HMM Tagger.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Project: Part of Speech Tagging with Hidden Markov Models \n",
    "---\n",
    "### Introduction\n",
    "\n",
    "Part of speech tagging is the process of determining the syntactic category of a word from the words in its surrounding context. It is often used to help disambiguate natural language phrases because it can be done quickly with high accuracy. Tagging can be used for many NLP tasks like determining correct pronunciation during speech synthesis (for example, _dis_-count as a noun vs dis-_count_ as a verb), for information retrieval, and for word sense disambiguation.\n",
    "\n",
    "In this notebook, you'll use the [Pomegranate](http://pomegranate.readthedocs.io/) library to build a hidden Markov model for part of speech tagging using a \"universal\" tagset. Hidden Markov models have been able to achieve [>96% tag accuracy with larger tagsets on realistic text corpora](http://www.coli.uni-saarland.de/~thorsten/publications/Brants-ANLP00.pdf). Hidden Markov models have also been used for speech recognition and speech generation, machine translation, gene recognition for bioinformatics, and human gesture recognition for computer vision, and more. \n",
    "\n",
    "![](_post-hmm.png)\n",
    "\n",
    "The notebook already contains some code to get you started. You only need to add some new functionality in the areas indicated to complete the project; you will not need to modify the included code beyond what is requested. Sections that begin with **'IMPLEMENTATION'** in the header indicate that you must provide code in the block that follows. Instructions will be provided for each section, and the specifics of the implementation are marked in the code block with a 'TODO' statement. Please be sure to read the instructions carefully!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "**Note:** Once you have completed all of the code implementations, you need to finalize your work by exporting the iPython Notebook as an HTML document. Before exporting the notebook to html, all of the code cells need to have been run so that reviewers can see the final implementation and output. You must then **export the notebook** by running the last cell in the notebook, or by using the menu above and navigating to **File -> Download as -> HTML (.html)** Your submissions should include both the `html` and `ipynb` files.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "**Note:** Code and Markdown cells can be executed using the `Shift + Enter` keyboard shortcut. Markdown cells can be edited by double-clicking the cell to enter edit mode.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Road Ahead\n",
    "You must complete Steps 1-3 below to pass the project. The section on Step 4 includes references & resources you can use to further explore HMM taggers.\n",
    "\n",
    "- [Step 1](#Step-1:-Read-and-preprocess-the-dataset): Review the provided interface to load and access the text corpus\n",
    "- [Step 2](#Step-2:-Build-a-Most-Frequent-Class-tagger): Build a Most Frequent Class tagger to use as a baseline\n",
    "- [Step 3](#Step-3:-Build-an-HMM-tagger): Build an HMM Part of Speech tagger and compare to the MFC baseline\n",
    "- [Step 4](#Step-4:-[Optional]-Improving-model-performance): (Optional) Improve the HMM tagger"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\">\n",
    "**Note:** Make sure you have selected a **Python 3** kernel in Workspaces or the hmm-tagger conda environment if you are running the Jupyter server on your own machine.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Jupyter \"magic methods\" -- only need to be run once per kernel restart\n",
    "%load_ext autoreload\n",
    "%aimport helpers, tests\n",
    "%autoreload 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "# import python modules -- this cell needs to be run again if you make changes to any of the files\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "from IPython.core.display import HTML\n",
    "from itertools import chain\n",
    "from collections import Counter, defaultdict\n",
    "from helpers import show_model, Dataset\n",
    "from pomegranate import State, HiddenMarkovModel, DiscreteDistribution"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 1: Read and preprocess the dataset\n",
    "---\n",
    "We'll start by reading in a text corpus and splitting it into a training and testing dataset. The data set is a copy of the [Brown corpus](https://en.wikipedia.org/wiki/Brown_Corpus) (originally from the [NLTK](https://www.nltk.org/) library) that has already been pre-processed to only include the [universal tagset](https://arxiv.org/pdf/1104.2086.pdf). You should expect to get slightly higher accuracy using this simplified tagset than the same model would achieve on a larger tagset like the full [Penn treebank tagset](https://www.ling.upenn.edu/courses/Fall_2003/ling001/penn_treebank_pos.html), but the process you'll follow would be the same.\n",
    "\n",
    "The `Dataset` class provided in helpers.py will read and parse the corpus. You can generate your own datasets compatible with the reader by writing them to the following format. The dataset is stored in plaintext as a collection of words and corresponding tags. Each sentence starts with a unique identifier on the first line, followed by one tab-separated word/tag pair on each following line. Sentences are separated by a single blank line.\n",
    "\n",
    "Example from the Brown corpus. \n",
    "```\n",
    "b100-38532\n",
    "Perhaps\tADV\n",
    "it\tPRON\n",
    "was\tVERB\n",
    "right\tADJ\n",
    ";\t.\n",
    ";\t.\n",
    "\n",
    "b100-35577\n",
    "...\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 57340 sentences in the corpus.\n",
      "There are 45872 sentences in the training set.\n",
      "There are 11468 sentences in the testing set.\n"
     ]
    }
   ],
   "source": [
    "data = Dataset(\"tags-universal.txt\", \"brown-universal.txt\", train_test_split=0.8)\n",
    "\n",
    "print(\"There are {} sentences in the corpus.\".format(len(data)))\n",
    "print(\"There are {} sentences in the training set.\".format(len(data.training_set)))\n",
    "print(\"There are {} sentences in the testing set.\".format(len(data.testing_set)))\n",
    "\n",
    "assert len(data) == len(data.training_set) + len(data.testing_set), \\\n",
    "       \"The number of sentences in the training set + testing set should sum to the number of sentences in the corpus\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Dataset Interface\n",
    "\n",
    "You can access (mostly) immutable references to the dataset through a simple interface provided through the `Dataset` class, which represents an iterable collection of sentences along with easy access to partitions of the data for training & testing. Review the reference below, then run and review the next few cells to make sure you understand the interface before moving on to the next step.\n",
    "\n",
    "```\n",
    "Dataset-only Attributes:\n",
    "    training_set - reference to a Subset object containing the samples for training\n",
    "    testing_set - reference to a Subset object containing the samples for testing\n",
    "\n",
    "Dataset & Subset Attributes:\n",
    "    sentences - a dictionary with an entry {sentence_key: Sentence()} for each sentence in the corpus\n",
    "    keys - an immutable ordered (not sorted) collection of the sentence_keys for the corpus\n",
    "    vocab - an immutable collection of the unique words in the corpus\n",
    "    tagset - an immutable collection of the unique tags in the corpus\n",
    "    X - returns an array of words grouped by sentences ((w11, w12, w13, ...), (w21, w22, w23, ...), ...)\n",
    "    Y - returns an array of tags grouped by sentences ((t11, t12, t13, ...), (t21, t22, t23, ...), ...)\n",
    "    N - returns the number of distinct samples (individual words or tags) in the dataset\n",
    "\n",
    "Methods:\n",
    "    stream() - returns an flat iterable over all (word, tag) pairs across all sentences in the corpus\n",
    "    __iter__() - returns an iterable over the data as (sentence_key, Sentence()) pairs\n",
    "    __len__() - returns the nubmer of sentences in the dataset\n",
    "```\n",
    "\n",
    "For example, consider a Subset, `subset`, of the sentences `{\"s0\": Sentence((\"See\", \"Spot\", \"run\"), (\"VERB\", \"NOUN\", \"VERB\")), \"s1\": Sentence((\"Spot\", \"ran\"), (\"NOUN\", \"VERB\"))}`. The subset will have these attributes:\n",
    "\n",
    "```\n",
    "subset.keys == {\"s1\", \"s0\"}  # unordered\n",
    "subset.vocab == {\"See\", \"run\", \"ran\", \"Spot\"}  # unordered\n",
    "subset.tagset == {\"VERB\", \"NOUN\"}  # unordered\n",
    "subset.X == ((\"Spot\", \"ran\"), (\"See\", \"Spot\", \"run\"))  # order matches .keys\n",
    "subset.Y == ((\"NOUN\", \"VERB\"), (\"VERB\", \"NOUN\", \"VERB\"))  # order matches .keys\n",
    "subset.N == 7  # there are a total of seven observations over all sentences\n",
    "len(subset) == 2  # because there are two sentences\n",
    "```\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "**Note:** The `Dataset` class is _convenient_, but it is **not** efficient. It is not suitable for huge datasets because it stores multiple redundant copies of the same data.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Sentences\n",
    "\n",
    "`Dataset.sentences` is a dictionary of all sentences in the training corpus, each keyed to a unique sentence identifier. Each `Sentence` is itself an object with two attributes: a tuple of the words in the sentence named `words` and a tuple of the tag corresponding to each word named `tags`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sentence: b100-39560\n",
      "words:\n",
      "\t('We', 'ran', 'east', 'for', 'about', 'half', 'a', 'mile', 'before', 'we', 'turned', 'back', 'to', 'the', 'road', ',', 'panting', 'from', 'the', 'effort', 'and', 'soaked', 'with', 'sweat', '.')\n",
      "tags:\n",
      "\t('PRON', 'VERB', 'NOUN', 'ADP', 'ADV', 'PRT', 'DET', 'NOUN', 'ADP', 'PRON', 'VERB', 'ADV', 'ADP', 'DET', 'NOUN', '.', 'VERB', 'ADP', 'DET', 'NOUN', 'CONJ', 'VERB', 'ADP', 'NOUN', '.')\n"
     ]
    }
   ],
   "source": [
    "key = 'b100-39560'\n",
    "print(\"Sentence: {}\".format(key))\n",
    "print(\"words:\\n\\t{!s}\".format(data.sentences[key].words))\n",
    "print(\"tags:\\n\\t{!s}\".format(data.sentences[key].tags))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\">\n",
    "**Note:** The underlying iterable sequence is **unordered** over the sentences in the corpus; it is not guaranteed to return the sentences in a consistent order between calls. Use `Dataset.stream()`, `Dataset.keys`, `Dataset.X`, or `Dataset.Y` attributes if you need ordered access to the data.\n",
    "</div>\n",
    "\n",
    "#### Counting Unique Elements\n",
    "\n",
    "You can access the list of unique words (the dataset vocabulary) via `Dataset.vocab` and the unique list of tags via `Dataset.tagset`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are a total of 1161192 samples of 56057 unique words in the corpus.\n",
      "There are 928458 samples of 50536 unique words in the training set.\n",
      "There are 232734 samples of 25112 unique words in the testing set.\n",
      "There are 5521 words in the test set that are missing in the training set.\n"
     ]
    }
   ],
   "source": [
    "print(\"There are a total of {} samples of {} unique words in the corpus.\"\n",
    "      .format(data.N, len(data.vocab)))\n",
    "print(\"There are {} samples of {} unique words in the training set.\"\n",
    "      .format(data.training_set.N, len(data.training_set.vocab)))\n",
    "print(\"There are {} samples of {} unique words in the testing set.\"\n",
    "      .format(data.testing_set.N, len(data.testing_set.vocab)))\n",
    "print(\"There are {} words in the test set that are missing in the training set.\"\n",
    "      .format(len(data.testing_set.vocab - data.training_set.vocab)))\n",
    "\n",
    "assert data.N == data.training_set.N + data.testing_set.N, \\\n",
    "       \"The number of training + test samples should sum to the total number of samples\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Accessing word and tag Sequences\n",
    "The `Dataset.X` and `Dataset.Y` attributes provide access to ordered collections of matching word and tag sequences for each sentence in the dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sentence 1: ('Mr.', 'Podger', 'had', 'thanked', 'him', 'gravely', ',', 'and', 'now', 'he', 'made', 'use', 'of', 'the', 'advice', '.')\n",
      "\n",
      "Labels 1: ('NOUN', 'NOUN', 'VERB', 'VERB', 'PRON', 'ADV', '.', 'CONJ', 'ADV', 'PRON', 'VERB', 'NOUN', 'ADP', 'DET', 'NOUN', '.')\n",
      "\n",
      "Sentence 2: ('But', 'there', 'seemed', 'to', 'be', 'some', 'difference', 'of', 'opinion', 'as', 'to', 'how', 'far', 'the', 'board', 'should', 'go', ',', 'and', 'whose', 'advice', 'it', 'should', 'follow', '.')\n",
      "\n",
      "Labels 2: ('CONJ', 'PRT', 'VERB', 'PRT', 'VERB', 'DET', 'NOUN', 'ADP', 'NOUN', 'ADP', 'ADP', 'ADV', 'ADV', 'DET', 'NOUN', 'VERB', 'VERB', '.', 'CONJ', 'DET', 'NOUN', 'PRON', 'VERB', 'VERB', '.')\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# accessing words with Dataset.X and tags with Dataset.Y \n",
    "for i in range(2):    \n",
    "    print(\"Sentence {}:\".format(i + 1), data.X[i])\n",
    "    print()\n",
    "    print(\"Labels {}:\".format(i + 1), data.Y[i])\n",
    "    print()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Accessing (word, tag) Samples\n",
    "The `Dataset.stream()` method returns an iterator that chains together every pair of (word, tag) entries across all sentences in the entire corpus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Stream (word, tag) pairs:\n",
      "\n",
      "\t ('Mr.', 'NOUN')\n",
      "\t ('Podger', 'NOUN')\n",
      "\t ('had', 'VERB')\n",
      "\t ('thanked', 'VERB')\n",
      "\t ('him', 'PRON')\n",
      "\t ('gravely', 'ADV')\n",
      "\t (',', '.')\n"
     ]
    }
   ],
   "source": [
    "# use Dataset.stream() (word, tag) samples for the entire corpus\n",
    "print(\"\\nStream (word, tag) pairs:\\n\")\n",
    "for i, pair in enumerate(data.stream()):\n",
    "    print(\"\\t\", pair)\n",
    "    if i > 5: break"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "For both our baseline tagger and the HMM model we'll build, we need to estimate the frequency of tags & words from the frequency counts of observations in the training corpus. In the next several cells you will complete functions to compute the counts of several sets of counts. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 2: Build a Most Frequent Class tagger\n",
    "---\n",
    "\n",
    "Perhaps the simplest tagger (and a good baseline for tagger performance) is to simply choose the tag most frequently assigned to each word. This \"most frequent class\" tagger inspects each observed word in the sequence and assigns it the label that was most often assigned to that word in the corpus."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Pair Counts\n",
    "\n",
    "Complete the function below that computes the joint frequency counts for two input sequences."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 12 unique POS which are:\n",
      "['VERB', 'NOUN', 'ADP', 'PRON', 'CONJ', 'ADJ', '.', 'DET', 'PRT', 'X', 'NUM', 'ADV']\n"
     ]
    }
   ],
   "source": [
    "print('there are', len(list(data.training_set.tagset)), 'unique POS which are:')\n",
    "print(list(data.training_set.tagset))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 50536 unique words in the train set\n"
     ]
    }
   ],
   "source": [
    "print('there are', len(list(data.training_set.vocab)), 'unique words in the train set') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your emission counts look good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def pair_counts(sequences_A, sequences_B):\n",
    "    \"\"\"Return a dictionary keyed to each unique value in the first sequence list\n",
    "    that counts the number of occurrences of the corresponding value from the\n",
    "    second sequences list.\n",
    "    \n",
    "    For example, if sequences_A is tags and sequences_B is the corresponding\n",
    "    words, then if 1244 sequences contain the word \"time\" tagged as a NOUN, then\n",
    "    you should return a dictionary such that pair_counts[NOUN][time] == 1244\n",
    "    \"\"\"\n",
    "    \n",
    "    emission_counts = {}\n",
    "\n",
    "    for sequence_A, sequence_B in zip(sequences_A, sequences_B):\n",
    "        \n",
    "        for a, b in zip(sequence_A, sequence_B):\n",
    "            \n",
    "            if a not in emission_counts.keys():    # Sequence A defines the keys of emission_counts \n",
    "                emission_counts[a] = {}            # emission_counts is a dictionary with values themselves as dictionary\n",
    "            \n",
    "            if b in emission_counts[a].keys():     # Sequence B defines the keys of emission_counts.values (dictionary)\n",
    "                emission_counts[a][b]+=1\n",
    "            else:\n",
    "                emission_counts[a][b]=1\n",
    "    \n",
    "    return emission_counts\n",
    "\n",
    "\n",
    "# Calculate C(t_i, w_i)\n",
    "emission_counts = pair_counts(list(data.training_set.Y), list(data.training_set.X)) # tags sequence x corresponding words sequence, by sentence in train set\n",
    "\n",
    "assert len(emission_counts) == 12, \\\n",
    "       \"Uh oh. There should be 12 tags in your dictionary.\"\n",
    "assert max(emission_counts[\"NOUN\"], key=emission_counts[\"NOUN\"].get) == 'time', \\\n",
    "       \"Hmmm...'time' is expected to be the most common NOUN.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your emission counts look good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['time'] 1275\n"
     ]
    }
   ],
   "source": [
    "max_value = max(emission_counts['NOUN'].values())  # maximum value\n",
    "max_keys = [k for k, v in emission_counts['NOUN'].items() if v == max_value] # getting all keys containing the `maximum`\n",
    "print(max_keys, max_value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Most Frequent Class Tagger\n",
    "\n",
    "Use the `pair_counts()` function and the training dataset to find the most frequent class label for each word in the training data, and populate the `mfc_table` below. The table keys should be words, and the values should be the appropriate tag string.\n",
    "\n",
    "The `MFCTagger` class is provided to mock the interface of Pomegranite HMM models so that they can be used interchangeably."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your MFC tagger has all the correct words!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a lookup table mfc_table where mfc_table[word] contains the tag label most frequently assigned to that word\n",
    "from collections import namedtuple\n",
    "\n",
    "FakeState = namedtuple(\"FakeState\", \"name\")\n",
    "\n",
    "class MFCTagger:\n",
    "    # NOTE: You should not need to modify this class or any of its methods\n",
    "    missing = FakeState(name=\"<MISSING>\")\n",
    "    \n",
    "    def __init__(self, table):\n",
    "        self.table = defaultdict(lambda: MFCTagger.missing)\n",
    "        self.table.update({word: FakeState(name=tag) for word, tag in table.items()})\n",
    "        \n",
    "    def viterbi(self, seq):\n",
    "        \"\"\"This method simplifies predictions by matching the Pomegranate viterbi() interface\"\"\"\n",
    "        return 0., list(enumerate([\"<start>\"] + [self.table[w] for w in seq] + [\"<end>\"]))\n",
    "\n",
    "\n",
    "# TODO: calculate the frequency of each tag being assigned to each word (hint: similar, but not\n",
    "# the same as the emission probabilities) and use it to fill the mfc_table\n",
    "\n",
    "word_counts = pair_counts(list(data.training_set.X), list(data.training_set.Y))\n",
    "\n",
    "mfc_table = {}\n",
    "for word in list(data.training_set.vocab):\n",
    "    mfc_table[word] = max(word_counts[word], key=word_counts[word].get)\n",
    "\n",
    "# DO NOT MODIFY BELOW THIS LINE\n",
    "mfc_model = MFCTagger(mfc_table) # Create a Most Frequent Class tagger instance\n",
    "\n",
    "assert len(mfc_table) == len(data.training_set.vocab), \"\"\n",
    "assert all(k in data.training_set.vocab for k in mfc_table.keys()), \"\"\n",
    "assert sum(int(k not in mfc_table) for k in data.testing_set.vocab) == 5521, \"\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your MFC tagger has all the correct words!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "these is the most used POS for a sample of words in the train set\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'vaults': 'NOUN',\n",
       " 'fizzled': 'VERB',\n",
       " 'flight': 'NOUN',\n",
       " 'perceives': 'VERB',\n",
       " 'Madeleine': 'NOUN',\n",
       " 'Cautiously': 'ADV',\n",
       " 'Alors': 'X',\n",
       " 'autumn-touched': 'ADJ',\n",
       " 'half-acre': 'NOUN',\n",
       " 'highlight': 'NOUN'}"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('these is the most used POS for a sample of words in the train set')\n",
    "{k: mfc_table[k] for k in list(mfc_table)[:10]}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Making Predictions with a Model\n",
    "The helper functions provided below interface with Pomegranate network models & the mocked MFCTagger to take advantage of the [missing value](http://pomegranate.readthedocs.io/en/latest/nan.html) functionality in Pomegranate through a simple sequence decoding function. Run these functions, then run the next cell to see some of the predictions made by the MFC tagger."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_unknown(sequence):\n",
    "    \"\"\"Return a copy of the input sequence where each unknown word is replaced\n",
    "    by the literal string value 'nan'. Pomegranate will ignore these values\n",
    "    during computation.\n",
    "    \"\"\"\n",
    "    return [w if w in data.training_set.vocab else 'nan' for w in sequence]\n",
    "\n",
    "def simplify_decoding(X, model):\n",
    "    \"\"\"X should be a 1-D sequence of observations for the model to predict\"\"\"\n",
    "    _, state_path = model.viterbi(replace_unknown(X))\n",
    "    return [state[1].name for state in state_path[1:-1]]  # do not show the start/end state predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example Decoding Sequences with MFC Tagger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sentence Key: b100-28144\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['CONJ', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'CONJ', 'NOUN', 'NUM', '.', '.', 'NOUN', '.', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('CONJ', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'CONJ', 'NOUN', 'NUM', '.', '.', 'NOUN', '.', '.')\n",
      "\n",
      "\n",
      "Sentence Key: b100-23146\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['PRON', 'VERB', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', 'NOUN', 'VERB', 'VERB', '.', 'ADP', 'VERB', 'DET', 'NOUN', 'ADP', 'NOUN', 'ADP', 'DET', 'NOUN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('PRON', 'VERB', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', 'NOUN', 'VERB', 'VERB', '.', 'ADP', 'VERB', 'DET', 'NOUN', 'ADP', 'NOUN', 'ADP', 'DET', 'NOUN', '.')\n",
      "\n",
      "\n",
      "Sentence Key: b100-35462\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['DET', 'ADJ', 'NOUN', 'VERB', 'VERB', 'VERB', 'ADP', 'DET', 'ADJ', 'ADJ', 'NOUN', 'ADP', 'DET', 'ADJ', 'NOUN', '.', 'ADP', 'ADJ', 'NOUN', '.', 'CONJ', 'ADP', 'DET', '<MISSING>', 'ADP', 'ADJ', 'ADJ', '.', 'ADJ', '.', 'CONJ', 'ADJ', 'NOUN', 'ADP', 'ADV', 'NOUN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('DET', 'ADJ', 'NOUN', 'VERB', 'VERB', 'VERB', 'ADP', 'DET', 'ADJ', 'ADJ', 'NOUN', 'ADP', 'DET', 'ADJ', 'NOUN', '.', 'ADP', 'ADJ', 'NOUN', '.', 'CONJ', 'ADP', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', '.', 'ADJ', '.', 'CONJ', 'ADJ', 'NOUN', 'ADP', 'ADJ', 'NOUN', '.')\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for key in data.testing_set.keys[:3]:\n",
    "    print(\"Sentence Key: {}\\n\".format(key))\n",
    "    print(\"Predicted labels:\\n-----------------\")\n",
    "    print(simplify_decoding(data.sentences[key].words, mfc_model))\n",
    "    print()\n",
    "    print(\"Actual labels:\\n--------------\")\n",
    "    print(data.sentences[key].tags)\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluating Model Accuracy\n",
    "\n",
    "The function below will evaluate the accuracy of the MFC tagger on the collection of all sentences from a text corpus. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "def accuracy(X, Y, model):\n",
    "    \"\"\"Calculate the prediction accuracy by using the model to decode each sequence\n",
    "    in the input X and comparing the prediction with the true labels in Y.\n",
    "    \n",
    "    The X should be an array whose first dimension is the number of sentences to test,\n",
    "    and each element of the array should be an iterable of the words in the sequence.\n",
    "    The arrays X and Y should have the exact same shape.\n",
    "    \n",
    "    X = [(\"See\", \"Spot\", \"run\"), (\"Run\", \"Spot\", \"run\", \"fast\"), ...]\n",
    "    Y = [(), (), ...]\n",
    "    \"\"\"\n",
    "    correct = total_predictions = 0\n",
    "    for observations, actual_tags in zip(X, Y):\n",
    "        \n",
    "        # The model.viterbi call in simplify_decoding will return None if the HMM\n",
    "        # raises an error (for example, if a test sentence contains a word that\n",
    "        # is out of vocabulary for the training set). Any exception counts the\n",
    "        # full sentence as an error (which makes this a conservative estimate).\n",
    "        try:\n",
    "            most_likely_tags = simplify_decoding(observations, model)\n",
    "            correct += sum(p == t for p, t in zip(most_likely_tags, actual_tags))\n",
    "        except:\n",
    "            pass\n",
    "        total_predictions += len(observations)\n",
    "    return correct / total_predictions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Evaluate the accuracy of the MFC tagger\n",
    "Run the next cell to evaluate the accuracy of the tagger on the training and test corpus."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy mfc_model: 95.72%\n",
      "testing accuracy mfc_model: 93.01%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your MFC tagger accuracy looks correct!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mfc_training_acc = accuracy(data.training_set.X, data.training_set.Y, mfc_model)\n",
    "print(\"training accuracy mfc_model: {:.2f}%\".format(100 * mfc_training_acc))\n",
    "\n",
    "mfc_testing_acc = accuracy(data.testing_set.X, data.testing_set.Y, mfc_model)\n",
    "print(\"testing accuracy mfc_model: {:.2f}%\".format(100 * mfc_testing_acc))\n",
    "\n",
    "assert mfc_training_acc >= 0.955, \"Uh oh. Your MFC accuracy on the training set doesn't look right.\"\n",
    "assert mfc_testing_acc >= 0.925, \"Uh oh. Your MFC accuracy on the testing set doesn't look right.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your MFC tagger accuracy looks correct!</div>')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 3: Build an HMM tagger\n",
    "---\n",
    "The HMM tagger has one hidden state for each possible tag, and parameterized by two distributions: the emission probabilties giving the conditional probability of observing a given **word** from each hidden state, and the transition probabilities giving the conditional probability of moving between **tags** during the sequence.\n",
    "\n",
    "We will also estimate the starting probability distribution (the probability of each **tag** being the first tag in a sequence), and the terminal probability distribution (the probability of each **tag** being the last tag in a sequence).\n",
    "\n",
    "The maximum likelihood estimate of these distributions can be calculated from the frequency counts as described in the following sections where you'll implement functions to count the frequencies, and finally build the model. The HMM model will make predictions according to the formula:\n",
    "\n",
    "$$t_i^n = \\underset{t_i^n}{\\mathrm{argmax}} \\prod_{i=1}^n P(w_i|t_i) P(t_i|t_{i-1})$$\n",
    "\n",
    "Refer to Speech & Language Processing [Chapter 10](https://web.stanford.edu/~jurafsky/slp3/10.pdf) for more information."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Unigram Counts\n",
    "\n",
    "Complete the function below to estimate the co-occurrence frequency of each symbol over all of the input sequences. The unigram probabilities in our HMM model are estimated from the formula below, where N is the total number of samples in the input. (You only need to compute the counts for now.)\n",
    "\n",
    "$$P(tag_1) = \\frac{C(tag_1)}{N}$$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your tag unigrams look good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def unigram_counts(sequences):\n",
    "    \"\"\"Return a dictionary keyed to each unique value in the input sequence list that\n",
    "    counts the number of occurrences of the value in the sequences list. The sequences\n",
    "    collection should be a 2-dimensional array.\n",
    "    \n",
    "    For example, if the tag NOUN appears 275558 times over all the input sequences,\n",
    "    then you should return a dictionary such that your_unigram_counts[NOUN] == 275558.\n",
    "    \"\"\"\n",
    "    tag_unigrams = {}\n",
    "    \n",
    "    for sequence in sequences:\n",
    "        \n",
    "        for tag in sequence:\n",
    "            \n",
    "            if tag in tag_unigrams.keys():\n",
    "                tag_unigrams[tag]+=1\n",
    "            else:\n",
    "                tag_unigrams[tag]=1\n",
    "                \n",
    "    return tag_unigrams\n",
    "\n",
    "# TODO: call unigram_counts with a list of tag sequences from the training set\n",
    "tag_unigrams = unigram_counts(list(data.training_set.Y))\n",
    "\n",
    "assert set(tag_unigrams.keys()) == data.training_set.tagset, \\\n",
    "       \"Uh oh. It looks like your tag counts doesn't include all the tags!\"\n",
    "assert min(tag_unigrams, key=tag_unigrams.get) == 'X', \\\n",
    "       \"Hmmm...'X' is expected to be the least common class\"\n",
    "assert max(tag_unigrams, key=tag_unigrams.get) == 'NOUN', \\\n",
    "       \"Hmmm...'NOUN' is expected to be the most common class\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your tag unigrams look good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frequency of tags in train set:\n",
      "{'.': 117757,\n",
      " 'ADJ': 66754,\n",
      " 'ADP': 115808,\n",
      " 'ADV': 44877,\n",
      " 'CONJ': 30537,\n",
      " 'DET': 109671,\n",
      " 'NOUN': 220632,\n",
      " 'NUM': 11878,\n",
      " 'PRON': 39383,\n",
      " 'PRT': 23906,\n",
      " 'VERB': 146161,\n",
      " 'X': 1094}\n"
     ]
    }
   ],
   "source": [
    "import pprint\n",
    "pp = pprint.PrettyPrinter(indent=1)\n",
    "print('frequency of tags in train set:')\n",
    "pp.pprint(tag_unigrams)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Bigram Counts\n",
    "\n",
    "Complete the function below to estimate the co-occurrence frequency of each pair of symbols in each of the input sequences. These counts are used in the HMM model to estimate the bigram probability of two tags from the frequency counts according to the formula: $$P(tag_2|tag_1) = \\frac{C(tag_2|tag_1)}{C(tag_2)}$$\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your tag bigrams look good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def bigram_counts(sequences):\n",
    "    \"\"\"Return a dictionary keyed to each unique PAIR of values in the input sequences\n",
    "    list that counts the number of occurrences of pair in the sequences list. The input\n",
    "    should be a 2-dimensional array.\n",
    "    \n",
    "    For example, if the pair of tags (NOUN, VERB) appear 61582 times, then you should\n",
    "    return a dictionary such that your_bigram_counts[(NOUN, VERB)] == 61582\n",
    "    \"\"\"\n",
    "    tag_bigrams = {}\n",
    "\n",
    "    for sequence in sequences:\n",
    "        \n",
    "        l = len(sequence)\n",
    "        \n",
    "        for index in range(l-1):\n",
    "            \n",
    "            bigram = sequence[index:index+2]\n",
    "            \n",
    "            if bigram in tag_bigrams.keys():\n",
    "                tag_bigrams[bigram] += 1\n",
    "            else:\n",
    "                tag_bigrams[bigram] = 1\n",
    "                \n",
    "    return tag_bigrams     \n",
    "\n",
    "# TODO: call bigram_counts with a list of tag sequences from the training set\n",
    "tag_bigrams = bigram_counts(list(data.training_set.Y))\n",
    "\n",
    "assert len(tag_bigrams) == 144, \\\n",
    "       \"Uh oh. There should be 144 pairs of bigrams (12 tags x 12 tags)\"\n",
    "assert min(tag_bigrams, key=tag_bigrams.get) in [('X', 'NUM'), ('PRON', 'X')], \\\n",
    "       \"Hmmm...The least common bigram should be one of ('X', 'NUM') or ('PRON', 'X').\"\n",
    "assert max(tag_bigrams, key=tag_bigrams.get) in [('DET', 'NOUN')], \\\n",
    "       \"Hmmm...('DET', 'NOUN') is expected to be the most common bigram.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your tag bigrams look good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frequency of tags in train set:\n",
      "{('.', '.'): 12588,\n",
      " ('.', 'ADJ'): 3334,\n",
      " ('.', 'ADP'): 7595,\n",
      " ('.', 'ADV'): 5124,\n",
      " ('.', 'CONJ'): 8174,\n",
      " ('.', 'DET'): 8008,\n",
      " ('.', 'NOUN'): 9782,\n",
      " ('.', 'NUM'): 1412,\n",
      " ('.', 'PRON'): 5448,\n",
      " ('.', 'PRT'): 2168,\n",
      " ('.', 'VERB'): 9041,\n",
      " ('.', 'X'): 147,\n",
      " ('ADJ', '.'): 6666,\n",
      " ('ADJ', 'ADJ'): 3758,\n",
      " ('ADJ', 'ADP'): 5895,\n",
      " ('ADJ', 'ADV'): 645,\n",
      " ('ADJ', 'CONJ'): 2500,\n",
      " ('ADJ', 'DET'): 386,\n",
      " ('ADJ', 'NOUN'): 43664,\n",
      " ('ADJ', 'NUM'): 467,\n",
      " ('ADJ', 'PRON'): 249,\n",
      " ('ADJ', 'PRT'): 1301,\n",
      " ('ADJ', 'VERB'): 1167,\n",
      " ('ADJ', 'X'): 31,\n",
      " ('ADP', '.'): 1099,\n",
      " ('ADP', 'ADJ'): 9533,\n",
      " ('ADP', 'ADP'): 2347,\n",
      " ('ADP', 'ADV'): 1805,\n",
      " ('ADP', 'CONJ'): 217,\n",
      " ('ADP', 'DET'): 52841,\n",
      " ('ADP', 'NOUN'): 29965,\n",
      " ('ADP', 'NUM'): 3467,\n",
      " ('ADP', 'PRON'): 8109,\n",
      " ('ADP', 'PRT'): 1675,\n",
      " ('ADP', 'VERB'): 4690,\n",
      " ('ADP', 'X'): 53,\n",
      " ('ADV', '.'): 7577,\n",
      " ('ADV', 'ADJ'): 6143,\n",
      " ('ADV', 'ADP'): 6352,\n",
      " ('ADV', 'ADV'): 4336,\n",
      " ('ADV', 'CONJ'): 789,\n",
      " ('ADV', 'DET'): 3309,\n",
      " ('ADV', 'NOUN'): 1478,\n",
      " ('ADV', 'NUM'): 597,\n",
      " ('ADV', 'PRON'): 2136,\n",
      " ('ADV', 'PRT'): 1305,\n",
      " ('ADV', 'VERB'): 10835,\n",
      " ('ADV', 'X'): 4,\n",
      " ('CONJ', '.'): 612,\n",
      " ('CONJ', 'ADJ'): 3372,\n",
      " ('CONJ', 'ADP'): 2222,\n",
      " ('CONJ', 'ADV'): 2759,\n",
      " ('CONJ', 'CONJ'): 9,\n",
      " ('CONJ', 'DET'): 4636,\n",
      " ('CONJ', 'NOUN'): 7502,\n",
      " ('CONJ', 'NUM'): 575,\n",
      " ('CONJ', 'PRON'): 2058,\n",
      " ('CONJ', 'PRT'): 760,\n",
      " ('CONJ', 'VERB'): 6012,\n",
      " ('CONJ', 'X'): 18,\n",
      " ('DET', '.'): 1385,\n",
      " ('DET', 'ADJ'): 26236,\n",
      " ('DET', 'ADP'): 978,\n",
      " ('DET', 'ADV'): 1937,\n",
      " ('DET', 'CONJ'): 70,\n",
      " ('DET', 'DET'): 662,\n",
      " ('DET', 'NOUN'): 68785,\n",
      " ('DET', 'NUM'): 1073,\n",
      " ('DET', 'PRON'): 1093,\n",
      " ('DET', 'PRT'): 220,\n",
      " ('DET', 'VERB'): 7062,\n",
      " ('DET', 'X'): 156,\n",
      " ('NOUN', '.'): 62639,\n",
      " ('NOUN', 'ADJ'): 2839,\n",
      " ('NOUN', 'ADP'): 53884,\n",
      " ('NOUN', 'ADV'): 5804,\n",
      " ('NOUN', 'CONJ'): 13185,\n",
      " ('NOUN', 'DET'): 3425,\n",
      " ('NOUN', 'NOUN'): 32990,\n",
      " ('NOUN', 'NUM'): 1783,\n",
      " ('NOUN', 'PRON'): 4369,\n",
      " ('NOUN', 'PRT'): 3946,\n",
      " ('NOUN', 'VERB'): 34972,\n",
      " ('NOUN', 'X'): 74,\n",
      " ('NUM', '.'): 3210,\n",
      " ('NUM', 'ADJ'): 705,\n",
      " ('NUM', 'ADP'): 1559,\n",
      " ('NUM', 'ADV'): 234,\n",
      " ('NUM', 'CONJ'): 442,\n",
      " ('NUM', 'DET'): 156,\n",
      " ('NUM', 'NOUN'): 4524,\n",
      " ('NUM', 'NUM'): 267,\n",
      " ('NUM', 'PRON'): 109,\n",
      " ('NUM', 'PRT'): 69,\n",
      " ('NUM', 'VERB'): 537,\n",
      " ('NUM', 'X'): 3,\n",
      " ('PRON', '.'): 4078,\n",
      " ('PRON', 'ADJ'): 359,\n",
      " ('PRON', 'ADP'): 2216,\n",
      " ('PRON', 'ADV'): 2099,\n",
      " ('PRON', 'CONJ'): 455,\n",
      " ('PRON', 'DET'): 695,\n",
      " ('PRON', 'NOUN'): 340,\n",
      " ('PRON', 'NUM'): 39,\n",
      " ('PRON', 'PRON'): 318,\n",
      " ('PRON', 'PRT'): 919,\n",
      " ('PRON', 'VERB'): 27860,\n",
      " ('PRON', 'X'): 1,\n",
      " ('PRT', '.'): 1794,\n",
      " ('PRT', 'ADJ'): 467,\n",
      " ('PRT', 'ADP'): 2189,\n",
      " ('PRT', 'ADV'): 866,\n",
      " ('PRT', 'CONJ'): 285,\n",
      " ('PRT', 'DET'): 2021,\n",
      " ('PRT', 'NOUN'): 845,\n",
      " ('PRT', 'NUM'): 117,\n",
      " ('PRT', 'PRON'): 166,\n",
      " ('PRT', 'PRT'): 261,\n",
      " ('PRT', 'VERB'): 14886,\n",
      " ('PRT', 'X'): 2,\n",
      " ('VERB', '.'): 11699,\n",
      " ('VERB', 'ADJ'): 8423,\n",
      " ('VERB', 'ADP'): 24927,\n",
      " ('VERB', 'ADV'): 15076,\n",
      " ('VERB', 'CONJ'): 2105,\n",
      " ('VERB', 'DET'): 23764,\n",
      " ('VERB', 'NOUN'): 14230,\n",
      " ('VERB', 'NUM'): 1320,\n",
      " ('VERB', 'PRON'): 8001,\n",
      " ('VERB', 'PRT'): 9556,\n",
      " ('VERB', 'VERB'): 26957,\n",
      " ('VERB', 'X'): 28,\n",
      " ('X', '.'): 303,\n",
      " ('X', 'ADJ'): 3,\n",
      " ('X', 'ADP'): 61,\n",
      " ('X', 'ADV'): 7,\n",
      " ('X', 'CONJ'): 24,\n",
      " ('X', 'DET'): 5,\n",
      " ('X', 'NOUN'): 58,\n",
      " ('X', 'NUM'): 1,\n",
      " ('X', 'PRON'): 9,\n",
      " ('X', 'PRT'): 8,\n",
      " ('X', 'VERB'): 62,\n",
      " ('X', 'X'): 552}\n"
     ]
    }
   ],
   "source": [
    "pp = pprint.PrettyPrinter(indent=1)\n",
    "print('frequency of tags in train set:')\n",
    "pp.pprint(tag_bigrams)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Sequence Starting Counts\n",
    "Complete the code below to estimate the bigram probabilities of a sequence starting with each tag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your starting tag counts look good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def starting_counts(sequences):\n",
    "    \"\"\"Return a dictionary keyed to each unique value in the input sequences list\n",
    "    that counts the number of occurrences where that value is at the beginning of\n",
    "    a sequence.\n",
    "    \n",
    "    For example, if 8093 sequences start with NOUN, then you should return a\n",
    "    dictionary such that your_starting_counts[NOUN] == 8093\n",
    "    \"\"\"\n",
    "    tag_starts = {}\n",
    "    \n",
    "    for sequence in sequences:\n",
    "        if sequence[0] in tag_starts.keys():\n",
    "            tag_starts[sequence[0]]+=1\n",
    "        else:\n",
    "            tag_starts[sequence[0]]=1\n",
    "\n",
    "    return tag_starts\n",
    "\n",
    "# TODO: Calculate the count of each tag starting a sequence\n",
    "tag_starts = starting_counts(list(data.training_set.Y))\n",
    "\n",
    "assert len(tag_starts) == 12, \"Uh oh. There should be 12 tags in your dictionary.\"\n",
    "assert min(tag_starts, key=tag_starts.get) == 'X', \"Hmmm...'X' is expected to be the least common starting bigram.\"\n",
    "assert max(tag_starts, key=tag_starts.get) == 'DET', \"Hmmm...'DET' is expected to be the most common starting bigram.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your starting tag counts look good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frequency of starting tags in train set:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'ADV': 4185,\n",
       " 'ADP': 5583,\n",
       " 'ADJ': 1582,\n",
       " 'PRT': 1718,\n",
       " 'DET': 9763,\n",
       " 'PRON': 7318,\n",
       " 'NOUN': 6469,\n",
       " 'CONJ': 2282,\n",
       " '.': 4107,\n",
       " 'NUM': 760,\n",
       " 'VERB': 2080,\n",
       " 'X': 25}"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('frequency of starting tags in train set:')\n",
    "tag_starts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Sequence Ending Counts\n",
    "Complete the function below to estimate the bigram probabilities of a sequence ending with each tag."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your ending tag counts look good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def ending_counts(sequences):\n",
    "    \"\"\"Return a dictionary keyed to each unique value in the input sequences list\n",
    "    that counts the number of occurrences where that value is at the end of\n",
    "    a sequence.\n",
    "    \n",
    "    For example, if 18 sequences end with DET, then you should return a\n",
    "    dictionary such that your_ending_counts[DET] == 18\n",
    "    \"\"\"\n",
    "    tag_ends = {}\n",
    "    \n",
    "    for sequence in sequences:\n",
    "        \n",
    "        if sequence[-1] in tag_ends.keys():\n",
    "            tag_ends[sequence[-1]]+=1\n",
    "        else:\n",
    "            tag_ends[sequence[-1]]=1\n",
    "    \n",
    "    return tag_ends\n",
    "\n",
    "# TODO: Calculate the count of each tag ending a sequence\n",
    "tag_ends = ending_counts(list(data.training_set.Y))\n",
    "\n",
    "assert len(tag_ends) == 12, \"Uh oh. There should be 12 tags in your dictionary.\"\n",
    "assert min(tag_ends, key=tag_ends.get) in ['X', 'CONJ'], \"Hmmm...'X' or 'CONJ' should be the least common ending bigram.\"\n",
    "assert max(tag_ends, key=tag_ends.get) == '.', \"Hmmm...'.' is expected to be the most common ending bigram.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your ending tag counts look good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "frequency of ending tags in train set:\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'.': 44936,\n",
       " 'NOUN': 722,\n",
       " 'NUM': 63,\n",
       " 'VERB': 75,\n",
       " 'ADJ': 25,\n",
       " 'ADV': 16,\n",
       " 'ADP': 7,\n",
       " 'DET': 14,\n",
       " 'CONJ': 2,\n",
       " 'PRON': 4,\n",
       " 'PRT': 7,\n",
       " 'X': 1}"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print('frequency of ending tags in train set:')\n",
    "tag_ends"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### IMPLEMENTATION: Basic HMM Tagger\n",
    "Use the tag unigrams and bigrams calculated above to construct a hidden Markov tagger.\n",
    "\n",
    "- Add one state per tag\n",
    "    - The emission distribution at each state should be estimated with the formula: $P(w|t) = \\frac{C(t, w)}{C(t)}$\n",
    "- Add an edge from the starting state `basic_model.start` to each tag\n",
    "    - The transition probability should be estimated with the formula: $P(t|start) = \\frac{C(start, t)}{C(start)}$\n",
    "- Add an edge from each tag to the end state `basic_model.end`\n",
    "    - The transition probability should be estimated with the formula: $P(end|t) = \\frac{C(t, end)}{C(t)}$\n",
    "- Add an edge between _every_ pair of tags\n",
    "    - The transition probability should be estimated with the formula: $P(t_2|t_1) = \\frac{C(t_1, t_2)}{C(t_1)}$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your HMM network topology looks good!</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "basic_model = HiddenMarkovModel(name=\"base-hmm-tagger\")\n",
    "import pandas as pd\n",
    "# TODO: create states with emission probability distributions P(word | tag) and add to the model\n",
    "# (Hint: you may need to loop & create/add new states)\n",
    "\n",
    "states = {}\n",
    "\n",
    "for tag in list(data.tagset):\n",
    "    \n",
    "    state_emissions = DiscreteDistribution( {word: occurence / tag_unigrams[tag] for word, \n",
    "                                             occurence in emission_counts[tag].items()} )\n",
    "    \n",
    "    states[tag] = State(state_emissions, name = tag)\n",
    "    \n",
    "    # transition edge from start to each tag\n",
    "    # For the start tag, how likely is it to be tag_i ? distribution of probabilities for <start> over tags which adds up to 1.\n",
    "    basic_model.add_transition(basic_model.start, states[tag], tag_starts[tag] / len(data.training_set))\n",
    "    \n",
    "    # transition edge from a tag to the end\n",
    "    # for a tag_i, how likely it is at the end of the sentence or not\n",
    "    basic_model.add_transition(states[tag], basic_model.end, tag_ends[tag] / tag_ends[tag])\n",
    "    \n",
    "basic_model.add_states(*states.values())\n",
    "    \n",
    "# TODO: add edges between states for the observed transition frequencies P(tag_i | tag_i-1)\n",
    "# (Hint: you may need to loop & add transitions\n",
    "\n",
    "import itertools\n",
    "\n",
    "for tag_1, tag_2 in itertools.product(data.training_set.tagset, data.training_set.tagset):\n",
    "\n",
    "    basic_model.add_transition(states[tag_1], states[tag_2], tag_bigrams[(tag_1, tag_2)] / tag_unigrams[tag_1])\n",
    "\n",
    "# NOTE: YOU SHOULD NOT NEED TO MODIFY ANYTHING BELOW THIS LINE\n",
    "# finalize the model\n",
    "basic_model.bake()\n",
    "\n",
    "assert all(tag in set(s.name for s in basic_model.states) for tag in data.training_set.tagset), \\\n",
    "       \"Every state in your network should use the name of the associated tag, which must be one of the training set tags.\"\n",
    "assert basic_model.edge_count() == 168, \\\n",
    "       (\"Your network should have an edge from the start node to each state, one edge between every \" +\n",
    "        \"pair of tags (states), and an edge from each state to the end node.\")\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your HMM network topology looks good!</div>')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy basic hmm model: 97.54%\n",
      "testing accuracy basic hmm model: 95.94%\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div class=\"alert alert-block alert-success\">Your HMM tagger accuracy looks correct! Congratulations, you've finished the project.</div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hmm_training_acc = accuracy(data.training_set.X, data.training_set.Y, basic_model)\n",
    "print(\"training accuracy basic hmm model: {:.2f}%\".format(100 * hmm_training_acc))\n",
    "\n",
    "hmm_testing_acc = accuracy(data.testing_set.X, data.testing_set.Y, basic_model)\n",
    "print(\"testing accuracy basic hmm model: {:.2f}%\".format(100 * hmm_testing_acc))\n",
    "\n",
    "assert hmm_training_acc > 0.97, \"Uh oh. Your HMM accuracy on the training set doesn't look right.\"\n",
    "assert hmm_testing_acc > 0.955, \"Uh oh. Your HMM accuracy on the testing set doesn't look right.\"\n",
    "HTML('<div class=\"alert alert-block alert-success\">Your HMM tagger accuracy looks correct! Congratulations, you\\'ve finished the project.</div>')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- The performance of this model improves by a few percentage points compared to the base line represented by the simplest MFC tagger which simply chooses the tag most frequently assigned to each word."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Example Decoding Sequences with the HMM Tagger"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sentence Key: b100-28144\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['CONJ', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'CONJ', 'NOUN', 'NUM', '.', '.', 'NOUN', '.', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('CONJ', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'NOUN', 'NUM', '.', 'CONJ', 'NOUN', 'NUM', '.', '.', 'NOUN', '.', '.')\n",
      "\n",
      "\n",
      "Sentence Key: b100-23146\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['PRON', 'VERB', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', 'NOUN', 'VERB', 'VERB', '.', 'ADP', 'VERB', 'DET', 'NOUN', 'ADP', 'NOUN', 'ADP', 'DET', 'NOUN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('PRON', 'VERB', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', 'NOUN', 'VERB', 'VERB', '.', 'ADP', 'VERB', 'DET', 'NOUN', 'ADP', 'NOUN', 'ADP', 'DET', 'NOUN', '.')\n",
      "\n",
      "\n",
      "Sentence Key: b100-35462\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['DET', 'ADJ', 'NOUN', 'VERB', 'VERB', 'VERB', 'ADP', 'DET', 'ADJ', 'ADJ', 'NOUN', 'ADP', 'DET', 'ADJ', 'NOUN', '.', 'ADP', 'ADJ', 'NOUN', '.', 'CONJ', 'ADP', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', '.', 'ADJ', '.', 'CONJ', 'ADJ', 'NOUN', 'ADP', 'ADJ', 'NOUN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "('DET', 'ADJ', 'NOUN', 'VERB', 'VERB', 'VERB', 'ADP', 'DET', 'ADJ', 'ADJ', 'NOUN', 'ADP', 'DET', 'ADJ', 'NOUN', '.', 'ADP', 'ADJ', 'NOUN', '.', 'CONJ', 'ADP', 'DET', 'NOUN', 'ADP', 'ADJ', 'ADJ', '.', 'ADJ', '.', 'CONJ', 'ADJ', 'NOUN', 'ADP', 'ADJ', 'NOUN', '.')\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for key in data.testing_set.keys[:3]:\n",
    "    print(\"Sentence Key: {}\\n\".format(key))\n",
    "    print(\"Predicted labels:\\n-----------------\")\n",
    "    print(simplify_decoding(data.sentences[key].words, basic_model))\n",
    "    print()\n",
    "    print(\"Actual labels:\\n--------------\")\n",
    "    print(data.sentences[key].tags)\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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GDRua1teU65H50eZrR0dH8/vvv3PlyhXatGlD165dpfMuxFMwGo3s2bOHw4cPM3XqVFPNAyHKkATComJSShEVFcW8efOYMGECNWvWlA6MEKJEaMFTRkYG586d4/DhwyQkJBAUFETLli0JCQnBwcEBkGJM5YXWB0pOTmbr1q2cOHGCZs2a0bNnT9zc3ADZl0IUltFoZMOGDdy/f58xY8ZgY2NT1k0SlZsEwqLiUUoRHx/PnDlzeP7552nYsKF0WIQQxUophdFoJC0tjfPnz3PkyBGSkpKoXbs2rVq1ombNmtjb28u1pwJQSpGSksKePXs4dOgQDRs2pHfv3nh4eMga9EIUkl6v57vvvsPJyYmhQ4dKQUBRliQQFhVPRkYGX375Jd27d6dly5bSERVCFBstKLp48SKHDh0iOTmZunXr0qpVK/z9/SX4rcCUUqSnp3PgwAH27NlDnTp16NevH9WqVZN9LkQBaUvFzZ8/n6ZNm9KxY0c5f0RZkUBYVCz5+fl89dVXBAcH06tXL3laL4R4alra86VLlzh48CD3798nJCSEtm3bEhQUJNWFKxltPeI9e/awa9cuGjduTN++fXF1dZXjQIgCUEqRmprKzJkzefHFF6lTp46cO6IsSCAsKg6j0ciqVavIyspi1KhRWFlZlXWThBDlkHb/y8vL48qVK+zdu5e7d+9Ss2ZN2rVrR506dUxz26TzVnlpD0i2b9/OgQMHaNOmDT179pQq00IUgFKK27dv8/XXXzN16lRZVkmUBQmERcWglGL//v0cOXKEt956C1tb27JukhCinFFKodfriYqKYv/+/Vy8eJFq1arRoUMH6tevj6OjY1k3UZghbXTr119/5dSpU3Tp0oXOnTtjZ2cnHXshHkMpxfHjx9m1axeTJ0/Gzs6urJskKhcJhEX5p5QiMjKS77//nilTpkh6mhCiwLSiV4mJiRw9epRjx45hY2ND69atCQ8Px83NTaZYiALRCjVu2LCBGzduMHjwYMLCwrC2ti7rpglhtoxGI6tXr8ZgMDBs2DC53orSJIGwKP+Sk5P58ssvGTVqFMHBwRIECyGeSClFZmYmFy9eZO/evaSkpNC0aVPatGmDp6enTK0QRWY0Grl16xYrV65EKcXzzz9PYGCgdPCFeITc3FzmzJlD+/btpcipKE0SCIvyLT8/n3nz5tGkSRM6dOggF08hxCNpo7+3bt1i9+7dXL16lRo1atC5c2dq1aqFtbW1XENEsdHr9Zw9e5bVq1cTGBjIkCFDcHd3l2NMiP+hlCIxMZHZs2czceJEvLy85DwRpUECYVF+KaXYvHkziYmJjBw5UtaiE0L8gXYvS09P5+jRo+zbtw8rKys6duxI06ZNcXJyAqTolSgZ2lIxu3btYseOHfTo0YMuXbrIQxch/odSirNnz7Jt2zap9SJKiwTConxSShEREcHq1auZNm2aFLERQjxEKUV+fj63bt1i586d3Lx5kwYNGtCxY0f8/f3lwZkoVdqI18qVK7l//z4jRoygVq1aki4txAO01T9sbGwYOHCgnB+ipEkgLMqn5ORkZs6cybhx4wgICCjr5gghzIRWwff48ePs27cPe3t7OnXqRGhoqCxrI8qcwWDg0qVL/PzzzwQHBzNo0CAp8CjEA7Kyspg1axaDBw+mdu3acm6IkiSBsCh/9Ho9X3/9NQ0aNJB5wUII4L8Bxu3bt9m5cyfXrl2jQYMGdO3aFW9vbywtLeU6IcyGUoqcnBy2bdvGvn37GDhwIK1bt5YCbUL8/27fvs3SpUuZPn26ZPyJkiSBsChflFLs27ePS5cu8eqrr0p6oxCVlHaPysnJ4eTJk+zYsQOj0UiXLl1o3rw5Dg4OgMz9FeZLKcX9+/dZunQpVlZWjBo1Ck9PTzlmRaWnlOK3334jMTGR4cOHS4q0KCkSCIvyQ+s0LFy4kClTplClShXpMAhRCRmNRpKTk9m9ezfHjh0jICCAnj17EhQUhIWFhVwXRLmhlMJgMLBv3z62bNlC//79adeunWQxiEovLy+PWbNm0bt3bxo2bCjngygJEgiL8iMvL485c+bQrVs3wsLC5KIoRCWilEKv13P79m22bt3K7du3adWqFe3bt8fDw0OuB6JcU0oRFxfHDz/8gNFoZNSoUbKEjKjUlFLExMTw7bffMmXKFFOFfyGKkQTConxQSrFt2zbi4uJ48cUXJSVaiEpCm0957tw5tm7dCkD37t0JCwvD3t5eAgVRoeTn53P48GE2bNhA3759ad++PdbW1mXdLCHKhFKK33//nbS0NJ577jlJkRbFTQJhUT7ExMSwePFipk6dirOzc1k3RwhRwpRSpKenc/DgQfbu3Yu3tzd9+/YlMDBQ0kZFhaYttfTdd99hbW3N6NGjpbK0qLRycnKYPXs2zz77LLVq1ZLzQBQnCYSF+cvLy2Pu3Ll0796d0NBQuQgKUYEppUhISGDr1q2cOXOGhg0b0qtXL7y8vAApfiUqB23u8Pbt29m5cycjRoyQKUGiUlJKcfPmTX7++WemT5+OjY1NWTdJVBwSCAvzppRi9+7d3L59m9GjR0tajBAVkFIKo9FITEwMW7Zs4caNG7Rr144OHTpIUTxRqSmluHXrFkuWLKFOnToMHjxYpgSISkcpxcqVK3Fzc6NHjx5y/IviIoGwMG/x8fEsXLiQyZMn4+LiUtbNEUIUI23U68aNG2zevJnExES6d+9uWv5IOjtC/FdWVhZr167l6tWrvPLKK/j7+8v5ISqVjIwMZs6cyYQJE6hWrVpZN0dUDBIIC/NlMBhYsmQJYWFhtGjRQm76QlQg+fn5XLp0ic2bN6PX6+nTpw+hoaHY2trKuS6KhVIKpRTZ2dlkZ2eTm5tLfn4+BoMBo9FY1s0rNKPRyJkzZ1i7di2vvPIKNWvWLOsmCTNgaWmJhYUF1tbW2NraYmdnh729fYVbSk4pxfHjxzl9+jSvvPKKFE0VxeGRgbBVKTdEiIcopbh48SK5ubk0adKkQl3MhaistCWQzp49y6ZNm7CxsWHgwIHUqVNHCmCJItMe3CulSEpKIjo6mqtXrxIVFUViYiK5ublYW1tjY2ODtbW1KXAorxo1asR3331HdHQ0Xbt2xc7OrqybJMqINq3EaDSSn59vethja2tL1apV8fb2pk6dOvj5+eHh4WE67svjtVan09G0aVOOHDlCREQE9evXL5ffQ5QPEgiLMpWTk8OGDRsYO3YsVlZyOApRnimlyM/P59SpU2zevBlnZ2defPFFQkJC0Ol00pkRhaYFvzk5OVy9epVTp05x48YNjEYj3t7e1K5dmx49euDp6YmrqytWVlYV6jjLzc1l9erVXLt2jREjRuDj41PWTRJmQJtukpKSQkJCAvfu3eP48eOsX78evV5PQEAATZs2pW7dujg5OZW766+FhQXPPvssP/74I7Vq1cLW1rasmyQqKEmNFmVGKcXGjRvR6XT079+/XF2khRD/RylFbm6uKQD29PSkf//+BAUFlesROVF2tHWlr169yr59+4iOjsbX15emTZtSq1YtPDw8Kk3KpNFo5Pjx46xZs4Zhw4YRHh4u55X4U0ajkeTkZG7evMmpU6e4efMm7u7utGvXjtDQUBwdHctNX8toNLJq1SqqVatG586dy027hVmSOcLC/Ny7d49vvvmGqVOn4uDgUNbNEUIUkhYAnz59mi1btuDp6cmAAQPw9/evNEGKKF5Go5H79++zb98+Tp06hY+PD+3bt6d27dqmka3KSClFdHQ0ixYtolmzZvTp0wdra+uybpYwY9q8+Vu3bnHgwAGuX79OvXr16Nq1K9WrVy8X1+iUlBTmzp3LpEmTcHV1LevmiPJLAmFhXgwGA4sXL6Z58+Y0bdq0rJsjhCikB0eAPTw8GDRoEP7+/hWucIsoHUajkRs3brBlyxZiY2Np164dbdq0wdXVVUY//39KKTIyMvjuu+/Q6XS8/PLLODk5lXWzRDmgHTvHjh1j9+7dVKlShf79+xMSEmLWAbG2tOa9e/d44YUX5N4iikoCYWE+tAJZO3fu5I033jDri7AQ4v9o89LOnj3LunXrcHV1ZfDgwdSoUaPYOijS0ak8tGrPN27c4JdffiE9PZ1+/foRHh6OjY2NHAuPkJ+fz6ZNmzh9+jSvv/463t7esq1EgWiFDM+fP8/GjRuxsrJi6NCh1KpVy2znEefk5PD5558zduxYmSMvikoCYWE+cnNzmTlzJiNHjqR69epmeeEVojLTApQHK5VmZmZy7do1Vq5cye3bt+nWrRs+Pj5kZ2eTkZFBbm4uer2e/Px8LCwsMBgMpvcyGAymCr7agy9LS0ssLS2xsbHBzs4OZ2dn7O3tcXBwwNnZGRcXF1xcXHBycjL9rjbaLNeM8k8pRWxsLGvWrOH+/fsMHDiQxo0bV7hiVyVFKcWxY8dYvXo1L7/8slTWFYWiXdvPnTvHL7/8gqenJ0OHDjXLhypKKU6dOsWxY8cYP368ZIiIopBAWJgHpRT79+/nzp07vPjii3JBE6KMaB2h/Px88vLySEtLIyYmhvj4eBITE4mPjyczM5Pc3Fzu3LlDZGQkjRs3xt/fH39/f1xcXHB0dMTR0REnJydsbW0fWrJGC1gfPMcfDKy1ADk/P5+cnBzS09PJzs4mMzOTtLQ00tPTTX+n0+mwtLTE1tYWDw8PPD098fT0xNfXlypVqpiWy5HrifnTUjR//fVXTp48SZ8+fWjVqpWsK10ESilu3brFokWL6N27N+3bt5dzQBSKUoq8vDwOHz7Mli1baNu2LT179sTOzs6szke9Xs+sWbPo378/derUKevmiPJHAmFhHjIyMvjyyy+ZOHEi7u7uZd0cISoFrahVeno6SUlJ3Lhxg+joaOLi4sjMzMTCwgJHR0e8vb2pVq2aKdhMS0tj06ZNpKenM3ToUEJDQ7GxsSm1dhuNRvR6PXq9nry8PLKzs4mPjycuLo74+HhiYmLIyMhAKYWTkxPe3t7UqFGDmjVrUqVKFRwdHWXqhRnR6/WcOXOGVatWER4eTt++fXF2djarDnd5o5QiMTGRBQsWUL9+fQYMGCBFtEShKaVITU1l7dq1REZGMnLkSGrXrm02D1aUUly7do3NmzczadIkOcZFYUkgLMqeUop169ZhZ2dH7969pfMjRAnQ1vJNSEggOjqaK1euEBMTQ3JyMlZWVri7uxMYGIifnx++vr6mtVe1kVyApKQkNm7cyKVLl+jfvz8tW7Y0uzmbWuq2FignJSURFRXFrVu3uH37NhkZGdjY2ODj40OdOnWoWbMm1apVk/Uoy4BSipSUFJYvX05SUhKjRo0iICDAbDrZFUFmZiZLlizB1taWUaNGYW9vX9ZNEuWQ0WjkypUrLFu2jCZNmtC/f3+zOZYMBgMLFy6kY8eOhIaGlnVzRPkigbAoe4mJicybN4/p06fj6OhY1s0RolzTrt1KKdLT07l16xZXr14lMjKS5ORk7Ozs8PX1pW7duvj7++Pt7f1Qutv/BrVKKbKysti6dSsHDhygU6dOdOvWDXt7e7MKgJ/kwbnNSUlJ3L17l4iICG7evElmZiYeHh7Url2b+vXr4+/vbxpZKE/fsTxRSnH69GmWL19O586d6dGjB9bW1rK9i5n2UGjlypVER0czYcIEXFxcZDuLQlNKkZmZyapVq7hz5w7jx483i7nDSinu3LnDTz/9xLRp02RUWBSGBMKibCml+P777wkKCqJ9+/Zl3RwhyiWts5uens7169e5ePEiN27cID8/H19fX+rUqUNwcDBeXl4PLavyuA6MNoJ8+PBhNm/eTGhoKP3798fV1bXMOz7FRbvPZWZmEhsbS0REBJcuXSIlJQVPT08aNWpEgwYN8PDwkGJNxUQpRU5ODqtXr+batWu88sorBAQEyLYtYQaDgW3btnHo0CHefPNNPDw8ZJuLIjEajRw7doyVK1cybNgwmjdvXuZZHEajkW+++YYmTZrQtGlTObZFQUkgLMpWdHQ0S5cu5e233y7VOYZClGdaQamMjAxu3rzJmTNniIyMBCAgIID69esTHByMu7t7kVKX9Xo9ERERrF69Gnd3d4YMGYKvr2+l6FxoI+mxsbGcPXuWiIgI8vLyqFu3Lk2bNsXf3x9HR8dKsS2Km1KKmJgYFi9eTHBwMEOGDDGb9MrKwGg0cvToUdavX88bb7yBn5+fHMeiSLTq7l9//TUNGjRgwIABZd6Hi4qKYtmyZcyYMUNGhUVBSSAsyo7BYGDx4sU0b96cJk2ayA1ZiMdQSpGdnU10dDRnz57l8uXLZGZm4u/vT1hYGHXr1sXFxeWp0kuVUkRHR7NmzRpSUlJ4/vnnqV27dqUtLKWNtKelpXHhwgVOnjxJfHw81atXp3Xr1oSEhEhRpwIyGo2cOnWKlStX8txzz9G0adNKe1yVJaUUFy5c4Pvvv2fcuHGEhITI8SuKRJs28/3335Ofn8/LL7+Mk5NTmR1PRqORb7/9loYNG9KyZUs5rkVBSCAsyoZSips3b7JmzRqmTp2KlZVVWTdJCLOiXYPT0tK4du0aR48e5fbt27i4uBAeHk5oaCje3t5YWVk9dVqaNvdr06ZNnDx5kmeeeYZWrVrJnM0HaHOMc3JyiIiI4ODBg9y9exc/Pz/atm1LvXr1TKObss0eptfr2bJlC8eOHeP111+vNNkF5kopxfXr1/n6668ZNWoUDRs2lP0hikR7WLhlyxZOnz7NW2+9hZubW5kdT9HR0Xz77be88847ZT5CLcoFCYRF2TAYDCxYsIAuXbpQv359uQkLwf8FW0lJSZw+fZrjx4+TnJxMQEAALVu2pG7dujg7OwPFE2xpKdZHjx5l3bp1hIeHM2DAAEn9fQLt/pidnU1ERAQHDhzg7t271K5dm06dOlGzZk2ZU8z/Lc+1dOlSsrOzGTdunBxbZkIpRVRUFPPmzWPw4ME0b95c9osoMqPRyMGDB9m0aRNvvfVWmT3sUkrxzTffEBoaKqPCoiAkEBalTynFjRs3WLduHZMnT5bRYFGpacFocnIyJ0+e5NixY2RnZ1O/fn1atGhBQEDAQ1Wdi4vRaOT27dusWLECGxsbhg0bVmxzBrWA/sFKzQ9Ws37w5+C/Qf2DVau1l4WFxSOrWZsTpRRpaWmcPXuWAwcOkJmZSbNmzWjXrh3u7u6VMgVYm2u9cOFC/Pz8GDp0qMzbMzNKKe7fv8/cuXPp06cPrVu3LvOiR6L8Ukpx9uxZli9fzoQJEwgKCiqT63ZMTAxLlixhxowZsiyeeBIJhEXpMxgMzJ8/n27dulGvXj2z7uAKURK04DAxMZETJ05w4sQJcnJyTE+xfX19sbW1LZFzQwva1q9fT0REBIMHD6Zx48YFeiClVZLOy8sjLy+P3Nxc0tLSSElJIS0tjfT0dNLT08nKyiInJ4fs7Gz0er3pdy0tLR8Kfo1GoynY1el0KKVM39nCwgJra2vs7e1NLxcXF6pUqUKVKlVwc3PD1tYWGxsb059lfS3R9mtcXByHDx/m2LFjeHl50bVrV0JCQkrkgYY5UkoRFxfHwoULadGiBT169JAHnmYsPj6eOXPm0K1bN9q3by/BsCgypRRXrlzhu+++Y+zYsWUyB10pxaJFi2jWrJlUkBZPIoGwKF3a3KSNGzfy1ltvSedIVCpKKVJSUjh37hwHDx4kLS2N8PBwWrVqhbe3d4kHc/n5+Rw5coSNGzfSunVrevXq9Yf1gLVgVwtq4+PjuXv3LomJiSQnJ5Oeno5SCmtra2xsbEyBqbOzMy4uLjg7O+Pk5IS9vT0ODg5YW1s/FOz+2Qjvg6PFD44i5+XlkZmZSXZ2NpmZmaSlpZGamkpqaiopKSnk5uaSm5uLwWDA0dERd3d3qlatSvXq1alWrZqpXWVxndHSgiMiItixYweJiYm0bt2adu3alekcutJw+/ZtFixYwIABA2jVqpUEVmZOKUVycjJz5syhQ4cOdOrUSfaZKDKlFJGRkSxevJiXX36ZOnXqlOr1TinF3bt3Wb58OdOmTZO5wuJxJBAWpctoNDJr1ix69eolo8GiUtACoosXL7J3715iYmKoU6cOHTp0ICgoqFTmkmrzAX/44QesrKwYMWIEPj4+ptHh+/fvExUVRWRkJPHx8WRkZGBpaYmzszOenp74+/vj6emJu7s7bm5uppHNskpd/t/Ua71eT0pKComJiSQkJHD37l3u379PWloaRqORKlWq4OvrS0hICL6+vnh6ej6UpluSbdfamJCQwM6dOzl58iS1a9emV69eplT0inId1Ka9LFy4kJdfflnqP5Qj2kO6OXPm0K5dO7p06QKY95QEYb60gqhfffUV48ePL/U0aYPBwMKFC+nYsaMUgxOPI4GwKF2RkZH88ssvUilaVGjavN+YmBj27NnDuXPnqF69Oh07dqRevXrY2dkBJd/J1JZc2rhxI0eOHKF37954enpy69Ytrl+/TkpKCgBVq1bFz8+P4OBgvLy8cHd3x8HB4aH3Ki8dif+9d2VmZhIfH090dDTXr18nJiaGzMxMHB0dqVmzJnXr1iUoKAgnJyfTXN6S+q7aciNHjx5l586dODs7069fP+rWrYulpWW52cZ/RinFtWvXWLx4Ma+88gq1a9cu19+nMlJKkZqaypw5c2jVqhXdu3eXfSiKTBsZXrRoERMnTqRGjRqldjxpD+XWrl3LlClTpL8pHkUCYVF6jEYj8+fPp2PHjjRq1KismyNEsTMajaSnp3Pq1Cn27t2L0Wikbdu2NG/evNTSYbW04pycHC5cuMC8efO4ffs24eHhODk54evrS1BQECEhIbi7u+Pi4lLug7DC0ILRpKQkbt26RUREBHfv3kWn0+Hj40NoaCh16tR56jWZn9SG/Px8Ll++zJYtW8jNzaVfv340atTILOY6F5ZSioiICJYuXcq4ceMIDg4ud99B/B9tZLh9+/Z07NhR0qRFkWnXhh9//JE33ngDb2/vUrs26PV6Zs2axcCBA+WaJB5FAmFRem7dusVPP/3E22+/LU/nRIWhpebeunWLnTt3cv36derVq0enTp3w9/cvlbV4tQD83r17XLx4kVOnTnHq1Cl8fHzo0qUL4eHheHt74+joWC4DrZKkBaUZGRncvn2b8+fPc/36dQCCg4MJCwujZs2auLi4lEhAoNfruXHjBps2bSI5OZkePXrQvHnzclNYSyuOs3TpUsaPH0/NmjXLRbvF4yUnJzN79my6du1K27ZtJRgWRaaU4vTp06xfv54pU6bg6upaateIs2fPsn//fiZOnCjXJfFnJBAWpcNoNPL111/TokULwsPD5YIkyj2lFJmZmZw4cYLdu3ej0+no1q0b4eHhODg4lPi809zcXGJiYrhw4QIXL14kJSUFNzc30tPTuX79OsOGDaNXr17lJqAyF9qDjfT0dCIiIjh9+jR3797F3d2dJk2a0KBBA6pVq1asSyJpo/jR0dFs3LiR6OhoevfuTcuWLc1++Y8bN27w1Vdf8dprr0kQXIFo65nPnj2bvn370qJFC9m3osiMRiP79+/n8OHDvPnmm3+YelNS8vLy+M9//sPYsWPx9fUtlc8U5YoEwqJ0aOu6vfvuu7KWpCi3tMJHsbGx7Nixg3PnzhESEkKPHj2oUaPGQ8WjSuJzk5OTuXjxIidPniQ2NhYnJydCQ0MJDQ3FwcGBFStWkJeXx8svv1yqKWgVlXYfzM/P59atW5w4cYLLly+j0+lo2rQpzZs3N23n4lx/OTo6mrVr1xIbG0u/fv1o0aJFqWQWFIZWmXXevHmMGzeOWrVqmVX7xNPTirx9+eWXPPfcczRu3Fj2sSgyo9HIxo0biY2NZdy4caWSGaiU4uDBg1y/fp3Ro0fL8Sv+lwTCouQZjUZ+/PFHgoKCaNu2rVyIRLmjjRJGRETw66+/kpKSQocOHWjdujVVqlQBir/Akpaye+/ePU6dOsWZM2fIycmhVq1aNGvWjMDAQFxcXDAYDBw8eJCNGzfSu3dvOnbsWCqVqCsjbeQ2JiaG48ePc+bMGVNQ3LJlSzw8PIrlYYh2/719+zbr168nPj6ewYMH06hRI7OYVqKU4t69e8yZM4fhw4fToEEDOd4qKG1fz549m5EjR0olcPFU9Ho9S5YswdPTk4EDB5ZKyn12djaffPIJkydPxs3NrcQ/T5QrEgiLkpeUlMScOXOYMWNGqaXDCFEcHkx/3rFjB05OTqalv0pirq1W5fnOnTscOXKEK1euYG9vT6NGjUzzfLXPVUoRFxfH999/D8DIkSPx8vKSTmop0R6O3Lt3j+PHj3Pq1CkcHBxo164dYWFhODs7F0snz2AwmKrtGwwGnnvuOWrVqlWsqdmFoS2zM2vWLJ555hmaNGkix1wFp43+z58/n/HjxxMYGCj7XBRZdnY2s2bNomPHjrRu3bpUVk/YuHEjFhYW9OvXT45d8SAJhEXJUkqxbt067O3t6dWrl1yARLmglCIxMZE9e/Zw7NgxgoOD6dWrF9WrVy/2ETmtivGtW7c4fPgw165dw93dnZYtWxIaGkqVKlX+UNU5Pz+f/fv3s2XLFgYMGEDr1q1lykEZUkqRl5fH3bt32bdvH1euXCEgIIDOnTtTq1YtbGxsnvoz9Ho9Fy9e5JdffsHd3Z0hQ4ZQvXr1Ul+/WevEtm/fnnbt2sk1vZJQSnH9+nWWLFnCpEmT8PX1lX0vikSbfz5r1izGjh1bKssqJScn8+WXX/Luu+/KgIx4kATComRlZmbyn//8h2nTpplSSIUwR9r8zKioKLZs2UJkZCStWrWiS5cupiqXxXWz1tKer127xv79+4mMjMTDw4M2bdrQqFEjnJyc/jTFVutALF26FKUUo0ePxsPDQzqkZkK7b2ZnZ3P+/Hl27txJZmYmbdu2pXXr1ri6ugJFT6PXjpujR4+yYcMGGjduzDPPPIOzs3OpHAN5eXksWLCAmjVr8swzz0gl4UpGKcW5c+dYvXo1U6ZMwd3dXa49oki0dceXL1/O1KlTS7x/qJTi22+/pX79+rRq1UqOW6GRQFiUHKUUO3fuJD4+nmHDhsmFR5glLQC+efMmGzZsIC4ujp49e9KqVatirbislMJgMBAVFcWBAwc4d+4cbm5utG/fnkaNGuHs7Aw8OkgyGAwcO3aMVatW0a9fPzp27Fip1v8tbx4srLZ7927Onj1LzZo16d2791MXVtNS9n/99VeOHDlCv379aNeuXYkW1DIYDPz888/k5eUxcuRIs5irLEqfUopDhw6xa9cuJk+ejJOTk1yDRJEopdi1axeXL19mwoQJJXpN0R5y//DDD7z99tuSQSU0EgiLkpOXl8eHH37Ia6+9hre3d1k3R4iHaIHp9evX2bBhAxkZGfTu3ZumTZsW6/xfg8FAUlISR44c4ejRo1haWtKqVSuaNWtWoNFcpRRpaWn8+OOPJCcnM2bMGHx8fKTzWY5o6e+nTp1ix44dWFtb07t3bxo0aICtre1TBcT3799n1apVJCYmMnz4cFP15uI8PoxGI9u3b+fy5cu8/vrrxZLqLcovo9HI77//zuXLl5k4cSJ2dnZl3SRRTun1er777jsCAgLo0aNHid7XDAYDM2fO5NlnnyUoKEjuoQIkEBYl6fTp0xw8eFAWMhdmRUsvvXTpEps3b0YpRd++fU1BSXF9RlZWFpcuXWL37t0kJSXRtGlTWrdujbe3d4FHco1GIxcvXuTHH3+kffv2dO/evUSKdInSk5eXR2RkJL///jvx8fF06tSJNm3a4OjoWOT9ajAYuHjxIitXriQwMJBnn30WNze3YlvS6ezZs2zatIkpU6Y8VTtFxWEwGPjll19ITU3l5ZdflgwBUWTp6el88cUXDB8+nJCQkBL7HKUUp06d4sSJE4wbN06mdgiQQFiUFIPBwBdffMGgQYNK9MImRGHo9XrOnz/Phg0bsLOz45lnniEkJKTYlhvSUp/37t3LhQsX8PPzo0uXLtSqVavQI385OTmsW7eOCxcuMGbMGHmCXYFoyzDdv3+f3377jYiICNq0aUOnTp1M89GL8p45OTns3LmT3bt306dPH9q3b/9Uo7dKKWJiYliwYAETJ06UTATxkPz8fL755hu8vLxKbSkcUTHdvHmTpUuXMm3aNFxcXErsc7SllN566y3c3d1L7HNEuSGBsCgZN2/e5KeffuKdd94ps2U+hID/CzouX77M2rVrsbCwYMiQIYSEhDz1mq8PFkc6efIkO3fuJD8/n/bt29OqVStcXFwKnaaqzWVavHgxNWvW5Pnnn8fBwUECkApKK4C2detWTp48SbNmzejVq9dTBcTx8fEsX76czMxMRo8ejZ+fX5HeKyMjg88++4zBgwcTGhoqx6D4g6ysLNNSOG3atJFjRBSJUopt27YRHR3N6NGjS6zfqJRi06ZNAPTv31+OVyGBsCh+WnW+Bg0a0LJlS7nQiDKjrcG6Zs0a8vPzefbZZ6lfv36xBMDa/Mxdu3Zx+vRpAgMD6dmzJ4GBgUV6fy1g37dvH5s3b+aFF16gSZMmMspSCWj327S0NHbs2MGhQ4do3rw5vXr1okqVKkU+lk6cOMGqVato06YNffv2LVRWQn5+PgsXLqROnTolPndPlF9KKZKTk5k5cybDhw+nbt26cqyIQtPWZZ8/fz5t2rShefPmJXYcJSQkMHv2bP72t79JvQMhgbAoftp6be+99x729vZl3RxRCRmNRm7dusWaNWvIyMhg4MCBhIaGPnWlSKUUubm5XL58mW3btpGSkmJaGudplhJRSpGens6PP/5Ieno6Y8eOpWrVqtKhrISUUqSmprJjxw6OHDlCixYt6NGjR5ECYoDU1FR++eUXIiMjGTlyJLVr137iwxWj0ciGDRtITEzk5Zdflqwe8VhKKe7cucOiRYuYOHGirDEsiiw+Pp558+YxadKkErsHKqWYP38+7dq1o3HjxsX+/qJckUBYFC+lFL///js5OTkMHDhQboaiVGmjtOvWrSMqKoqBAwcSFhb21E99tcrNR44cYe/evVStWpXu3btTu3btp6r6q7339evXWbJkCa1ataJ3797FVrRLlF9KKVJSUtixYwdHjx6lU6dOdO7cGUdHx0K/l9FoJCIigh9//JGGDRsyYMCAR6bbP1gca9q0aTg4OBTH1xEVnHbcrF+/nmnTppmWgxOiMJRSHD16lJMnTzJ+/PgSK8J2+fJlfvvtNyZPnixZV5WbBMKieOXm5vLxxx8zceJEPD09y7o5ohJJS0vj119/5cSJE/Ts2ZP27dsXS5B67949duzYwZkzZwgNDaVHjx54eXk9dXo1/Ld417Zt29i9ezdjxoyhTp06clMWD9HmEG/cuJFLly7Rt29fWrduXeiHJVol83Xr1nHx4kVGjx79p6PD8fHxfPnllzKyJwpNKfXQMluyVqsoCr1ezzfffENoaGiJzTvX6/X8+9//ZsKECfj4+BT7+4tyQwJhUXy0J8IHDx7ktddekw69KHFKKfLy8ti/fz+//vorzZo1o3///jg5OT1VmrLRaOTGjRts2bKFmJgY2rdvT8eOHXF2di62JWkyMjL47rvv0Ov1jBkzpsipr6JyUEoRGxvLqlWriI+P5/nnn6dhw4aFLsZmNBq5cuUKS5cuJSwsjEGDBpnWgc3LyzMVPpL6DqIoDAYDy5Yto0qVKgwaNEj6AaJIkpKS+PLLL5k8eTJVq1Yt9vdXSrF161YyMjIYPHiwXOsqLwmERfExGo3MmjWLPn36UKdOHbmwiBJlMBi4cOECK1eupHr16gwZMoRq1ao9VQCcn5/P+fPn2bx5M0ajkV69ehEeHv7UI8v/+zm3bt1i0aJFtG7dmj59+hTb8k2i4jMajVy/fp0VK1bg5OTEsGHD8PX1LVTAoZQiOzub1atXc/36dcaOHUtAQACrVq1Cr9fzwgsvyLxgUWQ5OTl8+eWXdO7cWR6oiCLRUqTPnj3LK6+8UiLXo5SUFL744gvee+89mQJSeT0yEJaV0UWhxcfHk56eLuudihKlzQP++eefSU1N5aWXXqJWrVpFHnnQCmCdOnWK3377DRcXF4YOHUqtWrWKPbVPr9ezb98+fv31V1566SVTBWshCsrCwoLatWvz/vvvc+zYMebMmUOjRo3o37+/abmuJ9HpdDg4ODBy5EjOnTvHggULqF69OikpKcyYMUOCYPFUbG1tGTduHLNnz8bLy4uaNWtKn0AUik6no3nz5hw/fpyzZ88SHh5e7MeQi4sL3t7eXLt2jbCwsGJ9b1H+yYiwKLRVq1bh6upKjx49yropogLSRrG2b9/O/v376du3L23atClyYSltzuTRo0fZvn073t7e9O/fn4CAACwtLYv1pqt91s8//0x8fDyvvPKKVIUWT00pRWZmJr///jtHjx7lmWeeoVWrVoXKMFBKERkZyYQJE2jZsiWTJk3Cy8tLjk3xVJRSXL16leXLlzN16lSZ+iEKTXvovXjxYiZPnlzsBdiUUly6dImdO3cyceJEeQBYOUlqtCge2dnZfPjhh0yfPh1XV9eybo6oQLQ1e8+dO8fKlSupVasWgwcPLnLHSgse9u3bx549ewgKCqJfv36FTi8tzOfFx8ezcOFCateuzbPPPouNjY10CkWx0eYPr1ixgpycHEaMGEGNGjUKdIzl5+czb948wsLCsLa2Zv369QwdOpTmzZtLtoJ4Kkopdu/ezdmzZ3njjTekeJYoNKUU27ZtIzU1lSFDhhT7NSk3N5ePPvqIN998s0TmIguzJ4GwKB7Hjx/n1KlTvPrqq9LBF8VGq5j7ww8/kJKSwogRI0yp94U9zpRS5OTksHv3bnbu3EmDBg3o27cv1apVAyix9QovXrzIt99+y5AhQ2jVqpUEF6JEaEXeTp8+zapVqwgNDWXQoEE4Ojo+8tjWqvxeu3aNCRMmYGFhQWxsLF9//TUBAQEMGzYMe3t7uaaLIjMYDHz77bd4enoyYMAAOZZEoWlzzocPH46/v3+xZ2tt2LABa2tr+vTpI8dn5SOBsHh6BoOBmTNnMnDgQEJCQsq6OaICUEqh1+s5ePAgGzdupHfv3nTq1KlIIwpaAHzw4EG2bt1K3bp16d+/P56eniV608vPz2f79u3s27ePCRMmFHiEToinoaXhb9q0idOnTzNs2DAaNWr0h7Q/pRR37tzh66+/ZsaMGVSpUsX0bzk5Oaxdu5aLFy/y6quvEhAQIMeuKLKsrCw+++wzBgwYQFhYmBxLotC0dX/ffPPNYl9b+N69e3z11Vf89a9/LbF1i4XZkmJZ4unFxcWRmZlJYGBgWTdFVABamucPP/yAlZUV77zzTpGrQWdnZ3Ps2DF+++03goKCmDJlCj4+PiXaEdPmMv/www9kZmby3nvvFbiIkRBPS6fT4ejoyNChQ2nRogU//PADBw8eZNiwYQ/NS8/NzWXZsmUMGzYMFxeXh97Dzs6OYcOGcf78eebNm0efPn1o3769dBJFkdjb2/PKK6+wYMECfHx8nqq6v6ic6tSpw6FDhzh27Bht2rQp1vf29PTE0dGR27dvS7FXYSIjwqJAlFKsW7cOe3t7evXqJRcQ8VRyc3PZuXMnO3fuZNCgQbRs2bJIo8B5eXmcOHGCTZs24evry8CBA6levXqJpyUrpUhMTGThwoWEhIQwaNAgmQ8sylRubi67d+9m+/btPPPMM7Rt2xZLS0vWrFlDTk4Ow4cPf+R5oZQiISGBJUuW4O7uzosvvvjYVGshHkUpxYkTJ9i5cydvvfUW9vb2Zd0kUc4kJCQwf/58pk6dWuyFsw4ePMjVq1d56aWX5PpWuUhqtHg6OTk5fPTRR0yZMgU3N7eybo4op5RSxMTEmDrcw4cPx9XVtVA3JK2o1pUrV1i5ciUODg48//zz+Pv7l8q8XKUU169fZ9GiRQ8FHEKUNaUUcXFxLF26FCsrK9q1a8fGjRt5//33cXR0fOLv5uXlsWHDBs6cOcOECROKfZ6eqBwMBgMrV65Ep9MxbNgwOYZEoSil2LJlC3l5eQwaNKhYj5+0tDQ++eQT/vrXv8qawpXLIwNhqeYinkjr+Ht6ej40v0yIgtLmAu/atYuZM2fSs2dPXn/9ddzc3AodBMfGxjJr1ixWrFjB4MGDmT59OgEBAaUSBBuNRg4dOsRXX33FuHHjaN++vQTBwmzodDqqVavGtGnTqFOnDhMnTqRu3brY2tryhIfe6HQ6bG1tGTJkCM8//zyzZs3i0KFDGAyGUmq9qCgsLS0ZNGgQ169f58yZM0889oR4kE6no2vXrly8eJH79+8X63s7OztTo0YNLly4UKzvK8ovGREWT2Q0Glm4cCHt27enUaNGZd0cUc4opUhOTmbp0qUYjUZGjx6Nh4dHoQPglJQUNm3axPnz5+nXrx+tW7fGxsamBFv+sPz8fDZv3szZs2d5/fXXS7wIlxBFZTQaWbVqFSkpKaSmpmJjY8OoUaNwd3cv0DGrjSx/9dVXpmXMbG1t5XgXhRIdHc3cuXN5++23ZckaUShaiv3p06cZO3ZssT5wvnjxItu2bWPy5MlyTas8ZERYFF16ejr37t2jVq1aZd0UUc4YDAZOnDjBRx99RGhoKG+99VahAkitEvTWrVv58MMPcXFx4R//+AcdOnQo1SA4Ozub7777jrt37zJ9+vQKFQRro/W5ublkZWWRkZFBeno6aWlppldGRgZZWVnk5OSQn58vIzxmTCnFtWvXuHz5MqNHj2bq1Kk0bNiQTz75hBMnThRohFcbWX777bfJy8tj5syZJCQkyH4XheLr60u/fv347rvvyMvLK+vmiHJEp9PRuHFj0tLSuHnzZrFee0JCQkhISCApKanY3lOUXzIiLB5LKcWuXbuIj4/n+eefrzCdf1GytIrKK1eu5M6dO4wZMwY/P79CHT9Go5GIiAhWrFiBr68vQ4cOfagabmlJSUlhwYIF1KxZ0zQyVp4YDAbS09NNwe39+/dNI4WZmZlkZmaSm5sLgIWFBVZWViilsLa2RqfTkZeXZ5qXbTAYUEphY2ODvb09Li4uuLq6UrVqVTw8PHB2dqZKlSo4OzvLOsplJDs7m08++YQXX3yR2rVro9PpUEoRFRXFt99+i6+vL8OGDStwERqDwcD+/fvZvHkzY8eOpW7dunIfEAVmMBj47rvvqFatGv369ZPrgigwpRRXr15l8+bNvPXWW8VWzV4pxfLly6levTqdO3culvcUZk+KZYmiMRqNfPTRR4waNYqAgICybo4oB7R5vAsXLqRu3bqFTqtUSpGUlMTKlSuJiYlh+PDh1KlTp9Q7UFphr3nz5tG5c2e6du1qlvOBH7yG5+TkEBsbS0xMDJGRkcTFxZGWloaFhQUuLi64uLjg7e2Nu7s7Li4uODs74+joiKOjo2mE/VH7SfscvV5PdnY2GRkZpoA6MTGR+Ph40//rdDrc3Nzw8vIiMDCQGjVqUK1aNdP2k0CqZCilWL9+Penp6YwYMeKhc0YrhrV582aOHj3K2LFjTYFyQd73xo0bLFy4kF69etG5c2csLCxkP4onUkqRmZnJp59+yogRIwgJCZHjRhSYwWBg0aJFtG7dmsaNGxfLsaOU4vbt2/z8889Mnz5dlourHGQdYVE00dHRwH9TnIR4EoPBwPHjx1m1ahUvvPACTZs2RafTFbiznZeXZ1oCplu3bowdO7ZMliXSnkR/8803vPDCC4SHh5tV501LZ05OTubatWtEREQQExNDTk4O7u7uVK9enXr16tGpUyfc3d1xcnJ66Pef5rtYWVlhZ2eHm5sb/v7+f0hZU0qRlpZGYmIicXFxXLt2jZ07d5KVlYWbmxu1atWiXr161KhRw/SAxJy2bXmllCI6OpqjR4/y/vvv/+HBkVYM69lnn6Vhw4Z8++23tGnTht69e5tG/x9Fp9MRFBTEX/7yFxYuXMidO3d48cUXZd6weCJtvevRo0fz3Xff8e6778rSXKLALCws6N+/P0uXLqVBgwbFMiVKp9Ph5+dHTk4OiYmJeHl5FUNLRXklI8LikZRSrFy5kqpVq9K9e/eybo4wY9pc3jVr1nDz5k3GjRuHt7d3gTs7RqORGzdu8P333+Pj48OQIUMKXVCruBiNRk6fPs3KlSsZN24ctWrVKvNOmxb4pqamEhERwYULF4iKisLGxobAwEDq1q2Lv78/rq6uZhmcGI1GMjIySEhI4OrVq1y6dIn4+Hg8PDwIDQ0lNDSUqlWrPjEgE4+Wn5/PZ599Rs+ePWnSpMljt6P2sGL58uWkp6czZsyYAp9v2dnZrFq1iujoaMaPH1/gAlyicjMajWzcuJHk5GRGjx4tKdKiwJRSfPfdd9SpU4e2bdsW23tu2LABGxsbevfuLdewik9So0Xh5eTk8P/+3/9j2rRpsnaweCStwuzXX39NjRo1eO6557CzsyvwKHBmZiYbN27k3LlzDB8+nPr165dZCrLBYGDv3r3s2LGDN954Ax8fnzK7QWrzrKOjozl58iQREREYDAZq165No0aNqFGjBk5OTlhaWpa7m7jRaCQrK4vY2FjOnj3LxYsXMRgMhIaG0qJFC3x8fCQoLgSlFDt27ODq1atMmDChwOePXq/nwIEDbNq0iRdffJHw8PACBSjaefL7778zfvx4goKCZF+JJ8rJyTEtn9e0adOybo4oR+7fv89XX33FjBkzsLe3L5b3jI2N5ZtvvuHdd9/F2tq6WN5TmC1JjRaFd+PGDdzd3XF1dS3rpggzpZQiIiKCJUuWMGjQIFq1alXgTrhSigsXLrB8+XIaNmzI3/72NxwcHMqsQ63X61m/fj2XL19mxowZVKlSpUxSsnNycrh+/TqHDh3i1q1bVKlShWbNmjFx4kRcXV2xsrIq90GHhYUFTk5OhISEUKtWLQYOHEhSUhInTpxg2bJl5OXlERYWRtu2bU2ZBeX9O5ekxMREtm/fzrvvvluoh0hWVlZ07NiRkJAQvvrqK65cuVKggnCWlpZ07twZb29v5s+fz9ChQ2nRooWM8onHsrOz46WXXmL27NkEBgbi7u5e1k0S5US1atWoVasWhw4dokuXLsVyP/D09MTCwoL79+/j5+dXDK0U5ZGMCIs/pZTim2++ISwsjObNm0snVPzBg9VkX3vttQKPCimlyMjIYOXKldy8eZPRo0dTq1atMutEa2nHy5cvJyUlhVdffRUHB4dS/XyDwcDNmzfZu3cvV69epVq1arRp04bQ0FDTfLrKcA5q1anj4+M5cuQIR44cwcnJiS5duhAWFmYaCagM26KgDAYDixcvJjg4mG7duhVp22jZBytWrODevXuMHz++QKnSSinu37/P3Llzad68Of369SuXGQqi9GgrUVy8eJHXX39dChWJAlFKkZyczOzZs5kxYwaOjo7F8p7bt28nJSWF5557Tq5bFZukRovCSU9P55NPPuEvf/lLqQYFwvxpRa1Wr17NrVu3eP3113FzcyvQTcRoNHLhwgV+/PFHWrZsSd++fbGzsyuFVv85pRS5ubl89913WFlZMXLkyFJpj1IKo9FIYmIihw8f5ujRozg6OtKuXTvCwsLKZDTaHOXn53P9+nV2797NrVu3CAsLo3v37nh4eMjoI/89ji5fvsyaNWt49913n7qQjMFg4MCBA2zcuJGRI0fSqFGjAm3n9PR0vvnmG+zt7Rk9enSxpS6Kikmv1zN37lyaNm1K+/bt5VonCkSrW+Ph4UHXrl2L5biJj49n9uzZ/POf/5SHMhWbBMKicI4fP87p06cZN26c3KSEiVZkZ/Hixbi7uzNs2DDs7e0LNHKUnZ3NunXriIiI4KWXXjKLeYWZmZksWrQILy8vnnvuuWKpSPk42na4ePEiO3fuJD09naZNm9K6deuHlhcSD9NGAw4dOsT+/fvx8/OjV69e1KxZs0KkihdVTk4OH3/8McOHDy+2ZWmUUty9e5evv/6a8PBw+vXrV6C1s3Nzc1mzZg23bt3itddeK/DDMVH5KKVISEjgiy++YOrUqXh6esqxIgokMTGRuXPnMmPGjGIZpDEajXz22WcMGTKE4ODgYmihMFMSCIuCMxqNzJkzh549e1K3bl25QQmT+/fvM2/ePNq0aUP37t0L9ARVKcXNmzf59ttvqVu3LoMGDSrTucCalJQU5s+fT/369enfv3+JPg3W0n0PHDjA0aNH8fX1pUePHgQFBZXJ8lDllTaH+uzZs2zduhUrKyueeeYZ6tWrV+me5iul2Lx5MwkJCcVehVcrYvf999+Tk5PDmDFjCpSlYDAY2LVrFzt27GDixIn4+/vLsS3+lFKKAwcOcOLECSZNmlTpzl9RNEopVq1ahbu7e5GngvyvXbt2ce/ePV544QW5XlVcjwyEJbdM/EF6ejoJCQkEBgbKRUEA/7353Lhxg88//5x+/frRq1evJ3ZclFLk5+ezefNmFixYwPPPP8+LL75Y5mtIKqVISkpi1qxZNG/enAEDBpRIJ0xLf7569Spz5szh888/x2g08vbbbzNp0iTq1atnlksdmTOdToe9vT0tW7bkL3/5CwMGDGD9+vV89NFHnD9/HoPB8Id1jSuqhIQE9u3bx8CBA4s9TVxb+/XVV1+lXr16fPTRR9y4ceOJ29bS0pJu3brxwgsvMGvWLC5cuFBp9ocoHJ1OR6tWrVBKcfjwYTlORIHodDq6du3K/v37yc3NLZb3DA0N5dKlSxgMhmJ5P1G+yIiweIj2lPbWrVuMGDFCOukCpRTnz5/n+++/Z+zYsQXKEtCCzcWLF+Po6MioUaNwcXEp8+NJKUViYiJz5syhc+fOdOrUCSje4kta8a1Lly6xceNG9Ho9vXr1Ijw83JRiWtbboaLQHjZcvnyZdevWAfD888+b1n6uqNvZaDQyf/58GjZsSKdOnUr0eyqluHTpEkuWLGHgwIG0a9fuiYG3Uorbt28zf/58+vXrR/v27WVOt/gDLVPm888/591335Uq0qJAlFL8+OOP+Pn5Fcv1TynFxx9/zLBhwwgKCiqmVgozI6nRomCMRiNffPEFgwYNolatWmXdHFHGjEYjhw4dYvPmzbz++usFSnU0Go1cunSJpUuX0rt3bzp27GgWaW/aesdz5syhd+/etGnTptjTSXNzczl9+jS//fYbDg4O9OvXj7p165rF96/o9Ho9Fy5c4JdffsHDw4OhQ4fi5eVVIQOwy5cv8/PPP/OXv/ylxOe1a+Lj41m4cCHBwcGmJZaedC2Ij49n3rx5NG7cuMSnH4jySSnF3r17OXfunFSRFgV27949Fi5cyPvvv1+gGgZPsn37dhITE3n++ecr7APUSk5So0XBpKSkkJ6eLmuqCYxGI9u2bWPHjh1MmzatQEFwXl4eGzduZMWKFbz++ut06dLFLDo2SiliY2OZNWsWzzzzTLEGwVoBrD179vCvf/2L48ePM3r0aKZPn07Dhg3N4vtXBlZWVjRu3Ji//vWvhIWFMXPmTFasWEFKSkqFSrvMzc1l1apVDBs2DGtr61L7XA8PD95++22ys7OZM2dOgbarp6cn06dPJzIykmXLlpGTk1NKrRXlhU6no127duTl5XH06NEKda6KkuPl5UVAQAAnTpwolvcLDw/n4sWL5OfnF8v7ifJDAmFhopTi1KlT1K9fv1iesInyy2AwsHnzZk6ePMmUKVOeuKaolgo9d+5cYmJieO+998xmjrlSipiYGObMmcPQoUNp0aJFsQXBubm5HDx4kA8++IBLly7xxhtvMHHiRIKDgyUALiO2trZ07NiRf/zjH9jZ2fHhhx9y8OBB9Hp9WTftqSmlOHToEFWrVqVOnTqlen5p87NfeuklwsLC+OSTT7h169YTAxcnJycmTZoEwPz580lPTy+N5opyxNLSkhEjRrBp0yZSUlLKujmiHNDpdPTq1Ytdu3aRl5f31O/n7u6OnZ0dMTExxdA6UZ5IICwecvToUVq2bGkWAYwoGwaDgXXr1nH58mUmT578xGqxSimuX7/Oxx9/TGhoKOPHj8fJycksjiFtJHju3LkMGzaMxo0bF8t8Ir1ez7Fjx/jggw84fvw4r732Gq+99hq+vr6yBJIZ0Ol0ODk5MXjwYKZMmcLBgwf59NNPiYqKKrcjTtrSZb///jtDhw4ts/PLysqKHj16MGLECObMmcOJEycwGo2P/HmdToeNjQ2jR48mMDCQzz//nOTk5HK7H0Tx0+l0eHl50aFDB9auXfvY40kIja+vL66urly6dOmpryc6nY5mzZpx4sQJuTZVMhIIC5OEhARycnIkLbqS0gK81atXc/fuXSZNmoSjo+Njf8doNHLgwAEWLVrEK6+8Qvfu3bG0tDSrIHjOnDkMGzaMsLCwp2qXtn3Onz/PBx98wJ49exgzZgxvvfUW/v7+WFhYmMX3Fv9Hp9Ph4+PD9OnT6dy5M7NmzWLt2rXk5OSUy87Oli1baNmyZZmvu6rT6WjYsCEzZsxg7dq1bN68Gb1e/8htqtPpsLKyYuDAgXTo0IGPP/6Y+/fvl8t9IEqGVg04KiqKiIgIOTZEgfTu3Ztt27Y9dcVnnU5H06ZNOX/+vKRHVzISCAuTM2fO0LBhw1KddybMh8Fg4KeffiIhIYHx48c/cbF6ba7i7t27eeedd0o9VfNxHgyCn3/++acOgo1GI3fv3mXWrFls2LCBF198kWnTphEcHCwBsJnT6XRYWlrSqlUr/v73v5OamsrHH3/MzZs3y83Ik1KKe/fuce7cObp3724Wx5tOp8Pb25v33nuP69evs2TJErKzsx8bwFhYWNC5c2cGDx7MZ599xs2bNyXgESY2Nja8+OKL/PTTTzKfXDyRTqejZs2a6HS6YrmWuLq6YmNjQ1xcXDG1UJQHEggL4L8d/RMnTtCiRYuyboooAwaDgdWrV5OWlsYrr7zy2CBYKUVqairz588nLS2N6dOn4+HhUYqtfbJ79+6ZguCnSYfW5j5///33zJ8/n7Zt25qCfkmBLl90Oh0uLi6MHj2aZ599lq+++or169eXiw63UorVq1fTp08fnJycyro5Jto2nThxIs7OznzxxRckJyc/9ncsLCxo0aIFY8aMYf78+Vy8eFGCYQH893gKDg6mTp06bNmyRY4L8USWlpZ0796dbdu2PfXxYmlpSXh4OMePH5djrxKRQFgA/02LzsrKwt/fv6ybIkqZwWBg/fr13Lt3j7Fjx2JnZ/fIn9VGWj/99FPq1KnDmDFjsLe3N4sRKk1cXBxz585lyJAhTxUE5+Tk8Ntvv/Hhhx/i6urKP/7xD1q1aoWNjY1ZfV9ROJaWljRq1Ii//vWvJCYm8sknn5j93OFr166RkJBgtvUbbG1tef7552nTpg2ffPIJt2/ffuz21Ol01K9fn4kTJ7J06VKOHTtm1ttflB4LCwsGDBjAiRMniIqKKuvmCDOn0+moW7cuCQkJJCQkPPV7hYeHc/78+adOtRblhwTCAqUU586do0GDBjLKVckYjUZ+++03IiMjmTBhwhOD4OvXr/PFF1/w7LPP0rt3b6ysrMymY66UIjExkblz59K/f3+aNm1apLYZjUbTPOC7d+/y/vvvM2DAABwcHMzmu4qno41kjh07lr59+/Lll1+yf/9+DAaD2QVk+fn5rFq1iueee67U1gwuCktLS7p06cLw4cOZNWsW586de2IwHBgYyLRp01i7di07d+4sN6nqomRphe5WrFgh8zXFE9na2tKmTRt27dr11NfvqlWrYjAYpHp5JSKBsHgoLVo6+pWH0Whk586dnDt3jtdffx17e/vH/uzJkyf5+uuvee2112jSpEmxLUFUHLR07blz59KtWzdatWpV6GNZKUVcXBzz5s1jzZo1jB49mnHjxlG1alU5LyooCwsLmjVrxjvvvMOBAwdYvHgxGRkZZhMMa0va2dnZ0aBBA7M/DnU6HY0aNWLKlCmsWLGC3bt3P3ZkRStm9s4777B//342bNhQIZa5Ek9Hp9PRpEkTLC0tpYqveCKdTkeLFi24cOECWVlZT/Ve1tbW1KtXjzNnzshxV0mYT09WlJnU1FQyMjKkWnQlopTi8OHDHDp0iIkTJz523qHBYGD37t2sX7+eKVOmEBwcbHYd8oyMDObNm0fbtm1p3759odqnlCI7O5stW7bw6aefUq9ePd5//33q1KljVsG+KBk6nY5q1aoxbdo0PD09+eijjwq0Pm5pyM7OZuPGjWW6XFJh6XQ6/P39efvttzlw4AC//PLLE4Nbd3d3pk+fzrVr1/jpp5+KZV1QUb5ZWFjwwgsvsHHjRjIyMsq6OcLMubi4ULduXY4ePfpU76NVjz558mQxtUyYO+nlCS5fvkxISIhUi64klFJcvHiRzZs3M3HiRFxcXB75s3q9ng0bNnDkyBGmTZuGj4+P2XXIs7OzWbhwIY0aNaJr166FCl6NRiOXL1/mww8/JDY2lvfff59u3bpha2tbgi0W5sjW1pZBgwYxYsQIFixYwIEDB8p0nphSikOHDlGzZk38/f3N7rx7HJ1Oh4eHB1OnTiU2NpbFixeTnZ392N9xcnJi0qRJpKWlsXTp0nJRxEyUHJ1Oh6+vL82aNWPz5s2SNi8eS6fT0aVLF/bt2/fU6fR+fn6mASJR8UkgXMkZjUaOHz8uadGVhFKK27dvs2zZMiZOnPjYtN/8/HxWrFjB7du3mTx5Mq6urmZ1jCilyMvL45tvviEgIIC+ffsWOAjWUqmXLFnCjz/+yPDhwxk7dizu7u5m9R1F6bKwsKB+/fq8/fbb7NmzhxUrVpCbm1smo8OZmZls376dAQMGlNtj0snJiddeew1HR0dmzZpFamrqY9catrOzY9y4ceh0Or766qtyu96zKB46nY5evXpx/vx5sy9oJ8qej48PVapUISIi4qnex87Ojpo1a3L58uViapkwZxIIV3LZ2dnExcVRo0aNsm6KKGFKKeLj41m0aBFjxoyhevXqj+xg5+XlsWzZMjIyMnj99dfNslCUwWDgxx9/xMHBgSFDhhSo0JtSCr1ez6FDh/jggw/w9PTkH//4B3Xr1pU0aAH8t/Pt6enJ22+/TX5+Pp9//jkpKSml2glXSrFz504aNWqEp6en2Z17hWFjY8Pw4cMJDQ3ls88+Iz4+/rHBsI2NDS+99BJVq1Zl9uzZZGVlSQBUiTk4OPDss8+yfPlyGRUWT9SrVy+2bdv2VNk8Op2O5s2bSzX7SkJ6fpWYUoqrV68SEBDw2EJJovxTSpGRkcFXX33FgAEDqFu37iM71zk5OXz77bfodDpeeeUVbG1tza4jbjAYWLduHVlZWYwYMQIrK6sn/o5WDOvLL7/kwIEDTJ06lQEDBpjl9xNlSxudHD16NK1bty7QkkDFRctWOHDgAL169aoQx6alpSV9+vShV69efPbZZ9y5c+ex29La2poXXniB4OBgZs6cSXp6unRIKymdTkfjxo2xtraWwlnisXQ6HSEhIWRlZREbG/tU7xUSEkJUVNQTp3SI8k8C4Uru6NGjNG/evEJ0tsSj6fV6vv/+e5o1a/bINHitaNTixYtxdHRk5MiRZrlci9FoZNeuXdy4cYOXX365QPN58/Ly2L59O59++iktWrRg6tSpjx0RFwL+G8B17tzZNG/49OnTpTIq9euvv9KmTRvc3d1L/LNKi4WFBW3btmXEiBHMmjWLK1euPDaosbKyYtCgQYSHhzNz5kySk5MlCKqkrKyseP75500PP4V4FEtLS9q3b8/evXuf6nrh6OiIp6cnt2/fLsbWCXP05GEUUWHl5eVx584dXnjhhbJuiihBRqORzZs3Y2trS/fu3R+ZApybm8tXX32Fr68vzz77rFkWT1NKcezYMXbv3s2MGTNwdHR84s9HRUWxbNkynJ2def/99yvtPGCj0UheXh65ubmmP7X/zsnJITMzk4yMDLKyskx/r9fr//AyGo0PpZ3p9fpKEaCkp6czZcoUQkND8fT0LLFU+tzcXPbt20ebNm24cOFCiXzGo+h0OiwtLR/608rKCltbW2xsbEwvOzs7XF1dcXV1xd7eHltbW2xtbbGzs8Pe3h4bG5s/Pce05ZXeeOMN5s+fz4svvvjY9b4tLS3p3bs3dnZ2fP7550yZMgUPD49Kef5Wdn5+fjRo0IBt27YxcOBAOQbEn9KqPu/YsYPMzMzHrojxJM2aNeP48eOPzaAT5Z8EwpWUUoobN27g4eHx2KrBonxTSnHy5EkuXrzI1KlTHxnc5uXl8fXXX+Pr68vgwYMLlGpc2pRSXL58mVWrVvHOO+9QpUqVx/5sfn4+v//+O3v37mXo0KE0a9YMCwuLCnNDezD41EbzU1JSTK/4+Hji4+NJT083BbgGgwGlFDY2Ng8FN/b29jg6OuLk5ISDgwOurq7Y2NhgZWX1h5eFhYUpSIL/jvRVlvnVOTk5/PDDD9jb2zNkyJASOU9+/PFHXn/9ddq0aVPs7/0kSinTMaL9qdfrH3qAoj04uXv3LufPnycrK8v071qlZ1tbWxwdHXF2dsbT0xM/Pz/c3d1NwXNQUBDTp09n1qxZZGRk0KFDh0ceQ5aWlnTp0gVbW1s+/fRTpk2bhpeXV4U5j0XB6HQ6BgwYwL///W/atm1LtWrVyrpJwkw5OTkRHBzMuXPnaN26dZGuFTqdjtDQULZv305eXp6sJFGBmV9vV5SaY8eOSVp0BaaU4s6dO6xdu5apU6c+ch54Xl4eS5cuxdXV1ayD4KioKJYsWcIbb7xBtWrVHnncKqWIiYnhm2++wcPDg7/97W9UqVKl3B7nWsBrMBjQ6/UkJiYSGxtLbGwst27dIjk5maysLIxGI/b29qZgw9PTk0aNGuHk5GR62dvbY2dn98RtUV63VUlTSvGXv/yFJUuWsG3bNl566aVinWMeGxtLSkoKAwYMMOu6DY/KAFBKkZWVRUZGhukVHx/P1atXSUpKIjU1lezsbKytrXFxcaF69ep88cUX3Lt3j759+2JnZ2d6yPLgNrWwsKBdu3amYHjy5Mnlbkkp8fScnZ3p1asXa9euZdy4cQUqkCgqp06dOvHzzz/TsmXLIh8nrq6uWFtbk5CQQPXq1Yu5hcJcmF+PV5QKvV7P1atX6du3b1k3RZSQ9PR0vvvuO0aNGvXIdEJtiSRLS0teeOEFsw2CU1JS+OqrrxgxYgSBgYGPnOOcn5/Prl272LFjB8899xzNmjUrd50lpRS5ublkZ2cTFRXFrVu3uHnzJnFxcej1ehwdHfHy8sLb25uOHTvi5uaGo6MjDg4OUvirhGlFtF599VVWrVrFvHnzGD9+PE5OTk+93bUpDD169MDOzq6YWlwyHvVddTqd6aHLn1FKkZOTQ0ZGBmlpady9excXFxe2b9/O4sWLadasGZ6engQGBlKzZk1q1KiBk5MTNjY2WFhY0Lx5c2xsbJgzZw4TJ06kZs2acrxXIjqdjnbt2rFv3z4iIyMJCQmR/S/+QKfT4efnh9FoJCYmBj8/vyKPCjdo0IDz58/j6+srx1oFpXvC3K6KP/Grkrpx4wY///wz7733npzcFZBer+fbb78lMDCQbt26/ek+1uv1rF69mtTU1AIXnSptWlD45Zdf0qxZM7p27fqnKZRKKe7du8fSpUtxcnJi+PDhuLm5lYtj22g0kp6eTmJiIhEREVy/fp179+5hYWGBt7c3NWrUICgoCG9vb9N8zIqU4l1e6fV6fv/9d06dOsUbb7zx1MdbdHQ08+bN4+9//7tZjwaXhKysLBYtWkRubi59+/YlJiaG27dvExUVhV6vx8PDg+DgYOrWrUu1atW4c+cOP/zwAxMmTCA4OFjOhUpEKcWFCxfYuHEjM2bMMMtaFqLsKaXYt28ft2/fZuTIkUW+RkRGRvLLL78wbdq0cvdQXTzkF2DIn/2D+Q3/iFJx5swZwsPDpQNRASml2L9/P3q9nk6dOv3pPjYajWzZsoX79+8zYcIEswyC4b/pwMuWLSMgIIAuXbr8aRBsMBg4cOAAGzZsYPDgwaZUKHM9trVRsejoaC5cuEBERASpqam4urpSu3ZtunbtSkBAAHZ2dlhZWZnt96jsrKys6NOnD05OTsycOZPJkyfj4eFRpPcyGo1s2rSJnj17mv1ocElwcHBg4sSJrFixgm3btjFhwgR69OiBXq8nNzeX6Ohorl+/zpYtW4iPjzel+L/77rv861//on79+nKeVBI6nY569eqxbds2Tp8+LdO7xJ/S6XSEh4ezdetWsrKynlhY81GqV69OSkoKWVlZODs7F3MrhTmQQLgSMhgMXLhwgbFjx5Z1U0Qx0+YF7969m2nTpv1pqrMWKJ87d46pU6eabRCspYpmZmby8ssv/+FprLbe6rJly8jKyuK9994zy4qySilTeveFCxc4fvw4cXFxuLu707BhQ55//nn8/Pz+dG6kMG8WFhZ07NgRGxsbPv/8cyZPnlzoQk7anPY7d+4wevToSrv/ra2tGTlyJL/88guzZ89m0qRJODk5YW1tTZ06dahduzZ9+vTBYDBw//59rl27hqOjI9OnT6dOnTq0adOGsLAwatasaVr2rbJuy4rO0tKSwYMHs2jRIsLCwsz2HibKlrOzMyEhIZw6dYr27dsX6T1sbGyoXr06N27coFGjRnJNqYAkEK6EkpKSyM3Nxdvbu6ybIopZZmYm3333HSNGjPjTqspKKc6ePcvWrVt5++23i/yUtKRpyySdOnWKd95556H1jLXA8vz58/z444906tSJHj16mFWKnFZ1NyEhgWPHjnHmzBlyc3MJCQmhV69e1KxZEwcHB0A66+WdTqejdevWWFtbM2vWLN54441CrVGtlGL9+vX06tWrUo4Ga7QlmwYPHszmzZtNyyVphe607WllZUX16tXx9fWlY8eODBkyhA8++IDo6Ghu375NUlISnp6eNG3alNDQUFxcXMw6Q0QUnk6nIyAggKCgIHbv3k3Pnj1l/4o/0Ol0dO7cmeXLl9OmTZsipTZbWFgQHh7O6dOnadSoUQm0UpQ1CYQroatXr1K7du1Ks+RJZWEwGFizZg3NmzcnJCTkD/+uLZn1888/M2nSJFxdXUu/kQWglOLmzZumatdawKjJycnhl19+4cqVK7z22muPLJ5V2pRSGI1GkpKSOHnyJMeOHUOv1xMeHs5LL72El5fXI9dXFeWbTqejWbNmWFtbM3/+fF577bUCVzWOiYkhJiaGsWPHyrHBf0f7+vXrh729PZ999pkp5fx/t432/7Vq1eKf//wnCxcuZNSoUdSsWZOoqCiOHz/O9u3bsbOzIywsjCZNmuDp6Ym1tbVs5wrAwsKCgQMH8umnn9K6devHLqcnKq+AgAAMBgNRUVHUqFGjSO9Rp04dfv31V/R6vVk9cBfFQwLhSsZoNHLq1Ck6d+5c1k0RxUgb6U1MTGT48OF/6OgppUhISGDJkiW8/PLLZlsBUUshXrx4MaNGjXoozVRbQumbb74hODiYd999FwcHhzL/HtqSMZcuXWL37t2kpKQQFhbGSy+9hLe3t3S8KwmdTkdYWBhWVlYsXLiQ119//YnVSpVSbNiwoVxUii5NlpaWdOvW7aFg2MfH50+3pU6nIygoiIkTJzJ//nxGjBhBWFgY9erVIy8vj7i4OE6ePMnixYsxGo2Eh4fTvHlzvL29ZaS4nPPw8KBly5b8+uuvDBs2TPal+AOdTkebNm04dOgQAQEBRTpGqlSpgo2NDfHx8fj6+pZAK0VZkkC4ksnOziY6OpqgoCC5aVQQ2lzZDRs28Nprr/3pvOCcnBwWL17MgAEDqF27ttnu+7y8PBYtWkSXLl1o0KCBqZ1aQayNGzfywgsv0KRJkzLNaNCq7d+7d49du3Zx9uxZqlevTt++fQkJCSlXwe8TVg4QhdSgQQOGDRvGvHnzeOutt/Dx8Xnkz2pzg7V6DeVxX5TUcf7g2sEzZ87krbfeeuSDBZ1OR82aNZk0aRKzZ89mxIgRhIeHY2tri7+/P35+fvTr14/4+HiOHTvGokWL0Ol0NG/enJYtW+Lp6Vmi30WUnF69evHBBx/QuXPnQs/PFxWfdp5/+umnZGdn/yHDrCAsLS2pX78+58+ff+QDOVF+yfJJlczVq1fZvHkzkydPltToCsJgMPDtt99Sq1atP60SbTAYWLp0KW5ubgwcONBs97vRaOSHH37AYDAwevRoLC0tUUqRmZnJDz/8QHJyMuPGjSvTglja3N/IyEi2bNlCXFwc7du3p02bNqZUc3O4SWrXdW0+tdburKwsMjMzyczMNP13dnY2WVlZZGRkkJGRQXZ2Nvn5+RgMhodeRqMRg8FgSgHXGAyGsvqaZksrWpeUlERQUNAj5+tfvnwZW1tbgoODy6CVf067PmijpRYWFlhbW2NlZWV62draUqVKFVxdXXFycsLBwQEnJydcXFyoUqUK9vb2piW+tPOhqOeFlu2ybNky3nzzzceuHayUIjo6mpkzZ/Liiy/StGnTP82O0QqUHTp0iNOnT+Ps7EzHjh1p3LixWWSZiIJTSrFr1y4iIyN55ZVXzPb+JsqO0Whk3rx5dOrUidDQ0CKd39evX2fNmjW88847cn0on2T5JPHfG8apU6cIDw+Xm0UFoZTi5MmTZGVl0a5duz/t9O3YsYPMzExGjRpltvtdKcWBAwe4c+cOb7/9tikIvnXrFosWLaJ58+aMGTOmzKqDKqXIz8/n3LlzbN68GUtLS3r27EmjRo3KLKVVC271ej16vZ60tDTi4uKIj48nMTGRhIQEUlJSyM3NNQW2NjY22Nra4uDggIODA46Ojtjb2+Pg4ICvry9OTk7Y29ubAh9LS0ssLCywtLQ0/bcWHD0Y4JjrcVXWLl++zE8//cSrr76Kl5fXQ/8WGxvLV199xV/+8peHisGVpQcfcmgPOB48xrRXbm4uKSkppKSkEBsba3qQkp6eTlZWlmkunY2NDa6urnh7e+Pp6YmHhwfe3t44OzubguonVUrXUs7HjRvHnDlzGD9+PHXq1HnkyLCfnx/Tp09n5syZAH8IhrXP8/Pz47nnnmPgwIFERkayb98+NmzYQEhICF27dsXf31+WLysHtNTXXbt2ER0d/cTpCKLy0ar779u3j4YNGxbp+PD19SUlJYXMzEycnJxKoJWirEggXIkYDAYuXbpE165dy7opopikpqayadMm3njjjT8UcdAqKx85coSpU6eabZEHrTjWpk2bmDFjBra2tuj1evbu3ctvv/3G6NGjadCgQZkFW7m5uZw9e5bNmzfj4uLCiy++SFBQUKnNL3xwNDcjI4OYmBiioqKIjY3l3r175OXlAf9di9XDwwMPDw+qVatG/fr1cXd3x9bWFhsbG6ytrU0BrnQUS4e2pvWPP/7IW2+9hbu7OzqdDqPRyJo1a+jbt69ZLvlVVNoDo7y8PPLy8kwBc2xsLPHx8Vy5coX4+HhycnLQ6XS4ubnh4+ODn58fgYGBVKlSBQcHhz9MLdDWjp04cSILFixg9OjRj13KxMfHhylTpjB79mzgj8Hwg+9rY2NDvXr1qFu3Lunp6Zw5c4bly5djMBjo0KEDTZs2xcXFpcLso4rIzs6OPn36sHbtWiZNmiT7SvxB7dq1Wb16NWlpaUUqFGpvb4+3tzc3b94kNDS0+BsoyowEwpVIUlISFhYWZlstWBSO0Wjkl19+oWPHjlSrVu0P/x4fH8+qVat47bXXzPoJZlpaGosXL+all17Cw8ODzMxMVqxYQXJyMu+++y5Vq1Ytk46NXq/nzJkzrF+/Hjc3N0aPHk3NmjWLtARDYRgMBlJTU4mPjycyMpLbt28TGxtLXl4eDg4O+Pj4UL16dVq3bo2vry+Ojo6m0bUHR2pF2dOqSefm5jJv3jymTJmCs7MzCQkJXL16lRdeeKFC7S8tsHxwhNvHx4d69eoB//dQJz8/n/z8fOLj44mOjiYqKorDhw+Tnp6OTqfD09OTGjVqULduXTw9PXF1dcXKyorg4GAmT57MnDlzTLUCHhXg+vr68uabbzJ79mx0Ot0jf/bB33FxcaF9+/a0bt2amJgYdu3axa+//krDhg3p1q0bvr6+kv1ghrTzbNu2bdy4cYPg4OAKdV6Jp2dnZ0eDBg04efIkXbp0KfTxodPpaNy4MWfOnJFAuIKRQLiS0EYH69Wr96fFlET5opQiIiKC+/fvM2rUqIcu6kop8vLyWLZsGQMHDjTrCtF6vZ5vv/2Wdu3aUa9ePaKioli4cCFNmjThpZdeKpOiU0oprl+/zsqVK7GwsODll18mMDCw2DvA2jxeg8HAvXv3uHnzJpcuXSIqKgq9Xk/VqlUJDg6mVatW+Pn54erqioWFhakd5rhPxR9pqZtZWVmmAlpbt26lQ4cO2Nvbl3XzSpVOpzM9tLG3t8fFxYXg4GDTvF2j0UhmZibR0dHcvHmT33//nfj4eHQ6HV5eXjRo0IDg4GBThWij0UizZs0eGQxXr16dyZMn88UXX6DT6QgPD3/ieaPT6bC2tqZGjRq89NJLZGZmcvDgQebPn4+rqyu9e/emfv36UnHazNjY2DBgwADWrFnDjBkzZN+Ih+h0Otq2bcv3339Pp06divRAu06dOuzatQuDwVDiD8RF6ZGIqBI5deoUAwcOlBtEBZCTk8OaNWsYOXLknz7Y2Lx5M76+vk8cBSlrv/32G5aWlnTv3p1jx46xcuVKRo0aRVhYWKmPvGhLTP3888/ExsYyZMgQUzuKaxtqI2LJyclERERw9uxZYmJisLW1pWbNmjRp0oSBAwfi4eEhAW8FYmFhQbdu3cjKymLmzJkkJSXxr3/9S/bt/0+bt2thYUGVKlWoUqUK9erVo0+fPiilSE5OJioqikuXLnH48GEyMjLQ6/W8++67/PWvf6Vt27Z/Ot9YGxmeNm0aX3zxBUCBguEHf9/JyYkePXrQpUsXLly4wObNm1m1ahW9e/emadOm2Nrayn40AzqdjkaNGrF582YuX75MgwYNyrpJwsz4+PiglCI2Npbq1asX+rytVq0aBoOBxMTEP83CE+WTBMKVRHZ2NomJibIGWgWglGLnzp2EhIT8oYKqUooLFy5w5coVs64Mro1oHzx4kGnTprF27VoiIiKYMWMG3t7epdqxVEqRk5PDrl272LVrF7169eLVV18ttsJcSimys7OJiori5MmTXLp0CQsLC4KDg2nfvj3+/v6m0V5RcVlYWNCvXz+OHTuGwWCQdYOf4MFibFWrVqVq1aqEhYWhlCI9PZ379+9z+vRpFixYwKJFi2jVqhVhYWE0aNAAV1dXUzaJFgw/OGe4MMGw1gZra2vCw8Np1KgRt27d4tdff2XTpk107tyZtm3b4ujoKAFxGbOysmLIkCH88ssv1K5d22zrYoiyYW1tTcuWLTl48CBDhw4t9O9bWFgQGBjIjRs3JBCuQCQQriRu3ryJl5dXkdZQE+YlLi6Oo0eP/mn6V2JiIitXruT11183632dnJzMt99+y3PPPWda2untt98u9aVLjEYjV65cYcWKFfj5+fH++++bCho9DaUUWVlZREZGcujQIW7fvo27uztNmjSha9euuLm5SdGqSig7O5vc3Fx8fHzYuHEjgwYNkhS7QtLm8rq4uBASEkLHjh358MMPsbOzIzY2lj179qCUol69ejRt2pTq1avj4OCAn58fb775JnPnzjXN9yvK+WdpaWlKz7537x6///47//rXv+jYsSMdOnTA2dlZzusyVLduXaysrLhw4QLh4eFl3RxhZsLDw5k9ezbPPvtskR6UNG7cmJMnT9KyZUs5zysIWUe4kli+fDk+Pj506dKlrJsinoLRaGTRokU0atSINm3aPHQhzs/PZ8GCBTRv3pzWrVub7UU6Pz+fuXPnYmNjw+3bt+nZsyedOnUq9bnrmZmZ/PLLL0RERDBy5Ehq1679VEGJVjE3MjKSAwcOcP36dby9vWnbti3169d/aG1VUTlt3ryZxMREnnvuOebOnUvTpk3p2rWrHBNPQZvS8OWXX9K9e3fatm1Lamoq586d49SpUyQmJhIQEEDr1q0JCQkhKSmJOXPmMGLECMLCwp562xuNRpKSkvj11185f/487dq1o3PnzhIQlxGlFFevXuXnn3/mvffeM5ulyYR5UErx6aefMmjQIGrXrl3o309LS+M///kPf/vb3ySrp3yRdYQrM6PRyNWrV+ncuXNZN0U8BaUUkZGRJCUl0bx58z+kRB88eBA7OztatWplth0wpRRbt27l2LFjeHt7M2HChEeuCVpSn6+lZS9btozGjRubbmhFaYP2IDEhIYGDBw9y5MgRqlSpQvv27Rk2bJipWre57g9RerKysti7dy9vv/029vb2TJgwgc8//xxXV9dHLu8jnkyn0+Hh4cG0adOYOXMmBoOBrl270qVLFzp37kx2djaXLl1i3759/PTTT1SvXp22bduyaNEiJkyY8NhlmArCwsKCqlWrMnLkSJKSktiyZQv/+te/6Ny5M127di3ytUUUjU6no1atWtjb25tGhWX7C41WvPDgwYOEhIQU+thwdHTE1taWpKQkmWpYQUggXAkkJiai1+vx8vIq66aIp2AwGFi9ejXPPvvsQ0+5lVLcv3+f3bt3M3XqVLOda6oF8p9++imtWrXi7bffLtU1VJVS5Obmsm7dOi5cuMDYsWOLdCPU3kuv1xMREcHWrVtJSEigWbNmTJ482XSeSedLaJRSHD16lODgYDw9PU3pvRMnTuSLL77A1dVVlnx5Cto84qlTp/Lll19iMBjo3r07FhYWODo60qxZM5o1a0ZWVhZXr17lwIEDZGZmMnnyZP71r3/RsmVLbGxsirz9td/TAuI+ffqwYcMG/v73v9OnTx/atGnzVO8vCsfS0pJBgwaxfPlyGjZsKKPC4iFhYWH89ttvZGdnF3oKmYWFBXXr1uXixYv4+PjIOV0BSCBcCVy/fp2goCCzDZBEwRw/fhwXF5c/pPPk5+fz008/MWDAAFxcXMqodY+nlCIxMZH/9//+H4MGDWL8+PHY29uXahAcExPDN998Q0BAAO+9916RitsopcjMzOTEiRPs2LEDZ2dnevbsSZ06dWTkRzxSbm4uO3fuZPz48aa/0+l0eHt7M27cOBYvXsy0adNMQbIomqpVqzJt2jRmzZqFwWCgV69eD01HcHR0JDw8nMaNG5OWlsbJkyf57LPPcHNzo0+fPrRv3x4vL6+nmqahjVCPGTOGmJgY1q9fz/bt2xk4cCDh4eFSwKmUBAYG4uzszLlz5yTjQjzE2dmZatWqcePGDRo2bFio39Wqk//2228yraWCkEC4glNKcebMGVq2bFnWTRFPISsriy1btjBx4sSH5rEqpdizZw+urq7FMt+tJCiliIqK4v3336ddu3aMGTOmVDuDBoOBgwcPsmHDBp5//nmaNm1a6LnASinS0tLYvXs3hw4dolatWrz66qv4+vrKutziiS5evIirq+ufLtkREhLCwIED+eqrr5gyZQrOzs5l1MqKwc3NzTQyDJiC4QfpdDqqVKlC586dCQgI4JNPPuHevXssXLgQOzs7OnToQOPGjZ9qnq+2jvGECRO4c+cOK1euZPv27QwdOpTg4GB5MF3CrKysGDBgAN9//z1hYWHyAEI8pG3bthw8eJAGDRoU+hz39/cnLi6OnJwcsy5KKgpGrsQVXE5ODnfv3i1yCqgoe9r83+DgYLy9vR/6t/v377N//34GDx5sltVnlVKcP3+e1157DRcXF0aPHl1qHRJtWaTly5ezb98+3nnnHZo3b16o7aQFwOvWrePf//43GRkZvPPOO7zyyiv4+/tLECyeSK/X8/vvv9OvX78/vQbrdDpatmxJo0aNWLZsGfn5+WXQyorFxcWFyZMnc/ToUbZt24bRaPzTn9PpdAQHBzNjxgxu377NiBEjGDZsGBEREfz73/9m2bJl3L17F6PRyBMKiz6SpaUlgYGBTJ8+nd69e/Ptt9+yaNEi4uPji/yeomACAwOpUqUKZ86ckW0tTHQ6HQ0aNOD27dtkZmYW+vft7Oxwc3MjNja2BFonSpsEwhVcQkICDg4OODo6lnVTRBFlZmaye/du+vfv/9Df6/V6fvrpJ5555hmzG0VSSmEwGNi5cydz587F2dmZ999/v9jW5i3I5yclJfH5559jNBqZPn16odJOtbV/N2/ezD//+U+ys7N5//33GT58OFWrVpXqz6JAlFLcvHkTg8Hw2DnA2hrD1tbWrF279pGBmygYbcR3ypQpHDp0iG3btj0yENLpdISEhDB+/Hi++uorLC0tGTduHH/729/w8fFh4cKFfPzxx5w8eZK8vLwiB1RWVlaEh4fzz3/+k6CgID7++GM2b95MTk6OBGklxNLSkgEDBrBx40YMBkNZN0eYETs7OwICArhy5Uqhzz9tnvClS5fk3K0AJBCuwLTRuPr160unvZxSSnHgwAEaNGhA1apVTftRKcXJkyexsLCgSZMmZrd/tXnLhw4dwtfXlzFjxuDr61sq7VRKce3aNT7++GPatm3LyJEjCzV/Ny8vj0OHDvHPf/6TuLg43n//fV588cViWV9YVC5KKbZs2UKvXr2emD1gZWXFyJEjuXr1KocPH5YO1lPS6XS4uroyZcoUDh48yPbt2x87MlynTh1eeeUV5s6dy+3bt3F2dqZHjx7861//YuDAgezbt49//OMfbN++nfT09CLtH51Oh62tLT169OCvf/0rsbGxfPDBB5w/f14CtRISFBSEo6Mj586dK+umCDNiYWFB27ZtOXToUKHPZZ1OR8OGDbl48aJcpysACYQrMKPRyMWLF596eQhRdjIyMti/fz+9evV6aB+mpaWxZcsWhg0bZnZzzTIyMliwYAFZWVm0aNECR0dHOnXqVCrHoNFo5PDhwyxZsoTx48fTqVOnAqdCG41Grly5wkcffcSxY8eYOHEiL7/8cqlWthYVh1KKe/fuERcXR2hoaIGOIQcHB8aPH8+GDRu4ceOGdLKKgTZn+MCBA08Mhhs0aMBLL73EvHnzuHv3LgDW1tY0aNCAyZMn88YbbxATE8MHH3zAzz//TFxcXJEDYnd3d1555RVeeukl1q9fz4IFC4r8fuLRLCwsGDhwIJs2bZJpB+IhwcHBxMbGFik92tPTk5SUFPLy8kqgZaI0mVcPWhSr7OxskpOTqV69elk3RRSBVggrLCwMd3d3098bjUY2bdpE69atqVatmtkEaUop4uPj+eKLL6hRowb9+vVjx44djB49ulTm0ur1ejZt2sT27duZOnUqtWrVKtC20dKolyxZwvfff8+QIUN48803CQgIMLuHDKJ8+f333+ncuTN2dnYF/h1PT0/Gjh3L4sWLSUpKKsHWVR4Pjgzv2LHjscFwaGgow4cPZ+7cucTExJgCUwsLC6pXr87o0aP5y1/+gqOjI5999hlLlix56OcKw8LCgpCQEN555x3q1avHf/7zH7Zv3y6d62IWEhKCtbU1ly9fLuumCDNib29PYGAgly9fLvT56+joSNWqVU0PzET5Jb28CuzOnTt4eXmV2rxMUbxycnI4dOgQXbp0eSgl+s6dO0RGRtK5c2ezCoLv3LnDZ599RpcuXejbty8//PADzzzzTKkE67m5uSxdupQbN24wbdq0An2mthbw3r17+fDDD/H29uZvf/sbDRo0MMvCY6J8SUtL49KlS7Rs2bJQx79Op6N27dr07NmTb775RuaQFoMH06T379/Pzp07HztnuHHjxgwbNoyZM2f+YZRWe6/+/fvzr3/9i4CAAGbNmsW8efO4c+cOSqlC7S8tXbpr16689957XL58mU8++YRbt27Jfi8mMios/oxOp6NVq1YcOXKk0L8r84QrDgmEKyhtfnDDhg3NJlgSBaeU4tChQ9SpU4eqVaua/t5oNLJ69WoGDRpkNg84tGNtzpw5jB49mnbt2rF//36srKxo06ZNiR5/SimysrJYsGABlpaWTJw4sUDrAz84en38+HFmzJhBv379ZC1gUSy0bI7w8PAiFbLT6XR06NABb29v1qxZIx2tYvBgMLx371527Njx2GC4SZMmDB06lM8++4yEhIQ//KxOp8PBwYHu3bvz73//m7CwMBYsWMD8+fOJiYkpdMEznU5H1apVmTRpEn379mX+/PmsW7eO3Nxc2f9PSXu4ZDQauXbtmmxPYRIYGEhsbCzZ2dmF/t369etz6dKlEmiVKE0SCFdQ2nzHevXqSce+HMrPz2fXrl306NHjodHgs2fPYm1tbTYF0IxGIwcOHGD58uW89dZb1K9fn/j4eLZs2cLIkSNLNCVaW9po1qxZBAQEMHLkSGxsbB67XZRS5Ofns3v3bj799FNatWrFlClT8PLyMovtKSqG7Oxs9u/fT/fu3Yt8XFlaWjJ06FBu3brF0aNHpfNeDLS5uVOnTmXv3r3s2rXrsWnSLVq0YODAgcycOZOkpKQ/3QfaiG779u35xz/+QcOGDZk7dy6LFi0qdECs0+lMBRD/+te/kpSUxIcffsitW7ekkvhTsrS05JlnnmHTpk2yLYWJo6MjAQEBRUqP9vHxISUlpUhBtDAfEghXUNnZ2eTk5ODm5lbWTRFFcPr0aXx8fPDx8TH9XW5uLuvXr+fZZ581i/Vr9Xo9v/76Kzt37mT69On4+/tjMBj48ccf6du3L56eniX22UopEhMTmTlzJs2aNWPgwIFP3CZKKVJSUpg/fz6nT59mxowZdOjQwSy2pahYTp06RY0aNZ76HLC3t2fcuHGsXbtW5qIVI3d3d6ZMmcKuXbvYu3fvY4PhNm3a0KNHD2bNmkVKSspjR5Ht7e3p2LEjf//736lTpw6zZs3ihx9+IDExsdDp0lWqVOHll1/m2WefZeHChaxfv1463E9Bp9NRr149srKyuH37tjxYEsD/pUcfPny40L9rb2+Pu7s7UVFRJdAyUVqkB1hBRUZG4uvrW6giLcI85Ofns3XrVkaOHPnQaNKePXsIDg7G39+/DFv3X/n5+axatYqYmBimTZuGk5MTAEePHiU3N5eOHTuW2AirFgR/+eWX9OrVi7Zt2z6xqJVWQX3ZsmV069aNrl27YmVlJaPAwkQphdFoxGAwmNbBNhqNpldBaQ+InnvuOVJTU5+6Xba2tvTv3585c+Ywbdo07O3tn/o9H8XCwgJLS0usra2xtrau0OeHFgzPnDkTKysr2rVr96ff18LCgo4dO5Kfn8+sWbOYNm0azs7Oj9w2Wsp0586dadmyJTt37uSjjz6iTZs29OzZ03StLAhLS0vCwsIIDg5m5cqVfPrpp4wdO5bq1atX6H1TUqytrenVqxebNm3izTffLOvmCDMREhLCypUrycrKwtHRscC/p1Wav3jxIrVr1y7BFoqSJIFwBaSU4sKFCzI/uJyKjIzE0tKSGjVqmP4uNTWVPXv28M4775TpPlVKkZuby3fffYdSikmTJpnmKqekpLBu3TqmTp1aYsWmlFIkJCTw+eef88wzz9C6devHBsFaKvSGDRs4deoUr7/+OoGBgXJeVFAPjvJoxdDS09MfeiUlJZGYmEhGRga5ubkPvbQg+M/er6Di4uK4c+cOubm5xXacKaW4desWI0aMIDQ0tMSzGHQ6HdbW1jg6OuLq6kqNGjXw8/PD398fV1dX0zlXns8jbU7u5MmT+eKLL7C2tn5kYTMLCwu6du1KXl6eKRh+UodZp9Ph6OhI//796dChA5s2beIf//gHzzzzDG3atCnwgzidToeTkxNjxozh5MmTfPnll/Tu3du0NFx53gelTSuEtmHDBmJjY/H19S3rJgkz4OjoiK+vL9euXaNx48aF+t169eqxevVqlFJyLpZTEghXUFevXqVTp05l3QxRSEajkR07dvxhbvDOnTtp3rw5rq6uZdq+rKwsFi5ciJeXF8OGDTN15oxGI2vWrKFjx474+PiUyA1BKcX9+/f58ssvGTRo0BOr8SqlSE1N5ZtvvsHJyYm//vWvODg4yM2qnNOq8hoMBgwGA+np6cTFxZGQkEBcXBzR0dGkpqaSnZ2NwWDA2toaBwcHnJ2dcXZ2pmrVqgQHB+Po6Iitre1DLxsbGywtLbGwsDCNjmr/XRBGo5G5c+fy5ptv0rRp02L93nq9njlz5tCoUSO6detWrO+tMRqN6PV68vPzycrKIjMzk5SUFO7cucOBAwe4d+8eRqMRPz8/wsPDqVevHs7OzlhYWJTL80qn0+Hp6cmUKVP4/PPPsbS0pFmzZn/6XSwtLenduzd5eXnMnj2byZMn4+DgUKDPcHV1ZcSIEXTt2pWVK1eya9cuXnjhBUJCQgq07XQ6HTqdjmbNmhEYGMjSpUs5e/YsY8aMwdXVtVxu+7JiZ2dH165d2bJlC6+88opsO4FOp6N169YcOXKEsLCwQh0Tfn5+JCcnk5GRUaTCiKLsSSBcAaWmppKfn1+iczRFyUhMTCQmJobQ0FDTxTglJYUTJ07w7rvvltlN+8H5tQ0aNKB///6mUSmlFFeuXOHOnTuMGDGixILguLg4Zs2axZAhQx7ZWX3w52/cuMHixYvp1KkT3bp1k7nA5ZDRaDSN1iYmJhIVFUVMTAxRUVGkpKSg1+uxs7PD3d0dDw8PqlWrRv369XF1dcXe3h47OztsbW1LLVBLSEjg/v37NGjQoNg/z9rampdffplPP/2UoKAggoKCiv0zLC0tsbS0xNbW9qEU3vDwcNPDh5SUFO7evcvp06fZtGkTTk5OtGrVivDwcKpUqVLu1t7W6XR4e3szdepUZs6caSpW9ahgeMCAAeTn57NgwQJef/31AgXD2uf4+vry5ptvcunSJVasWEG1atUYOnQonp6eBR4d9vDw4K233mL37t18/PHHjBgxgoYNG5a77V5WtHnf27ZtIyEhQfpJAvhvBei1a9cWOj3axsYGd3d37t+/L4FwOaV7QuqXVBMoh06fPs2hQ4d4/fXX5WlnOaKUYu3atVhZWfHMM8+g0+lQSrF69Wrs7e3p169fmexPbamhuXPn0rFjR7p06fJQpys3N5cPPviA4cOHl0iV8gfnBPfr149WrVo99jOMRiOHDx9m3bp1jBkzhrp160onsRzQ6/VkZGSQlpbGnTt3uHnzJtHR0aSkpGBpaYmrqyvVq1fH19cXPz8/qlat+tAobllf65RS/PTTT/x/7J13WBRn1Pbv2ULvvXdBQFDEgogFFSto7GKJomLBgt2YxLyJKa+xd2PXxN67Yhd7A1QQpffe27J1vj/yzb4Sigss7C7O77q8EtfdnbMzs7PPPeec+2hqarbYd5UkSXz48AHHjh3DqlWroKGhIdObY1wuF5mZmXj69Cnev38PGxsb9O/fH3Z2dmCz2TKJq6mQJImsrCxs2rQJkydPRqdOnerdtwKBACdPnkRhYSFmz57daC8Oat89fvwYN27cgK+vL/r379+o8W0kSSI5ORkHDx5Ep06dEBAQ8EXXfJp/IUkSly9fRmVlJQIDA+l9RgOSJLFlyxYMHDgQrq6ujXrdlStXQBAEAgICWjBCmmZyDsCYuv6BFsJtDJIkceTIETg4OMDHx0fW4dA0Ag6HgzVr1mDZsmXi2cFFRUXYsGEDVq1aJZO7jSRJIjs7G1u3bsU333yD7t271xCV1I9ATk4OZs6cKXXBSZU3b9iwAQMHDoSPj0+D2xAIBLh8+TLevXuHefPmwcDAgF7kyBGf/96UlZUhNzcXiYmJSEhIQG5uLvh8PjQ1NWFlZQUbGxtYWVnByMgIbDZbLHbl9XhWVlbi559/xqpVq6Cnp9di26EW8RkZGZgzZ06L9eM3NiYOh4O3b9/i1q1bAAB/f3+4u7srlCkdSZLIyMjA5s2bERQU1KDPBp/Pxz///IPq6mrMnDkTSkpKTdpeSUkJTp8+jbS0NEycOLFRo/FIkkRlZSWOHz+OvLw8zJkzB/r6+gqzv2VJWVkZ1qxZgx9//FHmLUc0sockSTx58gQJCQmYOnVqo75DcXFxuHLlChYvXkzfdJdfaCH8tSAUCvHLL78gJCQEJiYmsg6HRkJIksTr16/x8uVLzJ07FwwGQ5xh0tXVxeDBg1t9cUOSJNLT07F9+3ZMmjSpzt6ZnJwcrFu3Dj/99FOLLCYqKirw559/om/fvvD19a33R4bKsBw5ckS8MKX7gWUP1c/L4/GQmZmJ5ORkfPr0CTk5OeDz+dDT04O9vT0cHBxgZmYGPT29GsdYUY4fSZK4f/8+EhISEBwc3OJx8/l8bNq0CV27doWvr6/c7CfKeTs+Ph6XL19GRUUFRo8eLS7dlZc4G4IkSaSlpWHLli2YNWsW2rdv36AY3r9/P9hsNqZOndqkLDj1HYmLi8M///wDa2trTJgwoUFn6v8iFArx5MkTXLx4EUFBQXB1daUX5F+AJEkcO3YMurq6GDp0qEKcmzQtS0lJCdavX4/Vq1c3qsqDSmKsXr1a4lYJmlanXiFMN821MYqKiiAQCOi+FwWDJEk8ePAAQ4cOFS9gysrK8P79e6xatUomIjgpKQm7du0SL6z+G4NQKMTp06fh7+8PbW1tqcfA4XCwY8cOdOvWrUERDADl5eXYvXs3LCwsEBQU1KTsDE3zoVy6q6qqxKI3ISEBFRUV0NXVhbW1Nby9vWFqagp9fX2FK5+tD6FQiHv37rWa+Q6bzUZwcDD++OMPODg4wNLSUi4W8gRBgMlkon379nB0dMSnT59w7tw5XL9+HRMnToSlpaXcCzSCIGBlZYX58+djx44dmDt3Ltq1a1fn/mWz2Zg+fTp2796NkydPIjAwsNFeBFSVQ/v27bF69WrcuHEDa9asEXshSFL2z2Qy0atXL1haWmLv3r3o0aMHhgwZolDZ+NaGIAj4+flh8+bN6NevX4uOJaNRDDQ1NaGmpoa8vDxYWVlJ/DolJSWoqamhuLiYFsIKCJ0RbmO8fv0ar1+/xuzZs+kfQAWioKAAmzZtwk8//QQVFRWQJIlLly5BIBBg9OjRrXosSZJEbGwsDh06hFmzZsHBwaHW9qkRXWfPnsUPP/wgdeHJ5XKxf/9+6OrqYvz48fWWf1L9w9u3b0f37t0xaNAguSgV/VqgMvElJSWIi4vDhw8fkJGRAeBfN00nJyc4ODhAT0+vTWfoY2JicPHiRaxatarVhB5JkoiMjMTly5exYsUKuV2A8fl8REZG4vz583B1dcWIESMale2UFSRJIj4+Hrt378b8+fMbNCerrq7Gjh07YGlpidGjRzfLmI8qzz527BhUVFQwadIkiVs8SJJEeXk5jhw5ApFIhKCgIGhpaTU5lraOSCTCrl270LlzZ/To0UPuz0maloUkSdy4cQNcLhfffPNNo1oUTp06BSMjI/Tr16+Fo6RpIvVmhOX71ixNoyBJEu/evYO7u7usQ6FpJM+ePYOHh4d4Ji+Hw8Hz589bveyROoeOHDmCkJCQOkUw8K9QPX36NAIDA6We1aOMaFgsFsaOHdugCM7KysLGjRvh5+eHwYMH0yK4haGEb0ZGBu7fv49du3ZhzZo1+Ouvv5Ceno7u3btj6dKl+OmnnzB79mz4+vrC0tIS6urqbXaRKRKJcPPmTQwaNKhVs53UTFR7e3tcvHgRIpGo1bbdGNhsNrp27SouN/z999/x9u1buY2XgiAItGvXDrNmzcLOnTuRmppa71xpZWVlhISEIDk5GVeuXGnWZyMIAhYWFliyZAnc3Nywdu1aPH78GAKBQKLXamlpYc6cObCzs8PatWuRnp7epHnYXwMMBgNDhgxBWFgYhEKhrMOhkTHUNfX9+/eNOh8IgoCzszNiY2Pp75oCQpdGtyEEAgFSUlIQEBDQZhedbRGBQIDnz59j3rx5YqfoZ8+ewcnJqUVNd/4LSZKIiorCyZMnMX/+fFhYWNR5HpEkifDwcJiamtZbMticGK5du4b8/HzMnz+/3swK1ce3Y8cOTJw4sUGHV5qmQf2gU67hcXFxiIqKQlZWFlRUVODg4ICePXvC3t4eampqCtMDKm3y8/ORm5srkxuQDAYDo0ePxv/+7//i/fv3cHd3l8tjQBAE1NXVMWbMGHh6euLQoUN48+YNAgMDoaqqKpcxAxCXLAcFBWHbtm1YunQpzMzMasVLEARUVVUxb948bN68GSoqKs3ydSAIAkpKSujXrx9cXV1x8OBBvH79Gt9++y309PS++L5sNhv+/v6wsLDA5s2bMWnSJHh4eMh9WbossLa2hrKyMuLi4lpk6gGNYmFgYACBQICSkhIYGBhI/Dpra2ucPn0afD6fbs1SMGgh3IYoLy+HUCiErq6urEOhaQTJyclQUVERm5txuVzcv38f8+fPb7UfZZIkERERgdOnT2PhwoV1Lvao55WVleHWrVtYsWKFVBdWJEni6dOneP36NVasWAFlZeV6Y0hJScGOHTswY8YMevEiRSizo8rKSsTHx+Pt27dISkoCg8GAvb09evfuDVtb2xoO5oq07z8X9//9f5IkIRAIIBAIIBQKa/x/Q9mBsLAw2NraIjs7u1U+Q134+flh586dWLJkSZN7Han+XjabDWVlZaiqqopvblDf8+Yea4IgYGtrix9//BEXLlzAb7/9huDgYNjY2MjteUQQBDp06IDJkydj8+bNWL58OYyMjOoUwxoaGggNDcX69evFQrY5n4sgCBgbG2PFihW4d+8e/vjjD0yYMAGenp5fdFCnslvGxsbYtWsXMjIyMGzYMLkYNSZPMJlMDBkyBFeuXIGzs7Osw6GRMWw2G+3bt8fbt28b9f1VU1MDk8lEWVlZowQ0jeyhhXAbIj09Hebm5nR5qAJBWfb37NlTfMH98OED9PX1YWxs3GoxvHr1CufPn8eiRYtgamra4POvXLkCLy8vGBoaSm1BRfUlX7hwAcuXL693VBRJkkhMTMTu3bsRHBwMJycnelHXTEQiEbhcLrKzsxEVFYWYmBhUV1fD0tISHTt2hL+/P/T19RXiuvK5mBUIBKiurkZRURGKi4tRWlqKkpISFBUVoaSkBFwuVyxyRSIRhEIhGAyG+A+Tyazx97rgcrl4+PAh+vTpg3/++aeVP21NmEwmQkJC0KdPnyYfK2o/8Pl8CAQCMJlMKCsrw9jYGFZWVrC3t4e5uTlUVVWbLKgIgoCysjLGjx8PZ2dn7Nq1C/7+/vDx8ZHbc4wgCHh4eIDH42Hjxo1Yvnx5nYaUBEFAW1sbixcvxoYNG6CkpAQfH59mi2EWiwU/Pz84Ozvj4MGDePfuHcaPH//FlgOCIGBqaooVK1bg4MGDOHjwIKZMmUIbQ30GQRBwcXHB2bNnkZ6e3iiTJJq2B0EQ6NKlCy5evNiofl82mw0bGxvEx8fTI8wUDNosq41AkiROnjwJExMT9O3bl/4SKggcDge//PILVq5cCV1dXQgEAmzevBnDhg1rlUwnSZJ4/vw5rl69ioULF35RfOfm5mL9+vX46aefpGbCQpIkMjMzsWXLFoSEhMDW1rbeTPCnT5+wf/9+zJ49u97+ZZqGIUkSQqFQbHAVGRmJjIwM6OjowM3NDR07doS+vn69GXlZQzlTczgcVFZWorCwENnZ2cjLy0NBQQEKCwvF/ZRKSkrQ1taGjo4OdHR0oK2tDX19fejo6EBFRQUsFgtMJlP8X0r0Utm2//75bxzPnz/HmzdvEBISIvOyU2qkkpeXF3r37t3oY/d5ZpwSw3w+H9XV1cjJyUFqaiqSkpKQn58PVVVVODk5wcPDAxYWFlBRUWnSuUKSJAoKCrBv3z6YmZlhwoQJjRpb0tqIRCI8efIE169fx9KlSxvM/OTl5WHjxo0YNWoUunXrJrXvEofDwdWrVxEREYGgoCA4ODhIdO5xuVycO3cOKSkpmD17tkQl1l8Td+/eRWJiYquMP6ORb6qqqvDrr7/i+++/r/emfF08f/4cMTExmD59On0OyR/0+KS2jlAoRHx8PC2CFYzU1FTxAh34dy5veXm51Htv64JayF+7dg2hoaFfHLlFkiTOnz+PQYMGNerH4UuUlZVh9+7dCAwMbFAEJyYmYv/+/Q2KZZq6ocRjRkYGIiMjERMTAz6fD3t7e/j4+MDe3r5GKay8IBAIUFxcjJKSEmRlZSEtLQ25ubkoKiqCSCSCqqoq9PX1YWpqCisrK3h6esLIyEicsaT+ANIv4RYKhbhz5w7Gjx8vF/uMxWJh+vTp+PPPP+Ho6PjFyo7/8rnYZzKZNfrcTExM0LFjR/F5VFRUhOjoaJw7dw6lpaVwcnJC7969YWVl1SjHZIIgYGhoiCVLluD06dPYsmUL5syZ0yIzyaUBg8FAz549IRAIsGXLFixdurTeViRDQ0MsWrQImzZtgpKSktR8DFRVVTF69Gi4ubnhwIED8PHxweDBg79oWqisrIwJEybgwYMHWL9+PebMmQNra2u5OHflAS8vL9y4cQPFxcWt6s1BI3+oqqrCysoKnz59QpcuXSR+nY2NDa5fvw6SJOnvlQJBC+E2QnV1NTgcDt0frEBQplje3t5ik6x79+6hT58+zRq/Iem2X716hStXrmDRokUSlTlnZ2cjKSkJQUFBUrnIU4vq/fv3w8vLCx4eHvWK4LS0NOzevRuzZ8+mRbAEUJU+1dXViI+Px8uXL5GYmAh1dXV4eHhgxowZMDY2lnm/4OcVSTweD7m5ucjOzkZiYiLS09NRXFwMgiCgo6MDMzMzWFtbo1u3bjA2NoaGhkYN4d7a7uqZmZkQCARy099KEAQMDAwwcuRIHDlyBEuWLJGqaQsllJWVlWFqagoTExP0798fZWVliIiIwJEjR0CSJPr164fu3bs3KkusoqKCyZMn4/bt21i3bh3mz58PU1NTudiv/4XBYKBPnz7g8XjYunUrlixZUuc4KIIgYGJiggULFmDLli1QUVFB+/btpfKZGAwGnJyc8P333+Pw4cPYunUrZsyYAR0dnQbfn8FgwNfXF0ZGRtixYweCgoLg4uIil/u5tVFTU4OnpycePXqE4cOH0/vkK4YgCHTt2hWvXr0S9+NLgq6uLvh8PsrLy8XJDRr5hxbCbYSMjAwYGRnRbnUKBIfDwadPnzBq1CgQBIGKigp8+PChUfPrmgJJknj9+jUuXLggsQgWiUS4du0aBg4cKB7xJI04zp49C3V1dQwZMqTO8j5qRNL27dsxffr0VsmUKyqU0VVFRQXev3+Ply9fIjc3F6ampujWrRtGjRolvlEmq31Ixcjn85GXl4ekpCTEx8cjIyMDHA4HmpqaMDExgYODA7p27QpDQ0NoaWnViFdejv/t27fRt29fqY8Paw4EQcDLywtRUVG4c+cOhgwZ0mL7ixLGOjo68PX1Rd++fZGamoqbN2/i2rVr6NWrF/r16yfx6CwGg4GBAwfCwMAAmzdvxty5c+X2pheDwYCfnx94PB62bduGRYsW1fk5CYKApaUl5s2bh+3bt2P+/Pmwt7eXymeiRiXNmzcP9+7dw2+//Ybp06d/UdgSBAFXV1csWLAAu3btQkBAALy9vWVe2i9rCIJA//79xeP45HUuN03r4ODggHPnzoHH40m85lFSUoKJiQlSU1PpMaYKBC2E2wCU0ZCTk9NX/2OmSKSnp0NPTw8aGhogSRJv3ryBo6OjVMuO/wu1nfPnzyM0NFRiQ668vDzEx8dj0qRJUssGP3r0CAkJCVi6dGm9GfC8vDxs2bIFkydPpjMXdUD1cxYXF+Pt27d4/fo1ysrK4ODggEGDBsHa2lqmM3wpI66ysjLEx8cjMTERKSkp4HA40NLSgrW1NTp16oRhw4ZBW1sbampqCnGMKyoq8PHjR4wdO1bu4mUymZg4cSL+93//F25ubvWOQZMmlCi2tbXFnDlzkJ+fj7CwMPzyyy9ikSzJmCSCINC5c2eoq6tj165dcp2xZDAYGDp0KLhcLnbu3IkFCxbUKZ4IgoCdnR3mzJmDnTt3IjQ0VGolyZ8badnb22P//v3w9vbGoEGDGrwpThAErKyssHTpUuzatQvFxcUYMmRIi1ciyTsGBgawsLDAu3fv0L17d7k872haB21tbairqyMrKwu2trYSvYYgCDg5OSEuLo4WwgoEbZbVBhCJRPjzzz8xYcIEib+wNLKFJEkcO3YMpqam6NevH0iSxB9//IHAwEDY29u32DajoqJw5swZLFiwACYmJhL90JMkiaNHj0JXVxfDhg1r9uKAJEkkJCRgz549WLlyZb29ycXFxdiwYQMCAgLoRcl/EAgEyMvLQ0REBCIjI8HlcuHq6opu3brBzMysyeZFzUUkEqGsrAwFBQWIjY1FQkIC8vPzoaysDFtbW9jb28POzg5aWlpQUVGRW5fgL3H37l2kpKTIrSkK1foQFhaGlStXyqRSiJo/feXKFcTHx2PkyJHo3LmzRBl0qh1i586dmDhxIjp27CiX+xn4t1f81KlTyMnJwdy5c+t1ZCZJEtHR0Th8+DAWL14Mc3NzqX4marTd4cOHQRAEpk2bVmfJ9n8pLy/Hnj17YGJignHjxn3VVWXUb9OJEyewatUquar2oGldSJLE1atXIRQK8c0330j8uoSEBJw5cwbfffed3F6zvlJos6y2DJ/PR2lpKT27TIEQCAT48OEDBg4cCIIgkJ2dDS6XC0tLyxbZHkmSiImJwalTpxolgoF/F0pRUVFYvXq1VC7sxcXF2LdvH2bOnFnvOVtRUYGdO3eib9++tAjG/zn65uTk4PXr14iIiIBQKISHhwemTZsGY2NjsNnsVu+TBYCSkhKkp6fj/fv3SExMBIfDgZ6eHtq3b4+hQ4fCwsICysrKMu9HlhYCgQD379/HzJkz5fbzEAQBT09PvH79GmFhYfD392/1WAmCgJGREYKCgpCeno7jx4/j4cOHmDJlyhevP1TGctGiRdi6dStEIlG9HgKyhslkYty4cTh69CgOHDiA4ODgOkspCeLfecQTJ07E1q1bsWzZsjrnETcVqlQ6JCQEYWFh+OOPPyQyxNLQ0MD8+fNx+PBhHDp0CFOnTpVr5+6WhCAI2NjYgCRJpKamwsHBQdYh0cgIgiDg7u6Of/75BwEBARLftDUxMUFRURG4XO5X+z1SNGgh3AagRp+oq6vLOhQaCcnLy4OSkhJ0dXVBkiTCw8Ph5eXVInegSZJEfHw8/v77b8yfPx9mZmYSL75IksTTp0/h7u4uFfMHHo+H/fv3o3///nXOACZJEjweD3v37oWzszP69+8vl4vf1oDqp83Pz8fr16/x6tUrsfidOXMmTE1NW9XlmRLj5eXlSExMRHR0NJKSksDlcmFqagp3d3f07dtXbMIFyE8/rzRJSkoCi8WS+3mjTCYTkyZNwpo1a+Du7g4rKyuZHA8GgwErKyssX74cz549w/r16zFgwAD4+fmBxWLVGxNB/DsDlxLDTCYT7u7ucnlOUfv60KFDOHLkCIKCgur8bFTpN4/Hw6ZNm8Rj86QphtlsNoYNGwZra2ts27YN48aNQ7du3eptm6IM0GbMmIETJ05g165dmD179le7nqBKzcPCwmBnZ0e3m33FmJubo6qqCiUlJdDX15foNerq6tDU1EReXp7c/0bQ/AsthBUckiQRFxeHdu3a0RdsBYEkSURGRqJDhw5gs9ngcrmIiorCsmXLpL7II0kSycnJ2LdvH+bOnQtLS8tGbYPP5+Phw4dYsGBBs2MTiUS4ePEitLW16xW4IpFIXIY9YsSIr+6cpsRvSUkJXr58iRcvXkAoFKJjx46YMWMGzM3NW62cmIqluroaycnJePfuHeLi4sDn82Fubg43Nzf0798fRkZGX00JIUmSuHv3rsLcoNHS0sLEiRNx5MgRrFixQmYZCqqX1cfHB66urjh69CiioqIwY8aMBrOinzsvb9++HWw2u1XmqzcWSoBOnToV+/btw/HjxzFp0qQ6e24JgkD37t1RXV2NjRs3Yvny5VIfF0UQBNzc3LBixQrs2rULGRkZGD58eL1VI1T8EydOxOXLl7FlyxYsWLBAotLqtgZBEOjYsSMuXryIkpISepTSVwyTyYStrS0SEhIkFsKUV0JycjIthBWEr2uV2UaJiYmBi4uLrMOgaQQRERHw9PQEAMTFxUFfX1/iC62kUOVdf/31F2bNmtVoB1aSJPHx40fo6elJbKrV0Hu9efMG0dHR9S4QRSIRrly5gpKSEgQGBn5Vxi0ikQjFxcUIDw/HunXrsHHjRpSWliIoKAirV6/G6NGjYWVl1eIimCRJVFZWIjk5GVeuXMG6devw+++/4/79+zA1NcXs2bPx008/Ye7cuejVqxfMzc2/GhEM/FvWn5SU1KiRGrKEIAh06tQJxsbGuHPnTo1xVbKKR09PDyEhIejVqxfWr1+Ply9fQigUNvgaMzMzzJ07F0eOHEFiYqLMP0d9UJnVwsJCnDlzpt7PRY1g6tWrF7Zs2YKysrIWicfY2BgrV65Efn4+du/ejYqKigb3HYvFwogRI9C1a1ds2rQJxcXFcruvWxI1NTV06dIFDx8+/Co/P82/UBUcERERjToPnJ2d8fHjR/rcURBoIazgCAQC5Ofnw9TUVNah0EhIeXk5KioqYGJiApIk8fjxY/j4+Eh1G1Q/6Z49ezBt2jQ4ODg0aeF++/Zt9O/fv9kCLCcnBydOnMCsWbPqLLmjZiq/efMGs2bN+ip6a6gy41evXmHr1q1Yu3YtkpKSMGbMGPz0008YP348rK2toaSk1KKiSygUIi8vD0+ePMHOnTvx+++/49SpU2AwGJg4cSJWr16NefPmwdfXF6amplBWVlYIEShtKAMqNze3eg2R5BEmk4nx48cjPDwcWVlZcrE4o7LDixcvxvXr13Hy5Elwudx6Y6N6hmfNmoV9+/YhKyurlSOWHFVVVcyePRupqam4dOlSg2J44MCB8PDwwM6dO1FRUSH1WAiCgLq6OmbOnAkbGxusX78eubm5Db6GyWRiwIAB6Nu3LzZv3oyCggK5OGdaE4Ig0KdPHzx79gw8Hk/W4dDIEEdHR6Snp6O6ulri11hbWyMjI6PBG3w08sPXk3Jpo+Tl5UFVVZUe3q1AJCYmwsLCAioqKuLs25QpU6QmLkiSRFFREXbs2IFx48Y1uZSwoKAAubm5za424HA4+OuvvzB27Ng6nVKpzPOFCxewcuVKaGhoNGt78gw17igxMREPHz5EQkICrKys0L9/fzg6Ora4yKQWtDweD6mpqYiMjERsbCz4fD4cHBzQq1cvtGvXDsrKyq3af6wI8Pl8PH78GLNnz5Z1KI1GW1sbo0aNwpEjR7B8+XK5yOJTmd7vvvsOx48fF88O/u/c6M+fb2dnh0mTJmH37t1YvHgx9PT05PIcVVdXx/z587Fp0yYoKyvXOyedwWDA398f1dXV2LNnD0JCQlrE8Z3NZiMgIADGxsZYv349goOD6/Ro+Dyu3r17Q0lJCZs2bcKiRYukauylCBgZGcHExARv375Ft27dZB0OjYxQU1ODlpYWcnNzYWNjI9Fr9PT0IBQKUVZWRpfWKwC0EFZw0tLSGt33SSNbIiIixA6oCQkJMDMzk6oxSXl5ObZu3YqhQ4eiU6dOTTo3qEx1t27dJB4mXxdCoRBnzpyBnZ1dne7PJEkiNzcXBw4cwNy5c2FgYNDmzuXPTa+ePHmC169fQ0NDA71790ZgYKBY+LfU56ZMrioqKhATE4NXr14hKysL+vr66NSpE2bNmgVjY2PxQr2t7X9pQLUZKCsrN8pxXV4gCAJdunTBs2fPEB4ejn79+snFZyAIAqqqqpg2bRru3r2LP/74A/Pmzav3N43qfS0rK8PevXsRGhoq0XxiWaCuro5FixZhw4YNUFFRga+vb71iePTo0Th+/Dj279+P2bNnt8gIIwaDge7du8PQ0BB//fUXRo4cCS8vr3p9GBgMBnr06CEWw4sXL4axsbFc7uuWgCAIDB48GOfPn4enp6fCjnqjaR4MBgNubm6IjIyUeP43g8GAoaEhcnNzaSGsANCl0QpOTEwMXF1dZR0GjYQIBAIkJibC0dERIpEIT58+Rc+ePaX2/pWVldixYwd69eqFHj16NHnRwuPx8Pr1a/j4+DT5PahS0qSkJIwbN67WgoskSVRVVYkXZXZ2dm1qkSUSiVBeXo5Hjx5h7dq12LFjB5hMJhYuXIhVq1ahV69eYjOaljBJ4/F4yMnJQVhYGNauXYu1a9ciOjoavXv3xvfff49ly5bBz88PZmZm4tFGbWn/SxPKJKtv374KuyBmsViYNGkSrl+/joKCAlmHUwMmkwk/Pz9MnDgRO3bsQGxsbINl0t7e3mjfvj3++ecfuS0/pMYZhYaG4s6dO3j69Gmdn4kyEgsMDISysjIOHToEPp/fYjHZ2dlhxYoVCAsLw40bNyAQCBp8vqenJ8aNG4fNmzcjJyfnqyqTdnR0BIfDQXp6uqxDoZER1BilmJgYiEQiiV/Xvn17fPjw4av6vigqtBBWYIRCIdLT0yUu16CRPfn5+QAAQ0NDVFVVITU1FS4uLlIRIBwOB/v27YOrqyv69+/fLMfl1NRUqKmpwcjIqEmvpzK9Z8+erbfnVyAQ4ODBg3B1dW2WaJcnSJIEl8tFXFwc9u3bh99++w1xcXEYP348Vq9ejREjRojHHrXEtqurq5GUlIRTp07ht99+w19//YWKigoEBgZi9erVmDlzJjp16lRv+SlN3VRUVCAxMVFux/dIiqGhIfz9/fHPP/80KIBkAbXgnDt3Lv7++2+8ePGi3kUkVVJMEASuXLnSqAVqa6Onp4fFixfj8uXLePXqVb2fiXKd5vP5OHbsWIuKYQMDAyxduhSxsbE4duxYg32wlGHQhAkTsHXrVrnpM28NmEwm+vXrh3v37n01n5mmNgYGBqisrASHw5Ho+QRBoF27dnJt7Efzf9BCWIEpLS0Fl8uFoaGhrEOhkZD4+HixcVViYiLMzMykYrzD5/Nx9OhR8UK3OUKLJEk8fPgQvXr1alZGed++fRg5ciRMTU1rvY9IJMLly5dBkmSbGJNEkiTy8vJw9epVrFmzBmfPnkWHDh2wevVqzJgxAw4ODi3S/0uSJDgcDmJjY3H48GGsWbMGJ0+ehJ6eHhYsWIAffvgBo0ePhq2trdyWkMo7VGWDi4sLNDU1ZR1OsyAIAr169QKHw8Hr16/lbpFGEARsbGywZMkSXL16FQ8fPqxX5LLZbEyePBkfPnyQy89CQRAEDA0NsXjxYpw6dQpv376tN1ZlZWXMnDkTRUVFDbpOSyMmLS0tzJ8/HwKBADt37kRlZWWDz+/UqRMCAwOxfft2ZGdny+3+liYEQaBbt26IjY1tMWdvGvlHRUUFFhYWiI+Pl/i8NzMzQ3FxcaNMtmhkg2KvPr9y8vLyYGBgoPAi4muBJEnExMTAzc0NAPDq1St06dKlWeKEMl86e/YsRCJRnSXIjaWyshIJCQno3Llzk/uLL168CGNjY3h5edXZFxwREYE3b95gxowZLdIP19JQfbc8Hg9v377Fxo0bsWHDBnA4HMyfPx/fffcdvL29oaGhIVXxSW2Xw+EgKioKf/31F37++WdcvXoV9vb2WLFiBb777jv4+fnB0NCw3rmhNJIjEonw4MED9O3bt03sSyaTialTp+LcuXMoKyuTO0FDCcdly5bh3r17uHXrVr1iWE1NDbNnz8aFCxeQlpYmd5+FgpqHvHjxYhw5cqTB0m9lZWXMmTMH6enpuHTpUotmu1VUVDB16lRYWVlh8+bNKCkpabAk3d3dHRMmTMC2bduQn58vt/tbmmhoaKB9+/Z48+bNV/F5aWpD3QiKioqS+DVKSkpQUlJqETd4GulCKygFJjY2Fs7OzrIOg0ZCeDwe0tPTYW9vDz6fj4SEhCY7OlOQJIkbN24gKysLU6dOBYvFavb7xcfHw8LCAmpqak16/fv37xEZGYlJkybV6qckSRKZmZk4fvw45s2b16RtyBLK+KqwsBAXL17ETz/9hFu3bqF///749ddfMXbsWHHps7QFMIfDwbt377B79278/PPPePDgATw9PfHDDz9g2bJl6NWrF3R0dGi3ZymTmpoKBoMBS0tLWYciFQiCgLm5Oby9vXHhwgW5XNwTBAFtbW0sX74cr1+/xu3bt+vNjurr62Pq1Kk4dOjQF+fkyhJqvy9YsAD79u1DQkJCvT3DqqqqmDdvHmJiYnDz5s0WFcMsFgsjR45Et27dsGnTpgYFLkEQ6NixI8aMGYPNmzejsLBQbve3NBkwYAAePHggd+0ENK2Hg4NDo0qdmUwmrK2tkZiY2MKR0TQXWggrKCKRCElJSU2eD0vT+lClVdra2sjMzISmpmazxl5Rs3ejoqLEfbjNPRdIksSTJ0/Qs2fPJmWWi4uL8c8//9Q7L7iqqgp79+5FYGAgzMzMFObcpfpvo6OjsXXrVmzYsAFCoRCLFi3C0qVL4eHhIfXSZ5IkUVlZiffv32Pv3r34+eefcf/+fXh6euL7779HaGgounXrJu73VZR9qUhQJll9+vQBi9V2hiwQBIFBgwYhISGhUeV+rQlBENDQ0MDChQvx6tUr3L17t05BSBAEnJyc4O3tjePHj8u1WCEIAra2tpg9ezb++uuverPY1GdfsGABnj17hvv377eoGGYwGBgwYAAGDRqEzZs3IyMjo0Ex7OnpiREjRmDLli0oKiqSy/NHWlBjvthsNlJSUtr0Z6WpH319fRAEIfZ5+RIEQcDe3p7uE1YA2s4v+1dGdXU1CgoK2kyW4msgJSUF1tbWYDAYePPmDTp16tRkB1qSJBEdHY2wsDAsWrRIar2LlEOmo6Njo19L9Sn369cPtra2tf5dIBDg77//hru7Ozw9PRVCuJEkieLiYjx//hxPnjyBjo4OBgwYgPbt27fIvE9KcKempuLx48dISEiAiYkJevToIR61RLdCtB4VFRX49OkTxo8fL+tQpI6qqioCAwNx9OhR/Pjjj80ak9ZSEAQBTU1NLFiwANu2bYOysjJ69+5d63tHEAR8fX2RlJSE+/fvw8/PT26vL5Rwnzp1KrZt24YlS5bA3Ny8zufq6OiIRzApKSk1+QalJDAYDHE7x7Zt2zBnzpx6nfwJgkD37t0hFAqxfft2hIaGQldXt0XikgdYLBb69euH27dvw8HBQdbh0MgAFosFBwcHfPz4EcbGxhK9xsHBAeHh4RCJRAo7beBrgF5RKShlZWVQUVFRyP7KrxGqP9jFxQUkSeLt27fo2LFjk98rNTUVR48exZw5c6S2AKFitLGxafRcY2ruMJfLxYABA+rsC7579y4qKioQEBAg92JOKBQiMTERe/bswf/+7/+iuLgY8+fPx5IlS9CpUyepG08JBAIkJSXh2LFjWLNmDS5evIj27dvjhx9+wMKFC8WZX3nfb22Nd+/ewc7OTuFNsuqCIAg4OzvD0tISYWFhcpu1+NzY6c6dO3j58mWdsbLZbEyaNAlPnz6V+3JEah5yYGAgNm/ejNzc3Hqfq6enhyVLluDy5cstbgpG9QEHBwdj9+7d+PTpU4OZ4R49eqBPnz7YtWtXm+6FpPZLcnIySktLZR0OjYzw8PBoVJ+wtrY2Kisr5bpKhYbOCCssCQkJsLW1pe8yKQgCgQDJyckYMmQISkpKwOfzmzSaiCRJFBQUYM+ePQgKCqrTkbk5PH/+vM6My5diys7OxtWrV/Hdd9/VKiElSRIJCQm4desWfvzxR7m9eUONPoqIiMCtW7dAkiT69++Pb7/9VurClzK9ysvLw7Nnz/D69WsoKSmhR48eGDp0KHR0dOhyZxkjFArx8OFDjBo1Sibb/68AaejvAoEAfD4ffD4fAoFA/EckEkEoFEIoFIr///PXC4VCODk5Yc+ePdDX14eGhkbLfqhm4uvri23btmHq1Kn1ZmXc3d2xadMmzJgxo8a1iMlkgsVigcViQVlZGZqamlBXVxf/hlLftdb6zlElxlwuF1u2bMGyZcugp6dXZ7bbwMAAS5YswYYNG6CiogI3N7cWi5Ma/TJv3jzs3LkTU6dORYcOHercHoPBQJ8+fVBZWYk9e/YgJCSkRSpl5AENDQ24u7vj6dOnGDJkSJv8jDQNY2tri2PHjoHD4Ug07UNVVRWamprIzc2FlZVVK0RI0xRoIayAkCSJT58+1fvjRCN/8Hg8VFdXQ1tbG1FRUbCxsWm0ICRJEhUVFdi1axdGjBgBJycnqR7/6upqZGZmws7OrlGvo0YljR07FgYGBrViKisrw759+zBz5ky5K5+jBGlJSQkePnyIZ8+ewdLSEpMmTYKdnZ3UbzSJRCJUVFQgMjISjx49AofDQZcuXTBv3jyYmJjQGV85Ijc3F+Xl5bC3t5fa94wyW/v8j1AoREVFBcrKylBRUYHKykpUVVWBw+GgsrISZWVlKC8vB4/HE4vaz/+IRCIwGAwwGAwwmUzx/1PGeSwWq8Zjn0M938rKCr///jsGDRok9zdXO3XqhK1bt8Ld3b3ekmINDQ38+uuv8PX1FX8eoVAovmHA4/HA4XAgEAjAYrGgrq4Oc3NzWFhYwMbGBubm5lBSUgKTyWzR31iCIODt7Q0ul4utW7diyZIl0NbWrlMMm5iYIDQ0FFu2bMGsWbOkfv3/7/ZsbGwQGhqKHTt2YMKECejUqVO9YnjIkCGoqqrCgQMHMGvWLLm92dkcCIJA3759sXv3bvj5+YHNZss6JJpWRkNDA5qamsjJyamz/eu/UIZZycnJsLS0pNfrcgothBUQgUCA1NRUDB8+XNah0EhIbm4udHV1wWazERERgS5dujT6PXg8Hvbv349u3bqhW7duUr+oxsXFwczMrFFloCRJ4sqVKzA1NUXXrl1rxcTn83H48GH07t0b7du3l2q8zUUgECA9PR23bt1CYmIiunbtimXLlkl9JBnl+JyQkIDw8HCkp6fDyckJEyZMgKWlJZSUlOgfSDmDKvX38vKSyCSLys5SIovP54PL5aKwsBD5+fkoKSlBaWkpSktLUVJSAi6XC5FIJH6dqqoq1NXVoaGhAXV1daiqqkJNTQ26urrQ0tKCpqamWJixWCwwmcwafyihS4nhxlYT8Pl8rF27Fj4+Pk0em9ZakCSJgIAAnDhxAhMmTBCb2HwOn8/Hrl274OXlVee1kiRJCAQCcLlccLlcVFVVISMjA+np6Xj79i0KCgqgpqYGBwcHeHh4wNLSEmpqai1yo4oSWFwuF9u2bcPixYvrHLtGEAQsLS0REhKCnTt3IiQkpEXNMgmCgIWFBUJDQ7F9+3YIhcJ6vR2YTCZGjRqFY8eO4fjx45g0aVKbFIrm5uZQVVUVT3yg+fpwc3NDdHS0REIYAJycnBAZGYnevXu3cGQ0TYUWwgoItdCS9zI2mn+hSoNtbW0hFAqRlpaGCRMmNOo9BAIBTpw4AUNDQwwcOLBFFmTPnz9H9+7dG7Wwio+Px8uXL7F69eo6RyXdvn0bIpEIgwYNkovFNUmS4PP54rEkHA4HAwYMwOTJk6GmpibVGIVCIbKyshAeHo7o6GgYGhqiT58+CAoKkvq2aKQLVSK/dOnSGsdJJBKBw+GgoqICFRUVyMvLQ3Z2NgoLC1FYWIiysjIIhUKwWCyw2Wzo6enBwMAAOjo6cHBwgI6ODvT09KCqqlpL0Mpy7BWLxcLkyZOxZ88eODk5yfVvC2U2NXjwYOzduxeLFi2qNYaNxWJh0qRJ2L59O+zs7GBoaFjrPdhsNthsNjQ0NKCvrw9LS0t4eXmJWyRKS0sRGxuLmzdvIi8vT2xa5+zsLPX54AwGAwMHDhSL4UWLFtXp00A50c6ZMwe7du3CwoULYWNj06Ji2NTUFIsWLcKWLVsgFArrvQnLYrEwceJE7N27F5cuXcLIkSPlvrqgsTAYDPTv3x93795F+/bt6Wv4VwZBEHB1dcX58+cxbNgwidZhFhYWuHLlSitER9NUaCGsgGRkZMDAwEAuXT5p6iY+Ph7e3t7Izc2FkpJSo0qERSIRwsLCUFJSgpCQkBZZXHC5XCQnJzfKHbeyshKHDx/GtGnTai2cSZJEYmIiHjx4gO+//17mo2eorOyLFy9w+/ZtaGtrY/jw4XBycpJa+SOV3SsvL0dERAQePnwIgUAAb29vrFixQlzySC+e5JPPe27j4uLAZrNRWFiIjx8/IiUlBfn5+SguLkZ1dTVUVFSgrq4OIyMjmJqaolOnTtDX14eBgYG4R5LK0AKt13faVAiCgLW1Ndzc3HDjxg2MGTNGrmOmXItzc3Px999/Y+bMmTWuMQRBQF9fH8OGDRPPLJfkGkR9P1VVVaGqqgoTExP06dMHXC4X8fHxePToEc6ePQs7Ozv069cP9vb2UruBwWQyERAQAB6Ph507d2LhwoV1jmQjCAKOjo6YMWMGtm/fLnadbkkxbGRkhCVLlmDz5s0gSbLeG6YsFgvTp0/Hzp07cffuXQwYMKDNtXt4eHjg/PnzKCkpkbtWH5qWx9LSEkVFRaisrJSoek5HR0dcddJYE1Ka1oEWwgoGSZJISkqqd6wBjfxBZQYtLCwQFRXVqBJhkiTx5s0bvH79GsuWLWuxcrOMjIxGzTUWiUQ4f/48XF1d4ezsXOtcrKysxP79+zF16tQ6e95aA0rYlJaW4v79+3j69Cns7Owwe/Zscb+OtAQw5TJ97949JCUlwcnJCZMmTYKtra1MM300dUP1hlM3SLKzs5GRkYHExETk5OTgyZMnMDU1xaVLl2BiYgIbGxt4enpCX19f3OLwOW3h+DIYDAQEBODXX39Fz549pW7EJ20YDAb8/f2xb98+3Lx5E8OGDasRL2VG9e7dOzx58qTRJoCfb0dVVRVubm5wc3NDZWUloqKicOLECYhEIgwcOBCenp5SmSPOZDIxevRoHDt2DHv37sWcOXPAZrPrFMOurq6YPHkytm7diqVLl8LY2LhFxTBl2LVp0yYwmUx06dKlzrhUVFQQHByMLVu2QEdHp86WGUVGRUUF7u7uePnyJQYOHNimPhvNl6EqfXJzcyUSwioqKtDT00NmZmaTxlLStDy0EFZAPn36RF+AFQgulwuBQAANDQ18+PABffr0kejYUVnVCxcuiMv/WuqYR0VFwcPDQ6LnkiSJDx8+4NOnT/j+++9rxSQUCnH06FF06dKlTpHcGohEIhQWFiIsLAxv376Fp6cnVqxYUaeZV1OgRFRZWRmeP3+OR48eQU1NDb6+vpg8ebLUSydpmodIJAKfzweHw0FaWhqSk5ORkJCAoqIiCIVC6Ovrw9zcHG5ubuJM4++//w4tLS1Zh96qaGpqYsSIETh27BiWLFki96WtLBYLU6dOxcaNG2FhYYGOHTvW+N5RwnLr1q1wcXGpVSLdGKj31dDQgI+PD7y8vJCSkoKwsDBcunQJAwcOhLe3d7Md5plMJgIDA3HkyBEcOnQI06dPr/MGKEEQ8PDwELtOL126VGrXt7qgsuyhoaHYunUrmEwmPDw86hTD2tramDt3LrZt2wZtbW04Ojq2meshNbN637598PX1bZPGYDT1Q92Eio6OlshIkSAI2NraIjk5mRbCcgothBUMkUiE/Pz8Jo3eoZENWVlZ0NPTAwBkZ2dL5MpMjUmiFkKGhoYttpAQCASIiYnBjBkzJNpGRUUFjh49ihkzZtQaIUCSJJ48eYLCwkIEBQW1elmcSCRCZmYmbty4gYSEBPTu3Rs//vgjtLS0pCaAeTwekpOTcffuXaSlpcHd3R1z586FiYlJi7vM0kiGQCAQ9/B+/PgRCQkJKCgoAIPBgKmpKWxtbREQEAB9fX2oq6uLs3kkSeLBgwfo1KlTm5wd/CWokuOHDx8iMjKySaZ+rY2qqipmzpyJnTt3wtjYGCYmJjW+gzo6Oo0ukZYEFosFBwcH2NnZIScnB9euXcPt27cxcOBA9OzZs1kZYjabjSlTpmD//v1i86m64qaOF4/HE4th6remJaDKpBcsWIBt27aBwWDUuvlAYWhoiJkzZ2LXrl0IDQ2t1+FbETE1NQWbzUZqairatWsn63BoWhFKCJ84cQIBAQES3Sx0dHTEo0ePMGjQoFaIkKax0EJYwSgrKwNJkhKXsNLIFpIkkZGRAXNzc5SWloLNZkvUJ8LhcLBnzx4EBARIdXxLXRQVFYHL5cLExOSLzyVJEufOnUPnzp3rjCsrKwuXLl3CypUrW7WHXSQSISUlBVevXkVWVhb8/PwwadIkqWXRqRFLL168wJMnT6Cqqop+/fph2rRptPGVjKFK0wsKCpCWlobo6GikpqaCx+PBwMAAjo6OGDZsGMzMzKCsrFxnqenn7xUeHo6JEyd+tceUzWZj4sSJ2L17N5ydneW+r40aLTRmzBgcPnwYixYtqnGDjiqRjoiIwLNnz+Dj4yN1oyszMzPMmDEDubm5OHfuHO7fv4+xY8eiQ4cOTc6qKysrY/r06di1axfOnDmDcePG1fleDAYDvXr1EovhJUuWQEdHp5mfqn6o/b1w4UJs2bIFLBYLrq6udWaGra2tMXnyZOzduxehoaEtKtJbEyaTib59++L+/fviPnGarwcjIyOUlZWhurpaouujqakpcnNzxaPuaOQLWggrGGlpaTA1NZW5+RCN5CQkJKBDhw5ISEiAnZ3dFy+EfD4fR44cQYcOHVpkTNJ/iYuLg6Oj4xfjouZXf/r0CatXr671fC6Xi4MHD2Ls2LHNKkGUFKo8OTk5GRcvXkRhYSGGDRuG2bNnS2UkEfX+qampuHXrFuLj4+Hu7o45c+aIZ/5+rWJJVlB931TFRHx8PN6+fYuMjAwwmUxYWVmhQ4cO8Pf3h56envgYSXqcsrOzUV1dDRsbmxb8FPKPjY0NXFxccOPGDYwePVruz3OCIODu7o6EhAScO3cOEydOrHF9IggC48aNw9atW+Hq6gpdXV2pfyYGgwETExOEhIQgISEBx48fx507dzB58mQYGRk1aXuqqqqYO3cutmzZgsuXL2P48OH1iuEBAwaAx+Nh27ZtWLJkCdTV1Vu0TNrExEScGQ4ODq5zlBNBEHBzc0NhYaFYDFNmcooMQRDo2LEjLl26hKqqKrl2WaeRPioqKjA0NER6erpEni/6+vrg8/koKytr0ZtUNE2DVlMKRnx8PNq1a6fwPyRfE1lZWRg4cCDCwsLQsWPHBp8rEolw9epVEAQBf3//Fr97SJIk3r59Cx8fny8+l8fj4ejRo5gyZUqtkmiRSIRr167BxMSkxc1RSJKESCQSC+CSkhL4+/vD09MTLBZLKgK4uroakZGRuH37NoRCIfr16ycesQS0DXMkRYE63lVVVYiLi8Pbt2+RnJwMgiBgZ2cHLy8vWFtb1xA3TTk+jZ0d3JYhCAKjRo3CmjVrxMZZ8g5l9rV9+3a8evWqxk1EgiCgo6OD/v3748KFC5g2bVqL9D9TN13atWuHH3/8EY8ePcK6deswcOBA+Pr6NliNUB+qqqoIDQ3Fhg0boKKigkGDBtX5u0AQBIYMGQIej4cdO3Zg4cKFze5XbgiCIGBubo45c+Zgz549mDt3LqytresUw3369EFRURGOHTuGadOmtYnvl6amJpycnPDmzZsmG7HRKCYEQcDFxQXR0dFwcnL64rFnMpnQ1dVFQUEBLYTlEMW/Gn1FUOZJI0eOlHUoNBLC5/NRUVEBDQ0NpKWlNZhdIUkSr169QmxsLBYtWtQqi4Xq6mpkZmZ+sfyaJEk8evQIJiYmteYnkiSJ+Ph4vHr1CqtWrWpRgx2hUIiUlBScP38e5eXl8Pf3R8eOHaWSAaYMth48eIBXr17BxsYGgYGBsLW1lYrAppEcapZrXl4eoqKi8P79e1RWVsLKygodO3YUZ3yl+R3hcrmIjIzEkiVL5OJYU9lvoVAIkUgEkUgkvinw37/zeDzweDxwuVzx/wsEAohEIggEAvF7CASCGmOi/vv3/6Kmpob169ejf//+crFPJMHIyAibN2/G2LFja9ywo65Lz549g6GhIVxcXKCjowMlJSUoKSmBzWZLrcqDIAiwWCz07dsXbm5uOHnyJF6/fo3p06fX6mGW5L3U1NSwaNEibNy4EcrKyujbt2+dYpjBYGD48OE4c+YMdu/ejZCQkFo3LaUJZQQ0bdo07NmzBwsWLKjTbZy6SXHgwAFcv369VW7ytjQEQaBv3744fvw4evXqpTDfD5rmQwnhI0eOgCRJiY49ZZjl4ODQChHSNAZaCCsQfD4fRUVFEvVy0sgHRUVF4r5EgUBQbz8JSZJISUnBlStXEBoa2qKLl8/Jzc2FlpbWF7dXWlqKsLAwLF++vM5RSYcOHcLUqVNbzGBIJBIhLS0NFy5cQGFhIUaMGIGOHTs2KcPyOVR/aXJyMm7duoW0tDT06NEDK1euhK6ursIv1hQJkiRRUVGBlJQUvHr1CgkJCVBXV4ebmxumTJkCQ0PDFi2rTEpKgpaWVouW9QuFQrFQ/fxPSUkJSkpKUF5ejsrKSlRVVaGqqgocDgccDgfV1dUQiUQ1yryp/ycIAmw2G2w2u4aoY7FYYDAYYLFYYDKZYDKZtW4cfOkGT6dOnXD58mXExMQojOOplpYWfH19cfr0aYwaNUrsVSAUCsHn8+Hp6Yk9e/agR48e4HK54psEWlpaMDU1hZ2dHezt7aGrq9vs/n9q7NDcuXPx8uVLbNiwAQEBAfDx8WnUTRyCIKClpYXQ0FBs3LgRSkpK6NmzZ52xUU7ZJ0+exJ49ezBnzhyoqKg0+TNIElv79u0xYcIE7Ny5E4sXL4aBgUGt5ykpKWHKlCnYunUrjI2NW6Xtp6WxtrYGn89HZmYmLC0tZR0OTStiYGCAyspKcDgcifqE7e3t8ebNG4mFM03rQQthBaKgoADKyspfpZupolJQUAA9PT1kZ2fD0NCw3lELZWVlOHDgACZPntyiIzA+hyRJvHv3Dh06dGhQ8JEkiZs3b6J79+613KtFIhGOHz8OT0/PWpliacWYlZWFixcvIiMjAwEBAejSpUuzBTDwbzY8KioKt27dEs8DnT59epvoYVMUSJJEeXk5Pn78iOfPnyMrK0u8SB41ahQ0NTVbpRebJEk8fPgQffv2bfLrSZJEZWUlKisrUVFRgfLycuTm5iIvLw9lZWWoqKhAZWUluFwuAIgFq5KSEnR0dKCjowNNTU0YGxtDTU1N/EdDQwNqampi0VrfHwC1/l8a+8XZ2RnHjx/H0KFDFWZUjEgkgrq6OtTU1DBs2LAa1zeSJGFkZAQmkwl/f3/xaK3CwkJkZmYiMTERDx8+RFVVFQwMDNCpUye4uLjA2Ni4ydUuTCYTXl5esLe3x8GDB/Hhwwd8++23jeotJQgCenp6WLRoEdavXw8lJaV621DYbDYmTJiAf/75B/v378esWbNa9NhRPdqVlZXYsWMHFi9eXKehp4aGBmbPno2NGzfCwMAA9vb2LRZTa8Bms9GjRw88fPgQkydPlnU4NK2IqqoqTExMkJycjA4dOjT4XIIgYGVlhStXrkAoFLaJ1oC2BH00FAjKfZhGccjMzIS5ubnYKKuuRQuXy8XevXsxYMAAifpNpIVIJEJMTEyDDrkkSaKoqAhv3rzB6tWra5VER0REICMjA1OnTpVq3NR2L168iNjYWAwbNgwzZ85sdgk0lXUMDw9HeHg4TE1NMWHCBLHzJy2AWxaqDLeqqgrR0dF4+vQpcnJyYG1tjd69e8PJyUmcvWrNY1FeXo6kpCR8++23tbb7uUGXUChEcXExCgoKUFhYiKysLOTk5IiFrkgkgrKyMjQ0NKCpqQkTExPY2NhAS0sLmpqa0NTUhJaWVo0bOZ9vT97OP4Ig4OjoCGNjY4SHhytMiTTV47xx40a4urrC1ta2xv4ePHgw1q1bBy8vL5iYmEBJSQnq6uqwtLSEl5eXeExaSkoKIiMj8ddff0EkEsHT0xPdu3cXlzc3tsTZ0NAQS5cuxeXLl/G///u/CAkJgZmZmcTv8/l7rFu3Dmw2G506dapXDE+ZMgUHDx4Uj+FryRYPgiDQo0cPVFRU4K+//sKCBQvq7FHW19fHzJkzcfDgQSxZsgR6enoKcU7VBUEQ8PLywtq1azF69OhWq+SikT1UeXRMTEydrun/RVdXF1wuF5WVlfTUFzmDFsIKxMePH+Hs7KywPxpfIykpKejYsSOePXuGgQMH1jp2QqEQ586dg4mJSav3GfF4PJSVldVZxvY5V69eRZ8+fWpVIhQXF+PkyZMIDQ2VWraBEqq3bt3C06dP0bdvXwQGBjbb9EUkEqGgoAC3bt1CVFQU3N3dsWjRokb369E0DarnNz4+HuHh4UhNTYWtrS369euHdu3aiReQsjgWVGWEg4MDlJWVxb22ubm5yMrKQkZGBjIyMlBeXg4ulwtlZWXo6elBX18fpqamcHFxgZaWFrS0tKChoVHrbr+in19MJhNjx47FunXr0LVrV4VYxBEEAVVVVQQGBuL48eNYunRpjUoPdXV1BAQE4MyZMwgJCRFnej8XyyoqKmjfvj2cnJxAkiRycnLw8uVL7N69GywWC/369UPnzp0bVT5NlbGPHDkStra22LhxIwIDA+Hp6SlxGwZBEDA2NsaSJUuwadMmsNnsehfibDYb06ZNw4EDB8RGhy0565wgCAwYMEDcLhMcHFzrt4EyuRsyZAgOHDiAhQsXtmjpdkujp6cHU1NTfPjwAZ6enrIOh6YVcXR0xD///CPRc5lMJrS0tFBSUqIQ19CvCVoIKwhUj2SfPn1kHQqNhJAkifz8fOjr6yMvL69WbzdJknj69CmysrKwYMGCFjWZqouUlBQYGhrWexebJEkUFhbiw4cP+PHHH2ssngQCAY4dO4b+/fvDwsJCKk7NXC4Xjx8/RlhYGDw8PPDjjz9CR0enye9NGQmlpaXhxo0bSE1NRa9evfDDDz80631pJIMkSQgEAmRlZSE8PBzR0dEwMTGBj4+PuCxUVseAJEnw+XxwOBwUFxfj1KlTMDAwwJ9//onKykqQJCle4FpYWKB79+7Q1NSEmpoaVFVVv7rqASMjI3h7e+PSpUuYMmWKQnx2SnC5ubnh6tWrGDNmTI1/9/DwQHh4OGJiYuDm5lbvZ6Iyv2ZmZvjmm28wbNgwpKam4u7du7hy5Qo8PDwwYMCARrW0MBgMeHh4wMTEBLt370ZeXh4GDRokcckk5dg8f/587Nq1C8HBwXB0dKxz+8rKyggKCsLevXtx4sQJBAYGtmhpJmWMdeLECZw5cwYTJkyo9dtGZY+zsrJw+vRpTJo0qdV//6RJv379cOfOHXh4eNC+El8RxsbGYl+HL7U5UMZyiYmJsLa2bqUIaSSBFsIKQlVVFcrLy2mjLAWCyriqqamBJMkaF0pq/u2tW7ewePHiVu+9I0kS0dHRcHV1bfCH++bNm+jZs2et2F+8eIHKykqplEoKhULExMTgzJkzMDExwdKlS2FsbNys9xUIBIiPj8fVq1dRVlaGQYMGYdq0aS06ToTmX0iSRElJCd68eYMnT55AJBKhV69e8Pf3h7a2tkwWigKBAKWlpSgqKkJ8fDySk5ORnZ0tdlzOysrCqFGj4ODgAG1tbbHBHb2o/ReqnPjnn39GRkaGwhgDMRgMDBw4EFu2bEFiYmINx1YGg4ExY8bg77//rlGV8CXYbDYcHBxgZ2eH0tJShIeHY926dXBxccGQIUMkvnYRBAFTU1MsX74c+/btQ35+PiZMmCBxdpRaWAcHB2Pv3r2YN29ejRLwz1FVVUVwcDB27dqFs2fPYuzYsS0qPFksFsaOHYv9+/fj5s2bGDJkSK3vEpPJxIgRI7B79248fPgQvr6+CnltJghC3EdfVFT0xQormraDiooKDAwMkJmZCScnpwafS92Yi46Opg2z5AxaCCsIpaWlUFNTA5vNlnUoNBJSUVEBBoOB0tLSWkZZZWVlOHToEKZMmVJj/mlrEhsbi2nTptX776WlpYiKiqrVG1xUVITz589j2bJlzTofSZJEdnY2Tp48ibKyMkyZMgUODg5NFh9UBvL9+/e4evUqSJJEQEAAOnToIBVzLZr6obLvSUlJuH37NpKTk+Hq6opp06bB3Ny8RcsxP4+BgsvlIjs7G8nJyfj48SOysrIgFAqhp6cHBwcH9OzZE9bW1lBXV8fVq1fRo0cP9O3blz5HGkBNTU08mic0NFRhMniqqqoYP368uET68zJ8CwsL2Nra4tGjR/Dz82vU8WcwGNDV1cXw4cMxYMAAhIeHY8OGDejYsSMCAgKgra39xfcjCAKampqYP38+Tpw4gd27d2P27NkS37CjeriDgoKwfft2LFmypN4KHTU1NYSEhGDr1q24ePEivvnmmxY9hioqKggKCsKmTZugo6MDb2/vWnFR2eqNGzfCwsIC7dq1U8jvoJKSEjp27IhXr15h8ODBCvkZaBoPdRPkw4cPXxTCwL8jlG7cuEEbZskZ9JFQENLS0mBpaUlfYBWIiooKqKurIz09vcbihM/n4+DBg/D19ZXZD39VVRUqKyvrHRVDkiQePHiALl26QEtLS/y4SCTC33//jUGDBjW5v5YkSXA4HFy5cgUvX77E8OHD4e3t3WQjF0oAR0RE4MqVK9DQ0MCYMWPg5OT01ZWwtjbUsXz58iXu3bsHJpOJ/v37IygoqFVMrygBXl1djZSUFMTGxuLTp08oLS2FtrY2bG1t0aNHD1haWtYw5aH+KxAI8OrVKyxYsIA+T74AZQx0584dfPz4ES4uLgqzz2xtbeHs7IwbN25g5MiRNc6DYcOGYdOmTejevTu0tLQa/ZkIgoC6ujoGDx6M3r174+bNm1izZg369++PAQMGfNHgjyAIKCsrY/Lkybh06RI2bdqEhQsXQlNTU2Ix7OrqiqlTp2Lz5s1YtmxZnbN8gX/F8MKFC7Fp0yYoKSlh6NChLSqG1dTUMG/ePKxbtw66urp1epxoaWlh+vTp2LdvH5YuXSqzG8PNpXfv3ti3bx/69++vMO7qNM2nffv2OHfunERZXk1NTXC5XHC5XFoIyxH0kVAASJIUl3Up4g/E10pxcTH09PSQkJAALy8vAP8KyStXrkBbWxt9+vSR2fFMTU2FkZFRvWV4HA4Hz58/x7Jly8QxkiSJ169fo6KioknZM8p19927dzh16hQ6dOiAn3/+ucnjwKi+4oiICFy7dg36+vqYNm0a7Ozs6JLWFkYkEqGwsBB3797Fmzdv0K5dO0ybNg3W1tYturD+XPimpqbi/fv3+PTpEzgcDoyNjeHs7IyJEyfCyMhIIhOjlJQUqKmpwdjYuMVibkuwWCyMHz8ep0+fxvfff68wC36CIDB06FBs3LgRnp6esLKyEvf+amtrw8fHB9euXUNgYGCztqGuro5Ro0ahT58+OHfuHH799VdMmjQJjo6OX/xesFgsfPPNN9DQ0MCGDRsQGhoqsaMyQRDo2LEjJkyYgK1bt2Lp0qW1Rt1RqKurIzQ0VCyG/fz8Wux6SRAEdHV1ERISgr/++gvz5s2r5ZJNEASsra0xdOhQHDx4EPPnz1c48yyCIGBiYgIGg4GsrCzY2NjIOiSaVsLS0hLFxcUS9Qmz2WyoqamhpKREotnDNK0DLYQVAMrwp3fv3rIOhaYRUJngN2/ewNjYGCRJIioqCrGxsViyZIlMSwtjY2PrzehQcVpYWEBfX1/8eGVlJc6ePYv58+c3egFMGYedPHkSpaWlmDVrFmxtbZu0ACNJEtXV1Xjz5g1u3rwJQ0NDzJw5E1ZWVgpTrqmoCAQCsflYWloavL29sWrVqhbN4lDHOy8vD2/fvsWHDx9QVlYGY2NjdOjQAT4+PtDV1W10/zdJknj06BG8vb3p80ZCCIKAk5MTdHR08OLFC/j4+CjMzVkVFRWMGjUKZ8+exYIFC8TXMIIg4OPjg/Xr1yM7O7vebKqkEAQBAwMDBAcH4+PHjzh+/DhsbGwwduzYL2Z5mUwm/Pz8oKqqim3btmHhwoWNEsNdu3YFj8fD1q1bGxxNpKmpKRbDbDYbffv2bVExbGlpifHjx2Pfvn1YvHhxrcw7VW2QmpqKy5cvY8yYMQp3M5PFYqFnz54IDw+HtbW1wnwvaJqHsrIytLS0kJ+f/0UhzGQyYWlpiZSUFHoUqhyhWFearxQul4uysrJ6y1hp5JO8vDxoa2uDw+FAV1cXubm5OHfuHGbMmCHTO94kSeLTp0/19rQIBALcuXMHQ4YMqfGasLAwuLm5Ndooh8/n48GDB1i7di1cXV2xYsWKJmdtuVwunj59ijVr1iAiIgLBwcGYP38+bGxsaDHTgvD5fERHR2PDhg04dOgQPDw88PPPP2P48OEtMgeUyji/ePECf/31F9asWYNjx46BIAgEBgZi9erVWLBgAfr37w9zc/NGjbCh4HK5+PDhAzw8PKQae1uHyWRizJgxuHz5MqqqqmQdjsRQIl5fXx9Pnjyp0VOuqqqKwYMH48KFCzUebw4MBgPOzs74/vvvoauri99++w3R0dEQiURffJ2Pjw/8/PywdetWFBcXSxwTQRDw9vZG//79sXnzZpSWltb7PB0dHSxatAi3bt2qtT+kDUEQcHd3R+/evbF3717weLxaz2EymRg1ahRSUlLw5s2bFo2nJSAIAp6ennj//j24XK6sw6FpRdq3b4+PHz9+8XlU9UNqaqrCnd9tGTojrABUVFSIXUxpFAOSJFFQUCB2IyUIAgcPHsSYMWOa7YjcXCorK1FaWlrnHUmSJJGRkSG+YBMEAZIkkZeXh2fPnuGnn36SeDvU6w4fPgwGg4FVq1Y1asTI5+8jFAoRGRmJixcvQl9fH3PnzhX3XdN33lsGar+/ffsWly9fBovFwvDhw+Hi4tLkfu6GtkWSJHJzc/H27Vu8efMGFRUVsLW1Rbdu3TB58mSoq6tL9XjHxcXBwMAAurq6Unm/rwlzc3O4ubnh5s2bGDVqlMJ8B5lMJoYPH44tW7bAw8MDOjo6AP5doHbu3Bl37txBcnIy7O3tpbI9gvh3nvHIkSPRsWNHHDhwAK6urhgzZkyDvcMMBgPe3t4gSRKbN2/G0qVLJTLfol7bt29f8Pl8bNy4EStWrKhzVBlBENDT08Py5cuxdu1asFgseHl5tdixJAgCffr0QX5+Pk6cOCGeafw5ysrKmDZtGrZu3QpLS0uZ/1Y2Fh0dHZibmyMmJgadO3dWqNhpmgZlmBUWFiaRUZqdnR2ePn1KO0fLEXRGWAFITk6myz4VDD6fj9LSUvFi4+zZs3ByckLHjh1lfvHLzc2Fjo5OveXN9+7dQ58+fcTnG0mSuHTpEgYOHCixgYtQKMTjx4+xbt06eHl5YcmSJfX2rNUHZYL17t07rFmzBvfu3cP06dOxePFiWFpa0kZYLQQ1Y/fNmzf45ZdfcOfOHUycOBE//PAD3N3dpebATR3fjIwMXLhwAf/zP/+D3bt3o7S0FBMmTMCaNWsQHByMzp07Q1NTU6rHmyRJPHz4UKZ9+ooMQRAYPnw4njx5goKCAlmH0yh0dXXRt2/fWtlfNpuN4cOH4+LFixAIBFLdJjU6ZfXq1eDz+Vi3bh1yc3MbzApRmeEBAwZg69atqKiokHh7DAYDfn5+6N69OzZt2iSejV1XXHp6eli2bBnOnTuHiIiIFs1UUVnf4uJi3L17t9a2CIKAoaEhxo0bh/3796O6urrFYmkJGAwG+vTpg/v378s6FJpWxMbGBrm5ueBwOF98rra2NsrLy79YGULTetAZYTmHmjdb33xAGvmEx+NBKBQiPz9fPLpl/PjxctH3FBcXB0dHxzr/raKiAvHx8Rg3bpw4G0yNoZk8efIXz0GSJFFeXo5jx46huLgYy5cvb9JdfaFQiOTkZJw5cwZCoRCBgYESGc7QNB1KAL9//x6XLl2ChoYGpkyZAnt7e6ntd0r85uXl4cWLF4iKigKTyYSHhwfmzJkDY2PjVnHTLCsrQ1paGqZPn97i22qr6OjowM/PD+fPn0dwcLBcXNskgSAI9OzZE8+ePas1W9jFxQVhYWH49OmT1F2xqezwlClT8Pz5c6xfvx6TJ09Gx44d6913BEGgV69e4HA42L17N+bNmyexyQ6DwcCQIUPA5/Oxfft2LFy4sM4WAoIgYGRkhEWLFmHLli1gs9lwc3NrsfUGi8XCzJkzsXHjRhgbG8Pd3b1Wv7CbmxsSEhJw9uxZTJw4UaGu+05OTjh+/DhKSkroapOvBGVlZaiqqorHnDaEuro6WCwWSktLa3iw0MgOxfjl+oqhZnNKq1SLpnXg8XhgsVhISEhARkYGpk6dCmVlZVmHBZIkERcXBycnp1oLHZIkERERAScnJ7HpA0mSuHDhAgYPHiyev9nQeyckJOCPP/6Aqakpli5d2ugRSyRJIjMzE7t378bhw4cxaNAgrFy5Es7Ozgq1GFI0BAIBYmJi8Oeff+LOnTuYMmUKli5dinbt2kllv4tEIuTn5yMsLAx//PEH9u7dCzabjblz5+L7779HQEAAzM3NW22kRGxsLGxsbL64aKFpGF9fX6SkpCApKUnWoTQKZWVljB07FmfOnKnRr8pgMDBy5EhcuXIFfD6/RbbNZDLh7e2NRYsW4ezZs7h+/XqDGWgqu+vg4IDDhw83qv+UyWQiICAADg4O2LVrF6qrq+vNDJubm2P+/Pk4cuQIYmNjWywzTBAENDQ0EBwcjDNnziArK6vWthgMBgICApCfn4+XL18qVD+lqqoqXFxc8Pr1a1mHQtNKMBgM2NvbIy4u7ovPZbFYMDExQUZGRitERiMJtBCWc4RCIcrLy+k7iwoGh8OBUChEREQEFi5cKDd3/qqrq5GTk1PneAfKRbd3797ibHBWVhaysrLQrVu3BgWtSCRCeHg49u7di2nTpmH48OGNEv4kSaKkpAR///03tmzZgg4dOmD16tXw8PCge+NbEJFIhMTERGzYsAHnzp3DqFGjsHTpUjg4OIDJZDYrK0SSJCorK/HixQts2LABGzduRHFxMaZPn44ff/wR/v7+MDU1lVqptaRQZft9+vRptW22VZSVlTFmzBicOXOmxYRjS9GuXTsYGRmJ+/WAf0WajY0NNDU18e7duxYVgxYWFli5ciXi4uJw8ODBBssqqd5mLS0tnD17FkKhUOJtsVgsjBw5EmZmZti9e3edRlVUTNbW1ggJCcHevXsRHx/fop/fzMwM48aNw4EDB1BZWVnrOWw2G1OnTsX169eRk5PTInG0BARBoHfv3nj8+HGjjhON4kIQBNq3b49Pnz598TtDEASsrKxowyw5ghbCck5paSnYbPYXs3E08kV+fj6ePXuG4uLiWqVfsqSsrKze8yk3Nxc8Hq+GK/TVq1fh5+fXoMs1j8fDsWPHEB4ejpUrV8LJyUniMklqFvDt27exZs0aaGpq4pdffkGfPn2grKwsN/utrUGNs9q7dy/27duHAQMG4Icffmi2ERY15zclJQWHDx/GL7/8ghcvXsDf3x+//vorJkyYAEtLy1YXv59TWlqKvLw8ei67FKDm14pEIsTExCjcwm7UqFG4d+8eSkpKxI8xGAwMHz4c165dq1c0SgOCIKCpqYn58+dDXV0d27ZtQ1lZWb37kMViYdy4ccjNzcWtW7cata+p1+rq6mLPnj0NimE7OzuEhIRg165dSE5OblEx3KFDB3Tt2hVHjhyplRWn+pfHjBmDw4cP15vNlkdsbGzA5/ORnZ0t61BoWglbW1ukpaVJ5C/g4OCAhISEVoiKRhJoISzHkCSJ1NTUVi0ZpGk+JEkiJiYGNjY2cHd3l6ubGCkpKbCysqpTqD558gRdu3YVZ2Dz8/ORlJSE7t271ysYOBwO9uzZg8rKSixbtqxRrtBCoRDR0dFYs2YN4uLi8N1332HkyJFNGoVDIxlUlvb8+fNYu3YtbGxs8PPPP8PT07PZAriqqgpPnjzBmjVrcOjQIVhaWuL777/HggUL4OzsLFPx+3mckZGRcHV1lYtWhbYAi8XC2LFjce7cOYXKClMjhHx8fHD9+nWxeQ1VJmxubo7Xr1+3+FghJSUlTJgwAW5ubti4cSMKCwvr3aaysjKCg4Px6tUrvHr1qlGxsdlsTJ48GSoqKjh48GCDYrhdu3YIDg7Gzp07kZmZ2WL7gCr7ZrFYuHHjRp3mWW5ubrC3t8elS5cURggzGAx4eXnVqDagadtoaGhAJBJJNFLOwMAAhYWFrRAVjSTQQljOSUxMhJ2dncwXkDSSQZUTnzp1Cl5eXuLxHPIASZKIj49Hu3btap1PfD4fUVFR4hJokiRx69Yt9O7du94+yvLycmzfvh36+vqYMWOGxIKfGpOzY8cOnD9/HlOmTEFISAiMjIzo87yFoIywXr58iTVr1qCqqgo//vgjBg0aBBUVlSbvd6FQiOzsbBw/fhw///wzYmJiMHnyZPz4448YMGAAdHR05GrElUgkwtOnT+Hj4yM3MbUF7O3toa+vjxcvXijUwp8gCPj4+CAhIQE5OTni2CmjqVu3brWKuGcymRg8eDAGDhyI9evX19k3S6GpqYk5c+bg4sWLSElJabQYnjZtGkQiEY4dO9agGHZxcUFgYCC2b9+OvLy8FjuuLBYLU6ZMQVRUFKKiourtF05JScH79+8V4vwiCAI9evRAZGQkPVP4K0FJSQnm5uZITk7+4nN1dHQgEAhQXl7eCpHRfAlaCMs5ycnJsLOzk3UYNBLC5XLx999/w8rKCgRBwMDAQNYhiREKhUhJSanTeC0tLQ2qqqowMjIC8G8J9bt379C7d+8636uyshI7duyAo6Mjxo8fL1EfL0mSqK6uxvXr17F+/Xq4ublh1apVaN++vcI4zioiJEkiLS0NmzZtwoMHDxASEoJJkyZBV1e3yWKQz+cjNjYW27Ztw7Zt26Crq4tVq1YhODgYDg4OctvXXVBQgOrqalhYWMg6lDYFNRbnypUrCjfyRlVVFUOHDq01TsnU1BTm5uZ49epVq8RBzQ6eNGkStm7d2mAPoaGhIaZNm4aDBw+iuLi4UdtRUlLC9OnTUV5ejlOnTtVbykkQBDw9PcVzlxu7ncagqqqK4OBgnDt3Drm5uXX++7fffouzZ8+2aBzSRE9PD5qamkhJSZF1KDStAEEQcHJywsePH794s4bNZkNXV7fOc52m9aFXn3IMZSBEG2UpBpTDsp2dHczNzVFVVSVXC24ej4fKykro6enVeJwkSTx//hxeXl7iv7948QIuLi7Q1NSs9T4CgQCHDh2Cra0tAgICJHIVprLRv//+O9LT0/H999/D19e33lnGNM2HKlc+ffo0tm/fjr59+2Lp0qX1lsZL8n5cLhdPnz7Fb7/9hrNnz6JXr174+eefMWTIEOjq6sr1DQ3qPPfw8KDPuxbAwsICjo6OuHfvnkJk7SgIgkCnTp3Eo+M+zwoPGzYMt27darWsHlUKPG3aNOzcubPeHl2qfNnPzw8HDx4El8tt1D6nSqxzc3MbNN8iCALe3t7w8/PDxo0bG+xhbg4EQcDY2BhjxozBwYMHUVVVVWs7JiYmGDRoEI4dO6YQJfjUHOhHjx4p1PeBpuk4OjpKZDJHmeXRztHygfyuWmhQUlICBoMBLS0tWYdC8wVIksTbt2+RnJwMf39/VFZWgsfjyVW5b1FREdTV1WuJAC6Xiw8fPqBz584gCAI8Hg+PHj3CwIEDa70HSZK4efMmeDweRo8e/UURTImxEydO4MCBAxg/fjxmzZrVrGwkTcNQhlXv3r3DL7/8gurqavz888/o1q1bk/qAqWN4584d/PTTT3j58iW+/fZb/PDDD/D09FQYUzORSIQXL17Ay8tLIeJVNBgMBr755hvcvXsXZWVlsg6nUbBYLHzzzTc4f/58DVFoZmYGExMTREREtJqYIQgCzs7OmDlzJnbv3o20tLR6xXDPnj1hZmaGixcvNio+giCgoqKCkJAQJCUl4dKlSw2KYV9fX3h7e2PLli11ilRpQBAE3N3d0b59e5w5c6bOfuEePXpASUkJ4eHhci8uKSO5uLi4Bh3BadoOenp6qKiokMhkz8HBAYmJia0QFc2XoIWwHJOdnQ1DQ0PaKEsBKCwsxNmzZxEUFAQWiwWBQIDS0lIYGhrKOjQA/4qZxMRE2NjY1BKvGRkZ0NLSgra2tvh5mpqaMDY2riUYEhMT8fDhQ0yfPv2L5a8ikQgfP37Eb7/9BqFQiJ9++gkdOnQAg8GghUgLQZIkSktLsXfvXly4cAHBwcH49ttvoaGh0SQBXF5ejmvXruF//ud/kJKSgoULFyI0NBT29vYKdxzT0tLAZrNhYmIi61DaLPr6+ujevTuuX78u90Llc6gMq6amJt68eVMj9uHDh7dqVpiKx9HREdOnT2/QsIoqSU9JSakVtyTbUFNTQ2hoKKKjo3H9+vUGxfCQIUPg6uqKnTt3tpiDM4PBgL+/P4qLi/H48eNa22AymQgMDMSjR4+Qnp4u9+eYpqYmzM3NJRqrQ6P4qKurQ0dHR6JMr4mJSQ1fAhrZQQthOSY1NRXW1tayDoPmC1Djg4YNGwYTExOIRCLweDxUVVXJVY9wQkJCLaMskiTx8uXLGiZZ9+7dQ//+/WuVuVZVVeHQoUOYNm3aF03Aqqurce7cORw9ehRTpkzBpEmToK6u3hIfi+b/IxAI8OrVK/z2228wNzfHd999B3t7+yYJ4NLSUly5cgVr1qxBcXExli9fjpkzZ8Lc3FyhxO/nPHnyBF5eXvSNxRaEIAgMHToUb968QV5enqzDaRQMBgOjRo3CjRs3xBk8giBgamoKY2NjvH37tlUXrdRs0ilTpmD79u3Izs6uc/sqKioICgrCxYsXmzSuR01NDYsWLUJERATu3Lkjds/+LwwGAyNGjICZmRn279/fYqOllJSU8O233+L27dtIT0+v9e+ampoYN24cjh8/LvdGVJ+XR9O0fQiCkHg0kpGREcrKyhTOU6EtQgthOSYxMbFOYyMa+YEkSTx48ACamppiMSkQCMDj8cBkMuWmF1EkEiEtLa3WjRUej4fY2Fh07NgRBEGgtLQUmZmZcHZ2riWYw8LC4ODgAGdn53q3Q5IkMjMz8eeff6KsrIw2w2oFSJJEUVERdu/ejVu3bmHRokXw9/dvtBs0SZKoqKjAlStX8Ouvv6KsrAzfffcdJk+eLFcl/k2Bx+Ph/fv38PT0lHUobR4NDQ34+fnh8uXL9YoqecXU1BT29vY1xt4QBAF/f3+EhYW16FzhuqBm7QYGBmLnzp0oKiqq83mGhoYYP368uL+2sdvQ1NREaGgoHj9+jAcPHnxxlrGKigr+/vtviWamNgVdXV1MmjQJhw4dQkVFRa1427dvD3t7e4WoPHByckJ6ejoqKytlHQpNK+Di4oIPHz588XmqqqpQUlJCaWlpK0RF0xD06lROEYlEyMvLg7GxsaxDoakHyo33yZMnGDt2rFjslZeXg8ViQVlZWW4EII/HA5fLrdVvnpubCzU1NWhpaYEkSTx79gydOnWqMQqJJEnk5eXh6dOnGD16dJ2CiOpLffHiBTZu3IhBgwYhKCioSSW5NJJDzcX9448/YG9vj5UrVzY6a0uZYN29exe//PILCgsLsWrVKkyaNAl6enpt4vilpKRAXV1dbloV2jIEQaB3795ISEho0Rm0LcXQoUPx8OFDsXChssJ6enqIiYlp9c9D9ZoOGTIEf/31F8rLy+udt+vi4oJLly41+gYEQRDQ1tbGokWLcOvWrTrLkimojG15eXmDRlvNgXLg7dKlC06dOlVrG1QJ9YcPH5CQkCDX55iGhgbs7e1bvaKARjaYmpoiLy9PoptE+vr69d7comk95GOVTlOLiooKcLlc6OvryzoUmnqorq7GkSNHMHHixBqCr6ysDAwGA+rq6nIjhDMzM6Gnp1dL4L569QoeHh5gMpkQiUR4/vw5evbsWSsbfOHCBQwePBiampq1hBE1o/bs2bO4ceMGVq5cie7du8vNZ2+LkCSJyspKHDp0CBcvXsSCBQswZMgQsNlsiYUrddxevHiBn376CXFxcVi6dCmmTZsmFsBtQQSTJImnT5+iZ8+esg7lq0FFRQXDhw/H2bNnFSorTBAE9PT04OrqWsPtl5orfPPmzRYRfpLE5e3tjU6dOonLkusSVcOGDUNaWhrevXvXaNFFffYlS5bg8uXLePnyZb3voaysjLlz5yI+Ph43b95ssWM8cOBAVFZW1sjQU6ioqGDSpEk4fvx4o7PgrQlBEOjVqxfCw8NlHQpNK6CjowMWi4WCgoIvPtfe3p42zJID6JWqnFJYWAgtLS26n01OEYlEOH/+PNzc3Gr13ZaXl6OqqgqGhoZyISRIkkRycjKsra1rxCMUChETEyMui05LS4OSklINMyGSJJGRkYGMjAx4e3vX+XkqKiqwY8cOFBUVYcWKFXWabNFID5IkkZSUhN9++w3q6upYtWpVrWP7pdcLhULExcVh7dq1ePToEebOnYs5c+bAxMSkzQhgCg6Hg9jYWLErOk3LQxAEunTpguLiYrnP2P0XgiAwcOBAPHnyRFyWSxAErK2twWazkZiYKJPPw2AwMHjwYBgbG+PEiRO1xCdBEOJs7fnz51FcXNwkMWxkZISlS5fi7NmzDbplq6ioIDQ0FM+ePcOjR4+kLoYJggCbzcaUKVNw586dWtUFBEHAxsYGnp6euHjxolzfcLG3t0dxcTEKCwtlHQpNC8NgMGBqaoqsrKwGn/f5CCVFuj62RWghLKdkZGTI1Qxamv+DJEm8e/cOGRkZGDp0aK3MZ3l5Oaqrq+WqDPPTp09o3759jcdKSkogEAjEVQePHj1Cjx49atx8IUkSly5dwtChQ6GiolLrfYuKirBp0ybY29tj5syZtCFWC8Pj8RAWFoa9e/di0qRJGDt2bI0s/5cgSRK5ubnYtWsXjh49ihEjRmDx4sWwsbFpsxn81NRU6OjoQFtbW9ahfFUoKSlh5MiROHPmjFyLlLrQ1dVF586da8xEZrFYGDRoEK5duyazhSuTycTo0aNRXl6OsLCwOsWwiYkJBg8ejOPHjzc5e21sbIzQ0FCcPHmy3nJwqrd40aJFuHHjRqNdqyVFR0cHY8eOxZEjR2oZC1E3LbKyshAbGyu3gkJFRQWurq54/fq1rEOhaQUk7RO2sLBATk6OTKpMaP6PtrnyaQMkJibCwcFB1mHQ1EFJSQnOnz+Pb7/9tk4zrIqKCvD5fLmalZubmwsjIyPx30mSxPv379G+fXuw2WxUV1eLs2afPycnJwe5ubl1ZtNyc3OxYcMG+Pj4ICAggK5eaGFKSkqwY8cOxMbG4rvvvoOrq6vE4pWaBXzx4kWsX78erq6u+PHHH+Hm5tamjxtVFl1fNQNNy0EZPZEkiZiYGFmH0ygIgkC/fv3w8uVLlJeXix93dnZGRUWFRONRWgplZWUEBQXh1atXiIyMrLNfmJoZXldJsSQQBAFzc3PMnTsXhw4dqjcLThAE9PX1sWDBApw8ebJFxChBEHBxcYGLiwvOnz9fS/yz2WwEBgbi3LlztYy15AkfHx88e/aMFj1fAba2tkhNTf3iDUAdHR1UV1fTc6ZlDC2E5RCRSITMzExYWFjQizc5QyAQ4MyZM+jXr5+4jPRzSJJEWVkZRCLRF0cMtRZVVVXgcrnQ1dWt8fjr16/FAjcpKQn6+vq1Yr558yZ8fX2hrKwsfoxyKd6yZQuGDRuGfv36tdlsojxAkiTi4uLw22+/wcXFBQsWLICOjo7E1waRSITIyEj88ssvKC4uxk8//SQ+pm39+lJdXY1Pnz6hU6dObf6zyiNsNhtjxozB2bNnwefzZR1Oo9DW1kb37t0RFhYmFndsNhsDBgyQuVuxuro65s6di3PnztVZWslisTBhwgTcvn27yWOsCIKAra0tgoODsWPHjnpLOAmCgJmZGebOnYu9e/ciNTVV6vuGwWBg6NChyMjIQFRUVK0SaXNzc3Tr1q1JRmGthY2NDXg8HnJycmQdCk0LY2pqitLS0i86hTOZTKiqqsr1DZyvAXr1KodwOByUlZXV6NWkkT3UzF0ulwsfH596F9YlJSVi4xF5IC8vD1paWjXEbHV1NQoLC2FhYVHDTOi/vc4fP34Uj4UC/s9heNeuXejfvz+daWtBSJKEQCDArVu3sG/fPgQHB2PQoEFgsVgS7XOSJJGfn49t27bh6tWrmD17NoKCgqCtrf1VHDOSJJGYmAgjIyNoaGjIOpyvFicnJ6ipqdWZvZRnqKxwZGQkSkpKxI97enoiIyNDpnOSCYKAoaEhJk+ejIMHD6KioqLWvtXW1sbIkSNx7NixJo99otybg4KCsHnzZuTk5NQrhqn2mG3bttX7vOZAZcLPnz9fy2mXOlbZ2dlyWyLNYDDQtWtXvHjxQi7jo5EebDYbmpqaNa4bdcFgMGBubi7TChMaWgjLJRUVFVBWVgabzZZ1KDT/H0pUhIWFITAwsMFyUkoI/3dUkazIysqqNVInKSkJxsbGUFdXR1VVFRITE+Hm5lbjda9fv4azs3MNEUGSJE6dOgULCwv4+vp+FYJKFlClzPv27UN0dDS+//57ODo6SiyAuVwubt26hT///BNubm747rvvYGdn99UdrydPnsDb2xtMJlPWoXy1EASBsWPH4vLly+ByubIOp1Goq6ujW7duNXqFlZSU0KdPH9y5c0emgoYgCDg7O8PLywv//PNPrXEtBEGgU6dO0NHRwZMnT5ocK0EQcHd3x4QJE7B582YUFBTUK4ZdXV0xZswYbN++HSUlJVLfP4aGhhg2bBiOHz9eS9wrKSlhwoQJOHfunFy6SBMEgR49eiAiIqLV51HTtC7UjaGEhIQvPs/KyqpFqihoJIcWwnJITk4OjI2N6XJTOUIoFOL48ePw9/dvcKQVSZLgcDhgsVhycyMjPj4e7dq1q/FYZGQkPDw8xGXRJiYmNYyu+Hw+Hj16hH79+tUQT5GRkUhKSsK4ceNocdFCUL3Z69atg5GREebPny9xvzlJkkhNTcW6deuQkJCA7777Dv369auzl72tw+VykZCQABcXF1mH8lVDldgaGhri9evXCrXgozKNERERKCsrEz/m7e2NmJgYlJaWyjy+/v37g81m1yjh/vzfR48ejfDwcOTn5zdrO127dkVAQAC2bNlSr8glCAJeXl7o27cvdu/eLfXeR6r/WVVVFeHh4bVisLCwgKenJy5fviyXJdKGhoZgs9lfdBSmUWwIgkC7du0QHx//xeudtbU10tPTFeq62NaglZYckpycDBsbG1mHQfP/IUkS4eHhUFNTk2gEC4/HA5PJlAuhSJIkMjMzYW5uLn6MGp3Tvn17cbl39+7da7wuPT0dBEHA0tJS/FhpaSmOHz+OGTNmQE1NrdU+w9cEZWK2fv16DB06FCNHjqxR0t7Q67hcLi5duoQdO3ZgyJAhmDNnDvT19b+6LDDw7/74+PEjTE1N5aYy42uGIAiMHDkS165dq+X8K+9oamrCw8OjxlxhNTU1uLu7y0WZK4vFwsSJE/HmzRt8+vSpVv+slpYWhg4dijNnzjTLqIkgCPTs2RO9e/fGtm3b6u1/ZDAY6N+/P+zs7LBv3z6pZz+ZTCbGjRuHx48f1+pbJggCfn5+SElJkUiEtDZMJhNeXl7NytDTKAZ2dnZIT0//ojeCiYkJCgoKalV00LQetBCWM6i5rVZWVl/lAlbeoLJz9+/fx4QJE74obilBoqSkJBdCuLq6GqWlpTA2NhY/VlBQAJFIBCMjI1RXVyMpKQmurq41+oCfPHlSo2dYJBLhwoUL8PHxqSGOaaQDNdv3zp07OHbsGBYtWoRu3bpJVBVCkiTS0tLw+++/IycnBz/99BM8PT3BZDK/6mvIo0eP4OPjQ1fWyAHUzEwrK6smOxnLkgEDBuDZs2di8Udlih8/fiwXZa5qamoICgrC0aNHa2VrCYKAh4cHGAxGszPyDAYDAwYMgLu7O3bs2FHvTQ1qzBOLxWrWGKf60NTUxPjx4/HPP//U2v9sNhsTJ07EmTNn5O6mCzVf+/3793Jx3tC0HJqamhAIBF+silBWVoZQKKSFsAyhVwhyhkAgQE5OTo0MHo3s4PP5OHHiBEaPHg1NTU2JXlNZWQldXV25EMKlpaVQVlauMWs2MTFR3C+anp4OPT29Ghne6upqfPjwQZz9psptP336hMGDB3/V4qolIEkSPB4Px48fx5s3b7Bq1SpYWlp+cT+TJAk+n48bN25gx44d+OabbzBr1ixoaWl99ceIw+EgNTW11uxsGtnBYDAwYsQI3Lx5U6HGhRAEAW1tbbi6utbI5BkYGMDExKTeObutHaOlpSUGDhyIo0eP1lpUs1gsjBkzBmFhYc12qGUymQgICIC5uTn2799fr6Bjs9mYMWMGcnNzcfXqVamWKlMmXvb29rUcvKm+S1dX1zrLxWWNjo4OdHV1kZycLHex0UgPFosFIyMjZGdnN/g8JSUlaGho1DKAo2k9aCEsZ/B4PAiFQrr0VA4gSRIPHz6Enp4e3N3dJe7RLCsrg66urlxkovLy8mBoaCj+O0mSePfuHTp27AgAePXqFbp06VIj1oyMDGhra4tLSoVCIc6dO4dRo0ZBRUWldT/AV0B5eTl27NgBHo+H0NBQiUYjkSSJvLw8bNy4EYmJiVi1apU460MDfPjwARYWFhLfvKJpHUxMTODs7Iz79+8rlAigSm4fPXokzjIyGAz4+fnh9u3bctGPSvUu19c/a2BggB49ekilf5Yaz8RkMnH8+PF6yz9VVFQQEhKCiIiIOmNqDgwGA8OHD0dMTEytMmiCIDBw4EBER0fXO/ZJVlDl0U+fPpV1KDQtCGWY9aUSfQaDATMzM9o5WobQqyY5o7S0FGpqanJjtPS1QpVEP336FKNGjZJYYPB4PFRVVcnNiJqEhAQ4ODiI/87lcpGWloZ27dpBIBDg06dPtcqinz59ih49eoDBYIAkSSQkJKC6uhodO3aUi8/UViBJErm5udi4cSOcnJwwderUGpn7+hAKhXjx4gXWrVuHnj17Yu7cudDT06OPzf+HJEk8evQIvXr1oveJnMFgMODv74979+4p3OxMAwMDtGvXDs+fPxcvbG1tbcHn8+VGbLFYLHH/7H8NeAiCQJ8+fZCRkYGkpCSpbGv69OkoKCjAxYsX6y1/1tDQwPz583Hjxg28e/dOqvtJRUUFkyZNwqlTp2r1LKupqeGbb77BqVOn5K7s1M3NDbGxsQo3W5tGcgiCgIODAxISEho856k52PJyDfkaoYWwnJGamgoLCws6syNjhEIhTpw4gREjRjQqq1RdXY2Kigpoa2u3YHSSQZIk0tPTa/SbFxUVQUlJCerq6sjPzwebzYaOjo74NXw+H7GxsXBzcxOXRV+8eBHDhw+nb85IEarcfOPGjRg0aBCGDRvW4Egu6jVVVVU4cuQIwsLCsGzZMvj4+HzxdV8b5eXlyMzMhLOzs6xDoakDQ0NDeHh4yGXZakNQWeF79+6JhRWLxUK/fv1w8+ZNGUf3f2hqamLcuHH4559/ao2rYrPZGDNmDM6fP9/sUVYEQUBJSQlz587Fx48fcfv27XqdpA0MDBASEoLDhw9L1SGXIAjY2NjAw8MD165dq5HppsZL6evry505la6uLvT19REfHy/rUGhaEFNTU+Tn53+xR97W1hYpKSmtExRNLWi1JUdQwkWS/kCaloMkSTx+/Bja2tpiQSgpXC4X5eXlcuFUy+fzkZubCwsLC/Fjnz59gqOjIxgMBiIjI+Hq6lqjlzknJwdqamrQ0tICSZJITk4Gj8eDs7MzfU5KCZIkERMTgx07dmDatGno0aOHRKXQmZmZ+P3336GiooKVK1fCxMSEPiZ18OnTJ1hZWUmUXadpfQiCgL+/P54+fYqSkhJZh9MoTExMYGRkhLdv3wL4v1m9qampKC4ulnF0/0L1zzo5OeHKlSu1ssJ2dnYwNTXFs2fPmi0OCYKAmpoaFixYgPDw8HoFJ9W3O23aNGzbtk2q+4q6QZGcnFwr+8ZkMjFy5EjcvXtXrnowGQwGevbsWcOJnKbtQbU41uewTqGrq4uSkhK5aLH4GqGFsBxBkiRSUlLo0UkypqCgAPfu3cOoUaMabXjF5XLB5/PlQghzOByQJCmeD0ySJGJjY8WZsqioKPEsYerf3759iw4dOoizjNevX8fAgQPpbLCUEIlEePnyJf755x8sWLBAohsMQqEQT58+xebNmzFmzBhMmDABKioqtAiuA5Ik8ezZM/Ts2VPWodA0gLa2Nry8vOrNIsorDAYDgwcPRlhYmDgrrKamhi5duki9B7Y5UCXo8fHxdfbPBgQEIDw8XDwbuTkQBAEdHR2Ehobi0qVLiIqKqlcMu7u7Y9iwYdi2bZtUS+OVlZUxYcIEnD59upZTtI6ODgYNGoSzZ89K3b26Obi5uSEhIUGhjONoGoeSkhJMTU2RlpbW4PPU1dXB5/PpUnkZQQthOUIkEqG0tBR6enqyDuWrRSAQ4NSpUxg2bFiNkmFJ4XK5YLFYclEaXVFRATU1NXGZPY/HQ2ZmJuzs7FBeXo6KigqYmpqKn0+SJKKiotCpUycA/5ZRZ2Zmio21aJqHSCTC/fv3ceXKFSxZsuSLI9KoUuijR4/i3r17WLFiBTp16kS3TTRAeXk50tPT6QoGOYcgCAwaNAgvX76Um0yqpNjb24PBYCAxMVH8WO/evfHq1Su5GtejoqKCwMBAnD59GlVVVTX+TVtbGz179sT169elloUyNjbGwoUL8ffffyMuLq5eMdynTx+4uLjgwIEDzS7P/hxra2u4ubnh6tWrtbbt5eWFyspKuXD4ptDW1oaRkRESEhJkHQpNC0FVYCQmJjZ43qmoqEBTUxN5eXmtGB0NBb2ikiOqq6tpx2gZQpIkXr58CSaTiS5dujRpIc3lcsFkMuXCrTYtLa1Gv3lZWRlYLBbU1NQQHx8PS0tL1XQSgQABAABJREFUKCsri59fUVFRQxw/ffoUnp6etFO0FBAKhbhy5QqePn2KpUuXwtjY+IsiuKCgABs3bgSDwcDy5cthZGREi7svkJCQAEtLS/qcVQC0tLTQo0cP3Lp1S27EiSQQBIHBgwfj5s2b4gyjvr4+jI2N8fHjRxlHVxMbGxu4ubnVErwEQaBnz55ITU2VqkmPhYUFZs+ejb179yIrK6teMTxq1CgoKyvj9OnTUsvSUk7R8fHxNW5SAP+WSI8bNw6XLl2Sqwxsr1698PjxY4U6/2kaR7t27b7YC85gMGBsbIzs7Gz6XJABtBCWI3JycqCnp1dDnNC0DiRJori4GGFhYRg/fnyTs248Hg/KyspQUlKScoSN47/95iRJIj4+HjY2NmCxWIiIiICnp2cNYZWUlAQzMzOoqKiAy+Xi+fPn6N27Ny2+mgFJkuLxU3FxcVi8ePEXKw1IksSnT5+wdu1a+Pr6YuLEiXQptASIRCKx4zm9r+QfgiAwYMAAvH79GsXFxQqzACQIAh06dEBRURFycnLEj/v5+eHu3btyVX5LZd4TEhJqza1VVlaGv78/zp07J7WsMNWfPHHiRGzfvh0lJSW1jitBEGAymZg6dSoyMjJw584dqR17FRUVjB8/HqdOnaoheClnXldXV7kpxycIAm5ubkhKSlI4B3UayTEwMEBRUdEXv2NWVlZfLKGmaRloISwnkCSJjIwMmJmZ0Ys4GSASiXDu3Dn4+flBV1e3yceAx+OBzWbL3MmXOp8sLS3Fj3348AGurq4QCARITk5Gu3btarwmOjoaHTp0AEEQSEhIEJdu0TQdoVCIU6dOISsrC/PmzYO6unqD55ZQKMTdu3dx4MABhISEoGfPno3uU5cXSJKESCSCUCiEQCAQ/6F6oai/C4VCiEQikCTZrAVqdXU1UlNT0b59e/oaqiBoaWmJS3QVCcot+tatWxCJROJRKeXl5XJX3qisrIxx48bhzJkz4PF44scpV2UWi4Xo6GipbY8gCHh4eGDAgAHYunVrnUZBBEFARUUFc+bMwb179+rtK27Ktu3s7ODk5ISbN2/W6o0eNGgQoqKikJOTIxdiWF1dHebm5nR5dBtGS0sLTCYThYWFDT7PysoKqamprRQVzefQczfkiOTkZDg6Oso6jK8OyiSqqqoK3bt3b9Yims/ng8ViyVwICwQCFBYWwtjYGMC/Qj81NRUjRoxAbm4ulJWVoaurK34+lTHu3bs3SJLEkydP4OPjI6vw2wR8Ph/Hjx9HeXk5Zs+e3aCLMUmS4PF4OHPmDNLT07Fq1apm3ZBpDahsN5fLBY/HQ2lpKfLy8lBUVITS0lKUl5ejrKwMHA5HbCxEEASEQiEYDAYIggBBEGAwGFBWVoa6ujq0tbWho6MDHR0dGBkZQU9PD0pKSlBWVgaLxap3f5Akibi4OJibm4vN4WjkH4Ig0K9fP/z6668YMmQI9PX1ZR2SRBAEgS5duuDWrVsoLS2Frq4uWCwWvL29ER4ejnHjxsnNd5cgCNja2sLW1hb37t3D4MGDxbExmUx88803+Pvvv+Hk5CS1lgIGgwFfX18UFRVhz549mD9/fq1KN4IgoKuri3nz5mHz5s3Q19eHlZVVs7dNEASGDRuGTZs2oVOnTrCxsRF/XjU1NQwdOhTnzp3D3Llz5eImY8+ePfHkyRN07NiR9n9og7BYLJiamiIzM7PBxIKenp7C+SW0FWghLEdkZmbC19dX1mF8dZSXl+Py5cuYM2dOs92RqTvu8iCEhUKhePFRVlYGkiShpaWFR48ewcnJqcbzS0tLweFwYGJigqqqKiQmJiIwMFBuFnOKBo/Hw9GjR8Hj8RAcHNxguwNJkigvL8e+ffugo6ODRYsWyV0pNCXUS0tLkZ+fj4SEBGRkZCA3Nxc8Hg8sFguampowMDCAvr4+jIyM4ODgAB0dHairq4PFYokXnZ+7lFNZYy6Xi4qKCpSWlqK0tBSZmZmIiopCSUkJ+Hw+CIKAoaEhLCws0K5dOxgYGEBHR6fG94wqi6YXk4qFlpYWevXqhatXr+Lbb7+Vq/O+IdTU1ODp6YnHjx/D398fBEGge/fuWLduHQICAuTK64PBYGDo0KHYvHkzOnXqVMMk0cLCApaWlnj+/Dn69Okjtf3PZDIxatQoHDlyBEePHsXUqVPr/F20tLTE1KlTsXPnTqxcuVIqZqEqKioYO3YsTp8+jdDQULHAp7LVjx49QnR0tMyNIAmCgKurK86cOYOqqipoaGjINB6alsHR0RGfPn2Ch4dHvc/R0dEBj8dDVVUVfTO3laGFsJwgEolQVlYmF27DXxMkSeLixYvw8fERZ0+b815cLhcMBkPmQriwsBCamppQUlICSZJITEyEpaUllJSUEB0dDT8/vxrPp+5WstlsfPz4EaampvTFuInw+XwcO3YMfD4f06dPb7BfnCRJ5ObmYvv27fD29sagQYNkfu5QJYPV1dXIysrCx48f8enTJ+Tm5oLJZMLQ0BAODg7o2bMnzM3NoampCSaTCSaTKc7ySisOoVAIoVAojiU1NRW3b99Gfn4+gH/LyTp06ABLS0skJCRg5MiRKCoqAofDqVF+TWWkP89EUy0MSkpKUFFRgaqqap03LBRFmCkqVFb4559/RkFBAQwNDWUdkkQQBIFevXphy5YtGDhwIJSVlaGlpQVbW1u8ffsWXl5ecnXuaGhoICAgAGfPnkVISEiNbGhAQAC2bdsGT09PqRo9slgsTJ48GTt37sTFixcxatSoWjeqCIJAx44dkZubi7/++guLFy9u9gxwqlTd0tISDx48wKBBg8THgsViYezYsTh48KBUs+BNRVVVFVZWVvj48SO6dOki01hoWgZbW1u8efMGJEnWe01QUlKChoYGioqK6LVXK0MLYTmhpKQETCZTLubPfi1Q5ZTZ2dmYMGGCVBYtHA4HKioqMi+5Sk9Ph5mZmXjR8eHDB7i4uKCqqgq5ubmwtbWt8Xk/fvwIZ2dnkCSJp0+fwtvbW64WcYoASZIQCATiTHBQUFCDFQYkSSIhIQF79uzB+PHjm+xULg2ozGxOTg6io6MRERGBwsJCaGtrw9nZGX5+frCysoKmpqY4xpaOlSAIcSZZSUkJmpqasLW1RYcOHZCbm4vY2Fg8efIEp0+fhkgkQlZWFiIiItCuXTs4ODhAQ0MDbDYbTCZTfHOB+l7yeDxxv3J1dTU4HI64mkNNTQ0aGhrQ0dGBubk5jI2NYWxsDG1tbbGQbo3P/zWhoaEBX19fXLlyBUFBQQqzb/X19WFmZoZ3796hS5cuYDAY6NevH06ePNnsNhtpQwnOZ8+eITIyUmyWSM0B9vDwwP379xEQECDVuJWUlDBr1ixs2LABBgYGdWadKeO0nJwcHD16FEFBQc2+IchgMBAQEIANGzagc+fONcpSLSws4OTkhHv37mHIkCEyPU6Ug/ejR4/QuXNnuqKlDWJiYoLi4mKxmWpdEAQBfX19FBYW1vB2oWl5aCEsJxQUFEBPT0/mAuprgsvl4vz585gwYYLUXJ6rq6uhqqoq0+NIGWVZWFiIHaNTUlLQt29fFBQUQFNTs8ZdcJIkkZSUBH9/f/B4PCQnJ9Nl0U1AKBTi5MmT4HK5CAoKavCcEolEiIqKwokTJxAcHAxHR8dW3d9UWTKXy0VycjJevXqF2NhYKCkpwcnJCd988w0sLCygoaHR6ucBdUOBy+UiIyMDycnJSEpKQkFBAfh8PjQ1NWFoaAgTExPMmTMHWlpaOH78OFxcXKCkpITIyEiUlJTA2toa3t7eMDU1bbC/mNqmSCRCVVUVKisrUVFRgeLiYqSnp+Pjx48oKCgAl8uFhoYGLC0tYW9vDwcHB2hqaoLNZks1E/41QhAEfH198T//8z/Izc2FiYmJrEOSCAaDAT8/P5w9e1YsLK2srCAQCJCZmSl3C1qCIDBmzBjs2bMH7du3F5fiUvt/48aN6NWrVw3/CGlsU0NDA/Pnz8eff/4JfX19sSnj5zCZTIwfPx7bt29HWFgYhgwZ0mxRqKmpCX9/f5w8eRLz5s2r0Z7h7++P9evXo2vXrjKtQiAIAu3atcOJEyfA4XDobGAbRENDA0pKSiguLm7w2mZtbY3U1FR06tSp9YKjoYWwvJCdnQ0zMzNZh/HVQJIkHjx4ADs7O9jY2EjtfblcrsyFMACkpqaK+1Gqq6tRUVEBAwMD3L9/Hy4uLjUWIdXV1cjPz4elpSXS09Ohq6tL9yo1EqFQiLNnz6K0tBQzZ85ssCdYJBLh4cOHuHPnDhYtWtSqTvEikQjl5eX49OkTXr58idTUVBgZGcHT0xNDhgyBnp5eq5dmU8K3vLwciYmJiImJQWpqKvh8PoyMjGBnZ4d+/frBwMAAmpqaUFZWrrG/OBwOSkpK4OvrCx0dHQwePBiFhYWIiIjA4cOHIRKJ0LNnT3Tt2hXa2tp17mtqpIumpmaN0tCuXbuKRXJlZSXKysqQlpaGuLg43Lp1Sxxjhw4d4OzsDF1dXSgpKdGiuAmoqalhwIABuHbtGoKCghQmM2ZnZweBQIDU1FTY2tqCzWajZ8+eePjwISZNmiRX5wLVa+/p6YmwsDCMHDlSvJ81NDTQs2dP8QhBacetr6+PefPmYdu2bQgNDYW1tXWt56ioqCA4OBh//vknzMzM0KlTp2bH0blzZzx//hxv3rxB165dxe+nrq6OgQMH4uLFi5g+fbpMf7M1NDRgY2OD6OhodOvWTa7OGRrpYGxs/MWbfBYWFnj69GkrRkUD0EJYbkhMTISLi4usw/hqyM3NxatXr7B48WKp/ujw+fwvjshpaUQiEUpKSsTzarOzs6GjowNlZWXExsZi+PDhNeIrLS2FkpISVFVVERkZCXd3d5kLeUVCKBTi4sWLyM7Oxty5cxvsORMKhbh+/ToiIyOxdOnSVnGGJkkSJSUliI2NxbNnz5CdnQ07Ozt4eXnh22+/hbq6eo2S39aAJElUVVUhPT0db968QXx8PAQCAWxsbNChQwf4+/tDQ0NDfEOhodgSEhJgYGAg9ldgMpkwMjLCoEGD0L9/f2RnZ+Phw4f4/fff4ejoiAEDBsDKykric5wSyVpaWtDS0oKFhQV69OgBgUCA6upqpKen4927dwgPDwefz4eDgwO6du0Ka2trmV8LFAmCINC7d2/8/PPPyMvLU5isMDVK6fbt2wgODhY7Sq9duxYcDkeuTLOA/8v+btq0CdnZ2TA3Nxc/7u3tjQ0bNqCgoAAGBgZSPXcJgoC1tbXYGGvFihUwMDCo9TxtbW2EhIRg06ZNYoO85kBlmnfu3AknJyfxdYIgCHTt2hVPnz5FXFycTMeuUeXRd+/eRbdu3WQSA03L4ujoiLi4uAYN2gwNDVFQUACRSKQwNwLbArQQlgNIkkReXh769u0r61C+Cqjs3bBhw6RehiQQCGSeTaXmtFKfLTk5Gba2tuDxeCgsLBQvfCgyMjJgbm4OgiAQHR2NWbNmySJshUQkEuHmzZtITEysc0QIBZX1PHPmDDIyMrBkyZIWE0mU2VVFRQXev3+PR48eIT8/H/b29vDz84Ojo2OtrGpL83lMMTExePHiBbKysmBgYABPT0/4+fmJW0MaExc16qtnz5519h2y2WxYWVlh8uTJ4HA4ePnyJQ4cOAB1dXX4+/vD2dm50dv8/L3ZbDZcXFzg7OwsNjyMjo5GWFgYcnNzYWlpCR8fnxqmPLQwrh9VVVX0799f4bLCnp6euHbtGoqLi6GnpwdtbW1YWlqKM3zyhoqKCoYNG4YLFy7UGCOkpqaGfv36iXu1pQ1BEHB3d0dRURF27NiB5cuXQ01NrcZ3giAIWFhYiE22vv/++2a3aBgaGqJHjx64evUqAgMDxecVm83GqFGjcPLkSSxfvlxqLVJNwcHBAUePHkVlZaXM1xA00oW6CXTt2rUGDbMMDQ1RWVmJ6upqubuB1pahhbAcwOfzUVJS0uCMMRrpQJIkIiMjwWQy4e7uLvVFqUAgkKrrZlMoKCiAuro6VFRUQJIkPn78CG9vb+Tl5dXZH5yYmAh7e3vxqBpFcW2VNSRJ4vHjx4iIiMCiRYugqqpa5/lEkiT4fD7+/vtvVFdXY+HChS3iVEr1/H748AHh4eHIyMiAjY0NhgwZAicnJ/Eir7WEGCV+ORwO3r17h6dPnyInJwe2trbo06cP2rVrJ/6xb2pMHA5HPOqrIQiCgJqaGvr06QMfHx/ExMT8P/bOMy6K83v718wW6gJL7wgiTZQuCIIFK9jbzxqNmkRjEjUxaow9mqbGxBiNURM1xl6JCioW7AURG2JBEFA6S1nYXbbM88Jn9i+hwzZgv58PL9gyc2bmntn73Oec6+DEiRM4fPgwRowYAW9v72Y5xO9un8FggMvlokePHujRowcqKyuRkpKCixcvYu/evXB3d0fPnj3RoUOHFu2rLUNHxlauXClXkG4N50lXVxcBAQG4fv06oqOj5UrYJ0+elItoaRIEQcDb2xsJCQlISUmR1+wSBIFu3brh/PnzSqvVJggCPXv2RGFhIf744w/Mnj27hgNKEAT8/f2RlZWF7du31/qZpu6TroF++fIlOnbsKD9eZ2dn2NnZ4dq1a+jVq5faxpuBgQGcnJzw+PFjBAcHq8UGLcrDzs4OBQUFEIlEdf7+s1gssNls8Pl8rSOsQjTr6dxOKSsrA0mSWpEEFcDn83Hq1CmMHDlSKbWQYrFY7Q+wgoICWFhYgCRJSKVS5OTkwN7eHk+ePIG7u3u1SRlFUcjKyoKjoyPS0tLg6OhYb32rlrdQFIW7d+/i3LlzmD17djU15f9+TiQSYfv27WAwGPjwww8V6gTT/X3T0tKwc+dOLFmyBAkJCQgLC8Py5csxe/ZsdO3aVR4BVsUkjz7mp0+f4o8//sCKFSuQlJSEvn37Yvny5Zg5cyZ8fX3lEfGW2PTq1SuYmpo2Wm2fVqL28fHBV199hXHjxiE2NhbffvstUlJSIJFI5A58c6GPycDAAEFBQZg7dy4WL14MV1dX7N+/H8uXL0dcXBxKSkogk8latK+2iIGBgVxBurVAO3e3bt2CSCQC8DbCV1paivz8fDVbVztMJhMjRoxATEyMXDEdAHR0dNC/f3959EoZkCSJ4cOHQ09PD4cOHYJUKq3xGYIgEB0dDRaLhX///bfF9wqbzcaYMWNw+PDhasdLkiQGDx6MCxcugM/nt2gfLYFeBLp27ZrSzrsW9aGvrw8Gg1HvGCMIAsbGxigtLVWhZVq0jrAGUFpaWqeIixbFIZPJEBMTg5CQEKVF38VicYt7ILYEiqKQk5MjX8kvLS2FVCoFl8tFSkoKOnfuXG2cicViFBYWwtbWFvfv30fXrl3VZXqrgaIopKSk4PDhw5g9e3a9CqtCoRBbt26FsbExJk6cqLDUO5lMhvz8fPz7779YtWoV9u7dCycnJ3z99deYM2cOgoKC6nTOlYVMJkNBQQH+/fdfrFixAidOnECXLl2wZMkSzJo1C127dlVoOjhFUbh58yZCQkKa9X0GgwEPDw98+eWXGDlyJI4cOYKff/4ZmZmZCnVQ6fY0PXv2xKJFi/Dxxx+Dx+Ph22+/xR9//IGXL1/K+xxr+b/+vKmpqfJ+0a0BMzMzmJmZ4dmzZwDeOprdunXDjRs3NNaxcXBwQIcOHXD16tVqNgYGBuL169d48+aN0vbNYrHw3nvvIT09HZcuXar1HLFYLEydOhXJycm4c+dOi84jQRDo2LEjHBwckJCQUG1bZmZmCAoKQlxcnFqvlYeHB968eYPy8nK12aBFOZAkCXNz8wYXxhwdHfHq1SsVWaUF0DrCGkFWVlaLBSG0NMzLly+RmZmJ3r17K81BkEgkanWEASAjI0OuhJ2XlwcLCwtQFIWCgoIaqW5CoRAEQYDNZiMjIwMuLi5qsLj1QLei2rFjBz7++GNYWVnVOZYqKyuxadMm2NjYYOzYsS12gimKgkAgwN27d7F+/XqsW7cOQqEQH3/8Mb766iv07t0bXC5XpWmYdO1zSkoKfv31V7lNc+fOxfz589G9e3cYGRkp5X6jo84+Pj4tSmlmMpno3LkzFi1ahB49euC3337Dnj17UFJSovBJMZPJhJ2dHcaPH4/ly5fD29sbO3fuxI8//oh79+5Vi1S1ZwwNDdGrVy+cPHlSY53I/0KnQ58/fx5SqVQuPnX37l15lFjToKOuly9fruZ8sVgsDBgwALGxsUrNWtDX18fHH3+MuLg4PHr0qNbPGBgYYNasWTh48CCysrJatD+SJBEdHY0rV66Ax+PJX6f7GD98+BB5eXkt2kdL0NPTg6OjI54+fao2G7QoD1dXV7x48aLO9wmCgJ2dHV6/fq1Cq7RoHWENIDMzE46Ojuo2o01TVVWFI0eOYOzYsWCxWErdjzLqP5tCUVERzMzMAACpqalwd3dHYWEhdHV1a4hw5Ofnw9TUFOXl5ZBIJNr64HqgFxN+//13TJ8+HQ4ODnWmQ9NOsIuLC0aNGtXsMUf3+83NzcX+/fuxbNkyXLx4Ef3798fq1asxZswY2NraNtgnV9HQTvnVq1excuVKHDlyBN27d8fKlSsxZswYWFpaKr0ONicnBwYGBnIV2JZALwYFBwdjxYoV0NfXxzfffIPr169DKpUq3BmjU6fDwsKwbNkyDB06FGfPnsWqVatw48YNVFVVtRoHUBkQBIFevXrh8ePHrSYqTBAE3NzcUFRUJHeyuFwuTE1NkZaWprHX09jYGEFBQTh37pzcRoIg4Ofnhzdv3iA3N1eptnO5XMyePRs7duxAdnZ2jX0RBAEbGxtMmjQJmzdvbnH6srGxMSIjI3H06NFq+9LT08OAAQMQExOj1pKF0NBQXL9+XWPHi5bmQRAEOnTogIyMjHqvrY2NDXJzc7VlMypEK5alZuhU1tDQUG1qtJKgKArXr1+HtbU1XFxclHqehUKhWh1huk+ssbExKIpCeno6oqOjkZaWJhfpeZfMzEw4ODjg9evXsLGx0bZNqgOKolBeXo7Nmzdj5MiRNXoxv/s5gUCAzZs3w9XVFcOGDWvWOaUFtlJSUnDmzBnweDyEhoZi4cKF8kUOdTwv6PNw8eJFXL16FU5OTnj//ffRoUMHldUg03bcunUL/v7+kMlkkEqlEIvF4PP54PP5cuXNqqoquYo6RVHyBQOSJMFms8Fms6GrqwsDAwNwOBwYGBiAyWRi+PDhCAkJwZ49e3D16lVMnToVlpaWCj++dyPSXl5eSE9PR0xMDGJiYjB48GAEBga2277E+vr66N27N06dOoWpU6e2inOgo6OD4OBgXL58Wd6jt2fPnrh06RI8PT018hjoSPbatWsRHh4uLxtisVjo27cv4uLilHr+aUVdWiV60aJFNbJICIKAr68vMjIy8Oeff2LWrFnNXlyka3GvX7+O58+fo1OnTtWEwhISEqoJaqkSgiDg5eWFAwcOoLy8vNHaB1paBw4ODsjNzYVYLK4zQ8zKygo8Hk8jgirtBa0jrGZEIhF4PF6r6ZnYGiktLUVCQgI+++wzpf+wCYVCtaZGl5aWgiRJcDgciEQiFBYWwt7eHpcuXUJgYGC146coCq9fv0aHDh3w5MkTbR/reqiqqsIff/yBkJAQBAUF1esEb9myBS4uLs1ygmUyGUpLS3H16lVcu3YN5ubmGDBgADw8PFTe8uhdKIpCcXEx4uPjcefOHfj5+eHLL79UiaovRVGQSqUQCoXg8/l48+YNXr9+jf3798PT0xPJycmQSCRyZWgDAwMYGBhAX19f7uy+6wBTFAWhUIiysjKIRCJUVlbKnWeBQCB3TnV0dGBtbY1Xr17h008/xbRp0xAeHi5XB1d0j1W6hnHOnDnIzMzEiRMnEBsbi2HDhsHHxwcsFksjHSllQSv9Ll++HAUFBa2iqwJBEAgJCcGGDRswePBgsNlsuLu74/Dhw6ioqFB7R4G60NPTQ9++fXHq1ClMmTJF3lfcz88P586dQ2FhoVLPP0EQCAgIQF5eHrZu3Vqrsj5BEBg8eDB+/fVXnD17FoMGDWp2GQiTycTo0aNx9OhRzJs3Ty4QSQuIHT9+HHPmzFFq9lhd6Orqwt7eHi9evIC/v7/K969Feejp6cl/f+pyhOmFz/rUpbUoFq0jrGYEAgFIktQq9SoJmUyGkydPIjw8HCYmJkrfn7ofXjweD0ZGRmAwGHKnWEdHB69fv8bw4cOrfZaiKGRnZyM8PBzXrl2r08Fr70ilUuzduxdWVlbo27dvnZMvkUiErVu3wtnZGUOHDm2SEyyVSpGVlYX4+Hg8ffoU/v7+mDt3LiwsLNQapacoCkVFRYiNjcX9+/cRGhqKr7/+GiYmJkobKxRFgc/no7i4GC9evMDLly+Rk5MDiUQCfX192NjYAHi7uv7ZZ59BX19f3tO3uSnidAq6RCKRR5ArKyvx+vVrcLlcGBoaYt++fdi+fTu8vb3h7e0NT09PWFtbw9jYWKFp4CRJokOHDvjkk0+QkZGBI0eOIDY2FmPGjIGbm1u7ytrQ19dHr169EBcXh0mTJmlcG6LaMDMzg7W1NR49egQ/Pz8YGBjA3d0d9+7dQ3h4uEY+YwmCQGBgIBISEvDmzRt5X3ldXV35+Z88ebJSbScIAgMGDEBubi4OHDiASZMm1RjrTCYT06dPx/fffw8nJ6ca4o9N2ZerqyssLS1x48YN9OzZU74Y5ebmhgsXLuD+/fsICAhQS1Q4NDQUN27cgK+vb6sY81oaB4vFgpmZGXJzc+uM9jMYDOjp6YHP5yuk7EdLw2gdYTVTVlYGDofTriY3qoKiKGRmZiIrKwujR49WyQ+aWCxWyyoyDd17EwByc3NhaWmJiooKiMVimJqaVvusVCoFn88Hi8VCcXEx7Ozs1GGyRiOTyRAXF4fi4mJ88skndbbcEolE2LZtG2xsbDB06NBGt+YSi8V4/PgxYmNjwefzERkZifHjx0NfX1/tE2Yej4fY2FjcvXsX4eHhWL58OQwNDRVuFx1Jf/36NR4+fIinT5+ivLwcHA4HnTp1QmBgIBwdHWFoaAgmkwmSJHHixAn06dMH1tbWCrGHngTTEWQAMDExga2trbyeq6qqCleuXMGff/4JXV1d5OTkID8/HyRJomPHjvD19YWTk5PCxMEYDAZcXFzwxRdf4MmTJ9i7dy/MzMwwduxY2NjYqH18qAK6LdHKlStRXFwMc3NzdZvUICRJIjIyEqdPn4afnx8IgkCPHj1w8OBB9OjRQ2OvG5vNxsCBAxETE4OZM2fK74mgoCBcuHABxcXF8rIMZcFkMjFhwgT89NNPuHjxIiIjI2ukSBsZGWHGjBnYsmULFi1aBDMzs2Y7w8OHD8fPP/8MX19f+UI5g8HAsGHDsGPHDnTp0kXlQQqCIODp6YmDBw9CIBBo22q2IQiCgKOjIzIyMuDm5lbrZ0iShK2tLV6/fq2dk6kIrSOsZjIzM2Fvb6+xP46tGalUikOHDmHEiBEq+zFTtyNMK0ZTFIW0tDS4uLggJycH5ubmNewSi8WQSCQQiUTQ09PTZiX8B4qikJiYiJs3b2LhwoV1nh+xWIydO3fC2NgYo0ePbtAJpvvs3r59G2fOnIGhoSEGDx4MT09PpQtMNQQt9HXmzBlcvXoVoaGhWL58uUJbMdHR18LCQjx69Ah3795FUVERTE1N0aVLF4wbNw52dnbVorvv7lsmk+Hu3bv48MMPVXKu6H3o6OggMjISnp6e+P3332FnZ4fp06eDz+fj6dOnSEhIwOvXr2FsbIyAgAD4+PjIU8dbomrNYDDQuXNnLFu2DNevX8dPP/2EoKAgDB48WCMWTJSNoaEhIiIiEBsbi0mTJrWK43Vzc8PevXuRl5cHa2trODo6QiAQoKCgAFZWVuo2r1YIgoC3tzfOnj2LjIwMODs7gyAI6OnpISwsDPHx8Rg7dqzSz7+uri5mzZqFNWvWwM7ODh4eHjWcYRcXFwwePBi///47FixY0CxFfoIgwOVy0aNHD5w6dQrjx4+XR1/t7OzQsWNHJCQkoF+/fiofc/r6+rCzs8Pz589bpIqvRbMgCALOzs64d+8eKIqq9brS4nA5OTl1fkaLYtHmXKgRiqLw5s0b2Nraage7gqHFdIyNjeHm5qZSER91OsL0xAuAfDLzriDIuxQWFsLIyAg5OTlwcnLSjsF3oIXGDh8+jE8++aTOVXmJRIJ9+/aBwWBg/Pjx9TrBFEWhrKwMJ0+exLJly/Dw4UN88MEHWLhwIbp06aJy5ef/2iYSiXDx4kWsWLECfD4fS5cuxahRoxQS4aTFv7Kzs3H06FGsWLECv/76K968eYMhQ4Zg2bJl+PLLLzFo0CA4OzuDzWbL6xT/u+/8/HxIpVK1OBR0e4vFixdDKpVi/fr1AIAePXrgk08+wcqVKzF69GgUFxfjt99+w6pVq3D69Gm5zc1VgiUIAiwWCxEREVi2bBnEYjFWrFiBO3futPkexLSC9P3798Hj8VqFmi6LxUK3bt1w7do1UBQFNpuNgIAA3LhxQ92m1QubzcbgwYNx/PjxagrSoaGhePjwIcrKypRuA0EQMDU1xaxZs7B9+3YUFBTUqiRNC3sdPXq02Qq7BEEgIiIC6enpyMrKqnbMUVFRSEhIaLFKdXMgSRIhISG4fv26yvetRbnQ4qT1jVkbGxul9vDWUh2tI6xGaEdYm/6geMrLyxEfH4+RI0eqtMZGKpWqraZHJpOhqKgIFhYWEIvFyM3NhZ2dHV68eIFOnTrV+HxeXh7Mzc3l/YO1jvBbKIoCj8fD9u3bMWXKlDrVgqVSKU6cOIGysjJMnjy5zgUQus724MGDWLVqFcrKyvDFF19g1qxZ6NChg9prwCQSCe7fv4+VK1fiyZMnmDdvHiZPngwul9uiMUHX3L5+/RpHjx7FqlWr8Oeff0JHRwczZ87EsmXLMGnSJHh4eDQpsnnv3j14e3u3uC9zS9DT08PkyZPRu3dvrFu3Do8fPwbwNmrcqVMnjBs3DkuXLsW0adMgEAiwceNG/Pjjj7h69SpKS0tb5BAbGRlh4sSJ+OSTTxAfH4+NGzcqvcWNuuFwOOjRowdOnz6tblMaTWhoKJKSkuQ9hENCQpCYmAixWKxmy+rH09MTMpkMz549k79maGgIPz8/XL16VWXjrGPHjhg+fDi2bNmCysrKGu8zGAxMnDgRjx49kkfYmoOuri6GDRuGQ4cOVXNOuFwuAgMDq7WVUiUeHh5IT0/X2B7UWpqHoaEhhEJhvQuYtra2yMvLg1QqVaFl7RetI6xGpFIpioqKNDZVqrUik8kQGxuLbt26Kb2m6b+oM5VFIBCgsrISXC4XVVVVkMlkYDAYyM/Pr7HYQvfENTc3R3Z2traP9TtUVVVh69at6Nu3b51tkmQyGeLj45GWlob333+/1rRpiqKQl5eH3bt34/vvvweLxcLXX3+NCRMmwMrKSu0OMEVRyMrKws8//4yYmBhMmzYNM2fObHGGCq0wffHiRXz33XfYsmULWCwWZs+eja+++grR0dGwtbVtVuaETCbD7du30a1bt2bbpygYDAbCwsIwc+ZM7NmzB+fPn682cWGxWHB0dMSoUaOwdOlSjB49GqmpqVi9ejW2b9+Oly9fNjuaS9eazZ8/HwEBAVi3bh3OnDmDqqoqRR2eRkFHhe/du4eSkhJ1m9MozMzMwOVykZaWBuBtWxR9fX1kZGSo17AGYDAYGDx4ME6dOlVtfPbp0we3bt2q1SlVBnQk2s3NDf/880+t94q+vj4+/PBD7Nu3r0X9pr28vMBms5GcnFxt//369UNSUhKKi4ubve3mYmRkBGtrazx9+rRNL3K1N/T09GBgYIDCwsI6P6Ovrw+RSKTtJawitI6wGpFIJJBIJNraTAVCR9mfP3+O3r17q8UpVZcjXFlZCTabDRaLhTdv3sDMzAwVFRVgMpm1KhRmZ2fDwsJC277rHaRSKfbt2wd7e3u5kuh/oSgK165dw40bNzBr1izo6+tXe492gHfs2IG1a9fC3Nwcy5cvx4gRI1ocZVUEdC/gPXv2YOPGjejevTu++uordOzYsdmifXSLo2fPnmHz5s349ttv8erVK0ycOBHLly/HkCFDYG1t3eIWQEVFRaioqICTk1Ozt6FI6JqvRYsW4fbt29izZw+qqqqqTVwJgpBHimfMmIEVK1agU6dO2LlzJ9asWYPr169DJBI1ebJLi3tFRERg8eLFePbsGX744QdkZ2e3yYmzsbExQkJCEBcX1yqOj3beExIS5BPa8PBwXLlyRePtd3NzA0VReP78udxWExMTuLq64u7duyqzn8FgYOTIkSgpKcHZs2drTZF2cHDA0KFDsWPHjmbdR+/uJyYmBgKBQP66gYEBIiIi1DLmSJJEaGgorl27ptL9alEutBhWVlZWnZ+hfQJtNoBq0DrCaqS8vBw6OjpqTfFra0ilUhw5cgTDhw9XywKDovuLNoWKigp5imlGRgacnJyQm5srbzfzXwoKCuStltRZ16wpUBQlbx8yduzYWp1CiqJw//59xMTE4LPPPqumokxH2Xfs2IF169bBzs4Oq1atQlRUlFLUlpsKnap848YNrFixAjo6OlixYgVCQ0Ob7aBSFIWKigpcvHgRy5cvx/79++Hr64tvvvkGU6dOhbOzs0L73z569AgeHh6NVuVWBQRBwNjYGF988QUkEgk2bdqEioqKWifOBEHAwMAAPXv2xPLlyzFhwgTcuXMHS5cuxenTp1FeXt4sh5jL5eKTTz7BgAEDsGHDBsTGxkIsFmu8w9UUCIJA//79cefOnVYRFSYIAp07d0ZWVhbKysrkfXmfP3+OiooKdZtXLwRBYMiQITh16lS1LIf+/fvj0qVLKs08YLPZ+PDDD5GQkIDHjx/X6gyHhYXBzMwMMTExzR7zdnZ2cHV1rbZQQdciP336FHl5eS0+lqbi6emJly9fah2iNgS9eJqenl7nWGWxWOByuWoZc+0RrSOsRl6/fg0rKytt6yQFQVEUHj58CAaDAU9PT7U5Hurab25urjyym5aWho4dOyI1NRUeHh61fp7P56O0tBSWlpYa5VioA4qi8OzZM5w9exYzZ86sdXGKoii8fPkS+/btw2effSaP7tIO8M6dO7F27VrY29tj+fLlGDhwoMao+lIUhdevX2P9+vW4cuUK5s2bhzFjxsDAwKBZ9slkMuTn5+PAgQNYvnw50tLSMGPGDHz99dcICwuDnp6ewheFZDIZbt26he7du2vEOX0XOuo7ZcoUuLi44KeffkJxcXGdEx1aDbpTp0747LPPMG/ePBQXF2PlypU4cuQISkpKmjShJwgCJEkiKCgIS5YsQVpaGtavX4+8vLw25QwbGRmhW7duOH/+fKs4Ll1dXXTu3FkeRaX7YL948ULdptUL3WeXJEl5VJggCFhYWIDL5ao0XZcgCJiYmOCjjz7Cn3/+WWtKKYPBwIQJE3D//n08evSoWbbRzv+VK1dQWloqf11XVxf9+/fHyZMnVZ6qamxsDAsLCzx//lyl+9WiXDp06FBviQRJkrC2tkZubq7qjGrHaB1hNUGn8LaXfpCqoKqqCidPnsSwYcPUtrhAK92qA1qBnKIouVNclxBWVVUVxGIxiouLYW9vr/Z6VXVC17Tu3LkT06ZNqzV9+d1052nTpsHe3h4AUFxcjH379uHHH3+EpaUlli9fjgEDBmhEBJhGIBDg2LFj+OWXX9CjRw98/vnnsLOza5Z9UqkUmZmZ2Lp1K9atWwc9PT0sXrwYM2bMQIcOHZR635WWlqKoqAguLi5K20dLYTKZGDp0KCIiIrBhwwbk5+c3+B26XcakSZPw1VdfQSaTYfXq1Th06FCTVZLp6PCsWbMQFhaGtWvX4tq1a21GdIUgCAwYMAC3bt1SiYJxS6EjivQ1oKOX165d0/j6P5IkERUVhdjYWPn4YTAY6N+/P86dO6dy+52dnTFs2DBs3bq1WvoyjaGhIaZPn47du3c3O2PA2NgYoaGhiI2NlR8fQRAIDAxETk4OXr9+rdIFGLpO+saNG61i4UdL4+ByuSgpKWmUcrT2uiuf9jv71QC0IkWKg05r7dixo9xJUQfqSo2mKAr5+fmwtLSERCKBQCAAg8FAaWlpranRZWVlYLPZKC4ubveq5WKxGNu3b0f//v1rbTNFURT4fD42b96MESNGwM3NDXw+H0ePHsW3334LXV1dLF26VGNSoGlo5dfVq1ejpKQES5YsaXYatFQqxfPnz/HLL79gy5Yt8PT0xIoVKzB06FCYmpqq5JifPXsmb62kyZAkiZ49e2Lo0KH46aefqrVlqQ+CIGBmZoYxY8Zg6dKlAIA1a9YgJiYGfD6/SRMiJpOJHj16YMGCBUhISMC2bdtahePYGExMTODj44OEhIRWMUmkxefevHkDgiDg6emJ7OzsVpEe3bFjR0ilUmRkZMjPtYuLC0Qikcpr0QmCQI8ePWBvb49Dhw7VurjToUMH9OvXD3/99Vez1Lnpuu5nz55Vi8bp6OggKiqqWlspVeHt7Y0XL15AKBSqdL9alIexsTEYDAZ4PF6dn3FwcEBmZqYKrWq/aB1hNfFu1E5LyykrK8OVK1cQFRWlVkeEoii1RFdlMhkKCwthZWWFgoICGBgYQCaTQUdHp9a055KSEhgaGiInJwcODg4qt1dToCgKJ06cgKmpKcLDw2sdO2KxGFu3bkVISAi8vb0RHx+PFStWQCAQYMmSJRgxYoRCeu0qCoqiUFlZiX379mHHjh2YMGECpk6dCmNj4ybZSFEUZDIZXrx4gXXr1mHXrl0ICwvDypUr0bNnT5WmfdNq0cHBwSrZX0shCAJBQUGYOHEiNm7cWG89WG3fNTY2xpgxY7B48WKUlJRg+fLl8trMpmzH0tISX375JSwtLfHtt9/i5cuXrcJ5rA+CIDBw4EBcvnxZ451J4O2iRGhoKC5fvgyKoqCnpwdnZ2ekpKRo/LVgMpkYMGAATp48KbeVyWQiMjIScXFxKreHJEmMGzcOGRkZtUZJCYJAZGQkZDIZLl682Kzzq6uri6ioKBw7dqxaVLhr164oLy9X+T1kYmICY2NjrVPUhiBJEubm5vXWAJuYmKCsrEzjnxFtAa0jrCYoioJAIICBgYG6TWn1UBSFkydPIiIiAsbGxuo2Ry0OkVgsBp/Ph6mpKXJycmBlZYXs7GzY29vXmq5aWloKDoeDyspKGBoaqtxeTYCiKCQlJeHBgweYOHFirQsGEokE+/btg7GxMbhcLlatWoXnz59jwYIFmDhxIkxMTDTGAQbeOoypqalYtWoVKIrCsmXL4OXl1eTFGZlMhlevXuGnn37Czp070bt3byxfvhzdunUDm81W+TELBAJkZmbC3d1do853fRAEgS5dumDGjBnYsmVLNQXexn6fy+Xivffew/z58/HgwQOsWrUKjx49glQqbXSUmcViYcSIEZg8eTI2b96M+Pj4Vp8qbWpqCm9vb7lzqckQBAFfX188evRIHqXs0aMHrl271ips9/T0RGVlpdwRo53C7OzseiNayrJHR0cHH330EY4dO4bMzMwa55DJZGL69Ok4e/Zsre83Zh++vr7g8/nV7lm67OFdB1lVhISE4ObNmxo/XrQ0DoIgGqwTNjAwgFAobPXP6taA1hFWE3w+HyRJVmu9oqV5vH79Gi9fvkRERITaJ8nqSo2uqqoCQRBgMpnIzMyEo6Mj0tPT4ezsXKs9tGK0TCaDrq6uyu3VBPLy8rBv3z589NFHtd6HMpkM586dw40bN5CVlYXLly9jxowZmDlzJqysrNQ+1t6FjgIfOnQIu3fvxpQpUzBhwoQmi2HJZDLk5ORgy5Yt+OOPPxAWFoalS5eiW7duClV/bioZGRmwtrZudc9LgiDg5uaGmTNnYseOHU2OJtHPExsbG3z66aeYOHEijh49ik2bNjVaCIvehpeXF7766ivcv38ff/zxR7MUqjUFkiQxcOBAXLx4sdZ6UU3D1NQUlpaWSE1NlU+CCwoKUF5erm7TGoTFYqF///44ffq0fLzo6ekhMDBQLa2g6EyHyZMn4/fff681K8DExAQTJ07En3/+2ayUYnrx6MiRI3JHhF4UkMlkePr0aYuPo7HQjnlqaqpWPboNQStH14W+vj7YbLbKF5vaI1pHWE3k5eWBy+Vq29a0EIlEguPHj2PIkCEaUTuoLrGsyspK6OjogCRJpKenw8nJSS6UVRtv3rwBk8mEiYmJRpw3VSMQCLB9+3aMGjWq1hppiqJw584drF69Gvr6+hg5ciS++OILdOzYUeOExSiKQkZGBr7//nsIBAJ8/fXX8PT0bJKdtGDY3r178dNPP8HDwwPLli1DSEiI2vucUxSF27dvIzAwUKMWHxoLQRBwcXHBjBkzsHXr1ialSb8LSZLw8PDAokWL0LVrV6xbtw4xMTGorKxstB1mZmb47LPPYGVlhR9//LFV9xy2tLSEu7t7q+jLSxAEIiIi5HXNenp68PDwwL179zTedgDo2rUr8vPzkZOTI38tPDwciYmJaqldpaPSgYGB2L17NyQSSY33fXx80KlTJxw5cqRZEVxXV1cYGRkhKSlJ/hqDwcDQoUNx8uTJGvtUJiYmJtDT06t2/rW0bqysrJCfn1/n2GQwGOByuSgqKlKxZe0PzZrRtRNoBVpNiyq1NiiKQmpqKsRiMby9vTXiXKprUpObmwsrKyuQJIni4mIYGRmBx+PB3Ny81s+XlpZCJBLBwsJC4xw7ZSOTyXD8+HHY29ujW7duNcZNRUUF/vnnH3z77bdYsmQJvvvuO/j4+GhkiymxWIzTp09j8+bNGDlyJN57770ml1sIhULExsbKnf7ly5ejT58+0NXV1Yh7SiwWIzU1VWPu8eZAt6Oh06RfvXrV7BYvOjo66NWrF5YuXYqCggKsWbMGKSkpjZ7ss9lsDB8+HCNHjsQvv/yCO3futApn7L+QJIno6GjEx8e3CiEhLy8vZGdny3sKh4aG4vr16+o2q1Gw2Wz07t0b586dk48VLpcLBwcHPHjwQC02kSSJIUOGoKysrFbhNJIkMXLkSDx9+rRZ9dgkSWL48OE4depUtfFFl2c8e/ZMIcfRWFuCgoJw69atVnmvaqmJubk5BAJBvToH5ubmKCgoUKFV7ZP2NQPWIF69eqVVjG4hYrEYMTExGDFihMb0YlZnD2ErKytUVFRALBbLo8O1pT3TKsgCgQAWFhZqsFZ9UBSF+/fvIzU1FWPHjpUvAlAUBYlEghs3bmD+/PnYsmULli1bhoEDB0JHR0fjHDCKosDj8bBhwwa8ePECX3/9NXx8fBqdkUBRFKRSKe7du4cVK1YgMzMTX3/9NUaMGKFRytd0/2NDQ0ONqP9vCQRBoFOnTpg+fTq2bNnSolYsBEHAyMgI06ZNw+TJk/HPP//gr7/+arS6NEmS8PX1xeeff46YmBicOHFCpREuRWFtbQ1nZ2dcv35d4x0EPT09uLm5yR1HJycn8Pn8WvviaiLBwcF4/vw5iouL5a/169cPFy5cUNvYYbPZ+PDDD3H69OlqytY0enp6mDp1Knbt2gU+n9/k7dvZ2cHJyalafS5BEPKocHOUqZsDQRDw9/fHgwcPWuV9qqUmLBYLBgYG1XpW/xdHR0dkZWWp0Kr2idYRVhM5OTm1trXR0jgoisKNGzdgZ2cHR0dHjZq4q2OfdOukoqIiGBkZyRXJa0u9l8lkqKioAI/Ha1eK0RRFoaioCHv37sX06dPlqse0MNSPP/6I+Ph46OrqYvHixfD399eYcfUuMpkMDx8+xOrVq+Hn54fZs2c3SbSL7mG+YcMG/Pvvv5g+fTo++ugjmJmZaeTxJiYmws/PTyMj8k2FIAi4u7tj4sSJ2LJlC4qKilrkDJMkCXd3dyxZsgQcDgcrV67EgwcPGiWwQhAEbG1tsWjRIqSnp2Pbtm2orKzUeIfyXQiCwLBhw3D27NlWERWOiIiQ9xRms9nw9vaulnqryejo6CA0NFQefSUIAo6OjqAoSq2TdS6XiylTpmDHjh2oqKioNn7psoTu3btj3759TRYeop3e8+fPy0sQ6OwOkiSbLIDXEkxNTcFisepVGtbSurCysqr3elpZWVVr46VFOWgdYTVRWlra6iMc6qSiogIXLlxAdHR0u0vt/S90qr21tbXcAc7IyICTk1Otjg2tRCgSiWBmZqYGi9WDRCLBjh07EBUVBQcHB1AUhbKyMuzduxe///47IiMj0alTJ7i5uWHAgAEa5xRSFAWhUIjDhw/j4MGDmD17Nvr27dtoB5GiKFRUVODo0aP4+eefERISgkWLFtXaO1lToCP4vr6+6jZFYdBq0lFRUdi6dWuLBZMIgoCenh7GjBmDWbNm4ejRo9i1a1ejxbAMDQ0xe/ZsmJmZYd26dSgsLGxVzrCtrS3s7OyQmJio0XbTIlnvRoFDQkJw584dlasQNwe6j++9e/fk6Zx0z+xLly6p7RgIgoC3tzd8fX3xzz//1LCDIAhER0cjNzcXSUlJTR4jZmZm8Pb2rpZ+Tadlnzx5UmWqvkwmE35+fq22lEFLTTp27Ii0tLQ63zcxMUFJSYn2eiuZ9u1BqAmhUAiRSKR1hJsJRVGIj4+Hn59fu3Lk6kImk6G0tBRcLhdpaWlwcXFBWloaOnXqVOvnBQIBGAwGqqqq2k37LoqiEBcXBwMDA4SHh8vToL/55hvo6OhgyZIlAICnT59iypQpGpNq/y5FRUX46aefUFZWhkWLFtWpCF4bUqkU9+/fx+rVq8Hn87F06VKEhYVpvFAarYxsZWWlblMUCkEQ6N69OwICAvD7778rJJpJEAScnZ3x1VdfwcjICN9++y1SU1MbNYlis9kYNWoU+vTpg3Xr1qk00qUIhg4diri4OI1X1WUymfD398ft27dBURQcHR0hEAhaTR0gh8OBh4eH3H5a0TgtLa1ZqceKgiRJDB48GDweD1evXq0xdtlsNqZNm4ZDhw41WYWXIAj0798fN27cQFlZmfy1jh07gslk4unTpyq5VwiCQEBAAJKSklrFwomW+iEIAvb29vWWyJiYmMj9BS3KQ+sIqwEejwddXd1227ampfB4PNy9exd9+/bVuEiWOlSjpVIpJBIJ2Gw2cnJyYG1tjcLCwjqFsiorK8FgMCCTydqFI0xRFNLS0nDlyhW89957yMvLw/r163H58mXMnTsXo0ePBo/Hw+HDh/Hhhx9CT09Po8YVRVF4/PgxvvvuO4SGhuL9999vdB0vrQa9efNmHDt2DNOnT8fkyZPB4XA06hjrIjk5GZ07d24TadH/hSRJ9O/fHx06dMDOnTsVUm9IEAR0dXUxcuRIvP/++9i1axcOHz4MkUjU4GSdwWAgLCwM06ZNwx9//IEbN260CmeYIAg4ODjAzMwMDx480Gib6QWQxMREiMViMBgMeHt74/79+xptNw1BEIiMjMSVK1fk41VfXx9dunSRO8fqQldXF9OnT8eJEyfw5s2bGinSdnZ2iIyMxD///NPkKK6JiQmCg4Nx9uxZ+XYZDAaio6MRExOjMsfUysoKMpkM+fn5KtmfFuViZ2eHgoICVFVV1fq+np4eWCyWfAFGi3LQOsJqgMfjgcvltoqJqKZBURROnz6NXr16aaQTR1GUyicD9ISEIAgUFxeDw+FAIpGAw+HU+nl6hVFHR6ddLMZUVFTgr7/+wvjx43HhwgX89NNPiIiIwJdffglbW1tUVlZi69atmDhxIqytrTXmvqQFvE6dOoXdu3dj9uzZ6NmzZ6Oi1fR3r1+/jm+++Qaurq74+uuv5e2fNOUY60Mmk+HOnTsICgpqFfY2B1rZlsFg4Pjx4wpLsyRJEp06dcLSpUtRXFyMH374oVF9h+m+xwsXLsSpU6cQGxurstTPlkCSpFra2jQHc3NzMBgMeW1gSEgIEhMTW02Uz9LSEmZmZnjy5Ik8KhweHo6rV6+qfayYm5tj3Lhx2LZtW40oGkEQ6N27N8rLy3H37t0m9/Pu1asX7t+/LxcLo2uFWSwWnjx5otDjqAsWi4UuXbo0K8Vbi+ahr68PmUxWby90Y2PjegW1tLQcrSOsBnJzc7VCWc0kJycHaWlp6NGjh0ZOjtXx40QLZInFYkilUggEAnC53Dr7v5aVlYGiKBgbG2vkOVQkUqkUBw8ehK6uLg4fPoyCggIsXboUoaGh8qj4nj174Ofnh65du2rM+aDreX///Xe8ePECixcvbnQqNEVRKCgowMaNG3HlyhV8+eWXGDhwINhstsYcX2MoLi4Gn89Hhw4d1G2KUmEymZg0aRJevnxZTZ22pRAEAQMDA8yYMQN9+/bFunXrcOfOnQadFYIgYG5ujoULF+LBgwc4cOAAqqqqNHriTdff6uvr4/HjxxptK5PJRFBQEG7cuAEAsLe3R0VFRTU1Zk2GJEn069cPZ86ckZ9nKysrGBoa4sWLF2o99wRBIDAwEA4ODjhx4kSNxQU2m4333nsPhw4danKUzcDAAL1798a///5bLSo8dOhQ/PvvvypZgCEIAt26dcOdO3eUvi8tyofBYIDD4dQ7Fi0sLFpN6URrResIqwFt66TmIZVK8e+//2LQoEEaX9uoSgoLC2FqaoqKigro6+vLF1rqcnoKCwvBYrHafI06RVG4d+8e/vrrL5SWlmLixImYPn06TExM5O9fvHgRZWVlGDJkiMaIrlEUhdzcXKxduxa2trb4+OOPG71oIZFIkJCQgB9//FHeHqe+saDJpKamwtXVtU2mRf8XXV1dzJgxA3FxcQqvz2UwGOjevTvmzZuH2NhY7N27t94IBPB2ws3hcDBnzhyUlZVh27ZtEAgEGu9gDhkyRKWpqs2BrvW8f/8+JBIJmEwmvL29kZycrNHn9106duwIsViMzMxMAG/HWK9evXDx4kU1W/bWUR83bhwePnxY66KInZ0devbsiX379jVpnBAEgbCwMKSlpVVT8nV1dQWDwVBZX2EHBwcIhUKtc9QGIAgCTk5OSE9Pr/Mzjo6O8vtMi3LQjJlfO4KO1rS3/q2K4NWrV+DxePD19W2VE3tlQFEUCgsLYWZmJm+h9PLlS7i4uNT5nZKSEohEojYnQPQuMpkMiYmJWL16NT766COsWrUKnp6e1ZzdtLQ0nD17FjNmzNCYhRWKovDo0SOsW7cOUVFRGD58eKNso1tD/frrr7hz5w4WLFiA3r17t7ooMA1FUbh9+zZCQkLUbYpKIAgCpqameP/997Fz506FT3LpVkkLFiwAAKxduxa5ubn1Ol60GvW0adNgZmaGDRs2aHytmpubGwiCQGpqqrpNqRczMzMYGBggMzMTBEEgODi4UdF6TYHJZKJ3796Ij4+XjyEvLy9kZ2drRBqnvr4+pk2bhj179tSwhxa/ysvLQ3JycpO2q6uri379+uHUqVNyJ5ogCAwePBinT59WSVSYxWLBy8sL9+/fV/q+tCgXugVZZmZmrc9igiBgaWmpXfRQMlpHWMVIpVKUlJTUKWSkpXakUimOHz+OIUOG1NobV1OgKErl0Qi6dRKdaZCTkwNbW9s6P19eXg4+n98m0/MpikJJSQm2bNmC2bNnY+rUqZg4caK8ZzD9mbKyMuzYsQPTpk2TR4jVCUVRkEqlOHfuHPbs2YPPPvsM3bp1azBKTY+3xMRErFmzBp07d8a8efNgaWnZKh1gmvLycuTk5Gh0aydFQ6s+jxgxAr///ru8b6kit6+np4eJEyeib9++WLt2LR4+fNigrgGbzcaYMWMQGBjY6FpjdcFisTBkyBCF1lsrA5IkERISgmvXroGiKNjZ2aGyslLjFxrexc/PD+np6SgpKQHwVtina9euahfNAv7vXurZsyd2795dYyywWCy8//772L9/f5PPeXBwMDIzM5GTkyPfl7u7O0QiETIyMlRy7MHBwbh9+7ZGZz5oaRyOjo7Izs6u81paWFigqKhIe62ViNYRVjEVFRWQSqVtPi1VkVAUhSdPnoAkSbi7u7ebiXFjoXsH5+TkwMrKCiUlJTA1Na3z83R/USMjIxVaqVxoRzIpKQmrV69GZmYmBg8ejOjo6BrjRSqVYs+ePejevbtGjCeKoiAWi7F3714kJSXhq6++gqOjY4N2URSFyspK/Pnnnzh58iTmzZuHfv36tYlU4levXsHa2rrOOve2Cl3j6OPjg/379yslwkSSJLp3747PPvsM+/btw6lTpxp0GhkMBvr374/Bgwdj/fr19bb8UDfe3t4QCoX19udUNwRBwMfHBykpKRCLxWCz2fDy8sK9e/c09rz+F11dXfj7++P69ety0ayIiAhcv35dIwTLCIJA3759UVlZWUMBnVYa7969O44ePdokJ4PNZmPAgAE4ffq0/HskSSIqKqraa8rExcUFJSUlTW4FpUXzMDU1RVlZWZ33jKmpKSorKxXSYk9L7WgdYRVD13Gqe/LdmpBIJIiJicHQoUM1fpJPEIRKry1FUeDz+dDV1UV+fj709fVBkmSdTi4twgQAhoaGKrNTmdAR3u3bt+PUqVMYP348JBIJPvzwwxrZAxRF4cqVK6isrMTAgQM14j6sqKjA5s2bIRQKMWfOHJiYmDTKCc7IyMCaNWtgZGSERYsWwcHBQSOOp6XQadFtWS26PgiCQFRUFMrLy2vtiaqofTg5OWHRokV4/vw5duzY0WAEmm79M27cOGzcuBHp6eka6bQxmUwMHToUJ06c0OiosKmpKUxNTfHixQu5CJImRFMbC62kfOvWLfkk3crKCnp6evXWPKoSNpuNqVOn4tixYzXSSwmCwMCBA/Hy5csm1eXTi1Vv3rzBmzdv5K917twZpaWlKlkkYjKZ6NSpk8aXAGhpGHqxt64WSkwmE0wms0FdBy3NR+sIq5ji4mJt66QmkpiYCHNz81ahHqvq9kkURUEoFILBYEAoFEIikYDL5dbZYkcikaCyshIkSbYJR1gqlSI5ORmrV6+GtbU1Pv/8cyQkJCA6OrpGDTRFUcjMzERsbCymTp2q9rpgiqKQl5eHtWvXwtnZGe+//z709PQa/J5YLMbZs2exefNmjB8/HqNHj27U91oLVVVVeP78Oby9vdvtc5LJZGLKlCm4ePEiXr58qbRnirGxMWbPng0jIyP89NNPKCgoaLBu2M/PD1OmTMHmzZuRmpqqkY6br68vSkpK8OrVK3WbUie0+BK92GFnZ4eysrJWlR7N5XJhbW0tbx9ER4UvX76sMePCysoKQ4YMqbVXt66uLsaNG4e9e/fW6YjUBpvNRv/+/avVCrNYLPTv3x+nT59WybGHhITg1q1b2pTZVg6LxYKpqam8ndp/IQgC+vr6Ci+V0fJ/aB1hFZOZmalVjG4CQqEQZ86c0ShV3/pQtSNcUVEBkiTBYDDAZDKRm5sLe3v7Oj8vkUhQWloKXV1djezD3FjoSPju3btx7NgxzJ49G0OGDEFSUhJkMhnCw8NrOFFCoRDbtm3DhAkTYGZmpibL30JRFF69eoX169djwIABGDJkSIPZDhRFobS0FFu2bMGjR4/w1Vdfwdvbu1XcF00hNzcXBgYGbSp1v6kQBAFjY2NMmjQJu3fvBp/PV9q+2Gw2/ve//yE8PBxr165t0PEmCAJeXl6YNWsWtm3bhgcPHmiM00PDZDIRFRWFkydPanRUuEuXLkhLS4NAIICuri5cXV3x6NEjjTufdUEQBCIjI3Hx4kVIpVJ5ynd6ejrKy8vVbR4AyPscs1gsXLp0qUaKtLu7OxwcHHDu3LkmRYX9/PyQl5dXLSrs4+ODnJwc5OfnK+VY3t1/p06dkJOTo9RngxblQwsZZmdn1/m+paVlnY6ylpbTtmZQGg7dFsXa2rrdRjqaAkVRuHnzJjp06ABra2t1m6OR8Hg8GBgYgMfjwczMDK9evapXMVoikcgnXZqeZl4XFEXhxYsXWL16NXR1dbF48WI4OTmhuLgYJ06cwOTJk2scm0wmw8GDB+Hp6an2fsEURSElJQWbNm3C1KlT0b1790aJYr18+RJr1qyBi4sL5syZ0yYzSyiKwt27d+Hj41NnVkN7gSAIuLq6Ijw8HLt27VKqQ0eSJCIiIjBt2jRs2bKlwX7GBEHAxcUFn3/+OXbv3q1xKb3vpq/m5ORolG3vwuFwYGFhgZcvX8rVo2/evKlusxoNLUpVUVEhd/709PTQqVMnuRCbJkCSJKZMmYIzZ87gzZs31exiMBgYNWoULl261CQHVkdHBwMGDEBMTIx8ezo6OujTp49KosI6OjpwcHBQeLs1LaqlIeVoALCxsZEvuGhRPFpHWIVQFIX8/HytU9dIKisrcfHiRQwePLjVTPgJglDpj1JJSQlMTEyQnZ0NW1vbBseXRCJBVVVVq4wGUxQFkUiEY8eOYdu2bXjvvffwv//9D7q6upDJZNi9ezeioqJqKCZTFIXk5GSkpaVh1KhRao2gymQy3LhxA7t27cKnn34KT0/PBse2RCLBpUuXsGXLFrz//vuIjo4Gk8lsNfdEU5DJZEhOToa/v3+bPL6mQtdhMhiMGtEsZezL3d0d8+fPR2xsLE6cOFGv6BFBELCzs8OCBQtw9OhR3LhxQ6PSNGlRo5MnT2q0oxAaGioXc3JxcUFBQUGrivKxWCyEhYXJxydBEOjZsyeuXr2qMdF4giDA5XIxZswY7Nq1q0aKNJfLxbBhw7Bnz55GC30RBAFfX18UFBQgKytL/lpQUBDS0tJQVFSk8ON4F5IkERwcjFu3bmn0+NbSMI6OjsjKymqwhZL2OisHrSOsQsRiMUpLS7U9hBsBRVG4fv063N3d1Z7G2hRkMplKH1Y8Hg9cLhe5ubkwMTFBaWkpLC0t6/y8RCKBWCxudTWldDbFunXrUFhYiCVLlsDLywskScozB0QiESIiImo4UMXFxdi/fz8++OADtaoQS6VSnDlzBnFxcZg/f36DytC0sNnOnTtx8+ZNfPXVV41ynFszPB4PEolE+4x8ByaTiYkTJ+Ly5cv1Rg0UAUEQsLa2xoIFC5CWloa///67XrVSepL2xRdf4N9//8X169c1xhmmBajS09ORn5+vkZNIgiDQpUsXvHz5EpWVldDT04ODgwOePn2qbtMaDUEQCAgIwOPHj+WCPnZ2dhCJRBrV/5S209jYGBcvXqwxHrp37w6xWIy7d+82eqzo6Ohg0KBBiImJkY97fX19hIeH4+zZs0ofcx4eHkhPT29SfbMWzYPD4YDP59c5XqysrLSOsBLROsIqhH5YqVukpzVQUVGBq1evaoyyb1NQ5cMqJydH3jrJxMQETCYTurq6dX5eIpFAJBKBy+WqzMaWIpVKcf36dfz000/o06cPpk+fXq1+tLi4GEePHsWUKVNqqESLxWLs3r0b/fv3h729vdrGkkQiwbFjx3D//n3Mnz+/wT6/7wppGRoa4vPPP6+3JVZbgKIo3L9/H+7u7tpn5H/gcDgYP3489uzZoxLRFAMDA3zyySegKAq///57vZM0giBgYWGBefPm4dSpU7h69arGOMP6+vro3bs3Tp06pW5T6sTAwAAWFhbIyMiQK3M3lJquaRgbG8PZ2Vne/onFYqFbt27yPsmaApPJxLhx4xAfH1+j5pLBYGDixIk4fvx4kyLyfn5+KCwsrFbj2aNHDzx8+BClpaUKs702OBwOLC0tNbpVmJaGoTP06I4e/8XMzAylpaU1Mhm0KAatI6xChEIhWCxWmxO3UTQUReHy5cvo0qVLq3LYANWnRhcUFMDU1BSlpaVgMpngcDj1OlhCoRACgaBVRNzoiOj27dtx4cIFfPHFFwgJCalWOyqVSrF//3707dsXNjY2Nb5PT8p79uypNidYLBZj//79yMrKwmeffQYOh1Pv5+m+2WvXrsWAAQMwZswY6OjotLoFoebQntsm1QdBEHBzc4OXl1e16JMy98dms/Hee+/B0dER69evR0lJSYPO8Pz583H69GlcvnxZI5xhWpn5yZMnSk9VbS4EQSAkJESeHu3h4YGsrKw6J8WaCJ3Cn5CQIE+PDggIQHJyskb0FH4XU1NTDB8+HLt27apmG0EQsLe3R5cuXRAXF9fo33Emk4n+/fsjLi5OPuYNDAzg5+en9IUAkiQRFBSkTY9u5bDZbHC5XOTk5NT6Pr3Ar3WElYPWI1MheXl5sLCwaPciMPVBOz83btxAZGRkq5sQq9re8vJy6OvrQywWIy8vDw4ODvV+vrS0FFKptFG9atUJ3Sd39erVMDMzw8KFC2FlZVWj9vfBgwcoLCysdazk5ubi5MmTeO+999QmDFZVVYWdO3eirKwMs2bNgp6eXr3nXSqV4sKFC/jrr78we/bsGo5/W4bP56O4uBhOTk7qNkUjIUkSUVFRyMrKUokQEUEQYDKZGD58OMLDw/Hdd9/VKzxFEARMTU2xYMECnD17FgkJCRrhDBsaGiI8PByxsbEa6SzQPWhfvHgBkUgEfX19WFpaIiMjQ92mNQknJydIJBK5qI+ZmRm4XC7S0tI06rzTCw9MJhNXrlypYduQIUOQmJiI3NzcRtlNC7NlZ2cjNzdX/npkZCRu3Lih9P6v3t7eSE1N1bgFBy2NhyAI2NjY1Pl8pbuCiEQiNVjX9tE6wiqETmPVZAdEE4iPj0dAQABMTEzUbUqzUNWPvkwmA5/Pl0dvCgoKYGdnV+/4Kisrg1gsbjAqqS4oioJEIsH58+flfXJHjRoFNptd47gqKipw4MABvPfeezVSoquqqrB9+3aMGTMG5ubmarnnBAIB/vjjDzAYDMyYMQO6urp12kELgf3zzz+4ffs2Fi9eDGdn53b1rHj27Bns7e2hr6+vblM0Fh0dHUyaNAnHjh1DeXm5Sp41JEmid+/eGDduHNavX48XL17U6wxzuVzMnz8f58+f1whnmCAI9O7dG8nJyeDxeGq1pS4MDQ1haWmJly9fAgCCg4M1Tom7IZhMJnr06CGPCpMkKf9f0yBJEu+99x5OnTpVrY6ZIAgYGhpi6NCh2LdvX6PHLovFQp8+fXD27FnIZDL5fdChQwd5uriyMDU1haGhoUb3zNbSMC4uLvL7/78wmUyYmZlpWygpCa0jrCLomj8rKyt1m6LRlJaW4u7du+jdu3erdAJU2UdYKBRCIpGgoqICpqamKCwsrJEe/F/4fD5kMpnGOsLl5eXYunUrkpOTsWjRInTp0qXWcSCTyXDixAn4+vrCycmpRqT4zJkzMDMzU1uabWVlJf744w9wuVy899579da8UhSF8vJybNq0CVKpFHPnztX4iL2ioSgKt27dQnBwcLs67uZgY2OD8PBwHD58WGXPGrpv6ocffog//vij3l63tBMwb948xMfHa0SdKIfDQXBwMOLj49VuS20wGAwEBwfjxo0bAN5G+egIcWsiMDAQKSkp8rTuzp07IyMjQ+PSvAmCgLm5OaKjo7Fv374aKdJBQUEQCoWN7pFNC7O9qxZNkiQGDBiA8+fPKzWllSRJBAYG4vbt20rbhxblQ2u91Ia2l7By0TrCKoKiKOTk5MDW1lbdpmgsFEXh7Nmz6N69ezUxpNaEKuu/+Xw+mEwmSkpKwOVyUVRU1KAjXFFRAQaDoXHtk+g+ud9++y0cHBzw2WefwczMrFaniKIopKen49GjRxg8eHCNc/7q1StcvnwZEydOVEtacUVFBX7//XfY2Njgf//7X4Np2bQolru7OyZPntxg+nRbRCgUIiMjA56enuo2ReMhCAIREREoLS1FcnKySvfr5uaG2bNn4++//65XXZdOk547dy5Onjwpr39VJ/3798ft27eVLmDUXLy8vPD8+XN5xo6BgUG1VNvWAIfDgaOjIx4/fgzgba2si4sLHj58qGbLakIQBHr06AGBQFAjastmszFu3DgcPHiw0YsRenp6iIiIqKYWbWtrCw6Hg6dPnyp1/Pv6+uLhw4fa9OhWDJfLRVlZWZ1ZCJaWlhqrft/a0TrCKkIqlaK0tLTNK7+2hOLiYjx8+BC9evVqtY4A3c5HFVRUVMDAwAA5OTkwMzMDRVH1KkYDb51nPT09jXGEKYqCVCrFpUuX8Ntvv2Hy5MkYMmRIvRFUiUSC3bt3Y9y4cTWOQyQSYdeuXRg/frzKF1Po+vbffvsNTk5OGDVqVL1OMEVRePbsGdauXYvBgwfL+wO3R7Kzs8HhcFrtApiqYbFYcoXbkpISle2XIAg4OTlhzpw5OHjwYL3RXjrqNn/+fBw9ehR37txR2ySOIAgYGxvD19cXly9f1sjJpLGxMUxNTfHy5UuQJAlfX18kJSVppK310atXL1y5cgVSqRQEQSA8PBzXrl1Te4p8bTCZTEyYMAFHjhxBRUVFtXPt7OwMFxcXXLhwodFR4e7duyMlJUUuLEeSJAYOHKj0+nRra2swGAx5fbaW1gf921dWVlbr+7a2tnVGjLW0DK0jrCKkUikkEola+5hqMhRFIT4+Hj169Gh1PW7fRZUOfHl5OTgcDrKzs2FqagodHZ0GI6AVFRXQ0dHRiDpMiqIgEAjw559/4ubNm1i8eDG8vLwabCt08eJFmJmZwdvbu0ZKdFxcHGxtbeHr66vyxRSBQIBNmzbBzc0Nw4cPr/dayGQy3L17F9u2bcPMmTPRrVu3Vrv401IoisLdu3cREBCgblNaFRYWFujTpw8OHz4MqVSqsv0SBAFbW1t8+eWXOH36NM6fP1+nk/OuM3zw4EGl10s2xMCBA3HlyhWNS9UFqisAA2/b8jx48ECl17alEAQBFxcXlJWVyVOEO3bsCB6Ph+LiYjVbVxOCIODg4IDAwEAcP368xnujRo3C+fPnG11bbmBggO7du+PcuXPybbi6uqKqqkqpPcDp0oXWuHCi5S0MBgPGxsZ13ifm5uYoLi7WyAWl1o7WEVYRAoEATCZT2x+zDng8Hh49eoQePXq0aodAlTXCubm5sLa2Bp/PR1lZGWxsbOp1vuhaVAMDA7W38KIoCrm5ufjhhx/A4XAwb968OlOh36WoqAhnzpzB+PHjqx0rRVHIzMzE9evXMXbsWJUfX0VFBTZv3gx3d3cMGTKk3usglUpx8eJFHDt2DJ9//jlcXV1b9ZhvKRKJBCkpKWpZvGjN0K2BysvLVaIi/d99W1hY4Msvv8TVq1dx6tSpOh02giBgZWWFefPmYd++fY2uu1Q0dLq2p6cnrl69qpEOQ+fOnZGamgqpVAozMzNIJBKVRvwVAZPJREBAgFzsi8lkwtvbG8nJyRp5zgmCwKBBg/D48WOkp6dXe4/L5aJnz574999/G+WA0GULycnJ8sgei8VCv379cPr0aaXYT+83KCgIycnJrWrhRMv/QT8n8/Pza31fR0cHVVVVWkdYCWgdYRWRl5cHU1PTdpv6WB8UReH8+fMIDQ3ViEhlS1Dl9c3Pz4epqSmEQiFKSkpga2vbYDSVdoTV6XDIZDIkJydj3bp1iIqKwtixYxtM6QbeOpCHDh1C3759YW5uXu09sViMXbt2YcyYMSpPr62oqMDWrVvh7OzcoBMskUhw4sQJ3LhxA1988YVWRR5vF8EkEgksLS3VbUqrg8lkYuzYsYiJiUFlZaXK929iYoLPP/8cDx48wMmTJ+t1hm1tbfHJJ5/g77//RmpqqlqcIpIkMWjQIFy4cAFCoVDl+28Ic3Nz6OnpISsrC2w2Gx4eHmpbOGgudHuiO3fuQCwWyxdsbt26pbFOmoGBAcaPH4+///67Wk0wQRDo27cvUlNTkZ2d3ahtcTgc+Pv749KlS/Lr5uPjgzdv3lRTqFY0tra2EAqFGtsvW0vDODs716kcraOjA4qitL2ElYDWEVYReXl5sLS0bPeT3tooLS3FgwcPWn00GHj7w6mqSQuPx5O3TuLxeLCzs6v38zKZDOXl5fW28VE2YrEYMTExOHLkCObOnYtu3bo1KnpLURRSU1ORk5ODPn361EiJPnv2LMzNzeHn56fSYxMIBNi2bRscHR0bTIeuqqrCrl27kJmZiXnz5oHL5bb68a4IHj58CE9Pz3bTL1mR0A6mn58fTp48qXKHiSAIcDgczJkzB48fP8aJEyfqdYYdHR0xa9YsbNu2rUb0TVVYWVnBxcVFIwS8/gutAJyYmCiP8iUmJqrbrCZjbm5eraWPjY0NJBIJCgsL1WxZ3Xh7e8Pc3Fze/olGT08Pw4YNw6FDhxrlyBMEgT59+uDWrVvyxSldXV2EhYU1ut64OTAYDHh7e+P+/ftK2b4W5WNtbV2nQB6bzYahoaFGlhi0drSOsArQtk6qGzoaHBISAkNDQ3Wb02JUNZmnKEouyMHhcFBQUNCgIjndd7i2nrzKhhaS2rJlC7KysrBw4ULY29s32g6RSIR9+/Zh4sSJ1coLKIrCmzdvcOHCBUyYMEGl57+qqgp//vknrK2tMWLEiDr3TddCb926FQRB4OOPP1Z7VF5TkMlkSEpKQmBgoPZ8NBM6avXs2TNkZGSoZf8GBgaYM2cOUlNTcezYsXqdYRcXF8yYMQObNm1Cdna2yp1RkiQRHR2NuLg4VFVVqXTfjYGuDRaLxbC3t0dRUZFaov0t4d0ewnR6dEBAAG7duqVxiw80BEHgf//7H86dO1etJpggCAQEBEAgEODJkyeNsp/L5aJTp07VBOLCwsJw//598Pl8pR1Dt27dcPfuXY2NvGupH0tLSxQXF9eq/k0QBMzMzDR6Mam1onWEVURWVhbs7e3VbYbGUV5ejnv37iE8PLxNTISZTKZKUlfEYjEqKyshk8lgYmICoVDYoMgYnVajasVouh74u+++g729PWbNmgVDQ8NGX296scTR0RGdOnWq9j2xWIzdu3djzJgxMDY2VtYh1IBWrjYwMMDo0aPrdYIrKyuxefNmmJubN9hTuL0hEAhQUFAAR0dHdZvSqtHV1cWYMWOwf/9+tTh3BEFAX18fc+fOxfPnz3H06NE6W7kQBAFPT09MnDgRv/76KwoKClTuHNnZ2cHW1hZ37txR6X4bA71gnp+fD319fdjb2+Pp06dqtqppEASBzp074+XLlxAIBCAIAoGBgbh3757GtvihHY3evXvj6NGj1WoxmUwmRo0a1WhhOoIgMHDgQFy8eFGeas3hcODu7l5v27GW2u/o6Agej4fy8nKFb1+L8uFyuRCLxbWK+b3rCGvqYlJrResIqwCKolBWVgYTExN1m6JR0ErRQUFB4HA46jZHITAYDJWIGYhEIrmQirm5OSiKalCRXCaTQSKRwNTUVGWLDjKZDA8ePMD69esxbNgwDB8+HEwms0lOcEFBAS5evIhRo0ZVS6OmKArXr1+Hjo6OSlWXxWIx9u/fD6lUigkTJtRbF15WVoaNGzeiY8eOGDNmjFYj4B0oisLz589hZ2fXqpXiNQG6x6+NjY3a2gPRzvCcOXOQnp7eoDPs7++PIUOGYOPGjfLsFlVBkiSGDRuG2NjYRveJVRUEQcDHxwf37t0D8DbKd/v2bTVb1XQ4HA5cXFxw//59UBQFMzMzMBiMOsWANAGCINC7d2+8evUKL1++lI9J+v7icDhITExs1Fi1srKChYUFHj9+DIqiQBAE+vXrh4SEBKUtVuno6MDV1RUpKSlaZ6kVQpIk9PX168waqC91Wkvz0TrCKoBOjdRO9qpTVlaGpKSkVt03+L+wWCyVRISrqqrAZrORm5sLNpsNDofTYKSRoiiIRCKVLchIJBKcPXsWBw8exKefforAwMAmqznLZDLs3bsXgwYNqtGDu7i4GKdOncLEiRNVphItlUpx7NgxlJaWYurUqfWe86KiImzYsEE+4dc6wTVJTExEQECA2lXM2wIEQWD48OFISEhQWR0Z3QdcJBLJ/xgMBj744AO8ePECR44cqdcZDg0NRc+ePfHLL7+Az+erdPLu5OQEExMTjaup/K8CsJubGzIyMjTOYW8IWkH58uXLAN5GVf39/TU6PRr4v+yKvXv3Vhu7DAYDo0aNwvHjxxt1LWg16jNnzsi3Y21tDUNDQ7x48UIpthMEgeDgYI0/x1rqxtLSss7FIhsbG20vYSWgnZmpAD6fL1/p0fIWiqJw6dIlBAYGqlzlV5mQJKmSHyCRSAQ2m43S0lIIhUJYWFg0uJggk8kgFArB4XCUuvBA18/u3bsXBQUF+PLLL2FsbNzkfVIUhcePH6OkpKRG6rxMJsO+ffvQt29flYnQyWQyxMXFITs7G7NmzarTCaYoCkVFRfjll18QGRmJnj17tpmFHkUilUrx/PlzDB8+XN2mtAkIgoCxsTF69+6NmJgYTJkypckLDO8+uyQSCXg8HsrKylBeXo7CwkIUFBSgvLwcQqFQ7vhKJBJIpdIaY1wkEmHHjh04c+YM3N3doaOjAzabDQMDA3A4HJiamoLL5cLJyQmZmZn45ZdfMH/+/GqZLcq8b+iFgz179sDX11ejShZsbW1RWVmJ0tJSmJqawsDAAK9fv4aLi4u6TWsSzs7O4PP5yM/Ph5WVFfz9/bFlyxYMGzZMY8Xx6LTuS5cu4dq1a9We305OTujQoQMuX76Mfv361Ts+CYKAk5MTmEwmXr58CXd3d5Akif79++Ps2bPw8PBQyjlwcXHBnj17IBQKtXPOVoiTkxNevXoFPz+/Gu8ZGhoqtca8vaJ1hFVAcXExOBwOWCyWuk3RGMrLy3Hnzh0sXLiwTTkJbDZbJRHhsrIyGBgYID8/H0KhEFZWVo1yhCsqKpSahk6XAWzevBk2NjaYM2dOs8W5RCIRDhw4gClTptQQyHrw4AGKiorwwQcfqGT8UBSFa9eu4d69e5g7d26dytsURaGwsBC//PILBg4ciLCwsDY1vhXJ69evYWBgAC6Xq25T2gwEQaBHjx64efMm0tPT4eLiUuf4o51e+rmQlZWFrKwspKeno6ioCHw+Hzo6OuByueBwOLCwsECHDh1gbGwMfX196OjoVPv776SefhZs2LABFhYW6NevH6qqqsDn88Hn81FUVITMzEyUlZWhuLgYSUlJmDp1Krp16ybfl62tLaytreX3G/2nqHPl4uICXV1dpKSkwMfHR2PuVSaTCQ8PDzx69AgRERHw9fVFcnIynJ2dNcbGxvCuSNaQIUNgaWkJFouF169fa7QuAIPBwNixY7Fu3ToEBATIfzMJgsDIkSPx448/IiQkpMFFfAaDgYEDB+L06dPo1KkTSJKEm5sbDh8+jPz8fKW0zzM0NIStrS2ePn2q7c3eyqC7ANCK9v+9dgYGBnJtGE1dSGqNaB1hFVBcXKzSukxNh6IoXLlyBX5+fm1CKfpdSJJUSY0wLaRCTzY7d+7c4HckEgkqKyuVJpZFURSys7OxefNm9O7dG5GRkc1+WFMUhcuXL8PW1haurq7V3hMIBNi3bx8+/PDDBuuiFQFFUbh//z7Onj2LuXPn1jlm6XrmjRs3IioqCt27d9fe83VAURSSkpLQpUsX7Q+6gmGxWHJhn88//7zaAiwtmFdWVobU1FSkpKQgKysLUqkUVlZWcHJyQmhoKMzMzGBiYtJidXMul4sFCxZg/fr1ePDgAQYOHFjr9X5XWZ3P5yMkJARZWVlITExEcXExmEwmjI2N0bFjR7i6usLe3h66urpN0huoDZIkMXToUBw7dgze3t4aU75Ai0vFxcUhPDwcPj4+2Llzp0ZHUmuDTtXdunUrBg0aBBaLhcDAQNy6dUujHWHgbY1vUFAQTp48iXHjxsnHmYWFBfz8/HDhwgUMGzaswaiwh4cHjh07htevX8Pe3h5sNhsRERGIj4/HpEmTFG73u+nRvr6+Ct++FuVia2uL/Px8SKXSGs8jfX19kCQJPp+vUnHQto5mPPXbOPn5+bC0tFS3GRpDRUUFbt68iS+++KLNOQo6OjoqiQgXFxeDxWJBT08PPB4PFhYWDX6nsrISIpFIKbXqFEXh0aNH+PvvvzFhwoQWR1dKSkpw7tw5LFiwoEbP4JMnT6Jz585wdnZWhOn1QlEUnj17hv3792POnDkwMzOr87P5+fn45ZdfMGzYMAQFBbW5sa1okpOTMXXqVHWb0eYgCAKurq4wNTXFrVu3EBYWhsrKSmRmZiIxMRFPnz4FQRDo2LEj/P39MWLECBgZGSmtrZqBgQHmzZuHDRs2gMVioW/fvjVStmmhrZkzZ2LTpk0oLCzE6NGjQZIkqqqqUFFRAR6Ph2fPnuH8+fPIz88HSZKws7ODh4cH3NzcYGJi0uRjoEWQ6Pvc09NTY+5bJycnecaPra0thEIheDwezM3N1W1ak7CysgKDwcCbN2/g5OQEf39/bNq0CSNGjNCYhYfaIAgC0dHRWLVqFXr27ClvT0gQBKKiovDtt9+iV69eDWpusNlsREZGIjY2Vp7BFBQUhO+//x58Pl8pGVru7u44duwYxGKxRqX8a2kYY2NjCAQCiESiGvcHk8mEoaEheDye1hFWIJr7FGpDZGVlaVfm/j8UReHWrVvw9PRskzeyqlSjS0pKwGAwwOFwUFRU1Kgor1AohFgsVrgjLJPJcPnyZZw5cwazZ8+Go6NjiyaTMpkMJ06cQFhYGMzNzattKzs7G7dv38by5ctVIrD05s0b/Pnnn5g5cyasra3r/Fx+fj42btyI4cOHa53gRlBUVAShUAg7Ozt1m9ImIUkSAwYMwDfffIP79+/j1atXsLCwQGBgIAYNGgQjIyOwWCyVjFOCIMDhcDBnzhz89NNPYDAY6NOnT6371tXVxcyZM7Fu3TpwOBz06tVLnnptamqKjh07yjUIKisrkZGRgZSUFFy4cAFisRgODg7w9vaGq6srzM3NGxU9ZTKZGDJkCE6cOAF3d3eNibjq6enBzs4Oz549g4+PD1xcXPDs2bNW5wjTEcqbN2/C0dERlpaW0NHRQXZ2Njp06KBu8+rFwMAA0dHROHLkCD7++GP52DAxMUG3bt1w7tw5jB49usH7yN/fHydPnkRxcTHMzMzA4XDQuXNnXL9+HQMGDFC43VwuFyYmJkhPT4e7u7vCt69FeTAYDDCZTIhEohrzOoIgYGJigpKSEvUY10bRSnWqgOLiYm0d3P9HJBLh8uXL6Nu3b5t0FnR0dJTeJ5GiKPB4PFRVVYHD4UAmkzXKERaJRPLIi6KQSCQ4cuQIEhISMH/+/BY7wXR69ZMnT2qIkYjFYuzduxcjR45Ueko9fY63bduGSZMmoUOHDvXWBG/cuBFDhgzROsGN5OnTp3B1ddXqJigQiqLk98/evXuxadMmiMViFBYWYunSpfjiiy/Qq1cvmJubKy36Wxe0kNfcuXNx/vx5XL9+vVZRQYIgYGhoiM8++wyxsbG19lwlCEJeu+zn54cJEyZgyZIl+PLLLxEYGIjnz5/j119/xapVq7B//348ffoUIpFIfn5q26eXlxcEAgHS09M1Rm2XJEkEBgbKex0HBATg3r17GmNfY6HTvB89eiRXWw4KCsLt27c1/lgIgkD37t1RWFiI58+fV2un1K9fP9y6dQulpaUNHoeenh5CQkLkrc3oNk1XrlxRSgYZSZLo1q2bVj26FcJgMMDlclFUVFTr+xYWFigoKFCxVW0brSOsZOgazrYY/WwqdF2gg4NDq1vVbiyqqBGWSqUoKSmBSCSCrq4uOBxOo2plaaVpRTjCFEVBKBRix44dyMnJwYIFCxRSBy+TyfDPP/9g5MiR1eykKEo+KVZ2z2C6XvH3339Hr1694O3tXacTzOPxsHHjRgwaNAjBwcFaJ7gRUBSF27dvaxcNFAQdIU1MTMSaNWuwefNmmJiYYOHChdi0aROqqqogEAhAkqRazzdBEOByuZg7dy6OHz9ep1NHEARMTU0xd+5c7N27F8+ePat3Mk8QBBgMBoyNjeHv748pU6Zg1apV+Oijj2BmZoYTJ05g2bJl2LRpExITE1FRUQGZTFZtmywWC9HR0Th27JhGOQ5ubm5IS0uDRCJBp06dkJWVBYFAoG6zmoyxsTE4HA6ys7NBEAQCAgLw8OFDpfXTVSQsFgtjx47FwYMHqy1yGxsbIywsDKdPn25wGwRBoGfPnrhz5w4qKysBvG2FY2xsjKdPnyrF7q5duyIlJUXpC/NaFAstmJWdnV3r+/b29nW+p6V5aB1hJSMQCFBVVdWmWgQ1F4lEgnPnzmHAgAFttm+orq6u0muEJRIJRCIRhEIhADTaAaUd55YKTFEUBT6fj02bNsHAwAAzZ86Enp6eQibZ9OTY39+/2vb4fD6OHj2KiRMnKr2uTCKRYOfOnXBzc0NERESdTnBZWRl+/fVXREZGaoWxmkBFRQXevHmDTp06qduUVg1FUaioqEB8fDyWLVuGK1euYOTIkVixYgWio6NhZmYGAwMDDBgwACdOnFBJyUZDEAQBS0tLzJkzB//88w9SUlLqdIZtbGwwc+ZMbNu2DW/evGmUg0qrSpMkCVtbW/Tr1w9ffvklvv76a4SFheHOnTv45ptvsHHjRty8eRNlZWWQyWQgCAJ+fn4oLi7Gq1evlHHozYJW7M7MzISenh64XG6r7CNKkiS6d++Oa9eugaIomJqaQk9PD2/evFG3aQ1CC15xOBwkJiZWiwr36dMHSUlJjerbbWJigo4dOyIpKUkeFe7Xrx/Onz+vlHvTwsICLBarVZxjLf8H/eyr65lnamoKHo+nBsvaLm3TG9EgysrKFOJ8tAUePnwIMzOzNl0XSIu7KBOpVArg7diSSCSNFmITCoUwMDBo0SIE3SP3p59+goeHB8aNG6cwMY7KykocOnQI48ePr6F0e+LECQQGBip97EilUhw7dgw6OjoYOnRoneeKXgjo0aMHwsPD2+zCjjLIzs6GmZmZtsdlM6EoCqWlpTh16hRWrFiBzMxMfPrpp5gzZw68vLyq3Y8EQSAkJAR5eXnIyMhQn9H/wc7ODrNnz8Zff/2FtLS0Op3hTp06Yfz48fjtt9/A4/GaFa0lCAJGRkbw9/fHrFmzsGTJEvTt2xePHz/GmjVrsHHjRiQmJkIkEiEqKgoxMTEasWgAvP098fPzw927d0GSJHx8fOSOVGuCIAh07doVz549k5foBAYGtor0aOBtuurIkSMRExMjT+8GACMjI0RERODkyZONOo4BAwbg0qVL8sVyLy8vFBQUKCXVlY683717V+Hb1qJcHBwc6nSEjYyMGpWOr6XxaGdvSqasrEypfVtbCxKJBLGxsYiKimrTTgOTyVRJRFgikUAgEKCiogL29vaN+h4tvtCSyGV2djbWrVuH3r17IyoqSmHRWYqiEB8fDzc3t2oCKhRF4dWrV3j48KHSxw7d1is9PR0TJ06ss361srISmzdvhq+vL3r37t2mx7OioVPc/f391W1Kq4NOxT969Ci++eYb8Hg8LFiwAO+//z7s7OzqFHlisVgYPnw4jh07pjFpkgRBwNnZGdOnT8eWLVvw+vXrOp1hPz8/REZGYtOmTfK00pbs19DQEN7e3pg+fTpWrFiB3r174+bNm1i9ejWSk5Nx8+ZNZGVltWg/iqRr1654+PAhKIqCj48PHj9+rDGOelPgcDiwsrLC8+fPAQB+fn5ISUlRSZcFReDg4ABnZ2ckJCRUiwr37t0bDx8+rLOmk4aO9Onr68vPAYvFQnBwMK5evapwx4Z2hO/fv99qzrGWt5iZmaGkpEQe9HgXWlVae00Vh3YGp2SKiorabD1sU3j27Bl0dHQ0XiWypTAYDKU/oMrLy0GSJEiSRGVlJUxNTRv1PaFQCB0dnWY5bhRF4enTp/j5558xfvx4hUdBeTweEhISMHLkyGqOulQqxd9//40xY8Yorf8x8Pb4njx5gvj4eHz00UfQ1dWt9TNCoRB//PEHOnXqhEGDBmmd4CYiFovx5MmTFrfXak/QpQhHjhzB6tWrUVVVhcWLF2PSpEmwsLBocAzSqZ0AkJqa2qwJNy00Rf/JZDL5n0gkQllZGUpLS6v9lZWVQSgUQiqVVvv8u6JVHh4emDRpEn7++WcUFhbWahtJkujVqxfc3d2xdetWhT1fCYKAnp4eunbtitmzZ2Pp0qXw9/eHlZUVPv/8cxw9ehT5+fl1imypChsbG0ilUuTn58PU1BRVVVUoKytTmz3NhSRJhIaG4urVqwDepn0zGAwUFhaq2bLGQZIkhg8fjrNnz4LP58tfNzQ0RI8ePXDmzJkGxwlJkujbty/OnDkDqVQKgiDQo0cPJCUlyUudFImNjQ1EIlGjUre1aA606GptjjA9D6qoqFC1WW0WbfskJZOVldXoiF1bRSqVyqPBbX3yy2AwqqVOKYOioiLo6uqCoiiUl5c3WohNKBQ2Sy1WJpMhKSkJBw4cwOzZs+Hs7KzQ6yiTyXDy5EmEh4dX68lIURRu3rwJXV1d+Pn5KW3sUBSFnJwc7NmzB7NmzarzfEokEuzatQuWlpYYNmyY1gluBiUlJfIaQS31Qy+8XLp0CfHx8fD398fSpUvl47Mp9wODwcCwYcNw4MABeHh41JnJQTu5UqkUAoEAOTk5KCwsBI/HQ0FBAXg8HkQiEaRSqTwzhSAIMJnMWiPStPPLYDDkfywWCzo6OjA2NoapqSmMjY3RuXNnrF69GsuWLYORkREYDIa83pe2f+TIkdi6dSsOHDiA8ePHK6zNEb0PQ0NDhIaGwt/fH/PmzUNubi42bNgAExMTREZGwtvbGzo6Oir/DSNJEh4eHnjy5Al69eoFFxcXpKamIiQkpNX9nrq7u+PIkSMQCATQ09ODj48P7t69Cxsbm1ZxLBYWFggICMCZM2cwatQo+RiNjIzEypUrMXDgwHp7zdOLUvQii7W1NYyNjWFvb49Hjx4hMDBQoeeBwWDA29sb9+/fr9GFQYvmwmazoaenh5KSkhptG+nOHxUVFdpuNApC6wgrmcLCQri6urbrB1BGRgaqqqrg5ubW5s+DKiLCpaWlYLPZEIvFEAgEjRZiEwgEYDKZTXLgZDIZLl26hAsXLuDzzz+HtbW1Qq8h7YQ+fvwYy5YtqyGQFRMTgzlz5iittycdbdu+fTvGjh0Le3v7Wo9PKpXi0KFDYDKZGD16tMb0Gm1NUBSFBw8ewNPTU+mCZ60ZWgX69u3bOHXqFFxdXbFw4UJYWFg0+96jU5GNjY1x7949BAYGAoDc4S0qKsKLFy/w6tUrvHnzBiKRCCRJwsLCApaWluByufD394eJiQl0dXXBZrPBZDKr/f33uUJRFKRSqdxplkqlEIvFqKqqglAoRGlpKYqLi5GXlwehUIiqqipMmjQJAQEB4HK5sLOzg4ODA5ycnGBsbAwdHR1Mnz4dP//8M+Li4pSSkUEQBHR1dTFs2DDk5uZi2bJlSEtLw4ULF3Do0CF069YNERERMDMzU+lCWEBAAOLi4tCrVy/4+/vj+vXrCAkJUdn+FYWhoSEcHR3x+PFjBAUFISAgAH/99ReioqJaxTOVIAhER0fjm2++kbciA/5vESU+Ph5jx46t9z5ls9no2bMnzp07h8mTJ4MkSURGRuLYsWPw9/dX6HkgCALdunXDkSNHEBkZ2SrOsZa380hLS0vk5OTUcISBt+Pt3awELS1DOxtRIhRFyRuot1ekUinOnDmDAQMGtIuHMJPJVHoaXUlJCYRCITgcDqqqqqCnp9fgd+joEpvNbvQEjo7k37t3D1988QVMTEwUvpAhk8lw+PBhREVF1WiXFBcXBx8fH9ja2ip0n+9CR3m7deuGrl271np8MpkMsbGxyM/Px0cffaQwcbD2BkVRSE5ORnR0dJtfEGsuUqkUKSkpOHjwIMzNzTF79mzY2dkpxOliMBgYPHgw/vjjD+jq6uLx48d48eIFKioq5Iq2vr6+GDx4MPT19aGjowMWi9Ui55t2khsSi6QoSt6T/OnTpxg2bBjy8vKQmZmJ69evy9MAbWxs4O7ujsOHD8PY2BihoaFKcYZ79OiBVatWobKyEt7e3vDy8kJRURGuXLmCdevWwdbWFv3790fHjh2V/jwgCAIdO3ZEfn4+ysvL0aFDBxw4cAASiaTV9eGm+/JevnwZgYGBsLCwgFgsBo/HazUlZEZGRujVqxdOnz6NSZMmyduSRUZGYs2aNRgwYEC1zKb/QguFxcfHo7y8HEZGRujQoQOEQiFycnIUnkHo4OAAHo8HPp+vbePZSqDryXNycuDr61vjGWxlZYW8vDx5yYuWlqF1hJVIVVUV+Hx+u04DpBURO3fu3C4mv8pOjaYoCiUlJXIHuLYakrqorKyEvr5+o66DRCLB0aNHkZ6ejrlz58LQ0FDh14+iKLx48QJFRUU1evDm5ubi9u3bWLp0qUL3+S4ymQwxMTHQ09ND3759a51Q0wJaycnJmDt3bqMWHbTUjlAoRF5eHhwcHNRtisZBURRyc3Oxf/9+lJSUYNKkSXB1dW3x4iG9KJefn4+HDx8iMTERd+/eRXFxMUaPHo0ePXrI26y8m4qsagiCAIvFwujRo7Fr1y4kJCRgypQpCA0NlTvJAoEAr169wosXL+Do6IjVq1fD29sb/v7+6NKlCxwdHeXZMS09DrruMy4uDhMmTJBHx0eMGIGoqCg8fPgQR48ehVAoRL9+/RAUFARdXV2lnT8dHR1YWloiKysLnp6eMDQ0RHZ2NpydnZWyP2Xi5uaG/fv3o6KiAgYGBvDy8kJycjIiIyNbxRyBFshauXIlCgsL5V0bjIyMEBQUhPPnz9fQuvgvHA4HnTt3xo0bN9C/f3+wWCyEh4fjwoULmDx5skLPg66uLlxdXfH48WNtm79WhIODAxITE2t9z8bGBrm5uSq2qO2iLXJTIkKhEBRFtds2IRRF4dy5c+jZs2e7iaIxGAylR4Rp4QuSJOtdef4vAoGgQUeYoiiIxWLs2bMHOTk5+Oyzz8DhcJTy4ymVSrF//36MGjWqWsSITkOOiopS2r4pisKdO3eQmpqKCRMm1JqqS1EU7t+/j3PnzuGTTz5RqlhXW4de9LC1tW23z8PaoHsBHzx4EOvWrYOfnx+WLFkCNze3ZjvBdJ1vcXExzp49i1WrVuHnn39GTk4Ohg8fjh07dsDc3ByhoaGwt7eXC+hpwgSZwWBg0qRJKC0txdGjR0FRFEiSBJvNhrGxMbp27YoRI0ZgxYoV+Pnnn5Gfnw8Wi4VLly7hhx9+wOrVq3HgwAGkpKTIf3+b23KpV69euHv3LkpLS6u9rquri8DAQHz11VeYNm0aHj58iGXLluHEiRPyGnhl/AbQrXAIgkDnzp3x8OFDhe9DFejp6cHe3h7Pnj2TR0fv3LmjbrOahL6+PiIjI/Hvv//KFbzpvsI3b95sUN2cdqavXLkir7MPCAhASkoKBAKBQm0lCALBwcG4deuWtuVOK8LKygr5+fk1XicIAqamploBNAWidYSVCK3SqwkTDHVQVlaGp0+fKlwAQpNhMplKbVEik8lQUlICmUwGoVDY6OganRqtp6dX57WgaxP//PNPVFVVYebMmUqLgNJtdHR0dKplC9Dq1EVFRQgNDVWaE/zq1Sv8+++/mDlzZp0K0S9fvsT+/fsxe/ZsGBsbt5sxrCySkpLg7++vFRn7/0gkEty+fRsrVqyARCLB8uXL0bNnz2anI9P3eHJyMtavX48ffvgBBQUFmDx5MlatWoXJkyfDw8MDdnZ26NixI27evKlxE2OCIKCjo4OPPvoIT58+xdmzZ2vYSEeu3d3dMWvWLNy7dw9Tp07FihUrMHXqVFhaWiIuLk7uLCckJKCwsBBisbhJx2tkZITg4GCcO3euVhtIkoSzszM+/vhjfPnllxAKhVizZg127tyJvLw8hbY4IggC3t7eePbsGcRiMXx8fPDgwQONu36NJTQ0VD7+7O3tUV5eXm3BQdOh0+efPXsmVxYHAFNTU3Tu3BmXL19u8NrY2NjAxMQEqampAN6Ot44dOyIpKUnh9jo7O+PNmzdKUabWohwMDAxQWVlZ6ziiHeHWev9rGtoZiRIpLy9XSkppa4CiKCQkJMDf379dRdIYDIZSHWGKoiAQCOQPyKYI6IhEonrT9wQCAX7//Xfo6+tj6tSpDdb1tQShUIhjx45h3Lhx1aKxYrEY+/btw//+9z+l7J9W2t61axcmTZoEU1PTGueDoigUFBRg586dmDZtmsIFwtojMpkMqamp2pomvB1feXl5+PXXX3HhwgV8+umnmDBhAoyMjJrtABcXF+PEiRNYvnw5Ll26hP79+2P58uWYOHEiXFxcqtWS0oI/Fy9eVHj0SVEYGBjg008/xZUrV+p02OlIV0hICH7//XfIZDI4ODigT58+mDdvHr7++msMHDgQr1+/xsaNG7FmzRqcOHEC2dnZqKqqanASSRAE+vXrh5s3b9bbroggCFhaWuJ///sfli5dCltbW2zYsAFbt27Fq1evmlS+Uh/GxsZgMBgoKiqCg4NDq3MeaWjl5KysLPD5fOjo6MhTd1sT+vr66N+/P44fPy5/jSAIDBgwABcvXmywRIogCPTv3x/x8fGQyWTyKHFCQoLCxgwNh8OBra0tnj59qnWeWgkGBgbyjKH/YmZmhvLyclRVVanBsraHtkZYieTk5MDGxkbdZqgFoVCI27dvY968ee3KiWAwGAqNBPwXOuoDvO0j1xQhNqlUWmdaanl5OTZv3gwXFxcMHz5cqSIs9CKJs7MznJycqr13+fJlWFpawt3dXSn7psWxevToAXd391rHJp/Px+bNmzFs2DB06tSpXY1fZZGTkwM2m92uhQOBt4tRFy9eRHx8PKKjoxEWFtaiCHBubi5iY2Px5MkTBAYGYv78+TA1Na01rZpWSOfxeMjNzQWPx8Mvv/wCBwcHeU9dExMT2NragsvlwsTERKmLYQ1hbGyMTz/9FOvXr4exsTE8PT1rnCeSJBEdHY2CggL8888/mDJlCphMJgiCAIfDgaenJzw8PCAWi1FYWIjExETs2LEDUqkU3t7e6NatG+zs7Op83nG5XPj4+ODSpUsYOnRovdeJIAgYGRmhf//+CA8PR2JiIrZu3Qpzc3MMGTIELi4uLar5ZjKZ6Ny5Mx48eID+/fvD1tYWr169alJ5jKagp6cHOzs7pKWlwdfXF8HBwThz5ozSsoCUAS38de7cObx+/VoucmVtbQ0nJyfcunULPXv2rHcbnp6eOHToEPLy8mBjYwNnZ2eIxWK8fv0ajo6OCrU1ODgYN2/ehK+vr8K2q0V5sNlscDgcFBUVgcPhVHuPbp8pEonU+oxuK2gdYSWSn58vF1JoT1AUhcTERLi4uLQroTA6ZU+ZjrBUKkVVVRWYTCb4fH6jHQu69ve/qc4URaG0tBS//vorfH19VdLGoqysDPHx8Vi4cGG110tLS3H69GksXLhQKTZQFIXY2Fjo6uqiZ8+etU64RCIRtm7diu7duyMgIKDVTMo0nQcPHsDLy6vdtk2i0/F37twJU1NTfPXVV7VmIzRmOwDw5s0bxMTE4OXLl+jTpw/Gjh0LAwODatujP1tYWIikpCQkJyejpKQEXC4X1tbW6Nu3L44dO4awsDCw2WxUVlaCx+PhwYMHKC4uRlVVFaytreHr6wsvLy+Ym5urVFCLIAhYWVlh1qxZ+O233zBv3jzY2dnV6gxPmjQJv/zyC+Li4hAVFVUt/Z4gCLDZbNja2mLIkCGIjo5GYWEh7t69i507d0IikSAwMBDBwcHyViX0PgiCQFRUFL7//ntERkbC0NCwUXbr6+sjPDwcISEhuHfvHnbt2gUjIyOMHDkSLi4uzTqPBEHA398fhw8fRr9+/eDv74+kpKQ61e41nZCQENy8eRM+Pj7VVLEb2w5QE9DT08PAgQNx/PhxzJ49W35dBw8ejK1btyIkJKReR4XJZCI0NBSXL1/G2LFjQZIkwsLCcOXKFUyYMEGh19XDwwPHjh2DWCxuN5otrRmCIGBubo7CwkJ06NCh2nu0boIyhVnbE+1zVqICKIqSD+DW+CPVEiQSCc6fP48ZM2a0u2MHoNTU6LKyMnl9mkwmq7FSWB//bbVEO8G//PILQkND0bdvX6VfL1pALSAgQD6xpl+PiYlBaGioUhaP6B62ycnJmD9/fq0OmUQiwYEDB2BtbY1+/fq1y7GrDOh68P/973/qNkXl0AtQZ86cQUJCAiZMmCBvh9GU8UULMGVlZSEmJgbZ2dno378/pk6dWqPcgd7no0ePEBcXh/LycnTt2hUjR46Eo6OjfBJMURR4PB5kMplctf3dtMmysjK8evUKSUlJOHv2LJhMJoKDgxEUFKQyp5jufzx58mT8+uuvWLhwIbhcbrX90o7uRx99hB9++AE2Njbw9/ev1TaCIMBgMGBlZYVBgwZh4MCByM3Nxc2bN7Fp0ybo6OggLCwMQUFB8rImMzMzeHh44Pr16016LtB2devWDf7+/khOTsbOnTvlDrGzs3OTRcpsbGzA4/EgFArh6emJM2fOtErHhk6PPnLkCAQCgVxAKy0tDX5+fuo2r9EQBIGQkBCcPn0ab968gZ2dHQDA0dERXC4XDx8+rHdBlSAIhIaG4ocffsDgwYNhYGCA4OBgfPfdd6ioqGjUwktjobM80tPTlZZxpUWx2Nra4vXr1/K+7zR0Bk9DomxaGofWEVYSMpkMRUVFsLCwULcpKufJkycwNjaW/yi0J5Q9MSwtLYVQKISpqSlkMlmThIdEIpHcEabbMP36668ICwtDnz59VOL48Xg83Lx5E19//XW1/eXk5ODBgwdYsWKFUuwoKCjAwYMHMXv27FrTw2UyGS5cuIDi4mJ8/PHHWkEnBVJaWory8vIaafBtHYqikJOTg7/++gsmJiZYsmRJs0TXZDIZcnJycPToUeTk5GDAgAGYMWNGrQ5wVVUV7ty5g9OnT8PMzAxDhw6Fm5tbrY4SQRAYOHAgNm/ejO7du9cQdqRVmrt27QqxWIzs7GzcunULGzZskPdS9fHxqVeATxEQBIGuXbuisLAQv/zyCxYsWFBDd4IgCBgbG+Pjjz/GTz/9BDMzsxpRlNq2SxAEbG1tMXLkSAwZMgSZmZm4cuUKzp49C0dHR/Tp0wcuLi6IiorCxo0bER4e3mQBQbo1VGBgIHx8fOQRYhMTE/niRGMzYPT19WFra4sXL16gc+fOAN72lW+NmWf0saSlpcHb2xuBgYFITEystW+qJqOjo4MBAwbg5MmT+OCDD+S/HUOGDMGhQ4fg4+NTb6kRh8NBx44dkZycjNDQUHA4HDg5OSElJQVBQUEKOxcEQaBbt264ffs23NzcWtU5bq84ODjg2rVrNV6ndQny8vLa3e+qMtA6wkpCIpGgvLy8XaUGA2+P+9y5c4iOjla3KWqBIAiFC128S1lZGcRiMfT19SGVShv9Y0bXFtMKyTweDxs3bkRERAR69eqlEsePoiicOnUK4eHh1erapFIpjh49iqioKKW01hEKhdi1axeGDx9ea80+3Sbp5s2bmDt3rlLro9sjaWlpsLOza3VRq5YgFouRkJCA2NhYjB49GkFBQU1OC6dF2/799188e/YMUVFR+OCDD2rtRCCRSJCcnIyjR4/C2toaH330Eezt7Rt0sKysrODg4IDbt2+jR48edT5PWCwWnJ2d0aFDBwwfPhzp6em4cOECjh49Cj8/P/Tq1QtWVlZKK6sgSRK9e/dGUVERtm/fjpkzZ9aacmpnZ4f3338fv/32GxYtWtSkmnQWi4WOHTvCxcUFFRUVePz4MWJiYlBaWirvE5yYmFjveaqPdyPEvr6+SE5OxrZt22Bra4vhw4fD1ta2wecwQRDw9fXFvXv30KVLF7i6uiI1NbVVOsIkScrrVr29veHp6YmYmBh5d4PWAkEQCAsLw9mzZ5GbmwtbW1sQBAFXV1fIZDK8fPmy3ggsSZKIjIzEnj17EBwcDAaDgT59+uD48eMICAhQ6D3l4+ODCxcutMosgvZIfW2SzM3NUVBQoGKL2ibasIeSoNNj21tNXHZ2NoRCIVxdXdvtiqMyVRlLS0shlUohk8lgZmbWpHMsEAigq6uLwsJCbNiwAX369FGpE5yfn48HDx5Uiz7TbYpyc3OVIpQik8kQExMDBweHWlPUKIpCdnY2Dh06hA8++EBpfYvbK3S/5m7duqnbFJVAKzhv3LgRDx48wOLFixESEtKk3wE6W+PAgQP48ccfYWNjg+XLlyMiIqLWKHB2djbWr1+PM2fO4IMPPsDs2bPh5OTUqAk0SZIYNGgQzp0716iSDoJ420fX09MTs2bNwuLFi2FkZISNGzdi3bp1SEpKUlrdGoPBwKhRo6Cnp4d9+/bVai/dZmjgwIHYsmVLs1IHCYKAoaEhgoODMX/+fMyZMwdSqRRZWVnYuHEjnjx5ArFY3OzjoFtEdevWDcuXL0eXLl2wceNG/Pnnn9Va8dSFu7s7nj17Boqi4OPjg4cPH7ZaJWB3d3e8fPkSVVVVMDQ0hKGhYa29UzUdHR0d9O3bF6dPn5ZrhDAYDAwaNAixsbENLo7b29uDJElkZWWBIAh06NABFRUVCj8X5ubmYDKZyM3NVeh2tSgHExMT8Pn8Gs8bgtD2ElYkWkdYSVRVVYEkSaULD2kSMpkMZ86cQd++fdvVcb+LMp1KeoJM1wBaWVk16fsCgQB8Ph8///wzBgwYgPDwcJWmAB87dgx9+/atVvcklUpx4MABjBo1SuEr1BRF4d69e0hPT8fw4cNrPdby8nL88ccfmDhxorZNkhIQCoXIyMiAl5dXmz+3FEXh8ePH+Pbbb9GlSxd89tlnTRLEolObz507h5UrV4IkSSxbtgyDBg2Cvr5+je3IZDKcP38eGzZsQEREBBYuXIgOHTo0+dlrb28PMzOzJvelJUkSXC4X0dHR+OabbzBo0CDEx8dj2bJliI2NRVlZmby2WVEwGAxMmTIFeXl5OHPmTK3ChHQbmg4dOuDvv/9ukWYDXU88atQobNq0Cc7Ozvjuu++wYsUKnD9/Hnw+v9nHSDvEERERWLlyJWxtbfH9999j3759KC8vr3ObdH12fn4+OnbsiKysrFYrmsPhcGBhYYG0tDSQJAlfX18kJSW1Oseejgo/f/4chYWFoChKntKfl5fX4AIHg8FAz549cf78eVAUBRaLhZCQEFy5ckWh54IgCAQEBODu3but7hy3R+iF+fLy8hrvmZubo6ioSHsdFYDWEVYSRUVFMDExaVcOIY/HQ3Z2dqtVsVQUyhTLolNhSJJsUkSY7p+7b98+DBo0CGFhYSq9RtnZ2Xj58iUiIiKqRYOTk5PBYDDg7e2tcHsKCgpw9OjROnsii0QibN++Hb169WoXjpo6yMvLg66ubpNE3VojVVVVOHLkCP755x98/PHH6Nevn7yNT0NQFAWpVIrHjx9j1apVePbsGRYvXowxY8bU2VtYLBZj7969uH37drWoc3NTdgcPHozY2NhmPbvoGtguXbrgyy+/xJw5c5Cfn49Vq1Zh586dyMnJUVi5CJ1ePHPmTFy7dq3OCT1Jkhg7diz4fH61KF1L9qurq4v33nsPnTp1wgcffID09HSsWLEC+/fvR1FRUbP3QQvfDBo0CCtXrgSDwcCKFStw9uxZCIXCGsfHYDDg5uaGlJQU6Ovrw8DAAIWFhS06PnVBkiQCAgJw584dAICvry8ePnyo1PIiZaGnp4fevXvj9OnT8td0dHTQq1cvxMXF1ftd2ml+8eIF+Hy+vJ43OTlZob1iaUf4/v37Sp2naFEMdEu22vqFW1hYoLi4uFXeK5qG1hFWEvn5+bCwsGg3k2uKonD58mUEBwfL61C1KB4ejwfgrbPdlNZJhYWFKCsrw6RJk1Teq1Emk+Hw4cMYMmRItdov2nkYM2aMwutyRSIR/vrrLwwfPhyWlpY1jlcqleL48eMwNzdHr1692s19qkroiLyfn1+bPb90yv+6detQVFSExYsXy9vjNPb7eXl52LRpEw4fPoyJEyfi448/rve3o6qqCnv27EFZWRk+//zzJpdI1IazszN0dHTw9OnTZm/jXfGp9957D0uWLIGtrS02bdqEDRs2ICUlBWKxuMURDHpy+Mknn2D//v1IS0urdZtsNhszZszArVu3kJiYqJD9uru7QywWQyqVYvr06Vi8eDEMDAzw448/4vfff8fLly8hkUiaHSHmcDgYO3YsFixYgIyMDKxatQqJiYnVUiPpNkpJSUlgMBjw9PRs1enRXl5eePr0KaRSKczMzFBVVYWysjJ1m9VkaAXolJQUlJSUyF/r3r07UlJSanVm3sXQ0BBeXl64ffs2gLcqz1ZWVkhNTVXotbW2toZIJJLPJbRoNmZmZigqKqrxup6envxZpKVlaB1hJVFQUFCtPUxbRyQS4e7duyp3sjQNZR87XfNWUVHRaEVyuia4vLxcLZHPtLQ0FBYWIjg4WP4avXDi4OAAFxcXhe5PJpPh5MmTsLW1rbMu+MaNG8jMzMTYsWPbVdaGKpFKpXj48GGrU4FtLHQq9Nq1a9GjRw9Mnz69SZHvyspKHD9+HOvWrUPXrl3x1VdfwcPDo95yBYlEgsOHD0MkEmHGjBn19ihtCgTxtl9uXFycQiJFBEHAxMQE/fv3x7Jly9CnTx8cO3YM3377LW7dugWBQNCiyT1BELCxscEHH3yALVu21FlLaWRkhNmzZ2P//v1IT09v9v5oWCwWBgwYgFOnTgF4K2YzZMgQrFixAl27dsWuXbuwbt06PHr0qNl1xATxtn/yBx98gBkzZuD8+fNYu3Yt0tLS5FFnZ2dn5Ofno7KystXXCZuZmUFfXx/Z2dlgs9no1KkTHj9+3CqPh8PhIDg4GOfOnZPbz+Fw4Ofnh4SEhHqPiSAI9OrVC1euXIFEIgFJkoiIiMClS5cUaiOTyYS3tzeSk5Nb5Tlubzg5OeHVq1c1XmcwGKAoShvZVwBaR1gJ0GqfrVHJsTnQfUKdnZ3B5XLVbY5aUfaEXyAQAHg7IW7MpLuoqAgbN25EZGQkLC0tVa4UKZFIcPToUYwcObJa1Le8vBxxcXEYPXq0QuuUKYpCSkoKUlJSat02RVF49eoVzpw5g2nTpinMkdBSk/LyclRUVMDa2lrdpigcqVSKM2fOYM+ePZg1axbCw8MbLYhFURRSU1OxZs0aFBcXY+nSpejVq1etatD//d7p06eRl5eHqVOngsViNft5Q9e1vlvf6ubmBoFAgOzs7GZtszbolGI/Pz8sXLgQEyZMwI0bN7BixQp5j+PmTsbpCO2oUaPw66+/1hpFpB3m6dOnY/PmzQpJIQ4MDERmZqbc+SYIAvr6+ggLC8OSJUsQFRWFEydOYM2aNbhz5w6qqqqadYwkScLFxQXz58/HwIEDsW3bNuzYsQNFRUXQ19eHqakpsrOzYW1tjaKiIoWm0KqSd2uDCYJAYGBgq61hpevTb9++DT6fL3+tT58+uHbtWoO13Pb29mCxWMjIyAAAeHh4IDc3Vx5hVpSNQUFBuHv3botLBrQoF7pNUm0LfUwmE0wms9XqA2gS7UvSWEXQ6XJtcQJYG7Roy3vvvdcmIz9NQZnHT1EUSktLYWhoCDabXW8kkxbW2rhxI/r16wcvLy8wGAyVimNRFIVnz55BIBDAx8enWm1wXFwcAgMDFdpnmz7m/fv3Y+bMmTVS9Ok66T///BOTJ09ukpCRlqZBO3uurq5tqk0HRVEQCATYvXs3ysrKsGjRokb3BqYoCnw+H4cPH8azZ88wefJkeHh4yFOKG/runTt3kJSUhC+++KJBp/m/3wXePqcLCgqQnZ2NzMxMFBcXQygUyidSOjo64PF42L59OyZMmAAHBwcYGBg0yr6GIAgCTCYTrq6umDt3LnJzc3H69GmsXLkSoaGhiIyMrLMeuqHtdu/eHQUFBdi6dSs+++yzGotbBEHAy8sLUVFR2Lx5M+bPn9+i3sc6OjoICwvDpUuXMHbsWPl23q2V7ty5M168eIETJ07g+PHjiIqKQlBQULMWL5hMJvz8/ODl5YVz585hzZo16Nu3L7y8vJCcnIxOnTrB3NwcGRkZcHd3b5XPNF9fX2zfvh3Dhg2Do6Mj8vLyUFVV1SrLrLhcLry9vZGQkIDo6Gh5hN/GxgbJyckICQmp87t0VPjixYvo2LEjdHV10blzZyQmJqJfv34Ks9HBwQE8Hg8VFRUwMjJS2Ha1KJ53RbHevbcZDAZMTExQWFjY7tq0KhptRFgJyGQyVFZWwsDAQN2mqIQXL15AR0cHjo6O6jZF7ShzEiIQCFBaWgpjY2Po6OjU6QhTFIWysjJs2rQJPXv2RHh4OMRiscodYalUimPHjmHkyJHVbC0sLMTt27flkwRF7m/fvn3o06cP7Ozsau21unPnTvTs2ROdOnVqlRPG1gJFUUhMTKw1Nb21Qtfz/vDDD+ByuZg7dy5MTEwadXxSqRR3797FqlWrYGhoiGXLlsHLywskSTbKCc7MzMTBgwcxc+bMRrf4oigKIpEIT58+xZ9//only5fjjz/+wKNHj8DlchEaGoro6GiMGjUKI0eORN++fTF69Gg8e/YMBw4cwJo1a7B8+XL8888/ePLkSYvTmYH/qyO2sbHBtGnTsGjRIohEIqxatarZolMEQSA6OhpcLhf79++vtWaOdjBcXV2xe/fuFqUTEgSBnj17IjExERUVFbW+z2Aw4O7ujvnz52PGjBlITEzE8uXLcf36dYhEoiafRzqyPnjwYCxevBhZWVmIiYnBtWvXIJFI0LlzZzx8+LDZx6RubGxsIJFIUFBQAENDQ1hZWdVZ+63p0GUGCQkJ8gwu+rWzZ8/WO/bo+u+XL1+irKwMBEEgIiIC169fV2gKrK6uLjp27IhHjx61ynPcnjA3N0d5eXmNyC8tmFpb/bCWpqGNCCsBmUwGiUTSpiIhdSGTyXDu3Dn069dPpU5We6SiogKlpaVwdHSsV5Gcz+fjt99+Q3BwsFwISiwWg8ViqewaURSFJ0+eAAA8PT3lE3eZTIZ///0XvXv3VqiSMEVRuHr1KmQyGcLDw2ttNXPq1CkYGBhoxbFUgFgsRlZWlsLrv9UFRVF4+vQp/vrrL4wYMQLdunVr1L1EL0odOHAAubm5+OSTT+Do6Nik8VdeXo6tW7diypQpjWqZRmdGXLt2DdeuXZM7vcOGDQOXy63X+aa/W1ZWhuHDh4PH4yElJQWnTp1Cfn4+XF1dERYWBhcXlxo9jZsKQRAwNzfHuHHjMHDgQCQkJOD7779H586dERUV1SSxSSaTiYkTJ+Lnn3/G+fPn0a9fvxrfJUkSo0aNwubNm3Hq1CkMHTq02c9DExMTODs7Izk5uV4FfpIk4ezsjE8//RSZmZmIiYnB6dOnERUVhYCAgCZF9oH/O2cffPABevXqhblz5+KXX35BRESEXHm5NUKSJLy8vPDo0SNYW1vD398fiYmJ8PLyUrdpzcLCwgIuLi64ffs2evbsCYIg4OrqColEgvT0dHTq1KnO79JR4Lt376J3796wt7cH8LbzQocOHRRiH0EQCA4OxsWLF9G9e3eFbFOLcqCfswKBoEaGhKmpqdYRVgBaz0UJ0Cs37cERzs/PR15eHry9vdVtikagTEezoqICIpEIYrG4TqVYPp+PTZs2wdfXF3379pXbIxaLwWazVeYI09HgYcOGVaudzM3NRWpqqsKd0Tdv3uDcuXOYMGFCDQVqiqLw4MEDPHr0COPHj9eKY6mAV69egcvltom2STKZDDdu3MBff/2FGTNmIDg4uFH3kUwmw8OHD/Htt9/C0tISCxYsaLITLJFIsGfPHoSEhDTYYoyiKPB4PBw4cADffvstysvLMXfuXHzxxRfo0aMHzM3NwWAw6t0GrXybnJwMiUQCGxsbREZG4vPPP8fXX3+Nzp074+TJk1i5ciUOHz6MnJwchbQm4nK5GDZsGJYvXw5LS0usXbsWu3btarD/6rvo6elh5syZOH/+PO7fv1/rZ3R0dDB9+nTcvXsXt2/fblF98oABAxAfH9+oSB1JknBycsLs2bPx4YcfIjExEd988w1u3brVrNpekiTh5uaG6OhoAMCePXtw586dVq0EHBQUhKSkJMhkMnh4eODZs2etuoY1Ojoa8fHx8utLkiQGDhyIs2fP1ntcdPbC1atXIZFI5D2Kr169qtDorbOzM968eQOhUKiwbWpRPHR7NVoo9V3Mzc3lfau1NB+tI6wEiouLweFwFN4SRtOglX/DwsLa/LE2BWXJ2VdUVEAmk4EgiBr1rRRFobKyEr/99hu8vb0xcODAapN1VUeEHz9+DAaDIa+BBN46BseOHcOgQYOgr6+vsH0JhUL89ddfGDt2bA2xNlq47tChQ5g+fXq19k1alANFUUhKSoKPj0+rXnSgFTljYmIQFxeH+fPnw9XVtVGpzJWVldizZw/279+PDz/8EMOGDWtyBJWiKFy7dg3l5eUYNGhQvVFcgUCAf//9F9988w2YTCaWLl2KcePGwcrKqsnXwNjYGN7e3rh+/bp8gkWSJIyNjREaGoovv/wS8+fPB4vFwoYNG7B+/Xp5v9N3xbeaCkEQMDQ0xKBBg7BixQpYWFjghx9+wK5du1BQUNCobZuYmGD27NnYuXMnsrKyav08h8PBxx9/jAMHDiA9Pb3ZrY7oRY269lPbdxgMBhwdHfHpp5/igw8+wJUrV/DNN98gOTkZUqm0ybb4+/uDy+Vi1apVsLOzw8KFC/Ho0SPIZLJWNTkmCAJOTk7g8XgoKyuDubk5mEzm/2PvvKPbqrK2/1xVy5YlW5Zb3HtvqU5z4vSekA5JgLwQIEOHYYYyMDMM78wAWfQ+EAZCCGmQOL07PXYc9xb33i1Lsq0u3e+PfPe+ES6xZdmSHf3WyppBlu499+pIOs/Zez8bTU1Nlh6aSRAEAS8vLwgEAhQWFtL1nePHj0d1dfU9o3geHh5gsViora0FcGeToKCggE61NgcCgQBubm4oKysz2zFtmB8qC6Q3oz8PD49BbRba6B2bEB4GJBIJnJ2dx3z6ZXd3N3Jycu77lkkjRXd3N/R6PVgslpHgo2oBv/rqKzpK8HvBq9VqwWKxRkQIU07RDzzwAL0Ip+oc6+rqkJiYaLb5Qjnp+vv7IzY2tsfmgEajwffff4+VK1fCw8PDNk9HAJIkkZ+fj9jYWEsPxWSoz9R3332Hqqoq/PnPfx5QOzySJFFVVYV33nkHTCYTb7311qD6Ct99nMbGRhw5cgT/8z//06sjNUmSMBgMyM3Nxd///ne0tLTgzTffxJo1a0wynqIgCALz5s3DxYsXe7QAIggCDAYDYrEYK1euxDvvvIN58+bh1KlTePPNN3H06FHI5fIht0ZycHDAkiVL8Pbbb0MsFuPf//439uzZc89jEwQBHx8fPProo/jss88gk8l6PJ8gCHh4eODxxx/HF198gY6ODpPGy2KxkJycjDNnzgz6+qgI8csvv4zNmzfj6NGj+Oc//zmoKChBEAgPD0dFRQXs7e2xbt06eHl5Ye/evfjmm296vXZrhs1mIzAwECUlJWAwGAgPD6fLa0YjDAYDS5cuxYkTJ+jNcS6XiylTpuDSpUv9vjdMJhMzZ86kWyc5OjrCy8sLt2/fNtt7SrlHU32LbVgvXl5evbr58/l8dHV1jarPuTViE8JmhiRJtLe3j3lHWqplUlhY2JhIfzQXAzG/MZWOjg4wGAyo1Wojt2WtVosffvgBnp6efda9UWZZIzEnc3NzweVyjRxMSZLE/v37sXz5crNFZUmSRFlZGXJzc7F69epe+wUfPnwYPj4+Y8q0ydppb2+HXq8fte3jSJJEd3c3Pv/8czg4OOAPf/gD7Z7c32t0Oh3Onz+PL774Ahs2bMBDDz1kch2tRqPBd999h3Xr1vUpwDUaDX7++WccPHgQjz/+OB577DGzbcC6u7vDxcUFBQUFfT6HIAhwOBwkJCTglVdewXPPPQe5XI5//OMf+O6771BTUwOdTjekCLGDgwOWLl2Kt956C2w2G2+//TaOHDnS7+KPIAjExcUhOTkZX331Va/tRSgn6UWLFuHLL780KT2UIAjEx8ejtLQUnZ2dJr2ewWAgLCwMr776KpYtW4bdu3fjo48+Ql1d3YAEsaOjI1gsFqRSKcLCwgAAr732Gry8vPDOO+/gypUrJvczHmkoYZaRkQGDwYD4+PhR3euWIAiEhIRArVbTWQOU+VVaWlq/bW8IgkBsbCxKS0uhVCrpnsL3EtCDJTIyEiUlJaNmjtyPUK7jvUV+ORwOtFrtqP2MWAs2ITwM3A89hHU6HS5duoQ5c+bYBMYI0draCiaTCbVaTdvl63Q6/PLLL2CxWFizZk2faZAajYZeeA0nGo0Ghw8f7jGWkpISdHZ2YuLEiWY7l0KhwM8//4xNmzb1ENckSSIrKwvl5eVGkWkbw09RUdGobZtE1dl+9NFHCA0NxcaNGwd0HXK5HF999RUyMzPx5z//uUd2wmDHcOTIEXh5eWHixIm9Hqe7uxtffPEFVCoVXn311QGlbA8WqgZ2IKUeDAYDXl5eeOihh/DXv/4VAQEB+Oabb7Bjxw7k5OQMqQ6RIAgIhUKsXbsWr7/+OqRSKd5++22cP38eKpWq10UgFdX28PDAnj17eq3jJQiCNiPq6zn3wtHREVFRUbhx48aQFqNUi6Q33ngDkydPxqeffooffviBbpvS3+tCQ0NRUFAAT09PKJVKqFQqLFu2DC+//DLS0tKwY8cO1NXVjYrFcnBwMGpra6FWqxEQEIC2tja6H+9ohM1mY8GCBTh27Bh9/11cXODj43NPkS8QCBAYGEg/LyQkBM3Nzb32yzYVsVgMOzs71NfXm+2YNsxPX0KYy+VCp9MNWzne/YJNCA8DjY2NY76HcFVVFbhc7pi/TmuC+gFkMpngcDjQ6/U4dOgQ5HI5Nm3a1O+CXavVjogQzsnJgb29vZErpk6nw4EDB7B69WqziSODwYBDhw4hJiYGQUFBPURAa2srDhw4gK1bt9rqgkcQqt+tOTc8RpLGxkbs2LEDM2bMwNKlS3tNSb4bkiRRWlqKf/7zn/D19cXzzz8/oBTq/qisrER6ejrWrVvX6wYOJYKpFGBz1ttTEASBsLAwdHV1obGxcVCvc3R0xJw5c/DWW29h6dKlOH36NN5++22cPXt2SGl8BEHAxcUFmzdvxksvvYTi4mK88847yMnJ6XUhyGKxsHHjRrS0tODMmTO9npfJZGLDhg1obW3FuXPnTGprNGfOHFy8eNEsxk5Uj+K33noLYrEY//znP5GSktJrmybq/PHx8cjNzQWDwcC4ceNQW1tLt6h64YUXkJycjI8//hhHjx41qXXTSMLj8SASiVBXVwculwuxWDyqRRpBEEhISEBtbS1d48lgMDB//vw+5+Tdr501axZSU1NBkiTs7OwQGRmJzMxMs72HDAYDCQkJyMzMNMvxbAwPYrEYUqm0R+Sew+HAzs7OrJsj9yM2ITwMdHV1jel0YZIkcfbsWSQnJ9sibSOIXC6nU+HYbDZOnz6N8vJyPPbYYz1s9X+PRqMBg8EYViGs0WiQkpKCNWvWGKVEFxQUgCRJxMTEmOU8JEmiuLgYFRUVWLJkSY9rUqvV+O9//4tVq1YNqN2MDfOhUCjQ1NSE4OBgSw9lUJAkicrKSnzwwQdYvXo1Zs2a1e9nharPvXDhAr755hts3boVy5cvH/JGj0qlwn//+19s2rQJfD6/xzmpuuWAgACsXr36nkJ9KDCZTMyaNQvnz583SSByOBxER0fjj3/8I/7whz+goqICf/vb3/Drr7+aXJcL3Fm8u7u7Y/v27Xj44Ydx+PBh7NixA9XV1T0MtbhcLp588kmkpqb2GYHjcrl44okncO7cOZP6qnp7e4PNZqOystKk6/k9VEr4smXL8Je//AXt7e3429/+huvXr/eaau7j44PGxkbodDrExcUhJyeHfg6LxcKUKVPwxhtvoK6uDv/85z9RVVVltWKYwWAgLi4OWVlZAID4+HhkZWVZ7XgHAo/Hw7Rp04yEb1BQEDQaDWpqavp9bUBAABQKBZqbm2lH97tN7MxBQkICcnNzbVFFK4bD4YAkyR5CmMlkwtHRcVS7xVsDNiE8DCgUimHZpbcWpFIp6uvrERUVZUuLHiGolE0HBwfweDykpaXh5s2bePrpp+8pgoE7IpXJZA6bECZJEtnZ2RAKhQgICKDnhUajwa+//or169eb7dxUSvTmzZvB5XKN/mYwGHDixAm4ublh0qRJtvk5wtTW1kIkEo2q7z8qqvvll1/i8ccfH1A9uVqtxg8//IC0tDS8+uqrRvXwQxnHiRMn4O3tjZiYmF57Yf/8888QCoVYtWrVsM9tgiAwefJkFBUVmVQDSx2DSpvetm0bXn31Veh0Orzzzjv47rvv6PZLpghtBoOBkJAQvPHGG5g1axa++OIL7Nq1C52dnfTxqLTqZ555Bj/88ANqamp6Nc9ycnLCH/7wB+zcuRNNTU2DGg+1YXDhwgWzChSqrdTWrVvx7LPP4tKlS/j3v/+NyspKo3vm6OgIoVCIuro6hIeHo7y83CjNm7oHTz75JB544AF8/vnn2LdvH5RKpdUJTIIgEBMTg4KCAhgMBkRHR+P27dsmpa1bC1RdcFZWFh3ZZ7FYmDNnDk6dOnXP1PfExERcvnwZJEnC29sbGo0GLS0tZhufl5cXlEqlrR+tFUMFP35fYkJ9d0mlUssMbIxgE8JmRqVSQa/Xj6qF4GC5cuUKxo8fb0s57YXhMsui2gCxWCxUV1fj0qVLePbZZ+9p4kO9drhdo7VaLY4cOdLDKTo7Oxt8Pt9sNYwGgwEHDx7ExIkT4e/v38Mluri4GLm5uVi3bt2ItYqycQfKQG/ChAmWHsqAoebMd999hyeeeOKegpb6HO7YsQNMJhMvvvhinz29BzuO6upq3LhxAxs3buwxd0mSxKlTp9DR0YENGzaAxWKNyCaPg4MDoqKihtRzF7izYKPagKxfvx5/+9vf4Ovri48//hhffPEFampqTIpIEQRBRz3ffPNN2Nvb4+2338bly5fp/q0EQcDb2xtbt27Fl19+2Ws0mmrf8+CDD+Kzzz4btPCfOHEibt++bfKGQX9QrZpefvllLF68GN9++y127twJiUQCkiTBYDAQERGB/Px8uLi4QKPR9BgHtXEQFxeHv/71r1CpVPjf//1flJaWWl2vXhcXFxgMBnR0dMDFxQU6nW7Up346OTkhNDQUN27cAPB/xmClpaWQyWR9vo4gCEydOhXZ2dlQqVTgcDiYMGECrl+/brZNDCaTibCwsFHt0D3WYTKZEIvFaG5u7vE3Z2fnIWXY2LAJYbMjk8nA5XJ7RKrGCmq1Gunp6ZgxY4Yt2jaCqNVqtLW1QSaTQafT4emnn4aTk9OA3wOlUgkOhzMs4pAkSeTk5EAoFMLf359+XKPR4MiRI1i9erVZzkulWVdXV/foq0qSJORyOfbs2YOHH354TG9EWSs6nQ7FxcW9RjOtEarN03//+1889dRTvdaa//75xcXFeO+995CUlIRNmzYNKBtjIGg0GuzatQsbNmzoUVZDkiTy8vJw9erVAZVBmBOCIDB79mxcvnzZbFE5qo54/vz5eOuttxAXF4dvvvkGH330EUpKSkw6D9WDeM2aNXjppZdw69YtvPvuu6ioqKB7r8fGxmLu3Ln4+uuvezXvIggCEydOxKRJk7Bz585+XX1/D5/PR1BQEHJzcwc99oHCYrEwfvx4/OUvf4Gnpyf++c9/4vTp01CpVIiJiUFeXh7dp7ivNG3q3m/ZsgUPPvggvv/+e+zbtw8KhWLYxj1Y2Gw2bQDGYrEQHByM27dvW3pYQ4IgCCxatAipqan0vHJwcEB0dDTS0tL6fa1IJIJYLEZJSQkAYPLkybh165ZZU5knTJiArKwsq9sUsXEHgiDg5ubWqxB2d3fv9XEbA8cmhM2MTCaDUCgcs9GooqIiiMVio/Y9NoYftVoNiUSC/Px8LFmyBG5uboMSG5QQHg6BotfrkZKSghUrVhhFgzMzM+Hi4tIjcmsqXV1d2Lt3Lx5++OEetZhU2mhSUhL8/PxGhRAba3R0dECv14+K7wbKVfzHH3/EM888c885ajAYcPnyZVo0z5w502z+CCRJ4tKlS3ByckJcXFyPcbS0tODHH3/Ek08+CYFAYJZzDgYPDw/weDxUVFSYPfXX3t4eM2bMwF//+lfMmjULP/30E95//30UFRWZHCEeN24cnnvuOSxbtgxff/019u7dS6ekJicnw8vLC7t37+71+AwGA8uWLQObzcahQ4cGJQzmzJmDy5cvD2utJXXPlixZgtdeew3l5eX43//9X8hkMnR0dEClUiEqKor2ZegLBoOByMhIvPHGG1Cr1XjnnXdQUlJiFVElgiAwfvx4ZGRkAADdRmm0izRvb284ODjQop4gCMydO9coe6Ev7jZkc3d3h52dHaqqqswyLoIgEBQUhIaGBiiVSrMc04b5cXNz69U5WiwWo7W11UKjGhuMTbVmQaRSKYRCoaWHMSwYDAacO3cO8+fPt/RQ7iuo3tRNTU1ITEyEl5fXoIWeUqkEl8sdFoGYm5sLe3t7BAUF0Y9RqdKrVq0yy6aQwWBASkoKJk6cCF9f3x7R4GvXrkGpVGL27Nk2EWwBqGh9eHi41RvoUSn7e/fuxUsvvQRvb+9+54xOp8OhQ4dw4cIFvPLKKwgMDDTrHOvo6MCJEyewYcOGHp8Vqp/wqlWr4OPjY5G5zWQykZycjLNnzw7L8SljrQkTJuCtt97CokWL8Msvv+Ddd9/F7du3TaohZjKZiI+Px5tvvgmdToe3334b+fn5YDAY2LBhA9rb23Hy5Mk+naQfffRRFBYWDjgFlSAIBAYGQiaT0e7AwwnloP3UU09h48aNOHjwILKyslBWVobw8HCUlZXdM7JORdEffvhhbNq0Cd999x3279/fZ0uqkcTPzw8tLS1QqVQIDAxEbW3tqO91SxAElixZglOnTtGbJV5eXuBwOP0arREEgYiICDQ2NkImk4HBYGD69Om4evWq2d4nyq27oaHBLMezYX48PT179S9wcHDo01XexsCwCWEz09LSMmadapuamiCXyxEaGmoTG31gyqKtP6iU388//xxsNhtsNtuk+aVUKoelplun0+Hw4cNYtWqVkQBKT0+Hm5ubWaKzJEmivLwcZWVlWLhwYY/jNTU14dixY3jkkUfAZrOHdC4bpkFFWMePH2/V3w1UmvHevXvxwgsvwMPDo8/xkiQJhUKBb7/9FrW1tfjjH/845NZIv4fKZFiwYAFcXV2Njk0Zv4lEIkydOtVi95UyMKqtrR1WUxaq3jchIQFvvvkmFi1ahJ9//hnvvfceSktLodfrB/XdSgm9zZs34/HHH8e+ffvw3XffQa1W46mnnsLly5d7dSSmXJu3b9+OgwcPDjgSzmKxMHHixCH3FB4oVN1vVFQU3nrrLaxevRqvv/46MjIyoFAoBhzdIwgCkZGRePPNN9HV1YV//etfvZqKjSQODg5wdXVFZWUlHBwcIBAIBtXGyxqhBG1HRwd9LVS/67Nnz/Yb8eZwOIiKiqLn6/jx41FcXGy2CC5VP27O1kw2zItYLKZ9Ae7GwcHBqkobRiM2IWxmmpqaxqQQptL3pk+fbvURn7GEUqnEV199hbCwMAgEAhgMBpPSI9Vq9bAI4YKCArqmi0KlUuHo0aNmiwar1Wr8/PPP2LhxY4/6SJVKhR9++AHr16+HSCQa8rlsmIZKpUJjYyMCAgIsPZQ+IUkShYWF2LNnD5555pl7iuCOjg589NFHEAqF2L59OxwcHMw+nry8PLS2tiI5OblHlkNpaSnS0tLw0EMPWfw7l8fjIT4+HtevXx+R81GC+I033sCCBQuwe/dufPzxx6ipqRl0iixBEAgODsYbb7wBFxcX/O///i+qq6uxfft2/PTTT6itre118e/u7o7HH38cX3755YAcdQmCwPTp05Genj7i0Us7OzssXbqUrqfNyMhAZmbmgO8VtWnwyCOPYOXKlfjss89w/PjxQdVJmxOCIDBhwgTcunULTCYTUVFRyM3NHfUijc1mIykpiW5JRvWBrq6uvqdp1syZM3Ht2jXo9XoIBAK4u7ujrKzMLOMiCAJxcXEoKCiwtVGyUrhcLjQaTY/PtL29PfR6vcU+q2MBmxA2M1SN8FhDoVAgPz8fiYmJVh3xGUtotVr897//RVBQECZMmACtVgsGg2GSWc5wCGGtVouUlBQ88MADRoI3LS0N48aNg5+f35DPQZIkjh8/jqCgIISEhPQQC2fPnoW7uzvi4+Nt89KCVFdXw93d3Wqd5Cmjqx9//BHbt2/vt7yAJEk0Nzfjgw8+wJQpU7B+/foh9wfuDYVCgV9++QVbtmzpYa7Y3d2N//73v3j44Yetoic9QRCYNWsWrl27ds96RnOek8PhICEhAa+//joSExPx1Vdf4euvv0ZDQ8Ogo8N2dnZYtWoVnnjiCezfvx8XLlzA6tWr8eWXX/YqQqgI3pIlS/DVV18NKOri6uoKHo+H2traQV2rOaDSbLds2YKnnnoK//jHP7Bv375BpU0ymUz6flN9tRsbGy0iQKOiolBSUgKtVouYmBiTejxbG5QLdF5eHv2+8Hg8xMXF3TOTwNPTEzqdjm6dNGPGDFy5csVstdMikQharXbUO3SPVajfiN9//9rZ2YHFYqGrq8sSwxoT2ISwGSFJEp2dnRYxNBlOqMiFv78/+Hy+pYdj1ZgrNVqv12P//v1gs9lYuXIlpFIp9Ho9WCyWSWJDpVKZ1W2WJEnaXCU8PJwWFUqlEsePH8fq1avNkhJdW1uLjIyMHtFlkiRRVVWFGzduYO3atTYRbEEoYzRr3YwgSRJlZWXYuXMntm/f3m+tLUmSqKmpwQcffICVK1ciOTl5WKKxJEnizJkzCA0NNaqtB+58h+zZsweTJ082S39ic+Hh4QFHR0ezRaEGCkEQ4HK5mDp1Kv76178iNDQUH374IXbt2gWpVDqo71sGg4HAwEC8/vrrsLOzw9GjR+Hp6Ylvv/0WGo2m1zTp2bNnw9fXF3v37r1ntIzJZCIxMRFXrlwZcdHGYrHg7u6OpqYmJCUlISEhARqNBn//+9+Rk5Mz4N8mqjfp9u3bkZSUhPfffx9XrlwZ8UihWCwGALS2tsLNzQ0ymaxXt+/RhkAgQHh4ONLS0uio8ECc2dlsNiZPnoyrV68CACIjI1FTU2O2+lAul4ugoKB7Gq3ZsAwcDgeOjo49PAgYDAYcHByGpXXb/YJNCJsRnU4HpVJpFTv45sRgMCA1NbVH+p6N3hnqPTIYDDhz5gzq6+vx8MMPg81mo6OjAxwOB/b29iYJWqVSaVYhrNfr6dpgSqCSJInr16/D19cXXl5eQz6HVqvF7t27sX79eqO0VJIkoVar8eOPP+Khhx4Cn8+3zUsLYjAYUFBQgOjoaKt7H0iSRF1dHb799lts376935p1Kmr8ySef4JFHHsHEiROHrd1YS0sLLl++jNWrV/f4W15eHmpra3u0CLMGkpOTkZqaahEHXyqqO2fOHPztb3+Dg4MD3n77bZw6dWpQBk8EQYDH42HDhg3YvHkzKisrce3aNezdu7fXYxAEgfXr16O+vv6eApcgCCQkJKCgoMAi5k7x8fHIycmBs7MzmEwmVq1ahSeffBIHDx7Et99+C7lcPmAxzGQyMW3aNPz5z3/GpUuX8NVXXw349eaAisgXFRXB3t4e7u7u/ZpKjRaouuDz58/Tmwvu7u7g8/koKyvr8/5S7b2ysrKg0+lgZ2cHf39/FBcXm+U9oY5/69atIR/Lhvmh+rD35hDt6OhoiwgPAZsQNiMKhQIkSZq9lsySUGmCGo3GYq6lo4mh/iCRJIm0tDTcunULf/jDH+h0GJlMBjs7O/D5fJN6VCsUCrMJYSrCptVqERERYRQNPnXqFFatWmWWaPC1a9cgEAgQGxvb43gpKSkIDQ01ikbbsAxtbW0gCMLqarRJkkRrayu+/vprbN68GQEBAX3OFYPBgIyMDHz//fd45plnEBkZOWzzymAwYP/+/ViyZAkEAoHReTo7O/Hzzz9j69atI9oveCBQplk1NTUWTZ+kzKxWr16NV199FdXV1fj73/+OjIwMaLXaQQliymhq6tSp+Oijj5CamtprVNjOzg5PPPEEjhw5gsrKyn7P4ezsDLFYjNLS0iFd52ChhGNpaSlYLBbGjRuHyspKBAUF4fXXX4e7uzveeecdpKenD7hXM0EQcHd3xyuvvAJvb2+88847KCwsHJGNEKpulaoNpnolj4Vopbe3N3g8Hj1HWCwW5s6di9OnT/f7OrFYDCcnJ5SVlYHBYGDatGlmdY/28/NDfX39qHfoHovcLYR//347OTkNq5HhWMcmhM2IQqEAj8cbcz2EU1NTMW3aNJsj7wAgSdLkHyWSJHH79m0cP34cTz75JOzt7em/SSQS2Nvbw8HBwaT51dnZaZKA7g2DwYDDhw9j+fLlYLFY9NivXbuGwMBAeHp6Dvkc7e3tOH36NDZu3NhDkJSUlKCgoAArV64cc5+10QYVwQwLC7Oq7weSJCGTyfDFF19g+fLl/UarDQYDrl69isOHD+PFF180W9/rvsZ1+/ZttLa2Yvr06Ubn0ev1OHjwICZNmgR/f/9hOf9QsbOzQ3R0NG7dumVxQUIQBNzc3LBt2zZs27YN586dw4cfftin+VVfx3B2dsYLL7yAt99+Gx988EGf1+bq6opHH30U33zzTb/RFwaDgRkzZuDixYsjfo9cXV2hVqvR1dWFqKgouq7Wzs4OK1aswHPPPYezZ8/is88+63VB3RccDgcrVqzAtm3b8PPPP+PXX38dkTZLAQEBaG5uhlKpRHh4ON2Dd7TDZDKxYMECnDhxgr6H0dHRqKurg0Qi6fN1DAYDM2fOpOdWUFAQmpubzZYeLRQKIRAIUFdXZ5bj2TAvXl5eqK+v7/G4h4cHmpqaLDCisYFtFWlGuru7jcTLWECtViM/Px8TJkywRd4GiCn3iYq879q1C1u3boWLiwt9HCqyRdWImIJcLjdLhIkkSVRWVqK7u9tIXKhUKpw5cwbLly8fsjjV6/U4cOAA5s2bB5FIZHQ/u7u7sXv3bmzevHnMfdZGK7du3cLEiROt6vtBoVDg888/R1JSEiZNmtRvOvSlS5dw9uzZe7ZTMgdarRY///wzNmzYYLQxRZIkioqKUFlZiWXLllnVvbwbgiCQlJSEq1evWo27LIPBQEBAAF5++WXMmDEDn376KX755ZdB1cyx2WwsWbIEb7/9Nt5++22cPHmyR9SUiiBPnDgRP/30U7/XHx0djcrKyhFva8JiseDl5YXq6mqEhoYaRaUJgoC3tzdeeeUVREVF4d1338XVq1cHFR0ODg7Ga6+9BolEgh07dqC5uXlYxTCXy4VIJEJTUxM8PDygVCrR0dExbOcbSWJjY9HU1ESnutrb2yMhIYGuAe4Lam5R683g4GCzOWpT7bjy8/OHfCwb5sfNzY02S7sbkUjU7waKjf6xCWEzIpVK4eTkZOlhmJWcnBz4+PiMuesaLkz9Meru7saXX36JNWvW9EjhNBgMaGtrA4PBMMmIzWAwoLu722yOvikpKVi8eDEdAaRqg/39/eHh4TGkY1OCQCKRYMaMGT3uQ0pKCqKiohAcHDyk89gwDwqFAq2trfD19bX0UGg0Gg2+/vprxMTEYPbs2X1uzJAkifPnz+PChQt4/vnnjTafhgOSJHHx4kV4eHgYpfSTJAmlUondu3fj4YcfNlvmxnDh6ekJgiBQX19v8agwBUEQYLPZtKEWAPz9739HWlragPsPU/W9L7/8Mv7yl7/g66+/hlKpNHotQRBYsWIF2tracP369T6P6+joCA8PD5SUlJjnAgdBdHQ08vPz4e7uDoVCYZTGTjlxz5s3Dy+//DIuXbqETz/9tNf+pL1BtVl67LHHkJycjHfffRdpaWlmM4n8PQwGAzExMcjOzjYS+WMBLpeLSZMm0XXnBEEgOTkZ165d67cVDp/PR2BgIPLy8kAQBJ0ebS5iYmLGRKuqsYiDg0Ov0X+BQGBz+x4CNiFsRhobGzFu3DhLD8NsUCZZc+bMsdoIhbVhSmq0Wq3GN998g+nTp/fqvKvT6SCVSsFgMODm5jboMWk0Gmg0GrNEhOvr69HS0oKEhAR6nBqNBqdOncKyZcuGHA1Wq9XYu3cvNm7caJRqS/VVvX37NlasWGGbj1ZCZWUl3N3drcYXQafTYe/evXB1dcXSpUv7nI8GgwGnTp3C5cuX8dJLL8HZ2XnY55RMJsOJEyewfv36HuM6duwYIiIiEBgYaPVzm8Vi0am/1gYl1DZu3Ijnn38eZ86cwccff4y2trYBC72ZM2fipZdewoEDB/Duu++io6PD6LVsNhtPPvkkfvvttz4jotRxzFm/ORAIgkB4eDhKS0vBZDLh5ubWayolQRDw8PCgo8PvvPMOrl27Bp1ON6DxUkZaf/rTn3Dq1Cn897//7bFpYK7riY2NRWFhIfR6PRISEpCdnT0mRBrVkiw9PZ12w/bw8IBQKOw3BZzKyrh8+TIMBgP8/f3R0dHRbx/iweDj4wOpVGpzIbZCHBwcoFare9RwOzo6orOzc0x8LiyBTQibEYlE0iOVczTT2NiI7u7uHu09bPTPYNqt6HQ67Nu3D2KxGHPnzu114a7T6ehG6lRLicFACeGhRoRJksTRo0cxf/58I1GdlpYGb2/vITtFkySJU6dOISQkpEedpkqlwp49e7Bp0yarMxG6n8nIyLCatGiDwYDTp0+jvb0d69ev7/NzqNfrcerUKWRkZOCll16CUCgc9vGTJIkjR45g+vTpcHV1NfpbfX090tPTR03NO0EQiI+PR2FhYb+RK0tCEAR8fHzwpz/9CbGxsfj3v/+Ns2fPDqgHMoPBwNq1a7F06VLI5XL861//MjLIIggCrq6uWLlyJXbt2tVnanFUVBSqq6tH3M3VyckJarUaCoUCUVFRKCgo6PV5VBR9/vz5+OMf/4hLly7hyy+/HHBLKoIg4OnpiT/96U/g8Xj497//jbq6OrMvxl1cXKBUKqFQKBAaGoqKiooBp3NbO2KxGC4uLiguLqYfmz9/Ps6fP9+vIVlwcDA6OjogkUhgZ2eHsLAwZGVlmWVMXC4Xbm5uFumFbaN/7O3tweFwemx6CAQCqFSqEevxPtaw/l/dUURHRwecnZ0tPQyzQJIkrly5gunTpw9LH82xymDcNA0GA86ePQuJRIKNGzf2eZ91Oh0MBgMYDIZJNcIajQZ6vX7IQrilpQXl5eWYNm0a/Zharcbx48exYsWKIS/im5qacOPGjV57Bh87dgzh4eEICgqyCtFl4069a0lJCSIjIy09FJAkifT0dGRlZeHxxx8Hh8Pp9XkGgwHnzp1DVlYWnn/++RFrdVdfX4+8vDwsWrTIaP7qdDrs2rULq1evHlX954VCIcaNG4fCwkKrjkJwOBzMnTsXr776KoqKirBjx44BpXRzuVxs27YNXC4XcXFx+PLLL5GZmWkkhqdOnQoWi4XLly/3ejx7e3t4e3uPeN9lLpcLb29vVFRU0HXC92r55OnpiZdffhnBwcH45z//iczMzAHXgFOtqFatWoWPPvoIly9fNmv9OJfLha+vL0pKSuDi4gKSJMdMnTBBEJg/fz7OnTsHvV5PO7M3NDT0W/PJYrEQHR2N7OxsEASB6dOn4/r162Zz86Yi7zasCwaDAaFQ2MMh2t7eHiRJjok+25bAJoTNhMFggEwmGzNCWKlUIjc3F4mJiTbhMQyQJInMzEzcvHkT//M//9Ov465Op4NarQaDwQCfzx/0ubRaLdhsNu3wbOp4z507h6SkJKOIbEZGBtzd3YdcI6rX67F3714sX77cSJyQJImqqipkZ2ebJfXahvlobW2lo2OWhEqbT0lJwRNPPAEHB4dev7NIkkRqairS0tLw9NNPj1j/acr8bfny5UYGb1RtPZPJxOTJk0fV9yyDwUBSUhJSU1MtPZR7QrUdefrppzFnzhx8+OGHOHPmzD1bxAgEAjzzzDO4desWVq9ejV9//dUoUsdisbB582YcO3asTwfmxMRE3LhxY8TToyMjI5Gfnw9vb29IpdJ7RqWp2uFFixbh2WefRUpKCnbu3Dng9FgGg4GEhAS8+uqruHz5Mnbu3Gm2SDjVRik7O5s2RisvLzfLsS0N1fKqra0NbW1tAO5s3iQkJCA9Pb3feTN9+nSkpaVBp9PB398fXV1d9DGGOqbIyEiUlJSMmcj7WMLJyanHRhBBEOByuTYhbCK2VaWZ0Gg0UCgUY8JUiiRJFBYWwsvLa1RFKawBkiTvKThJkkRNTQ1+/fVXPPHEE/dckOt0OshkMrDZbJNqMdVqNVgs1pCEsFwuR2ZmJmbNmmV03OPHj+OBBx4w+bjAnfuRn58PhULRQxBotVrs2rULGzZssJo6VBv/955FRUVZVMBRjurff/89nnjiCYjF4j5F8OXLl5Gamopnn322R//e4Rzf7du30dHRgSlTphidUyaT4dChQ9iyZcuozLoJCwtDS0vLqOhfSRAEmEwmpkyZgtdeew35+fnYsWNHvy2ECILAuHHj8Mgjj+DQoUPYtm0brl27ht9++42O3onFYixfvhy7du3qEY2jBEVVVRWUSuVIXCZNWFgYSkpKwGKxIBQKaWfie0GllL/++utwdnbGP/7xDxQVFQ3I+4K6H6+88gqEQiH+9a9/DaqVVX8EBwejoqICBoMBsbGxY6afMHBH+CYmJuLSpUu0aRblzN7XZg1BEPDy8oJKpUJbWxtYLBaioqKQk5NjljG5u7tDpVKZre7Yhvnw9PREQ0NDj8ft7OxG/HtmrGATwmZCo9HQu6qjHYPBgEuXLiE5OXlURSmsgYGkJslkMvznP//BI488Ajc3t3veY6VSie7ubjg4OJgkBrVaLZhMpsmLbapHcHR0NBwdHUEQBEiSRHZ2NkQiEXx9fYc0T1QqFX799Vc8+OCDRmMkSRJnzpyBl5eXxQWXDWOo93/8+PEWfV8UCgW+/vprrFmzps/+v1Tk9cyZM3jhhRfg5OQ0YmOmzLvWrVtn9NtgMBhw6NAhzJgxY8hO65aCx+MhMjISt27dsvRQBgxBEHBxccHzzz+PadOm4V//+hfS09P7TOWlopFJSUk4ePAgnn32WVRXV2P37t30b/706dOhUql67T9sb28PsVg84k7HIpEIarUa3d3diIiIQFFR0YBfS0WX1qxZg8cffxw//vgjDhw4MKD6Q2oNtHbtWqxduxYfffQRrl27NuSUXWdnZ3A4HLS0tCA0NBTV1dVWW58+WKg5dPPmTfoeu7u7g8fjoaqqqk/Bz2KxMGHCBKSnpwO4k31w8+ZNs6SlM5lM+Pn5oaKiYsjHsmFexo0bh8bGxh6PCwQCm8GZidiEsJlQq9Vgs9ljYrHe0dGBjo4OBAYGWnooow6SJPtN31WpVPj2228xf/58hIaGDmi+SKVS6HQ68Pl8k1qrUAsGUyPCarUaFy9exPz5842coo8dO4aVK1cOac5TLWX8/f3h5+dndKzGxkZcuXIF69ats6VEWxldXV1obW2Fv7+/xcag1Wrx008/IS4uDuPHj+/1OSRJIisrC8ePH8fzzz8/oqUrJEkiLS0NQqEQ4eHhRo9XV1ejuLgYCxcuHNW/GTNnzsT169dHXQolk8lEUlISXn75ZZw6dQo//vgjuru7+3SAXrBgAezs7HDu3Dls374d3d3d+PHHH6FSqcBms7FlyxYcOHCgx0KUwWBg0qRJ90xzNTd2dnYYN24cKioqEB4ejtu3bw9ajBIEgZCQELz++uuQyWR49913B9wyi8FgID4+Hq+88grOnz+Pn376aUg9lVksFkJDQ1FYWAgHBwewWKwx1S7GxcUFnp6eyM/PB0mSYDKZmDVrFs6fP9/nawiCwJQpU3Dr1i3odDr4+vqiq6vLbP1kY2Ji6PHYsB6cnJx6zcJxd3dHc3PzyA9oDGBbXZoJlUoFOzu7Ub2oAe4s0m7cuIEJEyaMiej2SEKlj/UlOPV6Pfbt2wcvLy/MnDlzwHNFLpfDzs7O5NRglUoFvV5vUkSYSoH18PCgI1fUY46Ojn1G4QZKR0cHUlNTezjmarVa/PLLL1i5cuWIGRrZGDgVFRXw8vKy2HeEwWDAyZMnAQCLFy/udaOEJEmUlJTgwIEDePrpp4e9T/DvUSqVOHz4MNatW2f0nUDVw69du9Zsvb0tha+vLzQaDZqamiw9lEFDpT6/8sorsLe3x7/+9S/U1NT0uvBns9l4+OGHkZWVhaKiIjz22GNgMpnYuXMnlEolfHx8MHHiRBw9etRIcFLmR0VFRfesSTb3tcXExCAvLw9+fn5oaWkxKYJKEAQcHR2xdetWLFq0CB9++CEuXLgwoI2Pu1s0EQSBHTt2oKmpyWRhFR8fj+zsbDCZTAQFBfXbYmi0wWAwMG/ePJw5c4ZOj46Li0N5eXm/tdZisRhsNhuNjY1gsViIjIxEbm7ukMdDteEqLy8f0Xlr4944OTlBLpf32NgSiURm2wS537AJYTPR2to64gut4UCv1yM9Pd1mkmUiWq22z0V5amoqJBIJ1qxZM6h7K5VK4ejoaPKimdo5NyUibDAYcOLECSxatIgW0nq9HikpKVi5cuWQahtJksTBgweRnJxsFKkjSRI3b94EQRBW05rHxv9BGb1NmDDBIu8NFeXNzc3F5s2be53XJEmirq4O33//PbZt2wYPD48RHStJkjh79iwiIiLg7e1t9HhGRga90B3tc5vBYGDy5MlIS0sblZEjgiDA4/Gwbt06rF27Fh9//DGdyvv76+Hz+di2bRt27doFuVyOzZs3w8nJCd9++y00Gg2WLl2KnJwcNDQ0GL1WKBSCz+f32s93OAkODkZZWRm4XC7s7OyGVMvNZDIxadIkvPrqq8jIyMCXX34JuVw+oPecy+XioYcewvz58/H++++b3AfYx8eHFvRUW6jROOf6IjQ0FFKplI7qOTo6IiwsDBkZGf2mR0+ePBlXr14FYN70aIFAAL1ej+7u7iEfy4b5EAgE0Gq1RhkWBEHAycnJVtNtIjYhbCba29vh4uJi6WEMCZIkUVlZCT6fb3En2NEK5dB8NyRJori4GBcvXsTWrVsHnUIvk8mGFBFub28HSZL9OlP3RU1NDTQaDZ0mTxmpcblcBAYGDmkhX1FRgZqaGsyaNYs+DkmSkMvlSElJ6VEzbMM60Gq1KC0ttVjddlNTEw4ePIjHHnsM9vb2PcZAkiTa2trw+eefY8uWLUPOWjAFqVSK1NRUrFq1yujcSqUSBw8exMaNG4dkXmctUOmZ2dnZo7qHJYPBQFxcHF599VWcPXsWP/30E9RqtZEAIQgCvr6+WLFiBb755huQJIn169fD2dkZ3377LVgsFlasWIF9+/YZRWuYTCbGjx8/4unRHh4etL9ESEgIiouLh3R+qr76xRdfhJ+fH/7xj3+gpKRkQCZaTCYTiYmJeP7557Fv3z4cPnx40JFGPp8PR0dHNDQ0ICAgALW1taMuJb8/OBwOpk2bhgsXLtBR4dmzZyM1NbVfQ7eEhATk5uZCp9PBx8cHcrncLGnjHA4H/v7+A3qPbYwcbDYbXC63xwaFUCiETCazvVcmYBPCZkIikUAkEo36Hf4LFy5gxowZNgFiIlqt1miBS5IkWlpasGvXLjz++OMmudVKJBIYDAaTNyc6OzvB5XIHLYRJksSpU6cwZ84cOgWWJEmkpKRg2bJlQ1rIU6nP69evN2rHREWJk5KS4O7uPuo/T2ORlpYWcLlci6Ssd3d349tvv8XGjRv7nB9yuRyffvopVq9ejcjIyBGfQ1Tf6+nTp/fIdDh27BhiY2OHbDBnTbi4uMDOzq5XJ9PRBEEQcHNzw5/+9CcYDAZ8+OGH6Ojo6CGGk5KSIBAIcPLkSTCZTGzcuBGOjo7YuXMnYmNjoVAojPorEwSB+Ph45Obmmq3P60DgcDhwc3NDXV0dIiIiUFxcPORjEgQBNpuN5cuXY9u2bdi5cydSUlJ6bBr09VpfX1+8/vrrqKmpweeffz7gqDL1+qioKBQWFoLP54PJZI6pCBhlmpWVlUW7//r7+0Ov16O2trbP17m4uEAgEKCyshIcDgcRERHIyckZsiCi7ndBQcGQjmPD/PD5/B4p805OTujs7DRrD+/7BZsQNgNUg/fR3kO4u7sblZWViImJsfRQRi2/T43u7u7GN998gzVr1sDHx2fQi1+SJCGVSqHX6yEWi00aU1dXF4RC4aCFq1QqRVlZGSZNmkQ/VlZWBq1Wi4iICJPGAvyfiRCfz0dUVJTR30pLS1FTU4M5c+aMGaEwlqDSkmNiYkY8oqnT6fDLL78gLi4O0dHRvc4PhUKB//znP5g9ezYmTZpksYh1Tk5ODyOspqYm3LhxAytWrBhTc5vBYCAxMRFXr14dE9EIHo+HLVu2YPLkyXjvvfd6OPcyGAxs2bIFV65cQUVFBZhMJh588EHweDzs27cPq1atwoEDB4yilW5ubmAwGCNeSx0dHY38/Hz4+/ubNYJKGWm98cYbqK+vx0cffYS2trYBvf98Ph/bt29HcHAw3n33XVRXVw943lDCjM1mIyAgALdv3x4Tc45CJBLB29sbeXl5AO6kPs+cOZOOEvcGg8HA1KlTce3aNRAEgcTERLOVKoSGhqK8vNwmrqwMsViM9vZ2o8ccHR2hVCptNd0mYBPCZsBgMKCjo2PUp0ZnZ2cjODgYfD7f0kMZtajVatrZWafTYdeuXUhISEBCQoJJi1+DwUCnu5ja+7SzsxOOjo6DjghfuXIFCQkJdEq2wWBASkoKli5dalKaNUVXVxeOHTuGDRs2GF2PWq3Gnj17sHHjRqMosQ3rgaoPHum2SZS7uFKpxJIlS3qtw9dqtdizZw98fX2N0u1HEqot0qJFi4xKGfR6PQ4ePIglS5aMud7sVHpmQUHBqE6Pvhsmk4k5c+Zgy5Yt+Oyzz3Dz5k06mksQBAQCATZv3owffvgBSqUSbDYbDz30EDQaDXJyciAUCo1SoVksFqKjo83W53WghIaGorS0lC4h6M94abBQ9+GJJ55AYmIi3n33XWRnZ98z6k1FlZcsWYINGzbg888/x40bNwYULff19YVEIkFXVxftajzWmD9/Ps6fP0+LzylTpqCgoKDfWt3Y2FgUFxdDrVbD29sbUqnULOnRQqGQLleyYT14eXn18BxgMplgMBhjqlxgpLAJYTOg1+vR2dkJJycnSw/FZKjewbNnzx5T0YqRhmqnYTAYcPr0aRAEgUWLFpnc/sdgMEChUIDJZJq0gCZJEjKZDI6OjoMag0qlwtWrVzF37lx6PtTW1qKtrQ0JCQmDHsfd4zlz5gzi4uKMUltJksT58+fh5eWFsLAwk49vY3jp7OyEQqEY0d63JEmivLwcly5dwpYtW3ot26DSjtVqNR544AGLlHZQbZFqa2sxffp0o7ldXl6OxsbGQbnFjyaEQiFcXFxQXl4+ZiJ0BEEgMjISr7zyClJSUnDq1Cno9Xq6fjM6OhpBQUE4duwY7cGwdetWNDU1wc7ODikpKVCpVPTxxo8fj6ysrBG9P97e3pDL5bRAGo73h8ViISkpCc899xz279+P/fv3Q6PR3PM8DAYDMTEx+OMf/4gTJ04M6HVcLhcikQjNzc3w9fXt0+V7tEJF2uVyOVpaWgDc+Wz5+Pj028rI2dkZzs7OqKyshJ2dHcLCwsySHs3hcODr62urE7YiqFr9trY2o8cZDAaYTKYtImwCNiFsBqgfx9FsftLY2AiVSmXRvqBjAbVaDSaTicLCQty8eRNbtmwZ0rwgSZIW16bUZN4thAezAL99+zacnZ3h7u4O4I4gP3XqFBYuXGjy9ZAkCYlEgrS0NCxevNjob21tbUhNTcW6devGpFAYKxQXF8Pf33/EIvYkSaKrqwu7du3CI4880mtWBEmSuHr1KgoKCvDoo49a7HvYYDBg3759WLlypVG/b51Oh3379mH9+vVDyqSwZhgMBqZNm4YrV65YeihmhSAIuLu7409/+hNycnKwb98+6HQ6ul/86tWrcfPmTdTU1AC4I9SefPJJtLe3o66uDpcuXaIFhK+vL2Qy2YjWtbLZbDg7O6O1tRXh4eFmqRPuDYIg4OPjg7/85S+QyWR4//33B5QqTdVlv/baa5BIJPjkk0/uWTdMtYWiPFl+nyI62mGxWEhMTMSVK1fo+zBv3jxcuHCh36j5tGnTcO3aNQB33KNv3Lgx5LHc3YbLhvXg4uICiUTSw7+Aw+EYbb7ZGBg2IWwGRrsQJkkS169fR2JiosmRSxt30Gg0kMlk+OWXX2hX26FApUbb29tDKBQO+vVqtRpyuXxQ6e56vR7nzp3D/Pnz6cckEglKS0sxZcoUk4UqSZI4fPgw5syZYyRoqLTRRYsWmXSNNkYGqrZ7JFtaGQwG/PLLL5g+fToCAgJ6FcHFxcU4ceIEnnrqqV5dpEcCahwqlcqoDIJKJedwOBZz2R4JCIJAREQEysvLx0x6NAWVAvzcc89BKpXi22+/pXvy8vl8bNy4Ed9//z20Wi0IggCfz8cf/vAH8Pl8/PDDD3RKK4fDgY+PDyoqKkZ0/JGRkSgoKEBwcDDKy8uH7TwEQcDe3h6PPfYYZs6ciffeew85OTkDSpXm8XjYtm0bIiMj8d577/UZ6aUMnIqLi0EQBPz8/Eb8fg43lGnWrVu3oFarQRAEgoODjaLEvb0mLi4OpaWlUCqVdAp5Z2fnkMcTEBCAqqqqIR/HhvkQiUSQy+VGadAMBgPOzs62XsImYFM9ZkCpVILD4Yxap2W1Wo3s7Gxb72AzoFQqce7cOaxcuRJeXl5Dvp8GgwESiQQODg4mtU9SqVRQKpWDEuTt7e1obm6mHXdJksSFCxcwZcoUk3sZU31dKyoqjNJDSZJESUkJWltbMW3aNNv8s2LUajVqa2sREhIyIucjSRKXL1+GWq1GcnJyr3ODcmR/8sknLerRoNfrsX//fqxevZp2WAfufP5+++03rFu3btRulA4UJycnuLu7o6SkxNJDGRYokScQCPDFF1+gu7ubdoR2dXXF+fPnafHm4uKCN954AxKJxKj9zaRJk/rtC2tuqA0KKsOnu7ubdiQeLphMJmbOnIlnnnkGBw4cwG+//TagzREWi4VFixZh/fr1+Oyzz5CZmdmriHZ3d4dcLodCoUBsbOyI112PBM7OzhCLxbQZGJvNvqchHZ/Ph4uLC6qqqsDj8RAQEICioqIhj0UsFkOn06Gjo2PIx7JhHhwdHaHVaukNOQqRSDTmMiRGApsQNgPt7e1wcnIatUK4qqoKTk5Oo7rG2RowGAyoq6tDcnIyJkyYYBZRRxmx8fl8k6L1KpWKTpkZCFSa6eTJk+n0ToVCgfT09CHVj5Mkif3792P58uVGYlqr1WL//v1Yu3btgMdowzLU1NRAIBCMWNS+trYW586dw+bNm3tNKe7u7sZ//vMf2pHdkmRnZ4PL5SIyMpJ+jKp7Dw4Ohp+fnwVHNzIQBIFp06bh6tWrlh7KsMHhcLBx40b4+fnhs88+g1wuB4PBwMaNG3HmzBmjuj0fHx/8+9//xu7du9HW1gaCIBAeHo7KysoeC9jhxNvbG+3t7XRtYX+teMwF1Srp1VdfRXNzMz7++OMBRaoYDAZiY2Px4osv4uDBgzh+/HgP85+720IFBASgpqZmzLkaMxgMzJkzB+fOnaNr0qdNm4aMjIw+NxUIgqDdo4H/S48e6qYLm82Gp6cnnf5vw/JQhnN3f48QBAEnJydIpVLLDWyUYhPCZkAikYza1klU1GWsmriMFCRJ4sqVK0hPT0dISIjZUszVajU0Gg14PJ5J7w+1+z/QSK5Go0FaWho9H0iSxM2bNxESEgKRSDTo8wN37k1hYSEUCoWR2zB1z1xdXREaGmqbf1YMleI7YcKEETmfQqHAjz/+iIceeqhX4a3T6bB7927Exsaa7MhuLtRqNR31vXszVC6X49y5c1i1atV9U3ISGRmJiooKKBQKSw9l2GAwGHjggQcQFRWFjz/+GDKZDCKRCAsXLsSBAwdoUUYQBGJjY5GYmIj33nsParUaAoEAPB4Pzc3NIzZequd3e3s7QkJCRixiT6WJP/nkk4iLi8O//vWvAbU7IggCnp6eeO2111BcXIydO3dCqVQa9WWOiopCXl4exGIxSJIcc1EwatOkqakJUqkUJElCJBJBJBKhrKysz7TxmJgYlJWVQalUIjQ0FPX19f26TQ90LGPVoXu0wmAwwOVye2R3UELYZmw2OO6PX+dhhuohPBoX8gqFApWVlWO6fm24oVxhz549i+joaLNGNru6usDhcMDhcEx6f6RSKZhM5oCi/SRJ4vbt23BxcaHTTPV6Pc6ePYuFCxeavJjXarU4ePBgD7MguVyOkydPYs2aNaM2m+J+Qa/Xo7CwEHFxccP+PUG16YqOjkZ4eHivdcGUg+/ixYstKjKpjSKxWIzAwECjx48cOYJp06aN+rZ6g8HR0REeHh4oLS219FCGDYIgwGAwsGTJEiQmJuKTTz5BZ2cnZs2ahaamJpSWltILUQaDgfXr1yMtLQ27d+8GcKfVTXZ29ogtVhkMBkJDQ1FcXIyIiAgUFxeP6EKZyWRi/vz5eOKJJ7Bz506cPn36nhFcgiDg6OiI5557Dnw+Hx988AFtDnR3nTBJkvD29h6T0Uoej4f4+Hg6wstkMjF79mycP3++z9fw+Xy4u7ujoqICPB4Pnp6eZqmhpurLB9LiysbwQxAEXF1de9SMi0QiW0TYBGxCeIhQTrimRsssCUmSyM/PR0BAgEn1pzbuIJPJsGvXLtqx1pzOsF1dXbC3tx+06zNFQ0MD3XJiIJw/fx6zZ88Gk8mkhTGPx4OXl9egzw38n1BwdnY2qi2ljLNmzJgBV1dXk45tY+Rob2+HVqsd9rZJVPZATU0NFi1a1KsIzs3NRWZmZp8p0yOJUqnEsWPHsGbNGqOxNjU1ITs7u9drGOtMnz6931rGsQKDwcDcuXMxefJkfPLJJ1Cr1Vi3bh327dtn1MLE3d0da9aswZEjR5CamoqEhATk5eWNWDovFV0sLi6Gp6cnWltbR9zQjDJ8+vOf/4y8vDz85z//GVBPYw6Hgw0bNmDq1Kl4//33UVlZSUdHlUollEoloqOjx2S0kiAIJCUl4dq1a/RciYyMRE1NTZ99fRkMhpFjdGJiItLS0ob8WfT09ERXV5dZzLdsmAc3N7cemSUikQgdHR22DYtBYhPCZqC1tRVubm6WHsagodKiZ8yYcd8t1syFVqvFrl27kJycjMDAQCiVSrMuzjs7O8FgMCAWi016j1pbW+nUuHshlUrR0NBgVOd48uRJLFiwwGSjH4VCgWPHjmHt2rVG46+qqsLt27cxf/5829wbBRQWFiIsLGxYo68kSUIul+PAgQN46KGHjFoQUTQ3N2Pv3r14/PHHTWonZk6oenp/f394e3vT89hgMOC3337DokWL7rsNRipaV11dPeSUzNEAg8HA/PnzMXHiRHz66afw8vKCk5OTkfhgMBhYuXIlvL29cfToUXR2dqKrq2tE74+vry8aGxthb28POzs7tLa2jti5KQiCgEgkwnPPPQcXFxe89957qK+vv6dIYzKZSE5OxsMPP4wvvvgCaWlp4HA48PT0RGVlJYKDg1FVVdWjlngsMG7cOPB4PJSVlQEAHBwcEBkZifT09D7vW0REBMrKyqDRaBAVFYWKioohG6Sx2Wy4uLiMaEq/jb4hCAJisbhHL2EejweNRjPmauaHG5sQHiLU4k0gEFh6KINGKpWio6MDAQEBlh7KqIQkSZw5cwZ2dnaYMWMGAJhdCMtkMmi1WpNq0KnaKR6PN6Aa4bS0NERHR9MO0y0tLWhubkZMTMygz02d//LlywgNDYWHhwctFCiDrDVr1oxYP1obpmMwGJCZmYmJEycO+3l++eUXJCUl9eq4rlQq8f3332PNmjXDHpkeCAqFAqdPn8aKFSuM6t6rq6tRW1t73/ouODg4wM3N7b5pucJgMLBgwQLEx8fj22+/xZIlS3D06FGjfp4+Pj7w9fXF1KlTsWvXLggEgmFtZfR77O3twWKxIJPJ4O/vb9H3hsPhYM2aNVi+fDk++OADZGZmDqhuOCIiAq+88gqOHTuGlJQUhISEoLCwEGKxGCqVakAR5tEGg8FAcnIy7UhOEARmzZqFy5cv9xn1EwgEEIvFqKioAJ/Ph5OTE+rr64c8lqioKBQUFIz5TI/RgqurK9rb243eDyaTCYPBYIsIDxKbEB4iJElCq9X2Gr2wZkiSRHp6OmJjY0fd2K0BKm04PT0dDz74IFgsFkiShFqtNuv9lMlkUKvVEAqFg15UUy0PBALBPdsn6XQ6XLlyBbNmzaJNss6fP4/p06ebfD3d3d24cOECli1bZiQUsrKywGQyR6Te1MbQUSgUaGpqQmBg4LC9X9T3kVqtRlJSUo/z6PV6HDhwACEhIUaGa5aCaikWFRUFd3d3o57Y+/fvxwMPPHBfu6Cby7F2tMBgMLB48WL4+fnhxIkTCA4OxtmzZ+nrZzKZWLRoESorKzFz5kzk5uYiKytrxO4Pm82Gn58fysrKEBERgaKiIou+NwwGAxMnTsSLL76IX3/9FYcPH75nRJcgCLi5ueHPf/4zampqcOXKFeTn54PJZMLNzQ1NTU0jNPqRJSEhARUVFZDJZAAAPz8/GAyGPt2/GQwGJk+ejOvXr4MgCEycOHHI6dEEQSAsLMyo/t2GZXF1dYVEIjGK/lLrUJsQHhw2ITxEKCE82hY9BoMBaWlpmDp1qsUXlaMRqVSKn376CVu3bgWfzwdwJ9Kp1WrNFuUkSRIKhQIqlcqkjAOVSgWdTgeCIO4ZEa6pqQGDwaDb0HR3dyMzM7NXUTLQsZ89exYJCQlwcXGhj6FUKnH48GFs2LDBZpA1SqipqYGnp+ewRu/b29tx/PhxbN68uUcaPkmSSEtLQ2trK5YvX24V31fUJs+SJUvodHGSJFFcXAyVSmVxJ2tLQhAEoqOjUV5ebhQVHeswGAysXr0ajo6OkMlkOH/+PC1egDspq11dXYiKikJ8fDwuXrw4onXCkZGRKCwsREBAAGpray2ePkkQBLy9vfHqq6+ipqYGX375JTo7O/sVWpQT9fbt2xEREYG0tDS0tbUhIiIChYWFY1Kk2dvbIyIiArdu3QJJknSf5osXL/Z5vVFRUSgpKYFOp0N8fDyKioqM6tZNwcfHB21tbcPeh9rGwKDSoO/eQGIymeBwOPfV9645sAnhIaJWqwfVp9VaqK+vB0EQJpsg3c9oNBr88MMPWLBgAXx9fenHdTod9Hq9yfW0vUHVkZkihNVqNRgMBnQ6Xb8RYaqN0d214rm5ufD19TW5t7RcLsf169exYMECo2jwhQsXEBYWhnHjxpl0XBsjC0mSyMjIGFZhp9PpsHfvXixZsqRHCQBJkqivr8fJkyfxyCOPWEX2ClUSkZCQYGT0ptPp6JR/c34HjEb4fD6cnZ1HpGetNcFisfDggw/Czs4Ozc3NOHnypFFUODk5Gampqdi2bRvUavWIRtiolGiRSASVSmU1xkeOjo7Yvn07vL298d5776GhoeGe94TD4eDBBx9EfHw83njjDfD5fJSUlIzZSNicOXNw+fJlWvRMmTIF+fn5fbYpc3Z2hlAoRGVlJYRCIezs7Ho4DA8WDocDHo9ntLljw3JQvzF3b2gxmUzw+Xybc/QgsQnhISKTyWBvb29x99LBcu3aNSQmJtqicoPEYDDg5MmTcHJywvTp043EgU6no3dszYVcLgefz++1l+q9aGtrA5/Ph8Fg6FcIK5VK5OfnY9KkSSAIAjqdDhcuXMD8+fNNGjNJkjh+/DgSExONhI1MJsOlS5ewbNmy+6av6mhHp9OhqKho2NqrUa7iTCaTnn93o1Kp8MMPP2D9+vVW48wvk8lw5coVLFmyxGiT59atW3B0dERYWNh9Gw2mYDAYmDRpklkca0cbXC4XW7duhb+/P3788UdIJBIAd6KZU6ZMQWlpKZhMJmbMmIF///vfI9ZzWSQSQaPRQKFQQCwWD1kYmRM2m42VK1di1apV+OijjwaUNs5kMjFr1iyMGzcOe/fuRUFBAdRq9QiNeOQgCAI+Pj70piAACIVCeHl5oaioqNfXMBgMTJkyBWlpaWAymYiJiRlQLXZ/MBgMBAUFjenWaKMJFosFDodj9P1BEAQEAoFNCA8S22p0iMhkMggEglG18FGpVMjLyxt285uxBtXaJScnB+vXr+8h5rRaLQiCMJsQvtuIzRQhXFdXB5FIRH9h9nWO0tJSuLm50edoamqCQqFAUFCQSfO6vb0dWVlZmDdvnpFQoNolmWL8ZcMytLa2gs1mD8t7RpIkOjo6cOrUKaxbt67H58ZgMODgwYOIiIiwmj7nVA/jSZMmGd0TjUaDQ4cOYfXq1fd9NBi4syCLjY1FYWHhmHTzvRcODg545ZVXIBAIcOjQIVqA8Hg8REZG4tatW5gxYwYaGhqwe/fuEUlT5nK5cHd3R21tLcLDwy1eJ/x7GAwGxo8fj+eeew4HDhzAiRMn7nlfwsPDweVy8fLLL9MbVNZ0Teait3ToOXPmIDU1tc97RH3+tFotxo8fP+Te1VSdcElJyZi8x6MNJpMJkUhk5ABPCeG+2mvZ6B2bEB4io1EIV1dXQygU2gTJIKD6Re/Zswdbt24Fj8fr8Z5rtVowmUyzCmGJRAJHR8dBZxyQJImmpiY4OTn1W9tJkiQuXryI2bNn0yZZFy5cwMyZM01a0JMkiaNHjyI5OZmunQbu9DMuKirC3LlzR9Vn5X6GJElkZ2cjKipqWMSdwWDA3r17sWDBAohEIqN5QZmqNTQ0GJmtWRqJRIL09HQsXrzYaJPn2rVr8PLygr+/v2UHaEUIhUI4ODgMqEXOWMTJyQnvvvsuTp48Sfe/BYDk5GRcuXIF48aNQ3R0NGpra+n6z+Hk7jrh0NBQlJeXW937cnfdcH5+Pr7//nuoVKo+x+nl5QWpVApXV1ds2LABn3zyyYCMt0YblOlVfn4+lEolLUpbW1vR0dHR62tcXFxgb2+Puro6uLm5QaVSDTlSGBQUNGZbVY1GXFxc0N7ebvSYUCiEXC63us+2NWMTwkOAJEnIZDKTonWWgup9OW3aNEsPZVSh0+nwww8/YPHixb22dgHuRIXMGREG7kTk7O3tB51KTAlhZ2fnfoVwZ2cn6urqEBkZCYIgoFQqkZubiylTppgkPhobG1FcXEwLa+D/HH+XL19+T/dqG9ZFRkYGJk6caHYhSpIkMjMzYTAYMHny5B4iuLW1FYcOHcKjjz5qNWUnVDR4+vTpRjX7CoUCJ06cwJo1a2wp/3fBYrEQFxeHjIwMSw/FIhAEAV9fXzzwwAP4xz/+Qdfkuru707WWTk5OWLRoEfbv30+nUA8nISEhKC0thbe3N1pbW6HRaIb9nIOFimo9//zz4HK5+OCDD9DR0dHrwp7L5cLZ2RmNjY2Ii4vD1KlTUVFRgR9++GHMmToJBAL4+vrSLYw4HA7Gjx/frzv75MmTkZ6eDi6Xi5CQEOTn5w9JIPH5fOj1+jF3b0cjBEHQQvju99TZ2bnPzREbvWP71R4iLS0tRoYp1o5CoUBZWZmtdc0gIEkSJ0+ehEAg6NdlW6vVmrVGmCRJSKVSsFisQR9Tr9dDIpGAwWDAxcWlz+Pn5eUhJCQEPB4PJEkiJycH/v7+Jm3uGAwGHD16FAsXLjQS3yUlJZBKpZg8efKgj2nDcshkMnR3dw+LsVlnZyeOHz+OdevW9Yg2a7Va/PTTT1ixYgVcXV2t5nuqr5T/ixcvIjQ0FJ6enhYeofWRkJCA3Nzc+zY6QRAElixZgubmZnz++efQ6XR0bWtqairCwsIgl8sxb9487N69e9gjbZ6enpDJZNDr9eBwOFZjmNUbXC4XDz30EKZMmYL3338fVVVVvc6jyMhIFBUVwcvLC93d3XjqqafAZrPx2WefQSaTjZm5x2AwMHv2bFy4cIHuKTxjxgxcv36913lDEAQSEhJQUFAArVaLSZMm4ebNm0MaA5fLhaenJ6qrq4d0HBvmwdXV1Sg1Gug9Smyjf2xCeIi0tbVBLBZbehgDpry8HJ6ennBwcLD0UEYNpaWluHnzJjZu3NivINVoNDAYDGZNI1Wr1WCz2YOONFEO1m1tbX0KGYPBgKtXr9Ju0VRadHJyskmRrcbGRlRXVxttFmg0Ghw8eLBXwWPDuqFarZi7bZLBYEBKSgqmT5/eYxOR6l8tFoutol8wBWUAl5SUBEdHR/rxzs5OXLhwAStXrrTg6KwXd3d36PV6qzJmGmmEQiG2bNmC69ev47fffgNJkoiKikJVVRUCAwORn5+P5ORkKJXKYe+9zOPx4OjoCIlEAn9/f5SVlQ3bucwBk8nEnDlzsGnTJnz++efIyMgwuj8EQSAiIgLFxcVwcHAAi8VCV1cXNm3ahOjoaOzYsQOtra1jRgwHBwdDIpHQQofKLqiqqur1+S4uLmAwGGhtbYW/vz+am5uHZM5GEASCg4NtdcJWgpubG1paWozeCz6fj+7ubtv7MwhsQniIdHd3jxpRSQmf37sd2+gdyqxq165d2Lp16z3fZ61WC51OZzbBR5lgCIXCQUeEu7u7weFwIJfLIRaLe32/5XI5vSAC7qRhd3Z2IjAwcNBjNRgMOHLkCBYuXEi3uKHSXx0cHGxOuqMMkiRx48YNk1Pk+ztuaWkp6uvrMWvWrB4p0bW1tbhx4wZWr15tNY72JEmivb0dubm5Rin/d7dR6uszdr/DYrEQFRWF3NxcSw/FYhAEgfnz58Pf3x/p6enIysqCg4MDQkJC0NbWhtbWVuj1ejz88MP47bffhj2tMTg4GOXl5QgJCRkVgoYgCERFReHll1/Gb7/9hiNHjtAdGgDA19cX7e3t0Gg0tLhnMBhYuHAhli5divfffx81NTVWf50Dwc7ODgkJCbh27RqdfZaUlERHiX8Pg8FAfHw8/Tvs6emJ8vLyIY0hPDwct2/fHhP3c7Rjb28PpVJp9F5wOJwx6Z4+nNiE8BBRKpXg8XiWHsaAUCqVqKmpQWhoqG3RNgD0ej1++eUXzJgxA/7+/ve8Z2q1Glqt1mxCmDLFEIlEg47QNjU1wcXFBTKZrNfUaKo/bFRUFB3xu3z5MiZNmjToXq1UPXJNTY1RCxyVSoUjR45g7dq1ttrJUYZCoUBDQwNCQkLMely1Wo1ff/0VGzZs6PE5UavV+PHHH7Fx40ar21w8evQoZs2aRRvAUWUL169fx+LFiy08OuuFIAg6JfN+Xji7uLggOjoaEyZMwJ49e9DU1ISkpCRkZmaCx+OhpaUFHh4emD9/Pnbt2jWsLtKUY3RwcDAqKipGRe9dgiDg4eGB119/HWVlZfjuu+9oEy0Oh0NHuSMiIlBYWAjg/1oIPfroo/jkk09QWFg46ucglQ5948YN6HQ6EASBuLg4lJSU9BrpJQgCEyZMQHZ2NvR6PV0zPJT7IBaLIZVKR8Tp3Eb/cLlcaDSaHkL494/Z6B/b6nQI6PV6qNXqUSGESZJEQUEBAgICrG6RaY1QTrBKpRJz5swZ0MZBV1cXGAyGWYUwSZI9HHUHQlNTE0QiEaRSKdzc3Hr8nbq+adOmgSAIaDQa3Lx5k/7vwZKSkoL58+fTopokSVy5cgWBgYF9movZsF6qqqrg6upq1u8KkiRx7tw5hISEwNfX12hOUBkFERERVrdR19bWhvz8fKNoMACcOHECU6dOhZOTk1WN19rw8/ODXC6/rw1cCILAokWLUFRUhBUrVuDbb7+Fm5sbNBoNnJyccPv2bRAEgTlz5qCzs7NHCrA5xxEQEIDGxkbY2dlBpVJZpWFWbxAEAT6fj6effhpCoRAffPABJBIJ7aBcXFwMX19f1NTUGL0mMjISzz77LH788UfcuHFjVAj//vD09IS9vT0d2RUIBAgMDERWVlavz3d3d4dKpYJMJkNkZCTKy8uHFDHk8/mwt7fvUZtqY+ThcrlgMBhG5mVcLhckSUKr1VpwZKMLmxAeAgqFAgwGY1QIYQC0W7Rt0dY/VOP606dPY8uWLQN2re3s7ASHwzGbEO7s7IRKpYKTk9OgXkeSJBobGyESiWAwGHqdn62trVCpVPD19QVwpw5aKBTC3d190OOkaoPvTqNVKBQ4e/Ysli1bZosGjzJIkkR6ejqmTJli1mO2tLTg1q1bWLRokdGcIEkSxcXFKCsrw9KlS61qvpAkiSNHjmD27NlG7cAkEgkyMzONjLNs9A6bzYa/vz9KS0stPRSL4u3tDT6fD6FQiICAABw+fBjjx49HZ2cnHa3kcDh49NFHsX///iG3uukLyvFcq9XC2dkZDQ0Nw3Ke4YLL5WLdunWYNm0aduzYgdraWoSFheH27dsQiURQqVTo6uqin08QBPz8/PDSSy/h5MmTOH369KiOZjIYDCQnJxuZZlE9hXsT+RwOBxEREcjNzYVQKASPx0NTU5PJ52cymfD29u7TvMzGyMHhcODg4GC0ycjhcMDhcIw+Azb6x3pWHKOQrq4u2NnZjQoTILlcjpaWFpPqP+831Go1du7ciQ0bNgyq13JnZye4XK5ZhbBcLjdq1TIQSJJEXV0dxGIxvWP4ezIzMxEbGws2m23US3iwkCSJlJQULFiwgBbcJEni7NmziImJ6TUabcO6UavVKCkpQUxMjNlEHkmSOHjwIBYvXtwjyqxQKHDw4EFs3rx50Gn5w01LSwsKCgqQnJxsVBt85MgRJCUlDfqzeb8yadKkYYtyjhaoqPDZs2exatUqlJaWgsvlQiqVora2lo7qeHl5YcaMGfj111+HJXrJYDDg5eWFhoYG+Pv7W2U/4XvBZDIxe/ZsPPjgg/j444/R2dmJhoYGEAQBsViM+vp6o+cTBAE3Nze89NJLyMrKwsGDB0d1L9yEhASUl5dDLpcDuNPft6urq1eBe3d5AgDEx8cjOzt7SO95eHg4iouLTX69DfNAEAScnZ2NWq8xGAzY29tbtSO8tWETwkOAMsoaDRGB7OxshIWFjZrotaUwGAw4ePAgwsPDER0dPaj3lpoP5hLC3d3dkMvlRi61A6WrqwsKhQKurq49TIcMBgPS0tKQmJgIgiDQ2dmJiooKk1pqNTY2oqqqysgpWi6X4/Lly1i6dOmo+GzYMKalpQUcDmfQmQh9QbXp0mq1SEhI6JESffToUSQkJMDb29uq5gtJkjh27Bjmzp1r1P+6paUFeXl5Ay6ZuN8hCALh4eGoqam5r/uPUg7HUqkUMpkMjz32GM6cOQODwYC2tjajqM6iRYtQUVGB0tLSYRGp4eHhKCwsREREBIqKisx+/JGAIAjExMTg+eefx8GDB1FYWIiuri6EhoaipKSk1+cLBAK88MILaGpqws6dO6FWq0fdJgBwxyQpJCQEOTk5IEkSLBYLU6ZMwdWrV3u9Hm9vb0gkEigUCsTFxSE/P39IUfHfp6DbsBxU32DqfScIAo6OjjYhPAhsQngIdHV1jYp6W5Ikcf36dVta9D0gSRL5+fmorKzEypUrB32vurq64OjoaLbUTqqOZ7CCRKfTQaPRoKOjo9fWSS0tLVCr1fDx8aGvOSgoyGixPxAMBgOOHTuG+fPnGzlFnzx5ElOnTh1UNN2GdUCZqI0fP95s81ilUiElJQVr1qwx2iQiSRLl5eWorKy0yhTj5uZmFBYWGrlbU9HguXPnjorvfmvB3t4eTk5Ooy4N19ywWCxMnz4dly5dgo+PD5YuXYqysjK0tbXRgpQgCLqH7k8//WR2B1iCIBAaGoqKigq4urqiubl5VIpB4M61+Pj44I033oBIJMLBgwcRFBTUpxs2QRDg8Xh46qmnwOVy8dlnn43KVjNUOvSlS5eg1+tBEASmT5+OW7du9Tpf7O3t4efnh8LCQnh6eqK7u3tIQsnV1RXd3d339caWtSAWi3vUa/P5fJsQHgQ2ITwEpFKp2aImw0l7ezvkcjkCAgIsPRSrRiaTYd++fXjkkUfA4XAG/frOzk6zpUpSZgdcLnfQc0wikYDH40Emk8HDw6OHwMjKykJsbCyYTCYMBgMuX76MWbNmDXqMTU1NqKioMGrH1dbWhszMTCxYsGDQx7NheXQ6HXJycjBx4kSzCFPKICsyMhJeXl5Gf1OpVNi3bx/Wr19vdSnRBoMBJ06c6BENbmxsRElJSQ/jLBv9QxAExo8fj1u3bo060WFOCILA1KlTkZubC4VCgVmzZmH69OloaGhATk4OnQpNRdF9fHxw9uxZs98zsViMzs5O2Nvbw2AwQCaTmfX4IwlBEHBxccHWrVtx8OBBnDp1CnV1df2agHE4HGzatAkhISH46KOPIJVKR9289PPzg1KpRHNzM4A776mTk1Ov7ZEIgsCUKVNw48YNsNlsBAYG4vbt2yaf287ODkKhcEi1xjbMg4eHBz0HKIRCIWQy2aib05bCJoSHQEtLi0nmQiNNbm4uIiMjR0Uts6XQ6XTYs2cPkpOTTU7RlMlkJqUx90V3dzeEQiHtxDxQWlpa4OzsjJaWlh4RYZ1Oh4yMDCQmJgIAOjo60NHRgaCgoEFdMyUU5s2bR4sYKkL8e2MhG6MHiUQCnU4HV1dXsxzvboOsu6HSjqOiohAQEGB1orK9vR2FhYWYOXMmPTaDwYCUlBQsXLjQVmIySAiCQHx8PAoKCkZ1baY5cHR0RGBgIHJycsBkMvHEE0/Azc0NWVlZRk6vTCYTa9euxYULF9DW1mbWMXA4HAgEAshkMri7u6Ours6sx7cEoaGhmDBhAtzc3HDr1q17Zh+wWCwsXboUU6dOxQcffIDW1tZRJRzYbDYSExNx5coV2jRr9uzZfZpmBQUFob6+Hmq1GuPHj0dmZqbJNegEQcDf3x9VVVVDvAobQ8XR0ZGuFadwc3OzuXoPApsQHgKjISKs1+uRnp5OCx8bPaFSx9VqNZKSkkxalFO76uZMl6SMsgazgUG581I9hEUikdHfqTohHx8fAEBGRgZiY2MHFQEnSRISiQQlJSV0bTB13uLiYqNUUhujB5IkkZWVhZiYmAE7pfeHXq/HkSNHMH/+fNjb2xulF1dXV+P27dtYuHCh1c0VkiRx4sQJzJo1i/48kySJhoYGVFZW2kpMTMTZ2Rl6vX5URx/NAeX6SwkWkUiEp556Cjk5OT3SGZ2dnbFo0SLs2bPHrMZZDAYDQUFBKC0t7bOmdrQhFApBkiRWrVqFRYsW4Z133kFDQ0O/4pbJZCI5ORmLFy/Gjh070NjYOGrEMEEQSExMRGZmJjQaDV0zXVVV1WtarEAggEgkQmVlJYKDg1FdXT2kFjuUYdZouV9jFXt7+x49pJ2cnIbNdX4sYhPCQ6Crq8vqI18dHR3o7OyEv7+/bfHWB83NzTh+/Dg2b95sctRcp9NBLpebNVLU3t4Oe3v7QYuS6upqeHl5wWAwGAlckiSRm5uLqKgoMJlM6PV6pKWlGaU2D5TTp09j5syZRk7Rhw8fxqJFi2zRslGKwWDAzZs3MXny5CF/V5AkicrKSkgkEkyaNMnoeBqNBvv378e6desGne0w3JAkiY6ODuTm5hptilHze/HixVY35tECm81GWFgY8vLy7vvFs4+PD1QqFR21SUpKApvNxsmTJ43uDUEQmDVrFtra2lBQUGC2+0b13i0pKUFQUBDKyspG/XtiZ2cHDw8P1NTUICkpCUKhEB9++OE9XbEZDAamTp2Khx56CB988AEqKytHzeYtR+sAAQAASURBVL0QiURwdXXF7du3QZIk7O3tERERgczMzB7XQLlH37p1C3w+H87OzkPKBPDx8UFDQ8Oo78s82nFwcIBarTYyP+tNHNvoG5sQNhGSJNHZ2WnVQpgkSeTk5NDCx0ZP1Go1vv/+e6xZswYuLi4mCwCtVovOzk6zLpJbW1vBZDIHLc5bWlrA5XLB4/GMRDQldKh+v62trdBqtfD09BzU8eVyOXJycui0UapvcU1NjVEvYRujC7lcju7u7kHPh97Q6XT49ddfsWrVKqM5SJIkrly5Ag8PD4SEhFjlXDl+/DhmzJhBlzlQ0eC6ujrb/B4CVJ1wVlbWqBEawwWXy8WkSZNw5coVAHeimYmJifj0009RX19vdH/YbDY2b96MX375BSqVymxj8PHxQV1dHTw8PNDe3m52U66RhhL3t2/fRlBQEIRCIf7nf/4HX3/99T3bBREEgbi4ODz22GP46quv6L7O1g7VRur8+fMAQKdHX7p0qVeBGh0djaKiIhgMBsTGxg7ps+ji4gKNRtMjLdfGyMLj8cBkMo36BvN4PJsQHgQ2IWwier0eKpXKrDWh5kav1+PmzZt0mxwbxhgMBpw8eRIeHh4YP378kO6RVquFVqs1qxCWSCQmCWG5XN5r66TOzk7IZDLaLfr69euYMGHCoCLOlPnRhAkTjIzBDh8+jAULFtiiZaMUatMsNDR0yO8h5Tzt7OyMoKAgo7+1tbXh6tWrJrmyjwQdHR3Iysoy6hsMAL/99hsWLVpkm99DxNfXF01NTf0aGd0vTJ48Gbdu3YJOpwOTycT8+fPBYDCwc+dOozpqgiAQHBwMX19fpKammk2g8fl8uraUw+EY9SIdrVBCWCwWQ6VSwcvLCy+88AL27duHixcv9hu9pAzKtm/fjl27do0aY7eIiAjU19fTJQfe3t7Q6XRobGzs8VyxWAwWi4WWlhbExsYiPz/f5GtkMpkQCoVGbb9sjDxMJhM8Hs8oHd7e3h4qlcoWrR8gNiFsIiqVCjqdzqpbaMhkMnR1dfVwa7Vxh/Lycty6dQvr168fcqsYrVZL928zF11dXYOuEe7u7oZOp4NSqYS7u7tRamdeXh5CQ0PB5XJNToNVKBS4fv26UQ/V+vp61NXVmSWl1obluHHjhlkinkqlEidPnsSKFSuMNmL0ej0OHjyIxYsXW+UG4t2tv+7e5KmtrUV9fb1tfpsBPp8PV1dXm8kO7rSgcXZ2RklJCZ226uTkBDabjXPnzvVIkV6zZg3OnTtnNuHB5XLh4eGBqqoqeHl5jYnWVq6urpBKpdDr9XB2dkZbWxvGjRuHV155BZcuXUJKSkq/Zm2UCdRzzz2HgwcP0kZU1oy9vT2io6ORlpYG4E4GwdSpU3Hx4sVe06Ojo6ORm5sLV1dXus2iqQQHB6OsrGxI47cxNHrrG8zj8UCSpFkzSMYyNiFsImq1Gmw222qdmCnjm6ioKJNaAY11FAoFdu/ejc2bNw+6f25vaDQa6PV6sy7w1Wo1hELhoOaYTCYDj8dDW1ub0QYISZJIT0+nF/N1dXXgcDjw8PAY8LFJksTly5cRGRkJFxcX+rHDhw9j4cKFtmjZKKazsxPt7e3w9/cf0nFIksT58+cRExMDNzc3o8fz8vKg0+mQkJBglYJSKpUiIyMD8+fPN3KK/u2332y1wWaCwWAgLi7Olh6NO/di1qxZdJTXzc0NPj4+SExMxOnTp436+1ItgmbNmoVDhw6ZJdJDRZrLysoQFhY2JoyP+Hw+BAIBmpqaEBISQrcIcnZ2xksvvYTy8nL8/PPP0Gq1fV4rQRDw9PTEH//4R5w6dQpnzpyx6sgaVUd+5coVuqfwpEmTkJWV1WvmxYQJE5CdnQ0Wi4WAgAAUFxebfO6AgIBRVVM9VhEKhUYp6hwOB2w225YePUBsQthEVCqV1fW+vBuDwUC7RVvjotOSUG1QoqKiEBwcbJb7Q6VGm7NmXKfTQSQSDWp8HR0dcHJyQmNjo1HrJJVKhebmZvj5+QG4E/2bNGnSoCLhKpUKqampWLJkCT2muro61NXV2ebZKKeoqAh+fn5D3hTq6OhAWlpaDzdolUqFlJQUrF692ir9CkiSxNmzZzFlypQe0eCGhgbb/DYjUVFRZjV+Gs3ExsaiuroacrkcbDYbERERaGlpwYoVK/Dzzz8bGeAQBIG5c+eipKQENTU1Zrl/VCpxQECA2Y5pSQiCQEBAACoqKhASEoLS0lI6/dvBwQFPP/00VCoVvv76636jZQRBQCQS4U9/+hNu3LiBY8eOGb0X1gbVBaKmpgbAnRRoDw8PFBYWGj2PIAh4e3tDJpOhs7MTEyZMMDkFnIqe19fX3/ct0SyNh4eHUSo8QRCwt7eHUqm04KhGDzYhbCIqlcqqIwRSqRRKpbJHH9n7HZIkUVJSgpKSEixdunTIKdEUVFqKuRyTSZKk07sGQ319PcaNG4fu7m5alFPX7OXlBT6fD61Wi5ycHEyYMGHAi3uSJHHz5k34+vrSkT6DwYAjR45g8eLFtqyDUQxVL061whrKcU6ePImkpCSjDSGSJHH69GlER0fD09PTKgWlTCbrIeD1ej0OHz6MZcuW2ea3GXFzc4Ner0d7e7ulh2Jx7OzsEBgYiMLCQtro6MKFC5g2bRpUKlWPyDmPx8Pq1avN1k5JLBajo6ODTikeCxGkyMhIFBUVwdvbG01NTbRIIwgCdnZ22Lp1K1xdXfHxxx9DKpX2Gxl2dHTESy+9hIKCAhw6dMhqBR+DwcDMmTNx6dIlWvjPmTMH58+f73F9bDYbgYGBKC4uRmBgIOrr602u2RcKhdBoNDbBZWFcXV179Bq3GWYNHJsQNhFr7iFMkiQyMzNtadG9QKVEb9q0yaxtfqiebeY6plqthlKpHPQcq6uroxead48lLS2NTouur68Hm82Gu7v7gI+r0Whw5swZLFu2jH6Mqg22OemObrq6ulBXV4fw8PAhHaexsRFlZWW0mzhFU1MTsrOzrbJnMHDn+/LChQuYMGEChEIh/XhtbS0aGxtttcFmhs1mIyAgYEz0rjUH06dPx/Xr12EwGODl5YWuri6oVCps2rQJBw4cMHKDJQgCCQkJ0Ov1yM7OHvK5BQIB7O3tIZFIYG9v32v/2dGGt7c3Ghsb6bXP78UAm83G2rVrER8fjw8++AAtLS39imEHBwc8++yzqKqqwoEDB6xSDBMEgcmTJyM/Px/d3d0A7mwINDU19TBBIwgCEydORGZmJgQCAfh8Purr6006L4vFgkAgGBNGa6MZgUDQoz+7rYXSwLEJYRNpbW2Fq6urpYfRJ+np6T36d97vGAwG7N+/HxMmTEBgYKBZ7w31JWSuLAGFQgGpVDqommOSJNHW1kb/eFNj0el0KC8vR2hoKABjUTxQCgsLIRQK4eXlBYIgbNHgMURFRQU8PDyGlBat1+tx5MgRLFq0yKhkRK/X47fffsPSpUvNUos/HHR1deHq1atYsGCBUTQ4JSUFS5cutc3vYWDChAnIzMy09DAsDkEQCA0NRXNzM+RyOcRiMQiCQGVlJXx8fDB+/HgcPny4RzuljRs34sCBA0M2w2EwGHQbJT8/P1RUVAz1kiyOi4sLDAYD3QqOShe+GyaTiQULFmDJkiX44IMPerSsuhsqzfQPf/gDmpqasHv3bmi12uG+jEEjFArh7e1N1/xyuVzExsbi5s2bPZ4bHByM6upqaLVaxMbGIi8vz6RzMhgMBAQEoLy8fEhjtzE0qBrhu+ews7OzzdF7gNiEsIlYc0S4o6MD3d3d8Pb2tvRQrAaSJJGfn4/a2losXrzY7BsE3d3dYLFYZosIKxQKyOVyowjVvdDpdHSql1gsptO+a2pqIBAIIBKJoFarkZubi4kTJw7quCdPnsSSJUvAYDDovqr19fW2zZZRDkmSuHHjBqZOnTqkY9TU1EAikRgZYVGfOa1Wa7UGWVQ0OD4+HiKRiH6soaEBjY2NmDhxolWOe7QTHByMuro6m6sp7hjbhISEID8/HwRB0OKFIAgsXboUOTk5PcRcUFAQvL296VTYoRAZGYnCwkLaOGss1Am7u7ujubkZQUFBfV4Tg8HAlClTsGnTJnz00Uf9mj4RBAEej4ft27eju7sb33//PTQajdXdq+TkZKSmptL1zLNnz8a1a9d6pD47ODjA2dkZdXV1iImJQX5+vkmp9gRBICgoyGaYZWEEAgFUKpXR++zi4mIrPxkgNiFsIp2dnRAIBFa5SMrLy0NYWJhVm3mNNHK5HHv37sWjjz46LBEeuVwOOzs7s0WEVSoVVCrVoDZburu7odfroVAojNygs7KyEB8fD4Ig0NLSAhaLRUce7gUlcjQaDUJCQkAQBEiSxNGjR7Fw4ULbHBvlKJVKlJeXIyYmxuTvMsp8bunSpUY9qdVqNY4cOYI1a9ZYpUEWcGfD6dKlS0bRYJIkkZKS0iO6bcN8CAQC8Hg8NDc3W3ooFocgCEyfPh03btyAwWDAhAkTcOnSJej1evD5fKxbtw4//fRTj97C69evx+nTp43cYk2BiggHBgaiqqrKqk2hBkp4eDiKiooQGhpKG2b1BkEQiImJwbZt2/D555+jsLCwX0HH5XLx+OOPg8lk4ttvv4VarbYaAUhlF7S2tqKjowMEQWDcuHFgMBioq6szei6TyaTd2318fCCXy3uk1g4UPz8/1NbWjol5M1qxt7fv0S7p9y2VbPSNTQibAEmSkMvlVtsLMz09HVOmTLH0UKwGvV6P/fv3Y8aMGfD29jb75gVJknQaszlrhAfbjkmhUIDH46Gmpga+vr4A7lx7QUEBYmNjacOr8ePHD9gkjCRJnDhxAvPnzweLxQJJkmhpaUF1dbUtWjYGqKurg7Ozs8lu5yRJoqysDBqNBhEREUaPX758GUFBQVZr2EeSJFJTUxEVFUWXuZAkicbGRtTW1tqyHYYZKhJlA/D390d7ezs6OzsREBCAhoYGOpozYcIEsNls3Lhxw0h0icViTJo0CSdPnhySGHN3d0d3dzeYTCYUCoXJxknWAtUWqqKiAiKRCB0dHf1GOykB+dxzz+GHH35ARkZGv8/ncDjYsmULHB0dafdpaxHDXC4XCQkJ9FxhMBhISkqiW3TdDfX5YzAY8Pb2Nrm3N5/Ph0qlssra6fsFygjubtMyBwcHul7cRv/YhLAJGAwGdHV1DSptdaSQSqVob29HYGCgpYdiFZAkiZycHLS3t2Pu3LnDsrA1GAzo6OgAn883W0RYp9OBy+UOKnotkUjg7OwMiURC9/mVSCS0e7hOp0NOTs6gFvhtbW2ora2lI8oAcPz4cSQnJ5vVbGwsQ5IkDAYD1Go1urq6IJVK0draisbGRtTV1aG6uhoVFRUoLS3F7du3UVhYiJycHNy6dQvp6ek9/t28eRPZ2dnIz8/H7du3UVpairKyMlRUVKCqqgrV1dWor69HU1MT2traIJVKaQMenU5HL4ioTbOhCD6DwUA7K98dDZbJZLhy5QoWL15sNmd2c6NQKHDhwgWjdmAAkJKSggULFtjm9zBCpQCbmpI51rCzs6PTo8eNGwe9Xk/X6zKZTGzatAmHDx82ivAQBIFFixbh5s2bPRxjBwObzYZQKERnZyccHR3HRDqll5cXOjo6wGKxwOFw7mnmRBAEfH198eKLL+LQoUO4dOnSPcXwxo0b4eHhgc8++8xqXJMJgsDMmTNx/fp16HQ6EASBCRMmoKioqIdxkqurKzQaDaRSKcaPH4/MzEyTBD2Xy4WDg8OYmDejGR6PZzQP+Xy+TQgPEJalBzAa0el0UCqVRv0mrYXbt28jMDDQaFF6P9PV1YUDBw5g+/btw3ZPdDodLYTNtejX6XSws7MblBCuqamBt7c3bt68SW/SlJaWIigoCEwmE83NzTAYDBCLxQM6HkmSOHPmDGbMmEGLAolEgqKiIqxfv/6+i5b1tkhQq9Xo7OxEZ2cnurq60NnZSaemdXd3Q6lUQqlUQq1WQ6fTwWAwgMlkgs1mg8lkgsVigcFggMlkgslkgiAI+m9sNtvoHlN/02g00Gq10Ol00Gq1tNCm/pEkCZ1OZ/SPig5Q5+JwOGCz2bh48SLmzZuH5uZmiEQiCIVC2Nvbg8fjwc7ODjweDw4ODuDxeL2+34WFhWCxWLQRG3Wfjh49ihkzZljlZiHwfxHr0NBQuh0YcMfhuqKiAo888sh9N79HGh8fH7S3t6O7u9sqs6tGEoIgMGnSJJw9exbTpk1DTEwM0tLS6P7V48aNw/jx43H8+HFs2LCBnpsCgQBz587FoUOH8Pjjj5s8Z4OCglBVVUUbZvWWOdWXSKLWQyqVCmq1GhqNBmq1GlqtFnq9nv6eogymqO8k4I6gZDAYRt+HLBYLbDabFrFcLtfoH4vV+7L17vFyOBzY2dmhu7sbXl5eqK6uhqura7/3hyAIeHh44KWXXsKnn34KpVKJhQsX9vmbzmazsWbNGvz222/45JNP8Nxzz/X5PTmSuLu7w87ODtXV1QgODoajoyP8/f2Rl5dn1OGBw+EgKCgIRUVFiIyMxPHjx6HRaAZdDsJkMuHl5YWamhqMGzfO4td/v0KZYwUEBAC4ExFWKBQwGAxWuxltLdiEsAlQC0trE5skSSItLQ3JycmWHopVQJIk9u/fj2nTpg1LSjSFXq+HWq2mo7DmwGAwwM7ObsBzjCRJNDU1wdPTEwaDAQKBgG6jNW3aNABARkYGYmNjB3zMzs5OZGVl4c0336Rrg0+dOoUZM2bAwcHB5GuzdqgFHyUs5XI5Wlpa0NraiubmZjQ2NqKzsxPd3d0wGAzgcDhwdHQEn8+Ho6MjxGIxIiMjaQF5t6ikFn4jjV6vh0ajMfpXXV2Nuro6zJw5E0qlEh0dHWhsbIRCoYBKpaJFPCW2uVwufT3Ozs5wcXHBqVOnMG/ePFRXV8PJyQl8Ph9NTU0oLy/HmjVrRvw6B4pCocC5c+fw8ssv96gNnjdvni0aPAJwOByIxWI0NDQgLCzM0sOxOP7+/mhsbIRarUZsbCwuXLgArVZLb4YuW7YMb7/9NpKSkuh+3ARBYNasWfj73/+Ouro6k3/nQkJCkJ6ejoSEBBQWFmLGjBkgSRJarRbt7e1ob2+HRCJBe3s7mpub6U0+lUoFvV5Pi1gqi4nL5fYQtywWi97go5DJZD027ah/Wq2WFtUajQZ6vZ7eSKREsZ2dHZycnODm5gYnJycIhUIIBAI4OzvDz88PJSUlCA4ORklJyYAMIgmCgEgkosWwQqHAqlWr+vQ4YLFYWL16NQ4dOoRPPvkEzz77LOzt7S0qBplMJmbOnInz588jKCiI7il86NAho24RVBulCxcuYMqUKWAymZBKpYNqq0gdJyAgAJWVlUhMTByOS7IxACiDOAo+n09vmtu8LvrHJoRNQKvV0tEba6KzsxNNTU0IDQ21urGNNCRJIi8vD/X19di0adOw3g/qh9ucXzadnZ1gs9kDjghTtbsBAQHg8/lgs9lQKBSora1FaGgoDAYDMjMz8fDDDw/YJOvKlSuIjY2lMx+kUqmRMB4LkCRJi8Tu7m7U1dWhtrYW1dXV6OjogEajAYvFgouLC8RiMdzd3REdHQ1HR0da6HK5XKu/H9RClGphRJIkcnNzMWvWrH77QJMkCY1GQwtj6n87Ojpw5coVqFQqNDY24vbt23T6dUFBAcaNG4cvvvgCrq6ucHFxoYWzWCyGnZ0dvSi2xPcotWEYFBRktOhrbm5GaWkptmzZYvXv51iAMirKzc21/WbhzsLV09MTJSUlCA8Pxw8//GDUUonP52PZsmXYt28fnn32WVqc8Xg8+vEXX3xxwPeRyiTRaDRwcnJCdnY2HBwccOjQIVqQU4ZdIpEIIpEILi4uCAsLo8uA7o7UDudn2WAwQKfT0cKY+qdSqSCVStHS0oKKigrI5XLI5XJ0dnairq4Ov/32GwICAlBfXw8HBwe4u7vD3d0dLi4u4HA49Pfi7zNvBAIBXnjhBXz11VfYs2cP1q9f3+dvMZPJxKpVq3Do0CF89tlnePrpp+Hg4GCx+UwQBOLj43HkyBEoFAo4ODggICAAcrkcra2tcHNzo8cWEBCA3bt3Q6fTISwsDAUFBUZ/HygBAQG4fv36cFyOjQFAbeDc3Q/azs6OXtvYhHD/2ISwCeh0OqsUwmVlZfDx8bFNetxJid67dy+eeOKJYb8fOp0Oer0ednZ2ZpsTjY2NdArrQNBqtZBKpWCxWHQbmMbGRjg5OYHH40Eul0OpVBq5SfeHSqXCpUuX6IUVZSw0ceLEUZvGSJIkSJJEd3c3pFIpKisrUVlZibq6OqjVanC5XHh6esLb2xsLFiyASCSio7nW+HkfClS2wMaNG++ZLkgtdO9Oc9ZoNLh06RL+8pe/0KlYOp0OWVlZOHPmDB577DHIZDK0tLRAIpHg9u3b6OjoQEdHB50iyePx4OLiAhcXF7i6usLDwwMuLi70Apv6PJn7vqtUKpw5cwbPPPMM/ZjBYMDx48cxd+5cWzR4hCAIAtHR0fj++++h1+v7THm9XyAIApMnT0Z6ejqWLl2Krq4ulJaW0qUsBEEgMTERqampKCoqQlRUFP35mDJlCk6fPk2L6N4gSZJuy1ddXY2ysjLU1NRApVKBwWCgtrYWwJ22K1u2bIGTkxMd4bV0aiWDwQCHwwGHw7mnsR8VyW5sbMTHH3+Mbdu24Z///CcMBgOKi4tx6dIlus0g1UHB3d0dHh4e8Pb2hlAopL/3n376aXz33XfYtWsXNm/e3OdagslkYuXKlTh69Cg+++wzPPPMMxYVw0KhEIGBgcjJycG0adPA5XIxadIkXLlyBatXr6af5+joCGdnZ9TW1iIuLg7nzp3D7NmzBz1uJycnyOVyOmJvY+RxdnY2Mh+8u5TKRv/c3788JkK581r6x+FuDAYDXVN0v2MwGPDbb79h0qRJtHvycKJUKqHT6cxaD9na2jqoGmHqy665uRm+vr4gSRJZWVmIi4sDg8Ggoy4D3RTIy8uDh4cHXT/Z2dmJGzdu4NVXXzXtgiyEXq9He3s76urqUFxcjKqqKnR3d0MgECAgIACRkZFYvHgxHB0d6VS+sSR4+4KqazbF0ZkkSRQXF8Pe3h5+fn5GqcXnz5/Hgw8+SC8sqZRXKt2c2jTS6XTo6upCc3Mz2tra0NbWhoKCAnR0dND11A4ODhCJRBCLxfD29oa7uzscHR3paLwp37/UBoCnpyedXgrcMYUrKioyqr+0MfyIxWI6zXa0brCZk/DwcKSkpEAgECAwMBCZmZl0nTBwJ518/fr12L17N9566y3694HD4WDt2rXYt28fXnvtNbDZbJAkic7OTjQ2NqK4uBilpaXo6OiAvb09fH19ERwcjHnz5kEgEIDFYuGTTz7B5MmTUVtbC5Ikrba+/14QBAEOhwN3d3dwuVx4e3sjODgYEydOhI+Pj5GHglKpRHNzM5qamtDY2IiMjAzI5XKo1Wqw2Ww4OztDKBTiwoULaG9vx8aNG+kSkN9//7BYLCxfvhwEQeDjjz/G888/b7IbvznuwZw5c/Drr78iMTERDAYD06ZNw4cffogVK1bQ6ekEQdBGWYsXL0ZDQ4NJqbSOjo5gsVjo6OgYsAeJDfPi7OwMqVRqVBPM4XDojWcbfWMTwiZAufNa04JJrVajurr6vk/rI0kSt2/fRlVVFf785z+PyDkpR0oqEmsOqAXLQIWwQqEAl8tFc3MzJk+eTLdN2rZtGwAgPT29hztuX+h0Opw5c4au8SRJEteuXUNUVBScnJyscn7d7YQskUhQVlaG3NxcOsrh4+ODyMhIzJo1C25ubrTgtcZrGW4oIevn52dS9FOv1+P48eNYt24d/YNLkiSys7Ph5OQEf3//HveV+m82m00vwvh8Pp2hcPf7R6VBSiQStLW1obW1FVVVVbhx4wbkcjlUKhVYLBaEQiFEIhF8fX3h4eEBsVhMR5R/n+pIodPpcOLECTz22GNGAv7kyZOYNWsWnTpuY2Sws7ODt7c3ysvLERcXd19+Hu9GJBLBwcEBjY2N8PPzQ25uLnQ6nZFwCQsLg1gsxtWrV+noHUmSiI6OxpEjR3DixAmQJInCwkLI5XK4uroiIiICDzzwALy9vWkTvrvvNUmSdM9db29v1NTUGG1yjUaoGvT6+nr4+PigtrYWvr6+tFDmcDiwt7eHi4sLIiMj6Ywh6juos7OT9oZwdHTE9evXsXnzZsTFxcHBwQFCoRAuLi709w+V3bJ06VIAwIcffogXX3zRYpHh4OBgyOVyNDc3w9PTE25ubhAKhSgpKUFUVBT9vOjoaPznP//B6tWrIRAI0NDQQGf5DBQmkwk3Nzc0NDTYhLCFcHZ2RldXF72RYYsIDxybEDYBqVRqVbulJEmisrIS7u7u9/1CTqFQYM+ePXj00UfB4XBG5AdIIpHQdUXmOh/Vp3qgUa/6+nq4u7tDIpFALBajs7OTNvDq7u5GS0sL/P39B3Ssuro6aDQa2mhDqVQiNTUVL7744hCuyPxQixaVSoXy8nLk5OSgtLQUBoMB/v7+GD9+PB544AG4uLgYGYTYAG7cuIEZM2YM+n6QJImioiLweDwjwatWq3Hy5Els27bNpHt89/vDYDDAYrEwbtw4jBs3rodbrU6ng0wmg1QqhUQiQU1NDa5cuUI7EDOZTLoe0MfHh64LFIlEyM/Ph0AggI+PDy0gJBIJ8vLy8NZbb9nmxwhDpUfn5eUhLi7O0sOxOARBIC4uDvn5+YiKisLBgwfR1dUFZ2dn+jkMBgMbNmzAjh07MH78eBAEgaKiImRkZKC+vh5nz57Fs88+iw0bNtDClzp2f+cNDg7GqVOnMGXKFBQUFGDmzJnDfr3DCUEQCAwMRHl5OcLDw1FUVITp06f3+3zqHjGZTLoumspqWbt2Lfbu3Yva2lps2rQJarUa7e3tqKmpQWlpKSQSCbq6umgvhvz8fLz66qvYunUrfHx8IBQKwWQywWAwRmQTlsViYcqUKbh27RpWr14NBoOBOXPm4Ny5c4iMjKTP7+HhAbVaDblcjsjISOTn5/e6mdkfBEHAz88PNTU1iI2NHa5LstEPXC6XLgugIvp8Ph9dXV0WHpn1YxPCJiCTySAUCq1q0ZSeno6JEydaVbr2SGMwGHDkyBHExsYO+ot8KEilUrDZbLOmQSmVykFlHTQ2NsLFxQXV1dUQi8XIzc1FUFAQOBwOCgsL4eXlNaBNEoPBgDNnzmDOnDlgsVh0Kqmfn98920+MFDqdDlKpFPn5+cjMzERrays8PT0RHx+PefPmwcXFpYcBio3/Q61Wo66uDkFBQYN+rcFgwLFjx7BmzRq6FozKGKDMp8x9339/PDabDbFYTEceJk+eTI9DpVKhu7sb3d3daG5uRm1tLW7cuIG2tjbI5XLcvHkTcXFx+Pnnn+Hp6Ylx48bh+vXrGD9+PL2QsM2bkSUsLAwXLlyw3fv/T0xMDH7++WfMnDkTMpkMlZWVRkJYr9fTrswvvvgi3NzcEBQUhGnTpuHBBx/ETz/9BLFYjICAgEHdTy8vL7S0tMDd3R2nTp0ajksbUQiCQGhoKE6fPo01a9bg7NmzJrWSoe4hi8XChg0bcOjQIezevRtPP/00goKCMGXKFAB3vn+oXvFUSvr169fx4osvYtKkSbRjtrOzM3x9feHl5QVfX18IhUL6/TTn+o0gCMyYMQMffvghli5dCjs7O8TFxeHgwYOQSqX0nGIwGAgMDERZWRliY2Pxyy+/YNmyZYM+X2BgIFJTU802fhuDgyAIsFgso1RokUh0zx7aNmxC2CTkcvmAo2sjgU6nQ0lJiUlfXmMFKipeWFiIP//5zyO2IUCSJDo6OsBkMs1a46ZWq436m95rDI2NjfD29gYA2NvbIycnh3YDzsjIwKRJkwa0KJLL5SgrK8ODDz4IgiCg0+lw6tQpbN261WKbLJSzc2trK7KyspCZmQmlUomIiAgsXrwYPj4+sLe3v683gQZDbW0thEKhSVktJSUlYLFYRqlzCoUCqampeP755y36HhAEQbd3EovF8PPzw+TJk+lUx1u3boHH4+HRRx9FfX09vVA9ceIEHQWjTLt8fHzg5eVF1yOPVHbJ/YizszMtICiH+vsZHx8fyOVyuLi4gM/no7i4GAkJCZDL5SgoKMC1a9fQ1taGoKAgtLS04KmnnjJKY169ejU+++wzTJ48eVClD3Z2dgDu/H4oFAoolcphyTC7O/2YiowOV4TU3d0dra2tcHV1RVdX15B7VrNYLDzwwAM4fvw4Pv74Yzz77LN0JhhBELCzs4OdnR29ETFlyhQEBwcjLy8PTzzxBJhMJtra2lBdXY2SkhKcP38e3d3dIAgCLi4uGDduHHx9feHn5wehUEh7IZh6b8RiMYRCIcrLyxEVFQU7OztERkYiMzMTc+fOpZ8XHx+PjIwMbNmyBTKZzKT33tXVFa2trbYNLQtB9eNWq9X0Y0KhEFKp1HKDGiXYhPAgIUkSMpkMTk5Olh4KDdUa4O5d4/sNrVaLn376CRs2bBjR9HAqtZLqJWsudDrdgBeFBoMBDQ0NiI6Ohr29PQwGA2pqarBhwwao1WqUl5cbOUX2BUmSuHz5MhISEuDg4EDXmVHmKiMNSZJobW3FrVu3kJaWBr1ej7i4ODz88MPw8PCga91sDI7s7GzEx8cP+t5R0eDFixfTDr8kSeLChQuIjY01a428OaGu8/Tp01i7di2CgoIQFBQEkiTxyy+/IDw8HCtWrEBXVxcaGxtpc6Fz587RaWVUr1I/Pz94e3vD2dkZTk5ONoFsBuzs7ODl5YWKigpbnTDuiC1vb290dHRAJBIhNTUVHR0dqK6uRlBQEJYsWUJn+/j4+NAu7dR9GzduHIKCgnDp0iUsWLBgwPeTw+HAw8MDbW1tcHR0HFQ5DXAnUi2XyyGVStHV1QWpVIr29nZ0dnaiq6uL7l+u1Wpp0zwGgwGDwUBnH3E4HHozi8fjwd7eni5r4PP5dK/2u3sR9wf1G6pSqeDg4ACpVDrk32kmk4klS5aAw+Hggw8+wAsvvNCndwaTycSyZcug1+uxc+dOPP/88wgLC0NYWJiRH4JarUZjYyPq6+tRWlpKf/fweDx4eHggJCSEzsoSCoUD3nAkCAKzZ89GamoqIiIi6P/+8ccfkZSURP+GhoWF4ddffwWTyYS7uzsqKyuN6ogHgkgkojNyLGUSdj/DYDDg5OQEiUQCDw8PEARBf45t9I9NCA8Sg8FglFZiaUiSREZGBuLj4+/biBhJkjh79iy8vLzoL/uRwmAwQCKRgM1mm61uXK/XQ61WD1gI6/V6KJVKKJVKuLm5obm5GXZ2dnByckJ9fT24XO6ARIpWq8WVK1folkmU8Fm6dOmItUSgWnxkZmbi8uXLkMvliIuLw9atW+Ht7T2k3fHh5ve1rHcbQFHvkUqlMuqDqdFooNPp6MWhVquFXq83Wiz2BmU6RTld3/2P2hmm2h5xOBz6/7NYLOTl5WHr1q0wGAz08foyl7qbyspKqNVqo/YsXV1duHHjBv74xz9a7fsCAOXl5VCr1UaLO5lMhps3b+Ktt94yiuRER0cDMG631dLSgubmZlRVVSEzM5NuA8Xn8+Hi4gJ/f394eXnB3d0dYrHYaJPGmu+LNUAQBKKiomx1wncRHh6On3/+GVVVVdBoNNi0aRO2bt1KR3ipOZWUlIS///3vqK+vh7e3N11jv3z5cuzYsQMzZsyAg4PDgM5JEAQCAgJQWVlJm0vdLYTv/j6jhFtVVRUqKiogkUjQ2dlJL8aFQiGcnJzg4uICPz8/8Pl82qCKw+HQacAGgwEGg4F2clar1fRvmVKpRFdXF6qrq5GVlUVHdO92lKdSjMeNGwcXFxcj13/KLMjDwwM1NTXw9fVFTU0NfHx8hvz+MJlMzJ8/HywWCzt27MAf//jHfsXwypUrcfDgQXz66ad49tlnaUM/6juby+VCIBAgNDSUvsdUFlR9fT3KysqQkZFBZ595enoiMjISAQEB8PLyojfkejMpjImJwcGDB9HZ2QmhUAgfHx/odDo0NjbSG9z29vbg8Xhob29HXFwcsrOzBy2EqWCARCKxCWELIRKJ0N7eTv+3o6MjysvLLTii0YFNCA8Sg8EApVI54B+X4YYkSeTl5ZlsUjMWaGpqwqVLl/D666+P+GYASZJQKpXQ6/VmiwhrNJpB7VxrtVoYDAa0tLTA29sbRUVFCA0NBYPBQE5OzoDNK3Jzc41aJlVXV0OhUCAiIsLkaxkI1CKoqqoKFy5cQFlZGYKCgrBmzRoEBARYTeSXWgjq9Xr6X1dXFyQSCSQSCW3gREVBtFotLWipqAeLxaJFKVUXxmazwWKxaFFL/S+VqkhBmUhRx1WpVOjs7IRer6cjC9T/p6IvlOCmxtHV1YX09HQoFApwOBz6vHZ2dnS6tIODA/h8Pv2/QqEQfD4fR44cwdy5c2kBzWAwcObMGUyaNMmqMmR+j16vx5EjR7B8+XKjuua+xv57ASsQCCAQCBAcHEyb7ZAkaRT1qqysxLVr19Da2krfWycnJ/j5+WHcuHHw8vKCq6srfc/vV8fyvggNDcXFixctPQyLQQmfmpoanDp1CoWFhWhqasLChQuRnZ0NPz+/XjOdeDweVqxYgQMHDuC5556j57e7uztiYmJw9uxZrFixYsBzLTQ0FMeOHcPUqVNRWFiIGTNmQK/Xo7u7GyUlJcjPz0ddXR1UKhWcnZ3h5+eHiRMnwsXFBU5OTia3NRsod/eB7+joQE1NDW7evInGxkaoVCrw+Xz4+fkhKCgIwcHBdD/d8vJyBAcHo6ysDNOmTTPLZ4/BYCA5ORlMJhPvv/8+Xn75ZYhEoj7F8Jo1a7B//358+eWX2L59ew93e6CnaSBlGDhp0iQAoN30GxoaUFhYiLS0NEilUggEAoSHhyMiIgL+/v6ws7OjNwXs7e0RGRmJW7du0eOdMWMGLl68iM2bN9OCPDo6ml4vXL582aR6and3d7qFo42RhSAIODk5GaVCOzo6orOz05aufg9sQniQUDuYVGqgpWlpaYHBYKDbkNxvaLVa7NmzB6tWrbJIH0pKdFBixhxQDo4DjTC3tbVBIBCgo6ODNqxYunQpDAYD8vLysHHjxnt+CRoMBpw8eZJ2lzQYDDh+/DgWLlw44DS0wUKSJG1gdOnSJXC5XMyaNQsbN26Eo6Ojxb64qUWpSqWCSqVCW1sbGhoa0NzcjJaWFnR0dNCCk4q8U/0mvby8EBcXB0dHRyOhSc0PS5h4UZFNvV6Pa9euITQ0FA8//LBRJFqlUkEqlUImk6GrqwsNDQ3o7u5GV1cXurq6UF9fj6KiIjQ0NODIkSNwcHCAvb09Ll68iI0bN+LKlStwdXWFs7MzHfG5W/RZktraWrS3txulg8tkMty4cQN/+ctfTDomlXbm6OgIHx8fxMfHA/i/jVJqsV5VVYWysjJcvnwZUqmUXqz4+vrCx8cH/v7+EAgE4PF4VrPhYwnc3d2hUqmsruxouCFJEhqNBoWFhThx4gQ0Gg3mzp2LBx98EDt27EBQUBBycnJQUVHRa5oyQRCYOHEiTp06hdLSUoSFhdGbLEuXLsW//vUvzJ49e8C/JVSdp5OTE7KysvDLL7+gtLQUGo0G/v7+iImJweLFiyEUCnsVcsMNQRB0irS3tzdiYmLoFOPu7m7IZDJUV1fj9u3bOHXqFJ1x8//YO+/wqMr0/X9mJm3SO+m9kE5CCqGF3ruAgKKoIBZEAcWyrr9Vd127qKvYFXWRrtIE6b23QEICgYT0XieTSaac3x9c53xBQkggDTb3deVSYDLnPee85z3v8zz3c981NTXMnDmTzMxM9Hp9q72r5XI5/fv3Ry6XSzRpR0fHmwbDotfzV199xdy5cyWbm+bCyMgIZ2dnnJ2d6dGjh5QYEH3Qt2/fTkFBAZaWloSGhhIZGYmbmxv9+/fnp59+IikpCYVCQVxcHG+//TYajQalUolMJqNHjx6sXLmSIUOGSO+Dlra7+Pv7k5GRIQXuXWhf2NnZkZWVJQW+1tbWqFQqDAZDu7H67kZ0jmjuLoJI4+kskyo5OZnw8PBOE5i3JwRB4OjRoygUCmJjYztkE9nQ0CAFRK11fK1WS21tbbOp0YWFhTg6OlJcXIytrS0lJSV4enpSU1NDVVWVJKLVFHJyctBoNBI1q7i4mOzsbGbPnn1H59IY9Ho9ubm5bNu2jfT0dMLDw5kzZw6urq7XUdvaA6LScGVlJaWlpWRlZZGbm0tRURF6vR5jY2Ps7e1xc3PD09NTqn6IwZ6RkVGnpmvD/9mCyGQyzp07R69evZpt9SUG0N988w3Tp08nJiYGnU5HdXU1P/30EwMGDECpVHLp0iWOHDlCVVWVRO82NjbGyspKShQ4ODjg6uqKtbU15ubmmJubt/lm2mAwsHHjRkaOHCkldARBYPfu3cTExLR60CWXy7GwsMDCwgJnZ2eCgoKkRIRYoS8rK5Mopbt375bEcpydnXF3d8ff3x8XFxdsbW0xNzfv1HOrtXAthfV/JRCuq6vj+PHjbN26FVtbW8aPH09gYKA0T/39/dHpdJiZmZGSksKgQYMa/R4TExPuu+8+Vq1axSuvvCLtBRwcHIiPj2fLli1MnTq1yXkkBlSZmZmcOXOGL774gtTUVEaPHs3cuXM7dT+8WNEUmRuenp706dMHnU5HXV0dFy5c4I033mDLli3s3LkTCwsLoqOj6d69O87OzpiYmNzR8eVyOX379kUul7NkyZImg2EjIyOmTJnCihUr+Prrr3n88cclq5vbwbWJAR8fH4YPH059fT0lJSWcO3eOdevWUV5ejpOTE6mpqaSlpRESEoKtrS0eHh6kpKTQs2dPZDIZ3bp1o7KyEp1Oh7u7O9nZ2S0KhGUyGe7u7pw+fbqrAtlBsLOz49SpU9KfraysUKvV6PX6ThOzdEb870VPdwixZ68zTCpRCXXKlCkdPZR2hyhatnHjRp577rkOux8VFRWYmZlhamraapQwnU6HTqdrluiXqBhtb2/P5cuX0Wg0EpX1+PHj+Pj43LKiKwoe9e/fH4VCIfVc9+/f/443CdceQ6/Xc/78eTZt2kR1dTVDhgxh+vTp7bLZv5bWXFxcTE5ODhcvXiQvL4+qqirMzc0lpc9+/frh7u4u0fzEuXW3v9g1Gg3Z2dk89NBDzT4XmUxGZWUl+fn5zJo1S6JrGwwG6uvrWbhwIebm5lKwJ1ZnDAYDarWa8vJyicZYWlrK2bNnqa6uRq1WSwkkGxsb7OzscHV1xcXFRaJo29jY3JDga8k9EASBwsJCcnJyrhMTqq2t5cCBA7z00kvN/q47wV8VZUW65rXXqra2ltzcXPLy8jhy5IhE9RQ39iEhIbi5ud2wcb/b56QImUxGZGQkZ8+eJSIi4p45r79C7K89cOAAf/75Jx4eHsyZM6dR/YPw8HD+/PNPTE1NKSgouGlwIfZYb968mdOnT0uBjUwmY+TIkbz++usMHjxYshu7dix6vZ5Lly6xa9cuMjMzcXV1JSgoiBkzZrBp0yaioqLo1q1bm1+X1obYH2xsbExMTAyRkZHMmTMHg8FAdHQ0RUVF7NmzB51OR2BgILGxsfj7+0vv3JbOP7lcLlGuP/zwQxYtWnSdf/21MDY2Ztq0afz000989913zJ49u9VYV3K5HKVSKTFORowYgUaj4eLFi9TW1rJw4UL69u1LXFwcISEh7Ny5k549ewJX+4Td3Ny4dOkSUVFRnDlzpsXidW5ubpSVlaHValtt79CF5sPBwYGKigqpAiyK0Ol0uq770QS6AuEWora2Vuq/6GhUVFRQXV2Nt7d3Rw+l3SEIAqtWrWLAgAE4Ozt32MaprKwMExMTLCwsWm0MOp0OQRBu6BG9GbKzs4mJiUEul3P+/HlJ7OfkyZPExMTc8vdrampISUnhvvvuQyaTUV1dzZkzZ3jttdfu+JzEStiJEyfYtGkTFhYWjB49mtDQ0DalzYpBWX19vUSVu3jxIuXl5SiVSjw9PQkKCqJfv364uLjck8HFX1FcXIylpWWLVNXF6mnv3r2lyoUgCOzYsYM+ffpcJ94jXjdxbTQ1NZVEBf8qJAZIlXjxJz8/n0OHDlFVVUV1dTU6nQ6lUomVlRWurq64u7tL/sH29vY3VOMbu2+bN29myJAh0rMkCAIHDhwgJCSkRT7dbYFrxXJsbW2xtbW9TqBGo9FQUFBATk4Op0+fZtOmTajVaqytrfHy8iIoKAgfHx+cnJwkJsXdPHeDgoI4cODAPVlNEtfBw4cPs2nTJnx8fJg/fz5ubm5A43PX39+f8vJyrK2tKS8vb7JdxsjIiKlTp/LNN98QHh4uzXcrKyv69+/Ppk2bmDlzJjKZTLL8O3DgAIcPH0apVDJw4EBmzpyJubk569evp6CgAHd3d/Lz83F3d2+7C9MOkMvluLq6UlJSQkBAAObm5syYMQNBECgrKyM1NZVt27bx008/4eTkRK9evYiMjLzOFqm5xxGD4XfffZcXXnjhppVhY2NjZs6cyddff83PP//Mgw8+2OotSOLYzc3NiYyMxNPTk8rKSiZNmkRycjInT57k6NGjhIeH07t3b6ytrYmIiCA5OZkhQ4awY8cOdDpdi8ZlaWkp6Sd0VheBexlKpZL6+nqpAiyXy5HL5TcV3ezCVXQFwi1EZWUllpaWnSIQvnDhAn5+fv+TtOjU1FSKiop4+OGHO3TTVF5ejiAI2NnZtVpFWLSVaG4gXF5ejpGREUqlkvT0dGbMmEFDQwOZmZncf//9t6TEnTp1isDAQOkldvjwYSIiIu5I+VEUETt8+DDbtm3DxcWFRx99FF9f3zYRUxEDX41GQ05ODmfPniU9PZ3a2lqcnJwIDg5mwoQJODs7d2j/cUdBEASpjaIl17+2tpbTp0/zwgsvXNdfe+7cuev+7lZo7HOiRYqrq+sN/yYK9KhUKmpqaiRrkbNnz1JeXo5arZbmvKurq1RNdnNzw9raGmNjY6qqqkhPT7+uR76+vp6dO3fy3HPPdUqV/Wuvk1KpxM/PDz8/P5KSkqQNZllZGVeuXCElJYWtW7dSV1eHg4MDwcHBBAUF4enpiZmZWafoz24JXF1dpT7PzuLKcKcQqzGnT5/m119/xdXVlXnz5kkV4KZgaWmJUqlEoVBQVVVFaWlpk72+vr6+uLq6cvDgQQYOHCgFQoMHD+b111+noKCAuro6/vjjD3Jzc4mJieHpp5/G1dX1urEEBQWxceNGYmJi7pl+z5CQENLS0vDz8+Py5cskJiYil8txcnIiKSmJ/v37U1tbS1ZWlpSssLa2Jj4+nujoaGxtbZvVtiOTyUhMTEQmk/H++++zcOHCmybqjY2Neeyxx1i6dClr165l8uTJbbaXk8lk2NnZ4eXlRV1dHdOnT2fy5Ml89913rFmzhr179+Lk5ERISAgpKSncf//9aLVaqqqqbmAS3Oo4okBTVyDc/jAyMpJYRoCUKO4KhJvG/14EdYeoqanpFBtpQRA4ceIEffv27dBxdATq6upYuXIls2bNuqP+mjuFIAiUlpYil8tbtbokqjWK1bZbfVatVksq0wUFBXh6epKfny/1DjUFnU7H7t27JbpsfX09e/bs4emnn76t8xED4IMHD7Jt2zb8/f15+umncXNza/XAQxAEtFqtRLkVgyQnJyfCwsJ4+OGHsbe3l8RA/pfREuE0EYIgcOjQIcLCwqR+dZE236tXrza1yLi25w8gODhY+jfRXkyj0aBWq8nPzyc/P5/jx49TXFws9dxmZ2djbm7Ozp07cXd3x9XVleTkZNzd3SVl9LsJ1wp0+fj40L9/f0m5vKSkhPPnz7NlyxaKioowNjbGx8eHoKAgAgICsLW17fTPgZGREd26dSM/P/+eCIT1ej0XL15kzZo1mJiYMHv2bHx8fJq9DhobG+Pn58fx48eRy+VkZ2fj7+9/08/LZDImT57MkiVLiIuLw8rKStIz8fT05OmnnyY6Opphw4bx2GOP3XQ+ODk5UVpaiqenJ8ePH78t9eDOBm9vbw4fPkz//v0lReRrixlir214eDhhYWFoNBpyc3M5cuQIH3zwARYWFiQkJBAdHY2dnV2ThRCZTEavXr2knuFnn32Wbt26NXqtTUxMePzxx/nss8/YsGED48aNa7Mii5gU2bJlCzExMRgbGzNy5Eiys7N56aWXuHz5Mtu3b+fgwYOsXLkSc3NzMjMzWxwIe3p6cuXKlf9JpmJHQ6RCi4Gw2CJQX1/fwSPr3OgKhFuI6urqZosYtSXUajV5eXkEBgZ26s1Na0MQBLZu3UpQUBB+fn4dPRwKCwtRKpWtunETNx7NqQhXV1ejUCiorq5GEAScnZ0xNjbmzJkzhIeH3/KlmpOTg0wmw8PDA0EQSE1Nxd7evsV9YSIN+eDBg2zduhVfX1+ee+45unXr1uqbqLq6Oq5cucLx48dJT09HoVAQFhbG+PHjcXd3lwSY/peei1tBpCG35L5qtVr27t17XVKkurqa06dPs3jx4g67vgqFQhLbsre3l8TgxJ5HnU5HSUkJ//znP5k2bRrV1dUcPXqU3Nxcdu7cSVRUFO+//74kTuXp6Ymtra0k4nW3zBuZTIaRkZFEqw4ICJAouDU1NWRkZJCens727dvRaDS4uLgQEhJC9+7d6datW6cMjCMiIjh37lyLPUw7EwRBoLi4mNWrV1NYWMjUqVMJDQ1tsRCg2Pt78OBBADIyMhg4cGCTn3dxcSEsLIzdu3czZMgQjhw5wtatW7Gzs8PZ2ZlHHnkET0/PJschsptMTU0pLy+nvr6+WUnZzgw3NzcqKysxMTFBpVKh0+lu+m6UyWQolUoCAwMJCAigoaGB3NxcDhw4wLZt27Czs6N3795ERUVhY2Nz077t+Ph4BEHg448/ZuHChY3SpMVjPfnkkyxZsgRTU1NGjBjRZomH7t278/PPP1NaWoqzszMeHh4YGxtTXFxMVFQU4eHhGBsbk5GRQUZGBvn5+ZKmQXOq1WIgnJOT0ybj70LTEFlSNTU1mJubI5fLsbKyoqqq6q7s9W8vdAXCLYAgCFJFuKORl5eHg4PDXf+CaglEYSjR9qQzbOKqqqoQBKFVlU5Fe67mBMIiXa64uJjy8nL69u0r0WBFj8CmjrN9+3YGDBggZRK3bNnC2LFjm/0iFoOPkydP8uuvv+Lu7s6zzz6Li4tLq73MxSD7woULHDp0iMuXL2Nvb098fDwjRoyQNm6dYT50RgiCQGZmJi4uLi1aL5KTk3F1dZVeoGJvcHx8fKdYA/8KMTBUKBQcPnyYgQMHMmDAAOnfDx06hJ2dHXPmzKGkpISioiJyc3NJTk6msrISjUaDmZkZdnZ2uLu74+Pjg7OzM05OTjdoAHTGufZXUS6x39FgMKDRaMjMzCQ1NZWffvqJ6upqHBwcCA0NJSQkRKJTi9/TUePv3r07y5YtQ6fT3XUtP2JrxpYtW9i3bx+jRo1izpw5d6S27O3tLVnc5OXl3bI6K5PJGDp0KAsXLmTXrl34+fkxb948XF1d2b17Nxs2bOCpp55q8pgKhQInJyep5UatVt/1+wxTU1Opf9LMzIyKiopmWU7KZDJMTU3x9/fHz88PrVbL5cuX2bdvHxs2bMDd3Z2BAwcSEhIi6Uxcq1mQkJCAwWDggw8+YPHixY0yx2QyGRYWFsyfP5/3338fU1NTBg0a1CbPobGxMT179uTw4cPSe75fv37s2bMHPz8/FAoFvXr14sSJEzzxxBM899xzLFu2DBMTE8aNG0dERMQtEzoeHh73DJPgboPIpKqoqJBYCNbW1lRVVXX00Do17q43TSdAVVUVvr6+HToGkRYdHR3dKTdkbQW9Xs+KFSuYOHEiFhYWHT0ciQYsCAIODg6t9r0qlQpjY+NmBcLFxcXY29tz5coVVCoV3bt3p66ujpqamlvSP1UqFRcvXmT69OnIZDJycnJQq9UEBQXdcl6J9Jv09HRWrVqFUqlkzpw50rPRGiJb1246Ll68iIuLC4mJiUybNk1iZfwvzf87wZkzZ1qkxqvX69m+fbskoAZX58uJEyd48cUXO/V1r6mpuSFZptVq2bx5M7NmzZIUqcUKqoiGhgbKy8spLy8nPz+f5ORkSkpKqKqqkmjJ7u7ueHl5SX3JFhYWkigJdL75KApyWVhYSLRPuMooys3NJTU1lbVr11JWVoaNjQ2hoaFERETg5eUlBXDteU7dunWjpqaGurq6TplsuRkMBgMpKSksX76cgIAA/t//+3/NtihrCnZ2dtja2lJXV0dlZSUqlapRRpq4Xh45coSNGzdibm5OUFAQc+fOBf6vd3Xr1q3k5ubi6enZ5HGDgoK4fPky3bp1k5LudzNE1pPYOpSVlXVTunJT32FiYkJwcDDBwcHU1dWRmprK9u3b+fnnnwkLC2PAgAF4enpeJ16XmJiIXq/nvffe44UXXrhpMGxlZcXChQt55513MDU1pU+fPq3+7MlkMvr3789//vMfhg8fjqmpKXFxcWzZsoXa2losLS3x9/fn119/xcrKCn9/f5577jlKS0v5/fffWbduHWPGjCEmJuamGgQuLi6Ul5ej1Wo7tHXtfxEy2VWf+srKSunPVlZWqFSqjh1YJ0dXINxClJWVERsb26Fj0Ol0pKamMnjw4E638WoriMG/IAiSPURHQ+xVBFq1IlxeXo6xsXGz5O6zs7Px8PAgOTkZQRBwcXHhwoULuLq6NqkOLPZ/hoeHSyJZW7duZdCgQbc8rmhLs2rVKsrLy5k8ebJE/btT6HQ6ioqK2LdvH2fOnJFoaFOmTLkpDa0LTUMQBNLS0hgwYECzr9+VK1fQ6XRS+4EgCOzbt4+oqKjbDlBEQTORvqzX69Hr9ZJvtkqlora2Fo1GQ319PfX19TQ0NEi+xAaDQVJUB6SNmLhBFX/S0tJQKBRkZ2dTUVGBlZUVFy9eRC6X4+bmhlarve53RZiamkoBrhgwilRjlUpFdXU1eXl5ZGdnc+bMGUpLS9Hr9dLveXh44O7uLllviV7TnWnOimOxsLCQNvSih2xJSQkpKSn8+uuvlJWV4eDgQHh4OBERETg6OrZLy4GRkRH29vYUFxffFYGwqMD8yy+/UFxczCOPPEJAQECrVcJMTEzw9/dnx44dEq33r4GwTqfj/PnzrF69Gnt7e55++mksLCx46623qKyslNp2lEolo0ePZs2aNTz77LNNjtHPz48//viDoKAgMjMz7wlLq4CAADIyMvDx8SEzM5OEhITb+h7xOpibmxMbG0vPnj2pqKjg5MmT/Pjjj2i1Wvr160dcXBy2trbI5XL69OmDXq/nww8/ZOHChTcNhm1sbFi4cCEffPAB5ubmbVLscHZ2xtzcnCtXrhAUFCSp8l+8eJHo6Gjs7e0xNjamoqICX19fLl26RK9evaS58Pvvv7Np0yYmTZpEWFjYDarS4v6hoaGhKxDuANjY2EiBMFxd67sC4abRFQi3AOKGoS1FYpqD8vJyFArFPSEo0lyoVCp+//13nn766U5DmausrJQ21K3p0VZeXi5tOm+F/Px8vL29KS0tJTIyEhMTE06fPn1L/z+DwcC+ffuYM2cOMpmM8vJyLly4wPTp05s8Xk1NDZs3b+b48eOMHj2axMTEO6L+wdXnqrq6mlOnTrF//37q6+tJTExk0aJFXbTnVkBlZSVarbbZoicGg4EdO3YwZMgQabOsVqs5dOgQCxYsuKUKeX19PWq1mrq6OqqqqigqKpIqrVVVVdTV1UkBlUwmQy6XY25uLlk7mZqaSlRGUa1VfM6uffbFoFiv19PQ0EBDQwOVlZXs3r2bsWPHcvToUVQqFVVVVezatYvQ0FD+9a9/YWRkhLW1Nfb29jg6OuLi4oKzszMWFhZYWFhc9+yJ1EhTU1McHBwkxoNYgbtWsEsU1yksLESj0aBQKHB0dMTV1RVPT088PT2xsrKSguTOMqdFoSBLS0t8fX0ZNWoUarWagoICkpOTWbZsGSqVCldXV8LDwwkJCcHR0bFNzkEulxMUFCQp/HaWa9QYtFothw8f5vfff2fIkCHMnj271Tf+Il38t99+w8TEhPz8fMlyyWAwkJOTw5o1a6itrWXGjBkEBgZKXvB9+/Zlw4YNkm0SQEJCAlu2bCEzM7NJ4S03NzdKSkoYNGgQe/bsuestrWQyGT4+Phw+fJhevXpx5MiRVv1ue3t7Bg8eTFJSEgUFBezdu5e3334bV1dXBg0aRFBQEP3798dgMPDxxx/z3HPPYWtr22gw7OjoyLx58/jkk09QKpV07969Va+9XC4nKSmJXbt2ERAQIFWJxUSnTCYjKCiI9PR0wsLCSElJISEhAYVCQUBAAM8++yyXLl1i7dq1bNy4kalTp16X/DEyMsLKyory8vK7Ipl1r8HOzo7i4mLpmbW0tKSoqKijh9Wp0TkiirsIDQ0NHWpMLQgCZ86ckXxY/xcgCAK//fYb8fHx0iagM0D0eKypqWnVe1FVVdWsF4hYjaivr6egoIAHHngAuGqrNXjw4CZ/NzMzE2NjY0loaP/+/cTExNyUcq7T6Th+/Dhr164lOjqav//973esni5u5Hbu3ElqaipBQUHMmDEDT0/Pu876pTPj4sWLeHt7N3vdKi8v58qVK9f5jh49epTAwEAp+WYwGKitraWiooLS0lKuXLki9amr1WpMTEwwNzfHxsYGZ2dnXFxcCA0Nxd7eXrKfEz0OxWAY7oxaLAgCe/fuZfjw4Tz66KPS2FNSUgB48cUXgasWSuXl5ZSWllJSUsLZs2cpLi5GpVKh1WqxtrbGyckJb29vyadXrOyIuLYKbW1tjYuLCzExMVJgrtfrqaurkxStMzIy2L17NzU1NQA4ODjg6upKQEAALi4u2NvbY2Vl1Sl66uRyOZaWlpJY0IQJE6irq+Py5cucPXuWPXv2oNVq8fX1pWfPnvj7+ze6qb8dyGQyQkJC+OOPPxg5cmSnXANE/1mxl3nRokW4uLi02VgDAwPRarUIgsCVK1eIjY2lurqadevWkZqayoQJE4iNjb2OfSCTyRgyZAj/+Mc/GDFihNQmI/Z6/vrrryxYsOCmLB6R1m1hYUFxcTE6na5D9z2tARcXFyorKzEzM6O6uvoG5eg7hajQ6+XlxQMPPMDkyZNJTU3lzz//ZPny5cTGxtKnTx90Op0koNXYO1Qmk+Hu7s7jjz/O0qVLmT9/Pl5eXq02v2QyGVFRUfz++++o1WosLS0JDQ1l5cqV1NTUYG1tTVRUFDt27GDGjBls3LgRvV4v7XGMjIwIDg5m8eLFpKSksGzZMtzd3Zk8eTJOTk7I5XI8PDzIzs7uUo7uADg5OXHu3Dnpz1ZWVly6dOmuT2a1Jf43IqlWglgF6OhA+OTJk0yePPl/ZlJnZmaSnp7OK6+80qnOuby8HAsLC9RqdYtM52+FmpoaLC0tb3mudXV1aDQaNBoNWq2WsLAwysrK0Ol0TSoECoLAzp07GTBgAAqFQrI7Wrhw4Q3HFAXKfv75Z3Q6HfPnz8fDw+O274P4DCUnJ/PHH3+g0WgYMGAAkydPlpgWneke3ws4ffp0syl2giBw4MAB4uPjMTU1lfrgN23axLBhw/j999/Jzs6mrKwMvV6PjY0NDg4OklWPo6MjdnZ20qbp2o15W0Or1fLnn3/y+OOPS9VmvV7P5s2bGT9+vFTpFSvNfn5+Es1a/G99fT3FxcUUFxeTlZXF77//Tnl5OTKZDCcnJ7p3705AQAAeHh6NUoXFqrWRkRGmpqbY2toSEhIiHUP0Ai4oKCA/P5+zZ8+ybds2KZnm4OAgeQd7eHjc4E/e3s+G2GNsaWlJREQEERERCIJAZWUlaWlpHDx4kFWrVkn/HhUVJSWybne8bm5uFBUVdbrgS9RFOHz4MGvWrGH06NHSGtqW98XFxQUrKyu0Wi3Z2dkcPHiQtWvXkpiYyD/+8Y+bqn9bWloyZMgQfv/9d2bPni3N1Z49e7Jx40YuXbp0U9cJcb7X1NRgMBg6vADQGhDbjcQ5XVlZ2Wa9zzLZVdG66OhoevToQVlZGfv27WPJkiXY2NhgZGTEu+++y0svvdQow1Amk+Hv78+sWbP45JNPWLx48U39iG8HlpaWBAUFcfLkSfr164dSqSQoKIizZ8/Sp08f/P39+fnnnzE2NpZEYv/KQDQyMiIyMpLu3buze/du3n77bQYOHMiwYcPw8PAgLy+vK/jqANja2koiriLdXnQV6boXjaMrEG4BOkMgLHrGdqbKaFtCq9WyfPlypk6d2mTPa0egoKBAqgi1ZkVYzNLeClVVVZiYmEiCWc7Ozpw7dw4fH58mx1NTUyPRoAVB4Pz585I6rgiR4vrnn3+yZ88eJkyYQGJi4m1v+sQA4NChQ+zatQtHR0fuu+8+goKC2nwj+b8MvV5PVlYWEydObPJzYpBWW1vL7t27GTVqFKtXryYzM5O0tDQ0Gg3Z2dn4+PgwfPhwHB0dG62SdhQEQeDs2bPY2dlJiRpBEMjOzqa2tpawsLCbbviv/a9SqcTb2xtvb29JC8JgMFBRUUFRURFpaWlSD60oSBQeHo6fnx9mZmaNzuW/HkMU6woODpbscHQ6HeXl5ZSVlXH58mX27NkjBYOiNZKvry8+Pj7SetPeLQPXnoe9vT29e/cmMTERrVYrqW8vX76c6upqPDw8iImJISwsDCsrqxY94yI9vry8vFnKvu0BsX1DVNxevHhxm1aBr4WFhQUhISGS6nddXR0LFizA3d29yePLZDIGDBjAa6+9Rl5ensT+MTIyYuLEifz6668sWrTopu+K4OBgsrKycHR0JC8v7zov77sRop9yXl4ezs7O5Ofnt7kImJh8cHJyYuLEiYwZM4b09HS2bt3K7t27eeWVV3j55Zdxdna+4XmWyWSEh4czdepUPvzwQxYvXoy9vX2rMS8GDBjAihUr6Nu3r6Qe/dtvv5GYmIiZmRmWlpZUV1fj6elJRkYGsbGxja5tpqamDBs2jPj4eFauXMmbb75JYmIi2dnZXcFXB8DU1JSGhgbpz1ZWVtTU1FwnDNmF69EVCLcAdXV1GBkZdWggnJ6ejoeHx11vZ9AciIJONjY2hIeHd/RwbkB+fj5mZmbSprS1oNFomh0I29jYSJl9pVLJyZMnbynmdvr0aQIDA7G0tMRgMLBt2zZGjx4t/bvBYODy5cv8+OOPeHh48Oqrr9429VGkb+/YsYMjR44QHh4u2Xl0BhrovY6SkhKp7+xaiNUttVpNSUkJ6enpXLx4keTkZKqrq8nJycHf35/Y2Fi+/fZbZs+e3eFq+U1Br9ezceNG7r//fonuKAgC69evZ+TIkbfF2BDnu9jr6+joSFhYmFQlLy8vJy0tjV27dvHf//5XUmaOjo7GxcXlln3+1/6bsbEx3bp1o1u3boSGhiIIAjqdjpqaGioqKsjIyODEiROsX7+ehoYGbGxs8Pf3Jzg4GE9PTywsLDA1Ne2QirGJiYlUxR43bhxVVVVkZWVx8uRJNm3ahJmZGZGRkcTExODs7HzL62JkZISPjw8ZGRktVvZtCxgMBs6fP8+PP/5I3759GT58eLuKoNXX1yOXyzlz5gxxcXE89dRTzRZnNDMzY9SoUfz+++888cQTUkIiMjKSjRs3cvHixUZ7UGUyGb6+vmzZsgVPT09JWKmj78WdQCaT4efnx+XLl/Hx8SErK4uIiIh2Pb6JiQkRERGEhYXx0EMPsWLFCqZPn87w4cMZNWoUwcHB1z3HMtlVP2K1Ws0nn3zCokWLGlUNvx2I1lyFhYW4ubnh7e1NZWUlVVVV2NnZERoaSkpKCuHh4Zw9e7bJfYVMJsPOzo7HH3+c1NRUvvvuO3JzcyWq9d08b+42mJqaUl9fLwW+JiYm14lMduFGdAXCLYBKpcLU1LRDe3OPHTtGXFzc/8TCUlVVxR9//MFzzz3XKc+3srISJyenVhctq6+vb5Y9lCic8ueffzJmzBiJOteU4JVOp2Pv3r1MmzYNgMLCQmpqaggKCgKuVqM3bNjAqVOnmD59OuHh4bfVRyUIAiUlJWzZsoWzZ8+SkJDAK6+80qhaZhfaDpcvX8bX11eqkFZXV1NYWEhKSgoXL16kuroaOzs7goKCGDp0KGVlZTz//PNS9Sc9PR07O7tb2q10JARBkFShRQEgQRDIz8+nuLiYHj16tOqck8lkmJubY25ujoeHB4MGDUKj0VBaWsrp06f5+eefUalU+Pr6Eh8fT0BAQIv76cV+Q3t7e+zt7fH395eCY/FYFy5cYP/+/eTl5QFXKbT+/v50794dBwcHbGxs2j3ZJJfLsbOzw87Ojh49elBfX09JSQknT55k2bJlqNVq/P39iYuLw9fXt9FNskwmIzQ0lOTkZPr06dOu4/8r6uvr2bBhAydPnmT27NmSuFB7QGQ0fP/992g0Gtzc3OjWrRsajabZ3yGTXbXv2bZtGzk5Ofj4+ABXkw0TJkzg119/ZfHixY3uaTw9PSkuLqZXr16cPn2aoUOHttapdRj8/f05fvw4o0aNYseOHR02DrlcjrOzM0899RTW1tYcOHCA9evXU1tbS2JiIr1798bR0VGqKCclJaFSqfjyyy+ZN29eqxRCjI2NiY+PZ9++fdx///2YmZkRGhrKyZMnGTx4MGFhYWzcuJFp06axdevWZp9XWFgYr776Ko888ghvvPEGjz32GN27d+9KfLcTTExMJLcDpVKJQqHAYDBgMBg6emidFl2BcAtQW1uLubl5hz3QWq2WrKwspk6d2iHHb08YDAY2btxIYmJiq/bGtBYMBgMqlQpbW9vrKMV3CnGz25yKcE5ODm5ubuTl5REVFUVpaSkmJibY2Njc9HcKCgrQaDTShmjnzp3069cPY2NjMjMz+e677wgICODVV1/FwsKiRdddzDiWlZWxceNGzp07J1HzmtPz3IXWg3gvTp06haOjI+vXr+f8+fNUVVXh5OREeHg406ZNw8XFRapu5efno1AoJLVeQRD4448/GDZsWKcW5hMrv6NGjbqu8rt+/XqGDh3aLD/uO4Goeu3l5YWnpyejR49GpVJx/vx59u7dy/Lly/H09KRPnz50795dSnK19HkQg2NjY2OsrKzw8fFh2LBh6HQ61Go1V65cISMjg9WrV1NeXo5SqcTX15fw8HC8vLxwdHRsV79jsU/S09MTDw8PxowZQ01NDSkpKezevZv//ve/ODo60rNnTyIiInBycpI2/t7e3mzYsKHDqJWCIFBaWsrXX3+Nvb09r7zySovXwzs5tlarZevWrezZs4cZM2ZgZ2fHxIkTUSqV5ObmtogybmpqytixY1m3bh3PPvusVBUODQ1l/fr1pKWlNdo6YGZmhlwux9bWloKCgnuC5urg4EBlZSX29vaUlpZiMBg6NEBTKBQ8+OCDko3cI488woEDB3j33Xdxd3dn2LBhUvvQyJEjKS8v54cffmD27Nl3rEsiJknef/99JkyYgKmpKYmJifzyyy8MHjwYT09PSkpKsLKyQqfTXWfFdavvtbGxISYmhv79+/PTTz8RFhbG5MmTO4S18r8GU1NTSRBOqVRiZGSEwWDoqgg3gc67u+mEqK2tbValrq2Ql5eHubn5PW+bJGbC09LS+Nvf/tYpF87a2lp0Oh21tbWt2scm9ubeKhAWBIHi4mI8PDxwcHDAxcWF48ePExwcfNPrJQgCe/bsoW/fvigUCtRqNcnJybzwwgv89ttvHDhwgIcffpiwsLAWbw5EAZ2NGzdy+vRpBgwYwOuvv465uXmnvH/3IkS6c0VFBampqRw7doz169czePBgYmJimDp1Kh4eHtIG6tr7IggCO3bskJIicJVxUF1dTffu3TvkfJqLK1euUFVVdR3NsaioiMzMTGbNmtXufbQKhQIbGxsSEhJISEigrq6O1NRUDhw4wIoVK/D19WXgwIEEBgbekTq6+HvGxsbY2NgQGRkpXQO9Xk9hYSGXL1/m6NGj/PrrrxgMBskCKSAgAFdX10b9lNsC4nWxtbWld+/e9O7dm4aGBi5fvszx48fZsWMHxsbGxMTE0LNnT+zt7SVqeFOJvbaAwWDg3LlzLFu2jHHjxtGvX792C5ZEccJvvvkGBwcHXn31VWxsbNBqtdjZ2UlU1pYEpTKZjJiYGDZv3kxWVpaU6BKrwmvXriUkJOQG5o/YEqBWq9FoNDQ0NLR5UqmtoVQqpWSSVqulurq62TTztoD4XMycOZOvv/6aHTt28MADDzB+/HjOnDnDunXrqK2tJSkpid69ezN9+nS+/PJL1qxZw/3333/H81JktF28eFFKmKnVakpLS7G3t8fW1pby8nLc3d3Jyspq9t5TLpfj4uKCpaUlr732GqtWreLf//43jz/+OG5ubl17gjaETHbVMqmqqopu3bp1VYSbga5AuAXo6EA4OTmZyMjIDjt+e0Gv17NixQruu+++TvviFbNtGo2mVb3y9Hp9s7yqdTodFRUV6PV6bG1tsbKyIjU1laSkpJu+ZOrq6khOTubll18GrtLsrays+PLLL3F2dua1115rcf+RKLC0fft29u/fT58+ffh//+//3bG1UheaBzFxkpeXx4kTJ0hJSUEQBAICAujRoweFhYX87W9/uyW9Xa1Wc/78eSZMmCBVg7du3cqgQYM6tVqsyBwZMWKENE5BENi8eTMDBw7sUIE9cf6bm5sTGxtLz549qamp4dy5c6xfv56qqioSExPp27fvDcJjd3pMIyMjPDw88PDwoH///uj1esrLy8nLy+PcuXMcOHAAlUqFg4MDYWFhhIaG4uLigqmpaZuLcInfbWpqSkhICCEhIWi1WvLz8zl58iTffvstDQ0NXLx4kWPHjtG3b992qyRptVo2b97M0aNHeeaZZ/D29m63dUyn07Fv3z42bNjA/fffT2xsrPTcGhkZERoaKvk7txSmpqaMGzeONWvW8MILL0jJj5CQEORyOSkpKTfsLcQ+4cLCQmxsbCgoKOjUOgHNgZGREe7u7uTm5mJnZ0dpaWmHBsLwf73Djz32GEuXLmX16tVMnTqVhIQE4uLiyMvLY+fOnbzxxhsEBwczZMgQVq1axZ9//smwYcPuaN2QyWQMHDiQ3bt3ExYWhqmpKREREZw4cYLhw4cTEhLCuXPniIiIIDk5mejo6GZ/r6urK/n5+cTGxjJz5kyOHz/Ohx9+yPjx4+nTp0+rWld14f8gk8mwtramuroauDrnjY2N0Wg0/xPaQreDrkC4mRAl5DvKINxgMHD27FlmzJhxTwcYgiBw5MgRlEolERERnfZcKysrsbW1pbS0tFUXF71ej0qluqklhoi6ujqpIh0QEEBDQwN5eXn4+fk1+nlBEEhLS8PNzQ0bGxt0Oh3Lly9HrVbz9NNPEx8f36IXkxiAHThwgC1bthAZGdnVA9xOENeiy5cvc+TIEbKysrC1tSU6OponnngCBwcHjI2N2bdvX7Or+ydOnCAoKEha3yoqKrh06VKT/ebtDVHZGv5PjbWgoICcnBzmzJkjfa60tJTU1NRO10IiblB69+5NQkICxcXF7N27l3//+98EBQUxfPhw3N3d22SDqFAocHJywsnJiaioKKm1o6ioiHPnzrFixQqJMtq9e3fCw8NxdnbG0tKyXaqhxsbGeHt74+XlxdixYykrK2P16tV8+umnbNu2DX9/f3r16oWfn1+bUZSrq6v57rvvMDIy4sUXX2y3ZJ7Yuy/2lr/88stSf6gImUxGcHAwhw4dIi8v77Y8cKOioti4cSPp6emSpZeoIL1u3TpCQkKuo9uKgfCBAwek4PFuD4TFc8rMzMTb25srV64QEBDQ0cMCrlLRn3jiCT799FN+//13xo8fLyldP/TQQ9TU1HDy5ElWrFiBSqXiP//5D5aWlvTu3fuOntHIyEjWrl1LVVUVtra2JCYm8uOPPzJs2DAiIiJYvXo1DzzwALt27WoRldzHx4ddu3YBVyvEcXFx+Pj48M0335CRkcH999/foYWlexliICwIAgqFAqVS2agFVheuoisQbgHKy8ub9GdtS1RVVVFTUyNZINyrUKlUbNiwgfnz53fqvsTc3FycnZ0pLCxs9UBYrVbfshKuVqtRKpUcPnyY0aNHU1lZiZmZ2U3HIggCu3fvZuDAgajVar744gtqa2t5//33W2wDotfrSU1NZfXq1Tg7O7No0SLJ/qELbQNBEKiqquL8+fMcPXqUgoIC3N3dSUhIYPr06VhYWFxXyRMEgZSUlFsqiMPV+7l3714eeOABqRp84MABevbs2WqMDDGIFX2vr/2pqamhuroatVqNWq2moaFB+qmvr8dgMEiql3q9HkEQpHNNSUlBLpezdOlSTExMMDY2luyedu7cibW1Nba2tlhYWKBUKqVnROx/7KikjUKhwNXVlalTpzJmzBiOHDnCl19+ia2tLSNHjqR79+5ttv5dS9+2sbEhKCgIvV6PRqOhoKCAlJQUVq9eTUVFheSDHBERgaura5u3OoiU3W7dukk9kc8++ywpKSls376dwsJCfHx8SExMJCAgoFW0B0Q68tKlS4mNjb2h17wtIQgCFy5c4PvvvycxMVFSOG/snIKCgti2bRvV1dW3FQibmJhIVOiXX35Z+v2QkBBkMhnnz5+/oSrs4eFBQUEBQ4cO5cKFC/Tr1+/2T7aTwN/fnzVr1jBgwADOnj3L4MGDO3pIEszMzHjqqaf46KOPJB9ocZ2ytrYmKSmJPn36kJWVxfr163nrrbckW6Zu3brd1jtYqVTi5+dHSkoKffr0wcvLC41GQ3FxMc7OzlRUVEi0fFFRujlwcHCgvLxc+rNMJpP2C2vWrOH9999n7ty5nUIZ/l6Dk5MTpaWlwNXrbmFhgUql6uBRdV503kijE6K8vLzD+uUuX76Mt7d3pw4O7xSCILBhwwbi4uJwdXXt6OE0iby8PGxtbTEzM2tV+rZer6e+vv6WlM6ysjJsbW05ceIETk5OnD9/XhLVaAyiWrCZmRlvvfUWycnJvPjiiy0KggVBoKioiF9++YWKigpmzJghWWp0vchaF2LlU6TSHjx4kOLiYvz9/Rk4cCBBQUGYmJjc9No3NDRICuK3ujc5OTkYDAa8vb2Bq2yDo0ePsmDBgmaPU/z/uro6KioqJE/coqIiqqqqqK6uRqVSYTAYJDEPMzMzTE1Nsba2lgJWkZ5rYmIiBbYKhQKFQoFcLpfmt8FgoKSkhOzsbBYtWoRCoaChoYHS0lL27NnDI488gk6no6SkhAsXLqBSqairq6Ourg6tVotCocDS0hJbW1ucnZ1xd3fHwcEBJycnrK2t280fWdykDBw4kH79+pGSksK6deuQyWTcd999BAcHt0vArlAosLCwICAgAH9/f8aOHYtWqyUnJ4eUlBSpYuzk5ERkZCQhISG4u7tL76O2GJ+rqyvV1dUYGxuTmJhIr169qKurk8S2li9fjoeHB3369CEkJERaM1sq8JeSksL333/P9OnTiYmJaZeEniiKuGXLFvbs2cPs2bOb1HeQyWT4+/tTXV1NfX09Wq32toL1iIgI1q9fT2pqKuHh4chkMuRyORMmTGD9+vWEhoZet8cwNzdHq9Xi5OTEnj177gnBLHt7eyorK3Fzc2Pr1q0dLph1LcT1YN68ebz//vtYWlqSmJh4nZ2SsbExAQEBLFiwgLFjxzJv3jyJ/TN8+HDCwsJarD2QlJTEhg0b6NWrFwqFgvDwcM6cOcPQoUNxcHAgLy8PJycnCgsLmx0IW1lZoVar0el0181VExMTpk+fzpEjR3jvvfd45JFHburz3oXbg6OjIxkZGcD/zana2toOHlXnxb0bVbUB6urqOqTnTBAETp48SUxMTLsfuz2Rl5dHcnIyr732WqdeFEVrIEdHx1anAhsMBrRa7S2rzNnZ2Zibm9PQ0ICTkxPbt2+nX79+jY5FpJvX1NTw7bffMnbsWBoaGoiJiWnW2MVK3pYtW9i3bx/jxo2jT58+dyT004XGIQaTKSkp7Nu3j6KiIvz9/RkxYgSBgYFSH+ytrntNTY0U3NzqeHv37qV///5SNTglJQV3d/cb5rYoxqXX66mqqqKgoICCggKys7MpLy9HrVYjCAJWVlbY29vj6OiIr68vNjY2WFtbY2Vl1aTqfksDmD179jB06FDJ0kYQBC5dusTw4cObrPKI7QdVVVVUVlZSXFxMeno6JSUlUt+9lZWVZEfk5eWFq6srJiYmUiDe2vNe3OBGRUUREREhVWWNjY257777CAgIaLcKtphcMTU1lQLjcePGUVdXx5UrV0hOTmbZsmWSUGCPHj0ICwvD3t6+VQNjpVKJpaUlJSUlUq+uhYUFcXFxxMXFoVarSUtL48CBA6xcuRI3Nzf69OlDWFgYSqXylsGNXq9nx44d7Ny5k/nz5+Pl5dVuVGiVSsW3334LwGuvvdYsGraYHFYoFJSWluLl5dXiYysUCiZPnsyaNWvo3r27VH0OCQlh7dq1ZGRkXBeQm5mZYWtrKwmXNTQ0YGpq2uLjdiZYWVkhl8sxMTFBpVJRU1NzgybHtYHntf9tD8hkMmxtbZk/f74UDP+1TUx8RgMDA3nnnXf48ccfSUhIYOvWrfzyyy/07duXfv363ZDUu9nx/P39KS8vp6KiAkdHR3r16sXKlSsZMmQIwcHBnD9/nvDwcM6dOyfR6m8FCwsLTExMpATaX8feq1cvXF1dWbp0KcOGDWPgwIGdJiFxt+OvFeCuQLhpdAXCLUBdXV2HiDfV19eTmZnJ1KlT79nAQ6fTsXr1aiZMmNDpG/q1Wi2VlZUoFArs7e3bPRAWBEFSDtVoNFhaWpKXlydZIv0VGo2GFStW4OTkxPPPP8+ZM2cICwu7ZVJHDHxSU1P55Zdf8Pf357XXXsPGxuaenYcdAbHfOjMzk71793L58mU8PT0ZPHgwAQEBt0VHvXjxIj4+PrdkkKhUKtLT05k0aRIymQydTseOHTuYMmUKWq0WjUZDUVERWVlZZGdnU1hYSH19PaampnTr1g0XFxcSEhKwt7fHysoKCwsLyZ6lLaFSqThy5AivvPKKdKy6ujr27NnDokWLmjy+kZERtra22NraSlVwETqdDpVKRXV1NQUFBVy6dImjR49SUVGBsbExnp6eBAcHExgYKDFCWnPzJtKWxarr2bNnJZuhKVOmtLiNobXGBFerg6K4lcFgoKqqipycHE6fPs2uXbvQ6XQEBgYSFRVFQEBAq8wFsY/z2vskfp+FhQU9e/YkJiYGlUpFRkYGBw4cYPXq1Xh7e9O3b18CAwMbfX7ENbGwsJDFixdjb29/22NsCQRBIC8vjy+//JKYmBjGjBnT7MquiYkJPj4+ko/07QTCMplMCoDPnTsneWwrFArGjh3Lhg0bCAwMlBI+crkcT09PSktLMTU1pby8vFOztcRKu/hTX19PRUUFFRUVVFdXU1tbi0ql4uLFi3zyySecOnWKt956S1Im1+l0EvPE2NgYCwsLLCwsMDc3x8bGBltbW+zs7HBwcJAYK42p8N8pRBrxM888w5IlS3jiiScIDAy84RgymYyoqChGjRrF/v37WbBgAZWVlezevZt//vOf+Pv7M3ToUIlNeLMxmpiYEBUVxYkTJxg2bBje3t5UV1dTUVFBWFgYq1at4v7772fVqlXNrqArFApJkKwxi0mZTIaPjw8vvvgiS5cupbCwULJY6sKdQalUUldXJ/1ZDIzvBUZHW6ArEG4BNBpNhwTCoiDTvSosIAgC586do76+np49e3b6B7Wurk6qirm5ubXqd4t9kLcKhIuKitDpdHh6elJRUYGJickN80OsXL///vsA/OMf/8DIyIj9+/fz2GOP3XIclZWVrFy5koKCAmbNmiVVpbrQOtDr9RQVFXHw4EFOnDiBra0t/fv3Z/r06Xck1CMIAqmpqYSGhjb5HYIgcPbsWfz9/TEzM6OyspL09HROnz6Nubk5ZWVlwNVeLx8fH2JjY3Fzc8Pc3LxDe2wFQWDfvn1ERERIND1BEDh27Bh+fn535Ot9bZDs5eVFQkICBoOB+vp6VCoVmZmZXLhwgd27d6NWq3F2diY0NJSwsDAcHR1vKXLXEoh2QmFhYRw6dIgPP/yQ2NhYRowYgbW1dYeuk3K5HDs7O+zs7IiIiECr1VJVVUV6ejqHDx9m1apVWFhYEBoaSlRUFK6urrclctW9e3fOnj1L//79b/oZmUyGlZUV0dHR9OjRA5VKRVpamkSf9vf3p0+fPvj5+UmiMd988w12dnY899xz7fZOFwSB8+fP891333H//ffTs2fPFq2nRkZGeHt7c+HCBUpLS297UyuXy7nvvvv45ZdfCAsLk1oswsPD+fXXX8nNzb0u8eDv709KSgqOjo6UlJR0ikDYYDBQV1dHbW0tlZWV5ObmUlhYSHFxMeXl5Wi1WollIbZd2NjYYGlpib29Pb1798bMzEyyHevZs6f03WICuKGhAbVajUqlQq1WU11dTVpaGpWVlVRVVUl6BXZ2dnh4eODl5YWHhwc2Njatsg7IZDI8PT158sknWbp0Kc8++2yjrAW5XM6gQYMoKSlh2bJlzJkzhxkzZjB+/HhOnz7N8uXLMRgMDBgwgJiYmEbfLTKZjN69e7Ns2TIGDx6MkZGRlIiLi4ujsrJS8mCura1ttmiss7MzJSUlTVaR7e3tWbhwIT///DNLly5l9uzZ7ebZfa/C3Nz8ukDY2tqaoqKiDhxR50ZXINxMiAtjewfCgiBw5swZwsPD71m5+fr6etatW8esWbPuih5oUaiquLiY8PDwVv1u0e+tqXmm1WqpqKiguLiYHj16kJ6eTkBAwHXX7tpNl1qtZurUqZibm5ORkYFCocDd3f2mLxq9Xs+RI0dYu3YtAwYMYNasWe1mX3KvQ1R8PnPmDPv27aO2tpaEhAQWLlyIvb19qwSXer2ezMxMxo4de9Mx6PV6iouLWbNmDTY2Nrz11lvU19dz5swZxo4dS79+/fDw8MDMzKzdvGabi/r6enbt2sXChQulMel0OrZu3crcuXNbPVkjl8tRKpUolUqcnJyIi4uTevmzs7M5d+4c33//PbW1tXh4eBAbG0tQUBAODg6tcs1MTU1JSkoiJiaGTZs28c9//pMJEyaQkJDQKdZLmeyq/YuoSt2nTx8aGhooLi7m7NmzkvCWq6sr0dHRdO/eHWdn51u+z0SF3z/++AOdTtescxWDYtGuqra2lrNnz/LHH39QUlKCn58f6enp9O3blwkTJrSrP/CxY8dYuXIl8+bNw8fHp8VzQya7aklz4cIFCgsLb3ssIhXWwsKC5ORkKflsYmLCsGHD2Lx5M0888YQ0Pk9PT7Zu3UpMTAyXLl1qdwtHvV5PZWUlpaWlZGVlcfnyZYqKilCr1ZiYmGBjY4Onpyeurq706NEDZ2dnzM3Nr9MW+Ov6ZWNjw65du4iOjqayshJnZ+dmj0dcP/V6PVqtlqKiInJzc0lNTWXr1q3U1dVha2tLYGAgoaGhuLm53XZgJ5PJCAgIYNasWfznP//h+eefb1SwVS6XM2XKFJYuXcq6deuYMmUKlpaW9OnTh169epGTk8Off/7Jxo0biYiIYNCgQbi7u183/11dXSWdBRcXF3r16sXvv/9O//79sbW1pbi4GBsbG0pLS5sdCPv4+JCVldVkIguuUvAfeeQR1q9fzwcffMAzzzzT5UBxBzA3N0en00mtDHZ2dqSlpXX0sDotOv4tepdAo9EAtHsgbDAYSE5OZtq0affkoiD2+nl7e9/W5qAjUFpaioODAxUVFRKlqrXRVEW4oaGB2tpaMjMzmTRpEsnJydf1BxsMBnbt2sWff/7JI488wrJly6TK1o4dO27aiyMIAhUVFSxbtgy1Ws3ChQtxc3O7K+5JZ4a4ccrIyGD79u1kZWURFBTElClT8PX1bXUqsUqlQq/XY21tLYlZGQwGioqKuHDhAufOnaOgoACVSkVBQQFTpkzB398fIyMj3n//fR588MFOzT45cuQI3t7e0oZQTBba29u3i6q+qGwsVk26d++OIAio1WouXLjAsWPH+O233zA3NycmJobY2FhJ0fV277OoGjtt2jSSkpJYtmwZBw4c4OGHH8bZ2blTPaNif7GnpyceHh6MGDECjUZDRkYGJ0+eZNu2bcDVam9MTIzESBB/91o4Ojqi0WhQqVQt8nsVAx8rKytJaOv8+fP87W9/w8PDg6NHj6LX6+nTpw+urq5tmugxGAzs3r2bLVu2sHjx4tu+XzLZVQulXbt2kZ+ff4Od2LWfuxUUCgUTJ07khx9+IDIyUqoK9+zZkw0bNlBWVoajoyNwNWisra3F3d2d/fv3twm98tp1qqysjJycHDIyMsjKyqK8vByZTIadnR2+vr6SmKajo+N1CtstGVO3bt0oLi5m2LBhnDt3rkXndO3zb2pqiqWlJX5+fvTv3x9BENBqteTl5ZGWlsb69eul/UJMTAzh4eE4OTm1aL7JZDIiIiKYNGkSn376KS+88MINjBBxTI899hgffPABe/fuJSkpSfp7X19fHn/8cWpqajhw4ACff/45lpaWjBgxgoiICIyNjTExMaFHjx4cOXKEcePG4ePjQ1lZGSqVipCQENLT06V+4ebu1ZydnTly5Eizr+mECROwtbXl7bff5rnnnpOezS60DCJjS61WY2pqipWVFTU1NR09rE6LrkC4mairq5MEFtoTomR9R9k2tTUqKyvZuXMnixcvvmtot1euXMHDw4O8vLxWD4RFa5imEi41NTVoNBpJrGb//v14enoCV4PkVatWkZ2dzYsvvkheXh4ODg7Y2dlRU1NDRkaGZJNzLfR6PcePH2fVqlUMGzaMQYMGdYlh3SFEr9bDhw+zd+9elEolAwcOZNasWW1G/RIEgYyMDFxdXamtreX48eMkJyeTl5cniR8lJSXh4eHBjh07UCqV9OrVC4AtW7bQo0ePDhEEbC4aGhrYunUrjz/+uLReGAwGNmzYwPTp0zuENSNuai0tLYmOjiY6OhqdTkdeXh7Hjh3j888/ByA2NpaEhAScnJxuO/khk8lwc3PjhRde4MCBA7zzzjsMHTqUwYMH39R2pyMhXhtzc3MiIyOJiIiQkjLnz5/njz/+oLi4GEdHR2JjY4mMjMTW1lZae+RyOfb29pSWlrYoEP4r0tLS+Pbbb3n99deJiIiguLiYo0ePsnTpUhQKBYmJicTHx2NjY9Oqc0gMgnft2sXLL7+Mra3tbd0jUURPr9eTkpJCaWkpGo1GslEyNjbGxcWF7t27ExoaKgVKNzuWWG23t7fnxIkT9OrVS7pPvXv35s8//5QU58U+WYVCQXFxMXq9/o6ZCGIvb11dHdnZ2Vy6dIm0tDTKy8sxMjLCzc2NgIAAJkyYgKOjI7a2ttLz3hpz3N7eHq1Wi5WVFSUlJXcsAnZtMG5qaoqfnx++vr6MHDkSjUbDlStXOHnyJHv27EEmkxETE0NcXJzEjLjVOclkMhISEqioqOCzzz7jueeeu2GdFu/VU089xTvvvIOLi8t1wmdiMm3EiBEMGTKE9PR0tmzZwsqVK+nXrx/9+vUjPj6er7/+mrFjx2Jqaoq/vz/nz58nNDSU3377jbFjx7JlyxZGjBjRrPsgKnQ3t69YLpczcOBAbG1tef/995k3bx6+vr6dbl3r7BD3kGq1Gjs7O0xMTGhoaOjoYXVadAXCzYRGo2nV/q/mQFRBdXNz6/QCUrcDQRD49ddf6d+/f7uJldwpRLETf39/DAZDsylCzUV9fT1yubxJAZW8vDxUKpVkA2NsbIytrS3V1dV88803WFpasmDBAszMzFixYoVESzp27BihoaHXVftEf9pffvmF0tJSFixY0CRtugtNQ9zg5eTksGPHDi5cuEB4eDiPP/447u7ubRaoGQwGamtryc7OZsWKFeTm5lJaWir1R3p6el63yddqtZw+fZpnn30WmUyGVqvl0KFDPPnkk5363p87dw5ra+vrhILS0tJQKBQEBgZ24MiuQrx2xsbG+Pj44O3tzYQJEygsLOTo0aP85z//wdTUlP79+xMdHS0p2LYURkZG9O/fn/DwcFasWMGpU6eYNWtWp6+giMJMbm5uuLm5MWjQIFQqFbm5uRw/fpydO3cil8sJCwujZ8+euLu7ExgYyIULFwgICGjx8QwGA0ePHmXdunXXbapdXFwYO3YsI0eOJC8vT0oqODg40L9/f8LCwu7Yo9hgMLB371527drFggULbisIFlsptmzZwvHjx6UkgYeHB7Nnz8bIyEii6BYUFHD+/HnWr1+Pp6cnEydObHI+KBQKxo8fz7fffktsbKyUSElKSuJf//oXY8eOleanq6urZIXT0uq8WLmuq6ujsrKStLQ00tPTyc3NxWAw4OLigp+fHxMmTJDsy9pacM/IyAgbGxupSiYKALYmxPErlUq6d+9OcHAwOp2OwsJCTpw4wRdffIFCoaB379707NnzumC/McjlcoYPH05VVRXffvstc+fObbQw4+DgwOOPP84XX3zB4sWLbyiiiL3T4eHhhIaGUlRUxM6dO/nXv/5FUFAQZWVl5OXl4enpSXx8PPv27eOxxx6jrKwMe3t7iouLm90maGdnJzHYmrtXkslkREdHY2Zmxmeffcbs2bPp3r17p17XOiPMzc1Rq9UAXYHwLdAVCDcTHSWUdfr0aaKiou7JRUDs92mO12lngV6vp7CwkOjoaCwtLVu9iq3RaG5Z2SkoKKCyshJPT09qamokVc/PP/+c+Ph4RowYgZGREdXV1WRmZvLwww9Lm7JHHnlE+m5RVOnHH3+kb9++PProo12KjbcJ0RLl5MmT7N69G4CBAwcybdq0O95Q3ww6nY7S0lJSU1M5ffo0JSUluLi4kJ+fz9///ncCAwMbnUuCIHDhwgXs7e1xcHAAID09HVtb207NPNHpdGzevFlSuIarz+OGDRsYO3Zsp9RQEDedIk14zJgx5ObmsmfPHjZt2oSfn5+k0trSKptMJsPBwYG5c+dy9OhRPvjgA8aOHUvfvn07Re9wcyDSl0WKuVarpaysjDNnzrBmzRoqKirQarVYWFgQHx8v9dE3B2I1dufOnSxcuJBu3brdQCe9NmExadIkMjMz2bVrF2vXriU4OJikpCS8vb1bzAQTBIHDhw+zbds2Fi5ceFv9joIgcPnyZb766itiYmJ4+eWXMTExkXr9bGxsrgsufHx8JK/lY8eO8eGHHzJ+/Hj69Olz02smVoVPnjxJQkICcDV4CQ8PZ//+/YwcORKAgIAALl++jKWlJdXV1bcMhPV6PdXV1RQVFZGSksKlS5coLS2VvKoTEhKYNm0a5ubmHaY/4eXlRUFBAba2tpSWlmJtbd2mx/vrWjBq1CgKCgrYv38/77zzDu7u7gwaNIjAwMCbvodF+6tvv/2WFStW8MADD9yw7ol9xZMmTeKzzz5j8eLFN9hDiRCTHDNmzGDcuHEcOHCA7du38/HHH/PUU0/h4+PDL7/8glwul+i1ZmZmUs//rWBkZIRSqaS6urpFRQOZ7Kql11NPPcUXX3zBjBkzJIXzLjQPFhYW1wXCWq22SzX6Jrg73padAB0RCIsb1qFDh7brcdsDOp2OlStXct99991V1W5RSdJgMNwRVe9mUKlUTW4MBEEgJycHtVpNREQEaWlpWFhY8MEHHzB58mTi4uKQy+VSkOvr64tSqSQnJweZTIa7u7vUx/T7779z8uRJ5syZg7+/f9cC2UKIfW3FxcXs3LmTEydOEBgYyEMPPYSnp2erVjXEY4nV5hMnTnDu3DkMBgMhISGMGjUKHx8fqT/Nz8+vyc377t276d+/vzRXtm/fzuDBgztte4IYFGi12uvofllZWdTU1BAREdHBI7w1RNqkv78/fn5+1NXVceLECZYtW4aRkRHDhw+nR48eUr9mc2FkZERiYiKBgYF89913nD59mocffvi2abgdBVGwydXVFRcXF4YOHUpdXR1nzpzh9ddf56233sLW1paoqCiioqLw8PC4qa+zwWBg69atHDp0iAULFtzS5k4mk6FUKqWAvLa2lhMnTvDLL7+g0WhISEggMTFRUiRv6rvEtXf9+vU8//zzt2Wxd63N0qOPPirNeYPBQLdu3Th58mSjwYVIbxar2p988glyuZzevXs3Oga5XM7EiRP57rvviI6OlubeiBEjWLJkCQMGDECpVOLt7c2RI0fw9PQkOzv7OkaGuDaJjJRTp05x4cIF6urqcHR0JDQ0lIkTJ+Lh4YGJiUmHqc3/FQEBAaSkpODl5UVWVla7UnDFue7t7Y2Xlxf33XcfZ8+eZcOGDVRXV5OUlETv3r2l+3vtuIyNjZk1axYff/wxmzdvZvTo0Tes2zKZjMTERPLz8/n+++954oknmmSZiQmp4cOHExISwqJFi/jyyy9xcnKioaGBjIwMQkNDuXjxIr6+vly8eLHZ6uE2NjZUVVXh7u7e4mvk5+fHM888w6effopOpyM2NrZTzJ27AXZ2dlRUVABX54xWq202Rf1/DV2BcDOhVqvbvXdOtC8RRSvuFQiCQHJyMjKZrN0VKO8U9fX1KBQKCgoKbsvH8VYQM643W+wNBgNZWVkoFAocHR05deoU9fX1LF68+Dr6kMFgYP/+/QwfPhyZTMauXbvo06cPRkZGlJSU8MUXX9CtWzf+9re/dVkVtBCivUZmZiabN28mNzeX3r178+qrr7aqx/K1we/ly5c5dOgQ6enpWFhYEBMTw9y5cyVf2WsDQ0dHxyaTdiqVipycHGbNmgVASUkJJSUlhIaGtsq42wIGg4FNmzYxatSo63qDxb/rjNXgpiAGLH379qV3795kZGSwefNmfv31V4YNG0bv3r1bVCmTyWQ4OjqycOFCtm3bxr///W9mz57dqPfo3QCRQm1paUlcXBw9e/Zk4cKF1NTUcOrUKb777jvq6+sJDAwkLi6OwMBAad0Ue8aTk5NZtGhRi6ymxGfJysqKpKQk+vfvT2FhIfv27eODDz7Azs6OIUOGEB4e3uj9EQSBrKwsfvjhB+bPn3/byuE6nY7//ve/PPzww1IQLFKMLS0t0Wg0nDhxAoVCgYuLS6Pn4eDgwIIFC3jvvffw9/dv9HNwtSpsbW3N6dOniYuLk6jj3bp1k+xzHB0dqaysJD4+nqysLPr06YMgCNTW1pKcnMzBgwcpKirCycmJ6Oho+vfvj6ur600TFR0NMSm8bds2Bg0axMWLFzt0LGZmZsTGxhIbG0t+fj5//vknb7zxBpGRkYwYMUIS2BJhamrKk08+yXvvvYetrS19+/a94RrLZDImTJjA559/zsaNGxk/fvwtgyCZTCZ5pT/22GMUFRXx1Vdf8fnnnzNhwgRSUlLo3bv3DQKdTcHT05OcnJzber+I41mwYAEffPABQFcw3Ew4OTlRUlICXK0IGxkZodFobsoO+F9GVyDcTFRUVEiele2F9PR0/P39m8zk3Y3QaDT89ttvPProo3dddqqoqAhHR0fJuqi1F2SVSoW5uXmTgXBxcTFyuZwrV65ILypRLEtEdXU1JSUlBAQEoNFoSElJYezYsZw+fZr//ve/TJgwgcTExLsugOhICIKARqMhOTmZLVu2ADB06FDmzJnTZPLido4jWvMcPHhQoi0nJCQwZsyYJjfXorJnU2NJTk4mICAACwsLicIZFxfXqem0okfotW0ihYWF5OXl8fjjj9+1GyMx4AsODiYoKIjc3Fw2btzIli1bGDJkCH379m22NoVIvRw5ciT+/v58++23DBo0SPIFvVthbGyMm5sb+fn5REVF4efnx8SJEyktLSU9PZ2dO3fy888/4+zsTGxsLJmZmRQUFLBw4cI72vSJQbGbmxtTp05lwoQJXLhwgR07drBy5Uqio6NJSkqiW7du0jpaUVHB119/zaxZs/Dw8LhtYSxRBT0kJET6jjNnzvDPf/6TEydOUFRUxEMPPcTixYt55ZVXbjp+W1tbhg4dyubNm69ri/nr5yZNmsRPP/0kMRIARo0axdq1a4mJicHa2hojIyMsLCzIzMzk+PHj7Nmzh+LiYvz9/RkxYgR+fn5Nvrs6G7p164ZKpcLJyYmdO3dKwmMdBfG6ubu7M2vWLKqqqjhw4ADvv/8+vr6+jB49WtKZEIWv5s+fz7vvvouDg8N1c0X8PmNjYx599FHefvttfHx8mrVnkclkxMbGcubMGSZMmICvry9PP/00mzZt4vLlyyQlJXHlypVmXS/x+cnIyLij6+Lm5saiRYv46KOPMBgMxMfH3zXzrKNgY2NDTk4OcHUNNTIyQq1WdwXCjeDufTu2MyoqKtq1MisIAidPnryl/9rdBkEQ2L9/P15eXo2aw3d25OTk4ObmxuXLlyWaXGuitra2SeZBfX09WVlZaLVacnNzGThw4A2WMYIgcOLECUJDQzEzM+PYsWM4OTmxfft2UlJSmD9/Pp6ennfdte8oiII1+/btY9++fbi5uTF9+nR8fX1bLUklBtnZ2dlS5dfOzo6EhATGjh2LnZ3dLZNGgiCQlpbG+PHjb/oZg8HAgQMHmDBhAnB1Ph0/fpxnnnmm084HQRDYsmULgwYNknrnROrrtX93t0OsfsydO5eioiI2b97M66+/zpgxY4iPj282ZVomkxEUFMSLL77I999/z8WLF3nooYfavAeyrSCTXfW9vXjxIpGRkchkV9WknZ2dcXZ2pm/fvqhUKjIyMvj3v/9NXV0dERER7Nixg5iYGJydnVtMN29sDKampkRERBAWFkZFRQVHjhxh6dKlKJVKBgwYQPfu3fn2228ZMmQIoaGhd3S8PXv23EB5NTY2Zv/+/RQVFQFX23R69Ohx0+8QBIGdO3dSWVnJwYMHGTp0KHZ2djcwgEQKqqWlJWfPniUmJka65hqNhry8PDw8PFAqlWzevJlt27ZhYWHBsGHD8Pf3v6uC32thbGwstWWp1Wr0en2nSQyLSYxRo0YxcOBAjh07xpdffomzszPjxo3Dy8tLYoU9+eST/Oc//2HhwoWN2sdZWloyd+5cPv74Y1xcXCQWUVPHjo+P58svv2TMmDE4OzsTGRnJlClT+Oijj/j4448pLS2ltLS0WVZgTk5OHDp06I77U11dXVm4cCEff/wxQFcwfAtYWVmhUqmA/1ORrqur6+BRdU50BcLNRG1tLd7e3u12vPr6eqnX715CdXU1O3bsYNGiRXddNVjs2/Ly8uLUqVNtEgjX1dU1SVUuLCwkOzsbS0tLBg4cSExMTKPjPHDgAA8++CCCILB582aysrKwtbVl8eLFXVToZkIQBMrKytixYwfHjh0jKiqKBQsW4OTk1GpzV6fTkZuby4EDBzh37hx2dnb06tWLCRMmYGVl1aKNmUajoaysrEkv3ZKSEqqrq6V15dKlS9jZ2UmiWZ0RFRUVpKWlMXXqVGneVlZWkpqayuTJk++5uSwK2DzyyCPk5+ezdu1a/vzzTyZNmkRERESzqrsymQx7e3vmz5/Pxo0bee+993jyySc7var0zRAUFMTatWsb3UyLQerJkycZMGAAM2fOpKKighMnTvD111+j0+no3r078fHxeHl53bH7g1wux8HBgZEjRzJkyBCysrLYvn07b7/9No6OjkydOvWONv2CIFBcXHyDcF1wcDD3338/n376KYIgSMJTTeGnn35i5cqVUuKod+/efP311zckReRyOePHj2flypVERkZKFaS+ffvyww8/oFQqOXXqFOHh4SQmJjJr1qy7xunhZhArjeXl5RgbG1NdXd3p2tCu7flOSEjg5MmTfPPNNzg6OjJx4kS8vLzw9fXlwQcf5NNPP+Wll166gbkoJtimTJnC559/zssvv3zLNj8XFxf0ej0lJSW4ubkRGRnJhQsXSEpKwsrKip07d/L888/zyCOP0KdPnyaTkc7OzlRUVKDT6e4ocSxS9p999lmWLFmCsbEx0dHRd+V61h6wtLSkpqZGWouUSmVXIHwTdAXCzUR79wgXFBRgaWnZ6vY8HQlBENi4cSO9evXqdC+c5sBgMJCTk0PPnj2lF1RrQxRla2xxb2hoYPXq1ZL3a0NDQ6M9gCUlJdTX1+Ph4UFKSgp79+7l5ZdfZtCgQZ0m491ZIfblFhYWsnnzZs6fP09iYiJ///vfW9RreKvvLy0t5ejRoxw+fFgSs1m8eLHUY3w7xyktLUWpVF5nj/XXYx8/fpwePXqgUCgwGAzs2rWLgQMHdtrNhCAI7Nixg4SEBInSJQgC27Zto1evXvc0zUsul+Pu7s4zzzzDpUuX+OWXX9i+fTszZszAzc0NuHXvpbGxMePHj8fT05MPPviARx999I6rlR0BR0dHysvL0ev1NyShtFoty5YtQ6vV8thjj2FiYoKVlRWenp6MGzeOiooKzpw5w6+//kp5eTleXl4kJCTQvXv3RsWImgtR8CgwMJDy8nIKCgpISEjgq6++kiqmkZGRLa5G63Q69Hr9DcGFQqFg7ty5rFixguLiYgIDA3F2dm5yfD179mTZsmXAVds9FxeXRtcHsSosk8m4dOkSPj4+HDlyhO3bt3P48GHeffddhgwZwu7du7Gzs6OoqOiuD4QB/Pz8yM7OxsXFhdzc3E67LxH7iBMTE4mNjeX48eMsXbpUUjuPjo6mrKyMzz77jEWLFt2whxCrvFlZWfz444+S9dbNIJfLiYyM5PTp07i6utKjRw+WLVvGmDFjOHr0KMOHDyczM5OzZ8+ye/duHnzwQcm+7q9z3dLSEr1eLzli3Ol1cHFxYd68eVIwHB4eftetZ+0BKysryXtcVO/WaDQdPaxOia5AuJlo70D47Nmzd4USaktQWFhIcnIyf//73+/KhUv0alUoFG3mKV1fX99oIKzRaPjmm284ePAg3t7eEpW2MVr0sWPHiIiI4MiRI7zxxhs8/PDDDBky5K685u0FUQArJyeHDRs2kJOTw6BBg7j//vuljeOdVHjg6hpy5swZ9uzZQ1VVFT169JD8hW83+L0Wly5dapJBotPpOH78OI8//jgAVVVVFBYWdmqPRrVazeHDh3nllVekMdbW1nL06FH+9re/ddpxtxbEeREQEMArr7zCoUOH+Oijj4iPj2f06NHNoqXK5XJ69uyJg4MDX3zxBcOGDWPgwIF3FSPH3NwchUJBTU3NdQFYQ0MDy5Yto6GhgTlz5lxnFyb2Xzs6OjJo0CAGDRpETU0N6enpHD58mNWrV2Nvb098fDxRUVFS+0FL5pRYvV23bh2LFi3C2dmZESNGkJ6eztatW1m1ahUJCQkMGDBAUo9uzv2Cq++bayFS3qdNm8Ynn3yCh4cHNjY2TX5XWFiYpBjr5ubGE088cdP7bmRkxJAhQ/jwww+xsbHB29ubp59+mpCQEFQqFcHBwZSUlNCjRw+ysrI69brRHIiV0uTkZPz9/cnJyen0VpVi8iUxMZGYmBhJxC0iIoIxY8ZQXFzM999/Lz0L10IulzNp0iTee+899u/fT1JS0k3PVSaTERcXx/Llyxk2bBienp6o1WpsbW2llqxTp07x8ssvk5KSwvfff4+/vz9Tpky5IWEsl8sxMTGhrq6uVQo7MpkMDw8PnnnmGT7++GPmzp17S12M/0VYWlrS0NBAQ0MDRkZGXdToJtAVCDcDgiC0ayBsMBhITU1lypQp98zDbTAYWL16NWPGjLlrqzh1dXXIZDKqqqqa1RtzO9Bqtdcp/gqCQF1dHV999RX29vbExcVRVFRETU0Nbm5uN1jkiLRoa2trzp8/T0BAgKQc3YUbIQbAWVlZ/Pbbb1RUVDB8+HBmz559x7Zeok1VTk4OO3fu5OLFi/j7+0sCJK1pxyb2BzdGlRdRVFSEXC6XKP1HjhwhMjKyU/fY7t+/n5CQkOuCn927dxMREdHu4oUdCZlMJlFVIyMj2bBhA2+88QYPPPAAYWFhzRKt8fX1ZfHixXzxxReUlZUxceLEu0aI0djYGFdXV7Kzs6W5UF9fz48//ohOp2POnDlN2oWJ65+1tTVxcXHExsZSV1dHdnY2R48eZceOHRLVMjY2Ficnp2ZVchsaGvjhhx+YNGmS9E4wMjIiLCyM0NBQSkpK2LdvH++++y7e3t6MGDECLy8vjIyMbvrdYj9fbW3tDe9KhULBY489xvLly6V9idgzrVAobvheHx8fnJ2dKSgo4IEHHiAoKOiG44rvmAMHDrB161by8vKYM2eOpM47ePBgvvrqK/r374/BYMDe3p5Lly41eV3uFri7u1NWVsaAAQPYt29fRw+n2RArxEOGDKFXr15s27aNf/3rX/Tr14+cnBzWr1/PxIkTb0h6GBsb8/jjj/POO+/g5+fXpFaIm5sbKpWKmpoabG1t8ff3Jzc3F7lcjrm5OZWVlTQ0NBAREcHf//53/vzzT958800mTZpEfHy8VHEW+50rKyubZDC09Px9fHx4+umn+fzzz5k3b1672l/dDTAyMkKhUFBfX4+5uTkWFhbU1tZ29LA6JboC4WZAp9PR0NDQboGwSqWisrLyBiXguxnp6elUVFTQq1evjh7KbSM/Px8HBwcKCwvbxDoJQK/XS9Vm0Z5CpEBNnDiRuXPn4uPjQ25u7g0qkQBXrlxh7969PPTQQyQmJrJ+/fo26WW+F6DX67l8+TK///471dXVjBkzhqioqDsW1hEEgcrKSo4fP87+/fsxMjIiKSmJ+++/HysrqzZ5WYu9xvfdd1+j33+tOrRIiz58+DBz5szptJsHjUbDzp07mT9/vjTGuro69uzZw6JFizrtuNsSMpkMGxsbZsyYQWZmJsuWLePIkSNMmTKlWdZdoqXOd999x/fff8/MmTPvCh93MZC/fPkyUVFRNDQ08OOPP2IwGHjsscdaHNCLrS3du3cnODiYhoYGiouLOX78ON988w0NDQ2EhoYSHx8vCUU1FkDu2LEDR0dHyXbor8dwdnZm0qRJjBgxgtOnT/PTTz8hl8sl2nRj3yuTXbX2uXLlCs7Ozmg0GkpKSjh//jyZmZnk5+cTHBxMfX09b775pvSuMDY2xsnJCU9PT8LCwnB1dcXV1VVStZ49e/YNgZFGo+HIkSNs3rwZf39/Fi1aREpKCidOnCA2NhYADw8PzM3NycjIwNraGmtra/Lz8yXK5a0gJgT/+qPRaKipqUGlUqFWq9FoNNTX16PVamloaECr1aLX69HpdAiCIP1XvEbiPRc3/AqFAlNT0+t+lEqlNGbRQsbExOS6H0EQsLKykuwq7ybIZFetviZOnEi/fv1Yv349eXl5HDx4EBcXlxv8o2WyqzZr06ZN45tvvuGll1666b7W1NSUoKAgzp07R9++fYmLi2P//v14e3uTn5+PlZUVhYWF+Pj4YG5uzvjx44mLi+Onn37i8OHDPPDAA1JyyN3dndzcXIKCglr1/P39/Xn00UdZunQpCxYsuGs1ENoKpqamNDQ0AP/n59yFG9EVCDcD4sLdXoFwfn4+Tk5Od7XlxbVoaGhg7dq1TJ48+a49J0EQyM/Px9XVlfz8/BteMK11DK1WK1Fx1Wo1n3zyCd27d2fcuHEIgkBOTg4RERHU1tZel90XBIHCwkLeeOMNpk2bxqOPPspPP/1E37597yoKZHvAYDCQkZHBb7/9Rk1NDePGjSMqKuo6WuXtQKvVcunSJXbu3ElWVhZhYWE89thjuLm5SZYXbQWVSoVer79plVSn03HmzBnmz58PQHZ2NiYmJjcI8nQmnDp1ChcXF6kfFuD48eN4eXl16nG3B+RyOX5+frzyyits2bKFf/3rX8yYMYOoqKhbPu9KpZLHH3+cVatW8dlnnzF37lwsLS07/QYyMDCQ3377TfLY1ev1PProo3f83IpiW56ennh4eDB27FgqKio4ffo0a9asobKyEl9fX3r16kVAQIBUpRUDjsWLFzd5zWUyGRYWFvTu3Zv4+HgyMzP5448/+PXXX0lKSqJv3743iFclJCSwceNG0tLSOH/+PBYWFnTv3p24uDg8PDykY167/tfV1VFQUEB2djbr16+ntLQUd3d37O3tGTVqlNQDDFeTgMnJyaxduxZHR0fmz58vBRHW1tZs2bKFsrIyHB0dUSgUDBkyhG3btuHj40NxcTH19fWSyrJOp0OlUlFbW0ttba3UL11eXk5VVRW1tbVoNBp0Op1UtTY2NsbU1BQrKyusrKxQKpUolUpsbGykAFUU7BKD3MYSBmI/tV6vR6vVotPpqK+vR6PRoFKpKC0tpbq6mpqaGhoaGtDpdOh0OrRaLcbGxpiZmXHu3Dk2bNhAWloap0+fxt7eXhpXU5X7zgSZTIaTkxOPPPIIV65c4auvvuLVV1/l448/JiIi4oZgODo6mrS0NNasWcPMmTMbPUexr3jr1q306dOHoKAgVq5cyZAhQzh//jy+vr5kZmbi4+MjfV60Odq/fz/vvvsuY8eOpW/fvnTr1o3CwsI2Oe+wsDCmTJnCJ598wgsvvCC1IHThKgOgvr4eAFtbW/Lz8zt4RJ0Td2dU0s7QarXI5fJ2CeIEQSA5OVmyibjbIQgCp0+fRqlUNlrBvJuQlZVFQEAA6enpTSrz3i5E/1gbGxvUajUfffQRYWFhjBs3DoVCQXFxMUqlErVajampKb6+vtLvZWRk8Nlnn1FVVcXEiRPRarWcP3/+phXC/zUIgoAgCFy6dIm1a9dSW1vL+PHjiYqKuu3NjlidUKlUHDx4kD179mBubs6gQYN45JFHJOpze1z/wsJCHB0dG92QiwkUc3NzKVDes2cPffv27bTiaQ0NDWzZsoWZM2dKf1dfX8/WrVuZPXt2B46s80CkR44fP57o6Gi+/vprzpw5w9SpU5vUMBCradOnT2fz5s188MEHPPfcc82qKHckHBwcKC0tZfny5dTU1PDEE0/ccRD8V4jUZicnJ4YMGcLgwYNRqVSkpKSwe/du/vvf/9KtWzfi4+PZtWsXkyZNajbLQ7zugYGBBAQEUFJSwh9//ME//vEP4uPjGTp0KPb29hQUFLBz507y8vJISEhg3LhxUt9lU8cxNzfHwcGBsLAwRowYQX19PcnJyWRlZaFSqUhNTSUsLIy8vDyWL19OQ0MDDz30kOQ1L4pwzZs3j969e7Nt2zamTZsGXO01Xr58ORYWFqSmppKVlcX777+PVqtFrVZLx7e0tMTe3h43Nzfc3d2xtbXF0tISS0tLzM3NpfXp2j7ua69Pa0Nco6/9f7Edpq6ujurqaszNzdHr9ZiZmbF582ZMTEyoqalBp9NJ5yMmSZydnXFwcLjundGZnhm5XI6Pjw9vvvkmu3fvZtGiRcyYMYMpU6Zc5xahUCiYNGkSb775ZpPe8z4+PhQWFqLRaKTquuglPXbsWI4fP86AAQOuuxbGxsYMGDCA8PBwvvvuO06cOEFCQgJFRUV3bKHUGGSyq77H4p7ppZdeumvb71oTIlugpqYGuPp8dvUIN46uQLgZELOH7bHg6fV60tLSmD17dqdaYG8X9fX1rF+/njlz5tz1lcm8vDx69epFfX19my20orjBkiVLCA8PZ+zYsVKwIgbCpaWlODo6YmFhgcFg4MSJE6xatYpx48axc+dO3NzcOHnyJJ6enveU6vjtQAyAs7OzWb16NdXV1UyYMIHIyMg7CoANBgP5+fls27aN8+fPExYWxlNPPYWbm1urCF+1dDxpaWlNitccPHiQhIQEFAoFdXV1pKenM3HixE65xgiCwMWLFzE2Npb6vgRBkCpjd6P/eFtCJpPh5eXFq6++yrp16/jnP//J7Nmzm+yZE4WkRo8ejaWlJe+99x4LFizAwcGh015bKysrsrKysLOzY+HChXfcwnAriM+xtbU1vXr1olevXtTV1ZGRkcE333xDRkYGMpmM4uJioqOjcXBwaBbzQ/zebt268fDDD1NZWcnOnTv55z//ib29PRUVFUycOJH58+ff1r5D/H6lUkl8fDxxcXGkp6fzyy+/8OOPP9LQ0MC0adMkOvfp06f517/+xaZNmwgLC2PmzJn4+/vzzjvvoFarKSgooKamhszMTLKysiSxIm9vb5KSkrC1tW3Ukq8zzKObBdoKhQJjY2Osra2Jj48nPT1dqtiLOgtqtZqqqioqKirIycnh2LFjFBcXU1tbi7m5OS4uLvj7++Pt7Y2LiwsmJiYtFltrC4jJnMGDByOTyXj11Vc5efIkDz/8MNHR0dIYlUolDz30EMuWLeO1115rtEXCwsICDw8P0tLSiI6OJioqiszMTLRaLY6OjuTl5TVKkRcp2IsWLWLXrl0sW7YMuVxOQ0NDm2hSyOVy+vfvT01NDf/5z3947rnnWlWD426Fo6MjpaWlwFWadJdqdOPoCoSbAa1W226UXrVaTV1dXaf29WwuBEFg//79+Pj43PX9zgaDgZqamusoW60Nkd72+++/s2DBAsaMGXNdxa60tBQHBwfKy8sJDAxEoVCwbds29u3bx4IFCzhw4ADx8fHA1Yrf4MGD7/rkw51ADFZ/++03CgoKGDt2LDExMU2K6jQFUak7JSWFbdu2oVarSUpK4r777msVa6XbhcgIGD9+fKNj0Ol0pKamMmLECGQyGSkpKXh5ed1Ax+wsMBgMbNq0iTFjxkjzV6/Xs3nzZsaNG9fhG83OCLE6PG3aNFJSUvjyyy8ZNmwYSUlJTQZncrmcpKQkTE1N+fDDD3nmmWdwcXHpdNdYvP/l5eWMGDGi3Te54vUwNzeXEoxff/01Go2Go0eP8umnnyKTyYiMjCQuLg4XFxdMTU2l3zMYDJw9exYfH5/r1gqZTIadnR2jRo3i0qVLCILAa6+91mrVeTEoDgkJ4ZVXXmH9+vUcO3YMPz8/ysrK+PLLL1m6dKlEW01LS+OVV17B29sbCwsLKisrefDBB7GxsZE+r9fr6devH1qtFg8Pj043V1oKb29vtm3bRmxsLJmZmfTs2RO4GgRaWFjg5uZGWFgY8H/v6KqqKgoKCrh8+TInTpygoqICpVKJr68vQUFB+Pr6YmVl1W4FlMYgk8kYMGAATz31FOnp6WzatIm9e/de17sbHByMn58fO3bsYPTo0Y0mMxISEjh8+LAUCH/33Xc4OjpSU1ODXq+nqqqq0f2qGJAPGTKEgIAAZs+ezU8//cT06dObpXbfUsjlckaNGkVFRQXLli3jkUceue13/b0Amez/RMqgKxBuCl2BcDPQ0NDQ5tlnEZcuXcLT0/OeeIBVKhXbt29n4cKFd31AVlVVhVwup6amBmdn5zYJhNVqNRcvXmTMmDE3BMEAqampREVF8fPPPzNu3DjWrFlDVlYWzz//PObm5pw5c4Z58+ZRVVUl+Uz+L0IQBIqKitiwYQMZGRmMGjWKxx577Kb+zM35voqKCvbt28fhw4fp1q0bEyZMwN/fv0M3OiIaGhooKyu7rpf2WmRmZmJra4u9vT0Gg4G9e/dKQXFnRE5ODjU1Nde1UmRlZdHQ0NBlk3ELyOVywsPDefHFF/nmm29IT09n5syZTTJD5HI5iYmJmJiY8PHHHzNv3jzJ0qszwGAwsGXLFlJTU5k9ezZXrlxpUh29rceybt06Bg4cKLE//Pz80Gq1lJaWcvLkSX788UfUajXBwcHEx8fj7e2NVqvlySefxNHRkbfeeovQ0FDpndjQ0MC3336Ll5cX9913X5speZuZmTF58mSJPZCcnMypU6fQarXSZ/R6PUOHDmXSpElkZ2fz/fffS+4EouDUlStXcHV1Zc+ePW0yzvaG6Lfq7u7Orl27mvysKLJmbm6Oq6srMTExGAwGNBoN1dXVZGRkkJyczPr164GrPsXh4eH4+Phgb2/f7vsghULBlClTWLJkCVFRUSiVSt59910GDhzI4MGDMTMz47777uOtt94iMTGx0YA2ODiYtWvX0tDQgJOTE3V1dQQFBXHhwgWcnJwoLCxssnAj9g736NEDgLfeeovZs2fj4+PT6muMQqFg2rRpfPnll/z6669Mnjy507b/tAdsbGzIzMwErj7/Yr9wF65HVyDcDLSXdZIgCJw9e/aeMAgXBIGtW7cSHR19T6gWFxcXY29vT2FhIe7u7q3+/RqNhqVLl5KdnU1oaOgNi7cgCKSkpNC3b1/Kyso4fvw4rq6uzJ8/H6VSSV5eHnK5HEdHR3bt2kVoaGi7+l53BohqzRs2bCA5OZkhQ4bw4IMP3lYALPaT5efns3XrVlJSUoiLi2PBggU4Ojq2O/25KVRVVWFiYtIo5UwQBA4dOkRCQgJyuZzS0lLKyso6bZLEYDCwefNmhg4dKiUDxQrx8OHD71qxvfaEWGV87rnn2LBhA2+99RZPPfVUk9U7mUxGz549MTY25j//+Q/PPvtsp6gMC4LArl27OHr0KAsXLiQnJ4ctW7a0Sa9hc8aSmZlJQUHBdQJDMtlVb1c3NzdcXV0ZOXIkVVVVJCcns3HjRkpLS5HJZJw6dYr6+npSU1P55z//yaRJkzA2Nmbbtm2Ym5u3aRAsQi6Xk5CQgFqtpqamhrlz51JQUMCVK1e4fPmyRP0V6c9GRkZkZmYSFBSEXC5n0KBBvPrqq6jVaiorKzvkPrQ2lEqlJN5VWlqKwWBoUcAq2gmJdOk+ffqg0+kkz+oTJ06wbt06lEolERERREVFSde2Pa6dqakpc+bM4d///jePP/44r776KitXruStt95i5syZBAYG0r9/fzZu3MjMmTNvOHdbW1vs7OzIysoiKCgIPz8/DAYDFy5coEePHqSlpREaGtrkuRgZGeHg4MCQIUOoqqri008/ZezYsfTv37/V6eTGxsY89thjfPTRR+zcuZMhQ4bc9XP0diH2CAuCIClIt3R+/y+ga1fRDFRWVmJra9vmxzEYDFy8eJHhw4e3+bHaGuXl5Rw5coRXX331nliECgoKcHV1JTc3t9WFzOrr6/nyyy9xcHAgMDCw0f5jvV5PfX29pIjp6enJ7NmzpY3TsWPHiImJQS6Xs3//fh5++OF74ro3ByJdbfv27ZII1D/+8Y9G+9aa812iqvTGjRspKSlh4MCB3H///W1C57pTiAJgPj4+jQaJWq2WtLQ0xo4dKwnXRUREdEr/WEEQKCsrIysri1mzZkm9wUVFRRQUFNCjR49Od/07K8TgbNKkSfj7+7NkyRJmzJgh9Qje7HciIyMxGAwsWbKEhQsXtplfenMgCAJHjhxh+/btvPDCC1hbW+Pq6kppaWmzrXtaEzqdjt9++63JgFXsvba3tycpKYmkpCRUKhUvv/wy9fX10vM6e/Zsyb7s+PHjPP/887d8JkW9A7lcjiAI6PV66d+uDSYMBoMUoDYWZMhkMpKSkrh48SJRUVE88sgjUuJPo9FI80OhUDBs2DC2bt1KYGAgcrmcuLg4rKysKCkpQa/Xo1ar73phIiMjI1xcXKitraWhoYGamhpsbGxu+/tEwSh7e3upt1yv15Ofn8+ZM2dYvnw5KpWK4OBgevXqhZ+fX5syi2QyGfb29syePZsvv/ySV199lccff5zU1FS+/fZbIiMjGT58OO+++y6lpaU4OTnd0FsdGxvL8ePHCQ4OpkePHuzdu5eKigo8PT3ZunXrLRMion99cXExcXFxvPLKK3z11VdkZGTwwAMPNCnudzvnq1Qqeeqpp3j77bdxdna+Z8RnWwpra2tUKhWCIGBmZobBYKChoaGrf/ov6EoLNANVVVV3tDC25DgGg6Fdgu62hCAI/PbbbwwePLhdrlt7ICMjA19fX/Ly8lq137mhoYEffvgBS0tLpk2bhl6vl+yTrkVZWRnl5eXs37+fuLg4HnvsMYmur9frOXnyJHFxcRQUFKDVatvM57gzQVTZ3r9/P//v//0/ysrKeOWVV5gwYUKL7WDE/t+jR4/y5ptvsmrVKvr378/rr7/O8OHDbyuobi9kZGQQEBDQ6PiysrKwsbHBzs4OnU7H4cOH6dOnT6c9F9Gq41rhlj/++IMBAwZ0vbxvAzKZjKioKBYuXMivv/7Kxo0br/NjbezzPXr0YOrUqXz00UcUFxff9LNtCUEQOHfuHKtXr+bZZ5+VLFHs7Owk5kd7jyclJQVjY+PrbOuagsgaUSgUZGVlYWpqipmZGWZmZgiCwHfffcf48ePp06dPo2v+X4+/Y8cOPvnkEwwGA4WFhSxatIhp06bxxRdf8Ouvv5KdnY1er+frr79m2LBh/Pjjjze9dwqFglGjRrFlyxapQiRWNkUGjUwmIyIigry8PMlj19LSkoEDB0rrSnFxccsvZieDWP0WvXFbc26J19HIyAgvLy/Gjh3LK6+8wqJFi/D19WX9+vW89tpr/PDDD1y6dImGhoY2ed7EfuARI0bw5ZdfotVqCQ8P57XXXsNgMPDBBx/g5ubGpk2bGj1+eHg4aWlp6HQ6/P39KS0txcLCAiMjI0pLS2/ZeyqTXfXUFueLKKRlZWXFu+++KylKt+b52tnZ8dRTT/HDDz+Ql5fXIetYR0MMhPV6PaampgiCIPkKd+H/0BUINwO1tbVtvhEWBIH09HR8fX3v+v7gnJwcLl26xIABAzp6KK0CQRAoLi6W+mNaKwOu0+lYtWoVOp2OmTNnolAoqK+vb1S9sbS0lJSUFLKyskhISLhujpSUlADg5OTEkSNH6Nmz5z1NIRUEAZ1Ox9mzZ3nrrbc4ceIE8+fP5+GHH26x6q0gCKhUKnbs2MHrr7/O4cOHmTFjBi+99BJxcXFtonDZmhDpmn5+fo3+2+HDh+nVqxeAVMW5WS9xR6OmpoZTp07Rv39/6R5WVlaSmpraJr7d/ysQe/QWL15MZmYm3377bZMbV5lMRkxMDPfddx+ffPIJZWVl7bqJFMXffvjhB+bPn4+Li8t1Y7O3t6e8vLzdxgNXE5abNm1iwoQJLaYVGhsbM2/ePFatWsWmTZvYtWsXhw4d4tixYwwfPpzo6Ohbfofo1XvgwAFqa2txcXFh0KBB2Nvb8/TTT9OjRw8+//xzNBoNU6dORaVSMWXKlCbH6uLiQkNDQ5PXUqlUkpCQwO7du6Vq9JgxY0hLS8PR0VES2RIr1A0NDdTX11NXV4darUalUlFTU0NVVRWVlZVUVlZSXl5+3U9ZWRmlpaVS20Z5eTkVFRVUVlZSVVUl+QCrVCrUajUajUbyBBar5HeKgIAALl++TLdu3SgqKrrj72sKoqJyUlISzz//PIsXL8bX15cVK1bwxhtv8Pvvv1NUVHRdxb+1jjto0CCsra3ZtGkTBoMBCwsLHnjgAWbOnElWVha//PJLo8mvbt26odPpKC0txcbGBjMzMywsLMjJycHU1FSy6GkKf722pqamTJ06leHDh/P+++9z9uxZDAZDq56zl5cXDz30EJ9++mm7J886A8zNzWloaECv10sWsF2B8I24d3fLrQiVSnXdy7itcObMGWJiYu7qDZ9er+e3335jzJgxnT6IaC60Wi1VVVWYmZlhZGTUKpUpg8HA+vXrKSwsZN68eRgbG0sv+GsDYUEQKC8vZ8mSJYwcOVKy6hDniCAIHDt2jKioKABOnDjB008/fcfj66wwGAxcuXKF1atXU19fz/Tp0yXaXksD4Orqavbu3cvevXsJCgpi3rx5uLi4dAoLjOZCq9VSW1vbKPOivr6etLQ0xo0bB8ChQ4eIi4vrtOIh+/btIzIy8jpGzI4dOyQ6ZhduH6IN0JNPPsmaNWtYsmQJTzzxhOQr3djnY2Nj0el0fPbZZ5LPcFtDEATy8vL48ssvmTNnTqPMFj8/Py5fvkxQUFCbj0cc0+nTp3FxcbktlWRjY2NGjBhxw9+XlZVhZWV103tw7fGzsrKIjIzkyJEjZGRkSO8A8cfX11fq8xUZS7cap5GREc7OzuTm5uLg4IBWq6WhoeG6/2q1WpycnPj666+xtrZGrVZTVlZGcnIyJiYmHDp0iP3791/3eb1ej8FguG58Ik0bkKjdIv7652v9fq8NdEXKtzh2Y2NjjI2NMTMzQ6lUYm5ujlKpxMLCAjs7O+zs7FAqlZiamqJUKqVqfGPJAdGjOikpicuXL0vuC20NuVwu0ej79u1LaWkphw4dYsmSJVJPbUhISKuJtcrlcmbOnMlbb71FcHCwJNoWEhLCv/71Lz777DOef/55/v73v1/HfJDL5QQHB5OWlsaAAQMIDg4mJyeHCxcu4OPjw6VLl+jWrVuTx3Z1dWX79u3X0ajlcjm9evXC3d2dL774gr59+zJs2LBWS+SLDJeioiK++OILnnvuuUYLDfcqxL2MmFQxMTHpCoQbQVcgfAsIgiBVhNv6ONnZ2UyaNKlNj9OWEKtTZWVlkkfhvYCqqioUCgXV1dU4OTndcX+lIAj8+eefpKSksGDBgutsNnQ6nRRoiz2TH330EWVlZfTr148VK1bg7e193XcdO3aM2bNnk5eXJ/U73WsQ6ZDr1q0jPT2dyZMnEx0d3WLBEVEBetu2bRw9epQePXrw4osvdoiiZ2ugsLAQa2vrRtenvLw8rKyssLa2RqfTcfr0aebPn98pn8u6ujr27NnDwoULpfGpVCoOHTrEK6+80inHfDfCxMSEadOmsX37dt577z3mzZuHq6tro9dXtE6pra3l888/59lnn21TAT5xvfv444954IEHbqoQ7uPjw4kTJ9pNqEmr1fLnn3/y6KOP3tYa8dcgr6qqipKSEtLT01Gr1bc8B4PBwP79+ykqKiIvL489e/ZICrzXfkas0jUXImX3q6++wsbGBoPBgMFgQKFQSDaBooiUXq/n6NGj9OzZEz8/P/z9/TEzM8Pc3JyJEydiZmaGqakppqamN9gLXisq1hL8tSp5bUAsVp41Gg0ajUaynayrq6O2tpbMzExOnjxJXV2d9Bmxr9zCwgIbGxvs7e1xc3PDwcFBqmra2dlx9uxZ6Vjtte6I98LFxYUJEyYwevRozp8/z59//smKFSvo06cP/fv3lyzvbndcMpkMS0tLHn30Ub766iv+9re/SVZdFhYWzJkzh6eeeoolS5YwbNgwRo8eLe13evbsybZt2+jfvz89evTgzJkzyGQyhgwZQkZGBomJiU2Oy8LCgrq6uhvuq0wmw9PTkxdffJGvvvqKwsJCZsyYcd2+6E4gk8kYOnQoBQUF/PLLLzz88MOdNhnc2hADYZ1OB1xd/7uUo29EVyDcDNTW1ra5IERJSQlyufyu9g/W6/WsW7eOCRMm3FPU3MrKSmxsbMjPz5csM24XgiBw8OBB9u3bx+LFi6+j3Iv0MhMTE2lT+P777zNq1ChUKpVU1XF0dJS+r7i4GL1ej6urK6tWrerU/Z+3A7EPePfu3dJLeMaMGS1WghYEgdLSUjZt2sS5c+fo1asXf//731vNr7MjICaevL29bzgHMUESGxuLTCYjNzcXc3PzW1afOgKCIHDy5Enc3d2lqoKodh0cHIy9vX0Hj/DeglwuZ+jQoTg4OPDRRx/x1FNP3dTKRFQKrq2t5YsvvuCpp55qs15tlUrFkiVLGD9+/E2F0cR+zo0bN7aLYJYgCJw4cQJXV1dcXV2b9Xn4v2CtqKiI3NxcMjMzuXLlCtXV1VL/oo2NjVRBvdl5CILAhQsXJA/XoqIi3nzzTSoqKiR6sEaj4cSJE0RGRmJtbU1+fr6kAH6rsdbW1vLggw8SEhIiBbONBfvJycls2bKFkSNHAnD27FmOHj2Ku7s7vr6+7f6+b2oO3owqrdVqJap2dXU15eXl5OXlce7cOSorKzl9+jQqlYqsrCyUSiV+fn64ubnh5uaGtbW11EcNbRsgi0J3kZGRREZGUlxczLZt23jzzTeJiopixIgRODg43HbiViaTERAQwMCBA1m2bBnz5s2TAkNbW1tGjhyJubk5+fn5vP/++8yePRsnJycCAgL46aefqK2txdPTU5q7jo6O7N+//5bPo5mZGVqtVkq2/HVM1tbWzJ8/nxUrVkjr0rWe23cCuVzO9OnT+eCDD9izZw8DBw68a9/7LYFcLkehUEiBsKgc3YXrce9EK22E9lJGvHz5Mj4+PndtpkrscdbpdPeE/dO1yM7OxsvLi8zMTHr27Hnb3yMKwPz222+88MILjVINxZd4aWkpH3zwAWPHjqVHjx588803mJiYoFQqr5uLp0+fJiwsDL1ez7lz51i8ePE9c+11Oh3nzp1j1apVeHl58dJLL0nWRc2FwWCgpKSETZs2cf78eQYMGMBrr72GlZXVPXGd0tLS6Nmz5w3notVqSUlJ4dlnnwXg4MGDxMfHd8oElVhxe+ihh6S/02g07Ny5k3nz5nXgyO5diH3AFhYWfP7558yaNeumFihiX+jKlStZvnw5Dz30UKvPo7q6Oj7//HMSEhJu2Q/u4OAgVf/amjKv0+nYtm3bTavBgiCg1Wqpr6+nsLCQy5cvc/nyZfLy8mhoaMDGxgY3Nzd8fX3p06cPtra2WFtbY2RkhMFg4K233iIvL+86ls+1qK6uZtOmTXh4eBAREUF2djZWVlZ8//33aDQanJ2d+f7774mNjWXu3LlSULxw4cJbBsJ1dXWUlZURFRV1y/1N9+7dWb58OUVFRbi4uBAaGsqyZcskplRnSlbdbO6YmJhgb2/f6FgFQcDBwQEfHx82bNhASEgI5eXl7N27l+LiYrRaLUqlEk9PT3x9ffH19cXe3h4zMzMUCkWbvEvE7+zWrRsPPPAAY8aMYd++fbz33nv4+/szbtw4unXrdlsBsVjJPXXqFEePHqVXr14ShX3IkCF89tlnvPrqqxw7dox33nmHKVOmEBsbi5OTE7m5uXTv3h0HBwcKCwupra1FrVaj1WqbXBdEtkBNTU2j90Amk2FqasqDDz7I9u3beeedd5pkrLT0fM3MzJg7dy5vv/02np6eNxWYvJcgk131vVapVNJ87aoI34jOtyvqZNDr9a0qkHQznDlz5o6CrI6GWA2ePHlyp9xs3wmuXLlCcHAw27dvv2UfzM0gCAJXrlxh2bJlPP300016K5eUlLBs2TLGjh1LYmIiZWVlkshEQECA9OITq37Tpk0jKysLe3v7e0KlWxAEcnNzWbVqFWq1mkceeQR/f/8WvfBF250//viD8+fPM3DgQKZOndqp1Z9vB3l5eVIP8LUoLi7GxMQEW1tbdDodqampndaW7eLFi5iYmEhVSUEQSE5OxsnJqVU2QV1oHKKS7Lx58/jss8+YPHkysbGxjT5nCoWCKVOm8O2337JhwwbGjRvXaklbrVbLjz/+iKurK6NGjbrlc65QKFAqlahUqjYPhFNSUrCzs5ME5vR6PbW1tVRUVHDx4kUuXbpETk4OWq1WCqTi4uK47777sLCwQKlU3vR85HI5ffr04cCBA3h5eTU6z21sbHj++eelP8fHxzfZv2phYXFdQulmEASBtLQ0vLy8mkV3NzU1JT4+ngMHDjBp0iR8fX2xtrYmOzubysrKThUI3w7EKmlJSQmurq74+/szYMAAiaVVV1eHSqXiypUrZGZmcvjwYWpqajA1NcXHx4egoCB8fHywsbFpNUrvX8dna2vLmDFjGDRoEIcOHeKjjz4iODiY0aNH061btxYf08TEhIcffpiPPvqIsLAwiXbt6uqKra0tFy9epF+/fvj7+/Ptt99y7tw5AgMDOXnyJN27dyc8PJy8vDwyMzOxtramuLj4pgkduNrXbWNjQ1lZWZPzRaFQXMdYmT17drOV2m8FBwcHHnvsMb766itefvnlu37e3gpyuRwbGxsqKyvx8vLC2tqaqqqqjh5Wp8O9FbG0AfR6PYIgtGmlVqvVkp2dzZQpU9rsGG0JUUzE3NycwMDAe2rjKlpV9OvXD5VKdVuBpqg6/emnnzJr1qyb0hDFF+7HH3/MzJkzpZ6b4uJilEolZ86cYfDgwdLny8rKqKmpwcvLi59++onExMS7ss/1WqhUKjZt2sTx48eZOHEicXFxLeoDFgPgTZs2kZaWxqBBg5g6dWqn9AC+U9TW1lJfX3/Dy1wQBI4fP050dDQKhYILFy5ga2vbKV/6er2ezZs3XxcA6XQ6tmzZwvTp0++5e9bZIJPJ8PLyYtGiRXzyySc0NDTQu3fvRtcRIyMjHn74YT7++GP27t3LgAED7vj+6PV6Vq1aRX19PY8++miz3rNyuRxPT0+uXLnSLLry7UKn0/HHH3/Qr18/Tp48SUpKCleuXJEC8ICAAEld28rKSvKCvdk1qaiooLa2Vuq/NTExITY2lo8++ojs7Owmg4jWhlqtZtOm/8/eeYdXUW5d/DcnyUnvBdILJLQktITem1RBekdBEERARFCKolgQK9JEpUkRUGnSqyC9BwIEQiqpJKS3k5wy3x98M5eYBBJISNCs5+G515NzZt5p77x777XX2svYsWNLfQ3btm3Lt99+S8+ePbG2tsbV1ZWbN28SHx9frGr9iwYXFxeuXbuGi4sLMTExuLq6yr275ubmmJub4+joSPPmzdHpdLKIZnh4OCEhIRw8eJD8/HycnJzw9fWldu3aODg4lKtnu9TL27lzZ1q1asXff//NN998g7+/P3369Cmz9aazszPNmzfnzz//ZMSIEfK90K1bNw4dOkSDBg1wdnZm1qxZ7Nq1i4MHD6Knp8fgwYOpX78+e/fuJSoqCldXV8LDw0tM6Ehjt7GxISUlBW9v78eOS6FQ0LRpU6ysrPjpp58YPHhwscynskIQBOrWrUvXrl358ccfeeedd/41oq7FQaKcS8GvlZVVdSBcDKoD4SdAkh2vyAAjJSUFhUJRJfv3SgO1Ws3OnTsZO3bsv64anJ+fT3p6urx4KSszQOrDWrp0KQMGDCiRNi6JQeXn5zN48OBCwhN37tzBy8uLxMTEQpXkkJAQateuLfeRDRw48IUMHERRRKfTcfnyZX777TcaNWrE/Pnzy1S9lXqA//zzTzkAHjZsGMbGxi/kOSkNEhMTsba2LvIi12q1XLt2jfHjxwNw+vTpKpkkkRSC09PTZVquZJ2jp6eHl5fXv/baVSUIwkOPz3feeYfFixej1Wpp27ZtkfvlUXrht99+i62tLX5+fk99jURR5ODBg0RERDBjxowyvTs8PDxkK7nyuEeklhS1Wk1cXBxhYWGcPXuWv/76i8zMTFxcXGjQoAEdO3akZs2acnKuLPtesWIFq1evxsTEBKVSKasYp6WlERISwooVK7Cysqrwe76goIBffvmFpk2blknzws7ODhsbG+7evUu9evVwdHREo9EQEhJCmzZtKnTMzwP29vakpKTg6+tLbGxsiWJsgvDQG1pPTw8jIyNq1KhBy5Yt5Xd9REQEN27c4Pjx4+Tn5+Pu7k7Tpk3x8fGRGQzlEdCZmJjw0ksv0bZtW/bv38/HH39Mz549ad++vZyUKc12evXqxUcffUTHjh1xdnZGEATq16/Pli1bePDgATVq1MDQ0JBBgwbh5eXFBx98wNmzZ2nWrBmGhobExcXRunVrbt++TceOHR+7P3t7ex48eFAqoTtBEKhVqxZvv/02y5YtIycnp5C13tNCEAQ6d+5MZGQku3btYuDAgVXu3ViesLCwICsrSxZKk+w2q/E//LuilgqAVqst8wuvrAgPD8fT0/OFXPRJojY1a9bEw8OjsodT7sjLy0NfX5/09HTs7OzKPGEWFBSwcuVKAgIC5D6c4pCZmcl3332HUqksYo90+/ZtLC0tSU1NxdnZWf78/PnzdOvWjbt37+Lg4CBTm14kiKJIfHw8mzZtQqPRMHXqVDkTX9rfp6ens2fPHoKCgujcufO/PgCWEB0dXaxQVlpaGhqNBjs7O/Lz8wkNDa2yavT79u2jS5cusi+2KIrs2bOHnj17vrB6CS8ipGrN9OnTWbJkCRqNho4dOxYbDFtZWTFx4kSWLFnC1KlTn0pAUJq/Tpw4wfvvv1+m51UQBDw8PLhy5cpTK0dLybeCggLu3btHSEgIt27dIi0tDQsLC7y8vMjKymLBggWFBAifdl+iKNKoUSNiYmJk4Rp4WGUPCAigcePGfPfdd0yePBkHB4cKmbtEUSQvL49ly5axf/9+Zs+eTXp6uiwEVZrApFOnThw/fhxfX1/s7e2xs7Pj9u3bz03BuyJhbW2NVqvFwsKCkJCQMv1WWiOam5vLIlfwcC4OCwvj4sWLbNu2DVNTU5o2bUqTJk2wtbV95v5iqUI8YMAA2rVrx2+//cbx48cZMWIEdevWLdXa1cTEhF69erFz504mTpyInp4e+vr6NG/enNOnT/PKK6/I2wkICGDQoEF8/fXXDB48GCsrK6KiojA1NX1s8kCCs7Mzly5dKtPxOTo6MmPGDJYuXUp2djbdu3d/5neDnp4eI0eOlG2k/P39X/j7tySYm5tz//59RFHE2NiY3Nzcyh5SlUN1IPwEVHRFWBJQaty4cYVsv6KRm5vLgQMHmDJlyr8yqyYtFBISEuRsaWmh0WjYvHkzlpaW9O7du8Tzk5mZyeLFi6lbty43btwo9D2NRkN0dDTe3t7k5OTIrIHMzEzu37+Pt7c369atK5HOWFUhiqJMz7t48SJ9+/alefPmpaaRST7Ahw8f5ty5c7Ru3Zr58+f/a0SwSoPQ0FACAwMLfSaKIteuXaNevXoYGBhw+/ZtbG1tq2TveGpqKuHh4YwcOVKuBsfGxpKenk6DBg3+M9exqkAKhqdNm8bSpUsRBIEOHToUGww7OTkxYsQIVq5cybvvvlum+0tisGzZsoWZM2c+FRPKwcGB1NRU1Gp1qaiNUuCbm5tLXFwcN2/eJCQkhMzMTOzs7Khbty6DBw/G3t4ec3Nz0tPTuX37NoGBgU89r2o0GjIzMwkJCeHKlSuEh4dja2vL/fv3EQQBZ2dnpk2bxpgxY7C1teXcuXN88sknjBo1iqZNm5Yru0qn0xEVFcW6devw8vLCzMyMAQMG4ObmRseOHenatSvNmjXD3t6+xP1KlcLffvuNrKwsXFxcUKvVhISEPBdnjYqGQqHA3NwcY2NjHjx4gFqtlhN0ZcGj85aNjQ3NmjUjMDCQ/Px8EhISuHjxIsuXL0ehUNC4cWMCAwPl8/60c57E6njzzTe5c+cOmzZtwtPTkwEDBjzRGUEQBFq0aMHhw4eJiYmRk6utW7dm8eLF9OzZU1bpFoSHlmoJCQmoVCquXLmCQqEgKSmJgoIC8vLyHmvhZWNjQ2pqapmPzdbWlhkzZrB8+XJUKhV9+/Z95ufDxMSE119/nRUrVvDee+9ha2v7r3znWFpacvfuXeDhMefl5VXyiKoeqgPhJyA3N7dCq0tSRnrw4MEv3EMoWQHVqlWrQnu1KhPR0dGyYnRAQECpf6fT6Thw4AD3799n2rRpJU7aOTk5LF++nCZNmlCrVi327NlTaOGlVquJiYnB19e3UKUgPDwcV1dX4KHi+LBhw57hKJ8vtFot169fZ+vWrfj6+vLBBx+UOoAVRZHs7GyOHz/OiRMnCAgIYO7cuc+FUliVoNPp5OTMP3Hp0iW5Anzu3Dlatmz5vIf3RIiiyOHDh2nRokWhhdO+ffvo3LnzUy1Aq1E+sLa2ZurUqSxevBiFQkG7du2KDYb9/Py4f/8+q1atYvLkyaW2VUpISODHH39k8uTJsghVWSEFvyqVqsRAWJor7t+/z/Xr1+XA197ennr16jFy5Ejs7e2LCFpJLKcmTZqUqX9QFEVUKhUJCQlcvXqVGzdukJeXR+3atWndujUjR44kMjKSw4cP079/f+bMmUOdOnXk6paPjw+iKLJlyxZ27NjBq6++Su3atZ9pwa/T6WTRwNDQUIYOHYq/vz9NmjShT58+3Lp1i1u3brF69WocHR1ZuXIl3bp1K3F7xsbG1K1bl6tXr1K7dm3Onz9PVlYWycnJL3wgDODk5ERaWhparfapA+HiILUVeHp64uHhQb9+/UhOTubSpUusXLkSfX19WrRoQZMmTZ7J016hUFC3bl3mzp3LwYMH+fTTTxk4cCCBgYGPraIaGhrSq1cvdu/ezeTJk+WkmI2NDWFhYfj6+srfdXFxITMzkxkzZuDk5MSsWbO4desWNjY2xMbGUqdOnRL3Y2pqSk5OzlMdm5mZGVOnTuXHH3/kt99+Y9CgQc/Ufy0xS3r06MGqVat45513/pXvHWtra9LT0+WKcHUgXBTVgfATkJmZiZmZWYVV2zIyMuRM5IuGnJwcjh49yjvvvFPZQ6kQSD2Mrq6uMv24tL+7fPkyZ8+eZdasWSUuplQqFT/99BNeXl706tWL69evo1QqC91rWVlZJCUlkZSUJNOtJLXowMBAbt++jaOjY5Ws+P0ToiiSmprK5s2befDgARMmTMDDw6NUz5bkJ3zy5EkOHjyIn5+frPr4XwqAJWRmZqJSqYqoj2dlZZGeno6rqyt5eXncvXuXAQMGVLlzlJOTw8WLF5k7d648tpSUFMLCwuQKcTUqD5aWlkybNo3Fixejp6dHmzZtilwTqdcuMTGRP/74g2HDhj2Rspiens6yZcsYOnToM9mXGBgYYG9vT3x8PJaWloV6fOPj47l16xbBwcE8ePAAa2tr/Pz8GD58OI6OjiiVysdSRtVqNRcuXJADgpIg7VNSkL548SL37t3DzMyMxo0bM3bsWGrUqIGBgQEqlYoDBw5gbm7OmjVr6Nu3r5w4EEWRrKwsvvzyS5kR8aj9UqtWrfDz88Pe3v6xPraP+uemp6cTGhrKyZMnuXDhAt26dePDDz+Uk/q+vr7Mnj2bt99+m/z8fFQqFZ6enk9kpgmCQLt27diyZQsjRowgOTmZ2rVrc+rUqRJFIF8keHl5ce/ePYyNjcnKynpsdfNpIQgPfYKdnZ1xcnKiZ8+exMfHc+rUKb766ivs7e3p0qUL9erVk+/Vsm7f2NiYvn37EhgYyNq1awkKCmL48OElJpwF4aGd2t69e4mPj8fFxUVOgp04cYL69evL956FhQVWVlbEx8fTqVMnfH19+eOPPwgICCAyMvKJgXB+fv5TJRmk45o0aRKrV69m06ZNjBgx4pmD4Xbt2nH79m327Nkj08D/TTAzMyMnJwedTicHwv+GVobyRHUg/ARkZ2dXyGQoISwsDC8vrxeuH04URU6ePEn9+vWxt7f/Vz5UUiDcpEkTsrOzsbOzK9Vv7t27x+bNm3n33XeLNYQXRRGNRsMvv/yClZWVHKjk5+cXsV6IiYnB0tKShIQEubKnUqkIDw9n6NChrF+/vthFalWCdLx///03e/fupVu3bkyYMKFUgh6SfcWVK1fYvn07rq6uzJw5s8L66F4UpKWlYWlpWWTeuHPnDu7u7hgZGXHnzh2sra2rXKVGFEVOnz5N/fr1ZVqsKIocOXKEVq1aVeh8W43SQeoFnjZtGt9++y1GRkYEBAQUGwwPHjyYxYsXc/bs2UL9tI9CSmStXLmSNm3aEBgY+My9kS4uLkRHR+Pg4CDTj2NjYzExMaFBgwb07dtXfhak3zwJoigSERGBpaUltra2Rf4GDxktsbGxXLt2jaCgIHJycnB3d6d58+aMHj0aMzOzQhoP169fZ/PmzXh7e7N8+fJC74TY2Fg2btzIn3/+yaVLl9BoNCiVSlauXMnIkSO5d+8ex48fZ+HChdSuXRsvLy88PT2xs7PD0NAQY2NjdDodKpWKlJQUIiIiSEpKQhAE3N3d6dq1K926dWPt2rVER0dTt25d4GHlUPJr3b59Ow4ODtSqVQu1Wv3ERbKUZJPEoTw8PPjrr78YMmTIC11Rkyj/ly5dwtHRkZiYGGrWrFnh+zQwMMDd3R03NzcGDRpESEgIhw4dYsuWLTRr1ox27do9FW1XOp5Zs2axd+9ePv30U1577TW5d/ifMDQ0pEuXLuzZs4c33ngDQRCoV68ev//+O7m5ufJ7RKFQUL9+fW7cuIGnpyd+fn5kZGSQn5/PoUOH6NSpU4nvdhMTE/T19cnKyiryfJX2mAwNDRk/fjyrV69mw4YNjBo16pmCYX19fUaPHs2CBQuoV69eiefnRYWBgQEajUauCBcUFKDT6V64mKMiUR0IPwG5ubkV5j0qiiIhISEvZD9cTk4Ox48fZ+bMmS/c2EsLtVpNenq6bHXxJL9FURTJyMhgxYoVvPrqqyV6oOp0OrZs2YJarea1116TqW95eXkYGhrKE5QoikRFRWFpaUlGRgYuLi4IgkBCQoIsjHXv3j1effXV8j3wcoSUGFi/fj1mZma89957pQ5itVotd+/eZevWrRgZGTF+/Hg8PT1fqF7oikJERASenp6FPhNFkQsXLtCiRQvgIS36cQJtlQWVSsVff/3F1KlT5bFlZWVx8eJF5s2bV+XG+1+FIAhYW1vz1ltvsXjxYoyMjIqo3ksL03HjxvHNN9/g7OxcbGVQq9WyYcMGatasyUsvvfTU11gK+iIjI7l9+zYXLlzA398fLy8vWrdujaenJ9bW1s90Dx0/fpx27dqhp6dXqLc4NDSUy5cvExYWhqmpKb6+vowcORIXF5cilTtRFElJSeHXX38lNTWVsWPHFmstGBYWxqJFi0hPT5c/69evH0OGDJH3//fff8tKzTVr1uT7778nKSmJ+Ph4unbtKvdwXrlyhZCQECwtLVmzZo0ckIuiyFtvvcWKFSsYMWKELMZoZmbGxx9/TEhICO+99x4+Pj588803jBw5koYNG5Y4zyqVSpo2bUpQUBCGhobY2dkREhJCcnJysa0aLxIcHR1JSUmhVq1axMfHP9fKmVQpbtiwIf7+/ty/f59Tp07x5Zdf4uHhQc+ePXF1dS2VsNk/t9mvXz8aNGjAmjVraNmyJT169CiStBAEgWbNmrF//35SU1OxtbXF1NQUHx8frly5Qtu2beX9+vn5sXnzZl5++WWaNGnCoUOHGDJkCJ999hmLFy/mjTfeKLYIoFAoMDMze+pA+NFjGjduHGvXrmX9+vWMGjXqmZIwZmZmjBs3jjVr1jBv3rwXkqFZEvT19dHpdHIgrFar0Wg01YHwI6gOhJ+AnJycUhnOPw00Gg1RUVH069evQrZfURBFkaNHj9KwYcOnnsxeBEjZ8UdFqh6H/Px8fvjhB5kuVFIQvGfPHhITE3nrrbcKTd75+flF+tXu3r2LmZkZMTExODk5FfKIjYiIoGbNmlWu4gf/65fbv38/58+fZ9CgQTRq1KhU/W46nY6YmBi2bdtGRkYGAwcOpF69ev86a66nhVS1+qfSpUqlIiYmhlGjRpGfn8/du3fp169flQospQqZg4ODXG2RejLr169fZh/MalQsBEGgRo0aTJ48maVLl/L6668XG9DZ2toyevRoVq1axaxZswq1auh0Onbv3k1WVhZvvvlmmRZgoiiiVqtJTU3lxo0bXLt2jaSkJBwcHPDx8SErK4v58+cXYdI8LbKzs7l37x5DhgwhPj6eoKAggoKCSE9Px83NjaZNm9K/f3+sra2LPQ5RFCkoKODEiRMcPHiQ7t27065duxLbY+rXr4+XlxfXrl1Dq9Xi6enJ/PnzEQSB33//XQ5U27dvj0KhID09nZs3bwIPE6eCIDBmzBg5STFu3DjOnDnDrl27GD58uEwB9/LykhXBc3JyaN26NQqFgnr16rF//35q1qyJgYEBTk5O/Pjjj0RGRtKnT59iK22SuNLSpUuxtrbG3NwcpVLJhQsXqtx8U1ZIfvN2dnZcu3at0sYhCAI1a9ZkwIAB9OjRg8uXL7NmzRpMTU3p2bMndevWLVMVVBAEfHx8mDNnDuvWrWPFihW89tprRYJVExMTmjdvzrFjx2Q7xrZt27Jt2zbatm0rf8/JyYnMzEyys7Np0KABCoWCjIwMmjZtiouLC19++SWTJk0qVmDUwsKCzMzMZz5HSqWS1157jV9++YWNGzcycuTIZwqGfXx8aNasGVu2bCm1p/mLACkQ1ul0GBoaotFo0Gq1lT2sKoXq0soTkJubW2GBcHZ2NjqdrkoGMo9DVlYWp0+ffqbM/ouAlJQUzM3NiYuLe6I1lFarZdOmTdSsWZMuXboUm02X6OSXL19m4sSJGBsbF/p7QUFBIUqRpPQp+U5aWFig0+kIDg6mUaNGnDlzhtatW5fb8ZYXdDodoaGhfPbZZ6SnpzN37txSqaBKXsBr1qzhhx9+oEWLFsydOxdfX9/qIPgRaLVa4uLicHd3L/R5bGwslpaW8j1rYWFR5TLbGo2GgwcP0rt3b/k+V6lUHD9+nB49elTy6KpRHCQa8sSJE/n555+JjY0t9jt169alQ4cOrFmzBrVaDfxPUPHKlSuMHz++VIJaUvIxJCSEjRs3smDBApYuXcr9+/fp0aMHH374IdOnT6dnz54oFIpnUtv95z6PHTtGREQEX331FT/88APZ2dkMGTKEjz/+mMmTJ9OyZUvs7OxKDILDw8P54osvCA0NZfbs2XTp0qXEIDgzM5NFixbRunVrBgwYgLGxMbNnz8bMzIxp06Yxbtw4bt26hSiKeHt7k5eXx/Lly8nMzJQDibNnzxITEwNArVq15OOYP38+N27ckOnckkr1zJkzOXDgAAcOHJAdMdzc3OSKtqurK++//z6xsbHy8ReHGjVqyEFjVlYWHh4enD9/Hp1O90zXobIh6bUYGRmRnJxc6ccjCA/tkdq2bcu8efPo2bMnu3fvZuHChVy/fr2QFVdpYG5uzqRJk6hVqxaLFi0iOjq6UG+5pBR/8eJF2WbHw8ODrKwsHjx4IH9P8k+Ojo7Gzs4Oe3t7QkJCsLe3p2nTpgwYMIDvv/+ekJCQQtuHh0mzlJSUZzgr/4OBgQFjxoyRHTqkeedpIAgCvXv3JjExkUuXLhUZ94sKfX19DAwM5MSZQqEo833zb0f16vIxkF4qLi4uFbJtSfn3ReqrEUWRQ4cOERAQgI2NTWUPp0IRGxuLk5MTcXFxNGzYsMTviaLIX3/9RWJiIu+++26Ji6Rr166xZ88e3n///WKTH5KAhLSo02q1hIWF4erqKveRp6amotVqMTY2JioqijFjxlSZZIRkibR9+3Zu3LjB6NGjqVev3hOpzFL1+NChQxw/fpzOnTszYsQIjIyMqsyxVSXk5eWhUqkKPX+iKHL16lUaNWoEwMWLF2natGmVopFLlWxRFPHy8pJpm8HBwXKFuPp6V00IgoCnpyejR49m+fLlzJgxAzs7uyI06U6dOnH37l32799Pnz59uHPnDtu3b2f27NklJmUeFZ2S6M5xcXHY2dkRGBhI9+7d5QrsP6tXBgYGZGRklJmZVNw+Y2NjuXr1Km+88QYdO3Ysdp8lbSsnJ4ft27dz8+ZNhg8fjq+vb4kUVlEUiYyMZP78+Xh4eDB37lxSUlIICAhg+PDh7Nq1i61bt8pBqJWVFQqFguPHjxMeHl5oW6mpqRw9epTatWtjaWmJu7s7169fJyIiglmzZrF582aZzSRVOmfNmsXSpUvJycmhf//+hcYpCIIcLO3atYsvv/yyWG9jPT09WrRowe7du1EqldjZ2aFSqXjw4AE1atQo07WoShAEATc3N5KSklCpVFWml1KiA/v6+lK/fn1CQ0PZtm0bO3fupH///tSvX/+xAnCPbsfAwIBevXrh5ubG999/z6uvvlqIXWRjY4OHhwdBQUG0atUKpVKJn58fly9fpnv37vJ2GjduzNWrV6lfvz5+fn6EhobSu3dvIiIi6N69O5aWlvzwww/079+fFi1ayO8iJycn4uPjy+28SMHw6tWr2bp1a6lE+0qCUqlk7NixfPvtt9SqVetfYamkp6eHiYkJGRkZWFhYoKenVx0I/wNVZ5VURVGR/ni3bt2SJ7AXBenp6Zw7d+5fXw2WhLIcHR25f/8+Tk5OJS5qQkNDOXDgAJMmTSo2qSEFAOvWrWPKlCklKh1LfRvS31JSUkhKSiInJwc3NzcUCgXBwcHUqVOHuLg4atasWSJbQRRF+Z9Ei9FqtfI/jUZT6N+jf5O+/+g2nnSudDodN2/eZMGCBejp6TF//vxCSpMl/U6j0XDu3Dk++ugjkpOT+fDDD+nVq1eFWpa96MjKysLExKTQy16r1RISEkLDhg3RarXcvHmThg0bVqlzKIoi+/fvp2fPnvLYtVotBw4coFevXlVqrNUoCkF4qDbcq1cvVqxYQXZ2dpG5QU9Pj9GjR3P+/Hn+/vtvfv75ZyZNmlREaFB69uPj49m7dy8LFixg0aJFBAcH0759e+bPn8+sWbPo2LFjiR6r+vr6snL0kyDNYxqNhtjYWHmfX3zxBdeuXaNdu3ZMmTKF5s2b88orr5TK1/VRIb+PPvoIpVLJ/Pnz8ff3LzaAlvZ/+PBh5s2bh0qlYvr06RgaGuLk5MS7776LiYkJgwcP5quvvpIX4Z6enoSGhhIeHl7kfGs0Gvbv309+fj5AofN85MgRvv7660JVMkEQsLCwYPr06URHR7Nx40ZZSOef57Z///689NJLfPnll9y5c6fIdxo3bkxGRgb379/H3t4eGxsbrl+//kJX0iT2Q2pqKkZGRqSlpVX2kApBEAT09PSoW7cus2fPpn///vzxxx988803xMbGlvrcKxQK/P39efvtt9mwYQN///13oep3t27dOHbsGFqtFkEQaNWqFefPny9Eqa1bty53795Fp9PRuHFjbt++jbW1tZys8fLykoW69u3bJwdf1tbWZfYSftI5kXqGU1JS2LFjx1NTfyWBsZ49e/LLL79UOiOgPCAlt7KysoCHc3Q1NbowqivCj4HkQ1gR9EKpItylS5dy33ZFQRRFDh48SKtWrWSxpn8rJJGnzp07k5WVVcSmRvpOSkoKq1atYsKECcWKtIiiSHJyMitXruSNN97A1dW1xMWVNOlKf09ISMDIyIjMzEy8vLyAh5W+3r17c+rUKQICAsjPz0ej0ZCZmUlaWppMm8vMzCQrK4ucnBzUajVarVZ+ST76v1IWWdqnQqGQ/+nr62NiYoKpqSnm5ubyPwsLC6ytrVEqlejp6ZGfn8+OHTsIDw/n9ddfL5UtilarJTw8nC1btmBiYsKbb76Jm5tbdTBUCkRGRsqJEQlpaWmo1WocHBxISEhAqVSWqq/9eUEURe7fv09iYqLcPy/NgQCenp7V1/4FgCAItG7dmoyMDH766SdZ5+DRa2dqasrw4cMZN24cn3zyiTwfSMrR8fHxXLx4kevXr6Ovr4+fnx+jRo3C2dm5THYxEt03Li6uRE0GiW0SGxvLhQsXuHHjhlxZk/YpUZf/+usv6tevX6o2DGnu37JlC2lpabz11lu4u7uXOHZJSPGXX34hJycHR0dHBg0aVOw7QxIDW7t2LWvWrMHY2JiTJ09iZGQkqzU/inPnznHv3j28vb0pKCiQq2R169aVF72P9pNKdNvJkyezZs0aVq1axWuvvVaIti69E1q1aoWDgwM//vgjr7zyCi1btpTnHVtbWzw9Pblx4wbdunWT9StepDVNcXBxceHChQvY2dmRkJBQatvE5wkpIPb19cXHx4dLly6xdOlS6tWrR79+/bCysipVddjd3Z3333+fJUuWkJGRQc+ePdHX18fDw0NOGnl4eODq6kp+fj5JSUk4OjoCD+nxBQUFpKWlyQUdURRJSEhAo9HIFmfvv/8+K1euJCUlhaFDh8rin+UpRCaJ9k2YMIGlS5fKCdenYUQJwkNLpcuXL3P69OlCImEvIiRhvKysLARBQF9fv7oi/A9UB8KPgUT1rAg7j5ycHPLz86vUYvVJSE1N5cqVK3zwwQcv9MRQGoiiSFpaGsbGxhgYGBQrTCHZgfTs2bNYARl42Ae+dOlSXn755SfK8ut0OvnvUkXawMCApKQkLCwsuHv3LleuXMHS0pLt27fTuHFj/vrrL+Dh4tPGxgYLCwssLCxwcXGR+0Ulb2I9Pb1CNDjpJfFo5VeqckhV45ycHLKyssjKyiItLY3o6GgyMzPJyMhArVZz//594uLi0Gg0DBo0SK7OWFlZYWJiUkT8S0oMbNu2jbi4OAYPHlzqxWc1/ker/GfgGBISgo+PD3p6ely6dKnUwmTPEwcPHqRjx46F/FP37NlDjx49qtxYq1EyFAoF3bt3Jzk5mV9//ZXRo0cXYieo1WoOHz5Mp06duHnzJoGBgXIgGhoaioWFBU2aNGHKlCnY2to+U49vrVq1OHv2bKHPJF/eiIgILly4QHh4OFZWVjRt2pS3334bGxubIvvU6XRcvHiRV1555Yn7VKvVnD59mj179tC1a1c6dOjw2ABep9Nx+/Zt1q1bR7t27VCr1SQkJBRrRyXZ6jVt2pRevXrRqVMn1q1bx6BBg8jLy2Pz5s3k5ORw5coV7O3tsba2xsfHh4yMDOChmq/kOzxw4EA6dOhQIk3U2NiY8ePHs2nTJlasWMGECROKsN8EQaB27drMnDmT5cuXk5SURJ8+feTntV27dhw5cgRra2vS09NJT08nKyvrhU6UOzg4kJaWhr+/P/Hx8UVECasalEolLVu2pGHDhhw9epTPPvuM3r1706pVq1JZFNra2jJz5kyWLVuGRqPh5ZdfRk9Pj7Zt2/L333/j7u6OQqGgYcOGBAUFyYGwQqHAw8ODiIgI6tWrh4WFhRwEZ2Vlycw3MzMzpkyZwqZNm1i5ciUDBw4kOzsbrVZb7vO+sbExb775JkuWLMHU1FQWmSsrJLr1l19+Sd26datkMqQs+GdFuDoQLozq1cdjIFE+y/thlRazjo6OpRIPqQoQRZHDhw/TqlWrF07c62mgVqtRq9Xk5eUVm7XX6XRs3boVFxcX2rVrV+zLRgqUmzZtWqK/5qOQAtHk5GQSExPZv38/MTExFBQUcOTIEfbv3y8Hts2bN+fdd9+Vq7LSwq6iX9hSNSIzM5PffvuNrKwsFi5ciIGBAffv3ycpKYkbN26QkZFBXl6eLKrh5OSEm5sboaGhnDp1ipdeeonXXnut3NRe/yvQ6XRER0fTrl27Qp9du3aN9u3by73o48aNq8RRFkVmZibBwcG88sorhSoHDx48wM/Pr/oeeMGgr6/PsGHDWLZsGQcOHKBHjx4oFAp0Oh1//PEHBQUF9O7dm6+//pqzZ8/SrFkzmjVrRv/+/TE3Ny+TBczjYG9vT1JSEvCwlSQkJIQLFy6QkJCAs7MzzZo1Y8iQIZiZmT12n1IQV5z1kwRRFImNjWXDhg0YGhqWys+8oKCAffv2ce7cOcaPH49SqWTZsmXMmTOnyLpCcmPIycmhT58+cvLy3r17DB06lCNHjjBp0iRUKhVffPEFzZs3p3///rRu3Vre1vTp0xFFERcXF+7cuUOnTp0ee/6USiWjRo1i27ZtLFmyhMmTJxdS/Ib/KYfPnDmTn3/+mXXr1jFy5EiMjIxo0qQJoijK4lIuLi6EhoYSEBDw2P1WZSiVSvkcBgcHV/ZwSgWpyt+nTx+aN2/Opk2bOH36NKNGjXosC036rRSsLlu2jB07dtC/f38CAgJYuHAheXl5GBsb06xZMzZt2kTXrl3l+83f35/g4GACAwPx9/fn5s2b2NrakpqaKmtYCIKAkZERo0ePZufOnaxevVpeH1QE21JiO3z//feYm5vTtGnTp5prHBwc6NWrFxs2bGDq1KnP5FVc2TA3Nyc7OxtBEDAxMZGF0KrxENWB8GMg9UpWhFjCi9YfnJ6ezpUrV/4zPp8PHjzAzMyMpKSkIpRdye4lIiKC2bNnF3t/aLVaNm/ejJWVFb179y6SlXyUnpycnEx4eDgnT57k+vXrKBQKatasSXR0NA4ODlhaWvLhhx+yfft23NzciImJoVOnTsX69D0P3Llzh3Xr1tGwYUMWLFggi1rVrl1bPi7p2UlLSyM2Npb9+/fz+eefY29vj5ubG7du3SIvLw9vb29cXV1lz0vgP3F/PS2kbPujTJL8/Hzi4uLw8vIiJSUFjUYjWxNVBYiiyPHjx2nSpEmhStG+ffvo2LFjiaq61ajaMDIy4o033uCLL76gRo0a1KtXj4MHD7J06VKaNm3K+fPneeutt9izZw8DBgx4LHW4rJCShmq1mhs3brBgwQJycnKoVasWnTt3xsfHR06ylWafd+7cwdvbu9ikt7SfgwcPcvz4cQYOHEizZs0euy4QRZHU1FR+/vlnTE1NmTNnDoaGhnz22WcMHTq0iE2YKIqEhYVx6NAh5s2bJ2tNxMTEYG5ujpWVFTdu3OCNN95g//79ODk5ya0rj+pSGBgY0LBhQ+7du0dkZKRMUX0c9PT0GDRoEHv37uXbb79l2rRpxSZ/zczMmDx5Mr/++itLly5l0qRJWFhY0KFDB2JjY8nKyqJTp06cP3/+qYOPqgADAwM5WfOoUvKLAEEQcHBwYNq0aVy+fJnvv/+eNm3a0KtXr8dWh6VAesqUKSxZsoSdO3fSt29fXFxcCAkJoUmTJri4uJCTk0N6eroslOfj48PevXvRaDQEBASwZs0axowZQ1hYGLVr1y60DwMDA/r378+BAwf44osv5DVWed8nUh/8hAkTWLx4MRYWFiUy9p60nXbt2nHp0iXOnj37QlOkraysZLV/iSZdjf+hOhB+DKSKcEUEwqGhoYwePbrct1sRkJSiW7VqVeXsWCoCUrWqRo0aJCQkFJpEpd7hbdu28f777xe7iNfpdBw5coSEhASmT58uL66kxZtKpSI8PJyrV68SGhoqC6LY2dnRsWNHPvnkE3Q6HQcPHsTQ0JAaNWqgr6/P3bt36dKlC4cOHSpkP/O8zkl+fj67du3iypUrvPbaa9SpUwcoHLhK/1+iYUvVbFEUWb9+vWzFkJSUREREBMeOHeP+/fvo6+vj5OREgwYN8Pb2xtraWj5vL+rLpyKQnZ2NgYFBISZJfHw81tbWGBsbc+HCBerWrVulqMYqlYqTJ08ya9Ys+VpKar1Dhw6tvr4vKKR3Y6tWrZgxYwZmZmYYGBiwePFiGjRoILcU2dvbs3r1ambPnv1MVoRS20ZycjKXLl3i4sWLqNVqNBoNXbt2JSAgQA76ynJP6XQ6Ll++TPv27Yvd571791i7di0ODg588MEHWFpaPrHF5erVq2zcuJHevXvToUMHFAoFO3bswNnZmcaNGxdJrGZlZbF69Wpef/11OUiWrKdatmxJZmYmarUaOzs74uLicHZ2Jj8/v0iQKwgCfn5+nDt3DjMzM6Kjo4sEJP+ElCzo1asXJiYmfPXVV0yfPh17e/sic7tSqWT06NH8+eeffPXVV0ybNo3mzZtz8eJFtFotHh4e7Nixg7y8vAqznaxoKBSKQj65VUU5urSQ+ocDAwOpW7cumzZt4ssvv2TcuHGPVeaXqoXTpk3jm2++wczMjPbt23P48GEaN26Mvr4+9evX5/r163Ts2BFBELC0tJTvXz8/P1lTJyoqqtgeYD09PXr06MGhQ4dYtGgR8+fPrxC3AInFMH78eFauXMn06dNxdHQs83709PQYM2YMX331FQ0aNChR6LSqw8rKivT0dOBhIFySLdp/FVVntVQFUVGBcG5uLtnZ2S+MzYBUDZ4zZ84LOQk8DWJjY3F0dCQ4OLgQvSw7O5uff/6ZUaNGFVkoALIdzPHjx5k1axaGhoZotVqysrK4desW58+fJzExEScnJxo1akS3bt1kX8q1a9eSmJiIQqEgLS2N+Ph4DA0NcXFxkdUr8/Pz5QrB84IoikRHR7N27Vo8PDz44IMPHkuPl+xE9u7dy+XLl+nbty/NmjWTF22WlpZYWlri7e1Nt27dUKvVpKenExcXx40bNzh69ChqtRpHR0d8fX2pV68elpaWpep3+rcjOjoaR0fHQsmVoKAg/Pz8UCgUXLp0iZdffrlKnadLly7h4eEhC85JdmPNmjX7TyTW/k2QdDPu3r3L6dOniY6Oxs3Njddee41vv/2WX375hUaNGhW6/3x9fQkODmbHjh0MGzasTD17UjU2KSmJixcvcuXKFURRpGHDhowbNw5HR0eWL1+OhYXFU9sQqlQqEhISZEsvab8qlYoDBw5w5swZhg4dSqNGjZ5YBc7Ly+OPP/4gLCyM6dOny7TU6Ohozp49ywcffFDk+LVaLRs3bqRFixbUqVNHHkN+fj4hISH06dOH27dv4+npib6+Pvfu3cPFxYX4+Phiq722traoVCoaN27M5cuXqVWrVqnmA4VCQceOHTE2NubLL79k2rRpuLi4FAmG9fT06Nu3L1ZWVixatIhBgwZx9+5dateuTV5eHpaWlsTFxeHt7V2q81/VIImwpaWloVAoSE9PL7M9V1XAo5XR8+fP880339C7d2/atGlTYqJUEASMjY2ZOnUqX331FR06dCApKYm0tDRsbW1p3rw5O3bsoH379nJLloeHB+Hh4XLBwMDAQNYNKe7+lNhjxsbGLF68mIkTJz62JeFZjt/Ly4uRI0eybNky3n333TJbfkoV9q5du7J161beeOONFyopIsHY2BiVSgU8tJ3Ly8ur5BFVLVQHwo+BWq1GT0+v3G/8+Ph4bGxsXoj+YEkpukWLFi+0AEZZERUVRbt27Thz5oxMQ9VoNGzYsIEmTZoUa00jCVytX7+eKVOmoFAoOHPmDKdPnyYlJQVvb2+6du2Kh4cHpqamRaoCBQUF8mJOshfIzs6mTp063L59m3r16nHp0iWaNGnyXCp+0iL06NGj/PXXXwwdOpSGDRs+9nlQq9VcvnyZ7du306hRI+bNm4e5ufljs9BKpRIHBwccHBxo1KiRLNJ17949goODOXr0qOw926hRIzw8PLCwsKhSHrnPA1J16lGqvk6n48aNG4wbN46MjAxSU1Px9PSs5JH+DwUFBRw6dIjXXntN/iw7O5uzZ88ye/bsShxZNUoLKcCLiIjg9OnTRERE4OTkROvWrRk9ejSCIPDVV18xYsQIDh8+TIMGDQoFpYIg8Morr/DFF19w8+bNEhWeH91fQUEBCQkJXLhwQW4XadKkCRMnTsTe3r5QUszV1ZWYmBh8fX2f6vhiYmKwtbXF2NhY3n9YWBgbNmzA3d2dDz744LFzmPSb6OhoVq9eLVvbSC0j+fn5bNiwgSFDhhRJ/IiiyKlTp8jMzGTcuHGF5rSYmBgsLCywtLTk0qVLtGzZkvz8fB48eEDDhg2JjIwsdg40MjLC1dUVY2NjLl68yKBBg0odZCgUClq2bImpqSnfffcdkyZNKtYFQKFQ0KFDBywsLFizZg0RERF4enqSkJBA06ZNuXLlSqncA6oq3N3dCQ4OxtLSkpSUlBcyEJagp6dHy5YtqV27NmvWrOH27duMHDmyxGS2FEBPnTqVb7/9FgMDA86ePUuvXr1wdXUlLS2NrKwsWZm6QYMG3Lhxg4CAAHx8fIiKikKtVhfLWJDg6OiIqakpLVq0kIXaKuJ+EQQBf39/MjMz+fHHH5kyZUqZNW4EQaBDhw5cuHCB4ODgKmdLWBoolUoKCgqAh0FxTk5OJY+oaqE6EH4McnJyMDQ0LPdA+M6dO/j4+LwQD1N6ejqXL1/+z/QGS0hNTZUnTEk848yZM2RkZBRZsEjIyspi8eLFNGzYkH379hEZGUmtWrXo3bs3Xl5eTxSGejQQTkpKoqCggIyMDDw9PQkKCqJLly5s3bqVt956q2IO+h948OABq1evxtjYmNmzZz/WkkESktm0aROiKDJlyhScnZ3LHKxKGWUrKyusrKzw8/OT+2Jv377NqVOn2LJlC9bW1jRu3JgGDRpQs2bNFzJL+zSIiIigR48e8n/n5OSgUqmws7Pj5s2buLq6PnVlrCIQGhqKkZGR3B8qiiIXLlzA29u7zNn5ajw/SDTk6OhoTp06RUhICLa2trRp04bhw4fLiTytVssPP/xAgwYN6NevH7/88gvbtm1jyJAhhZ59IyMjxowZw6pVq3j//feLTaqq1Wru3bvHuXPnuHnzJgYGBgQGBvLWW2/JrJni5h93d3cuX7781McZFBQkKwPn5eWxa9curl69ysiRI2Uv9MfN2xqNhmPHjnHw4EFGjhxJw4YNCynyHz9+HCsrqyKUaHjIPPrzzz+ZPXt2oTYbSYeiefPmaLVaYmJiGDFiBAUFBahUKpycnNBoNMWOSxAEGjZsyO3bt9FoNCQnJ5eJfSYFD2+88QY//PAD48aNK1bPRBAEmjRpgomJCWPGjOHu3bvExsbSpk0bfv755wpRBX5esLGxIS0tDXd3d5KTk/Hx8ansIT0TpMrmO++8w/bt2/nyyy+ZOHFiiXRhQRCwt7fnjTfe4IMPPiA9PZ2ePXtiZGSEt7c3N27ckAVAfXx82L9/P1qtlhYtWhAUFCR7MRcXdAqCgJ2dHbGxsXTv3p0JEyawcuVKxo8fX4gRUZ7H3rp1a7Kysli3bh0TJkwo8ztSqVQyYsQIVq5cibe3d4U4yVQkpEBYFEWMjY1fuN73isaLOUs9J+Tk5BSxf3lWiKLInTt3Ci1mqypEUeTAgQO0bNnyP1UNzs/PJy8vj4KCAqytrWULox07djB79uxCk6gkDpWens7ChQu5fPky1tbWdOzYkTFjxsh9UqWZ3AsKCmTFzsjISNLT07G2tsbe3p7ExERMTExQKBQVSqmX+pgvXrzIli1b6NevH23atClxMShVi/78808uXbrEgAEDCAwMLHHRWlZIgbGNjQ0tW7akZcuWqNVqoqOjuXLlCj/++COiKOLn50dgYCCurq5yUPxvS9xI3qVSdUIURUJDQ3Fzc8PQ0JBLly5VKbVWrVbLvn37Cvk5FhQUcOzYMSZOnFjJo6vGPyE9+4mJiZw9e5bLly9jZGRE69at6du3rzw3PUof3r17N2q1mn79+qFUKhk5ciRffPEF58+fp0WLFoUE8Dw9PWnevDm//fYbY8eOlQNpiTYcHByMiYkJzZs35+2335YFeZ70HNvb25OcnPxUvqRarZaQkBAmTJhAaGgoa9eupW7dunz44YeYmJg8sQqcnp7O2rVr0Wq1zJs3r1CyUBRFkpKSOHToEHPmzCmyjsjLy+PHH39k+PDh2NnZFfqbWq3m5s2b9OrVi9jYWExMTLC2tiYhIYGcnBzs7OxKDIQBfHx82LdvHz4+Pty6davM7wwpwJkyZQpLly5l1KhRRSjv0vfq1q1L//79WbJkCXXq1OGVV14hPz+fzMzMFzbZZWJiQkFBAW5ubkRGRtK6devKHlK5wMDAgMGDB3Px4kW+/vrrEq8rPLy2Hh4eTJkyhRkzZhATE4O7uzstWrRg//79tGrVSq4ea7VasrOzadSoEfv27aNx48ZERETg5uZW7DhsbGxkRe7atWvz1ltvsWzZMl577TUaNGhQ7u9uhULBSy+9xPr169m5cycDBw4s07pemr8aN27M9u3bGTly5Au1vlAqlWg0GjkQrqZGF0Z1IPwY5ObmPvFlWFaoVCpZibiqQ+oN/i/4Bj+KlJQUjI2NSUlJwcnJCZ1Oxy+//EK/fv0K+clJmfoDBw6wY8cOmjZtysaNG3F0dHyq5EleXp6s9hsTEwOAnZ0dubm52NjYcOfOHfz8/Cqs+in1/23dupWYmBjeffddnJycSrz2Go2G69evs2XLFvz9/Zk/f36F9nxK41AqlXh7e+Pt7Y1Wq+X+/ftcu3aNX3/9lZycHOrVq0erVq1wdXX9V/UVq1QqNBpNoXN89epVGjdujEqlIioqqsqIT4miSHx8PBkZGfLCRhRFbt26hZWV1WPvq2o8X+h0OjIzM7l48SJnzpyRFWCnTJlCjRo1ip3LpMr+xYsXmTNnjpwclHw8v/rqK9ky7dFg+KWXXmLhwoUcOnSI9PR0goKC5OB3xowZ2NnZlXnutLe3JzMzE5VKJdObS4vs7GwyMzPZt28f4eHhjBkz5ol+7/C/loQNGzbQuXNnunTpUqT6qdVqWb9+PS+//HIRkR2dTseuXbuoVasWTZo0KdImExUVhaWlJVZWVpw8eVKuWCcmJqJSqbC2tkar1ZY4ThsbGxQKBZ6enly8eJEOHTqU+XmTAqHp06fz/fffo1arCQwMLDYYrlevHmZmZuzZs4eePXvi5eVFaGgoLVq0KNM+qwqMjY0xMzNDT0+PxMTEyh5OuUFKLDVr1kzur09OTqZz587FrisEQSAwMJBRo0axevVqPvjgA9zd3UlKSkKlUsmq5e7u7ty9e5datWqRkZGBjY0NkZGRtG/fvtj7zsbGhvT0dFmDx8PDg6lTp7Js2TJGjhxZId7Nenp6DB06lKVLl3L69GnatGlTpn0IgkDfvn1ZsGABkZGReHl5lev4KhJKpRKFQiFfs7y8vKdKHP5bUR0IPwZSIFyeSE1NxcjIqMorKkqehs2bN//PCdpIVTdJnfPcuXOIokjr1q0RRRGNRsPdu3fZs2cPmZmZWFhY0LBhQ+bOnftMlBlJaVOn0xEWFoaFhQXm5uaEhobi7+/PlStXGDZsWDke6f8geVuvXr0af39/Zs2aJfe4FffdpKQktmzZQmZmpix2URk9u3p6ejg5OeHk5ES3bt1ITU0lODhY9jhu0KABLVu2xNnZGaVS+UJP/AkJCVhZWcnaAjqdjsjISPr27UtSUhJmZmZVxuNbFEX2799P586d5T4xrVbL/v376dev33+uv7uqQUp63blzh7///puEhAT8/PwYM2YMTk5Oj00gSYHab7/9xowZM4rMeQ4ODowcOZJVq1bx3nvvYWpqikaj4f79+5w9e5YHDx6wYMECpk2bxttvv429vf0zJfeMjY3R19cnOzu7TIGwTqfj9OnTBAUFERgYyLx580qV+M7Ly2PHjh3cunWLSZMm4enpWaxexNmzZxFFUa6cPfq30NBQrl27xrx584p9Fs6cOUPz5s0BuH79OiNHjgSQFfatrKzQ6XQlPkf6+vrUqlWLgoICkpOTyczMLOIPXBoIgoCLiwszZsxg8eLFqFQqmSH0KDw9PfH09CQ+Pp5t27bh6OjI1atXad68+Qs55yoUChwcHNBoNKSlpaHVav9V7TeCIODm5sZ7773HihUrSElJYcCAAcVShhUKBS+//DIDBw6kVatWdOvWDWdnZ0JDQ+V+WV9fX27cuEGTJk3kYkF0dHSJYrPW1tZkZ2ej0Whk9pibm5scDGs0miIJovKAsbExr7/+Ot9++y0ODg5lblE0NjZmyJAhbN68mZkzZ1apNqTHwcDAAAMDAzmmqQ6EC6M6EH4MKiIQjoiIKKROWVWRkZHBhQsX/lNK0RJiYmJwdXUlNDSUBg0a8OuvvzJt2jR0Oh1BQUHs27cPhUJBr169MDMz48cff+Sdd955ZmsQiYqfl5dHdHQ0Wq0WT09PIiIiaNiwISdOnMDd3b0cj/Qh1Go1R44c4dixY4wePZoGDRqUuMDKz8/n6NGjHDt2jJ49e9K6desqE2Dq6elhb29Pp06daNeuHRkZGVy9epVff/2V/Px8mjRpQvPmzalRo8YLuaiJj48vVElNSkpCX18fW1tbdu/eXag3sbKRnp5OWFgYw4YNk6vB9+7dQ6VSvdAiOi861Go1sbGxnDx5klu3buHo6EiHDh3w8fHB2Ni4VNclPT2dH3/8kVdffbXYHkOpxzQsLIxVq1ZRq1YtLl26hE6nIzAwkA8++IBTp06RkZGBg4PDM9+zEj0zIyNDViZ/EjIzM/njjz9Yv34977//Pt26dXviOCQdhFWrVuHh4cH7779fRPRQQlpaGjt37uTdd98tIhiUm5vLhg0bGD16dLHvDLVaza1bt+jVqxdpaWnk5OTg5uYm09atra1lynFJY5b6d48dOyZ70vv7+5fq3BS3LUdHR959910WL15MQUEBnTp1KrTvmjVr4ujoSF5eHmPGjGHjxo1cvnyZ11577YUQBS0Ozs7O5OTkUFBQQE5Ozr+yPczGxoZ33nmHVatWsX79ekaNGlWsJWSNGjVo1aoVGzZswNvbm4CAAC5dukTDhg0BqFWrFvv375fvu4iICPLy8uRA95+Qngm1Wi3vT0q6TJs2je+//x6gQoJha2trXn/9dX766SemTp0qs/BKA2luO3HiBOfOnXthvIUVCgVGRkbk5uZiampKXl7eYxNp/zVUn4USIGXMy0q1etI2b9++Td26dcttmxUBURQ5ceIETZo0eaos8osOyZ4iMzOTs2fP4u/vT2JiIp9++ilHjx5lyJAhvP/++9SuXZtVq1YxcuTIp/Ko+yekinB2djYqlYqUlBRcXFzIy8sjNTUVLy+vchUfkXrcli1bxq1bt5g7dy6+vr5FJkepdzA8PJzPPvuMqKgo5syZQ8eOHZ8oAFZZkALEzp07M3v2bCZPngzAsmXL+Pzzzzl+/DiZmZnysb0ICAsLK+QJeufOHWrXri1bdpXU6/W8IbFJAgMDC1Wo9+7dy0svvVSikmg1yh/S/Z2WlsaBAwdYsGAB69atw8nJiffff58pU6bQsGHDUrcA5efn8+OPP9KpU6civXzSvlJTUzl27BjBwcHs2rWLkydP8vrrrzN//nz69OlDzZo16dOnD9HR0dy8ebNcnj9JOfpJ50Kn0xEcHMwnn3yCubk5gYGBNGrU6LELQkk47K+//uK7776jd+/ejBkzBjMzs2LPmU6n4/fff6djx45FFtmiKLJt2zYaNGhQojBQWFgY1tbW2Nracvv2bby9vdHT05NdCWxsbORK1OPGLak4N2zYkIsXLz7zebazs2PGjBn8/fffHDp0CJ1OJ/9N6mGWepdnz56Nnp4eBw8efGHm13/C09OTmJgYTExMyMrKquzhVBiMjY2ZOHEiWq2WNWvWkJ+fX+Q7giDQqVMnateuzdq1a3F2diYsLAytVgs8tOySWizq168vW3tJ7hfFbU9fXx+1Wl3kc0dHR6ZPn86WLVsICgoq9/tHEATc3d0ZMGAAP//8M9nZ2WXah0KhYOjQoTIj8EW5v01MTOSYJj8/v9Dz+19HdSD8GOTk5JQr1VAS+anqFZHs7GxOnz5Nt27dKnsozx2iKJKcnIylpSVJSUns27ePq1evcujQIUaMGMHMmTPx8fFBFEVWrVpF69aty01OX+rfyM7OJj09XVardnZ25tq1azRr1qwcjvAhJHreZ599ho+PD9OmTcPS0rJYil9ubi6//vorP/30EwMGDGDixIkvjLG8IDz0vaxZsyb9+vXjk08+Yfjw4dy9e5dPPvmEH374gdu3b6NWq6v0C03quXVycpL/+/r16zRs2JDs7Gzy8vJKXQ2raOTl5XH+/Hk6duwo3yPJycncu3evWOXcapQ/JAuimzdvsmTJEhYuXEhycjITJkxg/vz5dO7cGSsrqycqIj8KnU7H5s2bsbOzkyuCUvCbm5vL+fPn+eqrr/jiiy+IiYlh5MiRbN26Fa1WK1MkH+3zf/XVV9m8eTO5ubnPfLxPCoSlMW7YsIEtW7YwceJEOnXqhIGBwWOtcURRJDMzk2XLlsn90AEBASUGoKIoEhISQkxMDF27di2SKLh16xZ37twpsT1AFEVOnjxJmzZtgIce3IGBgcDD1oL4+HisrKxkWuPjmC0WFhZYWFhgZWXF3bt3iw1wygJBELC2tuadd97h3Llz7N+/X15MGxsbY2FhQZ06dbh79y7W1tb07duXZcuWFfreiwRra2tSU1OxsbEpMaD7N0ASpBw7dixKpZKffvpJttp59DuBgYEUFBTg6+vLsWPHZL9geFjhdXJyIioqigYNGhAfH4+trS0xMTHFvlcVCgUGBgYlBt01atTgnXfe4ddff+X69esVEgw3adKExo0bs3HjRjmgL+1vpQr5jh07qvS64VGYmpqSm5srJ9VexGeyolAdCD8GGRkZ5UqHycnJQafTVWmKjfQi9vf3x9ra+j+3aFWpVGRmZpKYmMjJkydxd3dn3LhxzJo1izp16siLv/379wPQs2fPcjtHBQUFmJqaEhcXR1xcHPb29rJ9UlxcXLlZCxQUFLB7927WrFnD66+/Ts+ePdHX1y+yba1WK1dPAD744AP8/f1fWDqNtHCsVauWXKFq0qQJO3fuZP78+ezbt4/U1FR0Ol2Ve7lptVpZhAQeVubi4+Px9PQkNDQUDw+PKtOvdPbsWby9vQupWx86dIi2bdtWeW2EFxlS5TIpKanQPd2qVSs++ugjRo4ciaura5mC30e3fezYMeLi4hg5ciR6enqoVCpCQkJYuXIl8+fP5/Lly/To0YOPP/6Y1157DW9vbxwcHBgzZgw//fRTIe9KSYipQYMG7Nu375kWZVIVKTExsdjnVqfTcefOHT799FOUSiVz586lVq1aREdH4+LiUiJDQRLE+uSTT6hVqxbTp0+XlaxLgkqlYvPmzYwaNarI85idnc0vv/zCq6++WuJzkJuby927d/H39yc3N5e4uDi8vb1lhe2cnBwsLS1loazHBcISjTMyMhJjY2OSkpJK/G5pIQgCVlZWvP3221y+fJk9e/bI/bMODg64uLhw+vRpAAICAggICODChQuyvc6LBEtLS/Ly8nByciI6Orqyh1OhkILh0aNHY2xszNq1a4sEw9bW1piYmODv709cXBwKhYKgoCD59w0aNODmzZs4OTmRnZ2NnZ0dUVFRJe5PSjSU9PeaNWsybdo0fv31V27cuFEhwfBLL72EKIocPny4TNsXBIGuXbsSGhpKdHR0lVsvFAcTExNycnIKqdpX4yFezBXtc4IkhFReiI2NxdHRsUr3J+bl5XHixAm6dev2nwuCpR6wq1ev8v3331O/fn0+//xz6tevL18zURS5efMmZ8+eZdy4ceV6LQsKCjA0NCQmJkbOmCYlJWFqaoqDg8Mz0/QliuSyZctkenNxwbVEb1y1ahXbtm1j3LhxDBs2rEQq4IsIQRAwMzOjefPmzJo1i8mTJ5OZmcmiRYtYsWIFd+7ckX33qgLS0tLQ09OThesePHiAkZERZmZmBAUFVRladEFBAUePHqV79+7yeLKysrhy5Qrt2rWr5NH9OyFVO69cucK3337Ld999hyiKvP3228yYMYPAwMBncj+Q5rxDhw7x+uuvk5SUxObNm5k/fz579uyhYcOGzJs3jzfffBM/P78i85Svry/+/v5s2bKlUDAkifBcuXKlxMpRaVGzZk1SU1MLLd4l3YWtW7fyyy+/MGbMGIYMGSIHobdu3aJ+/frFHm9ubi6//fYbW7ZsYdKkSfTq1euJiSYp4ePh4SEHrxJ0Oh2//fYbgYGBhdob/onQ0FAcHR2xsLAgOjqamjVryj22arWajIwMnJ2d5UD4Sa0yfn5+3L59G19fX65evVpu85kUDF+/fp3du3ej1WpxdnYGHmoXZGVl4eDggCiKvPnmm1y5coWDBw++UFUoSRHZyMiIhISEyh7Oc4EUDGu1WjZv3lyIuqxQKAgMDOT69euMGjWKsLAwzp07Jz/TtWrVIjw8HKVSiY+PD1qtloiIiGL3IwgCNjY2j/WzFQQBZ2dnJk+ezIYNG7h161a5v48NDAwYMWIE586d4/bt22XavomJCQMGDGDz5s0vRJLHysqK9PR0ORH6Ij2LFY3qQPgxUKlU5Sb0IPkH//MFWZUgVYPr1q1bZWiWzwOiKJKdnc327dv55JNPaNCgAQ0bNmTw4MFFFLMfPHjAL7/8wvjx4zE3N3+maylVcHJzc8nKyiIvL0/21ZT6wMzMzAgPDycgIOCZ9xUaGsoXX3xBvXr1ePPNN4tN8mg0Gk6fPs3nn3+Os7Mzc+bMwdvb+4WtAj8JUlXF2dmZoUOHMn/+fJo1a8a2bdv49NNPOXbsWJXoA5IoetJ1CA0NxdvbG51OR1RUFLVq1arU8Um4desWFhYWuLq6yp+dPn0af3///6TeQEVCFEXu37/P9u3bWbBgASdPnqRHjx589NFHvPLKK+UmCpeYmMjixYvx8vJixYoVrFqeCxVIAAEAAElEQVS1ChsbG2bNmsWMGTNo2bJlsW0VEhQKBf369SMxMbFIr6qZmRkDBw5kw4YNaDSapx6jkZERoijKVEtRFAkLC2PhwoWo1WrmzZsnM3qkv0dGRuLp6VloO1Iy9MsvvyQvL485c+aUStxSErI6efIkAwYMKDJf3rp1i8jISPr06fNYNe6TJ0/KCaOLFy8WmvdTUlLIzs7G0dERjUaDQqF4YiDs6upKVlYWtWvXJigoqFwXv+bm5kybNo1bt26xc+dO3NzcyMnJITk5maioKExNTbG3tyc1NZWpU6dy6dIljh49+sIswBUKhfwevn///gsR7JQHDAwMGDduHKmpqezdu1e+XoIg0LhxY4KDg3FycmLw4MGcOXOGtLQ04GEySmrT8fLyIikpibS0tGLfnVJFOD09/bFjEQQBV1dXJk+ezLp167h79265H6+5uTljx45l/fr1pKSklPp3giDQqFEj9PX1uXz5crmPq7xha2tLSkqKbKH1ojyHzwPVqtGPgVqtLjdhF51Ox927d2UV1aoISRH4nXfeqbJjLE9IfRIXL15k27Zt+Pr6MnDgQO7evcuOHTsYMmRIIRqJWq3m559/pnfv3sVaZjxpX/Cw4n7nzh2uXbtGbGwsWVlZaLVaWUjt66+/5uLFizx48AClUomNjQ3h4eH079//qa+JVqvl6NGjckWnpCpwUlISv/zyCzqdjhkzZlCzZs3/xH0gQRAETExMCAwMpGnTpsTFxXHo0CH279+Pn58f3bp1k8Vvnvd5iYmJwcXFBfhfha5du3bcv38fIyOjKhFkajQa9u3bx8svvyyfn7y8PI4fP87bb7/9n7qXKgqSfVtISAiHDh0iKSmJFi1a8O6778p9++VxnqWgMjg4mO+++w6dToeJiQljx47FxcWlzPRqpVLJ2LFj+eabb6hduza2trbyWBs1asSpU6c4ffp0ib6jT4Kenp6simpoaMiff/7JxYsXGT16NPXr1y8SmGZnZ5OVlYWjo6N8vFqtlhMnTrBnzx5GjBghK9aWZjw6nY4NGzbQt29frKysCv0tJyeHjRs3Mm7cuGIVeSVkZmZy7949Xn/9dTQaDbdv36Z3797y/hMTE9FoNNjZ2aFWq59IjYaHooEuLi7k5uaSl5dHVlZWkfE9LSRWzdSpU1m6dClxcXFkZWXh6urKqVOn8PPzo379+ty8eZM6deowdepUvv32W/T19enwFL7GlQFHR0fUajVZWVkUFBSUq3hqVYUgCCiVSsaPH8/XX3+Nra2t7LlrY2ODvr4+ycnJdO/enV27dhEcHEyHDh3k9UpiYiJ+fn4cOnQIURTJyMjA2tq6yH6sra0JCwt7oo2PZK00adIkVqxYwVtvvYW7u3u53T/S9vv06cOqVauYPn36Y5/TR6Gnp8ewYcNYtmwZvr6+z2SfWdEwMzMjJydHngurA+H/oToQLgHSgqO8AmGNRkNmZiZ2dnblsr3yhiiKnDt3Di8vL2rUqFHZw6lwSAqcGzduRBRFpk6diouLCxs3buTWrVsYGBgUmbz37duHlZVVmY3YJcGVffv2ceXKFVxdXWnSpAkdOnTAysoKY2Nj9PT0CA4O5o033iA2NpabN2+iVqsJCgoiLS2NyMjIMovbSNTAX375hezsbObOnYuVlVURARe1Wi0Hyv369aN169aFhG3+a5AWmK6urowbN47MzExOnz7N999/j4ODA7169aJWrVrP9RxFRUXh6+sLPGSqxMXFUatWLU6fPk3dunWrRLtFTEwMOTk5cqJFEvSqWbPmf2JOqUhIiqx///03Z86cwcbGhi5duuDr6/tYz9+yQAoG4+LiOH78OEFBQVy8eJHXXnuNESNGPJNCvNTH26tXL9auXcv06dPlaqaenh5Dhw7lyy+/pFGjRk8VqCkUCmrUqMG5c+e4fPkybm5ufPjhhyXaG6WkpGBhYYGBgYGsnr9u3Tq5elwWMUBRFLl06RIajYYWLVoUoUTv2rULPz8/atWq9dhqcEhICF5eXhgbGxMTE4OxsbF8LqTqv6GhIfb29rK4X2mYOo0bN+bmzZvUqlWLGzdu0Lp163INIkxNTZkyZQpfffWV3KZx6tQpxo4dS7169di4cSPwsOd22rRpfPPNN+jr65f5PVoZ8PT05Nq1a3JP/H8hEIb/XdfJkyfz9ddfY29vT506ddDX18ff35/Lly/Tp08fxowZw5YtW2jVqhVKpZJ69epx+/ZtAgICWLZsGYGBgbLl1z9hY2MjV4yfdB8IgoCnpyfjxo3jhx9+YOrUqYWsBMvjeFu0aEFUVBTbt29n8ODBpX6nuri4UL9+fY4cOVIoCVzVICUKpZaKf/aA/5fx7+Q7lhPKsyKcnJyMqalplZ1I8/PzOXToUKEM9L8RUv/X9u3bWbJkCe3atePdd9+VqZzh4eGkpaVRr169QguyyMhITp8+zYgRI8pkYSQphX766acYGBgwZ84cpkyZQps2bfDw8MDKykpeYOp0OvT19cnNzcXe3h4bGxteeuklevfuzYEDB1i5cmUhwZkn7Tc+Pp5Fixbh4ODA9OnTi4ifPUoDDA8PZ968ebRv375Y4az/IqRqkKWlpUw5bdOmDb///jufffYZFy5cQKVSVThtWloES9XotLQ0jI2NMTIy4tq1a+WmWv4s0Ol0HDx4kG7dusnPh0aj4cCBA+UqKPdfgpSkioyM5Oeff+azzz4jNzeXqVOn8u6779KkSZNy8fDW6XRkZGRw7NgxPvvsM9asWUPNmjXx9/enf//+jBo1CiMjo2fejyAItG3bFn19fY4dO1bouXFwcKB9+/Zs27atzJUKSSE7LS2NzZs388orrzBu3LjHahpERUXh4eEhW48tXLiQOnXqMH36dLlaXVrk5OSwbds2RowYUWi9IFnOBQcH07dv38cGrTqdjtOnT9O2bVsArly5gr+/f6F3zb179zAxMcHe3p6CggJZiftxEASB+vXrExERgb+/P5cuXSr1cZUWUmV4xowZKJVKQkNDSU5OJjU1lZo1a5KVlUV2djaCIGBra8v06dPZt29fuVg6VTTs7e1JSUmR3Rz+SxAEATs7OyZMmMDq1atlWm1AQABXrlxBFEUaN25MaGgof//9NwB16tThzp07mJmZYWpqiqWlJffu3St2+7a2tqSlpZX6eRcEgbp16zJkyBBWrFhBcnJyud4/CoWC/v37Ex0dzeXLl0u9bUEQ6NevH6dPn35sz3Nlw9jYGJVKhSAIGBsbl4ta/78F1YFwCZAqwuXh2yqKInfv3sXDw6PK9loGBQXh4OAgC178G6HT6QgJCeHTTz+VK6QtW7aUFy8FBQWEhoYSEBCAg4ODTI9RqVSsW7eOESNGlImCKooiN27cYP369UyaNIkBAwY8VolbCtLDw8MxNDTEy8uL+Ph4+vXrx6xZs3B0dGT58uVPnMB0Oh1Xrlzhu+++4+WXX2bAgAFFhF7y8/PZu3cvS5YsoVu3bkycOPGxNiL/dQiCgJGREc2aNeO9995j+PDhnD17lo8//pgjR46QlZVVYYs6lUpFRkYGDg4OAISEhFCnTh0KCgpkr+nKRmpqKpGRkQQGBsrV4MjISBQKRal6LKvxP0hMjvPnz7No0SJ++eUX6tWrx/z58xkyZAhOTk7P/B4RRRGVSsWtW7f44Ycf+PTTT4mJiWH06NHMnTsXOzs77t69y7hx48pVjVwS4zl06BCxsbHy54Ig0K1bNyIiIggLCyvTccTGxrJo0SIePHhAu3btaNy48RPPz927d3FxcWHz5s389ttvTJw4kR49epQ58S05CPj5+eHm5lbob/n5+axfv57hw4c/kTKZlZXF/fv3ZV/wy5cv07Rp00L7SUxMxNzcHCMjI9RqNTqdrlT3gYWFBXp6elhZWREfH19hlSALCwuaNWtGVlYWqampBAcHY2hoSI0aNQpZW9nZ2TF16lS2bdtWIWrA5Qk7OzsyMzOxt7cvdL/+VyAIAl5eXrz88susXLmSvLw8atasSUFBAampqZiamtKkSRO2bNlCVlYW7u7uJCcno1AocHJyQqPRlPg8GxoayvdxWcbTuHFjevXqxbJly0hPTy/X+8fQ0JBXX32VnTt3kpSUVOptW1hY0LlzZ/78888qSzk2NjYmLy9PXstUB8L/Q9WMyqoACgoKZOXe8kBISAj16tWrkgvCgoICDhw4wMsvv1zZQ6kwZGZmsnbtWjZu3MiYMWMYNWpUEYGX3NxcsrOzadq0qWyTIYoiR48exdHREX9//zLtMz09na1btzJt2rQSe4q1Wi23bt3i2LFjJCQksHv3blJSUoiPj6dOnTrk5uZSs2ZNlEol/fr1w8PDg+3bt5c42arVanbu3Mm2bduYNm1aEc9LURSJjo5m4cKF3Lt3j7lz5xIYGFguCZ//CgwMDKhduzZTp05lypQp3Lt3jwULFrBjxw4yMjLKfWGXlZWFgYEBRkZG6HQ6bt68SYMGDYiOjsbOzq7SLYmkZ6R58+Yy40UURfbu3ctLL71UfW+VEpKH+fbt2/n444+5ePEigwcPZu7cubRt27ZcVNtFUeTBgwf8+eeffPzxx+zatYuAgAA+/vhjxowZg6enJ/fv32fjxo28+eabFdJ7bmNjw9ChQ1m1ahUqlUr+3NDQkKFDh7J169ZSBWtqtZr9+/fz3Xff0aNHD9555x3Z/uxx0Gq13L59my1btqDRaJgzZ06ZNR8kxMfHc+HCBfr161foc1EU2bNnj2wR9bhti6LIlStXqFevHkZGRty/fx+dTif3L0vfycrKwsjICH19fZkaXRr6pr6+PnXr1uXevXtYW1sTGRlZ5uMsLTw8POjZsycqlYpjx46h0+nw8/Pj+vXr8ncka5w333yTX375hYiIiCobDEuCkubm5v8Z5eh/QhAEWrdujYeHB9u2bUNfX5969eoRFBSEQqGgRYsWKJVK9u3bh6GhIcbGxqSnp+Pm5kZBQUGJAaW+vj46na7MgaNEY+7YsSNLliwp14BOEB56BPft25c1a9YUUs1+0u/atWtHREQEsbGxVfJ+NjY2RqPRoNFo5KC4Gg9RHQiXAJVKhb6+frlVhOPi4qpE5eafkHqTTExMylWAoCpAEsOSvHAtLS358MMP8fHxKZJJl6r2rq6uZGZm4uHhATzsJfvrr78KCWeVdt+HDh2iffv2ODo6lvhbrVbLhx9+SPfu3QkJCeGLL74gLy+P/Px81q1bx40bN8jKygIeUk07duzItWvXSExMLOR3KylfL1++nJiYGObOnYuLi0shsa/8/Hx27drF0qVL6dOnDxMnTizSM1yN0kEQBBQKBY6OjowdO5bZs2ejUqlYsGABW7ZsITU1FVEUy+WFmJ6eLl8ntVpNQkIC7u7uBAUF0bhx40q/fnl5eVy4cEEWOpKo3ElJSfj5+VX6+KoypDkqKiqKlStX8uWXXyKKIu+99x5vvfUW3t7ez9wDLFGsr1+/zrfffsuiRYtQqVRMmzaN9957j2bNmsnJlMzMTH744QdGjRpVYewgQRBo0qQJbm5u7N69u5Aqbf369TE3N+fChQslPjuSsN/XX3/N3bt3+eCDDwgICMDS0pLc3NwS1X0lltfBgwe5evUqr7/+OqNGjXpqaymNRsPWrVt5+eWXCyUppCr12bNnGTRo0BOrtjqdjlOnTtG2bVsEQeDy5ctFaNEqlYrs7Gysra0xMDCQF+ilCYSlKtr169dp1KhRhdCjJXh6eqJWq2nVqhUXLlzg0KFD1KlTh7t37xYKeCSBovHjx7NixQri4+OrZPAg0b7NzMxISEiokmN8HhAEgYEDBxIREcHVq1dp1qwZFy5cAKBRo0bY2tpy/fp1Hjx4gLe3N6GhobRq1YqwsDBycnKKDVYfbaEpKxQKBe3bt6dJkyasWLGiUELtWSHRvx0dHfnzzz9Lfc2NjIzo06cPv//+e5W8Tx5V1jcyMirXc/aiozoQLgFSIFweIjSSMnB5qTWWJ7RaLXv37qV3795VQnCnvCDRjNevX8/WrVt54403GDBgQIm9bjqdjp07d+Lj40NCQgIuLi7yZ507d34spbk4qFQqgoODi4in/BNKpZJu3boVGreEqKioQi/f48eP06FDB7Zu3cqYMWOYMmWKTMVJTExk0aJFuLq68uabbxYSiRFFkXv37rFw4UISExOZN28eTZo0qbI0/RcJUh+xjY0Nw4YN44MPPkCpVLJw4UI2btwoB8TPgsjISDkx8+DBA4yNjTE0NOTOnTvUq1evHI7i6SGKImfPnqVu3brY2NjIn+/fv5927dqVm/3cvw1SX2twcDCLFi1i1apV1KtXj48//pgBAwYUUlV+Wuh0OlJSUti1axcffPAB+/fvp0OHDnzyyScMHjyYmjVrFhLf02g0rFmzhubNm1e4L7VCoWDIkCFcunSJqKgo+RnR09Nj8ODB7N69u1g9BK1Wy9mzZ/niiy9o2bIlb731ljw3K5VKdDpdsVUcSRBr6dKlnDhxgiZNmpSKQl0SpN7i3NzcInO8Wq1mw4YNxdrvFYfk5GTy8/NxdXWVXQyaNWtWaJspKSkyLVVPT0+2TyrtO9vV1ZXExETq1KnD7du3K8wKyN7envT0dGxsbGjatCnr168nLCyM7OxsMjMzC31XEAR8fHwYOXIk33//fZmsa54nJBuypKSk/4yF0j8hCAKGhoa8/vrr/P7773LVNysrS6ZKd+jQgV27duHj40NoaCh2dnakp6djaGhYrE2Svr4+pqamZGRkPNWYFAoFPXv2xMnJiQ0bNpS6elsa6OnpMWTIEIKDg7l582ap3uFSgi8nJ4eQkJByG0t5QU9PD319/epAuBhUc9ZKQH5+/jOpZD6Ke/fuyfTWqgRJzEOn0+Ht7V3Zwyk3SFZV69ato2HDhsyZM+eJ9NEHDx5w7tw53n77bS5fviz3BEVGRjJixIgy3weSOEhpxNE6dOiAvb099+/fL/S5sbExH3zwgay46+DgQFxcHJmZmcTExHDkyBG2b99OSkoKt27dYsCAATRv3rzQ4i4vL48DBw5w5swZhg0bRsOGDf9VCY+qBEEQsLKyon///nTp0oXjx4+zcOFCGjduTPfu3cukRCtBqi7Vr18fgNu3b+Pt7U1mZiYFBQWygFZlQaPRcPjwYSZNmiQfW2Zmpnw/VleDC0Pq/7148SJHjx7FwsKC3r17U6dOnXJ5P0gBdlhYGIcPHyYxMZGmTZsybdo0atSoUWLgJ6kb6+vr07Nnz+eSJDM1NWX48OGsX7+e999/X06aODo60rhxY/bu3cvgwYNllkFGRga//voraWlpvPvuu0WYNkqlEgsLC1mY8tFju379Ohs3bqRLly60atWKy5cvP9MxqlQqfvvtN8aNG1dEIOv06dMYGRmVyvtdFEVOnTpFYGCg7FcrBcWP4sGDB4iiKLfsaDSaMqnWm5qaYmdnR35+PlqtlqSkpELU6/KCvb092dnZGBsbU6dOHTw9PTl48CAxMTEkJSUVKQZI9lk5OTksWbKEd999t1h/+8qEu7s7CQkJ8rn7r7Z6SMrvvXv35vfff8fBwYGwsDAaNWqEo6MjdnZ2nDt3DkNDQ2JiYrC0tMTMzAytVktycnIRholCocDS0pLU1NSnZp/o6ekxaNAgVq9ezbZt2xg0aFC5rW+MjIwYO3YsP/74o2xP9yQolUoGDhzI77//jo+PT7m1VpYXlEqlHAhXU6P/h+qSUAlQqVTlVs0IDQ3Fx8enyi0KRVFk9+7d9OzZ818zuUv037Vr1zJmzBgGDx78xCBYFEX+/vtvWZEzNzcXGxsbtm3bRq9evZ7qPlCpVCiVylIttjw8PAgMDCzyedeuXQsp7np4eBQRZElMTGTGjBl06tSJFi1ayPsTRZGoqCi++OILHjx4wLx582jcuHF1EPwcIClNv/zyy7KFy8KFCwtRpksLnU5HfHy8vDC+desW9evXJyoqCjc3t0qv6gcHB2NlZVVo4f7XX3/RuHHjKregrUyIokhKSgrbtm3j448/JiwsjAkTJjBjxgx8fX2fOQgWRZHU1FQOHDjAJ598wp49e2jbti3z589n4MCBODo6lniviKLIxYsXuXbtGmPGjHluizdBEPD19cXZ2ZkDBw7Iz4UgCPTo0YNLly6RnJwsB7Kff/45rq6uzJw5s1jrFKm/LzExUf4sJyeHTZs2sW3bNqZMmcJLL71EfHy8zLB4GoiiyOHDh/Hx8cHLy6vQ31JTU9m7dy8jRowo1bOp0Wi4dOkSzZs3RxAEgoKC8PPzKzRPS60GgiDIgnl5eXllei8pFAr8/PwIDg6mXr163Lx5s9S/LQtMTEwwMDDA3NwcS0tLkpOTefvttykoKODMmTPFzn2CINCqVSuaNWvG6tWrq1SlSgr+JMXk/Pz8yh5SpUIQBFq2bIlSqUSlUnHhwgUEQcDf359bt27RvXt3Tpw4IdOdjYyMMDIyIjw8vNhtWVlZFVstLguUSiWvvvoqsbGxHDp0qNzEqiT6fteuXctUca5bty7m5uZcvny5XMZRnjAyMpL9sKvSc1bZqA6ES4BKpSq1qfbjIPWe1q5duxxGVX4QRZGYmBgyMjKeKObxIkBaLHz11VckJiYyd+5c6tSpU+rFyOXLl3F1dcXc3BylUkl8fDxpaWk0bdr0qc6NUqlEo9GUKuiRhLAe3Y+BgQFDhw4ttNixtLQsVrArIyODzz77TK4aFBQU8Oeff7J8+XL69evHuHHjsLCweOGv8YsGQRCwsLCgb9++fPjhhxgaGvLZZ5+xZcuWUqtd5ufnk52dja2tLTqdjoSEBJydnbl+/XqZxdvKG1qtlv3799OnTx/5OcvNzeX06dN06dLlP3+/ST3iiYmJrFu3joULFyKKInPmzGHcuHG4ubk9kxe15PsbFhbGypUr+fzzz0lJSeHNN9+U7ZWMjY2fKNQUHR3Nli1bePPNNzEzM3vaw30qSFToU6dOERMTIz8TFhYWdO3alU2bNrFp0yZZ2bl3794lJg2kQPH+/fuFRAEB5syZIycRY2JicHNze+rznpqayvHjx4tYIul0OrZs2ULnzp1xcHAo1fbDw8MxMzOjRo0aaLVaLl68SIsWLYp8LyoqCn19fblylp2dXWaRPF9fX27cuEHTpk25evVqhfQxSnOeqakp+fn5FBQUYGJiwgcffMCGDRu4detWsftVKBT06NEDa2trNm7cWOp35/OAo6Mj6enpWFhYkJSUVNnDqXTo6+szYsQIYmNjuXjxIvn5+bJ/cKNGjUhPT0ej0RATE0OjRo1QqVQlCkhJgfCzXmsjIyMmTJjAuXPnOHv2bLndO5Llm0Kh4NSpU6XarkKhYODAgezZs6fKBZuPVoSfh/Xji4LqQLgESDfLs0KtVst+elUNe/bsoWvXrlWOsl1W6HQ6Ll++zBdffEGHDh2YMGFCmRRWIyIiMDMzw9zcnIKCAiwtLdm5c+djF11PgpRxe1QIQhLG0Wq1aDQa8vLySElJITExkdq1a2NnZwc8DIIbNGhAkyZN0Gq1hUSX2rRpU2g/RkZGtGjRgsGDB2NkZER8fDwLFy4kNjaWefPm0ahRo0J9gNV4/pAWh6+88grz589HT0+PTz75hG3btpGdnf3Yl9Gjon1paWkoFApMTEyIioqqdJZJVFQUubm51KlTB3h4f1+9ehVXV1e5cvVfhPSc37t3j+XLl/Ptt99So0YNPvroIwYOHIi1tfUzVfJFUSQvL4/Tp0+zYMECNmzYQIMGDViwYAEjRozAycmpVAG2RDdesWIFr732GjVr1qyU+8nCwoKhQ4cWUWl1d3dn69atPHjwgLlz55ZK2dnFxYXo6GgOHTrE999/z4ABAxgxYoSsDaFWq7l///5TUzF1Oh2///47Xbp0wdraWv5c6hlOTk6mU6dOpTqPoihy/Phx2rVrh0KhIDU1lezs7GKDdKl/VqJnZmdnP9GS6Z9wcHAgPz8fW1tbkpKSZBHG8oarqytarZbU1FRcXV0JCwvDx8cHV1dXli5dSmRkZInB8LBhw8jMzGT37t1VZpFuYWEhrwseZRv8l2Ftbc3o0aO5ceMGiYmJ2NnZodVqyczMpGfPnkRGRhIaGoq/vz/37t0jKSmpWFEsKysr0tLSnnk8giBgbm7O1KlT2bVrF7dv3y63+0dPT4/hw4dz8OBBOcn2JLi6uuLk5MT58+erzH0MDxkbubm58v9W4yH+HXzYCkB5UaOTk5MxMjIqlWjG80RSUhL37t1j7NixL2yQJHlhbt++nTt37jBjxgycnZ3LrO588uRJGjduzNmzZ2WLhPT09GcSjDE1NcXa2prQ0FAcHBwIDw8nKiqK6OhocnJyZPsLpVIpL1pfeeUVcnNzyc/PRxAEVq9ejYmJCXZ2dnh6euLp6UmNGjVQKpU4OjrSvXt3hg4dSpMmTTAyMuKvv/7i0KFDDB48mICAgGoadBWDFBAPGjSIrl27sm/fPj766CNeeukl2rRpU6yQm7TI0NPTIzIyEldXV/Ly8tDpdBVibVNa6HQ6Dh48yEsvvSTfZ2q1moMHDzJmzJhKG1dlQlIlDg8PZ/fu3WRkZNCtWzfGjRtXKq2AJ21bolcfP36cCxcu4OnpyahRo/Dw8Hiq1paCggJ+/vlnOnbsWKnq3pKq8blz5zh8+DBdunTh8OHDnDhxgrfeeou4uDiUSmWpAntjY2N27NhBr169mDt3bhFvdI1Gg1arfep3e0REBNHR0bz66quFxpOXl8evv/7K+PHjS80ky87OJiwsjBEjRiCKIteuXcPX17fItZQSFpI1DTykfJe1em9oaIibmxtRUVHUrFmT6Oho/Pz8yrSN0sDNzY3k5GRSUlLo3LmzrFbt4+NDQEAAy5YtY+bMmUUSL5Ig0/jx41m8eDH29va0bt260tcnenp6GBgYYG1tLYtXVvaYKhuCINC8eXM6derEyZMnGTlyJJ6enoSGhtK0aVMcHBy4evWqrH6uUqnIzc0t8s6ys7MrNwqxIAjY2try5ptvsmLFCqZNm1ZsC8XTbNfGxob+/fuzdu1a3n333Se2j0jruaVLlxIYGFjpFocSrK2tSU9Pp2bNmtWB8COoDoRLQHZ2drnQxGJjYyvMhuJpIYoiBw8epH379s+8QKssSBYaP//8M66urrz//vtPpAEWh9zcXMLDw2nQoIEsWBUcHMwbb7zxVNVgSQzn7t27pKam8uWXX1K7dm3c3d3x8PCgVatWmJmZYWhoiIGBAfr6+nLFVlrsShXjgoICVCoVycnJREREcPjwYa5fv46npyeTJk2ib9++ODs7k5yczIoVKzAxMWHOnDlPJcpUjecHQRCwtrZm+PDhdO7cmV27dnH06FH69u1LkyZNCi367927h6urK4IgcOPGDRo0aEB4ePhTBz/lhQcPHhAdHc1rr70mjzUsLAylUomHh8d/7v4rKCggJCSE3bt3A9CzZ08aNGhQqgDuSVCr1URGRnLw4EHi4uJo3rw57733HjY2Nk9dWdZqtWzfvh1LS0u6du1a6ddLT0+PESNGMHfuXE6dOoWLiwtz587FzMyMRYsWcfPmTfz9/R9rQxcUFMTatWtxdHRkypQpxQakubm5KJXKp04c/PbbbwwePLjQtiXP4AYNGhTpGX4cbt68ibu7O2ZmZrJa9MCBA4scY05ODjk5OVhYWBQKhMu6uJZsYS5fviz/r6+vb7lee0EQcHJy4tixY+Tn5+Pu7s6RI0dkhWhBEBg+fDiLFy9m5syZMgvqUZibmzNx4kS++uorHBwc8Pb2rtT7U6FQYG1tjYmJSbG9rv9VKBQKxowZw4IFC+jbt69szdWyZUsGDhzI8uXLZUXp7OxssrOziwTC5ubmMiuqvK6xu7s7w4cPZ+XKlbzzzjvlYhEpCAJNmzYlKCiIgwcP0qtXrydus0aNGnh7e3Py5Em6detW6XMsPGyvS09Pp1atWuTm5lYndf4f1YFwCcjMzCwXet/t27cr3eLkn0hLSyM4OJj58+dX9lCeChINbf369fTr14+WLVs+dfXz1q1buLq6yjYAV69eRalUEhAQUKbtSP2bhw8fJiQkBBcXFwYNGkSdOnUwMTEpFVVR+ruenh5KpVJe6NSsWRM/Pz90Oh0FBQU8ePCAK1eusGbNGuBhlWLMmDF07NjxXyN69l+AIAjUrFmT8ePHExMTwx9//MHBgwcZMGAA9evXR6FQEBcXR4MGDYCHVOSuXbty6NChcl/AlgWiKHL06FFatWolV9a0Wi0HDhx4borDVQWSBdLu3bsxNDSkf//+eHt7o6+v/0zXR6I/X7lyhSNHjqCnp0e3bt3w9/cv0QKuLNs+c+YMoaGhzJw5s0rMGVqtluDgYNLT09HX12fcuHGy7+WgQYPYtGkTdevWLTG4/e2334iIiGDq1Kn8/PPPaDSaYr+bmJiIvb19mY9ZFEWuXLmCvr5+kep5TEwMFy5cYP78+aW+97VaLX///Tc9e/YEHuo8pKenF1GLhofva5VKhaOjo3xMWVlZT8UIqV27Ntu3b6d///4cOHCAgoKCctFCeRQ1a9YkOzsbeBjoSDZe9erV49ixY0yePJns7GyWLl3KjBkzihXVs7OzY8KECfz000/MmDFDdk6oDAiCgLOzMzk5OXI/a3Xw8PC8eHl5odVq2blzJ927d2f79u1otVqaN2/OunXrSElJwcjICDMzM6Kjo4sUhZRKJQUFBeU+roYNG5KamsqPP/7ItGnTyqXgo6enx9ChQ1m4cCENGjTA09Pzsd9XKBT07t2br7/+mjZt2pS5laG8IQgCpqampKSkYGhoSH5+fpWibVcm/jsrljIiKyvrmenMUp9YVaqQSArJAQEBlf5glhUS9XD37t38+uuvTJkyhdatWz91EKzT6Th16hTt2rUjJiYGBwcHIiIiePnll0u9OBBFkQcPHvDTTz/x/fffU6NGDebNm8fkyZMJCAjAwsLimRfFEhQKBUZGRri4uNCnTx8+/PBDXn31VZo1a8bhw4c5e/ZslRIZqUbpoFAocHNz4+2332bIkCFs376dr776ioiICOLi4nBxcSEzMxOVSoW1tTURERH4+PhU2nhzcnK4dOkSbdu2lZkMiYmJPHjw4F8hvPckiKKIWq3mwoULfPLJJxw5coThw4cza9Ys6tWrh4GBwVOdA4kRkp6ezq5du/joo48ICgpi9OjRzJkzh2bNmj0V6+Wf+4iIiGDHjh1MmjSp0hlB0vEuX76cU6dO8fXXX1OzZk2uX78uBxy1atXC1ta2SL+dKIpERkby6aefYmBgwOzZs/H29sbc3LxYT1rpPq1Ro0aZz2FeXh47d+5k6NChhd43arWaTZs2MXDgwDIxyFJTU3nw4IH8HF+5coX69esX+95JSUlBFEXZWxoerk+e5trZ2NhgaGhITk4OBgYGFeLda2RkhL6+PmZmZiQlJeHm5kZkZCTOzs4kJiai1Wpp164dTZs2ZcWKFeTl5RV5Z0nXvV+/fvz444/k5ORU2ntNSlhKc3B5qRL/G2BgYECbNm3Yvn07arVa9ls2MzPDz8+Pc+fOERAQQEZGBvfu3StyDaVAuLyvrSAItG/fHk9PT9atW1dsf/LTwNzcnBEjRrB+/fpS2Q/Z2dnh7+/PX3/9VSXWZaampuTm5qKnp1d9Hz+C6kC4BEg+ws+C7OxsudJYVZCbm8uZM2fo0qVLZQ+lTBBFkdzcXH766SfCw8OZO3fuMyl/wsMsfHJyMt7e3sTHx2NlZYVKpaJDhw6l+r1Op+Pvv/9m4cKFuLu7s2DBArp37465uXmFC1QJgoC+vj6enp5MmTKFqVOncu7cOb766itZPboaLw4EQUBPT4+6desyd+5cOnXqxMqVK2XLkfj4eOzt7WX7jsrSHBBFkXPnzlG/fv1CnqAHDhygQ4cOL7zw3uMgKbKfO3eOjz76iBMnTjB69GhmzpyJt7f3UytAS+Ja8fHxrFmzhk8//ZTc3FxmzpzJ5MmT8fT0fCZ16Uf3k5aWxg8//MDrr7+Ovb19pbIKdDodwcHBfPrpp3h5eTFz5kwcHR0ZOXIkv//+u0yZVCgU9O/fn3379slVDLVazYEDB1i2bBlDhgxh+PDhcpLAxsaGBw8eFLvfxMTEMr+PJQZEnTp1cHFxkc+ZZDulp6dHYGBgqc+l9LvGjRtjYGCATqfj7NmzJfbDRkdHy9Z+EjIzM586ieHr60tISAh+fn4EBQWV+7tCoVBgZmaGqakpCQkJNGzYkOvXr2NiYoIgCGRnZyMIAr169cLV1ZXVq1cXm8AVBIEWLVpQv3591q9fj1arLddxlgXOzs6kp6ejp6dHRkZGpY2jKqJ58+ay3aSXlxfh4eEIgkDr1q35448/cHNzIy0trZAqvARDQ0O0Wm2FXFs9PT369++PRqPhzz//LJfATxAE6tevL/tjP+nZEQSBl156iRMnTpCTk/PM+39WSCJZUiBcvU58iOpAuASURyAsSe5XBeoZ/G8RW6dOHaytrV+Yyo1kjfT1119jb2/P5MmTMTc3f+bxh4aG4uXlhb6+Pjk5OYSFheHt7V0qxemCggI2btzImTNnmDVrFt27d39myuLTQBAEBEHAxcWF6dOn07p1axYtWsTdu3erJ7kXEFKCIzAwUO57/+abb1izZg21a9cmNDQUDw+P5+b1+k+o1WqOHj1Kt27dZBpoRkYGISEhtGjR4oWZU8oCURTJz8/n/PnzfPzxx5w/f56xY8cyY8YMvL29nzrpJQV0t2/f5rvvvmP58uW4ubnx4YcfMmzYMDlQLa9zqlKpWLlyJd27d6devXqVeq1UKhWbN2/mt99+480336RXr15yJd3FxYXAwEB27NgB/K/v1MPDg9OnT5OamsqSJUu4c+cOc+fOLdI7XKNGjWJtbkRRJDY2FhcXl1KPU6pYnzhxgpdffrkQ9TkzM5MdO3aU2jNYglqt5syZM7Rr1w5BEEhNTSU3N7fEccXFxaHT6WT7J1EUyc7OfqpAWBAEGjVqRHBwMI0aNSIoKKjcK0MKhQJnZ2e0Wi3x8fHUrl2bqKgo+dpGRETIib9BgwahUCj4/fffix2HQqHg5ZdfRqPRsG/fvkqrYtnZ2ZGVlYWFhQXJycmVMoaqCEEQ8Pb2lkWYTExMuHbtGqIo4uHhQXx8PJmZmSiVShISEop48SqVSpRKpUylL28YGBgwduxYgoODOXfuXLmsiRQKBa+88goXL14stsr9T9ja2tKwYUOOHTtW6WsyKRBWKBSyI0k1qgPhEpGfn//M1Y27d+9Sq1atKrM4LCgo4NixY3Tv3v2F6eMTRZHbt2/zzTff0K1bNwYMGFAuVSedTseFCxdo3rw5eXl5qNVqDh8+TO3atZ94brRaLVu3biUvL4/p06c/FdWuIqCvr0/btm2ZNGkSq1evJioqqnqie0EhCAIZGRk0a9aMuXPnEhMTw6FDh9i+fTv169evtPvt+vXrWFtb4+TkBPzPAiYgIKDKKeOXBwoKCrh8+TKfffYZZ86cYdy4cUyZMoVatWo99Rwqqd1fuHCBzz//nO3bt9OxY0c+/PBDunTpUiGe31qtlt9++w1HR0c6duxYqZVgyd9Xo9Ewe/bsIrZICoWCnj17cuvWLSIiIuTPevfuzbp16/j000/x9/dn8uTJxQoDurm5ce/evWL3nZ2dXeb7dNeuXbRp00a2LoKH748dO3bQokWLMivTRkdHY2RkRI0aNeTqsL+/f7GJd1EUSU5ORqFQyArYUv/40yrRuru7k5qaipmZGenp6eWuHiv11Orp6RETEyMzR9LS0vD29i6UpFUqlYwZM4bIyEiOHTtWbKArfefChQvcuHGjUt5pUuXS2tq6RLbBfxXm5uZYWFjQsmVLbty4QXR0NPn5+djY2ODk5MTNmzd58OABWVlZRfqB9fT0MDExqTArL3gY/E2aNIk///yTsLCwcrl/zMzMGDRoEBs2bCgS3P8TgiDQo0cPTp06VaHHWRqYmJjI3sbV1Oj/4cWIhioBzyoiIYoi4eHh1K5du0oESaIocuPGDezs7KoUVftxkHp416xZw6RJk2jRokW5BfA5OTkkJCRQu3ZtkpOTyc7OJiQkBC8vr8deL1EUuXDhAikpKbz22msl3iP3798nOjpa7vu7ffs2QUFBcr9XZmYmN2/elP87KyuLoKAggoKCSEpKIioqSv7v8PBwmcYSGhpKUFBQiX6GkoDFuHHj2LBhQ6n6WKpRNSHROE1MTHBzc2PKlClcunSJgwcPlujFWZHQarXs27ePXr16yX2SKpWKkydPVmpwVRHQaDRcvXqVzz77jKNHjzJ69GimTZuGl5fXM9mS5eTkcOzYMT7++GPOnDnDiBEjeO+992QLtIo4h1KyIi4ujmHDhlWarZpGo+HIkSMsWbKEfv36MWrUKExNTYs9ZlNTU4YOHSovNHNzczl27BgpKSkEBATQpUuXElkRNjY2JfYIq9XqMr3X4+PjuXnzJl26dClEiY6KiuLOnTt07969zHZ9x44do127dujp6cksrZYtWxa7nby8PLKzszE0NJQDeI1Gg0qleupAWKlU4uTkRHJyMm5ubuXquSrB2dlZbg2TKsExMTHUrl27iPKyqakpkydP5siRI1y9erXYsZibmzNhwgTWr19fKRVZAwMDlEollpaWxMXFVSeYH4Genh716tWTg9/w8HBSU1MxNjamYcOG3Lt3D5VKJTt9PApBEDAzM6vQAFEQBOzt7Rk7diyrVq2S11zPuk0/Pz8cHBw4cuTIE7dnY2NDo0aNKr1X2NTUVO7JrqZG/w/VgXAxkHrBnqXyqNFoiI2NfaKy3POCKIrs3buXHj16VHl/WUkUa8eOHRw9epT33nuvSNXgWbcfHh6Oi4sLhoaGJCUlERYWhr29fbGqnY9CpVJx6NAhRo4c+VhRnLS0NBYsWMCFCxfkKsiaNWvIy8sjODiYU6dOkZSUxKVLlzh16hT5+fls3LiRzz77jLy8PDIyMliyZAlxcXF88803HDt2DHjo/7xy5crHZvElulKDBg04efJk9WT3AkLqC3ZycpIpZ/b29jRv3pxu3brxww8/sG7dOrKysp7b9Y2MjESj0VCnTh15jJcuXcLDw6NcFPYrG5J12c2bN/n888/Zt28fw4YNY+bMmdSqVeup5k0pEZaRkcHOnTuZP38+YWFhTJ48mWnTplGrVq0KbZ0RRZE7d+5w4MAB3njjjXJXCC7tGNLT01m6dClBQUHMmTOHxo0bPzapKQgC/v7+mJmZsW3bNhYuXIgoivzwww9cvXr1sf12FhYWxT4XKpVK9qotDbRaLX/88Qe9e/cuJCyp0WjYuHEjgwYNKnMwKlnrSR71CQkJaLXaEi0Wc3Jy0Gq1CIIgqytrNJoSVbFLi8aNG3PlyhUCAgK4dOnSU2+nJDg6OpKdnU1eXh4ajYb69etz8+ZNbGxsyMzMLFJFs7S0ZOrUqWzatKnYJJ8gCLi6uvLKK6/w448/ylWt5wV9fX15jouLi3uu+67qEISHPuDXrl3jlVdeITExkZCQEARBwMPDA0dHR9RqNenp6cUyNSQLpYoeo7e3N3369OGHH36QA/NngZ6eHoMHD+b48eMlFiYeRffu3Tl9+nSFH+vjoFQq0Wq16HQ6BEEoNxGxFx3VgXAxkHxcnyUQVqlUFBQUVBm6YHh4OKIoUqtWrcoeymMh9eOtXbuW+Ph4Zs6cWUgts7xw/vx5mjVrhkKhkPs8nJycnlgtv3PnDvb29k/06q1Tpw4eHh5s3ryZ27dv06JFC/z8/LCysmLt2rW0aNGCjh070qFDB3bv3o1Go6Fhw4Z4eXnh7u6Ov78/9erVo2fPntStW5c///yTS5cuERgYWCq/SkEQaNeuHWfOnClWiEJaoFej6iI6Ohp3d3ciIyPx8PAgKioKNzc3WrVqxUcffYSFhQUfffQRp06dQq1WV+j11Ol07N27l27duskBoUaj4fDhw/Tu3fuFrgZLAXBERARffvklf/zxB6+88grvv/8+derUeeoeYMk2ZtOmTXzyySfk5uby3nvvMWHCBFxcXCpcUA+QFe0nTJhQIfPokyAJYn3yySfUqVOHt99+u9TjkPpiFy1aRJcuXRg1ahRubm40aNCAEydOlHi/W1hYyB7sjyI1NRVTU9NSvddFUSQsLIzk5GRatWpVqBp8+vRpTE1NadiwYZmrwZcvX8bHxwdzc3PZxiowMLDE6nZmZiaiKGJoaChblUnCUk8bCAuCgK+vL3fv3sXd3Z2IiIhyXxBLytGGhoayOnZkZCRGRkaYm5uTkJBQZExOTk6MHz+elStXkpycXGww3LJlSzw9Pfntt9+eq3iWIAjUqFEDlUpVLZZVDBwdHUlPT8fBwYGXXnqJs2fPIooi9erVw9raGniY1ImNjS1yXS0sLMjIyKjw9YggCLRq1Yo6deqwfv36cqEGW1lZMWDAANavX/9YirQgCFhbW+Pr68upU6cqVQFdX18fURRRKpXVjMH/R3UgXAykReWzZFyTk5OxtrauEkJZUjW4e/fulSayU1pkZWWxdOlSjIyMmDBhQonUuWdBQUEB0dHRsnVFaGgorVu3xtTU9InXPDw8HC8vrydStAVBwMrKivHjx7N48WI5ixwXF8edO3fkvimlUsmDBw+4fft2idsxMTFhwoQJ/Pzzz0RERJR6EjU3N5ery2lpaURHR3Pq1Ck2bNjAp59+SlBQUKm2U43KQXp6OlZWVoSGhuLj48PNmzdleyITExP69+/PjBkzuHDhAl999RVRUVEV1veTlJREbGwsAQEB8vN4584dlEol7u7uFbLP5wFJrXnFihWsXbuWrl27MmfOHPz8/J5aqVnyFF+3bh2LFi3CwsKCefPmFRLAeh7Iyclh+fLl9OvXj9q1az+XfUqQVP63bNnC1q1beeutt+jRo0ep3j+SuvXy5cuJjo5mypQpciVJEAT69OnDiRMnSqysGBkZoVQqyczMLPR5WloaVlZWpTr/Go2GP/74g0GDBhV6h2dkZLBnzx6GDx9eZoaAKIr89ddfdOrUCUEQUKvVXLlyhRYtWpT4m3v37mFhYVFo3BqNBoVC8UyJektLS1mIzdzcnJiYmKfeVnFQKpUYGBhgampKUlISNjY25Ofnk5ubKyf1/glBEKhbty59+vRhxYoV5ObmFnnXKRQKBg4cSGxsbBE7rYqGRPfOzc19Yl/ofw2mpqbUrFmTyMhIhg8fzq1bt8jLy8PJyYnc3Fy6d+9Ofn5+sdV+Ozu759Z3rVAo6NevH7m5uRw4cKBc3pcBAQEYGxtz+vTpx96PgiDQvXt3Tpw4Ue59+aWFJFKn0+kwMDCQXSj+66gOhIuB1ND/LC+asLAwPD09q4QoVUJCAomJiTRq1Kiyh1IipP6Rb775hvr16zN8+PAKo/FFRUVha2uLmZmZ3HfbqlUrjIyMnrhPjUZTpuRG7dq1GTVqFEuWLCE3NxcHBwc8PT3lTJxarcbe3p7atWvL+5aqtY9Wp11cXJg0aRJLliwpssArCYIgkJyczLBhw2jdujVNmjShR48ejBs3jo8++qha/bIKQ61Wo1KpMDIy4t69e3h5eREZGVmo1UIQBBwdHZk2bRrdunVj5cqVbNq0qdT3R2kh9TW2b99evke1Wi379++nZ8+eL2Q1WBQf+n+vX7+e77//Hj8/P+bNm0fTpk2fOlmo0+mIiYnhp59+YvHixTg7OzN//nz69OlT6gCsvCDRd318fGjTps1z3bcoisTFxfHll19SUFDAnDlz8PDwKHUVODg4mIULF+Lt7S17a9+4cUO2X7G1taV+/folVlak4O7R50AKrqXq1JPGHxwcjJ6eXiFfbJ1Ox86dO2nduvVT6WxER0ej1Wrx8PAAHr6HjI2NH9tWEBcXh1KpLGSdpFar0el0z7Q+0dfXp27duty8eVNWjy5P6OvrY29vjyiKJCQkoK+vT40aNYiLi6NOnTqPTfy2bt0aX19f1q5dW2zV19DQkLFjx7Jjxw4SExOfWzDs7OxMRkYGCoWi3OfYFx2SGnlQUBDu7u5YWFgQGhqKvb09arWali1bkpyczIMHD4oEnyX19FcUlEol48aN48yZMwQHBz/z/aNQKBg2bBgHDhwgLS3tsd+1s7PD29u73BSsywqpIqzVajEwMHjuLQZVFZUfpVVBqNXqx/Z/PglSD6q3t3elLxJFUeTw4cNV2uNTWjh9++23dOvWrUL7mEVRJCgoiIYNG6JQKEhNTUWn02FkZISDg8MT9+vs7Ex8fPwTJ7G4uDjCwsK4efMmrVu3pkePHigUCqysrBg5ciSnTp3i0qVLnD59mu7du+Pk5ES7du3QaDT8/fffXL16lYCAAJKSkrh79y43btygYcOGDB48uNQTqEqlwsLCgi5dupCXl0daWhrZ2dmo1WqMjY0JCQnh2rVrJCUlyVL61XTpqoHU1FRZPEmlUqGnpycnUh6F9GJr2rQpH374IUqlUhZiKi97hKysLK5cuULbtm0RBEFe3Kanp+Pr61vpc1xZICkHb9++nYULF2Jtbc38+fNp3779U4lVSaIjUVFRLF26lGXLluHj48NHH31Et27dSmXFVt4QRZFDhw6RmZnJwIEDn9v+JYr5yZMn+eabb+jZs+djBbH++dv8/Hx+//13Nm/ezMSJE+UKssR+2Lx5s9wv26NHD44fP14itc/GxqbIojQlJUVWXn4c1Go1O3bsoH///vL7QBRFIiMjuX37dpkFsqTfS8kkiZp46tQp+Zkq6TeJiYkUFBQUYl2o1epn7hGW+jqDgoLw8/Pj+vXr5comkZJ0hoaGsnVS3bp1CQkJwcnJ6bHvUMkySa1Ws3fv3iLjkmjKAwYM4Oeff35u1VkzMzNyc3OxsLAgPT39uezzRUKdOnUIDQ1FX1+fRo0a8fvvv8vMOHt7e8zMzEhLSyuiHC1Z+jxPmJubM3HiRDZu3Mj9+/ef6T0pCAJ2dnZ06NCB7du3P/Y5UigU9OjRgyNHjhQ5D88LBgYGsmhgZY2hqqE6EC4GBQUFz0Qh1mq1xMXFPVF46XkgPT2dGzduPPeqQGkhiiIREREsXryYYcOG0apVqwqtoouiyK1bt6hfvz6AvADIzc3F0dHxiefI19eX8PDwJ/ZWaLVaXnnlFZl+1rt3b0aMGIEgCLRo0YKmTZuiVqupW7cuHTp0kF/uc+fORU9PD2tra+rUqYNWq6VHjx7yoqd9+/ZMmjSpVMcZHBxM06ZNeffddzl8+DBvvvmmTMl2dXXF3d2d48eP89133zFnzhy+/vpr9uzZw61bt2SRlurAuHKQnJyMra0tKSkpWFlZkZycjJ2dXYnJLEEQMDU1ZfDgwbzzzjucOHGCb7755plf8qIocvbsWXx9fWWxHlEU2b9/P506daryrRYSJAHE48eP89FHH5Gbm8sHH3zAyy+//FTtF48GwN999x0//fQTTZs2ZcGCBXTs2BFjY+NKmW8ld4ATJ04wfvz4Z0rolnW/2dnZ/Pjjj/z999/Mnj2bwMDAUiU0pcTK559/TmZmJvPmzSskjigIAk2aNEGn08kepfb29nh6epZIj3V1dS1C901OTi5UWS1pLJcuXcLGxqaQ9aFGo+HXX39lyJAhcq9uWZCVlUVISAjNmzcHIDc3l9u3b9O0adMSr09BQQEpKSno6ekVSoBJbJFnTWy7urqSmJiIg4MDubm55V6Vc3Z2RqVSybTXunXrEhoaiq2trayGXRKUSiXjx4/n/PnzXLly5f/YO+/wKqr1+3/OOWknvffeA2kkIYQWeu8I0gRFBVFAARuWq14VvddyUUQREGyAFOm99xoIBBJCIKT33k/KKb8/+M1cYgKkAt4v63nyKMk5M3v27Nmz3/2ud61G64U7d+6Mg4MD27ZteyjvKX19fZRKJYaGhg81g/l3ga2tLbW1tRQVFREWFsahQ4dEpfDMzEwCAwNJTEwkNze33vf09fUfeq2qoGQ+fvx4li9fjkKhaHUw3KdPHzIyMrh58+Z9j2Vra4uTkxNRUVEPfX11N1tGV1f3SUb4/+PRF7A+hmitYnRNTQ1KpbKe0uSjgLDr3KlTp0felsag0WiIi4vj119/ZebMmQ8lg15YWIhKpcLKygqVSsXOnTvx9vYmLS2N8PDwB37fxMSE4OBg9u7dy5gxY+4ZtDs7O+Ps7Cz+WyaTiT6Uwg6ipaVlg++Zm5vTo0cP8d92dnbY2dnV+0xj37sbAg3w4MGDzJkzB6lUiqenJ4sXL+bpp5/m3//+Nzo6OowaNQqJRIJKpaKkpITc3FwSEhLYs2cPeXl56Orq4urqio+PD15eXpiYmKCjoyMG90/QfsjJycHOzk70Ir958yZ+fn4P7HfBw/ONN97gzJkzfPnll/Tr149+/fqJ9645ELzHX3vtNfG7paWlJCQkMHHixL/FOFAqlcTHx7Nx40asrKxYsGBBkza97gWVSkV6ejpbt26lsLCQYcOGiZTqR9kfQgbx559/Zu7cuWIdaHtDrVaTmJjI6tWrCQ8P58UXX2zy+1OpVHLmzBm2b9/O008/TVhYWKPBs7a2NhMmTGDlypV07NgRPT09hg4dyrJly+jevXuD81lbWzdQQy4rK3ugeGVNTQ07duzg5ZdfrpcNPnv2LIaGhgQEBLRo0+Ty5ct4eXnVK8exs7PD0NDwnt+rra1FqVRSWVnZgBpdU1PT6kDY0NAQS0tL0tPTcXd359atWw/cKGgOHB0dxWBXrVZjYWFBWVkZEokEExMTCgoK7ns/BFulxYsXY21tjZOTU72+l8lkTJo0iUWLFuHn59fu7BRdXV0MDAwwMDAgLS1N3NR4gjuQyWQ4OTmRkpKCm5sbFhYW7Nmzh4iICM6cOYOrqysnTpwgOzu7XqmEXC5/JAGZRCIhLCyM1NRUfv/9d1588cVWMRF1dXWZNGkSa9eu5b333rsnY0PICq9evZouXbo89M1kExMTSktL0dHReZIR/v94khFuBAI1uqXIyMjA0tKyRTvHbQmFQsHp06cZMGDAY7dg1Wg0REdH8/vvvzN37tyHRiOPj4/Hy8sLbW1tCgsLuXr1Kh4eHuTm5mJjY/PA70skEgYNGsTNmzc5fvz4Y2lKXl5ezo8//kj//v3rBc3a2tr07NmTDRs28OOPP4q/l8lkYt3dmDFjeP311/noo4+YPXs2fn5+3Lp1i++//54PP/yQb7/9lv3795OamkpFRcVjef3/C0hOTsbFxYXExES8vLy4efOmaFvUFGhraxMZGcl7771Hamoqn3/+uehH3VQIZQR2dnbis6HRaDh+/Djh4eH3XcQ/DhBqdpcsWcLWrVuZMmUKs2fPxt7evkVzjUqlIiUlhaVLl7JixQq6dOnC+++/T0RERIs2GdoagjjW008/3eSa3NaitraW3bt3s2rVKqZNm8bo0aObrMpcVlbGihUrOHPmDG+99Rbh4eH3XYi6ubnh6urKkSNH0Gg0ODg4YGNjw6VLlxpkVszMzCguLq73e6Hm/n44efIkLi4uIptLaOeOHTuYMGFCi8QvlUolx48fp3///sCdcXns2LEHem9XVlai0dzxPr67trmioqLVYllwZ0EeFBQkluE01o+tgZGRkVhKUVZWhlwux8DAgPz8fFxcXBq10rkbgpL0M888w/Lly0UF7bshl8t58cUXWbNmTbvTlaVSKZaWlshksgZZzSe4g06dOnH58mWMjIzw9fUlJiYGY2NjsrOz8fT0JCsrq4FQmp6eHiqV6pEEZQINv7Kyskl+wA+Cl5cXbm5u7N+//77HcnFxwcjIiNjY2Fadr7kQfJsrKirQ09N7Ipb1//EkI9wIWpMRFmqJXFxcHnl24OrVqzg6OjapLuphQq1Wc+7cOXbu3Mm8efOwtbV9aPS9S5cuiQuS2NhYtLW1cXZ25tq1a01e2Ovr6zNr1iy+/fZbiouLGT58+GNRfy3UWn/zzTdERETQtWvXBv0qTIT3u1ZBlVhfXx9bW1u6du2KUqlEoVCQlpbG9evX+fXXX6moqMDCwgJvb286duyIra2tuPh5gtahoKAAc3NzsrKyRIp0c0stJBIJ5ubmzJw5k9jYWH766ScCAwObTAdWq9Xs3buXiRMnigFKdXU1p0+f5s0333xs77Pg27tjxw5iY2MZOXIk4eHhLc7YCgH19u3bycnJYdiwYYSFhbVb8KtSqaisrEShUKBQKKiqqqKgoICioiKqq6upqakR7fmqq6tRq9WoVCpu3LhBcXExhoaGnD17Fh0dHXR0dNDV1UVHRwd9fX3MzMwwNzdHLpejq6uLrq4u+vr66OnpNaskRaPRUFhYyOrVq9HT0+Odd95pcgZao9Fw69YtVq1aRdeuXXnhhRea1JeCYvBnn31G165dMTMzY8SIEfz888907ty5XpBqYmJCfn4+SUlJom9mTk6OKJjV2DxVUVHB/v37ef311+v1xZYtW+jWrVsDZk5TkZ6ejlqtFtcEZWVl5OTk4OPjc99rzszMxMjIiLq6unrXVlZWhra2dpu8czp27Mjy5csZNmwYGzdupKqqqs3YY4LHso6OjqiA7+bmJm7uXbt2jV69et33GBLJHT/prKwsVq1axdy5c+slKSSSO161kZGRrF+/npkzZ7abvgjcYRqUlpZSVFSERqN5bOfARwGJRIKPjw+7d+8G7lDhExMTuXr1quiVLZPJGgil6erqIpFIUCgUj8TnXBBf+/zzz0UGXEshlUoZM2YMn332GeHh4fcU1ZNKpYwYMYLNmzcTEBDwUN1lDAwMqKysREdH50kg/P/xJBBuBAqFArlc3uLv37x5k969e7ddg1oAlUrF/v37mTx58mM1WQt07QMHDrBgwQIsLS0fWvsUCgU5OTm4u7ujUqm4ePEijo6O6OvrI5VKxRd3U2Bqasqbb77JL7/8whdffCF6XAKPRBxHqH9cs2YNZ86c4dy5c6xbtw5nZ2fRmzg4OLhFVjcSiQRtbW20tbXx9/enY8eOqNVqamtrSU9P58aNG2zevJmioiKMjIzw8vLC398fZ2dnsa5UOM4TPBhKpZLS0lLkcjlqtZqamhr09fVbvEiQyWQEBgbi6enJ9u3b+fjjj5kyZQoBAQH3DX4SExORSCT1rHcuXLiAq6trm1Io2wp3Pwf79++ne/fufPjhh+jr67eIzgp3KOqbN28mPT2d4cOHEx4e3qoA+O4sgUqloqCggNzcXLKyskhPT6eoqIjS0lJRwE8ul6Ovr4+lpSUWFhaYmZmJAayenh7a2tpoNBp27dqFl5cXEydORCqVUldXR21tLTU1NdTW1lJbW0tlZSXJyclER0ejUCjEoLqurg4dHR2MjIwwNjbG0tISe3t7LCwsMDc3x8zMrF7QJdQh//LLLwwdOpTevXs3aSGn0WhQKpXs27eP48eP8+KLLz4wGPwrLCws6NGjBzt27GDq1Km4ubmhr69PXFwcgYGB5OTkcPz4cWJjY0W/X2NjY7HNmzZtQqlUYmRkRFhYGN26dRPpuceOHRM39IT2CgJZH374YYs3UQ4ePEjfvn2RyWRoNBouXLhAQEDAfbPTwqamEAjffe7y8nLx3rcWNjY2KJVKqqurMTExIScnBw8Pj1YfF+5k+oyNjSkvL6eoqAg3Nzd8fX2Jiopi5MiR7Nu3D5VK9cDAVSqVMmDAAJKSkti1axejR4+u1x8SiYQBAwbwxRdfEB0dXc/ira3h4uLCmTNnqKiooLq6ulXrxP9FCMyFoqIi/P39KSwsJCoqStxoMzc3Jy4urt53pFLpI69XNTExYcaMGaxYsYKFCxdiZmbW4jFkYmLC8OHD2bhxI7Nnz77n+Pb29kalUnH79u1WBd/Nhb6+PoWFhRgYGDyhRv9/PAmEG0F5efkDa4nuh7y8vPtaIrQ3BAEqmUz20ChyTYFGo+HYsWMcO3aMBQsWtGqyaQkyMzMxMzNDX1+f0tJS8vPzxftsamrarIWFkDV9+eWXuXjxIj/88ANubm4MGzYMe3t7pFJpu1+boLR66dIlfvnlFwoLC3nvvfeIjIzkjTfeEC0eJBIJUqmU5cuX88ILL7T6vIIXnVwux9vbGy8vL0aMGEFtbS1ZWVncunWLgwcPkpOTg66uLj4+PgQGBuLh4SG+EB+XMfk4ory8XKzztrW1JTU1tdWlA4KY1qRJk4iIiODnn3/mwoULTJgwodHsmBBcDR48WHyR19XVceDAAV544YXH6v4Jauc3b95kzZo12NnZ8e6772JhYdHiALiwsJAdO3YQHx/P4MGDmTFjRosCYKFtSqVSzFDeunWLzMxMysvL0dXVxdraGgcHBzp16iQGniYmJo1uUjR2n6KjoykoKGDhwoX3Vam+F1WvtraWsrIy8aegoICkpCQuXLhAcXEx1dXV6OrqYmRkhI2NDZWVlZw/f57XX39dtBd6UHZMo9FQVFTEqlWr0NXV5YMPPmgRe0QiuePF+eGHH5KVlYWDgwPDhw9n69atXL58mevXrxMZGckrr7yCSqXi1VdfxdLSksrKSvLz8/nggw+QSqVkZGRw8uRJPvroI4YNG0ZISAjHjh1j4cKFYpvq6upYs2YNEydObHHAU15eTmJioiiUqFKpOHXqFC+++OIDrz09PR2JRNKACVJRUdFmdlza2tq4ublx69YtOnXqRHR0NO7u7m1ybIlEItrnpKamEhoaiqOjI1u3bsXS0hKFQkFlZWW9zdL7tfO5557js88+w83NjaCgoHpt1NbW5tlnn2XJkiWinkV7zFEWFhZUVlYilUqpqqp6Egj/BVKpVCzl8fLyYteuXVhZWVFYWEh2djYdOnQgLy+PkpISMWiWSCTo6ek9dMGsuyGRSPDw8GDgwIGsXr2aV199tcWMC4lEQteuXTl27Bjx8fH1LNjuhlQqZdiwYezZswdPT892ZTLcDUGl29LSkoqKiifMBp4Ewo2ioqKixYFwRUUFtbW1ojrvo8KePXsYOHDgY6PqqlarOXr0KKdOneK1114ThaMeJmJjYwkICAAgLi4Oe3t7cnJyqKysxMbGpkWLMolEQnh4OP7+/pw7d47ly5cjl8uJjIwkICAAQ0NDZDJZm000QvCbk5PDyZMniY2NxcnJiTlz5pCUlMTOnTuprKykS5cuHDlyRFR+dnd3p2/fvu0y6QnH09XVxc3NDTc3NwYMGEBtbS35+fncuHGDI0eOsGbNGgwMDOjQoQMBAQE4Ojoil8sf2gvg74KysjIMDQ1JTU3F1dWVmzdvEh4e3maLUzc3N9577z327NnDokWLmDRpEgEBAfXuQ1ZWFnl5eXTq1Ek8b3x8PAYGBqIP6uMAIcDauHEjmZmZTJo0CT8/vxYpzwuU6n379nHx4kX69OnD008/3SxVacFCqKqqitTUVBISErh16xYlJSXo6+vj4uKCr68v/fr1w9TUFCMjoxar5AtZw3Xr1jF//vwHWjXd62+6urpYWVk1muVXq9Wiwu/t27f59ttvcXR0xN/fn40bN6JWq5HL5Tg4OODo6IiTkxMODg7I5XJx40DwBv79998ZNGgQffr0aRUVUC6XM2LECLZs2cLs2bNxcnLi6NGjTJgwQWQAaDQaDAwMqKqqQiKRUFNTg1QqRVtbG6lUKtYbDx48mF9//ZXNmzfTuXNnsYzoboGswMDAFj17Go2G06dPExwcjIGBARqNhvT0dGQyGfb29vf9rkqlIicnBwsLiwY17eXl5U0KHpsCQTDo9OnTPPXUU6xYsYIxY8a0GVXTwcGBjIwMcnJygDsbzsLzYWBgQGlpaZOvxdDQkFmzZvHdd99hb2+PlZVVPWVxR0dH+vTpw9q1a3n55ZfbZXFvYmJCWVmZGEw8bmVnjxoClf3cuXN06dIFtVpNSEgIq1atwsHBAVtbWy5evEhycnK9uvdHJZh1NyQSCb179xbXUfcTQ30QtLS0mDhxIuvWrcPT07NR9ofQV4IftoODQ2svoUkQxq6+vj55eXkP5ZyPO54Ewo1AoVDUe0ibg+zsbMzNzR9JrYOA3NxccnJyxKDvUUOtVnPkyBHOnDnDa6+99kg2CdRqNTdu3GDChAloNBqioqLo2LEjZWVlpKen11N4bgn09fXp06cP3bt3JzU1lZMnT/Lbb79hYGBAt27d8PPzw8bGBgMDgyZnRQWhlKqqKsrLy0lKSiI+Pp709HQyMjKIiYnhk08+YcCAAejp6REUFMTw4cMpLi4mJiYGd3d31qxZQ1VVFba2tnz22WeMHz+e7t27t4gu2hxIJBJ0dXVxdHTE0dGRfv36oVAoKCgoIDY2lp07d5Kfn4+ZmRl+fn4EBASI/fN/fXdSqGO8desWffv25cKFC0ycOLHNji/swI8ZM4bg4GB+++03oqKiePrpp8VF6cGDB+nTp4+4kaZSqdizZw9Dhw59LO6PsCF07NgxDh06RL9+/XjuuedalKERrH+OHDnCyZMniYiI4B//+AfGxsZNulaVSkVZWRkZGRlcu3aNW7duiXZsPj4+TJgwAUtLS/T19dt0U6yiooJly5YxadIkHBwc2uW+SKVS9PT0iIuL488//2TOnDmixV1dXZ2Y1UtPTyc9PZ0DBw6Iiytra2tRiDAuLo5XX321ni1SSyFsPh48eJCbN2+KY1VgqQjHt7S0pKCgABcXF2pqatDV1a23sJVIJFhbWzN9+nSmTp1Knz59xL+Vlpaya9cuFixY0OLFsFKp5OTJk8yZM0fMmh87dozu3bs/cINapVJRU1NDaWlpg9rk8vLyNhWq8/T0ZMOGDRgaGorsgLbaqHZxceHIkSMUFBSg0WjQ0dHBxsaGjIwMnJycSEtLa5b2gZOTE6NGjWLVqlXMnz+/XoAhkUjo378/X3zxBVFRUW22eXg3jI2NUavV6Ovrk5+f/1hYZD5u8PT0ZNOmTWg0Guzt7ZHL5RgZGXH9+nVcXV0xMjIiKiqKkJAQ8TuPwku4MWhpaTF58mS++OIL3N3dCQ4ObtEYEkqK7OzsOHnyJP3792/0ONra2vTu3ZsDBw7w7LPPtqt1qADBD1sul1NZWdnu5/s74Ekg3AgEdcmWPABpaWk4Ozs/ssWiRqPh4MGD9OzZ85GrVsN/FTKFILitdrKbi4qKCkpLS3F0dEShUIjZLltbW7KysggLC2v1OSQSCTo6OsjlcvLz8zl8+DBdunTBzMyMY8eOkZeXR01NjVjfJSwKdHV1kclkqNVqlEolZWVlVFdXi1m5qqoqgoKCcHd3Jzw8nEmTJqFQKBgyZAhTp07lqaeeYs6cOQQEBKCtrY21tTX9+/cnMjKSDh068PvvvzNmzBji4uJ49913cXNzY8aMGXTv3v2h2WoJVHJnZ2ecnJwYPHgwNTU1ZGVlERcXx/r16ykpKcHKykqsQ7azs3vkljSPAunp6Tg6OhIVFSVmktrjPgnZ4YULF7Jv3z4++eQTJk2ahIuLC7GxsYwbN07s+4yMDMrKyu5J83qYEDa11q9fj52dHQsXLmwRDRru2OWcPn2affv24e/vz7vvvvvAkg2NRoNCoSAjI4OrV69y/fp1KioqsLe3x9/fn169emFhYdGuVmN1dXWsWrWKsLAwQkJC2u2eKBQKNm3axO3bt3n99dfrZScFMS4TExPs7e3FDJBQc3rhwgW++uorHBwcMDQ0ZNOmTQQEBBAYGIitrW2rNgV0dXUZM2YMX3zxBZ07d2bBggV8/PHHFBcXY2BgQHp6OgqFgp07dxIVFYWtrW29zWmlUsmFCxfw8PDg/PnzjBo1isuXL9OrVy8sLS3Zvn07Xbt2bZWQY1xcHGZmZmLNsUKhIC4ujlGjRj3wu6WlpUilUiorKxsI7pSWlrbpfGBsbIyBgQEFBQV4enpy/fp1unfv3iZjyszMDKlUSkVFhfju8/Dw4Pbt27i6upKSkkL37t2bfDyBdpqQkMDOnTt56qmn6gUPOjo6PPfcc3zzzTf4+vpiYmLS6mu4G9ra2qKQZGZmZr1g7gnuQF9fH21tbUpLS/H39+fmzZv07NmT33//nV69eqFQKDh06BDTp08X6cfm5uYUFxc/4pbfgYGBAS+++CJLlizBycnpgXaV94JUKmXs2LF8+eWXdO7cudEEkEQiISIigk8++YSysrKHkiQyNDQUhckeJR39ccKTQLgR1NbWtjije/PmzUfqL1deXk5MTAwffPDBI1+wajQaTp48yYkTJ5g3b16TMyztgezsbKysrNDS0iIuLg4HBwcKCwtxdHQkNTW1xQwAAQLtbc2aNfz8888kJSVhYmLCvHnzCA8Pp3///mKtYHp6OrNmzSIuLo5ly5ZhZGSESqVCIpFQVVXFu+++S/fu3XF0dKS0tJRLly7x5ptvij7HEokEY2NjnnnmGd566y1Wr17Njh07mDRpEi+//DK+vr5iRvbll19m9OjRODk5oVQqycjIIDo6mj///JPVq1fTqVMnevXqhY+Pj1hX1d73SDiHXC7Hw8MDd3d3hg8fTk1NDSkpKVy7do3Vq1ejUChwdnYmLCzsobbvUSMnJwdXV1dUKhUVFRVYW1u3m6qkkB0eNWoUISEhrF69mqysrHqbJGq1mgMHDjBw4MCHqm75VwjU5T/++IOMjAymTJkijvXmjAmNRoNarebq1ats2rQJW1tbFixYIFpENVaHq9FoyMvLIy4ujkuXLpGfn4+pqSnBwcFMmzYNBwcHsW8ehjbAvn370Gg0jBgxol2yCIIn8bJly/Dw8GDhwoVN2hyWSqVoaWkRGxvL7t27+eijj+jcubNYJ3rlyhWWL1+OUqnE19eXrl274ubm1uy+k0gkdOjQAYVCgaGhIV9++SUxMTGcOHECe3t7Ro8eTUFBASqVCm1tbT766KN6G8MlJSW88sor1NXVYWNjw+LFi3FwcODo0aN06dKF+Ph4/vGPf7T4XgqK60OHDhVLDq5cuYKzs3OTFrsZGRmiBdTd7dZoNJSUlLR5aVFQUBAxMTGEhoZy/PjxZgWn94Opqan43qusrERPTw9PT0/27NnD2LFjOXfuHGq1ulljWCqVMnHiRP71r3/h4+PTwNvZwcGBiIgItm3bxtSpU9v0+ZBIJJiamqKjo0N+fv6T+spGoKWlhbe3N/Hx8bi7u3Py5ElefPFFvvvuO1H8LSMjg/z8fJEObG5uTlFR0SNu+R0IdfmjRo1ixYoVvPHGGy2uF7a0tCQyMpItW7Ywffr0RseKoaEhISEhnDx5kuHDh7f7eNLV1aWurg6ZTEZdXV27nuvvgieBcCMQxEGaC8GioaU2C62FRqPh3LlzdOjQoVViX23ZlsOHDzNv3rxHWjMtWEkJL8zo6GhCQkK4fPkygYGBbVLTLaigJiUliaI0gwYNqldjKWSMi4qKuHz5MiqVioCAANzd3cXjlJeX4+zszKFDh/jkk0/Yv38/mZmZvPLKK/z5559ifaZEIuGpp55i6dKlpKSkUFBQwNKlS7l8+TI7duwQxVQEeyj4rzCKq6srY8aMITk5md9//51XX30Va2trAgICCAoKIigoCFdXV9HW4GEGxn5+fvj6+jJ+/HiKi4u5ffs2Fy9eZNu2baJqdVBQEC4uLg+tfQ8TGo2GgoICHBwcsLS0JDU1FU9Pz3anTAkv/9dee40XXniBqKgoQkND6dChA8XFxSQkJDwyBXphIX3u3Dm2bdtGnz59eP7555stXiUEtCkpKWzYsAGVSsX06dPx8PCoN46Ez9XU1JCUlER0dDTx8fFIJBJ8fX0ZNmwYLi4u4kbBw+wTjUZDXFwcp06d4v3332+XjQm1Wk1UVBTr169nwoQJhIeHN2n8aTQaqqqqWLduHdnZ2bz11ltiRlUmk+Hj44O3tzfjx48nPz+fuLg4Nm/eLGaOunXrhpOTE1paWk0qG8nIyCAhIYH9+/dTWlrKiBEjOHXqFG+//Taenp5iXaqZmRnu7u7k5+eL36+qqiI/P5+srCzi4+MZNWoUzs7OyGQyNm/eTP/+/VslhJSRkUF5eTkdOnQA7lCdjx49ytixY5t0bYKwY1VVVb3afYGG7+jo2OK2/RUSiYSgoCDWrFlD7969ycjIaFUy4G4YGBigo6NDeXk5lZWVWFhYYGtrS35+Pubm5pSWllJbW9ss9ppEckf474UXXuD777/nvffeq/f+lkgkDBs2jI8//pikpCTx+W4rCJvoTyyUGodEIsHf35/Tp08TERFBRUUFcrmc8PBwcnNzcXFxIS8vj/j4eDEQNjQ0fKCv9MOERCKhW7duxMfHs3379gbMg+Ycp1+/fnz88cekpaU16tohkUjo27cvX3/9tVjm1p4QxqtUKkWpVLbruf4ueBIINwKhnqi5ECT1H5W1SG1tLSdOnGDWrFmP5PwCNBoNV65cYdeuXcybN++RCGPdDZVKRUJCAs899xxqtZqkpCSGDRvG/v37RXuS1noydujQgc6dO5OUlASAkZERL774YoNaMLVazZYtWygsLMTQ0JCioqJ6gbBMJkNfX5+CggK2b9+OnZ0dsbGxREdHM2PGDH799VeRnujs7MzYsWP5z3/+I4qeTJ48mc8++4wJEyYQHBzc6EJZWPR7eHjwj3/8g8mTJ7N+/XoyMzPJysoiOTmZ4uJirKysCAwMJCAgQKx7fxgvfeEc5ubmmJubExYWRm1tLXl5ecTGxrJjxw7y8/OxsbEhKCgIf39/zM3N283X9WGitraW0tJSFAoFTk5OJCYmMnLkyId2/ujoaAYPHkzv3r359ddfxYV8REREs+zF2goajYbs7GzWrl0LwOuvv46dnV2z77OQ0d2yZQsZGRmMHj2a4OBg8fkUgu3S0lLi4uK4ePEiOTk5WFtbExwcTP/+/bG0tHyk4oOCd++vv/7KSy+91KZ1osLxFQoFf/75J0lJSbzxxhsNhJru993k5GRWrVpFQEAAU6dOvadAjEQiwcbGBhsbG3r37k1hYSExMTGsXbuWmpoaunfvTnh4uEirbQy1tbV8/vnnXL16FbVaDSAqoaakpDBr1izOnz9PXV0d9vb22NnZUVJSIn6/srJSpGIKQXVqaqrYRicnp3uqbDelL4S6ZWH+zcnJoaKiAi8vryYdIzk5GWNjY5FCLkBgibQ15dfBwYHy8nLgzrybkpKCt7d3m9Rzm5mZUVNTQ25uLs7OzpiYmCCTyaioqEAmk6FQKFq0+HdxcaF///788ssvzJkzp967Tk9PTxQrevvtt9tUs8XR0ZGsrCxKSkqoq6t7pHowjytcXFzYsGEDMpkMU1NTCgsLiYiIIDU1FWNjY4qLi7l06RJ9+/ZFKpWK3raPE2QyGVOmTOFf//oXXl5eDZTKmwq5XM6YMWPYsGEDr7/+eqPioJaWljg5OREdHU3Xrl3bdR0jzKlPAuH/4kkg3AhaGggXFhZibGz8yOiDCQkJGBsbt2ih2FbQaDRcv36dDRs28Nprrz0WfqOCoIulpSVZWVno6uqKdRIqlQpzc/NW95epqSkRERGkpKQQFRVFr169GkxowgbBr7/+Kv77r3Sguro6CgoKADhy5AiRkZFIpVJUKhVHjhzh5Zdf5scffxQtmp599ll+//13wsPD8fLywsfHhyFDhrBmzRpOnTrFpEmTsLa2vuf1yWQyvL29effdd0U/YD09PaZMmYKOjg4xMTH8+OOP1NbW4ubmRqdOnXB3d8fMzOyhqT0LNG8nJyecnJwYNGgQlZWVZGRkcOXKFX744QeUSiVeXl6EhYXh4uLySGn4rYFQs5Oenk63bt2IiYkRKbvtjbq6Og4dOsQrr7yCk5MT7733HuvXr+fHH39k2bJlD6UNd6O6upqDBw9y/PhxRo8eTZcuXZodiGo0GsrLy9m3bx8XLlxg0KBBPPfccyLNt7q6mpycHKKjo7l27RoKhQIfHx8GDhwoZn0fhoBJUyDUBQ8ZMqTNs1zChsPKlStxc3Pjrbfeqic89aB2HT16lIMHDzJ16lT8/f2b3GdSqRQrKyv69+9P7969yc3N5cSJE3zxxRfY29szaNAgPDw8Gtx3HR0dZsyYwfbt28XMXEpKCj179uTgwYO8/PLLdOrUiQsXLhAeHo5Go6n3Ts/PzxdpgaGhodja2rJ7927gjrfuc8891+L7XlJSQnx8PBMnThRFsk6ePEn37t2bPGcWFBQgl8sbbEQIIlptrbWhra2Ni4sLycnJBAcHEx0djbe3d5sc29bWloKCAjIyMujcubMoUlZYWIiNjQ1ZWVktKk0Ssm1xcXEcPXq0niCRkJUUSrPuJVbUElhaWooWd08C4cZhZGSEjo4OBQUF+Pn5cePGDbp27crWrVuxsbGhqKiImzdvolAoMDAweCwDYbhT7/ziiy/yww8/4Ojo2OJ64ZCQEA4cOEBsbCxBQUEN/i6VShk0aBBr166lS5cu7bq2EoRanwTC/8WTQPgvUKvVoqhDc3Ev6sPDgEql4sCBAwwaNOiRLdw0Gg23b9/mt99+Y86cOQ1EPh4VMjIysLa2RkdHh9jYWPz8/MQaiczMzFYpRguZpN9++w0tLS22bdvGp59+yqBBgxpQ68rLy/nggw/Izs4G7iwgCwsL631GEMmCO1mPqKioei/wU6dOsXfvXp5//nmxTm7p0qX06tULmUzGl19+ydixY3n77bc5ceIE//73vxk4cCB9+/a9r/CUlpYWHTt2xMfHhytXrrB+/XocHR0ZN24c48aNo6Kighs3bnDp0iUxWPb19aVTp044OzuL1/owgk+pVIqRkZFIoxbogrGxsRw6dIjs7GwsLCwIDQ2lY8eO2NjYiM/E4x4cKxQKdHR0yMvLQ19fHy0trYeSidVoNFy+fBkrKyvR2kUul+Ps7MyAAQPYsGEDaWlpDBs2rN0FzDQaDbdu3eL333/H0dGR999/v9m+oIKN0blz59i+fTvBwcF8+OGHGBoaUllZydWrVzl//jy3b99GLpcTEhLC888/j62tbZOouQ8TQmZy3759GBgYEBkZWe/3LcHd1ydQoTds2MDTTz9N586dm7QQ02g0lJWVsXr1alQqFe+8806rvOG1tLRwcHBg4sSJjBkzhqtXr7Jx40aUSiX9+/enc+fO4gaGwIgZN24cKSkpHDx4kIKCAtEzuKqqihkzZnD16lVCQ0Opqamp9xwJc3BISAi//PILJ0+eZN++fajVaiZPnoyfn1+LrkOwXerUqZN4PoVCweXLl+t5FN8PdzsFBAcH1/ubSqVCrVa3S+mT4CM8ePBgli9f3ma0XxcXFy5dukRubq44Zn19fbl58ybOzs6kpKTQoUOHFp1LJpOJ/sIdOnSot3Egk8mYMGEC//rXvwgLC2u1DogAIRCWSqXU1NS0OTPjfwFaWlp4eHiQkJCAj48P+/btIzIyktraWiwtLSktLUUikZCXl4ebm5toddbcevH2hjDPDBkyhNWrVzN//vwWsYKEsfj777/j6+vb6OaJwAxMSkpqMnOkJRACYYnkjq/5EzwJhBtAUL1s7i6fEAT6+vq2U8vuf+68vDyKiopE8ZhH0YaMjAxWrlzJjBkzcHR0fCwWkxqNhhs3buDj44NEIuHKlSuMGzeOwsJCTE1NycnJITQ0tMXHVqlUrFmzBoVCwcyZM9HR0WHx4sWN2iOVlpaSnZ0t7oarVKp6dWtwJ1MhZAW1tbUxNTVFoVDg6uqKq6sr//jHP9i1axd5eXlYW1sjk8kYP368+P358+fzxRdfIJfL6du3L8HBwaxbt47Tp08zbdo0PDw87vmiEWqKw8LCCAwM5OTJk/z73/8mJCSEESNG0KVLF7p06YJKpSI7O5u4uDi2bdtGQUEBFhYWBAUF0bFjR+zt7R+acJBEIkFLSwtzc3N69uxJz549qampITk5mYsXL3L06FEA/Pz8CA0Nxd3dvV3VfFuLgoICdHR0UCgUlJWViTWT7Q21Ws3u3buZMmWKGAQplUoOHz7MrFmzMDc3Z+3atXz++efMnDmzVWq694JGo6G6upqtW7dy9epVpkyZIqpUN+dcQvnD2rVr0dfXZ+7cucjlci5evMiFCxcoKCjAzs6O8PBwxo0bJy6QHyWLRvivRqOhtraWoqIiSktLxZ+UlBT++OMP+vbty1dffUVdXR1KpZLa2lqRGixAqMnV1tZGS0tL/NHV1cXMzAwLCwuMjIwwMDBALpdz8uRJkpKSmD9/vmjD9KAgSJhXf/rpJ/r27SsKqbVFHwoCbp07dyYsLIzU1FR2797Nzp076devH5GRkcjlcgwMDDAxMeGnn35i/vz5HDhwgOzsbLp168aWLVsIDAzE0dGRyspKzp49i7a2NmfPnsXU1JRr167h7+/Pr7/+SseOHcnKykJLSwsrKytmzpzZ4meuurqaEydOMH/+fLGfrl27hqOjY5PpzPn5+ejp6YkuB3dDqVRSV1fX5vZ3EokEPz8/duzYgbm5OUqlkoKCAqytrVt9bGtra6RSKfn5+ajVamQyGa6uruzcuZMBAwZw+vTpVrXbzMyMp59+mp9//pk333yz3trN0tKS3r17s3nzZl544YU26bO7LZSEd98T1IdEcscj98SJE7zwwgvk5eUhlUpFmnROTk49SyUDAwNqa2sfywy7RCKhR48exMbGsn//foYNG9bscSSUollbW3Pu3DkiIyMbHEMmkzFw4ED279+Pp6dnu72PBK0aYS55gieBcAMIg6O5GWFB4GLAgAGPZEF16NAhIiMjW13r2hIIgfgPP/zA1KlT25y21xoIC7aJEydSVlZGaWkpzs7OnDt3Djs7O1JSUlr8slepVKxdu5aysjJeeuklcQK/1yLKzs6O4cOHU1dXh4WFBWVlZXh6etb7jK6uLlOmTOHcuXOEh4fzzjvvcOzYMWJjY0ULkDFjxrB8+XLefPPNBllnW1tbXnvtNZYsWcLMmTPx9vZm9uzZohKzt7c3Y8eOvS91WKAi9+vXjy5durB//34++eQT+vbtS+/evZHL5Y3SlGNiYvjll1+orKzEycmJ4OBg/Pz8MDExeShZNuH4enp6+Pn54efnh0qlEn1Md+3aRX5+PnZ2doSFhdGxY0exXu1xGa+ZmZli1islJaVdX4h3Iz4+Hm1t7Xrj8dq1a5iamuLk5IRUKmXGjBmcP3+er776ijFjxhAREdFmQbpareb27dv8/PPP+Pr68v777zc70yLU0G7evJlbt27Rs2dP6urq+Omnn0Tq/PDhw3F1dW13H+37tVHYbBUsmNLS0sjMzCQ3NxeFQoFSqcTQ0BATExPxOd27dy///Oc/cXBwEANc4b+NQaVSoVQqxZ+6ujqqq6spLi6mqKiIvLw8kpOTOXr0qCjMtmzZMtEOycbGBmtra2xtbbG1tRXZCVpaWiiVSvbt28fp06d56aWX8PLyape+FDZA3NzcmD17NtnZ2ezdu5cPPviA/v3706NHD0xMTKioqODjjz8mPT2d7777DhcXFzHT8eqrr2JhYYGDgwN1dXVcv35d3JAMCgriyJEjFBUVceDAAXR1dXn22WdbnI0RWBUODg5YWVkhkUjEzaSxY8c2OdOVk5ODpaUlOTk5DWySVCoVVVVV7cISMTQ0RE9Pj5KSEry8vIiPj2+TQNjS0hKJRCIKY8nlchwcHCgoKMDc3Jzc3FwxQG4JJBIJoaGhREdHc+DAgXrKuwJ9+p///CcpKSm4ubm1+nqkUin6+voYGhqSnZ2Nj49Pq4/5vwgnJyeysrJEm7WKigr8/f1Zu3YtZmZmGBgYEB8fz5AhQ5DL5ahUqscyEIY7a7pnnnmGzz77DF9f3xatcaVSKePGjeObb74hNDS00fdbSEiImFxor7JCoSa7uroatVrdqmfvfwVPAuG/QKAeNTegrKqqEq1OHjYqKyu5du0a77777iNZ3JWUlPDdd9/x1FNPPRY+o3ejrq6O0tJSLC0tSU5Oxs7ODh0dHbKzszE3N+fatWstmnCUSiV//PEHRUVFzJo1q0kbJyUlJVRVVaGtrc348eNxcnJq8BlPT0+WLFnCwoULKSgowMbGhsmTJ7No0SL8/f3Zt28f7733HikpKaxfv55p06Y1mMScnZ2ZOXMmK1euZO7cuTg7OxMYGIinpyf79+/n008/ZdSoUQ+suZRIJBgZGfHUU0/Rq1cvduzYwT//+U9GjhxJWFiYKJ5laGiIr6+vSFMWMlgxMTHs27cPQBSbcHV1xcjI6KEFnzKZDHt7e+zt7enXrx/l5eWkpqZy6dIl9u7di46ODv7+/oSEhGBnZ9fkusj2gGBZU1NTg7OzM7dv324zG5P7QaVSsWPHDkaOHCmOJZVKxZ49exg9erS4gJfJZHTt2hV3d3d+/vlnrl27xpQpUzAyMmpxnwkCTTt37uTy5ctMnToVPz+/ZtHjhEzygQMH+PXXX9HV1cXGxoaYmBiCgoKYMWOGWBrxsO+toD5dUVFBWloaCQkJpKSkUFZWhlQqxcbGBicnJ9HTXF9fH7lcjq6urljDtWLFCqZPn06vXr3apP1qtZorV65w7do1Fi1aRHh4OHV1ddTU1FBTU0NpaSk5OTnk5ORw/fp1sZ5WKpWio6NDYWEhJSUlzJs3DwsLC1HsqD0pjRKJBHt7e55//nny8vLEuUgul7No0SKcnZ15/fXXCQ0NxcrKCn19/Xsu7oRyloqKCjIyMjh//jwZGRm4uroyZMiQFrdRqVSyf//+epY9OTk5KBSKeoKID0JycjK2trbk5eU1eK/U1NRQVVXVKkXre0FLS4sOHToQExND586dOXjwYKOZq+bC1NQUlUpFbW2tGAjL5XK0tLRQqVRUV1ejUqlatRiXyWRMnDiRzz77jODg4HqMNH19fcaOHcuGDRt44403Wr15J5HcsS/U09MjLy/viXL0PWBmZibWCXt4eJCYmIifnx81NTWinZYwLnR0dB57Ox9TU1OmT5/OqlWrePfdd1tUnmBtbU1gYCAHDx5k9OjRDcaNrq4uXbp04eTJk4wZM6bdNhj19fWprq5GKpWKZYL/l/EkEP4LVCpVi17olZWV6OrqPnShLKEmqT3M45uCyspKfvjhB/r160doaOhj90LIysrCxMQEAwMDrl69SlBQkJi979q1KzKZrNmLCqVSyfr168nPz+fll19u8vcTEhKwsLCgsLDwnmqsAtXXzc2N+Ph48bP9+vXjypUr6OrqcuvWLcaNG8fXX3/NiRMn6N27d71jSSQSvL29mTp1KkuXLuX111/HxsYGAwMDMZO3Zs0aTp48yZQpU3BycrrvfZNIJFhZWTF9+nQyMzPZtGkTBw4cEDc+7p5EZTKZqPbcqVMncSMiPj6eU6dO8ccff4iBc3BwMPb29hgYGDy02mITExNRCbu2tpbCwkKxJlpgC4SFheHl5XVf1dr2gMCsqKqqwtnZmWvXrj0UxfXbt2+jUCjo2LGj+Lvk5GSqq6sblHoIir8LFixg3759LFq0iOeee65FJRkajYbExER+++03PD09ef/995s1FjQaDcXFxVy5coXff/+djIwMevToQa9evQgICHgk2X4hsBfsQW7evElOTg5SqRRHR0e8vb3p2rUrFhYW6Orq3rfeWqPRcOrUKcrKynjxxRfb5Dpqa2vZvn07V65c4dVXXxWffR0dHTH7aGdnJ953IWisra3lypUrrFixgsjISPT19Tl8+DAlJSWoVCqMjIywsbHB2dkZDw8PLCwsMDY2bvMFliC0NGjQIBISEqirq+Ott97C29u7yRsdQgmImZkZZmZm+Pv7M3HiRC5cuMCOHTu4efMmTz31VLMEqTQaDTdv3kRXV1e0uNNoNBw+fJiePXs2q64wNTUVV1fXRlXKS0tLG9Q7txUkEgkhISFs3LiRyMhIcnJyqKysbHUNrEwmw8DAgLKyMsrLyzExMUEqlWJhYUFFRQV6enoUFxe3WhTQxMSE8ePH8/PPP/POO+/U67vQ0FD279/P9evXCQwMbNV54I7Kdl5eHrm5ua0+1v8qBAp8UlISPj4+XL9+ne7du2Nra0tiYiKZmZn4+fmJfsLa2tqPdSAMd2rbO3fuzB9//MELL7zQ7PlNKpUyZMgQPvvsM3r37t2gbl0ikdCrVy+++uorBg8e3G7Pub6+PrW1tUgkkmbbl/0v4kkg/BcIgXBzFx0ZGRk4ODg89EJ/wZ9w1qxZD33BJ6iYdujQoc2yFW0JQXTHw8MDtVpNYmIi/fv3R61WU1xcLKpHN+d4arWaTZs2kZOTw+zZs5scBKvVai5duoSFhQUGBgYPnEA9PT1RKpVkZmbi4OBAp06d2L59O8OHD2f37t288cYbzJo1i88//xx7e/sGVhdCjc5TTz3Ff/7zHxYuXCgK2djb2/P6668TFRXFkiVL6Ny5MyNGjHhgNlRYzL/22mvcunWLDRs2sHfvXiZMmCCKxP21DTo6OlhZWWFpaUnPnj1RKpVkZWURFxfHn3/+SVFREVZWVmJ9sZ2dndg37TmeBPq3YK0yePBgKisrSUhIICoqii1btmBoaEhoaChBQUHY2dm1aF5oDurq6kQFXEEk66/UyLaGSqVi165dDB8+XOx3tVrNvn37GDJkSKPjVOi7kSNH4ufnx08//USXLl0YMWJEk4S0hCzpjh07uHjxItOmTaNDhw4PnDuFGtqCggKuXLnC8ePHOXXqFB4eHjz//POEhISIY/hhzEVCbW9dXR2ZmZnEx8cTGxtLfn4+RkZG+Pr60qdPH5GK3ZxxrdFoyMrKYufOnSxcuLDVtk2CQv2KFSswNTXl3XffbTI9XKPRsHfvXqKiovjoo4/qBXpqtZq6ujrRkzctLY1NmzZRXFyMtrY2dnZ2BAYG4uHhgY2NTaufbbVazalTp9i+fTvjx48nLCys1ZsdAqulT58+dO3alT179rBo0SJeeukl3NzcmtxHO3fuZOjQoeI1VlVVce3aNUaNGtXk9qnVagoKCsR56a/fKysrQ6PRtEtGGO5sggi2UhYWFmRkZLRa90So4xWeE6Hu2cPDg5SUFFE5urWBsBDInz9/nkOHDjF48OB6wllPP/00f/zxB76+vq0uIbO1tSU3N5f8/HxUKtUjcwp53BEYGEhUVBTjx49nz549DBkyBFtbW5ycnCgpKcHe3p5bt279bQJhgOHDh/PVV19x/vz5FlkdmZqa0qNHD3bu3MnUqVMbfN/c3Bw7OzuuX7/ebsklAwMDampqxIzw/3U8eXr/gpZMahqNhqSkpDapP2kuEhISMDQ0bCCq0d5Qq9Vs2LABIyMjRowY8dgFwQLi4uIYOHAgZWVlomKhUItSUFAgisM8CMKi788//yQ9PZ05c+Y0axetpqaG9PR07O3t6dy58wM/7+rqikwm48aNG4SHh2NgYEBISAhFRUVUVFSQnp6Oq6srs2bN4scff+Ttt98W69IESCQSunTpgkKh4Ouvv+att94Saw5lMhldunShY8eObNmyhY8++ohJkyYRGBh43yBd+K6Pjw/vvfcely5dYtmyZbi6ujJu3DixHqyx78F/bToEJUaFQkFqaiqXL19m5cqV1NTU4OLiQkhICD4+PhgbG7d7ACoETkZGRoSGhhIaGopSqRQp1D/++CMqlQp/f3/CwsJwdXUVF1Jt2S6lUklVVZX4/4JFVnsiKyuL/Px8OnXqJF5LXl4eqampD8xCSiQSvLy8+OCDD1izZg1fffUVM2bMuOcYgDvPUXp6Oj/99BMuLi588MEH980CC4J0eXl5XLp0iYsXL1JRUUFhYSHl5eW89dZb9O/f/6HRnoX2FBcXc/36dS5fvkxWVpbIchg+fDjOzs71NjBakikXNhknTJhw3/5s6vFu3LjBqlWrGDRoEH379m3wjN+tQH23eJcQPBsbG/Puu+9iYGCASqWq93ltbW2x/CAsLAy48x4VLHOuXr3Kvn37qKurw8HBQVRzFzKDd1+bQCNvzNJOrVaLAfnChQtb3S9/hSDSNXbsWPz8/Pjhhx948cUXRaHF+yEtLY3y8vJ66sfnzp1rNlOrvLwcpVJJeXl5PYbG3X83MDBoNyV5fX19HBwcSExMJDQ0lEuXLjXp+h8EZ2dnMjIyyMnJEanELi4unDp1CgcHBzIyMggODm71eQTv108++UQsN4D/zlWGhoZcuXJFtHFqCQSGVHl5OXV1dQ3E6p7gv3B1dWXLli3I5XIx82hra4uNjY1Ys33jxg169+79twiEBTbJ888/z1dffYWnp2eDdVdTjtGvXz8++ugj8vLyGmwASSQSBgwYwI4dO+jUqVO70Jb19fVRKBRoaWk99n3+MPAkEP4LWkKN1mg0pKamMnLkyIcaEKrVavbv38/AgQMfaiZarVZz8OBBioqKeOmllx7b3VC1Wk1ubi52dnakpqbi5OSETCYTs8H5+flNVrdWq9Vs2bKFlJQUZs+e3eyFSHp6OkZGRuTk5DSJRmptbY2xsTHJycmipUDfvn1ZvHgxAwYMYM+ePbz88st4enoyatQoli1bxhtvvNEggyhQbaqrq1myZAnz588XAw8h+Js6dSrJycmsWbOGEydOMHHixPt6DwvH1dLSokuXLqI65L///W+6du3KoEGDHkhxvbt+SxC2UqvVFBUVkZSUxOXLl9m2bRva2tp06NCB4OBg0aapPTN+dwfsnp6eeHp68tRTT5Gfn8+1a9fYunUrRUVFuLq60rlzZ3x8fESv2da2qbq6mtraWkxNTUlJSWkzH897QVCKHjRokJhx1Gg0HDx4kF69ejVJtETIps2YMUNUGZ8yZQpBQUH15iSBYnv8+HH279/PxIkT6dSpU6PzlqCcnJOTQ1RUFFeuXEEikRAQEEDPnj05cuQIoaGhTJgwodmLkJZArVZTVVVFcnIy0dHRJCQkIJFI8PT0pHfv3ri4uIhBXVthz549WFtbNzsjIGTNVSqVKJh1+PBh9u7dy+TJk8Xa6crKSiorK8W64JqaGhQKBdXV1eJ/hWBfLpfj7+/Pl19+We8cQkAjbAoplUoxQBaeUeFHS0uLyspKLl68yMaNG6mtraVz584EBQWJjBFjY2NiYmJYvnw5H330Ed27dxcFuqRSKefPn+fKlSu88cYb7WZZI/S1n58fc+bMYfny5bz66qvY2dndt8937tzJoEGDxL6oq6vjyJEjzJw5s1n3r6ioCCMjI/Ly8hg4cGCDv5eXl2NoaNhuGWEhq3rp0iWGDRvG999/T11dXasyqBKJRMxu5+TkiL93dnYmOzubiIiIVilH/xWmpqaMHDmSdevW8eqrr4rrE5lMxtixY/n5558JDg5u1TXZ2NhQXl4ubqo/CpHSvwMERe3y8nKsra3Jy8vD0tKS4OBg1qxZg7a2NllZWWg0GgwMDKioqHjELX4whPKgESNG8Msvv7TIUsnQ0JCBAweydetWZs6cWe/dIZHcUZiuqKggJyfnnmV0rYG+vj55eXl/i82Hh4HHM4J5hBBEG5oz8AQ/2IftmyvUqAQEBDy0c2o0Gi5cuEB0dDRz5859rGsLCgoK0NbWxsTEhKtXr4r9lJ2djaWlJQUFBXTq1OmBx1GpVGzdupXExETmzp3bIjXb6OhoXFxcSEhIaJKfoYmJCfb29qSkpFBZWSnW4FlaWqKnp0daWhr5+fnY2NjQvXt3srOz+e2333jxxRcbTMpSqZSBAweiUCj44YcfmDNnTr1AXiqV4uHhwTvvvMPJkyf58ssv6du3L3369BEVjO8HuVzOwIED6dKlC7t27eLjjz9m1KhRdO7cuVkLBKlUiqWlJZaWlnTu3JmamhqKioqIjY1l9+7domVUYGAg/v7+WFhYPJRMoJaWFnZ2dtjZ2YmCW7du3SIqKopNmzZhYWFBSEgIAQEBWFhYtJjGmpeXh1qtxsbGRqx3bU/k5+eTnJzMtGnTxD4sLS0lJiaGDz74oFn9KpPJ6NWrF+7u7qxcuZL4+HjGjBmDXC4XM4u//fYbGo2GhQsXNsj4CYJXgnhRXFyc6O/7yiuvoKenx65duzh8+DCTJk1qUJvelhAysoWFhVy7do2YmBjy8vKwt7enU6dODBkyBFNT03bzU05OTub06dO8//779a5RCHBramqorq6mpqaGkpISCgsLRZslQRm/srKS8vJyEhISkMvluLi4cOLECQwMDOr96OrqYmRkhK6urihiJJPJOHDgALm5uXz77bdYWlrW856810aUEBwL/69Wq+sFzYJSdlVVlSgumZqayrlz57h06RJlZWUUFxeTlJTE+PHjCQoKIjg4GFNTU/T09CgvL+fNN99s93IBQMxYTpw4kbVr1/Laa6/d87nOzMwkIyODGTNmiL9LSEjAwMCgUUHE+yEzM1OkizZWo1xaWiqKDbYXfHx82LNnD2ZmZqjVakpKSlotAirQ4rOzs0WVWn19fVQqFYaGhhQWFrZR6+/cu+7du3P27Fmio6PrZX9dXV2xsLDg0qVLREREtPj5NTQ0RKPRoKenR1FR0UMZk39HSCQSnJycSE9Px8PDg5s3b+Lo6EhJSYloEaZSqaioqMDExISSkpJH3eQmQRhjV69e5eDBgwwZMqTZYykyMpIjR46Qnp4ulpYJ0NHRoWfPnhw+fJipU6e2ZdOBO9ToysrKJxnh/48ngfBfoFQqm53hrK6uFuvmHhY0Gg0nTpyga9euD203UqDY7dq1iwULFrRINe9hIiMjAzs7O1QqFbdv32bYsGEA5ObmYmFhwfXr1++70w93guDt27eTkJDAa6+91qJMhFqtFn0rfXx8mpQ5EnYdMzMzKSsrE/t6yJAh7Ny5k27dunHgwAGeeeYZZDIZY8aMYenSpezZs6dRZoJMJmPkyJFs2LCBlStXMmvWrAbjVUdHh759+9KpUyc2btzIokWLmDx5Mr6+vg9ss0QiwdTUlMmTJ9O7d2/Wr1/PwYMHmTBhQpOv+a/H09PTE2vl+vfvT3V1NampqVy5coUffvgBlUqFh4cHoaGhuLm5YWJi0u5BsUwmw9TUlLCwMEJDQ6mpqSEtLY2LFy/y7bffoqWlJVKoHR0dmxWo5+XlUV5ejqOjI1FRUa2umbsfhLrPXr16idkljUbDsWPHCAsLa9GzLSx63nnnHTZs2MCXX37JCy+8QG5uLmvXrmXQoEH06dOnXva5traW5ORkzpw5Q0JCAiYmJoSHhzN48GBMTU2RSqXExMSwfv16QkND+cc//tEuyt5CIJ6amsrFixeJj49HIpHQoUMHRowYgYuLi6jk3J6oqqpi+fLlDBo0iLy8POLi4sjOzqaoqIiSkhLKysrEDJRgdWRubo6pqSnOzs6YmJhgYmJCWVkZq1at4sUXX2To0KFiVlVo/70C2cLCQn766SeMjY354osv2l3ITgiYKysrOXPmDC+88AJwJ4N09uxZzM3NmTZtGocPH2bw4MGNUqbbCwIL4cyZM1y9erWB37xGo6GsrIwdO3YwYMAAcT4VauzvrlFtKhITE7GxsSExMbHBu0aj0VBaWoqhoWG79oGlpSVaWlrk5+fj6+tLbGwsffv2bdUxbW1tqa6uBv6bbNDS0sLY2BiVSoVCoWjTzKqWlhZTpkzhhx9+oEOHDmJfCu/B1atXExYW1uJNS8Gn28jIiPz8/GZvePxfQmBgINeuXaN79+7s2rWL7t27ExcXh56eHllZWVhbW5ORkYGxsTHl5eWPurlNhpaWFlOnTmXRokV06NBB1E5oKgSdja1btzJ37tx6m1sSiYTw8HA+++wzFApFm5dCGBkZUV5ejra2Nkqlsk2P/XfEk0D4LxCsCZrzosnKympU4bE9UVVVxcWLF1m4cOFDq43Lzc3l119/5ZVXXmlSVvNRIz4+Hj8/PyorK1Gr1eIOe3p6Ok5OTly7du2+E4xarWbXrl1cv36defPmtXjXt7CwELVaTVZWVrMWFD4+Ply8eJHbt2+Ltcw+Pj6sW7cOd3d3fvnlF0aNGoWxsTHa2tq8+OKL/Otf/8LW1pbw8PAG40JLS4unn36an3/+mV9//ZXp06c3GLMSiQRzc3NmzpxJQkICv//+O05OTkyYMEEU27ofBEGtBQsWEBcXx9q1a7G2tmbChAkPpFvfC0IGSqBR+/r6ioJn8fHxHDt2jLVr12JqakpISAiBgYHtLm4ltEkul+Pj44O3tzdqtZqcnBwuX77MmjVrqKysxMPDgy5duuDt7S0GnPcKQvLy8kRFWF1d3XbNMpSUlHDt2jU+/PBDsT0KhYLTp0/z1ltvtap+Ti6X8+yzz3Ls2DGee+45bGxsRIsbuMOgSUpK4vTp09y4cQMTExO6du3KmDFj6m1mlJSUsG7dOnJzc5k1axaurq5tdj+FzGVZWRnx8fGihY6ZmRmdO3dmwIAB9TKhbQXhvGq1mrKyMnJzcykoKCAtLY3c3FwuX75Mfn4+2tramJqaYmlpiYODAy4uLqLKsZGRUb0MLfx3TKnVas6fP8+mTZt49tlnCQoKalIpgUajIS4ujp9//pmhQ4fSu3fvdq/NF9otk8kwNjZGLpdTUlIiBusajYbdu3dz+/ZtIiIimDNnzkMtPRLa17dvX3bu3EmnTp1QKpWkpaVx9epVjhw5woULF/Dx8WH69Oli23JycigoKMDf37/ZtPasrCxsbW0xMzNrMDcLKuntVR8sQCaT4efnx/Xr1wkJCWHfvn3ieGgp9PT00NLSorq6GqVSiY6ODlKpFCcnJ/Lz89HV1W0T5WgBEokER0dHAgMD2bNnD+PHj6+XFTY2Nm50c6OpEJSwtbW1KSgoeGKhdA8Itdn79+9nxIgR5OfnY2VlJXrZJiUl0a1bN1JSUjAwMPhbBcJwh7k3ZcoU0VKpOSULEomEsLAw9u7dS0pKCu7u7vXGkKmpKW5ubkRHR7c5O8zQ0JDKykrkcvmTjDBPAuEGaK5dgEajIS0tDWdn54c2EWo0Gq5evYqLiwumpqYP5XyVlZWsWLFC9L993Cd9jUZDSkoK3bt3JzExEWdnZ3FhkZ2dTVBQEFpaWvekmKnVavbs2UNMTAzz589vcU2aRqMhNjYWV1dXbt++3WQjdolEgqurK1KplMTERHr27CnW2vXt25cLFy4QHBzM0aNHxQywkZERc+fO5YsvvsDc3BxPT88G59LW1ua5555j2bJlrF+/nkmTJjXKgJBKpfj6+vLhhx9y6NAhPv30U4YOHUpkZGSTKKFSqVTMgJ88eZIvvviC8PBwhg4d2uqMhrB4trS0pEePHvTo0YPa2lrS0tKIjo5mxYoV1NbW4u3tTWhoKJ6eng+ltlgmk+Hg4IC9vT3Dhg2jqKiIGzducOTIEdauXYutrS0RERH4+/tjaGjYINDIzMxEJpOho6PT7tngAwcO0LVrVzHzK9iweXp6inVdrUF2djbHjh1j3LhxpKenc/z4cUJDQ7lw4QLx8fGYmprStWtXRo0aJVpESSQSkf577tw5tm7dSt++fZkxY0ab0JAFem5+fj5Xrlzh0qVLlJeX4+rqSo8ePfDy8hL7oy3OJVyLUO+ckZFBamoq6enplJeXixYy1tbWYv17cnIyS5YsaSCw1JT21NTUsHnzZm7cuMGbb76Jra1tk75XW1vL7t27OX/+PLNnz26yUnJbw8TEhLfeekukbOvo6KCrq0teXh7V1dXtHgA2BmEeTkhI4P333+f06dPcunWL3Nxc1Go12travPzyy6InrkQi4ejRo+I82RwoFAqRGtqYYrSgoSD4t7cnQkJC2LFjB127diUnJ6fV/S+TyTA0NKS8vFwM5u+mzZqbm1NQUNCm855UKmX48OF8/PHH9OjRQ+xTmUzGqFGjWL9+PcHBwS2imQse4CUlJfXqnp+gISwsLMRgS0dHBy0tLRQKBU5OTqSkpDBlyhSOHTtG586d/3Z9KZFICAoKIiYmhh07djB+/PhmbRhpa2szYsQItm/fzmuvvdYgK9yvXz82bNhAt27d2pSNpKurS21tLUZGRk8CYZ4Ewg1QWVnZ7Ak/JSWFkJCQh7Z4UKlUHD58mAkTJjwUkSylUskvv/xCWFhYPXXZxxmVlZWUlZVhZ2fHqVOnRIEqtVpNRUUFlZWVWFpaNvoSFKhtly5dYt68ea2mgEdFRREUFERubm6zxpajoyOGhobcvn1bVDMXKDP79+9n5syZrFixgoEDB4qBnq2tLbNmzWL58uW88cYb2NjYNLhfOjo6vPTSSyxZsoRt27YxZsyY+9rkDB06lLCwMDZs2MCpU6d45plncHd3bxJdWqBbd+7cmd27d/Pxxx8zYsQIunTp0ib1vcL3dXV18fLywsvLC6VSKQahR48eZe3atVhaWtKpUycCAwPFbEt7BsVwZwHQvXt3unXrRkVFBcnJyZw/f54dO3ZgYmJCWFgYwcHBol9xZmYmBgYGZGVltatQVkVFBRcuXOC9994T21pXV8fBgwd55ZVXWjWnCEHs5s2bGTt2LDY2Nhw+fJg//viDlStXMnfuXN566y3Mzc0bnEdgnaxZswa1Ws3rr7/eaEDQHGg0GqqqqkhPTycqKor4+Hi0tbXp2LEjkydPxt7evkl18E05T01NDVVVVWRkZHD79m2Sk5PFbJG5uTn29va4u7vTq1cvjI2NMTQ0FJ/pyspKFi1axOzZs5tN8RdqsJcvX46VlRULFy5s0jwjZBhXrVqFXC7n3XffbZZ3blsjODiY4ODgBr8/f/48sbGxD92aUIBwj27cuMGNGzcoKCgQlYJlMhmnT58mMTERLS0t9PT0OHnyJJMmTeLo0aOYmZlhZWUlZg+1tbVFmvpf73FFRQXa2tqkp6fToUOHBu0QxnJTmDmthZubGwUFBahUKmxsbEhOTm5UxbqpkMlk2NjYUFxcTG5uLg4ODsCd7Ozp06dxdXUlJyenVedoDEZGRowcOZI//viD+fPni/3m5eWFRCIhMTERHx+fZh9XKF0qKysjOzu7Tdv8vwapVCraTTk5OZGTk4Oenh7W1tZcu3YNc3Nz8vPzkcvlVFZWPurmNhsSiYRx48axaNEigoODG1hZPui7QUFB7Nmzp9GssIeHBzU1NWRkZIiMqraATCYT15RPAuEngXADKBSKZi2MBMrryJEj27ll/0VGRgZKpbLZNQktgVqtZtu2bejr6zNgwIBHthhpLgT1TW1tbW7fvk3//v2BO/dXpVJRWlraqBqfoMR9/vx55s+f3yzri8ZQVVVFfn4+ZWVl+Pn5NWv32dTUFENDQ/Lz86mpqREzt0ZGRgQEBHDr1i3c3Nw4f/48vXv3Bu5MrN7e3owbN46lS5eKlkl/ha6uLrNnz+bbb79l9+7dDBs27J5tE176s2fPJjY2llWrVuHl5cWYMWMwNTV94LMikUgwNjZm4sSJ9OrVi02bNnHkyBHGjx+Pr69vmwu/aGlpYW1tjbW1NT169EChUJCRkcGlS5f47rvv0Gg0+Pr6EhoaipOTU7vX3AnZ+sDAQAICAqiuriYzM5Pz58/zzTffoKOjg7+/PxkZGaKnZmuEXO4HQVsgICCgXnlDdHQ0VlZWrbJhq6qqYt26dZw/fx5/f392796NgYEBXbt25ffff+f69evs2LEDb29vMQssoK6ujlOnTrFr1y5GjhxJt27dWlxqIgj83Lp1iwsXLpCeno6VlRUhISFi7bEQ3LQUArU5Ly+PhIQEbt++TW5uLlKpFDs7O9zd3Rk2bBg2Njbo6emJVNDGoNFo2LJlCwEBAeICvakQdBtWr17NkCFD6NWrV5OeJ41GQ3x8PD///DMDBw6kT58+j1z9X6FQsHr1anx9fUUxPJlMJi7aHiX91NLSko8//piioiI2bNjAhg0bSExMxNjYmLfeegtra2tqa2v5888/6d69O5aWluLYKCwsFN87cEeoxtTUFHNzc9Ez1NzcnLS0NExNTcnOzqZfv34N2iB4Nj+MQFhXVxdra2syMzMJDg4mOjq6njVUS2BnZ0dsbCx5eXnivTQxMaGiogJnZ2du3LjRhldwBxKJhIiICA4fPsz169fx9/cH7gRnQ4YMYe/evXh5ebVoXWNjY8OVK1eoq6t7Qo2+DyQSiUi19/Hx4caNG1hYWFBZWUlRUZH4fKtUKqqqqv6Wfamvr8+0adP4/fffeeedd5pV1qSjo8Pw4cPZunUr8+fPrzd/y2QyIiMjOXbsWKOewy2FTCYTGS1PAuEngXAD1NTUNIvnr1KpqK6ubjc7h79Co9Fw+PBhevXq1e4LF41Gw5kzZ0hMTGTevHkPtQa6tUhOTsbNzY3q6mqqq6vFgLagoABDQ0OKiooa7L4JtlBnzpzhjTfeaHUQDJCUlISVlRVJSUmMHTu2WROZQJ1MS0ujoKBAnFwFyszSpUt54YUX+Pnnn+nataso1iJkjfPz81mxYgVz585tIIwl1NzOmTOHxYsXo62t/UBxF5lMRmBgIN7e3uzbt49FixYxYsQIunfv3iSldYnkjo3GnDlzSEhIYP369ZiZmTFhwoRWZ/7uBaEWSajjVSqVFBcXc+3aNXbt2iUqb4eFheHn5yfa8bRntlgul+Pp6YmHhwdKpZKcnBzOnDkjKovfvn2boUOHUltb2+aZa4VCwfHjx1mwYEG9bPDu3bt59tlnW2QdJ/iof/XVV1y9epUePXrg4eHBpEmTsLCwELNfPXv2xNnZmRUrVpCUlMSIESPQ0tKioKCA3377DZVK1SJ/WKENeXl5XL16lUuXLlFUVISbmxvdunXDx8dHpGI2ty/vVkEuLi4mNTWVa9euiWruFhYW+Pj40L9/f1xcXMRaSGganVmj0XDr1i2uX7/O+++/36z+V6lUHD16lP379zNjxowmBdECXfvAgQMcO3asyd9rTwh9XF1dzdKlS0lOTsbV1ZXw8HAGDRqEo6MjWVlZYgajubhy5QoWFhYtFjRSKBSimJOVlRWvvPIKAwcO5PXXXwfuBEQmJiZUV1eTlpbGvHnzsLW1rVcPLvzU1dWJSt/FxcUUFhZy6tQpiouLiYmJQalUkpubC4C9vT3W1tY4ODhgamqKrq4uFRUVYiB8t1VVe0DwER4wYABHjhxpVYAizP0SiYSsrCzx98JaS19fv91qbXV0dHj66afZuHEj3t7eIhMpKCiIzZs3k5eX1yLHD3t7e9FC6W5f7SeoD4lEgq+vL7///jvh4eEcPXqUwMBAUlNTUavVpKenY2pqSnV1NVVVVaKq+N8JQgKiY8eObNmyhWeeeaZZWeHAwEB27txJUlJSvZI2YSNn0aJFzS7bvB+EQFgul1NVVdUmx/w740kg/BdUV1c3yFbcD4WFhcjl8odWv1RZWUl8fDzjxo1r18WLRqPh5s2b7NmzhzfffPOxtkn6K4S2BwUFkZKSgo2NjfjCLSgowNzcnKysLCIjI8XvqNVqjh49ysmTJ3njjTfahCKo0Wi4ePEiAQEBHD169IEK1X+FIDSRkpIi1jkL99zW1hZTU1PKy8sxMjIiLi6uHm1d2PEWFHufffbZBi8XIVP52muv8dVXX4k05vuNKyGQGz16NBEREaL38LRp05pUJy/UaPn5+fGPf/yDM2fO8PXXXxMeHs7w4cPFgKU9IJFI0NbWxtramr59+9K3b18UCgW3b9/m4sWL7N+/H5lMRkBAAKGhobi4uDQrqGlpexwdHenZsycmJiYMHTqUs2fPsm3bNtauXYuXlxcRERF4eXnV2+hoCTQaDZcuXcLJyUmsxRNEkvT09HB3d2/ycQQF26ioKLZv305qairjx4/n/fffF5kWf22nRHLHkubdd9/l559/ZvHixQQHB7Nv3z6GDRsmZjObEszBnUAwPT2dS5cuceXKFVQqFR07dmTs2LG4ubmJG3ctCX41Gg0VFRUkJiYSExPD7du3qaurEwV4+vbti62tbavHR3V1Nb/88gtTp05t8jtEoGGvW7eOrKysRu2o7vW9iooKVq9eTV1dHe+++26rldbvDgDu3jQQIGwUC3ZPws/d/66urqaiooLCwkLKysqoqakhISGBhIQEsazB1dWVOXPmYGlp2ew2Ojo6tvj9pdFouHbtGqdPn+bgwYPitQk+zF5eXqJN1OXLl3FwcBCthoR+FbLacCfTamhoKDIv7u6zpUuX4u3tzd69e5kwYQIlJSXk5uZy4cIFiouLKSoq4vLly0gkEqqqqrCxscHR0VG0nDM3NxeZDncvpFsCiUSCv78/R44c4amnnkIikYibhi2Fg4ODKAgmQEdHBysrK6qrqykpKWnxZseD4Ofnh7GxMVFRUXTr1k0s24mIiODkyZMtWk8JFkoSiYTy8vKHotfyd4WVlRVlZWUYGhpSUVEhChEKrguOjo6UlpaKzIm/WyAMd9Zco0aNYtGiRVy/fr1ZDAptbW1GjhzJ5s2bG4hVGhsb4+joSHx8PGFhYW2yFhGy8E8C4Tt4Egj/BdXV1U1+aWo0GjIzM7Gzs3toD+65c+fESb29INho/PLLL8ycObNJ9NfHCSqVioyMDEaOHMnp06fx8fER2y9YKmVlZYkvLrVazbFjxzh69CgLFixosxeaUqnk5s2buLm5YWlp2WwVYEGoRUtLi8TExHqK0zKZjMGDB7Nnzx5RbCEwMLDeIkJLS4tnnnmGb7/9lu3btzN69OgGGSeJ5I7t0YIFC/jyyy/R1tYWhbke1DY7OzsWLFhAdHQ033//PYGBgYwaNapJVGMhCIyMjKRTp07s3LmTjz76iDFjxtC5c+d2Zx8I7dPX1ycgIICAgACUSiXZ2dlcvXqVDRs2UFpaipubG507dxaziu2hpCssMpVKJU5OTiiVShYsWEBxcTFxcXHs37+f3377DWdnZ7p06YKfn1+L2lJbW8uBAwd44YUXxO+pVCp27drF6NGjmxRIKRQK4uLiOH78uFgL6+Liwo8//igqmz/oWg0MDJg4cSILFy5k586d/Otf/xIXp/eDWq2mpqaG5ORkzp07R0JCAoaGhgQHB/PSSy9hZ2fX4kW0Wq2mtraWjIwMYmJiiI2NpaqqCkdHR4KCghg4cCDW1tZtOi41Gg27du3C09NT1DBoyncKCwtZtmwZTk5OvPnmm02y7RPEA5cvX05ERATDhg2rdy2NZS/vzmJWVFSIP4IP8N1+wOXl5dTU1KBUKlEqlSLVUaPRoKWlhZaWFtra2ujp6aGrq1vvRy6XY2JigrW1NcbGxmRlZSGRSDAzM6NPnz5MmjRJ1MVorhgN0KLgWUBdXR1Hjhxh8eLFrFixgvXr11NbWyv+vVevXujr64viis1lVdzNysjNzSU8PBwHB4dG6wwLCgo4e/YsI0aMICIigtzcXDIyMrh69SpFRUUoFAq0tLQwNDTE3t4ee3t7bG1tsbOzw9DQULQsaiozwtzcXNw88fb2Ji4urlWBsKmpqVhSIASQEokEe3t7Kioq0Gg0lJeXt4sjhUQiYfz48SxbtoyQkBBRU6Nnz558+eWXDB8+vFlMQEAsd9DR0aGoqOhJIHwf6OrqYmZmRllZGSYmJmhpaaHRaJDL5dy8eZPevXsTGxsrzjl/V+jr6zN9+nRWrlzJ+++/32R9GSErvGPHDhITE+tphAgMwN27dxMSEtImsYaw4aytrY1CoWj18f7ueBII/wXNCYQBUlNTG5hhtxeUSiXHjx+vt5BtD9TU1LB69WqGDRvWppYlDwtVVVXU1NRgZmbGjRs3mDBhgvi39PR0QkNDOX/+PLq6uqjVak6cOMGhQ4dYsGBBm76E8/PzkUgk5OTk4O/v36I6JDc3N2QyGcnJyQ0oQ35+fqxfvx4DAwPq6upISUnB09Oz3vf19PR45ZVX+PrrrzEzM6NXr16NtsPc3JwFCxbw9ddfo6WlRdeuXZt032UymUgr3r17N5988gljx44lNDS0SUGDUD88efJkIiMj2bBhA0eOHGHixIlNEuRqS2hpaeHk5ISTkxNDhgwR60zPnTvHhg0bsLCwEO2ZzM3N24y2rNFoKCgowMjIiMrKSpGyb2FhQWRkJD169KC8vJzExETOnz/Pn3/+iZWVFV26dMHf3x8TE5MHvhw1Gg3Xr1/HyMioHkVUEGK7VyAmZB9TU1M5ceIEN2/exMXFhbCwMMrKyhg1ahSTJ09ucjZTpVIRHR3Nhg0bGD9+PLa2tqxduxaVSiVS7O+G4DErXLtQahAeHs7IkSMxMzNr8cJArVZTWlrKzZs3uXjxIqmpqZiamhIYGMj06dOxsrJqEyGtxqDRaEhOTiYqKop//OMfTRrnGo2GxMREVq5cyZAhQ4iMjGzSfVcqlZw6dYpNmzYxYcIEfH19xXKL0tJSysrKKC8vp7y8nLKyMhQKhZgV12g0yGQy9PX10dfXx8DAAAMDA/HflpaWGBkZYWRkhJ6enhhsCT93//uvAZjgI52bm0tUVBQnT56krq6Ojh07Mm7cOMaNGycyIRQKBYsXL+bGjRv4+fk9lHeSENxGR0ejp6cnamT88ccfomaDWq1m9erVODk5oaWl1WLdjpqaGlQqFfn5+fdcT5SWllJTU4Orqyu+vr74+vrWa6tALa2oqCAzM5OsrCxu3rwpakxIpVJMTU3F4NjZ2RkLCwvkcjm6uroN2BgymUz0EQ4NDWXv3r306dOnxX0vbHwoFArRQgnuCGZdvXoVQ0NDysrK2i0QdnR0xMnJibNnz4rXYW5ujq2tLfHx8c0WAtXR0UFPTw+pVEpxcXGbt/l/CVKpFC8vL27cuIGLiwvl5eWo1Wrs7e05c+YM48ePF9dLQi393xUeHh6EhYWxefNmpk2b1uQ1zN0K0gsWLKg3t3t6eoqlFALjpDUQ3CmAJ4EwTwLhehAWfU3ZYRcg1Lo9DNy+fRttbe02VY/7K9RqNVu2bMHR0bHJwdDjhtLSUoyMjFAqlZSUlNSjgRYWFopZKW1tbU6ePMn+/ft54403mkQvbA7i4uJEkYjnn3++RccQdk8rKipEj1kBOjo69O7dm6NHjzJo0CD27NnDnDlzGky8hoaGzJ07ly+//BITE5N7vvAtLS2ZN2+eWDPcVBqORCLB0NCQ8ePH061bN9auXcvx48eZPHkyjo6OTT6Gk5MT8+bN49q1a6xevRp3d3fGjBnT5velKZBKpZibm9OlSxfCw8NFwa2LFy/y3XffIZVK8fPzIywsDEdHx2Z7j/8VgmJ0QUFBA0qVVCrFxMSE0NBQQkJCUCgUpKSkcPbsWXbt2oW5uTnh4eEEBASINbl/hUqlYvfu3YwdO1b8u0qlYufOnQwfPrxBQKVSqcTa5cuXL2NoaEjPnj2ZMGECWVlZrF69mkGDBjVZq0BQvN24cSNpaWm89tprIj3U3t6e5cuXk5yczIQJE9DV1aWkpISEhATOnTtHZmYmjo6OREREMHnyZAwMDFoV/BYUFHDt2jWioqIoLCwUvZ6nTp2KgYHBQ/HPramp4bfffmPy5MlNqvtSq9WcO3eOLVu28Pzzz4vBoBBM3p2hLSwsJDc3l+LiYvLy8rh58yaJiYn4+vpy4MABjhw5gqGhIebm5piamorUO2NjY0xMTMT+lclkSKVS8b9t1S+1tbWiWNy1a9fQ0tIiNDSUWbNmMWHCBGxsbBqMYz09PaZOncrSpUuZMWNGk23oWgqhVOb69ev8+OOPFBQUkJiYiL29Pc7OzpSXl1NZWUnfvn3R09Pj3//+N+7u7mzdupVu3bpha2vbrDGan5+PqampKE7VGMrKylCpVI2OF6lUWm9zQgjIhZrwuro6amtrKSwsJDMzU2S+FBcXU1tbi1wux8rKCjs7O1xcXLC2thYF/g4dOsTMmTPJzc2lqqqqxf7mOjo6mJubk5OTU88z2NbWlgMHDmBmZkZxcXG7JRakUimjR4/m22+/JSIiQizDEd6hwcHBzRpTMpkMc3NzSkpKyMvLa5c2/69AIpHQsWNHdu/eTc+ePYmKihLnoKSkJHR1dSktLUUikfytM8Jw51pHjBghUqQ7duzY5HEVFBTEtm3bSE1NrVeqpKOjQ1hYGGfOnGHUqFGtnvuEQFiw9/u/jieB8F/Q3EC4qKioWTXFLYVGo+HQoUP069ev3RYAgpeoIPjxd6zTgDubE66uruTl5WFkZCS+uAWKX01NDVZWVpw/f549e/aIdi5t2a9qtZorV67QvXt3rl692iIxDrizS2hhYUFxcTEZGRkNbHW6devGRx99xNChQ9m2bRv5+flYW1vXuxZh53v27Nn85z//wcjIqFGPYYnkjjr0q6++yuLFi9HR0SEwMLDJ/SKVSnF0dOSNN97gwoULfPPNNyINs6mBopaWFsHBwfj6+or+xUOGDKF3797tanl0P0gkd4TFvL298fLyQqVSUVBQwJUrV9i4cSOlpaW4uLgQHh6Oj4+PWLbQnLamp6djYWFBUVHRfTe6hLZ06NABPz8/6urqSEpK4uzZs+zbtw8jIyMiIiIIDg6uRwlNTk5GqVSKwkgajYb09HSKi4vx9/cXf1dVVcXly5c5evQoVVVVREREMG/ePCwsLJBIJJw8eZIdO3YwY8aMeiUH94NAy125ciX+/v68/fbb9bxQrayseOONN/jxxx9ZsGABDg4OlJSU4ObmRq9evfDx8REzsy2p9wUoLi7m8uXLnDlzhoqKCvz8/Bg1ahTu7u5tYuPV3DYdPnwYW1tbAgIC7pmJF6BUKtm2bRt79uxh8uTJ5OTkcPHiRYqKiigpKaGqqkqs3ZfL5VhYWGBjY4ORkREHDhygf//+/Oc//xGzV0I/tqQ/W3q9KpWK1NRUzp07R2xsLDo6OoSHh/Pqq6+K9YISiUS01dFoNJSVlVFaWipmOQXLu5kzZ/Lpp5+KyupteQ0ajYa6ujr+/PNPTp48yaeffoq5uTlWVlb4+PiQkZHBd999h729Pfv378fGxoYzZ86gVquRSqUsX76cxYsX06VLF8aPH09wcHA9yu297nVSUhLOzs5isN3Y58rKytDT02tWWZREIhEz8gIF3d3dXcz2q9VqVCoVxcXF5OTkkJ2dTVRUFPn5+VRUVFBXV8eVK1cwNzensLCQ8+fPExoaipGRUYN3zIMgk8mwtrYmLS2NoqIiMRA2NjamoqICf39/0tPT77kR0BawtbXF09OT06dP079/fySSOyJHf/zxB2VlZc2iN0skEiwtLcVN0ie4P2xtbcnPz8fe3p6cnBzs7OyIj48nNzeX/Px8sfTm7x4Iwx32w7PPPsuqVat47733MDAwaPL6Z9iwYezatYvZs2eLa3CJREK3bt1YsmRJg7KWlkAikaCnp4dSqXyiGs2TQLgehDqxptaKVFRUoFKpHkptSHFxMSkpKTz//PPtRtVLS0tjx44dTa47exwhUA69vb1JSUnBxcVF7K+ysjJkMhkVFRWkpaWRmpraLplguDM2hF1iBweHFvenTCbD1dWVwsJCkpOTGyi8Ghoa4u/vT0xMDJGRkezbt49p06Y1OI5ADXvppZdYtmwZb775Jra2to0Gw/b29sydO5dvvvmGF154oVk7msLCq2vXrgQEBLB582b++c9/MmnSJAICApq0uSIs6ocPH07Xrl35448/OHnyJJMnTxaDr0fFVBCuz9bWlkGDBjFo0CDKy8u5ceMGFy5cYNOmTfU8ggWv6ge1NysrC3d3d2pqappVV6Sjo4OPjw8+Pj4olUoxU3z48GHkcjnh4eGEhISwfft2hgwZImZvNRoNO3fuZPDgwchkMhITEzly5Ag3b97Ew8ODp59+Gg8PD/F+1dXVsWnTJm7dusU777wjBsb3g0DLPXToEIcOHeLZZ58VSwSERXhZWZkYoJaUlGBvb09cXBzvvPOOaHXSknstLKpiYmI4duwYxcXF+Pn5MWHCBNzc3NpVBO1B7crLy+Po0aO8++67SKVSsS5OqVRSUFBAbm4ueXl5pKWlkZWVxbVr11CpVPj7+xMfHy9m/EJCQjA1NcXU1LSeyJxGo+Hq1av89ttvzJ07ly5dujx02zvh3qempnL27FliY2PR19enS5cuzJs3r4Gg1F9RW1vL66+/zqFDh8Ta5JqaGlGb4KeffiImJoann35a3Ihuzb0UAsPbt2+zatUqzMzMsLS0ZNmyZYwZM0YMglNTU5k+fTq6urr4+/ujVqtJS0tj4sSJeHp6kp2dze3bt4mJieG7775DpVLh6OhISEgInp6eODs7i3PC3fckOTkZDw8Prly50mgdriBOp6ur22pfe0CcQ6VSqTif2draEhQUJH5GsCH7+uuvRf2CJUuWiHOwsbExDg4OuLq6Ymdnh52dHXK5vN5my1/PaW1tLbIyBBgZGSGVStHT0yMzM7PV13Y/SKVShg4dyrfffktkZCS6urro6+vj7+9PVFSUGBw3FdbW1iQnJ1NUVNSOrf7fgJGRkVhXXVtbi4mJCdra2tTU1HDz5k3RzePvTo2GO2Pd3d1dzPBOnjy5ycy4kJAQdu7cSVZWVj1GncDSaGwd2JL2PQmE/4sngfBdEKjRTa0Rzs/Px9jYuN2FfTQaDefOnSM4OLjd1JvLyspYuXIlzz33XKvERR41VCoVaWlpDB48mG3bthEaGir+raysDCMjI2JjY8nKyuLLL79stlVLU5Geno6NjQ1xcXGEhIS0+BwSiQQ3NzdiY2OJj49n4MCBDf4+YMAAli1bxquvvsoXX3whClI0diwfHx8mT57MN998w1tvvYWFhUWjn3NxceG1115jyZIlTJ8+XcwaNqfdRkZGTJs2jeTkZNasWcOxY8eYNGlSg4z1/Y5haWnJ7NmziY+PZ926ddjb2zN+/PgmBWLtDeH8xsbGhIeH07lzZ6qrq8nIyCAqKoqlS5ei0WgIDAwkLCwMe3v7RmtOhQV4x44dyc3NbfZ8IhxPW1sbLy8vPD09qaurIz09nQsXLvDpp59y6dIlXF1dcXFxwcLCgvz8fK5fv469vT0fffQRurq6REZGMmHCBIyNjesFVcLcYGRkxNtvv92kjcK7Bfe0tbV5//33RbGcoqIiYmJiOHfuHCUlJfj6+vLUU0/h6uqKrq4uN2/e5KeffmL48OH06NGjycyUu4Ovw4cPc+vWLdzd3Rk5ciQeHh71stCPAgKNefXq1YSEhJCQkEBmZiapqakUFxdTV1eHoaEhlpaW2NjY4O7uTnR0NKNGjWL8+PEPZFUI179r1y6ioqJ47bXXmqTk3pbXV1dXR3Z2NmfPnuXKlSsYGhrSpUsXBg0aJGZ+mwLBW3vVqlX1bIICAwNZvHgx4eHhHD9+nI8//hhvb29Gjhwpqng353qFd35SUhJ79+7l9u3b7N69mxEjRjBt2jQkEglbt25FqVRSVlbG6NGj642jjIwMCgsL6dSpEzo6OlhYWODv78+oUaNEa7Tz58+zadMmkpOTxdpcMzMznJyccHV1xdnZmdu3b9OpUyd0dXXvWWpQUlIiZv3bC3+tEbawsKBXr14UFhbyyiuv8N133/Hee++hUCgoLS0lMzOTlJQUzp8/T1FRkRggu7i44OzsjLOzM+bm5ujo6KCtrS0Ki6anp4vn0dLSEjej28tC6W4I9+DcuXP06tULiURC9+7dWbNmTbMZdw4ODpSXl4viT4/6nfQ4Q0tLCxcXF1JSUjAzM0NPTw9tbW20tLSIi4vD2dmZ2NhYqqurH3VT2wRSqZQRI0bw2WefcfPmzSYzqHR0dBg0aBC7du3ipZdeEr8jk8no3r07x48fx8vLq9Xtk8vlTwLh/48ngfBdEDLCTc3e5ebmYmNj0+6TX21tLWfOnOGVV15pl3PV1dXx66+/0rNnz3oCHH9H1NXVoVAoMDQ0JDMzk9GjR4t/y8/PJz09nbi4OFasWNHkgKy5EGxqAgICOH78OCNHjmzV8dzd3VEoFGRnZzf6srWzs8PY2Jjc3FxCQkLue05hx7GsrIxvv/2W119//Z5+yS4uLsydO5elS5cyffr0ZmWGBUilUjw8PHjnnXc4efIkX375JX369BFr65pyPKlUSocOHXj33Xc5fvw4n3/+Of369aNPnz7tuihsLoRM9t3BaGFhIZcvX2b9+vWUlZXh4eFBeHg4bm5uYiakoqKCoqIitLW1sbe3b3VJgpAp9vDwwN3dnaKiIrp164ZGo+Hrr7+msrKSsrIysrOziYiIEBWX/5q51mg0ZGdn88MPPxAREcGgQYOaFKSr1WpiYmJYt24dgwYNomfPnlRUVHDs2DHOnz8vZmfHjh2Lk5NTgwDP29ubt956ix9//JH09HTGjx9/3zlZUJuNiorixIkTyGQyevfuzcSJE+sF9Q8TQoBVUVFBQUEBt2/fJiUlhUuXLpGZmUm3bt2orq7G0dGR4cOHi6JFQl+kp6ezbNkynnrqKfr169ekMVFaWsrPP/+MlpYWCxcubEBfba/rFLxvz58/z+XLl9HS0qJz587Mnz8fCwuLJjEi7j5eaWkp58+fJzk5WaTkymQyhg0bxtdff42HhwdVVVXo6OiQlJTEoUOHyM7ORktLi44dO9KxY0esra3R09NDR0dHDI6FrHtNTQ1VVVWkp6cTGxtLXFwct27dYuHChbz88stoa2uzdOlSNmzYwNChQ3n22WcpKirixx9/RF9fH11dXYKCgtDR0WH37t0MHjy40edCS0sLR0dHHBwcGDZsGDdv3mTfvn2kp6fj6uqKvb09+fn5nDt3jqNHj5KdnU1lZSU7duzAw8MDW1tbDA0NxTkuPz+/VfXxLYW/vz/Lli1j/Pjx4saYra0tFhYWuLu707NnT3G8KxQKSkpKSE5O5vbt2xw7doyKigqkUqm4VsrPzycxMZHy8nL09fWRyWTY2tqiUqkoLS1t1hqsJRAClOXLl9O1a1d0dHRwcnKiurq62RZRgv2YYAP2OL2PHkd06NCBuLg4vLy8KCsrE5/Nq1ev0rVrV0pKSqisrHzUzWwz6Ovr88wzz/D777/z/vvvN2l8SCQSOnfuzL59+xp4XAcGBrJr1642GWtPMsL/xZNA+C4I9Kim7lonJSXh4eHRzq26Q5vS19dvlXXBvSDUHmtpabVr/fHDQlFREfr6+igUCurq6rCysgLuXOeVK1fIz8/H29u7XTcw6urquHHjBsHBwWg0GrENLYWJiQk6OjrU1tY2WscklUoZNGgQ+/fv55lnnuE///kP/fv3v6eSr1QqpXfv3lRVVfH999/z6quvNirAIpFIRP/OpUuX8vzzzzfLG+9uCB7FnTp1YtOmTSxatIhJkybh5+fXpOdNCDIHDRpEeHg4mzZt4tNPP2XixIl07NjxoVM/HwQhGLWzsxNp1BUVFaL10Nq1a7GxsSEsLAxjY2PkcjkKhaLVlKe/orCwkKSkJEaOHMnVq1dFyqKwaXLr1i309fVF25a7qdPx8fH89NNPTJw4kbCwsCb1cW1tLdu3b+fy5cs888wzlJaWsnjxYoqKiujQoQNjxozBxcXlvtlZgQnw+uuvs27dOhYvXsxLL73UQE1WrVaTnZ3NkSNHiImJwc/Pj+nTp+Po6Nis4KstcHed5Y0bN0hNTSU/P1/Mqnl4eBAUFERMTAzLly/HycmpUfEpQd37p59+Ytq0aU0S8BHKQZYvX06PHj3uGZi1JdRqtVirfPHiRdRqNWFhYcyePRtLS8tmZ2YFT+hDhw5x48YNAgICeOONN9DR0eG7775jxowZfPTRR2hpabFz505WrFjB8ePHqampYfny5TzzzDMUFBQQGxvLwYMHyc/PF72fzc3Nsbe3Fze6NRoNenp6ODo60rFjR0aMGMH69etJTU2lS5cuzJw5k02bNpGdnc1vv/3Gli1bcHV1ZeXKlVhaWrJ9+3a2b99OeHg4KSkpTJ8+/b7XKtAQAwICRNbHwYMHOXjwIIGBgfTr1w+lUom7uzvl5eVoa2tz7NgxcnNzqaurw9TUFHt7ey5fvoxKpaKyslIUdXsYsLKyQqVSieyN69evN9C8EK5RT08PMzMz3NzcxPKHuro6qquryczM5Pr16xQXF3Pw4EEqKiowMDDAzs6OoqIisrOzRcG39i7NcnZ2xtTUlLi4ODp16oS2tjbBwcFERUUxfPjwJh9HsM4SBC2fBML3h4uLC3v37iUsLIx9+/ahra2NtbU1OTk5og1VRUXFo25mm0Fg4Xl5ebFz507Gjx/fpHlRLpfTu3dv9u7dy3PPPSd+x9TUFAcHB2JjY+ncuXOr2iaXyykpKXkSCPMkEK6HuylYTflsVlZWPepte0CtVnP48GH69u3b5i8+wY7j1KlTvP32239bcay7kZqaipOTE8XFxZibm4v1iNHR0axbt4733nuPw4cPN0mptaUoKSlBKpWSm5vbqB9kc6Gvry9a69ztfyxAIpHg6+vLhg0b0Gg0ODs7c+nSJXr06HHPc0ulUoYMGUJVVRUrVqxg9uzZjYoGCcHw7NmzxWC4JZlh4VhmZmbMmDGDhIQE1qxZg6OjIxMmTMDMzKzJdGnhGImJiSLlevLkyY9EXbopkEgkyGQyTExM6Nq1K127dqWmpobExEQuXLjAmTNnyMzM5NSpUwQEBKBSqVqt0CsIFG3bto3ExESWLFlCcHAw8+fP5+jRo/Tr149Ro0aRm5vLxYsX+emnn1CpVISEhIgL/G3btjFnzhzc3NyaFIwVFRWxdOlS0tLScHFxYc2aNXh6ejJq1Cg8PDyaJXYmkUhET8aDBw/y+eefM3v2bJydnUVxoR07dpCbm0tkZCQffPDBQ8uAwp2APysri+TkZK5fv05WVhZqtRpra2v8/PwYNmyYqCYuzEG//vorAwcOrKdbcDfUajVnz55l8+bNvPrqqw+0rhM2bk+fPs3WrVtb9Ww29bpLSkq4dOkSp06doqamhk6dOjFjxgzs7e2bNWaF49XU1HDlyhUOHDhATU0Nffv2ZeLEiRgYGJCfn09dXR3//ve/mTlzJomJicyaNYuLFy9SU1MDQGhoKKNGjUJLS0vcdOrfvz91dXUMHTqUw4cP06FDB7Zv346xsTH6+voiE+Xu9+nzzz/Pl19+ybFjx4iMjGT8+PF89913aDQaKisrCQ4OJjAwELlczvz580lPT+ftt98G4NSpU/To0eOBDBdhHrC3t2fatGmUl5dz6tQpfvjhB9RqNVVVVUydOlWsjRcC9+zsbFHYLjMzk3//+98YGBhgZWWFp6cnLi4u2NnZYWpqKl5TW44BbW1tPD09iY+PJyQkhAMHDtC7d+8HrkeE65XJZOjp6WFqaoqLiwtHjhxBR0eHDz74gLKyMrGUZNu2bdTU1PDhhx/i7OyMi4sLHh4e2NnZiZsrbXltw4YNY/v27QQGBiKTyYiIiGD16tUMGTKkyWshYbNZIpFQUVHR6k3v/3VYWlpSXV2Nubk5RUVF6OnpYWJiQnV1tSiS9b+UEYY7a61x48bxz3/+k/Dw8HvO/3dDIpHQtWtXPv74Y0pKSsRNYIlEQu/evTl48GCTXT3uBX19ffLy8lAqlS0+xv8KngTCd0GtVjd4Qd4LKpWKoqKiNvH0uh/KyspITU2ttyvUVigvL+fnn39m+vTpD2UR2d7QaDSkpqbi7OxMQkICPj4+AFy5coU1a9bg6+uLgYFBu9Z1C0I1Pj4+XL9+XaxBag1kMhkODg6kpKSQmJhIhw4dGnxGqPE8ePAgw4cPZ9WqVXTp0kX0imsMUqmUsWPH8ttvv7F69WpefPHFRvtFqFN+9dVX+fbbb3nuueeapSb912MJgfsHH3wgKkMPHTqUyMjIJgVLwjG8vLx4//33OXr0KJ9++ikDBw6kb9++D10FuDkQ2qWnpyfSOD09PUlKSkKj0bBnzx7279+Pr68v4eHh9VSNm7pBV1FRwdmzZ9m/fz/R0dH885//pHPnzujp6VFWVsalS5f44IMPxEX5iBEjGD58uFjbOXv2bIqKinjhhReQy+WoVKp7ZlgFSuTFixf56quvqK2tZeDAgfTu3VtUe777upsLmUzGoEGDsLe35z//+Q+RkZHEx8dTW1vL0KFDxdrM9rrfQrApWP5cv36da9euUVxcjImJCa6urnTr1g1HR8d6lj9/pZgnJiZy8+ZNPvjgg0azwGq1mr1793L27FkWLlyIlZXVA69JUDe+efNmk7/TkmtXKBRcu3aNEydOkJ+fT4cOHXjmmWdwdXVtduZduNbCwkKOHz/OhQsXcHBwYPz48Xh5eYkBiMBGGD9+PBEREUilUiwtLbGwsBCDYB0dHWbNmlVvE034761bt7h27RqA6KN7v/6Ry+XMmTOHzz//HAsLC2bMmMHGjRtFOvKkSZPqUfiFescZM2Zw+PBh9u/fT79+/YiMjKwnXHYvCLW0Q4YMIScnh6qqKv78809kMhnjx48nICBAVHp2d3fHxcWFTZs24eTkxKeffkpZWRl5eXkkJiZy4MAB8vPzUalU4ph0c3MThbkEP+eWjg2JREJYWBiHDh3i5ZdfJicnB4VC0SIbJblcjrm5OdnZ2VRXV2Nvb4+dnR3u7u5kZGSIHuEWFhai0Fpubi7V1dUYGBjg4uIiBv9WVlYtvjYhU1dZWUlGRgYuLi44OjpSW1tLXl4ednZ2TTqOjo4OBgYGVFVVUVpa2uz++L8GHR0dLC0tKS0tRSaTYWVlJYqyFRQUYGJi8j8XCAPiHPLbb7+JrgkPgpGREV26dOHQoUOMGzdOHON+fn6sXbuWoqKiRjVemgpjY2PR0/v/en37k0D4LjQnIywYgt+rvrKt2nP27FkCAwPvSXNtKZRKpVgX3JiVzt8Rgk1LREQE27dvp3///sTExLB27VpmzZrFTz/9hFqtbjeBLKEN0dHR9O3bl40bN+Lp6dnqY0okEjw8PEhLS+PWrVuNTlrCDuInn3zC6NGj0dfX58aNGwQGBt73uFpaWkyZMoWffvqJtWvX8swzzzQq1iJkhufPn8+3337L5MmTWy0Cpqury9ChQwkLC2Pjxo2cPn2aKVOm4O7u3mS6tI6ODgMHDiQ0NJQ///xTpFx7e3s/9gwHoe8yMzNF26X333+fqqoqrl+/zu7du8nLy8PZ2Znw8HB8fX0xNDRs9LpUKhXZ2dkcPnyY2NhYMcj29fWlZ8+eSCR37JFOnjxJYGBgPQsWoR2WlpaUl5cTGRnJ6NGjuXr1Kt9//z0ymYzOnTsTFhaGhYUFWlpa1NbWkp6eztGjR9m1axeGhobMmzePTp06tWldriDAJGxSrly5koEDB/L666+3Gw1RCP5yc3OJjY3l+vXrFBYWYm5ujo+PD+PHjxftiZpynbW1taxbt47Jkyc3KnaoVCpZv349WVlZvPXWWw/sP6GOduXKlRgbG/Pmm2+22Nv1Xsevrq4mKSmJEydOiHZ0Q4YMwcPDo0We2cIx4+PjOXz4MIWFhXTp0oU333yznoiWSqXi+PHj7Nu3j1deeaWeX7CVlRVPPfUUN2/eJCEhAX9/f0aPHt2gLUqlkuXLl4uq/YWFhVy8eLHRDUQBEokECwsL5syZw5IlS5g9ezbjxo3j0KFDPPXUUxw9ehRbW1s6deoEwLZt2xg8eDAeHh54eHiQm5vLnj17+Oijj+jVqxeRkZFNHh/p6emMGzeOtLQ0JkyYwMGDB9m6dSuDBw8mJCQEPT09sQ7ewcEBPT09kVIcFBQksj/KysooKSkhJSWF+Ph4UXFbV1cXe3t7MUC2tbUV66ebyjJzd3cnJycHtVqNlZUVaWlp+Pn5Nem7d0Pw3k1NTaW8vFx8F5uamqJSqTAyMqKmpgY/Pz/x+Gq1moqKCkpKSkhNTSUxMZGjR49SUVGBnp4ezs7OuLm54eHhgbm5OXp6ek2i5stkMnr16sXRo0d59tlnkUqlBAQEEBMT0+RAWGAoaTSa+3pAP8EdSCQS/Pz8SExMFLPDurq6SKVSMjMzsbGxoby8/FE3s80hkUgICgri7NmzHD16lEGDBjVps6xfv3589tlnDB48WFSLF4QEo6OjGTBgQIvbZGRkJNpVqVSqe4r0/V/A/90rbwQCNaMpLy9Bgbg963RUKhWnTp1i1qxZbb7Tf/jwYTQaDQMGDPifCIIB0Y5FT0+P3NxcSktL2bx5M/PmzUNfXx8dHR2ysrJwcnJqtzbU1NSQn58v2ly01WLdzc1NFE9QKpWNZm5NTEzw9/fn7NmzDBs2jL1799KhQ4cHTnC6uro8//zzfP/99/z555+MHz/+nkGkk5MT8+bN47vvvkOpVBIeHt6q8SOR3PEufuWVV7h27Ro//fQTvr6+jB49WhQiacoxLC0tmTFjBjdu3GDdunU4Ojoybty4x5YufTfS0tKwsLAQrTyMjIywtramV69elJeXixTqzZs3Y2FhQUhICIGBgVhYWKBSqbhx4wYHDhygpKSEXr16MXr0aHR0dPj444+ZM2eOeP1VVVWcPHmSBQsWNOiTqqoqli9fjpGREXPmzEEul+Pp6cmIESPIycnh3LlzLF68mLq6Ouzt7UlOTkZXV5eUlBS6devGrFmz2lyYSqlUEhcXx7Zt29DV1eWll17C2tqa1atXs2bNGqZMmdJmG4RCje+tW7eIjo4mLS0NY2NjOnTowNixY7G1tRWFfZoDYfPB0tKy0fp6hULB6tWrkUgkzJ0794HXI7BefvzxR3r27MmgQYPaZAEjiF5lZGRw6tQpYmNjsbCwoEePHkyZMgVDQ8MWvevUajV5eXmcPHmSixcvYm1tzcCBA/H29m5AJa6pqWHjxo2kpqaKivbC3wUv5bS0NLZu3co777xD//79ReukuxETE8Mff/xRrw1Hjhxh6tSpDxyfLi4uPPvss6xcuZIXXngBtVrNq6++Sk1NDd999x1wJyBPT0+vZ2Voa2vLc889R0FBAfv27ePjjz+mR48e9OnT577PRW1tLRUVFajVaszMzAgICCAgIIC0tDR27drFrl276NevH/7+/lRWVmJmZtbgPggbmubm5pibm4s+wWq1murqaiorK0lLSyMlJYXdu3dTUFAgbgg7OTnh4eGBg4ODSB1v7D4bGhpiZmZGRkYGwcHBXL58GV9f3xY975aWluLz5ubmBtwJSuVyObq6uuTn59f7vFQqxdjYGGNjY5ydnenRowdqtRqFQkFFRQXJyckkJydz9uxZscbawcEBd3d3vLy8MDMzE9dqd7dXIpEQERHBJ598QkVFBYaGhoSHh7NhwwYGDBjQ5Gfd0tKSkpKSBu1+gsbh5eXFjh078Pb2Jjo6GgMDA3R1dcnMzMTY2Ph/MhCGO+N44sSJ/Otf/yI4OLhBnX1jMDMzo0OHDpw+fbpe8BwZGcnvv/9O7969W8xu1NPTo66uTtxIexIIPwGAmGlryuSemZmJvb19u7bn9u3byOXyNj+PoOa4cOHC/6nBX1FRIVLbk5OT2bBhA2+88QZOTk6kpKRgaGhIVlYW/fr1a5fzCzY41tbW3L59W/RMbQsICz61Wk1xcXGjlHyJ5I6V0tKlS/nHP/5BRUUFGRkZuLq6PvD4crmcV155hSVLlrBt2zZGjx7d6EJAIrnjRzx//ny++eYbamtr71uL3FTIZDKCgoLw9vZm7969fPrpp4wePZqIiIgmU99kMhkdOnTgvffe48iRIyxatIghQ4bQq1evZtWnPmwkJSXh7OyMlZVVPWqtRCLBxMSE0NBQQkJCqKmpITU1laioKD755BPKysqoqqrCxsaG559/noCAAPGlKAQdwstWUDJ3dXVtUMdWVlbGkiVL8Pb2ZsyYMfVerNra2hgbG2NlZYWuri5VVVVoaWlRVFREfn4+oaGhTJs2rV6GuTUQ6LgJCQls2bIFtVrNhAkT8PT0FMfBq6++yoYNG1i8eDGvvPIKpqamLcpQCoHf5cuXuXbtGlVVVbi5udGlSxemTZsmBgWtGTclJSXs3buXt956q8HzVF5ezvfff4+DgwMTJky4bxmD0OYLFy6wYcMGnn32WQICAlo1vwgMqIKCAs6fP8+5c+dEi45hw4ZhYmLSIlaFQJePi4vj0KFDFBYW0rVrV958801xY+qvfVpaWsqyZcswNzfn9ddfrxckK5VKNmzYQGZmJvPnz0dfX5/ffvsNbW3tBtdfXV3Nt99+W8+nFiAqKoqSkpJGA+e7IZHcsWgqKSnh448/ZsyYMeLzMnfuXL799ltUKhWjRo1qkN2XSqVYW1szdepUioqK2Lt3Lx9//DHdunWjf//+jQbEubm5Yj20s7OzON4EXYacnBx2797N5s2bSUlJoX///k26B0J9roGBAQYGBlhbWxMaGiqOe6HGPTU1lYsXL7Jz504UCgVGRkbY29vj5eWFk5MTlpaWYiYqNDRUZDstXbq0xYtnYSM6PT2dkJAQ8ffm5uZoa2s/0EJJuDZDQ0MMDQ2xtbUlIiJCVAUXysmSkpJYt24dpaWl6Onp4eDggI+PDy4uLlhbW6Ovr4+hoSEeHh5cvXqVbt264fL/2DvvsCjOtY3/dum9V6kiIAiCgIqKvfcWe4tGc6yJQY2mJycx1d5jTOyxJcbee++9UBQFpPe6wLbvD8/MB9IWRc3J8b6uvYR1mXlnduad93me+7lvV1fy8vLIzs7WmHbq7OzMzZs333gJawhnZ2cyMjJwdHTk/Pnz6OrqIpPJSEtLw97envz8/H8kVVcikWBpaUn37t35/fffef/996udXyUSCd26dWPBggW0bt1aZOM4OztTXFxMSkoKTk5OzzUe4Tkv+Nj/L+OfEwXVAmpSEX78+LFGAcbzQq1Wc/jwYdq1a1drFE9B+GPNmjWMHj261havfxckJCRgY2NDdHQ0eXl5/PDDDzg7OyORPLUjcXJy4sGDB9Uuhl4EV69eJSAggMuXLzNkyJBam8xNTU3R09NDLpeTmppaaW96nTp1MDc3Jyoqik6dOrFv3z7Gjx+v0YJZ6JNbsGABurq6dO/evcK/k0gk2NvbM23aNObPn09JSQnt2rV74WOVSJ4qQ/fr14/Q0FDWr1/P6dOnGTVqFA4ODhpXh/X19enatStNmjRhw4YNnD17lpEjR4rVh7/TA1apVJKXl0dJSQlOTk5VLv709PRE0QxdXV1atWqFubk5t27dYuvWrdy6dUu0Ztq3bx+DBw8Wvz+5XM7BgwfL+BKq1WqysrJYsGABjRs3Fr9vgY587949jh8/TmJiIt7e3owYMQI3Nzdu3LghquWmpKQwf/58TExMaN68OUFBQWIl/3mC04SEBLZs2UJOTg79+/cXk0mlt6Wrq8vw4cM5evQo3333HVOmTKny3JXevlwuJyYmhgsXLnD//n0MDAxo1KgRo0aNEtWmhfP9olCr1WzdupW2bduWuV+F875o0SIaNWpEjx49qp3j5XI5u3bt4vr160yfPl3j+6GycclkMm7dusWJEyfIzMwkMDCQ8ePH4+Dg8FzBv5DASElJ4eTJk1y9ehU7Ozu6dOmCj49PpYkotVpNfHw8S5cupXXr1nTu3LnMuZDL5WzYsIHs7GymTJkiBshCcPYsCgoKkMvlWFtbk5mZKVLqhbaSpk2banQ83t7eqFQq4uPjkcvl6OrqiiyTSZMmMXjw4Er/VqBZDxs2TGTmCAFxp06dMDY2Fs9FfHw8derUITY2toywonD/ODo6MnbsWFGgbP/+/bi5udG6dWuN7edKj0toJ9HV1cXLywtPT086dOgg3hspKSk8efKE6OhoTp8+TXZ2Nnp6etjY2GBqasqVK1do27atWNF9njYjwSpJoK4LcHFxEXtFaxpkC8Gx0HdqY2MjCpkqlUrROjEiIoLTp0+Tm5uLoaEhzs7O6Ovrs3fvXkJCQtDR0cHDw4PIyEiaNWum0bFZW1uLfa6CnsIbVA6hAmxkZEReXh5SqRSlUolSqcTY2BiZTPa6h/jSIJFIaN68OefOnePq1as0bty42mtMSGjfvHmTpk2bitd6aGgo58+fL9M/XBPo6OiI87ZSqXzeQ/pH4E0gXArFxcUaVY4Ef83g4OCXtqjOyckhNjaW0aNH19o2VSoV27ZtIzg4uNZtWl431Go1T548IT8/n9mzZ/P222/j4uIiHmNycjIWFhYivexlQKVSERkZSfPmzTl8+LBG1BdNoaWlJfbPCP1xFUHIIO7bt49Jkyaxe/duMjIyNFqwSCQSjI2NmTJlCvPnz0dHR4dOnTpVGgzb2toyY8YM5s2bJ4ok1YYHLjwN6KdPn86FCxeYO3cuLVq0oGvXrhov/gS69JQpU0TLGn9/f3r37l1mIfq6UVhYCDxlM1SUWBMojnFxcezdu5e4uDjCwsL4/PPPxYCzX79+pKenc/fuXfbu3Ut0dDRPnjyhQ4cOODo6YmhoyO3bt7GwsKBOnTpiv3BmZibz58+ndevWtG/fHpVKRUpKCqdOneLq1avY2trSpk0bfHx8MDQ0RKFQsGfPHi5fvsz06dOpU6cO8DRYefz4MWfPnuXgwYNYWVnRsmVLUduguiSMEBju2LGDiIgIevbsWaXQm7Cg79ChA9bW1sybN48xY8bg5+dX7nsVhK7i4+M5c+YM9+7dw8LCgiZNmtCtW7cy/amVnXulUilWT6VSqfiq7hqKjo4mNjaWkSNHlkk+pKWlsXDhQtq0aUP79u2rPD9qtZrCwkJ+++03lEols2bNei7FeyHQefz4MSdOnCAqKgpXV1e6d++Ol5fXcwuOCeO7ceMGx48fp6CggNDQUGbMmFGteJdKpeLWrVusW7eO4cOH06hRo3JU6TVr1iCXy5kwYUKF/dXPwsrKijVr1jBw4EDkcjmPHj1i6tSp1K1bV2O9BrVazc6dO3n33XeJi4tj06ZNDB8+HLVazZkzZ/j000/ZunUrurq6VdpbCf2jQ4YMoXPnzuzfv58vv/ySli1b0r59e4yNjYmIiMDb25tjx47RuXPnSrcj+PD279+f+Ph4Pv/8czp16kSLFi2eq2e79LaFf/X09HBxccHFxUX0HRe80FNTU4mKiuLhw4d88803xMTE8NVXX9GmTRtcXV1xc3PDxMRErNJXNR5zc3O0tLTIzMwsw8JzcHAgLi6O4uJiFArFC7PVhDEIiuIODg40adJE7FcXguO7d+9y+fJl3n//fZycnFAoFGIPtJGRUbVrQmEelslkFBcX17qeyz8Rbm5uJCcno6+vj6GhIYaGhujo6Ih0/n9iRViAkMhdvHgxPj4+lSb1BEilUnr06MHvv/9OcHCweD02bdqUBQsW0Lt372rZRBVBW1tbLP69CYTfQERRUZFGC+2SkhLS09M1FlR4Hly5ckVcgNYGBBGn5OTkWq1U/p1w8+ZNrl+/jre3dxkbEbVaTXJyMn5+fujo6Ly0B1VKSgrwNKgRRE1qE15eXly4cIHHjx9X+aDw8fFh8+bNZGZm0qJFCw4dOsTQoUM13o+ZmRnvv/8+8+bNQ0dHh7Zt21a6WLe0tGTGjBksXLgQmUxGr169ao1ur62tTYsWLfDz8+Ovv/4SfYN9fX01Dri1tLRo1KgRXl5e7Nu3j3//+9+89dZbBAcH/y3aAnJzcykpKUEqlZZJ0AgBXEREBPv370cmk9GxY0fGjBlTbuErUDJtbW1p1aoV3377La1bt+bWrVvs3LkTCwsLIiMjGTt2LCqVCqlUKlaC27VrR3BwMOfOnePkyZPIZDIxkBFUkAUl6jVr1qBSqZg1a1YZNknp6pJMJuPRo0ecOnWKv/76C1dXV1GQ71k1XWFBeuLECY4ePUrr1q0ZNGiQxsJPEomEwMBALCwsWLZsGZ07d6ZNmzZoaWmhUChITU3l7NmzXLt2DWNjY0JDQ+nRo4doq1YRhMDuwYMH3L59m8ePH1NYWFhGSNHExAQ3NzcCAgJwd3ev8JlRXFzMhg0bRLVhYdtPnjxh8eLF9O7dm2bNmlUbBKelpbFs2TLRg7mm/WBCNezcuXNcuXIFIyMjWrZsycCBAzXuwa9oXHK5XBRLi4iIwMPDg7feegt3d3eNgmqlUsnRo0c5duwYU6dOFZk7AgoLC/n111/R19fn3XffrdFCT1BU9vX1JT8/n06dOolsEE2OLTY2ltjYWEaMGIFUKmXRokXs2bMHDw8PCgoK6NGjByEhISxatAi1Wl0ugH8WpSvEXbp04cCBA3z11Ve0atWKBw8e0KpVK5GWXBmEth8vLy+aNGlCSkoKe/bs4ciRI3Tq1IlmzZq9UEBc2bgFL3QHBwcaNmxIQUEBderUwcTEhM2bN2NsbMzVq1fZvXs3xcXForKzq6srdevWxdzcHAMDgzLiVWZmZhgbG5OWllZG78LGxobs7OyXXqESmEelg34LCwtKSkpo0aIFd+7cYdGiRcyePRsdHR2RKu7t7Y2VlRWGhoZlnh1mZmYoFAokEglFRUVvAmEN4Ovry+3bt6lTpw7JycmUlJSgUCgoLi4WE7X/ZDg7O9OkSRO2b98uzjNVwc3NTWz5E4pYlpaWGBgYkJCQoPH8Vho6OjooFAq0tLTeBMKvewB/J8hkMlHBrioUFRUBvDTVUrlczpkzZ3j77bdrbZsZGRls27aNqVOn1nqA9rqhVquJiori4MGDfPfdd+zcubNM34SwKDYyMirnwVubuHfvHt7e3ty5c4eGDRvWupCam5sb586dIzU1laKiokqvP21tbdq1a8eRI0fo06cP3377Lb169ao281gaFhYWfPDBB8yZMwepVErr1q0rPR5TU1PCw8NZtmwZW7ZsYeDAgbVmTyWRPFUUHTVqlOgb7ODgwMCBAzUWwhIq3W+99RbNmjVjw4YNnD59mqFDh74QxbQ2UFhYSHFxMWq1WgwuZTIZV65c4dChQ5iYmNCjRw+8vLw0YqskJydTUFDAW2+9hZ6eHjKZjOPHj3P9+nX27t3L4cOH8fHx4fz583h6ehIdHc3+/fvx9PRk4MCBuLq6ltmPwH5Zvnw5jRo1omfPnpV+txLJU+/fBg0a4OvrS0FBgaheK9iXhYWF4ebmhra2Nnfu3GHr1q24uroya9asMuJImkIikeDq6srMmTNZtmwZSUlJODs7c+rUKWQyGU2bNuWDDz7A0tKy2l7zoqIijh49yqlTp3B0dCQoKIi2bduWEYoSKJAxMTHs27ePjIwMOnbsSFhYmBisCQJZNjY2NGjQQHzv0aNHLFmyhBEjRlRZSRQ+Hx0dzS+//CIGzZomf4TExe3btzl58iS5ubk0btyY9957D2tr6+e20lGr1WRkZHDp0iXOnz+Pjo4OrVq1YuDAgTUS0youLmbz5s0kJCQwc+bMcj3e+fn5rFixAltbW4YMGVLjuSQzMxOlUilWmmrSAqRSqdiyZQt9+vQR59cJEybw008/sX37dqZPn462tjZOTk5MmTKFxYsXiwkZTRg31tbWYkC8Y8cOjhw5IlqkVTafq9VqsrOzxYBaKpXi4ODAO++8Q3JyMrt37+bw4cP07NmTxo0bP1d1SFMEBQVx7Ngx3n77bXR0dGjTpg16enpiEJOdnc2jR494/Pgxp0+fJi8vD319fRwdHalbty4eHh5YWFhgampKRkYGMpmsTCCcn5+Pjo4O+fn5taqEXhUkkqeOC8uXL2fw4ME4Oztz9+5devbsiaOjI7GxsURHR7Np0yZycnIwNDTE1dUVHx8fXFxcsLS0RFtbm6KiInFt+AaVQyJ56oKxb98+GjRowIULF0TVc2F+/acHwhKJhB49evDvf/+bhw8f4unpWeXntbS06NSpE/v37xddXrS0tGjSpAnnzp2r1nO+Imhra4ttH28C4TcQIUi5V4fc3FyMjIxemmL0kydPUKvV5bLkzwu5XM7q1avp0aPHS61ivw4IHp0LFizA3t4eNzc3VCpVmWBfLpejUCjIycmpVbrys+O4du0aXbp0YcuWLRqLmtQE9vb2FBQUIJFIKCgoqHThJJE8VcM8cOAA/fv3x9/fn9OnT9O1a9caXU8WFhZMmzaNOXPmAFQaDEskEoyMjJgyZQorV65k9erVvP3227W6IJNKpXh6evLJJ59w9OhRvvnmG3r06EGrVq00ssoQtuHk5MSMGTM4f/48c+fOpVWrVnTp0uW1eQ/n5uaKatESiYTDhw9z5MgRnJycGDt2LE5OThr3bKrVavbv30+7du3Q09MT+6Xv3r3Lhx9+SEBAAHfv3mXixInk5+dz7do1vLy8ePfdd/H39xevp9JBsODnOnjwYEJCQjSe84TkQ0hICMHBweL+BG9WhUKBXC5nxowZ1KtX77nnUmHBJJPJsLa25pdffsHc3JzZs2fj7e2t0bUhBBpLly7F2tq6SlEneFoBcnFxoXXr1qSmprJlyxauXr3KhAkTMDY2Jicnh/379zNz5kyxuvHgwQOWLVvGu+++W63armCb9+effzJu3Di8vb01OgaVSkVsbCzHjh0jIiICNzc3+vTpQ7169TS+R57dJiAKX504cYKkpCQCAwP517/+VeN+YsEC6Oeff8bc3Jzw8PAy87QQwC9ZsgQPDw/69ev3XK0W8fHxSCQSSkpKMDMz0ziQVqvV3LlzB7lcXqbKa2xsTJs2bfj8888pKSkBnl7fzs7OvPfeeyxYsACJ5Kk9Sk3aNjp27EhERASJiYlcuXKFEydO0LJlywrnopSUFHGeECCVSnF0dGTcuHE8efKErVu3cvDgQQYMGCAyomq7Quzh4cGGDRvQ0dHB2tqamJgYfH190dHRQUdHB2NjY5ycnERlZ6VSKVo6xcTEcOXKFbKzs7l8+TIymYwDBw7g7++Pvb29uKYyNDQkLS0NOzu7Wht7dbC3t0dLS4snT57g4uKCv78/9+/fx8fHh4CAABo2bCgKjaWlpRETE8PNmzfZtWsXCoWC69evY2hoyL1797C0tBTXkf9E5l1twNzcnJKSEhwdHUX/a+GeFVTN/+nQ19dn6NChbNy4kY8++qjK2EMikeDv789ff/0l3hsSiYRGjRoxb968Sp1EqoKQ8Bbu0/9lvAmES6G4uFhcQFaF2NhYnJ2dX0ogrFarOXHiBK1ataqV7avVao4cOYKhoSEtWrT4R03MgkrzsmXLGDhwoCj8Ym1tXSYIKy4uRktLi4SEhJcmcJaXl0dqaiqWlpaoVKqXIshlamoqLjgSEhKwtrau9LNGRkY0atRIlN0XaLA1YQMI9Jvp06czd+5c1Go1bdq0qTQY1tfXZ8KECaxdu5alS5cyfvz4Ggu6VDcePT09unbtSuPGjdmwYQNnzpxh1KhRuLq6ip+pbhva2tqEhYXRsGFDNm/ezL///W9GjhyJp6fnS7VDqwiRkZGiyvgXX3yBp6cn77///nNVqrOysoiIiCjT+vDkyRPS09MxNjZm5cqV7Ny5kz59+jB48GAMDAy4d+8eJ0+eZNu2bTg5OdG0aVMaNGiAoaEhZ8+eZdeuXUyaNIm6des+1/coLMZNTExo1qwZeXl57Nu3j0aNGhEbG8vatWsJDQ0lNDRUpCxrGvQrFAru3bvH/v37yc7Opm3btmzfvp29e/eya9cuJk+erBELQiaTsWzZMpo1a0bbtm01CiCEz9jZ2TFp0iQOHDjAsmXLmDJlCjt37iQsLExUG46MjOTnn39mwoQJ1WozyOVydu/ezdWrV/nwww+xtbWt9POC0Elubi4XLlzg9OnTaGtr07p1awYOHCge+/MEwEqlkvj4eE6ePMmdO3dwdHSkbdu2NGjQ4LmSRkJ7ypIlS2jatCndu3cvE+QKxzF//nwCAwPp2bPnc+sNCG4Lwpyk6Xbkcjlbt25l5MiRZaivJSUlHDlyhNmzZ7Nx40bMzc3F+8HJyYmpU6cyf/58jSr9pREbGysqvXt6ehIZGcnhw4fp3bu3KNwkbEsQraposSuVSnF2diY8PJzIyEi2bt3Kvn37GDRokKhEXVvQ19fH2tqaJ0+eEBQUxLVr1yr0ZxYqVlpaWtja2mJjY0Pjxo2Bp1X3JUuWsHPnThITE3n8+DEZGRnAU7FJQYXZxcWljGXZy1y7CF7ply5dwtXVFX9/f3777TfRPUG433V1dalTpw6Ojo6EhYWJ1+2cOXOIjIxkzZo1HDx4EFNTU7y8vPDx8cHNza1M4eSftAZ7Xmhra2Nrayu26hgaGlJSUkJubi45OTn/+IowPL0OGjRowMmTJzl16hQdOnSo8trQ19enZcuWHDp0iOHDh4sMEWNjYx4/fixWijWF0M8vCJX9L+NNIFwKQiBcFYQ+L01USp8HhYWF3L9/n/79+7/w9tVqNY8fP+bUqVN89NFHr3yR/zIhUA2XL1/OuHHjRKXQx48f4+rqWuZYU1JSsLS0JDMz84V9byvDkydPsLW15fHjxyLVrbYhkUiwsbERaZMNGzas9FgkEgnt2rVj4cKFdOjQATs7O27cuEFoaGiN92lpaUl4eDgLFixArVZX2jMsLBTefvtttm7dyoIFC5g0aRImJia1XpmwsbHhvffe4/r16yxbtkyk7RoZGWlclTEzM2PcuHHcv3+fdevWUa9ePfr371/r460IarWanJwcTp8+zalTp+jbty9TpkypMvCpbnunTp0iODgYQ0PDMn29UVFRbNy4kdjYWAYMGMDo0aPFhX7r1q1p1aoVubm5PHz4kIsXL/LHH39QUFBAamoq33zzDS4uLi90rCqVipiYGNatW4eDgwOzZ8/GwsICpVJJQkIC58+fZ968eRgZGREWFkajRo0q9WgX+oqvXr3KgQMHMDExEZWJhbl72LBh7N+/n++//57333+/2mDy4MGD+Pr6VtkLXxmExEq3bt1IS0tj9erVxMXF8dlnnwFw//59fv31VyZNmoSHh0eV45DJZKxZs4bi4mI++uijSkWxhP7xqKgojh49SmJiIn5+frz77rtllK9rAqGinJ2dzYULFzh//rzYo9+zZ88X8uNWq9VERESwatUqBgwYQJMmTcqcZ0Esbd68ebRo0eKFRPfUajUxMTHiM8DIyEgjLQC1Ws25c+ewsbEpk6wQaO516tQhLCwMW1tbFi9ezIcffigmqwRv9YULFyKVSqucl0vvLyoqCl9fX06cOMGgQYNwd3cnLi6O7du3s2/fPvr164e/vz/a2tqibVl1AnI+Pj58/PHHXL16lZ9//hlXV1f69u373PPKs5BKpQQEBHDt2jVatWrFyZMnNVJKLr1vqVRK/fr1OXr0KCEhIYSFhSGXy8nMzGTJkiXEx8ezb98+bt26hVQqxd7ennr16uHh4YGjoyP6+vq1bocnkUgICgpi+fLl9O3bF2tra2QyGQUFBRVS64V9C8+Rhg0bolAoaNiwIb169SI1NZXIyEiOHTtGUlISOjo6uLm54evri5eXFyYmJq+NhfR3gETytN89KSkJExMTVCoVSUlJWFlZia1C/wuQSqUMGjSIH374gaCgoCrnWYnkqeK0YC1pYmIiqkefPXtWYzFAAQJLSKFQvAmEX/cA/k6oSSAsSPPXJtRqNbdu3cLd3f25lEGfRVFREevXr2fIkCGvZHH/qiAE+EuXLmXMmDH4+Piwa9cu3NzciImJoVmzZmU+n5SUhLW1NdHR0S+FbiV4tAo+iy+z8u7l5cX9+/d59OhRtcqKgoDSrVu36NGjB5s3bxZVB2sCgcr3wQcfMH/+fFQqVZVqtzo6OgwaNIj9+/czZ84cpkyZ8lw2G9VBS0uL4OBgvL292b17N19//TUDBgwgMDBQYyEsqVQqeg8fOHCAr7/+mv79+xMSEvJSxLSEAPjIkSNcvHiR6OhovLy86NOnzwtdm4WFhZw9e5Zp06bx5MkTjhw5wvnz50lOTmbOnDmir/Cz1S74/8VcUFAQPj4+rFy5UhRa27hxI1paWvj7+xMSEoK9vb3GVX7Brm3Xrl3cunWLoUOH0qBBA3HRrK2tjaurKy4uLvTp04e4uDhOnz7N3r17cXZ2pnXr1nh6eoqU7fz8fM6ePcvx48dxcXHhnXfewcXFpdwiXEtLi27dumFpacmcOXMYP358pRXt3Nxcbty4wYcffvjCicLevXvTu3dvvv/+e5Em+euvvzJ58mTc3d2rDIIzMzNZtmwZnp6e9OvXr8J7VKVSkZ6ezrlz57hw4QKWlpa0a9dOFFV83gRKfn4+9+7d49SpU6Snp4vUZ3t7+xfu9VepVJw9e5adO3cyYcKEcskAtVpNamoqCxYsoFOnTlVqEWgCmUzGw4cPcXNzIz09HRcXF43u4/z8fPbt28fUqVPL9SsfOHCAadOmoaWlRf369Rk+fDiLFi0SBeUAkSa9ePFiRo0aVaGCeWkolUqePHlC586dRX9jqVSKm5sb77//Pg8fPhTZDW+99ZbohatJglVHR4emTZsSEBDAmTNnmDNnDiEhIXTt2vWF1wESyVOf5aVLl9K/f39RjK0mLUdCIhP+X2BSR0cHW1tb/P39MTY2FnUh8vPzSUpKIjo6mr1795KWliZSwt3d3fHy8sLa2hpjY+Pnov+XhtA2lpycTJ06dXB1dSUyMpKQkJBqtytYQmVkZGBkZETdunWpW7cuXbp0oaioSEw03r9/n71796JSqXBxcREDY3Nz81plT/3dIQTCwrrt0qVLyGQy8Tv8XwrMrK2tad++Pdu2bePdd9+t8howMzPDx8eHCxcu0LFjRwACAgI4dOiQ2O+rKaRSKbq6uhQWFv5Pne+K8CYQLgVNAmGFQkFmZqY4kdcm1Go1x48fp1+/fi+8KFOr1ezbtw9XV9cyCsr/7RBUPRctWsQ777yDr68vEslTn+DmzZtz5cqVMn3QAiVP6EkxMzOr9THJ5XIiIyNp27YtBw4ceC4FP00gkUhEH9f8/HzkcnmV16uWlhadO3dm+/btzJo1C3hKG6xfv/5z7d/Kyopp06Yxd+5clEplpdZK8DTI6d69O6ampmIwLFj31CYE2u3gwYNp3rw569ev58yZMwwZMkTjKohE8lTkqW/fvjRp0oR169Zx5swZhg0bhr29fa2MWaDQHTlyhHPnztGkSRNmzpzJt99+S0pKirigft5tX716lfz8fFavXk1+fj5t2rQhJCQEW1tbUlJSiIqKYsaMGZVeL0JAtGzZMuzt7Rk/fjy6urrI5XLS09O5du0a69evp6CgAE9PT5o2bYq7u3ulFXihCrh+/XoaNGjAZ599VmmwJlBYSytP3717l8OHD7Nx40YaNGiAkZERFy5cwNfXl/DwcGxsbKqcI6VSKc2aNcPc3Jxly5YxfPhwkbYqeMtKJBLu3LmDu7v7Cyu9Hjx4kN9//53IyEgOHTpEbGwsFy5c4IMPPqhSyERI6i1btoyuXbvSunXrcoF9UVERERERHD16lJSUFJo0acIHH3wgWj89D025pKSEmJgYTp06RXR0NK6urnTt2pV69epp1B6kCRQKBTt37uTmzZvMnDmzXDJMEGJbsGABffr0ITQ09IWfe/n5+WLQWFJSUqU9VulxHD16FD8/vzItCULPfVBQkBjoSSQSgoODycnJYdGiRUyfPl0MLl1cXJg0aRJLly7lnXfeqbIXvLCwEJlMhlQqRUdHp0zVUUtLC09PT6ZPn879+/fZuHEj586dIyAgQOPEhETyVBm5Q4cONG3alL179/L111/To0cPmjVr9kKMJUtLS3E+8/LyIjIyssbaG1ZWVmhpaZGWllbGQsnW1paYmBjS09PR1dXF2toaa2tr/P39UalUyOVyCgsLiY2NJSYmhu3bt5OZmYm2tjZ16tTB09MTDw8PbGxsamyTJ5E87fO+fv06Tk5ONGrUiGvXrhESElLt3wlifIJQm5B8Eb4HAwMD7OzsaNasGXK5nIKCAh48eMC9e/c4cuQIcrkcR0dHGjRogKenJ7a2trV2H/5d4eDgQHp6uqiBILD6njx5Ql5e3isTS3vdkEgktG3blm+//ZaIiAh8fHyqrAp37NiRFStW0Lp1a/EeMTc35+HDh/j4+NRo34JQ1ptA+A1ECPL/VUGhUKBSqTQS1aoJ1Go16enp5OXlvXAfq0Abvnr1Kh9//PE/xuBdrVYTHx/PokWLGDNmjBjgq1Qq0tLSsLKyQiaTlammCxX85s2ba6QI/jzIyckR/e8MDQ1fmk8xPK08CAqiBQUF1V6HXl5eFBcXk5CQQJcuXUSF4Oe9JszNzZk+fTrz589HLpfTvXv3SnsqpVIprVq1wtjYmLlz51ZLD30RSKVSUX341KlTfP/993Ts2JEOHTpoTKOTSCTUqVOHDz/8kLNnz/LTTz/RsWNH2rdv/9xUPKEqevjwYc6cOUNwcDCffvop5ubm5Ofni0ma5wmEBfGh06dPs3TpUkJCQujRowf169dHJpNx8OBBAgMD2bJlCx999FGlwZ5ATZ07dy5NmzalW7du4kJOV1cXR0dHHBwc6NatGzk5Ody+fZsDBw6QkpKCo6MjoaGh+Pr6ikmmoqIi/vzzT+7cucPbb7+Nl5eXRn238P9JiZCQEHx9fdmxYwfr1q3DzMwMW1tb7O3tRUphdYwIgSr63nvvsWTJEnJzc2nSpAmLFi2iRYsWtGjRgvv371dbvdMERUVFbNy4EbVazddff425ublY7agqCBYSDO+88444DoEWmJ6ezqlTp7h06RKWlpZ07NjxhXp0VSoVT5484ezZs9y4cQMzMzNatWrF0KFDa1X8Ua1WU1xczLp168jPz+fDDz8slzAR5uUFCxaIQmy1MS8ISsSC+I6FhUWV2xWq8adPn+bTTz8t839paWlcuHCBL7/8ssw2hIVrdnY2K1euZPLkyeJ34ubmxvjx41m6dCkTJ06stG8vMzMTMzMzUlNTsbW1LXfuBcq9n58f9vb2XLx4kXv37rFu3Tr69u0rPmOqO2cSiQRTU1MGDx5M69at2bx5M8eOHWPYsGHi2Gp63nV1dfH09OTOnTuiinSrVq1qtB1ra2tMTExITExEpVKJzyMbGxsKCgrE/vfSkEql6Onpoaenh4WFBQEBAeJ1nZWVxePHj4mOjubChQvk5ORgZGSEs7Mzvr6+uLi4YGdnV4YdUNF4GzduzLp16+jatSseHh7s3LmzzPgqg5WVFUqlkoKCgio9kIX2IV1dXRo3bkxISAgqlYqCggIePnzInTt3OHnyJEVFRdjZ2eHv70/9+vVxdHR8Jb3SrxIGBgbo6Ohgb2+Pnp6eeO6KiopeqrDp3xF6enoMHjyYjRs38sUXX1SZqHJ2dsbY2JjIyEj8/f1FyvTZs2erFWJ8Frq6um+o0bwJhMuguLi4WpGjrKwsDA0NX0oP6JkzZwgJCXnhILuoqIjVq1czfPjwf0xWTVg4LVy4sBz1TMiuq1QqjI2Nyyz4BSqqSqXCwsKi1gNhtVrN3bt38fb2JiIiQqxQvywYGxujo6ODiYkJjx49qvZ61dbWpkOHDuzfv5/Ro0fz119/kZKS8ty2QQKNdtq0aSxatIiioiKRwVBZtS8oKAhjY2OWLFnCyJEjq/XdfF5IJBJ0dHRo164djRo1YtOmTXz99deMHDkSDw8Pjb57YQHaqlUr/P39+f3337l48SKjR4/GxcVF43ELPZ9Hjx7lxIkTBAYG8vHHH5fpASoqKiI+Ph57e3uNWyGEhV9SUhIHDx7k/v376Onp0ahRIz7//HNxsXT27Fns7e3ZunUr48ePr9SaSGBMzJ8/n+7du9OyZctK+7+FwKJly5a0bNlSrGpcuHCBHTt2YGxsjKenJ5cuXSIgIIDPP/+8xt6mQhB15swZDh48SP369dmwYQOWlpbEx8dz6tQpvv32W+zt7enQoQP169evMjAUKnUzZ85k/vz5rF27lk2bNtGxY0c2b95Mbm5ujWzFKhuzUqkUg1ih4nr37l1CQ0MrXBQrFAoOHz7MiRMnmDFjBo6OjgCid/TBgwdJT08nJCSE8PBwbG1txeOpybiEIOHixYucP38eiUQi+kQLYnu1eS8KyRmBWTB58uRySSRB5HDJkiWMHj1ao55aTRETEyMmSISAqbrx7tq1izZt2pSxcVKpVOzcuZOOHTtWeH1IJBJ69+7NunXrWLt2LWPGjBFFlTw8PMRgeMqUKRXS8iMjI/H09OTBgwdVCqhJJE+VdM3NzWnUqBE2NjbMnj2bsLAwOnXqpDElXiKR4ODgwNSpU7l79y5r1qzB1dWVAQMGVJssqGhbwcHBHDx4kAkTJrBhwwYKCgpq1M6lr6+PqakpqampopcpgJ2dHfn5+aJ/eXXjkEgkSKVSbGxssLa2Fqu3JSUlpKSkEB8fz927dzl48CCFhYWYmZnh4eGBp6cndevWFfsshW05OTkhk8lE0U0dHR2RKl0VLCwsRA9chUKh8XmQSJ6KipmamhIYGEhgYCDwtGUjPj6eW7du8euvvyKTyXB0dCQwMBAfHx/Rsum/OSjW1tbGxcWFwsJC8XvMzs4mMzOT7Ozs1z28VwqJREL9+vVxcHDgxIkTdOzYscrvtkuXLhw6dAhfX1+0tLQIDAxk3759yGSyGrGb9PT0RF/4/2W8CYT/A2EBVl0QmpiYiJ2dXa0HVEqlkkuXLvHee++90OQmPMC9vb1rnB36u0KtVpOYmMiiRYsYNmxYuYVTXl4eBgYGYoBX+rtRKpWUlJSQlpaGs7PzSxnb9evXad++PXv37qVv3761vo/SkEqlWFlZoaenR0xMDEFBQdVWxZo0acKePXvIz8+ndevWHDx48IU8qoUqw9SpU1m+fDm///47gwcPrtJf1svLi/DwcJYuXUp+fj5hYWEvTbxNoKpNmDCBO3fu8Ntvv+Hj40Pfvn01psuV3saNGzfEimv37t2rXHwK88j58+fZv38/vr6+zJo1q8Ieablcjlwu17hvr6SkhIcPH7Jv3z6ysrJo06YN/fv359dff6Vt27ZiwFVUVMSBAwdQqVQMHDiw0qqUWq0mLi6OJUuW8NZbb2ksJCd8xtjYmMDAQAICAsTq2M6dOzE3Nyc6Opo9e/YQEhKCg4ODRv1vcrmc69evs2PHDpydnfnggw/KJGzc3Nxwc3MTBQWPHDnCxo0bCQoKomXLluUqPqXHK1Td58yZQ0lJCceOHePw4cPo6em98CIgMzOTtWvXoq2tXcZe58qVK4wYMaLMmFQqFSUlJWzevJnk5GQ++ugjTE1Nyc7O5vz585w+fRoLCws6duxI/fr1a9w3KATieXl53Lx5kzNnzpCbm0tAQADjxo2jTp06L6X3Xdh3cnIyixcvpnnz5nTp0qXcvoTE4W+//cb48eM1soaqyf7j4uIwNTUV2TlVKesLz5WIiAg+++yzMpTouLg4YmJiRHXWZyEkzIYOHcqKFSvYvn07b731lhhQeXl58a9//YulS5eW6xEX7LSaN2/O4cOH6dWrV5XHVVBQgEqlwsbGhp49exIWFsaePXv48ssv6d69O6GhoRrRaIWx+fn58dlnn3Hs2DG+/fZbsTe7Jgl4FxcXUlJSxHkyMTERLy8vjf9eInlqr5aUlFSmxUe43gWGVU2C69LHr6enh4uLCy4uLrRo0QKVSkVeXh6ZmZk8ePCAS5cusX37dlQqFfb29nh5eeHt7Y2trS3e3t7cunWL9u3b4+HhwYMHD6oNhHV0dNDV1UUmk4lzQE1RevxmZmaYmZnh5+cnitjFxcVx8+ZNjh49ilwux93dHX9/f7y9vTExMal1AbGXDeE+iYqKwszMDFNTU7Gqnp+f/7qH98pRWjgrJCSk0iKHcA9v3bpVZGWZmZlhYWFBbGxsjejRAkvyf93/+k0gXApFRUWVerPC//c0PW81rSo8ePAAY2PjF6aDREVFcefOHT7++ON/jEp0YmIiCxYsYNCgQRVWE9PT07G2tubRo0fl+nNzc3PR1dUlKyurVhddAkpKSkhMTMTS0pKMjIyXZs8kQCKRULduXRITE4mOjq6WHgpPKUghISGcOXOGtm3b8s0335CTk4O5ufkLjcXY2JhJkyaxatUq1qxZw8iRIytdTEkkT9VVp0+fzqJFi8jNzaVr164vlbYvlUrx9/fHw8ND7JEbMGAAjRo10jgY0NLSIigoCC8vL/766y++/fZbhgwZgq+vb7n7Sy6Xc+PGDXbu3ClWX+zt7Su9D5OTkzExMalSJEuoLN+8eZODBw+io6ND165d8fX1RU9Pj4SEBDIyMkQLE7VazZUrV7h58yajR4+mefPmlQbBsbGxLFmyhBEjRjx3VU6tVpOQkMBvv/2Gk5MTq1atQldXl4yMDK5fv87vv/9OXl4e9erVo3Hjxri7u2NqalpmX0qlkujoaLZu3Yq+vj7jxo0rp/xeGoaGhgQHBxMYGEhWVhYXLlxg2bJlGBoa0qZNGxo2bFgu4REVFcXChQvFRWpBQQHz589n7NixxMbGipWY0scll8spLi6mpKRE9LXU0tJCR0dHtLJRq9Xs2LGD+Ph4cdtBQUHMnj2b1q1bl7Ery8zMZOXKleTk5ODp6cmkSZNITU1l8+bNPHz4kMDAQKZMmSImWmsaAOfm5hIREcHZs2dJSkrC29ub/v374+rq+tL7DdVqNZGRkaxcubJSz2mhl33z5s3VCog9D5RKJQ8ePMDR0VH8zqrS8lCr1WzdulVUmy+9nW3bttG7d+9q7eaE63X+/PkcOnRI1E0QKjxjxowRbbUERolcLichIQFHR0cyMjLKaFpUBIEqLFzTlpaWDB8+nOTkZP744w+OHz/OwIEDqV+/vkbzqUTytG+1W7duNGnShK1bt3Lu3DmGDRumMXPG1NRUdGkIDAzk+vXr1VqDPTsGGxsbHj58WCbgFQJKwdu7NkRD4emzQAgu3d3d6dChg9irm5CQQGRkJNu2bSMzM5PMzEwUCgVGRkai20J11G+JRIKRkRFqtZqMjIxatU+USqVYWlpiaWlJQEAACoWCvLw8oqOjuX37Nnv27BGZCIGBgbi5uWFmZvZf0RLn4eHBiRMn8PX1JSIiAm1tbbS0tCgoKHjdQ3stsLa2pnXr1uzYsYO33367SkHSsLAwTpw4wZAhQwAIDQ3l4sWLNSqACc+FN4HwG4goLi6u9sEXFxdHWFhYre5XEMlq06Zij1ZNUVBQwIYNGxg5cmSVAf1/ExITE5k/fz6DBg0iODi4whtcsEy6f/9+OWGL1NRULCwsSE9Pp02bNrU+vtjYWKysrMjOzhYFLl4mhEA4IiJCpHxrcs20b9+en376iU6dOtGoUSNOnjxJr169XnghamhoyPjx41m9ejW//PILY8eOrfQekkieqk/PmDGDJUuWkJOTw8CBA19YmbYqCAuUAQMGEBoaypo1azh79ixDhw7FxsZG4wqoiYkJw4cPJzo6mvXr1+Pm5sbAgQPFLHZERAR//PEHenp6jBkzBldX12oXIg8ePECpVFYoriZU9c6cOcOpU6dwdHRkxIgR4nYFGu7+/ftp06aNeN0plUrWrFlDo0aNGDhwYIVjENoMFi9ezNtvv/3cPbJKpZJTp06xe/duBg8eTHBwsLg/BwcH7O3t6dy5M/n5+dy5c4cTJ06wceNGbGxsCA4OpkGDBqjVav7880+Sk5MZOHBgGVXp6qClpYW1tTXdu3enc+fOxMTEcOTIEf766y/8/Pxo27at6Pfu6enJli1b2LhxI7t27SI+Pp5z586Jglo9e/YkNzeXR48ecffuXRISEsjKykKpVIp+i8IxCz2AFhYWmJmZsWPHDjIyMnB1dSU9PZ3Zs2fTuXPnMhXA1NRUPvjgA5GqXrduXebNmycqsI8YMaLGys9CkiQyMpLTp08TFxeHm5sb7du3x8vL65Wp0KrVai5cuMCff/7JhAkTKmQgqNVqzp8/z44dO5g6depLEc4rLi4mOTkZBwcHCgoK0NHRqbI1KCIiguzs7DJMCEHkTSaTVcu2EWBkZMTkyZP5/vvvMTMzIzQ0VKy+NmjQgJEjR7Jo0SI++OAD6tSpg0wmE5kj2traFdrzlEZaWho6OjplgiupVIqDgwOTJk0iKiqKTZs2YWVlxaBBg7Czs9N4XrOxsWH8+PHcvXuXX3/9VWTOVMdSEVperl27Rrt27fj5559RKBQ1mstdXFw4fvw4KSkpYuVeS0sLAwMDCgsLycnJwcnJSePt1QQSyf/36lpYWNCgQQNUKhUKhYKkpCQ++ugjLl++THx8PBcuXKCoqEj0BXZwcCiXzBPaRmQyGWlpaXh6er60cQvXQtOmTWnSpAkKhYKcnBzu37/P2bNn2bx5M8bGxjRo0ICAgACcnJyqXde+LlhYWFBQUICLiwtpaWk8evQIqVTKyZMnKS4uxtDQEBsbG6ysrLC1ta2xANp/GyQSCR06dODrr7/m0aNHeHh4VPq55s2b8/3339OnTx8MDQ0JDAzk4MGDGsUxAoyMjFAoFBQXF9fmYfzX4U0g/B8I/pRVXUCCoJXQr1VbyMvL4+HDh4wYMeK5t6FSqdi3bx8+Pj41Ntb+O0KtVpOSksL8+fMZMGBApWIqQpU+ICCAc+fOlVksCAtQCwsLoqKial3pW61Wc+PGDRo2bMitW7fKVZVeFlxcXMjNzUUikZCRkVGt7Y5E8tR4vU6dOty8eZMOHTrw008/0blz51p5QOro6DBmzBg2btzIsmXLGD9+fKW9oUJQ+cEHH7By5UpWrVrF6NGjX3rFSqhIf/TRR5w8eZLvv/+eLl26iJRiTfYtlUrx8vLi008/Ze/evXz55Zd07tyZW7dukZ+fz4ABA/Dx8dGomidct3l5eWWUqQXhqkOHDnH58mX8/f2ZOnWqqIBdervC4mfQoEHi+7du3SIlJYXZs2dX+N0KdND58+drZPNS2dhzc3NZu3YthYWFfPzxxxX2IAv9b2ZmZjRv3pzmzZtTXFzMw4cPOX36ND/88ANyuZyGDRsyfvx46tWr91yJQGFx6OXlhZeXF7m5uZw/f56ff/4ZPT09OnbsSFBQkLhwDA8PZ8eOHWzYsIHdu3fj4eHBl19+SUlJCU5OTvj5+REaGoqtrW2FqtiCuE1qaipxcXG0bt0aeLqoEFSdnz3fkyZNYvfu3ahUKrZv3467uztDhw6lbt26Gld/hZ5JuVxOdHQ0p06d4uHDh9jb29OqVSvGjh0rJkBf1fyvVCo5cOAAZ8+eZfr06RUGYUKi99ChQ0ybNq3WPG2fhUwmIy8vDy8vL/Ly8tDR0ak0ISyXy9m6dWu5RJxCoWDLli0MHTq0RkGdmZkZ4eHh/PDDDxgbG4v3lUQiwd/fn2HDhjFv3jxmzJhBWloaDg4OZGVlabSWSE1NFZOIpSHcX/Xr1+fTTz/l9OnT/PjjjzRr1oxu3bppnFgR7NG++OIL9uzZw7///W8x8VzV/digQQNOnDhBv379KCkpIS8vT+NKqETyVCFapVKRmppKgwYNxLEIVoevsk9UOJdaWlq4uLjQuHFj2rdvT/369fnkk09o0qQJubm5YtLLwMAAd3d3/Pz8cHd3x8LCAnt7ex49ekRGRoZGTK3aGreOjg7W1taEhYURFhaGQqHgyZMn3L59W2TkODo6EhwcjI+PjzhXv841oqCrEBMTQ2RkJLdv30ZfX5/Hjx9jbGyMXC7H1NSUgoICbty4QXp6Ojk5OVhYWNCqVSuCg4P/sT7M+vr6vPXWW2zatImZM2dWOg+Zm5vj6urKzZs3CQ0NxdTUFCMjIxITE6lbt65G+zIxMaGkpORNIPy6B/B3QnU9wiqVisLCwloXoLp16xYeHh7PvV2B5nj9+vV/BCW6tLdkv379quxdVKlUpKSkiAIBz9J9ExMTsbGxITIystYFztRqNXfu3GHMmDGsXr2a8ePHv5KJWThWa2tr4uLiNFpYSqVSunbtyubNmwkJCcHFxYXLly/TsmXLFx6P8DAePnw4f/zxBwsXLmTSpEmVVjoEat6ECRP4/fffWbhwIRMmTHjpXtfCONu3b09AQAC///4758+fZ9SoUbi4uGgspqWnp0f79u2Jjo7mxx9/xNvbmy+//FLjCrOAvLy8MgvC9PR09u/fz+3bt2nWrBmfffaZqH77LNRqNSdPniQoKEg8zzKZjOXLab8QNAABAABJREFUlxMeHl5hckStVpOWlsaCBQsYPnz4c9Gh1Wo1UVFR/Prrr7Rq1YrOnTtrFDAIFWwdHR0UCgWxsbEMHDiQsLAwHjx4wB9//EFeXh4eHh6EhITg7e2NgYFBjSjCwufMzMzo0qULHTp04OHDhxw6dIi//vqLkJAQ2rZti4uLCxMmTKBOnTr89ttvhIWF0b17dzw8PDRaXJWmWXp6etK+fXumTp1KVFQUhw4d4scff6Rr1640a9aMJ0+e8O6773Ls2DExkM3MzMTLy0vjhKVQPXz06BHnzp0jIiICa2trWrRowdChQ8tVp14VSkpK2LJlC/Hx8cycObNCazqlUsnBgwc5f/58Gd/dl4GEhARkMpkoXKRUKitNBl25cgVDQ8My4oZCZdvCwkJUOtcUQnV1ypQpLFq0iEmTJokiWRKJhEaNGqFUKpkzZw716tXDw8ODyMhIjazscnJy0NLSqnR9IFQ327VrR0hICDt37uSrr76iX79+GvuhC3OyoBWwbt06zp8/z7Bhw8oI/JWGnZ0dKpWKnJwc6tWrx71792jRooXG501Qy05NTS1joWRtbS1W619VQFkaUqmUwMBAbty4ga+vL97e3ujo6Ig+4cXFxaSmphITE8Ply5f566+/UKlUZGRkkJGRwePHjykuLhaZJK9q/MJ+dHR0cHd3x93dvQzT5erVqxw4cECk7QcGBlK3bl1xnn1VENw/1q5di5aWFiEhIRgbGxMbG0t+fj4uLi64u7vTqVOnMueuqKiIR48ecfToUXbv3i360v+3r3efhUTy1Kv72LFjXLp0qdL2JqlUSocOHdi6dStNmjRBKpUSEhLCxYsXNW47MTIyori4+I1Y1usewN8FgsJmVbS83NxctLW1X9hzsjQUCgWnTp2iX79+z70NuVzO+vXrGTRo0H+9SnTpxXrPnj1FmlllKC4uFnuoLCwsyn1/CQkJNG3aFAMDg1oXicnKykIul2NgYCB6Vr4K6OnpYWlpiYmJCdHR0dX6HApwd3dHpVIRGxtL9+7dWbNmDU2bNq21BIG2tjYDBgxg7969zJkzh/fee69StWJ4Kt0/fPhw9u/fz08//cTkyZNfWrWoNIRF6+TJk7lx4wbLli3TWAhLJpNx6tQpjhw5QosWLRg3bhwXL17kxx9/FJM2mlxnAgXPzs6OoqIiVq1axcOHD2ndujWff/55tUmBoqIizp07R3h4OPA0IbR582ZUKlWFrRuCevrixYvp3bv3cyl3y+VyDh8+zKlTpxg7dmyNegKF5NaWLVvIzs5mzJgxYj9i/fr16dq1K9nZ2URFRXHu3Dm2bNmCtbU1gYGBNGzYEAsLixpXALS1tfH29sbT05OMjAzOnj3L3LlzMTU1pbCwECcnJ1avXl0r4of6+vo0bNgQPz8/EhMT+fPPP9mzZw+nT5/m/v37mJubo62tjZGREVZWVsTFxVW5yFer1aJf6rlz54iMjMTa2pqmTZvSp0+fl6KAXxMUFBTw66+/oq2tzQcffFBh5VXwEb579y7Tp09/KR7upREXFwc8/d61tbUxMDCocG4rLCxk165d5RKXhYWF7N69mylTpjxXf6VEIsHV1ZVx48axbNkywsPDRZEliURCSEgISqVSFA08cuRIte0pAvtCk3WHRPJU0X/EiBHExcWxZcsWjh49ypAhQ3Bzc9M40efq6srMmTM5ceIE3333HT179qR58+blmDNSqVR0SwgKCuLMmTOVLtorgp2dHQYGBiQkJJR538rKCm1tbZKTkzXazsuAr68vx44dQ6VS4efnx7Vr18QgX09PD2dnZ5ydnWnVqpVITT5z5gw///wzf/31F3FxcVhZWeHl5YWvry8ODg4YGRmJbS2vCsI1IShSl5SUkJGRIfoXJyYmYmtrS3BwMH5+flhYWLxUNWq1Ws2tW7dYv349gwcPJjAwkNu3b7N37160tLTEQlNFYln6+vr4+Pjg7e1NTEwMq1evplWrVnTs2PEfFwxra2szaNAgFi9eTEBAQKW98u7u7pSUlJCQkICzszNBQUEsXLiQt956S6MEtb6+Pkql8k0g/LoH8HdCdf2Wqampomx9bUHwDn5ef1W1Ws2hQ4ewt7evFT/M14309HTmzZtH9+7dadasWbXHU1xcjJaWlkg3exa5ubnk5+djZ2dX6+IRERERuLu78/jxY9zd3V9qr2tpCIuVnJwcYmJiNP47wUrpwIEDTJgwAR0dHdGLrragpaVFjx49MDU15aeffmLKlClV9gNqa2vTvXt3LCwsmDNnDhMmTKh1EZ2qxioIYW3fvp1vv/2WoUOHivTm0lAoFNy8eZPt27eLdjyCEnTXrl0JCAhg3bp1XLx4kWHDhlVbHVYoFERFRZGZmcnPP/9M586dGTZsmMZ0xhs3bmBvb4+tra3ITFixYgU//fRThfOTTCZj2bJltGjRokaLVShLhVYqlcyaNavSSnVFKCoq4siRIxw/fpxu3boRFhZWLqjV0tLCysqKZs2a0bRpU2QyGfHx8Vy9epXFixcD4O3tTXBwMM7OzhUmCgTbIkFwRYBgr9K7d2/MzMzYtGkTEydOxN/fv9bnBKlUipOTE5MnT+by5ctEREQwatQo2rVrh7m5OXp6emhpaVXYCiAEv0Ll98GDB1hbWxMaGkr//v0xNTV97QI4gojR0qVL8fT0pF+/fhVeb3K5nG3btvHkyRPCw8NfeoJWrVbz+PFjkepnbm5eYeJErVZz6tQp6tati7Ozc5lq8NGjR6lfv/4L9aUK1bYhQ4awcOFCZsyYIbbkSCRPbYc8PDxYtWoVQLX7UqlU5Ofno6Ojo3ECXng+hIeHc/PmTVauXImPjw99+vTRmD2gq6tLx44dadiwIevXrxcV0J+d14KDgzl06BBjxoxh06ZNKBQKjROrBgYGGBsbk5ycXKYIYWdnh1wuJzMzU6PtvAwIFO/MzEw8PT3ZsWMHJSUl5RiDpanJTZs25ejRoxgaGvLxxx+TlpZGREQEu3fvJi0tDWNjY+rVq0fDhg1Fpd9XfT/r6uri4OCAg4MDbdu2RSaTERsby5UrV0QV/cDAQIKDg7G3t6/1Nc2TJ0/YtGkTH3zwAY6OjkgkEhwdHcnLy8PNzY3ExESys7PJy8urdBtSqRQPDw8+/PBDFi1ahJWVVaX6Mf/NcHJyolGjRuzZs6dM+1Np6Ojo0KpVK44cOcLo0aOxtLRER0eHlJQUjeYxQZiuJpZf/0S8CYT/A8F2orpAuDYrVmq1mnPnzmlcRaro75OSkjh58iSffPLJa18kvQgEtcW5c+eKi2VNznNWVhampqbExsaWs2+Qy+UUFRWV68OsrfFeuXKFsLAwrly5QmBg4CulQHl4eHD8+HGys7ORy+UaLT4Eit6uXbvIzs6mZ8+eHDhwQPSiqy1IpVJat26NiYkJ8+bNK0MTrOzzLVq0wNzcnEWLFvH2228TEBDwynqsTExMGDFiBNHR0axbtw43NzcGDRok+ocmJSWxceNGioqKGDNmjBioC+OTSCTUqVOH6dOnc+rUKb7//nt69uxJy5Yty1QABGpsfHw8W7du5ebNm/Ts2ZOvvvqqRsJGcrmcI0eOMHDgQOApxXrRokV4e3tX2EagUChYvXo1devWrXH2XK1W8+jRI1auXEmLFi3o2rWrRnOVcKyPHj1izZo1ODo68umnn5bxaq0MUqkUIyMj6tevj7e3N0qlkqysLG7fvs2+fftISUnB1taWoKAgGjRoIPalqlQqFi9eTGFhIZMnTy7jjyrQXo8cOcI333xTYxp7TaGlpUXTpk1ZuXIlixYtoqCgoBzdVnjmFBQUEBUVxYULF3j06JFIex48eLAoDvN3WOQJ9kgLFy6kffv2tGvXrsJ5o6SkhPXr15Obm8uUKVNeiWiXUqnk8ePHmJubk5+fj6WlZbk2GSGhc/ToUWbOnFlmTFlZWZw8eZJPP/30hccqBLwFBQViMCwEoGlpabi7u4tCN4IgUGX7LC4uJi8vD0NDwxoz0bS1tQkKCsLHx4f9+/fz9ddf06dPH0JDQzWqTEokEuzs7Jg6dSpnzpzhu+++o0+fPrRo0UL8+3r16rFu3TqxXSAuLo569eppND5BGEuwhxKuJSsrK4qKil6rcrCOjg6enp7cvXtXXIvk5uZWqTNiYmIi2jUaGhqKFPhu3bohl8tJSUkhMjKSQ4cOkZycjL6+PnXr1qVhw4a4urqWma9exf0uzLO+vr74+PigUChITk7m8uXL/Pzzz6jVagIDAwkNDRWT2S8yLrlczp9//snIkSNF3/T8/HxSU1OJjIwkLi6OgoICbt++TWJiIrGxsYwfP562bduW25ZQ6f7Xv/7F/PnzRQupfxIkEom4PmjZsmWFFl4SiYTGjRuLPtmCaNbly5c1EiTU1dUVReL+l/EmEC6FqirCQsa5Nu1xSkpKuHz5Mh988MFzTTAKhYJ169bx1ltvvXTa2cuEWq0mMzOTefPm0aVLF1q2bKnx+Xjy5Al16tThyZMntGrVqsz/ZWVloaOjQ3Z2No0aNarVMRcXF/PkyRNcXFzYunUrAwYMqNXtVwdnZ2dyc3PR09MjLS2tWp9DAYaGhjRt2pRjx47Ru3dvtm7dSkJCAi4uLrU6PonkqaqooaEhS5YsYcyYMVUyFiSSpwqr06ZNY+HChWRnZ9OqVatXRnkShLA+++wz9u3bx1dffUWfPn1ITEzk0qVL9O3bt9oFpI6ODu3atcPf359169Zx6dIlRo8ejY2NjSiatH37dpGub2VlhZ+fX40CBUEPQKlU4uHhgVqtZvPmzeTm5jJq1KhyFQuVSsWOHTtQKBT079+/RgkPlUrFiRMn2LdvH2PGjNHYn1AQHty1axdXr15l6NChNGzY8LmFsLS1tbGxsaFt27a0bdtW7BW7cuUKx48fR6VS4ePjg4+PD5s3b+bGjRucOHGCb7/9lsaNG6OlpUV8fDx79uwhPDy80p7H2oZEIsHe3p7333+fJUuW4OjoiJ2dnUhTv337NhcuXCA1NRVHR0eaNWvG8OHDxQXd3yH4FaBWq4mOjmb58uUMHTq0UvFCgeavpaXFxIkTX5mgjVKpJCcnBwMDA7KzszE1Na2wIrJ3716aNWtWxtdbpVKxZ88eWrZs+cKWcgIkEgmtWrUiPz+fJUuWiPTxmJgY3N3dsbOzw83NjXnz5vHhhx9W2gpRVFREUVERZmZmzyVsKJFIMDQ0pF+/fjRr1owNGzZw8uRJRo4ciZOTk0bBsI6ODm3atKFBgwasXr2aK1euMHr0aCwsLNDT08PGxobExET8/f25efOmxuw2bW1tbG1tiY6OFtXZAZE1UVhYWOPjrS0Iz68jR47QunVrXF1diYmJqTIQ1tbWRk9Pj5KSEuRyuejrK9CpXVxccHZ2pkOHDiiVSpKTk3nw4AFnzpxhy5YtaGlpid7Anp6emJubi3Pmq2gX0tHRwdnZGScnJ/r06VMuKG7SpEmZe6emY4qPj6e4uFi091EqlSxbtowffvihTPW/pKSE7Oxs4uPjee+99yrdntAOV69ePS5dukS7du3+VnNmbcDIyIhevXqxdetW3nvvvQqf34Il2PXr1wkLCyMkJISff/6Z3r17axQIC1aB/8t4Ewj/B5pUhJOSkggNDa21/cXExGBqavpcnnNCNVlPT6/SRcl/AwSV3AULFtC+fXtat25do6AgMTERKysrbt++XU4gKCsrCzMzM1JSUjQOFDVFQkICxsbGFBcXY2Bg8MqzkSYmJhQXF+Po6EhCQoLGxycs0H744Qd69OhBhw4dOHjwIO+8806tB50CTfD9999n8eLF9O/fn9DQ0Er3I5FIcHJyYtasWSxevJjMzEx69er1yvqqJBIJ+vr64j4/+eQTbGxs+PHHH6usaD+7DVtb2zJVlJYtW5KYmEhCQgJdunTh3Xff5cGDB+jq6pahZ2oCtVrNgQMH6NSpE1paWly7do2oqCjs7OzKJZDUajVnz57lzp07zJgxo0Y0N5lMJiZJZs2aVWWvd2moVCoiIyNZv3493t7efPbZZ7VmeSFsw8DAAF9fX3x9fVEoFKSlpXH//n22bNnC3bt3USqVHD9+nD59+jBt2jRGjx7Nn3/+yfDhwysNgouLi0XlTG1tbfT19UUf4dLvSaVSZDJZuYWDlpZWhZU9oarWv39/1q9fj4+PD9euXaOgoIC6desSFBREXFwcZmZmNGvW7IXP0cuASqXiypUrbN68mQkTJlTYGy7QulesWCH63L6qVhGA7OxscnNz8fb2pri4GJlMVkaRWXAhuH79Op999lkZpkBSUhJ37tzhiy++qNV5RiKR0KVLF/Lz8/n555+ZOHEid+/eJTAwkKioKIYMGYJSqWTevHlMmzatwmeIIPr1ooJGAgU1PDycK1eusGjRIkJDQ+natWulCv/P/r2trS3h4eEcP36cb7/9lsGDB9OoUSMaNWok9tCuXr1aY70TieSpkv/ly5fJzs7G3t4e+P9AuLi4uMaWTLUJJycnkpOTUSgUeHt7ExkZWaVwp1DhFtY0FVXwhb/V1tbGyckJJycnWrduLc5jjx494saNG+zatQuAevXqiYGxkZHRS+3fLT1G4Xrp3bs33bt3JykpiQsXLrBgwQKMjIxo2bIlgYGBGBsba3xdCg4bwvi1tLTo0qWL+Kx/FvXq1SvH8iuNhw8f8vbbb2Nubo6xsTEymUykdP+3roefhUQiITQ0lCNHjhAREVFG3K/0ZwTRrGbNmonJ1tTUVPGeqgxvKsJP8SYQLoXqeoQF+fbawokTJ2jVqtVz0aKzsrLYt28f4eHh/9VCAdnZ2SxYsIDWrVvTtm3bGgcFCQkJuLq6ijSf0khLS8PKyoqHDx/Weo/ajRs3RKGH+vXr17oQV3UwMDDA3Nwcc3NzIiIiyli2VAdra2vc3d25fPkyTZo0Yf/+/WRlZb0URVehX23GjBksWrSI3NxcOnbsWGllUiJ5avU0ffp0fvnlF1avXs3IkSNfuj8z/H9iZdOmTRQXF7Nq1SpiY2NZtmwZ3bp1o2XLlhr3v2lpaeHt7Y2trS2//fYb1tbWfPHFF7i5uSGRSETrpIr62qtCRkYGT548YcyYMeTm5rJ582bc3NxE8bTSx/LgwQN2797NjBkzNL7+hRaFlStXUqdOHcLDwzWqRAkU3+3btxMREcHIkSPx8vJ66XOTtra26FkcGxtbJkBNSUnh008/ZdeuXXTr1g1vb+9K55d79+7x5Zdf4u7uTkhICLq6uri6uvLvf/8bHx8fAgMD0dbW5q233uKnn37C1NSUhw8fkpycTNu2bbl79y6LFy+ucPsSiQQ/Pz82bdqErq4uPXr0ICEhgQMHDvDTTz8RHx/PoEGD6N+//0s7T88LpVLJ0aNHOXHiBNOmTRP7+kpD8LxeunQpHh4elfYNv0wkJCSIldOioiJyc3PLsKTUajXbtm2jc+fOZe4TlUrFH3/8IQrl1Ta0tLTo168f69evZ82aNTx69Iju3btz7NgxBg8ejIuLC3K5nMWLF/Pee++VE8WRyWSoVKpKxXJqCm1tbZo2bYqvry9//fUX33zzjaiLoAlbREdHh44dO+Lj48Pq1au5fv06bdu25eTJk/Tu3ZuioiKysrI0Su4LSaLCwkLS09PLBMJmZmakp6dTUFBQa1X6msLc3BxDQ0OSkpLw9PTk+PHjKJXKSq9tLS0tLC0tycvLIzMzs0bJaR0dHRwdHXF0dKR58+bI5XJRPPDKlSv8+eef6Orq4unpSUBAAM7Ozq9MM0BbW1usFPfs2ZO4uDjRP97Dw4O2bdvi5uZWLfsjOTm5nO5LgwYNmDx5Mp988glKpbLM55s0aVKlAKm+vj6JiYmcPXsWgD179jB//nzGjh37gkf894IgnLVt2zZmzZpV4VrIw8MDmUxGYmIizs7O1K9fn1u3blXrKf6mIvwUbwLh/6C6inB+fj5yubzWKMgFBQXExMQwbNiwGv+t4EXZunXrV6Ky+7KQnZ3NvHnzCAsLo127djVeNAu9g7q6uhWKgMTGxuLg4EB0dHStGsorlUru3LnDyJEj2bx5M/369Xvl34EgyqNSqapVoH0WQqVi7dq1NGvWjCZNmnD8+HH69+//Uo5DWPDMmDGDJUuWkJubS9++fSvN9At9uxMnTixnr/SyUFRUxMGDBzl9+jS9e/cmNDRU7BMLDAxk/fr1XLx4kVGjRlUYDAgQqgH79u3j5s2bdOrUicmTJ3Pt2jWWLFlC9+7dadmyJSkpKRQWFtYoEFar1Rw7dowmTZqgp6fH77//TnBwMFevXmXAgAHleh5XrVrFmDFjNFYzF4LnVatW0aVLF42p6YKl0tq1a2nYsCGffvqpRlWm2kZxcTHdu3fHzs4Oc3NzsU/04sWLNG7cuMrxBAYG4urqSosWLejWrRuDBw9m9erVODk50apVK9q2bcuwYcPo3Lkz3bp1o1GjRmzevJnr168zfvx4Ll++XOX2dXR0aNu2LUuXLmX9+vXcv3+/DPUzMjKSpUuXir8rFAqN72mJRFJOHKz076UZFcJnhd+lUqn40tLSKvOzjo4O9+/f59SpU4waNYrY2Fji4uLEBa/wr0qlYtWqVbi6uhIQEEBcXJy4ndL7q+q9qj5bHdRqNU+ePBHplra2tkRFRZV5VsfExJCUlMS4cePKVIMfPHhARkYGTZs2fWnXq46ODkOHDmXp0qVERERgbGxMdnY2NjY2orhgSUkJK1asYOLEiWUC8rS0NFFUqrYgkUgwNTUVdRE2bNiAs7MzAwcO1EgET6jkfvjhh+zZs4cVK1aQkpKCTCbD1dWV6OhomjZtqtFYhOA3IyNDfE9bWxtTU1MSEhJeayAskUjw8vIiMjKSFi1aUFRUJIrxVfZ5a2trYmJiXkjoS7i3bG1tsbW1pUWLFpSUlJCVlcW9e/c4duwYiYmJGBkZ4e3tTUBAAHXq1Hkl9oP6+vp4eXnh6ekpevxu27aNoqIiwsLCCA0NrdLy79nniZaWFu+88w47d+7k/PnzZfZVHbW3tHczQN26denevXstHe3fBxKJBG9vb0xNTbl8+XKFFmVaWlqEhYVx6tQphg4dSuPGjfnzzz/p2LFjldsWEvtvAuE3EFFVRTgrKwsjI6Naoemo1Wqxl6ami3u1Wk1kZCTx8fEMHz78vzIIFkRL5s2bR4sWLZ5b/l6pVKJQKEhJSamwx1VQ+TY1Na1VD+GcnBwKCgqwtrYmIyNDFH541fD29ubixYvk5OTU2N/a3d0dqVTKw4cPadu2Ld999x3dunV7KVUReDqZm5ubEx4ezi+//MJvv/3GqFGjqkxQ6OvrM2rUKHbv3s0PP/zAe++9V+siR0Lv47p163BxceGzzz4rk1SRSJ5aLb3//vtcvHiRefPm0bZtWzp16iT2gAnbkclkHDp0iNOnT9O8eXO++OILjIyMRDq6r68va9as4dKlS+Tn52NtbV2jKnxRURFXrlxh1qxZ3L9/n9jYWMLCwqhbt67YuyZkd3/55Rc6duxYZRW0NFQqFadPn2b37t2MGzdOIx9VQaV5165dXL58mbfffpv69eu/NobKuHHjGDt2rEjtk0gkYmKiOs9e4f+uXbuGgYGBSPuDp9VimUxGz549MTY2Jjg4uMzfSqVSjRgZ7u7umJiY4ODgIHp7CpQ0S0vLcmreQmBaHVQqVZlqilKpFMXK1Gp1hb8LP6tUKvHvhZ9VKhUymYw1a9bg7OxM//79yc/PJysrC5VKhVwuF72NMzMzOXz4MK1atUIul/PXX3+V2W7pV+mxlH6v9L0m/FuaPimcB+Hnil6nT5/myZMnXL58GTs7OxISEti/fz+6urro6uqyc+dOGjRowI0bN9DS0kJbWxupVMrq1asJCwsjISFB3JagOi7YMJV+73krcHp6erRr1469e/fyxx9/oK+vL859Wlpa9O3bl82bN7Ny5UomTJggVn1SU1NF1fPahqCL8Omnn4piWoMGDRJbraq7//X09Ojfvz8NGjTg448/5q+//hKFeqqiEJeGvb092trapKSklPESNjMzQ6FQvNY+YQB/f38OHTpE+/btsbS0JDExsVIxMIHNJJFISE9PrzUPZKHH2N7eHjs7O9q0aYNSqSQpKYl79+6xa9cu0tLSMDMzIyAgAH9/f5ycnMSA/WUlt42NjWnRogXNmjUjOTmZw4cP8/XXX+Pt7U3nzp3Fth9h/xYWFmRlZZU7L1ZWVnz66acMGjRItMJ0cHCgYcOG4rxV0XEYGhri4uLC+fPn0dPTY+rUqTg4OPxXromrg1QqZcCAASxatIigoKByiWaJREKzZs347rvv6Nu3L66urmRlZZVjxjwLYX4sKSl5FYfxt8WbQPg/kMvlVS48MjMzNe6T0wQnT56kT58+Nd5ecXExGzduZMSIEa+ELlrbEGh08+fPJzQ0lE6dOj33wrmgoECUivfw8Ci3n6ysLBQKRa0HTw8ePMDNzY24uDhsbW1rNVtfE9SpU4f09HRRIKYmgbBE8tT258CBA0yZMgUvLy8uXLhQY3p6TSCRPBVuESq9CxYsYNKkSVX2kGppadG7d2+srKz48ccfmThxYq3YK6nVavLz8/nzzz+JiIhg+PDhYv9NRdvW0tKiWbNm+Pj48PvvvzN79mzGjBmDi4sLJSUlnDlzhv379+Pn58cnn3xSRgFUOHZra2s++OADzpw5w4wZM7CyskIqlWq8YLpw4QIeHh7o6+vz+++/M3LkSNauXcu//vWvMvfQX3/9haWlpcbfZUlJCX/99RcREREa9wOr1Wri4+P59ddfcXJy4vPPPxeD/teBZ6uiAoTATdNEmImJCc7OzrRr106cX7W0tIiLi6Nnz56V9uhpctza2toEBgYyY8YMUlNTuXTpEjt37uTkyZNYW1sTEBDw2ttcSvf6dunShVGjRlWa/E1OTmbevHn88MMPGqv8VwSlUlkmEBd+Ft6v6PfS7ykUCjEANjAwoG7duigUCgwNDSkpKeHChQvk5eVhZGTE3bt3USgUIqsnNTWVmJgYHjx4IL4v/CsE6sJLpVIBlKuel/699L96enro6emhr6+Pnp4et27domHDhqxduxZfX1/Onz+Pjo6O+AoICGDLli0sWrSIwYMHo6+vz5MnTygqKsLc3Jzi4uIKkwZV/fvsz89CCLJ69+5NcHAwa9as4cKFCwwfPrzcHFbR3wLUr1+fL7/8ksmTJ9OyZUuysrIoLi7WiIVlaGiIsbEx8fHxZd43NTVFoVC8VuVoADc3N1JSUiguLsbDw4OoqKgqxcBsbGzQ0dEhMTHxpYxHeD5JpVJRfKtz586UlJQQHx/PzZs3Wb9+Pfn5+Tg5OREcHIyPj49Io67t+VmYdx0dHRk1ahQFBQVcunSJX375BSMjI3r06CG2jtWrV49r167RunVr4P+TcgUFBTg6OhIUFMT9+/fJyclBT0+P7du3Y2hoiIWFBVZWVtjZ2eHk5ISpqak4Dzdo0ACJREKLFi1eGqPt7wCJ5GnPtp+fHwcPHqRPnz7lPmNmZoajoyMRERE0atQIFxcXoqOjCQkJqXS7urq66OjoiFoY/6t4Ewj/BwLlpbKFSFxcXK0p66anp5OTk1MueKsOgmewu7t7hYIlf3cIQfDChQsJDg6mS5cuL7TwS0lJwcrKivT09HILscLCQpHKVF2fRE2gVqu5fv06QUFBYp/w6/oerKyskMlkuLi4EBcXVyNBMIlEQkBAANu3byc9PZ0uXbrw888/07Jly5cqTiLQvoYPH86+ffv44YcfmDJlSpUUf4lEQlhYGJaWlixdupShQ4fSqFGj5752BE/gLVu2EBISwueff65RJVwikWBhYcH48eO5fv06CxcuxN3dXVQPDw8PrzIjLZE8VUBu2bIlHh4eXL9+nZUrVzJq1Khqg0+FQsHRo0cZM2YMhw4dwtvbm8LCQszMzMR5Sa1Wc+PGDe7cucOsWbOqrV4JQc/q1asBmDFjRrXnQfAcPHHiBIcOHWLQoEEEBQW99gCuMkilUnGOqIq5IZPJRIElX19fdHR0KCwspLCwEHt7e7p168aGDRsoKSnB19dXZLUUFhYik8kwMDCodiyZmZmYmpoCT71Se/XqRffu3cWF9uuezwWP4CVLllC/fn369u1bIQ1USIIsWrSIAQMGaFz9qwxC5fV5IdjVODg4YGJigp+fH1ZWVnTt2pWioiIuX77MF198USaAkclkfPXVV8yYMQN3d/cKj7F0NfvZinlFvz8bsJeUlFBUVERxcTFFRUXExcWJStL37t1jx44dom2NXC5HLpdjZGQk9tiHhoZy5coVMjIykMvlHD58uEwgVJr5ILx0dHTQ09MTKz3Cq3TALbye/Yy+vj5Dhw7l3LlzzJw5k1GjRuHv71+Gpl5636Xfc3d3p3HjxjRr1ow5c+Zw7dq1KoURBQjJgqysrDLvW1lZidfj64SRkRFGRkakpqaKNlRdu3at9PP29vbIZDJycnJeyfiE61lPT4969epRr149+vbtS3Z2No8ePeLatWvs2bMHbW1tfH19CQwMxNnZGUNDw1qds4VxGBsb065dO8LCwrh79y579uxh69at9OzZE1dXV/744w9ycnJIS0vj0qVLREZGolQqsba25t133xVZUkLFs7i4mKysLDIyMoiKiiIlJQWVSiVeb66urhgZGTF9+nRxbv2nQiqV0qNHD2bPnk2rVq3KscmkUilt2rTh2LFjBAYG0rRpUy5dulSlx7IwFxQVFdUag+G/EW8C4f+gukA4KSmJoKCgWtnX5cuXadiwYY0rusnJyZw+fZpPPvnkb7vwrAr5+fksXLiQgIAAunXr9sLHkJycjIWFBZGRkeXU8fLz89HV1SUpKYmWLVu+0H5Ko7i4mJiYGAYOHMiePXvE7ObrgIGBAaamppiZmREVFUVoaGiNJjI9PT1atGjB8ePHGTBgACYmJqKq6cuGtrY2PXr0wMrKijlz5jBhwoQqK70SiQRfX18++OADlixZQlpaWpWiWxVBWFht2rSJjIwMJk6ciKura40nf6G6a2JiwpUrVzAwMKBdu3Yaq1UKIm+dO3fGz8+P7777jrfeeosmTZpUejzR0dHigvXChQvMnDmTpUuX0q9fP/E+Sk1NZePGjbz//vvVsgMEUaxly5bh6+tL7969NQpGsrOzWbt2LSqVilmzZr0yK6LnhUTyVKjq1q1b+Pv7VzrWqKgo/Pz8KCkpISMjA3t7eyIjIwkODiY/Px+lUsmgQYM4evQoderUobi4GJVKhbe3Nw8fPsTPz6/KcajVas6fP8+NGzfENhtjY2PxZWpqSkFBASYmJuUCFyFQ1ISu+rwQPIIXL15M27ZtK/UIFtwOli9fzvDhw1+Z33dVEBLLderUEed8V1dX0VnBwcGhjOq7Wq3m1KlTuLm5VWqHKFS6akuMqKCggEOHDjFs2DASEhIYP348mzdvplmzZuWUYIuLi/n555/FimpBQQHjx4/Hzc1NrFKXppaX/ldQOi8uLqakpITi4mIxyBZsfYqKisjLyxPfEz4n/FtcXIyenh4LFiwgMzOT+vXrY2ZmVoZeL5VKywXWUVFRWFlZ4ebmxsSJExkxYgQeHh5lKuOlXzo6OqhUKvT19UlKSiIjI0M85yYmJsjlcpKSklAoFGWC7lcNHx8f7t+/T5MmTUhPTy/jefwsjI2NRbbR64JUKsXS0hJLS0uCgoIoKSkhMzOT27dvs3fvXtGH3d/fH39/f2xsbGq1dQyeVhobNWqEv78/jx8/ZteuXfzxxx8kJiYya9Ys3NzcaNq0KR07dsTMzEwjmzWh7Sc/P5/o6GhOnDjB+fPnadSo0StZs/wdYGFhQbt27fjzzz8ZO3ZsuTW0l5cXmzZtIjs7Gx8fH/78809kMlmlCW6J5Gnfd3Fx8ZtA+A2qDoSFRWNtqOoqFAouXLjAO++8U6O/UyqVbN68mV69ev1Xegbn5+ezYMEC/P396d69+wsvMATbC0tLS9RqdbmkQl5eHiYmJhorWGoKQbykqKgIuVxerTz9y4RE8tRuSEdHh4cPH1b5gK7s71u2bMns2bPp2bMnPXv2ZOfOnfj5+b0S1VepVErz5s0xNzdnyZIljBw5ssqFtUQioU6dOsyaNYulS5eSlpbGoEGDNHqIK5VKrl69ypYtW2jXrh3vvPNOjT1OBb/rHTt2EBUVRb9+/QgMDCQ6Opq1a9fi5+dHv379qq2qlpSUkJubi5ubG506dcLf359ff/2Va9euMWzYsHJiIyqVigMHDtCxY0dxDsjIyKCkpIT69esDTxfPv/76K717967QP/XZ43j06BErVqygR48etGjRotrrRqVSce/ePdasWUP79u3p0KHDa7M10QRCxfb+/fucPXuWe/fu0atXr0qrBgEBAQQEBJR5T7CGKY3S4oaTJk3SeDzp6elkZ2fzww8/iIFIfn4++fn55OXl8fjxY65fvy4GKHK5XKToCoGGvr4+BgYGGBgYoK+vj6GhIWZmZpiZmWFkZCQGHLq6umWqgqV72SvDo0ePWLp0qVjhrew5GBkZycqVKxk7diw+Pj5/i4VTSkqKWFV1d3cnLS2Npk2bUlBQwP79+wkPDy8zztzcXA4fPszMmTNf2RgzMjLE1gGZTIaPjw8TJ05k8eLFTJo0qUzfqa6uLu+++y5Llizh6tWrNGjQABsbm5em31A6wBVe8LRd7NixYxw8eJCuXbuWqSwplcpywbOVlRUPHjygX79+KBQKUbBvwIAB6OnpiZ7IwkuhUKBSqUhMTCQuLo4ff/wRqVSKSqUiIyODu3fvsn79em7fvi32aZeuZJf+WU9PDwMDAwwNDTEyMhIDbeFvSv/77M9VUYaFBOzhw4dp3749WlpaZGRklLHmKg1hXEVFRVUqTL8qCNR3BwcHHBwc6NChA8XFxcTGxnLjxg2WL1+OSqXCy8uLxo0b4+7uXqtCh9ra2tStW5fmzZuzevVqmjVrRt++fbGzs9NYDK/0sejq6mJpaUnTpk1p3Lgxw4YN49ChQ8yZM4dOnTrRrl27v/Vz6UUhkUho3749X375JbGxseXYLAYGBgQEBHDx4kU6d+6MqalplX3tgBgIV+ea80/Gm0D4PygpKal0QS2Xy8nJydFYfbUqJCYmolKpql2sloZareb27dvk5+eXk5//u0OgXy5cuJAGDRrQq1evWrvZnjx5QosWLdDX1y+3kE9KSsLe3p579+7VmtqwQD318/Pj0aNHuLu7vxL7gqpQv359cQEtk8lq3K9sZmaGl5cXly5domXLlmzatIm4uDjq1q37kkZcFsJCY+rUqSxevJjs7Owq1YoFIZXw8HDWrFnD0qVLeffddyv0cIWn31lOTg4bN24kPT2dDz74gDp16tQ4AC4uLubIkSMcO3aMNm3aMHToUPT19cU+pc8//5zt27fz1Vdf8fbbb+Pt7V3pMWRnZyOXy3FyckIikeDg4MDMmTM5ePAg33zzDcOGDSvTL5qamir2nJWUlBASEsKKFStEVoUQKFckuFTRsdy8eZO1a9cybty4aoMZIQu/Y8cOrl27Vms92rUNYfFeUFDAnTt3OHPmDMnJybi7u9O9e3eCgoLYvHkz77zzziu9ZwUq+ZYtW+jUqVOFegWlBWGe/VkQrpLJZCINWyaTUVRURGFhITk5OcTHx1NQUFCuEihsS6DMlqbB6unpYWhoKCrNrlu3TkziPHjwQOxrFf7V0dHhzp07/Pbbb2UCt9LjFfb1qiGoVMvlcpydnTl//jx2dnYcPHiQwMDAMq0xarWa/fv307hxY6ytrV/ZeKOiovD09CQxMRFLS0sMDQ1xd3fnX//6F0uXLiU8PFycD4TgZfTo0ezZs4eIiIiXqphfUV8xPA1iunXrRkBAAL/99hv37t1j2LBhoqbDs2MyNTUlKiqKzp07c/bsWaZOncqlS5c4ceKEyL4pDeHaWbduHWvWrGHq1KnY2dkBT9dJU6ZMoXnz5owbN06sZpeuYgvvCde7TCYjNTVVvE9KU84VCoX4+7OK7ML9oa2tXY6NIXiHnz17lvr165Ofn8+hQ4fw8/Mrk2wSklBCUr6kpKSc3ebzagvUJqRSKQYGBtSvXx9vb28GDhxIRkYGt2/fZs+ePaSlpeHk5CQyFYT1xPOMU3hubtiwgYSEBD7++GOxjac2jltoexkyZAidOnVi48aNXL9+nQkTJlToIvJPgZ6eHv369WPr1q1MmzatTLJFaCP7+eef6dSpE8HBwVy5cqXKvnY9PT1yc3PLzeX/S3gTCP8HJSUllWbOBeXCF/WiFahazZo1q1EwWFRUxB9//MGYMWNee+BVEwhB8OLFi/H29qZ37961FgQL9KOcnBwcHBzKbffJkydi9ae2xKxUKhU3b95kyJAh7N+/X2OLiJcJJycnDhw4gIGBAbm5uTU+VqlUSqdOnVi1ahUtW7akS5cuHDhwgPHjx7+y7KBEIsHFxYWZM2eyaNEi0tLS6NOnT5X2SgYGBowbN46//vqLn376icmTJ5frs1UqlVy/fp3NmzfTpk0bxo0bp1F1rDSUSiV3795l06ZN1K1bl08++aQcHVgieSoCNmzYMCIjI0UxHCGweHZ/2dnZFBUViT3dQqa7R48e+Pv789tvv3H16lUGDx6MkZERJ0+eJDg4mJ07d/Luu++SmZlJYmKi2Krx8OFDzp8/z8cff1zl/CAoQ+/du5fw8HCcnZ2rPHa1Wk1aWhq//PILNjY2fPrpp69VEKsiqFQqCgsLuXv3LmfPniUpKQl3d3c6duyIp6enWN3w9fVlxYoV7Ny5k169er2SSo0gBrN69Wp27NiBtbU1xsbGuLq6oq+vXyHd+dlzK9gYVVTJrm7holAoygQNz77y8/M5duwYV69epWfPnsjlck6ePClW7EpKSsTgIS4ujpSUFDw9PVm/fr1YSdPR0cHY2LhMJa6il1DFFpKWFfW3Pvuq6HxUBME+RalUYmdnJwY9586d49NPPxXnMbVaTWpqKlevXuWzzz57ZdexWq0mIiKCsLAwYmJiyiSSvL29GTlyJIsWLWL69OmiVoLw8vT0JCIigkOHDtGjR49XXrERWEezZs1i7969fP3115Wqwwtjz8zMxNXVlcePH9O1a1dcXFxYvHgx/fr1IzQ0VJyjhHNga2uLUqkkNzdX7OM3NjZGR0cHhUJRJpisDDVdxD8bGAsBc+nAuTSNXFdXl5iYGExMTDh8+DDZ2dllaOVyuVwUWrt06RJ5eXl8/vnnWFhYlFEeNzAwEPuOS98TFd0vBgYG4vOqqr7w572Ohb+1sbGhbdu2tG3blvz8fKKiojh//jx//PEH1tbWNGvWjIYNG2JiYlKmiis4JQhJhGfHUVhYyNKlS3F0dKzU//ZFIezT2tqayZMnc+zYMX744QfCw8NrVdz27wSJREJQUBAHDhzg/v37+Pn5lTlOR0dHtLW1iYuLIzAwkGXLllUpGCmoRr8JhN+gyguloKCg0opTTVBcXMzNmzeZNm2axttSq9UcPXoUDw8P3Nzc/mtubGGSXLp0KR4eHvTp06dWg3iFQkFxcTHZ2dnlfF2FBbybm5uoMFgbkMlk5ObmYm5uTlxcHCNGjHjt34ednR2FhYW4ubnx8OHD57JycnJywtDQkIiICEJCQti1axfp6emV0r9eFqytrZk5cya//vorv/zyC6NGjaryvtPW1qZ///7Y2Njwww8/MHHiRLHnLzc3l82bN5OSksJ7770nWjloCmHRvGXLFrKyshg9ejT16tWrciEqkTz1+/v000/ZuXMn33zzDSNGjCi3aMzMzBRFmJ79ezc3Nz766CP27NnDN998w8CBA7ly5QoNGzakXr16uLm5sX79etq2bYuurq4odjVy5Mgqq0YKhYJ9+/Zx7do1Pvzww2rbPFQqFbdu3WL9+vX07t1bI/r0q4KQYHv48CGnT5/m8ePH1K1bl/bt2+Ph4VFhsK6jo8M777zD8uXLWb9+PQMGDHjpQX1BQQHr168Xnx+jRo3CxMQEKysrGjZsSIMGDejbty8NGzZ8rnFU9zdCVauiBK5SqeTYsWMUFRXx888/lxOrEyiycrmcU6dOsW/fPr777jvMzc3LqCvL5XIKCgrElyAUJAiAyWQysVItVKtL2+QIxyEs9AWKa+mKtPBz6Qq1oaGhGCzExcWJ41CpVGhra7Nt2zaaN2+OgYEBcrlc3Mf27dvp1KnTS62wPovi4mISEhKoW7cuJ06coF27duL/SSQSAgMDKSwsZNGiRUybNk1Ua87OzsbY2JjGjRtz9epVdHV1X8hl4UWgq6tLnz59aNCggegX3qtXL5EVA0/nY29vb+7fv0+jRo24fv06wcHBNGjQgA8//JCVK1cSFxdHv379yrSlODk5iS4PAgTv5OzsbI16F2t6/wj3hiYid4JPdb169ejSpQubN29m0qRJZQJCIemlVCpZvny5mMisX7++eL/I5XJkMlmZe6WoqEhMjAqv0veLUqmsMPAVWiOE+6D0/SD8bmxsLFp+VmZB9mzvtYmJCcHBwQQFBVFYWEhsbCznz59nz549WFpa0qRJEwICAjA3N0cikTB9+nQMDQ2ZOXNmGYaFXC5n7dq1eHl50bNnz1fy7NDS0qJDhw6YmJiwbNkywsPDX5ujx8uGlpYWb731Ftu2bcPb27tM7KKtrU3z5s05ffo0Q4YMQaFQkJubWymjtbRY1v8q3gTC/4FQEa4ImZmZ1VoJaILY2FhMTU01ynDC0wk2PT2dkydP8tFHH/1X8feLiopYsmQJrq6ulaqPvgiys7PR1dUlKysLX1/fMv+nVCpJT0+nXr16tSbmo1ariYqKwsnJifz8fJFW+Lqhq6uLkZERlpaWxMTEPJeNiba2Np07d2b//v1MmzaNli1bcuzYMQYNGvTKA31DQ0PGjx/P9u3bmTt3LpMmTaryO5RKpbRu3Rpra2sWL17MsGHD0NPTY/369YSGhvL222/XOBMtk8k4cuQIJ0+epGvXroSFhWncTyyRSDAyMmLw4MEEBwezdu1a6tevT79+/cSAJDs7W1zoVQQDAwP69+8vCmnBU3/bzz//nNzcXG7fvk3fvn1Rq9X88ccfBAQEUL9+/UrHV1JSIiYFwsPDRTpsZSguLmb37t1cu3aN9957DxcXl9ee8BE8i+Pi4jhz5gz379/Hzs6Oli1bMmrUqHJBrRAsP378mJSUFFJSUkhMTCQ2NpYVK1Zw7tw5pk+fjqenZ63Pq0qlklu3bvH111+TkJDAhg0b6N+/P4MHD+bSpUuiAurBgwcJDQ2lYcOGtbr/6qBQKNi9eze3b99m+vTp4qK2NCSSpx7MZ86c4cSJE3z00UfPbUP3rKDTs97CpZWXBcq3ECQIisvFxcXk5OSQmpoqBgxC0H3y5EnkcjmGhoYsXbqU6Oho0dv54sWLYtBTUlLCuXPn6NatGw8fPizXT126EmdgYICenl6V3sXPBhSV9Zrm5uaipaWFvr4+ycnJ5ZKVEslTD1CZTCYGw8bGxqSmpoqiav/617+YN28eurq6tGnT5rWsBYQK9UcffcS2bdv48ccfGTt2bJlEdHBwMHv37mXs2LHs2rWLkpIS9PT0sLW1Zdq0aWzcuJElS5Ywbtw4keUgiCUlJCSI+9LT0xN9Z2tif/YyIJFIqF+/Pnfv3iUgIECsBgvPldKJHB0dHezs7NDW1katVtfY/7m0VVdlL6VSKQbU+fn5YruETCYjPT1dbKMoKCigsLBQ7MUu7eMtVKcrCqhNTEwwMzPDxMQEIyMjunTpQseOHUlJSeHq1avs378fc3NzvL29OXToELGxsdy8eZM5c+aIc9nFixdFQcxXmUCVSCQ0adKEtLQ09u3bx1tvvfVftW7WFBKJBC8vL4yMjLh+/Xo55f7g4GB++OEHBg4ciJeXF3fv3q1U2FVbW1vsEf5fxZtA+D+oarKNj4+vlkZYHQSlyrCwMI1vTLVazdatW+ncubPGwfPrhlqtFoNgZ2dn+vfv/1JoiBkZGZiampKWllbONkhYPOXl5b3w91Ya165dIygoiNu3b5ejo7xOuLq6iqqdzyvQ4efnx9atW0lOTqZly5Z888039OjR45VnVAWa8IABAzh58iTff/89kydPrjIYk0ie9ulOmjSJqVOnoq+vz+zZs2tkMSYsQO7evcvvv/+Ou7s7n3zySYVBgiaQSqV4eXmJ1eGvv/6akSNH4uvrS2pqKnZ2dlX6bEqlUjw9PalTpw63b99GrVZTUFDA5cuXCQkJERW+o6KiytA/nz0mQYFWT0+PKVOmoKenV+nxCFWZVatWYWxszMcff/xaqdDCd5KQkMC5c+e4ceMGhoaGhIWF0a9fPzGgr2x8ly9fpk+fPmJri7AI7NatG4MHD2bdunVYWlrSs2dPPDw8xHP4vMGeUqkkKiqKPXv2kJ2dTUJCAleuXGHIkCHMnTuXxYsXM2jQIB4/fgxAYGBglR6PtQ2hX/n3338XkyKVfb8qlYr9+/dz4cKFMlXK54FEUrHH8/OitLhTQkICsbGxFBQU0KpVK2xtbUlJSeHzzz+ncePGoo1RYWEhc+bMYdq0abi7u5fppRb+zcnJITk5WQwqhIpcVT7Gpb2EhUBIEGMSXklJSaLntiDeZmxsLAbbgmhTnTp1sLS05Ntvv2XChAnExMRQXFyMvb09BgYGTJ48mfnz52NgYEBoaGiNv4PagEQiwdjYmFGjRnHlyhXmzp1L3759ad68OVKplLp165KamipWLYWeU6F9ZPTo0Rw4cECc1x0cHDAyMkJbW5uUlJQy+7GwsCAuLo7i4uLXGggD1KtXj71794rJEuG4KoK1tbX4vdcUpYPq50VF4mfPvoqKisRA+dlXcnIykZGR5OXllenDlsvlwNO5ISIigk2bNvHo0SNUKhVHjhyhb9++fPXVVzRs2JCDBw8ydepUjSz8tmzZgqenJ8HBwVy+fJl169ZhbGyMh4cHvr6+BAcHc/r0abZt24ajoyO+vr4EBQWVUYIvDaHd68cff3wtzLZXBS0tLfr378/KlSsJDAwsk/C3srLC2tqaqKgogoKCOH78OC1btqzwutLR0RGfjf+reBMI/weVVYQFiqSXl9cLPUxkMhlRUVEMHDhQ4+1ERkaSkpLC2LFj/zZBV1UQFt7Lly/HwcGBgQMHvrRsYEZGBubm5mRlZZWjNxUVFaGjoyMGdbUBlUpFdHQ03bt3Z82aNbz11lt/m++kXr163LlzR8z+Pk8grKurS6tWrThy5AjDhw+nQYMGnDt3jo4dO76W49TS0qJt27ZYW1szf/583n777UoVpYUF8dq1a+natSupqalcvnwZd3d3jRQkBUGtTZs2kZiYyOjRo2vFp1siedrLLFSHV69eTf369Xn8+DE2NjZVVqoFZefMzEw8PT3p3bs3P/74I8nJySxcuJD8/HzWrVvHv/71rwoDaiFwXrp0KU5OTgwaNKjK60KtVhMdHc3KlSvp1KkT7du3r7GqZ21AWKjl5ORw+fJlTp8+jUqlomnTpkydOlWsSmoyruDgYHx9fTl//jzw9Pvo2bMnK1aswN7enqCgIJYtW0a/fv3o1q0boaGhBAQEiErslfWpCgsGwa4mPj6ea9eucf78eaysrOjWrRsNGzYkJCSEIUOGcPXqVfr168eYMWOYOHEis2fPxtjYmH79+vH999/Tu3dvQkNDK+yzqy0Ic/Ovv/6KWq3mvffeqzQpolAo2LVrF7dv32bGjBnVMgheNUp/L1lZWeK17u3tzeXLl/Hx8RHPJzxlWDx+/BgLCwu6du1a6X2gyULwWTEzoQ/72R7T0q8tW7bQtm1bSkpKcHNzE9cUhYWFYh926T7V5ORkRowYga6uLgUFBTx48IDY2FhRtX7mzJn4+Phgb28vBtFCH6qWlpZY3S5NLy9txfVssF7Re6X/r6JzD0/vL1dXV1auXMndu3cZPnw4hoaG2NrakpiYiK+vL7du3SojTqitrU337t2xt7dn7ty5jBkzhrp162JhYUFGRkaZfZmamiKTySgpKdHgqni5MDY2RqFQIJPJcHR0JDExsdJA2MHBgZKSEtLT01/xKJ+isnmrNPT19TE3Ny/3fmX3gPB+cXGxWG3+4IMPuHv3rviZx48fM2bMGBwdHZkyZYpGybPc3FwePHjA/fv3CQoKIjg4mPXr1+Pn58eAAQPYvXs3W7duZciQISxZsoQRI0bg4ODAF198wapVqypNJuvq6hIcHMy5c+fo3bv332r+qi1IJBJcXV1xdnbmzJkztGvXrsx336ZNG06cOMGoUaNISEigpKSkwvMlrJ/fBMJvgFwurzIQfpGASq1Wc+/ePZydnTWm05aUlLBlyxYGDRr0UkQGahvCQmvFihVYW1szePDgl0qJSUhIwMrKisePH5fLFufm5mJiYkJ2dnatWF7BUxVqXV1dDA0NyczMrJHq98uE0Fd67NgxDA0NSUtLe64quETy1Erp3//+N3l5eXTq1InFixfTpk2b15aNl0gk+Pv7Ex4eztKlS0lPT6dt27Zlriu5XM6JEyc4cOAAQ4YMISgoiKKiIlFReuzYsVVWNQU7sx07dtCmTRtGjx5dZaX2eY4Bnvr7ffbZZ+zYsYPdu3fj5+dXbZC+b98+cnNzGT58OGFhYeTk5LB69Wp+//139PX1CQkJqTArLlgHLV68WPQIrupeVCqV4jkcN27cCyf9ngeCpsD9+/c5ceIEqampNGjQgDFjxuDs7KxxckeYh+7cucO+fftEsRqVSkXfvn1ZuHAhcrmc5cuXs3HjRm7cuMHw4cOZMGEC9+7d47fffuPRo0d4eXlhYmKCpaUlVlZWGBgYiPTs/Px80tLSSE9Pp7i4mAcPHmBmZoapqSmNGjUiICAAbW1tOnXqRPPmzTlx4gSZmZnMmTMHW1tb3nrrLfz9/Zk8eTLJycls3ryZ48ePM2TIkDKV6do8twUFBaxYsQJbW1sGDx5cpUPCH3/8wePHj5k+ffoLC0S+bMTExKClpYVSqcTZ2Znff/+dDz/8sMz1XlJSwh9//MHIkSOrvI40bX0oDS0trSqfz3K5HC0tLXr16sW+ffvo27cvbdq0qXIfCoWCtWvXsmnTJjp27EirVq1o3ry52GualJTE3LlzCQsLw8vLS3xfeAn9paWp5fn5+WVEoJ5VVC5t11X6JfTnChVv4efS7wnXzLFjx2jSpAnx8fGsWLECFxcX7ty5I7Ltng2yW7ZsybfffsuQIUMwNDTk4cOHpKSkoKurKyo4C5X60pY+pXtlq/pd0+9UE+jp6VGnTh0eP35M/fr1iYiIoEmTJhV+Vkgc5ebm1sq+XyWqYl0BYtuAubk55ubmNG3alEaNGmFmZiYmX65evUpwcHC185iQ7B04cCCzZ88mPz9fFOQSEjpt/iNy2a9fP6RSKdnZ2aJdXHV6HX5+fmzYsOGV9Si/DkilUvr27cvcuXMJDQ0tM1/7+/uzbds2VCoVVlZWxMXF4eXlVW4bhoaGInX+fxVvAuH/oLJAWC6Xk5WVVeNej2dx8uRJscpSHdRqNefPn8fc3BwfH58X2u+rgLBAXLlyJRYWFgwePPilq7ImJSXh6uqKhYVFuUVdQkKCSAupLQ/hu3fvUr9+feLi4nBwcPhbJSdsbW0pLCzE1dWVR48eiVS0msLExARfX18uXrxIhw4dsLW15ebNmzRu3PgljFozSCQSnJ2dmTlzJsuXLyc5OZkBAwagq6tLTk4O69evp6SkhI8//ljsJTY0NGTcuHHs3LmTn376iUmTJpXrbxR8qDds2ABAeHg4Dg4OLzUANDQ0ZPDgwWzZsoW7d++ybds2evXqVaFvY1ZWFqdPn8bd3Z0mTZogl8u5cOECP/30EydPnmTlypUsWLCgnHe0Wv3U83zRokU0b96cjh07VroIEILPTZs2kZqayqxZs2otcaQJBDGm+Ph4Tp06xf3793FycqJ9+/Z4eXnVyM9SCP7PnTvHqVOnsLa2xsvLi4SEBDw9PWnYsCEffPABP/zwA7t37+bJkycoFArq1KnD1KlTcXd3x93dHYVCgY+PDwEBAQwZMoT79+/z0UcfiWwEXV1d7Ozs8PPzw8bGBmNjY9LS0pgyZQpdu3blzp07pKeni4rf7777LmfOnEGhUIjj7NOnD507d0ZLS4s6derw/vvvc+fOHdasWYOLiwt9+/Z97n7cis5LdnY2S5YsEe3rKpubS0pK2LhxIzk5Obz//vsaCQm9TggiRgqFAgMDA2JiYigoKCiTyBGepTY2NlV6ab4sFBYWolQqMTIy4vHjx9UGwfC0ajp06FAOHDjA+fPn6d+/f5nvwszMjI8//pjFixfj5uZGvXr1au1aqax/u7rX2LFjiY2N5eeff8bb25uIiAg6duzI5cuXKSkpQaVSlfHIFl4NGzZk8+bNnD59Gl1dXRYuXIhUKkWhUPDw4UOioqKYM2cOZmZmlY5bIpFU6A8s/C4oNj9bPa/ovWeDdeGlq6uLhYUFV65cwc/Pj8jISNLS0ipUchbOXWZmJvn5+eUSCJW9/pugpaWFm5sb27dvR0dHh27dutGlSxfq1avHr7/+qhEdWSaTceLECQwMDIiPjycqKorg4OAyn5FKpWJCRq1Wc/LkSUJCQvj888+rTSQbGRlRWFj4jw/w7O3tadiwIYcOHaJPnz5lkhbu7u5ERUXRsGFDrl+/XiHTzdDQUDy//6t4Ewjz/wuyim4sQeXyRQIfQUXT09NTo8/n5eWxb98+pk6d+l8xQQpBsImJCUOGDHklFcScnByKiorKeEQKSEpKEr0Oa6OioVaruXbtGr179+bq1auVUnRfFwThCzs7Ox48ePBC7IVOnTqxfPlyWrduTffu3dm8eTNBQUGvNaMq9IuFh4ezYcMGFixYQLt27fjjjz9o1aoVHTt2LGeLpKOjQ79+/bC3t+enn37iX//6l+ilV1RUxOHDhzl58iR9+/aladOmr8ROB57SaXNzcxkwYADFxcV8++23vP322+V8/k6ePElSUhIfffQRurq6XL9+HXNzcxwdHXn06BHff/89Bw4cIDIykoEDB4rXeUpKCgsWLKBLly5V+jELyuorVqygbt26hIeHv7LKv0qlIi0tjYsXL3Lp0iV0dXVp2bKl2Pdbk4qoSqUiJSWFI0eOcPPmTfz9/Rk3bhynT5/mzp07fPTRR0yaNAknJyfi4uLYs2eP2KMrlUoZN24c3t7ewNNK3OXLlxk9ejQrVqwgIiIClUqFi4tLla0QhoaGfPHFF8yaNYvZs2dz9+5dFixYwLvvvku7du1wdnYmNjYWY2NjBgwYQPv27cs8a7S1tQkICMDb25tTp07xww8/0Lx581pRN05NTWXhwoW0bt2aDh06VHofC7RpiUTC+PHjq+wl/7tA+O6LiopwdHTkzz//xMvLq8y9nJ+f/1qfpQ8fPsTZ2VlkEjyrFF8ZtLS0cHJyorCwkOvXr+Pn51emh93d3Z0JEyawfPly3nvvPVxdXWullUOgVz8PXF1dadCgAStWrCApKYlGjRrx8OFDvLy8KlVGF2wQZ82axZkzZ5g4caLoJXz27FmePHnCxIkT8fDwKLNYf7bn9dkAuzTlvPRLUDsXXkL/+LNK6KWtw4RXVlYW169fF1keCoUCHR2dcmMqKSnhzp07wNM5RTifgphaaWG10v3lwvkXAvtnfwcqfL/076W/x2d/FyAkBwRUJwQpl8srFFKKiYkhJyeHM2fOcO7cOb7//nsaNWqElpYWzZo1q/JaEcRHe/bsibW1Na6urpw5c4bAwMAyKtyXLl2iR48eYiKod+/ehIWFVbltAUKb2N99HntRCC0/33zzDa1bty5T/AkLC+Po0aP079+fVatWMWDAgAoDYUHz4H8VbwLh/6C4uLjCrGNxcXG5iaOmuH79Ot7e3hgaGlb7WbVazcGDB2nUqBH29vZ/65tYeAD98ssvGBgYMHz4cI16Ml8UCoVCtB94lqKsVqtJSUnB1dVVDIZfFPn5+WRkZODi4sLGjRtfW99sZdDS0sLV1RWVSiX2kj3P+CQSCQ4ODpiZmREREYGfnx8qlUpczLxOCOIrw4cP59///jcTJ07kxx9/pE2bNpUeq1QqpUWLFlhaWrJs2TKGDBmCnZ0dv/32G/b29nz66aeYmZm90u+ysLCQvLw8fH196dmzJ3fv3mXFihU0a9aMHj16iHTAbdu20bRpUxo2bIhSqWTv3r3069eP/fv34+XlRZs2bWjevDl//fUX33zzDe+88w4GBgbMnz+fAQMGlFORLA21+qmv6S+//CIK3bzsRIdAWb516xbHjh0jMzOTkJAQceFbk35koVIVHR3N/v37SUpKolWrVnz++edkZ2fzyy+/UK9ePT755JMy9i7m5uZMmTKFzz77TOwpHTt2rBhgJCUloVaruX79Oj///DNKpRKAW7duVTkeiURCcHAwEydO5KuvvmLFihVERUUxe/Zs3nnnHbp27Yquri5OTk5cvHiRVatW8e6775ZZgAr95J06dSI0NJSdO3fy1Vdf0bNnT5o1a1Zj/2u1Wk18fDyLFi0Sv+PKApGioiKWLVuGhYUFw4cPf+3CRJqisLCQjIwMUlNTgac9pf7+/mV8g48ePYq/v/9reZaq1Wru379P/fr1SU9Px9zcXOPno1wuR61W4+LiQkREBAcOHKBLly5lgmFPT09Gjx7N4sWLmTZt2ktntFQHiUSClZUVM2bMQCKR8O9//5v27dtz7dq1SpXRJRIJJiYm9O3bl3379rFmzRrCw8NF+q1EIqG4uPiVsROerYqV/j0nJ4fvvvuOzz77DG1tbVEx+9m/UalUfPrpp2RkZDBz5kysrKzEfnKBci4oOZcWXhN+F4LAZ38XtlHV78KYhbkLKBfklLbKEQL36qqBFa2BBZaLcMxCAOvj48ODBw+qfAZFRkaybt06evXqRd26dUlOTubChQvIZDKysrK4cOECeXl5eHp6MnToUI4dO4a2tjb79u3Dx8enWuaSWq0mJiYGNze3f6Rq9LMwNzenRYsW7N+/n6FDh4osAy8vLzZs2ICBgQElJSVkZWWVOXcSiUQs8r2pCL+BWF18FikpKVhbWz/3QlGtVnP27NkKMzEVfVYQ+vnss8+ea3+vCkIQvGrVKvT09Bg1atQrCYLhacUcntJHn808KpVKUlNTqVevXqW+aTVFXFwcNjY24gPk76bgLVQIIiMjKSgoQC6XPzeDQSqV0qVLF/bv34+fnx/dunVj79691XrovmwIlN9Vq1bh5OTE/Pnz2b59O2ZmZgQGBlY6NolEgo+PD1OmTOH9999HIpHwySefEBIS8looaYWFhWIFSyqV4ufnx5dffsnGjRvFwCktLY179+7x0Ucfoa2tzYMHD5DL5RgbG3Px4kU+++wzpFIp+vr6DB48GH9/f+bOnUtqaiozZsyocgGiVCo5efIke/fuZdKkSZUqb9YGhAVZQkICJ06c4Pbt2zg7O9O9e3e8vb2fK7iTyWRcunSJI0eOoKurS+fOnQkMDERbW1s8rqFDhxIUFFRm24JlUHp6OnPnzuXzzz/nvffeE61s1Go1Fy5cwMLCgk8++UScY+BpICxUfyqDRCKhV69ePH78mK+//pp58+bh4uLCypUr6dKlC506dSIzM5OEhAS0tbVZuXJluWBY2I6ZmRkjRowgKSmJrVu3cujQIfr27UtgYGClFj3PnqeHDx+yfPlyRowYUaXIXEFBAYsXL8bV1ZWBAwe+MmZEbaCgoEB0BzA2NqZFixa4ubkhkUhEBfQzZ87wySefvJYAUah6tW7dmlu3bonMA02QlZUleieHh4ezYMECDA0Nad26dZnkiZ+fH0OGDGH+/Pl8+OGHZbxcXweE9oF+/foxe/Zs9u/fj46ODiNHjqxyDWVra4uNjQ3FxcUsWrSIiRMnipWq7OzsVzr+yn43NTXF0NBQTIonJiZWqMehVqtFR4vSTMO/Q4KpNoOdR48esW3bNnx8fOjevTu9e/fGz89PtAErKiqqNIHh7e3N3Llzxd9HjRrFqFGjKvysRCKhQ4cOdOjQQeOxqVQqLly4QPfu3Wt2UP+lkEgkdOrUiS+//JJOnTqJrZz6+vpiq4K7uzvR0dHlkgh6enpvqNGvewB/FxQXF1cYPCQlJb1QNjktLY28vDzc3d2r/axarebPP/+kS5cutVbNfFmQy+WsWbMGLS0tRo4c+cqCYHgqhmVsbExubm455UOB7pSWloaLi8sL70ugRQcHB3P//n08PDz+Fg+0Z+Hh4cHp06cxMjLi/9g76+iqru5rP1fiQoiRBBLigeAkwV2Ct2gpUNwhWHEKbd86bSmQ4O5OcC/u7iFEIO7ucuX7g++cHyEJJCFA+r6dYzAGcO8999xz9tl7r7XmmjMmJobq1auX6TgSiQQXFxd27dol0tt8fX2JjY3F0tKynM+6ZFCpVPj5+Ymq0K1atUImk2FjY8PKlSuJjY0Ve2HffGbUajVhYWFs3bqVjh07kpKSwrNnz6hbt265imKVFIJSrGBLJZG8siMZNWoU9+7dw8fHh+fPn9O6dWtcXV1RqVQcP36cjh07sn37dvr06VOILmtgYICmpiY1a9bk3Llz2NnZYW5uXqgnOjc3l/379/PixQvmzZv3wfqBhX7AO3fucPnyZdRqNc2bN6dHjx6ltuERqr/x8fGcP3+eu3fv4ujoyIgRI7CxsUEmk4m94tnZ2cyZM6dQMJCdnc327dtJSUlhzpw5aGtrY29vLyZD4FV7x9WrV7l37x4BAQEFziE6OpqEhIR3jn+5XM64ceNYsGABy5YtY8aMGcybN4/169cTEhLCV199RZUqVfDw8ODRo0esXbuW0aNHF0lNlEgkWFlZMXnyZIKDg9m/fz/Hjh2jb9++uLi4FBsQC1XIDRs2MGrUqGL9pd8UVHtb73BFRUxMjOgOMHfuXJ4/f46tra34uiCAV1YLtPeFEKgbGxsTGBhYQNX1XUhMTMTAwICcnByMjIz4+uuv+eOPP9DW1qZx48YFguGGDRuSnZ3NX3/9xcyZM8tNF6OskEgk2NjYYGlpyYgRI5g1axa+vr707Nmz2H2CwMYTftvixYvp3bu3OJdUBMhkMqytrQkLC8POzo4XL17QuHHjQu8TklkCc60ioTyfgw4dOlC7dm08PDxEfQ54FVjVrFmTy5cvF8ueK+15lHbNePbsmWjnVZH30eUJPT092rRpw/Hjxxk8eLDIsmrevDmHDh2idevW3Lt3r5D1mqam5v+8WNZ/P2eghMjJySm0MVar1cTExBRZKS4phP6edwWKQhY/JiamWBpbRUF+fj6bN29GpVIxbNiwjy4clZqaioGBAdnZ2YV6gPPy8pBIXtlqFNU/XFooFAqeP39O7dq1RR/hinhvKleuTGZmJhYWFoSFhb3XsTQ1NWnXrh2nTp1CU1OTtm3bcubMmU8yUebn53PkyBG2b9/O+PHjadu2rdj3I4hoPX78mI0bN5KTk1Pgs7m5uRw9epTly5fTtWtXJkyYwMyZM8nPz2f58uWkpaV99N8kiHe8OdfIZDLc3d0ZMWIEjx49QkNDg/j4eGJjY4mOjhbt3Tw8PMTxp1arCQkJwcfHhxEjRvD999/TqlUrfv/990ICTampqfj4+JCdnc2MGTPKfbMsUGyfPn3KypUr+emnnwgPD2fo0KHMnz+fjh07FtgslQS5ubn4+fmxdOlSli5dKnobjx07Fnt7e6RSKU+fPuWXX37Bzs6ugL3S67/b29sbuVzOpEmT0NfXR0NDg44dOxZgdkRFRYmbhlq1ahWoXkVFRZXYE1RHR4dvvvkGf39/Dhw4QOXKlZkyZQr29vb89ttvmJubc+3aNQYNGoSenh5r1qx5qz2M4Cc9Y8YM+vbti6+vL3/88QdPnz4V6bOv34MHDx6wfv16xo8f/9YgOCUlhb/++ouGDRvy+eef/+OCYHhl15KXl4ejoyMdO3YkKysLQ0ND4JVg4vPnz2nbtu0nm69fvnwp0pWjo6MLBOnvQmJiouhSIJVKMTY2ZsqUKfj6+vLw4cMC911oAWnfvj1Lly79qBXU4qCjo4OlpSUKhYKePXuyd+9e1qxZQ0ZGRpFzrqA6nJiYSJcuXWjTpg3r1q0jPz+/QgWTNWrU4NmzZ1SvXp3w8PBi+yqNjY2RyWTEx8d/5DP8eKhfvz6dO3fGxMSkEKvFw8ODbdu24efn99HXWMFisGXLlhVyr/ahIJFIaNOmDU+fPi0w7mxtbUlOTsbU1JTQ0FDRD1qAlpbWvz7Cn/oEKgry8vIKVfqEQLg4mfx3QaFQcPPmTb766qt3PpAqlYo9e/bQq1evCqVI/Cby8/PZsmULeXl5jBw58pOca3R0NHp6esjl8kJ91/Hx8RgaGpKSkvJeCQwBycnJKJVKKlWqRERERJkrrR8agmekhYUF/v7+7yWYJSxkJ06cIDU1lebNm/PDDz+Qlpb2VvXO8kZKSgobNmxALpczd+7cQn6mEokEIyMjJk+ezJ49e/jzzz8ZN24cpqamREdHs379ekxMTJg3b57YCyyVShk2bBjHjh3j999/Z9KkSYWqpx8SGRkZaGlpFSviduXKFT7//HO6d+/OwoULxeD31KlTTJkypUCAFhYWJgbBtWrVEgM5R0dHNmzYwOPHjxk0aBAZGRn4+PjQsmVLOnXqVK5Bj1qtJiEhgevXr3Pjxg0MDAxo27Ytw4cPL5Xq8+vHS0tL49atW1y6dAltbW06d+5MrVq1Cgg45ebmcvjwYe7du8eYMWMKiY0JWgHe3t40b978rb9bUBb29PTE09OT2rVrc/78eY4cOSJWSks6z0kkr4TdfvzxR77++mscHBxwc3Oja9euuLi4sGzZMl68eMGQIUMYNGgQ27ZtY9WqVaJAVXGQy+W4urri7OyMn58fBw4cQKVS0aNHD+rUqYNMJuPGjRvs37+fadOmFfBufRNJSUksWrSINm3a0L59+3+ktYjQAx0UFESnTp1QKBSif65KpWL37t107969RLocHwqPHz+mdu3apKWloampWeI+V6FFCsDU1FSs7FhYWDBx4kS8vb1FyqNwj6VSKe3atSMnJ4dly5YxdepUkXXyKSCVSqlfvz737t2jUaNGxMfHY2FhwZ9//smECRMKqaIbGBhgYWFBTEwMUqmUVq1aoampyalTp0hKSvpkv+NNWFtb8/fff2NhYUFSUlKx/ctVq1YlPz9fvI//CxDm3OPHj+Pn50fbtm3ZuHEjQ4YMoU6dOh98jRXmhBUrVlC3bl12797NyZMnadGiBfXq1cPQ0PC/PjDW09Ojffv2HD58mFGjRonaKq6uroSEhKChoUFsbGwBbR1NTc1iBdH+V/BvIPz/oVQqC20IVCoVKSkpZa6eJCQkkJ2d/U6Krlqt5uHDh0gkko8yYZQV+fn5bNu2jczMTMaOHfvJAvaYmBjkcjlGRkaF7llMTAxGRka8fPnyvXuEBVEhZ2dnoqKi0NfXL9KEviJALpdTrVo18vPziYiIKLNglgDBE/Xy5ct0796d+vXrc+XKFbp27fpRFrTg4GDWrFlDmzZt8PT0fGvwJohoXbx4kV9//RV3d3du377NF198QaNGjQqMEUFps0ePHpiZmfHbb78xfvz4Im0FPgQSExMxMTEpUg04MzOTEydO8O2331K/fn2qVq3K0KFDiYqKokOHDgX6WcPDw1m6dCnDhw8Xg2Dh91WpUoUZM2Zw/PhxZsyYQX5+Pl5eXri5uZXLbxT0Afz9/Tlz5gwxMTG4ubkxadIkkYVRFvpzeHg4p0+fJiAgAFdXV0aPHi1agb1e5Y2Li2P16tVUqVKFb775ppBPtFqtJjAwkJUrV/Lll1/i4eHx1v72/Px8Hj58yIwZM5BKpfj7+9OkSROePHnCDz/8UGpmyetshd9++40lS5ZgZWWFg4MDP//8s0iZnjlzJoMHD2br1q3F9gy/eVwNDQ3q1q1L7dq1CQwM5MCBA+zfvx87Ozv8/f2ZPXt2sdZLwrVbtGgRXbt2fauqeEWHQqHg8ePHPH/+nAULFvDy5UvRb/rZs2ekpKTQpEmTT7aWCv3BLVu2JCAgAHt7+1IlHCIjI9HW1i5QbRMox+PHj2fZsmVMmTJF7ImGV8Fn165dycnJYeXKlXh5eRUQi/vYqFWrFmfOnKFPnz4kJiYyYcIELC0tWbhwIePGjStg+ySVSrGysiIiIkLcizVu3JiaNWty/PhxevfujZWV1SffG5mbm4uezDKZjOzs7CID4cqVK4vMi/9mCL2lUVFRHDlyhODgYNq3b0///v3R1dUlIiKCZcuW0aRJE7p27fpOheqynoNKpeL69ev4+voydOhQ6tatK1pwXbx4kcOHD2NtbU2bNm2oUaOGWPT61OOpvCGRSGjRogXff/89MTExIiOlWbNm7NixA2dnZ/z9/QsEwlpaWoXYRf9r+Geugh8AxQXCCoWiTAGfWq3mzp07opz82yD07vXv37/CUtTy8/PZuXMnqampnzQIFkST1Gp1oV5AISMpBMjv27csUA0bNGjAkydPClhYVDRIJBLs7e3JyMggMzOTrKys9z5ex44duXz5Mrm5uXTo0IGLFy++lcZZHlAqlZw9e5bVq1czfPhwunTpUqJnQiKRUL9+fTQ0NFizZg3NmzcvFAS/DqlUStOmTRk3bhyrVq3i5s2bHyUjKjAWimrDuH79OhYWFtSqVQt4VVH6/PPPRQuVJ0+eoFKpiIyMxMfHhyFDhlC7du0i+0tlMhlGRkZIpVIMDAwICgoqoBZaFiiVSuLj4zl48CALFizg5MmTtGnThh9//JH+/ftjaWlZavXnrKwsrl69yk8//cT69etxdHTku+++Y/jw4djY2BQ4nlKpFG062rdvz6hRowppKahUKq5du8aqVasYP348jRo1euczGxERgYGBAZUrVyY+Pp68vDyys7OxsLDA0NCwVL9JgEQiwd3dnb59+zJ//nxxQ6yrq0v//v3R09Nj5cqVHDlyhC+++AJdXV3Wrl1bIgVX4f66uLgwc+ZMrK2tOXjwIFlZWVy7do3U1NRCY1nYrP7555/07NmT1q1bV9i5rCTIzc0lKCgIBwcHatasSWBgII6OjuTn57Nnz55PvpampqaSnZ1NlSpV8Pf3p2bNmqUaQ+np6eTl5RXq45dIJDg4ODBmzBi8vb3FpKcAqVRKz549sbCwEMfTp4KxsTFyuZy0tDSMjY2Jjo6madOmjB07ltWrV3Pt2rUC49TExISoqCjxnIU+eT09Pby9vYmMjPzkm3UtLS2MjIxITEykSpUqREVFFfm+SpUqIZVKSUlJ+eTn/KGgVCoJDQ3Fx8eHZcuW4ezszI8//kjnzp1Fb9oqVaowbtw4jh07xsiRI7l37165BV2CGGNwcLDYDjR79mzRqktDQwMXFxfGjBnDf/7zH5o1a8aZM2eYP38+W7Zs4eXLl/+VAaCuri6dO3dm//794m+zsbERXVYePXpU4DcLFeH/tutQGlTMqOsToKhAWJiQyyKOJHhSCvSE4qBWq7l27RqWlpYlEtT6FFAoFOzevZukpKRPGgTD/1XptbS0cHBwKPR6REQEzs7OZaJlvonc3FwiIiKwt7fnyJEjDBgw4L2O96Hh4ODA9evX0dfXJyEh4b09lM3NzbGwsODBgwc0atQIa2tr7t69S9OmTT9IJjUrK4sdO3aQkJDAnDlzStxTqlQqefToETt27KBdu3ZMnTqVDRs2sGXLFr788stiKYkSySt7gZkzZ7J8+XLi4+Pp3LnzBxV+S0hIKFIIT6lUcuDAAQYMGICGhgbZ2dlcvnwZLS0tpk+fjoWFBRs2bKBq1aoEBQUxaNCgItWAhWrtwYMHefbsGT///DM6Ojrs2bOHhQsXMmLECKytrUsVrObk5ODv78/Zs2dJSEjAw8ODadOmYW5uXqZgSqlUEhsby/nz53nw4AH29vYMHDgQW1vbIn0f1epXXqM7d+4kLi6OWbNmFSlgmJeXx5EjR3j06BGzZ88uEeVdrVZz8+ZN3NzckMlkPH78GBcXF549e4axsfF7jQWJRELPnj25cuUKP/zwAz/99BO6urrUrVuXM2fOMGXKFA4fPszChQvp378/169fZ8OGDYwYMaJElROlUsnBgwdJTExk27Zt5Obmcv78eX766Sdq1KiBp6cnVlZWyGQywsPDWbZsGV988UUBkbB/IgQGlba2tuif/uLFC1q2bMmdO3fQ19cvdeBZ3ggPD8fCwgKpVEpISAi9e/cu8WeFBJFEIsHc3LzQ6xLJKyX8IUOG4O3tzddff13geZDL5Xz55Zds2rSJjRs3MnLkyI8qZilACESePn1KgwYNuHfvHs7Ozjg5OTFr1ixWrFhBQkICXbt2RS6XY2FhQVZWVgG6seAr/uWXX+Lj48PkyZOpWrXqR/8tAiQSCba2toSGhlK9enVevnxZgJEjwNDQEE1NTVJSUlCpVP/I9oPioFAoePHiBYcPHyYlJYXOnTvj5uYmJnfDw8O5d+8e9+/f5969ezx58oTU1FTatWvHyZMnOXjwIC1atMDNzY1KlSqVyutXqP6mp6fz9OlTLly4QF5enshae3OcC8fV09PDw8MDNzc30Q96+/bt5OTk0KhRIxo3boypqWmFLUSVBkKL1OnTpwkPD8fGxgYtLS1q1apFWloa0dHRZGZmiq0TWlpaog3X/yr++Xe9nFBUIJyQkEClSpXKtIjEx8ejUqmwsLB46/syMjI4deoU06ZNq5CbE4VCwZ49e4iLi2PcuHEfzc+vOOTm5pKTk0NWVpZIFRUgVItzc3PF6tT7ICoqCiMjI/Lz80lLSyvSKqEioXLlyqSlpeHs7ExYWFi59DN369aNPXv24ObmRufOndmyZQuNGzcu14VdoGyuWrUKR0dHpk2bVuJkS1ZWFvv27SMoKAgvLy9sbGyQSCRMnz6d3bt3s2jRIsaOHVusrYjQezdr1ixWr15NXFwcgwYNKtCPWpbfk56eTnx8PGFhYSQkJJCbm4tEIuHatWtIpVJCQ0MxMTERkxVBQUFkZWWJ9OVr166RnZ2NmZkZHh4eaGpqMmbMGNF3tziKfk5ODuvWrUMikTBjxgx0dXWRSCQMGTKEBw8e4OPjQ8eOHWnbtu1b5zWVSkVCQgKXL1/m9u3bVKlSBU9PT5ydnct0bQTro6dPn3L27FnS0tJo2bKl2L9d3LMq0Jw3btyIu7s7Q4cOLRQkCoHDhg0bAJg5c2YhunRxEJIoU6ZMAeD27dt07dqVc+fO4eLi8t4bI01NTb7++msGDx7M8uXLmTJlilhlVqvVDB8+nGfPnrFjxw6qV69OZmYmGzZsYOTIkW9NwAoMnfj4eKZMmSJuavr370+3bt24ffs2q1evRl9fn4YNG3Lq1CmGDBlSrJXSPwm5ubmsXbsWAwMD0T89IyMDbW1tDh8+zIQJEz55tfvRo0fUq1ePzMxM1Gp1qfp1MzMzUalU5OTkFNveIzBg8vLyWLp0KTNmzChAo9bQ0GDo0KGsXbuWHTt2MGjQoE+yyXdzc+PgwYMMHTqU1atXizZkZmZmzJgxg7Vr17Jt2zYGDhxItWrVyM7OLlDFNjAwICoqitq1a/Pll1/i7e3NlClTCq39HxNOTk7cv3+fZs2aceHChSLfY2BggJ6eHomJieTl5X3yfVN5QKlUEhgYyKFDh8jOzqZ79+7UqVOnwHysUqn4888/WbduHdnZ2eJn27Zty7JlyzA1NSUmJoZLly6xZMkSNDQ0sLOzw8HBgapVq6Kjo4OGhgZSqRSZTIZSqSQvL4+cnBxiY2MJDg7mxYsXpKen4+DgQL9+/bC1tS1xsUoqlWJiYkL79u1p06YNcXFxXL9+HW9vb/T09GjevDn16tX7ZErz5QVtbW26d+/OwYMH8fLyQiqV0qRJE3bs2IGBgQHx8fHinCTcv9e9p//X8G8g/P+hVCoLLZ4JCQmFFPFKAsGT0s3N7a2Lj1qt5uzZs9StW7dcFI7LGwqFgr179xIREcGkSZMqxGSek5ODXC4nMzOzkHCTsHlITU19b6sfgRZdu3ZtIiIisLS0rJC2Sa/DwMBA7CsLCAigRYsW7zWmJBKJSDcMCQnBzs4OTU1Nnj9/jqura7mcs1qtxs/Pjw0bNtCrVy+aNWtWok2sWq0mMjKSNWvW4OzszLx58woEaELf8OXLl/ntt98YPXp0AXGZN3+ngYEBkydPZseOHSxevBgvL69SWZgJvVJBQUGcPHlSTKLY2NhgamoqivgImdht27aRlpaGra0tnTt3xtfXF09PT3R1dcnNzeXYsWNkZmby5ZdfoqGhQUpKCqtWrWL27NlUqlSJlStX0qZNmwIiUIIytKOjI3369CkwXmUyGQ0bNsTOzo6NGzfy8OFDRowYUaDqrlarUSgU+Pv7c/r0aWJjY2ncuDHTp08X58HS9v4KgoMXL17k/v37WFpa0qNHD5ycnN7qIyycy8mTJ7l48SIjRoygRo0ahcaGWq0mPj4eHx8f6taty+eff16q5zQqKgpNTU1MTU1JTU0lISEBc3NzIiIiyqUfXiKRUL16dUaOHMm+ffswMTFh6NChODk54e/vT6tWrahVqxYLFiwQRWbS0tJQKpViz/Cbv1ewrsvLy2PixIkFaPbCWG7bti0tWrTg2LFj/Oc//ymQHBOSKBVtvSkJ1Go158+fJyUlhaysLLp06UJsbCz6+vrcvn0bJycnsa/8U0EIGFq3bk1wcDDW1talGpPJycno6Oi8sy1LEDXMzc0VfYRfFwTS1NRk5MiRLFu2jAMHDtC7d++PXpmsXr06iYmJaGtrk5ubS1pamjiX6OnpMWHCBHbs2MGyZctwd3cnMzOT1NRUsRJubGxMRkYGKpWK+vXro1KpWLp0KdOmTftke6Zq1apx7NgxLCwsiI2NRalUFtrnyeVydHR0/vGBsDCHBwYG4uvrS3Z2Nr169aJ27dpFVnIlEgmjR49mz549YiDs7OzM0qVLxftVrVo1BgwYgEKhIDExkcDAQAIDA1m0aBGJiYlUqlSJ1NRUcf+soaEhMj/s7e1p1qwZVapUea8+X0ErxMrKit69e4se8JcuXeLYsWNYWVnRunVratasKc6v/7T5snHjxhw7doyIiAisra2pXr06GRkZODk58eTJE1FfQEtLC6lUWkhN+n8J/wbC/x9v0lcENdSyGNQrlUru3r3LxIkT37rRS01N5erVq8ybN++9zv1DQKFQ4OvrS2hoKFOmTKkwE3l2djYaGhpFBsKZmZlIJBJSU1NxdXV9r4lLrVbz+PFjhg8fztmzZ3Fzc3vfU//gkEqlojhCeQhmCcfs3Lkzp06dYsKECXTp0oWjR48WGZSUFkqlkjNnznD27FkmTJhQYs8/pVLJ1atXOXjwIAMHDhQtrd78rEwmo3Xr1lhZWbFmzRo8PT2LVckVFoQhQ4Zw/Phxfv31V6ZMmVJiem1mZiabN28mOjqaHj16FPApfj1bvmzZMnr16sXAgQPJzMzk/v37eHt7c+nSJQ4cOADAgwcP8PPzo1evXtja2pKRkcHixYtp27atqAY+f/58Nm/ezJ9//smoUaNQKBR4e3vTunVrPD09i7w3EolEtPM5f/48P//8MwMHDqRBgwakp6dz9epVrly5goGBAZ6enoWy/SWF4Fn86NEj/v77b9LS0mjWrBmzZ88WhQff1S6SmJjIunXr0NHR4dtvvy2kGC68LyAggNWrV9O7d+8SJ1Fe//ytW7do2LAhMpmMoKAgbGxsSEhIIDMzs1QU8rdB6Nu8d+8eL1++xNfXF1dXV27evEmrVq2QSCTo6OjQu3dvGjVqxObNm9m0aRMKhYIJEyaICQO1Wk1eXh7r169HJpMVGSi/jsDAQC5evMimTZswNDTk77//5qeffsLR0ZFOnTpRvXr1MvU/f0qkpaVx+vRpateuza1bt0Rf10qVKnHhwgXmzJnzyX9PWlqa2GN+4cKFYm2sikNycjKVKlUiPj7+nQG0VCqlRYsWZGdns2jRImbNmlWg+qylpcX48eNZvHgxp06donPnzh+1Wi7YKIWHh+Po6Ii/v79oDynMuYMHD+bo0aNs3bqVlJQUYmJicHJyAsDIyAiFQoFSqUQieeWZrFAo8PHxYfr06aX2JS8PmJmZkZ2dLWrI5OXlFVnw0NPTIyYm5pP2aZcVAgU5ODgYX19fMjMz6dmzJ/Xq1SvWw1ylUhEYGMiePXto0aIFhw8fRl9fn8WLFxfSshB6eC0sLLCwsKBhw4asWLGC7Oxs5HI5L168YPPmzaLQ7JufLU8I5+Lo6IijoyM5OTn4+flx/vx5du7cSc2aNWnVqhW2trbF/vaKCA0NDbp27cqRI0cYP348Ghoa1KhRA6VSybNnz+jWrRsSiQRNTU1kMtm/gfC/KJoaHR0djYuLS6mOI1SqBPrP23D8+HGaNWtW4WgYCoWCQ4cOERwczJQpUwoJ+3xKJCYmihvDN5V34+PjMTAwICkp6b2pU+np6WRnZ2NkZERwcDA9evSoUPeoKEgkEpycnIiKiiIjI4OMjAzRV/N9jtmgQQMOHTpEYmIidevWZd++fURGRpaZKi7QZLdv305SUhLz5s0r4On6ts9lZGSIn5szZ06xCrmvn79QMV67di3BwcEMHjy4WOqsTCaje/fumJiY8OeffzJ27NhC1jxvnlNaWhpLliyhXr16jB49utjNa15eHunp6WI/n76+Pi1atCA8PJyXL1+ybds2xo8fz969e9HT06NPnz6iHUrDhg3p0KGDeB5GRkZMnDiRy5cv880335Cbm8vYsWPf2b8tZMI7dOiAg4MDf/zxh/g8NWrUiIkTJ2JlZVXqzbIgXBIXF8eFCxe4f/8+1apV4/PPP39n9ff1Y6hUKh48eMDOnTvp0qULrVu3LnKTqVQquX79OgcPHmTs2LE4OzuX+vlUqVTcv3+fcePGAXDr1i0aN24sKva+S+2/NDAyMqJVq1ZkZmby/PlzFAoFYWFh5OfnF6hsWFtbM2fOHDp37szixYv59ddf8fLywtjYmJycHNasWYOhoSGDBg0qdpyp1WoePXrEli1bCigLDxo0iJ49e3L37l22bNmCWq2mbdu2uLu7l5hK/imhVqs5fPgwTZo04fr168TGxuLo6MjJkycJCgqibdu2ZWJwlTcEBpFEIiEoKIg2bdqU6vNCAKytrV2itiypVErHjh3JyckRqcNCy4VQefXy8mLRokXo6emJyZePAaFqLQiH3rhxo9AcJZfL+eyzz9DX1+fcuXMFkrj6+vqoVCqRtinMU5mZmSxbtoxp06aVirlTHpDJZBgYGJCTk4ORkRGxsbFF6rsYGBigVCrfW7jyY0OpVPLixQsOHDhARkYGn332GfXq1St2LAqJS4E9OGDAAKysrMjKysLT05NOnTq98/48evQIf39/cnJyxPnx5s2bpfLefl8I56ijo4ObmxsNGzYkOTmZBw8esGvXLjIzM/Hw8KBZs2aYmppW+KBYeFZOnDhBZGQk1apVo2nTpuzevZvMzExycnLQ1dVFJpOJgln/q/jnykaWM4oKhGNiYt7Z41sUrl+/joeHx1snjoSEBB48eEC7du0q1MOkVCo5cuQIAQEBIh26Ip2f4CGsr69fYLMuXFMjIyOys7OLtKcpKdRqNc+fPxeV9tRqdYkCtYoAW1tbIiIi0NPTIzU1tVyOqa2tTePGjTl37hwaGhq0a9eOU6dOlUlcQVg0//rrL7S1tZk6dWqJg+Dg4GB+/fVXzMzMmD59eqn8f42NjZk2bRomJib89ttvhdRWX4dEIqFp06YMHz6cVatWce/evWIVpZVKJTt27KBZs2Z89tlnRQYnAp01Ozub7OxsNDU1yc3NFdW9jx07xo8//kidOnX4/fffuXTpEv3796dSpUps2LABW1tbunXrVig4lclkIhXS2NiYJ0+ekJ6e/tb7IvQvX7p0ic2bN2Nubi5SSRs3blzqIFhITty8eZM//viD5cuXU6lSJebMmcOkSZOoVatWiavKQnLk0KFDTJ48mXbt2hUZBOfl5bF//37+/vtvZs2aVaYgGF7NJYC4aQsJCcHV1ZXAwEAMDQ3faw55ExKJhLZt2/L06VPGjBnD48ePefr0KcnJyYXeK5fLcXNzY+XKlcjlcgYNGsTevXvx9vbGxMSEr7766q1B8L1799i2bRuTJ08uYK8jBBatWrXim2++YciQIQQEBPD999+zefNmwsLCUCgU5fabyxtRUVE8fPgQT09PQkND0dHRwdjYmKdPn5KRkUHHjh0/+VolJCHq1KlDTk4O2dnZpbZfjIiIQEdHp0h7wOIglUrp3r079vb2rFmzpkB/JiD6rR87dozbt29/VGEcV1dXgoKCsLa2JjQ0tMgNt+Ad7OLiws6dOwkPD0etVqOnp0d+fn6B/kWJREKbNm1o0KABK1asICcn56P9FuH7q1evTmhoqGj5VNT1tLS0RKVSER8f/1HPr6wQKP2LFy9m69attG3blm+++QY3N7ci97JCQvvUqVP89ttv2NrasmDBAmrXrk3lypXZvn0748ePL5FryqpVq0hPTyc/P19UMPb19f2kfavCutquXTtxPQPw8fHh119/5fz58yQnJ1do/10tLS06derEkSNHUKvVODg4kJGRgUQiISYmpsD7/pcD4X8rwv8fb/YIC3TH0irvKpVKHjx4wNSpU9/6voMHD9KuXbv3rtiVJ4Qg+OnTp0ydOrVCVgmEivCbtGh4tbE1NTUlPDz8vVUy7969i5ubG35+ftSoUeMfo/pobm5OSkoKzs7Oorfm+0IikdC6dWt+++03evToIdoQJCcnl2qT97o/cJcuXWjVqlWJrqtCoeDixYucOnWKoUOHUrNmzTLR+zQ1Nenbty8ODg4sWbKEvn370rhx42JpxDVr1mTq1Kn4+PiQmJhYiFYt9DerVCratm1b7DllZmYya9YskpKSCAgIYN26daxevZqYmBjq1atHbm4uNWrUwMHBgQ0bNlCtWjU6d+7Mrl27kMvl9OnTp1BAqFQquXDhAqdOneLbb7/FxMSE48eP8/PPPzNs2DBcXFwKnI9KpSImJkZUanZ0dGTYsGFYW1sjlUp59uyZaDvVuXPnd4qVCRXNixcv4ufnR/Xq1enZsyf29valplOr1WpCQ0NZt24dNWrUYM6cOcUm4FJTU0XK9IwZM95rjrp79y7169dHJpMRERFB5cqV0dXVJTIyEiMjo3JvBzExMcHKyoqwsDC+/vprJk2axPXr1/n888+L7LUzNDRk+vTpqNVqZs6cSc2aNZk0aRL5+fnFqmvfvn2bPXv2MHXqVKpWrVpsT7yGhgYODg7Y2dmRnp7OzZs3WbNmDVpaWrRu3Zr69esXSUf/VFAqlezdu5cePXqQm5vLs2fPaNiwIZmZmTx8+JDvvvuuVIJUHwoKhYKAgADat29PSEgI5ubmpR5HQkK3tNVtmUxG37592b59u6gW/fpzbGpqyrRp0/jzzz/R0tISbWY+NAQbpaysLAwNDYmKiiqygiqVSqlevbrY8z9mzBj09fXJyckpFGwInslZWVmsX7/+nW0C5Q0HBwcCAwOxtbUlLCysyPeYmZmhVCpJSEj4aOdVFqhUKl68eMHBgwdJTU0tUAEubnwI9Npdu3ZRrVo15syZU8jzuqQJ7jNnzrB///5Cr12/fp3IyMhyZeaUFUI/ca9evejWrRsRERFcunSJEydOYGlpSevWrXFxcalwe2ahKnzq1Cmio6OxsrLCzs6O0NBQHj58iIWFhdiDXZGToB8a/wbCvJoI1Gp1gU2uILykq6tbqmOFhYWho6PzVlp0VFQUgYGBDBo0qMI8NEqlkmPHjvHo0SO+/vrrCvdAQ0FV6KIoM+Hh4djb22NgYPBegbBSqeTly5f06dOH7du3F6CkVnQItg2VK1cmKCiIli1blsu5Gxsb4+joyM2bN2nTpg3u7u5cvnyZzz77rETHFwTk9u7dy6hRo0pkbyJknLds2UJycrLYY/o+v0cqldKwYUMsLS1ZtWoVL168oG/fvkUGbxKJhKpVqzJ37lx8fHyIj4/niy++EIMQtVrN33//Tbdu3d4a0GtoaPD8+XPOnTsHwNatWzE1NSU+Pp5z585hZmbG+PHjad26NTdv3qRPnz4cP36ckJAQZs6cWWCDJ1CQ9+/fj7+/P3PnzhVbKwQRk3Xr1uHu7s7nn3+OTCbj2bNnnDx5koSEBFq2bMn8+fMLiOrAq6rN/Pnz2bp1q9h3/HrFXah4pKamcuvWLa5cuQJAq1at6NOnTyGGRkkgUKHPnTvHyZMn+eqrr6hXr16Rx1Gr1YSHh7NixQqaN29eYn/p4qBQKLh37x4jRowQA0h3d3eUSiVhYWHY29uXe0uIRCKhXbt2nD59mhkzZjB+/Hi+/fZb7O3tqVOnTpGBbW5uLgqFAk9PT5ycnAgNDeX777/H09OT5s2bo62tLY7F69evs3//fmbMmFGkvVRRkEqlVKpUiY4dO9KuXTtCQkI4c+YMhw8fpkaNGrRr1+6T9xILDJ2kpCSaNm3K48ePkUqloo2NjY3NewsDlhcyMjLIy8vD2NiYS5culVqrQq1Wk5KSgr6+fpkEH+VyOQMHDmT9+vVs27aNoUOHis+JRPJKIX/KlCksXryY8ePH4+Tk9MGvm0QioV69ejx58oRatWrx8OHDAkwFAVKplMqVK5Ofn8+IESNYvXo1jRs3JiMjo8jKoEwmo0+fPqxdu5bdu3czcODAj5KwlkheWSidO3eOFi1acP369SLfIwSCRbE+PjWE+Tw8PJz9+/cTHx9Pz549adCgwVvtjARxwl27dhEfH8/gwYNxcnIqc995cnIyv/76K5mZmYVei4yM5Pr16+Wm1VAeEPraHRwcsLe3F5NyFy5cYNeuXTg7O9O6dWvs7e0rDHVaR0eHjh07snXrVipVqsSxY8fIycnh1KlTLF26FFNTU54+fcq8efMwMjJi/vz51KlT51Of9kfFv9RoXm2KJBJJgUk0LS0NTU3NUmVzhc2Ih4dHsROySqVi//79dOvWrcIIUCmVSk6cOMG9e/cqbBAMr84zKSkJhUJR5CYhJSWF7OzsMvubChB6BPX09IrNXldkVKlSBV1dXcLCwsqNWiSRSPD09OTMmTMolUratWvHlStXClHwikJ+fj6+vr4cO3aMWbNmlTgIjoiI4Oeff8bY2Jjp06e/dxD8+m+xtLRk7ty5ZGVlsXDhQuLj44ukt0kkEipVqsSMGTNE5eacnBwxII2NjcXKyuqt56WhoUHbtm3F9xgaGuLp6Sn+zri4OM6fP8+kSZOIjo5mzZo1jBkzhtTU1ALB2OtiSTExMcycObOAvoDQI/7tt98SHR3NtGnTmDVrFkeOHKF9+/b8+OOPdOvWjUqVKhUZ9BsYGDBu3DhatmzJb7/9xrVr10T7iqdPn+Lt7c1PP/1EVFQUI0aM4Pvvv6d9+/aiHVBpIPRW+/j48ODBA+bNm0f9+vWLPI5KpeLOnTssWbKE/v3707179/e2ghESalWrViU/Px8/Pz/q169PUlISMTExVK9e/YPMgS4uLsTFxZGWloaLiwv29vasX7+e58+fFxh/QkC0ePFiPDw88Pb2RkNDAz09PSZOnEhwcDDz58/n2LFjpKWlcfnyZQ4ePMjs2bNLHAS/DqF33MHBgXHjxvHdd99hZ2fHpk2b+P777zlz5gypqamfhAaYn5/P3r176d+/PxoaGmIFzt7enq1bt9KvX79P4pNbFIQqoYaGBv7+/tSoUaNUn8/JyRHtAcvqfCCXyxk+fDhpaWns2rWrEK3Y2tqaCRMmsGrVKsLCwj4KTbpBgwY8fPiQOnXq8PDhw2LnWmtrazIyMrCzs2Py5MmcPHmS2NjYYunPwm+NiIjg7NmzH218mpiYkJmZiZaWFqmpqUX+HoHanpSUVGE8WoXkY3R0NCtWrGDFihV4eHjw/fffi+18Rc0dgkXdoUOH+O2336hZsyYLFizA2dn5vfZaUqmUZs2aYWVlhYmJibjeaWpqoq+vz4MHD8p87A8NiUSCtrY29evXZ+rUqcyfPx8nJyd2797N/Pnz2b9/P1FRUSiVyk92/wXXhlu3bvHHH3/g5eXFqVOnuHDhAo8fP+bixYvs37+f0NBQTp8+zcWLFyvMXPox8W9FmKID4aSkJAwNDUu14crPz+fJkydvpUWHhoYSExPDuHHjKkSwqVQqOX36NHfv3q3QQTC8uk/Z2dlIpdJCQZHQq5iVlfXetgpC5joqKgpjY+MKk7AoKWrUqEFUVBRZWVnk5uaWm3+kjY0Nenp6PH/+nJo1a2Jra8vdu3eLrcYIi+fGjRtRKpXMmTOnRPRFpVLJrVu32L9/PwMGDKBBgwblrnQqkbxS6h0xYgTXrl1j4cKF4ne9mcQS3jt69Gj27t3L0qVLmTBhAmq1Grlc/k4asVQqpWXLlujq6pKZmUnr1q0LeDxbWlry66+/MnPmTFJTU8nLyyMvL4+IiAiys7NFVkpmZiarV6/G2NiYYcOGFfpeQazq9OnThIeHY21tTVBQEF27dqVu3brvHAfCHNiyZUvs7OxYsmQJR44cEX2527Rpw6hRo0rdLvImVCoVfn5+bN68mTZt2uDp6Vns4pufn8+RI0e4d+8e06dPf2fSoaR48uQJrq6uyGQyYmNj0dDQwMjIiGfPnqFQKD6YZ7iWlhY2NjYEBQVRq1YtzM3N6d+/P2vWrGHChAk4ODgArwL1pUuX0rJlSzp06IBUKmX8+PGsXLmSy5cvM2LECJKSkjhx4gTjxo0jLS2NP//8s0wuB69D+KyBgQHt27endevWhIeHc+nSJX766SeqVatGu3btcHR0FKvRHxJCtd7AwEAUrnz+/DlVq1YlMTGRmzdvMn369AqxZr3eH5yenk5GRkapg1khAZ+ZmYmJiUmZzkOoWo0bNw5vb28OHDhAr169xHlNInllizd06FCWLVvG119/XabkSWnOp1q1aqSmpqKnp0dmZmaRQo5CgjIlJUV8BqdPn8758+cJCgoq1hZLW1ub8ePH88cff1C5cmXc3d0/+HiQy+UFkpRpaWmFvN2NjY3R1tYmPj6+kCvJp4DQr3z48GGCgoLo1KkTI0aMeOdznJ+fz7179/D19aVGjRrMnz+/3NS6jYyM6NKlCyEhIXTr1o0aNWrQv39/mjZtyo8//lisj3ZFgnAdKlWqRJs2bWjVqhWxsbHcunWLFStWoKGhQfPmzXFzc8PQ0PCjjgNBYPCHH34oUdHCzc1NXIP+l/BvIAyiNP/rm+3k5ORSCyRFRkaiqalZLC1aqVRy+PBhevToUSGyLiqVijNnznDz5k2mTZtWoXrCioJCoRAD3jd7U9PT04FXC9L70DrUajUPHz6kT58+PHjwgDp16nxUu4n3hSDkcffuXfT19UlOTn7vwEWATCajc+fOHD16lJo1a9K5c2c2bdpE06ZNCwVZAo19+fLluLq68vnnn5dozOfk5LB3715evnzJ9OnTP+gGDV79phYtWlC9enXWrVtHQEAAvXv3FoPM7OxssV9VU1OT/v37c/LkSf744w8GDx5cYouqWrVqUa1aNV68eMHQoUO5desW8GojsHTpUqKjo4mMjBTfb2pqWqCHLykpiWXLluHi4kKvXr1EurTgtyv4F8fGxtKmTRt69uyJoaEhCQkJbNq0iSdPnjB48OC3VtUFS7eHDx9y5coVZDIZ+vr6pKSk0KVLF2rVqvVez4JarSYnJ4cjR47w4MEDxo0b91bLrLS0NDZs2IBMJmP27Nnlpg6rVCq5d+8e3bp1A+DevXtioiA0NBSZTPZB+9IaN24s2jZVqVIFDQ0NRo8ezapVq0SBwsWLF9OpUydatWolXnNtbW3Gjh3L6tWr2bNnD/369cPKygorKyu6d+/Ohg0bqF69Op07d6Z69erlkgCTy+XY2dlha2tLVlYWfn5+nDx5ksTERBo0aECzZs2wtLQst2Tbm8jOzubQoUNMmjQJuVwuBpvGxsZcvXqVGjVqULVq1Q/y3aWFQqHgxYsX9OzZk8jISMzMzN6ZJHsTaWlpGBgYkJ6eXuq2rDeho6ODl5cXS5Ys4ejRo3Tv3r1AMFy3bl369OnD0qVLmTFjxgcNOjQ0NLCzsxM9TQMDA4u0JDQ3NychIYGsrCz09fWxsbFBR0eHtWvXYmRkRP369YucAypVqsTEiRNZvHgxZmZmH4zRIUAmk2FtbU1kZCTGxsbExsYWCoT19PTQ1NQkOTm5SDHWjwVBSPT48eM8efKEDh06MHDgQHR1dd96jYTe4T179iCTyRg/fjw2Njbluh9Sq9U8ffoUuVxO48aNMTc3R6VSYWZmhqOjY4XejxYHwcbys88+o0uXLkRGRnL58mVOnz5NlSpVaNmyJTVr1iy0nuXn55OXl/fO+1IaSCQSBg4cSEBAAMuWLSvSyktTU5O8vDykUimfffbZB5vLKzL+935xERCEsl5/wGNjY0VT95JArVZz8+ZNGjVqVOwgDgsLIz4+Hjc3t0/+gKtUKv7++2+uXr3K9OnTC/UMVkTk5eWJioJvJilSUlLQ1dUlKSmJKlWqlPk70tLSSEpKwsbGhh07djBy5MgKf13eRNWqVUlOTsbR0ZHg4GCqVatWbseuU6cOe/fuJSoqiurVq6Ojo0NAQEAhunNISAgrVqyga9euJRbFSkxMZNWqVVhYWDBjxoyPplguUPJmz57Nrl27WLhwoUhN/vHHH/nll1+wsbER6aNdu3bF0NCQ5cuXk56eTm5u7juD/EqVKtGkSRNkMhlt2rTh/PnzaGlp8c0339CqVSs6deokUhg1NTX5/fffGTJkCFKplOjoaLy9vXF3d+f27dtYWlrSsmVLcnJyuHfvHmfOnBGTFHXr1i3Q72xmZsbUqVM5e/Ysv/76KwMHDixEQc7NzSUoKIjz588TGhqKs7Mz/fr1w9bWFrlcTlBQEBs3bsTNzY0ePXqUenMPr+bHqKgo1q9fj5WVFfPmzSuWfSJY0K1cuRJ3d3e6d+9eronDzMxM4uLisLOzQ61Wc/fuXYYNG4ZEIiEkJARtbe1Cm9rygkQioUaNGvj6+pKTkyM+o59//jmDBw/m999/Ry6X069fP5o3b17o+ujq6jJ27FiWL1/Od999h0wm45tvvsHIyEi0Rtq0aZOoFlqnTh20tLTe+zmSSF7Z8Li7u4u2ItevX2fVqlVoamrSvHlzGjZsWK6+rmq1mlOnTuHq6ioGu4IqelpaGo6OjlhYWFSYjVtycrKo5H7u3LkyJWTj4+MxMjIiKSnpvQNheDVeJk2axJIlS9DS0irgMS6RvFKKz8nJYcmSJcyYMeODjXtBm+Hu3bs0bNiQO3fuFBkICx69CQkJmJubo6GhQeXKlenXrx+7du1CKpUWKfIlVJMHDx7MypUrmTdvXpGCmuUFiUSCjY0NYWFhWFlZFWm1KZVK0dbWJjc395O0FAjtFSdPnuTu3bu0bt2a77777p2sP7VaTVJSEr6+vqKGxtv8g98HeXl5hIWFoa+vj4WFBXl5eWRnZ5dpjaloEJLnQiIxNzeX58+fc+nSJfbu3Yujo6PYT6ypqcmlS5dYvnw5CxcuLLckgETyyingP//5D2q1mmXLlqFUKjE0NCQlJQV4pfNx9uxZTExMCrRw/S+hYqwgnxgCNfr1zWFkZCQNGjQo8THy8vJ4/PgxkydPLnIgKZVKDhw4UCGqwYJAzYULF5g1a1aRPYMVEYmJieIE+WZglZKSgpGRETExMe+1gQgLCxMn5JycnHd6QVdE6OrqIpfLMTMz48WLF+XqG6mhoUGbNm04c+YMw4YNo3Pnzhw7doyaNWsCrxbR+/fvs2XLFkaOHEnt2rVL1A8cFBTE6tWr6dy5M23btv3o2XNhoz98+HBu3LjBr7/+ytOnT7l48SKampqsXLlSpMIJVGdDQ0NmzpxJQEAADRo0EDfoUVFRxMbGEhERQUpKCrm5uWJ/u6amJlu3buX27ds0bdqU9u3b4+vry9OnT6lVqxYvXrygQYMG9OnTB6lUSmhoKD4+Pnh6erJ37162bNlCQEAAcXFx3Lx5E2trawYPHoytrW2xgkYaGhp06tSJmjVrsnbtWh49esQXX3xBcnIyV65c4d69e1SqVIl27doxYsQIsRVAOJaTkxPffPMN27ZtY+HChYwdO7bE1lVCT9rly5c5dOgQX375Je7u7kWeq9BHdf/+fbZu3cpXX31Fw4YN3+u+FnU+gYGB2NjYoKWlJeoKWFhYoFKpxArPh9xE6+npoa2tTVJSEk5OThw9ehR41dsvCAO9zb9eS0sLOzs7Tpw4wVdffSUyeXR1dWnRogVNmzYlICCA48ePs3fvXlq0aEHLli3FIOd9qdMymQxTU1O6d+9O165dCQ0NFVXdLSwsaNOmDa6uruLzUtbvS0pK4tKlS3z77bfi2hwUFEROTg5yuZw6deqUykLtQ0KtVvPs2TMcHR2Ry+UEBASUSQwzPDwcAwMDtLW1y6UlR+j9nzx5MosWLUJTU7PAZlcieeUIkJmZiY+PD19//XW5VqReh4uLC/v376dHjx4cOXKE/Pz8QnshU1NTDAwMRKVlQXTKxMREDOhHjBhRpM6ERCKhTp06tGvXjpUrVzJt2rQPGlDZ2dlx//59WrRogZ+fH23atCl0Pjo6OqSlpX1UGyCBNXf69GmuXr1K06ZN+fbbb9/J+BPE+f7++2/Onj1L+/bt+eqrrz5oC0RqaiqJiYmYm5tTqVIlQkJCUCqV/7h2tHdB6CeuW7cudevWJTMzk/v377Nv3z4yMjKoV68eR44c4eDBgwQHB+Pj40OLFi3Kpfou7G1+/PFH1Go169ato0+fPvj6+pKSksKAAQN48uQJDRo0KNCy9b+EfwNh/q8i/PrDnpqaWqrNUGxsLHK5vEh6kVqtJiQkhJSUlGKpPR8LKpWKCxcucO7cOWbOnPmPCYLhVbZcT08PlUpV6JyFDWx0dHSZJ1GhOuTm5sbz58+pXr16uSvHfgxIJK/UQXV0dHjw4EG59idJJBKaN2/O999/T2pqKrVr12bPnj1ERERgZWXF2bNnOXv2LDNmzCjWvkWAECRduXKFI0eOMGrUKFxcXD7peJRKpTRp0oTTp09z4cIFVCoVO3fupEWLFowYMaLABrJevXoMHjyYyZMn8+WXXxIbG4tCocDMzIwqVapgY2ND3bp10dLSQiaT0bNnTxQKBfn5+dStW5eIiAjOnTvHvXv3aNSoEd26dWP79u2MHDkSfX19nj17xrp16+jZsycbNmxg+/btKBQKTpw4Qb169ZgxY4bIWinJNbO2tmbixIn85z//YfPmzTg4ONCjRw+mT58uJnyKOo6wkI4ePZrr16/z22+/8cUXX9CoUaO3jishMbB582YyMzOZN2/eW3tYFQoFhw8fFvUKiusJfF8ICtESiYQnT57g5OSElpYWmZmZhIeHi0yHDwWpVErNmjV58uQJHh4eJCQkEBUVhY+PD2PHjkWlUvHnn38ye/bsQhVWpVLJ0aNH8fPzY/fu3axfv17sARXUXuVyOTVr1qRmzZrExMRw7tw5fv75ZxwdHencuTPVqlUrl+qOEBTb2dlhZ2dHTk4Ofn5+XLx4kV27duHk5ESrVq2wt7d/qxVLUVCpVPj6+tKhQwcxgBdYVy9evKBFixakpKTQunXrCrN+PXjwgDZt2pCenk5aWlqZmDjx8fGYmpoWEMF7X0gkrwT/pk6dyh9//CFW8F+fy7p06UJ2djYrV67Ey8urXFgEb8LAwABDQ0NRtyI2NrbQNdLS0hIV9YW2E0NDQ7Kzs6latSpeXl4sW7aMsWPHFlk1k0gkdOjQgbCwMPbt28eXX375wZKqpqampKSkYGpqSkxMTKE2GYnklQ9tWFgYWVlZ5daiVByE1pOLFy9y5swZGjRowIIFC945lgThx4cPH7J3717s7e1ZsGBBubI7ioPQiiLsFYREYHmwISoihOupr69PixYtaNGiBXFxcZw8eZLjx4+LrR9ffvklCxcuFAUCX78PQsJY2D+p1Wrx70qlUhTbE3zMBSZlfn4+7dq149atW+Tl5VG/fn2uX79OfHw8lpaWGBoacuTIkQKq4TKZDJlMhlwuR0NDo8AfIVkn/BGYaEJRUfi78Kci499AmFebi9fpVWq1mvT09BJ7/AoLtFDpKOp1X19funfv/lG97t6ESqXi0qVLnD17lunTp5frYvsxkJiYCFCkv2JkZKS40JY1C5yfn09gYCBdu3Zl//79NGzY8B91fV6Hk5MTMTExZGdnk5+fX66bAX19fXES7dy5M+3atePo0aMYGhoSEhLCnDlzSjS2cnNz2b17N+Hh4cyePfu9hX7KC4GBgWzatEmks+Xm5vLDDz/g5uZGvXr1gFden0IQ2759e+rXr4+TkxOVK1cu1aZfUIJOTk7m+fPnZGRk8OjRI9atW8fDhw8ZMmQIPj4+7N69W/T5y83NJTo6ukQ+o0J1wM/Pj8uXLxMfH0+TJk0YMGAAR44cQSaTiQm/tx1LCHqaN28uKh0/ffqUL7/8skiqnSCItWXLFlq1aiUKYhVHhU5NTWX9+vVoaWkxd+5cDAwMSnT9Sou8vDxevHhB//79Abhx4wZdunRBIpGQlpZGRkbGB68yCv2Zx48fp3379uTk5PDTTz8xdOhQGjduDLyai/76668C87SgMeHn58e0adPQ19dn0qRJ+Pj4cPDgQXr27FnAKgdeCbENHDiQzz77jLt377Jx40akUint2rWjfv365dJ3LXxeR0cHNzc3GjZsSEpKCk+ePOHgwYMkJydTr149mjdvjqWlZYmej9DQUIKCghg8eLD43vz8fE6dOkVqaip2dnYkJCSUa9vH+0ChUBAVFYWNjQ0xMTGYmZmVmrKtUqnE6lh5KeQLkEgkmJiYMG3aNP766y80NDQKtHFJpVJ69uzJjh07RF/et9nolAUymYw6derw4MEDatasiZ+fX6H7J5fLMTAwIDo6WjxvXV1dcnJykEhe6V+MGTOGdevWMW7cuCJtmGQyGV999RW///47t2/fpnHjxh/kedbW1katVqOvr09aWhr5+fkF9ndCQjonJ4fExMQPxi4T1pBbt25x9OhRHB0dmTVrVonmMZVKRVhYGLt27UKlUjF69Gjs7Ow+ii6KWq3Gz88PeGXfB//X+vDfGgi/DuHeCC0AWVlZ4mvR0dF4eXkRGBjI2LFjyczMJDExkZSUFFJSUkhOThbZTCqVSvwDr1qrtLS00NLSQkdHp1AAO23aNKRSKRoaGkyZMgWpVMovv/wino+gxQOvYiMhiBb+KBQKkTGZm5sr/nm9xVQ4vqGhIZUrV8bIyAgjIyMqV66Mqamp2D+voaFR7vNMWfBvIMyrG//6opWfn09OTk6JN2P5+fk8fPgQLy+vIm/oixcvyMjI+KTVYLVazZUrVzh9+jRff/11uS+0HxqvewhbWVkVek3oqXqfYCo5ORm1Wo2hoSEvX76kb9++5XHqHx0SiQQ7OzseP36Mvr4+cXFx5Sr+I2Tdly5dStu2bWnQoAG//PILvXr1Ytq0ae/s7RXu1+rVq7GysmL69OkVigplbW3NmjVruHDhAufPnycwMJCIiAjmzZvHihUruHr1Kg8ePKBly5Z8++23GBkZlXnjIJG8Uni1sLDAwsKCFi1akJSUxPnz51GpVCxYsIB79+6Jlljm5uZYWVlhbW1drCWDUBkIDg7m8uXLvHjxAjs7Ozp16oSDg4N4revVq8e2bdtYvHgxw4cPL9HGSejFmzFjBkeOHOGXX35h5MiRBUSvcnJyOHDgAE+ePGHMmDE4ODgUe1y1Ws2LFy9Ys2YNrVu3xtPT84P2fIaFhWFkZIShoSEZGRnExcVhb28PvKrG5efnfxR6WLVq1YiLiyMsLAw/Pz8mTZpUYMPeunVr8vLy8Pb2Ztq0aejp6XHw4EGeP3/O5MmTxQBWV1dXrJIdPHiwgDqwAIEe27p1a5o1a0Z4eDh///03hw8fplatWrRt21asEpcHBDpry5YtadasGcnJydy5c0dUj3dzc6NRo0ZUqVKlyO9UKBTs2bOHPn36FEhqRkdH4+fnR6tWrdDR0cHIyKjCMHYiIyPR09OjUqVKnD17ltq1a5f6GLm5uWRmZpKTk/PBBMDMzc2ZOnWqGAw3aNBAHHNyuZwvv/yS9evXs337dr766qtyfxbr16/P+vXr+eKLLzhx4gQdO3YsMDfIZDKMjIyIiooS5zdtbW1R8VYieWURN2TIEFatWsW0adOKdInQ1tZm9OjR/PXXX1hbW5eb2vzrEKrX6enpyOVyUlNTCwS7QkVYpVJ9MC/h/Px8Hjx4wKFDhzAzM2PSpElYWVm9cz0SBLQEKm7v3r1p0KDBR23bUygUBAcHi60eEomE9PR0VCrVJy0YfSwIQpfp6emkpqbi4eFBUlKS6Kmsq6vL33//TVpaGjY2NmJAaWlpiaurK5UrVxbb4ISqrRCECoyfD7nHfz1YFgJxpVKJQqFAqVSSm5tLamoqSUlJpKSkEBUVxdOnT0lKSiInJ0csQFauXFnc19jY2FCpUiX09fU/mkYM/BsIAxRS9MvMzBQ3GSVBbGwsMpmsSLsDlUrFgQMHPmk1WAiCjx07xsyZM0tUSapoECZuiURSKNhVKpWkpKRQpUqVMnsvCuqFNWrUIC4uDm1t7TLbV1QECPYi9vb2hISElLspvbm5Oebm5ly+fFlUbxUUPt8VBIeEhLBy5Uo8PT0/ST/wu6Crq0vHjh3p0KEDOTk5BAUFcf36dTZu3MjUqVMZOHBgiURHygKZTIaZmRn9+vXD09OTHTt2YGZmxrhx43Bzc0MmkxXIusL/LUgKhYLQ0FCuXr3K06dPMTExoVWrVgwZMgQdHZ1Cm6NKlSoxbtw4rl27xm+//Ua/fv1o3Lhxsb3GAoTet759++Lq6sqKFSto164dnp6exMTEsHbtWmxtbZk3b95b+w0FhsrRo0cZMWIENWrU+KCVCLVazZ07d2jYsCFSqZSgoCCsrKzEef7FixdIJJIPqhgtQEdHB7VazcKFC+nYsaNY8RIglUrp0KEDubm5LF26lOrVqxMREcGUKVMKXFOBtj5p0iSWLl2Kr68vvXv3LvKZkkheibfY29szevRoMjIyuHHjBmvWrEFLS4v27dvToEGDct2ACP3EnTp1okOHDsTFxXH9+nV8fHzQ1tamadOmNGjQoEBL0ePHj1EoFAUYOWq1mmvXrqFSqahcuTLp6em4urpWGEX/p0+fUrNmTdRqNc+fP+err74q9TXMzs5GLpeTlJRE/fr1P8h5ClXKKVOmsHjxYrS0tHB1dRXPVVNTk+HDh+Pj48OhQ4fo2bNnuc7Pgv6GsbExcXFxZGRkFCg4CGrMERERItVYS0urQLVMIpHg6upK3759Wbp0KbNnzy7U4iUk7L744gtWr17N3Llzyz3ZKpFIqFq1KhERERgZGZGcnFyo6lu5cmVRtKq8IFBhnz17xv79+8V7VpJKrmBpeOrUKa5evfpR+oCLQ3Z2NomJichkMrG4kZ6ejlKp/K8KhF+nMicnJxMZGUlQUBChoaGitZauri5DhgzBxsYGS0tLzM3NxQS7EOBWNIrx6wm04vDmflygcAtBc1ZWFgkJCcTExBAVFcW9e/dIS0sjLy8PQ0NDrKyscHJywsbGhipVqhRiXJQX/g2EKRwIZ2RklHiTq1arRSuMogbEy5cvxd7gTwFhA3H48GFmz579jwyC4f/ok0qlslAfdlZWFgqF4r2us1qt5sGDB3Ts2FH0GK0om6yyQOhLrVatGgEBAbRs2bJcjy+VSmnUqBEzZ87khx9+oF69eixatIhOnToVmUASFu87d+6wa9cuRowYQa1atSrsWBQWHV1dXerUqUNSUhKtWrVi7Nixb7X8Kc/vr1SpEuPHj6ddu3asW7cODQ2NAlVDIaMcHh7O9evXefjwIbq6ujRr1owePXqIyurFnavQT9qyZUucnZ1Zs2YNDx8+5KuvvioRZVYqlVKrVi2+/fZb1q1bx99//01+fj7Dhg0Tg82iIIiy7Nixg8jIyI9Gi1er1Tx+/BgvLy8Abt68KV5PQan6bfZ35XkeMTExBAQE0LdvX9zc3Dh69GihHkNBCfzSpUts3bqVnTt3FplYEMbp1KlTWbJkCb6+vmLPcFEQxrahoSEdO3akXbt2BAcHc/r0aQ4cOEC9evVo164dlpaW5bb5EsaalZUVvXv3pmfPnoSGhnL58mX+/vtvDAwMaNasGbVq1WLfvn0MHz68wJqcm5vLiRMncHFxQSaTERkZSf/+/SvE/CFY7vXr14+srCzS0tLK5FyQkZGBrq5uqfVJSgshgPPy8sLb25vx48fj5OQkXkttbW0mTpzI77//joGBgehjXR7Q1NTEwcGB4OBgTExMiIqKKiAMJ5zb/fv3UavVSKVSdHV1CwTCwvvc3d1JTU1l6dKlzJw5s9C6I7wnICCA3bt3iyr85QkHBwfu379P1apViYyMxNnZucDrxsbGyGQykpKSSmy1VxyENTQkJIS9e/eSlZVFv379qFmz5juTl8Jacf36dQ4fPkydOnVYsGDBJ9WIiYqKQlNTEwMDAzHASUtLQ6FQ/OMDYSHgS05Oxt/fnwcPHhAdHY1arcbCwgInJyc8PT2xsrLC0NCwwLisCHPah4LQYiWTycQ+Y2NjY5ycnMT3CPuD2NhYIiMjCQwM5Ny5c2RmZmJkZETNmjWpU6cO1tbWIoPhfa/Zv4EwryopbwbC+vr6Jfqs4Ek5ceLEQjdDqVRy6NAhevTo8UksHtRqNTdu3ODQoUP/2EqwAJVKJfYivLlRzczMREdHh9TU1FJ7PwsQ+i6rV6/O0aNH6dWrV3mc9ieDhoaG6MEbHh5ersdWq9X4+/vj6+uLi4sLDg4OmJqaiv7FLVq0KPJZOHLkCHfv3mXGjBniJruiQ+j/P3/+PHPmzCnkX/0hIVyfGjVqMGvWLJYuXYq2tjaurq7ExMRw48YN7t+/j7a2No0aNeLrr7/GzMys1Js9oUo0e/Zsjh07xk8//cTw4cNxdnYu0bEERdSsrCzkcvlbg2i1Wk1cXByrVq3Czs6OmTNnfjR6a1xcHPDKoiUnJ6dAr7BCoSAsLEzsYfpQUKvVRERE4O3tTe/evUlOTsbKyorExETy8vIKUIEVCgW+vr6YmZkxbNgw1q1bx6RJk4oU3RGq9FOnTsXb27uAgNbbIASoLi4uODs7k5yczI0bN1ixYgU6Ojq0bt2a+vXro6enV25BhLAZsre3x97entzcXEJDQ7l27Rpr164lIyODly9fiurdUqmUu3fvEhsbS82aNUXV6NLYG35IpKWlkZKSgo2NDUFBQVhYWJRpIx8VFUWVKlUICgr6oIEwvLoHtra2jB8/npUrVzJp0iSRngqIY+n3339HT0+PZs2alVtCxMPDg3PnzlG/fn3u37+Ps7NzgWNbWFgQGRlJfn6+KMiTm5tbpBhVu3btSE1NZc2aNYwbN67QXCKVSunbty8///wz9+/fL3fdD0tLS44dO0b79u0JDg4u9LqxsTGamprExsa+1/eoVCpiYmLYv38/MTExfPbZZzRs2PCdVGZBCMvf35/du3djbGzMtGnTPghVvDQQKtpyuVxsnRG0eVQq1Sd3VikL1Go1+fn5REZGcvPmTbH/2cHBgRYtWmBlZYWJiUmFY8BVBLz5XOvo6GBra4utrS3NmzdHrVaTmZlJbGws/v7+7Nu3j5SUFCwtLWnSpAmurq5ikrgs4/rfQJjCYlkJCQkl3gwJtOiiqghhYWEkJiZ+EtElYQN/6NAhcYP8Twg8ioNKpSInJwegUOY3LS0NPT09EhMTSyxw9ibCw8MxMTFBqVSSmJiIra3t+57yJ4VEIsHe3l7sOcnNzS2XgEOlUnHr1i327dvH+PHjiYqK4tSpU4wbN45OnTqxefNmmjRpUmAhy8jIYMuWLeTm5jJr1qwy36NPgbi4OI4fP86kSZM+ahD8JszNzZk4cSKLFy8WK4Du7u5Mnjy5TMI8RUFLS4uePXvi6urKpk2b8PDwoHv37sWKzwlKozt27KB9+/Z4eXkRGhrK+vXradGiBZ06dSoQEKhUKp48ecLWrVv57LPPaNas2UfdFPj5+eHs7IyGhgYRERFiTye86muOj4/HxMTkgwbmkZGReHt7M2jQIKpWrcpff/0lLuBpaWniOiL0yUZFReHl5YW2tjb79u1jxYoVTJgw4a3B8KRJk1i2bFmJg+HXP29sbEzXrl1p3749ISEhXLhwgcOHD+Po6Ejbtm2pXr16AZ/q8oCWlhbOzs5YWFjw8OFD+vfvj7+/P3///TdGRkY0bNiQjRs30rBhQ/Ly8oiKiqJt27YVRlAnNDRUDH4fP35M7dq1y5Q0iIyMxNDQELVa/cHE4l6H0G87evRoli1bxpQpU0S/dIGRMmXKFBYtWoSenh716tUrl/vu4ODA9u3b+eyzz9i6dSsKhaLAemFhYSH2TWpra6Onp0dGRkaRx5JKpXz++eds3ryZvXv3MmDAgELjXVtbm1GjRuHj44OtrW25tjwZGhqSlZWFqakp165dKxSs6+rqoqWlRWJiYpkqwoI2ypEjR/D396dz586MGjWqRFRmlUpFREQEe/fuJTMzkwEDBoiMik8NoYVALpeLbAQhEBau0z9lvypQnq9du8aNGzfQ0dHB3d2dCRMmYGJiUiHEoP7pkEhe+SHr6+vj4OBAly5dSE9PJyQkhOvXr+Pr60v16tXp0KEDtra2pU6k/BsIU5gaHR0dXUiQqSgIdjt169YtNPkKFbBu3bp99OyWWq3m9u3b+Pr6Fism8U9DVlaW2OP25kQeGRlJpUqVSExMLNMGQqBF16lTR8zK/zcYujs6OnL06FEMDAyIiYl57+BeqVRy+vRpLl26xIwZM6hSpQpWVlYcOXKExMREcZMcGBgo+gonJCSwYsUKatSoQa9evf5RlCeVSsXhw4fp0aPHWxNj169fJygoiH79+qGhocGWLVsIDw/HyMiI8PBwLCwsGDRoEPv27SM1NRV9fX0iIyMZM2YMjo6OqNVq/v77b86fP0/Pnj1p1KhRkd9jaWlJly5d8PPzY8yYMaW2pCkJpFIpLi4ufPPNN+zcuZOFCxcycuTIAhUEITu7b98+Xrx4weTJk8UedCcnJ+bNm8fmzZvx8fFh+PDhVK5cGYVCwfHjx7lx4wYTJkwoUu31Q0Kg5Xfp0kWct19PUAp2Ex9SRDAyMpIlS5YwcOBA6tWrR35+PvDKqs/ExISEhATMzMxQKBTs3LmT+Ph4JkyYIAZ8ffr0Yd++faxatYrx48cXGQgKSRIvLy98fHw4cOBAsT3Db4OWlhYuLi44OTmJnpd79uwhOzubRo0a0aRJkzKxD4qDWq3m4MGDNG/enMaNG9O4cWOxUuzj48OVK1fIyMjA1NSU2NjYT25D+Pp537t3Dzc3N7HyNmbMmDIdJyYmBhsbG/T19T9aW45EIqFmzZoMGzYMHx+fAtVCiUSCubk5Xl5eLFmyhLFjx77V37qk0NfXx9jYmKysLHJzc8nIyCjA5DI1NUVbW5vk5GQsLCzeGUjK5XIGDRrEkiVLOHfuXCEBLgAbGxs6duzI1q1bmThxYrntyfT19dHS0kIul5OcnFyI1SGTydDU1CQnJ6dYccOiIASFp0+f5vr167Rr144vvviiRB7PghjloUOH8Pf3p2fPnri7u3+Q9aKsyM/PJy4uDrVajYODA/B/dnuv619UZAi930ePHuXRo0e4ubnh5eWFqalpudjT/YviIZVKqVSpEvXq1RN9mR89esTOnTuRSCT06dOnVEmfij/aPgLepEYnJSWV2EPtzp07oielALVaTXR0NDExMbi5uX30Dd/du3fZvXs3U6dOFemx/3QkJyejoaGBjo5OocEdExODtrY2BgYGZcp2qtVqnjx5Qt26dbl37x4NGzYsr9P+pKhSpQoJCQlYWlq+Fz1a6C/as2cPd+7cYc6cOWJyRVdXl0aNGnHhwgVkMhldunTh2LFjYi/TwoULadOmjRgk/pOQmppKWFgYdevWfesz1KBBA65evcqGDRtQqVR07twZMzMzxowZw8OHD2natCnm5ua0bdsWR0dHRo4cSVBQEL6+vqK64pkzZ4iPj3/r2JNIJDRp0oTo6Gjy8vI+2HMtkbxSGR41ahSenp4sWrSIixcvolQqUavVBAcH8/PPP6OlpcW8efMKCLEJvacTJkygVq1a/PLLL9y+fZslS5YQGhrK3LlzP3oQDK8C3bi4OOzs7FAoFDx+/LiAYm5kZCQKheKDMEGE9WDp0qUMGDBA/F4NDQ3x2XR0dCQoKAiFQsGOHTuIj48vFOzK5XL69u2LhYUFq1atEhkyb0J4LidPnkxQUBD79+8X6eulhVQqxcDAgJYtWzJ37ly8vLzIzc3lr7/+YuHChdy6dYvs7Gyxf7GsiIiI4NGjR6KVlUQiQVtbmypVqpCens7nn3+Ou7s7iYmJvHz5kuPHj3PixAliYmJEL81Pgfz8fIKCgnB1dRUDu7IwR5RKJXFxcejq6n5wWvSbkEgk1KlThwEDBrBkyRLRw1d4zdramnHjxrFy5UrCwsLK5Vq7ubnx6NEj7O3t8ff3L3BMHR0dKlWqJApM6ejovHP8amlpMXbsWM6dO8fjx48LnaNEIqF9+/bk5eWJldvygFQqxczMjPT0dCQSSaFeZiEQFp6Rd0Hojzxz5gw//PADubm5fPvtt3Tt2vWdujWCENbhw4f5+eefMTU15T//+Q9NmzYtdxbH+yI2NlZUOxZ8wlUqFenp6aIgZEWGSqXixo0b/Pjjj+jp6fH999/Tv39/LCwsSlwBfvLkCXv37n3vcwkKCmLbtm3lNqZTUlKKZWB8LDx+/Jj9+/eX6L1Ctbhp06Z888039OrVi507d7J27VoyMzNLdF0q9mj7SHi9IixkeUrSaxoXF0deXl4hqwO1Ws2xY8fw9PT8qBUwtVrN/fv32bFjB9OnT//H9GGWBMnJyeTn5xfqsRB6DjU0NMpsAJ+WlkZubi5GRkYEBARUaBGn0kDIHtvY2ODv71+mYwgehevXryc2Npbp06djaGhYIPBp3749N2/eJCsri1q1apGcnMzx48fx9vZm2LBhtGrV6p1iHhURISEhWFlZvfMZ1tbWxtHRkZycHPbs2YOGhgZaWlpoa2sjl8vR0tJCKpWK3n7a2tq4ubkRHh5OcnIyMTExVK1aVfTUe9d3CSIzHxpSqZTGjRszZ84crl+/zrJly9i9ezerVq1i0KBB9O/fHy0trSLFm+RyOZ6enrRv356JEyeSnJzMmDFjMDAw+CTjICwsDBMTE/T09EhJSSE3N1cUNFKr1eIG39rauly/V61WEx8fz9KlS+nTp0+BKrREIsHZ2ZmAgABsbW0JDg5m586dJCQkMGHChCJVbuVyOf3798fExOSdwbCOjg5TpkwhODiY/fv3iz7UZYHQ12thYUG/fv348ccf6datG9euXWPBggWsX7+ewMBA8vPzS70hUygU7N69m169ehUI/IUqsaamJq1btxYZBx07dmTEiBEkJSWxdOlSvvvuOw4dOkREREQBD8yPAcEWx9jYmICAAGxsbMrEJsrLyyM3N5eUlJRP4o0skUho2LAhvXr1YtGiRaK4k/Cak5MTw4YNw9vbW6zkvc931a1bF39/f2rXrs2DBw8KvK6pqYlcLherwLq6uu+8rxKJBCMjI8aPH8/GjRsL2C8JkMlkDB06lMOHDxf4fe+LatWqifZZ6enpBV6Ty+UYGxuL7UnFQegvvX37Nt999x2BgYHMnDmTgQMHFlhvi/tsXl4ely9f5rvvviMxMZH58+fTo0ePT6IG/S6o1WoCAwPR09Mr0NYjMI0qekVYrVZz6dIlTp06xaxZs+jVq1eZHCRevnzJrl27UCgUYjJPGAdC0lmpVIp/BAGuN5+F2NhYNm7cKCoxv/m51z8jKDYL/37zWCqViq1bt/L48WPxfcJ7hPe/fq5v/vv1c339769fO8Fi6fX3vPkdgYGBpU4SCGtUrVq1WLBgASYmJvj4+BS7Rr6Of6nRFOwRFny9SpLVffToEa6urgUqXWr1K5ufFy9elMlCoawQlCt37NjBtGnT/quCYCE5IQTCr/8uhUJBYmIiRkZGZd5APH/+nOrVq5OTk4NCofhH2ya9Dk1NTapUqSL2CpW2R0lYmFavXo2xsTHDhg0rcpNnbGwsCmU1a9YMU1NTli9fzpo1a6hWrdo/dhympKRgZGRUovPX0NBg6NCh/PTTT2hqaha5yXq970mopF+8eBFbW1uqVq3K8+fP3/k9Qu/eh/KlLOr7zMzMGDhwILNnzyYxMZGffvrprarqwmJ29uxZLly4wMqVK7ly5QorV65kxIgR79zYlTdep6/Cq2xzzZo1CyQdIiIi0NTULNd5U1gLlixZQo8ePWjUqFGhYzs4OLB3717at2/PyZMn6dChAxMnTnxrn7JABd26dStr165l9OjRRb7/9WDYx8dHtFZ6n35y4fw1NTWpW7cuderUISUlhUePHrFv3z7S0tJo0KABzZs3p0qVKu+sjghsnKysrELXJzIyksePH1O5cmXq1q3L7du3iY2NpUuXLri4uODi4kJ+fj5RUVHcvXuXNWvWoFAoqFevHo0aNRKTWB9yrPn5+Ym2Xw8fPnwne6Q45OXlIZVKSUhIoE6dOh/gTN8NgXGSn5/Pn3/+ycyZM8V9kEQioV69emRmZuLt7c2MGTNKPDcWBTMzM9EKKyQkpECfsJaWFoaGhkRHRwOgp6dXIkaDkPQdPHgwy5cvZ+7cuQVapQSqd6dOndi+fTsTJ04sl35ZOzs7rly5IlopvW6/JlSMnz17RmpqaqHefiEYEDb+2trajBkzBltb2xJZISkUCp4+fcq+ffswMzNjypQpVK1atcKvuU+fPhUVxF+3AUxLSwOoEH3MxSEhIYELFy4wdepUsZpdFhgZGZGdnc3JkycJDg5m9OjRXLt2jevXr2NgYMCIESO4desWarWaoKAgBg0axJkzZ4iMjKR9+/bUqlULeGWDmJ+fz9WrV7lx4wZt2rTh0KFDdO/enVOnTtGvXz92795N37592bVrFz169ODEiRP06NGDO3fuYG1tTffu3YFXlla+vr6ig8LJkyfJzc3Fy8uLx48fExAQgKamJlZWVhgYGPDw4UO0tbUxNTWlYcOGXLx4keTkZGrWrMm5c+do3rw5Hh4eorBhbGws586dIyEhgVq1anHmzBn69OnDgQMHmDNnDiEhISLLqKwQWih79+7N/v37OX36NJ999tlbn4mKm3b5iMjPzxcn4dzcXPLy8t6pGi2IBjVu3LjQa8ePH6d169YfTcxDrVbz6NEjtm/fzuTJk//RwUdxSExMBCjUq5mXl0deXh5paWkl6usuCnfu3MHNzQ1/f3+cnJw+icL3h4BE8koZNDMzk8zMzFLTXZKSkli0aBG2trZ89dVXb610dO3alVOnTrF582bS0tJwcHD4ID67HxN6enolotYImUxdXV1mzpzJ2bNnxQXdxcWlgHWGg4ODeLz27dtz5swZUZG3pPTSzMzMEqvavy8UCgWXLl3Cx8eHyZMni4rEBw8eLDbTmpaWxsqVK/Hz82POnDm4ubkxceJEnJyc+O2333j58uVHrdopFAqx+iS0jnh4eIhjU/Bf1tXVLZPtTXFITExkyZIldOnShaZNmxb5LFSpUkUUwxGsp0ridyqXy/nqq6/Q09Nj/fr176wMe3l5ERISgq+v73tVhos6fuXKlWndujWzZ8/m66+/Rk9PjzVr1vDTTz9x4sQJ4uLiig1kcnJy2LdvXyGRI6VSye7du2ncuLFIF1YoFGRmZuLu7i6+T0NDg+rVq9OrVy8WLFjA5MmTMTAwYNu2bXz33Xds3rwZPz8/MjIyyn3MqVQqHj58SP369VGr1bx48QJHR8cyHSshIUH0ov0YVmLFQSqV0rJlSzp27Mhff/1FUlKS+JpEIqFp06a0bt2aZcuWlZh2WNz3uLq6EhYWhq6urhj0AmLLgKC0rKurW6iyVBwkEgn169fH3d2dLVu2iH34r7/eunVr0tLSuHv3bpnO/U2YmZmRkJBAtWrViIiIKPR9xsbGKBQKUlNTC7ymUqkICwvD29ubPXv20KtXL77++usS+QGrVCqCg4NZtGgRx48fZ8iQIXh5ef0j9n5q9SuruqysrAKK4YLdELzdm/ZTw8/PD0dHx3JpYdDW1qZz585ER0dz9epVDAwMaNu2LVu3biU8PJzLly9jYWFB7dq1uXTpEocPHyYmJoa9e/fi7e3NH3/8QW5uLnK5HHd3dw4ePEheXh7nz5+nQYMGnDt3Dh0dHdLT0/Hz8+PatWvo6uoil8u5e/cutWvXZuvWrdy8eZMFCxbw/Plz9PT06NOnDyYmJrRs2ZK7d+/y+PFjNm/eTLt27fDz80OtVrNt2zaaNm0q3sutW7fy6NEjHj9+zN27dzl37hytW7cmIiKCBQsWcO3aNXbu3Mnt27fx9/fn1q1bnDt3jtq1a3Pz5k1evnzJ6tWr6dGjRyEbsrJAJpPRsmVL7ty58873/hsI8yr4FTb5ubm5aGpqvnMiSk5OJiUlBTs7u0L//+TJkyItZD4EhIz6li1b8PLyKtCv99+EmJiYItW58/LykMlkJCcnl6mSm5+fT2hoKA4ODjx48KBA3+B/A5ydnQkNDcXAwKDApuZtEBaq33//nebNm9OrV6939veamJjw5MkToqOjmT17Nk2bNuXixYufrHevNFCpVBw8eFCcpF++fElycjLVq1cnPDz8nYHDjRs3ePjwIfv378fc3JyZM2dSo0YNALy8vHj69CnLli0jPj4eZ2dnfH19efToEcHBwXh6eiKXy7lw4QLx8fHcvHnzrd8lCAgJYjLp6elkZ2eTn5+PSqUqt2sCryriy5cv5/r168yaNYumTZtSo0YNvvnmG+Li4li0aBGxsbHiPRYy17/88gu2trZ4eXmJ7QoaGhp07dqVQYMGsWLFCi5dulTu51schLYKc3NzsrOziYuLK1C1USgUpKWloaurW26K0YmJiSxevBhPT09atGhR7Hqiq6tLZGQkYWFhNGnSpEQ0LgFyuZzBgwejpaXFxo0bi6VeCj3DEydO5OXLl+/VM/w2yGQyzM3N6datGwsWLGDUqFGkpaWxaNEiFi5cyKVLl0hJSSkwXi5fvky1atUKeXP7+fmRlpaGUqnEw8OD5ORkkXL/5por/EbBMq5Lly7MnTuXWbNmiXZ4//nPf/D29ub69evlRovNyckhOjoaOzs74uPjkUgkZWYTRUZGYmZmVkA5/FNBKpXSpk0bWrduzdKlS8VeXeG19u3b4+rqyooVK95K930bJJJXHr8PHz7ExcWlQF+vUNkV7M60tLRKlbyRSqX06NGDnJwc/v7770L3WktLi6FDh7J79+5CVOaywMTEhKysLIyNjYukZBsZGaFUKsXkqFqtJjY2lrVr17JixQqaNm3K3LlzqV27dokYFFFRUSxfvpyNGzfSsWNHZs6ciZOTU4Wuor6OpKQk0QXkdRafoL4sPOcVFYaGhqSlpZXLHCLQebW1tVEqlYSEhBAZGSlqbbi7u7NhwwaysrIIDg7GxsaG2bNnM3HiRKpWrYq1tbXYdiaVSlEqlSILRiqVolKpkEgk4rnK5XLx/Wr1K59uhUKBgYEBtra2BRLs6enp3Lt3D21tbdRqNcOHD+fy5cvY29vTuHFjhg4dyt27d8VE6LNnz2jUqBG///47Xbt2RSaToaOjg6GhIba2thgaGvLs2TMaNmzIr7/+Sq9evUQavGCP+uzZM7GFrDyQlpZWIgHdijvaPiKE4Pf1v78rGHr27BlOTk6FaNGnT5+madOmH8X+QK1W4+fnx/r165k6dapoffDfiNTUVHJycgp5RwoWC4KiaGkRFRWFtrY2+vr6hIeHiwqG/y0QstVCQFy9evW3vl+tVvPy5UuWLVvGgAEDCgnBFfX+pKQkFi9ejIeHBzo6OmhqauLp6ckff/xBp06dKozNSXEQevo3btyIVCrF1NQUS0tLzMzMSE5Opnfv3m+lPDZu3LhAhVHwRxX+PmnSJNRqtbhR6du3L3369CnQN/3XX38BvDUBJzA//v77b06fPo2GhgYaGhpoamqKNLPly5e/lyiZUJV+9OgRW7ZsoUOHDnTs2LHABk1fX1+kcf322298+eWXIi3qxIkTjBgxAldX10LXSyqVUqtWLWbPns2KFSsIDQ2lf//+H5S+qla/8rx2dnZGJpMRGBhI1apVC4zJ9PR08vPzsbCweO/eNKGNY8mSJbRv355WrVoV+9sUCgX79u0jISGBzp074+/vT0hISIlbPIQN49ChQ9m0aRPr169n1KhRRfa0C8HwpEmT8Pb2Zu/evfTt2/eDbDiFoNTa2pr+/fvTp08fgoODuXTpEkeOHKFKlSq0aNECa2trTp06xezZswtc99zcXPbu3Uu/fv3YuXMnU6ZM4d69e8hkMlGZviTXxdjYWAzosrOz8ff35+bNm/j6+mJoaIiHhwf16tXD3Ny8TBoGkZGRot3WvXv3sLOzK7NYY3R0tKiu/jH2Du+CEPAqFAqWLl3KtGnTxP5+mUzG559/zvbt21m3bh1jx44t05xTvXp14uPj6dChAydOnKBr167iaxYWFly5cgV4RcMvbe+5XC5n5MiR/Prrr9jZ2eHi4lLg/larVg13d3eOHDnCgAED3mv+EbyOtbW1iY+PJz8/v8AYNTExEWm/GRkZHD16lDt37tChQweGDh1apM7C6xB+d2pqKocOHeLx48d07dpVvO7/tD1faGgoRkZGZGRkFKCK5+fnk5GRgVQqrdDCmq6urhw7dow7d+7g4eEBUKZ7YGFhgZmZGZcuXcLKyoqmTZvy008/4e7ujrm5OeHh4fj5+dG3b19yc3Pp3r07kydPZtq0aUyYMIE+ffoAcPToUZKSkggMDCQtLY1r166RmppKYGAgKSkpBAUFERUVxYMHD0hKSuLFixdERESQmZmJnp4e8fHx2NjY4OrqCkCNGjUIDAxEKpWSmJiIqakpKpWKy5cvc+fOHTQ1NalRowZ37tzh8uXL4rw8dOhQFi5cyNWrV/Hw8CArK4uMjAwcHR1FpsyQIUP4z3/+w61bt2jZsiVpaWkEBQWRnJxMfHw8n332GYcOHRIT0sI5lhZqtZrU1FR27tzJF1988c73/xsIQ4GJKzU19Z09bAItukOHDgXel5aWxu3bt1mwYMEHn5zU6leG5OvWrWPKlClUr179HzchlgaZmZniZu51CN6LGRkZZaKLPnnyhNq1axMdHY2hoWGZHrqKjEqVKqFWq7GwsCAwMJCWLVsWO06EMbV27VpGjRpVZDDz5vvDw8Px9vamR48eeHh48OOPPxIfH0+VKlWoXr069+/fp1mzZhVqbAqiEUKWPiwsDEAUboiOjiY2NpYaNWowZMgQDh48iKOjY7Fj423iHsLG8XUUtVkuSUCSnp7O8ePHWbp0KT///DPnzp0rUFV9vd+qLBB6wvfu3SvaIhU1rwi/qUWLFtjb27Ns2TI2bNhAtWrVmDdv3lstiCQSCaampsyePZtt27axaNEixo0bV2ahu5L8pvv379OqVSsAbt++jbu7e4HrFB4eTl5eXon68t71XRkZGfj4+NCyZUvatm371iD4wIEDhISEMG3aNAIDA7GxsRFFu0p6LYSgb9iwYWzcuJF169YxcuTIIjPqr/cML126lP3799OnT58PWn0RgmKhpzcnJ4fnz59z5coVvvvuO6pUqUJISAh6enro6OggkUi4efMmxsbGaGhooK+vj5mZGREREfj5+TF48OBSf79EIkFPT4+GDRuKXsShoaHcvn0bHx8fUbzJ3d0da2vrEgUXwriqW7cuUqmUBw8e0Lx58zKNYWEebdasWYUSN5JKpXTq1In8/Hy8vb2ZOnWquMbK5XIGDhzI6tWr2bNnD/379y/1ONLS0sLa2prs7GxSUlLIysoS51hLS0vi4uLIyclBS0uL3NzcUgXCgpbCqFGjWLNmDfPnzy8k8vjZZ5/x/fff06ZNmzK3VQkQqsIqlapQICxU+I8fP87Jkydxc3Pj22+/LZFwoFqtJjs7W9RbaN68Od9///0/uu3o6dOn6OrqYmBgUOA6ZWZmolAoKnwgrKmpyejRo/H29iYsLIyuXbuKc1dp4OjoyM8//0xcXByNGjVCW1ubuXPnkpOTQ6tWrTAwMMDe3p709HRsbW2Ry+Vidfj1gkatWrVYs2YNlSpVYvPmzQA0a9YMQ0NDNmzYgJmZGXPmzEGhUNC7d29R00Umk6GlpYWrq2uBPcm8efNE8djGjRuLz3z16tXp3r27KOrWq1cv2rVrh0Kh4MGDB4waNQonJye0tLTIz8/HxcWl0JzQrFkz1q9fj1wuR61Ws2nTJgwMDFi7di1mZmZ06NCBly9fYmJiQseOHUtdRBH2ds+fPxcT+TVr1nznvfk3EOYVvVaYgOPi4t5JTcrIyCA6OhonJyfx/9RqNVevXqVu3bof3P5ArX5lRr5+/XomTpz4SexIPiYEGo1QAXsdsbGx6Ovro6OjU+pNrNDj1adPHx4+fEitWrX+MfSikkJDQ0NUZoyIiEClUhX5G1UqFXfv3mXXrl14eXkVoiq+CYGSv2nTJoYMGULdunUBaN68OadPn2bw4MF06dKFzZs34+Hh8cn8gwUVxtzcXJKTk3n58iWhoaGEhoaSkZEh9qNZW1ujo6NDTk4OVapUYdSoUYwdOxYrKyuOHj3KihUrmDhx4ierbmdkZLBy5UpatWpF69atcXFxYfbs2ezcuVMUmtHS0iIgIAAHB4dSVwpUKhUBAQFs3ryZ+vXrM3fu3BIt7vn5+SgUCgwNDcUM8LuEBiWSV9Y4w4cP59y5cyxcuJDRo0fj4OBQ7vNYbm4ukZGRODo6olQqCQoKomfPnuLrQhsA8F4iM8KGdfny5dSvX79QkvR1KBQKDh06RHBwMJMmTSI6Opq9e/fSvHlzbty4UewzWhyEYHP48OFiZXjEiBHFCmhpa2szefJkli1b9lGCYeF74ZUVTv369alUqRIhISH07duX27dvs3fvXqytrXFzc+PAgQNMnz6dkydP0qpVK1QqFUFBQaSmpr4X60n4nJaWFs7Ozjg5OaFQKIiLi+Phw4fs2rWL1NRU7O3tcXNzw9nZWfT0ffM7VSoVT548Ydy4ceTl5RERESGyQEoLlUpFSkqKGLxVJMVcqVRKt27dUCgU+Pj4MGnSJHFjrKGhwciRI1m8eDEnTpygW7dupTp3qVSKu7s7T58+xdzcnBcvXohCYVWqVCEvL4+MjAy0tLRK7cMLr+63o6Mjbdq0YdOmTXh5eRV4rnR1denSpQsHDx5k7Nix77X229nZER4ejlwuJycnBz09PVHMKjIyksDAQCpXrswff/whWg++DWr1KxulmzdvcuzYMWrWrMncuXMLiYX+0yAwzvT19Qv0B8OrRK8QBH+q/UJJIIiuzZ49G19fX77//nu6deuGm5tbqRIUQivF6+0Ub66d+vr6WFhYiP8uSsPCzs5ObBd5veUHEF0QimonKQ6vn4PwuaioKAICAsjKysLFxQVPT0/8/f3FPm9BhPH1AL0oBwapVFrgHAXHndf/T2grKw2EZy08PJxDhw6RmprKsGHDCjFBisO/gTCvAmHhwUtKSnprRQMQs/evZ92zs7O5dOkS06ZN+6DnqlarCQgIYN26dYwbN+6DbB4rGjIyMlCpVGhraxeYIIVeG319/RLZXb2J9PR0sRd0165dDBkypDxPu0JAIpFgb29PRkaGKJplaGhY4D0qlYoLFy5w6tQpZsyY8U7vaZVKxdWrVzl69CheXl4FEjHNmzfn559/JjMzExsbGzQ0NAgMDHxndbk8IGwe0tLSSEhIICgoiLCwMKKjo0XKYfXq1bG1taVt27ZUqlQJHR0d5HI5wcHBbN26lebNmzNt2jQxKZKSkkJMTAyPHj1i6dKljB49+qNuRoQxvmbNGurXry/ayFhaWrJs2TKsrKzw8fGhXr169OvXD19fX3Jzc2nfvj3u7u6ihdbbkJWVxZEjR3jw4AFDhw7F2dn5nRtahULBhQsXOHnyJEOGDMHV1ZVHjx7h4+NDjx49aNGixTs3ljKZjA4dOmBlZcXq1avp3bs3jRs3LtdAIDExUaw2Cm0Qb242Xrx4gaam5ntZJ+Xm5rJy5Urs7e3fGhAolUoOHz5MQEAAkyZNQldXFysrK5KTk9HW1iY1NbXUgbAAoTK8efNmNmzY8NZgWEdHh4kTJ7JixYqPFgwLyM/PZ/v27Xz55Ze4u7vTuHFjMjMzCQgIwNvbm4SEBHbt2sWTJ0/o1q0b+fn5hIeHi4JE5QUhgVC1alWqVq1Kp06dSE9P5/nz52JwXqlSJerVqydSqAUav9DnaGpqSlRUFHp6emVOgAsWJfHx8eVu31UeEKjQvr6+YkJQKBxoa2vj5eXFokWLMDIyKrU2So0aNTh06BDt2rXj3r17YiAsJLfT09PR1NQkLy+vTOcukUjw9PTkyZMnXLhwgXbt2hWoCjdr1oyzZ88SERHxzraht31HtWrVuH79OmZmZiLN/eXLl+zdu5e0tDSRnv2uIFhI3D548IBDhw5haWnJlClTsLS0rFAJkrIiPT2d9PR01Go1Li4uBV7LzMwUrbPKS6vhQ0Ho4R0yZAgRERGsXLmSjRs30q5dO1q1alUi28V/EiwtLenQoYPI2tDS0sLOzo7MzExRW+NTxCGCwNqTJ0+4ePEiKpWKTp060bBhw1K1XP0bCFNQNTolJeWtGYnX1aKFiyzQpKpVq4aZmdkHHRDBwcGsXr2asWPH4ujo+F8fBMOryTM3NxcTE5MCFWGVSkVcXBw6Ojpl2iCFh4cXyDyXp2JsRYKjo6OoTpyWllYgEFYqlRw9epS7d+8ye/bsd1JUhfffvn2b6dOnFxrvRkZGuLq6cvXqVTw9PencuTMnTpwoET2lJHi9KpCVlUVCQgIxMTEEBAQQERFBcnIycrkcExMTHB0dad68OTY2Nujr6xcQingT1atXZ//+/bi4uKCpqYlSqeTKlSscOnSIFi1asGrVKm7evMlvv/1Gr169aNy4MTKZ7IP2tioUCq5cucLRo0fp06cPTZo0KbAZMjAw4D//+Q+WlpZoaWnRsmVLmjdvTnh4OMePH+fYsWO0aNGC1q1bF9nuoVarCQ0NZf369djZ2TF//vx3Bs5qtZr09HS2bNlCVlYWc+fOFROHDRo0wNramtWrV+Pv7y+qGr8NEokEV1dXpk+fzrJly4iJiaFHjx7lEpSp1WqePn2Ki4sLMplMtE1604c8JiYGiURS5uc/Ly+PdevWYWZmRu/evYsNYlUqFUePHuXp06dMmzZNrB5oa2ujoaFBfn4+EomErKysMgVVr/cMC8Hw22jSgoCWj48P+/bto1+/fh+FEXPnzh3kcjkNGjQQz0VfXx9ra2uMjY359ddfOXr0KDk5Ofz1119Urly5wPpaWhu4kkImk2FkZESjRo3w8PAQK7337t1j9erVKJVKnJyc8PDwIDQ0FGdnZzQ0NHj8+PF7WR4JyZrk5OR3MnE+FWQyGb1792bv3r2sWrVK9LmWSCQYGBjg5eXFwoUL0dfXp379+iX+DUI7kqGhIZcuXUKpVCKTycR5IzMzE3Nz8zL5UwsQKte//PILLi4uBfYKWlpadOnShUOHDuHl5VXmYNPCwoL4+Hhq1qzJo0ePuHLlCiEhIfTp0wcnJye8vLzIysp66zGUSiX+/v7s27cPLS0tRowYIbZrVMQxURbExcVhYGBARkZGIWE5wdXinxAICxDssc6dO0dISAiHDh3C0NCQRo0a4enpSaNGjUQHDShbL3FFgJA8fd3RQFtb+6PeJ+H5VyqVxMTE4O/vz927d0lOTsbFxYVBgwaJlO/SXud/A2EQJ19Bte5t1L68vDxevHjBwIEDxYudn5/PyZMnGTFixAfdGL948YJly5Yxbty4QrSS/2YI6qFGRkYFFiqlUklOTg7p6emlTgoI3qINGzYkKCiIatWqlci25J8IS0tLUTArODiYatWqif6Fe/bsITQ0lJkzZ6Kvr//Wa5iXl8eOHTuIiYlh9uzZRb5fyMD7+PjQtm1bateuzf79+4mJiSm1R6sw8alUKjIyMoiKiiI8PJyAgABiY2PJzs5GX18fS0tLnJ2dadKkCZaWlgWCuZJ+n4aGBnXr1hWpslu2bEEulzN9+nSxQt62bVtcXFzYtm0bp0+f5vPPP6d27drlKliiVqvJy8vjwYMHbNq0CU1NTebMmVNklV4ieeWXN3nyZPHfgnDF+PHjSUhI4PTp0/zwww+4u7vTqVMnkTmhUCg4efIkFy9e5KuvvhLFwN4VBAcFBbF27VqaN29O165dC4hoCf2/s2bN4sCBA/zyyy+MHTv2nUr2QhA6d+5c1qxZw6pVqxg5cuR7Z5kF+n6XLl0AuH//fiHhDIVCQUZGRpkXdYVCwdatW9HU1CxkAfQ6VCoVp06d4t69e8ycObMAhU6o8CckJIgVxrJWF18Phjdt2sS6desYPXp0sQJaOjo6TJ48maVLl35QAS0BGRkZ+Pr6Mnny5AJzuUqlYteuXXTp0gUzMzMSExP54YcfsLa25sSJE+Tl5YlK3E2bNqVevXqij215r4PCMbW1tXF0dMTBwYG+ffuSlJTEkydPOHnyJEeOHMHDwwMrKyuuX7/O8OHDy/x90dHRmJubEx8fT/Pmzcvxl5QvpFIp/fr1Y8eOHaxZs4Zx48aJVRdTU1MmT57M4sWLMTQ0LHFAL5PJqF+/PhERESiVSuLj47GwsBAt5VJSUqhatWqJ7ZOKg4mJCQMGDGD9+vXMnj1bfNYlklfq1cePHycqKqrM7REmJiYkJyfz7Nkzbt26xZQpUxg+fDiampooFArRGuvNJI4gThgSEsLevXvJzs6mX79+ojf1f9se7/nz56Io3JtznFDwEHpXKypeV70XKvj6+vqiynlKSgphYWFiIrpevXpUrlwZJycnXFxcqF69uthyAf/c4PhD4vVrLHjFv3jxAj8/P6Kjo9HS0qJGjRr07NkTe3t7cc0q67X8NxAGkYqmVCpJSUl5qwVCaGgoJiYmYp+MoEoqZLQ/xKAWguDly5czduzYMnHo/8l4PRB+/foqFAqxv6q01Zz8/HwCAgLo3Lkzhw4dws3N7b92QjI2NkapVGJiYkJwcDCtWrUiPz+fzZs3k5WVxZQpU97a+yr0P65btw4NDQ2mTZv21oXKyspKtFNq0KAB7dq14+TJk2/dLAqBuWBlExISQmhoKC9evBC9BU1NTalWrRrNmjXD3NxcVGwtr0pzdnY2x48f58aNG/Tt2xd3d/cCQYFEIqFq1arMmDGDgIAAjh07xu7du6lbty5NmjShatWq4sawpOckiDvk5+cTGRnJjRs3ePToEZaWlnzxxRecP3+e7du306dPH2xsbApV7Ir6HuH/zMzMGDRoEN26dePs2bP8+uuv1K1bl0aNGrF3714qV67M/PnzqVSp0jvPNy8vjzNnznDhwgVGjBhBjRo1iv1uTU1NvvjiC5ycnFi6dCmff/45zZs3f+vGTiJ5JWg0ceJE9u/fz19//cX48ePfS0RLqVQSFxeHlZUVaWlppKSkFOqhSkhIID8/nypVqpSayqZQKNizZw9ZWVmMGTOmWIEXlUrFuXPnuHbtWqEgWICDgwMvXrzAysqKyMjIYq9vSSBQfocNG8amTZtYu3atmFgo6r2CgJZQGe7Tp88HEatRq9WcPHmSevXqFfI7DQgIICYmhjFjxhAbG0tWVhZ2dnbI5XKxely3bl169uzJzZs3OXXqFLq6unh4eODm5kblypXfaT1TVgjPs6mpKW3atMHDw4Po6GgGDBjA3bt3OX/+PAqFglq1atGgQQMcHBzQ1tYuUSAj2OGYmpoSFhZWoVlJQqLtyy+/ZNu2baxZs4YxY8aIqsc2NjaMGTOGZcuWMWPGDKysrN75+yUSCfXq1WPdunU4ODgQFBSEhYUF2tramJiYEBMTQ61atd7bqkYikeDm5sa9e/c4ffo0PXr0EM9NW1ubDh06cPz4cUaPHl2q4wqJy6tXr3L79m26du1KkyZN6NixoxjoyOVyTE1Nef78OdnZ2WJ1UKVSERMTw/79+4mOjqZnz540aNCgQgtFvQ+Etj5hr/x6IkxgGmVmZqKvr18hroEQ6Ar7kszMTCIjI4mOjiYiIoKoqCgyMzOBgmKXmpqaNGnShKlTp+Lp6YlUKiU6OpqgoCAuXrxIdHQ0EokEIyMj7O3tsbGxoWrVqhgZGYnz3YdI8FVUvH6Ns7OziYmJITw8nJcvXxIdHU12djZGRkbY2dnRunVrqlatSuXKlcu1VeDfQJhXGybBTysvL6/YyqBarebOnTs0bNhQ3JCqVCqOHTtGt27dPkgmXcgWrly5kpEjR/7PBcEA8fHxyOXyQn3ASUlJaGlpkZGRUchW6V0QevEMDAwIDg7m888/L89TrlCQSqUYGxtjaGjIvXv3SE9PZ9OmTWhrazNu3Li3BrWC7cPy5cuxs7Ojb9++71ykpFIpXbp04ciRI9SrV4/GjRtz6tQpUlNTMTIyEjcP2dnZJCcn8+LFC0JCQggPDyc7OxstLS2qVq1K9erVRZVDfX39D2azo1Kp8Pf3Z/v27Tg7O79T0VMQfGjfvj3btm1j/vz5tG3bFgsLCypXroytrS1WVlZYWVmhr69fgKojUJ7T09OJjo4mKiqKly9fkpKSgrGxMQ0aNGDmzJki3bhZs2bcv3+fdevWUaVKFXr27Em1atVKtQgYGRnRu3dv2rRpwx9//MHSpUtp06YNY8aMeWcQLLBkNm7ciFwu55tvvsHIyOid3ylQpatVq8a6devw9/dn4MCB71R2F4Loc+fO8ccffzBhwoRCQVNJkZSUhKamJnp6evj5+WFlZVVorMfExJCXl4eVlVWpaMFKpZIjR44QFRXFhAkTin2GBNuJCxcu8PXXXxc5roQg4tSpUzRt2pSnT5+W+rcWBSEY3rx5M+vXry82GIb/6/VcsWIF+/btK9FzXhoIFkE3b95k/vz5Ba5Bbm4uu3fv5ssvv0RTU5OLFy/SokULcT0NDAzEwsICZ2dnatasSc2aNcnNzSUqKopbt26xdOlS5HI5derUwc3NTQykPtRGUmDVuLm5oaGhQVZWFgMGDODZs2f8/fffbN26FVNTU+rVq0fdunUxNjZ+q0VOSEgIHh4eojVJRYeGhgaDBg1iy5YtYi+6MP5r1KjBoEGDWLZsGTNnzixRIsvS0pL8/HxsbGxE9W1hjo2NjS23+yiVSvniiy/45ZdfaNiwYYHqb6NGjTh58iRJSUkl9oJWKBT4+fmxd+9ezM3NadOmDR06dODIkSOoVKoCFT8TExMx0NPV1SUhIYEjR47g7+9Ply5dGDVqVIVSDP8QyMnJISYmBisrK9zc3Aq9npaWRl5eHjKZ7KMHwoKPbU5ODmlpaYSHhxMVFUVUVBTx8fEoFAo0NTUxNzfH0tKS2rVr06lTJ/T09NDT02PTpk2cP3+e+vXr4+XlxWeffVZgbRUsFTt27Ci24glWRg8ePODkyZNkZmYilUoxNDSkSpUqmJqaYmZmhqWlJXp6emhqaoqCsR+yLas8IST6FQoF+fn55Ofnk5OTQ3x8PHFxccTHxxMfHy8mpGUymVjw8PDwwNLSEgMDA3R1dT9oj/y/gTD/R41WKpVi1rMoCEqRU6ZMAf7P9iAzM7NQ4395QOjhW758OUOHDv0ogkMVEXFxcajV6kLZ8tjYWAwNDUlISCg1rfHp06c4OzuTkJAgZmz/m+Hk5ERCQgLJycksXrwYBwcH+vfv/9YFR61WEx8fj7e3N82aNcPT07PEyZ6aNWuya9cusQ/bxsaG7du3Y2FhQXh4OLGxsajVaipVqoStrS2urq507doVQ0NDUTDjY4z11NRU9u3bx8uXLxk8ePBbhaIUCgXPnz/n9OnTHDt2jLt375Kenk7Xrl3566+/kMvlxMbG8vjxY7799lsiIiLo2LGjGPwLxzhy5Ajp6enMmDGD2rVr4+HhgZmZGTo6OoXmHi0tLRo3bkz9+vW5c+cOK1asoHr16nz++eclppqr1WoSEhLYsmULZmZm+Pr6cv/+fX7//XcaNWpEp06diu0hfvLkCVu2bKFjx460bdu2VMk+ieSVuubXX3/NoUOH+O233xg3btw76YcymYz27dtjYmLC4sWLGTVqVKl7zAUWjbW1NXK5nDt37uDu7l7oPeHh4Uil0lJRIlUqFWfOnOHp06dMnTq1WDaFWq3m+vXrnDx5kunTp781KKhWrRrx8fEiNbq8INCkt27d+tZgWKgMT5gwgZUrV4qBaXkld1UqFTt37uSzzz4roFGgVqu5efMmBgYGuLq6kp2dzaNHj5gzZw4SiYTc3FyuXLkiJlVer+LZ29tjZ2dH7969SUhI4P79+2zfvp2MjAwcHBzw8PDAzs7unXaIpcWtW7dE/9D79+/j7u5OlSpVsLCwED2LIyMjuX//PqtWrSI/P19Uora1tS3U4pOUlCRS8z+WYNn7QlNTkyFDhrBx40Y2bdrEsGHDxGC/YcOGpKamsnTpUrHl5m3Q0NDA2dlZFEXLyckRdT+io6OB/6vOvS+MjIzo27cvmzZtYvbs2eL6p6enR6NGjbh48SK9e/d+6zHUajURERHs2bOHzMxMvvrqKxwdHdm/fz9xcXGi+Nnr97JSpUoixfP8+fPcvn2bdu3a0b9//xIJGv43IDU1FblcTkJCQpHCZMnJySgUCmQy2QdLCKlUKjIzM0Wh1JCQEKKiooiLiyM1NRWZTIa+vj7VqlXDysqK2rVri4k1DQ2NIvclarWaZs2asWLFCnr27PlWMU2JRIKWlhZaWlqYmJjg5OQkBot5eXnk5eWRnJxMTEwM8fHx+Pn5cf78ebKyslAoFCiVSrS0tNDX18fAwEAMxA0NDalcuTIGBgZisCyXy8WgWSaTIZVKxb9LJJICjBXh78K5vH69hIqtYDkp/BHGueAcIRQ2UlJSyMzMFAVa09PTycrKQq1WI5fL0dTUxMTERJwz69atW+Aafwpv7H/GrPuBIVCjBbGS4gLhmJiYQkHTiRMn6NixY7k/uMJk6+3tzdChQ6ldu/b/xGRZFF4XyxKgVquJi4vD0NCQlJSUUlVzVCoVDx48oG3btvj5+Yn9OP/NsLe358iRIwQHB1OvXj0GDBjw1t+sVqsJCwvD29ubXr160axZs2Lf/6aAVWxsLFFRUWRnZ/P1119jb2+PWq3m7t27eHl50f7/sXfe4VFV2/v/zGTSe+8kpJBACCEQeke6VAURpTdpKk1BQb+260VFAUFAEaT3Jh0EpJcgNdQkpPfeJmXa+f3B75xLTIdQBN/n4blXmDlzyj5777XWu973lVdwd3fH1NRUmpSf5tgWJ/vLly+zZcsWWrduzZw5c6rMyCckJDBw4EDCw8OlxcLR0ZFPPvlEyv6ampqSkZFBcnIyOTk5jBs3rhS1T6fTcfHiRcLDw1EqlXTs2LHKsSv2K7Zp04aQkBDOnj3LggUL8Pf3p1+/fhUuvOJ1Xrhwge3bt/Pqq6/SoUMHFAoF7u7udOzYkQMHDvDFF1/wyiuv0LlzZ6myo1ar2bt3L5cuXWLChAmPJeJjZGTEoEGD8Pb25ocffmDIkCFSUFpZ1T04OBgrKyuWLFnCm2++SbNmzWp0Dvfu3cPf3x+VSkVkZCT9+vUr8/2oqCjkcnm1FWMFQeDcuXOcPn2aWbNmVSgGJrKHdu3axYcfflil0rixsTGCIEgMl0dVjv47xJ7hYcOGsXbtWlauXMnYsWMr9RmeNGkSS5cuZdOmTZX2PVcXgiBw/fp1CgsLS4lMwoOe4X379vH+++8jl8u5fv26FLwKgkBERIS0mSpPUVmk4ru4uODs7EyPHj3Iz8/n1q1bUluBg4MDzZo1IyAgQFq7H3Usq1Qq7t+/T//+/VGr1URGRpai2crlckxNTSV7JtGr/NatW5w6dYpNmzZhbm5OQEAAQUFBODs7S5tGBweHf5R9n2jZtWrVKtasWcPIkSPR19dHLpfTsWNH8vLy+Pnnn5kyZUqlrCOZTEazZs04cOAAxsbGkjq4s7Mzf/31F4mJiRQVFREdHY2lpSVmZmZlPIGrC5Eiff78ef7880+6du0qrT8dOnRg/vz59OzZs1xWoMiO2rNnD9evX2fAgAE0b95cCo5cXFyIiIjA1NSUzMxMyRpGEAQsLCxITk7mhx9+4NVXX622j/CLBNEfNikpqdwWgLy8PEnQ8lEqwg/vQwRBIDc3l8zMTNLT04mOjiYlJYXMzExKSkowNjaW2FuBgYE4OTnh4OBQqtpa3Wcjk8lo2LDhI+/RxZhDFKMSiwPidYjruBiQFhQUkJOTIzEMCgoKyM3NJTo6mvz8fCkwFYNUrVZLSUkJd+/exdXVtdRaJJPJ0Gq1xMfHY2hoiLOzc7n3VPx9QRCkoFoMtsWA29jYGCsrK6ysrKQqtpmZGZaWllhZWUlzgxiEi7//PODfQJj/VYRzc3MxNzcvd8MvKkMHBgZKi5VIbRg+fHitPlAxCP7hhx8YOXKkJGTzsqKgoAC5XF5mcUpKSkJfXx9bW9saBbJiP6aHhweHDh2iT58+tX3Kzx0sLCw4fPgw9evXx8vLq9L+NUEQuHPnDitWrGDUqFEEBgaWovaKE3N+fj4JCQnExcURERFBeno6KpUKCwsLXF1d6d27N5s3b2bq1Km4urry448/SrSiZzWeBUEgMzOT9evXk5+fz9SpU6tNva1Tpw5TpkxhxowZkqjHu+++S5MmTUrdnyNHjhAREYGhoSFFRUWlAglxU6TValm0aBGdOnWiZcuW1fp9MSDu3LkzrVq14vjx43z99deEhITQq1evUlQskdK8du1alEols2bNKmPdYWFhwZtvvkmXLl3YtWsX//d//8drr72Gh4cHq1atwtramk8++aRWKhZyuZymTZvi7OzMsmXLiIqKYsCAAZUmEGUyGXXr1uXDDz9k4cKF5Ofn06lTp2q/63FxcXTs2JHMzEzkcnm5FmsZGRnodLoqvePhfwHdnj17mDVrVoUbWXGt2Lx5Mx988EG1nATE1o/i4mIUCgXZ2dm1xlIRg+Hhw4ezZs0aVqxYwbhx4yoNhidPnsxPP/3Ehg0beOuttx6LqlhcXMyWLVvK9FGLPcONGzfG2dlZqrSLSTpBEDh+/DgmJiZotdpq+VOLys+tW7emdevWFBcXc//+fUJDQzl06BAGBgY0btyYxo0bS2yBmoztlJQUqaKRlpYmURkrOh+FQoGNjQ1t27albdu2ktdlWFgYmzZtIiUlRfKYdXd3l/Yi/4T1XuxFHz16NCtXrpSCYYVCgZ6eHn369GH16tWsXr2aMWPGVJpQ8fb2Jj09nXr16rFlyxYUCgWhoaFcuXKFdevWkZSUxI4dO9DpdBQXF0uBZ6tWrWjYsGGl1PO/Q0wMffXVVzRp0kR6z+zs7HBycuLmzZtSxR/+1wd8+vRpDhw4QOvWrfn888/LzIuurq6cOXNG6m12cXGhuLiYU6dOsW3bNlQqFSNGjChl4fSyQNTSsbGxobCwsMx8IggCSqUSc3NzKdCq7FgP9++KFdTk5GRiYmJIT08nPz8fmeyBL7e9vT1169YlKCgIOzs7bGxsymh/PC6e1PMUA3Lxfujr62NkZFRmbaiMLZGfn8/ChQu5fPkyH374IS1atJCqu4IgcPbsWd58801cXV3Zv39/KftYcS4SA97qzk3/tPH9byAMUj9HZmZmpU3Yly9fZujQoRKF4OjRo7Ro0aJKi5CaQFStXbRoEcOGDXvpg2BxghQzZg9DVCKuyvf270hISJA2xenp6Xh5edXqOT9PEHvzli5diru7O/379+f+/ft06NCh3M/rdDquXLnC5s2bmTx5Mh4eHhQWFpKbmysJWEVHR5OXl4dM9kDt193dnc6dO2Nvb4+1tbW0KRGp1ZcvX8bV1ZU+ffqwdu1amjVr9kx64dRqNefOnWPPnj306NGDDh06VPs8RBptYmIinTt35siRI7Rs2ZLx48dLiTHR83fz5s1oNBoEQShjmSEqYMMDyv+nn37K1q1bywjBVQaZ7IH1zauvvkr79u05cuQIX331FW3btuWVV17B2NiYy5cvs23bNrp06ULnzp0rVA2GB6Ja48aN4/79+8ybN4/bt28zfvx43n777VqlqMtkD8TGZs+ezbp16/jxxx8ZO3ZspX3K4hj78MMPWbJkCQUFBfTu3bvKypnYh21tbc2FCxcICAgoM68XFRWhVCoxNjaucg4Xq5MbNmzg/fffr9BrXqSTb9y4kalTp1bpG/rwdXp4eBAXFycFWbXZriEGLaK10q+//lplz/DkyZNZvny5VBl+1CrNwYMH8ff3p27duqUSNampqYSGhjJ37lzkcjmRkZEA1K1bF3jALjl79qyki1GTOUP8HWNjYxo2bEhAQABqtZrk5GSuXbvGpk2byMvLw8PDgyZNmuDv71+mn788hIWFERQUBMDNmzfx8/OrVsVcPKa+vr7UL9i3b18uXLjAzp07iY6OJjw8nNu3b+Pn50dQUBDe3t6YmJg814GxWJEXg2GRJi1Wi4YPH85PP/3Ezp07ef311yt8b/X19VGpVOzfvx+FQsGnn35KcHAwOTk5TJkyhZs3bzJz5kyMjY0lUdP4+HjOnDnD1q1b6dOnD61atao2e8HGxoZu3bqxbds23nnnHWlu6N69O3v27CE4OBiFQoFWq+XWrVts3boVJycnZs2ahYODQ7nPw87OjtzcXDw9PYmLi6OgoIADBw7g7e3NhAkT+Oyzz6QA7WWDRqMhOjoab29v6tWrV+5n8vLypHcQSgtJiqrxiYmJkntEdna2VN21t7fHycmJpk2bYm9vj4WFBRYWFs/1u1ObqGgtio2NZfbs2ezcuRN3d3fq169faq3TarXs3r0bpVJJQkICkZGRdO/e/aW4Zw/j30CY/1WEc3JyKtyQZmZmolQqJXqWUqnk0qVLfPzxx7V2HmLQ8uOPPzJkyBCCg4NfugH5d6hUKklg4uFAWAyQCwoK8PT0rPZ9Eqs6DRs2JCkpCQcHh+daqv9xIE6EixcvZvDgwRw9ehRLS0suXbpUhnopCILUj/frr7/SrVs3jh07RmJiIiUlJZiYmODm5oaHhwctW7bEysoKU1PTSvs5ZDIZnTp1Yv78+XTv3h0PDw/09fW5f/8+9evXf1q3QXqv1q1bh56eHh988EG1AxR4sIifOnWKAwcO8NZbbzF16lQmTZrE+PHjSwUrGo2G+fPnc/fuXQCJxvSwZUZ+fj5ZWVnSd06cOMHy5cv58MMPa0yLlMlkWFhY8Prrr9OpUycOHjzI7NmzMTIywtjYWKrEV+c6lUolp06dwt3dnbfeeksS/RkwYECNgvTqwMzMjHHjxnH48GGpb9jDw6PScWRjY8PUqVNZvnw5RUVFVdr8ZGRkYGhoiKmpKTdu3KB3795ljp+VlUVxcTF2dnaVBsKisu+vv/7K2LFjK7ynYrC8Zs0aJk+eXCORLzEQFkW9EhMTadCgQbW+WxOIwbBIk64qGH7nnXdYsWIFGzdufKTKcEpKCmfPnuXTTz8toxK7efNmSRdArA536dJFeq63bt1Cp9NhYmKCoaHhY1WlxYDNw8MDDw8PevfuTV5eHpGRkVy9epXdu3djYmJCo0aNaNy4MQ4ODpJPrgitVsv169cZMmQIgiBw7do1evbs+cjvhkwmIysrixYtWnDnzh2GDh2KiYkJd+/e5fTp02zatAkzMzPq168v0ahFW6HnDYaGhowZM0YKhkeMGIGBgQEGBga88847zJ8/nyNHjtC9e/dyE1IrV65EqVTSqlUrMjMz8fHxIS0tTRIxEudGsTplZ2cnCZIlJSWxfv16wsPDGTp0aLXWc5lMRufOnfn888+lAE0mk+Hr60tBQYGk7Lt161YKCgoYOnQovr6+lc7RBgYG6HQ68vLy2LZtG/369WPKlCm4urqSlJSEnp4emZmZj3ej/6EoLi6mpKSEtLQ0unTpUurfRAHJjIwM9PX1KS4u5tChQ2RmZpKcnCwlji0tLXF2dsbFxYVGjRpha2uLsbExRkZGL03AW11otVrOnj3L9OnTuXLlCoIg4OvrW0ZUNjIykv379wMPEo+7d++ma9eu/6gWjdrAv4Ew/1ONzs3NrdC/8c6dO/j4+EhZ6StXruDl5VUu3e5RIAgCKSkpLFy4kEGDBpWiW77MKCoqIjc3Fzc3t1ILnJglzM3NxcXFpUbHvHHjBiNHjuTMmTM0adKktk/5uYDo+bps2TJGjRpFw4YNiY2NlaxJxP6S1NRUIiIiiIuL4/LlyyiVSpo2bYq5uTkeHh4MGDBAEmB4lMXGzs4Od3d3rly5QqtWrejRowcHDhygXr16T2WyLSkp4dixYxw7dowBAwbQsmXLGvU85ubmSvTi2bNnS33q69evL5MEiI6OZvv27aX+Licnp9TxcnJySgXCGo2GFStW8MYbb+Dt7f1I1yiTPbBi8PX15ezZsxgbG1NcXCzZsVQliHb//n1WrVpFUFAQH374IUZGRrRs2ZKjR4/y1Vdf0bNnT9q3b1+rVXyFQkHPnj1xd3dn8eLFvPHGGzRr1qzSTb6FhQVTpkzhl19+Ye3atQwdOrTCc0pNTcXBwQGVSkVaWloZ2yR4ECxrtVrs7e0r/d2cnBwpmVSRf7vYU//zzz8zfvz4GiXnRHh4eHDkyBG6devGjRs3avTdmkCs1FUloAUPKqrjxo1jxYoVrFu3jmHDhlU7INVoNGzevJk+ffqUoQ/funWLnJwc2rRpg0wmIz09nfj4eMaMGQM8YE6cPHkSd3d39PX1q2XFUxPo6elhbW1Ns2bNCAkJQaVSkZqayvXr11m3bh0FBQVStdjb2xtbW1upL8/NzU0aV+X1LdcEomL05cuXsba2xsrKCgcHB9q1ayf9xs2bN9m5cyeZmZnY2dlJFW5RYOZ5gaGhIWPHjuXXX39lzZo1UjBsbGzMu+++y3fffYe9vX0pq0KNRsOGDRuwtbXl66+/5ocffsDS0lISWSwuLqa4uLjC3xSF7qZNm8aGDRvYsmULQ4cOrVaywMDAgNdee43t27czY8YMif7ZpEkTvvrqKywtLenbty/Nmzevcu7TaDTcuHGDK1eukJubS0hICBMnTpTWOBMTExQKBfn5+TW4oy8OEhISsLS0JC0tDXNzc6KiokhNTSUmJobU1FTS09O5cuUKWq0WIyMjVCoVAQEBdOvWDWtra4lh8CJ6Kz8JxMXFMXbsWCIiIqS/a9euXZlk5NatW0lJSZH+7o8//iAlJUXqb39Z8G8gzP8qwtnZ2eVWqgRBIDQ0VMpkqdVqjh8/zvDhw2vl90Xhp/nz5/PGG28QEhLy78v+/1FUVIRKpSrTuy1aoxQVFVWrv09EXl4ehYWF2NjYcO/ePUks40XCwz2+77zzDq6urkRGRpKZmcnJkydJTU1l9uzZ2Nvb4+joiJeXF0qlEh8fHz744AOp97E27otcLqdHjx5s2LCBFi1a0LBhQ7Zt2yb1UD2pey9SmX/77TdsbGyYM2dOtT1pxX6b8PBwVq5cSZs2bejVq1epAKC8Dainpye9e/fGwMCA2NhYSVzvYRQVFUlZbENDQ0aMGMHbb7/9yBtqUcBlw4YNpKenM2fOHFxcXEhISGDLli0cPnyYwYMHS760D1NTNRoNhw8f5uTJk4wcObKUKr2JiYlEN1y/fj3nz59nxIgRteqVLpfLCQwMZObMmfz0008kJyfTu3fvShMVJiYmTJw4kd9++02ybimPlRAfH4+7uzspKSlYW1uX+7yioqIwMjKqUH1b9JZetGgRXbp0qTA5Kc7fixYtYsSIERUGy1XBzMxMmpvS09NLMQlqE2JVTRTQ+vXXXyvsGYYHwfD48eOlBMTw4cOrDIYFQeDGjRsUFBRIwa6I4uJiNm3aJAVKgiBw7NgxWrduLT0nUeHe3NwcrVb7yBZa1YFM9kDJtU6dOri7u/Pqq6+iVCq5e/cuV65cYffu3dIYMzU1RaVSER0djaOj42O1RT0s+AhIjCfxPTUyMpLOqUePHqhUKmJiYrhx4wa//fYbhYWFuLi40KRJE/z8/EoldJ7Vmqavry8Fw2vXrmXEiBEoFAqsrKyYMmUK33//PZaWlvj4+AAPqOaFhYWMHDlSeg5mZmZs2bKFli1bkpmZycqVK4mJiWHfvn3Y2dnRrl27UuNP/N7bb7/Nd999x61bt6qlQyGTPfAw3rdvH1FRUdStW5dz585x9OhRMjIymDdvXqVsGJG6e+fOHbZv346BgQGtW7cmJCSEc+fOldqvmJiYYGVlRXZ29hN7r581Hu5TFanM6enpJCUlcejQIaKjo0lPTwceqHc7OTnh6elJo0aNsLCw4MCBA1J1t1+/fi8sU+9pwN3dnSVLljBx4kSio6MxNDQsY1mVlpbG5s2bS/1dbGwsJ0+eZMiQIS/kGK0I/wbC/K8inJWVVW5fVkFBASkpKZLUeUxMjKQ0+riD5eEgeNCgQTRv3vylGoBVobi4GLVaXaaikJmZiaWlJdnZ2TWaMMPDw6WMvkajqVKA5Z8AcUHWarXk5+dz+fJlvv32W/z9/VmzZg1arRZra2upf7d79+40bdqUV155BZVKxdq1a7GysuKdd955Il6GdevWlSqPvr6+dOrUicOHDzNq1Kha/R34H8X7wIEDnD17VmoxqEkmWa1Wc+DAAc6dO8fo0aPx8/Or1ndjYmJwdHREEATef/99iX798Hd9fX05evQoH330EaGhoTg4OBASEvJIdEdR/Xzjxo20a9eOsWPHSht2d3d3ZsyYwZ07d9iyZQtmZmYMHjxYCijEDaaxsTFz5swpt09XJpNhZ2fHe++9x5UrV1i8eDHNmjWjT58+tTZOZDKZ1Hv3yy+/sGLFCkaMGFGGlvowDA0NGT16dCkf078Hw3FxcbRq1YqbN29Sv379MvdXFCRUqVRST+rfoVKp+Pnnn2nYsGGFAjeCIJCVlcUPP/zA4MGDH0vTwdjYWFLgzMvLQ6PRPDE/TTEYHj58OGvXruWXX35h3LhxVdKkf/nll1LU14pQWFjIli1bmDBhQhmxuBMnTuDm5ib1Cubl5XHlyhXmzJkjaQuEhobSuHFjQkNDa6Tq/bgQ31dzc3NCQkIICQlBp9ORlJTE119/jaWlJZ999hmxsbEEBwcTHx+Ps7Oz1Etfk2dfWFhIYWGhND9XdD8fDoz9/Pzw8/Nj0KBB5OXlER0dzZUrVzhy5AharRYvLy8aN26Mn59fKVX+pwWxF33MmDGlKsP6+vo4OzvzzjvvsGzZMj744APs7Ow4ePAgw4YNo7CwkEOHDnHp0iVu3LghUZNFy0qAwYMH07lzZ/bv31/mvdDpdMTExNCoUSM2b97M3LlzJT/ayq5foVDQu3dvfv31V0mx9+OPP2bz5s0kJyeX65kurrcRERHs3LkTjUbDwIEDqV+/PkeOHCE3NxetVkthYaGUKBHtctLT02tNEf5Z4eH9hsikSE5OJjExkdjYWHJzc6V2KltbW5ydnSkqKqJXr14UFBQwbdq0UvOxyAhRqVRSG8S/e+DHg0KhkGwWDQ0NOXDgQJnkUExMjERHV6vVkr3S7t27GTJkyDM8+6ePfwNhkDJ0+fn5mJubl/n3hIQE7OzsJIuLw4cP07Vr18fu1RHFhBYsWMCAAQPKWEv8iwe9i2q1ukzAmpGRgampKbm5uTWibF6+fJmQkBBu375NvXr1/jG+jSLESl5xcTE5OTlER0dLIlb5+fmEh4cjCALvvPOOZBdiYWGBoaEhJSUlREdH07RpU6KjoykqKuKXX37B3NycCRMmPDGanUKhkCjR77//Pi1btuQ///kPeXl5FbYiPAp0Oh2RkZGsW7cOT09P/u///q9CRdfyIPaCrlq1Cnt7e+bMmVMjD9LQ0FAaNGjApUuXpB7Dv0OhUODm5kaTJk04dOgQ9+/fR61W1yiZI1aBt2zZQlJSElOmTCmTlBM3zwEBAcyZM4e//vqLZcuW4eXlha+vL3v37qV37960a9eu0ndAJnugxNusWTP8/f3ZuXMnX331FcOHD8fX17dW+hXFwOPdd99lx44dzJ8/n8mTJ1coSAX/8zFdt26dJPwk3kPRN9nGxobDhw8zaNCgMsfR6XSkp6ejp6dXLqNEo9GwdetWzMzM6NevX4VOAnl5eSxatIgePXo8dhJToVDg6OgoCdHl5eWVsoyrbYhBi3gfV6xYwdixY8sdt/BgMz9+/HhWrlwpVYbLm3sFQWD//v0EBgaWGZdZWVn88ccffPTRR9Jnz507R2BgoPSuqlQqQkNDGTx4MJcuXUImk9XqPFFdiOct0qgtLS355JNP0Gq1zJ49GwcHB9atWydZOwUGBuLv74+VlRUGBgZVjoXc3FyMjY3JysqqtuDjw5+xtLSUFLA1Gg1ZWVlERkZy+fJldu7ciYGBAf7+/gQFBUl2dU+DWipWaMWeYXGsKBQK7O3tGTRoEAsWLOCdd96huLgYR0dHIiMjmTp1quQbDGWVcGUyGX369Cl3rlSpVMyaNYtz585RXFzMjh07aNasGcuXL6/U4iw7O5vLly9z5swZPvroI3r16oWenh7t27fn5MmTZRiCGo2G+/fvs2vXLkpKSujbty8NGzaUAnNXV1fu37+PiYkJWVlZ0m+LScVbt25JQeLzDkEQpBa0oqIikpKSSExMlASrioqKgP9Vd11dXWncuDGWlpaYm5tjbGyMXC5HpVLx119/oaenR8OGDcsdg0qlErlcjlqtrrV2w5cZRUVFrF27lrFjx1KvXj3effddnJycSn2mSZMmhIaGsmfPHr744gs6dOjABx98gJub2zM662eHf1YU8ISg0WiQyWRoNJoyC7voByn6XmZlZREfH8/o0aMfa0ERN2sLFiygd+/e1bZQedmQmZmJVqst428WHx+Pvr4+NjY21a6aqNVqoqOjee2119i0aRMdOnR4ru+5WN3Mz88nIyOD+/fvExsbS3JyMmq1GjMzM+rUqYOnpycdOnTgxo0baLVaZs6cWe7GSl9fH2traxQKBffu3WPRokV4enoycODAJ1Z5EhEcHMyuXbtITU3F0dGRxo0bc+rUqXJFjB4FBQUF7Nmzh7CwMN5++23q169fo6y7Wq3m1KlTHDx4kIEDB9KsWbMaf//27du0atUKDw+PCoMJEeKGOTs7m9jY2AqVNP8OrVbLjRs32Lx5My1btmT48OFVJjAMDAxo1aoVPj4+zJ07l1WrVjF8+PAaX6O5uTnDhg3j7t27rFmzhsDAQPr161dp9bYmMDAw4I033uDUqVN89913TJw4kTp16lQaDA8bNowNGzZIQlaGhoao1WqUSiUWFhZkZ2eXEQgBpD55AwODMhsvkaqblJTEe++9V+67ISqCL1myhBYtWtTKXCKTyXBzcyMxMRELCwtyc3OfaCAsQl9fX7qPorVSZcHw6NGj+e2330r1gT6MhIQELl26xCeffFIqgaDT6di9ezcdO3aUvCwLCws5ffo077//vnT/oqOjpaBN7Hd/loGDIAiEh4fj7u6OsbExycnJ2NvbM3LkSARBoKCggOjoaMLCwjh69CharRYPDw8aNWqEt7e3NOf+fXxkZmZia2tLfHz8Y28+FQoFDg4OODg40KpVK0pKSsjKyuLmzZscOnSI1NRULC0tqV+/Po0aNcLR0REzM7Mnuv4ZGRmVokk3aNCA2bNn8+2339K5c2f++9//EhAQgL6+Pv7+/syaNYtZs2ZRUlKCTPZAGV+pVErHs7W1pUuXLuWes4GBAQ0aNOD3338HHjC/+vbtKwXNJSUlUouV+N+nTp3i8OHDdOjQga+//porV65I47V+/frs2LFDqupqtVru378vKez269dPCoAfPh9HR0fS09Oluf3hlhdzc3OUSuUzH89/hyAIFBcXS+KjCQkJJCQkkJycTEZGhrQvdnR0lISqevXqhZmZGYaGhhgYGFSaEE1LS8PIyIjU1NQKmTWFhYWYmJhI9+Z53pc97xAEgX379uHt7Y2/vz9yubxcHR19fX3q1KkjCdHa2toSHBz8TBw9njX+DYT/P8RA+O+bHpVKxd27d+nRowcAJ0+epFmzZlVudCuDSKf7/vvv6dWrF61bt34ulSCfB2RkZCAIQpnNalpaGmZmZhVaGZSHlJQU9PX1sbCwIDExsUJK5LOA2I+YkZFBSkoK4eHhJCQkkJWVJXlR+vj40KpVK+rUqYO5ubkkHiFaeV28eJHZs2djZ2dX7j2Ry+V4enoSGxtLaGgo7733HgMGDHgqNC1DQ0PatGnDsWPHeOutt3jllVf47rvv6Nq162NVokXq3Pr16wkKCmLu3Lk1WkjFd3HNmjXodDpJEKumC7GoChofH19KDKY8yGQyvLy8UKlUwIM+OV9f32pVkDZv3kxSUhITJkyotiCTIAhER0ezcuVKOnfuzFdffcX+/fv54osveO211wgJCak2M0Iul1O/fn3mzJnDjh07+PrrrxkzZswjiUOVBz09PTp27IiNjQ0//vgjI0aMKOVj/XcYGBgwdOhQ1q5dy5o1axg1ahQFBQXIZDJJbb68ilB+fj4lJSVYWFiUYgGJHsAnT56UhMPKg0qlYvny5fj6+parhPuo8PLy4tSpUzg7O5OcnPzUrN0UCgVvv/02Gzdu5JdffpHaJMqDkZERo0ePZtWqVRI1Xdw8aTQa1q1bx2uvvVbmvkZFRXH//n3eeustiQL9119/4e7uLlXldTodx48fp3PnzqSmpqKnp4elpeUzF4UKDQ2lefPmyOVywsLCCAgIkOZNKysrgoODpcqsUqnk3r17hIWFsXfvXmSyB37YjRs3xtPTExsbG+RyOdHR0Xh5eXH79u1SvrWPC5FG7eLigrOzM126dEGlUpGUlMStW7fYsmULOTk5kvBWgwYNcHFxeSI9maKA1pdffslnn31GQkICy5cv5+effyY8PJyYmBhJo2Xs2LFcunSJjRs3IggCzZs358yZM6jVauBBMrWihKFMJqN58+YS88ne3l7qT9ZoNCxZsoSwsDB++uknYmNj2bRpE46OjsyaNQs7OztUKhWHDx+WLBnNzMzw9vbm+vXrODg4sGvXLvLz8+nXrx+NGjWq0FbO2NiYkpISHBwcSElJoVGjRtK/if7xJSUltX6fqwMxeZednU12djZxcXEkJCSQlpZGfn4+enp6mJmZ4erqipubG4GBgbi4uEgtG49CsxdbopydnYmOji5TlRRRWFiIQqFArVZjamr6byD8GBD3d39X6q8IIrvyn8aOrE28vFf+/yGacms0GoAygXB2djYy2QNV1pKSEi5cuMAHH3zwyC+qSMf57rvv6NGjB23btv03CK4EeXl5yOVyzMzMpL8TBIHc3Fz09PTw9PSs9rFu3bpFgwYNJAXDh4/5NCBSvUMb4LsAAQAASURBVHQ6HUqlUvLDCw8Pl9SczczMcHZ2xtfXl+bNm+Pi4lIqsCuP4rl//37++usvZsyYUaXVjbOzM59++imOjo40bdr0qfYqdezYka+++oq+ffvi4OCAu7s7ly9fpk2bNjU+lkhL3bx5MwkJCYwfP16ywKgudDodf/31F5s2baJXr1506tTpkRf7y5cvExQURGhoKG+88UaV33FxccHLywu5XM7169d57bXXKjy2Tqfj6tWrbNy4kfbt2zNy5MhqUS9FGv2RI0c4fvw4I0eOlPx0R44cSXx8PBs3buTYsWMMHTq00urrwxBFg4YOHUpYWBhLliyhU6dOdO/evVZ8h2UyGY0aNeK9995j8eLF9O3bt9J5UqT3rly5kg0bNtChQwdMTU2JiorC09Oz3O+lpaWhUChK+caLdmPr169nxowZFfobq9VqVq5ciY2NDa+99lqtbiAcHBxIT08nICCA2NjYR3o3HgViz/Dbb7/Nhg0bWLZsGRMnTqwwABWpr6tWrZKq8fr6+ly8eFGi0j9870R14MGDB0vHVKlUHDp0iIkTJ0qfzcvLIz4+npEjR7J582ZMTEyqLXL3pCAyid58800EQeDKlSsMGjSozOdEqrmVlRUtWrSgefPmCIJAZmYm4eHhXLx4ke3bt0vrVnh4OK+++qrkVvEkRJQe7i/28vKibt269O7dm+LiYmJjYwkLC2PNmjUolUqJqVO/fn0cHR1LWRY9DiIjI9m7dy8JCQkA7Nmzh0mTJtGlSxfGjRvH77//zoABAzAxMeHLL7/kxo0bREZGStTvO3fuUFJSQv/+/StkLslkMho3boy5uTklJSX069cPPz8/dDod+/bt48svv6SkpAQDAwMcHBx46623pGoZPEiotWvXjqNHjzJ06FAEQcDT05OvvvqK4OBg+vfvT+PGjauc30TtBDs7O+Li4kr9m6OjIyUlJZWqYD8qxL2FIAgSSyEtLY20tDRiY2NJTEwkOztb6sO1sbGhTp06BAcH4+DggL29fRlmT22NxVu3buHm5kZqamqFyRax8v9vIPx4KCkpYe3atQwZMqTa+9v8/HxJmftlxb+B8P+fQJRKJcbGxqUGg+g526BBAxQKhZS9Lk9Qq7q/lZ2dzfz58+nWrdtzT819HiAGvA9XddRqNUVFRVJvVnWg0+m4ceMGffr04fr16wQGBj7RIPDhBEteXh5xcXHExsZy//59srKyEAQBW1tb3N3dadGiBU5OTtja2tZIhEij0bB7927u3LnD9OnTK+2jEwSBxMREtm7dir+/P82aNSM+Pv6pVcVlsgeet/Xq1SM0NJTOnTvTq1cv1q1bR/PmzWs0CWu1Wi5dusT27dtp27YtI0aMqFHFSEykbNq0ibS0NGbMmFFtv93yoNFouH79Ol27dpU2GVXB0NAQDw8PiXKZn59fpp9ZnC82bdpEZmYmU6dOrbZqsyjCt2rVKkxMTPjkk09KCb/IZDLq1KnDBx98wF9//cWSJUsICgqib9++kmp4VZDL5TRq1IhPPvmEtWvXsmjRIkaPHl0rgYtM9sBXd/bs2SxcuJD8/Hwp0C4P+vr6jBw5khUrVrB27VrMzMy4d+9eheJVopLmwzYROTk5LFu2jNGjR1doHyFaAmk0GoYOHVrrWXRzc3OKioqws7Pj+vXrT1Vh9uFgeOPGjSxdupSJEydWyH4yMDCQaNIrV67ktddeY9euXUyfPr2MQNaZM2ewsLAgICCgVDXY2dlZevcEQeD8+fMEBQVhbGxMamqqRDN+VhAr2ba2tlhYWJCTk0NOTk61zkkMQu3t7bG3t6d169ZotVrS0tKIjIxk9+7dFBcXExoaiouLiyRyZWlpWaXI06NCPKaxsTH+/v74+/szcOBAaY26du0ap06doqSkBHd3d4KCgqhfvz6WlpaPnOSKiopCpVJJ1dmsrCyWL1/ON998Q9OmTbl06RL29va0bdsWNzc3Pv/8c6ZNm0ZBQQGNGjUiNzeX/Px8TExMuHDhAsbGxlhYWGBtbV2qWilWuK9evcqYMWPQ09Pj6tWrzJgxg9zcXACOHTvGH3/8Qd26dcsEfW3atOHLL7+kcePGHD16lNTUVGxsbJgxY0a1RTXFdi2NRlPGM9jGxgatVkteXl6N76EIMdAV9xb5+fkkJSWRnJxMfHw8ycnJFBYWSsUbBwcHKeAV7bmephiVKEpob2+Pp6dnhXuuvLw8Ken7r1r0o0EQBP78809sbW0JCgqq9jPOy8vD3NxcGlsvI/4NhP//w8/Ly8PMzKxMT9PVq1cZMGAAOp2OI0eO8Oabbz5SBVcQBHJycliwYAGvvPIKHTt2/DcIrgJiIGBmZlYqu5Wfn49MJkOtVper6lgeCgoKSE9Px9PTk82bN9eqYrEoKlFUVER2djZRUVHExsYSFxdHYWEhBgYGuLq64uHhQf/+/bGxscHc3LxaVb2KoFKp2Lp1K0lJSUyfPr1SGw+RGrt06VIGDx7M3r178fb25u7du7Rv3/5RL7vGkMlkdO/enZ9//pm2bdvi5eWFvr4+kZGR5dqW/R1icLdx40aKiop4//33a2yrotVquXbtGlu2bKFdu3YSrfNx3sWsrCzUajXp6ekEBgZWa37Q19fH29ubqKgoDA0NuX//PsHBwdK/azQaLl26xM6dO+nUqRNjx46tdhVYq9Vy4cIFdu/eTd++fWndunWFAZuenh4tWrQgICCAgwcP8uWXX9K/f3+aN29erY2vuOGaOHEif/75J/PmzWP48OE0aNCgVpgutra2fPjhhyxdupS8vDxef/31CnuYjIyMGDNmDHPmzEFfX5/c3Fx69uxZ5nNiUkitVkuJIFE4rkuXLgQEBJR7fJ1Ox6FDh6Te4SdBJTM1NZU295mZmU9UOboiKBQK3nrrLTZv3syyZcuYMGFChT2NBgYGjBo1ijVr1vDuu+/yxhtvlNFzyM3NZd++fcycOVO6Z6Iy+7hx46RxolarOX36NFOmTEGlUpGTk4OBgcFje/U+LkJDQyVl96ioKOrUqfNIz0RMNLi4uGBmZkZgYCAjR47ExMSE5s2bc/PmTQ4fPoxGo8HNzQ1/f3/8/PykgO9JMcdEMbLAwEACAwPRaDTk5uYSExPD9evXOXToEDqdDm9vbxo1aoSPj4/UmlOdefPVV18lJCSEXbt2sWrVKsLCwti9ezfjxo3DysqKdu3asXz5cq5du0ZGRgZFRUV07doVBwcHbG1tpTlVJpNx9+5dKQmen5+PVqvFwMAANzc3/Pz8qFu3LnZ2dgQHB5OYmMh7771HVFSUdC5JSUls2bKFWbNmlWEspKWlERcXx7x585g8eTJNmjRh9erVRERE0KJFi2rfSwcHB+keirRvQGoVSEtLq/I4YlCoUqkoLi4mNzeX+Ph4SahKnBsMDQ1xcHDA2dmZ4OBgevbsiZmZGaampk8smVIT5OTkoNVqyczMrFRRPzMzUwqAn4RzxYsOQRBISUnh2LFjzJ49u0ZFnszMTGnNeVnx8l75/4dOp0MQBElc5eEXsKioiKysLNzc3IiNjUWj0eDt7V3j3xArUAsWLKB9+/Z06tTpXzp0NaBWq8nMzMTCwqJUVUJMWuTn51fbxzExMRF7e3uKi4spKiqqsFelKojCErm5uaSnpxMZGUlcXJxUvbC0tMTT05N69erRvXt3SbG5NiijIkpKSli/fj1KpZJ333230mrow57C48aNw9/fn7NnzyKXy0lMTESn0z3Vsejq6oqlpSX37t0jMDCQnj17cujQIerVq1fp5K1SqTh58iSHDx/m1VdfpW3btjXejObk5LB582ZSU1OZPHlytanAlUEQBK5du0bDhg0loa7qQCaT4e/vz65duzAxMeHKlSsEBwdLInrr16+nuLiYqVOn1shvOScnh3Xr1lFYWMjMmTMlC6eqYGZmxsCBA2ndujUbN27kzJkzvP3229WulOvr69O1a1e8vb359ddfadmyZRnv5UeBTPZAUfq9995j1apVknVPRVUDExMTWrVqxZo1azA2Ni43UabRaEhNTZVUmrVaLdu2bcPR0bFSm6RTp05x8eJFPvjggye2WZPL5djZ2Um2cYWFhc9EMVmhUPDmm2+ydetWiSZdUTCsr69P8+bN2b17N/Hx8ahUKun56HQ6du7cSdu2bUvNuRcvXpSqVSJu3ryJnZ0dTk5OZGVlATxzFVmtVsudO3fo0aOHVMWujX7egoICjI2Nyc3NpW7dujRv3pxmzZpJzzwqKoq7d+9y5swZCgsLsbW1xcfHhwYNGuDo6IilpeUTm7cVCgW2trbY2trSpEkT1Go1+fn53L17V1KkNjQ0pF69egQHB+Pq6lqpur5cLsfZ2ZmJEyfy5ptvsn//fr799ls+//xzXF1d+eOPP+jevTsBAQF4enpiYmKCvr6+tDH/+3EfroqqVCoKCwuJiYnh7t276OnpYW5uzt69e9m4cSNhYWHUqVMHHx8fmjVrRlBQEK1atZKOqdFoCA8PZ+/evSiVSoYNGyYlPkRf4GPHjtVIEd7FxYX09HTpWYoBsMi0ycnJKXUtYqtUfn4+WVlZxMTEkJycTGpqqtS7a2Fhgaurq8QccHBwwMjICAMDg6dukVUTiNXgxMRE+vfvX+HncnJypPvzb0W45tBqtaxdu5a+ffvWyBJUZC5YWlr+oy29HhcvfSAMSMIqfxf3iIiIwM3NDWNjY44dO0anTp1qnDURBIH8/Hy+//572rRpwyuvvPJvEFxNqFQq8vLyygQCOTk56OnpoVAoqqW+KArgNG7cmIiICOrUqVPpZPswPaSwsJC0tDSSkpIIDw8nMTFRsmyyt7fHx8eHTp064e7ujpmZmbQoPamFqaSkhJUrVyKTyXjnnXcqrRKKQdqaNWt4//33JUEjd3f3UiqRNbEYelzI5XJ69OjBwYMHadiwIY0aNWL79u0kJyeXq5wqUqtWr16NhYVFjcWsxE2T2GPboUMHRo0a9dhVYBE6nY7Lly/TtWtXrl69Wu3qlSiYJY6Z+/fvU1JSwvnz59mzZw+9evWiQ4cO1UqgiNd47do1NmzYwCuvvEKXLl1qXBGQyWS4uLgwbdo0QkNDWbBgAW3btqVnz57VotOJ1zRnzhxWrlzJ0qVLGT169GOr04oKsuPGjWPDhg0sX76cd955p8JzKigoYODAgaxevZq7d+8SEhJS6nMlJSUUFBQgCAIODg6cOnWKhIQEpk+fXu5mQBAEbty4wcGDB/nggw+qTR1/VLi5uZGcnIyxsfEzC4ThQUD0xhtvsG3bNpYuXcqkSZPKzLdiYnDr1q188803hIaG8vPPP0tzU1RUFPfu3eOzzz6T7llRURH79u1jypQp0lqo0+k4fPgwffv2RS6XS9oQNWH9PAkkJCRgZGQkJSeio6MZMmTIYz//uLg43N3diYmJkQTRZDIZBgYGGBgY0KRJE4KDg6WqYHx8PBEREezZs4eMjAyMjY3x8PCgYcOGkthYbfX0PgzxnGxtbWndujWtW7dGo9GQnp7OrVu32Ldvn6SS3LBhQxo2bIibm5vE2hDPRVxTc3NzycjIoGvXrrRs2ZL27dtjZ2dXo2BOXF/lcjn6+vqYmppib29PSEgIQ4YMIS0tjVOnTlFYWEjPnj2ZMWMGQUFBpeZSnU7H7du3+f3339FqtZINklwu5+rVqyQkJODl5UW9evXYsGFDjaz+3N3duX79OkZGRhQUFEhsNhMTE/T09Lh37x5nz54lKiqK1NRUsrKypN5dW1tbPDw8aNy4Mc7OztjZ2ZUSqnpeA96KcPv2bXx8fDh37lyl+4yCggKpqPFvRbhmEC3oZDJZjd1nlEoleXl52NnZvbS0aPg3EEan06HT6SgoKCgz0f311180adKE/Px87t27V2OTaTEInj9/Pq1bt6Zbt27/BsE1gFqtlsQTHkZ8fLxEFatOYkKj0XDnzh0mTZrErl27Sm2MxSBCHAMJCQnExcURERFBenq6pCzr4uJCvXr16NChA46OjqU2hE9r0i4qKmLZsmVYWVkxbNiwSoMkQRAIDQ1l69atzJw5s1Rlz8/Pj0uXLmFubk52dvZTDYRlMhl+fn5s2bKFxMRE3Nzc6NSpE0eOHGHUqFGlnktJSQkHDhzg7NmzDB48mKZNm9bIB1Nsedi0aRMpKSm8//771e6xrS7y8/PJzc1FpVLh7u5eowqou7s7Tk5O3LlzBwcHBz777DNsbGyYPXs29vb21e4FLiwsZMuWLcTExDz2NYr0zVatWtGwYUO2bNnCl19+yciRIyUxssqOLQppTZ48mX379jFv3jwmTZpUo6p2RTA0NGT48OFs3bqVhQsX8u6775arEJ6fn4+VlRWdO3dm69atWFtblxJSKywsRK1WY2RkRHp6Ovv372f27NnlJscEQSAmJobVq1czbdq0R1IUryk8PT05f/68pDz7d6rx04RCoWDQoEFs376dxYsXS/f8YRw4cECqVvr5+bF+/XqWLl3KmDFj2LRpE2+++abEWhEEgbNnz1K3bt1Sia/4+HiUSiV+fn7Sf4u2Nc/KzkMQBC5duiTRopOTk7GwsKg2C6my48bExODp6cm1a9cIDAws93My2QMPb2NjY+rVq4evry+9evVCq9WSkpJCTEwMV65cYc+ePahUKmxtbfH398fHx0eyRalN32DxOPr6+mUUqePi4ggLC5OCRicnJ4KDg2nQoAH29vYUFhaydetWIiMj6du3L5MnT6516q44dzk7OzN48GAGDBjAxYsX2bZtG7dv32bgwIEYGBhw8+ZNdu/ejUKhoH///lIbh9inLnoI161bV9JyiIyMpGnTphX+triPEAQBY2NjEhMTAdi3b5/UNpObm0tSUhJnz57FxcWFunXr0rRpU+zt7bG2ti6VhHsRAkFBEIiMjKRJkybY2dlV6rSSk5ODmZnZM33f/6nIyspi165dzJ49u8YMrIKCAjQaDQqF4l9q9MsMUYwkOzu7lFWFTqcjMjKSfv36cfXqVfz8/Gq0AIpB8IIFC2jevHmtWmy8LKgoEBZpjdWtNOXn56NWqzE3NycqKoo+ffqQnJxMbGwssbGxREVFkZubK/X3uLu707FjR2mBeh4ylAUFBfz000+4ubkxePDgSictnU7H2bNnpb68v3sKu7i4kJycjI+PD9HR0U9djMbQ0JBOnTpx8OBBxo0bR6tWrfjiiy/Izc3FyspKevfWrVuHh4cHn376aY2rYlqtlitXrki9wCNHjqx1CxZBELh9+zbe3t6EhYVJXuPVhdgPev/+fZKTkxk8eDBjxoyp9oIk3qfffvuNoKAgPvroo8eydXsYorjZmDFjuH37NqtWrZLEtKryDRY3pH379sXd3Z0ffviBUaNGSUJJjwOFQsHgwYP5/fff+fHHH5kyZUqpeUBsc9HpdISEhODr68vKlSt5//33JZp4QkICZmZmaDQafvnlF0aPHl2uAKLYk75kyRLGjRtX60mUimBvb09GRgZNmjQhPj6+VO/4s4BCoWDgwIHs2LGDxYsXM2XKFGlOTkxM5Pz585JnsFwuZ+jQoWzcuJEPP/wQHx+fUr2BBQUFHDlyhBkzZkjHFwSBQ4cO0aVLFykYiIuLw9jYuNY8qh8FGo2GGzduMHnyZIkW3aRJk8dexwVBkGzWjh07JllHVQXxPigUCtzc3HBzc6Nt27bodDpyc3NJTU3l3r17HD58mNTUVPT19XF3d8fX1xdvb2/s7OwwNDSsNSqteAxDQ0N8fX3x9fVlwIABUj/r1atXOXHihCSE1LFjRz799NMn/kwfPq/27dvTtGlT9u3bx+eff45cLsfKyorBgwfj5+dXhgEik8lo0qQJBw8elLxtmzVrxqVLl2jSpAnwYN5Vq9WoVCrS09Olvt34+HhycnJQKpWEhoZSt25dbGxs6NWrF3Z2dpibm0tr3PDhw1/4wEOpVJKTk0NRURFeXl6VPvOsrCwpEK7NNrIXHRqNho0bN9K9e3ccHBxq/P2CggKpDUFMBL2MeLHfxGpArAiLE5SI5ORkDA0NsbCw4MSJE4wYMaLaxxTl63/88UeaNGlCz549/w2CHwGi1cDDGwXRjkIul1fary0IAiqVCqVSyenTp8nJyWH58uVcvHiRxYsXY2JigpubGx4eHjRr1gxra2tMTExqjTJbWxATKosXL8bPz69K31+dTsexY8f4888/mTFjRrmVRRsbG4qKinB1dSUyMvKZqJe3aNGCgwcPkp2djbW1NU2aNOH06dN07NhRUsJ+6623aiy6JI6PTZs2kZuby3vvvffEAhix6t6yZUt2797N4MGDa1StzszMJD09naSkJGbMmEFJSUm1+3SKiook26zhw4eXsgKpTcjlcgICAvj444/ZvXs3X331FcOGDcPPz6/K35PL5TRp0gRbW1uWLVtG9+7d6dChw2P3Iunp6dGvXz/2798vVSnFYFij0VBUVERJSQlubm74+vrSr18/li9fzowZMzAzMyM+Ph5BELh48SIfffRRhUJteXl5/PTTTwwYMID69es/tXfE1tYWpVKJra0tYWFhT1U5uiI8HAwvWbKEyZMnY2BgwJo1axg0aFApVom+vj69evVix44duLi4oFKppCTU0aNHCQwMLOX/np6eTlRUFMOHD0cmk6HT6UhKSkKr1VYoXPY0kJKSglwul8SPbt68yeTJkx/7WajVarKzszE2Nq6VHmi5XI61tTXW1tb4+/tLdPX8/HxiY2MJDw/n/Pnz5OXlYWRkRJ06dfDy8sLHxwdLS0tMTU1rrXIsiueJVOmwsDCWLl3Ke++998TmqKpgamrKoEGD8Pf3Z9myZYwcORI/P78Kr9fMzIy6dety9epVGjVqhLW1NZcuXcLBwYGMjAxSUlJQKpXIZDKsra1xdnbGxcWFJk2aSInzr7/+WlLuFSvJOp0OGxsb0tPTpSrci4yMjAzMzc2Jjo4uV7RQhFarJSMjAzs7OykQ/hdVQ2z5ys3NrVDboioUFBRI7RharfYJnOU/Ay/9iBMzIA8v1vBAuMPf35/k5GSAGtmWKJVKfvzxRwIDA+nVq9dL3YT+OMjJyUGtVpcKhEU7IiMjI4laJwiCpNiclpZGREQE8fHxpKenSxZYvXr1oqCggLFjxzJo0KDnXmQC/ieytmjRIpo0aVLlWNJqtRw4cIBLly7xwQcfVOgpbGRkhKWlJUZGRiQkJDyTxcfMzIyQkBBOnjzJgAED6NSpE7Nnz+bEiRM0b96cOXPmlEt7rQwajYZz586xZ88eunbtSqdOnZ4ozaqkpITExETMzc2lpFlVECnfhw4d4uzZs9SvXx+5XI65uTm3bt2isLCwSgXw+Ph4Vq1ahZubG3PmzHnsHtyqIApWvf3224SHh7NmzRqCgoLo169flRVomeyBDdKsWbNYunQpGRkZteK9q6enx6uvvopMJmPhwoVMnToVc3NztFotJSUlANjZ2SGTyWjevDlZWVn88ssvTJkyhfj4eFJTU3nllVfo1q1bufeuuLiYX375hWbNmtG6deunOk+IYkFmZmakpKQ8N5tDPT09Xn/9dXbv3s2SJUskltTfe7B1Oh27du1i9OjRFBYWSskKpVLJuXPnmDNnTqkK/vHjx2nTpk0pf2HRLaAiG6snjYdp0TKZjIyMDORyeY2EaCqCOD6LioowNzev9f2BTCaTqukODg6EhIRIvcZ5eXlERUVx//59Tp8+TUFBASYmJri6uuLl5YWnpyc2NjZYWFhUKzhWqVTodLpy2Tapqals2bKFjz/++KmxKSqCaPU2c+ZMfvvtN6ZPn46tra2UMM/LyyM3N1diioWHh7N9+3aCg4MxMjIiMzOT5ORkmjVrhpubm2QnJdK7/35tItX5YYVo8bmUlJSg0Wie9i146oiIiMDLy4ubN2/i6OhY4edKSkrIzs6WgrGX2c+2JsjLy2Pbtm1MmTLlke+ZqLcj9q+/rHj2q+szhtjX8bDSpSAIXLlyhQEDBnDs2LFqVzHEgGzhwoU0aNCA3r17v9SD63GRnZ2NRqORaLFiP6RSqUSpVHL79m1CQ0NJTk4mLy9PWvh9fX3p2bMnrq6uGBoa8sknn/D222/zyy+/0KpVq2dKt6suRLut77//nrZt29K1a9cKx5LY47xz507u3r3LBx98UGlwJApmFRUVUVhYKG3IniZkMhldunRh/vz5tGjRgl27dpGSkkK/fv0YMGBAjZ6PqLS8evVqtFptjdSSHxVi/5OTkxNRUVE0atSoymqHKMC3Zs0aPDw8mDt3Ln/99Rd5eXlcuHABV1dXUlNTS7VoPPxdjUYj+WAOGTKEJk2aPFUBFblcjp+fH3PnzmXLli3897//Zdy4cVVaWImVk+nTp/Pzzz+zdu1ahg4d+tg9gnp6evTq1QuZTMaCBQskum1xcbFUJRPPu1u3bpKP9q1bt7hy5QrTpk0r953S6XRs2bIFa2vrZ8bmsbKyQqvVUlRUhFqtfi4CYXhwz/v378/69ev59ttv2bp1a6l7KAgC4eHhxMbGMmzYMPT19dm+fTsLFy7EzMyMzp07l2pzyM/P58qVK6WC45KSEnQ6Hfn5+Y9E96sNqNVqrl+/zoQJEwC4evUqDRs2rJXnkJSUhJ2dHVlZWY/sXlATPNxrbGxsjKOjIy1btpTmlPT0dOLi4oiKiuLixYvk5OSgUCgkMUhPT08cHR2xsbEp874cOXKElStX8t5779GmTRvpndZoNGzZsoWBAwdWGQRrtVri4+PJzMzE29tbcnXQarVERUVRVFREvXr10NfX5+bNm9jb2+Pi4kJxcTFXrlxBEAScnZ1JSkoCoEGDBtja2pZ7H7y9venduzdLlizBzs6OzMzMUsrMzs7OeHh4EBAQwNq1a5k9ezZWVlYcPXqUnJwcmjVrVq05S9QSyMzMLOXMYGFhgUqleuEDYXEe8PLyQk9Pr1LWQ0lJCUVFRRgZGVWYVPkXpaHT6di+fTstW7Z8rCTTw22GJSUl/1KjX1aI9kmieAogydjb2dlx79493njjjWoNtMLCQhYtWoS/vz/9+vX7Nwh+RIiBXXZ2NiqVioSEBPbu3StZFYWGhqKnp0dAQACBgYGS5+DD1SnxecXFxUlBYVZWFh4eHv+IIDgzM5P58+dLlc2KNuOijcTmzZtJTk5m+vTp1aqk+vv7c/XqVczMzCTrgqcNa2trdDod06ZNY/jw4fzwww9s3ryZvn37VmvDKb63J0+e5MCBA/Tt25d27do9tUr/xYsXadq0KefOnauUFi22SuzcuZM7d+4wbNgwiWrr6ekpUcPat2/P1atXqVu3bqljiR6Bq1atwszMjDlz5mBtbf1MxrFM9kDBeeTIkVy9epUFCxbQvXt3OnfuXGlWWqyGTJo0iTVr1rBs2TLGjx//2D3NYjCs0+n48ccfGTVqFIWFhVhZWZU6tkKhYNiwYXz11VecOXMGX1/fcucCQRA4cuQISUlJFQbKTwN16tQhOTkZPT09SkpKaq33uzag0+kk5d81a9YwdepUSRlXpVKxbt063nrrLUlbYdCgQfz8889s376drVu3SscRBIGTJ0/SuHHjUmyKnJwcZLIHPvG1UYF9FGRkZAAP+rXFxPjQoUMf+50TBIHY2Fjq1KlDdHR0uUmvpwExgSZ63Lu4uNCyZUvgQWCalZVFamoqUVFRHDt2jPT0dFQqFWZmZjg7O+Pl5YWrqyvnzp3j999/59ixY/Tp04f333+f4OBgyW6yMu9Y+J+ftK2tLcbGxpJP94QJE9i3b5/k871nzx5at25NQUEB33zzDV9//TXOzs7cvn1baoNYvXo11tbWldLpZTIZISEh7N27Fzc3N1599VVsbW2l8fswbty4QVhYGB06dKBx48b89NNP1fb1dnd3Jzk5GaVSWer9dXR0RKlUvvCBsEqlIjExEX9/f5ydnStNJhYXFyOTyaRA+Hma655HCILA3bt3iY6O5q233nqsOSk3Nxd4wEIqKiqqrVP8x+GlD4TFzbRcLpcqwrGxsTg6OnLz5k38/PyqFSQolUqWLFkiCUb8GwRXD2JWuqSkhJycHKKjo4mNjSUmJobQ0FASExOJiIggICCA7t27k5eXh4GBAYIgMGbMmErvsyAIhIWFUb9+fRITE3F2dn7uaTeCIJCamsqCBQskv9zKFhG1Ws3atWtRKpVMnjy5WnZS8MDP9+DBg3h7e3P//v1q2/7UBsTAbt26dcjlctzd3aWKt56eHhERERX2bT58jPj4eNatW4e5uTkff/yxRIV9GtBoNERERNC5c2cOHDiAi4tLuZ/TarVcv36dLVu20LRp0zJiMdbW1piamhIbG4uDgwNnzpyhX79+KBQKaW46ceIEhw8f5vXXX6d58+bPvDoobqKbNGlC3bp1Wb16NXfu3GHkyJFYWlpWykQwNDRk1KhRbN26lSVLljBp0qTHVuGVy+W8+uqrqNVqli1bRm5ubrlWXKINTG5uLpaWlmU2XGLAc+LECWbNmvVMKxN16tTh9u3b2Nrakpqa+kwthB6G2Fut1Wr5+OOPOXjwIIsWLeK9997DzMyMo0eP4ubmVqqnWgycu3XrxooVKySBs8LCQk6fPs2HH35YaszExcVhZWVFUVHRMxnrojBWcHAwenp65OTkUFhYWGvV26ioKFq0aMGJEyekPtJnjYfPQaFQ4ODggIODg6RordVqKSgoIC8vj+TkZKKiorhx4wZ79uyRdCw2btzI4cOHGThwIK6urlJSsjL89ddfREZG0qdPH4lxcuPGDf7880/y8vIkarqenh7r1q3jww8/ZPPmzSxfvpxp06YRFBREcXExnp6eeHh4YG9vX2XyRF9fn3bt2lFYWIinp2eFn2vVqhXbt2+nQ4cOUkUzJyenWuJmTk5OhIWFlUlk2draUlxcTEFBQbkCfS8KRHu6+Ph4GjRoUOkYF7Ux5HK5pLr9LypGUVERa9euZdSoUY99rwoKCtBqtZiYmJTyt37Z8NIrOOl0OoqKitDT08PQ0BBBELh8+TJNmjThxIkTdOrUqcqFqrCwkGXLluHp6flvEFwJRBGP9PR07t69y759+1i2bBmff/45X375Jb/99htRUVG4ubkxbNgw2rdvT0BAAO+++y79+vUjICAAtVqNpaUl5ubm1aIsXrt2jcaNG3PlyhWCg4Ofi01HRRAEgcTERL7//nsGDBhAu3btqsykrlixAq1WyzvvvFPtIBgeZKYLCwtxdHQkKirqqVBixOe/f/9+vv/+e1q3bs3nn3+OhYUF9+/fl/o+Dxw4gE6nq/A4RUVF7Nq1iyVLltC1a1cmTZpUbbuh2kJcXBwmJiZkZWWV60stCALp6eksXbqU/fv3M3HiRAYOHFimWi+OZVNTUxISEigqKpI2EcnJyfzwww/cvXuXjz76iFatWj3zIPhhiJTnd999Fz8/P+bNm8e9e/eqHEv6+vq8+eab1KlThyVLlpCfn//Y5yIKaHl7e3P79u1yk5dhYWGcPXuWzp07k5SUJN1n+F9iZcOGDUyZMuWxBYweBzKZDGdnZ9LS0nBycpIon88agiCQnZ3N7t27GTZsGEZGRpL/6qJFi4iIiOD48eO8+eab0rwlelyampoyffp0/P39WbRoEQUFBZw8eZKAgIBSNFbRN9zQ0LDaasq1DVFxvlmzZsCDymC9evUq9Z6vLkQhMFEZvKIE2vMGPT09LC0tcXd3p3nz5rz55ptMmjSpVCXV1NQUfX19Ll68yN69e6lTp06Vxz1//nwpVwYzMzNat27N0aNHS9Hira2tOXnyJIIg4OXlRa9evfj+++/Jy8t7pOtxd3cnPj6+0s94enpSUFBARkYG+vr6+Pn5cfPmzWqtldbW1uTm5mJgYCBV2kQhMVEs7UVGfHw8Li4uxMfHS1X9ilBUVFRKM+BxE6MvMnQ6Hb///jsBAQH4+vo+1rHEBJZGo5Gq8S8rnp9d1TNESUkJhoaGyOVyNBoNkZGRNGzYEK1WW+VkXlRUxNKlS3F1deX1119/rjaqzxJiv7SoshgREUFCQgKZmZno6elha2uLt7c3LVu2pE6dOpibm6NQKCSBDjFBYWFhUaoyk5KSgqGhYbVEkJRKJdnZ2djb2xMeHi71Ez6PEDfiixYt4q233pL6PytCYWEhy5cvx9raWuq3rAlEMR4rKyvOnTv3xAV5BEHg/v37rFu3DicnJ+bMmSNVuXr06MHBgwepV68eQUFB7Ny5k+Tk5DJCOTqdjvDwcNauXYu3tzdz587F3Nz8mTzTv/76i6ZNm3LlypUylipqtZrTp0+zf/9+unfvTseOHSvsh9XT08PBwQEnJycuXbpEQEAAYWFhFBcXc/DgQV5//XVatGjx3Aq7yWQy9PX16dGjB97e3qxcuZJ27drRo0ePSseTnp4eAwcOlISX3nvvvcfeACkUCnr06MGCBQvIzMwsNabz8vJYt24dHTt2lBSJV61axfvvv4+BgQF5eXksW7aM4cOHPzOBpofh6OhITk4OjRs3JiUl5blQjtbpdKxfv54uXbpI1VE9PT169+4NwMSJEyWRPhG5ubns2bOHmTNnYmBgQN++fZHL5Xz77bfk5eXx8ccfl2kDiI+PRy6XV1qte5LIyMhAp9NJgXhoaKgkzPa4UKlUqFQq9PT0/vGbfrVajZ+fHyEhIQQGBpayaVqyZEm1VGhbtGjBhQsXpPGt0WhQqVS88sorZGZmSp/Lzs6me/fu0jNo27YtSUlJrFy5Uurjlsvl1WZxPNy3WxH09fUJCAjg6tWrdOvWjcaNG3PkyBE6duxY5fFFZwYnJyfS0tIkL3ALCws0Gs0LXX0Tqbtubm7ExcVVmewpLCxEo9FIz/bfHuGKERUVxbVr1/j0008fW7tCrVZTXFwstYWKekkvI176qE2n01FYWCjRFbOzs9Fqtdy8eZM2bdpUupkrLi5m2bJlODo6MmjQoJcuCH64mlJQUEBycjLx8fGEh4eTmpqKUqnE1NQUJycn6tWrR0hICC4uLpiYmEgvcUWbC5FOZ2FhUSpbKPYqVWadJCI6OhpHR0fUajVAjb1onxYEQSAmJoZFixYxatSoSvuqRFXyJUuWUKdOHd54441HHneenp5kZWU9UUEeMSGya9curl+/zttvv01gYGApkadGjRqxc+dOMjIycHBwoGPHjvzxxx+MGDFC8rZTKpXs2LGDu3fvluqxfRbQaDSEhYUxduxYTp8+zeuvvy5da1JSEqtXr8bIyIhZs2ZVq1Lt5eVFVFQU4eHhvPLKK/znP/+ha9euzJkzBxsbm2ceAFUHMpkMX19f5syZw6+//kp0dDSjR4+utF9dFF7asWMHy5cvZ/LkyRgaGj729VpaWhIeHs7u3bsl4bXdu3fTrFkz0tPT0dfXZ+DAgSQnJ7Nnzx769u3LypUrad26dZU9jU8Lot+rjY0Nt27deuaBsKiiXJ5Vh2gx5OzszPnz52nTpg1mZmYIgsDOnTtp06ZNmcD5zp07hIWFSRsw8XharZbs7GzMzc1xdXV96tcsMsKCgoLQ19eXKoK1FZQnJydjZWVFSUmJpMz8T4WZmRmrVq0qNZeL87Wvry9RUVH4+PhU+gybNWtGXFwcf/zxB6ampgiCgLe3N507d+bIkSOcPn0agMzMTIYPH87Vq1e5c+cOUVFRDBw4kKSkJBQKBTt37kShUFQrSBWTslXtIWQyGS1atGDLli106dIFNzc3UlJSUKvVVSbiRRVeUfk9KCgIeCCCZ2BgIPVmvojQ6XTcv3+fdu3aYWpqWiWTIisrC51OJ9Gj/w2Ey0dxcTHr1q3j7bffrhH7ryIUFRVJwm1GRkYvXfzyMF7eK///EPvwRK79vXv3cHNz49atW/Tp06fCSby4uJjly5dja2vLkCFDXvhBJApYifZFcXFxxMbGcv/+fWkis7Gxwd3dnWbNmuHk5ISdnV2pSa0mmxpRNfRhCyBRVEhPTw9nZ+cqjydW68Re7+exP1hUEl66dCnjxo2rtJ9GEATy8vL48ccfadCgAf37939kGr4YuNy8eRMLCwvS09OrRWWrLsTxcuvWLTZs2ECjRo34v//7v3IDI0NDQzp06MAff/zB22+/TevWrfnss8/IycnBwsKCGzdusGnTJpo2bconn3zyzFW/09LSJJE9ExMTLC0tKSoq4vDhw5w+fZqBAwfSvHnzaj8bLy8vdDod0dHRbNmyBTs7OyZPnvyP2xDIZDIsLCx499132bt3L/PmzWPixImVvqt6enq89tprbNiwgV9//ZXx48c/luWV6AAwZcoUzp49y9GjR/H29ubWrVt8+umnfPPNN6jVajw9PenSpQtff/014eHhz1QhujyIllV6enrk5uY+80x9VlYWW7dulSq7IsQ5aefOnXz99deEhYUxf/58pk+fTmJiIlFRUaUUoeEBUyc9PZ2BAwfyww8/MG3aNKm3XK1Wo1KpyMnJeSa0YTHgHz16NDKZjPDwcNzc3Gpl4ykIAnFxcbi7uxMTE4Onp+dzkXR5VIi9u+X9ffPmzVm7dm2VFnYGBgYMGjSI5ORkcnJycHNzk9b83r17k5iYSHFxMS1atMDAwICcnBwmTpwoWYxNnjxZGoOtWrWqVh93SUkJYWFhUiW5Mnh4eJCfny/53VtbWxMXF4ePj0+V3zU3N8fY2Ji0tDQp2SP6NmdnZz/z5NaTgmhHlZeXV62CRVZWFvr6+sjl8lJaPf/ifxAEgT/++AMXFxcaNmxYK+OmsLAQ+J917L8+wi8xxIqwiYmJ5DlrZGSEk5NThaILRUVF/Prrr1hZWfHWW2+9cEGwmBwoKioiJyeHqKgoYmNjiY2NpbCwEAMDA1xcXPDw8KBv377Y2tpibm6OgYFBrU3sWq0WlUpVivoqnpOhoWG59ggPQ6PREB4eTpcuXdi8eXMpWtXzAkEQuH37NitXrmTSpEn4+vpWeo7Z2dksXLiQFi1a0KNHj8fuRffw8ODIkSN4eHgQFRVVa16PYi/h1q1bSUlJYdy4cXh5eVUYZMhkMlq1asV//vMf+vXrh5mZGcHBwRw4cICcnBwyMjKYOHEiHh4ez0WgcuPGDQIDA7lx4wYBAQFERESwceNGPDw8+OSTTyoVjPo7BEFAoVBw9epVANq3b09WVhYJCQl4e3s/d2O2OtDX16d///64u7uzYMEC3n777UrtpRQKBUOGDOG3335j3bp1jBgx4pHnVLGlwsHBgXfffZdvvvmGHTt2MGHCBAwMDMjPz0en00nMlNatW/P111+zcePG52oel8lk1KlTh9TUVFQqFVqt9plpT2g0GtavX0/37t0liqcIQRDYvn07rVu3xt3dHTc3N/T09Pjmm28oLi5m/PjxpRI64oYuJCSEN954gyNHjrBgwQKmTp2KlZUV6enpGBoaolKpnolAWEpKCjqdDmdnZwRB4MKFC7Rq1arWjh8eHk5QUBB37tyhXr16/8j3uzpwdnbGycmJM2fOVKmzolAocHd3LyPYqFAo8PDwKPV3fw9AxbFVXdEgnU7Hn3/+ibe3d7V60BUKBT4+Pty9e5c2bdpI83515mZbW1vJS1gMeg0MDLCwsChF+37RkJaWhrm5ObGxsVKffWXIy8uTHCT+rQiXhagdc+rUKebMmVNreyCxN1uj0WBsbPzMk63PEs9+V/mMIaoWW1hYUFxcTGxsLAkJCXTu3LnczxcXF/Pbb79hamrK22+//VxWGWsCkbqamprKzZs32b17N4sXL+bzzz/n66+/Zv369SQlJeHj48PYsWOZO3cun376KRMmTKBXr174+flhZ2dXK5TGhyEmKBwcHEoFwhqNplqKi2KPoLW1NSkpKU9VFbk6EJMuv/32G5MnT64yCE5LS2P+/Pm0b9+enj171sqm2M7OjsLCQlxdXYmMjHzs48GDZ3TmzBn+85//4ObmxuzZs/H29q5y8ra0tKR+/fqcPXtWeh9/+OEH3N3dmT17NnXr1n0ugmCtVsvVq1dp2rQpFy5c4MaNG2zYsIEhQ4YwatSoUgyGqiAqQq9YsQJXV1eaNGnCrVu3aNiwIZcvX37CV/JkIZfLCQkJ4d1332XLli0cO3as0oyzgYEBI0eOJDMzk3379j2ycIdWq0WtVmNmZoa5uTmdOnXi7t27mJqakpmZiUKhQF9fH2NjY5KTkzl27BjvvvsuW7duRaVSPerl1jpkMhkuLi5kZWVhaGj4zKiUYjBYVFRUhhINDxhUUVFRUqJRLpfTtWtXDAwMiI2NLRNsZGVlceHCBan63q1bN1q3bs0PP/xATk4OiYmJWFtbPzOq3sWLF2nSpAn6+voolUri4uKqVLCvCZKSknB0dCQhIaFMkPciQWR6nDhxguvXrz8Xm2yx2n/p0iX69etX7Xm6RYsWXLp0CZ1OR0BAADdv3qzW99zc3CgpKSErK0ua+0SmR3p6+gspTiQy3Nzd3UlKSipjBVgecnJysLa2Rq1WSzZK/+J/0Gg0rF27ltdff71W2/vy8vLQ19eXPMZfZpHf5ycF/oh43AlWrH7a2NiQnp5OSUkJGo2GBg0alDm+Wq1m1apV6OvrM2zYMMni5HnP6j58DYWFhaSnp5OUlER4eDhJSUlkZ2ejr6+PnZ0dvr6+dOjQAXd3d8zMzKS+jad9jRqNhvz8/FJVeaVSKTX0V2VpFRERgY+PD3FxcdjZ2T0Tn9yKIPahbd68mXfffZc6depUSocW7ZR69+5N27Zta+1ZiEbqVlZWnDlz5rHG8sOWSIIg8MEHH+Do6Fjt48lkMrp168a8efO4du2aRI2zt7d/LKpsbSMvL4+MjAyioqI4f/4877//Pj179qxRIkjsdV+zZg0As2fPZsWKFWRmZhIREYG3tzdbtmxh0KBBz/3cUhlkMhnu7u7MmjWLxYsXk56eLmkplHddBgYGTJw4kfnz52Nra/tIY12r1aKvr4+5uTkqlYrjx4/z8ccfs2rVKrp164aBgQFyuRydTsfPP//MG2+8QUhICL/88guHDh2qtB3macPFxYWrV69iY2NDamrqU1dRFv3Md+/ezYwZM8oEpqKNx/Dhw6WKnNh/qVQqGT58OAsWLGDGjBlYWVkhCAJ79+6lffv2EmtCT0+Prl27IpfL+e677/Dw8JAE5J72xkyj0XDlyhUmTpwIPBCmcXZ2rhVaNDxIoiuVSiwsLFAqlc+NJdaTgqWlJRMmTGDBggXk5eXRpk2bZ7KXENt0jh8/zokTJ2okzCeTyfDx8WH9+vUUFBTg4uKCUqkkNze30ucnk8mwt7cnMjISjUYjzUtixTM3N1fqi33RcPfuXRo0aMDt27erHOPiHGNra0thYaEkvvgvHkAQBE6dOoWxsbFkJVZbEG355HI5xsbGaLXa5yJh9SzwXAbCD4swiX90Oh1KpZKCggKUSiVKpZLCwkIKCwulv8/Pz6ekpAS1Wo1Wqy3zR6fTlcrCidUDIyMjtm/fjp6eHqmpqejr6/PZZ59Jvqbin4yMDG7dukX37t1Zt24dZmZmmJmZYWJigomJCaamptIfMzMzSSn272IST/reiferoKCAxMREScAqLS2N4uJiLCwscHZ2xs/Pj3bt2uHk5FSq7/J52Ajm5+dTXFxcqsKWkpKCubk5Wq220uqgIAhcvXqV1q1bc/XqVYKCgp6LaiL8z4dz+/btTJs2DRcXl0qD4KSkJBYuXCipB9fms5HL5dStW5f09HRJOKGm2VgxkfTHH39w7NgxBgwYQKtWrWqkciwe49q1a1y9epWQkBCGDh3K/fv32bBhQ436bZ8kxATGX3/9RUpKCn379qV///41uk6NRsPJkyc5cOAAffv2pW3btujp6eHl5UVBQYHk1anRaCTxsH8yxL64mTNnsmrVKpYvX87YsWNLWaY8/FkzMzOmTJnCvHnzsLW1rbEomiAIGBgYYGxszPnz53FxcaFr165YW1vz+eefExwcjJ2dHb///js+Pj40b94cmUzG0KFD+c9//kNAQABeXl7PxRzo5OREZmYm9erVK0WvfFrQ6XSsXbuWnj174uTkVEbdee/evdSrVw9/f3/p3woLC1m1ahWjRo3C398fMzMzvv32Wz788EMKCgq4e/cun376aRmxrS5duqCnp8ecOXPo16/fM1GMTkhIQKFQ4OTk9ERo0SJlVKfToVAonqsE35OAaAM2e/Zsli1bxo0bNxgyZMhTFQAUBIGMjAzWr1+PSqVi5syZNWLtwAMNCzc3N6KioggKCsLZ2ZnY2Ngqgzx7e3upv1+j0QAPxrqVlRVJSUkvZNCh0+lITEwkMDAQR0fHKtdtMRB2dHSUfMOfh7n3eUFGRgb79u3j448/rnWGTGZmJiYmJhJL6kUcj9XFMwuEHxZfUqvVFBQUkJaWRkZGBpmZmaSlpZGVlSWpmmk0GgwMDDAyMioVeIr/a29vj5mZGUZGRlK5X/wjl8uljfnDL+bD2UlR/Obh///3IFo8D5VKhVKpJD8/H6VSSU5OjhScK5VKiouLKSkpkbJbYoXCwcEBOzs77OzscHBwkBQEFQrFI9mjiOcoihPExMQQGxtLdHQ0OTk5UlbS3d2d9u3b4+DgINHOnvfJJjc3V7JPEpGWloahoWGFVjQiioqKiI+Px9fXl127dvHOO+88jVOuEjqdjjNnzrB//35mzpxZqbDHw3ZKQ4YMoWnTprX+zGQyGd7e3ty5cwdLS0uSk5Or9Px7GKLA09q1a3FycmLu3LlYW1vXWBQtNjaWtWvXYm9vz7fffsuJEyeQyWRSX3FkZCR+fn6Pcom1ArF9YP/+/SxdupTp06cTFRVVo4qlmNRYs2YNxsbGfPTRR9jZ2Unf9/Ly4ubNm1hZWREWFka9evW4devWPz4QhgfjzNjYmPHjx7Njxw4WLlzI5MmTy7W+kslkkljYTz/9xNSpU3Fzc6v2fRYVMDUaDYcOHWLy5Mno6enRrFkzGjZsSGhoKM2bNycrK4vZs2dLCTJzc3OGDx/OypUrmTNnznNha2NoaIhWq8XZ2blKz9PahiAInDx5Eq1WS/v27csEwdHR0Vy+fJlPPvmk1Bq6bds2GjVqJCUwOnXqhFwuZ968eRgbG9O3b99y+zllMhkdOnTAz8+P3bt3M2/evKd2reI1XbhwQUo2FhYWEhUVxVtvvVVr825iYqLkrers7Pxc9aQ/KchkMmxtbfnggw84fvw4//nPfwgJCaFnz55YWlo+kQS1WAzIysriyJEjXL58mZ49e9KhQ4dHqjbK5XKaNGnClStXCAoKIigoiOvXr0tK0BXBzs4OpVKJoaEheXl5mJmZIZPJcHBw4N69ey8kNVr0dU5JScHPz6/Kd0elUpGZmYm3t7dkjfm8FC2eNTQaDevWrZOYcbWN3NxcjIyMpDjpZcZTmYl1Oh3FxcUUFhaSlpZGdHQ0ycnJpKamUlBQADwQPbC1tcXOzg5bW1v8/PywsbGRAh8DAwP09fWf+4yRGOCL6pfin7y8PCnQv3LlCpmZmeTn50sVDNFLtE6dOri5uUmVZjFYF9VQRW/c+/fvS/3MxcXFGBkZ4e7ujoeHByEhIVhbW2NqalqrAlZPE+KEKvZEiBRhlUpVZbUgPT0dMzMzioqK0Gg0ODo6PunTrRKiSMfx48eZOXNmpT3OgiAQFRXFkiVLGDly5BO1dPHy8uLw4cPUqVOHuLi4aimZinZGe/bskbL8DRs2rPFkqlQq2bt3L9euXeONN94gKCgIQRA4fPgwsbGxeHl50b17d/bv3//MhGU0Gg03btxg69at1K1bl/r169OqVSvOnj1breBcEARKSko4duwYJ06c4PXXXyckJKTMJtjd3Z2SkhIsLS25d+8eI0aM4OjRo3Ts2PEf+f6WB319fQYNGsT+/ftZsGAB77//frlVFZlMRt26dRk6dCiLFy9m1qxZVYrjiRCVvC9duoSzs7PkCSz2nhkYGHDhwgVWrVpVRtG+fv36NGrUiK1btzJixIhnviETq4YWFhaSmNrTQlJSEvv372f27NllgoeSkhLWrVvHkCFDpISByJa4f/9+KW9guVxOhw4diI2NZfXq1YwbN67C3ywpKcHa2poGDRqwY8cO6tevX0oj4klCVBKeNm0aMpmMmJgYHB0da40WDXDnzh3q169PXFxcpe0wLyIMDQ3p1KkTMTExnDp1imvXruHh4UHbtm3x8vLC1NT0sd83kQUXGRnJ6dOnSUpKolWrVnz66aelbBgfBfXr12f//v2Sd/KJEyeqFLATWXZmZmakpaVJ7C87Oztyc3OlKvGLhJiYGJycnIiNja0WW0osgpmamqJUKv8RRZqnAUEQCA0NpaSkhPbt2z+R42dnZ2Nvb4+ent5LkZSrDE/k6jUaDZmZmSQnJ3P37l1iYmLIyclBoVBgb2+Ph4cHgYGB9OjRA0tLSynAfZSq6PMGseqsp6dXaqPl4uKCv78/8L9gWaRmFxYWkpSURHJyMteuXWP//v0UFxdjbGyMq6srcrmchIQEcnJyMDAwwMrKirp16xIYGEifPn2wsLDAwMDghbh/IvLy8jA2Ni4VCKekpKCnp1dp76koQtWwYUMiIiLw8vJ65j0nOp2OP/74gzNnzjB9+vRKqWGCIBAeHs7y5csZP358Kdrhk4CFhQVFRUV4eXlx9+7dKiddnU7HjRs32Lx5M40aNWLu3LmYmprWuAp88+ZNNm7cSEBAAHPmzJGy5YIg0KVLFw4fPsw777xDcHAwO3fuJCUlpYxi7ZOEmHjZvHkzeXl5jB8/XmrLyM3NxdzcvMq+c0EQiI2NZc2aNdjb2/Pxxx9XSMuzs7NDq9ViZmYmtS+IicLnqb/9cSH6yBoaGjJ//nymTp1ablJIJpPRuHFjsrKy+Omnn5g5c2a1ghJxc3ro0CEmTJggba5LSkrIz8/H0NBQurd/twuTy+X079+f//73v1y7do3g4OBnOp8qFAocHR0pKCh4qmJZJSUlrFq1ikGDBpV5NoIgcPToUZycnCQ/cEB6V6ZOnVqmvUKlUnHv3j3Gjh3LkiVLmDZtWrn+2mlpaZiamqKvr0+nTp344YcfmD59+lNJZCYkJGBqaoqNjQ2CIHD+/PlabUXR6XQkJCTQpUsXLl68SM+ePWvluP8EiPZGv/zyC5aWlvzwww8A3Lx5kxMnTrBhwwYMDQ1p0qQJ9erVw8bGRrIeKq+nWNw/FRYWUlBQQGZmJuHh4URGRpKVlYWbmxvt2rXD39+/1qz2zM3NMTIyIj09HUdHR8niq7IEnVwux8DAQBLHEmFjYyO1wJiZmT32uT0vEASBu3fv4uXlxenTp6u1XqtUKgRBwNramvz8fKn487IjJyeHXbt2MXXq1CcSpKrVavLz87Gzs5MYtC8zHvsOi3TinJwcIiMjuXbtGrGxscADCX1/f3+aN2+Os7OzJFQCz0cf6rPCw8GygYGBRO1u1KgRgBQkZ2VlERMTw+3bt8nNzUWlUuHs7Ezjxo1p0KABTk5OL+T9FARBom2I1GidTkdubq4UCFcEnU5HWFgYQ4YMYc+ePWVofU8bOp2OAwcOEBoayowZMyq11hEEgTt37rBixQomTZqEj4/PEz93Q0NDzM3NMTQ0JDExscLPCYJATk4OmzZtkiyRaqrkLD7XzZs3k5iYyNixY8vYUMhkMkJCQtizZw9ZWVnY2trSvn17/vjjD4YNG/ZUeuxVKhVHjhzhxIkTvPrqq7Rr1w6FQsFvv/1GSEgI165do0mTJpUeo7i4mH379nHx4kXeeustgoKCKl1s9PT0pKpFZmYmUVFRODo6EhMTQ2Bg4JO41GcGUS1YDIanT59ebmAkUmtFEbYxY8ZUuSnQarUkJyfTvHnzUqq8OTk53LlzB61Wy5dffsnq1atxc3Mr43FsaGjImDFjWLx4Md7e3o9dSXociD2WBQUFaDQaKTn6JCHOV/b29lL/tAiR3n/ixAnmzJmDnp6exHhYsWIFr732WhkauyAIHDlyBC8vL4YMGcKFCxeYP38+M2fOLPPMU1NTsbCwICcnh86dO2Npacl3333HzJkzayS8V1OIgW+rVq2QyWSoVCoiIyMZOHBgrf2m2P/v6OhIRkbGUxc+e1YQW3yWLFlCx44d6datmzQPhoSEYGpqyk8//cSJEyfQaDTs27cPFxcX7t27h0qlkjRXPD09kcvlaLVaiouLiYmJITc3Fx8fHzw8PKhXrx6vv/46bm5upbRZagsKhYKAgACuX79Oz549cXV1JT4+vtJAWCZ74Kuur69PRkaG1ONvZWUlJVSfhVf2k0RkZCRdunTByMioWnojarVaEqtVKpW1wgz4p0On07F161bat29fqYbM40C05FOr1aUKkS8rHikQFnswcnJyuHz5MqGhoRQUFODp6Unjxo0ZMGBAqarXixSkPUmI90kMkp2cnHB0dKRFixbAAyGS2NhYbty4wYoVK9BoNAQGBtKyZUtcXV1fqIpwTk4Opqam0ssp0ut1Ol2lgXBRURG5ublYWlqSmJhYLeP7JwWtVivRh2fOnFluT6QIQRAICwtj9erVvPfee9WiKNcG5HI5Hh4e5OXlSeJzD/dHin3o58+fZ9euXXTu3JmxY8dW2af9d2g0Gi5cuMCuXbvo2LEjo0aNqpC2b2xsTMuWLfnzzz8ZOHAgHTp04LPPPqNfv361ah/wd2i1Wu7evcuGDRvw9PRk7ty5UgVXo9Fw7949evbsybFjxxg3bly5lQqxor927Vp8fX35v//7P6naXRnE5xAfH4+1tTWXL1+mdevWhIaG0rBhwxfmvRYh9oTq6emxcOFCZs6cWW5/uVwuZ9CgQSxatIg//viD7t27V7lRUiqVvPrqq6WOlZGRQXp6Oi1atMDPz48333yT5cuXM3v27FKVZpnsgdJ1mzZt2LZtG6NGjXqmGwQXFxdu376NkZERWVlZEtX7SUBUfL5w4QJz584t8yw0Gg2//fYbAwcOlCjtgiCwbds2XF1dadmyZblV3hMnTvDpp5+ip6dH69atkcvlfPvtt3zwwQelqM8xMTGSe4GBgQGtWrVCLpfz/fffM23atDJJi9pCcXExt2/fpk+fPsADtWh7e/tS+hSPi+zsbCwsLFCpVOh0uheqElgRdDodf/31Fxs3bmTUqFGlEv2RkZH88ssvbNq0ibS0ND777DPy8/P59NNPKSkpYeDAgSQmJlJcXAzAmjVraNy4sbTHmTdvHjExMRgbGzNp0qQn3jInk8kIDg5m06ZN9OjRQ/ITDgoKqvB3xURWYWEhycnJ0t9bW1tjYGAgtX+9KCguLiY3N5f8/Hzq1q1brUqm2Dpobm5OYWHhS18RFgSBmzdvkpSUxIgRI57YmC4pKUFfX5+ioqJSOkUvK2ocCKvVau7fv8+RI0dITEykUaNGDB48GDc3t1r3kv0XpZMIpqamNGjQgAYNGqDVaklNTeX69eusXr0agM6dOxMSEvJC9FmIinbiy1lYWIhOp0Mmk1UqZHP//n3Jf9PCwuKZ0Uo1Gg27du0iIiKCGTNmVLrxEQSBK1eusHHjRt5///2n2j8mkz2wh7h9+zYWFhakpaVJglmCIJCcnMz69euRyWTMnDmzxpvRv9sqTZ8+vcosp0wmo2PHjnzzzTe8+uqrmJubExgYyPnz5yW/0tqEqCy6bds2UlJSGDZsGH5+fqUW5ISEBGmRVqlUZZIxgiCQn5/Pzp07iYiIYOjQofj7+1d7UZfJZHh6epKUlERxcTFpaWl4e3uXapN40SCTyWjTpg0lJSX8+OOPTJs2rdwKrIGBAePGjWPevHm4urqWouT+HRqNhjp16hAQECB9RqvVsmPHDjp06ICrqysKhYLg4GDu37/P+vXrGTNmTKlNgEwmo0ePHnzzzTfcvHnzifboVwU3NzeOHj2KtbX1Ew2EBUGgsLCQ1atXM3z48DLJG5ESbWFhQbNmzaQ2hpMnTxITE8OMGTPKbKQ0Gg0bN26kd+/eUgJLJpNJAbPIBhAVqePj4yW9DPG3W7RogVwuZ9GiRbz33ntPpEISExODra2ttFacP3+e5s2b1+qGPCoqCi8vLxITE7G3t8fQ0LDWjv08QqVSsX//fi5fvswHH3wgPbeMjAy++eYbiRUkCAKenp6Se4GBgQETJkzg5s2bWFtbU1hYiFwuJzk5mddff10adw0bNuTo0aMsXryYxo0bS//2JOHk5CQljP39/Tl+/DgajabC1quHhbFE9WiZTCYJlr5ogXBKSgoWFhbEx8dXSygLkNgupqamFBcXPzEBtX8KCgsL2bBhA+PHj3+ifsqirlBxcbHUVvkyo9ojTswWf/fdd2zbto1WrVrxf//3f7z11lv4+PhUGXyJC61KpXqsExYVXEtKSh7rOP906Onp4eLiQo8ePfj4448ZOnQoN2/e5IsvvuD8+fP/aCEGkW3wcO9Ceno6pqamGBoaVvjSCoLAtWvXJFXHxo0bP8Wz/h/UajVbt24lJiaG999/v9LAXafTceHCBTZt2sT06dOfiYiKh4cHcXFxuLm5Seq0RUVF7Nu3jx9++IHWrVszderUGm1CRXrw/v37+f7772ndujXTp0/H1dW1WsewsbHBx8eHv/76C4Du3btz8uTJWn/vi4qKOHDgAN988w3e3t58/PHHZQJYMVHRuHFj7t27h6+vb6lst1ar5fLly3z11VeYmZkxZ84c6tevX+MFvW7duuTn50tUsaysLExMTEhNTa21633eIJfL6dy5M82aNePHH39EqVSW+znRk3TNmjWlqisPQxAEbty4QZ06daTNqZhhP3z4MDY2NhIVUewHzs7O5tSpU2WsIwwNDRk2bBgbN26UBB2fBczMzCgsLMTJyanC664N6HQ6Nm3aRFBQULmWVQkJCRw9epRhw4ZJlOhbt25x4MABJk2aVKZ/WxAE/vrrL4qLi2nXrl2Z9ocWLVrwxhtvsGDBApKSktDpdGRlZaFUKkv1bstkMpo1a8bAgQNZtGgRCQkJtWrzIQgCZ86ckSrVarWa8PBwGjRoUKu/ERkZiY+PD7GxsXh4ePzjE9UVQUwILl++nPj4eGbNmlVq3VCpVFy4cEEKgmUyGf379ycsLIxXXnmFOXPmcOTIEUn1Gf7ntiDuacRkSnZ2Nvn5+Xz44Ydcv379idu/GBsb4+Liwv3797G2tpbESyuDo6OjZOspnp+hoSEmJibk5OS8UJY1UVFR1K1bl5iYGLy8vKr1naysLNRqNaampqhUKkxMTF7Yd6Mq6HQ6duzYQXBwcI3cOx4F6enpknezsbExCoUCtVr9RH/zeUa1dmo6nY7Dhw/zyy+/0LNnTz766CNCQkJqNGgLCwuZOnXqY6tfqlQqPvnkE06cOPFYxxGh0Wj4/fffn8qElJ6ezunTpyv8d0EQ+PPPP8nJyan2MWWyBxZN3t7evPPOO0ycOJHTp0+zbNkyCgsLa+Gsnz7EIMrc3FwKJtLT06U+yooCYZ1Ox7179yTrmWdRyVGr1WzcuJHU1FSmTJlS6Tui0+k4ffo0u3fvLpU1f9qwtLQsJZgVERHBf//7X5KSkpg7dy5t2rSpkeCYuPH7+uuvSUhIYM6cOTU+hthH+scff6DVanF0dMTOzo6bN2/Wyrsqin59+eWXJCQk8NFHH9GtW7dyE3qiL3VQUBBXr16VrKzESvLSpUs5cOAAkydP5vXXX3/kxdzOzg6NRiNVh0XBpr/++uuF2jD9HXK5nB49etCwYUN++ukniQ75MGQyGR4eHgwePJglS5aQn59f5jOiR/PD/qwlJSVs2bIFX19faYyLMDAwYOzYsRw4cKCMPZFM9kC5unnz5mzfvv2Z3X8jIyO0Wq2kxPqkEBoaSnJyMn379i2TwCkpKWH16tUMHjxYokQnJSWxatUqJk2ahI2NTZnj5eXlsWPHDoYNG1YuRVLUAhg8eDALFy4kPDyckpISCgsLy1S9xc+++eabLFy4sFatpIqKioiMjJTaD+7fv4+NjQ3W1ta19hsajYb4+Hjq1q1LeHg4vr6+tXbs5w3JycnMmzcPNzc3JkyYUKYdyNnZma+++kpKBtjb2xMQEICVlRWbN29mw4YN5doKXbp0iezsbOm/69atK7EMREbCw4JUTwIymYygoCCuXbuGQqGolq2Zo6MjeXl5qNVqKYmrp6eHiYnJEz/fp43bt29Tt25dSkpKqvRYFiGKABoaGqLRaCSBtJcRERER3L59u9w5uLaRlpaGtbU1RUVFmJmZScnNF3mfURmqvNuCIHD27FkuX77Mxx9/TOPGjR+pH8PExITc3FzS09O5du0aRUVFCIJAXFwcFy5ckKxubt68SUJCAnl5eahUKsLCwkqZjxsYGFBcXExWVhbXr19HqVSSlZVFWloaN27cIC8vj4iICJKSkiQ/2ZiYGOLj48nIyOD27dtotVrpvO7cucPPP/9MWFgY2dnZnD17lszMTEkY5MaNG1I2Ly0tjWvXrlFcXCxVuC9fvkx2djbZ2dkkJiaWyliLx4iOjiY6Oprff/+dHTt2kJKSQnR0NJcuXaK4uJiMjAySkpK4e/cuS5Ys4dSpU49U0ZXL5bi7uzNjxgycnZ1ZvXr1P7IyLNrziNLu4r0XrZAqmiQyMzOBB8IWSqXyqQtRqFQqVq9eTW5uLhMnTqyUJaHT6Th+/DiHDx8u0yv3tGFiYoKlpSVqtZrff/+dX3/9lUGDBjFu3LhKxb3+DkEQKCgoYN26daxYsYJBgwYxfvz4CpWSq0KdOnUwNDTk3r17yOVyevbsycGDBx/Lf1EcS4sXL2b79u2MHDmS8ePHY2trW+E5pqeno1arsbW1JSEhAS8vL9RqNceOHePrr7+mXr16fPTRR49dzTc0NMTIyAhLS0ssLCy4e/cuQUFB3Lhxo9Sc9SJCT0+Pvn37Ymdnx7p168qdt8TqYLNmzVi5cmWZDHZycjK5ubkSvVoQBM6dO4e1tbWkfvx3X2YbGxvefvttfv31VwoLC0ttBGQyGb169SI8PJzw8PBnskkwNDTE0tISnU4nCe7UJsTWha1btzJu3LgylF1BEPjjjz+wtbUlJCQEeNBvvXjxYt5+++1ytQx0Oh2bN2+mbdu2lTJAZDIZTZo0YciQIfz3v/+V2g7Ka2cRezSHDRvGggULiI2Nfex7ITIIPD09MTc3l/Y6YnW4tiAy4aysrEhLS3su7PxqG6Jbw7fffku/fv3o379/qYSU+JmYmBh2797NihUr6Nq1K506dSIiIgI/Pz/WrFlTYVUqLS2NsLAw6Znr6+uXEhw7deoUP/zwwxPf79SrV4+IiAgA/P39uXPnTqXjUGSDGRoaSoG8aIuWkZHxRM/1aUKlUpGUlIRcLsfe3r7arTx5eXmSc4xarX5pA+GioiLWrl3L8OHDn0obVFZWlmQxampq+tLbJ1U54kpKSjh06BATJ06s0ab47xC/V1RURFRUFIsXLyY9PZ1ff/2V06dP89tvv3H27FmKioo4ePAg4eHh7Nixg7i4OBYuXEhaWhqFhYVSxaSwsJCzZ8/y888/89lnn7Ft2zauXr3KvHnzyM/PZ9asWezdu5f33nuPgoICpk+fTlZWFt9++y13796luLhYolinp6djZGTEr7/+SmRkJB9//DHR0dF8++23pKWlMXr0aI4fP84XX3xBbm4uY8eO5dy5c6xatYrMzEzmzZvH7Nmz2bBhA3FxcZSUlFBUVER2djaXLl0iLy+P9evXSxNFdnY2q1ev5uDBg6xbt44ZM2awZ88ekpKSiIqKqpa4TmX3WaFQ0L9/fwoLC7l///4jHedZIz8/v1RwkpCQgIGBQYXqoaLiso+Pj0TNeZovd3FxMb/++itqtZoJEyZUGQQfPnyYU6dOSZ7Cz5IOJHpZL1u2DD09PaZPn07Dhg3Lta6o6PtarZZr167xxRdfYGBgwGeffUZgYGC1j1Ee9PT06NmzJ/v27UMQBHx8fFCr1cTExNR4Eyy2VOzdu5dvvvmGgIAA5s6di6+vb5Xnd+vWLfz9/UlMTMTOzo709HT++9//cvPmTamSXFPxsPKgr6+Pi4sLCoWCgoICtFotMplMUpB/0aGnp8fQoUPJz89n79695Qb/MpmMPn36SH7TYlJEpOL6+vpKG/DCwkIOHjwoCWwVFxeXUXmVyWQ0atSIBg0asHXr1jLjytjYmGHDhrFu3bpyK9VPGuLGUqPRkJubW+sJEVHxedCgQWXmVlHx9+TJk7z11lvIZDJyc3P58ccf6dWrF02aNCmXPXH58mWSk5Or1c8vBrhvvPEG58+fr9RSRqzIjRo1ih9//PGR5oG/49SpU5KzQHFxMREREbWu0p6ZmYmVlZUUEJdXQf+nQhAENBoNBw8eZOPGjUybNo1mzZqVCWYEQSA6OpolS5YwZswYXnnlFdavX8+QIUOwt7enV69eHDhwgD59+uDl5SWxvh7eN168eLHUMeVyOSYmJnh4eDB37tyn4v3t6OiIVqslIyMDf39/wsPDK03MinsQc3NzKRDW09OTfHNflAqc2AOdkZGBl5dXtdfCnJwcLCwsUCgUqFSqF0LfpqYQBIGDBw/i7e39xO0yxd/LzMzEzMwMrVb70gtlQTUCYbGhv7aoQvb29rzyyiscPHgQhUJBly5dKCgo4NatW+h0OjZs2ICLiws+Pj6sWrWKmzdvYmFhwfHjx+nYsSMrVqwAHtA5XV1duXfvHjY2Nujr61O3bl0iIiLw9PTk3r17uLq6SnS42NhYbG1tKS4uJjk5mdGjR/P6668jCAJmZmb4+PjQq1cv5HI5165dA5AUivX09KhXrx5arRZnZ2d0Oh02NjasX7+e8PBwrKysMDc3x8LCglatWjF58mR69+5NXl4eZ86c4fTp0wwdOhRTU1Pc3Nzw9vamY8eO5OXlERMTg5mZGXZ2drRr1w4jIyP8/f0fe2Dq6enh5uZWqSXO8wqtVkt2dnapMZednU1JSQlOTk4Vfu/y5csEBwdz9erVp+oBWlRUxIoVKySq5d8z4Q9Dq9Wyb98+QkNDmTZt2jPdFIkT4vLly7l9+zatWrUiODgYlUpVoypwZmYmy5YtY+/evUyYMIHBgwdXy/O1OggMDCQrK4vExEQMDAzo0qULBw4cqNExNBoNV65c4YsvviA9PZ05c+bwyiuvVKha/TAEQeDSpUs0a9aM0NBQYmNj+fnnn+nVqxfvvvtuubY/jwqR/qunp0d0dDS+vr5ER0dTv379p9ID9zzA0NCQ8ePHc+3aNc6cOVPuNevp6TF69GjOnDnD3bt3JV/R69evExAQIL1/x44dIzAwUHrOCoWi3CBLLpfTr18/YmNjuXbtWpnf9Pf3x8PDQ+pdfNpwcXFBqVSi1WprtV9Zp9Oxb98+nJycyvXMFRkugwcPxtLSEqVSyZIlS2jVqhVt27Ytd9xnZ2ezefNmRo8eXW2xFzGx3apVKyIjI6X+0Yo+GxgYyMiRI/npp5+Iiop65GeSlZVFdnY23t7ewANqopOTU62qRQOEh4fj7e1Neno61tbWz9zXvrYgJhdXrlzJrVu3KmTFCIJAVFQUS5cuZdSoUZKQnaWlJVevXqVfv34YGBjg7u5OvXr1mDVrFgMGDMDKyoq2bdvSr18/vvnmG1q1aiUd08jIiNGjRzN06FDGjBnDwIEDH0mXoabQ09Ojbt26REZGYmtrS35+fqW6N/r6+hgaGmJgYEB2djaCIKBQKLC3ty+3veOfiqSkJJydnbl79y7169ev1nfEPnArKys0Gg0ajealE9wVWbEXL15k4MCBT6UartPpyMzMlITJFArFS1mFfxhVXr21tTWGhoZER0c/9o+J9Ie8vDwaN25Mbm4uP//8Mz4+PpJwwrBhwwgLCyMlJQUbGxt8fX3p378/Xbt25eDBg4wYMULisot/dDpdmb/7+98D0n/LZDKWLl3K+vXrpT5UpVLJ/PnzcXFxQS6XY2pqStu2bTl+/DhTpkzBzMyMLl26cPDgQSZNmoSFhQUWFhaEhITQp0+fUpvqH374gW3btmFubk7nzp1xd3fn+PHjKBQKtFot0dHRrF69mrp165Y6J3iQQRSp14+D4uJiwsPDqVev3uM9tGcA0QJJDIRFAY78/PwKTdpFao6LiwvR0dH4+fk98fMU6fHLly/H0tKSESNGVBoEazQadu7cSVhYGNOmTavVPrSaQq1Wc+LECf773//i4+PD3Llzyc/Px9PTk5iYmGodQ6VS8eeff/Lf//4XX19fZs2aRd26dWt1IdPX16dz58788ccfCIJA06ZNiY2NrVZ/lbjILFiwgMOHDzNu3DhGjRpVytqtKuTm5pKWlkZBQQGbNm0iODiYuXPn0rRp0yeSRfX29iY3N5fs7GwaNWrE1atXpSD8ZQiE4QGdcPLkyezfv7/cnnCZ7IE/55gxY1i9erXUmqLT6SRarVKp5NSpU/To0YPY2FgsLS3LtWcSYWRkxKhRo9i4cWOpXkTx99544w3OnDnzRAWrKoJoq2VqalprgbAodnXt2jWGDBlSZiwLgsDevXtxdnYmODiYvLw8Fi1aRGBgIN26dSt346TRaFi7di1du3bF3d29RueTmJiIh4cHzZo146effiI6OrrSYLhhw4aMGjWKpUuXcv/+/Ud6N0JDQwkKCsLQ0FASzWrXrl2Nj1MZdDod4eHh+Pn5ERcX98IIZQmCQHp6Ot999x3m5ua8++675bbACIJAREQEP/30U6kgWBSxMzExkYSBTp8+TePGjcnJycHX1xcjIyPq169P3759mTlzJp06dZKOb2BgwIgRI7C2tqZhw4acP3/+qc2PwcHBXLt2DWNjY2xtbSstNujp6UnJ7rS0NODB+LWzs5MC4xcBt27dws/Pj4yMjEqLFQ9Dp9ORnp6OpaWl5Gv7IrojVAa1Ws3atWsZNGjQU3M4ET3p9fX1kcvlL0xi7nFQZSCsUCgYPHgwy5YtkxacR31533vvPe7du8eFCxeYMWMGtra2eHp6YmdnR7NmzUhKSiI1NZXGjRtTp04dZs6cye7du7l48SKWlpbY2tpKfYgRERFERESQk5Mj9QDfunULeGB/YGNjw++//46hoSFnz57F2tqaCxcuoNPpuHv3LlZWVpKKaKtWrUhKSiIoKAi1Wk2fPn3Iy8uTenq//vprLl26xP79+9mxYwfffPMN0dHRTJo0iUWLFhEdHU1OTg75+fkIgoClpSU2NjaoVCoSEhIoKSnhlVdeoUOHDtLAc3Nzw83NDR8fHwoKCsjMzEShUDBw4EBiY2MfuQ9SEATy8vJYsmQJgYGB/0jD9oKCAvLz8yUxjJKSElQqFQqFosJKY3x8PBYWFhQXF2NiYvLEfRrFbPiPP/6Ik5MTQ4YMqXBCEelj27ZtIzo6mqlTpz4zWydBEEhISOC7776TrC26deuGq6srhYWFODs7ExkZWek7LlImv/vuO65du8asWbPo1q3bE8nmihY7d+7cIScnBxMTE1q3bs3Ro0crPEfxHVi/fj2LFy+mbdu2fPDBB9StW7dGmU9BELh79y5Xr15lzZo1eHp6MmLEiEr9oB8XIg1W3EAlJCRga2tLbm7uC2e3URFEEZ3JkyezatUq4uPjyw2GfXx86NatG7/88gs3b96UKHlyuZzTp09Tv3597O3tpY2qm5tbpb/p7u5Ot27dymgriIF337592bRp01Pv17a2tiY7OxtLS8saCSlWhuzsbNauXcvo0aPLqNoLwgMv7NDQUN58803y8vJYuHAhwcHB9OnTp9wEkCAIHD9+HJVKRZcuXWr0fmg0GjIyMigsLKRHjx6MHj2aJUuWVBrgymQyGjRowNixY1myZEmVc1Z5v3nhwgXatGmDTCYjPz+f2NhYGjRoUKvvtkajISUlhTp16khCjv90iPPivHnz6Ny5M2+++Wa51X+xXWnp0qVMmDCh1L3VarXs2bOHvn37oqenh1qt5uzZs7Rs2ZL09HRycnJwcnLC3t6+wrVSX18fHx8fFAoFERERFBUVPdHrFuHj40NcXBxqtRofHx/u3btX6Ti1t7dHX19fSqLJZDJsbGzIzs5+bBeV5wFarZaoqCisrKzQ19evtlCW2PJjYmIiBcIvg7+2CHHOtLa2pnHjxk8tQabVatHpdGi1WikeERlTLyuqvHKZTEa9evUYNWoUy5cvJyQkhF69ej1SH2uzZs0ICQkp9b2vvvqqwt8NCQlh9erVpT5vamrKqlWrKvyNCRMmSCInDx9LXJxfffXVUp83Nzfnyy+/BJAWqe7du3PlyhV+/PFHzM3NiYmJISwsjG+++QYrKysSEhIoLi6mTZs29O3bt9RxHz5XJycnxo4dK1V8PTw8CAoKAuDLL7+UPjtq1Cjpu++9914Vd7F8CIKAWq3mwoUL/P7773Tu3FnqjfunQalUoq+vL2VSs7OzpZe1Iv/FGzdu0KhRI27cuEFAQMAT7XkQxbwWLlyIn58fAwYMqHASEftnN23aRFpaGlOmTMHY2PipVwUEQZD6/U+fPs3AgQMlr0yZTIaRkREWFhaYmZkRHx+PTqcrt0pUUlLC/v37OXfuHIMGDZL6wZ7k9ZiamtK4cWPOnTtHr1696NixI1999RV9+vQptUkSEw5nz55l7969tGjRgs8++6zGKs7iu3TixAnmz5/PiBEjcHR0JC0t7YlnT83MzBAEAQsLC3JycrC1tSUzMxMfHx9u3rxJ27Ztn+jvPy+QyWTUqVOHESNGsGTJEj7++OMyGhUymYyOHTsSHh7O0qVLmT17NlFRURJTYcaMGeh0Osmex9PTs8rf7Ny5M9euXeP06dN07NhR+j3RsuXkyZNcv379qbZeWFhYoFQqadCgAQkJCTRs2PCxjqdWq/nll1/o0aNHuQwOpVLJb7/9xujRoykuLmbx4sW0a9eOV155pUJ9hqioKI4cOcLHH39c47m3sLCQkpISSkpKcHZ2xsfHh3HjxrFkyRImT56Mj49Pub8rk8nw9/dn0qRJ/PTTT0ycOJF69epV67kkJCQgk8lwdXWVAn9PT89ar0gplUpp3UpOTq40GfO8Q2TZnTx5UrLN8vb2rnBMhIWF8dtvv/H++++XElUTBIHbt29jYGAgPdvbt29ja2uLXC7H0NCQu3fvYmZmhrGxcYVUdVE8748//sDS0pKEhISnkmiwtLREoVCQnZ1NQEAAe/bsKbXf/Dvs7OxITEwsJQRmbW1NTk4OBQUF//gqaFFRkaSMLTIqqwONRiNZJqn+H3tXHR3F+Xbv7G5W4u4uhAgeXIq7OwVSoALFoaVFi7alLS3WFi1tcUJxd/dACCQQd082m2RdZub7g2/mlyWuJC33HE7Lsjs7MzvzziP3uVejYf2E/yvIycnB5cuXsWzZsnpNQhUKBQwMDCCXy2FoaMjGNI0xV6gtVOrICYKAn58fVqxYAYqisHr1ahw8eBAZGRnQ6XSVrsQy1XqCICr8U9r7i79W3p+331N8O8xrxfeptD9WVla4efMmTp48CWNjY7Rr1w73799HSEgIeDweaxj+9nbfDtTKOubirxX/7NvnoCJQFIWioiJcvXoVq1atQlhYGBYsWICBAwc22gqPTCaDQCBgH4AFBQVstbA06jFFUYiMjERgYCBrOVNXQSrTbfz5558RGBiIkSNHlnueGbqgWCxm/TbrOwmmKAqxsbFYt24dcnNzsWLFCnTo0AFcLlfvvnJ1dYVCoYBMJishDESSJF69eoXVq1ejqKgI33zzTYlt1BUIgkCvXr1w+/ZtqFQqWFhYwNfXF48ePWLXHpIkERUVhXXr1uH58+f48ssvMWbMGBgZGVVp/yiKQkJCAr777juEh4fD3d0dw4cPx/Pnz0sU8eoCAoEA1tbWMDIyQlxcHFq1aoWnT5+iQ4cO9Ur/awggiDfiSD169MCOHTtK9ZDm8XiYPHkyxGIxFAoF5HI5IiMj4ejoCDs7O2g0GjZIs7e3r/D343K5mDp1Ks6dO4ecnBy9821gYIAPP/wQISEh9dZ9AsCqegoEAmRlZdVoWxRF4fTp0zAzM8MHH3xQ4nyQJImQkBC0atUKfD4fP/30E/r27YtevXqVWvBixlZ2796NqVOnlks/LwvMel9UVMSOLTAJ7u+//15hx83HxwczZ87Ezp072Znx8sCoiXfq1Iml6d67d4/tDtcmEhIS4OLiApVKBY1Gw6qXN0ao1Wrs27cPDx48wJIlS8pNgp89e4a9e/di/vz5JZTFKYrCyZMnMXToUPB4PFY8sl+/foiMjISrqyvLCKNpuoTAXXF4eXkhOzsbzZo103se1CUIgoCXlxfi4uJgY2MDsVhcLoPPwcGBHe1iYGpqCrVa/U49ymsL+fn5MDExQUxMTJWKdCRJsveEWq3+TyXCOp0Of//9N4YNG1bvOjE5OTksy8zU1JSNqWvixtHYUelMiaGHjR8/Hv3798fDhw/x+++/QyQSISgoCC1btoSlpWW1rJUaItzd3Ut0EKo691QXYKqyUqkUMTExePToEVJTUxEQEIAZM2bAycmp0SvAyeVyiEQitlIlFotBkiSsra1LrVoxtFFLS0tIpdJKz6hUFTRNo6CgAJs3b0a7du3Qr1+/cs8147+p0+lYJen6BJO0nzx5EtHR0Zg4cWK5giK+vr54/vw5DA0NUVRUBCMjI9A0DYlEgn/++QdpaWmYMmUKfHx86r16aGNjAwcHB7x48QLt2rXDwIEDsW3bNnTp0gX5+fkICQmBRCLBmDFj4OfnV+V7gKZpFBYWsudq/PjxEIlErIdsXl4e3Nzc6ujo/geGopuTk4OkpCQEBwdj69atGDRoELKzsyGVSmtdzKchgyAI9OnTBxkZGTh69Cg+/PDDEr+tWq2Gh4cHTpw4ATMzM0RERLAsH6bTwCTClfk+a2trDBkyBPv378fcuXP1WADu7u7w9/fHuXPnMHr06Hp51nG5XJibm4PH4yE3N1dPU6IqYOyCnj17hiVLlpQo4NE0jefPnyMlJQV9+/bF77//jmnTpsHPz6/M79PpdPjzzz/RoUOHct9XHrKysiASifT8R5kEd9asWdi2bRumTZtWJm2Zee/nn3+O7du3Y+rUqeVSnJVKJV6+fImvvvoKBEGgqKgIWVlZte7vS9M0oqOj4ePjA7FYDAsLi0b5bGYEEXfs2AEnJycsXLiwzC4mRVG4f/8+zpw5gwULFsDR0bHE7/D69WsAb0TogDe2ZxKJBE2bNsWFCxcQEBCAnJwcttlQHtXWyMgIlpaWsLS0xIMHD6DRaMpkjdUmAgMD2QKlgYEBcnNzy1xfrKysoNFooNVq2f2zsrJiu3KNHdHR0fD29kZMTAz69OlT6c/pdDrI5XJ2jJDxEf63gynEAaiT4ltFyMnJgbW1NaRSqV6c3RitVmsLVY5mCYKAhYUF+vfvj2+++QYTJ05EYWEhfv31V6xbtw579+7F8+fPkZeX96/3vqwvMAlNbGwsTp48iR9//BE//PADwsLC0K1bN6xatQrBwcFwdXVtlA/a4mBmwA0MDNhALS0tDQKBoEyv3ZSUFDg6OiIhIQHOzs61plj89n5JJBL8/PPP6Ny5c4VJMKMkzeFw8Omnn9Z7EkySJEJDQ/Htt9/CyMgIy5cvh7+/f7kJrIuLC7KysuDi4oKEhARotVrcvn0b3333HRwdHbF06VI0adLknVBoGCulixcvgiRJODo6QiQSYdOmTdi4cSNat26NZcuWVYsWr9VqcffuXXz77bcwNTXFihUr0Lx5czx79gytWrVCUlISHBwc6uS6Kg0+Pj6sbgDT0VapVHB1dUVMTEy97ENDAo/Hw4cffoiUlBTcvHmzRNcnMzMTgYGBGDx4ME6cOIEWLVqw3ars7GwIhULw+fxKB1kEQaBTp04AgPv37+t9H6Mw/fDhQ2RnZ9feQVYApggokUjK9FqtCLm5udi/fz8+++yzUueCJRIJ9u3bB3Nzc5w7dw4LFy4sN7mlKAonTpxgPb6ruy4kJSXB1NSUVTFlwHTeZs2ahT///FPPR/ZtMO/9/PPP8ccff5QqssYgPj4eNjY2bMfx5cuXrDhTbYKmacTFxcHHxwcxMTG1nmjXB5hkfv369ejUqRMmT55c5n1EkiSuXr2K8+fP48svvyw1CdbpdDh58iSGDx8OHo8HmqZx48YNdOnShU248/PzYWNjA1tbW5AkWWFiGxQUhLi4OIhEonoRs2MKLykpKSBJEs7OzkhOTi7z/YwlEI/HY3UezM3NweFwGn1HmLk+HB0dIZPJqtSEkMvlUKvVMDU1hVarhVarrbdn7LuEWCzG6dOnERwcXO/xOiNyZ2NjA5lMBj6f/14sC1XoCL8NgiDA5/Ph7u4ONzc3jBw5EgUFBYiKisLdu3eRkZEBgiDg4OCApk2bwsXFBXZ2djA1NS1BH34P6D20lUolcnJykJmZidevXyM1NRUKhQJWVlYIDAzEhAkT4OjoyF7A/7ZzKJFIwOPx2OPLycmBRqOBk5NTiffSNM3aJT19+rRUb8uaggkSf/zxR/Tp0wc9evQoM+ijaRoqlQo7duyAmZkZJk2aVK8UdSaY2L9/P6RSKWbPng0XF5dKnRM7OzsoFArY2tri3r17uHXrFgwMDPDll1+W6d9cn/D09ATwxuYkMzOTnQf97bffquVxzqhK79u3DwKBAAsWLICDgwMIgoBOp0NERARmz56N06dPo127dvV2/Pb29pDL5eBwOFAqlfD390d4eDg6duyIBw8eoE2bNu/8t6hvCIVCzJgxA+vXr4eDg4NegpaYmAhPT0906dIFQUFBsLe3B5fLZUXdTE1NWf/5yoLH42HSpEn48ccfERAQoEdpNTU1xaBBg3DkyBHMnj27XoIZNzc3ZGZmgiRJqNXqctXp3wYz2797924MHTq0VIsbkiTx66+/IjExEd7e3liyZEm5YwWMynJERAQWL15cpf15ezsZGRng8XilBtEEQcDDwwOzZ8/G1q1bERwcjObNm5fZGfb09MTcuXOxadMmTJ06tcR7mRlXxjuY6c4MGzas1u8prVYLmUwGCwsLJCQklGk51RDBiKLeuHEDFy5cwPTp08uc1Qb+J37FiCe+Hecx24yOjgZJkggICAAASKVShIeHY/ny5azFZWJiIuzt7WFra4usrKxyE2GCeGOndevWLQQFBeHRo0f1osxtZGQEDoeDoqIi+Pv7IzIyEu3bty/1vUKhECRJwtDQEFKpFDY2NhAKhTAwMGj0ibBOp0N6ejo6duwIU1PTKiVVjFgYQxOnKOpf3xEmSRKHDx9Gnz593llMlZ2dDV9fX0RFRbHX4X8dtRKhM9Uua2trdO7cGZ07d2Y9wtLS0ljlVbFYDIJ44x/n6OgIZ2dn2NnZsQly8XlbZrv/FjCJbnFbJybhzc7ORmZmJlJSUli/XFNTU7aI0KdPH9jb27MJ1b/pvJSG/Px88Hg8tmJcUFAAlUoFOzu7Eu/VarWIjY1Fv379cOHCBYwYMaJW94W5jn/66Sf069ePVf4uC0qlEr///jvs7OxYW5L6+L0Yoajbt2/j7NmzGDBgAHr06FGlUQUulwuRSITw8HBcunQJ69evR4cOHepcDKsyoGkaHA4H3t7emDNnDoYMGYLVq1djx44dKCwsZBXGK7stmUyGkydP4sWLFxg7dixat26td5xisRjAm4AnPj4eo0aNqpPjKg2WlpZQq9WwsLBATk4OgoKCcPz4ccyaNQshISGQy+X/KXVN4H9KqzNmzGDFs2xsbAC8YYR06dIFJEkiNTUVoaGhmDJlCjw9PZGWlgaKoipdDCr+fba2thgwYAD27duHefPm6T2Xunbtihs3biA6OrralOCqwM7ODi9evICBgQHUanWVVOdpmsY///wDBweHUql4zMzm5cuXsWTJEpbtUl4SHBUVhVOnTmHJkiU1Cl51Oh2ys7NhbW1dpuUdQbwRmpw3bx42bdqESZMmlakDwbx34cKF2LRpE4KDg9GiRQv2vVKpFKmpqZg2bRoIgoBEIkFBQQFcXV2rfQxlIT09HWZmZjAwMEBGRkaFYm0NCWq1GocOHUJGRgaWLFlSpuUc89wJCQlBamoqFi1aVGYBhSRJnDp1CiNGjACHwwFN03j8+DH8/f1hamqKq1evwsfHB6dPn4ahoSE8PT2RkpJSYUfYxsaGFcMLCQnBqFGj6rz4zOPx4OnpyYqsXbt2rcyRBYFAAJFIBJIk2Y4w04ljnjONFQy1Oy0trcqWlYWFhazlHaOG/2/uCDOjJ/n5+XpWYPW9D2KxGFZWVpDJZDA2Nv5Xn/PKotZXi+LiO9bW1rC2tkbLli0BgPUQLigoQEZGBtLS0vDixQuIxWLWHofP58Pa2ho2NjYwNzeHubk5LCwsYGFhAT6fDy6XCw6Ho/ff4t9bnyjuT8zIkTP/1el0KCoqQn5+PgoKClBQUACxWIycnBwoFAq2Q2FhYQFbW1s4OjpiwIABsLCwgJmZGUun+S9CKpWyUvzMHAmPxys1+GcWU5VKxV47tQWmE/zLL7+gX79+6F5MRbY0yGQy/Prrr3B3d8fo0aPrrRPMdL727dsHIyMjLFmyBDY2NlW6fkiSRHR0NF6+fAkPDw+0adMGQUFB75xqz3QmUlJScPToUcjlcri5uWHcuHGws7Njvb2nT59eqW3pdDo8efIEJ06cQNu2bbFy5coSgRvDMggICEB+fj4EAkG9ej4zCt7m5uaIiYlBv3792IDJ1tYWSUlJNVYOboxgOn4jRozA9u3b8eWXX0IgECAvLw+2trZISUlBZGQkBgwYgN27d2PJkiVITU0Fj8erciLMfF+3bt3w4MEDPH36VE8sjcfjYfz48QgJCcGSJUvqfC7RysoKBQUFMDMzQ35+fqXXOZqm8eDBAyQmJuKLL77Qu59p+o0P+oEDB3Dp0iX88ccfFaou0zSNpKQk7NmzB59//jmsrKxq9JzSaDTQaDSsR3xZ22LE/BYsWIDNmzeDJMkyxeuYOfv58+dj69atoCgKrVq1AvDGO7hZs2YQiUSgaRqPHj1C8+bN62R0JT4+Hp6enqywWmMQAmIC5e3bt8PZ2RlffPFFmeeGYRowOhhz584tM6hm/IR1Oh1bOFKr1bh+/TpmzZoF4I0X7bBhw5CSkoIWLVqwyXdF9xaHw0FAQAAyMzPB4/GQlZVV5+rcBPFGQDYyMhJBQUFQKBRl6jdwuVyYmZlBJpOx4xR8Ph8EQTT6RDg+Ph5OTk5ITk5mWRaVRVFREQwMDGBiYgKFQgGCIBrFPVIdMMX3I0eOYObMmdVm0NTGfqjVavB4PCgUinItSf9LqFdZYQMDA1hZWcHKygpeXl4A/mcvw3jFqlQq5OTksF5yqampkEgkKCwsZIe5mQRUJBLB0NAQQqGQ/SMSiSAQCNiKG5/PZ//O5XLZBQiA3v9rNBp2u1qtllW0Y2wdmBkGtVoNlUoFlUoFpVIJuVyO7OzsEjRlDocDY2NjNrE1NzdH8+bNYW9vDyMjI3a/GFug9/gfZDIZrKyswOVyUVhYCLVaDYFAUOoi+fr1azRp0gRRUVEVzsBWBYx40qZNm9CjR49SFVaLo7CwEFu3boWfnx+GDx9ebwmkQqHAhQsX8OjRI4wePRqtW7euUgJeXAwrNTUVI0eOhFwuR2ZmJvLz8+Hg4FCHe1/xvuXl5eHkyZNISEjA8OHD0apVK5w7dw7Xrl3Dhx9+iKCgIJw7dw4SiaRc9UWKopCSkoKDBw/CwMAA8+bNg5OTU5m/aWhoKMaNG4fnz5/Xq8cf8GYNcXJyAkVRSEpKgkgkgouLC2JiYlh6dEBAwH9y3SCIN77SCQkJ+OeffzBixAjI5XJYWFiwNiotWrSAjY0N9u/fj4KCAgiFwlLHKioDPp/PWjg1adKEZR4wysaMSE9F60NNYWlpCaVSCXd3d6Snp1faJiYpKQknTpzAokWL9AIeRgV+9+7dePbsGbZt21apJDgjIwPbtm3DRx99VKZqcFXABMBFRUWlMn7ehrOzMxYsWIAtW7aAoqgyRxaYZHju3Lnse1u2bIm7d+/i448/BkEQIEkSDx8+ZP9e24iMjESPHj2QmZkJGxubd15UrAhMp/+PP/7A4MGD0bVr13L3WS6XY9u2bbC1tcX48ePLTVhJksTJkycxbNgwlukVGRkJc3NzdhREKpWCpmm2ycG4RFSUNBAEgTZt2uD06dNo3rw5QkNDy13bawve3t44d+4cK2aXk5NTppChhYUFtFotq/rO5/NhamraqKnRxW3H7t27Bw8Pjyp9vqCgAIaGhqw9HJfLrRehs3cBmqZx9OhRtG/fvl5EN8uCVquFTqcDl8tlPayZ58J/MZ5g8M79dRhaNY/HYxOd4sE30xFiOq3F/18mk0Emk0GpVOolp2q1GlKplFXpYxJakiSh1WrZhJe5EB49eoTMzEzY29ujW7duMDAwYJNmPp+PtLQ0vHz5EuPGjYOhoSEsLCzYpJuiKISEhMDc3ByTJ0+GpaVlqXZO71F5MHM0BEFAJpOxVMC3KXgURSE8PBydOnXC5cuXa40WzXRKNm/ejI4dO6Jnz57lJtiMknTr1q0xcODAegl4KIpCVFQU9u/fD29vbyxfvhwmJiZVutZ0Oh0ePHiAU6dOoVu3bggODoZEIsH27dvh4ODAikTVN5jq6eXLl3H//n307t0bkyZNYlkS3bt3x9q1a1kf4Xbt2uH69esYNWpUqXNphYWFOHXqFCIjIytVLJBKpSgqKoK9vT0OHz6MyZMn1/s93KRJEzx79oydj2/bti0eP36MDz/8EKdPn4ZSqfzPVnI5HA7GjRuHn376CdevX2efH8+fP4e5uTmEQiGGDRuGdevWITU1FU5OTjVSkndxcUG7du1w4sQJBAcHs2sBh8PBqFGjsHnzZrRt27ZOuxnMLJehoWGlRboKCgqwY8cOTJkyBba2tgD+N+oREhLCihDOmzevXJVlBrm5udiyZQvGjBlTa4WYtLQ0mJqaQiKRVEoNnSAIODo6Yv78+WxnuGPHjmUmw87Ozpg/fz42btyI+Ph48Hg8ODo6st/N4XDYv9cmdDod6xt89+7dcudrGwJIksSNGzdw6dKlCueBgTfjS1u3bkVgYCCb3JYFphus1WrZbjBFUbhw4QKGDh0KDoeDpKQk2NraIjk5maWpGxgYsLO4FcHNzQ15eXkYPHgwDh06hKFDh9b5+TYxMQFJklAoFPDx8UFcXBy8vb1Lfa+NjQ3S09NZCjDDXmOo0o0VsbGxGDx4MICq0ZqZdYhpZikUCohEogZfLKouoqKiEBcXhxUrVrzTdUAikbDnmcfjQa1WQyQSsXnYfxUN/sgJ4n9eu2//UJWZkyrPV475t927d+PSpUvw9vbG7NmzS1CBNBoNNm/eDD6fj/79+5egUQYGBuLSpUv45ZdfMGHCBHbe8D2qB4lEwnY8pFIpSJJkVRaLQ6vVIjU1lfXyq2pFsiyo1Wr89ttvCAwMRN++fcsVxiooKMAvv/yCzp07l/ve2gLj23n06FHEx8cjODiYtZmoyjYyMzPx999/g8vl4osvvmA9VpnOk6OjI+Lj49GhQ4d6W7hpmmYVnC9cuIDmzZvjm2++KSG8Ym5uDj8/Pzx+/Bi9evVCjx49sH79egwcOJB9GDM06Lt37+Ls2bPo1KkTVq1axS765eH169dwd3eHTqeDVCqtk0C5Ijg7O+Pq1asgCAJKpRK+vr44ceIEG0AlJSXVy2xqQwRBEBAKhZg+fTq++uorODg4IDc3FzqdDoaGhiwDaOjQofj6669hZWVV407DoEGDsGbNGiQkJLCdUEYMslmzZrh8+TKGDx9ep7+HsbExjI2NkZCQUKGFkkajwZ49e9CtWzdWmEipVOLy5cu4efMmevfuDV9fXzx48ABDhgwpd92iaRpZWVnYtGkThg8fXmt+2jRNIy0tDebm5tBoNJVeOwmCgL29PZvgUhRVpg0Jkzh/+eWX+Oijj1jdBpqmcefOHXTs2LFOAsDc3FzweDyYm5uzyUJDvFcZcUfG637JkiXlekEz18LmzZvRq1cv1l+6ou84fvw4hg4dyjLn0tLSoFKp2GfXixcv0Lx5c7x8+RKurq4gSRJKpbLSs/ACgQDOzs6QyWQgSRI5OTl1ZqNY/DsZtwpvb2/cu3evzPvS0dER9+7dY/VhCIJg45bq2qG9azAjDTKZDM7OzlVmouXm5rLaQAqFAoaGhv/KZEyhUGDv3r2YOnVqvbuHvI3c3FxYWVmBJEnweDzodLp/rehuVfCvz9aYgKW0P0zH1tzcHGq1GsD/qFrF//D5fMyYMQP37t3Ds2fP9JJr5t8HDx6MefPm4ezZs9i+fTsKCgrqxdz93wZmRonxDszIyChz9jcrKwvGxsbIz8+Hvb19rcxdaDQa/PHHH7C1tcWwYcPKrFAyFc0ff/wRH3zwQb0kwSRJ4vHjx1izZg0sLCzwzTffVCkJZgTaTp48iZ9//hkffPABFi5cyCbBwJvZRxMTE1haWiIxMbEuD0dvv7RaLZ4+fYpVq1YhMjISCxYswKRJk0pVgyYIAgMGDMDNmzeh0WhgbW0NDw8PPH78GMCbbnlMTAzWrl2L8PBwLFq0CCNHjoShoWGF54qmaTx8+BDt27fH69ev4e3t/U5UFRm6oLGxMTIyMmBhYQFTU1OkpaWhY8eOrA/hfxWMmNW0adMQGRmJp0+fwtTUFIaGhuw6IJfLYWtry67pNfkuoVCI8ePH4+DBg3r2RRwOB4MHD8adO3cgkUhqfFzlgQns8/LyyvV8pCgKp0+fhkgkQt++faHRaHDv3j2sWrUKeXl5rD3Y+fPn8emnn5a7btI0jfT0dGzatAmjR4+u9cJYamoquFxuqVY75YEgCNjZ2eGLL77AmTNncOfOHVAUVeZ7jY2N0aRJE4SFheHevXtQKpWIiIhAUFBQbR2KHpKSkuDm5gadTofc3Nx3UkyrCExBlLGN+/LLLytMguPj47FhwwaMHDkSvXv3rtQzLzo6GlqtlmUR0DSN8+fPo1evXjAwMABFUYiOjkaTJk0QERHBMjgYMZ/KgCAIBAUF4fnz5wgMDMSzZ8+qdC6qA4Ig4Ovri+joaLi6uiIzM7PM+5Kx6iquD2NlZYW8vLxGGycyYnDMqEZV7l+KolBUVAShUAgOhwO5XP6vTIQpisKZM2fg7+9f5XNU2yhunaTRaGBgYACtVsuu/8yY6n8R//pEuDIwNTWFVCqFsbExcnNzS/w7QRAwNTXF7NmzcfDgQaSkpJRYvBgxjyVLlsDFxQXffvstnj59+p+9sKoLjUajpwKclZUFjUZTQtWT8X/09/fH8+fP0aZNmxp/t1arxeHDh0EQBCZOnFjmokzTNHJycvDjjz+if//+FVKnawqappGdnY0tW7bg2rVrmDt3LkaMGFElQTWSJBEZGYl169ZBIpHgm2++YbshxbfB4XDg4eEBsViMoqKiOjVZZ7q2UVFR+OGHH3Dt2jV8/PHHmDVrVoWBsaOjI8zMzPD69WsAwMCBA3HlyhWkp6djx44d2LdvH8aMGYM5c+boJfoVQalUIi0tDd7e3nj69Ok7sypiRi+srKwQHx8PAGjbti2ePHmCwMBAxMTEsKMd/1UwQjqGhob4/fffYW1tzYrsAUBycjJatmyJlJQUPHr0qEYBJ0EQCAwMhLm5Oe7evau3LXNzc/To0QPHjx+v06DWxcUFeXl5rIZFaWAEoCIjIzF27Fg8fvwYq1evxrNnzzBz5kxMnToVAoEAO3fuxIQJE8oV1WMSn61bt2L8+PG11glmQFEUmzxUR7WZKYYsWrQIFy9exM2bN8tMhsPCwtCsWTMsW7YM58+fx759+2BtbV0nIng0TSMiIgLNmjVDQUEBqxrckEBRFJ4+fYqff/4ZQ4YMwbhx4/Q0U0p7/7Nnz/D777/j008/Rdu2bSt1LZAkiRMnTmDYsGHsfZmfn4/4+Hh2GxKJBEqlElZWVsjNzQVJkvDw8KiSKByTlMbHx6N169YIDQ0t81qoTTCJsJmZGSiKglQqLfV9TELPdLqBN+uGWCyGSqWq8/2sCyQkJMDNzQ3x8fGV1ixgwIg28fl8vUT430SNpmkaiYmJCAsLw8iRIxtExzUtLQ0uLi4oLCxkbQWZ+5IZO/0v4n0ijDcUa5lMBgcHByQkJJT5PicnJwQHB2Pbtm0oLCws9T0CgQCDBw/GnDlzcP78eezcufN9d7gKYOa8mQBFLBaDoih2xq04wsPD4e/vj5iYGDRr1qxGCw1Jkjhz5gxycnIwbdq0cpPgjIwMbNiwAcOHD0fXrl3rNAlWq9W4cuUKfvrpJ7Rs2RKLFi0q1Qe0LDAd9l27duHo0aMIDg7GlClTyvTdJYg3yrw5OTkQCoWlFoZqAxRFITk5GZs3b8aRI0cwbNgwfPHFF/D09KzU+SQIAv369cPFixdBkiRsbGyQlpaGpUuXwtPTE8uXL0dgYGCVH6yMl6VAIGAT4ncFBwcHGBoaslTYli1bIjIyEiKRCNbW1oiPj//PryuFhYUYPHgwSJJEWFgYbG1t2aSDmQGdMmUKTp8+jdzc3BqdLy6Xi7Fjx+L8+fMoLCxkt0UQBHr16oWYmBikpqbWynG9DSbpy8/PB0EQpRZBaJpGQkIC9u/fjyZNmuDnn3/GkydP8Nlnn2HWrFlwc3MDTdPYv38/mjVrVqYFEfDm/gwNDcWOHTswderUOhGMY0QyCwoKaiRuZGVlhS+++AI3btzA9evXSwRzJEni1q1b6NmzJ2xsbLBgwQKcO3cOlpaWdXL/6HQ6JCcnw8vLC/Hx8XB3d28wnS6apqHRaHDs2DGcOnUKCxYsQLt27cpdc0mSxLVr1xASEoIvvviiSiykqKgoaDQaNGvWjP3+q1evokOHDuwYS0JCAlxdXZGamgpHR0cUFRXBxcUFOTk5rEVaZWBubg4TExM2scrLy6v0Z6sLKysrSKVSaDQaNpEvDcbGxtBqteBwOGzia25uDqlU2mgT4cjISPj4+KCoqAhWVlZV+izTHWdG3qRSKYRC4b8qEVar1di/fz/Gjx/fYNSws7OzYWtrC7FYDEtLS72O8H8Z7xNhvBEukMlksLOzQ3JycpkPR4J4Y97evXt37Nixg6VTl/Y+FxcXfP3113B2dsbatWvx9OlTdj7kPcoG81CwsLAASZLIz89nVRmLQ6lUQiKRsBXFt/+9KqBpGtevX0dERARmzJgBgUBQ6oOemWnbuHEjxo0bx3rs1gVomkZycjJ++OEHREVFYfHixejevXulaboM3fj69ev49ttv4ebmhqVLl6JJkyYV7rOnpydSU1NhZ2eH9PT02jgcvf3KysrCjh07sG3bNnTu3BlLly5FYGBglTyPmQ5AUVERzp49i7Vr18Ld3R3e3t7o1atXtezHGF/LoKAgpKamwtLS8p369fr4+EChUCA7Oxs6nQ42NjbgcDjIy8tD+/bt//P0aODNeqHRaNCkSRMkJSWBy+XC0NCQFUkrLCxE27ZtMXToUPz55581ZujY2dmhW7duOHr0qN7rIpEIQ4YMwbFjx+qMBWRnZ4fCwkKYmJjoBdyMoGR6ejoWL16MnJwcFBUVYebMmZgzZw7c3NzYudjbt29DLBZj+PDhpa4DDEvj4sWLOHHiBBYuXFhlDYLKorCwEBwOB0VFRdVW9Qb+5zG9YMEC3L59G5cvX9ZLhjMyMqBWq+Hh4QGCIGBgYAA3NzdERUXh6tWrtd4FYRwurKysEBUVhaZNmzaIbhCjabFx40bk5uZi8eLF5RYgmGfI0aNH8eDBAyxevLhKFHatVosTJ05g1KhRbIIjlUrx5MkT9OrVi6VJP3v2DG3atEFSUhJrE8bM+1Zl/eVwOGjRogVevHgBf39/vHz5ss7jLSMjI5ibmyMzMxM+Pj6IiYkp9TtFIhFLRWU6wgwbg/l7YwIjBsfn80sVMq3M54uKimBtbc0mwgKBoMEUjGoKpuBjb29f4yZNbaKoqAimpqYs61Kr1b6T0a+GhveJMN50cZVKJWxtbZGenl4uHZTD4aB3796wtLTEkSNHyp1LYrrD8+bNw5kzZ7Bjxw4UFRW9T4bLAaNiJxQKoVarIZFIIBQKS1DY4uPjYW9vj/j4ePj7+1e7ksiYnF+9ehVz5swp4Slb/H3p6enYuHEjJk6cWGeUWWaO99ixY9iyZQsGDhyIWbNmVcmvk/HdXb9+PV68eIHFixejf//+ZSb4b8PExAQqlQoeHh6Ijo6u6SGx+5Sfn4+///4bGzZsgJeXF1avXo327duXS8kra1sURSEtLQ3Z2dnYt28fZs2ahWXLlkEul7MWFVWFRqNBdHQ0mjdvjqdPn6Jly5bvTPSOIAi4ubkhNzeX9ckmCAItW7ZEWFgYS48uPq/6X4RKpUJ+fj68vLzg5uaG69evQyAQoKioiHUJsLGxQadOnWBgYIAbN27UmCLdp08fxMXF6c3QEwSB9u3bIy8vj+3g1zYsLCygUqlgamqK7OxsNmmNjo7Gpk2bEBwcjD59+mDbtm347LPP4OTkxLoWMIW1c+fOYfr06aUGP0yXZufOnYiIiMCSJUuqNFZQVWRkZLAFzJoqoBMEAQsLCyxcuBD379/H+fPn2cLznTt30LlzZ3A4HNA0jRcvXqBVq1ZYunQpbt++jUuXLtVq8SI9PZ2dCU5KSoK7u3utbbu6YJSbv/32W7Rs2RKfffZZmc865v0qlQo7duxAbm4uvvzyS5ibm1fpGfT69WvQNM0qktM0jXv37iEwMJAdfVKr1UhMTETTpk3x/PlzBAUFgSRJiEQiViOhsiAIAi1atEB4eDjat2+Px48f1znVk2FQMZ7RZTEKORwOTExMwOVyWeVo5nw2xo5wfn4++18PD48qPycZtxfG8lCpVP6rOsJZWVm4ceMGxo4d22COibGnNTU1RUFBAStS+L4j/D4RBvC/hzBFUaxfcHng8XiYNGkSUlJScPXq1XKDHmZ2eOnSpXB0dMS6desQFhb2fna4DKhUKvB4PAgEAqjVaiiVSvD5/BKBEjPzFR4ejtatW1crWKNpGklJSdi7dy9mz55dplAIkwT/8ssvmDx5cp35yjKWSOvWrYNUKsWqVasQFBQELpdbqe9jbIcOHTqE3377DQMGDMDcuXNha2tbpf0VCoUwNTWFUCgslyFRGTCduZCQEHz77bewtLTEqlWr0KdPn2p3bcViMXbv3o3du3fjo48+gru7O8zMzGBgYICePXuW6AhVFrm5ueByubC0tERkZOQ7r+Q6OTlBKpXCzMwMqamprCBMWFgYTE1NYWFhwc4P/1ehUqmQnp4OIyMjeHl5oWvXrnj48CGys7PZIFokEoHH42HKlCm4ePFitQslDEQiEcaOHYtDhw7pPSsMDAwwcuTIOusKMzZRpqamiImJwdmzZ/HNN9/g6NGjiIqKQnBwMD755BNYW1uzQo/A/9aFXbt2ITg4GJaWliWua4btsn79etja2mL+/PlVtmOrCpg11czMrNY6QQRBwNzcHF9++SWePn2KM2fOQCqV4sWLF6zIF0mSuHfvHrp16wYzMzMsWrQIjx49woULF2rlN2P8cQMCAlhbx5qwlWpjf3Q6Ha5fv45du3bhk08+Qd++fSu0O5JIJNiwYQMsLS0xffr0SgkNFodOp8OpU6cwatQoNklSKpW4deuWnvOGWCxmu4oRERGwtraGsbExuFwuZDJZlSml9vb20Gq1MDExgUQiqRd7Ij8/P7x69Qqurq6spklpMDU1hUgkQmZmJgCwXdTGmAhnZGTAwcEB0dHR1XIvKCoqglKpZAsiKpWKXacbO7RaLf7880+MGjXqnd77b6O4XkHxjvD7RPh9IgzgTeAvFApRWFjIqhBXBJFIhJkzZ+LatWt4/vx5hcmCQCDA0KFDMWvWLJw+fRq7d+9+PztcCpiHAtOl12g0JfwlGVVgDw8P5ObmwtnZucrfQ9M08vLy8Pvvv+Pjjz8ucxvF6dB1lQQzyeLff/+NAwcOYNKkSfjoo48qbR0BvAk8nj59irVr14IgCKxYsQJt2rSpVjWSy+XC1dUVCoUCBQUF1RJlYmyezpw5g3Xr1rH7NGTIEBgbG1crAZbJZDh16hS+//57ODs7Y8WKFejatSvatWuHmzdvAgA6dOiAV69eVTkAYpgBzZs3Zy0tqjKfVhfg8/ng8XiwtbVFUlISaJqGg4MDlEolioqK0LFjR9ay478KlUoFsVgMtVoNNzc3GBsbIzo6GhcuXGB9SBnLCgsLC4wYMQIHDhyocSe9ZcuW4HK5ei4CBEGgefPm0Gq1bDestsAwRRQKBW7duoVDhw5BoVBg5syZaNWqFXx8fDBhwoRSOzM6nQ5//fUX2rdvj8DAwBL3nlarxbVr17B582YMHz4cI0eOrJfgKDExEQYGBnB0dKzVrompqSkWLlyIiIgIbNq0CU5OTuwzJC8vDwqFgtVZMDU1xYIFCxAWFoazZ8/WOBkmSRJxcXHw9fVFamoqrK2t36lQlkKhwJ49e/DkyRMsXry4Qpo7TdNITU3FDz/8gI4dO7IiWlUBUwwwMDBglXJpmkZYWBhcXFz0PK1fvnyJgIAA5Ofng8/nQ6VSwcXFhRWEq+poCp/PR5MmTRATEwNvb29WTLEu4eTkhOzsbJbZVFZia2try457AW8aMCRJlimw1ZDx6tUr+Pn5IT09vVrxV1FRESiKgqmpKasV8G/oCDMMFIFAgPbt2zcYSjTwJhFmRN0KCgpgamoKiqLeJ8J4nwgDeJN0CYVC5Ofnw8XFBUlJSZX6nIWFBWbPno19+/ZVqnNGEATc3d2xePFi2Nvbv1eWLgUqlYqtUuXm5oLD4ZRQjmSUU+VyOSsoVFXI5XL89ttvGDJkCGvr8DaYJHjz5s2YNGlSnQnGPHnyBGvXroWZmRmWLl2Kpk2bVppqxMzc/vrrr7h06RI+//xzjBs3rsbdHB8fH3YGSCwWV+mzcrkcly5dwpo1a1BQUIDFixdjzJgxVaLWMWDEXe7evYu1a9eiqKgIy5cvx4ABA9guRY8ePXDv3j2oVCqYmJigVatWuHXrVpUSEZIkER4ejjZt2iAyMhK+vr7vvDrN5XJhb28PIyMjxMTEAHjTdWzatClevHiBFi1aIDo6ulF2FGoLWq0WRUVFSE9PR2BgILRaLWbNmoUzZ86Ax+PBzs6OvZcIgmA7gw8fPqxRosrhcDBhwgScOHECCoWCfZ3H42HkyJE4fvx4rSiuazQaxMbG4q+//sK6deuQnp4Of39/tGvXDqNHj0ZGRgYePXpUpg0SY1VD0zT69++vt64w6vebN29GeHg4lixZgtatW9fbOEBOTg40Gk2NhLLKgrGxMWbPns3a6BSnSbdr107PO9PU1BTz589HREQETp48WaPnsUKhgFwuh7W1NWJjY9+ZZQpDhWeskebPn1/heA1DG9+0aRM+/PBD9OrVq1qJiU6nw8mTJzF8+HD281qtFhcvXsTAgQPZ64uiKISHh6NVq1ZITk5mYzBXV1colUpwudxq+X+3a9cOoaGh9UaPtrKyAk3TKCoqYsfrSoODgwM77kXTNEQiEctwakygKAoJCQlsYl+drmdhYSGr/aLT6aDRaMql6jcW5Obm4ty5cwgODm5wSX1eXh5sbGxAURSr0k1R1PsZYbxPhAG8SYQFAgFycnLg7u7Odl8qAkEQcHZ2xpQpU/D777+zC1xFEAqFGDp0KGbPno0zZ85g165d72eH/x+FhYXg8/ng8/nIysqCVqstYa0RHx8PDw8PdtarKoEbIwDyxx9/IDAwEF26dCkzCc7MzMSmTZswceLEWk+CGU+3rVu34tKlS5g3bx5GjBhRaQoaYz9w7tw5/Pjjj2jRogW++uoruLm51Uog6+rqirS0NNjb21eKSsp0rC5duoRVq1YhLS0NixYtwuTJk6s031x8exRF4dWrV1i7di2ePHmCuXPnYtKkSSUo7DY2NnB2dkZoaCgAoFevXrhz506VOtkymQxFRUVwdHREaGjoO7NNKg6CIODh4QGZTMYqHhMEwQZ6pqamsLGxQVxc3Dvdz3cJrVYLiqKgVCrh7OwMiqLg5uaGZs2a4fz58yWSLC6Xi4kTJ+L06dOVXq9LAyOI6Ovri2vXrul1hX19fSEUCvHixYsqb5+57tPT0/HPP/9g1apVOHLkCDw8PLBs2TJW8V2r1SI+Ph4hISGYOXMmTE1NS6U7h4eH4+HDh5g6daqeX6RWq8XVq1fxww8/oHXr1pg3b1617tPqQqfTQS6Xo7CwEC4uLnXyHUVFRWjatCmkUilCQkKgVCrx9OnTEl7IBPHGZ3j+/PmIjo7GP//8U+0iBiMyyOfzERUVBV9f39o6nEqBuX7u3LmDjRs3YvTo0Rg7dizLiigLFEXh6tWrOHjwIObNm4fmzZtXe9woPDwchoaG8Pb2ZrvBr169grGxsd5vrVQqIRaL4ezsjOfPn6Nt27ZITEyEp6cnFApFtTvpXl5eyMnJYZPSuhajIggC9vb2yM7Ohru7OxITE0u97xmFZIYJKBQKYWRkVOf+47UNmUzGCsLZ29tXizFQUFAAAwMDWFpaQqfTsXT2xgydToeDBw9i4MCBlbb9qk8kJyfDzc0NJEmyhUGapt93hPE+EQYAlpKRlZUFDw+PMhey0sAoSffr1w+//fYbVCpVpZNoZnbYzs4Oq1evRlhY2H/Wx4tBQUEBjIyM2MIETdN6M66MymSrVq3w+vVr+Pn5VWn7NE3jxIkT4PF4GDZsWJnKqWKxGBs3bsSECRNqNQkurua8fv16BAQEYPHixXB2dq50AsxQw9euXYvU1FSsWLGCVZSurf00NzeHUqmEu7s7oqKiyt0flUqFa9euYeXKlUhOTsYXX3yBjz/+uMqzycz2GCGsjRs3IiQkBBMmTMD8+fPh6OhY6u9FEAQGDx6MS5cuQafTwdbWFi4uLggNDa3UvcgIu3h5eUGj0SAvLw8eHh5V2u+6ACPEIhaLodPpIJPJALwpUuTm5kKhUKBLly4lfG3/S1AqlZDL5ax1CgMDAwNYW1uXWI8JgoCdnR169+6NgwcP1lg4a9iwYbh9+7bemAuXy8WIESNw4sSJSiVUzDVfUFCAa9euYc2aNdi2bRsMDAwwb948LFu2DB988AFMTU3h6OiIwsJCFBQU4Ndff8Wnn35aqqAVwxTZu3cvZs6cyVJMKYpCYmIivvvuO7x69QqLFy9Gjx496p39kJ+fDx6PB5lMxgpL1TauXr2Kvn37YsGCBcjMzMS6detgY2NTqtULQRAwNDTE/PnzkZycjJCQkConwzT9xj84ICAAOp0OeXl5dXZsZX2/UqnEn3/+iVu3bmHp0qWVKhSr1Wrs27cPjx8/xuLFi6tkz/c2dDodTpw4gREjRrAdMZqmcebMGQwaNEjvtbi4ODg5OUEgEODRo0fw9/dHUVERzM3NoVAoqi2gJhQKYWdnh5ycHDg7O5ep5FybCAgIwKtXr1jLrNJgZmbGKiRrtVoIhUJYWVnVyxxzbUIikcDExAQJCQnVVpTPzs5mCwGMLs+7dGioKWiaxtOnT6FQKNCtW7d3XkQvDbm5ubCxsQFJkuz9wIgpAm/WwIbWxa4vvE+E8SZoYhIvxlO4KgkpQRDo3r07PD09q2TRwShLDx8+HHPmzMGpU6ewa9cuPY/K/xqKiopgYWEBDofDUqOLz2qqVCqkpKTAzMwMPB6vSv51NE3j4cOHiIiIwJQpU8qkhBQWFuKXX37B0KFDa7UzyFCtf/jhB7x8+RJff/01evfuXekElpkl/vPPP7Fv3z5MmDAB06dPL1PkqyYwNDSEmZkZ+Hw+UlJSSlyPTNB18+ZNrFy5EnFxcZg3b16ZgXllwChL//XXX/j111/Rvn17LFu2DP7+/noLdmlwd3cHn89HbGwsOBwOBgwYwHoMV+Z7Q0ND2Y6Evb19hR2U+gKT+JibmyMjIwPAm9/G09MTERERaN68ORISEtgk+b8GjUYDiUSCoKAgyGQyCIVCKJVKEAQBLy8vnD9/HqmpqSWS4e7du0MikSAsLKxGXWELCwt069YNp06d0nvdy8sLZmZmLDW3NNA0DblcjtDQUGzcuBHr169HZmYmgoODsXLlSgwbNgx2dnZ6wlcODg7IyMhAeno6BgwYUCb1VqFQYMeOHRg3bhw7w5eTk4OdO3di165dGDJkCGbPns1auNQ3cnJyYGFhAa1WWycztHK5HK9fv0abNm0gEokwa9YsxMXFsd2n0sAkw7Nnz0ZWVlYJMbSKwIgdBgQEICsrCyKRqIS+RV2BER/7/vvvIRKJsGjRogoLkczzZMuWLdBoNFi4cGGNnyWhoaGwtLSEp6cnu524uDiQJFkiaXr69Clat27N2pxZWFiw9mfMmlddFKdHP3z4sNrbqQyYkbekpCS2M1zac8fMzAwajYa9BgmCgI2NTaU0aRoSoqOj0aRJE8TFxcHb27ta2xCLxaw4VmPvCDP30T///IPg4OAGSTWmKApisRhWVlbQarWsnV7xfSUI4p25ZLxr/DePuhSYmZmxvrQ8Ho+VuK8suFwuxowZA41GgxMnTlQ5kXZzc2PtKr799tv/rLK0VCqFlZUVdDodG0wUp5nk5eVBIBAgOTkZvr6+VfLVTUxMxLFjxzBz5swy1SiLioqwZcsWfPDBB+jcuXOtBImMLcnJkyexdetW9O3bF7Nnz65Sx5SZk123bh2sra2xdOlSNkGsCzDUT0bcg6GXMcH7jRs3sGbNGkRFRWHu3LmsXUt1E+DCwkIcO3YM33//PWxtbfHNN9+gc+fOlabtMMnv5cuXQZIkvLy8wOVyERsbW+FntVotUlJS4OnpiSdPniAoKKjKx1BXYObI7OzsWO0CgiDQsWNH3L9/H4aGhnB2dq7Ucf4bwfgIt27dGllZWbCxsYFMJoNAIABN05g6dSr+/PPPEnPUAoEAwcHBOHLkSI3EagiCQM+ePfHq1Su92UAul4uRI0fi9OnTen7zzMx7fHw8/vzzT6xevRqPHz9G37598c0332DSpEnw9PQsc13j8/kICwuDQCAos+Ck1Wqxf/9++Pv7IygoCBKJBCEhIfjpp5/g4eGBb775Bq1atXqn1f/09HQYGxuz+hy1jUePHsHPz49NRGUyGdzc3CAUCrF371693+RtGBoaYsaMGZBIJNi/f3+lk2FGzMzS0hLx8fHw8vKqlWOpCDqdjqVCDxs2DOPHj6/wnBYvygYEBGDq1Kk1LkgolUqcOnUKo0ePZq8tiqJw4sQJDB48WO+aJkkSsbGxaNq0KVJTU6HT6aBSqWBvbw8DAwNkZWXBzs6uWvvBsPRiY2Ph5uaGxMTEagk+VgVOTk7Iz88Hh8OBTqcr9foyNjYGRVHQaDTsNWVpaYm8vLxG0/igaRoxMTFwc3ODRCKBg4NDtbajUChgYGAAHo8HrVYLjUbTaDvCNE3jyJEj6Nq1a4380OsSSqUSSqUSVlZWbEefpun/bAf4bbxPhP8fVlZWUCqVoGka9vb2SEtLq/I2+Hw+PvnkE7x8+bLKdEWCINjZ4ZkzZ+LUqVPYvXt3o6PN1BRMR1in00EqlYLP5+s9oBnq2bNnz9CmTZtKb7egoAA7duzAtGnTynzAKhQKbN++Hc2aNUOfPn1qJclkHhzfffcd8vPzsWzZMrRt27bSVETG4umnn37Cw4cP8cUXX2Do0KFVtrOoDpo2bYqkpCQYGBhAJpNBLpfjypUrWLNmDaKjozFr1ixMnz69TMpyRWC6yleuXMG6deug0WiwfPlyDBo0qMrCGYxib3Z2NnJycsDlcjFgwADWT7Q8JCQkwMbGBnw+H3FxcWWKp70L8Pl8WFtb6wlmAYCnpyeysrKgUCjQuXNn3Lt37z85VkGSJFq3bg17e3tkZmbC3t4eGRkZrE1Ep06d4OLigrNnz5ZYj11dXdG+ffsqFy7fhpGREQYPHoyjR4/qbcfDwwOWlpZ4+vQpW+y5du0a1q1bh/3798PT0xPLly/H559/jmbNmlV4T+t0Ohw7dgwcDgf9+vVj1c2Lg6ZpXLp0CQqFAh988AGOHz+Ob7/9FhwOB8uXL0ffvn0hEone+fWdmJgIgUAAW1vbWqdl63Q63Lx5Ez179mSP8/79+2jbti0+//xz0DSNPXv2VJgMf/rpp5DJZPjrr78qlQwnJCTA0dERIpEIkZGRpSp01yYYJf09e/bgzp07+Prrr9GmTZsK12JGIX/Tpk0YPXo0+vfvX+PfgKbfeAS7urrqaXokJiZCKpWiRYsWeu/PzMyEUCiEhYUFHj16hObNmyM1NZWlZUskklJtvioLxv5Po9HAysqqzry9GTA6M8z3lSaYxeFwIBKJQJIkm5ibmZkhLy+v0TQ9NBoNW8QyNDSsdvKqUChY2zSmCFJVq6yGgoiICKSnp6Nv377vfF0tC0xx2MDAABKJBGZmZiBJUq841ViKMXWB94nw/8Pc3BwymQxarbZcwYOKYGRkhDlz5uD06dN49epVlbfBdIeXLl0KW1tbvdnh/8KFyvibMVXV4gkRRVF4+fIlvLy8IBaL4e7uXuH2GFGpXbt2oWfPnvD39y91nk6r1WLPnj1wdHTE0KFDa7ygMUHK3r17sWfPHnz44YeYOnUqzMzMKk2DlsvlOHjwIH777Tf07dsXCxcurDbtuDpwcnJCZmYmbG1tcfDgQaxatQqJiYlYsGABZsyYAWdn5wopy6WBpt94Wz58+BCrVq1CfHw8Fi1ahAkTJlT6/JQGPp+Prl27st7erVq1QnZ2drliXwwtunXr1sjNzWWDs4YCDocDV1dXqFQqZGdns2uAsbExXF1d2Tn5lJQUyOXyd7y39QvmOurduzc4HA4rBpKUlARjY2NYW1uDx+Nh7NixCA0NLREMEwSBgQMHIjo6utrrPbOdjh07QiwW680jEgSBUaNG4ciRI9i5cyfWrl2LlJQUfPLJJ1i+fDk791uZIhJFUTh9+jQKCgrQsWNHmJiYIDU1tcT5CAsLw+nTp2FgYIAff/wRFEXhm2++wejRo2t0b9UmGLVqnU4HBweHWt+nuLg4CAQCVphJo9Hg0aNH6NatGwwMDDBlyhTw+Xxs37693GRYJBLhs88+Y8UVNRpNmddIcSsgJlmoS52B4qrQjHdyZWjuOp0O586dw5EjRzBv3rwqi02WBcYpYOTIkexrJEni1KlTGDx4sF6izQhqBQQEgKZpPHr0CC1atNCj2jJxQHXB4XDQsmVLhIWFoW3btnVOj+ZwOHBxcUFKSgpcXV1LHSciCAIikQhCoZBVijYxMYFYLK6xnVt9gXnG5OXllRAxrSxIkkRRUREsLS3ZjrBarW6UHWG5XI59+/bho48+qpbCeX2hsLCQFVSUSCRss6n4zH5juQbrAu8T4f+HqakpcnNzodVq4e3tXW0lVoIgYG1tjdmzZ2PPnj0l5tMqu43is8MnT57E7t27IZVK/9XJMDMjamZmhsLCQmi1WtjY2LAPaoVCgdzcXFAUBVtb20pRuWiaxj///AMLCwv07t271ECBoigcPnwYXC4X48aNq1ZyV/z7GCueNWvWQCAQYNWqVfDz86tUwMEE90+ePMGqVavA4XCwcuVKBAUFgcvl1lsgy9g7REZG4ubNm0hMTMSXX36Jzz77rEYzwDqdDhEREVi7di3u3r2LmTNnYsaMGWwQV5PjIwgCnTp1wvPnzyGVSmFgYIDu3bvjypUrZd43jDJ1YGAgnj17hhYtWjSIZKE4fHx8IJFIoNFoWIYIc6z37t2DSCSCp6cnIiMj/9Xrw9tQKpWIjo6GsbExaJpGRkYGHB0dkZmZCZ1OxyZCRkZGmDx5cqkUaaFQiPHjx+PgwYM1ok/yeDyMHj2aVRzW6XR4/fo1jhw5gsjISCiVSqxcuRJTp06Fq6trle5lmqZx8+ZNhIeH4/PPP4eTkxMoikJubi777zqdDuHh4Vi8eDEoioK7uztWrlyJsWPHNpgEmIFarYZUKoVUKq31ZJGmaVy5coUtjgBvXAaMjY3ZeWs+n4/g4GCYm5vjt99+K1dVWCAQ4JNPPgGHw8Hu3bvLTYajo6PRtGlTFBQUgMPh1CiRKw86nQ5Xr17F1q1bMWHCBIwePZr1sC0LTGF1586diIqKwtKlS+Hi4lJroz83btxAYGAge46BNwraeXl5aN26dYnvefbsGVq3bg2pVIqkpCQ0adKEtXdh2BM1OX8EQaB169YIDw+Hn58fXr9+XSt2ZuV9n4+PD2JjY+Hj46PH3ikOZg6aSYStrKyg0WjqnLpdW0hKSoKLiwtiY2Ph7+9frW3I5XLIZDJYWlqCy+VCq9VCpVLV2zx9bYGh/bdu3VpvJr4hIjU1lX0eFhQUsIlwQ5xnfhd4nwj/P4yNjZGXl4eioiLY2NiUSjurLJiubnBwMH777Tfk5eVVezuM77C1tTXWrVuH8PDwRkOjqSpomoZUKoW5uTmys7NZSxQGaWlpsLGxQUREBNq2bVup7T158gQxMTH48MMPS52HoCgKFy9eREZGBj766KMaKS8ztgC7du3CyZMn8dlnn2HcuHGVpiIywfzGjRtx9epVzJ49G+PHj4exsXG9JsD5+fnsvC5Jkhg/fjycnZ1rJKzDzIT99NNPOHXqFMaOHYuFCxfCzc2txglwcZiZmSEwMBD37t0DAHTp0gUvXrwoc8QgMzMTPB4PFhYWePHiRalB27uGg4MDxGIxzMzM2OQHeENdT09Ph1wuZ+nR/5VEmOnAvX79Gnw+HxqNBiqVCgKBAGKxGGq1mmWMEAQBf39/eHl54cyZMyW6wgEBAbCwsKjR+SMIAoGBgaAoCseOHcN3332H48ePo2/fvvj111+Rl5dXYbJS1nGGhYXh0qVLmDt3LpvQKZVKFBYWoqioCLdu3cKSJUswb948LFy4EFu2bMGgQYNKtVRqCCgqKmLHLWxtbWt122KxGGlpaWjZsiWAN+v7zZs30aNHD733GRgYYOLEibCzs8Nvv/0GuVxe5m/P5/MxZcoUCAQC7Nq1C2q1usR7i4qKoFKpYG1tjaSkJHZdq03QNA2JRILffvsNz58/x9KlS9G8efMKC7dMB/6nn36CpaUl5s6dW6vXRmFhIW7fvo3Bgwez2yRJEmfPnsXAgQNLBNsSiQQymQzOzs5ISEiAWq1mbXTMzc2h0Wggl8trzMyxtbWFUqkEn8+HoaEhUlJSarS9iuDl5YWkpCTY2NggOzu71PfY2dmxAn/Am0SYJMlG0Y2jaRrR0dHw9PREamoqPDw8qnUNSaVSqNVqtkDXGFWjaZpGbGwsIiMjMWzYsAa5zhZHeno6O7+cl5cHa2traDSa94nw/+N9Ivz/YBT98vLyYG5uzj50qgtmZnHgwIHYsmVLjQRZRCIRhg8fjs8//xzHjx/Hnj17/pXK0jqdDkqlEubm5sjLywNFUWyFmaZpvHjxAr6+vpWe48zIyMCRI0cwffr0UudPaJrGgwcP8ODBA8yYMaPadg3Mvj948ADffvstnJ2dsXjxYnh5eVV6gZTL5Th+/Dg2bdqETp06YdGiRTWysagqKIpi7Va+//57AMDSpUsxcuRIGBkZIS8vr1pVa8auZdOmTdi/fz/69++Pr7/+Gv7+/nUi1EAQBPr06YMbN26wSpTNmzcvM8lhKHoKhQIKhQL29va1vk81hampKdRqNezs7JCcnMy+bmhoCEdHR8TFxbHemTVZZxoTSJLE1atXERQUBAMDA6Snp8Pc3BwEQYCiKCgUCj21eQ6HgzFjxuDZs2cl2D5cLhdjx47FxYsXq73m63Q6vHr1Crm5udi5cyeGDRuGr7/+Gi1btoSPjw8sLS3x/PnzKq3ZNE0jPj4ehw8fxpw5c2BpaQmapmFjY4PY2Fg8evQIa9euxevXr6FUKvH111+jX79+9aIfUBMUFBTAxMQECoWiVrtAzJxqUFAQS1MsLCxEcnJyqUwPHo+HcePGwdXVFVu3bq0wGZ48eTKMjY1LpVQnJCSwVkCRkZHV7paVBWYs6Pvvv4ePjw/mzZsHS0vLCj/HWDpt2LABffr0wZgxY2rVN5SmaVy8eBHt2rXT25/MzExkZGQgKCioxHlnbIb4fD4ePnwIPz8/FBQUwNLSEnw+ny001FS8SyAQwMfHB5GRkQgKCsKTJ09qtL2KYG1tDalUCpFIBIVCUeIaIQiCTXyZdcbY2FhvZrghg6IoxMbGwtHRERqNptpeuTKZDDRNsyrRJEmyGjmNBSqVCgcOHMDEiRPrRPW+NkHTNLKzs2Fvbw+afmMNam1tDYVC0Wjnsmsb7xPh/4eZmRk7u8Hj8WBtbV1mVa+yIAgCXbt2RcuWLSucR6oIHA4H7u7uWLp0Kdsdfv78+b9KIKd4ZZDpfDHCVgyFlfFlrMg2SaFQYNu2bRg/fnypyoY0TSMyMhInTpzAvHnzqk3DYqrtW7Zswc2bN7Fw4UIMGjQIQqGwUsEoSZIICwvDmjVrIJPJsGLFCnTq1KlWPYHL23dm1mz79u34+eefYWNjg2+++QajRo2ChYUFmjRpguTkZHC5XCgUiiptOz09Hb///jt27tyJzp07Y8WKFWjZsmWdH5ujoyNsbW0RHh7OJsa3bt0qEWxQFIVnz54hKCgIkZGR8PHxaZDm8iKRCBYWFjA2NkZcXJxesN6pUyc8ePAAhoaGaNq0aaW9kxszmGtWq9XCw8MDBgYGiI2NhaenJ+RyOTgcDpRKZYlAjaFI79u3rwQd1sbGBj179kRISEiV1lQmWf3xxx9x6tQpzJgxAwMHDoRCoQCPx2MtKYYNG4YzZ85Ump7JsEN27NiBTz/9FE5OTsjJycGZM2dw5MgRPH/+HHZ2dpg9ezYMDQ3RqlWrBi3WUhwpKSkwMTGBgYFBrXaBVCoVHjx4gO7du7PF09DQUAQEBJQZZPN4PIwcORJNmjTBpk2bKkyGJ06cCCsrK/z66696SvrPnz9HixYtoNPpkJiYWKatVVXBaFwcOXIEhw8fxvTp0zFgwIBKUaF1Oh3Onz+P/fv34/PPP0enTp1qvfiYn5+P0NBQvWuPoiicOXMGffv2LTE3SdM0Hj9+jA4dOkCr1eLx48esUJa7uzsIgmA7VTU9fwRBoG3btnjy5AlatWqFly9f1mnnlRH21Ol0MDIy0mPvMLC0tASHw0F+fj5omoaxsTGrfN/QodVqIZPJoNPpYGVlVe3ZcmbEjymCKZVKCASCBvnsLQ1M8cfNzQ1+fn4Nfs3VaDTIz89nE2GVSgWRSAS5XP4+Ef5/vE+E/x8mJiasgh/wRpU1ISGhxtvlcDgYPnw4LC0tsX///hrNqRSfHZ45cyaOHz/+r5od1mq14HA4EAqFSEtLg0AgYBNhpmOXmZmJgICAchdhkiRx4MABBAQEoG3btqWKY6WmpmLXrl2YNWtWtSqbjLjAtWvXsH79erRs2RJfffVVpcVfmCrdli1bcPr0aUyfPh3BwcH1Qmdk5phjYmLw888/Y/v27fD398fatWsxYMAAmJiYsHRlV1dXZGdnw87OrlLUMua4du3ahU2bNiEgIACrVq1C+/bt6yW5B97ccwMHDsT58+dBkiTs7OxgZ2eH8PBwvftEIpFAKpXCxcUFoaGhteoZXZsgCIIdEcjIyGATNYaOm5SUBLlcjq5du+Lu3bvvclfrBTRN49SpUxg4cCD4fD44HA7Cw8PRvHlzpKSkwNTUlBWlKQ6CIODn5wdPT0+cPXtWL+ElCAI9evRARkYGoqKiKlxPmTGI3bt3Y9euXejXrx9raTZ69GicOnWKDW6ZERczM7NKdYWZ8YRNmzZh8ODByMzMxHfffYdNmzZBpVLhs88+Q6tWreDn54ezZ88iKysLEydObDRWGCkpKRAKhTUKpt8GI8Dk7OzMFkl1Oh1u376NHj16lHtf83g8DBs2DM2bN8eGDRvKfZ4aGBhgwoQJcHR0xJYtW6BQKEBRFOLi4uDr6wu5XA6tVlsjD9zix5SRkYHvvvsOCoUCy5cvr9QsIjMPvG3bNrx+/RrLli2rNo21ou85efIkevTowSY1zPqflJSEdu3alfhOqVSKzMxMVvcgKioKzZs3R0xMDJo0aQLgf4lRbeyvu7s7srKy2N8jJyenxtssC1wuF66urqwXfWZmZon3MDPC+fn5oCgKRkZG0Gg0jYLJk5mZCXNzc9a6srq/DzNDz1Df5XI5RCJRo0iEafqN7dj9+/f1bMIaMhiGhVAoBE2/se/j8/nvO8LF8D4RxptAxcjICCKRCDk5OaBpGl5eXoiPj6+VBJPL5WLSpEkoLCwsEYBVZ18JgoCHhweWLVsGKysrrFmz5l8xO6zT6dhkPz8/nw1mafqNBZGTkxOio6PRqlWrMhdhmqZx584d5ObmYuTIkaUmwQUFBfj999/x0UcfsVXoqoDpdv744494+fIllixZgh49erAdoIo+q1KpcPbsWfz0009o0aIFlixZUi9iC8x3P3nyBGvXrsWRI0fQrVs3rFq1Ct27dy+1i83MWdna2pZrQUFRFHJycrBnzx5s2LABbm5uWL16NXr06FFrQU1V0KRJE2i1WiQkJJRppRQTEwMPDw/29/T09KzXfawKmjRpgvz8fCgUCshkMvZ1kUgEOzs7JCYmws3NDWq1ulyV7H8DUlNTkZ+fz9JddTodcnNz4ezsjNTUVBgZGZU5X8jhcDBq1Cg8ffq0hJChQCDAxIkTcfjw4XI7NFqtFrdv38batWthZ2eHlStXok2bNqwAlqurK5ydnfHgwQN2+1wuF8OGDcPp06fLXaeZJHjJkiXIyMjAuXPnEBMTg9GjR2P16tUYO3YsPD09odVq2fnh6dOnV5qB8q5B0zSysrJA03StKkaTJIlLly6hf//+4HA4oGkacXFxMDY2rtS4A5fLxeDBg9GuXTts2LCh3NEjRoncw8MDW7ZsQVJSEivgmJCQABcXlxrN3jHd3Bs3buCXX37BoEGDMHXq1EpR3plAff369XBycsK8efPqrLjKFI2YDjyDM2fOoHfv3qVSRpOSkmBvbw+RSISXL1+Cw+HA29sbWVlZLNsrLy8PVlZWtbLPJiYmcHBwQHx8PFq1aoVnz57VWdOAIAi2gcIIZ70NS0tLqNVqKJVKUBQFY2Nj6HQ6FBQU1Mk+1RaYmVh3d3f2+Kr7+2RnZ4PD4bCjK3K5HEKhsFEkwjqdDn/99RfGjBnTaMS9FAoFhEIhuFwudDodKIqCQCCAUqlsNM+Nusb7RPj/wcyHZmdng6IoODo6Iicnp9aSS4FAgE8//RTPnz/HnTt3amUxFgqFGDlyJD7//HOcOHECf/31F4qKihptd1ir1UKn00EgELBVQsZ2ITw8HD4+PsjJySnTNonp9J47dw6ffvppqQurWq3G9u3b0b17d7Rs2bJKiwBNv/G9PXPmDDZv3oxevXphzpw5lRaRIkkSkZGRWLt2LbKysrB06VL06NGjzh8ANE2jqKgIV65cwerVq3Hv3j2MHz8eS5YsQbt27cqV/edyuTAxMYG1tXWphSGappGbm4t9+/Zhw4YNcHR0xMqVK9G3b98azVzXFDweD/3798eFCxdAURS8vb1BURTL8mBok+3atUNCQgJsbW0btFiHo6MjsrOzYWxsjMLCQvb14urRXC4Xbdq0qXOrkHcJiqJw/PhxDBw4kL1uk5KSYGlpCWNjY6Snp4MkyXKt1YyNjTFmzBjs3bu3BEPHx8cHDg4OuH37dqnXemZmJjZu3IgnT55g0aJFGDJkSImAn6FCnz9/Xm8cxsvLC0KhEJGRkSW2q1arER8fjz/++ANTp06Fra0tFi5ciG+++QYff/wxfH192XWC8Ue9fPky+vbtWyvdx/qCSqVCQUEB5HJ5rRWeGHo6l8uFm5sb+/rly5fRs2fPSnvkcjgc9O/fH126dMEvv/zC0ldLA0Op9vHxwerVq+Hh4QEOh8P63NdEcDE/Px9bt27Fs2fPsHjxYrRt27bSFltPnjzB5s2bMXz4cAwfPrzOxHBIkkRISAiGDBmi11XKzMxEXFwcOnXqVGoR+vHjx2jXrh1omsbDhw9ZHQytVssys3Jzc/Xm+2sCgiAQFBSEx48fo23btggLC6vThoGnpycSExPh6OiItLS0EtePQCAAh8OBWq1mO8Jvr+kNFcxsd05ODqtAXB1IJBJwuVw2PpDL5Y2CGk3TNK5fvw4zM7MGyx4rDRkZGbC3tweHw0FRURFbdGA6w+/xPhFmYWhoCJVKBYlEApIkYWVlBa1WW6uUFWNjY8yePRvnzp0rQdOsLpju8JIlS2Bubs4qSzfG2WGtVguNRgMOhwOJRAJ7e3vweDy2Gsnn82Fvb1/mvJdKpcKuXbswfvx4WFtbl1iodDod9u7dC0dHR/Tp06dKtDwm2Fq/fj2ysrKwbNkytG/fvlJBFk3TyMvLw44dOxASEoLg4GB8/PHHsLS0rNPFlKGpHTlyBGvWrEFGRgbmzJmDuXPnwtfXt1JBEkEQ8PLyglQqhVgsZq8rJgHev38/fvjhB1hbW2PFihXo379/vapcl4egoCCkpqYiJycHBgYG6NevH86dO8dSB1NTU+Hr68v6CNcWTbMuwIhbMN1fBgw9OiEhAUqlEh07dkRoaGijmDmrDmJiYlBYWIi2bduyM+5Pnz5F+/btodPpkJeXB51Op6c2/zYIgkDLli1hYWGB69evl1CRHjNmDK5cuaLXpSFJEnfu3MHPP/+Mjh07Yv78+eXaiDk7O8PDw0OPqs7lcjF06FB2VpiiKGRkZODkyZNYu3Yt/vzzT1y8eBEffvghVq1ahTZt2pR6L4nFYiQkJGDw4ME1EnR8F1AqleByuSgsLKxVxejz58+jb9++7HosFovZMZqqgMPhoHfv3ujevTt++eWXct0jGEq1mZkZoqOjUVBQgNjYWPj5+VXrGEiSxJMnT/Ddd98hMDAQc+fOrXSRVaVS4dChQzh37hwWLlyINm3a1Ol6Fh0dDYlEgo4dO7KvURSFkydPon///qUWQVUqFWJjY9GsWTNotVq8evUKfn5+kMvlMDMzY2mmYrG41jrCAODn54fY2FjY2NhAqVTW6T1jbm4OmUwGGxsb5Ofnl5hJZka/dDodtFothEIhzM3Ny3Q1aChgmBzMbH9NhK3kcjm4XC67jcaSCGdnZ+Py5cuNagwFeKMY7ejoCIIgWKFCphhT/Hf8LytIN9zIr55haGgInU7HVuo4HA7Mzc1rddFkVAPnzJmDv//+u4TwTU22y3SHZ8yYgX/++Qd//PFHo5sd1mq1IEkSCoUChYWFcHJyAkEQrOhESkpKmV1ciqJw5MgRNGnSpFTqNEVROH/+PAoKCjB+/PhKL2RMF/jQoUPYuXMnRo0ahY8//phVqK3os2q1GhcuXMB3330HT09PLFu2DE2aNKmzIIWZ/42OjsaWLVuwYcMGCIVCrFixAh999BEcHR2r5GHK0L2ysrJAEASkUiny8vKwb98+/PDDDzAzM8OqVaswcOBAdra4oUAgEKBz5864ceMGaJpGmzZtkJaWhuzsbKSlpcHKygpCoRCvX7+udZXX2oZIJIKRkRHMzMxKUNSNjIzg7OyMmJgY2Nvbw8DAoM6tQt4FtFot/vnnH4wePRo8Hg8URUGlUiEtLQ3Nmzdng8uCgoIKabdcLhcTJkzApUuX9ERtmDW6S5cuOH36NCiKglwux65du3Dnzh189dVX6NKlS4UFMIIgMHz4cFy6dAlyuZx93c/PD0qlEsePH8f69euxdetWAMCMGTPg4OCAoUOHYsyYMaVun2F2/Prrr/D29oa1tXW5XcuGiMLCQggEAshksmqrzr6NnJwc5OTkoFmzZqxI1u3bt9G2bdtqKbpyOBx0794dffv2xU8//YS8vLwyz7FGo4FQKETbtm3x/fffQyaTVVl4kaZpyGQy7NmzB+fPn8eCBQvQu3fvSiUGxa2R1Go1Fi9eXKuU89Kg0Whw9OhRjB07Vu86TUtLQ3JyMjp37lzq96elpcHc3BwmJiZITk5GRkYGmjVrhoSEBHh7e7PHk5+fXylF7MrCysoKIpEIWVlZ8PPzw4sXL+rsnjE0NIRAIIBOpwOHwynR6eVwODA0NASPx4NEImHXm4beEc7PzwdBEBCLxXB3d680y+JtMNd68WS6qKiowSfCOp0O+/fvx7Bhw2r12qxrMDoDzNhBQUEBG7uq1Wr2nNM03SibZ7WF94nw/8PQ0BAGBgaQSqUsdcbT0xPx8fG1+j2M8M2MGTOwfft2ZGRk1NqizHSHV6xYAXNzc6xZswYvX74ERVGNIlhSq9UgCAJyuZy1iyEIArGxsXB1dUVcXBwCAwNLpVyFhYUhLi4Oo0ePLpFkMl2jBw8e4PPPPy+XClz8MxRFITo6GmvWrIFWq8XKlSvRrFmzCpNoJhl99eoVVq9ejaSkJCxbtgz9+vWrs3lZpst5584drFq1CocOHUK7du2wdu1aDBs2rEZzYkwibGxsjI0bN+L777+HmZkZVq5ciSFDhjSYDvDbIAgC3bt3R2hoKGQyGQQCAbp27Ypr166x4ljZ2dng8Xi17mda2yAIAo6OjhAIBEhNTdWj9zH0aKb72KVLF9y9e7dR3POVBUOlFIlE8Pf3ZxOe/Px8+Pn5wcrKChKJBDweDyqVqlK/p6WlJYYMGYIDBw7oUaQJgkDv3r0RHR2NR48eYd26dbC2tsaiRYuq5KVtb28PHx8f3L17FyRJIi0tDfv370dqaiqOHDmC4cOHY+3atRgyZAiuXr0KgiAwYcKEUotkjMjJjh070KZNGwwdOhRKpRJFRUU1EmCsbyQnJ8Pc3Bw8Hq9WRhFomsbVq1fRpUsXNrBWq9V49OgRunXrVu11icPhoFu3bhgyZAh+/PFHVjvkbeTm5sLExASjR4+Gt7c30tLSoFQqK33vURSF169fY+3atTA3N8eSJUvYAnB5YJ5PL168wI8//oju3btjypQplfasry5omsazZ89gZGSkp5hLkiROnjyJwYMHl5rQ0DSNR48esTTvZ8+eQSAQwN/fHwkJCSxNnqIoSCSSWiuSAG9+y1atWiEsLAzt27fHkydP6izo53K5cHR0REpKSqmNFA6HA2tra2i1WjYRNjc3b/AFrZSUFDg6OtZ4Plin06GoqAgmJiZ6FmcCgaDBdiSZa5ckyVIp/w0ZJEkiIyMDLi4uoOk3lrCMfoZardaLhRu7xlBN8D4R/n8YGhrCzMyMVSdmksrExMRaX6AIgkCTJk0wfvx4/Prrr7W6CDJiU6NHj8b06dNx9OhR/PXXX6x3W0MGI5rACJU4OjqyD143Nzc9pcHiyMvLw4EDBzB9+vQSHQCafmO1cvjwYcyePbtSwReTVB44cAB79+7F5MmTERwcDCMjo0oFKHl5edi+fTuOHDmCyZMnY8aMGbVK9SoOnU6HlJQU/P3331i1ahVevXqFKVOmYMWKFejYsSMrhlCd72aCLbVajSdPnuD+/fsQCARYtWoVhg0b1uA6wKXB1NQUfn5+ePToEQDggw8+wKNHj/D48WO0aNGC9RFuDFQnX19f5OXlsYUiBgRBwNfXF6mpqVAqlQgKCmK9Zf8tKCoqwpkzZ/Dhhx/qBd8qlQoffPABCIJAamoqzM3NKx1UEQSBLl26QKlUlhDREQqFaNasGb788kuMGjUKo0aNqtCypjQMGDAAhw8fxrp167Bjxw44Ojpiw4YN8PX1ZYtTISEhKCgowLRp08pUVidJEn///TdsbGwwaNAgODo6QiaTsQyaxgBGyMnY2BhmZma1snZIpVI8f/4cXbp0Ybf38uVLODg41DiZIggCnTt3xqhRo/Dzzz+XKFrT9Btve6Y4yuFw0LJlS2zcuBESiaTc5y3TGdu/fz8OHDiAjz/+GKNGjap0oVSr1eL48eMICQnBnDlz0KVLl3oZ7VCpVDh16hTGjBmjt2ampKQgOzu7VKVoZn8jIyPRsmVL9rxZWVnB2toaaWlprKo1SZIsVbo20apVK7x48QKOjo6QSCR6LI3aBDNKlJCQAHd3dyQlJZV4j7W1NXQ6nZ6XcENPhF+9egVfX182Ea4ulEolCgsL2XUaeHMPC4XCaneZ6xJM8njy5EkEBwc3yH0sDyRJQq1Ws3P8mZmZrHigRqOpVFPov4D3ifD/QyAQwMzMDEqlEvn5+QDeSO+npaXVScWdEXHo27cvtmzZUuuJKrMgL1myBKampli7di1evHjRoKs+UqkUZmZmyMzMhIGBAezs7KDRaJCWlgapVAo/P78SAa5Go8Gff/6JwYMHl5gLpGkahYWF2LFjByZPnszOSZQHiqIQERGBdevWwcDAAMuWLau0V5xSqcS5c+fwww8/oEmTJli6dCmaNm1a6wEKo3x969YtfP/999i1axecnJywbNkyTJ8+HV5eXjVO7CiKQnp6Onbu3Ilff/0VVlZW+Oyzz8Dn8xu0qNTb4HA46Nu3L65duwatVgszMzN4e3tDrVbDzMwMz549Q+vWrd/1blYKLi4uyM7OhlAoLDFTZmxsDDc3N0RERMDU1BS2traIi4t7R3tau6AoCidOnECnTp305nLlcjkyMjJYgaT09HQYGhrC3Ny80vccj8fD5MmTcfz4cVaNmyRJXLlyBS9fvsQHH3xQ5XWZSXKuXbuGbdu2QaFQwMHBAcuXL0efPn1Yz+KLFy/i2LFjSE9PZ5WfSwNJkjh+/DiUSiUmTJgAHo8HU1NTyGQyCIXCRpUIp6eng6bpGontFN/ew4cP4e/vzyq4kiSJq1ev1pqnMkEQaN++PcaOHYvNmzfrCSAxz4rmzZuDpmkkJiZi6tSp6NatGyu2VRooisKrV6/w7bffgs/nV2lchqFCM/PLixcvhpubW70UJGmaxo0bN+Dl5aX3+zHd4CFDhpRJby1+b+bl5SEjI4MVGCNJkk18mVirthMOJycnqNVqVqQtIiKizhJPpoHi5uZWYkSFIAhYWlqyz3CCIGBiYsLaKTVE0DSNhIQEODs7Q6lU1qhIoVQqoVar9RhqDdnGh6IoHD58GD169KiU+nxDg1wuB4/HY+9LsVgMa2trdmyveCJc3YbJvwGNq7xRh2AoKjKZjK3UmZubQ61WQ6VS1QltgyAIfPDBB5BKpdi6dSsWLFhQrZmm8rZvaGiIkSNHonXr1vjzzz8RGhqKMWPGNMhunkKhgLm5OTIyMiAUCiESiZCdnQ2BQID4+PgSdkjMg5nP55dKg9Nqtdi+fTu6devGWq2UBZqmIZVKcfToUSQmJuKTTz6Bp6dnpYITkiQRERGBI0eOwMPDA0uXLoWFhUWtn1+NRoP4+HjcuHEDiYmJ8PX1xYQJE+Dm5lYp66bKgCRJJCUl4ezZs8jMzES/fv0QHByM48ePQ6PRsPNyDe3aKQ9OTk6wsLBgOxL29vZ49uwZ8vPzUVRUVK7CcEOCg4MDioqK4ObmhsTERDg4OLD/xnQ3r1y5gnbt2uGDDz7A7du3ERgY2KBFwCoCTdN4/fo14uPjsWTJEva6Y8YdsrKy2KA5KSkJAoGAVaKtDJhRlTZt2uDMmTMYM2YMTp48ibi4OHz99dcoKCjA9u3b0axZswoFYpgE+NatW7h9+zZ8fHwwe/Zs0DSNzZs3gyRJdr/atm2LHTt2ICAgAIsWLSpz3acoCtevX0d0dDQWLlzIBi6mpqZQqVSwsLCAVCrVuxYaKhg6qEgkqragVHGo1WrcvHkTs2fPZl9LT0+HXC5nPWlrAwRBsPZYmzdvxpw5c+Dq6gqFQgGJRAJHR0c2kWGKHFwuFxs2bMDChQtZBWSapqFQKHD8+HFERUVh6tSp8Pb2rvT9SVEUnj17hsOHD2PIkCHo0qVLvTJZioqKcO3aNSxevJjdZ6YAIJFIyrQ1ZKilzDl8/fo1AMDb25sVxmKOQ6vVgiCIWj8uDocDPz8/vHr1Ch06dMD169f1hL5qE5aWlqxOwZUrV0CSpN7xMMfLaBNYWVnh5cuXIEmyQXYcZTIZpFIpKIqCpaVljWJUpVIJkiT1iukajaZBWhHRNI3nz58jLy8P06ZNa1QxD4P09HTY2tqy+YtcLoeRkREoioJWq9VLhBsqNb0+0PDuuncEgiDYWUdGLZTH48HIyAiFhYUwMTGpk+/lcDgYNGgQZDIZduzYgZkzZ9a6aACHw2F9h8+cOYN169Zh0qRJrLhIQ4FMJoO5uTkKCgpgaGgIoVCIR48ewd3dHa9fv9arQjMiAJcvX8bSpUtLPDhJksThw4dhaWmJPn36lHucFEUhPDwcBw8eRPv27bF8+fJKUdQY5eRDhw4hPz8fU6dOhZeXV60lHowqbmZmJu7evYtnz57BxMQEPXr0YOfBANT4N2Qo0FFRUTh16hQUCgUGDRqE1q1bs3RQLy8vPH/+HMAbwYXGJBjB4XAwYMAAnDp1Cs2bN0dUVBRMTExw6tQpuLm5NZoHgFAohEAggLW1NRITE9GxY0e9397b2xv79++HVCqFv78/QkJCWJZFY4VCocDevXvxySef6AVgOp0OZ8+eZddKiqKQn58PCwuLSs1YFgdBEBgwYADWrl2L1NRUCAQCzJs3DyKRCKampvD29saNGzfQv3//MgN9Jim7cuUKmjdvjkWLFrHUXJqm4e3tjfv376NXr16gaRr3798HSZIIDAws02aM0T64efMmFi1apPc+RnDHyMgI6enptZr41RUY7+P8/PwaCzrRNI3IyEhYWVmxLAGmMPrBBx/UeiLFKI1zuVxs2rQJc+bMQVFRETu3Hx4eDldXV7Yg2b17d/B4PL1k+PXr19i7dy+aN2+OZcuWVXqel7m+/vnnH0RHR2PevHlwdnau12c3TdM4deoUOnXqpEc5p2kax44dw9ChQ8uMW5jn69y5cwEAT548gUgkQmBgIGJiYtCkSRP2WMRiMczMzOokIWzbti1rrZieng6VSlWrjQcGpqam4HA44PF4kEqlUKlUeh1PpjCSk5MD4E3izAiFNkTk5ubC1NQUqampNY5vFAoFSJJk42mKoqDRaBqkRodMJsOhQ4cwe/bsRkkhZhg4zPOQKcQZGRmBJElWtZx5b2PSmqhtvE+Ei8HQ0BBcLped1+BwOHB3d0d8fHy5dhw1BZfLxdixY/Hnn39i7969+Oijj2o9OC8+O9yqVSu2Ozx27NhKzb7WB2QyGUxMTJCamgonJyfw+Xy8fPkSTk5OcHR01AsEtVotdu/ejbFjx5awIaJpGnfu3EFiYiK+/vrrMh+qjArr4cOHkZ6ejs8//xweHh4Ayk8uaZqGSqXC5cuXcevWLQwaNAhdu3Ytc76vKmCS0oKCAoSGhuL+/fvQ6XRo164dFi5cyD4wauP3omkaWq0WL168wNmzZ8HhcDBkyBAEBgaW6DB7eHjgwoULsLKyQmZmZqNKhJkZWoVCgcjISMhkMkyePBmLFi3CTz/99K53r9IgCAL29vYQiUSsCF7xgN/Q0BDe3t548eIFOnfuDD8/P4SGhqJnz54N4v6uKhgl+NatW8Pb21uvGxwVFQUul8vSCXU6HWt/Vx3aLZ/Ph1AoRGhoKP7++2+9tWbEiBH4/vvv0bFjRz3PXiZ4ePr0KY4fPw4vLy989dVXpd6jgwYNwubNm9G5c2c8fPgQDx48wPr167F7924MHjy4RLeZOcbDhw/jiy++KDFTy+FwYGpqyrJmGgPEYjH4fD5kMlmNaYYkSeLixYsYNWoUe16kUikiIyNLMIdqCwRBoFmzZvj000+xZcsWmJmZoXfv3iAIAmFhYXodUYahweFwsH79eri5uSE3Nxcff/xxlcSGmELojh074O7ujiVLltS5IFZpyMjIwIsXL7Bq1Sq9+zAmJgZKpRLNmzcvc5/S0tIgEAhgY2MDmUyGzMxMCIVCODs74+7du3o09tzc3FKtD2sKgnjjfpCTkwOCIODg4ICYmBi0aNGiVr8HeBPPWVtbs9f729RfU1NTdrafpmmYmZlBo9E02EQ4NjYWPj4+eP36Nfr27VujbeXm5oLD4bDFAEbnoaF1hCmKwj///IP27dvX2+hBXSA5ORlt2rQB8L9uvKGhYakd4YZKza8PNF7OXC2DIAjw+XxwOBxkZWWxr9WVYNbb4PF4CA4Ohlwux7Fjx+psLpkgCHh7e2P58uUwNjbG2rVrWVpOfYBRVJbL5cjPz0dCQgIiIiIQHh6OuLg4KBQKpKamwt7eHnK5HDk5OcjNzdUT4aBpGufOnYOtrS2CgoJKJMGxsbE4d+4cZs2aVWYlT6fTITQ0FOvWrYO9vT2WLl0KT0/PCuckdDodnj9/jjVr1kAsFmPFihXo2bNntYR0ioMkSeTn5+P69etYv349a9vx0UcfYeXKlRg2bBirol0bybZcLsft27exevVq3Lp1C+PHj8fSpUvRqlWrUhN6ExMTqFQquLq61rqSen2Az+ejT58+2LRpE9zd3dGkSROYmZk1uAdwRWDohMXV7Rkwwfe9e/cAvBEGu3v3bqN8wNE0jSdPniAlJQXDhg3Tux4pisLp06fRrl070DTN0gwFAgG0Wm2VizQajQb79u2Dvb09goKC8PTpU7313sLCAp06dcL58+f15kOTkpLw008/4fbt25g1axY+/fTTUu9RJvB2d3fHli1bcPXqVcybNw/e3t5wdnbG06dPSxx7UlIS/vjjD8yYMYPd5tsoTrFsyEI7DNLS0mBhYQEDA4MadViYmUWKouDl5cV2Ox4/foyAgIA61TAgCAJ+fn747LPPcPHiRYhEImi1WiQnJ7MWQAxIkgSfz0dubi5u376NadOmVSkJ1ul0uHv3Ln755RcMHDgQwcHBMDQ0rPegXKfT4fDhwxg2bJjeuWWSheHDh5fLYrt//z7atWsHHo+H1NRUdmbRzMwM2dnZek2GvLy8OkmEgTfPABcXF8THx6NDhw54+PBhndw3BEHA3d0dKSkpsLW1ZeNJBjweDwYGBuxsv6mpKUs9bmhgih0+Pj7IycmpcQGL6YIzrAKSJKFUKhvUc5gZx4mLi8OQIUMabRJM02+8n5mxGalUCj6fD4FAwMYOjUEktD7wviP8/yAIAkZGRhAIBBCLxewcpKenJ65fv16i+1IXEAgEbLX5woULGDRoUJ3N94lEIowePRqtW7fG33//jadPn2L06NF1ZoVDURSysrLw+PFjtivH5XJhYmLCduLDwsKg0+kQExMDQ0NDSCQSSCQSaDQafPjhh+y2EhIScP/+fSxfvlzvN2EU/nbv3o1p06aVqtTMvOfQoUOQSCSYM2cOXFxcKkWDzszMxJEjRyCXy/HJJ5+wYh81OScSiQQRERF48OABJBIJAgICMG7cODg7O9e61RJDS7x9+zbu378PLy8vfPbZZ3B2dq7w2haJRDAzM4ORkRFiY2NrbZ/qE+3bt8e6devw6aefIjc3FyKRCFevXoWvr++73rVKgQmwnj9/DgMDAxQUFJSglPn4+EAsFkMsFsPZ2Zm1T6hvKmVNkZ2djaNHj2LBggUlkqbo6Gi2kyISicDhcJCZmQkLCwu2C1NZ6HQ6HDx4EBqNBtOmTUN+fj5++eUXNGvWjO3+EgSBvn37Yt26dejevTvMzMxw+vRphIeHY/To0WjRokWlGDxOTk5Yv349jh07BisrKwBAv379cOjQIXTo0IG9BzMzM/Hbb79h6tSpbHGuNLi4uCAxMRFisbjBzhcyKK4YrVKparRuMoXQAQMGsMes1Wpx8+ZNzJgxo86vc0bgqGXLljh06BDEYjEMDAzYAgzjHHDo0CEUFhZi3bp1yMnJwfbt2zF37twKGQuMyOOBAwcglUqxaNEi2NravpP7l6ZpREREQC6Xo0OHDnr/Fh4eDg6Hg8DAwDI/zzCO5s+fzxa37OzsWJszDofD0pOZUaO6ovkTBIG2bdviyZMnGD16NE6dOlVnyrleXl64desWqxzdrFkz9t8MDAzA5/Oh1Wqh1WphamqKwsJCaDSaWt+PmkKj0SAjI4OlexdnxFQHBQUF4PF4LDVaq9VCKpU2qERYoVDg4MGDCA4ObpSUaAYURUEul7PFK6lUymoDURQFDoejt6b8l5PihvvkrGcwYlkEQUClUrGVQsZSSavV1suFIhKJMGvWLGzYsAFCoZClXtUFOBwOvLy8sHTpUpw+fRpr167F5MmTERAQUKtzrpmZmQgJCUFWVhY6duyI4OBg2NjYgMvlgsvlsseXmJgIQ0NDKBQKzJkzBxEREUhOTkZERAQuX76MYcOGgcfj4a+//sKkSZNKLJ6Mz2bv3r3RtGnTEueNJEk8efIEISEh6N27Nz755JNKdXJlMhnOnTuHx48fY+jQoejYsWO1adA0TUMsFiMiIgKPHj2CWCyGr68vhg8fDg8Pjxp3lsv6zoyMDFy8eBGvX79GUFAQvv76a1haWlb6d+ZwOHB1dYVGo0FOTg50Ol2DDrxLA5fLBZ/PR0pKCpKTkzFmzBg8ePCAVVJsDHByckJBQQHs7e2RnJxcIhE2MDCAv78/wsPD0bNnT3To0AG3b9/WKyQ1dKhUKuzevRvDhw8vofSu0+lw7NgxDBs2DOHh4bCzswPwP/qlubl5pRNhiqJw5swZ5OXlsXNg9vb26NSpE06fPo1Jkyax94ehoSEGDBiAbdu2QavVIiAgACtWrKhUh46ZCX706BH69euHxMREODo6AngTMJMkieTkZHh6eiIvLw+bN2/G+PHjWb/ksmBra4uoqCj2+dSQ70eappGSkgIzM7MqiZmVhszMTOTl5bGe8kwHx8zMrF5EwxgRnd69e6NNmzb48ssv0atXLxAEAY1Gg1u3buHChQvo168fevToAQMDA1bQcOPGjZg3bx6rdF7atiMjI/H333+ja9eu6N+/f62M3FQXzGzyRx99pHd9qdVqHD9+vMTrbyM5ORlCoRC2trbQaDSIioqCnZ0dAgMDkZSUBCcnJ7aIxHSwunXrVifHQhAEmjZtihMnTsDY2BgmJiZITk6uk8Tb3t4eOTk56Ny5M548eaInMMmovufm5qKoqAimpqbQ6XSQSqUsZbihQCqVgiAISCQSODg41CgGZpSyGW0D4E0iXFRU1GB0LGiaxvnz5+Hr61sjv+SGgIKCAhgYGLDnmkmEAbCJcHG8nRj/l9Bwn5zvAObm5uysGZMIC4VCGBoaIj8/nw1e6hKMaNeCBQvwww8/QCAQoGvXrnV2gRIEAZFIhLFjx6JNmzbYs2cPvL29a2V2mKGrhYSEYNiwYejYsWOZ6sbMvKpSqQRBEHBycsL9+/fRtm1b9O3bFxwOB+vWrYOHhwecnZ1LCH1RFIWjR4/CysqqxEwkU2Hft28fJBIJvvjiiwqtlBgK96NHj3DixAm0bNkSq1atqnLHnBG8ysnJQVhYGB4/fgy5XI6mTZtiyJAh8PLyYgP32u7+kiSJuLg4nD17Frm5uejVqxfGjRvHLoxV/b4mTZqwfqsFBQWNJnlkkJycDH9/f9y/fx9cLheLFi0CTdO4du0axo4d2ygeAgxLwNHREQkJCSVGAwCgW7duOHDgAD744AO0a9cOP/74I0aPHt0oqtsURSEkJASOjo4lxMCYBITP58PPzw9nz56Fq6srDAwMkJiYCJFIVCmLNGZbt2/fxrNnz7B48WK9Gd3+/ftjzZo1SEtLY7t3Go0G6enpuHr1KtasWVPpAiWTBJ89exZffvklioqK8Mcff6Bt27bg8/ng8Xjo1asXrly5gnHjxmHLli0YOHAg2rRpU+H2LS0tUVhYCA6HA61WWyfCP7UFZs0wMDDQE0eqznbOnTuHnj176l3Pdc2gehthYWGYOHEiPDw80KJFCzx48ABubm4IDQ2Fubk5lixZUoLi26pVK/B4PFZ52t3dXW/cR61W48SJEwgPD8eMGTPKZQPUB2iaxq1bt+Ds7MxS0JnXHz16BCsrqxJ08Lc/f//+fXTq1AnAG5YHn8+HWCyGj48P7t+/X2L2Xy6X15kwKfCGhmxmZoa0tDS0a9cOjx8/rpOEx9raGhqNBubm5sjMzNRjbHC5XFhYWCA9PR1FRUWwsLAAh8MpYYnXEJCSkgInJydER0cjICCgRueJoigUFRWBz+frJcIKhaJBdIRpmkZycjKePHmCFStWNIp4oDxkZ2fD2tqaLV5kZWWx1HaSJPUS3/+6WNb7GeH/B0N3IkkSFEVBqVQCeLNoubq6IiEhod7msJju9BdffMF2Iuv6uwnijTLwihUrYGRkhLVr1+LVq1egKKpa380onp49exaLFi2qUEyKUQ/My8sDl8sFj8dDQUEBsrOz0alTJ4wfPx69evXCzp07S6hAMw/c2NhYTJ48mX3gMMkgMwvs6emJxYsXV6gqS1EU4uPj8d133+HBgweYP38+Jk6cWGnLKZqmodFokJqaihMnTmDlypXYunUrCgoKMGnSJKxbtw5Tp06Fv78/m9jU1qL79vzv0aNH0a1bN6xZswZ9+/ZlE/nqfJ+zszMyMjJgaWmJvLy8Wtnf+kRoaCh69+4NV1dXFBUVsUWT0NDQRuPFyuPxYGtrC5FIVOqsNkEQcHFxgUqlQm5uLqysrFjF2oYOJjlNTk7GhAkTSnQfVCoVTp48ibFjx7JCd8bGxjAwMEB+fj4UCkWlKOA0TePFixc4f/485s+frydkQxAEhEIhRo4ciZCQEOh0OuTk5ODHH3+ETCbDzz//jNDQ0ErN89E0jQcPHuDMmTNYuHAhrK2t4e7uDhMTE0RGRrLrart27fDq1SusX78eHTt2rHTh09LSEnK5HBwOByqVqsL3v0totVqo1epqi5kxyMvLQ2xsLNq3b8+eo7S0NMhkshol2FVBYWEhZDIZnJycWB0LX19frF27Fh4eHpgzZw5sbGxK7AsjtjV16lT8+uuvbExB0zRSU1Oxfv16KJVKrFixokEkwRKJBFeuXMGoUaP0CgwKhQLnzp3DmDFjyt2GSqXCq1evWLGe0NBQeHp6Qq1Ww87ODjExMXpjKUwMUJcFOy6Xi1atWiE0NBQtW7bEq1evoNVq6+R7jI2NodVqodFo9L6DIAiYmZmBJEkUFRVBKBTC1NS0wSXCNE0jOjoavr6+SEpKYoVEqwuNRoOCggIYGxuzay5JktBoNHXChKsqtFot/vrrL0yYMKHORgTrExkZGXqF4eLzwm8nwv91vO8IF4OxsTGbPBUUFLCJj7e3N+Li4tC5c+d63R8rKyvMnz8fmzZtAp/PR8uWLev0wmW6w2PGjEGrVq2wd+9eeHt7Y9SoUVVeGAoLC3Hy5EnMnDmzXIEFpgOUnJyMp0+fshShs2fPgiAIJCcnszfw48eP8cknn+Cff/7BwoULwePxWGGZEydO4KuvvtKbNyooKMDhw4eRl5fHzmZV1AUWi8U4duwYS51t1qxZpSiHzDxGcnIyQkNDER0dDaFQiJYtW2L69Omsl1td/X4kSSIrKws3b97E8+fP4e3tjalTp7KWHrUBCwsLqFQqNG3aFLGxsWjatGmtbLc+oNPp8OrVK8ycORMKhQKvXr0CTdOwtLSEl5cXQkNDS/WibmhgrNAKCgpQUFBQqnYBj8dD27Zt8fDhQwwfPhw9e/bEjRs3KvTSfpegaRpxcXE4c+YMvv766xLdTaZz7+7uDjc3N+Tn57PHzQiucLncMimnxbeTlZWFffv2Yc6cOaUKaxHEG6uc69ev4+jRo3j27BlGjBiBDh06sIr0ERER5SrlUhSFhw8f4vTp01iwYAFLeSQIAkOHDsXx48cRGBjIrgkKhQKWlpYs+6UyYDpnhoaGyM7ObpAWJAxycnIgFAqhVCqrTf+kaRqXLl1C165d2UCapmlcvHixRIe4LhEdHQ1XV1dwOBzcuXMHkZGR6N69Oz788EPs3LkTjx8/RocOHUq9NgiCQGBgID7++GP8/vvvmDZtGpKSknDz5k2MGzcOrVq1ahCzejRN4+jRo+jRo0cJu6QbN27A19e3QvZFSkoKTE1NYW5uDpIk8fz5c3Tp0oX1omeKkQzUajUIgqjz37FFixbYtm0bRo4cCS6Xi+zs7BoVZ8qCg4MDOz+uUCj01jQLCwtQFMVSjxk/8IYEpiHQokULFBYW1njsQK1WQ61Ww8TEhP2NSZIESZLvnK1E0zQuX74MW1vbctf1xoT4+Hi2CAUAEomEnfF+29v6v473iXAxGBkZQafTsUkUszi6u7vj2rVrenMe9QGCeGOXMmvWLGzduhUCgQB+fn51vg8cDgc+Pj5YunQpzp49y/oOV2V2mDGsr4zK4MWLF7F37169zvNXX33FBnpMoOPh4cHaTL1+/RqBgYEoKirCzp078dFHH7GBIEVRCAsLw6FDh9C9e3dMmzat3IWWpmkolUpcu3YNt27dQq9evRAcHAyhUFjuuSZJEmKxGFFRUQgNDUVmZiarPDtkyBCYmpqWSQWvLcjlckREROD69euQSqXo3Lkzli5dCjMzs1qnCTKCWYaGhqySemN5YOTm5oIkSdja2iI6Oho8Hg8xMTEIDAzEgAEDsHv3bnTs2LHWPbzrAl5eXrh69Sq4XC7EYnGJBIggCHTo0AFbt27FoEGDEBAQgCNHjiA/P18v8GxIyMzMxPbt2zF9+vRSE6WcnBzcvn0bS5YsAUEQrKVdUlISG2QyVMTyoFQqsWPHDowaNarcWVWGfr5lyxbs27dPj8I5YsQIHDx4EP7+/qWKZFEUxdKhGQ9Z5rMEQaBJkybQarVISkqCq6srduzYgYCAAHb2vrIBCkEQMDQ0hLGxMbKzs/UEeRoaGDGz3Nzcat9jEokEz58/x8qVK9nzKRaLERMTU28z8My4j62tLX766Sc8ePAAc+fOxYgRIwAACxYswObNm6HT6dClS5cyk2E/Pz8MGTIEn376KXr06IGlS5eyGiUNAbGxsUhJSUFwcLDePhUWFuLmzZtYsmRJuc8XpmDEnIP8/HyQJInMzEw0a9YMGRkZMDc312NjiMVimJiY1Lmvu62tLVv0btWqFZ49e1YnYoJeXl5ISUmBnZ0d0tLS9NZehg4tFovB4XBgYmKCwsLCWv3+mkKtVqOoqAg0TcPU1LTGySpjEVXcmo6iKJaF8y6RkZGBGzdulBBgbaxgxvGY2IAZD2SejxqNpkRjpiFrTNQ1/rtHXgoY9WIOh6O3KJmbm0Mul0On09V7oMxQHWfMmIHffvsNM2bMqJchfibIGjNmDFq3bo0///wTPj4+GDNmTIUCMTqdDmFhYZg7d26F+0kQBPr374+DBw/q0Ye0Wi3y8/PZvzPzv/v27YNAIMC1a9fg6+sLU1NT9OjRg1WulMlkOHLkCJKTkzFnzpxyg13Gszc8PBwhISGscJiFhUWJzzBJularRWpqKp4/f44XL15ApVKhSZMm6N27N7y9vdnkua5+n+JUulu3brE+y0OHDoWPj0+ddp2ZaxF4Q7PRarWNInFkBGgCAwOhVqtZivr58+cREBDAKnTHxsZWKFDUEODo6Ii8vDzY2NggIyOj1E6gtbU1RCIRUlNT4enpicDAQDx9+rTEWMG7BvOA/vXXXzFu3LhS1zaSJHHo0CEMHDiQfZBHRkaylD2JRAITExOIxWK9IOttkCSJAwcOoEmTJnp2bG9Dq9Xi0KFDyMzMxMSJExEVFaU3C+nt7Q1zc3M8ffpUj6ILvAns7t69iwsXLuCLL74o1QqGy+Wif//+OH36NPh8PkxNTfHhhx/i559/RlJSUqUpvoyehEAgYLtsDem3ZcAoRguFQpiZmVUr0WE6kW3btmVVUBkqfbt27cr93WsLjKrxlStX4O7ujokTJ0KtVutdS3Z2dliwYAF++eUXkCSJDz74oMQYD0mSuH79Oi5evIgvv/wSt27dQnp6eo0VeWsLGo0GBw4cwPjx4/USFJqmcebMGXTu3LlCizKFQoGYmBiMHTsWwJuZ6qZNmyIxMRE9evRATExMCdcFsVjMJoh1CR6PBz8/P7x48QJBQUH4888/MWjQoFpNBBidk7CwMHh5eSE9PV2v08gk4zk5OeBwOBAIBCgoKGhQ93BeXh5MTEyQlpZW7ix4ZaFUKkHTtN69StM0eDxevdy/ZUGr1WLfvn0YNWpUg7kHawq1Wg2pVMoWX9RqNZRKJXt8crm8xDlvDBZ8dYX3M8LFYGRkxHq8MRZKzOvGxsYl/ODqCwTxxsZpxowZ2LZtW73PK3t5eWH58uUQCARYvXo1Xr9+zc7IURQFtVqttz8ymQxqtbpS3SeCINCxY8dSu0AGBgZ6whmFhYXIyspCUlISHj9+jIMHD+LBgwe4f/8+1Go1oqKisHbtWhgbG2Pp0qUVJsFpaWnYsGEDzp07h88++wyffPKJXhLMBC2FhYV49OgRfvvtNyxfvhwHDhwAj8fDtGnT8O2332LatGlo1qwZDA0N62TugknYCwsLcf36daxevRq7d++Gra0tli5dinnz5sHf379e5myaNm2K9PR0lgreGEDTNJ4+fYo2bdogOjoaTk5OaNu2LQoKCpCRkQEOh4OBAwfi/PnzDdLL8W0YGhpCp9OxnpilgcvlolOnTrh9+zYAoHv37rh3716dzMNVFzRNQ6VS4ffff0eXLl3Qtm3bUgtQjx49glKpRKdOnUAQBEvZYwLp5ORkGBoawszMrMzOAk3TuHfvHrKzszFq1Kgyq/4qlQo7d+6EUqnE/PnzMWnSJNy6dUuvKMfhcDBq1CicOXNGbzaXoijcvHkTly5dKjMJBv5Hj719+zY0Gg0mT54MgUCAHj16sMyjysLJyQkkSbL+nA0VSUlJ4PF4cHJyqlaiI5VK8fDhQ/Tt25d9TS6X4+HDh6xic12BEbK6dOkSFixYAGdnZ/zwww9o2rQp1Gq1HnWYIAjY2Njgq6++wuXLl3HlyhV2TWESnw0bNiAyMhLLli3DiBEjsGDBAvzxxx948eLFOw9GaZrGzZs3YWVlVUIcKSsrC+Hh4RUW0xgVbxcXF3bc7MmTJwgICIBMJoOdnR0iIiIQEBCg9xnGQ7iuQRD/s1Gyt7eHSqVCQUFBrX8PU7BkFP6Lw8zMjBWPYpoOEomk1vehuqBpGrGxsfDy8kJcXFytWAwyloXFYzq1Wg2BQFCn3t/lgaZp3L17FwYGBiWKmo0Z+fn5EAqFLONCoVDodd7lcrmeGC4T6/5X8b4jXAwmJiasSnTxpJfD4cDZ2RkpKSlwdXV9J/vGUOo+++wz/P7775g9e7ae6mRdf7dIJMK4cePQpk0b/PXXX2jatClGjhyJBw8eYOvWrdizZ4+eSXpxW6SK4ODggKCgIJw+fVrv9Xbt2iE8PBzAm3nphQsX4uDBg4iMjATwhrKekZGB7du3Q6PRwMjICNOmTYOPj0+ZwRYzm3T69GlERERg2LBhaNu2LdulYBL7rKwshIWF4cWLF1AqlXB3d0eHDh3w4YcfltoxrgvQNM3Os96+fRvZ2dnw8/NDcHAwa8dR33BycsLZs2dhbm6OvLw8WFhY1Ps+VBVSqRR5eXlwd3fH33//jbZt20IoFKJnz564cOECPvnkE/j7++Po0aPIysqCk5PTu97lciEQCGBpaQmBQMB66pYmzNOyZUtcvHgRGo0Gjo6O4HK5SE1NhZeX1zvac32o1Wps374dHh4e6NevX6n3VH5+Po4dO4YvvviCZR9kZWWBz+fD2NgYHA4H6enpMDQ0hJ2dXZn3ZVZWFk6cOIHFixeXSfGTyWTYtm0bHB0dMXbsWBgYGEAgEKBXr144ceIEpk2bxq4rzs7OcHV1xYMHD9CjRw/QNI2rV6/izp07WLhwYblFQJ1Oh5MnT8LGxgbW1tbs+ETz5s1x4sQJSKXSStmJEAQBOzs7iMVi5OXlNWgv4fz8fFZvo6prJxOsMt7OBPHGMik0NBTe3t51ugbpdDq8ePECx44dg7OzM4KCghAYGAihUIgXL17A3d29xPVEEAQsLS3x1VdfYePGjdBqtejZsyfu3LmDixcvYvjw4ejUqRP7W7m5uWH+/PnYunUrJk6cWOdaIOVBLBbj0qVL7AgCA4qicOTIEQwePFiPzlwamE59r169wOFwkJ+fD5lMxl6vXC4XWVlZJVw40tLS6s3T3c3NDQUFBZDL5fDz82Pt5mrzvDMdNzMzM2RnZ+ut0wKBAFwuFwqFgvXnlUgkDaojHBUVhdatWyMiIgIeHh413i9mjSrOYMrJydFTka5PMMWXc+fO4auvvvpXUKIZ5Obm6jWXlEqlHpNToVC80y58Q8P7jnAxGBsbg8/ng6KoEhXCpk2bIioq6t3s2Fv7MXXqVPz+++9ITU2t1woyh8NBkyZNsHz5chgYGGDp0qVYtGgRzp07h++++w5qtRrAm0Vep9NVuvtkYGCAXr16sb7CBgYGMDQ0hJ+fH0iShKenJ/bs2YMFCxaww/9CoRA0TSM7OxsKhQJHjhzBiBEj4OvrW2oSzMwBX758GWvXroVIJMLy5ctZi5a8vDzcu3cP27ZtwzfffIP9+/eDw+FgypQpWLlyJaZPn46goCBYWlrWefeBmfvduXMnVq1ahUePHqF3795YuXIlpkyZAi8vr3cW8Nra2kKlUsHOzg5xcXHvZB+qioSEBJYdEB8fzwZb7du3R1RUFAoKCtiO3JUrV955V6YiMJ7OKpUKeXl5ZdoemJubw97eHq9fvwaXy0X37t1x48aNBtH1VqvV2LFjB6ysrDB69OhSgxCdToe///4b/fr10xNqefLkCZo3bw6tVsuyd1QqVZmCN2q1Gnv27MHo0aPLFJSSyWT49ddf4ePjg/Hjx+vRd3v06IGEhASkpKTofWbYsGG4cuUKpFIpLl26hHv37mHBggXlJsEkSeL48ePIy8vDmjVr8PLlS5ZZYWRkhICAgCq5BNjY2EAqlUKj0TSI37U0qFQqqFQqFBYWwt3dvcqfVygUuHnzJvr378+uvRqNBteuXdN7rTZBkiRiY2Pxww8/4OLFi5gyZQqmTJmC3NxctGzZEsAbFeTS7MsYmJmZYeHChbh27Ro+//xzvHr1CkuXLkXXrl311m+CIODq6op58+bhwIEDCA0NfSdrEEmSCAkJQZ8+fWBlZaV3XFFRURCLxSwrozwUFRUhOzsbPj4+AP5Hi46Li4O/vz9bFHmbXl18prGuIRAI4OrqitjYWLRr1471+q1NcDgc1iNYoVDo3Z8CgQA8Hg9yuZwVy5LL5Q3m2UNRFNLT01lRr9qwN5JIJKAoSq/rLxaLwePx3on1G0VROHToEPr379/g/Jtriri4OD06u1Qq1Ss2KJXKEho4/2UV6feJcDEwCZhCoShB+3R2dkZaWto7X6gIgkBAQAAmTZqErVu3Ij09vd73ydDQEKNGjYJGo8GLFy9AURR27tyJo0ePgqIoVsAlIyND73OMGndqaiqioqLw5MkTXLlyBefPn4dKpWKp0CYmJvD19YVOp2M7dYMHD4ZQKESzZs3A4XDA5/ORkpLCHnteXh42bfo/9q47Kor7+97ZQltYem9SRFEBEUTsHQuiicbeEjVqEhuWqImxG5MYW2KLPRqNxt4VOyrSFFFAqvQOCwu7y/b5/cFv5svK0pSW6D3Hk5Nld3Z2Zj7lvXffvTto2yuSJGmBDrlcjmfPnmH9+vVIS0vDt99+i6FDhyInJwenTp3Chg0b8Ouvv+L169fw9fXFqlWrsGLFCowcORL29vbQ1tZu8glCJBIhJiYGBw4cwLp163Dz5k24u7tj9erV+Prrr+Hh4fHevs6NAeoe6evrNytF/11Bidt4e3sjKysLurq69AZMT08PXbp0wYMHD0AQBLp164bY2NhWZ2OhDm3btkVhYSEIgqiR1sdgMNCnTx88fPgQANC5c2ckJia2OKW9oqIC+/fvB5fLxcSJE9X2jFIVVgAqlRqFQoFnz56ha9euyM/PB4fDgUQigUgkUqsYTSkNGxoa1qjkKxQKsWfPHri4uCAgIKBaUK6pqYlPP/0U586do5MOBEHAzMwMHTp0wKZNmxAREYHFixfX2jtJBcGpqamYPXs2LC0t0b59ezx9+pQ+Zt++fREcHFzvoNbMzAzl5eWQy+Wt1geyuLgYWlpa9RIzextUNbh9+/b0BpokScTFxcHAwKDR2RtUy8yePXtw9OhRDB8+HN9++y3atm2LoqIisNlsGBkZQSaTISMjo9beSYlEggcPHkCpVNJJqZoEsQiCgI2NDRYvXozTp08jNDS0WedW6poWFBSgf//+KucokUhw+vRpTJw4sU5NCIoG3aFDB2hra9MWYlTSsWPHjsjKyqIZKlVRXl7epB7Cb8PX1xdhYWGwtbUFj8dr9HmRIAjY29vT/slVdWcoOrBQKIRUKoWhoSEqKipaTTJLIBBAqVRCIBDA0tLyvfu2KTsuBoMBfX19+vni8XhgsVjNrjVCtUsJBIJ/hVtEQ0BpyFR1SalqnQRUJidbs+98c6N18qhaCJRoAUVJrUpTMTMzg0AgoCkGLQmKRjdx4kRs374dixcvrtPKoLHx7Nkz/PPPP/RiLRQK8f3336NDhw7w9PSEp6cnQkJCwGQykZCQgNjYWBQUFEAmk4HD4YDD4dDm9pqamujQoQOOHTtGV7nKy8uRmZkJd3d3XLp0Cc+ePUOnTp3obLJAIABQSdXt1KkT/Pz80LdvX2hqakIikeDcuXP4448/sHbtWjx9+hQKhQIBAQGoqKjAn3/+iYKCAhgZGaFLly6YPXs2TdlqLsozUBkQJCQkICQkBGlpaTAxMUHPnj0xceJEOuhtjRO0g4MDSJJETk5OqxfMkkqlSElJwbhx43D79m14enqqKPgOHjwYv/zyC4YMGQIulwt3d3cEBwdjxIgRrfLaU7C0tEReXh6MjY1p4Sx1cHV1xenTp1FWVgYulwsXFxc8e/asmohPc4BiO+zduxfm5ua1BsFv3rzBnTt3qql4ZmRk0IrOMTEx0NHRgba2NsrLy6tRZKlnNDg4GD/88IPazZxEIsHevXvh4OCAUaNGqa1MEwQBT09PBAUF0Wr11PEJgkBISAjOnj1ba9VEoVDgwoULSE5OxsKFC+k1xM/PD3v37kW/fv3AZrPpqnZ2dna92nAMDAwgl8vBZrNRWlra4muTOhQVFYHL5dYpZqYOYrEYd+/eRWBgIH3/lEolrl69is8++6xRhJWo+biwsBAXL15EUlIS/P39MWfOHFp8kKJie3p6gsFgIC0tDVwut9o9p46VkpKCo0ePwtbWFuvWrQObzcauXbtw6tQpTJgwQS2jhyAIWFpa4ttvv8WWLVugUCjQo0ePJhePonr1T548iS+++EJlPqcCWUNDw3rZ5VGJi+nTp9NMq7KyMlhaWkIgEMDExAQPHjygxxAFym+3uXpFKeVuag/j4OCAuLi4WkX03uU7bG1tkZaWBmNjY3q+BioDYQMDA1r1Xl9fH+Xl5a0msZyeng5LS0ukpqaiXbt2731NlEolSkpKwGKxVJJhZWVlLcJuKy8vx+nTp7Fw4cImVylvbsjlchQUFKi0HrzNthCLxdVs0VpLEqYl8DEQrgIGgwE2m03704pEInpi1tLSgp6eHgoLC+v0qmwOUJszgiCwbds2BAYGwtrautk2t66urjhx4gQePHiA8PBwxMbGIjc3F8uWLcOOHTuQn5+PmzdvIjk5GS4uLhgwYAAsLCxgZGTUoIVdJpOhsLAQ2dnZiI6Oxps3b2BkZAQzMzMsXboUffr0ga2tLT2Z5ubmYtOmTfjzzz8hEomwbNkydOvWDbq6urh27RpcXFwwbNgwODg40Juy5gp+Kd/AmJgYhIeHIzc3F1ZWVujRowemTp1KZ8NbcwBGEATatm2L8PBwyOVySKXSVh0I5+Tk0JZPr169wuzZs1X+bmpqCjs7Ozx//hw9e/bEoEGDsHXrVvj5+bW4t2FtMDAwgFgsRqdOnZCUlARXV1e179PR0YGLiwtevHiBvn37on///jh27FizZ8Epdejff/8dHTp0wCeffKI26CRJEuXl5Th48CA+//xzleoBSZK4d+8e+vXrB4IgkJubS9PqeDxetb5apVKJEydO4NNPPwWXy632e+VyOY4dOwZjY2N8+umntfaIMZlMjB07FidPnqTbL/755x9kZ2dj2rRpiIiIgL+/v9rPKhQKXL58GUlJSSpBMFDJNNLT00N8fDzc3NzAZDLRs2dPPHz4EFOmTKnzHlGtJLq6uigsLKzWd9kakJaWRitGN8QmhQqqnJ2dYW5uTr+WkpICkiTfqd9Y3XeUlpbi6tWrePHiBQYNGoSpU6dWow1SPrhffvklgMpEsIeHh8paRj2758+fx+vXrzF58mR06tSJPs6CBQuwd+9eHD9+HJMnT1Y7b1YV29q6dSsUCgV69+7d5MHw5cuX0b59+2rXtLy8HNeuXcPixYvrda1zcnKgUCjohE50dDRdBbawsICmpiZSU1PRr18/lc+VlpbSjLzmgo6ODoyNjZGVlYVu3brRCuSNCXt7ezx69Aj29vbIy8tTcSXQ09ODVCqlA2Eej9cqAmGSJJGQkAAnJye8evUK48ePf+9xRomOUv3QFAQCQbOvs0qlEqdOnULv3r1Vqqb/FQgEAigUCvo6U1ZhVR0ZKGp0VTS11WdrxsdAuAqoTQUAaGhooLy8XCVDaWtri8zMzFYRCAP/E8QhSRI7d+7EggULmsQPTx0MDAwwbNgwDB06FCKRCDk5OTh37hwOHTqEffv2wd/fH3v27IGJicl7iRBoaGjA2tqaVvqdNm0asrKyEBISQqtsDh8+HEZGRggODsZ3332HyMhIOruloaGBMWPGoEOHDvS5NNdgp9RGi4qK8OLFC7x48QICgQDOzs4YNGgQHBwcoKur+6+bfOzt7XHt2jXo6+sjNzeX7gVrbaDoT+7u7igpKYFcLlcbKPj7++PYsWPw8fGBhYUFrKys8Pz5c3Tv3r0Fzrp+0NHRAZfLhZaWVq2ezgRBoF+/fjh16hR69epFVxkzMjLeqV/zXUBRtfbs2YP+/ftj0KBBNc4Jcrkchw8fRvfu3atZWfH5fMTHx2P8+PFQKpXIysqCiYkJuFwupFKpyoaKJEk8f/4cCoVCbZWHqtAKBAJ88803dVYlKPV8U1NTPHr0CBkZGeDz+Zg/fz5EIhG2bNmCfv36VatoKRQKXLlyBfHx8Zg/f361jT6DwcCQIUMQFBRE+7R37doVP//8c73oa0wmkxZ4LCoqqvW9LYXMzEyw2WxYWFg0aK4Ti8W4c+cOFixYQAeCJEni6tWrGDZs2HtVcqgAOCgoCBEREejZsyfWrFkDPT09tedYUlICmUwGU1NTkCSJmJgYzJo1i36vTCZDZGQkzp8/j27dumH16tXVbAa1tLTw9ddf49ChQzh69CimT5+uNgggCAImJiZYunQptm/fDrlcjv79+zdZMJyeno7IyMhqrAmSJHHt2jV4e3vX696RJImHDx+iR48eYLPZUCgUCAsLw2effYbIyEh06tQJZWVlEAqFKjRNoDIQ1tfXb/KAvyqqqkePHDkSf//9d6NTRo2MjFBeXg4bGxsVTQ2CIFT6hykfYZlM1ioSsImJiRg5ciSCg4PpJNT7QKFQQCKRQKlU0gl/ionQnMkPauxmZmbSrIX/Gvh8vkriV6lUori4WKW15O3n/ENXjf7YI1wFDAYDWlpa9OAsLy9X+XtrEcyqCqoyPHHixBbrGa6oqMCtW7cgEolw6tQpbN26FcOGDaPpxo0FgiCgqakJJycnTJkyBatXr4aFhQW2bNmC+fPnY/z48QgPD1eheJSXl8PNzQ0WFhZNnvGiJhMej4eoqCgcPnyYtjqSSCSYPHky1qxZg5kzZ8Ld3b3GTVfBOL1tAAEAAElEQVRrh7GxMSQSCczMzFp1nzBJknj58iU6d+6MuLg4uLq6VttoUX1cLBYLKSkpIAgC/v7+uH37dqvtuQT+51PJYDCQn59fqzCdg4MDxGIxcnNzwWaz0bt3b9y7d69Z7ptSqcSzZ8+wY8cOTJgwAYMHD65xTlAqlbh8+TLts/v2pvzJkydwc3MDh8OBXC5HRUUFysvLoampCVNTU5WxJJPJcOHCBVr9uSooVdv4+HjMnj273owGJpOJ4cOH45dffkFZWRnmzp1LV5U8PDyqWR9RQXBcXBzmzZtXI+3Tzc0NBQUFtAWSkZERTE1NkZCQUOc5MRgMmJmZQalUoqCgoNWNRaVSicLCQlRUVDTIcYG63w4ODirJq6ysLBQVFcHd3f2dzofqVTx79iw2bdoEBoOB77//Hp988ola1gD1maioKHTs2BEaGhooLi6GVCqFpaUl3VO8fft2PHz4EAsWLMCYMWNq1HPQ1NTEzJkzQRAEDh48CLFYrPaeEQRBOyXcv39fxYapMSGRSPDnn39i4sSJKjRv6ne9ePECw4cPr9c6VVFRgejoaPj6+gKo7P+kBNLi4+Ph6uqKvLw8mJqaVks88Xi8Or2JGxsEQcDDwwOvX7+GpqYmzMzMGl0AUkNDg+6Lzc/PV/mbgYEBFAoFhEIh9PX1IZPJIBKJGvX73wVSqZSu0HM4nEYJzCn2mKampsq8XlFR0az7IIFAgL///hvTp09v1Uy290F6ejrs7e1VknQCgUBlfH3sEVbFx4pwFVATFo/HA5PJVBHNofo9qAWpOTOXdYEKhgE0a2WYJEm8evWKVnb98ssvm8XLFqj8zXp6ehg6dCi6d++Oo0ePwsnJCStXrgSHw0FZWRnKy8ub3DeVotBnZmYiOjoa8fHxEAqFsLW1RZcuXTB69Gjo6ek1ayW6qcFkMqGnpwcTExMkJyereHu2JvB4PMhkMpiYmODUqVM1UlepwOvGjRtwcXGBs7MzlEolUlNTW221GwDatWuHmJgYWtSkpo0k5Sn85MkTjBs3Dl27dsXNmzchFAqbtCdPLBbj0qVLePnyJZYsWVKrjgHVg/ns2TOsXLmy2ialoqICDx8+xNKlSwH8T2SFz+dDR0cHjo6OKu8PCQmBhYUFHBwcqn1PcnIyrl+/jhUrVjSoGiESiXDp0iVYWFio2OYQBIGhQ4fip59+Qv/+/cHlcqFQKHD16lXExMRg0aJFtdqDUB6Wjx8/xpgxYwBUKlU/fPgQHh4edc4bZmZmyMzMRHZ2dr1/S3NBJBJBJBKBxWI1KBAWiUQICgpCYGCgCjX+6tWr79S2QFHzb9++jdDQUPj4+GDVqlUq1PvaPhsREYFx48aBIAjExcXB2dkZUqkUly5dQmhoKEaPHg0fH5969Ttqampi+vTpOHnyJPbu3YuvvvpKLWWcUlZeunQptm3bBrlcjqFDhzZacpkkSdy9exfGxsa0EjYFpVKJkydPYtSoUfWeI+Li4mBlZUX36r948QKdOnWCSCSi/ZafPn2q4h9MISsrq0bV96aEgYEB2Gw2ioqK0K1bN4SGhsLNza3Rjs9ms2FiYgKRSISysjIV5o65uTmUSiWKiorg6upKayi0NAoKCsDhcJCbmwsHB4dGed4oEdOqLQcKhQJlZWXNZsGoVCpx5coVuLm5wdHR8T+zH3sbaWlpKuuhVCoFQRAqFqHqtI7+S/ZRDUXrieZaASi5e0q04e0Mnrm5OQQCAS3U1JpABcOTJ0/G9u3bVRSVmwLU5uDEiRNYuHAhBg8eDE1NzWafXAiCgIGBARYsWIBt27ahoKAAAQEBWLZsGdavX48ff/xRRRTgfUCSJEiShEwmQ1paGq5du4bNmzdj7dq1uHjxIrhcLj7//HP8+OOPmDdvHnr06AFDQ8P/XO8Fg8GAk5MTxGIxcnJyWq3IwqtXr9C2bVvIZDIUFBTUuPgRBAE3Nzfk5+ejoKCApqvevHmz1f42oFIoLjc3FwYGBiguLq7xfQRBwNfXF1FRURCLxeByuXB0dMSLFy+aZI4gSRJ5eXl05fS7776rMwhOTEzEqVOnsGDBgmobb5IkERISAicnJ3osJycnw8rKCjKZDEKhUEU9WCQS4fr16xgzZky1qjKfz8f+/fsxc+bMeluhURvUXbt2wczMDFu2bMGjR49UEqWGhobo0qUL7t69S/cEv3z5EoGBgXWqvRMEgT59+iAiIgJisZh2BsjMzFRRmq3ps5SlWWsS26FAVexFIlG9N7xUNdjZ2RkWFhb063l5eUhLS6MrjvU9VklJCU6fPo3169dDLpfjhx9+wLhx42pUcH4bfD4fZWVlsLGxoVXoSZLE2rVrIRQKsXr1anTv3r1Boj8aGhqYMmUKzMzMsHPnTlqc820QBAF9fX0sW7YMkZGRuHr1aqNQGEmSRHZ2Nu7evYvJkyerXAeqAi6TydC1a9d6XSOFQoF79+5h4MCBACorgKGhoejVqxeSk5Nha2sLNpuNpKQktG/fvtox8/LyGoWC21AwmUx4eHjQYpxJSUm0DWRjgCqgUOO46nimhLOKiopUVKRbGmlpabC1tUVCQoLae/UuKCoqgoaGhkr1l9JMeduqqylACTC+evUKo0aN+k/tx6pCoVAgKytLpSIskUjAZrNV2kveDoQpNuN/9brUhY+BcBUQBEH3bOro6NBUNQosFgu6urp1bk5aChTV54svvsDOnTvp3sHGBjWpXL58GUuXLm0VggMMBgM9evTAhAkTcODAAdqf73280ajJQSQSISkpCdeuXcMvv/yC77//HseOHYNQKMSYMWOwdu1aLF++HEOHDqVptq1V8bkxQBAEHB0dUVBQAKlU2qgbh8YClajp2rUrUlJSYGtrWysVSlNTE3379sWtW7cAVFoNZWRkoLCwsLlOucGglOytra3rpPQZGBjA1NSUft+gQYPw4MGDRu0LIkkSUqkUt2/fxi+//IKBAwdixowZtQaClLLzgQMHMHfuXJibm1d7r1AoxK1btzBq1Ch6MY+JiaH9tEtLS1XElCIjI2Fvb1+tH1wmk2H//v0YOHBgvZVQSZJEWVkZtm3bBicnJ4wfPx5mZmbw9fXFzZs36fmVqgqHhITg+PHjiI+PR2BgYLU+0ZpgZGREez6TJAktLS20bdsWsbGxdc7hlpaWKC8vrzGYaknweDxoaGhAoVBUEzOrCSKRCHfv3lXZsFI2WAMGDKhXNZgSiDl58iQ2bdoEJpOJ1atXY8KECfUOgKnjUD64mpqaSEpKQlBQEPLy8jBv3jxMmzatRkp1XWCxWJgwYQIcHBywY8cOCASCGoNhPT09LF68GDExMbh06dJ7j1uZTIY///wTY8eOrXY9RCIRzpw5g8mTJ9e7D7uoqAg8Ho8eV0VFRZBIJLC2tsaLFy/QuXNnVFRUgM/nVxuXVLKiuSqDVUEQBLy8vPDixQtwuVxwOBxkZmY26vHt7e2RnZ0NLpcLHo9H/43D4YDBYKCsrIxmWbWGQDg2Nhaurq6NqodDsbPMzMxUKsJ8Pr9ZvKOlUin+/PNPTJo0qd5z8r8REokE5eXlKsWfoqIiFZFakiQhl8ur7Yf+q9ekPvhIjX4LVJaEyWRW8+ckCAIODg548+ZNi9B46gOCINCpUyd8+eWX2Lt3L7788ksVtbjGgEwmw6lTpzB9+nSYmJjU2Fd19epVpKamok+fPujcuTOCgoKQnp4OBoMBPp9Pq9qZm5ujvLwcOTk5MDMzQ/v27dGpUycoFAqcOXOGXiRdXFzg6elZY28DJR6Wn5+Py5cvY+LEiQ363dRGXiQSISsrC3FxcUhMTKSzlm3btsUnn3wCc3NzcLncVkWPb244ODjQglnZ2dmtjkIsFApRWFgIBwcHnDx5Et7e3rXeL4Ig0KNHD2zYsIH2s+zZsyfu3buHCRMmtMpFQltbGzo6OtDX169VMAuoTBT169cP9+/fR8eOHeHo6AiJRIKsrKxGEc1SKpVIS0vDiRMnYGBggO+++67OTD+1Ad6zZw/Gjh2rdp6iAiAPDw862JXL5cjMzESHDh2gq6sLHo9HV1eoQHzWrFnVjnP9+nXo6Ohg0KBB9Q6CCwsLsXPnTvTq1Qt+fn40fWzIkCHYsGEDBgwYQFtXcTgcMJlMPHnyBNu3b28Q7ZzBYGDgwIG4desWOnfuDAaDgd69e+Pq1avw9fWtlbZmZGREC9FQwjutBampqXSgWJ+ePJIk8ejRI7Rr107FEqy4uBixsbEYO3ZsrfeO6km+efMmXr16hV69etWbAl0TQkJCMHDgQBw9ehS3bt2Cj48PVqxY0Si2K0wmE2PGjMGVK1ewc+dOzJ8/v8bAWk9PDwsWLMDu3btx7tw5jBkz5p3ojCRZ6dGtr68Pb2/vatXga9euoUOHDvWeFyjGho+PD9hsNm255O3tDSaTiTdv3mDEiBEoKCigqchVIZfLIRAIWiQQBir3H2KxGGVlZbR4lpOTU6PN+dbW1rhx4wYsLCxQWFgIJycnAP8LhMvLy8FisaCpqdnigTBVURwwYECDkld1gUoAVGXhKBQKlJSUNPl8RZIkbty4ATs7u2oCjP81VFRUgMViqYwxim1RtRJPkmS1/dCHvJ/9cH95DaAmJyaTCT6fr5KhpZRDk5OTW13mvSoIgkD79u3x5Zdf4sCBA3SVobHw4sULmJmZ1blYdO3aFfn5+fSGxsHBAW5ubujduzf++usvDBkyBN27d0dmZiY6d+6MEydOYODAgYiMjMTZs2ehra0NZ2dnXLhwAQEBAQgNDcXt27fr/O19+/ZFYmIiSkpKan0vNREnJSXh+vXr2LVrF9atW4dffvkF9+7dg6GhIaZPn441a9Zg2bJl+PTTT9GuXTsYGBh80JMGALqFwNzcvMlp+O+CN2/ewMLCAmw2GykpKTXaC1WFvr4+7SMMAH369MGzZ89ahYBJTbC0tISmpiZycnJqFfei5oTs7Gy6AtG/f//3Fs2igsVDhw7hwIED8Pf3x1dffVWvIJjP52PHjh0YMGBAjRTM/Px8hISEwN/fn/57ZmYmrQNgYGAAHR0dOiCIjY2Fvr5+NY2E5ORkPHnyBNOmTasXhZUSC/r1118xbNgwDBkyRCXo0NXVxYABA3D16lUolUrI5XKcPn2aVvN+l2vatm1bFBcX0zR3R0dHWnCoNmhoaIDJZEJbW7vOOa+5kZ2dDTabrbbSrw5CoRD37t2Dv7+/SgXj9u3b6NmzZ4093UqlEhkZGdi/fz+2bt0KU1NTrFmzBqNGjWpQBfht5OXlISQkBCdPnoSxsTF69uyJYcOGNar3KZPJREBAALp06YJt27ahtLS0xudHT08P8+bNQ3p6Ok6dOtVgQT+SJJGRkYH79+9j0qRJ1X5HZmYmIiMjMXr06HofUyKRICIiAr169QJBEJDL5YiMjES3bt1oRo2pqSni4uLQvn37amsnVQlvqQSOpqYmXFxc8PLlS3Tp0gWxsbGNqi3C4XAgEolgZ2eHtLQ0ldd1dHRQUlICJpMJFotVIyuguUApVwuFQtru6n1BkiSKiorAZDJVkh1Uj3BTt45lZWXh8ePHGDt27H++DzYzMxNWVlYq47qwsFBFTJJ6vt5uG/qoGv0RNDgcDp1NqaioqDYhOjo6IjMzs9U/NARR6fc6d+5cHDp0CNHR0Y02wYaGhsLX17fOCpu5uTn69++PGzdu0IbqHTp0gLGxMRQKBRITE3HixAnMmjWL7qXV19eHpqYmKioqwGAwYGhoiIqKCiQnJ0MsFkNLS6vO36GlpQVHR0eaVkhRQQoLCxEXF4ebN29i9+7dWL16NTZv3oyzZ8+ioqICvXv3xrfffov169dj/vz58PPzg52dHZ0c+S9nEhsKDQ0NcLlcGBsbtzoldaqPr2vXrsjJyYGenl69NlkEQWDw4MF4+PAhpFIpDA0N4erqirCwsFYX6FNwcXFBdnY2ZDJZnRR1HR0ddOrUCeHh4QAqE1Xx8fHV1PHrAjWmiouLceLECWzevBk2NjZYvXo1PD0969zYkCQJgUCAbdu2oUePHjVawygUCvz1118ICAhQ8UQMDQ2Fl5cXcnJyoKmpSQfdcrkcQUFBKkEUULnRPnz4MD7//PN6PQdU68f27dsxceJE9OzZU63aOJVwy8zMxF9//YWioiIsXboUnp6eePz4cYOfGS0tLXTp0gVPnjwBSZLQ1NSEm5sbnj17Vuux2Gw23c5TlXrZ0lAoFMjPz4dYLK4mZqYOlHiTm5sbTZekEibPnz9H//79q1UvlUolkpOTsWPHDuzZswft2rXDunXrMGzYsHdWo6V0IB49eoTAwEC4u7tj7dq1GDx4MLKzs+Hm5tboawEl2NezZ09s2bKlVk9ZXV1dzJs3D/n5+Thx4gRkMlm9nzWJRIIDBw5g0qRJ1SqwMpkMJ0+exJgxY+pt60eSlZ6zRkZGNCsjMzMTWlpadCsGpc3w+vVrtRU5gUBQZx99U4IgCPj4+CAsLIymlDZmS4yOjg4YDEY13RmKzcPj8aBUKqGhoaGiO9ASKCgogJGREZKTkxuNSUiSJPLz86GhoaHyzCmVSgiFwkZNKr0NqVSKo0ePYty4cY1W3W6toNatqgKRJEmioKBAhX5O6Z68fW//S4KuDcXHQPgt6Onp0eIelLpaVVCBmVgsbqEzrD+oXs5Fixbhr7/+arQNfXFxcb2sDgiCQLdu3ZCRkYHs7GyIxWIVDzmpVAqFQkFPhCUlJdi4cSOEQiEmTZpEH4ckK/14nZ2dkZ+fX6eAEUEQsLKywp07d3DkyBFs3LgRK1euxLZt23D9+nWUl5fD19cX8+fPx+bNm7FixQqMHj0anTt3pqlbH3rFty4wGAy0adMGIpEIubm5LX06KpBKpUhOTkbHjh0RGRmJzp071zsTbGlpCQsLC0RFRdGB8Z07d1qllRJBELCzs0N+fj709fXr3LwRBIHevXvj8ePHUCqV0NXVRYcOHRAREVGveYEKPHJycnDkyBFs3rwZurq6WLduHYYOHQptbe16KfDy+Xxs3boV3bp1g5+fn9qxRvV4i8ViutIEVNIoX716BQ8PD+Tk5EChUNALf35+PkQikQpTRalU4uzZs3B3d68XLY4kScTGxmLXrl2YPXs2OnfuXONntLS04OfnhyVLlqC8vBxfffUVdHR04Ofnh4cPHzZ4jSAIAr169UJoaCgtXNK9e3eEhobWOuex2Wzo6+vTyYnWArFYDIFAAIlEota/+22Ul5cjODi4ml3P7du30a1bN9reh0psxsTE4KeffsLRo0fRo0cPrF+/Hv369avXc6gOVFXk5cuXWL9+PUJDQ2FkZIQvv/wSxsbGyMnJAZfLbTKldQaDgcGDB8PPzw+//PILCgsLaxyX2tra+Prrr1FaWopjx45BLpfXOYapsdC2bdtqauRU8pDJZMLLy6tBPdS3bt2ixzFFbe/evTuYTCaeP3+OLl26QCaTobCwUO1zUN/9RFPC3t4eRUVFEIvF6Ny5M6Kiohot+clms2FkZAS5XI7i4mKVQMTAwAB8Pp+mIb/djtfceP36NVxdXZGYmIh27do1yjGpxCfl4EBBKpU2qW8ySZJ48OABuFxutRaA/yJIkkRKSorK+qdQKFBUVKQiREclst9ed1uzMGhT4+Nu/y1QtLby8nLaU7gq2Gw2dHV1Wx0FrSZQqoVLly7FxYsX8fDhw/d+4JlMZr0r4rq6uujWrRsOHDhAL4KUGEzv3r2xePFi5OXl0RW4b7/9FlwuF0lJSfRCxOVy0bt3b/Tq1Qvnzp2DVCqt83ulUikqKirg4uKCKVOm4Pvvv8fGjRuxdOlSjB07Fl5eXrCwsKCzYP/1SbKxQRAEnJ2dwePxIBaLW7y3qSqo7LO+vj7tI1zf+0sQlT7CN2/ehFwuh7W1NfT09BAXF9fEZ/1usLKyQklJCSwsLOrl6WxjYwMGg4HMzEwQBIEBAwbgwYMHtQb6lGpyZGQkfvnlF+zZswfW1tY09bS+lTeKRv3rr7+ie/fuGDZsWI0Jp+LiYpw5cwaff/65ShIjOTkZurq6MDQ0hFgsRmlpKa0YfffuXfTu3Ztm9JBkpVVSUlJSvZRClUolwsPDceTIESxYsKBWQS0qkff69Wvw+Xz4+/vTPbAmJiZo27YtXdltCMzNzaGnp4ekpCQAlfe3oqKi1vWGwWDA2NgYmpqarcpCSSwW03oQdQniUD3c3bp1o4Miah0OCwvDgAED6GOGhYVhw4YNuHLlCoYPH441a9agW7du72zdRwXACQkJ2Lx5M65cuYJJkyZh4sSJ0NfXh729PR0o1qU18L6gmAYBAQHYunUr8vLyanyGtLS0MGfOHIjFYhw9erTWyjBJknjx4gXi4+Mxbtw4tWrqFy5cUEuXrglUpY/P58PFxQUEQUAqlSI2NpYWx6L0I3JycqCvr6+W2p6RkdFookzvCg6HA2trayQmJsLb2xtRUVGNxvqj2HEymQwVFRUqxRUOhwOZTAaZTEYHxS0FpVKJlJQU2NnZobS0tNFErCiVYoVCocLIoZhI6qzDGuM78/PzERQUhClTpnwQhQ2FQgEej1et+iuRSFR0daj9/9tzQGtlvTUH/vtPRwOhp6cHuVxOG06/XRFmMBhwcHBASkpKC53hu8Hc3BzLli3D/fv3ERQU9F6TvK2tbb2VFakqh6mpKezs7KBQKHDp0iWQJImjR4/i7NmzOHXqFC5evAiFQoHbt29j1KhRuHXrFv755x9cvHgRYrEYBw4coEVw6sogkiSJ1NRUTJo0Cb169YKDgwMMDAz+8/0hzQ17e3sUFhaCy+VWsxprKVAbPg8PD/B4PCgUigYv6G3btoVSqcSbN2/AZDIxfPhwuhe0tUFLSwtsNhtmZmZ48+ZNne9nsVjo2bMnHjx4AJIkYWVlBW1tbaSkpKgshFQWPzY2FocOHcL69esRHh6OgIAArF69GkOGDGkQ9ZQkSWRmZmLbtm0YOnQoBg8eXOPmRCaT4dixYxg6dCisra1Vqrt37tzBoEGD6Hm5tLQUVlZWEIlEiI2NVek1lslkOHHiBCZMmFCjwB4FhUKB+/fv49KlS1i6dCnatGlT628Ti8XYt28ftLS0sHLlSly7dk2l92rYsGG4e/dugxXVmUwm+vXrR98fTU1NdOzYsU56NKXDUFRU1KDva0pQlikKhaJOIaTi4mJERkZiyJAh1arB3t7eYLFYuHPnDtauXYuwsDBMmTIF3377LTp37kxTw98FCoWCpsGfOnUKAQEBWL58Odq3b49nz57Rgk8ymYwO8Jo6aUoQBHr27InRo0djx44dyMrKqjUYnjlzJhQKBQ4dOqQ2SUwloE6ePInZs2dXCzxIksTp06fRu3fvelXuq+Lu3bvo2bMnvSa/fv0a5ubmMDY2Rn5+PnR1dcHhcBAbG4v27durXYPz8vJgYWHRosloir0WGhoKCwsLCIXCRqUpt2nTBjk5OdDQ0FBJGnM4HMjlckilUhgbG7eoNadEIkFhYSE0NTXB4XAarWdbKpXSKsVV739ZWRkYDEatHuvvCoVCgZMnTyIgIKDF2QbNBcoppepaRzFFqgoVSqVSte1LTUlRb+34cH95DWCz2WCxWKioqICtrS14PJ6KeiJVCYuJiUHfvn3/NZVEgiBgZGSExYsX4/fff4dIJMLIkSPf6eHv27cvzp49S6tE1gUul4uvvvqKngTHjRuHsWPH0n9nsVhQKBSYPn06mEwmdHR0sGjRIsjlcigUCsyfPx9A5b3R1NSsM7tXXFyMwsLCRqP2fIR66OnpQSKRwNbWFhkZGbQaZkuCojZOnjwZr169Qrt27Rqs7koFMjdu3ICzszM6dOiAU6dOISMjo1EUlhsTDAYDZmZm0NTURGZmJpRKZZ0Jn65du+L27dsQiUTgcDi0WrGzszMKCwuRlJSEFy9eICcnB+bm5ujWrRvGjx9P98o3FFRy4vjx45g6dWqtwQRJkrh//z5IkkS/fv1U3ldcXIzMzEx8+eWXSElJAZfLBZ/Ph6GhISIjI+Hs7Ez3gZEkieDgYJiZmdVJiZbL5bh8+TJiYmKwdOlSGBoa1vp+gUCA3bt3w9bWFmPHjqU9VKs+H5aWlrC3t0dYWBj69u3boOvl7u6OCxcuQCAQQE9PD76+vvjrr7/g5+dX42esrKwaVQeiMZCeng59fX1afLImKJVKXLlyBX379qXpz0BlxejmzZvw8vLChg0b0L59eyxYsADm5ubvndRUKpVIT0/HxYsXUVRUhFGjRqkE1VKpFBEREfj6669BEAQKCwvBYrGabVNN9a2y2Wzs3LkT8+bNq3Hu0dLSwowZM3Ds2DH88ccf1YJdqVSKgwcPYuTIkWqtDmNjY5GVlYXp06c3aD8jEokQHR2NlStXgiAIusebqt5TCUmCIPDq1St89tln1Y5BqXy3hIfw23B1dcWFCxdAkiTatWuHV69eoU+fPo2yx7OyssLjx4+hq6uL8vJyOjlrYmJCV4oNDQ0b1bqpoSgrKwObzUZubm6dicCGoKSkhA6Cq45bgUAAFoulMuYbAyRJIiwsDHK5HD169PjX7NHfFxkZGbCwsFAJenk8HnR1dVX2QBUVFdDS0qq2lsvl8g/mWr2NjxXht8BiscBisSCRSGBmZoa8vLxq73FwcEB6enqrF8x6GwRBgMvlIjAwECkpKTh+/DikUmmDN09t2rSBgYEBHj16VK/PEgSh4q2rp6cHLpdL/9PR0aFfo0QzqKxk1fdpa2vXuhGnesfOnDmDgQMHNgnl5iP+Bx0dHRgaGkJXVxcJCQktfToAKhfXsrIyWFlZ0T7CDZ3cCYKAp6cnsrKyUFBQABaLhcGDByMoKKhVBRoUnJyckJeXp1bc722QJEnTPSMiIpCWlgYej4crV65g5cqV2LdvH9LT09GvXz+sWbMGCxcuRPfu3aGnp9fgIJgaj9evX8fff/+NwMDAOoNgyqf1iy++UEnSUZvs7t270xRgQ0NDeoMVHByssmkViUS4efNmnRYzUqkUx48fx5s3b7B48eJag2CSrPQU3r59O5ydnTF+/Hg6OTdixAicP39epf/P398fQUFBDa4K6+rqwsHBAa9evQJQycCpqKiotQfczMwMFRUVEIlEraKfnSRJZGdng8Vi1RrkkGSlj/Tr168xcOBAAP+z4vr5559RUFAAU1NTfPfdd5gxYwYsLS3fOQim6H/p6enYuXMn9u/fj27dumHNmjXo2rWrCrU6KyuLZlqQJIlnz57B3d29Wasm1Dw0ffp07Ny5s1a3Cg0NDUyfPh16enrYu3cvKioq6J7+c+fOwdTUVG1QIBQKcfz4cUyfPr1B6yV1TZycnOhqf3FxMfLz89GhQwcoFArExsbCw8MDEokEPB5P7XMgkUhQVlamYpXVUtDX1weXy0VmZiZ8fHwQHh7eaPO9gYEBysrKYG1tjaysLPp1U1NTuo9TX1+/RVvuUlJS4ODggPj4eHTs2LHRjltSUgIWi0Xby1EoKyurVsFsDPD5fJw/fx5Tpkz5YKqcJEkiLS2tWgKDcm2punaLRCK1gfCHGgQDHwPhaqACYZIkweFw1KpwUpWwxpTYby5Q6qILFiyARCJRWTQbcozx48fj/v37eP78eaugjFJ9XmfOnKFFZj7kgd0coMSa5HI5cnNzW/w5IEkS8fHxcHJyglgsRlFR0TtXcDU1NdG7d2/cvXsXAODr64ukpKRWpw1AEJXe5gUFBdDT01NJ3FFjQiaToaSkBLGxsbh9+zYOHDiApKQkrFmzBn///Tfd4+ru7o41a9ZgypQpcHNzoxNP79p3WVZWht27dyMuLg6rVq2qZmn0Nvh8Pv744w/MnDmzWkBaVlaGyMhI9O/fH0Bl9ltTUxOmpqYoKiqCUCiklYmpoLljx441BmEkSUIkEmHPnj2QSCSYP39+rcq1JFnpebx161Z4enri008/pTd1BEHAy8sLJSUlKvR0GxsbGBkZ4dWrVw3eUPfv3x/BwcFQKBRgs9no1KkToqKianw/Va2nKO0tDaVSiezsbBUxs5red+HCBfj7+4PNZuPVq1f46aefsG3bNsTExODgwYMYPXo0/Ty865yuVCqRmZmJ3377Dfv27YO3tzfWrVuH7t27V+stJkkSDx8+RK9evcBkMqFUKmmadHOvKQRBoFOnTpgzZw727NmDhISEGp8lNpuNqVOnwsTEBHv27EFFRQXCwsKQkJCAyZMnV0sgKJVKXLp0CW5ubg1m8ygUCty9exd+fn50NTgsLAyenp40/be8vBwWFhbIyMiAsbGxWqqtRCIBg8FoFE/mxgDlI2xvb4+CgoJGE0XV19eHQqEAl8ul+/gJgqAZLDweD1wuF8XFxS2SbCVJEomJiXB0dERWVlaj9WxT86ZSqYShoaHKM8jn86FUKhs1EFYqlThx4gT69+8PS0vLD2oPmJSUhLZt29L/TylGV7VOAv5XEa4KkiQ/6NbBj4HwW6ACYQaDAW1tbbU2BlpaWjAyMmpVwiQNAVVxnTlzJszNzbFz506UlZXVewKmKsvffPMNzp07h6CgoBZNClCbvwMHDqCoqAjTp0//YDKBLY327duDx+NBJBI12IansUGSJCIjI+Ht7Y03b97AxsbmnRdZSmH5+fPnEAgE0NbWRteuXREcHNyqqsIkScLa2hr5+fkwMDBAdHQ0oqKicP36dRw8eBC//PILNm7ciN9//x2PHj2CRCJB9+7dsXTpUvTs2RNTpkzBhAkTMHnyZMTExEAqlb63eJxSqURcXBx+/PFHODk5YeHCheByubUeUyQSYe/evfDz80P79u2rBSZ3795Fly5daHVkSjHaxsYGoaGh8Pb2pjfTZWVlCA4OxsiRI9V+J0mSKC0txdatW2FpaYmZM2dCU1Oz1iC4sLAQ27ZtQ+/evTF8+PBq2XQWi4VRo0bh0qVLKkyhgIAAWnitvqDab0pLS8Hj8ej+xYiIiBqTTdra2rQCa2sIhOVyOQQCAUQiEaysrGq8D6mpqUhLS4NYLMbatWtx48YN+Pv7w9fXF5MmTYKJicl7PYtUD/DOnTuxb98+eHp6Ys2aNejdu3eN4lpisRhxcXHo0qULCIJAUVERZDIZLCws3vk83gcEQaBdu3b46quvcPDgQdoWUB1YLBYmTpwIS0tLrFu3DqdOncLcuXOho6NTbUwlJibi1atXGD16dIOvcXJyMphMJh0wyWQyhIaG0qyMpKQk2NvbQ0NDAzExMTW2JwiFwjqZXs0FgiDQuXNnxMXFgc1mw9bWFvHx8Y0y37PZbHC5XLDZbOTn59PHpHQWysrKoK+vj/Ly8hZhdCgUCqSlpdEVasoKqzFQVFREW2FSzwAl0KZUKhtNNZpqwSksLMTgwYM/qCCYJCu9mquqcgNAbm5utb5/yob07evTGphELYWWn31aGdhsNphMJh0IU9msqqAEs+qj0tqawWazMXbsWHTu3Bm//vprrXYNb4NSQly2bBni4+Oxbds2ZGRkNHtVUC6XIyoqCvPmzcOhQ4fAYDAQHh5OUz4lEsm/+h61dlhaWqKwsBC6urotbv0gk8mQmZkJJycnhIWFwcfH572OZ2BggI4dO+Lp06cAKqt0ISEh1QT0mguUjVhxcTFSU1Px6NEjnD59GgcOHEBISAgiIiLw559/4uXLl2CxWOjevTtmzpyJZcuW4bvvvsOcOXMQEBAANzc3WFtbq4gymZqawtzcHDExMe91fnw+H3/++SdOnjyJWbNmqagp1wSJRIKjR4/C1tYWgwYNqrZAl5SUICQkBMOGDaOrTwKBgFYjfvbsGXr06EGfw+PHj+Hh4aG2n5MkSeTl5WHLli3o1q0bPvvss1qrURTFd+vWrRgyZAgGDBigdtNOEAQ8PDzA5/ORmppKv+bk5AQGg4Hk5OQ6r19VsNlsuLu70yJZbdq0QXl5eY0+wdra2tDQ0KCVllsalDUKn8+nVb2rgtq47dixAxkZGUhPT8ecOXOwdOlS2NnZISoqqppwVkNA+dRv374dR44cga+vL1avXo0+ffrUSgEmSRIxMTGwtbWlky4RERFwd3ev8zluSlDJkW+++QZHjx6ttR+cxWJh4MCBiI+Pp10u3oZIJMLx48cxbdo0tUrOtUGhUODGjRsYOnQoPRYohoaFhQUdkHh6egKo7EGuiWqbk5MDS0vLVhEIA6ATL0VFRfDx8UFoaGijHdvU1BRMJhPFxcV00PF2ICyRSFrEmlMqlUIkEqGiogJmZmaNej9ycnKgra1dTTCvpKSE3mc3BsrLy3Hq1Cl8/vnnTWbJ1FpBFbLe9krOy8uDpaWlymtUIFwVVEX4Q0oeVMXHstlbYLFY0NDQgFgshoaGBkQiEWQyWTXaQPv27fHw4UMMHjy4hc60ccBkMmkF2C1btuDrr7+ut1ACQRAwNDTEvHnzEBERgV27dsHR0RHDhg2Dra1tky5ulHXJ1atXQZIkZs+ejRUrViAwMBBMJhPa2tqws7NDmzZtsG7dOnh4eDTZuXzIMDY2hlQqhZWVFVJTU1vUBiMzMxOGhoZgs9lITU3FxIkT32tiJ4hKH+Fdu3ahf//+MDY2hp2dHZ4/f46ePXs26aJBkiRkMhmKioqQm5uLpKQkZGdn08Ijenp6sLW1hZ2dHXx9fSGXy+Hu7o7w8HBMmzatznOjqow//vgjRCIRdHR0MHToUFy6dAmdO3duMKNCLpcjIiIC58+fR7du3bBq1Sq1Wee3QQXBTCYT48ePrzZnkCSJixcvom/fvjAwMAAAWs2Vz+eDwWBAQ0OD7jGsqKjAo0ePsHjx4mrfRVUg9+zZg7Fjx6Jr1651ag6kpKRgz549mDJlCjw9PWv9PSwWCwEBAbhy5QoWLFhAJ1SHDx+O69evw8XFpd70M0o5+MiRIxg4cCBYLBZcXFwQFxeHPn36VHs/k8kEl8uFUChEQUEBXF1d6/U9TYW8vDzo6OioeMcDlWyBjIwM3Lx5E3fu3IGZmRn27t0LIyMjmtodFBQEX1/fapu6+kAulyMhIQGXL19GRUUFAgIC4OHh0SBl6Xv37tHWXpSl1owZM1p8k0gQBNq0aYOFCxdix44dkMlkaunaIpEIhw4dwrx581BWVoadO3diwYIFKj7MFy5cQIcOHWq1CKsJeXl5KCgooIWwSLLSr7Vv375gMBiQy+VITk7Gp59+Sms2qEuGAJVBUkOVqpsSDAYDHh4eiIqKQs+ePWm7xsYIrBwdHZGXlweZTAaJREJXiamCC+V/XVFR0egCUnUhOzsbxsbGePPmTaP2BwOVyv5vV5mVSiXdO9wY7D2qxaJr164tbsXVEsjJyYGpqalKUpeyPXxblbuioqJa8kGhULSaZFRL4GMg/BYYDAY0NTUhkUhomqBUKq2WQbGwsKA9/lp6gXxfMBgM9OzZEwYGBvjtt98wbdq0BtlEsFgs+Pr6onPnznj69Cn2798PTU1N9OzZk67MUMd6135DoHKwZmdnIzw8HI8ePYKlpSVGjhwJV1dXMJlMHD58GOPHj0dUVBTEYjFKSkogEAjeaUP1EfWDhoYGjIyMoKuri5SUlBZTUidJEs+fP4eHhwfy8/Mbzf7B2toaRkZGePnyJbp06YKhQ4fi2LFj8PX1bTT6PfV8S6VSZGRkIDExEfHx8SguLoa2tjYsLS3h4uICHx8fWFhYqASY1Ea0bdu2EIlEEAqF9d646enpwcHBAS9fvoSvry9cXFwgEomQlZVVr95qSnwoJSUFp06dApvNxoIFC2BjY0OfW22QSCQ4fPgwGAwGLY719mdSU1MRHx+P8ePH03/Lz88Hl8tFeXk5YmNj0a1bN/o6PHv2DPb29tUotSRJ4uXLlzh69ChmzZpVp5I0SZK0ddScOXPqFTBQVeErV67QCtIEQaBDhw44f/48srOz1ar21gRLS0vI5XIUFRXBwsICvr6+uHHjBnr16qVW6MTQ0BBKpRI5OTn1On5TgaqiUwJBTCYTUqkUMTExuHnzJoRCIfr06QM7OzvMnTsXxsbG9P0rLS1FREQEfvjhh3pfJ0qU7dWrV7h8+TIIgsCoUaPQqVOnBlc5ioqKwOPx6F67/Px8yGQy+pluaRAEARsbGyxduhRbt26FTCaj9TAoTYBjx47Bzs4OAwYMoIUqt2/fjkWLFoHL5SI2NhZxcXH4/vvv30kALygoCAMGDKAr5AKBAImJifQYLSgogJaWFvT19ZGUlARTU1O18xHFzmiJ3uuaQBAEvL29ceLECQwdOhQGBgZIS0trFAcKS0tLREdHg81mQywWQ1dXFzo6OtDV1QWPx6MT+M3NOKJECilb0LFjxzbq/RAIBJDJZCo2hhRz5W3K/ruAovknJCTghx9+eN/T/VciNTUVDg4OKtdSLpdDJpNVC3rVVYSVSuXHQPgj/gdKTEoikYDP54PFYqn15jMwMIBcLkdZWRldqfg3gyAIdOzYEYsXL8auXbvA4/HQr1+/BlUwtLW10b9/f/Tp0wdpaWkIDQ3F/fv3wWAwYGdnBycnJ9jY2NB2L5QQz9sbVqVSSdMf8/LykJaWhtevX9NZU8oSx9bWFk5OTvRmx9nZGQcPHsSkSZOQkJAABoMBZ2dnyOXyD36gNxUosSaxWIzMzEwoFIoW6c8mSRKvXr3CnDlzEBISAi8vr0ZZzBkMBvz9/XH+/Hl07tyZ7ntLSUmBi4vLO38HtWnl8Xh4+fIloqOjUVRUBCMjI7Rr1w4BAQGwtLRUoTXW9F3Us//48WNwOBwUFBTA1ta2Xr9twIABOHPmDHx8fMBkMjFo0CDcvn0bM2fOrHG8UGM0NTUVFy5cAJ/Px5gxY+Du7l6v+YIa23v37oWZmRkmT56slp4slUpx7NgxTJw4USWrnZubCwMDA/B4PCQlJWHMmDEgCAIymQx3797FF198oXLuCoUCwcHBuH79OgIDA+sMRilxpNOnT2PhwoWwt7ev931ms9nw9/fH5cuXMX/+fBAEATabDT8/P1y7dg1z586t13GoY3l7eyM0NBSffPIJnJycUFBQgPLycrXJPSo5WxN9ujlB2cDo6urixo0bePToEUxNTTFy5Ei0a9cODx48gKOjI5ydnVWu7dWrV9G7d+96VcSoVoHnz5/j2rVr4HK5GD9+PFxcXN5Z5O3Ro0fw9vaGtrY2SJJEeHg4unTp0qo0JwiCgIWFBb799lts27YNMpkMvXv3BgCcP38eEokEM2bMoMdiQEAAHQzPmDEDR48exVdfffVO/q18Ph9xcXH47LPP6OA7PDwcrq6u0NXVBUmSiIqKQseOHcFkMmkLJXVQKBTIy8trVRVhoDJgLS8vR3l5OXx8fBAWFvZecz0FMzMzlJSUwNjYGAUFBXSyjsvlgsfj0eyWlqBGx8fHo1evXoiMjKyxev8uoKrfBEGorGVUIFyXdkR9IBaLaWu++rCQ/otISkqiVfcp8Hg8aGlpqQTCJElWY+kAlUHzR2r0R6hAW1sbUqkUxcXF4HK5KC0trdaErqGhATMzMzrz/V8AlW1evnw59uzZg6KiIowePVptpaa2Y7BYLDg7O8PJyYlWrE1PT0dycjIiIyPpvuuqgTBVySopKYGBgQF0dXURExODHj16QCQS4ezZszh06BC6d+8OFosFf39/XLhwAZs2bcL06dPh7OwMBoMBT09P7NmzB59//jlMTEywdOlSHDlyBHZ2dhg9evR7i698RHW4uLjg/v37EIlEdKa7uVFUVASlUgkjIyPExMRg7ty5jXaf27dvD4lEgrS0NDg5OWHIkCE01bUhoOjO+fn5CAsLo+1xOnTooBL4vst5W1lZIS8vD9bW1nTlsT5o06YNJBIJcnNzYW1tDW9vb1y/fh2lpaXVemypRTQ+Ph63bt2CWCzG8OHD4eHhUW/qIFUF2rNnD3x8fDBs2DC1QQZJkrh37x6MjIyqbaTfvHkDLS0tmpJvYGBA20ew2WyVjZxMJqM9gpcvX05XH2uCUqnEw4cPcevWLSxZsgQWFhYNuh9UVfjq1avIzMyEnZ0dCIJAly5dcPXqVRQXF9d5DlWP5ePjgz179iAgIAAaGhqwt7dHcnIyvLy8qr3f2toaISEhKCkpaVGmklwuR1xcHNLT0yGRSGBlZYWFCxfCwsICDAYDfD4ft27dwrJly1QSFoWFhXj58mWd1WAqkfL06VPcu3cPVlZWmDlzJuzt7d9L+VQikSA8PBwLFy6kf0dERESDkhfNBYIgYGpqiqVLl9I0ablcjsTERCxatEiln5nyRQeA2bNnY/r06bTCekNAqWl7e3vTc7xCocCDBw8wa9YsOjB+/vw5pkyZAoVCgYSEBPpvb0OhUKjdlLc0NDU14eLigtjYWLi7u+PevXuQyWTv3SNuZGQEmUwGAwMDZGdn06wULS0tlJaW0mOhuSvCSqUS+fn50NLSgo6OTqP2wlPFJIIgVNYIiv1Rm1J/fUCSJK5evYq2bdu+E83/vwCFQoGCgoJqYn7FxcV0y0lVCIXCaowvkiQ/6ELRx0BYDXR0dGgVXFNTUxQUFMDZ2VnlPVQVJjk5udF7KloSFMUuMDAQR48exb59+zBjxox3yh4TBAENDQ2Ym5vD3NwcXbt2BVC5OZXJZFAoFPS/lStXIioqCkKhEL169cKqVatw584dCIVCdOnSBQcOHMDs2bOxdetW+Pn5gcPhYNKkSXj9+jUOHz4MLy8vBAQEQEtLC/369cPevXtBEAQGDhyInj17Ijg4GD///DN69OgBPz+/FgnW/quwsbFBYWEhNDU1wefzW+TaxsbGwsXFBQKBAAqFolF9Kak++hs3buDrr7+Gm5sbzp49q1aIQh2USiWKiooQFhaGyMhIOsD56quvYGRk1KD+xZqgq6sLqVQKBwcHJCQkwNfXt16fY7PZ6NWrF+7du4epU6dCR0cHXl5eePToEa26rFAo6OA9PDwcpqamGDFiBFxcXBp07pQQ0bFjx/DZZ5/V2qObmZmJO3fu4Lvvvqt2/Ly8PJiYmCArKwujRo2ij3H79m0MGDAATCaTrhYeP34cQqEQS5YsqXPTpVAocO3aNURGRmLZsmUqLR0NgaamJoYOHYqLFy9iwYIFACqTq7169cLt27cxYcKEeh/L1NQULBYLubm5sLGxoe1dKEXjqjA0NASDwYBAIGi0vsb6gkqSxMTE4NatW3j06BFsbW2xcuVKFXYGSZK4fv06fHx8qlElL1y4gEGDBtUYGJEkCR6Ph/v37yMsLAwdOnTAggUL6GTF+46hhIQEGBgY0BvK7OxsMBiMVlexpEAQBIyNjREYGIhly5ZBIpHg999/Vzv/UmuxjY0NoqOjMWjQoAbPkWKxGE+ePMHSpUvpoDclJQVaWlp08qm0tBRCoRBWVlYoLS2FWCyuUW2b8tduLdZJFKj5+fbt23TiPS8vD3Z2du91XIr6rKuri9zcXDpZpaOjA5lMRvekN3cgTNGy8/Ly6IJCY6GsrIyme1cNsCmxPGtr6/f6vrS0NERERGDVqlUfbCBXWlpKFwGqorCwUO0YV9c3TD1/Hyo+3F9eC3R0dOgNhYmJCYqKitS+r23btkhKSvrPqRITBAEOh4PZs2fD3NwcP//8s4rk//scl1qQORwOuFwuDA0NwWKx8PjxYyQkJKCkpAQXL15EYmIiBg0ahOjoaOjo6MDa2hrx8fGYPn069u3bB7FYTPffrVq1Cnw+H5s2bUJqaioIgsDw4cMxdOhQAJWbUD8/P6xatQrl5eVYt24dHj9+DJlM9p+7dy0BY2NjeiKu6qPaXKCUXb29vREdHY0OHTo0KpWRIAh07doVaWlpKCoqoj2Gb926VePzQ1V/X716hZ07d2Lr1q2oqKjA7NmzsWrVKgwbNgwWFhY1Wrg0FFpaWrRPY1ZWVoPU37t27YpXr17RG7B+/frhyZMnyMjIwK1bt7B582bs2rULABAYGIhFixahU6dO9T53qofz+vXrOHHiBL7++mv4+PioXXipgIrq93/bT1ihUIDP54PP50Mmk9GCPXw+H+np6XBzcwNQ2Ze2Y8cOsNlsmgZa07lS9+r06dOIjY19ryAY+J+vcF5eHt2vS4lfPX/+HEKhsN7HYrFY6NKlC8LCwgAA7dq1Q2pqKh1EVAWXy6UTi81Br6R6xHk8Hq5cuYK1a9fi0aNHGDJkCLy8vGBtba0ivEixAZ49e4bhw4erHCs7OxspKSm0/c7b35GTk4MjR47gxx9/hFKpxMqVKzF9+nRYWVm9Mw26KpRKJW7fvg0/Pz/6e58+fQpfX99WX2XKzs6Gnp4ebGxs8OjRIxX7LqDyt6Snp+PWrVv46aefMHToUGzduhUFBQX1nidIkkRoaCjatGmjsrkOCgqixdyASoqto6MjNDU1kZycDAcHhxqr9AUFBbS4YWtDmzZtkJubC6lUCk9PT0RFRTXK/sfAwAA6Ojp0IAxUKlWLRCKaGt3cqu/p6emwtrZGampqo1DAq4LP54MkyWqVZolEQgfJ7wqpVIo///wTEyZMaHWsguZEfn4+TE1Nq62nGRkZ1ZI3JElCJBJVC4Q/dNXoj4GwGlDm5wKBAMbGxjWanFtZWaGwsPA/679F2SsNGTIEv/zyCxISEho9cKQW2LS0NAgEAuTn56OoqAg7d+6EhoYG+vfvj7t378Ld3R1AJQV26dKlWLJkCcrKyujekxkzZmD06NHYvXs3Ll++DJlMplIloBahadOmYeHChQgNDcWmTZuQmJjY7JZP/zVQHoFcLhepqanNnlwQCAQoLCxEmzZt8OzZM3Tt2rXRJ3QtLS10794dDx48AAD07t0bL1++pBWMKVCBXHBwMNasWYOrV6+iT58+WL9+PcaOHQtra+sGtRrUFwwGAzY2NpBKpSgtLW1QVcHAwABt2rTB06dPERsbi6CgILx8+RJr165FSUkJJk6ciPXr1+OTTz5psLUGSZK0cm1iYiJWrlxZqyo9VRm0sbFRW/WkNlYFBQWwt7eHoaEhSJJEWFgYPDw8wOFwUFhYiM2bN6Njx46YOnVqnR7BEokEBw8eRHFxMRYtWvTO9PSq0NTUxODBg3HlyhV6PBgYGKB9+/YICQlpUKLC29sbz58/h1KphK6uLgwNDZGVlVXtvVwul9ZDaMpAmOpvT0tLw759+/Djjz9CIBBg8eLFCAwMhJGREfT19atZoyiVSvzzzz8ICAhQSUwoFAqcP38eI0aMoEVcqO9ITk7Gjh07sHPnTlhaWtLjSB3l731QUFCAgoICdOrUCQRBQCwWIzo6mhZia40gSRJv3rzB0aNHsWTJEvzwww949eoVzp8/T+9JKOXY/fv3Y9q0aTA2Nkbfvn0xYsQIbN26td4JbqlUips3b2LEiBH09eDxeMjMzKTXZmocUrZ1VS2U1CE7O7tGj+mWhq6uLiwtLZGYmAgvLy+8ePGiWoLhXWBvbw+hUAg+n08fz9TUFBUVFZDJZOBwOM1uQ/j69Wu0bdsWGRkZcHJyatRj5+fng81m0/MBhfLyclRUVEBLS+udxjFJkrh9+zZMTEwaJOz6X0R8fDzat29f7fW8vDyYm5tXe10ikVRjC8nl8o8V4Y9QhaGhIWQyGSoqKmBiYlKjvy41uFuDOElTgSAI9OjRA1999RUOHTqEhw8fNsqCQIEkSdy4caPaxu3y5ct48uQJ+vbti/j4eJWeBoIgUFxcrCJixmAw0LlzZ/zwww/Izc3FTz/9hOzs7Gr3jeqDDgwMxOjRo3H8+HHs2rWLVgD/iHeDi4sLvTlu7sRCWloazMzMoFQqwePxGlXsgwJBEOjfvz/Cw8MhFArB5XLh5uaGp0+f0lUrkUiEW7duYfXq1YiNjcXs2bOxfPlyeHl51RqMNRZcXFyQlZUFTU3NGjdTVIBRUVGBgoIChIWF4cSJE0hKSsK6detw+/Zt2NjYYPXq1bC3t8fYsWPh5OT0TsG7UqlETEwMNm3ahA4dOmD+/PnQ19evNSh99uwZ4uLiMHHiRLWVJB6PBy6Xi+TkZAwYMAAsFgtKpRIhISHo2bMnUlJSsGXLFowYMQL+/v519owKBAL8/vvv0NHRwZw5c2gLk/cFQRDo3r073rx5g4KCAvq1YcOG4eHDh2oFGGuCubk5WCwWsrKywGQy4enpicjIyGrzlYaGBrS0tKBUKiEQCN77N7wN6hl/+vQpfvzxRxw9ehQdOnTA2rVrMWnSJJibm4MgCOTl5UFbWxtaWlr0hoskSbx+/RqlpaUqVVaKXltQUEDT+cViMcLDw7Fx40acPHkS3bt3x7p16zBs2LD37ims6XcFBwejR48edHXyzZs3MDQ0bLX6H5Qy9969ezF79mzY2tqCw+EgMDAQqampOHPmDN1+dPToUXh5edFBPsVO+OSTT7Bt2zaV6mRN3xUREQErKytae4AkK/26vby8aB9ikUiEnJwctG3bltZUqKlvkyRJZGVlwdraulUGMRQ9OiwsDFZWVqioqEBJScl7H9PCwgLFxcU0c4NK0FMJTH19ffD5/Eb6FXWDSqZYWFhAoVC8UwtcbajqIVz1PgsEApAk+U7zLUmSyM3Nxf379zF58uRW+fw0F6j75+joWI1Jw+fzq4kqUkKXb6+L1Gsf6rX82COsBtRiK5PJoKOjg7KyMrWqwwRBwNLSErm5uWozL/8VEAQBJycnLF++HPv27UNmZibGjRvXKD1opaWluH37drXXy8rKsH37dpw+fRpDhgzB0aNHoaenBwsLC3h6emLfvn3VNikEQUBfXx9ffvklnj17hh07dqBPnz7w8/OrJhfPZDLh7u4OFxcXhISEYOvWrfDy8sLw4cNpk/uPqB8IgoCjoyOSkpJoq4T3Ea1pCKhNmo+PD+Lj42Fvb09vzBobBgYGaNu2LcLDw9G/f38MHToUv//+O3x8fBAVFYVbt26hXbt2WLx4cYMrp40BKysrXLt2jZ6TLCwsIBaLUVFRgeLiYqSnpyMrKwu5ubkQi8XQ1NSEra0tnJ2dMWDAAFqUiVJav337Nt68eUNbydQXJEmioqICFy9exOvXrzF79mw4OTnVOaZycnJw8uRJup9XHfLy8sDhcGhFV4IgaIXivLw8nDlzBjNmzICrq2udgktFRUXYtWsXPD09MWLEiEZXBqb0Cm7duoWpU6fS64WJiQlevXoFb2/veh2HyWTCy8sLkZGRsLe3h5ubG/bu3at2Q8PlcsFgMJCbm9to1R2qR/zhw4eIiopCmzZtMH78eLRp06ZajzglWsZisWBhYUGfn1QqxenTpzFp0iQViqRcLse5c+cwevRoVFRU4O7duwgODoaFhQUmTJgAR0fHJqfOikQiPHv2DMuXLwdBEFAqlSq+uK0RBQUF+O233zB58mSVYJPD4WDevHnYv38/Tpw4AQMDA8hkMgQEBKj8FoIg4OvrCyaTiW3btmHhwoWwsbFRO2YkEglu3LiBL7/8kv67WCzG06dPERgYSL8vPT0dRkZG4HA4yM7Ohra2do3jmCRJZGZm1lvLoCXQvn17XL58GSRJwtXVFa9evUL//v3fa29gYWGBkpISsNlsCIVCaGlpwcDAgG75MDY2bpIkVk2gtHBEIhEsLS0bXVdAnYcwUBkIs9nsd0psyeVy/PXXXxg9ejQMDAw+6L2aWCxGYWFhNQq0SCSCVCpVm8hTKBTV1o2PFeGPqAYtLS06W0dVUGqqgrq6uuL169fNfIbND4IgYGJigsWLF0MikWD79u01UsbrC8ryJi0tjR6EBEGAyWTCzc0Ntra2EIvFtJ3GvHnzEBQUhL59++LJkyc1fjeTyUTXrl2xatUq5OTkYPPmzXjz5o3a92tpaaF///744YcfQJIkNm7ciCdPnkAmk73z7/oQ0aZNG1p0ozmpXVKpFElJSejYsSPCw8ObhBZNgcFgYMiQIbh79y7kcjlMTEwgl8uxbNkyJCYmIjAwEF988QWtjtscoOYnSqQmLS0NBQUF+OOPP/DTTz/hp59+wp49exAUFISKigp4eHhg1qxZWLFiBZYvX46pU6eiR48esLS0xJAhQ3Dnzh2QJAkWiwU/Pz/cvHmzQWOcqvD9+OOPkMvlWLFiRb2C4JKSEuzevRuTJk2qtaKfmpoKDQ0N2NrawtzcnK7miUQiXLx4EYGBgfUKgrOysrBlyxb0798fI0eObBJ7HIIg0KdPH8TExKiwhoYNG4agoKAGtdR06dIF0dHRUCgUMDExoXtz34axsTGYTCZdhX5XUBT/qKgobNu2Db///jv09PSwcuVKzJ07Fy4uLjX2iGdlZYEgCLraR90jCwsLlR5Ekqz0as7Pz0d0dDQ2bNiAwsJCLFiwAPPmzaNt8poS1Bpka2tLbxqpcdSxY8dWuckuLi7Gzp078emnn6qlhVLshuTkZOzduxdTpkxRqwRM6QNMnjwZ27dvR3p6utqx/uLFCxgbG6tstl+9egVzc3Na8IwkSURGRtK06JcvX9IWSupAtUyoswFrLTAyMoKuri7S09Ph4+ODyMjI92Y7mZmZQSAQQFdXF/n5+QBAs2TKyspgaGhYrd2mKZGXlwd9fX1kZmaibdu2jfq8U8rQIpGomuCcQCCAUqlssI8wSZIICQkBk8mkE6EfMsrKymgmUFWUlpZCW1tb7bhXZ3FJ9Qh/qPhYEVYDTU1NWnVTqVRCqVSqDYSpSlhERMQH41Oro6ODL774Avfv38fmzZsxe/bsd55AKbGrs2fP4uzZsxCJRBg2bBgtztOzZ0/6mk6cOBFRUVGwtbXFhAkTsGHDBnTp0qVG1V6qOjx79my8fPkSe/fuhY+PDwICAqrRVAmi0stvwoQJ6NOnD06ePIm7d+9i8uTJdFXlQ59w6wKHwwGDwYCRkRHS0tJommRTo7CwECwWC7q6ukhLS8OkSZOa9PtsbGygq6uLO3fu4OXLl5BIJDAxMcGsWbOapPcXAL05pWxjCgoKkJ+fj/T0dOTn59OUPT09PZSVlYHD4YDD4WDmzJm0gFbVRJM6UL2oV69eRUlJCYyMjNClSxdcuHABBQUFdTJeqMDp0qVLeP78OaZNm4YOHTrUOSdSPYy//fYb+vbtC29v71qp03l5eWCz2WjTpg00NDQgFApx8eJFdOzYEUuXLq3Tl5IkSSQmJuKPP/7AtGnTaLGtpgKHw4Gvry/u3btHe686OztDKpUiIyMDDg4O9fp+KysryOVy2iaDsnfp27evyudtbGyQnJxMJykbuskEKunnwcHBCA0NhYmJCYYMGQJXV9d6Pd8kSdIVL6qdhc/n4/r161ixYgWt6E2SJJKTk/Hzzz9DW1sbpqamWL16dbOzcSiRrHHjxtFB+/Pnz9GuXbtW5yxAkpXeq7///jsGDRpUo5AXxXYQCATo378/Tp48iTlz5qhtzyAIAp07dwaLxcLOnTuxYMEClR5+qVSKa9eu4YsvvqBfk8lkuHnzJsaPH08fRyqVIiEhAcOGDQNJknj58iX9vKuDVCqFXC5vdCpuY4LBYMDb2xuRkZEYNWoUioqKUFFR8V7PBXUP9PX1UVBQAFdXVxgYGNAWSgYGBkhKSmrEX1E7KFptYmIiJk6c2KjHFovFEIvF0NHRUalMUuuYVCpt0P2nkn+XL1/GsmXLPujAjUJ6ejpsbW2rrbPUs/Q2qMS5uopwVU2dDw3//cjtHaCpqUlTB6msVU19G9bW1nTW60MBk8nEwIEDMXv2bOzfvx937959575hU1NTDB8+HG3btoWjoyM+/fRTmJmZIT09ne5ZoGhcRUVFSE5OhqGhIT799FMcP3681sotQRBgMBjw8PDA6tWrUV5ejvXr1yMpKUltZpcgCFhZWWHJkiUYNWoUDh06hP3799O+nB9RM1gsFkxMTKCjo9NsytEkSeLFixfw8PBAWlpak/f0UerHHA4HGzduRO/evfHTTz9BQ0NDrXjR+34Pn8/Hq1evcPnyZezYsQNr167Fli1bcO3aNWRmZsLR0REjR47EkiVLsHbtWixduhTDhw+Hl5cXNDQ0wOVyoaGhoTKOaoOWlha6dOlCizlpaGjQ1kq1qWMrlUrEx8djw4YNkEgkWLNmDTp27NigINjd3R2DBw+u9RxlMhmKi4sRFxeHvn37QiAQ4Oeff4alpSW+//77egXBz58/xx9//IGvvvqqyYNgoHJOGTBgACIiImjKI5PJxKBBgxAUFFTveYXBYMDd3R3R0dEAQFOl3/4uyie9qKioQYrAMpkM8fHx+O233/Dzzz9DKpVi8eLFWLp0Kdzc3Optk0W1RshkMrpv/+zZs+jXrx/MzMwgkUgQERGBDRs24Ntvv0Xbtm2xZ88e+Pv713n/GhsUPVcul9MJCZIkaVp0a9oUUommffv2wcvLC/369asxCObz+dizZw+mT5+OJUuWwNDQELt27UJFRYXaZ4IgCHTq1AmzZs3Cb7/9RrOnqICWy+XC3t6evj5paWkAoML0KCoqApPJhJGREcRiMXg8Xo22SUAltZvL5VarZLU2dO7cGTExMWCz2bC3t8fr16/fay/AZDKhqakJPT09uiKsq6sLbW1tWv+guTRnSJJEfHw8nJ2daVp2Y0IoFILFYqntPebz+XSQXN9xRpIk/vrrL/j5+TVbor01g0rquri4VPtbTk4ObGxs1H5GqVSqrQg3BSvq34KPgbAaaGpqQqFQQENDAxKJBIaGhjVaKLHZbGhrazerwEFrAEEQaNu2LVauXInIyEgcPnz4vZMBEokEHA4HDg4OSElJUVlw2Gw2xowZgzNnzkAul6NHjx5QKpUIDw+vc2EiCAJ6enr4/PPPMXnyZBw5cgR///03Ldjw9nurBs82Njb48ccfcePGjRo3Eh/xvz5ypVJZIw29saFQKBAdHY0uXbogMjKy1mri+0KpVCI5ORmbNm2ClpYWfH19YW1tDS0tLQwePBjXr19/599MkiSkUikKCwvx6NEjHDhwABs2bMDWrVvx5MkTaGtrIyAgAIsWLcKaNWuwcOFCTJgwAb6+vnBycqJF+wiCQPv27ekezYbY9AD/EwQLCQmBRCIBQRDo27cvoqKi1Fp6UJvuw4cP48SJE5g6dSqmTp1a774vPp+PHTt2oEOHDhg5cmSdgbNQKIRQKERubi5YLBZ++eUXxMfHY8KECXWKkSkUCty5cwdnzpzBkiVL4Ozs3GwbKX19fXTq1Ilu5yAIAp6enkhNTa33ukHRWCn1aHt7exQUFFRTB6e8hMvKyuqkXiuVSvD5fAQFBWHt2rW4ePEifH19sXbtWowbN47ebDbkOvF4POjo6EChUEBXVxfJyclITk6Gj48Prl27hjVr1iAkJAQjRoyAg4MDZs+eDS0trRbb1N6+fRt9+/alKYRZWVmQyWSwt7dvkfOpCXK5HIcPH4a1tTWGDRtWq/XY3r170a9fP3Tu3BlsNhuTJk2CnZ0dfvvtN7VrHvA/dtbs2bOxe/duJCUlQS6X4+rVqxg1ahRdQSLJSh/ooUOHqrwWGRkJT09PMBgMJCcnw9LSskatBorZ8W8IZqhgvqCgAD4+PggPD3+v4zEYDJibm4PBYNDJUyaTCS6Xi6KiIlosqznWT5lMhpycHGhoaEBXV7fRLYiEQiFdVHo7EC4uLm4QI4B6xsrKyt67T/u/AoVCgdTUVLVrWWZmplohOolEAhaLVWNF+EPFx0BYDahNFYfDQXFxMW2hpA4MBgOOjo5ISUlp5rNseRAEAWNjYwQGBoLD4WDLli11KlDWBmrjbm9vj6SkJBVlVSprzWaz8eLFCzCZTEydOhUXL16sd08qg8GgfYcJgsCmTZsQGxtbY3VYW1sbw4cPx4oVK5CVlYUNGzYgOjr6P2uX9T6gKJ88Hg98Pr9ZlKMpGwozMzPExcXRHrKNDYlEggsXLuDQoUMYP348Zs6ciWHDhuHGjRsAKvs3MzIyGqQqStEcY2Ji8Oeff2Ljxo3YvXs30tPT0bVrVyxYsACrVq3CnDlz4OfnB2dnZxgZGdWZtbWxsaGFsrKzsxv8W42NjenrSZIkuFwu3N3dq/XkS6VSPHnyBJs2bYKJiQm+++47tG/fvl7tIZTq55YtW+Dt7Y2AgIB60dzKy8vB4/GQmpqKv/76C3369IGjo2Od9hlSqRRnzpxBWFgYvv3222ZXqiUIAoMHD8aDBw/oOU1HRwfe3t4IDg6u93xpa2uLsrIylJaWgsPhwMTEBOnp6SrvMTY2hlgshlQqrZEtI5PJkJycjEOHDmHTpk3Iz8/H3LlzsWzZMnTr1q3BfXtVUVhYCCaTSQe3e/fuRUVFBbZt24aysjIsWrQI8+fPR1paGjw9PZtE4b2+KCsrQ2Jioopo2YMHD9CzZ0+1vXUtBYVCgb///hsMBgNjx46tcQ6Qy+U4cuQI7OzsMHDgQPoeslgsjB49Gu3atcOOHTtq7EGlEmlz587F3r17cfbsWXA4HDg6OtLvodoy3Nzc6OPL5XJERUWha9euAICIiAh06dKl1rkgMzNTbcWqtYEgCHh4eODFixdwdnZGWlpagxTf1R3P0tISQqEQZWVlIEkSDAaDpkZzuVzaSqmpQSXheDwe7O3tG721r7S0FEwmEywWq1pShNoj1FfYks/n459//sHnn3/eqsZmS0IqlUIoFMLIyEjldao1gurfr4qKigqw2eyPFeG38DEQVgM2mw0mkwkdHR3weDyYmJjUKAxFVUaTkpI+2GqhhoYGJkyYAD8/P/z666+Ijo5+p2shkUhAkiQsLS3B4/GqVZiZTCY+++wznD9/HlKpFFZWVujduzf++eefegdeVIJjwoQJmDFjBk6dOoUjR47UujmgekBnzJiBy5cvY+fOnWqtmT502NjYQCgUgsFg1Jg4akzEx8fDwcEBJSUlIAii0ZXbqYDtl19+QVFREb7//ntaAKZ79+5ITEwEj8cDh8OBj49PrRRi6ngCgQARERH47bffsGnTJty5cwdt27bFokWL8P3332Py5Mnw9PSEsbFxjWJEtcHCwgJ8Ph9WVlbvlJxjMpnw8/OjabtUEBccHEyPz7S0NGzZsgWhoaEIDAzEqFGj6h08UXS8rVu34pNPPoGfn1+9e72ys7ORlpYGJpOJxYsXw8LCAhYWFrVWFUQiEQ4ePIjCwkIsXrwYhoaG9b4WjQlzc3PY2Njg2bNn9HXt06cPQkJC6r2xZrPZdG8wQRDo0qULoqKiVN6jp6cHpVJZLRCmhGuCgoKwYcMGnDhxAu3atcPq1asxdepU2NraNspG6M2bN9DS0qLHS0FBAT799FOsXbsWEydOpO1jQkJCMGrUqBatQjx8+BCdO3emK2EikQivXr1Ct27dWuyc3oZSqcSVK1eQl5eHL774osYgQKFQ4PTp0yBJUm2wzGKxMHLkSHh5eeHXX3+tcX6m9jNfffUVfv31V3Tu3Fml8hsUFITevXurUJpLSkpUqPBJSUlwdXWt9XdlZGS0uqq7OlDaCVFRUdDV1YWJicl7t/5YWlqCz+fTDDMqEJZIJNDR0YFcLn+vYLu+oBKmr1+/RseOHRv9+FlZWdDV1YWurm61IFskEkFDQ6NeFWGFQoGzZ8+iZ8+e/4rkSXOhuLgYurq6aj2BS0tLYWpqWu0zFRUV0NDQqHY/GtMS9d+Ij4GwGhAEAS0tLbDZbJSVlcHS0hI5OTk1vt/JyQnp6ekfbKWQohP7+vpiwYIFOHXqFK5cudLg60EFvg4ODhAKhdXomARBwMHBAba2tggODgYA+Pn5ISsri65g1RcMBgPOzs5YtWoVDAwMsG7dOoSHh0OhUKg9DoPBgJOTE1auXAkfHx9s27YNp06dglAo/BgQ/z+0tbXBYDBgYGDwTtXIhoAkKz1nvb298fLlS7i7uzfapprqowkLC8OWLVswcOBAfPnllypCPjo6OvDx8cHDhw8BAH379kVYWFg1qirV75uQkIB9+/Zh/fr1CA0NRd++fWmac48ePWBkZFTvPszaoK2tDU1NTRgaGiI1NfWdKvPOzs60JyhQ2cdvY2ODhw8f4tixY9i9ezf8/PwQGBgIS0vLegfASqUS9+7dw5EjR/DVV1/B29u73hVkuVyOBw8eICYmBsOGDYOLiwvCwsJqFQyiqNdcLhdz585tNI/gdwGDwcDw4cNx48YNetNhamoKKysrvHjxot7H6datGy3O6OrqioSEBJVNDMVkYbFY4PP59LO3Z88ebNq0CTk5OZg1axZ++OEH9O7dG7q6uu99Tah+Uh6Ph8ePH+Pq1asQCATIz8/Htm3b0LdvX5our1QqceHCBQwePBhcLve9vvd9IBKJ8OjRI5W+9JcvX8LGxqbFkiVvgyQrvXqfP3+Or7/+usZ+WqVSSesGzJw5s8ZgmclkYtiwYejXrx9+/fVXFBQU1Lh2FRQUYNCgQbh+/TpevnxJM1iio6PRo0cPFeXv58+f02yt7OxsaGlp1dlvyuPxWs11rgs2NjYoLy9HWVkZvL29ERYW9l5rvo2NDU1/FggEYDAYMDY2pqnEDAajySvCJFnp6+3i4oKcnBzaH7oxUVhYCE1NTbXe8QKBACwWC9ra2vU6z/T0dAwbNqzRz/HfCpIkkZSUBEdHR7VJBoVCoZbqLhaL1baiqOsb/pDwMRCuAVpaWtDQ0KAl7WsTTNLX14dEIoFEImnms2xdIAgC9vb2+O677/DmzRv89ttv9ep3of4ulUpBkiQsLCwgk8mQkZFR7b0MBgNjxozBzZs3UV5eDi0tLUybNg3Hjx9vcI8ylfAYPXo0Fi5ciKCgIPz+++81Cs0QBAE2m41evXph7dq1IEkSa9euRWhoKGQy2QcfEGtqasLc3BxsNhvJyclN+l0ymQxpaWlwcHBAVFRUo/YHS6VSnDp1Cjdu3MCyZcvQvXt3tR7igwYNwtOnTyEUCmFsbAxHR0eEhYUB+J89SFBQENasWYOzZ8/C3d0dP/zwA+bNmwcPDw86MGvs4IxSUi8sLHynDZWGhgb69u2L27dv00JKRkZGWL16NbS1tbFu3Tp4e3vTIlx1gSRJiEQiHD58GBEREVixYgUcHR3r/VmxWIyDBw/i3LlzsLS0hIuLC6RSKZKTk9VaJZEkifz8fGzevBmenp6YOHFioyQZ3hdt2rSBtrY24uLiAPzPjisoKKheGXkqEVhQUACRSAQLCwtIpVIVcR2K8cJisXD27FmsWbMGZ86cQefOnbF27VpMnz4ddnZ2dE/5+4BKUKSmpmLfvn3YtGkTUlJS4OXlBV1dXUyZMgVmZmYqQdObN2+Qnp5eo9hTc4AkSURFRcHe3p6umigUCty9exdDhgxpkXN6GyRJIi4uDlevXsWCBQtqrJwplUoEBwfj2bNnmD9/fp0+sJR4m7+/P7Zu3aq2lUksFuPKlSv45ptvEBgYiGPHjiEqKgp3795Fly5dVBIYJFnp496tWzcQBIHo6Gi4ubnVyvIQi8WQSCRNKmzYmKjKxOjUqRPi4+Pfq4Kmp6cHmUwGXV1dFBUV0awzPp8PNpsNBoPR5BVhSsvDxMRErc/v+4IkSZp1oK4ySbG46qJGi0QinDhxAtOmTatTB+JDAyWU9fY1EQqFNTK0qED4bSiVyg/62n4MhGsA5cFVXl4ObW3tapWeqtDQ0ICRkRHy8vKa8QxbL7hcLr755hu0a9cOmzdvRnJycp1BokKhgFgsBlBJI9TW1kZGRobaz5mZmcHb25sWKHJycoK7uzsuXLjwThUwgiBgZ2eHb7/9Fh07dsRPP/2Eu3fv1rgYUeJbEydOxPz58xEcHIxt27YhMzOzWXpjWyuojTqAJleOzszMhL6+Pl2peNtQ/l1A0Ud37twJgUCAb7/9ttaKp5GREezt7Wl66rBhw3D79m1kZ2fj1KlT2LBhA/Ly8jBnzhysWLECPXv2pKvKTbnouLi4IDMzEwRB0GOqoejatStiY2MRGhqKTZs2oaioCIMGDYKrq2uDKqskSSIjIwObN2+Grq4uFi1aBCMjo3oHwTweD1u3boWmpiYcHR1haGgIJycnZGRkwNDQsFrWm8qUb9myBZ9++imGDBnSamw2GAwGRowYgevXr9MbaWdn5xqTfuqgpaUFOzs7JCQkgMFgqAgLSiQSJCQkIDExEY8ePQKPx8PcuXOxcuVK9OzZs94iZnWBUvsOCwvD5s2bcezYMXTs2BFLlixBx44dIRaLwWKxVPpUgUrK3j///IPPPvuszoCtKSGTyXDnzh2VClNOTg5EIlGziqjVBJIkkZ2djSNHjmDu3LkwNjaukfXw/Plz3Lp1iw6W63PuBEGgZ8+eGD16NHbs2IHMzEx6nSVJEg8fPqSZV7a2tggMDMRff/2FM2fOVFN2p/zLLS0toVQq8eLFC3h6etb6/TweD9ra2q1eMZoCQRC0jzDVsvI+LgEaGhogSRJ6enooLi4GQRAwNDSESCSCXC6nk49NCbFYTBd3zM3NG70aSNFzJRJJNR0AhUJBFxtqqwiTJInLly+jU6dO9fKi/5CgVCqRlZWldt+Tn5+vkoCsitoC4Y8V4Y+oBh0dHbBYLAgEArDZbMjl8honJ0ox90PuE34bbDYbw4YNw/Tp03Hw4EHcvn27Vqo0k8mEWCwGSZIwMjKCubl5NeVoCgRBwN/fH5GRkcjPzweDwcAnn3yCV69evZcHn4aGBgYNGoQVK1YgNjYWP//8M9LS0mq8pwRBwNbWFosXL0a/fv2we/du/P3337QIxocIFxcXlJSUgMfjNVmrAFXRcXd3R1JSEpycnN57EidJEllZWfj555/h5uaGmTNn1tm/RBAEhg8fjtu3b0Mmk0FbWxsJCQlYtWoVOBwOvv/+e0ybNg12dnbNFoxRrIzc3FyYmZkhMzOzwcdQKpUoLi5GZmYm/vjjD0yaNAlff/01xo8fj6tXr9b72ZbJZAgKCsKuXbswduxYjBs3rt6bX5IkkZqaip9//hndu3fH6NGjUVZWBgsLC1haWiI8PBxeXl4q15VSkd+/fz/mzJkDHx+fVuft3qFDBwgEAvq+sFgsDBgwAHfu3KnXdWUwGPD09MTz588BVNq7PHr0CNeuXcP69etx8eJFtGvXDt26dYOrqytsbGwa7dlTKpXIy8vD2bNnsX79ekRERGD8+PH4/vvv0adPH5BkpUdlbm4uvvrqK5VNLqX6qqGh0ahtDO+C5ORkMJlM2i+XJEncv38fffv2bRVJk/LycuzZswcTJkyo0WeaJEnExsbi9OnTmD9/fr2TSxSo4G7SpEnYuXMnrfRfVlaGO3fuYPTo0fT7rK2t4evri4KCAhXrQZIkER0djfbt20NLSws8Hg/l5eV10mwLCwthamr6rwpsHBwckJubC4lEojL+3gVsNhtcLhcsFosunhgYGEAoFEIikUAqlTZ5RZgS3EtOTkaHDh0a/fjUb5DJZNUo8CKRCCUlJbWKZZEkiZSUFERHR2PUqFGtbh5vadRGf87IyKixMFBRUaF2Df7YI/wRamFoaAi5XE7LjWtqatZodUEQBNq1a4fExMRmPsvWDQaDgfbt22P58uWIjo7Gnj171AaJ1IJIJRpYLBbMzMyQkZFRY/JBT08PQ4cOxblz56BQKKCjo4Np06bhzz//fC8bJ4qmNG/ePAwbNgy7d+/G2bNna/VgZLPZ8PHxwerVq8FisbB+/Xo8efKEzu5+SDAzM6PvWVP6Ib58+RJubm6IjIyk1UrfFVQf0vbt2zF27Nh6VxEpJgGTycS2bdvw66+/ol+/fmjXrh38/f1hYGDQIps9a2trlJSUwMLCAqmpqfV+BkmSRGFhIQ4cOIA//vgDkydPhqWlJRwcHMBkMuHq6gqRSET7iNZ1nO3btyMuLg4rV66Eu7t7vTczSqUSERER2LVrF6ZPn44BAwagoqICpaWlMDc3h6mpKWJjY1VUwhUKBW7cuIFLly5h8eLFaNu2bavcaDOZTAwePBhBQUF0QNG1a1ckJibWy0qJJEm4uLggISEBL168wJ07d3Du3DmUlpZi/vz5+Pbbb9G/f39oaWnV2gNaX1DWXtHR0di2bRu2b98ONpuNb7/9Ft988w3atm0LNpsNoLKvNDo6GlwuF+3bt1c5jkgkwoULFzBu3LgWDTYVCgVu3ryJ4cOH08+jQCCgRbJa+pmRSqXYt28fevToAS8vrxqD4JSUFBw+fBjffPNNvfv03waliDxr1iz8/vvviI+Px61bt+Dt7a0SqAqFQkRERGDnzp24fPkyHj9+TD+7oaGh9HVLTEyEo6NjnUnJlJQUODk5Nfh8WxI6OjqwtbVFYmIiunTpgujo6HcOHigLJTabTSfEuFwuLXJH/bepQJKV/rMODg5IS0uDs7Nzo38HtW8uLy+vRoEXCoUQCAS1BsJSqRRHjx7FxIkT622x9CEhLS0N5ubm1YJakiSRk5Ojdk6g2ozUVeE/VoQ/Qi0MDQ3B5/PpjLG+vn6tG3srKyvk5uZ+8JmVt0HRfhYtWoQ2bdpg48aNNVbOqcmfIAha/ba2Knzv3r2Rm5tL96O6urrC2dkZ165dey+KMkEQYDKZ8PLywurVqyEQCLBu3TrExcXVeFyqN2/cuHEIDAxESEgIfvrppxrp3f9VcLlcMJlMaGpqIj8/v0m+o7i4mO4xy8zMfK+gh+pxO3ToEObNm0d7Ydbnc2KxGDdv3kRycjISExOxZs0azJkzB2VlZcjNzX2n82kMaGpqgsViwcrKql692pRoy9mzZ7F582bY2dlh7dq1CAgIgJGRES1Ex2azMXToUFy/fl3tOKB6Rh89eoQff/yRtoEyNDSsNxVaoVDg2rVruHjxIpYuXYoOHTqAIAikpqaiTZs24HA4tNAK1dcmkUhw/PhxvHz5EsuXL3/nwKA5QBCVfsDJycn0eqKjo4NOnTohIiKixrmCEhvLzc1FUFAQQkNDcebMGQwaNAgDBgzAwIEDYWFhASaTCRMTEyiVylp1LeoC1SZw9epVrF69Gjdv3sTAgQOxYcMGjBo1CsbGxip9xpQaeF5eHtzc3FTGEElWes+6ubnBxsamRXuD8/PzUVxcjI4dO9Jre2RkJFxcXBrdR7WhoNRxuVwuhg0bVmMQnJmZiT179mDOnDmwt7d/r+tJWSbNmzcPO3fuxK1bt1Qo4yRJIiQkBC4uLujQoQOWLVuGGzdu4OHDhygtLQWPx0ObNm1o8UIfH59av486/6YQZ2pKMBgMdO3aFeHh4bC2toZEInlnZwSCIGBmZgapVEpb7hkaGoLFYkEqlYLBYLxzS0t9kZiYCBsbG5SUlDSJEjPFpBSLxdDX11f5m1AopG2V1Am7kSSJmzdvwtbWVsWm6yMqQSUy1PUHKxQK5Ofn12hLV15eDl1d3Wqvf+wR/gi14HA4EIlEYDKZkMvltGBWTaB6/2qy4fmQQVVNAwIC8MUXX+DQoUO4du0aLY5FgVJspqjmpaWltS42GhoaGDduHE6dOgW5XA4Gg4HPPvsMERERSE9Pf+8AlOoFnj59Oj7//HOcPHkShw8fRmlpaa10aWtrayxevBh+fn7YvXs3jh8//sHQpdlsNp2pfB+aem2Ij4+Hk5MTsrOzYW5uXm8vwrehVCpx//59nD9/HkuWLKmRhvg2FAoFXrx4gXXr1iEnJwc//fQTzM3NabGTqkJTLQEmk0kLzhUWFtaYvCFJEhUVFbhz5w7Wrl0LqVSK1atXY+jQoXSmefjw4bh58yad4PP29kZWVhYKCgqqHSs/Px/bt29HaGgoli9fjn79+tVbUAuo7F86fPgw4uPjsXz5clhZWdHBSkJCAqytrWFgYICXL1/SNlZlZWX47bffIJVKERgYqFahtLVBW1sb3bp1w4MHD+j5bsCAAXj06FG1xJ9SqYRAIMCTJ0/w448/Yvfu3dDT08OMGTPQvXt3dO3aFZ06dVJRzTc1NYVIJEJFRUWDEoJUb2JSUhKtMl1eXo758+dj2bJl8PT0rNHSSyqVIjg4GAMGDKhWYcrPz8fTp08xcuTIFqc43rhxA/369aM34HK5HPfu3cPgwYNb9NxIkkR4eDgSEhIwbdo0tVVzkiRRUFCA3bt3Y/r06Wo3wu8CStvBzs4OAoFAxXatoqIC9+7dw4gRI0AQBIyNjbFkyRLcuXMH+/fvh5OTE7S1tSESiZCVlYV27drVek5Uf6iFhcV7n3dzo127dkhJSaEV22NiYt75WJQSdXl5OZRKJR0IV1RUQEdHp0n3kQqFAhkZGTAwMACHw2kSX96cnBxwuVy6QFAVQqGQ3lu9PeaoFqXg4GBMnDixxeeL1oqEhAS0a9eu2utSqRRisbhGRf6ysjK1f5PL5R8rwh9RHTo6OhCLxWAymZDJZDA3N6+1wsVms2FjY1NrT+mHDir7vHLlSqSnp2P79u0oLCykrxfVU0oQBGxsbCCTyWrtcSQIAh06dACXy0VoaCgtQDFhwgQcO3as0ehFDAYD7dq1w6pVq2BiYoJNmzbVqRTNYrHg4+ODNWvWQEdHBxs2bMCjR4+qBf//NVBJDKVS2SRjgargdu3aFREREfDy8nqnxVKhUODWrVt4+PAhli1bRgdddX13cXEx/vjjD1y+fBkzZ87ErFmzYGVlhf79++PGjRsAgO7duyM2NrZeVNemgpOTEwoKCqBQKKq1ClDV7MePH2P9+vVITU3FkiVLMGnSJBU6N0EQcHFxgVgspsVh3laUpo5169Yt/Prrr+jWrRsCAwNhbm7eIEGtwsJCWhRrwYIFKlUESnDLwMAAtra2ePHiBbp06YK8vDz88ssvaN++PWbMmPGvEt/p168fwsPDaRFGS0tLaGtr072aEokEiYmJOHToEM1GGT9+PFavXo0RI0agX79+tEibu7s7YmJi6LGmpaVFay7Uh6FE9Ybev38fGzduxOnTp+Hp6Yk1a9Zg4sSJsLa2rnWMkSSJO3fu4MWLFzAxMVHpT1MoFDh58iRGjhzZonZJQKVSbUJCAk3lJUkSycnJ0NbWblF/UpIkkZ6ejvPnz1frra76ntLSUuzatQujRo1qdLu45ORkiEQibNq0CX///TfCwsLonnt7e3vao51qHVq8eDHu378PbW1tKJVKZGZmwsjIqE47HIFAAKlUCiMjo0Y59+aEgYEBDAwMkJaWBh8fHzx79uydGYCmpqaQSqVQKBQQCATQ1NSElpYWSktLoa+v36RrR0VFBRQKBfLy8ppMHC4/Px96enpq1YuFQiGUSiX09fWrzSsymQzHjx/HuHHjWpyh0VohlUpRWloKMzOzan+jKOk1BbUCgaDGinBr0EdoKXwMhGsAFQjr6emBz+fDysqqVi9hatOYkJDQjGf57wNBEDAwMMCcOXPg6+uLn3/+GaGhoVAqlSqLirW1NTQ1NeukFrNYLIwbNw6XLl2CQCCg+57MzMwQFBTUaIEYQVT6c44aNQoLFy7Ew4cPsX37duTk5NT6HRwOB2PGjEFgYCAiIyOxZcuWBvVt/hvh7OyMiooKFBQUNLr6JeVv6+DggPj4eHTq1KnBx6Dot5GRkVi8eHG9NmVyuRxPnjzB5s2b4eDggBUrVsDJyYmmh/r6+iI+Ph6lpaXQ09ODp6cnHj161CL3mSAIODo6Ijc3F8bGxiqezlKpFBEREdiwYQPtTzpr1qwa6cQsFguDBg3C7du3afpU7969ERMTAx6Ph6SkJPz444948+YNVq5cid69ezfIqoii1P7888/o3bs3Jk+eXE1RWC6XIzo6Grq6uvQmsaKiAlu3bsWIESPg7+//r8tmGxoaom3btggPDwdJkmAymRg4cCAuXryIK1euYMOGDfjnn3/g6uqK1atX48svv0Tbtm1pCxFra2sIhUKUlpbCzs4Oubm59FhjMpnQ0tICm82udUOtUCiQlpaGw4cPY/369UhLS8OMGTOwYsUKdO/evV4ewxTV9dq1a3B3d4dYLKarfSRJ4sWLFxAIBOjZs2eLVupJkkRQUBC6deumssG+efMmBg0a1KLPj1AoxP79+zFlyhS1CSSKubFr1y707t27Ru/sd4VcLsfJkycxduxYODk5YcmSJbhw4QLu3LmDGzduYMSIEWoTIc7OzkhJScHVq1fx9OlT+Pj41HleZWVl0NXV/VdW+hgMBry8vBAREQEHBwcUFhZCKBS+07F0dHQglUrp6i+LxYKWlhaKiopgaGiI8vLyRj77/yE9PR1mZmZIT09H+/btG31cUuwgbW1ttcEsn8+HQqGg26iqfi44OBi6uro19sd/BJCbmwtdXV21AW1BQQGMjIxqDGqlUqlaxX6FQvExEP6I6tDR0UFFRQUMDAzA4/Ggr6+P0tLSWj/j7OzcZHTQ/xpYLBb69OmDpUuX4vbt27hx44YKjc/Y2BgGBgb1sl6ysrKCt7c3Ll26RG8qJ0yYgPv37yMrK6tRgxFqE7p06VL07NkT27Ztw8WLF2nF65o+Y2lpiYULF2Lo0KHYt28fjh8/jvLy8v9kQGxubg6pVAq5XN7oC3pWVhaMjIzA5/Ohra1dTZGyLiiVSly/fh2vXr3CokWLaPpWTaCqZXv37kVwcDCWLFmCoUOHVvM01NPTQ9euXfHw4UMAwMCBA/H48eMmV/+sCZaWligsLISlpSXS09OhUCgQHR2NjRs34v79+5g1axbmz58PW1vbWjelBEGgS5cuePPmDe0JzuFw4O7uju+++w6HDx/GuHHjarV5qQkKhQJBQUE4fPgw5s6diz59+qhdjCmLkZKSEojFYuTm5uLo0aOYPXs2unXr9q/dVA8ePBh3796FSCRCZGQk7ty5g/Pnz6OgoADffPMNbXtEtd1UhYaGBuzs7JCcnAwOhwNdXV2ascRkMmnaYdXWEqqCLxQK8ejRI2zatAkHDx5EmzZtsHbtWnzxxRewt7cHi8Wq932USCQ4cOAAPvnkE3A4HIjFYto3VCQS4cyZM5g6dWqLJyrKy8sRERGBAQMG0L+toKCA7mluKSgUCvz555/w9vausR9SJpNh7969aN++PQYOHNiozztJknj06BEMDAzQqVMnEAQBc3NzLF++HH///TfkcjntS171M9HR0ejSpQuWLl2KqKgoXLp0Ce7u7nV+X1ZWVotW398XFPuCxWLBzs7unZ1CdHR0oFQqwWaz6UCYxWKBz+fDwMCgyajRlL2cvb09MjMz4ejo2OjfoVQq6daZt58dACgqKqJFm6hnmWIF3bhxAxMnTvygg7K68ObNGzg6OqqdK7KysmBtbV3j/C2VSmlxw6qQy+Uf9DX/9+0gmgna2tqQyWTgcDg0r76uwMXU1BRlZWWQSCTNeKb/XlCiWCtWrICPjw9KS0sRExNDLxBcLrfWHseqxwkICMCLFy9oCqeBgQEmTpyIgwcPNnowQhAEWCwWevTogdWrV6O4uBjr169HfHx8rWJaTCYTXbp0wdq1a6GhoYF169YhLCzsP6cubWBgQG98i4qKGu24lLCNl5cXnj9/Dg8PjwZN3kqlEjdv3kRUVBTmz59fZ8VLqVTi9evX2LBhA+zs7LBs2TJYWFio/QxBEBg0aBCePHkCkUgEMzMzWFlZ4cWLFy1yb7W0tGh7r7t37+LHH3/E5cuXMXHiRCxbtgxt2rSp94ZaR0cHXbt2xb179yCTyXD37l2EhISgsLAQS5cuRceOHRu0OaeSC7t370Z0dDRWrlxZo08kZROjp6eH8vJyPH/+HBoaGli+fHmrVYauC5SomFKpRFxcHAIDA/H48WP4+/tj/vz5sLCwoIWvavp9lOhWREQEGAwG2rZti/j4eJAkCQaDQVMveTweLUKWkZGBI0eOYM2aNYiJicGECROwbt06DBgwoF7VX3W/4/z583BycoKZmRk4HA60tbVpn9SgoCC4urq+t6DT+4IkSTx48ACenp60gi1Jkrh16xb69OnTYpR6kiRx7949lJeX11h1lclkOHbsGLhcLj799NNG36zy+XxcvXoVkyZNoo9NsZ8MDAwgl8tVNAKAynkxNDQUvXr1gp6eHsaNGwcej4d79+5BqVTWOt+lpqbSXvP/Rpibm4PJZCI3N5cWz3oXaGlpgcPhgMlkorCwEGw2my6+UCzEpkJ8fDzs7OygVCrVVhXfF3K5HEKhEEKhUG0vOJ/Ph0AggIaGBv3MK5VKHD9+HP7+/jAxMflXzuvNAWo97Nixo9q/ZWdn19rmJZVK1faEf6wIf4Ra6Ojo0N6gfD4fenp6kMvltar5cTgccLlc2hvuI+oGQRDQ0NCAqakplEolzpw5g0OHDkEoFMLKygo8Hq9eCoo6OjoYM2YMTp48CZlMBoIg4OXlBQsLC9y8ebNJghGCIKCvr48ZM2Zg6tSpOHHiBA4cOFCrWitBENDR0cH48eOxYMECPHjwANu2bauTYv1vAmUPoaur26gMCblcjvj4eLi5uSEqKgqenp71XjCVSiXu3r2LiIgILFy4sNZKMCUadOXKFRw/fhxffvklRo4cWSfl19jYGHZ2dnj+/DkIgsDQoUOrMR2aA1QwxGazcfz4cYSFhSEgIAArV66Eq6uritpvfUAQBHr16oUbN25g7dq1eP36NX744QeMHj0aYWFhDTo3pVKJxMREbNq0CW3atEFgYGCdHqgvXrygRbJCQ0OxcePGBvUgtxYoFAoUFxfjxo0bWL9+PY4fP44BAwbAzs4OCxcuhIeHBwYMGICQkJB69R62a9cO6enpEIvFcHNzo8V7CIKAqakpTVsODg7Gxo0bceTIEdjZ2WHVqlWYO3cuXFxcGiRmVhVUVTAmJgbjxo1DdnY2dHR06HuZm5uLkJAQfPLJJy1esacq4EOHDqV/a1lZGV69eoXevXu3yHNEkiTevHmDW7duYfbs2TVuTq9evYqysjJMnz690avqSqUS586dQ+/evVX6DanEQYcOHbBu3TpER0fjwoUL9DPJ4/FQVlaGNm3aAKi0sps/fz7evHmDM2fO1PjsKpVKZGdnt6hy+PuCwWDAw8MDUVFRaNeuHVJTU98p0U4QBIyMjKClpYXs7GywWCyYmJigrKwMenp6dbIP3xUKhQIlJSWoqKiAlZVVkzA1KNHTsrIytUGtQCCgK5AMBgMkSSIsLAxSqbTFxuO/BXK5HDk5OWp9gqlAuDZF9poqwh97hD9CLdhsNhgMBrS1tVFWVgYtLS3aF60mEASBNm3a4M2bN814pv8d6OnpYfny5TAzM8PmzZtRUlKC8vLyelnRUBUSpVKJ58+f02qskyZNwuPHj5tUxIzBYMDV1RWrVq2CtbU1Nm3ahODg4FoXSIKo9KBdsmQJevXqhR07duDcuXMQCAT/iYDY1dUVEomkUa87j8ejF1mZTAYrK6t6fY6yAAkODq4mxKQOZWVl2LVrF9LT07Fy5coGVR79/f1x+/ZtyGQyWjSsqgprU0Mul+P169f49ddfkZCQAE9PT3h5edXL31MdKBXPEydOoKCgAO3atcPXX38NCwsL+Pn5ITg4uF6JKkpU6+LFizh69Cg+//xzBAQEqF2Uq0KpVCIkJARhYWHQ0dFBjx49aOGefwOoDWFoaCi2bt2KLVu2oKysDF9++SW+++47zJo1CwKBgKY1W1hYQE9Pr16e9JQYTUFBASwtLZGfnw+FQgGZTEazGY4cOYKkpCRMnToV3333HQYOHNgo/tZFRUX466+/MHv2bGhrayMrKwtyuRxt2rSBQqHAiRMnMGrUqBYXyCJJEqGhoXBxcaHttkiSxOPHj+Hm5tZigjwCgQCHDx/G559/rra9g5qzoqOjMXv27DrHSUNBkpXe6ampqSoJAqBy/rtz5w5GjRoFAwMDLFy4EKmpqfj7778hk8nw7NkzeHh4gM1mQ6FQ4OXLl+jVqxfmzZuHrKws+n1vg2IoqKPL/pvg7e2NqKgocDgcGBkZ1emrXhPMzMzo5BglQlZSUgIul0u3oTQ28vPzoaWlhZycHLi4uDRJkqq8vBwaGhooLy+HiYlJtb9TtqSUqF9paSnOnTuHadOmNfpz/l9DcXExGAyG2jlDoVCo9W2uCplMpjbp9pEa/RE1gs1mg8Ph0HY5FD2vNnTo0AFxcXHNdIb/LVBZqZEjR2LhwoVQKBR48+ZNvfqEgcreuEmTJuH8+fO0RD+Xy8WkSZNw9OjRJqesa2lpwd/fH0uXLkVkZCR+/fXXOm2c2Gw2unfvjtWrV0MkEmHjxo14/vz5v96P2sHBAUqlEjk5OY0mmBUbG0uPr/bt29dr0aQqV9euXcOCBQtqXSSoCtpPP/0EZ2dnfPXVV3X2EFcFQRCwt7eHhoYGkpKSwGKxavXdbUwoFArExsbil19+wZkzZzB8+HCsXLkSMpkMRkZGKCwsbNDxSJIEj8fDsWPHsHPnTnh7e2Pnzp1ISEign01TU1M4OzvjyZMndR4rKysLP//8M4qLi/Hdd9/VS6SF2qy/fPkS3bt3h56eHjw8PP4VFQOJRILXr1/jjz/+wMaNGxEVFYURI0Zg3bp1GD9+PGxtbcFms6GpqYmePXvi/v37tL5B//79cffu3TrnPEo1PzY2FlwuFywWC2fOnMHGjRvx8OFDcLlc9OjRAzNmzICjo2ON1kfv8tsOHToEf39/2NvbQ6FQICcnh1b7Dw8Ph0KhoNWZWxJisRh3797FiBEjVF57/PgxhgwZ0iLnpFAo8M8//8Dd3Z32ya4K6rm/cuUKvv76a3A4nEa/jhUVFThx4gSmTp2qQg2nPFy9vb3pXm9dXV3MmzcPxcXFOHz4MJ48eYLu3buDIAjk5eXR1UwOh4NvvvkGxcXF+Ouvv6rN+2KxGARBqBXr+TfB1tYWIpEIpaWltHjWuwSt9vb2KC8vp205jYyMUFJSQttRNcWakZ6eDmtra6SkpKi132kM5OXlgcvlQiwWVwvYqHVFW1ubVhg/deoU+vfvX+/E9oeMjIwM2NnZ1Whhp1Qqa2z1oFrw1O2bPlKjP0ItKO9bDodDZ+fqI2tvZ2eHnJwc2groI+oHgiCgVCppWrO1tTXmzZsHExMT/Prrr7h8+XKtglTUMWxtbeHh4YFr167RVWF3d3dYW1vjxo0bTV5tpcRGFi1ahEGDBuG3337DP//8A5FIVCtdWldXF1OmTMHs2bNx9epV7Ny5EwUFBf/a6rCNjQ3EYjEEAkG9KoZ1gar0e3p6IiIiAj4+PnV+hiRJpKWl4e+//6afpdro0DExMdi2bRs+++wzjBgx4p2y0wwGA/7+/nRfnZeXF7KzsxsciNYHVO9nXFwcfvrpJ5w5cwb+/v74/vvv6We+sLAQNjY2tdqQvX1MgUCA8+fPY+PGjdDX18fatWvRq1cvtGnTBiYmJnj58iU9tkaMGIE7d+7QNkBvH0sqleLatWvYvn07hg8fjhkzZqgVf3obSqUSz549w8qVK6GrqwsrKyuUlZXBw8Pjna5VU4MkSZr6+c8//2DNmjU4f/483NzcsGbNGsydOxeurq7VRNYAoE+fPoiKioJAIAAAeHh4ICMjo1bfegqdOnXCgwcPsH//fjx//hyvXr3CjBkzsGrVKpiamkIikTRqEKVUKnH16lXo6+ujT58+IAgCCoUCQqGQ1tI4e/YspkyZ0uLVHZIk8fz5c1hZWdFUeioxZmFhAVNT02YP1Ckl7czMTIwaNUqtj2phYSEOHjyI2bNnN8k5kiSJy5cvo3379tXYLkVFRQgPD4e/v7/K69ra2pg7dy5NKTc2NgZJknR1mGKbaGlpYe7cuRAIBDh27JiKxWBRUVGtirb/FjCZTLRv3x5xcXFwc3NDbGzsOwWt1DUUCoWQSCQwMDCgiy4SiaRJkuGxsbFo164d+Hy+2mrt+4IkK72u9fX11dr4SKVSlJSUQFdXFzo6OoiJiUFeXh78/PxaPGnW2kH1B9fklJGXlwdDQ8MafaGpteDtv1P7iJYWNGxJfAyEawHVzE9lWqytrWu1UAIqJzeFQtFkPR7/ZVCBMFAZHBobG8PGxgYeHh7Iz8/H+vXr8fLly/9j77vDorj+r89sg6UtvfcOglJU7F1UVCxoLIkaeyyxx5Ki6THFxBqNsURNYtRo7B07glRFpPfeYYHtZd4/fGd+riywIKD5hvM8PCbsMn3uvedTzmlWXIrBYGD8+PGIi4ujFaMZDAamTZuGhw8ftpihbQ9Qwli9evXCZ599BolEQvdaUaW96v6GwWDAyckJH374Ifz8/LB161ZcvHixxQDAmwgul6siBvKqEIvF9ARbXV2tkdplaWkpfv75Z8yfP79ZAQmlUon79+/j2LFjWLVqFQICAto8KVNZuurqapSWloLD4WDAgAF0xq89QJWGP336FF999RX+/vtvjB07Fh9//DG6d+9Oq/7q6+tDoVDA1ta2xVJbqnT55s2b+PTTTyEUCrF582ZMmDCBzkhRxPdF8RxLS0vY29vj0aNHKuenVCqRl5eHr7/+Gvn5+di8eTN69uzZ4iKYEpK6cuUKTp8+jYCAABgbG6OsrAx6enpwdHR8YxZMFPmtra3FrVu38Pnnn2Pv3r3Q1tbG6tWr8eGHH6Jfv34q108dDAwM4ObmRrd0aGtro3v37rS1krp91tTU4Nq1a/jtt9/w8OFDuLm54eOPP6bvB5fLBZvNpj1D2+t8nzx5gri4OLzzzjs0iRMKhVAoFJBIJLh9+zb69+8PGxubdtnnq0Amk+HKlSsYP348fe3lcjmuX7+OsWPHdnrvMkmS4PP5OH78OObOnas2MyoQCLBz507ayqgjSHBycjIeP36MyZMnq1wDpVKJc+fOYfjw4WpLxjkcDtzc3GBoaIjDhw9DJBIhLi5OxeqGyvguWrQIEokEhw4douf03Nzc1y6c1h4gCAK9e/dGTEwMjI2NwWKxNGrfehk8Hg9SqZS2x+LxeHRAUS6XtzsRpvyetbS06LaKjkBJSQmMjY1VxLAoiMVi1NbW0oJ6f/31F959993XHjT7N0AulyM3N1et97MmQlkSiYTWDlG37S4i3AW14HK59EClVCphbm5O93I1BQaDAXNz8y7BrFaCEk14sZxKR0cHurq6UCgUePfdd/Huu+/i/Pnz2L59OwoKCpqMwurp6WHy5Mk4duwYFAqFSon0wYMHO03V+8VM78KFC3H+/Hns2bOn2UwvVYkwdOhQfPzxxygtLcWXX36JlJSUf1W5NJWdZ7FY7dIjm52dDUtLSxQVFdHlx82Bz+dj9+7dmDp1arM9vpQgTXh4OD744IMmy45aAw6HgyFDhuDKlSsAnmf8YmNj6YxfW0FlCuLi4vDVV1/h0qVLCAsLw6ZNm+Dn59fI9kZLS4uO+hcXF6t9X6htRkZG4tNPP0V2djbWrVuHd955R20vqYuLC0iSVLmnoaGhuHHjBh2waWhowMmTJ7F3716EhoZi8eLFGvWlUsfy22+/ITk5GevXr0dNTQ1cXFxQWVkJBweH16bw+/JxNjQ0ID4+Hjt27MDWrVtRVFSE2bNnY8uWLQgNDaUzkJo8SwRBYOTIkbh9+zbkcjkIgsDQoUMRERFBj4fUYvnJkyfYuXMntm7diqqqKixduhTjxo2Dvb09PD09UVxcDIVCAS0tLWhra0OpVLabhVlZWRmOHTuGxYsXq2T1i4qKoK+vj5KSEuTl5TXKJr4OUJlXY2Nj2NnZ0dng7OxsMBgMWuips4/pjz/+wNChQ9WOMzKZDEeOHEGPHj06rKy8rq4Ov/32G+bPn6+iGEySJPLz85GVlYUhQ4ao3bdSqURsbCw2b94MIyMjfPnll5BIJI1KWikyPH/+fADAgQMHIBaLkZ+fT9+LfzucnZ1RVlZGC9UlJCS0ehs8Ho8O6ovFYpiamtJkRKlUtvt8X1dXB5FIhLq6Ojg5OXVIZp4iZBwOByYmJmqJMKWd8ujRIwQGBv5PBEc6Aw0NDZBKpTA2Nlb7eXNl08BzItxUe8x/nQj/d89cAxgZGaGhoYEelExMTGg7iuZeXG9vb6SkpDRZwtCFxqBewhdLyrW1tWFpaUmXCbq5uWHDhg2Ii4vDnj174O7ujtDQ0EYlrwRBoGfPnrh37x4iIyNpJcIePXogLi4O58+fx5QpUzotI8BgMODi4oINGzYgIiIC3333HYYMGYIRI0bQfTIvg1KVnDdvHtLT0/Hnn3/Czs4OU6dObRexm86Au7s70tPTkZOT0+I70xyoEkeqLDooKKjZ74vFYuzfvx/9+vVDz549m9yvTCbDiRMnUFxcjLVr12pUsqsJCIJAUFAQrl69Cj6fDx6PB09PT8TExGDo0KFt2odYLEZcXByuXLkCIyMjzJw5E87Ozi1a7Dg4OEAkEtF2FlSm58Ws8rlz52BoaIilS5fC1ta22feCwWAgJCQEV65cgaurK5hMJqytrWFtbY3o6Ghoa2vj9OnT8Pf3x8cff9wqW56amhrs3bsXdnZ2eP/99yEUCpGTk4OgoCDcuXMHISEhr02BmFqsZmdn48GDB8jKyoK9vT2GDRsGNzc3cLncV3p27OzswGQykZeXB1dXV1hZWYHNZiMnJwc6Ojp48OABnjx5AnNzcwwdOhQeHh702NGjRw8kJiZi8uTJYLFYqKiogIWFBXg8HoqLi1FbW9tqv+2XIRAIsHfvXkyZMkVFsZQkSbo/uLCwEJ9//vkb0QMql8tx4cIFzJkzh17wkySJS5cuYfTo0a+lPDcxMREVFRVYsGBBo2dFqVTi2rVrkEqlHaa0LZPJcPjwYQwcOBCurq4qnykUCvz111+YNGlSk3NSfn4+7Z9rb2+Pb7/9FqmpqRCJRGqzTFpaWpg7dy6OHTuGvXv3ory8HGPGjGn383od0NLSon2Ee/bsSVv/tOa+cTgccLlciMVi2j/4xYRAexPhsrIyGBsbIyMjA/369WvXbVOggoT19fVqRdEkEgldiuvg4PBaKjP+rSgsLKRt9dShoKCg2fsqlUqbHJvlcvl/Oivf9QQ2Ax6Ph4aGBmhra0MgEMDY2Bh8Pr/ZAYogCLi4uCA7O7vTbVP+7aB6CilQNjxyuRwVFRV0f0OfPn2wZcsWWFpa4ttvv8WpU6dQV1enkmVlsVh45513cPbsWbpMncFgYPr06YiNjW1XWx9NQEXJqUxvcXExvvzyyxb7i6h+pI8++giWlpb44osvcP/+/Te+B516D0iSRF5e3itN6pQCroODA/Lz8+Hl5dVshvfEiRMwNjbG6NGjm5xkpVIpjh49iqqqKrz//vutEsXSBPr6+ggICMCdO3fojF94eHir7huVBbx9+zY+++wzxMTEYP78+Vi1ahXc3NwaZYDVwd3dHdnZ2dDR0aG1DuRyORISEvDVV1/h5s2beOedd7By5UrY2dm1uCghCAK+vr6oqqqi20QI4rlV2WeffYbr169j2bJlmDZtmsaBBZIkkZmZiW+++Qa9e/fG22+/DW1tbZSUlEAul0NbWxuVlZWtsstqD1DXKisrC8eOHcNnn32GixcvwtfXF5s3b8bSpUvRo0cP6OjovPJxMZlMDBs2DDdu3IBSqYRAIICBgQE2btyIffv2wcDAAOvXr8eqVavg5+dH75O6H8nJySBJEo6OjsjJyaEDaTKZ7JU9SeVyOY4dOwZ3d3f06dOn0bnm5uYiMzMTkyZNgru7+2sP0pEkiYSEBPB4PNqzlspUVVVVwcfHp9OPsaGhAcePH8fs2bMbLUYpfYKIiAjMmzevQzIzSqUSly9fBkmSGDNmjMr5UyXvSqWyyXeMJEncu3cPffv2pccdqVSK3r1746effmqyFYzD4WD27Nng8XiIj49/I4Ik7QGqPDo6Ohq2trYQCASoqqpq9XZ4PB50dHRQXFxMO5NQlTHtPcenpaXB3d0dxcXFHda6IJfLIZPJ0NDQAHNz80bPklgshkwmQ2lpKYYMGdJh5dn/a6BaGtSJ61Gf19XVNeuIIZFI1L5/1Dz3b+/dfxV0EeEmQJW1isVi2tfN0NAQEomkRfEfW1tbVFVVqRWQ6YJ6UGJZL15bgiBgbW0NNpuNvLw8ld/r6OggJCQEmzdvhkKhwKefforz58+r2A9ZWVlh4MCBOH36NE02dXV1MW/ePBw+fPi1WBURBAFDQ0MsXLgQs2bNwvHjx7Fv3z660qCpv9HW1sb48eOxfv16PHr0CN999x3dA/2mggpi1NXVvZJydFlZGVgsFgQCAUxNTZucPEmSxN27d1FcXIy3335bLamjou2HDx+GTCbDe++91yHlthT5jYiIgFgsho2NDfT09JCamtriPaOi6pcvX8bmzZuRkpKCpUuXYuXKlXB0dGyV96uFhQXKy8thZ2eHnJwcPH78GJ9//jmuXr2KmTNnYt26dXBzc2vVNtlsNkaOHInLly+jtrYWv/32G06fPg0/Pz+MGDEC9vb2GkX5qZaT+/fv4+eff8a8efMwYsQIekJ+9uwZtLW1wWazYW9v3ym2SdQxFRcX48yZM9i8eTN+//13WFlZYf369Vi/fj369u0LPT29ds9k+Pj4ICEhATt37sQXX3wBJpMJc3NzbNiwASEhITA2NlbrAW1iYgKhUAihUAhfX188ffoUAOgSuurq6jYfk1KpxPXr11FfX4+pU6eqfUZSUlIQExODvn37vhHZHblcjvPnz2PixIkqi7vz588jODi408mYUqnEhQsX0L17d5qYUyBJElVVVfjtt9+waNGidg/IUft48uQJIiMjsWDBgkZEWywW48SJE5g2bVqTJFwikSApKQk9e/YE8HxMlkqlWLJkCYKCgrBt2zZUVVWpHdtYLBYthnTw4MFmhSP/LSAIAp6ennTCw93dHSkpKa3ejqWlJS2QpqWlBSaTCbFY3O5iWVSw0dzcHEql8pUrRJoCpQjN5/NhaWnZ6HOBQICKigqwWCyYmJi89qDZvwUKhQJpaWlNJgGoytXm7OCaIsJAV2n065+13mDo6urSkfna2lowmUxwOJwWCa6WlhY9GHRBcyiVykbeu05OTiBJEjk5OY2+T/X+Tp8+HR9++CH4fD4+/fRTXLx4ke7HHD16NHJycpCWlkaX57q7uyMgIAAnTpx4LVl7ShjL09MTn3zyCRwdHfHll1/i5s2bdOlQU39naWmJ1atXY+jQobT38Ju6sGCz2TAyMgJBEC321jcFkiTx9OlTeHp6IiEhoclSZ5IkkZaWhmvXrmHRokXQ1tZWKyghl8vx22+/AQDmzZunVsW3vWBmZgYHBwfExsaCxWJhzJgxzSqXK5VKVFdX4++//8aWLVtQWVmJtWvXYsmSJXRvXWuP1cTEhF5Y/fDDD7h27RpmzpyJDRs2wMPDo1UE+EV4e3vj1q1b+Oijj8Dj8fDZZ59hxYoVuHz5ssZBD7FYjGPHjuHu3bvYtGmTiqUS5b+sr68PoVAIV1fXDsseUKV6VVVVuHbtGj7//HPs27cPLBYL77//Pj755BOMHDkSxsbGbboHzUGhUKCyshLnz5/Ht99+i/r6ekilUmzZsgXLli2Dn58fnj171uw2tLW1YWtri8zMTLi4uCA/Px9yuRwWFhZgs9koKipq07FRmcp79+5h4cKFavvL6urqkJ6ejl69er2WvtuXQWWDDQwMVAT1SktLkZ+fj969e3d6VUF+fj6ePHmCiRMnNtq3VCrF/v37ERoa2iFCcFRFzpEjR7B06dJGrQokSeLKlSvw9PSEk5NTk/tPS0uDmZkZjI2NQZIkYmJiEBgYCCaTieDgYAwdOhTbtm1DRUWF2vEtPz8fkydPhq2tLXbt2gWhUNiu5/k6oKenBzMzM+Tk5NDiWa2ZhwmCoN0VKisrad0LoVDY7mJZEokEZWVl9BqiJY2NtoIStOTz+bT91osoLS2FSCSCnp5ekyX4XWgMsVgMoVBIe6G/jPLychgZGTVb3iwWi5sM+isUiq7S6C6oh56eHgQCgYptEuXx1hwYDAZcXV07vfz23wxqAn6ZCJuYmIDFYqGsrKxJ0koQz83oZ82ahQ0bNqCmpgafffYZzp07B7FYjJkzZ+LPP/+ks82UsnRBQQEeP378WkmklpYWxowZg02bNiEtLQ3ffPMNMjIymiXoLBYLffr0wSeffAKBQIAvvvgCiYmJb5yYFpPJhJOTE6RS6SupdcfHx8PX1xcpKSno3r272sVaVVUVDh48iAULFjQpJiGXy3HkyBFafK2jFgMUCIJASEgIrl+/DqlUCi8vL9TU1DQiJkqlEiUlJTh27Bi++eYbMBgMfPTRR5g9ezYsLS3btDimyuuePn2Kp0+fIjExEW5ublizZg08PT3bXAYlFotx7949fP/997CxsYGPjw8mTZoEHR0d2NnZwdTUlFY/bu7YCgsLsXXrVjAYDKxdu7aRTYxIJEJZWRkMDAxQVVXVIdlGSvH5/v37+P7777Ft2zbU1tZi7ty5+PjjjzFhwgRYWVm1+35JkkR9fT0ePXqEbdu2Ydu2bZDJZFi+fDm+++47VFdXQ0tLCwwGA0OGDMGdO3datI3z8fHB06dPYWhoCKVSibq6OlhbW0MsFrepZJPq/T1y5Ajee+89tSV3CoUChw4dorUcDAwMWr2f9oZUKsXFixdVFJFJksTly5cxbNiwTl98y+VynDhxAmFhYY0COUqlEv/88w9MTU1pHYv2RkVFBa2cr06oqrS0FBEREQgLC2vyOSdJEnfu3KH1DWQyGeLi4mgvYeo5HTt2LL7//nsUFxc3el6zs7Ph5uaGqVOnwtnZGTt27EBdXV27n29ngslkomfPnoiOjoabmxtKS0tbLUxnYmICJpOJqqoqsFgs6Orq0n7LL6+FXgV8Ph8sFgv5+fnw9PRst+2+CMo6ydTUFAqFotH8KhaLcfbsWTpTrKur2yHH8b+I/Px8WFhYNJnRLSsra3GtQNnbqcN/PSP83z1zDUBlhF1dXcHn80EQzz1iS0tL4eDg0OTfEQQBDw8PPH78mPZa7ELzoDJTLys6GxoaQkdHB3V1dSpiP+pAEATMzMzwzjvvoKamBjdu3MCXX36JgIAA6Onp4dq1a5gwYQJdajx37lzs3LkTTk5OTZKnzgBF5JcsWYLk5GQcOXIETk5OCAsLa7KEiSAI8Hg8zJo1C9nZ2fj9998RERGBt956640pOSIIAq6urnj06BEyMzMxaNCgVm+joaGBJgba2towNDRs9B2JRIJffvkFY8aMUWstAPyfIqtMJqMzwZ0BR0dHcDgcZGRkwNvbG0OHDsX169cxb948KJVK5Ofn4/Lly8jLy8PQoUOxefPmVglMvQxK1Ck+Ph5Xr16FgYEBhg4dCh8fH7q3vC0BAIlEgtjYWFy6dAlWVlZYsWIFdHV18c0339C9SUwmE6GhoTh48CACAwPVRpgVCgUiIiJw7tw5zJgxAwEBAWoX4Hw+HxKJBPr6+sjNzcXChQvbdD1eBmVhk5KSgsjISJSWlsLT0xOTJ0+Gvb19h1YISCQS5OTk4N69e8jMzISjoyPGjh0LFxcXer9U2SIV9HFyckJ9fT0tgNUU3NzcEB4eDoIgYG5ujuLiYhgZGYHBYLSpMkkgEODnn3/GW2+9pVbVlWpDSEpKgru7OwC8Ef2fT548gb6+vko2uKKiAqmpqZgxY0anHgulXA0Afn5+avtyk5KSsGnTpg7pz6usrMRPP/2ECRMmqO2LlsvlOH78OMaPH99sEKO6uhqFhYXw9fUF8Dz7BEDleWQwGOjXrx+0tbXx448/Yvny5SoZ7tzcXAwYMAAsFguTJ0/GhQsXsGPHDqxYsaLZvsY3HT4+Prh27RpYLBZsbGyQnZ0NPz8/jf/exMQESqUSDQ0N9DqgoaEBOjo6r+wy8CLy8vJgb2+P7OzsFsUmX3U/dnZ2SE1NVRn/SZLE7du3kZWVBS0tLZr0d6FlUP3BXl5eTQarsrKyWrSUpIQ71W1fLpe/EW0trwtdRLgZ6OnpQSQSwcjIiO5RtbS01MgaydnZGefOnfvPq7FpCioa9XIUVFdXF/r6+igvLwefz2+WCFNgMBgwMTHBtGnTMGbMGISHhyM3NxfXrl2Dh4cHHRG1t7dHcHAwDh8+jJUrV77WiBhBPPce9vHxwccff4zr16/jiy++QGhoKPr379+kMBKlSL1p0yaEh4fj66+/xtixYzFo0CCNxJQ6Gi4uLrT/XVuQk5MDCwsLpKSkoEePHo0WjEqlEmfOnIGFhQWGNGH7IZfL8ccff0AikWDBggWdumCnssJXr16Fp6cn+vbti6tXryIyMhL3798Hn8/HqFGjMH/+/FciYRQBfvjwIa5fvw4rKyvMmzcP9vb2iIuLQ3R0NDgcDgQCgcYlxtQEGRcXhwsXLsDExASLFy+mRbVIkkTPnj0RHh6OSZMm0SrVpqamiI2NVRFWosQ8fv/9d/D5fGzYsKFRFvhFZGVl0USOw+HQNlBtuS7Ac2L37NkzREREoLS0FE5OThg5ciTc3Nw6jPySJAmSJFFSUoKHDx8iPj4eenp6GDx4MGbOnKkieEWBwWBgxIgRuHnzJnx9faGlpYWePXsiIiKCvsbqYGJiAqlUioaGBnh6eiItLQ3Dhg2je+tbE/GXyWQ4cOAAAgMD1ZYSU+W+ly5dQkhICOLj42FkZNThFRYtgcoGz549W+W5u3nzJgYMGNDp2WCxWIzTp09j8eLFKteeJElUV1fjjz/+wIoVK9q95J8kSdTU1OCnn35CcHAw+vXrp/YexsTEQCwWo3///k0+VyRJIi4uDj4+PtDS0gJJkoiKikKvXr0ajcUEQSAgIABaWlrYuXMnlixZAjc3NygUCtTV1dFBTCpgxmQy8dNPP2H16tUd0hvdGTAxMQGXy0VRURF69eqFmJgY9OjRQ+NzMTY2hkQioYNgJiYmqKmpgb6+PgQCQbscI0mSSE9Ph52dHTIyMtSqObcXKioqYGdnByMjI/qZJ0kSZWVlCA8PR1BQEKKjo8Hn87uIsIYgSRIpKSmYM2dOk5+XlJSgb9++zW6HEjBrCv9lIvzfPXMNQBFhHo9HC46YmZk12Qfz8t8qFIouwSwNQU0cL/cXUlFSJpPZ6j5Tqod40qRJ2LZtGxYvXoyFCxdi69atSE5OhkKhwPDhwyGXy3H37t03os+WIAhwuVyEhoZiw4YNiI+Px9dff02Lcqg7RkqResyYMdi4cSOePHmCrVu3oqCg4LWfE4/HA4fDAZ/Pb7UKJrUICwwMRHx8PAICAhplVZ4+fYqkpCTMnDlT7UCuUChw7tw5VFVVYcGCBZ2+WH9RZTk/Px9JSUnIysrCnj17EBwcjM8++wyDBg1S29OsCV4W1srIyMCKFStUhLVsbGxQXl4Oa2tr5Ofna7RNsViM+/fvY/PmzYiIiMD8+fOxevVqFSEsShAsKiqKLglkMBiYNGkSLl26RAe1lEolLdJlb2+PDz74oFkSTAm7aGtrQy6XQ0dHp9XiLkqlEkKhELGxsdi+fTs+//xzxMbGYvjw4fj888/x3nvvwcfHp83XvSlQYlt8Ph+3b9/GF198gZ9//hkcDgerV6/Ghx9+iP79+9NiW+r27ePjg5KSElRWVoIgCPTp0wcxMTHNtj5oaWnB2toaOTk5cHd3R1ZWFrhcLvT09FBfX69xT6ZSqcT58+dBEARCQ0PVEiihUIhff/0Vs2fPRm1tLbS1tWFtbf1aiQyVYTUwMFDpda2trUVCQgKGDRvW6cdz48YNuLu7N8qoUzoFo0aNandfXZIkUVlZiW3btmHYsGFqg4NUVcTp06cxZ86cZgMkcrkcERERGDJkCP3/8fHxTfZaEwSBbt26YenSpdi7dy+ePXuGyspKaGlpqQSxGQwGxo4dSwttUYr2/zYwmUz4+/sjNjYW3bp1Q2ZmZqOqtubA4XDAZrMhl8shFothYmKCyspKGBgYtFtGWKFQICsrCzwer0N7c6lgp1gsVlGMVigUOHr0KCZMmAClUkmLgnX1CGsGiUSChoaGJvuDFQoFampq1PZkv4jmeoQB/CsDUe2FroxwM6AmCDabTYsYmZubo7KyskVfVC0tLVhZWSE3Nxfdu3fvrEP+14JaFKojSw4ODsjKykJWVhYCAwNbtV3qHuno6CAsLAy5ublgsVg4e/YspFIpgoOD8fbbb+PHH3+Eh4cHbGxs3ogBgSrDX7lyJRITE3Hw4EE4OzsjLCysSR9hqixy5cqViIuLw+7duxEUFISQkJB2X/BrCi6XCysrK2RnZ6O8vLxVtg0ymQwZGRkICgqCTCZTKcV7MauydOlStZOqUqnErVu3kJycjNWrV7+W0k2KVOrq6mLZsmUYPXo0Nm3ahLNnz8LT07PN1SJKpRI1NTW4desWoqOj4evri3Xr1qm1rDA3N4dIJIKpqSlycnIaBRRePNaGhgY8fPgQt27dgr29PRYvXtysCjSPx0P37t1x//59hISEgCAI2Nvbw9zcHDExMfDx8cGpU6dQUFCA999/X22Z7ctQKBTIzc2lJ20bGxuNotUU+U1NTcXDhw9RWFgIBwcHDB06FK6urtDV1e2wd4CyukpLS8Pdu3dRUlICLy8vvPPOO7C3t2/VfeZwOOjVqxciIiIwYcIEWFpaQkdHB9nZ2XQZ8st4sU84LCwMNTU1IEkSenp6qKmpoUUfWzqHqKgoPH78GBs2bFBLkBQKBf744w90794dvr6+uHTpEiQSiYq38OuAVCrFuXPnMHfuXBXf4Nu3b6NXr16v1G7QFtTU1ODu3bv46KOPVJ5dyoaIIIgmK1jaCqqve/fu3RgzZgwGDBigdvtKpRLHjx/HoEGDWgxgUHoG1LxYVFQEbW3tJhflwP+1xKxYsQK7d++Gl5cXrKysGmWQGQwGRo0aBQaDgR9++AFr1qx5rS1KbUVAQAB++eUXhIaGwsDAAMXFxS2WqVIgCIIelyorK2FoaIjq6mo4ODi0GxGWSCQQCASora2Fi4tLu2xTHQQCARQKhQoRJkkSDx8+BEE8t9g7duwYdHV1aauoLjQPkiSRm5sLMzOzJitHamtr6aRPc2iOCP8bg1Dtia4nsRlQQhBMJpOO8pmamoLP50MmkzW7sKbUidPT0+Hr6/tGkKs3GWw2G0wmEwqFolGQwcHBAQqFAkVFRS0GIJoDi8XC3Llz8e2332LdunUQCAS4cuUKzp8/D319fezZswdbtmzpEDudtoLJZMLPzw8eHh64efMmvvrqK4wePRoDBgxosqSTyWSiV69e8PDwwJkzZ/Dll1/inXfegYeHR6eXvzCZTDg6OiI5ObnV/oVURqyoqAienp4q2Vy5XI7Dhw8jODi4yR7GqKgo3L59Gx988AH09PTa7Zw0gVKpRGVlJW7duoXY2Fi4urrCwcEB77zzDgwNDREZGYnExMRWq9hS78HVq1eRmZmJPn36YOPGjbSisTqwWCzo6enBxMSEFrJ68bvUsd6+fZvObKxcuRKWlpYaPS+jR4/Gtm3bMHjwYPo6h4aG4rPPPoOxsTEGDRqEWbNmaVyCLBaLIRKJQJIkMjIyMG/evCa/S5H3zMxMPHz4EHl5eXBwcMCAAQPg5ubWoQSIsuIqLCzE/fv3kZycDCsrKwwaNAgeHh5t9hcmCAKDBw/G9u3bMXr0aGhra2PgwIG4e/cu3Nzcmtymm5sb7t27BzabTbsW8Hg85OTktFhmSZVPnjlzBuvWrVNbtkj1BdfU1GD27Nm02JhcLoetrW2rz7O9QJX5mpmZqShXNzQ0ICoqChs3buzU+VepVOLcuXMYPHiwSiUDSZIoLS3FlStXsGHDhnZtmaLelf3792PatGkIDAxs0j4uKioKVVVVmDt3brPXhRLJGjBgAJhMJk1qevfu3WJPM0EQcHR0xJo1a7B06VKMGzcOSqWy0TExGAyMHDkSLBYLP/zwA1avXg1TU9N/1XrJ2tqaHkMDAgIQGxvbrAL3iyAIglb2r6iooK06nZ2d240Il5WVwdDQENnZ2S2Wz74Kqquroaenh/Lycnh5edG/O3fuHNatWweSJFFbWwstLS1wOJwuIqwhnj17hm7dujX5PFVXV9PuHM2hKSJMVTH9l0uju57EZvAiEZbJZLQSHtU711KGydPTE3/88ccrkbf/EppSSjQ3NwebzUZ5eTmkUukrZfbMzMwQEhKCkydPYtmyZVi2bBkqKytx7do1nDhxAt9//z1mzZqlsRdqZ4Agnvsmjx8/Hn369MGJEydw//59zJgxA+7u7mqPkxLTmjNnDtLT03H06FG4uLhgypQpnd6P5eHhgUuXLtE2K5ri2bNn8Pb2RkxMjEp/JEmSuHbtGjgcDgYPHqyWBCcmJuLMmTNYv369WoGtjoJSqURBQQGuXLmC7Oxs9OvXDx9//DEMDAzw119/4f79+wgNDcWYMWPw999/IzAwUKMFgVwuR1paGu3dO3z4cLz99tsaky1HR0cIBAJUV1fTgllyuRw5OTm4du0a8vPz0a9fP3z44Yfg8XgaP/vUQs7d3R1RUVEYPnw4SktLcfr0aVRUVGD8+PEYP358q96l8vJy6OjooLq6GvX19Y1IFkV+09PTERkZifz8fNja2qJfv3549913weVyO/TdVSqVKCsrQ3R0NGJjY8FmszFgwABMnDgR+vr67bJvMzMzGBkZIT09Hd27d0dAQAAuXboEgUDQZFDH0tISIpEIDQ0NcHJyQkZGBh0gaclLuLy8HPv378eiRYtgYWGh9pnKzMzElStXsGnTJmhra6O6uppeQL1OxWipVIoLFy5g6dKlKtng8PBw+Pv7d5hnalMoLCxEWloatmzZonIdFQoFDh8+jEmTJrW5510dlEoloqOjcerUKbz33ntNCgYCz0nR33//jfXr17cY8BUKhUhKSqJtn2QyGZ48eYK1a9dqTPKsra3Rq1cvPHjwAI6Ojhg+fLhaMjx06FCwWCxs27YNa9asabZ14k0Dg8GAj48PEhMT4efnhz179mDy5MkaEz1ra2tkZWWhsrISxsbGUCqVYLFY7WK/SQVI7O3tkZycrDFBbwuqqqpgbGyMyspKWjn6jz/+QHBwMCwtLen2KC6XCxaL1UWENURKSgpmzZrV5Oe5ubnNivdSaC4j/LJWxX8NXU9iM2AwGGCxWPS/AoEAurq6YDKZkEqlLTb7m5iY0C//6xYSedNBiUWp66mmIsQCgQAikeiViDBBEBg0aBAePXqEuLg49O7dm1aaDgkJwYoVK7Bp0yZ069YNo0ePRvfu3cFms9+IQYIgnqtiL126FCkpKTh69Cjs7Owwbdq0JiOCDAYDHh4e2Lx5My5duoQvvvgCU6dORc+ePTtEqVQdqD44ykJJk2tJ9ZUOHDgQjx8/pjM9JEkiOzsbd+7cwSeffNIoq0L5Zv72229YvXp1pyyoqIhqWloaLly4AD6fj5EjR2LOnDkqJenDhw/H999/j1GjRtEiYnl5eXB2dm6yVFkqlSIuLg5XrlwBh8PBuHHj4OPj02ohNBcXFyQlJQF4HkHOzMzEzZs3AQAjR46kRcTaeq1CQkLwww8/oKKiAjExMQgNDcXUqVOxb98+jBkzRuN+MGrhRpXTU364FPl99uwZHj58iJKSEpr8zps3j95+R4leAc/LXePi4vDw4UNIJBIEBgZiyZIlsLCwaLLft60gCALDhw/HrVu34OPjA319fdjZ2SElJaXJYBKbzYaFhQWKiorg7u6OpKQk2NvbQ6lUori4uMl9NTQ0YMeOHQgLC4O7u7vawFJtbS3279+PhQsX0uWrNTU1dLC4sysuXjy2+/fvw8HBAXZ2dvTvGxoa8ODBA2zatKlTx265XI5Tp05hwoQJKotOkiQREREBNpuNoKCgdjkmyv/64sWLiIuLw/r169W2RlAQiUTYt28fwsLCaAub5rYdHx8PV1dXOsiRkZEBQ0PDVpF4hUKB+vp6fPrppzhy5AjEYjHGjh2rViRu0KBBYDKZNBlu7lzeNPTq1QsnT56ke6mrqqqaVXmnQLUzkSSJqqoqeHt7A3j+LrdXRjgtLQ0+Pj5ISkrqUIVuqhqnoKAAOjo6iI+PR21tLYYNG0YnOWQyGT0ndhHhllFfX4/6+vom31dqvdOjR49mt6NUKiGRSJqch//rybquJ7EZEAQBfX19CIVC6OjooL6+HgYGBjA0NERVVVWLkWY9PT26Z+TFkq0uNAabzQaDwVBLhLW0tGg7gerq6lfO8LFYLMyePRs7duyAh4cHeDweCIKAsbExNm/ejH379mHEiBG4e/cuTp06hQEDBmDgwIEwMDB47VliKmDQrVs3bNmyBeHh4fjyyy8RHByMoUOHgsPhNBrQKDGtyZMno1evXjh69CgiIiIwa9asTilDMzQ0hKGhIUpKSiCTyTQKCgkEApSXl0MikcDBwYFeVIpEIhw6dAhz5sxplIWi+ob37t2LuXPntrsQzcugiGpCQgKuXLkCFouFsWPHwtfXVy1RpUo3Y2Nj0b9/f4wYMQJXrlzB0qVLG5Uq19XV4f79+3jw4AFsbGwwZ84cmjC35Zzs7e3x999/o6amBps2bUKvXr3wzjvvwMnJ6ZVIHLUYLygoQFJSElgsFrZs2QIDAwOQJAlnZ2dERERg+PDhGu8jLS0NDg4OqKmpgVAoRHJyMo4dO4aKigo4Ojpi2LBhcHd373DySwlDPXnyBA8ePEBNTQ28vb3pihHK8q0jQBAEvL29ceLECdTW1sLIyAhDhgzBjRs3mix7BQBfX188ffoUw4cPx6VLl+Dv7w+FQtGkl7BEIsHevXsRFBRE+8Kq+86+ffsQHBysQpRLS0vBYDBgbGz82pwRhEIhrl69irVr16r4Bt+4cQMBAQGd2nNKifeJxWL07NlT5VrW1NTg3LlzTfZet2VfQqEQR44cgVQqxfr165ttA6CskpydndWqSKvbfnh4OC1CSPVbDxo0qFVzYHV1NRgMBhwcHLBmzRrs3r0bIpEIYWFhalWn+/fvDyaTiR9++AFr165tsjrhTQJVBs7n8yEQCODt7Y3Hjx8jODhYo2M3MzOjxUCp54bFYkEoFL4yQVEoFCgpKYGvr6/aPu32RHFxMXx9fcFgMCCTyXDy5EmsWLFCxRFEJBLBwMCAznp3oXm05B+sVCpRUlJC63M0BaqitamMsFKpfOPfs47Em1H7+YaCakCvra2l1TepCJ4mFkoMBgOOjo7Iysr6zzejtwRKWKEplW1zc3MYGBggOzu7XfZlY2ODwYMH4/jx41AqlfTv3d3dMXjwYMTExGDFihVYtWoV6uvr8dVXX+HAgQPIzc2FXC5/7feTIrdjxozBpk2bkJOTgy+//JJWw1b3fUrIaP369ejRowe2bt2Kmzdv0kJwHQUulws7OzuUlpaipqZGo7/Jz8+HpaUl4uPj6QU6pWjr5ubWqGeGWhj+/PPPGDVqVIf25VPqmNeuXcOWLVvw6NEjvPPOO9i0aRMCAgKarCBgMBgYM2YMrl+/DrlcDn9/fxQUFKC6upput8jLy8PBgwfx1VdfoaGhAatXr8by5cvh6uraasJKHWdERAR+++03REdHw8zMDKNHj8aSJUvg6ur6SmROoVAgOzsb3377LW7cuIGPP/4YDAaDjvgzGAyMGzcON2/e1Eg9nyRJSCQSZGVlITExEU+ePKHLt0NCQrBlyxYsWbIEfn5+aq2H2gMkSUIgEODx48fYs2cPvvjiCzx79gzjx4/Hli1bMGvWLDg7O3eKNZm2tjb8/f0RFRUF4HmLQVlZGWpra9V+nxq/MjMzoaurS+tYMJlM+hl7EXK5HCdOnACPx6OzdC9DoVDg5MmTsLKyojM7FHJycsDlcmFpaflaFlFUD6uXl5dKxqSurg6RkZEYPXp0px6XRCLB33//jWnTpqks8qlrOGLEiGbtSzQFSZIoLy/H999/T1cI6evrN3muSqUSd+7cQUlJCd566y2NiGxhYSHkcjmcnJwAPM+w5+TktFr4s6Kigq7KMTAwwIoVK1BQUIDff/9dbRsUQTxXSZ8yZQp++OEHFBcXv/a5VhOwWCy4ubkhJSUFPXv2RExMjMZ/a25uDolEgvr6elopnyAIiMXiVz53KqtcWFhI9+12BJRKJSoqKgAA+vr6OH/+PPr16wdbW1v6uaypqYFSqYS2tnYXEdYQiYmJzdpxiUQiCASCFqs05HI55HJ5kz3CQJdqdBeaADV419fXQ19fH3V1dXR5KvXStwQfHx/cv3+/0+0b/o0gCKLJBbOzszPKyspaVV7b0r5GjhyJ7777DvHx8XS5IUE8933dtm0bHjx4gCFDhmDGjBkIDQ1FbGwsDh06BA6Hg2HDhqF79+4dqkSr6XmYmZlh0aJFSEtLw19//QVzc3NMnTq1ydKyF4//+PHjiI6OptVtO+JcCIKAk5MTIiMj6UBCdXU1LTqno6MDAwMD8Hg88Hg8uqzK1dUVDx48gKenJ10y++TJE5pwvQi5XI5Dhw7RgYyOOA+lUony8nKEh4cjISEBvr6+WLFiBSwsLDSOtDs5OYHFYiE9PR3e3t7o3bs3rl69Cm9vb1y7dg1CoRDDhg3D9OnT2yT0RJHJvLw83Lt3D+np6XBzc8Nbb70FqVSKIUOGIDExsS2nr7KP0tJSnD17FgUFBQgLC0P37t3BZDKRmJiI6OhoWrHWwsIC3t7euHXrllqyRQlOlZWV0X7HiYmJsLW1hUKhwPTp0zFv3rwOz+xLJBLk5ubiwYMHyMjIgLW1NQYMGAAPD4/X9o4TBIGBAwdi7969GDlyJDgcDnx8fGg7IHXHZG1tjfr6esjlcpiZmaG+vh5aWlqoqamBQqFQ8fYMDw9HYWEhVq9erXZRSoljFRUVYdWqVSrPOPUMCASCDlWibQ51dXW4c+cONmzYoHJcN2/eRGBgYKf2BlP7dXJyUml1oDxAS0tLWxSn0nQ/ycnJOHz4MMLCwhAUFNQssaVspa5fv47169dr1FZEncugQYPoTP/Tp0/h5OTU6hL4zMxMuLm50f+vp6eHpUuX4uDBg/jtt98we/bsRotzgiDQu3dvsFgs/Pjjj1i5cmWHV/e0B4KCghAeHo5FixaBz+ejrq5Oo1JkKqgnEomgra0NhUIBhUIBiUTyyiJGubm5sLCwQH5+PgYOHNhh11AkEtEZ7KqqKohEIsycOVNlf1QwjiAIWhy1C01DoVAgIyMDAwcObPI7AoFAIwVumUwGBoPR5LPUJZbVhWZBZYINDQ1p8QILCwvExsZqRMhsbGzoqOabPpC/TrBYrCZ7hAmCgK2tLVgsFgoKClQWdK8CLS0tvPvuu9i+fTvc3Nzokms2m40FCxbgm2++gaurK+zs7KCnp4fBgwejf//+yMnJwfXr1/HPP/+gR48eGDx4MG0v8bruMZPJhJeXFz766CPcv38f3333Hfr374/Ro0eDy+WqLZc2NTXF0qVLkZCQgF27dqF///4ICQlpV5shimRQ3rDffvstevToAWNjY/B4PLDZbAiFQtTV1aGurg5CoRDm5uZ49uwZpk2bBgsLC+jo6NBlgLNnz25kI6BUKvHPP/8AACZNmtSuEyzV/5uTk4PLly+jsLAQgwYNwieffNIm0TGCIDB27FhcvnwZVlZWkEql2LFjByZOnIiJEyfCzc2t1T3p1DEWFxcjMjISjx8/hp6eHgYNGoQZM2bQCy1KiVQT+7em9lNVVYXz588jJSUFo0aNwrx581TK8ceNG4d9+/YhKCiI/v3YsWOxdetWDBo0iPYSpYhnTEwMUlNTwWKx4O/vj4EDB8LExAQ1NTUwNDSEh4dHq46xNedClXQ/fPgQSUlJMDAwwIABAzBt2jTo6uq+EQsDS0tLcLlc5OTkwM3NDf3798eff/6JwYMHqx0DWSwWeDweqqqq4ODggKqqKujq6qK6uhoSiQQsFgskSSIhIQG3b9/Ghg0bmswSpKSk4OrVq2q/I5fL6XLrlvpNOwIkSeLWrVvw8/ODiYkJ/fzV1tYiMjISH3/8caeOxeXl5bh161ajIJ1UKsXJkycxc+bMV9YJUSqVuH37Nq5fv45ly5bB0dGxxXPMzs7G77//jpUrV6pcp+ZQX1+PZ8+eYcqUKfR+7969iwkTJrR6XMrOzm5UIszlcrFo0SIcPXqU7jt/uXeRIAgEBASAyWRix44dWLFiRYcFatsDBPHcMurYsWMgSRKOjo5ITU1FUFBQi3/LZDKhra0NkUhEl6HLZLJXzghTSvD29vaIiopql2qEpiAQCMDhcFBWVob4+Hjs27ev0ZjB5/Pp8+uyT2oZfD4fIpEIVlZWTX6nuLhYI3cHmUzWbPvKf52fdD2JLUBfXx8FBQWws7NDfn4+gOcTf1lZGZRKZYuLbspvr6qqqkXD6/8yqAGyqYywra0thEIhgOeLsPYaRG1tbTF06FD8+eefWLx4MV0qampqipkzZ+LXX3/Fxo0baTLJZrPh5uYGNzc38Pl8PHz4EPv27QOHw8HQoUMRGBhIE7XOHliocunhw4ejV69e+Oeff/Dpp58iLCwMgYGBjcpgqV6knj17wsPDA8ePH8cXX3yBuXPnNing1BoolUo8ffoUf/75J/T19WFlZYV+/fphzZo1ardN9dxGRkbi4sWL2L59O+bPnw+SJHHhwgV4e3vDw8OjUUn0o0ePkJiYiA8//LDdROmoxUhiYiIuX74MmUyGMWPGYPHixWr7sDXdplKphIGBAW7evInMzEz0798fkydPRp8+feDt7a3xdqltUerFcXFxAIDevXtj9erV9KL3xe05OTkhJycHcrkcAoGAJqUt7Qd4XtZ2+fJlxMfH0xlrdQEWW1tbWFtbIyYmhu5FNDY2pp9HLy8vPHr0CPn5+fTvR40aRfeqX7hwAXZ2doiPj4dCoWjXTBB1zYqKivDo0SMkJCSAw+Ggb9++WLduHS049yYtCJhMJoYMGYLw8HC4ubnB1tYWIpGoSTEegiDg6emJ1NRUeHh4IDw8HLq6uqirq4NUKoWOjg5ycnJw9OhRrF27Vq0nOUmSqKiowIEDB7Bs2TK11lwCgYAubW3OU7YjQJIkampqEBERgY8++kjl9+Hh4ejdu3eHigK9DLlcjqNHj2LChAmN7JIePHgACwuLZm2vNAHVc5mbm4sNGza0aJdCkiTy8/Oxe/duLFq0SOP3iCRJREdHw9PTkx4fysvLUVtbq5LZ1QRSqRRlZWUqImYU2Gw23n33Xfz111/YtWsXli1b1kgBnyAI9OjRAwwGgybDmviQvy5oa2vDzs4OGRkZCAoKQkREhEb2eEwmE0ZGRhAKhRCJRNDX14dCoYBUKqXbttqKjIwMDBgwAHp6eh0q2Mrn82FgYICEhATMmDFD7fPO5/PpdZuOjk4XEW4BBQUFsLa2bpJjkCSJnJwcjfSHKCLc1Lqriwh3oVkYGBigoaEBRkZGePLkCYDnL7FYLNaICDOZTFhbW6OwsLCLCLcAqj9PHV4UyOLz+e3m9UsQBIKDg7F161YkJCQgMDCQXgwHBAQgJSUFp06dwqxZs+iBgvrX0NAQISEhCA4ORnZ2Nm7duoXz58/DxcUFgwcPhouLS5tJ06ueE2WdlJeXh+PHj9PCJ+psoagWgIULFyIxMRH79+9HYGAgxo8fr6J63BoolUpcv34d9+/fx6JFi+Dg4IDCwkJaCVjdpEwReaVSienTpyM6Ohr37t0DAMTHx+OTTz5ROXZqIqDsQDRVJm4O1DMYGRmJ8PBwmJqaYsqUKXB3d2/zxE0FeBISEnDz5k0oFAqMHDkS+vr6eOedd5CXl4cDBw5gwIABLUZtFQoFKisrERMTg5iYGJAkCX9/fyxatKjZSRN4rhwdEREBIyMjFBcXt5htVSqVqK6uxpUrV/DkyRP069cPn376abNWOQRBIDQ0FL/88gt69OgBgUCAJ0+eICkpCVevXsXkyZMxYsQIzJ49u1FGncpgDBo0CGVlZTAwMGg2Gq4JqN7r8vJyPHr0CPHx8WCxWAgMDMTy5cs19kp+XSAIAt27d8fZs2dp14KAgABERUUhNDRUbaWHu7s7wsPDERAQgPLycrpfWCwWo7y8HDt37sT8+fNV+vdehFAoxJ49ezBlypQmA2ICgYDuQe5M0knh4sWLGDhwoAqR5/P5iI6OxocffthpYy6lBq1UKtG/f3+V/dbX1+PKlSv44IMPXqlKRSAQ4ODBg2Cz2VizZk2L4xxJkigoKMDOnTsxd+5ceHp6anw9ZDIZ7ty5g4ULF9LbioyMRK9evVo9/tXV1YHJZKp116CCsDNmzMA///xDl0C/PLYQBAFfX1/MmzcPO3bswPvvv9+hFkCvAgaDgV69eiE6OhozZszAiRMnIBKJGlUwqfs7CwsLZGdnQyAQwNjYGAqF4pUzwjKZDLW1taiurqb1IDoKeXl5kMvliIyMxOLFixuNqVTwSkdHB0wm840QHn2TQbU0+Pn5Nfu9wsJCjYQoW0oedRHhLjQLHo8HPp8PLpdLkzQtLS3I5XKNo3WUdL2/v39HHuq/GpS4TlOWAdSEymazkZeXp5E1gaagotO7d++Gi4sLHdVnMBgICwvDd999h9jYWPTq1UvtYMFiseDu7g43NzfU19cjKSkJFy5cQE1NDXr06IF+/frBysqq022YCOK5muUHH3xAlyt5enoiNDRUbUaBwWCgR48ecHZ2xpkzZ/Dll19i9uzZcHNza/WklZCQgNjYWKxfvx48Hg8kScLOzg5xcXF0YOllEiSTycBisRAfHw8PDw+4uLhg1qxZmDFjBjZt2qTSn0ZNrPv378fcuXNf2WpDqVSisrISt27dQmxsLLy9vbF8+fJXUtpUKBQoLy/HnTt3kJCQACcnJ8yYMQNOTk4Qi8X44osvwOfz4eDgAC6Xi/T0dHTr1k1lG1RpeUVFBeLi4vD48WMoFAr4+flh4cKFsLS01Fix18jICPX19fDy8kJ+fn6TRFihUKCsrAxXr15FSkqKxqXgSqUSQqGQFtZZsWIFbG1t4eXlhXfeeQf+/v6or69HQECA2ueJJElUVlaCyWQiNzcXPXv2bLPqr0wmQ3l5OWJiYhAfHw8Gg4GAgAAsXboU5ubm/6pshL6+PpydnfH48WMMGDAAffr0wb59+zB27Fi15+Hg4IDS0lLo6OioKIXm5ubi8uXLmDp1Knx8fNTeS5lMhiNHjqBbt27o06dPk/e7uLgY2tratOJ+Z4HqTU5KSsInn3yi0ot77do19OnTp1OJeVlZGc6fP4/169c36qE+d+4c+vbt2+aSVGqM2717N7y8vDBx4sQW33WqHHnfvn2YPXt2q0UDs7KyoK2tTQdJxGIxYmJisHLlylbf55KSEtparCkwmUxMmjQJXC4X33//vdoSboIg0K1bNyxcuBC7du3CkiVLXjnD3lHw9PTEP//8Ay0tLRgbGyM/Px+enp7N/g1VgUYFHs3MzCCRSNDQ0PBKGeGysjJwuVwUFRU1qQjfXsjNzcX9+/dhZGSktkKEaquhgiKvI3j2b4JMJkNmZibGjBnT5H2jtDVsbGxa3J5UKm2xIuC/HJj496wGXhP09fXR0NCgQoQ5HA64XC5qa2s1ImSurq64f//+f74hvTlQfs1U+fPLYDAYsLGxQVVVFXJzc5skpW0BQRCws7PD0KFD8ccff2DJkiX0okZHRwcLFy7Etm3bYG9v32w/HJVZ7du3L4KCglBTU4OYmBgcPnwYcrkcgYGB6NWrFywtLTvUeuVlsFgs9OrVC926dcPNmzfx9ddfIzg4GIMGDVIrVGJgYIDZs2cjNTUVv/32G7y9vTFp0iSNRYMEAgEuXryI9957DzweD0qlEjU1NTAwMEBWVhY++ugjTJ06FUOHDqW3V11djQ8++ADOzs5ISkpCcXExBg0ahLS0NPTp0wcxMTEYPnw4fbxSqRT79+/HsGHDGilItwYKhQK5ubm4evUq8vLyMGDAAHz00UdqS0Y1AUmSEIvFSElJQXh4OKqqqjBgwABs3LgRhoaG9PtP9cTeu3cPoaGhGDNmDK5evQpPT08wGAwIBALk5eUhOjoa6enp0NbWhp+fHxYsWABzc/M2BVW0tbXB4XBgaWmJ9PR0jBw5UuVzuVyO7OxsXLlyBSUlJRg+fDjeeuutZu871SualpaG+Ph4FBcXw8zMDJMmTcLDhw+xbt06WtHW1tYWX3zxBcrKytRmevl8Pq10raWlBWtr61aNl3K5HKWlpYiNjUVCQgJIkqS9fk1NTTtF6bkjQBAEhg4dijNnzqBfv36wtLQEi8VCYWGh2rI4LpcLNpsNiURCkwqxWIxdu3bh7bffbnJRrFQqcfHiRchkMkycOLHZa5+fnw8WiwVra+v2PNUWQZIkTp8+jdGjR6sExqqqqhAfH4+PPvqo0+6xRCLB4cOHMWnSpEaBuOLiYjx9+hSbN29u8zhCZe+HDRuGIUOGtBiQe1FIa968efDy8mrVvqkqnuDgYPre5+TkQF9fv1XewRTS0tLg7u7e4veYTCbGjBkDHR0dbNu2DStXrmxkm0QQBLy8vLBkyRLs3bsXixYtalWmu7NgYGAAY2Njeo0SExPTqJ1HHShl7YqKChgbG6OkpAQikeiViHBeXh5sbW2Rk5MDBweHNm+nJSgUCjx79gw9e/aETCZTWwFAWbgZGBhAKBQ2W1XUhefVFEqlslmrUEpMTZNKuIaGBrX3BYCKa8p/FV1EuAWw2Wxa8l0ikUAul4PJZMLExATl5eUaEWErKys0NDSgrq7ulT1w/1dBlWaIxeImv2Nvbw8+n4/s7Ox2L+UgCALDhw/H48eP8ejRI5XForW1NcLCwvDLL780KS7z8raYTCZMTU0xevRoBAcHo7y8HFFRUdi7dy8IgoCfnx969+4NGxsbetHRkQMRQRDQ1dVFaGgo+vfvj7/++gt3797F9OnTaSL54v4ZDAa8vLzwySef4OzZs/jiiy8wa9YsjUhnbGwsnJ2d6UxIeno65syZg2fPnkEoFCIpKamRiIhCocD9+/dx5MgR+lgiIiJgaWmJrVu34uLFi0hPT4evry+9GDY2Nm5SPbc5UOWyT58+xeXLlyEWizF69GjMnz8fWlpabdoe8DwCf/fuXcTFxcHCwgKjRo2Cp6enWtJKEASGDRuGH374AaNGjYKPjw+OHj2KS5cuITMzEyUlJTA3N0fv3r0xYcIE8Hi8V/L7BZ6TbxsbG4jFYpSWltLHLZFI8PjxY1y7dg1KpRIhISHw8/NrVNZPfV8kEiEnJwfx8fFIS0uDUqmEm5sbhg0bBldXV/r9qKysRGJiIvr37w/gOUEbM2YMzp49q7Z8rrS0FCYmJigsLISBgYHaMv6XrzuVIYyNjUVsbCyUSiUCAwOxePFimJubd2rAqSPh6uqK+vp6lJWVwdLSEr1790ZkZKTankkWiwVHR0dkZmbCyckJT58+RX5+PkaPHo3Ro0c3mY1/+PAhHj9+jA8++KDFEv3i4mJIJBI4Ozu3+7k2h5ycHBQVFWHBggUq2eBz585hyJAhGvW9twdIksTFixdhaGjYKHOuUCjw999/Y9y4cU0uPlvadnFxMbZv347Jkye3qAxN/U1UVBROnz6NpUuXtrp8mOoLLy4uRvfu3UEQz+3qbt26hSFDhrQ6gE8JDE6aNEmj42AwGBg8eDC4XC5++OEHrFq1ihagpEAQBNzc3LB8+XLs3r0bCxcubDXZ72gwmUwEBgYiOjoao0ePxq1btyCVSlsUoKRaNIqLi6Gvr4+srKxXLo1OTk6Gg4MDHczoCJAkiaKiImRkZODjjz/G3bt31T4rlAq2np4eGhoaOlS4698OkiSRmpoKFxeXZiuXysvLYWRkpFFFGJ/PbzILT3GaN+k96mx0EeEWwGQyVaIulJgBZaGkCSFjsVgwNjZGRUVFFxFuAgRBgMPhQCKRNPm5vb09IiMjO8z3liqR/v777+Hu7k5HwQmCQN++fZGamorTp09j+vTpGpfLUqTYysoKEydOxIQJE1BSUoLY2FgcPHgQMpkM3bt3R1BQEK2M3dGE2NTUFMuWLUN6ejr+/PNP3Lx5E2+99Rasra0bLTy4XC5mzJiBXr164bfffoOzszOtqtuU8EJ8fDxGjRpFf25nZwdra2tER0cDeJ5lf3mRw2azYWhoqBIBj4mJAYfDQXp6OhgMBu7fv4/hw4fDwsICKSkp2LRpU6tKXKle3aioKNy4cQOGhoaYNGkSnYVt7cIReE4inz59ips3b4LP56NPnz5Yv349XR7WnDiFnp4eWCwWvvvuO0gkEpSXl+PMmTNYtWoV3N3d6TGnPSsfnJycUF5eDpFIhPz8fMTHxyMyMhI2NjaYMWMGXFxc6GtBHadcLkdZWRmePXuGhIQEVFVVwdzcHAEBARgxYoRK9uZFcjJ+/Hjs3bsXPXv2pHvNKYuR3NzcRov1nJwcODk54dmzZ9DS0lJLsl4UCYuJiUFcXByUSiVdKk5lkf/XJnWqqiMqKgoTJ05EYGAgfvrpJ0ydOrXRO0AQBDw8PJCWloYePXrgl19+AUEQTfZDkySJtLQ0nD17FuvXr2+x8oN6HqhxrbOutVwux8mTJzF58mQVYlFSUoL09HRMnz69U46FJEkkJiYiLi4OmzZtalQSnZGRgaqqqjaVo1IkeNu2bXQ7gSb9f5cvX8ajR4+wYcMGWniutQgPD8eAAQPoa1tXV4fc3Fy8++67rd6eRCJBdXV1qyoGGAwGgoKCoKWlhW3btmHFihWNlLEJ4rn6/fvvv49du3Zh/vz5r1QR1BHw9fVFeHg4pk2bBiaTicrKyhbLVw0NDaFQKMDn82FmZoa6ujrIZLI2Z4SVSiUKCgpgY2MDa2vrDhPKksvl2L9/P4yNjSESiZpMDFHiX1wuFxUVFW0KEP2XkJiY2GxrCqWPoql4HGUBqw5dRLiLCLcIFotFlzRzOBwIhULo6+vD0tISxcXFGm/H29sbycnJrVZe/K+AxWLRRLip4IKVlRVEIhFIkqQtrdoT1GJx3LhxOHz4MFatWkVH2xgMBmbMmIGtW7ciPj4ePXv2bPXAQWU6bWxsYGNjg3HjxqGsrAwJCQk4duwYhEIhunXrhp49e8LBwQHa2todVkpPLZY/+ugjREZGYvv27ejRowfGjx+v0gtK/evm5oaPP/4YFy9exOeff05nh18+PqVSSRMlCrq6uvjwww8RERGBiooKuuz1RbDZbLUelVKpFOnp6bSdy6VLlzBixAgcOXKkRRGSF4+ptrYWt2/fRlRUFFxdXfHee+/Bzs6u1deXEqwqLy/H3bt3kZCQAGtra4wbNw7u7u5qxdEoQimRSFBZWYlnz57hyZMnqKqqApvNRlpaGr755hvo6uri66+/hrOzs8bn1tpjd3BwwIULF5Cbm4tvv/0WQ4YMwdq1a+nSTqpXu76+HqmpqXjy5Any8/Ohra0NDw8PTJw4Eba2ti2SJYIgYGVlBXt7ezx69AiDBg0CQTwXQ5swYQJOnTqFdevWqZAISkX7woULMDU1pfsUX/Qajo6ORkJCAt3PPn/+fNjY2PzPT+QEQaB///7YtWsXQkJCYGZmBi6Xi9zcXLi6ujb6vqurK65duwYDAwMIBAI4OzujsrKykcAjSZIoKSnB/v37sWzZMo0yNTKZDA0NDSBJstOsk6iyX5lMpkIOlUolTp8+jTFjxnTa4rqsrAy//fYbVq5c2WhxSdklvfXWW63uQ6eyaz/99JNGJJgK7P3+++9oaGjAxo0b2+Q9DjwXSEtISMCmTZvody4qKgrdu3dv01hUX18PDofTagJGVUtxOBzs3LkTixcvblRaTAX0VqxYgV27dmHOnDl0FvtNgJmZGTgcDkpKStCjRw96jmju+KhrJRQKYWxsDLFYDAaD0WRioCXw+XyIxWLU1NTA3d29Q64NSZK4d+8e+Hw+rTvh5OSk9rsKhQJCoRCGhoZ4+vRph8xv/yuQyWQoKCjAzJkzm/1eTk4O/Pz8NLq31LVX9125XN6sx/B/AV1EuAUwmUwwGAzIZDLazxR47g8cGxur0TYo0nHhwoWuPuFmwGQyIZPJaDXSl8HlcsFgMKCvr4+ioqIOya4TBIFBgwYhISEBd+/eVVHko/wPt2/fDltbW1haWr7SBEMpiltbW2PUqFGorq7G06dPcenSJZSXl8PGxoa2NjIyMuqQTBeHw8GgQYMQEBCA69ev44svvkBwcDAGDhzYSDGay+UiLCwM/v7+OHLkCFxdXREWFqZCipRKJRQKRaOMeUBAABYvXoyvv/4aHA6n0YKbxWLRC1lqIcZkMjFy5EhkZmYiMzMTwPPy+K1bt2q0AFcoFCguLsa1a9eQlpaGoKAgbNiwAcbGxm0iwHV1dXjy5Anu378PoVCIvn37Yv369Wq3Ry1Sq6qqkJycjOTkZJSWlkJXVxeenp6YNGkSrKyswOVysXXrVjQ0NMDOzg49evTAw4cPVTLqrwpKaToqKgr379/H06dP0a9fP4wYMQLDhg2j+3xzc3Px9OlTZGVlQalUwtXVFUFBQZg+fToMDAxaTTYZDAbGjRuHPXv2ICgoiC6Z9vX1xbVr1/Ds2TN0796dPsaysjKYmZkhPz8fzs7OMDU1RXZ2NqKjo/H06VNwOBxa8MrMzExjkbD/FVDkNy8vD+7u7ujXrx8ePnwIFxeXRvdFX18feXl5EAgE6NatG+rq6lBVVdXo3eTz+di9ezdmzpypcZmzUCiETCYDl8vtNPIplUpx+vRpzJgxQ+X4c3NzUVJSgkWLFnXKcdTX12PPnj146623GvVdUuSRx+O1umSX6gnesWMH3n77bY1IcGVlJX755Re4uLhgzpw5bfZ/p8ri3d3daaFIhUKBe/fu4b333mvTOJSdnQ0HB4c2idIRBAFvb28sW7YMe/fuxaxZs9CjR49GZNjR0RGrVq3Cjh07MHPmTAQEBLwRZJjJZMLf3x9xcXEIDAzE77//jtGjRzd7LSjdGbFYDB0dHZAkSRPjtoDqNc7OzqZbU9oblZWVuHz5Mr39wsLCJn2TBQIBxGIxDA0NIRaL1Qa9u/AcFRUV0NHRafYaKZVKFBYWYvz48RptUygUNlmV0JUR7iLCLYLJZEJHRwcNDQ0qRFhfXx91dXUab8fOzg4VFRX0QNeFxtDS0oJQKGyyp4bD4cDAwABcLhcFBQWt8l1tDZhMJt59911s3boVnp6esLW1BQA6m0v1C2/cuLHdbJxYLBbMzc1pYRSRSITMzEzExsbi/Pnz0NXVRffu3dGjRw9YWVm1qZe1KRAEAX19fUyePBkDBw7EmTNncPfuXUyaNAl+fn4qEziDwYCLiws+/PBDnDt3Dl9++SVmzZpF3wuK0NbX16t4ajIYDCxbtgyXLl1CUVFRo15wFosFPT098Hg8SKVSKBQKzJkzB1999RWWLVuGzMxMaGlpYfPmzSpRUKqUMCsrCwMHDgRBEJDJZEhPT8fly5dRU1OD4cOHY/r06RqLfb0IqVSKrKws3L59G9nZ2fDw8KAXwS/2/lK2S2VlZUhLS0Nqaiqt3Ovl5YXg4GA6y//ypDN69GhcvHgRnp6eGD58OHbt2oVhw4a9UjkbSZJoaGhAUlIS7ty5Az6fj169emH16tXYtWsXvLy8cPv2beTm5iInJwcKhQL29vbw8fHBuHHjwOPx2kXl3NLSEs7Oznjw4AEdVGKz2ZgyZQp+//13eHp6gsPh0KWAlEBMdnY2duzYASMjI/Tq1QurVq2CkZHRf3rCZjAYGDRoEO7evQs3NzcEBATg+++/h0QiURmHqMxiUVERli1bhhs3biAqKgoSiQQKhYL+nkgkwi+//ILBgwe3ikQUFRVBR0en0xSjKW9bQ0NDFbVguVyOM2fOYNKkSR3qkUpBKpXi0KFD8PPzQ1BQUKNzb2howKVLl7Bq1apWBdoodWiqJ1gTEpyeno4DBw4gNDQU/fr1eyVrHJlMhvDwcCxbtozeb1ZWFrhcrkaKtE0d36tkIgmCgIuLC1auXIndu3dDLBY3uuYE8Vzkcs2aNdi+fTsUCkW7imi+CgICAnDw4EGMGjUKAoEADQ0NzQbuORwOTExMkJ2dDaVSCZIkoaWlBZFI1Kb9p6WlwdHREfHx8R1i26lQKHDs2DGEhISgqKgI9vb2SExMbLKipKamBlKpFPr6+hCLxZ3Wy/9vA0mSePr0KTw9PZt9p+VyeasCCs3ZeHUR4S4i3CIYDAZ0dXVpoSs+nw/gebmnWCyGQqHQKOqppaUFHR0d1NbWdhFhNWCxWLQtlVQqVfsdSjm6oaEB6enpGDVqVIccC0EQMDY2xrRp03Do0CGsX7+eXmgSBIHevXsjPT0df/31F2bPnt2uGX6qp1hPTw89evRAjx49IJfLUVRUhISEBBw5cgRCoRC2trYIDAyEh4cHjI2NG5Uyt3XfZmZmWLRoEXJzc3H8+HFcv34dM2bMoNVpKysrUVNTAzc3N0ybNg0BAQE4dOgQunfvjkmTJkFbWxs2NjbIy8uDvb093Usrl8uhUCgwceJE7Ny5E0ePHoWtrS1kMhk4HA709fVRW1tLR9JXr16NTZs2QVdXF/7+/jh16hRGjRqF6dOn09ebJEnk5+dj0aJFKCwsxNWrV5Gfn49r166BzWZj3Lhx8PHxaVXfNXW85eXlePjwIaKjo6Gjo4Nhw4bh3Xffpft2qQxxXl4ekpOTkZGRAT6fD0NDQ3h4eCA4OBhOTk7gcrl0SXxT6N69O06ePIni4mJYWVnBxMQEiYmJtKd1a45bKpUiLS0N9+7dQ35+PhwcHDB27Fjo6+sjPz8f//zzD+Li4pCdnQ2xWIxRo0Zh/PjxMDY27pDJkMoK//TTT+jbty+dQXRxcYGpqSmioqJoX9zHjx9jy5YtkEgk8Pb2xqZNm+hn+788SVOgykYvXLhAl1BSmV/KCosKDO3duxdDhw4Fn8+Hi4sLbty4QYs9UuX9f/zxB6ysrDBixAiNxzCKZMtkMo37014VQqEQFy5cwMqVK1Xe/YyMDAgEAo36aF8VCoUCJ0+eBIfDwYQJE9S2P5w7dw69evVqVd80SZIQCoXYsWMHhg8frpZgvwilUol79+7RqvzqqgFaiydPnsDU1JQmvZQV1fDhw9tEsKlA1ogRI17puF4mumKxGIMHD25Ehq2trbFmzRr8+OOPUCqVLV7DzoCtrS2kUinq6urg6uqKpKSkRj7TL4IgCJiYmCAlJQVKpRISiQRGRkZtygiTJInMzEw4OzvDwMCg3as2qMCUSCTCgAED8MMPP8Df3x9yubxJQaba2loolUro6OjQhLgL6vH48WOEhYU1+wyXl5dDX19fIy5BjTHNEeH/RV2N1qCLCLcAgiCgp6eH+vp6mJubo7y8HMBzIsxiscDn89X6pr0MJpMJV1dXpKWldarAyL8FVA92c0SYIAg4ODggLi4OtbW1HXo8BEHA398fiYmJuHjxIiZPnkwvwphMJqZNm4ZvvvkGkZGR6NevX4fcT2qbbDYbjo6OcHBwwMSJE8Hn85GVlYW4uDhcuHABLBYLXl5e8PPzg5OTE7S0tNo8sFGkw8nJCRs3bkR8fDx++eUXODs7Y8KECdi6dStu3LiBv/76C926dYObmxs2b96MEydO4Ouvv8a8efMQGBiIy5cvw83NDY8fP8aTJ09QXV0NbW1tmJiY4Mcff4SZmRntCy2VStHQ0IDp06ejtLQU9vb2kEgk+OWXX+Dv7w8zMzMYGhrigw8+UCGiubm5WLBgAW7fvg2CILBs2TIMHz4cs2fPhrOzs8YEiurhFQgESEhIwL1799DQ0IDAwEC8//77MDc3p615srKykJqaiqKiIigUClhYWMDb2xszZ86EtbW1SmZO0+vPZrMxbNgwXL9+HXPnzkVISAj++eefFrN0L5LfzMxMPHz4EKmpqdDX14ednR38/PxQUFCA33//HVwuF46OjujTpw9t45SQkAB/f/8OL1MzNzdHt27dcPv2bYwdO5YWhTE3N8fmzZvh7++P2tpahISEQF9fH/fv30dgYGAjP9EuAHp6enBycqLFVPr27UuXtRIEgZqaGuzcuRNvv/02WCwW7t27h6CgIIhEIojFYvD5fOjp6eHixYvg8/lYvnx5qwN5hYWFAJ5XOXU0SJLEjRs34OPjozJvyuVy/P333wgLC3ulbKgmUCqVuHbtGgoKCrBq1Sq1AaOcnBwkJiZiy5YtrXpm5XI5Dhw4gG7dumHo0KFN3guqT/706dPIzMzEhx9+qNYLvrWQy+W4dOmSSoCxqqoK+fn5WLhwYZu2KZVKIRKJ2sUrliAIWFhYYN26dfjpp58gFotV7J2o71haWmLNmjX46aefoFQqO9w3tyUwGAz4+voiMTERvXr1wq1bt5otUaaIsEwmo/tpm7OTbA4SiQRlZWWwt7dvl0DJy6itrcXff/+NtWvXgiAINDQ00JVgTe2rtrYWDAYDOjo6dNKjC40hEolQU1PTrMgcSZK0EJqm65uWMsL/VmvB9kIXEdYAlJewoaEh0tPTATwnQzweD9XV1RoRYYIg4OnpiZiYGAwZMqSDj/jfByaT2WJGGACcnJxw+/ZtiEQiCASCDl3EM5lMTJ06Fd988w18fHxURDu0tbWxdOlSfPfdd7CxsemU7Ai1fUNDQwQGBiIwMBBSqRQVFRVITk7G1atXUVZWBn19fXTr1g0+Pj6wtrame6tbc3xUZrpnz57o1q0b7t69i3Xr1uHSpUuoqanB4sWLcezYMTg5OUFHRwdz5szBkydPsGPHDri6utJk0s/PD2FhYTA3N4eenp5Gi26lUom6ujqUlpYiLi4OkZGR6NatG7S0tCCTycBms5GVlYX58+fj/v37NJEtKSnBrFmzYGxsrNE5UhNERkYGnUF1cXFBSEgIbeMTHh6O7OxsCAQC8Hg8ODo6om/fvrC2toaRkZFacazWgiAIDBgwAJ999hlqa2vh7u4OkUiE3NxctX2bSqUSQqEQ2dnZuHPnDqKjo1FZWQkTExMYGBiAxWKhrq4O5ubmmDhxIszNzWn7JeB5EO/8+fPgcrmor6/vlH6tkSNH4rPPPkNdXR3S09MhlUpp8S0LCwvw+Xz4+/vj9OnTsLW11XiS/6+Bspm5cOECgoKC4O/vj+vXr0MsFkMul2P79u0IDg5GQEAAKioqUFpaChsbG9q+pKKigra+WrduXasXpFRvGkEQtJhZR4EkSVRXV+PBgwf48MMPVbLBCQkJ4HK5He4lS5IkIiMj8eDBA5VA3IsQi8U4cuQIZs6c2arsm0KhwIkTJ8BisTBp0qRmCb1AIMCBAwego6ODtWvXtltVGaW9QIl4kiSJBw8eIDAwsM1tP0VFRTAyMtLI31QTEMRzp4N169Zh586dEIlEGD9+vEolHkE8F+dbu3YtfvrpJ8jlcgwYMOC16bFQlWOnTp3CkiVLaLux5q6pubk5nQ1WKBSQy+VoaGho9b4bGhrAYDCQm5uL4cOHv8ppNAJVGTFkyBBYWVmhvr4eBEGgrq6uSbVy6j3mcDjQ09MDk8nslFaGfyOys7NhYWHR4vudmZmpcZBDoVBALBY3OTZpWtX6v4z/9tlrCMr7zNHREfX19fTvjY2NUVVVpbEStJOTE86cOQO5XP6fE3ppCVRGmBLLago8Hg8SiQT6+vqoqKjo8EW8np4e3n33XRw8eBAff/yxSkmPubk5Zs+ejf3792Pjxo2vxSSew+HQKtTDhw+HSCRCZWUlnj59irNnz6KyshJGRkbw8vKCj49Pqwgp8HxC19HRwdChQ3H06FHU1NQAACIjI7Fs2TIcOnQIlpaWtK0NQRAQCATYsWNHoz5aTcFgMGBoaEiXGU+ePBmZmZm4fPkyrly5gj59+mDLli149OgRGAwGtLW1oa2tjYqKCmRkZMDf3x81NTW0EvKLIEkSUqkUBQUFuH//Ph49egQulwsHBwc4OjqivLwcJ06coH/n7OyMYcOGgcfjgcvldlj2SVdXFwEBAXjw4AHGjRuH4OBgXL16Fe+99x6kUikEAgHq6uqQlJSE6OhoJCYmorKyEo6OjnB3d8fEiRPh6uoKOzs76OrqNttDbmFhgerqajg4OCA/Px9WVlbtfj4vlo7HxsYiIyMD9fX1iI+Px8qVK2Fubk73Bn/11VeQSCQIDQ1Ffn4+bG1tYW9v3+7H9L8CZ2dn1NbWorq6GkZGRuDxeMjIyMDVq1fh7+9PZxaNjIygUCjAZrNhbW0NiUSCu3fvori4GB988EGbxisqSCWVSpu0SmlPnD59GkOHDlXRG5BIJDh79iwWLVrUoQs4inCfPXsWH3zwgcoxvPidq1evwtramhZ+03Tbd+7cQU5ODtatW9fseqC8vBw///wz/Pz8MHbs2HZbOygUCly6dAljx46l5wOxWIyoqCisXr26TdskSRJZWVlwdnZudxJqZGSENWvW4Oeff8apU6cwZcqURtfCwsJChQwPGdJ6D+T2goODA2pra+nKoYyMDPj4+DQ5LlPjcF1dHbS0tCAWi9tEhPPy8mBpaUn37rYXqP7V0tJSzJkzBwRBoLCwEGZmZigpKWkkHvciysvLoa2tTZOxLiKsHlSVVktrpvz8fAwaNEijbb5oXaUOVI/wfxldRFgD8Hg85OfnQ19fH/X19bS9j62tLYqKijTeDkXaGhoa1E6q/2UwGAwwmUxIpdJmLQN0dXVp5eji4uIm5frbCwRBwM3NDX379sXvv/+ORYsW0YMGQRDw9fVFTk4Ojhw5giVLlrzWyBrVz66rqwt7e3uEhIRAIpGguLgYSUlJOHHiBGpra8Hj8eDq6gofHx/Y2to2K3pD9ZeUlJTg6dOn4HK5tIXV9evXsWrVKvz44484d+4cKisr8f7779Pej+2RqSGI517GPj4+8PLyQmpqKr799lswGAz89NNPsLa2homJCUxMTGBkZIT6+nqsXr0a8fHxuHLlCi1QIpVKkZubi6ioKFy4cAF5eXl0RsnAwAA8Hg8uLi5wcnKCmZkZWCxWpwlIUJlpX19f7Ny5E2ZmZigvL8c///yDpKQkugxbS0sL/fr1Q8+ePTFjxgzY2dlBS0uLLmvS9FgpGwVjY2NkZWU1qfTZWlC2Us+ePUNcXByqqqpgbW2NwMBATJo0CQRB4Ntvv6WJOgAYGBhg+PDh+PHHH+lMgUwma5NIz38F2tra6N69O2JiYjB69Gj07t0bW7ZswYQJExAaGkov/NlsNszNzVFWVgYHBwdER0fj1q1b2LNnD+2R3lo0NDRAoVBAW1u7wxezeXl5yMrKwqxZs1RE6e7cuQMnJ6cODZaQJInU1FQcO3YM69ata1JwKDs7GxEREfjkk09a1ReclpaGK1euYNOmTU1mCakSyF27diE0NBT9+/dvV1JXVFSEqqoqFUXm5ORkmJmZwczMrM1jX3Jy8iv3BzcFPT09rFixAvv27cOxY8fwzjvvNHoOTU1NaTKsUCgwfPjw10KG2Ww23N3dkZKSgl69eiE6Oho+Pj5Nfl9fXx8MBgNisRg8Hg9isbiRqGRLoITKTExMUFJS0q7OGkKhEMePH8eiRYugpaVFP5+2trYoKSlB7969m8wIV1VV0VlOai7rgioUCgXS09NbfHfkcjnq6uo0rnxTKBQgCKLJd6ArI9xFhDWCkZERnjx5QnsyUhldKysrPHjwQOPtcDgc2NraIisrq1VCOP8FsFgsul+0udJoNpsNMzMz6OjoICMjo8OsAV4EQRAICQnB999/j6ioKJWeYAaDgbFjx2LXrl24du0aQkJC3oj7ShEjLpcLFxcXODs7Y/z48ZDJZCgqKkJ6ejquXLlCR2qdnZ3RrVs3ODo6wsTEhB405XI5Fi5ciO7du+PIkSMQi8XIy8tDamoqkpKSkJqaitmzZ2Pp0qVYsGBBuygNN3U+LBYL3bp1w/79+/Hnn3+iuroaISEh0NHRQWVlJQ4dOoS9e/ciPz8fxsbGOHfuHDgcDuLj41FcXAySJGFnZ4cpU6bAxcUFNjY2MDU1VSG8bTl2qlf35f+nsuQNDQ2or6+nf/h8PsrLy1FdXU1/RkVlc3JysGnTJrBYLFRVVUFXVxfz58+Hn58frK2tVYIwr3ItTU1Noaenh6SkpDZZulHnKJFIkJ2djfj4eKSkpAAAPD09ERoaCmdnZ3qRShDPLbEGDhyIK1euYObMmfQz6uvri/r6etqOjsPhdAkKNgOCINCvXz8cPHgQI0eORG5uLqRSKd56661GvZNubm7IysqCk5MTjh8/jilTprxSSXNJSQmA52SjIxdPcrkcJ06cwOTJk1WIYn19PW7evIkNGzZ0GLmh9Af279+P5cuXq/WApQKEhw4dwpw5c6Cvr69xv151dTUOHDiAxYsXqwgdvvy9rKws/Pzzzx3ik6tUKnH58mUEBwfTWVW5XI7r168jNDS0zftSKpUoKyvrkCoT4PkzTbUlHTx4EAcOHMD8+fNViBUV5HuxZ3jkyJGvhQwHBQXh+vXrePvtt3H58uVmSQfVP9vQ0ABTU1Pk5eVBKpXSiRdNoFQqkZWVBW9v73ZtXSBJEqdPn4a/vz+cnJzo8Tw7OxuBgYF49uwZ7a6h7phEIhG0tLSgVCohlUq7KiLVoKKiAkqlskUv98rKSmhpaWlcDalQKJptjevKCHcRYY1AZYL19PRoosZms2FkZITa2lqNByqCIODl5YWUlBQEBgZ2wpH/e0D1pMpksmaJMJWJr6qqQlFRUasmiVcBm83GwoUL8d1338HR0VFlccRmszFv3jx8/fXXcHR07DBbp1cBRTq0tLTg7OwMZ2dnjBo1CjKZDGVlZcjOzkZcXBzOnTsHuVwOCwsLeHl5QV9fHw8ePMDJkydx4cIFfPTRRwgLCwOHw4FAIMDXX3+NESNGYOjQoZ1yzhS5f/fdd3HhwgX8/PPPMDMzw86dO/HkyRMolUoAzwVfli1bhpCQEISFhaFnz54qvpYvklWKsL78uxc/k0qlEAqFEAqFEIlEjX7q6+tRW1uLhoYGurxfJpNBqVSCzWZDR0cH+vr60NfXB4/Hg52dHby9vWmv49zcXJSXl8PLywu5ubn4/PPPwePxsG/fPgwfPrzdlT9dXV1RX1+PmpoaSCQSjfr5KMEeyu86ISEBFRUVsLCwQI8ePTBs2DBYWFg0OakSBIHBgwfj66+/RllZGSwsLEAQBIqKiuDv74+DBw/CxMQEWlpa7dZf+L8KW1tbKBQKHD58GGVlZQgMDERxcTFcXFxUvufq6ooTJ06gsLAQLi4uqKura/OYSfXhy2Qy2NradigRffr0KSQSiUrAmCRJuje6rRltTfZdWFiI3bt3Y8GCBbTo3stQKpX4888/0b17d43He+r9OXDgAEaNGgVXV9cmSXBKSgpNll/FhqgpVFVVITs7m862U2rgQqFQxaKqLdtlMpntmol8GdQ8tmDBAvz+++/YvXs33nvvPZUx8kUyvH37dsjlcowZM6ZTyTBBEHB2dqb947W1tVFYWEg7MLwMHR0dGBgYoKamBvr6+pBIJK3OCFNK1WVlZejWrVs7nMVzZGRkIDk5GZs3b1bp1S8tLYWRkRGdxVYHkiQhFovBZrPpebErI9wY6enpcHNza/EZpdwlNH2WWyLCXRnhLiKsETgcDqRSKRgMBthsNiQSCXR1dWFoaEhnczSNcLm6uuLOnTudRuD+LWCz2fRA2RwRBp5fw7y8PPD5/GbV8NoTBPHcWmjq1Kk4dOgQPvjgA5VMhaGhId577z3s3r0bGzZs6JT+uVcFQRDgcDiws7ODnZ0dBg0aRJfdlJaWIjk5GefPn0dJSQkUCgUePnyI6dOnY8qUKVizZg3i4+PRr18/DBkypNOfZSaTiXHjxuHAgQP47rvvUFhYSJNgCoaGhggLCwOPx0NSUhLi4+PpQJZEIqH/pX4oMvwyIQaeVyxQvchcLpf+l/oxNzeHoaEh9PX16WeZ+uFwOLQCaEVFBVJTU/H48WOUlZWBw+HAyckJAwcOhIODA/T09PDDDz9AS0sLDg4OsLe3R0JCQrPWG60FtUC7fv06WCwWRCKRWuJJ2ezU19cjKysLiYmJyMjIAJvNprO+NjY20NPT0/jYdHR0EBwcTPd4AkBubi5CQkLwxx9/wNDQkC5N70LTYDKZsLGxwfXr1/Hrr78iOjoaUVFRjYiwkZER7ty5g9DQUMTHx0MgEDSqYGgNcnNzwWKxOlQoSywW4/Tp05gzZ45KUKW0tJS22OqofRcXF2PHjh0q3ugvgyRJ3Lt3D5WVlZg1a1aryNWFCxegr6/fZOCQJEkkJyfj4MGDWL58OZ19a09Q9kgDBw5UmTuvXbuGYcOGvVK2Ljc3F3Z2dp3y/nI4HMyePRtnzpzB9u3bsXz5chgYGKhcLyMjI6xevRo7duyAQqHA2LFjOzX7RWlNpKWlwc/PD/Hx8U0SYS0tLZiamiI3Nxfa2tq0r3prUFlZCS6Xi5KSEowfP75dnh2RSIQjR45g1qxZKs+LXC6HSCSi57im7rlcLodQKISNjY3K97vwfyBJEvHx8Rg2bFiL301LS6Pt8jRBV0a4ZXStNjQA1bdG/TfVw0oJJ7Wm59fExAQikQhCobBT1Fr/LaBKX6noYXMwNzenBSX4fH6nlVESBIGePXsiNTUV//zzD6ZNm6ayCHJyckJYWBj27duHdevWtXsWr6NBEATYbDbdc+vt7Y3S0lLI5XL6O2KxGBcuXEBUVBQmTJiATz/9tMWFIEmSOH/+PDw9PeHh4YHo6GicP3+e7mX29fWFp6cnwsPD8fDhQ/Tt2xchISG4f/8+srOzMXv2bLWDOIvFwttvv41r166Bz+fTEzMFiUSCyspKsNls2sebw+GAw+FAS0sLWlpaNLnV0tICk8mkJwwGg0H/qPv/ls5XKBSitrYWxcXFSEtLQ25uLq08T/kM29jY0OVwL25z9OjRuHz5Mjw9PTF69GgcPXoUQUFB7VpORlVVmJub06Xk1LHX19ejqKgIjx8/RlpaGsRiMRwcHNC9e3dMmDCBVqZuyyKLIAgEBQXh9u3byMvLowW7QkJCwGazcenSJXz22WddQcJmQJIknjx5gqSkJNjZ2YHL5aJ79+7Yvn07lEolvaiRSqU4deoUdHR0MH78eBw/fhwCgUDlO60F5SHc1GL+VUGRTFtbWxVVVIVCgTNnziAkJKTDxtWSkhJs374dM2bMUOmbfRkZGRm4ePFis/296pCamoro6Gh8/PHHakkDSZJ49uwZDh06hBUrVnSYE0FdXR0eP36Mjz/+mN5+bW0tMjIyMGPGjFfa57Nnz9o1E9kSWCwWwsLCcO3aNWzbtg0rVqxoZLtmaGiI1atXY9euXVAoFAgNDe20hT+DwUBQUBAePXqEsWPH4vDhw5gwYYLa/VNZ7OTkZNp/XigUapw0oby1LSwskJub22KJrSYgSRKXL1+Gs7MzvLy8VD6rqKiArq4uamtrm60E4vP5EIvFMDU1hVAopOfgLvwfBAIBSktLm6wSoUCSJPLy8lql6yEWi5t1t6Dsk/7L+G+fvYagelcB0GJBwP+JE7WGCHO5XJiZmSEvL69TJ4w3HVRvKUEQLSolGhsbQyQSwcrKii4T6SwwmUxMmTIF33zzDRITE1UWTARBoG/fvsjNzcWff/6JefPm/U9E2t566y24u7vDwcEB1tbWsLCwwM2bNzFw4ECNJrS6ujpERUUhKysL7u7u8Pf3xy+//IJRo0YhJCQEZ86cQU5ODoKDg5GSkgI7OzuQJAlvb+8Wt6+np4c5c+Zg4sSJsLKywq1btxAeHo709HQwmUyMHj26UZasPfBiVk0sFqOiogJFRUVIS0tDYWEh6urqwOVyYW1tDXd3dwwePBjm5uYqz3lT8PX1xalTp1BcXAx7e3uw2WxkZ2e3a4kkj8eDUqmEqakpkpOToaOjQ/d819TUwNTUFH5+fliwYAF93MCr9SZT0NLSQmhoKP7++2+8//77qKyshJ6eHsRiMfz8/Ggxti4y3BjUYve3337Dpk2bcOjQIbrcUktLC4WFhXBwcKCtedhsNgYNGgSBQAA3NzfU1tbSWZm27JvP5wNAh5S+Utu/ceMGNmzYoFISnZmZidLSUixcuLBDMqRlZWX46aefMGXKlCb9u0mSRGVlJX755RcsWrRII9tECvX19Th8+DDmz5+vNgBO9QQfOHAAq1at6jASTJIkbt26BX9/f7qUlRIgCwgIeKXgvFKpRG5uLkaOHNleh6sRqHGey+Xi+++/x5o1axo5Bujr62PlypXYuXMnlEolJk6c2Glzs5ubG06ePAlzc3OIxWI6AKkOPB4PcrmcFkFsrY9weno6jIyMUFdX98rkhiRJ5OfnIyoqCps3b270PJaUlMDCwgJFRUVN9gcDz4mwTCaDoaEhBAIBtLW1u3qEX0JRURFMTExaDKyJxWLU1NS0as1LtXU2R4T/6/ejiwhrAGoxLpPJYGJigoqKCtrfk8fjgc/nw87OTqNtEQQBb29vJCcndxHhF0BlFZlMJgQCQbPf5XK50NXVhZGRETIzM5tcuHQUdHR0sHDhQuzcuRP29vYq6n0EQWDKlCnYvn07bt68ieDg4H/tgp4gCCxfvhzLly9X+b1CocDZs2c1ImaU8MyMGTPw448/0qXsVJZWV1cXI0eOxJo1azBq1CiMHz8eR48ehaenJwoKCtT66L58jL6+vjh58iRmz56NkSNHQiAQIC0tDUlJSRorKzZ3/NSPXC5HRUUFSkpKUFhYiJycHNTU1EAsFkNfXx/W1tbw9PTE4MGDYWlpqTKpteYZ4HA4GDp0KK5evYp58+YhODgYFy9exJo1a175XKh+59zcXJSUlKCoqAiFhYXIzc2Fj48P3nrrLdja2tI9XB0lfNajRw9cvXoVjx8/BkmStD1Ut27dEB4ejpCQkA7rA/23gupf3bdvH5YuXQo7Ozv0798fDx48gLOzM/z8/BAXFwc7OztcvXoVxcXFWLlyJa5du0Z7UkdERKCmpqZN1kl1dXV0W1BH9XCfPXsWAwYMUPEkpYSz3nrrrXZfsL1IgidNmtSs8q1QKMTPP/+M0NDQVgWlFAoFTp06hV69eqn9O+q+/vzzz1iyZEmHetILhUI8ePAAGzdupPchFovx4MEDleBDW1BXVweRSPRa2oIYDAaGDBkCHR0dfPvtt1i9erVK+T5BENDV1cWKFSuwa9cunDlzBpMnT+4UMmxgYAAzMzPk5OTAw8MDKSkpTRJhS0tLyGQyup2moaFB41YGpVKJgoICsNlseHh4vPIzJJPJcPToUUyfPl0tkcrOzoazszOys7ObfG8A0MEzHo8HgUBAuxZ04TmosmhN1rE1NTV0O5amaIkIy2Syrozw6z6AfwOoUg6hUAhTU1NUVVXRn9na2qKwsLBZWfyX4eHhgb/++qsr6/ECWCwW3bTfEhEmCIImGnl5eZ1+HQmCgL29PcaOHYsDBw5g5cqVKsRBS0sLCxcuxLfffgs7Ozt4eXn9a+9zU4tCqVSqkeCFSCTCvXv3YGRkhLy8POTm5sLb21tl+2w2G3V1dVAqlXB2doa+vj5SUlJQU1MDX1/fFq8d5fNNbU9PTw+BgYEaCdJRJFehUEChUEAul6O+vh6lpaUoKytDWVkZiouLIRAIIJVKoaenBwsLC9ja2mL06NEwMjKCoaEhtLW127WHt3///vj0009RW1sLX19fnDlzBuXl5a1aZFLiPEKhEFlZWUhNTUVGRgY9jllYWMDKygpWVlb44IMPOjUqzGAwMGXKFGzbtg0ODg4oLS2lydmECRNw9uxZzJs377V5gL5pIEkSFRUV2LVrF2bNmkULGvXs2RNbt26FWCxGYGAg9u/fDxMTE0RFRWHdunXQ1taGo6Mj7ty5AxMTEzqj0JznZ1OorKyESCSCjY1Nq0qCNUVBQQGSk5NVeoBJksSjR49gYGDQ7iKElNjP9u3bMXHiRPTp06fZxeLBgwfh7e2NgQMHanwcVM9vTk4OPvzwQ7UkuLq6mr6vHSGM9eK+Hj58CHd3d5UgU1RUFFxdXZu0iNIUpaWlMDExeW2LaoIg0Lt3b2hra+Onn37Ce++9pyL8Rc0N77//Pnbv3o2///4bYWFhHX68VHl0VFQUevfujRs3bmDgwIFqxzZLS0taZZnD4aC2tlbj/QiFQkilUpSWlqJv376v9ByRJInbt2/DyMgIfn5+areVm5uLcePGISIiosmMMFXlQZIkeDweysvLmxTV+q9CJpMhNTUVw4cPb/GeFRUVwdraulXbFwgE0NXV7coIN4MuIqwBGAwGtLW16WgWZSEBPDdBT09Pb9X2bGxswOfzIRAIuvqE/z8oCxs2m62RQIS7uzuysrJQVVWlsepte4JSwE1LS8OlS5cwceJElYnNyMgIixYtws8//4z169f/K8SzWgMGg9FInOplUCWNQ4cOhZGRERgMBiIjI+Hp6alCQJ88eYJx48bRZHLs2LH45ZdfMHfuXI2IkLoeF2rbcrkcMpmM/lcmk4HP56OiogLV1dWorq5GTU0Namtr6V5oHR0dmJmZwdzcHK6urhg0aBD09fXpSGxnkDM9PT0EBATgwYMHGDduHAYOHIhr166peKqquw4CgQDV1dVIS0tDVlYWraxuZ2dHZ6uNjIygo6OD+Ph43Lt3D0wms83lsm0FQRBwdXWFra0ttLW1kZiYCEtLS3A4HIwePRo//PADMjMzX0nB9n8JtbW12LFjB0JDQ1UWpgYGBjAxMUF2djY8PDxQXl6O06dP45NPPqEDC/b29igrK4Ovry84HA5qamraFDwsKyuDQqGAlZVVu98ThUKBP//8E5MnT1bRfBAIBDh//jxWrlzZ7tk7qid48uTJCAoKava9+uuvv6ClpdVonG8JIpEIf/31F+bMmaM2eCAUCrF7926MHj262b7k9oBYLEZ4eDjef/99ej8SiQQ3btzA4sWLX3nfnd0frA4EQaB79+5YvHgx9u/fj1mzZjWynqLI8J49e3Dy5Em89dZbHU6Gvb29cfnyZUydOhUlJSUQCAS0xsyL4PF4YDAYtG0SpfKuCfLz82FkZAQ+n99sqXJLoKokbty4gY0bN6p97+RyOaqrq2FiYgKJRNKsTgul02FkZISGhga15/1fBuU8o0l7ZXp6equEsoDnY0xTugpUsLyLCHehRRAEAR0dHZoIp6Sk0AsJMzMzPHz4sFULC21tbfB4PLo5vgvPibBSqQSHw2mxRxgA7OzsEBkZCSaTCaFQ+FrsVhgMBmbNmoWtW7fC1dVVJXtJKfNOnjwZe/bswfr16/9ngh5MJhM8Hg81NTXNRndTUlJw6NAhvPXWW+jWrRsEAgGuXr2K2tpaVFZW4vbt26ipqYGFhQXefvtteoHp4eGBPn36NGld8jJKSkqQmZmJvXv30grQUqkUMpmMFrZjMpm0V7WBgQFMTU1hbGyMbt26wcTEBMbGxnRfFovFUvEWfh0gCAIjR47EDz/8gOHDh6N///74/PPPMXHiRBgYGEChUKCurg7V1dXIzc1FdnY2CgsLIRKJYGhoCFdXV/Tr1w+Ojo60SNjL5+Pg4IDKykoYGhqisLBQJVPfWedoYmKCyMhIAICzszMMDAzA5XIRFhaGEydOYMOGDf95YZWGhgbs3LkTAwcOVPEwB56PQQMGDMCDBw/AYDCQlZWF5cuXq5QW6+vrQ6lUwsnJCQ0NDSgvL2/TcWRnZ4PFYrUpm9wSEhISIJfL0bNnT5Vs8KVLl2gP7fYCVYq8Y8cOTJs2TWWfL0OpVOLixYsoLi7GihUrWrVgJEkSV69ehZubm1oRHKlUil9//RVeXl4YMmRIhwfYHj9+TFeBUEhKSqLt3F4FSqUSGRkZCAsLe+2BK4Ig4O7ujuXLl+Pnn3+GSCRqFOjQ1dWlPz9x4gSmTZvWoWTYxMQEurq6KC0thZWVFXJzc+Hr69voewYGBmAwGFAoFLQtnyaggs6mpqYQi8WvtB5SKBQ4evQoQkNDm+yDr66upoUjKfHJplBWVgYmkwkTExO6TLcLz0GSJJKSkuDp6dni86dUKpGfn99qBwmBQNAsyW4pkPFfQBcR1hC6uroQCAQwNTWlSz0IgoC5uTlqamrovg5N4eXlhdTU1C4i/P9BqdCy2ewWS6OB55n4uro6mJubo7CwsFXCJe0Fqu9owYIF2LNnDzZu3AhjY2MVMtyvXz+UlJTg0KFDWLJkyf9E5I06r4iIiGb72Tw9PfH999/TC7y5c+fi3XffBQCsWLGC3tbLpJPJZGL69OkaDfZKpRIRERGYMmUKLRj0oiK0rq4u/Wy9+EPt+00ElQEwMTGBra0tHj58CFdXV7BYLGzfvh16enqorKyEXC4Hj8eDk5MTfH19MXbsWJiZmdHXU5OScsozOi8vr9NL+EmSRHl5Obp164bff/8dbm5udF+fp6cnTE1NERERgSGvwZ7rTQBJkpBIJPj555/h4+OD4ODgRmSJIAj4+Pjg0KFDePr0KdavX4/Y2FhMmDCBvmYMBgNGRkaQyWRoaGhAUVFRm46F8hB+VdL0MoRCIf7++28sXrxYJftUVlaGmJgYtUI9bQWlurpz507Mnj272SysUqlEeHg44uPjsX79+lYvFktKSvDw4UN88sknje6bUqnE2bNnwWQyMXny5A4nwVKpFFeuXMGcOXPo85XJZLh8+TKmTJnyytdXKBSiurq63Z+NtoIgCDg4OGD16tXYvn07xGIxBg8erHKeXC4Xy5Ytw969e3H8+HHMmDGjwwKgDAYDvXr1QmxsLAIDAxETEwMfH59G+zIwMICBgQEkEgnq6upgaGiocUY4NTUVpqamcHR0bDOpJ0kSkZGRIEmyUdDtRVRUVMDMzAyFhYWwtLRsdn/19fVgMBjgcrng8/ld2g8vgOoP1sTqSiQSgc/nw9LSslXbFwgEzVYISCSS/7yvc1cDloagiLCRkRHtHQw8X0wqFIpWGZ8TBEET4VfxdPxfArUQ4HA4qKura/H7FMExNTVFdnb2a7uO1IQbEhKCX3/9lbbZevFzalF64cKFFsuJ/w0gCAK9evVCTk4OXXqrDpTvNrW4oDKyL/6os+EhCEJjm6KUlBRIpVKMGzcOfn5+8Pb2houLC2xtbWFqagoul0vv50V7pNdFrKiScKVSSZdrU6rTKSkpiIiIwIULF7B371589dVXePr0KTZv3ozffvsNlpaWePr0KQYPHozVq1fjm2++wYcffogZM2YgKCgI1tbWYLPZGl074LlSu6GhIYyNjVvd3tEeUCqVEAqFGDduHBQKBWpqauDk5ATg/9TZr169qtF48L8IuVyOQ4cOwcLCosmSXGqhU1JSgpEjR2LYsGHg8/moqamhv0NVpxQVFcHY2LhVfYcUlEolqqqq6GemvUCSJG7cuAFXV1c4OjrSzy2lej1u3Lh2K6UkSRLZ2dnYuXMn5s2b1ywJJkkSUVFRCA8Px5o1a1pt2aRQKHDs2DFMnjy5kTAZSZKIjo5GYmIi5s2b1+FluSRJIjU1FVwul77G1LVQKpXt0n5QWVkJAwODN6p6g9ISWb9+PW7cuIHLly9DoVCofK6trY0lS5agsrISf/zxh8rn7Q1/f38kJSXBw8MDGRkZjdYKwHNyTpUbS6VSjY9HoVCgsrISNTU18PT0bPP9rK6uxj///IN333232ecyIyMDbm5uKCgogL29fbP7EwqF9BxMuSl04TnEYjEqKythY2PT4nfr6+vbpLjdUgtmFxHuyghrDENDQ9TW1oLD4dC9h1S5oZaWFkQiUauUOB0cHFBeXt5s/f5/CdSgq6WlpdHClyqr5PF4NBF+XeSGIAgMHDgQ6enpOHfuHMLCwlQWrWw2G3PnzsV3330Ha2vrZvvR/i3Q1tbGxIkTcfDgQaxatQoGBgadnk0sLS3Fzp07weFwsHfvXhgZGYHH44HH48HIyAgGBgbQ1dWlyeHLPy9nh1/OGFP7efFfCkqlkia0L/9LXoptjQABAABJREFU/YjFYtTX1zf64fP5qK6uhlgshlwuh0KhgLa2Nk1KTUxM0LdvX9pOYd++fQgLC4OXlxdkMhkYDMYrC9sAzwMVjo6Or1Qu+yqora0Fi8VCQ0MDhEIhYmJisHLlSvpzU1NTDBw4EGfOnMGcOXP+U8JZcrkcx48fBwA6U/UySJJEbW0t9uzZgzFjxqCwsBBMJhPu7u5ITk7GwIEDAfyfuF9MTAycnJxQXFzc6uOpr69HbW0tDA0N26Q43RQqKipw//59fPTRRyol0cnJyaipqWl1GWBToMjgr7/+ikWLFjWrqktlac6ePYt169aBx+O16hhIkqRLvV9W0yVJEgUFBfj777+xdu3aTilJVCgUuHjxIsaPH0+/Q1TJ99ixY9ul9zolJeWNFIWk1gkbNmzAzp07IRKJMGHCBBU7OC6Xi/feew/79+/HsWPH8Pbbb3cIoTc3NweDwYBIJIK2tjbKysrUZtBNTEyQlZVFzzkKhaJF8lNeXg4Wi6USTGwtqDEnODi4WQ9iyglixIgRuH79OsaMGdPsdynhL6qNratH+DlIkkR6ejpsbW014gA5OTmwt7dv1TxIkiTq6+ubHbO7iHAXEdYYJiYmSE1NpRfRVKSOwWDA2NgYVVVVrRJEooR3qquru4gw/i8LyOFwUF9frxGxdXFxQX19PSorK6FQKF7rQpnFYuHtt9+m+4VfVlrU1dXFkiVLsG3bNpiZmWnc//qmgiCe24BRqqtLly5V6UvsSFD+hpSglr29PS18xefzkZ+fj6dPn6K+vh4ikQgKhULFBol6tqi+YSaTqfLfL58DRWwpKBQKugdZoVCoLbemAmS6urrQ1dWFvr4+bbHk5eUFExMT2kaKzWbTCwV112/cuHG4dOkSvLy8EBISgkuXLsHX1/eVM0lUpjAmJgZSqbTTxftKS0thamqKrKws+Pv7QyaT0X7t1PGNGDECX3/9NXJycjrED/pNhFKpxIULF1BaWorly5c3uSgXCoXYtWsXBg0ahF69euHrr7+GRCJB7969cfPmTfTv358eEx0dHXH58mUYGBggIyOj1UqhdXV1EAqFcHBwaLf2DqVSiVOnTmHUqFEqWWaxWIyTJ0/inXfeaZdsKUmSePz4MY4dO4Zly5Y1O/aSJInExET89ddfWLlyJczMzFo9pgmFQpw+fRqLFy9WOX6KFOzfvx/Tp0+HpaVlh4+XJEkiJycHUqlUhfwXFxejurpabXlua6FUKpGamopRo0a9sXOavr4+Vq9ejX379uHPP//EjBkzVN4rLpeLxYsX49dff8WxY8cwa9asdifDBEEgICAAiYmJ8PX1RUJCgorFEwVKA4LKnEokkhZV2ouKimBoaIjq6uo2VWyQJIknT56gpqYGw4YNa/Y+ymQylJeXw8bGhhbMagpCoZDW1mEwGF1E+CXExMQ0q1FAgfIZd3FxadU7RlVddWWEm0cXEdYQ+vr6dK8Dk8lUKWuxsbFBQUFBq8RmCIKAh4cH0tLS3pi+mtcJighTqtEtLdQIgoCjoyNu3boF4PmA+7pl+XV1dfHee+9h+/btsLS0VBElocq05s6di71792Ljxo3/+l4ZBoOBYcOGQUtLC99++y2mT5+OgICADg1IyOVyPHjwABcuXMDs2bNpRdCXxXRezNK+WI78cmky9UMpS8vlchXSS5V0vzj5UMRVW1tbpR/35Z8Xs86vskD09vbGqVOnUFxcTFuvFRUVtYtokYODAy5dugQDA4NOFe8jSRLFxcWwsrLCs2fPYGlpibKyMpw/fx6rV6+ms1RaWlqYNm0a/vrrL3zwwQdvVOllR0CpVOLGjRt48uQJ1q1b12TGUCwWY8+ePfDx8cHw4cPBYDBgZWWF1NRUeHh44NixYyrKtPr6+hCLxTA0NERVVRXq6+tb5bFdXl4OkiTbjbyRJIm0tDSUlZVh/vz5KtngO3fuwM7Orl1KdpVKJSIjI3H27FmsXbsW1tbWzW4zOTkZR44cwcqVK2FjY9Pq/ZMkifDwcLi7uzd6P0mSxB9//AEfHx+NPEPbC+fPn8eYMWPo+ZQkSVy8eBEjRoxolwUwZdnzJq9jCOK54OmyZctw+PBh7N+/HwsWLFAhmFpaWli0aBEOHDiAI0eOYM6cOe063hDEc7uzw4cP4+2338bvv/+OcePGNXoOrKysIJVKaUJMCT42h+TkZLr6qS3WZvX19Thx4gSWLVvWYqCLEvBisViQyWTNEluq2sfJyQkEQdAWhF14vpbJysrC5MmTW/yuQqFATk4Ohg4d2qp9UO4ZzQUUFQpFp/hpv8n479SavSK0tbUhEonAZDJhYGBA91lRBKesrKzVfapdfcL/B4pwcDgciMVitf0zL8POzg5VVVUwMTFBfn5+Jxxl8yAIAjY2Npg6dSr2798PoVCocm+pLGpoaCh27doFgUDwr7/3lGrtihUrcOnSJfz444/Iy8ujSWd7gBrMU1NT8c033yA6OhobN25sZIvxIl7M+L5IXLlcLnR0dKCnpwdDQ0OYmprC0tISdnZ2cHJygpubGzw8POgfd3d3ODs7w8nJif6xtbWFubk5XXqto6MDLpcLbW1taGlpgcPh0L3RmvbrNgctLS2MGDECly5dApvNxogRI3Djxo126TfX09ODWCyGlZUVCgoKXnl7rUFWVhYcHByQm5sLMzMz9OrVCwqFAomJifSzQ+kpmJiY4MGDB//696U5kCSJiIgI3L59G6tXr26yUojytLW0tMSECRPoYEz//v3x4MEDaGtrw87ODpmZmfT1op5/MzMz2iu7NcjJyYFCoWi3QIlMJsMff/yBadOm0WSM8tQNDw9/ZfVhKtgVHh6OS5cuYf369c2SYIqYHzhwAMuXL2+x77GpbZSXl+PevXuYNGlSo8+io6NRVFSESZMmdVr1UmFhISorK1X6oSsrK5Gdnd2obLutqKqqosfANxlUT/CCBQtgYGCA7du3q8zBBPFcAXnhwoWQy+U4fPgwbWPUXrCysoJYLKbb6dT161tYWEAsFkNbW1vF+aApUAJwEomkTT7UJEni77//RlBQkEbPfWVlJYyNjVFeXg5DQ8NmiXdDQwMUCgV4PB5dRcnlct/YyoHOREFBAfT19TWyTZLJZC2qP6sDtQ5rjuh2EeEuIqwxuFwuRCIRCIKAkZERqqqq6M+srKxQWlraqgGTKkssLCzUKOL3vw5qYNTS0oJEItGICFNCZVZWVq9VMOtFUEJSHh4eOH78eCOyQhAEBgwYAF9fXxw8eFCj83zTQRAE7Ozs8OGHH6Jv37749ddfsXXrVjx69IieCFt7byjyy+fzcffuXXzxxRc4efIkxo8fj7Vr13ZaGfabAIIgEBQUhPT0dFRXV6Nnz55ITU0Fn89/5W1zuVwYGBiAx+MhLS2tHY5Wc5SXl4PH4yE3NxcEQcDFxQXTp0/HP//8oyI+yGAwMHXqVNy4cYP2wP1fA9WXeuHCBaxdu7bJnnuZTIY///wTBEE06h329vZGXl4ehEIhevbsidjYWPozJpMJGxsbKJVKVFdXt0qAjMreU0HfVwVJkrh79y4sLCxUhH1IksSJEycwcuRIFfX9toBSZY6MjMQHH3zQ7HhB9er98ssvWLp0KZ29ass+T5w4gbFjxzbqK66srMSJEyewaNGiTitDJEkSFy5cQHBwME1WSJLElStXMHDgwHbpT6b6ud3d3f81i2k2m423334b7u7u+P7772kfV+D/yPD8+fNBkiQOHTrUrnM0i8WCj48PUlJS4OrqiuTkZJXPqfUlFcgRCAQtCrE2NDSgvr4edXV1rfaYBZ73d2dlZSEkJESj5z4tLQ3u7u4oLi5uscKCmv+p7LZSqWxTxvp/EXFxcfD399coKEbNla0dO6gKuOb2oVQq/1P6G+rw3z77VoDL5dIDkpGRkUokz8zMDLW1tbSStKbQ0dEBi8VqdXT+fxEEQdCZO4VCodHkw2KxoK+vDzMzs9eietsUGAwGJk6ciKqqKty9e7fRwp3BYGDChAlgsVj4559/OlSpsrNA3b/+/fvjk08+wcSJE/HkyRN89dVX+P7773HmzBk8fvwYZWVl4PP5EAgEEIlEEIvFEIlEaGhoQG1tLUpKShATE4OTJ0/im2++wbff/j/23jo8qmv/Hl5nXOPuTnB3d/dCoUihQJHiUO+3771t721pi1tb3IoUhxCcYgFK8AQIcXcd1/P+wW+fmyE2M0kghKznyROYzJzZx/bZ6yNrrUBSUhImT56ML7/8Eq1atXrjHr9vAhKJBB07dsTff/8NiUSCtm3blnttWQo2mw0vLy/odDpkZma+NpJJrHzUajVKSkrAYrHg7e0Nb29vBAYGltk3BwcH9OnTB4cPH653RJiQif3792PRokUVkjaDwYDjx4+joKAA06dPL1PCKJFI4OHhgRcvXqBRo0aIj49nnklEMEutVkMul5uoSlcFvV6PrKwsCIXCGhFpKywsRHh4ON5//30T8vT8+XNkZmaWsbmxFFqtFnv27EFCQgKWLFkCe3v7SkkwEdGaM2dOuX6/5oD4gRYXF5exndHpdNizZw+GDRtm0i5T28jOzkZiYiI6duzIvFZcXIxHjx5V+xgT0DSNJ0+eoHnz5m/VnMxmszFy5Eh07doVv/76K1P6T8Dj8fDRRx+Boihs27bNIleQykBRFDp06MDYKN25c6fMfEayfkRsUalUVrrNwsJCxnbSEp0a4GVL2Z49ezB16lSzMvpGoxHx8fEICgpCXFxclRUihYWFoCgKDg4OjLZGAxF+OZdHRUWhRYsWVb6XeET7+/tbTFgbMsLmoaFH2EwIhUIYjUZoNBpGlICAx+PBaDRa7CXM4XAQEBCAFy9e1MgC420HicaamxFmsVjw9fWFTCZDfn7+G1WOfhUCgQAzZszAihUrmH630uByufjwww+xatUqXLt2Db3qkVcqn89HkyZN0LhxY6hUKmRnZyMmJga3bt1CVlYWIzJFot5JSUnIy8uDRqNBUFAQevTogYCAAHTp0gXOzs7g8/n15thUB3379sWPP/6IgQMHok+fPli5ciUGDRpU7YVFcHAwHj9+DIVCAblc/lrETMjijfhRqtVqeHh4gMViYcSIEfjll1/QoUMHpo+VKLPfvn0bz58/t0iPoa4jISEB27ZtwyeffFJhhsVoNCI8PBxxcXFYuHBhhYvWbt264ebNm2jevDmEQiEyMzPh4+MD4KW4YFhYGJycnCxSjlar1cjJyWEqB6oDo9GIo0ePolevXibPPI1Gw3i5Vud6ViqV2LZtG7hcLj755JNKF/eEBG/btg2zZ8+2mgQDLz0+9+/fj5kzZ5pkbUhJtE6nQ48ePV7bPEbTNM6dO4cePXowx4CmaVy+fBlt27atMeVvg8GA7OzsSn1K6yrYbDb69u0LkUiElStXYv78+fD29mbOEY/Hw/Tp07Fz507s2LED06dPrxES5+XlheLiYri4uCArKwsqlcokO29vbw+JRIL8/HwolUqoVKpKtxcfHw+xWAwej2fR3G00GnHy5Ek0btwYISEhZn1Gq9UiJycH3t7eOHbsGHr16lXp+zMzM8FiseDq6gq9Xs8oZr/ryM3NZaoZzUFMTAw6d+5s8fyhVquZNq2K0JARbsgImw2BQACKoqBWq+Ho6MgQLwBMH2JVE9aroCgKTZs2RXR0dL3LcliKV8WyzCHCRDCLBCWs8cesTTg4OGDGjBnYsmVLuSWdIpEI8+bNQ3h4OJ48eVLvrgEiUOLv74+BAwdizpw5+Pbbb/Hvf/8b3333Hb777jt8++23iIuLw9WrVxEdHY2UlBSMGTMGffv2hbe3N3PfNeDl9RQUFITIyEi4uLjAw8MD9+/fr/Z2vb29kZ2dDYlEYlGmsDrIz89n/IslEglUKhVj2WFnZ4devXrh+PHjJvcEn8/HxIkTceDAgRrL0LxJ0DSNtLQ0bNiwATNnzqxQzZimaVy5cgX//PMPPvnkkwpLWsnzJCUlBWq1mlGmJcfQwcEBer0eDg4OSEtLM3ucpHKjssyqOSCZjYSEBAwYMMCkJPrKlStwd3dHaGio1dsuLi7GmjVrmHm3KhL89OlT/PHHH9XKBJNtHTt2DM2aNSujbF5SUoLjx4/XmAK2uSgsLMTjx49NAqwKhQIRERE1qu6clZXFqOK/jWCxWOjSpQsmTpyI1atXm/TVA/+zPuRwONi+fTs0Gk21n9MCgQDBwcFISEiAk5MTEhMTTf4ukUhgb2+PkpKSKsWyaJpGbGws2Gy2RSX9RE38/v37FvXjKxQKpiKruLi4ygROQUEBKIqCra0tdDodVCpVne8lr22QKoqmTZuaRUCNRiMyMjKsCjbJ5XIIhcKGjHAVaCDCZoLYoahUKjg7O5chwi4uLsjMzLR4u4GBgUhKSqoX5bHVAUVRoGkafD4fCoXC7L6cgIAApKenw9nZ2aLF3esARVEICQnBwIED8fvvv5d5oJGSofnz52PHjh1ISkqqd2SYgCgns9lscLlc8Pl8CAQCFBcXM/32MpkMN27cwNq1a+tF73RtYMiQIbhw4QK0Wi2GDh2Kc+fOWdyS8Srs7e0hl8vh4uLy2gSzUlJSGEEnNzc3CIVCppqGoij06NEDycnJJvcE6SMODg5GeHj4W32vEGGlNWvWYMqUKRV6sNI0jYiICFy4cAFLly6FVCqtdNEqEong6emJ2NhYtG7dGg8ePDD5G5/PB5/Pt2iuyc7Ohk6nq7YqMOlvnjhxoknWNDc3FxcuXMCECROsykyQY/nzzz+jZcuWmDBhQqWkk1jFbN26FQsXLrTYkuTVbT1//hyPHz/GmDFjTLZD0zSOHDmCrl27VtlLWZMggYUOHTowCr00TePWrVto1KiRRWrhVX3P8+fPERwc/FZnlCiKQqtWrTBnzhxs2rSpjFgfh8PBtGnTwOVysXXrVhOLN2u/r3Pnzrh9+zbat2+Pu3fvmtyLLBaLaY8gSssVQa/XIzU1FSqVCk2bNjV7DFqtFrt378akSZMs6hVPTEyEt7c3iouLIRAIKrX+pGkaJSUl4HK5EAqFkMvl0Ov177xVj9FoxL1799ChQwez3q9QKJg+a0shl8shEokqnXsaMsINRNgiEMEs0i9MhJAoioKrqyuysrIs3ia5uGtC+OZtBiHCAoEAMpnMbCJkY2MDlUoFX19fxMfH1/IoLQdFUejVqxfc3d3x119/lQl4kN69mTNnYvPmzSYBlvoO4u+Zk5PDvGY0GrFhwwb8/fff78xxMBdEldzGxgYxMTEICAgATdNISEio1nYlEgkkEglsbW0RFxdXQ6OtHMnJyfDy8mKyIvb29iYPY4FAgPfeew/79+83uWcoisLo0aNx9+5dpKWlvZXXCE3TKCoqwrp16zBq1Ci0bt26QhL84MEDnDhxAkuXLi0jwFQRyCLbzc0NSqWSyfIT1WgWi4Xc3Fyzj11KSgr0ej38/f0t29FX9uXGjRtwcHBAkyZNmP3Q6/U4ePAgBg0aZLEiKtluQkICfv75ZwwbNgyDBw+uVEOApmlERkZi3759WLp0Kfz8/KpFUOVyOXbv3o3p06eXyXTFxsYiLi7OJPv9OqBQKHDr1i3079+f+V61Wo3Lly9j6NChNTqWR48eVare/7aABK0XL16MvXv34vbt2ybrO9LKxOPxsHXr1moLnPr6+iI3Nxf+/v548eJFGf90iUQCgUAADodTaaBTqVQyXr1+fn5mfTdN07hw4QLc3d0t8pEmFR1BQUHIysqqUjiPpmnI5XITIsxms9/50uji4mIUFxeblOFXBJqmkZKSAjc3N6usvJRKJcRicaXf05ARbiDCFoEQYS6XyyjgEbi5uVmsHA28LL3x8/PDixcv3spFXU2BEGGxWMwIKJkDgUAAkUgEe3v717aItxRsNhvjx49Henp6hRYwTZo0wfDhw7FhwwbI5fI3MMo3g6tXr5aJeBcWFuLrr79GRkbGO31PlAcWi4UhQ4YgLCwMADBo0CCcO3euWlZKFPXSh5nNZiMtLa1GbJkqA03TyM7OZr6Poij4+vqWeVg3adIEtra2iIiIMLkOxGIxQ5LftsoBsjhct24devbsWUZYqfT7iIDWwoUL4ezsbNaClVi0kYxvQEAAowZOURTc3d0hEAhQVFRk1hxLFKNZLJbVWU1C/M+cOWMikEVKBIuKiqzqnyWZlY0bN2LWrFno1KlTleqoEREROHLkCJYsWQIvL69qETi9Xo/9+/ejbdu2aNSokcm2tFot9u3bh4kTJ9aIOrO5IAGHpk2bws7OjnntwYMHcHd3rxHVbwKdTofs7Gx4enrW2DbfJEhQetmyZTh16hSuXLliEoTj8XiYNm0a+Hw+tmzZYnErXGmIxWL4+fkhKysLbDYbubm5zN9YLBYcHByYcvPKiHBOTg5YLBbYbLZZgSRyP1+9erWMWF1VIEJZwcHBjCBfZSBiXxKJBCKRCAqFgrFxe5dBqiiq8msmiI2Ntbp1Qy6XV5q1BxoywkADEbYIUqmUiXAZDAaTSdLLywvp6ekWL9wpikKzZs3w5MmTmh7uWwVyk5Ob1lwlbaJ6q9FokJeXV+0y0dqCQCDArFmzEB4eXm7Qg6Je+oC2adMGv//+e73ogawKKpUK165dK/dv9+/fx+rVq2udlL1tIJkLpVKJ1NRUtGnTBqmpqcjLy6vWdhs1asREqquzwDMHKpUKMpkMer2eEfLw9PQs86Bns9kYN24cwsPDTex+KIpCy5YtIRaLcevWrbcqWKJSqbB+/Xq0atUKffv2LXcBQrKc27dvx5w5c8o9NpVBJBLBxcUFiYmJaN++Pf755x/mGPn5+TG9yQqFosptETE7iURSLcXjv/76Cz169GD6wIGXx+LgwYOYNGmSxdkOg8GACxcu4MiRI1i+fHkZIlrefly+fBlhYWFYunQp3N3dq93vfOPGDeTl5WH48OFlSqJv3LgBR0dHi8pVawIk8zto0CDm2tLpdDh79iyGDRtWo5nbtLQ0SKXSaguo1SWQ6r7ly5fj+vXrOHnypMmagmSGRSIRtm7davVcScqjb926hZYtW+Lhw4cmfydBJ71eD51OV+EcFxMTw/iGm0NmDAYDdu3ahTFjxjCBEnNB/Mft7OyQmppapeewUqmEWq2GUChkWt7EYvE7XRptNBpx9+5dizy8X7x4UUZs1VwolcoqA3ENGeEGImwRnJyckJeXx5R6lF6c2djYQCaTWbUoCwgIqNf9oeaAoigYjUamn8FcIkxRL/2Y8/PzwWKxTNS86xJIP/CMGTOwdetWFBQUlGurNGTIEDg5OWHPnj11ltTXFOLj4xEbG2vyQHBzc4O/vz++++47TJ48+Z2PVJYHHo+H/v374/Tp0+Dz+ejUqVO1S8mJYBafz6/1igQSTCSWPDKZjFE2fhXOzs7o2rUrTp06ZRIUYbFYGD9+PM6ePfvWeAtrNBps3LgRgYGBGDZsWLmLD5qmkZ6eXqWAVmVgsVjo0KEDbt++jaCgIKSlpTELdm9vb9A0jfz8fLOIsE6nQ15eHqRSqVUiN0TMJzEx0aRUl3jcNmvWzKLyZJqmodPpcOjQIdy9exefffZZlaTWYDDg5MmTuH79Oj777DOzs+uVjSEhIQGnTp3CzJkzy5D44uJinDlzxuqe5+qM69atW/D392dsdEhlgUgkqpK4WIro6Gg0bdr0rS+LfhXEy3f58uWIiYnBvn37TMgoh8PB1KlTIZFIsGXLFqjVaqvmH+LFGxISgocPH5pYnbm4uECj0UCr1VZon2Q0GhEXFwedTmeWij5N07h27Rr4fD7at29v8XkjgoosFgv5+flVVgKoVCro9XrmMwqFokJ/9HcFKpUKmZmZCAgIMOv9er0eBQUFFttiAS/Pt0KhYHQCygOxV3rX11nv9t5bAIqiYGdnh6KiIrDZbNjY2JgorAqFQsYWxlI4OjrCaDTWWRL3OkBuRKFQCA6HY9YijcDf3x9JSUlwdnZGdnZ2bQ2x2qAoCkFBQRg5ciQ2btxYbjSZw+Hggw8+gFwurzcewxXBz88P4eHh+Oqrr5j+xe+++w7Tpk3De++9h5YtW77TD82KQFEU2rZti+TkZOTn56NXr164e/dulX6TlcHV1RUlJSUWKwpbg5KSEtjY2CA+Ph4SiQQGg6FCAR+KotCvXz+8ePECKSkpJiI2Tk5O6N+/P/bv31/nibBWq8WWLVvg7OyMsWPHVkiCs7KysHr1anz44YcIDQ216vonVUYxMTEQCoVMBgcAo/xMhB/NGbdcLoeDg4NViyWNRoM9e/Zg0qRJJiWRqampuHv3LkaOHGnRdtVqNf744w/k5eVh6dKlsLOzq7QfWKfTYf/+/Xj+/Dk+++wzs/usK0NRURE2bdqEGTNmlCHVRqMRp06dYqzfXie0Wi3OnTuHYcOGMceUpmmcPHmywsCLtSC+yc2bN6+xbdYlUBQFsViMxYsXQ6FQMFVaxKKRzWZj8uTJkEql5QphmgOxWAwPDw8olUrIZDKTAKSjoyPUajX0en2F87per0d6ejo0Gg1CQkKqvK7z8vJw6tQpTJ061WIFcxLQCgwMhFKpBI/HqzKzq1AoQNM0Q8RelzVfXQU5hsQNwxzk5ORAIBBYbXdWXFxcacWGXq9nrud3GQ1E2AJIJBLI5XITUkxAVHCtsR/hcrnw9vYuI6P/LoH0CJcuozEXdnZ2kMlkCAoKYvrh6iooikKXLl0QEhLCRJpfBY/Hw+zZsxETE4OLFy/W2/JgqVSKTp06oVmzZmCxWBCJREhLS0PHjh0RGRn5podXpyESidClSxdcuHABdnZ2CAwMxP37960mhCKRCAKBAPb29oiPj69VYkkUo5OSkuDr6wuBQFBpaSyfz8fYsWPx119/mVRJEG9hhUKBe/fu1VkyrNPpsHfvXibIVd4ilKZp5OXlYe3atRg/fny1g0C2traws7NDcnIy2rRpw9go2djYwMXFBXw+36yAR3Z2NuRyuVXKykS92M3NzUQgS6fTYc+ePRg/frzZC2OaplFQUICVK1fC1tYWs2fPrlQNlaZpaDQabN++HUVFRVi0aFGVojHmQKFQYP369RgyZEgZpW+appGcnIynT5/WqEWRubh79y7c3d1NMnWxsbEwGo1Vlo5bCplMhoKCggorOeoDKIqCQCDAzJkzYWdnh3Xr1kEulzNkmMvlYvLkybCxsbGqnYmsBSIjIxEQEIDnz58zc5ijoyPT+1sRESYewzRNVxl00ev12LdvH4YOHQonJyeLxkkQFRWFpk2bIiMjA25ublUGsAiJI0RMJpNVqWBc33Hnzh106NDB7OAfeVZae8yqIsIGgwEURTVkhN/0AN4mECIMgCHCZOJis9lwdHQ0UcC1BC1btsSjR49qbKxvG8iNLhAIwGKxLCrPlEql4PP5sLGxQWJiYp1dEBOwWCyMGTMGKpUKZ86cKZfoCoVCzJ8/Hzdv3nzr+iAthVQqBZvNRmhoKO7du4cWLVrg6dOnb50Q0usEUSOPjIyEQqHAgAEDcOHChWpVEBAhpdpu00hPT4e9vT1iY2MhkUjg6OhYqXAIRb30xxWJRLh9+3YZn8/Jkyfj6NGjdVJ5X6/X46+//oJMJsO0adPKJfw0TaOwsBBr167F0KFDLeofqwhsNhvt2rXDnTt30KxZMzx//hwGgwFcLhf+/v4oKioyK2iYnp4OrVZrVVltbm4uLl26hAkTJpiURF+7dg0ikQht27Y1azuEYK5YsQKdOnXCxIkTq+wplsvlWL9+PUQiEWbNmlUj3qVarRY7d+5EcHAwepXy5yUg4lnvvffeaxXIAl5m3s+cOWOSYTcajTh58iSGDh1qtjCPucjIyICTk9M70e/J4/EwYcIEhIaGYuXKlSaVe2T+sbW1xR9//GFxzzDx/SbPPjK3OTk5wcnJCTwer8J5LTExEWw2G+7u7pWeX6KUrlKp0LNnT6vmFqPRiKysLHh4eCA2NtasntWcnBzQNA1XV1fQNA2ZTPZOC2VptVokJSUhJCTE7M+Q9gNrUZVvs16vZwIu7zIaiLAFIESYpmmmX5iA9HWQm99SvOt+wqXtk4xGo9k9wsDLRZ+bmxujvvg2CE1xuVx89NFHePjwoYmYDQFFvTShnz9/Pk6dOoUnT57UWzJMiDCbzTZRiq6uAFR9h52dHZo0aYJbt27Bx8cHXC4XsbGxVl8nISEhKCkpQUFBQa0FIYxGIzIzM8Hj8SCTycDhcMxSI+ZwOOUKZwEvCXzPnj1x+PDhOjV/Go1GnDhxAqmpqZg1a1aFi0CZTIbVq1ejd+/e6Nq1a41lTFq0aIGoqCg4OztDpVKhuLiYUcZVqVRVBm2JqBabzbY482cwGBhbJAcHB2afcnNzcebMGbP7/2maxv3797F+/XpMmjQJffv2rXLRlpeXh59//hmNGjUq41lsLfR6PQ4cOAAAeO+998qMnfTnCoXCN9LS8ejRI9jZ2cHX15d5LSUlBQUFBWjZsmWtfF9tbLeugsPhYPjw4ejRowd+/vlnZGRkmPyNlElv3brVovWHRCKBk5MTOBwOUlJSmHmXz+fDxcUFFEWVme+A/1kZ6XS6KrP9xcXFOHLkCKZMmWJxSTRBXl4eOBwObG1tkZCQYJaKcVFREQwGAxwdHRlPYT6f/05mhElZtKurq9lVMHq9HikpKWb3E5f3nTqdrtIgSUNp9Es0EGELIJFIoNFooNfrGdJbGt7e3khJSbFq2y4uLtDpdO9snzC5GXk8HrRabbmTf2UgojA8Hs/iz74JkB6k2bNn48iRI0hISCiXDDs7O2PevHnYtWtXue+pD5BKpaAoCvn5+TAYDMjKykLLli3rdLlrXcGgQYNw5coV6PV6DBw4EOHh4VZth1gYZWdng6KoWlOOJnMcefBSFGW2jY2zszNDeEtfFxRFoU+fPsjOzkZ0dHSduGaMRiPOnj2LJ0+eYP78+eVG5YmYyerVq9G5c2f07t27RkvUnJ2dwefzkZmZCX9/f8ZnPSAgALa2tkwPX0WgaRrx8fGQSqUW9buS/tGCggITWySDwYD9+/dj8ODBcHJyqvKcGwwGnDt3DocOHcLixYvRvHnzSj9DPDdXrFiBfv36YdiwYVYv/EuD9P1mZmbio48+AofDKTOO4uJiHD9+HBMmTKiR77QEWq0WYWFhGD16NDMuo9GIsLAwDBw4sMazwXq9Hs+fP6+XQlmVgcVioXfv3hg7dix+/fVXpoWkdM+wSCTCtm3boNFozJ6HOnXqhOjoaNjY2DDe6Gw2G7a2ttDpdCgpKQFN04ywEdkuKaV+tUS/NIxGIw4dOoTu3btbrD5fGklJSfD29oZOp0NhYaFZHsKFhYXgcDiQSqUwGo0oKSmpkcqMtxW3bt1Cx44dzZ7jS0pKoNPprC5lB8A4M1T2dxaL9U7dx+WhgQhbALFYDK1WC61WC7FYXKaP1d3dHVlZWVZtm8ViwdPTkxE1eddA+hS4XC40Gg2Ki4stWtD6+fkhOTkZXl5eVgcjXjeIVcPMmTPx22+/IT8/v1wy7O3tjVmzZmHTpk310ltXKpWCw+GApmm4uLjg0aNH6NChA+7du1enMnx1DcQX1snJiRGuycrKslowztPTEyUlJbC1ta21e4iIypBMo0wmM8liVQZSDp6eno6YmJgyJdJTpkzBoUOH3rgPt9FoxJUrVxAREYGlS5dW2BenUqmwdu1atGzZ0sTupqbAZrPRpk0b3Lt3D61atcLDhw9B0zQ8PDzg4OCApKSkSrNXRF1aIpFYZG+kVquxf/9+E1skktmVy+VVegbTNA21Wo09e/bg/v37+PLLL6sMltA0jejoaKxduxaTJk1Cjx49auR40jSNCxcu4PHjx5g3bx6EQmGZcRgMBuzbtw99+/atUZ9ec8f37NkzCAQCE4Xx7OxsJCUloVOnTjW+yJXJZFAqlVYp2b7toCgK7du3x8yZM7Fx40Ym8EZ6hqdOnQoej4dt27ZBq9Watb0WLVogPj4ejRo1QmRkJLKysnDz5k1kZWVBp9Phzp07+Ne//oXvvvsO//3vf/HHH3/g3LlzSExMhF6vr9DWjNwTaWlpGDBgQLWugydPnqB58+YoKSmpUtMBeHlPlJSUgMvlMkRYqVS+s6rRWq0W8fHxCA0NNfszmZmZcHV1tXoeIxnhygJzJGP8Lp6T0mggwhaA1NJrtVoIhcIyWRMbG5tqZSNbtGiBx48f1zuiYw5IVJXD4TCl0ZaQIFdXVxQUFMDf379cn966CuILO3r0aGzatKlckTCKotCoUSNMnjwZ69ats7r8vq6CEGGlUgkfHx/cvHkTrq6u0Gq1VonPvUugKApDhgzB2bNnweVy0a1bN1y6dMmq64PP54PH48HJyanW+oTlcjmEQiFSU1Ph7OwMDodjkSImn8/HxIkTcejQIRMSRwJGHTt2xNGjR9+YwBwpkb106RKWLFnCVDu8CpVKhd9++w1BQUEYPnx4rYmVtG7dGo8fP0ZwcDASEhKg1Wrh7OwMvV6P+Pj4StVutVotcnJymLJ7c0DTNMLCwhAaGsqU9JH+wL/++gtTpkypdBFNSijXrVsHg8FQpTI08HLRfe3aNezZswcLFiyosdJkmqZx/fp1XLt2DQsXLiy3pJGmady9exf5+fkm9lCvC3q9HqdOnTLpDaZpGufPn0fv3r1rpYc3NjYW/v7+NZ5pfltAURQaN26MBQsWYNeuXbhz5w4z3xCfYQ6Hw2SGq4JUKoVUKkVGRgY2bNiAzZs3IysrC35+fuDxePD09MS8efPw8ccfY/LkyWjbti2SkpLw8OFDPH36FNeuXWNa9kpDqVRi7969mDp1arV6cw0GA1JSUuDn54f4+Hj4+flVWUqr1WqhUCiYjDAhZdaqH7/tSEhIgKOjo0XezU+fPjXLFqsiGI1GGI3GKjPC7+p9XBoNRNgCUBQFHo8HnU4HgUAArVZrQtZsbGyg1+stUjwuve1GjRohISGh3vvHlgcSZCCRVblcbhERtrGxAYfDgb29PZKSkt4qpWWKohj15B07dpT78KQoCq1atcLo0aOxbt26cn2I31bw+XwIhUJkZWXBxcUFUVFR0Gg0aN68Oe7evVtv9rM2QCy5DAYDkpKS0KNHD9y/f9+iHnsCNpsNDw8PCIVCpoy2ppGWlgYXFxfEx8fDw8MDPB4PYrHYom0EBgbCz88PV65cKVMi3b9/f2RkZCAqKuq1Xzc0TePevXs4efIkFi1aZNIbWxoajQZbt26Fs7MzRo8eXav9WZ6enowXKZ/PR35+PhwcHODg4ACFQlFpL3hOTg7y8vIs8jJOT0/H7du3MXr0aBNidujQIXTu3Bne3t4VfpZ4KK9YsQLNmzfHhx9+WOUCXqfT4ejRo/j777/x6aefwtfXt8ZIcGRkJMLCwrB48WLY29uX+768vDwcPnwYM2bMeO0LStJ3SNM0goODmf0uLCzEkydPqsy8W/udDx48QOvWrd/pLBJFUfDz88OyZctw4sQJnD9/nlmv8Hg8TJ8+HRwOB9u3b6+UDNM0jZycHCQnJ+PevXto0qQJ5s6diw8++AAdOnRgRNdcXV3h4eEBX19ftGvXDi1btkSjRo0wfvx45OXl4fvvv8fTp0+ZOc9oNOLo0aNo1aoVAgMDq7WvhYWF0Ol0cHFxYYSyqjr3Op0OWq2WsU8yGo3Q6XQVBgbrM0hw1JLqDIPBgLi4OLNssSqCUqkEh8OpdF6qKmP8rqCBCFsILpfLZIQ5HI5JGR6Px4NEIkF+fr5V23ZycoJGo7FqEfu2g2SESbCBeOhZ8nkXFxcYjUYUFxdb5ev3JsFisTBixAgIBAIcOXKk3CAARVHo0KED+vfvj3Xr1tWb64TNZsPBwYGxV8jJyUFOTg46d+5cRiW4AWXB4XAwYMAAhIWFwcbGBo0aNbI6gBAYGAiZTIbc3NwaDyYRomNjY4OMjAyw2WzY2dlZnLWiKAqjRo1CREQEsrKyTPaTz+dj0qRJOHDgwGstkSZ9sfv378eCBQsYoZtXodPpsHPnTgiFQkyYMKHWyROLxUKTJk0QExODxo0b48mTJ+BwOIxHcWXHKCsryyLFaGITNWbMGCbzQ8ozExMTMWjQoErtjh49eoSVK1di7NixGDhwYKULNJqmoVQq8ccffyAzMxPLly+Ho6NjjZHgqKgoHDx4EIsXLy63R4+maWi1Wmzfvh1DhgwxS/CtpkHE2IYPH84cK5qmcenSJXTq1MniAJM50Ol0SExMtEj5tr6CtDZ98cUXuHv3Lg4dOgSdTgeapsHhcDBt2jSwWCzs2LGj3DJp4hu+Zs0ajB49Gm5ubmjVqhViY2NBURRjUVTeZ58+fQqKotCtWzd8+OGHmD17Nnbu3MnYpMXFxSE6OhojR46s9nVJ+oPJv80h1lqtlkkYsdlsGI1GpqXwXYNGo0FsbKxFnttE3LA6rRbE77mqjHADEW4gwhaBoiiIRCIolUqw2WwIhUKTUmiKouDo6Gg1EWaz2e9sn3Bp5TqJRAKDwWBxZjw0NBQJCQkQiUR10kqlKrDZbEyZMgUZGRk4d+5cuUSGxWKhR48e6NSpE9avX29V9UFdA4vFgoODA+zs7KBUKiEWi/HPP//Aw8MDer3e6p7XdwUURaFly5bIyMhAbm4uI6BlTo/aq9sJCAhAbm4udDpdrQhmpaenw9bWlrF1cHNzs3ihRlEUpFIpRo4cif3795sEjUiJdNeuXXHw4MHXUhlCMnPbtm3D/PnzKxSlIURRp9Nh6tSpry2D2L59e0RGRqJly5ZMn7C/vz8UCgWSkpLK/QxRjOZyuWb1cJMSYQDo2LEjs/9yuRy7d+/G9OnTK8zu6vV6nDt3Dn/++SeWLFmCNm3aVFoqTnqXf/31Vzg6OmLu3Lk14hFMth0XF4cdO3Zg/vz5FV6fNE3j9OnTkEgktZJ5NWeciYmJUKlUJh7Ncrkcd+7cQZ8+fWplTMQb1lzl2/oO4u6wfPly5OTkmJRDc7lcTJ8+HTRNY+fOnWWqL4jP9aRJkzBgwACIxWK4u7vj77//RmFhIaOXkpubi6tXryImJgaxsbHIy8tDYmIiM9dRFAV/f38sW7YMhw4dQnJyMnbv3o0pU6ZUW5yKBKhatWoFrVYLtVpt1rkvKSkBh8NhiC8JXL2LRDg5ORl2dnaV+vm+ivz8fNjY2FTrGaFUKsvVNCiNhtLol2ggwhbCwcEBBQUFoCgKNjY2ZbJyPj4+VgvNUBSF5s2bv5N9wqUzwmKxGDqdzuKMsJ+fH9LS0uDn54e4uLhaHG3tgKIoCAQCfPzxx7h16xbu3LlTIRkeMGAAQkNDsXnz5lpT+H1dYLPZkEqlEIlESE1NRUhICO7duwcOh4M2bdrgzp07b3qIdR5CoRDdu3fHuXPn4OnpCbFYbJWVkpubG+RyOWxtbZGWllajYzQYDExQg6jvW2sNQVEUWrduDR6PV6ZqgJRI5+bmMsSvtkDTNJKSkvDbb79h3rx58Pf3r5AEHzhwAMXFxZg1a5ZF4lPVAQluENGrvLw8aLVa+Pn5obCwEMnJyRV+lgQVzV34Hjt2DFOmTDHxsT1y5Ajatm2LwMDAMseFpmmoVCrs3LkTDx8+xNdff80s7CsCIYA///wzevTogfHjx9fYQo6maaSmpmLz5s2YPXt2hWXWNE3j4cOHiIyMrJYlTXXHeuzYMQwdOtREkOzy5cto1apVhaXc1f3Ox48fo2nTpu+83cqrEAqFmDNnDgQCAdavX89UWvB4PHz00UfQ6XTYvXu3CRmOiIiAr68vmjVrxljJbdq0CRs2bECHDh0wb948qFQqPHnyBIMGDcLXX3+NKVOmoHPnzti7dy9iY2Nx9+5dJhDo4OCAvn374vPPP4e/v3+latLmQqfTISkpCY0aNUJ6ejocHBzMItc5OTng8XhMT6zBYIBcLn/t/tpvGqQsukuXLhZ95vnz5wgJCamWdoQ5gYeG0uiXaCDCFsLOzo4R8LG1tS2TefTy8kJ6erpV2yYiDLGxse9knzCbzQaLxYJAIIBSqbT4GHh5eSE/Px9eXl6Ii4t7a4MJNjY2mD9/Po4dO1ZGHZeAzWZj1KhR8PDwwJYtW95qMsxiscDn86FSqZgepIiICMjlcnTu3Bn//PNPrfna1heQMrnHjx9DoVBg0KBBOHv2rMUZUVLK5uTkhJSUlBq9hwwGA7RaLbKzs8FisaDT6eDh4WH19jgcDsaPH48zZ86gqKjI5G9EwfXo0aNl/lZTIKXeGzduxPTp0xEcHFzu+/R6PY4cOYLc3FzMmTPntZFgAh6PBz8/P2RmZjJCaJ6enpBIJJVqDWRlZcHZ2bnKxZTRaMTx48fRqVMnpkSYpmk8ffoUcXFx5ZZn0jSNgoICrFq1Cnw+H4sXL65SUdZoNOL27dvYuHEjpk2bhp49e9aYyBhN08jMzMTatWsxbdq0SnvzUlNTsWfPHsydO/eNif8kJyejsLAQrVq1Yl5TKpW4fv16tRWCKwIJALRq1eqd6/M0B3w+H5MnT0ZwcDB+/fVXpjKQz+dj5syZUCgU2LdvHxPkv379Ovr27YvMzEwMHToU//3vf3HhwgXk5uYiLS0N6enpzPyt0+nQqVMnuLm5IS4ujukp/vvvv5n797vvvsNvv/2G69evIy4uDvv37692ixhZ39ra2uLFixcIDg42657Lz8+HVqtlSnvVajVUKtU7R4RVKhVevHhhkYAfTdOIiYlh2leshVKprPJ4N5RGv0QDEbYAJAtMyqFdXFzKlG06OTkhLy/P6gWkvb09I27yroH4M3I4HBQXF1tMhEnftrOz81snmPUqXFxcMGfOHOzYsQPp6ekVkuHx48fD3t4e27Ztq9QKpS6DzWYz1RVarRYeHh6Qy+VIT0+Hu7s7eDxehSWcDfgfbG1t0bx5c1y7dg2NGzdGfn6+xWXlXC4X7u7u4PP5ePHiRY2OT61Wg8ViITMzEy4uLuBwOHBwcKjWNp2dndG3b18cOnTI5H6nKAoeHh7o3bs3Dhw4UOOBRZqmkZubi3Xr1mHChAlo1qxZuYsWg8GA48ePIzU1FXPmzAGfz38jJIKUR4eGhiI6OpqxUMrNzS13btFoNEhKSkJQUFClGVeappGQkIDnz5+b9AArlUrs27evXMVa8pkVK1agU6dO+OCDDyAQCCo9LlqtFocPH8bZs2fx2Wef1Ui2qzTy8vKwdu1aTJgwoVK/4oKCAmzYsAFTp06Fl5dXjX2/JTAajTh58iQGDx5s0l9P7ntLPJ8tgVKpRGFhYYV2PQ14uYYZMWIEevXqhZ9//hmpqakwGAy4fv06Bg8ejMLCQhw6dAgFBQXQaDRwcXGBi4sLBg8ebNLK4ufnZ3JupVIpBgwYAE9PT+a1wMBAzJ07l8nOy+VyHD16FJmZmfjpp5+wc+fOaq+BXrx4gYCAALDZbERHR5utYlxYWAiappn+eoVCAa1W+84R4aSkJDg5OUEikZj9Gb1ej6ysrGrPLwqFosogZkNp9Es0EGELUZoIu7q6Iicnx+TvTk5OkMvlVpMSHo8HHx+ftzqjaS04HA5j7i2TySzuf2WxWHB3d4dcLodKpXqrs4ik1HvSpEnYtGkT82B5FWw2GxMnToREImFEOd6264bFYsHe3p4JgpDSq4iICFAUhR49euDatWtv3X69blAUhYEDBzLHqkePHrhw4YJFx41cdyqVympP9IqQnZ0NqVSK5ORkSKVScLlci/qmygO5PgoLC8u0lJC/aTSaGhVdo2kaxcXFWLlyJUaOHIm2bduWS5wIYXnx4kWFHrSvAxRFITQ0lCG20dHRcHV1BZfLRWJiYrnCfIWFhYyFS2VjJiWfEyZMYBa5NE3jyJEjaNGiBYKCgkw+T7K6GzZswIcffog+ffpUWmZL7JQ2bNiA/Px8fP755xUKkVkDmqZRVFSEtWvXYujQoWjXrl2F5dAKhQIbN25E//7932hWND09HRkZGejQoQPzmlKpxOXLlzF06NBaG9eLFy+YtosGVAwWi4VevXph4sSJWLVqFbZv344pU6Zgw4YNmDVrFjIyMrB//34mKMbhcLBo0SKMGDECFEWBoij4+vqaeM62bNkSAQEBjJ82m83G0qVLTVoxSguYkZLs6tgmEdG4Fi1awGAwIC8vzyzvaNLDT8QQKYqCQqEAi8V6p4gwKYvu3LmzRfdkcXExuFxute+zoqKiKp+varW6VizW3jY0EGELQYgwTdOQSqVlfIPLU5O2BBRFoVmzZnjy5ElNDPetAimNBl5GN60RvAoODkZqairs7e2tLlGvKyA944MGDcKGDRugUCjKLObJQ3HSpEngcrnYuXPnW1lW7+joCBsbG/D5fCgUCoSEhCAiIgJ6vR7t2rXD8+fPX6sK8NsKYrPx4MEDdO7cGU+ePLH4uIWEhCA/Px8qlarGKlOIQippLeFyubCzs6uRXkMOh4MpU6bg8OHDZTQbOBwOJk2ahLCwsAqzn5aAeOL+8ssvGDBgQIWLHKPRiLCwMDx58gQLFy6ESCR6o+WkYrEYDg4O0Ov1KCkpgcFggK2tbYVEOD8/HwaDoVKFWKJQ7OrqymTESUn08+fPy3jb6nQ6HDlyBGfOnMEXX3xhIvJU0fbT0tLw448/Ijg4GLNmzarRYAJN05DL5Vi3bh26deuGbt26VUiCtVot/vjjD4SEhKBv37418v3WwGg04tSpUxg8eLBJb/Dt27fh7+9vFlGxBjRN459//kH79u0byqLNALE77NGjB5YvX46srCzs3bsXUVFRmDdvHvLy8pCcnAyaphnxvxUrVqBZs2ZgsVgoKirC6NGjmbLVvn37QiwWM/7NLVq0wPvvv8+ci5ycHNy4cYPpDW/ZsiUGDx5crXOl1WqZ4FlmZiZEIpFZrQCENJeu+CH2be9SEEWtViMuLg5Nmza1uCza39+/2iXLBQUFVVZcqdXqaguq1Qc0EGELYWdnx3jcSqVSyGSyMour0lljaxASEoK4uLi3urTXGpCMMIvFYhacloAIw5Q2f3/bs4ik97NNmzbYvHlzuZUGxHt56tSpoGm6jChHXQdFUYwIB4/HQ3Z2Nry9vZGQkAC5XA6pVAp/f388efLkrT+frwNDhw7F+fPnIRKJ0LRpU0RERFh03JycnKBQKCCVSmtUsTszMxO2trYoLCyEWCyuMcsZUgbdpUsXHD9+vIyKtJOTE0aNGlUjQSKFQoG1a9eiS5cu6N27d7n9ckajEefOncO9e/ewZMkSSCSSN04e2Gw2WrVqhefPn8PZ2RmJiYnw8fFBZmYmjh49ir1792LPnj04fPgwLl++jH/++Yexh6kIOTk5uHDhAiZMmGBSnrlr1y5Mnz7dJEMsl8uxceNG5OTkmJXVJZnjNWvW4P3338fQoUOZ1pmagkqlwsaNG9G8eXP079+/3HNJ0zT0ej12794NGxsbjBkzhqlaehPIzMxESkqKiSepWq3GhQsXMGLEiFr7Xr1ej4SEBDRq1KjWvqO+ISMjA//973+ZtWBBQQF++eUXAMDChQuRmpqK06dPw2g0MmuXVatWwcnJCba2tvDz80NAQAA4HA46d+4MlUoFV1dXsNls9OrVixGiIlUZU6dOZYjyjBkzql1tk52dDZFIBLFYjISEBAQEBJjVH2wwGKBSqaDX602IsFgsfu36CG8KRH3e3d3dorJoAIiKiqqw1cYSyOXyKgMPKpWqWlUD9QUNRNhCSCQSqFQqhgiX53fr4eFRrWykvb09DAZDtcj024jSPsI8Hs+qDKC7uzvy8/MRGBiIp0+f1sIoXz9YLBYGDx4MHx+fCj0JgZflUNOnT4dWq8XevXstts95k7Czs2OEPYqLixEQEACaphEZGQngZUT8ypUr5WavGvA/ECsNDoeD+Ph49O/fH1euXLEoMEKIm52dXY1WVaSkpIDFYjH9Yub4UZoLiqLQt29fZGRk4OnTp2VKpNu1awcHBwecP3/e6mCKUqnEpk2b0LRpUwwaNKhCEnzp0iXcuXOHIcF1BS1atEBkZCTkcjm+//57ZGdnQ6PRwGAwwMfHB35+frCxsUFOTg7CwsKQlZWF48ePIzk5uUxQVq/XY//+/Rg6dCiz2DUYDDhw4AA6duyIoKAgAP8TFPvpp5/g5+eHjz/+uMrAgFqtxsGDB3H+/Hl8+umnaNmyZY2JYpX+jt9//x1+fn4YMWJEhZUJRqMRBw4cgFqtxuTJk99oPx3JBg8YMIApZ6RpGvfu3YO7u3utehmnp6dDLBbD0dGxVrZfHyEUCjFq1Ci0adOGybqFh4fj3LlzcHR0ROfOnXH48GGcOXMGKSkpuHbtGjIzM9GsWTOo1WqEhYUhMDAQbdq0wenTp/H999/jyJEjTABr5cqV2LVrF7Zu3YrMzEy0adMG7du3R0hICEaNGlWta4GmaTx48ADNmzcHm81myJk50Ov10Gg0jAgm8HLulEgkNX4f12XcvHkTnTt3tmifjUYjUlNTzbKsqwoajaZKkktsDN91vDtXZQ2BPDANBgPEYjHjj1Ya3t7e1fICJn3C1tifvM0gEX8ejwehUGgVEebz+eByuUw2q74cPzabjbFjx4LH41Uq/kN6g9Rq9VtFhm1sbFBcXAyFQgEulwsXFxfY29vjxo0bAAB/f3+oVKoGT2EzwGazMXDgQISHh8PNzQ329vaIjo42+/M8Hg+urq4QCoU1JphFej1LSkrA5XLBZrMZRdGaAo/Hw8SJE/HXX3+VmZPZbDbef/993L59GwkJCRZvW6PR4I8//oCnp2eFxImmaVy9ehXXrl3DokWLqlRBfp0wGo1ITk7GtWvXwOPx0LhxY4wfPx4sFgvNmjVDjx490L17dwwYMADvv/8+goKC0LNnT7Ru3RqbNm3CkSNHmLmEqAfLZDLGQ5csnNPS0jBs2DBQFAWj0YiHDx9i5cqVGD16NEaMGFGl8FZeXh7WrFkDuVyOTz/9FK6urjV+DLVaLbZv3w47Ozu89957FZJgInSWmZmJmTNnvvFeuuzsbCQmJppkg7VaLc6ePcv0l9YWHj58iBYtWtSZ6/ltgL29Pb788ktcvHgR+/fvx/vvvw+pVIpffvkF0dHREIvF0Gg02LNnD3bv3o3U1FR4e3tj3bp1+Ouvv7B9+3YcPnwYV65cwYoVK/Dtt9/i559/xr1797BhwwaMGDECQUFBsLe3h6OjI1avXo309HQ0btwYJSUl1dILIVZZrVu3hsFgQHp6Onx8fMz6LOkHFgqFDAlUKBRvTCPhTUCtVjO2U5aAWLOSbH91YE621xyy/C6gQTfbQpDSXYPBYGL1Q8pQKIqCm5sb419pzY1PURRatGiBhw8fon379jW9C3UWbDabybQLhUKrMuIcDgdeXl4oLi4GTdMoLCysN1FsNpuNKVOm4LfffsPJkycxatSocqONPB4PM2bMwI4dO5iSKS6XW6cfQnZ2dkyJmKenJ/R6Pezt7fHw4UMmatmtWzdcvnwZkydPrtP78qZBesuPHTuG7OxsDB48GGFhYWjRooVZPbkkq5ySksIEk6p7vEm5XE5ODmxtbWuFCFMUBR8fH7Rr1w5Hjx4tc51IJBJMnToVu3fvxqeffgqxWGzWful0Omzbtg1SqRTjx48vt3eLpmlcv34d58+fx/LlyxmRmLoAmqYRERGBc+fOYcyYMWjVqhUuXrwIGxsbqNXqMqJoGo0GL168QMeOHdGjRw+0a9cOO3fuxO7duzFt2jSo1WocOnQI8+bNA4fDYQSnDhw4gIULF4LH48FgMODs2bO4fv06li5dyoj8VDbGqKgo7NixA8OGDWOskWryGNI0DYPBgL1794KiKEyePLnSTPCFCxcQFRWF5cuXv/GsCU3TOHnyJPr168eMhZAVe3v7Kv2XqwODwYBHjx5h6tSptbL9+goifGVvb48RI0agd+/e2LNnD/bu3Yvt27eje/fuGDduHLy8vJgkgLnnkGTnQ0JCQNM0aJqG0WhEZmYmoqKicPDgQcjlcnTo0AG9evVieofN3T4RK3VxcUFeXh4jaGkOcnJyIBKJGOJLWiN4PN47kxGOjo6Gj4+PWR7spZGQkABfX99q9wfTNG0WyW3wEX6Jd+OqrEEQIkwycmKxuEz2wc3NDfn5+dXqRwsMDERSUlK9yWiaAw6HA71eDxsbG8ZCyZr9J33C7u7u1crM1zVQFMV4EsbExODSpUvl9pGTnuHp06eDpmns2LGjzvcM29nZwdbWFnq9Hu7u7sjMzISjoyOEQiGioqJAURQ6derE+OQ2oHLw+Xz07NkTZ8+eZTIElpQ5BwcHo7i4GDKZrEYEswoLC8HhcJCdnQ0+nw8Oh1MrZcMURWHAgAFITk7Gs2fPypRIBwUFoV27dvjrr7/M0mDQ6XTYtWsXaJpmAkqvgqZp3LhxA2fOnMGyZcvg4OBQp0hwRkYGLly4gMWLF2PYsGF48OABXFxcIBAImHOiVqthNBqh0WhQVFSE/Px8BAQEgKIoiEQifPzxx1Cr1bh48SJOnjyJ1q1bw8fHBxRFMeSyT58+8Pb2hkqlwtatW/H06VN8+eWXlZJgsmA7evQo/vzzTyxYsAC9e/dm2mRq8jgYjUYcOnQIJSUlmD59eoXBQaPRiOvXr+PGjRtYvHhxnRD4yc7ORnx8PLp06cKM2WAw4NSpUxg+fHitEozCwkIoFAp4e3vX2nfUV9A0DZVKhTNnzuDf//43+Hw+/vzzT/z6668YPXo0AgICGIJo7fVOURRYLBY4HA68vb0xaNAgfP3111iyZAn0ej1+/PFH7N271+z1FBG8CwgIgEAgQHx8PDMXmIP8/HzGOolclzKZDFwu950gwiQoWpH4XmV4/PhxjVRe6PV66HS6Kolwg33SS9T/q7KGQSTgiZATKeksDYlEAr1eXy1fVycnJ6ZU7F0ByQjb2NjAaDSiqKjIYiJMURSCg4MRFxeHkJAQPH/+vJZG++YgFosxd+5cRERE4ObNm+UeI1Ji/uGHH4LD4WD79u1MD25dhEAggJOTE7RaLSQSCQoKCuDu7g53d3dcvnwZNE3D1tYWoaGhuHPnzjsVILIGFEWhc+fOeP78ORQKBfr06WORlZKzszNkMhn4fL5V6u2vIjc3FzY2NigqKoJEImHssmoDAoEAkydPxoEDB8q0VxCinJ+fj3v37lV6PHQ6HQ4ePAiFQoGZM2dWSIIjIiIQFhaGZcuWwcnJqc6QYIKjR49i9OjRsLe3h5OTE54/f45nz57hhx9+gEwmw5dffompU6ciOjoaw4cPx8KFC5GUlISYmBhGcDAvLw/jx4/H8ePHcffuXQwbNowRNbxx4waUSiX69euHvLw8/PLLL5BIJFi4cCFsbW0rJcEFBQVYs2YNcnJy8PXXX1dp12QtjEYjjh49ivT0dMyaNavCBSLRJTh79ixT3v6mQdM0Tp06hT59+pgIkEVHR0MoFFpEUqzB06dPERISUiMK7+8SiALwDz/8gKysLHz++eeYMWMG/P39azzQUxoks+zq6opx48bh//7v/yCRSPDDDz/g1q1bZuls3Lt3D+3atQPwP3JmDshcYTQamUo8YjfH4/Hq3NxYGygqKkJOTo6JnZU5MBgMSE5Ohp+fX7XHQNZ65hDhhoxwAxG2GCwWi1E+BV6KM71aWkZEAlQqldXfw+FwGOXjdwUkIywWi6FSqVBUVGSVcrajoyOKi4vh6+tbL5Sjy4OdnR3mz5+P8+fP459//qlwH3k8HqZOnQqBQIBt27ZV65qsTRBP2ZKSEhQVFYHP58PLywsikQh3796FUqkERVHo168fLl++3CCaZQakUilat26NK1euMKTYXFJLyuAEAgEyMzOrPZbc3FxIJBJkZ2eDy+XWiBhIZfD19UXHjh1x9OjRMtcKn8/H1KlTceLECeTm5pb7eYPBgGPHjiErKwsff/xxuWqnxCfy9OnTWLJkCZycnGplX6qDvLw85ObmokmTJjh27Bjee+89HDp0CDt37sSDBw+g0WiQlZUFjUYDBwcHPH36FH/99RdSU1Px3//+FxcvXkRhYSHGjBmD/+//+/+QkJCAkJAQKJVKaDQaZGRk4OTJk5g2bRoSEhKwYsUK9O7dGxMmTKi0p9ZoNCIqKgo//fQT2rVrh1mzZtWaurbBYMDJkycRFxeHuXPnVpjhJaXGhw4dwsKFC+tMUCM7OxsxMTHo3r07Mx6j0Yjjx49jxIgRtbqQNRqNiIyMNPEsbkDVMBqNuHjxInbu3InJkydj+vTpNep/bS4oioKNjQ1GjRqFpUuX4sqVK9i3b1+l2iEajQYpKSkICAiARqNBamoqQkJCzB47qfpxdHRkPiOXy98ZsaxHjx6hUaNGFvfels6kVxdqtRpsNrvKuaGhNPol6v9VWcOgKAq2trbMgtLR0RH5+fkm72Gz2XBycqq2sE+rVq2YXuN3ARwOhxEhUygUUCgUVhFhkUgEgUAAgUCAoqKiOkv+qgsHBwcsWrQIx48fx4MHDyq8TjgcDiZPngwbGxv88ccfNeYNW5Pgcrng8XhQqVSQyWQIDg6GwWBg2guIAriXlxekUqlF4k/vKkjgICIiAiwWCy1btqywguBVkDlMKpXWiGhfcnIyeDweM2+aK7xiLSiKQv/+/ZGVlVWu7ZazszNGjhyJ7du3l1kUEnXe+Ph4zJ07FwKBoMwikPiqnjhxAosWLXoji1xzkJSUBA8PD3C5XNjb2+P58+dQqVRljkeXLl3g6OhoUv7apEkTjB49GpmZmYiOjsbvv/+Oixcv4vPPP0ePHj3w888/Y9OmTRg3bhyePn2Kbdu2Yfbs2ejevXuF2UPiyXvs2DH8+eefmDt3Lvr06VNrizGDwYDTp08jOjoaCxYsqLAcn2TvduzYgYULF8LNza1OnE+apnH69Gn07duXyQYDYCqdatvOSKFQIDMzE0FBQXXieLwNoGkaFy5cwO3bt/HFF18gNDT0jRNAYjG3bNkyRqCrota92NhYODs7w9bWFgUFBeDxeGa3B5CMMLFEJK+p1WrY2Ni88eNQ2zAYDLh16xa6detm8WdTUlLg5eVVI8dIrVabRcQbSqNfon5flbUE4hNM1N2KiorKvMfLywtpaWnV+p7AwECkpKTU+f7OmgKXy4VWq4VAIGB86Kwhwmw2Gz4+PsjKyoJIJCoTqKgvoCgKjo6OWLRoEQ4ePFjGNqb0+9hsNiZOnAgPDw+sX78ecrm8TgVYiJIwj8dDbm4umjZtylRatG/fHqdOnQJN02Cz2Rg2bBhOnz7dkBU2A87OzvDx8UFkZCT69euHa9eumaUkTlEUAgMDodfra6TPPicnhynDIoJ2tb2w5nK5mDJlCo4cOYKSkpJyLZW8vLxw4sQJZp6haRrnzp3Dw4cPMX/+fIhEonJJcGRkJA4fPozFixfXirJxTSE7O5shdT169MCnn35ahnSy2Wy0a9cOHA4HzZs3B/Dy2C1atAjOzs54+PAh1Go1I8ojk8kQHx+PH374AS9evMCzZ89w48YNfP7555USJpqmkZWVhRUrVjCl0P7+/rUq8nT69Gk8efIEixYtqjQTnJSUhN9//x0LFiyoVeEpS5GVlYWYmBj06tXLpDf4xIkTGDlyZK1mc4gXqre3d4OyrJmgaRrPnz/H7du3sWTJkgpbA4g/tV6vh8FgYO6t0q8ZjUaTOYuIvZV+P/n3q9us6NnO5/Mxbdo0aDQaXL16tcz7SKtH165dAQDPnj2ziMiTnmilUglnZ2fmdY1GUyfaDGobeXl5UCgUFpc30zSNJ0+emF2CXhXMJcINGeGXaCDCVoAQYZqmYWdnV0aEgKIoRvCnOmTDwcEBLBar3hK5V8Hn86HRaCASiaDT6aDRaKwiwhRFISQkBDExMfD390diYmItjLZugPQCzZ8/H3v27Kkwe0fI8JgxY9C0aVOsXr3aajGy2gCXy4WNjQ1sbW2RnZ0NLy8v5OTkwN3dHV5eXrh37x4TcGrcuDG0Wq1VNjjvGiiKwrBhw3DhwgXY2dnB1dW13AxpeQgKCoJarUZeXl61+suJqnBxcTGjeFvTitHlgczDPXv2xMGDB8vMJSwWC++99x5evHiBx48fw2g04vLly7h58yYWL14MqVRaLgm+d+8eDh48iCVLlsDd3b3OkKaqwOFwMHv2bAwZMgQAmEy3k5MTvL29wWaz0bhxY1AUhfbt22PUqFGgaRqPHj0qE4wlmd2wsDDcvHkTS5curbCUmCzQb9y4gV9//RV9+vQxy0+4OiAkOCoqCgsXLiz3XJKxpaenY9OmTZgxY0at99taAqPRiLCwMPTv399kURsXFweVSmW2r2t1cOfOHbRv377eZ/JqCjqdDsePH8e0adMqVaUvKSnBv//9b4wYMQJbtmzB/v37kZKSgm+//RajRo3Ctm3bsGfPHsY5Q6fTITIyEgcOHMDhw4dx//59FBUVYeXKldi3bx/0ej2SkpKwaNEirFmzpsJgJxHSnDRpEm7cuFHGmUOpVCI+Ph7NmjVjlNybN29u9j1hNBqZJAYhvoQcV3QP1heQAGnr1q0t7qc3GAxITExEcHBwjRwjc22RGnqEX6JhdrMChPwCL3vpFApFmYnHy8sLGRkZVhE5AoqiEBAQgLi4uGqN920BIcISiYSxpbL2+Pn5+SE5ORmNGjVCTExMnSF8tQGKouDl5YVZs2Zh27ZtSExMrHB/2Ww2hgwZgs6dO2PVqlXIy8urE8eGy+XC2dkZPB4P+fn5YLPZTC+pTCaDQCDAo0ePQNM0WCwWhgwZgjNnzjRkhc2Ar68vBAIBXrx4gYEDB+Ls2bNmnXMPDw9GsK465fRqtZpRI+bxeBAIBOX23NYGSCZUoVAgMjKyzH7z+XxMnz4dR44cQVhYGC5duoQlS5aU6+NI0zTu37+PQ4cOMSS4rsPZ2Rk5OTnM/21tbfGf//wHfn5+CAgIgEgkgkgkYhapoaGhEIlEmD59OqRSKbRaLR48eAAWi2XSu0bmZZVKhbNnz+LOnTvlfj8Ryvn9999x48YNfPrpp+jSpUutCi/p9XocPXqUKYeuKBNF0zRycnKwYcMGvP/++2jatGmdWqhnZ2cjNjbWRH1Wr9fj5MmTGDlyZK2LV5FgY+PGjWv1e+oTSAtIVVUFtra2GDlyJGiaxqxZs5CQkIB79+4xCuAzZsxAfHw8bty4AZqmceXKFSQnJ2PChAkYM2YMHj9+jNjYWEyePBl79+5FWFgYfH190aNHD4wbN65Kz2sbGxs0bdq0jPBkYmIi0xKj0WiQmZlpkZ5DSUkJOBwOeDweU3JL7JMstRJ620CCFZ07d7Z4HikuLobBYGDKyasLhUJh0kpRHkiAsqE0uoEIWwUHBwcUFhaCpmkIBAIYDIYyRNjOzg4KhaJaFkoA0LJlSzx+/LhOkJXahkAggEajgVQqhUAggFwut5roODg4QKFQwMPDAykpKdU+D3UdJGgyY8YMbN68uVIyzGKx0KdPHwwcOBCrV69GVlbWG7++KIqCs7MziouLodPpoNfrERISApVKhdTUVPTp0wcnTpyAwWAARVFo3bo1cnJyqt1+8C6AoigMHToUZ8+eZQRQkpOTq/wcEczi8XhlBAEtQUlJCbhcLoqKimBjYwNnZ+fXqkDL4/EwefJknDp1qow4FskaBwYGYtWqVfjkk0/KXYzQNI2HDx/i4MGDWLhwITw8POoUaaoInp6eSE9PZ8os1Wo17Ozs8N5774HL5TIqzevXr8ePP/6IK1euwNHREdnZ2bh+/ToeP36MuLg4TJ06Fb/88otJZpBkk1u3bl3udxNBrP/85z/w8fHBsmXLar33VqfT4c8//2SyY5WVYxYWFmLNmjUYNmwY2rZtW6fOp9FoxOnTp018g4GXPd8ymQwtW7as9fEmJSXBwcGh3hOYmsSzZ8/QqFEjs84NRVEoKirCkydPoFarmTYBuVyOR48egcfjoUmTJgCAXbt2McrdXC4Xnp6eOHToELhcLoYPH47bt2/j2rVrzHbN+e4WLVrg8ePHzGtE/K9Lly4AgLS0NNjb21vkoV1YWAiRSFRGqKmkpKRO2JDVJjIzM8HhcODi4mLxZ5OSkpiqnJpAYWFhlaSalNY3ZIQbiLBVEIlEUKlUMBqNYLFY4HK5ZUoHeTweUz5mLUiJb2pqarWsmN4WkIywWCyGSCSCQqGwOhMlEolga2sLtVoNrVZbxkalPoJYR82aNQubN2+u1IeaxWKhS5cuGDt2LFatWoXk5OQ3SoZJvzMhwmq1Gm3atEFaWhpomkazZs1w9+5dJrvF5XIxePBgnDp1qlpVF+8CKIpCkyZNUFxcjNzcXPTt29esrDCLxYKjoyNsbW2RkJBg9fVBiHBKSgo4HA58fX1fe6mlk5MTRowYgd27d5vMyUQp+MmTJxgxYkS5mU3ynn379mHBggXw9PSsU6SpMri5uUGj0eDSpUvYvHkz/vWvf2Hr1q0IDAzEf/7zH2zbtg0nT57EjBkzMGHCBMyYMQOHDx9G165dkZKSgpMnTyI4OBg+Pj7Q6/WwtbUFn89H27Zt8cMPP+Dy5cs4evQoevfuzXwnqSDYv38/Dhw4gLlz52LYsGG1WgVA/Ih37NiB4uJiLFiwoNKe4JKSEqxevRr9+vVD165d69T5pGmayQa/6ht8/PhxDB8+vNYXrzRN4/bt2w1l0RZCqVSWqytQEXQ6HdLT0zF9+nS0bNmS2cbNmzfRrFkzRlTQ3t7e5DlH0zRjTySRSDB//nwcPHgQz549M3usQqGQ6f0HXlZ3xMbGMn2q9+/fR6tWrSw6/wUFBWCz2RCJRMw1qtPpIJPJ6jURJjZy1lS7kOdLTfUHAy+JcHlVTaVB+tAbiDDQcASsAFE3JmWahMCVBpfLhYODA7Kzs6sVURWJRODz+SgoKICnp2d1h16nUVosSyQSoaSkBCUlJVaVIFIUBT8/P6SmpsLFxQWZmZlMhqs+g5DhmTNnYvPmzZg3bx58fX3LfTBTFIU2bdpAKBRi/fr1mDFjBtMj+CZga2sLvV7PlNH6+fkhLy+PyWL6+Pjg/Pnz+PDDDxmxo/DwcKSlpdUpgZu6CC6Xi379+uHs2bP44IMPcPr0abOixsHBwXjx4gWSkpKs/u6cnBxQFIW8vDy4urq+FqGsV0Gul+joaFy8eBGDBw8G8FJ9d+fOnViyZAmcnZ2xcuVK+Pv7o1WrVqAoiumR3b17NxYvXvxGxm4NSDni5cuXkZmZifv376NPnz6YPHmyyfOosn0hC2StVoukpCRcv34d7dq1g5ubG7788ksm81V6G0R9eefOnWjatCm+/vprCIXCWj1mhHj//vvvsLW1rdDuqvR7161bh44dO6JPnz518nyeOHEC/fv3N/ENTk5ORlFREVq0aFHrYzYYDIiOjsaQIUPq5PGpq3B2dkZubi5omq7y3tJqtXBwcMCAAQPA5XKZYI6joyNmzpyJ06dP4+LFi+jduzemT5+OmJgYBAUFQa/XIyMjAxMmTIBGo4FWq4WbmxsWL16MRYsW4aOPPjJrrLm5uUxfP03TePHiBdzd3SGRSGA0GvH06VPMnj3b7PNP0zRjAUT0bQAw4llVleq+zdBqtVbfLzqdDvHx8RgxYkSN3WsKhQI+Pj6Vbo+Iqr2uNqW6jIZQnxUoTYQpioK9vX0ZQSsWiwV3d3dkZGRU67uIgEl0dPQbL1+tbbBYLBiNRqaHUK/XQyaTWb29xo0bIyYmBqGhoXj27Fm9P34EpJJg+vTp2Lx5c6XZXoqi0LhxYyxYsAA7d+7EnTt33liG1dbWFlKpFHq9HllZWZBKpXB0dISDgwOio6MxePBgnDhxggk68fl8DBkyBCdOnHhnzq21IAJIsbGx0Gg0aNu2La5du1bpcaMoCv7+/tDpdMjMzLS6vSA1NRVCoRAsFgtsNrvWPYQrAovFwrhx43D37l0kJCQgLi4Of/zxBz755BN4e3tDKBQyGdHs7GymHHrPnj1YvHhxlQuLugDS93Xz5k189913kMvl+OWXX/DZZ5+hffv2sLGxYchrVftC3sPn89GoUSPMmDEDR48exbRp07Bz507s378fSqWSUbCVy+XYu3cvdu/ejQ8//BCTJk2yKDtm7f4WFhZi5cqV8PHxwYcffgg+n1+hMJZarcbmzZsRGhqKwYMH18nzmZmZiYSEBJNsME3TOHbsGIYOHfpaFq5JSUnM/NsA80DTNIKDg/H48eMq58qSkhJERESgRYsWuHLlCgCgqKgId+7cQePGjREREYGhQ4ciKyuLEWDq2LEjwsLCcO3aNQwaNAheXl44e/YsMjIyEBcXh5CQEPz4449VZgKBl6X3//zzDzp27MiM/erVq+jZsydYLBYKCwthMBgsPv/p6eng8/kmwnlKpRJ6vb5C67K3HUQp3N3dHba2thZ/njjQ1KSqtlKprDIDT1xZGnqEGzLCVoFcOKTR3MXFxUSQhIBYKFUVHawMpJcjPDwc/fr1q5MP7poCm82GwWBg1O54PF61iDARLOvfvz+OHj0Ko9H4WnsT3ySI8M20adOwadOmKjPDfn5+WLZsGTZu3Iji4mL069fvtR8rJycn2NnZQa1WIz8/HxRFoWXLlsjIyEBmZiaGDBmCjRs34uHDh+jYsSMoikLbtm1x7tw5JCUl1aoVS32AWCxGp06dcPHiRfTt2xe//vorBgwYUGmk3tfXl1Hr1ul0Vj00c3NzoVarweFwmMDhm4JYLMbEiROxceNG6HQ6fPLJJwgMDGSuGzc3N7z33nvYvn07evXqhWPHjjGZ4LoOku3ctWsXZDJZjataUxQFiUSC3r17o3379jh9+jT++9//4uOPP0ZJSQn+/PNPtGzZEt98881ryf7QNI3ExET89ttvGDRoEHr27Fmlf/GWLVvg5ub2WsSmrAFN0zh+/DgGDhxocgyTk5NRWFiI1q1bv5Y57vbt2+jQoUNDWXQVMBqNKCkpQXx8PO7du4e4uDjk5OTg5s2b6NmzZ4XnytbWFsuWLTN5zd7eHp999pnJax9++CHzbz8/vzK2PDNnzjT5f0X9+qVBbLGKiooYgbji4mKkp6ejUaNGjJVPSEiIxUGXgoICGAwGE2E9lUoFDodTr3vNr169ih49elh1vzx//hyBgYE1WqKsUCiqJMIGgwEsFqvhHkdDRtgqcDgcCIVCJpLj4OCAgoKCMu/z9fVFSkpKtbNV3t7eyM7Orla/8dsAkhHm8/nQ6XRgsVjVIsJOTk7Q6/UQCoUoLCys98fvVRAy/NFHH2Hjxo2V9gwDgIuLC5YuXYr79+/j6NGjr11gzM7ODnw+HyqVirmfmjZtisTERCZa2rp1a5MMMJ/Px8iRI3Ho0KGGXuEqQFEUevXqhbt370IkEsHLywuPHj2q9DNSqRQcDgd8Pt8qwSyj0Yj8/HwoFArw+XyIxeI37kkqFAqRnJwMLy8vhISEmCxWSfBFIBDgxx9/xPz589+acmilUom1a9fCxcWlVq2dKIqCVCrF+++/j3HjxuE///kPfv/9d8yYMQPjx49/LSTYaDTizp072LhxI6ZNm4bevXtXSmx1Oh22bNkCqVSK8ePH19ksSFpaGpKSkkz6lo1GI44dO4YhQ4ZUqQZcE9DpdIiKikKrVq1q/bveRmg0GiQlJeHUqVP46aef8J///AcRERFo3rw5vvrqK/z666+4cOECnj9/XucqlWiaRm5uLnbt2sXcB0Qkq0WLFsy9GxkZiXbt2lk8f8hkMsjlcpN2NpVKBT6fb5Ho1tuEkpISZGZmIiQkxOLPlvYPrqm52mg0mp0RbugPfokGImwFWCwWpFIpY6Hk6OjI9EaURmm/4epAJBLB3t4e6enp1dpOXUfpjLBGowGfz6/W8SNiP0SxsLxgRX0HRVFo1KgRZs6ciY0bNyIuLq7SMmlbW1ssWrQIGRkZ2LFjBzQazWt7mAuFQiYCnZ2dDaPRCHd3dxgMBnh4eCAqKgqjR4/GpUuXGLVoQlwMBoPZ/rjvMhwcHBAaGoqIiAgMGjQIFy5cKOMRWxocDgeOjo4MebT0+KrVakb0TiwWw9PT8431JBG7nLVr1+Kzzz4Dm83G3bt3TfaJ9ASnpqaiTZs2Zqlr1wXodDrs2LEDzZs3x5gxY8Dj8WqdvLNYLLRs2RLLly+HVCqFvb19rX8nyewSu6tPP/20Sl0DnU6H7du3g8fjYdKkSXW2J44Q3qFDh5oQ3uTkZOTk5FhFTKxBamoq+Hy+Veq39Qmk5N9oNCI3Nxc3btzA2rVr8c033zDPRhIImj9/Pjp16gQ7Ozs4Ojri448/xtatW3Hv3j1Gsf1Ng/SZ//rrrxg1ahRTQWUwGHD9+nUmg61QKJCTk2NxC4vBYGDKoEtX/SiVSgiFwnpLuu7du4fGjRtbRfT1ej1SUlLg7+9fY+PR6/XQarVmEeG6WBXzJtBAhK0AqecnZuROTk4oKCgok5ESi8WM+E91wGKx0KRJE0RFRdWJCbW2UDojTH4XFhZWa5uNGjVCXFwcAgMD672fcEUgPcNz5szBH3/8UWmkmqIoCIVCzJ07F3w+H6tWraqRYI45EAgE4HA4EAgEyMnJgU6nA5vNRpMmTUBRFKKjo9G6dWvY2dnh1KlTzJg4HA7Gjx+Po0ePvnNZf0tBURQGDRqES5cuwdPTE0ajsdKqFWLLZTQaER8fb/H3qVQqZgEmEAjemO0QTdMoKCjAypUrMXbsWHTo0AHTpk3DyZMnkZ2dzbzn4cOH2Lt3L5YuXYpFixbh/PnzlVqR1QXQNI1//vkHHA4HQ4YMea2lbkScb/jw4Thy5EitVmXQNI2ioiKsXr0aeXl5+Pzzz+Hq6lrp9aTVarFr1y4YjUZMmzatzpJgco9kZmaiU6dOJtlgohT9OrLYNE3jzp076NChQ61/V10DIb1arRZZWVm4fv06Nm/ejK+++gqrVq3C06dP0a1bN3z11Vf417/+hbFjxyIoKIgJOpFzRlEUYxd24sQJ7N27FwqF4o3NIUSE6+zZs1i3bh2mTp1qElSJjY2FSCSCh4cHgJcWUN7e3hZXdshkMlAUBTabbUIKlUoleDxevSRdBoMBN2/eRI8ePax6ruXm5kIgENRo2bhWq4Ver6/y/DVYJ/0PDUfBSkilUoYI29nZMZ63pW92gUAAGxsb5OTklOntsAQURaF58+b4888/MXz48LeiTM8asNlsE7EsiqKYTLs1+0xRFIKCgnD+/Hn06NEDd+7cMbH5eJdAURQCAwMxb948/Pbbb5g0aRKaN29eYc8wyZ5cvHgRP//8M+bNm1frJIZkhDUaDVQqFXQ6HXg8Hjp27Ij9+/dDoVCAxWJh+PDhOHnyJMaPHw9nZ2cAQGBgINzc3HDz5k307t273t4jNQFPT084OzsjOjoa/fv3x9mzZzF37twKr4WAgAA8fvwYqampFt+LSqUSOp0O2dnZ8Pf3f2OCU0VFRVi5ciWGDBnC9Jc7Ojpi3Lhx2LVrFxYuXIhnz57hzz//xOLFi+Ht7Q2apjFt2jRs374dS5curVJh+01BrVbj4sWLmD9/foWLzRcvXuDSpUtgs9lwdHREq1at4Ovri0ePHuH27dvg8/kM0XJ3d0d6ejoMBgOTWeByuXj//ffL3T4RYrt58yaSkpIQEBDAKNFqtVrk5+cjJSUF7dq1s3rhRTyJ9+zZg4EDB6JXr15Vbkur1WL37t3Q6XSYMWNGnSXBwP8I74gRI0zGmZSUhNzcXLRv3/613DdarRZPnjzBokWL6v0cajQaodFooFarkZ6ejvj4eKbHl8/nIyAgAB06dMB7770He3t7RuPAHFDUS3/yL774AqdPn8a///1vDBo0CB07doRYLH4tx5YQ4KioKJw4cQLu7u745ptvTCo3aJpGeHg4BgwYADabDZqmrSZ2MpnMpJqPbF+pVILNZtdLIpyWlgaj0Qhvb2+LP0vTNJ49e4aQkJAaJaQ6nc6sa7WhNPp/aDgKVsLOzg7FxcWgaZq5mPR6vclDjKIouLq6Ijs7u0KhInPh6uqKkpISqFSqeuvHxmKxmNJoPp8PrVZbrR5h4GWfdnZ2NlxcXJhJqz5OyOaAiGItWLAA69evx7hx49C2bdsKr0s2m43+/fvDyckJa9euxbRp02rVXkkgEMDOzg5ZWVnQ6XTQarWQSCTw8/ODUqmEq6sroqKiMGjQIBw8eBB///033nvvPSYaP378ePz6669o1apVnSUtdQXDhg3DoUOHsHDhQpw4cQKFhYUVKoT6+vqipKQELBarzBxXFXJzc03KdIkv5utEUVER1qxZg969e5sImhAhwpiYGKxevRpFRUVYvHgxY1NHgkcDBw7Etm3bsGDBgjfe31we4uPj4ejoWKkImbe3N2JjY+Hh4YGRI0fi/PnzePr0KXr27ImffvoJ48aNQ4cOHRAeHo4HDx5g9OjRiIyMxJUrV/Drr78yWdWK5k4ul4tu3brh77//hqOjI5KTk3H16lVcvXoVd+7cga+vL8LCwsxStC0NmqahUqlw7NgxPHv2DHPnzjVLFI9kgg0GA6ZPn/5aemutBU3TSEhIQGFhIdq0acPsm8FgwMmTJ19bNhh4ubAnqr/1ATRNMyW7CoUCBQUFSElJQWZmJrKyslBcXAw2mw0XFxcEBgZiyJAhcHd3h1gstoj4lgeKoiAWizFu3Dj06NEDp0+fxrlz59CyZUt06dIFnp6e4HK5Nf48NRgMyMvLw927d3Hr1i04Ojpi6tSpCAgIKHP/kuNAPGxlMhnS09MRGhpq8feSyjGhUGgyT5JnR31bdxHv4G7dulldhfPo0SMMGjSoRsdFRC3NIcL17ZxYiwYibCWcnJxw7949AGAuJoPBUOZ93t7eSElJqXapkUgkgqurKxITE9GsWbNqbauugmSE+Xw+pFIpFAoFtFpttUqKhEIhs4igaRoymczixVh9AkVR8PT0xNKlS7F69WpotVp06tSpwomcxWKhTZs2sLOzwx9//IHhw4ejS5cutVJ+KRAI4ODgAJlMBp1OB5lMBgcHB3A4HAQHB8NgMCAyMhILFy5Ehw4dcOrUKQwePBgSiYTJ8PXs2RPHjx/HtGnTGtQQKwApZzUajcjKykKHDh1w+fJlJqjwKsRiMUNmc3JyLFJQzsjIAI/HYx7O1thLVAdyuRwbNmxAu3bt0Ldv3zLXBCljXLNmDb7//nt4enqWEc/q2rUrUlNTceTIEUyYMKHOLR5iYmIQHBxc6cJHKBRCKpXC1tYWLi4uGDJkCBYtWoRevXpBKBQiNzcXhw4dwpgxY+Dp6QmBQIDY2FgIBAK4ublh0aJFVWYPfH198X//93/YsmULoqOjoVKpmGeik5MTYmNjGUG8V38qGntiYiJ27NiB4OBgfPXVV2Z5Ems0GmzZsgVcLrfOk2DgZWby6NGjZbLBKSkpyMvLqzRYWZMgokmdO3eu83Pnq2sCYrUok8lQVFSE9PR0ZGZmIj8/H0VFRdDpdMzzxdvbG6GhoejduzdcXFyYsl1zLMUsHWNUVBQSEhKQnZ2N9PR0JCUlYc+ePRAIBOjevTv69u2LFi1awNPTEw4ODiZzS2VjeVXXoLi4GJmZmYiOjsazZ8+g0WjQsmVLfPLJJ3B1dQWLxSqzPZqmce7cOfTq1Yshri9evGCs5CxFVlYWuFwupFKpyfVTVFRUL4mwUqlEdHS01VWapFKKBF5rClqt1qzA2asVrO8yGoiwlbCzs2NsRTgcDsRiMUpKSsrU+vv4+CA8PLza30eyFw8fPmQk7+sbSEaYoijY2dkxUdzqEGEWiwUfHx9kZGTAw8MDiYmJaNWqVb08fuaCoii4uLhg+fLlWLNmDbRabaXS/6Q8dvny5Vi/fj1ycnIwfPjwakfMy/seR0dHUBQFvV7PVFIAQKdOnXD06FEUFxdDp9Nh6NCh+Omnn3Dnzh306dOHWcT07t0b//3vfxEfH4+goKB3+jxXBhaLhSFDhiA8PBwffPABfvnlFwwbNqzcBRCfz4ejoyMKCgqQnp5ehixWBKJQqlAoYDQa4eDg8Nq8JIln7KZNm9C4ceNye2dpmkZkZCSOHDmC9evX4/jx42jVqhVzDRJQFIWxY8diw4YNiIiIQLdu3erUdVVSUmJR2wJFURCJRMjKymJ66hUKBeRyeZn+PvJ+cxbGfD4fnp6ecHV1RUFBARISEpi/aTQaXL9+HTqdDhqNBhqNBjqdjpnbuVwueDweQ4yJdd7Zs2cxZswYBAcHM8RcKBQyPwKBwKQ3k5xzR0dHTJ48uc6X/tE0jdjYWKhUKhPlWIPBgGPHjmHYsGGvLRus0Wjw5MkTfP7552/s+n6V4JEflUqFoqIiFBcXo6SkBPn5+cjIyEBhYSHkcjnUajVYLBYkEgns7Ozg6emJJk2aMD70dnZ2JmTwdeyf0WjEL7/8gr179zKtAjRNw9bWFgEBAejbty/8/f1x+vRphIeHo3HjxggICICdnR3c3Nxgb2/PBHFEIhGMRiP0ej1UKhWKi4uRlZWFwsJCpjLRxcUFzZo1w/Tp0+Hh4WFS+VIeCgoKEBUVhfHjxzPH+9atW+jatatV+5uRkcEIu5b+TplMBpFIVOfvRUtAvIO9vLys7u9NS0uDjY1NjfoHAy9bZUrPixVBq9XW6XaR14n6c2W+ZggEAqjVagAvF5UODg7Izc0tE92xt7evMbXi0NBQXLt2rVq+xHUZpEeFpmlIpVLQNF1toSaimhwTE4PQ0FA8e/aswRYC/yOdS5cuxYYNG1BSUoKhQ4dWGCGkKArOzs74/PPPsX37dmzevBnTp09nsrE1NSYbGxuIxWKmvIu8HhAQALlcDjs7O7x48QKdOnWCj48Pjh07hi5dujALdYFAgAkTJmDfvn344osv6mQpa10ACawRmyw/Pz9ERkaie/fuZd7LYrHg5+eH4uJixMXFmV3dQoiwWq2GVCqFh4fHa3vwajQa/Pbbb/Dw8MCoUaPKXNc0TeP27ds4evQoli5dyqiTb9++HYsWLTLJIlIUBT6fj48++girVq2Cm5tbnQqyiMViKBSKSt/zKsGIj49H9+7dmUVYy5Yt0bFjR0ZUzN7envmMuc8bvV4PHx8f/Otf/8LixYtx9uxZ7Nu3D7dv30ZwcDCWLFli0ptIeog1Gg3zW6VS4cmTJ9i9eze6deuGpUuXQqFQ4OnTp1CpVFCr1VCpVNBoNNDr9Ux5H4fDgcFgQGxsLJRKJQYOHIj9+/dDLBZDJBJBJBKZkGfyGql0ICSp9M/rIE5GoxGHDx/GqFGjmHuDCGcVFBS8Nt9g4GUG2s7OrkarNkorL7/6W6fToaSkBCUlJZDL5ZDJZCguLkZhYSHy8/MZnQitVgs2mw2RSMQQB0dHR6ZSSSKRQCKRQCwW15lMNrl3hg8fjsOHD0OlUgF4uR5s0aIF5s+fj6FDh+LKlSsIDw9HcnIy1q9fDwcHB4bkZmVlYdu2bUhJScEnn3zCiEkKhULY2tqiTZs2DMl/leibM76LFy+iS5cujKiSTCZDSkoKZsyYYdU1l5+fD4PBUEZtXKVSwdbWtl5lH41GI65evYrBgwdbfX9GRUUxQqA1icLCwkrbZAhUKtVrsbp7G9BAhK0En89n1KApqmIvYXt7e2i12hq56Nzc3KDVaivt53ubwWazmT5EiUQCNpsNuVwOjUZTrah4cHAwrly5gi5duuDWrVs1OOK3G+S6Xbx4MbZs2YL9+/fj/fffr/RYi8VizJkzB2fOnMEvv/yC2bNn16iIlkQigVQqhV6vNxFKEwgECA4ORlFREf755x+0bNkS/fr1w6FDh3D37l10796dGUNoaCgCAwMRFhaGMWPG1BnCUtfA5/PRp08fnDt3DgMHDsTevXvRuXPnciP3wcHB+OeffyyyE9Lr9SgoKEBRURHEYjHc3Nxey7nQaDTYtm0bbG1tyxV4MhqNuHXrFk6dOoVly5bBzc0NANC+fXskJCTg2LFjGD9+fJlFtZ2dHT766CNs3boVixYtqjP2MoGBgYiMjETfvn0rPL4xMTGIiYlBZmYmxGIx2Gw2Zs6ciYcPHyI7Oxt///030tLSkJWVhQ8//BAGgwFXrlxBeno67t27h3bt2lU5DlItwGKx4OHhgenTp2P8+PG4e/cu8vPzy2TZyX0tEAhA0zTy8vJw6tQpZGZm4qeffkJISEi5xIYQKUKE9Xo9MjIysH79enzwwQdo3bo1FAoFiouLGeuuwsJCKJVKqNXqMmS69HjIvwnhIHoV5f0uncEm+8Hn88FisUx+XiXapf/99OlT6PV6NG7cGEajkckcHj16FMOGDXstgSNyPK9fv44OHTrAaDTCYDDAaDRW+UPEphQKBXOslUolVCoV82/yQ441IceE3IrFYkilUkilUtjY2MDb25uxbCt9jGujn7amQcShnj59ikuXLqGgoAAtW7bE7du34eTkhFatWmHOnDlo3LgxFi5ciIMHD0Imk2HChAlo1qyZSQCuqKgIq1atQn5+PgYMGIAmTZrU2DiLi4tx9+5dfPPNN8w1FxUVhcDAQKuCx0ajEUVFRaBpmlGfJlAqlbCxsakzQYqaQEFBAQoLCxEQEGDV54l/8IQJE2p4ZC+vG3Pa/4itVQMaiLDVEAgE0Gq1jIBIaS/h0pM1n8+HSCRCQUFBtYkwl8uFt7c3EhIS6i0RJmWxpLRDoVBAJpNVq6TSzs4OKpUKdnZ2kMlkZpmNv0uwsbHBvHnzsGvXLmzduhXTpk2rdILkcrkYPnw4PDw8sGbNGkyePLnGDOEdHR3B5XKZ0mhyP5Fezd27dyM7Oxs6nQ79+vXD+fPncfLkSXTo0IF5gLNYLIwePRo//vgj2rRpU6MeffUJFEWhU6dO+P777zFy5EhQFIX4+Hg0atSozHs9PT2h1WpRUFAAvV5vVmBKp9NBqVQiOzsbAoEAgYGBtbEbJiBKwRwOB1OmTCkzTiJwcvbsWSxZssSEzLJYLIwZMwZr1qxBZGRkGaVeIjY3atQo/P7771i6dOkbm0eMRiPy8vIQHR2NiIgIREdH44MPPqiwTM/f3x+bN28G8HI/iRiQg4MDDhw4wLyPVGUYjUZ88803AGDWwthgMODGjRvo16+fybYkEkmVSv0qlQqXL1/GpUuXMHDgQKavt6L5hKIoRoWWx+MhKSkJO3bswAcffFClfgHJ1JVH6gghJBY6KpWK+SGEj/zOz883yWST18magGyPbJN8d+kfALh//z4CAgLw008/MYFghUKBmzdvQqPRMIFb8jcAVrekkFJ0vV7PEF29Xs9k5q9cuYIOHTrgypUrMBgMTH/3q2S+9G8ej8dk2MViMYRCIUQiERwcHCAUCiEWi5lsLZfLZYID5PyVDha8rSDHNCUlBdeuXcOzZ8/g5eWFESNGMAHZ5cuXMxaGSqUSw4YNQ1JSEmiaBpfLNakIINu8desWoqOjoVar8eTJkxojwjRN48qVK2jbti2T/Tcajbh27RpGjhxpFWFVq9VQKpUQiURlKgrkcnmVNmdvE8i5adeundWBKlLib43adFUg6+WqjnfDOvh/aCDCVoLP54PNZkOhUMDGxgbOzs6IjY0t8z5Sgpqfn2+RyExFaNOmDR48eGDiA1dfUDojzOPxwGKxoNPpIJfLq7VdPp8PBwcHFBUVwd7eHunp6QgJCamhUdcPCIVCzJgxA4cOHcKGDRswZ86cSidTFouFdu3awdXVFZs2bUJ6ejpjwVCd69LV1ZUpm8vJyYHRaGQezMSCjM1mM4StQ4cOuH//PiIiIkxsk8RiMSZOnIjdu3fj888/byiRrgBSqRTt2rXD33//jQEDBuDcuXMIDg4usxiysbGBQCBgsryurq5Vbpv0g5LyVXd399raDUYddv/+/VCr1Zg9e3aZzDZN07h69SrOnz+PJUuWwMnJqcy1yuPxMGPGDKxevRpeXl5wd3cvQ4bbtWuH7Oxs7NixA7Nnz35t/q5GoxEZGRl48OAB7t+/D6VSicaNG2PUqFFo3bo1Tp06hYkTJ5Z7/5Gs2qsg5cKvgsVimVVeR8b29OlTGI1Gs+dVsj/379/H0aNH4efnV8bapSqQz+/btw8zZswwSzuD/L2m7FxKl49X9ru8f9+6dQtSqRRz586FwWCAXq+HVqvFxo0bsXz5cjRq1AgGg4E5VoSYEhJrCUiWuzQJLf0THR0NNpuNuXPngsPhgMvlmmRgLf1dn1E6mJKeno47d+7gwYMH4PF46N69O8aMGQOpVMoci27duqFPnz4YOXIkhgwZghs3bkAkEjHb8fX1LWNXpNVqsXXrVqb97syZMxg/fnyNHF8SaPniiy+YbHB+fj6Ki4utDhorlUpwOBxotdoywbji4mIEBwdXe9x1BXq9Hnfv3sWCBQusPh9JSUmManhNQyaTmVWtRHqJG9BAhK0Gl8sFn8+HXC5niHBFnrd+fn5ISkpCy5Ytq/29ISEhOHXqFOOxWp9AHtKvmoFX10KJol7aoMTGxqJx48Z4/vx5AxEuBxwOBxMmTEBYWBhWr16N+fPnV7owpSgK3t7e+Oqrr/D7778jOTkZU6dOhUgksvoBYWNjAy6XC6PRCJVKZbLgEwgEaN68OZMFCw0NxaBBg/DkyROcPXsWnTp1Yq4biqLQtGlTPHz4EMeOHcP7779fr0qzagoURaFPnz5YsWIFvv76axw7dgz5+fmMPzOBUCiEo6MjUlJSkJOTYxYRzs/PB5fLRUlJCdzc3GqtioVk2A4fPoy8vDx88sknZcooSRbkwoULWLZsWRlBLAISuHz//fexY8cOLFmypIxSMUVRGDx4MHbs2IGTJ0+W24NcU/ul1+uRnJyMO3fuICoqCmw2Gy1atMDUqVPh4+PDfG9QUBBWr17N2Hm8LkJC0zQyMzOxZs0aSKVS7Nq1C0FBQfD29oa7uzsT0ARgIhiUkJCA/fv3g81mY9asWcwC3FwRNoPBgDNnzuD27dv47LPPXlvZ/auwlgCq1WpcuHABM2bMMAnIxMTEQCgUYuDAga9NJIumaRw5cgSDBg0qc9834CUIadXr9UhNTcXdu3fx+PFjJiC8YMECJutZug++uLgYmzdvxujRozF48GCwWCx07doVkydPxp9//sl4uZcmLjRN4+HDh7h06RLz2v3795Gfn19tWysSDGzWrJnJfHzt2jW0b9/eaoV1lUoFFosFtVptUr1nNBpRXFz82kQSaxs0TSMmJgYODg5WnwuapnH//n20adOmhkf3cttyudys463RaEwCNu8yGoiwlaAoykSkhBiJlyfs5O3tjYiIiBr5XiKxn5eXV6YX420HiVrr9XrY2NgwGeKaIMKNGzdmeiFPnz5tteR9fQYpORw2bBikUil+/fVXzJ8/v0xW7NXP2NjYYOHChTh58iRWrFiBWbNmwcvLy6rjK5VKweVymd7w0pZkpDz6zp07eP78OTQaDXx8fBAYGIjs7GxcunQJw4YNM1mcjh07Fr/88gsePXr0zquFVwQnJycEBgbiwYMH6NSpE65du1amt5qiKPj6+iIzMxNxcXFo3rx5ldslftByuRxubm61Zp1E0zROnDiBxMRELFy4sEyU22g04vLly7hy5QqWL19eJSGnKArNmjVDYmIiDhw4gA8//LAM0WWz2Zg0aRLWrVvHKK3WxLVF0zQ0Gg3S0tJw69YtREVFMVn7hQsXwsXFpVzSzePxMHHiRCxfvhw6nQ49e/asdXEamqaRlJSEzZs3Y/bs2XBzc0N6ejri4uJw8+ZNFBUVgcfjwcXFBb6+vvD09IREIsGpU6eQl5eH999/Hy1atLBITZYs9Hbv3g2tVosvvvjirVvM0TSNu3fvwtXVFX5+fszY9Xo9jh49ijFjxrxWhV2ZTIa0tLQa7UGtDyCBKIVCgZiYGDx8+BAJCQmQSqVo06YN5s2bB1dX13LPFU3TKCwsxNq1a9G5c2cMGDAALBYLRqMR58+fB0VRCAsLw6pVqzBu3DiTe5WmaezatQvFxcXMa3FxcUhOTq42EVar1fj777+xbNky5rrT6XS4e/culi5davV9lJ+fDx6PB6PRaFJhotFoIJfL65Uo06VLl9C7d2+rA+tarRbx8fFMO1JNgsyP5ihZ18dkmrVoIMLVgEQiYcp2iVcm6RkuDRcXF+Tm5pqUeVoLQuqePn1a74gwABMiTHpFZTJZtZWy3dzckJ2dDS8vL+Tm5jYo5lUCFouFnj17wtbWFqtWrcJHH32Exo0bV3r8+Xw+xo4di4CAAKxduxZjx45Fhw4dLF6MS6VS8Pl85OTkwGAwQCaTmTxYid9iZmYmEhMT0bhxYwwfPhy///47rl+/jq5du8LBwYF5v0AgwPTp07Fx40ZGhOVtWjS/DlAUhSFDhuD333/H/PnzsWbNGgwePLjM/REaGoq///6b6W2r6jjm5eVBqVTC1taW8bKsaRiNRpw9exZPnjzB4sWLy/Q8GQwGXLhwAREREVi2bJnZ5b4sFguDBw/GH3/8gcuXL6Nfv35l9lcgEGDmzJlYvXo1HBwcqrxHKgKxekpNTcXt27cRHR0NGxsbtG/fHoMGDYKDg0O5fZTEM1UmkyE5ORl79uyBQqHAZ599hmnTpmHKlCmwsbGpletdq9Xi2rVrOHv2rMn84OPjg86dO8NoNEKtVkMulyMzMxO3b9/GqlWrYG9vD6FQCC8vL9y4cQOJiYnw9PSEh4cHJBIJIzpVkUhWUlIStmzZgvbt22Po0KFv5UJOpVIhLCwM8+fPN8kePn/+HDqdrsb0FszFgwcPEBIS8s73C9I0zfjXp6amIioqCrGxsdBoNPDz80OrVq0wbtw4sxSQ8/LysGbNGvTu3Rt9+vQBi8UCTdO4d+8ebty4gc8++wx2dnb4+eefy73WO3XqhKdPn+LatWvw9PQEj8dDamoq2rZtW619vHnzJoKCgkwqeh4/fgwXF5dqVQOkp6dDIpGUqcRRq9UoKSmpN9dWfn4+cnJyEBoaavU2CgoKwGazzRK0shRGo5Fp16wKGo3mrZw/awMNRLgakEqlKCkpAQDGhkGtVpcpaXJycoJCoYBKpar2hEBRFFq1aoVz584xE2x9ApfLhU6ng0QiAU3T4PP5jI1OdSCVSsFms6HRaCAWi5GXlwcfH58aGHH9BIvFQuvWrWFvb4/ffvsNw4YNQ9euXSu93lgsFtq0aQNPT0/8/vvviI2Nxfjx4y3qQyH2GCqVClqtFrm5uSZlYxwOB927d8fevXtx69YtRiHazc0NRqMRp0+fxuTJk03KMb28vDBkyBBs3boVS5Yssbr8qz7D29sbNjY2yMjIgI+PDx4+fIjOnTubLGrc3d3BZrORk5NTpWAWsU4igYzaEAUhmd7bt29j2bJlZR7+RqMR4eHhuHfvHpYuXQpbW1uLCAaPx8PUqVPx66+/Mr6kpUFRL1XXZ8+ejY0bN+KTTz6xaD81Gg0SExMRERGBmJgY2NjYoFOnThg2bBhTEVPZePfs2YMvv/yS6S/V6XTgcDjo168fhEIhvv/+ewwYMABdu3atsYWoXq/Hs2fPcPToUdja2uKLL74oN7jEYrEgFAoZddr4+Hh8++236NixI9hsNlQqFdLT05Geno7o6GhcvHiRURaWSCRwdHSEq6srfHx84OTkBKFQiEePHuHChQuYNm0amjZt+lY++2iaxrVr1xAYGGiitq/X63H8+HGMGTPmtdrMEJGkmuo/fVtAsr1FRUWM53VcXBwyMjIY5eNmzZqhb9++cHBwYNZ35iArKwurV6/G0KFD0a1bN+Y6jY2NxZ9//olPP/2UqY4pbw5lsViYMmUKE0DauHEjevfuXe1+TpVKhfPnz2PRokXMvpBA4ujRo6t1P+Xm5jLq6aVBqiSt9dqta7h58ybatWtXrTVEdHQ0GjduXCvzl8FggEajMSvJo9VqG9ZC/w8NRLgacHZ2Zkgaj8eDVCpFQUFBmZue9BPLZLIaWZD4+/sjKyurRoh1XQPJAhMvWaFQiPz8/Gpvl8PhwNPTE0lJSQgODkZsbGwDEa4CRCX3008/xcaNG5Gbm4sRI0ZUukCnKAqurq74/PPPceDAAcZiydnZ2ayFBPGKFAgEMBqN5Z779u3b4/Dhw7h//z4mTJgAkUiEkSNHYvfu3YwXoq+vr0mJdNeuXZGQkIADBw5g8uTJ9crTsCZAURSGDx+OY8eOYezYsTh48CBDWggcHR0hEolQWFgImUxmknl/FTRNIyMjg1kI1bRiNE3TiIiIwKVLl/Dpp5+WIcEGgwEnT55EVFQUlixZYnX5rFQqxaxZs7B58+ZyBbZIoGXy5MmMknRFffWktzU5ORk3b95EVFQUbGxs0KVLF4wePZoh6ub2yTZq1Ah6vR5KpRLAy3LtUaNGYd26dXBxcUFOTg6OHz+O8+fPo0WLFujatSt8fX2Zc1rV95QWfMrLy8P9+/dx8+ZN8Pl8vPfeewgNDS03U036hk+ePIn4+Hj07dsXkyZNYpwAgJc95w4ODmjWrBnzGZKRI1mX7OxsPHz4EHFxcYiMjASLxUJISAjCwsIQEREBDw8PuLm5wc7ODvb29kxbxavjqUsET6FQ4MKFC/jss8+YhTBN04iOjgaLxUJoaOhrHW92djbkcvlrUXR/XXhVlEyr1SI/Px95eXnIzMxEUlISIw5FROECAgLQtWtX+Pn5MUEowLJrh1z3q1evxtixY9GxY0emLz4zMxMbNmzA3LlzK201Kg2ZTAYulwtHR8dqE0mapvHPP//Ay8vLpJIwKSkJKpWqXKcAS7adm5sLHo9XJhCo0WjAZrNrrS3mdUKj0eDu3bsmgQRLYTQa8ejRIwwZMqRW7nODwcC0uFUFrVbbkBH+f2ggwtWAo6MjUlNTmf/b2dmhsLAQvr6+Ju8jmYOCggLGs7I6ICrIGRkZ9UqND3hJWHU6HcRiMTQaDWxsbJiFXnVASsqfPXuG5s2b4+bNm+jTp0+dWiTVRRDxoGXLlmHr1q3Yvn07pk6dWml0mqIo8Pl8TJ06FREREVixYgUmTJiAtm3bVhkFJb33UqmUWYC/WoYrkUjQqlUrhIeHIykpCU2aNEFQUBBsbW3h5uaGQ4cOYcmSJSbRdjabjYkTJ2LVqlX4+++/G879K6AoCo0aNYJWq2VeS0pKQkBAAHOcuFwuM48VFRVVSoSJSArxADd38WcOaJpGZGQkTp48iU8//bQM8SS9lrGxsViyZAnEYrHV302I7qhRo7B161YsXry4jMoyEWYbOHAgQ5hJRJ6Q38zMTNy6dQv379+HQCBA586dMXjwYKbnz9zx0TQNhUKBs2fPYsuWLQgKCsLjx4/B5XIxdepU/PLLL7CzswNFUXBxccGMGTNw9+5d/PDDD9i5cyc6dOgAV1dXBAUFwcXFBS4uLrCxsWH8b7VaLeRyOYqKipCRkYH4+HhkZmYiPT0dUVFR2LBhA9q0aVOGABMim56ejhMnTiA1NRX9+/fHhx9+aEKAyzu+pX+z2Wx4enrC09MTBoMBkZGRiImJwZdffokuXbpAoVCgpKQERUVFSE9Px4MHD1BYWIiSkhJotVpwOBzGzoeUe9rb28Pe3h4ODg5MZRBFmfr5vo65gKZpnDt3Dq1atTKpctHr9Th27BgmTpz4WgN0NE3j9u3baNeu3VsVGCzPAkutViMvLw+5ubnIzc1Feno68vLyoFAoGPFNR0dHuLu7o02bNnBycoKDg0OZ1gFrrwOappGWloa1a9cyzzpCgouLi7F+/XpMmjTJ7EAHEeUSCAQ1QiK1Wi3OnTuHOXPmMK8ZjUaEhYVh0KBB1epJ1+l0KCoqgpOTU5n1rVqtBovFqhdiWTExMXB0dKxWn7ZarUZOTk6tJWH0er3Z81kDEf4fGohwNVC6R5iiKNjb26OgoKDc/jl/f38kJCTUiCAFi8VCixYt8OjRIwQFBdWrBT3JCItEImi1WrBYLKhUqhrZdmBgIK5evYqRI0fi0KFD0Gg0DfLxZoCiXvqBzps3D4cOHcLq1asxZ84cZsFd0WdIJtbPzw9bt25FdHQ0xo0bV6WqNLF0oSgK6enp5b6nf//+OHPmDK5cucIsLsaOHYvdu3fD1tYWt2/fLqOey+PxMHfuXKxYsQKurq5m2a28S2Cz2Rg8eDAuXLiA3r17Izw8HJ988gnzd4p6qb4eFxeHxMREBAQEVLgto9HIeAiHhobWSAAQeLngfPToEQ4cOIBly5aVydDqdDr89ddfSE9PNyGk1QFFvbRMSktLw8GDBzF58uQyC0dyrRcWFmLHjh2YNm0aZDIZbt++zWQz27dvj0WLFlUoeFUZDAYDsrOzER4ejpMnTyI0NBTr1q1DSkoKJk6ciClTpuDf//43kzlSKpW4f/8+du3ahbCwMCgUChw4cAAdO3ZEeno6vv32W0RFRaFbt27w9PRk/GQJkbS1tcWjR4+Ynly9Xo8+ffpg8eLF+OWXX5hqAVJiGh8fj7CwMOTn52PgwIGYMWNGpV7klYEEwPbt2weFQoHFixcz4ntisZghke3atWPeT/qsVSoV42mak5OD3NxcPH/+HIWFhSguLmYW5mw2GxwOBzY2NrC3t4etrS3z4+DgAFtbW3A4nDI2Q9XxvC0qKsLNmzfxzTffmPQGP3z4EGKx+LU/y7VaLSIjI016ld80SltF6fV6puS/uLgYeXl5KCoqQmFhIfLy8pCXl8cIKpKso6OjI5ydndG+fXs4OTmZ+BvX1j6S3vWNGzdi0qRJjCgjTdNQqVTYvHkzevXqhQ4dOpg9Bp1Oh4SEBIbAV3d8T548gb29vYmIZWZmJlJTU/Hxxx9Xa/tarRYGgwFqtbqMBoNGowGHw3nrCZfRaMSVK1fQt2/fam0nJSUFLi4uVs+NVcFgMDDe3JWBVEq87eelptBAhKuB0qrRwEsP1JycnDLvo6iXNjORkZHVFn0i22vRogW2bduG0aNHv1XR3KpAeoRFIhH0ej34fD7Th11dODs7Q6FQgKZpsNlsyGSyBiJsAYgy7eXLl/Hzzz/j448/NlE9LQ8ko/b555/j+PHj+PHHH/HRRx/B39+/3M+RxS6Xy4VKpSq3NJqI8jRr1gzXr1/Hhx9+CIlEAj8/P7i4uMDT0xPh4eFo3ry5iSAFRVGwtbXFxx9/jE2bNmHBggXw9vauM4vANw2iP3DixAkMGTIEp06dQkFBgclCLDg4GKdPn65SMEutVkMmkzHWSTVxn5ES0t27d2PJkiVlssxarRb79+9HYWEh5s+fX6P3NovFwtChQ/HHH3/g0qVLGDBgQLn73r59e1y8eBGzZs2Cj48P2rdvj7lz58LFxQUcDsfiUku1Wo1nz57h3LlzuH79OrRaLZYvX44+ffqAy+XC19cXW7ZsQf/+/Zk2mfPnz2Pt2rW4efMmM3e+99576NmzJ0QiEQoKChATE4O0tDT06dMHEyZMYGzKCEmkKAr37t3DJ598ghcvXqBnz55o3LgxLl68iHHjxuGbb77B+PHjERsbi3PnzoHFYmHIkCFo2rQp+Hy+1aJhWq0WN27cQHh4OAYNGoQePXpUuVgjQTeRSGQS+ChdLUUy84RYkd+kR7S4uBj5+flISEhAYWEh5HI5k20kGUihUAixWAyxWAyJRML82NraMu0cHA6nwp/Tp0+ja9euJmRBp9Ph+PHjmD59+mtVigaA5ORkCIVCszxHrQEhtaUJbekfhUKBoqIiRvCN/MjlciiVSkZclM1mMwELe3t7ODk5oXHjxnB2doZQKGQ8j8sri69t0DSNFy9e4Pfff8eMGTPQpEkTZgxarRZbtmyBv79/uWJ7lcFgMCA3NxdCobDaGWG9Xo/w8HCMGzfOpDc4PDwc/fv3rzYZIgkLmUxWhggTH+TXZQVWW8jNzUV+fn61WhdI0KtFixa1pm+gVqtNLOsqgtFohE6na+gR/n9oIMLVgEgkglKpZBaEbm5uePLkSbnv9fLywunTp2EwGGrkgefo6AiVSmW2QtzbAlIabWtryyhwFxUV1YjUu0AggKOjI7KysuDn54e4uLgG30QLwWaz0bdvX7i5uWHjxo147733mF6oyiAUCvH+++8jKioKmzdvRr9+/dC3b99y7wUXFxdGhV0ul5dLuFgsFoYPH45ly5bh0aNH6NKlCyiKwqhRo7Bp0yZ06tQJ+/fvx8cff2wSKCJ9z5MmTcLGjRvx6aefNihJl4JAIECvXr1w/fp1tG/fHlevXsWYMWOYv3t7e4PH4yE5ObnSuYz04Dk4OMDFxaXax5emacTGxmLr1q1YtGhRGXsurVaL3bt3Q61WY86cOVaTscrA5/Mxbdo0rFy5Eq6urowvvFwuR1RUFK5du4a8vDy0bt0aqampaNKkiVUiNDRNIz8/Hzdv3sStW7cgEAhQUFCA1q1bY+7cufD09GT2TSAQYPTo0SafzcvLw61btxgSTOzNSBbi8uXLiImJAQCUlJRUuEht3rw5mjdvjr/++gtdu3ZFt27dcPHiRWRkZGDp0qXYuXMnBgwYgKlTp8Lf379Kca+q9jkuLg5//vknbG1t8dlnn5mtK2AOKIpiCGnpAMmrJJBkl0uTYELm5HI5Q9QUCgXkcjkKCgqQmJgImUwGtVptksk0GAxMtlKn0+Gff/5B3759kZaWBh6PBy6Xi+zsbDx//hwPHjzAixcvIBKJIBQKwefzmfGSbDTp/SNl3RW9Zu7xPnv2LFq1aoWSkhKTfS79Q/aB7Bf5t1arhUKhgFKphEKhgEajgVarhVarhVqtZn5I0IEcBy6XCw6HAy6XC5FIBDs7O9jZ2cHR0RF+fn6QSqVMYIHsO8lwva4SdnNB0zQeP36MnTt3Yt68eSYZfb1ej3379kEgEFglgKbRaKBUKmFvb19tEhkfHw/gZUUcGV9eXh5iYmIwceLEah/TgoICCAQClJSUlCHCMpkMFEW91ZlHmqZx/fp1dO7cuVrnwmg04unTp5g7d24Njs4URUVFZjkFkDmtgQi/RAMRrgbEYjH0ej1TYiuVSiv0vLWzs4NKpWJKRaoLgUAAHx8fPH/+HO3bt69TD4jqgM/nQ6vVMlYaPB4PMpkMCoWi2pMpRVEIDQ1FTEwM0y/cqVOnenPsXhdYLBaaNWuGZcuWYfPmzUhLS8PIkSOrfEiwWCw0b94cX331FbZv346oqCh89NFHZUqsnZycwOVyUVJSAo1GU27kklRFBAQEIDw8HJ07dwaLxYKbmxuaNm3KZHsePHjA9GuV/mzLli2hUCiwcuVKxsqi4Tp4eWy6dOmCf//735gzZw62bNmCQYMGMZk20meZlZVV6VyWn58PmUzGCBxV59jSNI2UlBRs3rwZ8+bNK1OFoNFosH37dgDAxx9/XKuZIYlEgtmzZ2P16tUoLCxEdHQ0kpKS4OfnhyFDhqBRo0ZMNcPq1avx999/o3fv3lWOh5QYP3v2DBcuXEBWVhbatGmDwYMHIywsDN27d8eIESPMUq8dNWoUzp49i0OHDkGr1WL06NFMsKqoqAg7duxgMsClA7mvgsfjoU+fPggLC8OZM2eY4APxOs7Pz8fQoUOrVdJL/FYPHz6MhIQETJw4Ec2aNatWCXJ1QMhWecELqVQKd3d3k9dKCzO9+n9CqlUqFX777TcsXLgQrVu3ZgijTCbDxYsXMXXqVAiFQqhUKmRmZjLrhNKZVABM+Tq5Vkq/RkgrRVHMuS1v3wghU6vViIiIQKdOnXD16lWGbJYm16VfK03ICZEVi8UQiUSwtbUFn88Hj8cDn89n1IPJD/l/6WP66rl92+ZeIj71119/YenSpSaBOYPBgGPHjiE/Px8LFy60at2SlZUFpVIJT0/Pao3TaDTi1KlTGDJkCDNXkyAIqRCpLjIyMmBjY1OuY0pRURGAtzsjrFar8fDhQyxfvrxa12lhYSEMBkOl2hrVRUlJiVnCkAaDoSEjXAoNRLgaICIgKpWKEegoXSpdGqRPQqlU1ojSM0VRaN26NR48eID27dtXe3t1BUKhEEqlEiKRiHl4kuizuR6glaFRo0Y4deoUOnfujPDw8CptYBpQPiiKgru7Oz7//HPs2LEDGzduxIwZMyCRSKoslba3t8eiRYtw6dIl/PDDDxg3bhzatWvHlI7a2dmBy+VCLpeDoigUFxeXW74nEAgwfvx4rFixAgUFBXBycmL8X1esWIGJEyfizz//REBAQJmHD0VR6Ny5MzQaDVauXIlly5Y1kOH/B6lUig4dOuDx48fw8PDA48ePGSLFYrHg5OSEmJgYKBSKcucyktHU6XRQqVQmCt6Wgiiurlu3Dh999BGCg4NNtqVUKrFlyxaIxWJMnTq11jIPhHykp6fj+vXryMnJwffff4/PPvuMKc0vPS6RSIT58+dj5cqVkEqlaNeuXbnHwGg0orCwEDdu3MCtW7dgb2+PPn36ICgoCOfOnUN4eDg++ugjNGrUyCwyLZPJ8Ntvv6F79+4ICgrCH3/8gQULFoDH48FgMGDTpk34559/mM+QbOCr2yZlyn5+fsjIyMCKFSvQt29feHh4IC8vD4GBgdixY4fVQVhCEC9duoS///4bvXr1wpQpUyoV1qqLqIrQkXuhoKAACxYsYLLRNE3jypUr6NatG0aMGFEj+1w6m13RWAkZvXXrFkJCQjB79uy30obqTYJYTp09exbLly+Hq6urScnxxYsX8fTpU3z66adWE43U1FQolcpqPZNomkZqaiqKiorQrFkzZjtFRUV4/Pgxvv322xqp1MnJyYFEImGyv6VRUlICNpv91maEiSaFr69vtSovSZ92o0aNapV8ymQys4gwqXZ53e0YdRUNR6EaoCgKAoEAKpUK9vb2jOWPWq0u0wzPZrPh7u6O9PT0GivHDQoKwokTJ5gS4voAkUiEkpIScDgcRmmQKKXWBHx8fJCXlwculwuDwQCFQlErxubvCsRiMWbPno3w8HCsWLECs2fPLlO2Wh44HA4GDBiApk2bYvfu3YiMjMSkSZNgZ2cHBwcHsNlslJSUwGAwoLCwsFwiTFEUunfvjk2bNuHmzZvMgtLW1haDBg3C9evX0a9fP+zbtw9z5swpE/BgsVjo1asXjEYjVq1ahcWLF8PBweGtWojXBiiKQp8+fbBixQp88MEHCAsLMwlUNGrUCA8fPkRSUlKF/YUZGRkAAFtb22p5COfm5mLNmjX/P3vnHR5F2X7/z+xmN9n03iEJJBBCQgi9F6nSi1JEmiAIIgiIguirvi9WVBQUUIoVpQlI7733FggtkAIhPdn0bfP7g9/Ml0gCCWwKmHNduYCwO/Ps7JTnPPe5z2HQoEGFJnPSPWHBggV4e3szYMCAMlnQMhqNpKWlceLECY4cOYJSqaR58+bMnj2b8+fPc/78edq1a1fkOWNvb8/rr7/O3Llzsba2lvsHpd7fa9eusWvXLhISEmjUqBGTJk3Czc2NmJgYvvrqK4KCgpg5c+YjF5ek45GQkMD3339Ps2bNeP7559HpdHTo0IH69esD96JyFi5cWOh9ycnJmEwmuZKYk5NDTEwMx48f5+rVq9jb21OjRg2qV6+Or68vAwcOpG7dunh4eLBv3z4iIiJKddwlgn3ixAk2bNhAcHAwM2bMeGbbE4xGI6tXr6Z3796FJsA5OTls27aNN99802z7elg1+36YTCb27t37xNmx/0YYjUa2bNnC8ePHeeuttwqdt6IocujQIQ4cOMBbb731xGZxJpOpEMl+HGzcuJHOnTvLRFRyLm/evLnZsn0TExOxsbEp0k05NzcXBweHp5YIS1n1AwcOfOJr5cSJE/To0cNMIysaWq22RIRdMtV6Fu+5j4MqIvyEkCRNgCzl1Wq1RUZsVKtWjdjYWHli8qSQgt4TEhLw9fU1yzYrGjY2Nty9exeFQlEo9sQcEUqA3IOVnZ1N9erVuX79uuw+WoXHg0qlokePHlSrVo25c+cyYMCAEkcl+fj4MHXqVHbv3s3HH3/MwIED8fDwkHvkpIpZcbC3t2fgwIGsXbuW7t27y2StRYsWHDx4ECcnJ0wmEwcOHChSoqpQKHjuuedQKpV89dVXTJw48YknH88CXF1dCQoKIikpCYPBQGxsrBylVLNmTTkPt7iKYEJCAmlpaQQHBz+2FCw1NZU5c+bQq1evQhVVqfI5b9486tSpQ69evcy6si2KItnZ2URGRhbq+x07diweHh7yOdauXTvu3r3LypUreemll4p0knZ3d2fMmDEsXLiQV155BVtbWw4dOsSpU6dwdnamQ4cO1KlTBysrKwoKCli/fj1Hjx5l6NCh1K1bt0STL1EUuXjxIj/99BODBg2iUaNGKBQKLCwsaNWqlfw6BwcHunXrhqWlJZs3b0ahUJCbm8vVq1e5cuUKly9fJiMjAy8vLxo1akS/fv2wt7fn2LFjHD58mCtXrjBu3Dhq1KiB0Wjk6tWr7Nq1iy5dupToetHr9Zw/f56///4bJycn3njjDby9vZ9ZMiaKIleuXCE3N5cGDRoUOn/37dsnu6mX970mOTmZrKwsAgICynW/TzsMBoMs4Z86dWohEysp0m3Tpk1MmTJFzgR/XKSkpAA8kZljUlISt27dYuTIkfI2tFotJ06cKORc/iQwGo1yHND9+cQSsrOzcXBweCpVd1JLjiiKTxx3lJOTQ0pKygPRquaEKIpotVo8PDwe+VrJiK4K91BFhJ8Q9ztHC4KAvb19sSdj9erVOXjwoFmco+Felbl27dpcunTpmSHClpaWcsSFpaWlfAOVek3MgcDAQK5fv07dunWJjIx8oIe0CqWHQqGQ8zEXLlzIjRs36Nev3yP7NQXhXuZw165dCQ0NZenSpdjY2KDX69FoNFhYWHD37t2Hvr979+4sX76c69evExwcDNwj50OGDGHRokW89tprfP/99wQEBBTpcq1QKGjbti1WVlbMnj2bCRMmPNIN+1mHdFy/++47nnvuOXbs2MGrr76KQqHA398fjUbDtWvXMBgMsturXq/HwsICS0tLOerExcWl1JMg6YH+7bff0rFjR1q2bFmIRGRmZvL111/TpEkTnn/+ebOoYSRX4ejoaPbu3cvVq1fx8/OjW7du1KpVq8jzWKlU8sILL/DDDz+wbds2unXrVuQ54+bmRlhYGK+++iq1atWia9euTJ48uVD0U1xcHEuXLsXHx4f333+/xFVgk8nErl272LlzJxMnTpRl6P/sXTUYDFy9elVu5WnYsCGenp7k5+fz999/U7duXQYOHIivr6/8WaX9h4WFsXbtWjp37sxff/3F1KlTUalUDB8+nFmzZhESElLshF0aY2RkJGvWrMHKyoqhQ4dSo0aNZ74iYTQaWbVqFS+++KJ8DUiLOHv27GH69OnlPiZRFDl48CCNGjWq6g8sIURRRK/Xs2zZMjIyMnjzzTcL9dZKC1HLly9nypQpT2zyJsUxmUymx14okfqA27VrJxdlRFFk165dNGzY0GwqOJPJJPe73++YLUGr1T7xokBFYufOnbRv394shmVeXl5m6cl+GDIzM0v03Up+Ak/r92JuVBHhJ4S7uzvJycnyv+3t7cnMzCzytT4+Pty9e9dsztEAERERbNiwgU6dOj0TJ7UUn6RQKOS+NoVCUWQs1eOiTp06nDhxgt69e7Njxw6zLUz82yEIAt7e3rz77rv89ttvfPnll4wdO7ZEcmNBuBezNGPGDDZt2sTy5cspKChAEARZZlscXFxc6N27N+vWreOdd96R9+Xn50d4eDiHDh1i6NCh/Pjjj7z77rtFSsIUCgXNmjXDzs6Ob7/9lmHDhhEREfGvPi98fHxk47Jr167JkxpLS0tEUWTTpk1kZGTI6g0pAzwvL48dO3bIpkBpaWklrrJLkue5c+fStGlTnnvuuUIkODU1lS+//JIOHTrQoUOHJ1rVlnoqU1JSOHToEMeOHcPa2pq2bdsyePBguTXjYeNWq9W88sorfP3117i6utKkSRPg3kQjLi6O3bt3c/nyZfz8/HjnnXfYs2cPLVu2lNtjdDodW7duZf/+/bz00kvyOfewfUokNz8/n2XLlpGQkMDUqVNRKpVcv36d9PR00tLSuHv3LikpKWi1WnJzc7l48SI+Pj6cOnWKjz76iEaNGsmxTg/7nLa2toSEhMhuwefPnyciIgInJydefvllFi1axLvvvltIBSUtLERFRbF27VoABgwYQO3atZ95Agz3Pv+JEyewsbF5IHJl69atNG7cuELk4AaDgePHj/Pmm28+89+BOSAZwy1ZsgSFQsH48eMLyXwlN/slS5bw5ptv4u3t/cTH1WQyce3aNUwm02PLq6U+4A8//FAeT1ZWFocOHWLmzJlm++71ej0mkwmtVvtAy58oimRkZDy13huZmZncunWLIUOGPNF2JGO1sja1NZlMJSbCUjvl0/i9lAWqiPATwsXFpVDWqaenZ7EVLI1Gg06nw2AwmI0I+/v7k5KSQk5Ojjxxe5ohTaYVCgUqlYrc3FxUKpXZKsKStHPNmjXY2tqi0+nQarVVfcJmgiAIaDQaRo0axf79+/nss88YOnSo7AT7qPeq1Wp69OjB9u3bOXjwIKdPn8bBweGhixWCINC3b18mTZpESkqK/EAWBIEePXrw6aefEhERQcuWLVm8eDGvv/56kT1LgiDIbtjz58/n9u3bdO3a9amUdZkLPXv2ZPny5YSGhnLw4EECAgJYtmwZaWlp2NjYMGHCBHx8fApVZbVaLcePHycnJwcXFxfmzJlDSEgI/fv3L9Tu8E9IvbPz588nJCSErl27FiLBd+/e5ZtvvqF79+60atXqsUmwKIoyMdy9ezeZmZk0atSIiRMn4unpWartCoKAra0t48aN46uvvkKlUpGcnMzBgwdlaXL//v1lGaW7uztz587lzTffJCsri19++QVvb2/ef/99+R50vzOw9JOdnU1SUhJpaWmkp6dz9+5djhw5Qnx8PBEREXz55ZdYWloWylsNDAykefPm2Nraolar+eKLL+jRowdxcXF06tSpxNUJSQa+dOlShg0bxs8//0ydOnXQaDTUr1+fc+fOsWbNGgYPHoxCoUCv13Pp0iXWr1+PQqGgd+/ehISE/KuMWfLz81m3bh3jxo2Trw1RFElLS+PYsWNmk6aWFteuXcPOzq5E8skq3JP2Lly4EA8PDwYNGvQACY6OjmbhwoWym705YDKZSE5OliOmSnueiKLI3r17adSoUSGflf379xMaGmoW01EJKSkpssHpP4mwRMyexCOioiApJyIiIp64iqvT6YiOjqZ///5mGl3RkPwX7o+HKw5SgakK9/DveTKVASQpdExMjPw7T09PIiMji3y9paUlGo2G9PT0B2IYHhcajQYXFxfi4uKoU6eOWbZZkZByhBUKBXZ2duTl5aFQKMjOzjbbPqSHg16vx8fHh+joaBo0aGC27Vfhnmy0Xbt2+Pn5sWTJEq5du0aPHj1KJMdTKBR4eHhQp04dkpKS2Lt3L5s2baJDhw7Fusq6u7vTtGlTtm/fzksvvSS/RqPR8NJLL7Fs2TKmTZtGfHw869at44UXXij2QeDr68v06dNZunQpCxYsYPjw4SXK5nvWIC0aKRQKfH19+fHHHwkICGDUqFHUq1ePn376iZycnAekyZmZmWRkZJCXl8fgwYOpW7cumzZtYvbs2UyaNKnYnmG9Xs+PP/6It7c3vXv3LkQg4uLi+O677+jXr1+JcquL2/7t27fZu3cvkZGRVK9enV69elGzZs3Hzh2WSHV8fDwAr732GoMGDWL06NF4e3vL/cQSGjRoQHp6OhMnTsTd3Z3hw4cTFBREQUEB165dIzY2lsTERJKSkmTnbcmU0cXFBScnJ27fvs3hw4d5/fXXqVevHmq1Wo6uKW6V/+rVqzg7O3P+/Hnq1q1b6kpTtWrV5OvFz8+Pffv20aVLFxQKBQMHDuTTTz/lxIkTKJVKNm7ciKWlJf369aNWrVoPHINnHVIPcEBAwAM9gevXr6dt27YVsvAqOVW3b9++ahL8CEjqk3nz5hEREUGPHj0KLeSIokhMTAwLFixg1KhRBAUFmW3f0r3TwsLisZyKc3JyOHLkCG+//XYhj5X9+/fz1ltvmW2ccM8oy8HBgfz8/AcImE6nIzMz0ywpKeWN/Px8jh49yuTJk594WwkJCVhZWZX5NS+pcEqy4CgV4/5N9+WHoYoIPyGknmAJjo6OxVYvJefo+Ph4sxFhgIYNG3Lq1KlngghL0mhBuBejk5iYiIWFhVmJsIWFBdWqVePmzZuEhYVx4cKFKiJcBhAEgYCAAGbMmMGyZcv46quvGDVqFO7u7g+9AUsRPdIij6urK9euXeP48eO8/PLLD0ToSOjXrx/vvvsu3bt3lx86kstx3bp1WbduHUOHDuXrr79m//79tG3btsjtSAtcr7/+Otu2bWPWrFmMGDGCOnXq/OsmkEqlkm7durFkyRJSU1OZNGkSQUFBZGdnYzQaiY2NfUD6mZmZKRtFVatWDRsbG1544QU8PT1ZvHgxEydOfGDSpNfr+fnnn9FoNAwcOLBQ5uWNGzdYsGABQ4cOJTw8vFQPbymn9tSpU7I/Q+vWrenTp4+8uPE4kwHJQOzAgQNERkbi6enJgAEDeOGFF9i4cWORBjGSrPjXX38lMTGR3NxcVq9ejV6vR61Wyw7bXl5e1K9fHw8PD6ysrOQMV5PJJMvR58yZU+I+dsnNNiIigqVLl/Liiy+W+vNaWFjQvn17du3axQsvvMBnn31Go0aNcHFxwWQyUbt2bSZNmkTnzp15+eWXqVGjxr+qAnw/tFotO3fuLNSmAfeyYSMjIwvJVct7XDdv3mTEiBHlvu+nCaIocvv2bebNm0e3bt1o3bp1ofu+9P/fffcdw4YNK7I39kmQnJxMRkYGKpWq1Akjkgw3MDBQXnCUjLwCAgIK+RI8KURRJDExEScnJ1JTUx94Nur1+iKNY58GnD9/nmrVqpkl8/fs2bPl0mZlMpkwmUwluu/m5eU9ld9LWeHf+aQyIxwcHMjKypJd2BwcHIrNZpT6IOPj44vNlSwtJDnn/v370ev1T72M834i7ODggNFolPuujUaj2WKiateuTVRUFG3btmXPnj1VfcJlBEk6Onr0aA4ePMjnn38uO9s+jIS4uLhgaWlJTEwM1atXZ9CgQaSkpLB06VICAwN54YUXCplwSNdW9erV2bx5M4MHD5b/T6FQ0KtXLz777DPZ+Xb27Nk4OTlRr169YsmwJNMODg5myZIlsrz3ceRqTysEQSAwMJAbN24wYsQI9uzZQ926dfH19UWtVrN7925UKhWtW7fm4sWLrFixgvT0dBITE/H29iYnJ0e+N7Zq1Yro6Gj2799fyNPAaDSycuVKcnNzGTduXCFjocjISJYsWcKYMWMeINzFQVoZv3LlCrt27SI2Npa6desycuRIubL5OHJDQJa2Hj58GEG4F9/Vq1cv+VyUHKe///57Bg8eTHp6OtevX+fKlSucP38eURSpU6cOzz//PAUFBZw9e1aWRUvXwz/HJhmE/fjjj2g0GmbMmFEiMy0JklS5QYMG3Lp1i7CwsFJ9dgmNGzdm48aNWFhY0KlTJ5YuXUrNmjU5cuQINWvWZOLEicTGxhIQEPCvJcGiKLJ9+3YaNmxYKE7GZDKxdu1aunTpUiEVMlEUOXv2LLVq1Spzw56nGaIocv36dRYsWMDLL7/8AIGRyN+cOXMYMmQIYWFhZn8WSC0Qjo6OpS6Y6HQ6du7cyfjx4+Vx6XQ6tm/fztixY80+1ri4ONzc3HBwcHhgbqbX6wHMFtNUXtDr9ezatYtBgwY98bYMBgPnz58v5NxdVjAYDAAluvfm5OSg0Wj+NfOYR+Hf+bQyI+zt7cnLy0Ov12NpaYmjoyN5eXkUFBQUqdWvUaMGmzdvNusY3N3dH5q3+jThfiJsb2+PTqfDwcGBjIwM8vPzzTKJEASB4OBg9u/fT//+/cnPzycjI8OsvTNVKAylUkmbNm0ICgpi0aJFXLhwgUGDBhVJKgVBwMnJCbVaTVpaGkajkezsbEJDQ/nggw/Ytm0b//3vf+nWrRtt2rSRXW4VCgX9+/dn5syZdOrUqdDqt5WVFa+++irffPMN06dP5/XXX+ebb75hwoQJBAQEPLT/ODAwkA8++IB169bx0UcfMWDAACIiIv41pj+XLl3Cx8eHkydPsmPHDrZs2YK1tTUnTpxg+/bt7N+/n+3bt5OamsrcuXPlOLn4+HgGDRrE2rVr8fX1RRRFOnfuzNy5c2ndujVWVlaYTCY2bNhAXFwckyZNkqXzUhXjzz//ZOLEiY+sfkp9tRkZGRw+fJiDBw9iZ2dHhw4dGD16tLz6/TgEOC8vj4sXL7Jnzx5SU1MJDw9nzJgx+Pj4yH1ZN2/eJC4ujuvXrxMbG8v58+fZvXs3Xbt2JS0tjatXrzJixIgHMj29vLyYP38+kydPLrJ/2mQycenSJX766Se6dOkiR32V9HNIE3tJVWFnZyc7S5cW1tbWBAcHs3r1ajIzM1m3bh09e/Zk+vTpuLi4YDQa+f7779m6dSs9evR45q+Nf0IURZKTkzl27Bj/+c9/Cv1fbGwssbGxjBo1qkKOi9Fo5MCBAwwcOLDc9/20QBRFTp06xR9//MFrr732gPJIIsFffvklAwcOLJMqnyiKJCUloVAo0Gg0pZJGi6LI+fPncXFxwcvLS16Yu3jxIk5OTvj4+Jh9vCkpKTg6Ohbpbq3T6RBF8anyX5HacBQKxWPfJ+9HZmYmeXl5eHp6mmmExUOr1WJtbV0iIpybm1u1IHYfqojwE8LS0lK2kLe0tMTKykrOZyyKCDs7O5Oenm7WCqRCoSA4OJhLly49M0RYFEXs7e3JyclBrVaTn59vNiIMyAsWJpMJLy8vYmNjq4hwGUNylX777bdZv349H3/8MSNHjpT7UO+Hs7OznMutVCpJTU0lKCgIjUZD7969ad68OatWrWL//v0MGDCA4OBglEoloaGhuLu7s2zZMiZOnFioYuzj40OvXr1YtGgRkydPZsyYMXz33XdMmjSJ6tWrP5QMazQaBg0aRLNmzfjzzz/ZuXMngwYNolq1amZTKVRGSET16NGjXL9+XZbxGo1GjEYjcC8eyMbGhpCQEJycnGQibDKZqFWrlizvW7p0Kbt37yYqKopr164xcuRIRFHk3LlzTJkyRSarUu7zli1beOutt+RJXVGQiOj169fZuXMnt2/fpn79+rzxxht4eXk9lpRdcoq9desW+/fv59q1a/j6+tK+fXt8fHxITU3l7NmzrF27lqSkJPR6PU5OTvj6+hISEkLnzp2xtbXlp59+4sSJEzRq1Ijvv//+AedsQRDo1KkTJpOJefPmMWHCBLl6Io1h48aNnD59mnHjxlGzZs3HemYcPHiQJk2asGbNGho0aFCq2Bwp/igtLY3jx49z7tw5Ll68yH//+186derEH3/8IS9mWVhYMGLECGbNmkVQUBC1a9f+V5FhURRZu3YtnTp1ws7OTv7sBoOBv/76iz59+hRp0lceSEpKIjc3918fC1ccjEYjO3fuZO/evUydOvUB92fJrG/OnDm8+OKLZeoAHBsbi42NTakrdlLrxKBBg+RnktFoZNOmTbz44otmf05J/gjZ2dlFnld6vR6j0fhUVYQlRUfHjh2fuA1KWkSWfBLKGllZWdjY2JRo3Hl5ecX6rfwbUUWEnxCSu7FOpwP+b9Kcm5tbZH+BnZ0dBQUFFBQUmE2jLwgCERER7Ny5kzZt2jzVfYwqlUqWNtra2sq9wSaTifz8fLPtx8rKCk9PT27dukV4eDgXLlwgPDzcbNuvQvHQaDS8+OKLhIWFsWTJEho1akT37t0LXQ9ubm7odDrUajW2trbExcXRrFkz4N757uHhwbhx47h69SorV67Ezs6OF198ER8fH1566SVmzZpF9+7dC5mYCIJAy5YtuXHjBmvXrmXAgAGMHDmSuXPnMmnSpGKzUO9/f0BAANOmTePMmTP88MMP+Pr60qtXL3x8fJ7q6644SBVJiQTDvUUKOzs7rl27BkBAQAAKhQJHR0fCwsLkuCtnZ+dCVV69Xs/y5cuBe31TW7ZsoWfPnixYsEA2sDMajezYsYNDhw4xderUYnvaTCYTqampHDlyhCNHjuDg4MBzzz1H3bp1H1u6rtfruXPnDgcPHuTQoUMAstw+MzOT1atXo1Kp8PT0xM/Pj+eeew5vb280Gk2hSUVeXh5bt27lzp07+Pv74+vrW2y2qEKhoHPnznI19fXXX8fW1paEhASWLl2Kp6cn77777kPdth+GgoICrl69SocOHYiMjGTcuHEl2o5Efi9dusThw4fJzMykfv36TJs2jZ9//hl3d3eCgoIIDg5m8+bN9O/fX1bxvPrqqyxatIgZM2aYpcfuaYCU/RobG8uwYcMKuZ1fuXKF7OzsCsurl3rEmzVr9q+VrD8MOp2O1atXc+vWLd55550HKpj3O9b379+fJk2alOn3eOPGjVITFVEUuXr1Kkqlkpo1a8q/u3btmqxqMjdyc3MxmUxkZWUVWfHU6XSYTKYSuRhXFqSlpXHnzh3q1q37xN+xpGoqr2jTrKysErfMmJN/PAuouiuaAVIVU8L9BO6fkOQuSUlJDzhKPglq1KhBQkIC+fn5T7XkQSLCBoMBW1tbmfyaTCa50mQOSFX0y5cv07RpU/bv32/WHuQqPBwKhYI6deowc+ZMVqxYweeff87IkSPlyqy9vb1s8W8wGEhJSXlgG0qlkuDgYGbMmMHx48eZO3cuISEhtG3bFi8vL5YuXcpHH31UqAqjUCgYNGgQX375JYcPH6ZVq1YMHz6cb7/9lgkTJpSoYqJSqWjcuDHh4eEcOXKE7777jmrVqtGtWzf8/f2fOUJcq1Yt/Pz8+PHHH8nPzyczM5OBAweyZMkSsrOz5YmXRqMhPDyc7du3I4oiL7zwgiwfFEWR4OBgrK2tyc3NBe4RxtOnT3Px4kVatWqF0Wjk77//JjIykqlTpxbqAZeg1+u5evUq27dv586dOzRs2JBJkybh5ub2WNduQUEB8fHxnD17lr///psrV66gUqmoW7cuXl5e+Pr64u/vj5+fH25ubqhUqmJzd6XJ6G+//UaNGjX44IMPUKlUfP/99+zcuZNOnToVeW4olUqef/55BEHg22+/pWHDhuzYsYMXX3yRJk2aPNE96erVq7i7u3P79m0yMzOL7YmX7rkJCQlERkZy6tQptFottWvXpm/fvvj7+8vXUadOndi5cydBQUH079+fjz76iGbNmuHr64sgCAQFBdGxY0eWLFnCpEmTKqwKWp4wmUwsX76cvn37Fpr4GwwGVq9ezQsvvFBhJFSn03Hy5EneeuutqgrQP5Cbm8vSpUsRBIHJkyc/QNokqfKcOXPKhQRLkUz5+fk4OTmV+NoXRZH169fTrVu3Qh4L0u/K4txLTU3FxsYGrVZbJBHOy8vDaDQ+NURYclVv3ry5Wcacl5dHQkICAQEBZhjdo5GVlVXi6ntRLt//ZlQR4SeEIAjY2NgUIr4eHh4kJiYSHBxc5Os9PDy4e/euWYmwlZUVbm5uxMXFUbt2bbNtt7xxPxG2t7dHpVJhaWmJQqEgLS3NrPuqU6cOv/32G7179yYvL4/MzMx/TQWjMkAy0nrllVc4c+YMc+fOpU2bNjz//POoVCrUajU2NjYUFBSQmpparAGdWq2mZcuWNGjQgF27dvHdd9+hUqmIjIxk//79dOjQoZBE2srKirFjxzJ79mw8PT0JCwvjlVdeYe7cuYwbN65YV+p/7tfS0pK2bdvSvHlzjh8/zk8//YRaraZr166Eh4fLvctPM6Tj9cYbb2Btbc3XX3+NXq8nMzOTHj16sGLFikLEsHnz5igUCqytrRk7dqw8KZOqEo6OjjIRhnsOqVLm5fLly0lJSWHKlClyBVQyqcrOzubIkSPs3bsXjUZDly5dqFev3iNjj6T3i6KIXq/n7t273L59m6ioKM6ePcvt27exsrIiICCA/v374+/vj7e3N05OToV6wB+1j7y8PFavXs2lS5cYNmxYIWOvMWPG8M0332BjY0PLli2LrQw3a9aMNWvWsGfPHhYtWvTQ3vWSQBRFDhw4QMuWLdm7dy9+fn5yr/b9xDc6OpoLFy4QHx+PlZUVISEhDBo0CD8/vyIjNsLDw1mzZo3sq9C/f39+//13pk6dKp/zHTp04Pr162zatInevXs/c4tD90MyohJFkfr16xeqBp86dQobG5sKk4lLPeLOzs5Vz7b7IPkJzJs3j6CgIHmhorieYGlRqqy/w+zsbNlp2dfXt8QENiYmhszMzEJGeHFxcfLvymLcUn/w3bt3iyRVmZmZiKL41BCu3Nxczpw584Db++NAFEWioqLw8/Mrl8KUKIpkZWWVuKc8Pz//qerdLmtUEeEnhCAIuLi4kJKSIstPJCJcHAICAoiOjqZp06ZmG4dSqSQ8PJwzZ85Qq1atp3YCLq2ASkTYwsICa2tr2YjEnHB1dSUrKwu9Xi/HWlVNFsoXkktugwYNCAwM5I8//uCTTz5h0KBBqFQqfHx8MBqNZGVlyX34xW3H2tqaHj160KpVK9asWcPixYv59ttvCQ0NLdSfKQj3on1effVVFixYwNtvv01ISAjjxo1j4cKFvPTSSyWWMUqEuFWrVjRv3pyrV6+ydetW/vrrLxo3bkzLli1xc3N7ao21lEolnp6epKam8v7776PX61m4cCHZ2dn079+fPXv2cPLkSY4ePYrBYCA7OxulUklQUBDu7u7o9Xp5gunq6ipLoCUyO2XKFOrVq8eiRYtQKBQoFAq2bt1K//79MRqN3Llzh507dxIZGUmdOnUYO3ZsoUzb+yERPKPRiE6n486dO8TExHDjxg3i4+NJTU0lJiaGtLQ0nJ2def755+Xe2/sJe2lgMpmIiori119/JSwsjP/85z8P9PZJUVxz5szBysrqgXPLaDRy+vRpVqxYIUuMf/nlFyZPnlxkVbwkkCZGN27coFevXpw7dw57e3sOHz5MXFwccXFxZGdnY2tri7+/Py1btiQgIED2SXjYPjUaDY0aNeLAgQP06tWLxo0bc+TIEQ4dOiRHkllYWDB06FA+/fRTatasWWaT8cqAgoICVq9ezejRowsRl4KCAtatW8fYsWMrVJK8e/du2rZtW6V2+v8QRZHY2Fi+++47unbtSrt27R44NlJE0pw5cxg4cGCZ9gTfj/T0dAoKCrC2tsbHx6dE35nk4/D8888XMuLbuHEjXbp0KTNFRkJCAq6uriQkJBS5D61Wi8FgeGokuIcOHSI0NPSxspuLwtGjR8tl8URCeno6NWrUKNFrizPz/beiigg/ISSHW6laKRHjGzduFPueatWqcfbsWbOPJSwsjPnz52MymZ7qh56FhQUGgwFra2tUKhVKpRKFQlFsPvPjwsbGBhcXF2JjY6lXrx7nzp17pidslRmCcC8ua8yYMZw9e5bFixcTFRVFQEAAKSkp+Pj4kJeX90ijH+l6HDlyJFlZWRw4cIDXX3+d1157jRYtWhTqHw0KCmLQoEF8++23vP322wQFBTF16lTmzZtHcnIynTp1KvEEVpr8h4SEEBwcTFJSEseOHeO7775Do9HQsmVL6tWrh4ODw1NFigVBICwsjNOnT1OrVi0GDx7M4cOHyc7OZteuXQwYMABPT08iIyNRqVQYDAb+85//kJ2dzfz584F7rvb16tWTTc+qVavGt99+S5cuXdDr9Xz//fd4eXlx69YtvvzySxo3boybmxuHDh0iNzeXNm3a0Ldv3wdIoWQolZuby507d7hx4wY3b94kKSkJo9GIs7MzLi4ucjVYFEW6d+9O69atqVGjxhPFYEkxSWvWrJGNv4KCgoqtfLq4uDBhwgS+/fZb1Gq1XLlJT09n+fLlpKamMnHiRKpVq4YoilhaWjJnzhwmTpyIs7PzA59b+kx6vR6DwUBBQQFpaWly9EpqaipXrlzh7NmzvPfee5w5c4a2bduSlJREcHAwnTp1wsHBAVtb21JXawVBoG3btsyZM4euXbtiaWnJyy+/zOzZs6lbt67c121nZycb0k2fPr3UmahPA0RRZP/+/VSvXr2QBFIURfbt2yfL6isKWVlZxMbGVmUH/3+YTCbOnj3LsmXLGD58eJHP+/uJ8pAhQ8olA1ZCeno6t2/fRhTFEvsC3L17l/j4eMaOHSv/LjExkVu3bjFq1KgyG2tsbCze3t7Y2dkVSYQlo9OngXDl5+dz4MABJkyYYJbvWqfTERMTw5AhQ8wwupIhNTWVRo0aPfJ1koLpafheygtVRNgMcHBwKFQBdnV1JS0tTc7P/CdcXFzkWBhzElZnZ2c5Run+DMOnDRIRtrCwwMrKSj5OmZmZZt2PINyLUYqKiqJZs2bs27cPg8Hw1GcxP81QKpVydXj69OkcOnQIa2trvLy8SmWWplAo6NevH3fv3gVg5cqV7Nixg44dO9KyZUuZBDVq1IiMjAy+++473nzzTXx8fJg+fTo//vgjcXFxDBkypNRO5QqFAk9PT3r16kXXrl2Ji4vj0KFDbN++HTs7Oxo2bEhYWBiurq6V/lwTRZHq1auzYMECoqKicHNz4+OPP6ZOnTrY29vLrt7/JGpwbzJQUFDA7du3OX36NDt37gSgX79+dO/eXZYmhoaGcvLkSb777jvy8/M5ePAgL7/8MkuXLqVNmzbyJMtoNJKRkUFycjJXrlzh5s2bJCYmyhX+mjVr0qFDB5ycnLhz5w4nTpzgypUrVKtWjRdffJHatWs/tunU/TCZTERGRrJs2TIiIiJ49913S+Tw6uHhwYQJE5g7dy7Dhg0jKyuL1atX0759e0aNGlVokadNmzYUFBTw8ccfM2rUKHQ6HQkJCaSlpZGRkUFmZibZ2dnyoqdKpcLR0RE3NzecnZ0JDQ3lxo0bfPDBBxw7dozc3FymTJlCSEjIE312Ce7u7nh4eHDhwgUaNmyIm5sbXbt25ffff2fixInyOeHv70+vXr1YsGABb7311lPtX1EUMjMz2b59O2+//Xah7z8rK0v+fUXKwo8fP06dOnVkJca/GZIz9L59+3jzzTflnvb7IYoiN2/eZP78+QwbNqzcF8bv3LlDenq6TCAftW9RFNm6dSsdOnQoVA3evn07bdu2LZVDfGmRmpqKm5tbsUaA2dnZ2NnZPRWE69y5c/j4+JgtdeXatWu4u7vj4OBglu2VBKWJRKqqCBdGFRE2AxwdHbl69arcw+ji4iJLbou6ETk5OWE0GtFqtWaN7FGr1QQFBREZGUmbNm2emqrTPyFVlqytrbG0tKSgoAALCwu558ScnyskJIRVq1bRrVs3dDod2dnZVTFKFQypOtyyZUtUKhWrVq1CqVSSmJj4QATNw+Dr64uHhwc1atTg0KFDjBw5koMHD7Jjxw7atm1L27ZtsbW1pWPHjuTk5DB//nzeeOMNHBwcePPNN1m1ahWfffYZY8aMKXLSVJLPYWlpSWBgIDVr1kSv1xMfH8/x48f5/vvvAahZsyYREREEBAQUkmRV9LUrVRx3797Njh076NGjB507d5ark49y14Z70XKWlpbY29sTHBzMiy++yIQJE1i/fj2ffPIJqampdO3alS1btvDjjz/KhoNGo5Hk5GSSk5O5ffs20dHRXL58mYSEBIxGI25ubtSqVYtOnTpRvXp1NBoNBoOB69evc/jwYa5fv46bmxutW7dm+PDh8qKHOfq+srOzWblyJdHR0YwePZoaNWqUmOgIwr34sAEDBvDGG28QHh7OpEmT0Gg03Lx5k7t373Lz5k1SUlLk3HStVsuYMWPo0KEDERERVK9enXr16uHo6ChnbUuScukzCoKAVqvlr7/+ol69eqxZswYnJye8vb2f6PPfD4VCQadOnVi/fj0NGjRAoVDQunVrTpw4wZEjR+ReaEEQaN26NbGxsfz++++88sorz4xzsSiKbNmyhaZNmxYiAxI5adiwYYXGGRqNRvbv38+IESMq/H5SkZAi1pYvX87t27eZNm0ajo6ORZLg69evs2DBAkaNGkVISEi5H7dbt27h4OCAyWQqUQ+n5Ow+YMAAeayZmZmcP3+e//znP2U2foPBIM9xiyPCknlTWZJxc0Cv17Nz506GDBliluMliiJHjx6ladOm5Xr+FBQUlOhYS8azT4tkvTzwbDyRKhhOTk5kZGTIJE1amSuup1GpVOLo6EhqaqpZSZcgCLLjaJs2bcy23fKGhYWF3FuoVCrR6/VYWVmRmZlp9oqtt7c36enp6PV6/Pz8uH79Oo0bNzbb9qvw+HB1dcXFxQUfHx9q167NrFmzmDhxIs2bN3+gClkUBEGgT58+/Pzzzzz33HNs2bKFiRMnkpaWxpYtW/jwww9p0qQJnTt3pmfPnqxatYr58+czfvx4NBoNgwcP5syZM8yZM4fnn3+e9u3bl2i/xY1FrVZTo0YNAgICGDBgACkpKVy5coX9+/fz559/YmVlhb+/P3Xr1pX7Ne8nOOUFURRJT09n4cKF2NnZ8e677z4gzy0tpM/foEEDwsPDOXnyJEuXLmXu3LkcOXLkATJZUFDA3LlzuX79OjVr1qRFixZUr14dZ2dn+bUFBQVcuXKFQ4cOER0djZubGy1btmTQoEHyooK5JjaiKHLhwgWWLVtG48aNef/99x9p1HX/e0VRJCcnhz179jB//nzUajWnTp3i448/xs3NDScnJzw9PQkKCqJ58+Y4Ozvj6OiIhYUFFy5c4NdffyU8PLxEBlqiKHL58mUCAgK4c+cOBoNBljCaE8HBwfzxxx/cvn2batWqoVarGTlyJJ9//jm1a9eWpdAKhYIBAwYwZ84cdu3aRefOnZ96YiZF6pw+ffoBwpGSksKxY8f44IMPKvRzxsXFYTKZKlSaXdEQRZHMzEzmz5+Ph4cHU6ZMKfK6FUWRyMhIlixZUmLDxLIY682bN7G1tUWtVj9y4UoURXbt2kXz5s1l1ZIk1W/QoEGZ5vdqtVoUCgVarbZQROH9Y9NqtTg6OlZqozwpYsrS0pLq1aubZZt6vZ5r167Rt29fs2yvpJDiJh8FqaXoWVPnPAmqiLAZ4OjoSFZWlhz3olAosLCwoKCgoNibkZ+fH3FxcWbPd/Pz8+Pu3btPtfRBqghbWFjIPcJqtVo2TDInEba2tsbBwYG7d+8SFhbGhQsXaNSo0VM/UXsW4O3tLTsMBwUFYWFhwbFjx9i/fz9DhgyhevXqD33ICoJA9erVsbe3x9nZGaVSye7du+nUqRPDhg0jPT2d3bt388knnxAUFESnTp04fPgw8+bNk/NcGzZsiL+/Pz///DNnzpxhyJAheHt7PzEplOS87u7utGrVCp1OR3JyMrdu3eLs2bNs2LABvV6Pg4MDNWvWxN/fX/4sUoRPWZyjklPqt99+S+fOnWnTpo1Z2zekXuqmTZsSFBTEp59+ik6n48SJExQUFBR6raWlJdOnT5cf7tJK9tWrVzl8+DC3bt3Cy8uL5s2b89JLLz22sdTDIE3oVq5cKffh1ahRo8j9SEZder2enJwcYmJiiI2N5fr161y9epXo6GhCQkIYOHAgderUwWg0smrVKl577bWHZljXq1dPNnYbOXIkderUeejnNJlMHDx4kE6dOnHs2DEcHR0JDAw0u2+ESqWiffv27Nixg5EjR8rndI8ePfj111+ZOHGifK+2tLRk7NixfPbZZ/j6+lZItc2cEEWR1atX061bt0KyY5PJxPr16+nQoUOZEpGSjG/v3r20bt26UhORsoSU7fzDDz/w3HPP0aFDhyKvASnvdcWKFUyaNAl/f//yHyz3KvjXr18nMzMTPz+/R6oJsrKyOH78OO+++658LeXl5XHw4EGmTZtWptdXZmYmtra2JCcnFzvOjIyMCr0GSgKTycT27dvp2rWr2Y5XTEwMdnZ25Wq8ajQaMRgMJaoISwqJyl6pL09UEWEzQK1WYzKZMBqNqFQqFAoFdnZ2aLXaYnt1a9SoQWRkJO3btzfrWOzt7XFxceHWrVtFxjc9DZCqwBYWFjg6OpKfn49arUar1RbKazYHBEGgTp06cp7w5s2bMRqNz4x872mGk5MToiiiUCjkG/eECRM4d+4cCxcupHbt2vTu3RsnJ6diH2JKpZJevXqxbNkyxo8fz5dffklgYCABAQE4OzvTv39/unbtyokTJ1i6dCkajYbc3Fw+//xzpkyZgqOjIy4uLkycOJFjx47xzTff0Lx5c7p06fJEZkv3Q5JQ+/r64uvrS8uWLTEYDOTk5JCens7169c5d+4cW7ZsIS8vDwsLC9zc3PD09MTT0xMfHx8cHBxkKbJarX7scWVnZ/PDDz/Qr1+/Ml0QEgQBZ2dnPvroIz744AMCAgKoUaOGLImWPBeysrJQKBRcuXKF48ePExcXh6+vL82bN+fll1/Gzs6uzCb6RqORM2fOsGLFClq2bMnLL78sy8kk6XhOTg6ZmZlER0cTExNDXFwcOTk5suO5s7MzWVlZWFhYMHv2bOrVqyffW0RRxNHRke+++4433nijWPm9IAjUrl2b119/nYULF/LCCy881NU8KyuLxMREqlWrxrJly7CwsKBevXplcoyaN2/ORx99RGZmpiw3bdOmDWfOnOHAgQO0b99eHqejoyNjxoxhwYIFTJs2DXd396eSDIuiyJUrV0hJSaF58+aFJNFxcXFcv36dl156qUI/W05ODpGRkfTp0+epPMZPCpPJxMmTJ1m1ahVDhw4tttdXWjTasmULU6ZMwcvLqwJGew+5ubmkpqaSk5NDXl7eQ9WCoiiye/duIiIi5NeJosixY8eoWbMmLi4uZTrW5ORkXF1diYmJKbL/3GAwkJGRUem9auLj48nJyTFbvJkoihw/frxc3aLh3vWuVCpLTISBf+0CWVGomu2bAdIqo9FoBApnBRdlZy4IAj4+PuzcubNYQ63HhSAIREREcPr06aeWCGs0GvLz82UirNVqcXd3Jz09HZ1OZ/b9hYSEsHHjRjp16gTcW+0s6wdJFR4NjUaDUqmkWrVqGAwGUlJSZPl/SEgIO3bs4JNPPpErl8VJVWvUqIGDgwO3bt1ixIgRLF68mHfeeUeuINra2tKuXTtatmzJlStX2LJlC9u3b+fNN9/ko48+ws/PD5VKRcuWLQkLC2Pt2rX897//pWfPnjRu3NjsK6uCIMjmR46OjgQEBBSqNubn53Pnzh3ZLfT48eNotVp0Op3s1uvo6Ii9vT1OTk64ubnh6OiIRqORfywtLR+oKptMJtauXUuzZs1KHB/1pJ/T2tqa999/nzlz5vDKK6/g4eEhG0NJCx4ZGRnUrFmTVq1aUatWLaytrcv0IS5Jw6Vc4wkTJuDs7ExqaiopKSlcv36d+Ph4EhMTMZlM2NvbExAQQK1atejcuXMhSfPKlStp0KABPXr0eMCoSxAE6taty7Bhw2Qy7OPjUywZ9vPzY+LEicyfP5/MzEzat2//wHGQMm2Dg4NJS0tDrVaTn5+Pj49PmRwrW1tbwsLCOHLkiFxVUSqVDB8+XJZISwoKQRCoUaMGffv25fvvv+edd94ptRFdZYDBYODPP/9k4MCBha59k8nEypUr6d27d4WrsS5duoSvr2+5mvVUFuj1ejZu3Mjp06eZPHkyXl5exZLgnTt3cuDAAaZMmSK7nVcUsrOz0el02NnZFesvIyEnJ4cDBw4wY8YMecx6vZ7t27czbty4Mic5MTExeHh4EB0dXeQ1LBkbVqtWrUzH8SQwmUxs2bKlVOkQj4JOp+PSpUtMmjTJLNsrKXJycuRn+qNgMpnM7rXztKOKCJsBUh+fwWAA7k1a3NzcHpp76+HhQVZWFrm5uWZ3dAwNDWXBggWyvPhpg42NDTk5ObJp0p07d6hevToqlYrMzEyzG5D4+fmRnJyMwWCgRo0aREVF0aJFi6obRQVDMkGqVq0aqampaDQaWSlgbW1Nr169aN68OStXrmTPnj28+OKLhIeHPxBPpFQq6dOnD4sXL+aDDz6gRYsW/Prrr7z22muF8mPVajWhoaEyOVm/fj2vv/46DRs2pGfPnnLG4LBhw4iPj2f16tVs3bqVPn36UL9+/cfuHy4JJEmxhYUFGo0GJycn6tatW6gH1WQykZ+fT2pqKunp6Wi1WjIyMjh37pxsvpSXl4der0ehUKBSqWRibG1tjVKpJCkpiYEDB5Z4IpWVlcW5c+dkZYUgCERGRuLi4kKdOnVK9Lns7e3p1asXv//+OwEBAZw/fx6DwUDdunV54YUXCAgIeOyc35JAWiGHe33Hhw8f5vvvv8fNzY3AwEAWL15MXl4e1tbWuLq6yu7Uvr6+ckVaInoSif7pp59ISUnh9ddfp3r16sWOWyLDQ4YMYd68eUyaNKnYibsgCHh5eTFlyhS+++47tFotvXr1KiT3FEWRQ4cO8cILL3Dy5El8fX2Jj48vUwPATp068d1339G+fXvZ6dbFxYUXX3yRpUuX8vbbb8sqBUEQaN68OXfu3GHRokWMHz++zHJOywKiKHLw4EGcnZ0LSdRFUeTSpUvk5+fToEGDCn12GI1G9u7dy/PPP19hY6gISGZ2ixcvRqlUygstRX0XRqOR9evXc+7cOVn5U9HPe61WS2JioryIWVwLmFQNrlevnrxgL4oi58+flz01yhJS+4yfn1+xZljSom1l7UMVRZGkpCTu3r1LvXr1zPbdJyYmYmFhUe6VcMkxuiSfo6oi/CCePpZUCaFUKrG1tSUjI0NegXV1deXixYvFrryoVCosLS3Jzs42OxH29PTEaDSSkpKCp6enWbddHrC1tZWJsKOjI9nZ2YUm6kWZMzwJrKyssLGxITU1lfDwcI4fP06LFi3Muo8qlB5WVlay3PfixYsEBgai1+tleaq04DR+/Hiio6NZvnw5W7duZdCgQfj7+xcymfLz88PDw4OjR4/SpUsXFi5cyMaNG+ndu3ehB4L0Hg8PD1599VVat27NzJkzuXbtGt7e3gQEBNCkSRPq1KnDxIkTuXnzJmvWrGHdunV07tyZxo0blyj2wly4/zNKMTp2dnZyn9v9JE+CwWAgLy/vgZ8VK1bQrVu3UhETSSa6bt06vvvuO4xGI/v27aN3796l+gx169blhx9+wNvbmzFjxuDt7S1/L+Y6lvcvGBgMBpKTk0lISOD27dvcvHmTW7ducfXqVdzd3WnSpAm1a9fG398fNzc3XF1dCx2Xosx2DAYDR44cYd26dXTs2JExY8agUqlKZOoWFhbG4MGD+fbbbx9Jhp2cnHjrrbdYuHAhv/zyC0OGDJGJZlpaGllZWXh5efHbb78RGhoqO0uXBaRrxdnZmcuXL1O/fn35nGzYsCFnz55l06ZNhYxjFAoFffv25ccff2T16tUMHDjwqcm912q1bNy4kWnTphU6pnq9nhUrVvDyyy9XeCSalCNdq1atCid35QUp+3fhwoU0b96cbt26FbswqdPp+OOPP0hKSmLatGlma3F5UsTExJCcnIyPjw++vr7F3oezs7PZt28f06dPl8dtMpnYsGEDgwcPLvNrSRRFUlJSCAgIwMXFpchjZzAYMBqNJXK+rihs2bKF9u3bm03RJYoiJ06cKBc11T9RGh4hzQkqwzlfWVBFhM0AhUKBk5MTaWlpskOju7s7ycnJxRJhQRDw9PQkISHB7GRVoVAQEhLCpUuXnkoirNFoyMnJAcDOzo6srCxsbW0xGo2kpaWZfX9SNevSpUs0bNiQ1atXy/mcVag4KJVK2f1Xq9WiUqnIyMh4IGZIEAQCAwN55513OHv2LEuWLMHLy4u+ffvi5eUlG9j179+fuXPn0rBhQ0aMGMGXX36Jl5dXkTEH0r+Dg4OZP38+CxYswMPDg7CwME6ePMlff/2Fvb09ISEh9OjRQyaAGzdupFmzZrRq1QoXF5cHqtPljeIW4VQqVaHjKIoia9euLXWvlL29PSNHjsTe3p5du3YREhLCG2+8UWqTFEtLSxo0aEBwcPATy+kkoivJyO/evVtISp6VlYXBYMDW1hYPDw8cHBzIzMwkKyuLmTNn0qxZs1KRGVEUSU5O5tdff8VkMjF16tRiiWxxEASB8PBwRFHkm2++eWTPsLW1Na+//jrLli1jwYIFjB49GhsbG06cOEFYWBjZ2dmIokhCQkKZJwgolUq6du3Kxo0bqVevnnzfVCqVDBo0iE8//ZSQkJBC55aFhQUjRozg66+/Zu/evUXKvCsbTCYTmzZtomnTpnh4eMi/l6rwbm5uFeI2fD9EUeTw4cM0atToqaq0PwlMJhMnTpxg9erVvPTSS/JizD8hiiJ5eXksXboUlUrFxIkTK1zCfj9iY2OxtrZGr9fj5ORU5D1IcoWuW7duoapjVFQUSqXS7EWCopCXl0dubi56vb7Y+aXRaESn01VaIpyamkp0dDQDBw402/Wq1+s5e/Ys48ePr9REWJJGV/b7bXmiigibAVLlMiMjQ/6dk5MTWq1WdpIuCjVq1CA6OpqIiAizj6lRo0Zs3LiRdu3aPVUnvCAIclQSIBPg+yse5u5vEASB0NBQOZhepVKRmJho1tzNKjweJLM0o9FYSCZfFFQqFY0aNSI0NJTjx48zd+5cgoKC6NmzJ+7u7nh7e1OnTh12795Njx49GDduHF9++SVOTk7FVk+kBat33nmHP/74gwMHDvDKK69gb29PYmIily9fZtu2bSQlJWFpaYmTkxM7d+5k5cqV1KpVix49ehAcHIydnV2FTZCl/mKdTif/5OXlycZUUgWpuH6vR0GhUNCzZ0/mzJlD9erVH/uzenh4yCZZj/o8oiiSn58vy71TUlK4ffs2SUlJJCcnk56eLpsXurm54eXlhZ+fH61atcLBwQErKysUCgWnT5/m77//pl69ekydOrXUY9fr9Rw4cIBNmzbRs2dPOfv6cSAIAvXr10elUjF37lzGjx8vKxuKgqWlJUOHDmXTpk18/fXXvPbaaxw5coSRI0dy6tQpQkNDOXv2bLm44AYFBZGTk8OdO3cKLWTY29szatQoFi1axIwZMwpNjDUaDePHj+eLL77A2dm5WAJTWXDnzh3Onj37QFxSdnY2mzZtYurUqRW+eKrX6zl69CgTJ06s1MfSXCgoKGDNmjVcuXKFKVOm4OnpWSwJ1mq1zJ8/n4CAAPr161epFgqk6CR7e3vy8vJQq9VF3keys7PZu3dvIVdoo9HIhg0b6NmzZ7mcf7m5uajVam7fvk3Tpk2LfI3BYKCgoABbW9tKdx6KosiOHTto2bKlWbN0ExMTUSqVcmxceSI1NbXEvjZGoxFBEJ4qXlDWqCLCZoKUJSxBpVLJE9CibmiCcC/aZfv27WVC7AICAkhOTiY7O7tQ5edpgKWlJfn5+QDy2KUHQ1lUhOGedDYxMRG9Xk9gYCBXrlypIsKVAO7u7sTGxpKZmYmNjc0jiZIgCGg0Gtq0aUPjxo3Zv38/X375JSEhIXTv3p3evXvzySef0LJlSzw8PBg7diwLFixg8uTJD61EajQaRo4cyeHDh5k9ezb9+/enadOm+Pv707VrV/R6PZmZmcTGxhITE8OVK1e4efMm77zzDp6ennh7e1OrVi18fX1xd3fHzs4OjUaDWq2Wf6TcbKVS+UAlWZL0Go1G+cdgMKDT6dDr9TLBzc/PJzMzk9TUVLnKmZWVRU5ODjqdDoVCgVqtxsrKCldXV9zc3PDx8aFu3bpcvXq1SCn1o2AymUhOTubFF1/kxx9/JDQ0FA8Pj1Lf0yTjQKnXWZJs5+bmkpmZyZ07d0hJSSEjI4PMzEzy8vJQKpVoNBpcXFzw9vYmMDCQli1b4u7ujqWlJUqlUvZJuH/iGBUVxapVq7C1tWXChAn4+PiUamIg9cn9+uuvKJVKpk+fbhazHUkmPnr0aObPn8+YMWMIDAwsdrsqlYqePXvi4uLCBx98gEqlwsvLi59//pnu3btz4cKFMu0PlqBWq2nbti3bt2/nlVdeKTTemjVr0rp1a3777TfGjRtX6PtwcnJi/PjxfPPNNzg7Oz+0n7oiYTQaWbFiBb169Sq0WCSKIlu3biUiIqLC1VeiKBIdHY2trW2FTMbLE5I8d9GiRbi7uz9S4pycnMzcuXNp0aIFnTt3rnTeKTqdjujoaLKzs7Gzs8PKyuoBUispD4KDgwt9v7du3SIrK4uwsLByGWtmZib29vakp6cXS77y8/PR6/WV0gwvIyODixcvFoqdelKIosjRo0dp3LhxhSyGJScnExoaWqLX5uXlFWss+m9F5bobPMVwcnLi9u3bMqmVyK9ery9WfuPr60tycnKZZHqp1Wp8fX2Jjo6mfv36Zt12WcPS0lJ2h3Z2dkYURVnOKVV6zP0gs7Kywt7enuTkZCIiIti5cyft2rWrullUMLy9vbl+/br8PSQkJJRo4UiSj3bp0oXWrVuzd+9ePv/8c+rWrUudOnX4+++/GT58OIGBgQwbNox58+Yxbdq0YsmM5IbbqlUratasyZIlSzhx4gRDhw7FyckJS0tLORe4YcOGADJxTU5O5saNGxw5coS//vpLjlWrXr06zs7OGAyGIp0cS0JKpetCrVZjaWkpn8cuLi4EBQVhZ2dX6Od+p+j7/xRFEVdXV7Kyskq1cCZl7Do6OtK3b19CQ0N59dVX+eCDD2jUqFGJtyNVRKKioti7d69MiiUjLwcHB3x8fAgJCcHJyUl21JZ6cP/5mYravslkIjo6mtWrV5OXl8eAAQOoU6dOqQmwwWBg3759cu9rixYtzGqUJggCtWrVYuzYsfzwww+MHj36of2e0nkZFRXFmjVr2L17N3q9nry8vIdWlM0JQRBo2rQpW7duJSMj4wHy3aVLF+bOncvevXvp0KFDoe+rWrVqjBw5krlz5zJjxoxi+w4rCqIoEhkZSU5OzgOxKMnJyRw9epQPPvigAkf4f9i1axft2rWr8Mp0WUG6J168eJGff/6Znj170qZNm2KvYem+8v3339OvXz+aN29eKSthBQUFZGVlkZqaSs2aNYuMBMzJyWHXrl1MmzZN/p0k15d6ossDMTEx+Pj4cP78+WKlz1qtFoPBUOnMskRRZN++fTRp0sSsYzMYDJw9e7bClBilkUbn5uai0Wgq5XVQUagiwmaCm5sbKSkp8mTWwsICe3t7UlNTi+2Xs7KywmQylQkRVigUNGzYkBMnThAeHl6pJhaPgqWlJQUFBQCyVFGhUMgmP2VBhBUKBXXq1OHixYu0adOGhIQE8vPzzSqdqULp4ejoiF6vx9fXF5PJJEfWlPShLwgCNjY2dOvWjbZt27Jv3z62bdvGuXPnaNSoEXXr1iU8PJzs7Gy++eYbpkyZgrOz80Ndfr29vZk+fTq7du3i448/plu3brRq1aqQMy4gV3d9fHzw9vamdevWTJo0ifj4eM6ePcvly5fJz8/Hw8NDNmZyd3cvtq9YoVDIFc77K50P++xFQRRFMjMz5WMjHcu6dety8eJFOe6mJFAqlTRo0EA2CWzTpg1169YtdRVSkje/8847ODs7Y21tXeQ9sbT3MUmVEx0dzbp169BqtfTp04fw8PAH4qNKsq2EhAR++eUXLC0tmTlzZpmRNkEQqFmzJuPHj2f+/PkPzUKFewuuN2/e5OOPP+bbb78lICCAS5cuER4ebvaxFQdbW1saNmzInj176Nu3byGyq1KpeOWVV/jss8/w9/enZs2ahf4/NDSU3r1788033/D2229XaCvBP6HT6VixYgXDhw8vJKc1Go2sWbOGLl26VIrxZmdnc/PmTYYNG1bhYykrGAwGNm7cyIkTJ3jjjTfw8/Mr9rOaTCbOnj3LsmXLGDVqVCGX78qG3Nxc2QfD0tLyAXWBKIrs2bOH0NDQQou1kv/BmDFjyuWziaLInTt3cHR0RBTFYhdNpTi/ykaEtVotJ0+e5O233zZrNfjOnTtYWlpWWOym5Bpd0tdqNJpKey1UBKqIsJlgY2NDbm5uIUc2FxcXkpOTi+3RUqlUODk5kZycXGpzmZJAysctC6JdlrifCFtaWqJWq8nLy8NkMlFQUIDJZDL7PiXn1jVr1tC1a1e5H7VmzZpm31cVSg57e3uysrKoXr06KSkpcvW0tKvfgnAvL7hbt260a9eOzZs3M2HCBHr37k3Pnj1p0qQJer2eOXPm8Oabbz6S4KhUKrp06UJERAQrV65k37599O/fn5CQkGJbIeDe4ldgYCCBgYEYjUaysrJITEzk0qVLbN68mfT0dCwsLPD09KRatWoyiba2tpYrv/eT7cfFggUL+PXXX2nWrBnNmzenadOmREREsGzZMlq1alViSZuNjQ0NGjSQ/+3v71/qnlTJbTMkJKQQQXoSiKJIQUEBkZGRbNmyBZPJRLdu3QgLCyv1vVAURfR6PXv27GHnzp306dOHpk2blrm8UhAE/P39mThxIt9//z29e/emadOmRa7kx8fHo1KpqFevHr6+vmRnZ3P06FF69uxZpmP853g7duzIF198QdeuXR+YmDk6OjJ8+HCWLl3K9OnTC5FHQRBo1aoVWVlZzJ8/n4kTJ1aKSbREQHx9fQkMDCz0+1u3bhEXF8fw4cMrxaTy5MmT1K5d2+wpFJUBUizZ0qVLsba2fuD8+SeMRiN79uxh9+7dTJ48udh87sqCO3fuoNVqsbW1JT09/YH4naysLNkpWrr+pRzc5557rtzmd9JioI+PjxwdVxSys7NRKpWV4hqWIBmNNWzY0Ozz7SNHjtC4ceMKkdyLokhOTk6Jn9l5eXnlmmzxNKCKCJsJarUavV5fiAi7urqSkpJS7HukPuGbN29So0YNs4/Jzs4OGxsbEhISysUwxVyQiLAoinJIeGZmptw7XFBQUCaVWk9PT9LS0tDr9dSrV4/z589XEeEKhr29PTqdDicnJxITE7G3t0ev1z+RIZGNjQ19+vTh2rVrKBQKli1bhlKppHPnzrRs2ZKvv/6aN99885F51YJwLzpm/PjxXLt2jdWrV7Nx40Z69uxJcHDwI81YlEqlLPGtVauWTN5yc3OJj48nLi6O48ePk5iYKC8A2dra4uTkhJOTE/b29jg7O+Ps7CxfJ1K1WHLKvn/SJP1pNBrJz88nKiqKqKgofv/9d2xsbAgICEChUFC9enWGDRtWLlI7qdd2165dvPnmm2bZXmpqKkeOHOHIkSO4uLjQv39/AgMDS10BlrYXHx/Pr7/+ir29PdOnT3+oYsDcEAQBX19fpkyZwrx588jOzqZDhw6FJqBS72DLli1lM8GJEycybtw4li5dyvjx48st19LV1ZWAgABOnTpF69atH/gsderUoWXLlvz000+8/vrrhSaOCoWCLl26oNVq+emnnxg9enSFL+Cmp6ezY8eOQgQE/q9nuG/fvpXCeVhyrX/55ZefuQmuyWTi4sWL/Pbbb3Tq1InnnnvuoYRDr9fz119/cf36dd56660iZcaVDbdv3yYvLw8LCwu0Wm2hyqIoimzZsoVGjRoV+n1aWhpRUVEMGDCg3D6fXq+XF2udnZ2LfV12djY2NjaVqkc4Ozub48ePM3XqVLMeL6PRyLlz55g0aZLZtlkaSB4hJV10yMvLq1QLFJUBVUTYTPgnEYZ7Rj/R0dEPjVDy9/fn8uXLZjfMgnsT7Xr16nHq1KmHSogqG6ysrNDpdJhMJtnwRlrFUigUpKamloktv42NDU5OTsTHxxMWFsayZcvo1avXM9tv9TRAo9GgUqlwdnbm2rVruLu7k5KSUqxzdEmhUqkYNmwYc+bM4b333iMpKYlNmzZx9+5dAP7zn/8wc+bMYiNs7odSqaR27dpMnz6dqKgo1q9fz6pVq2jfvj2NGjWSV58fth2pyqvRaGTzp3r16gH/R14NBoPs8Jyeno5Wq+XKlSukpaVRUFCAwWCQ8xtNJpP8o1Ao5PuSRJIvXbok71sy3XJycmLQoEHEx8ezY8cOOnfuXKZ9RFKVZ/78+fTr1++xJqzS5yooKCAqKop9+/Zx+/ZtGjRowKRJk3B1dX2sCCupCrxt2zb27t3LgAEDaNSoUYXcCwThXl721KlT+f7778nJySnkEJufn8+FCxfo0aMHR48eJTQ0lLS0NDp37kx4eDifffYZr776arnkygqCwPPPP89PP/1E06ZNH1gMEgSBzp07c+PGDTZt2kSvXr0KjcnCwoIXXniBn376id9//53hw4dXmLGRyWRi9erVtG/fvtBCgiiKnD59GoVCUWnajuLj49Hr9QQEBFT0UMwGURTR6XSsW7eO8+fPP9JFXRRFcnNzWbx4MRYWFkyZMuWpkICKokhcXBwWFhZYWVlhaWlZ6HxLTU3l2LFjhdzKRVFk8+bNtGnTplwVAJJ3y6OKK9nZ2bK/Q2WA1BscEREht/GYCzExMWg0mgozqMvPz0cUxVIR4aqWv8KoIsJmgmRak5OTI5M0Ly8vDh069FCS6+fnx/bt28skt1YQBCIiIli8eHGhnq3KDisrK/R6PUajEUtLS6ytrcnJycHe3p7MzExSUlLKpFIrVSwiIyN5/vnnycrKQqvVlovrahWKh729PY6OjmRlZeHo6EhSUtITE2EAHx8fWrRowbp16xg+fDiTJ0+Wq5Nr165lzJgx/O9//6N+/fqPNEOSfAHq1q1LSEgIsbGx7Ny5k61bt+Lr60vLli0JDg6WJ2YluRb/2WusVquxtrbG19cXKN5MqyQmW5s3b2bdunXyvx0dHXF1deXy5csoFAo++OADkpKSGDhwoCzHNidEUSQmJoYFCxbQo0cP6tWrV+J9SJ/PYDBw8+ZNDh8+TGRkJB4eHrRr147Q0FC5kvi4xDo2Npaff/4ZNzc3/vOf/2Bvb1+h909BEHBwcGDSpEn88MMP/PnnnwwcOBALCwtu3LiBm5sb9vb2HDt2jKFDh3Ls2DFCQ0Np27Ytvr6+/PDDD3Tr1k02FirLz+Ln54darebq1avUrVv3gX1J/cKffPIJfn5+D5BJlUrF8OHDWbBgAatWrWLAgAHlvgAhiiLXr1/n1q1bD0if8/PzWb16NePHj68U7sOS5LNly5bPjAGOpBT54Ycf8Pb25t13332oK7QoiiQlJTF//nzCw8Pp1atXpfhuSgKTycStW7ewtLTEZDJhb28vV1JFUeSvv/6iU6dOhQhceno6586d44MPPijX+5JWq8Xa2prk5ORiM7MlDwobG5vHVm6ZE5J0+OjRo2avBku53U2bNq2wgokUt1XSa18qKlXh//B03CmeAqhUKmxsbMjMzJSJsK2tLdnZ2Q99n52dHbm5uRiNxjK5kNzd3dHpdA+1uq9ssLKykitblpaWckZz3bp15YpYWVTQJdOW5cuX07NnT3x8fIiJiakiwhUMJycnrK2tSUpKwsHBgaSkJLN8/4Ig0K1bN/773/9y7do1atWqhaenJy+99BK9e/fm0KFDfPzxxzg4ONCnTx9atGiBs7PzQ0mxRHL9/f0ZPXo02dnZREVFceTIEVauXIm9vT3BwcEEBgbi5+eHRqPBwsLiscjJw8bwKFSvXp0pU6ag1WpZvHgxCQkJrFq1CkEQsLOzY/To0WRlZfHZZ5/x8ssv4+/vbxYCJVVtduzYwcGDBxk+fDihoaEl2q4Uq3Tr1i2OHj3KlStXcHBwoEmTJvTs2fOJJcuiKJKXlyeb8QwcOJCIiIhKowiR+tzHjx/PTz/9xOLFixk+fDj79++ndevWpKSkkJeXh7e3N9euXaNt27ay6db06dP54YcfiIuLY8CAAWUanyEIAt27d2fLli3UqVOnyONnY2PDuHHjmDdvHh4eHg/kv1paWjJ27Fi+/fZb1q9fX+7KHJ1Ox/Llyxk0aFChqrYoimzbto3g4OBKo7LKzc3lwoULzJgxo1KM50lhNBo5duwYq1ev5oUXXngkyRBFkWvXrrF48WJ69+5daZ2hi4PBYCA9PZ20tDRsbGxk93+4V22Mjo4utBgjSaVbtWpVJt4yD0NcXBxeXl7cuXOn2NYhiQhXpgzhvXv3Eh4ebnYloV6vJzIykq5du5p1u6VBaUxdpWfc0xapWtaoIsJmgrRin5mZKf/OyspK7u0r7sas0WiwtLQkPT0dDw8Ps49LrVZTq1Yt2Q25styYHgbpWBmNRjkOJjMzEzs7O5RKJcnJyWW2bw8PDzIzM8nPz6d+/fqcPXu20sjf/q2oVq0aqampsnQsLi7ObNu2srJi6NCh/P7778yYMUOuOtja2tK5c2fq1avHrFmzWL16NYcOHcLW1pawsDAaNmyIu7v7I00nbG1tadSoEQ0bNiQ3N5ekpCSioqI4cOAAK1aswGQyYWNjg4eHB+7u7jg4OODk5CT3/d6fKywRUclF/f4///n3oiBJDXNychBFkYiICHbv3o2FhQV6vV5WRMyaNYtu3bphYWHB+fPn+emnn3Bzc6Nr1674+/s/VoXYZDKRkZHBsWPH2Lt3L8HBwbz33ns4ODg8dLx6vZ6MjAwiIyM5e/YsCQkJuLm50aRJE3r16oWTk5NZCJLBYODixYusWLGCOnXq8P7771cKJ+CioNFoGD16NH/99RezZ88mJSWFoUOHcvjwYUJDQzGZTOTk5MgLeJJx4+TJk1m1ahVffPEFY8aMeays55JAEARCQkL466+/uH37dpHqDan3uX///vz444+89dZbD/QTWllZMWHCBObOnYuFhUW5RcRIVR5HR8cHKtrJyckcOHCA999/v9KcG1FRUXh5eZld8lneEEURrVbLn3/+SWpqKtOmTXtggeSfMJlMHDp0iA0bNvDqq68+NHO7sqKgoIDs7GxSUlLw9PTEZDLJqriVK1fSr1+/Qr3yaWlpnD59upBUujwguSM7OTlx9erVYn0HpJaXyiKLlqrBU6ZMMfvxiomJwdbWttw8GIpCaaXOOTk5z6Sh3pOgigibERJhk6DRaFAqleTk5BT7kFIqlXh5eREXF1cmRFgQBBo3bszWrVtp06aN2bdfFhCEe5mtRqMRQRBwdHQkLi4Oa2tr1Gq13MdZFrCxscHV1ZWYmBhCQkLYtm0ber3+kcZHVSgbCIKAu7s7N27coHr16uj1erMuhAiCIFdoN23aRP/+/eWFGEEQ8PT05LPPPuPnn38mJyeHHj16cPPmTX755Rdyc3Px8vKiTp061KpVC1dXV2xsbIr1A5AMqQICAmSSJ+VH3rlzh6SkJO7evUtUVBTp6enodDqMRqOcgXu/4ZUoijI5lsiy9GNhYYFarS4Us5Sfn8/du3e5fv06BoMBf39/GjZsyOjRozly5Ag3btzgxRdf5MMPPyzk3Fy/fn3q1KnDuXPnWL16Nbm5udSpU4ewsDC8vLywt7d/oLoojTcnJ4f09HSuX7/O2bNnOXToEGlpafzwww8EBQU9sDgovS8tLY1bt25x7tw5bt68iSiKBAcH07FjRwICAuT7qjkgSTCXL1+OVqtl9OjRsmlYZYZarWbAgAH88MMPnD59Wl5keOmll4iNjZUXae6HRqNhyJAhHD9+nNmzZzN48GAaNGhQJp9VrVbTsWNHtm7dyujRo4vch/RsunPnDj/99BNjx44tJKWUrpk33niDb7/9FqVSSdeuXcv8u8nMzGTz5s1MnTr1AYOsv/76iy5dulQa0mk0Gtm7dy8dO3Z86gjg/ZAMsX7//XdatmzJyJEjH7ngptPpWLNmDVevXn1oBnxlx927d8nNzcXKygofHx+SkpLQaDScPXsWg8FAw4YNC1WDt2/fTvPmzSukqhcfH094eLjcClgUTCYTWVlZlcKZWOoNDg8PN7uyT1owa968uVm3W1pkZmaW6lwoTebwvwVVRNiMcHJyIiMjQ5ZtqlQqbG1tSU1NLfbBKQgCfn5+xMTEFLrhmRP+/v7yzbYyufg9DBIRBrC2tsZgMGBra1uIHJRVNSM0NJSLFy/Su3dvBEEgMzOzwowQqgAuLi5kZmbi6elJenr6I9sNSgtBEOjXrx+zZs2iQYMG1KhRQz63JKnwuHHj2Lp1K7/++iujRo2iW7du5OXlER0dzeXLl/ntt9/Izs7G2toaDw8PAgMD8fT0lKu7RfXkSHFIdnZ2eHt7A//XoyqKYqG/F/Wn0WikoKCA1NRUUlJSSE5OJi4ujujoaO7cuUNWVhZOTk4EBQVRq1YtPDw8qFatGllZWej1eqKiojh9+jQeHh44ODhQq1Yt9u3bR3R0NO7u7rI7ta2tLU2aNKFRo0akp6fzxx9/0Lt3b/r37y/3LksSb1EUycjI4MaNG+Tk5ODq6oqLiwuvvvoqjRo1on///syYMYNPPvmE2rVro9fruXv3LrGxsURGRhIbG4vBYKB69eqEh4fTu3dvuepr7t6unJwcNm/eLMcMtWrV6rGcpSsKCoWCjIwMBgwYwMcff4xCocDPz4+NGzcWa4ylVCpp1qwZ1apV44cffuDGjRv07dsXlUpl1s8tkdzNmzeTlpZWbByZQqGgR48e/PDDD2zYsOEBLwtJnTFx4kTmzJmDQqEoUxM3URRZs2YNrVq1KlQxl3qGb9++zSuvvFJpzpH09HQSExOpXbt2pRlTaSCKotxzffnyZcaOHVvo/lvcezIzM1m0aBH29va89dZbT4UpVlEQRZHbt29jNBpRq9UolUrs7Ozk83DMmDGFFv3S09M5efJkufcGw73nTXJyMtbW1sUu+MI9ImwwGCoFEc7KyuLIkSNMmzbN7GPJy8vj0qVL8jyxopCcnFzi+Wlpo5b+LagiwmaEu7s758+fl/8tSdLS0tIeGo9Uo0YNNmzYUGbjsrGxwdPTkxs3bshOtJUZ91eE4R4RNhqNcj+1UqkskSHQ46JOnTr89ttvvPDCC9SqVYvIyEi5364K5Q9XV1dycnJkImwwGMy6qCNNtocOHcqSJUt47733HphYKZVKunfvTlBQEEuWLKFp06b06NGDsLAwwsLCAORq9d27d4mOjpYruzk5OVhYWKDRaLCyspLdyaV+MCn6SJrwCIIgTyYkR+e8vDy0Wi1arZacnBzy8/PJz8+Xo6Ts7OxwdHTE09OTJk2ayAT0UcfIZDKRnZ1NTk4OWq2W9PR04uLiuHr1qrzoIDlS2tvbY2dnx5IlS7Czs2PMmDG4uLiQl5dHfn4+RqMRhULB/v37+e233xBFkU8//ZQzZ87g4eGBtbU1Dg4OrF27lnPnztGxY0dsbGywt7eXiW+vXr1wd3cvVJU3JyR5+MGDB9m8eTMRERF8+OGHlVYG/TCkpaWRmZlJv379UCgU/PTTT5w+fZrIyEgGDx780B5yHx8fpk+fzrJly/jqq6949dVXH5mdXVpYW1vTsmVLtm/fzuDBg4t9nWSe9fnnn+Pl5UWzZs0eIMN2dna8+eabzJkzB5PJVGaV4ejoaK5evfqA7NRgMLBixQoGDBhQadRBoihy5MgRGjRoUOExU48DURSJjo5m6dKlBAcH8/777z+SPEkmewsXLqRt27byosjTdu3eD6nVJycnh+zsbDw9Pdm1axe1a9cu1IcuiiI7d+6kWbNm5d4bDPeIsE6nIyUl5aFpClIMoKOjY4V+L6Iosnv3bho1alQm1fPo6GhcXFwqvN82IyOjVDnZBoOhUpiYVSZUEWEzQqoI3w83NzdSUlIeWsF0dnaW8x/LqsrZpEkTTpw4QVhY2FPx0FAoFDIRdnBwwGAwyA88qRJWVj0oPj4+ZGdnk5mZSf369dmzZ89T01/9LMLa2hpRFPHy8uLEiRO4urqSmppq1lVNqa+xbt26rFq1iqFDhz4wGQeoXbs2M2fOZMWKFXzyyScMGzZMltKq1Wp8fHzw8fGhYcOGQOG+XIm8SpLh3NxccnNzSUtLQ6fTyee20WgslAmsUqnQaDQEBARgb2+PtbU1VlZW8s+TSIWVSiUODg44ODjIVWlJ6iXJt6UJ2smTJxk3bhyJiYnUrVuXZcuWUVBQIG9H+pHUJ1qtlg8++IDAwECGDRtG/fr18fT0JDo6mujoaH7++WdGjRrFe++999BMSnNA+h5OnDjBpk2b8PX1ZerUqXh5eT211/Xx48cJCwtDpVIRHR3Ne++9x7p167h69Srjx49/6Hsl2fGoUaPYt28fn376KYMHDzarOZggCLRp04aPP/6Ynj17PnTybm1tzeuvv85XX32Fs7PzAxVtyYNjypQpfPPNN5hMJp5//nmz9gzr9XqWLVvGgAEDCj1bRFHk2LFj2NnZERISUmnOF4PBwOHDh5kwYUKlGVNJIFWBN2/ezPHjxxkyZAihoaGPXNgwmUwcOXKEtWvXMmLEiCIdyZ82iKLIrVu3UCgUcmykIAgcOnSImTNnFjom6enpHD9+nPfee69CPndGRgYajYa0tDS8vb0fWhHOzc2t8PzmjIwMTp8+XSbVYJPJxIEDByrFvDArK6vEZFwURXl+UYX/Q9XRMCM0Gg25ubmFfufj48OFCxce+j5HR0e5r6Kseo9CQ0PZvHkzBQUFld46XZKV6/V64F5F0GAwkJ+fj0qlQqFQlKkZg0qlwsvLi9jYWKpXr87t27cxGAyVphLwb4NCoUCj0eDp6UlMTAxBQUFmyRIuaj99+/bl008/5ezZs0RERBT5kHNwcGDUqFFcuHCBxYsXExISQs+ePYs0fhIEQa76Pm0QBAG1Wo1KpSIlJYXZs2eTlJQEQIMGDZg5cyaiKMqVa4PBgMlkIjU1lT179pCRkUFsbCxNmzbFxcWFcePGUbt2bU6cOIFer8dgMHDixAlSUlLKjAhLLtUnT55k27ZteHp68tprr1GtWrVK3wf8MBiNRg4fPsyoUaNIT08nKyuLZs2a4ezszJtvvsnq1at5+eWXHykZVSqVtG/fXlY6XLp0if79+z80qqY0cHR0pF69euzbt48ePXo89LVubm6MGTOGRYsWMWnSpCKNkuzs7Jg8eTLz5s3DYDDQo0cPs0zqRFGUzfDCw8ML/V9OTg5///03kyZNqjQTSFEUuXHjBnZ2dmXiLVJWMJlM3Lhxg19++YWaNWsyc+bMEqkx8vPzWbNmDdevX2fatGm4u7tXOAExB6RWkry8PDw9PQG4ePEiX3/9daG5oOQU3bJlywrrT799+zbu7u4kJycTERFR7OuMRqMcd1lR35FUPW/evHmZ9MPm5uZy8+bNBxbMyxuiKJKdnV0qhUBZJdQ8zXh6ZwKVEBqNhry8vEK/c3FxITU19aHvU6lUuLi4kJCQUGZjc3R0xNramjt37pTZPswFQRDk7GBAltikp6ejUCiwsbEhPT29TMfQoEEDTp8+LUtOzelUXIXSQRAEnJ2dUalUaLVaXFxciI+PL5N9WVtbM2bMGH7//feHmnIplUrCw8N57733sLa2ZtasWWzduvWBhbBnAZKJ1NGjR+WWBBcXF1QqFVZWVtja2so5xO7u7tSqVQsfHx/g/yZwgiCwfv16mjRpgp2dnSyb/fXXXwkKCjL7mCXn0g0bNvDRRx9x6dIlXnvtNV5//XX8/PyeahIM9yalJpOJatWqcerUKerVq4dKpeL27dsMGzYMOzs7vv76a1lp9DBIDs7vvPMOFhYWfPbZZ8TExJil/UQQBLp06cL+/fsfeW0IgkCNGjV48cUXmT9/PlqttsjXSD3D165dY/Xq1RgMhiceZ2ZmJhs3buSll14qdG6IosjGjRuJiIiQz+nKgp07d9KuXbtKQ84fhZycHJYvX86SJUsYPHgww4cPfyRZEkWR5ORkvvrqK/Ly8pg2bVqZuZ1XBHJzczEYDCQlJckGg40aNaJp06aFPmNKSgpnzpyhQ4cOFfLZJcdoiQh7eXkV+9qcnBwKCgoqRL4tIYW03G8AAQAASURBVC0tjQsXLpRJxVYURSIjI/H3969wZ+zSEuGqinDReLpnA5UMUi+rTqeTf2dnZ0dWVtZD33e/YVZZQRAEGjVqxMmTJ8u0v9ZcsLGxkU2RbGxsUCqVZGVlyavHJZngPS4E4V6MzI0bNzCZTNSrV4+zZ88+FcftWYWvry9paWlyrFBZLkz4+vrSu3dvFi9eLEt/i4IkL+3Xrx9vv/02cXFxfPDBB2zdulWOKHoWzhmNRsPrr79Os2bNZNOqh/WTKhSKQp4I2dnZ7Nq1ixMnTlBQUED//v1ZsmQJr732GocOHZLdsJ8U0kP++vXrLFy4kI8//hitVsu0adPkKvCzsBIuuZU2a9ZMlu22aNECgMjISCIiIhgwYACtWrXi008/lZ23HwZBENBoNAwaNIj+/fszb948duzYgcFgeOJz2N3dnerVq5fo2SMIAhEREbRq1YoFCxaQn59f5GtsbGyYMGECiYmJ/Pbbb7J66HFgMpn4+++/adGixQMkKyEhgRMnTtCjR49KRb60Wi23bt16Kjw/RFEkKiqKWbNmYTQaef/99wkJCXnkYpQoily4cIHPP/+cVq1aMWLEiEqvZistkpKSsLCwIDMzE51Ox+3bt+nWrVuhHk5RFFm3bh3PPfdchZLL6OhofHx8MJlMD43rycrKIj8/v8KciUVRlFNSyoKoiqIoy6IrekFVp9ORn59fqj5lg8HwTDwHzYkqImxGWFlZoVQqC7na2tnZodPpCpHjohAUFMS1a9fKbGyCINCgQQMuXrz4RJOG8sL9FWFra2v5uDo7O6NWq8u8su3i4oLRaCQ9PZ169eoVMkGrQvlCEAQ539nZ2RmdTkdqamqZLoS0atUKFxcX/v7770cSNUEQcHNz49VXX2XKlCncuXOHDz/8kN9//12W1T/NhFitVtOvXz+6devGwoULGTJkSLGuxBLc3NxQq9UEBAQwbNgw5s6dy9ixY9mwYQNz5sxh4MCB9O/fn/j4eE6dOvXYx0civ6mpqWzZsoUPP/yQZcuWERoaykcffcSQIUPkWJXKRGSeBAUFBZw9e5ZmzZqRkpKCTqfDy8sLo9HI3bt38fb2RqlU0rZtW0aNGsX333/P4cOHZc+Fh0GhUBAeHs7MmTO5ePEiX375JUlJSU98/vbs2ZPt27c/8jkojaFjx47UqFGDJUuWFPkeQRCwsrJi3Lhx6HQ6fvjhB3Jzc0s9Tsmw6cqVK3Tt2vUBg6w//viDPn36VCgBKQrHjx+nTp06ldr9VXJ3Xrp0Kb/++ivDhw/n5ZdffqjjsAQpGmn58uW88cYbtGnTxuzO8RUNURTlKEhra2u5B9fFxaXQ6+Li4rh27Rrt2rWr0M+fmpqKRqORo/mKQ3Z2Nnq9vsKIcHJyMlevXqVFixZlcrwyMzNJTk5+qAFueUGv1yOKYolbrwwGg2xGW4X/QxURNiMk2e79RNja2hoLC4siZV73w8vLi8TERLNVR4qCq6sroig+Uqpd0ZCqE1I1wMbGBpVKRWZmpizJLEsZOdz7LoOCgrhy5Qqenp4UFBSQlpZWpvusQvGQHKMlIpyVlVWiSfXjQqlUMmTIEC5cuMDp06dLVMkSBAEvLy9GjhzJu+++i7u7O4sXL2bWrFls2LCB+Ph48vLynkpSfPPmTXQ6HSNGjGDJkiX07dv3oa/v0qULNWvWZPr06bRt25ZOnTrRqFEjLC0tZc8EtVrN6NGjWblyZakWNiTym5aWxv79+/nyyy+ZPXs2mZmZvPrqq8ycOZPWrVvLE+5nafIM9yoz9vb2uLi4cOzYMerXr49arSY5ORkLCws5L1MQ7mVkv/322+zatYvly5eTn59fonPZ2dmZiRMn0rx5c2bPns3+/fvlSVdpIQgC1apVw8nJiQsXLpRoG0qlkn79+mFpacny5cuLlD9LPeyvvPIKbm5uzJ07F61WW6ox6nQ6fv/9dwYNGlSoyiWKIufOnSM/P5/mzZtXqnNIr9ezf/9+nnvuuUo1LgmSyd6hQ4f43//+h7OzM++//z7BwcGPHK80P5kzZw5JSUnMmDGjkHPys4abN29iZWVFRkYGtWvXxt7evhCBNBqNrFy5kt69e1eoDFev18sGiJ6eng8lUtnZ2ajV6gohwqIosmHDBjp06PDQqvWTbP/48eOEhoaWyfZLC71eXyqZc15e3iMXMv6NqCLCZsY/pdCCIGBvb09mZuZD3+fq6kpBQcEjZdRPAqVSSb169Thz5kyln4zf329tY2ODra0t6enpuLi4oNPpHrmw8KQQBIH69etz7tw5VCoVNWrUICoqqkz3WYXi4ebmRkZGBv7+/qSmpspS+bKEjY0NY8eO5Y8//iiVAkEQBJycnOjSpQszZ85k9OjRmEwmli5dyn//+1/mzZvHxo0buXr1KikpKSUiJxUJo9HIxo0b6d69u5wb/LD4BUEQCA8Px87ODhsbG65cuSIbdAwcOJB169aRm5srx/h069aNX3755ZG9nnq9noSEBHbu3Mnnn3/O559/TnR0NL179+bDDz9k0KBBVK9e/Zl+yJtMJvbu3Uu7du3kSZkUNxQbG/uACZggCLi7uzNt2jR0Oh1z5swp8aKDhYUFbdq0Ydq0aRw7dox58+bJCQilhSAI9OzZk02bNpW4p1epVDJ06FAyMjLYsGFDsRVtlUrFCy+8QEREBF999VWJK9iiKLJnzx7c3d0fcCDOzc1l9erVDBkypNJVT2JjY+V2qsoGURSJj4/n66+/5ujRo0yePJk+ffqUiDSYTCbOnTvH559/TuPGjXn11VcrrKpYXrh9+zZwr9rq7u6OUqks9JmjoqLIysqiSZMmFTVE4P+qwSWJ6pGIcEWoKGJjY7lz584DPdbmgiiKHDx4kNatW1eKxRkpPrGkY5EMZyvbPa2i8ezOGCoIDg4OD5DeomKV/gkLCwvs7OxIS0srM1dAQRBo3Lgxv//+O126dKnUF4NGo5HJrkajwcbGhrS0NDlTNjc3F5PJVKafoWbNmixfvpyCggIaN27Mvn37ykxuU4WHQ61WI4oiNWvWZO3atfj7+6PVanF1dS2zfUpEbdCgQcyfP59333231FJElUqFr68vPj4+9OjRg7y8PG7dusWNGzdYu3YtGRkZGI1GbGxscHZ2xs7ODicnJ9zc3LC2tsbS0hKVSiU/vEryU9LPVhJIJinJycnUr1+/xO+zs7Ojdu3aJCQkoFKpSExMxMfHB19fX0JCQti2bRt9+/ZFEARat27NuXPn2L17N507dy60nZycHG7dusWpU6e4evUqoigSEhLCgAEDqFatGmq1+l91PWZnZ3Pz5k2GDRvGnTt3UCgUeHp6IooiFy9eJDQ09IH3SAqbYcOGceDAAT777DNGjRpVogqdRKQnT54sxyz16dOHFi1alEqqKhlhqdVqoqKiCA0NLdG+JdXAvHnz2LZtW7H5wUqlkk6dOmFvb8+XX37JmDFjCAwMfOg+UlNT2b59O++++26h60YURbZv305wcHClq0ZK5L2iZbL/hCiK5OXlsWnTJo4ePcoLL7xA48aNS3SOSLmzf/31F5cvX2b8+PGV7riXBURRJCkpicjISDw9PVGpVFhaWsrPmIKCAlasWMHgwYMrfHEvOTkZFxcX7ty581BSLooiWVlZqNXqcpftG41G/v77b3r27FlmKQ3x8fGIooivr2+ZbL+0yMvLe2T29j9fb2lp+cxfW6VFFRE2Mzw9PeW+Dwk+Pj7cvn2bRo0aPfS9fn5+xMbGEhAQUKbjy8nJQavVyhK6yggrKyu5IixJztPS0rC2tsZkMsk3XEdHxzIbg7W1Nba2tiQlJREYGMiff/5JXl5ehTsF/hthYWGBWq3G0dGRu3fv0rRpU+7evVvmfTrS4tGtW7f49ddfefXVVx9rUiIIgrzYFRYWJhMWKVMzNTWVtLQ0srKySE9PJyoqitzcXHQ6HXq9Xo4bMplM8p/3t1HcXwFTKpVyDrFEolUqFba2tjg5OeHo6IiNjQ329vY4ODjg6OgoP0zvlxILgoAoimzatInOnTuXKj5MqVQSEhLC5cuXadu2LRcuXMDb2xuFQkGvXr343//+R8uWLfHw8MDCwoJhw4Yxa9YsAgMDMRgMXLp0iYsXL5KZmYm7uzsNGzakS5cucmzKv/FBLooiZ86coVatWtjY2LB582YaN26MhYUFJpOJmJgYunbtWuz7pb7hatWqsXDhQjp06EDHjh0fSVakOLsOHToQGhrKzz//zNGjRxk+fHipYmyUSiU9evRgw4YNhISElGjRRiLx48eP59tvv8XS0rJYSbBCoZAjpBYsWMDAgQNp3LhxkcTZaDSybNkyunXrVqgnUyInhw4dqrC81ochOzubqKgoBg4cWCnGJrUpnDp1ir/++ouQkBA+/PBDbG1tSzQ+URS5ffs2P/74IwEBAbz77ruPjPx6VpCZmcmpU6eIiYnBw8MDOzs7XFxcsLW1leO8XF1dqV27doUfj7i4ODkKVMqbLw5Sr3N5kndRFLl27Rr5+fmEhYWV2T4OHDhAixYtKnxhQoIUPViainBpiPO/BZXj23yG4OLiQmxsbKHfeXh4cPbs2Ue+NzAwkMuXL5dpSLelpSVBQUGcP3++UoSBFwdra+tC5idWVlayvNJgMGBjY4NWqy1TIqxUKqlbty7nz5+ne/fuODo6cvv27TKJe6nCw6FUKvHw8CAnJweNRoOTkxOxsbGyW25ZQhAE+vTpw5w5c9i9ezedOnV64uvmfrJpbW2NtbU11apVK9U2JDJsNBrlH+nfEnGW/tTpdGRnZ5Oenk5aWhqxsbFotVq0Wq2srlCr1XJes6enp2x4dfnyZQYMGIDBYMDCwqJEn11y/922bRvjx49n69atdOnSBbinmunevTu//fYbI0aM4NatW1y7do2srCyGDh1K586dadCgAS+99BJeXl7/monxo2Aymdi/fz+DBg3CYDBw5swZJk6ciCAIaLVa8vLyHpkpK1VmZ86cyZIlS7h69WqJYmyk93p6evLWW29x6NAhvvjiCzp27Mhzzz1Xosq8IAjUrl2bNWvWcOPGDYKCgkp8LtnZ2TFhwgS++eYb1Go1rVq1KvK90j7efvttvv/+e5KSkujatWuh81YURc6fP09GRgZt27YttB1RFPnzzz/p0aNHkbngFQmpbzkwMLBSmGRJiy9//PEHFhYWparkSgT64MGDbNy4kYEDB9KwYcMKd+EtL4iiyKlTp/Dw8CAvL0++Bzs7O2NlZYVWq2XLli289dZbleKY3Lx5kyZNmnDy5MlHFgLS0tLQaDTlOm69Xs/69evp27dvme23oKCA8+fPM23atDLZ/uNAStIoKSQiXIXCqCLCZoa9vf0DvYvOzs5y3E9xDwnJUGTnzp1lKvkVBIGmTZuyefNm2rRpUyb7MAdsbGxkIixVBSTbd4PBgKOj4yP7rp8UUq/jypUr6datm5wt/CjJXRXMD8mIKi8vD41GgyiKJCYmPvSaMidUKhVjxozhs88+o1q1aiWSlZY1FAoFCoXiiVanRVGUXe0LCgrIycnh7t27JCQkcO7cOTZs2ICNjQ1ffPEFKpUKZ2dn3NzccHFxwd3dHXd3d6ysrOQKtEKhkI+Lv78/ycnJaLVa4uPjOXv2LOnp6SQkJHDr1i22bNnCxYsXadasGYGBgbz//vts27YNW1tbevToUSkmgJUJSUlJ5OfnU716deLi4lCr1TLxTUxMxNXVtcRVVkdHR9544w22b9/OJ598wsiRI6lVq1aJjrnUOxwaGsqKFSv47LPPGDp0KP7+/o98v1qtplu3bqxfv54pU6aU6hqSxvzNN9+gUCho3rx5sfvz8PDg7bffZunSpfz4448MHz5cNk/Lyclh5cqVRao7zp8/j1arrZQtMEajkb179zJgwIAKvTZEUSQtLY1169Zx/fp1+vfvT3h4+EN9A/75/vT0dH7//Xfy8/N55513ZGf3fwNEUSQmJoavvvqKzp07k5iYSH5+PhkZGQQEBCCKImvXrqVFixa4u7tX9HDlLGcpxvJhREoURbRabbn2oUoLW7a2ttSoUaPMzqOrV6/i4uLygKt3RSIzMxNHR8dSV4SrUBhVRNjMsLe3l50rpZPT2dkZrVb7yCBrd3d3srOzycvLK1OTCD8/P5KTk8nNza0UK8tFwdbWlry8PHlRwM7OTl5F1mg0WFlZkZiYWGYyGAkeHh6kp6eTn59PvXr1+OGHHzAYDCV+6FfBfPDx8eH8+fNYW1ujVqtJSUkpt3B4iTyMGjWKRYsWMX369FJJkiorBEHA0tISS0tL7OzscHV1lU140tLSiIqKYsaMGVhZWVFQUEBSUhLJycmkpKRw8uRJkpOT0el0ckVauu9Jlen8/HzmzZtHXl4ev/32G40bN8bHx4dmzZrRt29ffvrpJ15++WVZDjhkyBA++eQTIiMjS9RH+m+BJMtr0qQJarWaw4cPF3Izvnz5MiEhIaXapkRKg4KCWLp0KS1btqRr164lksALwr0s6bFjx3L+/Hl+/PFH6tatS69evR5ZXQ4PD2fdunXExsbi7+9fqjE7OzszadIk5s6dC1AsYZWqyOPGjWPjxo188cUXvPbaa3h6erJ582bq1q2Lv79/offm5eWxfPlyRo0aVao2gPKCRJhKe8zMBVEUyc3NZc+ePezdu5e2bdvy0ksvlUpqKcmoV6xYQceOHenQoUOlPNZlifT0dBYtWkRwcDBOTk4oFAqqV68O3FPCRUdHc/XqVWbOnFkp7n+SJ4ter8fV1fWRcx+dTicvipYHdDodW7ZsYeTIkWW2T5PJxJ49e3juuefKZPuPA1EUycjIKJVpXhURLhpVRNjMsLOzIz8/H71eL9/g7e3t0ev15OXlPdRJz8LCAmtra7KyssqUCNvY2FCtWjWioqJo2LBhme3nSSDFJ0nSaDc3N0wmE+np6Tg4OGBtbS07LpYlbGxs8PLyIjo6muDgYPR6PRkZGbi5uZX5vqtQGD4+Pmzbto1atWqRm5tLQUHBI68pc0IQBIKCgujWrRvz58/n7bffLjNTjoqGKIrs2LGD5s2b4+LigiAI2Nra4uLiQp06deTrUhTFB34kSL38lpaWdO3alaioKAYNGlRIohoWFsa2bdvo16+fLBMfNWoUCxYsYObMmZVOnlpRMBgMnDx5kqlTp1JQUMDFixeZNm2avOhw7do1evfuXepjpVAoqFWrFjNnzuSXX37h22+/ZdSoUTg5OZVoW0qlkvr161OrVi02bdrEf//7X/r27UuzZs2K7T1Wq9V07dqV9evXM2HChFJNXiUCPnHiRL799ltEUaRly5bFjlWtVtOnTx98fX2ZPXs27du35+TJk7z//vuF9isZZAUGBhIYGFji8ZQXRFFk7969NG/evNwXYaU4pMOHD7Np0yaCg4OZMWNGqRYCpUrhH3/8QWJiIpMnT36k+/CzBslQbP78+XTq1In9+/djYWHB3bt3adasGVlZWVhaWvLrr78yaNCgSuNFkpGRgY2NDSkpKXh5eT30O5M8L+zs7MqlIiyKIocPH8bPzw9vb+8yO58yMjKIj4+vVIuzUk53Sb1+pIWsynJeVSZUac/MDBsbG/mGJ0GhUGBpaUlubu5D3yutDN68ebNMxygIAs2aNePIkSOVNrZFqVQiiqJsCOTk5CQTYUdHRxQKhSw3L0sIgkC9evU4e/YsSqWSoKAgLl++XGmP27MMGxsb8vLyCAsL4+zZs6jV6kLXWXlAEATatGmDr68vf/zxR7GRLk87tFotx48fp0OHDsVW3ARBQKFQyOZcKpUKtVot/1haWtKiRQsiIyMJCQnhxo0bcja4hD59+nD06FHu3LkjV5MDAgJo3749P//88zN7fEuLK1eu4OjoiJubG7GxsbLxGdxb5U9JSSl1j7kEqXo6fvx46tevz8cff8zp06dLnGkvCAI2Nja8+OKLTJ06lSNHjvDpp58SExNT7DaaNGnCnTt3iI+Pf6zxuri4MGnSJLZt28aBAwceej9WKBQ0btyYKVOm8M033+Dg4CC70EtISkpi//79vPjii5Vmons/CgoKOHPmjByVVR6QCPDJkyf58MMPOX/+PJMnT+aVV14pFQk2mUycP3+eWbNm4eXlxbvvvvuvI8Fwr4916dKlBAcH07BhQ7KysuT7p06nA+5J8728vCoV4UpOTsbNzY1bt26VyMg1OztbrnSXNXJyctizZw/du3cvs/1J/dxhYWGVauHbaDSWigjDvee6vb19GY7q6UQVETYzBEEo5Hgs/c7Gxobs7OxHvrdmzZpER0eXOdGqVasWsbGxD0xMKwukm5rJZEIQBFlul5mZiZubm9ynVB6ENDg4mKioKERRpGHDhk9FDvOzCCsrK0wmE9bW1iQnJ+Ps7Exqamq5j0OpVDJ48GBu377Nvn37nrlzQRRF9u/fT3h4+BOZ0QnCvSzuhIQEdDodtra2hfKYJQLWt29ffv/9d5n0CoJAp06dMBqN7N69+5k7vqWFKIrs3r2b9u3bIwgChw4dKlQFlVxan0RiKggCSqWSjh07MmnSJDZs2MDSpUvJysoq8fEXBAFvb28mT57M888/z8KFC/ntt99IT09/YBtqtZrnn3+ejRs3lphw/3Nfrq6uvPnmm+zatYvt27c/ctHkxo0bdO7cGU9PT7788kvZY8BgMLBixQq6d+9eKSeJkklWtWrVyi3pwWAwcPnyZT799FP27NnDqFGjmDBhglx1K6khVmZmJkuXLmXNmjWMHz+e3r17/+siz+CefPfXX3/F2tqa3r17k5OTg6WlJTdv3qR69eryokN+fj4vvfRSpfJHuHHjBjVq1CAhIQFPT8+HvtZoNJKVlVUuSh5RFNmyZQtNmzYtlWFUaWEwGDh06NADxnoVDckUszRS58zMzDKLZ32aUXmutmcIGo3mgUqVl5cXCQkJj3xvjRo1uHXr1mNNDkoDe3t7nJ2dy7z6/LiQbjjScbC3t0epVJKeno6Pjw+5ubnk5+c/sspuDri7u2MymUhOTiYgIIA7d+5U2gWEZxlSfJI0SXB1dSUmJqZCxmJpacm4cePYunWrnG/7rCA7O5v9+/fz/PPPP/G23N3dcXV1JTo6msaNG3PixIlCx0qKp1IqlRw+fFj+P5VKxYgRI9i2bRu3bt164nE8zcjMzCQ2NpZ69eqRl5fH5cuXiYiIkO+RV69eJTAw0CxSREEQqF69OtOnT8fR0ZGPP/6Yy5cvl+p5ZGFhQcOGDXnvvfdwcHDg448/ZtOmTeTk5Mjfr2TaGBcXV2hxpLRwcXFhypQpnDp1ig0bNmAwGIp8XVpaGhs2bGDkyJGMGDGCdu3aMXv2bA4ePMiZM2fQarXFOlFXNERRZOfOnXTs2LHMCZIUXfbFF1+wevVq+vXrx5QpU6hZs2ap9m0wGDh27BizZs3C1dWV6dOnExAQUCmPb1lDr9fzxx9/IIoiQ4cORaVSyVXWq1evYjAYsLW15ebNm7zyyiuViqhI8Vbe3t4ywX0YcnNzyc3NLRcinJCQQGRkZLFxauaC1IL3qNio8oa08Fea+35ubi4ajaashvTUoooIlwHs7e0fcDQuKRF2dnYmKytLlsqUJZo2bcqxY8cq5ST+/oowIMvZ0tLScHBwkPtpyoMIq1QqWRJtY2ODu7v7v35yXhFQKBR4enqi1+vJzc3F0tKS27dvV8j5KwgCzs7OjBo1isWLF5OWllbuYygLSPmVwcHBZnFytbW1pXbt2ly4cIGIiAguXryIXq8v9BqVSsWQIUP4+++/ycjIkH/v7OzMsGHDWLRoETk5OU80jqcZZ86cITg4GGtra65fvy5njsK97+vq1atmzxq1srKiX79+vPLKK/z++++sWrWKvLy8UlWHbW1t6d27NzNmzODu3bv873//4+jRo/L3b2lpSefOndm0adMTLfza29szceJEbty4wapVqx44v6TMYCmHWqlU0qJFC95++2127tzJu+++S8+ePSutAWJCQgJZWVllGttnMBi4ePEis2fPZtWqVXTv3p0ZM2ZQt27dUpkRSg7D3333Hbt27WLixIn07t37Xzv51ul0/P777+Tl5TF8+HD5WN64cQN/f390Oh13794lNzcXhUJR6RYLDAYDSUlJsmP0o7xrcnNzycnJKXPfDqPRyN9//023bt3K1PxJFEX27NlDq1atKk12sASj0SgreUoKnU5XqeTdlQVVRLgM4OnpSWJiovxvQRBwd3cnOTn5kRMJS0tLOUeuLCHJFq9cuVIpq5tSNIy06uXg4IClpSUpKSnY2NiQlZVVIrm5udCoUSNOnTqFIAg0atTogcpWFcoHvr6+xMfHY2Njg6OjI3fu3Clz9URxEASBWrVqyTLQ+83dnlbk5eWxe/duevToYZbtKRQK2rRpw7Fjx2TTreTk5Ade5+npSYcOHfjjjz/k71Pqzw8PD3+m+7EfBoPBwIEDB2jXrp0sWW/durW8UGg0GomJiSlR715poVAoCAoKYubMmeTk5DBr1ixu3LhRqnNcWjB65ZVXGDduHPv37+fTTz/lypUriKJIs2bNiI6OlmXKjwOp9ej1118nNTWVJUuWyM80URQ5c+YMGRkZsrRceo+7uzu1atUiLCyM3377rVR90eUFURTZt28fLVq0MLu7siQLP3PmDB9//DFr1qyhW7duzJw5k3r16qFSqUplhqXX69m1axeffPIJoaGhvP322/j6+lYqYldekEyjFi1ahMFgYNSoUfLxFEWRuLg4OQnDZDJx5swZmjdv/kStKGWB3Nxc2f3fxcXlkaQrJycHo9FYpmavoihy7do1srOzadCgQZmeX3l5eURGRtKoUaNKdx7n5ORgZWVVKiJcUFDwr3NpLwmqiLCZIT34/1khcnd3JyUl5ZEPWqVSWS6GWXCPXNrZ2T2WYUlZQ6FQYGVlJVeCrKysUCgU5OfnY2Njg8FgwNnZuVycowFq1qxJYmIiOTk5hISEEBUV9a+cmFc0/Pz8iI2NpX79+ty5c4ecnJwHKkDlCUEQaNu2Ld7e3vz5559PNRGWHDiDgoJwc3Mz24M/PDycxMREcnNzadCgQZGLSIIg0LFjR5KSkjh37lwhCW2fPn1ITEys1OZ+ZYXExEQKCgrw9/cnNzeXmJgY6tSpI383BQUF6PX6Mpt4Sk7eI0aMYNCgQSxatIg///xTzngv6TYkI8i33nqL3r17s2zZMr788ksSEhLo0KED69evf+JxWlpaMnbsWGxtbfnmm2/QarVkZWWxcuVKRowY8UBFJy4ujrNnz/LRRx/xxhtvsHHjRhYsWEBGRkalOc/y8vI4c+YMLVu2NNs2JTPPgwcP8sEHH7B9+3YGDBggE2ALC4tSXfsmk4mbN2/y2WefceHCBWbOnEmHDh1KRaSfJYiiSFZWFnPnzsXJyYkRI0YUOhZ6vZ67d+9iZWVFfHy8vOCkVCorHRGWCg53794tkSuzpNAry4qwXq9n3bp19OvXr0ydqUVR5PTp09SsWbNSydUlpKWlFWoVKwl0Ol0VES4CVUS4DODo6FhI4gf3XI9zcnIeKXmWXFPLwzBL6tOqjPJohUKBtbW1TISliY5Op0OlUmFlZYWNjc0T9ZeVBhqNBhcXF+Li4nByckKj0ZQbCa/C/8HBwQGtVou/vz9XrlxBEAQKCgoqdEySeVZCQgK7du2qdNdSSVFQUMCOHTvo1q2bWXsRvb29sbKy4vbt2zRu3JjTp08XuYikUqkYPnw4K1asKKT0UKvVvPrqq6xbt67CpPAVAVEUOXjwoBxFdO7cOWrWrFmI9MbFxeHm5lamcjeJyIaGhvL+++9jMpmYNWtWqXuHJRlfeHg47733Hm3btmXp0qWcOnWKQ4cOFVJRPe44VSoVgwcPJjw8nC+++IKlS5fStGlTqlWrVmgSr9fr+e233xgwYAB2dnb4+fkxffp0/Pz8mDVrFgcPHkSn01X4uXbp0iW8vb3NYgZkMpnkXukPP/yQCxcuMHr0aN566y3q1KlTbNxVcZByTH/99VcWLVpEt27deOONN8zSUvG0Qqr2fvrpp4SGhjJw4MAHFgTy8/MxGAyYTCauX7+Ot7c3Hh4ecrpIZUJMTIxcmKlRo8YjX5+Tk4NCoSgz4iiKIidPnsTV1bXMZeSiKLJr164y70F+XGRkZJS6F/v+WNcq/B+qiHAZQCLC9z9EpYDxkvT+lpdztCAIREREcOnSpXLpSS4tiiLCklOeg4MDVlZWJCUlldtkpWHDhpw+fRqlUkm9evU4ffp0hU+U/m2QMrnt7OzIysrC0dHxiSfQ5oCVlRWvvfYaO3bs4NKlS0/deSGKIkeOHMHPzw8vLy+zbtvKyorQ0FAuX75cyHjun5AWASMiIli3bl0hibS7uzsDBw7kxx9/rJStHGWBgoICTp8+TfPmzQHYv38/bdq0KZTDHB0dTUBAQLm4zEp9vy+99BLDhw/njz/+4JdffkGr1Zb6fFer1TRp0oT33nuP1q1bYzKZmD17NvHx8U8sT1YqlXTp0oWwsDCWL1/+wARe6oPXaDQ0aNBA/r2lpSXdu3dnypQpHD9+nC+//JJbt25V2LUsuaZ37NjxibZjMBi4efMmixcv5tNPPyU3N5epU6fy2muvERAQ8FhVtYKCAvbs2cP//vc/HB0dee+992jQoEGl66MsT5hMJk6ePMm8efMYNGgQXbt2LfLYpqamYm9vz+HDh/H09MTa2hobGxtZ9VZZIIoiMTEx+Pn5kZSUhIeHxyNfn5ubiyAIZUaEc3Jy2L59O7169SrzYxUfH49OpyvRAkBFICMjo1QKAmlhr4oIP4jKc9U9Q3B2diY7O7uQZFOpVD4Qq1QcHB0dycrKKhfprYODA9bW1uVWWS0pBEFAo9HIUhuFQoGtrS1KpZKMjAxcXFxQqVSkpKSUy3ESBIGwsDCioqLQ6/VERERw9uzZp47wPO2wtLTEzs5OjlBycHCoNNJ+Jycnxo0bx9KlSysFOS8NdDodW7ZsoWfPnmafYEjy8QMHDqBSqYiIiChWhSIIAj179uTKlSuF8rqF/8feeYc3cWZt/55Rt1wky733boxpNqGHXkIJkARCCIEEwkLq5k3bzabtm939krybZNMgJKElpNBDBwMGA6YZMGDce5GrbBVLVpn5/uCaWYxtsGxZko1+15VrF9saPRrNPPOc55xz3wSBoUOHIjo6Gtu2bbO7Xk5LQ9M08vLy4OnpCalUisbGRigUig6LsoKCAkRFRVl1bCRJIioqCn/5y1/g4uKCDz74AOfOnetSsbkrGKvBUaNG4auvvkJlZSX+9re/4auvvkJZWRlomu7x/KrX63Ht2jW8++672LZtG9LT09lrRqFQYN++fXjyySc7XOsEQcDX1xcvvfQSpkyZgm+++QabN2/u1AKqr2loaEBTU1OPhNBomoZGo0FGRgY++ugj/PDDD4iKisJ7772Hxx9/HF5eXj26zxlxtn/84x/Izs7G66+/jjlz5kAsFttl1swaMKXmW7Zswb59+/Dyyy9j0KBBXZ7fwsJCtLa2YvPmzQgJCYGLiwtcXV3tzlaKoiiUl5fDz88PLS0t8PDwuO9rFAoFBAJBn2S2aZrGgQMHMHz4cHh6elr8+He/V3p6OkaPHm2XInpMNYY5gbBOpwNJko5AuBMcgXAfIBKJYDAY2gXCJEnCy8urW8rRYrEYAoHAKh6pHA4Hw4cPR2Zmpt0FdU5OTmwgzPhGGo1GNDU1ITAwEM3NzdDpdFbLZstkMlAUBYVCAT8/P+j1ejQ0NFjlvR3chskO6vV6KJVKNhC2h2uXIAiEhIRg/vz5+Prrr9vZxdgzTG9wUFAQAgIC+uQ9YmNj0djYCI1GgxEjRuDixYtdBrMikQhLly7Fli1b2vWikiSJ+fPno7y8vJ3V0kDkzrI8kiRx4cIFDBo0qN0Ck6Zp1NXVwcvLy+rjYzYq58+fj5dffhmnTp3CJ5980qN7kfGJf/bZZzF48GAMGjQI3377LT799FMUFxeDoiizjknTNPbt24eoqChMnToVb7zxBk6dOoVt27ZBp9Nh+/btGD9+PLy8vDoNPAiCYC2g3nvvPbi6uuLDDz/Evn37zFLO7g2MMFpqamq3F+I0TcNkMqGkpAQbN27Ee++9h+zsbCxevBjvvfcexo0b1+OAlaZpyOVyfPnll9i4cSPmz5+PF198sctz+KBA0zRKSkrw97//HRwOB2+99dY9e2lpmkZOTg5u3ryJkJAQNDY2wsXFBSKRCGKx2K4ywgaDAS0tLeDxeOByud3SIWhsbASfz++T4LG6uhq5ublWKVVWq9W4du0aW41jjzQ1NUEmk3X779va2sDlcvu0r7q/Yj933QCCJElwudx2gTBBEPD29u5WpojL5cLf35/dFe9LmPLo69evm72j39c4OTm1y6Azu1/Nzc3w8PCAQqEAl8u1Wo8oh8NBbGwsbt68CS6Xi5iYGNy8edMq7+3gv4SGhqKsrAwBAQEwGo0oLy+3m6CIIAikpqYiISEBGzdu7BeCajqdDocOHcLcuXP7bIHh6+sLg8GAuro6+Pj4gMPhdFmFQhAEIiIiMHjwYGzfvr3d74RCIf70pz9h586ddvW9W5rm5mbI5XLExMTAZDLh3LlzHXxumU1AV1dXm42TIAgEBATgtddew9ixY/H555/j999/N3sTiCAIjBkzBlVVVQgPD8d7772H0aNHY+PGjfh//+//se073TlmWVkZzp8/j/nz54MkSchkMrz++utobW3FX/7yFxQWFmLixIn3vdYZobC5c+fiL3/5C+rq6vDee+/h1KlTfa4Qr9frcfHiRYwaNeqe42SC34aGBhw6dAjvvfceNm/ejODgYPzlL3/B6tWrWY/pngbAzc3NrLhZXFwc3n33XSQmJoIkyQc2CKZpGmq1Gj///DPWrVuHxx57DIsXL4ZQKLxnENzY2IiTJ09izZo1cHJyAkVR4PP54HA4cHd3t6vzyWQQNRoNpFJpt16jUqnA4XAsXiJvNBqxfft2q1hx0TSNa9euITQ01C5FsoDbY1QoFGZpB7S1tUEgENjVNWYvOALhPoAJhO/OVDKBcHceoFFRUcjPz++rIbbD3d2dFbOxJ5geYZqm2b4TgiDQ3NwMd3d3tLS0wMXFBQqFwirjIQgCQ4YMYUuihw8f7rBRsgGBgYGoqqpCSEgIysrKoFar7apUliRJzJ07FwaDAXv37rWrsd0NTdPIzMxEYGAg/P39++x9SJLE6NGjcf78efB4PAwbNgznzp2759/Pnj0b+fn5yMnJafc7T09PPPXUU/juu++sZp9mTZgMfXJyMivKR9M0AgMD2/2dXC6Hm5ubXXi0crlcjBw5Eu+88w7a2trwwQcf4NKlSzAYDN2eHwUCAWbMmIG9e/eCy+UiJSUF77zzDqZOnYo9e/bg73//O06dOgW1Wt3lMdva2rB582Y88cQT7ZRrhUIhFi9ejKamJjQ2NqKoqKjb9yVBEJDJZHjmmWewdu1a3Lhxgw2IzVHP7i5M1tDb27vLha7JZEJTUxNOnz6NTz75BP/3f/+HlpYWPPfcc3j77bfx8MMPQyKR9HjRy5RWHzhwAH//+98hEonw7rvv4uGHH7Y7QSdro9frceHCBXz44YcgSRLvvPPOPUuhGTQaDf7zn/+Aw+EgICAANTU1bPuXk5MTpFKpXQUplZWV8Pb2RmVlJUJCQrr1Gq1WCx6PZ9GMME3TuHr1KjgcDhITEy123K4wGo04ceIEpkyZ0ufv1VNomjbbE1in0/Wp53J/xhEI9wFMqVdLS0u7n/v6+kIul3frwRkSEoLS0tI+GmF7OBwOhg4danfq0S4uLu0Wum5ubuByuWhoaIC7uztaW1vh6emJiooKq40pKCgItbW10Ol0CA8PR0NDQ4fv2UHf4unpiaamJgQEBKCqqgomk6lbvffWhM/nY8WKFcjKyrK7++pOtFotDh8+jHnz5vX5eyUmJuLatWswmUysevS9rK8Y254tW7a0mwcIgkBSUhKSk5OxdetWu6tk6S0mkwlnzpzBmDFjAAAZGRkYNWpUh4W2XC6Hr6+v3Syemefek08+idWrVyMtLQ2ffPIJW97cndenpKSgsrISVVVVIAgCfD4fgwcPxuuvv47ly5cjNzcX77//PjZt2oSSkpJ23z1TTi6TyTB48OB2x6ZpGkeOHMGoUaPw5ptv4ueff8a+ffvMsl4jSRKBgYFYvXo1GxB/8MEHOHz4MFpaWix6jx89ehQTJ05sV8ZoMplQV1eHEydO4JNPPsHHH3+M4uJizJs3D3/729/w+OOPIygoqNdBiE6nQ0ZGBj744API5XK8+eabePTRR+Hi4mI315otMBqNuH79Oj766COcOnUKf/rTn/D444/D2dn5vudFo9Hgq6++gkwmQ3JyMpqamiASiUDTNEiShMlksqvsI03TKC8vR2BgICoqKhAcHNyt12k0Gri4uFg0ENZoNDh48CAWLFhgleuvqqoKBoMBISEhdnu9Mx7g5pxnJiPsoCOOQLgPYPpZ71ZGlUqlUCqV3SqX9PDwgFKptEr/K5PpvHbtml1lrxirHGaBIZVKWYEsJgsilUpRU1NjtUDDyckJ3t7eKC0tBZ/PR0BAAIqLi63y3g5uI5VKQVEUpFIp5HI5xGKxXYpTubi44IUXXsDvv/9uFRV4c6FpGufPn0dQUFCfB1RM8FpQUAC1Ws2qpd7v3omIiEBycjK2b9/ebm4iSRKPPPIIVCoVjh8/bnfntjcUFhbCyckJfn5+0Ol0yM7ORkpKSofvp6SkBKGhoTYaZdeQJIng4GC89tprmDx5Mr777jusX78eDQ0N9/2eBAIBZs2ahV27drVTDedyuQgJCcFzzz2Hd955BwEBAfjxxx/x/vvvY9++fZDL5aisrMSJEyewePHidpsGNE2jqqoKZ86cwcKFCxEREYG33noLpaWl+PTTT1FfX2/W9UOSJPz9/bF69Wq89NJLkMvl+PDDD/HTTz+xG929uR7r6+vR2NiI6Oho6PV6FBUVYceOHfj73/+Ozz//HJWVlZg3bx7ef/99PP3004iKirpnSW53oGkaBoMBZ8+exfvvv4+srCy88MILeOaZZx54OySDwYArV67gX//6F3bu3InHH38cr776KoKCgu6bBWaEtL755htERUUhLi4OISEhuHnzJmQyGaviq9fr7c5DuLi4GCEhIaipqYG/v3+3roHm5mZ2nWYJmM2txMREeHt79/l1yLzf+PHj7VoB3WQywWQymXWeHRnhrnEEwn0AU0p1t9gVn8+HyWTqVrDp7OwMsViMurq6vhpmO7y8vMDj8eyqPFosFrP2ScBtsaq2tjaoVCq2f8vd3d2qYkkEQWDw4MHIysoCAKSkpODChQsDaiFu75AkCVdXV7i6uqK8vBxisdiqmyHm4OXlheeeew7ffvstGhsb7WqMTG/wnDlzrLLQFYvFkEgkKCkpAQCMHTsWp06duu85mTNnDoqLi5Gdnd3ub3k8Hp599lkcOXIEhYWFdnVuewqzEJswYQJIkkRRURFkMlmni+Sqqir4+flZf5Dd4G7BqaCgIHz00UfYs2fPPcuJGXXw+vr6TjUymHt/4sSJePfdd/Hss89CrVbj3//+N5YtWwZ3d3colUoYjUb2tQaDARs3bsRjjz0GV1dXEAQBFxcXrFmzBikpKfjHP/6BzMxMmEymbl9DjLeyr68vnn76abzzzjtwc3PD559/jn/961+4dOmSWX3ENE2DoigYDAYcOnQINE1j/fr1ePfdd/Hbb79BKBRi+fLl+OCDD7BkyRJERkZaRGWYKbHMzMzEe++9h3PnzmHVqlV48cUX4e/vb1fiTdaC+S5UKhVOnDiBd999F4cPH8acOXPwl7/8BTExMd3quWbKy7/88ksEBwdj9uzZKCoqQkREBIqKimA0GuHi4gKhUIi2tjaLeEVbCoqiUFtbCzc3N2g0mm4pRuv1eqhUKrO9bbuCpmnU1tbi2rVrmDx5slWeUWq1Grm5uRg2bJhdb/6oVCoIhUKzFKBVKlW7dhEH/8V+tzz6Oe7u7uzijLmhGFGE1tbW+5YoMCIklZWVHXrD+gKmPPrChQsICgrq8/frDjwer92CRiQSgSRJtgyWUcxTKBQwmUxW89KMj49HWloaKIpCbGwsdu3aBa1WCycnpz5/fwe3CQgIgFarhVgshslkQllZGUaPHm3rYXWAIAjExMRgxowZ+Oabb/DnP/8ZIpHI5g9Zxjc4JCTEauW1XC4XSUlJSE9PR1JSEoYMGYL9+/dDo9F0qUjK+IcvX74cX3/9NYKDg9neR4Ig4O7ujmeffRbr1q3D22+/bVeLyZ7Q3NyMkpISPPPMM6AoCunp6Rg3blyH74dRrzdHNdQWMBZJ06dPR2pqKvbu3Yv33nsPM2bMQGpqaqfiLUxWeMeOHXj11Ve7VHbmcDgIDg5GUFAQxGIxpFIpoqKisHnzZmg0GoSEhCA+Ph719fXg8/kYMmRIu2NxOByMHz8e0dHR+OGHH3Dt2jUsWrSIDZbN+Yxubm6YNWsWpkyZgoKCApw4cQK///474uLi8NBDDyEoKKjdZ2VKG9va2lBTU4OioiLk5eWhqqoK58+fx7JlyzB8+HAEBgaaPZ7uQNM0dDodLl26hIMHD8LT0xPLly+3mie1PcKck5KSEpw8eRIlJSWIiYnBqlWrEBgYaNZ5YUTGvvrqKwwaNAgzZ84EQRCorKzElClTIJfLodPpIJVK4erqitbW1m4LUlkDg8EAvV4PkiQhEAi6lR3V6XQWDYQpisL27dvxyCOPWGVtxVRIxcbG2n3A2NLSArFYbJYCdEtLi91VHdgLjkC4j/Dw8GAzhcykwOVy4e7ujrq6um5NerGxsbh165bVJNyHDh2Kb775BnPnzrWLshAul9tul57D4YDP58NoNMJgMCAwMBD19fU9KhPpDe7u7uByuZDL5fDx8YFMJkN5eTliYmKs8v4ObitH5+XlwcfHByqVyqp94uZCEATGjh0LuVyOTZs24bnnnrP5/cVkg1966SWrLXwJgsCwYcPw2Wef4fnnn4eLiwsCAgLYHfh7vS44OBgTJkzAli1bsGbNmnYLgOjoaEyfPh3r1q3DK6+80m/Lv2iaxsWLFxEfHw+RSASVSoXS0lIsW7asw8JSo9HAaDT2m4UNs2mxdOlS1NTUYM+ePTh8+DBmzZqFYcOGdchuJicn48CBAygqKkJkZOQ9j11VVYVTp07hrbfegru7O+bMmYOWlhaUlJQgIyMDv/32G4YNG4YvvvgCISEhCA8PZ0vzRSIRfH198dprr+Hw4cP4+9//jgULFmDo0KFm36PMpk1CQgLi4uLQ0tKC7Oxs/P7775DL5YiPj0dCQgIaGxtRVVXFPrvc3d0RHh6OadOmoaqqCp6enp1+55aApmmoVCqcPXsWJ0+eRGBgIFauXInAwMAHzlblzsxvcXExLl26hJKSEshkMowdOxZPPfVUt/p/OztuVVUVvvnmG0yYMAETJkwAh8OBVquFTqeDQCBARUUFCIKAv78/PDw8UFxcbFd+tbW1tXB1dUVzczO8vb279YzQarVoa2vrls3S/aBpGpcvX2YFsqyxUWsymXDixAmsXLnS5hvV96OlpcXsDTKlUtlt0bMHDdtHOwMUmUwGhUIBiqLYSYQgCHh6eqKurg7R0dH3PUZgYCCbebTGYpXJDNXU1FglC30/uFxuOzEULpcLgUDA+tt5e3sjOzsbIpEICoUCvr6+VhtXQkICrly5gpkzZyIlJQWZmZmIjo62+wl0IMBUS5w+fRre3t6orq6Gp6dnu00ne4PD4eDRRx/FV199hb1792Lu3Lk2y7zQNI309HRERkZa7Z5hiI6OhlwuR1lZGSIjI/Hwww/j8OHDSE5OvudCnCAITJw4EdnZ2cjIyMDYsWPZ75ogCIwfPx6lpaXYvn07Fi1a1C8X9QaDAadPn8Zzzz0HALhy5QqioqI6zYa0tLRAJBLZfEPFXJj+2ueffx4VFRXYuXMnW56flJTEBgMCgQBz587F77//jjfeeKPL71Ov1+PHH3/EwoUL2c1lxorG1dUVp0+fxvvvv4/U1FTU1NSgpKQE586dQ319PXQ6HbhcLmQyGaRSKaRSKUaPHo1vv/0W4eHheOKJJyCVSsHhcNj/CIJgAyiKomA0GtmNWZ1OB51OB4VCgYaGBigUCigUCjb4KSkpQWVlJfLy8uDm5oZJkyYhKSkJ/v7+cHFxAUVR2LVrF2bOnGnx8854Th8/fhyXL19GQkICXn75ZXh5eT1QGWCTyYTm5mbU1NTgxo0bKCoqgkqlQlBQEIYPH45FixbBycmpx/MHRVHIzs7Gli1bsHjxYiQnJ7Pnt6amhi01bm5uhrOzM2iahp+fH4qKiuzmXmaEsgICAlBWVtbt4Emn04GiKItkb9VqNQ4cOIA1a9ZY7bzk5eXByckJAQEBVnm/3qBUKs0WV9NqtXbhMGCP2MedNwBhAjaTydTuRvby8kJdXV23Fu1MtotR4utrGNGsS5cuISAgwOZBBZfLZRcczL+dnZ2hUCjQ3NwMHx8fnDhxAp6enqipqbHaop7pY9uyZQtmzpyJxMREHDhwAAaDwayeDQc9x9fXF0qlEsHBwcjIyIBUKmVttewVgUCAVatW4R//+Ae8vLzu6xHaV7S2tuLo0aN4/fXXrb4IdnZ2RmBgIDIyMhAZGYmoqChs3boVTU1N8PT0vOdr+Xw+li9fjn/84x+IioqCj48Pe/5IksTixYvx8ccf4+zZsx08d+0dmqZRVlYGHo8Hf39/0DSNU6dO4fHHH+/0c/T3MjeSJBEUFISXXnoJRUVF2L59O/744w/MnTsXiYmJ4HA4SEpKwv79+3Hjxg0MGjSow3mgaRpHjx6Fu7t7h54+JqOk1WoxduxY8Pl8REZGIiIigv09RVFQKpVs0NrU1ISGhgYMGTIEFRUVbLUEM567n9l8Ph9cLpf9TyAQQCQSQSKRwN3dHWFhYWyALRQK2XuN8T7Pzs7G7t270dzczNrnXL16FbNmzYJCoYCbm1uH+9Oca5r5jEVFRTh06BAqKysxatQovPPOO31Sbm0r7u7DZryVlUolFAoFGhsbUVJSgoqKCjQ1NQG4vbZKSEjAQw89BF9fX3aN1hu7KaPRiEOHDuHs2bN45ZVXOghMlZWVISgoCPn5+ZBIJNDpdDAYDKwYmb0EwgBQUFCA6OhoXLlypdPWjM7QarWgabrXvuYURWHPnj0YNWpUt3qTLQFN0zh48CCmTJli95uojIewufO/TqdzBMJdYD933gCDy+WyD6I7CQgIQFpaWreOwePxWJ9cawXCI0aMwLp16zBr1iybl+owC4y2tjbw+XyQJAk3Nzc0NjaiubkZ8fHxaGlpQVhYGCuWZK2HO9Oj2tTUBIlEAolEgvLycoSHhw+YBYY9w+fzwePx4OXlherqagQFBaG+vt6uA2Hgtur4Sy+9hH/+85+QyWSIiYmx6vVC0zSOHz+OhIQEeHl5We19Gfh8PoYPH47jx4/j6aefBp/Px7Bhw3D27FnMnj37vufCw8MDCxYswPfff4//+Z//YbUWmF7U559/Hv/6178QEBBg1/YXd8OIZD388MMgSRJyuRxarbZL25Lq6uo+9X22Bkyfd0REBF5//XXk5eVhz5492LVrFx555BEkJSXhsccew88//4yYmJh2uho0TaOyshInT57EX/7ylw4Bo0qlwu+//46XXnqp3XPszioCkiTh7u7Ozhl3B1SNjY34/fffUV5ejvnz5yMhIcGsRXJX1x6fz0dERATCw8MB3K4EkMvl2LBhA4KCgnDw4EFW90IgEEAgEMDNzQ2enp4Qi8WsTyuPx+tyPEajEfX19UhLS0NFRQXGjRuHadOmQSgU4ubNm93+DPaG0WhkW6GYTLxKpUJzczNUKhX0ej3a2trQ1tYGHo8HV1dXdlMiOTkZnp6e7TYYLCXq1NTUhO+//x5CoRBvvvlmpxsNOTk5SElJQXp6OgQCARoaGtgNFldXV7sKhKuqqjBu3DjI5fJuzzNarZZ1c+gpNE2jqKgIlZWVeOyxx6w2f9fW1qKurg6DBg2yyvv1ltraWgwfPtys12i12n7bNtTX2M+dN8Bggri7d2GkUikUCkW3g7aQkBAUFxdbTcDKx8cHwO0bzdYlIhwOBwKBgM2IEwQBqVQKkiTR1NTE9pX5+vrixo0bVh0bk2HIycnBmDFjMGzYMGRmZrKLGwd9C0mS8Pb2ZoU8jEYjKioqutVyYEsYa7Xnn38e69evx6uvvtous9nXKJVKpKen46233rJJkMhstm3atAkVFRUICQnB6NGj8cUXX2DGjBn33XxjvGazs7Nx8OBBzJ49u0PryTPPPINvv/0Wb775pl0J0NwLlUqFoqIiPPnkkwCA06dPIyUlpcsKk5qamgHT78UIX8XFxSE6OhpFRUX4448/sHv3bkybNg0CgQBZWVlITU1lr1m9Xo/Nmzdj4cKFHUoEKYrCb7/9htGjR5tV2XT333l4eGDVqlUoKirCL7/8gmPHjuGxxx5DQECARSop7hTR9PDwgE6nY69Zk8kEjUaD1tZWtLW1QalUoq6uDq2trVCr1ayY0Z0b7Xq9HhUVFcjMzIRIJEJSUhLi4+MxfPhwEASB8vLyXo/Z1jAl6ndm4n19fREXFwcXFxfw+XwIBAK2/7uvs3tGoxGXL1/Gb7/9hhkzZmDcuHGdBrQURaG6uhq+vr7Iz88HTdMQiURwcnJiPYTtZdOOUX92dnaGyWTqdhaxubkZAHqVEW5ra8POnTuxcOFCqyViaJrGyZMn8dBDD/Wbir7m5mazSqMZIThHRrhzHIFwH8HhcNjs5Z2LMbFYfE/7iLuJiorC9evXu12e0ltIksTw4cNx/vz5bnvH9eVYhEJhOwsliUQCkUiE6upqVtFQLBZ38Gy2BiNGjMCRI0cwevRoDBo0CGlpaR1K4R30HWFhYaiuroZEIoHBYEBhYSEmTZpk62HdFyYLtmDBAnz11Vd4/fXX2Y2evoTJOiYnJ9s0cx4WFgZXV1dkZmYiJCQEXl5ecHNzQ35+PuLi4u57HkiSxJNPPol//vOfiIyMbPcaRtX94YcfxrffftsvxLNomsaFCxcQHx8PZ2dnGAwGXL58uUvFZABoamrqoII8EOBwOIiKisLLL7+MiooK/PHHH8jLy0Nubi4iIyNZley0tDS4u7t3eg5u3ryJsrIyLFmypNfnhyRJRERE4I033sClS5fwzTffIDAwELNnz4afn59FAmKapnHjxg0EBASwiuhcLhdubm73XeyaTCbU19fjwoULuHTpEgQCAd555x0MHjzYKnPKgwpN05DL5fj555+h1+s7LYW+E4VCAaPRCDc3N5SWloKiKHh4eEAsFqOtrQ1SqdRuvqv6+no4OTlBp9OxmwvdobGxETwer8fzLdMOEhQUhNDQUKudD7VajaysLLz99tt28x3cD3P7fSmKgl6vt/tnoa14cFQSrAyTvWR6UhicnJxAkiTUanW3jhEaGoqKiop2olF9CUEQGD58OK5evQqDwWCV97zXWJycnNDa2sr+zN3dnbUO4XA48Pb2hlqthkajgclksur4IiMjUVtbC5VKBZlMBicnpwGx694fIAgCISEhqK+vh0QigVarhVwu7zdessx9lpKSgm+++QZ6vb7P37O5uRlnz57FjBkz+vy97oW7uztiYmJw+vRpGAwGcDgcTJw4EUeOHOnW6wmCgLOzM5555hls3rwZLS0tHX4/adIk+Pj4YNu2bVafF8yFsUkaP348CIJAfn4+pFJpl6XrFEXZfT98b2GskdasWYOPPvoIXl5eWLlyJX766SdcuXIFJ06cwBNPPNFh01Gj0eCnn37C0qVLLbboIwgCfD4fI0eOxLvvvovY2Fh88cUX2LBhA6qrq3s951AUhWPHjmHixIndWojTNI2GhgYcP34c//rXv/D5559Dr9fj+eefx5tvvokxY8YMqB5ge0OtVmPXrl345JNPMGzYMLz22mv3TRrU1tbCw8MDTU1NqKioQFtbG+urrlAo7KpypaamBj4+PigrKzPLNkqlUrHJC3NhPIMzMzMxa9Ysq2lXMEr94eHhZotP2Qqaps226zQYDDAajY6McBc4AuE+grGLaGpqavegZPpWGhoaunUcqVQKvV7fLhjsa2QyGWsPZGvuDoS9vLzQ2toKlUoF4HYpt1KphEAg6LDp0NcIBAL4+fmhpKQEHA4Hw4YNw/nz5606hgcZf39/KJVK+Pv7w2Qyoba21qr3SW8hSRLTp0+Hh4cHtm7d2qebXYwYSGpqKpt1shU8Hg9DhgxBaWkpysrKAAAJCQmoqalBY2Njt45BEATCw8Mxfvx4/Pjjjx3OHSOeVVtbi7S0NLveICkqKgKfz0dAQADbwz1hwoQuv6O2tja78x3tC5g+Xj8/P7z22mvw9vYGTdN44YUXoFQqkZeXxwr0ALcDyt27dyMxMZEVxbL0eIRCIcaPH48PPvgAISEh+Oyzz/DFF1+gqKgIFEWZfZ0xAYBarUZERESn3zmjNVJXV4djx47ho48+wieffILKykosXLgQH374IebPnw8/Pz9wuVxHANwHMKWlR48exbvvvgu1Wo133nkHY8eOBY/Hu+85z83NRWxsLEpKSsDn80FRFGvdVV9ff1+hQGuSn5+P6OhoVjG6u9dTa2srOBxOjwJhk8mEbdu2Yfbs2RaxX+ouer0eaWlpmD59utXes7fodDq2tL67GAwGUBTVTmfBwX9xBMJ9iEwm67CwY3oEuxsIM97D1iz95XK5GD58OM6dO2fzBeTdgbBYLAZBENBoNKBpmn2QeHh42CRwHzFiBOsXnZycjOvXr1ste/+gIxQK2b5QiqLQ2NjYITto73C5XCxZsgRNTU3Yt29fB3E9S8BkkLKysjBlyhSbL5QJgkBycjJEIhHOnj3LPtRHjBiB9PT0bs85TOaXpmkcO3as3esYT9dVq1YhLS0NN27csPlc1hk0TePIkSOYOHEiuFwumpubUV5efk/RFr1eD5Ik+00/W28hCALe3t4YPXo0Lly4gMWLF2Pt2rW4ePEi/va3v2H9+vW4ceMGbt68iZycHMybN69Pr3EmIJ4yZQo++OADDB8+HJs3b8ZHH32ErKwsdqHaXY4fP45Ro0axi1Qm8NVqtSgoKMD27dvx/vvv4z//+Q/q6urw2GOP4YMPPsBTTz2FyMhIR/Dbh9A0DaVSiYMHD+Ldd99FUVER/ud//gdPPfVUtzcUGQGoiIgI5ObmwtnZmb1GgoKC0NjYyJb82xqaplFRUQF/f3+UlpaapUOgVqvB5/PNDoRpmsbZs2fh4uJiNc9g5n0LCgrg6upq8zZAc1CpVODxeGYFtQaDwTFP3ANHINyHeHt7o7a2tsPP/fz8UF1d3a1jMP2E+fn5lh7ePd9z6NChuHbtms3LCsViMRv0ArezsDweDzRNQ6PRICAggFVQraystOrYmH7EoqIi6HQ6eHl5gcfjoaqqyqrjeFBhRGaYUlm1Wo26ujpbD8ts+Hw+Vq9ejaysLJw5c6ZPArbdu3fj4Ycftor6fHcIDQ2FTCbD9evXodPpAADjxo3D+fPn2X93Bx6Ph2eeeQZpaWkoKirqcO4kEglWr16NjRs3WqSM1dI0NTWhrKwMycnJoGkaWVlZiIuLu+diklHEfdCIj4/HpUuX8MgjjyAxMRFr167FX/7yFyQmJmLv3r1YuXIlaJpGdnY2mpqarLIhKRQK8dBDD+Gvf/0rHn30UZw6dQrvvfcedu3aBblcft8x6HQ6XL16FSkpKdBoNCgvL8eRI0fw+eef48MPP8TevXvh5uaGVatW4W9/+xsWL16MyMhIVijSgeWhaRoGgwHl5eXYunUrPvzwQzQ2NuLll1/GypUrzRY31Gq1qK+vR2BgIAoLC9nWOC6XCw8PD7S1tdlN72ZbWxsUCgW8vb2h0Wi6LXxF0zQr4GRu1pEp858/f75VrYsoisLBgwcxbdq0fuWlrVar4ezsbNY1yATCDjrHcWb6EFdXV6hUqg4K0QEBATh9+nS3jkEQBKKionD8+HFQFGW1G/bOntewsDCrvGdnSCQSVFRUsP9mJlk+nw+1Wg0XFxdoNBoEBwfbpCzZ2dkZbm5uqK6uRlhYGIYNG4aLFy92aXviwHIQBIGwsDAUFBSAy+VCr9ejsLAQgwcPtvXQzIIgCIjFYqxduxaffvopJBIJEhISLLbQra6uRkFBARYvXmw3i2eZTAaZTAa1Wo2ysjLExMTAw8MDfn5+yM7ORkpKSrePJZFIsHz5cnz//fd466232i3eCIJAcHAwnnjiCXz11VestYm9cObMGTY7bjQacfr0aTz99NP3fA1jJ2cv36U1aG1txY4dO7BgwQKkpaVh2bJlIAgCEokEI0eORFFREVatWoWEhARcuXIFu3fvhpOTE8LDw5GQkAB/f39IJJI+WwzyeDxW9bqpqQlnzpzBf/7zH4jFYowcORKJiYlwd3cHSZJsoNXS0oIzZ86gsrISGzduZG0So6OjMWPGDPj7+8PJyYm1mXLQtzBVRVevXsXZs2dhMpkwevRo/PWvf+1Vz7VCoYBIJAJJkigrKwNJknBxcYFAIICnp6ddBcLNzc3g8/nsHCMWi7v1OqPRiJaWFrPEtZjX/f7775g+fbpVfdFpmkZNTQ0UCgWio6P71f2lUqnM3tDW6/UP3DPDHByBcB8iEAjQ1tbWIQthroVSQEAAu7tsrXI4DoeDlJQUnDlzxqoKfncjkUiQnZ3N/pvJCAO3rWCYPjlXV1fU19db1UsYuN2LmJycjMuXL7OB8Ndff405c+Y8kFkba8JUS1y4cAFCoRAuLi4oLS21+jVgCZgS7+effx5ffPEF/vznP1ukXIuiKOzYsQMzZswwS1yjryEIApGRkZDL5Th16hRrezVjxgz8+uuvGDJkSLfvH4IgEBMTgxEjRuCnn37Cc8891y7gIQgCw4YNQ21tLb7++mu8/PLLdrHw1Ol0OHfuHF588UUQBMFmrAMDA+/5vTc3N9u8z9uaML2/MTExmDt3Lt5//31UVFQgMDAQAJCXl4ecnBz89a9/hVgsxtChQ2E0GlFXV4f8/Hykp6dDLpezJdahoaEICQmBTCaDu7t7hwxWT88rTdMgSRIeHh6YM2cOZs6cieLiYhw8eBDr1q2Dt7c3IiIi0NLSwvZTnjt3Ds899xyGDx8OPz8/8Hg8kCT5wHy3toJZkxmNRlRXV+PatWu4du0atFotYmNjsWzZMvj7+4PD4fT6uygsLERERARqa2vR0NDAeu3yeDw4OTnZVe+mXC6Hj48Pqqqq4O3t3e0MrV6vR3NzM8LDw7t9vmiaxqVLl0DTNIYNG2b1a/7AgQOYOHGi3Zz77sLM/+bABMIOOscRCPchQqGQbVK/c0KRSCRQq9UwGo3dWuwxTfGtra1Wu5iZPr6PP/4YBoPBZjeRk5MTtFot+28ul8uWwTY3NyMyMhLu7u4wGAxobW01W02vtzDn6csvv8S8efPg5eUFgiDswof5QcDX1xdtbW0gSRK+vr64deuWTa/X3sAoYS9duhSff/453nrrrV7bapSWlqKmpgarVq2yu8V1UlIS5HI5CgsL2eqO8PBwUBSF0tLSLsWDumLWrFn4z3/+g2PHjmHq1KntXksQBKZPn46GhgZs3boVy5Yts2mpGE3TyM/Ph0QiYUWgTp48iTFjxtx38alQKKyaPbElNE3j1q1buHXrFt5++22IRCLMmzcP27dvx4svvgi9Xo+NGzfimWeeYed9giDA4/Hg7+8PPz8/jB8/ni3drK6uRklJCU6fPo3Gxka0trayFnzOzs7w9vaGm5sbxGIxnJycIBQKwePxwOPx2gVFNE1Dr9dDr9ez4mVqtRotLS1oamqCSqVin0ccDgepqamQyWSgaZotj/Xy8oKfnx/GjBkDT09P9vj2dp/2d2iaZv9ra2tDTU0NCgoKcPPmTdYqaNCgQVi6dCnrEW2p74CmaeTm5iI5OZmtbKMoCkKhkF3HCIVCuwnG8vLyEBUVhbKyMgQHB3f7PDD3QnczyMz9eOjQIbzwwgtWL01uampCfn6+XVVJdZeamhr4+vqa9Rq1Wt3t7+ZBxBEI9yECgQB8Ph9KpbKdGALj76dSqbplgcHn8+Hn54fS0lKrln3KZDJIpVIUFhYiLi7Oau97J0xWnYEph6NpGpWVlUhJSYGPjw+amprg5OQEhUJh9cyXVCoFSZJoaGiAj4+P3fgwPwg4OzuDz+fDYDDA29sb58+fh1ar7ZeBMHD7+h48eDBaWlrw+eef47XXXutxX6/RaMSOHTswb948uzsfTDb/l19+QUBAALKzs/HQQw+BJElMnToVhw8fNiu7wAQ/zzzzDP71r38hJCSkQ8kbh8PBokWL8OWXX+LAgQNWtem4G4qicPToUVa8rLW1FTdu3MCcOXPu+5mZTYOBPrfQNA2VSoXNmzdj5cqVEIlEbHb/2LFjyMnJwfXr15GYmIioqKhOz8ed/tLu7u5wd3dHQkICe/y2tjbWfk+tVqO+vh5KpRJ1dXVobW2FXq9nrUfurOxixMqYZ7xQKIRYLIanpyeioqIgFovZ/4RCYbvrbMmSJWhsbMRnn30Gf39/rF+/Hm1tbXB1dUVISAj8/f0RGBjIujdwuVxwOBxHprgTmACXoij2P5PJhLa2NtTX16O+vh51dXUoLS1l+8alUikiIiIwc+ZM+Pj4wNXVtc/mAabXeOHChdi+fTsEAgEMBgNEIhG8vLygVCrh4uJiFz2qFEWhrKwMQ4cOxZ49e8yy2dPr9TCZTN1WMqYoCr///jsmTpwId3d3q17XNE0jLS0NKSkp/TI4VCgUiIqKMus1zc3NA95loDc4AuE+hMPhwNnZGc3Nze0CYYIg4OLigpaWlm4FwsyisbCwEElJSVabNAiCwOjRo3H69GnExsba5CEsEAg6iOdIpVKo1WpWeTsgIACVlZXw8PBAfX09/P39rTpGHo+HQYMG4fLly5g5cyZGjBiBL7/8Eo888ojdBSADDYFAAG9vbxQVFcHHxwd1dXVoaWnpN56AnUEQBMaOHYvm5mZ8++23WLt2rdn+f0wmQqPRIDk52S4X0M7OznByckJcXBxOnTqF1NRUcDgcJCUlYc+ePaivr4e3t7dZx5RIJFixYgW+++47vPHGGx3UWAUCAZ577jl8+umn8PDwwMiRI21ybhoaGlBfX89uMGZnZyM0NLRb/ctqtXpAewgzUBSFLVu2YNSoUQgLC2O/Jy6Xi4ULF+Kzzz6DRCLB3/72tx59h4z6s1AohIeHh6WH3yVMEK3X6/G3v/0NIpEIGo0GCoUCJSUlKCsrw7lz59DS0sIG3yKRCC4uLmyWmgmQ7SGAshY0TcNkMsFoNLL/azAYoNFooNFo2q0TOBwO3N3d4eHhAS8vL8yYMQMeHh7sxoS17nlG6FMsFqOiogJ8Pp8dZ2hoKJRKpd08q3Q6HZqamuDr64vGxkaz7gm9Xg+j0ditTVuapnHhwgXo9XqkpqZaff5Vq9W4cOEC3nrrLbt8Lt6PnvQIt7S02JU2hr3hCIT7ECZ72dzc3OF37u7uUCgUCA0N7daxoqKi8Msvv1i9/zEpKQl79+6FRqOxqr8bg0AggF6vb/e5fXx8UFBQwPo2BgUF4cKFC0hISEBRUZHVxZKYLMWPP/6IGTNmQCaTgcfjQS6XIygoyKpjedBgyolLSkpAkiS4XC6Kior6/XknSRKzZs3Czz//jC1btuCZZ54xq+fcYDBgx44dWLhwod2qRRIEgcTERCiVSmg0GjQ0NMDb2xtCoRBjxozBkSNHsGTJErPmO2bTcNq0aVi/fj1effXVDmWHLi4u+NOf/oSPP/4YUqkUsbGxlv5o94SmaZw4cQIPPfQQ+Hw+6x386KOPdiuwUavVbH/sQIWmaZw7dw5KpRLTpk3rUObu5+eH2tpajB8/3uxNIlvD9EbGxMSw6q9ubm5wc3NDSEgIm+U0Go1s0Me0AjHl1kwgaG8q6H0Nh8NhM+RcLhc8Hg/Ozs5wdXWFSCRiM+d3ZtFtSWFhIYKCgqDT6dDQ0AC9Xs+WwPv5+fWo37Ov0Gg04PP50Gq1oCjKrHFptVoYDIZu2UA1Njbi4MGDePHFF22io5KZmYno6Oh+uZnIVMmYGwhrNBp4e3v3y8DfGtjnCmkA0ZUwVnBwMMrKyjBkyJBuHUcmk6G5uRkmk8mqk7uzszN8fX1RUFCA5ORkq70vA7OIbWtrYxc8np6eMBgM0Ol0MJlMcHV1hVKpRFBQENLS0mwiluTr6wuDwYCGhgZ4enqyPsz3E75x0HtiYmKwb98+KBQKxMfH49atWxg/fny/P+9cLhdPPPEEvvnmG+zatQsLFizo1r3P2PCIxWLExMTY7XkgCAKDBg3Czp07kZycjIyMDDz66KNsJcqHH36IlpYWsxeKBEFg/PjxKC4uxs6dO/H444+3O28EQcDLywurV6/Gl19+iddeew1+fn5WO09arRaXL1/Gm2++CYIgIJfLodFouqXOT9M0a58xUKFpGrW1tdi1axfeeOONDlU1NE3jjz/+wLhx43D58mU88sgj/arE0Wg0Ij09HStWrOj090yfMJ/PZz+7i4uL2X2BDmwLTdPIyclBXFwc6uvrWWVlJycntoc9Pz/f6hVsXVFWVoaAgAA0NDSwZfndpampCTRN33euNhqN+OmnnzBr1iybeCdrtVocP34ca9eutfp7WwJGk8Dc7K5Go+lXc6S1eXDqamyEt7c35HJ5u58x6pWdeQx3BVNGaM5rLMXYsWORkZEBiqKs/t4CgQAkSbYTzHJ2dgaHw2GDYWdnZxgMBnh4eKCurg4Gg8Hq4+TxeIiPj8eVK1fa+TBbw8vyQcfb2xskSaKxsZENhG3tf20peDwenn32WeTm5uLw4cPdygC1tbVh9+7dWLhwoc0zIvcjICAAjY2NSE5OxsWLF9l718XFBSkpKTh27FiPsl4kSeLJJ59EXl4eq0x6J4z11lNPPYUvvvgCjY2NVsmu0TTNKsxLpVLQNI309HSkpqZ2q42C8U+3Fz/ovkCv1+PHH3/Eo48+Ck9Pz3a/o2kaeXl5uHnzJp577jkkJyfj4MGD/SYzStM0SkpK2EDIXjepHPQeiqJQWFiIqKgoFBQUwNXVFUajkS3Hl0qlbNBpa2iaRlFREcLDw1FaWmq2U4hCoQBBEPfcoKNpGqdPn4ZIJLKJSjRN07h27Rq8vLzg6+vbL+89Zh1sThUM88wYyJunvcW+V0kDAE9PT7aXtbOfd/cBzuFwEBwcjJKSEqs+9AmCQFxcHCoqKqBSqaz2vgwkSUIoFHYIhBlBJK1Wy1rnML03arXa6uMkCAIjRozAhQsXQNM03N3d4ezsjPLy8n6zSOuvSCQSeHp6Qi6XIyYmBiUlJQNmA4LxGH7xxReRkZGBs2fP3vN6YtSHw8LC+kU1AtPjrdVq4e3tjRs3bgC4/bknTJiA8+fP9/h+FgqFWLVqFbZv347KyspOg+Hk5GTMmDEDX375JdRqdZ/fq3eKZJEkCZ1Oh6ysLDz00EPd+q5MJhNaW1sHbCBMURQOHz4MqVTaaf+gRqPBpk2b8PTTT0MsFmPmzJnIzMxEfX29jUZsPkeOHMHEiRPttmXBgWXQaDQwGAxwc3NDQUEBeDweuFwu68/L5XLtprqDoigUFxezWjQRERFmvV6lUoHD4XQpVMr49qanp+Pxxx+3yXPJYDDg4MGDeOSRR+x+g7grmPWuOeePCYQdGeGu6Z9XQz/C2dm50wDSw8MDKpWqnSLy/YiLi0NOTo4lh9cthEIhoqKicOPGDZsEdSKRCK2trey/xWIxTCYTq7bKlDrW19dDIpGgqanJ6mMEbpe7M72OXC4XqampyMjIsMlYHiRIkkRQUBCUSiV8fHxY4ZmBhEQiwYsvvog9e/bg2rVrXd6HKpUKR48exZw5c/rFw54pj87OzsakSZNw9OhRtvLE3d0diYmJSE9P79G8QxAEfHx8sGjRIqxbtw4qlarTYHjMmDEYOnQovv76a7Pm455QVFTEbmoCwI0bN+Dj49PtrBBFUTAYDHZjt2JJGGuhzMxMLF68uIONFEVR+O2335CcnIzIyEgAt/3jp06dit9//71fVIE0NzejvLwcgwYNsvVQHPQhTIbV398fJEmipqYGANiqDz8/P3A4HLsJUIxGI5RKJSQSCeRyOfz8/Mx6vUqlAkmSXX4WvV6Pbdu2Yd68eXB1dbVJNjg3NxcikQghISFWfW9LotPpzNZEMJlM0Gq1A3bz1BLY/0qpn+Ps7AyNRtPh54ylwp2ZzvsRGBiIiooKqwejzGLRVuXRd3sJM96OAoGAzbaHhISgrKwMYWFhKCoqsvoYgds9nXFxcbh+/TqA20JjOTk5NinVftCIi4tDa2sray1QUFBg6yFZHC8vL6xduxZbtmxBYWFhh3mApmns378fI0aMgJeXl41GaR4EQSAhIQG3bt1CZGQklEolu2gkCAIzZsxAenp6j7PCBEEgKSkJI0eOxHfffddppQBJkpg+fTr8/f3xww8/9Nn9StM0Dh06hMmTJ4PL5cJkMuHYsWOshVJ3jwHA7jP9PUGj0eCHH37A0qVLOyzaaJrG1atXUVZWhtmzZ7ObPARBYNy4caitrUVeXp4tht1taJpGRkYGBg8ebBfBj4O+5fr160hISIBSqQRBEKivr4ezszOMRiNCQ0NhMBhgMBjs4lpoaWlhlcy7K3rFQNM0+/rOPgtN0zh69Ci8vLyQkJBgk7mLoijs3bsXs2bNuq9Puz3TE/Vnxk7M2rai/QlHINzHODs7szsyd8JYN9yZ6bwfjEhUS0uLpYd5X4KDg9HS0mKTTJuTk1O788TYTzk7O7OL5qCgIJSVlSEkJASlpaU2yVwTBIGRI0ciMzMTJpOJtW+w9wXaQIBRX6+srER0dDSKiooGXEk6QRAIDAzEqlWr8M0336CqqqrdZ6yrq8PFixcxY8aMfhUoSaVSGAwGtLa2YtSoUe0ywDKZDElJSTh58mSPv0/Gm1gsFmPnzp2dbuZxuVw8/vjjoGkav/76a59kFxsaGlBeXs6KDtbW1kKpVCI6Orrbx2DG3p++3+5gMpmwefNmpKamdvB/pmkazc3N2LZtG5599tkO2XAej4dFixbh119/7fOMfm8wGAzIyMgYEEJ+Du5Pfn4+oqOjUV5eDolEgqKiIjg7O4OiKAQGBkKtVoMkSZurnjPZ6+DgYKhUKkgkErOqiZj7UywWdwi2mCqPrKwsPProozYJQpnPZzAYOswt/Y3a2lqzLQWNRiNIkuwXFWK2wnFm+hiBQAA+n9+hPJop5zVH/IrH48HT05MN/qyJQCDAoEGD2B5Ya8Iob9+Ji4sLhEIhmxH29PREU1MTAgMDUV1dbbMe0ZCQECiVSlY8YsyYMTh9+vSAC8rsDR8fH9ZWa/To0bhy5cqAPOcEQSAyMhJLlizB559/jsbGRgC3A6Rdu3Zh6tSpdtFzZg4CgQDh4eHIycnBqFGjkJ2dzVbRMFnh06dP90qjgMvl4umnn0Zubi7OnTvX6bXB4/GwYsUKVFZWYv/+/RYNhmmaxqlTp5CSkgKhUMiKZI0aNcqsXlFGEX8gLWpomsbZs2fR3Nzc6SaOyWTCzz//jAkTJiAgIKDD7wmCQHR0NLy8vJCRkWG39/2tW7cglUrh4+Nj66E46GOamppgNBrh4eGB3Nxc+Pr6orW1FUKhEHw+H0FBQVCpVHB2draLe7mgoACRkZEoLi7utqUng9FohEKhgFgs7rBJpdFosHXrVixZssRmmW+aprF7927MnDnTJnZNlqSpqQnu7u5mBfOM00x/3gDoa2x/Bw5wmOxlZ4u4gIAAVFZWmnW8mJgY5ObmWmp43YYgCDz00EPIzMy0enm0u7t7h75fLy8v0DTNCo5JpVKYTCZQFMVKzNsCLpeL+Ph4ZGdng6ZpJCQkoLS01CYCXg8SXC4XYWFhKCgoYIWzBopg1t0wIk9z5szBv//9bygUCpSUlKC8vBzjxo3rdw88xof70qVLcHFxQXh4OLKystiARiqVYvDgwb3KCgO3Wyr+9Kc/4Y8//kB+fn6nxxIIBFi7di2uXbuGtLQ0i811ra2tuHDhAiZMmMBqG1y9erXbIlkMAy0jTNM0qqqqsHfvXjz77LMdFqo0TeP8+fNQqVSYOHFil5+bJEksXLgQhw8ftknF1P2gKApHjhxhRdIcDGwYL3uSJFFUVASZTMauT5ycnODs7Ay1Wm0XfZuMknloaCiKi4sRFhZmdqDV2toKkUjU7nUmkwm//vorRo4caXZwbUlKS0vR0tKCwYMH22wMlqIndoJMIOyYd7rGcWasAONzeyeMkItcLjdrcceo+tli19vX1xckSaKqqsqq79uZ4Jivry9MJhMUCgUMBgNIkoSbmxu7y9rc3GzVMTIw5dEXLlwARVEQi8UIDg62icjZg0ZSUhIaGhogEokgk8ls1ituDZiNqXHjxuGzzz7Dpk2bsGDBgn4rohQSEoKqqioYDAZMmzYNaWlpbK8uQRCYNm0aMjIyehXkEAQBDw8PrFixAj/88APq6+s7Fc8Si8V44YUXcObMGZw6darXcy1N07hy5QqCg4Mhk8lA0zRu3LiBgIAAsxc1FEWxPrMDAa1Wix9++AGPP/44PD09O5RE19XVYffu3Vi2bNl97aU8PT0xevRo7Ny50+6ywrW1tWhoaEBCQoKth+LACly9ehXJycnQ6XSseKNIJAKHw4FUKmWr2Tw8PGw9VOj1elaJvqqqymwxKaPRCJPJBKFQyP6M2cBSq9WYNGmSzeYriqLYbHB37OnsGaYE3dxnhl6vB4fDGTDPjL7AEQhbAV9f3w5ewsBt5UC5XG5W1iEwMBANDQ1miWxZCi6Xi5SUFKuXn90tlgXczhJptVqYTCbo9XoAtzPsNTU1CA4ORnFxsc0WQ4GBgWhpaWEX7ePGjcOpU6dsIjT2oMDYfDU0NKChoQF+fn7Iy8uzuwWxJSFJEpMmTYK7uzuys7PNtrywJ9zc3CCVSlFWVgY/Pz+4uroiNze3XVZ45MiR2LdvX6++U4IgEBERgblz5+Krr77qVKOBIAi4ubnhxRdfxJEjR5CZmdmr9zQajTh69CimTZsG4PbiLC0trUcLxIEklkVRFHbu3ImwsDAkJyd3+ExGoxEbNmzAnDlz4O3tfd/PTBAEJk2ahIKCApSUlPTl0M2CKYN/6KGH+n1ppoP7YzAYUFJSgoiICMjlcri7u7MZV4VCgbCwMPB4PNTU1MDX19fWw0VVVRWkUimA20FTTzKORqMRAoEABEGApmnU1tbi4MGDeOqpp2wqTlVeXo66ujoMGzbMZmOwFEajEWq1mv2uuotKpYKLi8uAeGb0FY5A2Ap4e3t32gsskUjQ2trKBnLdQSQSQSAQ2CTjSRAEhg8fjmvXrpk15t5yt1gWcLtcWqlUgsPhsGMJCwtDcXExwsPDUVhYaLXx3Q2fz0d8fDyuXLkCAIiKikJTU5PNbJ0eFAIDA+Hr68v2CR89etTWQ+pz9Ho9qqurMXbsWPzwww/Q6/X9MvgnCAKDBw/GlStXWBXnAwcOtCsFnjRpErKzs83SVejqvVJSUjBkyBCsW7eu07mMIAi4u7vj5Zdfxs6dO9uVapsDI9TC5XIRFBQEAJDL5WhtbTW7BBG4vRgaCLv7NE0jKysLRUVFmD9/fofFMqOwzWyAdPfzikQiLFy4ED/99JPdqPVrNBpcvnwZY8eOtfVQHFiB+vp6cDgcyGQy5OTkICIiArdu3YKHhweam5sREhICgiDQ1NRkdlDTF5SUlCAkJARNTU1wc3Mz29+aaUVj1Iz1ej22bNmC+fPnQyqV2jQb/Mcff2DGjBkDYgNKr9dDr9eb3Wvd0tLiCITvgyMQtgISiaTTwJXH44EkSbMe2ARBICwszGY73jKZDDKZDPn5+VZ7T7FYjNbW1nYLUalUira2NgiFQjQ1NYEgCPj7+6OmpgahoaEoLy+3WQb2TvVoiqLA4/EwaNAgXL58uV8GKf0FPp+PuLg43Lx5E0FBQSgtLe3QkjCQoGkaJ06cQHh4ONauXQtXV1f8+OOP/bY3OjExETdv3gRFUYiIiEBbW1s7uzhnZ2dMmzYN27dv7/V9RJIkZs6cCVdXV/z222+dnjNG0PDll1/GL7/80iMfdSagmzZtGrvAPHbsGMaMGdOjUj29Xg8+n9/vFzUNDQ345ZdfsGLFig6quczmwenTp7FkyRKzMkqMXZZIJLKJsOPdMLZPoaGhcHNz6/ffm4P7c+vWLcTGxrL/PzQ0FPX19WyfcFhYGGs5ZG72tS9gxltYWIjw8HCzr1GlUgmj0QhPT0/QNI0//vgD/v7+GDRokE2v9+rqalRVVWHEiBED4r4zGAzgcDhm9/oyvegD4Rz0FY5A2AowgfDdD2UOhwMXFxezM4UxMTG4deuWzSyCxo8f387ipK8Ri8UwGAztMjdCoRAcDgeurq6siraPjw9aWlrA5XKh0+msmrW+m4CAAGi1WjZIHz16NDIzM/ttkNIfIEkSQ4YMQWFhIWQyGdra2gZ0n3BLSwuOHTuGefPmgc/nY8mSJaBpGlu3brWbbJg5+Pr6Qq/Xo7GxEXw+H5MnT8aBAwfY3xMEgVGjRkEul1uk4oPL5WLJkiWoqanBsWPHutw48/PzY/2bzZl3mR7Xuro6tjdUo9Hgxo0bPV6c6fV68Hi8fr2oaWtrw3fffYe5c+fC39+/w+81Gg02bdqEp59+ukdiQhwOB4sXL8bevXttLpxlMpmQlpbmEMl6QKAoClevXsXgwYNhMBjQ1NQEJycntLS0gKIo8Pl8+Pj4wGQyQa1W2zwQpigKcrkcvr6+KCoqQkREhNlzS3NzM4xGIyQSCa5du4bCwkLMnTvXptc74xs8bdq0fqubcTdtbW1s8swcGN0cB13jmJmtgEQigVar7aBkTJIk/Pz8zBKfYuxTysrKbBZUJSYmory83Grl2SKRCBRFdTh/IpEIrq6uqKurA3A7I8jj8VgPX2uLet0Jn8/HoEGDcPHiRdA0zVpmdNYr7sAyMGrKxcXF4HK5CA8Px5kzZ2yeFeoLaJrGnj17MHr0aFZwhc/nY/ny5VAqlfj111/73aYLh8NBZGQkq4qfnJyMioqKdnZxAoEACxYswLZt2yyy0SUQCLBy5UqcPXsWly5d6vRaIQgCQUFBeP7557Fx40azguHDhw9j1KhRrJDMhQsXEBkZ2eMFMBMI91cY8RofH59OFbMpisL27duRmJiI2NjYHgf8vr6+GDlyJHbv3m1TbYaysjIAQHBwsM3G4MB6tLa2ora2FmFhYaiuroabmxuampogEAhAURRcXFzg6uoKnU4Hg8Fgc9VohUIBiqLg6uqKqqoqtn3DHJiqK61Wi+3bt2PZsmUd/IStTXV1NSoqKpCSktKvNw3vRKFQQCKRmP15NBqNIxC+D45A2AoIhUIQBNFB8IlRjq6pqTFrse7q6gqj0dip0Is1EAqFiImJwbVr16wSZBAEAYFAAJ1O1+5nrq6uEIlEqK2tBU3TIEkSHh4eaGxsREhICEpKSmwWBDF9iOfPnwdN0+ByuUhNTbVrn8uBQFBQEMRiMaqrqzF06FAcP37cZlZafQVN06ioqMCNGzcwderUdg9GPp+PlStXora2Fjt37oTJZOpX19vw4cPZgFQoFGLy5Mn4448/2n2GQYMGwcXFpUs/YHNg5pE//elP+P3337sUWCMIAqGhoVi9ejV++OGHbgXDarUa2dnZGDVqFAiCgNFoxPHjxzFlypQeL87a2tr6bWk0o56dk5ODRYsWdfgMNE3j8uXLKC8vx+zZs3uVUSIIAlOnTkVhYaHNXBZomsbhw4fx8MMPm9136aB/UlVVBU9PTwgEAuTl5SEyMhKFhYWIj49HVVUVIiMj4eTkBJ1OBx6PZ1MhKQCoqamBt7c3jEYjjEZjj7x+lUolTCYT9u3bh3nz5sHb27sPRtp9aJrGrl27MG3atHZK1v2durq6Dsr694OmaajVakcgfB8cgbCVEAqF7QI5hoCAAFRVVZn1oOZyufD19UVFRYUlh2gW48aNw5kzZ2AymazyfgKBoENA4+fnB4qiUFdXx+76R0REoKCggC0ftyX+/v6gKAo1NTWsV6q1hcYeNJycnBATE4P8/HwkJiZCLpejurra1sOyKCaTCb/99hvmzZvXob+SIAgIhUI8//zzKC4uxt69e/tNIMxUu8jlcqjVatYiqqSkpF1WmCAILFq0CPv27bNIDzhBEPD29sbzzz+P7777rsv5mCAIhISEYM2aNfj+++/vGQzTNI2MjAwkJibCzc0NwG1vUT6f36OsC4PBYOiXGWGmTPyXX37BypUr2c3hO2lsbMSvv/6KFStWWKScUSgUYtGiRfj5559tMuc2NzejuLi4U0VsBwMPRgCO+b6vX7+O+Ph45OXlsU4WTA+uVqu1iyAtJycHsbGxqKqqgoeHh9m6BYylj1KpxNixYzF06FCbX+uVlZUDqjeYoampCe7u7mZ/JkY12kHXOAJhK8B4U6rV6g6/8/LyQkNDg1nlWyRJIjo6up29iDVhSgV1Oh3q6+ut8p53B8IEQcDT0xMqlQp6vR4mk4nN2pSWlrJK3bYMArhcLoYOHYrz588DuC3w5ePjg5ycnH4TnPQ3OBwOkpOTUVBQgODgYPB4PLsQzbEUNE0jOzsbbW1tGD58eKcPRWa+WbNmDXJyctqpL9s7AoEAvr6+KC0tZf89ZcqUDgrS3t7eGDlyJP744w+LfDZGhHDZsmX46quv0NjYeM/M8Nq1a/Hjjz/i5s2bnf6dTqfDyZMnMW3aNBAEAYqicPToUUyePLlXizMmEO5PCzyaptHW1oYNGzZg3rx58PPz6zB+vV6PDRs24JFHHun09z2BIAjExMTAz88PaWlpVp8DTp06hSFDhvQoy+ag/2EwGJCTk4NBgwZBr9ejvr4enp6eqKqqgr+/PzQaDSIjIwGAFcqy5X3MiNJFRESguLgYoaGhZldhMNVJLS0tmDFjhs3nJZqmsWPHDsyYMaPDJnF/hqZpNhA2B4qioFKp2M1YB53jCIStRFcWSkKhEHq93uzFHJP1stUCl/EUtlYPppubWwfhEw8PD7Ysh+mHDAwMRG1tLcRiMSiKsrlYSkpKCrKysmAwGECSJMaPH48TJ07YdEwDndTUVGRlZcHDwwMxMTHIzMzsl+JRncH0YS1atOi+5ZYuLi5Yu3YtLl++jKNHj/aLYJipnGB66xkF9uLi4nbzJ0EQmDJlCm7evGmxFgiCIJCQkIBZs2bhq6++ume2mckMb9mypVM16StXrsDPz48tE2xqakJ5eXmvs4P9MSNM0zS2b9+OgICATnv2KIrCwYMH4ebmhtGjR1t0Mc3hcLBgwQKcOHHCapu2wO0S9rNnz2LChAk2Dw4cWAdGGFMqlaKyshJubm4QCARsttVkMrWzUGN0Q2yFRqNBc3Mz/P39kZ+fj6ioKLNeT9M05HI5Tp48ifj4eLsItkpKSlBbW4uUlBRbD8Wi0DSNxsZGVg+kuzDaOvZQfWDPOAJhK+Hp6cmKOt2JUCgEj8frNFt8L2QyGVpaWmy2wCcIAqmpqbh8+bJVys48PDzQ0NDQ7meenp5Qq9VwcnJilbeZkjuTyQQvLy+bCmYBtzdABAIBK5oSHR2Nuro6h6dwH8I8LHQ6HYKDg9HY2Njh2umP0DSNY8eOITw8nPWivB9ubm54+eWXcfbs2XsqI9sLTDBaUFDAzitCoRATJ07skNkWi8V4/PHHsWnTJovNQUzgPXLkSHzzzTfQaDRd/l1wcDBWr16NLVu2IDs7mw2G9Xo9Dh8+jFmzZgH4b5n0sGHDel3yazAY+lW/KU3TuHDhAoqKivDYY4916hecn5+PzMxMs62SuotUKsWsWbPw008/Wa2V58aNG/Dw8LB5sOPAOjA2WQkJCeByubh58ybi4uLQ2NgIkUiE5uZmcDgceHl5AbjdBiCTyWy6SdLU1AQXFxdwuVzU1taafa1qtVqsW7cOIpEIbm5uNu93NplM2LFjB+bOnTtglKIZTCYTWlpazM4I0zTNatQ46BpHIGwFCIKATCZDU1NTh8wBl8uFu7u72WrCzORzZ++ctZFKpfDw8EB+fn6fZ4U7ywi7ublBp9NBIpGw2SIul8sGwLGxsTbvE2YsX5jMuVAoRFJS0oAq17U3JBIJpFIp8vLyEB8fD6FQOCA8nBsbG5Geno558+aZVcLm6uqKV155BRkZGThx4oTdB8MuLi5wcnJi50QmOC0oKIBcLme/R4IgkJiYCD8/Pxw6dMhi3y9Jkpg4cSIiIyPx/fffQ6/Xd1kmHRwcjBdeeAE//fQTK/JVUFAAPp/PblbodDqcO3fOItnB/pQRZsomt2/fjtWrV3fqF6xUKrFx40asWLGizwRdmDm4tbUVWVlZfT4PmEwmHD58GNOnT+/T93FgPzBCb0OHDgUA3Lx5E/Hx8cjPz0dMTAwqKioQExMDV1fXHpe5Wpr8/HxERkZCqVSCIAizMrpGoxFbt27FoEGDEBQUBD6fb1O7JGbeVSqVGDJkiM3G0VdQFAWTyWR2DzdFUaAoyuabFPaOIxC2EkwgfDdMv9udC7zuwOFwEBYWhoKCApst8DkcDsaPH4/jx4/36fsQBAEXFxeoVKp2P+dyuSBJkt1IYJSjQ0JCUFxcjMjISJueH+D22IcOHYpbt25Bq9WCIAiMHTsWZ8+e7Xf2Nv0FkiRZsbSIiAi4u7vj0qVLVssG9QUUReHXX3/F5MmTIZVKzXotQRCQSCR4+eWXcfLkSZw8edKug2EOh4OkpKR2QYtIJMKMGTOwY8eOdvczh8PBokWLcOrUKVRWVlp0DHPmzIGrqys2b97c5b1KEAQCAwPx6quvYseOHTh9+jT279+PmTNngiRJ0DSNa9euISAgADKZrNfj6k+BsEajwYYNG/Dkk0/C09Ozw+9NJhO2bNmCMWPGsCJCfQWHw8HSpUuxY8cOs6uvzKW6uhpqtRoxMTGOsugHBLVaDZVKBV9fX6jVaigUCgQFBaG0tBRBQUHIzc1FXFwcgNtBm0KhsMh80FOYSozo6GiUl5fD19e32/MKTdNIS0uDXq/H1KlTYTAYbB4IG41G7Ny5E/Pnzx+Q2U+TyQSKosz+bBRFgaZpRyB8HxyBsJW4VylzQEBAjxZx8fHxyMnJscTwekxMTAyqq6v73FOYCYTvXASTJAk+nw8vL692CtoREREoKiqCn58fWlpauixvtBYuLi7w9vZGYWEhgNsel0KhECUlJTYd10BmxIgROHbsGIKCgmA0GmEwGDrt0e8v5Ofno7q6uldZRXd3d7z88ss4ceIE0tPT7TYYZvygr1692k4ga8SIEairq+tw37i6uuKxxx7D5s2bLWqVxeVysXjxYphMJmzbtu2ebSje3t7485//jF27diEnJwfR0dFsi8aRI0cwdepUiywUmUWnvcNkjJKTk5GUlNSpVdKJEydgMBh6LSDWHQiCQEBAAIYPH96n3sI0TeP48eMYN26cY/H5gEDTNK5fv46IiAiIRCK2J5jH46GwsJBVZWYCYYPBAJVKZfaGpiXR6/WoqqpCaGgo8vLyEB0d3a3X0TSNmzdvIjMzE8uWLWOfrc7Ozjbb9KFpGrdu3QJFUYiPjx+Qm0+tra0QCARmB8JarRZ8Pt8xF90HRyBsJUQiUTtRpzvx9/fvkcWLn58f5HK5TRe0Tk5OSExMZJWR+wpXV1eo1eoO2SBPT0+YTKZ2/de+vr6or68Hj8eDm5tbp73Z1oQgCIwZMwYZGRmgKAoEQWDChAk4ceJEvy/XtVf8/PzQ2NgIlUoFsViMqKgoi/jO2oK2tjb88ssveOKJJ3rd+ySTyfDKK68gLS3NroNhb29vmEymdr3dQqEQ8+bNw6+//tpuHmUEtiQSCQ4fPmzR75jP52PZsmVQKpXYsWPHPTPDHh4eCA4OBkmSOHToEIxGI0pLS0HTNEJDQy0yHsZH2J5hgkGtVstmxu+mpKQER48exdNPP221z0MQBGbMmIGCgoI+a+dRqVS4ceMGRo4cOSAX5A465+zZs0hNTQUAZGVlYciQIaAoCkVFRfDw8IBKpUJoaCjrJ07TtE0rOzQaDQiCgJOTE4qKihAWFnbf19A0jfr6evzyyy9Yvnw5xGIxm9yRyWQ2ywgbDIYBnQ0GgIaGBkgkErM/n1KphFgsdgTC98ERCFsJkiRBkmSnWQVXV9ce+WFKJBLweDybBnpMqe+ZM2f6tNTX1dUVra2tHd7Dx8cHKpUKGo2GXdg4OTnBZDJBq9UiOjoaeXl5fTau7kAQBGJjY1FWVsY+gAYPHozi4mKbq1oPVJhSzIKCAoSGhsLFxaVdhrG/wAgtSaVSxMfHW+SY7u7uePXVV5GWlma3PcM8Hg/x8fG4cuVKu4CFyS7e/XOSJLFkyRJkZGSgqKjI4sHws88+i+rqauzdu7fL81VfX4+amhr885//RFFREbZt24Z9+/Zh0qRJFlmgMTZE9qwAStM0cnNzcfz4cTzzzDOdLvbVajU2bNiApUuXWj0rJhQKsXjxYvz000/Q6XQWPTZN07h48SJiYmIcvp0PECqVCvX19QgLC4PRaEReXh4SEhLQ1NQEqVTKWjwGBAQAAOsgYcvgpKSkBIGBgTAajWhubmbV7e+FTqfDhg0bMHfuXAQEBIAgCCiVShiNRpspRjP3nKurKyIjIwfs5hNzLZn7+ZRKJVxcXAbsebEUjkDYSnA4HAgEAmi12g6/c3FxgcFgMPvBfGc/rC0JCAgAl8tlvT/7AqFQCKPR2CET5O3tzfZ8Mf8rEAjg5eWFyspKxMTEIC8vz+aZQCcnJ0RHR+Pq1augaRoikQjx8fEDQsTJHuFyuRg0aBCOHz+OmJgYVr2TUe/uDzC9ZAcPHsSiRYss+jCTSqX485//jPT0dKSlpdldMMyUQl+4cKHdz5me4J07d7abSwmCgKurK5YuXYrvv/8era2tFruvCIKAQCDAqlWrUFBQgH379nU4XzRN48CBAxg7diw8PT3xwgsvoLGxEfv370dMTIxFxgHcLnWz10CYsfj4/vvv8dxzz8HNza3DNWs0GrFlyxaMGDHCJmWMBEEgKioKUVFR2Ldvn0XnXqPRiOPHj1ul1NuB/ZCTk4PQ0FCIRCI2Q+rh4YFbt26xPsJRUVGsGByTpbNVBpUpJY6JiUF9fT2cnZ3v63VtMpnw888/Izo6GkOGDGGvbyaB4+rqapNrXqfTYc+ePZg/f/6AzXoy64CeiKupVCpHINwNHIGwlSBJEh4eHl1aKInFYjQ2Npp1TEY19fr165YaZo+wRqkvs4N6d0adKYF1dXVlyygJgkB4eDgKCwsREhKC2tpai+/+mwuTOT99+jRbHj1+/HhkZGQ4RLP6ACbrfv78eXh7e6O8vBwjR45Eenp6v9l4oGkaO3bswPjx4+Hp6WnRhxnjd/nKK6/g7NmzOHz4sN0FwwEBAWhtbe0wLwYHByMiIgJpaWntvkuCIBAXF4ekpCT88ssvFv2eCYKAWCzGn/70J+Tk5GD//v3tzpdCocCNGzcwduxYEAQBPp8PPz8/REdHY926dWhpabHIeHQ6HZycnHp9nL5Aq9Xi22+/xdy5cxEWFtZpX3B6ejo0Gg1mzpxps8UZSZKYN28eLl++bDGdBpqmkZeXBxcXF/j5+VnkmA7sH5qmce7cOTz00EMgCAJ5eXmIjIwEh8NBeXk524MbHx/PBr5yuRxeXl42C4RNJhMKCwsRFRWF0tJSBAcH3/NepCgKhw4dQmtrK2bPns2Om1F9B2CTCgimBSMqKgqBgYEDOthraGgw20MY+G8g7ODeOAJhK0EQRJdewkx/WU+8ToODg1FRUWFTRVxGGbmwsLBHJd7dfQ8Oh9MhaJRKpVAqlXB3d0d9fT378+joaOTm5kIoFEIgEPS5mFd3CAoKgk6nY68BRqmxvLy83wRn/Yno6GgoFAo0NzfDZDIhJiYG+fn5NhdP6w6MHUR5eTkmTpzYZw95qVSKl156CZcuXcL+/fvtSllbIBAgOjq6w0YfQRB49NFHcerUqXb3PHA7yJkzZw6qqqqQkZFh8fvKxcUFa9aswY0bN3Dw4EGYTCbW3zk1NZXN+rS2tuLSpUv429/+hmHDhuHTTz812xngbmiaRmtrawcbInvAaDTi119/RWhoKBsU3AlN0yguLsbRo0exfPlym/fyOTs7Y8mSJdi0aVOnVVrmQtM0Dh48iClTptj8szmwHs3NzaitrUV0dDQoisLVq1eRnJwMADh9+jSSk5NRVlbWrq2lvr7e4hub5qDT6dDW1gaJRILc3FzExsZ2+bc0TePSpUvIysrC8uXLO7Q6KBQKcDgcuLq69vWwO9Dc3Izjx49j7ty5NlWstga1tbXdKl+/E2ajwhbfTX9jYF89doanpycaGho6XQwFBgaivLzc7GN6eHiAoiizs8mWxsnJCTExMR169ywFk2W5O7MrEAhgNBrh5+fXTnnby8sLjY2NoGka4eHhKCgosPiYzIXH42H48OHsAp3L5WLChAk4evSorYc2IAkODoZEIsHly5fh7++P2tpahIWF2byCojsYDAb89NNPePzxx/u8FJaxVsrOzsaePXvsKhhOTU3F+fPnO8wpEokE06ZNw2+//dZhvCKRCM8//zx2797dJ8rsLi4uWLt2LbKzs3Hw4EE0NzfjwoULmDRpEru4vXDhAsLCwuDp6YlJkyZh9uzZ+Pe//92rNg177RFmMr0NDQ1YsGBBh0UpTdNQq9X4/vvv2b5ge8jexMXFISwsrEN2vyfI5XI0NjayysAOHgxu3LiBqKgoCAQCtLW1oaKiAuHh4dBqtWhsbISbmxuqq6tZKy2apnuc3bMUpaWl8PX1BZfLRWVlJYKDgzv9O5qmUVJSgj179mDVqlWdVqI0NDSAx+NZvdefoij88ccfGDlypE1tqKwBTdPQaDQ98lm3B7/q/oAjELYiXl5eXQpbBQUF9SgQJkkS/v7+FvXQ7CkTJkzAqVOn+qTUlyRJSKXSDl7MfD4fXC4XUqm03Tlwc3MDn89HXV0dEhIScOPGDZtnXZm+x6ysLBiNRra0vbS01CGa1Qe4ubkhNjYWly5dQlhYGG7evInx48fj1KlTdhXs3Q1jLePt7Y3Y2FirBA3Ozs546aWXUFBQgO3bt7PKprYmPDwcTU1NUCgU7X5OEARGjx6NxsZGXL9+vcNYPT09sXz5couWJd+Js7Mz1q5di+vXr+Mf//gHkpKSWMGYtrY2HD9+HDNmzABwe+4aNmwYVq5ciQ0bNuDcuXM9CrxomobJZLIrH2GmJPjo0aNYsWJFpwrQJpMJP/74I0aOHGm167k7EASB+fPnsyXSvdmgOHr0KMaOHdtrVXcH/QeTyYSzZ89i9OjRAIDy8nJ4eHhALBajrKwMHA4HXC4XbW1t8Pf3B3D7WqmtrYWPj49Nxsz0B0dHR0OlUrH9zJ39nUKhwA8//IBly5Z1mcFubm4GTdOQSCRWGP1/x1ZdXY3r169j+vTpdjOf9BXMBmhP5paWlharfjf9FUcgbEU8PT3R2NjY6SKIKY3uycOY6RO25cKVIAh2sq+qquqTsbi7u3fIfHO5XMhkMuj1eigUCvZ9SZJEUFAQysrKEB4ejsrKSuj1eouPyVy8vLwgkUjYDLVYLEZSUhLOnDljF4HHQILpFW9tbYWTkxMKCgoQEhICrVYLuVxu6+F1SWNjIw4fPownnnjCagIgTA/sCy+8gOrqavz88892EQzzeDyEh4cjNze3w+/4fD6eeuop/Pzzz2htbW33O4IgEB8fjzFjxuD777+3+OYcQRBwdnbGihUrcPnyZVAUBYqiWNVkZ2dn+Pv7s4s05lp88803cejQIezevRsGg8Gs88sEwvZUetvQ0MCKY3WW6aVpGkeOHIHJZMK0adPsatHKXPNLlizB5s2be6wjoVKpkJ2djVGjRtnV53PQtzQ1NUGpVCIkJAQAcOnSJSQnJ4MgCOTm5sLDwwM1NTWIiIhggxiKoqBUKm3qIZyXl4eYmBjI5XJ4e3t3WsGh0+mwbt06TJ8+HREREZ1e18zfcTgcq27OmUwm/Prrr5g7d67d6iVYEqPRCJPJZHYg3JsA+kHDEQhbEYFAAIPB0Gk2ysPDAxqNxuyHMUEQiIyMRElJic2zXFwuF2PHjsWJEycsfmyCICCRSDr0+jK91waDAa2trWhra2N/Fx8fj5s3b8LJyQlOTk496sG2NIyw2PHjx0HTNCuadfbs2U6ttRz0jri4OIjFYhQVFUGr1UKr1WLs2LE4efKkzYO8zjCZTPjtt98wZcoUq5c0Mb6Szz//PNRqNTZu3GgX1+SoUaM6zaISBIGQkBAMHjwYO3fu7PB9EgSBqVOnQiAQYOfOnX0iBnb9+nXMmTMHdXV12LFjB/R6PQ4dOtSpfy5BEJDJZHj99ddRXV2Nb7/9tp3t2/2wt0BYo9Hg66+/xqOPPtqlOFZOTg4yMjKwYsUKu8pkMzDWdpGRkfjjjz/MvkZomkZmZibi4uIcvXgPEDRN4/Llyxg0aBB4PB4oikJOTg4SEhIAABkZGUhOTkZhYSFCQ0PZa5+iKBiNRpt5get0OqhUKnh4eCAnJ6fT/mCTyYQtW7YgOjr6vn7YWq0WPB7PanMSM6e0trZi+PDhD8TGU0tLC6t1Yy56vd7ufeftAUcgbEX4fD5MJlOnAatQKASfz++R2JSnpyc7wdkSgiCQnJyM3NzcDhkaSyCRSDotc/Tx8YFSqQSfz28XKAcFBaGiogIkSSI6Oho3b960i+Bn0KBBqKysZMs9fXx8IJVKO816Oeg5BEEgIiICzs7OKCwshIeHB0pLSzFixAjk5OTY/H65G6Zsrba2FhMmTLDZQ14kEmHFihUgCALr16+3iJhQT2E2+urq6jptH2DEsXJycjr1C+fxeHj66aeRm5uLU6dOWfT+1+l0OHr0KObPn481a9aguroaX3zxBVQqFaKiojr9/phM8sqVK+Hv74+PP/642yJajDCXPQTCBoMBmzdvRnx8PFJSUjr9rI2Njdi8eTOeffZZu1YuJUkSc+fOxfXr15Gfn2/WNaLX65Geno6pU6f24Qgd2BtGoxGZmZkYPXo0CIJAbW0teDwe3N3d0draihs3biA2Nhbl5eXtbMKYqjRbbQpVVFRAJpNBKBSiqKiowzxlMpmwc+dOmEwmPPLII/cUoTKZTNDr9VYNhPV6PX7//Xc89thjdrmx1hc0NzfDxcXFbEEwmqZhMBgemPPUGxyBsBXh8XgQiURdBrudZTy7A4fDgZeXF2pqano5wt7j6uqK6OhoXLhwweJBp1Qq7fT8BAQEoLKyEhKJpF0vobe3N9ra2qBUKjFo0CBkZ2fbRSAsEAiQkJCAy5cvA/hv5urIkSN2Z2HT32GUFhlBj+vXr0MsFiMhIQGZmZl2cT0waLVabNu2DU8++aTNd3EFAgGWLVsGiUSCr7/+mvXotgV8Ph9RUVG4ceNGp793cnLC008/jU2bNnWqCC4Wi7FmzRrs27fPYi0kTCYwJCQEvr6+rEBXXl4ejEbjfe9jPp+PuXPnYsaMGfjkk09w7dq1+75Go9FAIBDYPBCmKAoHDhyAyWTCnDlzOg2C29rasGHDBsycOROhoaF2n7kRi8VYunQpNm/ebNYm7p2WSfb+GR1YjvLycggEAnh7e7fLDnO5XNTV1UGlUsHX1xc3b97EoEGD2Nc1NTXBxcXFZvN7bm4uYmJioNPpoFAo2vUqUxSFtLQ0lJSUYNmyZfcNoDQaDfR6Pdzc3KwyJzHaGb6+vl2Waw9EmpubIZFIzP68TOuNrdcS/QFHIGxFOBwOpFJplyW6PRXMIgjCrgShHn74YZw8edLiQZ27uzsUCkWHjLqbmxuUSiXbE8zA4XDg7u6Ouro6+Pr6oqGhwS5KPQGw5dDMDnFsbCxaWlpQXV1t45ENLPh8PiQSCaKjo1FXV8dmfCZMmICMjAy7uR4Y+5WoqCi7echzOBwsWrQIoaGh+Pzzz/tEdKq7MOXRnVXTEASB6OhoJCQkdFoCzZQkv/jii/jxxx9RWlra68+h1+tx+PBhzJo1CyRJgiAIqNVquLm5ISgoCOvWrYNWq73n+5AkiREjRuCVV17Bb7/9hj179tyzb1ipVEIsFlutb7wzaJpGVlYWsrKysGzZMnC53A7XKkVR2LlzJ7y9vftN3yxTPTJ06FD8+uuv3Xp2mUwmHD582O56nx30LYx/7dixY8HhcNhAeNiwYSAIAjdv3mynpMyI6AG3e+plMplNrhem4igmJqZDQM7c1xkZGXj++ee7pUyvVCpZGyZrzEkKhQKHDx/GY489ZtM50JrQNI3GxsYeKWOr1Wrw+XxHINwNHIGwFWEWZJ0FwgRBsJnNnhw3NjYW+fn5Nu8TBm5bQXG5XBQXF1v0uCKRCHq9vsMiRSwWQ6vVIiAgABUVFe1+Fxsby4rXuLu7o6Kiwi42C3x9fcHhcNjvm8PhYNy4cWzvsAPLQJIkIiMjwePx0NLSAqVSCYVCAS8vL3h7eyMrK8vm55umaVRWVuL8+fOYN2+e3XgiMt7dc+fOxbBhw/Dxxx/3WNCvt+MIDg5GU1NTl+XsBEFg3rx5yMvL67TygyAIBAYG4tlnn8U333yDurq6Xn2OzMxMBAYGws/PD8B/RaHGjh2LlStXwsfHB5999hlUKtU934cRGXzrrbdQVVWFL7/8sssNh55mBiwFTdMoLS3Fb7/9htWrV8PZ2bnTvuDMzEwUFBTg8ccf71cLVoIgMGvWLFRVVXVrXpDL5VAoFHalhO2g79FoNCgsLMSgQYPYsmjGwpGiKJw9exZJSUkoLy9HQEAA2zvOWCfZKhBubW1FU1MTAgICkJubi8jISJAkyXrWb9++HWvWrIGrq2u3xqdSqUBRFFxcXPr881AUhW3btmHKlCkD3i7pbqqqqlghWnNQq9UQiUR2s56wZxxnyMrcy0vY19e32/1inR1XrVb3WPnSknA4HEycOBHHjh2z6KKZy+WCpulOA2E+nw+hUIja2lr290ymKD8/H8Bt8ayuyiutDUmSGDduHE6cOMGKZqWmpiInJ6dHfeIOOocgCMTFxaGmpgb+/v5Qq9UoLS0FSZKYOXMmDhw40Cd2X+ZgNBqxefNmLFiwwC57KUmSxOTJkzF9+nR88sknfaYKfy+EQuF9fcqZ3uaffvqJtfW4E+ZamDNnDr744gs0NTX16HPodDocOnQIs2fPZhcZSqUSWVlZGDduHLhcLhYsWIDk5GR8/PHH9w26CYKAi4sLVq1ahejoaHz00UfIz89vN88xdia2tMJobGzEunXrsHz5crbl4E5omkZZWRl27drVpe+ovcPn87F8+XJs376d9aHvDJqmcezYMYwdO9aRcXnAuHjxImJiYlhf1ytXrrBl0a2trbh+/TpiYmLYftw7N4Nqa2s7vXesQU1NDaRSKYRCIascTRAEqqurWeV3Ly+vbge1zCZfX4vEMZlsuVyOiRMnPnCbTj31Ama8hx+089UTHIGwlfHz8+uy/NXb2xvNzc3tlI+7C5/Ph5eXV4eMqK1ITk5GaWlpB//P3sCUId2d9WZKoAmCgEqlarcZEBgYiMbGRrS2trIq0vYAQRAYPHgwCgsL2f5LsViMxMREu+td7e8EBARALpdj5MiRUKvVuHr1KmiaRlBQEGQyGbKysmw2NpqmcerUKTg5OWHo0KF2+9AiSRIPPfQQFi1ahM8++wyFhYVWvUYJgsDIkSNx7ty5Lt+XUZGeOHFil5ZJzHEefvhhfP755z3adLp48SJ8fX0REBAA4PZ3mJ6ejuTkZLYMksPhYMqUKZgxYwb+7//+D2VlZfc9XzweD9OnT8ezzz6LH374AQcOHGhn+VZXVwcvLy+zx2sJNBoNvvnmG8yaNQvR0dFdeoquX78ey5Yts9k4ewtBEPDz88P06dOxefPmLjfJ1Go1rl+/jtTUVLu9Zx1YHoPBgJMnT7IBmclkwuXLlzFixAgAtwPdpqYmxMbG4sqVK0hJSWn3erlcbjMP4Zs3byIuLg4mkwk1NTUIDAxEU1MTvv76ayxatKhT5fd7oVAowOFw2pV+9wU6nQ6//PILnnzyyQdS+EmtVrObLuag0WggFov7YEQDD0cgbGXuJYglEAjA4XB6pNLKlEfn5OTYRRAlFAqRlJRk0aCOy+VCIBB0Kojj7e2NpqYm8Hi8dr8XCARwdnZGU1MT/Pz8oFarO1WftQXOzs6Ii4tjhcWY/urTp0/bhefxQMHZ2Rk8Hg++vr6QSCS4evUqDAYDqzi8f/9+m53vxsZG7N+/H0uWLLH7MlKCIJCUlIRVq1Zh/fr17IaCtQgKCoJSqbynoCBBEJg4cSK4XC4OHDjQ6fhIksSECROQmpqKzz77zCwLI51Oh4MHD2Lu3LnsorG1tRWnT5/G1KlT2y0kSZJEamoqli5dii+//LJbGg6MSvbbb7+N4uJifPbZZ2wrTVVVFVuKbU0MBgM2btyIuLg4PPTQQ52WQ+v1evz4448YO3Ys4uLi+nVwSBAERo0aBYFA0GmrCk3TOHv2LOLj4/s8CHBgX+Tn50MsFrObYHV1dWhra0NgYCBomkZ2djY4HA6CgoJw8+ZN1mOYoadBTW+hKAq5ubmIi4tDS0sLm1T46quvMGXKFCQlJZl9z9bW1oLP5/epzR/TchIcHNylEv9AxmQyQavV9uiaUalUdllhZo84AmEr4+Tk1KWICkmSEIvFPbJ1IQgC8fHxuHXrlt0oDz/88MM4e/ZsjzLcncHsPnaWZQ4NDUVZWRnc3NzaLZQJgkBMTAxycnLA4/EQEhLClkrbGoIgMG7cOJw6dYr9zry9veHt7W03CtcDAS6Xi5CQEJSXl2PkyJHIy8tjr6Hg4GB4eHj0icr5/TCZTNi2bRumTp0KDw8Pq753T2FEhV566SX8+uuvSE9Pt9p5EwqFSEhIuO93xePxsGLFCmRkZHQZfJIkiWnTpiExMRH/+c9/oNPp7vs5aJrGpUuX4OPj0y4bnJmZiaioqE5715hy7BdeeAFbt27tloggQRBwdXXFmjVrMGzYMHz00Ue4ePEilEql1b1qKYrC7t27weFwulSIpmkau3fvhouLCyZPnjwgFqscDgdPPvkkjh8/3iGbbzQaceLECUyaNGlAfFYH3YOiKBw5coTd8GLmg6FDh4IkSVAUhaysLAQFBYHL5YIkyXZzAk3T0Gq1NmkZ0Gg0UCgUCAwMREFBAby9vfH9999j6NChGDt2bI+u4+bmZhiNxj7r2aVpGtXV1cjIyMCCBQseyHtNrVaDIIgeZXZ7WlL9IOIIhK2MSCSCwWDoVK2WEczqaXmzTCaDSqWyi2wiQRDw8vKCu7s78vLyLLJYJgiiQ6DL4Onpifr6egQHB6O0tLTda+Li4nDr1i3QNI2hQ4fi8uXLdhNk+vv7QyAQoKioCMB/F+iHDh2ymw2N/g5zDeTk5GDixIlQqVTIyclhf79gwQLs37+/T7yvu4LJHigUCpt6BvcEZp567bXXkJ6ejr1791qlz5rJ1J09e/a+94azszNWr16NjRs3dtmjy1QEBAUFYf369Whra7vnvKDT6XDgwIF2gmZtbW04fvw4ZsyY0eV3yIh9vf766zh9+jR27Nhx3zmaESqbMGECXnnlFezbtw+ZmZkAYLW5iynbLywsxFNPPdWpQjRN07hw4QJyc3OxePFiu69q6C4EQUAikWDp0qXYsGFDuyqjmzdvQiqV9kjAxkH/RS6Xo6mpia14MBgMuHTpElser9VqUVVVBV9fX1RWVoLH47XbuNJoNCAIwiaBcG1tLdzd3cHj8XDt2jVcuHABoaGhHapYzKGvP4/JZMKWLVvw6KOPws3NrV89Iy1Fb5wCGhsbHYFwN3EEwlZGKBRCKBR2GswxCqI9UY4GbmebPT092wWCtoTxxz169KjFgjo3N7dOS5vd3d3R3NzMPoTuXCwGBgaivr4ebW1tiI6ORkVFhV2IigFgF7t3CouFhoaCw+GgsLDQxqMbOISEhKC0tBTe3t4YP3480tPTQVEUq+CdkJCAI0eOWC3IUKvV+PXXX/HUU0/1274nDw8P/PnPf0ZhYSF++ukni1V+3IugoCBQFIWqqqp7/h1BEAgNDcW8efPw7bffdrnJweFwsHDhQri6uuL777+HXq/v9BqgaRrnzp1DUFAQGwDRNI1r167By8sLvr6+9x27TCbDa6+9hrq6Onz33XdQq9XdKpUODAzEc889B6FQiM8//xzZ2dl97g5A0zSuX7+Oo0ePYtWqVV1mJEpKSrBz5857/k1/Ji4uDkOHDsW2bdtgMplgMplw8OBBzJgxw6HG+gDBZIMffvhh1jNXLpeDy+XC09MTAFBYWAiDwYCoqChcu3YNsbGx7a4RhUIBsVhs9fmepmncuHEDCQkJMBqNyMjIwJgxYzB37tweb1zRNA21Wg0ej9cnYnE0TSMjIwM8Hg/Dhw9/IINgoHflzY4e4e7jmMmtDEmSXZb3ArczhNXV1T0KHO2tT5gpo1QqlZDL5RY5JtNjfffnc3Nzg8lkgkQiQU1NTbvzJxKJ4Orqirq6Ojg7O0MikfR4s6EvYKwWmGuCy+Vi6tSpOHDggCMrbCGY8q3m5mbMmzcPV65cYXvxCYLAI488gszMTNTU1PT5vUNRFLZv347hw4cjODi4Xz/kxWIx1q5dC6PRiG+//bZbwV1v4HA4SE1NxdmzZ+/7t4wwVlRUFDZu3NilZzSPx8OTTz4JJycnrF+/vtNsrVarxeHDh9spRRuNRhw4cACzZs3q9ncoEolYe6WPP/4YtbW13TpfLS0tGDduHFauXIkdO3Zg06ZNUCqVfXauS0tLsXXrVqxevZr1Q72bxsZGrF+/HsuXL++34lj3g7FUam5uxtmzZ1FeXg6NRoPY2FhbD82BFWlsbERhYSGb/WX6xFNTU9l+2ytXrkAsFiM8PBxnzpxBUlJSu2Mwqu/Wnu8pisKtW7cQHR2NrVu3wmQy4cknn2QD+p5gMBig1+tZ3RZLU19fj71792LJkiW9Gmd/p6GhocdtU1qtFiKRyMIjGpg4AmEbIJVKuwyEfX190dDQ0ONSw9jYWNy6das3w7MofD4fY8eOtZiVkpeXF+rq6jr8nMPhwMXFBVwuF0qlst1iliRJxMTEsNZJQ4cOxaVLl+xiswC4vTgeMmQIzpw5w45p0KBBaGxs7FJh3IF5cLlcBAUFobCwEImJiXB2dkZJSQn7excXF8ydOxebN2/u02wbYwVRXFw8ILJKBEGAz+fj6aefRlBQED7++ON72s5YgpSUFFy9erVbVR0cDgfz58+HwWDAnj17utxY4vP5WLJkCZydnfHtt9+2K5NmVKGjo6NZxVeappGTkwMnJyezNjMIggCPx8O8efMwY8YMfPzxx7h58+Z9z1d5eTmCgoIQFhaGt99+G66urnj//fdx6dIlmEwmi51vmqZRX1+Pb7/9FitWrIC/v3+n5dA6nQ7r1q3DtGnTulSRHihwuVw888wz2L9/PzZt2oTJkycPmBJwB/fnTo9woVAI4HZLxPXr11mlf0aMis/nQyaTQS6XdxDKampqsokHrlarRXNzM86dO4eMjAyMGjWK/Ry9OaZer4dIJLJ4IGwwGLBp0yY88sgjA3aDrbv01EOY6Ud3BMLdo3+vwvopPj4+XWZIBQIBTCZTjwNhHx8fKJXKHilP9wUEQWD48OHIycnpVO3ZXKRSaacZYeB21k+pVILL5bZbJBMEgcTERFY4JykpCbm5uV1miKwNoxZ97tw5dtxcLheTJ0/GoUOH7CZg788wdlXXrl2DUCjEpEmTcOrUKfbcMtepUCjsVCnWUrS2tmLz5s1YunRprxcj9gJBEOByuZgzZw4mT56Mf/7znygtLe2zcyiTyeDq6trtFhAej4fnnnsO2dnZ9xT34vF4eOqpp+Dm5oZvvvmGDYY1Gg3S0tIwa9YsduOCoijs2bMHs2fP7lFQRJIkRowYgRdeeAGbN2/GkSNH7jnn5+fnIzIyEgRBQCgUYv78+XjppZdw6NAh/Oc//+nSm94cmHLHr7/+GnPnzu1SpdVkMuHnn39GSEhIj4V2+hMEQUAmk2Hu3Lk4cuQIEhMTbT0kB1aCpmk0NzcjJyeHVUxnNjN9fHxYX+/a2loAt+cQrVYLtVrdoV2ioqKCFdmzJuXl5bh16xaqqqowfPhwDB48uNf3bGtrKwwGA4RCoUVLo5mSaIIgMGbMmAE/t9yPngpemUwmdqPCwf1xBMI2wNfXFzU1NZ3+jsfjQSQS9cjfEridXfT09ERZWVlvhmhRXF1dER8ff08P0O4iFAq7zASFhISgsrIS3t7eHUqf7/Rolkgk4PF4qK+v79VYLIlMJoOvry9b1k4QBFJSUlBcXNxpBtyB+TDK4iaTCZMnT0Z6enq7DSMul4unnnoKhw8f7hM/boqisHPnTgwePBgRERED7iFPkiRGjRqF5cuX46uvvkJWVlaflPYTBIGxY8e228i439+LxWI2cLyX7ROXy8WTTz4JqVSKdevWQafTIS0tDUlJSWwvIADcunULXC6XDU57+jlCQkLw9ttvIzs7u8u+YZPJhLq6unYLa4IgEBQUhDfeeAMJCQn417/+hcOHD/e4T5vJ8q5fvx7Dhw9HSkpKp5+LoigcP34cCoUC8+fP7/cVDeZQXV2NQYMGYceOHY6WlQeIAwcOYOzYsWy/JU3TOHHiBCZMmACSJNkeXE9PT7i5ueHGjRsICgpig2SG+vr6dnOINTCZTDh27BhCQ0OxevVqyOVyhIWF9fq4ra2toCgKTk5OFquOoGkatbW12L9/P55++ukHvuqC2YS5+zrqDswaeaBstvc1D85TzI7oSvAJuF3K5+vr2+OFOJP9vH79em+GaFEYb8/09PReZ2EFAgH0en2HhQgjeiSXyxEcHNzB8kIsFsPb2xvFxcXgcDgYPHgwLl68aFfZ1qlTp+LYsWNsaa5AILBoWfmDjoeHBwiCQENDA7y8vCCRSHD69Ol259bd3R1PPfUU1q1b1yMbs66gaRp5eXnIzc1t50E70GB0Cl555RXs2rULR48etbiiNONnXFhYaFaVibu7O9auXYuff/4ZhYWF98wML168GO7u7vj000+Rnp6OmTNnst+ZyWTC7t27MXv2bIv0r7m5ueHFF1+Et7c3/vWvf6G8vLzd2Bibks56xfh8PiZOnIg333wTJSUl+Pvf/94jCz2j0YhNmzYhICAAU6ZM6TTApWkaV69exenTp/Hss8/2SW+gvaLVanH+/Hm8++67UCqVOHnypGNOfgCQy+XIy8trl51sampCU1MTIiIi2L/LysqCm5sbAgICkJmZicTExHZzPE3TaGlp6VFQ01MoisLRo0exa9cu/PnPf2b7ei1RbswEwpb0qWVKoufOncs+qx9kjEYj1Gp1lxoN90Kr1YLL5fZbIU5r4wiEbYCrq2uXQieMNcndysfmEBMTg9zcXLvatfbz84O7uzvbp9tTBAIBSJLstPTbx8eHtVC6s/8T+O/i+dq1awCAYcOG4dq1a1axfekOjMptW1sbq4hLEARGjx6NGzdudKoy7sA8mHNcXFwMHo+HCRMm4Pvvv2+XRSMIAoMGDcLQoUPx448/WsyKrLW1FVu3bh1QJdFdQRAE/Pz88Nprr+HatWvYsmVLt3x6zUEsFiMkJKRLn+CuxhUQEIAVK1bg22+/RUVFxT2D4ccffxwNDQ1oaWlpV/7HzK2WEkwiCAICgQBz587Fo48+ii+++AIZGRnshlhNTQ28vb27zL4SBAEPDw+sXLkSixYtwtatW7FhwwY0NTV169yYTCb8/vvvIEkS8+bN6zK4Lysrw7Zt27B69Wqr+xnbEsYvNjw8HN7e3li+fDmOHTvGWt45GJhQFIVdu3Zh+vTp7UpMT58+jWHDhrEbQUqlEgqFAm1tbfDx8UFpaSni4+PbHUuv10Or1cLNzc1qYz927BiOHj2KpKQkeHl5obKyEr6+vhbJtDY0NIDP51tsHqBpGocOHYKLiwsrSPago9VqYTKZ4OzsbPZrW1tbHWXRZuAIhG2Aq6srjEZjl5YejNVLT/H394dGo+lxeXVfQBAEpk+fjsOHD/dKjIjP58PJyanTjLpMJkNrayvc3NxQV1fX4X2io6NZT2OZTAaSJNHQ0NDjsVgaLpfLWikxmxhisRgpKSl92rf6IJGcnIyrV68CAFJTU1FaWtqhZJ8gCMyePRs8Hg/btm2D0Wjs1bmnKAp//PEHYmNje1VK259gPL9feuklEASB//u//7OoyjFBEJgwYQJOnDhh1oYfQRCIjo7G0qVL8dlnn3Wp2kzTNJqamsDlcvHwww/j008/RUtLC4xGI/bu3Ys5c+ZYvCyYJEkMHjwYb775Jk6ePMmWSjPWJ/eDw+EgNjYW77zzDnx9ffG///u/OHnyJAwGQ5fnnaIoHD58GFVVVVi6dGmn/X7Mufj222/xzDPPwNfX94G4hhlMJhOOHDmCyZMngyRJSCQSrFixAj/88AMUCoVjXh6A0DSNwsJCKBQKDBs2jL3edTodLl68iNGjR7M/y8/PR2BgINsn3NLSgvDw8HbHU6lU4HA4VvEQZtoXzp49ixkzZiA+Ph4CgQDZ2dkdlKx7Sn19PUiStIj4F03TKCoqQkZGRq/VrAcSWq2WTfz05LW28KvurzgCYRvA5/MhEAi6LL309PREY2NjjzO6XC4XPj4+dmURBABRUVFoa2vrVf8ys8DuLEPK4XAgEolAURT0en2HMmwvLy9QFIWGhgZwuVwMGTIE58+ft5uFDEEQGDJkCIqKitjPRxAExo8fj0uXLkGlUtnNWPsjBEEgKiqK9ZH28/PD4MGD8euvv7bblCIIAhwOB8uWLUNDQwN+++23Hm/e0DSN4uJiXLt2bUCXRHcGk+l86qmnMHz4cHz00Ucdyn57c+ywsDCoVCqze/2ZrP8TTzyBTz/9tFOVa5qmsXv3bkyfPh2LFi3CiBEj8Mknn+DixYvQ6/WIj4/vk++Sye6+8cYb8PDwwP/+7/8iIyOjS+Gqzl4vFAoxa9YsvP7667h69So++ugjFBcXd3ie0DSNM2fO4OLFi1i9enWXlQparRbffPMNpk+fjtjY2AfqGqZpGrm5uRAKhQgMDARw+xyHh4dj8uTJ+OGHH+xGdNGB5dDr9fj999+xcOHCdoHZ1atXERQUxAaANE3j/PnzGDRoENra2lBUVASZTIagoKB294lSqbRoGXFXUBSF9PR0nDlzBq+88goKCwsxePBgmEwmFBUVWUzhvaWlBTqdziJl1hqNBhs2bMCyZcseqEqT+8EEsz35vlQqVY8yyQ8qjkDYRri4uHQZCDs5OXUayJkDUwZsT4ETSZKYPHkyjh492quy7a56rEmShJeXF1paWuDm5sbu0DJwuVxERUXh1q1bIAgCQ4cOxZUrV+yqhNzJyQkjRozAiRMn2O/Ozc0Nw4cPx7Fjx2w8uv6PWCyGk5MT6uvrwefzMXr0aLS2tnYQXiIIAiKRCKtXr0ZdXR1+/PHHbtn13I1Wq8WPP/6IJUuWQCwWP1BBBAOHw8GkSZPw5JNP4ssvv8Tly5ctcs/x+XyMGDGi26JZd8KohM+ePRv//ve/22X2aJpGWVkZqqqqMGrUKJAkialTp2L8+PF48803MWbMmD4VcmEsqR599FHMmzcPFy9eRHZ2tlll+gRBwNvbGy+++CJmz56NDRs2YNOmTaziPk3TyMrKwpEjR/DCCy+wQkB3YzAYsGXLFkRFRT2QKq40TWP//v2YPn16u4CIEWzz8PDArl277OoZ4qB30DSNkydPwtfXt52oocFgQFpaGqZMmcL+rLW1FZWVlXBycoJUKkV+fj5CQkI6BL0KhaJH6r/mQFEUTpw4gVOnTuHFF1+Es7MzysrKEBoaipaWFhgMhh570t4J0+9MkmSvg3uj0YiffvoJw4YNe+A22e5HfX19j7+v+vr6B956yhwcgbCN8PT07LIsVyQSwdnZuceqxgRBICYmBgUFBX3qiWouTMazrKwMjY2NPT6Oh4dHl3YhISEhKCsrg7+/f6d91kOHDkVWVhZomoanpyeEQiHKy8t7PBZLw9gGXLp0ie2DZuyVLl68aFEBpwcRgiCQkJCA7Oxs0DSNkSNHwtPTk1XCvRsnJyesXr0afD4f//73v82yqaEoCtu3b0dCQsID/5BnRPxefvll7N27F7t37+51Jo0gCIwcORKXLl3q0bEIgsCoUaMwYcIEfPHFF2zpNvO9zZkzh+0DJAgC/v7+iIiIwIEDB+7ZX2wpSJKEQCDA7NmzUVlZif/3//6f2doRjDDgO++8A3d3d/z973/HyZMnce3aNezcuRNr1qyBVCrt0iZpz549oGm6T0rB+wNVVVVQKBSdlqZzOBwsXLgQxcXFyMzMtKtNZwc9g6Zp1NTU4NSpUx1U0cvKykAQBIKDg9mflZeXw8PDA9XV1fDy8oJCoUBAQECHjbLKykq2oqAvMJlMOHz4MM6cOYMXX3wREokEcrkcfD4f7u7uKC0tRWBgoEU28GiahkqlApfL7XIDrbvHOXnyJJRKJWbPnv1APx87Qy6Xs7715sLYLjnOafd48J5sdgIjiNUZJEnCx8enS4ul7uDp6Ym2tja7C5yEQiFGjhzZLuNpLl35MBMEgcDAQFRWViIsLAzFxcUd/iYsLAx1dXVQq9XgcDhITU1FRkaGXS1i3N3dERUV1a5s283NDcOGDXMoSPcSRjTtxo0boCgKoaGh4PF4iIuLw549ezrN7AgEAixZsgQpKSn45z//yQbR94Kx1MjPz8fcuXMfyCDibhgRrddffx3V1dX48ssve13u7+npCU9PT+Tk5PTo9SRJYsKECRg2bBg+//xzqNVq5OTkoK2tDUlJSexCghHOefHFF/Hkk0/is88+Q1FRUZ/ei0zWdvTo0Xj++ecxadIk/Pvf/8bRo0fv2fd7NwRBwMnJCbNnz8b//M//4MiRI1izZg0mTZrUZdaApmmcOnUK+fn5ePrppy3qFdpfoGkahw8fxsMPP9ylQrZIJMLKlSuxd+/ePr8eHPQ9er0eGzduxLx589qV6ZpMJhw8eBDTp09n53KmLDolJQW5ubkwmUwwmUydbnrW1tb2WYbOZDJh7969uHLlCl555RVIJBIQBIHc3Fy2FPr69esW879ua2tDa2sr+Hx+jwNhpmXo6NGjWLFihUPduBMaGxshk8l6XBptjVL8gYJjdWYDmD6wewk1BQUF9aqfjsvlIjAwsIN6sq1hMp5ZWVlmWZ/ciaura5f2UwEBAaitrYWPj0+nFlQCgQA+Pj5sn/LgwYORk5PTo7LXvoIgCEyZMgVpaWlsposgCEyaNAkXLlywKxG0/oivry+am5uh1WrB4XCQlJQEiUSCoqKiLhezHA4HEyZMwJo1a/Dbb79h06ZN0Gg0Xd6fSqUSW7duxYoVKwa8SrQ5EAQBZ2dnPP/88wgPD8dHH33Uq+wqSZJ4+OGHkZaW1uNjcDgcTJ8+HUOGDMHHH3+MLVu2YMGCBWwpLGN9RVEU4uLiMHjwYKxatQpff/11n7af6PV65OXlITExERwOBykpKXj77bdx8+ZNfPzxx6ipqTH7vQ0GA0wmE9566y0cPnwYP/zwA1paWtodh7FJOnr06D17hwc6CoUCOTk5eOihh7r8G4Ig4O7ujmeffRYbNmzotN/cQf+Apmn88ccf8PX1RXJyMhuA0DTdrjKA+blWq0V+fj7i4+NRV1eHqqoquLm5dfCIp2m6V0HNvTAajdi+fTsKCwvx8ssvw9nZGQRBgKZpXLlyBYMHD4bBYEBxcTFiYmIs8v5tbW3Q6/UgSbJHgTBN01Aqlfjuu++wbNmyLitSHmQYgcKeiJExGXtHINx9HIGwjZDJZPd8aAYHB/dKOZopAb1+/brdPZjd3NyQmJjY40yss7Nzl0G0k5MTjEYjxGIxlEplp/ZII0aMYD2EJRIJ/Pz8cOvWLbPH0Zf4+flBJpO1s5tydXVFamoqjhw5YnffaX9CIBAgICAAhYWFAIBRo0bh+vXrWLhwIbZs2YK2trYurc1CQ0Px17/+FSKRCO+99x4uXrzYITtnNBrxyy+/YPTo0QgJCXE85DuBy+XikUcewWOPPYYvvvgCly5d6nGfZXx8PGpra3vVbsEEw1KpFNevX4e3tzf7O4qisGPHDsydOxc8Ho8VXXv11Vexbds2nD59uk96RGtqauDk5MRmpgiCgEwmwwsvvIDx48fj008/xR9//NEtayqaplFbW4uvvvoKS5YswcyZM/Huu+/C09MTH374IY4ePcoep7S0FNu2bcPatWsf2EUqTdPIyMjA0KFD77vYZ8SzZs+ejfXr13dq7efAvmGqL65fv47HHnusXQkxTdM4cOAApk6d2q5PvKysjHWqIEkSSqUSXC4XQUFB7Y5tMBigVCrh6elp0fEaDAZs27YNtbW1WLt2bTthJbVajYaGBoSGhkKtVoOmaYsFRm1tbTAajeBwOD3aJDMYDNiwYQPGjRtnMfGugYbRaIRCoehRjzBN09BoNI5A2AwcgbCNkMlkUKlU7TxM78Td3b3TnkVziI2NRWFhod145TIQBIGJEyfi1KlTPfJpFYvFrKH73XC5XNY/TSgUoq6ursN7x8fHo6ioCDqdjlVlTk9PtzvBk0ceeQSHDh3qkBW+cuVKrxb9DzokSWLo0KG4dOkSgNubDgaDATKZDGFhYdi9e/c9Xy8SifDYY49h7dq1SEtLw6effori4mKYTCbQNI3Lly+joaEBU6dOdTzk7wFBEBg8eDBeffVV7N+/H7/88kuX8+G9EAgEGDJkCM6ePdurDSK1Wo2amhosXrwYn3/+OZspvX79Ong8HqKjo9uN3d/fH6+99hrS0tKwf/9+i+ox0DSNCxcuYMiQIR36+rhcLkaOHIl33nkHtbW1+Oijj5Cfn9/l/EXTNBoaGvDVV19h/vz5SExMZMXgZs+ejTfeeAOFhYWsQvX69euxfPly+Pr6Wuzz9De0Wi3OnDmDyZMnd1utOzU1FbGxsdi6datDSbofwWz+/PLLL1i1alW7jQ+apiGXy1FbW9uuVYKmaZw9exYjR45kK/fEYjErxngnWq0WFEVZ1M7GYDBg8+bN0Gg0eO655zp4xpaXl8PLywsCgYAV8LJU+bFOp+vx5zGZTNi+fTvc3NxYOzIHHTEYDNDr9T1SfjYYDNDpdI5A2AwcV6GNEIlEIAiiy5JciUQCg8HQ4/Jh4HbmlVH4sze8vLwQGBjIBiPmwEzAnZ0bDocDf39/VFRUwN/fH1VVVR3+RiwWw83NDdXV1QBu+wvX19fblacwk33kcrkoKChgfy4WizFu3DgcPHjQ7gL3/kR09P9n76zDs6r///84973u7mbBgo2NjkmM7m5FAUFASQGxi4+ogLQiCIKiSEp3iXTXqMFg3Z337vj9we+cL3PBChi653Xt4mK773Pe533q/XzF8+nD/fv3KSoqQi6X07RpU06dOsWAAQO4evUqN27cKJdUCYKAi4sL7777rmSjsmzZMq5du8bmzZt5/fXX/5N9lZWFIAjY29szY8YMCgoKmDdvHklJSZUmtO3atePUqVNVbnFQq9Xs3r2bZs2aMWzYMJo3b87ChQtJSUnhzz//pG/fviX8LcUWl+nTp3Pr1i3Wr19fpcBeaVCpVFy+fLmYh+k/921mZsaoUaMYNGgQ69atk3xtn4RGoyE9PZ0lS5bQrVs3GjVqVGx7giBgY2PDuHHj6NmzJ7NnzyY3N/c/bWMiZgddXFwqlZGRyWR0795dKrGtez7XfohE9/vvv+f1118vEfzRaDRs376dLl26FOsTLywsJCIiAn9/f65fv45KpcLCwgJ7e/sShDM/Px89Pb0aI315eXmsWLECQRB44403SpBg8foNCQkBkPqDayoom5KSgoGBQaWJsFhl8eDBgzq/4KdAXJdU5ZpRKBSo1eoS10UdykYdEX5BED02yyqj0tHRwdjYuFqZP21tbTw9Pbl161atK6WVyWR07dqV/fv3Vzp6rqWlhZ6eHjk5OSX+JgpmRUdH4+Pjw+3bt0vdd6NGjTh37hwajQZtbW2JCNWmeZLJZHTr1o29e/dK2Saxx/rOnTskJyfXqvG+TDA1NcXExISYmBhJffjSpUtoaWkxbtw41qxZ81SFaEEQ0NbWJiQkhI8//pjAwECmTJlCenq6VI5Wd36eDkEQMDQ05PXXX6d169Z8/fXXUiCiIvMnCIIkmnX79u1Kz7lGoyEuLo5r167RpUsXZDIZnTp1onnz5syYMQNdXV28vLzK3LeJiQmTJk0iNzeXFStWkJ+fX+3zHhUVhYGBwVOJmFwux9/fnw8//BArKys+//xzjh07hlKplHrFFi1aRFhYGM2aNStzMaxQKDh06BAff/wxffr0Yd68eWzevLncPvh/K5RKJfv376dr166VJg86Ojq89tpr3L59u9aJMNahODQaDUlJSSxcuJCBAwfi5+dX4nw/ePCA9PT0Ej3DERER2NraYmBgQFRUlER23d3dS5CX1NTUGmkxEJMaCxcuxMbGhtdee61UEbeioiLu3btHQEAAKpWKhw8fUq9evWrt+0kkJyejq6tbqWCZqLOwZ8+e/7TuQEUhipFVReW7sLAQHR2dumq0SqCOCL8giBH9jIyMMv9uY2NTwgu3svto2LAhV65cqfI2niVcXFwwNjbm5s2blfqeIAgYGxuXSoTh/yyUnJ2dSxUcE5WDw8PDKSoqksjl+fPna51olo+PD/n5+cWOQ19fn06dOknWJnWoPGQyGcHBwVy4cAGNRoO5uTk2Njbcvn0bV1dXevfuzfLly8nLy3vqHIu+r0qlki5dujBq1Ch+//13vvzySy5fvoxCoag7TxWATCbjlVde4Z133uG3337jzz//lAjd0yAIAp07d+bAgQOVzsSpVCo2btxI7969pT47cSxixigtLa3ccejp6TFmzBgsLS1ZuHChZMVUFWg0Gk6cOEHz5s0rtBASy5x79+7NrFmzuHDhAl999RW3bt1i4cKFvPLKK7zyyitlZhcUCgWrVq3Cx8eHsLAw2rVrx6effkp+fj6ffPIJf//9d6VUql9miAt2AwMDXFxcqrSY1NPTY8KECezbt++plSV1eDEQy6G/+eYb+vfvX2rlhVKpZOvWrZI2wJM4fvw4oaGhZGZmEh8fj6mpKdnZ2cXaJ0TExsbi5ORU7fGmpKQwf/58QkJCGDhwYJkZ1fT0dGl9KZJWU1PTau3/n9tXKpUVVsEWA41r1qxh/PjxdbY+FYCoMl7VjHCdCnflUEeEXyAcHBxKLd0VUa9evVItgCoDV1dXYmNja12fMDxe+Pbs2ZM9e/ZUenzlBRGsrKxIS0vDxsaGrKysUrPuZmZmGBsbSxZW5ubm2NnZ1brsuZaWFp07d2b37t3SuARBoFmzZiQkJPDo0aNaNd6XBaKvrbhQFVWhjxw5gkajITQ0FH9/f1asWFGmeJYIjUbDo0eP2L9/P2+++SYtW7bkww8/ZMCAARw9epSPP/6Ybdu2kZSUJPUR16F0CIKAm5sbs2fPJj4+nvnz51dIiVcQBLy8vMjMzCzVWq0saDQabt68SUFBQbHFsNij27RpUwYMGMA333xDXFxcuePQ1tZm8ODBBAcHV1nVGR734N24caNEGfPTIAgCdnZ2TJ06ldatWzNmzBjS09Np0qRJmd8Rhd0MDQ3p3bs3crlcynK/+uqrTJkyhfPnz/PVV19x9+7dWuVL/yyg0WjYtWsXXbt2rXLppkhCJkyYwO+//87Dhw/r7vlaBJVKxenTp1myZAmjRo2iSZMmJe4zUXVZV1e3hNpydnY2MTEx1K9fn7i4ONLS0vD19SU9Pb0EORRF6mxtbatM/jQaDdHR0SxYsIDOnTvTqVOnMgmS+Dzz9fVFLpdz8+ZNfHx8aqwMWWy1UKvVFVI0FtWPly9fzvDhw3F1da0jwRWASISrMlf5+flS62UdKoY6IvyCIGZ8k5OTy/zM04hyRWBiYoKRkZHUD1vb4OXlhSAIxfpgKwJHR8cyfZgNDAykrJChoSFpaWklPiPakYjl0GI5ZFUySs8SgiAQGBhIWloaMTEx0oJKV1eX3r17s2nTplo13pcJtra2aDQaya/bx8eHpKQkUlNTkclk9O7dG2tra3744YdyKwXy8vJYvXo1I0aMwNzcHHgcwPDz82Pq1KlMmzYNQRBYuHAh3333HRcvXqy2f+6/HSYmJowdO1bybr58+fJTr3MdHR1CQ0OlYEZFUFhYyKZNmxg8eHCxKHpubi779u2jX79+tG7dmsGDB7Nw4cKnkhq5XE6nTp3o06cPCxYsqFKp9rVr13B2dpaupcpAo9GQl5fHmTNnmDVrFs2bN+eLL77g9OnTJVpQVCoVO3fuJCMjgxEjRpTaA+3k5MSkSZPo06cPv/76K8uXL68ywX8ZEBUVRU5ODr6+vtXelqOjI6+99horV64kMTHxXztnLwvEe2P9+vUcOnSImTNnlloODY/J7o4dOxg4cGCJv1+8eBFfX18MDAy4ceMG+fn5eHp6oqWlVUKgSCTCdnZ2VR7z7du3Wbx4MUOHDqVly5blZglF67Pg4GAArly5QlBQUJX2XRrUajXp6eloa2tjYmLyVLKVm5vL0qVLCQsLq9E+5X8zNBoNycnJVVYZT0lJqZLa9H8ZdUT4BcLa2rpcYRhbW1tSU1Orlc2Vy+X4+vrW2hItmUxGjx492L17d6WO09raukxxK11dXaysrIiNjZX6hUtDQEAAt27dkvbr4eFBUVFRtfybnwV0dHTo1KkTO3bsKPb7gIAA5HI5V69efUEje7mhpaVFcHAw58+fBx6XnLdo0YJDhw5JveNDhgzBxsaG7777rtQKBLVazebNm/Hz8yv1RS+TybCxsaFPnz58/PHHdOrUidOnT/PFF1+wYsUKaSFVm6632gItLS3atm3LpEmT2LZtG3/88Ue5AQlRuffatWvk5eU9dfsajYZ9+/bh5eWFu7t7sd8fOXKEgIAAKZMTEhLCyJEjWbZsGffu3Sv3fIkaBBMmTOCnn37i5MmTFQ5WqdVqjhw5QlhYWKUXjaJtxpIlSwgKCqJHjx4MHDiQyZMn8/fffzNv3jypgkStVnPo0CHu3bvHmDFjyi2l09LSokGDBnz44Yf4+/szf/58Nm7cWK3y79oIjUbD7t276dChQ40I3YmtLf3792f58uUl/Jrr8Pwg9gPPmzcPjUbDjBkzyszSqtVqdu7cSdOmTbG3ty/2GbVazd9//01oaChqtZorV67g6OgIgJOTU4lgklKplKrTKgu1Ws358+dZvXo1EydOrBCRzM/PJyUlBScnJwoLC0lJSZHGVxNQqVTk5OQgk8me2iOcn5/PDz/8QHBwMG3btq0jwRVEdYMnomd1HSqOOiL8AmFra0taWlqZ5WZmZmYolUqys7OrtZ/AwECuXbtWrW08KwiCQP369cnPz69Uma+5uTnp6ell+r26uLjw6NEjvL29uXv3bqmfMzc3x8LCQspGa2lpERYWxu7du6t3UDUMQRAIDg4mOTm5GKmXy+UMHDiQ7du316re5pcJTZs25eLFiyiVSqlX/OLFi5IiuVju2qhRI7766isiIyOla0m0Snr06BF9+vQpN1IvCAJ6eno0aNCAt99+m08++YSGDRuyd+9ePvnkE1atWsXVq1clUly3YH4MUfxu9uzZ5OfnM3fu3HJLlM3MzPD29paE8MpDfHw8J0+epG/fvsXOXWZmJidOnKBbt27S70XbtXHjxvHDDz9USFXc3d2d9957j4MHD7J9+/YK9TvHxsaSnZ2Nt7d3uZ/7J8Rs1+LFiwkKCqJz586S6qijoyPTp0+nffv2LFmyhPXr13Pw4EHOnj3LW2+9VaEyOlHcsV27dnzyySeo1Wo+++wzDh48+NTWgZcFycnJREZGlisqVlmIz+527dqxfPnyOo/hFwC1Ws2FCxeYO3cuYWFhjBgxosxrXqPRcP/+fSIiIkq1zhLbzFxcXMjNzeXWrVuEhIRw//59fH19S3y+qKgItVpdqcCKRqNBpVKxd+9etm/fzrvvvlshP3qNRsODBw+wt7dHX1+fR48eYWFhUSULnrKgVCpRKpUUFhaW2Xes0WgoLCxk1apVuLi40KNHjzqbpEpAzLpXlcxmZmZiampaF3ioBOquzhcIQ0NDCgsLy1RNlslkGBsbk5WVVa39ODo6kp6eXi0rpmcJLS0tunXrxq5duypFhLOyssrMtHh5eXHv3j1cXV2Jjo4u9XMymYzQ0FCOHz+ORqORFi2xsbFSuWxtgY6ODl27dmXHjh3FjsXZ2Rl3d3f++uuvf8Vi9HnDwcEBQDrf5ubm1K9fnzNnzkjzKZa7jhgxgmXLlnHo0CGUSiUpKSn88ccfjB49ulT1ztIgCIKkktysWTPeffdd3n//ffz9/Tly5AiffPIJCxcu5NSpU2RmZlZYLOrfDFEM6vXXX6dbt27MmzePo0ePljo3otf2oUOHyu1nVSqVrF+/nn79+hUrZxStb0JDQ0uUJguCgKenJ5MnT2bt2rVPJduCIGBpacmMGTN49OgRa9asKZc0ajQaDh8+TNu2bSvV06fRaMjJyWHRokUEBgbStWvXYiJbgiBIFmGffvopDx484KOPPqJRo0aVttgQBAEjIyOGDBnCzJkzuX//Pp988gnnz59/qQW1NBoNhw4dIjQ0tMYVbWUyGW3atCEgIKCODD9HaDQa8vPz+fXXX9m5cyfvvvsuLVu2LFOATqyoWLt2LcOGDSvxTNdoNPz111+EhoYik8mIjY0lLi6OVq1aERkZWayqRERhYSFaWloVvp81Gg0KhYK1a9dy69YtZs2aVale0fPnz0taB9euXSvmfVwTUCqVKBQKioqKSs0IazQayePYzMyMfv361ZHgSkKlUqFUKiu8pngSorJ4TYqj/RdQd4W+QIgR+/Lsg1xcXIiKiqrWfvT19bGxsan2dp4VBEEgICCA9PT0Yn2w5cHU1BSFQlHmosLW1lYSHMjJySmzVNLf31/qC4PHcyVmhWvTok4QBBo1alQiKywIAn369OH48eOl9kLXoXwIgkDjxo05f/68FAzp0qULhw4dKpZlF6/R2bNnc+PGDebNm8d3331Hz549cXBwqNJiQyTFZmZmtGzZkilTpvDRRx8RFhbGrVu3mDt3LnPmzGHz5s3cvXuX3Nzc/2w/uKjk3LRpU2bPns2lS5dYunRpqVUhLi4uGBoalqlGr9FoOH/+PIIglBDKSUhI4MaNG7Rv375M/15XV1feffddduzYwcGDB8sl3CJxHD9+PLq6uixcuLDMEtnMzEzCw8Np2bJlha8njUZDVlYWixcvpmHDhnTt2rXchefDhw/Jz8/nxx9/JDw8nHnz5vHw4cNKXVfidWtra8u4ceMYO3Ysx44d4+uvv35pBbWysrK4dOnSMyvhFD2GXVxc+Omnn+oqeJ4xRIGpuXPnIggCs2fPfupzWq1Ws379eho3bky9evVKfDY7O5ubN2/SvHlzAC5duoSjoyPOzs7k5OSU2tOZkJCAlZVVhYjwk/ZIcrmct99+u0J9uCKUSiX379/H29sbjUbDrVu38PPzq9B3KwpxvaWjo1PqMRUVFbF27VpkMhmDBw+u8wquAkQ+UJX2DPEaMjMzq+FR/btRR4RfILS0tNDX1y+39NnNzY3IyMhq7Ue0Ubp8+XK1tvMsoaOjQ5cuXUr0wZYFuVyOjo5OmUTY3NycwsJCFAoFJiYmZZJEAwMD6tWrV6x0vFWrVkRERFTLuupZQEtLi+7du7Nz585ii01TU1PCwsLYvn37f5YoVRWCINC0aVMuX74svYAcHBxwcnLi7NmzxQiLmOGbOHEiKpWKc+fOkZqaWiGLpYqOxdjYmMDAQEaPHs0nn3zC6NGjMTIyYtu2bXz++ecsXLiQffv2ERUV9Z/0eIXHqvCTJk3C19dXEtJ68n6Qy+WS7kBppCwrK4sdO3YwbNiwYtkhlUrF5s2b6dq1K4aGhuWOwdbWlnfffZdz586xbdu2p3qh6+rqMnz4cIKDg/n6669L6BBoNBpOnjxJYGDgU/f95HcyMjJYtGgRTZo0kcqhy/rsvXv3+PXXXxk/fjxBQUFMmTKFDh06sGLFCtauXVtmq0l5kMlkeHh4MG3aNHr27Mn69etZsmQJjx49emmeRRqNhtOnTxMQEFApb9TKQi6X069fP0xMTPj1119RKBTPbF//ZRQVFXHo0CGWLFlCr169GDZs2FPL/8VqjJycnGItEU/+/fLly/j4+GBoaCj177Zp04aMjAzMzMxKrSSIi4vDzs6uQmXNsbGxfPPNNwQFBTFixIhKVybExMRgbGyMmZkZ6enpFBQUYG9vX6ltPA0pKSkYGhqWOp+FhYWsXr0auVzOiBEjaqTP/r+I1NRUTExMqmSBpFKpyM7OrpLQ4n8ZdUT4BUIU0inL7kPsj4uNja32osLPz487d+7UShsl+L9eqqSkpAplrsVyybKIsK6uLmZmZiQlJeHt7c3t27fL3E67du04fvy4tGjW09OjQ4cOJcqQXzTEOcrIyODhw4fFft+qVSvi4+N58ODBf5IcVQc2Njbo6OhImXZBEOjbty/79u0r9fq6f/8+2dnZrF27loyMDD7//PNSVXmrA7Gn2MnJiS5duvDuu+/yySef0KVLF7KyslizZg2fffYZ8+fPZ8+ePTx48OA/018s+jZ36tSJiRMn8ueff7J69epiStx+fn7k5eXx6NGjYt9Vq9Vs376dZs2alRDCuXPnDmlpabRq1apCPbNmZmZMnTqVmJgY1q5dS2FhYbnfEUvshw0bxpIlS7h06ZI03vz8fI4fP06nTp0qnAFKT09nwYIFtG7dmg4dOpRLgh8+fMhPP/3E2LFjcXZ2RhAEtLW1ady4MR9//DHm5uZ8+eWXVe751dLSIjAwkA8//JAmTZrw/fff8+OPP5KQkFDrr8eCggKOHTtG586dn/m+tLS0GDp0KBqNht9//71Gnxn/dWg0GlJTU1m8eDFXr17lvffeIyQk5Kle3BqNhqtXr3LkyBFGjx5dKoErKiri+PHjhIWFAY+vmZs3b9KxY0ciIiLw9PQs1YIpISHhqWRUo9Fw48YNvvvuOwYNGlRuQKu8bVy8eJGGDRsil8u5f/8+bm5uld7O05CSkoKurm6JYF1BQQGrVq1CX1+fV199tUplvXV4jOTkZKysrKpUmSL2cNd0e8e/HXVE+AWiIhZKdnZ2ZGRkPHWR9TTY2tpKCoa1FTo6OnTr1q3CmU0LC4syj0e0/hD9/u7evVvmNt3c3FAoFJLFlCia9ODBA2JjY2vVQk5LS4vevXvz559/Fgtq6Ojo0L9/f/7444+6xVUlIZPJeOWVVzh27JhUHm1vb4+7u7tkrwX/54n4888/M3bsWBwcHHjjjTeYOHEiJ0+e5LPPPuPixYs13isp9ngaGBjg5+fHwIED+eijj/j000/p1q0bubm5rF+/no8//pgvv/ySDRs2cPnyZdLT0yXf4tp0DdcURFG8Dz74AAsLCz7//HNu3LiBWq1GLpfTuXNn9u7dK933YlY0IiKCzp07F1toPGmjVNFyPkEQMDAwYMKECQiCwJIlS56apRdL7KdOncrWrVvZtWsXKpWKM2fO4OnpWSHbC9FeY968eXTq1Im2bduW6ysaGxvL999/z6hRo3B3dy923OIx9O7dm/fee4+7d+/y5ZdfcuvWrUoHAcUARcuWLfn000+pV68e8+bNq3K2+XlAJEH29vbV8nqtDLS0tBg5ciS5ubn89ttvtTY4/bJAFJc6e/Ysc+bMoUGDBkyZMgULC4sKZWLv3bvHunXreOedd0rtrdRoNERGRqKvry8FzyIjI7GwsKBevXqEh4eXWoKs0WiIiYnB2dm5zP2rVCoOHTrEr7/+yqRJk6rc0yuS6QYNGkikuFGjRpXeztP2kZqailqtxtraGkEQpL7qZcuWYWpqyvDhw6uUyazDY4jP9uoQYbGNqA4VR91svWDY2NiU6zGora2NlpZWhexAyoNMJsPb25s7d+5UazvPEmIfbEpKSolMTmmwt7cvV9RKPF4XFxfi4+PLFSVr1apVMcEpXV1devTowdatW2tdVtjX1xe1Wl1MDVsQBLy9vXF0dJQIXR0qBjHTfufOHek+E32E9+/fL/WPK5VKfv75Zzp06CARCpGMTZ8+nddee43Dhw/z6aefcuLEiWdmiyS+6J4kxh9++CGffvopw4cPx8rKir///ptvvvmGjz76iCVLlrB//37u3r1LTk7OSy1q9E+Iasb9+vXjrbfeYuPGjaxbt47c3FyaNGnCo0ePpEBjfn4+69at49VXXy0mEiWWxlpZWeHt7V2pBYhI/kaOHImHhwfz5s17KukTBAFHR0dmzZrF3bt3WbFiBbt3735qf6841ri4OObPn0/Pnj1p3bp1uSQ4ISGBxYsX89prr5V7bIIgYG1tzYQJExg6dCgbNmxg6dKlVcroitUMHTt25NNPP5WyzZs3b651FkKiOm9p5bDPCuI1M3r0aHJycvjtt9/qgpdVhNgT+cMPP3Do0CGmT59Ox44d0dLSqhAJFu+/8ePHl9lDrFar2bdvH506dUIul0tevY0bN0Ymk5GYmIirq2up38vOzi5TuCg/P5+ff/6ZixcvMmvWLFxdXasciElKSkKtVmNnZ0d+fj7R0dH4+PjUeGAnOTkZQRCkgF1GRgbfffcd9erVY+jQoXU9wTWAhISEKlsnKZVKZDJZHRGuJOpm6wXDwcGh3MWGXC6XyHJ1ERwczJUrV2rVQuSf0NLSokePHiX6YP8J8WFclpcwPJ7b+Ph49PT00NLSKrMXW+wTvX79uqSsLQrpZGRkcPv27Vo1Z1paWvTq1Yvt27cXmyOZTEbfvn05ceIESUlJL3CELx+MjIxwd3fn2rVr0rm2sbEhODiY/fv3o1ar2bt3L/r6+rRr165Uv2Bvb2+mT5/OmDFjuHnzJp9++im7du0iLS3tmQdTRCVqDw8POnbsyNtvv82nn37K1KlTadOmDdnZ2Wzfvp0vvviCTz/9lB9++IH9+/cTERFBenr6S2+BIwgCHh4ezJ49G319fb788kvu3btHq1atOHz4MGq1mm3bthEYGEi9evWKfTc7O5t9+/YxYMCAKi8gxEqN1q1bM2/evApVkpiYmPDOO++QmprKvXv30NXVLfc7YmZqyZIlDBo0iObNm5e50BW9KBcvXsywYcPw9/ev0KJYJpPh5+fHBx98QEBAAPPnz2fTpk3Fys4rAyMjI3r16sWHH36IWq3myy+/5M8//6wVhFgkQtra2ri5uT33/evq6jJmzBiys7PZsGFDXc9wJaFUKjl37hxz5szBxcWFGTNm4OjoWKHrXK1Wc/HiRX788UfeeuutUkub4f8qKrKzs/H19ZV+d/z4cbp06UJ6ejo6OjqlWhSpVCqKiopKlKmKWb/58+ejo6PD1KlTsbCwqOIsPMb169fx8/NDLpeTmJiIiYlJpRXhnwZx3Nra2piZmZGQkMD8+fNp3rw5PXv2rPEy7P8qqkOEc3JyMDAwqCPClUTdbL1gmJiYkJ2dXeZCWVQprQnBLE9PT2JjY2u1fYOYnUtLS3tqr7ClpSWpqallLqhsbGzIzc1FoVDg5uZGREREmdsyNjbGx8eHCxcuSNvT0dFh0KBBbNy4sdZF7D09PTEyMirWZwiPr6fu3buzcePGupK7SkAmk9G2bVuOHj0q3YsymYxu3bpx+vRp/vrrL86ePcvw4cPLjXrL5XLc3d0ZN24c06dPJycnh6+//pply5Zx8+ZNFArFcyEAYqbU2tqaoKAgBgwYwPTp0/n000+ZNm0aTZs2JSsri61bt/L111/z6aef8t1337Fp0yauXLlCXFzcSyfGJZb5Dhw4kDFjxrBx40bu3bvH8ePHOX/+PHfu3KFXr17FFgkajYZdu3bRrFkzbGxsqrV/uVxOu3btGDBgAIsWLeLmzZtPnT9R3OTVV19l3rx5RERElPodjUbD7du3WbFiBSNHjiQ4OLhcEpyUlMTixYsZMGBAlcotRc/gjz76CJVKxeeff85ff/1VJbImCALm5uYMGjSI2bNnU1BQwBdffPHCCbF47rt27frCyjl1dHQYM2YMOTk5/Prrr9VugfovQCRkopXd5MmT6dGjR4X7UhUKBdu2bWPbtm1Mnz69TBIsYvfu3XTs2FG6RsTqMnd3dyIjI/Hw8Cj1+2lpaRgYGBQjwhqNhps3b/LNN9/Qpk2bUm2aKgu1Ws2lS5do3LixJOoVFBRU42RIrVaTn59PYWEhSUlJzJ8/n969e9O+ffs6ElxDEEvNKyqY+E+kpqZibm5eR4Qribo6hhcMXV1dyXS9NIhEWPQ1rU6pi56enhTJ8/DwqPJ2njW0tLTo2bMn27dv55133inzIWttbS31QZZGTnR0dDA2NiY1NRUfHx9u375Ns2bNSp1DmUxGhw4dWLVqFa1atUJbW1sqN7a1teXIkSMl+gpfJEQF0h9++IHAwEDpZStmss+dO8fFixdp2rRprRlzbUe9evXIy8sjJiYGFxcXBEHA1NSUVq1a8fnnn/PTTz8V85wtD6IQ3pAhQ+jbty/Xrl1jx44dZGdn07RpU5o1ayb1JD6P8yPuR19fH319fSwtLQkJCZH66/Lz84mJiSEqKkqqKMjPz8fQ0BAbGxvc3d1xcXHB2toaCwuLYvdbbbu+ZDIZ9erV48MPP2Tv3r3s2bOHDz74gOXLl5fIzsTFxXHt2jU+/PDDGjkOmUxGcHAw5ubmLF++vNzyZdGX1MPDg/79+xMYGMiKFSvo2bOn5FUqfu7KlSv89ttvTJgwATc3t3JJcEpKCosWLaJfv36EhIRU+bgEQcDExIQhQ4bQpk0b/vjjDw4dOsSQIUPw9fWt9LUrCAIWFhYMGTKELl26sGfPHj7//HNCQ0MJCwvDyMjouV5L0dHRZGRkEBAQ8Nz2+U88WSa9bt061qxZwxtvvFEnNlQKNBoNSqWS48ePs2fPHrp27Urb/++5XZHrRlRZX7VqFQYGBsyePRtDQ8Nyv5uQkEBCQgINGzaUemJPnTqFm5sbhoaGhIeHExgYWOp3ExMTsbKyku5jpVLJ/v37OXHiBOPHjy/Rr19VpKenk5WVhaurKyqVips3bzJ69Ogav5dEIpySkkJiYiLvvfdeuc+iOlQearWawsJCDAwMqvR9UcG87pxUDnVE+AVDT08PHR0dsrKyyhRKcXZ2ZuvWrWUSvopCJpMRGBjI5cuXa+wh/CwgCAKBgYFS6WZZvW1GRkYUFBRQVFRU5ry4u7vz8OFDfHx8OHDggCSkUxocHBwwNDTk7t27+Pn5SSJFgwcP5ssvvyQ4OBhbW9saPdbqwMHBgfr163PkyBG6du0qzZFMJmPo0KEsWbIELy8vzM3Na+25rk3Q1tYmLCyMvXv3Mm7cOOCxiNLNmzextLSsEmkV+yWbNGlC48aNSUxM5PTp0yxduhRtbW1atGhB48aNpXP0PM+TuD+ZTIa2tjZ+fn74+vpK6rkKhYLk5GSSkpKIjIzkwIEDpKamUlhYiKGhIVZWVri7u2Nvb4+9vT2WlpbSovR5H0tpx6arq0vPnj2JjIxkxYoVbN++nddff10SIlEqlfz222/07du3yhH4svbt5ubGe++9x6JFi0hOTqZXr14lFuw5OTkcPHiQGTNmSKX17733Ht9//z2PHj1i0KBB6Ojo8Pfff7N7926mTp1aQun6SYgkeMGCBfTt25dGjRrVyDkQxeMmT57M7du32bBhA2ZmZgwePLhKHtqi4vawYcMkQvzpp5/SsmVLOnToUCnv1KpCo9Gwc+dOOnfu/MJtXkQF75EjR/L777/z/fffM27cuBovbX2ZoVarefToEWvXrsXMzIzZs2dXSlBILINftWoVHTp0oEOHDshksnK/L1YMhIWFSdeIUqlk27ZtTJgwgaKiIh49ekS/fv1KVYxOTEyUSlyzs7NZvXo1SqWS999/H2Nj4xq7xsPDw/Hx8UFLS0sSVrW0tKyRbYvQaDTk5ORw9epVFAoFGzdurJAtVB0qh6ysLMlWtSpIT0+v8xCuAuqI8AuGXC7HwsKCpKSkMomwgYEBCoWiXMJXEYgEc/Xq1fTu3btWCxtoa2vTu3dvtm3bxrvvvlvqWOVyOXK5HIVCUeaDw9vbm6tXr9K0aVMUCgUFBQVlLnrlcjldunRh586dUsYDHpdg9+7dm59//plp06bVGlVEQRDo0aMH33zzDc2bN5f6jMT+6U6dOrFx40bGjBlTq891bYGYTd+9ezfp6emYmpqyefNmXF1dCQsLY9OmTUydOrVKcykSQ3t7e/r27UvPnj2JiYnh1KlTzJs3DyMjI0JCQggODi5GKJ83ntynrq4uTk5OODk5ERISAjxekObk5JCZmUlqaiqRkZGcOXOG5ORkcnNz0dHRwczMDCcnJ4kg29raoquri5aW1nM9LrGcODMzk1GjRpGbm8vcuXPp0KED7dq149KlS5JAX02PScx+zpo1i1WrVrF69Wpee+019PT0pMzSgQMHCA4Olkqyxft2xowZ/P7778yfPx9PT09u3brFzJkzy1XBFUnwd999R+/evWnSpEmNHpN4/fr5+fHhhx9y5swZFi1ahJ+fH7169ap0sO3JZ+uIESPo2rUrhw4d4osvviAkJITOnTs/0xK/xMREHj16xJgxY2rFYl4kw8OGDWPLli0sWrSICRMm1Chhehmh0WjIysrizz//JDw8nEGDBkkWQRWFQqGQMrFjxoypsCCeWCHz2muvSZ9/8OAB8fHxeHl5kZOTg1qtLtN7OioqisDAQO7fv8+qVato0aIF3bp1q9H1g+hn3L17d+AxKfb09KzR4I6oFr1gwQJsbGyws7OrC64/I6SlpWFqalqlUnONRkN6enqpCuZ1KB91q+MXDFGtMykpqRj5ehK6uroYGRmRlpaGo6NjtfZnZWVFQUEBOTk5tT5y5OPjw969e7l58yaBgYEl5kYul6Onp0dubm6pyoxiZmb37t1oaWlha2vLw4cPpWxvafD19WXr1q1ERkYWE9Vp3bo1ly9f5tChQ3Tp0qXWvARMTEx45ZVX2LNnD8OGDZMWjoIg0KxZM65evcq5c+do0aJFrRlzbYahoSGNGzfm+PHjWFtb8+jRI6ZPn46WlhYHDx7k1q1bBAQEVGsuxUWvu7s7bm5uFBYWEh8fz4ULF1i+fDkAAQEBNGrUCDs7OwwMDGrNuZPJZJiYmGBiYoKzszMNGzZEo9GgVqspKCggPz+f9PR0oqOjiY2N5eLFi5Llhra2NtbW1tjY2GBjY4OjoyNmZmbo6elJlTE1dZziAvq3335jzJgxAKxcuZIZM2awbds2Pv30U9LS0vjkk0+eWZBIFDB766232LJlCwsXLmT8+PGYmpqSnJzM6dOn+eijj0ocs66uLkOGDOHjjz9m+fLlzJ8//6kkWBTG6tWrV5ntHzUFHR0dQkNDCQkJ4ciRI/zvf/8jNDSU9u3bV6m8WQwADB48mC5dunD8+HHmzp2Ln58fXbp0wdbWtkYJsUajYf/+/bRt27bWlSBraWkxYMAADhw4wPz583n77berbKXysqOwsJBTp06xZ88eWrRowccff1ypZ6Fod7dmzRp0dXV5//33MTU1rdD3VSoV27dvp0ePHhKp1Gg07NmzB1dXV6ytrbl48SIuLi5lPj/i4+MRBIF79+7x2muv4evrW+OBnaysLFJTUyWxt4sXL9K2bdsau17UajU3b95k7dq1ODk5YWxsTHZ2dl0P6jNCWlpahWy/SoMYsKiIBV8diqOOCNcCPM0GSCaT4ejoSFRUVLWJsK6uLu7u7uX2y9YWaGlp0adPH9avX4+fn1+JSKpMJsPW1pb4+HgcHBxK3Ya5uTkKhYLc3Fz8/PzK9PwToa2tTdeuXdmxYweTJ0+WHvhyuZzXX3+d//3vf/j4+NSa0nJBEGjTpg3ffvstUVFRxdRPtbW1GTx4MAsXLsTT07PaYkD/BQiCQIcOHZg9ezYmJibMmjVLWiwPHjyY33//HW9v7xpbQIul0yIp7tOnD2lpaVy+fJk//viDzMxM7O3tadiwIT4+PlhbW9e67L7YQmBoaCiVTHt5eUn+xUqlEqVSSV5eHgkJCSQmJpKYmMjly5elUj6ZTIapqSmWlpbY2Njg7OyMhYUFxsbGGBkZoaurW6n7Ta1Ws379ekJDQ3Fzc0Oj0WBqakpsbCxjxoxh/vz5PHjwgL1799K/f/9n2lelq6vL4MGDOXz4MF9//TXjx49n7969dOzYsdRsUkFBAatWrcLLy4uRI0fyyy+/kJmZSdu2bUtkCjQaDfHx8SxZsoR+/frRuHHj59ZzbmRkJPUz79y5ky+++IJu3brRokWLKt0fYsl0r169CAsL4+TJk3z33Xe4uLjQpUsX3N3da0SUJy0tjRs3bvDJJ5/Uimf4PyF6YJuamjJ//nwmTpyIk5NTrRzrs4BKpSI8PJyNGzdiZWXF9OnTK+3xrFaruXr1Kr/99hudO3eW7p2KbuPu3btkZmYWqxZJS0tj//79DBkyBEEQuHnzZplq7JmZmVy4cIFmzZoxa9asZ5ZBvXXrFvXq1UNHR0cKqLq7u9fItgsKCti5cyeXL19m4sSJREREcO3aNQwNDevEsZ4REhMTq9x+9zS7rjqUjdq1ovqPwsnJicuXL5f5d0F4LJj16NGjci0zKgKxFPD06dM0a9asytt5XvDw8MDCwoILFy6UOHZBELC1tS3XWkosPU9JScHHx4d169Y9dZ/BwcHs2LGDhw8fSqJi4iLttdde48cff6zxPp/qQPRR3bRpE1OmTCkWMLC0tKRPnz78/PPPTJky5YX3w70M0NbWJj4+ntDQUKytraVz7OXlhZmZGefPn6dVq1bPpJxWW1sbW1tbOnfuTKdOncjPz+f+/ftcvnyZgwcPotFocHNzIygoCA8PD6l3Wfx+bYJYTqujo4OOjg4GBgZYWVkREBAgkWTxJy8vj5SUFFJSUkhKSuLs2bOkpaWRk5ODSqWShP6srKxwdHTEysoKU1NTzM3NMTY2LpGh+Ouvv8jPzycsLEwaR8+ePdm8eTOGhobk5eXx448/cvz4cb744gu6dOlC27ZtJZG8moZcLqdjx47Y2NgwZ84c1Go1r776arF9iZ6oy5Ytw9PTk379+qGlpcWsWbP4/vvvefjwIcOHD5eCAqKn8KJFixg6dKgk6PM8IQiPFaFfffVV4uPj2bhxIwcOHKBfv35SCWtVMsRGRkZ06tSJNm3acPHiRdauXYuuri7dunWjQYMGVS6x12g0HDt2jCZNmtRoX3hNQyaT0aJFC4yMjFi4cCFvvPFGhS2wXkaIyuGxsbH88ccfZGVlMXz4cLy9vSuVfdRoNBQUFLBx40YiIiJ4++23JeHDiqKwsJBNmzYxZMgQifCJXuOFhYU0bdoUpVLJ/fv3pZLkJ/cfHh7O8uXLMTAwYPr06ZUO4lUUarWac+fO0bFjRwAiIiKws7Mr1cqpMhCfKytXrsTJyYn3338fQ0NDTp06hUwmw8LCoi4j/IwQGxtL48aNq/RdMehcW1r3XibUEeFaAGNjY7Kyssr9jLu7O+fOnauR/bm7u0uWQLWdGMlkMvr378/y5csJCgoqoaZna2sr+fyW9rIRBAEfHx9u3bpFx44dycnJIScnp1z1X7E/+c8//2Ty5MnSy1AQBPz9/WnevDlr165l/PjxtSI7JwgC9evX58SJE5w/f75YGbQgCISEhHDr1i327NlTwj6mDsVRWFjIihUrGD58OJcuXSp2rchkMgYMGMCSJUsICQmpsrJjRSCSN0NDQxo0aECDBg0k25D79+9z6dIltm/fDoCbmxsBAQESURfJR21eNP9zfGK5tYeHRwk7nby8PDIyMsjIyCAlJYXY2Fhu3bpFRkYGubm5KJVK9PX1MTAwwNraGkNDQ3bt2sXkyZPJzs7G0NAQmUyGp6cnCoWC7777jkmTJmFqakqvXr1o2bIlGzZs4MSJEwwdOpT69es/k3tEfH6YmZmRnJzM8ePH6dSpk7Sv2NhYli9fTrt27QgLC5N+b25uzrvvvsumTZv45ptveOutt7C2tiY6OpolS5bw6quv0qBBgxcuTmZvb8+kSZN48OABmzZtYs+ePQwYMAAfH5+nChOVtU09PT1atmxJs2bNuHPnDrt372bTpk106NCB5s2bV7ptIDc3lzNnzvDee+9V9hCfOwRBoEGDBrzzzjssX76cbt26ERoa+q/Lxon97du2bSMiIoKePXvSvHnzSgc7RJ/tVatW4evry/vvvy/15FdmG8ePH8fOzo569epJ3y0sLOTw4cN4enri4eFBbm4uKpVKqujQaDQoFAp27tzJhQsX6NWrFxcvXnxmJBgePxcTExOlKrBz585VSxtAo9FQVFTE8ePH2bt3L0OHDi2WEU9ISEBPT6+uP/gZojpiV2q1GpVKVUeEq4AXv4qvA0ZGRuTn55erCm1mZkZmZma5qscVhZhJefToEV5eXtXa1vOAvb099evX59ixY8XUkeGxcvKxY8fKJcLe3t7s3buX7t27Y2NjQ3R0dLnl0YLw2Mt49+7d3L9/Hy8vL2nborfskiVL2L9/P926dasVLwW5XE7fvn1ZunQpDRo0KEb0RQK3YMECvL29y+xF/69DpVKxZcsWLC0tGThwICqVioMHD9K3b1+JuDk6OuLr68uhQ4fo2bPncytDFf+1tbXF1taWli1bUlRURFpaGpGRkdy4cYO9e/dSVFSEjY0N3t7e1K9fH1tbW/T09F6Y+FZV8M9xiiXX/2wLESPg+fn55OXlkZeXR2RkJMuWLaNFixYcP36c7du3SyKDurq6PHz4kOTkZGJiYlAoFFhbW2NkZMTrr79OREQEv/32G7a2tgwcOLDS5ZhPg0aj4e+//8bOzo5Zs2axevVq4uLiGDp0KA8ePGDdunUMGTKkhEewIDxWwB46dCinT5/m22+/pV27dhw5coQ33nijXM2D5wnxHvH09GTGjBncunWLTZs2oa+vT//+/XFzc6vSu0sQBLS0tPD398fX15eYmBgOHDjA/v37CQoKon379tjY2Dx12xqNhpMnT+Ln5/fSLObFajCxKiApKYk+ffrU+gB2RSD2NO7bt48rV67QoUMHRowYUekAo0ajobCwkH379nHq1CmGDx9OgwYNKh3MEv23Dx8+zMyZM4tlg8PDw1EoFPj4+KCrq8v169dxcXFBR0cHjUZDbGwsq1evxt7eng8++IAbN25gY2PzzK4xjUbDrVu3cHd3R19fH6VSSUREBL17967y9qKjo/nll18wMjLi/fffL9ZrKqpGC4JQ44rUdXgMtVpNVlZWlUubCwoK0NLSqiPCVUAdEa4FMDQ0RFtbm8zMzDIfMqIISXZ2drVFrmQyGQ0bNuTSpUsvBREWhNLVkeFxJkksnyzrxefo6EhycjIKhYLAwECuXbv2VGU9LS0tqdx45syZxR4uou/j//73P9zc3GrNQtTGxoYWLVqwffv2YsJZ8Nim69VXX2XlypVMnjy5WEltHf4vExAVFcWUKVOQy+V0796dOXPm0KZNG+m+lMlk9OrVSxIIMjc3f2FjFsuobW1tadasGUqlktzcXOLj47l9+zZbt24lNTUVXV1dXFxcqFevHvXq1cPMzAwjI6OXvjJALCXX1tbGxMQEpVLJoUOHeOONN+jevTuC8NgiSaFQoFAoePDgAYsXL8bQ0JD79+/z4MEDUlJSpCCkuL2//vqLHTt20KNHD0JDQ7GyspIEvfT09KpcPp2RkcGuXbuYMWMGFhYWvP3222zcuJEpU6agp6fHtGnTcHV1LXPbcrmcli1bkpuby4cffsjQoUOLBelqE7S0tGjQoAE+Pj5cu3aN1atXY2trS+/evXF2dq7ytSeTyXBxcWH06NFkZGRw5swZlixZgrm5OR06dMDX17fMLFxhYSFHjhwppv3wMkAQHiuQT5s2jXXr1rF8+XLeeOON52Iz9SwgZoD379/P1atXCQ0N5eOPP65Sq5FGoyEqKoq1a9diZ2fHBx98UOV5UalUrFu3jh49ehRbY4gBUUtLS5o0aQLAjRs3CAgIQKlUcuzYMfbt28fgwYNp1KgRcrmcyMjIGuvVLQunTp2SWj+ioqIwMjIqNu6KIi8vj/3793P69GkGDBhASEhIqUGlvLw8ZDJZndbIM0JeXh5KpbLKRDg9PR0jI6M6IlwF1BHhWgBRKCYtLa1MIqytrY2VlRVxcXE1ovYcEBDAjz/+iFqtfikWBaampoSGhpZQR9bR0UGlUpVbEvKkV7Ovry+rV69+6nGLZYwHDx7k4sWLJYTFTE1Neeutt1i6dCmzZs2qFf7CgiAQFhbGvHnzJP/lJ//m7OxMt27dWL16NZMnT651iqkvCqLNzqFDh3j33XelhbSZmRlt27blzz//ZNSoUdL5t7CwoHXr1mzfvp2RI0fWisWoSOLMzMwwMzOjfv36UqlbRkYGkZGRREREcOLECalc2NHRES8vL5ycnLC2ti611/ZlgUaj4ciRIxQWFtKlSxfpOESirKOjw6FDhxg/fjzJycnk5OQwePBgSfFapVKhVCpJT08nNTWV5ORk7t69y5QpUzAwMJCUwmUyGYaGhpiYmGBqaoqVlRV2dnaYmJhImWsjI6MSGXi1Ws3WrVsJDQ2VnhUymQwtLS1kMhkymQyVSvXUY7x06RJHjhzhl19+4ejRoyxcuJAxY8ZUaQH8PKCjo0OjRo1o0KAB58+f54cffsDBwYE+ffpUSwBK7E3u0qULYWFh3LlzhwMHDrBx40aaN29Oy5Yti6ktazQaLly4gJOTk+Tt+jJBEAQMDAwYPXo0Bw4c4KuvvuKtt94qN3BS26DRaEhISJCcINq0acPHH39cJaVxeJwB27NnD6dOnZJ65KtaLafRaDh8+DA6OjrFWos0Gg0RERGoVCoUCoWkbxAREUHjxo357rvvkMvlvP/++8XUfuPj42nYsGGVxlIR5OTkkJSUJGmYXLp0iZCQkErNo0ql4urVq2zcuBEvL69ygwj5+fmS4KG1tXWNHUcd/g9ZWVlSoLUqEC0fX5bnQW1CHRGuBRDLTVJTU8vM0AqCgIuLC48ePaqR0lY7OztUKhVJSUkvxcJAEB6rI3/11VckJCRgb29fTIgnJycHPT29Ur+rpaWFu7s79+7do1mzZhQUFJCenv7UEh+5XM6gQYNYtmwZgYGB6OvrFytTdXd3p2/fvvzwww/MnDmz0v1IzwI6OjoMHTqU3377jenTpxfzVxYEgaZNm/Lo0SM2b97M0KFDX1riU1MQ+27XrFnD+PHji5VMCoJAu3bt+Oyzz4iJicHZ2Vn6fadOnfjkk0/KVSx/kRDLVHV1dbG1tcXGxoZmzZqh0WhQqVQkJiYSFRVFREQEJ0+eJCMjQwq2eXl54eLigr29vSSMUlsFueD/AhknTpwo1XNco9Fw4sQJDAwMaNKkCVlZWXz55Zf07NkTIyMj5HK5tPgwMjKSznOHDh0YOHAgGzduJDo6mr59++Lt7S35KGdmZpKSksLFixfJysoiJyeH/Px84PF9aGhoiLGxsaT0ffToUWbPnk1qaioymYw1a9agr6/P/PnziYqKYvny5QwcOJCmTZuW6KEWy3p3797NlClTsLOzw8vLi8OHD/PVV19Vyh/1eUO8Dlu1akWTJk2kLK6Liwt9+/aV7p+qjF18BwQEBODv709ycjLHjh1j3rx5WFpaEhYWhr+/P3K5nL179zJ69OiX+pmnra1Nt27dcHZ2ZvHixQwYMIDmzZvX2mMSxfAePXrE7t27iYqKol27dgwePLhKtnCifsD9+/dZu3Ytzs7OVc4mP7nN+/fvc+jQIT788MNizw+NRsOuXbto2rQpJ06cwNTUlJSUFG7evMnKlSvp27cvr7zySrFnpFqtJi0t7Zna2Fy7dg1PT0+pLPrGjRuMHz++QscKj4n6b7/9Rl5eHm+++SYeHh7lzl9GRgZ6enpoNJoy11l1qB4yMzOrpficmZlZ6y1RayvqiHAtgbOzM9HR0TRv3rzMz3h7e3Ps2DG6dOlS7f3JZDJ8fHy4efPmS0GEAfT19enZsyebNm3inXfekXrHLC0tSUxMLPPFIwgCvr6+XLt2jZYtW+Ls7MyjR4+eSoQFQcDJyYmgoCD+/PNPhg4dWuLvrVq14tGjR6xfv57XX3/9hYtniQTdy8uLgwcPluhjFXuJFy9ezN9//01oaGitXDw/L+Tm5rJs2TIGDBiAm5tbqf2pvXv3ZsOGDUyfPl1acBoYGNC9e3e2bt3K+PHja72AzZNEViaT4eTkhJOTEy1btgSQ+o2Tk5OJiIjg+PHjJCUlUVhYiKGhIfb29ri5ueHk5ISjoyP6+vrI5fIqqQLXJMS+vnXr1kkevf/8e3x8PAcOHGDWrFnIZDLMzMzw9/fn1KlTdOzYsczxC4KAjY0NEydO5MGDB2zevJl9+/YxYMAAfH19SyXcarWavLw8cnNzyc3NJScnh9jYWKlveceOHTx48IB79+5hampKQEAAS5YskQIQc+bMoXfv3nTs2BFzc3PJW/nYsWP8/fffTJ8+XXrOiUrU7u7urFq1irZt29KxY8cX/gwqCyIhbtOmDc2aNePMmTMsXrwYNzc3evfujZ2dXZUJnRg4sLW1ZfDgwfTp04fbt29z7NgxNm7cKIkaOTk5lakn8bJAFNF67733+P7777lz5w6DBw8uFqh90RDFo27evMmePXtQKBR07NiR0aNHVzlgLPap/vnnn9y8eZNhw4YREBBQrSCARqMhPT2dVatWMWrUqBJ2ZpGRkSgUCrKzswkKCiI9PZ0FCxZga2vL+++/X6qOQG5uLgqF4pm1zWg0Gk6dOkWvXr0QBIHk5GSAp5Ysi8e6c+dObty4Qc+ePWnRokWFMpDp6emYmJhIrTZ1qHmICZ6qQDy3L7JV62VG7Xxj/gdhZ2fH3bt3y/2Mra0tSUlJNfYib9SoEbt376Zdu3a1NqL8JEQRq+PHj3P9+nUCAwMRBAFra2vpZVAW3N3d2blzJ2q1moYNG3L16tUSojSlQewJ/fzzz2nevLlUivTk3wcMGMDixYs5dOgQnTt3fuGLEbGnesGCBTRs2BBnZ+diY9LV1WXMmDEsWLAAMzOzF644+6JQWFjIypUradKkSbn+q02bNuXAgQPcunULf39/4PEct2zZkkOHDvHgwQM8PT1f6jl8st84ICAAQOo5zsnJIS4ujocPH3Lw4EGSkpIkSyN7e3scHBxwdnbGwcEBAwMDdHV1n5kN0T+Rk5PDihUrGDhwoJTJfRJFRUX8+uuv9OvXr5hXcMeOHSWF5qctBAVBoF69ekyfPp07d+6wdetWtLW16d+/Px4eHsVU5eVyOcbGxpJYnVgO2q1bN8aNG8f169f55Zdf+Oabb/D09KSwsJD8/HySk5NJSUlhwIABXL9+ndWrV9OwYUP09fWJjY0lOjqajh07snPnTszNzTE3N8fS0lL6efvtt/n111+5d+8er7/+eq2xdisLenp6tGnThqZNm0oZYkdHR3r06IGzs3O1A0u6uroEBQURGBhIcnIyM2fOxNjYmDlz5tC4cWOaNGmClZXVCw/kVBXie2/mzJn8+eefzJ07l9GjR1faKqimIWZDT548yZkzZ7C2tqZfv354enpWS+CrqKiIS5cusXnzZpo0acKHH36IoaFhtY5Vo9GQn5/P999/T1hYGPXr1y/RzrBz5046derE9u3b8fT0ZO7cuSQkJPDuu++WmUDIzMzEwMDgmQWkUlNTyczMxN3dHY1Gw+XLlwkKCipzLjQaDdnZ2Rw6dIhTp07xyiuvVLokPSUlRSrb/TcItdVGxMTE4OLiUuXvJyYmSj3sdagc6ohwLYGFhQVpaWnlklxLS0uKiopqxDRbEAQ8PDxITk5+qUy4tbW1GThwIKtXr8bHxwc9PT3s7OxISEgod+5MTU0lVb769etLUeqKRDeNjIwYNmwYq1ev5v333y+haqmnp8fYsWOZO3cutra2L8TP858wMDBgwIAB/Pbbb5IYz5MwMzNj3LhxfP/995iZmZUgy/92KJVKNmzYgLm5OV27di03EKSlpcXgwYOlXipxIaCjo0O/fv3YsmVLqSW5Lzu0tLQwNTXF1NQUR0dHmjRpIvUdKxQKcnNziYmJITY2ltOnT5OQkEBhYaHk3W1jY4OjoyPOzs6YmJhgZGSEgYFBjQXdCgoKWLVqFU2aNCn1nhP7/szMzIrZgMBjtXlTU1PCw8MJCgqq8Hz4+/vj7e3N9evXWbduHebm5vTu3Rt3d/cSxyWq4h44cIDp06eza9cuzp8/z7Rp03B0dCw2nicDbEqlkoMHD7J//37MzMywt7fnu+++Iysri9TUVDIyMoiJieHq1aukp6ejUChQKpUUFRVJi93WrVtLfss2NjYYGBigp6eHvr4+enp6tYIAin2v7dq1o0WLFly6dImVK1diYWFBjx498PT0rDYhFgSBtLQ03NzceO+990hNTeXs2bMsXboUXV1dmjRpQnBwMNbW1i9FMPhJCIKAvr4+gwcP5sqVKyxZsoSuXbvyyiuvPFfBHJFQ3r17l2PHjhEfH0/jxo2ZOnUqlpaWVbLOenLb0dHR/P7776jVaiZNmoSjo2O1z5WoNP3jjz/i5eVF+/btS4zx7t275ObmYmBgwN9//42pqSlTp05l8eLF5QphpaSkPNM+2itXruDv74+2tjYqlYrLly+XqlWh0WjIysri+PHjnDhxgoYNG/LBBx8UCwhWFNHR0RgaGmJqavqve8/VBogtWv98T1UGdRnhqqPuiq4lMDc3Jzc3t1xvXy0tLczNzUlOTq4R4qqrq4uDgwOPHj0iMDCw2tt7XnB1dZX647p164ajoyOXLl0q9zva2to4Ozvz4MEDgoKC0NbWJi0trcKlKIGBgVy9epVt27aV2ltramrKxIkTmT9/PpaWli+cWArCY/9kDw8P9uzZI1kAPfl3R0dHhg0bxo8//si0adNeGkuR6kKtVnPgwAFSU1OZOHHiUxdVgvDYp9nIyIgLFy5IYiqCIBAYGMi+ffu4efOmVKHwb8aTfflGRkbY2toSEhICPBZfEUuDExISSExMJDY2VuqhLSgoQE9PDzMzMywtLXFxccHGxkYS+Cotw1PafIolyBs3bsTKyqqYF++Tn3n06BF///03s2bNKkGo5HI5nTt3Zv/+/ZU+b9ra2gQHBxMQEMClS5dYvXo1FhYW9O3bVyqvFwQBjUbD77//TosWLdi4cSMymYz33nvvqZkYuVxOaGgohw4d4uTJk5IY35PPKrHXT61Wo1arpQBFZmYm9+7d44cffsDGxobAwEDOnDlDXl4eBQUFkpWUgYEBxsbGmJiYYG1tja2tLcbGxhgZGUn/lrbgfRbXt0joWrZsSZMmTbh69Srr169HT0+PXr164evrW2UypVKp2L17Nz169EBXVxdHR0f69u1Lz549iYuL49SpUyxcuBAjIyMaNmxIUFAQ9vb20vX0MtzPMpmM4OBgXF1dWbNmDZcuXeL1118vJhZW0xDvwUePHnHy5Elu3ryJjY0N7dq1K1e5uzLbz87OZseOHVy9epV+/frRpEmTGgngiCT4hx9+wMzMjL59+5Z4PhQVFbFx40bkcjnvvvsu/fr1Y/z48cTExGBkZFTu+isyMrJE5VhNQaVSce7cOYYNGyYFeRQKhSTAJz4XsrKyOHz4MCdPnqRhw4bMmjWrWk4R4przSUGwOtQc1Go16enp1eorz8/PL6YJU4eKo44I1xKImZLs7Owye1cF4bGn4MOHD/H09KyR/TZt2pTz58+/VOWxgiDQu3dv5s6dS9OmTTExMSE7O/up3/H39+fmzZuEhITg5+fHtWvXsLOzq9BxC4LAwIEDmTNnDteuXStRiiT2E48cOZJly5bx3nvvVSnyWpOQyWT07NmT+fPnExAQUMJqRRAE/Pz86NatG4sWLWLatGkvTWVAVaHRaDh//jznzp1j2rRpUg/m0yAIAoMHD2bp0qU0bNhQqgrQ0tJiwIAB/Prrr/j6+v4ny8bE+ROJk46ODmZmZvj4+BT7nNiHLCozR0dHc/36ddLT0yVrDiMjI8zMzHBycsLW1hZra2usrKwkuydxX9u3bycrK4uxY8eWGsgoKChgzZo1DB8+vJin9pPw9/dnw4YNVRI8EwMCzZo1o1GjRly8eJFVq1ZhYWFBv379cHV15ebNm1y8eBELCwvat29Ply5dnrqQ12g0ZGRksGjRIlq3bs27777Ljz/+SFxcHAMGDJAqWMRtiH3a4ryL/dyBgYGsXr2a7Oxsxo4dK/U+KpVKcnJyyM7OJisri+zsbJKTk7l27Zok+JWXl4dKpUJHRwd9fX2MjIywsbHB2tpaClqYmZlhYmIiqWM/Ke5V1WeeOKeNGzcmODiY8PBwtm3bxsaNG+nSpQuNGjWq8P0qzmVMTAypqanFgh2C8Fhh3cXFBRcXFwYOHEh0dDQXL15k5cqVKJVK/Pz8aNy4MW5ublKZf21+PwrCY4ulKVOmcOLECb766iv69u1Ly5Yta0y/QBTai42N5dy5c1y+fBk9PT1atGhB9+7dpWxUdQmwQqHgxIkT7Nmzh+bNm/Ppp59WSVirrO3n5OSwbNkyHB0dGTJkSLHsuSjudfz4cfbv38/IkSMJDAyka9euaGlpcf36dal1pKztx8bG0rp162dyvSQnJ1NYWIizs7NUFt2gQQO0tLRQq9UkJydz4MABrly5QqNGjfjggw+qHeAWn0nGxsa1Vp3+ZUd+fj4FBQVVzuhqNBoKCgrqiHAVUUeEawkEQcDIyKhcIgzg5eXFxYsX6dChQ43s09/fn127dlFYWPhSqQEaGxvTpUsXtm7dyqBBgyQv0PLKdurVq8ehQ4cACA4OZsuWLXTo0KFCCwUxa/Hmm2+ydOlSHBwcsLa2LkEsGzZsSGpqKsuWLWPatGkvXMBEX1+fESNG8PPPPzN9+vQSpEAQBJo3b05BQQGLFy9mypQpZRKHlx0ajYY7d+7w559/MnXq1BLCKOVBzKB7e3tz9OhRunXrJi2OPT09sbS05OzZs89sAfQy4p/zoKOjg52dXYneOjGbmZ2dTU5ODhkZGURHR3Pr1i1OnDhBZmYmSqVSInpqtZorV65IGRoLCwt0dHSQy+XS/b9p0yYaNGhQou/vSWhra/PKK69w+PBhRowYUaXzJpKqZs2aERISwqVLl/j555/R09Pj/PnzaGtr8+677+Lv7//U7YvEbdmyZXTp0kVSo50xYwbr16/nu+++Y+zYsU9d2ArCY2uhSZMmceDAAebMmcMbb7yBj48P2traUo9xWVCpVOTn55OXlycJfyUnJ5OUlMTDhw/JzMwkOzub/Px8SXFbX18fKysrLC0tMTdKuWA0AAEAAElEQVQ3x8LCAktLS6mUUjw3FcnsCsJjEcTAwED8/f2JjIxk7969bN++nVdeeYXWrVtXyCtWo9Gwc+dOunbtWmqp8JMBHHd3d8kFIDk5mfDwcHbs2EFaWprUN+/v7y9da7XxHhfnrW3btvj6+rJ27VpOnz7NiBEjJJeFykAkhfn5+URFRXHx4kXCw8MxMDAgJCSEd955B1tb2xopKddoNJL68ZYtW7C3t2fmzJmlilFVZx+pqaksXbqU4OBgevToUezdL/59/fr17Nq1iyVLluDq6sq8efNwcnJCrVZz7do1hg4dWuaYRCeOZ+EkIAZxGzVqhEwmQ61Wc/HiRQYPHsz9+/fZs2cPcXFxhIaG8tFHH9WYlY5CoSAvL4/8/PwqiznVoXzk5+ejq6tb5XtJdCuoI8JVQx0RrkUQ+4Td3NzK/IyjoyO7du1CpVLVSKRXLIWLj49/5gbwNQmRwJ09e5aHDx+ipaVFZmZmuUEEa2trioqKSE9Px97enszMTPLz8zEyMqrwPl1dXenVqxcrVqxgxowZJYIHgiDQrl07UlJSWLNmDWPHjn3hBueurq40b96cDRs28MYbb5QIFshkMtq2bUthYSHLli1jwoQJlSKJLwtiYmJYvXo1EyZMqFIPlyic9vXXX9OqVSvJqkAul9O/f3+WLFlCo0aNSvSQ16F8iJlAUfjJ1dVV6tsVF8gFBQXk5eWxZ88ezp8/z+DBg4mMjOT8+fNkZmaiVquBx88zcUE9duxY7t69i5mZGXp6eujq6kqEWdxv69at+fLLL8nOzq7WNf9khtjLy4vZs2eTlZVFcHAwhYWFKBSKcgmURqPh+vXr/PrrrwwfPrxYBtPAwIBRo0Zx7Ngxvv76a0aNGlUhqyTRasfLy4s1a9bQokULunTp8tSqBblcjpGRUZnPRbEsVqFQSMeWn59PUlISqampJCYmcvv2bdLT08nJyZHKNQ0NDSWSbGFhgbW1NdbW1ujr60vnRkdHp9hiUC6X4+npycSJE0lKSuLw4cN8+eWXNGjQgA4dOmBra1vmezAhIYHY2FhGjx5dYUIgl8ulYE3btm0lobhr167x008/kZ+fj5OTk1RhY2Ji8sKDnf+EIAjY2dkxbdo0zp49y4IFC2jdujWdOnV66lhF4puWlkZ4eDg3btwgOTlZ0r7o3Lkz5ubmNdonqlQquXfvHlu2bEEul/Paa69Rr169GlXi12g0REVF8f3339O5c2fatGlT7DorKCjg2LFjHDhwgOzsbN544w0aNmzI4cOH8ff3R1dXl/T0dLKzs0sV5RORn59PYWHhM7GxKSoq4uLFi0yYMAF4bIF05coVcnJy0NfXp2PHjgQFBdW4jWNOTg4ymYzc3Nw6D+FnhOzs7Cr7acP/eRD/FyvSagJ1RLgWQbRQEnvuSoO1tTX5+fnk5ubWCFkR+4suXLhQqn1MbYa2tjaDBg2S/DiTk5PLJcLa2to4OTkRGRlJSEgIzs7O3Llzp1JG9ILw2DLp/v37bNy4kREjRpSI4snlcvr168eKFSvYsmULAwcOfKH2OoIg0KFDB1asWMFff/1Fu3btShyvTCajc+fOKJVKlixZwsSJE/9V5uzJycl8//33vPbaa7i6ulb5uKysrGjZsiU7d+4slkV0cnLCx8eHw4cP06NHj3/NvL1oiBlXuVzOhQsXePToEXPmzMHc3FzKWCmVSlQqFUVFRdy+fZvvv/+eESNGkJyczPXr18nMzEShUKBSqSTBF7FP2c7ODj09PY4fP05oaCgGBgZVVrzWaDRERkby7bffkpyczB9//EFKSgo7d+5k27ZtdOzYkcaNG5co81Sr1Rw/fpwDBw4wceLEUpV/5XI57du3x8nJidWrV9O+fXvCwsKeSkgEQZCI+bp161i0aBGjR4+uVrmkIDxWx9bX1y+WgXB1dS02F2q1GpVKJZ2frKwskpOTSUtLIy0tjYcPH0qlngqFAkEQpPMjqmLb29tjamqKoaEhRkZGDBkyhJ49e3Ly5EmWLFmCpaUlHTt2pH79+sWED0X/1w4dOlS50kkmk2FiYoKJiQk+Pj6oVCry8vJ48OABN27c4NixYxQUFGBtbS1Z1ok977VBjExbW5tWrVoREBDAli1bmDNnDgMGDJBKaeHxtSeWx9+9e5d79+6RlJSEvr4+9evXp3v37jg5OUkEuiaPSaVScf/+fbZv305OTg79+/fHz8+vxsWYNBoN165dY+3atbz22mvF2ppUKhU3b95k06ZN2NvbM2zYMLZu3UqvXr0AOHPmDMOHD0cQBB48eICbm1u548vLy0NXV/eZvO+jo6PR1dUlMzOTXbt2sXv3bjw9PRk7diyOjo5Sm0JNIycnB0NDQ/Ly8uqCvM8IsbGxODg4VPn8ZWZmVqhKpg6lo44I1xIIwmMPxCtXrpSrfizac4gXfk3st2HDhixfvpy+ffu+VIqAgiDg7OxMQEAAf/zxB23atKF+/frlficoKIirV68SEhJCkyZNuHDhQrmBh9Igl8sZMmQIc+fO5dSpU7Rq1arUMtDRo0ezYMEC9u/fT9euXV/oQ0oulzNixAjmz5+Ph4dHqWRQJpPRvXt39PT0WLBgAVOmTHnpBbRE5cxly5bRs2fPCpWolgdBEOjYsSOfffYZHTp0kErFBEGgT58+zJkzh9DQ0Dpj+xqCSHaPHTvGX3/9xeTJk6W5FRfmOjo60ucOHjzI5MmTi2WUxZ+ioiIyMjJIS0uT/r18+TJqtZpvv/2Wo0ePIpfL0dPTkwiQnZ0dtra2mJqaYmJigqmpaan9iiqViiNHjrBnzx7y8/OZPn26lOH28vIiJiaG3bt3s2vXLpo1a0b79u0xNzdHqVSybds2bt++zYwZM8q93wRBwNvbm9mzZ7Ny5Uru3bvHG2+88dT+SUEQMDY25q233uLYsWPMmTOHkSNHVtuDtTyIZFkul0tZCmNjYxwdHYH/E/V58vwUFBSQkZFBenq61Ed+5swZMjMzyc3NpbCwEC0tLYyNjTEzMyMkJITMzEx++OEHdHR06NChA6GhoZiampKSksK9e/ckElMTx6OlpYWJiQlBQUEEBQWhVqspLCwkJiaGyMhIjhw5QnJyMiqVCgsLCxwcHHB3dy/W5/7PsTzLZ6s4x6amprz++uvcvXuXFStWYGRkRPPmzYmJiSExMRGFQoGFhQVeXl507twZFxcXqUyzpscnnuv79++zbds2srOz6d27N0FBQTVO5MRgzKFDhzh06BBTpkyRRCxFW7Pff/+dzMxMRowYgYuLC3PnzmXIkCEYGhqSkJBAQUEBrq6uaDQaLly4QKNGjcrdZ3x8fLX8sEs7BkAq2b558yaFhYWEhobi6+vL6NGjy60grAlkZGRgampKTExMHRF+RoiPj69W2XlWVta/Xt/lWeLlYT3/Adja2pKcnFwuERbLcyMjI8st0akMRDXBlJSUMr3xaitkMhldu3Zl27Zt3Lt3j1deeaXcz3t5ebFv3z5UKhX16tVj8+bN5Sp1lwU9PT0mTpzI3Llzsbe3x8PDo8Q509fXZ9KkScydOxdjY+MX2j8qCAImJiaMGDGCNWvWSP3CpZHhsLAwdHV1+eabb3jnnXeqFal8kdBoNOTl5fH999/TunVrmjdvXiPHYWRkRLdu3di0aRNvv/22tOixsLCgZcuW7Nmzp9w+sjpUHBqNhr1793Lx4kWJBJc2r2q1mg0bNuDv719CGEmElpYW+vr60oJDXGSqVCq+/PJLRowYga2trSQklZWVRUJCAjdu3CAzM5OsrCzy8/PRaDSSFZGpqSlWVlaEh4cTFRVF+/btuXfvHsHBwSiVSolMuLi4MH78eNLS0jhy5AhfffUVrq6uZGVlYWRkJLVZVKR/1tTUlClTprBr1y6+/PJLxo0b99QqB5HIhYWF4enpyY8//khAQAD9+vWrtsJvVVDa+RHLsZ2cnID/Oz8ilEolmZmZZGZmkpGRQVxcHKmpqTg6OnL//n2+/fZbFi1aRGhoKIWFhbi5uUmVAmKGtqZIMTwOLhoYGODt7Y2XlxedOnUCHmfQkpKSiI+PJyIiglOnTpGeno4gPLaLEsXHLC0tMTMzw9TUtIRS95NjLW3M/wwkiPOTnZ1NdnY2mZmZpKWlkZycTHJyMjk5OeTn50tlzT///DO2traMGzcOPz+/Yu0CzwJi5cadO3fYsWMH+fn59OrVi4YNGz6TTKYYWFm/fj0pKSl8+OGHUuIgIyODXbt2cfnyZXr27EmrVq2Qy+X88ccfuLu7S2JYYpBcJpNRUFDAw4cPJbXmshAVFVUtL1hx7KKo19WrVzl58iQJCQlERkZKgey0tDSOHz8uBZaeJaKjozE3Nyc2NraOCD8DaDQakpKSytWzeBpSUlKqpTj9X0cdEa5FsLa2Jisri8LCwjKb3gXhsf9vREQEoaGhNfICEf0xL1++TJcuXV66BbyhoSETJkxg1apVvPrqq+WSWvFhkZqairW1NRYWFkRGRpZQuH0aBEHA2tqaUaNGsXLlSmbNmlVikS5mYqZOncq8efMki44XSYa9vLwIDQ3lp59+YuLEiaXOlUwmo3Xr1hgbG7NgwQJeffVVAgMDXzqfzcLCQlauXImvr2+pPpFVhVgef+jQIR48eCApuAuCQOfOnfn8888JCwuTLC3qUDUoFAq2bNlCVFQUU6ZMKbMCRswY5+TklNqqUBaeJDRt27bl6NGjjBkzBmNj41LFbkRFW1HhMycnhxMnTvDLL7/QunVrfHx8WLlyJYGBgXz22WeSkJRIlsX+WH9/f+rVq8eXX36JTCbDx8eHK1euEBgYWCF1XLFcvE+fPnh4eLBs2TJ69epVIYVgMZD6wQcfsHnzZubOncvo0aNxcnKqdc/9f45HW1sbKysr6RkuZufE85KTk0NWVhanTp1i/vz56OnpsXHjRurXr4+LiwseHh64ubnh4eGBsbFxjWY9n9yGsbExxsbG1KtXj9atW0tqy6LwWE5ODikpKaSmphIXFyeJxBUUFCAIAjKZrNiPIAiSRRYgXd/idp+00NLT05NssczMzPDy8qJ58+ZSkEFcVxQUFHDy5EnWr1+Ph4cHPXv2rLCDQmUgEtIrV66wf/9+dHR06N69O35+fs9MO0Oj0ZCYmMiPP/6Ih4cHU6ZMQVdXl+zsbI4ePcqJEydo0aIFn376KcbGxmg0Gi5dusStW7eYPXs2MpmMoqIiLly4wLhx4xAEgfj4eExMTDA0NCx3vzExMbRs2bJK86hSqcjOziY8PJxTp06RnJyMl5cXvXv3JiUlhVu3blGvXj0EQeD8+fMEBgY+l57QpKQkDA0NMTQ0fOF6J/9GqFQqkpOTq5WEio+Px8/PrwZH9d9CHRGuRRCFQp4mg+7m5sbRo0dRq9U10osiCAKNGzfmt99+o0uXLtXe3ouAt7c39+/f59ChQ+WWIQvCY5XfiIgIbG1tadKkCWfPnq00ERa35e/vT9u2bVm1ahWTJk0q1qcmfsbKyoq3336bxYsXo6enV63IX3UhinnFxcWxZcsWBg0aVOo1JJPJaNiwIZaWlvzwww8kJibSvn37l+ZFqFAoWLNmDTY2NnTv3r3GSbyOjg79+/dn8+bNTJ8+XZoXIyMjOnTowI4dOxg9evRLFzyoLcjJyeHnn39GLpfzzjvvlJmJ0Gg0hIeHc/z4caZPn16lhaEgCISEhLB7925ycnLKVE0XBAFdXV10dXXJzc1l3759PHz4kKVLl+Li4sKvv/7KxIkT6dOnD0qlEoVCgUKhID09nZSUFNLS0oiIiOD06dPcuXMHDw8PTExMiIiIYOLEiXh5edG4cWO8vLywt7fHysoKAwMDaZ9i7+GTmcLAwEBmzJjBypUriYiIYMiQIU9VDhV7cUeMGMHly5dZtGgRXbt2pU2bNi9Va4yIJ8+LhYUFZ86cYfbs2bRu3Zq//vqLv/76i5iYGORyOYmJiezdu5fCwkJMTExwdXXF09MTV1dXSVStpp/NT5ZVi8EcLy+vYp95stf9SXIrEtwns+NitvhJsiyWoVc0u6qvr09YWBgtWrTgzJkzLFq0CBcXF7p06YKrq2u1rwONRkNaWhqnTp3i77//xsnJieHDh+Pu7v5M+6dFRfn169fTt29fWrRoQVZWFvv27ePvv/+mYcOGvPfee1IVnGh3tGHDBiZPniz1k0dHR6OlpYWtrW0JteayoFQqSUhIkCoaKgKlUklqairXrl3j4sWLpKWl4enpSZcuXXB3d5eeewsWLJCcClQqFRcuXOD111+v1lxVBKKSthhYqW3Bsn8DioqKKCwsrLBoa2nIzMysK42uBl6+t96/GDKZDAMDA3Jzc8u1t7CyspIiyOVFKCsDR0dHcnNzycjIqLKX2YuEmZkZAQEB7N+/n8DAwHJfRkFBQZw6dYqWLVsSEBDAgQMHJFXXykIUooqOjmbTpk0MGzasxMtSEB57DL/11lssX76ciRMn4u7u/sJeKnK5nMGDB7N48WJOnDhBmzZtSh2L2IM9c+ZMVq1axZ07dxg5cmStF2UoKipi3bp16OnpMXDgwGeyuBcEgaCgIPbu3cvNmzclARZBEAgNDeXzzz8nNja2xtoX/ivQaDTEx8ezYsUKGjRoQJ8+fcoN9sXFxUkEtDoLAWNjY/z8/Dh79ixhYWFlXt8ajYZ79+6xevVqaVGtp6dHZGQkN27c4JNPPpFImfhsFisDVCoVBw8exMzMjDVr1uDg4IBarUapVJKRkUFiYiLh4eH8/vvvRERESARNJpMVs48S+5Wtra2xtbWVRKT27dvHnDlzmDBhQoXscuRyOY0aNcLd3Z2ffvqJ69evM3LkyJd6wZuRkcGFCxf45JNPMDExYdCgQfTp04eIiAiOHj1KVFQUzs7ONGvWDFNTU+Lj47l+/Tq7d++msLAQa2trPD09qV+/viTU9TzmQszyP89AoxgQad++PS1btuTSpUusW7cObW1tOnfuTIMGDSotNKZUKqWA9KNHjwgODmb69OlYWVk986Bgfn4+W7Zs4c6dO0yZMgWZTMb69eu5du0aISEhzJ49GwsLC+l8iv64S5cuZejQoTg6Okrk+Pjx45J9mUql4saNG7z99tvlXgtFRUUoFIpyy4c1Gg2FhYVER0dz6dIlwsPDUSgUUpuC2J/95H5SUlLIyMjAw8MDeJz9U6vVz8SiqbRjSk9Px8PDAxsbm2e+v/8iRKHA6qxTsrOz/7W2l88DdUS4FkEQBBwcHIiNjS2XyGlpaaGnpyep+dUEdHR08PT05ObNm7Ru3bpGtvk8IUZvQ0JC+PXXX5k2bVqpxFYsD964cSP5+flYWlpiZGREVFSUVOJalX2PGDFCEtwprQxXLGkfPXo0S5cuZerUqS+0HFFHR4c333yT+fPnY25uXqyv8kmIPYmTJ0/mwIEDfPHFF7zxxhv4+fnVysWyUqnk999/R6VSMXLkyGe6sJTL5QwaNIhffvkFPz8/6XrT19enZ8+ebNq0SVqQ1eHpEH0xf//9d4YMGULjxo3LnDtxEfvDDz8wZMiQavfKiZUSq1atol27diXIt1ji+eeff3L58mXeeOMNqbJDoVDwyy+/MHTo0FIXwaIlzbp168jKyuKDDz4o0Z9vbGyMs7MzjRo1YujQody+fZtDhw4RGxtLQEAAoaGhGBsbS/2fmZmZpKSkcObMGbKzs8nNzSUvL4+7d+8yatQo/P39cXZ2xsrKCjs7O8zMzKSMpKmpqWTlJAgCFhYWTJs2TfIcHjlypCQqVxvv8bKg0Wg4cuQITZo0kRaFYrbYz88PPz8/8vLyuH79On/99RdJSUl4eXnRqlUrXnvtNYqKioiOjiYiIoJdu3aRnJyMnp6e1Dfq7u6Oubm5dE2+THNTHgRBQF9fn5YtW9KsWTMiIiLYs2cPGzdupGHDhrzyyisSSfznMYvZ6vT0dM6cOcOpU6fQ1dWlQ4cOjBo1SiLSz1oULCoqilWrVuHs7Eznzp357bffSE9Pp02bNnzyySclhMo0Gg3Z2dksXLiQTp06FWtZys3N5fbt2wwYMAB4bMOlra2NhYVFuePIyMjAwMBAeg+IWXy1Wk1qaip37tzhwoULxMfHY2ZmRnBwMG+++Sb29vZlluhrNBpOnjxJ48aNJVHAc+fOlftsrEkUFBSgUqlIS0urK719RsjIyMDY2LjK1Z1KpZK8vLw6IlwN1BHhWgSRCMfFxZX7OblcjouLC5GRkTXWhygIj3159+7dW6oK8ssACwsLnJycSEpK4siRI3Tu3LnU4xD7qJKTk3F1daVZs2acPXtW6r+pCvT19Xn77bf53//+h42NDQEBAaWSYV9fX15//XUWLlzIlClTXhgZFgnu+PHjWbJkCQYGBnh6epZJhkVPUh8fH1avXo2Xlxf9+/cvVXDrRUGlUrF582ays7MZM2bMM8+uCIJAvXr1sLKy4ty5c9J9I7Ya7Nu3j3v37lXI8/W/DFEY5o8//iAmJoZp06ZJC++yPl9QUMDKlStp3759mUGcysLJyQktLS0ePnxIvXr1pN+r1Wru3r3LunXrqF+/Ph9//DGGhoZS9ujvv//G1NS0mC3Lk2ONi4tjxYoVBAQEMGrUqHIrT8R7LSAggICAANLT0zl79iyrV69GS0uLVq1a0ahRo1IzlWq1mvz8fOLj4/n++++Jjo7G29ublJQUIiIiyMrKIjs7W+pFFTPX5ubmWFtbY25uTrNmzfj2228JCwujX79+ku+yuFCvzddxdna2VBZd2rMXHutJNGvWjGbNmpGZmcn169fZtWsX6enpuLu706RJE9q3b0/37t1RKpUkJSXx4MEDLly4wLZt24DHrUkNGjTAx8cHY2PjZ2Zb87whZqXq16+Pj48PqampnD9/nlWrViEIAs2aNSM4OBhLS0vkcrkUVDhx4gTp6ekEBQUxfvx4SVzxWc+J2Bu+b98+fv31VxwcHLh37x65ubl07dqV+vXrl2qFptFoyMzMZMGCBTRr1oy2bdsW67u+cuUKnp6eUpLhwoULNGzY8Knvk6ioKBwcHKQg3d27d7l27Rr3799HJpPh4eFBu3btpB51eHqAQKFQcOHCBSZPniwF3a5evfrU7HRNIT8/Hz09PdLT058aCKhD1RAfH4+trW2VAxv5+fmo1epqlVb/11FHhGsZ7O3tOX369FOVo93d3YmMjKRZs2Y19kCsV68eycnJZGZmvpT2L25ubkRFRTFgwAC+/fZbfH19S/XklMlkBAUFceXKFVxcXAgODmbevHkUFhZW2XMSwNzcnIkTJ7J06dIySa4gCDRo0IARI0awZMkSJk+e/MJUmQVBwN7entGjR/PTTz/x9ttvl5tZE4nfhx9+yN69e/niiy/o3r07zZs3fyHKs09CqVSyZcsWEhMTGTt2bIle7WcF0TN66dKlhISESBlBXV1d+vXrx8aNG5k9e/ZL2Xv5PKBUKrly5QqbNm2iSZMmjBgx4qn3YFFRkRSMeeWVV2rsutPS0qJNmzYcPnxYKkPMzs5m27Zt3L17l1dffRUfH59iC5a0tDT27NnDzJkzSyWmFy9e5I8//mDw4MFP7TF8EuK2LCws6Nq1K2FhYcTGxvL333/zzTffYGVlJVmoiNkuuVyOkZERXl5ezJkzh23btnHmzBnefPNN6VmkVqtRKBQUFBRQWFhIQUEB6enpJCcnS7ZFnp6eHDlyhF9//RVXV1dsbW0xMzPDwsICc3NzzM3NJdEqPT09qaRXS0vrmVjuVAQajYa//vqLwMDAp7b2iOMzMzMjNDSUVq1akZmZyb179zh9+jR//PEH1tbWhISEEBAQQPPmzQkNDUWpVJKenk5kZKREoAE8PDwICAjA09MTY2PjKvtQ1yaI2hZdu3alQ4cOxMXFcfbsWb7++mvJbikqKoqgoCC6du2Kp6fnM+mv/idEgbDc3FzCw8P55ZdfCA8Pp3Xr1oSFhREUFISZmVm5lSSJiYksWrRI8uJ+8rOip/egQYOQyWSo1WouX77MmDFjytyeQqGQRNoePHjAw4cPUSqVUsCkZ8+eWFhYVClgcufOHaytrbG0tAQgJiYGfX196f/PGomJiVhZWZGYmPhStszVdojXo62tbZXvndzc3GfmXf1fQd3qrJbBwcGBxMREVCpVuYtnLy8vTp8+XWOCWfB48e7u7s6dO3do1qxZjWzzeUHMpp8/fx4TExOGDBnCzz//zMyZM0uIx4j9nWvWrKF79+6ShcXDhw+f6kP8tDG4ubkxYsQIli1bxsyZM0v1BRWEx97NarWaxYsXM2nSpBdKhuvVq8fQoUNZunQpkyZNKtfPThAeW4D069ePFi1asGXLFg4ePEjPnj1p2LBhtQIJVYVSqWTz5s0kJCQwduzYp4oF1TQcHR3x9vbmyJEjdO/eXTqPDRo0YM+ePVKPWh3+D2q1mqioKLZs2UJBQQFvvfWW1A9bHpRKJb/88gtGRkb06NGjxl/+jRo1Yvfu3WRkZPDgwQM2btxIo0aN+OCDD9DX1y92j6rVajZv3ky7du2wtrYu9rfCwkK2bdtGeHg406ZNq1DPbnnQ0dHB3d0dNzc3CgoKiIiI4MSJE2zZsgVXV1datmwpZbHEUtchQ4Zw+fJlFi5cSK9evWjdurXkk/zkferq6lpsX2q1mqKiIm7cuMFPP/2Ej48PjRs3Jisri7S0NOLi4rhx4wapqakoFApUKpXUb2pqaoqZmRnm5ubY2NhIgl+i3dSzCpjl5+fz119/8e6771Z6+zKZDHNzc5o2bUqTJk3Iy8sjJiaG8+fPc/ToUamtJTAwEBcXFxo3bkzTpk1RKBRkZ2dz584drly5wvbt25HJZNSrV4/AwEDc3NwwMzN7aReoooBXcnIy9+7dIyoqSjo+a2tr9PX1SUlJYc+ePXh5eeHl5YW1tTWmpqY1RorFtoKsrCzi4uK4c+eOJCxlZWXFq6++ypw5czAxMXnqPGs0GiIjI/n+++/p378/TZs2Lfa8EUusi4qKpHsiMTERtVotKfpqNBpyc3NJTU3l3r173L17l+joaACuX7/O6NGjadWqFSYmJtW+1kVS3r59e2nfp0+frjEbwIogJiYGS0tLoqKiXsrkyMuA+Ph4mjRpUuXv5+bm1liL5H8VdUS4lsHQ0JDCwkKUSmW5RNjMzIysrCyUSmWNvmhbtGjB8ePHadq06UsX1baxsZF8mP39/bl58yZbtmwpVcDKysqKwsJCcnJyMDU1pVWrVpw8eRIfH59qHbdIslNTU1m2bBnvvvtuqcRMEB4r1QqCwHfffcfkyZNfaJl0gwYNUCqVLFq0SCLD5Y1FDDxMnDiRR48esW3bNrZv305oaCgtWrSQXprPujdMpVKxadMmEhMTGTdu3HMnwfB4Id27d2/+97//ERoaKok2aWlpMWjQINauXYu/v/9zy1LXVoj9hJGRkezZs4fY2Fh69+5N48aNK5QtUSqVbNiwAYVCwauvvvpMSt9F66QPPvgAe3t7xo8fj4uLS4nnh0aj4c6dO0RHRzNy5MhiAjxJSUmsXLkSW1tb3nvvvRIEujoQSW6DBg3w9/cnPz+f8PBwjh07xm+//YabmxstW7bE29sbfX19QkJCcHFxYeXKldy+fZvhw4dLZLksyGQydHV1CQkJoV69evzyyy/8+eefjBo1qliA9ElVY4VCQUZGBunp6dK/165dIyUlRbKb0mg06OvrY2xsjKmpKdbW1pIglWg5ZGRkVKrYYHkQy9O9vb2r7aUpEnofHx+8vb1RqVRkZmZy+/Ztzpw5w+bNm9HV1cXT0xN/f3+cnJxo0aIFLVu2lETP7ty5w5kzZ9i0aRO6urp4e3vTsGFDXF1dpQVrbXu3PulLnJ6ezsOHD7ly5QoPHz5EJpPh6+tLr169cHV1LdYDW1RUREJCAvfu3ZMsf/Lz8zExMcHS0hJzc3Ps7e0xMzNDX19fqiAQ73dRLK6oqIiCggKJ9CYkJJCSkkJKSgo5OTno6elhZWVFWloaMTExjBw5kj59+lTIbkwc65UrV/jll1+kHvrSvrdnzx46dOiAtrY2Go2Gs2fP4uTkxPXr17l9+zYPHjwgMzNTqrxo2rSppA3w2Wef8corr9RYtjY1NZWUlBRpTZKfn8+tW7fo0aPHc7l+ROFCGxsbtLW1//Pvr2cBtVpNYmJiucmHpyEjI6MuSFFN1BHhWgaxrEqhUJSbXTMwMMDQ0JCUlJQaM1UXBAFvb29+//13srOzy/TtrK2wtraWeuAMDAzo06cPX3/9NdeuXSvRv/ekOFjLli0JCgpi165d5OXlVTu6JpPJaNeuHUlJSaxatYpx48aVKdwVHByMXC6XyHBppdzPA+JYBEGQstQVyWLJZDLc3NyYOnUq8fHxHD58mK+++gobGxuaN2+Ov78/JiYmNS4wI5LgjRs3kpyczFtvvfVCstEiLC0tadGiBbt27WLYsGHScdarVw9LS0vOnTtH69ata90C+FlDo9GgVqvJzs7m0qVLnDhxApVKRadOnRg7dqwk2vQ0KJVK/vjjD9LT06Xv1fQ4CwsLOXjwILdu3UKj0TBjxowyszoKhYJff/2V4cOHSwtEsRR6w4YN9O3bV/ITfVbnXCaTYWhoSOPGjWncuDF5eXncvHmTo0eP8vvvv2Nvb0/z5s3x8/Nj2rRp7Ny5kzlz5jBu3DhcXV2fOi5RR2DChAmcPn2ar7/+mt69e0uZZfEHHj9PjYyMJJHHJ+1+xP+LJEcU+0pOTub69etkZmaSnZ0t9brp6elJ2WXRRkosxzY3Ny/WswyPs++HDh1i8uTJNSogJPbMWlpa0rJlS1q2bCktXEXiFxcXhyAI2Nra4u3tjaurK8HBwTRv3lwqe7x9+zZ79+4lMTERU1NTGjRoQEBAAM7OzhIhfJ7PhSdJr1KpJDExkYcPHxIeHk5cXBwqlQpnZ2eCgoLo3bt3MaXlJ8cp9pm7urri4uJCWFgY8PjeSElJkUrtY2JiCA8Pp6CgAIVCgVKplFq/xH+1tLTQ0dGRAiU2NjZ4enpKZDoiIoJNmzZhYmLC3LlzK1VBpVKpOHLkCAcPHixVpFIM0CUnJ3Pjxg1CQkLYunUrd+7c4eDBgwQGBqJQKPD19aV58+Y4ODgUI4WCIJCTk4Nara6xzJyY/RWDhKJavb29/XMTRVKr1SQkJODl5VXXf/qMoFarpfVqVREXF/dcFMT/zagjwrUMWlpamJmZkZycXC4RfVIwqybLanV1dXF2dub+/fsEBwfXyDafF7S1tdHR0SEvL09Sbxw1ahTLli3D0dERKyurYi/0Ro0acfjwYVq2bImhoSHOzs7cunWLRo0aVXs+5XI5AwcOZOXKlWzYsIFhw4aVmuEXhMdeoKNGjWLJkiWMHTsWLy+vF0aGGzZsCMCiRYsYN25chWyexL87ODjw6quvkp+fz/379zl79iz79u2TepHd3NywtbXF3NwcY2NjyTe7KlCr1WzcuJHU1FRGjRpFUVERRUVFVdpWTaF169Z8+eWXtGrVqlhWoEuXLvz444/4+vr+66PqarWavLw8srOzSUhIICoqioiICBQKBT4+PgwbNgx3d/cK90yLi/U//viDjIwMxowZU6NzKAZUbt++zYYNG3B2duZ///sfCxcuJCUlpVT1fo1Gw6FDh3B2dpZaKfLy8ti8eTP3799n6tSp5Yp91TSeFIISy3tzcnK4f/8+586dY/v27ZiamhISEkJYWBjfffcdPXr0oG3btk/Nqou9x61atcLb25s1a9Zw5coVXnvttVLbPv45pif/b2hoiKGhYZnZD6VSKalf5+bmkpmZSXx8PA8ePCAtLY2MjAzy8vLQ0tJCV1cXKysrHBwcSE1NxcjICBMTEwoLC59Jr7K4LblcjoODAw4ODrRp00ZS1BXJ8Z49e0hNTUVLSwtTU1OcnZ1xcHBg0KBB6OnpkZycTHh4OBs2bCAzMxM7Ozspu29paVnhwFBFIBI8lUqFUqmksLCQhIQEYmJiiIqKIj4+nvz8fEmxvEmTJjg5OWFhYVFpr98nP6urq4ujo2O1A/SiFdO6detQKBQMGjQIX1/fClfAicGtjRs3EhUVxXvvvYe5uTkqlYqioiKys7N5+PAhkZGRkiCarq4u58+fx8PDQ7qPPv/886c+r+Li4rCwsKixZ1NhYSEXL15k0qRJUub8r7/+kiydngeUSiU5OTmoVKrn1pP8X0NRURFqtbpa101qauoLWzP+W1BHhGsZBEHAzs6OuLi4YsqlpcHb25tbt27RqlWrGt1/8+bNOXPmDEFBQS+V9YsgCJiYmJCeni6RXkdHR7p3787q1auZPHlyid64hIQE8vPzMTAwoG3btuzbt08qWa4utLW1GTVqFIsXL2bHjh306dOn1PkUBAF/f3/Gjh3LqlWrGDFiBA0aNHihZFhPT4/ly5czfPjwSl8H+vr6BAQE4O/vT1FREZmZmcTGxvLw4UMuXrxIRkYGubm50kugsigqKuLChQvY2dnh5OTEggULKr2NZ4XMzEzGjBlTIpgSGRnJm2++iY+Pzwsc3bOHTCaTMnq2trZSpsjc3LxKPXMKhYJ169ahUqkYPXp0jZa+q9Vq4uLi2LhxIzk5OQwfPlwqQ2zRogUnT55k0KBBJcaclJTE4cOH+eCDDxAEgaioKH766Se8vb2lUugXCUEQMDY2pmHDhgQFBZGfn09cXBwXLlzg1q1bKJVK5syZw+nTpxk3bhzW1tZPvb8FQcDa2pqpU6dy7NgxvvrqKwYNGkRISEiNteaI5LE0P2ixskAU+MrPzyclJYUHDx6wdetWgoODmTNnDvC4vN3R0REXFxfc3d0xMzOTAqM1/UyVy+VYW1tjbW1NQECAVCYuEvmoqCgePnwo2VzB43vE2NgYMzMz8vPz2bFjBz/99BM6Ojr4+fnRrFkzfHx80NfXL1N4S5wPtVqNSqVCpVJRWFhIRkYGmZmZZGRkkJqaSmpqKrm5uWg0GmQyGZaWljg6OhISEoKdnR3Gxsbo6+vXmve8OH937txh9+7dKBQKevbsSUBAQKWqQDQaDWlpaSxfvhx9fX169+7N+fPniY6OJiYmhvz8fHR1dXFycsLNzY1u3boRExPDZ599JpG+P/74gzZt2lSo9zgmJqbGWpvEtgsxaAyPRfsSExOrbPFYFRQVFaHRaEhISCjXzrMOVUdSUhKmpqZVJsJiK0OdkFn1UEeEaxnE7FlCQkK5ytEALi4u7N+/v8b37+Pjw6ZNm6pdsvG8IYpVPXr0CC8vL+l3LVq04MGDB2zfvp2BAwdKL30jIyMcHBy4e/cuDRs2xMPDg9TUVNLT02ssAqqrq8uECRNYsGABxsbGJVQqnxy7l5cXEydOZPny5fTt27dGFcErA0EQqF+/PlOnTmXp0qWkpqaW6q1ake3o6OhIC8WGDRtKWQqxt7CyyMvLY9WqVbz++usMHjz4mVskVRaFhYV8/vnnvPnmm8VEiFJSUvjmm2+YOXPmv97vTyaT1UhGLjs7m5UrV2JpacnQoUNrrBxatE/ZsWMH169fp3fv3jRt2rQY6WjevDnz5s2jd+/exYJnKpWKDRs20L17d4yNjdm3bx9Hjhxh2LBhtTJwKIrbeXp6Uq9ePZRKJVlZWVy/fp1jx44xbtw4/Pz8aN26NX5+ftja2pYpdCTezx07dsTX15c1a9Zw6dIlhg4d+szbaMTMtIGBgfROcnR0JDMzk27dujF+/Hip1zQtLY3o6Giio6M5e/YsmZmZwGNdCBcXF3x8fCSSUdPkWCwX1tXVxcLCAnd3d+mZp1QqpTFmZGSQlpZGeno69erVIz09ncTERHJycti6daskmCn2a5ubm2NpaSllu5+0sxL//2QgQcxGW1lZSUrW2tralc70Pi+Ivr4XL17kyJEjGBoa0qNHD+rXr/9U/YAn2y8yMjIkMbf9+/eTl5dHgwYN2Lt3r6Ti3KNHD0xMTKReZYC9e/fSpEkTLC0tEQSBgoICrl+/zrRp0yo0X3fv3qVx48Y1NheHDh2iZ8+eyGQyNBoN58+fx9/f/7kG2dLS0jA2NiYjI6Na1pJ1KBuJiYkVCkSWBbVaTWZmZh0RribqiHAthLOzM9evX3/q5ywsLCQhkpp8QBoYGGBvb09ERMQLy0xWBYIg4OTkxJ07d4oFEcQy5Xnz5nHx4kUaN24sLSKaNWsmZb/19PQIDg7m5MmT9OzZs0aOWywJfOedd5g3bx4GBgZS72Bpn3VxcWHatGksXryYzMxMOnbs+EIW16IY1qxZs1i+fDnR0dEMHTq02kqYTy7eKgNxofT999/j7u5O//79a6UlkZaWFn379mX79u1MmTJFCh7Y2dnRrFkzDh8+zIABA16ae+pFQBScWrZsGY0aNaoxdWjRf/jo0aNSS8Rnn31WqpiVubk5FhYWRERESMI6Go2Ga9eukZGRga+vL/Pnz8fAwID3338fMzOzWn9OBeGxR7GlpSVt2rThlVde4dGjR3z77besWbMGX19fioqKsLW1JTAwEC8vL+zt7aW5f7KtxMnJiVmzZrFnzx4+//xzqXLkefa75ufns3fvXiZMmIBcLkdLS0vyiHd1dS0WdMvLyyM2NpaoqCiOHz9OQkICSqUSCwsLPDw88PHxwdnZudh5rKnjEOdER0dHCuaYmpoWC5Q92bcrjjknJ4fbt29z+fJlHj58SG5uLk5OTgQFBeHh4YGtra1EbJ+c99p+HcL/Ha9KpSIyMpJjx45x9+5dvL29GTNmDE5OThLZF+dERF5eHikpKSQmJvLgwQOio6NJS0tDqVRiYGDArVu3AJgxYwYBAQHo6emV64Odk5PDsWPHmDFjhjS2Bw8eYGpqWmGCER8fLylLVxdxcXEUFBTg7u4ujef06dPFRPmeB+Li4rC1tSUpKQlra+vntt//CsRse3WEshQKBXl5eXVEuJqofSvJOmBhYUF6evpTrZH09fUxNzevUBl1ZfBkeXSDBg1qbLvPA87Ozhw9erTE3Onp6fHmm28yf/587O3tpR4+Hx8ftm7dKnkIt27dmkWLFtGlS5cay0AJgoCZmRmTJ09m3rx56OnplVl+LQgCNjY2zJo1iyVLlpCRkUG/fv1eSOZTFMuZPn06GzduZO7cuYwdO7baVjCVhVjmtnTpUpo2bUrnzp1rXeZNhNh7vm/fPu7duyeV2gqCQJcuXfj8889p3759Xc9VGVCr1YSHh/Pzzz/Tv3//GrEKEcstT58+ze7du6USZlFhuLTty2Qy2rRpw7Fjx/Dz80MQBPLy8vjtt98IDAzk22+/pU+fPrRu3fqFeedWB+I16ebmxvz589m0aZPklaxWq7lx4wanT58mNzcXKysrfH198fHxwcHBAW1tbSlT2adPH4KDg1mzZg3nz59nyJAhGBsbP/P50Gg0XLhwAQcHhzL7sZ8MupmYmGBiYkL9+vXp1KkT8LjiID4+nsjISI4ePUpCQoJUkeXn54enpyf29vZSpcCzPKZ/kli5XI65uTnNmzeXhLfS0tKIjIzk2rVrHD58mMLCQunceHt74+TkVMxPtDZek6LSdGxsLGfPnuXatWsYGhrSunVrhgwZgpGRkVTynZ+fT0JCAvHx8URHRxMVFUVmZiZKpVIS1PLw8CAoKEi6l9euXUuLFi0YNWoUJiYmT50DjUbD0aNH8ff3l9qp1Go1R44coX379hWaw4KCAvLy8rCwsKiR+Tl48CBt2rSRAr3R0dFSm9fzgqgYLQYDq6vGXofS8fDhQ8keqyooLCyUgoB1qDrqZq8WQl9fn8LCwqcSYUEQcHV15eHDhzVOhOvXr8+2bdskgviywMLCgpycHBQKRbEsudh7PWLECJYvX87MmTMxMzPDxMQEKysrIiIiCAgIwNbWFktLS8LDwyXhqJqASHAnTZrEwoUL0dbWLjPbLvb4TZs2jZ9++omVK1fy+uuv16gNS2XGraury7Bhw7hw4QLz58+ne/fuhIaGPhdyrtFoiIuLY9myZXTt2pVWrVrVWhIsQkdHh379+rFp0yZmz54tvaRMTU1p164d27dv54033qiVC9UXCYVCwd69ezlz5gwTJkyokFBbeRAX3VeuXOHPP//E3t6eyZMnV0jIShAE/Pz82Lx5M7m5uRgZGbFjxw4uXryIubk5M2fOxM7O7qU/h4Lw2I5pxIgRXL58mTVr1tC5c2f69++PXC6XehPDw8PZsmULmZmZGBgY4OHhgaenJ+7u7tjZ2TFr1iz279/PF198wbBhwwgMDHym/rmFhYXs3buXt956q1LPgyfPl0iOfXx86NKli1RWHR8fT3h4OGfOnCErKwsLCwvq16+Pr68vDg4OGBgYPLfgx5ME2crKCisrK5o0aSLZOiUmJnLr1i127NhBSkoKWlpaODk5Ua9ePdzd3bGxsUFXV7dawoTVwZM903fv3uX69etERkZiaGhIgwYNGD16NIaGhiQkJHDixAni4uKIi4uTFMTNzc2xs7OTxLxMTU2LefSK2fMrV66wYcMGOnToQPv27Sv8bsrMzOSvv/5i1qxZ0lxnZmYSExMjBcCehqSkJIyMjGqkKi8rK4v79+9L2gSiNVjLli2fux91dHQ0ISEhAC9c9+Dfiur29xYWFj4T7YP/GuqIcC2Evr4+urq6ZGZmPjUSV79+fU6fPi1ZF9QUTExMcHBw4Pbt2yWsh2ozxGxFYWFhqQ/vwMBAyefz7bffRl9fn1atWnHq1Cn8/f2RyWR06tSJffv2ERgYWOOLB0dHRyZNmsTixYsZOXIkAQEBZZJhfX19xo4dy/bt21mwYAFvvfWW1MP0vCGXy2natCkeHh788ssvnDt3jmHDhuHs7PzMxqPRaAgPD2fNmjUMHz6chg0bvjTXob+/P3v27OHq1atS9l8QBMLCwvjkk0+IjY2tEyD5/xCDHT///DPm5ua89957FcrmlIeCggKuXr3Knj17MDY2ZsyYMbi6ulZqMWlkZISPjw9nz55FrVazfv16Zs2aRbt27coUMXpZIZPJCAkJwc3NjbVr13L9+nVGjhyJubk5pqameHt7S1m6zMxM7t+/z/Xr19mzZw9FRUVYWlri4uJC69atWblyJf7+/gwfPhxTU9ManycxGyxW9tQUtLW1sbW1xdbWloYNG6JSqcjLyyMpKYnw8HB27txJcnIyxsbG+Pj40KBBA8nO5nmTTLlcjoWFBRYWFvj6+kpl/zk5OURHRxMREcG2bdtIS0sDHgeIHRwcJFIp+vqKJLkmqi5UKpWUHU1LS+P+/fvST0FBAcbGxpibm2Nra0t+fj6nT5/m5MmT6OrqYmtri4ODAw0aNKBr164YGhqip6dXbiuO2Ou/ceNG4uPjeeeddyr1PtJoNOzcuZMWLVpIFToajYZz584RGBhYYfIn2tfUxHV+8uRJgoODpT74vLw8wsPD6dmzZ7W3XRmo1WqSk5Mlgv9vetbVFqhUKnJzc6ulGZKdnY2RkVHd+akm6ohwLYT4kktKSnoqEXZ0dCQ+Ph61Wl3jHootW7bk5MmTBAUF1dh2nzW0tLSwsrIiMTGxVJNxQRBo37498fHxbNy4UVJo3r59u5T58fPz448//iA2NhZnZ+caHZ8gCDg7O/POO++wePFiRo8eja+vb5kPMjG7eOLECb755hvGjRuHh4fHCxPRsrKyYtKkSVy8eJGlS5fSoEEDevbsWeMLXrVazcmTJ9m5cydvv/12hXxPaxO0tLQYMGAAa9asoUGDBlKZvb6+Pj169GDr1q1MnDjxuUf5axPExfvBgwf566+/6N+/P02bNq3WnBQUFHD+/Hn27t2LlZUVr732Gm5ublXO4Pn7+/P++++Tm5vLN998Q5s2bV6q67AyEAQBS0tL3nnnHY4ePcqcOXMYOnQoISEhkiCTaIHk4OBA69atJbXihIQEHj58yIMHD7C2tmb37t0cP36ctm3bEhQUhJ2dHRYWFpiYmFT7mlcoFOzZs4dx48Y90/tHLpdjbGyMsbExHh4edO/eHYVCIRFjMQtramoqEWNHR0cMDQ1fSOWOvr4++vr6WFtbExwcLAl0FRYWkpiYSExMDAkJCVy5coXMzEwKCgqQyWTo6+tL2XHx/JqYmEgWd0/uQ7xns7Ozyc3NJScnh7S0NOLi4oiJiSE5OZnCwkLy8/MlRW07OzssLS2xsbHB2dlZCjaI2WotLa1Kl3OrVCouXLjApk2bCA0N5bXXXquUfoVGoyE6Oprr16/z8ccfS99TKpX8/fffjB07tsLbEnubq4uCggLOnDkjWSYBXLt2DQ8Pj+cusCje11lZWdjZ2dX6KqyXEZmZmWhpaVXLezohIQFbW9t/7TvpeaGOCNdCiGW0iYmJ5ZIkeKyEKapQ1kSPypMQ1aNFe6GXASLRfPToEd7e3mX2/w0ePJglS5awd+9eunXrhr29Pffv3ycoKAgtLS3atWvHgQMHGDVqVI0/ZERRrIkTJ7Js2bKnkmG5XE6bNm2wtbVl+fLl9OvXjxYtWrwwES0tLS2aNm2Kv78/+/bt4/PPP6dly5Z06NBBsj6p6pyJmYUdO3Zw7do1Zs6c+cKy4NVFvXr1sLGx4fTp07zyyitSVrhFixbs37+fyMjI/6Qap3iOL126xLZt23B3d+fDDz+scjBFo9GQn5/PqVOnOHToEA4ODowbN07KDlV2m2I558GDBzl8+DAajYZu3brRqlWr/8S50tbWlpShV61axZUrVxgyZEgJgic+C7S0tKhXrx4eHh60b99eKkm/c+cOP/zwA9u2baNVq1aoVCrgsRCZjY0NLi4u2NjYYGVlhZmZWbFgRXlZwAsXLmBra/tcKyrE60hPTw8XFxecnZ3p1KkTSqWSmJgYwsPD2bZtG6mpqZiZmeHv709AQAAuLi5Sme7zvHb+KdBlbGyMp6dnMVGuJzP8mZmZZGVlSR7O0dHRZGVloVAoUCgUZGRkSNZM4meKiopQKpWYmZnh4OCAu7s7TZs2xdXVFRsbGywtLbGyspIyVjUh5qXRaEhMTOTXX3+loKCAyZMnV8m2SKlUsnbtWgYMGCAREY1Gw927dyWx0IqOJzY2ltatW1f6WP65nRs3buDg4CBlp5VKJcePH2fw4MHV2nZVkJKSgqGhIWlpac+1N/m/BPFZUZ1gXnJycp2QWQ2gjgjXUri4uBAZGfnUz4negMnJyTVOhI2MjHBycuLWrVs0atSoRrf9rCD2TV+5cqXcz+jq6jJ27Fjmz5+PsbExrVq14sSJEzRo0ACZTEarVq04cOAAaWlpz0TYSBAE3N3defvtt1m6dCmvv/56mWXS4ufr16/Pe++9x/Lly3n06BH9+/d/Yf0hgiBgZGRE//79CQsLY//+/f+PvfMOi+Ls/v53trBL7713AQVEQLAg0hSxo9g1lhhj8iSaYmI0PibR9CeJxkQTEzUW7L2A2DV2FOyAgPTeYWH7vH/4zvxCQKXssgvM57q4kgvZe87O3DNzn/uc8z1Yu3Yt3N3dERYWBltb21e2vWiNxsZGbNu2DVKpFB988AF0dHSU9A2UD4vFwuTJk7Fu3Tr4+/vTCy4ul4uJEyfi4MGDeP/993uN0AUVTUpJSUFCQgKdsuzo6NghFXGSJFFZWYlz584hOTkZ7u7uePvtt9tUA/wi5HI5MjIysHPnTtjY2GDJkiV488034eXlpXatupQJQTxXhl6+fDmOHz+ONWvWYM6cOXB3d3/htfqno8Pj8eDt7Y0ff/wRiYmJuHz5MiZPngxXV1e6tjUvLw/3799HZWUlremgo6MDCwsL2kE2NTWFvr4+3TZIKpXixIkTSo8Gv4p/OppOTk5wdHRETEwMhEIhCgsL8ejRI+zbtw81NTUwMzODj48PLcikqrT6fypSUz+UmBgVPRYIBCgvL0dFRQUaGxshEokgk8nA5/Ph7OxMb2JYWVnRUWQ9Pb0WOiLKSIcXCAQ4efIkbt26hbFjx2LQoEEdeseQJIlLly5BW1u7Rb/3kydPYuTIkW1+JguFQtTU1HRK+Rd47vSePXsW06ZNo+0pKiqCTCaDnZ1dl84XqlTF3NwcpaWldJcNBsVCObGdCRpUVlZ2q9JFdaV3rMC6IRYWFrh69Wqb/tbNzQ0ZGRlwd3dXqA0EQWDIkCG4cuXKC1WO1RFbW1ucPHnylWJjenp6+M9//oP//e9/GDVqFPLz81FfXw99fX1oamoiMDAQFy9exMSJE5Xy3QniuWrrO++8g59//vmVdbBUavIHH3yAPXv24IcffsCCBQtotUtVQBAEDA0NMWXKFIwaNQp3795FfHw8hEIh+vXrBz8/P1hYWEBTU/OlPSypVgIbN26Et7c3xo4dqzDVblViZWUFd3d3XLp0CdHR0fQC2sfHB4mJiXjy5MlLN0C6O1TUqbi4GNevX8fDhw9hZ2eHOXPmwNHRsUPOjEQiQV5eHhITE5Gfn4/g4GB88sknMDQ07NSiorq6GgcOHEBeXh6mTZsGd3d37N69G5GRkbh37x7Gjx/f65xhPp+P2NhYeHt746+//qLvzbbWDfJ4PIwdOxb9+/fHzp07cfPmTUybNg2Ojo4IDg4GALq9kUAgQH19PUpKSlBWVobMzExUVlaisbGRTs2ura1FTk4OUlJSkJeXB2NjYxgaGoLP59PRaeqnI9kAHYU6jqamJlxcXODi4oIxY8agvr4eRUVFSE1Nxe+//w6hUAh7e3t4e3vD3d2d7mfb0UwIuVwOmUzW7EcqlaKpqQnV1dWora1FQ0MDHfWtrq5GQ0MDZDIZ5HI5AEBbWxv6+vowMDCAoaEhvLy8YGpqCk1NTfD5fLqWuCvP5z+/Y1NTE65evYqkpCT4+flh1apVndIQKC0tRUJCApYvX97s+VNYWIiamhp4enq2eayamhrweLxOCYqSJInMzEzw+Xw6y4EkSVy+fBlDhw5VSeZXfn4+rKyskJKSwkSElUROTg4cHBw6/HmSJFFRUcFEhBUA4wirKQYGBqitrX3l3xEEAWdnZzqFT9Evqj59+mDv3r2oq6uj017VHR0dHQiFQshkslcutKma1x9++AEEQSA1NZVOYw0PD8dXX32FyMhI6OnpKcVWKk166dKl+Pnnn9HU1ISgoKCXRl20tbUxZ84c/P333/jmm28we/Zs9O3bV6V1PARBQE9PD6GhoRgyZAiqqqpw7949uo6Oz+fD0tISZmZmMDIygoGBAd3fEXi+OPn1118RExMDb29v5OXlqey7KJq+ffvit99+g52dXbMFk6+vL7Zs2YI333yzx9RgUQIg1dXVKCkpQVFREaqqqmBgYIDAwEDExMTQabDtgSRJ1NTU4M6dO7hy5QpYLBYiIyMxd+7cTom5UFHqK1euICkpCcOHD8fs2bPB5/ORmZmJR48eYeXKlfjuu+9QUFBA9/bsTbBYLLi5uWHFihU4ePAgvvrqK8ydO7fNqt5UucoHH3xAax1ER0dj6NChtJqxjo4OdHR0YG5uDhcXFwD/F8EUi8WQSCRoaGjA559/joULF4LNZqOkpASPHj1CTU0NxGJxM+dOU1MTWlpa0NbWpv9L1b5SEUyqNpVynNlsNv1DOd7U/3dkfrFYLOjr60NfXx99+vSBVCpFXV0dnj59itTUVBw8eBDA83esn58fzM3NweVyaWdWKpU2q8dtbGxEU1MTGhsb6Z+mpiYIhUJIpVIQBEHby+fzaYVlXV1dmJiYwMXFha7T/vemgTq2AGtsbMTNmzeRlJQEBwcHvP/++52uh5RIJNixYwfGjh3bLNOLJEmcPn0aYWFh4PF4bR6vqKioUxkowPONoMTERERHR9PPRYFAgPT0dIwfP14l1yU7OxthYWG4du1at87KUmdKSkrQv3//Dn+eep4oOhO0N8I4wmqKvr4+ZDIZGhoaXimUYGdnh9LSUojF4nY9xNsCn8+Hg4MD0tPTERgYqNCxlQWfzwefz0dVVVWbmtxbWFjgrbfewvLly3H06FEMGTKE7uPo5+eH8+fPY9y4cUp7IREEASsrK7z33ntYv349mpqaMHz48Jc6CxwOB8OGDYOjoyN+++03+Pj4YPz48Wohpc/hcGBmZoaIiAiEh4dDIpGguroaBQUFKCsrQ25uLu7fvw+hUAiRSIS///4bPB4PAwYMQH5+PgoKClRqvzLgcDj49NNPm/XFJUkSBQUF+Oqrr+Dh4aFiCxUD5dQYGBjAxsYGQUFBsLKyoh2e9sxNqpY4Ozsb586dQ1ZWFjw9PTFv3jxYW1u/NMOgLWPL5XLcv38f+/fvh42NDZYtW0anqonFYuzatYuujaWEAx0cHFR+f6kCgiCgpaWFmTNn4uHDh9i4cSOGDh2KkSNHtimiSaURh4WFwcfHBzt27MD169cxZ86cF9Z4/rMul8fj4f79+3Bzc8OIESOa3UPUtaT+K5VKUV9f38yBFAgEEAgEKC0tpYWipFIpZDIZJBIJ7XxSdcxUyjD1w+FwQJIk7WgCz0scKMebgtp4pcai5jD1//+0kyRJNDQ0IDExEceOHQOXy6XTka2srODk5AQzMzN6k0BTUxNGRkawsbFp4eBTEVvqHqP+n/ou3QGqfrmhoQF///03Ll68SGtpWFlZdXqzkCRJXLt2DQBa1PtXVVXhyZMnmDp1arvGS09P77RQVn5+PsRiMa0XQZIkUlJS4Orq2ikhpc5QWVlJR917UxZMVyGXyztddieVSkGSJHN9FADjCKspXC4Xurq6qKysfKUjrKOjQ/d8VLQjDDx/aZw7dw7+/v7dInLFZrNhaWmJgoKCNu0gU3XFa9euxdKlS3Hv3j30798fBEEgMjISX3/9NcLDw5UqU08QBExNTfHee+/h559/hkAgQExMzCv7SNvZ2WHFihWIj4/HN998g9dff11t+ptSCzIejwcLCwtYWFjQix3guWriH3/8gejoaMydO7dH7zzX1tZizZo1mD9/frOXX05ODjZt2oR33nlHKfeuKulMumdJSQmuX7+O5ORkaGpqIiwsDLNnz6ZF+zrjAANAQUEBncI/d+5cehFKLUQvXboEIyMjutd3QEAAvv32WwiFwl7bU5M6P/369cPKlSuxc+dOfPPNN5g/fz4sLS3bHB02NjbGO++8g+TkZKxbtw5DhgzByJEjX6r6KxKJcOrUKSxcuLBVm/75XuLxeNDW1m6xCfrPZ8/Lfk8501KplBaEon4HgHZqKSf3n/x7c4aKKv8z0kxFoblcbrNaVGrep6enIzU1FSUlJaiuroalpSW8vLzg4OAAPp+vkhRlZUKdy+LiYpw/fx737t2Dl5cXlixZQl/Dzn5fqp7y2LFjWLZsWbP3KkmSSExMxJAhQ9olCkqSJPLy8hAcHNyp51FCQgIiIyPpuSCXy3H58mXMnj1bJde5rq6OnvuGhoaMo6UEBAIBxGJxp6K5EomEzgJh6ByMI6ymUI5RRUXFK+sIWCwWrK2tkZ+f/8p2Sx2xw83NDfHx8airq2u1JZG6QTm2ubm5bRb5osSr5s2bhw8++ADr16+Hl5cXjI2N4e/vj4SEBEyePFnpdhsZGeG9997Dpk2bUFtbiylTpry0VpZKlZ43bx5u3ryJ77//HqNHj8bQoUPVUoSJIAjI5XKkpaVh69atCA8PR0REhFraqkj09fURFhaGI0eOYP78+fQCx97eHg4ODrhy5QoiIiJ61AK3rVAORU1NDW7fvo0bN25AJpPB398f77zzjsLad1A1VUePHsXTp08xfvx4+Pv7N1voUQvmxMREfPzxx/Qig0pxzcvLU7gWQ3eDIAjo6+tj0aJFuHXrFv73v//R2R9tjQ5TfcmpzgSUGJezs3OLa02SJO7evQtTU9NO9S1/mfbCP6EiwF0Ni8WCjY0NbGxsEBYWBpFIhOLiYjx58gQJCQkoLS2FlpYW+vTpAw8PDzg4OEBTU7Nb9rSmnN+Ghgbcu3cPly5dglAoxODBg7FixQoYGBgo9DvJ5XJs374d0dHRMDMzazZ2ZWUlUlNTm7VRagtUHXZbss5eRElJCSoqKuDl5UVvwlH1wlZWVh0etzOUl5fD0NAQ5eXlTOskJVFXVwctLa1OPWeqqqroMgeGzsGcQTXG0dERz549g7+//yv/1t3dHU+ePHmp2FJH0dDQgIeHB1JTU7tNH01nZ2ccPny4XZ8hCAJDhw7F/v37sWnTJkyfPh1BQUEYOXIkvvjiCwwfPrxLhAl0dXXxn//8B9u3b8fvv/+O11577ZXRUjabjeDgYLi4uGD79u24e/cuZs+erVIhrX9DkiREIhFOnDiBu3fvYuHChXBxcVEb+5QJQRAYNmwYPvvsMxQWFtKiKCwWCxMnTsR3332HoKCgLu8XqUokEgkqKipw9+5dJCcnQygUwtvbG/PmzYOlpaXCFviUEFZiYiJSUlIQFhaGadOmQUtLq8X4JEli9+7diIqKarapyGKx6PToF7Vl622w2WwEBQXB3d0d8fHxSElJwaxZs9rczoYgCBgYGGDevHl48uQJtmzZAg8PD4wbN66ZGBLVN/ifG0g9HSol3NHREY6OjoiOjkZTUxMqKyuRlpaGy5cvY8+ePXRWkLu7O1xcXKCvrw9tbW21rPkFnkfTa2trkZaWhps3b6K0tBSurq6YMmUK7OzslJIVQ6VEi0QiWv+DQi6XIyEhASEhIe3OSGpoaACfz+9wxJSKRP+7LvnMmTOIiIhQWaSvoKAAtra2KC4u7rQaNkPrVFdXw9DQsFNjlJWVqdX6rjvDOMJqjJWVFdLS0l75dwRBwNXVFdeuXXulUnJHoNSj9+7diyFDhnSLHSgjIyNUV1e3W0DM0NAQwcHBsLKywqlTp1BdXY2RI0ciPDwchw4dwuuvv94lO6Q8Hg/z5s3D4cOH8eOPP2Lx4sUwMjJ66XchiOf9p999911cvnwZ33zzDUaPHo3BgwerPL2JasmwZcsWWFpa4pNPPmnRl7Sno6WlhZiYGBw4cADvvPMOPY+o9ipnz55VmThKVyGVSlFcXIw7d+4gJSUFEokEvr6+eO2112BhYaHQGneSJFFfX49z587h6tWrCA4OxqeffgpdXd0XHoNq5xMaGtrsbyil71OnTvXq9Oh/Q2WxLFq0iE51DgsLQ0RERJtV39lsNry8vLBy5UqcOnUKa9euxYQJExAQEAA2m427d+/CxMSky9vIqBNUjbaWlhZsbW0REREBsViMhoYGZGdnIyMjA1euXEFDQwO0tbVhY2MDZ2dn2NnZwcDAQGWRI7lcjrq6OpSWluLBgwdIT0+HQCCAs7MzIiIi4Ozs3Cmxu7ZQUVGBw4cPY9myZS3mZHl5OR48eIBPP/203TY8e/YMtra2HV5vlZSUID8/H9OnT6d/V1ZWhoqKCvTp06dDYyqC9PR0+Pr64u+//4aPj4/K7OjJdFYxGgCtGN1bn4mKRP09ml4MlRotl8tf6XyZmJigvr4eIpGoXXUubcXa2hpNTU2oqqqCmZmZwsdXNPr6+iAIAjU1Ne2qwyAIAlFRUdi1axfee+89/Pbbb6iursa4cePw5ZdfIjMzE66urkp/+BAEAQ6Hg4kTJ9Lq0IsXL4a9vf0rj83lchEWFoa+ffvSojSUo9HVD02qP+X58+eRmJiIqVOnwt/fv1fWtRAEgeDgYCQlJSErK6tZNHzMmDFYs2YNQkJClNK3WhVQtZcymQz5+fm4ffs27t27B4Ig4OfnhwULFsDS0rJTolcvOm5dXR3Onj2L69evw9fXt03plgKBAPHx8XjjjTdajUzp6enB3NwcmZmZPbrlVUfgcDgYOHAg+vTpgx07diA5OZkWNWtrdFhbWxuTJk1CcHAwtm/fjsuXL2PKlCk4fvw4Fi5cyKRo/gNKe4HH49HlO1QrpfLycuTk5CA7OxtXr15FbW0tWCwWDA0NYWpqCjs7O5ibm8PIyAi6urp0BPlFx/knL6qzBp7XcdfW1qKyshJFRUXIyspCSUkJxGIxTExM4OXlhdmzZ8PCwqJD/X87glQqxfbt2xETEwNzc/Nm/yaXy7F//36MGDGi3dFgkiSRlZVFawu0F7lcjlOnTiEyMpJ+1pAkifPnz2Pw4MEqax0ol8tRVFSEUaNGobq6mlEkVgJUUMDX17dTY5SXl3daqI3hOYwjrMYYGxtDKBRCIBC8MmVSQ0MD+vr6KC8vh729vcJt0dDQQP/+/XHjxg2MGTNG7ReBbDYbpqamKC4ubvfD3MnJCQRBoKKiAkuWLMG2bduwceNGjB49Grt27cInn3zSZcJGbDYbISEhMDExwfr162lH8lWLQio6vHTpUty4cQPfffcdBg8ejOjoaKXvwFNQD/xt27ZBR0cHq1atUnjtV3eDy+UiNjYW+/fvx7Jly+gFob6+PoYOHYqTJ09i5syZ3XrRT7W8yc7Oxs2bN/HkyRNoampiwIABeOutt5ptyCjaAa6urkZSUhJu374Nf39/ur/wq44ll8tx4sQJ9OvXD05OTq3+DUEQGDRoEK5cuYK+ffsqzO6eApXq/NZbb+H27dv46aefMHz4cERGRrY5zZ0gCFhbW2PZsmW4ceMGli9fDm1tbaZX5iug6q7ZbDasra1hZWWFQYMGAXg+t2tra1FeXo6Kigrk5ubiwYMHqK6uhlAohFwuB4/Ho/sFa2pq0m2X/i1gJpfLm7V0ampqols6yeVy8Pl8GBsbw9raGoGBgbC0tISpqalKFKxJksTVq1chlUpblHSRJIm0tDSUlpZiwYIF7bZLLpfj2bNnCAkJ6ZBtxcXFKC4uxuzZs+nf1dfX49GjR/j4449V9o6sr69HU1MTDA0NIZFIVKZa3ZMhSRJlZWWdCkyQJImSkpIOzz+G5jCOsBrD4XCgqamJ+vr6VzrCLBYLzs7OyMjIUEoKGUEQGDhwIDZt2vRKNWN1gCAIODg4ICcnB15eXu36LIvFwsiRI5GYmIi3334br7/+Ok6fPo1Dhw5BIpHgwoULzVp4KBuCIODl5YUPP/wQGzduRH5+PsaMGfPKXWNqcTRo0CD07dsXhw8fxhdffIG4uDj069dP4ZG4fyIUCnH27FlcunQJEyZMwMCBA9V+znQFBEHA29sbp06dwsOHD+Hj40OrwIaHh+Pzzz9HWVlZp/tldiWU8I1AIEBGRgZu3ryJZ8+ewdTUFAEBARg1ahRMTEyU5tzLZDKUlZUhKSkJDx8+RFBQEFauXNnmTRdK/fXOnTsvFcwhCAIeHh44dOgQRCJRs57QDP8Hi8VCYGAgXF1dsXv3bnzzzTd47bXX2lU7zOFw4O/vDysrK1haWmLt2rWYOnUqvLy81Lb+VZ345/lhs9kwMjKCkZER3N3dMXjwYADP571EIoFQKKQdWrFYjKamJtTV1dEZZv+ExWJBV1cXlpaW0NHRgZaWFjQ1Nem+zS9T/u5KqIjZ8ePH8eGHH7Z49wiFQuzcuZPuGd5eJBIJ6uvrO1TnSfUNjoqKotPVSZJEcnIyPD09Vep8UgJMFRUV0NXVZZ5xSoDaSOrM5h71vu1NmiLKhHGE1RwjIyNUVVW9UkGQIAj06dOHVp9VBmZmZuDxeMjLy4Ojo6NSjqFInJ2dcfHixXZ/jiAI+Pr64vDhwygtLYWlpSWio6Ph5OSEdevW4YcffoC3t3ebW4YoCgsLCyxbtgzbt2/Hr7/+irlz5zYTlXkRVMRx9uzZyM7Oxt69e5GUlEQLlCjSQZHJZHjy5Al2794NBwcHLF++HIaGhmqxOFIX2Gw2Jk+ejPj4eHh4eNDZBdra2hgxYgQOHTqERYsWqf05k0qlqKqqwqNHj3Dnzh2UlpbC3t4egYGBmD59OvT09JTm/FKL+KysLCQmJqKsrAzDhg3DhAkTXloD3BoSiQS7du3C5MmTX7kI1dPTg6WlJdLS0uhNDIaW/LN2+O7du3SbpBEjRtAtgF4GFc1zdnbGG2+8gaysLMTHx+PKlSuIi4tjRGIUAEE87+2soaEBPT09VZujUKiU6NGjR7dQiaayP1xcXDqcWlpaWgp9ff0OaQUUFRWhtLQUs2bNou0SiUS4evUq3njjDZXO6+zsbDg7O9NCWd05M0ldEQqFYLPZndJtkcvlEIvFPa7loqpgHGE1x8HBAbm5uW1KxbOxsUFRURFkMplShDE4HA6CgoJw9epVODg4qP1CxMrKCqWlpZDJZO2ORmpoaCA0NBSJiYmYM2cOWCwW+vTpg6+//hq//vor/vvf/2L16tWwsrLq0siwtrY2Xn/9dSQlJeGrr77CggUL2lynRGUNLFu2DCkpKdi4cSNcXV0xbty4Ti8sqR34AwcO0Clfrq6uzIu0FQiCgIuLCwwMDHDnzh26DyWVenv27Fnk5uaq5T0mFotRUFCAu3fv4uHDhxAKhejTpw+io6Ph6OjYJX1OGxoakJqairNnz4LD4WDkyJHo169fh4S2KEVZLS0tunf4y6DqvK9du8YIybQBNpsNf39/uLm5Yd++ffjyyy8xa9asV+osNDY24vTp01iyZAnYbDZcXV2xfPlyXLx4EV999RWioqIwfPhwZiHI0AKSJPH3338DAAYPHtxinuXk5OD27dv49NNPO/R+olocOTo6tvvzVG1wVFQU7QiRJIkHDx7AwsJC4e0v2wNJksjIyEBgYCCePn2qlBI7BqC2tha6urqdWhs1NTWBxWIxEXsFwaxS1RiCIGBlZYWioqKXilRQUDdXbW2t0mzq378/Hj16BLFYrLRjKAojIyPI5XLU1NS0+7OUUvbjx49RVVVFq0/r6+vjgw8+gKmpKebOnYuEhASIxeI2XR9FQBAEuFwuRo0ahdmzZ2Pjxo04d+4cpFJpm2ygPh8QEIDVq1fD0tISX3/9Nfbs2YPa2tp2fw+qF+SBAwfwzTffwMXFBStXroSbmxvjBL8Eqm3SsWPHmqUf8vl8jBs3Dvv27euyOfUi/tnrMyUlBb/99htWrlyJHTt2QENDA/Pnz6f7v3p5eUFLS0spaaskSUIulyM3Nxfbtm3D6tWrce/ePcyaNQvLly/HgAEDOpySWVtbi2PHjmHatGlt3izz8PDAs2fPIBQK23283ghBENDT08P8+fMxZcoUbNmyBTt27IBAIGh1jlPRYBcXF7p9CyUOFRUVhRUrViArKwtffPEFHj16BLlc3tVfiUGNKSsrw7FjxzB79uwWAQGhUIht27ZhxowZ7RbI+idpaWnw8PBo1zOHKsGorq6Gt7c3/VmpVIozZ85g5MiRKt34lEgkKCgogJOTE3JzcxlHWEnk5uZ2unyxoqIC+vr6Ku8G0lNgIsJqjpWVFU6fPt2mtkhcLhd2dnbIzMx8ZaudjmJoaAgzMzOkp6fD29tb4eMrEoIgYGxsjPLy8g4p8WprayMkJASJiYmYMWMGPSaXy8U777yDFStW4Pbt27hx4wZmzpxJqwB3xcuMqldcuXIlNm/ejMePH2P27Nm0WnZbPq+pqYlRo0Zh6NChSExMxOeff46goCBERka+chySJCEUCnH16lUkJCTAz88Pq1atalOqNsPz829rawtHR0dcunQJUVFR9NwZMGAAEhIS8OTJk3bXt3cWKuW4rKwM9+/fR0pKCmpqamBtbY2AgABMmjSJFp9T9nWWy+UQCARISUnBhQsXIJVKMXToUIwfPx76+vqdtkEul2P37t0ICwtrV022np4ezMzMkJmZiX79+nX4+L0Jam57eXlh1apVOHr0KD777DNMnz6d1iugEAgEOHv2LN5///0W14R6pr/55ptIT0/H7t27YWJigqlTpzKtRBggFovxxx9/YNKkSS3mA9W318bGBv369euUUFFxcTGsra3b/bnDhw9j9OjRzaLB6enp0NXV7dLsstZoaGgASZLQ0tJiFKOVBEmSKCwsbLOa/ouoqKiAsbEx87xTEIwjrOYYGxujoaGhTW2RKOfo8ePHCAwMVIo9BEEgNDQUly5d6tTLpKtwc3PD06dPO9SXjyAIhISEYM2aNRg5ciT94CEIAubm5pgyZQoePnyI0NBQ/PXXX7Czs8PEiRO7rH6NIAgYGhpiyZIldKr07Nmz4eHh0eZoLBWtmTx5MiIiInDmzBmsXbsWAQEBCAsLg5GRUbOxSJJEU1MTbty4gaSkJDg4OOD999/v8nrpngCLxcK4cePw/fffY/DgwXSEgsvlYvLkyThw4ADc3NyUuutLkiRkMhkEAgGys7Nx9+5dPH36FHw+H56enpgyZQosLS2hpaXVZUrjjY2NdF/U/Px8uLi4YPr06XBwcFDouXj8+DEKCwsxd+7cdn03KoX92rVrTBuldkIQz/vhTp06FYGBgdi5cydu3LiBuLg4Wnjo8uXL8PT0fKmYDIvFgoeHB1asWIErV67g22+/xZAhQxAZGdllc5VBvSBJEmfPnoWuri6CgoJaOMF5eXm4du0aPvnkk05lK9XW1kIul9ObcW3l0aNHdIkVZRslnDV27FiVi0nm5+fD2toaDQ0NANDu78fwaihHeODAgZ0ao7y8nFHSVyCMI6zmcDgccDgcCIXCNvUHdnR0xJkzZ5Rqk6enJ/bt24eqqiq17nlKEAScnJxw/vx5OrW5vejp6SEsLAyHDx/GggULmo09fPhw3L59GyKRCCtXrsTly5fxzTffICAgAFFRUV3WKkhDQwMxMTFwd3fHtm3b4OXlhfHjx7ernzQlbhMXF4eoqChcvHgR33zzDdzd3TFixAhYWVlBIBDgxo0bOH/+PBwcHPCf//yHEdToJObm5ujfvz8SExMRGxtLzxcPDw/w+XykpKQgICBA4W2GBAIBiouLce/ePaSlpaGurg62trbo378/LTjVVb0+Kec3NzcXV69exdOnT2FlZYUhQ4agT58+0NbWVrgdjY2NiI+Px5w5czpUZ9WvXz8cPXoUjY2NTIuRDkA9mz/66COcO3cOX375JcaPHw8vLy9cuHABy5Yta9NzhcfjITw8HAMGDMDRo0exZs0axMbGwtfXVyk6GQzqCUmSyM3NxYULF7BixYoWc0cikWDbtm2Ii4vrtIOXl5cHS0vLdm3KiUQiHDt2DDNnzmzm8GZnZwPAC1u2dRUkSeLRo0fw8PCgM+iY+0fxSCQSVFdXw8zMrFPjFBQUYMCAAQqyioGZ6WoOm82GgYFBm1NVTE1NIRKJUF9frzQlSA0NDfTr1w8pKSkIDw9X6913Ozs7lJSUdFhhjyAIDBs2DKtXr0ZBQQFsbW3pf+NwOHjttdfw448/ok+fPoiKikJwcDASExOxdu1aBAYGIjIyEgYGBvRYyoISYFqxYgUOHjyINWvWYO7cuXS6dnvGMTQ0xPjx4zFixAhcu3YNa9asgVgshkAgQHh4ON59912Ym5szDrACIAgCMTEx+PzzzzF8+HB6Y4nFYiEuLg6bN2+Gt7d3h0UxqBpMqVSK4uJiPH78GPfv30d5eTkMDQ3h4+ODWbNmwcLCAlwut0uuKWVTU1MTnj59iuvXryMrKwvGxsYYPHgwpkyZAh0dHaWVGZAkiYSEBLi6usLV1bVDY+jq6sLExAS5ubnw9PRUsIW9A4IgwOfzMWrUKPj5+eGvv/7Cxo0bMWTIkHZtsFLPrNmzZyM3Nxe7du3CuXPnMH36dNjY2NB/w9BzEYlE2Lp1K6ZNm9airIdKiTY1NW2TIN6rSEtLg7u7e5vHIUkS169fh7W1Nezs7Ojfy+VyJCQkNGujpCpkMhkyMjIQFhaGe/fuwcHBQaX29FQkEglIknxl68tXUVlZyaSuKxBmJavmEAQBGxsb5OXltenvNTQ0YGZmhoKCAqXaFRISgmvXrkEqlSr1OJ2FEvCh0n06gqamJsaOHYvdu3c3+76UmFloaCj27t0LuVwOXV1dTJ48GStXrgQArFmzBlu2bEFhYSHkcrlSBZCotMOZM2dixowZ+OOPP7B79240Nja267gkSUIsFiM9PR2pqanQ09NDREQE+vfvj+zsbNy6dQtVVVVK/z69BX19fYSGhuL48eO08A9BELC3t4e1tTWuX7/e5vNMCVxJJBLk5+fj/Pnz+Omnn7BixQr8+eefqKmpwejRo/H5559j+fLlGDVqFOzt7cHj8ZTqBFN2NTY24u7du9iwYQNWrVqFM2fOwNvbG59++ik++ugjDBkyhG67pCwnOC8vDzdu3MCkSZM6dYzg4OB2XRuG1iEIAhYWFnj99dcBPE9ZP3LkCJqamtp1blksFhwcHPDxxx8jJCQE69evx86dO1FfX89cox4MSZI4ceIE7OzsWrQ0o+73ixcvYsaMGZ1OP6aUlduzgVZXV4fz589j3LhxzWzLyclBY2OjWmykNTU1QSQSwcDAAJmZmXBxcVG1ST2Sqqoq6OrqdrrEp6GhoVNibwzNYSLCag5BELC2tkZeXl6b0nsJgoCnpyceP36stAcstXBhsVgoKipSa3VBNpsNS0tLFBQUdDiNmyAIBAUF4cKFC0hNTcWAAQPo60AQBCIiIvD111/j/v378PX1BUEQMDAwQFxcHKKjo3Hjxg1s2rQJ2traGD58OPr166fUOjZqDnz66ac4cuQIPv/8c8yYMQOenp4vXAhQzlNRURGuX7+O1NRUmJubIyIiAn369AGfz4dcLkdpaSn+/vtvfP/99zA1NUVISAi8vLygqanJRF06CDWHVq9e3UyEhcViYcKECfjpp58QGBjYagou5WCKxWKUl5cjLS0NDx48QGlpKbS0tODs7Izw8HDY2NjAwMCgS6P4lNqzQCDAo0ePcOPGDRQVFcHGxgbBwcGYPXt2l4urSSQS7NixA3FxcXTUuSMQBAFvb2+cPHkSTU1N7SpDYGidxMRETJgwARERETh06BA+//xzTJ8+/aXPrX9DEATd5q9fv35ISEjA559/jqioKISEhHRYXZxBPSFJEk+fPsXt27excuXKFvOEihTPmDFDIRlyAoEA9fX1tJr5q6CivsHBwXRmGPA8AnvixAnExMSoPBpMtYOysbEBh8PpkBAYQ9soKCiAlZVVp97DIpEIEomEcYQVCOMIdwNsbGzoyENbXuJubm7Yu3dvh+ti2wKbzcbgwYNx5cqVTkvBKxs3NzdkZGQ0a1nQXthsNmbOnInffvsNffr0afYQ4vP5dCsjJyenZjVIurq6iIiIQEhICLKysnDx4kUcOnQIzs7OCA4OhqOjI7S1tRXuoBAEAR0dHUyfPh1ZWVnYuXMnzMzMMHnyZFpNUy6Xo7GxESUlJbh9+zYePnwILS0t+Pv744MPPoCxsXEzu1gsFiwtLTFp0iSMHj0aT58+xZUrV3DgwAG4uLhg0KBBcHBwYMRqOoCmpiaio6Nx5MgRLFq0iF7QWVhYwMvLC+fOncOYMWMAPE9zpmp809LS8PTpU1RWVkJbWxuurq6IioqCtbU19PT0VCLAIpVKUV1djfv37+P27duoqqqCk5MTQkND4ezsDF1dXZXMD5IkcenSJejp6SkkRVJHRweGhobIy8vrkBgfw/9RUVGBlJQUWnn+tddeQ2ZmJnbt2gUzMzPExcW1S4SQev5NmjQJISEhOHz4MC5evIhJkyahX79+TNuRHoJAIMCWLVswZ86cFo4BlRJtaWlJb1B3luLiYhgZGbWpzIokSRQUFCAzM7OFAnp2djbEYrFaRIMB4O7du/Dx8UFdXR2kUqlaa790VxSlGF1TUwMejwdNTU0FWte7YRzhboCxsTFqa2shlUrbVFtgY2ODmpoaNDQ0QFdXVyk2EQSB/v3748yZMxAKhWp7UxIEAVdXV+zZs6dNLaheNo69vT369u2LEydOIC4urpmT6OjoiCFDhmDXrl144403mh2H6oHp6emJPn36QCAQ4PHjx7hw4QJ2794NMzMz9OvXD+7u7jAxMQGfz1eYo8BiseDi4oJPPvkEFy9exGeffYaIiAjo6Ojg4cOHdK2or68vli5dCgMDA7DZ7Jcen2q95O3tjb59+6KhoQGPHj1CUlISSktL4ejoiMDAQDg6Ora5nVNvhyAIBAcH4+zZs8jNzYWjoyNdIzt8+HCsXbsWOjo6yM7ORl5eHsRiMUxNTeHu7o6JEyfCwsICfD7/lddOGZAkCalUipKSEty9exepqaloamqCl5cXJkyYADs7O4XO6Y5SXl6OhIQELF++XCFRGBaLhYEDB+LGjRvtqhlkaA6V2hoaGkq/r1gsFlxdXfHJJ5/g0qVL+OabbxAZGYnQ0FBoaGi0yyE2NzfHwoUL8ezZM+zduxenT59GXFwcHB0dGZ2DboxMJsPu3bvh5+fXoqcvSZLIycnBtWvXWhXP6ihPnjxps/Mqk8lw4MABjB07tpnGg1QqxalTpxATE6MW808mkyEzMxNjx45FZWVll2cO9RYoQbexY8d2apyamhpmXaVgGEe4G8Dj8SCXyyGRSNrkCGtoaMDQ0BClpaVKc4SB54rK1tbWePToUbN0YXXD1NQUtbW1EIvFnXLYWSwWxo8fjy+++AIBAQFwcnJqliIdHR2Nr776CsnJyQgMDGz1fLBYLOjq6iIwMBABAQEQi8V49uwZHj58iO3bt0MgEMDQ0BA2NjZwdHSEiYkJ9PX12908XSQSoaamBpWVlSgrK0Nubi4KCwvB4XBw7NgxZGVlYeHChVi4cCGd1tyR68disaCnp4egoCAMHDgQjY2NePz4Ma5evYq9e/fCyMgI3t7e8PT0hJWVFb1BoK5zRRVQ9Ys8Hg8xMTHYunUroqOjkZGRgfz8fNTV1aGhoQF//fUXFi1ahLFjx8LQ0JB2elXh+ALP51h2djZu376NtLQ0sNls+Pn5Ye7cubC0tOwy1em2IJPJsGPHDsTExMDExEQhY1Lp0YmJiW1+NjM0h+rJ+vjxY3z22WfN5gu1gRgZGQk/Pz/s3r0bV69exezZs+Hs7Ez/TVtgsVhwcnLCsmXLkJqais2bN8PBwQGxsbFd1u6OQXGQJIk7d+6goKAAs2fPbnH9xGIxtm3bhmnTpims/ILq+Tt27NhXjkeSJG7dugVNTU14eXnRf0+SJLKysiCTyeDq6qoW866kpAQ8Hg+Ghoa4fft2hwUEGV4OSZKoqanptMhVVVUVI5SlYBhHuBvwT8e2rTL7VJ2wMkUPWCwWhg8fjpMnT6q1lDuPx4O2tjaqq6s7HbnW1tbGjBkzsG3bNqxcubJZihSXy8WCBQvwv//9Dy4uLjAyMnrhi45yYPh8Pjw8POjUSqFQiJKSEhQVFSErKwvJycmoqamBUCgEn88Hj8cDl8sFl8sFj8eDRCIBi8WCVCqFUCiEWCyGUCiEXC6HpqYmjIyMYG5ujr59+yIyMhJmZmbgcDjIzc1FfHw8fvzxR8TFxcHZ2blTAkXU99HR0UFAQAACAgIgkUiQk5ODBw8eYPv27WhsbISFhQX69u0LNzc32hZVOHOqgqrplclkaGpqQlFREQoLC5GdnY3i4mLU1tYiNTUVcrkc0dHRCA0NhYWFBSQSCVavXg0nJ6dOt17oqN1yuZyO/t+6dQuFhYUwNjZGQEAARo4cSafcA+q10UGSJG7fvo2mpiaEhIQo1DY9PT3o6uqisLAQDg4OavW9uwMkSeLo0aOIjo5+4bOZIAgYGxvjrbfewsOHD/HHH3/A1dUVsbGx7YqMUPXDAwYMQN++fXHx4kV89dVXGDRoEKKjo5mSjm4CSZKorKzE3r178d5777XYgKIyDGxsbDpVDvVvGhsbUVFR0Uz5+UXU1dXh5MmTWLJkSbPsMKo2eMyYMSrvG0yRnJwMb29vsNlsZGZmIjQ0VNUm9UgkEgnEYnGn9ST+3b2EofMwjnA3gMViwdraGgUFBXTK5MsgCAJ9+vShVWiVmebi7OyM+vp6lJaWwsLCQmnH6QxsNhtOTk7IyMiApaVlp16MBEHAy8sL169fR0JCQjMlSEpFesSIEdi5cyfeeuutNqdgUmNoamrC0dERjo6OGDx4MIDnL3aRSISmpiZIJBL6h4rMUQ4sm82mnWUej/fSiJyDgwOWLVuG+/fvY+fOnTA0NERsbCysra07/YKmjqmhoQE3Nze4ublBLpejtrYWhYWFtHBSY2Mj9PT04OzsDEdHR9jZ2UFbWxsaGhpKUw3uKijxMWqDorS0lN7gyM3NpVXMjY2NYW1tDW9vb4wYMQKGhobIzc3F/v37MXDgQDoLgM/nY8SIETh8+DAWLlzYZW2ORCIRKioqkJqaipSUFDQ0NMDJyQkhISFwdnbucrGrjlBTU4MDBw5gyZIlChem4XA46N+/P5KTk5mWI+2EUvQtKCjA3LlzX1mOQRAE+vXrh1WrVuH06dNYs2YNoqOjMWTIkHanS1P3U1BQEI4fP47Vq1dj5MiRGDx4MCOopeZIpVL89ddfGDVqFKysrFpcq+zsbNy4caNV8azOUFlZCR0dnVfWB8vlchw8eBDDhg1rln1CkiSePHkCLpfbLJtMlchkMty5cwcLFy6ESCRCcXFxm9aYDO2nrKwMenp6HW6FSFFaWgp3d3cFWcUAMI5wt8HOzg65ubkYOnRom/++vLwcjY2NSlWX4/F4CAoKwqVLlzBlyhSlHaczUCrK169fx7Bhwzo9HpvNxpQpU7BmzRr4+fk12yGmajpTU1Nx/fp1DBkypNMvFWrh1tkH6L+hFvFeXl64c+cONm3aBAsLC4wZMwZ2dnYKXUSwWCwYGhrC0NAQffv2hUwmQ2NjI6qrq5GVlYXU1FScOnUKYrEYfD4flpaWsLKygo2NDYyNjcHn86GpqdmuBa8yoRxdkUgEkUgEoVBIp6GXlZWhtLSUbjHFZrNhYmICCwsL2NraYsiQIdDX13/h9/Hw8IC2tjbu3LmDoKAg+vchISG4cOECXUOsDGQyGWpra5GdnY27d+8iOzsbfD4fffv2xcyZM+laZHW4Bm1BJpNh7969GDZsWKdFSl6Ej48PNm7ciNjY2G5zXtQBymEYO3Zsm3u8Uy3ixo8fj+DgYOzfvx+XL1/G1KlT4ebm1q5nFqXuP2PGDERERODIkSM4e/YsxowZgwEDBnSo7zyDciFJEufPnweLxWo1u0MgEODPP//EnDlzmolWKoK29A8mSRIPHz5EWVkZZs6c2exvJRIJjh07hpkzZ6pcKZqisLAQJEnCysoK1dXV4HA4aqv30p0hSRJFRUV0t5XOjMOkRise9bgbGV6JnZ0d/v777zYrQWtoaEBXVxdVVVVKl1kPDg7Gt99+i7Fjx6rtQ9TGxobu5asIB09fXx9TpkzBtm3b8NFHH7VIkZ4zZw6+++479OnTR61r0Kg6vODgYAwYMADJycnYvHkzTE1NERMTA2dnZ6WkcLHZbOjq6kJXVxd2dnYIDQ2FTCaDRCJBQ0MDCgsLUVRUhGvXrqG6uhpCoRBSqRRaWlp0zbS+vj4MDAxgYGAAPp8PDQ0N+ofD4YDNZoPD4YDFYtER5n8LqshkMsjlcshkMkilUkilUjriTqWZNzQ0oKqqCnV1dRAIBGhoaEBtbS0EAgFIkoSGhgZ4PB6MjIxgZmYGW1tbBAQEwMzMjI7Mt6dels1mIy4uDps2bYKPjw99T/F4PIwfPx4HDhzA0qVLFbKYoqK+xcXFuH//Ph48eIC6ujrY29vDz8+PbjOkChGuzkKSJO7fv4/S0tJXRhw7A5WqXlpa2ua2Kr0dqu1NQ0NDhxS8CeJ5C7/FixcjLS0Nu3btgqWlZTNV/LZCqeG/8cYbyM/Px4EDB+hWTv369VMbp4UByMvLQ1JSEj755JMWmhlyuRyHDx+Gp6cnvLy8FHpcuVyOR48eYcSIES+dWw0NDTh48CAWLFjQwr5r167BxsZGbdJaSZLElStXEBQUBDabjezsbIVvgDP8H7m5uZ1uNSoWiyEQCBhHWMEwT/hugp6eHurq6uh02FfBYrHg6emJhw8fwtbWVqmLWAMDA9ja2uLhw4cICAhQ2nE6A1VLVltbq5CHCEEQGDBgAK5fv47z589j5MiRzVKkzc3NMWbMGGzZsgXvv/++2i+mKId40KBBCAgIQGpqKnbt2gUOh4NRo0bRLUeUNY+o+j1qR9rU1BQ+Pj4A/q+uViqVora2FrW1taipqUFdXR2Kiorw5MkTNDU1QSQSQSwWQywWN0sdp8Zv7d6hfkf9l81mg8vlgsPh0CnmOjo6MDIygomJCezt7aGtrQ09PT0YGhrS0dF/OtmKOEf29vawtbXF1atXER4eTo/v5+eH06dPIy0trZkIS1ugvqNcLkd5eTnS09Nx9+5dFBcXQ0tLC97e3pg2bRrs7Ozo+drdnF8KkiQhEAgQHx+PxYsXK1XIisPhoG/fvrh37x7jCLcRuVyO/fv3Y8KECZ1qZcRms+me6ZcuXcLXX3+N0NBQREVFtTvFmcViwc7ODkuXLsXTp0+xf/9+nDx5EnFxcXBxcelVWgbqSFNTE37//XfMmDGjxTucJEk8fvwYjx8/xsqVKxV+bKq85WXlD3K5HEeOHIG/vz9sbGyazZX6+nqcP38eS5YsURtF5sbGRqSmpuKTTz6hz5+6tHPqieTl5cHX17dTYzQ0NIDFYqltwKm7ot6rcwYaHR0dEASB+vr6Zo3ZXwRVy3r8+PFmTpqyCA8Px9GjR+Hn56eWO4ocDge2trbIysqCoaGhQs4Hi8XCzJkzsXbtWvj4+DSrPyYIAkOGDMGdO3dw/vx5REZGdotFFEEQ0NDQQEBAAAYMGID09HQkJCRg//79CAkJweDBg6Grq9slL/N/O5ZsNhtmZmZ0BO5Vm0JyuZyO8lJiT/92jtlsdrOfV9UpdhUEQSA2Nhb/+9//MHDgQFr9ncPhYPLkydizZw/c3d1f6URQUW+BQICMjAykpqYiOzubbqs1fPhwODo6Qk9Pjz5uT2Hfvn0YOHCg0kWsCIKAv78/du/e/cqIEcNzUlNTaSdWEaUjlLq0v78/Dh48iNWrV2PKlCno169fu7IZKGfXzc0Ny5cvx/3797Fjxw4YGBhg8uTJtIPDXOOuhSpx8PDwaNETmCRJ1NfXY8eOHXj99dfpLgiKpLS0FPr6+i9Ml6dSovPz8xEXF9fCvjNnziAgIACGhoYKtaujkCSJe/fuwd7eHgYGBpBKpcjKysLo0aOZua0kqqurO339GxoaaF+AQXEwjnA3gcvlwtjYGCUlJW1yhAHA2toaFRUVEIlESt1BIggCzs7OEAgEKC0thZWVldKO1VGoOuHHjx/D399fYeMaGhpi/Pjx2LlzJ5YuXdrMMeFwOHjttdfw5Zdfwt3dvdNpMV0J5SRSvY+Li4tx4cIFrF27Fo6OjggLC4ODg4NKa3ZfdVzKue2utX5mZmbw9vbGuXPnaFE2gnjeF1tfXx+3bt3CoEGDWiy6JBIJBAIBsrKy8PjxYzx9+hQSiQR2dnbw8fHB2LFjYWxsrPZZCp3h8ePHyMrKwooVK7pkftrZ2dEp9MbGxko/XndGJBLh8OHDmDNnjkLnIEEQMDIywvz585GdnY09e/bg/PnztAPbns076vnn6+sLT09PJCcnY+PGjbC3t8fYsWM7XevH0HaoVknPnj3D8uXLW5x3uVyOvXv3YuDAgUoRoaKcXE9Pz1avOUmSqKurw759+/DGG2+0eN+UlZXhwYMH+PDDD9XGgZFIJEhKSsKsWbMAPHewSJJUarvN3kxDQwOkUmmb1+4vgnm/KIeeuxLqYRAEAUtLSxQVFb1SsIFCU1MTBgYGKC4ubnPbpY7CZrMxePBgXL58GVOmTFGbB/4/cXJywpkzZxQ6JkEQCAoKwq1bt/D3338jNDS02Xc3MjLCjBkz8Oeff+Ljjz/utHS+KqBUy2fMmIHx48fjwYMHOHToEAQCAQYMGICgoCCYmZmpZSZAd4bFYiEmJgZffvklhg0bRu8mczgcxMbG4tdff6UzMGpqapCbm4sHDx4gOzsbMpkMdnZ28PT0xIgRI+hohjrel4qmoaEB27dvx/z587vsfuNyuXBxccGTJ08wZMiQLjlmd4QkSdy8eROmpqZ0L2BFw2Kx4OzsjGXLliE5ORm//PIL+vTpg7Fjx760pV1r/LNkpH///rh+/TrWrVsHFxcXjB49GhYWFr3inlIl5eXl2LdvH5YsWdLCySRJEnfv3kVRURFmzZqllM0JuVyOhw8fYurUqa1ea5lMhp07d2LYsGGwsbFp8W9Hjx5FVFSUWqWzZmVlgcPh0JvzaWlp9MY2g+IpLy+Hnp5ep8pAACA/P19tasx7Eowj3I1wdnbGgwcPMHz48Db9PYvFQp8+ffD48WOlS+ITBIGBAwfi22+/xZgxY6Ctra20Y3UUU1NTSCQSVFdXK1RsgMvlYubMmfj666/h6ekJc3Nz+t8IgoCvry8ePnyIQ4cOYfr06d02kkAQz/sEBwUFITAwEBUVFbh27Ro2bNgAPp+PwMBA+Pr60mI1zAKx8xgaGmLw4ME4fvw4vXvf1NQEqVQKgUCAZcuW0alStra26NevH8aMGQN9fX2l1nSrK5QSsa+vL1xdXbv02AMHDsS5c+cwePDgXnfe24pAIMDJkyfx7rvvKv19pKGhgeDgYPj6+uLs2bNYu3Ythg8fjvDw8Hanz1Jq1WFhYRg0aBCuXLmCH374Ae7u7hgzZgzMzMyYa64ExGIx/vzzT4wdO7ZV1feqqirs3r0bS5cuVVrmj1gsRm1tbav920mSxKVLlyCVSjF8+PAW2Tnp6emora2Fv7+/2swPuVyOU6dOITo6mt68vnv3LgYOHKg2NvY0SktLYW5u3unzW1ZWptDe2AzP6Z4r8l6KhYUFSktL2/z3BEGgb9++ePjwYZtFtjqDrq4unJyckJqa2iXHay8cDgfW1tbIzc1V+NhmZmaYMGEC/vzzT0gkkmb/RhAEJk2ahLS0NDx48EAtz017oNIGzc3NMX78eHz22WeYMWMGqqqqsG7dOqxZswYnTpxAfn4+XZ/b3b9zV0PVNMtkMvj4+ODMmTPYunUr1qxZg//+97+Ij4/HgAEDUFNTgzfeeANr1qzBokWLMHjwYJiamqpNm6muhBJ8ycjIwPjx47v02FTKenFxMerr67v02N0FkiRx8eJF9OnTp9P93NsK5cCOGTMGK1euRGlpKVavXo2bN2/Sz6b2jqepqYnIyEh89tlnsLKywnfffYctW7agrKyMec4pEJIkcerUKejr67coAQGep/du2bIFo0aNaiFOpUgbcnJyYGZm1iKiS5IkcnNzcfbsWbz22mvN0vxJkoRYLMbBgwcxadIktSlDIUkSxcXFqKiooMUWpVIp8vLylJ412JvJysqCi4tLp8agRC5NTU0VZBUDhXrcnQxtwsjICHV1dZBIJG1OYTE3N0d1dTXdn1WZsFgshIeHY8eOHRg4cKDaPPwpCIKAt7c37t+/j/79+yt87MGDB+POnTs4d+5cM9EcajE2f/58/PLLL1ixYgUMDAx6hKNCqT07OTnByckJkyZNQmFhIVJTU7Ft2zaIRCI4OjrCx8cHbm5u0NLS6pateJQJ5fRKpVI0NDQgJycH2dnZyMzMRG1tLbhcLszNzXHr1i0sW7YM5ubmdMqvtrY2rl27Bnt7+159TkmSRENDA3bu3In58+erpNcxn8+HlZUVnj17RiueM/wftbW1uHTpEj7++OMuvzb/rB/Ozc3Fvn37kJSUhKlTp3aoRRz1TB81ahRCQkJw5coVfPfdd3Bzc2sWIe7N92RnoKKp165dw4oVK1qsJUiSxIULF8BisVqUIymalJQU+Pj4NMvkogS6tmzZglmzZtFig//k3LlzcHJyUrtn8+nTpxEWFkZH0PPy8qCnp9fp+lWG1iFJEoWFhZ3uqEJlJjCOsOJRL0+F4aXo6uqCy+Wiurq6Wfrty9DR0YGJiQlyc3Ph5uam9AeyjY0NNDQ08OzZM7rlhDrh4uKCs2fPQiaTKbymlcViYc6cOfjyyy/h5eXVYpfawcEBERER2LJlC95991212yhQBFwuFw4ODrC3t8eYMWNQXV2N7OxspKSk4MiRI+ByuXBycoKnpyccHBygra3da2pXgf/r29vU1ITq6mrk5OQgPz8fBQUFaGhooLMWnJycMGXKFBgaGkJXVxdSqRSrV68GQRDNyg6io6Px+eefY/jw4b26dQ9Jkti/fz8GDBgAZ2dnlc2ngIAAJCcnM+lr/4IkSZw8eRKDBg1SaQ9MgiDg4OCA9957D48ePcKOHTtgbm6O2NhYmJubd6hsRUdHByNHjsTQoUNx7do1/PTTT3B0dERMTAysrKy6bSmMKqmtrcWWLVuwYMEC6OvrN/s3kiSRl5eHM2fOYPny5UrVpiBJEmlpaQgNDW32e6lUip07dyIoKAgeHh4t7vXS0lJcv34dH374oVpd/5qaGjx+/BiTJk2ibb516xb8/PzUys6eBFWOZ2Fh0alxRCIRrVnAoFh63kq8B0PtaldWVrbZEabSox88eAA3NzclW/g8/Tg8PBxJSUmdTgVRBmZmZpBKpaiuroaJiYlCxyYIAoaGhoiLi8O2bdvw4YcfNovCEwSB8PBwPHr0COfOnUNUVFSPXSxT6dMmJiYwMTFBQEAAxGIx6urqkJGRgZSUFJw4cQJSqRSmpqZwcHCAs7MzTExMeoSwE9WyqKGhAbW1tSgoKEBxcTFKS0tRWVkJNpsNfX192NnZwcXFBeHh4TAwMACPxwOHw2nx3TkcDsaPH48DBw5g6dKl9CaKjo4ORowYgcOHD+ONN97olYJlJEniwYMHyMnJwccff6yyBR3Vsu7EiRMQiURKz8DpLpAkidLSUty7dw+ffvqpWtzXHA4H3t7e6NOnD65du4Yff/wRXl5eGD16dLsFtYD/00+IjIzEkCFDcPPmTWzYsAGWlpYYPXo0HBwceuW92REkEgm2bduGYcOGtVrnLxQKsXXrVkybNk1hrRBfRHl5OUiSbFYfTJIkEhMTQZJkq20RpVIpdu/ejbFjx6qdCvPFixfh5+dH2yWRSHDv3j0sXbpUxZb1XOrq6kAQRKfnglAoBI/HYzYslADjCHcz7O3tkZub267G556envjrr78QGxurRMv+j759++Lw4cOorKxUuLPZWVgsFuzt7ZGTk6MU2wiCwIABA3Dnzh0kJSVhzJgxzV6UXC4X8+bNwxdffEG3VFKHhaGyoXYyTU1NYWpqikGDBkEmk0EkEiE/Px+5ubm4dOkS3e5LV1cXJiYmsLGxgYWFBQwNDWFoaPjCHnrKOocvqvkjSRKNjY2oq6ujf0pLS1FaWorq6mrU1NRAIpFAS0sL+vr6sLW1hbOzMwYNGgRLS0v6hdae9El/f38kJiYiLS2Nru8iiOf9qi9cuIBnz56pNBqqKhoaGrBjxw4sXrxY5cqsOjo60NLSQllZGezs7FRqizpx4MABjBgxAjo6Oqo2hYZ6JoWGhiIwMJAW1AoODsbIkSM71K+TSpkODQ3FoEGDcOfOHWzduhW6uroYN24cXF1d6fueoSVUz12SJFvtyU2SJI4cOQJ7e3v4+Pgo/Tw+evQIbm5u9CYGpVKdnJyMDz/8sIUKMEmSuH79OjgcDvz8/NTqOjc2NtJRasqunJwcaGpqMum2SqSmpkYhpXAlJSUwNTVlHGElwDjC3QwHBwckJye36zOWlpYQCASora3tkjoQHo+HoKAgXLp0CRMnTlSrlwEA+Pr6IjU1FQMGDFCKbSwWC9OmTcOaNWvg7e3dwtk1MDDA7Nmz8ccff2D58uVqqbCtbKjaYg6Hgz59+sDd3Z3+N5FIhMrKSpSXl6OoqAh3795FdXU16urqIJfLoampCS0tLWhqakJfX592kDU1NekfDQ0N+ofqJ/zvBSjVc1cqlUIikUAikUAkEkEkEkEoFKKxsZG+b6qqqiAQCCAUCukf4HmLMl1dXejr68Pc3Bze3t4wMDCAsbEx9PX1m0WBOjvX2Gw24uLisG/fPri5udE6ATweD7Gxsdi7dy8++uijHply/yJkMhl27dqFQYMGKV0Zvy2w2Wx4e3sjJSUFtra2KrdHHXj27BkKCwuxYMECtTwfVLnB2LFjERoaihMnTmD16tWIiIhAaGhoh+rNKSc7ODgYAQEBuH//Pvbu3QsAiImJgbe3d69UdX8ZJEkiMzMTFy9exCeffNIigk6SJB49ekRnFig7wk45vaNGjQJBELQ41u7du/H++++3eG+TJInKykokJibi/fffVyuHhSRJJCcnw9bWlg4AUHXWISEhamVrTyM7OxuOjo6dHqewsBBWVlYKsIjh3/SeFVMPgVKOlsvlbX54aWhowNraGjk5OfD19VWugQAdpfruu+8wcuRItXL0CIKAm5sbjh07BrFYrJR6C4IgoK+vT/cPXrFiRYsUaW9vb6SnpyM+Ph5z587tVc5La/xzQcjn82FtbQ1ra+tm81Uul6OpqQmNjY1oampCU1MTampqUF1djeLiYvr3QqEQIpGIdnKlUimA507Tv2GxWLSjzGazoaGhAT6fDw0NDWhpaUFbWxv6+vpwdHSEjo4OeDweeDwe7Yy3lsasLAiCgLu7O3R1dXHnzh0EBQXRUeF+/frh9OnTSt3gUTdIksTt27dRVlaGuXPnqsV3JggC/fv3x7Zt2zB69Ohenw4rlUqxd+9eTJo0Se1Txann9vTp0xEZGYmjR49i9erVGD16NAIDAzukxE4QBLhcLgYMGAAfHx9kZmbi5MmTOHToECIjIxEYGAgtLS21mLuqhCRJ1NXV4Y8//sDcuXOhr6/f4pzU1tZi27ZtWLRoUZesKQQCAcrLy+Ho6AiSJFFRUYHffvsN8+bNa7V/tEwmw549exAdHa30lO32IpFIcPbsWcydO5f+XW1tLTIyMjB9+nQVWtazoerZ+/Xr16n5QJIkSkpKWq1HZ+g8vXv13Q0xNTWFQCBAU1NTu14G/fv3R0pKSpc4wsDzqKejoyNSU1MxePDgLjlmW9HR0aFFxzorYPAiCIKAj48P7t69iyNHjiAuLq7ZxgWLxcK4cePw448/4urVqwgJCWEecK+AxWJBW1u7zfNeLpdDLpfT7ZtaS3MmCIKOFHeHlEU2m41JkyZh48aN8PX1pVOBuVwu4uLisHnzZvTt21ftnQ5FUFFRQddMt1VFvyswMzNDU1MT6uvre7USK0mSuHfvHkiS7LL3jiIgCAJmZmaYP38+ioqKcOjQIZw+fRrjxo2Dj49PhyO5VPaLq6srCgsLkZiYiISEBAwcOBAhISEwNjbutZE5mUyGrVu3YsiQIXB3d2+1VdK2bdsQFhYGZ2fnLrEpNzcX5ubm4PP5qK+vxy+//IIxY8a06oyQJImrV68CgFr2401PT4empibs7Ozo6PatW7fQt29ftQpU9DTkcjmKioowatSoTo9TUlKCiIgIBVnG8E9651O3G8PlcukHc3twd3dHVlZWix63ymTEiBE4f/48xGJxlx2zLbDZbLi7u+PRo0dKPQ6LxcKUKVOQmpqKx48ft/h3Ho+H+fPn49ixY8jLy1OqLb0RFosFDocDLpcLDQ0NOpr7zx8NDQ1wOJxu1dKJqje+ePFiM+fe0dER9vb2LX7fE6EWxpQyrzpdOx6PB2dnZzx69KjHX4eXIRKJcPjwYUyZMqVbOngsFgvW1tZ46623MHfuXJw/fx5ff/01Hjx4QGeZdAQ2mw07OzssWLAAH330EUiSxHfffYfff/8dOTk5kMvlCvwW6g9VFyyTyTBy5MgWc4UkSZw/fx4ymazLBCZJksTNmzcREBCApqYmbNy4EYGBgXQWzr//trS0FElJSZg2bVqLumFVI5PJkJCQ0OzcikQiXLhwAVFRUSq2rmcjFAohEAhgbGzcqXFkMhkaGhp69caqMul+b6deDkEQMDU1RVlZWbs+R9WFVFZWKsOsFhAEAWtra2hra+Pp06dqtSAkCAK+vr64d++e0hcd2traeP311/HXX3+hpqam2XmgruWsWbOwceNGCAQCpdrC0DOgsgnOnDnTbEOMxWJh0qRJSEpKQm1trQotVC5UbRuHw8HQoUPVygkGnt/X/v7+uH37tqpNURlUhMza2lotarc7CqV+7+TkhA8++ACTJk3C0aNH8eWXX+LRo0eQyWQdfrexWCwYGxsjNjYWn332GTw8PLB582Z8+eWXSE5OhkgkUqv3pjIgSRIZGRk4d+4cFixY0Kr4VG5uLs6cOYO5c+d2WamBUCjE06dP4e7ujt9//x1OTk4YMWJEqxs6YrEYW7ZswYQJE1TaGqw1SJJEUVER6urqaIFFqtbaxMQE5ubm3fbe7A4IBAJap6QzSCQSkCSpVplPPQnGEe6GODs7Iysrq12foeoL09LSlGRVS1gsFqKjo5GYmKh2u9y2traoqKigRY+UBUEQcHJywrBhw7Bz584WdapUCrW/vz+2b9/eqUgDQ+/B1NQUAwcOxMmTJ5stlk1MTBAcHNzi9z2JgoICnD59GrNnz1bbGlxHR0cUFRWpXTZMV9HQ0IDTp0+rpVhiR6AcYg8PD3zyySeYMGECDh48iK+//hrp6emdcogJgoCmpiZCQkLw2WefYeLEibh8+TJWrVqFY8eOobq6Wu3en4qAJEnU1NTgzz//xOuvvw49Pb0W/97Y2IjNmzdj1qxZXVp3W1hYCB6Phz179sDQ0BATJkxo9Vkjl8tx7NgxWFtbq51KNEVCQgLCwsLoTQYqQhwTE9MtMzW6EwUFBbC0tOz0e6qmpgba2tpql23QU2Dugm4GQRCwtbVFfn5+u168lIhLampql71UCYKAi4sLhEIhCgoK1GphrqmpCXNzc2RnZyv9WARBICoqCgKBAH///XeL80AQBMaOHYva2lpcunRJrc4Tg3pCEARGjRqF5OTkZtkhBEEgOjoaqampKC4uVqGFyqGpqQmbN2/GtGnTOtTvtavQ09ODiYkJcnJyVG1Kl0OSJE6dOgV/f3+YmZmp7TXqCJRD3K9fPyxfvhwxMTHYu3cvvvnmGzx58qRTpUeUkr6npyeWLFmCpUuXQigU4quvvsKmTZuQnp4OsVjcY94PEokEf/75J8LDw+Hm5tZqyvGePXvQt2/fTosNtQcqmyE9PR16enqYMWNGq2KWVP/yJ0+etNAAUReqq6uRkZGBgIAAOhqck5MDqVQKJyenHnVvqhvUuVZERkxxcTHMzMzUco71BJiz2g2xtbVFaWlpu1+6Tk5OKCkpQVNTk5IsawmHw0FERAQSEhK67JhtgcViwc/PD3fv3u2ShYWGhgbmzp2L48ePo7CwsMUxuVwuXn/9dZw+fRrZ2dk9ZrHDoDx0dHQwYsQIHD58uNnmlra2NmJiYnDw4MFWlbK7K3K5HAcPHoSzs7PaRl8oqI3HO3fuqNqULqesrAzJycmt9oHtSXC5XPj6+uKTTz7B6NGjcfDgQXz77be4f/8+ncrYUVgsFiwsLBAXF4f//ve/8PPzw8GDB/HFF18gKSkJ1dXV3fodQUVStbW1ERYW1qoTfOvWLRQUFGD8+PFd6gDU19fj5MmTCA8Pf6kTXF5ejr1792LevHlqKU5IlZAEBAQ069996tQpjBgxgokuKpl/OsKdHae4uLhVpXIGxcA4wt0QTU1NyOVyiESidn2Oz+fD2NgYRUVFSrKsJVSroMLCQlRUVHTZcduCu7s7MjIyuixCbmpqSiv7/jtlkiAIGBkZYdasWdi8eXO7xdAYeh8EQSAkJAS5ubnNIo8EQSA4OBjl5eXIyMjo1gtmCpIkkZKSgvT0dLWNvvwbLy8vPH78uEdtRrwKuVyO/fv3Y8SIES1SXXsqXC6XjhCPGzcOx44dw1dffYXU1NROi1NSPY4HDhyIZcuW4Y033kBpaSm+/PJL/PLLL3j8+HG3S78nSRKpqalISUnBrFmzWnXISkpKsHfvXixcuJBWxu8Ku+rq6vDVV1/BxMQEs2fPfqGzKBKJ8Oeff2Ls2LGwtrZWSwdFJBLh5s2bGD58OG1fWVkZCgoK4OPjo5Y29ySkUikqKioU0pmksLAQNjY2CrCKoTXUfzXB0AIOhwNdXV1UV1e363NUPWpKSkqXLo75fD6GDh2KM2fOqNWi3MjICFwut8tSSAmCQEBAAOzs7HDo0KEWDjhBEPDy8sKQIUPwxx9/dKnCN0P3hMfjYeLEidi/f3+z+nINDQ3ExcVhz5493b7unOrhGR8fj4ULF6pl9KU1LCws6MhRb4AkSWRmZqKkpEQtRcyUCZXW7OXlheXLl2Py5MlITEzEZ599huvXr3c6pZka38bGBrNmzcLnn38Of39/HD16FKtWrcKhQ4dQWlpKt4tTVyiF5R07drywH3BTUxN+//13xMXFKa29YWt2lZWV4auvvkJpaSnGjBnzQieY6hdsb29PpxyrI8nJybC1tYWpqSmA598xKSkJQ4cO7bLNhd4Mdc939n1FzU1zc3MFWcbwbxhHuBvCYrFgb2+PZ8+etetzBEGgX79+XR6loCJUDx8+VKtIJ4fDgbe3N+7evdtlx2SxWJg2bRru37+Phw8ftli0sFgsjBgxAhwOB8ePH1frRQ2D6qEU0CUSSbP5RBAEPDw8YGBggGvXrnXreSSRSLBlyxaMHj0aNjY2arvw/DeUQOGTJ09UbUqXIJFIsGfPHkyZMgU8Hk/V5qiEf4pqffTRR5g7dy5u3ryJ//73v7h06RIaGxs7fS9S4lpBQUH4+OOPsWTJEgDAunXr8NVXX+Hy5cuoq6tTS6eYakU0ZcoU2NratriXZTIZDh48CHt7+y7rx0uSJNLT0/Htt99i1KhRMDU1hb+/f6vHJkkS586dQ0VFBWJjY9VWrE8qlSIpKQnR0dH096irq8O9e/cQEhLSbZ6h3ZnCwkKYmJh0WumZEo1j+j0rD8YR7oYQBAE7Ozvk5ua2+0VnZGQEqVTa5e1VdHR0MGDAAFy4cEGtXs5+fn5ISUnpUlVOTU1NLFiwADt37kRVVVWLf+dyuZg3bx6Sk5O7rIaZofvC5XIRFxeHAwcONEuTZLPZiIuLw/Hjx9HQ0KBCCzsOJbykq6vbLaOMfn5+uHfvXo+/h0mSxO3bt6GtrQ1PT09Vm6MWsFgsODs745133sGbb76JtLQ0rF69GsePH1dYjS9BELCwsMDEiRPx3//+F5MnT0ZWVhbWrl2LDRs2IDU1FQ0NDWox/6RSKfbs2QM3NzcEBga2+HeSJHH37l1kZmZ2WfmDVCrFhQsXsHXrVixatAhGRkYwNjZutQ0SSZK4d+8eLl26hAULFqj1Zk9mZiY4HA5dn0oJgHl5efWakgVVQpIk8vLyYGtr2+l5LBAIQBAEtLS0FGQdw79hHOFuiqOjI/Ly8trtwGloaMDd3R3379/v0pcjQRCIiIjArVu31CoqbG1tDbFY3KXpi1RLpaioKPz555+t1nhpa2tj8eLFiI+PVzvFbQb1w9nZGRYWFi1Uya2srODn54dTp051yzmUlpaG69evv1C0Rp0hCALOzs4oLi7u8T3CBQIBjh8/jilTpnSL+u2uhMViwc7ODgsXLsSHH34IgUCAL7/8Ejt37kRJSYnC7ksejwc3NzfMnTsXq1atwtChQ/H333/jiy++wMaNG1XqFJMkicuXL6O0tBSTJk1qMUeolOm9e/diwYIFSk/dJUkSDQ0N+PPPP3Hr1i0sW7YMLi4uuHTpEoYOHdoi0ksJH+3evRuLFy+Gvr6+Uu3rDHK5HAkJCc36HguFQly+fBnR0dEqtq73kJWVBWdn506PU1paCkNDQ0bcTIkwb6xuip6eHgQCQbtTnAmCwIABA5CcnKwky16Mnp4efHx8cOXKFbVZlFPtKh48eNClxyUIAqGhodDR0Wm15ytBELC2tsaMGTOwadMm1NfXq805Y1A/2Gw2YmNjcerUqWZOF0EQGDNmDG7duqXQRbeyIUkSVVVV+OOPP7BgwYJuG8Xg8XhdLlDY1ZAkiTNnzqBv376wsrLqdlH7roLFYsHU1BRTp07FqlWrYGhoiB9++AHr169HRkZGp3oR/xNKYKt///546623sGrVKgQEBODixYv44osv8MsvvyA5OZl+pyj7mUCSJJ4+fYqEhAQsXLiw1VRRsViMTZs2YcKECUoVn6K+b2ZmJtasWQNjY2MsXboURkZGEAgEePbsGby8vFp8pqysDJs2bcK8efPUfo6XlZWhpKQEvr6+dMuk+/fvw8LCose1M1NXKKVnKyurTo9TWloKc3Nz5ropEcYR7qZoamqCw+Ggrq6u3Z+1s7NDeXk5hEKhEix7OZGRkbh+/bpaRUgGDhyIW7dudbm6K5vNxqxZs3Dz5s1W64Wp+s+BAwfizz//hFQq7TaODEPXY2FhgQEDBrTYWNHR0cHo0aOxf//+Li0B6AxisRibN2/GyJEj4eLi0m0XAdQ93FNLHCghs2vXrmH06NFMNLgNEAQBXV1dxMTE4IsvvkBgYCDi4+PxxRdf4Pbt2xCJRAqbKywWC9ra2vD398e7776LTz/9FMHBwbh58ybWrFmD77//HpcvX0ZlZaXCHPF/U1VVhd9++w2vv/56q72/KaVxOzs7BAUFKdUJbmhowK5du/DHH39g9uzZiI2NBY/HA0EQuH//PhwdHaGrq9vsMzU1NVi/fj0mTpzYar9jdYIkSZw/fx4hISH0hoNUKkViYiJGjRql1rb3JCQSCZqamprNpY6Sl5cHOzs7BVjF8CKYt1Y3hcPhwMrKCnl5ee3+rLa2NqysrJCRkaEEy14MQRAwMDCAl5eXWgn4ODg4oL6+HpWVlV16XGpBtHDhQmzdurXV47NYLERHR0NDQwOHDx9Wm3PGoH4QBIHRo0fj1q1bKCsra/b7QYMGobKyEunp6Wo/h6geo/r6+q32GO1OUO3jnjx50u3Vu1uDJEns378fkZGRap0uqo4QBAEej4fg4GCsXLkS06ZNw/Xr17Fq1SocO3YMVVVVCtu4IggCBEHQWh2LFy/Gf//7X4wePRp5eXn46aef8Pnnn2Pfvn3IyMhAY2OjQo7d1NSEX3/9FWPGjIGrq2ur/YJv376N9PR0TJs2TSniU5TY0JkzZ/D555+Dy+Xi008/hYeHB22PXC7HxYsXERoa2szGuro6rF+/HhEREWqtEE3R0NCAu3fvYvDgwXQ0+NmzZ2CxWHByclJ7+3sKpaWl0NXVVUhdb2FhYacjywwvh3GEuykEQcDe3h45OTntXtgSBAF/f3/cvn1bSda9/NiRkZG4cuUKmpqauvz4rcFms9GvXz+kpqaqxElwdHTE6NGjsXnz5lZ7Q3O5XMyZMwePHz/G1atX1d6RYVAdurq6GDFiBA4dOtQsw4Fqp7Rv3z61bstF9Ri9f/8+Zs6cqbaqrO3B0NAQUqlUrbQRFMXTp09RUlLCKNF2Eg6HA3d3d/znP//Be++9B5FIhK+//hq//fYbMjMzFX7PUuI7Hh4emDlzJj799FNaLOr48eNYs2YNfvzxRyQkJCAvLw8CgaDd7x2qzZCdnV2rQnckSaKoqAj79+/HokWLFN4WjYrmnj17Fp999hlycnLw/vvvIy4uDjo6Os3sKSoqQn19Pdzc3Ojf1dbWYv369QgMDMSwYcPUPtuBJEncvHkTnp6edCkJSZI4ceIEoqKiesSztLuQn58Pa2trhcyZmpoaGBoaKsAqhhfRvdRHGJrh4uKCo0ePduizHh4eOHHiBMRicafl3duLsbEx3N3dcf36dbWI+FDtneLj4xEWFtblojwEQWDYsGHIyMjAsWPHEBsb2+IBqqOjg7feegtff/01TE1N4e7urvLzxqB+EASBkJAQXLx4ETk5ObRYB0EQ6NOnDwwNDXH16tUWkQ91gKqH2rVrF959990e0y5CQ0MDrq6uePz4MR2p6QmIxWLEx8cjLi6u2/R2VndYLBbMzc0xefJkjB49GikpKdi1axdIksSwYcMwYMAA6OrqKnQOEQQBDQ0NWFpawtLSEuHh4RAKhSgqKsLDhw+xa9cu1NfXw9jYGK6urnB3d4eFhQV0dXVfuNAnSRIXLlxASUkJ3nvvvVadsMbGRvz222+YMmWKQutuxWIx8vLycOnSJaSlpcHLywvvvvsuLCwsWrWXJMkWIlk1NTX4+eef4e/v30x0Sp2RSqU4f/483nzzTdre0tJSlJWVwdvbu8c8d7oD6enpcHd37/Q4AoEAEomEybZRMowj3I0xMjJCVVUVSJJs90POyMgI2trayMvLg4uLi5IsbB2CIBAVFYWff/4ZgwcPVotFlLW1NZqamlBVVQUzM7MuPz6LxcKsWbPw5ZdfwtXVFT4+Pi2uqYmJCd58801s3LgRy5YtY4QvGFqFx+Nh0qRJ2Lt3L5YtW0Zv7FDtlL7//nv4+fmp3ctVKBRi48aNiI2NbbXHaHeFIAj0798fly5dwuDBg1VtjkKg2rEYGRkx7ZKUABWxHTRoEIKCgpCXl4ezZ8/i1KlTcHd3R0REBOzs7OiUZ0XCYrGgpaUFFxcXODs7Y+zYsRCLxcjPz8fTp09x6tQplJeXg8fjwcLCAq6urrCzs4OFhQW0tLRAEATS09ORlJSEjz/+uNWNdplMhp07d8LLywsDBgzo8HegotQCgQA5OTm4c+cO0tLSoKOjg0GDBmHKlCn0htqLjtHQ0IB79+5hxYoVAIDKykqsW7cOgwYNQlRUVLdwgkmSxKNHj6Cvr0+n0ZIkiaSkJAwdOlQt1li9BZIkUVBQgPDw8E6PVV1dDW1t7S4PVvU2GEe4G6OnpweSJFFXVwcDA4N2fz4gIADJyclwdnbu8kWnqakp+vTpg8uXLyMyMlLli14ulwtfX1/cvHkTo0eP7nJ7qIXPwoULsX79elhaWrZwdKl2LLGxsfj111/xwQcftEjxYmCg6lKTkpKQkpICf39/eo5YWFhg8ODBOHToEF577TW1mTtSqRTbt2+Hu7u7UgVzVIW9vT0KCwshkUh6xKKmrq4OJ0+exIcfftjjrpU6QRAE2Gw2HBwcsGDBAjQ0NODWrVvYsmULnf0REBBAvwcUfS2oMfl8PlxdXeHi4oLo6GjIZDJUVlaiuLgYmZmZSE1NRXV1NVgsFvh8Pq5evYpJkyahpKQEMpkMenp6YLFY9HgXLlxAdXU1XnvttVc6mpTSM0mSkMvlkEqlKCsrQ0FBAXJycpCdnY3GxkZYWFjA29sbMTExMDY2pu1/1di3b9+Gq6srdHV1UVJSgnXr1mHkyJEICQnpFk4w8Px7JCQkICYmho5qNzQ04MGDB1i5ciVzj3YhQqEQ9fX1MDEx6fRYlZWVMDY2Zq6fkmEc4W4Ml8uFqakpiouL2+0IU1GKn3/+GRMnTuzyxRlBEBg5ciR+/PFHBAcHK0Rdr7P2DBo0CL/++itGjhypkp5tBEHAzs4OEydOxMaNG/HRRx+16KdIEASCgoJQVlaGzZs34+233waXy2UelAzN4HA4mDJlCn777Tf07duXnkfUfbd69Wrk5OTA0dFRxZY+F6o5ffo06urqMHfu3G6z+GwPenp6MDAwQF5enko2HhWJXC7H8ePHMWjQICYrpYugzrGuri7Cw8MxbNgw5Ofn4/Llyzh9+jTs7e0RGhoKZ2dnWgVZmXZwOByYm5vD3Nwcvr6+IEmSdlDXrFmD2NhY6Onp4e+//0ZVVRWEQiG4XC7YbDYaGxtx9epVTJgwASdPngSfz4eGhkaz+54kSTQ1NaGpqQmNjY2oqalBY2MjpFIpZDIZdHV1YWVlBScnJwwbNgwmJiYd+t4SiQQXLlzAggUL8PTpU/z++++YNm0a/Pz8utVzKD8/H/X19fDw8KB/d/XqVXh6eqpd5k9Pp6KiAtra2goRysrNzYW9vb0CrGJ4GYwj3I2hBLNyc3ObPQDbiomJCVgsFsrKymBjY6MEC1+OkZERfH19ceHCBYwZM0blCyozMzNoamoiLy9PZQqLVL1ybm4uduzYgfnz57eor2KxWIiJicH27duxa9cuzJ49mxHCYGiBvb09XF1dcebMmWb3l6amJqZMmYL4+Hh8+OGHKo1QkiSJe/fu4dq1a1i2bJlKNqC6AhaLhX79+uH+/ft03XZ3hEr7e/ToERNpUiEcDgeOjo5wcHCAQCDAkydPkJCQgIqKCvTr1w+DBw+GtbU1OBxOl1wj6hhHjhxBaGgoJk2aRL+T5HI5xGIxJBIJysrK8M0332DVqlXQ19eHSCSif8RiMT0el8uFnp4eLCwsoKmpCT09PWhpaUFDQwMaGhrgcrmddlRJksTDhw+hq6uL7OxsnDx5Em+++Wa326giSRKJiYkIDw+nn58ikQiXLl3C22+/3a2+S0+gqKhIYTXvhYWFCAoKUoBVDC+j+2x5MbSKi4sLnj592qHPslgs9O/fX2U9Lqla4Vu3bqGmpqbLj/9v2Gw2Bg8ejEuXLqnUDhaLhdjYWFRWVuL8+fOtXhsul4sZM2agrKwMCQkJ3aY/LEPXwWKxMGHCBFy8eBFVVVX076netlwuF7dv31aZCjmlGrtr1y4sWrQIenp6PXrR1rdvXzx48EDVZnQKmUyG3bt3Y8KECQqJeDB0DqolUkBAAJYuXYply5bB1NQU27ZtwxdffIHjx4+jqKhI6e8HuVyOo0ePQiqVYuLEic02Zql0aR6Ph8OHD2PixIkICQmBr68vBg4ciJCQEERGRmLkyJH0T3h4OEJCQuDv7w8vLy/Y2trC2NgYurq64PF4ConWymQyHDp0CPX19bhy5Qo++uijbucEA8/7NGdmZjZzmB49egQjIyOm7Y4KUJRQllwuR1lZGczNzRVgFcPLYBzhbo6lpSVKS0s79KKj2iilpKSorMelrq4ugoODcfbsWZW3BaIchCdPnqi8tROPx8OiRYuQlJSEJ0+etHpu+Hw+Fi9ejOvXr+P69esqP38M6oehoSHCw8Nx8ODBZs8IFouFGTNm4OjRo2hoaFCJbQ0NDfjll18wbdo02NjYdLsFaHuxtLREY2MjamtrVW1KhyBJEnfu3AEA9O/fv8dfr+4Gm82GkZERIiMj8emnn+KNN96ARCLBr7/+is8++wwnTpyg1wqKfFdQbXvu37+PBQsWtNp1gXKUtbW1ERERofK5Q7VpO3v2LGxtbfHhhx/CxMRE5Xa1F5Ik8ffff8Pf35/emJJKpUhISEB0dLSKret9kCSJ/Px82NradnosqizA1NRUAZYxvAzGEe7mGBsbQyKRoK6urkOft7CwgEQiaRYx6koIgkBoaCgePHiAyspKldjwT/T19eHk5EQv+FSJgYEBFi1ahK1bt6KsrKzVxYuOjg6WLFmCI0eO4NGjR4wzzNAMgiAQHh6O7OxsPHv2jJ4fBEHA0tISfn5+OHHiRJfPG7FYjN9//x1BQUG9xqni8XiwtbVFVlaWqk3pEI2NjTh48CCmTZvWY1PYewKUwJa1tTUmTpyIzz77DPPmzUNjYyN+/vlnfP755zh27BgKCgogkUg6de+TJInMzEwcPHgQb731Fq0a/e+/SU5OxoMHDzBr1qwub0/4b1ukUimuXr2KTz/9FKtXr8b8+fOhqanZLZ9BTU1NuHr1arM2lIWFhRAKhUyLRRVAbXRaWlp2eqz6+nrw+XyV3i+9BcYR7uaw2WwYGBigoqKiQ5/ncDjw9fVVaYqklpYWhg0bphYpvgRBICIiAufPn4dMJlO5LU5OThg3bhw2bdqEpqamFteIIAiYmJjgrbfewo4dO5o5OwwMwHMHbPLkydi7d2+zzA8Wi4VRo0YhJSUFhYWFXTZvpFIp4uPjoa+vj1GjRnUrUZrO4ufnp7JSlM5AkiROnDiB/v37KyTawdA1UE6xvb094uLisGrVKsyfPx8EQWDr1q347LPPsHv3bqSlpaGhoaFd71+SJFFRUYHNmzdjwYIFLxROy8vLw969e7Fo0SLo6Ogo8uu1C7lcjqKiIqxbtw4bNmxAQEAAIiMju62+BkmSSElJodPGgf8THoyIiGAcKBVQW1sLTU1N8Hi8To/FKEZ3Hb1nBdKDcXJyQnZ2doc+SxAEBg4ciOTkZJU5fpRic05ODoqLi1W+SHRycoJMJkNeXp5K7QD+TzzL3d0d27Zta/UaUaJps2fPxsaNG1FaWqoCSxnUFYIg4OPjAw6H08IJ09XVxfjx47Fz584uuf/lcjlOnTqFiooKlUeHVIG7uzuePXsGiUSialPaRUFBAe7cuaMWooYMHUdDQwO2trYYM2YMli9fjiVLlsDS0hKnTp3C2rVrsX79ely4cAHFxcWvnKNNTU3YsGEDxowZ88LoY21tLTZu3IjZs2crJErWEUiSRHl5Of766y+sW7cO3t7esLGxwdy5c7utEww8r3E+e/YsoqOj6c3EmpoaZGRkdKo3M0PHycvLg62trULO/bNnz9Siq0NvgHGEewDOzs7Izs7usANpbm4OmUzW4aiyIuDz+YiOjsbhw4dV7gizWCwMHz4c586dU7ktwPOo/8SJEyEUCnHixIlWd+0JgoCnpycmT56Mn376CVVVVWphO4N6wGazERcXh8OHDzerfycIAgEBAQCAW7duKXXOkCSJGzduIDk5GW+88UaP6KfbXgwNDcFms1X6rG0vUqkUu3fvxsSJE6Gtra1qcxgUAEEQ4HA4MDExQWhoKJYsWYJVq1YhMjIShYWF2LRpEz777DNs3rwZN2/eRHl5OV1bTJIkJBIJ/vzzT3h5eWHw4MGtLvzFYjE2b96MIUOGwNvbu0sdM6rncF5eHrZu3Yqvv/4apqam+O9//wvg+Wa3g4NDl9mjaEiSRHZ2Nh3tp353+fJlBAYGMvepCiBJEhkZGXBzc1PIWIWFhbC2tmY2NLqA3rUd3wOhes8ePXoUMpmsQxEWLpcLHx8f3Lp1S2U7/lTU6vz588jIyECfPn263IZ/2hIYGIiTJ0+iuroaRkZGKrOFQkNDA2+88QbWrl0LCwsLDBw4sMV1opwagUCAdevW4YMPPoCOjg7zIGWgnxPu7u5ISkrCuHHj6HnB5XIxa9Ys/PDDD/Dy8lJK30lqkXD48GF8+OGHvXZeEgQBDw8PPHnypFsoulLpl3K5HP7+/r3ymvV0CIIAQRDQ1NSEl5cXPD09QZIkampqkJWVhXv37uHkyZMgSRKWlpbw8PDA06dPIZPJMH78+FbnhFwux+HDh6GtrY3o6OgumTeUk97Q0ID79+/j4sWLEAqFGDZsGOLi4qCtrY36+nqcPn0aH374odLtUTYnT55EZGQkveYTiUS4evUqPvzwQ+Y+VQFyuRy5ubnN6rU7ikwmQ0lJCaytrRVkHcPLYBzhHoCRkREkEgkaGhpgYGDQ7s9Tjt/mzZsxevRolT1EuVwuJk6ciP379+P9999XacRIS0sLAQEBuHz5cjOnQZVoaWnhnXfewffffw8TE5NWWz0QBIFhw4ZBIBDgl19+wX/+859WBUwYeh8sFgvjx4/H2rVrERwc3Kwtg5WVFYKDg3H48GHMnj1boXW71O72b7/9hrfeegumpqa9dj5SG35JSUkYPny42tdHCwQCHDp0CG+++WavS2PvrVCOsZGREYyMjBAQEACZTIbq6moUFhbir7/+QnZ2NlxdXfH999/DxsYGTk5OsLe3h5GREV2C8fjxYyxbtkyp6cdUj+KKigo8efIEKSkpqK6uhouLC2JjY+Hi4kILu5EkiaSkJPj5+b2wnrm7UFpaiuLiYjrSTim629nZwcTERNXm9UqEQiEEAoFCzr9IJEJTU1OH1vMM7Yd5s/UAWCwW9PT0UFNT0+Ebh2oAnp+fT6faqAInJyeYmpri5s2bGDJkiMpeVgRBICwsDN9//z2ioqLUomcmQRAwNzfHvHnzsHnzZrz//vutOhUsFgvR0dEQiUT47bffsHjxYvB4vG794mdQDAYGBoiOjsbu3bvxzjvv0I4YQRCIiYnBF198gczMTLi6uipsvpSVlWH9+vWYPXs2nJycev08dHR0RGlpKRobG1UqHvQqKIEsX19f2NjYqNocBhXCZrNhbGyMvLw88Pl8bNmyBRoaGqivr0d+fj6ys7Nx48YNNDQ0oK6uDikpKZgwYQJu3LgBc3NzGBsbg8fjQUNDA1wuF1wut82bQJTSs1gsph2EgoIC5ObmIj8/H1VVVdDW1oa7uzvGjx8PGxubVlWgKysrcfPmTaxYsaJbP4NIksTZs2cxdOhQ8Pl8AM83BJKSkjBr1iy131zrqdTU1EBbW1shivpNTU3gcrnM5mMXwZzlHgBBEHB2dkZWVlaH6144HA6CgoJw9epVlTrCBEFgwoQJWL9+PXx8fKCnp6cyW4yNjeHo6Ijbt28jJCRELV6eVGrl2LFjsWHDBixbtgza2totbGOz2Rg3bhz27t2LzZs399qaTIbmEASBoUOH4vLly3j48CG8vb3pf+Pz+Zg2bRri4+OxfPlyhSlfrl+/HrGxsfDx8VGLe0jV8Pl8GBkZobi4GK6urqo2p1VIkkReXh7u3buHFStWMItrBmRlZSE+Ph5LliyBoaEhCIKAjo4OLC0tERAQAJIkUVZWhrVr1+LTTz+FtrY2ysvLcevWLVRVVUEikUAqlUImk4HL5UJLSws8Ho92kP/9bGhqaoJQKIRQKERjYyOA51ljGhoasLS0hJ2dHQYOHAgTExPw+XywWKwXPl9IksThw4cRFhamlNKPrqS+vh6pqalYuXIl/X0zMjLAYrEYcSUVkpmZCUdHR4U8K4uLi2Fubt6txdy6E4wj3AOg2uykpKR0qj4hICAA33//PWJjYxWyCO4IVEpWYGAgkpKSMHHiRJUtwqj2Mhs3bkRwcLDaOJKUknR5eTk2btyId999t1XbOBwO4uLisH37dmzduhXz5s1j+n8ygMvlYsaMGdi2bRtcXV2hqakJ4P8E1y5fvoyLFy8iKiqqw88SkiRRX1+PDRs2ICIiAoGBgYwT/P8hCAL9+vXDvXv34OLiopbnRSaTYceOHZg0aRIjvNPLoVSXN23ahAULFrQq4EMQBEQiETZv3oxx48Zh+PDh9N9QtbvUj1wuR2NjIxobG+kor1gsplXrqZZPXC4Xmpqa0NTUhJaWFjQ0NGhnl/ppK/n5+cjMzMSMGTPU8n5rKyRJ4vr16/Dw8KAderlcjoSEBIwcOZJxnFQESZLIysqCp6dnp+cXSZLIz89nsnC6EGabt4fg5OSE/Pz8Zn1C24uJiQn09fU73IpJUVBpyU+ePEFRUZFK1Y9tbGxgaWmpdEXd9sJisTB69GgYGBggPj7+hdedy+Vi9uzZAIDt27dDLBZ3pZkMaghBEHB1dYWdnR0uXLjQbF6zWCxMmTIFSUlJqKys7NCcJ0kSTU1N+PXXXzFgwAAMGzasWy8+FQ1BEPD29sbjx49V3qu8NUiSxN9//w1tbW34+voy164XQ21orVu3DrGxsS9skySRSPDXX3/B0dGxxWY8QRBgsVhgs9ngcDjQ0NCAgYEBrKys4ODgAHd3d/Tr1w++vr7w9fWFj48P+vbtC3d3d9jZ2cHU1JROOWWz2S+N/LaGTCbD3r17MW7cOHrTr7siEolw4cIFjBgxgj4HpaWlKC0tRf/+/VVsXe9FJpMhNzdXYRH5/Px8hbVhYng1jCPcQ9DW1oZUKoVIJOrUOFTapKqdPj6fj3HjxuHAgQMqXSyyWCyMHTsWJ0+eVLvenxwOB7Nnz0Z5eTlOnjzZalsl4Lkz/Nprr0EsFiM+Pp5xhhlAEAQmT56M8+fPo7KystnvjY2NMXLkSMTHx3foOUDVpjs5OTXrccnwfxgbG9PiKupGdXU1Tp48iRkzZjARpl6OUCjEb7/9hsGDByMoKOiFCtGnT59GQ0MD4uLi1Op+J0kSDx8+RGNjIwICArq1Y0GSJJ48eQJjY2NacZ4kSZw/fx4hISFMtpcKkUgkEIlE0NXV7fRYMpkMRUVFsLW1VYBlDG1BfZ5YDJ1CQ0MDRkZGKCkp6fAYBEGgf//+yMzMRH19vQKt65gtnp6e4PF4uHv3rkodczs7O5ibm+PGjRsqs+FFaGhoYNGiRUhJScHff//9wvPE4/Ewd+5cNDY2Ys+ePWrn1DN0PUZGRoiIiMCBAweabaJQyuPV1dVITU1t15hCoRB//PEHTExMMHHiRMaRegE8Hg/29vbIyMhQ+abjP5HJZDh48CBCQ0NhamqqanMYVIhEIsGOHTtgbm7+wjIJSq34xo0beP3119XOGROJRDhw4ACmTZvW7YWHZDIZTp8+jVGjRtHXghImU6WwKANQWFgIY2NjWrysM1ABLaYkpetgHOEeAlUnnJmZ2amFlba2NlxcXHD//n0FWtcxOBwOYmNjcfLkSTQ0NKjMDhaLhUmTJuH48eNqF8GhBEvefvttJCYmIiUl5YXXn8/nY968eWhoaMDOnTsZZ7iXQzm8BQUFePr0abN5o6GhgTlz5mD37t2oq6tr03gikQh//PEH9PT0esTCU5kQBAFfX992bzQoE5IkkZ6ejoKCAkRERDAL616MTCbDgQMHIBaLMWXKlFbvZZIkkZOTg71792Lx4sXQ1dVVqzlDpfibm5urbS1+e8jPz4dAIKAV/UmSxM2bN+Hp6alSUdHeDkmSChXKqqmpgaampsp0enojjCPcQyAIAm5ubsjMzOz0WGFhYbh06VKn6o0VhampKYYMGYIjR468MPW3K7C2toanpyfOnj2rVhEc4P/SWRcvXoxdu3a9dDOEz+dj/vz5EAqFTM0wA/h8PqZOnYodO3a02Bixt7fHwIEDcfDgwZfeeyRJQiQS4c8//4Suri6mT5/ORILbgLOzM7Kzs1X6XKMgSRJCoRDx8fGYMWOG2ggDMnQ9lPhSTk4O5s+f3+qCnCRJ1NTU4JdffsFrr70GS0tLtXM06+rqkJiYiMmTJ6udbe1FLpcjMTERUVFRdNRdIpHg4sWLzeqFGVTDkydP4OHhoZCx8vPzYWVlxbxDuxDGEe5BWFlZobi4uFM1tQRBwN7eHo2NjSgrK1OgdR23Z9iwYSgqKmoRtepqO8aPH4/Lly83q6lUFwiCgI2NDRYtWoSNGzciPz//pWnS8+fPh1QqxbZt2yASidTOuWfoGqgSBCsrqxabPFRv4aysLKSlpbU6Rygn+Pfff6edYA6HwyzM2oCBgQF4PF6nylkUyalTp+Dm5tYjomcMHYMkSVy+fBm3bt3C22+//UJxqaamJmzYsAExMTHw8vJSu/lCkiROnjyJgQMHwszMTO3saw8kSaKyshLZ2dnw8/Ojo8GPHj2CsbExLCwsVG1ir0Yul6O8vFwh14FqW8cIZXUtjCPcg9DW1qZbE3QGLpeL4OBgtRDNouyJi4vDwYMH0dTUpDI7DAwMEBYWhsOHD6tFFKc1XFxc8Nprr2HDhg0oLS194fXT0NDA3LlzwePx8Mcff0AoFKrFtWboelgsFqZOnYqzZ8+22Pzi8/mYNWsWdu3a1eq919TUhI0bN8LY2BhTp05VuxpBdYbD4cDd3R2PHj1StSkoKCjA7du3MW7cOLUSO2LoOqh636SkJLz77rvQ0dFp9e9EIhG2bt0KV1dXtVSEJ0kSxcXFSE1N7THR0rNnz2Lw4MHQ0tIC8Pw7njp1CiNGjGAihyqmqqoKBEEorD91dnY2nJycFDIWQ9tg3ng9CB6PB3Nzc+Tl5XVqHIIgEBQUhLt373ZahVoREAQBBwcH9OnTB6dPn1aZE0q1dcrJyUFWVpZaOo5Uj9KJEyfi559/RlVV1Uud4enTp8PIyAgbN25U6SYDg2oxNDRETEwM9uzZ06wkgmq11KdPHxw/frzZXKqrq8PPP/8MGxsbxMXFMU5wB6DqhFX5LJFIJNi+fTtiY2OZWsNeClUfvm/fPrz11lswMjJq1YGUyWQ4fPgwCIJAbGysWm6akCSJffv2YdSoUQpR8VU1AoEAd+7cQUhICH1N8vLy0NjYCDc3NxVbx5CXlwcrKyuFaGJQJQeGhoYKsIyhrajfU4yhwxAEARcXl04LZgHPFWVtbGxUvkijIAgC0dHRePz4MXJzc1VmE5/PR1xc3Et796oagiAQGBiIqKgorFu3DnV1dS88X1wuF5MnT4aDgwN+/PFH1NfXq8X1ZuhaCIJASEgIamtrcf/+/Ra9hcePH487d+4gOzsbJEmiqqoKP/30E/r27YvY2FhGGKuD2NnZoaKiotNZPB2FSoXV0dGh0y4ZehckSSI/Px+bN2/GG2+8ASsrqxcqRJ8/fx5ZWVmYO3euWt7zVIuhqqoqBAcHd/v5TJIkrl69ij59+tDOEUmSSExMRGRkJLP5qAY8efIEnp6eChmrsbERUqm0R2zgdCcYR7iH4ebmhvT09E6Pw2KxEBUVhaSkJLVxjP7phKoqUk0QBPr27Qs9Pb2XtitSNSwWC0OHDsXgwYPx008/vXShzeFwMH78eAwYMADfffcdKisr1fZ7MSgPDoeDWbNmYe/evS3mi46ODmbMmIFt27YhLy8P33//PYYOHYro6Ohuv9hUJVpaWjA2NkZ+fr5Kjl9RUYGEhATMnDmTSbHshZAkifLycqxbtw6vvfYanJycXtom6fz581i8eDH4fL5a3vdisRjx8fGYNm1ajxB8E4lEOH/+fLOWSVVVVcjKykJgYKBaXoPeBEmSePbsGRwdHRUyXklJCQwNDRnF6C6GcYR7GKampqiqquqUYBaFs7MzRCKRyhZp/4YgCDg7O8Pd3R0nTpxQmbPGZrMxdepUnDhxos2tZVQBi8VCREQE+vfvj/Xr17+09ROLxcKIESMQERGBH374AUVFRYwz3MughPK8vb1b3F/UBpCOjg7effddTJgwAaGhoWCxWMxirBNQvdtV0UZJKpViz549iI6OhpGRUZcfn0G1UJkdP/74IyZPnoy+ffu+0AnOysrC7t278fbbb8PQ0FAt73mSJHHp0iVYWlrC3d1dLW1sDyRJIjU1Febm5rC0tKR/d/HiRfj7+79QyIyh6xAIBKivr1eYYFlxcbFaKrD3dBhHuIehr68PPp+vEMVnLpeL4cOH48yZM2rjFLFYLIwePRrp6elIT09XmV0WFhYYNGiQWgtnAc+d9piYGLi7u+PXX399aT9mgiAwdOhQxMbGYv369SpV6WZQDSwWC2PGjMHdu3ebKY/L5XKkpKSguLgYRkZGMDU1VbGlPQdPT0+kp6d3aakFSZK4e/cuGhsbMXToUGbh1csgSRK1tbVYt24dRo4ciYEDB77QCS4tLcWmTZvw+uuvw8rKSgXWto2qqiqcOXMGU6dO7RHzWSKRIDExEWPGjKF/19jYiBs3biA8PLxHfMfuTmlpKa3+rwgyMzPh6uqqkLEY2g7jCPcwWCwWrK2tFRbFDQoKQlpaGqqrqxUyniLg8/mYOXMmdu/erbKILFWz/OTJE+Tk5KjEhrbCZrMxbtw4ODo64rfffntpmjRBEPDz88P8+fOxefNm3Llzh3GGexm6urqIjY3F9u3bIZPJIJPJkJiYiMOHD2PZsmV4++238ddff6mFkF5PwMLCAkKhEDU1NV12zNraWhw8eBAzZsxg6gx7IQ0NDVi/fj1CQkJeuhFSV1eHX375BZMnT1brKKtcLseRI0cQGhoKY2NjtbWzPTx9+hQcDodOVydJEikpKXB0dISxsbGqzWMAkJGRAXd3d4WMRZIkCgsL1XqzqafCOMI9EC8vLzx+/FghY2lra8PPzw9XrlxRK4fIzs4OQ4YMwb59+1QmWqWpqYnJkydj9+7dkEgkKrGhrbDZbEyYMAG2travVIimlILff/99HDhwAOfOnVNIqj1D94AgCAwYMACampo4e/Ystm/fjocPH2LZsmWwtLSEj48PrKyskJCQoFbPhO4Km82Go6MjsrKyuuR4crkce/bsQUhICKytrXuE08DQdhobG/Hzzz9jwIABCAsLa1X5mSRJNDU14ddff0VwcDACAgLUdp5QdZrZ2dkICwtTWzvbg0wmw6lTpxATE0NfH4lEgjNnziA6OlrF1jEA/6e0rihHWCQSoa6ujsm2UgGMI9wDsbOzQ15ensJSdqOionD16lWVKZu2BkEQGD58OEQiEa5fv66SBTlV36ehoYHbt2+rvVPAZrMRGxsLW1tbbNiw4ZWRYXNzcyxfvhw3b97E3r17IRaL1f47MigGFouFsWPHYvXq1WhsbMS7774LPT09EAQBFouFuLg4XL9+HTk5OcycUABd1UaJJEncu3cPZWVliIiI6BFOA0PbaWpqwoYNG+Du7o6RI0e+sP2RRCLBH3/8AQcHB4wYMUIt2yRRSKVSxMfHY/LkyeDz+ao2p9NQkcHa2lp4eXnR0eDMzExoaGjA1taWuW/VAKFQiJKSEjg4OCjkelRWVkJTU5PuFc3Qdajv042hw1hYWEAgELy0HrStEAQBIyMjODg4ICUlRa0WvRwOB9OnT8eZM2dQUFCgEtso4awjR468VIxKXaCcYUdHR2zYsOGVNcP6+vpYunQp6uvrsWnTJggEArWaAwyKhxLH2bx5MyZMmACJRAI2m02/7AmCgJ6eHqZPn44tW7YwKdKdhCAIuLu7IycnR+nnsr6+Hnv27MGcOXMYZdJehlAoxObNm2FjY4Nx48a9UCWccix5PB4mTZqk1mriJEnixo0b0NbWfqHYV3eDJEmcPHmyWXskuVyOU6dOYdSoUWp9PXoTtbW10NDQUJhoWWlpKczNzRUyFkP7YBzhHgiHw4GhoSHKy8sVMh6LxUJ0dDROnz6tdinAhoaGmDp1KrZu3aqyiLW1tTX69++P48ePdwsnkUqTdnV1xYYNG17aZxh43uJl3rx5sLW1xffff4+ysrJu8T0Z2o9UKsX58+fx+++/Y+7cuVi6dCmampqQnJzcQkXa29sbLi4uOHTokFoLxnUHtLW1oampicrKSqUdQy6X4+DBgwgKCoKdnZ3SjsOgfohEImzbtg36+vqIi4t7YQ9gmUyGI0eOoLq6GnPmzFH7+vG6ujocPXoUU6dOVcu+xu2FJElUVFQgJycH/v7+dDS4qKgIVVVV8PDw6BHOfk8gKysLjo6OCsuWePr0KSOUpSIYR7iH4u7urpB+whS2trbQ1dXFgwcP1MoJIggCHh4eGDBgAOLj41VSL8xisRATE4M7d+6goKCgy4/fEdhsNsaOHQtvb2+sW7cOtbW1L72uXC4X48aNw4gRI/Ddd9/hyZMnajUPGDoHSZIQCATYsmULkpOT8dFHH6FPnz7gcrmYNWsWDh48iNra2mafYbFYmDx5Mh4+fKgwTYLeCpvNhqenJ+7fv6+U+4okSTx8+BB5eXnNepIy9HwkEgl27twJNpuN6dOnvzCiKJfLcfbsWaSnp2PhwoVq34eX2tgZNGgQ3V6oJ3Dq1CkMGzasWYpsYmIiwsPDmSwONYEkSaSlpcHDw0Nh4+Xn58POzo55NqsAxhHuobi5uSm0/Q2lPHz06FG1E04iCAJRUVEQCoU4d+6cShw0XV1dTJw4ETt37lSZeFd7YbPZGDlyJIKDg/G///0P1dXVLz13LBYLQUFBWLx4MbZt24YLFy5AJpMxDnE3hyRJ5ObmYs2aNXQqvJGREQiCAEEQsLa2RkhICPbs2dMi8qupqYl58+Zh+/btr8wsYHgxBEHA19dXKY4wSZJoaGjA7t27MWfOHLV3cBgUh1Qqxc6dOyESiTBnzhxwOJwXtkm6efMmrly5grfeegtaWlpqvSCnyjcyMjIQHR2t1ra2h+rqajx48ABDhgyhv1N1dTXS0tIQGBjYY75nd0cqlSInJwcuLi4KuSYikQgVFRWwtrZWgHUM7YVxhHsgBEHAwcEBJSUlEAqFChvT2dkZWlpaahcVBp5HLOfOnYvr16/j0aNHXW4fQRAIDAwESZIt0kjVGRaLhbCwMERFReHbb79FaWnpS20nCAKOjo74+OOPcfPmTfz1118QCoXd5vsy/B8kSUIikeDs2bP4+eefMW3aNEyePBkaGhrNXu4EQSAyMhLFxcUtHDXquTBo0CDs3r1b7TbJuhOWlpaorq5W2DObgiRJ7N+/HwMHDoS9vT2zmO4lUJHgxsZGzJ8/H1wu94VO8MOHD3H48GG888470NfXV/s5IhaLER8fj+nTp/cIgSzg+XU4c+YMgoKCoKurS//uwoULCAwMhI6OjootZKAQCASQyWT0deosDQ0N4HA4Cqs3ZmgfjCPcQ+Hz+eByuQrts8vhcDBu3DgcOXJELRe82tramD9/Pvbs2YPi4uIud87YbDZmzpyJQ4cOKUSorKtgsVgYMmQIJk+ejB9++AHPnj17pTNsZGSEpUuXQkNDA99//z3Ky8sZZ7gbQdWirV+/Hg8fPsQnn3yCfv36vbDeic/nY86cOYiPj28xt6me2pWVlbh58yYzDzqIpqYmzM3NX3n/tQeSJHH//n0UFBRg5MiRau/gMCgGsViMXbt2QSAQYMGCBeDxeC90grOysrBt2za8/fbbMDU1Vfs5QpIkLl++DCMjI1pVuSdQV1eH27dvN1NzFwgEuH79OqPwrmY8e/YMtra2CsuuqaiogLGxsVqrs/dkmLPeQ1FWb0o3NzfweDw8ePBAoeMqAoIgYGNjg0mTJmHz5s1oaGjo0kU5QRCwtbWFr68vTp482a0EhAiCgJ+fH+bOnYtNmzbh8ePHrzx3fD4f06ZNQ1hYGL799lvcu3evW33n3opUKsWNGzfwzTffoH///nj77bdhbGz8yoWWo6Mj/P39cfDgwRbXWUNDA/PmzcPhw4dRUlLCOMMdgMViwdvbG6mpqQobs66ujk6J7imRM4aXIxaLsXv3bjQ2NtJOcGtQJREbN27EG2+80W3a8lRVVeH06dOYMmVKj1FQppx7Hx8fGBgY0L+7ceMG3NzcYGRkpFoDGWhIksSjR4/g6empsPslMzMTzs7OChmLof0wjnAPhWrJkZ6ertBFKZvNxsSJE3HkyBGIxWKFjasoKDXb4OBg/P77711uI0EQGDNmDO7evYvCwsJu5RAQBIE+ffpg8eLF2L59O27cuPFK+9lsNgYNGoT//Oc/2LdvHw4dOqSW84Lh+Qu8srISGzZswLlz5/Dee+9h+PDhbVaGpeb206dPW2yUUH2nJ06ciM2bN6udunx3wcPDA2lpaQp5bshkMuzevRtDhw5lVKJ7CRKJBLt27aLToV8UsaKUiH/55RfMmzcPrq6u3cIJlsvl2Lt3LyIiImBqaqpqcxSGQCDA5cuXMXLkSPp3IpEI586dQ0xMjAotY/g3crkcmZmZcHNzU8h4JEkiJydHYf2IGdoP4wj3YFxdXfHs2TOFize5ubmBz+erZa0w8DyyEh4eDjMzM5WIV+no6GDixInYtWuXWqaQvwyCIGBvb4/3338fJ0+eREJCwiu/A0EQsLOzwyeffIKysjL873//Q1VVlVrOjd4ISZKQSqW4fPky1q5dC09PT3z00UewtLRs94uXz+dj3rx52LFjR4uMC4IgMHDgQFhYWODo0aPM9e8ApqamkMvlnW6jRJIk7ty5g4qKCkRFRTELrF6ARCLBtm3bIBKJaCf4RenQZWVlWL9+PaZPn67QyJYyIUkSjx8/RnFxMUJDQ7uFzW2BJEn8P/buOz7H6/8f+OvK3nvvHdmSiBgxQ+ytZs2itm5US2lpVWmrahUtsUuV2HsGkSGRSITInmTPe13n90d/1/3lY0XcO+f5eHh8+hG5r3Nf87yvc877fePGDfj4+MDCwkJcMiklJQWWlpYtuk9T0tPQ0AAejyceuX9XfD4fxcXF9GWlHNFAWIUZGhpCIBBIPPkKwzAYMWIEjh07prAjP+rq6hgzZgz4fL7MM10zDIPQ0FAAUKrEWRyGYWBlZYUvvvgCKSkp2L9/P3g83ht/x8DAADNmzED79u2xcuVK3L17l06VljNCCAoKCvDjjz/izp07+Pzzz9G7d+9XJs55Ey5ZWlhYGA4dOvTCua2uro7x48cjKSlJaqWAVJmmpiY8PDyQnp7e4s8ghKCiogKHDx/G1KlTFb4WLPXueDwe/vzzTxBCMHXq1NcGwRUVFVi/fj2GDRuGtm3bKk2Q1djYiN27d2PChAkqNc2/sbERFy5ceK6smVAoxOnTpzFgwAC6blSBEELw+PFj2NnZSewc5JKNPlsui5IteoWpMG1tbdja2iInJ0ein8tlijUwMFDozq6GhgYmT56MrKwsnDt3TqZBmaamJsaNG4fDhw+jvr5eZtuVJENDQyxYsAD19fXYvHkzamtr33isNTQ00LNnT8yfPx9HjhzB/v370dDQoLDniKoihKCmpgYHDhzA+vXr0bNnT3z00UcSGV1QU1ND//79kZOT89JZIXp6epg+fTp27979ziObrVFoaCgSEhJafM0IhUJER0ejb9++dDSpFWhsbMT27duhoaGBKVOmvDaBT1VVFX755Rf06dNHqcrxEEIQExMDX19feHh4yLs5EsONBnt6esLKykr8d1lZWWAYBm5ubnJuIfW/JL0+uLi4GJaWltDQ0JDI51FvjwbCKoxb85meni7xQERNTQ1Dhw5V6FFhhmGgo6ODmTNnIiEhAVeuXJFpQObo6Ijg4GAcO3ZMKQNBhmGgq6uLKVOmwNnZGWvXrm1WdmhuqvSiRYsgEAiwevVq5ObmKuU+UDaEEPD5fNy4cQPfffcdCCFYunQpwsPDJfqg1dXVxaRJk7B7927U1tY+9zOufFu/fv3w559/0jXjb8nNzQ3FxcVobGx8698lhODatWsA8FwtUko1NTQ0YOvWrTAyMsKECRNee41XV1dj/fr16NatGyIiIpRqpDEnJwcJCQkYPny4UrX7TXg8Hs6dO4f+/fuLvxchBMePH0f//v1pcKSAHj58CE9PT4l8FvfSw83Njd6r5Uh17ijUS7Vp00biCbOA/5siaWhoiOTkZIUNchiGgaGhIebMmYNLly7h+vXrMmsrwzAYPHgwEhMTkZeXp7D76E00NTUxePBgca3hhw8fNisY1tPTw4QJEzB06FD89ttvOH36NAQCgdLuB0VGCAHLskhPT8fKlStx69YtLFiwAGPGjIGhoaHEH7Lc9d+lSxdER0e/sPSAYRh07doV+vr6OHnyJD3mb0FfXx+mpqYoLCx8q98jhKC4uBinT59+Y1BEKTdCCOrr67FhwwbY2dlhzJgxr60TXFdXhw0bNiAsLAw9e/ZUqmCSz+cjOjoaY8aMgb6+vrybIzGEEMTGxsLV1RW2trbivysoKEBlZSX8/f1pcKRg6urq0NDQIB69f1eEEDx69AgeHh70WMuR8twNqRYxNzdHXV3dG9d4toS6ujqGDRuGf//9V+YJqd4GwzAwNjbGggULcObMGVy7dk1mHXN9fX2MGjUKe/bsUdiR8+ZQU1NDx44d8eGHH2Lr1q24evVqs9Zdq6mpoW3btvj666+RkZGBn376CaWlpTQwkhAuAM7Ly8O6deuwf/9+jBo1Cp988gns7Oyk+nDl6gdXVla+NMO4uro6JkyYgLi4OIVNrKeo2rZti6SkpLfaZ3w+H9u3b8eoUaNgZmZGO1YqihCC2tpa/Pzzz/D29sbw4cNf+dKDEILGxkZs3LgRfn5+SldLmhCCy5cvw8zMDEFBQUrV9jdpamrC6dOnMWjQoOdeTBw9ehR9+vSRWI1aSnKys7Nha2v7ypJkb4tlWZSVlYlfhFDyQQNhFaenpwdLS0upjEhyo0KmpqZISEiQ6GdLGsMwMDc3xyeffILz58/j0qVLMlkzzNXn1dLSwu3bt5U6GGAYBh4eHli0aBGuXbuGAwcOgMfjNWt02MTEBPPmzUNERAR++uknXLp0iY4OvyOWZVFYWIiNGzdiy5Yt6NSpE7766iv4+vpCTU1NJp1GDQ0NTJs2Df/88w/KyspeyCJtaGiIGTNmYOfOnXjy5InU26MKGIZBQEAA0tPTm53kjxCCEydOwNbWFiEhISoVMFD/hyuB9tNPPyEsLAwDBw58bS1dLgh2dXUVB1zKcm5w2a3Pnj2LMWPGqEzNYOC/73b9+nW4urrC3t5e/PfFxcXIz89HWFiY0hyn1iQ5OVmiL2S4/Ck0UZZ80UBYxXH1hDMyMqTy+erq6hg6dChiYmKUYi2gqakpPv74Y9y4cQMnT56UyUi2uro6xo0bh2PHjqG6ulrq25OmZ18oNDY24pdffkFlZWWzAloNDQ1ERERg4cKFuHv3LtatW4fi4mIaDL8lkUiE3NxcbN68GRs2bEBAQAC+/vprdOzY8ZXZYqWFqx88ZMgQ/PXXXy+d9eDs7Ixhw4Zhy5YtLVr32hrZ2NiAx+Ohqqrqjf+WEIL09HQkJSVh7NixSjXtlWo+bur7unXrEBUVhd69e782OKyvr8fGjRvF15+yBZIsy2L37t0YMGAAzM3N5d0ciaqvr8e5c+cwbNgw8f2aEIKTJ08iMjISurq6cm4h9b9EIhEePXoEb29viX1mfn4+rK2tJTbCTLUMfWK2Aj4+Pu9UjuNN3NzcYGxsjLt370ptG5LCjU5+9NFHuH//Pg4dOiT1KcsMw8DW1hadO3fG4cOHlb6kELf+d9KkSWjXrh2+//77Zq0b5n7X0tIS8+fPR0REBNauXYtTp05JZeq+qhGJRHj48CHWr1+PLVu2wN/fH9988w26du0KXV1duY0gMAyDTp06wcDAAGfOnHnhPOB+7uTkhL///lvpamvLg7q6Otzc3JCZmfnGf1tTU4Pdu3djypQpdGRBRRFCkJubi19//RUjRoxA586dX/vCo6GhQRwEv27qtCK7desWBAKByiV9I4Tg6tWraNOmDaytrcV///TpU2RkZCAiIkKOraNepbKyEgKB4Llj9i4IIcjOzoaLi4tKnd/KiAbCrYCNjQ0qKiqkFmwwDINhw4bh+PHjSjEqzNW8nTdvHsrLy7F582Y0NjZKdWSSYRhERUXh0aNHyMrKUolRUK5U0vTp07F161acO3cOIpGo2aPD3FTex48f44cffkB2drZK7BdJIoRAIBAgISEBq1atQnR0NDp27IhvvvkGXbp0gY6OjkI8RNXV1fH+++/j2rVrLz2/GYbB6NGjkZ+fL9OEdcosODgYd+/efe2+EolE2Lt3LyIiIuDq6qoQ5wIlWYQQPHjwABs2bMDEiRNfO/WdEPJCEKxsI8EAUF5ejsOHD2Py5MkqVwe7rq4Oly5dwqBBg8R/RwjB+fPnERERQV9mKajc3Fw4OjpKdMZNZmYmvLy8JPZ5VMvQQLgV0NfXh4mJCQoKCqTy+VxdYT09PaSlpSlFJ5crrTRjxgzY2NhgzZo1ePr0qVTbrquri7Fjx2LXrl1KnTjrWQzDwNPTE0uWLEFycjI2b96Murq6Zo8Om5iYYPbs2Rg0aBA2bdqEPXv2NPv3VRnLsqiursapU6ewdOlSXLp0CSNGjMCyZcsQHh4u8ynQb8IwDIyMjDBp0iRs27bthdrZDMNAW1sbH374IU6cOKEyL4OkhWEYeHl5IS8vD01NTS/9N9w6w/r6evTu3VuhzgdKMgghuHPnDrZv347Zs2e/tn4pFwT//vvvcHZ2xogRI5QyCBYKhdizZw/69u0rsdE3RUEIwcWLFxEYGAgLCwvxsayqqkJCQgJ69uxJr2MFRAgRrw+W5Gc+ffpUYhmoqZajgXArwDAMfH19pTo9mmEYDBkyBDExMQqdQfpZDMNAU1MTI0aMQPfu3bFmzRqp1Fx+dnt+fn6wtrbGxYsXVSYQYBgGpqammD9/PmxtbfH99983e3SXYRioqakhJCQES5cuhbq6OlasWIE7d+60umRaXA3ghw8f4o8//sDKlStRUVGBuXPn4pNPPoGvry/U1dUVtqPEMAx8fHwQGhqKvXv3vrSkkrm5OaZMmYI//vgDlZWVcmqpctDT04OJiQmKiope+vOioiKcPHkSkyZNUrlRM+q/0f6LFy/i2LFj+OSTT95Ya7S+vh6///473NzclHJNMPB/gX9dXR169OihsPe6lqqpqcH169fRr1+/59YGX7hwAeHh4TA0NJRzC6mXEQgEyM7Ohre3t8TOyfLycqipqcHY2Fgin0e1HA2EWwlfX1/cv39fqkGep6cnNDQ0pBpMSoOamhq6dOmCGTNmYNeuXTh16pTURmzV1dUxduxYnDt3TuWy6Gpra2Po0KEYN24cNm3aJK4b3FwGBgYYPXo05syZg4sXL+Lnn39Gfn6+Up1LLcGyLJ48eYKTJ0/i22+/xcGDB+Hn54elS5di/PjxsLe3V5oESGpqahgyZAiePn360inQDMOgTZs2iIqKwubNm1852kn9X+mxhISEF/ZjY2OjuFSShYWFnFpISYtAIMCxY8dw69YtfPrpp7CxsXntv6+pqcFvv/0Gb29vDB06VCnXBAP/rcM8fPgwJk2apLTf4VW4zO7h4eHPJf+qqanBrVu30KtXL5UL/FUFl+RUkkFrfn4+bG1tVe48V0bK0bui3pmTkxMqKipQV1cntW2oq6tj8ODBOHr0qNIlhOKmdy9atAiZmZn45ZdfUF5eLpUgzMzMDH369MHBgwdVLnGQmpoa/Pz8sGTJEjx48AC//fYbKioqmr0f1dTU4OTkhE8//RRdu3bFb7/9ht27d6O6ulplAmJCCAghqK6uxrVr1/Djjz9i7dq1qK2txaxZs7Bo0SJ07twZBgYGStkx0tTUxPTp0xETE4P8/PwXfs4wDHr06AFHR0dER0crzQwSWWMYBoGBgUhNTX3ufioSiXDo0CF4eHggODhYKc8R6uUIIeDxeNi5cydyc3Px0UcfwcTE5LXHuKqqCuvXr0dAQAAGDRqklCPBwH/n9b59+xAZGSn1Gujy8OTJEyQmJiIqKuqF0eDQ0FCYmJjIt4HUK2VkZMDT01Oi11ZGRgZ8fHwk9nlUy9FAuJXQ1taGiYkJysrKpLYNrlQTADx48EDpAhduzercuXMRHByMlStX4tatW81OAPU22+nevTuePHmC1NRUpdtPb8IwDIyNjTF37lz4+flh5cqVSExMbPbLEW7Kenh4OL755hvo6Ohg+fLlOHv2bLPqFisiQghYlkVNTQ1u3LiBn376CatWrUJGRgaGDh2Kb7/9FqNHj4adnZ1CT39uDoZhYGFhgfHjx+OPP/4Q10p8lpqaGkaPHo3q6mqcPXtW6V6cyYq5uTlEIpF4GjkhBPHx8cjNzcWIESOUZqYA9WaEENTV1eGXX36BpqYmZs+eDT09vdeuCa6oqMAvv/yC9u3bo3///kp73yCEICEhARUVFYiMjFTa7/EqhBAcOnQIUVFRz01/rqurw40bN54LjinFwrIs7t69i7Zt20rsM7mM0a6urhL7TKrl6Jh8KxIQEIDU1FS4u7tLbRuampoYNGgQjhw5gjZt2ijlzV1DQwORkZHw8fHBzp07cfv2bYwbNw6WlpYS+z6ampqYMGECtm/fDk9PT5XLFMkwDDQ0NBAVFQUfHx9s374dycnJGDVqFPT19Zu1HxmGgb6+PkaOHIlu3brhn3/+wZUrVzBy5EgEBgYq/JQiQgiEQiHKy8uRnJyMxMRE1NTUwN3dHf3794ebm5vCZH2WNIZhEBQUhIyMDOzbtw+TJ09+4W26lpYWZsyYgR9//BE2NjZ0dPMltLS04O3tjXv37qF79+4oLi7GkSNH8PHHH0NLS0vezaMkhBCCsrIybNiwAR06dEDfvn1fO/rEJdpZv349IiMj0bVrV6V+KVJVVYUDBw7go48+UsnzOicnB3l5eZg6deoLo8HBwcEwMzOTcwupV+Hz+SgsLJRoVv6GhgbU1NS8cckDJRvKe+ek3gqXMCsjI0Pq03H9/PzESX+UFcMwsLe3x2effYaAgAD8+OOPiImJQX19vURGJBmGgZubG3x9fRETE6OUo5zNwTAMnJycsHjxYujr62PlypW4f//+W40AMgwDKysrzJgxA1OnTsXp06exZs0aZGVlKdTUckIIRCIRqqqqkJycjOjoaKxYsQKbN29GTU0NRo0ahaVLl+KDDz6An5+fXGv/yoKamhqGDRuGsrIyXLt27aXnuKGhIWbNmoX9+/fj8ePHKnsdtBTDMGjXrh3i4+PR1NSEHTt2YMSIEbCyslLpc6c1IYTg0aNH+PnnnzFgwAD069fvjUFwcXEx1q1bh/79+yt9ECwUCrFz50707t0bDg4O8m6OxAmFQhw6dAjDhw+Htra2+O9ra2tx7do19O3bl17LCqyoqAgmJiYSHax4+vQpDAwMoKOjI7HPpFpOsYdUKImys7NDZWUlGhsbYWBgILXtcKPCR48exaeffqq0a5aA/0ZkevbsiZCQEPzzzz/49ttvMWDAALRv3/6dS9hwiYW+++47dOjQAc7OzhJsuWLR0dHBe++9h+DgYOzcuRM+Pj4YNmzYa6f+/S81NTV4eHjg888/R3JyMrZv3w47OzsMHToU9vb2culMsCyLqqoqFBcXIzU1FY8ePUJ9fT3s7e0RFBSEAQMGwMjICBoaGq2ys6Ojo4Pp06fjhx9+gJOTE9zc3J77OcMwsLOzw+TJk7F161Z89tlnsLS0lFNrFZOTkxPKysqwa9cuuLu7v7aOLKVcWJZFXFwc/vnnH0ydOvWNWWkJIcjJycGmTZswZswYpZ9FwZUA4/F4KpksihCCtLQ0NDU1PXfdEkJw7tw5hISEPJc4i1IsXNkkf39/ib5sysnJodOiFYjyvkak3pqWlhYsLS1RWFgo9W0FBQWhuroa2dnZUt+WtHFrh6dMmYI5c+YgPj4eK1asED/A32UUy9DQEO+99x527typMrWFX0VNTU1cc5hhGKxYsUI8Ovw2+1BTUxOhoaFYtmwZ/P39sX79emzduhWlpaXiRFSSxH0mV96ooKAAN27cwB9//IHly5djzZo1OHfuHMzNzTFx4kR88803mD17Njp37gxzc3NoamqqXAfvbXAlk7Zs2YKampqXZpL28fHB0KFD8euvv6K2tpaODD9DX18fmpqaePTokdKWxaGexy2biImJwfHjx/Hpp582Kwh+8OABfv/9d0ydOlUlguDS0lLExMRgypQpKnle83g8/P333xgzZsxz36+qqgqxsbEYMGCAUh9DVUcIwb179xAYGCix48Rdx1w+HUr+6IhwK8IwDAICApCcnAwvLy+p3oA1NDQwcOBAxMTEYP78+Ur/kGMYBgzDwMHBAQsWLEBubi5iYmIQExODiIgIREREiLN7vs1+ZRgGISEhuHbtGq5evYqePXuq9IORYRjo6elh3LhxCAsLw86dO+Hm5oZRo0a9VZZkhmGgra2Nbt26ITw8HFevXsWaNWvg7++PQYMGwczMrEX7kQt4WZaFQCBAaWkpCgsL8fDhQ+Tn56O2thb6+vpwdHREQEAABgwYACsrK/H5rcrHrqW4ZRldunTBjh07MGfOnBfq3jIMgw4dOuDp06fYunUr5syZQ6eN4b/zsaCgAOnp6ejXr99zUysp5UQIQVNTE3bt2oX6+nosXrz4jTNjuJGpPXv2YM6cOXBxcVH6ew03JXro0KESzb+hKAghuHr1KhwcHODu7v7caPDZs2fRoUMHWkNWwdXV1aGxsVGis5SEQiEKCgowfPhwlTvnlRUNhFsRhmHg7++Pbdu2QSQSSTXZEMMwCA0NRUxMDAoKClRm2i8X6Lq6umLevHkoKSnB1atXsXr1atja2qJz587w8fGBnp5es6fSqKurY8KECfjhhx8QFBTUKuqCcnWnv/rqK3H93JEjRyIkJOStsiYzDANdXV1ERUWhc+fOuHTpEn744QcEBwejT58+Lw2IuWBXKBRCKBSCz+fjyZMnKCoqQklJCfLz81FVVQWhUAhjY2PY2dnB09MTPXr0gJmZmdKWNZInhmHQp08f5Obm4vjx4xgyZMgL1wfDMOjfvz+qq6uxa9cuTJky5YWAubWpq6vDtm3bMH/+fJw9exYCgUAlkwm1FlySqy1btsDd3R1Tpkx54/FkWRaxsbE4fvw4FixYILdlIJLEJYrS1dVFx44dlf77/C9CCKqqqnD27Fl88cUXz93rKioqEB8fj6+++krlvrcqIYQgIyMDTk5OEn0pW1dXB6FQSMtlKRDmDVPQ6Pw0FdPU1IQVK1Zg0aJFMDIykuq2uPU/KSkpmDVrllIn9HgdQggaGxvx8OFDxMbGIjc3F1ZWVggKCkKbNm1gYmICXV3d135/7i3xo0ePMHPmTKUfQX8bhBDk5+djz5490NLSwrhx42BjY9PiEd3KykqcO3cOly9fRkhICHr16gWBQICysjJUVFSgvLwcT548QXV1NViWhZqaGszMzGBjYwMbGxs4OTnBzMwMenp60NbWVtnzVh5qa2uxZs0aDB48GKGhoS89xnw+H9u3b4eJiQlGjRrVqq6FZwkEAmzbtg2Ojo7o168fVqxYgalTp6rMS8XWhhCChw8fYvv27ejfvz8iIiLeeG6LRCKcOnUK8fHxmDNnDiwsLJQ+eOLu97/99hsWL16skhmTCSH4888/YWFhgUGDBj03Grxnzx4YGhpi8ODBSn8sVRkhBBs3bkT79u0RFhYmsc9NS0vD+fPnMW/ePNq3kK3DAEa+7Ad0RLiV0dbWhpOTEzIzM9GuXTupbovLeHrixAkUFxfD3t5eqtuTF266b2BgIAICAsDj8ZCXlydO6NTQ0ABjY2NYW1vD0dERdnZ20NPTg46ODjQ1NaGurg41NTWEhITgwoULiIuLg6+vr7y/lkwZGRlh6tSpuHnzJr7++mv06dMHHTp0gLq6OkQiEViWhVAohEAggFAoRGNjI+rq6lBdXY2GhgY0NDSgsbER9fX1aGhoQFNTE9TV1XHlyhUcOnQI9fX1GDBgAPz9/dGmTRt07doVFhYW0NLSgrq6ujiZFe2YSJeBgQE+/PBD/Pzzz7CxsXlpllgtLS1MnjwZGzZswKlTp9C/f/9W12EghOD8+fMQiUTo06eP+P6QmJhIA2ElJBKJcP36dcTExGDGjBnw9PR8471GIBDg4MGDKCoqwqeffvpc/VllxuPxsG3bNowZMwampqbybo5U5OTkIDMzE2PGjHnuOD958gTJyclYunQpfdYoOIFAgNzcXIwbN05in0kIQXp6utKWFlVVNBBuZRiGQWBgIO7evfvKERlJ0tHRQVRUFI4dO4aZM2eq9MXPBVK6urrw9vaGl5cXCCEQCAQoLi5GcXEx8vPzkZaWJg7chEKhONADgMrKSnz22WcIDg5udWskuWBHV1cX+/fvx+bNm2Fubg4fHx9oampCQ0MDGhoa0NTUhK6uLgwMDGBsbAxbW1vo6elBV1cX+vr6MDAwgKGhoTirN4/Hw82bN3HmzBk8fvwYAQEBcHJyooGvHHBZot9//31s2LABX375JQwNDV84Djo6Opg5cyZ++ukn6OnpoUePHq3mWHGdpRs3buCLL74Qv6QJDQ3Ftm3bMHDgwFY/ZVxZcAn2Dhw4gNzcXPEI6JvWA/N4PPz1118ghGDevHkqszacZVkcOnQI7u7uSp/s61X4fD6io6MxatQo6Orqiv+eEILDhw+jd+/eUq3aQUlGXl4eTExMJDqFmWVZPHz4EOPGjVPJc19Z0UC4FfLw8MDx48fBsqzUpx1ySXBOnz6NkpKSFk95VUZcoKWtrQ0XFxc4OzujQ4cOr/0dQgj27dsHABJ9E6mMHj9+jD179kBHRwdjx4595dq4N51Penp66NmzJyIiInDnzh1s27YN+vr6GDBgAHx8fFptaSN5YRgGQUFBKCkpwebNmzF//vwXXvowDAMDAwN88sknWLNmDbS1tdGpU6dWcZyePn2KnTt3YtasWc+9JLCxsYFAIEBFRQWsra3l3ErqTQghKC8vx5YtW2Bvb4/PP/8c2trabwyCa2pqsGnTJjg6OmLUqFEqc38ihCAlJQUZGRlYsmSJSs7yIITg2rVrMDIyQtu2bZ87brm5ucjNzcXkyZNV4niquvj4eImXquPxeKipqaElAhWM6t2JqDcyMzODhoYGysrKZLI9XV1d9O7dG8eOHZPJ9hQVFxi/7o+amhoGDx6MlJQUPH78uFm/o6p/3N3dsWjRInTu3BkbNmzAzp07UVlZ+cK+bO6+19bWRufOnbF06VL0798fp06dwvLly3HlyhXU1dXRkj0yxDAMevXqBQsLC/z9998QCoUv/TdGRkb46KOPcPLkSSQmJqr8Maqvr8eWLVswfPhwODs7P3d+q6urw9/fH8nJySq/H5Qdy7JIT0/H6tWr0blzZ0yYMAE6OjpvDIJLSkrw448/om3bthgzZoxKlV6rrKzE3r17MW3aNJWd7VRRUYHTp09j/Pjxzx03kUiEgwcPYujQoc+NElOKSSgU4v79+wgMDJTo5z558gTGxsYqM8NDVdBAuBXS0NBAmzZtkJqaKpPtMQyDzp0749GjRygpKZHJNpWZgYEBxo8fj7/++gtNTU3ybo5caWlpoVOnTli6dCksLCywatUqnDhxAg0NDS36PIZhoKWlhaCgIHz66aeYPn06MjMzsWLFChw+fBhPnz6lQYaMaGhoYNy4cSgqKsLly5dfut8ZhoG5uTnmzp2Lw4cPIyUlRWWPj0AgwJ49e+Dr64uwsLAXAiCGYRAWFoaEhATxUgpK8QgEApw+fRq7du3CzJkz0a1btzfOvOISaa1btw7Dhg1DVFSUSiWJEwgE2LVrF3r16vXCCx5VwQW73Au+Z7/j/fv30djYKPW8LJRkPH36FCKRSKIzb7j6wR4eHio5G0KZ0aPRSnGJV2TVqdTV1UWvXr1w/Phxle3ISgrD/Ffmyt7eHmfOnGn1+4thGOjr62PgwIFYvHgxiouLsXz5cty8eRMCgaDFn6uhoQEnJydMmzYNCxcuBACsXr0aGzduRGZmJkQikaS+AvUK2tra+PDDD3Hp0qVX3o8YhoGNjQ1mz56NvXv3IjU1VeWuCZZlxeWRBg0a9MqOkr29Paqrq1FbWyvjFlJvQghBdXU1Nm3ahMzMTCxevBhubm5vDPoIIbh9+zb++OMPzJgxA6GhoSrVUSaE4PLly2BZVmXX+hNCcP/+fZSWlqJ79+7PfUc+n4/Dhw/jvffeU6mXG6rs/v378PHxkfh1mJ6eDh8fH5W8BpSZ6txtqbfi7OyM8vJy1NXVyWR7DMOga9euePDgAUpLS2WyTWWmpqaGsWPH4urVqygoKFC5jn9LcKOD06ZNw5w5c3Dt2jV8++23uHv3LkQiUYv2ETcd3dzcHCNGjMCKFSvQtm1b7Nu3D9988w0uX76M+vp6uv+lhGEYGBsbY9asWdi3bx9ycnJeGQzb29tj3rx52LVrF9LS0lTmmBBCkJycjPj4eEyaNOm19d11dHTg4eGhki8DlBkhBFlZWVi1ahXc3Nwwd+5cGBkZvbHDKxQKERMTgxMnTuDTTz+Fh4eHSnWSCSHIy8vD6dOn33huK7PGxkbs3bsX77///nN1oQkhiIuLg6GhIc0UrCREIhHi4+MlPnovEolQWloKOzs7iX4u9e5oINxK6ejowNraGrm5uTLdZmRkJE6ePEmn9jWDkZER3nvvPURHR7/TyKeqYRgGTk5O+OyzzzB27FicOHECq1atQnp6OoRCYYsDBIb5L+N3586d8dVXX2HKlCnIzMzEN998g127dqGwsLDFATf1agzDwMHBAdOmTcPvv/+OJ0+evDIYdnBwwPz58xEdHa0SwTAhBIWFhdi/fz+mT58OAwOD13aWGYZBeHg44uLilP67qwqBQIAzZ85g8+bNmDx5MgYMGPDGBFdc7fkdO3bg0aNH+OKLL1QykSS35n3SpEkwNzdXue8H/HcsDx06hKCgoBdmANTV1eHYsWMYM2aMSo3yq7La2lqUl5fD1dVVoudrRUUFNDU1VaYMmiqhV2YrFhoaioSEBJl1qLhR4fT0dJkl6lJmDPNfHWY9PT1cu3aNdnz/h5qaGnx8fLBw4UIMHToUhw4dwtq1a/Hw4cN3ntasrq4ONzc3TJ8+HUuWLIGtrS02bdqE1atXIzY2FrW1tfR4SJi3tzdGjhyJjRs3oqam5pX/zsHBAXPmzMGePXtw9+5dpT4OVVVV2Lx5MyZOnAhbW9tm/Y6LiwtKSkpaff4AeSOEoKKiAhs2bEB6ejqWLFnSrGmP3O/9/PPPMDAwwNy5c1WycywUCrF3716EhITA399f3s2RCkII0tLSkJmZicGDBz8X7BJCcOrUKQQHBzf72qbkiytd5+Hh8dzIviQ+NysrCy4uLnR6vAKigXArxTAM/Pz88PDhQ5mONurp6aFXr16IiYmho8LNwCUUOnny5CtHylo7DQ0N+Pv7Y/Hixejduzd2796Nn3/+WSLrfBmGgYmJCXr37o2vv/4aI0aMwL1797BixQrs2LEDWVlZdLReQhiGQfv27dGxY0ds3rz5lQnRGIaBo6Mj5s6di4MHD+LOnTtKeV00NDRg69atiIqKgq+vb7NHHwwMDODg4ID09HSl/N6qgGVZpKSk4IcffoCfnx/mzp3brHqjXId4zZo16NixI0aPHi3RDrei4MoIVVRUvBAgqpK6ujrs3r0bU6ZMgZ6envjvuQzg8fHxGDBggMp+f1XDTWUPDw+X+OyFlJQUBAQEqOSsCGWnmgs2qGYxMzMDwzB4+vSpzNYtMAyDLl26YPny5SgpKYGtrS29MbyBpaUl+vfvj+joaHz00Uf0jeJLMAwDTU1NBAcHi0vM7N69Gzo6OhgyZAjatGkDNTW1Fp9rXPklb29veHp6or6+HvHx8di1axdYlkVERATat28v7gzTc7pl1NTU0KtXL1RXV2P79u348MMPXxooMAwDOzs7fPTRR/jll18gEAiUqs6wUCjE7t274eHhgYiIiLdqN8Mw6NixI27cuIGQkBAptpL6X4QQ8Pl8/PPPP0hNTcWsWbPg4uLSrOPHsixu3ryJI0eO4IMPPlDZNaPcuuCTJ09i4cKF0NTUlHeTpIJlWRw+fBjt2rWDm5vbcz8jhGD//v0YMGCASo72q6qmpiYUFha+cDzfFXdNDBs2TKKfS0kGfU3ViqmpqSEgIEDmdSl1dXXRt29f/PPPPzLbpjLjppQ3NTXRtYFvwJVHateunbhe8OHDh/Hdd98hOTn5ndYQc9TU1GBoaIju3btj2bJlmDZtGkpKSrBq1Sr8/PPPSEpKQlNTEwgh9Fi1gLq6OoYPHw4dHR3s2bPnpTWGgf+OtZWVFT799FOcPHkS58+fV4pM3yzLimfEDBkypEXBUJs2bZCXl9fiMmLU2yOEID8/HytXrkRDQwOWLFnSrCCYC57//vtvnDlzBl988YVKB8ENDQ34448/8P7776v0uuB79+7h8ePHGDhw4As/S0tLQ1VVFTp27KiS318VceWNHB0dnxvdl4SnT5+Kk3JSiocGwq0YtwY1KSlJptOUGYZBhw4dUFBQgLy8PJltV5lpampi8uTJOHToECorK+XdHIXHMAw0NDTQtm1bfPnllxg5ciROnz6NFStWIC4uThyovus21NTU4OzsjEmTJmH58uXo3r07rl69iq+//hp//vknsrKywOfzaUD8ljQ0NDBx4kRUV1fjn3/+eWWAy2US/+KLL3D79m3ExMS8MnBWBIQQxMbG4sGDB5gwYcIbkyq9ioGBAezt7ZGZmSmFVlLP4gLZM2fO4LfffsOQIUPEU2GbEwRXV1fjt99+Q0VFBRYtWgQrKyuVDY5YlsWePXsQGBiostNACSGorKzE3r17MXXqVGhraz/3PRsbG7Fv374XMkhTiu/mzZsIDw+X+FT2x48fw8nJic7mU1A0EG7l7O3tUVNTI/O6lLq6uhg0aBAOHz5M1wo3k52dHXr16vXaUTLqRRoaGvDz88Nnn32GiRMn4tatW1ixYgXOnDmD6upqiQWpenp6CAkJwfz58/Hll1/C1dUV+/fvxzfffIMjR46gqKhIIiPSrQVXYzgvLw/Hjx9/bTBsZGSEjz/+GNnZ2di3b59CvnzgRpFOnjyJ6dOnQ19fv8WfxTAMOnfujNjYWIX7nqqEEIKysjL88ssv4trAISEhzeooc+uBV69eDX9/f0yfPl3iI02KhKsXXFlZiSFDhqjsulihUIg///wTUVFRcHZ2fi4I5hJkeXl5wcPDQ46tpN4Wj8dDTk4OvLy8JP7ZKSkpCAoKkvjnUpKhmncqqtm0tLTg7u6O9PR0mW87LCwM5eXlyMrKkvm2lRHDMIiMjERNTQ3i4+NpB/gtaWhowN3dHXPnzsW8efNQWlqKb7/9Fnv27EFxcbHE9qeamhpMTU3Ro0cPLFq0CPPnzwfDMNiwYQNWrlyJ06dPo7S0lL4AagYdHR3MmjUL9+/fx/nz51+5zxiGgZ6eHmbNmoXGxkZs3rwZjY2NMm7tqxFC8PjxY+zduxdz5syBmZnZO3+mr68vcnJyZFYLvrURCoW4fPkyVq9ejfDwcMyePVucV+NNRCIRrly5gi1btmDChAmIiopS2Rq6nEePHuH06dOYPn06tLW15d0cqSCE4OzZs9DS0kK3bt1eOBcKCwtx+/ZtDB8+XE4tpFoqIyMDNjY2MDY2lujnCgQC5OXlSXzdMSU5NBBu5RiGQVhYGOLj42XeMdfU1MTQoUNx+PBhOsLZTJqampg0aRL+/vtvVFVV0WD4LTEMA3V1ddja2mLixIlYunQpTExM8PPPP2P9+vXi0kuS2q8aGhqwsbHB0KFDsWLFCkyaNAmVlZVYt24dvvvuO5w/fx4VFRV0PfErcAHu7Nmzcfv2bVy+fPmV+4lhGOjo6GDKlCmws7PDmjVrxPtWnrgMslu3bsW0adNgZ2cnkSmj+vr6sLe3x8OHDyXQSorDjQKvW7cO8fHxWLx4Mbp27dqsQJarD/zXX3/h+vXrWLRoUbNKKikzbqrwtm3bMG3aNJiamsq7SVJBCMGjR49w5coVTJo06YXzQSgUYs+ePRg+fDgMDQ1V+pirGi7L+dsmLmwObimbJF5+UtJBA2EKbm5uyM/PB5/Pl+l2GYZBcHAweDwe7t+/L/cOqzJgGAb29vbo1asXdu/eTUcV3wE3pXbAgAFYsWIF2rdvjz179mD58uW4du0aGhoaJHZOcmuWXVxcMHbsWHz33XcYO3YsCgoK8MMPP+D777/H1atXUVVVJdFAXBVwx2nevHm4evXqa4Nh4L+XRcOHD0fXrl2xZs0aFBQUyG1/ckHCxo0bMXbsWLi7u0u0o9WlSxdcv36d3gckRCAQ4NKlS1i9ejXat2+Pjz/+GJaWls06ZoQQFBUV4YcffoCenh4+//zzZo8gKzOBQIDt27cjMjISXl5eKvt9a2trsWPHDkydOvWFTNCEENy6dQvq6upo166dyu4DVVVfX4+8vDz4+vpK/LNzcnKanVmekg/VnqtDNYuBgQGsra3x8OFD+Pv7y/SCVVdXx+jRo7Fv3z54e3ur7JQqSWIYBj179kRCQgLu3LkjlZp3rQk3ktixY0eEhYUhNzcX58+fR0xMDIKCgtCzZ09YW1tLLNEFV+rJ09MTnp6eaGxsRE5ODmJjY3Hy5EmYmJggPDwcQUFBMDY2hrq6eqs/vgzDwNTUFAsWLMAvv/wizqT+qnWIampq6N69O0xNTbF+/XqMHz8egYGBMl23SAhBfX09tmzZgsjISAQFBUn0ODIMAx8fHxw4cAB1dXUwMjKS2Ge3NoQQFBQUIDo6Gjo6Oli4cGGzA2Dgv6nQt2/fxpEjRzBq1CiEhoaq7BrZZ7Esi2PHjsHQ0BA9e/ZU2fsUn8/HX3/9hS5dusDb2/uFdcGVlZU4evQoPv74Y5WfAq+K0tPT4ejo+E55G16Gywvh7+8v0c+lJItesRTU1NTQoUMH3Lx5U+YXLMMw8PT0hImJCeLi4qQyNUUVaWtrY/LkyVi3bh28vLzotBsJ4dYRu7m5oaqqCrdu3cLvv/8OIyMj9OrVCz4+PtDV1ZXoOaqrqwsfHx+0adMGTU1NyM/Px82bN3HmzBkYGRkhLCwMQUFBsLCwaPVZJ01NTfHRRx/h119/BSEE3bp1e2XAwTAMgoKCYGZmhs2bN6O4uBi9e/eWWUe1qakJmzdvRmBgILp27SqV+5qOjg7c3NyQlpaGDh060HvnW+KmMp85cwaxsbEYOXIkQkND3+ocqa+vx4EDB1BQUIBPP/0U1tbWreI4EEKQmJiIe/fu4fPPP1fZAJBlWZw6dQoaGhro3bv3C8eWZVlER0ejd+/esLW1lVMrqZYihODGjRsvXfP9rvh8PnJycjBs2LBWcU9QVqr/ypJqFh8fHzx69AgCgUDm21ZTU8PIkSMRExND62K+BW6K9J49e5Sifqoy4UYg+/bti2XLlmHAgAG4fPkyli9fjoMHD6KoqEji01EZhoGuri68vLwwceJErFixAqNHj0ZZWRl+/vlnrFy5EidOnEBhYWGrPt4mJiaYP38+rl69igsXLrz2ODAMA0dHRyxcuBCpqanYsWOHTJJo8Xg8bN26Fc7Ozujbt6/URgfV1NQQERFBs0e3AMuyyMjIwKpVq1BeXo6vvvoK7du3b3ZARwhBTk4Ovv/+e+jo6OCLL76AjY1Nq+nwFhYWYt++fZgxY4bER9IUBSEESUlJSExMxMSJE6GpqfnCz2/duoWGhgb06NGj1Rx7VVJdXY3CwkL4+PhI5bPV1NTobB0Fp5qv8Ki3ZmpqCjMzM2RlZUnlhvA63LrXwMBAnDp1CiNGjKAPlGZgGAa9e/emU6SliGEYaGlpwc/PD76+vqioqEBsbCzWr18PAwMD9OjRA8HBwdDV1RX/e0ltV1tbGx4eHnB3d4dIJEJ+fj7i4uKwceNGAEBgYCDCwsKeq0/YGo7/s9Okf/vtNwgEgtcGmwzDwNjYGAsWLMDff/+NH3/8ETNnzpRaPVeBQIA///wT5ubmGD58uNRH8d3d3VFWVoaamhqYmJhIdVuqgJvKeuDAAeTn5+P9999HmzZtwDBMs9cCsyyLixcv4syZM5gwYQICAwNl0HLFQAhBbW0tNm7ciPfff19iyd8UDSEE+fn52L9/Pz755JMXgn1CCMrLy/HPP//g888/fyFIphQfIQSpqanw8PCQ+LI8QggyMjLg6enZ6mdyKTrmDW+R6SvmVuTy5ct4/PgxpkyZIpcHW1VVFb799lt88cUXsLa2lvn2lRGXoOXnn3/G4sWLW0VyFkUgEAiQlZWFixcvIjs7Gz4+PujRowccHBygoaEh1WMgEolQUlKCu3fvIiEhAfX19fD29kZ4eDjc3Nygra3dKtYnAkBNTQ02bNgAX19fDBo06I0dDpZlcfPmTRw5cgQTJkxAQECARPeVQCDAnj17wLIsJkyYIJPOMSEE0dHRsLW1Ra9evej1/wqEEPD5fFy5cgVnzpxBz5490atXr7fqABNCUFVVhZ07d0IoFGLKlCmt7p7L4/Hw+++/w9vbG/3791fJ784d5x9//BHjx49/6ZIxgUCAjRs3wt/fX6XXR6syoVCINWvWYPjw4fD29pboZ7Msi02bNqFLly6t6kWZAjsMYOTLfkBHhCmxgIAAnD59Gnw+Xy5Jq4yNjdGvXz8cOHAAc+bMoW/RmoFhGNjZ2SEqKgrR0dGYM2cOfTMtA5qammjTpg28vb1RVVWFpKQkREdHg8/nIzw8HOHh4TA3N4eamprEO0jq6uqwt7eHnZ0d+vbti4qKCqSlpeHkyZMoKyuDk5MTwsLC4O3tDSMjI6m0QVEYGRlh/vz52Lx5M/bv34/33nsPWlpar/z3ampq6NSpExwcHLB161ZkZ2ejf//+r/2d5hIKhTh06BAaGxsxdepUmV2HDMMgIiIC0dHRiIyMVNlj/S5EIhEyMzNx4MABWFhYvHUyLO4zkpOTsXfvXkRGRqJXr16t7l4rEolw9OhRGBgYoE+fPip7rjU0NGDz5s3o27cv/Pz8Xvg5IQSxsbHg8/lSW/9PSV95eTlqa2vh4uIi8c8WCAQoKiqSymdTkkVHhCkxozmDUQAAXN9JREFUQghWrlyJ9957T+Jvx5qLz+dj1apVGDp0KNq2bSuXNigjPp+PX3/9Fe3atUP37t3pg1kOBAIBysrKEBsbi8TERBgZGSEiIgIBAQEwNjaW+jFhWRZ1dXV49OgR7ty5g6ysLBgbGyM4OBhBQUGwsrJSyY47IQQ8Hg9//vkn1NXVMWHCBPFU9df9Tl1dHaKjo1FbW4upU6fCwsKixcdIKBTi77//xpMnTzB9+vQ3bl/S+Hw+li9fjtmzZ8Pe3l6m21ZkXA3nv//+G0+fPsWoUaPg4+PzVi9Zuezff//9N3JzczFlyhQ4OTm1unssF/xdvHgRn376KfT09OTdJKng8/nYvn07rKysMGzYsBdmjBBCUFhYiN9++w2fffbZO903KPkhhODo0aNgWVYqyazy8/MRHR2NL774QmUTySmZV44I00CYEiOE4PLly8jJycHkyZPlcnMnhODx48f4448/sHTpUpV92EoaIQRPnjzBDz/8IE7aQskHIQQCgQDZ2dm4cuUKMjMz4eTkhG7duj1XIkxa1xd3T+fz+SgoKEB8fDxSUlJACIGPjw/CwsLg4uIi9XbIEiEEQqEQ+/fvR1lZGWbOnAk9Pb03fjeRSISrV6/i+PHjGD9+PIKDg996fwiFQhw8eBBPnjzBjBkzZB4EA//XqePz+XjvvfdU4pi+Cy54PXHiBOLi4jBgwABERERAU1PzrfYNIQSZmZn4888/ERwcjCFDhkBbW7vV7V/uubx582Z8/vnnbz2arixEIhH27dsHHo/30uRYwH/Z4L///nsMHjwYISEhKrkfWgOBQIBly5Zh3rx5Es/2TQjB6dOn0dTUhKFDh9JzRDHQQJhqnurqaqxatQrLli2TWxDKsix27doFQ0NDDB8+nN5EmokQgps3b+LChQtYuHChRKZ7Uu+GK8+SmpqKK1euoLS0FJ6enujSpQs8PDzEHS1pnuOEEBBCUFZWhpSUFMTHx6OiogL29vYICwuDr68vjI2NlX4KNZfEKCYmBklJSZg/f36z1m9ySXG2bt2KNm3aYMSIEdDR0WnWvhAKhThw4ADKy8vx4YcfyrUOellZGdauXYsVK1a02nrs3Drg69ev4+TJkwgJCcHgwYNhYGDw1gFwY2Mjjhw5gpSUFEyePFmcUKu14ZJCrV69Gh988MELdXRVBcuyOHr0KPLy8jBz5kxoaWm9tFTSnj17AADjx49vNbkYVA0hBI8ePcLBgwexcOFCiY/YEkLw448/YuTIkXB3d5foZ1MtRgNhqnlYlsXatWvRr18/uRYBr6mpwXfffYfZs2fD2dlZJR+80iASibBp0yY4Oztj4MCBdL8pEC4BS2pqKmJjY1FeXg5fX1907twZTk5OL+14SasdNTU1yM7ORnx8PB49egRtbW0EBgYiODgYdnZ2Sj3qxbIsbty4gZiYmLe6fzQ0NODQoUN48OABpk6dCjc3t9f+nkAgwMGDB1FZWYlp06ZBR0dHkl/jrRFC8MMPP2DQoEFyvXfLAzcLIykpCf/++y8cHR0xbNiwFpUzYlkWmZmZ2LVrF3x9fTFs2DCVLQ/UHHV1dVi7di169eqFTp06Ke194XW4WsH37t3DvHnzXnq8CSFISEjA8ePHsWjRIrlf71TLEULwxx9/wNvbG926dZP45zc1NWH58uVYsmQJDAwMJP75VIvQQJhqHq4uXkpKCqZPny63N57cQ+fUqVN0dPMtVVdX47vvvsOsWbPg6uqqkh0XZceyLCorK3H37l3cunULtbW1CAwMRHh4OOzt7WUWiHLra588eYKkpCSkpKSIk4eEhobC09MTRkZGSpe4jhCCtLQ07Nq1C+PHj0dgYGCz9ifLskhNTcWePXvQqVMn9OnT56XHQiAQYO/evairq8PUqVPlMh36fxFCEBcXh7i4OMydO7fVXPcCgQAZGRk4cuQIdHV1MWLECLi4uLTo2VVXV4ejR48iLS1NXFapNY/6cfWwHRwcMGTIEJXcFyzL4vz587hz5w7mz58PQ0PDl/67kpISrFu3DvPnz4eDg4OMW0lJUm1tLZYvX46vv/4axsbGEv/89PR0nDp1Ch9//HGruQ8rARoIU81XW1uLb7/9FsuWLZPrm3CRSIQtW7bAyckJAwYMoDeUZiKEICUlBYcPH8aiRYvoOmsFJxQKUVVVhYSEBMTFxaG+vh4+Pj7o0KEDnJ2dZRoUi0Qi1NfX48GDB0hISEB2djaMjIwQGBiIoKAg2NraKs1LKW7K8+bNm9G9e3dERkY2K6DnRsz37duH0tJSTJo06blRZR6Phx07dkBdXR0TJ05UqJGhxsZGLF26FF9++SVMTU3l3RypEolE4gCYECIugaKurv7W14tIJEJKSgr27duH4OBgDB48uFlrzFWZSCTCwYMHUVNTI9Ms6LLEBcFxcXGYN28ejIyMXnrMGxoasHbtWkRFRaF9+/at+rxQBefPn0dOTg4++OADqRzLvXv3wtbWFj169JD4Z1MtRgNhqvlYlsXvv/+Ojh07IjQ0VK43fa628Lx58+gU6bfAsiyio6Ohra2NUaNGqeSbfFXDreXlRopv3ryJmpoaeHl5oVOnTjJbU/xse4RCIfLz85GUlITk5GTweDy4ubkhLCwMnp6e4mlfinpdEkJQXV2NzZs3w8rKCuPHj2/WFHRuvTFXLic8PByDBg0Cy7LYvHkzLC0tMWbMGIULDggh2LlzJ+zt7VWypjB3jWRmZuKff/4Bn8/HiBEj4Ovr26I17tz1tm/fPpSVlWHy5MlwcXFRuf32tgghuHjxIm7fvo2PP/642WvmlQnLsjh37hzi4uIwf/78VwbBIpEIO3fuhJ6eHn2WqgChUIhvvvkG06ZNk0ppI5ZlsXz5csycOVPiSbiod0IDYar5uBHFc+fO4ZNPPpHrjZ8QguTkZBw+fBhffvmlQkxBVAZc1tRVq1Zh3Lhx8PPzU7mOjCrj7suVlZVISUnBzZs3UVFRAXd3d3To0AFeXl7izqmsgmIAqKioQEZGBu7cuYPCwkKYmJggJCQEgYGBsLKyEicdUaRzjUugtG/fPhQVFWHmzJkwNTVtVhu5Mkt///03MjIyoK6ujuDgYIwYMUIhp4tzo+Dbtm3DV199pTSj92/CzVZ48OAB/v33X/D5fAwZMgSBgYEtGgHmXvJwa8l79uyJ3r17v3VWaVVECMG9e/ewd+9eLFy4ECYmJiq3T0QiEY4fPy5eE/yqIJgQgvPnzyM5ORnz5s1rtUnoVMnDhw+xZ88eLF26VCp925KSEmzcuBHLli1TyGdEK0YDYertNDQ0YPny5Vi4cCHMzMzk2hZudFNTUxNjxoyhb2TfwqNHj7BlyxYsWbIEJiYm8m4O1ULcyFVGRgbi4uJQWFgIOzs7hIeHw9fXF4aGhjLN+kwIQUNDA4qKipCYmIj79++Dx+PB09MTwcHB8PDwgL6+vkJlohaJRLh8+TLOnj2LKVOmNDv7LZc1d+nSpaiurkaXLl0watSoZgfTsiYUCvH9999j7Nix8PDwkHdz3gn3EiM1NRXHjx+HhoYGBg4cCF9f3xaPxrMsi5ycHOzevRuGhoYYM2ZMi5JqqSJCCLKzs/H7779jwYIFcHJykneTJE4gEODw4cPIz8/HrFmzXpnMiBCC1NRU7N+/H59//jl9fqoAQgi2bNkCX19fdOnSRSrX/OXLl1FQUID3339f4p9NvRMaCFNvhxCCffv2wcTEBP369ZN7J6GhoQE//vgj+vfvj7CwMLm3R1kQQnDq1Ck8ePAA8+bNo4XdVQDLsqivr8fjx49x+/ZtPHr0CKampggNDUVgYCAsLCxkepy50bWamhpkZGQgKSkJeXl5MDExQUBAAIKCgmBlZaUQmaifrQvbs2dP9OzZ87X7ihth3bRpE/r06YOwsDBcunQJly9fRt++fdGlSxeFGyUihOD69eu4f/8+ZsyYIfd93hLcjJb4+HhcuHABxsbGGDRoENzd3Vs0Asx9ZnV1NY4ePYqMjAyMGjUKAQEB9J74/xFCUFpainXr1mHy5Mnw8fFRynPndRobGxEdHQ2BQPDaJHeEEBQUFGD9+vWYP38+HB0dZdxSShoqKirw/fffY/ny5VLJnUIIwS+//II+ffrA19dX4p9PvRMaCFNvLy8vD1u2bMGKFSvkPsWDEIKioiL8/PPP+Oyzz2Btba1yD2lpEQqF+OWXXxAUFKSS6wZbK+7ezePxkJ+fj7i4OKSmpkJTUxP+/v4IDQ2Fo6OjzKd7siwLPp+PoqIi3L17FykpKWhsbBRnonZ3d29WfV9p4cpYbdu2Dfr6+pg4ceJLR4W4EaG//voLkyZNQkBAABiGASEET58+xb59+/D06VOMGjVKvEZVUdTW1mLFihVYunTpK7PgKiJu9P3y5cu4ffs2PDw80K9fP9jb27/T7IJnawt36tQJffv2ha6uLr0XPqO6uhpr167F4MGD5Z4bRNIIIaitrcXmzZthb2+PUaNGQUND45XfsaKiAmvXrsXYsWPpsiIVQQjBiRMnUFNTg7Fjx0rlmNbW1mLVqlVYtmyZQiVRpADQQJhqCZFIhG+//RYTJkxQiKLgXHmQU6dO4YsvvqDZkJuJm1a7cuVKzJ8/H05OTvTBroK4BE8lJSW4e/cu4uPjUV9fDzc3N4SHh8PLy0t8zchyCjWXhfnBgwe4c+cOcnNzoaenh6CgIAQFBcHJyUnma4u5urPHjx9HXFwcpk+f/lzd4GdrEc+dOxeOjo7PtY37Xg8ePMC+fftgbGyMsWPHwtbWViGuLS5plq2tLaKiohSiTa/Cnbe5ubk4c+YMHj9+jPDwcPTs2fOdpp9zxyg9PR379u2DpaUlRo8eTV+i/g9CCBobG/Hrr7+iXbt2iIyMVKiXOu+Ke4m+YcMGdO3aFVFRUa98sc8t+fj111/RqVMndOvWjZ4rKqKpqQnffPMNPvnkE1hZWUllG/fv38eZM2fw0Ucf0fNG8dBAmGqZixcvIisrC9OmTVOIC5tlWRw6dAjl5eWYPn06ndbWTIQQ3L17F0eOHKEllVqB/01uFRcXh6KiIlhaWiIsLAwBAQEwMTFp8TTTd2mTQCBAYWEhUlJScO/ePdTU1MDJyQkhISHw9fWFgYGBzNrF1RveuXMnIiMj0atXLxBCEBMTg3v37mHOnDkwNzd/ZVu4gPrmzZuIiYlBYGAgBg4cqBDrh/Pz87Fx40asWLFC4bJbA/8XdCQkJODixYsAgJ49eyI0NPSdSxexLIvS0lIcPHgQ5eXlGD16NHx8fFQqwJMUgUAgzoT+3nvvyX32lyRxmd+jo6Px/vvvIzg4+LXXMp/Px+bNm+Hi4oJBgwbR80VFEEJw+/ZtxMfHY/bs2VI5roQQ7N27F/b29vQFimKigTDVMtIuPN4SAoEAGzduhLOzMwYPHkwfVs3Esiz27dsHkUiE999/n+63VoTLfpyXl4f4+Hg8ePAA6urq8PPzQ2hoKOzs7ORSN5VlWVRVVSE7OxuJiYnIysqCjo4O/P39ERwcDBsbG6m3i5sxsWvXLvB4PDAMAz09PUyaNKnZ04q5/XvhwgXcuHED4eHh6N279yuz0coCy7JYvXo1BgwYgMDAQLm04X9xLw6Kiopw9epVpKamwsPDA5GRkXB2dn7nFyDcsTxx4gTu3buH/v37o2PHjs0qmdUaCYVC7N27FzweD5MnT1bIFyYtxefzcfLkScTHx2PGjBkvzOr4XwKBAH/99Rd0dXUxZswY+pJdhQiFQqxatQpjx46Fp6enVLbB5/OxcuVKzJs3DxYWFlLZBvVOaCBMtQwhBDt27ICLiwsiIyPl3Ryxuro6/Pzzz+jWrZvUsv+pooaGBqxevRqDBw9GSEgI3W+tEDfyUVFRgeTkZNy9excVFRVwcHBAaGgovLy8YGZmJvORIUIIeDweysvLcffuXSQnJ6OqqgoODg4IDg6Gt7e3uF2SPm8JIcjJycGXX36JpqYmfPLJJ+jUqdNb7wNu/fGZM2cQHx+Pbt26oVu3bjA0NJTLtZaUlIRz587hs88+k3sZvIqKCiQkJODGjRtgGAZdunRBaGgojIyM3rlt3IuI8+fP48aNG+jSpQsiIyOhr69P73GvIBKJ8M8//4hLiila0reW4l6G/PXXX9DW1hbnAHhTELxnzx4IhUJMnDhRZcqOUf+XIPHgwYNYtGiR1F72FBcXY9u2bVi8eDF9iaKYaCBMtQwhBHl5edi+fbtC1aXkOlbr1q3DyJEj0bZtW9rhaQYuC+7PP/+MJUuWvHbaJ6X6uPWZjY2NyMzMRHx8PLKysqCrq4uAgAAEBwfDwcFB3HmQ5TRqrl0PHz5EQkICHj16BC0tLfj4+CA4OBjOzs7ihCTvOop49+5d7N69G+PGjYONjQ127NgBS0tLjB07tkWjutz9KSYmBqmpqejSpQt69Ogh84CYz+fj66+/xvz582Fvby+z7XL9ivr6ety/fx/Xr19HaWkp/P390a1bN9jZ2UnkhQYhBE1NTbh27RrOnTuHgIAADBo0SCVr30oSy7I4ffo0UlNTMXfuXJVJHPZsgruoqChxVvjXTYcWiUQ4cOAAqqurMW3aNIXp41CSQQjB2rVr0bVrV6lVHOGqc3D1zVXhWlJBNBCmWk4kEmHlypXiupSKcpETQlBcXIxff/31reqCtnaEEFy7dg1Xr17F559/rjIjAdS74Z4FIpEIhYWFSE5ORlJSEurr6+Hs7IywsDC0adNGPLoi67XFLMuiuLgYqampSEpKQkVFBWxsbBAaGgpfX1+Ym5u/dWZhPp+PmJgYJCYmYtasWeJgUSAQ4OTJk7h+/TrGjBmDkJCQtx61fHad9qlTp5CUlISOHTuiV69eMDY2ltka6DNnzqC4uBiTJ0+W+hRz4L8s5hkZGbh27Rry8/Ph7OyMiIgItGnTRhxkSCIA5vF4uHHjBk6fPg0PDw8MGTIE1tbWEvl8VUYIwZUrV3D16lV8/PHHbxwtVQbcC5F//vkHqampmDFjBlxcXF77vZ4NgisqKjB9+nSFKPFGSVZOTg62bNmCb775Rmp9HZFIhNWrV2PChAm01JbiooEw1XKEEMTGxiI5ORkzZ85UqLWl3JTGjRs34oMPPqDBcDOJRCLs2LEDhoaGGDVqlEIdU0pxcNMMHz16JM74bGhoiODgYLRt2xaWlpZyWX/JlUPJyclBQkICHj58CADw9fVFcHAwXFxcoKur+8rzmiuB9Mcff8DMzAzjx49/YT0wNxtm586dMDU1xbhx41pc9okbIT5//jzi4+Ph6+uLPn36wNra+p3KAjVHXV0dli1bhq+++gqmpqYS/Wxu5L6hoQHp6emIi4tDfn4+bG1txcGvJKcncwEPVz2AyxNhZ2dH7/vNQAjBnTt3cOzYMXzyyScwMzOTd5PeGcuyePz4Mf766y94e3tj+PDhzcorIBAIsH//flRXV+ODDz54ZU1hSnmxLIv169ejXbt2iIiIkNp2KisrsW7dOnz11Vd0YEFx0UCYejf19fVYsWIFPv/8c4VLBEAIQW5uLn7//XdMnjwZvr6+tFPUDHS9MPU2uDIrpaWlSExMxL1799DU1AR3d3eEhITAzc1NvN5TlucSl4CpvLwcaWlpSE5ORklJCaysrNC2bVv4+/vDzMxMHLCzLIvExETs378fgwYNQufOnV+7povP5+PSpUs4d+4cBg4ciE6dOrW4NjMXwN+6dQuXL1+GlZUV+vbtCzc3N6lNySSE4MCBA9DT08OgQYMkMhrL5/NRWVmJtLQ0JCUloby8HK6urmjfvj3c3NwkPgWcWwN88+ZNXLhwAc7Ozhg0aJC4vjD1ZoQQJCcnY//+/fj444/Fo+fKijsnjh49irS0NIwbNw5+fn7NOh94PB527doFoVCIyZMn0yBYReXm5mLTpk1Yvny51AJUboZdbm4u3n//fdqPUlw0EKbeDSEER44cgUAgwKhRoxTuYufWvv7+++8YNmwY2rdvTztIb0AIQUFBAX799Vd8/vnnsLKyUrjjSikmblphbW0t0tPTkZSUhNzcXBgZGSEgIABBQUGwtbWVy2gxt7Y4Ly8PSUlJuH//PliWhYuLCwIDA5GRkYHHjx9j+vTpcHBwaFb7CCEoLS3Fvn37UFdXh/Hjx8PV1fWdatzyeDzcu3cPZ86cAZ/PR7du3dCuXTupZJp+8uQJfvrpJyxbtqxFpdNYlkV1dbV4n2ZlZUFdXR1t2rRBSEgIHB0doaOjI5UkZtXV1bh69SquX78Ob29v9O/fXzySTjUPVyYsOjoaCxYsUJh61y0lFAqRmJiIQ4cOITQ0FAMHDmx2dvn6+nps27YNxsbGGDduHF0TrKJYlsWmTZvg7++Prl27Su18J4Rg3bp1GDBgANq0aSOVbVASQQNh6t2Vl5fj+++/x/Lly6Gvry/v5ryAEIKysjJs2LABERER6N27t0zXMiojbtr7hQsXsHDhQjqth3prz9YHzs/PR3JyMpKTk9HY2AgXFxe0a9cOXl5e4vJrsh4t5ko0xcTEiKdC+/j4IDAwEH5+fnB2dn4uudLrEuuwLIu7d+/iwIED8PPzw7Bhw95p9JP7zIKCApw/fx4ZGRnw8fFBz5494ejoKLHRdZZlsWXLFvj6+r62U/hsf6Cmpga5ublITU1FVlYWGhsbYWtri+DgYPj6+sLY2Fgqo/9cG8rKynD27FkkJyejbdu26Nu3L8zNzQHQNcBvgxCCBw8eYMeOHZg3b16zX/4oIu7l7d69eyEUCvH+++/Dycmp2S+zqqursXHjRnh4eGD48OE0u6+KIoSgqKgI69evx/Lly8VJFaWhvr4e3333Hb766iuF7BdTYjQQpt4dIQTbt2+Hs7MzevXqpZAPU0IIampqsHHjRtjZ2WH06NE0AcYbiEQi7Nq1C5qamhg3bhwdaaHeCfdMqaqqEmeizs3NhZ6eHgIDAxEUFARHR0doaGhI/Vzj1pQeOXIEycnJmDx5Mjw8PFBSUoIHDx4gLS0NxcXFUFNTg729Pfz8/ODu7g4rK6vn2vfs/YObIn7ixAncunUL/fv3R0RExDuNfnP7rLa2FnFxcbh69SoAoEuXLmjfvr042H6Xz8/PzxdPE+RGwbhAXCgU4smTJ8jOzsaDBw9QVFQEHo8HW1tb+Pv7w8PDAzY2NuJyUtLKvMqyLLKzs3HixAkUFhaia9eu6NKlC4yMjKS2XVVGCMGjR4/wxx9/YPbs2XB2dlbKfcjlKjhy5AgyMjLEs76am3mcS6z5+++/o3v37oiMjKQvyVUY9+KvTZs26N69u1SPc2JiIm7duoVZs2bR80mx0UCYkgxu+vGKFSsUekpRU1MTDhw4gPz8fHz44YewsLCgN6nXaGxsxA8//ID+/fujffv2dF9REtXU1ISSkhIkJyfj3r17qK6uhpOTE0JCQuDj4wNDQ8PXljlpCZZlkZmZid27d8PLywsjRox4YfokIQRCoRAVFRUoKChAWloacnNzUVtbCx0dHTg4OMDV1RWurq6wtLSEtrY2NDU1xQFyaWkpDh06hJKSEowaNQq+vr7vPMrETTsvKCjAtWvXkJqaCjs7O3Tp0gXe3t7NngL6ss9ct24d2rdvDycnJ+Tl5SEvLw8FBQVoaGiAgYEBXFxc4OXlBTs7O/G6amkjhKChoQHJyck4f/48CCGIiopC27ZtpTLdurUghODx48fYsmULPvzwQ7i5uSndvuRGcc+dO4fbt2+je/fu6NGjx1uNvHEllXbu3NniDPCU8uBGg3/77TcsXbq0RUtB3mZbmzZtQnh4OEJDQ6W2HUoiaCBMSQbLsli3bh26deuGsLAweTfntUQiEW7cuIGYmBiMGjUKISEh4hEN6kVFRUVYu3YtPv74Y9jb2ytdp4lSDtza4sePHyMxMRGPHj2Cjo4OfH19ERISAltb2xYFexxCCKqqqvDPP/8gOzsbY8eOhY+PT7M6v8/WL66rq0Nubi6ys7ORm5uL6upqEEKgr68PGxsb2NrawtHREaampsjPz8e///4LMzMzvPfee3BxcZHIvYYLEh88eIAbN26goKAA7u7u6Ny5M1xdXZ+r/8q1ncfjgcfjobGxEeXl5SgqKkJpaSnKysqQk5OD5ORkDBkyBK6urnBycoKjoyMMDAygp6cn0wBBJBKhtLQUV65cQVJSElxcXNC7d284Ozu3OBkZ9R9CCLKzs7F582ZMnz5docoeNgd3DV+8eBE3b95E+/bt0bt377euDy0UCnH+/HlcvnwZM2fOVNoRcar5uLXBfn5+6Natm1SPNzctesmSJTAwMJDadiiJoIEwJTkZGRk4ePAgFi9eDE1NTXk357W4NUU7duyAnZ0dxowZoxJ1E6WBEIKEhAQcPXoUX3zxxQvlZChK0riMz0+ePBHXLa6uroadnR1CQkLg7e0NS0vLZgdoPB4PV69exenTp9G1a1dERUW986giIUQ8ciwQCFBZWYmioiKUlJQgPz8fFRUV4PF4aGhoQGZmJqqrq9GuXTv4+/vD3NwcZmZmMDExgY6ODrS0tKChofHcHy5g/t/1ttyUZZFIJN52dXU1EhIScPHiRVRWViI4OBjOzs7g8/moq6tDXV0dhEIhtLS0oK2tDXNzc9ja2sLa2ho2NjYwNjbG+vXrERUVhXbt2rV4n7zLvqyvr0dqaiquXLmCqqoqREREoFOnTuI1x9S74UaCuSDY09NTaZ53hBCUlJTg7NmzuHfvXosDYOC/smG7d+9GXV0dpk2bJrPa3ZR8cbMWly1bJvVs4Hfv3sX169cxZ84cem4pPhoIU5IjEonw7bffYsyYMUpRt5cr9xETE4Nbt27hvffeQ7t27WRe5kUZsCyLI0eOoKSkBB9++CFNJkLJDBdwNjY24uHDh+L6wBoaGvDx8UFISAhcXV3FCd3+dyQ0LS0NBw8ehLW1NUaPHg1LS0upXt/cs5NrN1caqaKiAhkZGYiOjgaPx0NERAR0dHTQ1NQEoVAo/iMQCCAUCsGyLFiWhbq6+guBoJqa2nMBMxfgamtrw8DAAIaGhkhNTUVSUhIcHBzQu3dvhIaGwszM7Ln727P7ITMzE9HR0fj6669lNvWZZVnk5ubi0qVLSE9Ph7OzMyIjI+Hp6SnxKfGtGSEEWVlZ2LJlC2bMmKEUI8HctP2HDx/i1KlTKC0tRdeuXdGtW7cW1aDm6n9v3boVbdu2xdChQ+k51koQQrB+/Xq0bdtWqpmiuW1t2rQJHTp0QHBwMD2/FB8NhCnJIYQgPj4e165dw4IFC5RmujGXMGb37t1QV1fHuHHjxFOA6U3s/wgEAmzYsAEeHh4YOHAg3TeUXHABVHFxMdLS0nD37l08ffoU1tbWCA0Nhb+/P4yMjJCfn4+///5bXNrNy8tL7iOLXJKu69ev4/z583B2dsbgwYNhZ2f3wvXEsixe9hx+mxd1DQ0NyMrKwp07d/D48WNoamrCz88Pbdu2haOjoziRF1dHec2aNejZsyfatWsntcRXIpEIZWVluHXrFhISEqCjo4OIiAiEhITQ5FdSQAhBZmYmtm3bhg8//BDu7u4Ku3+5F0fV1dW4ffs2rl+/Dl1dXfTu3RuBgYEtTnApFApx+fJlnDp1ChMmTEBgYKDc7wWU7MiibjCntrYW33//Pb7++mtah1o50ECYkiwej4fly5dj9uzZcHBwkHdz3opAIMCdO3dw7NgxuLq6YvDgwbQu5f+orq7G6tWrMXr0aAQGBipsh4pqPbgR17y8PNy5cwfXr19HbW0tysrKMGXKFAwaNAgmJiYKdR1zI9xxcXE4c+YM7OzsMGDAADg5OUlltsWzU81TU1ORkpKCiooKmJubw8/PD35+frCwsEBhYSGio6OxZMkSiXUYn008Fh8fjzt37oAQgtDQULRr106ciZuSPEII0tPT8eeff2LWrFnvVONamrip8Q8ePMD169dRXFyMgIAAdO3aFXZ2di1+qU4IwdOnTxEdHQ1CCCZPngwzMzOF3AeUdLAsi/Xr16Ndu3aIiIiQ+vaSkpJw8+ZNmi1aedBAmJIsQgguXLiA3NxcTJkyRaE6n83BdVBv3LiBs2fPwtvbG1FRUbC3t1eaEW5py8vLwy+//ILPPvsMdnZ28m4ORYHP5+Phw4c4fvw4qqur0adPHwgEAty9exclJSWwtrZGUFAQ/Pz8YGlpqTCZ7bkR4sTERJw5cwa6urro168ffH19pZoYimVZNDQ0oLi4GKmpqUhPT0dtbS3Mzc1x+/ZtTJ06FR07doSRkVGL7uFc4F1cXIyEhATcu3cPQqEQgYGB6NChA6ytrWniKykjhODevXvYvXs35syZ0+y6urLCvcDKzs7GrVu38PjxYzg4OKBLly7w9PR8p8R4wH+jwLdv38aRI0fQr18/dO3alU6FboWys7OxdevW58rDSQvLsti8eTM6duyItm3b0nNNOdBAmJK8uro6LF++HIsXL4aZmZm8m9MiXEAcGxuLixcvwsTEBH379kWbNm3EicBa602OEII7d+4gJiYGCxcubNF6LYp6V1zm5Dt37uDChQvQ1tbGwIED4efnJx5hJISAx+MhJycHSUlJSEtLA8uy8PDwQLt27eDq6ipO/ibPc5gbNX3w4AFOnDiBmpoa9OrVC2FhYeKSMNJq37NZpfPy8pCcnIxNmzYhJCQExsbGcHJygre3N+zt7WFlZQUdHR3x7z67Hhv4796fnZ2NxMREPHz4ENra2ggJCUFoaCgsLCxoICIjXILDgwcPYv78+XLP9v/suvmnT58iIyMDCQkJKCkpgZ2dHTp06AA/Pz+JZCgnhKC0tBTR0dEQCoWYNGkSbG1t6XnXColEImzYsAHt2rVDp06dpH4O1NXVYdWqVfjqq6+kWp6JkigaCFOSRwjB4cOHwbIs3nvvPaV+AHEd1LS0NJw5cwYVFRUICgpCREQE7O3txQ9tZf6OLcEd47KyMsyYMYNObaRkgltjmp+fL06w5OHhgT59+ohHvF51LXLrD8vLy5Geno74+HgUFxfD0NAQ/v7+CAgIgJOTk3ikUh7XNNfG/Px8nDlzBg8fPoS/vz969eol7sxLu10sy2LLli1wdXVFYGAgcnJy8ODBAxQUFKC2thb6+vpwcHCAu7u7uE2ZmZlISUlBTU0N7OzsEBwcDF9fX5iamtJcCzLGsiyuX7+O06dPY/78+bC2tpb5/uf6jyzLoq6uDllZWbh37x6ysrLEL6JCQ0Ph4eEhfrHyrm3kZlecPXsWV65cwdChQ9GpUyeoq6vT868V4pKjbdmyBcuWLZP62mBCCBITExEfH4/p06cr3WzIVowGwpR0PH36FD/88AOWL1/+VkXuFRn3Njs+Ph63b98Gy7LiGqeOjo7iRB6t5aHL5/OxYcMGeHl5oX///vTGT0kFN822rKwMd+7cQUJCArS0tNC5c2eEhoa2uPwJ13EuLi7GvXv3kJaWhsrKSlhaWsLX1xdt2rSBra0ttLW15dKZ5pIG3bp1C9evX4e+vj4iIyPh7+//XJ1gaSgpKcHatWuxbNkyGBgYiEeNq6urcf/+fZw/fx43btyAsbExjIyMUFxcDAcHB3Ts2BFubm6wsbGBtbU1dHR0xNmtgdb3wlDWWJbFuXPncPPmTcydOxcWFhYy2S73gorP56OiogJZWVnilydCoRAODg4IDAyEm5ubVNaEC4VC3Lt3DwcPHoS7uztGjBjRotJKlOpgWRYbNmxASEgIOnfuLJMXiL/99ht69uyJgIAAqW6LkigaCFPSQQjBtm3b4OLigt69e8u7ORLFjRKXl5cjNTUVd+/eRXl5OSwsLODl5QUfHx9YWlpCT09P5acCVldXY82aNRg6dChCQ0NV+rtSssF1quvq6pCXl4e7d+8iMzMTWlpaaNu2rTjBkqSDU5ZlUVtbi+LiYty/fx+PHj1CeXk59PT04O7uDm9vbzg5OUFfXx+6uroyK7PGlXnLysrCxYsXkZeXBz8/P3Tt2hX29vZSWWvLsiz++usvqKurw8/PD48ePUJ2djbq6+thZGQELy8v+Pn5wcrKClpaWmhsbER1dTVyc3NRVFSE0tJSlJeXQyQSQV1dHebm5rCwsICFhQWsrKxgbW0NPT09aGpqQktLS66j8KpCKBTi6NGjyMzMxKxZs2BiYiLxbXDPvqamJjQ2NuLJkyfIzc1FYWEhCgoKwOfzYWBgABcXF/H1YmxsLM5OLmkikQjZ2dn4+++/wbIsRo8eDTc3N/pStpV7djRYVtmbuUSidFq00qGBMCU9eXl52Lx5M7755huFSU4jadxISWNjI4qLi5GRkYGMjAxUVFRAXV0dVlZWsLe3h6urK8zMzKCnpyfuSKtCx48QguLiYqxduxbz5s2Di4uLvJtEKRGuY11bW4vq6mrk5+fj0aNHyMvLg0AggK2tLdq2bQsfHx8YGxvLbGSWm6LM4/FQWVmJBw8e4OHDhygoKEBTUxMMDQ1hb28Pd3d3ODo6wsjICIaGhlLr8D/bptraWiQmJuLatWsQCoUICwtDaGgorK2t3zqhH/fSoba2FlVVVSgsLHwumI2NjcXw4cMRHh4Od3d3mJiYiEfI3/S5XE3kpqYmlJWV4cmTJ3j69CmePHmCsrIyNDU1QSAQAAD09fVhaGgIIyMjGBsbw9TUFGZmZjAwMBDXSNbS0hIHzVz9ZOo/fD4fBw4cwNOnTzFjxowWzcLizgUej4empibweDw0NDSgoqICpaWlePr0KZ4+fYqqqioIhUJoa2vDwsICTk5OcHBwgLOzs/h4SfslEcuyyMvLw9GjR1FWVoYRI0YgICBAnL+Dat24usEhISGIiIiQ+jODEIKLFy+ipKQE48aNU/p+XStDA2FKeliWxerVq9G/f38EBQXJuzkywXVWuc5lUVERCgoKkJ2djYqKCtTX10MgEEBTUxO6urrQ1dWFjo4O9PT0YGhoKB4h4f4oS2cvLS0N165dwwcffEA7I9QLuFFNHo+Hmpoa1NbWoq6uDjU1NaivrwfDMDA0NISTkxM8PDzg5uYGMzMzhZlS++yaR6FQiNLSUuTn5yMrKwuFhYWoqamBSCSCoaEhLCws4ODgAFtbW3FgZ2Rk9FySqWe1dFo3y7IoKSnBrVu3kJiYCG1tbYSHhyM0NBTm5ubP/Xs+n4/a2lpxwFtcXIzi4mJUVFSgpqYGDMPA2NhYHNDY29vD0tIS169fR3p6OmbPni2Re9GzSZO4Osl8Ph/V1dXP/amsrERFRQXq6urE5w2fz4dIJBIHWdy9kguSnw2QNTU1oaOjAx0dHfFos6am5nO/qyqjhoQQXL58GY8fP8b777//3FpIkUgEoVD43PXX2NgofgnB4/HEf5qamsT7WF1dXfxcMjMzg42NjXhU39LSEgYGBlBTU5Npjgzu2Zqbm4ujR4+ipKQEgwYNQlhYGM1ATj0nLy8PGzduxDfffPPK+64ksSyLlStX4v3334erq6vUt0dJFA2EKekhhCAlJQWnT5/GZ599pjRBnaT977UkEAjEAQA3xayxsRG1tbXg8/niPwKBACKRSE6tfnslJSU4f/48RowYQQvJUy/gghYjIyMYGRlBX18fRkZGMDExgYGBwXMdWWXo1P7vdV1fX4/y8nKUl5ejoKAAJSUlqKmpQU1NDZqamqCuri5+8aWjowNTU1OYmprCwMAAurq6z70A09LSEr8EUFdXfy5o49ZiCgQCCAQC8Pl8NDY2IiMjA+fPn8fDhw/h4+MDJycncfBACIGOjg4MDQ1hYmICW1tb2NjYwMzMTDxThfPsvufz+fjuu+8wZswY+Pj4yCzgeRVuxPLZ4Jj7X+5+yY1EPxvccevMWZYVf6839HGUQk1NDf79919ERES8tEawmpqa+MWklpaW+NzT0dERn2fa2trQ0dGBtrY29PT0xEt6/pe8rslnM6ofP34ctbW16N+/P9q1ayfVGRiUcuLqBoeGhspkNBgACgsLsXXrVnz99dc0cajyeWUgTI8k9c4YhoGvry8OHDggTqbSGv3vjVhLS0u8Xk6ViEQiuLi4oLKyEuPHj6cjw5RK+9/r2sDAAAYGBnB2dkZISIj477kp1g0NDWhsbBSPylVWVqKqqgolJSXiETousOP+m2XZF6aZqqurQ0NDQzwKyo1+Ghoa4v3334eRkREMDAxw//59xMbGAgDat2+P8PBw2NvbQ0dHp9mjoZqamhgzZgwOHDiAxYsXy2R05XUdVy7xlqokYGwpQgjKysrw22+/4YsvvkDv3r1V7kUzIQR1dXWIj4/HxYsXoaenh759+8LPz4+OAFOvlJeXh5KSErRv315mL+5u3ryJsLAwGgSrGDoiTEkEIQTnzp1DUVERJk2aRB9eKo7P52Pr1q2wsbHB8OHDVWb6IUXJGjd6+b+am1vg2aR+KSkpSElJQXl5OWxtbREUFIQ2bdrA1NT0jUGFSCTCli1b4O7ujqioKHoPlzNCCB4/fowtW7ZgxIgRCAsLU5n7LDdyn5+fj8uXL+PBgwfw9vZGr169YG9vTwMN6rW4usGyWhsMADweDytWrMBHH30ES0tLqW+Pkjg6IkxJF8Mw6NixI5YvX46amhoYGxvLu0mUFGlpaWHKlClYu3YtzM3N0b17d9pxpqgWeNfghlsLy5UyioyMRFNTE7Kzs5GUlIQLFy6AZVk4OzsjMDAQLi4usLCweGFkUV1dHaNGjcIPP/yAkJAQ2tmTI0IIkpKSsG/fPnzwwQfw9vZWifsry7IoLS1FXFwc4uPjoampiW7dumHUqFEvLJugqFfJz89HSUkJwsPDZXbOZGdnw8jISOVm+FF0RJiSIEIIoqOjYWlpib59+9KHmoojhKCyshLff/89xo0bh7Zt29JjTlEKhEtWVVNTg4cPHyI5ORm5ubkghMDe3h5+fn5wdXWFra2teBTu0qVLSE5OxoIFC1RmBFKZcDWCL1++jDlz5sDe3l5p76vcuvWSkhIkJSUhISEBTU1NCAkJQadOnWBtbS2z8mSUauBGg9u1a4dOnTrJbFr05s2bERwcLNPgm5IoOiJMSR/DMIiMjMSGDRsQGRmpsqWUqP8wDANTU1MsWLAA69atg6GhIdzd3elDgqIUBMMwUFdXh6mpKcLCwhAWFgZCiDjRV1paGq5evYr6+noYGxvDzc0Njo6OyM/PR3x8PEJDQ2mgIkM8Hg8HDhxAYWEhFi5cCGNjY6Xa98+WI8vJyUFSUhLS09PBMAwCAwMxYcIEODo6yqw8GqVaCCEoKChAaWkp2rVrJ7NziKudPnnyZHreqiAaCFMSxZVfSE1NRXBwML1pqDiGYWBvb4/p06dj69at+Pjjj2FjY0OPO0UpGO6aZBgGlpaWsLS0RHBwMFiWRV1dHcrLy5GVlYXU1FQQQrB48WJERETAy8sLjo6OcHZ2homJiTgTMb3GJYcQgpqaGvzxxx8wNTXFxx9/LJOEZe+Km3HQ2NiIsrIypKWlIT09HZWVlbCyskJQUBB69OgBS0tLuu6XemeEEPz7778YMGCAzAZaCCG4c+cOAgIClOKapN4evTNREqWuro4+ffrg+PHjdKpsK8EwDNq0aYMRI0bg999/x6effgoTExN67ClKCaipqYlLXbm6uoqTbx0/fhwJCQmwtbVFfn4+bty4gdraWhBCYG5uDmtra9ja2sLR0RHGxsbQ19eHnp4eHUF+S4QQFBUVYdOmTejcuTN69+6tsEEjy7JoaGhATU0NCgsL8eDBA+Tk5KC+vh6mpqbw8fHByJEjYW1tDV1dXTq1npIYrrZ0WVkZQkNDZXaPEQqFuHHjBqZPn07vaypKMe+2lFLz9vbGvn37UFRU1GpLKbU2DMMgLCwMdXV1WL9+PT777LNWX/qEopQRl3xrwIABSEtLg6GhIXr06CEOkHk8HkpKSlBSUoLi4mIkJyejuroaTU1N0NTUFNeMtrS0hL29PUxMTGBoaAh9fX3o6+u/svxPa+xkEkJw9+5d7NmzB2PHjkVwcLDcgsf/zRfT0NCA6upqVFRUID8/H3l5eSgrK0NdXR309PRgZ2cHLy8v9OjRAxYWFtDQ0KAvQSipIYTg0KFDGDhwILS1tWW23ZycHGhra8Pa2lpm26RkiwbClMRxmSDPnTtH11S0ImpqaujRowfq6urw+++/Y/78+XQqEUUpKU1NTUyePBm//vorPDw8YGJiAi0tLWhpacHQ0BCenp7i4ImbIltVVSWum/zkyROkpKSgsrISdXV1aGpqAiEEWlpa0NPTg56eHkxMTGBmZgYjIyPxiDL3vzo6OtDR0XludPRlz5I3PV8U9fkjFApx6tQpxMbGYsGCBXBwcGhxW1+V9PTZv3/2v3k8Hurq6lBbW4u6ujrx8SotLUV1dTVqa2shFAqhq6sLMzMzODo6IiQkBDY2NrCysnquFJei7l9KtWRlZaG6ulqmo8GEEFy8eBHdunVTufrd1P+hgTAlcVwppRUrVtBSSq2MmpoaBg4ciNraWuzYsQMffPCBTN/eUhQlGdz6/969e2PXrl2YM2fOC1N2nw2G1NTUYGFh8dLyIoQQiEQiNDY2oqGhQfyHG3EsLi5GfX096uvr0dDQgKamJggEAgiFQgD/Lbnh/nCjjmpqalBXV4e2tja0tbWhqakJ4L8AnhtVffa/FYlQKERGRgZu376NUaNG4fr16+/8eSKRCMB/Nd75fD6amprA5/MhEonEP+f+m2EYaGtrQ09PD4aGhjAxMYGFhQU8PDxgZGQEQ0NDGBkZ0bXglEIQiUQ4dOgQhg0bJtMkrLW1tcjOzsb48ePpdaDCaCBMSYWhoSF8fHwQFxeHXr160ZtIK6Kuro7Ro0fjzz//xL59+zB+/HhxJ5WiKOXBMAx69OiB+/fv48KFC4iKimrRvZxhGGhoaMDQ0BCGhoav/bdc5uH/Dd64/xaJRGBZFizLQiQSgcfjgcfjQSAQAAAEAgFYln3hvxVFUVERDh8+jF69emHJkiUS+Ux1dXXxSwpNTU1oa2tDR0cH2tra4p9x/6uhoQFNTU3xSwL6bKYUXUZGBng8HoKCgmS2TUIIYmNj4efnR5d5qTgaCFNSExUVhS1btqBr1650VLCV0dDQwKRJk/DHH3/g0KFDeO+99xQ2AQxFUa+mqamJSZMm4fvvv4enpyfc3Nykuj2GYcAwjMqV32NZFgkJCbh79y6WLFkiLk1FUdSrCQQCHDlyBCNGjJDp9GSBQIArV65g7ty59GWRiqN3YUoqGIaBnZ0d9PX18ejRo1euYaJUE9eR/eCDD1BYWIhjx44p3MgMRVHNY2JigokTJ2Lbtm2oq6uj9/O3wNXV3bdvH44ePYqPPvoI7dq1o0EwRb0BIQRpaWlgGAa+vr4yDUhTU1NhaWkJOzs7mW2Tkg96J6akRk1NDVFRUThz5gwNglohhmGgo6ODWbNmISMjAydPnqTnAUUpIYZh4Ofnh/DwcPz111/itbvU6xFC8OTJE6xZswZNTU1YsmQJ7Ozs6AgTRTWDQCDA4cOHMXLkSJm+OBKJRDh9+jT69u1Lr9VWgAbClNRwnaeysjI8ffpU3s2h5IBhGOjr62P+/PlITk7G6dOnxUldKIpSHgzDoH///mBZFmfPnqUvtd6AZVkkJydjzZo16NatGyZPngxdXV3asaaoZiCE4NatW+IkbrK8bvLz88Hj8eDl5SWzbVLyQwNhSqq0tbXRqVMnXLx4kU6na8W4YDgpKQnnz5+nnWiKUkJcSaVbt24hNTWV3tNfoampCQcPHsShQ4cwd+5cRERE0PIrFPUWGhoacPz4cZmvDeZe9EVGRtJrtpWggTAlVQzDoHPnzkhMTERTU5O8m0PJCcMwMDAwwNy5cxEXF0eDYYpSUoaGhpg2bRr27NmD4uJiGgw/gxCCwsJCrF69Gg0NDVi8eDGcnJzoKDBFvQVCCM6dOwdfX1+Zr9GtqqrC48eP0a5dO3rdthI0EKakzszMDG5ubrhz5w7tNLViDMPAyMgI8+fPx61bt3Du3DkaDFOUkmEYBk5OThgzZgw2bNiA2traVn9f5+okX716FWvXrkW/fv0wefJk6Ovr0840Rb2lyspKXLlyBYMHD5bp2mBCCK5evYqwsDDo6urKbLuUfNFAmJI6hmEQFRVFRwEpcTD80UcfIS4uDqdPn6bnBEUpGYZh0LZtW/Ts2RMbN25s1bN9CCGora3F5s2bERsbi0WLFiEsLIxmhaaoFiCE4N9//0WPHj1gamoq0203NDTg5s2b6N69O32B1YrQOzUlEy4uLlBTU0NWVpa8m0LJ2bPB8N27d3HixAmahZailAzDMOjRowecnJywZ88e8Pl8eTdJ5liWRWpqKr777js4ODjg008/hZWVFe1EU1QL5ebmIiMjA7169ZLpdUQIQWxsLNq0aSPzAJySLxoIUzKhrq4uLqXU2qfRUf8xMDDA/PnzkZ6ejn///ZcGwxSlZNTV1TFy5EiIRCL8888/reYaJoSgrq4Oe/bswYEDBzBjxgwMGjQIWlpa8m4aRSktgUCA/fv3Y8SIETKfmszn83HhwgX06dOHzuZoZejRpmQmJCQEeXl5tJQSBeD/SivNnTsX+fn5OHDgAAQCgbybRVHUW9DU1MSkSZNQXFyMEydOqPxSB0IIMjMzsWrVKqirq+PLL7+Eu7s77TxT1DsghCAxMREAEBoaKvNZFbdu3YKjoyNsbGxkul1K/uidm5IZbW1ttG/fHleuXKGjwhSA/4JhXV1dzJ49G1VVVdi5c2ernGJJUcqKYRhoa2tjxowZSEtLw/nz51Xy/k4IQVNTEw4cOIDt27djwoQJGDNmDPT09OhUaIp6B4QQ1NfX4/Dhwxg7dqzMyxbxeDycOnVK5sm5KMVAjzglM9yaslu3bqG+vl7ezaEUBNeRnj59OtTU1LBp0yY0NDSoZGeaolTRs7M7VDEjPMuyyMzMxLfffovGxkYsW7YMPj4+tNNMURJy7NgxtG3bFo6OjjJfG3znzh3Y2dnBwcFBZtulFAe9i1MyxZVSSkhIoIEO9RwtLS1MnDgR9vb2+PXXX1FTU0PPEYpSIkZGRliwYAHi4uJw7tw5iEQieTfpnXAZoXfv3o1du3Zh3LhxmDRpEvT19eXdNIpSGbm5uUhOTsagQYNk/nKpqakJp06dwtChQ2W6XUpx0ECYkik1NTX069cP586dazWJVajm09DQwLBhwxAaGop169bh6dOnNBimKCXC1QqPj4/H2bNnlTYYFolEuHv3Lr799ltoa2vjyy+/hK+vLx0FpigJ4vP52LlzJ0aNGgUDAwOZbpsQgtu3b4tHg+kSh9aJ3tEpmXN0dISuri4yMzNpkEO9QF1dHb169UKfPn3w448/Ijc3l54nFKUkGIaBoaEh5s2bh8TERKXLCE8IQUVFBbZs2YIjR45g1qxZGDVqFPT19WlHmaIkiBCCs2fPwsLCAsHBwTK/vhobG3H69GkMHTqUXtutGA2EKZlTV1dHv379cPz4cRrgUC+lpqaGjh07YsqUKfjtt9+QkpJCzxWKUhJcMPzxxx8jLy8P0dHRCp8EjxAiLqGycuVKODs746uvvoKLiwvtJFOUhBFCUFBQgMuXL2P8+PEyn2lBCMH169fh7u4OW1tbeo23YjQQpmSOYRj4+vqisrISRUVF8m4OpaAYhoGPjw8WLFiA/fv348qVK0o7zZKiWhuGYaCnp4fZs2dDJBJhy5YtqK+vV8gXWizLIisrC6tWrcL9+/fxxRdfoH///tDS0qIdZIqSAh6PJ54SbWxsLPPt19XV4dy5czRTNAXmDQ8lxXtiUSrj7NmzyM/Px9SpU2lng3olbqripk2b4OnpiWHDhkFTU5OeMxSlJAQCAY4dO4a0tDTMnDkTlpaWCnH9EkJQXV2Nf//9Fw8ePMCYMWPg7+8v8/ItFNWasCyLf//9F+Xl5Zg6darMrzdCCP7++2+wLIvRo0crxL2IkrrDAEa+7Af0NQglN506dUJ6ejoqKyvl3RRKgTEMAzMzM3zyySeorKzExo0bafktilIimpqaGDp0KHr27ImffvoJDx8+lPvIMI/Hw/nz5/Hdd9/B2NgYX3/9NQIDA2kQTFFSRAhBZmYm7ty5gzFjxsjlenv69Cni4uLQr18/GgRTdESYkh/urRzDMBg5ciS9IVFvJBQKcfz4ccTHx2Pu3Lmwtram5w1FKQlCCB4+fIitW7di8ODBiIiIkOm0REIICCFIS0vD/v37YWNjg9GjRyvMCDVFqbrq6mp89913mD59Ojw9PWV+3bEsi40bN8LLywu9e/em133rQUeEKcXDMAx69+6N27dvo7a2Vt7NoZSAhoYGhgwZgkGDBuGnn37CvXv3wLKsvJtFUVQzMAwDT09PLFq0CFevXsWff/6JhoYGqY8OcwFwcXExfvnlFxw+fBgTJ07EnDlzaBBMUTLC5/Pxxx9/oFevXnIJgrnR6OLiYnTv3p1e9xQAGghTcmZiYgI/Pz/ExsbKfaocpRwYhkH79u0xd+5c7N+/H6dPn4ZQKKTnD0UpAYZhYG5ujs8++wx6enr48ccfUVBQILXrlxCCqqoq7NmzBz///DPatWuHxYsXw9vbG2pqarQzTFEywLIsYmJioKuri8jISLlcd3w+HwcOHMDYsWOhqakp8+1TiokGwpRcMQyDfv364fLly2hsbJR3cyglwTAMnJ2dsXDhQmRkZGDr1q2oq6uTd7MoimoGhmGgo6OD0aNHY+DAgfj1119x9epVidYbJoSgrq4OMTExWLlyJfT19bF06VJ06dIF2traEtsORVGvRwjB7du3kZqaismTJ8tlXTAhBFevXoWZmRl8fHzoCzBKjK4RpuSOZVls3boVXl5e6NGjB71BUW+Fz+eL1w1/+OGHcHJyoucQRSkJQgiePn2KHTt2QENDA5MmTYK5ufk7XcM8Hg+xsbE4deoUfH19MXjwYJiamtL7AkXJGCEEjx8/xpYtW/Dpp5/CyspKLtdheXk5vv/+eyxcuBAWFhb0XtD6vHKNMA2EKbkjhKCwsBAbNmzAN998Ax0dHXk3iVIyhBCkpKRg165dGDZsGDp16gSGYejDjqKUACEEIpEIly5dwqlTp/Dee++hffv2bzV1mRACoVCIpKQk/Pvvv7C2tsZ7770HW1tbAKD3AoqSMUIISktL8dNPP2HGjBlyWRcM/DfYsnnzZri6uqJv3770XtA60UCYUmwsy2LTpk0ICAhAly5d6I2KemuEEDx58gRbt26FjY0Nxo4dCz09PXouUZSSIISgqKgIf/31F3R1dTF+/Pg3jiBxAfC9e/fw77//wsDAAMOHD4ebm5tMM1JTFPV/CCGorKzETz/9hJEjRyI4OFguz2JCCJKSknDs2DEsXryYLotovWggTCm+vLw8bNy4kY4KU++kqakJx44dQ3JyMj744AO4urrSYJiilAifz0dsbCyOHz+Orl27olevXtDV1X3hOhYIBLh//z7+/fdf6OjoYOjQofDw8KC1gClKjrgg+JdffkHv3r0REREht2dwTU0Nvv32W8yePRuurq5yaQOlEGggTCk+bvqKl5cXevXqJe/mUEqMZVmkpaVh165diIyMRGRkJM0SSVFKhMv2fPjwYeTk5GDEiBEICAiAhoYG+Hw+0tLScPz4cairq2P48OHw8PCAhoaGvJtNUa0aFwSvX78ePXr0QJcuXeQ2M0MkEmH79u0wNzfH8OHD6Qvx1o0GwpRyKC4uxrp16/DNN99AX19f3s2hlBjXkf7rr78gEAgwderUd07CQ1GU7HD1f7OysnDgwAGoqakhNDQUN27cgK6uLoYMGULLIFGUguCWJ/3666+IioqSaxBMCEF8fDyOHz+OL7/8kk6Jpl4ZCNMFNJRCsbGxgbe3Ny5fvkzrwlLvhGEYmJiYYN68eWjXrh1WrVqFW7duQSQSybtpFEU1A5fwzsnJCREREUhMTMS6devQ0NCAiRMnok2bNjQIpigFQAhBfn4+fvrpJwwePFjuQXBFRQX279+PadOmQUtLSy7toJQDHRGmFA6X5n7JkiUwNTWVd3MoFUAIQXFxMXbs2AETExOMHz8eJiYmtANNUQqKqwMcGxuLS5cuwcHBAQMHDoS1tTViY2Nx9uxZuLi4YNCgQbCzs6OJsShKTliWxd27d7Fnzx5MmTIFfn5+cn22CgQC/PrrrwgKCkKvXr3oc54C6NRoSpkQQnDkyBE0NjZi7NixtINDSQQhBHw+HxcvXsTFixcxYsQItGvXjq4rpCgFwrIsnjx5gosXLyIxMRH+/v7o3bs3bGxsxM8CQggaGhpw584dnDlzBvb29hgwYAAcHR3p9UxRMsTn83HmzBncvn0bM2fOhL29vVwDT0IIjh8/jpycHMycOZPmBqE4NBCmlEtdXR1WrFiBjz76CHZ2dvJuDqVCuLrVO3fuhKGhIcaNG0fXDlOUnIlEIuTm5uL06dPIyclBREQEunbtCmNj41dem4QQ8Hg8xMfH48yZM9DT00NUVBT8/f3pmkCKkiIuKdZff/0FdXV1TJkyBYaGhnJ/jmZkZGDHjh1YsmQJjI2N5doWSqHQQJhSLoQQXL16FYmJiViwYAEdFaYkiqs9eunSJZw6dQoDBgxAt27doKGhIfcHOUW1Flwgm5ycjLNnz4LH46FPnz4ICwuDtrZ2s69FQghEIhEePHiAU6dO4cmTJ+jatSs6deoEExMTAKDXNUVJAJfALjk5Gbt370ZUVBQiIyOhrq4u92usuroa3377LaZPnw4vLy+5t4dSKDQQppQPn8/HDz/8gCFDhiAwMJDe1CiJI4Tg6dOn2LNnD2prazFx4kQ4OjqKk/RQFCV5LMuisrISly9fxu3bt2Fvb48+ffrA09PznZJfcf2ZkpISXLhwAffu3YOtrS169OiBNm3aQEtLi17XFNVC3Cjwvn37UFZWhqlTp8LJyUkhrimBQIANGzbAy8sL/fv3V4g2UQqFBsKUcnr06BG2b9+OpUuXQldXV97NoVSUSCRCYmIiDh06hICAAAwePFghpnlRlKrg1ug/fvwY58+fR0FBAdq3b48uXbrA0tJS4tcaIQSNjY3IyMjAlStXUFpaioCAAHTs2BF2dnZvNeJMUa0ZIQRNTU24du0azp49i549eyIyMlJhXiyxLItTp07hwYMHmDdvHl0XTL0MDYQp5cSyLHbu3AkjIyNaEJ2SKkII6uvrcerUKcTFxWHw4MEIDw+npRco6h2wLIuKigrcunULt27dgoGBAXr27Al/f3/o6urK5J7OjUAnJSUhLi4OdXV18PHxQYcOHeDg4AAdHR36bKGol+CWLhw5cgQuLi4YNmyYVF5ctRQhBPfu3cO+ffuwaNEiGBkZKUzbKIVCA2FKedXW1mLFihWYO3cunJ2d5d0cSsVxpZb27t2LxsZGjBkzBh4eHvThSlFvgcfjITMzExcuXEBRURFCQkLQrVs3WFlZya32LyEELMuiuroaSUlJuH37Nurq6uDk5ISQkBC4u7vDzMyMXutUq/ZsErrTp0/D2NgYI0aMgIuLi0LlayGEoKysDD/++CPmzp0LFxcXeu1Sr0IDYUp5EUKQlJSEEydO4IsvvqDZQCmp4zrMKSkpOHjwIOzs7DBq1ChYWVnRBy1FvQSXRKeoqAjXr1/H3bt3YWpqisjISAQEBCjMNEoO1966ujpkZmYiMTER2dnZ0NXVhY+PD3x8fODi4gI9PT2aM4BSeVwsUF5ejqtXr+L27duws7PDkCFDxOuAFe0aqK+vx/fff4/+/fujY8eOCtc+SqHQQJhSbiKRCFu2bIGzszNNhEDJDLeu8dq1azh16hTCwsLQr18/Ov2KovB/wWRNTQ3u3LmDGzdugGVZhIeHo3379rCwsACgHBmbuczTRUVFyMjIQHp6OkpKSqCtrQ03Nze0adMGrq6uMDIygoaGhtxGtSlKkliWRX19PVJSUhAbG4vy8nKEhYVJbe2+pAgEAmzcuBH29vYYPny4Qo1UUwqJBsKU8quqqsIPP/yADz/8kE6BoWSK6+yfOXMGcXFx6N69O7p37w59fX16HlKtDsuyqKurw/379xEbG4uysjL4+/ujc+fOcHBwUIlkNdz00MrKSmRlZSEjIwP5+fng8/kwMDCAi4sLXF1d4eLiAn19fejo6CjcqDdF/a9nz+vU1FQkJyfj6dOn8PDwQKdOneDq6qrwa+ZFIhEOHjyIp0+fYubMmSpxv6GkjgbClPLjkiL8/fff+PLLL2kWaUrmCCEoLy/H8ePHkZaWhj59+qBTp04yS/pDUfLCTSN++PAhbty4gYKCAri6uiIiIgJubm4qfw1wtcebmppQVVWFrKws5OTkIC8vD01NTSCEwNTUFDY2NrCzs4ODgwMMDAygq6sLPT09aGtr01ErSqYIIRAIBKirq0NlZSUyMzPx6NEj8UwHHx8fBAUFwcHBQWmuX5Zlce7cOSQkJOCjjz5SmnZTckcDYUo1sCyLAwcOgMfjYeLEibRjQckFy7IoKyvDv//+i8ePHyMqKgqdO3dW+DfpFNVcXN+goaEBmZmZuHnzJnJycuDg4ICIiAj4+PhAR0cHgHJMfZYGLpeASCQCj8dDaWkpSkpKUFhYiMLCQtTW1qKxsREikQg6OjowMjKCgYEBDAwMYGZmBgsLC+jp6YkDZS0tLWhpaUFTU1P8h6JehRvd5fF4aGpqQm1tLWpra1FaWori4mI8efIElZWVAABTU1N4enrC09MTzs7O0NPTg7q6ulJdu4QQ3LlzB0eOHMHChQthbGysVO2n5IoGwpTq4PF4WLNmDbp27YouXbrQGyElF9y9s7i4GEePHn0uIKZvqSllxK35bWhoQGpqKm7duoXi4mLY29ujQ4cO8PPzg56eHoDWG/w2x7P9Ki7PQHV1Naqrq1FbW4u6ujpUVFSgvLwc9fX1aGhoAI/HA5/Ph1AoFB8HANDQ0ADDMFBXVwcA8dpk7v9TrQP30oVlWfHsBKFQKE5ipaWlBUNDQxgaGsLa2hq2trawsrKCpaUlDA0Nxdersl63hBDcv38ff/75Jz799FPY2Ngo7Xeh5IIGwpRqKS8vx+rVq/Hhhx/Czc2N3hApueJKLp04cQKZmZno0qULunXrRpNqUQqP61TX1NTg3r17uHPnDsrLy+Hq6ooOHTrA3d2droWXIZZlIRAIIBQKxf/LBUEv+1+qdWAYBmpqauI/6urq0NTUFM8iUOXkbYQQZGVlYePGjZg3bx7NEUO1BA2EKdVCCEF6ejr27NmDTz75hNZ+pBQCIQRPnjzB+fPnkZSUhJCQEPTs2ROWlpZ0Gj+lMAghaGpqQmlpKRITE3Hv3j0IhUJ4e3ujXbt2cHR0FJcNoiiKkhdCCB4/foyNGzfiww8/hKenJ70vUS1BA2FK9RBCcP36dVy5cgUff/wx9PX15d0kigLw37lZXV2Na9eu4fr163BwcEDfvn3h6uoKDQ0NeTePaoVYlkVlZSWys7ORmJiInJwcGBgYIDg4GG3btoW5uTk0NTVpJ5OiKIXABcGbNm3C9OnT4eXlRe9PVEvRQJhSTSzL4ujRoygoKKBp9CmFwyUzSUpKwunTp6GmpobevXsjODiYJtaipIZ7rvP5fOTm5iIlJQX3799HU1MTnJ2dERwcjDZt2sDAwEC8xpCiKEpREELw8OFDbNmyBTNmzKBBMPWuaCBMqS6hUIidO3cCACZOnEiDYUrhcGv6srKycPbsWeTm5oqnTVtYWKj0+i5K+rjkSkKhEKWlpUhPT8e9e/fw5MkTmJmZITAwEH5+frC1tRUnWaLnG0VRiogrlblz507MmjUL7u7u9H5FvSsaCFOqjc/n488//4SOjg7Gjh0LLS0teTeJol6Kq0UcGxuLW7duwcTEBD169ICvry9dl0k1G8uy4PF4qK6uxv3795GamoqSkhLo6+vDy8sLAQEBsLOzey5jLEVRlCJjWRY3btzAiRMnMHv2bDg6OtL7FyUJNBCmVBtXOH7Hjh3Q1dXFmDFjoK2tLe9mUdQrcdOms7KycOnSJeTn58PPzw9dunSBvb09Xa9JPYdlWdTX16O8vBzp6el48OABysrKoKOjIw58HRwcYGBgQEvrUBSldPh8PmJiYpCamoo5c+bAwsJC3k2iVAcNhCnVx9Vr3LVrF/h8PqZOnQpdXV15N4uiXoub1lpbW4s7d+7gxo0bEAqFCAsLQ/v27WFlZUUzTrdCXHKr4uJipKenIysrC1VVVTA2NkabNm3Qpk0bODk5QVtbG+rq6vSlCUVRSokQgvr6euzcuRMsy2Lq1Kl0dhQlaTQQploHQghEIhEOHTqEx48fY+7cuXRqIKU0uKC4pKQEsbGxSExMhK6uLjp06ICQkBCYmprS5EYqhjvmAoEARUVFyM7Oxv3791FcXAxCCKytreHj4wMPD4/nZgrQc4CiKGVHCEFBQQE2bdqE0NBQDB48GBoaGvT+RkkaDYSp1kUkEuHcuXO4fPkyZs2aBScnJ3pjpZQKl/woNzcXt27dwv3796Gvr4/w8HAEBwfD2NiYjgQqGe5FnVAoxJMnT5CTk4OHDx8iPz8fDQ0NMDY2houLC3x8fGBvbw9zc3PxbAB6nCmKUiVCoRA3btzA0aNHMWHCBAQFBdHZT5S00ECYan24zIPR0dEYNmwYwsPD6do5SmnxeDwUFBTg9u3buH//PrS0tBAUFPT/2ru3nia6NgzAdykt7XRLoQXRAq2SuiEcoFFjTBRi9Ado3kP1f3ngiZ4aNcbExAMTE2OIkihGwkaRUlpaurOdmc50N9/BlzVWNqIvviL0vpLJzLSlgWFmrXnWrLUenD59GsFgEHa7ncHSX0QM1dA0Dfl8HktLS1heXkY8HkelUoHH48Hg4CCOHTuGwcFB+Hw+uFwu/g+J6EAzDAOFQgH37t2Dpmm4ffs2QqHQXv9adLAxEKb2ZBgG0uk07ty5g4GBAfzzzz9m7kyi/UgEWNlsFm/fvsW7d++g6zqOHTuG8fFxM6jiOf7niImsyuUyMpkMPn/+jJWVFWQyGRiGYT7pHRoawvDwMDweDxwOB9NmEVFbqdVqeP36NR49eoQrV65gcnKSE0PSn8BAmNqXmJ33yZMnmJqawq1bt3DixAmOs6N9T+QnFil0pqenkUwm4ff7MTY2ZnaxFbm1eb7/uo11ZKVSQT6fRzabxZcvX7CysoL19XVomgZJkhAMBnH06FGEw2EcOXIEkiSZXdh5/Imo3YgyNB6P4/79+7Barbh58yb6+/tZJtKfwkCYyDAMLC4u4u7du4hEIrhx4wb8fj8LYjoQRFleq9WwvLyMmZkZzM7Oolwuo7+/H2NjY4jFYgiFQgzMtiCOn2hcUBQFmUwG6XQa8Xgcq6ur+Pr1K3RdhyRJ6O3tRSQSQTgcRl9fH3p6etDZ2Wl+H48tEbUzUabm83k8fPgQc3NzuH79Os6cOcPeMPSnMRAmAv5fMGuahufPn+PFixe4evUqLl26hK6uLhbKdOAYhoFSqYREIoH3799jcXERqqqit7cXJ0+exPHjx9HX1we73d4WE2+JILfRaKDRaEDXdaTTaXNJJBIoFovQNA1WqxXd3d0IhUIIh8M4fPgw/H4/fD4fywsioh8Q6d+ePXuG6elpXL58GRMTE0yLRHuFgTBRK8MwkM1m8eDBAywtLeHatWs4d+4cnE4nC2k6sBqNBsrlMtLpND5+/Ij5+XkUi0VIkoRIJIKRkRFEIhG43W44HI59+dS42WyiWq2aiyzLSKVSyGQyWF9fx/r6OsrlMgzDQEdHB3p6ehAKhdDX14cjR44gEAjA4XDA6XRy7BoR0U8Ss+Ink0k8f/4cs7OzuHjxIi5dusR5K2ivMRAm2kqz2UQqlcLjx4+xvLyMyclJnD9/nrmH6cATT0er1SqKxSIWFhawsLCAeDwOXdfh9/sRDocxMjKCgYEBdHd373lrvsi3W6lUUKlUoKoqyuUyUqkUstksCoUCisUiFEUBANhsNrhcLvT39yMYDCIYDKKvrw/d3d3o7OyEzWZjzkoiol0wDAOKomBmZgYvXryAoiiYmJjAuXPnOBM+/S0YCBNtxzAMc3bpp0+fYnZ2FqdOncLExISZf5gFOR10oi4QwXEqlUI8HsfCwgJWV1ehqqo5GVQ0GkU4HEYoFDKDSmGna2W7Oqder0NRFCiKAlmWoSgKvn79ikwmg3w+D1mWUS6XoWkaDMMwn9p6PB4cOnQIvb29CAQCCAQC6O7uNtNJibFovIaJiHZPlOHVahXz8/N49eoVPn36hMHBQUxOTmJkZIQNjPS3YSBMtBNxLZTLZUxNTeHly5doNps4e/Yszpw5g2Aw2BbjKImE1vpBpGxqTQ+UzWah6zqcTif8fj+Gh4cxMDCAUCiEYDBoTjoly7IZyMqyjHw+j3w+D1VVoes6NE1DvV6H1WqFw+GA2+2Gy+WCz+dDKBRCIBCAx+OBx+Mx39t4HfK6JCL6/UQ90Gg0UCwWMTc3hzdv3iCZTCIUCuHChQsYHR2F2+0GwLKY/koMhIl+Vb1eRyqVwtTUFGZmZtBoNBCLxTA6OopoNPpdWhSi/Uj0hmg2m+Z643az2YSu62YwqygKVFWFqqqQZRmZTAbJZBKJRALZbBYWiwVutxuSJEGWZaytrUGWZfT09Jh5dGOxGIaHh+H1euFyuSBJElwuFxwOB68pIqI9ZBgG6vU6dF03h83Mz88jkUjAYrEgGo1ifHzczInO8pr2AQbCRLtRq9VQKBQwNzeHDx8+IJFIwG63Y3BwEMPDw4hGo/D5fJAkiRPs0G8nJiERgelO241GA9VqFZqmQdM0qKqKSqVi7m+16LqOZrMJ4FuLvljb7Xa4XK7vglZJksxtr9cLr9drjrm1Wq0AvnWzzuVyWFtbQy6XQy6XQzabhaIoZiAuSRJ8Ph/8fr+5BAIB+Hw+2O122O122Gy2776f1xgR0b8j6hTRI6dSqSCdTmNlZQXJZBJra2uo1Wpwu92IRqOIxWIYGhqCx+PhPQ7tRwyEiX4XwzBQrVZRKBSwtLSEpaUlfPnyBaVSCRaLBT6fz5yJ9vDhw3C73ejq6oLD4UBXV5eZqqajo8NccwzjZq1PKn/Wxs/vZr/1yei/XYsbjdZZjGu1GqrVKur1Our1upnKp3W/dV2v11Gr1czPiaWjo2PLRZxTdrsdDofDHEvrdDrNffFa63utsySLpfXc/F3n6cYURmIm63w+b052VSwWUSgUUCqVoOu6eQwsFgtsNhu6urrgdDrNYFzsu91us+u0CJpF4LxxbbFYzGPVugitfzMR0V4TDZ7At3IUwKY6RNQfoq6pVCooFAooFApmr55SqYRyuYxqtYrOzk44HA5z5vyBgQGEw2G43W7YbDaWg3QQMBAm+q+0di9VFAXZbBa5XA6ZTAarq6uQZXnTUzeOb9yZOK67OTatP/8zAXVrhS+2t1uLYEq8ttXnrFYr7Ha72QBis9nMJ5xbBWjbvSZ+rnUNbD5vWvf38zkm/letazFjtOiWLZ5yq6pqXl9iHLKqqpsaGzauhZ2Oy346bkR0cP2oDhN1XWs90tpoKHrZiIZCr9cLv98Pr9f7XV0GsMyjA4mBMNGf9qPZcUULbmt3VtrsV7vAbmy53viUb6v396rS583G7/UrPQfE57fqWr7x/V/9XiKi/4JogBXbom4TQW9rXfej7yBqQ9sGwp1bvUhEu7ddhSPGOhLR7/OrN3jiRrI19RMRERG1j53uANh0RERERERERAfKzv0oiIiIiIiIiA4QBsJERERERETUVhgIExERERERUVthIExERERERERthYEwERERERERtRUGwkRERERERNRW/gfkPKT8+tNc/QAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1800x1800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "show_model(basic_model, figsize=(25, 25), filename=\"exampleHMM.png\", overwrite=True, show_ends=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[6.60516956e-02 1.74941494e-02 3.98524490e-02 2.68866292e-02\n",
      "  4.28905751e-02 4.20195407e-02 5.13280653e-02 7.40903989e-03\n",
      "  2.85867205e-02 1.13759196e-02 4.74398935e-02 7.71337722e-04\n",
      "  0.00000000e+00 6.17893987e-01]\n",
      " [4.99389436e-02 2.81533978e-02 4.41629271e-02 4.83207600e-03\n",
      "  1.87289767e-02 2.89175401e-03 3.27112816e-01 3.49857285e-03\n",
      "  1.86540608e-03 9.74655949e-03 8.74268634e-03 2.32239311e-04\n",
      "  0.00000000e+00 5.00093645e-01]\n",
      " [4.74506603e-03 4.11598857e-02 1.01334577e-02 7.79330680e-03\n",
      "  9.36923865e-04 2.28147438e-01 1.29377528e-01 1.49691937e-02\n",
      "  3.50115927e-02 7.23201601e-03 2.02496448e-02 2.28833939e-04\n",
      "  0.00000000e+00 5.00015110e-01]\n",
      " [8.44346876e-02 6.84548352e-02 7.07838374e-02 4.83184381e-02\n",
      "  8.79226192e-03 3.68740110e-02 1.64701687e-02 6.65270008e-03\n",
      "  2.38026254e-02 1.45423344e-02 1.20740378e-01 4.45742049e-05\n",
      "  0.00000000e+00 5.00089148e-01]\n",
      " [1.00209588e-02 5.52135184e-02 3.63832852e-02 4.51761854e-02\n",
      "  1.47367042e-04 7.59104007e-02 1.22838616e-01 9.41511656e-03\n",
      "  3.36979302e-02 1.24443280e-02 9.84411840e-02 2.94734084e-04\n",
      "  0.00000000e+00 5.00016373e-01]\n",
      " [6.31474320e-03 1.19619930e-01 4.45907498e-03 8.83152172e-03\n",
      "  3.19156696e-04 3.01831047e-03 3.13617048e-01 4.89221621e-03\n",
      "  4.98340384e-03 1.00306390e-03 3.21983513e-02 7.11263494e-04\n",
      "  0.00000000e+00 5.00031915e-01]\n",
      " [1.42186216e-01 6.44433449e-03 1.22312969e-01 1.31746803e-02\n",
      "  2.99290420e-02 7.77451413e-03 7.48850281e-02 4.04728721e-03\n",
      "  9.91732912e-03 8.95714825e-03 7.93840316e-02 1.67974904e-04\n",
      "  0.00000000e+00 5.00819446e-01]\n",
      " [1.35483054e-01 2.97556240e-02 6.58000252e-02 9.87633477e-03\n",
      "  1.86552990e-02 6.58422318e-03 1.90942472e-01 1.12691512e-02\n",
      "  4.60051491e-03 2.91225256e-03 2.26649221e-02 1.26619676e-04\n",
      "  0.00000000e+00 5.01329506e-01]\n",
      " [5.17762374e-02 4.55803561e-03 2.81353953e-02 2.66499074e-02\n",
      "  5.77689750e-03 8.82405222e-03 4.31680253e-03 4.95162643e-04\n",
      "  4.03748001e-03 1.16680633e-02 3.53723878e-01 1.26964780e-05\n",
      "  0.00000000e+00 5.00025394e-01]\n",
      " [3.75274552e-02 9.76885261e-03 4.57901892e-02 1.81152599e-02\n",
      "  5.96171947e-03 4.22759125e-02 1.76759753e-02 2.44744273e-03\n",
      "  3.47244012e-03 5.45967994e-03 3.11390021e-01 4.18366279e-05\n",
      "  0.00000000e+00 5.00073213e-01]\n",
      " [4.00312064e-02 2.88215105e-02 8.52942886e-02 5.15865004e-02\n",
      "  7.20281131e-03 8.13147781e-02 4.86916888e-02 4.51672728e-03\n",
      "  2.73775265e-02 3.26983681e-02 9.22404677e-02 9.58093666e-05\n",
      "  0.00000000e+00 5.00128315e-01]\n",
      " [1.38545954e-01 1.37174211e-03 2.78920897e-02 3.20073160e-03\n",
      "  1.09739369e-02 2.28623686e-03 2.65203476e-02 4.57247372e-04\n",
      "  4.11522634e-03 3.65797897e-03 2.83493370e-02 2.52400549e-01\n",
      "  0.00000000e+00 5.00228624e-01]\n",
      " [8.95317405e-02 3.44872689e-02 1.21708232e-01 9.12321242e-02\n",
      "  4.97471224e-02 2.12831357e-01 1.41022846e-01 1.65678409e-02\n",
      "  1.59530869e-01 3.74520405e-02 4.53435647e-02 5.44994768e-04\n",
      "  0.00000000e+00 0.00000000e+00]\n",
      " [0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n",
      "  0.00000000e+00 0.00000000e+00]]\n"
     ]
    }
   ],
   "source": [
    "column_names = [s.name for s in basic_model.states]\n",
    "#order_index = [column_names.index(c) for c in column_order]\n",
    "\n",
    "# re-order the rows/columns to match the specified column order\n",
    "transitions = basic_model.dense_transition_matrix()\n",
    "\n",
    "print(transitions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## Finishing the project\n",
    "---\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "**Note:** **SAVE YOUR NOTEBOOK**, then run the next cell to generate an HTML copy. You will zip & submit both this file and the HTML copy for review.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['[NbConvertApp] WARNING | Config option `kernel_spec_manager_class` not recognized by `NbConvertApp`.',\n",
       " 'Traceback (most recent call last):',\n",
       " '  File \"C:\\\\Users\\\\lveys\\\\anaconda3\\\\envs\\\\nlp_py37\\\\Scripts\\\\jupyter-nbconvert-script.py\", line 10, in <module>',\n",
       " '    sys.exit(main())',\n",
       " '  File \"C:\\\\Users\\\\lveys\\\\anaconda3\\\\envs\\\\nlp_py37\\\\lib\\\\site-packages\\\\jupyter_core\\\\application.py\", line 270, in launch_instance',\n",
       " '    return super(JupyterApp, cls).launch_instance(argv=argv, **kwargs)',\n",
       " '  File \"C:\\\\Users\\\\lveys\\\\anaconda3\\\\envs\\\\nlp_py37\\\\lib\\\\site-packages\\\\traitlets\\\\config\\\\application.py\", line 845, in launch_instance',\n",
       " '    app.start()',\n",
       " '  File \"C:\\\\Users\\\\lveys\\\\anaconda3\\\\envs\\\\nlp_py37\\\\lib\\\\site-packages\\\\nbconvert\\\\nbconvertapp.py\", line 350, in start',\n",
       " '    self.convert_notebooks()',\n",
       " '  File \"C:\\\\Users\\\\lveys\\\\anaconda3\\\\envs\\\\nlp_py37\\\\lib\\\\site-packages\\\\nbconvert\\\\nbconvertapp.py\", line 513, in convert_notebooks',\n",
       " '    \"Please specify an output format with \\'--to <format>\\'.\"',\n",
       " \"ValueError: Please specify an output format with '--to <format>'.\",\n",
       " \"The following formats are available: ['asciidoc', 'custom', 'html', 'latex', 'markdown', 'notebook', 'pdf', 'python', 'rst', 'script', 'slides', 'webpdf']\"]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "!!jupyter nbconvert *.ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Step 4: [Optional] Improving model performance\n",
    "---\n",
    "There are additional enhancements that can be incorporated into your tagger that improve performance on larger tagsets where the data sparsity problem is more significant. The data sparsity problem arises because the same amount of data split over more tags means there will be fewer samples in each tag, and there will be more missing data  tags that have zero occurrences in the data. The techniques in this section are optional.\n",
    "\n",
    "- [Laplace Smoothing](https://en.wikipedia.org/wiki/Additive_smoothing) (pseudocounts)\n",
    "    Laplace smoothing is a technique where you add a small, non-zero value to all observed counts to offset for unobserved values.\n",
    "\n",
    "- Backoff Smoothing\n",
    "    Another smoothing technique is to interpolate between n-grams for missing data. This method is more effective than Laplace smoothing at combatting the data sparsity problem. Refer to chapters 4, 9, and 10 of the [Speech & Language Processing](https://web.stanford.edu/~jurafsky/slp3/) book for more information.\n",
    "\n",
    "- Extending to Trigrams\n",
    "    HMM taggers have achieved better than 96% accuracy on this dataset with the full Penn treebank tagset using an architecture described in [this](http://www.coli.uni-saarland.de/~thorsten/publications/Brants-ANLP00.pdf) paper. Altering your HMM to achieve the same performance would require implementing deleted interpolation (described in the paper), incorporating trigram probabilities in your frequency tables, and re-implementing the Viterbi algorithm to consider three consecutive states instead of two.\n",
    "\n",
    "### Obtain the Brown Corpus with a Larger Tagset\n",
    "Run the code below to download a copy of the brown corpus with the full NLTK tagset. You will need to research the available tagset information in the NLTK docs and determine the best way to extract the subset of NLTK tags you want to explore. If you write the following the format specified in Step 1, then you can reload the data using all of the code above for comparison.\n",
    "\n",
    "Refer to [Chapter 5](http://www.nltk.org/book/ch05.html) of the NLTK book for more information on the available tagsets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package brown to\n",
      "[nltk_data]     C:\\Users\\lveys\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package brown is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[('The', 'AT'),\n",
       " ('Fulton', 'NP-TL'),\n",
       " ('County', 'NN-TL'),\n",
       " ('Grand', 'JJ-TL'),\n",
       " ('Jury', 'NN-TL'),\n",
       " ('said', 'VBD'),\n",
       " ('Friday', 'NR'),\n",
       " ('an', 'AT'),\n",
       " ('investigation', 'NN'),\n",
       " ('of', 'IN'),\n",
       " (\"Atlanta's\", 'NP$'),\n",
       " ('recent', 'JJ'),\n",
       " ('primary', 'NN'),\n",
       " ('election', 'NN'),\n",
       " ('produced', 'VBD'),\n",
       " ('``', '``'),\n",
       " ('no', 'AT'),\n",
       " ('evidence', 'NN'),\n",
       " (\"''\", \"''\"),\n",
       " ('that', 'CS'),\n",
       " ('any', 'DTI'),\n",
       " ('irregularities', 'NNS'),\n",
       " ('took', 'VBD'),\n",
       " ('place', 'NN'),\n",
       " ('.', '.')]"
      ]
     },
     "execution_count": 217,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "from nltk import pos_tag, word_tokenize\n",
    "from nltk.corpus import brown\n",
    "import random\n",
    "\n",
    "nltk.download('brown')\n",
    "training_corpus = nltk.corpus.brown\n",
    "training_corpus.tagged_sents()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "57340"
      ]
     },
     "execution_count": 218,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(training_corpus.tagged_sents())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 219,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train samples: 45872\n",
      "Test samples: 11468\n"
     ]
    }
   ],
   "source": [
    "corpus = list(nltk.corpus.brown.tagged_sents())\n",
    "\n",
    "random.seed(42)\n",
    "random.shuffle(corpus)\n",
    "\n",
    "split = int(0.8 * len(corpus))\n",
    "\n",
    "train = corpus[:split]\n",
    "test = corpus[split:]\n",
    "\n",
    "print('Train samples:', len(train))\n",
    "print('Test samples:', len(test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 220,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "57340"
      ]
     },
     "execution_count": 220,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(corpus)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 221,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[[('He', 'PPS'),\n",
       "  ('let', 'VBD'),\n",
       "  ('her', 'PPO'),\n",
       "  ('tell', 'VB'),\n",
       "  ('him', 'PPO'),\n",
       "  ('all', 'ABN'),\n",
       "  ('about', 'IN'),\n",
       "  ('the', 'AT'),\n",
       "  ('church', 'NN'),\n",
       "  ('.', '.')],\n",
       " [('China', 'NP'),\n",
       "  ('never', 'RB'),\n",
       "  ('tried', 'VBD'),\n",
       "  ('to', 'TO'),\n",
       "  ('integrate', 'VB'),\n",
       "  ('Tibet', 'NP'),\n",
       "  ('by', 'IN'),\n",
       "  ('extirpating', 'VBG'),\n",
       "  ('the', 'AT'),\n",
       "  (\"people's\", 'NNS$'),\n",
       "  ('religion', 'NN'),\n",
       "  ('and', 'CC'),\n",
       "  ('institutions', 'NNS'),\n",
       "  ('.', '.')]]"
      ]
     },
     "execution_count": 221,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "corpus[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Rearrange data in order to match to default format from the project \"Part of Speech Tagging\".\n",
    "Originally tagged sentences represented as sequences of tuple, i.e. (word, tag). We need to rearrange data in order to match to default format from the project \"Part of Speech Tagging\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "def rearrange_data(sequences):\n",
    "    x = []\n",
    "    y = []\n",
    "    w = set()\n",
    "    t = set()\n",
    "    for sequence in sequences:\n",
    "        sequence_x = []\n",
    "        sequence_y = []\n",
    "        for word, tag in sequence:\n",
    "            sequence_x.append(word)\n",
    "            sequence_y.append(tag)\n",
    "            w.add(word)\n",
    "            t.add(tag)\n",
    "        x.append(sequence_x)\n",
    "        y.append(sequence_y)\n",
    "    return x, y, w, t"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_x, train_y, train_words, train_tagset = rearrange_data(train)\n",
    "test_x, test_y, test_words, test_tagset = rearrange_data(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 224,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['He', 'let', 'her', 'tell', 'him', 'all', 'about', 'the', 'church', '.']\n",
      "['PPS', 'VBD', 'PPO', 'VB', 'PPO', 'ABN', 'IN', 'AT', 'NN', '.']\n"
     ]
    }
   ],
   "source": [
    "print(train_x[0])\n",
    "print(train_y[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 225,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train words: 50630 number of tags: 450\n",
      "Unknown test words: 5427 Unknown test tags 22\n"
     ]
    }
   ],
   "source": [
    "print('Train words:', len(train_words), 'number of tags:', len(train_tagset))\n",
    "print('Unknown test words:', len(test_words.difference(train_words)), 'Unknown test tags', len(test_tagset.difference(train_tagset)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Unsimplified Tags\n",
    "#### finds all tags starting with NN, and provides a few example words for each one\n",
    "- You will see that there are many variants of NN; the most important contain $ for possessive nouns, S for plural nouns (since plural nouns typically end in s) and P for proper nouns. In addition, most of the tags have suffix modifiers: -NC for citations, -HL for words in headlines and -TL for titles (a feature of Brown tabs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "metadata": {},
   "outputs": [],
   "source": [
    "def findtags(tag_prefix, tagged_text):\n",
    "    cfd = nltk.ConditionalFreqDist((tag, word) for (word, tag) in tagged_text if tag.startswith(tag_prefix))\n",
    "    return dict((tag, cfd[tag].keys()) for tag in cfd.conditions())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NN ['investigation', 'primary', 'election', 'evidence', 'place']\n",
      "NN$ [\"ordinary's\", \"court's\", \"mayor's\", \"wife's\", \"governor's\"]\n",
      "NN$-HL [\"Golf's\", \"Navy's\"]\n",
      "NN$-TL [\"Department's\", \"Commissioner's\", \"President's\", \"Party's\", \"Mayor's\"]\n",
      "NN-HL ['Merger', 'jail', 'Construction', 'fund', 'sp.']\n",
      "NN-NC ['ova', 'eva', 'aya']\n",
      "NN-TL ['County', 'Jury', 'City', 'Committee', 'Court']\n",
      "NN-TL-HL ['Mayor', 'Commissioner', 'City', 'Oak', 'Grove']\n",
      "NNS ['irregularities', 'presentments', 'thanks', 'reports', 'voters']\n",
      "NNS$ [\"taxpayers'\", \"children's\", \"members'\", \"women's\", \"years'\"]\n",
      "NNS$-HL [\"Dealers'\", \"Idols'\"]\n",
      "NNS$-TL [\"States'\", \"Women's\", \"Princes'\", \"Bombers'\", \"Falcons'\"]\n",
      "NNS-HL ['Wards', 'deputies', 'bonds', 'aspects', 'Decisions']\n",
      "NNS-TL ['Police', 'Roads', 'Legislatures', 'Bankers', 'Reps.']\n",
      "NNS-TL-HL ['Nations']\n"
     ]
    }
   ],
   "source": [
    "tagdict = findtags('NN', nltk.corpus.brown.tagged_words(categories='news'))\n",
    "for tag in sorted(tagdict):\n",
    "    print (tag, list(tagdict[tag])[:5])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "450"
      ]
     },
     "execution_count": 226,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_tags = set(train_tagset)\n",
    "len(train_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 227,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'PPSS+HV', 'FW-AT-TL', 'WPS', 'WRB-NC', 'VB+TO', 'FW-NN-NC', 'IN+PPO', 'FW-JJR', 'MD+TO', 'FW-VB', 'FW-IN+AT-T', 'FW-PPSS+HV', 'RBR', 'CD-NC', 'NN+NN-NC', 'FW-NNS-TL', 'BEDZ', 'EX+HVD', 'NNS$-HL', 'BEDZ*', 'HVZ', 'PP$$', 'ABN', 'BED-NC', 'VBD-TL', 'FW-VBD', 'PPSS+HV-TL', 'DO*', 'DTX', '---HL', \"''\", '*-HL', 'HV-HL', 'JJ', 'DOD', 'NNS$-TL', 'BE', 'FW-NR-TL', 'VBZ-TL', 'BEZ-HL', 'PPL', '*-TL', 'NNS-HL', 'FW-NPS', 'VBN-TL', 'MD', 'BEZ-NC', 'VBD', 'RB+BEZ', 'BEN-TL', 'PN', 'DT$', \"'\", 'CC-TL', 'FW-UH-TL', 'FW-BE', 'PPSS+MD-NC', 'WPO-NC', 'DOD-NC', 'WPS-HL', 'CD$', 'DT-NC', 'DO*-HL', 'FW-UH', 'FW-PPO+IN', 'JJ+JJ-NC', 'CC-TL-HL', 'PPO-HL', 'DTI-HL', 'NP$-HL', 'FW-IN+AT-TL', 'VBN-TL-NC', '.-TL', 'HV+TO', ',-HL', 'WRB-TL', 'PPS', 'BER-TL', 'UH-HL', 'WPS+HVD', 'NNS$-TL-HL', 'TO-TL', 'WQL', 'CS-HL', 'DO-HL', 'PPSS+BEM', 'FW-PPO', 'RB+BEZ-NC', 'WDT+BEZ-HL', 'DTI', 'UH', 'VBD-HL', 'BEM-NC', 'NNS', 'VB+AT', 'VB+JJ-NC', '(', 'AT-TL-HL', 'NP+MD', 'NP', 'BEZ', 'DOZ*-TL', 'VBG-NC', 'FW-PPSS', 'PPSS', 'RP-TL', 'PP$-TL', 'WDT+HVZ', 'IN-NC', 'NN$-HL', 'PPSS+BER-NC', 'DO-NC', 'FW-VBG-TL', 'AP', 'EX', 'JJ$-TL', 'JJR-NC', 'DT+MD', 'TO', 'WPO-TL', 'BEDZ-HL', 'RB-HL', 'NN+HVZ', 'NP-NC', 'FW-CD', 'HV-NC', 'BEZ-TL', 'FW-NN$', 'HV*', 'VB+VB-NC', 'FW-CC-TL', 'DTS', 'QL-TL', 'VBZ-NC', 'VBN+TO', 'NR', 'EX-NC', 'NR-NC', 'VBG+TO', 'NNS-TL', 'FW-PPS', 'JJ-TL-NC', 'JJT-HL', 'JJR', 'RB', 'FW-VB-NC', 'FW-NP', 'CC-HL', 'NP$-TL', 'AT-NC', 'PPS+BEZ-NC', 'VB+PPO', 'DTS+BEZ', 'DT+BEZ', 'MD*', 'NPS-NC', 'BEM*', 'JJ-HL', 'VBN-HL', 'WRB+DOD*', 'WDT', '.', 'HVZ*', 'NNS-TL-NC', 'WPS+BEZ', 'VBD-NC', 'FW-IN', 'AP-HL', 'NR+MD', ')', 'PN-TL', 'NP-TL', 'VB+RP', 'NN-NC', 'PPS+MD', 'PPSS+MD', 'WRB+BER', 'WPS-TL', 'DT+BEZ-NC', 'NN-TL', 'FW-NN-TL-NC', 'CD-TL-HL', 'CC-NC', 'WRB+BEZ', 'FW-NPS-TL', 'FW-JJ-TL', 'FW-NN$-TL', 'EX+MD', 'FW-VB-TL', 'QL-HL', 'UH-NC', 'FW-PPL', 'PPSS+HVD', 'NP+HVZ-NC', 'HVN', 'FW-NNS', 'WDT-HL', 'AT-TL', '*-NC', 'HVD', 'NN+HVZ-TL', 'RBR-NC', 'MD+HV', 'FW-NN-TL', 'DTI-TL', 'VB-TL', 'WDT-NC', 'TO+VB', 'NP$', 'FW-*-TL', 'BER', 'TO-NC', 'HVZ-NC', 'FW-WPS', 'OD-TL', 'DTS-HL', 'BEZ*', 'DO', 'NN-TL-HL', 'JJT-TL', 'BE-TL', 'JJS-TL', 'FW-NR', 'FW-AT', 'HVZ-TL', 'PPSS-TL', '``', 'RP-NC', 'PN-NC', 'FW-WPO', 'AP-TL', 'BE-HL', 'NN+MD', 'NR-TL', 'PPSS+VB', 'FW-NP-TL', 'FW-JJ-NC', 'DO-TL', 'FW-VBG', 'FW-RB', 'HVD*', 'FW-IN-TL', 'FW-IN+NN-TL', 'RB$', 'RN', 'NNS+MD', 'VB-NC', 'PPL-TL', 'NNS$', 'FW-NN', 'CC', ',-TL', 'PPSS+BER-N', 'RB-NC', 'NNS-NC', 'AT-HL', '(-HL', 'PPS+HVZ', 'NPS$-TL', 'WRB+BEZ-TL', 'PN+BEZ', 'VBN', 'DOZ-HL', 'FW-*', 'WDT+BEZ-TL', 'DOD*-TL', 'AP-NC', 'CS', 'RB+CS', 'FW-PPL+VBZ', 'NN-TL-NC', 'VB-HL', 'PP$-NC', ':', 'JJ-TL', 'RP', 'FW-HV', 'HV-TL', 'DT-HL', 'NPS-TL', 'PPLS', 'PN+MD', 'FW-OD-TL', 'WQL-TL', 'PPSS+BEZ', 'BED', 'BER-NC', 'ABN-HL', 'WPS+BEZ-NC', 'RB-TL', 'VBZ-HL', 'NNS-TL-HL', 'NN+BEZ', 'RP+IN', 'WRB+DOD', 'VBN-TL-HL', 'MD-HL', 'WPO', 'NIL', 'NRS', 'DT', 'VBG-TL', 'PPSS-NC', 'NP-TL-HL', 'FW-CS', 'PPS+HVD', 'JJT', 'FW-TO+VB', 'BEG', 'CS-NC', 'OD-NC', 'DT-TL', 'FW-RB-TL', 'WDT+BEZ', 'IN-TL', '*', 'DOZ*', 'MD-NC', 'AP+AP-NC', 'BED*', 'PPS-TL', 'ABL', 'FW-DTS', 'NNS$-NC', 'FW-VBZ', 'WDT+DO+PPS', 'FW-VBD-TL', 'NN', 'FW-PP$-TL', 'WDT+DOD', 'NN+HVD-TL', 'BER*', 'PPL-HL', 'RP-HL', 'MD-TL', 'TO-HL', 'BER*-NC', 'FW-RB+CC', 'FW-CD-TL', 'FW-CC', 'PPO-TL', 'VBG', '--', 'PPSS+BER-TL', 'FW-IN+AT', 'FW-AT-HL', 'FW-NNS-NC', 'CS-TL', 'PPL-NC', 'NP-HL', 'JJS', 'HVG', 'PPSS-HL', 'VBZ', 'RB+BEZ-HL', 'FW-BEZ', 'VBG-HL', 'OD-HL', 'PPS+BEZ', 'PPS+BEZ-HL', 'NN$-TL', 'IN+IN', 'FW-PP$', 'NPS', 'PPS-NC', 'WPS+BEZ-TL', 'JJR-TL', 'AT', ')-HL', 'FW-OD-NC', ':-HL', 'NR-HL', 'BEDZ-NC', 'PPSS+BER', 'EX+BEZ', 'NR-TL-HL', 'DOZ', 'WP$', 'PN+HVD', 'WRB-HL', 'HV', 'AP$', '.-NC', 'WRB', 'RBT', 'NP+BEZ-NC', 'JJ-TL-HL', ':-TL', 'WPS+MD', 'OD', 'VB', 'VBN-NC', 'ABX', 'NR$-TL', 'UH-TL', 'PP$', 'PPO', 'FW-QL', 'NPS$', 'JJR+CS', 'QL', 'BEN', 'PPO-NC', 'BER-HL', 'FW-DT', 'EX+HVZ', 'FW-BER', 'NP+BEZ', 'NPS-HL', 'FW-PP$-NC', 'FW-IN+NP-TL', 'IN', ',-NC', 'PP$-HL', 'BEM', 'JJS-HL', 'DO+PPSS', 'FW-WDT', 'IN-HL', 'WPS+HVZ', 'QLP', 'NPS$-HL', 'JJ-NC', 'FW-VBN', 'NN$', '.-HL', 'NP+HVZ', 'WRB+MD', 'NN-HL', 'CD-HL', 'VB+IN', 'PN+HVZ', 'FW-AT+NN-TL', 'CD', 'PPS-HL', 'PN$', 'PN-HL', 'NN+BEZ-TL', 'WDT+BEZ-NC', ',', 'DOD*', 'NR$', 'JJR-HL', 'ABN-TL', 'DOZ-TL', 'CD-TL', 'FW-JJ', 'FW-DT+BEZ', 'IN-TL-HL', 'FW-IN+NN'}\n"
     ]
    }
   ],
   "source": [
    "print(train_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 228,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "316"
      ]
     },
     "execution_count": 228,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_tags = set(test_tagset)\n",
    "len(test_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'PPSS+HV', 'FW-AT-TL', 'WPS', 'FW-NN-NC', 'FW-JJT', 'FW-VB', 'RBR', 'FW-NNS-TL', 'BEDZ', 'NNS$-HL', 'BEDZ*', 'HVZ', 'PP$$', 'ABN', 'BED-NC', 'DO*', 'DTX', '---HL', \"''\", '*-HL', 'JJ', 'DOD', 'NNS$-TL', 'BE', 'FW-NR-TL', 'VBZ-TL', 'BEZ-HL', 'PPL', 'NNS-HL', 'VBN-TL', 'MD', 'VBD', 'RB+BEZ', \"'\", 'PN', 'DT$', 'HVG-HL', 'CC-TL', 'CD$', 'DT-NC', 'FW-UH', 'FW-PPO+IN', 'PPO-HL', 'DTI-HL', 'NP$-HL', 'VBN-TL-NC', 'WDT+BER+PP', 'HV+TO', ',-HL', 'BER-TL', 'PPS', 'WRB-TL', 'WPS+HVD', 'TO-TL', 'WQL', 'CS-HL', 'PPSS+BEM', 'DTI', 'UH', 'WRB+IN', 'VBD-HL', 'NNS', '(', 'NP+MD', 'NP', 'NRS-TL', 'BEZ', 'VBG-NC', 'PPSS', 'RP-TL', 'PP$-TL', 'JJT-NC', 'IN-NC', 'NN$-HL', 'AP', 'EX', 'DT+MD', 'TO', 'WPO-TL', 'RB-HL', 'FW-CD', 'HV-NC', 'BEZ-TL', 'FW-NN$', 'HV*', 'FW-CC-TL', 'DTS', 'QL-TL', 'WRB+DO', 'NR', 'VBG+TO', 'NNS-TL', 'JJT-HL', 'JJR', 'RB', 'FW-NP', 'CC-HL', 'NP$-TL', 'AT-NC', 'VB+PPO', 'DTS+BEZ', 'DT+BEZ', 'MD*', 'BEM*', 'JJ-HL', 'VBN-HL', 'WDT', '.', 'HVZ*', 'NNS-TL-NC', 'WPS+BEZ', 'VBD-NC', 'FW-IN', 'AP-HL', 'ABN-NC', ')', 'PN-TL', 'NP-TL', 'NN-NC', 'WDT+BER', 'PPS+MD', 'PPSS+MD', 'WPS-TL', 'NN-TL', 'CD-TL-HL', 'WRB+BEZ', 'FW-JJ-TL', 'FW-NN$-TL', 'FW-PPL', 'UH-NC', 'PPSS+HVD', 'HVN', 'FW-NNS', 'WDT-HL', 'AT-TL', 'HVD', 'WRB+DOZ', 'MD+HV', 'FW-NN-TL', 'VB-TL', 'WDT-NC', 'NP$', 'BER', 'TO-NC', 'OD-TL', 'BEZ*', 'JJT-TL', 'NN-TL-HL', 'DO', 'JJS-TL', 'FW-AT', 'HVZ-TL', 'PPSS-TL', '``', 'AP-TL', 'BE-HL', 'NR-TL', 'FW-NP-TL', 'DO-TL', 'FW-VBG', 'FW-RB', 'HVD*', 'FW-IN-TL', 'VB-NC', 'NNS$', 'FW-NN', 'HVD-HL', 'CC', ',-TL', 'WPS-NC', 'RB-NC', 'NNS-NC', 'AT-HL', '(-HL', 'PPS+HVZ', 'QL-NC', 'NPS$-TL', 'WRB+BEZ-TL', 'PN+BEZ', 'VBN', 'DOZ-HL', 'FW-*', 'AP-NC', 'CS', 'RB+CS', 'PP$-NC', 'VB-HL', ':', 'JJ-TL', 'RP', 'DT-HL', 'NPS-TL', 'PPLS', 'MD*-HL', 'PN+MD', 'WQL-TL', 'BED', 'BER-NC', 'RBR+CS', 'RB-TL', 'VBZ-HL', 'NNS-TL-HL', 'NN+BEZ', 'WRB+DOD', 'VBN-TL-HL', 'MD-HL', 'WPO', 'NRS', 'NIL', 'DT', 'VBG-TL', 'PPSS-NC', 'NP-TL-HL', 'PPS+HVD', 'JJT', 'BEG', 'CS-NC', 'DT-TL', 'WDT+BEZ', 'IN-TL', '*', 'DOZ*', 'NN+IN', 'BED*', 'PPS-TL', 'ABL', 'NN', 'BER*', 'RP-HL', 'TO-HL', 'FW-CC', 'PPO-TL', 'VBG', '--', 'NP-HL', 'JJS', 'HVG', 'PPSS-HL', 'VBZ', 'MD+PPSS', 'FW-PN', 'VBG-HL', 'OD-HL', 'PPSS+BEZ*', 'PPS+BEZ', 'NN$-TL', 'NPS', 'PPS-NC', 'JJR-TL', 'AT', ')-HL', ':-HL', 'NR-HL', 'BEDZ-NC', 'PPSS+BER', 'EX+BEZ', 'DOZ', 'WP$', 'WRB-HL', 'HV', 'AP$', '.-NC', 'WRB', 'RBT', 'JJ-TL-HL', ':-TL', 'FW-UH-NC', 'WPS+MD', 'OD', 'VB', 'VBN-NC', 'ABX', 'NR$-TL', 'UH-TL', 'PP$', 'PPO', 'NPS$', 'FW-AT+NP-TL', 'QL', 'BEN', 'BER-HL', 'EX-HL', 'NP+BEZ', 'NPS-HL', 'IN', ',-NC', 'PP$-HL', 'BEM', 'FW-WDT', 'IN-HL', 'QLP', 'JJ-NC', 'FW-VBN', 'NN$', '.-HL', 'NP+HVZ', 'NN-HL', 'CD-HL', 'VB+IN', 'PN+HVZ', 'FW-AT+NN-TL', 'CD', 'PPS-HL', 'PN$', 'PN-HL', 'WDT+BEZ-NC', ',', 'DOD*', 'NR$', 'DOZ-TL', 'JJR-HL', 'ABN-TL', 'CD-TL', 'FW-JJ', 'FW-DT+BEZ', 'MD+TO'}\n"
     ]
    }
   ],
   "source": [
    "print(test_tags)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "metadata": {},
   "outputs": [],
   "source": [
    "wordtags = nltk.ConditionalFreqDist(nltk.corpus.brown.tagged_words())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_items([('JJ', 47), ('VB', 15), ('VB-HL', 1), ('RB', 1)])\n"
     ]
    }
   ],
   "source": [
    "print(wordtags[\"clean\"].items())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "that \t 12 ['CS', 'DT', 'WPS', 'WPO', 'QL', 'DT-NC', 'WPS-NC', 'CS-NC', 'WPS-HL', 'CS-HL', 'NIL', 'WPO-NC']\n",
      "A \t 11 ['AT', 'AT-TL', 'NN', 'NP', 'AT-HL', 'NP-HL', 'NP-TL', 'AT-TL-HL', 'NN-TL', 'FW-IN', 'AT-NC']\n",
      "in \t 10 ['IN', 'RP', 'IN-HL', 'IN-TL', 'NIL', 'IN-NC', 'RP-HL', 'RP-NC', 'NN', 'FW-IN']\n",
      "to \t 10 ['TO', 'IN', 'IN-HL', 'TO-HL', 'TO-NC', 'IN-TL', 'IN-NC', 'NIL', 'NPS', 'QL']\n",
      ": \t 9 [':', ':-HL', '.', ':-TL', 'IN', '.-HL', 'NP', ',', 'NIL']\n",
      "a \t 8 ['AT', 'AT-HL', 'AT-NC', 'FW-IN', 'NIL', 'NN', 'FW-IN-TL', 'AT-TL']\n",
      "for \t 7 ['IN', 'CS', 'IN-TL', 'IN-HL', 'RB', 'NN', 'IN-NC']\n",
      "it \t 7 ['PPS', 'PPO', 'PPS-HL', 'PPS-NC', 'PPO-HL', 'PPO-NC', 'UH']\n",
      "well \t 7 ['RB', 'QL', 'UH', 'NN', 'JJ', 'VB', 'QL-HL']\n",
      "as \t 7 ['CS', 'QL', 'IN', 'CS-HL', 'RB', 'CS-TL', 'NIL']\n"
     ]
    }
   ],
   "source": [
    "wtlist = sorted(wordtags.items(), key=lambda x: len(x[1]), reverse=True)\n",
    "for word, freqs in wtlist[:10]:\n",
    "    print(word, \"\\t\", len(freqs), list(freqs))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Build a hidden Markov model for part of speech tagging with the Brown corpus with the full NLTK tagset.\n",
    "- this is largely inspired by the work found here: https://github.com/1ytic/hmm-tagger"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate the new emission and transition probabilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 230,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bigram_counts_brown(sequences):\n",
    "    \"\"\"Return a dictionary keyed to each unique PAIR of values in the input sequences\n",
    "    list that counts the number of occurrences of pair in the sequences list. The input\n",
    "    should be a 2-dimensional array.\n",
    "    \n",
    "    For example, if the pair of tags (NOUN, VERB) appear 61582 times, then you should\n",
    "    return a dictionary such that your_bigram_counts[(NOUN, VERB)] == 61582\n",
    "    \"\"\"\n",
    "    tag_bigrams = {}\n",
    "\n",
    "    for sequence in sequences:\n",
    "        \n",
    "        l = len(sequence)\n",
    "        \n",
    "        for index in range(l-1):\n",
    "            \n",
    "            a,b = sequence[index:index+1], sequence[index+1:index+2]\n",
    "            \n",
    "            if (a[0],b[0]) in tag_bigrams.keys():\n",
    "                tag_bigrams[(a[0],b[0])] += 1\n",
    "            else:\n",
    "                tag_bigrams[(a[0],b[0])] = 1\n",
    "                \n",
    "    return tag_bigrams     "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 231,
   "metadata": {},
   "outputs": [],
   "source": [
    "emission_counts = pair_counts(train_y, train_x)\n",
    "tag_unigrams = unigram_counts(train_y)\n",
    "tag_bigrams = bigram_counts_brown(train_y)\n",
    "tag_starts = starting_counts(train_y)\n",
    "tag_ends = ending_counts(train_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build Model on larger TagSet from Brown Corpus dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 232,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Edges Brown model: 7818\n"
     ]
    }
   ],
   "source": [
    "brown_model = HiddenMarkovModel(name=\"brown-hmm-tagger\")\n",
    "\n",
    "states = dict()\n",
    "for tag, words in emission_counts.items():\n",
    "    #n = tag_unigrams[tag]\n",
    "    #assert n == sum(words.values())\n",
    "    probs = {w:c / tag_unigrams[tag] for w, c in words.items()}\n",
    "    emissions = DiscreteDistribution(probs)\n",
    "    state = State(emissions, name=tag)\n",
    "    brown_model.add_states(state)\n",
    "    states[tag] = state\n",
    "\n",
    "n = sum(tag_starts.values())\n",
    "for tag, counts in tag_starts.items():\n",
    "    brown_model.add_transition(brown_model.start, states[tag], counts / n)\n",
    "\n",
    "for (tag1, tag2), counts in tag_bigrams.items():\n",
    "    brown_model.add_transition(states[tag1], states[tag2], counts / tag_unigrams[tag1])\n",
    "\n",
    "for tag, counts in tag_ends.items():\n",
    "    brown_model.add_transition(states[tag], brown_model.end, counts / tag_unigrams[tag])\n",
    "\n",
    "brown_model.bake()\n",
    "\n",
    "print('Edges Brown model:', brown_model.edge_count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 233,
   "metadata": {},
   "outputs": [],
   "source": [
    "def replace_unknown_brown(sequence, vocabulary):\n",
    "    \"\"\"Return a copy of the input sequence where each unknown word is replaced\n",
    "    by the literal string value 'nan'. Pomegranate will ignore these values\n",
    "    during computation.\n",
    "    \"\"\"\n",
    "    return [w if w in vocabulary else 'nan' for w in sequence]\n",
    "\n",
    "def simplify_decoding_brown(X, model, vocabulary):\n",
    "    \"\"\"X should be a 1-D sequence of observations for the model to predict\"\"\"\n",
    "    _, state_path = model.viterbi(replace_unknown_brown(X, vocabulary))\n",
    "    return [state[1].name for state in state_path[1:-1]]  # do not show the start/end state predictions\n",
    "\n",
    "def accuracy_brown(X, Y, model, vocabulary):\n",
    "    \"\"\"Calculate the prediction accuracy by using the model to decode each sequence\n",
    "    in the input X and comparing the prediction with the true labels in Y.\n",
    "    \n",
    "    The X should be an array whose first dimension is the number of sentences to test,\n",
    "    and each element of the array should be an iterable of the words in the sequence.\n",
    "    The arrays X and Y should have the exact same shape.\n",
    "    \n",
    "    X = [(\"See\", \"Spot\", \"run\"), (\"Run\", \"Spot\", \"run\", \"fast\"), ...]\n",
    "    Y = [(), (), ...]\n",
    "    \"\"\"\n",
    "    correct = total_predictions = 0\n",
    "    for observations, actual_tags in zip(X, Y):\n",
    "        \n",
    "        # The model.viterbi call in simplify_decoding will return None if the HMM\n",
    "        # raises an error (for example, if a test sentence contains a word that\n",
    "        # is out of vocabulary for the training set). Any exception counts the\n",
    "        # full sentence as an error (which makes this a conservative estimate).\n",
    "        try:\n",
    "            most_likely_tags = simplify_decoding_brown(observations, model, vocabulary)\n",
    "            correct += sum(p == t for p, t in zip(most_likely_tags, actual_tags))\n",
    "        except:\n",
    "            pass\n",
    "        total_predictions += len(observations)\n",
    "    return correct / total_predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 234,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 97.32%\n",
      "testing accuracy: 92.52%\n"
     ]
    }
   ],
   "source": [
    "training_acc = accuracy_brown(train_x, train_y, brown_model, vocabulary=train_words)\n",
    "print(\"training accuracy: {:.2f}%\".format(100 * training_acc))\n",
    "\n",
    "testing_acc = accuracy_brown(test_x, test_y, brown_model, vocabulary=train_words)\n",
    "print(\"testing accuracy: {:.2f}%\".format(100 * testing_acc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Hidden Markov model have been able to achieve >92% tag accuracy with larger tagsets on realistic text corpora."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Apply Laplace Smoothing\n",
    "smoothe only transition probability from tag to tag, and also add the unknown transitions, which tags exists in the training data. To do this efficiently, first find the unknown bigrams from the test data. It allows not to add unused transition into the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [],
   "source": [
    "tag_bigrams_test = bigram_counts_brown(test_y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create model with Laplace smoothing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extend transition model including 7552 train bigrams by 458 new bigrams\n",
      "Edges Brown model with Laplace Smoothing: 8276\n"
     ]
    }
   ],
   "source": [
    "Smooth_Brown_model = HiddenMarkovModel(name=\"brown-smooth-hmm-tagger\")\n",
    "\n",
    "states = dict()\n",
    "for tag, words in emission_counts.items():\n",
    "    n = tag_unigrams[tag]\n",
    "    assert n == sum(words.values())\n",
    "    probs = {w:c / n for w, c in words.items()}\n",
    "    emissions = DiscreteDistribution(probs)\n",
    "    state = State(emissions, name=tag)\n",
    "    Smooth_Brown_model.add_states(state)\n",
    "    states[tag] = state\n",
    "\n",
    "n = sum(tag_starts.values())\n",
    "for tag, counts in tag_starts.items():\n",
    "    Smooth_Brown_model.add_transition(Smooth_Brown_model.start, states[tag], counts / n)\n",
    "\n",
    "for (tag1, tag2), counts in tag_bigrams.items():\n",
    "    nominator = counts + 1\n",
    "    denominator = tag_unigrams[tag1] + len(train_tagset)\n",
    "    Smooth_Brown_model.add_transition(states[tag1], states[tag2], nominator / denominator)\n",
    "\n",
    "for tag, counts in tag_ends.items():\n",
    "    Smooth_Brown_model.add_transition(states[tag], Smooth_Brown_model.end, counts / tag_unigrams[tag])\n",
    "\n",
    "# NOTE: counts statistics from the test set is not used\n",
    "\n",
    "new_bigrams = 0\n",
    "for (tag1, tag2), counts in tag_bigrams_test.items():\n",
    "    if (tag1, tag2) in tag_bigrams:\n",
    "        continue\n",
    "    if tag1 not in states or tag2 not in states:\n",
    "        continue\n",
    "    denominator = len(train_tagset)\n",
    "    if tag1 in tag_unigrams:\n",
    "        denominator += tag_unigrams[tag1]\n",
    "    Smooth_Brown_model.add_transition(states[tag1], states[tag2], 1 / denominator)\n",
    "    new_bigrams += 1\n",
    "\n",
    "print('Extend transition model including', len(tag_bigrams), 'train bigrams by', new_bigrams, 'new bigrams')\n",
    "    \n",
    "Smooth_Brown_model.bake()\n",
    "\n",
    "print('Edges Brown model with Laplace Smoothing:', Smooth_Brown_model.edge_count())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "training accuracy: 97.30%\n",
      "testing accuracy: 93.86%\n"
     ]
    }
   ],
   "source": [
    "training_acc = accuracy_brown(train_x, train_y, Smooth_Brown_model, vocabulary=train_words)\n",
    "print(\"training accuracy: {:.2f}%\".format(100 * training_acc))\n",
    "\n",
    "testing_acc = accuracy_brown(test_x, test_y, Smooth_Brown_model, vocabulary=train_words)\n",
    "print(\"testing accuracy: {:.2f}%\".format(100 * testing_acc))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Smoothing only transition probability from tag to tag, and added unknown transitions, which tags exists in the training data. This technique improve the baseline model for 1% in absolute and achieve >93% tag accuracy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test sentence:\n",
      "-----------------\n",
      "['According', 'to', 'state', 'law', 'a', 'slave', 'had', 'to', 'be', 'at', 'least', 'thirty', 'years', 'old', 'before', 'he', 'could', 'be', 'freed', '.']\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['IN', 'IN', 'NN', 'NN', 'AT', 'NN', 'HVD', 'TO', 'BE', 'IN', 'AP', 'CD', 'NNS', 'JJ', 'CS', 'PPS', 'MD', 'BE', 'VBN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "['IN', 'IN', 'NN', 'NN', 'AT', 'NN', 'HVD', 'TO', 'BE', 'IN', 'AP', 'CD', 'NNS', 'JJ', 'CS', 'PPS', 'MD', 'BE', 'VBN', '.']\n",
      "\n",
      "\n",
      "Test sentence:\n",
      "-----------------\n",
      "['With', 'tips', ',', 'the', 'girls', 'average', 'between', '$150', 'and', '$200', 'a', 'week', ',', 'depending', 'on', 'basic', 'salary', '.']\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['IN', 'NNS', ',', 'AT', 'NNS', 'NN', 'IN', 'NNS', 'CC', 'NNS', 'AT', 'NN', ',', 'VBG', 'IN', 'JJ', 'NN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "['IN', 'NNS', ',', 'AT', 'NNS', 'VB', 'IN', 'NNS', 'CC', 'NNS', 'AT', 'NN', ',', 'IN', 'IN', 'JJ', 'NN', '.']\n",
      "\n",
      "\n",
      "Test sentence:\n",
      "-----------------\n",
      "['It', 'was', 'a', 'very', 'tempting', 'offer', '.']\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['PPS', 'BEDZ', 'AT', 'QL', 'VBG', 'NN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "['PPS', 'BEDZ', 'AT', 'QL', 'VBG', 'NN', '.']\n",
      "\n",
      "\n",
      "Test sentence:\n",
      "-----------------\n",
      "['He', 'saw', 'the', 'surprise', 'in', 'her', 'face', ',', 'and', 'laughed', 'as', 'though', 'it', 'were', 'the', 'funniest', 'expression', 'he', 'had', 'ever', 'seen', '.']\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['PPS', 'VBD', 'AT', 'NN', 'IN', 'PP$', 'NN', ',', 'CC', 'VBD', 'CS', 'CS', 'PPS', 'BED', 'AT', 'JJT', 'NN', 'PPS', 'HVD', 'RB', 'VBN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "['PPS', 'VBD', 'AT', 'NN', 'IN', 'PP$', 'NN', ',', 'CC', 'VBD', 'CS', 'CS', 'PPS', 'BED', 'AT', 'JJT', 'NN', 'PPS', 'HVD', 'RB', 'VBN', '.']\n",
      "\n",
      "\n",
      "Test sentence:\n",
      "-----------------\n",
      "['Add', 'holes', 'in', 'top', ',', 'forming', '``', 'S', \"''\", 'for', 'salt', 'and', '``', 'P', \"''\", 'for', 'pepper', '.']\n",
      "\n",
      "Predicted labels:\n",
      "-----------------\n",
      "['VB', 'NNS', 'IN', 'NN', ',', 'VBG', '``', 'NP', \"''\", 'IN', 'NN', 'CC', '``', 'NP', \"''\", 'IN', 'NN', '.']\n",
      "\n",
      "Actual labels:\n",
      "--------------\n",
      "['VB', 'NNS', 'IN', 'NN', ',', 'VBG', '``', 'NN', \"''\", 'IN', 'NN', 'CC', '``', 'NN', \"''\", 'IN', 'NN', '.']\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for sentence, tag in zip(test_x[:5], test_y[:5]):\n",
    "    print(\"Test sentence:\\n-----------------\")\n",
    "    print(sentence)\n",
    "    print()\n",
    "    print(\"Predicted labels:\\n-----------------\")\n",
    "    print(simplify_decoding_brown(sentence, Smooth_Brown_model, vocabulary=train_words))\n",
    "    print()\n",
    "    print(\"Actual labels:\\n--------------\")\n",
    "    print(tag)\n",
    "    print(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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