSmf6ajcmfw2aLTsa3fn+YlGmbfeqIHPOV7PVApXbhk6XsWFmke5eIQqWvDJZde0CWa/0bVGZDffRhLsiKYPke3twvHoewrXl2kRfK8+yUcvkcvrIXEGULOONE5HyauNvBACh7powWovQSk3+tloJ2ZRRKHNNnz1TkLkrXxA00ETpR/IMhvucIj+Y532PXCfnByG0h3oqVGbHsEleW3J/rXR80T+8tuJn7veWoy6+Ti0QMXXVqWO85SbXKdRl51syIatz79lyfK3W65A/UdFKQRM9JVQqwWUSqrtsnjrP06+WfW5TqIGTKyqn7nI5T6tNlvo3IWclLwqZd9/36ljJ42/y2iIfyjMcOlm/Q8iF1d1KyKNW+y1+8nHZpp48D+FL1X6d9UshG+n581ZBnLjMfc94hQDXvE4MkOIuk+tcVdGtXllftf8l5uV+fuSV/iTxm7voJiQk4LrrrsPIkSPRoEEDNGrUCGPHKnh84MCB5R4zJiYGMcSaB4ADdpVzaoMIIogggggiiCqMCn+ELFy40OeiO2yYQhmMi+4HH6jyyqysLN927KI7duxYhMNhXHrppTh48CC6du2KWbNmoWbNmggiiCCCCCKIozECxdSKx+/iohsVFYUHH3wQDz744BHXPVxUP56VRJPkB633kNFViKWWVhk09s8APEtt9btKScS2y5c2Iqm6eZr4SjXpcSeTSVkrZazEKoMuKRpadTXUT6qadm2VmnHbEZRM+7dTFQkrqpHs024iKQErQbVnzCA4ksIQRpksy0RA1NUmZqxwyUqiuzRBkJUfjQorqxDWJ8KkIdXlSZ/cVUJOtLto0hbX9rNiq04dhdsK8dWqQWRiY9zG53SM5haxiWFD2qelUh8uK4YS0dAyypJMyqN0jGNUGAl5Y2XduKYKoctsKORA3740ydViQ64Del0mhhJB2MpoW3Y/RBS0dV9anCDpCp8RYQNNrG1A44UJyEb5lsiyoSxN7mTzwFbyu5Wm7wmph7qbBL6P6aKObyUT+ZqVjI3mSXWZaNjNhMQKk24lgq9dgxQ0ScfFO75Rs2UicxGRH/V7oXccmeKRKig0gTfcVVJ5vuN4Sscyxn2pRq0Im9SZDOx0StalcR3q0ln2b8Yz/d7oVCKmNlfPbc3jhPhp1xfSMTrkq39/L89AtVNIPdqQRCk1wZokriahmhQMIO8FJsEjk0igpJzrbZMuz2Viujk3eq7SqU/6XWqIvgB8houGQB0+ltK0/I4witd8HXQ4RGzndHmNLHVvmNz8W8Rfjc9RGRHkNIIIIogggggiiN8ljloDu1C3bt6ymy9lfWb2EnOiVN+Y8j/bzDABuDzj0TPOUDJ9yUfJLLT482/Vri8hcl8izfi0B4jVtJP8TuqCZvbIMwHPPjxfSu2sxqJA6eQq0l2476nyO5EnrQZqFtlkKM36yXI8sk6X05G/CBPPQrqvbGPOpX6GvOkrGzaoAHs8tJP7YKeombfDHjS7SCUxV3GJfPehWBQ0vTLQhjKrd7YJydTMjti63dEz08hHUi0V7k+lypqMG5kupZuh6+U+eedP58SlrR5xl8qr3W+F9Bx1vlZk3LRO9kkEOk+RllGw5mXLOJFESIvx62FvGPZZ0UhMVJbM6n2zzGPUPWHiqSGzAmI3z+XXdpYiL5a+JSTO8AC5jgahYB+U0jde8pZDx+txQP4i3H84+3z7AQCrmSAQUnpK6A6VuRdPmqR2/28hF7oHFNrJY5R9g6CJzPXPJUTJIv8RfS4l86X0NFxP0B87ySB7NAaJyO3MU2WU4T5ERtSEdDeBynpphu5s1F5KhMxFHU/XQRNvwyefKOdE5bhWmuqfTaTgoheFQBzTRpGZGfHhUmmDVvpIqBoBCbUSxWdGSozSKSOgoTOEv+cu+0afGyGUrYgoru+Du3yRnGd9QTsdjTxazeW9wHIKjr7+Vi3yHzPb1BPExt0qz6C5Jz6S+W8QboCEVDiO2o+QIIIIIogggvgjRcAJqXgctR8hPJtm0SYzU2BRJHen9pjg3CblTM3M12GBn90itrNqmsqptu5ExyHnTMMFYRdJX45f5/55Zur5k9RIkvU4t63XZREqi/LpTr4pd6UZD81sjeiTmyvnYWVkyP71DMGHfvDszcxidUkfAKBavN6nVEdxGamryzdZPO7QpzLLjL1RlyWb2SDgy427emZq7iHwM9EjXeLHzrt2hkKP8r+RkunkK+U+m2Pt+Gy/15Z+BfE3zDigGZPL4lK6bNltLDP4g5+J62p8tvasobHlLhGBOMMNsDOzZJ/aTRjb5Dq57LGzV8/sqczSjSfxOz0bD2WfJm2MMOhxxBwlZ8Fnsqop0aXrGGqbDQAo+Crfa6t1hcw8zXi0CAlY/44cs9l5+rkjboqzTK4D9mmOVh3hV4RaSPlkxKBH2+V+213P8JYPrVElqTHs62POj9xTsZrsH5qrsRnq2EHa6Ll3Dyo+QSiDZtjE+TAIhM+VOTXDWy55V5X2xvSRcn5nsxobvpLwRoLKuhu1AF0xCdq1JNRAl4zbLcXDhpEeD2GNlnsXdQw5gmvkzXfvyQfGPk29t3wl45r/UR5PBAAiGinxuQ3XJ05clkJt3A1S4m81JKG5HFXu6+4SLpXdQu6Jq/lnoVbkPUXv4shPC9RCOdwUNy9HlrfI8xTqrsqCnQ0//nyTIP5gUWFOyBdffIF+/fohPT0dlmVhypQpvt9HjRqFli1bIj4+HjVr1kTv3r0xf74Yx+Xk5ODKK69EZmYm4uLi0KRJE4wcORLFxcUIIogggggiiKM1ArGyikeFP0IKCwvRvn17TJgwodzfmzdvjscffxw//PAD5s6di4yMDJx66qnYsUPNYFasWAHHcfDUU0/hxx9/xCOPPIKJEyfi3//+9//vTIIIIoggggjidwzXdSvl768UVeYdY6KgoACJiYmYMWMGTj65fF39sWPH4sknn/TM7X5NHHjy796y3UFUEA258dD94msR8w+lusnpEncLkc0MRHtAIHurhZAXS19/Tq3Wjsq9WJHQKDayWiOrA+ZqYlWmbO8RXwkeNlAuIPB95NPJ0tbpBNmnJnntmCgporrP3SL71wQ8n79IJqdOtIU9EQ3LSycxcdQQ2Dgt5PPt0akZZ9UCOadlAoeGztKwNe3Tb8Wty2kJYvXBvsYvYqcc06qhyHLO15JusI+TcWbFKVJg6RRReAyff4P8rtMLLsP8FM7S2Wq9TILUN0s6yt2m0mLuQbn3oZNFvdR4sjCk764w8DKVN7OvkUkHkX8Ge5oY8nXpmxPlmL3J7t1TgaUyc/LgKa/k0t2jz2OdEBaZKGj8WZgkWfI8Hb+VIhpaLYVc7Tv+OgXJs/IspwKN1wcrpiKayopDamyw54i5Z6FmknplwqUpv95/22ivrfo4IrYWqjSHpx4MP+nZLVXPOJdHmxQOQNc0h1IvnZSXEBPbmRhq0sjm2AAQef9N+b29/n2XjMdQttjRm7SYu41IzQfkOtodtJcRpff4ebHT1fPEJFJvPDCJs5RKjDVhNbKGnutvZsn2Wt/J7n6W/L6YPHya6dQLkad9pGv9jPJ7wycNYNKzTIjX7yefD1WSpJOdaSpVxn5asceRonQVRYfU44+80q+IJXlfVcp+joaoUk5IcXExnn76aSQmJqJ9+/aHXW/v3r1ITk4+7O9BBBFEEEEE8UePv1oqpTKiSj5CPvroI1xwwQU4cOAA0tLSMH36dNSuXbvcddesWYPx48dXWLjM3UFkLSJ0eiWXTjmDgZ1OyYvDLDurZEYTbiNftKEmimxnt5OyuZLnHvWW7T1qxmp8SgAAB0QszRAJ3X1U7qpn8O6ir6UtlQiVukTX3SfoDPstIEltX6ORzBxtvg56xsroh0OlzLYmuDmbhEzGpEDXzDxp5uqR3phAS4iSmSX6hIjiRLTNXaVIqqFOQqh0+TqZfv5EvhWEhHjusOyaunCaXo/KVdfRLK+DQkXslrKNDxHbpWd/LNTGglTpmmgZQx47tQQ9gvYFKl0l1y7Um9AdXYrpLpaZo9mnXYvE89hBdJcW3GJrAiLwOmuVm/H+mTLDTewtq5r76JKQk92MRPEMMZXLr7dp8jb5zWCniFeZK2LRdQqfKMRSZ60eBz8tlWOefpnsq2kWygSTjrWzLyODPi+jAl2SSQilQYqcAiF8oxyn7IM7pSw3fg8RtfX1L57wmNcWNUC8kqw6+hkh1MBdSWMrRSE9kZ8EGQvp+211Ig+ag/QMGySJriP7wNh6nDlrCblqRc/9Xk2WXS3vqsJpUmZf/SZdSk6l0uzgbJxw2T/JOw6V4DIJ1SAgoaYiuuZuFMTJ+U6jEY3E9dn3ftWIEosYgsQcUVsjoDsF/bGSSD3bPBsslGcclJkYTyhduf34DSIo0a14VMlHSK9evbB06VLs3LkTzzzzDAYNGoT58+ejbt26vvVyc3Nx2mmnYeDAgbj66qsPs7fyDexKSyOICYcOs0UQQQQRRBBB/Lbh/MX4HJURVaKYGh8fj6ZNm+K4447Dc889h3A4jOeee863zpYtW9CrVy90794dTz/99C/ub8yYMUhMTPT9PfhlUHoVRBBBBBFEEEdzVDkxFQCaNGmCSy+9FKNGjQKgEJBevXqhY8eOmDx5MkKhX0Y0ykNCnG/fQEy0hpV/FCU+y6ieEqnNXaOgy1AfISaxDoiXmmBiFCkazrlGQZg9/yvpksgasqKO07oNfYVA5tMBMDokRDx1V2n9ib0Emfc4Sfo3WxG7QqcIydGnLpqmFFOZcGj0UADAWaivSXWBZd1d+d5y+NwL1HrziGCWQFoUtRRq5SwWnQ8rVbUZGFqtRx4RGmJ2S+ReFT/3shyziVrXbiuER08/AoDVPEttv3KJ9LmAvCGi1P22mpKHhE45LLlOysA7PCsEXuSp1Mb8fwsU3PV5SbW5K9XHrMUoHaVb3GVL1e/HZHltu0ZN8ZbrPPMvAH6Nlsh0IslmaO+YFCGh2seotF5kptidM0HXg+IpNWLVkPvobFF6C6G25O9RS+B1S6c+DBkUANyNG+h3Re50l8uHvH2SGmeL+oneSsdpV8j2C/U4aSxprSUXfeotdxir2+uSUvAu0bLgdJL0Q0isnrLlHkmtWPXFW+bD/lMAAP3eHyC/a9Jv5MsPZadEqPQ8m4hEjhqiXmoIj2sufsVry7wiyVu2j1OEd3fpQtmmpvy+9l6Vfmj6ysVeW2SaMvA07wQAsNqJJoazQI9TeufZXUkfQ5PjjbIpADg/fCv7aq33pVWaAeD7q0WPpe0/VTrKaiE6RqXTZnjL4S4qfVE6V96ZxgeGVVB9SsufKzViK13ubfikS2T/sybrfkqqKnSWvGvdVUsBAPsnST/jz6RnWMsz2MeJ8iyTp0ueG6f2eQI9t5s36vMkPZLPZ8rx+w9SbYvkmNWuH4+qjjYpXY+80q+IH7fNP/JKf5KocDpm//79WLNGcqDr16/H0qVLkZycjFq1auHee+/FWWedhbS0NOzcuRMTJkxAbm4uBg5UAzw3NxfZ2dlo1KgRHnzwQa90FwBSU1PLHA8AYmJiEBMT42s7GB1V7rpBBBFEEEEE8XtEkI6peFT4I2ThwoXo1Uu+WIcNGwYAGDx4MCZOnIgVK1bgxRdfxM6dO1GrVi107twZX375Jdq0UV/m06dPx5o1a7BmzRrUr+8vFawIKMNlcw6TVDUCYnUSElXka/VVaZF/hlcSCMAxhNW6pHpJ6Mp7cYr82f4Faas5RmaJHvlwpaAGPLN1U3Vp2paNtI36iGLCJCuW2i2EkOm1pcnM0ENVNsgHoZNHBL0odWvXPyMqhZkXEyqSo0lk1cnttz3NNHT5Y2SLlImGYvR57smXtpOppFH7fpS8NcVre+ZzmdH9bYCatUS+FDKuSwTicKIio1mNZRbnzPxE+peg+lr6tuw/euhwAECxQygWe3XkKjJuDinYdmWUqom+poTIgAidkfVazZHu55eb5JwG6BJBu6WQNEv3Sv8MQdpKJ7+bVWpmG1kuYzBUj5CMZF3Wu5tQILpOoXZqbIROkpmr8+Ncb9mUUtutxNfnwGsyG/auRALde10muQPk90JuwaitUTBSk51BZNqOmrTN5duH3hohfSpWz1BUJymxtcn92pR8OrkyhsMXSFn0MdU1CZVmtlaGundWjPT50GyZjcecrM7UbkvqyYTSmWegyWiq3OOSca06bNUlEmeG9L+kVBFCmaht91RE6MjHgs5EsbqzQUIOEKpZT/bprDYIplxHq6X0z0Nt1wsJtN1DhCymaTfjGvJ+PPCDlN4mnq+u6b4n5Bk0LrjGAwYQFVRASnA9AiqAUoh0gEFFileILIKPSJ2jULiouoL+WG2yvGV3jfb2akjPPaPG+/U9o/FmZWiV1y9mS582y/8HQnqcWvFEgA3iDxkV/gjJzs7+xY+Fd9999xe3HzJkCIYMGVLRwwYRRBBBBBHEHzqC6piKx1HrHRNEEEEEEUQQf6QI0jEVj/8XMfX3jMI7BIoOnSmEUCtBwcY7r7rXa6vzyn0AgMhqIXi5y8ne2sCNm0UXIZTdR9ZdpVRHXSLHurvIcvz4bL1AUG4+1awbO/uGQiQ0EKyrjeiAn6mPajOn4kfv8drC2UJgc7Uuw7yHxbzr+HdFsdDoELAaZKi1KMtGNijSYqiRkAOdnZQuOqAh3HiysNe6EqwV4SwVWNdup1IS7gaBit080SYJ9Vb3jNUiwWZxmpzI+2S1SLOuY8zOANEB2E2Kp2THbiWp8cCmctax2bJsrN1JjZH1Bpz5iiBsdxXdB3eLpMBKPlQ6Jc5+0TCIu3NkmX2xpbj7gyI62seTAR2lCYxyLIcZ1wA8vYSiR/7rNUVfTiTSzVo3ghQkLbqPhnRoxQhU7SzQCpd1iJdVKH2223T3nQ8AOPPEBC2yTpGiw8dlyTGPkXSQUWTlseNTnt2kxr57iFJllAbxUi98n7QCp11fSI6exgqEEL70FLGYaP/REFnX6KTskmfQd810SsSitJFJdQHw0rCRj9/xmkJnnOs7NgA4X0lqxs7WCp5EMj9w13+85ZhTFPHUWS/PYviCK+X4euy5OaINglLRCgr1VFpFrIVjFHZVZ/U4DQmnzqSTWA+F1aPNu8hoFwGAM3Mq7V/tK/qGu6VL7z8h2x/fr8wxXdIs8p7rLz6SNnqX2seqNDHrmLiOOg/3O0lDGjI9ABS/o9K40RcM8Nri+tyIqo7mdTodeaVfEat2LDzySn+SCJCQIIIIIogggqiECNIxFY+jFgk5OEN8K3ylgCbIl8OQUK12RLz8UUqgQt3Ul3qErccPis/BtJuUOuApN1DJZB35Kre0eqnVQlQpWY3SI5N9R/s365FKYKjX2d6y8cBgoh9qkGfLLj0jI98KJCbJ7xopcQtoRtNUEAI0UF4fyM2RtkZEhtWlks4P5HvRXZe+biKPnwzydjF+M7tlllPwiBBLE67tqRa4ZDJB+mw1VqiM+wP5JnBpdnU9C46iWZwmfOZe9bzXlj6eSg319VkxUhQeWz7fV37frVGqOmTnTqS60imq5DI8QFCmrTcL7yntMVUK6LOI/0lKjK04TZBrJWPDzOicJaSiSiXlkUVLAQB2fSp/rkak4v26jLMleRkRodKgHj4S5gKZMVrHahLtRkEirHZqtrv6PNHzafbqRbK98T9qLMjZgtNf8pY7vXKq+j1JZqPOAkFKLFMaS55Kdish85oyW2ejIA1RF1/rLa89W6maZr4g99ZO1eTEJVKa6awRBV+7fZbq+yqyoO9E3h6aoFz60cdeU6hlY1lXl4Ib4iQAWJlCDs+9WfW5/uS/eW3uDxrFY++TNqQ0+v08fXJEAK5LY8+QYVvJjJp9jaw6ShnYXS0k+OKPZ3vL0YP0OCVydmSKjNfQyUoGwCPIArDSdel8q2OlLYVUVs31JfVRq4Wsa54X90chh4f7iz9T6VQ1ppxVcm9Cp8u7zl2v5ArsjqQyS89T5H21vd1NJAxcQ5reK+/Z4o/neMuxdyh0KfLBJK+t2j+fRVVHk9rHHnmlXxFrdy4+8kp/kqiwWNkXX3yBfv36IT09HZZlYcqUKb7fR40ahZYtWyI+Ph41a9ZE7969MX++v+Z51apV6N+/P2rXro2EhAT06NEDn3/+OYIIIogggggiiL9OVPgjpLCwEO3bt8eECRPK/b158+Z4/PHH8cMPP2Du3LnIyMjAqaee6tMDOfPMM1FaWopZs2Zh0aJFaN++Pc4880zk5eWVu88ggggiiCCC+KOHW0n//JWiyhVTCwoKkJiYiBkzZuDkk0/Gzp07UadOHXzxxRc44QQF7+/btw8JCQmYPn06evfufdh9cRx48Cpv2T5JoHJDXCu8fZTXFv/fuwD8zLhsPcm+a2iUUw/hC673lp1vNFybJOZYzgIhudpdFaxssx7Auu9k/xr2tckUDyZ1QYZaxoIdEEi9PJtvAJ6h2o67p3lNdZ+4Tn7XZC+3QIiErENiIFQmPLo7yWDKwKEEK5v+hZoKVByZ+570r61WmCTiqSH1ApKSsGqK8qKPoKYJdEw2s7uJYqwVo1ISrE7qkTB3ExG4AUHqdTV8vWye7JOMCA3R0qpFGjGHiES6VaWefEaApGHgzFUQsFskUHXUJQJFuyWKgMgEYexRH+ScjmBzQSs+CT8PK1YImeb8SyaL4mr0dXTvtY270W0BACslQ5Y1GddY1QOAu1LrUySTJgaleOwGOjWxV3Q83GWCcEZWqj6Fssi8sIukvcyYsGKI1Gw0MQBJT7Cy6l7pP7RYocVGeOWpsFYTAq451q7L/uW11Xz0Jvk9Sj0jpR+KYqp9rIxt24xzsqB3tpGZnL7OzkJ6F3TXeinJkmJxc4TwaRtyOO2z+Fkx0Av3USkJ93tJ6dk9yfDRvCM2S0q0dL48Y1FDNEGZrrNFGjnODvWMW0xMranSMb73Yz6lgIx6KY+X1aLGa3RAwucKgdZZKKrB4dNUe+kPlH6ksBK1OvNCSt+xOGWm0lKykyTF7h5SGjr8zmSV6tJP1Xsx6lLpU2zHAeUevzIjs9bh3eIrEut3fXfklf4kUSXeMSaKi4vx9NNP4//au+74KKqufWZ200hI74V0ShASTCAkoBQjoYMFRECKUgWRDxWlKKCI8qJ88KICKiDy+iFIB1+IVAEpkUAo0gkBEggltBTSds73x5R7luxuAhsI0fv8fvvLZu6cmTt37szee+5znuPi4gLR0fLN8fDwgHr16sGPP/4IBQUFUFZWBvPnzwdvb2+IjY2t4IgcHBwcHBxPJiTAKvn8k/BIomM2bNgAvXr1gsLCQvDz84PNmzeDp6c8CxcEAbZs2QLdu3eH2rVrgyiK4O3tDZs2bQI3NzeTxzOVOyZ3xRmwU8K43OPZaFi6JIeR/bWfzeiaKYqo0iE2wy76lRF/bEJlElfxKaZQ6RjG8mKoXgfpIJu5lWUyNUnbMHkZSSIzNyxghFA13A6zWfigmCArK+JRNptEAwu1E5SQ0Bsb2TG9XDNZ/ffIJK/5N5hXYSIJ8dVSeV9nM2yRhOMadilhhTSMMpd4JZScK+BKCLg+shqj4SCb5ZTtZzM2vULCxDMsfBALWCiirq48EFUVQwGMc2SoXo3i31i5XShTlFUJvniW5ES5Kd8HIYLtRwmXWuitI/EkXCHhjaoKI5mZYhYj+xp+3yV/6cKIfhqZFQAuLCGqpgrC+xDvkRKaSutUdkw+v00kyyliFHqqhrNSUjLxhKgerduH2Xm8stg1qQrBYnidcnUDAEDlmqlnrGy//DzoE4nScCrxVDyneB2ImiyWsrDk/P1yP3UykBmcD8kjo3jUkMxWpQMsDLHkhHzNWMZewDZB7Jr1nTvK5SeIMm6hfM+ERixfh5F3xVnuuz9cYvUYnU3CgpUQZDGQEEPvsudNOqSozLqQ0NAMRnBWQ9ILdzAPotNTihfQhRB0yXWqRGpVoRYA4NxqRniPEOVz3t3HvHFuCewZwmPyfSreycJlbeuzdx2qofXnSLhtCHk2rinPdRAj2KqhzniCtR3msvebkCD3Q8xh10nzwKhKqPqezLtCSahlAbIHRN+IEUsNJwj5XAkbNhxhbYvFzMtlo0gbSETxWlXuxcOkPxDl3Js75TbzfooEAzwGT0h14uuvv4YZM2ZATk4OREdHw5w5c6BZs2Ym9y0tLYXPPvsMFi9eDNnZ2VCvXj2YPn06tG/f3mi/7OxseP/992Hjxo1QWFgIERERsGjRIoiLk72EAwYMgMWLFxvZJCcnw6ZNm6CyeCSekDZt2kB6ejrs2bMH2rdvDz179oRr1+QXNyLCiBEjwNvbG3bt2gWpqanQvXt36NKlC1y5csXk8Uxl0f0q+4LJfTk4ODg4OKoDiFglnwfFsmXLYMyYMTBp0iQ4ePAgREdHQ3Jysva7ez8mTpwI8+fPhzlz5sDx48dh2LBh8MILL8ChQ2xSeevWLWjRogXY2NjAxo0b4fjx4/Dll1+Wcxa0b98erly5on2WLl16/+ks4pEMQhwdHSEiIgKaN28OCxYsAL1eDwsWyGFW27Ztgw0bNsDPP/8MLVq0gKeffhq++eYbcHBwKDeiUjFu3Di4c+eO0WdkQPCjqDoHBwcHB8dDobqWY2bOnAmDBw+GgQMHQlRUFMybNw9q1aoFCxcuNLn/kiVLYPz48dCxY0cICwuD4cOHQ8eOHeHLL7/U9pk+fToEBQXBokWLoFmzZhAaGgrt2rWD8PBwo2PZ2dmBr6+v9jG3omEOj0WsTJIkbTmlsFBW+BRF4/GPKIogERIkhaksuvr+bGkBapEU9EpMfewk4uZXlT5JIih7koRNaCgTPnUhzB0IXsz+3je/yPVoxgY+ti88x+zV5GRI6k+WRnTqgCmfkKhU4pgvI0Tqwol7XlGW9BrIdDhU5UAAAAd32UX8Vi5R1iOx9SopT8pmxFeJqLNCHcUdS5QbxXqEKAlKMiuyxKQSyDCfbaMqrmpqdEoSvbeTEeicesruf7rsQ5VEhVCZ1Gjbium+aIqmAIAG5v7X6qy0CdUoAD+2DKGSL/E0caO36ciOr6SDp0sfkg+7z2Kds+XqUUaWKYL7yH1PCCT97R5bslCXPLAu6696VReCXDsQJVFNj4E8IyrBVS6Xr8lrOOsvIuk7qj0lceIl5r4XnBWCNekv+ufl/iylsXbUNSW6EcqymRDE1EmLN3+hfXd5VyEQE30KuEPIwg6yOqvg5sPqnMRcv3aOMsFXus3aTpfEVIu15Syi6CqEKyRYmnTuFiFiB8hu/OEtmfaIGD5Q+66SNFWCqXxS8gyp96SMEGDrEvL5/h0AAODUmy0HCYHK80rure4FlvZevaeUFFx3LOuvgpf8jLnWZcshukCWyE9SliFsb7F3ifgUS/wmeil91zOI2RxnpGyhjqLUfJktlwghSjsGMkK3WI/0J7VNajGFXcfOrB+oyegoydxIB0RpC7oEo2vA3mXqfbB55VVmQ7RRtDrVYaRnQVH9NVLdzczUvnu/oywzk2CCmgRTFARTv4MAMvcyLS0Nxo0bp20TRRGSkpJg79695fZXj29vb2+0zcHBAXbvZpSFdevWQXJyMvTo0QN+//13CAgIgDfffBMGDx5sZLdjxw7w9vYGNzc3aNu2LUydOhU8PCrf7g/sCcnPz4f09HRIT08HAIDz589Deno6XLx4EQoKCmD8+PGwb98+uHDhAqSlpcHrr78O2dnZ0KOHLDKUkJAAbm5u0L9/fzh8+DCcPn0a3nvvPTh//jx06tTpQavDwcHBwcHxRKCqlmNMURA+++wzk+e8ceMGGAwG8PHxMdru4+NjVvYiOTkZZs6cCWfOnAFJkmDz5s2watUqI0pERkYGzJ07FyIjIyElJQWGDx8Oo0aNMlqxaN++Pfz444+wdetWmD59Ovz+++/QoUMHMBB+Y0V4YE/IgQMHoE2bNtr/Y8aMAQCA/v37w7x58+DkyZOwePFiuHHjBnh4eEDTpk1h165d0LChPFr39PSETZs2wYQJE6Bt27ZQWloKDRs2hLVr12oRNJUBZrHGFTuymYRBCUk1/EXU+ZLkETZeoeqiZMZ2W551SFfY6FvfOkT7bt9GJnYJkSRHxRkWpqnO/gR3otKqEkMBAPJuy3992OxEVLwKhquZ7JjXSRinr+xdoTlqjPKPKKTA/BtsZOzqTWZUSuit0JB4MmieFnWWR7YZhcsqsx+hDvPEqLM3Gu6pKUQCAAQpxDAyW3VoQwhwqr0fm3GBZKKzktBLqtyoznjRm4T4Xlc8PeFstkjz9oiRMoFKqs/ChlXvh1xB2ZOBNNyT5NoQ6imzL5J7Rfcc84KVrZcJzAIJ0dW1Yaqe6mzacGgzO74686apyUk6ePU6tVktgFE7SUp+lNI9jARql0gG8EVKWDANzybeHS2vCclRg9dkb4GmigtgpKarthkN47R5huTJuK48j4TYqXkqADRvglEo9Cmi2ukn10lXh5BpSRiqdn/JfVLvPfUCISUyK+cqPM/c2w703qp5hTIY0VmMKB+hZ5SH5QbzLAqN5X0NmxlRW6fUU/Rjz41E3js6MptXUXaO5HdSUtQb9hCP1HPkmlUvIn3J3yYh8arHjCrohjJPiRrGqnk/AEBU+oNE3y+5lNCu2HuS/lLCiP2qoqyQQDyQx8m9VZWkiSdT80IB6+dl6TtYPcl9VnPXGOVXUr0z5F0gUNVhhZyt70m8UI8BVZXAbty4cdpvqwpTXpCHxezZs2Hw4MFQv359EAQBwsPDYeDAgUbLN5IkQVxcHEybJueoatKkCRw7dgzmzZsH/fv3BwCAXr16afs3atQIGjduDOHh4bBjxw54jrwnLeGBByGtW7e2SJxZtWqV2TIVcXFxkJKSUuF+HBwcHBwc/zSYW3oxBU9PT9DpdHD1qnH6kqtXr4Kvr69JGy8vL1izZg0UFRVBbm4u+Pv7wwcffABhYWyC6OfnB1FRUUZ2DRo0gJUrV95/OA1hYWHg6ekJZ8+erfQg5JHqhHBwcHBwcPxTUB2Kqba2thAbGwtbt5IcSpIEW7duhYSEBAuWAPb29hAQEABlZWWwcuVK6Natm1bWokULOHXqlNH+p0+fhuBg80EhWVlZkJubC35+fmb3uR81NoFd8UmWrMiwg3lfBG95XUyMYsQnQ4ocMiS2JMqDRMFSDFDIWkVEA+F0uvb9m/Gy63BIV+b21L/8MjunqvRZxLQmKNTjSycISUhxmYOOuTjFRswVLp2W3bHUPUy1JKRbsvucalpQEilek5eWivcy4pbdM/XYsRopx73C3KJCA5JoK0++Vmkn69iCr7LEIzJdA7EZIw+qbmtpzxZtW/oM1mZNvlNIpGdJxxbosVrB/ZDS2XKPUEte2sDbt7Vtus4DAADg1HOfatvqriTKjWlyP/njQ0ZObPkzSZSl6lZQ8iEhV0q7ZY0DMYgtIxwZx9o8+hcldTtRyCxb9i27pgh5ZmGk0qq4zKUta9m1+bEZC95S7mMRcT+T5UM1mZ3YtB2rJ1HyVJeAaDr5siVfsTo1Vlzx5JpVddMDz8zUtsX+ylzZasJE0Zcx41e0X6J9f/k32T1LCb6lS+ew+ivLB2IIe4HpEtkLz7BfViXGi2RpotsA7fulF2WXcMCXbNlJ8FR0Y6hGyi7WX3TNleUikpyQaqPgbUU24DRTSha8yLq6ojNCl/cEoq9xecgiuU4rP9K2SefT5WP+xZbKdB1ZOxq2yiR32va6ZEbIVBNXiv5kGZMQygUPeUlXOrmPlV/K1L6LMcqPDnlXFM9hiqx2b8pK0CXfzte26Z+W3wsCId3qQmNYndPl55km26TJ7sQ68nJN2TqWIE6XzJIfGnbIM2eqA2JEQlXIpfrn+2vbpJvseS37ea58zHZMGVtVSsUzTPkas9kSkn6AvJShqV0DgEOfT+BRw8elfsU7VQJX75yseCeCZcuWQf/+/WH+/PnQrFkzmDVrFixfvhxOnjwJPj4+0K9fPwgICNB4Jfv374fs7GyIiYmB7OxsmDx5Mpw/fx4OHjwIrq6uAADw559/QmJiIkyZMgV69uwJqampMHjwYPj222+hT58+kJ+fD1OmTIGXXnoJfH194dy5czB27FjIy8uDo0ePVtqT81iiYzg4ODg4ODgeDV555RW4fv06fPTRR5CTkwMxMTGwadMmjax68eJFo4jUoqIimDhxImRkZICTkxN07NgRlixZog1AAACaNm0Kq1evhnHjxsHHH38MoaGhMGvWLOjTpw8AAOh0Ojhy5AgsXrwYbt++Df7+/tCuXTv45JNPHoi/UmMHIUazA5LmXCX74S02khac1TTiTFGPzti03AlZbNYOzqzcp0z2FugaslkgnT2Bcn6hbgw7piNRGlXJn5Sseve2fBwShqXmMQEATQ3SKEU8DSVUSVqE3AgeZBZ3RW4f22iiWkkgKGHNVPVSzZNCjys4sTpr6dhJSm/qPVLDD4WGjGDcIHEF2zdLyVvhSUiY9oQsq5JEiaqlUfilSm4MJ2TZmzJRsKSMeZRo2LHg4qp8I/2B5NJAlTRMw6tp+HiZQgB0dtU2+XiTsGI1bJnkVAEbphypKYWSkEwtX489eVBJanfMleskOJK2oeG6d+RZoHSR5D+iUEi0Rs+AKwljV/oJnmCETJU0qBdJO9C2V5RSERkh0oOQB1VPjEDIh6Iv64+ohOZTQiUWkpB1tR84szBQGjqbe1v27gQShV1Q85+QtjO6TtWjdYmR1KE+yS2jPAOl6cyzZdOaPbdamxP1Y6P8TqLiRCaESVVRVSAhivRdpfUNmpOJEtJvyLN59CQEXqpkrBLGvdhzXfILU3e2DZTJoZQkL9qRd4gSXq8LICGUyn3WQrcBjJ8Bpa6CK3lnkvppuZSojZFcgOIpJiqoRiG4Sj+i3g+ReBbVdxAl5qvh34I7aedLzF69J6qi8uNCdUqujxw5EkaOHGmybMeOHUb/t2rVCo4fP17hMTt37gydO3c2Webg4FAl3M4H5oTs3LkTunTpAv7+/iAIAqxZs8bsvsOGDQNBEGDWrFkmy4uLiyEmJgYEQdBCfjk4ODg4OGoiqksxtSbjgQchBQUFEB0dDV9//bXF/VavXg379u0Df39/s/uMHTvWYjkHBwcHB0dNgYRYJZ9/EqwipgqCAKtXr4bu3bsbbc/Ozob4+HhISUmBTp06wejRo2H06NFG+2zcuBHGjBkDK1euhIYNG8KhQ4cgJiam0ue+MzBJ+24/doL2XU1gVfD1em1b7VmT5bIjLJkR0tTv92RyYtlfmdom20Gvs31VNU6iQWDYwtxQunCZbCc0JMTObOICvnNb/hsYom3SyKppjPgJjswVLYTJCpulPzCSoz6OqDVmyHXNWMxcxXXXElec4g41SvpESHmgpHk3UiG9RZYUlOUiMZaFWUk35GMJRGtB+osk5wpXdFRyifuZ6hn4Ke1EFG61hFsAINjJLnnDDpb8SP8CuQ8FSp2J/gWekpfFhDBGusVMRlTUPfeKXE9C5KOubM2lT9zHRu51VR2WLk2QZYiSH5YBAMC9C+w63eZ+yPZV2kr6Yx3bpuoZkARvYiDToJGuyUsbVCmTLl2oCe5y3vpR2+b3n7Gser8tl6tMlr0EkqhQJTgjWbYyrPhBrsfzTE1W2kb6+POyS9YodXpRIdtXTe5I7reuXRdWZ8WVTgmX0j6SJNK2/BoyXiFLrnFK/anLP1tZAmrESOhawkAAEBWNmaPPz9a2PbWO9Sc1aaGqfAoAID7TgZUr2ix4i4U+4nFGOFXJ3QVf/KRtq9VVfm7VfgdgfO/FBIVYS56hvDff1747DpZJ04WLma6M4+T/YcfaJ5NEpfMkWaUN67u61oqGE1nuEVxJgrvb8jKIWJckNlMI9VIOeWcRjRYhQnnvkKXfsmWs72G+/LzY9CfE0r3bmH2ccn+oFg+BqoRa9hMjMtNlYJt+shKo4eyfpFxeNpMySMJEsqRa9ON/AQDA/k1GkHV4bojJ81cl3GtHVrxTJXAz70zFO/1NUOWcEEmS4LXXXoP33ntPEyi7H1evXoXBgwfDmjVroBblc3BwcHBwcNRQ/NOWUqoCVT4ImT59Ouj1ehg1apTJckSEAQMGwLBhwyAuLg4yid6/OZjS0cfOSWCnzACM8o8o+SIcezKvhEasqsfCXeE8SXXtKs8YbXyIsAuZGRtOKTNTkg5e14wdXwhQ0nO7kvwhdIav5EShhEkthE5JUw1gnBtBnTXoW5DzBBM1SCX3S/CVZeycxcwroqlhqqm7gYX3AQCApxLGSUim4E8InwrRUPV+AAAIteXZh2DDCJM0VE8laUr3WD0kkrtA30RO5Y13mcdF9X4AAAiesqdEbMg8PkbqqY5KSvE8RiAWm8szRymVeZTEOKboqxJG8SwLeRNDyPGV2ZNQmxDcCCESlRxAVOVV2vVf7bvNM/LM17YVCzXGInLv1b+NWY4dUPsGUWGlszjVUyFRYqkjSQql2Pm8xQjARkTraLnP0HBaNV07APOAqLNJAACxrRzui4eYx4iqp6rhvoI3U7ClM1exsdymghfpY5QwaiO3L/W8CU1I2PINpZ9eZYqkYisSUn9Kzu4pxDAbrS6UtFvMvDNq36n3MvPOqH0UALTnUfAnCrwFt9n5VcVaI6VhMmm6KM9WHfuSOtWX3zF4h+Q/ItfJQsJZH3Mc0Jrtq7xLavVi7zvRjSxZt5DbRLDfwepMyOVisNK3iRqulMOI3oK//L5RQ4kBmBdO8CDnIcRT7Rkk9073DPM+aSR2QsYXE9qycyrbqVfW6F2neB6NQnDJO131gOgi2LtQUongdoSYT95l9q/I5xdqP1gyNWtRncTUmooqFStLS0uD2bNnww8//AAC0X+gmDNnDuTl5Rkl26kIpnT0Z6zYVrEhBwcHBwcHxxOLKvWE7Nq1C65duwZ1SP4Hg8EA77zzDsyaNQsyMzNh27ZtsHfv3nJxxHFxcdCnTx+j5DgqTOnoS//3kZavQghjM0J15o55NM+K4oGg69l55LsyC8XbJO8FDaG7p8xKCkiIGAnhBSXk0yjElqyXa7M8OxLuqh6fchGI2JmghVmSnCdUqO6qfJ2ll4u0TbZ0Nm3vqlwTCTtGek3yuWi4KuU9aKGYdA1eDXsj9TTyQqmzzOtsXd5wg4Xw2igzSixmdaa8BEGdrdNQZAq1/jQ7qyrMpYXiAiAJ9RO8lJBFRzKDpeG4ajZjuo16rPT68tuIyxWvKyGArkRMjISCq/VDMgsE1VNEwl2pEJ06izXyftB7q7SjlE88XzQDtRpOSzLv0hBiKqx2v40Wzg4AkH+b1EnpB7QdKJQsuUZht7RvK7NpkXgi8C4Jn7yphGzStqXlHkooNLm3qoeCirIB6Vva+YuI94X0cUmtKxEzE90JX0j1ABj1DXJ8hcdCw0C1qRfhfBjlPKlN7rMC+oyq7wX6LjLyxCjPG94kNvWItLZWVxKyTjyTgnJ9KJiYf9IQWALVk2GUuyqLhRULSr4blEi4P713algxuQ6jZ0Tlr9H3M3nGBcUjJZE+rPYjiXpyyftZ5fwJ4STb+mMAX455cFTpIOS1116DpKQko23Jycnw2muvwcCBcgrtf//73zB16lSt/PLly5CcnAzLli2D+Ph4MAVTOvr3bKp8JYmDg4ODg+Oh8U+LbKkKPPAveX5+Ppw9y9YYz58/D+np6eDu7g516tQBDyLSAwBgY2MDvr6+UK+eHL1AvSQAAE5O8gwqPDwcAgMDgYODg4ODg+OfgQcehBw4cADatGHEP3WZpH///vDDDz9UWcUqguEsyZURVz7MtOwoCzGziZJdhwJJdU/dvqoSp+EvFqImtmCkONFXIWQ2ZV6eex//ix0/THab6/uwnCVGBDY19JW4ILUcE8cOsW3hJLxLWS6iKoBYm5Bp3eWwO9sA4qol7k4tVXYEI4BJh1mIshApuymlU2ns+NStrKojlpBwVSVNueDoys55gtgrJDAa1ku0Q6HsNzmUUdeqO9tIQ0/vyUsChj/ZMcG9fBZImrrdsEsJf6Suf7qEpahAYj5bQqJkW7ihtK8HOU8hWeZQU9MTop5ACcyKKx2z2BIU5hDlWU/ZXYwHGUFXbK6Q9mhaeqKqiZkyiRa9iDooVak9li6fejV7BtxCdrB9lSUJPMTuNyVAq6Bhy2reISmbqFb6s+dFOrpL/lLbVdsmkCUoPKL0Y+KhFJ9hz5AaCo35JO38FVZ/UEjfQggjX9O8QaWpsiqn3RD2jGGxvDSEp0noZmD5nCsll9gSkv4UId4qOU+uDWUEW693WrI6BSjE1zPsuZNI2LCmpkvCkqVCOVeJ0JiQ4FVVXgBAnXLNtVg4vnSOLG34K7lhLrL7YEhlcgNqP8c8ttx7+i12n+upOZLo/aZLUPuVsGviWZbUpbgAZoM5mez7dZksLJJlb6Eeea/s3CGXh5O2cWDvP1RVrA+z+6TmiwEAAG9liYjkgaFKqFoYLiGhqssw+ubdtW1l//2OHT9XCecnIduPAw+afI7jIQYhrVu3fqB1r4qiX0JCQvg6GgcHBwdHjQdfjnlw1FhihUByTOAxNstU87fkn2BCSyq9D08fZAfwYAQ5KTUVAO7LDaOSSQG0TLd4iglz2TVnIZuCt0Ka+2s/syEzDbwqj8bFAHJ8RSxMCCXbLmayY7op4aj3iCdCERADAC2fRd4RVu5Ow1nVzL50tqkvTxSk+WYESrx1kc8v+DA2rGGdHA6s68qEmGg7qkJWVPwJ7zKvghglhwJqXhoALcwRADSiny6GkMkoMVbxKEmEMCkoOV2k8+w6xcYxzEaZMVFPiEjCgtFb8XDQUGY/FoaKyuzLyKtAhLXwikyoLExlpDmnuuxYqJCRqXCYmmVYvccAABDE+pOohDJLB35j5cQrIjzdXN5vPfG4UM/bDaUu7kScjnpdzqXLxyH3VrqktB/J6gyXyQxdEawyEu7KZeRJKVcRIwsiIbA0t8weWXyL5v0BEloKXq7yMQk5EW+y7zaNQsuXK15EMZF5KDVxOQDNo3XvBrumWjRHT4HslfFIJvliaP4l1UPQmAi9lexg3xvIHrni+SybsF1nRTSPeD+koyzPlNhICaG9yfqLdId5anSKt1S6zfqrjnr5VMKlHxMgC217gtRfaX9CjKdeF1C8mTR7tppjh+aOwsskNL++7AGhxHtpOwuJL1Nybtk2YwJoJb+w7LW2vV+Qv9iRtieTU0El+JIsuNQDLKpyCCZIqNT7oe84WPt+82VZlM6lnTE9gOPJQ40dhHBwcHBwcDxJ4F79BwcfhHBwcHBwcFQBOCfkwWFV7pjqRNFBlo+hbOki7bvgIusy6HsO07YVz/gYAABsXiQpia8z158QLStD0pTa0u9MDO21H2Wi33dPMVdwrd5E7TFPcdt6E1cuIYOJkTJJzfDr/7HjK65mvMdcjDZ9Se6F7bIqp65DL3aeorvku6LzITBXs2H3Fu17yUHZ3Xr3HBtnujZit9q2i0wuNuxnJFBdXAw7vkLuLEpJ17bZRct6CniXuIq7v6h9V3PGUPdzyjfsnMkj5TaRrt3WtgkOzEWra6sQNsm9KdvDltCEWrbKX6LYmiSTHxf3Ydfe/yu2nFO2XSZUzlrNSJTvfsIIl3hVWV5wcmTncWXu+eI18jKM7dMh2rb5X7NlhOErFVczIQUXfjRd+25b1125NkbmVtVXS+d9xa4jkC2dFKfJrnDRlvQhZ0bxFWzke24zgOTVOUmWGtWlG7KUVfTtCu273TNK3qKrzL2u7yUTPqd1Y3lQxs1lIfMqGVZoyoibEwaw5aJpP79Q7pzFc+ez+jvI9Rc9iOrwywO079IO+XkuO86W1exGsXw4czrIz/iIz9hSmUpiNWxlCrb525jiqtPz8n0WY5iqr7rEAgAA9+Qli3tr2HKuXSO27CXWkfu74RxbutDVZ8TXn8fLy269t7JlgLKVC2SbDNaHbV57VfteumSp/EXP2sluBNNAUnNJic2S2bYDLI+Mlr/qPFMALlzB6u/QXlGu9WPaJ5cmsKXEoIny0satr3dr22rHyEuO+mTWRyn5u2wpy1+lQtetJ/tH6fvFs2dpm+zHTda+l3wjPw83d7JlJ+932BKXIV0m/toMYzl0qLZK4YRJ8jFfYSqsmHtd+cuW3/K3sGVQ9xULAQCgaOrb2rbaswjB9xHB1q5qIjxLirMq3ulvgipVTOXg4ODg4ODgqCxqrCfk3uIP2D8ku62qyle2muVUUWfYggvJJkkJdmrW1RKSGyGph/a9dIGchVMXy0LUjFQUlTwuRlkiL18ot69KOKT70nwvRqQ6RZlROsjC2sTGbHaihqsVL1qubbIfNlD7rqpiGnauYdv8WV4PSr7Uzk8VW1V1U6qSqITQ6Z5hOR6ky4xYquaewAPMi1S8PZ3V762h5c959gj7J1Ah6VKCLc1noah14sVTbJuzouaYwbYJoWy2KrjJ3imVDAoAID7bqVw9jNR0aT4KRVEVs06zOmeTe3vrtvyXEDqFBix8UQ1rlE4S0nKh0s61mPdFzV8EACAGyP1Zzd8DAEzBFkBrn7K1a7VNNv3YbFwlVdO8GWr2VHlnxaPkRTxCClkV8oinwJfN6tScJNRbaPidkb/FkODy1+RJ7p1ChBQbMw8izdqq5b7RMY8PJZxrxyUhwirxVPAm+WqocqySrdmwhnkgdS/1Y+cU5XNJqew6jPK8KCRR6m2UzpOsreq2QyzMXpcsPxtGiqEOJDu2GqpMMzX/xbxYutayR6lsHctSq+vA3kV4W8mFdDiVHZ+8wlWSLs3jYtTOasj6CZr9Wu6v9FmnyrOCh+IdIsRQ6Rg7v6Bm/yZZofFoOqtTGyUDMyV3+7G+p94/PM1sjOQComLkvzQPjNqOJARXvTYAgNL/k9vPfiLLoGzjycjfjwo2tgEV71QJlJZkV7zT3wScE8LBwcHBwVEFqJEz+moGX47h4ODg4ODgqB5gDUZRURFOmjQJi4qKHqstt6/Z9jW57v90+5pcd25fvfee48lEjR6E3LlzBwEA79y581htuX3Ntq/Jdf+n29fkunP76r33HE8m+HIMBwcHBwcHR7WAD0I4ODg4ODg4qgV8EMLBwcHBwcFRLajRgxA7OzuYNGkS2JFkcY/DltvXbPuaXPd/un1Nrju3r957z/FkosaKlXFwcHBwcHDUbNRoTwgHBwcHBwdHzQUfhHBwcHBwcHBUC/gghIODg4ODg6NawAchHBwcHBwcHNUCPgjh4ODg4ODgqBbUmCy6N27cgIULF8LevXshJ0dO3+zr6wuJiYkwYMAA8PLyquYacnBwcHBwcDwIakSI7p9//gnJyclQq1YtSEpKAh8fHwAAuHr1KmzduhUKCwshJSUF4uLiTNofPHgQ3NzcIDQ0FAAAlixZAvPmzYOLFy9CcHAwjBw5Enr16vXYrqeq0LZtW1i0aBEEBwdXd1UqhCRJIIrlHW+SJEFWVhbUqVPHrO3hw4chLS0NWrduDWFhYfDXX3/B119/DZIkwQsvvADJycmPsupQUlICa9asMTkA7tatG9ja2pq1zcrKAnt7e/D09AQAgF27dhn1vREjRkBCQsIjrf+jQFhYGKSkpEBkZKTF/XjbVQ1ycnJg//79Rm0YHx8Pvr6+1Vyzx4+BAwfCp59+Cv7+/tVdFY4qQI0YhDRv3hyio6Nh3rx5IAiCURkiwrBhw+DIkSOwd+9ek/bR0dHw5ZdfQlJSEnz//fcwatQoGDx4MDRo0ABOnToF33//PcyePRtef/31CuuSlZUFrq6u4OTkZLS9tLQU9u7dC88++6xZ2w0bNkBqaiokJydDixYtYNu2bfDFF1+AJEnw4osvwpAhQ0zarVu3zuT2F198EWbPng1BQUEAANC1a1eLdU9NTS33Y5CQkADNmjWzaFdcXAyiKIKNjQ0AAJw7dw4WLlyo/Ri88cYb2gDvfty9excGDRoE69evB2dnZxg6dChMmjQJdDodAMgDSX9/fzAYDCbtV61aBT179gRXV1coLi6G1atXQ48ePSAuLg50Oh1s2bIFfvzxR+jdu7fFa7gflR3AnT17FpKTk+Hy5csQHx9vNADev38/BAYGwsaNGyEiIsKkfXx8PHz44YfQuXNnWLt2Lbz44ovQuXNnaNCgAZw+fRo2bNgAq1atgs6dO1usR3UN4v7973+b3D5mzBgYO3as9iM4atSocvs8CW1XWloKEyZMgFWrVoG7uzsMGzbM6DmvqP8BAFy7dg2OHTsGsbGx4OLiAlevXoXFixeDJEnQqVMnaNSokVlbc6hs/ysoKIChQ4fCzz//DIIggLu7OwAA3Lx5ExARXn31VZg/fz7UqlWrwnPevn0bfvnlF+257dGjB7i4uJjdv7rb7siRIya3x8XFwfLlyyEsLAwAABo3blzRpXM8yai+3HmVh729PZ44ccJs+YkTJ9De3t5suYODA2ZmZiIiYpMmTfDbb781Kv/pp58wKirKYh0uX76MTZs2RVEUUafT4WuvvYZ5eXlaeU5ODoqiaNZ+3rx5qNfrMTY2Fp2dnXHJkiVYu3ZtHDRoEA4dOhQdHBxw1qxZJm0FQUBRFFEQBLMfS+e+evUqtmzZEgVBwODgYGzWrBk2a9YMg4ODURAEbNmyJV69etWsfatWrfCXX35BRMTdu3ejnZ0dNm7cGF955RVs0qQJ1qpVC/fs2WPSdtSoUVi3bl385Zdf8LvvvsPg4GDs1KkTFhcXa+0mCILZcz/99NM4depURERcunQpurq64scff6yVf/HFFxgTE2PWfu3atSY/Op0Ov/rqK+1/c0hKSsJu3bqZzNx5584d7NatG7Zr186svaOjI2ZkZCAiYnx8PH7++edG5XPmzMEmTZqYtb9z5w726NED7e3t0dvbGz/88EMsKyvTyivqdytXrkSdToceHh7o5OSEmzdvRldXV0xKSsLk5GTU6XT4008/mbUXBAEDAwMxJCTE6CMIAgYEBGBISAiGhoaatK3utkNEnDRpEvr4+OCMGTNwwoQJ6OLigkOGDNHKK+p/27dvR0dHRxQEAX19fTE9PR0DAwMxMjIS69Wrh3Z2dpiSkmLW3tr+98Ybb2BkZCRu2rTJ6L6XlZVhSkoK1q1bFwcNGmTS9oUXXtCe22PHjqGnpyd6eXlhfHw8+vj4oK+vLx4/fvyJbTtL7z11u6W+z1EzUCMGISEhIbh48WKz5YsXL8bg4GCz5R4eHnjgwAFERPT29sb09HSj8rNnz6KDg4PFOvTr1w/j4+Pxzz//xM2bN2NsbCzGxcXhzZs3EbHiBzIqKkob/Gzbtg3t7e3x66+/1soXLVqEDRo0MGnbvn177NSpU7mBgl6vx7/++stivRERX3rpJUxISMCTJ0+WKzt58iQmJibiyy+/bNbe2dkZT58+jYjygOR//ud/jMonTpyILVq0MGlbp04d3L59u/b/9evXsVmzZtiuXTssKiqq8EfU0dERz58/j4iIkiShjY0NHjlyRCs/d+4cOjk5mbW3dgDn4OCAR48eNVt+5MgRi33HxcUFDx8+jIhy31O/qzh79izWqlXLrH11D+KGDh2KMTEx5X6sKtP3qrvtEBEjIiJw/fr12v9nzpzBiIgIHDBgAEqSVGH/a9myJY4YMQLz8vJwxowZGBAQgCNGjNDK3333XUxMTDRrb23/c3V1xT/++MNs+e7du9HV1dVkmZubmzZ569ChA/bu3VvrNyUlJfjGG29YHARWd9tFR0djp06d8MSJE5iZmYmZmZl4/vx51Ov1uHnzZm0bR81GjRiEfPXVV2hnZ4ejRo3CtWvX4r59+3Dfvn24du1aHDVqFDo4OBj9oN+Pvn374htvvIGIiD169MCJEycalU+bNg0bNWpksQ7+/v64f/9+7f+ioiLs0qULxsTEYG5uboUPpIODA164cEH738bGxugFff78eYsv1JkzZ2JQUJDRS6GygxAnJyc8ePCg2fIDBw5Y/CF3dHTUXmY+Pj4mB3Hm7B0cHLTZrIq7d+9iQkICtm3bFjMyMiy2m6+vrzaAvHnzJgqCYDSoSU1NRV9fX7P21g7g/Pz8jNr8fqxbtw79/PzMlnft2hU/+OADRERMTk7G2bNnG5V/9913GBkZada+ugdxiIirVq3CoKAgnDNnjratMu1X3W2HKPc/9fpVZGVlYd26dbFPnz6YnZ1tsf2cnZ3x7NmziIhYWlqKer0eDx06pJWfPn0aXVxczNpb2/+cnZ3xzz//NFuempqKzs7OJsscHBy0uvv5+ZV7B5w6dcpi3au77YqLi/Htt9/GqKgoo7pXtu04agZqxCAEEfHnn3/G+Ph41Ov12gxCr9djfHw8Llu2zKJtdnY2hoSE4LPPPotjxoxBBwcHbNmyJQ4ePBifffZZtLW1xV9//dXiMRwdHTVvgIrS0lLs3r07Nm7cGI8cOWLxgQwMDMSdO3dq9REEweicO3bswMDAQIt1OHToEEZFReGQIUOwoKCg0g+jh4cH7tixw2z59u3b0cPDw2x527Zt8V//+hciIiYmJpbzSq1YsQLr1Klj0rZevXom2zYvLw8TEhIwOjraYrv17dsX4+Pj8T//+Q926dIFk5OTsXnz5njixAk8efIktmrVyqIXB9G6AdyHH36Ibm5uOHPmTDx8+DDm5ORgTk4OHj58GGfOnInu7u44adIks/bHjx9HDw8P7NevH37yySfo5OSEffv2xU8//RT79euHdnZ2uGjRIrP21T2IU5GVlYVt27bF9u3b45UrVyrVftXddoiIoaGhuGXLlnLbs7OzsW7duvj8889bbD9PT088duwYIiIWFBSgKIq4d+9erfzw4cPo6elpsQ7W9L/evXtjkyZNTE4iDh48iLGxsdinTx+TtvHx8Zr3tUmTJrh69Wqj8t9++83ivX8S2g4R8b///S8GBgbitGnT0GAw8EHI3ww1ZhCioqSkBC9fvoyXL1/GkpKSStvdunUL33//fYyKikJ7e3u0tbXF4OBg7N27t8WZhopGjRrhihUrym1XByJ16tSx+ECOGDECIyMjcerUqdisWTPs378/1q9fHzdu3IibNm3CRo0a4euvv15hPQoLC3Ho0KEYGRmJOp2uUg/jm2++icHBwbhq1Sqj9fk7d+7gqlWrMCQkBEeOHGnWfs+ePeji4oKTJk3COXPmoKenJ06cOBF/+ukn/Oijj9DV1RWnT59u0vatt94yO0i4e/cuxsfHW2y3nJwcfP7559HJyQmTk5Px9u3bOHLkSM2NHRkZqc22LOFhB3CIiJ9//jn6+flp51Td635+fmavm+Ls2bPYq1cvrF27tjaAtrGxwcTExHI/DPfjSRjEqZAkCadNm4a+vr6V7ntV0XavvPLKQ7UdosypMPdcZWVlYUREhMX269atG3bu3Bl3796NQ4YMwbi4OOzUqRPm5+djQUEBvvzyy9i+ffsK6/Gw/e/mzZvYvn17FAQB3d3dsX79+li/fn10d3dHURSxQ4cOeOvWLZO2GzZsQHd3d1y0aBEuWrQIQ0JC8Pvvv8c//vgDFy5ciEFBQfjee++ZPfeT0naI8nugQ4cO+Mwzz/BByN8MNW4QUl0YO3as2fXT0tJS7Nq1q8W1+fz8fBw8eDA+9dRTOGTIECwuLsYZM2agra0tCoKArVu3tkgOvR9r167F0aNHV8qmqKgIhw0bhra2tiiKItrb26O9vT2Kooi2trY4fPhwLCoqsniMPXv2YPPmzcutZwcEBJgl1CLKL1F1NkQhSRIiygMRS14aczh37hwePXoUS0tLK23zMAM4ioyMDNyzZw/u2bOnnHeiMlDX0R9kAD1y5MgnYhBHceDAAZw1a5bGh6oMqqPtEBEzMzNx06ZNZsuzs7Pxhx9+MFt++vRpjIyMREEQsEGDBpiVlYVdu3ZFvV6Per0evby8MC0trVJ1sab/HT9+HBcuXIjTpk3DadOm4cKFCy2S9VWsWLECAwMDy/FS7O3tcfTo0UZk1/vxJLWditmzZ2P37t3x0qVLD2TH8eSiRoToPgkoKyuDwsJCcHZ2NluenZ39wJodRUVFUFpaCrVr166KalrE3bt3IS0tzShENzY21uw1mcL169chIyMDJEkCPz8/CAkJeai62NrawuHDh6FBgwaP3X79+vWwbds2GDduHHh7ez/U+R8Xbt26BZcvX4aGDRuaLM/Ly4ODBw9Cq1atHui4GRkZUFhYCPXr1we9/tFpFl65cgXmzp0Lu3fvhitXroAoihAWFgbdu3eHAQMGaKHaj8q+qpCbmwseHh7a/1u3boV79+5BQkKC0fbKYN26dbB9+/bH1v8MBgMcPHjQ6LmNjY19LO8cgKptO46/H/ggpIpw6dIlmDRpEixcuPCR2N+7dw/S0tLA3d0doqKijMqKiopg+fLl0K9fP7PHP3HiBOzbtw8SEhKgfv36cPLkSZg9ezYUFxdD3759oW3bthbrp9onJiZCvXr1Km0/ZswYk9tnz54Nffv21V5CM2fOfCT296OgoACWL18OZ8+eBT8/P3j11VctvgitFbqz1v6tt96Cnj17wjPPPFOp66tqewCAr776ClJTU6Fjx47Qq1cvWLJkCXz22Weavs3HH39sciBz4MABSEpKgoiICHBwcIC9e/dC7969oaSkBFJSUiAqKgo2bdpk9sfQWnsV1gimPSmwRp/IGuTm5sKRI0cgOjoa3N3d4caNG7BgwQIoLi6GHj16PPQkwhpUViiPo4ageh0xfx+kp6dbFbNuyf7UqVOapocoivjss8/i5cuXtfKKIiQ2btyItra26O7ujvb29rhx40b08vLCpKQkbNu2Lep0Oty6desjsRcEAWNiYrB169ZGH0EQsGnTpti6dWts06aN2XNba9+gQQPMzc1FRMSLFy9icHAwuri4YNOmTdHd3R29vb0tLg80btwYN2/ejIhyNIaDgwOOGjUK586di6NHj0YnJydcsGDBI7Onyyaff/45Xrlyxey+j8L+k08+wdq1a+NLL72Evr6++Pnnn6OHhwdOnToVp02bhl5eXvjRRx+ZtG3RogVOnjxZ+3/JkiUYHx+PiPIyXUxMDI4aNcrsua21R5TDSsPCwtDe3h5btWqFPXv2xJ49e2KrVq3Q3t4eIyIi8MyZMxaPUVxcjMuWLcPRo0djr169sFevXjh69Ghcvny5FvL6sMjJycEpU6aYLbdWnwgR8dKlS0Y2KkpKSvD33383a7d//350cXFBQRDQzc0NDxw4gKGhoRgZGYnh4eHo4OBQ4XLKjRs3cNu2bdozeP36dfz8889xypQpFjVKEOWlF1MfnU6H48aN0/7nqNngg5BKwpzokPr53//9X4svA2vsu3fvjp06dcLr16/jmTNnsFOnThgaGqqF/Fb0IkpISMAJEyYgoqwV4ebmhuPHj9fKP/jgA3z++ecfif1nn32GoaGh5QYplSWXWWsvCILGm+nTpw8mJibi7du3EVEmdyYlJeGrr75q1t5aoTtr7QVBwC1btuDbb7+Nnp6eaGNjg127dsX169ejwWCwcOVVYx8eHo4rV65ERHmgrNPp8D//+Y9WvmrVKoyIiDB77efOndP+NxgMaGNjgzk5OYgoR2f4+/ubPbe19ojWC6ZVxSDGEiqavFijT2TtACYpKQkHDRqEd+/exRkzZmBgYKCRMNrAgQOxe/fuZu2tHcRYI5THUXPAByGVhLWiQ9bYe3t7G2k7SJKEw4YNwzp16uC5c+cqfJk4OztrL0o1xI2G/B09ehR9fHwemX1qairWrVsX33nnHY1U+CAMd2vs6SAkLCwMf/vtN6PyP/74A4OCgszaWyt0Z609rX9JSQkuW7ZMUzr19/fH8ePHW/wRtNbelL4NJRpnZmaa1bcJDg7G3bt3a/9fvnwZBUHAwsJCRJS1cSwpHVtrr9bfGsE0awcxhw8ftvhZtmyZxWfXGn0iawUW3dzcNG9FSUkJiqJoVJe0tDQMCAgwa2/tIMYaoTyOmgM+CKkk/P39cc2aNWbLDx06VOHL5GHta9eubdJ1OWLECE1/pLKiQYiyeBmdYWZmZlp8mVtrjyh7Hfr164eNGzfGo0ePoo2NzQO9SB7WXhAEvHbtGiLK9+D+H6SK6m6t0J219nQQQXHhwgWcNGkSBgcHVzj4tcY+NDQUN27ciIhytIMoirh8+XKt/Ndff8WQkBCTtm+//TY+9dRTuHHjRty2bRu2adMGW7durZVv2rQJw8PDzZ7bWntE6wXTrB3EWCs9bo0+kbUCi1ToDrH8c3/hwgWLz461gxjEhxfK46g54IOQSqJLly744Ycfmi1PT0+3OKuwxr5p06b4448/miwbMWIEurq6WnyZNG7cWPshQcRyoa07d+606Na01p5i6dKl6OPjg6IoPtSL5EHtBUHARo0aYZMmTdDJyamc1svvv/9u8UVordCdtfbmBhEqJEkq592pSvuJEyeil5cXDho0CENDQ/GDDz7AOnXq4Ny5c3HevHkYFBRUTsZfRV5eHvbs2VMTGExMTDTi36SkpBgNaKraHtF6wTRrBzEeHh64YMECTWL8/s+vv/5q8dm1Rp/IWoHF+vXrGy2DbtiwQfNCISLu27fPosCitYMYFQ8jlMdRc8AHIZXEzp07jX6I70d+fr5FvQtr7KdNm4YdOnQwazt8+HCLA6C5c+fihg0bzJaPGzdOm60/Cvv7cenSJVyzZg3m5+dX2uZh7SdPnmz0uV/34N1338VevXpZPIa1QnfW2IeEhOCNGzcqPMejsjcYDPjpp59i586dcdq0aShJEi5duhSDgoLQw8MDBwwYUOF9uHfvnkliZGVhrb01gmnWDmLatWuHn3zyidnyiiYv1ugTWSuwOHnyZFy6dKnZ8vHjx+OLL75ottzaQQzFwwjlcdQM8BBdDg6OfwTOnz9vFKKrhk1XhOnTp8Ps2bMhJycHBEEAAABEBF9fXxg9ejSMHTvWrO3q1auhoKAA+vbta7L81q1bsG7dOujfv7/Jcmv0id5//31IT0+HlJQUk3YvvfQSrF+/HiRJMlt/SygsLASdTgd2dnYmy6dMmQL16tUzG4I+YcIEOHnyJKxcubLS50xLS4Pdu3dDv379wM3N7aHqzfFkgQ9CODg4/rF4EH2fhx3EPEpYqv+jEliszLkrg4oGMY/6/BxPBsTqrgAHBwdHdeHmzZuwePHiSu0bGhoKCQkJkJCQoA1ALl26BK+//vpDn99ae0v11+v1FtWQr1y5AlOmTHkk564McnNzYfjw4dV2fo4nA49Or5mDg4OjmrFu3TqL5RkZGVYdX/0hfNjZeEX2j7L+1XnuJ+H8HE8G+CCEg4Pjb4vu3buDIAhgadVZ5XmYgrU/hNbaW1P/6jz3k3B+jpoBzgnh4OD42yIgIAC++eYb6Natm8ny9PR0iI2NBYPBYLJcFMVK/RA+Kntr6l+d534Szs9RM8A5IRwcHH9bxMbGQlpamtnyin4k/fz8YNWqVSBJksnPwYMHLZ7fWntr6l+d534Szs9RM8AHIRwcHH9bvPfee5CYmGi2PCIiArZv32623NofQmvtral/dZ77STg/R80AX47h4ODgMINdu3ZBQUEBtG/f3mR5QUEBHDhwAFq1avVI7K1BdZ77STg/R80AH4RwcHBwcHBwVAv4cgwHBwcHBwdHtYAPQjg4ODg4ODiqBXwQwsHBwcHBwVEt4IMQDg4ODg4OjmoBH4RwcHBwcHBwVAv4IISDg4ODg4OjWsAHIRwcHBwcHBzVgv8Hq0F+fstNHRkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "point_comparison = df.filter(regex='Cumulative|username').iloc[:,1:]\n",
    "adj = point_comparison.T\n",
    "adj = adj.corr().values\n",
    "\n",
    "print(\"quick point comparison heatmap...\")\n",
    "sns.heatmap(adj)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c8153425",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<Graph object, undirected, with 150 vertices and 22350 edges, 11 internal vertex properties, 2 internal edge properties, at 0x2b175c190>\n",
      "<Graph object, undirected, with 150 vertices and 524 edges, 11 internal vertex properties, 3 internal edge properties, edges filtered by (<EdgePropertyMap object with value type 'bool', for Graph 0x2b175c190, at 0x2c5928810>, False), vertices filtered by (<VertexPropertyMap object with value type 'bool', for Graph 0x2b175c190, at 0x2c59d1650>, False), at 0x2b175c190>\n"
     ]
    }
   ],
   "source": [
    "idx = adj.nonzero()\n",
    "weights = adj[idx]\n",
    "g.add_edge_list(np.transpose(idx))\n",
    "\n",
    "ew = g.new_ep(\"double\")\n",
    "ew.a = weights \n",
    "g.ep['weight'] = ew\n",
    "\n",
    "gt.remove_self_loops(g)\n",
    "\n",
    "tree = gt.min_spanning_tree(g,weights=g.ep.weight)\n",
    "g.ep[\"minspanningtree\"] = tree\n",
    "\n",
    "g.save(\"participant_graph.xml.gz\")\n",
    "print(g)\n",
    "\n",
    "thresh = np.percentile(g.ep.weight.get_array(),97)\n",
    "edge_filter = g.new_edge_property(\"bool\") \n",
    "for e in g.edges(): \n",
    "        if g.ep.weight[e] > thresh:\n",
    "            edge_filter[e] = True \n",
    "        else: \n",
    "            edge_filter[e] = False \n",
    "g.edge_properties[\"edge_filter\"]=edge_filter\n",
    "\n",
    "# g.set_edge_filter(tree)\n",
    "g.set_edge_filter(g.ep['edge_filter'])\n",
    "print(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "23a98bae",
   "metadata": {},
   "outputs": [],
   "source": [
    "ew_focus_on_user = g.new_ep(\"double\")\n",
    "\n",
    "for e in g.edges():\n",
    "    if g.vp['username'][e.source()] == user or g.vp['username'][e.target()] == user:\n",
    "        ew_focus_on_user[e]=2\n",
    "    else:\n",
    "        ew_focus_on_user[e]=1\n",
    "        \n",
    "g.edge_properties[\"ew_focus_on_user\"]=ew_focus_on_user\n",
    "\n",
    "gt.remove_parallel_edges(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "6d0a6a83",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|████████████████████████████████████████████████████████████████| 150/150 [00:00<00:00, 64913.91it/s]\n"
     ]
    }
   ],
   "source": [
    "fname = 'participant_graph_d3_js.html'\n",
    "# fname = '../../assets/participant_graph_d3_js.html'\n",
    "if len(glob.glob(fname))>0:\n",
    "    os.remove(fname)\n",
    "    \n",
    "g.vp['color'] = g.new_vp('string')\n",
    "g.vp['hover'] = g.new_vp('string')\n",
    "# g.vp['click'] = g.new_vp('string')\n",
    "# g.vp['image'] = g.new_vp('string')\n",
    "g.vp['opacity'] = g.new_vp('float')\n",
    "\n",
    "for v in tqdm(g.vertices(),total=g.num_vertices()):\n",
    "    fname_image = g.vp['image'][v]\n",
    "    g.vp['hover'][v] = '<center><strong>'+str(g.vp['username'][v])+'\\nTotal points: '+str(g.vp['total_points'][v])+'\\n</center></strong>'\n",
    "    g.vp['hover'][v]+='<br><center><img src='+fname_image+' style=\"margin:10px;max-height:150px;max-width:150px;\"></img>'\n",
    "    g.vp['hover'][v]+=badges[v]\n",
    "    g.vp['opacity'][v]=0.5\n",
    "    \n",
    "    #random online, offline color symboliser, offline = #ffb3ba/first\n",
    "    if g.vp['online_status'][v]=='Yes':\n",
    "        g.vp['color'][v]='#baffc9'\n",
    "    else:\n",
    "        g.vp['color'][v]='#ffb3ba'\n",
    "    \n",
    "g.gp['background_color'] = g.new_gp('string', val='#bae1ff')\n",
    "g.gp['opacity'] = g.new_gp('double', val=0.1)\n",
    "\n",
    "fig = gv.d3(g,\n",
    "#   graph_height=800, \n",
    "#   details_height=450,\n",
    "            show_details=False,\n",
    "show_details_toggle_button=False,\n",
    "#   zoom_factor=0.3,\n",
    "  use_node_size_normalization=True,\n",
    "  use_edge_size_normalization=True,\n",
    "  node_size_data_source='user_focus',\n",
    "  node_label_data_source='username',\n",
    "    edge_size_data_source='ew_focus_on_user',\n",
    "  edge_label_data_source='weight',\n",
    " show_node_label=False, \n",
    " node_hover_neighborhood=True,\n",
    " show_node_label_border=False,\n",
    "#  node_label_size_factor=0.55,\n",
    " use_many_body_force=True,\n",
    " edge_curvature=0.3,\n",
    "  show_edge_label=False,\n",
    "   show_edge_label_border=True,\n",
    "#     many_body_force_strength=- 150.0,\n",
    "        use_collision_force=True,\n",
    "  node_size_normalization_min=20,\n",
    "node_size_normalization_max=75,\n",
    "  edge_size_normalization_min=0.5,\n",
    "# edge_size_normalization_max=15,\n",
    "layout_algorithm_active=True,\n",
    "#             links_force_distance=450,\n",
    " )\n",
    "\n",
    "fig.export_html(fname)\n",
    "del fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "8f21c6b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now adjusting the HTML file for asset location, font, and []...\n"
     ]
    }
   ],
   "source": [
    "print(\"Now adjusting the HTML file for asset location, font, and []...\")\n",
    "\n",
    "# Open test.html for reading\n",
    "with open(fname) as html_file:\n",
    "    soup = BeautifulSoup(html_file.read(), features='html.parser')\n",
    "\n",
    "replaceString = 'assets/'\n",
    "new_text = str(soup).replace('\"Lucida Console\", Monaco, monospace','\"sans-serif\"')\n",
    "\n",
    "#may need this later for dependency changes\n",
    "# new_text = str(soup).replace(\"/assets/\", replaceString)\n",
    "# new_text = str(soup).replace(\"/code/assets/\", replaceString)\n",
    "\n",
    "new_text = new_text.replace('font-size: 8px','font-size: 15px')\n",
    "new_text = new_text.replace('font-size: 10px','font-size: 15px')\n",
    "new_text = new_text.replace('font-size: 9px','font-size: 15px')\n",
    "new_text = new_text.replace('font-size: 11px','font-size: 15px')\n",
    "\n",
    "new_text = BeautifulSoup(new_text).prettify()\n",
    "with open(fname, mode='w') as new_html_file:\n",
    "    new_html_file.write(new_text)"
   ]
  }
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