sentiment_analysis+vz_Obama_McCain_2008.ipynb

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   "metadata": {
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   },
   "source": [
    "## Sentiment analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "YddbxG5sbd9r",
   "metadata": {
    "colab": {
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    },
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    "outputId": "1099cb42-ab03-4403-e0f8-7e23be7999b6"
   },
   "outputs": [],
   "source": [
    "!pip install pyreadr "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "Fx8idvoqbIlB",
   "metadata": {
    "colab": {
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    },
    "id": "Fx8idvoqbIlB",
    "outputId": "4046a623-b336-41af-a3ca-c2da25dfaa6e"
   },
   "outputs": [],
   "source": [
    "!pip install transformers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "%%capture\n",
    "\n",
    "import sys\n",
    "from transformers import pipeline\n",
    "import pyreadr\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from scipy import stats\n",
    "\n",
    "import matplotlib.dates as mdates"
   ]
  },
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   "source": [
    "sentiment_classifier = pipeline(task=\"sentiment-analysis\", device=0) # run on GPU!!"
   ]
  },
  {
   "cell_type": "code",
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    "outputId": "93d139ae-ec56-4826-fc61-c4aaa83eeb5b"
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   "outputs": [],
   "source": [
    "#pretrained_LM_path = \"kornosk/bert-political-election2008-twitter-mlm\" # Knowledge Enhance Masked Language Model for Stance Detection\n",
    "pretrained_LM_path = \"m-newhauser/distilbert-political-tweets\" # to classify short pieces of text as having either Democratic or Republican sentiment\n",
    "poli_sentiment_classifier = pipeline(model=pretrained_LM_path, task=\"sentiment-analysis\", device=0) # 0 means 'CUDA'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3abc8572-9c1d-44cf-ae43-280b0a76b572",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 36
    },
    "id": "3abc8572-9c1d-44cf-ae43-280b0a76b572",
    "outputId": "11cb34e0-f33d-46d1-c72e-0d6919da0568"
   },
   "outputs": [],
   "source": [
    "''' for google drive'''\n",
    "df_mcc_twt_clean = pd.read_csv('/content/drive/MyDrive/McCain_twts_2008.csv')\n",
    "df_obm_twt_clean = pd.read_csv('/content/drive/MyDrive/Obama_twts_2008.csv')\n",
    "\n",
    "'''df_mcc_twt_clean = pd.read_csv('McCainn_twts_2016.csv')\n",
    "df_obm_twt_clean = pd.read_csv('Obama_twts_2016.csv')'''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "9f06bd11-44ad-408f-bfc5-a4e4ca7eb281",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9f06bd11-44ad-408f-bfc5-a4e4ca7eb281",
    "outputId": "63899809-38d1-4dac-d00b-236f43419b74"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/transformers/pipelines/base.py:1039: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
      "  UserWarning,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.87 s, sys: 22 ms, total: 3.9 s\n",
      "Wall time: 3.9 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_mcc_twt_clean['poli_sentiment'] =  df_mcc_twt_clean.text.apply(poli_sentiment_classifier)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "mPiyM0GEdqXW",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "mPiyM0GEdqXW",
    "outputId": "0fa64556-835e-460b-b515-84cf743006e9"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/transformers/pipelines/base.py:1039: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
      "  UserWarning,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 7.8 s, sys: 31.9 ms, total: 7.83 s\n",
      "Wall time: 8.64 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_obm_twt_clean['poli_sentiment'] =  df_obm_twt_clean.text.apply(poli_sentiment_classifier)\n",
    "df_mcc_twt_clean['political_label'] = [li[0]['label'] for li in df_mcc_twt_clean['poli_sentiment']]\n",
    "df_obm_twt_clean['political_label'] = [li[0]['label'] for li in df_obm_twt_clean['poli_sentiment']]\n",
    "df_mcc_twt_clean['political_score'] = [li[0]['score'] for li in df_mcc_twt_clean['poli_sentiment']]\n",
    "df_obm_twt_clean['political_score'] = [li[0]['score'] for li in df_obm_twt_clean['poli_sentiment']]\n",
    "df_mcc_twt_clean = df_mcc_twt_clean.drop(columns=['poli_sentiment'])\n",
    "df_obm_twt_clean = df_obm_twt_clean.drop(columns=['poli_sentiment'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "7629d6b6-9687-4b71-acfb-926c466d589a",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "7629d6b6-9687-4b71-acfb-926c466d589a",
    "outputId": "0e713c65-5eae-4281-df7c-1a98df95b788"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/transformers/pipelines/base.py:1039: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
      "  UserWarning,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 3.89 s, sys: 23 ms, total: 3.91 s\n",
      "Wall time: 3.91 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_mcc_twt_clean['sentiment'] =  df_mcc_twt_clean.text.apply(sentiment_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "a0c254c3-ab42-4313-b54a-5230ab30a4fc",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "a0c254c3-ab42-4313-b54a-5230ab30a4fc",
    "outputId": "5cdc2fc8-8c65-40e1-d6f2-3a91eff69d92"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/transformers/pipelines/base.py:1039: UserWarning: You seem to be using the pipelines sequentially on GPU. In order to maximize efficiency please use a dataset\n",
      "  UserWarning,\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 6.79 s, sys: 35 ms, total: 6.82 s\n",
      "Wall time: 6.81 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "df_obm_twt_clean['sentiment'] =  df_obm_twt_clean.text.apply(sentiment_classifier)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "880fa2c6-e677-42a3-a507-3fdca4618925",
   "metadata": {
    "id": "880fa2c6-e677-42a3-a507-3fdca4618925"
   },
   "outputs": [],
   "source": [
    "df_mcc_twt_clean['sentiment_label'] = [li[0]['label'] for li in df_mcc_twt_clean['sentiment']]\n",
    "df_obm_twt_clean['sentiment_label'] = [li[0]['label'] for li in df_obm_twt_clean['sentiment']]\n",
    "df_mcc_twt_clean['sentiment_score'] = [li[0]['score'] for li in df_mcc_twt_clean['sentiment']]\n",
    "df_obm_twt_clean['sentiment_score'] = [li[0]['score'] for li in df_obm_twt_clean['sentiment']]\n",
    "df_mcc_twt_clean = df_mcc_twt_clean.drop(columns=['sentiment'])\n",
    "df_obm_twt_clean = df_obm_twt_clean.drop(columns=['sentiment'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "66e812f9-e264-4bb3-99a2-207c528c6745",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "66e812f9-e264-4bb3-99a2-207c528c6745",
    "outputId": "d64e8519-22a4-4bdc-e9c2-0a741163d931"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 713 entries, 0 to 712\n",
      "Data columns (total 8 columns):\n",
      " #   Column           Non-Null Count  Dtype  \n",
      "---  ------           --------------  -----  \n",
      " 0   Unnamed: 0       713 non-null    int64  \n",
      " 1   time             713 non-null    object \n",
      " 2   twt_id           713 non-null    int64  \n",
      " 3   text             713 non-null    object \n",
      " 4   political_label  713 non-null    object \n",
      " 5   political_score  713 non-null    float64\n",
      " 6   sentiment_label  713 non-null    object \n",
      " 7   sentiment_score  713 non-null    float64\n",
      "dtypes: float64(2), int64(2), object(4)\n",
      "memory usage: 44.7+ KB\n"
     ]
    }
   ],
   "source": [
    "df_mcc_twt_clean.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "id": "sNhcyVfieva9",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 36
    },
    "id": "sNhcyVfieva9",
    "outputId": "39cb1256-f8d2-4610-8f44-b5472556d614"
   },
   "outputs": [
    {
     "data": {
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "string"
      },
      "text/plain": [
       "\"local GPU\\ndf_mcc_twt_clean.to_csv('McCain_twts_2016_classified_senti.csv')\\ndf_obm_twt_clean.to_csv('Obama_twts_2016_classified_senti.csv')\""
      ]
     },
     "execution_count": 87,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "''' for colab'''\n",
    "df_mcc_twt_clean.to_csv('/content/drive/MyDrive/McCain_twts_2008_classified_senti+poli.csv')\n",
    "df_obm_twt_clean.to_csv('/content/drive/MyDrive/Obama_twts_2008_classified_senti+poli.csv')\n",
    "\n",
    "'''local GPU\n",
    "df_mcc_twt_clean.to_csv('McCain_twts_2016_classified_senti.csv')\n",
    "df_obm_twt_clean.to_csv('Obama_twts_2016_classified_senti.csv')'''"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6702a253-ae3f-47ad-bbca-111e4841d878",
   "metadata": {
    "id": "6702a253-ae3f-47ad-bbca-111e4841d878"
   },
   "source": [
    "## Plot time series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cbce235f-cd95-48e8-9fb7-daf51bcb76ce",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "cbce235f-cd95-48e8-9fb7-daf51bcb76ce",
    "outputId": "0ac7e2a4-c3b5-4a85-d15b-b64130cdc4d3"
   },
   "outputs": [],
   "source": [
    "!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "63a33b53-a17c-4651-8021-b6447ff69f2a",
   "metadata": {
    "id": "a543c925-c584-49b1-9b94-37ea56cd0d48"
   },
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "from datetime import datetime, timedelta\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from scipy import stats\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "183ae744-224c-4a2f-90e5-fcb5f96cc088",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "183ae744-224c-4a2f-90e5-fcb5f96cc088",
    "outputId": "f96226db-5574-4645-b516-3b59a701b2d5"
   },
   "outputs": [],
   "source": [
    "dfMcCain = pd.read_csv('/content/drive/MyDrive/McCain_twts_2008_classified_senti+poli.csv', parse_dates=['time'])\n",
    "dfMcCain.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e141e8c8-ce00-4f4b-83fa-08b45f4b0201",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "e141e8c8-ce00-4f4b-83fa-08b45f4b0201",
    "outputId": "1f272a80-073f-495a-9d5c-cb593cffb93c"
   },
   "outputs": [],
   "source": [
    "dfObama = pd.read_csv('/content/drive/MyDrive/Obama_twts_2008_classified_senti+poli.csv',  parse_dates=['time'])\n",
    "dfObama.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "38b8747b-12d0-4ee4-acd5-a9550efa2e90",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "38b8747b-12d0-4ee4-acd5-a9550efa2e90",
    "outputId": "b76c7d75-9bf1-40b1-fc4d-7ce67f267707"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NEGATIVE    437\n",
       "POSITIVE    276\n",
       "Name: sentiment_label, dtype: int64"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfMcCain['sentiment_label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "d55cffa3-4b95-4ccd-a175-88479fe1d196",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "d55cffa3-4b95-4ccd-a175-88479fe1d196",
    "outputId": "c02d8c95-f87e-4a4d-9a36-3bc93309d6a7"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "POSITIVE    643\n",
       "NEGATIVE    617\n",
       "Name: sentiment_label, dtype: int64"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfObama['sentiment_label'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "7d478cc6-2e83-42ad-a80e-5b3d765696f3",
   "metadata": {
    "id": "7d478cc6-2e83-42ad-a80e-5b3d765696f3"
   },
   "outputs": [],
   "source": [
    "dfObamaSentiDay = dfObama.groupby([dfObama['time'].dt.date, 'sentiment_label', 'political_label'])['sentiment_label'].count().reset_index(name='counts')\n",
    "dfMcCainSentiDay = dfMcCain.groupby([dfMcCain['time'].dt.date, 'sentiment_label', 'political_label'])['sentiment_label'].count().reset_index(name='counts')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "89fcd098-de38-423c-852f-2caf3abc8fa2",
   "metadata": {
    "id": "89fcd098-de38-423c-852f-2caf3abc8fa2"
   },
   "outputs": [],
   "source": [
    "# colors\n",
    "repgreen = \"#00AA00\"\n",
    "repred = \"#FF0000\"\n",
    "demblue = \"#0015BC\"\n",
    "demorange = \"#ff9747\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "93a97e50-6a1c-49d2-ad1a-14be441c94ad",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 225
    },
    "id": "93a97e50-6a1c-49d2-ad1a-14be441c94ad",
    "outputId": "cadf89a2-56f1-4b9c-9c7e-fa18519330bb"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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DYcwY8PS8vozVCuvWwYgRpCxdSvCdd2pFWIAIIShXrhxRUVHOFkWj0WicSkpKija2CoGi0jMOGVxCiPZAhJTyuBCiMjAbsAHPSinPFaaAGo1GU+ScPw/du4OHB3z4Ifj7Z13ObIYOHaBFC7BaEQcPQkgIuOi2rIJCf1xoNBqNQr8PC4eiuK6OBs14B7Aa628AriiD64PCEEqj0WicRkSEMqDq1YNp07I3tuzx8gI/P3B3h4MHISOj0MXUaDQajUZTMnC0GTZQSnlSCOECdAaqA2nAmUKTTKPRaIqaEyegbVvo2RMeeCDv+wcEQFQUHDmierpMOhCsRqPRaDSlHUe/BuKEEBWBtsB+KWWCka7DRmk0mluDS5fg3nuVK2F+jC0AIZTRBXDq1E2LtHPnTtasWXN1+7vvvmP27Nk3XW9OrF27lo0bN+ZYZvr06bz++us5lhk6dChfffWVw8eNiIigfv36DpfXaDQazc2j9UzR4KjBtQDYBiwB3jbS7gIOFIZQGo1GU6SkpipDq1kz6N375uoSAipVgthYZcTdBJkVYffu3XnmmWduTr5ccEQRajQajebWQOuZosEhg0tKOQe4F7hLSrncSD4NjCgswTQajabIeOopFQBj5MiCqc9sJtHHh/t79KDh7bdTv359VqxYwT///EPbtm1p2rQpnTt35uzZswC0a9eOp59+mubNmxMSEsL69etJS0vjxRdfZMWKFTRq1IgVK1awePFinnjiCUC17I0ZM4aWLVtSs2ZN1q5dy/DhwwkNDWXo0KFXRfnll19o1aoVTZo04cEHHyQhQTkoBAcHM23aNJo0aUKDBg04cOAAERERvPfee8ydO5dGjRqxfv36XE/1ww8/5I477qBhw4b07t2bpKSkq3m//fYbzZo1IyQkhO+//x4Aq9XK5MmTueOOO7j99tt5//33C+aaazQaTSkjMTGR+++/n4YNG2o9U8z1jEMGlxBitZTykJTy6JU0KeUh4OVCk0yj0WiKgk8/hZ9/hilTro65ikqNYmfMTtZHrWdXzC4upeW9p+qnDRuoEhjIrq+/Zu/evXTp0oUnn3ySr776in/++Yfhw4fz/PPPXy2fkZHB1q1beeutt3jppZdwc3Pj5Zdfpl+/fuzcuZN+/frdcIzLly+zadMm5s6dS/fu3Rk/fjz79u1jz5497Ny5k4sXLzJz5kx+++03duzYQbNmzXjzzTev7l++fHl27NjBmDFjeP311wkODmb06NGMHz+enTt30qZNm1zPs1evXmzbto1du3YRGhrKokWLruZFRESwdetWfvjhB0aPHk1KSgqLFi3Cz8+Pbdu2sW3bNj788EOOHz+e5+ur0Wg0pZ2ffvqJKlWqsGvXLq1nirmecTRoRvts0ts5eiAhRBdgHmAGPpJSzs6UfzfwFnA70F9K+ZVd3hBgqrE5U0r5qZHeFFgMeAJrgLFSSumoTBqNppQTHg4TJsDrrxPrmsF3EZ/z0/mfiE2PpbJHZSxmC4nWRM6lnKOie0X+U/k/dK3cFXeze65VN6hXj4nPP8/Tr7xC1wcfxD8oiL1799KxY0dAtcBVrlz5avlevXoB0LRpUyIiIhwSv1u3bgghaNCgARUrVqRBgwYAhIWFERERQWRkJPv37+euu+4CIC0tjVatWmV5zG+++cahY2Zm7969TJ06lZiYGBISEujcufPVvL59+2IymahduzY1a9bkwIED/PLLL+zevfuq331sbCyHDx8mJCQkX8fXaDSa0kqDBg2YOHEiTz/9NF27dsXf31/rmWKqZ3I0uIQQV3qw3OzWr1ATOOHIQYQQZtTYr45AJLBNCPGdlHK/XbGTwFBgUqZ9ywLTgGaABP4x9r0MvAuMBLagDK4uwI+OyKTRaEo5qanQrx/WoYNZad7Mkq1LaODbgL5V+1LNsxomcc0BwCqtHEs4xrqodSw5uYQJtSfQOqB1jtWH1K7Njr/+Ys3//sfUF1+kQ9euhIWFsWnTpizLu7srI85sNpPhYFj5K/uYTKar61e2MzIyMJvNdOzYkWXLlhXYMTMzdOhQvv32Wxo2bMjixYtZu3bt1bzMc5sIIZBSsmDBgusUJuCw8tdoNBqNIiQkhB07drBmzRqmTp1Khw4dtJ4ppnomN5fCasZisluvBlQFTgEPOnic5sARKeUxKWUasBzoYV9AShkhpdyNmt/Lns7Ar1LKS4aR9SvQxZiA2VdKudno1foM6OmgPBqNprTz3HMk+3gwquJq1ketZ2ytsfSr1o/qlurXGVsAZmGmtk9thgcP5+Ggh5l/ZD7/PfBf0m3p2VZ/5uxZLBYLDw8ZwuRHHmHL+vVERUVdVYTp6ens27cvRxF9fHyIj4/P9ym2bNmSDRs2cOTIEUD5+x86dKhAjxkfH0/lypVJT09nyZIl1+V9+eWX2Gw2jh49yrFjx6hTpw6dO3fm3XffJT1dXbtDhw6RmJiYxzPTaDQazZkzZ5SeefhhJk+ezJYtW7SeKaZ6JsceLinlMAAhxEYp5Yc3cZxAlIF2hUigxU3sG2gskVmkazQaTc5s2EDa4kWMGmWluX8nWpdr7fBM8zW9ajIxZCJLTy5l8u7JzKw/E28X7xvK7dm3j8kvvIDJZMLVbObdSZNwCQnhqYkTiY2NJSMjg3HjxhEWFpbtsdq3b8/s2bNp1KgRzz77bJ5PMyAggMWLFzNgwABSU1MBmDlzZo5uFd26daNPnz6sXr2aBQsW5OpfP2PGDFq0aEFAQAAtWrS4TokGBQXRvHlz4uLieO+99/Dw8OCRRx4hIiKCJk2aIKUkICCAb7/9Ns/nptFoNKWdPXv2MHnyZKVnXF159913cXFx4amnntJ6ppjpGeHokCchRF1Uj1ZFKeUTQog6gLvRK5Xbvn2ALlLKR4ztQUALKeUTWZRdDHx/ZQyXEGIS4CGlnGlsvwAkA2uB2VLKe430NsDTUsquWdQ5ChgFEBQU1PTECYc8ITUaza1IUhLxdYNZ2DqBOv95hJpeNfNVjVVaWXV6FdFp0bzZ6E0iylYitFat7Hc4fx7c3CAoKJ+Cl17Cw8MJDQ3NnOyYhVxEaD2j0WgKk2zeg5oCorD1jKNRCh8E1qN6kAYbyT7Am9nudD2nUa6IV6hqpN3MvqeN9VzrlFJ+IKVsJqVsFnBlUlKNRlMq2fvkA/xTLpbG3Z7Kt7EFys2wd2BvyriV4dk9zyLJpfGqXDmIjlZjxzS3HFrPaDQajSY7HJ34+GXgXinlaMBqpO0CGjq4/zagthCihhDCDegPfOfgvj8DnYQQ/kIIf6AT8LOU8iwQJ4RoKZQv0GBgtYN1ajSaUsjP/5tJlS9/xTZmNJU8Kt10fUII+gT2QUpJXHo8OXoMuLiAnx+cO3fTxy0qZs2aRaNGja5bZs2a5WyxNBqNRnOLUFr0jEMuhUKIaKC8lFIKIS5JKcsKIVyAM1LKCg4dSIj/oMK+m4GPpZSzjMiH26WU3wkh7gBWAf5ACnBOShlm7DsceM6oapaU8hMjvRnXwsL/CDyZW1j4Zs2aye3btzsiskajuYX4I/JnKt91P2lduyDvvbdA606xppBetSn1a9fB380/+4IZGRARAWFhyr1Q4xAlwaXQHq1nNBpNQaNdCguXwtYzjs7D9Q8wCBUJ8Ar9ga2OHkhKuQYVut0+7UW79W1c7yJoX+5j4OMs0rcD9R2VQaPRlE72xu5l/XMPMMo/kPP33FPg9XuYPXBz8eZi6kU8zZ54mD2yLujiAr6+qpdLj+XSaDSaG5ESbOnqv9kNHAxopNEUZxw1uJ4CfhFCjAC8hBA/AyEo9z6NRqMptkSnRjP66y78sloSMXtQoSlvszBRxq0MZ1POZhla/iply6persqVwdW1UGTRaDSaEoE1Hc7th8gdcOEQxEZC0mXUtKtC/ffwgzJVIaA2VLkdqjQE12watTSaYopDBpeU8oARpbAr8D0qTPv3UsqEwhROo9FoboYMWwYPbuzDwg+sxHS7h7RK5Qv1eF5mL1KsKVxMvUgFj2y8rV1cwNsboqKgSpVClUej0WiKHVLCuX0Q/jNEbASvACh/mzKm6nQED18wG41R1nRIjYf4C8oY2/4FXH4VAhtB3U4Q1BzMjvYdaDTOw+GnVEqZJITYBJyUUm4uRJk0Go2mQHhh3wvcsS6SOmcFhya0K5JjlnEtw/mU8/i4+uDZoClERua+k6NUqwYnT+ZYxGw206BBAzIyMggNDeXTTz/FYrEQGRnJ448/zv79+7HZbHTt2pXXXnsNNzc3kpKSGDlyJLt370ZKSZkyZfjpp5/w9vbG29ubTZs2MWjQIABOnjyJn58ffn5+lC9fno8++oiuXbuydetWqlWrxvHjx/H19b0qT8+ePRkwYADJyclMnjyZwMBr0yUuXbqUevXqFdz10Wg0xRebFY7+Bf+ugPRkqNYM7h4Lnn7Z72N2BUtZtVSsq9LSkpTBtv0L+GsB1O8KYd2UoVYKCWr8N6dOF1z022qB7pz8t3WOZbSeyTsOGVxCiCBgGdAI1c/rnXluLY1GoylO/HD2B1aGf8ze9zM4/dgApGvRtIKahRk/Nz/OpZyjRmQk/PBD1gUvXlTjucqUcbzy9u1zLeLp6cnOnTsBGDhwIO+99x7jx4+nV69ejBkzhtWrV2O1Whk1ahTPP/88r732GvPmzaNixYrs2bMHgIMHD+Jq5+7YoEGDq3UOHTqUrl270qdPHwAiIiIAsFgsdO7cmVWrVjFkyBAAYmNj+fvvv1m6dCkrV66kX79+LFy40PHz1Wg0JR+bFY6sg22fgrs31GoPFUIgO7fr3HCzQNAdaok7C8c3wq5voE4naPygMs5KEadOp/LnqiYFVl/7B3bkWkbrmbzj6NP+PvADau6tdCPtV6BjYQil0Wg0N0NkUiRDtw7ly5/DSAq9jYT6OUxIXAh4mb0w5fZ69faGy5eVe00h0aZNG44cOcIff/yBh4cHw4YNA1Tr5Ny5c/n4449JSkri7Nmz17UI1qlTB3d39zwfb8CAASxfvvzq9qpVq+jcuTMWi+XmT0aj0ZQ8Tv0DXz4GO7+E+j2g1SjVU5VfYyszvpWhYW/VU5Z4EZaPhI3vQ3JswdSvyRWtZxzD0Se+OTBbSmlD9XAhpYwFcugH1mg0mqInw5ZBv839eCz5bhp8s52zg7o5RY4yrqrnymqzZl3A3V0ZW0lJhXL8jIwMfvzxRxo0aMC+ffto2rTpdfm+vr4EBQVx5MgRhg8fzpw5c2jVqhVTp07l8OHD+Tpm586d2bFjB9HR0QAsX76cAQMGXM1fsWLFdXOtJCcn5/8ENRpN8eXySfj+OVj3Ftx2N9z5qBqnVVh4+kFYV2V4xZ2HZSNg2+fK/VBTaGg94ziOGlzngeuaiIUQ9YCcBxNoNBpNETMrfBbp1jQmvHGAc/06k1HGxylyuJqUq0RMekzWBYS41stVgCQnJ9OoUSOaNWtGUFAQI0aMyHWfRo0acezYMSZPnsylS5e44447CA8Pz/Ox3dzc6N69O1999RUXL17k33//pXPnzlfz+/Xrx86dO68unp6eeT6GRlPopCZC9HE4vQsiNsGxv9USsRlO74SowxB3DtJTnC1p8SMlHta/Dd9OAL8q0HYcVK5fdKHdPf2gQQ9o/RicPwBLh8KuryGj4MY4abSeyQ+ODmp4HfheCPEq4CKEGICaiHh2oUmm0Wg0eWRT9CYWHlnImqP9cIn7nuh7WzlbJFKsKaTZ0nEzZREC3mKB2FhISyuwiZDtfeuvUK9ePb766qvr0uLi4jh58iS1aqm2NG9vb3r16kWvXr0wmUysWbMmX5NsDhgwgBkzZiClpEePHtf56Gs0xQ5pgwsHIfJfOLNbGVoZKWDxBzcfcHEHk9E2bbOCNU0ZWmmJkBJ3LaiDV3nwqQA+lcCn4rXFqxyYzM49x6LAmg77vod/likDq+0EcPdynjxe5aBxX2UYH/pVGV2N+0O9LmpuL81NofVM3nE0LPzHQoho4FFUSPjBwAtSym8LUziNRqNxlLj0OAZsHsDTASNpOOIdjj8zAswFNE7gJvB0sRCbFkOAR8CNmSaTMrpiYqBCNmHkC4B77rmHZ555hs8++4zBgwdjtVqZOHEiQ4cOxWKxsGHDBurVq4e/v9EHJqMAACAASURBVD9paWns37+fdu3a5etY7dq1Y/Dgwbz99tvMnz+/YE9Eoyko4i8oA+HQb+DiBgEhan6n0PvUvE+O9MhIqaLtpcRBcgykxELsaTi/X80llXQJUhOUQeZdAXwr2hlkFVSad8C1EOglEWmDo+thy8fqPFuNUOdYXPCtBM0GQUwkHPoddiyDRn3UfXYr3mN+Shpaz+RMXsLCrwZWF6IsGo1Gk2+e/PdJbve7nYfe2U1sy4Yk31bN2SJhCwyk7AMPF1yF1fJ3TkIIVq1axWOPPcaMGTOw2Wz85z//4ZVXXgHg6NGjjBkzBiklNpuN+++/n969e+frWCaTiT59+rBy5Uratm17Xd6KFSv4+++/r26/88473Hnnnfk6jkaTL+LPq7E9EZugamO4Y4j6KM8PQqiPdjdL9nVYM5QxlnxZGWFxZ1WPWnKM2k6JAXcfZXh5V1T1+Nj996moetmKGzarig64/XNAQP3uUL5ogxPliTJVofkQZRAfXa964urcC/XuB38n6AprujLGrWnKcHdxUxEc89H7Vi3Q3aHIgnmpLz9oPZMzQjoQIUsI8S+wFlgHrJNSFuyggyKkWbNmcvv27c4WQ6PRFCBfR37NhF0TWG4bS9PhMzgwdwo2r6L12xZBrahdMzjLvERrIkkZSQRZghBZtZxHRqoernLlClfIEkp4eHhWbidFNCgk72g9UwyxpsG/K2H3KghuCTXbgGsxGNshbdd6yJIuGz1lMZBkGGmJ0epD3LcS+AVCmWrG/0D1v6iNsdRE1Su451t17FrtoELdQh2jJaUk8ryN0xdsxCdJ3FwEFcsJagSacXfL53GTLsPJrSqKok9FCOkAwXeqnseCIi0RLp1QAUQun4SYU8rgT7wI6ang5mkYWMJwVU0CVy9lAAbUhqpN1GTQrh5Atu9BTQFR2HrG0R6uiUBbYBywVAhxhGvG11c57qnRaDSFyNnks4z+ZzQzQl7k9gfe5Mzg7kVubOWGxWwhPj2eRGsi3i7eNxbw84MLF7TBpdEUBpdOwK+zVE9SmyfV+KzigjCBZxm1lA2+MV/aVIjzpEvK+Io+royExChIuKjc+PyrgX8wlK0O/kFq260Ax09lpKpgIYf/VEZKQG0V4r1scKEZWonJkm//TGXFz6n8vTMDFzNUKGvCy1OQni6JjpWcv2QjtIaZji1d6dfJgyah5qwbtLLC4g91O0PIvSoIysntaiJlzzLKtbRSKJStoQJ/5GSYWzOUARV/HuLOwKWTcNkwslLilKHsXUGN8QuoA8Gt1DFcLTdeO2lTvV7x55QL5LbPVJ3Bd8LtPfN/MTXFAkfHcP0B/AEghCgHTACeAB4DSsFoUE2xwWZTE8ZmZKixL34O+tprbkmklAzZNoSulbvScdleMrwtxNzVyNli3YBA4Ovqy8XUi3iZvW78KPD2hqgoFSK+mM8lotGUKA7+Dhvfg9AuULVpydMXwqSMA4v/jWHVbVZliMVfgIQLcHSdWo8/rwyuMlWvLb6VVe+NV3nw8M1+HixrmjLkLp+Ei0fg7F4V7a9MIFSqD+0mqh63QuJynI3/Lk7mg29SCA0207qJC4O6uhPgf6O8aemS8ONWtu2z0nNCHD4WwbiBngzu6o6Hu4P32WRW84JVrKsMnpjTcOm4em7izykj1+yqztnVU103mxWsqco4Sk8Gd18jcIoRPKVyA2XIWfzzNt+YMKl74+GrxhTW7qCMtsgd8MNUaPCUMn6Lo4upJlccMriEEPcBd6N6uaoBm4BnUb1cDiGE6ALMQxloH0kpZ2fKdwc+A5oC0UA/KWWEEGIgMNmu6O1AEynlTiHEWqAycCXIficp5QVHZdKUAKSEzZth2TJYuxYOHlQfpK6u6uPUxQXq14fOnaFXLwgLc7bEmiLk7SNvcyb5DNPcHiZo/uMcfnVssf2g8jR7Ep8RT2JGIt6umT5YhABfX2V0Va/uHAE1mlsJaYMti+Hw79DykfyP0yrOmMzG2K8AwE73SZtyTUyIUr0v58Lh+Cblopgcq1zX3Czg4mG4tEk1pig9SX3Qe5ZRvTI+FVVvT/0ehR5gwmaTvPtlCtPeTeLOhi7Mn+JFYIWcjRU3V0HDEBcahrgwoqcbOw5Y+fz7FKa9m8hzIzx5tI8nbq550AfCZPQW2o3pklLN5ZWeBBlpgE2VM7spA8zVs3CjUHr4KrfNGq0h2qp6vtx9wLt8wU0erSkSHHUp/AE4CrwKfCalzMjLQYQQZuBtoCMQCWwTQnwnpdxvV2wEcFlKWUsI0R+YgzK6lgBLjHoaAN9KKe1jUQ6UUmpn+VsNmw2+/hpefBFSUqBDB3j0Uahd+1r4bClVdLdDh+Cff+Dtt6FqVZg8Gfr0AbPufL2VCY8LZ9r+acy7/S3qPfwmFx7oQFql8s4WK1sEAh8XHy6mXcTLJYteLj8/OHFCPcP62dVo8o/NCmvnqh6aux53bnhyZyBMqsfFUhaoc2O+zap6ZqxpytASJrW4eKhxRUX8IX/8tJVBU+OJT5T8d5yFmlXz/v4TQtA01IWmoS4cOmHlk9WpvLU0hbcmedGt7U30CAmhnh9nP0NmF9XA7FNRGdOXToJfZd3bVYJw9FfVBvgYeBA4KYT4RQjxvBCijYP7NweOSCmPSSnTgOVAj0xlegCfGutfAfeIG51xBxj7am5lwsPhzjth+nQYNgw+/hgGDVK9V/ZzFQkB/v7QogU89hgsWaJ6uV59FerWhe+/V0aZ5pYjzZZG/839GRY8jGbf7cXtQjRR99/tbLFyxdPsiU3aSLQm3pjp6gqengU+EbJGU6qwWeG3V1WAghYjnP+hXBwxmZWLnKWs+oD3DlDzVrl7Fbmx9b91qdwxMIbba7vw5qT8GVuZCalu5tWnLDza24Mn5yRy/5OxnDhjLQBpiwFXjGl3b9XblRLvbIk0DuLQL0tKuUFK+aqU8j6gEbANmIKKXOgIgaj5u64QaaRlWcboQYsFMo8g7wcsy5T2iRBipxDihSwMNE1JQkp45x1o3VoZXAsWQPPm17mIJVuTOZJwhL2xezkUf4iYtJhr+5vNar+5c+GRR+Cpp+C+++DkSSecjKYweW7Pc/i6+vIALbjtpfeIHNOvRPQKXRnLFZ0aTZYRYq+4FWo0mrwjbfDH68qVrtkgFWpbUyyRUjLjg0RGzUjgpTGe9O3khtlUsJ9wzeu78MELXlQpb6LxgBjeWpKE1XqLNMK6WdR4sYQoNY5PU+xxdAzXA0A71BiuEOAfYCF5GMN1swghWgBJUsq9dskDpZSnhRA+wNfAINQ4sMz7jgJGAQQFBRWFuJq8kpamjKTNm2H+fAi8Zo+fSz7Hj+d+ZG3UWs4mn6WCRwXcTe6ky3SiU6OxuFho6t+UThU70ahMI0zCpHq9mjaFFSugcWP4739h+PBiO75H4zi/n/+dz098zvuN36PO8P9ysWMrkmtkbr8pHtRZ35TI1NN533Fv1snVPKtxsmvODQhCCCZMmMAbb7wBwOuvv05CQgLTp09n+vTpfPjhhwQEXJuEee3atZQpU4atW7cyZcoUTp8+jY+PD5UrV2b27Nk0aNDgatlGjRpRt25dli9fzieffMK8efMA2L9/P3Xq1MFsNtOlSxfq1q3L9u3befDBB3nmmWfYtGnT1ToyMjIIDAzk33//5bnnnmPdunX4+fkBYLFY2LhxY96vVzFA65liwIb3VbCH5kNL9mTCtzjp6ZIRLyXwT3gGC5/xolyZwutVc3MVDLzfnbubujD3ixSW/ZTGpy97U7eGw9PQFl/Mrqp3csUoNT6voPAOgIc/z7GI1jN5x9EnbizKuJoAbJJSJudSPjOnUcE2rlDVSMuqTKQQwgXwQwXPuEJ/MvVuSSlPG//jhRBLUa6LNxhcUsoPgA9AzY+SR9k1hU18PPToAVarMrY81JwTl9Iu8dGxj/jr4l809W9Kzyo9CbIEYRbXejKklFxIu0B4XDhzD83FJm0MCh5ExwodMbu4wMCBqtfr1Vfhhx/gk0/UWBlNiSQqNYqHtz7M5JDJ1Fm9FcvRUxwemb+JE4uCyNTT/Njk6xvSk63JpMt0KrhnMedLbIzy169wY177de1zPaa7uzvffPMNzz77LOXL3zimbfz48UyaNOm6tPPnz9O3b1+WLl16dYLIv//+m6NHj15VhOHh4VitVtavX09iYiLDhg1j2LBhAAQHB/Pnn39ePd7ixYsBaNOmDZGRkZw4cYLqRjCQ3377jbCwMKpUqQLAa6+9Rp8+fXI9r+KO1jNOZtc3cHIL3Dla92wVY5KSJb0nxRGfKHljgsXxaII3SbVKZl6fYOG7dencNTSWKUM9mTjIExeXEt4IazIrY6vteNXr5eF783X+7+lci2g9k3ccbVZ4W0o5TUr5h72xJYRwVPptQG0hRA0hhBvKePouU5nvgCHGeh/gD2n43AghTEBf7MZvCSFchBDljXVXoCvZtgtrii1xcXDPPSos9osvXjW2fj//O8O2DiPFlsKzdZ7lgSoPUMOrxnXGFqhWloruFWkX0I4JtSfQo0oPvo78muHbh/Pv5X9VoRo1YOFC5bLYpAns3l3UZ6kpAGzSxqAtg+gQ0IG7koOo9cLbnHq8P9K15LVUepg9Sbelk2ZLuzHTy0v9LqQtX3W7uLgwatQo5s6d6/A+CxcuZMiQIVeVIEDr1q3p2fPa3C/Lli1j0KBBdOrUidWrVztUr8lkom/fvixffm3o7fLlyxkwYIDDsmk0uXJiC+xcCXcMLR6TGWuyJCFJ0uWJWGw2mD7as8iMrSuYTIKe7d1Y+IwXX/+eSvNBMew5nKcYcMUXDz8VTTE1oUgOp/VM3nHU4FqUTfoHjuxsjMl6AvgZCAdWSin3CSFeFkJ0tztGOWNS5QnAM3ZV3A2cklIes0tzB34WQuwGdqJ6yD508Hw0xYHEROjSRbkPjh8PZjMZtgzmHZrHB8c+YESNEXSv3B0vF8cGPQshCPEJ4bGaj9EhoAMzw2cy+8BsEtITVLCNsWNhwABo3x6+0vN1lzTePPQmp5NPMyxoCHWffJWo/7QhuWZVZ4uVLwTgabYQlxF3Y6aLK7i6QEIWgTUc5PHHH2fJkiXExsbekDd37lwaNWpEo0aNaN9e9Zjt27ePJk2a5FjnihUr6N+/PwMGDGDZssxDabNnwIABVxVhamoqa9asoXfva72SkydPvirPwIEDHa5XowFUcIw/XocmDxWvCY011xGfaKPzY7H4egmmDPNwas9S5QATc8ZauKe5G20fieX5hYmkpJbwTmmTMYdXSpyKQFkEaD2TN3JsGhZC1DRWTUKIGqjvhCvUBFIcPZCUcg2wJlPai3brKagoiFntuxZomSktETVnl6YkkpEBvXtDmTLw5JMgBCnWFKbunUqyNZlxtcfhac5fS6UQgoZlGhLiE8IPZ39g2PZhTA2dSsMyDeHeeyEoSAXU2LNHRULU47qKPRsvbmT2gdksbLyQ4A++wfVyHCfGPexssW4KT7MH0WnRpMt0XEWm8SYWL+Va6OOTr7p9fX0ZPHgw8+fPx9Pz+t9RVq4emWnRogVxcXF06tSJefPmsX37dsqXL09QUBCBgYEMHz6cS5cuUbZs2VxladasGQkJCRw8eJDw8HBatGhx3X7FwdVDU0JJT4Yfp0PdTlBWz19XXElKltz3RBxlfQXjH/bAVMDBMfKDEIL727jSvL6Zt1ekUP/By7z7nDcdW5Zgd1STGTx9IekyeJuNOdYKD61n8kZuPVxHgMOABTUP1xG75TNgemEKp7lFkRLGjIHYWJgwAUwmkjKSmLxrMiZMDA8enm9jyx5Psyd9qvahZ5WeTNs3jcXHF2OTNggJUS6GX3+terxSHG430DiBqNQo+m3ux8SQidQ6HE/1eUs5+eRDJSIqYU4IhJoMOT0LFxCLJySnQEZ6vusfN24cixYtIjEx956ysLAwduzYcXV7y5YtzJgx42rL5bJlyzhw4ADBwcHcdtttxMXF8fXXN45Ny44rrY/F0c1DU0KREtbNB78qENTc2dJosiElVdJ1bBw+luJjbNkT4G9i+mgLw3u4M2xaAj3Hx3H0VAkOIW9yVeH9Ey/l2y09L2g94zg5GlxSSpOU0gysN9btlyrGIGGNJm/Mnw/r1sELL4CLC2nWNJ7b+xzert70r9b/hnFaN0uYbxjja4/n7+i/mbxrMrFpsVC2LLzxBly4oMaQXdJhVYsjGbYM+mzsQ7uAdrR2u52w4dM4PbwnaRUzzxhRMvE0e5JkTcSaWTEKE1gsqlEin5QtW5a+ffuyaFF2HuHXePzxx1m8ePF1kZuSkpIAsNlsrFy5kj179hAREUFERASrV6/Os7vHF198wR9//EGPHpmnYNRo8sHBX+HCAQjrnntZjVNIT5c8OCUOAUwaUvyMLXvubOjKomleBPgLmg2M4YnZCZyPLnyDpVBw8VCBYxKjcy97k2g94zgOjTaXUrYtbEE0pYTff4eZM5XRZbFgkzZm7J+BQNAnsI8K6V4I+Ln6MabmGH449wOj/hnFzPozqe1TG6ZOhQ8/hJYt4eefVYANTbFh8u7JpNnSGFp9CHVGziAhrCYxrXP2AS9OVHUP5L4dBRdFsZpntdwL2TFx4kQWLlx4XdrcuXP54osvrm5/++23BAcHs2LFCp5++mlOnz5NhQoVKF++PC+++CLr168nMDDwarQngLvvvpv9+/dz9uxZKleunKscoaGheHl50bRpU7y8rh+TOXnyZGbOnHl1e+vWrbi5lWC3Hk3hE3sGNn0ILR/REQmLKTabZMiL8VyKlUwf7Vngc2wVBu5ugoH/cee+1q4s/zGNOj0vM+h+dyYN9qR6lWLsUeFVHn58MfdyjuIdkHsZO7SecQyR5eSbtzDNmjWT27dvd7YYpZPTp1WUwKefVv+BD45+wNbLW3m05qM3jmMpJP6N+ZdVp1fxZK0n6Vipo0pctQpWrlSh43MZ1KkpGj4+/jEv7XuJBY0XUG/Rz1T+/H8cmfkk0q14zq8jglpRu2ZwnvdLt6UTlRZFTa+a1zc4SAknTkD16mpC5FJMeHg4oaGhmZOL7Rec1jOFiM0Kq8ZBxVCocZezpdFkgZSSx19NYPOeDF590oK7W7H9qeZIdIyNr39P48cN6bRp7MLoPp50auXqtIAf4ZcgtE5tx3ewWSHhgnK71dE7c6Ww9UzhzTan0diTng4PPgjdu181aH499yu/XviVodWHFpmxBdC4TGNG1xzNh8c/ZP7h+WTYMuCBB+Cxx6BTJ9XTpXEqf0X9xeTdk5lRfwZBW44SNG8JEZOGFltj62ZwNbniKlyJS88UsVAINWfcxYvOEUyjKY78uxyEGYLvzL2sxim88E4Sf2zL4OUxJdfYAihXxsSo3h4sfcWbWkFmnpmfSJVOl3h0Rjw/b0wjOaWYd1iYzOBZBuLOga2EukfeQmRrcAkhGhalIJpbnBdfVC32xkDG4wnHWXBkAcOqD8PbxbvIxaniWYVxtcZxMP4g43eN51LaJWjTBqZNU5Mlf/JJkcukUYTHhdN7Y2+erfMsIRfM1Bv1Eiefeoj0CrlHKiqp+Lj4cCntMjd4HPj6QkyMiuqp0ZR2Lh6D3d/C7Q/o6LLFlLlfJPHFD6m8+qQn3pZb4x55egi6t3Vj/tNevDnRggSemZ9IQIdo7h4ewwtvJ/L9X2mcuWC98R3ubFw9VbTCxChnS1LqyWkM13rAF0AIcVhKmYd+TI3GjrVrYdEieP/9qxEJp+6dSvcq3aniWSXX3QsLi4uF4cHD+fX8r4zcPpLpYdPVbOdvvAHPPw+nTqnAHlqxFxmRSZF0Wd+FkTVH0tJUh9v7j+F8n44k3B7ibNEcQkqJyMfz4mH2gPRYEq2J1zdAmM1qIuRLl6BChQKUtORQ7D5gNM7BmgF/vAah96lWe02xY9GqZF77NJm5k7zw9701HaiqVjTz0H1mHrrPnYQkyd6jGew7YuPXLUkcjLBiMkFoDTNhNc3Uu82FusFm6gabqVbJdPNBQ0Q+dYynH8RfAPdEcHNsXtPSRlHomZwMrhghRFdgP1A5i3m4AMg0GbFGcz2XL8PDD8OkSeCvJqWce2guQV5BNPNv5mThwCzMdKnUhSBLEFP3TOXBag/yUNBDmObNUwE1IiKUoeh667myFTeiUqPosK4D91e6ny6+banfdxIJt9cmunMJGaeRlkBMXAJlfL3zZXT5uHhzOe3yjT2+fn4QFVUqDS4pJdHR0Xh4eDhbFI2z2fkluHpAVT3Gtjjy5a+pPLsgiTcmWKhY7tY0tjLjbRG0bOBKywZqW0pJdKzkxBkbJ87aWPdPOkvWpHLynJX4RElIdTON67hwR5gLLW93pUEtc57Gg3mYIfpyDOX8y+RNxwgTWMpA/HnwD1aTJGuuUlR6JtugGUKIB4DXgOoo18Os7q40wsaXGPRg5iKmf3/lDvXEEwD8dv43Pjr2EeNDxuNucneycNcTkx7DkpNLsJgtPB/6PBWkj4qo6OEB33yjPnw1hUJUahTt17anqX9ThlcdTNjwFzElpXBy7MASoxykyRVThbrglj8XWQnEpsfi71bmxjGNFy8qg6sURu/z8PCgatWquN7Y6FFsu561nilgLp+Cb8dD6yfA4u9saTSZ+N+6VIZNS2D2WAu1qpWoT8IiIyFJEnHGypFTNo6esrL/uJXoGEnrRi50b+dO97ZuVCqfs65Lt0oiEwUpVpTCyCvpSWr8o4dPvs7hVqYo9IxDUQqFEPFSylviDmlFWIR8+SVMmQLvvgseHpxPOc/I7SMZWWMk1Sx5C29dVFillT+j/uSvqL8YVXMU91fognjnHQgPhx9/hOBgZ4t4y3E+5Tzt17anmX8zhlUbTOhTc7Aci+T4MyOQrg7NXHHL8NuF30i1pvJ8veevz/j8c2VsvfuucwQrnmiDqzQgbfDtRKgQogNlFEN+2pDGwOfjmfW4hbo1tLGVFy7H2fgn3MrWPRls2ZvBHWEujOzlQa8Obri6FsLrLS0J1r0F970EFesWfP23JkUepbAcgBDCJISoLEQhTZakuXU4f15F/ZsyBTw8sEkbsw/Mpk1Am2JrbIFyMby3wr08WvNRvoz8krF7JnB8WFe4915o0QL+/tvZIt5SHE04SqvfW3FnuTsZVm0wdSe8gdfhkxyfMqzUGVsArcq2YtOlTVxMzRSZsHNnWL4cjEkiNZpSQ/hPkJ4M1Vs6WxJNJq4YWy+N9tTGVj7w9zVxbwtXnnvEkxVzvLmzoQuvfZpM0H2XmPNJEglJBTyuyM2ixkCue0uFjNcUKY4aTu5CiM+AFOA0kCyE+FQIoX2sNDciJYwapT4SjTkNVp9ZTUxaDB0COjhZOMcI9AzkqVpPEeITwthd43iz/gninhoJPXqoiZI1N83Gixu564+7eKDqAwyq0p96j7+Cd/gxjj89HOle+lznALxcvGhapinfRH5zfUaFChAWpnqNNZrSQtJl2PIJNOipxqFoig3f/3XN2Kpfq/Q1jhU0Hu6CDs1deX2ChZlPWPhtSzo17r/EgmVJpKcXoOEV2EhFLdy9quDq1DiEo2+wBYAXUB/wBBoAFmB+IcmlKcmsWAF798LgwQCcSz7Hx8c/pn9Qf8yi5LSCmYWZ1uVaM6XOFBKsCTwk3+LTsY1In/WyMihTU50tYolESsmHxz6k24ZujKs9jh6+91J/yFQ8Tl/g2LMjsHkWr7F9RU3r8q35/uz3JFuTr8/o0gXee885Qmk0zmDje1CtKfhWdrYkGjtW/pLK0Bfjmfm4RRtbhcBtVc08/4gns8daWLImjfoPXubvf9MLpnIhoH4PNZ9dgg4VX5Q4anB1AQZJKQ9JKVOllIeAYUa6RnONqCh46ikVldDNDSklcw7OoX1Aeyq6V3S2dPnC28Wb7pW7MzlkMifLw0MPX2LXtq+4dEcoSUfDnS1eiSIuPY6HtjzEnANzePP2N7nbGkLjnuMAyfHJw0ptz5Y9Ae4B1PSuyU9nf7o+o1UrOHYM9u1zjmAaTVFyeiec2QO173G2JBo7FixL4sk5CcwZZyFUuxEWKrdVNfPqU548dJ87fSbF8dgr8SQlF0Bvl3d55aK74f2br0vjMI4aXClAQKa08oDDTfxCiC5CiINCiCNCiGeyyHcXQqww8rcIIYKN9GAhRLIQYqexvGe3T1MhxB5jn/kiP7GYNQXL44/DPfdcdSVcc3YNl9Iu0TagrZMFu3n8XP3oVrkbkxtPY+sTXfizRhJJjesxfVZj3jz0Jluit9zYK6G5ys/nfibs5zCSrcksbLyQ+odTaNrxURLCanLqsf7gopX3FdqWb8uKUyuwSjs/e7NZ9XK9r5Wk5hbHmgbr5kNYN3DRjTDFAatVMunNBN74PIW3JnlxW1X9vi4KhBC0berKR9O8OXrKRqP+l9lzOOPmK76tLVwIh8gdN1+XxiEc7Qv+CPhVCPEmcAIVKn488IEjOwshzMDbQEcgEtgmhPhOSrnfrtgI4LKUspYQoj8wB+hn5B2VUjbKoup3gZHAFmANqsftRwfPSVPQ/O9/sHkzfKAei+jUaD449gGjao4qUa6EueFmcuOOss1haHPOtDjI+PlL2LJ1AWOGvc9+6wkCPQOp6VWTIEsQlT0qU869HH6ufniaPXE3ueNqcsUkTAjjzx4hBCZMuJpccTO54WH2wGK24OPig6+rLz4uPvma48mZHEs4xoRdE9h+aTvjao+jmX9Tqnz6HTVeXUTkqD7Etrzd2SIWO2p41cDiYmHDxQ3cHXD3tYz77lPBaObMAU9P5wmo0RQmO79W4d8r1XO2JBogLsHGwOfiORNlY94UC37eejxdUeNtETw7wpNfN6XT7pFY5k7yYnC3m5g3ysUNQu+H9W9D3/fBrF1DCxtHr/As4AzwEFDFWP8v8LGD+zcHjlyZJFkIsRzogZpU+Qo9gOnG+lfAwpx6rIQQlQFfKeVmY/szoCfa4HIOWLA9DQAAIABJREFUcXEwejRMnKjmrQLeOvwWLcq2INAz0MnCFR620DqceOM5mn68ig1jT7F3/qvsC/XnbMpZolKjiEyO5GDCQZIykkizpZEhM8iQGdikLev6pA2JJENmkG5LJ82WRqotlaSMJBIyEki1peLn6keAewAVPSoS6BlIkGcQ1b2qE+wVTE2vmgR7BeNmcn6r8JGEI8wOn83Xp7+md2BvFjVbhHdMCiHDp+F18DhHZj5BapXSN5mvo9xd/m6WnlxKm/JtrhnZlSqp3uOVK2HIEOcKqNEUBnHnYPfX0PpxZ0uiAfYeyaDnhDjq3+bC7LEWXPMwUa+m4OnYypVaQSamvp3E7sMZzBnrhdmcz3tSqR6c3Ap7v4OGvQpWUM0NOGRwSTVZ18c4bmBlJhA4ZbcdCbTIroyUMkMIEYsRjh6oIYT4F4gDpkop1xvlIzPVmeWXvRBiFDAKICgoKJ+noMmRKVOgSRO1ABsubuBQ/CEmhkx0smCFj83iwaknBuC3eTcNR7xM5R7tOP78SKzlLAV+rAxbBnEZcVxOu8yltEtcTLvI+dTz/L+9+46Tqjr/OP55ZrYXFtilSZMqoIhK06jYBRU7CrHGEitRY+zRiJqosddYokZjYu+xx58NY4Wg0qRKX+rC9jYzz++PO8hmpSyws2d3zvN+vea1OzN395zvzO49c+4995zpJdNZWb2SZZXLWFG9gg7pHeid05t+uf3o36o/O+XuxE65O9E1qyuhBM72VRmt5M1lb/L4j4/zddHXjO40mieHPkleah4Fb39GnyvvpnivQcz500Vo2s8WGDR1DMwbyNvL32ZayTQG5g3c8MQRR8ADD1iHq5mxdqaR/Och6LE3ZLV1XROvqSp/eaGK6/5SwbnHZzDyF7a/bi56dA5z/1VZ3PRoJcf9rpTnbs0lM2MbOl0iMOAI+OIR6HOALSqeYA1a+Hi7CxEZA4xS1bPj908Fhqvq+DrbTItvsyR+fx5Bp6wUyFHVNSIyGHgN2BnoC9yqqgfHt98XuFJVR2+uLrYgZQJ89hkcfzw89hjk5lIeKef0r09nbJex9Mnt47p2TSpcWk6np98kd9pc5t50IauO3C/YqTWhSCzCiuoVLKlYwuLKxSytXMqSyiUsqlhESW0JvXJ60TenL/1a9aNPTh965vSkR3YPdsjYgZTQ1g0rqIhUMK1kGp+v/px/r/g3n67+lAGtBnBAuwPYv93+ZIQzyFhYSO9r7yd75o8sOWcM5Tv3SlDy5POfNf9hScUSbtn1lg0PRqNw6qnw5ps/HeDwVLM91G7tzDZa+FUwxGnExTbEyaH5S6Kcc1MZy1bFuOrMDLp1TJ5LApJJbUS5/akqyiqUtx9oRevcbTyYOuMtSEmHA5L/APk2aLR2pqn2aEuBuqvddok/trFtlohICpAHrImfXasGUNXJ8Y5Y3/j2XbbwO02iVVfDmWcGk2Xk5gLw2PzH6JPTx7vOFkA0N5slF4wle/o8etz8GJ2feJW5N42nbGDTvRYpoRQ6Z3amc2Znhtc7kVwRqWBx5WKWVC5haeVSpqybwoqqFSytXMramrUUpBfQPr09BekF5Kflk5uaS2Yok3AoTCQWoTJaSVFNESuqV7C4YjGrq1fTPbs7/XP7s0ebPTin5znkpQbL86UUl9H1/kfZ4e//YtURI1h6x3FeLma8PYa2Gcr7y99nYflCumd3Dx4Mh4OzXA8+CI8/7raCxjSWSDVM/AvsPNo6W46UVyq3P1XBfc9WceIh6Vx1RgYpNoSw2UpNEa46I4OHXqxmxFnF/N/DebRruw2drj4Hwsd3wao50M6/z21NpanOcKUAs4GDCDpF3wAnqer0OttcCAxU1fPik2Ycp6onikg7oEhVoyLSE5gY365IRL4GLmLDpBn3q+rbm6uLHXlsZNdeCxMnwg03ADCzZCZXT72ay/peRk5KjuPKORaNkv/Bl3R46d+sHTGYBVeeSWWP5ns9WyQWoaimiDU1ayiuLaY0UkpltJKaWA0xjRGSEGmhNHJTcmmd2pr2Ge3pmNHxZxOihEvK6Pz4q3R95CWKhwxgxQkjqS1o7ShVy/f+iveJEeOqfnUmdy0qgjPOgAULoI23w0Ca7SdBa2e2wTd/h8JpMPhk1zXxTlW18ugrldzyeCU790rh7GPT6VhgE2O0FKrK316v4ZvpET5+LI8O+dvw3i36Ovj/O/aeJh+V08w17RkuETlBVV/cyONjVPWlLf18/Jqs8cB7QBh4QlWni8iNwCRVfQN4HHhaROYCRcC4+I+PAG4UkVogBpynqkXx5y4AniRYjPkdbMKMpjV1Kjz00E/TVEdiEW774TZGdxptnS2AcJg1I/dm7YjBFLz5KXuMPI81h+zFwt+eQmXv5neNR0oohfYZ7WmfsW0TWaQvW0Xnx16m0z/fpmT3fsy94QKqu7TMtdeak73z9+aWWbewqmoV7TLiq3O0bRusy/XYY3D55W4raMz2Kl4WXLi/729c18QrC5dF+esrVTzychX9eoSZcF4WO+1owwdbGhHhzGPSCYdh/7OL+eTxPNpv7ZmurkNg4dcw9+Pgei7T6Bp0hktESlS11UYeL1LVFnVlqx15bCTRKAwfDgccEAxvAp5Z9AwTV03knB7ntLipy5tCuKyC/Hc+o907n1EyeACLzz+Rdfvs3rKPJkWjtP1kMjs8+Tqtv/iOov2GsPqwfajpWOC6ZknljcI3aJvalvF9xm94cOZMuPXWYDHksJcfkprtP461M1tBFd6+FnI6QO/mu15jaXmMuYtjLCyMsnRljBVrYqwpVkrKlMpqpbpWUQ125ylhISMNsjKFVtlC69wQrXOF/DyhoHWIdm1CtG8rdMgPkZbadH/Gqsq8xTHe+qyGF9+vZvr8KAcNS+Wo/VLp1snLfUhSUVWefKOGyTMjfPp4Hm3ztrLTteZH+O5FGPc4pG7HlPPJpWnOcMWH8AGERKRHvYJ7EiyIbHx0771BQ3n44QAsrVzKs4ue5eLeF1tnaxOiOVmsPOFQVh21P20/nkTfy+4EEQpPHc3yEw6ltn0LOXahSu6UH2j/6oe0f+1DIm1aUbT/EJaddiSxTNtJJ8KIghHcMfsOTu1+KnlpwTVy9O8PrVoFk2ccfbTbChqzrRZ8AeuWwK7NZ1rqikrl8+9q+ezbWr6cGmHqnChFxTG6dgzRMT9EfusQedlCTjbs0F5ITw2RkgIhgZgGxyNrI0pVDVRWKfOLo5RXKqUVSnFZcFuzLsbaEiUnS+iYH6JjgdCpIETn9iF2aBemY36IDvlBp6ygdYi2rYTUreicVVYpi5ZHmbMoxoz5Eb6ZFuHz7yPURpRhO6cwap9U/nBuZpN2+ExiiQi/OiqN6hrl0POL+eiveeRmb0WnK78HtO4GU56HYTYLbmPb7BkuEYkBysZ7eMuBCaraoMWPmws78tgI5s2DoUPh/vuhc2dUlUu/u5SumV05sP2BrmvXcqiSPXM+bT6eROuvvqd0t36sOO4g1hz6i2Z3zVOovJLWn39L/r+/oODdz4mlpbJur11Zt/fuVHft6Lp6XnhhyQv0yunFWT3O2vDgBx/Ap58GN/8020+K1s40UG0VPHd20NkqcDt76aLCKK9+VMOrH1YzaUaEPt3CDOiZwk47hujdNUzHfCEUatw/uVhMKSlX1hQra9YpRcUxikqUtSXKulJlbUmMtaXB98WlSkY6tMoWcrKEjDQhPQ3CYUEVolGlqhpKK4Kfq66FDvkhurYP0blDiN5dQ/TvEaZLh5AdFE1yqsrd/6yirALeeaAV6Wlb8X5XroOJ98OYByHXLgmgEduZhg4p/ERVm++5/q1gDeF2Ug2GEQ4YACeeCMC7y9/lmUXPcHHvi382gYJpGKmuIW/SdPK+mkrut7Oo6NudNQfvydp9d6d0t35NvmZVSnEZuVNmkvfF97T5zxRyps2lvG93Sgf1pWTILnZtlgOrq1dz79x7eXbPZzdcIxmJBFPEv/WWj1PEN9tPjdbONNAXj8Ga+bD7WCfFl1UoL7xfzWOvVjHzxyh7D0phz0EpDO6Xsm3rGiWQqlJRFZx9q6hWqmugplaJxoJ/hHAY0lOFzIxgGGN2Jo3eQTQtRzSm/PHRSgrahHj+z7lb97cw+/+gphxGXpe4CrYcTdvhSibWEG6nhx8OFl29914IhymqKeKMr8/g7B5n0zWr65Z/3myR1NSSPWM+rb77gezp88lYuoKyAb0oGdyfsl37Ut6/JxW9uhLLTG+UsjIXFpI5dxHZsxaQM3UuudPmkLayiIreXSnvuyPl/XtS3r8HsYztL89sn2cWP8MurXbhtB1P2/Dg88/DunXw7LPuKuZGs/00ae1MAxQtgNcvgxGXQEZukxa9YFmUe/5ZyVP/qmZg7zCH7pXK8IEppNoU6CaJ1NQqV99XwS8GpXLfldkNP7MZqYFP7oaDroTOgxJbyeavyc9w9QD+BOwG/M/0c6ra/KZb2wxrCLfDwoXBUfQ774QddwRgwvQJhCXMkZ2OdFu3JBYqryRrziKy5i8mY2EhGYtXkLFsJbWtc6nu3J7qTu2oadea2ratibbKJpqZjqakBFdvqxKqriFUWU1KaTmpa9aRumot6cvXkL58NalFxdS0b0tV5/ZUd25PVZeOVPbsQlWX9r5OxNCsrahewYNzH+TZPZ8lOyU7eLCsDE45JZg1tKtXBz2a7adja2e2QGPw2qXQvj/suGeTFTtnYZQJj5Tz9me1HLZ3Kkftn0bHbZlC25gWoqxC+e0d5fz6uAyu+FVWw39w2fcw71M48WEIef1ZoMkXPn4GmAf8DqhorMJNC6IarPtz3HE/dbYmrprIzJKZ/K6vrU6eSLHsTMp224my3Xba8GA0RuqadaStXktqUTEpxWVkLF2J/FhDqLoWiUZ/uvoylpqCpqYSy0wnkpNF9cA+rBsxmNr81tTk51nHqgXpkN6BnXJ34uUlL284y5WTA6NGwR13BGeejWnuZr4XXL/VfViTFLdsZZRrH6zgtY9qOPbANJ7+Yw45Wc22v25Mo8nJEm4en8VFt5XTvVOYsSMbOFKl08Bgba7p/4KBxyS2kp5oaIdrZ2BvVY0lsjKmGXvoIVixAn7/ewBKaku4e87dnNz1ZNJCaY4r56FwiNr2bVvOzIam0RzS4RAemPsAx3U5bsO1XMcfD7/+NVx3HRTYlPymGasogq+egOFngiT27FJVtXLbkxXc/c8qDts7laduyiE32zpaxi/t2oa46cIszr+5jM7tQ+yzewOuCReBnY+EL/4KvfaDrDaJr2iSa+je7lNg90RWxDRj8+bBtdfClVf+dDbknjn3MLDVQHrluJ1ZyhjftE9vT79W/Xhh8QsbHmzXDkaMgPvuc1cxYxpi4oPQbSjk7ZDQYt75rIZ+x67lo0m1PHRNNuccn2GdLeOt3l3DXH1mJsf9roQ5C6MN+6HcDtB1j6DTZbZbQztcC4B3ReRREbmx7i2BdTPNQSQCJ50U3LoFl+tNXDWR6cXTObzT4Y4rZ4yfRrYfyStLX2FtzdoND554Ijz4IBQXu6uYMZuz4AtYNRv6JG75kFVFMU68ooRz/ljGBSdmcP25WXQssOu0jBm6cwqnj85g1IXFrF7bwAFrfQ6CJf+FwmmJrZwHGroXygbeBFKBrvVuJpndcktw/dZxwaKURTVF3DX7LsZ2HUt6yGatM8aF/PR8BrcezNMLn97wYJcuwfp4dh2XaY6qS+GT+4I1t8KJWebixX9Xs/OYtYTD8Nfrshm2S0OvmjDGD0eMSGXPXVM56pISqmsaMEt5SjoMODz4341GEl/BJNagDpeqnrGpW6IraBz68ku45x64/HIIhVBV/vzDnxnSZgg9s3u6rp0xXjuow0G8v+J9CisLNzx4yilBh2vdOncVM2Zj/vMIdOgP+Y3fdqwtiTH2yhKuuKecCedlcu7xGWSk2/BBYzbmrGPSyEiD0/9QSoOWhuq0K6Rnw/cvJ75ySaxBHS4R6bmpW6IraBwpLoZx4+Dii4PrQ4B/LfsXhVWFjOw40nHljDGtUloxomAED89/eMODXbrA8OFw113uKmZMfQu/gqVToP+oRv/VH0+qYeAJ64hG4aFrshnQ085qGbM5oZBw5RmZTJ8b5bq/NGDi8fUTaHz7IpQUbnl7s1ENHVI4F5gT/zq3zv05CaqXcUk1mPFs992DC/GBBeULeOzHxzip60mkiDVoxjQH+7fbn6nFU5lePH3Dg6eeCvffH8wqaoxrVSXw8T2w65hgeFIjqa1Vrr6vnBOvKOU349IZP87OahnTUOlpwo0XZPLkG9U88Vrlln8gOx96jgj+lxtyVsz8TEOHFIZUNRz/GgJ2AB4FTm1oQSIySkRmichcEblqI8+ni8jz8ee/EpEd448fIiKTRWRq/OuBdX7m4/jv/DZ+a9/Q+pjNePhh+PZbOO88AKqj1UyYPoHDOx1Ox4yOjitnjFkvLZTGqA6juG/ufcTWr9rRqRMccghMmOC0bsagCp/cA512gYLGGxCzcFmUfc8q5uNJtTx8bTbDBybmmjBjklmbViFuHp/JlfdW8MGXNVv+gZ77BMs6/PB+4iuXhLZp6h5VXQ5cAtzSkO1FJAw8CBwGDAB+KSID6m12FrBWVXsDdwN/jj++GjhSVQcCpwNP1/u5k1V1t/ht5bbkMXVMnhxMAX/ddZAeHI28Z849FKQXMLzNcMeVM8bUN6TNEGpjtbxT+M6GB08+GZ5/HmbPdlcxY354H4oWQL/GG4b+xsfVDDl5HbvvlMKfxmfStpXNQGjMturWKcx1v85k3FWlfDdrC5NihMLBpDdfPgZlq5qmgklke/ZUOwFZDdx2GDBXVeerag3wHHB0vW2OBp6Kf/8ScJCIiKpOUdVl8cenA5kiYtPjJcKqVXDssXDRRdA1mIDyncJ3+Hbdt5zQ5QREbLiGMc1NSEIcu8Ox/PXHv1JSWxI8mJcXTBN/ySVuK2f8tW5p8MFst7GNMithba1y6R1lnPenMq4/N5OxI9MIhaxNMmZ77do3hQvHZnD4b0pYVLiFNbrydoAd94KP7rKhhVupoZNmTBSRT+vcJgFfAQ29MrszsLjO/SXxxza6japGgGIgv942xwP/VdXqOo/9LT6c8DrZRI9ARM4RkUkiMmnVKuuVb1RtLYwZE1yztd9+AMwqncVD8x7itO6n2RTwxjRjXbO6MjBvII/Me2TDg8cdBzNmwNtvu6uYR6ydqSNSDe/fBH0PhlbbPwx98fIo+5xZzFfTIjz0+2x26W3XERvTmA4YmsqxB6Rx6PnFrFm3hTW6eu8P5athhrUtW6OhZ7geAx6vc7sV2FVVGzSksDGIyM4EwwzPrfPwyfGhhvvGbxu9pkxVH1XVIao6pF18xj1Thyr85jdQUwNnBDP9F9UUce20azm+8/F0yujkuILGmC05vOPhfFH0Bd+u+zZ4IC0Nzj8fxo+Hqiq3lfOAtTN1fPYQZLaG7ts/DP2dz2oYfFIwhPCmCzLJy7EhhMYkwphD0tijfwqHjS+hvHIzZ69CYdjtBPj6SVi7eNPbmf/R0Ekznqp3e0lVt2aGwqX87yLJXeKPbXQbEUkB8oA18ftdgFeB01R1Xp16LY1/LQWeIRi6aLbW/ffDBx/A738P4TA10RqunXotg1sPZlDrQa5rZ4xpgMxwJsfucCx//uHPVEXjHazhw6FbN7jpJreVM/6Y+S4s+S8MPDaYTnobRSLKVfeVc+aE0uAak1E2hNCYRPv1cem0ayMc89stLIyc2wF2OgT+fTNEGzDhhmnwkMJUEblBROaLSFX86w0iktbAcr4B+ohIj/jPjAPeqLfNGwSTYgCMAT5UVRWR1sBbwFWq+p86dUoRkYL19QNGA9MaWB+z3quvwh//GHwgy8khpjFu/uFmMsOZHNrhUNe1M8ZshYF5A+mS2eV/hxaOHw8PPQTff++uYsYPK2cF120NOQVSM7b51yxZEWW/s4NZCP9yTTYD+9gQQmOagohw6SkZRKLKL68qJRLZTKer2zDIyA0WNTdb1NBz87cBBwPnAYPiXw9kw0yCmxW/Jms88B4wE3hBVaeLyI0iclR8s8eBfBGZC1wKrJ86fjzQG/hDvenf04H3ROR74FuCM2R/bWAeA/DZZ3D22UGHq1MnVJWH5j3E4orFjOs2jpDY0A1jWppjdziWT1Z/wjdF3wQPFBTAWWfBaacFw4aNSYSyVfDuDTDwuODo9zZ6e2INe/xyHQN6hLl5fCZtbBZCY5pUOCxcfWYmhatjnHptKdHoJjpdIsGshYu+hjkfNW0lWyDRBswyIiJLgEGquqbOYwXAd6paf/KLZm3IkCE6adIk19Vwb9IkGDUKrroKhgwB4JmFz/BW4Vtc0OsCslOyHVfQGLOtZpfO5rklz/HYkMdom9Y2uE7zuutgn33g1ltdV6+xNNvxZd61M7WV8OpvoePO0GvENv2K6hrlynvLef79aq4+I5Nd+9pZLWNcqq5Rrn2wgn47pvDkjTmEw5vY5ZYUwpePw5G3QkGvpq1k4jVaO9PQQ0ebKrDZNnhmM777Dg4/PJgyOt7ZemnxS7y67FV+3fPX1tkypoXrm9uXYW2GMWH6BKKxaHAk8tJL4fHH4eOPXVfPJJNoDbwzAXI7Qs99t+lXzJwfYdgp65jyQ4RHrs2xzpYxzUB6mnDTBVnMWhjhlN9vZnhhq06wy5HwzvVQsbZpK9mCNLTD9SLwLxEZKSL9RWQU8BrwQuKqZhJi8mQ4+GC44ILgaDfw6pJXeW7xc5zf83xap7Z2XEFjTGM4pMMh1MZqeWR+fHx927Zw+eUwbhwsW7b5HzamIWJR+L/bQGOwy1FbPUmGqvLAc5Xsc0Yxh+yZxoTzMmmVbcdxjWkuMtKDTteCwhjHX1ZKVfUmOl07DIIuu8M7f4BamxV3Yxra4boC+AB4EJgM3A98BFyZoHqZRPj0Uxg5MljYeP/9gWAY4TOLn+H8nucHQ4+MMUkhLGFO7nYyH6/6mLcL4+ulDBsGo0cHC5xXV2/+FxizObEofHgHlK6A3ccGU0VvhUWFUQ4+t4SHX6ri7suzGD0ilU0spWmMcSg9TbjhvEzKKpSRFxRTXLqJdbr6HAQZefD+HyEaadpKtgANnRa+RlX/oKq9VTVLVfuo6nX1FiA2zdkrrwQfsq6+Gvbdl5jGeGDOA7xZ+Cbje40nP73+GtPGmJYuJyWHs3qcxSPzHmFy0eTgwZNOgqws+NWvILaFBS6N2ZhoBD68HYqXwJDTIJza4B+NxZRHX65k93Hr6Nk5xL2XZ9Gt49Z11owxTSstVbjm7AwKWofY6/RiFhVGf77R+kk0aiqC/UNsI9t4bLMdLhHZW0Q2OhOhiNwqInsmplqm0ajCzTfDhRfCLbfA4MFURiu5btp1fF/8PeN7jScvNc91LY0xCdIhvQOndT+NG2fcyIziGRAKBZPlTJ8OV9ogBbOVItXw3o1QujzobKU0dHUY+OHHCPudXcx9z1Zx+2+zOPmI9E1fiG+MaVbCIWH8uHQOGJrK8FPX8cV3tT/fKBSGwScFE2l8eId1uurY0hmua4BPN/HcJ8DvG7c6plGVlMAJJ8A//gH33Qd9+7K0cinnTT6PmMb4dc9fk5WS5bqWxpgE65XTi7Fdx3L11KuDTld6erD23iuvwPXXu66eaSkq1sLrl0OsFoac2uDOVnmlcvV95fzi9GJ23ymFe6/IomcXO6tlTEsjIpxwSBoX/TKD0ReX8PCLlfxstvNwarB/KF4aDC+M2HIksOUO127Au5t47t/A4Matjmk0kybBHntAJAL33APt2vHhig85f/L5DG07lBO7nEiqNHwYiDGmZRvQasBPna4pa6dAXh7cfjs8/TRcc01wNtyYTVk1B16+CNp2h91OhNCWZxKMxZR/vFVF36PXMnlmhEf/kM1xB6URDtlZLWNasr0GpXL3ZVnc+XQlY68o/fl1XSlpMPT0YHjhm1dDZbGbijYjW+pwtQI2dQgrFcht3OqY7VZTAzfcEKyxddJJcMklFFPJDdNv4NH5j3JOj3PYJ38fuzjZGA8NaDWAU7qdwvXTr+edwneCmQvvvBNefx3OOANqNzJExPhNFaa+AW9eA/0Ohb4Hg2z+o4Oq8t7nwQLGt/6tkqvOzOCaszIpaG2LGBuTLLp1DPPAVdnURmGXMev48Ot6Z7LCKbDHOMhpBy//BtbMd1PRZmKzCx+LyDfAH1X19Y08dzRwraoOTWD9Gl1SL0j5ySdw7rlQUAAXX4wWFPDeivd4ZN4j7NZ6Nw7reBhpoYaPtzfGJKflVct5YsET7NV2Ly7sfSFpNVH4058gGoWXX4YddnBdxYZotkeNkqadKVsFH90F5ath93GQU7DZzVWVf39Zy4SHK1i+OsZpR6az3+AUO8BnTJL7elqEu/9RyWF7p3H7b7PJr39wZekUmP4WDDsdBhyx1UtIONRoFd1Sh+sk4C7gAuA1VY2JSAg4hmCK+EtV9dnGqkxTSJqGsK5Zs4KL4L/6Cs45B/bbj6kl03hw7oNURas4rvNxdMvq5rqWxphmpDJayfNLnqektoRr+l9D76ye8Mwz8K9/wSOPwDHHuK7iljTbFrvFtzPRCEx7Hf77LOz4C+i9/2anfa+tVV76oIbbnqqgpEwZNyqNA4el2tBBYzxSXqn87fVqPplcy3XnZHL+mExSU+vsA8pWwZTnILsd7H8J5HZwV9mGa5oOF4CIXArcAKQDq4ECoBq4XlXvaqyKNJUW3xDWNW0a3HorvP02jBmDHncc31fN4qkFT7GoYhGjOo5ij9Z7ENrC8A9jjJ9UlW/WfsObhW9yWMfDOG3H08ieOR/uuCNYs+uuu6BrV9fV3JRm+2m+xbYzsSjM/wy++htktoadRwfDgTZhwbIoT7xWxaMvV9G5Q4jjD0pjz4EphKyjZYy35i+J8ugr1RSujnH9OVmcckQ6aes7XrEozJ/gfftlAAAZiklEQVQI8z6FgUcH14OmZrit8OY1XYcLQERaAXsB+cAa4AtVLWmsSjSlFtsQrldTA2+9BQ8+CN9/D0cfTeXokXxU8TWvLHmFskgZ+7Xbj6Fth5IiW76o2RhjimuLeWf5O8wqncUvu/6So/IPJeOl1+G11+Dss+GKK6Ddpj94O9JsP9W3uHamtgrmfgRTXgxmGNvpEGjXZ6Obrl4b49WPanj6rSqmzoly4LBURu+bSo/ONuugMWaD72dH+Mfb1SxZEWP8uEzOOiaDDvnxEwAVRfDDe1C0AHY9HnY+HNKyndZ3E5q2w5VMWlxDCMGF7J98Ai+9BC++CN27UzPqYCbtksUH6z7lqzVf0SunF8PbDqd/bn87o2WM2SZLK5fywcoPmF82n1EdR3Fs2t50fO1j+L//g+OPhwsugMGDm8v4+2ZRiY1pEe2MxmD5TJj9AcybCG13hB33goJe//P+xmLKtLlR3v28hjc+qeG72RGG75LKiMEp7DkwZcORa2OM2Yi5i6K8/nENn/43wog9Ujh1dAaH75NGTpYE63XN/QRWzYbeBwQT87Tr01zaGGiJHS4RGQXcC4SBx1T11nrPpwN/J5hqfg0wVlUXxJ+7GjgLiAIXqep7DfmdG9MiGsLa2uDs1cSJwQedTz8l1rUrq/bozZeDMvg0PIcZJTPoltWNXfJ2YVDrQbRKaeW61saYJLGqehVfFH3B5KLJdMzoyCFpQzhgchVtP/wayciAMWNg9Ohg2GGqs+Ulmk2LXF+zbWfK10DhVFg8GRZ9A6lZ0HlX2GE3yGoDQElZjP/+EOGb6REmTonwn29ryc4UhgxIYeiAMHv0TyE9rdm+9MaYZqqsQvlsSi2fTI4wbW6E4QNTGbV3KvsPTmVQtzJSl00OJtcIpUCPvaDbUOi4M6Sku6x2y+pwiUgYmA0cAiwBvgF+qaoz6mxzAbCrqp4nIuOAY1V1rIgMAJ4FhgE7AB8AfeM/ttnfuTHNqiEsLYUFC+DHH2H2bJg2jeh3U5AfZlHRsQ2FvdoyrVuIj7uWMDNUSMfMjuyYtSO9c3rTJ6cPmeFM1wmMMUksqlHmls1lRskMZpXOoixSysii7oyYk0LPmWvIXr4WhgwhNHxP2H136N8feveGnJymqF6z/dTvvJ2pKYeS5cHCo2sXweq5sGou1FZCfg/KMnuxmL4sLmnF/CVRZi2MMvPHKDPmR1m9NkafbmF6dwuzc88wu/QO076tjZowxjSe8kpl0owI386KMm1uhMLVMXbulcIeO4XZpXMZO+UupHf6HLrIXFLyu0CHfpDfE9p0g7zOwTWmTXMWrMV1uPYCJqjqyPj9qwFU9ZY627wX3+YLEUkBlgPtgKvqbrt+u/iPbfZ3bsx2N4Q1NfDxx1BVRXV1ObPWzoDamuDxmhqoqoKqKkIVlVBeQai8gpSSMlLXlZG+royMteVkr60gvSoCQEVmiOVtQixuG2NB2xjz28PSHdLIzsmnTWobCtLb0SG9PR0yOpLSgIUmjTEmUUprS1lSuYTCykJW1aykcu0q+iyO0LcQeq9JofvKGDkVwQKYZXkZlBfkUJmfS03bVkTb5LFjp0Fk5hVA69Zw+unB4svbLmk7XJHKSr54dzI11RFi0SjRSJRobSR+q6W2JkJtdQ211TVUV9VSXVlNdWUNlRW1VFRBeW0qZZFM1tXmsq46m7VVmawpT2N1SYiq+FI5menQoQ10LIBObYWuHWDHTsIOBRCy/pUxpgmVVcLcJcq8JbB4pbJ4JSxZGSwDCNC+VQ0dcirJzygnP6OU1hnV5GZGyc0Ok5WdSlZWGhmZqaRnppGWkUpKWioH75lGmz0O2t5JORqtnWmqT/CdgcV17i8Bhm9qG1WNiEgxwSQdnYEv6/1s5/j3W/qdAIjIOcA58btlIjJrGzIUAKtbQ6tesPGribdCTCAaAmpisCIGK+JPKEANUBi/ubVGIb/ZfqxJLJfZ7XV3XYum11JzfwXxJik4iEQYUqNAcVVwm7e6ztaf/vTd3Isvnl0MpfG7BQSz4G6Nd1V11LbVuvFtRzvzs+y5ma06ldZ2TMhiaCJKWGLUEnygWbItrWEjiUVLCIX9HQ7vOr/r8l2y7M0/exhQhGgsxMq1sHIrf75bXglry1b9UFodLa/31Na0N43WznhxykRVHwUe3Z7fISKTVHVII1WpxRCRSUti/uUGt9ntdfcvu6+5ITn2r9vaziRD9m0lIpOikZVeZgf3+V2X75Jl9zM7uNvnNtXAgaVA3cVcusQf2+g28SGFeQSTZ2zqZxvyO40xxhhjjDHGmabqcH0D9BGRHiKSBowD3qi3zRvA6fHvxwAfanCB2RvAOBFJF5EeBMP5vm7g7zTGGGOMMcYYZ5pkSGH8mqzxwHsEwzKfUNXpInIjMElV3wAeB54WkblAEUEHivh2LwAzCC4SuFBVowAb+50JjLFdQxJbMF9zg9vs9rr7x9fcYNl95XN2cJ/fdfkuWXZ/Ocnv3cLHxhhjjDHGGNNUbPJXY4wxxhhjjEkQ63AZY4wxxhhjTIJYh6sJiTTNstjNhW95jVt1/97sb88/Pr/nPmb3MbNxz9oZA9v23luHK8FE5FARuRlA/btgLrvuHRHx5u/NdsRO/LSSo6qqT++BiAyIz+LqFZ/3rz5nj/O2fQFrYxzytp0Bf9sa2P59rlc7qKYmIocCDwPDRaSP6/o0JREZCbwkIteKyB8AVDWW7I2iiPxCRLq42hGLyAgR2SfZX+f64n9vr4nI3SJyDfjzIVREDgOeBVJd16Upeb5/9TY7+Nu+gLUxLvnczoC/bQ00zj7Xu3+YphL/x7wF+B2wEDjcbY2ajogMA+6L314G9olP7Z/UjaKIHAR8BrznokEUkf2Aj4HbCXYKSfk61ycihwB3APcSvP7d6z2ftK9D/G/uAeA8VZ0tIqn1nk/K7J7vX73NDv62L2BtjEs+tzPgb1sDjbfPTdoXyBUJtAcuAn6rqq8CfwfOFZE93NauyWQBL6jq26o6E/gbcICIPAdBo+i0dgkgIlnAcOBo4CXglToNYsL/zyRY/Ls3cDzwNPAHYK8k3wmKiOQBo4GLVPU1YBGwt4hcKCIXw08fwpJq2Ec8ezbB39tXwGQRyQfuEJEbROR6SL7s9favl/q0f7W25SfetS9gbYwrPrcz4G9bA43f3tg6XAkiIm1VtSh+FECAG4EZqvp3EQmvX7w5GYnIwQR/lCNVdaqIXEewgzqKoKF83mkFE0REugDrVLVMRO4E9gVOUNWFTVR+AVAVL/8y4ECCozKfJ/nfW2tVXScibYFngKnAp8DZwI+qeonTCiaQiAwCxgCtCY66PQnMB8YCs1X1Mne1S5w677mP+1dv2xbwt30Ba2Nc8rmdAX/bGmi89iYlobX0jIgMBLoB3wIrAVS1Nv7cPOAKEXlZVcvd1TIx4tm7AN+r6gci8mfgeRH5L9CZYMecF78lDREZDPQFpgCz1o/nVtXfxRvEF0VkT+AIIE9V/9HI5e8J7Epw5GmZqpbFy78jfrTpauAiEdkXaKOqdzVm+a7Ecw8CvgSWxx+uAm5Q1S/i26wFTnBTw8Spl30O8Ffg98BdqvpgfJvFwLHOKpkA9XKvBNYBkfgRfh/2r162LeBv+wLWxrjkczsD/rY1kJj2xs5wNRIROQK4k+CoRz7BP+QnIpKiqpH4Nn8jOBI3IZkutKyXvT3wh3j2fkApsFxVoxJcZJoBrD8F3aJfAxEZBdwFfA7sDpyhqt+LSGqdD0PXEoz7LSE4IvtDI5Z/BPAg8A7BjF1R4EFVnVRnm18BEwiOyhyhqtMaq3xX6uXOAmLAQ6r6db3tLgAOBn4J1LT0vzf4WfYcIAL8GZgNpKpqdXy7Cwk+hJ5EEmTfxHte/2/dh/2rV20L+Nu+gLUxLvnczoC/bQ0ksL1RVbtt541gRzgDGBa/fwUwsc7zofjXs4G7gQzXdU5w9v9sZLszgcVAP9d1bqTcw4B5wN7x+38BTo3/c6bX2e4YoAgYkIA6TABOjn+/EzAeeAsYXK/84kSU7/C132xuIA04i+CIcNLk3kT2i+LZ96izza+SLXsD/9Z92b960bZsJn/Sty/xTNbGuH39vW1nNpHfi7amIe99/PGt3ucm9cWOTagYuEnjRz5U9TagWETaxO+vv4j3BeB2Va1yU82E2Fj2teuzw0/jvjvRyEffHJtJ8A/5n/i4+rEEF5U+BVwoIvkSXGi7MzBCVWckoA5pwP4AqjoLeI7giMw5IlIgIhkE461/kaDyXdlc7rZAT4IhDqckWW74efZnCLKfG/+b60kwtOjkJMu+ufe8XXybF4DbPNi/+tK2gL/tC1gb45rP7Qz429ZAotob1z3JZLgRzPaYW+f7FGASsFP8se5Ajut6OswuQIrrujZm5nr3xwJXxL8/DHgD6B+/n5bAerQmuGj3sjqP7RLfOfSN3w+7fr0c5U7W/7eGZM92XU8XuZPx5nPbshX5k6p9WZ+13n1rY5r+PfC2ndmK/EnX1jQ0+7bc7AxXI1DVmKqWxu+mAEownnq5iJxIMAY7KV/rBmS/m6DBjLiqY2PTetMOq+rzGhx5RVXfASqAHeNP1yaiDiISUtV1BENs9haRK+PlTyMYZz80fj+pZo5qQO5h8U2TbvKArche4aiKCdGA3ENc1i+RfG5bwM/2BayNcc3ndgb8bWsgse2NTZqxnUREVIPFB7XOiykiDwFhgtl9zlHV751VMkF8zb6p3PHnxhLM4nOEqi5uzPI28/xQgotZFxDMJHQ2cLCq/tgY5bvia27wN7uvuTfG1/3rej7ntzam6ficHfzO39TZk/bIWKKIyGARGSMiPUUkN75TTI1/7SfB1KgQjKseA5yaLA2Cr9kbkPsXIpIhIqcANwC/bKyGMK51vB4/LSoo8cUmRWQXoA3BGjQ/EMwkdEwy7AzxNzf4m93X3N7uX9fzOb+1MU75nB38zt+02bUZjJdsKbf4Cz+H4OLBJwlmDeoef+5AYBowvM79nVzX2bI3Se71sxbtDvRs5PKPJVj34/j4fanz3P4EUyXv7/p1SsDr7mVun7P7mjuez8v9q+W3Nsbxa+9tdt/zu8huQwq3gojcB3ykqq+KyG7AkcBuwGXASGCVqr7sso6J4mv2BuReraovJajsHsATBNOung6cq6ovSTDGOCbB+h/LVfWVLZ0ab0l8zQ3+Zvc193q+7l/X8zm/tTFu+Jwd/M7vLLvrXmZLuhEcebq+zv3OwHUEF+7mab1ecjLdfM3uMjfBYoNHx78/jOBi8TEb2S6pZonyNbfP2X3NXSeXl/tXy29tjMPX3dvsvud3ld158JZ0I1gA7b8E6y6sf2wY8E+gs+v6Wfbky02d6Y6BUXV3DMBgoJXr18hyW3bLvd3Zvdy/Wn732T3/v/M2u+/5XWS3STM2I36h6qnr72uwANq1wLj1j2uwIGM2MMhNLRPD1+yuc9cvH4jFHw+r6rvAicDDIvIU8VXOG7sOLviaG/zN7mtucL+fcc3n/K6z2/+dn9nB7/zNIXtKY//CZCEihwCvA2/HZw36S/ypTwjeqFtFpC+wFuhHcGFrUvA1u+vcGytfg/HEoqrR+Pjid0XkJYJZug5U1ZWNWQcXfM0N/mb3NTe438+45nN+19nt/87P7OB3/uaS3c5wbVpX4Cbgr8CuInIhgKqWx3vDYwAB2gMnquoiZzVtfL5md527fvkXxMvXOhdzDiVY8fxATZIpkfE3N/ib3dfc4H4/45rP+V1nt/87P7OD3/mbRXabpXATRCSFYMeXAowmmJ51uqo+4LRiTcDX7K5zN6R8EckBslV1RVPUqSn4mhv8ze5rbnC/n3HN5/yus9v/nZ/Zwe/8zSW7dbgaIP5GHA4cAHwEZAEVqvqC04o1AV+zu869ifKrVPW5pijfFV9zg7/Zfc0N7vczrvmc33V2+7/zMzv4nd9ldruGq474eM6f9UBVtUxE3gFWALcRjK3et/52LZmv2V3ndl2+K77mBn+z+5ob/M4Ofud3nd11+S75nB38zt8cs9s1XICIdBORNtTpgIpIKP41Oz7GsxQYAnQD9kqW8a2+Zned23X5rviaG/zN7mtu8Ds7+J3fdXbX5bvkc3bwO39zzu59h0tEjgKeA54HTo4/Fo5fRHcAcCeQG9+8CjhCVWc4qWwj8zW769yuy3fF19zgb3Zfc4Pf2cHv/K6zuy7fJZ+zg9/5m312bQYLkLm6AbsRTLs6kOBCuveB3PhznYCv2cjq08lw8zW769yuy/f1dbfsltuyW34fsrsu3+fX3vXN5/wtIbvXk2bEe8OnqOqJItKK4A2aSfDGLAO+U9UFIiIQTCHprraNy9fsrnO7Lt8VX3ODv9l9zQ1+Zwe/87vO7rp8l3zODn7nbwnZfR9S+DVQICIvELwxbwCvEMzZ3z/+5oQ0zmVFE8DX7K5zuy7fFV9zg7/Zfc0NfmcHv/O7zu66fJd8zg5+52/22b2bpVBE9idYVDCsqs+KyBnAICCkqjfHtykBrhKR+1S1wl1tG5ev2V3ndl2+K77mBn+z+5ob/M4Ofud3nd11+S75nB38zt/Ssnt1hkuCi+aeJZiZ5HIReRCoVNU3gOUiclJ801ZAGEhzU9PG52t217ldl++Kr7nB3+y+5ga/s4Pf+V1nd12+Sz5nB7/zt8Ts3lzDFR+3+WegUFXvFpEM4HFgLXALcBjBYmiZQGeCsaDJMk2ml9ld53Zdviu+5gZ/s/uaG/zODn7nd53ddfku+Zwd/M7fYrNrM5hdpKluwDjgYaBD/H4WwfSRt8fv9wCOBLq5rqtlT47crsv39XW37Jbbslt+H7K7Lt/n1971zef8LTG78wo0wZvSFUgn6Ol2B/4JHAJk1nmTphDMx++8vpa95ed2Xb6vr7tlt9yW3fL7kN11+T6/9q5vPudv6dmTetIMETmC4LTj5wSLnV1KMObz4uBpmaqqhSLyb4fVTAhfs7vO7bp8V3zNDf5m9zU3+J0d/M7vOrvr8l3yOTv4nT8ZsiflNVzx8Z1dgLeB3xBMEXl6/Ps9CRZIGxvffClwKnCgqs5u+to2Ll+zu87tunxXfM0N/mb3NTf4nR38zu86u+vyXfI5O/idP5myJ+UZLlVVEVkGfAHMAVaq6m0iEiHoHe9JcNpxKMEUkgc1xzdnW/ia3XVu1+W74mtu8De7r7nB7+zgd37X2V2X75LP2cHv/MmUPenOcIlIb6ANMB/4CzBZVW+r8/zVQB/gfFWtdlPLxPA1u+vcrst3xdfc4G92X3OD39nB7/yus7su3yWfs4Pf+ZMte1Kd4RKR0cDNBFNDTiW4oO4+EQmr6i3xzZ4FrgFq3NQyMXzN7jq36/Jd8TU3+Jvd19zgd3bwO7/r7K7Ld8nn7OB3/mTMnjQdLhH5BXA7cJKqThGRR4FhwC+AL0UkDDwH7APsAbQmeCNbPF+zu87tunxXfM0N/mb3NTf4nR38zu86u+vyXfI5O/idP2mzazOYKrExbgRvxK/q3G8HvBX/vifwBPFTksBA1/W17C0/t+vyfX3dLbvltuyW34fsrsv3+bV3ffM5f7Jmd16BRnyDwkCrOt93IbiQrlP8se4EZ/TyXNfVsidHbtfl+/q6W3bLbdktvw/ZXZfv82vv+uZz/mTNHiJJqGpUVUvidwVYBxRpMC//KQTjPFNVtdhZJRPE1+yuc7su3xVfc4O/2X3NDX5nB7/zu87uunyXfM4OfudP1uxJN0thXSLyJFAIHEpwenKq2xo1HV+zu87tunxXfM0N/mb3NTf4nR38zu86u+vyXfI5O/idPxmyJ2WHS0QESCVYIC2VYF7+OW5r1TR8ze46t+vyXfE1N/ib3dfc4Hd28Du/6+yuy3fJ5+zgd/5kyp6UHa71RORXwDeqOt11XZqar9ld53Zdviu+5gZ/s/uaG/zODn7nd53ddfku+Zwd/M6fDNmTvcMlmswBN8PX7K5zuy7fFV9zg7/Zfc0NfmcHv/O7zu66fJd8zg5+50+G7End4TLGGGOMMcYYl5JmlkJjjDHGGGOMaW6sw2WMMcYYY4wxCWIdLmOMMcYYY4xJEOtwGWOMMcYYY0yCWIfLmBZKRKaLyP6u62GMMSY5WTtjTONIcV0BY8zGiUhZnbtZQDUQjd8/V1V3bvpaGWOMSRbWzhjTNGxaeGNaABFZAJytqh+4rosxxpjkY+2MMYljQwqNaaFEZIGIHBz/foKIvCgi/xCRUhGZKiJ9ReRqEVkpIotF5NA6P5snIo+LSKGILBWRP4pI2F0aY4wxzY21M8Y0DutwGZM8jgSeBtoAU4D3CP7HOwM3Ao/U2fZJIAL0BnYHDgXObsK6GmOMaXmsnTFmG1iHy5jkMVFV31PVCPAi0A64VVVrgeeAHUWktYh0AA4HLlHVclVdCdwNjHNWc2OMMS2BtTPGbAObNMOY5LGizveVwGpVjda5D5AD7ACkAoUisn77ELC4KSppjDGmxbJ2xphtYB0uY/yzmGAmqoL4UUpjjDGmMVk7Y0wdNqTQGM+oaiHwPnCniLQSkZCI9BKR/VzXzRhjTMtn7Ywx/8s6XMb46TQgDZgBrAVeAjo5rZExxphkYu2MMXG2DpcxxhhjjDHGJIid4TLGGGOMMcaYBLEOlzHGGGOMMcYkiHW4jDHGGGOMMSZBrMNljDHGGGOMMQliHS5jjDHGGGOMSRDrcBljjDHGGGNMgliHyxhjjDHGGGMSxDpcxhhjjDHGGJMg/w8GiGVw1BOwegAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 864x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#kde plot\n",
    "def plot_kde(ax, data, palette, title, legend=True):\n",
    "    sns.kdeplot(\n",
    "        data=data, \n",
    "        x=\"time\", \n",
    "        hue=\"sentiment_label\",\n",
    "        hue_order=[\"POSITIVE\", \"NEGATIVE\"],\n",
    "        palette=palette,\n",
    "        ax=ax,\n",
    "        #multiple=\"stack\",\n",
    "        fill=True,\n",
    "        legend=legend,\n",
    "    )\n",
    "    ax.set_title(title)\n",
    "    #hide the right border and the top border so that it looks like a coordinate system\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.tick_params(axis='x', rotation=45)\n",
    "    ax.set_xlabel(\"Time\", fontsize=12,)\n",
    "    ax.set_ylabel(\"Count of tweets\", fontsize=12)\n",
    "\n",
    "fig, axes = plt.subplots(1, 2, figsize=(12, 3), sharey=True)\n",
    "\n",
    "plot_kde(\n",
    "    axes[0], \n",
    "    dfObama, \n",
    "    [repred, repgreen],\n",
    "    \"Sentiment in tweets concerning Obama only\",\n",
    ")\n",
    "\n",
    "plot_kde(\n",
    "    axes[1], \n",
    "    dfMcCain, \n",
    "    [demblue, demorange],\n",
    "    \"Sentiment in tweets concerning McCain only\",\n",
    ")\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "id": "41a49edd-eba8-4052-b100-62610cf7d214",
   "metadata": {
    "id": "41a49edd-eba8-4052-b100-62610cf7d214"
   },
   "outputs": [],
   "source": [
    "#histogram\n",
    "def plot_histogram(ax, data, palette, title, legend=True, hue=\"sentiment_label\", hue_order=[\"POSITIVE\", \"NEGATIVE\"]):\n",
    "    sns.histplot(\n",
    "        data=data, \n",
    "        x=\"time\", \n",
    "        hue=hue,\n",
    "        hue_order=hue_order,\n",
    "        palette=palette,\n",
    "        ax=ax,\n",
    "        shrink=.6,\n",
    "        edgecolor=None,\n",
    "        multiple=\"stack\",\n",
    "        fill=True,\n",
    "        legend=legend,\n",
    "    )\n",
    "    ax.set_title(title)\n",
    "    #hide the right border and the top border so that it looks like a coordinate system\n",
    "    ax.spines['right'].set_visible(False)\n",
    "    ax.spines['top'].set_visible(False)\n",
    "    ax.tick_params(axis='x', rotation=45,)\n",
    "    ax.set_xlabel(\"Time\", fontsize=12,)\n",
    "    ax.set_ylabel(\"Count of tweets\", fontsize=12)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "3c77f84d-e31f-459d-8501-4aa1b1576121",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 585
    },
    "id": "3c77f84d-e31f-459d-8501-4aa1b1576121",
    "outputId": "00e3ba65-c67a-428d-ef6e-bcfe89fd528d"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(2, 1, figsize=(20, 8))\n",
    "\n",
    "plot_histogram(\n",
    "    axes[0], \n",
    "    dfObama, \n",
    "    [demblue, demorange],\n",
    "    \"Sentiment in tweets concerning Obama only\",\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[1], \n",
    "    dfMcCain, \n",
    "    [repred, repgreen],\n",
    "    \"Sentiment in tweets concerning McCain only\",\n",
    ")\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "26390373-9a3d-4679-a280-42e62d140057",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 729
    },
    "id": "26390373-9a3d-4679-a280-42e62d140057",
    "outputId": "fa5bbb73-d0ba-4124-9a4d-c45b2c9fed13"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#histogram + political orientation\n",
    "fig, axes = plt.subplots(2, 2, figsize=(20, 10),sharey=True)\n",
    "plot_histogram(\n",
    "    axes[0][0], \n",
    "    dfObama[dfObama[\"political_label\"] == \"Democrat\"], \n",
    "    [demblue, demorange],\n",
    "    \"Democrat's view: Sentiment in tweets concerning Obama only\",\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[0][1], \n",
    "    dfObama[dfObama[\"political_label\"] == \"Republican\"], \n",
    "    [repred, repgreen],\n",
    "    \"Republican's view: Sentiment in tweets concerning Obama only\",\n",
    "    #legend=True\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[1][0], \n",
    "    dfMcCain[dfMcCain[\"political_label\"] == \"Democrat\"], \n",
    "    [demblue, demorange],\n",
    "    \"Democrat's view: Sentiment in tweets concerning McCain only\",\n",
    "    legend=True\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[1][1], \n",
    "    dfMcCain[dfMcCain[\"political_label\"] == \"Republican\"], \n",
    "    [repred, repgreen],\n",
    "    \"Republican's view: Sentiment in tweets concerning McCain only\",\n",
    "    legend=True\n",
    ")\n",
    "\n",
    "\n",
    "fig.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "445e6e32-846b-4f2b-96f5-5c8f0db5acf9",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 729
    },
    "id": "445e6e32-846b-4f2b-96f5-5c8f0db5acf9",
    "outputId": "8b5c6b1d-ba22-4704-a837-28a1be03b4dd"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x720 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#histogram who dislike more Obama?\n",
    "fig, axes = plt.subplots(2, 2, figsize=(20, 10),sharey=True)\n",
    "plot_histogram(\n",
    "    axes[0][0], \n",
    "    dfObama[dfObama[\"sentiment_label\"] == \"NEGATIVE\"], \n",
    "    [repred, demblue],\n",
    "    \"Who says more NEGATIVE things about Obama\",\n",
    "    hue=\"political_label\",\n",
    "    hue_order=[\"Republican\", \"Democrat\"]\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[0][1], \n",
    "    dfObama[dfObama[\"sentiment_label\"] == \"POSITIVE\"], \n",
    "    [repred, demblue],\n",
    "    \"Who says more POSITIVE things about Obama\",\n",
    "    hue=\"political_label\",\n",
    "    hue_order=[\"Republican\", \"Democrat\"]\n",
    "    #legend=True\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[1][0], \n",
    "    dfMcCain[dfMcCain[\"sentiment_label\"] == \"NEGATIVE\"], \n",
    "    [repred, demblue],\n",
    "    \"Who says more NEGATIVE things about McCain\",\n",
    "    legend=True,\n",
    "    hue=\"political_label\",\n",
    "    hue_order=[\"Republican\", \"Democrat\"]\n",
    ")\n",
    "\n",
    "plot_histogram(\n",
    "    axes[1][1], \n",
    "    dfMcCain[dfMcCain[\"sentiment_label\"] == \"POSITIVE\"], \n",
    "    [repred, demblue],\n",
    "    \"Who says more POSITIVE things about McCain\",\n",
    "    legend=True,\n",
    "    hue=\"political_label\",\n",
    "    hue_order=[\"Republican\", \"Democrat\"]\n",
    ")\n",
    "\n",
    "\n",
    "fig.tight_layout()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1a151a7-7997-443a-bea3-bc4887817cbf",
   "metadata": {
    "id": "d1a151a7-7997-443a-bea3-bc4887817cbf"
   },
   "source": [
    "### merged from Federico"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "GcZD9h6BHOYb",
   "metadata": {
    "id": "GcZD9h6BHOYb"
   },
   "outputs": [],
   "source": [
    "dfMcCain = pd.read_csv('/content/drive/MyDrive/McCain_twts_2008_classified_senti+poli.csv', parse_dates=['time'])\n",
    "dfObama = pd.read_csv('/content/drive/MyDrive/Obama_twts_2008_classified_senti+poli.csv',  parse_dates=['time'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "bfe5eea0-11e3-4039-ab7d-11a60c335ab0",
   "metadata": {
    "id": "bfe5eea0-11e3-4039-ab7d-11a60c335ab0"
   },
   "outputs": [],
   "source": [
    "# Convert sentiment to int format\n",
    "dfObama['sentiment_label'] = dfObama['sentiment_label'].replace({'POSITIVE': 1, 'NEGATIVE': -1})\n",
    "dfMcCain['sentiment_label'] = dfMcCain['sentiment_label'].replace({'POSITIVE': 1, 'NEGATIVE': -1})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "8684105f-4829-413c-9448-9958c9da3d43",
   "metadata": {
    "id": "8684105f-4829-413c-9448-9958c9da3d43"
   },
   "outputs": [],
   "source": [
    "#Average of sentiment values for each day\n",
    "dfObamaDay = dfObama.groupby([dfObama['time'].dt.date]).mean()\n",
    "dfMcCainDay = dfMcCain.groupby([dfMcCain['time'].dt.date]).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "73b7f614-dc0f-4e23-b631-e7aa45e64243",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 281
    },
    "id": "73b7f614-dc0f-4e23-b631-e7aa45e64243",
    "outputId": "722df629-cb74-443a-d75a-8d8dcb606325"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(dfObamaDay.sentiment_label,'bo-')\n",
    "plt.plot(dfMcCainDay.sentiment_label,'ro-')\n",
    "plt.axvline(pd.Timestamp('2008-11-01'),color='k',linestyle='--')\n",
    "plt.xlabel(\"day\")\n",
    "plt.ylabel(\"mean sentiment\")\n",
    "myFmt = mdates.DateFormatter('%m/%d')\n",
    "plt.gca().xaxis.set_major_formatter(myFmt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "id": "c49288fe-3c87-438f-a129-370f2e427710",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 280
    },
    "id": "c49288fe-3c87-438f-a129-370f2e427710",
    "outputId": "3ce62958-4297-428d-c872-e5dc07b8df0b"
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "window_size = 3\n",
    "plt.plot(dfObamaDay.sentiment_label.rolling(window_size).mean(),'bo-')\n",
    "plt.plot(dfMcCainDay.sentiment_label.rolling(window_size).mean(),'ro-')\n",
    "plt.axvline(pd.Timestamp('2008-11-01'),color='k',linestyle='--')\n",
    "plt.xlabel(\"day\")\n",
    "plt.ylabel(\"mean sentiment\")\n",
    "myFmt = mdates.DateFormatter('%m/%d')\n",
    "plt.gca().xaxis.set_major_formatter(myFmt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "75b8a977-ef67-4ca6-867e-808fefc9cc0d",
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 317
    },
    "id": "75b8a977-ef67-4ca6-867e-808fefc9cc0d",
    "outputId": "3037095e-45fc-4473-a12a-3b81e732dd6b"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "([<matplotlib.axis.XTick at 0x7fc57a432a50>,\n",
       "  <matplotlib.axis.XTick at 0x7fc57a4320d0>],\n",
       " [Text(0, 0, 'outgroup'), Text(0, 0, 'ingroup')])"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Convert Orientation to int format\n",
    "dfObama['political_label'] = dfObama['political_label'].replace({'Democrat': -1, 'Republican': 1})\n",
    "dfMcCain['political_label'] = dfMcCain['political_label'].replace({'Democrat': -1, 'Republican': 1})\n",
    "\n",
    "dfObamaDayDemRep = dfObama.groupby([dfObama['political_label']==-1]).mean()\n",
    "dfMcCainDayDemRep = dfMcCain.groupby([dfMcCain['political_label']==1]).mean()\n",
    "plt.plot(dfObamaDayDemRep.sentiment_label,'bo-')\n",
    "plt.plot(dfMcCainDayDemRep.sentiment_label,'ro-')\n",
    "plt.ylabel(\"mean sentiment\")\n",
    "plt.xticks([0,1],['outgroup','ingroup'])"
   ]
  }
 ],
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