OSNA_Project_1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Twitter Network Analysis\n",
    "### Online Social Network Analysis: Project 1\n",
    "- Chandni Patel (A20455322)\n",
    "- Omkar Pawar (A20448804)\n",
    "\n",
    "A lot of people use Twitter as their primary source of sharing information. It is a good source to acquire knowledge about any domain that we wish. Most of the user profiles are public, so scraping data from  twitter is easy and has fewer restrictions. All the information on twitter is publicly available and can be accessed using Twitter API. \n",
    "\n",
    "### Notes to run the code below\n",
    "- Update the twitter api keys below for authentication. Put your own keys to make the api calls\n",
    "- Run each cell to get the output for lines of code. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import Essential Libraries\n",
    "import twitter\n",
    "import networkx as nx\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import math\n",
    "import itertools\n",
    "import time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create authentication for twitter developer account using twitter library for python \n",
    "api = twitter.Api(consumer_key='hQqVc0baZHhIvdZehOB44cTPZ',\n",
    "                  consumer_secret='W88veO7CCaKnewU9SP4sybEJJGNXVKRehDjvJgFCWjBkjJM22C',\n",
    "                  access_token_key='4199714533-2nDVh4hv3RqDfIgYxFpJ6EuvylGAHT7ueLBOh43',\n",
    "                  access_token_secret='diROtrKxoAdPP0DqcW7nxYsv2SjSZKaiSxBgr8XszgBj1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to get list of friends for the specified user.\n",
    "def get_friends_list(user_screen_name):\n",
    "    '''\n",
    "    Params\n",
    "    user_screen_name: Screen name of the person whose friends list needed\n",
    "\n",
    "    Return\n",
    "    List of friends of the user requested\n",
    "    '''\n",
    "    #Get data using twitter api. Returns list of (user_id,screen_name)\n",
    "    Friends = api.GetFriends(screen_name = user_screen_name)\n",
    "    \n",
    "    #Empty list for adding tuple with user screen_name and friends screen_name\n",
    "    list_of_friends = []\n",
    "\n",
    "    for i in Friends:\n",
    "        list_of_friends.append((user_screen_name,i.screen_name))\n",
    "    \n",
    "    return list_of_friends"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to get top 50 friends of specified user.\n",
    "# Top friends are those who have highest number of followers.\n",
    "def get_top_50_friends(screenname):\n",
    "    user_screen_name = get_friends_list(screenname)\n",
    "    \n",
    "    user_df = pd.DataFrame(user_screen_name)\n",
    "    user_df.columns = [\"Users\",\"Follows\"]\n",
    "    \n",
    "    list_of_user_friends = user_df.Follows.tolist()\n",
    "    \n",
    "    lookup_for_user_friends = []\n",
    "    number_of_users_per_request = 99\n",
    "\n",
    "    for i in range(math.ceil(len(list_of_user_friends)/100)):\n",
    "    \n",
    "        start = number_of_users_per_request*i\n",
    "        end = start+number_of_users_per_request\n",
    "        list_for_api = list_of_user_friends[start:end]\n",
    "\n",
    "        lookup_for_user_friends.append(api.UsersLookup(screen_name=list_for_api,return_json = True))\n",
    "    \n",
    "    lookup = (list(itertools.chain.from_iterable(lookup_for_user_friends)))\n",
    "\n",
    "    to_filter = []\n",
    "    for objects in lookup:\n",
    "        to_filter.append((screenname,objects[\"screen_name\"],objects[\"followers_count\"]))\n",
    "    \n",
    "    to_filter.sort(key = lambda x: x[2],reverse = True)\n",
    "    \n",
    "    return to_filter[:50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get TSeries Data\n",
    "Tseries = get_top_50_friends(\"TSeries\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TSeries', 'YouTube', 72174488),\n",
       " ('TSeries', 'Twitter', 58334378),\n",
       " ('TSeries', 'jimmyfallon', 51650350),\n",
       " ('TSeries', 'nytimes', 47358702),\n",
       " ('TSeries', 'SrBachchan', 44350729),\n",
       " ('TSeries', 'BeingSalmanKhan', 41546262),\n",
       " ('TSeries', 'iamsrk', 41112296),\n",
       " ('TSeries', 'akshaykumar', 39245581),\n",
       " ('TSeries', 'sachin_rt', 34041881),\n",
       " ('TSeries', 'iHrithik', 29714237),\n",
       " ('TSeries', 'deepikapadukone', 27722541),\n",
       " ('TSeries', 'priyankachopra', 26647764),\n",
       " ('TSeries', 'aamir_khan', 26430949),\n",
       " ('TSeries', 'arrahman', 23370767),\n",
       " ('TSeries', 'AnushkaSharma', 22047959),\n",
       " ('TSeries', 'aliaa08', 20701386),\n",
       " ('TSeries', 'AnupamPKher', 18001389),\n",
       " ('TSeries', 'karanjohar', 17257349),\n",
       " ('TSeries', 'juniorbachchan', 15370471),\n",
       " ('TSeries', 'shahidkapoor', 15293112),\n",
       " ('TSeries', 'Asli_Jacqueline', 14742923),\n",
       " ('TSeries', 'TwitterVideo', 14318165),\n",
       " ('TSeries', 'ParineetiChopra', 13824032),\n",
       " ('TSeries', 'RanveerOfficial', 13791866),\n",
       " ('TSeries', 'ajaydevgn', 13705536),\n",
       " ('TSeries', 'ShraddhaKapoor', 13494527),\n",
       " ('TSeries', 'VineCreators', 13287298),\n",
       " ('TSeries', 'sonamakapoor', 13177389),\n",
       " ('TSeries', 'timesofindia', 13156937),\n",
       " ('TSeries', 'TwitterMusic', 11840778),\n",
       " ('TSeries', 'Varun_dvn', 11737921),\n",
       " ('TSeries', 'SidMalhotra', 9725574),\n",
       " ('TSeries', 'billboard', 9540962),\n",
       " ('TSeries', 'thevirdas', 7836035),\n",
       " ('TSeries', 'shrutihaasan', 7743217),\n",
       " ('TSeries', 'AllIndiaBakchod', 7037191),\n",
       " ('TSeries', 'bipsluvurself', 6557930),\n",
       " ('TSeries', 'arjunk26', 6328171),\n",
       " ('TSeries', 'AnilKapoor', 6189459),\n",
       " ('TSeries', 'RanaDaggubati', 6124948),\n",
       " ('TSeries', 'kritisanon', 6019856),\n",
       " ('TSeries', 'WhoSunilGrover', 6010046),\n",
       " ('TSeries', 'ayushmannk', 5866008),\n",
       " ('TSeries', 'DishPatani', 5807630),\n",
       " ('TSeries', 'rajinikanth', 5785034),\n",
       " ('TSeries', 'bomanirani', 5514027),\n",
       " ('TSeries', 'asliyoyo', 5430679),\n",
       " ('TSeries', 'MumbaiPolice', 5080671),\n",
       " ('TSeries', 'iTIGERSHROFF', 4602001),\n",
       " ('TSeries', 'rampalarjun', 4518339)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Tseries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TSeries', 'YouTube'),\n",
       " ('TSeries', 'Twitter'),\n",
       " ('TSeries', 'jimmyfallon'),\n",
       " ('TSeries', 'nytimes'),\n",
       " ('TSeries', 'SrBachchan'),\n",
       " ('TSeries', 'BeingSalmanKhan'),\n",
       " ('TSeries', 'iamsrk'),\n",
       " ('TSeries', 'akshaykumar'),\n",
       " ('TSeries', 'sachin_rt'),\n",
       " ('TSeries', 'iHrithik'),\n",
       " ('TSeries', 'deepikapadukone'),\n",
       " ('TSeries', 'priyankachopra'),\n",
       " ('TSeries', 'aamir_khan'),\n",
       " ('TSeries', 'arrahman'),\n",
       " ('TSeries', 'AnushkaSharma'),\n",
       " ('TSeries', 'aliaa08'),\n",
       " ('TSeries', 'AnupamPKher'),\n",
       " ('TSeries', 'karanjohar'),\n",
       " ('TSeries', 'juniorbachchan'),\n",
       " ('TSeries', 'shahidkapoor'),\n",
       " ('TSeries', 'Asli_Jacqueline'),\n",
       " ('TSeries', 'TwitterVideo'),\n",
       " ('TSeries', 'ParineetiChopra'),\n",
       " ('TSeries', 'RanveerOfficial'),\n",
       " ('TSeries', 'ajaydevgn'),\n",
       " ('TSeries', 'ShraddhaKapoor'),\n",
       " ('TSeries', 'VineCreators'),\n",
       " ('TSeries', 'sonamakapoor'),\n",
       " ('TSeries', 'timesofindia'),\n",
       " ('TSeries', 'TwitterMusic'),\n",
       " ('TSeries', 'Varun_dvn'),\n",
       " ('TSeries', 'SidMalhotra'),\n",
       " ('TSeries', 'billboard'),\n",
       " ('TSeries', 'thevirdas'),\n",
       " ('TSeries', 'shrutihaasan'),\n",
       " ('TSeries', 'AllIndiaBakchod'),\n",
       " ('TSeries', 'bipsluvurself'),\n",
       " ('TSeries', 'arjunk26'),\n",
       " ('TSeries', 'AnilKapoor'),\n",
       " ('TSeries', 'RanaDaggubati'),\n",
       " ('TSeries', 'kritisanon'),\n",
       " ('TSeries', 'WhoSunilGrover'),\n",
       " ('TSeries', 'ayushmannk'),\n",
       " ('TSeries', 'DishPatani'),\n",
       " ('TSeries', 'rajinikanth'),\n",
       " ('TSeries', 'bomanirani'),\n",
       " ('TSeries', 'asliyoyo'),\n",
       " ('TSeries', 'MumbaiPolice'),\n",
       " ('TSeries', 'iTIGERSHROFF'),\n",
       " ('TSeries', 'rampalarjun')]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "to_filter = [i[0:2] for i in Tseries ]\n",
    "to_filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('TSeries', 'BeingSalmanKhan'),\n",
       " ('TSeries', 'iamsrk'),\n",
       " ('TSeries', 'akshaykumar'),\n",
       " ('TSeries', 'sachin_rt'),\n",
       " ('TSeries', 'iHrithik'),\n",
       " ('TSeries', 'deepikapadukone'),\n",
       " ('TSeries', 'priyankachopra'),\n",
       " ('TSeries', 'aamir_khan'),\n",
       " ('TSeries', 'arrahman'),\n",
       " ('TSeries', 'AnushkaSharma'),\n",
       " ('TSeries', 'aliaa08'),\n",
       " ('TSeries', 'AnupamPKher'),\n",
       " ('TSeries', 'karanjohar')]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Select group of celebrities that we wish to focus on\n",
    "focus = to_filter[5:18]\n",
    "focus"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Takes 20 mins to run\n",
    "# Added delay to the function because api calls for twitter are restricted for 15 calls per 15 minutes.\n",
    "new_list = []\n",
    "for people in focus:\n",
    "    new_list.append(get_top_50_friends(people[1]))\n",
    "    time.sleep(90)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = list(itertools.chain.from_iterable(new_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_data = [i[0:2] for i in data ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save data to a .csv file.\n",
    "with open('/Users/omkarpawar/Desktop/new_dataset.csv', 'w') as f:\n",
    "    f.write('\\n'.join('{}, {}'.format(x[0],x[1]) for x in save_data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize network in NetworkX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tjYeHB+np6WzZsoWEhAQ6dOhAREQER48ezd3grqmpiZ6eHikpKQWyh+9de9QKep/c31sSvoygB7xWKSrWAoX8JGZ8ajJg03mCI+IK/EKmoyllx4B61LT4OxjI5XIOHTqEj48PwcHBtG3blt69e9O8eXOys7PZunUrixcvJisrix9//JFevXphYGBARkYGq1evZvbs2TRo0IBBgwaxadMmgoODmTx5Mn369EEmk/H48WPc3Ny4ePEi3377LatWrUJbW5ubN2/Srl07mjZtyuXLl6lWrRoKhYLY2Fj27duHrq4uXl5ezJgxg2vXrlG1alXi4uKwtbWlVatWWFtbM3XqVJydnbl//z5bt27FyckJgAoVKhASEkJkZCQLFiz4z04OefE+szhLU31ux6eSlYdFtrysY4kGxW8m1gKFjyFmfGri2cQaHZlGgb6GRJHN08NrmTq8H5s2bcqtfJTJZLi6urJz506io6OpV68e48aNo2LFisyYMYPGjRtz6dIlVq5cyeHDh6lYsSKjRo0iLi6OYcOGER0djZOTE99++y3Z2dksXbqULVu24ODgwKFDhyhTpgyhoaF4e3uzdetWypcvz7lz56hcuTKhoaFER0djZGTEgwcPSE5OpkSJEnTu3JmsrCymTJnCV199RaNGjZDL5ZQuXRpPT08yMjL47bffSE1Nxd3dHX19/VdOcXl5ekt+7eF731lcxKOUPAU9+Huf3JWYdx8P9qkcdFDYMnKUePlfo+vKP8UpMUKeicCnJrXKGTPB1QZdzfz/Fbxs5DrN3YFrfi+2E+zevZuKFSvSrFkzFi9ezN27dwEoUaIEQ4cO5cKFCwQEBJCamkq9evVwdnbm9u3bbNy4kfPnzwNQp04d3N3dOXfuHCNHjiQ6OppatWoxePBgypUrx5AhQxg6dCht2rTh+vXreHp6Eh0dTZkyZahXrx7Dhg3D0NCQwMBArK2tiY2NRaFQEBcXh6amJt26dSMnJ4fjx4+TmZlJ+/btARg1ahRnzpzB3t6edevW0bFjRx48ePDKrO7lloa8pjrflMYcsOk80/cXbGoxU65gxfFb7xxbUT/oQJ0UKjh375k4b1TIM5HqVLP3LVqQSEBHpkHv+hW4k5jGscgEJPx9Ogb8nX5rWtWUIU2sX0lvAqSnp3P48GF8fX0JCAjA3NwcNzc33NzccHBwyC3/z87OJjAwEB8fH06cOEHHjh3p3bs3X331FZs2bWLJkiXo6Ojw008/0aNHD7Kzs1m8eDGLFy+mbdu2VKhQgZUrV9K5c2emTJmCqakp8+bN49dff8XMzIyDBw9StWpVli1bxowZM6hXrx7379+nZMmSGBkZsXXrVi5cuED9+vVZsmQJnp6eLF68mJ07d/LgwQNu3bqFo6MjkZGRxMXFYWhoSJcuXejWrRu3bt0i7nk6Nm16v7WysihUSGppSDgzrvl/VioWpYMOPhUv3ycvTxwShDcRga8IuBKTxIrjt/IUzP7ZyDU5MwcjHc1XGr++i0Kh4MyZM/j5+eHr60tWVlZuEHR2dkZTUxOAuLg4/vjjD3x8fEhPT6d379707NmTqKgoFi9ezIULF+jfvz9DhgxBT0+PRYsWsXz5ctq2bYumpia+vr6MGjWK4cOH8+jRI1q3bs3t27cZP348kydPJigoiF69elG/fn0iIiIwMzPDwsKCjRs3Mm3aNKZPn054eDiVKlXCxsaG4sWL8/PPP3Pv3j1WrlzJihUraN++PQMGDMC8Rj2CH0p5LDFBJpP9Z2VlpRL6bDhzr0hUSFYpZcC8LrXeWKWozm0vnzqxBii8jQh8RcjHBrMPpVKpiIiIyA2CN2/epE2bNri5udG6dWuMjIxQqVRcuHABHx8ftm/fjr29PT/88APVq1dn7dq1bNmyhdatWzNs2DCsra1ZsGABq1atonXr1jx9+pSIiAhmz57NN998w5QpU5gxYwZWVlYEBweTkpJC+/btsbS0JDIyEnNz89znrV+/PtHR0Tx69IitW7cyc+ZMNDU12bp1K/Xr16dXr14sXbqUzmMXESa1Rq4CJP+dPpbw4hiuokT3H2ei/nMf4MmbiTxJy373EwhvpKupwfYBTq9lPgRBBD7hNS+rLH19fTl9+jT169enY8eOdOjQAXNzczIzM/H398fHx4e//vqLLl260KVLF65evcqyZcsoXbo0w4YNw9nZmUWLFrFu3TqaN29OVFQUenp6LFy4EBMTE1q1asXDhw+ZO3cuPXv2xN3dnYyMDB48eICZmRn16tVjwYIFuWuEgYGBODg4kJyczIoVKxgyZAgSiYRpW48x2e8q8k94yVpbQ4JlKQNuJ6QBn+/m9MIkkUAr29Ks7FlH3UMRihgR+IS3SklJISgoCD8/v9yiFDc3Nzp27IitrS2xsbFs2rQJHx8fpFIpvXr1onTp0mzatImoqCgGDx5Mx44dWbduHevXr6devXqEhYXRsGFDZs6cyYoVK1i8eDE1a9bE39+fX3/9lZMnT5KUlESpUqVo1aoV3bt3p379+nh7e2NlZUX//v2pXLkyTk5OrNi+H7Oec8iSiz9j4XXaMil/jm0mTnwRXvHpfkQWCoWhoSFdu3Zl8+bNxMXFMWvWLOLi4nB1daVy5cosXLiQBg0acO3aNdatW8ft27cZNWoUurq6jBgxgujoaBo1asTz58/ZsWMHlpaWZGRk8OjRIxwdHdHQ0OD48eM8fvwYKysrGjduzIABA5BKpTx+/Bh/f3/27NmDl5cXI0aMoEKFClhaWnL16lWqVq2KYcPvxOxI+E8SYNfFGHUPQyhixIxP+CAqlYrLly/j5+eHn58fMTExtGvXDjc3Nxo2bEhQUBA+Pj6EhYXh5uaGjo4Ovr6+VK5cmR49enD+/Hl27dpFhQoViI2N5ddff+XKlSv8/vvv1K9fn0GDBjF06FBUKhUGBgb07duXQ4cOcfPmTXx9fWnXrh3V3H8kttTXn+1h1EL+KGOkg5OliTjvU8glAp+QL+7evYu/vz9+fn6cO3eOpk2b4ubmhr29PQEBAaxfvx59fX0cHByIiIggMTGRHj16cO/ePQICAihRogQymYyBAwcyc+ZM0tPTmTp1KgsWLCAjIwMtLS08PT1ZuHAhjo6OpJt/RUzp+kg0RC9l4f2I8z6Fl0TgE/Ld06dPCQwMxM/Pj+DgYGrUqEGHDh0wMzPj8OHD+Pn5UbNmTQDCwsJo27YtqampHD9+HG1tbapVq4a+vj5BQUE0adKEhIQE7t+/n7uGuHpXEOa95qGgYE+++aSpVC+qO4TXiL1+ggh8QoHKzMzk6NGj+Pn54e/vj4mJCW3atEFHR4fjx48TGRmJlZUVN2/exNbWFqlUyoULF5BIJNSvX58zZ86gUqmoUaMGV65cAaDSdzNJNqqERCqWqN9EQwISeQYKDR1UiOD3X8Revy+XCHxCoVEqlZw7dw5fX1/8/PxISkrC2dkZlUrFyZMn0dLSIicnB6lUirGxMdHR0ahUKsqVK8fNmzepWrUq9x4/wbTfKiQyLXV/O0XKyzY+/27nI7yd2Ov3ZRKBT1CbqKio3OKY8PBwatasiVwu58qVKxgbG/Ps2TNKlChBXFwcMpkMuVyOoWMn9Ot1F2t7/6ctVb2oapWKtO+H+BT3+hVks+MvhQh8QpEQHx9PQEAAvr6+HD9+HHNzc1JSUkhKSkKhUKCtrU1qaiqmXb3QqVRb3cMtMqSA2MzxcT6VvX4F3ez4SyICn1DkpKWlERwcjK+vL/7+/shkMpKTk1EqlZQeuA4NAxN1D1H4jOjIpIxwqcLAxlbqHsp/yuth9qJw5+1E4BOKlH+ncQy1NNDJekJKWDB7fX3R+mY+EpHWE/JZJ/uyLOpmr+5hvNGLoBdBRs77z+11ZBIaVzFFT0sm0qFvIAKfUCS8TxqnvIket+JTi9wh0586iTIHqVSGSiL5YgtjmtuUYt33ddU9jNeEPUjCY00oGTkf34xYpEP/JioEBLV7VxrnZZumm/GphTyyz5dUApYl9bEtY8jWlfM5u30pp++lMsU/nBzVl7cFwkhHU91DeKPlx2+RKf/4oAd/v48OXY/jRFQiE1xtaG1n9kUWyojAJ6jVh6RxhI+nVEGNssa4miRwQXGfSmYlqWRWkiVLlvCsYjPkKr6YPYA6Mik2ZobqHsZrElOzCIlKyPeekSoVZOQomOR/DS//a8g0pP/KsDxm0eGoz3pmKHYAC2oT9iCJGYE3RNBTk+TMHIKDg3FxcQEgJiaGW0Hr2dK3LloJN5BJVOjI/nWJ+AxXRlRAl68s1D2M1+y6ULCHaytVoFC93gIrU64kS67k0PU4PNaEsjn0boGOQx3EjE9Qm/xM4wh5Z6SjSXBwMMuXLwdg8+bNdOnSBUXCHeTHfuPMpXAmbzjAkfMRNGjWkqfxj7mcqALJ51Vc1LSqaZFM6914nKzWziMvZ4aT911j54UYShhofzapUBH4BLUoqDSO8H50ZFLKGki4c+cOjo6OqFQqNmzYwNq1a/H29uann37CRE+TI8t+YenSpTRoYIutbRdqD1vJpQTlZ1Vg9K1jBXUP4Y1inmWoewgAyJUQFvM899+fQypUpDoFtSjoNI7wdirA6Ml1mjRpgkwm49y5c8jlcsqVK0dwcDA//PADGzduxNzcHBcXF6ZOnUqjRo34xa02Knm2uoefb2QSuP44Wd3DeM3m0Ltcuv9M3cN4o88hFSpmfIJaqDuN8yWTSF6k984c2UHLli0B2LBhA7169WLFihX06tULLS0tJk+ezLZt2wgPD+f3338nPDycOXNmU+6ZDjGmjqg0imYlZF7IVXDjUYq6h/GKlwVfiiI+rX6ZCp0RGAHwSW2YFzM+QS2SM+XqHsIXS0emwWBnKw4dOoSLiwtZWVls376dzp07s27dOn788UdWrVpFrVq1cHJyYvDgwUydOpWrV6+yY8cO6hbPpOSDE2hrgEr56X94Sc7MUfcQcn2KBV8ZOUq8/K/h5R/Ok9QsdQ/nvYjAJ6iF4kvdKa1mmhIlE1xt0Ex5hKamJtbW1gQEBFCjRg1OnDhBw4YNMTU1ZdasWcyYMYP169eTk5NDly5d+OGHHxg0aBA7d+7EZ0IfMvfPxs5YgbZMilT5rw8y8my0NCS0rl4aB3P9Ih0gi9Ievk+14Euhgk2h96g/5ygDN58n7EGSuof0ViLwCWoRm1Q0Fu6LAokEZFIJsgLdNqdCJc+mRzVdejpVJDg4mJYtWyKRSNi4cSM9e/bE29ubESNGsHjxYpo1a4a5uTm//PILv/32G56enri4uLB06VLWr19P37596dOxBQHj3GjwJAjDeydob1cKM2UisgcX8XSuyJlxzXEv9ZTgeZ5I/h0Yi4iitIfvUy/4Uv5/a8SnsPYnAp9Q6BJTs7j3JE3dw1A7HZkUbZmUVral2TO4Pq1MU5Aq5QXWOD3nUSSDXewActOcCQkJhISEYGxsjJ6eHtWrV8fb25upU6cyZswYevTowbVr1wgPDyc8PJyRI0eyZs0arKysmDhxIiNHjuTahVCOrZhA+tGVcGIlZ5d4MrqdA8sXzqFNmzZ0aFiLSR3s0FAVvZlMUdrD97kUfP1z7a+oBj9R3CIUul0XYpBIJPBRRfEqVNmZSDS1QfKJfH5TqZCnJJIdd5sqFS1wKFea4R2csLIoDYDuw/N0NC5HesUGHAqPRSIBBfm1Z06CZtlqTDkSQ2b2PS5q16C5gQ1rN2+jffv2rF69muHDhzN37lw6d+7Mo0ePOHToEEFBQTRt2hQXFxfS0tJIS0vj3r17HDt2jEmTJnHs2DEOHDhA//79SUlJITg4GB0dHVq3bk1wcHDu7NHDozPlHN14bFafLIXyHbMaFRTCqTEvi3yKyn60z63gKyNHyST/awRHxFPPskSR2vv3iVwxhM9J/rzBJdhXNEXjE9pRpimFiU1Kk7B7Gu1Nn3Fr30ocbCtTp04dxowZw7Fjx6hvU5aVPeugd3gWHrYGdLIvS3ObUlQ3M0Im/bhgIJFocCA8jmNRiWhXbcTqP2NY9agc8VXduPowmUaNGrFmzRrGjh3L4MGDWbhwIUOGDKF169aEhobSrl07NmzYgK+vLwsWLGDPnj3s2bOHXr16IZFI2LdvH2lpaVhaWlmZffsAACAASURBVHLy5En+/PNPNDU1cXZ2Zvjw4RxbM5UdA+vRyrY02jLpa6fCSJRyZFIJ0oKa8v6LjkyDIU2sC+W13sfnWPClVEFIVALeh6OK1Pqf6M4gFLo+G85x9Eb8Rz9P3QrFScmSc+Nx4Zejq1Sq/89a348GChxlDxjV0QlHR0eePHmCsbEx2dnZnD17lqNHjzJjxgw0NDSoXr06165dY9++fTRs2BBtbW2Gb7+E7+XYAvpmlGhIVNikX6eaZiKmpqaEhITQqFEj9u7dy507d5gzZw7jxo3jyJEjHD58mBUrVuDn50ffvn2xtbVl1apVnD59mtatW1O2bFkOHTrE6NGjuX37Nlu3bsXGxuaVl/Q7eJThi7eSqW2CnnFJ6tWxp1ENS7p8ZcGB8EcFfn6rrqaUCa7VilQJfoH+jouIotIvUMz4hEJnpJM/GfaL95OIjCv8oKfMySQr6hTIs0H1jouzSom2hoQ2ZTKRRJ+mePHiSCQSnj9/cRKGlpYWDRs2xNPTEx0dHRISEnB2dqZixYqMHz+ekiVL4uLiwsWrEQX3DUmkKNAgXLMKJo5uzJs3j0GDBrFw4UJSU1MZNmwYv/76Kz4+Ppw+fZrFixezZcsWunXrRv369Vm7di0LFy6kWbNmuLq6sm7dOpo0aUL58uUJDQ19Jejdu3cPV1dXeri3J+XsXua623Fz3Ug2e7owsLEVJQy06epgRhPjZy9+vu+oBpVIQFdTg/Y1zdDV1Hjn+ujL+xe1oAdgU8YILY3P+2DworL+J9b4hEKXnp0/RQ6Kgji2/m1XTpUSlTyb9FOb0X5wlkdndlOs3jcY2tRDU0Mjt+0LgEqejUQiobxmCvf2ryY4PZ709PT/v4yK5ORXTwsJDw/Hzs4OfX197t+/z9ixY/n+++95/vw5J06cYO6JOJAVy9/v918kmtqsufAEjyFjGDt2LHZ2dpQoUYJt27YxZswYEhMTmTFjBhs3bsTDw4M+ffowbtw4OnbsSEBAALNnzyYlJQUPDw/WrVuHq6tr7nOnp6czbdo0vL29kUgk/Pzzz/zyyy/o6+vn3ic5OZnVq1fj7e2NnZ0dkwaN4q9UY45HJiCBV36+L3vLNa1qypAm1tS0MOZKTBIrjt/i2BvuryF5sXJYQl8LW/NipGYpeJKaVWTWnACaVNBhdnY2fAYHA7xLRo6SGYE3qGlhTE2Lwj/yTKQ6P3P/7mj+tkNm83LfDxX2IIluq8+8clEqCpTybHRyklHomqCQy0GmlXubjkyKUqVCfj+MxiUz2L/pN2xtbQkPD+f58+eotPSp1vYHHF06IdHW41n8Q8KOHyDm5C6ePrqPrq4u+/bto3Pnzujp6ZGSksK8efMYMWIEGhovileWLVvG1atXWb58OaVKleLatWuYmZnljmFlSDSLDkcVfPGDUklpeRyS02tJSkqiQoUKVKpUiSZNmvDzzz+zcuVKhgwZwvjx4+nWrRt169bl8ePHbNy4kUWLFqGnp8fGjRtzx65SqdixYweenp6kpaXh6urK4sWLsbD4u5IyLi6OJUuWsGrVKlxcXBgzZgwODg65tz9JzWLXxRhuPEohOTMHIx1NbMwM6fLVm/8uX97/TPQTrsU+50laNlKJBPk/9o4WtaasT548oWnTphRrN5oYTD7ZLQ15IZFAK9vSrOxZp/BfWwS+z9P7dDR/+aYH3vu+H3uBGLDpPMERcUXuja0phZjlvbGzs6NmxwEc/Cucr5wacuv6Fcz1VGydOYzncQ9p2LAhrq6uREVFMWrUKL799lvkcjlaWlpkZmbSrFkzlixZQoMGDUhKSuL333+nV69eAJQtW5agoCDs7e2pUKECcrmc3r1707t3b+bOnYudnR0ODg4MHTqUS5cuvTK+xNQs6s85SnYhfGBQybNJ2/ozbZo25NGjRwwePJghQ4awYMECRo4cyaJFi7C0tKR58+aYmpoyceJEfvnlF0aPHs3IkSORSl+soFy9epVevXpx48YNrKys+P3333F0dMx9ndu3bzN//ny2bduGh4cHI0eOxMrKKl++h3c1N36pKKw5PXv2jObNm9OyZUu6DR5Dl99OofjMOmD8F22ZlD/HNiv0mbcIfJ+hvLzpNSQSJBKQK1UFfoFITM2iwZyjRa5kW6VU4lBKyuy2VtSuXZsyZcowbdo0hg0bxrJly1i+fDlVqlRh9erVhISE4OHhgY2NDY6OjvTv3x97e3syMjJo2LAh165dIyUlhYoVK5KUlISVlRWhoaEANGvWjHHjxuHu7s60adNo1qwZPj4+/PHHH+Tk5DB06FDkcjkSiYRZs2a9Nk7nX//gntyowLdvqOTZWKVHEHtkI9OnT2fIkCF4eXkxZcoUfHx8iI6OZsSIEbi4uFC2bFlCQkLYunUrdevWBeDp06cMGzaMHTt2YGBgwNKlS+nevXtuMdClS5eYM2cOhw8fZuDAgfz000+ULv1iS0d+ZB0+pLmxuopdnj9/TosWLWjcuDGzZs2iX79+XEk3IrNa2yKXFSkIUglYltTHrmyxQm13JALfZ+LlBeNA+COuPnxOQZ0I9jEXiEJL1+WRlhQy98+ik3NtBg0ahJOTEzKZDG9vb8aMGcP48ePZuXNnbvBbs2YN8+fPJzMzkyVLlnDnzh0WLFhAsWLFSEhIoEGDBhw8eJDMzEzgRYPXsmXLMmTIEGxsbJg2bRp9+/Zl9uzZAGRmZmJiYkK9evUICQmhbdu2/Prrr9SpUyc3WERHR1OvrQfFu04hS17wb1n5rT+Z09GW4cOHM2LECLy9vdm5cyfLly9n9+7dDB48mMOHD/P111+zbNkyDA0NUSgULF68mIkTJ6JQKBg1ahQTJkxAV1cXlUrF8ePHmT17NuHh4fz8888MGDAAQ8MXp6bkJUPxtqxD2IMkPNaEkpGT93VkXU0Ntg9wKrQ1p+TkZFq1akXdunWZPXs23bp1Q6FQsGvXLvZciWd6YASZOQoKY09jUVCY6WdR1fmJC3uQxIBN52kw5ygLgyMJiym4oAd/L0pficn7XpyiuEFXW0PCpPbVuXzUn9jYWL755hs2b96MSqXC09OTMWPG4O3tTaNGjbh58yb9+/enf//+tG3bFnNzcwYMGEDbtm0pXbo0sbGxLFmyhPT0dMqXL4+x8Ys3boUKFRg9ejQVK1bkxo0b6Ovrk5CQkDuG+Ph4jI2N2bp1K/r6+tSuXRsPDw9q1aqFt7c38fHxeHp6MrrvN4xxsX5R7VjAqtrZM3z4cH744QeWLl3Kzp076d+/P35+fgwaNIjt27czceJENmzYgKGhIUeOHKFChQqMGzeOli1bcuFaFBYuPzDOLwLX2f7Y/DCLfgu2066zB7dv32bkyJG5QW9z6F081oQSHBFH1v9b3vxTXtrgfMxZl5lyBSuO3/qgx+ZVamoqbdu2xd7enilTptC6dWuMjIzw8/NDT0+PDrYmlI/ajXbCjS8k7BVuuyONyZMnTy6wZxcK1ObQuwzbfpmo+BTkSlWhtTFRqFQ8S8umXU3zPD1ux4UY7iQWjaPKJADybJKO/46l4iFNmzalR48e6OnpMXToUPr378/ly5c5c+YMHTt25MiRI9ja2nLr1q3ckn4/Pz+MjY35448/WLlyJRs3buTatWucOHECKysrAgICyM7OplixYpw8eZLjx48THx+Pnp4eurq6eHh4AHDq1Cnu3r2LgYEBWVlZrFixgh9//JHq1atz4MABBgwYQGxsLP369WPfhuXoSJWkG1rkf1XrP8RHnMWtdkX8/Pzw9vamW7duANSpU4e7d+9y4MABnJ2duX//Pm5ubsyePRtzc3MWb/IlrlwT5hy5y+mbcUQ8TiMhS4rCsAzaZatxNtmAiLhUyhfXo0wxnTynJeVKFWduP8FYV/O1mVliahaT/K+9UsSSVw+eZdDDsTx6WgVX8J6enk67du2oXLkyU6ZMwcXFBUdHR1avXo1MJiMiIoIWLVrwVTUr/JZ6cSsxjVvxReN9U1je9nvOD2LG9wlJTM1iZUg0w7dfoqV3CF7+18jIefs6XkFQqeBYZEKeW5Dk1/69jyWVQKvqpfHuUBFV1AmuXbuGra0te/fu5fvvv+fMmTMcP36cqlWrkpWVxcmTJzE1NeXOnTsYGRkRFRXF4MGD2bJlCwkJCUilUtatW4enpycPHz5k3bp1tGvXjitXriCRSHj69Cndu3enUaNG3L59m8jISMLDw8nJedEO5+rVq9jZ2REUFETr1q1fjFEqxdnZmSVLlmBsbMzAgQMZPnw4O3fuxN4ghfltLP7zBJSPXb1Q5WRhWVyb48ePM2jQILp160blypWRSqXUrVuXU6dOYW5uzk8//YS1tTVXrlxhw4YNjFu7H68Tzzh0/THZciVy1avj+vcn+tkHIj6oBc9/ZR3y46xLCbDrYsGdmZmRkYGbmxvly5dn/PjxNG7cmE6dOrFkyRKkUil79+6lcePGjB49mt9++w1tbW1qWRRHW/blXao/Jrv0Ll/eT/MT9M905qLDUfhejiUqLlWtjSo/5AKRL+1fPvairpBTOvES/atJ6NjIge+++47SpUuzfv16vLy8aNWqFXK5nJMnT9KiRQukUim3b9/G0NCQhw8fIpFIyMnJ4caNG4wcORI/Pz9iYmIIDAzEysoKAwMDxowZw5MnTyhTpgxubm5IJBJiYmK4fPkympqaGBkZcfv2bczNzVm/fj1Xr16levXqHDp0iFatWr0y3okTJ9K2bVu6du1KWloafn5+qFQq+nZswfXVP/NThXg8nSvmHm1m+OwmKD9yn6RUg4t7fqNYsWKMHz+er7/+mvj4eDZu3MjMmTPZsmULZcqUYdWqVYwaNYpHjx7xrKQdk/2v/L8g4+3JuZebmFefvP1Ba3Hw5rRkfqTSM+XKAmtMm5mZibu7O6ampvz88884OzszbNgwvLy8UCqVTJgwgWHDhrF//3769u2b+7gutS2QK4reAd+FoaDSzyLwFQH/nMn12XCO4dsvsTIkmiepWe9c/1CXD7lA3Hua/vEv/JELHlIJVNd6gpubGy4uLjRt2pTdu3dTvHhxLl68SNu2bWnUqBETJkxg9OjR+Pv7o6+vT2BgIG5ubvz111+Ym5vz5MkTrl+/zqxZs9i2bRsZGRmMGTMGLy+v3MIOgAEDBqCrq0taWhrHjh1DR0eH7OxsSpQoQYUKFRg8eDA7d+7k8uXLlCxZkgoVKuSO9fz58+zYsYMxY8bQtWtXVq5ciaurK/Pnz+fBgwf8/PPPBPntYlLX+qQeXk6/KnLam8STdefCR/W/k0ilFC9rxblz55BKpSQkJBAQEICJiQk2Njb07dsXZ2dnHjx4QN++fek90os5B2/m+UDtj1mLflPWITkjfxrKFkRj2uzsbLp27YqBgQGDBw+mZcuWzJkzh6FDh/L06VPatWvH6dOnOX/+/CtbPmJjY2nlXJ+UyNB3nmLzOfrQ7NK7iKpONXpXJVuOQomKj7tAFKTmNqVY933d97pvfm1l0NfSID1b8YFHU6uoopvBw+2TkUgk1K5dm9DQULKystDX1ycsLAyZTEZcXBzjxo0jODiYuXPn4urqiru7OydOnGDSpEmsWrUKe3t7Ll26RNmyZalRowb16tVj0qRJGBgY4OjoyN69ezlx4gQODg6UKlWK58+fk56ezvfff09UVBRhYWG0atWKDh06MHjwYDQ0NDAwMGD79u24uLigVCpxdHTkxx9/ZMeOHdja2jJ//vzXfqa7LsRw6XYcN27f407UdZLv3yAn4Q6mXb340M+1KqWSnDvnyTqyDE9PT+Li4vDx8SEnJwcLCwv8/PwAmDNnDkeOHKHagEXEqEwK/bhwLQ1obJyC7r3TXLp0iVulGqJTtdFHP28n+7Is6mafDyN8IScnh27duqFSqejXrx+9e/dmw4YNuLq6EhYWhru7Ox06dGDu3Lloar7IiqhUKmbPno2Xlxd6enrISltRrJPXF7O/7590ZFJGuFRhYOP82eMJYsanNu9TyaZQFd2gB3lLXeZXr7EPD3ogVSqY38eF8PBwlixZwvPnz3ny5Am1atUiOjqa8uXLs27dOoyNjfHx8WHnzp0sWLCADh064O3tjaenJ1OmTKFdu3YkJCRQsWJF7t69y8WLFzlz5gweHh6kp6eTmpqKjo4O3333HRKJhEGDBqFUKtmxYwc2NjYUK1YMAwMDmjdvzrhx4yhWrBgVK1ZEKpXSsWNH6tSpw6hRozA0NOT+/fukpKS8sq/v36nvg1HPuCc3QmrpRIkm31Gy04SPyghLpFK0KjqwKyAIiUTC+vXr0dXVpXfv3mhoaNC4cWOaN2+Ovb0958MjidcoqZYeGdkKCLufSMWKFV/0D+z/7UevheV3Y1q5XM63335LdnZ2bhf7vXv34urqytatW2nRogXTpk1j0aJFuUEvMjKSypUr8+uvv1KyZEmqVavGkR2/M6VjTXQ18/b9fQ7zmoJIP4vApwZ/V7IVfmFKfsnrBSK/tjJ86I9LU6Ii88wW7MyNkEgkNGvWDF9fX86dO0eVKlXQ1tbmyZMnLF++HEtLSxYuXIidnR1nz57l22+/xcXFBZVKxZQpU1i/fj0SiQQzMzOKFSvG/fv3+euvv0hKSsLOzo4///wTd3d37t69y6pVq+jXrx8aGhosWbIEGxsbkpOTycrK4ueff2bu3LkYGRkRHR3N+PHjmT9/PtHR0Xh7e/Po0SOWLl3K9u3bcy+K7/rApEADiUwLyUfmhGUyGT0mLGHWrFkMHTqUlStXEh4ejo6ODkOHDqVZs2bMmzePwXPXq/XiWrP214wcOZJmzZrRq1GVj36+/GxMq1Ao+P7770lOTqZly5aMGTOGw4cP4+TkxMiRI5kwYQKHDx+mR48eufcfPnw41atX5+nTpxgbGzNlyhROnz5NrVq1sFTGonvjAMizkbzrnaBUIiFvHUSKsvxOP4vAV8jCHiR9UCVbUZPXC4S6eo1JeNESSHbVn/g/d+Pu7o6/vz8ZGRkAVKpUiXnz5vHo0SPs7OyIjY1FW1ubP/74g0qVKjFlyhTc3d25fv06OTk5LFu2jC5duhAVFUVISAgNGjRAQ0ODx48fc/r0aUxNTSlWrBjbtm3Dzs6OUaNGUaxYMSpXrsyFCxewtrYmMTExt6Lz3r17ODo60rBhQwIDA1m+fDl2dnY4OTlx8+ZNkpOTGThwIJGRkXn7wPSRFzy5SkJJ61rMnj2bffv2sXjxYiZMmMD169eZPXs2u3fv5sqVK2TqlCBbjVVW/8w6lDTQxrmK6Qd/6/nZmFapVNKnTx/i4uL4+uuvWbx4MSdOnMDMzIyWLVsSHh7O+fPnqVWrFgBnz56lbNmyLFu2DAMDA9zc3Lhx4wb9+/cnPDyc9u3b0717d35s48DCtuUokfEQlTwbDV4tepEo5WhKoWm10sg0Pp/Le74Uxv3D5/OT+UR8zAbbouJDLhAFvZVB81/tXKQS0JBKaFLVlL2ejYnYt5qePXuiUCjw9vamTJkydOrUifXr15OYmIienh67d+8mJyeHOXPmULFiRRQKBb6+vlhbWzNlyhTGjRtHYGBgbpWnTCbj1KlTfPXVVwAkJSVx8uRJ7O3tkclk3LlzB6VSyeDBgxk7diwqlYrLly/z6NEjFAoFKpWK8PBwnjx5QteuXTl8+DBdunQhNDSUGzduMGjQIH788UeOHDlC3dZdmLQ3rFA/MCWlZ3P48GHWrFmTu5/x5TmcABYWFlSqWr3QxvNvb8o6eDaxRkf2Yetg+dWYVqlUMmDAAO7du4eNjQ179+7l1KlTPH36lDp16uDk5ERgYCAmJiZkZ2fTs2dP6tWrR2ZmJtbW1uzbtw8fHx9SUlLo2bMnLVu2pEWLFmzfvp39+/czuFtbOpZMYF5DbcwSLpITdYoyikRcrIsxrq0dob+04OtKJQqtoW9B09KQ5Gv6GUTgK1SJqVkcj4z/ZNObL0kUcvrVr/DuO/6DTRmjgtuLpFKRo1C+UsavVIFMAn9GP2H58VuEPUjim2++ISUlhaNHj3Lnzh3c3d0JCAjAysoKZ2dn9uzZg4eHB76+vuzevZvLly/j6uqKTCYjMDAQOzs7Fi1axKpVq5g2bRppaWk8ffo0d81OV1eXjIwMTp06hZOTE+np6Zibm7Nnzx4sLS2RSqUsW7Ys91zKzMxMrly5wrVr12jdujWZmZls3rwZV1dXzMzM2L59O0qlkvPnz1Ol448oCvnt2rxRPQIDA3F2ds5NmalUKi5evMiMGTNo06YNh/f7F+qY/ulNWYda5YyZ4GqT57WwF0fx2Xz0ZumXJ/5ERERgZmbGpUuXCAkJISgoCFdXVxYtWsTMmTPR0NDgwIEDmJqasmPHDvT09Bg/fjxXr17F2toaT09PHB0dqVKlChs2bCAoKIguXbrg5OTE9OnT2bt3L7+OHo6HfUlurB9P6NzvWdO3IQMaWXLr2mU27TtSZCrAP1a2QvXR25j+TVR1FpKwB0mM2hXGzfhUdQ/lo+hoSjF9cBLVzRPs2bOHUqVKvdfj1HlAtQTQ0dRgVAtLhretzcOHDzEyMsq9PTMzkyNHjuDn54efnx9Pnz6lR48eDB06lDp16pCZmcmWLVvw9vYmLi6OzMxMGjZsyLBhw5gwYQJhYWF8++237N+/HxMTE+LjX3SXr1KlCmFhYejr62NoaIiVlRUnzl6iVseB3E3KpnnrdhwPPoBe9jPObV+K95zpHD16lMePH3PhwgVycnKYOHEiew8cRr/7IlTSwqvo05FJ6ft1GYo/vkBISAhXrlzh7t27uX0EZTIZSqUSkwbfoP/1N6+0cSoM72ppo47uDCqVimHDhhEaGkqJEiWQSCT88ccfTJgwgSNHjrB3715sbW1JTU2lc+fOBAcHo6enR5MmTVi+fDlGRkbMnTuX1atX8/333+eegxobG8uQIUN4/vw5a9aswc7OjuHDh9OmTZvcGfjt27fZvHkzmzZtIj09Hd1WPyMvbfOOEX868vsQcRH4CsHLN+GHbtYtKl50rrahh2N5vLy82Lx5M35+ftSsWfO9Hq/ulkRSpRzJ5b380OjFJ+rixYu/dh+lUsm0adP47bffMDY2JjU1lQ4dOuDm5kaTJk04e/YsixYt4uDBg8hkMipXroy+vj6XL1+mbNmy6OrqEh8fz5MnT3ILYO7du4eslCU1u4/hscQEqVSCSvr3moVUJUdDQ5O0W2fJCQvg4JbVuenTqKgo3MYtI92qCRJZ4bVuUcmziVneG5kiE21tbVQqFZmZmZQqVQpDQ0OSkpJISUnBrk49Eur9hLKQy+w1ULB7cCPsy7/+O3zpbY1pJYoctLS1X2lk+zFUKhWjRo3K3atZqVIlZs6cSY8ePShZsiQbN26kWLFibNq0iQEDBqBQKDAxMWHNmjU0b96cJUuW5FYQvzy+LCsrix49ehAZGYm/vz9du3blp59+ws7ODnjRzmjnzp1s3LiRq1evYmFhQUxMDObm5igcvyPbvNZHfU9FTX4eIi4CXwH7kBYpRVHV0gbM61LrlT+6rVu38tNPP7F27Vrc3Nze+Rwfc3J+fpEocsgKnE3KvWuUKFECe3t7HBwccv9frlw5ABo2bEi/fv2oX78+fn5++Pr6EhERQatWrXBzc6NmzZps3ryZFStWoFKpUCqVFC9eHKVSiZmZGZGRkWRnZ6NSqShetwPa9boj0dBCIv3vFJxKqURTAyZ3qIFHHQsWLFjAvHnzqPvTMiIy8neN462USrJunyPlwEIMDAxIS0tDKpVSp04dateujYODAw4ODlSuXBkNDY2P/0CjVEAeZrM6Mik6EYGYp0ezefNmTExM3nr/fzey1deUsm3VAk5vWkDl8mZvfez7UKlUjB8/noCAAACcnZ3p1q0bHh4eDBo0iAkTJvDkyRNcXV25cOECWlpaDBs2jF9++YWtW7cyffp0nJycqFu3Lhs2bMDAwIAWLVpw5swZbt26haenJ/3796dkyZJkZ2dz4MABNm7cSFBQEObm5iQmJmJsbIyenh7R0dEvutpXc8Govgeqz6ibe342rhWBrwAVhQt9frGWPSXIqzsy2atFKmfPnsXd3Z2hQ4cyduzYd5ZPq/uDgARQPbhM9IZx3L59m0uXLnH58uXc/2dnZ2Nvb4+ZmRkBAQEcPHiQ2rVrI5PJePz4Mfv27cPPz48TJ07g5OSEq6srSqWS5cuXc+/ePaRSKQ0aNODy5ctIpVIUlvUxcu6NVFPnvceorSFB46o/Fhm3Wb16NVNDEjh6I77gfij/osrJovzN3TR3qMxXX32Fg4MDFhYW//m7/ai/c3k2jsbpXE43JluhfGuvwX+mJbvVLsu4cePYu3cvu3btyp0hv6/OnTvTrl07fvjhh7yP+V+8vLzYvn072dnZfPfdd5QqVSp328vLk3Z++eUXJBIJNWvWZP369Vy5coWJEydiaWlJ7dq12bZtG+XLl6d69eocPHiQ0qVLM2zYMDp37oxMJiM0NJRNmzaxdetWDAwMSE9PR0tLCz09PR48eICenh7Z2dm0atUKDw8PHBs3p/WKc5/NOt9L+dW4VgS+AqTu1F5+0kuKRv/8JjZs2ICtre0rt8XExNCxY0dsbW1ZvXo1Ojpvv8i/7/pLQVHJs6nz0JevqlehXLlyuf9ZWFiQlJSUGwhXr17N8+fPycrKonr16q/MDi0tLTl16hR+fn7s37+fihUrYm9vz549e3j+/DlaWlqUsqmLpMUIJJp5f5NqSlTsGtyAmhbG9FkTwrE7hXM6v5YUMs9s4YdG1nh5eb1Sxfk2H9r8tWtlGecO7uaq1AqZuc3/t2G8HmClEnCsZML4NtVeyTrs3LmTIUOGMHv27FfOt3zneDdvZufOnbmn0Hyo6dOn4+PjQ0ZGBqNGjeLq1aucP3/+f+ydd3RUZdfFf9Nn0gspEEJIIQVCCL0qBBSQjkFBBKUISBPEigKiiCK+yqsCilKN1la1xAAAIABJREFUggoRAelIUUILEAghIZCQRiC9l6n3fn/kzUiUlgbhW+y17spkJnPvc2dy73mec/bZm61btyKVSunbty9Xr15Fo9GwYsUKHB0dmTdvHkqlknbt2rFjxw78/Pxo1KgRf/zxB/369WPWrFl06dKFxMSKFe3atWspKangBoiiiIWFBZmZmahUKuRyOcOHD2fkyJGEhISgUv39vzY57DT7YzMfiLhAfaGuVFweBb56Qk6Jjm5LDlbMYv8fYHhwEwIKI3n33Xd5/fXXee2116qs/srKyhg3bhxpaWls3boVV1fXO+7v5vqLSRBrZSVTXUgEA03zztOjkZa0tDTzlp6ejq2tLc2aNcPd3R1HR0c2bdrEvHnzsLe3Jzs7m6SkJM6fP09cXBweHh4EBwcTFBSETCYjMTGRvXv3kpmZiVqtRtlnBmrvTndMb952jEATMZucrR9T3rw78rbD6rWOdvNq6klPDaGhoTg5OfH999+bffPuhpmbzrIj+sY9H3NwUGM6ezpUTIIMd1fkqawx/5PgcOnSJUJDQ+nSpQvLly9Ho9Hc9dj5+fl4eHhw48aNitRgDfDJJ5+wcuVKSktLmT9/PmFhYXh7e7N69Wo++OADPvvsM6RSKaNGjeK5557j448/Jicnh+DgYPbv309QUBCCIBAbG8ukSZOYNm0alpaW/PLLL3z77bfEx8ejUqnQ6XRoNBry8/NRKBTY2dmZU6mdOnWqMjnJzs5m3bp1/P7771y8UYLl0HerlW14GFAXknKPAl894P8Lg7MSN8+ykpOTmThxIiUlJaxfv56AgADz34miyAcffMDatWvZtm0bwcF3/+fMLdGx4Xgyyw8l3Fd5NovMC/z65jAsLCywsLDA0tISpVJJVlZWlWD466+/kpCQQLNmzUhLSyM7OxsXFxfc3NywtbVFKpVSXl5OTk4OKSkpWFpa4uXlRezVNGzHfomkNmxHkwHVnkVkZ+dgPea/tdvXXdDVy4G5N62mdDodM2bM4Pjx42zbtg1v7zvPsGuy4lPIJIiiSHWycSq5hPkDW/4r+JWUlDBp0iQuXbpEeHg4Xl5ed93Xk08+ydSpU3n66afvfQD/w7Jly/j000/RarW8/vrrfPXVV2YFmf79+5OTk0Pjxo1ZsmQJmzZt4sKFC7Ru3Zrjx48TGBhIVlYWcrmc2bNnM2LECA4fPsx3333HwYMHsbCwqGBmajQUFxcjlUrx8PBgzJgxPPvss/j7+5vTzteuXWPt2rXs3r2bmJgYSkpKsLa2JjAwkAEDBmDbYTArIq5XIfY87KiORvDt8Cjw1TH+vzA4b4ZcInJi7hM0sq6YOQqCwKpVq1iwYAFvvvkmc+bMQSb7ezVSmX5atWrVPd9U7ndauDzhFHbRP1FWVmbeKmfWlpaW5oBoYWHBxYsXCQwMxMPDA7VajSiKmEwmdDodWq2W0tJSioqKKCgoICcnB61Wi323Z9B0egZpDdKclRAMOkqP/0zBiS24jJiPsnl7qMHq8a4QRWQSgeEeIlOfDMTT0xOpVIooiqxcuZIPPviAjRs30qdPn1u+/b7XskWBIQF2vBfaqUqtRxRFli9fzocffmj2RLwTVqxYYa6dVQfLly9n0aJFGAwGRo8ezZYtW/j+++/ZsGEDGzduRC6X88orr5Cens7Bgwfx8/MjOjoaX19fkpKS6NKlC7NmzcLCwoLVq1ezefNmZDIZ5eXlKJVKtFotEomEwMBAxo0bx4gRI3BzcwMgMTGRtWvXsmfPHi5dukRZWRl2dnYEBQWZ2cfJyclERkZy+vRpTp8+TblbByx7jEWUybmjvYko1lrx537g0YqvgeFBEzfqBYKANvEkDrG/snbtWrp06WJ+KSkpiQkTJqDT6Vi3bh1+fn7m186cOcOwYcN4+eWXeeedd+5KernfN09N5gW+fK49Tz75pPk5k8lEeXk5ZWVllJaWmn8eOHCAr7/+mqVLl6LX66u8fqvHxcXFXHN/AoNb7RX+7fIv0yL3GFkmDSnew+u3X04UEAuuo89Kwkmhp2MjgY6t/TGZTLz//vvMmzePmTNn/uu7fBC1bFEwIUWkU1NL3hnWgTbuf9f9jh07xsiRI3nxxRd5//33q0zKbkZ6ejqtW7cmMzPTrIV6N6xatYp33nkHmUxG+/btyczMZM6cObz88suUlZXRtm1bWrZsye+//46HhwdXr17F3d2d69evM2bMGIYOHcoff/zB2rVrKS4uRq/XI5fLMRqNSCQSunbtyksvvcSQIUOws7MjJiaGdevWsX//fq5cuYJWq8XR0ZG2bdvy1FNP4e/vT1xcnDnIZWRkmFm3Li4uZreR01ezuKppgdStdcX3dxPbUyWvqKvaahRkFdet/U9d41GNr4Hh/xOD82ZoFDKm+ur45K1p5OTk8Pjjj/Ptt9/i6ekJVKz+Vq5cycKFC5k7dy6zZ88232iuX7/OsGHD8PHxYc2aNXetvdyviYNaLiWQFJqXJ/zL6udWEEWR/v37M2DAAGbNmnVPx5iwIbJOmJhlV06SHb4IAKvgp7DvPRGpsv5rNnKJiCiK2JalY4reyeUTB8ytGi+88ALt27cnKCgIq0aN6bH00ANjD4qCgFQ08WKQNQvH/L0izcrKYtSoUchkMjZu3IiTk9Mt39+5c2feeu9Dsiy9uJRRRJHWiI1ajr+rDc+0b1plRblmzRrmzJmDhYUFtra2dOjQgbS0NP788080Gg39+/fnjz/+wNnZmYyMDOzt7ZFIJEyaNAm5XM66detISkrCZDJVMH5NJlQqFX369GHy5Mn07duXCxcusH79eg4dOkRiYiJ6vR5nZ2czu9bR0ZHo6GgiIyNJSUmhdevW+Pr6YmdnhyiK3Lhxg5iYGFJSUvDx8aF169ZVNksHF8Kj0s2tHdZqOU00Iq0siolOvMbqZOtq+yreTzxidTYw/H9icFbiZrUEo9HIt99+y9tvv41Op2Ps2LF8+umn5ibwxMRExo8fj8lkYt26dfj6Vijll5eXM2HCBBITE/ntt99o0qTJHY95PxifKrmUFX3tmT31JWJiYu7pPXFxcTz++OPExsbe9iZ6M2b9dJZt5++d6HE7lFw4SO7Oz82/WwU/hX2fiXftCawriIKAaNJTcHAtxkuHMBgMiKKIRqNBr9dj0X4oNt1H3dfm+luO06jDIfkwH08cQL9+/ZBIJBiNRubPn8+PP/7I5s2b6dy5c5X3nE8rYNa3u0g1WKFQKP7lhykCvfycmNbTh6g/fmPGjBnY2tqi0+nMtkJGo5Hg4GCuXr2KlZUVRUVFyOVyWrVqRZcuXYiIiCAyMhJBEJBIKmqaVlZWDBo0iClTpmAymdi4cSNHjhwhOTkZk8mEq6srfn5+eHl5IQgCUVFRXL58GR8fH5o1a4aVlRU6nY709HRiY2NxcHD4V4Dz9/dHqazIDuTn55OUlMTVq1dJSkoiPj6euLg4kpOTycrKQqVSoVarK1aCPj3QdB/TIAkxj/r4GhgepBxX/UBENOppfOM4i8f3p3fv3ub0VllZGR988AH//e9/kUqlvPPOO7z55psolUoEQWD58uV88MEHzJs3j1deecVcK1q8eDGrVq3it99+o3379nc8+p0UN9RyKXqTUGMiTOXFs+K5ilRQVFSUuWn9bpg9ezZarZZvvvnmlq+Losjp06f54Ycf+Dk6F1X7p2vUylAJwaCj+NgmtFG/I4oi1tbWlJWV4dvlCTIdg1F4BCMC0vsgFyYxGbC4vAfthf1kZGRQVlaGVCrFaegbdWL+WhcQjTqMez7FWa5l3rx5DB8+HKlUyrZt25g0aRILFy5k6tSpSCSSvydYd2GTSiQgRyT3wLeo0iIRRRG1Wk1KSgq2traIoohUKjVPCHr06EFZWRknT57EaKxwJBFFkUaNGvH000/Tpk0bjh07RkREBGlpaYiiiLOzs5lFnJ2dzcWLF3Fzc8PV1RWVSkVJSQkpKSlotdp/BbjAwEDUajXJycnm4Hbx4kUuXbpEcnKyWRBdo9EgkUjQarUIgoCLiwseHh74+fnh7e1Ns2bN8PDwwMPDg0NpRpbsvfzA2o1uh0fKLQ0M3xxJZNmByw994BONeqQyGe1dVbw1OJjzh3bw+eefo1KpmDNnDiNHjjTPIrOzs5k9ezabN2/G2tqar776iueeew6JRMKVK1cYP348UqmUtWvX4uNToXgfHh7Oyy+/zMqVK3nmmWfuOp5/Km7YqBX4N7YmwNWGKT+cqVFa+eaL57nnnuOJJ5645/6v/Px8/P392bt3bxXG6qVLl9i0aRNhYWEUFRWh1+uxatQYReiSWjExRVGkPDGS8shwpPlpzJkzh8zMTH766ScEQWDSjFfx7PMc6/afI8ukqfcVoMRkoG3+Edo0taOoqIi1a9fS5pVvSNZb1etx7xUSwLYkmYR1b2FpaYmVlRULFixg9OjRpKSkEBoaSuvWrQmZvID/HEisVkpdNOgQzmzh2uFNSCQSLCwsEAQBURSRy+V4e3sTHx+PVqs1v6dJkyZ06tQJg8HA+fPnuX79OgCOjo5mLc+rV6/i4OBAo0aNkEgk5OXlkZOTQ4sWLczBrWXLljg7O6PT6UhMTCQ6Opq4uDiSkpLIyMigtLTUvGLT6XQoFIoqgc3X15fmzZubA1vlsW6H8vJyjsamsub4Nc7c0CIIIqZa+jvWFjIJvD+k1SOtzoaE2T9H8du56w96GLWAiExbRNn53XiKmdxIvoJGo2Hy5Mk8//zzREZG8tlnnxEfH8/MmTOZPHlylRTnxIkTiYiIwMPDgw0bNtC9e3dMJhNffvklixcv5r333mP69OlIpVKioqIYNmwYEyZMYMGCBTU2yqxpw/TNQrcbNmzg999/Z/Pmzfe8j2+++YaffvqJsLAwfv75ZzZu3EhaWhpOTk6kpqbi7u7O1atXMRgMOD39LhrvTrViYoqCAIKBvAOrKYvei5OTEzKZjE2bNvH444+zf/9+xo4dS6fRrxEt86kgLdQXM08UkKRHU7Trc0pLS9HpdDgOmoNVYO/6OV4NoJJL2fJCAL98v4bly5cjkUiQy+XMmzeP559/npfeWkSUfc8akYQEg5bcn+ehz0gAwNLSEr1eb/Z2BHBycsLJyYnc3FyysrKQSqXY2NigVCrJz8/H0tISW1tbjEYjOTk5ODk50aZNG3x8fGjUqBEymYysrCwuX75sDmwFBQXI5XIkEgkGgwFLS0ucnZ1p1qwZfn5+tGrVCk9PT3Ngq+y7FEWRkpIScnJyyM3NJTc31/z4Ts+ZTCYaNWqEo6Mj9q7umDw6kmPfCq1Mwx1ZofWILp4O/DS5a53t71HgqwPUFZHhQUFiMjDaJZOBXVuzd+9e1q9fj1wux87OjoSEBAYNGsTkyZOxsbHh888/Z+fOnYwdO5bZs2ebSS4nTpxg3LhxJCYm0rVrV9avX4+Xlxfx8fGMHz8epVLJ2rVr8fLyIiMjg2HDhuHh4cG6deuwsLCo0bhrq8B/48YNWrVqZe6puhtyc3PZvHkzr7/+OgCBgYGkpqZSXFyMTCajqKgIiUSCs7Mz7733HtbNA1lwJK9OyAKiQUfJ0e/JP7UduVxOaGgokydPZtSoUSxbtoyZM2cibeSJut9sZJa3F26uNUwGXE4ux8lajb29PdesA7hqGVCvPYbVwc2sP51OR3h4OB9//DGJiYnI5XLazFhBmmhPTW7goiBQfuUE+TuWmtOYgLkBvrS0FJlMhlKpxGAwIJfLsbKyMgdGHx8fXFxckEgklJWVkZeXR1ZWFvn5+YhihVu6IAhYW1vj4uJiDmytW7fG29sbBwcHVCoVxcXF9xzElEqleYVZGcwqf97usaWl5b8mpA+avNfbz4m14zrV2f4eBb46wMO84pNK4FlvuPHnL+zYsYPWrVvzzDPP0LhxY7Zv387WrVvx8PCgsLAQtVrNlClT6Nu3Lz/++COrV68mJCSE1157jS5duiCKIlu3bmXq1Knk5eXx7LPPsmLFCqytrVm2bBlLlizh/fffZ+rUqej1eiZNmkRcXBzbtm0z9ylVFzfXA7Xa8ioki0qCwp0U+IODg1m5ciXdunW75f5LS0vZvn07P/zwA0eOHKF58+ZkZWWRnZ2NUqnEx8eHvLw8SkpK0Gg0jB8/nuTkZPbt20d5eTnq1k9iFzIBZLUPDBKTnq+f8efs/q18/vnn5Obm4ubmhpOTE0qlktTUVMQuL6D2f7zWx7odpIKRQFLo7lBe4dKgNbE6uzlCA7L2vFWf19mzZ1nw0adc8Hy2VkFaMOpJXzEOdCVmwgqARCJBoVBgMBiwsbExT+bKy8spLS1Fr9cjlUqRSCRYW1vj6OiIi4sLrq6uNG7cGIW1A0m4kCeoKTWICOUlmPLS0F86Qt6NVPLy8rCysrqnIObg4ICVlRVqtRpBEKr0qlZ3u7lVp8S1LUKbYbWqW9cUdcXmrMSjwFcHeJhrfJ7WsHtOH9RqNTqdjn379vHLL7/w+++/ExwczJAhQ5BKpYSHh3PhwgVcXV25du0aAwcOZOzYsSQkJPDFF1/g6urKa6+9xrBhwwD48ssvmT9/Pkajkddff50FCxZw9epVxo0bh4WFBWvXrsXDw4NPPvmE5cuXs35TOAlCo7tSym+H3BIdQUMnYbB0ZlDoSGz/Vw8c0e7O73/77bdRKpV88MEH5ucMBgPbtm3j66+/JiIiAisrK4qLi1Eqlej1enr27ElWVhZ5eXkUFxdTWlqKk5MT2dnZyOVyVCoVTz75JM2bNycmJoaTeUqsH3sRUSqvXR1OFDEmn2FySwlbtmxBq9WSmpqKTlfRe2VpaYljj5HQZiiSevTua1RyFcmJ74mPj0etVuM4bC7lDj53FJi+n3DUXufpRln4+vrSsmVLvL29UavVFdfp/nh0pprf8gSDjoK/fqT41K9IJBJkMhmCICAIFde+VCpFo9GYxQ/UajVKpRJRFCktLaWgoICioiJsbGwqHBXcAzD69kHnUNGXJkr/zjxIRSMgwdmUg48uEU151j0FKq1Wi1qtriLCUFfbnsRSPj9y7b6qLEHd9e9V4lHgqwM8rKxOwahHF7mFwhPhdOzYkREjRvDUU0/RokULdDode/fu5eeff2bXrl106NCBkJAQCgoKzOSKSobb5MmTcXJyYvXq1WRlZTF79mzGjx+PTCZj7ty5rFy5EgsLC5YtW8aYMWNYtmwZS5curbBjGTiS+ZuOEp1tRKFQYBT/TrH8k1J+c5PyreDU1BO572OMnPLqPQfPw4cP8+abb7J161bWrFnDli1biIuLQxAEM9OtUmR49uzZtGzZkrfffpuzZ8+aZ/FyuRx3d3dGjBiBs7MzJ06cYM+ePbi5uVFUVIRKpaLzU89wUdqcQkv3Gtc1ATAZuPa/FcfIkSM5cOAAAwcOZNeuXWRmZiJ3dKfJSytrd4y7wJB8lsIdn2AwGDAajcidvXF5/uMGQ4H/ZwtIJRoNfg3LViG133/MQfJ3/RdRrOh1VCgUKJVKFAqFuRYHmBV+jEYjRqPRbFOlVqtRq9Vogvoi7/AMSBV3rgOLAlIE/Mti8Ravm49186aXqrhidCDXpEGPDJVUwEmup5WmCLXEaA7Oldftzb9X97Xzcl+SFc3u+0SnLhRbKvEo8NURXlx3iiOXsx/0MKoFpUzC/CAdh/f+zs6dOyksLEQikWBlZcVTTz1FaGgoISEhyOVydu/ezS+//MLu3bvp1KkTwcHBpKamsnPnThwdHcnNzaVfv3489thj/Pnnn/z5559MmjSJmTNnolKpmDRpEtu3b8fNzY0NGzbg7OzMs+9+RWmLfiBT3JVSfieX7PNpBaw4nMDe6LSKys1NqaxbBU9RFLl06RJ//fUX27dvZ+fOnebz7tatG/379+fKlSts2rSJkJAQnn32Wa5cucKKFSvIyMgw39gqaeivvvoq+/fvZ9u2bTRu3BiJREJaWhrDhw+nadOm7Nu3j+zsbDqPm0ek1hlTLdKCMtGE5OJu3h/Vg+nTp2NtbY1UKuWJJ56gpKSEvakmbB9/oV5XfAHqYnYtGGn+HARBYMOxq3yy7wraB6xaJBr1GM9upTzqd4xGoznwmEwmHIa/g4VP57vv5C7QJp6mZNenyGQyZDIZUqnU/PhWm1wuRy6Xmx9LpVLKmrSj0OuJavnlSQUD7jmncS25glQqRSqVUqpqRJpNS/LVjUEUEW6zYvQzJuMoKUEikZjf+8/tXl/TinK+zWxWq//jmqAuNDor8Sjw1REWbIvh+xMpD3oY9w5BQJd0mlZ5EXTv3p3u3bvj6urK8ePHCQ8P5+jRo0ilUvR6PQEBATzzzDMMGTIEb29vdu3axS+//MK+ffvo1KkT7u7uXLx4kdjYWNRqNSqVipEjR5Kfn89vv/3G4MGDee2117CwsGDMmDFERkYSMHgyhsDB1Uo7/ZOVCdUguAAyBFyuHyVux3f/+wgE5HI5lpaWTJkyhdatW7N8+XKioqLo168fVlZW7N69m2vXrpnrOQqFwiwptWXLFtasWUOzZs1o0qQJsbGxtG/fnsGDB3Pt2jW+//57goODefnll8nOzuajQ9ehee0v3Cd8bJjT1ZGePXvSuXNn9uzZg6WlJZ06dSJK0warOljV3A6iUU/+nz9giN5FixYtzP8jOp0Og0dnJO1HgFRxX5rrbwmTAc2+xRRlXyc/Px+DwYCjo2NF03e7Uci8a88M9JJkM7GVAn9/f3x9fe/ZvaIStSGK3NyOU1tyV23wIAQ7Hq34GiAeNoKLFFg53BNTdhJHjx4lIiKCs2fP0qJFC7p3707Xrl2xsbEhMjKSrVu3Eh8fj0wmQ6FQ0KtXL0aPHk23bt04fvw4v/zyCwcOHKBdu3bY2Nhw4sQJjEYj5eXldO/e3bzqadmyJa+99hoZehUL/8qHGqh9/PvCr6bEmVGH9vgmnmnryujRo2nRogWTJ09m7969uLq64uDgQFxcHEqlkuLiYgRBwM3Njfz8fIYOHYqDgwO//fYbFhYWNG/enKioKAoLC3nnnXdo0aIFW7Zs4dChQ4wdO5YJEybw119/sXTpUgICAtD0f5VzWbVnxVkVJlG253Ps7OyIjY3FZDIhCAJKVx8cn56H3OrOjuS1gWjUE1L0B0f/2MPVq1cZOHAgH374odndIjHfQNjZLI4mFmAUai40UMPREWhrYnobJWfPnmXPnj3ExMRQWFiIKIrYdH4a2x7P10o4XC4RaSNJQ55wmPj4eC5fvoyDgwN+fn74+/tX+enu7n5LP8PaBI1KAYYePo1q3c5TG9xvluejGl8DxcPW0qAoTCcj7DWzDmC7du0IDAxEKpUSFxdHREQEERERqNVqunfvTseOHVEoFERGRrJ//35yc3MRRZFmzZoxdOhQBg8eTHp6uvnG36pVK0RR5Ny5c6hUKhQKBd27dyc+Ph5953GYGreipj1BXbwcmNs/oMYXnloh5f3H7Pnxq4/Yv38/KpWKwsJCXFxcKCwsxNXVlaysLDp06EBiYiIajQaTyYQoirRt25bs7GxiYmIIDQ3lmWeeYerUqeh0OmxtbZkxYwbDhw9n48aNfPbZZ3To0IGnn36a6OhotmfbY2xaPafwW0F76U/ydi5jwIABnDx5kkaNGlHu1gF94CAkclW91fckEujUWMm1nxZSapLi2XsUx+NSkaos6dyuDf06B5rrqbklOl79OYqjCbnct+SnUUfOz/MoTYsDQK1W4+bmZpb3kmhsaDptXa1Ynf9kFwqCQFpaGpcuXSI+Pr7Kz4KCAnx9fasEQ9fmLZiyMwt9LQg2CpkEmURSI6shuVRCdx9HZFJptQlk/8T9FOV/xOpsoHjYanyt7AQ+HeyNyWTiwoULnD171rxZW1ubRXFdXFwoKysjNjaWiIgIbty4QZcuXWjdujWCIHDmzBkiIyPNwrsdO3Zk+PDhKJVK9u7dy5EjR/D29iYvL6+iPqa2wWXyt1XU4WsCR5mWXKOyRgX2yn6s0r3/xcLCAr1ejyAI9O7dmxMnTtCqVSuSk5O5fv06FhYW9O3bF4PBwKFDh2jXrh3jxo0jMDCQ9evXExYWRlBQEOfPn+fcuXOsX7+ezz//HAcHB0wmE9evX8dkMmFvb49H/5fIbdKllnR6AwV/hlF2ZhuiKNKhQweuiK7Y95lY7+LCGoWM9wb6sfNcGseSCyscBW46F9GgQyKVIs2Io/D4Zsqyr+E8+Vsktfyu7wWCXov+5E+0sSxi1KhRHD58mC1btlBWVlYxdo0GpVJJk5ELKbXzrpk5cDW1IouKirh8+XKVYBhtcKbcp0+tVp1SCXW2kq4ugeyfuB/aunWp0Wne56PAVzd4ctmRh8p41iLzAmUHvyEjIwMvLy8CAgLw9/fH398fa2triouLiYuLMwdDgHbt2uHv749KpaKgoICYmBjOnTtHQEAAvr6+lJeXExMTQ1JSElChYtGzZ088PDyIjo7m6NGjOPd8HqN/39r3AtXWO8xkYIh4iqcH9uXq1avMmjXL7B5R6ZLdtm1bjh07hsFgYNy4cYwePZrY2FiWL1/O2bNneemllxg3bhyRkZHMmDGDwsJC8+5dXV3p3LkzI0aMYODAgZw7d46J02djHPBerWXMtLs/xbI4jeTkZDRu/jiNWly/dkUAgoAh7QKyJn53F8gWBdQKOe8OCOCvhJz6rQWJAiq5lLn9/Sk88ztLliwhIyMDqOita926NTk5OQQFBdGsWTPWbz+E6/NLavT/VxdakQ21JPLPOmBOiY4tZ67dU3vR3bR1RaBtMzuiUgrQmaq/OqxLjc5KPAp8dYCcEh3dlvxRq/TFfYVRj+ncNnIjfkEul9OkSRPs7e1RKBRotVry8vJIT0/H0dGRli1b4ufnR5MmTRAEgfz8fC5fvkxUVBQlJSUEBQWZHRcyMzOJjo7GysoKLy8viouLuXr1Kvn5+chkMvz8/FA8/hL5ti0e8AdQcUE+7lDC759VPipvAAAgAElEQVTOMjcZG41GAgMDcXR05Ny5c4SGhjJu3DgCAgJYv349K1euxMbGhk6dOnH9+nVOnTpFVlZFetvS0hKdTsfy5csZOXIkKSkpREdHc+rUKbZu3cqNGzdQKpVYD3gNTYsuNU5HiqKIJP08qlPfM3nyZL48Ww5N2zw4MskdoJTChB5ebDieUqOUtGDUo7sWh6ppABJRrBKs5AiYBIG2Lkrit35JXMReRFFEJpNhb2/PgAEDOHbsGG5ubsyfP585c+YQHR1NmzZtyLTxRdX5uWpNFuqqPtbQSyIquRTPRpYk5ZQC3NGx4p+rw9tp61b20taFzGBd4VHgqwM8bA3sMgT6646SkZJAQkICKSkplJeXmzUFTSaTWYvRwcEBW1tbFAoF5eXlZGdXpHMDAgLw8vIy6xVW6gtmZmbiE9gWmXc3ytWOlBkEDKVFWBkL0cf/ibbNCNTedUNJri1KYw7ikrSXvLw8TCYTWVlZ9OrVi4kTJzJ8+HASEir8+sLDw7Gzs6OsrIyioiJkMhlWVlaUlZXRp08fQkNDyc7O5ueffyYhIQGDwUCjRo2AislApYWPWq1G7+CN87Pv12q1KkMg9asXGDp0KJFNhjYYubBbQWIyMKGHFxtPp1dTFFqLb1ksrw5qT8t2ndh7uZBLN4pJz87j6MF9uGoEzm9dhVBeZG4p6Nu3L507d2bz5s1oNBoWL16MpaUlISEh6PV6pk6dyubNm+nevTvpGk8ym/QA2Z0ZqHXNiGyoK77qoDafyYNkolbZ/6PAV3s8TP/Mt8uXFxcXk5KSQkpKCsnJyaSkpJCQkMCVK1dIS0ujtLQUCwsL5HI5Op2O8vJys5qDTCajvLwcvVVjnHo9D00CkSAiSm+q7Rj1FQfXFoNl/bEOqwNZRiypP7yDo6Mj06dPZ+/evbz44oscPHiQnTt3UlJSYm44btGiBV5eXqSlpRETE4ODgwPFxcVIpVLs7OyQSCQUFRVRUFBA06ZNMRgMAMyYMYPevXuzfv36Cvm3/hMpaPY4xloUaUSDDmnsbgoKCrHp/lyDDnyiIKBNPElXT3suyFtgEiR3bNaubDvJ3reKd559jLfeeguocMZYvHgxq1evNqeUFQoFMpmMN954Az8/P7744gt0Oh0ffvghAwcO5I033uDzzyvYr0uXLmXevHlMnjyZzZs34+HhgcbNj8vy5phcAm6boruT3F1N8PWhK3y2P76KUMPDipquxu4lNVrXn/s/8Sjw1QEaevriZtQ0X15WVkZqaqo5KCYmJhIXF0diYiLp6eng08OsSXnHtJsgIEok9aoscq9QpkcxN8SNK1eusHPnTmJiYhAEAalUiouLC97eFeSfK1eukJubC1QwBY1GI1ZWVgQEBBAUFGRm7Hl7e7No0SJ+/PFH3nrrLYYOHcqZM2f46KOPcHBwQCaTURwYirFp21qPfWDLRuzatRuxDvoC6xuV+pZyW2dsuz6LxrtDhU/jTc3WEqFCuae3vzPTevmwacUnLF26lLFjx3L48GFSUip6ZG1tbc36kwsWLODzzz+ndevWZGdn88EHHzBixAiKioro1KkTV65c4YknnuDll19m2rRp/Oc//2HOnDksWrSIZcuW4eLiwsyZM+n91BC2nL3G/shYLiWmkH09lfkzJ/BcZ886YxEajUZ++uknFi39L7r+80F2d1H0hwG1qb/dLTVan3gU+OoAD8uKTxRMiJE/oUk/g5WVFVZWVmbNQDs7OxwcHHB0dMTJyQkHBwdsbGywsbHB2toaGxsbrKysbuli8MOJZD7cFffAVTuqBaOeoohN5B/fjEwmw2QymUWGK0kuOp0OlUqF0WikU6dODBo0iCZNmqDRaCgpKSEzM5OMjAwyMzO5cuWKOXAajUbzZ5aZmUmnTp3o1q0bO3bswGrA62QrXWs9/PLESBBFND51p1hfXxANOkpO/ILs8kFycnIY+eJLPPbC61zJKqNIa8BKKSXuxB9c+3MLv/38A+np6cydO5eTJ08CoFKpaNq0Kbm5uYwePZqpU6eyZMkSjhw5Qm5uLqNGjeLbb79FLpezb98+Bg0ahNFoZMWKFbi4uDB16lQ2bdrExIkT+eijj1i4cCGzZs3iww8/JCUlBYWiIjPx119/MXfuXLRaLV9++eVthcurA6PRyI8//sjixYtxcXHhvffe45cbdjUn/IhCBbGrHpV5qoP6YFzeD/z/mHY8YPi72qCSZzT4Gp+0JAvLrGj0okh+fj6ZmZkYDAaz5mLlz8qetUqpIsCs1VepXqJUKtFoNKib+CF9ck79swrrGCJQeG6v+XcXFxdcXFy4dOmS2W4oLy8Pa2tr9Ho9J0+eJD4+Hnt7e6ytrbG0tESj0SCVSomPj+fGjRsEBQXRuHFjMjMzOXXqFHq9HmdnZ+Li4jh16hQGg4HGLRNQ+tY+8KkkJjy9PHkYtIIkChUDnpvIlbBkrKys+O2nMHaG/8S6desIfTEUgEttLRkT8Qt+fn4AyOVy/Pz8SEtLo6ysjOHDh7NgwQKSk5OZP38+J0+epKioiGXLlrFyZYU26cSJE1m7di22trZERkZy/vx5pk2bxs6dO3n33XcZMWIE6enp+Pj4EBMTw+TJk81BD8DBwYG8vDxCQkI4efJkrQKfwWAgLCyMxYsX4+7uzqpVq+jVqxcSiQSntAL+upJTI8KPUi5FRIKhgRDpRBEOxWeTW6Kr91VaXeJR4KsDjGjflGUHLj/oYdwVLRppeHzUKLRaLTqd7rY/K2t4lZtWq63yWmWw1Gq1ODzeC7VU/oD9masHURAoS4xEKC8yCwabTCbS0tIwGo1ERkaiUqkQBIHc3Fysra1xc3Mzr4ArV8G5ublERETg5+fH+PHjcXV1JSUlhYiICFq0aEGrVq34z3/+g42NDXK5nMaNG/Pu9PF8eSixVpMktVxKVlo8lm72yNXOD0W9SGllx7Fjx9i0aRNvvvkmcrmcESNG4OrqilarNaurNG7cmOzsbBQKBcHBwXzzzTe89957fPHFF8TGxnL69GneeustNm7cyBdffMG+ffsoLS01v693797s3r2brVu3MmvWLPbu3cvmzZvR6/XMmjWL4OBg9u3bxxNPPEFMTEyVMVYGvs6dO7Nr164anader2fDhg189NFHeHl5sXbtWnr27Fnlb9q42/HuAP8aMxx/OJnKpYziGo2vPmAwCXx58ArvDwl80EO5ZzwKfHWARlYqevo63XftuuqiW4c2zBv8fJ3sy2QycT2vmD5fHHt42jj+BykmBnur8P/kE2xtbUlLS2P79u1kZ2czbNgwsrOzCQ8Px9raGpXq30ooqampzJgxgxs3brBnzx569OiBXq9nwYIFhIWFsWnTJjp06EBAQABFRUV4eXlx/vx5vL29GdnJgy8PJdZq/AaTQFPjNc6Er8Ri1GcgbfiXsY1agVQqZdiwYZSUlDB37lwAc89dpQN5WloaM2fOZO/evajVaho3boyXlxcRERHs37+f6Oho/P39AXjllVdo0qQJRUVFiKLIF198wSuvvMKmTZuYM2cO+/btIzk5me+//57Tp0/z9ttvM378eI4fP06fPn3MbTiVsLe3Jy8vj06dOvHee+9V6/x0Oh3r16/n448/xtfXl7CwMHr06HHbv68khHy4Kw6dwYR4h6njzQxHwNxq0FAgiPDDiVQa26oBSY2txe4nGv4V85Bgei+fGqcv7hdScsvMjw0Gg3lFV1ZWVmWFd6fnb34uXtoMg3WrWt14K9On9wuiYCL/wGp+TTyKhYUFpaWlSCQSQkNDefHFF7G3t6d7n/78HJ1HQs61Khfw022bsHHtKhYvXsysWbPYsmULSqWShIQEnnvuOVxcXDh37hxOTk4AvP/++8yePZvNO/bw9eEEVD0n82Z4NA6WCm4U6mp6BpgEkU5PT2FwgB2Tw06j9u7UIPv4KiERjGRejqJXr9kcPXoUk8mESqWiV69eXLt2jcTERBISEsjKyuK3334jJCSExMRE+vXrR2BgINOmTSMtLY0ePXrQrVs3EhMTsbCwYOzYsRQWFiKTybC0tGTIkCH8+OOPvPHGG2Ypupdeeont27eTnJzMnj17iIuLo2vXrqxcufJf41Sr1SgUCpo0aUJBQQFZWVk4Ozvf8dy0Wi1r165lyZIltGzZkk2bNtG1652FsMvKyti9eze7wsPJOX0Jp55j0DdqgUwmqzKJ/CfDURRh1HcnGmRJxSSKLNkTj0wCN8+D1fIMlh24XGNlmPrCI3JLHeJ+atfVBKJRT/766ZTlVzBQNRqNebOwsKjye+VW2SMFmP24Kq1erro8RqG934M8pWrDAh2mG5coLDNg0hZjyE6h+Pw+hPIilK4tsO32LBqv9hU1zpsapqWCEUEUUWRf5tX+rXi+fw+sra0JCwszG+3OmDGjShCPSsnjmYWroXFLRFGoU0kxtVzKtG6Neefl53F45oMG44V3K4hGPddWjEMoL8Ld3Z2xY8dy8eJF/vrrL8aMGUOXLl34z3/+Q0JCAkVFRTRv3pzCwkLGjRuHWq3m+1+28uLClRRgyfbdBxD1pQh5aWQe30aPjsFcv36doKAgtFotUVFR7N+/n+bNm9OlSxemT5/O5MmT6datG1OmTMHT05Pp06cTExNzywmXu7s7ERERTJo0iRkzZjB48OBbnpNWq+W7777jk08+oU2bNixYsIDOnW9veVRUVMTOnTsJDw9n//79dOzYkdDQUIYPH46rq+tdGY4Gg4HnvznCqetaaqpx+yBR33151R7Po8BXt6hs0GyIKz+FFJ5yM9HFroTi4mLy8/PvuBUXF2NlZYW9vT329vbY2dmZH9vb23NS1ZZUk+2DPq17hiiKIJqQ3LRCrZxVu1nLSSnQ/W+2evsbiygIiCY9hYfWUhy1G4lEgp+fHwEBAfj4+ODu7o6bmxsXdQ6EXSxFbxTv6DVYGygkIs4xG4lOK6DRk5Or5e1WQe+p/xuoKAiIaVG84FUhcrBp0ybKy8t57LHH+PTTT+nQoYINmJ+fz4QJE9i2bZvZ2fyNj5eT7dyOg3EZGAyGKv2KgkGHQqHgiVaN8RdSWfrWdDIzM4mMjKRdu3Y8//zzKJVK1q1bR1hYGMuXL+fEiROMHDmSXr16MX369FuOt02bNmzYsIFff/0VQRD48MMPq7xeXl7OqlWrWLp0KR06dGDBggXmc/gn8vPz2b59O+Hh4Rw+fJgePXowYsQIhgwZYhY4uB0yMjI4fvw4J06c4Pjx40TFJeA4fmWtNW4fNOpLiaW6eBT46gHR1wqYuCGS7BL9gx7Kv2CVE0tAwakqAex2m61tRVDLyMggNTWVtLQ00tLSzI8v2nRA17jNAz6jBwPBoKXw0FpKz+9FLpeb2xiUSiXWbQdg0X1M7fVI7wZRwDI/kfg1r6MJ6otD75fuSYlEKpgwFdwA+6b1Oz4qVso+KTuI3BvOwIEDmTZtGu7u7qxevZrvvvsOHx8fmjZtyv79+xk0aBCvv/46P//8M1/tPod1zxeRypR3bniXVMiXZe/7lqbaJGbOnIlWq2XDhg1ERERgNBrx9/fn119/pWnTprRu3Zrk5GRsbGxuub+QkBDmz59PeXk5y5Yt48CBAwCUlpayatUqPv30U7p06cL8+fNp1+7fThuV6drw8HBzLTE0NJRBgwZhZ3frNJ9er+fcuXPmIHf8+HGKioro0qULXbt2pUuXLlwUmvD10dQGmeasLupDe7O6eFTjqwcENbWju0+jBtnb17lHL9a8+AZQsQLKy8szB7PLly9XCWxpaWlcv34dR0dH3N3dcXd3p1mzZnh4ePDYY48RpXVk86Xyh47cUheQKtQ0GTiT78K+QV2WSWJiIvHx8Ry/fJ24xv3uT3uHREqJjQcStTUlUbshN5WgUa+TKWmETCZFZ/z7e5FLBEyCSL9WTZjWy4fFYbs4UVi/9VVBryX30BrSL/6BlZUVlpaWFBYW0q5dO+bOnYuNjQ2LFi3i0qVLSCQSPDw8sLOzw3fABJzF2Crjvx1EEQxIceo7hfyIH/j4448pLy/nxIkTaDQa3n77bZ544gk6d+7MwoULee65524b9OBvZmfPnj2JjIykqKiIVatW8dlnn9G9e3d2795NcHBVM9Tr16/z66+/Eh4ebjYxnjhxIuHh4VhZWf3rGOnp6VWC3Llz5/Dx8aFr167069ePhQsXmk1+RVEkLS2N78IvoDNW/ztoiNAaTaw8nPBAe/8eBb56QkPt7bsYFcmTP7xjDmwKhYJmzZpVCWxPPfWU+Tk3NzdUqluvXNqkZvBz3Jn7fAYNB1qjiR/OZvLNmA7mdNfksNNcuo/sXlEUadHvBRJ2fE1Hb2fa6M8zb9ESc70op6iUY0f+wNNBhf7Sn3yzZCfn0wqILndAIqlBOr7yxO4QMEVBQCqaCLHLQ9GuCftzXUlLS2P16tWEhYWh1+tRKCoczLdu3UpISAgXL15k5cqVtOk9BJthCxCqSZgyiBKUnUdxIyGKN1+Zxt5Ugcg//mRvqhUD+05hxcHLfLthI/t/33rH/VQGPrVajVwux9PTkz59+rB//35at25t/rvk5GRzsIuNjWXQoEHMnj2bvn37mgUQoILtefbsWXOgO3HiBGVlZeaV3KJFi+jYsSNWVlZcu3aN2NhYs4pQVFQU8fHxyOVy7IbMReoeVK3PpKGiIfT+PUp11hNySnR0/+Rggwp8Mkz0dCjh2dYO5sBmbW191/eJokhqaipRUVGcO3eOqKgos/N4k5ELKXfwqZEvnkQC1nKRQp3YoFmJd8LNBpkP7DtPOkXGb5/g5OTEtWvXsLa2pnnz5ri5uZn7D9euXQvAkSNHWHa6lCOJ+TUKzqIgYCrNQ6axQSaTIkj+DlCCQYdEIqGVvciSF3qbU1k5JTp+jEjgp71/kZyeibG8BH3WVXRxRzCVFeLl5cULL7zA8OHD+c/JIg5ezqFG9UdRwFiaj8LCFqVSWeV7kEtEjCYT/Vq73ZFd+Oqrr3Lx4kXOnTuHRqNh0qRJzJs3D4DLly8THh5OeHg4KSkpDB06lNDQUPr06YNSqTSvzm5ezV24cAE/P78qaUuNRkNsbCwXL140X0uJiYlIpVIsLS0xmUwUFRVhZ2dHQEAAgYGBJDo/xiXt3a/VhwVKmYTX+vrVmaN6dfEo8NUjJoedblC9fffiYmw0GomPjzdfkOfOnTO7qLdt25a2bduaveo8PT25kF7EyG+P18gNWiaaMB4PQ95tbL2bqNYX1HIprz7py5THvR+YS0d5wilyfv2wispO06ZNsbOzw9LSErVaTWlpKZGRkbh5+yMb/lHtPAGNej7v68SW4/Ecj01FYWmLv1czshPOYZUdw/mTERw8eBDBzp0Vh65w8FImRoOhSvpXKZNgNJng+kVuHFiH7sYV5Fb2NJ6yunai23fxabwdu7CgoICvvvqKJUuW4OHhQXh4OHv37uXYsWO0atWK8PBwsrOzGT58OKGhofTs2RODwcDZs2fNQe7EiRMYDAZzgPP19UWhUJCQkMCpU6eIjo4mKSkJiUSCSqUyC0E0a9aMwMBAgoKCzG7tvr6+VdKkD5sDzL0guKktv02/fa9jfeJR4KtHnE8rYNR3JxoEw/NWmnplZWVcuHDBHOSioqK4ePEibm5u5iBXGehcXFxuuV+9Xk+XMa9T6PUEJkk1gpdJj+v1COxzL5Isd0doMwzdQ1or9JHnMtAhlz9KmxJTanHfj28nFBFcEMGYZ4aRlJTE6tWrSUlJoXnz5mRnZ5Ofn09paSl6vR6bzk9j2+P5WjmAY9RT8NePPOakY9asWfTu3RupVEppaSmPP/44vr6+HM2QoO46ukJa6y7kFJVcSqinhMMRJ0izC6rd2O4RlezCgX62fPHFFyxfvpwBAwbQokULzpw5Q6tWrQgLCyMjI4Np06YRGhpKkyZNOHXqlDnIXbx4kZYtWxIUFISLiwsmk4nLly9z8eJFUlNTEUURhUKBTqcze1QGBwcTHBxsDnBNmzat0i6Ul5dHRkYGGRkZ3Lhxg4yMDNLT07mSlkGM18iHntV5M6QS+GBIqwfC8GyQga867r8NHQ2lt08ll/JGWxkFV6PNQS45OZmAgADzCq5t27YEBQXdU/oTKi7Ul156iZycHELf+i+Ld8eh05vuYjsjIhj0BGjjOLflK8aPH8/8+fOZ+cXPHMi1rZjtNwDnhurAjTw6lp/hqDSQHFXj+z8AwYRcJqVPS1em9fShpaslPXr0YPTo0cyaNcv8Z23btsWm/yukcOem7HtBWexhtIdWYTQazVJjzZo1w8HBgcPXTFg//mK1WK0quQRdZhI4Nq/12O4VMkwU/foBA7sGMnDgQE6ePElYWBilpaVMnjwZLy8v5syZQ79+/YiMjKyop7ZogUajobi4mMzMTG7cuIHJZEIqlSIIAq6urrRo0YJ27drRvn17/Pz88PDwoKSkxBzQrl27RlJSEikpKaSnp5OVlUVubi7FxcXIZDKzWpAgCOj1erPoud3gN8GtdY3KCg0VD4rh2aAC3/m0AlYcTuDI5Qqz0+q4/zZk3Kv5Yn1BFEX0V0/hm3mkSqoyICAApVJZ44nGZ599RlhYGEePHqWwsJCew1+gWf+XSBft/uWzpZJLMRgMiOkXaGFIIjHyEN9//z0ajYYpU6ZgYWGBR9vH2HsN1J7tUSgUD4UGJcCQIFeGuxbx/r4UknF6YOMQBQFEAUn+NaSGUkrysnFRG/EQMrDXyDly5AjGbi+h9Gxf62Ppk85w4+cKWS+ZTGYWN1A19sV59Ec1aqgXBROS++k6IAo00l4nY8si1Go1gYGBFBYWEhkZidFoxN7entzcXDQaDeXl5ZhMFZkbjUaDm5sb3t7etGjRAldXVwRBID8/38yEzsrKIi8vj+LiYgwGAwqFAolEgslkwmAwoFarqzik2NjYYGlpiUqlQiqVYjKZMJlM6HQ6ysrKKCwspMgzBGlg/wZh6VVXeFDuDg0m8DUUZ976wp3MF+8HhgU34b8jq/rA1WaisWPHDl5++WWOHz+OXC4nJCSEiRMn8uabb5KeU8hz735Blk5B+26PoRSNHN35M81MN0i8eI4nn3yS999/n08//ZRNmzYxevRowsLCKCgoYPr06by1YBHbY7K4dKOYG7kFJF+OI+16JiqvdogS2Z0bwgUBEfG+3UAFg46iiI3YpJ/Cov1Qyn16NyhjWNFYwaD0sdRzesNilK37ovStfV3FKicW8dh6cnNzadu2LRcuXCA/P58mIxdicPav0arkfsvXQcXnk7V6CkJZIVKpFJ1OZx6HhYVFRTBXqXB0dMRoNFJaWkpJSQk6na5KTVUmk6FQKFCpVCiVSrNJrlQqxWg0otfrzXJ/lpaW2NraYmdnh62t7b+2Wz0fkSll7bmCe2rxeNhwL9yDukaDCHw1SQc2FAWA6uJmaaKjCdn3rcm9j78za17827S0NhON6Oho+vTpw++//06zZs0ICQlh3LhxvP3222RkZDBs2DA8PT1Zs2YNP/zwA++++y6dOnUiKiqKVatWYTKZeOWVV+jcuTNXrlzhwoUL9OrVix9//BFX1wrLnri4OD766CN2797N2LFjeeyxxziTlM2B6zIyZY0qDGNvSqXJqGgg7+hmgdJYyrFMyX3ppas0WRW1xTTx8kP1zFJMNLxUVKXijDE1GkWzNrVqrldKYYinlKYl8bz77ruIoki/fv1o2qojO4y1S8Xd7+AnGHQUHv2R4lNb+eet8ObaW+UqTKFQoNFozB6Wlf6VlYIPdwti1tbWyGTVm5Q1JK5AfeBmgtj9wgPv4zufVvA/ia/qrYDKDQKLd10iqKndA1UAqC4crVTmL/h+/kPbqP8uildnoiGKUG4wsXhXHABPemoYMmQIX375JR4eHoSEhPDCCy/w9ttvEx0dzeDBg5kwYQKzZs1i/PjxnDt3DgcHB1QqFTt37mThwoXEx8cTEBDA1q1badq0KUePHqVjx44kJiby008/sWbNGhISEnB0dESn07Fx40aioqIICAjg+YAA9v/1C0b39vgH9+b4mfPYaOQENnVg5evj2aEtRm5lT6MJX9e7IJcoCJAeQ2MHa+Rye1KvxuN05VSDFI2WSKVIpGqUzYORyZXUikckkZD2Vzjf797OlClT+GHXX1g/NYddKcUgqd08+n5n8aQKFYpGzf8V9GQymTkAG41G5HI5SqUSiUSC0WgkNzeXvLw8M0vzn1ull+U/t4pzvPfnJRIJxq4TEBsH3rF2/jBDaxS4dOP+2iw9sMBXWVfacDy5xjf+coOJKT+cIaCxzUNJgKmpL1d1oZZL8W9cQVipzUTjw11xLDvxHS+++CK9e/cmJCSE559/nnfeeYcdO3YwYcIEli9fjqenJ+3bt8fFxYXc3FyWLl1Kfn4+Tz75JB06dCApKYnk5GRzs+9LL71EQkICcrkck8lEly5dmDp1KsHBwfj7++Pg4GAeh1arZdGiRZw4sYjz58+z/rtXKS0t5Y//1V/at29PZmYm3IhFdAuq1wAkQyDjzx+x0GqxtLSkZcuWWJdfId0UjETaQEWjZUpEKoJ2jT4bUURblIezpz8JCZ+zPTaPbape/Hm1oI5IFxLul45oJaRqy389V1nPq4ROV+GmcaegBRWrw8qt0rwZMKc9ZTKZeZNKpebn/o+98w6Pqt6+/md6eg8JkBAgCUloCR1BehUQQXovVxBFsdEUuBa4ckFFlKIXRBQRpTfBUAWkJBAgoYSQRnqd9GQy9Zz3j5iR0NMovr/1POdJmznnzEzO2d+999prlX9/54aFLaJ7wD826JWjUGt4rMd77IHv9r6SKIrVlrtKL9CSXqAFnl4LjAehvHxYm+QXERjeukyXcc2JWLTGqi00tHojln69ee21l+nZsyejR49mwYIFrFixgi+++IJ9+/Zx9uxZZs6ciZOTExqNhpEjRzJ//nx0Oh3FxcUcOnQIR0dHej6inlAAACAASURBVPToQfPmzZFIJKSlpVGnTh3mz5/P1KlTKyhf3A61Ws3cuXPR6XT4+/sjCAISiYQuXbqQkpJCfHw87dq1Y9KkSUSk5LPkXDFIa2kRZNQxzFfOyN0/MXz4cIqLizEYDOTmnsLNqg6F3r0wSR798rJUSJn8XEN2Xk4lq6iqlkWPBpNJgKpKZ0skyKydOCq4woFYjt7ILJvBrNE49XjTPkH7t79dOTvzTsjlcmxtbc3lSysrK3P5U6/Xo9frKSkpQaPRmE2bDQYDRqMRiUSCKIoYjUYMBgNSqRS5XI5CoUCpVCKTybCwsEClUmFpaYmFhYX5a0G99qRJJLUmdP604PaK1OPAYw18tc1uLCeMHI7M5FS0+pkhwIzv2JCWHg73Jb9IJWVmj1WBRFLm51WuLFK24KjiiUqklNg3pNeAlxgxYgRz585l7NixhIaGMmbMGEaNGkV2djZarZaioiIcHBzYuHEjtra2FBYW0qpVK3bt2oWXlxdHjx5lyZIlpKam8v777zNhwgSUyoo9OaPRSEhICPv372f79u0kJSUhCAKenp706NGDa9eukZCQQJs2bVi2bBmDBw/G39+fV199FZ1OR9Pe47lBQM32+kQBwajHKeEE+/Yd5rq3NwcOHGDjxo1s3LgRZ2dnss/twpiejmXncQjIHiwaTVmfaVavJozo2JjvzybU3Lne75hSKTIJyKWgq4pqGWXVlv0Rac/c6MmdEAw6DOqEv3/+K+jJ5XJEUTSXN0VRxGAwkJycTEJC2ePLszVRFDGZTNja2lKvXj18fHwqOHW4uLhgZ2eHhYWFeawhKyuL7Oxsc8k0Pz+f/Px8ioqKyMnJoaSkhNLSUpRdW2Dh+sQ7UrWK2ytSjwuPjdzyJObZnkUCzL18uews5Wy9kFwlJujtczI1of4gCiZk2dFYXdnJjcvnUSgU+Pn5ERsbi7W1NTY2NkyYMIENGzZgb29PVFQUbm5u/Pzzz3Tv3p0DBw6wZMkSCgoKWLBgAaNHj0Yu//vCTkpK4tChQxw8eJAjR46gVCrRaDT4+flRp04dToZewv25l2gY1BmZhQ3qtGSmvNyPgsvBLFk0n86dO/P+++9TJ6Ad/9l1gYsZepD+3a+5HySICEYjvm42JBcY7lp8KKVgEgRKYkLRhO1BkxKFh4cHAwcOZOvWrbz66qt07dqVGTNm4OPjg1qtJkOvxOTXG+smHVDIZOhve9sFgw6pVIq/vYBr1kWsdTkEjZnz2NQ5JNxul/R0Bq/yW1Ntkl1Eo560b6Zi0hQAmEcXbj92ObnF3d3dPF7g7e2No6MjUqkUjUZDbm4u2dnZFBUVmQk65X1BmUyGyWRCq9Xi6OiIh4cHDRs2xMPD466tfv36WFj8XSaf+uMFjkdl1drrfxrwj2V1PklW0tNggVETqAnm69tbL9eIY4QEEcFkxF3IobVFNlvXLgdg1KhRJCQkcPXqVXJzcxFF0exWvnv3brO32cKFCxk6dCgymYzS0lJOnjzJoUOH+P3338nMzMTNzY2MjAzq1auHl5cXcXFxaK3csGjzEgbXJigVigrBQTTokMrlGBIuM7ypLaExGaS5dXyoRU85ZBLo09QN25QQft/8LfsO/8GR2ELz4qMwJ5MzB7axYEwvBvXpztChQ4mOjkar1WJjY8OLL76ITqcjNDSUJUuW8Oeff3Lo0CG6d+/Orl27sHF2x9SgLY1adyE1K5fGHu7EXz5N+pndKASdOWPwHLEQsWG7h57v/0+QAKIo1MrQtgSQpl0ld98yNBoNoihiYWFBUVERUqkUT09PRFEkNTXV3POTyWTmXrSHhwf29vaUlpaSkpJCnTp1CAwMxMfHB1tbWzQajdlhPjU1FbVajVarNfcGy8uZ5bN7Op2OvLw87O3t8fT0xMPDg5wmg0hT1r591JOCBOjX7PHP8T2WHLo6faXq4mmwwKgJVKYXeL9Zx0JtzfiaiEiQyBRkSutwUOeITdALDPSz49dff0Umk5Gbm8vYsWNZu3Yt+/fvp0WLFtjY2LB48WIGDhxIVFQUX331lVkLMSAgAHt7e7O0k7u7O0ajkaKiIgICAnhuwly2RGkp1RmRSKR3ZUQShQoRkHm1ZneRCeo2RlIJaSeFXMrzPi6MGzcTfXoM/xo3kuDg4AquFJH9GzN48GDiIiM4d+4cy5cvZ/HixSgUCnbv3o1SqeS9997jvyvXYBHQnebTPuPI9Zu4vPgeAe52XNy5lotnt2MymVD/NevVxKs+arUatVpdJvllFHj8gmdPNwSDjtLkSCy9WiCR1eztykIh45fFrxLZrwFz585FJpORlZWFSqVCJpNRWFhIaWmpOdg999xzJCQkkJSUBJQ5NCgUCmxsbBAEgdLSUrKzs9FoNGg0GhITE8nPz6dFixYMGjSIwMBA/P39sbW1JTY2losXL3Ljxg3i4+PJyMigoKDALFtWVFREUlIStgY3aOEG8n+OVNntEClbdD5u1HrG9zS4FMgQ+LyLBV3at3qo8/HTjgcNwpcPnffwc+X17j53Zbk1lfHdBaMeXcgvZJzeTqtWrdiyZQtnzpxh6dKl1K1bl3feeQeTycThw4cJDg5GJpPRvXt3rKysCA8P58aNG/j6+qJWq9HpdIwcOZIRI0bQsWNHtpxPeiwl8vLKQLO6towcORKlUsnPP/9snuUCyM3NZdSoUUilUn799VfCwsIYMGAAfn5+lFi4UOL1PJaNy1RRbh9iFw06pDIZmrgwhGu/U5IUicFgwM3NDZ1OR0FBQdl8WM8Z2DTvWauv81mEXX4sWpcm6GvwHnJnNUSr1fL111+zbNkyZDIZBQUFeHp6kpGRQaNGjYiKikKhUCCKIl27diUoKIj09HR+//138vPzzVm7hYUFjo6OSCQScnNzad68OY0aNcLa2hqNRkNcXByRkZHUq1ePwMDACluDBg3Izs4mNjbWLBAfGZ9MWtvX/lEanXei/xPI+Go98D0VquKigKI4i4Krx1CmXCIowMcsFhsUFETjxo0r3OCeBdyrF+hf15bhre8/zlGbn4Vo0PFuoBRFURrLli3D3d2dZs2acfPmTa5cuUKXLl3o1asXFhYWHD9+nMOHD+Pl5WWWdCoPds8995z5swiJSWfCDxcxCLXfg7pdOqm0tJQ+ffrQqVMnli9fjk6nIy4ujpiYGG7evMlPP/1EXFwcdnZ25OXloWzaC6de/0LyELdwURCQCEaMF7aReWYHRmNZBu7u7k6bNm3IdWtDimPgYxFpfpbQ088VuUxaI04noiCAYOCDFwJ4tWfAXX9Xq9UMHjyYy5cv06lTJy5fvkz9+vW5desWKpUKX19fIiIisLe3p6ioiP79+9O7d29EUeTgwYMcP37czOA0Go1YW1vj5uaGlZUV6enpKJVKOnTogLe3NzY2NhQXFxMZGUlERATFxcW0bNmyQjBs3rw5b++MfKpcXmoa/8geX61lGVWAhVyKIIr42RlpUBRFypUzhIeHk5eXR8uWLSsEw2bNmt2XVv+sonazbxF9fBiS0+spLi7G09OT/v3707dvX+RyOdu2bWPr1q04ODiYad6jRo1ixIgRdOrUCalUil6v5/z58+zfv59du3ZR0HIUlj4dHtswuFImYXFbkYzEWK5cucKvv/5qZuKVM/QcHR1RqVTExcURERFB3S4jofXLldKmlCMwtZUD9TRxLFmyhJycHBQKBQsXL+PLeCfESpqw/tMxNKg+kzs1rBZPQCkr66s5atMoCt1Je283Nm7ceNfj1MU6Zq/ZwdWUXIzIyc9Ox8tOzvXfNlCan42vry+5ubm0a9eOxMREoqOjcXR0JC8vj0GDBjF8+HBcXV05efIke/fu5erVq6hUKrPWp62tLZ6enri6upKfn090dDQBAQF07NiRZs2aYW1tjVqt5sqVK0RERHDz5k08WnbG0P1NxMq4nzxDeBLKLbUe+PqtPMnNzOLaPESlIQFUCikL/yp15ObmEhERYfaeCw8PJyYmpoKNSFBQEIGBgbi6PjkR4ppAbXoESgQj73jn8PKAvpSUlLB582Z++OEHdDqdmdk2evRoRowYQefOnQGIiIhg37597N27l2vXriGVlolZy6wdqPfa9/AYg4Bo1GMdf4J6BdeRy+Xk5+dz8eJFLCws0Gq1Zko6lJXGNJauuI7+T5UEmeUIbH+tM4EeDuzYsYN58+aRk5OD3cDZyBq0euqUX54Ubr8pfvjTUX6IKEBSifdbKoEW9e0Z0KIuw1t7YNIU4O/vj7W1NevXr6d///5Axflik8lUUSDdVDZcXRoXhjLuBPVUBpydnTl37hw9evTAxcWFw4cPo9PpsLKyIicnhxdffJFRo0bRvn17zp49y6FDh/jtt9/KKgRKJUVFRZhMJuzt7fHx8cHLywuj0cjFixfRarV07NiRjh070rZtW9SCNYtO5SM8pezbmsDQoPp8OSrosR2vVgPf5pAEPtx3vXrySLUJox6P7FCeczXRpEkTmjRpgq+vL3Xr1kWv13Pjxo0KwTA8PBwbG5sKwfBZK5XWJsNWJZPQ3iqbiF+/4NatW1hYWCCKIqNHj2bkyJF06tSJ+Ph49u/fz86dO7l8+bJZ4cLDw8OsRv/ee++hbDmAtaeTHnuJ3BBzBsOp79DpdJSUlGBnZ0dRURE9evSgffv2eHl50bBhQ7y8vFh+Lp9jUdlVGy4WBJS5sUzs3wm1UUlBqYG8zFRCTh1HGdDj/8qdf6G8DLZ/xy+89tpruHcZiarDaHQmocpi9h9//DEnT54kLi6Oq1evsi8y95FIY6IgIEHEVaZFnZaAEiP1rSXEH/0Zd0cb+vTpQ1paGjt37sTd3R1RFMnOzuall15i1KhR9OrVyzyuc/jwYY4dO2YmxuTm5mIymXBwcKBFixY0bdoUmUxGeHg4cfV6oWrU9h+t3nKnlnBto9YC37MirKqQirxoGUd+fAQxMTFER0ej0Wjw8fExB8LyoOjj40NxcfFdwTA3N9dcKg0MDCQoKIjmzZs/VaXS262HItMLicsqrpUFiT76NKXHvzUPtDdu3JjffvuN7du3c+HCBbP6vb+/P3379kUikbB3714cHR157733GDZsGHK5/ImVyJtY6/jgeSe8vLzw8PBAoVBw6NAhJk2axIkTJ/D39wdqqGwsiogmQ0U3B6Me5HJEUVKr82vPAiQS6BvghsO17axevZqWLVty+PBhbhWYqkzwAigqKqJJkyZ07NgRfYMOxNsHVp08ZTSABOpJ8pFGHSE29BiTJ0+mQYMG/Pbbb5w5c6aM/FRSQmZmJkOHDmXUqFF0794dURQJCQnh8OHDHDp0iMjISNzc3MzsUJPJhFPdBtiO/+ofX/7+x2R8tVlSq1EIAnZFCTzPDRo0aECDBg1wdHTEaDSSl5fHrVu3iI6ONgdFmUxmDoblX93c3NBoNERHR5uD4c2bN+8qlQYFBT32UumDrIdqA962IhPr57B161ZCQkIoLCxEIpHg4+PDgAEDGDZsGB4eHqxbt45169bRuXNn3nvvPTp37lzhRv/EBndvheKffx4/P78K25EjR/jkk084d+4c7u7uTwdp6x8OC4WUBtE7CTm4jT59+vDLL79UUPfJKdbx7aFw1v6yh579BuFiZ/1Qglc51qxZw5ZDZ0jxG45EXgPZtSiAyUgnqwzss66wdetWevfuzZgxY4iPj2fTpk3k5OTg7+9PZmYmmZmZDBs2jJEjR9K1a1dkMhk5OTkcPXrUHAgFQcC2/VC0vr2fKqurmsY/psf3NIwwVAZyici0OonkpCWSlJREcnIySUlJZGZmUqdOHRo0aICnpyeenp44OTkhkUjQ6XTk5+eTkpJCTEwMsbGx2Nvbm4Nho0aNsLS0RKPRkJ6ezvXr1wkPD8fKyuquYOjt7V0rpdJHlogTy1Q8aiLDEE1G8o+tw60ohr59+zJ69Gjat2+PUqnkypUrfPnll+zdu9fsDu7u7k5MTIx5i4yM5Nq1a2T5DMDCr0u1z6cyUMokjG1hR1vrfG7evFlhKy4uxs7ODq1Wy4wZM4i0b094/tNPMRdNf81uSiSP1+S1mrCQS5FE7Cbt5FamTJnCihUr7nmNjBkzhmbNmrFw4cJK7V+v1+P3r88RPVpSk8o1EpMBU9h23ugfiFwuZ926dahUKt544w1atGjB9u3b+fnnn83iDPHx8WRlZTF8+HBGjRplJnqJosiNGzd4d1sEUTq7Gju/pxH/GFbntyfj+OLITQxPbXOvIu634jAajaSlpVUIhnd+r9VqzSoLLi4u5qFnjUZDTk4OqampJCUl4e7ubu4fKpVKtFotWVlZxMTEoFar72KVVrdUWhWll5ryQrO4jTgkiiL79+9n6dKlREVF0a5dO6ysrIiNjSUxMbFMj/CvVbxer0cQBORyOVZtBmPXeezj7XWZDGSun45K1FOnTh2cnJywt7fHxsbGLE116dIliouLcRzyAVKPlo/v3KoAUTBRdG4bRZEnqTfl6xrPGiwVUlq5yQlJ1mASpY9AyBH/Ml64//+YRAJKqYSSMz9RdOkgixYtYvbs2fd8bHh4OC+88AIxMTHY2NhU6tzVxTo6fnqkIomlhqCUQaO4vUT8sY9Zs2bRtGlTNm7cyJkzZ5g0aRLTp08nLi6OH3/8keDgYDp27IirqysRERHk5eUxYsQIRo4cSceOHfnXprB/tGTZk3Jgr5XC8cFr6c9M0IP7+0HJ5XJz+fN+KC4uJjk5+a7AmJeXR0pKCikpKVhZWWFlZUVRURFarRaTyURxcTFqtZrc3Fw8PDwQRZHr169z+fJlsrOzSUlJuSertE6dOg99PVW1HqqpnpLWILBodzizp44iK+oCoiiazTePHDliXtEqlUrc3d2pX78+3t7etGjRgubNm9OwYUOsndzo+dXZGjmfR4EoCJTGXkCqL8HC1haj0Uh+fj7FxWWM5HIVfoDS0lJUBTnYPMVKUqIgoI09T+HZX5FIJGjjL2JRU6MhoohMIsLlvRy/sA9br2boGnVB1bA1crm8guPK7T036/w4/ojJpcSuIXq9vkLfSkbZgifAXuD0uoUYMuP45ptvGDt27H1PY8GCBXzwwQeVDnoAOy6mIJPJMNZCVUpvFHB6fjTHFr7Ff//7X1asWMFrr73Gv//9b7Zu3crzzz9Phw4deOONN/jmm2/YuXMnP/74I1lZWfTt2xeNRsPUqVPRaDR4jf43SN1r/ByfFljIZbze3eexH7fGA9/mkASupRbU9G5rHb/s3MO6qZ1RKpVmexAbGxtsbW1xcHDAyckJR0dHnJyczK7Lrq6uuLm5mbO528WWy1HO7LpXxpicnAxgljaysbFBJpNhMBhQKBTExMSQk5PDuXPnyqSu1GpzqbRdu3a0atXqnqXS6kjE1VTWJyBD8O+NQ0YM3t7eeHt707x5c4KCgvDx8aFBgwZYWZUJdAmCQHFxMQUFBeZt7969kCYBz0Aeh4iyhULK/94fT5v/vY1KpUL1l6zYvd6LkpIS2k54H51oQnhKZ6skohGb5LNciI9HJpPRZvhMJD4damTfIiBmx5Mfth8PDw/eeG0Co0aNQmOSmkUV1IUlHDscTPeBL2KpkKIziqQVK7DT57DtjfGMmbOURq06cyslA5O2mOkjB1FwOZj/flxWsty5cye9e/e+7zmcPn2ayMhIdu3aVaXXEJVRWHutGImUswkFLFu5g2XLlvHxxx+zfPly+vTpw+TJkzl37hwnT55k/vz5aDQaZs6cyYEDB1Cr1fz0009s2rQJKysrhg0bRpSxAKRONesw8pSgTD3H/4noKNdoqfNZYXLeCxYZV5Bf+NlsB6LVatHr9WYFhnspxd/rrSt3X77dc0ulUmFhYYGVlRU2NjZmTy8XFxfc3NxwcXFBqVRiMBjQ6XQUFRWRmZlJQkKCWeDWaDSaZ8jK1eNVKhWCIGAymfDy8iIwMJDWnbqxMacxj9EE476QITLe9gb6otwKQe3OraioCGtra+zt7c1bfHw8dQLaUdT+XwiV8LWrEox6CN+FIfI4Op3OvBkMBvNC6PbNwsICiaUdRT3mPpWkA4lJT6P8y7S203Ds2DFe/fxnvvwjAa3BVHPzgSYD373oTu8uHe/6Uzmh6tCVZCwsVOiMf18nUsGIQqlETLtOT3cDJ3dt4uzZsyxatIhdu3ZhMpn4/fffad269X0PLYoiXbp0Ydq0aUyaNKlKp1/b5CmVXIKfPpYz333MG2+8wZw5cygoKGDFihVs3LiRESNGMGfOHDIzM1m1ahWHDh1izJgxzJw5k4CAAM6cOcOPP/7I7oNHsZvwz2N1SiXwyeBmT8w5p0YD3zPD5LwDKpmEd/v6PZBVJIoipaWllJSU3LUVFxeTm5tLRkYGmZmZ5hJm+U29uLi4QjA1GAyYTCYEQbin6eXtKFdyv92tufx35UHPaDSa92PX4WXsnx9Xrd5YTWV9EsGIV+E1/IQkrKyszJl0efAoz6oUCoX5tRgMBvLy8li8eDELFizgpqkOZ0vdMFILmZUoIBFM2McfxSrtkvkcTCaTWXaq/Ofbt/LHSbvNQO7V+qkaNhcFE3lH/oc0/gwuLi7YBPUnr1HPmmEu3g6jnvmDWjKjW8Vr5lEJVaIggMnAtHbOnPnhv0RHRyOKIkePHqVx48YPPPSBAweYO3cuV65cMZfQK4vHMS4zNKg+b3d0ZMGCBRw/fpyPP/6YKVOmkJ+fz9dff83atWvp378/8+fPx8nJiXXr1vG///2PgIAA3nzzTV588UX0ej0jvjrM9QJZrThUPCl0b+LKD1PaP7Hj11jge9aYnHeih58rb/dqUquu7eV9Ip1Od9fXoqIiCgsLKSwspKCggIyMDFJTU8nIyECtVpuDaElJifl5BoOhQvAURRHnQe/WiNCxKApIauBCK7l2nLzfvwL+DuJ3fi+VSiv8XB7IrayskEgkKJv2wuK5sSBX1Mg5IZgQBRNKdTROGWFYlmYjk8nMC4vyr3d+L5fLK/xcrHTmvG0nhKdoNS7PjEJ3ZCWpqako3HxwH/dfJLVEEOpUT86WN/uZf66S56ZRj/zafhzVVzlw4MBDe9iCINC6dWs+/PBDhg4dWtVTfyzjKLcPZYeFhTF79myys7P57LPPeOGFFygqKuKbb77hyy+/5LnnnuODDz4gMDCQnTt3snr1apKTk3nttddwe+4lPjl0q9bO83HjSYwv3IkaC3zP/lyTiFwi0sU6G395tjm43BmgyjO30tJS8/darbbCYwwGQ4WtPFOAv2/ydx39r49BFMV7llBvx+1B4s7Huw5bhJVv9Xs5MpMOk6z6N8zKKjKUD7dv3LiRTp06mX9/JSWfL49G88fN7Gqdj1QCb/bwIS54I1bW1jTuNZaojEIKtUbsLOT4u9sxos3D58DKsTkkgY/3X3ssQtoPg2DQoQndhnPWZerWrUt8vV5IPINqLSN11KRw+atXgeq1OSQmA7+80oGOTeo+9LG//PILK1euJCQkpFpVicexUL9zKLuc4Tx37lw8PDz4/PPPCQoKQqPR8P3337N8+XL8/f354IMP6NatG5cvX2b16tUElzRA2ajtM+92X44nMb5wJ2psqVqrzeLHAglGUcLxfAeCQ4PRXz9mLnXdXvICzGXHckJJuUtzufxW+ePK+3u39/isrKywtrbG2toalUplziLKS2t6vZ6SkhLUajU5OTkUFBSg1+uRyWTm/T8oOAq6khp5NyzlUFwDSyI7i8rNup06dcrsfXY7Wno4sHFyeyZvPM+J6KoFP4kE+jZ1o6e/G2cje3IhVYPqjsWahTyDL49G093Plde7+Ty0AlDeo/ho31WMJp6orJREIqEo4gg5RbnEpmTi8fpbtVqGTUuMIy8vD0dHx+p5bsoV/HA+9aGBz2AwsGjRItatW1ftUryLjYou3k4cjcqqlRKihVyKf13bCr+TSCQMHjyYF154ge+++47+/fvTr18/lixZwhtvvMH06dP5+eefmT59Oq6urnzwwQcs+2otp5cdr8CUfZYhkZRV155k0IMaDHw1ZXL6pCGRq1B1GIO7QoejWISdnZ2ZcOHg4GCe6ypnfJZ/X77J5XJKSkrIzc0lPT2djIwM81b+c0JCAllZWcjlclQqFRKJxBz0ysuXUOb2rFAosLCwwGAoE8q1tLQ0a1rC30G3HIbsBASDrlo9Pgu5lLbeHpyLy6nWYkYhhbpWZaXYRx3QX79+PdOmTbvvje2d3k0IvZVbpczCQi6jkbM1o9eHlN2kZYq7Xl+5/NXhyExORavvqfVYjqysLK5cuUJmRAQtMpO4oHFC5hlUNij+mFfnoigiKczEpClAJpPh0v7Fst/V0vFkCEgL09m8eTNjpkznZHR2lXv7ogh/3Mwmp1j3wBvi999/T6NGjejZs/ql/KysLMJ/WY40aCJCLQQ+ERje+t7zLgqFgtdee41x48axbNkygoKCmDFjBvPmzWPKlClMnDiRnTt3smDBArSNfkcI6M/jYDY/Djyp8YU7UWOlzqfJfqi6uHOoslxE9vbgdWcwK/++pKQEZ2dn7O3tUSgUGI1GSktL0Wg0FBcXo9VqzcQUpVKJlZUVlpaW5jGG3NxcbGxscHV1NcumFRQUIJVKzQHEaDSafy4737/LnlIrezxe31gttqFEMPJ5bxc+OFXNLN5kRLv1PQqyUmnUqBHe3t40btwYb29vXD0aE2NyJtugoMQgYmchp4GdnMVTBhB7PRxnZ+f77rYqvSRLhZTeAW4cvZFZ6efN79eE1nYas1VM+VetVlvBPy3d2ofvL+c/sZ6fYNThmnSS1nYa9uc4167yjclA8upJoCvGf+ibaLx7VIt5+LC+j0ajoUmTJuzevZt27aonZhwZGcmgQYMYP348vi9M5dPfa9bouLJD2cnJySxatIjg4GA+/PBDXnnlFbPp7cgvD3KhetX9pwZ3mv8+Sfxfj+8+kAhGnP5cQWZSHFlZWdjaiCLE9AAAIABJREFU2uLu7l7GlLOxMY8fFBQUkJ+fby5LlpaWIpfLMZlMyOVyHBwccHR0xNbWFpVKhV6vR61Wk5aWZvZ4s7CwoLCwkOTkZDIyMlAqleh0OnM2WFpaioWFhXnf5YFPpVKZA2l5GdTKygqrfm9j5duxamUuUUBICkd3bDUuQ99H4+hbJfeB2y/+kpIS4uPjiYuL49zNNE5kq8iSuZQx+24P0H/ZvzR1FBnXypW+bfxwcXG5Z/b3qOzBcpX+Sc958eO5xCpliqJBi+r0NwQ1cCIwMNAc7Dw9Pc3n9rSM8ogGHeqtC2gxZh4ZstrRhS3/bJ0id7Fq1Sq6zd/IteLqC7Lf3hO7XVS9UGskJS6akrQY9q18v1plsqNHjzJ27Fg+//xzJk6cCFRC2u8RYamQsXV6x0rPp4WHhzN79mxSUlJYvnw5L7744j9CueVBThlPCv/H6rwPZKIJH+1NLG6drsCuNBqN5kwOwNnZmXr16lG/fn2cnJzMxqUZGRlmObJydwdnZ2dEUUStVnP9+nXi4uLMpUuj0YiTkxMmk4m8vDwcHBwoKipCKpWaaf4qlQoXFxcyMjIQBME8BqDX63F3d0etVmMymfBp3wvt8zOq5BNnqZAxrXEJX334Lk4+rchrPRGqQIW/18X/6NqhAghGSs/8TOnVw+Ys8c6vBTJ71p1OeCSV/tV/xFZ51EYC9Gv24BX80zLKIwoCFuqb5KkzsWravVaOoZJL2Db9OZwoxs/Pj4BXvyLHol6199vLvw6zevreV1S93Ez2Ufuvd2L9+vUsWrSIbdu20bVr1wp/uxCfxVvfHiBVdEAmk1Z5drS6WY0oigQHBzN79mxcXV3xHLmQP5N1VdrXk4ZcKkEmlTzQKeNJ4f/m+B6AkuvHkYT8RP369fHx8cHf3x83NzcEQaCgoICkpCSioqK4ceMGJpOJgIAAAgIC8PX1xcrKipKSEhISEjh37hxRUVHY2toik8nIz8/HxcUFFxcXCgsLSU9Px93d3TzDZm9vT25uLlDW02vSpAmpqank5eVhMplQKpXI5XIKCwupW7cuDg4OREZGUrduXdzd3bl+/TrPTZhLolMbRNmjk0tuv2g1Gg3Lly/n26PXsOo8HkFatf2Uo6rlybe7N6StvYa4uDhz1lj+NT09nfr16+PVpBkKvy5gXw+5lR2u9ta0buzO+M4+ONuoiE5KZ+D/LlVrqP9BTLSnbtFnMqCMO4neuxtU4vN/FEhMBvShvyDG/EmnTp24fv06uX4vYhnQrdr7DvSwJzqz+JGz+EfNIARBYP78+ezZs4cDBw7g6+tb4e8XL15kwoQJNGvWjE+/+JojcUV8tn4LLVp3QGJpS0RSDkhlPKjPVtNZjdFoZOPGjXy87QyK1i8jPkMC4/A3e3ricw2fOJHlXvg/5ZYHoKm9ic6mq9y4cYMbN25w8+ZN7O3tzQGuPMgBJCQkcOnSJc6fP8+1a9dwcHBApVKZ+3O+vr6oVCqysrJITk7Gy8sLqVRKYmKiuZ+VlpaGVCrF1taWjh07otFoOHfuHDKZzFxatbe3Jz09HWdnZ0aPHs23336LwWDgjTfeIDg4mPT0dObPn8+mTZt479u9rDyR+AglHBFLhfyeF21iYiITP1lPolNrkCkfKjB8r4u/Ov8XDyob6fV6EhMTzYEwNjaWiIgyX8WMjAzz46zbDsGu85hq9T0f1IOqyTK/RBQQkVSLHCMadNQvukGqXdOaU5b5Kwt3TjzJhV9WkJiYyJkzZ9i6dSt/qlXVFhSXSwCJBKPw6LejR8muNBoN48ePJycnh127dlXoHRsMBpYuXcrq1atZuXIlY8aMMZeut23bxvLlyzl//jz7zkTwxpp9WPm0QyqRVNr/rzpIzMyl28qzPEvkliclPF0Z1Lg7w1Pvul4JKHQFBChy6OdrR9sW/nh7e5OcnMzFixe5ePEiYWFhXLt2DScnJ2xsbNBoNKjVavz9/fH09MRkMpGUlER8fDxNmjTB0tKStLQ0CgsLady4Mbm5uaSkpCCXy7G3t2fQoEHI5XL27NljHmvw8PAgMzMTT09PYmJisLKyYsGCBezdu5ezZ8/i7OzMnj17ePnllxEEgfXr1zNjxgxOnTqFn58fV1LyH2jaaRIEdAmX2Ln4Vdo1vv/w8Ma9x/jP7jBMbv7IZFKMorTCfh508VenEnC/iyg3N5eIiIgKZJMbN25Qv359cx/Oy8sLW1tbfoiGKwXVX3XezyyzpohdkpIcvBvUIzan+qUt3c0/qVPXgwIbr2qNWIhGPSqViq4+zhz9ei6yghQ++eQTxo0bB5RlUw2aNEP+8tIazy4fBQ9aGKWnpzN48GACAgJYv3692TkFICoqigkTJuDk5MT3339P/fr1KzxXEAQ6dOjA7Nmz6TVwCK9/tonIzBLcfIPQmQQs5FKauNkS6OnwSP5/VYW6WEf7T49SifXAE0dVe5yPE7ViS9R35UmiM4trerdPBHKJgCCIyLOjyTj+I45CIY6OjhgMBlJTU7G1taVdu3Y4OTlRUlJCVFQUMTExtGjRAkdHR3JycoiMjMTX1xdHR0diY2PJzMxEJpPh5OTEmDFjqFOnDsHBwYSEhGBtbY3JZKJu3bqkpqYSEBDAxYsXkUqlfPDBB3h6ejJ9+nT0ej1Tp05lzpw5tGvXDhcXF/bt20ffvn3ZtGkTffr0qfA6cop1ZgHhQq0BOwuF2bTzX+NH0a1bN955550HvhdGo5GV33zHij1nadTqeRzd6pMUG0XerWu81r81b706FWtr6wrPqYkyoEIqYV5AEfGREeZgV1hYaCaZlH9t3rz5PZX6a0qX8X7D+MO/PkpYevWDVQcPKxISEsiUP9yB42GoY8gkcvsXuIxcUiWBY1Ewob11GUPqdWyyrvFH8H4SEhIYN24coigSFRWFo6MjAF988QWfhRRg6dOhSkSo6uB+C6OrV68yaNAgpk2bxoIFC8yZnCAIrFq1isWLF7N48WJmzJhx39GZDbuPsmTXeRQNWyGBO+Y9yxZ7Ve03PiqeNYu3p4m5+SDUSuD7J402mCEIiCYDTokn6FIXrK2tycnJ4eLFi0RHR9O2bVvq1q1LcXEx4eHhSCQSAgMDEUWRsLAwSkpKMJlMuLm5MWHCBFq1asWJEyfYtGkTtra25Ofn4+3tjcFgID8/n6CgII4fP47RaOTNN99k5syZjB07ltDQUGxtbTl8+DBGo5GePXvSvHlzjhw5Qrdu3Zg+fTpvvvlmpV7a1atX6dOnD7GxsY9k8ZKTk8O///1vduzYwYcffkibNm1Yvnw5p0+f5q233mLmzJnY29sDNVQGNOqpnxdOX0+peXSgvFT8KKip/8chQfVYOaoVUEZCOHXqFEuXLiXSrh1S77vFmiuLfk0c2Ld/P6oaGENwK01kYS9Ppi3bhKrjaCSVIDqJBi1OiScJ37GKOnXqoFarkclkdO3aFZPJRHp6Oj179mTt2rUA5OXl0aBVF1xGLqlUT/nvA4rVKu3e2X/9/fffmTRpEl999RVjxowxPy4pKYnJkyej1WrZtGkTPj73nycrJ2KV6g0PHHCvbcbis3IvfRqZmw9Crcg6+LvbIX12StKPBqkUiUJFXqMebDmfzIULF5DL5bRu3ZrAwEDCwsLIzs6mTp06tG7dmvz8fM6dO8cff/yBnZ0dc+fO5eTJk8ybN4+DBw/yyiuvcODAAURRpGnTpri5uWEymWjbti1FRUUEBwczZswYsrOzadKkCf7+/oSEhPDyyy+Tk5NDSkoK3bt3p2fPnoSEhDBp0iQ6derEG2+8UemX1qJFC3r27MlXX331SI93dnZmzZo1HDlyhO3bt5uD7fHjx4mMjMTb25tFixahVqtrRtFHrqR9n6F8+OGHDBkyhEaNGlXKsd7f3Q6VvJr/6kY9v377BcOHD2fmzJm0adOGf/3rX7i7u0NBGhKhegIOMtFE3KU/sTUWIqOa75dRj6QgrawiMLQj9TJDEAzasj7dgyAKYNRTfPonUk78wuLFizEajbi4uGAwGIiMjEQQBKKjo9mwYQPr169HFEUcHR3xdVKiPrIO0ViFzLeaw/4SYMelFADWrFnD1KlT2bNnjznoiaLIjz/+SJs2bejbty9//vnnIwS9G2U96YcMt4silBpMfLjvOv1WnuTtrZf59mQcOcU1w8R82oVBLORSVHIp/Zq6sXV6x2ci6EEtZXzRmUX0XXmqpnf71EAqGCnZtwRnSQndunXDxsaGqKgojh8/jr29PYWFhTRq1Ihx48YxbNgw0tLS2LBhA3v27KFhw4ZkZ2fj5uaGn58fp0+fxt/fn3bt2rFhwwby8vIYMmQI33zzDSUlJYwYMYLLly+jVCrZvXs3/fr1Y9WqVbz99ttMnjyZ7777jvnz53P+/HkOHz6MQlG1PktMTAydOnUiOjraXMJ6FIiiyM6dO3nvvffo0KEDn332GUajkWXLlrFjxw6avPIlGTKXKp3T7ais5uftqIlyq0ouZYpTHGtWLKO4uBidTofRaMTV1ZWpr73FVm3z6slK/TUQrlSqqD9zI9VZK0gRsD32XyT6EpRKJQkJCdTxb0e2ayssGrcBUawoXG3UIwKauAu0t84n7do5IiMjcXZ2ZtKkSRw8eJBRo0axaNEiRFGkTZs2XL9+HUEQ8PT0xNPTk2vXrpGdnU3vGR+R4tqhxmbiHhVDgurBuR85dOgQBw4cMDs8ZGVlMX36dG7dusWmTZsIDAx84H5qgqBXk2XQpzXjc7VR8ryPq7ld8jQyNx+EWsn4jkdl/fMyvtsgSGX4vTyLOnXq8OOPP7J9+3ZOnDiBn58f77zzDlevXuXQoUOIosiAAQOYOnUqUVFRSCQS/Pz86N27N8nJyUgkEubMmUNMTAyff/45rVq1Ij4+nm3btrFlyxb8/PwICwujR48e5OTk0K9fP+bNm8fbb7/NggUL2LBhAz/99BM7duxgx44dVQ56AL6+vrz00kt8/vnnlXqeRCJh+PDh3Lhxg2bNmtG6dWs2b97MypUruXLlCnJRX+Vzuh2V1fy8HS42Kro1ca1GYiGiu3WJ3/dsZ9q0aTRs2JDmzZuzevVq3n33XcLO/EFRdCg8xGLq/rsXsMq/RZvmfrT0a4QpKaJsuL9KuxIQU68ilBbStWtXEhMTycvLQx19kRYFIaSsmUzB6S3Iky8iTb+OKi0crh3gh5c9kJ/byB87fyA+Pp66deuSmZnJ5s2badOmDUeOHGHTpk04OTlx48YN9Ho9giBgNBoJCwtDrVajVCqJ+u07fpwYRL+mbihkj+8mcOzUWa5evcrZs2fNQW/37t0EBgYSEBDA+fPnHxr0oHomzuXQGgV0RoHDkZmMXh/C5pCEKu+rRqoVNQxLhYwNk9rx5aggXu3q/cwFPailwBeVUfhMsZAqDwlJBlsuXY+mRYsWzJo1i2vXrhEaGoqvry+zZs2iWbNmHDp0CKVSiclkokuXLgwaNIhjx47h4ODAmjVruHTpErNnz6ZevXpcuXKFw4cPU1paSps2bZgzZw4AW7Zs4ciRI1hYWDBu3Di++OIL1qxZwyeffMK5c+eYPXs2+/fvf6DE16Ni0aJFfPvtt2RlVZ4IYmVlxYcffsilS5e4fv06TZs25dy5c4wf1ANlNW+A9xL8fVSoi3V8ezIOnVGoMiFcIhiZ0LasFL1t2zY+/PBDQkNDmT59Ou+99x6///47+/47E2UVb1ASwUTG8R+Jj49n8+bNfDntBRAMVTtZkwHNhd3MmzePU6dOYTKZ8Pf3R6fTcfPmTYTSQlxzIkjcuhj90a/p75BF0qHvibx0nvDwcKRSqVkuS6FQkJqayrFjx7C1tWX37t1MmTKFtm3bMnjwYAwGAwkJCRQXFzN58mTGjBlDamoqfdv6I5xaRzPnxzd7Zq2QEhwcjKOjIwUFBUyaNIk5c+awc+dOli5dWoHReT+oi3XV0hy9E+Vl0P8cvFHl4De8zb31Pp8UnqRrek2iVgLf016XrgnIZDIWbviN0NBQBg4cyJo1a/D09OQ///kPJpMJmUyGpaUlEydOpGXLlmzevBk/Pz+2bt3KqVOnmDBhAkqlktOnTxMSEoKvry+ffvopQUFBRERE0KpVK7KyshgzZgwGg4FevXqxbds2duzYwYwZM0hKSmLYsGH88MMPNG3atEZek5eXF2PHjmXp0qXV2se2bdv44YcfWLJkCVuWvPVQm6WH4UGCv/dDRHI+038Ko/Oy43x5NJqT0dlVWowpJCJ1Uk6zZdVSZsyYQUREBEOGDLmLCdiucR3+/WIzLBWVu6QsFVL0ob/iX8eKzp074+vrS1L4n/iXRiITK5d5WCqkdLHJwtaQx549e9i4cSNGoxGdToefnx+ZmZlmR3mpVIparWbTpk14eHjw6aef8s477/Dqq68yaNAghg8fjoWFBUqlkqSkJMLCwsjMzKSwsBCJREJ4eDguLmUlbFdXV0wmE3v27EEqldKuXTvcvXwITy+t1PlXFTIEJg/ti0Kh4NixY7Rs2RJra2vCw8MrWFs9DDsuptTK+ZUaBP5zMIorKfmVfm71qxU1A4mkLNN7Fhibj4JaCXx2Fk+PMWdtwYSU09fief755+nWrRvx8fH4+/tz69YtAgICWLx4MQUFBaxbt44XXniB/fv3ExwczIABAygoKOC3337j2rVrdOzYkfDwcIKCgsxkgtWrVxMaGoq9vT0lJSW0atWKs2fPcvLkSYYMGUJxcTGDBw9m9uzZDBgwoEZf14IFC9i0aRMpKdW7CXTv3p2LFy8y5uVBlMZffDix4j6oio3J5pAERq8P4ciNTHR/lZ0qfVzKerml535mShcfbty4wfjx4x/o+D2+Y0MWDAjAUiF7+I1KEJCJJjpZZZJ9bhdJSUnmcZIjR44wtYsv7ulnUUjFh5Y9RUFAJZewYEAAG96fgkwmIyQkhClTprBkyRIiIyNp1KgRBoOBZs2aYW1tbTbTLSkpwWAwUFJSgl6vZ9u2bezevZvXX3+dM2fO0KlTJ1QqFenp6Vy+fJmjR48SHR1NSkoKSqWSvn37kpeXx5EjR9i8eTNt27bl2LFjbAtLQi5/PBmfXC5nUFNn3nrrLSZPnsy6detYu3btIzGUb0dtWqtpjSbWnoit0nNndvfB4jG9l3e2qJ5V8srDUCvkln+aYPX9YJ0fT1tNGH/++SdOTk7m+bpVq1Zhb2/P3Llzad68ObNmzeLEiRM4Ojry9ddfM3LkSCQSCTqdjsWLF7Ny5UpKS0vx9/fn2LFjZUxByhrzrVu3pqCggPPnzxMQEIAgCAwfPhwHBwc2bNhQbV+ye2HevHkUFBTw7bff1sj+/rc9mE9DNVVyAr/fMOydIsblJrIg8tWxmCqr7SulYDSZ0CdeZkygM5+89S8sLSsnwHw5KZdpK7ajVrmjVMjR35a4iUYdSqWKVu5K6udf46ev/kNOTg4WFha8//779OzZk4EDBxIXF0enTp1YvmEr07/cgaV32zKR89sJNEY9SCQYEsNpVBrDr2uX4eHhwfHjxxk+fDgFBQUkJiYiiiKBgYFIpVI++ugjli5dil5f1ntVqVSkpaWhUChwdHSkffv2/PHHH3h5eXHp0iUUCgUbt2xn9tqdSJ08kKqsEfQaLLU5lEaeYNeWH80ZsEqlol+/fvz00090nr2ORIlblT6DykAigXZ1lUSsfoO2bduyevXqSpGzbkdNzXveD9UxYK2Su30lYSGXMrq9JwUa412zvs9iH+9BqJXA99RpF9YSdDf/pJ9dBuPHj+f8+fOsWrWK1q1bM2fOHBo1asQ777zDb7/9hrW1NUuXLmXatGnmjOHcuXNMmjSJzMxMSkpK+Oijj1i4cKF537GxsbRr1w6lUsnly5epV69MBHjRokWcOHGCo0ePPlLfoirIycnBz8+P8+fPm4kCVcX27duZOXMmU5duZPctCbpKMB/vNQwbkZz/QBHjqjIrpRJw1meScukPJnf15/1338TOzq7S+zEajUycOJHMzEz+++Vqhs35DKVrQ0pNElRSga4tffhi5nCcbVScP3+eYcOGUVRURL9+/fDw8GDPnj0kJiYycOBADh48yNmzZ2nfvj3O9Ruy5Oej3MwoEyCQGrUE/7qBS7u+Yf/2X3jrrbeQy+W0adOGcePG8c477+Dq6kpgYCB6vR6JRIK1tTVbtmxBo9HQuXNn4uLiCAgIICoqisLCQlQqFR06dCAmJobs7Gwat+1BmwnvczFdiygKFQK4YNCVmSOnXeeVTp4snzeTV155haysLLZv307dCcvBtfZ912SYKNn7H77+6D1GjhxZrX3VNoPyYdZLD8MjO5JApYUEnpXB85pCrdQky+vS/yTB6jshQ2DC0Be4HnGJid8cx71BI/p99AtN69nz7Q9r2f3LJhQKBR9//DHvvvuuOUiVlJSwYMECNm7cSElJCfXr1+fSpUt4e/99MYSGhtKjRw/q1atHWFgYDg5l2c4vv/zC5s2bCQ0NrbWgB2Vzem+++SYfffQRmzZtqtI+RFFk+fLlrFmzhsOHDxMUFETzkASWHLyBzmDigRapQpkuZH9PkTHtPM2/ftiFX51xApNJQCmTcnXbl+beVWWh1+sZO3YsJSUlbN68mb59++Jha4u9NJ2oqCjc69Zl4+Z/m7P0hQsXMnnyZJYvX86rr75Kz549sba2Ji8vj/r163PixAn69+8PgI1cxDEjjAW9euHi4oIoitRfNIpidQZTp05l1apVfPrppxQXF7N06VKKiorQarWo1WosLS3p2rUrPXr0AMqISAEBAbz++uukpaWZhQs0Gg1nzpwhICAAg1cHtJ0ncCax+J72VlKFChEQ67Xgu1tGmg5+lW++WU1ERASlHm0JExvWvrqkSU+d9LPsOraHunUf7N7+MKSkpKCOjQCTQ61Jr2mNAlHpRVV+/viODWnp4fBACcJy6cBGztb8cO7hOr3P2uB5TaFWMj745wlW3wVRRDQZkMlkCJK/6++CQYdEIsFDVsDnU/rynN/fdi3Hjh1j6tSpaDQacnNzmTVrFitWrKhQrty3bx/Dhw8nMDCQU6dOmcts58+fZ+DAgebmfW2jsLAQX19f/vjjj0qTZwwGA6+//jphYWH89ttvFXQQy7VDj9/MxmQ0YuJuzc/ufq60lKXz01f/IT8/n/fffx98nue/h6JrtdRTmVLUnaVWa4WUC0f24FwQzZaN6xg8eDBSqZTMzEzmzp3Lu+++y7Rp01i2bBkAJ0+eZMqUKXTt2pXjx4+zdetWnnvuOTp27Minn35Kbm4umzdvplWrVixZsoSBAwdiNBo5deoUvr6+9OnTx1w1KA98ISEhbNiwAT8/P1avXs2GDRvYu3cvUBbstm7dyqBBgwAYM2YML774ImPHjiUnJ4eXX36ZkJAQ7O3tKfVoi1PPf1VK7QWjjsKTP1K/fj0MLQajrcXPCcoWVr2cCtkwZ0yVy/3Jycns2LGD7du3c/PmTfoPGUGo24sYa3GxXp151NvxIAnC8v/fh+n01qa49tOOWgt88Hjq0k8Coij+RV54NKeCQf4OzJkzh127dlFUVISjoyPBwcG0atWqwnO+/fZb3nzzTfr06cO+ffuQy8sS8tTUVDp06MDatWsZPHhwLb6yivjss88IDQ1lx44dj/yc/Px8RowYgUql4tdff70vwaD8wr0Yl8H5y1fJy0pjUOdWfDz5BVxsy264oihy/PhxFq38jjT/EVXyBawMHqUU9aBSq0QwolAqscqPxyL+FAkXT7JlyxZGjx7NW2+9xeXLl9mxYweiKNKtWzeGDRvGRx99RMOGDfnf//6Hr68vDRo0QK1Ws3z5cjQaDdevXyc4OJg///yTDh06oNfrCQ0NLZur27qLAuemeDRvj72LO7FR1+gU4IX+5il+2/ELM2fOZNu2bTRq1IjLly/j7u6Ok5MTw8dP4eCNHNz8WuPk7oGdhRwLbS77v15A6+d7cUrRpkr9WNGoR0REWsufE5Tpt87u51fpsmFiYqI52MXGxvLSSy8xYsQIevbsiVKprHVrtfsJndcmHiVI/v+GWg18cJvm3T8183sIFFKR0jM/I4krM7SdMGEC33///V3swIULF7Js2TImTpzId999Z17FajQaunbtyvDhw5k/f/5jPXeNRoOvry/79++ndevWD318QkICAwcOpHfv3qxYseKBDMg7cfLkSWbNmmUmAN2e1U7/KYwjkZmPRQD5QTemRzbSFQREwcD4ZlYcWr2QiRMn0r17d0aPHk1kZCSHDx9m1qxZjBgxguzsbC5cuMC6detITExk3bp1BAcHM3bsWPr378/ChQtJTU2ltLQUpbJMbLo8+P4RlYlBr68gQl3ee/OQFhCzdw0/r/qUoUOHArBwxXpCiuwJz9RjNBor2AhZyKWUarW42lujLqnaDGH5raQ2CFf3wqMGkYSEBHOwi4uLY8iQIeZgd6foQ0RyPqPWn6uVjLW6Pb7/Q82h1ucOyuvSr26+SHqBtrYP99TBIEiQtR1OcWoUf/yxmW7dKhp2CoLA1KlT+fnnn5k/fz6LFy82/00URaZMmUJAQADz5s173KeOlZUVH3zwAQsXLuTgwYMPfOz58+cZMmQI8+fPZ9asWZU+Vrdu3bh48SLr16+nT58+DBs2jMWLFyOqbMqGiqv6IiqJQq3hnoxRjd7IqehstI9SB5NKkUhV/Bqlp27zPrz55pvo9Xpu3bqFTqdj4cKFLFiwgNmzZ3Py5ElGjRqFTCbjyJEjZleNqKgopk+fTnp6Ok5OTuagd1fwvcN5obz3liQ4ohowj1c/24xUKsWx3WDWRCmQKkyIEhlSRcVFidYoIJErUZfoqar32+MKeOUo1N4/QN+6dYvt27ezfft2EhISGDp0KIsXL6ZHjx53Bbvc3FzOnj3L6dP/r73zjori7P/2tcvSoiBiL9jFjl0UETWJsbeIikZjyWshasQYE9MefDRK1BinCm/GAAAgAElEQVTUGMUSe1SiUcEejA1pJmIBQRGxYke6sOyy8/7Bw/5cQaUsLuW+zskxZ3Zm9p7dZT7z7Wc5e/YsT1SVseg+Lmv+pB4pSD2qoGh4KwV3drWtGNelHj/7XStcP8MSikxhwoffraV7904625VKJYMGDeLkyZOsXLkSV1dXndcXLFjAnTt3OHny5Fu/qWQzadIkli5dSkBAAF27ds11nz///BNXV1c2btyojSEVBIVCgaurKyNHjsTd3Z1mzZrRZ9YyoPC9PvNKxIMkui4+AVDorORMmRFPbZwIi03ErrYVdevWZd26dSiVStLS0ujQoQNNmzYlMzMThUKBn58frq6uaDQarl27RmpqKhYWFtqM3vyEDmRyOchNMergjJl5NTIbdtSK4huOLNQ1v01ebmMXExOjFbs7d+4wdOhQPDw86NGjhzZsIEkSMTExBAQEaIXu7t272Nvb07VrV+bNm4e9vT0+V+LyZt3nkYLUowqKjrdWae7cvjaex6PIf6JtKUAm50x0HHEpSu0PPykpie7duxMREcGuXbv48MMPdQ7Zs2cPv/32GyEhIZiZ5SPJQM+YmJjg7u7Ot99+m0OAJUnip59+YuXKlRw7dixHzLKgWFtb88svvzB58mRcVh5FWdlaL+fNC/r2SigzNaw+FY3XmA40b95c+3l9++23LF++HEA76iclJYVWrVpx+/ZtKlasyJUrV8jMzKRhw4Zcupvwv5BB/sRYmQlmTRwLPQGhuJHdxu7GjRtasbt37x5Dhw5l8eLFdO/eHYVCgVqt5tKlS5w9e1YrdgCOjo44OjoyefJkWrdurRXGbMZ0tnhtBmX+12vEpz2KvrxDkDfemvCVhRKH15E9OmWKU0MePHhAly5dePz4MX5+fjg5OensGxoaiqurK3/99Ze2mN2QjB07lh9//JHjx49rXXEqlYrp06cTEhJCUFAQtWvr34XTqlUr7Lumc+Ja0RUVFzWSBH4Rj3D9/Tw3avVCUrTg9GNjMLPgvffeA7KELzg4mPfffx+ZTEZkZCTNmjUjODiY1NRUmjRpopfmyaUJlVrN6i8+xv3ODT788EOWLl2Kk5MTaWlphISE8MMPP3D27FnOnTuHjY0Njo6ODBw4kMWLF1OvXr08eVDsalvhNaaDTnJIxINEoh+nkpmPm1hp6W9Zmijy5JYXKfUlDm+gh20VvulqhYODAyqVirNnz9KqVSudfR48eIC9vT2enp4MGzbMQCvNya5du/j5558JCQkhKSmJESNGoFAo2LVrFxYWBWsgnReK61iWwiDTqDAyUvBe8+p82r0RQ7u3o2nTpri4uPDxxx/j6enJzZs38fb2RqVSMee7+WyOb1jqG0LkFUmjoXrmYxYPaEjDhg0JCgrSWnNXr16lXbt2dO3aFUdHRxwcHLC21q/HIM+F5GW0Rq4k8FaFD0pviUNekAFJJ9ejuBlESEgI9erV03k9PT2dHj160L9/f77//nuDrPFVaDQa2rZty/Tp01m5ciVOTk6sWLEih4tI35Tm9nfZN8bUs9tICj1EREQENWvWZNyU6aTXaM3pi9GYW1WiWj1bnmQYUwbD47mikGlo9eg4l04eIDExUStyXbt2pX379m8lNCBq5Eo2b134IB9p4aURdQZfftCYT3u11NksSRJjx45FrVazc+dOgyWzvI5ly5Yxd+5clixZgpub21tZY1lofyeplCjCfdm7fjm/normr/BYjORyneJ+wf9QK2mcEsaIdjVxdHSkUq167L1wP0fP1uHt306NmqiRK5kYRPhA94kJScpXD8eSTm6Nlz08PNi7d69Ot5bixL59+5g8eTIVK1Zk/vz5uLi4vLX3Luqi4uKATNJgolCQodGU3OuUJCSKrqxBLoP5g1owpnO91zYS0OcEdEHpxGDCl032E9PmwFtlps5PJoPezavhNaYDAD4+PkybNo2QkBCd9l7FAUmS8PT05Oeff8bHx4f4+HimTZvGlStXitzNmU1ZiA1ndQMqflZ+fpAhZYl2EV1Hx7oV2T3VQcTYBIXGaN68efMMuYB3TBR0qGtNx7rW+Fy8j7p0j27Xcjc+jdGd6hB9NYLhw4fj6+tL06ZNDb0sHdRqNTNmzMDX15e///6bZs2aUb9+ffbu3Qugt/KFN1G9ghlW5gqCYuJK7e+jpIueXKOmXEY8GYpyRfYejStAaqY8XzkCao1EUEwcVubGItYm0GJw4cumLNzcXsRYLsNIo2TWmMEsW7aM3r17G3pJOiQlJfHhhx8SHx/PkSNHqFq1KpB1g7a1teWzzz7D1dX1rVl9drWtsDI3JijmWb5SyQVFi6TRQGYGGcG7UMrNkFsVbkrCq1DIJKICj3L22TtkaPL3kJAlfs9walyZapaGq4kVFB+KjfCB7s2ttIufWiMR/k8Ao7o1Z8aMGYZejg53796lV69etGzZku3bt+eIOdrY2ODn50dSUhKdOnV6xVn0j11tK5waVyY+NYO78WlI/4spCd4+kjoDmaRB8SiSZ0dWQuxlKjRzINOiaOpOjRVGdG7fmjsJygK5UjMlifjUDAbY1XzzzoJSj8FjfLlx+V4CnsejshJfSjFm6XFELBuDPJd5Z4YiNDSUQYMGMWvWLD7//PNXuuAuXLhA//79iY6O5p133nnLq8yKDX+8MYQrhZhvJsgnkobyqbFYmRlhqUnm/J7VHN7rja2tLRYWFnidjmbZX9fQd6WSjKxElcAbcYXK7i3MBHRB6aL43HFfwK62FZvGd6JHkyqGXkqRojKvxI5zdwy9DC2+vr706dOHX375hdmzZ7827tS2bVu6du3KqlWr3uIK/49K5U0Z2LoWpopi+RMulZgZK5gxvBdnl07i8LLPadusEf/88w9GRkZs3LgRr68moFIVbLLD69ColJz03U1GRkahzpPdPUkgKNZ3jVnv2WJunPfRNiWNTAkWHr7K5XsJBl2HJEmsWLECV1dXDh06pB1j8ybmz5/PTz/9RGJiYhGvMHec24tO92+TlyeIT5kyhTlz5lC3bl327t2Lh/s3fNCyll6TOiVJIv3GOTQKMyR54eLJhZ2ALig9FKsY38uUhYQXQ8ce1Go1bm5u/Pnnn5w4cSJf09arVKlCeHg4V69epWWHLmwNus32kNv8cf4eJ6895lbcc+pXLsc7JkWTAPOOiYKw2ERinqYWyfkFOalZwQxF7EXc3NxYu3YtlStXZvz48WzYsCFrkK51OfbrMTtbJpNhVKEaag0YlSt8VmYtK3MGtyleJUOCt0+xjPG9TGnv9GKo2ENycjIuLi6oVCp2795NhQoV8n2OwyFXmOS5h3KNOiKTyd56IXFZqPF7HQq5jHImRiSmq9/OG948R5Ubh5k2bRojR47k+vXr9O7dm+joaNIkBXvO3+NI+APCYhPR57OqpMlEJi+898cQE9AFxY9ibfFl83I2n0IuI7MUWYDGchkV3jGmQ923N37n3r179OrVi6ZNm7Jjx44CJahsD77Fd4dj0FhUI1PK+Z2oNRKZGomYp6nsv3gfK3OF3mupyoJX4HUYG8n5xLE+F+/Gk1nUXd0kDW2b1OOPlfNx6NQBY2NjqlWrxsnLMWy5ks6Ksw8IjokjNiFd79m2MglAKlxxvDqDzJvnkD29SYUKFahQoUKJr58UFIwSYfG9SGnt9FLYJ9Hcpoa/qmfhhQsXGDRoEDNmzGDOnDkF+uMvSLPxrPEszYqki0Zp9wrkhkyWNfGjvpWC34Jis4bPFjHZyUTZVnxYbAILDkaQrsos8vcvbHcbYzl8Uvkm5wNP4+/vj0KhoFu3bnTr1g1HR0datmxZrDKsBUVHiRO+bEqbi+u9plX5bVzHfB+X356FBw8eZOLEiaxevRpnZ+cCrbUwn31ufUr1xes65stl6NX1VhyQy7L+U2UokSnerptcJgMjmQyZDFRvq8+uRpPVC7QA4iRpNFTNeMD3PavTq1cvzMzMuHHjBv7+/pw9exZ/f3+ePHmCg4ODVgw7dOiAqakofSiNlFjhg9I14qggFl9+exY6vPOQIyu/Yd++fdjb2xd4rYVpGv1yn9KiILeO+WGxCUQ/EUkwJR05UJC/drmkpmfmJWL+PUloaCg9e/Zk8ODBDBgwgCpVssqmHj58SEBAgFYMs2f7ZVuEDg4OBYqDF5b8eHMEeaNECx+UDheXmULOrF62THFqmOdjCiT66gzcetTBrX/7AqwyC32MCTJEMk9pHGhbFjFJe4rcsirp+fjdSyolXNjL88vHqFKlCkOHDqVSpUoEBQXh5+dHy5YtGTx4MIMHD8bW1lZ7XHJyMkFBQVqL8J9//qFx48Y4OjpqrcIaNYqmRRvk35sjyDslXvig5Lu48isEhnQ16mMwbEGEvrCU9IG2Zgo5mVJWslBx/z0XJc8jTiGPu4lljwmoMnl9Eo2kQcpU4fjOY96vZ8off/xBQEAANjY23L9/n2bNmjFixAiqVavG6dOn8fX1pUKFCgwePJhBgwbRuXNnnZhfRkYGoaGh+Pv74+/vT0BAAFZWVjpxQltbW70kzIgJFEVLqRC+bHJzcVmaK/D+566OGBYnCuL6M6SrUV+W09tOKy+JA22lzExkyY8Z6NiGljYVCYqJ49S1x2T1ICl7yDJVqEL3oQ4/RpLCivZjv+GxogqSJJHxYpwxU4WJiQnvNq3Ku9XVHNq2Bl9fX0aOHMnIkSMJCQlh48aNpKWlUblyZWJiYnBwcGDUqFHUqVOH48eP4+Pjw5MnTxgwYACDBw/m/fffz9GzVqPREBkZqRMnTE9Px9HRUWsVtmnTJt+N3Itb4lhppFQJ36sozrHA/FpghnY1TtzyDyeuPi7we2fTrpoxaz9qS+XKld9aSnlJG2grqTP4qZsZwwf15WmKkk4L/0JTvJstFSkyTSaVzv6MkTqNuLg4bt++TdM2Hfn4P79y/7mMW/cfcenfYOJvhpNy+TgDP+jJ2rVrqVKlCg8fPsTLywsvLy9at27NzJkzsbS0ZPPmzezZs4f69esjl8u5ceMGffv2ZfTo0TRu3JgjR47g6+v7yrjgy9y5c0crgv7+/ty5cwd7e3utVWhvb59r6VB2HC8oJg7/608KZNUXZeJYaaNMCB/kz3VgYiQnUyMVeV1YQZ7SDO1q1JfFZ/bgEo98liJJEo0aNaJRo0Y0btxY5/+rVKmiV1EsjIvY6H8u87f1xyJpNFg/v8uFXz5FkiQ+mLmEayaNkRuXzWQGSaOhW31LasYcwtfXF3t7e/7++2+Sk5NRqVRs2bKF4cOHo9Fo2L59O25ubqSkpCBJEpMnT2bJkiWUK1cOpVLJrl27WL58Oc+fP2fmzJkMGzaMY8eOsWnTJi5fvoydnR2JiYncuXMHZ2dnPvroI5o2bcrRo0fx8fHBz88POzs7rUv0xbjgizxNUbLVP4rAiNvEPn5GwuP7PIm+SAMe42SflTRTsWEbtl94kmscL7+8jcSx0kKZET54fSwwO1jcs0kVPu3RiMv3EvJtJSrkWS2W1BqpyPzyhnY16lN4J3drwLNnz4iOjub69es6/0ZHR6NSqXQE8UVhrFat2luvPzxz/elbsxgllZLNY1vTw64BgwYNIljWlHItehT9GxdTJJUSjd8ygg//wZ9//smSJUuYMmUKy5cvp2bNmly7do2hQ4eyadMm3nnnHVJSUvDw8MDT05OMjAyMjY35/vvvmTNnDsbGxkiShL+/P8uXL+fMmTNMmDCB6dOnk5mZyZYtW9i8eTPly5enQYMGxMTEkJyczKhRo/joo49o3Lgxp06dwsfHRycuOHjwYOzt7QmLTXplUoqpQo5Go6GmLIGke9d5VtkOmZEx6Kl+UEygyBtlSviyyS0W2LSGBc7tdNODCxJgtqttlWdxLYhLQl+uxoLWDb5NV2u2KL4siNevX0epVOawFLP/rV69+mtFsaCJA2+rdlTSZNK5Qiq/fzkcR0dHQkND6fejLxeflI6a1fwiy8yg1uMQInzXUblyZQICAjhz5gyurq64u7uzZMkSbG1t8ff3x9ramkOHDtG2bVsgy/U4e/ZsDh8+THp6OpaWlvz888+MHz9e+xu5efMmq1atYvPmzfTs2RM3Nze6dOnCqVOn2LhxI4cOHaJTp05YWVkREhKChYUFH330kTYm+O+//+Lr64uPjw/PrJtj2mU0kswIyQCxWEMkjpVEyqTw5Yf8WIkvCllexTW/GNrig+JRxxcfH68VwpeF8fnz51pRfNlSrFmzJjKZrMDfa0EsRmMjGZIEmZo8Ds7VaDAzUaA6583Ds7v5559/WBemLHXlGJJG8/pidI0GE4Wcmd3rsPj/9cfJyQk/Pz9q1KjB6dOnCQsLY9iwYfznP/9h3759PH/+nNu3b/P06VPc3d2ZO3euNiszMDCQadOmcfPmTVJSUqhZsybr16+nd+/e2rdLTk5my5YtrFixAktLS9zc3BgxYgRpaWl4e3uzadMm7ty5w7vvvotGo8HPzw9bW1s++ugjhg8fzrEbqSw4GIHybRX0vwLRj/TNCOHLI0UlZPnF0DE+KL6dW7JJSEjgxo0buVqKKSkpNGzYUCuINerbct/UhkTKoZIZU8Hc5I3fa0Esxtj4NNb6x+QraUFSKZnTqyHTe7fG6/QNfva7ppu9WEKRycC+vjVn/I5iUq8tZqamOg8eGpUSY2MTWlcx4vy2RYSfOUxkZCT9+/fn3XffJTAwkHr16nHs2DFu375Nv379+OSTT0hISGD37t20aNGCEydO0Lp1a/bv36+ttdNoNOzYsYPZs2ejUqlISkqiRYsWbNq0iXbt2v3f+2s0HD58mBUrVnDlyhWmTp3K1KlTqVq1KhEREWzatIlt27ZRr149OnXqxIMHDzhx8QaWH/4HSW781j/PlymoN6csIYSvhGHorM5sSmrKdVJS0istxcTERK0ovmwp1q5dW6emKz8WoyRRqAeFrzuZ4btzM//UHIxMYaKHT8GwZD/8zBo3jJBLV1iwzY87SZncuHufq5dDqVkOwn038OTeTSZOnIiFhQUrV65k06ZNeHh40LBhQ6KiorC1tcXHx4e4uDj69etH586d6datGzNnzsTFxYWNGzcil8vZtm0bQ4YM0b5/amoqS5YswdPTE5lMRmpqKj169GD9+vXUr19fZ63h4eGsXLmS3bt3M2TIEGbOnEmbNm1QqVQcPXqUTZs2ceLECep/7EF8ORuKQ6mJsPjejBC+EkhxcDVC6SuyTU5OfqWlGB8fT4MGDXLEFCvXqkfgQ4moRymv9AQUqoxCo0H+IIyZ7ctx0aITp6KflZhyjNx48eHniy++wMfHB09PTwYMGIBGo8HW1pZ169bRu3dvVqxYwciRI2nZsiV79+6lS5cufPbZZ1y7do2EhAQSEhJo3bo1O3fuJDU1FWdnZ8zMzPjuu+8YPXo0Tk5OhISEcPPmTUaMGMHq1at1Sgnu3LnD3LlzOXr0KEqlkoyMDEaOHImnp2eOcoWnT5+yfv16fv31Vxo1aoSbmxsDBw7EyMiIkKu3cdlyGakYlJqIGF/eEMJXAilOrsaCxspKGikpKVpRfFkY4+LiqF+/fq6W4jvW1XD66bReLPR78WnFrjF7XjOZQUJSZbDQuZ324Wf79u38+OOPDBo0iEWLFgGwdOlSwsPDkSSJgwcPEhcXxx9//MH8+fO5cOECMpmMXr160bZtWw4ePIhCocDBwYH169ejVquZNGkS165dY9u2bcycOZOUlBSaNWvGtm3bqFKlCj4+PrRpo2sNBQUFMXPmTGJjY3mWqsK8RU9aOn5AfdvmVCxvptMXU6VSsWfPHlasWMEjtRkN+k/llsqC4uKBFlmdeUMIXwmluLkai0sM1BCkpqYSExOTw0qMjo4mtY4Dlg4uUAgX5YtP8cWlGYMMMDPOeyZzxfT73Dv2G/cuB2pfCw8Pp0+fPjRq1IhTp04BWZZVo0aNuHTpEo0aNcLT05Np06YxePBg2rdvj7u7O0+ePKFjx47MmTOHBQsWYGVlRd++ffn5558B+O6779i9ezcHDx5k69atbN26lS+++AJ3d3eUSiX//e9/mT17to7r+sKdZ3yz/TQR8TJkSDrfV259MbcH32L+wStkqDUgM7ylB1nfSe8Woo4vLwjhK8GUNldjaWTGjn85EPao0Od5MW6Tn++9IKODTI1kNKxanhtPUnMIGeoMFMbGvN+8er4ymed85srJkye5efOmdn+VSoWlpSUKhYJnz55hbJyVGDJ27FjatGlDeHg4+/fv59mzZ8TGxtKmTRvOnDlD8+bNCQ0NpXfv3qxatYpPP/0Ua2trxowZg7u7OwBeXl7Mnz8fHx8fYmNjmTRpEl9//TX79u3j0qVLtG3bll27dlGjRo18/x2936wqxyMfGfzhIzeWDbdjWDsbQy+j2COEr4RTVlyNJZWiqrvMfzOG/D8gvSxkN6OukP7wJgdWfJNvK37kyJFcvHiRa9eu6Wzv0KEDCQkJ7Nq1iw4dsiyVwMBAxo8fz/nz57G2tuann35i5syZrF69mu3bt3P27Fnkcjnbt2/H3d0dDw8Ppk2bRvny5Zk5cyZubm4A+Pr68sknn7BlyxYaNGjAkCFD6N69O7Vq1WLJkiUoFAomLdnGwXuKYiliBaGPsPjyhBC+UkJZdjUWZ4q67jKv33thH5AiIyNxcnLi4sWL1KpVK9/rHzhwIHfu3OHSpUs62ydNmsTVq1cZPnw4n332GZA1ab1NmzYsW7aMHTt2sHfvXuLj45EkCScnJ0aNGsW0adMAmD17NmFhYYwYMYL58+cjSRL//e9/mThxIgDBwcEMGTKEhQsXMnz4cMaNG8ejR4+YO3cuU7/xwLjPHGSlqA2ciPHlDSF8AkERUhzqLl+kIA9IGo2GHj16MGLECKZPn16g933vvfdITk7m3LlzOtt//fVX9uzZQ7Vq1di1a5d2u5eXF35+fmzduhUrKysWL17M559/TmRkJN26dSM0NJQ6deqgVqvp06cP7dq1w8LCgl27dvHs2TNWrlzJ8OHDAYiKiqJv376MHTuW77//Hg8PD9asWUOHWeu49LT4xOj0gcjqzBtC+ASCIuRpihKHH/8uVOG5lKni05qxzJg8IdfO/kXNb7/9xrp16wgMDMTIyKhA53BwcMDY2JjTp0/rbA8ICMDV1ZWEhATu3Lmj3Z6cnEydOnUIDw9n3rx5/PHHHyQkJCCTyViwYAHBwcEcPHgQmUxGXFwcHTt2ZOHChZw8eZIrV64QHR3N5s2b6du3LwCPHj1iwIAB2NnZ4eXlxd5Df/FlQEapqIt8GVHH92ZKz6OOQFDMUKlUbFy9gtTof0BTMItPJgP72uUIPn2c+vXrs3DhQuLj4/W80lfz+PFjvv76a9auXVtg0QNIT0/PMc8OwM7OjujoaNLT07l79652u4WFBS4uLmzYsIEVK1aQlpbGsmXLAPjqq6+4ffs23t7eAFSqVIl9+/bx2WefMXnyZKytrenQoQPjxo3jzJkzABiVs2Lsoi38q2hB25lr2XSrHArj0id6AEnpKkMvodgjhE8gKALOnj1Lu3btOHz4MO/c8kfKLNjNyExhxHcfdmTfvn2cPHmSqKgoGjVqxJdffsmDBw/0vOqcfP7554wbNy5H7Vt+SUtLy1X4LCwsqFWrFq1atSIoKEjnNVdXV9avX4+JiQnjx49n/vz5aDQakjIkBn21kjl7wxm7PgA37wsEJZTnx+WrGD58OKtWreLp06d88MEHjJg6hxG/HKfr4hP8euY2idZNSKlQn6uPUotN7Z2+sTQzfNu04o4QPoFAjzx9+pSJEyfi4uLCkCFDCAsL41HEORqnXEajSs/XubLqLptqk02aN2/Oli1bCA0NJT09nebNmzNlyhRu3LhRFJeCn58fAQEBzJs3r9DnUiqVr3TTtmnThqpVqxIYGKiz3c7Ojrp163LgwAFWrFhBZoXavDfPm66LT/BnlBKjhl3wj0lg/8X7LD8exZKrltQcOY9R0+eyf/9+Ap8Y8c6gbwi5l4ZSrSlUnLWkYKaQ07SGhaGXUewRwicQ6AGNRsOGDRto0aIFlpaWTJw4kdWrV6NWq5k7dy5nNi4i858/kFRKkF5/A5bJsjrsvKrZQN26dVm5ciXXrl2jSpUq2NvbM2rUqBwZk3nhaYoSr9M3cPO+wMQt/+DmfQGv0zeIfZrI1KlT+fXXXylXrly+z/syGRkZrzxP27ZtkclkOYQPsqy+NWvW8OelR1T7yIMYZflcRSz9f9vuyyvzoNlInH8+hHHHkWhkitdPgChlSIBzu9qGXkaxR2HoBQgEJZ3Lly8zdepUJEliz549LF26lCtXriCXy1m3bh0TJ06katWqyGICaVT1HSLldTGt3w5NphqZ4v8yKRUyCZVKRa+WtZjxnu0b6y6rVq3KDz/8wJdffsnatWvp27cvbdu2Ze7cuXTr1u21x166m/DKYalmiocsORpBhX6zqdXKoRCfzP+hVCpfKXxt2rTh+PHjXLlyhefPn+tYhs7OzsxZ58uCgxFZIvaGHtCSBBgZEytVp9T6Ml+BTJZVkiJKGd5M2XkUEgj0THJyMrNnz+b9999n/PjxrFmzhokTJ/Lw4UMkScLX15cZM2ZgZmZGSkoKKSkpjOrdlaf7FrH1QxsSz+5AefUMHWuakRZ5is7lnlLnwjr6Wcbmq9mApaUlc+bMISYmhkGDBjF+/HgcHR05dOgQuSVtbw++hcv6YPwiH73SetIgJ6F8XVzWB7M9+FZhPypUKhXly5fP9bU2bdoQFhZGq1at+Pfff3Veu/YknXccxuR/xt2bFLIUYqYw4tMejQy9jBKBED6BIJ9IksSff/5J8+bNiYuLIzw8nHLlytGrVy9q1KiBJEkcP36cTz75hNTUVGrUqEGTJk1wdXVl06ZN1KhRg1qVK5D6rw9PD/7Mlk+6EH94BYrrp5gwejhbt24t0LrMzMyYMmUK165dY/r06XzzzcGYmKEAABQfSURBVDe0bt2aHTt2oFargRd7vL6+iwtkuc3SVJksPBxZYPHLdqWa9ZzCGZprXalxKUrtPjVq1EAmk2FnZ5fD3fnrqWg0soJnk5YVXo4HC16PqOMTCPJBTEwMM2bM4NatW6xZs4bOnTsze/ZsDh06RI0aNbCysmLnzp04OzsTEBDAgAEDuH37NrGxsRw/fhw7OzsWLlxIgwYNcHZ2xsTEhPT0dGxsbLC2tsbf3586depw48YNKlWqVKi1SpLEkSNH8PDw4P79+4z57Fu842qQXoD2XPmd6vF6V2rOps8ffPABLdt3IfBBJp37DiMpXY2pQs5fVx6WNY9lvhB9eAuGsPgEgjygVCpZuHAhnTp1olu3bly4cIGGDRvSo0cPoqKisLCwoHnz5uzfv585c+Zw7tw5Ro8ezcmTJ7WDTzdv3gzA+PHj8ff3p3z58lhbWwNoh6uWL1+ePn368McffxR6zTKZjH79+uHv78+WLVvYey2VNKW6QOdKV2ey+lR0nvbNiytVqdbwV8QjXNYH8+ORSFLbjma/1IEHVdqx/+J9Tlx9zJFwIXqvwkwhx1Qhp3fzanhP7ixEL58I4RMI3sCJEydo3bo1ISEh/Pvvv8ydO5egoCA6duyIvb09UVFRODs7s27dOjw9Pdm9ezdOTk6cOnWKoUOHUrFiRYYNG4aXlxddu3alcuXKhIaGUq1aNSpWrAhkCZ+ZmRm3b99m7NixbNu2Ta/X0LRNRzIqNSpwhqMkwclrT3RclLmRL1eqlOVK9ToTQ6y8MhqZXCfZR5CT6pZmDG1Ti1m9bAn86l28xnQQ7s0CILI6BYJX8OjRI2bPno2/vz8rV65k8ODBSJLEsmXLWLp0KV999RWLFy/Gw8ODCRMm4O3tjYeHB7Vq1aJatWqYm5uzf/9+jh07xsGDB9FoNNpGzFFRUTRv3hylMktI6tati7W1tXZG3cSJE4mOjqZRI/0kK+w5f6/Q55ABe0LvvbIP5KW7WVMgCjbpoOwloxSEFjUtRTsyPSAsPoHgJTIzM1m9ejUtW7akVq1aREREMHjwYJKTkxkxYgQ7d+5k3rx5LFq0iC1btjBhwgTOnDnDlClTUCgUfPHFF/z1119UqFCBYcOG0aZNGzw9PZEkiX79+pGRkcGTJ0+oW7eu1uKrW7cuZmZmhIeHY2xsjIuLC9u3b9fbNV19mFToAu50tYarD5Jf+fqvp6JJVxef6fClEdGVRT8Ii08geIHz58/j6uqKmZkZJ0+epGXLlgBcvXqVoUOH4ujoyOjRo1mwYAHHjh2jXbt2REZGMnToUGQyGZs2bWLKlCnMnz+fr7/+msjISK5fv05oaCjjx4/HxMSEsLAwTE1NqVixojbbMnvSQFhYGJA1jNXFxQV3d3dkekjNT0ovWGwv53lyb732NEXJ6agnb3RvCgqO6MqiP4TFJxAAiYmJzJgxg/79+/Ppp59y+vRprej9+eefdOvWjVmzZlGxYkXWrVun7cX58OFD+vTpg6mpKR4eHmzZsoURI0awfft25s2bR6VKlVi7di3GxsbaGXHZ4mZubq5j8SUnJxMeHg5A+/btMTY2ztG/sqBYmunnGfdVFoc+XKmC1yO6sugPIXyCMo0kSezcuVMbb7ty5Qrjx49HJpOhVquZM2cOs2fPxsfHh1OnThEQEEBAQAD169cnJSWF/v37Y2ZmxpAhQyhfvjwRERG0b9+e+Ph4pkyZQnp6Ohs2bKBq1aq0a9cOgAsXLpCRkQGgFb7atWsTFxdHVFQUKpUKmUzGxx9/rLckl6bVLTFVFO7P/XUWhz5cqYJXI7qy6Bfh6hSUWaKiopg2bRqPHz9mz549dOnSRfvao0ePcHFxwcTEhL///ptJkyZhZWXF8ePHMTc3R61W4+LiglqtpmbNmsyePZsuXbqwf/9+bXzOyMiIHTt2UL58eSZNmqR1WZ47d47q1auTmJioTV4xMTGhSpUqGBsbc/36dZo3b85HH31E27ZtWb58OaamhbvhObevjefxqEKd43UWh75cqYLcEV1Z9Iuw+ARljvT0dNzd3XFwcKBfv36cP39eR/SCgoLo0KEDjo6OrFu3jiFDhtCiRQt2796Nubk5kiQxY8YM7t69S3JyMt7e3kyaNIlZs2Zx9OhRunbtipOTEwCrV68mPj6eMWPGaM8fGRlJkyZNiI+P11p8kBXns7Gx0bpC69Spg52dHYcOHSr0NVcub0p32yoF7uT1JotDX65UQU5EVxb9I4RPUKY4duwYLVu25MqVK1y8eJFZs2ahUGTdtCVJ4tdff2Xw4MGsXr2akSNH0q1bNz7++GNWrlypHcS6ePFiTpw4QWxsLPv37+f3339HqVTi7OzM6tWrWbp0KZDVvPratWs4OjpSo0YNIKu/Z0JCAq1bt+bZs2c6wle3bl0qV66sjfMBeq3pm9ajEWaKgrX/epPFIbIN9c+bpnQICo54TBOUCWJjY5k1axbnz59n1apV9O3bV+f158+fM2XKFC5dukRgYCB3797l3XffZfny5YwePVq7344dO1i1ahWSJLFu3TqMjIxYtGgRwcHBfPHFF3z++efUrp3lDvTy8qJixYpMmDBBe/yVK1ewtLSkadOmBAYGaju3QJbw3b59W0f4nJ2d+fzzz4mLiyt0C7PWNlZ826/p/wrM8x6Py4vFcfvZ80KtrSxSs4IZcakZyMgqFckmu6VbzyZV+LRHI2HpFQFC+ASlGrVazapVq/jhhx9wdXVly5YtOSaBR0dHM2zYMOzs7AgODsbHx4eZM2fi7e1Nz549tfudPn0aNzc3atasyZAhQxgwYAD29vYsWrSIGzducPnyZXbu3AlkWXY7duwAYPDgwdpzhIWFYWRkhK2tba6uzpiYGK2rE7ImL2S3MHN1dS3055FtOSw8fJV09eu7q+S1D+TTFCXBMXGFXltZwkwhZ5xDPZzb1WZP6D2uPkgmKV2FpZkxTWtY4NyutkhkKUKE8AlKLcHBwbi6umJtbU1AQABNmjTJsc+BAwf45JNPcHd3x9XVlWXLlvHLL7/w999/06pVK+1+ERERDB8+nPbt22Nubs5//vMfvv/+e2rXrs24ceNo3bo1np6emJmZAfD7779Tu3ZtHBwcdIQ2PDyc1NTUXIWvbt26JCUlERsbS2pqqnZ+3dixY1m4cKFehA+yxM+uthWrT0Vz8tqTQlscopQh/2QnClUqb/rKTjiCokMIn6DU8ezZM77++msOHDjATz/9xKhRo3IUgWdmZjJv3jw2b97M/v37sbe3x83NjRMnThAQEICNjY123wcPHtCvXz969+6tdYUGBwfz22+/cenSJVatWkW9evUYOHAgkBUr9PLyIikpiXHjxum8b2hoKBqNhmrVquUqfHfu3KFJkyZERkbSoUMHAD744AO9tzCzq22F15gOxKUoC21xiFKG/CFKEwyPED5BqUGSJLZu3cpXX32Fs7MzERERWFnltFbi4uIYPXo0SqWSf//9F0tLS0aMGMGzZ884e/aszjHJycn079+fnj17cuTIEW1B+dixY1mzZg2SJLFo0SICAgK04hocHExcXBympqY4OOhOMA8PD6dhw4akpaVhZGSktRAhy9V5+/ZthgwZQnh4uFb4XmxhNm/ePL1+ZvqwOEQpQ/4QpQmGRwifoFjxNEXJnvP3uPowiaR0NZZmCppWt2R4+9dbIBEREbi6upKamsqBAwfo2LFjrvudP3+eYcOGMXz4cDw8PEhMTKRXr17Y2Nhw9OhRnXo5tVrNiBEjaNy4MYcPH8bb25v69eszefJkunfvztChQ5k4cSITJkzQcaN6eXlhY2ND3759dSzNR48eoVKpaNGiRQ5rD7LieSYmJjRo0EAnzgfw8ccfM2LECL21MNMnopQh74jShOKB+MUKigWvH1z6EM/jUTqDS7N5/vw5CxYsYMOGDcybN4+pU6dqyw5e5rfffmPu3LmsWbMGZ2dnbt26RZ8+fRg4cCCLFy9G/sLIHkmScHV1Ra1WEx4ejru7Oz169ODAgQP4+flx6dIlQkJCOHr0KFevXtUeFxcXh4+PD3K5XJvckk1YWBiVKlXKNb6XTXZJw+HDh3W2t2vXDlNTUwIDA+natWs+PtmiJ6srzEPh7nwNYmBs8UIIn8DgZM1we3WWYXbixV8RjzgT9VR78zhw4AAzZszAwcGBy5cvY2xhzfqzt3JYi4NaVsF97mzOnj3LmTNnaNasGRcuXGDAgAF89dVX2lFBL1qboWGRPMyoh1XNqnRqmISrqytPnjxhypQp7Nq1i/LlyzNjxgx+/PFHLC0ttWvdvHkzrVu3Ri6XU69ePZ3rCA8Px9TU9I3Clz2l4UVkMpm2pq+4CZ8+usKUZEwVctrVsSL0ToIoTSghCOETGJT/G1z6Zmshe3DpgkMReHl58SRoHxs2bKBKkw64H4/mdNRFQNdaNDF6wI+HwrAya8vG/f+lWZOaHDt2jDFjxuDl5cWwYcNeYW1WgJpteJypItHUlCnbz3Pr8FrGjBmDk5MTmzZtwsjISKcji0ajYe3atVStWlWndi+bsLAwlEoltra2PHjwIFfhq1OnDs+fPyc5OZlnz57p1PlltzBbsWJFoVuY6ZPsrjB+kY/K3HSGLNdlVoG5PhKFBG8HIXwCg1HQwaVKtcSDGg54H5nN1cepzFgf/EprMSNTAiNjEi3qMvH3y7xb8Qx/LnZj//79dO3a9Y3WJkbGKNUa/op4CLX7MWpQKxITE/nmm284cOCAjnv0xIkTGBsbExYWxrBhw3KcKiwsjKdPn9K4cWMiIiJeafHdvXuXFi1aEB4erm19BrotzD788MN8fWZFzbQejfC//pQ0VcmfxyeXZZUb5LfGUZQmlByM5uk7TUwgyCP/8Q0n6vGrB5u+Dgk5p64/wS/ikY5r6XWoNRLXE8Ht08m4fNAlX9YmyEBuxLlb8fj/fYy2da2ZOnWqzh5ffvklVatWpWXLlri4uABZ7tOtQbfZFnyboIcS5g07UKleMx7dCEeTkZajg0xsbCwBAQHUq1cPuVyeI0lHo9Gwe/du7fmLC9UrmGFlriAoJg61puSafebGRvz4YStkwN34NIzlMp3rMVPIMZLLeL9ZVZYMs6NX8+qGW6ygwAiLT2AQ9DG49HFyRv4PUpjyW2g89W3uFsjaTFNpuEB9tszQtbju37/P33//jY2NDZ6enrm6T00bZJUnLD8eRYa6PrXLV+TS3QSdZJ3stmXdu3fPkdkJ+m1hpm/y2xXGSCZDJgNVZvEQyuyMy2HtbBjWzka4LksxMkkqa155QXHA6/QNPI9HGSwT0MRIluUGLRASNSqY0axGBW0Cze1T3kSHXyAkJIQfvE/jceTaG2/+IGFurNBxlz18+JBWrVrh7e2Nu7s7/v7+OY5ycXGhe/fueuvkom8u30vIc1eYy/cS8iSUBcHYSIYkQaYk6aU1m6D0IIRPYBDcvC+w/+J9Qy9DL5gp5KQplVTOeEQ1c7hpXKcATaCzEiQ0Gg3lypUj6EI4vae6M8p1do56xpAzf/PDDz8QGBhYhFdVePJqMeVVKOtXLsfmwNv56jGqz9ZsgtKDED6BQZi45R9OXH1s6GXoFUmjQSYv2KQvc2MjvCd3RpJgyLdrUNi0JiNDiUxhot0n+0bt1LgyB5fM4My+bTRu3FhPqzc8eRHK/FiTLwqZcFsKXkQIn8AglCaLTx/IZNCsugU3nz4nLUMFslcLqEwGck0mHRR38P5h+ltcZfFBCJmgMAjhExgEQ8f4SgVqJQs+bMfYLvUMvRKBoEQhhE9gEJ6mKOm6+IQQvkJiLIfR9nVJTFPlq7epQFCWEcInMBiTt/1bJrt96BVJQi6X8WLpXHasK7fepgKBQAifwIBcupuAy/rgUtHtozgi0vQFgtwpWAqaQKAHWttY8W2/ppgbi59hUZDd23Th4Ui2B98y9HIEgmKDuOMIDMqYzvX4tl8zzI2NKGZj5koNaSoNCw9f5fK9BEMvRSAoFgjhExicMZ3r4T25M72bV8PESKhfUZCuzmT1qWhDL0MgKBaIGJ+gWBGXomTU+mCiHqcYeimlDlOFnMCv3hXZnoIyj7D4BMWKSuVNWercGnPj3KeoCwqODNgTes/QyxAIDI4QPkGxQyS9FA3pag1XHxRsDJRAUJoQY4kExZL8jLgR5J2kdJWhlyAQGBzxSC0otryY9GKqkGOmED/XwmJpZmzoJQgEBkdYfIJijV1tK7zGdMjRlPhhUjpXHyRRTGaYlgjMFHKa1rAw9DIEAoMjsjoFJRLR6zP/iKxOgSAL4TsSlEgqlzelu20VUfSeR2SyrDl1QvQEAiF8ghLMtB6NMFOIsoe8YKYw4tMejQy9DIGgWCCET1BiEWUPecPcWM63/ZrqTCQXCMoyIrlFUKLJT9mDTAYmcjkaJFRlICtGTGcQCHJHJLcISgWX7yWw+lQ0J689QUZWsXY22fPpejapwqc9GnH5XgILD0eSpiodiTGmCrlOks/L1yssPYFAFyF8glLFy2UPlmbGNK1hgXM73Ynk24Nv5c1KBIryD6Qw55fJoKdtFewbVHrj9QoEgv9DCJ+gzJJXK7FX82r4RTzKdT+5DJ3p5/lBJgP7+tZcuptYoGG85sZGeE/uLCw6gSCfCOETlHnyaiXmtp+luQLvf+7qiGFeyRaugrhesxJWmonYnUBQAITwCQSFJMttWjjhyrPrVSSsCASFRgifQKAH9CFc+UnQEe5NgaDgCOETCPSEvoQrr65XgUBQMITwCQR6RgiXQFC8EcInEAgEgjKF6PUkEAgEgjKFED6BQCAQlCmE8AkEAoGgTCGETyAQCARlCiF8AoFAIChTCOETCAQCQZlCCJ9AIBAIyhRC+AQCgUBQphDCJxAIBIIyxf8H1E3FSsGWbd8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create a graph in networkx to find its degree distribution\n",
    "G = nx.Graph()\n",
    "G.add_edges_from([tuple(x) for x in save_data])\n",
    "nx.draw(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Degree Distribution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Function to plot the degree distribution of a given graph\n",
    "def plot_degree_dist(G):\n",
    "    degrees = [G.degree(n) for n in G.nodes()]\n",
    "    plt.hist(degrees)\n",
    "    plt.xlabel(\"Degree\")\n",
    "    plt.ylabel(\"Frequency\")\n",
    "    plt.title(\"Degree Distribution\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_degree_dist(G)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### All the other degree measure calculations and network visualizations are done in Gephi. Kindly refer to those files or see the results in the report. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}