AndradeEduardo/LDA_TopicModelling.ipynb

## LDA_TopicModelling.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## Loading all deed files"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Importing text files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# modules to extract the text of the documents\n",
    "from os import listdir\n",
    "import textract"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "doc_folder = '/Users/EduardoAndrade/Documents/iLab1/TrustDeeds/word_format'\n",
    "pdf_folder = '/Users/EduardoAndrade/Documents/iLab1/TrustDeeds/pdf_format'\n",
    "src_folders = [doc_folder, pdf_folder]\n",
    "files = []\n",
    "for folder in src_folders:\n",
    "    target_files = [folder + '/' + f for f in listdir(folder)\n",
    "             if (f.endswith('.doc') | f.endswith('.docx') | f.endswith('.pdf'))]\n",
    "    files = files + target_files\n",
    "# files[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "corpus = []\n",
    "for doc_path in files:\n",
    "#     print(\"reading\", doc_path)\n",
    "    txt = textract.process(doc_path)\n",
    "    corpus.append(txt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(corpus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Text Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#modules for preprocessing the corpus by regular expressions\n",
    "import re\n",
    "import textacy\n",
    "# module for preprocessing the corpus by parts of speach \n",
    "import spacy \n",
    "nlp = spacy.load('en')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Regular Expression Cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def clean_corpus(sentence):\n",
    "    sentence = re.sub(r\"\\\\\\'\", r' ', sentence)\n",
    "    sentence = re.sub(r' s ', r\" \", sentence)\n",
    "    ## removing character sequences of Word files\n",
    "    sentence = re.sub(r'(\\\\n|\\\\xe2|\\\\xa2|\\\\x80|\\\\x9c|\\\\x9c|\\\\x9d|\\\\t|\\\\nr|\\\\x93)', r' ', sentence)\n",
    "    sentence = sentence.replace(r\"b'\", ' ') ## removing the beginning of some documents\n",
    "    sentence = re.sub(r'\\{[^\\}]+\\}', r' ', sentence) ## removing word macros\n",
    "\n",
    "    sentence = textacy.preprocess.replace_emails(sentence, replace_with=r' ') ## removing emails\n",
    "    sentence = textacy.preprocess.replace_urls(sentence, replace_with=r' ') ## removing urls\n",
    "\n",
    "    sentence = re.sub(r'(#|$| [b-z] |\\s[B-Z]\\s|\\sxxx\\s|\\sXXX\\s|XXX\\w+)', r' ', sentence)\n",
    "    \n",
    "    ## removing character sequences of pdf files\n",
    "    sentence = re.sub(r'(\\\\x01|\\\\x0c|\\\\x98|\\\\x99|\\\\xa6|\\\\xc2|\\\\xa0|\\\\xa9|\\\\x82)', r' ', sentence)\n",
    "\n",
    "    sentence = re.sub(r'(c/-d*)', r' ', sentence) #remove address\n",
    "    \n",
    "    sentence = re.sub(r'(\\\\x01|\\\\x0c|\\\\x98|\\\\x99|\\\\xa6|\\\\xc2|\\\\xa0|\\\\xa9|\\\\x82|\\\\xb7)', r' ', sentence)\n",
    "    \n",
    "    # removing trade mark of specific pdf file\n",
    "    sentence = sentence.replace(r'LE G A SA L E M D PL O C E S', ' ')      \n",
    "    \n",
    "    # striping consecutive white spaces\n",
    "    sentence = re.sub(r'\\s\\s+', ' ', sentence).strip()\n",
    "    sentence = sentence.strip()\n",
    "    return sentence"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "clean_texts = [clean_corpus(str(doc)) for doc in corpus]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'PROPERTY\\t\\t\\t\\t\\t\\t- 30 -\\n\\n10.5. \\tPOLICIES OF INSURANCE\\t\\t\\t\\t\\t\\t\\t- 31 -\\n\\n10.6. \\tUNIT TRUSTS\\t\\t\\t\\t\\t\\t\\t\\t\\t- 31 -\\n\\n10.7.\\tCOMPANIES\\t\\t\\t\\t\\t\\t\\t\\t\\t- 32 -\\n\\n10.8. \\tBUSINESSES\\t\\t\\t\\t\\t\\t\\t\\t\\t- 33 -\\n\\n10.9.\\tGIFTS\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t- 35 -\\n\\n10.10. \\tCHOSES-IN-ACTION\\t\\t\\t\\t\\t\\t\\t\\t- 35 -\\n\\n10.11. \\tBANKING AND FINANCE\\t\\t\\t\\t\\t\\t\\t- 35 -\\n\\n10.12. \\tLEGAL\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t' \n",
      "\n",
      " TION - 42 - 11.9. PROFESSIONAL AS TRUSTEE - 42 - 11.10. LIMITATION OF LIABILITY - 42 - 11.11. INDEMNITY - 42 - 12. APPOINTMENT, REMOVAL AND RESIGNATION OF TRUSTEES - 43 - 12.1. APPOINTMENT OF NEW OR ADDITIONAL TRUSTEES - 43 - 12.2. REMOVAL OF TRUSTEE - 44 - 12.3. RESIGNATION OF TRUSTEE - 45 - 12.4. \n"
     ]
    }
   ],
   "source": [
    "print(corpus[7][3000:3300] , '\\n\\n', clean_texts[7][3000:3300])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Parts of Speech Cleaning\n",
    "Spacy nlp documents were instantiated to perform parts of speech cleaning"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "nlp_docs = [nlp(clean_text) for clean_text in clean_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "At the trustees complete discretion, the distributions of trust income or other trust property may be made to any number of these eligible beneficiaries and in any proportion."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentence = list(nlp_docs[23].sents)[12]\n",
    "sentence"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Only nouns, verbs and adjectives will be kept."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tags_to_keep = ['JJ', 'NN', 'NNP', 'NNPS', 'NNS', 'VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Every token of the previous sentence are listed below. We can see many words that are not concepts listed, such as 'at', 'the', 'or', 'in', etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At - IN - ADP\n",
      "the - DT - DET\n",
      "trustees - NNS - NOUN\n",
      "complete - JJ - ADJ\n",
      "discretion - NN - NOUN\n",
      ", - , - PUNCT\n",
      "the - DT - DET\n",
      "distributions - NNS - NOUN\n",
      "of - IN - ADP\n",
      "trust - NN - NOUN\n",
      "income - NN - NOUN\n",
      "or - CC - CCONJ\n",
      "other - JJ - ADJ\n",
      "trust - NN - NOUN\n",
      "property - NN - NOUN\n",
      "may - MD - VERB\n",
      "be - VB - VERB\n",
      "made - VBN - VERB\n",
      "to - IN - ADP\n",
      "any - DT - DET\n",
      "number - NN - NOUN\n",
      "of - IN - ADP\n",
      "these - DT - DET\n",
      "eligible - JJ - ADJ\n",
      "beneficiaries - NNS - NOUN\n",
      "and - CC - CCONJ\n",
      "in - IN - ADP\n",
      "any - DT - DET\n",
      "proportion - NN - NOUN\n",
      ". - . - PUNCT\n"
     ]
    }
   ],
   "source": [
    "_=[print('{} - {} - {}'.format(token, token.tag_, token.pos_)) for token in sentence]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below, we selected only the words that fall into a part of speech category previously selected. We can see that this time only words that carry meaning are listed. Most of the concepts are related to the trust deeds business. For instance 'trustees', "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "trustees - NNS - NOUN - trustee\n",
      "complete - JJ - ADJ - complete\n",
      "discretion - NN - NOUN - discretion\n",
      "distributions - NNS - NOUN - distribution\n",
      "trust - NN - NOUN - trust\n",
      "income - NN - NOUN - income\n",
      "other - JJ - ADJ - other\n",
      "trust - NN - NOUN - trust\n",
      "property - NN - NOUN - property\n",
      "be - VB - VERB - be\n",
      "made - VBN - VERB - make\n",
      "number - NN - NOUN - number\n",
      "eligible - JJ - ADJ - eligible\n",
      "beneficiaries - NNS - NOUN - beneficiary\n",
      "proportion - NN - NOUN - proportion\n"
     ]
    }
   ],
   "source": [
    "_=[print('{} - {} - {} - {}'.format(token, token.tag_, token.pos_, token.lemma_))\n",
    "   for token in sentence if token.tag_ in tags_to_keep]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Besides removing filtering the token by pos tagd, the code below will also remove the remanining stop words from by using the STOPWORDS list provided by the SPACY package. This is performed by filtering the stop words with the is_stop function. To improve this filtering process, some terms found in the documents by exploration were added to the default stop list. Named entities will also be removed as they mostly refer to parties of the deeds, not to concepts related to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "does; being; much; such; well; anything; none; side; already; get; too; above; using; did; to; it; beside; about; its; unless; otherwise; enough; back; thence; something; thus; sa m ple; everything; nobody; their; in; which; meanwhile; wherein; thereby; he; among; five; whole; else; least; as; ten; seemed; everywhere; below; an; could; the; yourself; there; whether; with; each; am; moreover; inc; mine; mostly; nothing; perhaps; hers; we; very; full; give; whenever; these; on; own; doing; she; them; whereupon; one; together; therefore; noone; of; has; you; really; everyone; another; go; toward; or; yourselves; was; hereafter; must; still; two; latter; take; that; though; eleven; ca; many; off; re; six; other; whom; after; sometimes; nowhere; also; ever; any; within; per; again; upon; around; sixty; made; move; SA; at; onto; have; same; my; because; if; no; once; put; keep; under; rather; whereas; thereafter; former; her; someone; often; a; seem; can; then; over; besides; etc; regarding; several; throughout; just; here; ours; so; become; both; seeming; herself; until; used; for; now; becoming; becomes; yours; how; some; whither; but; may; without; your; less; most; empty; via; fifteen; done; seems; eight; alone; be; somehow; do; almost; others; nor; first; hereupon; became; whose; would; themselves; towards; front; herein; whence; and; i; more; sometime; part; by; myself; along; four; further; see; therein; anyone; anywhere; latterly; those; top; this; will; him; although; while; beforehand; out; forty; where; e; during; thru; what; namely; from; thereupon; fax; before; himself; between; had; please; wherever; when; whoever; yet; afterwards; might; all; whatever; whereafter; they; even; third; last; cannot; due; somewhere; nevertheless; been; various; indeed; bottom; than; since; itself; neither; except; name; call; not; hence; into; only; down; m; either; few; through; make; every; serious; his; nine; were; never; always; why; whereby; us; beyond; are; fifty; up; quite; anyhow; twenty; however; behind; ourselves; hundred; should; hereby; say; against; show; formerly; next; anyway; who; across; is; amongst; twelve; amount; three; elsewhere; our; me\n"
     ]
    }
   ],
   "source": [
    "spacy.en.STOP_WORDS.update(['SA', 'fax', 'sa m ple', 'm', 'e'])\n",
    "print (\"; \".join(spacy.en.STOP_WORDS))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also take advantage of the named entity recognition capabilities of the Spacy API to remove entities that cannot contribute to the finding of meaningful concepts in the deeds corpus. The only entity left in the corpus was the 'ORG', that stands for Companies, agencies, institutions, etc. (https://spacy.io/docs/usage/entity-recognition)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "entities_to_remove = ['PERSON', 'GPE', 'LOC', 'NORP', 'FACILITY', 'PRODUCT', 'EVENT', 'WORK_OF_ART',\n",
    "                      'LANGUAGE', 'DATE', 'TIME', 'PERCENT', 'MONEY', 'QUANTITY', 'ORDINAL', 'CARDINAL']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The filtered text will receive only the lemma of the nouns, verbs and adjectives. In this way, the lemmatisation is already performed and variations of a certain word will be returned just as their common lemma. Furthermore, the lemmas in the spacy API are set in lowercase. Thus, the output text will be prepared to be processed into a vector space."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filtered_texts = []\n",
    "for doc in nlp_docs:\n",
    "    filtered_text = ''\n",
    "    for sentence in doc.sents:\n",
    "        sent_filt_text = ' '.join([token.lemma_ \n",
    "                                   for token in sentence if (token.tag_ in tags_to_keep \n",
    "                                                             and not token.is_stop\n",
    "                                                             and not token.ent_type_ in entities_to_remove\n",
    "                                                            )])\n",
    "        filtered_text = filtered_text + ' ' + sent_filt_text\n",
    "    filtered_texts.append(filtered_text)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Perform a second regular expression cleaning to remove dirties found by parts of speech when it tokenised the text."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "filtered_texts = [clean_corpus(str(doc)) for doc in filtered_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.1. Definitions \"Appointor\" shall mean the person or persons (if any) named or described as such in the Schedule and any person or persons who succeed them in that position in accordance with the provisions of this Deed alive or in existence at any time or where at any time no such person or persons are alive or in existence the legal personal representatives of the last surviving one of them; \"Beneficiary\" means a Specified Beneficiary or a General Beneficiary; \"Business Day\" means a day that is not a Saturday, Sunday or any other day which is a public holiday or a bank holiday in the place where the act is to be performed or payment is to be made; \"Capital Gains\" means that part of the capital receipts of the Trust Fund which are liable to be treated as assessable income for the purposes of the Income Tax Law \n",
      "\n",
      " definition appointor mean person person name describe schedule person person succe position accordance provision deed alive existence time time person person alive existence legal personal representative survive mean specified beneficiary general business day mean day public holiday bank holiday place act perform payment mean capital receipt trust fund liable treat assessable income purpose income tax law mean\n"
     ]
    }
   ],
   "source": [
    "print(clean_texts[7][5291:6114], '\\n\\n', filtered_texts[7][2412:2825])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wordcloud\n",
    "A wordcloud was generated to depict the main topics of the document.\n",
    "\n",
    "Code derived from Python wordcloud module github page (https://github.com/amueller/word_cloud/blob/master/examples/colored.py)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# modules for generating the word cloud\n",
    "from os import path, getcwd\n",
    "from PIL import Image\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from wordcloud import WordCloud, ImageColorGenerator"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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nTRwFV124pFAqMbP3QP/YFNkfaXkIIQiicDhbE0Ud5M4FQCAMq99kV6qRq1NC\nzO9V4WK5kGT9Y08E3ugsdrFK0tokjwMQAqtYx65NISxHBUyegWEMqhXVglp/w3Ke9j9A9Kd2hQFe\nSa2jZYnq2CGM/kbm/nSiMMAuqufVtBfRwaW9bgzD5PBtd6hTjPt7oIRhYFkv/WvnF4tMzi1g2TaO\n4yIMA8M0iKOQYlnt87FLFRiZuvJN3mH1CV4Y6lP87qK68eW5CjXLVRttJeoGWBqDsK0+0fd2wK8O\nnirPc6JeR51fJQSuVyDL1Bldlu3Qa7cRQgymDIdv+kpCsIMojqm2TpdDBKHCI9hWI6WxG/phcfnr\nu5AnmIaNWRlRe75MV4WL5ain6G6q9z2NgY4aNcU9NRKz3Cv9IU17sLEZIdR1lMavrD8KQ11DbVZN\nW0L/9zTtWjq4tNeNEIJiuTL47zzP2Vy5xNLZ00iZM7WwjzzLEMDEzDzlWh0hBIVSmTzP2Vlfpbm5\nxtriOWqj47j7b8B23KtCQx2MmCYxqxfPs3b+FFLmjM/MMTU/p47WkPngFGWEwU4rYPHMKZIoYHz+\nAF6hBAiyOGLr0hnG99xI0Gmr0OqvEedZpu7jWYZnmli2M4TdHQRUZkBmyM3TiJE96stSqr6EYwf7\noy1fhXrSUxWGbgmZhCTtLfK43S/A6Krv7bQQpo1TKCFkv5OGW1ShVRhRwSf7RTKmrV5HSvX1pKcC\nzfJUaDpFNVJuPw/lyVdcPKO9Peng0t4QeZ7x5Lf+hi/9wb8j6HZwCwVsx+XGW+9UQSSunGKcZSmP\nf/NBvvYnv0/Q7WBaNkkcsXDwMD//D/57Juf2DB4bdDs88Kf/iUf/5isqaIQKmne+7yf56Kf+/iA4\npZScevpx/vz3/i+2N9bwCyUM0+Tw7e8CJHmW9p9TYBgmQbdzzcZotdaWEUchQggMyyLoduh22nie\nT6k6BN3jsxjaqsM7oh8MAhUq6ydV8DQOqArDuAd5Tp4GtE5+h7i5rjq+v6jgy/RK2DP7EHnSn+qr\nQ3NZjboMU4VTtqmCqbOuRmdOSQVXbU6F2c4FQMLsHepaNO1H0MGlvSHWFi/wxd//NNWRBr/+T3+H\nWmOcpbOn+OJ//DRBtzt4nJSSM88+zec/8285cud7eP/P/TJ+qcTS2dN87jP/hr/4j5/mN//5v8Ar\nFMnzjG//1ed56Ktf5MN/79e55e77EEJw7Lvf4qt/8vtU6qPc/4u/hmEYtHa2+MJ/+DRxFPFf/vN/\nydT8XjY2BSyRAAAgAElEQVRXl/nSH/w7drc2MCybPMuQMscrFFQ49T/1Z1lG2OtiGAamZakTmE0D\n07QwTHPwuDe97kZ/jc8Fw+hXRgqYOAJICJtqRGT7g4a40dYiaWeHyo3vwS6Nqim+qwhhYARbqrBj\n9IBat7K9/rRsS1Vvbp9TTXltX62rpRGUJxCFEeTqcTUdGHf7wRdBFiEt983/QUC7bnRwaa87KSXP\nPf5dWlubfPK//h/Zf+QdCCEYHZ9kdfE8n//Mvx08Ns8yHn7gS7iez8d+7bcZGZ9Sj52YYvn8GR78\nfz/L8vkz7LvpFlrb2zzy4F9y6NY7ue/jvzRoyXTPx36e5574Lk/83YO89yMfp1Stce75Z1g6e4pP\n/PY/4cid70EIwcjEFO//xC9z7sQzyDzH8YsYpoWRSxzXw+jf3P1CAcu2SeNYbUDOUtJUUiy7eFbh\ner2tr57M1dSc7YPhqPXBqKUqNJMIGXcQ0+9Qvx91QAiyXgu7OoE3vvdlu7ZLKaF1CeFVVTCOHYT2\nWn+vWEH906tCqaFGYoOzvmxkFqutCb1ttdYVd8Erq9GeW3mZH0DTFB1c2mtKSknQ7dBpNRGGgWma\nVGojXDp7ikK5wvSefYNP0sIwmD9wCNu5Uu4cdDssnj6BYZo8++h3MK8q5NhaWyYKemyvr7LvplvY\nXF1ie22FiZl5Hvubr1xzDXEYsLu5QbfdolStsXxOHYuycMPhK68vBNN79uMXy2prUb+CTUpJlibk\neU6eZQS9Xv+oDgPX80ni+GULTN703DJ0t9SUoVtWYWL2Cyy8GqK7qabqhAmFDISB4fqkweW1rR/0\nvCW1luVWIOqq5w92AKHCyPHVv3sVNfJyCtBaVaM6y1Xfb9oq+ITZP/ZEj7a0H2wI/+/T3uwMw+xP\np5n9/U8qzGzXw76qwS2A6xevKS1P4oiw16W9u8PffP5PXvLcY9Nzg6ALux2SJObM8adZvnBWPeCq\nkuvG2BiGTJFpTK/TwrRsXP/aEZLjeapTA4I0jgb7zUpVdT6YYZoUS2WEEKT9Vk9xFJJl1vCd0zV+\nSI16+nusVDVg1K/MNFU5e9gEp6xOQgbc0XmizYsEq6dxR+fUUTHXZIqA6qz6BWq9Ko1UVaDM1Wvl\n/QrF/kZj9e8xuCPqdZMESFQ4OsWXTEdq2ovp4NJec67v4/pXmq5e7jaRpclLGtVmaXJNFwrTtLBs\nh/1H3sGv/U//hxpxZbHaWNw/Jt4vFJBJgOU4WKbFfR//e9zzsZ9XN8Sts6pM23QQSY9iyYHuBk7/\n1OQ0SV70+qobRprEWP1QFULQae3SmJwmiaP+GpxECEGpUiPP1PcMU3CpDvoS4na/MENCZqviiSRQ\nU4gy63eOv9IrME8j8iSmdfJhTK+EYbvXBIvpFqgcfA/C6gdVod82Sgi1ZmV5Vzpq2H5/n5dUIz7D\nUCX0bunKJmMdWtoroINLe03FYUi7uUOe5yqkBBRLFcZnFzj2yLfYXlthdGJqcCPdWLl0zQGNfqnE\nxOwCa4vnAajUR9UeoVao9hDZHuQhBAmj45OUaiOsLV6gUCqr6buio9ZWDBvIBzfp8fm9pHHM2tIF\nFm68afD6OxtrhL2OqpiTappQIKiNNLBsB9OyKJTL5Gna75ghsOxhrXwTUGioIEl6/X6O/VZMWaxC\nwzDB8pBJoEZASYhdKGEX+2tO+bXbCwy/qoorOuv9SsRU/bdpqz+HziUVWJajNjRf7iNJvyzeKaqG\nv8YQrRVq150OLu01ZTkO5doIV3ojC0xLlZ1/84t/xre+/DnGpmcplCtsr6/y6F//1TUHNFq2w7vv\n/xh/9K//JV/70z/g/k/+KqVqndyq0d7dobm9wv6bbsG0beqFnNvv+QCPPPiXPPy1L3HrT7wfx/NJ\nOgE76+cQhmDuwCGEEOy76RbqYxM89JUvsOfgEepjE3Rau3znq18kDiNsx8PsN3fNpVrXkjLHMEzC\n/hqXZVlIII4iXN8nCgKSJFbdzAHbcbEd5zq866+MEAJZbKhwoT5oG4hfu/yI/tReCu11yBNs08Ze\nuKXfJipTwWVcCSbhVwGBFKOqO0Z+uXN+v5DDKajHSqn2hwFYtvp9B/V85pv3PdPenHRwaa8pger/\npw4FVB0oRscnWDh4mA984lf4+uf+mKWzpyjXRui2mswduJHa6Nhg3V8Iwc3vvoeP/Be/xd9+/k84\n/th3KFXrZGlCp9Vk/sAhFm48iuWamMLg/l/8ddrNXb70n/493/jin+L6BeL+ESbv+/gvMXfgEACN\nqRk+8iu/xRd//9N8+n//J9THJuh1WkzM7WFybgHTdhid3Q9AkiSEvS6d5i6maRH2usj+epdlWbie\nD1KSpjFhr0schuR5TrFcwfU8/GLpTdsSSgjxsnulZBqr6j6vrEZKtTkgHzS6lVlCFrSQMgEMTLuI\n4RYHDeGF5SLjHnQ2EaN7r33uPFUBJfMrnU76HeExLfVL014FfayJ9ppRBwFK0iQhTRJMy0QIYzAK\nSeKIF449yQvPPEme5ey76RYWbryJM88+RX18kn2Hbx48V5amLJ17gVNPP8HOxhqO61KrFDl0172M\nNMawC1fKpYP2LmefO8b5UyfotVsUK1UmZ2bYf/R2PMfErTYAQZ6lnDtxnOOPfos4ithz+BYO3/4u\nzhx7DL9Q4obb7yZubZBlOUGijtco10YIuh2iIMD1fQqlMnEYIgz1c8VRRLfdROZS9TUUgkqtfk01\n5DCQSaDaOzlFcMuDNS4pJWl7i87575O0NpC56igibBdvfC/FuZsRtqNCL9hVBR/jh9T0Y9Jv+7R1\nVk3zjuxV4eWW1DRhnql/R3eA167xI/8y6ODSXjMXTp2gtbtNuVYnCgL8YolOc1d1oJCSQqlM0Ouq\nm38UUapUuXTuNHP7DpCmKYYwaO3ukMQRpmWx/6ab8fwCeRrTXjpFtLtGZf4IcXub4sQe2kun8OqT\nBFtLCMOkMDZPsHmJwvgCwdYl3NoEzXPHcCsNTK+AXaiSxQHB1hJ2oYJbm6C3dh7Dckh6TbyRKSyv\nRNJr45Tr9NbO441MId0KSRxh2c41LayAQWHJUN94pURGLbV3qzSGuGrqLg1aNJ/9BsJ28Mb3YbpF\npMxJ21uq0rAxT3lyL2y9oJrihk019TdzK2yeVq2fWsvqycYOwe5FNaXYP/9LVKev0w+tvYnp87i0\nN05rd5s4Ctnd2mRmz352tzaIooCdjXVqo2N0Wk0c1yOOIuYPHMR2XMrVGoZh0mluDg6ODDodxmfm\nCHs9XM8nDbvILMV0fAzbI0tCAPIsIYt62MUapu2SpxGG62P5ZYRhkScRhu1iOB699Qv4o7PkaYxT\nqmOX6kTNdZJeC2GauNVx4tYWplsAmRNsLpHFAXkSUagXcVxvcLRJlmUsXTxNtdbAcdx+mbwkz3I8\nv4Dtuv2u8sNBwpVGuFl6zZpTvHUJhKB6+F4Mp3BlJDY6h1Ws0zn7OFmxgOnVoDwBGz21FibzfsGH\nCV5NrZ25JahMqfPSkNA48NJzzWR2pR0VQ/6BQHvd6ODSXjN+sURjcora6Bi241Cp1el12viFIvXG\nOK5fYOXiOTy/QBrHOK7H1PxedWCj4+AXigT9PVxpktBttzBMk1Kp1A8tl/xyaKUJtl/GcHxM1ydu\nbeL4DVzLReYZMkvJkwinPILMM8qzh4jbW9ilEUzHI+21sdwibnUMyyuShl3c+iR5EpNnCX5jhqjp\nYJfqqqP9VUHUbTf56hf/kDvu+iClUo3drQ2SJGZ6YR+maTG9sAfDGbIzpPJMVf69KCiyoI1VqF4T\nWqACxSqNqG+1i5jdVbXZ2HRUafvqcdWJo76gAmvrrPpnoYFMI4RTVCMxuwhZ1O9pGPdbQ3lq/evy\nIaGa9iI6uLTXzJ6Dh8llTnNnk+buFnmWUa7WWTh4GM9Xx8QXSiVkrk5F7vXa7O5uqAMjXQ/Tsqg3\nxihX6+R5hmlaJEnM6soi7XYP0zCp2Akj80fVqcTFKlLmtJo7bLZD8uYFRkYnqBcNKgtHADU62t3e\nwPKKVEamr+xPsny6nRb1ucMYhkm7tUPeX4/b6kWsXVqkXKnju0VVIi+E6qIRdDl7+jhbm2tYrkOh\nWqFQKeP5BSq1EVV9aA9hldzg9OJrGW5BrW0lEdjuNWtfWdBUjzFtGN13pWN+v6JQeNV+Jw7RP/TT\nUkermA7U59XIyi1B2g/M3FNrbJf3fGXx4Ny0yxWPegSmgQ4u7TUkDINvP/gFnn7iIdXnL5dEUcAt\nt7+XD330l3BcD8f1yPOM5595nG8++Dk67SaWZZNlKdOz+/jkr/7jQchtrC3x4Jf/Hy5dOI1l2UiZ\nY9sOv/hr/y0z8/vJ85znjj3GNx74HEkSDXrp3X3vR7jj7g9iWTZBt82fffbfcNtd9/Huez4yuNYT\nzz7Ot/7mL/iNf/i/Ua2N8nd//QXaLVVFuLp8gTzLiMKA29/1Pn7iAz9LnmXsbK/xjQc+x9rKIu3m\nNl//yp9hOw6mafGxn/9NxiZnVMXhq5DnuerWISWmdW2rozd0/cwwVcWfW77my87ILMHySVqnHsGb\n2IfhqKNi0u4OvaXncerTmF5RjZZMu3+USa4C6PKm4iQcjKBk1EaM7u+fkyZVNaJ1ZeO3lPJK5WF7\nG+SW2qTsl6E8BrZ7+c25cpE6zN52dHBprxnDMNh/8Gb27D9MY2wKCTz60IM89tADHL31bub3HgRg\n+dJ5vvy5P2BqZoH33f8LjE3O0G23CIMeoG7YURjw1S/+IVubq/zMJ3+LqZkFsiyj3dyhMT6FlJL1\nlUW+9hd/xMGbbuO97/tpTMvime8/zDce+Dz1kXEO3nQbuZR0Oy3iqzY5AyRJRLfTGhxwGQY9jj/9\nKO+576P86t//Z5iWxaPffoDHvvPXzM4fwDYcpvfu46Of+E1OPfckX//Kn/HRn/8NxsanAUGlWv+B\n70uv06bTauL6qs+h6P+MWZIgZY5pWaRJguN5/WpMiyxJrtrELRifnsPxvB/4Gj82KVX4yGwwwgSw\nijXKN7yLzrnv03r+W4OHC9PCHVuguHArOP5grCYvr21dXidLI9LV41gTh8G0yMMORqWoDvSUEooO\neXsNIUwoqjO88s4GRm0ORufUcxn9UVueqbL9sKOCtrUB1fH+yK2gR2NvIzq4tB9Lp9XEth1c30cI\nwZ79h/sjBVUaf9Mtd/LYQw/SbqnNp1JKnjv2GEjJvR/8ObI4ZWNpSbWIyiQrF8+z5+BhVpbOc/7M\n83zs45/i4N59kGcIx6ZemoE0JJcpJ44/SZZlvOe+jzE6NgnAnXd/kOeOPcZTj3+LAzfe8qp+lkq1\nzt33/hQjjQkAjt52N499569p7mzhOwVs26E4XmFlqY5hmNTrYzTGf3BV3OURk2XbFEplTLPfw7Hf\ndX714nmEIdQoNEtJ4pgsTXF9j167jVcsIYQgDHrXnA32ukgj1fkibKnzsvqEEDjVcWr7biUL2+RR\nD0wb0yth1WfhRcePyO426cYZDL+GcEtku0vIzgZ5aZysuYzsbSOKo8juFtg+pl8jWzsJpo3tvAMZ\n98h2lzBqs2Trp9QUZX+bgYy6IHPMnQ1EeQyinrrmqIc48K7X9/3R3lR0cGk/lrDXBV/i+j5SSlq7\n27xw8mlWl84T9Lp0O03iKBh0x8jzjPWVRUYaE0zOLCAQxFGouk8IgdnfjLq9tYYQBjN7bsQq1pEy\nH7RcQqrb+PrqIpVqnVK5Orgex/VpjE+zcuk8SRK93CX/QOXKCMXSlXJ323YQhkEUBXi2j8xfXXjk\nWcbO5ka/pZXEtGyiMKA+OoZfLDK37wCm4yBzSWvtImEGM/tuIE8ixLSJYVk0l87gSDE4suX1IIRA\nuiW1EThP+6dGq8o+KXOyOCDLcqThgq96FWYSsp0VdQJybRJhWkgpyYMWSEne3UAkAeboAlmekPe2\nMcrjSNMGw0AU6mra0LQwSmOIQg2cgjrkUkrIU/LuNvaed5EsPgFZijl+A/nWeWQaYdSn1QgsSxHl\nhrrWPB9MGw6mHdGViW9FOri0H4swjMGNYWd7nT//40+TxDGHj97BzNx+up0W58+cuPINUoXX5c7x\nhmmp6SXUoYRZlhIFAVma9lvnqca64spcVH/aKB+E2YtvTIZhImXOiyutr3Z1m6nLTNN82TJ20zBV\nB3njpTfAK6NLdYO8ZuNu1EP2tinXGuqolc4uviFxHJuNU08S99pMHLoTKXPC5iapUyGLApafeQi/\nOsrovptxSzWap56ksfcoWRLR3ljEdgsURqde2xuylKp4QhhX2jUB8fYSrVOPqCm6lyneMP0StZvv\nH3zgkGFTPcxwEE6xP2oKMSqTZDuLkEYY1Sny9joy7iHrPYRbIt+5hPAqyGAXGbXJe7sYxVHSlWcR\nlofwXITlIuwCoj6DjLoIx4ewjTRMxNpp9YGm3w9RTQFLRKGGbCzo8HqL0cGl/ViMy6Mg4MzJZ1ld\nvsiv/4P/hYV9qtXSxXMnry2jNgxq9TFOnzxG0OviegW67Xa/itAkSRJc16NcqZFlGTtb64yNjKrO\nDv3mrMJ0kAhGG5NcunCaMOgOiiLSNGF3e4NqrYFt26RpogIxvdIVXkpJc2eTH5psVxGmgWFcHZD9\nykSZs7W2SpqqIzlGxidwLh/bInNWnnkIIQzay6dxS7X+6CXC8fxBH0TDspF5TnvtAvbEjQjDIE9j\nTMdDGCam4w6KTjbPHqO3vUoaBszf9WHcUvVlrvbVk5c/DNj+S0ZccXMdw/YpH7oH8TLl8kIYGPaV\ntTdr+hbIIvKwiyTHcEuqgbFhY7olyHOEX8fyqur8M9PGqM9ilMbActQIbv89KkQLdbXGZXtqs5lh\nYE74yI3z6j2RUp31dXmUJiXCtEA4yCxW12u/juuC2nWjg0v7sZRr9atGIqqzOgjyPCMMejz9xENE\nUTB4vBCCG4/cztNPfJtHH3qAd9/zEcq1GkmaEAU9xqam+zdDi9HGJN/55l9RH52gVm8g84xet02x\n7OO4HgeP3M4T3/0Gx558mDvf+yEMw+T0CTVNef9P/wqmZeM4LpVqnQtnT9Jp7+L7RTbWVzh5/MlX\n/DOahontuIOc8zyfPM/Y3lxj/8GbAYlp2thXdY2XeU7UaVKbvQHbLxK1dyg2pgmbapuAW6qRuTGW\nq6r0LNenWC5jOh5usYpfbWC8qIdf1N7B9kuUxufZ3d5CtNpqP1W/OXClNvKf3yPxcrf4YuOaEZfX\nmCfrNcmiLqZh9qdrr/5GweXmNvnyc+SdLWRni3x3GfvI/WQXnkT2drBv+zmMqlqHlLtLxM9/A7m7\ngiiNYh1+P0Zjr5reE4J87TTp2UeR7U2wbMy5W7EOvEdNR6YR2eY5jLG9pGceQzZXEIU61qH3YYzv\nR579nuq3GHXUtGQSwe4qMo1ACERpRO1XG5nTo7AhpoNL+7FcfcTHngM3URsZ4y/+7DOMT83S7bQp\nV6o0xqYxjCtrD/sOHuW97/8ZHn3oAZ479j38Yok4ChgZneCTv/qPcfojrg//7Kf4yhc+yx/+3/+K\nSm2UPMvIsoRf+NQ/YmpmDzNz+7jv/k/w0De/zPPPfg/TtNneXOXIre/m6K3vVoUFrscdd3+Qr33p\nj/ns7/0rSuUKvV6XsclZ4jgejCAMwxxMd10mhMAyLTViAC7foCdn9jAzt5+vfOGzjE/OIoTBBz7y\nSWYX9l9ZVzEtRvfcRG93A9svqs3SloPp+pi2g+0V2Xjh+xRHp0jCLkmvjRGrSjuvOsrOxRPYXpHm\n0lmi9jadjUVqszewc/EEWRxQmdiDMCw1a5qECMv5MW/EYlDSfs3zCIMsaNF8/tsqSF/0GqZXpnbL\n/ZhugWz1JMkzX8M++pPk66eJNs5i7buLbOUkwv8G9rt+BdneIPrG7yEqE5h77yBfPUX0t/8e7yf/\nO6jNgJRka6fAtDD33km+s0T88B8hbA/rwN3IsE38+J8jinWshdsx9txJdv57RN/8PbyP/FN1AnOe\nqsrD6iR0tiFoIcM2ojIGxXq/P6I2zHRwaT8WKSVh0CPodBA5fPTjv87pk8fIsozJyQWO3PouWs1t\ngnaLi6dPsLu1wezeG7j3Qx9ndHSCs6eOMzI+QZakFAolLNthc3WJNE3J45Tb33kfTsFnY22JbqtJ\nuVxn49Ii9foYXqHIbXfdRxKGPPfUY4zOzXLfh36Oub0H6bVbnHrm+8g8Z3Z+P5/6r/5nFs+fYun8\nGeqVMW48+k7uvPtDlPrFGO+576PEieqRmOcZQhhUaiP8wq/+I0qlKrsbG4OfuVSu8guf+m84c+pZ\nOu0mxVKFYqnC+VPP4xdKFMtl8lxCaQzPrWD4BSzDpN1uE3QTxuslVU4+eQNBlGKYHpO3vl+N6ISg\nNrMf1zIgCSgUPAqHbsOyLPKgyfj+o+pk5qSjNv4KEEmEYUC0uYlhuwjbw+53tXglhBBIv94/3PFF\no7yN8+RpTOWGd2G4Lz2dWJgWhnVlw7VwfOyb7kdGPbKL38c++hFkd4d8ZwlkRnr6EZAS972/CV4J\n9t5F+OXfJT37GPbtn1BNmd/xM6qAQxjIJCJfP022ehLrwN3qRbIUa88d2Hf+IggDc+IAwV/+Lnlz\nBfPIB/p/Melfq4TtJdg4h/j/2XvzIM3O67zv9753//a992XWngXbYCdBcQFIiqRIUVJEW5EducqS\ny1VR8kdcSeWPJI6UpCpyuZxKVcpOrKiiiqJQFBWJomSZFAlSJAESINYBBoPZZ3qW3ru/fb3bmz/e\n21/PACAJLjBlo8/UVG/3u9vX/T73nPOc5ynN6QQxGMLODZTlQqasy4v78e9V7L9j+/FjR7fVZGX5\nKv1uGzeVZnbmMLlSidD3CUc+pVKNP/zD3+PQiXuwHZeXnv46/9Gv/+eMen08y+P9H/4FLr32Mi89\n/XUe+cDHuPjqS5x5/mkOnbgXy3Y4ec/DrCxf4Uuf+30m3/c4F155gdXrV/nIL/09XnzqSVauXGbp\nxP3cuHSObLaAimP+6rO/x8TMfOKR5XD81MN0durcGJyjPH2A57/x1zz8wZ/FtHSmMjW7CMCg12Bt\n+VUWjz2G43gcOXYv9a0N+p32HXLP2VyB+x/54Dg7WVm+wvqNa5Qnphn2e9S3NsgXy5qVuL3FxOwC\nzfoWja1NmvUdLNtGSgPLcei2mjheivLEFNRv0d1ZIW9ahD2BGnUxvCxWtoQfDjEsh2jQIo4kygiJ\n+i2km0YNQoL2FkYqh5MqvMW79P3je9mdmNkK1qCDU55D2K4uBb+xVHhbaRE7pXtVlotw0npg2LQ1\naSKOiDcuofpN/Oc/P2aIxr0GorEC6FusRl3itQvEzVVN4OhsQuG2sQPTQk4uIWTCfHTS2oH5tiH0\nZFhOk0qyFUS6OD7e2HMMAVGA2roGtUO3Zdb78bc99oFrP37oiOMIECgV0+t1KJSreKk0vU4bhMCy\ntYp6HMcIxFhZ/eEPfZxipcbn/vd/ztrN5cQGJWH3Kcafx3FEdWqOxz/9K3ew9EoTk7zvY5+msbXB\nF37/X9Kqb3P+5ef46Gf+ATOLh3jyz/5fLpx+nkee+ASmZWt24/2PMDm3SBxFvPT018iVKjheCsf1\nOPvisxy954E7ri0MfNr11TvmplLpDFMLB5CmXigDf8DatdPMHXl4/LSeK5SYmj+QuCZbVCanyRXL\nugRam8C0LLxUBnc+hZfOMOj1yJfKhEGAl86QyubIZPMIEWEaFjYKM1PSdG/DQpg2TnEaBRhOWuOF\nkKhsmeQLrFw12fYn59AsbY+o36R++ssYjneHAC6A4aTIHn4EYSfqF8m5kHx1RyiFCodgeRrUku2s\npMcFeg5s9LV/CSiM2XuQ+Uki+w3uyEJq4sXeN/Rrb7xCHPiIqaOotYuIiUPEl55BzJxA2CktITXs\n6tmzdBG1cQmx+IDetrIA8t9Dqa53aewD13780LG2dh2ZUNejOKKhFJbtIKRgMOgR9UJ6gzZhGDC/\nsESYuAQbpu4X7SpDJA/FAIShf8ecVK5YuoNeDtodWQqZyD8poigkjuOx35ftuPj+CNtx+eSv/gbn\nTz/Pk1/4LMdPPcL973sc3x9pAoVSLC6dpDo5A2ig3Fm7Qruxgmm545MK/CFbK+cYdJtki1NIIRj2\nWty8/Bxbt87jj/pki5NMzJ0klUnTayt6rVukcxVmFpcwTJvNW+eIAp/G+gqm7TC5cA9bt85jmSHD\nXkAchdhOilK1RnPrBttrl8iVZkjPHkcIQbuzSq+9jT/souKIyYV7cFI5glGfzZuvMRp2KVTmKdYO\nEIxGDLtdDGmQymR/bDNLFUcQjjBsD8NydaaiYp1hxSHIRKIqDvW2PyikgcxUtCbkA7/0lhletPo6\nceMW3qf/KaIwA1FAePGpN2wleCtqvmpvwuQSauUcavOqngtzswjDQm1c1sPK0kAcez/q5hnU6nlE\n7ZAmpbyd89+PvzWxD1z78bYjCHyklGSzRUDrEIZhoDMEx9XkiTjCth1cJ5XMWenXdttNzr38XcoT\n07QbdSpTMyjgtRee4fqlc5x7+TmiKBwfS7zFwrS6fIXLr7/Cxq3r5EtlcsUy0wsHOfPdpzl04h6W\nL53jvR/5FIHvs3Zzmcm5RVqNbdZuXMUwPsLRu0+xvb5KdWoW3x+RK5Y1ONTXuXnpu8wffZTG1jJh\nOAKluHX5eaLQpzRxgNVrpxFCUKgukC1M0t5ZoTZzDNtNA7B+/Qzd1ibVmWNs3DxLHIVMHbiP7dWL\nRFHI1MLd45m11WunqUwfYe3Sc0wt3MPmrXMUa4uk8zXa9VWaW9epzR4HoNfe5saFZzh41wdpbl3n\n5uXnOHTXh1g+/21sJ0WhMs/KlRcxTJtMYRIHrWDyVjNnP3T0G5gqIjdzVNud2CmtLRgMIBgg0iWt\nZtFeh9zkD96fEBgHHyb8xu8SXnkWY+4eQKF6DWSmjPDyY5q7Cn1EMCRaeY14+xqy8IN9u8T0ccTU\nEiHJzmgAACAASURBVPgDcNKIyjxkyxpoLUcTM+xES9JJQ35KkzkAtXFFS0yFI/0zNCDjZvbKj/vx\ntyb2gWs/3nY0W1v0+h1SXoaRP9T9CRUTRgH9URcpDKIooJKbxE0W9N1IZ3OMhgMuvvoi7/+5X6JU\nmySdy7N28xqvPPst5g4tjdUOajPzhIH/puMXqxPcvHwB3x/y+Cd/GVvC+z/+i7z41JOcefYbnHrg\nfg4cWSIaddi8cZmtjXW8TJbHPvJJhJA8/MGf5dWnv8rpp76Ck0pT/MBHUUrRaayRLU5RnjqM5aTo\ntjaJwoCdtUu46QI7a5fxhz06zQ2qM0uksmUsxyNTnMQwNJlja/UiUkp21i7hD3u066tMHbgPgOrM\nEuWpIwghCIMRhmlRrB2gvnmNQm2RxtZ1VBzheFncVJ5hv33bVSvy5Vkq00cxTJvVay8T+APqG1fJ\nlaYJRn38YZdee4tCZQ7zJ1gmxMsj3F0lEaXLhEIgomyS9Ej9c78PhomwPEQqDwitX+jp1wo7jXA1\nGBgzd2Pf90mCl75AcPov9M8NC/sD/wjDyyOnjyMrC4y+/q8Qbg5huRgHHoZEpR9haJWN2wkVUiJS\nBUTtIKKoAU5MHNJZYK4KvSb0W2A6OvNqrGqA62zrrHHmuP5+KodqbUK/qcWCAXH0MfDuNA/dj59+\n7APXfrztyGaK2JZLFIVYKRsEDPo9ut0WrpvC94dkswVM8617BdPzBzEMCy+d4dbVy0hpsHD4OJbj\nYlk2/W6HK6+/iuOmOXTi3je9Plco8aFP/10NcIMW4eYlXNvlscce1WWnYAiddaTf45FHHkQFQ724\nMgAUjuPw0KOPoh48hYh8SGSUhJQolZSKkkFWBBimTWniAOlcjdrcSRxvTzn9jbPLhmGSK89SqMwD\nYDtJX0YIjDdR1XUJVHD7UPP3HoY2EpuU2wegTdOhPHkYN5WnNncSL/3DEzJ+UIjbSnlxv0ns93Rf\nLfRRcajJEUoh0yWk5WIcehRVmCJsryFmTmBOLRF1t5EHH4Zhm3BnGQwL866PYRx4SM9pSYnIVBDp\nUnKNBs7dP0fc2YRghKwe0HNXUQjb1xEqxnnoM4jAR3V2ENkywnRwnvjPNKDt3k2liM4+iSzOIPKT\nOvs3LISbhcIkFCag30TFmjRCaQ7CQAOWm90rYyq1Z60S+ro3tx8/9dgHrv142+G6KVz3zkZ5LhtS\nqUyBgigKsR0XmbC94qRvIAzB1NwBUpmcdj0uFAkDn8D3KVQqDHo9hBB46QzGbi8syb52lcqHg37i\nNJws4JaHzNX2pIpQmtEmpW7Eo5BulnjQQvmDcW9GuYWEPbbHhsuXZ9m4cZaVKy/Sa28lKh4W1Zlj\n1DeuoeKYKPQpTx0BwLI9wmDE2vJpMrka+coctbmTbNw4i2FYxFFIoTqPl/keivFvUcVTsaJdX6XT\nWGPQrdPcuk62OPWWL7dsl/LUYerrV8iVZ4gCH8d9Z2eThOVqlRQV6SxFn/RY/QJAuFlkYQriCJkt\nJn5aIbhZpJuGMCAOBtpaKzcBuYm3OJJCeDmMTAnVa2ig2c2upAEIpDT1eST6iNGFbyInjiDyd5Yr\n5fy9WhbKSiHv+rD+/bj9mubufvN11g7qT0Z91I3TqJXXta2K6ehfmcOP/ng3cj9+ImH81m/91k/7\nHH5Q/NZP+wT2Q0ccR2y31wmiEa1BnTDyGQUD+n6XSEUMowHdYYswCgjCEQO/TxSHtIYNDp+8l1Qh\nS6k0gT/S4reFcnWsK5gvVTAtiwuvvkR1agbLcbjw6ot0Gg1yBU3U2Fxb5ehd9yGAbq9LbHhIN8Mg\niAixwPQwnAzdQYDh5YilwzASBNLBctLcWr7K9SuXyFcmsByPsFcnDkZYpkUqXWTY3iJfnCKbLeNl\nimRL0zhuBn/Ux/ayuJkCSoHjpklnK4wGbZSATK5KKlvGyxTwRz0sW5cRTdPGtBxS2TLmrgmjENh2\ninS+iuvlyOSruKk8XrZIr7UJQMoyiYYtPC+D5aTwMiWcVA4pJa6I8QpT5IqTyEGdMFa4qRzpfPVO\nPcfeli6r/YRmlIRhIiwHYXlIJ42wPNTK66jL30GtnkN4BUS6qP26tq4Rn/kK6tZryNwERmEKEUWo\nK8+gll/SpbrKgv6duvws0WtfQTVXEYVpsD2iS99GTh5BlOeJrj2HyE9ou5Nbr6I2rxCvX0TUDiPS\nReIL3yB67k9QjRXi7WVkeQ4Mi+j1rxFffAqRn0TmagjTJr74FGrzCtGFb6K2l5HleQ1+K2eJXvsK\n8cVvEV97HpGtIrIVRCqPcDOIwqTO7DIV3Su7zfZlP96R+O0ftMF+xrUfbxlhFOCHQ4SQOKbOomKl\nGPg9wliXTuI4wjRsOsMmYeRjmQ625RKrmP6gg2N5SClxLBdpGIRRQGN7k2e+9iWm5w9w9O5TvPj0\n1xkNBlSnZqhOz3L+9AuUqlrz79Jrp8kVy0zNL1KsTuB6+on51rXLvP7y88RxTGVymmvnX0vck2sU\nKlW219ewLJtCpcrK8hUMw+DkA49y4/IFNldvMXPgEF4qDUjCbgMVh6RSeTznKKBQUUTUb2FlKxRr\nixSqC4ShT72xCkCpNIOTKVLJ5Flbv8xo1MdxUqRyVZyknBoEIwbDLvnKHDuNVUbhiGymjFIxxYlF\nAHKVOaI4pDR5kDAMyFXmqYya0FrRRotBFytd0VYj7XVs09aeXOEQ2bhB2TYgU4VBA3au6DKXk9Wk\ngkEdJk6+s1p9po1x8BHi9QuEz30e62P/BLVxifDZz2Ge+pQmQrhpVBwRPvfHEMcYSz+jS3PSIL7+\nMtH5b2Cc+hTxteeJTv8lxv2/QHzteeTi/QgvT3z9tAY0f0D04p9jfuDXYXuZ6IU/xXziNxGTS5Ct\nIA89gpw8qlUxpIGx+CDBjVdQzVWY1D5w0fKL4A8w7/sU4Yt/hshUkLN3Ez73JxgP/TKquUZ84Vsw\n6MD29bFK/a6Lsxp0NOiatpaTqi7sEzd+SrEPXPvxPcPYpTsnZTspBIV0mbSrZ7SkNPTCK2t49p7F\nvVKKrFfQ5SQhEI5gFAywHJtQBGSyeUbDAcN+j+WL55g7eATfH1GdnGFyboGDx+7Csm2mFw4yOTNP\nOptj0O+Nz2v50nn6vQ6pTJZhv0uxWkNKg2G/z8VXX6ZUm0CpGH845PCJewgDn36nzcziQbx0hnJN\nl+DMTBEznQjVvsFRV0XheFYojiNu3DpLGPqkUnmuLZ8mCH0qpRm6vSYraxcoFafZ3LquySnlObZ3\nbmLbHuXSDPX6Kp6XxZAmnW4dy9aisds7NygUJslmyty89TpKKRbTHp6TTcqYsWa5CQmtmzB5t170\n/b4ufVqeBq3EQZh0Gfp1NDniTifjHyWUirXWH+wNGatY95yU0gPFa+dR7U3tr6Ui4pXXkbMnkYff\nuzeDN2ijtq5hPvGbyNLseP/xzTPIhVPI2bsRdorw23+Acc8n3ngWe2/LxGHkgYdQ6RLh2ucAhchP\nItwMMj+FLM3tvSxT0mXG20IIiTz0KGL2LuTKWVR3e7x/IaQuRaYKmkiyK9xrmJqUomJddjSspGSJ\n7rt9j37ufryzsf+4sB/jiOOIUTDAD0fjAVwpDJq9LcI4oDNqYSb9jEhF41aNY3kY0sQ0rPFHU1pc\nvHyaRn0T07BIuznsZIGtTs2wtbZCFEVMzS1Sqk6weOQYQkAYBCxfOqcdgW2H65cv0G032bh1g1Zj\nh+2NNSZm5ymUKiweOU6+WMGyHCzbxnJsZg8cJl8sc2DpJF4qjWXbGIaJMAxs12N7Y5XmzjaQ2JBI\ngyiOeeX1Z2j3WgjDZDQa0el06bZb9DptojgkjiNy2SpxHDEYdsmkChiGheuk8dws/X6L4bBLOl1A\nSoNUKk8uVyGKAtLpAtlMSato+H2Ggw5RFGBZLpO1A4AiCIZkMgVkqqxvqp1hTMl2slCY1wumm9Pu\nwukKZCaguqSzs9yU/liY1zRvrwCmO9ZO/JEiilCNVWitQ3sTGiuo+i0IhqjtZcIX/hQ5fy9y8UHE\nrlSUYSZgp8Y9SnYdBMLR+HtKKbBsDcygs0Vp7A0v785Wjfp752NqL7A3yk7dLvT7fUMIuK1kC4CX\nQ1QWCc9+FdVvYr7nVxOafF/30YSEcKgBWxrJEHMH1d3RWdl+/FRiP+Paj3H0/S4rzWuY0iLnFekM\nmpQzEzT6W6ScLJ1BA8/O0BrUGfhd8qkyvVGbSnYay7jzyXM46vPa689w/70fpFbde8q2bJt8qcJ7\nnvg45Ykp3vuRn6O+tYHrpWk36sweOExrZ5uttRXKE1PEUUR9c4N+t8NDP/MEpmly6Nhd5ApFUJBZ\nzDN/ZAmRKHl46Qxbayt46Qy16Rk9OxXHY8HdXTX126Pba3Lm9e8wUZ0jnyszGg7YXL1F6PvkyxWm\n5hfIZasMR13yuRopL8dw1MfzsniDLFEcUqssYFkOfjDE87JIaWBbeqF17BSt9hbV0gymioh9n5Sb\nwvDS4A/wnDTVygJKxZhOCgIBwUAvrsFQL+r5Wd2vKi0mZ60zRRUMwStCHGgSgYrAcFFeiWG/h5d6\nszDu2w1hWntkBRL5v+S/klJnXDs39LDv7oPOwv2E3/jXhM98FuGkEeV55Pwp5OIDhM/+EXJWay0a\nxz6IcehRwmf+SJcN184jDz0KTgqRnyR65a8QuQlUa10f8Y6Z49tkp4RE5GpE5/4G1d5EHnhwvD/V\nuEUshO5ZTS5x5052ATJE1W8iClOavLNzA5H3UZtXoDSLcNIavJ20BlIV6/scx/s0+Z9iiB/riezf\nTfytP8H/EEIpRXvYYLuzNi4LKhSVzBTtQZ1qbobOoIlpWPT9LgLIekV6wzYT+blxiTBWMYE/ZGXt\nGl/75h/z8AMfZXFee3MJIcmk83umg0rR67cxpIHrpuj22rRa28RxTDqdI5ctYUiDOI7o9ts4tovn\nZe445/6gQxxFpNP5sQmkUoowDGh36gyGXQQCz8uQSeexkidupRRxHOH7Q64sn+Hbz/4VH3r/L1Or\nzBCFISpWpNN5LMseA51SisGgS6uzQxSFpLwsuVw5sfu4ExziOKLTbdLtNkEIctkiacdF7Jb54mgv\ne/AKiAT4dXlumGQfMlksI7BS4Pd0/6u0iDA1lV91t7QlCejMLBxC6KPyszTrOxTKlTHL80f5nXiL\n7ybnpIiXX0QNO8jKoqaKTx/Xi39rHbV2XntvTR9HFqdRoa/BpLWOSBWQc/fq0uLrX0VZaYSKkQun\nENkqqrNFfP1lSBf1bFhxRgNMe0sfY9gh3rqKnL1b36N+i/jWqyAkcuEUDLtEr34JohAV+sjyPPKu\nj6C2riIyZchWUNvXQUoYtAnP/LVmICKJLj2NsfQBvR83mVdT8VuvQkLozMxJjXUT9+MnEj/wSWs/\n49oPAGIV0R91SNkZ/HCEIQ0USn9uWPRGbQZBl6xRpJabwQ+HOKaHY3p3LNqvvf4Ml6++QrtTZzjq\n88Lpr/Hq2acBcJ00H338P6aQr+pjxhHffvbfkEplmZ0+zPMvPUmn2yCOIzKZAp/4yD8gnyvT7bf5\n8pP/D4vzx3n0oY+Nj6WU4rsvfoVmc4uPf+TX8FzdZ+t0GjzzwpdYXbvGbslKCMHs9GHe/9gv4tgu\ncRzx/MtPcvPWJVrtHUb+kKef+UtMM9EezJb46ON/bwxacRxxdfksL77yN/R6LTQtW3Jg4SQPnXoC\nz8uM74PvD3nltac5f+kFgiAAFI7tcffJ93Ji6WEN3MOmVm1IV/SsUGtVEwtMG9ZfAy8PxUVor0J3\nCyaOa/Dq70B2EmXYmoARh5Cd1KAW+rofk5uGRBrrrRRI3m6ofhPVWEMlZbOxbqKXBWkQNTcRTgYV\n6tknEQXQXEU4KcTRn4HeNvgDVL8Blov0MlC4T19zdwvV20EIgTzyGNSvg+Wg4hDVuIkwBKK8AAjo\nNbSfFgLWLui+qelCv4XavIqYPoY88j5ddgyGqPotjFOf0sQUfwCGhbr8LGLuLk1zf/nfIJbej0gX\niM79jQa84qwem5AmpPL6tYOWfoAIfU00iWMQoLZvaGflYQdGPUS2QjxoI2aO75VM9+Mdjf27vB+A\nlliyDAcpBEYyFyWEJG1nCWKtK+haaTJODsuwsQxbZzZBnyg2ktfA3MwRyqVJ1jeu890Xv8LizHEm\nK/MgBKZpEo1C2o0dhDTw0mkGox4bWzfZ3lll6fApKpUZwjCg32+TSrIrlbAUR/7wTec9Gg3oD7q3\nZQeKM+e+w41bF3nPgx9jojZP6A+oNzaIohATtGK4ijk4t8RMbYFrty5w5vVneeC+D1Eu6Vkg07Bw\nEuFYpRQra1d56pm/YHrqII898klsy2F1/Rovnv46Ukre+/AnEhWNmDOvP8Mrrz3NPSffy8LcMWIV\nc/Hyy3z3ha/guRkOL56A1VchU9O9qB2to6dCHzH3gC4TegXGPa440CUxw9RsNoBhC7Yu6b5PFMCo\nrTO1wtyYWCDlG00ff3AopaBbH2d+yh9oQJCGTj4GbX1OQs/LCS8LTgaZLqGuv6ireKV5CAbE57+O\nmLlbg9vNZyEY6Axt8SHU6lnITqCCgc6AGzf1wHN5QR8vCnRGpJKstN+Czg7KzWg5JzerAf/6y9BY\nhVQetbWsgb/XGKtjxJe/izzyqO69jXpaxzAYJVl3rMkeUUB09TmEYWLc9VHk9HHdz+tsI1J5zSYM\nRzqrnFqCjSsoy9FzZoUpVK+pM92ppX3WwL+j2Aeud3EopcYkDCEkpUwNAYRxiFIxhjSRwsBD29S7\nVjqZu9KvieKA65tnmSodwnOymNKiVJygVJwgCHyt7ZerknHyhGFAHCoG3R5tv47tetiuLnf1+i2W\nFu+nmJrANVKUJt9qMPXtX1On28S1PeZmj5LLFAjqNylVJlBxSLB5WVtumDZ5ImQmSyNXQQhBNlOk\nVJgc2zgFgc9oOMC0bM6eexbH8Xjvw58gk84jhKBcnqLR3OTy1Ve56/h7KBaqdHtNXr/wXRbnj3P/\nfR8ak1nyuTJr68ucu/g8i/PHMMuHoHlD29P3m5rNlq5ohqCbg1RZA5Cb04umnb6T+RgM9Pe8ogYt\nBOSmEdm9e+d4Hj80csUR0dpFvfh7WT27latqtYzmOtLNguOhek2Em8GYPYlw0xroBk3EgUe1JuCo\nryWbpk7o96WzichP6Vmo0NcZWu0ItNc02Hh5PR8lTUiXUclHIYTWG8xWta+WZYObQ2TLerjZTkG6\ngFq/rO1U0kXI6iw2XjmrCSGdbRj2wB/qvlWvgbr0jPYD67eQqTxMn9zLqnoNKM/pgWbTQuwSRYKR\nJqmki/repIv6e14W7Ik9tuF+vOOxD1zv4lAqZhD0ieMQ105jSout1k22WjcAyHolZqvHiOKQm1vn\nGIy6SCmZrSzh2Rlubp1no7GMHw5JOTnmayfeRNJIZ7KaoOCl6Hc6BP6IKIqIwpBBT1Pcs5kix44/\ngOemx4rmP+qApxCS+dmjXL95ga8/9f9x4uhDTE8skHJTRL26pjBLiZmtIoQBUiDWbgCKOIqIoxBp\nGNqSRcXEcUww7LK5vUIqlWVr+xbbO6u33UPFcNij22tSLFRpNLfodFvMzdjcvHXpjnstDYNWewd/\n1McM+jqTUDGUFnQ50Errno2TgcZ1DUyWp+e4etsoIVHDFqKzBvkZaN2C9gqUD8Gg+Sa19V2vsR8q\npIGxeIpxLytMXJGlhMIUuOk9WSxpgGkldjQCcpOo5eegMIOoHtQ9ItDZWWkR1d7QPabcJOwso26+\nBNKCzhY013TpLT+lQWzjAmxfg+pB4lGP3mvfwKou4Ewd3YNiKZEHH9R9rAc+rftnTkoD0LALK+cg\nV0VkSih/iPL74/NhV5XEtPX2UajJL5ahxYQNi9HaZQYXnx3fGnfxXpyKJhqJwhSqsYKoHoBMKZEJ\nE5osY9r7813vcOwD17s4hJB4dnrcB1Eotlo3yKXKVPJziOTfVvMGI7/HQu0kzd4mNzbPcXzuUabL\nR2h0N1icuIuUnXtLEoCUBrXpWa0eH2u/rd2e0+4KZJk2luUAgjiKiSNtCCgNA+P7WnMo3tg1F0Jw\n5NB9SCE5c+5ZvvntL5BJ5zly6D6OH32QdGGXCXanZYpAkE7nyGTfrPlXb2ziB0P6222+9Z0v3nkG\nKr6DMDIc9oiikEtXT7N84+x476CI45hMOq8XzsI85Gf3BoQzEzpzCke6hLhLixcGTJyAUQdSJcTE\nXbo8aNhQO6bLg3ZaZ2pKofxeMn9kabDLTvxQfRchBNhu4jx8CdVva0WM2gFUv6WBdtCGVAH6Ld0n\nunUWOb2Ekg5y/gHi9hZ0myi3CKsXtDrFoAdWBoWhM6fioj73jInqtaB6WJNK6rcQk0cRS4+PM5hg\nZ4XGX/6veCd/BmfuBErIpN8kEFNLe0CWLhC1tzDSJdT2Dd2TK0yi/KEub/aa4GZ0CTAYoLoNrcqB\nVodXcYQ8/EgiFAzxoIO/epGotcnw+qsUHv+H2NFIMx2lgbr2IipdxDj1Sb2PKNDlw2wFjH3geidj\nH7jeJbFb3rvdmBHQ+nPjjWCmfJSVnUt0Bg2mSodwrBSdwQ7dYZMbm2eJVIQpLW1omAwoG9IcMwXf\nGP5oyK1rV8jkcoA2mRz0etiOQxD67Fqsb67cpNtqUZ2aodOoE6uYQqlCbWbujv2NQS/5PI7e7KNk\nmTZLRx5gYf446xvLXLj8Mi+/+k22tld4/AOfwXVSb3rN9wspJVIYzM8d45EHP/qmp2kBGpAAaRhI\nKXng3g+xOH1AA07yNE4cIU0HN+xBlNDd4xDh5lCWp8kMqg29TTCcvf5VuqL3Y7rgd5Ib24VRF7qb\nmk0oEqp3HGogy1T1/jI/WtlVtTZQO7c0YaKxgvKyxPVbiHSR6OJ3EPkJRH4CI1vWZUNpEDdWiYVE\nbd8g7jcRuZq2LJm/R0s8mQ4MO6hhVxtPZsp6mHrYBcvWJJBRX5cTZWJvEgwxvQyF930G+9DDGvSH\nXdTV53RWVzswPueotcn2n/7PlH/+n2DmaozV7J0UKlMGy0aYjs7Aeg2El0MUZzTd3bQRpRnNOEwM\nTd3DD+IevB9/7TLrv/uf6oPkqrB1TbsmgyZ+JMaqxLFmF4r9kuE7HfvA9S6JOBwSDdtIy02ouxJt\nVSHHSt/S9Mh6RZZmH2K7vcKNzbPkFkq4dgYpDBZqJ9mdoZFCEt3mWLxbLtoFlXE2IwSum6LX0Qtu\nHIUIIQn80dhRGCCdyyEQxFGEaWsKer5cHe9LCEkYaYbebqrmByO6vdZbXq8QAs9Nszh/gtmZIzz/\n0pOcOfsdGts3mazO6swBNIssOVX1PSYvXDdFNlNgMOiQTuW+L/DlsiUsy2Ew7FEoTiGiUnJCckxq\nGB9b6eMrFWtwCwaaiOEW9DZ2SpcQDWtv+NYr6XNubev3cJeJKKQGO5QuL0pLf9w91g8ZIlNCZEra\nTqTXACGQEwc1EWPhXmRhEtXZQUUBcvKwdha2HISbQaUKyMoCIl3QwJGbSO6xzjzFbq9OqUT8WOj+\n1tYyathFNdf0OZi23mevQeboo4jZk3eOGkd71jdKKfy1ywTrOnMSk4cQ1cW967nt2pRS+mdJBUCk\n8hpYMyX9vcaqln0qTuufmdZ4B6IwrUkYgzYqV9XlwXPfAsNAzN+bjDH8SLd8P36I2Aeud0nEfp9w\n1EFGI6TpIi2XOBiiezs+hpVGmC63ti8w8HtEcUA2VUYIyURhkavrr3Bp9SUEUM7NUCssYEiDXKrM\n8sYZMl6R2coSZtLjsm1XSxz1Gxxbuh8pDGIVI6Uc27tHUcgrlzRVPlcokUplUXGsh4sBwzC04rzl\nkE5l2dy8SbO1TT5XJoxCrl47Q6O5SeY2FfYwCmk0Nkin8zi2HjhWuwuUlEgzyWTGIXCdNArFTn2N\niereTJpM5rMc2+PwwXt47qUnef38cxxfegjbcojjmOGox2g0oFScREpJsVBjdvowl66cZmbqINNT\nBzGkvo7esIeUBrlsKcmuYi3ZFIdJvyjJsESsKe1xAKlIZ1rFeb1iD1t6ritd3QPBXWWKONRP+0ay\n0BYX7/StekOoMaglcBDHOtNBgJNGHn6EqL3JYPUSozPfIB52EW4ae+IQ6dpBzIOL+nfLSTNafoXh\n8lmCF78MSmGWZ0gd/xmc+bsTNX4I29v0Xv4y3vH3EdZX6Z/9BvGggz15mPSpn8WcODSWCUOBv3Ke\n/qtfH4OvM+iRWnqPJkjEEShQUcjo1jmC9Sv0Xn2SqNeg/e3PYyS/E0a+RvaBn0NY+j2PBm2GV19i\ndO00YWMdpMSqLpK+64NY2bK+X7kJnQ2+hUMztqdBLo4QI+1DpnZuatAzbVSvq4F5H7ze0dgHrndJ\nmF5B268HQwQxxDFSmggVowyt+g2ColfCM2yktLBNh0Ffz9rMFQ8wGLUxTRfLcBj0txGmx1z1OH44\nRAo5psQDlAo1pqcO8Nq5Z9mpr2Pbuof1noc+phduIFbijj/wOPSJwhBQREGAP9B2J5limWNHH+KZ\n5/8tX/rqH1AqTTIc9vH9IbXqHP1Bd7yPIBjxre98ET8YksuWME2LXq/NTmOdIwfvoViaelPPZ6I2\nT7k0xXMvfpWbty4hDa168d6HP4HrphFCcPzoQzRb27z0yt9w6eorpLwsYejT7bWYqM3z+Ps/g0Ri\nmTaPPPBRvvntL/C1b36eYqGGZdmMRkN6/Rb33/tB7jr+Hp1NxXEyL9TUPSs7rYHLsPT/OITtS2C6\nCK+AinwNdELq7ZNy2hhw/L7OsqJAL/5O9vuTBDrbOrNAofptbQljOagwQOQnCXpNdr7wz/A3rmLV\nFjHSBaKtG/g3zuIefggzX9P3fOsGO1/8FwjLwSrrbLb30pfovfQlKr/y27iHHkQIQdTZpvn132d4\n5QWizg5mcQoVhbSf/hyDi89Q+ZXfxixOj/ufKgoIG2u6x3T1JbLv7WvgylWhtaHLmKFP/9UnG+jh\n4QAAIABJREFU8TeXCZK+lr92CZlkxVZ1XiunJJc8unGW+l/8LxiZMmZpCuUP6Xzn8/Re+Qq1v/87\nWJVZDf5xpIEovq0UrWLNADUs/R6k8hrApo7qr/2+/jvaV45/x2MfuN4lIcZKDEHiXwVCxdpbSUVj\nORvXyWrNQcMmjgPiOEIIEylicin9lB/HIVIaDII+KZkj7eQZBD2GwQDXSuksxUnxvvf8PGfOf4d+\nt41SCjfl3UHgkMLg+NEHCcMQ07SwC2X0YzREYUAwGuJmsoDgxNJDpFM5rt84R7dTp1abY37qMHEc\n0+o1sBKxU8d2efDUE6ysXqbTaxHHEaXiBHcde5iFuWPj7W6PbKbAhz/wd7h4/hmarS1kLCnkS8hw\niPIB08VxPB575JMszB3jyvVXqbfWKOemWZg7Rm1iZk9ISAhKxQk++vivcvnaK6xtLBNHEZlslhNL\nD7Ewt8TQ7xJEI7JeQsBwEsKIimDzglbCqB5FuHmUpb3FlIqhvqyHjouL+j2sX9VDyZUj+vNRV4Nf\nbpK39cjvZjUAxhHCcpMylwHdHeJRj8ZXfpdg6wblX/yv8Y49hrRcVDgi6rUw8zXdJ/UHWLVFqr/6\nP2IWJpFuBpRicPk5tj7739J79Wu4Bx/YW8zjEH/9CtVf/Z9wZk9okDvzNXb+7HfoPvcXFD76j8fb\nOgv34MzfRbB1g/X/4x/v3mAN1t0dlJNCVBYofvw3USqm+dX/k86zf0b5iX+IVZlLHgJMxKCJ6tXB\nMHEKNWo//19gLtyH9LIQR3RP/zU7f/Y79F/5KrmZw7r0api6Z1Vd2BtDCH3U8stJBijASSUPIOGe\ngsbsybd37/fjx4p94HqXhIojqF/TfZTyIf3HVl/Wc0L5Wdg8B9LAKh3E6tf107unzQDJz0Knqedq\n3EQjTymG/R0tbDBqs9pcppqdxjFdgijAlBbZTIHZg0eYyM3hmC5rzetEItSDy4k1yuGD2ulYoYhV\nhBQG/qjP6sUzOvPx0piWjWnZFOwME/d8iE5jk3S+zPrls+SqUxSlx6BVx6pMIqXB/OxR5mePJgQU\npedwti/CqAmWhZJJNhMFSe9IUsqVeeS+D2lH3F0wF6DCEcJwUMQICQcWTjA7c5Cb2+eZr57EkAa9\nUUtvqxRhpIVkU16Go0dOsXTkfmIVUe+uMlk4iGnYDIMe9c4qWU9nnmEUaCHgYVuXAmfv1z2qO99A\nEkTXahrZKX3+2ZwGnFFXg5CTeftUbNOGYUL2sNxxH07kawT1dYZXXyJ930dInXg/0cp5okE7GfyN\nCZtrCMslbm9h3/UhnJlj+n4rBcTY00cxc1Wi9pYG5N3JXAXuwftx5k6OvcK84+/DmjjI4NJ3yX/g\nP0EkLE2deSWeYrdnMVGoe2duolZi2lqFUJq6nDrq6nKv39PXpF1OwbKRSmFXFzWtXwiQBs783Ug3\nQ9Rr6AFjaWhQGvV0yXBnJblHDmLySFKiVXslXhVDOaU/trfB9vSDhplkZm5237/rJxz7wPVuiVFH\nzwPNnNJP670tkBLVvIHITmqW2twjejHbbEJhATIVPU/Uugn9hgaw2yJGkwq0H1eAIU3WWzeJVYwQ\nMJVfwDa0NqBpWDiWh0Ix8LtsddcQiHGJcRj0ca0UE7lZ+q16knENaG6skC3XUHHM5MHjSMNk1OsS\n+T7CMGltrTHqdTAtm1xFq168kSCieluojdcR6Zq+djsNq6cBoZ+Yp+6BlZcQcaRLPYU51MrLycJk\noiaOsx4NCaIR+VSVXKqCaVhIIQjjgJ3OCrbpMQqatPvbDPwu89UTtPub2GYKz87QH7ZZa1yhmJnE\nszMIYaCAemeV3rCJa6WpuSWd+Q474Gb1w0Y4TEgbIXQ29IOGirWyRn4GtX0JkSpB6YCe69q+AnMP\nvL3fiSSDUIlskWb89RCFScLBAOX3dY8KUP0W8bCDROihXNtF+QM9fBxHBBtXGVx+gWDzGvGgi/L7\nhM11zPLMmw5rlqaJO9vsWqXIdBGzOMXoxmvEw44mQ8TR3sL/Rs1EJwUThzUl/40hBWLikB4gLs/C\nG0SvVBTir15g8NQfEW7fJB71iAdt4kFbH8u0NG0+mceiuaaV4AHiWGscZkqotYvQXNeA72b0/ctV\n9Xl3FTRWtSpItopYet/bez/2423HPnC9W0ImdftRRy/cO1f3ZIVAEwCSwUklDbBchDRR2UnUtacR\nu1JCt0eynuS8IrGKSdkZtjtrzJePcLN+eZxVvTF6foeMk8M0bDZbt1DEevRImlpmKl+iu3EdJ1sg\nk/aw3RTSSTPqd7G9NJbjkilq8dhMqcqgXSfj2VrPLvRRkY+wUrrvIySkyojsFNSWNKlh8zxq1EEU\n5lE7lxGVw6hRFzF5UtPHB3WE1MAi3Cxhf4dW1CPl5PCj0R3XYpuuHg9QMbGKCSOftJvHMhxcO0uY\nbO85WXKpMgO/g2cnc19K0extYEiLIBqhnAyidEA/VFhuopiR0TqEmQn9vgkBXllnZv06IjOpF9nu\nhl7gywd4O6H8PmrzGpRmEMFIO/tmq4jmGmLxftTrT2nZKMsBFWEdOKXvpUwyGIQe3AV6p79C48v/\nCpnK4x64D2f2OAgYrVx4y2MLaaAGHdSoj3AzWkw3oZWr+gqqflNfZ6T7nSRZvr5lCkwHkZhD3kkw\nGR9A35PQ15lVUhpXUUj7239M61t/iFWawVm4G2viAMofMLr+mn5drqazLNhjO4ah/lpKRHFal1Nr\nB/X/YAi9hlbRT+U1cQRQpRl979x9Bfl3IvaB690Sdlovar0tXVIqH9QSPZXDulxWmGf8x5+fBctL\nFglXZyHZSYQQBJE/dka2TQdDmsQqxjZsDGmQcrKsNa/jmB5hHDLwe3QGDQxh0Bu1GYUWxVSVem8T\nUFSykzT7O3h2ZjxTZrkpZk4+rIEWrVIvpIEfDtncukB55iDpdJl8dRqAjGcT71wj2ughvIIeDh20\ntHeSUgjD0oWqOGJ3BABpaYWEqXv1NY7BWqIQulyIAGFiSJOiN6VBycnTHTbxwwGdYR3b9BgGPTqD\nHUzDJohGWKbLMOjRHTaIogDXShPFIe3+DqVUhU5/Cz/s0xu1KGWm6Q4bZLwiQkhE4bas1snqGS7Q\n+oqZWgJmKV0a3H3w6Nf1e5qfe/sLZRhAc03bdThpCHxdesyUwE4hUzmQkrC1pYd5OztJppdLVDMk\ncu5u4kGH1rf+EJnKU/v7v4NZmgYhiLt1Os998S0PHfVbGBMH92bPQp+o30LaKUS2rBmAhpnMv8k7\nPbmCoT5v2DN7lBKKt2V2oQ/b11GDtp4lc7UrdNjv0H76j7Cnj1L9O/89MlMEBMHWddpP/zGQ9ILf\nOEg//lqMbV60bmNHq3HkalorMQrGIEw4SgafI02CSeXHxqT78ePHPnC9C0IptTfAmjL35l9SJTA9\nvQhKA/wuyk6DV9L25CrWTX8nN37qlYBtOEhpIIUxHkB2EjbVRG6GKI6QQqKCPgvZGURSDpwtHUIp\nReSH1NIzxLHuaXnZzNgzyx8N6Xc72I5mIRqmHnJWUUinu8H1G9/FMCxSXkGX0YTUrYpsTX9ue3pw\nVcWIjJ4D03RxYPO8/ro4jxg0oHlTX1chWfBFMlMlBMpOeha2B6ZHLT+fnK8kRrFQPZlcv2ShehIh\nJDudVTw7SxCNiOOIiewMariNDPvMZSc0ZkZ9HGGSzk0jY5+UGpF1s4hogOqt6v6bNCEaIryJPbsM\nw9IyT7vAmyrvDTaj9GJtud+zl6LiSGcDdkpvKyVi4ZQGKyuh4YeJmePmVazKPEauyuDcU2Tu/TBy\n4tCbHX+lQewPiLsNnAOnMIuTGviVwt9cJmpva5LEG8K/dZ542MNI5XRfsLlBsHEVe+YYRmnmzQv8\n9s29z00bSrN7oHfbXJ8uMcZadqkyp+WlIMkSDeJhl7jfwZleQmZK47EHf/UC8aDzA/+O3hjRyjlN\nhVdxAqIxwssjJw4QXvousjAFpkW8eQ3z7ie059d+/ERiH7jeLdHdhqCn/869gl4cY1/3T0bJH62b\nRw1bMOqiTFcvhG4eZbqIQYM4CpJ+lY0K+rq0Y3mEbl4DhZDEKkIphS2ELjF2NvRCedfPY2UnGfR7\nnD/9PIZpUZmYot/rkMrk8EdDtjfWKJar9HtdalMzDPo9Os2GVnU3LQ6eOMGRw49TyM/qnk93S+va\nDduIcJQoMwR6AbFToEJAaKBOlzVQK6WzluLiHsPS7+o+lzSJgwGB39UlRRJgEAa01xDSJFTaR2tX\n4DUOfVQcIL0i+XSNINTK447pYagQpTQrE2HqTEJ5iGCgFTBMDzVsY0gTFQ7AyuhMY5dlKED1tnVv\nK1PVPcp0RRNnwmFSTgv0uW5d0H2u7PdQyhj1iS89o4VhUwXU1jWEl9MisXGkF3vLRWTLgMA8+BDZ\nh3+B5tf/L3a++C9I3/9xjHRByyBtXCV914ewqvNIL4tZmsa/eZbBpecwS1OEWzdpPf1Hd1LJd0MI\n/I2rNJ/8PdL3fBjikPZ3/oR40CZz/yfG5WgVBoT1FeJRn2DnJir0iVqbjG6cRVgORqaEkYgj74ZV\nO4CKAjovf5nsg58aZ0r21BGt/B6GGPkKg0vPaZZkKo+/eoH2U58FeSfgq9An2FlB+QOCjasQhYSN\nNYbXX0WYDka2rH3GhCDuNZHlub2BaSeNMX0Mka+hgiFGtoJIFdmPn1zsA9d/4KGU0rM/jraDIPT1\n4hYFe6yoXSBDQHtVK2ns2pWnStpyIwr0Am96SS8psRgRkvagjiFNLMNhGOghW8stYBz8AKqzRnj2\nL/WxgDiKsGwHL51BoTBMC9OyyOQKxFFEoVLDsm2iKCKOItxUCsf1MEwL204xOXFi77oKc3rxttIa\njHaZcQn7Lu5uIqShWYWOtsEg8iGI9PamDSrS7DMrBSpCGCamV9KZTpJ9xVGAlCYKgVLaRFEmNvPS\n1JmmEhIlBJ6dIYwDYhVjGg4iM4cSMmH67WYGKQ1SSiGMFEoaCBVpVpy0kqwmWUgHCVFAxfoemq42\nkxw0NVCnyxAmSvG39YLeFEL368iUtSKGNPQ3g4EumapIM/iclAYxIPfY30VIk85zf87g88+zazxs\nFKZIHXsMAOlmyD/x6zT+7f/G9uf/B4Sth9szD34Su7ZAPOxpQ0f9pgGQvufDhPUVtj7732iLEdul\n8OF/hHfsvWMgirp1dv78nxO2NlFRgDAdRsuvsr36TxGmTereD1N44jf0vd+VaDryMNmHPk3vzNfo\nn/kbhGFiz56g+iu/rcWD81UKT/wGzSd/j80/+K8QdgrpZcm99zMMLj6r6fFJhK1Ndr7wz4g623qu\nzbQZXn2R0c3XEIZF+tTHyR28F4IhRq6SOFBr9RNVX0EYBnTryahJvM+Q/wnHvgPyf+ChlNLmg4a1\ntwBmJ/UCPmxpDyjT2QOvyE/+a6q46m1rinSqfKfihN8HO4UadQj9HqZXvE0zT3O5hBDEnU3C05/D\nvOeXkPnZPd+sYKA/Wt7tJ6uzQsO5gwiytX2JVktTkoUQ1GrHyGUn77jOKApYWT1NJlPDkCYbm+cZ\nDlsYpkOpuEC1chTjDeSSKPKpN5ZpNK4zGvWS+bMslcphioX5cSkpigLq9WvsNK4R+H0sO0WldJBS\n6cB4n53OBjv1a5SKC6ytn0EpxezsA4yGbdY2zuI6WeZmH8Rxdj3GFMNRm83N83Q6GygVk05XmKgd\nI5Uqj4/N9iWdEWendMnLK+oxBnT/EcvV9yoxTBTfI+NScax7fuuXNWsxGV4WqYIeAejsQKakSRKh\nj6gd1PJNcUTw0heJvSIKgehtYx77AEamNC5jKhUTtXcI6yugFEa+hlmoESy/QtzeQiYzgnFhio3/\n+78k/4FfI3vvhwmuvoAKRhjTS1jVBf37GcdaCLdbJ2ptogwT4aTBy6FWz49p6NLLYkwtaSZfe1M/\nkIW+zpSa60T1VYQAszSLWTuge01xCMVpwtYmo8//dxiPfAbryKMYuSpxexOiEJkujv3PwkF3zPKM\nvvavkT/za4hsBdXZRjopRHMNokDfsyjQs3CWq7UP00VEaVa/3u8jZk6M1Tv24wfGD4T5/YzrXRF6\nqFcriEcQ9InO/zVqUB8zsET5AMbhxxGmQ1xfJlp5CeFkNXCFI3BzmEs/m/g/dQjPfwmRnUC11xCR\nTxTHGIfej6gufd8z2V2Q47VXUO11jBM/t2db368Tvv6XGEeeQBZ0b0QpNRbz7ffrNFu3yGYn3gRc\ncRyyuXWB7R2tVed6BTyvSLe3xZWr3yQIBszNPjCecQqCIVevPcX29mW8lN5WxTGd7gapVIliYT7Z\nb8Dy9WfY3LpANjtBKlViMGxx+co3mOhusjD/CIZh0R80WFl5mW5vC0Oa1OvLDIdtTNNBSMna+mtY\nVor5uYcA6A8aXLz01f+fvTePsSy77/s+55y7vH2pfeuu3vfu2YczpGYoSqS4iJIlS44CQbYlJDBi\nR7ARJ4GBIMk/ToIYcGAYdpwETmBb3iTbkrxEFClKIqkRyRnOvvUyvVdXV9e+vfVu5+SP361XXdM9\no2Fs/zNTP6BR6Kr33r3vvvvO7/x+v+9CkvSp16ZQSrO+cYv19ZucOP4FqjsJyMvV43e4WnF3wD3D\nJrIwBhWoDz38k3dOLEQ25vMZZx3VPCmbE2shi2B9GRoTqKFp3PINAXv0R6QdvHIT013HP/KUAF4a\nowL97m1hF68IR6k5g95eILB9VHMamgKa8SaPweiszMacJWlvyH2Yxqj2KsH0KZRfwPW2cOvzuSpF\nMJgXmaQHCQJr37FUiTqy+crbcoA8Pst5eS4jGD+aHzeRToNSct97IWiDN3wA8/m/gDpwQfQUyZU7\nO+tiNhl3UEMH8Ifkfbgkwjz9p1FTJ2WjEJYENt+cknNJIgFkeIFQBUYPCchl3w35P1rsX9lPQihP\nvtxplPNjQvTBp1ChKCe49Zuk7/0eeuIcqnEAl8W4tRvooz+KOfqjkPRIL/0O2e2XMKe+CM7i2iug\nPbwzXwUTkM29RHb9jzC1Sfr5TrwUVB5+OoCqz5DdeRXdXkHVpnCAXb+1W93dF0NDhxkaOszG5hxb\n2wsPe8lBdDprHDv6WcbHTqGUIY7bXLz0NVZW3mNi/CxBUMI5x/LKFZZX3mN66gIzExfwtcgopWlf\nfLqSLs4vsb5+m6Xli8xMP8HM9GNo7WFtyvzd15m/+xq16iTDw4I0y7KYamWcmenHuHT5d9nYnOP0\nyS9Rq03yZve3aLWXBm2t+flXSZI+p09+iUplFJDEfPHy15i/+yonT/wExvi4PIFjcymonRav8YFC\nLhKsP5jgmkbYK3+EGprBbdyFoIya8UU4N+lDqSk8paWrqEd/Gvved9BnvgBeiL34TdT4SVySK9kb\nHzf3BmrqDCSRJJxr30Of/nHse3+EPvE89vK30J/6xfy2K+RVupPz7O6QnUMRpFVaWs69bVSpATNn\ncdd/gFu9hdu4B1Eb/fhPQ2MCWqvYd/8AVR3BXnsRNXwA/cx/ClmCvfEy7uZrqNoo+vGfglID+/1f\nR5/9MVRzCpdG2O/9OvrCF6DXIvv+P4fOJmb8OOSJi6CIu/MWdum6fD8e+6oYaK7Pk734G5DGmAPn\npN1eHYHeNvaNr+GWb6CmTqMf+SJ4AfalfwXFKu7O21BuYp7+M9Ka3Scg/weNfdOYT0JkscgI2XQg\nxKpyyDsu220TxvfBjoMyevw0KqxAeQQ9fha3eXu3xacUevy0VGBBGTN5Hpf2cO1lMpuS5TOth4ZS\nqOo4qjyMXb4squw2xa6+hx45tqd9KMrw+b+P8FZLpSbDw0dEh1EpgqBCpTJGnPTIcjSltSlra9cp\nFKpMj57C722I6O3WXbykj2mvQH8b5yyr69fxvAJjoycxxhcUpfEZGzuJ54Wsrl0bJCOlNKVSE609\nwrCCMQHFUhNjAjwvIEtFVSOKWmxs3qFRn6FYbGJthrUpYVilWh2n1VoijjsCbthJVGiZYe2ATEpD\nUB5FlYYEiPJBkVcCrrWCOvSkkM7TWAA4UQd3+xVUZVh+55wQZsdPCOw9iVAjszmwQKGK9QHgwd56\nWSplnattNA+gxo/n1Y0V65GNBdzmIm59QbQQId+1KJTxRHzXOiHyer603Jaukf3RP0TPnEUNzZB9\n7X+D7hb0tsm+9fexdy+iTz2PGjsGWmPf/ib25d9Gn/wMLu6Rff1vC9hkaxH7zh+IY9vSdezl78gc\nsFRHn/sC7s5bkrzzsO/+IfbKd9EXvoiafXRXnLg6gj7zOdyNV6Evihw4S/bt/wd37wr6zI/ibryM\n/f6vSxJ95bexl76DPvk8buEK2Yu/sT/r+I8Q+xXXJyF27DR21MTTPnb+NezGbVlorBWS631fMbVj\nVkiePApVWdyynFSsNCoo76pT7HChkp7MhT4scQFoHz1+Bjv3Azj4NC7uQW8DN/ssNotl6L6j6q5U\nPoTfscNgjy/X/REGFTyzd5Yg+ohuYFuSZTH9qEWp2MQPyvmD5DECjpDn27hNv7dFEJTxdwwf8/C9\nImFQodfbxO68V6UwO1JNSlRBtMp1IVH50R1x3CFNe6xv3KLTXdvzuv3+Ns5lZL0N6KzJefmF3c/I\nC3dR4I0HoeYPRBYPgChu7k1UfRx78Q/AWfTUWZxzuOXrwtVLY1R1NJ8waNTIYewb/w4ScQ92Cxdx\nqzdxd96UFt/mAqo6JjJT1RFBX9bG5Z4q1VGF8qDCV4BnPIb+1H9LMHV89/ychWJ1D/9MH3ocdfbH\nUFEH+9Y3cGt38jlXHfPML+yaP9oMe+nb6Ee+jDr5HGbqNOmv/WXYXkaf/XGyb/199Kd+HnvpO6jD\nT8g5KSVtxPclezU0A/0W9tbr6LM/LuobIHOrkUO7bUkQhZGbr2J+5r9HT58Gv0D2jb+DfvJnwQsw\nT/4s6viz6O4G9tJ3/uTPaD9+6NhPXJ+E8EJZVFwGJsDefQO78Cbm5E+gKuO4pEv65r/Y+5wdj6id\nsFkODc9FTnes3QePd5JYlBGb+j9BL08phR46jJ17Cbcxh4vbUGjQcw7aK2jtEUcttPHFEsUmZDtJ\n06bQWRGisFKSkHOQxAMmj+9Pbvl5OmcloTkr4AdtJFH7niz0QnvOH+c/0OqRS6EGrs73/2HPMR9S\nJjpncz3DJtXKOHvwR7UpNA7f+GBUnkjzFqFfkAXX/BBE1qgrZOrRo7jla6ihg5ihnGxuPNTkKQE2\nKC2PO/oZ2FqWRb42LtWv8QXSP3wYNSJtUYpN1NAsauwwoGHsKCiNPpU7F6cx9vv/HFUZRl2QNpop\nN6g++dW952eMVHf3O13vcNd2Nlv5fabC0q5j9E7YDLx8GcvtU5zNUFOnQWncjVdwt9/AfOkvf6he\noDr8BN7P/3XsxT8k++2/jn7uz2HOf+HhD97RZNypykwuUbXjPB2WBzqLD8hV7cd/kNhPXJ+E2FFY\n6G+BTXCtRWnVDR2WhaG3sQtvz8PFHVx/U4bbOOz2AiqsCWE56QrRs7WIG82ld7projJebORahR+h\nCx1WUMNHsIvvChdq9CSF6jjGBKCgUB7aXdOVGiALB8nT5RJWSu1a3X9Q2EzaY4UGWnt4Xkgcd7Em\nwNSmpDLZWTB1CbwCRimCoEy/v43Nkj0JI8tSkrRPGFRlJvZDhOcVMManUhrm0NhJWeBwu0oRvXWp\ntsIKqARcIKAEbeT6D4jGH6F5Wm6iT/84Lmqjz/4ElAUN6HZMHDvr0O8MqiQ39yb21X+DfuwnhaB8\n5y0xTdQeqj6Ou/WaADKmTuHm35VqbeQQNKdxN14RyPyhx3G3XsNdfxn13J8TROG1lyDqSOXT3RJZ\npzRBHTzP+/UI7c1X0fPvwtai3FPN6V0x4PtDafTRT+Eufgc3cRI394ag+epjEJbQJz5N9se/BsW6\ntBYRoAWdTdmcdDfFADMsw/o8Lu6iz31eWpwLl3DnPi88t86GIBY7m1AdFW3CqVPYt78pzs9v/x7q\nwHkICg+e4378R4n9xPUxD9n5ebJQ5Q7CqjqOvfs6dukioHBLFx98os3Ibn4XPX4G4jZ26RLmyHM5\nrB7hNy1flmrOL2HnX0U3Z1GVUaooXHed7N7bAsVP+9jlK7juBqoyhs1V0R0OPXKCbPFfiyzT0GHM\nh8xrBjtmbQTRuMMzs5kksQ8NN+CSeV5ArTrJ8soVtrbvMlSfAYJBQnQC5kcpQ6NxgNtzL7LdWmR4\n6MgAFdlqLRJFLcbHTu2xavkoUSjUKJeG2di+y9TUI4T3yzQ5cEEJlfRxUVs4c3EXslRmSv0WyqZi\nSfJh7zbu4KKOVAWFEhiDTbqwHQkoJ4uxG3fQ5WFUdWi3sio1xNI+lzayb/wu+vGfklZglkLckxmO\n8bHv/AH6yT+Fff13UGc+h7vxAxGUNR5qaBqak6jRQ7j5d7Fv/q7oEvbbMmfbXkGfel5aoM4O3IgB\nVGMC+/Jv4nrbmM//RaiNSBtz5pyIHttsAEjRj38VG3fJ/uD/QBVqmC/+lVwhX6FPfxb73vfQF744\naPW5m69i3/gdMD7Zy7+JvncF/Zlfwm0tkb30G2JlUh3BPPoV3J23cbffxN29CH5I9t1/ij7yBPrp\nn8f82F8g++4/If29v4saPoB57s/L9Zs+A4WyyD0FRdTwAQGyINWY+hBjz/346LF/FT9J4RfAZuip\nR2WQvPguyi+iZx4TzcLiLrtfFRvo0RO4lSs4m2IOf0aS2E5loA16+lFcZx3Xv4lqHsQceJIU8LQn\nSK7tBSHrTp6HLMFtL2C1R18F+bxJUSg2UcUGqlDLK8O9kaYR3e46mU3Ybi3inKPdXiHwy2jjUSw0\nCILSLmjkA2O3QlFKMzlxjs3NO1y//h06E2cpl0dwNqPb2yAMK4yPnQZgdOQ4a+s3uHXreyRJj2Kx\nQa+3xd27r1MqDTM6cuKHtqwwJmB6+jGuXvsW7137Q8bGThH4JdK0T7uzShhWmRo/i/IstrmMAAAg\nAElEQVSC+2zu84Vde7vk4Q+JbOWaUBmMjwpKqKAivLzWKnbtpiAFky52/Rbe7KfQ5XwzUW5CoQLl\nIVEgKTdRM2dQQYnse/9MSMzGE0DG6Cxq+jTu8gsCAT/xGdy1F8UhuDIiSMHKMCxcEQuSI0+hRg7i\nFi6jpk6hxo+KwvzQzJ4WoBo/hvnCX4LtFahPSMV361XMZ34RtMK99XXU1Bnc8AGI++hHvoR+5hfk\nHkhjmUFlMtf1fuF/kfbq5j1cqY6aPo05eCGXvTIi6WU81JEn8WYflQ2Q0oJuvPkq+rGfhE/9HMR9\nadl6oWyUSnXM5//SwEEArYXk/KW/As5ht5dxzWnU0Aw2J1Hr+uhgw7Fvc/LvF/uJ62MeewjmuZSQ\nUgp95HkhhuYzIv3AF0mhR45DfYqB425vMwdzZDl5dQR94Clwlq3+JlnaI+qtUwqrqLBMf/IsRhmM\nNhjtkdmURmmUPSD5qEWaxeixU1LFuft23ii6vQ2u33yBLItxzlIoVIU0vDmHVoaZmScYGz0BSlEI\nawT3AUZ2wvdLFIoN9H273XJ5hJMnvsCd+VdZuPc21qa5nFXI9PRjg2sXBGWOH/0cc3deZu7OywNp\nq1p1gpmZx/GDAtZlGONTKNRFYcM5fC8kLNTyWZ8Qm3fmX2I2eZgTxxR3F97g1u3vDXQbg6DM9PSj\nIle1M79zFvwH39cDn/XO52kteuiQKKTksxaXCyNTHkEVc6mrNBZHgGJdtCK1FqBEsYp75/dRZ35U\njBTzVqhqTktrcHhW2oW1canCGpOwvYy7847M5HaALtVR4QhOncQtXcUtXZME5xcFfh73pNIqN3ff\nm8n5WZ0taS8aD330aQFNjB9DhRXsjVfQ5SGUTbHXfyCt0+YU7tbrqLHDqPFj2De+BsMHpFKtjeFW\nbkoSH56Byghu8Sp69hERyN2ZnaIkgbZXsVdekDahCXBzb+Pm3oRCFf3YV7Ev/Qt5raEZ3OJ7sOMe\nffRpbH0CF/fJcjK2Coqin6mNtCW1RpcamIdoOO7HR4995YyPeThnYWshVxbvi7QRVhbEuCPk1aQr\nCuk5wCG79zb25nfxnvyze5UtopYsYjYheeUf453+SfSICOdu99bzpONQaFKXkqQRgRdinSX0Cig0\nlYIgu1x/Gxe1sYvv4DoreOd/lghIbYqzFs/4FPwSzlmStP+BQ25jgl1Sc558jAnkPPIFN8tirE3x\nveIAoQgQJz3SNCJNe0RRB+syCmEN39/r1LwDd+/2NvG9EM8LcSrBuvi+Cy3qHSa3hrFZimfKFEOZ\nL6b5DFEbRWK3CJIiLj9+HHewzqGAQn0Kv1jbtfTYgZfnvmYf+DnbDHftxRyIo9CHH/TkcnEXe+Vb\n6OOfhc4mrrshbdfc7JDKUG6nEg94W9gsf0wurZSlUl2sL+C2loQUDeKN1V4XRfb6mLxeawXqk9Db\nkvnWxAkRyL13RcjMQVkqtwPnBy0011qV6vzuRdz6Xehuoj/7K9gX/yX6R35JhH3/6B+hn/7TuIUr\nEPdQzUns7Teht43+9C9KW/SFf4x+4k9hX/9/c2Kyg3IDfexZ7JtfAxOgTz036B7I+/WgMSVJ5vIf\nSdI786PY3/8/0U/9DPatb6KOfQr3+r9DP/fnoVjD/v7fEyRl1BFbkzOfI1u+hd1eRQXiKu3SBF2q\nyc/qEKY5hS4/xEtsP3ZiXznjkx4Cw8517rrrECbihFxqSvLyCqKSXpsatOoGElADjT0JF1YBBVFL\nzAsHSD5FPQdHWGfJsoTMZaiCKIUrFL7xB8kgSWP6d18nXL2GCspCcvaK+NYSeAUUYK0kqijpEXgF\njPHo9tbJsiRPDPJTaYPOf6ZJn8wmeDmR2PcF6l4sNvG8B+V2Or11kqQnYI2giAK60RYm7aJQhEGJ\nLEvJbCJVoTI0yzNobYjTLTIrbUetAjLbpxA0SWwbhUZrjdGOzPUxqojSGQ5L5lK68RxKTWOMh6eL\n4FuU9jGqDIFPYrcwuoBWBTLXxZHhcZ9+4Qd80pRzvlX9A4R2swS3eBGOfgaqw6gsETRfloqAr1JQ\nG8VefwF9+FkRjb2vSlVKC6x+ewXXWgHcfS0+B8UqengGauO4pC9zrn4bqsM52q4kjxs9hHJWzlnr\nnPqQyWN3kJP9thCka+NiuaLAvf17qJPPQbmBffMb6BOfxl5/Cbe1iJ59VEwetZY5VXNaqqLmNGrk\nIPbW66jhg6J2kaWow0+KGWWufEH++e9satzOBkcpqDRx8++Ks3KhggukYiQnrRMUBrqfujaG8ovY\n5ibK5RSMJAY/ELZFoSL0gqibP9/fdQDYj48c+4nrYx7OWUFQZUn+L86Jx+SSQekejUEANXQYL3c7\ndr3NXEk+ld13Lsfjnfi8tFHiLplSRDYhtSkmtzpJbSrWJjnfqp90KYdVPOOzvDnP1a0VjjSewPNL\nxEvb6JUOUa+LH4aUyhV6nQ4Th2Z59dp3ODZ1nvHGARSaJO7k7TiLtSml8gg2S8mSHlHURmuDCSo4\nILMJWRZTeh/i0FqLdSnFQp1CUMmTXYHMJiRpJG2+oCIJ0sswWiSdrMsGXLDYrhGlyyjlE5pRomyF\nhn+BbrpKwRtnO3qPwAwTmiFS1aYT3yT0RvB1nShbw/hFMh1RC0/Sj5eJs3Xq4Xk68VUACt4oRpdo\nRZcBRdGbpmgmBLL+kMpLaS0oxHJDZlSDz9/hNu7gFi9BUN5VbHcZrrWA622h6lOoqbMy97z2AvbS\nN0XNojaBOvSUzHxWruNWb6BKTUGkVoZ2tSt3ZkVdQaFmrTU63/lHVL/6V2H5xm5bsjkpcyu/gCrV\npKKqjsjcrDGJm3sLdmxbRg9LAs5S4Z8NiaCyu/OOKNz7IW7znszTtIfrbopr9L0r0n4cOShtvEIZ\nhqbFlkVp0TusDAuIAkhuvUH/9a9T/en/Buf5eX/HoSZP5shV0Keex775ddTRp3HdTdSxZ3PhXIM6\n93mB6Wdp7iFmUcUqXqlGevm7qHKdbOkGujIMOLIkkteojuA6m5jZC5ixw/9+X/JPYOwnro9xSGsn\nFqi4UqK6YILcSVfn3CVfLDNslldHyGP9oqhJxB1ZEPvbud5bMQcKiAI7SmERJYQ0S9CeJstSafnt\ngcXvtvoym5LiKDXHpPXW7+H7AYVSCaUUpUoVPyzgGZ/Z8ZN4nk+7v4lzlmJ5BN+ExHEbazOSuJu3\n/zTFYkMWaqQ6UCjC4tADC/16a5GVrbscGjsBOXowzfp4JqRaGR9UcNZmeEog8JL8HJnNUErjnCX0\nxvFUkX66hHOC2LQuwmFRaKrhMbTy2Y7eo+hPUfRmSOwWoTdCNTzBeu9V4mwT51KcS7G2T8EbpZcu\nYl1Klq2T2h6Bacr1s8mHAjNc1MbdfgM1eQI1dUp+2d3EvvovUQcfE4h9d0t+H/dwWSrqJRe/ISaO\nQwfFiNMEqKGDcr8ojVu+ir38B+hDT2FXrqFay+hzX9nl8Tkr91UOPEje/TbJzTfEZcAvyDGdFdh9\ne00AF0E5b/8qkVDyQ9TMWQaJKxOVF7clhqOkiYAjdJ4cGpPyWjueWzsqI8bLN1qZnE8OqNhpgzMy\nK4jJvFKMr3yfdOEyLuqgVpZzLpgG44kU1soNuR7DuQP45qK0Ozsb+dzMw63N78pw9dty7ZVBVYdQ\n5Sa6u40q1UXM2FpUbVSq2aLMgj+ITL8fHxz7ievjHDaDbs7R0iZPVtFuX788Ipyefkv8nGaekC99\nZ1UQhqXmbtIrPSjimmUpW50VoiTC80KqxQZhbuTYiVqEflGItECU9ImSPiYXHjWeh18u0I1a+JWA\nark5ENNN0phUJ7T6W1QKdYpBGT9XX9hJGrF1dPotAq9AvTyEd5/ye2ZTWr1Nuv0WXtKn4izlsIbD\n0Y+73F27ST/pEqUJWmvKhRo6n4dtdlcHC4nRHlHSk5m9CVAoorRPM/fq6iV38XSR0IzSz1Ja0TXi\nbIuSfwCtAkRRTRGYBp34NtYl+LqGVmKSqZVPmrUl0SnRHHQuxaiQOFuj5M/i6TU8XcY3dbAfvrip\nQhWXxXuku9z2PfBD9LHnobeJvfeu/CEoyqLZ3ZDn9DZR/gkYOZzD4U+IXxdg77whiihbi5AmuM0r\ncOx5cfb1fMgyKDfI+h3s+gL9N38P290ivvhCbgrp0LVR/APnYPoMeD4u6pJYh9+cxGUp8Vu/T7p6\nGxWUCA6cxWQx6uB5bJqQ3rtGcPgxVKnOjmqIi7skm0sY7eNNHN19v0lEsnCZ9M5FbG8bXahgxg7j\nT59GlRvS6ktjspXbZGvzRBe/g4t7RFe+N9i0mZFZEQhevSUJdGhIju0XRbk+SySp9bZQo4exC5fl\nWjkrSVFpXBqhJ0/K61VH5KSjDs4sCCetUBFR3u0l+S5W/wQe4n7sif3E9XEO7UEtV1FPerA5Dzho\nHIT+JqxexdVncvdfWRFc0pNZWLEpiW/jpvyt2Njd7TuHLVR5d+5lNtorFIMycdpnrDHDielHSWzC\n69df4MT0I0w0RWV9fvU66+1lnjz+OQC6UYt3536AVppOf5vR+hRnZ5/GKI9OtM21hbdJ0piN9gpn\nZ59idkxU563NuL74LndXb1AISkRJj2qxyblDnyLwQuI04uLtH7C6vUghKGGdZagyxpmDT9GLO1yZ\nf53FjdsAXMxeJvSLnJ19Gt8L0UpTKw6RZBGeCVDsFQrWSlPJfyo0oTdCwZvA1zVCb4zUdgm9EQBK\nwUFULgUamlFMWMRh8XQZo8soDDU7ic4siVNoW8I4S5b2MGi88gm0KVMvhGQ2wqgiOFE/z+z90H+F\n1gVJ6P3chqO9vvvnnaomf6x8fhb77tdzYMTjqHsX94Jf3oeDcTiojKJGDqM4LITdQkUqGkUO/16h\n/W//JunqbbKVOVwa0f7m/yW+VM4SnPwR/CNPgJ8DZtbm2fqt/5nKl36V6NILpAtXpMrttcjOfY7K\n+c+Bg/jSH9P6nb9F87/4vwkOPTJ4G9nmElu//j9QfObnqH7lr8h5pjGdb/9Dui/8M1ShjA5L2F4b\n129T+fKvUvz0L8ixV+fY/td/A7u1RLp8C6UU7W/874PuQOHpn8U7cBZ16IncGaHKoBJ0FhV1pFXo\nBZBG6HNfkOvu54hIm8HSVZg8La9pPNzKDdz2inDRett5u97utln344eK/cT1MY771RVcIlqAFBsC\nxuhtCFx64zaMndp9khcKQiqNhDxsE9HEy1JYvy1f3sYB4qTP0uYdzs0+w0TzAJlNd9c750hSsa/f\nicympGk8WBSzLOX41HmGqhNstJZ55dq3mB4+ynBtnHppmMePPk+aJXzv0tfJ7nud7e4Gt5ev8NiR\n52hWRunGHX5w5Zssb95levgwd9dusLK1wOPHPkvJL+ZzKQBHKSxz4fCzWJeileH8oWdRSpHZlHZ/\nk8xmGO3RjjYlgaWxmF3mShON0siANhB4TcAQGDFvNKqA0YUcgehwWLrJLYyuEJpRErsFKHxdw9N+\nbtdSBjIC64PR4DI8LzeD1IIi9FQFT1dyOa2UNNmg07lMlm7jeXWsjag1P40xJWlHeaG03nbugfok\nJD3s9e9K2zdHAbq4K/p/vS1BF94PR1cKe+c1VGMaNXIEfeBR7MVv7KpXGG8voECBro5Q/dP/HWQJ\n27/5P5EuXqfxy38LXaziFt+TimR7WVpqueqJi7p0v/UPCB/7MtWv/leoQhXbXheCdXcjr0BzJOMD\nqNKcUH8fcTnbWKT33d8gOPYU1Z/6q1JRRh3SxeuYkYPSDgdMc4r6n/kfcVnG1q/912A86r/0NwSU\nBDKz2ryHW7kuyh0HHhEz1fU74r918FFYuYnrrItS/uZdGDksdJHuphCOW6uoCZcLGb8mKiDlIeis\n45auyucyefKjKczsxwOxn7g+SbEjuBpW2fHh2lGFd3FXdpJ+QTyaorZA39NYFrzSkCw6WQKFOr7L\nGKqOcWX+NXpxm4nmQeFvfcRefSmsUi8NY7ShXhkm9Apsd9cZro3nXCeDwT3wxd5oL+ftvhvcW7+N\nwxElfba7a0wNH2Jl8y4j9SmGqmPYnWQ6WPMUnvFRSpCIXq72ntqUKO0N1sZyUKMfd+lE25RyFQbz\nPlmnwOxtnTrnsK5P5iJ8XSXO1umm8zTCR0hti3Z8jXp4DnAk2SZKBZhCncx1sE5jVJFuchtPlwm9\niYE4755QBi8YocQp4ugehdIRep0rOCeKIG5jQVQblq7jxo+JUkWpiX7853Dzb0FYwlz4aQhKmLNf\nwt54Ebd+B330ObDgNu8JGOHo89jFS8JDGj6MGjuBVgZ34yVc2kdPnpVjOQf1cYGya42ujUpF4heE\nf1UfFWNGHK63LWCMNBL0o3NgLWZomvLnfkXQdoCpjeCSPu7aS7nw8w8RzopDtVIovyAtz7BMkPRx\nW/dwmwsy7ypU0ErhmlPCYzMeOiyjesLHot8S/7L+toBGbr0ic97WMurIMzLfundZSNDXvicyWlmK\n25iXiqo2Clf/GI49i7v7jnxnSg2xmHnra6jKMPbeZXRzWnQa9+OHjv3E9YkJtQvEKI/K4D1qQ3lE\nHFqbs9K6SGOBxmsNlUnZgVubIwoDeXzSwQDnpx7lXmuR+bWb3Fy6xPGpRzg4evyBI7sdYdv7fqd3\n+EOARqO1+ZMV5YEkS4So6xXQuajq0cmzDFXHpdLLEsqFGr2kSzzQX1QYbUizhHK4d6HoRi2SLMY3\nwUDZ3WhDMShTLTbAxlgbYV1MlnYwXumhu2RHylb0NgAFb9fkUilD5iLAopShny7SS+8CjpJ/iF46\nT2hGUMYjztZAKcL39eqEoxaDcmgUnt8gju7Rab2J5zcxRjzG1PABwA0WSeeEDqDq06iwhNucQ03n\n7a9SE33mJ6RCyGKxF8kE0q1GDmGGZqSF5TLpko0d2yUcD0Rl5Z+zCrc1J/5buZzXTmICBY1JVCO/\nJmksm6M7IjPmz16Qyu/+2Lm+D6EwPHjh3QApaRoTFB77Cr0Xf5ON9QUKj32J8NSPYOoTqPKQvO+g\nKK/7PhFpFYrlCTsw/e4GZDEqKMs8S2toTote4/qdXEqrIhXYxAncO98QGH99UhLVDlE/TeT3zslr\nOguNafTEqf0W4b9H7CeuT0oEJRg+hiqPCLopqIiSRmdV+uy1SVmUko60E4OyEJPLw+KT1NuSXWd9\naoAmDMKA2dIppkeOcWvpEtcW3mKieXDQosxypCI4enGb+4cncdonzWJ8LyDJYuI0ovBhvlJ5lMIK\nvhcwO3aCYii79PtJ9OWwSqsnCESFxjPewFJEq4wdX6+dZ1gcWa5zqJUk0DRLCL0Cra2LbG9flqSB\nIggajE/8GJ73voUWsC4hsduShJSHpyoEuolRZbQK8XUdXzfop8s5SKNK5rp4qkzBm0Th4Zs6gR5C\nPfC1tKytvkiW9Rmf+BxaB5SrFwBHmm4RpaugQJUNqnIUhcG6GJct46c+LF2Wd+wsbNzCdVZQyqDG\nz+K6SwIkaM7i2suoxkERV+6s4ta3ZRH2QvTwMezmHDiLbh7Grl4Rh+y1CD12Frf6Hi6ookfzZNNv\niTJ7c1Lur+7WQAlEHfvUYOymcsLz4BPMNyNUdnmCHxpxVySkjEhhVb74F/EPnKP38m/T+cbfo/vt\nX6Pw1E9Tfu6XULWxvR2B6L5ZodI5kETCaZ0LAcfC+Yo6woOL+1CsQ1gVbcaZczID8wtCXu5t4+5d\nxmUJzL+DGjuKvfZ9lDGo0aOokcO4xSsD5Csg38ecRrIfHy32E9fHOFzSzyHUOTw4rOKitrQCQRCD\nUVsGykkPtu9JGzGLxLSwtSTVV2NGTASL+fzFBMRJn3vrtygXahjt0U96+F4wWPwrxRrzq9cphVW6\ncYuVrQXKhfrg3Ppxl5tLl5hoHmRx444AIcIKvbgzsERxvH+uASO1SUK/wMU7r3Jw9Big6PS3GWvM\nUAzKTI8c4bVr32Fu+Sqj9Sn6UQeHo1EZQZFD28Mq99Zvs95ayonCIklV8EsY7eF8R9RfYmPjNQrF\nSeqVE4Pja4zo4NlEWqlOVEiM8qiYg6REaBWilME3NXZS5E5rseTPYF2E0UUCPUwnu8F2dImKfwSj\nyvTSOYwKBcBxX2WXpG2ytEscLZPEy4NFLkk2KFZOYLwdlXqFwkPl9jL0VlGFuogbr17Fte6hx8/j\n1t7DdVZw/S30wWflHtmcy6uECJd0UWENF7VAe9j1mxC3wS+JBY1zqPHzuIVXZdGvjKMqE3LfgMDb\nGxOoyrBUWUFxV43j/nu0tSIzMD8U3cLmtPCspk7JOe0+8n33doTLcq+v+vgAkq8KFQqPf4Xw7GdJ\n716m9+K/ovutfwDWUvnyrw7kq/6kUF4As48LjUAp+X6szeNuvZpb/GiojuHaG9BrQ/OgtCqXronX\n3LN/FmyGba3hDjwqaiL5xkwNHZDHrd7GdrdEWaQ2DlP7M6+PGvuJ6+Mc7SVBL7VXpK1TaAhisDou\nLSHAhZV8ppUrifuFXei8X8ptTR4SSrHRXmVu+T0cjoJf5Nzspwaw9FMzj3N5/nXenfsB5bDKielH\nSFLRhAtNwOkDT2Jdxts3vovnFzh/6FkKYRlwAwmnh4l9+V7AhcOf5ubiJS7OvYpSikqhzlBVZmPD\ntQkuHP40t5Yvs7w5j9aG6eEjjNSncCrD0z4zI0dp97d4d+5lyoUq52Y/ReAV8rclyvBRtIa1GY36\nOYqZt6ssYZeR8kZL60kpuU7OUoo1NI7RdxtYF6Ew9NI7eLpKyReSqVFlCnqMzHZI3DqhHkZhSLNt\nDD7GTBKna4SexpiHVHY2xg+GMSZfBJWP0RWMLuYADnAuRSnxMVNBFbt9Tz5/nFRJW3ekygqrUlls\n3ESVR4VQvj2P623IAq9zTpQyAnTQBlUeQ5WGcO3lXApq15PKtZdQQXlw/7i4J7MwhSARs1Rclcu7\n80FVGUJNngC01MU56GOHd6X8UPzLetsDmoJzjnTx2kD9XuVglJ3KW4xPK/hHnsCbOEa6cov4+su4\nJBLgxeDgiFK9zfIK/b6YOIlyTojdgDOBKH7Ux+Vzd1YSkc0GmxfSOHdP6Ml9ERTQ5Zrcx0ERt3wd\n199GT5wUV+lCrhBSHhJ5qP34yLGfuD7OEVYgqAqoIo2Fz6WUVFla48ojMuuyFqow8INyudVEeRiU\n2Eh0O2uAIwhrRP0twkKNE2MnyVyGzVKSqEXZK9DevkcQVgi14czkOYxfIIt7FIp14rhD1N9ERS2m\naxOExQbjxSbl6hhJ1Ia4R6E8PNh1JlmMddluBeYcrf4mhaDEkckzxFlEya/QTdq0o02MMaQ2pVys\ncWzqvBhQuoxiWCFKemQ2IcSx3l3m9MEnyGy2B6Qhs6QEZ1OytCsygViyoADaoYIqWgcC/7YxzhYw\nXkmuWc51c1qjUg+tA5QW6w1nLc4lKOWRpl1sZtEU8bwqRoeDa75TYTqdkWUxSdLFmBBjioNFNSxM\n5vB3+Y3Ok1tq26S2K2ofNkKrAN80MMUmdmgaQ0hWreMFw9DbQtemoFBHV2dxvXUcm6jCEK63gSpP\nQCY+WMplCJGthOpvCefLL6LHzkilNXJC/tY8iuuuSvU5fIDo3W+RbCwSHH86n3U5dG1M3sT9bsLa\nywnKYvvhNhZQE8cGBGFv7AjKC+j94F9jRg6iClWy5Zt0v/vrDBTz88gWr5MsXsWfOim8K2dJ717G\nbq3gH37sQUsR42OaU8TvfZ/k5mt406cFRegFqLCIu3dFElauGI/S4s0VlFBBEddeF6h7aw01NI1b\nuSUbh817qEIVNXMee/nbqOGD6NnHsHfelOc3p0W8GMRxej9+6NhPXB/n2BmUVyflZ9SWJKbUrmli\n7iKslBbLCGdJb79IlnOdUBrv8HN0uhsEhRpRv0UctUjiDmnSp948SKojbNonilqkSZ+ot0kctTFe\nQKE0JLqCpSbd9gphWBEQRdTG8wq4LMZmMf3uBtp4OGVYaS+jlWa7u0GSRjTKu/DuzKbEacRmb43Q\nK7DRXcFojziLWNi8ha8DMiePMdqjUqgTd1dplEboJz2KfgWHIzAhK90FHFDMuVpxvMba6kukaZc0\nbWNtysryC4Oqol4/Q6N5AYDtjSu0W9cYn/g8gb/bAo2jVZYXv02j+Qi12kmsTVle+RaeV8GYItvb\nV7BW/JnCYIjh4acJC2MoLYkoy/psrr9Fu30d5zK0DilXDg+Efq1NAEuWdgBHHN3DegbfH8aogMx2\nMbqEQpPZLpFdIvU7hF4RCMlUSloEpWJCwHW3wALdbZzxheTcyw1Eg4oQ1Hvb0NmS6sbzRQ097kG3\nlVuciBu2UiGgKTz2ZeLLL9D6t38TnRNrgxPPUv2Zv3Zf8lAoPxDo+I1Xc5NMX9Q1xncJxf6BMxSf\n+Tl6L/0Wye03UUEJZzPCM5/N1dZ3W3/Z5j1av/2/glKCUnQO29vCjByk/KO//ODMTBtKz/wZkrm3\n2fonfw1dESuXwlM/Q/n5X5J2aGUIoq7QSXCiZK+NXAvnQ2UIe/t16G6ghg+SvftNVGNKjDs9X7he\nOAiK6LFj8jq1cakWlc4V6IV8PpBVs5m0S/dnXh8Y+4nrYxrOWti+K63CgRyOn7c0+gzU4XP3Xefc\nQMJHNw6AV8Ru3CJbuYKbeYIsjbFpLKK22sOYIBenLaFSTxKPMhSKDZK4I383Pr5fwnoW60Brnyjq\n4oUVPL8o2oBJRBJ1SZIuoa5hvIBe3GG7u47vhTx65DmqpSY2t7uP04gkjSl4RQp+iVhHREmP0CsS\nekU845PZjMBEoKAS1ojSPkkWE6W7KhipTfGM+ILtVHTGlKnVz4jyR+cWrdY16vWz+L4gEYNg16/M\nZn2SZFvg13uue0aSbGF35og40rRNpzNHEDRpNh/B92v0o1U21l9jbe1lJiZ/AmMCnLNsbb7D1ta7\n1GqnKFcOYbOYra2L9PtL+H4dZ/vESZs4WsSYMnGyArqMtiEZkLouHgkKg8ORZBD3psEAACAASURB\nVGsYVSa1LYwKyVBE2Qq+roIZZTmyxHHEgWOPCDAiR+kt3HiHwuJthicP4xav4tbu7PICh0TAlu6m\ngBHinnCgChXUsWfwJo/T+JW/TXzrTeFlhSX86dN7kowZnaX+y38Lb2gmr45yHcwsFR1C59havcvW\n2iLTX/wvKZz9MdKl66AUi90+ycFzjDz+FXRpd9MQHH2Kxn/2d8huv4Xtt0W1Ymga/9AjAtVP+ji/\nsCch+EefpPmf/z2S229hu5vochN/9oLoKR64QBz1uDt3ncnZkxSqQ/e1sd2A+6aKdezydbyTz6NG\nDomeY3Ma/CJq9Ah27nX0wUflfS1fg/aaWMD0W+LI7GzewhQXasKyzAb34wNjP3F9bOO+AVEayRzL\nC/PFIc5JoA5cmldhebtLGXTtILoxS+YFZCvvAYpSZZRiUAKbYo2H8Qu4LCHrrGCTHkVn0TZGuYxC\ndRxlAqzLaLW36Pd76H6MIyRKenhAL+nhbIZ1IUXtU6lNUq6OoZThxPQjbHRWJFnhaPc3iQeJABIb\n42kfz/hUi809mogyq9hdmCwO6yxpllAvDmO0x3jtwIAo3CgO589zGFOgUpFZVJJso5Sm4A8Rmpz3\nhsF211EfAf34sM9jaPgJCkXhaBWKEyTxBu32TdK0jTFDZGmXVusahcI4Q8NPSVsS8PwKC3e/BoDx\n6nh+gyCcRCmPIJ0ksquE3iTgCLGkto2nRck/MMOARePn0lKGSnCUHTmq9dV7dFsbzJx8YqDeb9OE\nlcU5aknM8ORhmWUNHxDOk18QgrNS0CrB6BFUmlcNXjCAeG/0I8zMBZpjM7tXIOoM5JEU4JfqAzi+\n21pEHXt2kFScc2yvL7Ny5ypTR84RHH+a4PjTOGvZ/PZvEqwtMfnsV/YkIRUU8CeP4W3ehXItr3YQ\nYd+4h4vaqNnHds/HWhZuvM3ozHEKj35RPLe0B+1V+c5MHCeOuizevkxz/CDFWn4sm8HqDaEdZCmq\nMYEpVqG/hZ44juu1yTbuoZIY11qHybNkrQ3QAdYrwtq8ENmVgjQSqkB1dKAU73pbsiEIy/uOyR8Q\n+1fl4xpKQ67wTrEhSUp7gBMn3CyRL70J8hbK3rbE/QuC1oZa4wAui3BZgiHfHZp8YbAZKkvF7t4L\nUNqQWUu33SIMixQLJWwa45CWpDEehUJpUOWFYQHPL9zH6zJUCzlhM+3jKU3oCzhA5lYWpRS+EZkm\nB5D2cVmKNr54i6ndRSb0CjlPy6Mfd0hsQiWsDRJZZlM2u6v5/82uigSCzHROxF2VFQ26j8Qvel94\nXhU/qNNJruObJgUzge/XBgK7AEnaIk3bVKvHZUaWn4fv1/PHSnXnbEK79Ybs1HWAX5pEUnSKwqCU\nj3VxrusodiooRWCaOafO5kCOh3ucaeNx9pkvD4w31fQZSV55YnN5VeaCMir36rr/frE24+61txia\nOLgncQFibZInN2UtFiev85DzmD56nonZU3j+B1xvtyN6LPeVUgq0jxo9kl90X3hUWkOpgSpW9zw9\n6rWZu/IazbEDBJWazJtsKmjF6ggoTaU2zBM//p/gh/dxrpTKZaAUrr2G1Z64Pfe2BY04fgw2lyEs\noqZOyzzZATZFjx9HJT3U8AFc1EW1ViVxNafkNZMI1VkXvcmcyL0fD8b+VfmYxp7+uBJXXtfbIJ1/\nFbtxG5d0ZbgeVvCmn8BMnPvQnrrSGqWLOO8+9FPcIb37Gtn6DYHZg8wgxk5jR86ysnSX6YNH8LOI\n5Oo3MGOnGZ28MDg/ZzOSa38oA/8TX9hNhGkPPf+qVHtJj1QpVFDBGz2Jd+BJVA6Tds5h+9ukd17G\nrl3HZRHKL2JGT+HNPC7tTmfpxV0BaQRlUpvS6m3Q7m/lUk4W6xxJXtFZZ6kXd1FvutREh7sD9P+/\nUwdtArQO8CijyBfZ911vm7s8mx3Dy51jKoPWAVkmc5Ysa+F5dYqlY6A0neQmadbDuhijCvi6QZQt\noZV8VloFaBXgnGN9aY65y6+QRH2aYzMkcX9wHOcci7cusXrvJs5aJmZPMjpzfA+/KYn73L32JqsL\nN8nShKBQYvLwWcYPipbk+uJtluevsnznKt3WBpsrd1FKc+DkE9SHJ1BTp7l36yIKhTaG+atvksQ9\nRqePcWhkFqUM7c1Vbl9+BZsllKpNDp15BuPtXaqSOOLaW3/MxvIdPD/k4MknGJ6cRXk+m36Vlfmr\nHD77DF4gSa+9tcrd65c4dKaG5/vcu3WJlflrbK8vcuW1P8QPCgSFMkfOPYsfFkmTmFtv/TG99hba\nGA6feYZSLW8VKw21CfqdbeaWVthaXUAbj4nZU0wePoO2Ga45xe3rb9MYnWbx9mU6W2v4YYGZY48w\nOnlCNh3OwchsThPI358XiPL9fnxo7CeuT0BI0lonfuffYHvrmJHjmMq4+C+1l3YTxkeIKOmx1V6j\nXhkmyCKyzTl0ZQw9cR6HI1u+THL92yinSRNJmGQx2eYddG1yMCPodLcpBgU5ftIfIMScc6RzPyC5\n8wO8yQvo6qQAOLYXcHGHPakj6ZJc+V1sawkzeQFdbGDby6R3XsJFLfzjn0fnKhhxGgnHbGCOmSP4\nnPDFjPIIvAKb3VVGqnsXjh9mSO6wDzVrllcQSSKnsgcfIAfKz8k+5I/yokm8Qr93nSxtkSTraF3A\nFIcIzBgOi1Y+WgUYXRR3YJsJ0Vwp2lurvPO932Fo/ACTh86wsXyH5TtX91RFlcYIWZpw7c0XKJSr\njM7sVUK5e+0tbl96hSMXPoMfFOhsrWKzdM95FooVlNYUKw3qw1OgFP59cO+N5XnWFm5QbY4xMi1A\nDM8PBxV3UCgyPDHLvVsXuXfrErOnnuL9S9XqwnUK5SoHTz7O6t0bvPv93+Gxz/08taEJOttrLNx8\nh4OnnsBDEle/0+Lu9beYOf4oxhNT0zA/z2pjjMAz+H6I6m/jXIp20Ag8KFW5eellpg6fGyQupRRx\n1OPdl76OzVJmjj9KEve5+e6LxFGPgxMzJHHM3JVXWbj+NlNHzzMydYSV+Wu8++LXefLZn6CsHKo2\nxo5IsVtdQlWHRYj3wPmH3x/7MYj9xPWJCCeVVmeF4NSXMeNnBaDRXYfmrOz2WosinbMD/X2IjQnI\noprZVCDkfoHw/M/nswRZdE3zENFr/5Rs7Tpb3WHS5AjhQziVSRJTeFgLyGZkW/PoYhP/yGfFoVkO\nvHtuSILLlq+QbcwRnP4qJhcKNs6iTEhy5weYiXPo+oy4MtsUpQrgHKEn4rtpFmO0j3aWUkmEbJvl\n0T0zsjTpEakWSilsluZgDiH6up1zGlwbR5q0HwBsDN6aS6QKemhiAmOKaO3loI9djyZnE7JMKiM/\nGMEPhmVx1QWyrIMxJVLXE+doJ/JUnq6g2ovSHi6MgDIs33kNrQ0nHv8cQaHM8NRhNlcXBsdXSlFt\njlGqDTF/7Y2HnmO3tUFYLDM2c4ygUAZODp4LMDx5mOrQBPPX3mR4cpYDJx5/6OskcZ9jjz5PuZaD\nEPotBCQEflhi4tBp+t1tOtvrD31+uT7MsUeew/NDhsZnefn3Fli6fYVq8wPcn+8Lzw+YOnKOsFhh\n8dYlpmZPUMr6uM46dNZw28sQtRmqVgnHR5i7+voDr7GxNEdrfYknP/8LVBoC89fG48bb32W8MSRO\n0dYyeuA4R89/BpSiPjzJ2r2bbK8uUHZd8fMqN6T1bDMxw7QPvzf2Y2/sJ65PQiR9svVb6Oo4ZvSE\nJK3elsg6kbcpHALg2EFL6Q+6NRSBXxhULs4LZfFOY5GucVbUDGzC8OgE2piHEImd6Aw+rJDRGl0Z\nI737OsntF/Emz6OKTWlr6vvgzC4jW7uO8ouoQk1kinbOsNQEm2BbS+j6NFHSoxvn/mBeAWN8OtE2\nxaAiUPq0DyjxDlPCHxscJk8gO9VAlkYor4DnV3AupddfJAiHAE2WdWm1riL48oe8NeWTuS5KPVzK\nyPdrBMEw3c4cce1UjmK0dHvzJMkmvt+Q46SbZGmLQukocX+esHAQ36vBHjGrnCTtMlkMjaa9sUK5\nNoQfSivS8wMq9RGiXvsDPusHY/LwWdYXb/HK7/86E4fOMH7wJOVakx+2iVoOQ8LrL+KGpoX83l6H\nsSPQWkEdvLBrEPlBz68N43kyB/SDAuX6CK3NlT3yXx85jA/1UWnR7RCKtSffi+2Nhz5le32JsFCm\nWG4MknZ9aII0juh1tinWh1Fa0xidyekmCuMHaONhCzXU7FO7l2wHKLWD6sx2wVL7kPiHx37i+gSE\nSyNIOqjqeC6a24O0J8Pf7pqAN7rrUJ0QtY3y6MDi4f0hBosCYHBpRLZ8WSDz0bZ86ZzFddehJu2n\nNEkecpcpsix9qDKGUhrv4DOQxjI/u/cmeuiwtA0bBwbzLWyKi7Zx/U3it/7l3nmRzRfrLKKXdMlc\nSjmsYXJVeAUU/TLlsIZ1GQW/xP0L/g48HsAPSgQ5z8vzioTkNiaeJgiHWF97hX5vEa0Dong9n0d9\nMHgjdR00D2/Nah3QaD7CyvJ3WLz3TYrFCayNSZJWnrTyx5kivc5VsqxLlm1T1Ltttp3V0O2YhcYd\nciY1NktlI3GfP5f8/8PDJZFcU61pNIZ5/Ed+iqWFWyzOXWH+vdc5+siPMH30/A8lV6QBlcawsYCL\ne/8fe+/1bdd1nXn+Vtjp5HtuDsBFIEAQYKYkKlqSZalsl2y5y23XQ/c/1w/91jW6alhlq2RLogJJ\nWSWKlCCCyBk3h5N3Xqsf1r7nAiQlq9wePapJzBcS9+57wg7rW3POb34f5AlifOhA7A8AQSGe3PhI\nqSiLjI+9qYCPrd8ev5pj7yntTFUPHzilD7/xO//OlKVT1Xi8F3mksiEkojIeVUp/FHykQkRNbH/b\nZXfG0eHtcB/RmnMKJnv3EPOnsELCzMpTAPtQPAWuT2NY6yjw8SFgIR26LKxI3BxNVgntfkwURcZg\nfEirNkN5721Xkpu/gF5+ERE0wJRkH/xX1+8q8ulg7RPvzVFpye00LUzZbgAEDfSz30KtvjwFxnT3\nBt7659HrX3jMC8oiohm801/52AxRNhYohXQeW0mfJJ9U9iOG0KtRC5rsjbZoBC1qfpM4G6OV53pe\nXpta4xksmqxIp+64WmoHrrrJ4uLXGQw+IE33ESalXl+n0TjNcHgdL+hMS4b1xpnqOyt82UVJR6cP\ngnna7UsoFWFKNyNXr59ELn2D4eA6eT7A81rMzX8RY1Ky9AgYG9Saz1MUPYLaSZASY7PqjFjH7sQ7\nzh7yCQQtwnqL/v6mAzDpSlnp5A/ItsYHDlCiFsRDwnTMqWdfZvX8K9y+/BZ3fvtzFtbO4YdPjgn8\nXqyImsgXvulYiY/PGJb5H6SansZDjDEoJTGmJJkMqLed6oqQsmI+HvdNk3iIKT++hPvEx9SB882y\nphoP+XjAqLVm2Lr3AUWWoD1HfEkmQzdCMbvyB0k42d070N9xZcUj+5csAZm7/x/tO5HfmZV/8bU+\nbfEUuD4FIbTvxFHjnlsYsJU6fNOBVNhyg8p+pY3n/e6FQ0rl5n3ymGL7CrK5hH/+W26+B5woK26x\nyPOMsiggOOrVmOkioZTnwDOPMRjG6QCTa7Tyq2FjQ62xiNdaQa++Sn79+xQP/ztq4QKiPufo6UEb\nW+wgZ04hw4/3NTIV27EetvCUW2CyMiXQR/2u4wUmKxPifOTKh9bHBCcZZTGyyDGmJDcZ880VPOVK\nVEEwS6f7Imm5i0CiZIghIWotI1BM8nt4aoZG6wyGjNz0ycseHh20rFGrrVKrrWKtYTS4RhAu4gdd\nomiVKFqp5KdylK4jhKBedzJBhRmSM0Boj5KULD9EyTrGJggUUgRO1Fd5kEuonJjnVs6weecKOw+u\nM7t8isHBNr3dh7RmHRnFGEOexhR5QlkU5GlMMhmgojZeewlrDb1JjN9cwist1hQIUWVtHxqf8IKI\nwf5mtZgLtBeg9GMlUiGddNKHMj5rA4ospUgmZGmMKQvicR+/rOH5x2zL/t4Gew9v0plf42DnPqPe\nHuvPfQ6AqN6izDP2Nu4wv3aWNB7z6Nblj5QRPd8Zfw72N/ECdz/4QQ3RWqIs8ur7H2KNIYmHJJPh\n9HvMLq1z78oveHjjPdbOvUxRZNy/+g4zC2vU2nNkyaT6QgaTjI4rBeBU5nubiMYsVmpH0xcKW2RO\nqUN70F5w8lBh62m29THxFLg+DeFFqJlTFBvvUe5eQy1edMAFU68g0az8kirw+vBDftTrCbyI+c6K\nc6m1JUL5IPXUvqQ8vIdN+ohmnVa7S73RApMgdOCEWcsMlE+j1qLcu4GJD5C1OaKg5cqT1mKLxHk7\nVaUnEXUQzSVs74EDOwChUPPnKA9uU25fQay9dpx1WeMGSHVA4IX4OjjORIQgNA6YC1NQlDm66p21\nwhmMKVxlrVLcmM6K2ZK0iJ8oI1prkSIgkM7KRIijOaeyWshdRimEhyLAihJfdrHYKhuT0+PD2ipK\nPblhKPIhabJDo/UMWOkWN1siRYSv3AAxtnSkDuEjRPcJYonFgNagNQJDd2mdtfMvc+O9n3D3yj/j\nh3UW1y9UmYkgnQy59s4PSCYjiizmYOseo94ezZl5zr/6dYSQPLp1md7uw2lZTClvSpI4ypiV9li/\n8Bmu/+pH9PY20J7P+Ve+xsziCXeLBRFlrQlU/RyorpePRXDn/bc53LxNnueYsuD9t76L50ece+WP\naLa6hFGNlTMv8ODGu9y6/CZ5lrJ27iXmVk4jhKDVXWLt3Mvcuvwz7l39JVIpZhZOOJCVlauytdRb\nHZZPX+TGuz/m7pVfEDXaXHr9T/HCiP2NW9x7/+fkRY6UijuX3+SBH7J8+hJrz7xE1Ghz4TN/ws1f\n/4Tt+9eqjVaH8698FSklQkDUaKOkxKZuJkton6jRcXNpXghBA9Ga56jmKbBuluuI9Rq5vuW0EnGk\nJcr/GNP1kxjiX9XM/P82/qf/gP+zh7UWOzkgu/JfMJMD1OwzyPoc1uTY8R6qewa99hoAZnKIObyD\nLVJM7yHl7lVHNW8sInSA7J5GRh1sWZB98HeUezfRJz6DrM1iRruYw7vYbIwNZ8hOfZNGZxYlBfm1\n71FsXkYtXkS2lrHJAHNw19lneDWC1/53hA4x6ZD8yt9B0ERWmZWdHFBuX0G2V/Avfuc4u8tjsuvf\np9y7geqeRjYWnJXE5ADKHO+5PycVksK4jElXtH9jS5RQaOWzN9qkGXZoBC0m4/vk2SFYi/aa1Jtn\nAEE8eUSW7gMQBHOEtRVAkCZbJJNNLBbPa1NvniFNdiiLmFrjFNYWDPtXabQcpXw8vI1SIXnWQ6qo\n+rllMrpDlh7SaJ3HD2aq0tYm8fg+ZTHBD2bx/A5RbZXh4AZRbQXttbA2Z9i/jl+bASWQeBjyKcFG\nWIlAOXzD4IkmorBMxgPKPCOs1VFlhvHreH6ANYZsMnS9sWojgg4RUqG0JhuPyNKYLJ3Q335Ao7tI\nY2YBzw8xpiSrsqug1qLIU4YH26ggJGq0iUyG7G+BKSnyFKs8vNYcoiJC2PGB20SVLtMrBzvIZz4P\nXojZvI4Q4JkSWWuSH26j1l/EeCHxaIDyPGqNznRgGlw/Lx71yfOUIKwRRA2KPEX7oStNFjEIibGC\nyWRIaRyghlogioSyyCiy9FimSrgqg/I8dFB3AtTSI08nxOMB0uREvu+ySlNghSJPJ+ioiYw60zGQ\nLJmgPf/J7LN6RrMH76LayyjpOTfq1EmyiVobsNhJH1GfgcVnPunA9S9+uacZ16cgRKVc7l/6K4pH\n72J69ygGGyAVMmwjoplphmWTniNbWAMWZPcMNh1RZiOEUK5MF3VAKkdXl5py9zolIMIO3tmvY5Me\nJhkQdeedhI216NN/BCrAHN6lGGwgghb69Jew2QQz3sU6Pw6E8pHtVcqDuxT9h+5nXohaftGBqw7I\niwxrS7QO3KxWc4ly9xrF5uVqqLqJmjuH0AGB1IQ8aWWRF+nU9XihuYoUElOmJJMNGq3zaF2fZkRZ\ndkAab9NoPwvWMhxcRXtNhJCMh3eOj3fWgBiTVYPCOGWHYjztdaXJNo3mOZrt5wA7zdBqjTPk+a+x\nNp9+zCBcwJqCPDt0xwuXcSkVksSbNLwWedbDmgzf606/nKXE2tJdq0rWSQjXAxPxCDHpU1ce+E5U\nmTxDxTHErgcXIBwpssxc1tiYQSiPLB4z2NussjNLVGshLOSTEUUak8Vj8sT1EAXblEVG2OzQbM8R\ntWawowN3TxUZutF1mw8poTRO47DWxva3Qfv4YR0b1hCNGYj7WFGNHVgDkz6echmNDusVJf/JsNZC\nPqFWb2ASi5nsYYoJXmvR3Y9CYvIEM9oD5dFoLTgmLG70wJoSmw9RGIQOUfWuy+aLBFvmGGsx+/cQ\nQQOvOY8fLlejEQYT9zHxAJSP11w43mRVKjEqH2GGQ4xUqPosInTuDSbukz36Lb4QUJ9DeIEjr4Bj\n62YVmeqphiHwFLg+2XFEeKjsyEXQckQG8/lKUNdWkk++O2a0i2ws4l/6K/e7MgdZ9aIeYxla4xrX\nQyswa59DVPJRUofER55PLUvTGjSVJFDQxDv3DSaTPYoiBeWRazfTZGbWGSWHeMqV9OTyixRzz2DL\nnMivEwRNZxIoXNN9Y+8ak6TPyeUXSfIJcvYMdNawZe4ARHooHUA6IC9zlFC0Kk1D57ocTrOvI/8w\nK3yCcIHJ6C6e366yKiiyHkUxZjK6A4Ap02qmyqBUhB90/2A2nZQBfjiPUh9mHconSnyOfq8dCaUa\nAzjaYQfhAoP++5gyIYl3CKIFpAiP58wMaO0ktrJkDIAfNlC6DlHobG6OedhYqciSCcYUKOXjBTXX\njzkS1K02HkLAzMoptOeTZzFZRaEP622U9jHG2Z8I4e6PPJ24XpnJyJIRutZGnHrVyYNV83tH0lFZ\nMsaUGWr2BF5QByGRR2K2URuzdA6hNFK6LKbIYoQx+EWO/DjWnjXEV3+ICBou+642P9HFb4EIKXZv\nktx623mMFSnSrxNd/KZTfclTJld/4DJO5WHLjOjZP0a3FskO7pPcehNZmWWayT7+yvMEp14HISj2\n75LcetO9TpEhvIjaxW8h/Rq2zIlv/IRi/67zQTMF3vxZgtOvUxw+IL3/LkXvkSsF+3VkrUN45guV\nL9ljYw7a/6RnW39QPAWuT3BYgPEejHZc7ypoOJM75bkHc7znACvqOPASwjELh9sOqKyF+pxjpcWH\nztPLFG44ubFQMe0kpfZRwlk92MqG3Y2mHDEFXW9JIJBeDYQjeLjfW6TSeFZNldpLU2Clh1A+Kmi6\nftdjMd856XpTyicSbtG3XoQUsrIzUa7cYp1OoQWkkOz07jOKe5xdfRXFhxc8Sb15hrKISeJNhr0P\naHdfQgiF5zWp1U9N13ulIrL0sMqkjhQ4Hpufmv6s5EiHEByFW/zLVZDfG0pHaF0njjcoywl+cHb6\nPfY3rrF1511Wnvkcm7d+ybi/jTWGxswS65e+RmNmBeEdy2XFw30eXP0Z/d17mLJAaZ/ZlWdZffYL\n+GEDU+TYPKPIU26883csnX4FISQPr71FPD5EAJ2F05x77dtTLb88i3l08xfsPbxCkbnMU3sBncUz\nnHr+6+iKMWitZdLf4cHVNxnsP5i+f3flPGvnv4AfNRFCUGK5efkHRK05PD9i8/avyBNH8W91V1l/\n/uvUWvMfupYWkwwRRUrt0p85UWRbOpp5HpPceovg5Gt4yxewecr4vf+bfPsawYlXKMf7lJMejdf+\nBhm1HQAdSV6ZAjM+oPbcN1HtZYq920yu/hBv8QLCD0luvYW/9hL+8iVsmTF+7z+Tb32Af/I18t1b\n5Ds3qb/0l6jmQjXOMYF0jG4sIC98AzPeJzz7ZbzuCUgn7iEqsuN7Kmw+Ba0qngLXJz3KvHKxfXzO\nR1Q27KGr3ZsSTHI8iAyOWXikDFFUtX7lOQai1PRH22wf3CHNJ2jlszR7lnblbLtzeBclNXc3f02c\nDplpLrE8dw6tPIoiYzI5pDQ5h4MtAr/G2sJzRKETQE3zCXsHdxlWtibLs8/gNQKEEORFysbudfIy\npVmbpVmbnYLaKD6kP96nNAWHg02U8lidf5ZWfY6izNg6uM3D7SuYShVeCsny3DmiwL2vNbmbx6oy\nu6PwgznSZJcs3UeqwLH8ohDPbxGPLaPBLbTXACxhtITWNeLxA5J4s/L0Oi7/fVwYk1HkY0qTUuRD\npHLAJIR0yhjFmDTecoDltRFCEoSLDHq/JYwWkfIY1PN0wuHWTZJxj9mVZ1k6/TLJuM+j629z453/\nysUv/UfCygYkiwdc/+XfkadjVs59jrDWYdTbZvPWfyfPJjzz6p9jytIp+Jc54942m7ffwZQFncXT\nLDc+QxYPXSakvClwb995j4fX3mTp9Kt0Fk5hTMm451RZjscYIBkdcu2//2fKPJu+/7i/w+atX5KM\ne5z/7F/i+c7VeTLY42DzBkG9w+L6S4T1DsODRzy68c9YLBde/w8o/aHZOCHQs6edoaMQHC11Zdyn\nHO9T9B5Sjl3f0mYx5WAbAFXrIoM6kyvfx195Hm/u9GPPDsiog2zMub5fe9mplcQ9RFmjHO1R9jZI\nJr3qdScUgy18oDi4h55ZdX8jHOFCJEP37IVNRBC5vmTVp7NbN9zzKBXEQ8TMciXs+zTgKXB9okMA\ntr1CMtnH8+ooLyRPh1hr8BuLIKAsM5J05EpstvqjxhzTXZ4tXbbm0is8HRD4DZKDO4R+g5nWCr3h\nFh/cfZNXn/1TQr/Oxt4NV8pbvEQ9bHNv6zIgWFu4wHCyzwd33+TEwnMsdE+xtX+LGw/+mUtnvoa1\nlmv33kYKyWL3NJNkwNV7b3Jh/Uu0GwsIIYnCFge7VxnHfRZm1jlKg0aTA67c+SnLc8+w0D3FXu8B\n1+6/zSvnv1XxDFwXSkmPwKs5YHhsQRKVEkiRDxBC02w/ixAapTXN9gXSMn6AiAAAIABJREFUeJuy\nGKF00/WPhKbZuUia7FIUIzzPLSrKq1NvniHPB2hdp9Y8haxYi2FtddrXOgpTpqTpNr4/g7EleXaI\nVhEIiR90MOYkRTF6YtHXXhMhNUH4UXkjUxbMLJ7h1At/PM1qlRdw853vcrB5g+UzjoSzc/99xr0t\nnvvC3zCz5LK22ZVnEQIeXnuLpdOv0K5ces3E9ehGh5tc/MLf0uquYCYDbNMprZSDXTf/pzSjww20\nH7F6/nXC+gyYgvn5k26hLnNsnoDy2L77LvFwv3p/RzaYXX0WP2xw892/52DjOgvrL06/V1nmnLr0\ndbor5xFC0F0+RzLu0du5QxoPqTU/3PsRCO19NEOpWKlChw4ksgn+7DqqOY8d7yOA2rk/Ij98QHb/\nV2QP3qV26d+5LAmgcrV2L1INIJuyel1Xkjwa3vdXnp/+nSsdHm8yhPJg9uT0386o8ugCB4j1lzli\npWLNR00wjzL8T2kG9hS4PskhBGWeMDi4SxB18IMWk9E2ftgmiJxgaG+0zQe33zim3Fa7QdfXeJz6\nbZBCsbLwHGfXPsdi17nylqYg8hvsHN4lzSaEfh2sZaa5xNrCBUCQlxnbB7dZmXPsukBHrC+9gO9F\n1MI2v77xj0ySAXmRMJoc8OqFPyP0XRaTZCMe7V6j3VhAK4+FmXVGk32Gk49K8Xg64PTKy4R+Y/q6\nWZ5QjzqszJ/ncLiFVj5rC889saCVpqA0JVF97SOv6ZrukpqpvMysdmojgCpSal4Dms6tNi+H5OYA\n6QX4fheJT2HHFNb1g3RYIzU7+GLesf0AqSO8WhdfzVRmjzVyO0CaAIHEC5soG6Clm1MzJidPD9Cq\nhtQBRdlDqSaycmkWUtFZOD311hJC0J4/ifYjhnsPWD79KsaW9LZv4QU1pFKM+9vH59CvURY54/7O\nFLiOojGzTGvuBBQpNk8ww8q6PoudVFfYoDmzwu7DK9y9/EOWz75GI2qhkoErkSoNRU7ph/R27hI1\nZmnOrk2vhRCSmaUzeH6Ng80bLJw8FpuNGl1ac48dKxVRc5b9jeuYIuMPDeE3EF6Enj+DnllzFYkj\nBiWAKZFeRNBZxV97mclv/o5s6xrREQClY2yeIJSPzSYukwzqTnrMr6FnT6FnT01ZhEeh6rPk+3fd\n+2n/WKdleh9WlZDKsofHdDzt/n0nvjt/yrlUlznEQ2fVUv94oYBPejwFrk94mDInz8aUZUaWjlDK\np9ZYmP6+WZvj2VNf4ejBnSR9Hu1cpdtepV1fQCmfsszojbYYjveY66wDlv3+I7b2b2FMibElWR5X\nzDpACKKgOQW+WtAiK2LKarfrexFKud2w70UIIcmLmCQd4ekAv7L1sBaatS4bezcqCvvvv10Dr4an\ng2peR7ne1+8QtH08SlPSm+zRrS8Q52O09MjKlNCrkWRjkmzEQjjjVOxV4DQdi8QNb/sRVIrwUmiU\nrJOXfaTwsMJgbUFhM6QIUCLC2En1s6FjRso6hRmgZZ2k2CLUSyTFFlo6HcmsPMDagrp/Bi2ajAc3\nKcuEWvO0u762QNocjoBLyGkf6Si0DlBeQJaOsdZgyoIsGRGPDvng7f+Lx9nHjpHoiB4flr44Ik7g\nRajuKqpSdDjO1gXzsycoypzt27/iYPMGjZllFk+9xNzqBZQXutJaOiZLx0SNrhtEfyyUF6L9iDQe\nYB4TK9Z+hHzMxeBYP/L3TMtYsB8CJhk28ZcukFx/A3/1RYTyKCc9/MXzqOY85XCXfPcmsj4LRYbJ\nxni1Y3Aw6Yjkzj+ju+vkWx+gGnNT1qG/fJHkxk/w474zUp0c4i2eQzbm8ZaeJdv6gMnVf8KbPeVI\nIUEDb8Ft5oTSyKhNtvG+y7Ck59yhpXaMQsBee9PNIy6dh/Ghy9qeAtfT+CSGFzSZX30FpQK091EZ\nmsCvs9B1kkTGlFy98xOW585xauVVjsz5rLUszp3j5v2fs9e7i6dDrt17m/XlF5lrr5GXGaMb//jY\nq1pHsKiGlo0tkRyXWIwtp4vi0TCo6+noyvX4GGzKskAK9QeRGqbW8v+DcVQyTIuY/dEWWnooqZmk\nTrEcBCJskekcbIIfzlOUI4pIUDKkyLZRIkDJGtYatHR0+tJO8GSLshzjqTZShFNnYim86SCyFE5d\n31MzSBHgqRmUCCnMiFCvYG2OEnWE0NRbz7jPIxRZsYfr1z3JUvwwWFv3Q7fQP7bDr7fmOP3inzjz\nzaMj0yFYS9ScxcaHUDHoALYOB5j7G0jpyDZlaapNgiD0PLKiIM0Lllde5oUTlzjYusnu/d9y81d/\nT3/3Hmdf/lO0H3JE0T9yof7Qh59+1iclg8W/eGltFrtF34/w115ENebcBsPCVPi4NATrn0XWuxR7\nd935NwYWzrkMKRtj0jFlfwukIjj5GfzFZ6fvoZrzyKhDvnUVETQIT75WMV4F4enPk0Udiv07WFM6\nurvyIU+QtRlqL/4F2aPLZBtXEErjr7302E2oic5/lfT+u2Qbv0U2FtAzq+537SVEPXXPk19zJc65\ndaew8SmNp8D1CQ+3sGh6ezcw1WxOa+YU4cfYlhRlxijeZ757alpqOnoNJTT1WpftvRvMtE5grGGm\ntYzv1RiM98ger9Fb6A23yIsEKTUH/UfUazOoqtczSQaM4kNa9TkGo91phuZ7EcaU9EY7dJvL5GXG\nXv8B3fbqdKE70hq01mBM6doMfyBYaeWRFTHGlm44twLVJJ+QFQlSKpTQBDpymoXWkBQxunJJzosD\nZ9aoGk4NQzWRNscTbawtkCLACou1GUIotGgikBjiaqaKioloKgZlgBCKUC1isYTKqZdI5WNNjtYN\nBBooMTbD2hwhPEo7RlFDyYjSTHh88TemJIuftEXJ0zFFFhPUnHyQUh5hvcO4v0W9s0RY7dqtKaH3\nwBF2hKgYbcev7WvFbKuBUq53VpYGrRVFWeKp49JkPQwI/RYrjS4LJ1/g3vtvsHX7VyyeepnOwimU\n9glrbZJJnyJP8R/LuvIqG2vNnXB9vSO9wWwCe/fcKIZU8JjZos0mlA8vO9ZgbwO59Czab0A6xqQT\nB9hegB3uYisRX2/+DBqJqM9iszGiyDDbNzD79wgWzjpCRL3jmH+PbQSE1AQnXoL1z0w3AdPypfbx\nV19A+U03LBw2KDZvYNMYEdYRfoTfWYe5c45VmMTkjz5AeCF64TSyMe8o+0cODeC0C8MGQradf9fT\nAJ4C16ciRv1HCKloNk+CAO3XPvY4WdHUe8Mtuq01pNTTjKsoM3rDTbTyqUcd6lGbq3ffJPBqGFPS\niGaOyQ5CkBcZV+78FGMNWR7z3KkvTR9wKRV3Nt5FSs0k6bM2f8H1xoCTS89z6+E7PPLr5EWK70Ws\nzp0HYK/3kM39G4zjHkWZ89vbP2GmucSJxeeQUqEfmzUTCDwvfKJPN9c5ybV7b3P55o/QymN9+cVp\nqbIVdZFCEnn1KetLCklUSWNlReJALrtPUfbRqk2gF0iLberhBQaTX9GMXmScXMOYGClDGuFF8rLH\nKLlCp/46SvgMJu9gMRib0QwvYTFM0lsAhN4qvp5nEL+LEB6+niP0TzAY/woArZrUw/OUNkUJVw5U\nMuKJVMQa9h5+QHf5WbQfYk3J/qOrlEVOZ+G0OzNSMbt6gcOtm2zf/TWr5z/vWHlCYBqLFHmKFzae\nIIQAdBp10qIkSzKyosBa0EoyTjNmG3VWZ9uYbIyWx+MB2gsJG5XMlXGlP6k0c2vPceu9/8b+o6ss\nVjR7Uxbs3LuMKTNmV5594nsJ7Tu1ClFlXo+zCK1xgrRhC6Im5vCh0wNMhohaB7lykfL+e9g8duW1\nqI3ZuQVeiD18iKh3sXmMHewgpMZsXnVZVJEi24tPvhccK+4/rsRf3ff4dWw8xMQjRJYgG12sH2Gz\nBJvFiEgjvBBzuDHNjI/o9sekj+PXLbZuouZOIGptzHAfhEA2Pt4r79MUT4HrUxBKeWTpkLLM3EL+\nO2S+lPJYmj3H7Ye/ZBL3aDUW0donLxJ6w01Gk31Or34WEJxd+xzj2BEk6lGH0pSEFbVcAIvd08y2\n18iLhFrYrnpe7oGshS3OnfgcSTbG90Ia0fEQ78rcOdqNeSbJAKU8GlEXrQMKk9Osz1JiqPkNSlOg\npCYvc/Iypx51ObP2WkWSyPB0wIX1LxIGjen367aWefHcN4iTIUppoqCBkl5lMnJEqfz4sFiMUQTe\nMvXwWXqjt9GygTExYCnLMa7XlSGER+itVuAzjxTRVD2jNAmN6CJF2SMrdsmKPaQMkcJnkt7G0zMY\nkxN4s/h6AazF2BxPtQi8FUAi0dVnNZQmRslj9QipNPHogKv//J9ozCyTTvrsP7pGd+UcncUz02sw\nt3aBwf4DHl57i/7uPWqtOaeyPnLX9MLn/wN+2HjiHEgp6NRrZEWJEKCkxFhL1ziVFUzOjXe+izWG\nWnsepQPSyYCDzRu0505S7zgWpBCCuROX6O/e5+7lH9Lfu09Y7zDp73K4c4el06/RWTz9JCNQaoga\n1UDuh0J6iM6ycyfQPhQ5Nh0h2osIvw5+DblyETs+QAR1d4y12PGhU+xIRk60ubMCZY6Mmth0goha\njnghJLbIkNonOPkapKPj+8WUYPLpwDJCohZOU175MVYqvPUXyR+8T7lzB2/9RWwWUzy6BoB/8Y8o\nDx6R3/4VdtxHr79IfvMXlL0t/AtfdvJYD99HdVcw8ZD4p/8n1pSEr30bMzpAn7iE6W076v/imd95\n734S4ylwfQrCC5okcY94sodAoL0I/SEF+COR3OW5CyjpsbF3jUc7709JEbWow4VTX6FZX3KzRF6N\nyK9Xw8auhKcfW1SkkDTrs1W/4klDPIEgClo0PqZcabAkZYr0AqTQ7A43CL0IJTXNaAakJAga7A4e\nUQ9axEVMUCSUtkQIyf5o25FFihQlNUr7aOVXQrmWwK8TVsAHYqpj6OkA+XuoxWK6uy6nIISQWFtg\nTFrZikga0SWyfI9B/Gtm6l9AyiOvryM7F+UEcVEY8urfHp6aIfCWULJOq/4KSXafUfxb2vXP0qq9\nTJpvMojfY6b+xaoHaB2Y2ifLeUIoTl78KqPeJv2du1hrWDr9Aqvnv4TS2l0rUyKV4tSlr9DsLHCw\ndZv+zm0QEDUX6C6dQYgj1RWLsDmzq+eptxdpBCCj6IlszD7Wr5xbu8j+o2v0d+658+pHLJ1+mcVT\nr6C9yFndAEr5nHnpm+x0VzjYuM5ksIsfNjjz0reYP3Fp2ncTUtJdPufsT3icqWept+aYP3EJr9ZG\nJIfY4ZbrATUXQRhnMDrpwWgXhtsIHTig2rkOykPOnMRODpDdNWzvEaLRxezeBK2RtRb28AHGGuT8\nOezeLdi/gz79RWgtuHJqkcJwywFWNnHgmgzIH93AFhn+s190TMoyx6Zj0sv/hGzOIesz2Cwmv/dr\nZNSCsiB59x+IGjPkd94l/Ox3kFHTMTbjISYeoLpryNk1ZK2Dmj1BuXOH4t5vKDZvEFz62u+8bz+p\n8RS4PgXhhy2055h6teYSSj1Z+rBF5sofZYqUmqWoy/zii+RxD6M0Uod4QqBkALkT/jRR5yNgdFRi\n0zpAKY+8zCjKDK18/ErmSEmNp8OPJDdHC5ISiqLM8ZRPnI8oK6X1RthGVNT6OB1RlHllAulKfdbk\n5GU2BVFX5quT5DFlOnBlUCEJvTpZmQCgpUdepmRFymxz+Ym5ro8LJSPSfIth/GtCfw1fz1UA876z\nNDEpaf6IohygVRshNHF2m9KMmKS3qIfPoZXL0iwGKXxqwTkm6S1K84jQX6Moh4zT61hb4Os5jEkY\nTt4FofFUFyEUnmgBLnMWSIxNUaJWnUdDEDWZP3GRsshJhncxxQiT7VCIlDx1w7FKh+TJAY22z+zq\nN5n0bgIQNk+Qjh6QDm9Thl1MkWCKMacufZkyHzA5/AAjfFLvJGVp0Uq6ZMtYAk+zsP4S8yeeZ7B9\nn2wyxAtrFFlG0tsnPtyjzDP8epM8HjvSz8kXWT7zGmWRMuzt0+ouOvX0KqTUnDj/edi9g9257SSo\nEjc8P6O0y8z629jRJmJmFdt7VCm8lCAUdlABizWImROQjrGDLcTSc861u/cIUetiDx8gwpbLcDcu\nI+fPOtp7UMf2N6A+i8gTRHN+alFitQ9R24FWqAHrgCpPndagF2LGh2TX3kafuEjx6Kr7UtoHU2KT\nMemtd/BOvgBbN6EsncmkX6uGnoX7b5E7XdGg7sqIUqJPvUT8o/8D2ZpDdlf/oHXgkxRPgetTEKP+\nI8oioSzSShnCETSmIUSlCK6dYkaRIZWPipxSg1Q+0lr3wAkJUjGK+1ggTseApdtcwNM+eZFydvXV\naenP1yECwfbgAe1olm5rpSotOrZgaQpKWyIRZKXLHkKvNmX2GVsiKyV3ay2d2hxSSJY6JzHWUJQ5\naUW191WA0ILCFEReHV8HlJV1iQU85aOVR2BDt5MWkojGVC3+d4XNxlDm+DbE957HlimyALSgU3/d\nZT7lhCS9j+fNEXhLlCamNGOEVbRqryIQlOWQ0FtjEl+nFp3DmBwlazSjFyiKQzw9R57v0gwvURq3\nsCMkStQJghWkCCjKflVajKpB6I9nlgkhUdqnzA5c38ZkKK/FaP+3RO2zWAteOEuZjynSQ2w5Rvud\nyv8rImiskce76HCWtBhjbUE2cWUpQUEzDKDSJpyM+oAg8kPi8QCsod5dAuUhhCSMmkilKLIUFdYo\niwLhh4SRW4iLPMPzQ5LJiCBqIJVmMuzh+SFCSrbvX2O+3cEL60xGffywhRc5WxRhLUL7mLFjAboe\nmMAWiWNImsIpxIQdRNDAah+xeAG7eQVWX3LglQyhzDBbV1yWBlARN5ynWexsedyZfeIcE7axQZPB\nYIAxJZ1GC+/US6S//j7pe/9AcOlrqJlF7KSHd/IFzGif4uH7yNYCwfN/DFjMpId36iXU7Cp68Qzp\ne/+Af/GrmHiATUbk9y8jZ5bRa8+Rvv8G5c5d1NIzCM9Hn7h0rGD/KYqnwPUpCGtLlA4pi5Qin+D7\nTWyZuQqT8lzf4Ehs1loG2ZhH+9cYjHYojdMEbDeWWF28RCOacZlbkZEVKQQ1fB2glcfu4BHjdEDg\nOameowxotrnMzuAhSmiaUYedobMCWWitst1/QOTXaUVdtPQwtsRTvmP4KY0xJfJIjxDLzuAhdb/F\nfGuVvHTOxMaU7jhPkRfZtDQ5iA+dzFSZOxA0JcPkECkUSmoaYRspJIp/4cG3BkyOKNKqHNR37l6+\n01EUgKmYeGU5JE7vIoRGoNGqTp6PKMsxQngE/jJatdC6S5ZtYkxCWQ5Rqo4UHqVJ0FiKok9e7NNQ\nzyNl6DI4jph7qspuC4pygK9/t2J42DxJHu/ihV2KrEetcx5TZZxZso/y6gS1E5gyrWbAWmBLhPSQ\nOnLK5NaZRgbNk2STLbxwlsB3G6Aiz0gG+4x6e8wurzMeHNKeXaQockajHq3uImkS44cRo/GANB6T\nxiP8IMKf1JiRit7+Fsvr56eZVpGn9Pe3iMcDVk49RzwewepZDgcHHO7t4AchJ+fXkfKxDFkI7P49\n8OuIzhp26wNsf9O5GQR1J3xbqazb4TY05h2QeSH24B6iuehEmpMBorUIVXYjTIn16+7ftnSecM2q\nVGhy0CF5nvNPP/weaZrwV9/+X4iCiPCz33EYJxXha3/ujvdrpL/5J4L1l1Er5yGd4J/5rFMVkRIz\nOkQtnkWvXQKlUTMrhF/8j4DFJiNslhB95X8DIL/+NiJq4Z18/sle4KckngLXpyDqzRX2t39LMjlA\n6YBa0ID92xC0oLXE4+yo/miLD26/gdYBM+1VPBWQFQn94Ra90RaXzn7DESaUN+1pHTEPe5M9lNQU\npTNjnGsusz/awlcBjaDNTH2eSTZilPapB81pn2mpfdLNagnB7mCDrEzR0mOmPs/ueBdrDfNSczjZ\n5WC0Q2O2g3Pj3SMvMuaayxRlziA+dOWn9hoCwSQbEuho+hkLU5AXCSDw9YcV2n9P+I1j401A1GYp\nyoLSQjDt4VUmkkDgLWFsjpIhQgRgxkgZuf6icj5aAoExqSsZyoiiHCJlDWtSynKEsSlSRpQmdqVF\nWz6mS+jmv4wtsBxrISrtEdRaICp3Yqnxayt40UJFyqEqQRnS8SZho44fzYPU1GeedQuoUGivCZMD\nVLQI0sMLZtw8krV4QfeJ/tZk1CdNxhhryLMErT38oEY8HqC0jx/UyNKYZDwknYwQUuKHNTw/pCwL\n4vGANB5hSkOep+RZSjIZUpYFZZGj/QA/jFDao8wzPD+g2fmwqC6IoIHonnLswMkheDXHGhQCRvtQ\nKyEZYZMBRDPOt22465iKyRCrQ+zkENXoOrsVWwAStOf0MLMxcuGcE5w+uOsqE1KDKZAyYG5uniLP\n0UGE8AJMPKA82EAGDWw6xowOQSlUZxmUxhxsYAa7CKUpd+9WWo7akUHqbWyeIrRPcfc91OJZ1NxJ\nzGAPtfQMCFC1FvrCl1w2+SmMp0aSn4LIszGj3kPKMkVITSPq4EsPbOlU3quynjEF79/6IUIIzp/4\nPN5ji3Waj/ng9o+phS2eOflF0jwh8mvTBcRay+F4h358QDuadSzAsENvss9sY4GdwQZKKrqNRbb7\n9xFCMt9cYX+0zUJrlaJ0i/m9/WvMN1dohG32R9scjHeQQtJtLNKOutzdu8bZ+UsM0x6PDm4TeCGh\nV8fXIWk+YaG1hq5KVHmRoKSmPKJhV/qEbkZNuEzuX7FbtdbyzuW3eLh1jz/58rcIPGdDYmwKKKg8\nsaTwKcoBSrWqvytcL8wWCKGwtqh6YcoRLmxJWQyQMqTI9hAqwpYJSO0yMhlS5D2Ubrrdv7AUxQBP\ndXDMRkue9PGCCCFB+/NY8upzCaTwK3ByPUGRprBzFdFYdP5b1jgtQVn1z7wQvBo27iGijlMO6ay5\nTKVaN4ospX+wjZSSRmeOUW8PhKDZmWdwuOPmupozDA53kUrheYHrQSqFlJLJaIBUika7S29vE88L\nieotxsMDpNK0FPT3t9EmJwgj+v0DotlVmqvnnrh2RxqItrfh5rKU5xwPyophWO8i/Bqmt4GodbCT\nQ1cKLBJsMkL4dWzcQ86dcg4KOnDApLTLlqaSUNXQdJE6EBMSdIhBQJkhdQBBEzPcp9i8jk1jp8CR\nDJGtebAWNbOMqHeQfoSNh9gyd/qGR6K6ZYEIath0gpn0nIFrcw4bD5BzJ9x7jvadPmRr/iNjC5+A\neGok+TRgMtomnuziBy03S1N5J2HKJ44rypxJ0uf0wkW8ySHEPag8swIhmZ9ZZ3v/FtaWHA530Z1l\nRvGAyK+R5DG+jmgFXSKvziQbI4Visb0G1jLfXKYwBdYaunU3cFuakrnGEkrqaSlQSU3kN6a9sdCL\n6NTmqAdtZ1ciFKp6UH0d0G0sUfPqDJN+RcYYUyQ5CIGnjhfqonSZSbe+8MRw9b82orBGs94G8ipz\nlJTlACmdBBRCuaFhDKUZO+q8LciLfaQMsdax5Da2HzGOR5w/fYmyHJInm7jekcYWA4TwUaKBKSYI\nT2PKCVJFmHKCNRnYgjS9jdItEBIh+i7LQwAlWbmHFCHGphRmgBI1LIbCjGjYRac7mA5dKTRoOjkr\no1w/U3pOPeNo6xjUneAyYKzh8tV3WF89y9yy0zSMsxxRnyXJcshKRK1LLfAJfI+5sMZg0GdrZ5M0\nSajXGywuLjO3vD4FoPbcKvv7u8iiYHap0knME2YaXfqH++xNRsyefomw1phm+Xmesb2zRb93iFKK\nuW6X7uxpB1yujowA+oMe+SRndvFZhsM+WwNDdrBFvVZnZfk0QVhDWFv1iyxZlrG3t0Ov38OUJWEU\n0Z2ZZWamW4kXG/K8yd7uDqVxWpS+7zM/10ZIhews4rfmOfLCA8toPGJ3d5txb4QcHdBqdeh2F6jV\n6k+CsLUMhn12DsckSUG9HrLY9qnNu3NljfPYs3Ef0Zh92uN6Gp/cyLNJVc4SmOai2z0XyRPHiCob\nya11JZQidaWIIoMqg5FSI3AqFqO4z9bBQ9qNLnE6JvBCirIgzRN6431Ud53AC8lNRpJPGKeDStap\nxFfO/FBLja/DadmxHc2ipMJYw2xziaKfM06HNAInPaSVB0LQjrqkecw46VPz6hW7UFDzm1Ow+khM\n9e3+38dzz7zEhbMvVia+MUqGlKZdDQTD8abxiAov0bSf+J21lpt330FKxfnTlxxNXUYOmEyKkk2M\nSR07zmQI4TvQMznW5EhVx5gYL1hCqJAy7yGP3JutASSedKoYUvho2Zi+t6+6iCKB9hr4NSfc6tcR\nrWWOFlpM6Zh42cRtYKSqFlhLnEy4cuM9FmaXmGm7HltRluz0h+wNRrTrEdZYzizNYYzh+o0PeOvt\nH5MkCVpr8jyj0+ny9a99i+WlVVfKLQp+9tYb5FnGX3z7r2m1OuCFDPo9vvuD/0YQBPz5n/4VQjui\nzmDQ58c/+UcePLyHpz1nWWPhlVc+y2uvvo7WHih3vd/7za/Y2trg1Vc+x9v//FMmkzGmUuX4y2//\nDSdONKfXZG9vl5/87Ac8evQAJRVCus82P7/Id/7ibyqgkYzHE3761hsMhwPG4xHzcwv89Xf+Bq9I\nnEhukbkesh/xaHuLH/7oewyHA3zfpyxL8jznzJlzfOtPvo3nufvfGMONm1d58603SJIYrT13rtoz\n7lwtr01B2zEn/01u5//fxVPg+hSEQDrQsrZak4yjv6snL79WHp3mCg93rxCETZoVg6+Umv5oi829\nG5xYesH1cfyIKGiwPHsST/uEXjQFrsALiYI69co/SEuPZjRDPWxTlBlxNnYzYNaQFSmFycmKhNIU\ndOpzDOJD0iJmobnKXHOZNI+rYeOMds0tknE2oR40makvTAV8j44xtpxKLBlbUg9a/yYNbGstGzsP\n2DtwaupRUOP0yTNkdo9QLKNVg3E84uHmXZYX1ni4eZet3Q087bG9gwcfAAAgAElEQVS+epbVpXWU\ncqC8f7jL7v4mdx/dpFFr8ZurvwSg1eiwvrYynTsripz7G3d4uHUXYz5gaX6V0yfOEYRdV+qlw8Gw\nR6+/xerSSe48uMHmznU8z+P8acXi3Mr0s48mQ27fv8r+4Q6BH7K+coblhVNIpSqoEkziMXce3mB3\nfwtrDe3mDGvLp1mYdaScLE/Z3tvgwcZdDvv73Lx7ld3qfJxYPs3ZpXnOLs0dq6QIwdbWBm/8+B9Z\nWz3B5z77JaKoRq93wI/e+D5v/Pgf+au//FtqtTr1eoMvfv6rfPfv/xNv/fwnfOPrfwbA2z//CePR\nkK999ZvU6658XRQ5P3vrR2xtb/An3/hzlpdXKYuC31z+Fb/4xZvMdLqcO3fsAlCWJds7W/zynZ/z\n2iuvs7JyArAMhgPm54/tYSaTMT/44T+wf7DHl77wFdZPnEZrzWg0pCgKQk874V4haDcb/MW//2uS\nNOEfvvdfKMoCk4wotq+7suRgG1HrIFYu8s47PydJEv7i2/8r3ZlZiqLg8HAfISVaH5t77uxs8caP\nv8/K8gle/1x1rvqHvFGdq+/85d+6cyBl9fx+OpHrKXB9CqLWXCKodavFyaKlchnXh0qFQkhOLD1P\nnPZ5/9YP0cqvekQFZZmzOPsMS7Pn0ErjewH7o006tTlqfp160Jyqw1tr8Y8YYmWBkqpiBsLG4BE1\nv0FR5uyNNqn7LQbxIXE+ohG0ibMxFieuCzDJRuyPtmgVMc2wQ3+yTyNos9G7Tc1vAYeO+i01fjXn\nlRUpUsrp4v9vGXE8Zntvg82dh0ghWV1eRWg1XSAHwx4//vn3mJ1xunKdVpftvQ2u3Pw13/jiv+fs\n+gVMabh9/xo7e5tMqnmm+xu3AViaW2V99SwIV7r9+bs/5ua9qyzNr6KU4he//in3N27z1Ve+TCCc\nbt/G1j3eff8XrC6d5LC/T73W5LC/x9LcKotzK444MzjgB29+lyzPWJhd4qC3x7Xb7/O5l77MxfMv\nI4QkTWN+9Pbfc9DfY3nBWbzcuneNJI2Z77rFfTwZcfXmZXqDfYoiZ3tvg/7oEIFgtrNAtzP3xPky\nxnDlg8tgLV/4/B/R7TpQazSavPzSZ/jBj77H1tYGZ864ntXq6gk+//pX+OnPfsjSovvsN29e4ytf\n+WNWV05Mz/Pu3g63b9/gs5/5AucfA6hXX3mdGzevcfXa+5w9ex712OYsy1IuXnyRS5demh7f7R5/\nXmst9x/cZWPzIV/+4ld55Zl1RBEDkvZMw7EI40NHuTc5AknUmMf3AzztUZYFwq+h5tZBSGRzFvP/\nsPdeT5ZcV7rfb+dOf/ypOuW7q71HNzxAEnQALWiGnNHMxCjmSqE36e3+NQo9KOJKo6urETmXnKEB\nhyBIELYBNNhoNNDeu/Lm+JN+62FnnepCAzS6Mw9s9IpAoPpUnsydO7P22mutb31f0EU4PmEUYpom\n5VKZQkGnOqvV2pa5Ukpx9vwHZFnGZ57+PCMjjS1z9dJvfsHCwhy7d++DTEEcDumhPm32wHHd56aU\nYtBdwvGqWE6JQW+FpD2HbxfAH4ENNoKcf81BcHD6CZrledpBi0Sl2JZPpTRBpTiOkaPnim6FOI24\ntnwe1/KZrG5HoYiTkCAeEKcRvl1EGpKyV0capm5UVSlm3ksGOspLoxRLOpS8Gt28VpVlCQrFem8Z\nKcyhI9PaWTGO5VNyK4TJgJHiJKAZxTOV/ZtFWB81IQS7Zw+we/YAb/7uN1y9eRHNvtFFqdHh5jeK\nI0zT4qvPfBfP9RkEPX7y0j9y4doZdm3fh5SSJ44+QxgF/Ohf/y9mJmZ55smv6msMG7kVt+dvcOHq\nB3zx6W+ye7sWebw1f4NfvvJjbszsYd/Ow/nAbrDeWmF2Zjfffu5vsC3dv7aRFlUq49TZd4iTiOe/\n/FdUSjXSNOGd91/n5IfH2T61i3KpSrfXZm7xFs888RwH9xyDLCFqL2iEW+sWSJsqGc8+8hlut9q8\n8PI/8ZlHv8Tk+DaALRuFIcdlErO4OAcCLl+5gHnj6nA+19ZWSNOEZmtTW80wDA4fOsbi4jyvv/Ey\nAPv3H+LwoaNb4O8ry0uEYUir1eTke+8MP0/ThCxNabWaJEmyxXE5jsvU1Awalfnxz3hh4Q6maTE7\nu0fXj9IkRw/GGuyxYRvZiyyBu3rphOVgeDN5X6TCyPW3Du4/zMuv/Ip/+ekPOXTwKLt27qFarWPc\nJUyZJDGLC3MIBFeuXuTGzWufPFc5tJ+wB175rmFtqi3cz07tgeO6zy0KWjRXL2FaPpbtEwUdyuUp\n/ce48WJnMbTnNbJMWpgIRp0yo7Udmustt01qH0UvbNENW8zUd2FJm07QZLQ0iW26+E55WGfaQPL1\noy62tBkpjLPeX8G3i1S8OoOoy0hxnDgJc2YLnzAOUOiIY7Q4oRuK7QJplgwdZsmtYklb1xrCFkE8\n0GhCRL5oC0xDa36V3NrHzMz/P/soEar+UdcON8wwDPbuOIjnatSl5xaoVUZpd5pkmWZU16z9Rl53\nuxfhqJTixp0r2JZDqVCm3dELlmM7OI7L3OIt9u08PPyOZdkc2P0QruPlY9hcZAfhgFvz15ga365b\nHtprANQqdXqDLuvtVcqlKq7rUyyUOXPpFK7jM9mYxPUq4KR3vSsJhlPCaHeH95rEMUkSYxgGaZoO\n++g2GOTDKGQw6HPmzPv3LKb1+iiO7WyJjC3L4vCho5y/cAYhBIcOHdX1qrtsEAzIspTrN65yZ+7W\nxqwBYFomlXJZAxhUNmR3l1JiJX3oLg0RhwxrngrsEoPBAMu0sB1Hi0UaJnQWIWiBU9JtEVEvd1qp\nbnL2RobXBsia8xjlMTBtss4KKuixf7KB//z3ef/93/HW26/x7u/eYu/eAzz+6NNUKpqFJk1TwvAP\nzJXjbrwguvfyo9yNSazvyylwP9sDx3Wfm2n5eIUG0vKw7SKF8jSOU4Tly3rX5pa1E6tMsRky9PRn\noPteDAmWR6e3wiBsM1bfjSUdZmq7dNNtljBWnkYaW1+nLNOSIYYwGERdeiojSSMMIRlEXdIsJSMj\n6SVDCLtmy+hTcit0g5aucSWDIVy+VhijH3ZQKqMTNIfX9+3i0FGlmdTpQiGxPsrs/W9sQggsozTs\n49KfGfhecYsjEkLk7IL32sd9lqmMbq9Nq9Pkl6/8eLPtAAiCPtlH0ryWaQ2d1kctjkKCcMCVG+eY\nW7gx/DxNE409TGJUllFwfb789Nf53YfH+c2bP6dYKLF/10NDh/hJUWy30yJJYmzHJYk196MQAsuy\nMaSJaVqMjo7zrW98BxEH2pEIA5WEYEhs2yHqrqLSGNMtk2Bw8tQJbFs/u1OnTtAYHdtctNEIPtM0\n+eIXnmP7tp16ZvrrOZRdN7DbcQeipoazbzhGaWugiTD0Rs2Q+l1XGRgGlm2TpglJnPfHZYl2TvFA\n/+dGWgHbz1k1pANBe+uESHuI9DNKo1CsIw3JrhGL7dt2sLy8xLnzH3Dm7GnarSbPf/P7uK6LYRiY\nlsXo6Bjf+fZ/N7z/Lc/ZslFZiooH2rF9VJNLiLuc8f1rDxzXfW7StKk19rMFaRdqihuyDTkFYwhz\nViqD3vIQSagpczyoTNHuLdPuLTFS2zFkvMhUhmlYNMpT91y7H3V47/qrHJ7RtEi2dLBNhzjRLA1K\n808A6PQhugZX9mr69/liM7d2lcX2LXpBi32TjzKdC19GSUCURprg1zDx7ALSMAmiPh/cfJO9kw9T\n8mb+fSc4Z2/fQnQLn7jIf5xtuCQ1hE4LBAIpJfXqKF96+pv3RBzePU7qk0U0hWEgDcnu2cMc3HOU\nDdRgmutVlV2HZNBCCMloocjXnvkOq601Ll07y7un32CtucwXn/r6PWPIb59yqYwg1/8S4q50oUGW\nZTRGG1y7doU0VdRHJnQklKVkSYRhuVsjTWFw6nfvcPPmNZ798jdQKuPl377I+6d/x+OPPT1sZRgZ\naSClZG1tlX17D+lzOI5+XzfmIYfDk4/rIyPXTcrCyJ2WBGEw1hjndI5AHB0dA8OC4buttJMr1LXz\ny/I0YnLXNTeOI38HLGdL+tSybCYnpxkfn0QIgzNn36fTaeG6LpZl0xgd48rVi0RxNIzENudaDSdd\nSEtHgyr/PLiLsf4+ThFu2APH9SmwMGixvnR+mJaqjuzBK41rwlKliJI+lnQQwiDNUpS/NfWhd6eJ\nFovUdPAoFGES4Jgu5Y9heQfIlCKMB7niMcRZRJal2KZLplLCWMPxHdPVCDZ/E42WpPGQ9WK2cYCJ\n6iwnrrw0RA8COJaPbXrDsRpD9opMX/cjUcm/iwkDgUmmolzJ+E/8OoIs0/pcadZDCBvT0H09YyOT\nzC/dxnU86tXNubl7IfxjzHN8KqUa/UGXerWBZVpbFkG95uYQeAUIweTYDOOjkziOy5mL7zEI+pSK\nm2rIQzXrNEZFPdKwj8oSpFskSyJ9jDRBKQ4eOMKVq5d48+3X+MxTn6dUKpNl0A8SOkt32LZtVkcS\nSnH16iXePfkWhw8dY/++QyilWFyc591336IxOs6OHbsRQjA+NsHs9l2c/uAk9doIMzMasRlFEevN\nVUqlCiP1rUARQG/azFQ7HZWAXdr0OYbJ7PZd1GsjvHPiDTzfZ3JiGsMwCMKAfr/H+NgkpqspzVIk\naZYSJ5nOHmQZQRDgGDYyyzAN7cyjKOT2nZvUayN4XgFhCAb9Pp1OSwM7rE09rkMHH+LKlYscP/4K\nn3n6C/lcZfQHfTrtFjMzs1hSD1iMbN/s4Qq7+hm6xU3OxvvYHjiuT4GFgybl+k4KJa2wKww5jL7a\nnQXOX3+N2amHGavt4sqtt1nvzH3seaKoz0h1O9Iw2VbfM2zETLOEKAlJs3QoDbKhdgwMfWAUD7T6\nruVrrsC8N0uh6AzWWW7fxrUKFN2KbkreOJcwsUznnh4sQ8sfo5QiiPt0g6Zmn5f2vwtKOEkTOt0W\ncRLR7bWJk5iVtWV8r4jvCqT7pyEYTWlSLlWZW7rN4vISjuMijYhKqTgEgly4+iGvv/sSxw4+ge8W\nCKOAtdYKs9O7qZb/OEFBy7J5aP+jvHbiJd459Ro7t+1FGpLuoMNg0GP/7oewTIullQUWV+dp1Mex\nLYcgGrC4MkfBLw0X1w3zvAKmaXH19mX8vQ+jhI1frOp+pKCTgxl0im5mtM4XnnmW42+/zn/90X/B\n9XSPVxgG1EdGmZycxrJsms01Xn/zZUZHx3jyic9imiZKKZ584nMsLS3w+psvU6vVqVZq2LbD5595\njt++8iIv/foFPK+AIQ3iOCJNU77y3PNbHNdGTVEUx6Ba01FWTmK8ucgLKhWXL33pa7zy6q944Rf/\nTKFQxDAMojCkXKnyve/+DaZpkmUZx4+/wq07N4njiPX1NZTK+PG//CO2ZTMy0uCLX/gqjuMQRRGv\nvf4bgiCg4Bc0Y8igTxLHPPHEZymVy8MxTk1t4wuff47jb73KP/3ov+BtzFUUUKuNMDE5jYXQdSzT\n2tzM2J6+nyQC283v7f51Xg8c16fApGmzvnSeQW8ZIQxK1VlcXwMWLMujVp7CtXXP1SBs4ViFj9XK\nanUXAEU3bAHQGTSJ0xDH8qn7jWH9yjAkcgMaT8b15XNESYAQgkHcY7y8jf1Tj2OaDmE84Pydd2kP\n1rCkTZxGjFe2sXv86BZ9r08ypRSt/iof3j6uJVUMzQCfpvEf/O6fau3OOq++8yJBOCBOIqQUvPHu\nS0hDsnfnQY4dfAIpJdVK/Z7aWtEvkWXZMDUKWgn6kUNP8vqJl3jxtX9BGiaz07t45vHnwJBUSjWe\nffobnPjgTX57/IU8GDKolipsn9qpoyalcG2XaqWOvAt1p3+X5rUdwe7t+0iTkNPnT3Lx2oeQpyJ3\nTO8epu7iOODD8ycI43i4ASkVK3zu8edwbHfLuaulGo8ceoozF9/j+u3LmNLkc48/x+z0LvDzmlEe\nARtCcPjww0xNbeP2nZu02y09T9U6ExNTuK6Lyjkfn3r8MzRqFQpmhgpaYJgUbcnXPv8FlhduQX8V\n5ZrglKjXR3j+m9/jztwtlpcXSZKEQqFAozHBeK2CGjSH9atDu3awrVHDJ9CMMPpGcvFHkS/6Ibhl\ndszuYuR7f8ftOzdYX1slU4piocjkxBSO46KSEBENmB0fYaTo5KnGXNYk0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skSegxhWx+3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wGn7Fisz9eJkhTLOF9xDT2fZtllfb6OH8VEScqFhRbX7h+iKgpr7Qb3jnr0Rh5lx6RecjgZ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\nAB+38bk6NQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10e54f390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "d = getcwd()\n",
    "## join all documents in corpus\n",
    "text = \" \".join(filtered_texts)\n",
    "## image from PublicDomainPictures.net\n",
    "## http://www.publicdomainpictures.net/view-image.php?image=232185&picture=family-gathering\n",
    "mask = np.array(Image.open(path.join(d, \"family-gathering.png\")))\n",
    "wc = WordCloud(background_color=\"white\", max_words=1000, mask=mask,\n",
    "               max_font_size=90, random_state=42)\n",
    "wc.generate(text)\n",
    "# create coloring from image\n",
    "image_colors = ImageColorGenerator(mask)\n",
    "plt.figure(figsize=[7,7])\n",
    "plt.imshow(wc.recolor(color_func=image_colors), interpolation=\"bilinear\")\n",
    "plt.axis(\"off\")\n",
    "_=plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building the models to find correlated concepts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "#modules to build the topic extracting models\n",
    "from gensim import corpora, models\n",
    "import gensim\n",
    "import pyLDAvis.gensim\n",
    "pyLDAvis.enable_notebook()\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "sns.set(style=\"whitegrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2767 different terms in the corpus\n"
     ]
    }
   ],
   "source": [
    "#creating the dictionary\n",
    "dictionary = corpora.Dictionary([\" \".join(filtered_texts).split()]) \n",
    "print('{} different terms in the corpus'.format(len(dictionary)))\n",
    "#creating the bag of words object\n",
    "bow_corpus = [dictionary.doc2bow(text.split()) for text in filtered_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tfidf_model = models.TfidfModel(bow_corpus) # creating the tf-idf model\n",
    "tfidf_corpus = tfidf_model[bow_corpus]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Building the LDA models."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/EduardoAndrade/anaconda/lib/python3.6/site-packages/gensim/models/ldamodel.py:529: RuntimeWarning: overflow encountered in exp2\n",
      "  (perwordbound, np.exp2(-perwordbound), len(chunk), corpus_words))\n"
     ]
    }
   ],
   "source": [
    "total_topics = 50\n",
    "lda_model_tfidf = models.LdaModel(corpus=tfidf_corpus, id2word=dictionary, num_topics=total_topics, \n",
    "                                  passes=1, random_state=47)\n",
    "lda_model_bow = models.LdaModel(corpus=bow_corpus, id2word=dictionary, num_topics=total_topics,\n",
    "                                passes=1, random_state=47)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/EduardoAndrade/anaconda/lib/python3.6/site-packages/pyLDAvis/_prepare.py:387: DeprecationWarning: \n",
      ".ix is deprecated. Please use\n",
      ".loc for label based indexing or\n",
      ".iloc for positional indexing\n",
      "\n",
      "See the documentation here:\n",
      "http://pandas.pydata.org/pandas-docs/stable/indexing.html#ix-indexer-is-deprecated\n",
      "  topic_term_dists = topic_term_dists.ix[topic_order]\n"
     ]
    },
    {
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       "<div id=\"ldavis_el1202060400145442157366172\"></div>\n",
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       "   !function(LDAvis){\n",
       "       new LDAvis(\"#\" + \"ldavis_el1202060400145442157366172\", ldavis_el1202060400145442157366172_data);\n",
       "   }(LDAvis);\n",
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       "   // require.js is available: use it to load d3/LDAvis\n",
       "   require.config({paths: {d3: \"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
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       "    LDAvis_load_lib(\"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js\", function(){\n",
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       "            })\n",
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       "}\n",
       "</script>"
      ],
      "text/plain": [
       "PreparedData(topic_coordinates=            Freq  cluster  topics         x         y\n",
       "topic                                                \n",
       "3      32.051210        1       1 -0.009426  0.000220\n",
       "40     14.432954        1       2 -0.016656 -0.000772\n",
       "44     11.951673        1       3 -0.009170 -0.006819\n",
       "27     11.709898        1       4 -0.006163 -0.000390\n",
       "14      8.429031        1       5 -0.008492 -0.004052\n",
       "22      8.123675        1       6 -0.019578  0.002358\n",
       "10      7.091608        1       7 -0.017685  0.011123\n",
       "47      2.074981        1       8 -0.017349 -0.003336\n",
       "37      1.377237        1       9 -0.015923 -0.000776\n",
       "36      1.224570        1      10 -0.018588  0.000969\n",
       "20      0.724880        1      11 -0.010825 -0.000722\n",
       "45      0.352858        1      12 -0.004208 -0.003611\n",
       "7       0.177558        1      13  0.000438  0.007935\n",
       "39      0.116154        1      14 -0.008278 -0.001428\n",
       "28      0.115098        1      15 -0.014198 -0.000870\n",
       "23      0.028988        1      16 -0.014439  0.007439\n",
       "31      0.000584        1      17 -0.003358 -0.007850\n",
       "13      0.000516        1      18 -0.005742 -0.003039\n",
       "12      0.000516        1      19 -0.004047 -0.001036\n",
       "15      0.000516        1      20  0.004605 -0.000681\n",
       "49      0.000516        1      21 -0.002179 -0.003746\n",
       "11      0.000516        1      22  0.054969 -0.000391\n",
       "9       0.000516        1      23  0.005431 -0.001062\n",
       "8       0.000516        1      24 -0.003530 -0.001900\n",
       "17      0.000516        1      25  0.047555  0.005476\n",
       "6       0.000516        1      26 -0.002678 -0.001012\n",
       "5       0.000516        1      27  0.001971 -0.004411\n",
       "4       0.000516        1      28  0.012761 -0.007691\n",
       "2       0.000516        1      29  0.003698 -0.001087\n",
       "1       0.000516        1      30  0.013436 -0.001733\n",
       "16      0.000516        1      31  0.006371  0.010257\n",
       "24      0.000516        1      32  0.018824 -0.011184\n",
       "18      0.000516        1      33 -0.001318  0.000892\n",
       "19      0.000516        1      34 -0.001137 -0.000184\n",
       "46      0.000516        1      35 -0.007494  0.005305\n",
       "43      0.000516        1      36  0.009254 -0.000776\n",
       "42      0.000516        1      37 -0.001399 -0.005656\n",
       "41      0.000516        1      38  0.001313  0.010848\n",
       "38      0.000516        1      39  0.006333  0.005802\n",
       "35      0.000516        1      40 -0.003161  0.003768\n",
       "34      0.000516        1      41  0.015113 -0.007060\n",
       "33      0.000516        1      42  0.023363  0.011138\n",
       "32      0.000516        1      43  0.002210 -0.002436\n",
       "30      0.000516        1      44  0.006277  0.002179\n",
       "29      0.000516        1      45 -0.009993  0.001917\n",
       "26      0.000516        1      46 -0.008734  0.003355\n",
       "25      0.000516        1      47  0.004174  0.000216\n",
       "48      0.000516        1      48  0.003151  0.000270\n",
       "21      0.000516        1      49 -0.001408 -0.005583\n",
       "0       0.000516        1      50  0.005912 -0.000174, topic_info=     Category         Freq          Term        Total  loglift  logprob\n",
       "term                                                                   \n",
       "17    Default  6319.000000       trustee  6319.000000  30.0000  30.0000\n",
       "4     Default  3675.000000         trust  3675.000000  29.0000  29.0000\n",
       "27    Default  2360.000000          fund  2360.000000  28.0000  28.0000\n",
       "49    Default  1971.000000        person  1971.000000  27.0000  27.0000\n",
       "61    Default  1688.000000        income  1688.000000  26.0000  26.0000\n",
       "24    Default  1344.000000         power  1344.000000  25.0000  25.0000\n",
       "140   Default  1285.000000          time  1285.000000  24.0000  24.0000\n",
       "62    Default  1255.000000   beneficiary  1255.000000  23.0000  23.0000\n",
       "5     Default  1184.000000          deed  1184.000000  22.0000  22.0000\n",
       "108   Default  1003.000000      property  1003.000000  21.0000  21.0000\n",
       "76    Default   766.000000        clause   766.000000  20.0000  20.0000\n",
       "60    Default   763.000000           act   763.000000  19.0000  19.0000\n",
       "19    Default   796.000000           pay   796.000000  18.0000  18.0000\n",
       "395   Default   722.000000       company   722.000000  17.0000  17.0000\n",
       "196   Default   758.000000      exercise   758.000000  16.0000  16.0000\n",
       "48    Default   708.000000       include   708.000000  15.0000  15.0000\n",
       "46    Default   680.000000     appointor   680.000000  14.0000  14.0000\n",
       "83    Default   647.000000       capital   647.000000  13.0000  13.0000\n",
       "129   Default   605.000000    discretion   605.000000  12.0000  12.0000\n",
       "82    Default   608.000000         share   608.000000  11.0000  11.0000\n",
       "167   Default   590.000000         money   590.000000  10.0000  10.0000\n",
       "239   Default   569.000000      interest   569.000000   9.0000   9.0000\n",
       "36    Default   550.000000       account   550.000000   8.0000   8.0000\n",
       "37    Default   477.000000        period   477.000000   7.0000   7.0000\n",
       "38    Default   464.000000          mean   464.000000   6.0000   6.0000\n",
       "21    Default   437.000000          hold   437.000000   5.0000   5.0000\n",
       "297   Default   446.000000  distribution   446.000000   4.0000   4.0000\n",
       "252   Default   420.000000           fit   420.000000   3.0000   3.0000\n",
       "244   Default   412.000000           law   412.000000   2.0000   2.0000\n",
       "22    Default   420.000000         apply   420.000000   1.0000   1.0000\n",
       "...       ...          ...           ...          ...      ...      ...\n",
       "82    Topic50     0.003667         share   608.232894   0.1547  -4.9151\n",
       "366   Topic50     0.002543      director   387.766379   0.2390  -5.2810\n",
       "60    Topic50     0.004345           act   763.686611   0.0970  -4.7452\n",
       "49    Topic50     0.009089        person  1971.122189  -0.1132  -4.0073\n",
       "775   Topic50     0.000649      contract    74.715862   0.5196  -6.6470\n",
       "61    Topic50     0.007730        income  1688.545112  -0.1205  -4.1692\n",
       "76    Topic50     0.004134        clause   766.811076   0.0431  -4.7951\n",
       "52    Topic50     0.000926          sole   117.300054   0.4241  -6.2915\n",
       "41    Topic50     0.002228          date   357.214169   0.1888  -5.4132\n",
       "81    Topic50     0.001703   corporation   254.292663   0.2599  -5.6820\n",
       "83    Topic50     0.003553       capital   647.905013   0.0602  -4.9465\n",
       "17    Topic50     0.020776       trustee  6319.813300  -0.4516  -3.1805\n",
       "196   Topic50     0.003952      exercise   758.019644   0.0095  -4.8402\n",
       "48    Topic50     0.003732       include   708.533504   0.0198  -4.8973\n",
       "235   Topic50     0.001882         right   299.642298   0.1957  -5.5821\n",
       "107   Topic50     0.002195       respect   367.175735   0.1465  -5.4281\n",
       "195   Topic50     0.001998      absolute   328.855014   0.1626  -5.5222\n",
       "5     Topic50     0.005224          deed  1184.968915  -0.1582  -4.5611\n",
       "21    Topic50     0.002454          hold   437.969102   0.0816  -5.3167\n",
       "251   Topic50     0.002244         think   390.052460   0.1082  -5.4059\n",
       "377   Topic50     0.002142      security   369.818336   0.1149  -5.4525\n",
       "36    Topic50     0.002838       account   550.196017  -0.0010  -5.1711\n",
       "46    Topic50     0.003268     appointor   680.100780  -0.0721  -5.0303\n",
       "19    Topic50     0.003534           pay   796.109920  -0.1511  -4.9518\n",
       "165   Topic50     0.002125       appoint   368.929744   0.1091  -5.4607\n",
       "62    Topic50     0.004217   beneficiary  1255.152163  -0.4298  -4.7751\n",
       "167   Topic50     0.002730         money   590.216663  -0.1103  -5.2101\n",
       "108   Topic50     0.003099      property  1003.550147  -0.5140  -5.0831\n",
       "38    Topic50     0.002230          mean   464.223178  -0.0723  -5.4123\n",
       "239   Topic50     0.002260      interest   569.180759  -0.2626  -5.3987\n",
       "\n",
       "[4051 rows x 6 columns], token_table=      Topic      Freq        Term\n",
       "term                             \n",
       "2021      1  0.415066           &\n",
       "2089      1  0.695781          2f\n",
       "1459      1  0.241439         aaa\n",
       "1459      4  0.241439         aaa\n",
       "1507      1  0.176470        able\n",
       "1507      2  0.176470        able\n",
       "1507      3  0.176470        able\n",
       "1507      4  0.176470        able\n",
       "1507      6  0.176470        able\n",
       "195       1  0.334494    absolute\n",
       "195       2  0.097307    absolute\n",
       "195       3  0.158124    absolute\n",
       "195       4  0.133798    absolute\n",
       "195       5  0.079062    absolute\n",
       "195       6  0.082103    absolute\n",
       "195       7  0.057776    absolute\n",
       "195       8  0.015204    absolute\n",
       "195       9  0.012163    absolute\n",
       "195      10  0.012163    absolute\n",
       "195      11  0.009123    absolute\n",
       "195      12  0.003041    absolute\n",
       "195      13  0.003041    absolute\n",
       "168       1  0.300794      accept\n",
       "168       2  0.150397      accept\n",
       "168       3  0.133686      accept\n",
       "168       4  0.100265      accept\n",
       "168       5  0.091909      accept\n",
       "168       6  0.083554      accept\n",
       "168       7  0.083554      accept\n",
       "168       8  0.025066      accept\n",
       "...     ...       ...         ...\n",
       "2012      1  0.471568      |power\n",
       "2012      4  0.235784      |power\n",
       "2012      7  0.235784      |power\n",
       "2009      1  0.356390   |presence\n",
       "2009      4  0.178195   |presence\n",
       "2009      7  0.178195   |presence\n",
       "2013      1  0.342004      |print\n",
       "2013      2  0.085501      |print\n",
       "2013      4  0.171002      |print\n",
       "2013      5  0.085501      |print\n",
       "2013      6  0.085501      |print\n",
       "2013      7  0.171002      |print\n",
       "2008      1  0.602487    |settlor\n",
       "1444      1  0.433829       |sign\n",
       "1444      2  0.108457       |sign\n",
       "1444      4  0.216914       |sign\n",
       "1444      7  0.108457       |sign\n",
       "2010      1  0.478809  |signature\n",
       "2010      2  0.087056  |signature\n",
       "2010      4  0.174112  |signature\n",
       "2010      5  0.043528  |signature\n",
       "2010      6  0.043528  |signature\n",
       "2010      7  0.174112  |signature\n",
       "2007      1  0.542897     |signed\n",
       "2007      4  0.135724     |signed\n",
       "2007      7  0.135724     |signed\n",
       "2015      1  0.317892    |trustee\n",
       "2015      4  0.317892    |trustee\n",
       "2702      1  0.319143           ~\n",
       "2702      3  0.319143           ~\n",
       "\n",
       "[4859 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[4, 41, 45, 28, 15, 23, 11, 48, 38, 37, 21, 46, 8, 40, 29, 24, 32, 14, 13, 16, 50, 12, 10, 9, 18, 7, 6, 5, 3, 2, 17, 25, 19, 20, 47, 44, 43, 42, 39, 36, 35, 34, 33, 31, 30, 27, 26, 49, 22, 1])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pyLDAvis.gensim.prepare(lda_model_bow, bow_corpus, dictionary)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the topics for documents 03, 12 and 17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "np.random.seed(27)\n",
    "vec_bow_17 = dictionary.doc2bow(filtered_texts[17].split())\n",
    "vec_bow_03 = dictionary.doc2bow(filtered_texts[3].split())\n",
    "vec_bow_12 = dictionary.doc2bow(filtered_texts[12].split())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Viewing the topics of the selected documents"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "document 03 topics:  [(3, 0.075345944039359194), (27, 0.40886112389944279), (39, 0.018643289660613249), (40, 0.02759284971293401), (44, 0.45194924764671079)]\n",
      "document 12 topics:  [(10, 0.16041004212835228), (22, 0.44745773180268861), (36, 0.034127220990991462), (37, 0.020306193989949425), (40, 0.30730365022374589), (47, 0.015509030752539409)]\n",
      "document 17 topics:  [(3, 0.43117910486800543), (14, 0.043080651275866973), (27, 0.33344959275418595), (40, 0.024718801032967929), (44, 0.16250302721191706)]\n"
     ]
    }
   ],
   "source": [
    "vec_lda_topics_17 = lda_model_bow[vec_bow_17]\n",
    "vec_lda_topics_03 = lda_model_bow[vec_bow_03]\n",
    "vec_lda_topics_12 = lda_model_bow[vec_bow_12]\n",
    "print ('document 03 topics: ', vec_lda_topics_03)\n",
    "print ('document 12 topics: ', vec_lda_topics_12)\n",
    "print ('document 17 topics: ', vec_lda_topics_17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = pd.DataFrame(vec_lda_topics_03, columns=['topic', 'contrib'])\n",
    "df1['doc'] = 'doc_03'\n",
    "df2 = pd.DataFrame(vec_lda_topics_12, columns=['topic', 'contrib'])\n",
    "df2['doc'] = 'doc_12'\n",
    "df3 = pd.DataFrame(vec_lda_topics_17, columns=['topic', 'contrib'])\n",
    "df3['doc'] = 'doc_17'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0x167dd9cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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IV8OexVBx8zlhZecvcOGjdVRmXMbAzhZTHx8Kj0dw6rU3cH96Eo6jRzb5Itxu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\nIAiCIAidIJIoQRAEQRCETvg/eADP//4tmVcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x167dd6c88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=[10,3])\n",
    "plt.plot(df1.topic, df1.contrib)\n",
    "plt.plot(df2.topic, df2.contrib)\n",
    "plt.plot(df3.topic, df3.contrib)\n",
    "plt.legend(['Doc_03', 'Doc_12', 'Doc_17'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating the simmilarity between the documents\n",
    "Documents 3 and 17 are closer to one another than 3 is to 12 or 12 is to 17."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "simmilarity_03_12 = gensim.matutils.cossim(vec_lda_topics_03, vec_lda_topics_12)\n",
    "simmilarity_03_17 = gensim.matutils.cossim(vec_lda_topics_03, vec_lda_topics_17)\n",
    "simmilarity_12_17 = gensim.matutils.cossim(vec_lda_topics_12, vec_lda_topics_17)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similarity between docs 03 and 12 0.0242902625579\n",
      "similarity between docs 03 and 17 0.691911431814\n",
      "similarity between docs 12 and 17 0.0234388394818\n"
     ]
    }
   ],
   "source": [
    "print('similarity between docs 03 and 12', simmilarity_03_12)\n",
    "print('similarity between docs 03 and 17', simmilarity_03_17)\n",
    "print('similarity between docs 12 and 17', simmilarity_12_17)"
   ]
  }
 ],
 "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": "3.6.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}