TextSummarization_Extractive_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "wA0BF4EeGDFL",
    "outputId": "9812b223-effe-498c-e0af-74805a119f59"
   },
   "outputs": [],
   "source": [
    "# Natural Language Tool Kit (NLTK)\n",
    "import nltk\n",
    "import os\n",
    "\n",
    "# Regular Expression for text preprocessing\n",
    "import re\n",
    "\n",
    "# Heap (priority) queue algorithm to get the top sentences\n",
    "import heapq\n",
    "\n",
    "# NumPy for numerical computing\n",
    "import numpy as np\n",
    "\n",
    "# pandas for creating DataFrames\n",
    "import pandas as pd\n",
    "from tqdm import tqdm\n",
    "# matplotlib for plot\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "showing info https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/index.xml\n",
      "NLTK Downloader\n",
      "---------------------------------------------------------------------------\n",
      "    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit\n",
      "---------------------------------------------------------------------------\n",
      "Downloader> q\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "from nltk import download\n",
    "\n",
    "nltk.download()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 73,
     "resources": {
      "http://localhost:8080/nbextensions/google.colab/files.js": {
       "data": 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       "headers": [
        [
         "content-type",
         "application/javascript"
        ]
       ],
       "ok": true,
       "status": 200,
       "status_text": ""
      }
     }
    },
    "id": "uxC6T7wzGkPM",
    "outputId": "0fe43993-fa9c-4b18-c3a2-1000d3fee3f2"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "     <input type=\"file\" id=\"files-b32cadbc-bed3-422a-9d47-385a0e20b3aa\" name=\"files[]\" multiple disabled\n",
       "        style=\"border:none\" />\n",
       "     <output id=\"result-b32cadbc-bed3-422a-9d47-385a0e20b3aa\">\n",
       "      Upload widget is only available when the cell has been executed in the\n",
       "      current browser session. Please rerun this cell to enable.\n",
       "      </output>\n",
       "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Saving Apple_Acquires_AI_Startup.txt to Apple_Acquires_AI_Startup.txt\n"
     ]
    }
   ],
   "source": [
    "from google.colab import files\n",
    "uploaded = files.upload()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_text_file(text_file_path):\n",
    "    print('Reading file in ', text_file_path)\n",
    "    with open(text_file_path, 'r') as f:\n",
    "        text_data = f.read()\n",
    "    return text_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "id": "Yp7zh9cVGwOq"
   },
   "outputs": [],
   "source": [
    "# load text file\n",
    "with open('0a000f521734500aa360bf6bb2bb31446e4d66cd.story', encoding=\"utf8\", errors='ignore') as f:\n",
    "    file_data = f.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "drDGpOl8LwDf",
    "outputId": "487041ae-a131-4ad0-cba6-cdc02c4b28e8"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rory McIlroy is off to a good start at the Scottish Open. He's hoping for a good finish, too, after missing the cut at the Irish Open.\n",
      "\n",
      "McIlroy shot a course record 7-under-par 64 at Royal Aberdeen on Thursday, and he was actually the second player to better the old mark -- Sweden's Kristoffer Broberg had earlier fired a 65.\n",
      "\n",
      "McIlroy carded eight birdies and one bogey in windy, chilly conditions.\n",
      "\n",
      "\"Going out this morning in these conditions I thought anything in the 60s would be a good score, so to shoot something better than that is pleasing,\" McIlroy was quoted as saying by the European Tour's website.\n",
      "\n",
      "A win Sunday would be the perfect way for former No. 1 McIlroy to prepare for the British Open, which starts next week at Royal Liverpool. He won the last of his two majors in 2012.\n",
      "\n",
      "\"Everything was pretty much on,\" McIlroy said. \"I controlled my ball flight really well, which is the key to me playing well in these conditions and on these courses.\n",
      "\n",
      "\"I've been working the last 10 days on keeping the ball down, hitting easy shots and taking spin off it, and I went out there today and really trusted what I practiced.\"\n",
      "\n",
      "Last year Phil Mickelson used the Scottish Open at Castle Stuart as the springboard to his British Open title and his 68 leaves him well within touching distance of McIlroy.\n",
      "\n",
      "Mickelson needs a jolt of confidence given that 'Lefty' has slipped outside the top 10 in the rankings and hasn't finished in the top 10 on the PGA Tour this season.\n",
      "\n",
      "\"I thought it was tough conditions,\" Mickelson said in an audio interview posted on the European Tour's website. \"I was surprised to see some low scores out there because it didn't seem like it was playing easy, and the wind was pretty strong.\n",
      "\n",
      "\"I felt like I played well and had a good putting day. It was a good day.\"\n",
      "\n",
      "Last year's U.S. Open champion, Justin Rose, was tied for 13th with a 69 but Jonas Blixt -- who tied for second at the Masters -- was well adrift following a 74.\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# view text data\n",
    "print(file_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "Jv0kW_YXMLQ7",
    "outputId": "04819f22-1566-44f7-ea4c-ddf35621e407"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Rory McIlroy is off to a good start at the Scottish Open. He's hoping for a good finish, too, after missing the cut at the Irish Open. McIlroy shot a course record 7-under-par 64 at Royal Aberdeen on Thursday, and he was actually the second player to better the old mark -- Sweden's Kristoffer Broberg had earlier fired a 65. McIlroy carded eight birdies and one bogey in windy, chilly conditions. \"Going out this morning in these conditions I thought anything in the 60s would be a good score, so to shoot something better than that is pleasing,\" McIlroy was quoted as saying by the European Tour's website. A win Sunday would be the perfect way for former No. 1 McIlroy to prepare for the British Open, which starts next week at Royal Liverpool. He won the last of his two majors in 2012. \"Everything was pretty much on,\" McIlroy said. \"I controlled my ball flight really well, which is the key to me playing well in these conditions and on these courses. \"I've been working the last 10 days on keeping the ball down, hitting easy shots and taking spin off it, and I went out there today and really trusted what I practiced.\" Last year Phil Mickelson used the Scottish Open at Castle Stuart as the springboard to his British Open title and his 68 leaves him well within touching distance of McIlroy. Mickelson needs a jolt of confidence given that 'Lefty' has slipped outside the top 10 in the rankings and hasn't finished in the top 10 on the PGA Tour this season. \"I thought it was tough conditions,\" Mickelson said in an audio interview posted on the European Tour's website. \"I was surprised to see some low scores out there because it didn't seem like it was playing easy, and the wind was pretty strong. \"I felt like I played well and had a good putting day. It was a good day.\" Last year's U.S. Open champion, Justin Rose, was tied for 13th with a 69 but Jonas Blixt -- who tied for second at the Masters -- was well adrift following a 74. \n"
     ]
    }
   ],
   "source": [
    "text = file_data\n",
    "text = re.sub(r'\\[[0-9]*\\]',' ',text) # replace reference number i.e. [1], [10], [20] with empty space, if any..\n",
    "text = re.sub(r'\\s+',' ',text) # replace one or more spaces with single space\n",
    "print(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "gTkskJavMT2X",
    "outputId": "8c269216-1c07-48e2-f34f-ba7789d4fd38"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rory mcilroy is off to a good start at the scottish open he s hoping for a good finish too after missing the cut at the irish open mcilroy shot a course record under par at royal aberdeen on thursday and he was actually the second player to better the old mark sweden s kristoffer broberg had earlier fired a mcilroy carded eight birdies and one bogey in windy chilly conditions going out this morning in these conditions i thought anything in the s would be a good score so to shoot something better than that is pleasing mcilroy was quoted as saying by the european tour s website a win sunday would be the perfect way for former no mcilroy to prepare for the british open which starts next week at royal liverpool he won the last of his two majors in everything was pretty much on mcilroy said i controlled my ball flight really well which is the key to me playing well in these conditions and on these courses i ve been working the last days on keeping the ball down hitting easy shots and taking spin off it and i went out there today and really trusted what i practiced last year phil mickelson used the scottish open at castle stuart as the springboard to his british open title and his leaves him well within touching distance of mcilroy mickelson needs a jolt of confidence given that lefty has slipped outside the top in the rankings and hasn t finished in the top on the pga tour this season i thought it was tough conditions mickelson said in an audio interview posted on the european tour s website i was surprised to see some low scores out there because it didn t seem like it was playing easy and the wind was pretty strong i felt like i played well and had a good putting day it was a good day last year s u s open champion justin rose was tied for th with a but jonas blixt who tied for second at the masters was well adrift following a \n"
     ]
    }
   ],
   "source": [
    "# generate clean text\n",
    "clean_text = text.lower() # convert all uppercase characters into lowercase characters\n",
    "\n",
    "# replace characters other than [a-zA-Z0-9], digits & one or more spaces with single space\n",
    "regex_patterns = [r'\\W',r'\\d',r'\\s+']\n",
    "for regex in regex_patterns:\n",
    "    clean_text = re.sub(regex,' ',clean_text)\n",
    "\n",
    "print(clean_text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "lm-Aqcq2MW2i",
    "outputId": "34140b24-fd09-4df5-f26f-d7eb0746ed19"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Rory McIlroy is off to a good start at the Scottish Open.', \"He's hoping for a good finish, too, after missing the cut at the Irish Open.\", \"McIlroy shot a course record 7-under-par 64 at Royal Aberdeen on Thursday, and he was actually the second player to better the old mark -- Sweden's Kristoffer Broberg had earlier fired a 65.\", 'McIlroy carded eight birdies and one bogey in windy, chilly conditions.', '\"Going out this morning in these conditions I thought anything in the 60s would be a good score, so to shoot something better than that is pleasing,\" McIlroy was quoted as saying by the European Tour\\'s website.', 'A win Sunday would be the perfect way for former No.', '1 McIlroy to prepare for the British Open, which starts next week at Royal Liverpool.', 'He won the last of his two majors in 2012.', '\"Everything was pretty much on,\" McIlroy said.', '\"I controlled my ball flight really well, which is the key to me playing well in these conditions and on these courses.', '\"I\\'ve been working the last 10 days on keeping the ball down, hitting easy shots and taking spin off it, and I went out there today and really trusted what I practiced.\"', 'Last year Phil Mickelson used the Scottish Open at Castle Stuart as the springboard to his British Open title and his 68 leaves him well within touching distance of McIlroy.', \"Mickelson needs a jolt of confidence given that 'Lefty' has slipped outside the top 10 in the rankings and hasn't finished in the top 10 on the PGA Tour this season.\", '\"I thought it was tough conditions,\" Mickelson said in an audio interview posted on the European Tour\\'s website.', '\"I was surprised to see some low scores out there because it didn\\'t seem like it was playing easy, and the wind was pretty strong.', '\"I felt like I played well and had a good putting day.', 'It was a good day.\"', \"Last year's U.S. Open champion, Justin Rose, was tied for 13th with a 69 but Jonas Blixt -- who tied for second at the Masters -- was well adrift following a 74.\"]\n"
     ]
    }
   ],
   "source": [
    "# split (tokenize) the sentences\n",
    "sentences = nltk.sent_tokenize(text)\n",
    "print(sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "u9NXXiu1MaVs",
    "outputId": "2b091644-39d8-4202-b9dd-241b918327eb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', \"you're\", \"you've\", \"you'll\", \"you'd\", 'your', 'yours', 'yourself', 'yourselves', 'he', 'him', 'his', 'himself', 'she', \"she's\", 'her', 'hers', 'herself', 'it', \"it's\", 'its', 'itself', 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that', \"that'll\", 'these', 'those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do', 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of', 'at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above', 'below', 'to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then', 'once', 'here', 'there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other', 'some', 'such', 'no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will', 'just', 'don', \"don't\", 'should', \"should've\", 'now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', \"aren't\", 'couldn', \"couldn't\", 'didn', \"didn't\", 'doesn', \"doesn't\", 'hadn', \"hadn't\", 'hasn', \"hasn't\", 'haven', \"haven't\", 'isn', \"isn't\", 'ma', 'mightn', \"mightn't\", 'mustn', \"mustn't\", 'needn', \"needn't\", 'shan', \"shan't\", 'shouldn', \"shouldn't\", 'wasn', \"wasn't\", 'weren', \"weren't\", 'won', \"won't\", 'wouldn', \"wouldn't\"]\n"
     ]
    }
   ],
   "source": [
    "# get stop words list\n",
    "stop_words = nltk.corpus.stopwords.words('english')\n",
    "print(stop_words)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "id": "GKbuwA5HMcSV"
   },
   "outputs": [],
   "source": [
    "# create an empty dictionary to house the word count\n",
    "word_count = {}\n",
    "\n",
    "# loop through tokenized words, remove stop words and save word count to dictionary\n",
    "for word in nltk.word_tokenize(clean_text):\n",
    "    # remove stop words\n",
    "    if word not in stop_words:\n",
    "        # save word count to dictionary\n",
    "        if word not in word_count.keys():\n",
    "            word_count[word] = 1\n",
    "        else:\n",
    "            word_count[word] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 656
    },
    "id": "CBOoRMVGMfDg",
    "outputId": "c4cc82e4-3bdc-478b-acd6-9a6cdedd5097"
   },
   "outputs": [
    {
     "data": {
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N3/u8yv8f/PGm0+lIAEyL+r0scT8DQN2gZpF196clXSrpg5mfHenuq7r7qmPHjm3p8AAAAAAAw0Uvs8iOTT2XMrM5JG0i6e4hPi4AAAAAwDDTS4rsIpKOM7ORioD0VHc/d2gPCwAAAAAw3PQyi+wkSSu9AccCAAAAABjGBjUGEwAAAACAJgSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQMGmGb2DjO71MzuNLM7zGz3N+LAAAAAAADDy6getnlN0tfcfaKZjZY0wcwudvc7h/jYAAAAAADDyIA9mO7+b3efmP49WdJdkt421AcGAAAAABheBjUG08zGS1pJ0vVDcjQAAAAAgGGrlxRZSZKZzS3pdEl7uPuzmZ/vImkXSRo3blxrBzjcjN/7vK7XHvzxptPhSKaPofz8g933zH4uhoP6ORru5/PN/nmkGe8YB2Ooy5Dpcf4H855DaThfK8P52GdmnLdpNyN9h9PjWGakz/9m01MPppnNogguT3L3M3LbuPuR7r6qu686duzYNo8RAAAAADAM9DKLrEk6RtJd7v6zoT8kAAAAAMBw1EsP5nsl7SBpIzO7Jf358BAfFwAAAABgmBlwDKa7XyXJ3oBjAQAAAAAMY4OaRRYAAAAAgCYEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUEmAAAAACAVhBgAgAAAABaQYAJAAAAAGgFASYAAAAAoBUDBphm9jsze9zMbn8jDggAAAAAMDz10oP5e0kfHOLjAAAAAAAMcwMGmO5+haT/vQHHAgAAAAAYxhiDCQAAAABoxai2dmRmu0jaRZLGjRvX1m6HxPi9z+t67cEfbzrN+2ljH8V+mvade73XfQz29al5zyZtvOdg993GsQzVd9vfe+aOcUZ7zyaDfc/B7KOt9xzK77YNQ3me2/o8M/p75rYfymuuzX0P5XsOZVkxVMcyPe/bGf07n9nfs8mb7XMOx/u2v2MZqvPZ33vm9jNcyq3hqrUeTHc/0t1XdfdVx44d29ZuAQAAAADDBCmyAAAAAIBW9LJMyR8kXStpKTP7l5l9dugPCwAAAAAw3Aw4BtPdt30jDgQAAAAAMLyRIgsAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaAUBJgAAAACgFQSYAAAAAIBWEGACAAAAAFpBgAkAAAAAaEVPAaaZfdDM7jGze81s76E+KAAAAADA8DNggGlmIyX9WtKHJC0raVszW3aoDwwAAAAAMLz00oO5uqR73f1+d39F0h8lfWxoDwsAAAAAMNz0EmC+TdLDpf//K70GAAAAAEAfc/f+NzDbStIH3f1z6f87SFrD3b9S224XSbuk/y4l6Z72D7d1C0p6YgZ5nffkPXnP4XcsvCfvORzfc0Y6Ft6T9xyO7zkjHQvvOXO854xoUXcfm/2Ju/f7R9Jaki4s/X8fSfsM9HvD4Y+km2aU13lP3pP3HH7HwnvynsPxPWekY+E9ec/h+J4z0rHwnjPHew63P72kyN4oaUkze6eZzSrpk5LO7uH3AAAAAAAzkVEDbeDur5nZVyRdKGmkpN+5+x1DfmQAAAAAgGFlwABTktz9L5L+MsTHMj0cOQO9znvynrzn8DsW3pP3HI7vOSMdC+/Jew7H95yRjoX3nDnec1gZcJIfAAAAAAB60csYTAAAAAAABkSACQAAgH6Z2Sd6eQ14MzOzEWY2Znofx4yOADMxs+UGse1svbw2IzKz9/by2gD7GGlmX53G4xjZz896OhfpJt+619cH2Nc7M6+tNq37nppjadhPKw/23Hfb9H33d46m1VDfQ21c5y0cw4Dn3szm7HFf2XPR63XRyz3b67HgjTe19+JgK0JTW3Ea4rJiSO7l9FnXntb9TOV7D7o8n0Huz316fA0zibbuz36ecd/N/WnY9l1mdpSZXWRmfyv+DPZYGvZ9spmNMbO5JN0u6U4z+0Yb+36zmunGYJrZrpJOdPenaq9fKWk2Sb+XdJK7P9PPPia6+8q519JN8haVJlBy93827GfLzMsvSBovaf7aPvY3s3Mk1U/YIpJOlHSEu7+U9ru7ux9qZmMl/V/aX7Gvj7r7gvVjl/QhST+S9FZ3/5CZLStpLXc/puHYb3D31XM/y2ybO46tJB0h6Vh3v7O2fflcfETSq/3s/q3uvmrmPW8qv97wXZd9R9JH3P2RtP36kn6t+E7Kxy3Fd9j1nk3qx9KwzWHqPrdl6zRdc6X/zyfpHe4+yczeJem3kt7i7u8xs+UlfVTSB1S7zpuufTO7X9Lpqp0jMztY0g8kvSjpAknLS/qq8hOBTZZ0RuazvVfS/qpetxPTfuuekXSbuz+e+2LMbA5J49z9nqbvpum10s/K10fR2PCcpHslVcoKd5+Y20faz9qqXi/fd/dc48Xako6WNLe7jzOzFSR9XvE9flzd19xOyp+L3Od8StL2ks5399dLr2fv2X6O5ReSviFp0dqx3KT8+d/Z3Teu7fuB8udP5eMf0/5zznT39Wv7uETSnpLWTS9d6e63pp8tLulf7v6ymW2QjuVsSc/W9jvZ3V9tKv9r75crZ/u4+0dr22evqeQAd9+0tv0Jkk6VdF5xfsxs/n72IcV33nX+c8zsZElfkDRFsczYGEmHSlpP3Z/rGUnLSvqg4tlT3v4dmd0/oyhDHqu9vqGkGyR9zd1vaTiucvm0Z8O+J9R/v+leTp/ld5JOdvenBvoO3f1/mWO62d1Xqr2WO7byfn5Wes6vWPpR/TuRu0/spXxKx36p4nusW03Sz1W7P939S2a2u6RjFeXs0ZJWknSgpCVVK0Pc/TO5z9PPs+IeSRe4+2QzO07SOpLmlXRS6dfHSFrW3Vc3s0UlLenuf02feZSifpIrQ+ZROneSLHdcpeP+X27f6bi2TMflkq5y9zNToF4c93ckrSzpB/2V2w3fy9vqx+3uVzTV8SyW8XtXeumeVN7cJ+k6SVcqyq1Br8DQz/mZTdIVkq5x9+dL2+fKxOPd/en0u+NVPRcXSPqa4hr9PzNbUtJS7n5uj8eXuz+fTsfWZKfMa9kyzsy+VtpmdkmbSbrL3T+TOUe/k/RTSRMU5Z8kyd0npAaar0kaJ+l8xbX51rRthbufkXmWH+Dui5rZdopram9FebV8UeeufQe7p3/W789/uPs2tW0PknRK5jt5RtJD7v5a5mczvJkxwPyBYi3PiYqL8UJPX0K6sT4j6ROSFpT0P0UlszBK0iyKB+9a6hSMYyQdrghI9pP0H0lFxc4lfVHS99S5ESy9flfaz6Vp2w3S67NJOk/xsI+duP/UzA6VNFbSH9LL2yge9qdKGuPuO6TPcbO7r2Rm1ygKtgmSFpe0lOLm/FHpM42RtIWkRxU3wrfdfQUzmyxpTknPK++Y9F2ckr7H4kJ6qbRN8TmfKx1HcdPPnva/s6In/XeS/ujuz6bPUJyLHSTdragwvqoIpiVpW8X3/LKkJ9JxlI91r9rrh6XX55W0tqSiVWtDSddI+r6k3ygC2pUVD+mn0ntUCivFOci950PKV+BelPQnxUPizsw2UnyXknSCosJXFDa7pL8XUrUAGpO2e0HxsBmVjvNxSVdLWkXxYD+iqECZ2e3pAVW+zm9QnPcHM69dp7hXKudI0hXuvqKZbaG4nvZUPEzmUdwbTynO/byKStcs6dh+k17bVnHdXyRpbkn7qnMP3afqPfGx9P3NqjgXT9e+t29LOkTSrO7+TjP7tKRvpv39vPZ9bSFpMeXP0SyKa/ISRSAzn+LcziPpgfSZllc8BN/TsA+X9F9J16tzvayVvrP6tXK+opHl7PL5kfSvtK/6NXekqufiekU5sYW6r4s10++vKek0xQP7HjP7uTr3bPlYfttwLFMU56R+LMfUzv8+ivtpiqIMK5eLt0g6yN0PtOihPlUR6DylasXS0p+F05/yPq5P3+sZ6bUtJB3p7oeZ2S2SVlVUBP4i6c+Svpy+m/p1+B9Fub+BSuV/2t9BinvMFPeSKyoEC6tT5pyhKNdfVlXRs3Sluq3q7qP7PmRUTm9L77+WokL1O8X14MpXtl3SCsrfi1er+1pcTNJRinLzXUoVIcU9VX9+PKu45y9If1YubX+dpKUV15AUDR8PSFpf0iuK8qXYz4uSlpD0bkn3l47vbOXLp4UV5+2ctI/NJE1S3FtFT8ZcintyHkV5Xiju5Y+n72MbxX25gaI8NEUlsjj/8yueHXd3fbNRyfyCpDNK9YD9MtuV/U+d5/yi6TVTlFG3pn8XZcWPVC2fvqyo5M6l6n27s+Le/Hft2OdNx76kavdnKstvTc/rDygabfZV3C+/VvW+/ZmiXCl7Jh3j6ooGoiNq9//rqfK8jqIsvVJxb+1S2sdkxXW1VXp9fndfPD1jDlfUo3JlyDPqnLuF035eynz2f6bvMLfvexTXXPl6vk/SuqXjvkxxrc6quDYq3H1M2t+Biufp7OlH8yueNXeWjtslXax8HW83SccpnqOmeA7uqDgXayieKe9VNORMUdwvhblK/84FoE8p8yxXBFLrKsqRyYrzc4WiLlMvE9+tKAOXT+9RPva5FOfn0+qUJUtI+kfmWKy0zZzpzwKKsuJixXc8RtHA+VlJW6pahhb1ti3UXVf4j+Jafzp9P5U6Yd8BxHPkQsV3u42q52hdd583c9wys1NKn/NGRTnzsfRd1OuDTynqzLeU9v2p9FlOlvQrd7+8dP/lguybJY3I3J83uvuctW0npe9uZUU5aIqy8A5F+fdFd78o97lmaO4+0/1RnLwPKB6A9yoKsMXTz0YqHlyPKW6wJyWdKWk5RWX2IUUF42+KgvVSxQ28ZdrXApn3u1vRQ7iQ4mYs/lyoaJUqtnuLoqCYX9Ltmf3cWPr3toqH82vqtNifnY7nkrTNLaXt11cUjP9Ofxd/9lQ8vG5M291c+p1bJB0g6UuSRisKji8qep4uLf25Jv25WvHArf+5ZYDzsb6kRxSV3uMkLVE7F48oCpy7JW1Z+r2bFBWe+p/7+3n9IkmLlPaxiKKRQYqCepIiwBqbOwdpu6Z9H6AoRIrvahdFxfXxdPzl7Z9q+F6vU7TOFu+1SrquHlI8sIo/WyqCoJvTdp9T9JYpfYbs+Sz9u/zd3pW+260yr22ZOUdPKR5AR0v6YPr5rYpK7QdK7/F+RS/1nZKuT6/tmK6ZKenv59PfZ6fPVL8nVpF0uaRfKoKM5dKfH6c/ExQF8M2l4/yPmq/zpnN0q6Sra/fifxSVgtvTa+9RNBQ07eNfki7r8Vq5PnN+blXDNZe5X4rGlecUlY/KdZG2m0dReX5YcX/epahwle/dv/VzLBMa3v+O9PfRigrT7ulYXlb13rtV0lcUD+R9FPfeHg373D39Tm4fj0iaq7TtXJImpX9PTH9/Q9Ku6d9PKH8drqmolNTL//9Jen/mmG7KvaaGMrG23T6Ksvw1Rdn8bPr/k5IOTNuMSdfRdZKuTdfR6B7Pf3Ev3q6obBf3xQ/Te+yjaDRcv3Q+b8zs60ZFJeYORSBZ3v46SSNL245Kx3mjpDtzz6a0n/LxPakoK+rl0xWKHrni9+dW3Of3KMq6hRSNfT9WPIu77uXS745QBLGPKAKSCZK2Lv18R0Wv28HpT7kMeVlRwXyldI6eHeD773rOKxofliv9vygr6uXTCor7sak8P0rSh0v7+ZCk/+Tuz+K7TH8fKmmL9O8XMsd8sCKIKl8nP1c0xj2de1aUjvlASZ+qb1Pb/y2KIK68j9vUUIY0nLvn0nmav/TZj+hn33crdZKU9nVXw3E/poZ7VtJVkjZWXJeLKjoDnpA0Wy/nPr0+QdHrV/z/Xem1UYp6xd6SzlXcP0eoWoa8W1G3vFrd1+ePNfCzfGFFgPtPxfWbKxNvVu2erZdzaZtF05/HG46lfB3tpLiPn1OU7feodn+quQxtqisUZXS5DOmrE6Zt50vn4Z76OUrn7kuKet38xZ/65yxtP1mZ+mC6jqy2793SMf1F8QxZVHENnqOoE51d+nOporG6fH8errhuX1dca8WfBxQB+BmS3l16v2UVZchiGqAOPaP+me4HMN0+eBT0v0gXyG/TBXWjpL8rWv9WTtvdpuiiLn5vhKQHGvZ5qUrBQen16xu2rz+kLV2oyylTkKdjHJf+vaikrRWtHusrguH1FS0go9I2P1DpYVX8Xvp7blUf8Jcpgt6icFpT8cC/NXMcXa8N8F3njmOk4sFypqJg21NRqd9K0Qr48/K5SJ99zeJcKNIY75qK835X7f/npEKmKBjuVbQEnp2OY7lB7Dv3Xd2S+1nT96ooNOcvvTZfem2Whve8TVEoXiRptfTaJEWPyOKl87lVem35zHe7vKKH7NXatf92xYOmfo7OVFTIbla0uo9VPBRuyxzfpHTu7ii9Nk6RwiPVrnPl74k703vVt50o6br6ftJ7Nl3n2XOU3uPW2vu+lNn3Hf3s47Ty5xzgWvmToid9YvoOv64IeI7MXXNqvl92kPT32nZFq/Luiof52YqW3sNUC4AbjmVfxcPue8o8rBUVjbsz53/X0j5XLv1ZI30/xfW2cmm7jyp6eA5R9GLtmjm+2yTNXvr/7MW1lt53W0Wg9c702ku567B2P5bL/3+nz3JwvayQtFjp/+9Mr9Xv5S0VZcWWmT+nD3AdLCBpD0UweLWiknhQ7ftbuZ/zf3/5/Kd9PqyoCD2rTkXoSpWeH6X78C5FxekVVStOVyrKnXlK28+TXrtLpYaQ0n4+quh9KB/fQ4pepXr5dLdKZZqix/nudD7r9/mi/Xx/RXl2j6IRao10Pm/JXEM3Z35/Yua1vdLfh6V91v90PeeVue8VZUVT+XRyw+fJlaHPKFNWpJ8dm77bfyju+9Hp89eft7nPWTwbJiv/rDhXUem/P32W2xQNpZMyfyqNVIrAapL6r/DXz929it7dW8rfRz/7Prd8bSiu23Nqxz1vurZezHz+IkifUP/u03c+d+Z3mup4k3KvKepnRU/bAvX3rm2fO8aJan6WH61oODxTcb+tnr6bXJl4uyLrbNnMe1wjaY7S/heX9HzDseSuo6IBNnftNpWhTXWFpjLk5fTzOxR1kq+k72Du2j4eyPy5v5/P+WLt94tGitNUCjz7KX8WU2ROXKuofxd/Vk7nonx/bqRoTPifqh0w85e/x4bv9paBjmVG/FPOw54ppLzoTytaqI6W9A2PXPnLFelA4929nL4wRdGCUlhTcdGX97ln+uf9ki4zs/NUTaO61Mx+oqi0lV+/zMzOVVzMP1C0rE1R3Mivpm5zk+Tuvryi8L0q5fWb4mb9hKIS+Wt3vzwdz2Qz87TNt8zsZUXwYPFj+4eioJeZPaFoQd1TURFd3MyuVlQat5J0eMo5/6MiNWJbpfQ6M9tUccMUaSVvV+SYL6NocRyZti2O4xVFRcYUvRDHSvqJu19T+k7+ZGa/UBQw3yrOhcUEJadKej6dq0UlfT7l1e+pqDjtUowfUPTM5F6/xMwuVCetZqyiAPiluh0naYKZPZDOW5EesmbDvl+wmNTlT+n3t5L0UjrGhczsyNL2szZ8r7+QdLOZXZrebz3FQ3p1M/ueutOsv6locbva3W80s8UUhdk3FMHK0mb2iKKg3T59pqNr3+3liofPde7+u9Lnv0IReNXP0RZmdoSkL7n7FDN7XpFqcryZfTN9Jikeqv9RtN6dUfpM75T0ZTPbWdIjVh2wX74npOhRvUwxzqZvLG4aHzFC0h1m9ilJI9P3upviQTI6pajUr/PsOUq/s52Z7Vh634fN7Pfp9zeQtJ3iITe+YR8LSloqXV/Fff52xTmt+0L6Xt6mCAYuUlTErpK0U+aam1tRuamci5Ryd0lpv3MoHsj/UaRbf8Td/522vUzS7WZ2vpfGWWeOZU5F+bhS2md5IgNX3N8HS3omnf8iTfsrZjbS3aco0rdGKnqN71Y0nC2bXndJG5nZjxXjy4oxXbtLmmxmv/fq+KmLJF1vZmem7TZXXK9SpNl9QdIP3f0Bi8m6/pm7DlN66gJmNiF9vkmKYHodRS/AjmZ2XemzflVxPd6vTuD1eUn71e7d3dN39hF1eyYzTkiKiu/Oit694xXPjlcV9+luispi+Tsfr/z5n6xS6qfFxGT/80jLutmjdvKQmW2o6CWoPz++pLjPR7j7L9I+/qlIFdtR0i3puinKoh8peiWPq93Psyrumd+7+x6l4/maouX+3lr5dIvinP45bfoRRU/3PJI+ZGZrqXMPjTOzb6t77Ng8isroMZL2dveX03tOkvR2MxuftttOEcC/xcze6+5Xp+3WljTCYmzokuo8x0akv29S3lzqfs6/bGZHq5MKWJQVLzSUT+82s1nd/ZXavh9N1315PxMUqanlsuLL6eefVYwDvd/dXzCzBRT1iHNrz/05zWx1d78hffbV1ElF/qciIKs/Kx5XZCgconhuj1XUkXKp4F82s29JmsPMNlFcV+coriGpVoZYjBN/WqVzZ2ZLKcqvx9K5K87brQ37XkfSXWZ2Q9rvaopz9pyi7PqAx7jDRSTd31SPUZy7EZL+YWZfSd/xCMW1f4niHK+Ytv2H8nW8mzLn/yZ1ypcvSfqcxbClKxT1mPrxvJ67PhXnOvcs/7niHD6tCFqecPfX0nO1XiaeoJQpYWaPqfps+ZoiPf4dZnaSImvn3w3HYsV1ZDFWfZ70e2cr7tOz+05yjFVvKkO/limjl1CU7f/x0rhoMyvqQN9TZIT8J33ODWvnSJLOcffdlLdf5nNeUKsPHqy4fhZUTOJzg6rn+QhV67zymB/ls949l8gGkr6ruG/uVzyn3y/pMXd/KHN8d5jZb2vfyZ0WKcH9zUMyw5oZx2B+TzEmqesEWwyALnLTi0HaqyhywedRp4fxZkVLSjGWqRgf8qLyNsi85oq0jI8rLvTRigLp/NwOiuNNF9vSxTEq0gaLkzirooXzeXcfk9tPKuC+7e6Xpv9vIOlH7r62mY1SBEpW+vzjFZXP96b3uVrR4r63olK1oSJg2UpRSVtLERysqgjk3+Xu+2SOY253f67+en9qn/3u9FDqy6v3GJMyp+IBfk/udY+xY1uqM2HIFYrA+q/uvmHt/RZtOJSDG95zS8V3tZbiu7pOUcD+WPGwXq+0/U2Kh1Xle3X3B81sYUVLvBStt4+Z2d1pX/XB608O8J3Npag8Ti69Nodqk040/G7jObLuAfBS9IDsp3igKn2m7ytag5dQZ5zpPZLOUn6s4c/UuSeKfZyuCDTq9+FnFJXrbysKbimC7R8oGhi6rnPFgzl3jh5RPGgXKL3vuYpUqvXSa1cosh3e2rCPdyrun9tKn2c3RSVJiofSxooGpJ8XD++Cxcx7/1Lek7lzYWa3uPuKtdfudfclMtuer+o461GKsmySu2/X8L5drHnSlQsUqac7KxrhfiXpMHf/VcN+Jkla0TsT3YyU9Jy7z2ExfuoHkn6ieEh/UZ3r6kp3vzltf3z92M1sQTVfh4dI+qm7P2Rmx9YOaR51xqm5xyQSuTJnvDJlors/mPmMP1aMnayP5XpKMZb1iszvbOzul9Rey96LKVD4naIBwhS9lnspKqzLe4zF75uwrf78cPeXUuXvT4rn4l21/S+iTrB7o7s/ml6vP4dGNRzfe3PXubtfnY69mMX1ane/KQWtdaumz1QvK55y9/sz7zm/4vyvp/iur1AMP3inOmWIFBXzsxXjwd6uCHrXlHStu2+UOY5i//tlXh6lqOTXy4oR6pRPpiifDlAEDMuk9y+Ph/597tg9M0FROhZTBDOLpYruOEkLF4FkabvcdfI5RT1mU3c/tXhWqFNON5lFEcxJ0g3u/ngK0D5b+5xHe0MF08wWq587M1tRUXbUz9vTuX2r813XFWOey42i8ysat3LP29UUvVbzKs7NPIoev/tKv/+x9PetDe/5Y0Ug2FdGSfpNqdFjaUXK7x6K9O9l1F2GHK1IXS5fn5/xNDlR7lmeXl9GUe5+VZHS/vbcM97M7lU0jBdpmoXJiu91zfT3dYpn2w/U/bwdqc51NLuih/ZgRQbHmorGYElSqcMjV4bmyuhDFM/Kce5+b/Zbrn7uHUv/XUZxDlcpH0PpWM5Iv7NA+XO6+xMWcwkU19KTikbeg1Qd922K+v6FqtZ5b3D3z1qMiT1e8byaPX0nqyp6WJdL732dotHpY8pP6PNNRUNE+Tv5jaLxes7B1pdnBDNVgJkqJHe4+9KZn62vuEAeVGmQdlEBMLN5JMlj1s0HMrt3d1+stL8Riovr2UEe4+JqmAEs/byrYu/ux6efmeLiXdPd904V1lvc/Xkz215RSf+guy9be89bFYVJfea1H0n6pLt/PXOckzwG0hd/zy3p3+4+ungtbXdz2td2inSNA8zsHYqWrBVUbQ3aXPkKdtHS9oX6Z5e0m7uvaqXZANPneTX3uruv0PC9X6IYb/hM7fV1FOMJjrWYDXduSac1vOfFDd/VTb0eS1OFQVFRXyOzfdMMcz9RfjbSm5UmnVC01M2mThpK4a3p75Nz35Uibbc+AN77aTnMXbc/cve3N23fz37K9+FIZRoG0nZd329/57+f9+spGB/E/uZVtFAu5NVZJMcoHozva/jVFxSVrErrqSKg3bVUCVlFEdj9n6qTVihtt1rtOrxFcR1s5LXeFOuejXEtRW/jvooJDyxtOkbS4e6+tJltrAjMn1I8tCerYXbqFGBuUFSeU2DwSAowD1SkUZ1s0eK+g2qzJabfuSp37E3M7ARPk6E1vWZmG7n736xh5umistKw/3pWx26S3lZUNHs4vqaMjL8rc5+7+w/S75Xvi2xDgrsv19AwdKYyEwi5+7PWPJNmfT/bKILaF1WdWXjPXGOED2LGdTOb4O6rNHxf9e9b7r5/+tlc9esl813dpgiWrvNofFxaUTZtmcrWr9e/ryL4TM88FRW/wZQVDUGqKZ4126VtDlP/sxnvZtHj8boi/W4LRebCVYr7pb79xPJnLx3LjxTp4U+n/z+kuKefVvekO08qzvFl6bV1Fb2T5ytS06ekfYxUPFuk/PW8f+a6mODuqzSdtxwze4u6g90HlZ9s7j+S/s/dJ/S4765ZYXv5vdo+TlfUc+5TBMxXKRqNX+rndyrnKH3GrjI0fZ51FeXsvOrMVvtfVSeWWlERqI9197Uy73e1pA95Z4LFZRR1nPfkrpeGY8xe+6XybFEfYIZaM5tdmWecN8x+nH6nOEdfUmSSHJnZzD0aC3P14UPTNsUMxXMqgujLM9fni+nZVK7znu/u61oE/wcpAtzRiufkQYpy+Fce2RsLKp7vBykaTesHeVzT5xyuZqoUWY90rnvMbFzmQfYzxUQP90h9Ffc/mNlG6rQoyiKdcMX6DZd+drJq08NbzPx6vPIFxFOqzl5oil7B2cxsCcXN8mdFRf/DFtPbd1Xs0/7l7i7prPTw2ltRIVnBYlrzrylaXRYys30VKRNS9OjcL2lfdz8tBVQbKwqoX6v5AVf01r5gZm9VPHhGpRv+FoulLP6tqLD8Rp2H4AGKCu3Zaf8fUBR+2yl6tb7f8H4/T8dU/+yvpMLN0zlYXJHS8Frt9ecUKTaTa5+pCF4vlXSbmV2sTovy6orCeilFQTGLIgWm6T3XUV5ue0tBbT0wfFvpuypa3X8j6RzLp1n/XGmGOUnyWALg5HQsRQ9hefvvpc91mSKgl6I39QJ1rokD099ND+K9FWM5KtdGU4VM0TtYv26fNrPl3P222j62VPWemDX96Fu17Yp/vm5m82Tux/tz17nll8yRIiiq34sjFePZZpVUflB/tmEfRyrGbVVSxL2aTfAexYPtZasuh/AFxT01Qd2ziXp6/W5V75e7FC3ip5nZo+l3Fpb013Qcyyp6lT+kqNg8b9GCW1yHaypNgy7paov0pnLFbqdSmfA+Rc/r4el9flo6xmcVKfDrKVLN91eMIz9MUck8XNGLI0WgdIoiNe5AdaeD32mRfr2JpIMsWr9fUQQvv0z375WKmYz/rCi76sc+VtETPV7dgcG7S5+vqAh/xMzmLSrYkj6QKiDlc9C3G4vW6lyjztvVndXxoqLcKHoymsqf4u/zFee66Nl7RJER8owy93kqE/oaktJ9sbxHj9Q+advXzGxK0/PDo4HyKElHWTS0nizp5xY9m/Mpem2KHg83s//L7Gf1FJBuoWikPVDxXJpSu87HKNJFd1VnNs4p6X2espSSXvOEmX1JEQiXy7IfZb7vG6y07I4ibW8FRVre99X9HJ7boxdXZjabu99tkaqp9L0fnvbV13NqZu9RlCvl9PvfKRoTirLicsVzo9KTWPDaUjelfV9lndTZphTdsjVSsH6zIpjfxSLz5qeZfR+l6nVSBOMfcve+8tVjKYaJiuvwTHf/S/r9Dymef6t5WjIqlad/VZT771Nn1v05FKm8D6t6Pc+lKBdet2oDzhhJ85nZneqct38orotHlVdkOFymuH8Os1iX8GJJf3L3C9Mxvl9RZi+mKDvmtFIDjeWXJZpd0QN1e/r/Oyx6zL5R23YVRbbMxoo6UH0/n1E07pR73psahrdVPH/q9cStlBqM0q8XZejl6fMc6imzIO17gjrPeLn7LRap6VekusE56r6PzjGzDyt6Go9XDNP4lGrXi+IZWS9vlkrfVeU5ma7xYxXnvwhsH1E8r/6u7rrCexTlW/0Zl2XRAXOcOp1Cf1ekW59S2+6d6Z/l+vCeimfQRYrn1/yKMu3rip5Ls2gALYxW5/lSrvMukl57VVHWz6G4dh5w99fNbA1J21s0ehTDxV7OBZMWAfD31N2gt1h92+FipurBlCQzu0KRn3+DqpWp8Z563UrbTlKkMd6uzjjMHRQtUt9Vdw/BnqkVdDtVp3t/RPnUtDkUY6T6biLrtO7upRiAfJh1lh25S7WKfa2QHqG40dd397VK+/quomfgGIuetstVTeX4nqS/pfco9xzcrGgVe5viYVv+vt6teFBspAgUlbbZS1HQfFWRXvEbSacWD0Hv9JzUW4NmUaS+ramM3GdPr79fUfAuqygs3quY3WzWzOs7u/ulqQDsS5F191utmm5R2F9RAE4sHfckRbD+ncx7btPwXU3ObP+0YtbI+tTjr5S/q1T5Xk2lJWtKXDHrZK5XapS7vyfzPV7n7mvmzkVtu/7WjDxN0XP879rrtyo/Jf2JSufOosfAFQXokooAoTweZE6V7gkbeMmAlRX3c7lhQIrK6/fVfZ2fp+4lc6R4cNbvxQmK6/uy0nd1mzpTwtf3sY+iJ6icIv4tdR6SI9Ox3qdIGT689LuTFQ/+/ZQqDu5eHltXXA9d90v6d1EpvkcRCK6gqNisYNECfqIiBecwxYP8dnXGWW+R+2Ilbd5QJhzi7ifVN7YYr7KTp7EoqWw6Kd3nlevTU1qvRQpmXw+E4mH/wfR+/0g/X87dL7JIHd9aUQmYzyNbInd9fFFx7svnZ6f0Zw51liswRfD6mrvXx9X3HW/mc16u/LIBxbIOkxTncJRijPzTivE3fZU6b+jtt4ZsB0W5kLvPH1N3qvkXFSn2F6eyZE11Gk9yZehISZsqejDHK4KnkxTX0QvuvmRt+9xz6A53f7fFOLQ/KSpbpyju6dx1fr4iOHoy/f7n3f2IhvO5h7qXJ3JFOnU9i+Z8Rdm/lbqX3XlY3c/hJxUVuj0U9/pTismHPmwNPaeWH2ZyrqLsvyzdM+un99o583mkSJneS90ZCf9Sd+rsCu5eeT6Z2Sc8Gn+uVwRvN6ZzPVbSRfVr18wuUGZIgsfyZ5MUQWPRCDKHIrh93VN6X2k/L7n77KX/j1A0QEzx7lT9WxT3Vt/1bGYfS9+Lp89YmKwI0j6odN4sAuWLFI3sUrWx0BUNZ5tkgt0RmeN+Tp2yfM70WrHUy6HqXr7n/YpnyuvuvkMKCP+gaKgrb7ujYvjLXIog5Kuq+q/yPbjfUHcZMlkRCNfriS/l7v1U18z14Oae8ZOUbzB2j969zRXX42hFAPlL5YewbJJ5fQ/FM6XynPTImGgqz6TuusJJHlkwvdYJJyhmCS53Ct3i3UuAFD3jufrwC4re3+vTNTeP0kRjivp7YbIiBfowxXVadL4c7e77ps/0Z0UHyoLps72ieFYVPq8IoL+v7nWapbjmvqpBDoOakc1UPZjJvg2v72T5Qdoru/vHS9t938z+rXwPwSzppthc0S3+qsVkOwt6pkVZMVi53kLzqpltq6icFpNGFGMiblf0UJQr9uWJJV5TtOYUraOT03tuL2m99DAYkavcmNkj1t1zMELx8HtSUTgXXHGzfVERqF2rqHA/pKgIvaRST6SZvZoqMUXPyVh1WsSftmgRfkwxkU3uxrN0HPXPrlTxnKBOXv3u7v5Eep+u181sN0Xv0xnp9RPM7Ch3PyzznXw5BUXFcW+cfnSFYrxlfd875r6rVIBPLG+vSK24wTotg1Kcv8p3pahQX+SZNNB0TOdb9IgWx7hV+o4etkwPofKT4jxv1QH9VykmezpbeaOVHwD/mrv/NnOM5et2s4Z9Fk4u3xPu3tSjXex7R3XWR+zj7k9J2s3MRsd/+9LY5nT3b2b2s2fuXvRIo6vsWjEeIrePfdz9XutMdHOsxeQURW/Ca4pZkP9lZot6fhz4MYp76rB0Xicq7q0iPat8vyxk+RSk2TxaT1+zSL19XLHA/cRU8a2Ms1aMC+liZqs1lAlfVXWx9cJaXmqp91iseoLle00Lq6kz/sXd/RzFhFALWaSHS9LOFmPn/5O+i63S99J3fVgpXdHMPpq5DidI2tXMDvTamHAzu9XM5kvXjCxSdUelf3elYCrOf+7eLe6FFxQzYj6nKCcOKG03V+k9cpqyI55suM/f4e4frH2eS5WfsG1fZcpQRSPqpeqeQGiS4nlSl3sOnWMxTvxFxXNhXsXzYGuP8a71dNKHVboO3L3omc3d79kywCK4krp7FJ5094dr52eK8s/hBzx6rr+Xvrd5FJMPzZ8+05fVnTUyVxFcpv1cZmZWLis81sh7TpHtdGjpd2Ux0eC3FQH4ZorshR0VwcgLigaoEeqMJdwk8/H3UTRk/VLRs7uQmf1QcZ6/Y90pzO/x5iEJJykmvzs2/X9nRYP6xtY94dC/rTopyicVQf17zWxlr6bqv6jo8e67nhWNPPdKOsvdf1T7Xq4vn7d03bykCCLLAfM30/N0RBFcJk+m7+3f1j2BzBR1B1ivpb/XdvfVSq+fY2YvuPt2ZnZHOpa/p7pdbtsbUwB4R71Mt84cEfWMhFczZcjIhnpiNvPEYgjDIeruwc1OfOfuX6gd22GK8/PL9NI8imvvK4oGhwVq35fMbOdMefOJhuek1FyejayX0aW6X+UZVz+GkllKweXSinJ6pHX3jBdld1Ef3kHSuhb1Ybn7K6Vjf15Rh902835FOX66xUSEs3snc+qz7l5kHPxb0sfMbId0Da+jaEy/VnF/36aYZK5uDXfPzsEyXM10AWYq+LOtPoqgqQi+rlT0vl1mZuu4+1VSXzf2GEUrxs3uvrN1egiOUDyQb1WkIyyqaKmY0lDJuiUVQGep8wA7SZFOUJ8BTMrPbLWSooX/6bTv+RQV2s8oCtZPKS7+x1KF7QQzO1Ld6X2bKc0Y552Z177hDYu7mtmpiladonD6lKIl6ycW4w5+550emOIh+JbSQ/D4dKz7KipDcytmJS23dpff79LMZ5ei4n2MImB7vbT9Je6+saLHqu81RWVrTU9jPMzsIMXMaheoe7HleVIFe16LtLCfKx7s13r07vXtW5LcvdJabWZLe6RcFT2BRYVsnKLgzVUYT1S+wlBOMys8oxhvd4S6Z5j7i6JiXu8hXFNRuXlZUUm4UNFIcbhF613Rq/M15Rda7s+Glk9ly123sygqLGWTFbPx1e8JpWPsSrdIwXvXWBkzW06R6lNOY9tRMbvihz2lfZXk3ve53INakbKX28cL1p0i/oIitbUobz6taMn8laWGi9rn+ahFlsVqkjZUVD7fI+mQzP3yXeVTkOa3GOt5VPrZc4prfKSkD6tz778/PVhPUL43JVsmKGaA/bo6k5wVFrQYE1ZO+7pV+WBH1j2L7G5m9mnFjI1vVQTG49J73KXabIlpH7l0xety16HHWM/y7KyFUen7OU1x/W8l6YdmdrgyKZiK85+7d69J3/vB6mR1HOmldCiL8fuu6qyafYeouDbqMx3upLiO6vf5KZKWs1pDUlNDgsUYoFwZurznJ5B4QdImqQwc6H6WohJdzCz8vGI+gAUtP5vz/crPxnmWYlzUmun7uFZR5m6p7l6gc9P3/RNFg4MrztMyFgGWp6Bgd8X1s3BDRb0+zn6iOrOvSlEWlt1q3en3/20oK3ZUZ5xXYSdFz9gxZra7x2Qol1sKVIqNLFJSP5z2+cvS749RCo7c/SSLhtSN0/Fursia6GlIQtrHQRaNCUUD6gHufqFFg/t+ivvIFQ2rqygmLSwmYTvc3c+ymCinnqq/jSJVvXw9b6pIBf1uKivKUcljDedtacvPaHq+VYPdbRTPvZ+k4z4rvX61IgNoScV9U75nJWluKw2bSvW2V9Lnn9Wih3p7RYfDWrVti6E3z0qay7obyP/u7ttYdBrIY6ZfU74MebGhnrin8mXoCcqnK6+lzjP+ZKWJ76yWlqsI4FZSZBRI1QC8q1xJrsm83jSTuxRZQ7nybINMGX1iesZ9R51nXFOHkFSdufe9imerq9rpMlnRoSB16sOfKdWHL7X8DMVZVmu4MbPZ3f1IxfCbeqPheRYZGasqxp2+y8zersh0fFtm38tYZhhU0WgzHM2MKbJbq5q3v64idWx/z0/+s6KiNa+ofP9PkX64XCrYN1RcxHc1/P4oxYQHudS0ejqFlHq8Go59/czLR3t3CtPN3pzelUtjHCHphIbjf3s69uKBcqWi4L/IuycLulNRMdhW0QrqigrwHxTpQ8VD8BLv7i3KHetC6lR411BUOOtmSe+1pqJl8CRFJftSxYOweICNURR0ryoK5ZfSe8yuePg8o3go/VxRQO2cvpcr1Zm9btP0/83VaR0t+5Wq4ypOV6RabJzZdjZFBW5tRVrWA5K2Sy1eS6v2XVmMnVhVncJvM6UlM9Ln/rVKM8ylh+R8qs6W+3S9hbXMGgb0N2yba6R5ILOpK58m9kdF6+RT6XPOq3jgza6oEJTTQlzVYH52RVrno4rC+DjVJudSzOqXm0V2OUUv0svqVCJdMVNt3QhFylp5htoDFK2PuX0sp+hlK6eIP6BIk7ksbbex4v75b+b9pAga51InK+CqWit9heVTkJ5SBIxXKmagG+MxZu8v6f+3qTqL4HsVwcrXFQHt5xTf7UENb5tNtVKkIOZSR1dUd69p0UPWNYusYizjXz1SljaUtL3HTH3LqHu2xFy64gXq7qWT4v75m/LlwpbqZB78zd3vtPxEZucrrq8jVb13t1ec+yKrwxXf/2dV/a6lKGtukvQDr6U/mdmJivv6RUUQdr1HdsREdQKzEYr7fw9FL9cS6RiKhqQxih6r8oRtP1CnR6zueuUnkLq8YfsHG15/Ut3DRr6g/H14YcM+PqQoy8o9ZIcqrsWuGcGLX7LoXZ899aQsmH7nfYrv4yJFpXe8up/Df1WUGUUF8K2KCU7ea9Hz8iVFmn1xPg9Pn+/76qTfX6FoVPiyOs+KhxXlwNqqLusxRvHcncsjjfFCRQPso4rU4jXVaexZUFHJXkzR8FCYLOlSd38qBZ5/9GrPcy6F+U51XyfutWFBORYTmFzo7utYZwxxOTB8XVEv+qk6M3iW7/MF1MneWU4RCCym7rGVpij736e4xi9UlJXjlZ9BfBvFtVseBrGm57NLFlPmnvWYRfbDivN6X9p8McX1soyiLnOfOh0OG5e2NXWW+llXEdR/Jr2+naI3/X3pd672SM9cXHFtfzJzPD9SBIb1euJS6bt4hyJ9dQ1F4HWcl1KBrZOu/ITnJ767XJny2fNDabLXiyKwKl5fSPF8XFBxfopr/0JFI0VRxyqf/2Lm1nJdoTxHwQ+LQ0h/u7v/rH58ab+zqXvm3gmemZm79DuVeoviWf5Z9TD7seXHsG/mMZFS0XBYvi9c0cG0kqrDrJ5397ky+7+0/pri82+UeX1YmBkDzFuVz9t/UDHL4j8bfm+MJHlMZPAbRSvhJxWtm7MoTRKT+113/5lllgCp7f9Ud9/aOmPU6vvIPgjS59nAq+ldD7v7XJafUGJOdx+Z2c+fc5/fYtKbk1Vtrd1OUZn6lbtfl7ZbQ9KX3f3TqUDZQVEBuktRIJ2rqDjNp6hAz6Z4KOW+q48qHlZFL8aiaT8bqRbUlI5zHsXD4EDFOKuRiod8ccM/q+jRmVVRUTszvb65Ymr4HTzy9G/zzrTSlTE4NsAsYIqHy4AFeKpIH+TuX7fep4Y/S7F4dpFi9lnFg/o8RQvnwbXtpygChSIVePP0+d+v7utrsqJFvHjAbq1Yc/QTmW2l7skV1lX0dv9pgM/Qx2LCifpEDB9XNEgc6pkZc2u/P0KRlj6busdh/EHRCLRC7XcGNYuspXFOA71W+/kcKs2m11TelI8jtdq+IwWBP1f0ErysqGwtpCibXlPeVuquwJybvoOi0nOzohL82Vw5Yp0xKkUgda5ids8FlXloesOkA9ZJFSsHu7cqGkAW9dosgpafRfZf7j5n+r2VPFJ970/7qMyW6O6/y53Thtd2V5RHb1W1YvusomJ/nLr9yd1Xt8hu2VJRXt3uaQkYqy0bYJ2sjiKl8FOKc3CmOjMyf1LRK/qYonHyu6oGZCPT79TP3TnpOyj2WQyhmDdz3Be4+zIWPXMHKNLovtt0T1n03N6d9r2/0uQa7r57bvuGfeynCNzrw0aWHMx9aKUZyEuvvZCuiZtTo8OWikn5clkdUgw9ubq2j2JplMpzWNG4WK8AFvfBqYrro+hh/5Skedx969J+RyqCxWdrry2tCBAOVPdYrkmKzIArFUHDYYpK9vcV6Ynlxp4dFSm/uR5vWQwR2CZ9pjMVDXffVG2MvDUsueXRoLmluic483SMRysmQuqbLMndv5Q5jgUUPb/7qJoZ9QnFtX+2l2aGNbPfuvsXc8fUpN4AavnlkiYpysT6BDJy943q92z6ndkV9bhVFUHsxYplpIoAaX5Jb3f3Sen/s6l7qZ9sOZSOIzdfw0MeGWp9x2ORrfawujMPiuuxcj8ryoXlVe3BnZQ+R25G/Er5nK7vdynKnPpzfhbF+e/PXxX3xHHKTHDo7v+zaGQ/RlEm1RvaiuPaL/1zKUX9rhia8xFFPW/7AY6jvK+DFfWTF1WazdrdT7R851LP9ZZcw00Pv3NDeoYU4z/nUqw7e7Vqc3V4P7OTD1czY4DZF0Ck/xetPk8pP/nPDirNIqto1d2/VMiNV3S5f9fyExS4ovJfbgmdRVGJ/4k6N/acih6t0Yq0grI/pYIhFzCOUox1KSq9n1Ck155Q3oF1uu93UwRt5dQEKQKY3Ocf5/nB+7MpCoQiIB2n6DkcowjivqtoYXvczH6gqAz8S/GwHq14cD6tTGGSCuaNVO3F2FdR4bpMtcIhPdy2V5yrR9N7fElRGd6gdNyzeSz/srK619S7Jr32J0Va0uvpM5a/i9nSd/YDd68HdLkCfEtFoFxPsZKkA919qdLvllvAxqnas/fP9L7LeadV+MuSdlU8XL6g6kQaUgRra3knFbjoFbtU3RMarJf2/6yiMjBaURFqKnjPVjVo2kJxzX6/tt0PFS2yx2mAhg6LSa22V9xfnywdn6TuSVEsZno8TzEJSW5yrvsUFZ7iPthD0VBxgKo+rUilLXrcyz7p7n1jQCx6lk9WBO45b1P39PBXeGkW2VJ586RirPQoRY/g44ogcc+03WhFReQARS/Gqco8fBXfba4Cc6WqabYvKiYhuMRrae/WmRSi0pvi7os3fE5ZpKbWe6u2VVSQT0sP060UleefK78e7baKnuZLpb5ZZJ9TpHgdqAhwH1dcD7sp7tVH0/sf5O7fNLMz1TnPaynKiM3U3eBSjAnd1Wvjra3aqDeHolfiHkVl/TB1JnWYUxHcXtDwtXzOu7M6shNoKXpDfqU4L7eotP5iClAq585j8ot3Kcrpf6bv83HLj+W8LFVID1Q0en5J0ai3hLrvQ5d0n1cnkDpNEfjMVdt+ccV99c7MfuZUPNdu9urEUs+peh+erGicHKV849VdirLvj+nn2yjO/eqKYRArmNmfJK2vuP7XVvRKK31f1yhm4awHHhMVFd2TvDqc5GZ3H1+rAF6bvoc7M+fzTsX5+oJKs8UrMhLWr712qOI8v5gaSt6lCEzO94YlL8qNPYo1A7e2mIjk3vq25XIvXQeXKhpQiuyKG9LxvKb8kIQiCLhXtQnO0j6vV2ayJM/3eJ2QPtuNqs7yfrriHG6afvZHSeemoKycmrygojz5hjrp0Q8r6jOb195ubUU5N0bVtSpHKyruy6k7S2sWRc/keFWDzv0bGhI+prhfyuXzNYoGn5wvKMqI4rrdVtHgvrble/BywfF9ioyOeubBMZ6ZbC299nGVssvc/UyLzoKV1D3x3ZKqls+fU9QTymMz51bcs/Mos2Rcul5WUNS/1lc0hr5NUffr+yhKDZFm9j5VM8zudPfjLb8E1AGKHuiiwW60pPPcfb3yRtZ/Z8ySHpPKbaF4DuypeAavYKXG3nTOv6woS7uGAtXrFOl9uyY3tM7wpyYbKb73TRTPtKKHu3yvLaa4jm/P7cAbenCHg5kqwDQzUzxk3qbuVp/6eKrCbuqeRfbL5Ypn2vclilbirpZTRZpHuWV7b0WBdm7uDX2Q6+FYTGddT+8aqdKan9bchV/IpTFKnXFexfdVpL/m0nh/qmh9vcFLqZgpIP2aYixX8aB6TtIiucLEOml/5V6MFxW9IPWe5/sVge4Jkn5f3PypQvG6u69aOo7+ZkZdTdXFlscoAuAJad9FoXCMIi2iaz8W68+VC/C/KVoIL8685ZqKgq3SiqVo+T/Tq1PDb64o7LdQZ0a9jyiCjZ8qxnlVKg+p8M2lAr/k1UkKyj0Ed7j7u3PfT33ftUaa7yt6eG7KbO6eSfk2s4sUM2sWqcbfU6RGnpT+XW+s+ZU6168reoD2UVRcXld1IoqRiuutnMY2iyKAqbcSLqBIkynfc8spZmFdvfb6BxTpjeXz1fc5FQ/ljVSdTe+/igp2vbx5f6ogfE7Re7lfqlQeqXh4r6LoubxSnRlwNy3dL5soGl02UVQK+iowinuwK802PXRPVPSYl1N7P6V8b8ruHuOY+6Ry7grle6v2Unfa15hUWb+59J30tfZbZxZZV1yfkxVpvEWa2TyKntd670ARDM2nznleRBGIL6gYR1w5Px7jdedSpNhWxvN5aV22VGn4kiJdqlgHdN/0PV2ufPqtFBWJelbH+Yq1h29Ir62m6BUaoVT59dL6i+nzls/dD1TtvV5IcQ0uorg+Rqu7XF9IcZ43UVRSX1SUyU29hkUr+xXpc7uix7QrzS4d70P110r7qAwbUQT95fvwnvQeTamZvy+/Vfp7DkW5PKuivCgaUb6lWKu6KPM3UzTwzKVo1CiMUZSd7t2NpY8onsPlCuDJHrO3n6hMlo5izOqKVp0t/tlUsS2/NkFxn62ryNwpxgK+kv7kKl/Llhp7TpB0h+I6KJfLpli3styTurqizHuvosH5W+lHByrKyT8qroOubAQzu9rd36sai0l31mi6d2vb9tu7k+ojGynGw31Q8dwqj017qzrXRlFWHqFIF63XzWZTXBMLq9Y7nAKgrtl/rf9ZdHMNCcUs9/Xy+fLSZrMrGp8mKnoqD1V8/65oRPyc0tjjkvGKgOKLqo7DHqMYzzq7dfdU/lcRwPV6P++Ye11xHWXThEu/e667b9ZPffFQdSZJlOK+etrd11U/rJNhdpDimp6iCKrK18uWivWhX06/M5ukSV5qiE+vL+Lu/7Z8r/zF6Xo6WtFIekFxzVo1O20RRUPX/xTP+r7dq3Zvld73UsVwj/LY87XVyVzsarzzaDDcRKUUXHev1Aet/xm0B5zocEY2UwWYUrTAKW7acg/Wmf1sX55Sf3ZFS+0jipbC4uYrxvG8kGmVmqgYG9LVElq8ZpF+66kik01XcfcxFulv//LohdtA8ZA+3jvrt9WPvSvt1SJN4AKPVN99FQXWAd4wkDjdxIcpKgquaMXbzZtTiXNj83JpAk8q0o26ChMz+6siqCr3YnzOS3nr1ukJ2s1LM/pZLGXwNkUF61OqnqPDPTPONP3eqoretkXVSVddwku9DxYDsPdM38ML6lTQi79XVH5s1urufmrt/Y7NHIYrgsLlatsWU36vqk5r5VrKj0ktPKh8KvDnJX3AO5MUjFN8j+sprqWVSu/blDp1hDKpOZ4Z+1La10hVF1WfT/EALu7DqxUV0WcUlf+uFvuG/ebGYfzGe1zYvmGfKyrGuXxL1VTovrFPDb+Xmx7+cUULcWWckKKX/P2KAPbbHgsxT1L0phZjSV4r7fseRcW2uF8mKirSz2fKnHqa7RWKgOVORcv8bU0VwfT7RTl3qZrHMa+g7t6qzRQ9HuMVFatnFeNbllJtDJK7r57ea0t1MjuuKpfFZvZFRYWzaOEtjE776zl1qrTPUxSVzMbxfGm725TGqNUrfF5LNbVOS/os6mR1uKIseVDRIDG34nt8VnHd/1Zxb31LMXvgyxYzVl6k6rm7R91r2fZpCPbmVGapF0VF+Zjatj9W9I6dnrb5fTrWfVOlZ2FFQ4srlsJ4zMxOcPcdavu5R3HPbKOobD+nuD5yDZEys1W8tuB9ChDnVPfzaVZFxb4+LvUud1+m9PsbKBrsXlN+aZQzFPeQp+1HKhruih7SSgUwBU31LJ17FD24f0///pXHxIEvKa7Lk0uvTVLMrL2yxbqfc7j7wRYNruVMivKY8ovU3dgzr9eyCUoNLAen371P0bB0pqR96mWxpR7/zKmQxTIdC6t7YrVPKVKRf6U4t7tLWtXdP5nZR1fvTulncygaRLdRnM9zFUH3SqqmJud6+wc1rCH9zvfUnaV1dflaqW2fa0i4QNGAVimfvTtbZl7FGNgP1l4/0qMB61JVLaho1JxN3cu0fDAFR5WeSsUzv3w/P6e4VqfU9l2uK3ZNfFc6tmJYzqPKN3JYOr4vq3u5rEnKZEbVv5fad5HLMPuwosNgg9J2hyiC6HKd5RR3P7CffVfKJ0Wm0uaKsmJ1RcPUuYpnbq5zaSV3X7i2z67znF5fP3cM6V7Pjdf+raTvF/edpVl7FfXDazK72stTh8CbxcwYYB6nKExuTP+vp532bZpev0ORinmVxTiebyoK4wdL20xR9EqsrnzL6W3Kt4T+UtE7ODrt62lFxez9npkEJz2YVlVU4P6i6M16t7t/uOGzXqHutNf13X2eTCvZsqXvYVZFZam+SHy/rHva7HUVrXTj1Z0m8ITigd1VmKRCq96LsaSiwCwXDre5+15WTddbJ/15h6o9as8qUnazee6pgvQNVSdAOUPxgK2kvUj6r7t/rJ/voT426yYv9aT2x6Ll+kp1euQ+o3i4b1vbtHjIr6j47Kek/39CkYbyBcunApcnNDBFZckU1/TTip7B4rqeU5nUqXScudSceZRJJ1ekoe6naDEsvltvKMTfpebxMx8t7fsyj3F8cyl6Zaek3x+peDi+vZ/9rF1/XfEAr6e9Femd9RlqJygeVn8oB5sWS4xcomhV/7ii4vpJdx9b+4yTFPfevoqKzxctJqH4iVeXRCr/zrcVafXF/fINRdk0XpkJp9y9WKJlp/Q9LKyYEGMDr42FSe99qKLR4nXFeZpX0bBQH694lCI4y/VWPai4hiaqU/kp0gIrKbweSzv8RpGG9gdFKuEs6f3LD9kRivO5ROm1yYpAbw/LL5JuivN3p0q9jR7pcLlJkR5RZymZEYoAb35Fa/pK1kk1XVNx39W/79Hp7+8pw2Oc2zzp38+k9zxTkQmyh2rrL6afV86du8+W27fVxjhZLXOltu1fFCmiJ6X/X6X4zk8pb1YctuJ8f1eRgmqKlLj9JX2l3KhhMa5xkqIHdjFFI8k4xXl8Wpn7UHF9fdrdb0/72DZ9F3NkgvqfKL7z+rjUJdOf8jPhXkWmzENpvyMUYwifTQ2EiyoayKRobBunqPRPVExUcmEpAM31kEhxXr6YfmfTtI9LFM+fSaXXTlSaHV1RjnzW3e+wWgZI6Tivcve1S68N2MBiZp+XdLqnpbnS7zWNTfyQuhdxv8KaGzv3UvdkSbt7Zl0+y/fuSHENrK4I2E6RdHm6TnONzg+o+rzdRp05G36qKIsq4+oyxy3LTza3gKT3emYW3YaGhEfT7zzv7gs2lc8Ws93erggYuuqR/TSwrOXu19ZeO1eD6KlskhpajlP3xHf3KO7Rt7r7hywy39aqNzqlfWyo6ljwiYp6yeeUyYyqX8+l/Zyp3jPMJih6R4ve0Cvc/eZ+PufnlC+fzlJnNus5FVk0j1m1c2l5RdmxoAbReGmZDpT0ena8tqKTYuW0TdGz/DPF87JSZ1PcZ/9RJ2vpKu9hwsUZ2cwYYN6tqKw8pOoA22wLjEW++fGKi0WKisA1ilbCopV1E3V6B3Itp2eru2X7HsVD9xHvTBqxjuIB1zXDVPp5URh/Q1GpPsz6nzE21+JytLsvWW8l82rPlaXPsqYiFWt3ry2Dkis4rZ8JTSyTJpACoJ4Kk7S/ordD6gQ1+ymfrvcHdz+9v/3V9n2Vu69Te228qmkvV0vaw2PmuXJBc727/ze11O2nUo+MosD7hiKgPkURMB6mGHuWa636njpBmisqYqsqejG6UjAULbXreGfZhlnUz+LEaZvKJAWKnsWckz2TOtXPfk9Xdzr5CorCvG9R9bTtpco37Cyg7vEzUhTCq6lTgG+rCAQ3kvQ+70x+NLeiIjRXw372UPdMcC5pPe9Oe7tbURl7UNUH9aOK4GAbRSPGsek951D0gr9fEZzNkY6jrd63VdS5/icpzltuwqmNFUFZPc3204rK6vmqVgK3VvfMnbtKOtHz68PWJzl7TvF9rubdE1qdqMysqOlnd0taplShH6EIjrI9DfXvwt0nNJRxByt6sZZQaSymRzrcNeqeFOlyReaB1FlL+PT0p1zh+7ji3tw3d0xeXY5ke4+JJfZs2PZnpW3XVzxfLpC0izIp0u7+t8xuZN1jnI5Nnzk3YdscimfR7xQNKksproWllB/fu5pi3b8n0+8foLi+X1dkcEjqW9boIUUv+UYeEwzNp7gnZlX+PnxKMcb7U+pMWrSZUnp5/fmkKANz41K3UKfR6Yr0TDhZ3Y1FhyqClM+rM6v3xYp05dcV9+zO6X1OVYx7K9+3/bIYJtDXeKZoqBiZ3uPriuvtoBSo7OHNY8o3UDwfivv8JsW9untp88meJsZKvzuforK8jaKh9q2qjisbrThfcynqKX3lnrt/tNfP2J+G+1CKoPuvXlofN23/dXU3Or9L+QXo36q4D7+m2ri6Ho6ryC4Yld7vftVm0e2nIUFSNUug1qA1UjHT7KmK66z8mYse6Q0U5eqp5evJ8pPRfFPRIFPJPPCGpeL6+cwTlJ/47nFF+fDtVCcbpcgyaAoOu8aCK8rJrswod/9Fwz429GqG2dKKdO+D1Z0i/A3vYYhOaV/3qFo+LaCof3T11HuM++zrXEoNfvMpMwlX+d6qvV/jJEFWS7NOjUM/VycVuDBa0ei0SK7OZpFRtq6izvlhRfrxir1+JzOamTHArBcmxaDmyQ2/slNpO6Vtv6p4CM+tai/g6V6b/MWiV+8GZZaMUDxQNq0VYI8rUtPOUnUtnDMsBt3/QvGQ/4jHLGTZQfdNBtNKlh7sqgewTUFtvWU2VRhvzRVgVk333VCRnnW8x3p75V7lojf1BUljSy1ncygq2Ocon663g2KSmQFb69L+NlYELZeo9r1ntm3qqf284tyWxwNuoAhoCuMUDQ2j1T35jykC9K7JGNJ3uZ2kd3r0xIxTBP/Hp8/1v7TdfIqJBJaq7yP9fBZF6/t6iofuXxUPyPI4r83S36uomjrV36Q9Lun+emFo0ev+VPpc5ZTP8hiZ2RWV99ckbey18TNp+0nqXtLiZkUraO49pzTsJztWyCI9cUVVU9xeUKTQVB7UxX7TOdlMkQozRWkG3PQ5Riuu2+wDzDq9hsWEFtcqWuXvrx9z6RjracYjFLMF/qy23deVT7Pdr2HXH/fqhCEbKR6O2bEf5XsiNcIUy6AcKekwL/USZFrCb1ZUDg9NZdGXvdPbtKjiu/9I03fQi6JMNLOPuPs5tZ9tou5JkQ5UBFzj1fluXXFuulJNiwpfasyQZ9aQtB7G1Vj3+otzK+6DrnPXw2eeR1F+fVudidauVTyvipT/7RTX5VmKxrKiYeIsVcf3jlY8m0YperxfSa/PqijzLnf3fWrvXzR+9j0bUoPja7n7MP28PGnRFu7+YsPz6QlFb31lTHHax1vUSZErhmTckmksmuD9p/GtoAgwP6h4/q6pGM+1V2mbbGNBsr6i7JeiPNtMMRNvUw9WPXOqGFP+BWVmbXf3TRr28zlF8Pl2RS/76ophBquXNpus+O76Uuxr+5hd+WVqfqzqslvLS/qou/+g4VgWVVzPf7WYO+AqxXnskuoz/Y5NK+33Dnd/t2XG1dW228jd/2bVCWTK2SMXZI6jK8U87avpOzmu9O/XFLPBdk2GY51ZzrdVBP7bKBogTlE8b89O1+gWimB0V8U9uV59X00BTxPLp/JOkvSyd8/y3TcErLb9JaqN41fch2sqGsYrmVEDHE85w2wlRb3i3epOEa4st9PD57xG3eXTQ+pMTtg3Rtbdt7JBdi5l3q+/DpR6mvVGimy3V9Q9i/S1ytTZ0rGuqyhLVlCMD73K+0kRntHNdAFmnQ08qPk6Ravm2elnmyl6J+5VXCxHe6eV1T0/BvM45ZeMWFzRy/EHdVJC1lOnxaMoWNxjgoplFQ+ga939DxbTWm/t7gfV3vMqr65Z1fej9P+d1D0+Z+7SdiPSZ15fkSZZXwbl8nrQaJadQOloRcU7N35oLkUvy3hFZeZsZdJ9034/pnjQLVorTK5O300uXe8BDa617kRFr94d6rREj1Y0DFQesIretNxSNyPrwX4m6C5SIc5XdXxb4WxFL0BlkhKLRalfV3cPwW8UvZ6Xpn2tJ+l73jBRVHpIz6K4Jn+o6KXbSjGRQHEsC6a/T8scn/dTabpWKZ08/f+9ikD8TkUvyXmqBu/lXpz5Fa395yg/y/Fl6l7S4jLF+d7V0xjiVLAflN4rt58jlBkrZGa7KVo+b1Unxe1Or2UTWGfs0/KKCumHFZPBnKSoTHxekeYiRUXvM14ba5b2c50yvYbevJTEruqkGU9R515+ydN4xv6k4PT4hsaLg1SdufNoRc/JuLRJ+Vp0xX24cW0flygaPJZQ99ppKynf+3R5ev2GtN3q6X2fkSTvoXfFYpKeA1Wd0XZBZdLhUqVvK0Uj0prp+K5TlCNfV7R+96UP91P5fI8iAJg/7eO/inTPOwY63tI+9lP3JCen+SAyBkr7qo9xmqgo0xdT9NgX57XImKg/415VdXzvbIpe5+vTfv6ctvtYen1txXj28v37jOL7uDEFmksqeoDPUPU+vEqdYSVSZ9Ki4h7NBfW/UgQK9THFH1GmR0HRMLKiUmORoqK3lOK5Vq/wLKAI7p5QXPdneaTBj5D0Dy+NfeyngSa+yNJkHOk7vFDxrNhLtUDFG9a2y1X4m4KA9LPbFPfQdYqy/62K72TH2qanStq8oTHkNGWWqVF8h99Qb+sm/p+i931+d1/cYrzZsupkbVn579wzJAV19XFshyueb5urNq6uXlaa2fc9JuPJpfzOrZjQptf5K7Lfibvvbg1pkrXfX0oxaeESpdeWVGQ/bKeYIbgImpfzmEzpZUXjSuX+9IZloZqY2e+Un/huMUUD1sXpHl1TsVxaV++zNY/jv8YbMuYajqUpw+yXXluv0tJSQoPY9/HKl0+TJBVL3s2rNEbW+lmqp8f3y3WgvKAYj50bf3+3ooyqz5vymqKuUamzKeqrN0r6kbv/ucevYYY20weYA7EYx1hef3BuRQvImYq0noUUF8gx6rRQFcaoU/HJLRnRNZahxJseQmkf8ymtnTeVH62+v3KhXKSJHaV42H9LAyyDkvaRnUDJIrXq3+rMxrqdYgzVIhbLU7zoA6f7vuDuc9Zeu1VR+OXS9d7Ta2td+tk93j1b2eXKLxzvmYLmVkWAdIPiYS5FZXZ1j/Uui1a8zRQB5ljFNOx9u1EnrXYZRaD5fOnn23u+h+CLirSf4mF7vbs/lvuMxe94d8vvU4pKUH1A/3HKpEcrxortUNvHCYpgsp5OvqOihbZuDnXSF0coKvfzqzrdecEV5/jH6lQm11O0DN6nuOeKsYJrKoKwV2u/X6QB36DMWKFcMJPuiSnqflCvoMhAOEaRtVBUzCdJeqp4YFv0UP3G82NNc63M/a0PeK9qacbp9Z+rM46u3Co7MbOPq5RvvHgg956KRqDnigqODTz5zwcy+zhZ8Z3lep+a0uqKz3B5fz8vfab9FD2usyoahEYoKqG5dLiu8dCWSY8f4D2vUTRcXZr+v4GiUlAeP/fLAXaznhrWX+z1ONLvnKnMGKf0s77PmsqotXIVOOse37u54nqatbbpKMW1tpOiMvST9PoYxbCRmxQ9hscpys2n1EmllTqpilInm6eiv8qedY8pvlv5hr5jVG0sWkVxfeTS0r+qWPOw633NbBnPjD/vRSorb1Rcg6eouq7lfxWT5eQaaaTMrO31bUu/UyyNdYukR939w2b2imLyIlNnFtORikC6nqGzm3WWvCgaz2ZR3Ksje32GpvdfXfH8Kba9TTFpVLnh/ofqNDCUx4Kbop50vKrryM6rOG9zqTOubi7FuNr/KMPScmS1125T3G/j1dv8FU3fyc+Ub9Q4Vp3GC1c8g/b26KldVJ1ezCmK62GsuoPmiwYTvDWxhonvFI0chylm5r09HcNW/dUhM/fcYYqy/AzvIXhI33suw2wBz3TG1F8bYN8DNvik83Z7vW43NSzGcC+vaqPwg4oGziZ/VmbeFEWH0w6Khpw5FfWXZxTnbD1F4+4/FJ052ay74WDUwJvMHCxSFf7mnUkY5lVUohZStQfkVUVr518U+d9Pm9nzioJ0a8VYk8JkxQPsClXHn0xRBPcblt5/L48Z5g5TKqjKlZT0ILhMtbXzLKYY7y91pyfuvnPDj443s5vUWQZlS3e/s2HbCZIezhzPR2sV59+a2SEWEzt8WtHKI6VULqumuBS9qa+Y2Ufd/ey0zcckPeGdRZ8Pt5iKvEjXu8yiZb/4LtdU6hlpcI2ZLVv7bHO6+w1mlU681yRdbDEZT72ndryix6B4QI6Q9JxFT/IG6rTijZD0T8+sM5gKzfvSNqNLP3rVoheq+DxjFQ/oX6eHUq8tXlPMbHFP40EsUjX/q+h9OswidbkY0L+8l1p43f0pM1tJqvYCWPQOr6JI8ThO1XTy1RWBUb1n+gHF/WKK73SSoqX4Jq/NpJYCm6MVY8eeUhTq3/QYuP8JRcVhnGKa82cVrcRLqDob5SaKykt5bFKFmW2qak/DPxXXTDFeqnhQv83zqaxTyq3BHhODVdIcrbNu4flmtreqE1rUp+Mve1j563fF9Pf+pddcnfu17H5JV5tZpfHC3d+Ze8NMMPZ5xfX9VsW9XjSKTFakxuYq6Tcoro33pON/2qKn+xVFT/uG9d8ZpDnc/RKLm7QIcM9VlBk5f7VIIS4H5IdY9CQMmB6fzOWlcUUeExbVx81vqUhXnU9xzdat6e5uZsX9nB1334Nflo8l7asvc8VidtNZFJ/1PsW9UuHuP7RYYqkI+nb2Utqbmc3p7i9YTHK3R/pMn1RnorFnFZOH/FVRBpikFdz9LmuetfyhtO+FVE1B7GJmX1F1XOrvFPfioV7tPXpSMbnaLxUT6BVuskjV/qF3z676clNQ2xRcWqT21lNHL1JnVu+Risr7/orv8hgz290j7f56RTA+MgWh5Uaatymu4cPUmSzwajUvISZJ/0p1lbMkbWQxc/x/FZXeK9VpeOxP0Rj3tEVD6GOKes896XlQXEtbqXmJnpfd/ZXiWZmeCa44Z+UMsIcUZf14RY9935Aii3Fsny3t81KLjJ9ry4GHuz9vZlcqrqWcM8zsY94Z47awpMXd/bVUtzjMU4P2VHwn31aMNa+nSY5OZfuS6lzPns73LIpG50+UnxsW4zCLoPl5DXAfDMIoxb3xs/Q+IxXZYosrehDfoejJXEMNMUA/99yfFWNgX0tlS9F4N6bhWIo1YF+zWC1hMUWQ9opVU87HKO6bnnlm+Q4rjZE1s/MUda5T69tNDXf/Rrp+iiyTw939rP5+x8xez1x3/1RkN7xd3Wsg36cop9dVNKysr2gwG5YIMDv289IU+Slw3E+R+nZ9KrilCIZOUlwgH0/bXiLpEjP7luKGq886eWzaR7mF+Birzrq5YmrdeUTNhfg86UH9OUV6R7E20zQzs7crHmx9M4Mqeq/+pWgFfd7TWCEze6e753o91pC0nZk9pGrv23MW42GKyvS2irSCtRQP/Qcs0n2LXtHyGKyiN3UTRQD067SPpyTta5mFbtNreyoeaouZ2dVKrXX9fAVrSrolBT5Fr8eiuQdsqaApWgg/4f0vdVNuxdvZOq14XXKFZtrHvYoehoXM7Ifps3xH0hoWM7r21KKoaG291MyKB914RQXmClXTGN8j6WUzm8876dH7Kx4ObmbPFoemCBaOVFQkypWJ7RSViXXNbB8vjSXoJ6iZqO6KwzWK3ul1FQ0si0u62SK74LPuflqqZG2o6EX9rSLwONWiF7FIm/2uYhKReiXzoNTYMWfax9GK7/cGd99P0Wpddn8mGJWky83sCFVT3i8rrlGPXsUJqrbof770+64Yh5Vzf9pXPc14MAFa8fCqNF5YzLS3p2prQ6o7GDsh/fmKpF/UgoZrc2/o7l9N71G0hB+rNCuqmb1uZvP4tM2U97KldEZFufFI+hyVoMGih30HxTlxRSpeYaxisqtZVJ2opSnAvD997vI4uXqDw7OKjIamVPhF07Uyr0V64WcUGSOD4u6XWnWMkxTjWo+XpBR4f0xRvo1qKivStVnp9TaztRSVm7kVDTiXKa6Luzwz+VNyd+3/36ndh4coGhh/qMiGeKsiMFtU0Zqfm+RjdsU9WB9TfL5VG/q2kfQXM6tPelXYRN0TgHwo89pAjlLKbJGk1KD5jDrPrdck/SdVLIte03+nMmN9RVrf62pupOl54h13L7JDvmcxcdo8irTgtRTP86LB8HpJP/Pu2bYl6cgU7H5HUXbPrWiku1hRri9tMdPyA4oyPefyVP+Zw2Js5ZcUwx3WlbSydzLA9lMMX1gvff7ynBUTzWxN74xj+5DivlrcomGzHIxXsplqzpJ0WnpevyN9pn9aQ4N2g+I72bf0nXxXcW91NWpYdSzsLUpBg+JeqwxhSp9tFkW5sV4Kyi+XdKOZreZphYNpcIkiS6pIh55D0QAyd3pWzqfqszLXCJG951Rt9O7FTenZfJQ6nS+PKnpDy/t6Vv3Xz7pYdWm5IpaZS50GmWKMbC4rajDvUx9yVlyHu5jZ64qhbD9x999kfv3VzHW3kCJGuM7dN7S0BrJFR85sivrOlYqJB3tK351RkSKbWD5lLbf+4NXuflPDPtZX9JI8KHVmnfSYCnxldS8Zcbo6s25eqGgd+pw6S0f08ZgY5DZl1s6rH/dUfv6LlZlcQJGy2dNYIWuejc3UPRur3H3zhmPpysUvXrM0sYbi4VUoX8TFA/vDiorwB9QZWH2YN6wz1HDs71Dkxq+tzrqW20n6Ui5IcfdvWn4pjewi5J5fSmCsGsbspIKo6CG4JPUQTFYUqq+ps7RLY4uiRW/g19J+nlakcb1f8RCqpDGa2aeVSY9WTJLTFQhZPp38PEW61paKXo6i4WGEIjAtvqsJiunGf6+G9UstP6vdi56fdVINr7vnp/CXRypUkRI1tyJTobxMR+EiZYJRRetsE/d+Ut4HYs3pQIerx6nnS/uqTE5jDWtDKiqruQfEc97D+pBp3/WW8CuVZkW1aLRbSVGRLfeo7lbfTz+fZTVFYDJvOpYxitS3pUvbjFRcA8tafr2yL7r7u+r77uc951OM8yvv4/teXbJmN0X6+mKqpn0X5dPziqB+wElOBjiW7Bgnd9+qtt3Nil79uRTZFi9q4LLiesW1fXa6lzZS9AxmAzjPT4h2c8N9OEIRcP41/XxDxTCAz9b30c9nP0gROJVTAddUdX3gYrKWedO/7y39bLRiTFlT0NT0vkVa6s0+cOroZupe1/J7iuu+3khzgKJMPlSDm/wrN1nUP1UtKxdSTJJXLpsvcve1LdNgbNHg+6i617V1dy9nSxTbj1B8z33Xs6JsvEsxxvDVtN1sion/lrbu2evvUvdyIS8qztuL6szUOlmRDt7UACQz+7I6E3d9XvG9Djh/xUAseh1XUG0NaEV9YzVF0LBiETQoGru6simsOheCFI1fWyjOXdFAX9yfg02bz47jTfvquhd9cGMqL/FManf9tYbfHa9Ohtmi0xo8WXVpuVMV12oxh0ZRf/D0p78gcJpYZMpd45k0XMvPm3KFu78jnZPyGsgbuPt/2z6+6YkezI6bzOxniok3pAhOJkhSCiizQWXNzxRrWNanh14l10KsSNv4eNr2l4qKzxhV02yLCsliipSbCxUViBst0hsbU/4Gaay7l8dh/t7M9lAUeisVx+7uj1r0RnTJFRipcneQ19aNNLOrzGxWr40HSw5Tdy/Wb83sRnUq0l9WtNKerPwCt8erk7olRdBygiJI6unYFQX9+6x7XctsS7hFuttq6iylsbvFRDdFK96RinP7nPIL7Sr97imKsZrlMTvyGB9Z6SFw98G2KBbfywHp/59SpGY9ploao8fU3uX06K+5+3lmtrJleo6VTyd/iyJwfFrVnrOPKhpXigL/e4qZ9Ear2mP4rKRvWfesdqulIPhci56gTSQdlCowIyQ9XHt9V8UkTq9btdd/tOJcFJMxvJAaUZ5UVLCKyRxmV1w78ysmyyiC0e+b2U8lne/u2XFlOdbQa+ju5+a29+ae7fOVJrNKL/1dcf10BZhWnZxGZvaEomV1cXffxqKlVR7pkKYIWnKTbhTX7qaSjkrXRHZmSTW3hEvRQ9hYSeyRp8+0qKI3bKyiRyHXwy5Fhe5ZdVIoPyVpFutOj89K5dkZPkDPsac0TTP7rbt/MbOf4xRT0H9joPccwFbqzo64yDrDDIohBi9NRVkhd3/YOkME1lcEp0VLfNH4UDyjcufykYb781V3f9LMRpjZCI+e2F8M8vA2SQ19fe9rMdFLvaH4SEWD5APqcUmCATxhvaeOfkLxvL5d0oYWaZSHKMZg7m+1nt20z1+rM279k4o6RNPkX/spNQAryoFZFDM1361SWakIJvsm+HH351IZJMVkTPXy/E+K587Timd/rqGtj8fs3kep1gtvZrkMsJPTM7V+v32wYfcfVKRZ9xuQWDXl0hQB6i2KYL3ScJUC6sbgMt1HXQ13ivNzhDqNGkem/b/k7i+ZmSzGgN5tMdHPOdadki/F86s8bOhvFuujf6i/z9ij581sZe9MfLeqIkB/suFeHJB1xt8vaPnU7vr2jWMp089+mupLFYNshP2vpyFT6jyn585tWASB6tQ3WpPKsQ0afnanOkNs5JGtV9QHz1IMt3pKUdd8JcUgRaP75ZL292G8FiYBZseuinSIP6b/X6xOpa1XsxTBpSS5+98tUiGavGhm67j7VR652RMVk4Zke0Lc/TR1epOUWjU/PshjbPKkRTpPeXKBJyWNdp/6sUIe4wtyE2jkxoMtqmi9HGvd+fnjFetG1SvSH1B3hfF4xSQ/y5b2UYzn6JlFPvx1Sr0uZrae0sLXmSDlakUrZnkpjeMUD/sV03G9RVG4j1N+DUwpBr/3jdlRpB51pcyY2dLpIZYtyD0zyUuS/V7cfT2rpTFKmi0VkHem9zxK0SP509xbKp9OfnLa/l3F76XKzZbuvmPp9/9mMWnRrp5Zv9TMil6w+li+rRUVkEM80toXUbRqXlV7/UJFZenDyi8bsm8q9H+iqFC5Yobo8qQ6v7DohS7OXRGM/k/SIlZNeZf6f0Acq2hsKCaGeURxb2cDTGteN3S0RwriPpLkkZY3JbOdFJWhPb06Oc1RigfbHOpUmBdXNBTkgrHj1Bw0dHH3QxqORe5+XHrfceVyc5BOUqcVu0hv3cvdv9ywfe76f1nd6fHZnoNUnvWc2psLLpPscILB9laoe4xTkW5aTtd8UJEmK8tkWPSz74fNbG1FSvws6szQ/UXFc2e8qsu65DTdn3tZ9KJdIekki+W5umY4zbFYY66/crjuNcXMwntI+l+poXCMma3h7tf38r4lX1bvqaP1cez/s0j3LO7ReiPNSK9OoHeixbrXTXINwK8qGlX6ykpFXaMcdKyiOK8flzSPVec9GKNoGHq7uzcFfUr7uU3N577ICjlfnQywL3gnA2y7tI8x7v6smpeKW1jSjladC0He3ZNab0A5QxHg3yvpS2a2U+74Gt7z98o33L2aa9SQdF9D0LBN2qxcHrni+VWfC+ElxazGRYPe1f08x/uzuyJFuGgUWCQdx13K34u96Hf8fWb7ch0hl2H29dJrs6uzTNlg7Gc9jp3vLwhsg9dmpS9YfpZzpTKhnNZ+gaLufbuizJSiV/tYRfbXsESA2bGMohVwVPrzEUUv0mAe+DelC74862R/PZ9flHRcqphKkYb5/vpGlpkAqMwHkVLWj8+oM7mAK1p7dpK0s037WKGbUyB5mjqVqVkVlelyr9ZoRQvUKHXn5z/YUJFuCiTr4znWUG+90GXLKiqC6yoCj2UUD5rblQ9SJilSsYpW8eK8/lqdJUb2txivc5E6rW5lxeQCxZidR9WZCbBsT8W08D9VvgBvagnMfS+TLdIk6wP6K9z9/9Lfjb03ucqEdcaI3ZG2eULRa1R/wE6R9BOLCZl+56VJNryfsXwqPexTQV8U9uXX/644dydYNaVsQYsUsaJH93SLtfhmV4z9KQL4oidolKSzMsHoUel76/UB0dRr2KTpgby69T6ZVdPkNF9XPODeYdHj8F7Fd/ybhntrVU19RaWPmX1E0XMzq6R3mtmKioC85zFoqrZiF/tdxMw+rOj1eL22fe76P1dxP/XqOUm3WQwrmKrUXuVn3J0a9TFOz0k60zOTtpnZj5XJsPBMunvyBUW65tsUDSAXKSrKZ6nTs1U0tmSDDHd/QZn708w+oJhh9quK5+Q8auh9yDhZMbb1QOXL4XLQU55w57eq9tQ9l3mtF/O5eyWzxSIVNtfDNsKq49jnV5QhD9UaaRZW9D6eZ4Ob/OuVTAPwvzMNhouoE3SYImj7jaKOM6+q8x5MlvR/knYys+W8ttxPzWbp7yKAKg+xcamnDLCT037q49OlTo9uYfa0bdcETJ6f9OVId/+3mf2+n/fPWbBc31B8H0sonwFztbsXY20rQYPnM7Rkse52fS6ESxUNeMX9cqyZneYN6472452qTny3hqLBLHsv9rJDdz9U0qEW45sHHH9f1BEsPyTht949VOlqiwnhBmNnRVZST2Pnm4LAIXasOrOcb6g45r7GWC/NlJ7qQ+UOo+9bpNEOW4zBTCzyub+uHtdCa9jHbMpMD+2ZxY1L22+lGIg/r6Ji6PWWOUsLhpvZjsoHmMf3eoz9HPtxkvaoPQgPUVRIpmmskOXXpXJvXk9x0fr3bjGD7sdVW8NJMbtmeYHbe9VZ26wYz+FK6xLVKswDHfcoxedfX3FOF1CMtzhY3WsbHa+odB+k6vpGeytmPO1aYsQzS1JYw5gdry0YX9q+pwK8VOmaJfO9/FeRstrv4u61Vu4uuZbD9Hu5ZR1+rXg436/4rhZVFL43KdLCioL4d4rK1qfVMJavv2PKHEtfSpmXxhQrKnpfU/Sm/Z911vF7Iv1q0RN0iCIl8YJUsSyPn/qd97iGXfpONlZUTla26DX8g/ewpmVpHzcogoDDFGN271A/U89bTDI2UdVK4CqKltNLVFob0t2fsO7Fo9dQTHLx6V6PcYDjn6BoCLnMB1hnr599bKzItii3Yi+vmM1xTcW5PdY7wxZy47zuUZxf76dHo/yeO2Ze9jbK4WlhaYyTooGra8I2RaBSzrAYqUitHewYr0Gdo4Z9dC1JYO3NJ1AeT1+ecCc3Nm1qloaZqBivfHv6/ycV4yRzY5CbxrGfrup6n/9UlM25zBb3hqwmi/TLJRXl14GKBuB/KeowlbIy/SnGid3jnXGRa7l7V5CQGpOWUG1d29z3ZZmxfLlz3IZUb7rQ3Tdo+Pm7FHW58Sp1ovgg0i8z9Y2NFedtUGnW1s8EauqeC2FnRY/3S+l355B0iw9yiQ3rzCMw4Bj5wRrsvs3sVEUHQdGo9SlF8P2F0mZF4+2hg/mslllabkZjZhPcfRUrraFZvJbZ9lpl1hF397Xe2KNuDz2YHf9tqsQPQtP00E3+rE5LcONMV6XjulPxsBqvampSGxWb5b00SYV3UnkmahrHCjW0pl9qZl3BQXoIHG1mn/Dq+ouzKmZzW9yqs8KeolhipFxhvE/xMLxHzeM6evGsIvXuZ4o0pifT8dwiaVUzW0KRKvVnRSvs7xWV2qJnslhKY0/LLzGS0zRmp+nazKUxHq9OL1phM/Wjx4aU8ixoayvGVkrRMneNmsfT5XrOXlNUjMoVniJAOErSURaTZp2saP27S1GB2q6/ILgHTWOKi5TVojB/RNGg8HupMmHAZorKyyEpwCuPn+pLeZf6HhAvNhzHfsr3GmZZZ3kTqfNAnkdRJpyp6A2arOhd+nvtd0/wWLf0SkXZUZynKxQV0ovd/VRF+rPM7LbUIzKLOvdWXyNN0zFOhVfd/Rmrdtw23RdNsq3Y7r6dRWbItorZcB9WXFebafCpWHXzphb9PhZLeLxhrJ8xTorxc0eoM958e8X1LeUzLJreI7ccx0cV18RAPVtN+yzSWxfP9QQNdn+Z/Y9UBB9dE6gpZv/dTfGZlI6jcfKcfmwl6U9m9ilFo9enlck8kqLx15qX+Sr3Jo2biuOQux9iMSfAs4qy9LuKBrArVWowTIHutqVfXdnMisbpLSwmGXlRUSYtr+hZHsx4QLPS5HwWqdW9ju/rNwj17jTRORWztTY5TTFW/Gh1UpE3NLN/KJ5dJvU/wZU6s9BX6hu5hrsBNA2F+LS650KYV9FDWzQyzKZ+6oX9aEq/bsNg992UYVb0VkudxtueJ/hKckvLzWj6Zjm3mPDuETVnapQzGk1RTu/0hhzlEKEHM2loCW/slWnYx3WS3ueZmdoath9sa3151qyp6mXtZ9+3KmaxKvdgXq6ouC2hzsxmxXv23OrbUFH5gjoTkfSl/Ln7Xg2toQ8oHpzvUGcNp30V40QbTct3Y7HW5jqKtRxfUQRRVyhmI1vZzPZSjIEq1tSa4vkZ47ZTpDqtrAgIt1JM339aZtvcZ+96rfSzO2sFePa1NpnZRYrZkf+d/r+IYla/bNpfPz1nP1GtlVnR0rmpInAYn37nJEVF7kc+iNk+G46lmNF3YjqHxcRBr7j7qlbtZX5K0YP5Z0WB/xHFbLEbKyows6s6M+ZOiuC+nPK+Y0Nv4omK3vAXFZXc6939ifp2pe0fUCd97FXFA3l/xQQC9Rbied39E6XfvVMxbf35isaAIo26sFf6nMVEFEXlLZtq20Z5k47rGEV5u7fint5NMY79C/3+YnUf2VZsi7Th7RVpyo8qvp91FDNabjCNx53rfWu8R4eCRRpeoZ4iv6rXJvRJjWI/Tn8uUynDwt1PaXiPy5WW4/CYffI2RaPQ/aW/++3ZyuxzHsU6mtn01oF+vxcWY8B3dfd/1l5fSNEQt5HiO7tEkbXzePdeBnyPdykac/4paQt3b2pIGux+c1kizyjKmUEfZ2m/5XFysyvKsInuvpWlnl2LtcA3UwRXV3gmw6af/a+iyDYpKsdPSfpMJjjM/e6lmZfL1/TY0v9HKILEA7xhqZxcD5FFZtNHvGFt08w+PqGYULFS3+jl89T2c1PmuXKropyrP7eLcagXKz7vJornzb+k3lPwLYZ4PJJ+f2XFM+aGwZzPtvZtDVkwijGdvaTO9ncsdymy/wbsYZ9eLD/L+cHez7hvi7H08hiXPKzRg9kxqHzuBrN780xtOYNtCe4ab9Sin0q61szqqTxXtLDv3Lph67l7eS26cg7+62Y2rqggWKR+LeyR9z+f1FnDyVtI+2ji7n+W9GeLKcc/pBjkvpekSZZfU+tCy8wY5+4nWaQDbqwoBDfv50HXNGanSRtjTQfrHV4dz/AfRc9xk88olnUoJu+5UvFAOEQxy1/RKuqK2WQvVQTx5Zl2/2QxydK0OtXyY4q3te6JbkYq1nArJgX5nqKXb4JisoP6JDc7uPsKPT4gjlEEzZuotK5nvWes5JvqXrD+BfU2mdXhisr0YqpeG0WgWfxdvh/lDWl5LdpVMYnGy4qe6gsVE3kNRlcrdmrQWErROPGR0rV6SupNmirpnv+UYrxouRwerU6v4BvC+x/jJMtP2LaZIgh4StFA8U13f6yft5nT3W+wTg/zZoo02w9Pw3E/owiYth1o22kwn6Q70vOkXA5/VJF+P1Wse0Kb+RVlxPWpN7CNiu1nFVkURdC1gaK8eaeZ7e9pAiDrrMnXdZjK9My5+661zzKvOhMaFhMRbqpYguwZ63c4eDd3nyBphdSAUJznXn+3uJa3VncZd4Di2p1PUV7OK+kv6f2anGNmX1JkdhSdBU/2Glwm+3rva0b2p2kCtdsyz+1Jqs5vcdkg36vQNLFWGwa771XUnWF2j2Ls5+vqTFLZ7yz/DaYlO+2N4urMcl7cZ0epNLeLVSe0VOn12EHKiByO6MFMmlrCB7mPqxUtp8VMbasq1l5cq7Zd8aAapUG0BFsLvawDHP+y6qTy/M1bSj2w/LphtynGNkpROV9F0i/dfSkz+6Ai9fRyxXeyriKdbgmbhjWcpuK4T1f0mt6nCLSvVGe9w641tdJruTGyPVfUrWHMjldnFixfQ7kxlYMaazpYZvYrxXVbVGC3kXRvvRJT2r5YEHm8OsHykpLm8FoBZGZzlxtphoJFSlllTHF67TuKyYguUqSsjlBMBvRy+r3ZFJWAlVQdP7WIYvH0/d19zUEcx0jV1vX0fGpf49gXxTJFPY2TtOYlM3JByuFt9co0sdKsltOwj1wr9lh3X7iFQ6y/16KKCTS6et8kTfJpS92e2mPKjXFaRFF5K5ZVuEYRzC+hKEvXVWrUUPRUZRs1LCbs+ooi6FjZYjmOz7p7G0spDJkUWJYrvaYYG7++IoCrrzGcnQsgs99F+/t5Gz37FrNdf9rd/5P+/xZFVsS2inM1TWNfS+8zi6Tb0/P2x5I2V/RGra4I4s7tpfHWzLZ39xObKsmDqRz3U8adpJhk5wylBlpFemZTD+YDmZfnV6T/nqUe6k7WsH7rYOsbZvZ+xbOv/FzZWTHBUn0s+OT0/xmqF25a9HPP/FWR7fdQadupyryyyEwo38//7GfzN5T1kHVozWtcF9t2TV41XBBgJhYT0fxkWoKqVJE+RZ01oxaRtE29tW1qH1Qp3WBpdRaTTZv39oCcXhoqKscrJuIxRQ7+A4oKejF+bSHFLKk3S5pDkbZzm4Yg7aOf495LUdEuWlRXUqTm3NywfSsV9V4C/TeistMfi1SuYt3HK9z9zH62zU2g9RtJn6v1hMpifOr/qXuChlav8dTLWN7//yzSKvsmulGk8WytaAmXomJzirsf2LDP3ypm3CzPlpytxFj3up5XeT8pcE0VHsWDdVonrclOxODu9XG8rbJIjVtYMWbwFE+TpgxyH7n74Ly2KuIzulylzMyelvROr03Y5u6fGWSjxuqKtQDXVvR6PqA4T9mK/YzCGiYQUtwXdyuu7/0Vs9fe5e6DGj9rMcHcHV5a7kTSMj745U5y+66cT4tujDvcfdlpaVA1s3NUnVl3GUmnuvve6efzS3rGYxmeOSWN8f57t4v97uLuRzZVkgdTOe6njBspaS13fz5tN5eicXcww3SOzbzcWHeyFtNM688VjwnUcuXWnxQNCa8O9fN7erMWJpCzWHLpp4psomJ5prvc/d1DcMhTxcyucvfcMn0zBQLMpKElfFAtSdbJ2y9PDz3ovP1+9j/Dz5qVY7EExZGqVlS26yeQ/pxi1sO3q7NQ8vWK8TOVXiN3v2gIj7veojpKMdnQnMqnJ92t6VBRn9GVC9lSRWe0Yn3QG1RqUVasV3elIi2sbz1Hz6yNOZXH8nlFuu5LimB3tnQ8H+3n18qBdLZxIe2750qMmf1c0Wv/smJykysUlaZsY0RThWeA4+6poaEhSBnScbyl91lYEcRvoxifcooPflr++j4PUQTuZ9R7yNuQGlcOUu8ThgyZhora+e4+f227mxVpvINp1JgoaUdFhs0IRYrsHr30bE0PVlofU5F1UigmEHp3CmCKcn0WxUzUPWcdpPe5WZE6X6Q9jpB0Uz2oncrP8BtF/aHIYPm4YgzeNxS9ihtO5X7XL/33NcWcCu9y979Zw+zgTb17tf0e5O7ftJiUr2tOgUEeY1MZN0LSat6ZXXV2STd6mpWzYV/F0ljlnq2eJ0NMQXZXlspg6xtmdom7bzzQa+n14xWB/9mqNlAO2xTJJtbObN63Khri/5ru6w0lbe/ug50saMhYD1mHZvbLzK+qtG1PY29nRASYSVOP0GBakppSPNp6ILfRyzo9WWndsPT/tdXdU3W8RfrnaorWvhUtxkD+yN2zD8IhPN5Ki6piXMxfFD1ZOedPr4r6G2mwFexaIbt42n4HRU9l32Zpn7N5ZlmPFo/9H4rW8CfS//ubLMV9EFPbT+XxFGvVfV2ddT1z27VS4WnY95AuR9LjMSynGN+8jbvPOo37mqwIpKYoKqmtBoA2yAlDhlJDRe0VRYA1JT2Pignb/qrBNWospgh0yrOlfsQHMb7ujWQDTCBknQm+rlAEoo8peqUGNdbYWlrupGHfpggqiyVmrpZ0ehsNJRbptsUM5zdI+pK7fy/VK8pjsYv7ZcCskfSsXl4xY+00BdhNZZyk9ygaOsqZJL9391807Gc/xdjVZRX3xTsUa552rSc6VJX3FATPqagzbCD1zUQ+RjHOtCtroI1e4OGiqb5d6LFhtJhA6VZJK7n769aw/Nv0Yj1kHVp+2as+7n7c0B3h0CLAbFFTioe3NE6wjV7W6SGliOynTuroVYrUuHeoNsmLu+9mnTGbt0haw2O9yTve6NSHflpU/5drSZ4RKupvhMFWsBsK2Y+4+4K17SYpWm+vcff+FhefamZ2gWKpgBdqr/e6IHR/+y4qahUNPZhfUQvrerahjdbkqXzfZRQ9lx9XTORxiqIyPdWzZb4RzOxqd3/vwFsOvYaK2paKmRr/ophQpzKOu9dGjbTtkMyWOj2kzJjTFUHL7xXLBezr7kcMcj9nKCZgKS93sqG7b97WsbbNYgKdn6gzg/C6igaGW1UNLJX+3VPPmZn9RNFQOLdi0rG+H6ndRp2VVVpf3PvPJLlNMXfCzYosqGUVn/VH9W2HqvJusWzRHor0zUfU+W6fVYwf/dVQvO/MxMz+qmhsOFCR+fS4oqc7u2rD9DA1WYcWq0/Ih3guijcCAWaLmgKStlpU2uhlnR7M7GJFAX9iemk7SftImjvXMmsxC+TOigJ6I0Va7SzuPtWzF06NflpUv6kIUp5J2023CXemh8FWsMuFbA9pbB9T9D69rFiOo+2KykqKtcmuVzU1d2FNY3qzmX289N/ZFWtuPpprJbeYbbiyVt300kZr8lS+77WKoPJUd390oO0HsV9TlDHvdPcDzOwdkhZx9xsG+NVe93+o4no5S0Mw2VobLDOOu9dGDeueLXUhRaD6sjS4JapmFCmNdSuP9V6ndV+tLXeS2feQpF+nXp5NimO0GOt+myJIXkrRs1lZjsndtx/E/v/s7h+blmNsS6mBeoLiWbKRIs17EXUCPUkx9n6Ij2VX73HMcsqmyTVQDmkWzXCVMuJeUpzT7RRL5Jzkab3yGcFgsg4t0rpPUExIZZL+q5jw646hPcqhQ4DZoqFMYxvOLLPep5k9I2lpr03ykvnd9RUFxwXu/soQHmbPLNZZW0mxXtXziuBIiiU2uszoDQCDNdgKdrmQHSiNLW0/v2KW2fL4mctbOvYbFD3olVndFEs2tJrenCq1V81ILaozA4vJll6XtJG7L2Ox1MBF7r7aAL/a6/4HNWHIjKLXRo3p1eAw1IqUuul9HP0ZqvRrM7vNS2MWU9l0q7svl1KGN/XO0JXRiomy2lgW6g2VGpeOlvQ1xZI0+yvSUmdRjDvt21Rxzw71UkyNQ4Ey25XX7qysDT7Ux4ihMZisQzO7RtK33f3S9P8NFEPDhm39gXUwW5TS7s4o/f/fivV+ZnYXmdknJZ2qaCVdRNEifmeq8JeDlMqkJW0FFi27Ut3ro44erhWvqTBGkQ71/tJrruY1Y9eUdIvF9PHlQrbr+7L8BE/XKNYQbcMs7t41pb6ZbWLtrye6pKInAiVmdqq7b53pKWsr5X8Nj9mqb1bs8Ckzm6ZxnWXuvnNb+3ojufshPW73Zi3H/mr5dYp76sUys73c/WAzO0z5nqY2xvP9p+3gMjnfYgmU8tJSxTCEtyjG7RZeSa/1bKh6XgfL3d3MVnf3pyUdnoZEjJH0Rc8s0TTUzOwERYBxi6rrPXcFmN69tmd5bXDUzCjX3AAGs1bnXEVwKUnuflnqpR22CDAxZKyzGLQp0l1PSP8eoehhKAcNxSQvw8GnFKkLt0uSxQLsO0iaKcZVTEUFezCF7O7qTPC0oaUJngb5fv0538x2kXSOqimy2QWhiyCol6DHuhc/f0wxcQ2qimUhNhui/b9qsRxHMcvnWFV7q6eJmb1d0mHqTMRypaTd3f1fbb0HhsQ2imviS7XXe+3FKgK/m5SfRbwNN5nZKWo//dolHaHOOMYjFY13UgQ7N6ShKVKaRGeQ+z9YM8jEV5Immtlq7n6juz+YXnvDg8tkVUnL5oYC1aXMncKI9LvzDNWBvQnMSNdc1iAb6+63WA6vWPN8e0Vq97BFiizeEJm0x6Pc/V21bVqZiW+oWcyu+CdVZ1fczGfQ2RXbNpQVbBviCZ4svwi3S+p3+v9eHhQp7awY+7e/mY1TTKJCK/QbyMy2UwQTK0s6TtJWkr7j07iMQmn/F0s6WdWKwHbuvkkb+8fQsPbWKV5N0rdUTXtso+d9yNKvrWFt0OKY0yQ6PS3H1LD/GWniq7slLaFIiX1e7WVGTM2xnCZpt4GGAqVtH1CnQf5VxTjpvrXBUTUjXXPTwsxOcPcdzGxPRZlSNAJdIen7ntYzHo4IMDHkammPjysCTVfMKloYLenqwUwsMD3Zm2h2xcEaygq2zSATPE2NoR7792aR6ent+5FaSnFKPd8bp31e0mYrt+WXqeh6DTMWMztVLaxTbGb3KNalrIzjnhFTi22ASdXaet7OSBNfNY0hnh7nJ03cs6Jq6z3XhwKlbbdWzDXxbOrJWlnSAd7SOupvFtZZt3V9zSDX3LQwszslvU/S+YqG7mJWZ0lDPxHVUCLAxJCz0rqWikJhVUUKzjqlzSbP6DdSZszYsJ9dcWq8URXsoZjgyWJx9S9KKiawuEzSEe7+agv7nliM/fO0NJHNYOtyzQwsFq7+o7tfM0T7v0QxE3Exnm1bSTt7ZvF0zDhyk3ZNzUReZnaVu68z8JaD2ueQjO/sZVK1NgzXia+GWnqGdcnNLWFDvI76m0XpWisvrVMYdtecme2mqJMspliFou9HeoMmohoqjMHEG+Eld38pJnjTS+5+iZk9OyO2+A5gqMaMDTdPmtn2qlawW58afIgmePqtYkbB36T/75Be+1wL+x7SsX/o2QRJ3zGzpRSLs//R3ad1wqayzyhSxH+uONfXKNaVxIxtYksTee1nZkcrlidpq+ekPL6zNWnYxjOKMnrIDNeJr4baIJ9hxSRAmyqGEJ1nZj8YgsMa1oprzcyOUwzNeTr9fz5JP52OhzZV3P2Xkn5pZr+dHhNRDSV6MDHkhnPaI7qlFKTDJK2lTgV7V3d/eLoeWA9yPYpt9TIO9dg/DE4a9/1xxXIF49x9yZb2e5xi3cOnSu9zyHBrOZ/ZWCwZUKxTLKWJvCS9pkGM0TOzEyUtrRjiUTQgtTFOcqSkg9z969Oyn+mBia+qil7uzHCAxmEANsTrqL/ZlDOF+nsN0w89mBhy7r5F+uf30piEeSRdMB0PCdNmf0k71ivYip6dGd0UM1vc3e+T+iZsmjLA7/TE3U+yWNy7GPu3+Yw8w91MYAlFILCoOj1EbVi+PPGCu//PzKjUzPgGM5t1f1Zz96Va2lcfd59iZsN10pJjFePyP5H+v316baac+KpIoXb30QNtW7K14ho9xN2ftlhH/RtDcXxvEiPMbL5aPYSYZgbCycAbaojSHvHGGs4V7K9LutTMium/xyt611vh7ndLurut/WHwzOxgxVIL90v6o2KijKdbfAsqNsNQi0MyrjGzZd39zpb2V3aLmZ0t6TRV1+qc0ScuGevu5XGYvzezPabXwQxHzjrqg/VTSdemmXqlaNz44XQ8HtTwUAQwWMO5gr2ApPcoAsvNFWm+M8XyMjORByX9QNJ4d/+9mY0zs3d5e8vFULGZua2pCAQfUIzBbHMZjNkV49k3Kr3mKgUeM6g3ZFw+UHD3483sJnXulS2HqNEHU4kxmAAGxcw+rVgHrlLBdvcTmn9rxsBMfW9+b8RyMWa2rDoVm79RsZl5zEjLYMwohvO4fABDgwATwKAN1wp2MQmAmR0o6TZ3P5mJAd5cWC4Gw1UaE36oopfUJV2rmFDqgel6YANg4isAdcMlrQ3ADCQFlMMiqKx5xMyOUEw+cZCZzSZpxHQ+JrSL5WIwXJ0s6deSionxPqkYRzyjZ1gM53H5AIYAFSsAM5OtJV0o6QNp4pf5xUx9bza/VKx/uZCZ/VDSVZJ+NH0PCejJnO5+gru/lv6cqBiXOaMbkVLRJQ27cfkAhgApsgCANxUzW1qd5WIuYbkYDAdmdpBineg/Knrgt5E0n6SfSNEzOP2OrtlwHpcPYGgQYAIAAExnaWbaQlE5s+L/7r7YG3xIPRuu4/IBDA0CTAAAgOnMzLaWdIG7P2tm+0paWbGO68TpfGgAMCiMwQQAAJj+vpOCy3UUvYFHS/rtdD4mABg0AkwAAIDpb0r6e1NJR7n7eZJmnY7HAwBThQATAABg+iuWUdpG0l9YRgnAcMUYTAAAgOnMzOaU9EFJt7n7P8xsEUnLuftF0/nQAGBQCDABAAAA4P/btWMaAAAAAEH9W1vCE1q4ycJ6AQAAwEJgAgAAsBCYAAAALAQmAAAAC4EJAADAIrtYV6rF0JirAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1152x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(16,10))\n",
    "plt.xticks(rotation = 90)\n",
    "plt.bar(word_count.keys(), word_count.values())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "id": "9A4AMQgMMgyw"
   },
   "outputs": [],
   "source": [
    "# helper function for plotting the top words.\n",
    "def plot_top_words(word_count_dict, show_top_n=20):\n",
    "    \"\"\"\n",
    "    Plot top words\n",
    "    \n",
    "    INPUT:\n",
    "    word_count_dict - dict. word count housed in a dictionary\n",
    "    show_top_n - int. top n words to display (default 20)\n",
    "    \n",
    "    OUTPUT:\n",
    "    Plot with top n words\n",
    "    \n",
    "    \"\"\"\n",
    "    word_count_table = pd.DataFrame.from_dict(word_count_dict, orient = 'index').rename(columns={0: 'score'})\n",
    "    word_count_table.sort_values(by='score').tail(show_top_n).plot(kind='barh', figsize=(10,10))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 592
    },
    "id": "N9iJAIA8MkNd",
    "outputId": "67f79d82-ba50-4df5-ec79-f40cb439caa5"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_top_words(word_count, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "id": "cXp8MsxOMmPG"
   },
   "outputs": [],
   "source": [
    "# create empty dictionary to house sentence score    \n",
    "sentence_score = {}\n",
    "\n",
    "# loop through tokenized sentence, only take sentences that have less than 30 words, then add word score to form sentence score\n",
    "for sentence in sentences:\n",
    "    # check if word in sentence is in word_count dictionary\n",
    "    for word in nltk.word_tokenize(sentence.lower()):\n",
    "        if word in word_count.keys():\n",
    "            # only take sentence that has less than 30 words\n",
    "            if len(sentence.split(' ')) < 30:\n",
    "                # add word score to sentence score\n",
    "                if sentence not in sentence_score.keys():\n",
    "                    sentence_score[sentence] = word_count[word]\n",
    "                else:\n",
    "                    sentence_score[sentence] += word_count[word]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 220
    },
    "id": "pnWGwLkQMqRf",
    "outputId": "344186d0-ce76-43ae-b0c7-45e832f30733"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>\"I controlled my ball flight really well, which is the key to me playing well in these conditions and on these courses.</th>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Rory McIlroy is off to a good start at the Scottish Open.</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1 McIlroy to prepare for the British Open, which starts next week at Royal Liverpool.</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\"I thought it was tough conditions,\" Mickelson said in an audio interview posted on the European Tour's website.</th>\n",
       "      <td>22</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>McIlroy carded eight birdies and one bogey in windy, chilly conditions.</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\"I felt like I played well and had a good putting day.</th>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He's hoping for a good finish, too, after missing the cut at the Irish Open.</th>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\"I was surprised to see some low scores out there because it didn't seem like it was playing easy, and the wind was pretty strong.</th>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>\"Everything was pretty much on,\" McIlroy said.</th>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A win Sunday would be the perfect way for former No.</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>It was a good day.\"</th>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>He won the last of his two majors in 2012.</th>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                    score\n",
       "\"I controlled my ball flight really well, which...     24\n",
       "Rory McIlroy is off to a good start at the Scot...     22\n",
       "1 McIlroy to prepare for the British Open, whic...     22\n",
       "\"I thought it was tough conditions,\" Mickelson ...     22\n",
       "McIlroy carded eight birdies and one bogey in w...     18\n",
       "\"I felt like I played well and had a good putti...     17\n",
       "He's hoping for a good finish, too, after missi...     16\n",
       "\"I was surprised to see some low scores out the...     15\n",
       "\"Everything was pretty much on,\" McIlroy said.         13\n",
       "A win Sunday would be the perfect way for forme...      7\n",
       "It was a good day.\"                                     7\n",
       "He won the last of his two majors in 2012.              6"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sentence_score = pd.DataFrame.from_dict(sentence_score, orient = 'index').rename(columns={0: 'score'})\n",
    "df_sentence_score.sort_values(by='score', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "id": "svYB1CU3Msoc"
   },
   "outputs": [],
   "source": [
    "# get the best 3 sentences for summary             \n",
    "best_sentences = heapq.nlargest(3, sentence_score, key=sentence_score.get)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "FVX0Q93hMutn",
    "outputId": "bb2ba7ce-7c02-41b7-c81e-d1190bbe6ebb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "SUMMARY\n",
      "------------------------\n",
      "Rory McIlroy is off to a good start at the Scottish Open.\n",
      "1 McIlroy to prepare for the British Open, which starts next week at Royal Liverpool.\n",
      "\"I controlled my ball flight really well, which is the key to me playing well in these conditions and on these courses.\n"
     ]
    }
   ],
   "source": [
    "print('SUMMARY')\n",
    "print('------------------------')\n",
    "\n",
    "# display top sentences based on their sentence sequence in the original text\n",
    "for sentence in sentences:\n",
    "    if sentence in best_sentences:\n",
    "        print (sentence)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "Bj7ZFDTHMwF2"
   },
   "outputs": [],
   "source": []
  }
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