team16_LSTM_code.ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"midterm_project.ipynb","version":"0.3.2","provenance":[]},"kernelspec":{"display_name":"Python 3","language":"python","name":"python3"}},"cells":[{"metadata":{"id":"i-ZFM_78RZT1","colab_type":"code","colab":{}},"cell_type":"code","source":["import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import tensorflow as tf\n","import io\n","%matplotlib inline"],"execution_count":0,"outputs":[]},{"metadata":{"id":"Xn8vwxLMRZT6","colab_type":"code","colab":{"base_uri":"https://localhost:8080/","height":912},"outputId":"dc9c91e6-c1c8-4ac2-ea97-8a15705da0df","executionInfo":{"status":"error","timestamp":1552383598595,"user_tz":420,"elapsed":592,"user":{"displayName":"Aditya Govardhan","photoUrl":"","userId":"11824158970651999882"}}},"cell_type":"code","source":["df=pd.read_csv('stock.csv')\n","df.head()"],"execution_count":2,"outputs":[{"output_type":"error","ename":"FileNotFoundError","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)","\u001b[0;32m<ipython-input-2-2a6dc2ced74a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'stock.csv'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhead\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, escapechar, comment, encoding, dialect, tupleize_cols, error_bad_lines, warn_bad_lines, skipfooter, skip_footer, doublequote, delim_whitespace, as_recarray, compact_ints, use_unsigned, low_memory, buffer_lines, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    707\u001b[0m                     skip_blank_lines=skip_blank_lines)\n\u001b[1;32m    708\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 709\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    710\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    711\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    447\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    448\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 449\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    450\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    451\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    816\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'has_index_names'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    817\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 818\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    819\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    820\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1047\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'c'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1048\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'c'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1049\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1050\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1051\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'python'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.6/dist-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1693\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'allow_leading_cols'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mindex_col\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1694\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1695\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1696\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1697\u001b[0m         \u001b[0;31m# XXX\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n","\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n","\u001b[0;31mFileNotFoundError\u001b[0m: File b'stock.csv' does not exist"]}]},{"metadata":{"id":"6Uw0qb7VRZUA","colab_type":"code","colab":{},"outputId":"dbcd1b74-f4eb-492f-c78e-5f134cfac3af"},"cell_type":"code","source":["df.tail()"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/html":["<div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>Date</th>\n","      <th>Open</th>\n","      <th>High</th>\n","      <th>Low</th>\n","      <th>Close</th>\n","      <th>Adj Close</th>\n","      <th>Volume</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>1003</th>\n","      <td>2019-03-04</td>\n","      <td>21.520000</td>\n","      <td>21.610001</td>\n","      <td>21.320000</td>\n","      <td>21.389999</td>\n","      <td>21.389999</td>\n","      <td>103900</td>\n","    </tr>\n","    <tr>\n","      <th>1004</th>\n","      <td>2019-03-05</td>\n","      <td>21.410000</td>\n","      <td>21.650000</td>\n","      <td>21.280001</td>\n","      <td>21.549999</td>\n","      <td>21.549999</td>\n","      <td>110900</td>\n","    </tr>\n","    <tr>\n","      <th>1005</th>\n","      <td>2019-03-06</td>\n","      <td>21.480000</td>\n","      <td>21.480000</td>\n","      <td>20.660000</td>\n","      <td>20.780001</td>\n","      <td>20.780001</td>\n","      <td>94700</td>\n","    </tr>\n","    <tr>\n","      <th>1006</th>\n","      <td>2019-03-07</td>\n","      <td>20.809999</td>\n","      <td>20.809999</td>\n","      <td>20.340000</td>\n","      <td>20.570000</td>\n","      <td>20.570000</td>\n","      <td>95800</td>\n","    </tr>\n","    <tr>\n","      <th>1007</th>\n","      <td>2019-03-08</td>\n","      <td>20.410000</td>\n","      <td>21.100000</td>\n","      <td>20.410000</td>\n","      <td>20.990000</td>\n","      <td>20.990000</td>\n","      <td>138000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>"],"text/plain":["            Date       Open       High        Low      Close  Adj Close  \\\n","1003  2019-03-04  21.520000  21.610001  21.320000  21.389999  21.389999   \n","1004  2019-03-05  21.410000  21.650000  21.280001  21.549999  21.549999   \n","1005  2019-03-06  21.480000  21.480000  20.660000  20.780001  20.780001   \n","1006  2019-03-07  20.809999  20.809999  20.340000  20.570000  20.570000   \n","1007  2019-03-08  20.410000  21.100000  20.410000  20.990000  20.990000   \n","\n","      Volume  \n","1003  103900  \n","1004  110900  \n","1005   94700  \n","1006   95800  \n","1007  138000  "]},"metadata":{"tags":[]},"execution_count":33}]},{"metadata":{"id":"EH37yKIkRZUE","colab_type":"code","colab":{},"outputId":"76b0db5a-1cec-4140-9bf1-401a79fd1e03"},"cell_type":"code","source":["closing_data=df['Close'].values\n","closing_data"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([23.9     , 23.950001, 24.059999, ..., 20.780001, 20.57    ,\n","       20.99    ])"]},"metadata":{"tags":[]},"execution_count":3}]},{"metadata":{"id":"fVvdwqLpRZUI","colab_type":"code","colab":{}},"cell_type":"code","source":["from sklearn.preprocessing import StandardScaler\n","scaler=StandardScaler()\n","scaled_data=scaler.fit_transform(closing_data.reshape(-1,1))"],"execution_count":0,"outputs":[]},{"metadata":{"id":"ERIJ-D-gRZUL","colab_type":"code","colab":{},"outputId":"4e612be8-4e0e-4b31-ee5c-f8f2447473f1"},"cell_type":"code","source":["len(scaled_data)"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1008"]},"metadata":{"tags":[]},"execution_count":5}]},{"metadata":{"id":"GZtDRbBnRZUP","colab_type":"code","colab":{},"outputId":"835f5875-ad2b-43b0-9ae0-22826f7ee51f"},"cell_type":"code","source":["plt.figure(figsize=(16, 7))\n","plt.plot(scaled_data)\n","plt.xlabel('index')\n","plt.ylabel('Scaled Closing Price')\n","plt.title('Stock Price')\n","plt.show"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<function matplotlib.pyplot.show(*args, **kw)>"]},"metadata":{"tags":[]},"execution_count":6},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 1152x504 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"metadata":{"id":"DtgSxUyVRZUT","colab_type":"code","colab":{}},"cell_type":"code","source":["def window_data(data,w):\n","    X=[]\n","    y=[]\n","    \n","    i=0\n","    while (i+w)<=len(data)-1:\n","        X.append(data[i:i+w])\n","        y.append(data[i+w])\n","        \n","        i=i+1\n","        assert len(X)==len(y)\n","    return X,y"],"execution_count":0,"outputs":[]},{"metadata":{"id":"QXmpt2l_RZUW","colab_type":"code","colab":{}},"cell_type":"code","source":["X,y=window_data(scaled_data,8)"],"execution_count":0,"outputs":[]},{"metadata":{"id":"29bIACOkRZUZ","colab_type":"code","colab":{},"outputId":"4b65138d-e605-465c-ba93-ecbe035e5edb"},"cell_type":"code","source":["X"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[array([[-0.02028642],\n","        [-0.00254776],\n","        [ 0.0364758 ],\n","        [ 0.0506668 ],\n","        [ 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array([-1.6664012]),\n"," array([-1.53513809]),\n"," array([-1.51739943]),\n"," array([-1.52449475]),\n"," array([-1.4925658]),\n"," array([-1.60609096]),\n"," array([-1.51739943]),\n"," array([-1.5067568]),\n"," array([-1.54223271]),\n"," array([-1.59899528]),\n"," array([-1.5067568]),\n"," array([-1.49611347]),\n"," array([-1.4925658]),\n"," array([-1.61318628]),\n"," array([-1.65575786]),\n"," array([-1.85087958]),\n"," array([-1.78702168]),\n"," array([-1.62382962]),\n"," array([-1.61318628]),\n"," array([-1.71252115]),\n"," array([-1.54932838]),\n"," array([-1.56351938]),\n"," array([-1.43225556]),\n"," array([-1.33646836]),\n"," array([-1.04910816]),\n"," array([-0.98879792]),\n"," array([-0.99234558]),\n"," array([-1.05620348]),\n"," array([-1.0455605]),\n"," array([-0.89655873]),\n"," array([-0.91074973]),\n"," array([-0.85398715]),\n"," array([-1.12715635]),\n"," array([-1.20165759]),\n"," array([-1.05265582])]"]},"metadata":{"tags":[]},"execution_count":10}]},{"metadata":{"id":"hsXWpG4KRZUh","colab_type":"code","colab":{}},"cell_type":"code","source":["X_train=np.array(X[:807])\n","y_train=np.array(y[:807])"],"execution_count":0,"outputs":[]},{"metadata":{"id":"QgGjwWTeRZUk","colab_type":"code","colab":{}},"cell_type":"code","source":["X_test=np.array(X[807:])\n","y_test=np.array(y[807:])"],"execution_count":0,"outputs":[]},{"metadata":{"id":"dMV0ApCDRZUn","colab_type":"code","colab":{},"outputId":"cfbe34f7-3edf-416b-d649-019a76652a2a"},"cell_type":"code","source":["X_train.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(807, 8, 1)"]},"metadata":{"tags":[]},"execution_count":13}]},{"metadata":{"id":"mfCQb5fcRZUv","colab_type":"code","colab":{},"outputId":"33029845-9a18-48c6-b6ea-8c0dcc014fe7"},"cell_type":"code","source":["X_test.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(193, 8, 1)"]},"metadata":{"tags":[]},"execution_count":14}]},{"metadata":{"id":"_iLxsaL2RZUz","colab_type":"code","colab":{},"outputId":"480bffac-a05c-404c-890d-e1aa5fd2c951"},"cell_type":"code","source":["y_train.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(807, 1)"]},"metadata":{"tags":[]},"execution_count":15}]},{"metadata":{"id":"xC-QDkSJRZU4","colab_type":"code","colab":{},"outputId":"f52700bd-fad4-4c92-b8cd-6caef6311cd8"},"cell_type":"code","source":["y_test.shape"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(193, 1)"]},"metadata":{"tags":[]},"execution_count":16}]},{"metadata":{"id":"sJZ83SwcRZU-","colab_type":"code","colab":{}},"cell_type":"code","source":["b = 8 #b is batch size\n","w = 8 # w is window size\n","h = 200 #h is hidden layer\n","clip_margin = 4 \n","learning_rate = 0.001 \n","epochs = 200"],"execution_count":0,"outputs":[]},{"metadata":{"id":"IDUlquzGRZVD","colab_type":"code","colab":{}},"cell_type":"code","source":["inputs = tf.placeholder(tf.float32, [b, w, 1])\n","targets = tf.placeholder(tf.float32, [b, 1])"],"execution_count":0,"outputs":[]},{"metadata":{"id":"li23si9bRZVG","colab_type":"code","colab":{}},"cell_type":"code","source":["#Weights for the input gate\n","weights_input_gate = tf.Variable(tf.truncated_normal([1, h], stddev=0.05))\n","weights_input_hidden = tf.Variable(tf.truncated_normal([h, h], stddev=0.05))\n","bias_input = tf.Variable(tf.zeros([h]))\n","\n","#weights for the forgot gate\n","weights_forget_gate = tf.Variable(tf.truncated_normal([1, h], stddev=0.05))\n","weights_forget_hidden = tf.Variable(tf.truncated_normal([h, h], stddev=0.05))\n","bias_forget = tf.Variable(tf.zeros([h]))\n","\n","#weights for the output gate\n","weights_output_gate = tf.Variable(tf.truncated_normal([1, h], stddev=0.05))\n","weights_output_hidden = tf.Variable(tf.truncated_normal([h, h], stddev=0.05))\n","bias_output = tf.Variable(tf.zeros([h]))\n","\n","#weights for the memory cell\n","weights_memory_cell = tf.Variable(tf.truncated_normal([1, h], stddev=0.05))\n","weights_memory_cell_hidden = tf.Variable(tf.truncated_normal([h, h], stddev=0.05))\n","bias_memory_cell = tf.Variable(tf.zeros([h]))\n","\n","#Output layer weigts\n","weights_output = tf.Variable(tf.truncated_normal([h, 1], stddev=0.05))\n","bias_output_layer = tf.Variable(tf.zeros([1]))"],"execution_count":0,"outputs":[]},{"metadata":{"id":"b_bFQFJtRZVI","colab_type":"code","colab":{}},"cell_type":"code","source":["def LSTM_cell(input, output, state):\n","    \n","    input_gate = tf.sigmoid(tf.matmul(input, weights_input_gate) + tf.matmul(output, weights_input_hidden) + bias_input)\n","    forget_gate = tf.sigmoid(tf.matmul(input, weights_forget_gate) + tf.matmul(output, weights_forget_hidden) + bias_forget)\n","    output_gate = tf.sigmoid(tf.matmul(input, weights_output_gate) + tf.matmul(output, weights_output_hidden) + bias_output)\n","    memory_cell = tf.tanh(tf.matmul(input, weights_memory_cell) + tf.matmul(output, weights_memory_cell_hidden) + bias_memory_cell)\n","    state = state * forget_gate + input_gate * memory_cell\n","    output = output_gate * tf.tanh(state)\n","    return state, output"],"execution_count":0,"outputs":[]},{"metadata":{"id":"WUs3NXmpRZVM","colab_type":"code","colab":{},"outputId":"eb51f2d1-74a2-45d6-ac72-87a17474b42c"},"cell_type":"code","source":["outputs = []\n","for i in range(b): \n","  \n","    batch_state = np.zeros([1, h], dtype=np.float32) \n","    batch_output = np.zeros([1, h], dtype=np.float32)\n","    \n","    for j in range(w):\n","        batch_state, batch_output = LSTM_cell(tf.reshape(inputs[i][j], (-1, 1)),\n","                                              batch_state, batch_output)\n","        \n","    outputs.append(tf.matmul(batch_output, weights_output) + bias_output_layer)\n","outputs"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<tf.Tensor 'add_656:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_729:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_802:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_875:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_948:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_1021:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_1094:0' shape=(1, 1) dtype=float32>,\n"," <tf.Tensor 'add_1167:0' shape=(1, 1) dtype=float32>]"]},"metadata":{"tags":[]},"execution_count":38}]},{"metadata":{"id":"uXPOKYzGRZVP","colab_type":"code","colab":{}},"cell_type":"code","source":["losses = []\n","\n","for i in range(len(outputs)):\n","    losses.append(tf.losses.mean_squared_error(tf.reshape(targets[i], (-1, 1)),\n","                                               outputs[i]))\n","    \n","loss = tf.reduce_mean(losses)"],"execution_count":0,"outputs":[]},{"metadata":{"id":"-kxFZPxiRZVS","colab_type":"code","colab":{}},"cell_type":"code","source":["#we define optimizer with gradient clipping\n","gradients = tf.gradients(loss, tf.trainable_variables())\n","clipped, _ = tf.clip_by_global_norm(gradients, clip_margin)\n","optimizer = tf.train.AdamOptimizer(learning_rate)\n","trained_optimizer = optimizer.apply_gradients(zip(gradients, tf.trainable_variables()))"],"execution_count":0,"outputs":[]},{"metadata":{"id":"16fMahVuRZVW","colab_type":"code","colab":{},"outputId":"4257ca62-1e2a-4d75-ca28-6b396c8c8068"},"cell_type":"code","source":["session = tf.Session()\n","session.run(tf.global_variables_initializer())\n","for i in range(epochs):\n","    traind_scores = []\n","    j = 0\n","    epoch_loss = []\n","    while(j + b) <= len(X_train):\n","        X_batch = X_train[j:j+b]\n","        y_batch = y_train[j:j+b]\n","        o, c, _ = session.run([outputs, loss, trained_optimizer], feed_dict={inputs:X_batch, targets:y_batch})\n","        epoch_loss.append(c)\n","        traind_scores.append(o)\n","        j += b\n","    if (i % 40) == 0:\n","        print('Epoch {}/{}'.format(i, epochs), ' Current loss: {}'.format(np.mean(epoch_loss)))"],"execution_count":0,"outputs":[{"output_type":"stream","text":["Epoch 0/200  Current loss: 0.09508194029331207\n","Epoch 40/200  Current loss: 0.01598675735294819\n","Epoch 80/200  Current loss: 0.015596196986734867\n","Epoch 120/200  Current loss: 0.014485039748251438\n","Epoch 160/200  Current loss: 0.013005262240767479\n"],"name":"stdout"}]},{"metadata":{"id":"hyacXUD7RZVa","colab_type":"code","colab":{}},"cell_type":"code","source":["sup =[]\n","for i in range(len(traind_scores)):\n","    for j in range(len(traind_scores[i])):\n","        sup.append(traind_scores[i][j][0])"],"execution_count":0,"outputs":[]},{"metadata":{"id":"M-eFggzURZVg","colab_type":"code","colab":{}},"cell_type":"code","source":["tests = []\n","i = 0\n","while i+b <= len(X_test): \n","    o = session.run([outputs],feed_dict={inputs:X_test[i:i+b]})\n","    i += b\n","    tests.append(o)"],"execution_count":0,"outputs":[]},{"metadata":{"id":"q-4RB_oVRZVk","colab_type":"code","colab":{}},"cell_type":"code","source":["tests_new = []\n","for i in range(len(tests)):\n","    for j in range(len(tests[i][0])):\n","        tests_new.append(tests[i][0][j])"],"execution_count":0,"outputs":[]},{"metadata":{"id":"NVjhbwIfRZVo","colab_type":"code","colab":{},"outputId":"5df44b7f-04b0-4070-c4a1-00c18ec88bd9"},"cell_type":"code","source":["tests"],"execution_count":0,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[[[array([[0.57436013]], dtype=float32),\n","   array([[0.35128453]], dtype=float32),\n","   array([[0.23770472]], 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dtype=float32),\n"," array([[-0.8277733]], dtype=float32),\n"," array([[-0.94578105]], dtype=float32),\n"," array([[-0.88094974]], dtype=float32),\n"," array([[-0.7758842]], dtype=float32),\n"," array([[-0.800168]], dtype=float32),\n"," array([[-0.7947173]], dtype=float32),\n"," array([[-0.9879518]], dtype=float32)]"]},"metadata":{"tags":[]},"execution_count":29}]},{"metadata":{"id":"eJ94s5C4RZVw","colab_type":"code","colab":{}},"cell_type":"code","source":["test_results = []\n","for i in range(1000):\n","    if i >= 808:\n","        test_results.append(tests_new[i-808])\n","    else:\n","        test_results.append(None)"],"execution_count":0,"outputs":[]},{"metadata":{"id":"Z4iGv8GeRZVy","colab_type":"code","colab":{},"outputId":"8feb485f-f284-4b7c-c345-7387e5161a5f"},"cell_type":"code","source":["plt.figure(figsize=(16, 7))\n","plt.plot(sup,'r',label='Training data')\n","plt.plot(test_results,'g', label='Testing data')\n","plt.xlabel('Days')\n","plt.ylabel('Closing price of stock')\n","plt.legend()\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA7IAAAGtCAYAAAArn0iTAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4yLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvOIA7rQAAIABJREFUeJzs3Xd8FHX+P/DXJCEF0kijBJLQQgsQacpRLCCKvYCed5bDLneW8/TEE88TPcv9zu95ep7IKXqeHmJD0UPsFAsgYCjSEloIkN5Deub3x5tPZjbZTXY3m93Z5PV8PHjM7Ozs7KSx85r3p2i6roOIiIiIiIjIXwT4+gSIiIiIiIiIXMEgS0RERERERH6FQZaIiIiIiIj8CoMsERERERER+RUGWSIiIiIiIvIrDLJERERERETkVxhkiYiIiIiIyK8wyBIREREREZFfYZAlIiIiIiIivxLk6xNwRVxcnJ6SkuLr0yAiIiIiIqJOsHXr1kJd1+Pb28+vgmxKSgq2bNni69MgIiIiIiKiTqBp2hFn9mPTYiIiIiIiIvIrDLJERERERETkVxhkiYiIiIiIyK/4VR9ZIiIiIiIiV9TX1yMnJwc1NTW+PhUyCQ0NxYABA9CjRw+3Xs8gS0REREREXVZOTg4iIiKQkpICTdN8fToEQNd1FBUVIScnB4MGDXLrGGxaTEREREREXVZNTQ1iY2MZYi1E0zTExsZ2qErOIEtERERERF0aQ6z1dPRnwiBLREREREREfoVBloiIiIiIqJMUFRUhPT0d6enp6Nu3LxITE5sf19XVOXWM+fPnY9++fW3u88ILL+DNN9/0xCnb+OKLL3DZZZe1uc+2bduwZs0aj793WzjYExERERERUSeJjY1FRkYGAOBPf/oTwsPDcd9999nso+s6dF1HQID9OuOrr77a7vv8+te/7vjJumnbtm3YtWsXzj//fK+9JyuyREREREREXpaVlYW0tDTcfvvtGD9+PE6cOIFbb70VEydOxOjRo7F48eLmfadNm4aMjAw0NDQgOjoaCxcuxLhx4zBlyhTk5+cDABYtWoRnn322ef+FCxdi8uTJGD58OL777jsAQFVVFa688kqMGzcO11xzDSZOnNgcss3+97//Yfjw4Zg2bRo+/PDD5u0bN27ElClTcNppp2Hq1KnIzMxEdXU1Fi9ejDfffBPp6el499137e7naazIEhERERFR93DPPYCd4NYh6enAqQDpqt27d+PVV1/FkiVLAABPPfUUYmJi0NDQgLPPPhtz587FqFGjbF5TVlaGM888E0899RTuvfdeLFu2DAsXLmx1bF3XsXnzZqxatQqLFy/GmjVr8Pzzz6Nv37547733sH37dowfP77V606ePInbbrsN69atw+DBgzF37tzm50aOHIlvvvkGgYGBWLNmDRYtWoQVK1bgj3/8I3bt2tUcpMvKyuzu50kMskRERERERD4wZMgQTJo0qfnx8uXL8corr6ChoQHHjx/H7t27WwXZsLAwzJkzBwAwYcIEbNiwwe6xr7jiiuZ9Dh8+DAD45ptv8MADDwAAxo0bh9GjR7d63e7du5GamoohQ4YAAH75y1/i9ddfBwCUlpbi+uuvx4EDB9r8upzdryMYZImIiIiIqHtws3LaWXr16tW8npmZib///e/YvHkzoqOjce2119qdZzU4OLh5PTAwEA0NDXaPHRIS0mofXdedOi9HU+M89NBDOO+887BgwQJkZWU57BPr7H4dwT6yRETU9TQ2AsXFvj4LIiIip5WXlyMiIgKRkZE4ceIEPv30U4+/x7Rp0/D2228DAHbu3Indu3e32mfUqFHYv38/Dh06BF3XsXz58ubnysrKkJiYCAB47bXXmrdHRESgoqKi3f08iUGWiIi6lqYmYPx4IDkZMN95rqsDqqp8d15ERERtGD9+PEaNGoW0tDTccsstmDp1qsff484778SxY8cwduxYPPPMM0hLS0NUVJTNPj179sSSJUswZ84cTJ8+HYMHD25+7oEHHsD999/f6tzOOeccbN++Haeddhreffddh/t5kuZsedkKJk6cqG/ZssXXp0FERFb28svALbfIem4u0KePrF93HbB8OXDgADBgAFBQAPTt67vzJCIir9izZw9Gjhzp69OwhIaGBjQ0NCA0NBSZmZmYPXs2MjMzERTkmx6n9n42mqZt1XV9YnuvZR9ZIiLqOhoagCefNB7v3w+UlwM//zmwbZtsu/tuYOxY4LHHgLw8ICHBN+dKRETkZZWVlZg5cyYaGhqg6zpeeukln4XYjvLPsyYiIrJnyxbg4EHg8ceBRYskyH7xhRFig4KA//0PODWfHrZuBU6N/EhERNTVRUdHY+vWrb4+DY9gH1kiIuo61KAVc+cCwcESZANMH3XPPy9V24ICeczuKkRERH6JQZaIiLqOPXuAkBBg6FD5t28fkJNjPH/DDTIIlLJmjQwORURERH6FQZaIiLqO3buB4cOBwEAgNVUqskePAqedBuTnA2FhgGnieXz3HfDrX/vufImIiMgtDLJERNR17NkDqNEPU1OBrCzgyBEgJQWIj5ft48bJ8okngDPPBP7zH8DOhPNERERkXQyyRETUNdTUAIcPAyNGyOPUVKC+Hti7V6bbUX73OxnZ+Le/BRYulLllv/zSJ6dMRERdX1FREdLT05Geno6+ffsiMTGx+XFdXZ3Tx1m2bBlyc3ObH8+fPx/79u3z+PkuWrQIzz77bJv7vP/++9i7d6/H39sVHLWYiIi6hiNHAF0H1MTtw4cbzw0caKyHhUmABYCzzwZ69QJWrwYuvNB752oleXkyMFbv3r4+EyKiLik2NhYZGRkAgD/96U8IDw/Hfffd5/Jxli1bhvHjx6PvqTnQX331VY+epyvef/99BAQEYIS6eewDrMgSEVHXcOiQLFWQTU01npvoYF71kBBgxgzgq68699ysqrER6NtXAj0REXndv//9b0yePBnp6elYsGABmpqa0NDQgOuuuw5jxoxBWloannvuOaxYsQIZGRm4+uqrmyu506ZNQ0ZGBhoaGhAdHY2FCxdi3LhxmDJlCvLz8wEAmZmZOP300zF58mQ8/PDDiI6OtnseixcvxvDhw3HuueciMzOzefuSJUswadIkjBs3DvPmzUN1dTU2bNiA1atX47e//S3S09Nx+PBhu/t1NlZkiYioa1BBdtAgWao+scOGtR3UzjkHuP9+4NgxIDGxc8/Raj79VJbbt/v2PIiIvOSeNfcgIzfDo8dM75uOZ89vuymuPbt27cLKlSvx3XffISgoCLfeeiveeustDBkyBIWFhdi5cycAoLS0FNHR0Xj++efxj3/8A+np6a2OVVZWhjPPPBNPPfUU7r33XixbtgwLFy7EnXfeifvuuw/z5s3DP/7xD7vnsXnzZrz33nvIyMhAXV0d0tPTMWXKFADAvHnzcPvttwMAFi5ciNdeew133HEHLrjgAsydOxeXXXZZm/t1JlZkiYioazh0SCqs/frJY02TcLpjR9uvmz1blv/5T+eenxW9954sZ8zw7XkQWdmBA8CcOcCbbwJvvOHrs6Eu5IsvvsAPP/yAiRMnIj09HevWrcOBAwcwdOhQ7Nu3D3fffTc+/fRTREVFtXussLAwzJkzBwAwYcIEHD58GACwadMmXHnllQCAX/ziF3Zfu379elx55ZUICwtDVFQULr744ubnduzYgenTp2PMmDF466238NNPP9k9hrP7eRIrskRE1DUcOiRzxAaY7tH279/+68aOlf6xTz4JLFgAREZ23jlazYkTvj4DIuv7zW9kzuk1a+Txtdf69nyoQ9ypnHYWXddx44034rHHHmv13I4dO/DJJ5/gueeew3vvvYelS5e2eazg4ODm9cDAQDQ0NLh0Lpqm2d1+/fXX45NPPkFaWhpefvllbNy4sUP7eRIrskRE1DWoaXbcceedQHk5sG2bR0/J8k71oUJ9vW/Pg8iqHnjACLBEHjZr1iy8/fbbKCwsBCCjG2dnZ6OgoAC6rmPevHl49NFHse3UZ1NERAQqKipceo/Jkydj5cqVAIC33nrL7j4zZszA+++/j5qaGpSXl+Pjjz9ufq6qqgp9+/ZFfX09/vvf/zZvb3kujvbrTKzIEhFR15CXZ8wh66qxY2W5cydw1lkeOyXLKyiQJYMsUWsVFcBf/uLrs6AubMyYMXjkkUcwa9YsNDU1oUePHliyZAkCAwNx0003Qdd1aJqGp59+GoBMt3PzzTcjLCwMmzdvduo9nnvuOVx33XV4+umnccEFF9htpjx58mRcfvnlGDduHFJSUjDD1N1k8eLFmDx5MpKSkpCWloaaU/OuX3PNNbjtttvwzDPP4IMPPnC4X2fSdF3v9DfxlIkTJ+pbtmzx9WkQEZEV9eoF3HEH8Ne/uv5aXZfBoa64Amin+VaXoetAz54y/+7YsRzwiailjRuBUwPe2PCja2cSe/bswUh3b3T6uaqqKvTs2ROapuGNN97AypUr8Z4aH8EC7P1sNE3bquu6g+kGDKzIEhGR/zt5Uv7Fxbn3ek0Dxoxpf2CorqSqSkIswIoskT27dsly9mxg82agtNS350Pkhh9++AH33HMPmpqa0Lt3b5/OPetp7CNLRET+r6hIlu4GWUCC7E8/dZ9qi2pWDDDIUteTnw9Mnw6sWuX+MXbtkpYen3zCkb3Jb5111lnIyMjAjh07sG7dOgxWc613AQyyRETk/04NlNGhIJuaClRWSl/b7kAN9BQXxyBLXc8NNwDffCNT5rgrIwMYNUpGQh840Nje2Njx8yOv86fulN1FR38mDLJEROT/PBFkhw2TZWZmx8/HH6iKbP/+QF2db8+FyFM2b5bptNRIwyUl7h2ntBT49ltg5kx5fNVVxnNeGMSGPCs0NBRFRUUMsxai6zqKiooQGhrq9jHYR5aIiPyfCmXx8e4fY+hQWWZlSZPErk59zxITgePHfXsuRJ7y1FPA6tWy3r+//D27Y/VqoKEBuPRSeTxjBvD3vwN33y1Btlcvz5wvecWAAQOQk5ODAnOXCvK50NBQDBgwwO3XM8gSEZH/80RFNjkZCArqPhXZ4mJZ9unDpsXUNXz/PRARYTy+9loZxbyuDggOdu1YGzYA0dHA5MnGNlU5YkXW7/To0QODBg3y9WmQhzHIEhGR/ysslH5s0dHuHyMoCBg0yP0Kjr+prJRl794MsuT/jh4Fpk41BmtbsUICZ1MT8OGHwLx5rh3v+HEgKUn+X1HCwmTJIEtkCewjS0RE/q+wEIiJAQIDO3acpCS5IO4OKivlwjw0lH1kyf99/70RYs86S/q0pqbK46uucr35/IkTQL9+tttYkSWyFAZZIiLyf4WFHWtWrERFARUVHT+OP6iqAsLDgR49pC8gB0Ehf7Zxo7GekCDL008Hrr9e1nNyXDteW0G2utq9cyQij2KQJSIi/1dQ0LGBnpSIiO4TZCsrjSALSJgl8ieNjcD69bJuL8hqGrBggay7MshPUxOQm8uKLJHFMcgSEZH/81RFNjISKC/v+HH8QWWljLyqgiz7yZK/ee454MwzgY8+ArZtM7b36WOsq1Cr5k12RlGR3Njp29d2O4MskaUwyBIRkf/zVJBVFdnu0MxWVWTVaK7sJ0v+5sgRWb7+OlBbawRP89Q4qqWGoyBbWws8+6z8/ufmyryzJ07Icy0rshzsichSGGSJiMi/6bpnK7KNjd2jD5y5jyzAiiz5n969Zfnxx7I86yxZ1tYa+/TqJQHUUdPizz8HfvtbWfbrJxVeR0GWFVkiS2GQJSIi/1ZeLs0APVWRBbpHP9mWfWQZZMnfnDwpy5oaIDERWLRI+sVecYWxj6ZJ82JHFVk1Svkrr8hy505jhGMO9kRkaQyyRETkf+rqjIvYwkJZemKwp8hIWXqyn2xxMXDokOeO5ynsI0v+rqTEWL/4YmD0aBmoSU27o8THO67IqiC7cqUsQ0KAgwdl/tiBA233ZUWWyFIYZImIyP9Mnmz0g1MXqFatyI4dCwwe7LnjeQr7yJI/O3gQyM42Hs+f73hfZyqySm0tsHUrkJxs/G0oDLJElsIgS0RE/mf7dlmq/rGA5/rIAp6tyB475rljeRKbFpO/qKmR39V//lMeNzUBkyYBn34q/V//+Ed57Eh8vOMga55fNj1dll9+CQwZ0npfDvZEZCkMskRE5L9KSz0bZDuzj6yV5mltapKm2Qyy5A/WrJHBye6+Wx4fPy5N9gFg5kzg0UelL6wjCQnScsPeaOTmiuxVV8myrs5+kA0JkSWDLJElMMgSEZH/OnLEqHia5450V2dUZJXSUs8f012qfzH7yJI/ePttWQYFye9pZqbxnBq5uC0JCdJkuKJCQuqqVRJqdd22Invllcb60KGtjxMUJP842BORJTDIEhGR/zp8GNi/HxgwAOjZs+PH68yKrJWCbGWlLNlHlvzB119LNbSmBti2Tf7mlaio9l+vBoIrKABeew249FJgyRJpzVFbC/ztb/LcsGEy/Q4AjBlj/1ihoazIElkEgywREfkXc+Xw8GFg3z5g+HDPHFtVZL/9Viq8ahoOTzCPsOpr5iDLiixZWX4+kJsL3HyzPN6zx7YiW1XV/jESEoxjqa4I//yn0aw4OVm6Jmga8NVXwI4dwOzZ9o/FIEtkGQyyRETkX8yB8NAhCbItp9twV8+eMu3GG2/IRe+HH3rmuIC1KrKrV8uSTYvJ6tTAbhddJMsjR2yDrOor2xZVkc3PN8Lrrl1AVpasm6fZCQiQaqyjPrdhYWxaTGQRDLJERORfzBeuGzZIQPRURVbTjObFgGfDnVWC7JdfGoPmsCJLVqeC7KRJQL9+MuVOTg6Qlibbr766/WOoimxBgbTiULZtk+WAAc6fT69ezlWBiajTMcgSEZH/yMwERo6U9cRE4McfZd1TFVkA6N/fWC8q6vjx1EinVmharOvAwoWyfvfdwPTp7CNL1vb99xI0Y2OBpCSpyBYUABMmAI2NwDXXtH8Mc0X2yBHj5s3WrbKugq4zGGSJLINBloiI/McrrxjrM2ca61Oneu49zM0MzVNzuEvNPenriuxf/iLNJrdsAR5+GHj2WTk3VmTJqoqLgY8/NkYTTk6WIFpYKOE0wMnL2LAwaX1w6BBw8CAwebJs37pVbog5exxAgqzqY05EPsUgS0RE/qNfP2PdHGTVIE2ekJRkrKsgW1go1R93BAbK0ldB9pVXpHL95JPGNvOIrAyyZEWFhcCcOdJSYP582ZacLP1aq6tdnze6pgZ4+WUZpVgF2ZIS2xtXzmBFlsgyGGSJiMh/mOd3Pftsqcq89ppn38N8YZudLSOmxscDTz/t3vFqa2Xpq6bFN98MjB8vlSeFQZasbts2YPNm4N57gXHjZJv5JpNqLuws1cT/3HOBW24xtrvSPxaQyi6DLJElMMgSEZH/MA/01K+f9Hm74QbPvof5Ynn/fmDBAllfv96946kg64uKrDmcNjUZ60OHGuvmPrKLF7te6eosX38tc31S96RGBr72WmOb+ffW1SC7bh3www/AZ58Z/ewB4LTTXDsOK7JElsEgS0RE/qOkRALssWNAUFDnvEffvrIMDQWGDAFWrpTHrlZuAGmOrMKkL4KsuYKdnS3L/v1tv3fmiuwjj8gAV1YYmOqf/wT++EdfnwX5ipqrNTTU2GYendzVGy4TJgATJ7be7mr/evaRJbIMBlkiIvIfxcUywqh5ZGFPU/1wb7xRmjeqi+eCAtePpaqxQMcvfqdMcb16ZA6yVVXA//t/MliOmb2mxfv3u3eOnpSfLz9vcyWZug9VkVWDpQEda1rsyPjxru3PpsVElsEgS0RE/qOkBIiJ6dz3GDdOmh8+84wMIrV7twws1dEgW1HRsfPauBHIyHDtNWVlto8HDWpdybYXZJ98UsLsm2/KTYO8PNfPt6Py86Wi3fJroO7BXpBVA6cBHW8CP3++VGjNFV9n9OolzfDZp5zI5xhkiYjIfxQXA717d/77nHuucYEbECBVYHeCrGoeCUiQ/eEHYPBgzwfD8nLg3Xdbz3vbMgSmpLR+reojW1sLaJqsf/ghMHcu8M47wIkTwF13efZ8nZGfL0tPzOVL/sdekDWLiurY8Zctk79HV/XqJUtWZYl8jkGWiIj8R0mJd4JsS/HxHavIhoRI0+KXXpK5LF991f1zqatrve3ll4F584Dp041t33wDPPCA7X7m0YoVVZE9fhzQdWP7yZPG42+/df983VFfbwzsVVjo3fcma7DXRxaQGzYLFhg3XbyNQZbIMhhkiYjIfxQXd37TYnvi46W6efKka69TF+NxcVKRVQNJff21++eSnw988QVw+eVG0DxwQJbHjhn7TZ8ObNpkPA4MNKqvZoGBwIgRwAsvyOO0NFlWVxvHO37cu00pzeGVQbZ7qq6W1hDqRoty5ZXG76ovhIfLkkGWyOcYZImIyD9UV0uF01cVWUCqMUuXAh995NzrzEG2ulrmpAVkKpCGBuff31wpzcsDLrkE+OADo0qsBnAqL5d+pfZceqnj45unufnXv4DHH5fwqgZ90nV57C2qWTHApsXdVXW1NCv2VeXVEVWR5cjFRD7HIEtERP5BNTX1RZA198e77TYJks5QTYtVED50yNiuqqjOMFd/cnOB6GhZP3zYdgkY/WIjIoxt//kP8Prrjo9/5pnAE09ItTs11Zivs6ICOOMMWT961Pnz7ShzH2JWZLun6mrXB2LyBjYtJrIMBlkiIvIPqiLYmVPvOKKa27rKXJEFgIMHjYC5a5fzxzFPo5OXZwTZQ4ekWnrkiLFNzQEbG2u85tprjQtwRx58UEJjTIwRZAGZ9gfwbpDdutVYZ5DtnmpqHA/05EtsWkxkGQyyRETkH1R/zcRE7793WhqwapXtNmf6y6qKrAqyhw8DM2ZIc8mffnL+/c1T97SsyJaUSDPH9HTZZi/IOks14xw92tg2aZIsOxpk166VeXl//BGYPBlYvtz+wFVbtwJ/+IOsh4ezaXFXcPSo4ybvjqimxVbDiiyRZTDIEhGRf8jJkeWAAb55/z59bB8fPNj+a1RFVjUtBoDkZJmCZ+dO59/bHGTz8oxQcPiwEYhPO02WKsi2HCTHFaGhwIsvyvqUKdK0uqNB9sYbgfvukxsCP/wA/OIXwK9+ZTz/2GPAzTcD69fL47Vr5XvlzmjRZB3FxUBSEnD//a69zupBln1kiXzOp0FW07Rlmqbla5rmQvsqIiLqlnJyJJyZQ6E3tZy3Miur/de0bFoMyPmnpjoXhBVzkC0uBkpLZX3/fgmD8fHARRfJNhVkXR1huaXbb5cwkZICDBwIZGc7/9rSUtt+rlVV0gx6925gzx4JNtdeK4NmqUGvVq4EVqwAtmyR5uNnnik3D/Lzgc2bgaYm2S8nh9Uwf6J+b9rqo21PTY01+8iyaTGRZfi6IvsagPN9fA5EROQPcnKkWXGAjz66VHNeJTOz/de0bFoMSOjs3x84ccL591Z9ZDXNNshu2CCB+K9/BYYPl23qORVkr7rK+fdpSQWJpCTXKrK33247INaePbLMy5P5bceMAebMkarWzp3Sz3f/fnm8ciUwcaLs37cv8N13wOmnA//8p2ybPBn485/d/5rIu1SQLS2V1gPq5k57rFqRVX3czf3WicgnfBpkdV1fD6DYl+dARER+IifHd82KgdYV2Q8+aP819iqyCQlAv34S6pydgkdVZJOSpOKqRiZWc7tOnNh6sKeTJ6Wp7ooVzr1HWwYOdC3IZmTIYFZq2iBzf+Bjx4BRo4CpU+Xxt9/KQF6qwlVdDUyYIOtq3l3ACLonTgD79rV+z7o6Y7ogsg71e9PYKH3N09Odq2ZaNciGhQFBQcbfIBH5jK8rskRERM45dsw3Az0poaFAcLCsX3KJVArbGrCpvh547jlZNzeHnjJFKrJNTbbzpbZFBdmUFAl9tbXAzJmyLSREmir37ClNr81BtmdPp7+8Ng0cKKMHV1e3v29Dg1SJT540vr7du233GTVKQnlCggwA1TKYXn21LM1BNjLSqGKrgb/M7rhDqtLq6ydraNkkfd8+4Kmn2n+dVaff0TS5qcUgS+Rzlg+ymqbdqmnaFk3TthRwwAciou6poUEuiJOTfXseqip7002y3LDB8b5ffSVVyQULgEGDjO0DBhhTCDnbvFg1Y0xOlql2AOCcc2Q5erRUiDRN5tjtrCALGANutSU726gUq7lyDx8Ghg0Dpk8HrrgCmDdPznfECGmibQ6yaWlGM2lzkA0MNKZg2rRJqtzmGwFvvSVLTtdjLeZK/quvyqjdX3zR/uusOv0OwCBLZBGWD7K6ri/VdX2irusT4301wAcREfnWgQPSdHTUKN+ehwqyY8bI6KWq76c9KnT97nfGSKezZ8uyXz/bfdpSXAw88oismyvSgwfLSMXTpxvbVJBtaJDvl6eDrDPNi83Ne9WAVvn5MnDT+vXAe+8Z34/UVNl/yxY596IiGdFYMQfZsjLb71dREbBxo/FY9QnmdD3Wkp0tA3ft3i0Dk40eDezdazQ7d8SqTYsBBlkiiwjy9QkQERG16e23jaamVgmyvXtLNbFlkNV1Yy7W3FxZ9usn27KzjSl8VEXWmSD73nvSlDguDoiJMbZHR0v/UvM0O/HxEhpVE2BPBdmkJFk6M3KxeRAsVZHNz5fvV0upqfLcu+8C555r+/UBtkG2tLT19yswsPUxGWS968svgbFjHY8mfvSoBNmRI+XxiBHys1Q3NxxhkCWidvh6+p3lAL4HMFzTtBxN027y5fkQEZEF3XabsW4vDHmTCrIREXJhbg6y69bJiMpqftgTJ2R/dTE+cKDRx7ZPHwm3zjQtVvscOGAb9NSxg0z3pBMTJeyp6qSngqwaZMuZiuzRo9JvNykJ2LpVthUUSH/YllJTZVleDsya1fr5lhXZlt+vsjLpa3yT6fKBTYu9p7ZWfm4XXCCPly4F/vEP43ldl5+ZunEDGH/De/e2fWyrTr8DMMgSWYSvRy2+Rtf1frqu99B1fYCu66/48nyIiMiCzjjDWFdTX/hKVJQMOhQYKBfkOTnGQEyffirLd96R5YkTtkHMrEcPCbPO9DnNy5MKcGSkbZAdOrT1vv37y0BIalRYTwXZkBAJos4E2bw8+dowZaKzAAAgAElEQVSuuQb43/9k/tjCQvsVO/ONCTUPrllsrLFuryJbWir9a5ctM7axIus96nu9a5csb7sNuPNO4Mcfjefr610PsrrOiiwRtcvyfWSJiKiba2qS5YMP+vY8AGDIEPkHGEHy8GFZqov1Q4dkmZtr9IW1JynJGLjJEdUvVDXBNAdZe8EwMVGqsapy6akgCzg/BU9enoTe226Tn93LL0swsVeRHT4cWLVKwre9qZUCAuQYF10ErF0LrFkj0/bMmCHPl5UB27fLuvpaGWS9R1W/g4Nt+7y++qos1Y0H89/BgAFAeLgRfu2pr5efO4MsEbWBQZaIiKyttBQ47zzgiSd8fSbAn/8sTYgB4+I8L0+Wql+qGuDoxIm2g6x5BGJ7Tp6UfrAffGAEWVWRdtQfUQ0Gpfqp+iLIqr6PKSlSyVXVOUfnfPHFthW7ltRozGr9lVfkZxASIr8b27cb0w4lJLBpsatKSuRmgjvUTYPgYNvvuwqw6oaK+ecbECCDpe3Y4fi46m/Jqk2Lo6OlOby6yUZEPsEgS0RE1lZaKheOVhAcbIRJ1WxYXayrKXKysmQqmAMHHDctBiToZWc7vhg2T1GiguyQIVKlWrrU/mtUYOiMIJuU5FrTYk2TIK8Ci72KrLNU3+TTTzem5omOlt+NjAzprxwcLE2RWZF1zaWXyr+sLNdfa67IqpYIgPE3Ya8iC8jgUNu3Ox65uLZWllYNslFRcu6Vlb4+E6JujUGWiIisrazMOkHWTIVUNTqx6iubny/9QwHb+WNbSk6WC3ZV0W3po4+MdRVkIyOlUnvZZfZfoyqyKpR4uiJbXt52k8qmJvn6VWjt21eaDQOOK7LOUNP1pKUZ26KiJEht3izTEAEMsq5autSYC1n18XaFvSA7dqwRZNWyZZAdN05+jxzdGKmpkaWVgyzA5sVEPsYgS0RE1maliqxZRIQERRVky8vlwluNIvzCC8DNNzt+fXKyLO01L66uBt5/33gcGencOamKrJrLVQVAT2hvLtmGBmDBAlmq4G2uSHekIqvC/uDBxrboaPkeFRcDl18u2xhknZebazsi+Jo1rh9Dfa979DD6ik+ZIgFW16UiGx3duq/r2LGydNS8WFVkQ0JcPydvYJAlsgQGWSIisq6aGrmotWKQ1TQJauaK7KBBwJVXAhMnAnfc0fZgNW0F2eXLJaBdfLE8Li527pzCwiQwqhFhPV2RBRwH2e++A156SdZbBtno6I5VZFWQV3ORAkaYiI4Gzj/f2MZw4Rz1e7dqFXDXXcDnn7t+E0BVZGtqpCIbGwsMGyaP1XRJ9vo/jxkjSzVQV0v+EmRffhl49FHfngtRN8YgS0RE1lVaKksrBllAgpq5j2xEBPD668D69RJ026IqlPbCw1dfSTPhv/1NHv/yl86f09ChEiQCA+2PBOwuZ4Ksoi70VZPSUaPa/3605c9/BlasMEYrBozfiXPPNQJPjx5SEab2ZWfLMjlZWg7U1srvrivU7255uQTZQYOMn3lurlRk7QXZyEjZ11FF1upNi9VNmRdeMP5GicjrGGSJiMi6/CHImiuykZHSX9CZaUPUoFGqb61ZcbEce8gQaaI5darz52SeHig42PnXtadfPxlx1lGQ/fZbWfbsCYwfL+vqgr+tUYmdER4OXHWVbRhWlVdzuA0KYpB1lgqySUlSIZ0+HfjrXyWUtjctFCDVyDfekPWKChmt2xxkT5xoe+RuNeCTPVavyKrf64YG+T1kKwAin2CQJSIi67J6kO3XT6pOy5cD339vhFNnhIVJ1VSNdmxWUmJMOeMqFWTNzXA9IShIqsSOguzGjcD8+UBVldGkWE2j0tY0RO5S1bzp023PkUHWOdnZ8vuqqudPPy2/y6NHy4jaqp+1Iw8/bKw3NckAYykpxs/62DHHTYsBCbKZmTJ42c03204B5C9BVnFmNG8i8jgGWSIisi6rB9nkZKnGXHedPHZ2UCZAqosREZ0XZEeNcu/1bXE0l2xxsfSXNI8qDADXXw9ccgnw0EOeP5clS2S0YvN7Msg6Lztbfp6qyj1litxcycmRx23N8woYzX7PO8/YNmiQ/E1omowmXVfn+CbGkCESgI8dk7mBL73UeM7qTYtDQowbAIBR3SYir2KQJSIi6yopkaX5otFK1PQ6jY2ydKUiC0jwtde0uCNBNjVVlqNHu/f6tgwcaP+iXc1bO3So7fa4OODDD43Bnzzp0kuBbdukqq0wyDovO1uaFZuZbxjl5zt+bW2tvP6PfzRu4gDy9xAWJpXZr7+WbY4qsuHhslTTM7U8PmDdiixgW5V1pik2EXkcgywREVlXQYEsOzLibWdqOU+sujh3VmRk64qsrncsyE6aBLz9NjB3rnuvb8vAgVKx03Xb7SrIDhvm+fd0BYOsc7KzgZ07W1fQzTeM1HQ6Zvv3y9/kwYNSTR02zLYVgvp7GD4c2LVL1h1VZNXUUPZujPhDkDVPJ3XwoPQvrqry3fkQdUMMskREZF15eVJxi4nx9ZnYZ57XFDAqyM6KiGhdkT15Eqivdz/Iahowb55nB3pSEhOl2WfLrzMzUwaCavn98DYGWeeokXbvvNN2uznI/vvf0u/ZbPhw6XttvnFhvnmjbmSMGGFsc1SRVUHWXjXT34LsihXA/ffb9vMlok7HIEtERNaVmyvNUgMs+nHVu7ftxb+rg77Yq8iqkGjF8K6+1ooKGdxn+nSZf/TZZ6WZqq+DR1CQVAqbmnx7Hva8/z6weLGvz0Ls2iVzHbfXtHjKFOOxqsIXFQEHDsj60KHGwF6PP278nQ4fbryuvYqsCrI9ehjPWb2PLGAE2fBw4++egz4ReVWQr0+AiIjIoby8zulf6UmDB0v4HDgQeOIJ114bEdG6aaUKsu5WZDuTqr5VVAA//znw00/A7NmyzTxYj68EnbqsaWy03s2PF16QuXYfesi2X68vlJTY/7uy1xdd16XKf/Kkse34cblpERMDxMZKGDWH4gsukEG+zjjD8VRULYOsObT6Q0VWdXeYMAFYt07WGWSJvIpBloiIrCs316j4WNUf/iAVwKuucv21bVVkrRhk1WBWBQUSYpUbb5R5RX1NBdmGBtsKn6/pOvDjj1JpPHDAGJDLV0pKbJv/KqoiO3u2zM+7aJH8DfbrJ6NSK2p+WDXiccvKblKSDPLVFnVTxF+D7OmnSzPrM85gkCXyEYvdriQiIjLxh4rs3LnuhVjA/qjFxcWytHKQVRfsqk/kLbcYocaXzBVZKzl61LhBoQZB8qXSUvtTWqmKbGysDBoGAPv2ybKoyNhPBdmOaKuPrGpabOUge/HFwO7dtiN1M8gSeRWDLBERWZOuS5C1ekW2I9RgT7ould033vCPiqyaa/TBB6WP7Bln+O6czMwVWSvJyDDWd+703XkA0nqgtNT+75cKslFRRj9Xe0FWVWk7QgXZujpZmkf8ra2V5tdBftBw0FyNZpAl8io/+B+CiIi6pZISGb3X6hXZjoiMlBC7aBHw5JOy7bHHZBkX57vzcqRlkE1IAGbN8t35tGS1IFtVJX0oo6OlYp2YCKxf7/7xduyQEKn6JbujslLCrL0gq6q0UVHS57tnT5mrF7ANsseOAWed5f45ANL0u0cP+RsHpA9uY6ME2Npaa1djzZKTjfWCAuCdd+R7l5cnPydHfYSJqMNYkSUiImvKy5NlVw6yKhiaB4n69ltg1CjjOStR/RpVkLXXPNWXrBZkN22SiuamTdIv9q67gK++Ataudf1Y33wDjBsHnHee/ea4zlIV/7aaFkdFyWBZF18swaymxjbIlpV1vCILGFVZRQ0oVVPjP0F24ED5vVOtEq66SkZ7vuwy+XkTUadhkCUiImtSgyBZLSx5knkkWGXNGuBnP/P+uTijZUXW3ii3vmS1IPvNN8Z6errM2xocDHzyievHWr3aWP/7390/p7aarpuDLADMny/7r15tO9gT4Jkga56DFpBqMSAVWStPvWPWsyfw9dfyPfr6a9tps8w/fyLyOAZZIiKyJnVR2/Jitytx1ETUqkE2JETCouoLyCDbtpZBNjRUpm0pKHD9WNu3A2PGSJX0o4/cP6fSUlnau0GktqnlzJnyM1692rYiC3i2IqtaXZiDrL9UZAFg2jS5MXDWWcDChcZ2NXAbEXUKBlkiIrKm7hBkR4+WpsRKSAhwxRUSVqxI06Qqq6pzVquWWy3IZmQAKSmyPnGiLBMSgPx814+1fbs0LZ42DcjKal0hdVZbFdkRI6RZ+/jx8jgoSPpAr1nTOsjam77HVWp0aTX6tb8GWbMhQ4z1/Hxphk1EnYJBloiIrKk7BFnAdlCnL74A3nvPmgM9Kap5cUCA9X42VgqyVVVSeb3lFmlyOnOmbHcnyBYVyQBL48YZfTE3bXLvvNqqyMbHy/zA5pB63nny3p99ZluBHzTIvfc3U90HWgbZmhr/aVrc0uDBto9ffx344APg6afl+0hEHsMgS0RE1tQdg2xsrO/Ow1nq5xEVZY25Y82sFGSzs2WZnCxNTtX3yp0g+9NPskxLk1GQAwNtK/nOWrcOuPFGWXd2eqeLL5abFoWFwLx5xnZP/OxbBtmNG2XZFSqy48bJ8q67gMsvlybH//2v786LqAtikCUiImvqLkE2OlqCCWA7UIxVqYqs1frHAtYNsmYJCVKp/fpr4JFHnDtWVpYsU1OlX+nUqcDHH7t2PvX1wE03yXqPHs6Pit23rzHVznXX2S47qqZGlirI/v73Etr9OchGRAAXXAAsWGC7/d13gfvv9805EXVRDLJdVWUl8P77xl1cIiJ/o4Jsz56+PY/OFhBgVGKdrZL5EoOsc9QUOfaC7MmTwDnnAIsXG2GuLZmZEj6TkuTxZZcBO3cCBw44fz5ZWbL/0qUy6nSAC5eADz4I/OpXwPTpwJ49wCuvOP9aZ0yaZKxnZPh302IA+N//gFtvNb6GZ54BrrzS4e7Hyo/hSGkHplQi6qYYZLuqp56S/zRnz5aJz4mI/E1lpYRYVa3syuLjJSAGB/v6TNqngqzVBnoCrBdkg4KA/v1ttyck2D5W1da2ZGZKn1T19V10kSw//9z581GDNaWktD6H9syaBbz6qjQnHjFCQrUnREbKMilJqrCBgRKU/bkia1ZbK8t2Bsa6+t2rcdOqm7xwQkRdC4NsV1RfbwzNf/y40eeE/MO77wKHD/v6LIh8r7Ky6zcrVuLi/KNZMWCEoJYBzQqsFmQHDGh9IyY+3vbxvn3tHysry2h+CwBDh8oNhV27nD8fNRWMlX7Ptm2T6qWmyU2coUOB3bu7TpDVdVmOHNnmbuHB4aisq/TCCRF1LQyyXU1xsXwY7NgBPPSQ3DX94ANfnxU5S9eBa64Blizx9ZkQ+VZamvwddJcgO2WK/PMHjz8uI9i+9JKvz6Q1KwXZ3Fz7c62qOVOVvXvbPs6hQ8D+/RLyFE2Tv5GdO50/H1WRtdKAYkOGSH9SZfBgYOVK6RZVX++78/KUxYtl2bJ5eQsMskTuYZDtanbsMNZvuknmKGzvQ5Kso6ZGLsAqKnx9JkS+pfr3d5cg++STwPLlvj4L58TFAeee6/xgQd5kpSBbVGQ/NLZsZtpeRfamm6Q6ecMNttvHjJGKrKr6tceKFdmWZsww1seM8d15eMrDD8vPp53+yC2DrK7rqG/sAkGeqJMxyHY1e/bI8uhR6U8TF+f+pOnkfSdPyrKSd2aJAHSfIEue4Q9BNjzctrnxBx+03U82N1fGuzjtNNvtaWkSTk+ccP58goKseQNCufdemWu1thb40598fTZeYw6yBVUFGPHCCFy0/CIfnxWR9THIdjV79siHVGKiPI6NZZD1J1VVtkui7s6fRy4l7/OHIAsYzYtfflkqdo89Bqxebb+6WldnfxAw1dT4iJOj3RYXSzXWanP/mgUHS9/r4GDjZ9kNmIPsi1texP6i/fjswGcoqS7x8ZkRWRuDbFeze7c0W1IfVHFxRr8Ysj5WZIlslZf7+gzIn1glyNbUyP/njoJsWpos09OB884DXn8duPBCYMuW1vs6CrLq2M5+xhcVWbtZcTcWHhyO2sZa1DfWI78qv3n72sNrfXdSRH6AQbar2bMHGDXKeBwbC5SUAI2NxrbsbOD0023705I1qCDLiiyRKC319RmQP7FKkG2vP+rrr0sV9rTTZGobxV4LKk8F2eJiaw30RM3Cg6ULRVV9Fcpqy5AYkYjw4HB8cfALH58ZkbUxyHYlZWUy3Y55mPe4OGmqVGJqnvL73wObNwPffuv9c6S2qQDLiiyRKGHTOnKBVYJseyME9+kDLFokgwCdd56xPT+/9b6OgmxcnO17OXNOrMhakgqylXWVKKspQ1zPOMxInoEvD33p4zMjsjYG2a5EDfRkDrLqQ1Td5d2wAVixQtZzc713buQcNi0msu0nyNYJ5Ap/CbJmgwYBBw/Kel5e6+cdBdnISPl6nR0HgxVZy7IJsrVliAqNwqxBs7CvaB9yynN8fHZE1sUg25WoIGtuWtzyju2jj8oE7TExzo90SN7DwZ6I5MJd+fxz350H+R9/DLIAkJIChIW5VpHVNPksd6Vpce/ezu1LXtWyIhsVEoWZg2cCAO799F40NHX897mqrgrZZdkdPg6RlTDIdiW7d8tcc4MGGdvUh+gPPwDLlgGbNgGXXw4MHMgga0WsyBLJQDkA8MwzwLRpvj0X8i/+GmQ1DUhIaB1kdR2or7cfZAHnB3RsaJAbpNHRzp0PeZW9iuyYhDG4a/JdeGf3O1h/ZH2H3+P0l09H8rPJHT4OkZUwyHYl+/YBw4bZzk+nKrK//a1Mql5ZKaMk9uvHIGtF5oqss5PcE3U1tbWyDAnx7XmQ//HXIAvYD7L19bJ0FGSdnWKvrEyWDLKWZK8iq2kabp1wKwCZW7YjSqpL8FPBTwCA4uri5u2NTY1o0ps6dGwiX2KQ7UqKi+WD0Cw+Xj7Yhw0ztqWnA337so+sFamKbFOTUZUi6m4YZMldVgmyO3bIfKhhYc6/xl6QVc3se/Sw/5rYWOcqsirIRkU5fz7kNSrIVtRWoLy2HFEh8nOK7Sk3QoqqOzaN4qp9q5rXDxQfaF6f/PJkpD6f2qFjE/kSg2xXUl4ugz+Y9ewJfPed7dx0o0ZJRTYvTwITWYe5b+wVVxgX9ETdibqJExrq2/Mg/2OFIKvrwLp1wJlnuva6toJsWxXZXbuABx5o+9hqGisGWUtSQTavKg+NeiOiQuXnFBMmo0wXnnRyQC8HduXval7PKs4CADTpTdh2YhsOlBxw9DIiy2OQ7UrsBVkAmDRJtn/4IfDww3Jx2K+ffNA/8YT3z5McUxVZAFizRvo2E3U3rMiSu6wQZA8ckK47M2a49joVZM3zvrcXZJW//KXtsRXYtNjSVJA9Vn4MAJorssGBwYgMiUTRSduKbHZZNr469BUA4GDJQcx6fRZWZ64GAJyoOIHLV1yOvEpjBOx9RfswuPdgAGgOrnsL93biV0TkHQyyXYmjIKtccgmweLGsT5ggy4cfZhNWK2k5WnEA/0SpG2KQJXdZIchu2iTLqVNde92IEdIndv9+Y1t7Qfb3vwcuvVTWv/rK8bHZtNjSevXoBQA4VnEqyIYaP6fYsNhWTYvHLRmHma/PRENTA748+CW+PPQlLvzvhWhsasTbP72ND/Z+gJe2vtQ8SvG+on1I75uO/hH9m4PsN9nfNB+vqo4zJZB/4lVyZ/H2QD26DlRUABERzu3/s58Br78u64cPd9ppkYvMFVlAbk4QdTdsWkzuskKQ3btXBl1MdbHvobrBPGoU8PTTst5ekE1NBd5+GwgPBz77zPGx2bTY0noE9kBIYIgRZENMQbZnrE3TYl3XUVojP8+s4qzm1wDSl/bLQ18CAB5Z+wjS/pmG/UX7cbDkIEbEjsDYPmPx8f6PcbTsKHbm7Wx+XcHJjg0mReQrDLKdQdeBsWPlLqm3qp01NfLB3VZFtqWhQ2WZldU550Sua1mRZZCl7ogVWXKXGrXfl0F2zx5g8GDXf39HjjTWFy6UpTNNi4ODpZrb8rO8thZYuhR45x02LfYDMWExOFhyEAAQHWr8nOJ6xjVXZA+WHETAYuPSfUfeDuSU5zQ/PlFxAuuOrGt+3NDUgAv/eyEamhowPG44nj3vWZysP4nH1z9u0zc2v8rO/MVEfoBBtjMcOSKDL6xaBbz4onfeUwUeV4LskCGyPMCO/pZQUQFkZtpuY5Cl7ogVWXKXpkmYra8HPv5YqqPrOz4Hp0v27rUNpc5S1WQASEqSZXvT75j3z842Hs+fL38/t90GXHWVMd6CK9cI5FV9wvs0h9LeYb2bt8eGxTb3kVX9YJXtudttKrI783eivLYcf5n1F6z71Tq8fMnLyCrOQlJUEuYMnYPhccNx/tDz8UnWJzhQcgBJUfJ7xiBL/opBtjPsNJprYOlS7zQzrqiQpSsfUvHx0hyJQdZ7GhqAW2+17QOl3HCDjC7dt6/R/ItBlrojVmSpI4KCgIwM4OKLJVCeeab3uvs0NMgNyREj3Hv9hg3AoEEypY6uOz/Ykwqyui6zEbz2mmy/5BJZfvcd0KuXbVgmS+kb3rd5PTEisXk9NsxoWrz28FpEBEdgxdwVGB0/Gjvyd+BY+TEM6S2Fif1Fcm2REp2CGckz8Isxv8A7897BhvkbEN8rHgBw/pDzcbT8KPYX7cfpiacD6Pg8tUS+wiDbGVSQ/etf5c7sXi+MDKcCj7N9ZAG5cz1kCIOsN23aBPzrX8Att8hjXQeeekqCrRqoIzdX5gQGGGSpe2KQpY4ICpLp5cxaPu4sR49K+HS1f6wybRpw553SzaS42LUgW1UFlJQAB6V5Kl55BXjjDVk/dIjNii2uT68+AKR/bESIcS0X1zMOFXUVqG2oxboj63D5yMtx1eirMK7vuOamxaf1Ow2ADOoEGNP2AMDcUXObK68AcMGwC5rXzxhwBgBWZMl/Mch2hp07geRk4HS504WjRzv/Pd1pWgwwyHqbmh5BXZQcOAA8+KCMHh0uw+9jyRIZrTgigkG2O3v6aWDrVl+fhW+waTF1RFCQBDoA+NOfZOmtQQ0LTlW2+vZte7+2JCfLMjvbtSCrXrN9u6yPHSufIwMGyGMO9GRpqiI7IHKAzfaEXgkApBpbeLIQZ6ecDQAYmzAW2WXZKKkpwdiEsdCgYV+hBFlz0+SWEiMTm4PuiLgRCAsK42BP5LcYZDvDzp3AmDHGh0dOTtv7e0JHguyhQ7bz1lHnUT+nXjLUPjZulOUHHwDHjgGPPSZ9mgAG2e6srk4Ge5k40biQ7U5YkaWOCAoyWrWMHSvLQ4e8894qyMbFuX8MFUqPHHEvyO7YITdDR4+WbYNl/lAGWWtzFGTV9uW7lgMAzko5CwAwts/Y5n2GxAxBTFiM3YqsPf/7xf8wrs84nJ54OvpH9MeRsiMAJCwv+3FZx78YIi9hkPW0ujpg3z4Jsv37yzZvBFl3+sgCMnJxXZ39c6yokGH9i4paP+eKsjLgp586doyuIv9U8x1Vfd20SS661MWKGkkakJ/lTz9xeqTuSFWTAGD1asf7dVUMstQRQUHGdDNjxsjSW/+PFp6aJqUjQVZVZA8fdj7IpqTIctcu4D//kal8wsJk25lnyvLXv3b/nKjTqabFjoLsW7veQkp0ClKiUwAA4/qOa97n4tSLkdArATUN0pqlvSB7xoAzkHF7BmJ7xmJsn7HIyM0AAJz977Nx06qbPPL1EHkDg6yn7dsngz2MGSMfPAkJUmnrbO70kQXaHrl46VLg6qtl4Il161o/76zZs4G0NO/PrWtFqp+WajK5aRMwdSowaZI8Vj8PQILsxo3y/afuRVWTAKnKdCdvvAHcfbess2kxucM8oFG/fjKwobcqsirIxse7f4y4OKmeZmY6H2Tj4+Wz4qGH5Gv9y1+M5xYtkmD/y1+6f07U6dqryNY21uJnA3/WvL1feD+M7TMWi6YvQkRIRPNgToFaICKCnb8WHN9vPLKKs1BRW9G8ra6xG7YEIr/EIOtpaqCntDRZDhhg/abFgP0gu22bLKOjpcmruzZvluXJk+4fo6tQQVb1AczJkSrsb38LxMTYjnTp6k0J6jrMrSCOH/fdefjC//2fsc6KLLlDzSUbEAD07CnVSm/2ke3Ro2P/f2uaDBa1f7/zQRYAzjlHlpMnA2edZWwPDmazYj/QP0Ja8ZkHZgJkWh5lRKxxjaBpGrbfvh2PnSPXZwMjBwKQ/rGapjn9vqf1lYGitudtb952ouKEi2dP5BsMsp62c6fcDR4+XB57K8gWFMiHt2pK5KyBA+VDt+VE6oBMX3DJJfKh6ImLaXOVqbtSTYvVoE8lJUDv3sA118jP0HzxoyawN7NX1d6+3TsjY/uTf/0LeP55X5+F+8x/K90tyJorWZwqhNyhfm8iIiQU9uvnvVGLCwuloupCkLBr+HDXg6xq2aOm3CG/khqbiuVXLsfVo6+22R4aZLRMGR433OHrR8dLn+igANf+31QjHm/PNYKseW5aIitjkPW0rCwZWEF96HRmkN25E9izRwLPa68BM2e6/uEZGCgffh99ZBuSTp6UcJSeLhcBJzpwd65nT1ma+/11V+piqqpKqrI1NRJkAakemJkrCLoOvPCC7FNVZbtferrMlUiGZctsK3v+RgXZvn27X5Dt7Xi0TSKnqCCrWiglJBg3ETubCrIdlZoqAzepvr7OBNn582XU+/vu6/j7k9dpmoafp/0cvYJ7OdxneGwbQTZBgmxuZa5L79svvB/Cg8Ob56AFgGPlDLLkH9oNspqmzbGz7fbOOZ0u4PBh2z6N8fFyUdoZowJPnQqMGgXMmCHv8cQT7h1n/nwJxKoJMCCDDDU1AePGycV0aanRHNZVqkrMiqxtkFXB3tGFe329sV5VJVVGAFi71v7+HbnZ0NUUF8vfoqp8+xv1t5KW1v2CbMsbNUSuMldkAQmyBQXymdbZCgs71j9WUSIaG9UAACAASURBVPPQqoESnQmywcEy6j2b5HdZQ2OGOnxOVWRdpWkahsUMQ2ZxZvM2VmTJXzhTkX1Y07Rz1ANN0x4AcGnnnZKfO3zYGD0QMCYgr6iwt7f7dN045pEjMkDKhAnuHWvePFl+/rmxTU2onpoqFVkAyHXtLl8zVZFlkDXCqzNB9quvjD6zJSXG6Jsff2zsYw67n3zi2XP1Z6qP6e7dvj0PR6qrgSlTgG++sf98cbG0lhgxovsFWf4/QR2lBgkzV2QbG43qZmcqKPBMRfY0ae6JDRtk6UyQpS6rX7hch7VVrR3U2/2BIYfFDrPpI8uKLPkLZ4LsJQCe0DRtuqZpfwYw+dQ2aqm4WO7GmoOsGmDB0x+gqpnU3/4mIecXv3D/WFFRMujTli3GyI5qmZJiTOzOINtxasCrysr2g+z48cYgWyUlRqXq3XeNdXO/LzU4V3fX1GR8b3ft8u25OLJ3r4xI7WgU0aIi+b1ITJSB3Py1suyO4mKZnur//T9fnwn5KzVvqqrIqgqpN5oXeyrIDhsmN5HV+AcMst3ajjt2IOtOO2OZmARoAVh60VJsmL/B5eMPixmG4xXGTVNWZMlftBtkdV0vhATXFwD0BzBX1/X6tl/VDX33HRAbK+v2KrL2Bu7pCDXK8LBhHR9UApAmxB9+KBcAJSUSZOPi5IJSVWTdbbrKPrKiqcmYH9OZiqz5uZISucAPCpKbJf/8p2w331zgfLOirMxoQmjVIKtu6mRnO34+Nlb62APS/H/xYu+cm68VF0vAZz8/cpcabFFVZhMSZJmfLzf/3nmnc7r7lJXJ/9VqHtiO0DRjFGJABmWkbiuuZxyGxAxpd79bJtyCaUnTXD5+yybLRdVF+OLgF4h4MgJlNR6+fiXyIIdBVtO0Ck3TyjVNqwCQBSAVwDwA5ZqmlXvrBP3GaFPfBG9UZFWQHdL+f2xOGTXKWF+/XoKs6uurKrJXXOFeMFBTIXT3iqy5j7GzQTbm1KTmKshedJH0jf7vf2W7urmQmOi9eRKtzvx7ZtUga66kNzYC999v3JwA5GuIiTH+Lt99F3jkEe+eoy/ouvG1E7lLdckoKJClCrIFBXKD5KqrgF/9qv3jfPQRcPSoBGBz1xtH1OfyUMf9GF0ydaqxrj5HiTrByDjbASNLqkvw2PrHUFlXia0ntvrorIja5zDI6roeoet6pGkZqut6uHrszZP0C1FRwB13yLr5Q0xVZD0dZLOy5I7tIPf7RNhQ/S8B4Oqr5UNbHVtdBADAp5+6fmxVhezuQba6WpaRkRJk1ffDmYpscbH8690buPhimRrp2DEjyE6ZIhVZe9PzdDeqf2xcnH8E2fvuA/76V+DXvzb6PxcVSZgbObL1aNb+5qGHpOXITTcBX3zR9r6VlUBDA4MsdYyqyKr+5app8ZEj0vIIkL+1tv6/fO45mcbmlltknu/Zs4Fvv3W8/5YtwD33yLqngixHoycvGdtnbPP6oOhBKKkpQXhwOACgsq4bdW0hv+PMqMWXa5oWZXocrWnaZZ17Wn7qhRckXJj7x6iKrKebFufkSKXUU6MTzpsH/PADMH26ETz7nJqEOzDQ+PBXd5xdoSqR3SnIfv+9McqwooJsXJxcQKkQqm522GNuWlxSIhf4F1wg2z75xDjG6adL/9vCQs99Df5K/Z5Nny7fHyv+3qkg26sX8Oyz0h86MhJYtcp4PiFBRvxWo5f6qyeekBtvy5ZJJUzTHM/pqX5WDLLUESrIqu4+6jP5zTdlkMRLLpGby47Gfdi+Hfjd72R9xw6jtcvDDzt+z0svNQZmUn10O2q446lWiDwprEdY83pKdApKa0rRq4cMLFVV53gk+cOlh/F/3/vxVHfk95y51f+IruvNKUzX9VIA3aCNmxs0Dejf33abuxXZ118HXnnF8fOlpZ6db1HTgIkTZT7aTz4Bbr/dtunVJZcAkycDmZmOjuBYdwyyP/sZcOutttvMQRaQmx4REcZUEfZEREhFLjdXgmpMjEzJMnAgsHq19LGMizPCDvvJGhXZGTNkqaavsJK8POn/umCBDOLy73/L39eWLdK/Nz/fuJFkbi1RV+eb8/UU1Zx+/377z6ufHYMsdURkpPSDVTdge/SQsR62bTOmqAEcj2r+4otyE+nRR+Vm2Pffy/aMDMfv2cs0mmx4eMe/BsDo1kPkRYOiB6GkuqR5hOS2KrJv7XoLv/vsdyiu7kbXd2QpzgRZe/u0ceVNNtypyBYWAjfcANx8s+N9ysqMY3vS4MHA+efLB/n48bbPpaY6vgBtiwqyu3d376avKsiqZm5vvNH+9yMgQG5YZJ0arTAmRm46XHAB8NlnUsGbMcMIsmvWdM65+xN1w0QFWSs2L1YV16eekuaOaWnApEnAzp1y4dzQYATZ6683XuePA6bZC6Wq72JLrMiSp8ydKzf8lLPPlmV6ujG1Tcsgq+tyI3fHDhkA8corjeeSk42xCuxR4dWTgzJ5YiBHIietmLsCw2OHY2jMUDTqxmBoVfWOK7Iq5LL5MfmKM0F2i6Zp/6dp2hBN0wZrmvY3AOz57aygILlT215FtqpKwsiyZfJP2bNHPoxnzLAdZbGzgmxbUlOlAqgCmbNqauR7kJvrXkXXn5nneVXfNzUlBOB4+hWzvn2NqqK6wL/wQvmdKSyUQbhGjJCLrsceA/74R8+cu79SVb2xY6UyY9Ug26eP3KhQVZdJkyTAqpGKVZC96CJg+XJZ91WrhpIS90d5tTdtiKO5cVXTeE9MX0JkNnOmLMPC5G+ud2+5cWT23Xdyk/D776V/6qhR8v8IIP/PAsZNxZaOH5fXerpVjDmME3Wiq0Zfhb2/2Yv4XnKzva5RWgC1FVJVs2MGWfIVZ4LsnQDqAKwA8A6AGgC/7syT6nKio9sPss8+KyHv6aeN/jgBAdJ8NCdH+t4cPWrs74sgq/r9HDni2utqaoDzzpP1tWs9ekqWZ57/UwVZ1e/prbeAJUvaP0ZionEDwBxkf/c7GS37ootk29KlwKxZEmYdVby6uoYG4P33ZbCVoCCpdFo5yJrNmSPNixVzs0L1c/dFkK2qkvf//e9df62uy42F+HjggQeM7Qyy5G0XXihTwf3hD1LpnDJFutLMmSPdPADb/69HjpT91q6Vz+f582W7vSDb0CDdASZObN29qKN273bcp5yoE/QOlW5ratqd0hrH16+qWssgS77izDyyVbquLwRwDoAzdV1/UNd1x+0MqLWoqPabFn/wgSxDQ43mg01NtqMEmz9AfRFk1cAZrjRvbGyUquSYMXIHfNu2zjk3q6qoMNZVkD3vPLnoufpq546RmGisq2bJAQEy0u2uXcbvQUwMsGiRrH/zTcfO2199/LFUWZ54Qh6rIGu1Ju1qnliz0FBpbq6Yg64vg6z6HTa3FHHltfX1EoKffBJYuVK+LkdBln1kqbP06SM3ZWbPlsfnny+/m2vWGONRmP++1A3H3r2Bu+825my316ooL0/+j1FzrntSeLjtzAFEnax3mATZ/Kp8ADIVjyMMsuRrzoxaPEbTtB8B7ATwk6ZpWzVNS+v8U+tCnKnIqjvB+/bZjjz7+efAhAmy7usg687AVWoE5LAwuTg1B7vuoLLS6COsgmzPnkYgdYb5Dn97I9hOnCiBSI2e2d2oVguqP1xamlycWqmiUV8vvwv2Rqs2j3ZqDrLmaZi8Tf3enjzp+mtVMI2NlRBw2WXS17Ctimx0dNsDoBF5wvnnG+tqWijz31dai8uc0FBp5mtv5H41enxnBFkiL4sOlc+mgpPSsqu01vE1H/vIkq8507T4JQD36rqerOt6MoDfAVjqiTfXNO18TdP2aZqWpWnaQk8c05L695e7uG1VhVSQra0FfvxRgp9yySXyIaqCbG2t/POHIKtCXGio9A3tbkH2hx/kZ7l8uREIzD9bZ6iKbGho+68NDpYbH1u2uH6uXYG6EFW/q2pQFzXqqBWo1hn2/n4DA41186jkvm5aDLg3YrI5yCr9+xsX/vb2Z7Ni8oZhw4CPPgJ+8xuZH7ay0vh9PXECSEpq/ZqkJNsuPoq6MePpZsVEPqCaFjtVkT3VR7aitptd25FlOBNke+m6/rV6oOv6WgC9HO/uHE3TAgG8AGAOgFEArtE0bVRHj2tJs2bJIEl79jjep6pKqmmAXKyOGGE8N2UKMGSIEWTbuhDuTOYgW1UlTZ/boyqyoaHSRKrSxbt2VVW2Ayb5i9BQWX71lSw/+sioaLkbZCMjndu/Tx//HN3WE4qL5e9CVfQmT5aBxlTFxQrUjSBHf79Dh8oywPTfc1SUVDR9EWTdqcQq9vq8JiZKc297fW4LCxlkyXsuukg+X5uaJKAWF8v/s46mvRkwwH6QVdvM3UCI/JRqWnyyXv7vZx9ZsjJnguxBTdMe1jQt5dS/RQAOeeC9JwPI0nX9oK7rdQDeAnCpB45rPXPmyPKTTxzvU1VljI4I2E6EfsYZcnGr+ub4OsiWlEilKylJ+nq2paMV2fBwaY7ob1SQVRfyoaHuV2TVRZWzQTYiAigvd+09uoriYtv+lcHBwFlnSRN9q1B/v/aaFgPA1q0ywJuZmobJ34KsvYrsPffI8ssvW+9fWNi67zBRZ1Lh85VXpI99W/2zBw6Uv01z66qsLBlVvmdPNi2mLiEyxPZao6Sm/Yosgyz5ijNB9kYA8QDeP/UvDsCvPPDeiQDMtzZzTm2zoWnarZqmbdE0bUuBv47EmpRkVCHsqa+XZnvJycZUFYMGGc9HREiFNjNT9vVVkA0NBUJCZDCdzEwZ6fFf/2r7NeYga67IHjwoF+xtURXf1as7dt6+0DLIhoW5H2RTUmT5m984t39kZPdrwq0UFbUOQlOmyO+rq9NGdZb2/n4jI+1XdmJi/C/IqhHYzYPVDB0KXHut/VYDbFpM3qb+1p55Rvq/tnUjZeBAaWWkrkXeeEOaKL/4ojEYFJGfC9ACEBRgjFNwvOI4ymvt3xxnH1nyNWeC7Cxd1+/SdX38qX/3ADjXA+9t73/8Vp1IdV1fquv6RF3XJ8a7MkCO1cTEOG7uqfqghYcbVZqYGKnK3n23PB41SkLsgQO+C7KAnJ+5mWZ7fQ8dVWRvuUUG22hocPxaX82Z6QkqrKogGxLifpBNSJAbAHfd5dz+qiJrtZF6vaFlRRYwLkxd6dvdmdz9+7VCkHWmO4Gi69I3/Gc/s+3vCzgeAI9Ni8nbWt40avm7aqbmdFVNiZ980nhu2DDPnheRD4UEhjSv1zXWYeWelXb3Y9Ni8jVnguyDTm5zVQ4A80zfAwA4GMqyC1AXofv2yVyx5pBhDrLh4bLeuzewd6/MXwdIkAVkTrn2miZ2puhoudjs0QP45S+BjRvtB6amJgmvC0+N4WWuyJaXA+vXy3HWr3f8Xv5agQccNy0ODrbt++isXr2cv9sfGSnTHlmlAulN9oKsujC1Sr/h9vrIOmKFIOvKzYBdu+T/q+uvb/1cdLT8P2YOxtXV8l5sWkze1PLGYlutWVoGWfMMAwMHtt6fyE+FBEmQHR0/GinRKVjx0wq7+5mbFh8tO4rQx0Px44kfvXaeRA6vqDVNm6Np2vMAEjVNe8707zUAbZTRnPYDgGGapg3SNC0YwM8BrPLAca2pd2+5kP7HPyTcmQeMUEG2Vy/bIGumBn/69lvgyitl3VcVWQAYN076HhYV2R/E6vBhaYL12Wfy2FyR/eILoxKr5s+1x5+DbMipu5mqr6qmyYW6q9VYd6i+tN2xebG9IGsepCw3Fzj33NZ9UL3J3RtR7QVZXQcWLAC+/trxPvbk5bU9IrE5yJov3Nuj/l+YMqX1c717S4g1/46q/rSsyJIvtfV/w4ABxj66bvv/jeoWRNQFqIpscGAwLhp2EdYdWYe6RtvPiSa9qXlAqMr6ShwsOYjaxlrsK9rn9fOl7qut0tBxAFsA1ADYavq3CsB5HX1jXdcbAPwGwKcA9gB4W9f1nzp6XMtSQXbTJnm8bZssf/zR6DdqDrItB/YJD5e+ki+/LI+HDfPNCInq4nvSJOCCC6Qy+9JLxvOqOrtjh+3rVEW2qQnYvFm2jRljOzduS/4cZBsbbR/X1novyEZEyLK7DfjU1CR/Yy0reuYg+/zzciPlxRe9f36KCrLODt6ltBdk9+6Vr8vc3LE9J0/KYGKqC4OjfRQVetVo5G1RN+vsVarsTeVlb4RjIm9TswfYExcnLWry8uQmTEMDcO+9cnPa3ijcRH5KVWR7BPbAzMEzcbL+JDbmbLTZp7q+GvqpHoEVtRWoqKtoXifyFodBVtf17bqu/xvAUF3X/31qfRVkpGGPtNHTdX21ruupuq4P0XX9z544pmX17i1z02VkyOMffwTWrgXGjwcee0y29eplXIS3DEKA7FteLh+kGRkSIr3NHGT79wd+/nMZ7bG+XgJCQICE2O3bbV+nKrKAzLnXs6cE8bbCqvm5f/3L/vfEqlr2/a2pYUW2s5WXS5htq2mxmu/R1WmgPKmsTG7qmOeMdUZMjAQ/R38Ha9bI8quvjFBYXy+DhLW8saSopv3qtfaoFiOaBjz6qPzd3nJL++d79Kj8n2av8mweAV1R58ymxeRt99wjN4d37AD+8x/H+wUGAvHxMlq/akHQv7/cPGprtGMiP6Mqsj0CeuCslLMQoAVg7eG1zc+XVJegqLqo+XFlXWVzgHU0MBRRZ3Cms97nmqZFapoWA2A7gFc1Tfu/Tj6vrkc1pVNzom7bJmEWMJrXhodLReX224Gzz259DHWneNgwCYK+YA6ygMzTWVUlF6SXXy7bNm2SC4LkZOPDPSrKqDYfPy6hNiGh7el7zEH21ltlhEh/0XLuW29WZFWQ7W4VWXVh2VbTYtUiwtEI4t5QWupetwD1dTnqp/rpp3Lcxkb5P6WqSm6WvfCCdAW4/nrb/uyvvGJMDZaa6vh9T56Um2a/+pVMmVNU5Fzz5aNHZcR2e3271c0F89fCpsXkK3/7G7B/v7QSUjdcHVGfW6p1BG+8UBcUHChN5XsE9kB0aDT6hffD4dLDzc/H/CUGY180poysrKs0KrJ13ewmOvmUM0E2Stf1cgBXAHhV1/UJAGZ17ml1QeY+r9OmAT/8YDQvVnr1kmrHiy/a72+jwqN5vllvGzpU5sobOVIeq6/r4EGjylVYKM0cTztNpuj59ltpFq0uEE6ckPX4eAmrjkbX/f/t3Xd4nNWZ/vH7qMuyZEmuko0bNqYYm2KKKaaGjilLS2ADCckCy4bALwtLNoRsgOyGkpCEDaEsEGADIYQECAQIG8CQAMZ0Yww2GPduy1bv5/fHmXfemdGMNJKm6/u5Ll3vzDtFR/ZYnnue55wTWa1dn0VrgcWqyKbiA4ih2locumhaKC/Irlvnz9v84IP+req8bVvvlZr+2LlzYAu1eUE2VnvxsmXSySdLu+7qKqZVVdJxx/m3P/yw+95tbe5nf+AB/7beqvfNze51e8strjPixhvdHMG+5suuWRN7ARxai5GtxoxxrcWxPjgDckCwtTjPdf6NHT5Wm5o2hd1nZ5ubJmNkwiqytBYjleIJsgXGmBpJ50h6JsnjyV2hQfa889x/hE884a9uK7kg25s5c9wiQl6gTYerrnIrL3ttkd5/4itW+PdZu9Yt9jRlivv5DjnEnQ+tyFZUuDcELS1+AIkUGWS9uYXZIFqQ3bq1960dEmWothZ7VfDIlvuiIhfElgSm4B90kHsTGrrgWl9OP91VNFetGvw4d+4cXEU2WpC11n1AVFMjnXaaOxfaFeCF8JUr3b/Jm25y//a8ue69dUY0N7vfTaNGSd/4hnTwwe78e+/17DwIFU+QDW0tJhggG3gVWe/1SkUWOSjYWpwfCLJlY7Wp0QXZ1s7WsPvWltdqS/OWYCWW1mKkUjxB9ga5BZk+s9YuMsZMlbQ8ucPKQaEB5vDD3bGlRTrrLP98X0G2slJavDj+/USTIT8/vPUqtCLree899+Z38uTwx3qP27HDby2WwgPrjh0uLFjbc17fF18k5EdIic7O8L/P1lY/3CfbUK3Ixgqykvu38/HH7rK36vff/x7/c//tb+64cuWAhxe0bdvA3vz2FmR37nSvsZoat/DMTTf5oXvWLP/f2ttvu+P117sK9ezZrq1406aez+nxKrKeffZxx+98xwXyP/yh52Pa2twK0bGCbLTW4q1b3d9TQUHssQDpNnYsrcXIeb1VZOtawpfJ2bdmX21u2qzNTe4DUVqLkUp9Bllr7ePW2lnW2n8OXF9hrf2H5A8tx3hvQouLpb328s97Cz1JPVsio5k+3d/aJRN4b0i9kFlSIr3xhrscGdpCfz6vtVgKrwZNn+4C8DXXuODhzbuVpM8/T+jQk6qzUzr6aP/61q0usEeG+2QYqnNkvSp4tCBUWemvkH388e7199pr8T3vNn9Bi4R8mLJ16+CCrDeeri5XJZ43zw+o48a5f1ff+56bn/q3v0l//nPPICu5f3fjx7vbGhvDVycOFRlkR46ULr7YfagmSRde2HMV43Xr3DFWkK2ocHNnIxd7IhQg040Z47pdvNd4KrpsgBSLrMiOGTZGm5s2y1qr7S3uQ5yrD7laT577pM7b6zxJ0uLN7v8EKrJIpXgqskgEr0o2Zoyrav7v/0ovvhgebNK1gNNgeG+uvTf4oSE9VkVW8luLJT/Idnb68+Ruu83d59JL/cdkW5CdMsV9UFFe7tqxpdQE2dJS9xqjtdgX+mZzwgS3t6kXZDdt6n2+7G9+419ORJDdtm1g80DHjXPHDRvc8eOPXcvwa69Jd97pztXUhD/m0EP9sCqFB1lrw2+LtYJ4ZJCV3JZbzzzj5tk2Nkpvhm/L0OvWO5Jb3XzkSH/OcmfnwP9cgFTy/r0sXer+j0rH7gFAkkWryLZ3tWtH6w7VtboPII/b9Tidtvtpmlo1VZL04SbXRUdFFqlEkE2ViRNdJfX2293188+Xjo1YMysvC/86vLluXmvxzJn+bZGhLbTaElqR9d5AR1aETj/df/MuuTbE3vadzSSdna4yeN11bnEvr/KUitZiY9wbrGyaU5wIfbUWS+7fYFWVC7Iff+y2nxk3TnrkkejP2d3t/s0edpgLZYMNss3NbkrBQCqPI0a4n8Nrb/ZWYJakP/7RHSODrMf7t/bOO+HnQ4NsrHmy0YJsfr5bWOr4493vrZdecs9dUSGdfbZ05JHufhMnxv55vvY1t07AAQe43xUrVhBkkfnGjnXHN98M//8JyCHR5shK0qamTcGKbHWpK2RMqXLva7xKLBVZpFLM5GSM+XbgeGjqhpPDhg93c9j+Ice6sgsL3c/mzcc74gh3HDGi5zYG5eX+uWitxZFB9pRT/NWbd93VHZ9+OrHjT5aODr/FNXRBr1RUZCVXKQ9tiR0Keguyu+/ujl5L6/77u5B6663u/IIF0Z9z3ToXHM8/330I8dlnPRfyild9vXTPPe7yQAPblCl+mF640IXyiy7yb4/1xrqw0O+eCL3PhAn+G/NY82SbmmJ3i1RWui247r7b/WwNDdLvf+/fHqsiK7npAzU1rkq8bp37s+0t+AKZYO+93XHjRumYY9I7FiBJolVkJWlTox9kq0pcp9PYsrEqKfDf57BqMVKptxLg1wLHO1IxkCFt5cr45+tlIu8Ncl6emy/3/vuu0hWN96a5osIthlRW5ldkvdWLb7/dbfVxxhnSjBnSL37h5t3uvbf0pz8l92dJFK8iK/lBtrjYr34lm7e10VDS2xzZE05wR+/PZP/93fGZwELsra09HyP5H9BMmeLmb7/xhmvd/vWv+z+2PfZwq35LA58LOnmyX5F94w23AnPoh2O9bevjvfamTHFzXCW317M3lljb+kSryIa69143R9YL6aF6e9yoUW4/30cf9f/O/u3fYt8fyASTJvmXTz45feMAkihYkQ0E2XHD3QegS7cu7VGRNcZoSqXfbUZFFqnUW5BdaoxZKWmGMebDkK/FxpgPe3kc+mvSJNe6mK28+YcjRrgwO3t27L1uQyuykgtckRXZCROkq692b26Nkb71LXe/mTPd1j6Zzlq3EI9XGfSC7NixqWsfH4pBtreKrLdSuKe21v9QRfLnMEdavdodJ06U/vM/pfvuc1XGBx/s39j+8pfwfZAHU5FdudJVZZcscRWhU05xYXbePPfvJZaWFnecOtWFzjVr/HZlKXzhpVDbtvW+oM3Mma5VeyCqqtx2ZB9+6FaRDg0JQKZ65hm3Hd5RR6V7JEBSRLYW7z5qd82pnaOrX7xay7YtU77JV0VxRfD+s8fNDl5mjixSKea7amvtlyUdLOkzSaeGfJ0SOAKO9yY3ntUbvRV1Qxe/iqzIxtqGqLi45+qomairyx29KpO3ynSqqrGSH2SHUntxb0G2uFh6/PHweaU33iide65rjf300+gLPnkV2YkT3d/f178unXOOWw24P6tC//GPfpu8NLiKbEuLC6OSm0cuuZ/tlVd6f+wJJ7i5rd//vvtAZcIEd763INvS4hZg661FWHIfXg3GHnv4+00Dme7kk6VFi7JzgUYgDpGtxQV5BbrtS7epsb1Rf/n8L6oqrZIJ+eB0v3H7BS+3d7WrrTML3qshJ/RaHrLWbrTWzpa0QVJ54Gu9tXZVKgaHLOG9KR8xou/7egHW24onWkU21puDbAmykS2uXkXWmxOcCqNHuwrgqFE9F/jJVV6QjbUP6VlnudDq+eY3pd/+VvrKV9zCWNEWO1q1yv0Zhn64cuKJ7u/4scfiH9vTT0tnnulfH2hFdj//zYIOOkiaNs1dNqb3aqwk/fKX7t/YjBnh5/Pz3QdMoXu6dnS4cOx1QHihN5bIDowzzpCeeqr3xwAAMlJkRVaS9hy9pyTpix1fBNuKPfvX7h92naosUqXPPkdjzBGSlkv6paQ7JS0zxsxL9sCQRbzVl72Vi3vjBVkvkOZiRTZWkE11RdazbFnqvm86eX/u/d0OY0/3n7M+/rjnbatWelLvEgAAIABJREFU9Wx3Pfxwt63NtdfGt8VRV5cLyXvs4Z+rro59/94ceqiby9reHnuBqljy88OrwqEqK8Mrsnfc4SrPt93mrvdVkfX+DD133inNn9+/8QEAMoJXkc0zfkwYNWxUMMBOqAj/cHOfcfuEXV+9c3WSRwg48UzY+6mk46y1R1hr50k6XtLtyR0Wssp5bjPsuEKmVw0KrVJu3uzaOnOlIhtZGfRai1O5tUgqq7+ZorfW4t54q5AuXtzzttWre66km5fnVtzdvt3NU+2L95otKZG+9z3Xgh+rahyPqir3M3qvq0SoqgoPst7CT8895459VWRnz3b7Yj/zjAvAofOPAQBZxWsptiFTbowxGlHsOu++NPVLYfevLq3WgosWaNE3F0mS3l7/toBUiCfIFlprgyuhWGuXSWIHcPgqK6Unn4xv5eV//3fpgQdcm6fkqpTt7W6+YbwVWWvd/Z98MjHjT7TIiqx3vaIi+v2TITTIxlqNNtcMNMiOHeva4z/6qOdtW7dGr6R7c1RXxTHLwlsRuaREuummzPz7iAyy3p/lmjXuOH58389x7LFu7uBjj/Xd5gwAyFheJbbbdoed39LsOuhOmHZCj8fMmzRP+9fsr+rSai1atyj5gwQUX5B92xhznzHmyMDXvZKGyKQ7xO2009wqjn0pLHT7Xnqr93ohYcuW+Cqy1rpgeNFFbh5ePO3MqRbZ4uq1nxJkk6uvObKxGONW3v3oI7f9y7PPuvPWunmj0ba08dqNva1wehMaZDNVVVX4HNnQFZarqmJ/uAQAyDmxguxjZz2ms/Y8S7PGRt+ZwhijObVztGg9QRapEU+QvUzSEklXSPq2pI8lXZrMQWEI8QLX5s3xVWQlV5V9O9C2EvqGu60t+oI9qRZZkfVWt01lkA1dFXeoBNmBzpGVXHvxhx+6OaEPPeTOtba6boFoq3GXl7vz/a3IZqrIObKh/6523z314wEApI23InFkkD1p+kl6/OzHw+bORjp2yrH6YNMHWrh2Ycz7AInSZ5C11rZZa39qrT3TWnuGtfZ2a20WTFREVohWkY31hj80yHp7Yq4OWVDga19zbaLe9jfpkglBdsoUt0VMTc3Q2YJnoK3FkqvINjVJ3d3SZ5+5c16FMlpFVnJb4eRSRTYyyJ50kpsu4M2TBQAMCUbRg2w8Lp1zqUYNG6VbX7810cMCeoinIgskT2hFtrnZtRXnxXhZRguy3hw+yd/u49NPlVaRQfaHP5T231/60pdiPyYZDj3UBdmhUpEdaGux5IKs5913peuv919bsYLspEm5U5GtqnL//trb3fV169zWPocdFt+2WgCAnBGrtTge5cXlmjdpnj7eEmUnACDBCLJILy/IbtniKmK9bTDvBdnQNuTQiuyuu7rju+8mfpz9ERlkZ850rdDpCATV1UMnyHZ2ug9BYn0Q0pvQICtJN97oKvxS7CA7cWL4BymxeEE2kasMJ5r3M+7Y4eZ0NzRItbXpHRMAIC0GE2QlaWLFRK3euTps1WMgGeJ+x2eMYbUPJF5JiWu59SqyvS0q4wWB0C1PQoOs98Y73UF2MJXBRBtKQbajY2BtxZL7kCFyr1RvX9loc2QlF/4aGlw7cm+yoSLrbTH01lvSF1+EnwMADCmDDbKTKiepqaNJ21uGyPsPpE2fQdYYc4gx5mNJSwPXZxtj7kz6yDB0eHvJxluR3eKWf9eIEeFB1ptj+8EHyRlnvCIrsulUXT205sgONMhKbk7ooYf2PB+rIlte7o5ed0As2RBkTzzRBfnbbvM/KIqsUgMAhgQvyFoNrKI6cYT7IHT1Tvce7fnPntfjSx5PzOCAEPG8075d0vGSnpYka+0Hxph5SR0VhpYxY1w4LSqKryK7c6c7Tp4sbdzo3+4tqpTuCuRgVs9NtJEj3Z9Hd/fAWm6zSUfH4D48uOsud3ziCfchiTenOVaQHT7cHRsb/VAbTVtgbbxMDrKFhdLll0vXXuvmVRcUSDNmpHtUAIA0CAbZAbYGTxrhtqhbtXOV9q3ZVyf+5kT3fHvRaozEiuudrbU2ciJYmpeFRU7pb0XWW022utqvdkl+kPUqs+mSSRXZ8eNdiA3dTiVXdXYm5sODf/gHaVbIHnnxBNneZENFVpLOO88df/tbafp098ESAGDImT9jvsoKy3TZAZcN6PGRFVkgWeIJsmuMMYdIssaYImPMvyrQZgwkhFeRravrfYuayIpsZaVf7Qo939QkpXOBgUwKsl5VLd0rOafCYFuLQ3mLkEmxA51XhW1o6Hnbzp3SV7/q2rqzJchOmiQdcYS7PH16escCAEib8RXj1fjvjZo1dlbfd45i1LBRKi0o1codK9XS0RI8H3oZSIR4guylki6XNF7SWkn7BK4DiTFmjGsR/uQTaY89Yt8vsiJbWelCgrXuy6vIrlvn2mh/9avkjjuWTAqyu+3mjsuWpXccqTDY1uJQgc3gexVakW1okG64wV/o6777pIcflm6+OXuCrCQ99ph0xRXSlVemeyQAgCxljNH0kdO1bNsyrdrpb1O3sXFjL48C+q/PIGut3WqtPd9aO9ZaO8Zae4G1doisHoOUGDPGBdH29t4XmIkWZCUXHlpb/QDpuf32xI81HpkUZMePd/OOqcj2X2/ztaXwIPvkk9IPfiAtXOjOeX/3TU3ZFWTHjpV+/nPpqKPSPRIAQBbbbeRuWrZtmVbUrQie29C4IY0jQi6KZ9XiB40xlSHXq4wx9yd3WBhSDjnEvxxPkA1tLZZcUPCqsePG+ff3Am+qZdL2O8a4quxQCLKJmiPrWbOm97nFoa3FXsV782Z37AosI9DSkl1BFgCABNitejetqFuhT7f67z82NBBkkVjxtBbPstYGE4G1tk7SvskbEoacOXP8y/1tLZbcPFkvyNbU+Pf3Am+qZVJFVpKmTZM+/zzdo0i+RFdkq6rCX0+RQiuykUF261Z3rK/3gyyLJwEAhogZo2aoy3bplVWvBM/RWoxEiyfI5hljqrwrxphqxbdtDxAfY9x81gsukEpLY98vNMgWFvorHIdWZGtr/fu3tydnvH3JpO13JGnCBFdZTOcCWKmQyDmy8fCCbEODX/H29jj2jmvXutdnSUl8824BAMgBu410a3QsWLlAE0dMVL7Jj9pa3G27qdRiwOIJsj+R9Lox5kZjzI2SXpd0S3KHhSHn0kvd4ji9CW0tLinxWzVjVWSl9IS3TKvI1ta6uZren1GuSnRFti9ekK2vl5Yvd5cjK7Jr1vhBFgCAIWLXql0lSTvbdmp8+XhNrZqqu96+S++sfyfsfre9fptqf1qrL+q+SMcwkeXiWezpIUn/IGmTpM2SzrTW9pE4gCTwgmxXl6vcetdjzZGV0tNenGlBdvx4d8z1vWQTPUe2L0VF7mvZMn/v4s2b3SJjf/yju75hg6vYEmQBAEOItwWPJI0bPk5PnPOEumyX7njrjrD7vfTFS5KkJVuWpHyMyH4xg6wxpiJwrJa0UdIjkn4jaWPgHJBaXnCVelZkN21ylydODH/M44+nZmyhMi3Ieu3W3/2utHKlf/7ee92WR7ki1a3FkqvKvhP4dLmgwAXZ//f//NutdX/mBFkAwBBijNHEEe492bjh47T32L01f8Z8Pf3p0+ro6gjeb+SwkZKkrc1b0zJOZLfeKrKPBI7vSHo75Mu7DqRWQYE/zzCyIvvJJ+7cjBn+/efMcS3L3nzFVMmkVYslP8g+9ZR08cXucne3dMklbr/TXJHq1mLJrVzsfRiw335+a7Hkb9+zahVBFgAw5NSUu+leNcPd8fQZp6uutU4L1y0M3qey2C3cuXrn6tQPEFkvZpC11p5ijDGSjrDWTg35mmKtnZrCMQKOMX54DQ2ybW3S0qUuxHrzFiXpZz9zge3vf0/tODO1Iiv528I0NblqYbR5s0uWSDfdlH2LQ6UjyHqvt2HDpH32CV8d2ms3piILABiCivPd+7Rxw920r31r3KYnb659U+vq10mS2rvcwpwrd6xM/QCR9XqdI2uttZL+mKKxAH3zwmtoa7FXkd1jD78KJrmKbHGx9Le/pXaM3mrJmbJqceifSV7gn7wXYKMF2cMPl77//fRtXzRQqZ4jK/lBdrfd3Pzstjb/tkcfdcfu7vC2eAAAhoCifLftXFWp2/xk4oiJKiko0dUvXq0Jt0+QJNW3u/chX+xgsSf0XzyrFr9pjDkg6SMB4hGtIltX59o3d989PLQVF0sHHpj6INvS4o7e9kCZ4IQT3PHll117cV2dux4trHq3pbole6AWL3Zt0+mYI7urW5VRNTVumyPPs89Kp5/uX6ciCwAYYiZXTpYkDSt074fyTJ6mVU8L3t7V3aWGtgZJYtViDEg87/qOknSJMWaVpCZJRq5YOyupIwOiiVaRXbLEtcHOmBEeZCVp9mzpwQfd7anax9MLspkUXp57Trr2Wunmm6X775cOO8yd721Lni1bpOnTUzO+wbj1VvfzVVenviL7y19Ko0ZJ8+f7bduSO1dcLFVVuQ8GMum1AABACvzXMf+lGSNn6IRpJwTPGfnvxdY3rFd9m3sfsrlpc4/HA32JJ8iemPRRAPHyAkFoRXbFCnfcZZeeVdDp0932J1u2SGPGpGaMLS1ubHnxNDyk0KRJ/uX33nPHyIps6LzYzVnyn8rmzW7f1mHDUh9kKyuln//cXf70U//8qFHuWF3tguyUKakdFwAAaVZWVKbLD7w87Fx1qb/xyamPnqoPNn0gSWrpbFFbZ5uKC5iKg/jFs4/sKkkjJZ0mab6kkYFzQOp5CxeVlvqh1guytbVuX89Q0wItLA88kLw5nytWSHfe6V9vaXHjyzShIf/twMLjkRXZDRv8y9nSWrw1sGT/hg3pXWArdOsnL8h6iz+dyOeBAAA8dMZD+taB35KkYIj11LXWpWNIyGJ9BlljzPWSHpQLs6MkPWCMuS7ZAwOi8uYklpT0rMjW1PRsH/aC7LXXuq+Beu45acECadEiad99pe3b/duOOkq6/HK3ErCUuUH2zDOlb35Tys/39z6NDLKhq+5mS0XWC9zpWLU4VOjfeXm5O3pV+aOOSv14AADIMBNHTNTNx94cdm7UMPfhb10LQRb9E0/54suS9rXWtkqSMebHkt6VdFMyBwZENTVk5yevIrttmz8nUZJOOcWvgE2e7N/fW014IE46yR2vuEJ6/33pr3+Vzj7bndu0yR3b2twc3UwNsuXl0j33uBWeX3vNnauvD58/vHKlf/9sq8hKmbNStPfn+cYb7s/bC7YAAAxxpYXh75Emjpiorc1bqcii3+KZxLdSUuhKJcWSPo9+VyDJvCC7YUP4libjx/uX//Qn6Z//2V0ObTUeaJjw9oWVpBdfdEcvCEpuexXJX+SpuTkzg6wndAGn7m6/kixJqwMbktfWZkdFtrnZ369VSn+Q3Wef8K6AAw+UvvrV9I0HAIAMdN3hfnPnpBFuDQ8qsuiveIJsm6QlxphfG2MekPSRpEZjzC+MMb9I7vCACN6iOevXuxZZb06kN3c2mjVr3PzQxsb+f79HHgkPR0uXuuOrr/rnIoNsplZkPZELD4W2Sa9eLY0e7eZ7ZnJF9rPP3PhCq7FSeufIStJbb/mvAwAAENWNR9+oKw+6UlJIazEVWfRTPO/6/hj48rySnKEAcfBW3q1ym2uruNhVTEMrspEmTHArGodWHuP1m9/0PHf88dILL7iqcE1N9gfZSZNcgN1lF3ecONGt8PxFBu/pNn26+yBj4cLw8+muyKb7+wMAkCWqSqvCrlORRX/1GWSttQ+mYiBAXGpqpMcflw4/3F33QuQuu/T+uLKygVVkQ+fkeq65xgXZ2lrpF7/wt6wJDbJVVT0flymibQXzzjvSM89Izz8vnXGG+9kWLEj92OLh/Xl3dYXP6ZWk3XZL+XAAAED/7TNuH0nS3mP2luT2krXWykQu3AnEkGEbXQJxOOssaexYd9kLj3vu2ftjhg8fWJCNtmVP6Aq0d93lX86WimzoAliel17y5xVPmODC7s6dbg/UTBP6dxJZMf/Hf0ztWAAAwIDMnzFfr170qi4/8HKVFJToptdu0rX/N4gdJjDkEGSRG/baq/fbBxpkt21z7cs3hywVb4yrYNbWupWKPa2t7pjpQXbcuJ7n7rjDv2yMX4n2tjbKJKF73f7lL+64fLmb65vuObIAACBuh086XHkmT62d7j3UbW/cluYRIZsQZJEbvP1iYxlokN26VTriCOmSS8LP77ef9PWvh88jzZaKbF7IP/u33pLmznWXp0+XfvAD6V//1W8/zsR5shs3+pebmqTqavf3n8nt3AAAoE9TKqNMfwJi6LN8YYz5kyQbcXqnpLcl3e3tLwukVV+L7AymIrvrrlJFhVRZKX33u/5tM2b4c3Sl7AmykvTss27e8AEHuH1333hDeugh6eCD3e0VFe6YiUHWq8iOHy+tW+f+fgAAQNa65pBrdMvrt2hdwzp1227lGWpt6Fs8r5IVkhol3Rv4qpe0SdJugetA+txwg/SjH/V9v96CbFOTq7yeeKKrUIbatk0aOdK129bVuYWePDNmhN83W/aRlaSTTnKVZsmF8+ZmP8RK0ogRrsKZia3FXkXWqyT3VY0HAAAZ7eYv3ay7T7lbrZ2tWlu/Nt3DQZaIZ0LZvtbaeSHX/2SMedVaO88YsyRZAwPi8v3vx3c/L8ha60JpqEmTXGCVpNde8wNvZ6e0Y4c0alT054xc0bilxT1/a2vmB9lQxkQfb01NZu4lu3Gjm7e8337S739PRRYAgBwwvXq6JGnZtmWaOGJimkeDbBBPRXa0MSb4agpc9t7ZtydlVECiDR/ugml7lJesF2IlV53t6nKXt293x5Ejoz9ndXV4S3NLi7/gUzYF2VjKy6WGhnSPoqcNG9yCVV6AJcgCAJD1dhvpttBbvm15mkeCbBFPkP2OpL8ZY142xrwi6TVJVxtjyiSxxyyyw/Dh7hjPPNnFi91x61Z3jFWRNca14HpaWvz24mHDBjbOTFJeLtXXp3sUPW3c6ILswQe7tuLDDkv3iAAAwCDVltdqWOEwLd++XI8sfkS/WvSrdA8pZ7yz/h01dzSnexgJ12drsbX2z8aY6ZJ2l2QkfRKywNPPkjk4IGFCg2ysCqvH2zt15Up3jLZdjaeiwg+8ra1+kM2VimzoVjeZYsMGt8LyxIlu2x0AAJD1jDGaVj1Ny7Yt07PLn9X2lu26dM6lMpFTwtAvLR0tmnPvHO1Xs5/e+ad30j2chIp3SbD9Je0laZakc4wxX03ekIAk6E9FtqnJHV95xbUOH3hg7PuWl/uXQyuyuRJk091a/NprbkugUF5FFgAA5JTdRu6mBasWaNm2ZdravFUr6jJw0ckss75hvSTp3Q3v6uD/OTi4Z28u6DPIGmMelnSbpMMkHRD4mpPkcQGJFU+QjbzPX//qVsbtrU3Y26ZGcgFrzz3dZYJsYsyb51am9v5O2tvdnOaamvSOCwAAJNz06ulqbPffqy1ctzCNo8kNGxr97rqF6xbm1KrQ8VRk50g61Fr7z9babwW+rkj2wICE8iqn3/ymW/QpVEGgw3733d2xqcm1Cb/3nr9FTV/PK0mPPip1dIQ/ZzbzgqyN3EY6DT791B03bXJHKrIAAOScGSPd1oaVJZUqKyzTwrUE2YFq62zT4k2LtaHBBdkbj7pRklTfloHrnwxQPEH2I0m8a0R2mzPHtQgvXiytXu2ft9Zfpfjoo92xqcltu2Nt35W/0Iqs5CqyZ58dvidrtqqocKG/rS3dI5GWLnVHbw9ZKrIAAOScc/Y6R3edfJc+v+JzzRwzUx9u/jDdQ8pa5z1xnmbdNUvLt7v1RLwPCYZakB0l6WNjzAvGmKe9r2QPDEiokhLp+uvd5dC9UdvbXWD9z/90LaySa2P1VuuNDKqRpkwJv37eedLvfpcbFUOv2pyu9mJrpfx8d/mTT9zRW3wqF/58AQBAmNLCUl0y5xJVl1Zrr9F7acnmJekeUtZ68pMnJbm5sYV5hZpcOVmS1NCWgVsrDlA8/Y//kexBACkxerQ7hgbZ5sBS5KWlUlGRawluavLDW19B9vrrpdpa6TvfcaHYa0/OBV6Qra/3/+xSaetWv1oeWZElyAIAkNP2GrOX7n//fm1p2qLRZWl4H5LF2rvag5ff3/i+asprNKLEbRk5pCqy1toF0b5SMTggocaMccfNm/1zXpAdNsztC1tW1r+KbEmJ9C//4kKslJtBNl0VWa8FPD9f+jDQWrRqlbs+dmx6xgQAAFJi5piZkqQlW6jK9terq14NXv687nPVlteqoti9px0SQdYY87fAscEYUx/y1WCMyZ0/AQwd0SqykdvlDB/uKrLxBtlI06cPboyZJN1BdmFggYczzpA++8zNW37nHWmvvVz1HAAA5Kw9R7udIJZuWZrmkaTOsm3LBh00rbW6/uXrw84NuSBrrT0scCy31laEfJVba/v57h7IAGVlrvIaqyLr3ee++6Tzz3fX4w2yXhAuKUnMWDNBOoPsqlXSt78tHXSQdNFF7tw770iLFrmFuwAAQE4bU+Y66ba1bEvzSFJnxn/P0HEPHzeo59jUtElvrH1DNx11U/DcbtW7qbSgVPkmP6eCbJ9zZI0xu0paa61tM8YcKWmWpIestTuSPTgg4UaPjl6RDQ2ykqvKSvEH2eXLe9+jNhulM8i+/LJbMfm++/z5sI89Jm3fLh1wQOrHAwAAUqoov0jDCoeprqUu3UNJic5utz3kYPfO9RZzmlQ5KXhuj9F7yBijiuKKnAqy8axa/ISkLmPMNEn3SZoi6ZGkjgpIljFjoldkQ1uLQ8UbZMePl2bMGPz4Mkk6g+zrr0uVldIee0gjR7qtk+691912+OGpHw8AAEi5qpIq1bUOjSCbqNWEG9rd8wwv8t/Tem3aFcUVwdtzQTxBttta2ynpDEk/s9ZeJYlNHJGdIiuy0VqLQxUXp2ZcmcgL8ekKsnPnSnmBX1GPPCLNni3dc4+bIwsAAHJeVenQCbKJqpQ2trsOwfKi8uC53Ue5xUhzrSIbz/Y7HcaYL0u6UNKpgXOFyRsSkERjx7pFhDo6pMLCnos9wedVp1MdZHfskJYskc491z+3667S+++ndhwAACCtqkqqhkxrsVcpLcof3IKWXpAdXjRco4eN1pbmLcHqbK4F2Xgqsl+TNFfSj6y1Xxhjpkj638F8U2PM2caYJcaYbmMMK7cgdU4/Xdq2Tfrd79z1yIpsfe784x60ggIX8FP9Z/Lmm+54yCGp/b4AACCjDKWKrNdaXJw/uG5A73mGFw3X4ssWa/m3lgdvG3JB1lr7saR/lbTYGDNTbuGnHw/y+34k6UxJr/Z1RyChTjlF2nNP6ZZbJGt7Lva0c2f6xpaJystTX5F94w3XUnzggan9vgAAIKNUlVRpR+vQWF/WC5jFBYMLssHW4uJyjR0+VtOqpwVvKy8uH1pBNrBS8XJJv5R0p6Rlxph5g/mm1tql1tpPB/McwIDk5UnXXCN9+KH0/PM9F3uiIhsuXUF27739xaYAAMCQNBRbiwdbkQ1tLY5UUTTEKrKSfiLpOGvtEdbaeZKOl3R7cocFJNFXvuLmf/75zz1bi6uq0jeuTJTsIHvbbdLFF4ef+/xzVzUHAABDWmVJpRraG4Jb0+SyRFVko61a7Dli8hE6e8+zB/X8mSSeIFsYWj211i5THIs9GWP+zxjzUZSv0/ozQGPMPxlj3jbGvL0ldLVZYKAKC6WpU6VVq1xrcV6eOydJTz/t9i6Vcm87nYFIdpC9+mrp/vv969ZK69e77YwAAMCQVlXqCgxDob3Ym9taUlAyqOdpbG9UUX5R1EWjLph1gX5+4s8H9fyZJJ4g+7Yx5j5jzJGBr3slvdPXg6y1x1prZ0b5eqo/A7TW3mOtnWOtnTN69Oj+PBSIbfJkaeVK9zV2rGSMOz9pkvT1r7sFod7p82We+/oKsj/8ofTiiz3Pr1kj3Xyz1NUV3/fp6HDHHTuk1laptrb/YwUAADmlqsQF2bqWOjV3NOd0ZdaryCZi1eJo1dhcFE+QvUzSEklXSPq2pI8lXZrMQQFJ5wXZV1+VDjus5+3V1T33lB2Keguy3d3Sf/yHdNxxPW+76Sbp2mulP/whvu+zYYM7rlvnjgRZAACGPK8iu75hvfa7ez8d+9Cx6up2H5IfeO+Bmnvf3HQOL6G8luBu2z3o5wndQzaXxbNqcZu19qfW2jOttWdYa2+31rYN5psaY84wxqyV29bnWWPMC4N5PqDfJk92AW3NGunww9M9msxVURE7yG7dGvtxo0a54733usDbl7Vr3XH9enektRgAgCFvxkg3zevipy/Wp9s+1YJVC/TQBw9JkhatX6Q3176ZzuEllFeRbe9qH9TzUJGVZIxZbIz5MNbXYL6ptfaP1toJ1tpia+1Ya+3xg3k+oN8mT/YvH3FE2oaR8crLY6/k7IXPvCi/Rlpb3fHFF6Xvfrfv7+NVYr0gS0UWAIAhb1r1NI0tG6vP6z7X0VOO1rDCYfpo80dh97HWpml0ieVVZNs6B1UvHFJBtqCX205J2SiAVNt1V3ecM8dt9YLoysvdys5dXVJ+fvhtXvgcObLn4+rrpXHjpN13l156Kfpzh/7HE1mRrakZ3LgBAEDWM8YE54x+ddZXtaJuhTY1bQq7z862naosqUzH8BIqURXZhrYGlRfTWlwoaYK1dlXol6SJ6j0AA5lv772lp56SFizwF3pCT95ero2NPW/zwmd1tTvefbdffa2vd23J06dLq1f7j2lq8p/L2/pIkm69Vaqrc+G4qsrf1xcAAAxp/3XMf2l40XCdsccZGlM2RpubNgfnyUrS6p2re3l09vBWLaa1OH69BdmfSYo2Oa4lcBuQvYyR5s/3949FdF6QjTZP1qvIVlS44733Sr/6lau0ekF24kRp82a3zZHkVoj29urdudN/rg0bpDvukL74IrztGwDA2iv9AAAda0lEQVQADGnnzzpfDd9tUEVxhcaWjdXmps3B6qUkrdm5Jo2jSxxvi6G2LlqL49VbkJ1sre0xF9Za+7akyUkbEYDM4QXZn0X57MoLsu3tUmen9NFHLpxOniw9/7wLspMmufusCfwn09Tk7iv5c2/vukuqrHTbHX32mTRtWtJ+HAAAkL3GlI3RB5s+UPUt1cFzuVKR3d6yXdLgK7Jbm7equqS67zvmgN6CbG+78dL3BwwFXpD9yU9ci/C110qvv+7OrVjhji0t0qefSm2BTxC9VmKvIht6LpQXZCdMkE48UVq0yG2J5M1fBgAACDG2bGyPc8u2LUvDSBKvrrVO0uCCbH1bvRraG7TLiF0SNayM1luQXWSM+WbkSWPMxZLeSd6QAGQMr21Ykt56S7r5ZumYY9z81jcDS963tEjvvx/9sV6QXbXKX8nY47UWV1RI++3n2os7OqjIAgCAqMaUjQm7Xl5Urkc+emTQK/2mW0dXhxrbG1WcX6xu263O7s4BPc/aerd+yYSKCYkcXsbqLcheKelrxphXjDE/CXwtkPQNSd9OzfAApNVhh0m33OIuP/WUO7a2SqNHu5biSZNckF2+vOdjKypctTUvz7UMb9zo3+bNo5WkESPc6tEeKrIAACCKyCB73bzrtLlpsx796NE0jSgxvGrsuOHjJA28KusF2fHl4xMzsAwXM8haazdZaw+R9ENJKwNfP7TWzrXWboz1OAA5JC9Puvxyd9kLspK/4vBxx7kgu327C6S33ebfp6JCKiyUDjxQ+utfpU8+8W9ra/ODbEWFNG+e265HknbbLXk/DwAAyFrdtjvs+tl7nq19x+2rGxbcoI6ujjSNavC8+bFekB1ohZmKbARr7cvW2jsCXzE2hASQs4YNcxXY0JWLy8qkhQvd+ZYWt3VOVZX0ne9I//iP7j5eW7I3//XEE/3H19f7rcUjRrjA/Mkn0nPPSbW1qfm5AABAVjlp+kk6btfjgterSqt01cFX6YsdX+jjLR+ncWSDExlkB1uRrS0fGu+l+gyyAKCRI90xL/ArY/ZsV2ktLZW6u90WO962OsMDS76XBNaLmz+/5/PV17sqrjH+glIjRkgnnJC8nwEAAGS1qtIqvXDBC8HrFcUVwdAWuiVPtqlrSVxr8ZiyMSouKE7Y2DIZQRZA3774wh3vvNMdzz3XHUsDC5ivX++20JFctVby947dZx+3GnGohga3JU9trVRQkLRhAwCA3GNkJEl5Jk/lxe4D8WwOspEV2Yc+eEjW2n4/z9r6tUOmrVgiyAKIxyOPSFddJV1yiVu46VvfcudDg6xXkfWCbGOj//hJk9zKxl4Arq93W/J4qxoDAADE6bMrPtPz5z8vyVVlJamhvaG3h2S0yMWernv5On246cOw+9z37n266dWben0egiwARDrzTOmnP3WXd93VtQRLfpDdvt0PspdcIh10kHTppeHPMXu2m0MruYosQRYAAAzA1KqpOn7a8ZLcFjxS9ldkjYxGDxsdPOfNd5WkV1e9qm/86Rv6/svf77VSu7Z+rSaUE2QBoG9ekJX8IFtT4/aYnRDlF6m3ANSpp7rKLkEWAAAMgleRzeYgW9dSp4riCpUW+u+r1jesD15+6hN/54itzVujPkdzR7PqWuuoyAJAXKIF2d54Czt5CLIAAGAQyorKZGTU0Ja9rcWtna0qLSxVUX5R8NyGxg3By0u3Lg1eXrZtWdTnWFe/TtLQ2XpHIsgCGIz+BlmvIusZPTr6/QAAAOKQZ/I0vGh4VldkO7o7VJhXqOJ8f7Xh0Irs0q1LNad2jiRp+fblPR5vrdVHmz+SRJAFgPj0N8h6C0F5DjooseMBAABDTkVxRVYv9tTZ3amCvIKwiuz6hvW6YcENenTxo1q1Y5VOmnaSCvIKolZkX1zxos783ZmShlaQZd8LAAPX3yDrLRIlSQNYVh4AACBSeXF59ldk8wtVmF8YPLehcYN+8MoPgtf3Hru3Zoycocc/flxXHnylxpSNCd62dIvfejy+YnxqBp0BqMgCGLjQIDt2bHyPefhh6d13kzMeAAAw5GR7Rbajy7UWN7b7Wxeu2rEq7D5zJ8zVr07+lVbtWKVb/n5L2G1tXW2SpMvmXKZhhcOSP+AMQZAFMHChQXb27Pgec8EF0r77Jmc8AABgyCkvyv6KbEFegWaOmami/CLNnTBXW5q3BG/fe8zeGl8xXodPOlxHTzlaf1r2p7DH17XUqTCvUL886ZepHnpaEWQBDFxtrXToodLzz4e3DQMAAKRIRXGFtjRtUVtnW7qHMiCd3Z0qzC9UdWm12q5r0wWzLgjeduguh+q5858LXj91t1O1bNuysLmyda11qiqtkhli78UIsgAGrqRE+tvfpOOPT/dIAADAEFVRXKHl25dr1l2z0j2UAfFaiz01w2uCl3945A/D5r0ePulwSdIHGz+Q5FYsrmutU1VJHGuV5BgWewIAAACQtTY2bpQUe4/VTOct9uSpLa8NXh41bFTYfb1FnrY0b1G37Vb+DfmSpIPGD72dIKjIAgAAAMha48tdxdIoO1trO7rcHFlPTblfkY0MsiNLR0qStjRt0SdbPwmeryodehVZgiwAAACArPWzE36mE6adoLKisr7vnIE6uzvDWovHDR8XvDxy2Miw+xbmF6qqpEpbmrfojTVvBM8PxdZigiwAAACArFVeXK4Dag9QY3ujum13uofTb5GtxUX5RRo1bJTKCstUUlDS4/6jy0ZrS/MWvb7m9eA5giwAAAAAZJnyonJJ0oKVCzT61tG66MmLlH9Dvv7jlf9I78DiELnYk+TmyUa2FXtGDxutt9a9pd99/Lvgufy8/KSOMRMRZAEAAABktfJiF2SveuEqbW3eqgc/eFDdtlvvbXwvzSPrm7ePbKjp1dM1qXJS1PuPLhutlTtWylqr6+ddL0na0boj6ePMNKxaDAAAACCreRXZDzZ9EHY+G/aW9faRDXX3KXero7sj6v1HDxstSTpqylE6aIJbrbg4vzi5g8xABFkAAAAAWa2iuCJ4uaSgRK2drRpeNFztXe1pHFV8orUWRy7yFMpbnfmQCYfohGkn6JZjb9E39vtGUseYiQiyAAAAALKa11osSTcceYPW1q/V4s2L1daV+RXZju6eQbY321q2SZJmjpmpPJOnqw+9OllDy2gEWQAAAABZzWstlqQTpp2gvcfurZMfOVn1bfVpHFV8IveR7cuPj/2xxpSN0fHTjk/iqDIfQRYAAABAVgutyNaU10hy80azoSIbbY5sb6ZVT9OdJ9+ZxBFlB1YtBgAAAJDVQiuy1aXVktx+rNmw2FN/W4vhEGQBAAAAZLXQimyecRGnuKA4exZ76kdFFg5BFgAAAEBWKyss63Eum1qL+zNHFg5BFgAAAEBWM8b0OFecX5zxrcXWWnXZLlqLB4AgCwAAACAnHDX5qODlovyijK/IdnR3SBKtxQNADRsAAABA1mv+9+awFt1smCPb0RUIslRk+40gCwAAACDrlRaWhl0vzi9WZ3enum13cAGoTNPZ3SlJzJEdgMz8GwUAAACAQSguKJakjJ4nS2vxwBFkAQAAAOSc4vxAkM3gebK0Fg8cQRYAAABAzinKL5KkjJ4nS0V24AiyAAAAAHJONrQWM0d24AiyAAAAAHIOrcW5jSALAAAAIOdkQ0WW1uKBI8gCAAAAyDlZMUeWiuyAEWQBAAAA5JxsaC1mjuzAEWQBAAAA5JxEtBbPvW+ujv/f4xM1pB5oLR44oj8AAACAnJOIiuyba99M1HCiorV44KjIAgAAAMg5WTFHlorsgBFkAQAAAOScaK3FB//Pwbrr7bvieny37U7KuEIxR3bgCLIAAAAAck601uKF6xbqsmcvi+vxO1p3JGVcoWgtHjiCLAAAAICcM9jFnrY2b03kcKKitXjgCLIAAAAAck5vc2Sve+m6YFtvLKFBNhltxm+ufVPbW7ZLoiI7EDRjAwAAAMg5va1a/KPXfqRZY2fpnL3Oifn4LU1bgpebO5o1vGh4wsbW1tmmuffNDV5njmz/UZEFAAAAkHMiW4sjq6o7W3f2+vjQiuwflv4hoasf17fVh12ntbj/CLIAAAAAco5XkW3tbJUkdXV3hd3e3NHc6+NDg+yFT16ox5c8nrCxRQbZRFZ7hwqCLAAAAICcU5hfqOL8YjW2N0rqWZHtK8iua1gXdn1N/ZqEjS00yF6878UaNWxUwp57qCDIAgAAAMhJFcUVwdDYZcMrsjvbYrcWL9u2TPe+e69KC0qD5zY1bkrYuLwx3XHiHbr31HsT9rxDCUEWAAAAQE6qKK5QfXsgyEa0Ft/+5u26Y+EdUR/3fyv+T62drbrn1HuC5zY2bQxe3t6yfVArGXtBdu6EuTLGDPh5hjKCLAAAAICc1FtFtr2rXVc8f0XUx3ntyNOqpwXPeRXZhrYGTbx94oDnzH75iS9r/m/nB8eHgSHIAgAAAMhJ5cXlamhrkNSzItubxvZGGRmNHjY6eG5j48bgsamjSZ/XfT6gMf32o98GLxNkB44gCwAAACAnhVZkY7UC/2LhL/TEx0+E3d7Y3qiyorKwoLmpyVVkd7TukORv32Ot1TUvXqN3N7w7oPFhYAiyAAAAAHJSb63Fnm8//22d9fhZWrRuUfBcY3ujhhcND9sWZ3vLdtW31QdXM/YWi2rqaNKtr9+qI359RL/HV1JQ0u/HwClI9wAAAAAAIBkqikKCbERrcUlBSXCPWUlatH6RumyXDtnlkGCQjQyalT+ulJWV5AdZ7zmsdeffWveW8k2+9q/dv8/xsdDTwFGRBQAAAJCTYlVkT5txmt675L2w+37ruW/p0PsPleRXZI0xGl8+XvMmzZOkYIiV/NZibz/agjxXIzzofw7SnHvnJOkngocgCwAAACAnVRRXqK2rTW2dbero6gieLysqU215bdTHWGuDQVaS1v6/tXro9Id63M+ryHpBNj8vP+z27S3bE/IzIDqCLAAAAICcVF5cLkk66ZGTNO0OfyudssIylReVR33MtpZtYUFWknYZsYvKCsvC7hdZkd3esl3mh36r8KurXu3x3G2dbQP8SRApLUHWGHOrMeYTY8yHxpg/GmMq0zEOAAAAALnLWxX4pS9eCjtfVlgmY4yuPuRq3X3K3WG3bWzc2CPI5pk87TF6j7D7RVZkIy1cu7DHOe8xGLx0VWRflDTTWjtL0jJJ303TOAAAAADkqFjb25QVuerqLV+6RRftc1HYbRsaNvQIspK05+g9w65HVmQjeXNzQ62rdyseF+QV6MfH/LjvHwAxpSXIWmv/Yq3tDFx9U9KEdIwDAAAAQO6KGWRD2oQL8wqVb/z5rRsaXZCNbD3+ysyv6OAJBwevN7Q3qL2rPWpglaTmTj/gWmu1aN0i7XfPfpKkJ855Qv922L/1/wdCUCbMkf26pOdi3WiM+SdjzNvGmLe3bNmSwmEBAAAAyGax5sF6FVnJbYETev3CJy9UXWtdj4rs8dOO1wsXvBB27sB7D9TZj58d9Xt4ldrD7j9M434yTm+sfSN4W6yAjfglbR9ZY8z/SRoX5abvWWufCtzne5I6Jf0m1vNYa++RdI8kzZkzx8a6HwAAAACEKi4ojno+cuGmYYXDelRWI4Os1DMYf7Dpg5jfe2frTr3w2Qv6+5q/S5KWbF4SvI0gO3hJC7LW2mN7u90Yc6GkUyQdY73dgwEAAAAgQQrzCqOen7vL3LDrkcFWih5kjTE6cvKRau5o1lvr3ur1e7/w+Qt64XO/gvv+pveDl0cUj+j1sehbulYtPkHSv0mab62NPjsaAAAAAAahKL+ox7lnv/Jsj4WbhhUOkyR9Ze+vaL8aN4+1pKAk6nO+fOHLuv342/s9ltDg620LhIFLWkW2D/8tqVjSi8YYSXrTWntpmsYCAAAAIAcV5vesyIYu7OTxguy8ifO0S8UuenfDu9rYuDHm84Yu+tQfX5r6Je1o3aGRpSMH9Hj40rVq8TRr7S7W2n0CX4RYAAAAAAkVrSKbn9czyHqLPZUVlemsPc+SJB26y6ExnzfP5OnPX/lzzNtjBdWfHPcTvfXNt6KOAf2TCasWAwAAAEDCRZsjm2d6RiCvIltWWKY5tXPUfl27jpl6TK/PfeL0E/XXr/416m2jho2Ken7mmJl9DRlxIsgCAAAAyEn9bS32FniK9rhoqkqqop6PFmSrS6sVmFaJBCDIAgAAAMhJcbcWF/qtxf1RVRo9yI4uGx12/cqDrtQnl3/Sr+dG7wiyAAAAAHJStNbieCqy8YpZkS0Nr8geOP7AHuEWg0OQBQAAAJCTCvJ6btLS1xzZ/oi1jU5kazHb7SQeQRYAAABATjLG9KjK9tZa3N+KbLRQLEUJskUE2UQjyAIAAADIWZHzZKO1Fo+vGK+ywjJVFFcM+vvlm3xVllSGnaMim3gEWQAAAAA5K3IF4mgV2QtnX6hP/+VTlRaW9vv5nzz3SZ2717nB68MKh/VYNIqKbOIRZAEAAADkrB6txVEqsoX5hRpfMX5Az3/a7qfpyMlHSnKLP12y/yXBObceKrKJR5AFAAAAkLMiW4tjzWsdDC8sz58xX7ced6tKC8Iru1RkE48gCwAAACBnxdNanCjGmLCjJBXnF/eo0GLwCLIAAAAAclY8iz0NlpWVJBm5ANvV3SVJmj12tl644IWwYIvEIMgCAAAAyFnxbL8zWN22W5LftuytfnzwhIN1xOQjEv79IPXcIRgAAAAAckSP1uJkVGRteEV27i5z9dhZj+nU3U5N+PeCQ5AFAAAAkLNSsdhTsLU4pIX4nL3OSfj3gY/WYgAAAAA5KxWtxSUFJZJYnTiVqMgCAAAAyFmpWOzp/L3P16odq/SdQ76T8OdGdARZAAAAADkrFdvvFOYX6gdH/iDhz4vYaC0GAAAAkLNSMUcWqcffIgAAAICc1WOObBJai5F6BFkAAAAAOSsVrcVIPYIsAAAAgJyVisWekHoEWQAAAAA5KxXb7yD1CLIAAAAAchaLPeUm/hYBAAAA5KzIiixBNjfwtwgAAAAgZ0VWZJEbCLIAAAAAclbkqsXIDQRZAAAAADkrsrUYuYEgCwAAACBn0VqcmwiyAAAAAHIWrcW5iSALAAAAIGdRkc1NBFkAAAAAOYs5srmJIAsAAAAgZ9FanJsIsgAAAABy1nG7HqfL5lyW7mEgwQiyAAAAAHLW1KqpuvPkO9M9DCQYQRYAAAAAkFUIsgAAAACArEKQBQAAAABkFYIsAAAAACCrEGQBAAAAAFmFIAsAAAAAyCoEWQAAAABAViHIAgAAAACyCkEWAAAAAJBVCLIAAAAAgKxCkAUAAAAAZBWCLAAAAAAgqxBkAQAAAABZhSALAAAAAMgqBekeAAAAAAAk27ZrtinPUMfLFQRZAAAAADmvurQ63UNAAvGRBAAAAAAgqxBkAQAAAABZhSALAAAAAMgqBFkAAAAAQFYhyAIAAAAAsgpBFgAAAACQVQiyAAAAAICsQpAFAAAAAGQVgiwAAAAAIKsQZAEAAAAAWYUgCwAAAADIKgRZAAAAAEBWIcgCAAAAALIKQRYAAAAAkFUIsgAAAACArGKstekeQ9yMMVskrUr3OPowStLWdA8CQx6vQ2QKXovIBLwOkQl4HSJTZPprcZK1dnRfd8qqIJsNjDFvW2vnpHscGNp4HSJT8FpEJuB1iEzA6xCZIldei7QWAwAAAACyCkEWAAAAAJBVCLKJd0+6BwCI1yEyB69FZAJeh8gEvA6RKXLitcgcWQAAAABAVqEiCwAAAADIKgTZBDHGnGCM+dQY85kx5tp0jwe5yxizizHmZWPMUmPMEmPMtwPnq40xLxpjlgeOVYHzxhjzi8Br80NjzH7p/QmQa4wx+caY94wxzwSuTzHGLAy8Fh8zxhQFzhcHrn8WuH1yOseN3GGMqTTG/N4Y80ngd+NcficiHYwxVwX+b/7IGPOoMaaE34lIBWPM/caYzcaYj0LO9fv3oDHmwsD9lxtjLkzHzxIvgmwCGGPyJf1S0omS9pT0ZWPMnukdFXJYp6TvWGv3kHSwpMsDr7drJf3VWjtd0l8D1yX3upwe+PonSb9K/ZCR474taWnI9Zsl3R54LdZJujhw/mJJddbaaZJuD9wPSISfS3reWru7pNlyr0d+JyKljDHjJV0haY61dqakfEnnid+JSI1fSzoh4ly/fg8aY6ol/UDSQZIOlPQDL/xmIoJsYhwo6TNr7Qprbbuk30o6Lc1jQo6y1m6w1r4buNwg94ZtvNxr7sHA3R6UdHrg8mmSHrLOm5IqjTE1KR42cpQxZoKkkyX9T+C6kXS0pN8H7hL5WvReo7+XdEzg/sCAGWMqJM2TdJ8kWWvbrbU7xO9EpEeBpFJjTIGkYZI2iN+JSAFr7auStkec7u/vweMlvWit3W6trZP0onqG44xBkE2M8ZLWhFxfGzgHJFWgDWlfSQsljbXWbpBc2JU0JnA3Xp9Ipp9JukZSd+D6SEk7rLWdgeuhr7fgazFw+87A/YHBmCppi6QHAi3u/2OMKRO/E5Fi1tp1km6TtFouwO6U9I74nYj06e/vwaz6/UiQTYxon56xHDSSyhgzXNITkq601tb3dtco53h9YtCMMadI2mytfSf0dJS72jhuAwaqQNJ+kn5lrd1XUpP89rloeB0iKQItmKdJmiKpVlKZXAtnJH4nIt1ivfay6jVJkE2MtZJ2Cbk+QdL6NI0FQ4AxplAuxP7GWvuHwOlNXntc4Lg5cJ7XJ5LlUEnzjTEr5aZUHC1Xoa0MtNVJ4a+34GsxcPsI9WyDAvprraS11tqFgeu/lwu2/E5Eqh0r6Qtr7RZrbYekP0g6RPxORPr09/dgVv1+JMgmxiJJ0wOr0hXJTex/Os1jQo4KzJ+5T9JSa+1PQ256WpK3utyFkp4KOf/VwAp1B0va6bWZAINhrf2utXaCtXay3O+9l6y150t6WdJZgbtFvha91+hZgftn7Ce9yA7W2o2S1hhjZgROHSPpY/E7Eam3WtLBxphhgf+rvdcivxORLv39PfiCpOOMMVWBDoPjAucykuHfS2IYY06Sq0TkS7rfWvujNA8JOcoYc5ik1yQtlj8v8d/l5sn+TtJEuf9Mz7bWbg/8Z/rfcpP1myV9zVr7dsoHjpxmjDlS0r9aa08xxkyVq9BWS3pP0gXW2jZjTImkh+XmdW+XdJ61dkW6xozcYYzZR27BsSJJKyR9Te7Den4nIqWMMT+UdK7cDgPvSfqG3BxDficiqYwxj0o6UtIoSZvkVh9+Uv38PWiM+brc+0pJ+pG19oFU/hz9QZAFAAAAAGQVWosBAAAAAFmFIAsAAAAAyCoEWQAAAABAViHIAgAAAACyCkEWAAAAAJBVCvq+CwAASBRjTJfc9lmFclt0PCjpZ9ba7l4fCAAAggiyAACkVou1dh9JMsaMkfSIpBFye/4BAIA40FoMAECaWGs3S/onSf9inMnGmNeMMe8Gvg6RJGPMw8aY07zHGWN+Y4yZb4zZyxjzljHmfWPMh8aY6en6WQAASCVjrU33GAAAGDKMMY3W2uER5+ok7S6pQVK3tbY1EEoftdbOMcYcIekqa+3pxpgRkt6XNF3S7ZLetNb+xhhTJCnfWtuS2p8IAIDUo7UYAID0M4FjoaT/NsbsI6lL0m6SZK1dYIz5ZaAV+UxJT1hrO40xb0j6njFmgqQ/WGuXp2PwAACkGq3FAACkkTFmqlxo3SzpKkmbJM2WNEdSUchdH5Z0vqSvSXpAkqy1j0iaL6lF0gvGmKNTN3IAANKHIAsAQJoYY0ZLukvSf1s312eEpA2BFYz/UVJ+yN1/LelKSbLWLgk8fqqkFdbaX0h6WtKs1I0eAID0obUYAIDUKjXGvC9/+52HJf00cNudkp4wxpwt6WVJTd6DrLWbjDFLJT0Z8lznSrrAGNMhaaOkG1IwfgAA0o7FngAAyALGmGFy+8/uZ63dme7xAACQTrQWAwCQ4Ywxx0r6RNIdhFgAAKjIAgAAAACyDBVZAAAAAEBWIcgCAAAAALIKQRYAAAAAkFUIsgAAAACArEKQBQAAAABkFYIsAAAAACCr/H8oEx7jvSTK8AAAAABJRU5ErkJggg==\n","text/plain":["<Figure size 1152x504 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"metadata":{"id":"BBG6BVguRZV5","colab_type":"code","colab":{},"outputId":"3d7866bd-a892-4ba4-d6db-c20f95984caa"},"cell_type":"code","source":["#plt.figure(figsize=(16, 7))\n","plt.plot(sup,'r',label='Training data')\n","plt.plot(scaled_data,label='Original data')\n","plt.plot(test_results,'g', label='Testing data')\n","plt.title('Stock Price Prediction')\n","plt.xlabel('Days')\n","plt.ylabel('Closing price of stock')\n","plt.legend()\n","plt.show()"],"execution_count":0,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"tags":[],"needs_background":"light"}}]},{"metadata":{"id":"y50npbeiRZV8","colab_type":"code","colab":{}},"cell_type":"code","source":[""],"execution_count":0,"outputs":[]},{"metadata":{"id":"3QQDg9OVRZV-","colab_type":"code","colab":{}},"cell_type":"code","source":[""],"execution_count":0,"outputs":[]}]}