_Binance Coin(SCAAI).ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Copy of Binance Coin(SCAAI).ipynb","provenance":[{"file_id":"1idEjn-IVZfXQyRlVd-sGrFQwM9Idu9UC","timestamp":1630080720397}],"collapsed_sections":[],"authorship_tag":"ABX9TyObQSUArHtDVj5iCmvUuWdG"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","metadata":{"id":"eV5XH73CCVhW","executionInfo":{"status":"ok","timestamp":1630426067207,"user_tz":-330,"elapsed":9,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}}},"source":["from google.colab import drive\n"],"execution_count":1,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2Z7g6yKdDGVm","executionInfo":{"status":"ok","timestamp":1630426091362,"user_tz":-330,"elapsed":20995,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"56d5515e-d7ce-46d6-f24f-a04b09c8465c"},"source":["drive.mount('/content/drive')"],"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","metadata":{"id":"1iybRZmoGC0z","executionInfo":{"status":"ok","timestamp":1630426095614,"user_tz":-330,"elapsed":677,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}}},"source":["import pandas as pd"],"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"1aDGmeg2GcEY","executionInfo":{"status":"ok","timestamp":1630426103929,"user_tz":-330,"elapsed":348,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"95aa295e-9df4-4c13-8f7b-eb4345ed4867"},"source":["df =pd.read_csv('/content/drive/MyDrive/SCAAI_Drive_Swapnil Biswas_PS1/Binance Coin - Historic data.csv')\n","print(df)"],"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["              Date  Price(in dollars)    Open    High     Low     Vol.  Change%\n","0     Jul 27, 2021             303.29  304.31  307.62  298.53    2.26M    -0.33\n","1     Jul 26, 2021             304.31  302.60  327.62  301.19    2.86M     0.58\n","2     Jul 25, 2021             302.57  302.55  303.09  292.85    1.25M    -0.19\n","3     Jul 24, 2021             303.15  298.91  305.01  296.16    1.81M     1.42\n","4     Jul 23, 2021             298.89  293.51  301.15  281.68    1.98M     1.83\n","...            ...                ...     ...     ...     ...      ...      ...\n","1352  Nov 13, 2017               1.68    1.49    1.74    1.49  166.01K    12.75\n","1353  Nov 12, 2017               1.49    1.66    1.70    1.34  456.48K   -10.24\n","1354  Nov 11, 2017               1.66    1.71    1.93    1.58  256.71K    -2.92\n","1355  Nov 10, 2017               1.71    1.99    2.02    1.60  483.23K   -14.07\n","1356  Nov 09, 2017               1.99    1.99    2.20    1.90  283.35K     0.00\n","\n","[1357 rows x 7 columns]\n"]}]},{"cell_type":"code","metadata":{"id":"nGoj4PFAG0kN"},"source":["#importing all the python libraries\n","import math \n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","from sklearn.preprocessing import MinMaxScaler\n","from keras.models import Sequential\n","from keras.layers import Dense, LSTM , Activation\n"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"7ezVAfDfG4Zx","executionInfo":{"status":"ok","timestamp":1630408923136,"user_tz":-330,"elapsed":705,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"ee45fcd5-f918-4c92-aee6-a6f42ba59680"},"source":["#making a deep copy of the dataset\n","x = df.copy(deep=True)\n","print(x)"],"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["              Date  Price(in dollars)    Open    High     Low     Vol.  Change%\n","0     Jul 27, 2021             303.29  304.31  307.62  298.53    2.26M    -0.33\n","1     Jul 26, 2021             304.31  302.60  327.62  301.19    2.86M     0.58\n","2     Jul 25, 2021             302.57  302.55  303.09  292.85    1.25M    -0.19\n","3     Jul 24, 2021             303.15  298.91  305.01  296.16    1.81M     1.42\n","4     Jul 23, 2021             298.89  293.51  301.15  281.68    1.98M     1.83\n","...            ...                ...     ...     ...     ...      ...      ...\n","1352  Nov 13, 2017               1.68    1.49    1.74    1.49  166.01K    12.75\n","1353  Nov 12, 2017               1.49    1.66    1.70    1.34  456.48K   -10.24\n","1354  Nov 11, 2017               1.66    1.71    1.93    1.58  256.71K    -2.92\n","1355  Nov 10, 2017               1.71    1.99    2.02    1.60  483.23K   -14.07\n","1356  Nov 09, 2017               1.99    1.99    2.20    1.90  283.35K     0.00\n","\n","[1357 rows x 7 columns]\n"]}]},{"cell_type":"code","metadata":{"id":"H7npuRB7XNDj","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1630408926769,"user_tz":-330,"elapsed":358,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"bcc07f3c-0272-408e-ebdc-d01acef1acdd"},"source":["df.head"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<bound method NDFrame.head of               Date  Price(in dollars)    Open    High     Low     Vol.  Change%\n","0     Jul 27, 2021             303.29  304.31  307.62  298.53    2.26M    -0.33\n","1     Jul 26, 2021             304.31  302.60  327.62  301.19    2.86M     0.58\n","2     Jul 25, 2021             302.57  302.55  303.09  292.85    1.25M    -0.19\n","3     Jul 24, 2021             303.15  298.91  305.01  296.16    1.81M     1.42\n","4     Jul 23, 2021             298.89  293.51  301.15  281.68    1.98M     1.83\n","...            ...                ...     ...     ...     ...      ...      ...\n","1352  Nov 13, 2017               1.68    1.49    1.74    1.49  166.01K    12.75\n","1353  Nov 12, 2017               1.49    1.66    1.70    1.34  456.48K   -10.24\n","1354  Nov 11, 2017               1.66    1.71    1.93    1.58  256.71K    -2.92\n","1355  Nov 10, 2017               1.71    1.99    2.02    1.60  483.23K   -14.07\n","1356  Nov 09, 2017               1.99    1.99    2.20    1.90  283.35K     0.00\n","\n","[1357 rows x 7 columns]>"]},"metadata":{},"execution_count":109}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FwpPnuJHG61Z","executionInfo":{"status":"ok","timestamp":1630408935683,"user_tz":-330,"elapsed":367,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"a43787b4-b9fc-42f3-e90c-9cd26b7ecb3c"},"source":["#getting the info of the dataset\n","df.info()"],"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","RangeIndex: 1357 entries, 0 to 1356\n","Data columns (total 7 columns):\n"," #   Column             Non-Null Count  Dtype  \n","---  ------             --------------  -----  \n"," 0   Date               1357 non-null   object \n"," 1   Price(in dollars)  1357 non-null   float64\n"," 2   Open               1357 non-null   float64\n"," 3   High               1357 non-null   float64\n"," 4   Low                1357 non-null   float64\n"," 5   Vol.               1357 non-null   object \n"," 6   Change%            1357 non-null   float64\n","dtypes: float64(5), object(2)\n","memory usage: 74.3+ KB\n"]}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"luZLiN61G790","executionInfo":{"status":"ok","timestamp":1630408940622,"user_tz":-330,"elapsed":376,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"985a11da-47aa-4e31-cbf7-af4cfd5ae119"},"source":["#getting the number of rows and columns\n","df.shape"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(1357, 7)"]},"metadata":{},"execution_count":111}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":526},"id":"umaz4d0oG_-7","executionInfo":{"status":"ok","timestamp":1630408952159,"user_tz":-330,"elapsed":690,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"67d55d12-018c-4ce3-d5af-8d4447b7c03b"},"source":["#visualize the open price history\n","plt.figure(figsize = (16,8))\n","\n","font1 = {'family':'serif','color':'red','size':20}\n","\n","plt.title(\"Open Price History\" , fontdict = font1)\n","plt.plot(df['Open'])\n","plt.xlabel('Date' , fontsize=18)\n","plt.ylabel('Opening Price USD($)' , fontsize=18)\n","plt.grid(color = 'green', linestyle = '--', linewidth = 0.5)\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA7sAAAH9CAYAAADbBGuuAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzde5icdX3//+d7Zw85msBCMCHIKhDEEkQTqXhqFMVaodhiK6DVoG1qPdQe/H3RttbZ2lZsy9dDLZYoX4OlpE1NFYiiWGTbooGYYCAgJARYCCScFnLYZLOHmc/vj7lnd/Y0OzM799wz7309rivX7s7cO/OZPLn0+uRz35/bQgiIiIiIiIiIeNKU9ABEREREREREqk2TXREREREREXFHk10RERERERFxR5NdERERERERcUeTXREREREREXFHk10RERERERFxR5NdERGJh1k7ZmnMtmG2H7OjmHVj9i+YvSnp4VVF7vOFSf4MYbYXs/WYLa/w9d8c/d19usojr2Qsqyf5nKvHHNc9wTHdY475fnTc8dMYT3rce4uIiBTQZFdERKrP7O3AQ8DbgD8HOoCFwIXAc8CPMbsWs5bExlgNIaQJwYDrokcuJwSLHlsCfAa4APgZZqsqeIdFwALgJdUY7rSEsC76XJ3RI53RZ1035riO6Lj8z0YIHWNe7aXkPtvcaYzos8Dqafy+iIg415z0AERExBmzNwA3AT8GLiSEoYJndwB/jNk9wDeBFF4nLCE8A1yL2bHA3wH/BPxSma/x75j9D/B09QeYqFcDswnh+aQHIiIifmllV0REqsesFbie3CT2w2MmuiNyq4FdwAcwu6BWw0vIj6Ovr8CsvezfDmEfIWSrO6SEhdCnia6IiMRNk10REamm9wAnA/9DCI9NcWz+1N8/HX5k9HWeaczej9nPMevDrCe63nfxhK9mdi5mmzB7Pro++H7M/gyztoJjXjzuetPce/wCs/7oOtI/mtbfwFTMLhkzhtMw68Ts0eg63/xn7yo4pmuS1/odzDZj1htd23svZmsxe/0Ex0799xM3s1VjPvuqMc8vxewazB6Jmj+C2UbM3oNZc3TMOsxC9Bu/Mub1OgpeqxmzP8Jse/RaBzD7MWa/NuY9S+0x9jrkVdHvd4x5vCuOvzoRESmfJrsiIlJN74i+binh2Luir6/HLHftZu5azzdHj18C/DZwMXAM8CHgIuAn41ZIzS4B/pfc/6+9Ojr+r4G/AG7GrCl6/aei97g8+s33AiuAt5K7rvhO4IuYvbvEz1uKt0Rf7yeEHkL4tzHX+X4FOAicA5wJPBONddWoa1/HMvsq8C1gE7lrejuAzwOXAt8bc2xpfz9xC6FrzHW/hWOcC/wEOJeR5udHY/43YGn0GqsL/l7+e/ga6dyf7ui1UsB3GTl9/HjgdOAXwPcwG/kHllJ7wClAALZG79UV/X539Pt3Ar9HCKsq/esREZHq0mRXRESqaVn09YkSjs0f00Juw6KxTgTeSwiPEMJRQvgu8GfRsZ8bPsrsxcA3gCPAZdHko48Q1gP/QG6TrA9NMoZFhPAJQthLCPuAT0SPv6+E8RdndjxmHwL+EugHPjbJkU8SwlWE8CwhPEhuwnrfFK99IfBR4AZC+BtCeJ4Q9kefuXPMsdP5+ynmsxOsdo78Kd955Cbtawnh51Hz3eT+QWKgzNf6GPBO4B8I4euE0Bv9Q8fHgM3AFzB75SS/O3GPEB4BbgNWYvaqUb9hdha567HXlzlOERGJkSa7IiJSTQuir30lHHuk4PsXTfD8LYRwYMxj/x59fW/BauT7ye3q+21C2D/m+H+Lvq6eZAw3jfophKeB54HTJh92Ud8smOw9RW719HvAa4ZXAsfbMGYMXyKEb0/xPn8QfZ1ocrWB3Ipv3nT+forJ78Y88Z/y5SfIFwyv9AOEcITcP6KU8g8oeR+Ovk709/Nv5K4p//1JfrdYj7XR17G/u4bcPzwcLmOMIiISM012RUSkmvKT09klHDun4PuxkzCAx8c9EsKzwAvkJscvix49J/q6fYLX2BN9ffUkp+runeCx3jFjK8flBRO+FCEsJoRLCGFHkd/ZU+S5ybwm+rpz3DMhPE4If1jwyHT+fmrpR+RWtN8OPIrZVzD7FcyaCOGxSTc7G8tsPvDy6KcHJzgi/9hrJngOivf4LrnTmi/DbF70frPJrT6vLfJ7IiKSgKT/j01ERHzZFX1dWsKx+WP6ge4Jnu+d5Pfyq2cLxnz98gSn0h6MnpvFxKvHE61AB6CSlclKlbIKPtbC6GspK4nT+fupnRCOAq8D0uT+m/g4uR27d2P2/jJeKf85BglhcILn839nCyd4Dor1yL3eOmA+uWujIbcp28OEcHcZYxQRkRrQZFdERKrplujrOUWPyvnl6GtXdKrqWPMm+b38Ka75VeT8qvDvFT2tdvwpvI0s/1nmFj1q9LH1//cTwiFC6CR37e4byV1rvBS4DrNSr6POf44WzFomeD7/d/ZChaP8Orl/EMmfyrwGreqKiNQlTXZFRKSa/h14DHgTZidPcWx+te4Lkzz/knGPmC0it0vvAeCR6NH8rs4dE76K2bJxt7hpfPndrl8+7hmzJdEtdxZFjzTG34/ZSzBbCUAIgRDuIITfAz4YHVHaDtm562Z/Ef10xgRH5B8rZcfwiV5/N3A7sAKz1cBy4IaKXktERGKlya6IiFRPCAPkdjLOAP88fG/UsXKThDcDXyWE2yd5tXdgtmDMY++Jvv4LIWSj779F7pTn9457v9wtaDYwMrH24mvR10smeO7DwKfJbbQFjfP38xZytwka6/7o69jTi18gd/p1jtl6zD4V/ZT/+7mU8S4BskxvNTb/u18D1hPCZKfci4hIgjTZFRGR6grhDuDXyZ2m3IXZ2zFbgFkbZmdi9n/JnQr6j8AfF3mlu4FvYfay6HcvIre78cPAZwve7xly981dCtyE2Ssxm4PZK8hN5I4ZdbwHIWwCvkpuo6Q/x+wYzBZi9rvAFcAnhjd0aqy/n3Mw+zxmS6PmryB3r9xBxk+EtwJnRMcuB95FbgdsgKvJ7bT9p5j9HmZzMTshujfxa4ErCOHeaYzzO8Cz5CbbOoVZRKROWQiV3ApPRERkCmbtwB8CFwCnAm3APuC/gasJYeLTSHOn1N5O7n6xd5GbiJ0FHCV3G5//E90Td+zvvQb4c3LXes4hd6uaW4AvEMKTBceN/z++EAyzNOMnfZ2EkC7yGSf6HYDrCGH1JL+zitznG+vNo25PZNYF/ErR8Zj9DvARcn8//cAO4POE8IMJ3re0v5/J5FbjvznBM5cTwrqC47qBsaewP0YIHZN+9tzf/0JyuxpfTO5WQ8eR2/l4C3AlIWwdM54zgGuAV5G7jdV/kJvkZ6LnU+Tut3s5cDq5CfM2cvfe/V7B60w8prE9xjL7CvAGQnj1pMeIiEiiNNkVEZH6UjjZLTbRFElS7h8j/o0Q/jnpoYiIyMR0GrOIiIjIVMzOie6pm9vUC1YA/5romEREpChNdkVERESmdjXwfszmA/8A/DMhHEp4TCIiUoROYxYRkfox0fW0U107KVILZv8C/Ca5e+x+H1g9yf2hRUSkTmiyKyIiIiIiIu7oNGYRERERERFxp3nqQxrXcccdFzo6OpIeRlFHBo8wp2VO0sOQGKitb+rrm/r6pba+qa9v6utbpX23bdv2XAjh+Imecz3Z7ejoYOvWrVMfmKCdz+3k9ONOT3oYEgO19U19fVNfv9TWN/X1TX19q7SvmT022XOJncZsZqeb2faCPwfN7I/M7Fgz+5GZPRR9PSY63szsK2a228zuNTMXN3Fff9/6pIcgMVFb39TXN/X1S219U1/f1Ne3OPomNtkNIewMIZwdQjib3L3qjgDfAT4F3BZCOA24LfoZ4B3AadGfNcDXaj/q6jt36blJD0Fiora+qa9v6uuX2vqmvr6pr29x9K2XDarOAx4OITwGXARcFz1+HfCu6PuLgG+FnDuBhWa2uPZDra7egd6khyAxUVvf1Nc39fVLbX1TX9/U17c4+tbLZPcSIL9ufUIIYV/0/VPACdH3JwJ7Cn7nieixhrbjmR1JD0Fiora+qa9v6uuX2vqmvr6pr29x9E2l0+mqv2g5zKwVWAt8NJ1OH+7s7PxUOp2+EiCdTtPZ2XlFOp3+Qmdn52XAHel0+nGAzs7ODwD/lU6n9455vTWdnZ3XdHZ2rsladknvil7aZ7ez4f4N3LL7Fpa1L+OqzVfRc6SHPQf2cP2917N43mKu234dXd1dnLTgJL5055c41H+IXT27WH/fejoWdnD1z65my5NbaJ/dzle3fJX+oX7ueeoeNty/Yfg1dzy9gzktc/ja1twZ1j/d81M2PrBx+Pmdz+3EMNZuW0trqpXbHr2NPQf2sPyE5Vy1+Sq693dzZPAI1/78Wua3zufmnTezadem4d/fe2gvPX09rNu+rq4/03cf/O7w8zP5M+14egdL5i9x9Zk8dqr0M3Us7GDPgT2uPpPHTpV+ppVLVvKte77l6jN57FTJZ/r103+da7Zd4+ozeexU6Wd66PmH+PGjP3b1mTx2qvQz7erZxenHne7qM3nsVOlnOnPRmWx/anvZn+nGa27cl06n10441wwhlDc7rTIzuwj4aAjh/OjnncCqEMK+6DTlrhDC6WZ2TfT9+rHHTfbaK1euDPW+G3O6K016VTrpYUgM1NY39fVNff1SW9/U1zf19a3Svma2LYSwcqLn6uE05ksZOYUZ4CbgA9H3HwBuLHj8/dGuzK8FDhSb6DaK9tntSQ9BYqK2vqmvb+rrl9r6pr6+qa9vcfRN9D67ZjYXeBvw+wUPXwlsMLMPAY8Bvx09/n3g14Dd5HZuvryGQ43Nqo5VSQ9BYqK2vqmvb+rrl9r6pr6+qa9vcfRNdGU3hHA4hNAeQjhQ8FhPCOG8EMJpIYS3hhCejx4PIYSPhhBOCSEsDyHU9/nJJdr4wMakhyAxUVvf1Nc39fVLbX1TX9/U17c4+tbDacwzmv6Fyi+19U19fVNfv9TWN/X1TX19c7eyK7D30N6pD5KGpLa+qa9v6uuX2vqmvr6pr29x9NVkN2G7enYlPQSJidr6pr6+qa9fauub+vqmvr7F0TfxWw/FqRFuPbT30F6WzF+S9DAkBmrrm/r6pr5+qa1v6uub+vpWad96v/XQjLZ224T3PxYH1NY39fVNff1SW9/U1zf19S2OvprsJmzxvMVJD0Fiora+qa9v6uuX2vqmvr6pr29x9NVkN2Erl0y44i4OqK1v6uub+vqltr6pr2/q61scfTXZTdjNu25OeggSE7X1TX19U1+/1NY39fVNfX2Lo68muwk7/5Tzkx7CtK343I+4ZO3mpIdRdzy0lcmpr2/q65fa+qa+vqmvb3H01WQ3YR62UO85PMCdjzyf9DDqjoe2Mjn19U19/VJb39TXN/X1LY6+muwmrHt/d9JDKMsLhwd45NnepIfREBqtrZRHfX1TX7/U1jf19U19fYujr+6zm7BGu1/Yyr/+L57r7af7yncOP9bxqe8BjHpMGq+tlEd9fVNfv9TWN/X1TX190312HWq0+4U919uf9BAaRqO1lfKor2/q65fa+qa+vqmvb7rPrkMdCzuSHoLERG19U1/f1NcvtfVNfX1TX9/i6KvJbsKWtS9LeggSE7X1TX19U1+/1NY39fVNfX2Lo68muwm79eFbkx5CRbJZv9d6V0ujtpXSqK9v6uuX2vqmvr6pr29x9NVkN2EXLrsw6SFUZOPdTyQ9hLrXqG2lNOrrm/r6pba+qa9v6utbHH012U3Y1r31vVv0ZP6/b9/LQ08fSnoYda1R20pp1Nc39fVLbX1TX9/U17c4+mqym7B9vfuSHkLFDh4dxPOtq6arkdvK1NTXN/X1S219U1/f1Ne3OPpqspuwNSvWJD2Eih0dzDKka3cn1chtZWrq65v6+qW2vqmvb+rrWxx9NdlNWCPfL6y3f4ihjCa7k2nktjI19fVNff1SW9/U1zf19U332XWokbdQP9A3yFA2m/Qw6lYjt5Wpqa9v6uuX2vqmvr6pr2+69ZBDS+YvSXoIFTvYN8jBo0NJD6NuNXJbmZr6+qa+fqmtb+rrm/r6FkdfTXYT1tXdlfQQKvb84QFef+WPkx5G3WrktjI19fVNff1SW9/U1zf19S2OvprsJuziMy5OeggVe3J/X9JDqGuN3Fampr6+qa9fauub+vqmvr7F0VeT3YQ18r9Q7Xn+yKifdRui0Rq5rUxNfX1TX7/U1jf19U19fdPKrkM9fT1JD6FiY1d2dRui0Rq5rUxNfX1TX7/U1jf19U19fYujr3lejVu5cmXYunVr0sMoau+hvQ11sf3LPv09JpvTPvBXv8rs1lRtB1THGq2tlEd9fVNfv9TWN/X1TX19q7SvmW0LIayc6Dmt7Cas0e4XlmqySZ8b1G2IRmm0tlIe9fVNff1SW9/U1zf19U332XVo+aLlSQ+hLMUmu0MZv2cJVKLR2kp51Nc39fVLbX1TX9/U17c4+mqym7B5rfOSHkJZUlZksquV3VEara2UR319U1+/1NY39fVNfX2Lo68muwnb/MTmpIdQFq3slq7R2kp51Nc39fVLbX1TX9/U17c4+mqym7BLz7w06SGURZPd0jVaWymP+vqmvn6prW/q65v6+hZHX012E7Zp16akh1AWbVBVukZrK+VRX9/U1y+19U19fVNf3+Loq8luwvoz/UkPoSxa2S1do7WV8qivb+rrl9r6pr6+qa9vcfTVZDdhly2/LOkhlK2tuYlPnHfauMcHM1rZLdSIbaV06uub+vqltr6pr2/q61scfTXZTdi67euSHkJZMln4zVcvZdkJ8yd4Tiu7hRqtrZRHfX1TX7/U1jf19U19fYujrya7CVuxeEXSQyhLNgRSk/xXo1sPjdZobaU86uub+vqltr6pr2/q61scfTXZlbJksoGUGYeODo57blDX7IqIiIiISJ3QZDdh2/ZtS3oIZclmA01NxjvOXMw5HcdSuF/VJWvv5D/vfiK5wdWZRmsr5VFf39TXL7X1TX19U1/f4uiryW7CVp+9OukhlCUTciu7C+a0sOHD59Jx3NxRz3/zJ93JDKwONVpbKY/6+qa+fqmtb+rrm/r6FkdfTXYTdsOOG5IeQlky2TDq9kOfueAVHD+/bfjnV560IIlh1aVGayvlUV/f1NcvtfVNfX1TX9/i6KvJbsLaUm1TH1RHsiF3GnPem09fxM/+/K10fXIVoB2ZCzVaWymP+vqmvn6prW/q65v6+hZHX012E3bBsguSHkJZ8htUjdVx3FxObp/DkYFMAqOqT43WVsqjvr6pr19q65v6+qa+vsXRV5PdhK2/b33SQyhZCIFsYNTKbqHZLSlNdgs0Ulspn/r6pr5+qa1v6uub+voWR19NdhN27tJzkx5CyfJnKE+0sgswpzXFkYGhGo6ovjVSWymf+vqmvn6prW/q65v6+hZHX012E9Y70Jv0EEqWvx43Ncl/NXNam7WyW6CR2kr51Nc39fVLbX1TX9/U17c4+mqym7Adz+xIeggly4bcZHey05jntKbo02R3WCO1lfKpr2/q65fa+qa+vqmvb3H01WQ3YWtWrEl6CCUbXtktehqzJrt5jdRWyqe+vqmvX2rrm/r6pr6+xdFXk92Erd22NukhlCwT8qcxT7JBlU5jHqWR2kr51Nc39fVLbX1TX9/U17c4+iY62TWzhWb2bTN70MweMLNzzexYM/uRmT0UfT0mOtbM7CtmttvM7jWzVyc59mppn92e9BBKlslEpzFrg6qSNFJbKZ/6+qa+fqmtb+rrm/r6FkffpFd2vwz8IITwcuCVwAPAp4DbQginAbdFPwO8Azgt+rMG+Frth1t9qzpWJT2Ekty/9wCrv7kFmHxld05rir7BDCFaAZ7pGqWtVEZ9fVNfv9TWN/X1TX19i6NvYpNdM1sAvAm4FiCEMBBC2A9cBFwXHXYd8K7o+4uAb4WcO4GFZra4xsOuuo0PbEx6CCW5YuO93PPEAaDYacwpQoCjg9laDq1uNUpbqYz6+qa+fqmtb+rrm/r6FkffVDqdrvqLlqKzs/MM4Dzg9Z2dnZ/t7Ox8TWdn523AX4YQ/iI65jDwuXQ6fWVnZ+eHge+n0+nHo+d+A7grnU7vLXxdM1vT2dl5TWdn55qsZZf0ruilfXY7G+7fwC27b2FZ+zKu2nwVPUd62HNgD9ffez2L5y3muu3X0dXdxUkLTuJLd36JQ/2H2NWzi/X3radjYQdX/+xqtjy5hfbZ7Xx1y1fpH+rnnqfuYcP9G4Zfc8fTO5jTMoevbc0tOv90z0/Z+MDG4ed3PrcTw1i7bS2tqVZue/Q2tj+1nXNOPIerNl9F9/5ujgwe4dqfX8v81vncvPNmNu3aNPz7ew/tpaevh3Xb19X8M11/56P09bcCcDR1F+e+bOm4z9R7eCH3PD5Ej/0Hr1h0at1/pnI6fffB7w4/X+pn6uru4pRjTnH1mTx2qvQztaZa2X90v6vP5LFTpZ/p+LnHc+POG119Jo+dKvlMZy46kw33b3D1mTx2qvQz/WTPT7jrybtcfSaPnSr9TJuf2MzZLz7b1Wfy2KnSz7Rw1kIeeeGRsj/TjdfcuC+dTk94wa8ldcqpma0E7gReH0K4y8y+DBwEPh5CWFhw3AshhGPMbBNwZQjhjujx24ArQghbJ3uPlStXhq1bJ326Ltyw4wYuW35Z0sOY0kX/9BPu2bMfgL+7+Cx++zUnjTtm/ZbH+fR/7mDzp9/C4gWzJ32tEAI/2d3D609txya5/teDRmkrlVFf39TXL7X1TX19U1/fKu1rZttCCCsnei7Ja3afAJ4IIdwV/fxt4NXA0/nTk6Ovz0TPPwkUzrCWRo81tF09u5IeQkkKz1ye7D67rancf04DQ8VPY95495O879q7+Pa2J6o2vnrUKG2lMurrm/r6pba+qa9v6utbHH0Tm+yGEJ4C9pjZ6dFD5wG/AG4CPhA99gHgxuj7m4D3R7syvxY4EELYV8sxx6FR7hdWuANzapL/alqbS5vsPt5zGIAn9/dVZ3B1qlHaSmXU1zf19UttfVNf39TXN4/32f048K9mdi9wNvC3wJXA28zsIeCt0c8A3wceAXYDXwc+UvvhVl+j3C9s1MruJKce5ye7/VNMdrOh+Ot40ShtpTLq65v6+qW2vqmvb+rrWxx9m6v+imUIIWwHJjq/+rwJjg3AR2MfVI0tntcYG0rbqJXd4pPdgUzxyW4gf7/eKg2uTjVKW6mM+vqmvn6prW/q65v6+hZH36RXdme8lUsmvJa67hROTFOTrMi2lXjNbn5l1/PmVNA4baUy6uub+vqltr6pr2/q61scfTXZTdjNu25OegglKTzleLINqtpaxk92hzJZzruqix/c99TwY9loB3Dnc92GaSuVUV/f1NcvtfVNfX1TX9/i6KvJbsLOP+X8pIdQklEbVE12zW4qBYy+ZvfIYIaHnz3Mw8/2Dj+Wv9vVZK/jRaO0lcqor2/q65fa+qa+vqmvb3H01WQ3YY2yhXrhvHTerIkv9Z5oN+bB6PtMduR+ztnszFjZbZS2Uhn19U19/VJb39TXN/X1zdWthySne3930kMoSeH1tcfMaZ3wmJENqjLDjw1mchPbUZPdGbIbc6O0lcqor2/q65fa+qa+vqmvb3H01WQ3YY1yv7AQRiarC+e0THjMRCu7+e+zoXCym9+N2fdkt1HaSmXU1zf19UttfVNf39TXN4/32Z3xGuV+YYUT2EknuxPsxpy/DVHhym6YIRtUNUpbqYz6+qa+fqmtb+rrm/r6FkdfTXYT1rGwI+khlKTw3rltzakJj8nvxly4QdVgfrIbZt5pzI3SViqjvr6pr19q65v6+qa+vsXRV5PdhC1rX5b0EEoy1b1zoWBlNzPBaczZ8acxF54a7VGjtJXKqK9v6uuX2vqmvr6pr29x9NVkN2G3Pnxr0kMoyWCmjMnuRCu7Bb+en/cOZX1PdhulrVRGfX1TX7/U1jf19U19fYujrya7Cbtw2YVJD6EkpazsNjUZLSkbdRrzwPCth0Yey6/oZpxPdhulrVRGfX1TX7/U1jf19U19fYujrya7Cdu6d2vSQyjJYCYwuyXFdR88p+hxrakm+gZGbj00MOE1u2HcYx41SlupjPr6pr5+qa1v6uub+voWR19NdhO2r3df0kMoSf9Qlne96kR+ZdnxRY87PJBh3U+7+Vn380DhfXZHjsnPcTMZ35PdRmkrlVFf39TXL7X1TX19U1/f4uiryW7CGuV+YQNDGdqaS//P5d4nDkS/N36DqvyKrvdrdhulrVRGfX1TX7/U1jf19U19fdN9dh1qlPuFDWYCLanSbxV0/Py26PfGn8Y8FK3oZp2fxtwobaUy6uub+vqltr6pr2/q65vus+tQI2yhvmHrHvoGMzSnSv/PZTBa0c1fs1u4sjsUbVblfWW3EdpK5dTXN/X1S219U1/f1Nc33XrIoSXzlyQ9hCltfrgHgNe+rH3KYz/9jpcDDO/InD+NuXBiOzA0M3ZjboS2Ujn19U19/VJb39TXN/X1LY6+muwmrKu7K+khlGTpMbOn3JwK4D2vOQmA/qHcjswTncY8cu9d35PdRmkrlVFf39TXL7X1TX19U1/f4uiryW7CLj7j4qSHMKXBTJbWEk9hbmtOASMru4NFTmP2PtlthLZSOfX1TX39Ulvf1Nc39fUtjr6a7CasEf6FaigTaC5xc6rWaMfm/sHRpzEXTmwHh/K7MWfxrBHaSuXU1zf19UttfVNf39TXN63sOtTT15P0EKY0lM3S3FTafyqpJqMlZcOnMQ9MsPPy4PDKbpUHWmcaoa1UTn19U1+/1NY39fVNfX2Lo68muwlrhPuFlXvbobbmFEcHR5/GPGpld/gx37PdRmgrlVNf39TXL7X1TX19U1/fdJ9dhxrhfmFD2WxZtx1qa24aWdnNn8ZccHlu/hRn77ceaoS2Ujn19U19/VJb39TXN/X1TffZdWj5ouVJD2FKg5lAc1M5K7tN4zaoyq/ibnn0eR56phcYvWmVR43QViqnvr6pr19q65v6+qa+vsXRV5PdhM1rnZf0EKY0lMnSUs7Kbktqgrl8p4IAACAASURBVMlubmJ72wNPAzCrpcn9ym4jtJXKqa9v6uuX2vqmvr6pr29x9NVkN2Gbn9ic9BCmNJQtfTdmiFZ2B3OnMecnvfnLc7t7DnPqonmcdMwc97ceaoS2Ujn19U19/VJb39TXN/X1LY6+muwm7NIzL016CFPKncZc7jW7+ZXd3IQ2E+3G/FjPETra55BqMveT3UZoK5VTX9/U1y+19U19fVNf3+Loq8luwjbt2pT0EKaUO425jJXdltTwBlWDBffZDSHwWM8RXnLsXJpT/ie7jdBWKqe+vqmvX2rrm/r6pr6+xdFXk92E9Wf6kx7ClHKnMVe2sjsQXbObDYHDAxn6BjO8eEEbKTP31+w2QlupnPr6pr5+qa1v6uub+voWR19NdhN22fLLkh7ClAYzWVrK2o05NXx7ocINqvLX8c5qSc2I05gboa1UTn19U1+/1NY39fVNfX2Lo68muwlbt31d0kOY0lCmzA2qWia4z242DK/2tjU30dzU5H6y2whtpXLq65v6+qW2vqmvb+rrWxx9NdlN2IrFK5IewpSGstmyT2M+Ojj6NObCyW5rcxNNTbif7DZCW6mc+vqmvn6prW/q65v6+hZHX012ZUqDmVD+acxj77MbwvAqb1tziuamJoby9yMSERERERGpMk12E7Zt37akhzCloUz5K7sjuzHnVm+z2TD8WFtzU+6aXd8Luw3RViqnvr6pr19q65v6+qa+vsXRV5PdhK0+e3XSQ5jSYDbQUs5kt2X8bsyZUHjNbn6DKt8ru43QViqnvr6pr19q65v6+qa+vsXRV5PdhN2w44akhzClsu+z25xiYChLKDh1OZsd2ayqNVrZHXK+tNsIbaVy6uub+vqltr6pr2/q61scfTXZTVhbqi3pIRSVzQayAZqbyjuNGeDhZ3vZd6APyG1yVXgac3OTkQ2+J7v13lamR319U1+/1NY39fVNfX2Lo29z1V9RynLBsguSHkJRg9GpxmXdeiia7L71//7P8GOZLMP33m1rmRkru/XeVqZHfX1TX7/U1jf19U19fYujr1Z2E7b+vvVJD6Go/IS0nNOYZ7Wkxj2WLbhmtzWVW9nNOF/Zrfe2Mj3q65v6+qW2vqmvb+rrWxx9NdlN2LlLz016CEXlbx1UyWnMhTLZglsPtaRINTW5X9mt97YyPerrm/r6pba+qa9v6utbHH012U1Y70Bv0kMoarCCld22iVZ2x9x6qCVlwxNpr+q9rUyP+vqmvn6prW/q65v6+hZHX012E7bjmR1JD6GooeFrdqe5slt4GnNzE80pYyjre2W33tvK9Kivb+rrl9r6pr6+qa9vcfTVZDdha1asSXoIReVPNW5uKn+Dqrwmy53GPHKf3Saam5rcr+zWe1uZHvX1TX39Ulvf1Nc39fUtjr6a7CZs7ba1SQ+hqPyEtKWsld3RpzHPaknRP5Tl73+4E8htUNWS8r8bc723lelRX9/U1y+19U19fVNf3+Loq8luwtpntyc9hKLypxqXdeuhltH/WY2dKJsZzamm4VOkvar3tjI96uub+vqltr6pr2/q61scfTXZTdiqjlVJD6GoauzGHCa4xVBLkzGYCRM+50W9t5XpUV/f1NcvtfVNfX1TX9/i6KvJbsI2PrAx6SEUtevpQwAsWTir5N8ZexrzRPtQpaLJs+c9quq9rUyP+vqmvn6prW/q65v6+hZHX012E1bv/0J1+4PPcty8Ns5csqDk3xm7spuZYEabPy3a8yZV9d5Wpkd9fVNfv9TWN/X1TX1908quQ3sP7U16CEU9+txhzjzxRTSVsRvzrDH32c0UnKr85tOPB0bu2+v59kP13lamR319U1+/1NY39fVNfX2Lo2+ik10z6zazHWa23cy2Ro8da2Y/MrOHoq/HRI+bmX3FzHab2b1m9uokx14tu3p2JT2EorIhkLLSJ7owfoOqwnnyFy4+Cxi5BnjI8cpuvbeV6VFf39TXL7X1TX19U1/f4uhbDyu7bw4hnB1CWBn9/CngthDCacBt0c8A7wBOi/6sAb5W85HGoN7vFxZCbvfkcswquGb3lUsX8JFVpw7/nL+et2X4NGa/K7v13lamR319U1+/1NY39fVNfX2rm/vsmlmbmbVWezCRi4Drou+vA95V8Pi3Qs6dwEIzWxzTGGqm3u8Xlg2BMue6tBZcs/uFd5/FcfPahn/Or/o2R7cj8nz7oXpvK9Ojvr6pr19q65v6+qa+viV2n10zO9vM/tbMfmpmB4AjQJ+ZHTCzn5jZ35jZqyp4/wDcambbzCw/lT8hhLAv+v4p4ITo+xOBPQW/+0T0WENbPK/+5+tlXK47zqzmFHPbRlZ6W6NJbnP0okOOV3Yboa1UTn19U1+/1NY39fVNfX2Lo29zsSfN7ALgM8BKwIBuYAvQE/18LHAq8GngU9F1t38VQvheie//hhDCk2a2CPiRmT1Y+GQIIZhZWbOhaNK8BuCEJSeQ7kpz8RkX09XdRU9fD2tWrGHttrUsX7Scea3z2PzEZi4981I27dpEf6afy5Zfxrrt61ixeAUA2/ZtY/XZq7lhxw20pdq4YNkFrL9vPecuPZfegV52PLNj+DXbZ7ezqmMVGx/YyKqOVew9tJddPbuGn188bzErl6zk5l03c/4p57OrZxfb9m1j76G9rN22lo6FHSxrX8atD9/KhcsuZOverezr3Tf8+8val7Fk/hK6urtq9pmePfxKjpk3RLorXfJn6t7fTXPTOQxlAzft2giDLxnu8/W717Kvdx8vaX03AN954CbOOvHFNf1MlXTq3t89/Hypnbbt28aOp3e4+kweO1X6mRa0LeDmnTe7+kweO1X6mRbNXVT2/+7V+2fy2KmSz/TaE19Luivt6jN57FTpZ9r9/G7SXWlXn8ljp+l8pu793e4+k8dOlXymxfMWc8OOG8r+TEWFECb8A/wYyJC7bnY1uRXXyY49Afhgwe/812THFnmNNPBJYCewOHpsMbAz+v4a4NKC44ePm+zPihUrQr377O2fTXoIRb31qq7wB9dvLfv3/vb7vwgnX7EpHOwbCHc89Gw4+YpN4eQrNg0/f9P2J8PJV2wKu546WM3h1pV6byvTo76+qa9fauub+vqmvr5V2hfYGiaZDxY7jXk/8KoQwnkhhHUhhKeLTJifDiH8vxDCW4AVwKHiU2wws7lmNj//PXA+cB9wE/CB6LAPADdG398EvD/alfm1wIEwcrpzwzr/lPOTHkJR2RAwyj+P+Yq3v5y7P/M25s9qYU5ratzzM2GDqnpvK9Ojvr6pr19q65v6+qa+vsXRd9LJbgjhN0MI95b7giGE7SGE3yjh0BOAO8zsHnKnRn8vhPAD4ErgbWb2EPDW6GeA7wOPALuBrwMfKXds9ajet1APUPYGVQBNTcaxc3N7mM1pHX+2/PCthxxvUFXvbWV61Nc39fVLbX1TX9/U17c4+ha9ZjdOIYRHgFdO8HgPcN4EjwfgozUYWk117+9OeghFVXLrobEmWtltngEru/XeVqZHfX1TX7/U1jf19U19fYuj77Tvs2tmc8yspRqDmYnq/X5hIYRp7cYME092W/K3Hsr4Xdmt97YyPerrm/r6pba+qa9v6utbYvfZjW49dOGYx+ab2XeAg8AhM7vWzNomfgWZTL3fLywbqOCK3dHmtk10GnN066Gs35Xdem8r06O+vqmvX2rrm/r6pr6+xdG31NOYvwq8ANxc8NjfAL8O/AvQClxO7prav6nmAL2bcrvshAUCTdM8jbmtefy/qTRHK7uDjld2672tTI/6+qa+fqmtb+rrm/r6FkffUk9jfhXww/wPZpYC3g/8cwhhdQjhMuBa4LKqj9C5Ze3Lkh5CUdks017aneia3/zKbsbxym69t5XpUV/f1NcvtfVNfX1TX9/i6DvpZNfM3hT9eTswG3hR/jHgvcCLgEcLHtsDdBT83kuqPlqHbn341qSHMKXpruxOZCZsUNUIbaVy6uub+vqltr6pr2/q61scfYudxnx59DW/+dSbgNOi788AssAvRX8AFgFtwGpya4HfAR6v4lhdunDZhVMflKDcfXarb3iDKse3Hqr3tjI96uub+vqltr6pr2/q61scfYvdZ/fy6M/7gD7gtvxjwA7goYJjLgf+EXguhPDB6LGbqj5ah7bu3Zr0EIoKoToru+sufw03f+wNwz8Pb1DleGW33tvK9Kivb+rrl9r6pr6+qa9vcfQtdYOq/wWuMLO9wDxy1+Z+acwxK4FHqzi2GWFf776kh1BUNgSqcRbzqtMXjfq5ZQZsUFXvbWV61Nc39fVLbX1TX9/U17c4+pY62f0kcCu5nZcB7gH+fswxlwHrqzSuGaPe7xcWmHiDqenKX7Pr+dZD9d5Wpkd9fVNfv9TWN/X1TX19S+w+uyGE+8hdp/tO4G3Aa0MI+/PPm9lC4AvA16s+Qufq/X5hoUoru2M1N0XX7Dpe2a33tjI96uub+vqltr6pr2/q61uS99klhHAAuGWS5/YD11VrUDNJvW+hng3QFMtk1/9uzPXeVqZHfX1TX7/U1jf19U19favprYekNpbMX5L0EIoKIWAx7Mfc0uz/mt16byvTo76+qa9fauub+vqmvr7F0bfYfXY/ZGZlT4bNLGVmvzu9Yc0cXd1dSQ+hqLhWdme3pAA4PJCp/ovXiXpvK9Ojvr6pr19q65v6+qa+vsXRt9hk9irgQTP7mJkdN9ULmdkJZvbHwE7Gb14lk7j4jIuTHkJRuWt2qz/bTTUZ89qa6T06VPXXrhf13lamR319U1+/1NY39fVNfX2Lo2+xye5pQBfwReBJM/uJmX0xmvxeZmbvNbOPm9lXzGwLsIfcJlU/AnRCfYnq/V+oQiCWDaoA5rU1c+joYDwvXgfqva1Mj/r6pr5+qa1v6uub+voWR99JN6gKITwLrDGzTuDDwLuBT0xy+P3AXwNfDyHoBlhl6OnrSXoIRQWI5ZpdgPmzmunt97uyW+9tZXrU1zf19UttfVNf39TXtzj6TrkbcwjhSeAzwGfMbBHwCuB4cvOgZ4H7QwjPVX1kM0S93y8sG0Is1+wCzJvVzCHHpzHXe1uZHvX1TX39Ulvf1Nc39fUtsfvs5oUQngkhdIUQ/iOE8O0Qwn9rojs99X6/sDhPY54/q4VDjld2672tTI/6+qa+fqmtb+rrm/r6Fkdf3XooYcsXLU96CEXlVnZjOo3Z+TW79d5Wpkd9fVNfv9TWN/X1TX19i6NvSZNdM1tgZn8WbVL1rJn1R1/vMLNPmdmLqj6yGWJe67ykh1BUAGK6ZDd3za7j05jrva1Mj/r6pr5+qa1v6uub+voWR98pJ7tmdha5Dag+B5wLtALPRF9fB/wtcJ+ZvaLqo5sBNj+xOekhFBViXNnN7cbsd7Jb721letTXN/X1S219U1/f1Ne3OPoWneya2SxgI7kNqf4WeGkIYUEI4aQQwgLgpdHjJwD/aWZtVR+hc5eeeWnSQygqhNgWdpk/q4W+wQxDmWxM75Csem8r06O+vqmvX2rrm/r6pr6+xdF3qpXdS4BTgMtCCJ8JITxW+GQI4bEQwl8A7yN3b91Lqj5C5zbt2pT0EIqK85rduW0pAA4PZGJ5/aTVe1uZHvX1TX39Ulvf1Nc39fUtjr5TTXZ/HdgSQthY7KAQwn8AW4CLqjWwmaI/05/0EIoKxLcbc1tz7j+/gSGfK7v13lamR319U1+/1NY39fVNfX2Lo+9Uk91XAreW+Fq3RsdLGS5bflnSQygqd+uheGa7rfnJrtPTmOu9rUyP+vqmvn6prW/q65v6+hZH36kmu8cDj5f4Wo9Hx0sZ1m1fl/QQJhVCAKAptpXd3GnM/YM+T2Ou57Yyferrm/r6pba+qa9v6utbHH2nmuzOBY6U+Fp90fFShhWLVyQ9hEllc3NdLKYtqryv7NZzW5k+9fVNff1SW9/U1zf19S2OvlNNduPaiFcaQPwru7n//PoHfU52RUREREQkOVPeZxf4UzO7aao/wJ/EPViPtu3blvQQJjW8shvTZNf7ym49t5XpU1/f1NcvtfVNfX1TX9/i6NtcwjGviv6UIkxjLDPS6rNXJz2ESYUoZ1wbVI1cs+tzslvPbWX61Nc39fVLbX1TX9/U17c4+hZd2Q0hNJX5J1X1ETp3w44bkh7CpELNVnZ9blBVz21l+tTXN/X1S219U1/f1Ne3OPqWchqzxKgt1Zb0ECaVn+w2xbay6/ua3XpuK9Onvr6pr19q65v6+qa+vsXRd1qTXTNbYmavMbOF1RrQTHPBsguSHsKkstFsN65dyrxfs1vPbWX61Nc39fVLbX1TX9/U17c4+had7JrZ2Wb2J2bWPubx48zsFmAPcCfwtJn9ZdVHNwOsv2990kOYVP4CbK3sVqae28r0qa9v6uuX2vqmvr6pr29x9J1qZffDwB+FEHrGPP4N4O3Ao8B3gBeAz5rZu6o+QufOXXpu0kOY1PDKbszX7PY7Xdmt57Yyferrm/r6pba+qa9v6utbHH2nmuyeC9xS+ICZnQz8OnAP8EshhHcDy4Engd+r+gid6x3oTXoIkxrZoCre3ZgHhnxOduu5rUyf+vqmvn6prW/q65v6+hZH36kmu0uAXWMee0v09eoQQj9ACOFZ4Hrg1dUdnn87ntmRyPve/fgLrPr72+ntH5r0mBDzNbvDpzEP+dyNOam2Uhvq65v6+qW2vqmvb+rrWxx9p5rszgP2j3nsHHKXc94+5vGHgWOrNK4ZY82KNYm879//YCfdPUfY/vjYvCNGdmOOZwytqWiDKqcru0m1ldpQX9/U1y+19U19fVNf3+LoO9Vk9wng1DGPvQ7YH0LYPebxZkDnFpRp7ba1ibxvKprB5q/LncjINbvxzHabmoyWlNHvdLKbVFupDfX1TX39Ulvf1Nc39fUtjr5TTXa3Au83s8UAZnYuuetz/2uCY18B7K3u8Pxrn90+9UExaIomu5kik92R3ZjjG0dbc8rtym5SbaU21Nc39fVLbX1TX9/U17c4+k412b0SWAQ8aGZbyE1ys8CXJzj2AuCu6g7Pv1UdqxJ53/wENpSwshvbdszkdmT2es1uUm2lNtTXN/X1S219U1/f1Ne3OPoWneyGEO4BfgN4nNyK7qPAe0IIPy08zszeTm5SfMu4F5GiNj6wMZH3TUUT2KHM5JNdYr5mF3KbVHld2U2qrdSG+vqmvn6prW/q65v6+hZH3+apDgghbAI2TXHMD4H51RrUTJLYym40gy12vWw2v7Ab237M+ZVdn5Nd/eujb+rrm/r6pba+qa9v6utbzVd2JX57DyVzmXN+tfbo4OSnEIdoaTfOld3WVBODGZ+T3aTaSm2or2/q65fa+qa+vqmvb3H0Lbqya2ZvKvJ0APqAR0MIPVUd1Qyyq2fsbYxrI78bc7HJbjb+S3ZpSTUxMFTkVOoGllRbqQ319U19/VJb39TXN/X1LY6+U53G3MXIpryTMrOfAB+PrvGVMiR1v7D87YSODk6+qhpivvUQQEuz35Vd3QvON/X1TX39Ulvf1Nc39fUtifvs/tUUf64itynVOcB/m9nYe/LKFBK7z240ge0rdhrz8DW78WlNmdvJru4F55v6+qa+fqmtb+rrm/r6Fkffoiu7IYR0KS9iZsuBzcCngQ9Nf1gzx+J5ixN530x0jnIpk92mOFd2HV+zm1RbqQ319U19/VJb39TXN/X1LY6+VdmgKoSwA7gWeGs1Xm8mWblkZSLvm98Bufg1u/nTmOMbR0uqiYFitz9qYEm1ldpQX9/U1y+19U19fVNf3+LoW83dmH8BvLiKrzcj3Lzr5kTeN7+aWnw35pzYV3ad3nooqbZSG+rrm/r6pba+qa9v6utbHH2rOdldCBwt95fMLGVmPzezTdHPLzWzu8xst5n9u5m1Ro+3RT/vjp7vqOLYE3P+Kecn8r4Dwyu7xe6zG//Kbmuz32t2k2ortaG+vqmvX2rrm/r6pr6+xdG3KpNdy23XeyFwfwW//gnggYKfvwB8MYRwKvACI9cAfwh4IXr8i9FxDS+pLdQHoglm30AJG1TFvLL70DO9XN21O7b3SIq2x/dNfX1TX7/U1jf19U19fYuj77Qmu2Y2y8xeBVwHnAusK/P3lwLvBL4R/WzAW4BvR4dcB7wr+v6i6Gei58+zOGdhNdK9vzuR982v7BbfoCpa2Y1xHC2p3H+Cf/eDnTG+SzKSaiu1ob6+qa9fauub+vqmvr7F0bfobsxmlqWE++ySmw/dEEIod7/oLwH/B5gf/dwO7A8hDEU/PwGcGH1/IrAHIIQwZGYHouOfK/M960pS9wvLT3YHilwvW6trdr3SveB8U1/f1NcvtfVNfX1TX9/i6JtKp9OTPtnZ2flm4LEifx4E/gv4ixDCP5TzxmZ2AbAkhPCNzs7ODuB1wHeB302n01+J3n8B8L50On11Z2fnR4Dr0+n0wei5TwDfSKfTR8a87prOzs5rOjs712Qtu6R3RS/ts9vZcP8Gbtl9C8val3HV5qvoOdLDngN7uP7e61k8bzHXbb+Oru4uTlpwEl+680sc6j/Erp5drL9vPR0LO7j6Z1ez5ckttM9u56tbvkr/UD/3PHUPG+7fMPyaO57ewZyWOXxt69cA+Omen7LxgY3Dz+98bieGsXbbWlpTrdz26G185vbPcP4p53PV5qvo3t/NkcEjXPvza5nfOp+bd97Mpl2bhn9/76G99PT1sG77uml/pp2PL+Hg0QwZenjjy5sn/Exf/Mm17NyziLNeMsimR79R8mf67oPfHX5+qs+0e18LT/Tk/s3lvOX9ddupnM+U7/TxWz7OisUrXH2mavy35+Uz3bDjBtpSba4+k8dOlX6mjb/YyNa9W119Jo+dKvlMXd1dbH5is6vP5LFTpZ/p47d8nN3P73b1mTx2qvQzffLWT7KqY5Wrz+SxU6WfaeMDGzkyeKTsz3TjNTfuS6fTEy66Wv5U1Vozs88DvwMMAbOAFwHfAd4OvDhavT0XSIcQ3m5mP4y+32xmzcBTwPGhyAdYuXJl2Lp1a+yfZTrWbV/H6rNX1/x9X3/lj3lyfx/LT1zAzR9/w4THPLDvIO/48v/yz+97Nb96Zjz3NfvrTb/gG3c8CkD3le+M5T2SklRbqQ319U19/VJb39TXN/X1rdK+ZrYthDDhfYsSO4c0hPDpEMLSEEIHcAnw4xDCe4HbgXdHh30AuDH6/qboZ6Lnf1xsotsolrUvq/l77nn+yPB9dovthJwd/uuN8TTmZr+nMSfRVmpHfX1TX7/U1jf19U19fYujbz3ONK4A/sTMdpO7Jvfa6PFrgfbo8T8BPpXQ+Krq1odvren7dT93mDf+3e0819sPTHHNbjTXbYpxh6rCa3az2Yb/t4tRat1Wakt9fVNfv9TWN/X1TX19i6Nv0Q2qaiWE0AV0Rd8/ApwzwTFHgd+q6cBq4MJlF9b0/Q4dHRr1c3+Rye4F/3gHEO+th1pTI689kMkyqykV23vVWq3bSm2pr2/q65fa+qa+vqmvb3H0rceV3RklvwFKrQxkRm41dOqiecP32x2rcJW1Viu7/YOTT7wbUa3bSm2pr2/q65fa+qa+vqmvb3H01WQ3Yft699X0/fIruf/6u7/M609pn/Sa3UzB5dBx3s141GQ3M/k9fxtRrdtKbamvb+rrl9r6pr6+qa9vcfTVZDdhtb5fWH6yO7s1RWtz06TX7GayhZPd+Ga7qYJlY28ru7oXnG/q65v6+qW2vqmvb+rrWxx9NdlN2NptE94SKjb5yW1rqqnoZHeocLIb43gKJ9WTnVLdqGrdVmpLfX1TX7/U1jf19U19fYujb1mTXTObb2Z/aWZ3mNlD0X1wMbPjosdfXvUROlfrLdTzK7uzWppoTaUYyoYJd0HOZAqv2Y1vujtqsltks6xGpO3xfVNf39TXL7X1TX19U1/f4uhb8m7MZnY8cAfwMmB39HU2QAjhOTP7ALCQ3G2BpERL5i+p6fuNrOymaGnOTWIn2gV5KDsy8Yzzmt3Ca4OL7QzdiGrdVmpLfX1TX7/U1jf19U19fYujbzkru38NvBj4ZeCNjD+79UbgvCqNa8bo6u6q6fvlJ7ttLU20RptD5U8fTt90P6/6q9z9rTJZrexOV63bSm2pr2/q65fa+qa+vqmvb3H0LWeyewFwdQjhbmD8ea/wCHBSVUY1g1x8xsU1fb/+odyOx62pJtqao8luNMlc99NuXjgyCCRzzW5+bF7Uuq3Ulvr6pr5+qa1v6uub+voWR99yJrvHkTt9eTJZYNb0hjPz1PJfqFZ/cwsb734CiFZ2x0x2CyWxG7NWdqWRqK9v6uuX2vqmvr6pr29Jr+w+BZxS5PlXAY9PbzgzT09fT03eJ4RA185nue/Jg0BuZTd/j9ux99oNIYxe2Y1xafeDr38pb1p2POBvslurtpIM9fVNff1SW9/U1zf19S2OvuVMdr8PfMjMFo99wsx+GXg/uet2pQy1ul9Y4eZPqSajOTV6ZXeoYMI7kMmSKdigKs5rdme3pkhf+IpxY/RA94LzTX19U1+/1NY39fVNfX1L+j67ncAQ8HPg8+Su2/2Ama0H/gfYC3yh6iN0Lu77hf3T7bu5+/EXODIwcj1sfmOq/Nf+oSzP9Q4MPz8wlK3Zyi5Q9HTqRqZ7wfmmvr6pr19q65v6+qa+viV6n90QwlPAa4G7gA+S27fod4DfBm4F3hhCeL7qI3Ru+aLlsb32nueP8Pc/3Ml7v34XRwaGhh9va8llb2ke2Y2553D/8PO5ld7C3ZhjG2JuPM252x5526AqzraSPPX1TX39Ulvf1Nc39fUtjr4l32cXIISwB7jIzF4EnE5uwrtbk9zKzWudF9tr/9cDTwPQN5ihb4KV3bb8NbtD2VE7LvcPZUdtUBXvfswjK7veTmOOs60kT319U1+/1NY39fVNfX2Lo285pzEPCyEcDCH8LISwRRPd6dn8xObYXvuRZw8P3xU0uAAAIABJREFUf7/7md7h7/Mru60FK7uFpxDnTmMuvGY3tiECMLc1t7Lb2z80xZGNJc62kjz19U19/VJb39TXN/X1LY6+JU92zew9ZvatIs9fZ2bvrs6wZo5Lz7w0ttc+XDB5fOrg0eHvh6/ZLbhWdjBTeL/b0acxx3nrIYDmVBNzWlP0HvU12Y2zrSRPfX1TX7/U1jf19U19fYujbzkrux8jdy/dyWSAj09vODPPpl2bYnvtwpXS53pHrsltja6RzV8r2zeYGXX7oYExpzHHvbILMK+tmUPOJrtxtpXkqa9v6uuX2vqmvr6pr29x9C1nsnsGuZ2YJ/Nz4BXTG87M05/pn/qgCvX2Dw3vpPzcoZHdltuiFd1F89sAePpg/6jrZQcymdG7Mcd8zS7A/FnN7k5jjrOtJE99fVNfv9TWN/X1TX19i6NvOZPdueRWbycTgPnTG87Mc9nyy2J77cP9Q8MT2sLdlvOnLy+c08LslhR79/eNWtntHxy9shv3rYcA5s1q4eDRwfjfqIbibCvJU1/f1NcvtfVNfX1TX9/i6FvOZPdR4A1Fnn8D8Pj0hjPzrNu+LrbX7u0fYtH8WQA8W3Af3QWzW4DctbhLFs5i7/6+URtU9WdG32e3qQaz3Rc5XNmNs60kT319U1+/1NY39fVNfX2Lo285k93vAL9lZh8a+4SZfRD4LeA/qzWwmWLF4hWxvXZv4cpuwTW7He1zhr9fsnD2uJXd3DW7Iz/XZGW3rdndBlVxtpXkqa9v6uuX2vqmvr6pr29x9C3nPrtXAhcBa83sj4Ht0eOvJHet7k7gb6s7PKnU/XsP8PTBft7y8txkt3CDqpPb5w5/v2TBbB586hADhacxD2VHbUpVi5VdjxtUiYiIiIhIckpe2Q0hHAJeD1wDLAYui/4sAb4GvC6EcDCOQXq2bd+2WF73nV+5A4Dj5uUmu0cHRyazbzrt+OHv58/KraiOvc9ura/ZnT+rxd1pzHG1lfqgvr6pr19q65v6+qa+vsXRt5yVXUIIB4CPmNlHgeOih58LIYQivyZFrD57dayvP6slxeyWFH2DGV5y7Bxu/+QqUgXLtrNaUhwdyoxZ2c1gpIZ/rsmth6JrdjPZMGp8jSzutpIs9fVNff1SW9/U1zf19S2OvuVcszss5Dwb/dFEdxpu2HFDrK//zMGjzG3LTVxPf/H8cRPJ2a0pQsjt3Jw3dmWXWtx6qC337y5HBvys7sbdVpKlvr6pr19q65v6+qa+vsXRd9KVXTN7CUAI4fHCn6eSP15K05Zqi/X1T100b3iCe/oJ4+8Mlb/n7sG+kUnmw8/28orFC4Z/rsVC66yW3DiODmaJNpBueHG3lWSpr2/q65fa+qa+vqmvb3H0Lbay2w08YmatBT8/WsIfKcMFyy6o+mv2D+Vuh/zuFUt57y+fzNMHc5tT/dKSF407dlZLbtX30NFBWlK5We31dz4+akMrq8FFu/lxHB0sdivnxhJHW6kf6uub+vqltr6pr2/q61scfYtNdv8K+BwwVPBzKX+kDOvvW1/118yv0p61dAFNBcuybzlj0bhjZ0eTzINHh4YnnAD7jwwOf5+twZnqHie7cbSV+qG+vqmvX2rrm/r6pr6+xdF30tOYQwjpYj9LdZy79Nyqv+bBo7mJ6oLZLQBs+P1zyYZAW3Nq3LH5SebBvkHampv48NtP5+9/uJOBzMikM5uNf7Kbn3T3OZrsxtFW6of6+qa+fqmtb+rrm/r6FkffkjaoMrN5Zvb/zOy3qj6CGa53oLeqr7fn+SNs3PYEAC+alZvsnvPSY3nty9onPD5/rezBo4O0pJpYesxsgFG3IsrUcGX3v3c+i5c9z6rdVuqL+vqmvn6prW/q65v6+hZH35ImuyGEXuASYPxFnzItO57ZUdXX+8A3t3B118MAvCha2S1m9vA1u0O0NjfRFF2f21842a3Fym5r7j/Fq360i3/72Z7Y368Wqt1W6ov6+qa+fqmtb+rrm/r6Fkffcm499Augo+ojmOHWrFhT1dcrXJFdOGfqyW5bwWnMLakmmqNrfPsHazvZLTzF+vYHn4n9/Wqh2m2lvqivb+rrl9r6pr6+qa9vcfQtZ7L7d8AfmNmyqo9iBlu7bW1VX+/MJSO3DHpp+9wpj8+fxnx4IENrqml4Q6uBTMGkeXbrhL9bTbNbRya7Dz3j4xSVareV+qK+vqmvX2rrm/r6pr6+xdF30g2qJvByYA+ww8w2AQ8BR8YcE0IIn6vW4GaC9tkTX0tbqWPm5iamX77k7FE7MU9mdsEOzC3NTaSi05gHhrKYwff/8I28pH1OVcc4kcKdoA8dHSpy5PT0D2X42A0/54pfPZ1TF42/73A1Vbut1Bf19U19/VJb39TXN/X1LY6+5Ux20wXf/8YkxwRytyuSEq3qWFXV18tksyxeMIuLzj6xpOMLJ5ltqSZSTSOT3VnNKc5YXJvLtAsn3c0lTNIrdfdj+/nRL57mQN8gG34/3h39qt1W6ov6+qa+fqmtb+rrm/r6Fkffck5jfmkJf15W7QF6t/GBjVV9vaFsGJ6wlmLWqJVdG14N7s9kY510jh/HyH+KhadQV1t+p+dafLRqt5X6or6+qa9fauub+vqmvr7F0bfkld0QwmNVf3cp+V8wrr/zMXr7h/jwr5xS9LhMNpQ1SS1cUZ3VnBp1GnMqVcPJbsEGVf0x3ms3v9VWftfpOOlfH31TX9/U1y+19U19fVNf3xJZ2TWzS8xsh5n1mdkeM/trMytnRViK2Htob0nH/cV37+PKWx6c8rhyV3bbmkdSzmpN0RT9ODCUqenKbuH1xYW3Paq2bLSyW4O5bsltpTGpr2/q65fa+qa+vqmvb3H0Lbqya2bvBG6IfuwBFgOfBlqB/1P10cxAu3p2lXX8UCZLc2ryf2vIZMqb7DY1GW3NTfQPZZnTMrKye2QgM+p2QLU0lA1Tfs5KRXNdjPhnu+W2lcaivr6pr19q65v6+qa+vsXRd6rZxCfITXJXhhCOB14MbCZ3C6K2qo9mBprqflI/uO8pjgyM7E6878DRosfnVnbLmyTOa8v9m8ec1tTwRLm3f2jUdbS1Ftd1u/nTmGuxsqt7wfmmvr6pr19q65v6+qa+viVxn90VwDUhhLsBQgjPAX8GzAHOqPpoZqBi95O6f+8BPnz9NtI33T/82OPPj73b02jZUN41uwBzo8nu7Nbm4cnu4f6hUfe+rYVj547cz/foYDyT3ZHTmOOf7epecL6pr2/q65fa+qa+vqmvb3H0nWqyuxAYu568E7DoOZmmxfMWT/rcw88eBuCBfYeGH3tyf1/R1yv3ml0Y2Ql5dsvIym42jN40qhbu/szb+PxvLgdy98ONxfBpzPEr1lYan/r6pr5+qa1v6uub+voWR9+pJrsGDI15LP+zNqmqgpVLVk763M6nDgKw48kDw48d7Bss+nqZbPm3DMrvTDynNTVql+Jar+zCyIZZ/TGt7AZqd+uhYm2l8amvb+rrl9r6pr6+qa9vcfQtZcLaYWavzv8BzooeP63w8YLnpQw377p53GM/636ezpvvZ+dTveOe6+0f+28Pow2VuUEVjEx2ZxdcswskskFV/j3j2pE5G71sLU5jnqit+KG+vqmvX2rrm/r6pr6+xdG3lPvsfi76M9bVkxyfzBa+Der8U84f99jl3/wZvf1DLJzTwsqTj2HrYy8MP3foaPHJbiYbaCtzY6n8flaFpzFDwiu7MZ3GPLxBVSyvPtpEbcUP9fVNff1SW9/U1zf19S2OvlNNdjur/o4yyq6eXbzupNeNemxWS4re/iH2HxlkZcex9A1muH9v7pTm3ikmu0PZwJwyd2PO34Zn3GnMCezGnJ+oP7DvIGctrf5l4bXcoGqituKH+vqmvn6prW/q65v6+hZH36KT3RCCJrsx697fPe6x4+a18lxvPwAd7XN4rGfO8GT3UP9U1+wGUmXO4/KLuWNPY57VUvuV3fx7XrFxBxedfWLVxxBC7a7Znait+KG+vqmvX2rrm/r6pr6+xdG3lNOYJUYT3U+quWC2enL7XDovWsTCOa1s37OfR587wtHBzLhJ4Potj3PW0gUV3We3KZr5zW5JkRq1spvcacyQ26Sq+pPd3FfdZ1emS319U1+/1NY39fVNfX1L4j67ErOJ7if1wuFBTjl+Lh9786msOPkYFs2fxed/cznHzWvlgX0H+b1vbR33O5/+zx288yt3VLQbc/7oVJNROE9uS2SyO/Ke/ZnqX7ebv2a3SffZlWlSX9/U1y+19U19fVNf35K4z25szGyWmW0xs3vM7H4z64wef6mZ3WVmu83s382sNXq8Lfp5d/R8R1Jjr5YHnzrI0vkd4x5//vAAbz59EZ98++m0Fqx05ndi/t+Hnht1fP7UXIhOYy7zPOb8xC8AzQWz3aRXdgdi2JF55Jrdqr/0OB0LO+J/E0mM+vqmvn6prW/q65v6+hZH3yRXdvuBt4QQXgmcDfyqmb0W+ALwxRDCqcALwIei4z8EvBA9/sXouIa1+5lD/NqX/5d7Hl5KNjsyWe0byNA3mOHYea3jfmfv/r7h7/c8f4Qf3PcUMPo2PZlsKHtl932vPRmAjva5o1Z2k9ygCuKZ7A6fxlyD/ZiXtS+L/T0kOerrm/r6pba+qa9v6utbHH0Tm+yGnPyNZFuiPwF4C/Dt6PHrgHdF318U/Uz0/HlWiy11Y3Lqovmcd8YJ3Hx3P3/z/QcAePS5w5zV+UMATpg/a9zvFE5qP7b+53z4+m08c+go/YMjj+eu2S3vr+VdrzqR7ivfyfHz20Zds5vEBlWFK8sDmcZe2b314VvjfxNJjPr6pr5+qa1v6uub+voWR99Er9k1s5SZbQeeAX4EPAzsDyHk76/zBHBi9P2JwB6A6PkDQHttR1xdX3rP2Rw3v4kf3v8UIQS2PNrDYCY3GXvrGSeMO/66y89hTnTv24N9uV2Zf/zAM/QNjlzbWsnKbqGk77N7/Pw23njacQCjJvHVMpSp3a2HLlx2YezvIclRX9/U1y+19U19fVNf3+Lom0qn01V/0VKl0+mQTqf/ubOz82rgT4EdwLvS6fRXADo7OxcA70un01d3dnZ+BLg+nU4fjJ77BPCNdDp9pPA1zWxNZ2fnNZ2dnWuyll3Su6KX9tntbLh/A7fsvoVl7cu4avNV9BzpYc+BPVx/7/UsnreY67ZfR1d3FyctOIkv3fklDvUfYlfPLtbft56OhR1c/bOr2fLkFtpnt/PVLV+lf6ife566hw33bxh+zR1P72BOyxy+tvVrAPx0z0/Z+MDG4ed3PrcTw1i7bS2tqVb+9/Hb2f70z3jymRN5fGAjj/X0snNvG/8/e3ceH2V1L378c2bNvpCQkLDvIKCsbnXBfW2t2lprq7W11Xttrd3tfkPbX2sXW2vVVu/VqnWvuNd9wQWQfQkgBJAAIYGQQPZkMsv5/TGTkLCEBGbyhG++79crL5OZyeQMHxM4Oc9znuNHl3P8MBcvbXiJl0tebv/8iGsPI3LSWbolTKrfUt8SYVv9GqYPz+GZpVWx1x+iMbKJE0elHNFrWlmxhnfWRDfpDng/YHvjkh69pre3vM3z659vv7+0ppSmYBMPrHiAdF/6Aa+pvL6c6uZqHlr5UHunPYFSNpfnUut6g4CtiGunuz58ju2V2QzKCrOq9uGEvqbffvBbpuRN6ZP/78WjU39/TfO3zSdiI6Jek8ROR/qallcs572t74l6TRI7Hclr2l67nbc+eUvUa5LY6Uhf0+0f3s6a3WtEvSaJnY70Nf1p4Z84deipol6TxE5H+pqWli+lurm6x6/phfteqCgqKjro7lam4+ZGXTHGXHeYh1igGdgGLO+wOtvd5/9l7PNvAwZZa0PGmFOAImvtBcaY12PvLzTGeICdwEDbxQuYOXOmXbr0wJ2L+5JbX/o9L8yfzF+vnkp1Qyu/enkdK395HlkpB56zC7BgcxXX/O+i9o/PnpDHDy8Yz0V//aD9tmtPHs6vPzv5iMbTGAgx6X+ih1L/8/pZnDUh74ie52gs+qSaL9z/EY99/SQ+NSY3rs/95OJt/PjZYj47tZA7r54W1+feX9G8IopmFyX0ayjnaF/ZtK9c2lY27Sub9pXtSPsaY5ZZa2ce7L6eXGf3IfZduQX2XbFm/9ssUG2M+Zm19n+7GNRAIGitrTHGJAPnEd106l3gc8CTwFeAF2Kf8mLs44Wx+9/paqJ7rPj+6V/m1UWrWVteR0ZSNEeK79BZctP8nT7eVdfS6TBmoMfn7B7qczvuBN2b2i55lIgNqkKR3juMWa8FJ5v2lU37yqVtZdO+smlf2Zy+zu55wHKgFPgx0Y2jPgv8JHbbUuAK4EdAA/APY8yVXTxfAfCuMWY1sAR401r7MtGV3e8ZYzYRPSf3gdjjHwByYrd/LzaGY96DK/+X8fnp/Hvpdj7Z3YjXbbqcZOakdl7x3VUXoCWOk92O1591arLrc0e/biDU/evsvl+ym092N3T5mGVb9/Lz59cAvbNBlV4LTjbtK5v2lUvbyqZ9ZdO+siWib09Wdj8F+IEp1tqO58m+aIy5l+iK62Rr7W+MMfcBq4hOSuce7MmstauBA44jtdZ+Apx4kNtbgM/3YLzHhHE54zju5OH8aO5qXlxVTqq/6yRZKT5cBtquVlTVEKC0qtNpy0e1QVXHz22bdPa2tkl2oAcru9c9uBiA0tsvOeRjHl5Q2v6+qxdmu7o9vmzaVzbtK5e2lU37yqZ9ZXP60kM3AA/vN9EFIHYJoYeAr3f4+BFgShzGKFpheiEXThkERA+xTT3MDshulyEj2QtEdy4G+OlzxQc85ki5+sJhzLGv253DmEPhCLc+uaJbzxvucD3j3rhmVWF6YS98FeUU7Sub9pVL28qmfWXTvrIlom9PZjN5QFczMQ/Q8Xo55fRs5bhfmlc6jyTPvj/WlMOs7MK+VckLJw066P1Hs7LbkWOHMbdNdrtxnd0tVY28sLK8W8/babLbC7PdeaXzEv9FlGO0r2zaVy5tK5v2lU37ypaIvj2ZzZQANxhjMva/wxiTSXTld0OHm0cSvX6u6sKVE6/E6za0zU8PdxgzwKTCaILZ4wfytU+NPOB+tys+k1SnDmPuycpuTzaaCnfYz6w3DmO+cmJXp6yrY532lU37yqVtZdO+smlf2RLRtyezmV8BY4ANxpjfGmOuj739DlgPjAZ+DWCMcQFXA/PjPWBp5pXOwxhDcmwH4sMdxgxw5xem8sZ3z+Ccifnkph94iSKPOz4TOb/DK7vdOWd3/825uhLRlV0VR9pXNu0rl7aVTfvKpn1lS0Tfbh9mbK2da4y5BvgzB+6EXAF82VrbthmVG7gI2B2XUQpW3VwNQJLXTWNruMvLDrXJSfOTE7sEUW6q/4D7j+ac3Y6c3o25Oyu7HSe7h/tFQdge7MpZidPWVsmkfWXTvnJpW9m0r2zaV7ZE9O3RObXW2qeMMc8AM4gepgyxyw5Za8MdHhek8yHN6hDarieV1Lay6z/8ym5HB1vZdcdp2dKpya7H7cJlujfZ7XiN4cMdAt7xnN3eoNeCk037yqZ95dK2smlf2bSvbE5fZxcAa23YWrvYWvtU7G1Rx4mu6pm260n5vdEU3VnZ7Sg3LYEruw6dswvg97i7tUFVc+uRTXatTfzEV68FJ5v2lU37yqVtZdO+smlf2RLR94hmM8aYFGPMUGPMsP3f4j1A6abkRa/O1HbObkZyzya7owamMakwg3uumd5+W7zO2fU4ONn1eVzdO4y5w2MOtyrecbIb6YXJbltbJZP2lU37yqVtZdO+smlf2RLRt9szq9imUz8CbgEOfs2bqJ4dh9vPpfnSgH0bJmUkeXv2+X4P//n26YQ6rILGa2XXST6Pi0Co6wMGguEIj320tf3jw+1C3Xmye3Tj6462tkom7Sub9pVL28qmfWXTvrIlom9Plu5uB34L7AHuIbo788HeVA8sLFsI7Ds/NTO5Z5PdNh1XYeN1nV0n+T2uTocoH8x9721m0ZY9AEwbltVpwn8wHTeo6o2V3ba2SibtK5v2lUvbyqZ9ZdO+siWib0+Omf0y8Jq19uK4j6If++LkLwL7LrOTcYST3Y7idZ1dJw3OSmbbnqYuH7Ojprn9/fQkL7tqW7p8fMdLD9ELK7ttbZVM2lc27SuXtpVN+8qmfWVLRN+ezIqygRfiPoJ+7uWSl4GjX9ntSMLK7tj8NDZVNnS5kVTHw5LT/R6Cka5Xdjtet7c3Vnbb2iqZtK9s2lcubSub9pVN+8qWiL49mewWAwVxH0E/FwgHgH2T3Yyknm1QdTADUg+8HNGxZmxeOnUtIR6cX3rAfUUvruUbjywl1GGy63UbQuGuJ7CdJ7txG+qhv16srZJJ+8qmfeXStrJpX9m0r2yJ6NuTye4c4L+MMUPjPop+7Jop1wAdJrtxWNnNyzjwckTHmhnDswH4/avrD7jvoQWlvLluF3XNwfbbPG7XYc/Z7XgOcG+s7La1VTJpX9m0r1zaVjbtK5v2lS0RfXsy2Z0BbAXWGWMeMcbMMcb8cr+3X8R9hMI9tPIhAALh+B3GnJeedNTP4bTJgzO5auYQkn2H3ty7sn7fb3+8bkPwMMu1LR12d+6FuW57WyWT9pVN+8qlbWXTvrJpX9kS0bcnx8wWdXj/y4d4jAV+fcSj6YdmFMwAouecVodaSY/DYczZKUc/Ye4LBmUmU9cSJByxBMMRLr93AQWZ+ybyW6oa29/3uA6/stvay+fstrVVMmlf2bSvXNpWNu0rm/aVLRF9ezKzGhn3r67aPf1fpzB/UxV+z9FfptiYY3+DKoCsZC/WQl1zkOrGVj6uqOPjirr2++tbQu3ve3p8zm4vLO0qpZRSSimlHNPtw5ittVu785bIwUq0rGIZAKMHpnHdKSOcHUwfkxVboa5pDrKrLnpZof13mv7mWaNZ+JOz8bpdXe7GHI7YTrs398YGVW1tlUzaVzbtK5e2lU37yqZ9ZUtE36M/ZlYdleunXh+353rtO6fH5VzUt753Jj6389fqzU6J7ipd09TaPtl99uZTeeDDLbywshyACYMyKMhMxuPqemW34yHMQJeXNIqXeLZVfY/2lU37yqVtZdO+smlf2RLR95AzmrYNp4wxrg4fH+5NN6jqoceLH4/bc00YlMHEgoyjfp4xeWkMy0mJw4iOTmbbym5TkJ2xye6YvDR+fslx7Y8ZmB7dedrjdhGK2ENOYgMdNqeC3lnZjWdb1fdoX9m0r1zaVjbtK5v2lS0Rfbta2S0iuuHU74FWOm9QdSi6QVUP+d3H/mWCEiUrtjP17voAf3mzBIAUn4dk777zmtsmu97Y4c2hiMXrjr5vrW0/f9mJlV1tK5v2lU37yqVtZdO+smlf2RLRt6vJ7kgAa21rx49VfF067lKnh9BnZcUOY352RRnBsCUjtlN1xw24Oq7sAoTCFq87OkGe9f/e4vYrpnD59MFc+8DiTs/dGyu72lY27Sub9pVL28qmfWXTvrIlou8hD2Pef8Mp3aAqMZ5Y84TTQ+izUv3RFdzVZbVAdMfqNv/59ml8++wxpPujE+C21dy2Tao27qoH4PmVO1i1vZYNsY8/N2MI0Du7MWtb2bSvbNpXLm0rm/aVTfvKloi+ukGVw04ZcsrhH9RP+T1uvG5DU2uY/Aw/EwbtOx95UmEmkwoz2z9u26W5bZOqptboObopPk+nQ5bPnZjPlqrGuGzkdTjaVjbtK5v2lUvbyqZ9ZdO+siWib48mu8aYVOAaYCyQA+x/QVdrrb0hTmPrFxpaG5weQp+W4vNQ2xxkZG5ql4/bdxhzdGW3KRid7Cb73J0OWfZ7XLhM76zsalvZtK9s2lcubSub9pVN+8qWiL7dvr6MMeZEYAtwH/AD4KvA9Qd5Uz1QXFns9BD6tLTYYcpDs7veHXrfYcyxld1ACIAUr5um1lD743weF8aYXpnsalvZtK9s2lcubSub9pVN+8qWiL49uZjqnwEfcBWQa611HeTNfZjnUPu5ccaNTg+hT0vxRf+Xyk71dfk4j6vzym5j+2HM7vb3oePKbiJG25m2lU37yqZ95dK2smlf2bSvbIno25PJ7gzgDmvtM9baPXEfST91/7L7nR5Cn+aOnYubGbsM0aF42lZ2Y+fs1jYHAUjyumkMdF7ZdRnTK5ce0rayaV/ZtK9c2lY27Sub9pUtEX17MtmtA6rjPoJ+Lic5x+kh9Gmh2BJsVkrXk11v2zm7sd2Y62KT3XDEHnSy2xsru9pWNu0rm/aVS9vKpn1l076yJaJvTya7zwIXxH0E/dzsEbOdHkKf1nZYclby4Q5jjq7sLtu6l23VTTy0oBSAYDhCQ4fJrt/jxvTSBlXaVjbtK5v2lUvbyqZ9ZdO+siWib08mu7cBecaYvxljRhtj9t+JWR2BuR/PdXoIfVrbYcmHW9k9aVQOaX4Pj320jUVb9h2AEIzY9ssQQccNqhIz3o60rWzaVzbtK5e2lU37yqZ9ZUtE355MdmuAE4GbgRIgZIwJ7/cW6vop1P70N1RdC8ZWdg93zm5mspeLpwyiujHAnsbWfZ8f6ryy63NHN6jqjQvtalvZtK9s2lcubSub9pVN+8qWiL49uc7uI0AvrIf1L+X15U4PoU9rm+webmUXIDvFx96mIJX1AZK9bgam+wmGI7TGngPA7+29c3a1rWzaVzbtK5e2lU37yqZ9ZUtE325Pdq2118f9qytKqkucHkKfNjDdz96mIBmHWdkFyErx0RqKsG1PEwPT/fg8LoJhSyC0b7LbtrLbG+fsalvZtK9s2lcubSub9pVN+8qWiL49WdlVCaDXC+vaP796IvM3VpGR1J2V3ehjNu6qZ2C6n8ZAiNZwhJqmfYc1+9y9d86utpVN+8qmfeXStrJpX9m0r2xOX2cXY4zbGHOdMeZRY8ybxphpsduzY7cPjvsIhdPrhXVtcFYyV80a2q3HZqUEQmsFAAAgAElEQVREd2wurW5iYFrbym6E6tg5vFOHZuFyGVwGvc6uOmraVzbtK5e2lU37yqZ9ZUtE326v7BpjUoA3gFOBRiAFyI7dXQfcDjwI/DzOYxStIK3A6SGIkd3hvN6CrCR2NwQIhS1V9QGuP3UERZ+ZBBA7Zzfxk11tK5v2lU37yqVtZdO+smlf2RLRtycru0XATOByYBTQfukha20YvQ7vEZlZONPpIYiRnbrvWrwnjhiA122oD4SoD4TITdt3X29tUKVtZdO+smlfubStbNpXNu0rWyL69mSy+3ngfmvtC0DkIPdvAkbEY1D9yUslLzk9BDEKMpPa3z9x5AC8bherttcAkJPmb7/P9NIGVdpWNu0rm/aVS9vKpn1l076yJaJvTzaoKgRWdXF/E5B+dMPpf84ffb7TQxAjPcnLO98/kx01zeSk+fG59/0uJ7fDZNdlTG9cZlfbCqd9ZdO+cmlb2bSvbNpXtkT07cnKbjXQ1QZUkwC9+FUP6Rbq8TVqYBqnjx0IdF69TfW529/vrZVdbSub9pVN+8qlbWXTvrJpX9kS0bcnk923ga/GNqrqxBgzEvga8Fq8BtZflNaUOj0EsZpawwCMzUvj5FE57bf31gZV2lY27Sub9pVL28qmfWXTvrIlom9PJrtziO6+vAT4b8ACFxpjfgcsBwLA7+I+QuH0emGJ0xyMTna/dfYYXK72/dQwhl45jFnbyqZ9ZdO+cmlb2bSvbNpXNkevs2ut3QScA4SAXxHdjfkHwG3AduAca+32uI9QOL1eWOK0rexmJns73d5b5+xqW9m0r2zaVy5tK5v2lU37yubodXYBrLXLgBOMMZOBiUQnvButtSviPrJ+YkTWCKeHIFbzISe7vXPOrraVTfvKpn3l0rayaV/ZtK9siejbo8luG2vtGmBNnMfSL43LGef0EMRqag0BB1/Z7Y3JrraVTfvKpn3l0rayaV/ZtK9siejbk3N2ATDGFBpjbjLG/D72dpMxpqtdmlUX3tj8htNDEOtQhzEbY4j0wmHM2lY27Sub9pVL28qmfWXTvrIlom+PVnaNMb8Afg5497vrb8aY/2etnRO3kfUTnx73aaeHIFZmspfK+gDpSQcexmx7YWVX28qmfWXTvnJpW9m0r2zaV7ZE9O32yq4x5ltEd2ReCVwDTI29fSl22y9jj1E9sLR8qdNDEOvpm07hD587Hp+n8//mrl5a2dW2smlf2bSvXNpWNu0rm/aVLRF9e7KyewuwGDjNWhvqcPtqY8wzwPzYY+6O4/jEq2iocHoIYo3ITWVEbuoBt/fWBlXaVjbtK5v2lUvbyqZ9ZdO+siWib0/O2R0GPLHfRBcAa20QeCz2mG4xxgw1xrxrjFlnjFlrjLk1dvsAY8ybxpiNsf9mx243xpi7jDGbjDGrjTHTezD2PkuvF9b7jDFEemFpV9vKpn1l075yaVvZtK9s2lc2R6+zC2wD0ru4Pz32mO4KAd+31h4HnAx80xhzHPBj4G1r7Vjg7djHABcBY2NvNwJ/78HX6rP0emG9zxj0OrvqqGlf2bSvXNpWNu0rm/aVLRF9ezLZvRu4yRhTsP8dsd2Y/wv4W3efzFpbYa1dHnu/HvgYGAxcBjwce9jDwGdj718GPGKjPgKyDjaWY41uod77XMbQC3NdbSuc9pVN+8qlbWXTvrJpX9kS0bcn5+zWAruA9caYR4H1sdsnEt2kqgSoM8Zc1/GTrLWPHO6JjTEjgGnAIiDfWtt2wPZOID/2/mBge4dPK4vddkwfvF+YXuj0EPqd3jpnV9vKpn1l075yaVvZtK9s2le2RPR1FxUVdeuBc+bMWQEUAH5gFtHDii8CZsZuKyS6Ctvx7bKioqJfdfW8xpg04FXgZ9balXPmzPlxUVHR7QBFRUXMmTPntqKiot/PmTPnGuDDoqKibbHxfAV4q6ioqHy/57txzpw5982ZM+fGiIkUNsxoICc5h6fXPs2rm15lXM447lh4B9VN1Wyv3c6jqx+lIK2Ah1c+zLzSeQzNHMqdH91JfaCekuoSnljzBCOyRnDvkntZvGMxOck53L34bgKhAKt2ruLptU+3P2fxrmJSvCn8fWn0COsF2xcw9+O57fdvqNqAwXD/svvxuX28veVt7vzoTs4ffT53LLyD0ppSmoJNPLDiAdJ96by04SVeLnm5/fPL68upbq7moZUP9enX9Pz659vv74uvafX2Vir2JlHteiyhr6loXhEzCmZoJ6Gv6fVNr+N3+0W9JomdjvQ1zSud174rpJTXJLHTkbym4l3FLCxbKOo1Sex0pK+p6L0iNu3ZJOo1Sex0pK/pdx/+jtkjZot6TRI7Helrmlc6j6ZgU49f0wv3vVBRVFR00GOgTXevN2qMObNbD9yPtfa9Lp7TC7wMvG6t/XPstg3AbGttReww5XnW2vHGmPti7z+x/+MO9fwzZ860S5f27S3Ki3cVMyV/itPD6Fduf3U9D87fQslvLkro19G2smlf2bSvXNpWNu0rm/aV7Uj7GmOWWWtnHuy+bp+za61970jeuhiUAR4APm6b6Ma8CHwl9v5XgBc63H5dbFfmk4Haria6x4p5pfOcHkK/43EZQuFIwr+OtpVN+8qmfeXStrJpX9m0r2yJ6NuTc3YBMMakAJlEJ5tNR/G1PwVcCxQbY1bGbvspcDvwtDHmBmArcFXsvleAi4FNQBPw1aP42n1GdXO100Pod/weFxELoXAEj7sne7T1jLaVTfvKpn3l0rayaV/ZtK9siejbrcOYjTEDgR8CVwIjOtxVCswF/mStrYz76I7SsXAYc3l9uZ5s38vuf38zv31lPWvnXECqv8e/7+k2bSub9pVN+8qlbWXTvrJpX9mOtO9RHcYcO2S4GPgBMARYAyyI/XdI7PZVxpiTejwypdcLc4Df4wYgEErsoczaVjbtK5v2lUvbyqZ9ZdO+svX6dXaNMXnAS0R3W/4mkGWtPcFae7q19gQgC7g5dv9LscerHpiSpyfZ9za/J/q/fSAUTujX0bayaV/ZtK9c2lY27Sub9pUtEX0Pt7L7AyADOMda+3drbXPHO621zdbafwDnxh73/biPULg0X5rTQ+h3/N7YZDeY2JVdbSub9pVN+8qlbWXTvrJpX9kS0fdwk91LgH9Za5d39aDY/Y8Cn47XwPqLhWULnR5Cv+Nz985hzNpWNu0rm/aVS9vKpn1l076yJaLv4Sa7I4CPuvlci4DhRzWafuiLk7/o9BD6nd46jFnbyqZ9ZdO+cmlb2bSvbNpXtkT0PdxkNwx4u/lcntjjVQ+8XPKy00Pod9oPY07wyq62lU37yqZ95dK2smlf2bSvbInoe7jJ7kbgrG4+12yi18BVPRAIB5weQr/Tvhtzgs/Z1bayaV/ZtK9c2lY27Sub9pUtEX0PN9l9HrjCGHNhVw8yxlwAXAE8G6+B9RfXTLnG6SH0O711GLO2lU37yqZ95dK2smlf2bSvbInoe7jJ7p3AduB5Y8zvjDGjOt5pjBlljPkt8AJQBvw17iMU7qGVDzk9hH6ntw5j1rayaV/ZtK9c2lY27Sub9pUtEX09Xd1pra2Prdq+BNwG/MgYUw/UEr3UUAZgiB6+/BlrbX3cRyjcjIIZTg+h32k/jDnBK7vaVjbtK5v2lUvbyqZ9ZdO+siWi7+FWdrHWlgBTgVuBD4EQUEB0M6oPgO8AU6216+M+OqUSoP0w5gSfs6uUUkoppZRyzmEnuwDW2mZr7d+stWdaa3Ottb7Yf2dba++y1jYleqBSLatY5vQQ+p195+wmdrKrbWXTvrJpX7m0rWzaVzbtK1si+nZrsqsS5/qp1zs9hH7H7+2dw5i1rWzaVzbtK5e2lU37yqZ9ZUtEX53sOuzx4sedHkK/01uHMWtb2bSvbNpXLm0rm/aVTfvKloi+Otl1mN/td3oI/Y7HZXCZxB/GrG1l076yaV+5tK1s2lc27StbIvrqZNdhl4671Okh9DvGGPwed8IPY9a2smlf2bSvXNpWNu0rm/aVLRF9dbLrsCfWPOH0EPolv9eV8JVdbSub9pVN+8qlbWXTvrJpX9kS0Vcnuw47ZcgpTg+hX/J7XAk/Z1fbyqZ9ZdO+cmlb2bSvbNpXtkT01cmuwxpaG5weQr/UG4cxa1vZtK9s2lcubSub9pVN+8qWiL462XVYcWWx00Pol/weF63hxK7salvZtK9s2lcubSub9pVN+8qWiL7GWhv3J+0rZs6caZcuXer0MLpUXl9OYXqh08Pody792wfkpyfxwPWzEvY1tK1s2lc27SuXtpVN+8qmfWU70r7GmGXW2pkHu09Xdh12/7L7nR5CvxQ9jDmxK7vaVjbtK5v2lUvbyqZ9ZdO+siWir052HZaTnOP0EPolv8eV8HN2ta1s2lc27SuXtpVN+8qmfWVLRF+d7Dps9ojZTg+hX4pOdhO7sqttZdO+smlfubStbNpXNu0rWyL66mTXYXM/nuv0EPolv8ed8EsPaVvZtK9s2lcubSub9pVN+8qWiL462XWY/obKGX5v4g9j1rayaV/ZtK9c2lY27Sub9pVNV3YFKq8vd3oI/VJvHMasbWXTvrJpX7m0rWzaVzbtK1si+upk12El1SVOD6Ff6o3dmLWtbNpXNu0rl7aVTfvKpn1lS0Rfnew67MYZNzo9hH7J73ERCCb2MGZtK5v2lU37yqVtZdO+smlf2RLRVye7DtPrhTkjes6uXmdXHTntK5v2lUvbyqZ9ZdO+sul1dgUqSCtwegj9kt/jJhSxhMKJm/BqW9m0r2zaVy5tK5v2lU37ypaIvjrZddjMwplOD6Ff8nui/+v/66OtXPn3Bbywckfcv4a2lU37yqZ95dK2smlf2bSvbInoq5Ndh71U8pLTQ+iX2ia7c15ax7Kte7n1yZVx/xraVjbtK5v2lUvbyqZ9ZdO+siWir052HXb+6POdHkK/5Pe6O308Lj8t7l9D28qmfWXTvnJpW9m0r2zaV7ZE9NXJrsN0C3VntK3stkn2eeL+NbStbNpXNu0rl7aVTfvKpn1l00sPCVRaU+r0EPqllNjkdkCqj89OLeSTygaqGwJx/RraVjbtK5v2lUvbyqZ9ZdO+siWir7HWxv1J+4qZM2fapUuXOj2MLpXXl1OYXuj0MPqd5tYwTy3ZxqTBmbxavJMH528BoPT2S+L2NbStbNpXNu0rl7aVTfvKpn1lO9K+xphl1tqD7m6lK7sO0+uFOSPZ5+b6T41k1ogBZCZ7E/I1tK1s2lc27SuXtpVN+8qmfWXT6+wKNCJrhNND6Pcq61sS8rzaVjbtK5v2lUvbyqZ9ZdO+siWir052HTYuZ5zTQ+j3rpwxJCHPq21l076yaV+5tK1s2lc27StbIvrqZNdhb2x+w+kh9HvTh2Vz4xmjSPLG99tB28qmfWXTvnJpW9m0r2zaV7ZE9NXJrsM+Pe7TTg9BASk+Ny3BCOFI/DZs07ayaV/ZtK9c2lY27Sub9pUtEX11suuwpeV9e7fo/iLNH70UUWNrKG7PqW1l076yaV+5tK1s2lc27StbIvrqZNdhFQ0VTg9Bse+6u02BcNyeU9vKpn1l075yaVvZtK9s2le2RPTVya7Dbpxxo9NDUECq3w3Ed2VX28qmfWXTvnJpW9m0r2zaV7ZE9NXJrsP0emF9Q2psZbcxEL/JrraVTfvKpn3l0rayaV/ZtK9sep1dgXQL9b4hte2c3TgexqxtZdO+smlfubStbNpXNu0rm156SKDC9EKnh6DYdxhzUxwPY9a2smlf2bSvXNpWNu0rm/aVLRF9dbLrsHml85wegmLfBlUNcTyMWdvKpn1l075yaVvZtK9s2le2RPTVya7Drpx4pdNDUESvswvQEozfYczaVjbtK5v2lUvbyqZ9ZdO+siWir2OTXWPMg8aYSmPMmg63DTDGvGmM2Rj7b3bsdmOMucsYs8kYs9oYM92pcceb/oaqb0jyRie7za3xm+xqW9m0r2zaVy5tK5v2lU37yiZtZfch4ML9bvsx8La1dizwduxjgIuAsbG3G4G/99IYE666udrpISggOTbZbQlF4vac2lY27Sub9pVL28qmfWXTvrIloq9jk11r7fvAnv1uvgx4OPb+w8BnO9z+iI36CMgyxhT0zkgTS68X1jf4PdFvhXgexqxtZdO+smlfubStbNpXNu0rWyL6uouKiuL+pN01Z86cLOCaoqKie2Mf/8Za+/PY+43Ar4uKim6fM2fOfwGvFBUVbYvddzmwqKioqHz/5zTG3Dhnzpz75syZc2PERAobZjSQk5zD02uf5tVNrzIuZxx3LLyD6qZqttdu59HVj1KQVsDDKx9mXuk8hmYO5c6P7qQ+UE9JdQlPrHmCEVkjuHfJvSzesZic5BzuXnw3gVCAVTtX8fTap9ufs3hXMSneFP6+NLrwvGD7AuZ+PLf9/g1VGzAY7l92Pz63j7e3vM0v3v0F548+nzsW3kFpTSlNwSYeWPEA6b50XtrwEi+XvNz++eX15VQ3V/PQyof69Gt6fv3z7fcfK6/p2fXPsm7LEGoja6hnSVxe0y2v3sKMghnaSehrerz4cfxuv6jXJLHTkb6muevmsrR8qajXJLHTkbymeaXzWFi2UNRrktjpSF/TLa/ewqY9m0S9JomdjvQ1/eCNHzB7xGxRr0lipyN9TXM/nktTsKnHr+mF+16oKCoqOuhFeo21trtz07gzxowAXrbWTo59XGOtzepw/15rbbYx5mXgdmvth7Hb3wZus9Yu7er5Z86caZcu7fIhjpu7bi5XHqcn2/cFJ8x5g8unDaboM5Pi8nzaVjbtK5v2lUvbyqZ9ZdO+sh1pX2PMMmvtzIPd19d2Y97Vdnhy7L+Vsdt3AEM7PG5I7LZjXpovzekhqJgkryuuhzFrW9m0r2zaVy5tK5v2lU37ypaIvn1tsvsi8JXY+18BXuhw+3WxXZlPBmqttRVODDDeFpYtdHoIKibJ66Y5jpNdbSub9pVN+8qlbWXTvrJpX9kS0dcT92fsJmPME8BsINcYUwb8D3A78LQx5gZgK3BV7OGvABcDm4Am4Ku9PuAE+eLkLzo9BBWT7HXHdWVX28qmfWXTvnJpW9m0r2zaV7ZE9HVyN+YvWmsLrLVea+0Qa+0D1tpqa+051tqx1tpzrbV7Yo+11tpvWmtHW2unHO5c3WPJyyUvOz0EFeP3umkOxu/SQ9pWNu0rm/aVS9vKpn1l076yJaJvXzuMud8JhANOD0HFJHnie86utpVN+8qmfeXStrJpX9m0r2yJ6KuTXYddM+Uap4egYpJ9bgJxnOxqW9m0r2zaVy5tK5v2lU37ypaIvjrZddhDKx9yeggqJskT3w2qtK1s2lc27SuXtpVN+8qmfWVLRF+d7DpsRsEMp4egYpJ9blrieM6utpVN+8qmfeXStrJpX9m0r2yJ6KuTXaVi4n2dXaWUUkoppZRzdLLrsGUVy5wegorxx/kwZm0rm/aVTfvKpW1l076yaV/ZEtFXJ7sOu37q9U4PQcWkJ3loDISIRGxcnk/byqZ9ZdO+cmlb2bSvbNpXtkT01cmuwx4vftzpIaiYnFQfEQt7m1rj8nzaVjbtK5v2lUvbyqZ9ZdO+siWir052HeZ3+50egorJTY+2qGqIz2RX28qmfWXTvnJpW9m0r2zaV7ZE9NXJrsMuHXep00NQMQPTot9gf3mzJC6HMmtb2bSvbNpXLm0rm/aVTfvKloi+Otl12BNrnnB6CCqmbWX3tbU7+XBT1VE/n7aVTfvKpn3l0rayaV/ZtK9sieirk12HnTLkFKeHoGJy0/YdOrF5d8NRP5+2lU37yqZ95dK2smlf2bSvbInoq5NdhzW0Hv2kSsVHRpKn/f3istqjfj5tK5v2lU37yqVtZdO+smlf2RLRVye7DiuuLHZ6CCrGGMNfr55KfoY/Liu72lY27Sub9pVL28qmfWXTvrIloq+xNj7XFO2LZs6caZcuXer0MLpUXl9OYXqh08NQHXz3qZUsKd3Dh7edfVTPo21l076yaV+5tK1s2lc27SvbkfY1xiyz1s482H26suuw+5fd7/QQ1H4GpPrY03j0lx/StrJpX9m0r1zaVjbtK5v2lS0RfXWy67Cc5Bynh6D2k5Pmo6k1THNr+OieR9uKpn1l075yaVvZtK9s2le2RPTVya7DZo+Y7fQQ1H5yU6O7Mlc3Bo7qebStbNpXNu0rl7aVTfvKpn1lS0Rfnew6bO7Hc50egtrPgFQfANUNR3cos7aVTfvKpn3l0rayaV/ZtK9sieirk12H6W+o+p6ctNhkV1d2VRe0r2zaVy5tK5v2lU37yqYruwKV15c7PQS1n8FZyQBsrmw8qufRtrJpX9m0r1zaVjbtK5v2lS0RfXWy67CS6hKnh6D2k5eRxLj8NN7dUHlUz6NtZdO+smlfubStbNpXNu0rWyL66nV2HabXC+ub/vxmCXe9vZGcVB9vfe9MsmPn8faEtpVN+8qmfeXStrJpX9m0r2x6nV2B9HphfdPNs0czJDuZ6sZW1pbXHdFzaFvZtK9s2lcubSub9pVN+8qm19kVqCCtwOkhqINI8rp5+qZTANhSfWTn7mpb2bSvbNpXLm0rm/aVTfvKloi+Otl12MzCg664qz5gUEYSfo+LzZUNh3zMK8UV/ODfq2huDR9wn7aVTfvKpn3l0rayaV/ZtK9sieirk12HvVTyktNDUIfgchkGpvt5aEEpL68+cHe4yroWbn5sOc8sK+P1tTvbb9+4q55nlpVx34L3kHxOfH+n37uyaV+5tK1s2lc27StbIvp64v6MqkfOH32+00NQXfjhBeO59cmV/OiZ1extbCU3zU9hVjKjBqZy6d8+bH/c397ZyOiBaYwcmMp5f3k/dut4/pi2gW+fM5Ykr9uZF6ASRr93ZdO+cmlb2bSvbNpXtkT01ZVdh+kW6n3bZVMH8+Z3z6AgM4lfvLCW/35sOZfdM58pRW9QWR/gsqmF/PTiCWze3cin7/6QJxZtAyDVF53c3jtvMxN+8Rr/+mirky9DJYB+78qmfeXStrJpX9m0r2yJ6KuTXYeV1pQ6PQR1GGPz03noqyfyjdNH8uSNJ/P5GUPa77vj8yfwpZOGc9nU6Dbp/++Vj/F5XCz/5Xlcf+ES/nXDiQA8vmgbdS1BfvTMKpaU7nHkdaj40u9d2bRv31BcVsu8o7zm+f60rWzaVzbtK1si+up1dh2m1ws7Nt3yxAqykr38+rOT22+7+52N/OmNEk4ZlcMTN57c3vaRhaX88oW17Y+bNSKbf//XqQ6MWsWTfu/Kpn2dtXJ7DX94bT0ffVKNMYZXbz2dcfnpcXlubSub9pVN+8qm19kVSK8Xdmz62xendZroAnzzrDE8fdMp/PXqqcC+tl8+aTi/v3IKF04axIRB6azcXkNtU7DXx6ziS793ZdO+vW9nbQt3vLGBX7+8js/eM58Fm6u5+sRhpPrczHlpLaFwBIClpXt4++Nd3XrOxkCI+ZuqOm0WqG1l076yaV/ZEtFXN6hy2IisEU4PQcWJMYYTRw5o/7itrctl+MKsYXxh1jDWlddx8V0f8LWHl/DryybTHAzz1JJtVNS28NerpzEg1dejrxmOWP7nxTVcOX0I04Zlx/PlqMPQ713ZtG9irdxeQ1MgxIwR2VQ1tJLqc/PDZ1bxwcYqAKYPy+LOL0xjWE4KEwel84sX1nL5vQv4x7UzuOb/FtEainDftTO4YNKgTs+7bOsegmFLXXOQ7XubefDDLeyoaeYnF03gpjNHA9pWOu0rm/aVLRF9dbLrsHE545wegkqQg7U9rjCDz5xQyH+KK7j4rg863ffH19fzuyuOP+zzNrWGaAiEyEtPYuHmah79aBuPfrSNkt9chM/T84M1whHLqrIapgzOxOs+8PN31wcYkOrD7TI9fu6OrLXsbQqSneLFmKN7rr5Av3dl074HFwiF8Xu6t7t822pq2/d7eU0zrxRXkJPm4wf/Xk04YnEZiHQ4m8rjMvz04olcNWsoaf7oP1G+fPJwslN9fOfJlXzq9nfaH3vzY8u5/Yop5Kb7OWnkABZsqubrjxz81KW/vr2R+Zur+e8zR2tb4bSvbNpXtkT01cmuw97Y/AanDtXzNyU6VNu7YodAf+n/PmLNjjpy0/yMzUvjicXb2VrdxPRh2Xzp5GEUZCYDEApH2FLVyMrtNfx7WRkVtc1U1gV4/Ttn8NyKHe3Pe9Jv3+K175xBfkZSt8dY2xzkf15Yw/Mry0nyuhibl06a38O3zh7Ds8t3sKuuhQ83VZGd4uW4wgz+evU0ctP8R/Tncfc7m7jjzRJuPWcs3z3v2P/LSr93ZdO++7yzfheLtuyhKRDm38u288jXTup0FMv+tlQ1ctO/lrK1uolbzh7Dt84eC8D1/1xMya4GACYMSue6U0ZQWt1IayjCf4orCATD3PulGZw2NrfT8xljuPT4Qppbw7y2Ziej89JI8bm5862N/PCZ1QD43C5awxFyUn1cNGUQL6wo586rpzIuP52SXfXc8PBS3i/ZTW1TK9Mmv6VtBdPvXdm0r2yJ6KsbVDlsWfkyZhTOcHoYKgEO17a5NczHO+uYPiybyroWvvPUShZsrgZgYLqf/7tuJo2tIX76bDGl1U0ApPjcNLWGAUhP8lDfEuLzM4awfmc9xTtqOXHEAM6flE9hVjKDs5KpagiQ5HWzq66F1WW1rC6r4fYrjycr2csjC7fy/sbdrC6rZebwbLbvbWL4gFS2VDeyuz4ARFdZfB4X5x+Xz4uryjlt7EAunVLAqWNy+Md7m9m+p5lvnT2Gbz+xgtPH5nL7FcfjOsgKcEswzGV3z2fDrnoKMpOYf9vZB33csUS/d2Xrr30bAyH+8mYJkwdnMnv8QB5btI0/vr6h02Py0v3M/e9TqWsJ8vSS7Xxh1jDG5afx3Iod/HtpGRsr69nbYV+CH14wntrmIPe//0n7bW9//0xGD0w7qrH+Z47iOqkAACAASURBVHUFf3mrhO+dN47fv7aerdVN/OHK47lq1lBaguH265tba3lyyXZ+8mwxABMKvDx6w5lH/Is71bf11+/d/kL7ynakfbvaoEpXdh22tHypftMKdbi2yT4302Pn2eZlJPH4N06moraZd9ZXcs87m7jsnvntj731nLE0tYa4YvoQJhZkULKrnm8+tpz6lga+MGsoM4Zn89yKHfzwmdUsPsylja7530VErKWmqZU0v4c/X3UCV0zfdzmlHTXN/OqltXzllBGcOHIAxhjcLkN+ZhL/98EW3i/Z3en53ot9/PTSMobnpPLVT40gxRf90fL4om384fX11MT+4TsqN5VPqhpZtGUPp4zO6cGfZt+j37s9s626ibqWILlpfgZldv/oA6f0p76V9S0Ul9Xy/MpyNuysa199bePzuJh/29lsqWqkvKaZ7zy1ktP/8G77/U8u2U5Gspfd9QFG5qYya8QAvn3OWLJTfXz7iRWdJsv/+fZpNLWGj3qiC3DJ8QVccnwBADOGZ/Pu+ko+F7s0XNtEF6Irw188cRhnjc/j7/M28fDCrfzulfVMG5bFl04aJuK0CrVPf/re7Y+0r2yJ6KuTXYdVNFQ4PQSVIEfStiAzmS+dNJxzJ+bz93mbGZefTnqSh0uPL+j0D7Jx+em88d0zqA+EyEjyAnDF9CGcOjqX5mCYTZUNNLWG8Htc+DwuBmelsLs+QGNriHve3YS18NjXT2JiQcYBYxiclcx91x74y7GfXDSRH184gXfWV7K1uompw7JI83t4aEEpZ4/P48H5W/jj6xv499LtPPTVEwmEIvz0uWLG56czPCeVdL+HX376OC6/Zz4PfPgJ4/LTyImtrLSGInywcTdThmSSl973J0Kg37s9sXFXPef95X0AUn1ufv3ZyVw+bXCfnmT0l753vb2RP79ZAkB2ipe89CTuvmYadc0h1u+sY3VZLd84fRQD0/0MTPcTiVgi1vLJ7kbyMvycOHIAv3tlPQ2BEN8+ewxXTB9Cqn/fPy2evPFkxv7sVQBe+87pTBh04M+ceMjPSOLqE4d1+ZhBmUnMuWwyL69dx9zlZcxdXsaM4dkH/TnYlZ21LazYtpfzjsvHc5B9DpSz+sv3bn+lfWVLRF89jNlher0wufpb22A4wr8WbuXX/1lHxx8rS352LgPT9x0u+Oc3S7jr7Y2k+T384tKJzBg+gCWle9oPMbz+1BFMG5bF5MGZDM1OwedxUVnXwidVjazZUcsnVY1MHZrFBZMGkeb3sLeplT2NrVTVB2gIhDh/v91ZE6W/9e2uYDhCZX2AwVnJvLSqnL+9s5Fg2LKlqpHjh2TSGoqwfmc9v79yCl+Y1fXkxEmS+rYEwxgDdc0hMpO97G6I9qmsa+G0P7zLSSMH8JVTRnD6uNxubz7VEw98uIU31u7kyRtP7hO/4HinZBPbdruZ8/I6jivI4OmbTmmfoDcEQry1bhevrdnJp8bkcM1Jw1lSugcDWOC1NTt5ZlkZDYEQXzllOHMum9zl11K9T9L3rjpQf+gbiViMoU/8vOxtibjOrk52HVY0r4ii2UVOD0MlQH9tu7R0D5/7x0IAzhg3kEe+dmKn+621vL+xih/8exW7Y5OiKYMzeW3tToyB/X8k5ab52NsUJBzbstXvcREIRZhUmEFOmv+Aw6onFWZw1vg8vn76SLJSenYpp57or30BKmqbKa9pYcbwzpe7agmGueq+hawuq2XYgBR21rbQGo4wKCOJos9M4sLJgwhHLJfd8yFrdtTxx88dz+dnDnXoVXStJ31LdtVTWRfgpFEDDrqjeaLtbWzlvZLdPL9yB9OHZXPTmaPYUtVIOGK5/dX1LNxcTSjS+RvrlFE5LPykGq/b8Nb3zmR4Tmqvj9spbW1/8mwxTyzexnfPHcet546ltjnI5ffO55PdjV1+/smjBtAQCLGpsoGPfnJOQn/OqJ7rzz+b+wNpfcMRy3efWsmqshoeveEkhg5I4aw/zSM/w8+TN57i9PB63ZH21XN2+zDdQl2u/tp25ogBfPCjs8hK8R70H/7GGM4cN5CXbzmNK+5dwI6aZnbUNHPecfn87YvT2NMYXamd89JalpTuZUCqj+nDsslM9nL59MFMH5bNM8vK+P1r61lbXsfs8QOZNjSbQZl+tlQ18eD8Lawtr+M/xRV8+vgCslJ8pPrdnDgyh5G58fsHfX/tW9PUyhX3LqCitoVPjcnhzHEDuWDSIHLT/Dy0oJTVZdGN0nLTfcweP5BvnD6KoQNS2j/f7TLccvZYbvrXMn7ybDHj8tM5YWiWg6/o4LrT97FFW3m/ZDdvrttFxEJmspfTx+bidhk+2FhFxFqmDM5kTF4a9S0hlpbu4bYLJ3Dh5EFx+439hxuruPmxZdS1hACYt2E3d7+zidZwBIj+cuiG00cSDFkWl1aT4vWwp6mVhZ9Uk+x185OLJ/SriS7sa/u7K6ZQsquev7xVQvGOWt7fuJtQOMIdnz+B08bm8r2nV7JtTxPJXjeXTCkkJ81HktfNZVML2birgYvv+oBbn1zJjy4cz5i8tE6r4rXNQVqCYZpbw4QiEcbkpTv1cvud/vqzub+Q1vfv8zbx4qpyAH7/2nr++LkT2FLVyJaqrn/pJpVeekgg6Ydi9Gf9uW3Hyc2h5Gck8cD1M7nwzuj1hr9+2kiSvG4Ks5IpzErm6ZtOIRCKdNpops2XTx7O1bOGUl7TwrCczl/ryumDWbGthnvnbeKudza13+5xRTepOfe4fMKRCGeNz6NsbzNPL91OYyDM104bwZDsw4+7zaH6hsIRWsMRWoIRdta2kJ7koTkYpjUUITPZ260/m660hiK4THTS6MQhTq8U76SitoVLphQwf3MV8zdV89tX1rfff+7EfP7vKwf95Wq7CyYNYtUvz+fiuz7gC/cv5NyJ+eSm+alvCTEuP40Zw7M5fkgWbpfh3fWVZKd6yUrxsWp7DaeOziU/w5/w197V9+/2PU385j/reH3tLjKTvVwxfQifGpPDP+eX8vranQB8+oRCPC7Dim01LNqyh1A4QsTCfz+2nOE5Kfz6sslsrGygrjmItZayvc20hMJkJHn53IwhjB6YRkMg1OX/L5GI5TtPraQgM5mHvzaFSYWZPLlkGx9XRHd5txaOH5p5wHmykYilvLaZwszkY35X9CPRse0/vjyDH89dzVsf7wLgvmtncEHsVIjHvn7yIZ/juMIMTh41gPdKdvNeyW6GDUhh9viBJHndLNxcTfGO2k6PX/bzc9v3KFCJ1Z//7u0PJPUtrWrkT2+UcMnxBQxM8/PIwlLG5+/7xVgkYvvdz+hE9NXJrsPmlc5j9ojZTg9DJYC2PbwJgzJ45/tnMjI39YDJizHmoBPdNh6364CJLsDY/HTG5qdz1ayhhCOWPY2tlNdEJ7WPL97Gvz7aCkRX4epaghjAZQwPLywlN83H8JxUvnPuWE4dnds+QfF5XIQjlrK9Tawqq6W8ppnlu5fT2jiBmqYgNc2t7G0Ksq26iXfWV9IcDB9y3BMLMrh8WiHJPg9V9QG27WlibXktY/PTuXzqYEIRS5rfw4kjB/CnNzbw1rpd5GX4aQ1F2FrdRHVjKwCzRmRz4eQCRg1MZXRuGkOyk1lTXsu8Dbu54bSRnTYJiofislr+78NPmLch+g/7u6+ZRjBsWbFtL8u27SUQjLCnsZVvnzO2W8+XmeLlvmtncP0/F7N8614aAiHqA6H2w9izUryk+jzsqGk+4HOvmD6YOz5/QtwnvNZawhGLyxjmlc7jU0PPYG15HZnJXrJjRyq8umYnf3mzhNrmIN8/bxw3nzUGd+wfI5dPG0JLMNzecH/BcITnV+zgrnc2ct2Diw+432UgxefhySXbgegvNP74ueO5eEoB4Yilsj6Ax2UYlJmEAf45v5SqhgA/v2Qi02I7u193yojDvk6Xy/ToFzvSdPzZPDDdz/3XzeRfC0uZUJDByaO6v0v8fdfOZOOuetZV1PHk4u08sjD6s8XjMtx05iiSvW4eWbiVPY2tnP6Hd7lw0iAykr3UNLWypaqR+66d2b4zeVNriIZA6JjZoK8v0797e66yvoXvP72KQDBCfmYS507M47Kpg9vv31bdxKtrKnhyyXZ+eelxnDUhz7GxSui7Zkct4wels66iDoD/PnM09S0hHlpQyh2xDQMBdtW3UJCZ7NQwHZGIvnrOrsOKdxUzJX+K08NQCaBt+56qhgALN1ezuqyGuuYQhVnJXDVrCOGI5V8Lt7K6rJYtVY3srGthQGr0PLym1ug/QOtbgp2uHbo/r9tgMORl+PnyycPxuV3kZfhpaAlRtreZnXUtNLSE2LS7gU2VnS/tMjI3lar6APWBUPttLgMRC1OHZrFhZz0TCtKZMCidjCQv8zbspqSyvtP5zXnpfipj10duc8GkfH568USeW7GDjbsaCIYj/OjCCYzJ6/llX25+bBmvFO9kUEYSt100nsunDTn8J/VQOGLZvqeJNeW1vL52Fy3BMGeMzSUQiuDzuKhvCfH8ih1srGygIDOJk0flMKkwgw0765k5IpurZg5tnwA3BEIke93tE9H97a4P8O6GStZX1BOORFi0ZQ+fVDW2r8DnpENVnW0/PNjncUU3d4r9GT9386ntE8yeWl1Ww/+8uJazxudxy9ljsBbqA9HJTorXzY+fXU3Z3mZKdtUTDHf9d7THZVj003N01bAHEvGzORKxvFeym+nDsknyuTod0vxxRR33vbeZN9ftImwtLcHoIeZZKV5G5KRSWt1IbXMQv8fFRZMLqKxv4TMnFJKXnsRra3Zy/qR8zpmYH9fxSibt795QOEJNc/SybW0bqJ0/Kb/9En+HU9sUxO91YQysLqulbG8Tza0Rhuek0BgI8cjCrXy4qar98W1/l5w7MZ80v5u3Pq6kocPfTQDfOmsMU4dmMWvkADKTvZ3u+2R3A2vK69i+p4mhA1L4zAn7Vur2NrayuHQPZ43PY8W2vexuCOBxuXAZeGZZGfkZSYwflM6WqkZ+eMH4g/7C+1jvO29DJdf/cwmnjcllYLqf51bsYN2vLiDZ6+bFVeW4XYZUv4ev/nMJT914Mif14BdwEhxpX92gqg/726K/cctJtzg9DJUA2vbY1BIM8+D8LWyubCQUiZDsddPUGqamOch5x+VzXEEG+Rl+/vLh43x1+ufJSokeYpvqcxMIRYhY2+U/Qqy17KxrobqhlUGZSdQ0BRmRk0LEwuIte6huDOB1u3h80TbGD0rnZxdPPOhhTC3BME2tYTbvbmD9znqeW15GVoqPz88Ywv0ffMKKbTWdHp/sdbevOJ89IY9LphRwyugcCjKT+HBTFZsrG7j6xGHt/7iw1nZaOb34rx8wKDOJB6+fFY8/5iMWiViKXlrLqrJaSnbW0xwM43EZQhFLVoqXzGQv9S0h9jS2MigjiXMm5hEKWzbsqqc1FCErxcuuuhY2xzYhars817j8dGaOyCbF62H9zjo+rvyEWUPHcfzQLPY0tFLVEKCitpmsFB9XTh/SK9eJrmoI8EpxBWV7mxmQ6iMn1Udtc5BNlQ2kJ3nISvFx/nH5jM3X80F7wsmfza2hCC2hME8t3s4/3ttMTXOQz04dTE6ajwWbq9jbGKSyvuWAX3Lsfz10dWjH+t+9NU2tFO+o5ZllZazcXkNFTXSjv+wUb/svXIdkJ/Ots8bwhVnRX/DN31TFU0u2s7OuhV9cchyTB2ewfNteHvhwC68U78TrNriMIRCKHPRrjslL42eXTGRsXhqDMpL44xsbeGLRtk5H20R3LXdz+T0L2vcEyErxct+XZ5Dq97BhZz1Lt+7lqSXb6Lgf3vPf/BRLtuyhriXI00u3s6su0L7RZEdtv+BtM2FQOudPGsQ3Th9JstfNwwu38tEn1VQHSrjrc5+lMDOZ8trokT+vFFeQk+rniun7LmlXWdfCk0u2c+roHGaOGBCPND1WWdfC9/+9ioiNHu2ztbqJnXUt1Oz3i/PS2y/p9PH2PU2c/od3+e3lU7jmpL571YJEONLvX92gqg+rbq52eggqQbTtsSnJ6+bm2WMO+7j09DImD8484HMPxxhDQWZy+6FJuR1W5E4bm9v+/sVTCg47ziSvmwGpA5g1YgDXnjy8/b4LJw8iEIpQ0xTk4YWlFGQmce3Jw1m+rYbHFm3lo83VvLO+8oDnLHppHQADUn2EwhFeufV0hmSnsKuuhXUVdZw0ypl/MHTkchl+FbvcSyAUZmt1E8NzUniluIJ31+/mnfWVXDh5EIVZyRSX1fCf4grCYcvQASm4XYa6lmD7RPfhr53IqaNzDrqRWtG8lyia/flefW37y03zd+uwZNUzTv5s9sV+ufKNM0bx5ZOHU9UQOOC87NZQhDXltTQFwgzPSeFbT6zge0+v4s11uzhnYj6fmxGd9Na1BGloiR4RMDI31ZGdwPuiI+kbCkdoCITweVzdXjE9FGstTyzeTtneJixw0sgBrN9ZT7LXzdUnDu206m+tpby2hcLMJCpqW/jNf9bxQUlV+1E+F04axIWTB+F3u1i9I3oKzfWnjuTRj7by42eL+X//+Zjm2KkTEJ0wfvruD9t/uelzu/jqp0awY28zhVnJTB+ezcicVLJSvGzf08Su+hYmF2YyLCel07h+ctFEfnzhBJqDYYJhS0Vtc/u5/6/cehp+j5vFW6KXDPzC/R91ev35GX5+fNEESqua+OvbG/nsPfMBMAYKMpKYPX4geel+zp6Qx+CsFFrDYfY2Bjl1TA4fV9Rxz7ubaWgJsbh0D+t31nPvu5vITvWxuz7AqNxUtlSnc+Yf55Ge5Dlg0ri2vI4vnTyMe97ZxPzNVeyqC/DwAh9vfPeMHh39Yq0lFLEHfE8t3rKHF1buoDArmatnDe3yOYvLavnOUyvYvLuRwVnJ1LVEN60DeOzrJ9EainDb3NWcOW7gAZ87OCuZVJ+bDTvruj1mKRLx81lXdh3WH64X1l9pW9mO5b6RiGVdRR1PL93Oi6vKuemM0QzK9LNmRx0PLShlzMA0NuyqB+j0G/hfXHocN5w20smhH9b+K9IHu23jrnoiFsYPOvSK6LHcV3XtWGv7fslubn5sOS4DdS0hLptaSEFmMo8sLKWpNfqP51G5qfzi08eRmeylIDOJ5VtrSPa5OHV0brd+CXesWLFtL+t31rfvlVDXHMTtMqT4PGQme/F7XIRsA/XNPlqCkdiGgZZQOEIwHKGqoZWNlfUked18+vhC9jS18tzyHe1HvfjcLnLSfBRmJZPm9xCKRBiY5qeuJcTm3dEN5c4YN5CpQ7NYub2GYDjCiSMGUJiVTHVjK5srG3hqyXbqAyHcLtN+ybw2g7OSGZKdzMwR2dQ1h/hg425Kq5u4Yvpg1pXXsX5nPRdMymfCoAxOH5t7yBVJay1zl+9g5fa9JHvd5KT5uWrmUAKhME8s2kZDIMzY/DTOmZBHXkbizgPfVt3E3OVl+L0uLpwUvbRcWpKHgsxkrLW8sLIci+XU0bnkpvmje2R0c8OlhkCIkl31vLluFx9X1HH5tMFcNnUwK3aU8taaFipqW5hUmInLgNft4vW1O/lg477DsacNy+KLJw7jZ88VU5iVzG0XTmDK4ExcLsPaHbW8uKqcX156HHkZSbQEwzyzrIwHP9wSO5KrlZZghFmx02Nqm4NUN7by93mb25/f53Fx4+mjOH9SPq+u2cmXThrGkOwUNu9u4OEFpe3n8P/vdTM577joaQjWWpqD4fZfqBzs76s2l987n/UV9Xz0k3PITPHSEgzz17c3kuJ1882zxojduEqvs9tDx8JkV9r1wtQ+2lY2KX33/8u2uTVMss/NW+t28cfXN7ClOnoeK8CjN5zUafVZMil91YGO1bbhiOUPr63nsUXbaA6GOXV0DmeNz6OpNcTDC7e2n0/eUbLXzeljczl+SCbXnjLigPMrjwWPL9pGRW0zy7buZcHmfas+PreLjGQvoUiEpkC4/dBaiJ7LnuR143EbPC4XPrfB43aR5vcwPCeFjz6pbj8k+OIpgxifn0Gq383O2hZqmoN8srshulmdy7C1uomBaX7G5KdFN69bX0l9IERmspc0f+dN9Nwuw5TBmUwYlM5vL59CQ2uIZaV7GZOXxvJte3luxQ527G1mY2UDPreLIdnJfFLViNtlcBvDnVdPPexRPf3dob5/wxHLok+qeXFVOWeMG9j+5/jMsjL++Pp6dtUd+P2R4nNzxtiBrCqroaK2hWnDshg9MI1Un5u0JA9PLN7OntimkADTh2Vx8+wxDM9J4Qf/XsWqsn27rg/OSmbasCwWbq6murEVn8fF/2/vzqPkKss8jn+frt67k3SSzkYSCCQEBjkgAWVziTBIHDnCuE3GDQXFmRF11Dmj6JmhMzozOoriHJYjx2giYiBDUAKCyKoCIUASyEpCVrKRpZNOutN71TN/3JumknSW7nT1rXrz+5yTU32XKt57frzd96n73vc+8I+XHDIC7Fjd/OBSZs7bQHVZMTWVJWza/db/Zz/5u3NzMm9GPsjFc3ZV7CZszvI5fOSsjyTdDMkBZRu2EyHfdMZp64y+hX6jvpmxQyoSedxREk6EfE9UhZ5ta0f6kLkBWtrTvLxhFzsa29i1r51JpwymsbWT2S9v5NElW8k4DCgrZvTgCi4ZX8vwgWU8sXwbWxpaOHPUwK4i2N0pL0lx9uhB0XwEFaXsbm7n+TX1dKYzjB1SybjaKoqLontAS1LGwIoSxg6upKGlnaWb93JSTTljB1cyuKqUypJUt1eg3J1nV+9kYHlJt8/Z3rWvnWdX7+RPK3cwZ+EmILp6fc15o/nwpNEMrSqjvKSo6/dROuN0ZqJHvs1eMpfPnv+3RxzWnck47ekMe1o6GNHDK5+d6Qxv7m1laFUZFaUp1u2MJhgbPqCMmsqSYxoGHc36Tlf7WzvSdKQzDCgvvC8j+ltv+m9Le5oX1tazo6mNTMZJFRmPLdvGX17fQUc6w7lja/jS5AlcdubwA/5/bWztYPGmPWxvbOXkIVWcf8pbkxLu2tfOEyu2sXl3CyMGlnPHM6u7CtLffOHCaLK64xhVsbe1g+dX1/OnVdt56rXtNLV2cvsnJ/FvDy5ldE0Fs75wEWbGxl3NLHxjN++IRxgUut7+fg7mnl0zmwL8FEgBP3f37yfcpONWXdrzWVGlMCjbsJ0I+e4fHgh0+5inkJ0I+Z6oCj3b7k6gK0pTvPv0Q+/9e+/EYaQzztLNe7hn/gY2N7Rw9wvr6Ug7VaUpLh4/lI27Wnh9eyNGdJLf2NrR9fir/VJFRnVZMXtaDj8jfXfGDK7gA2ePpMiM5Vv3UlVaTO2AUhqaO3h48VYABleWkCoydseT9e1t7aS+qa1rsqLLzhzO7Z+YREXp4QuHVJGRKkpRVpzi5CHVR71/uajIKC9K9aoYKU4VHfDorlNrq3r8GQfPEr9/DgY5ut7034rS1CGPS/rYBWMPmOm6OwPKS7h0QvejmYZUlfLxC8Z2LX/iwpP5v5c30taZ4ZLxxz8CamB5CVPOHhnPwZGmqbWTodVlXHvxOL73+xXcOGsRa7Y3sXJb9GSGEQPLmHndOw95rnqhycXv54Ipds0sBdwOXAFsAl4ys7nuvjzZlh2feZvmceWEK5NuhuSAsg2b8g2b8g3XiZZtqsg4d2xN1xXUdMZp7UhTkoomyzqYu/PGrmY27mphZ1Mb44dVM3xgGcMHlNHcnmZLQwvp+JnUbZ0ZNtTv4/VtTdRWl/H2k2vYva+dzQ0t1De1M29NPTOf30DGnQnDq3kz08r8dW00t6f5yKQxjB1SwZt7WunMOIMrS1izYx81lSWMHFjOeyYO47RhVdRWlfXo/sQTLd8TTV/mW5wqOmyh2xsfyyp++1JZcYqy6ujLkOsuPZXV25u496WNjBpUzo3vm8CZIwdy0wOLufq25/jK5acztKqUklQRu/a1M2JQOSkzxtVWMn5Yda++VGlu7zzuiduOVS76b8EMYzazi4E6d78yXr4JwN3/+3DvKYRhzCt3ruSM2jOSbobkgLINm/INm/INl7LtfwfPDXCkiXmOl/INm/KN7GxqY1BFSdcohh2NbXxl1iLmrT3ybMYDyotJx0O5h1WXMaiyhHTG6Ug7JanoXveW9jRmkHFn8+4WGlo6eO27Uw6YsTtXeptvKMOYRwPZ42o2ARcm1JY+8/Cqh9VpA6Vsw6Z8w6Z8w6Vs+9/BhW0u7/1XvmFTvpGDr0gPG1DGrBsuYntjK81taTozGWqry9je2EZn2lm1rZHNDS28uaeVklQRGXd2NLaxtzWa0by4KHoOc1tnhtrqUjozTpEZ54ypYXRNxSEzi+dKLvJN1dXV9ekH5sq0adPOAibU1dXNjZfPBcbU1dU9kr2fmd0wbdq0n02bNu2GjGVOajq/iaEVQ5m9bDaPrn6UiUMncsu8W6hvrmfjno38evGvGVU9ipmvzOSZ9c8wdtBYbn3hVhrbGllVv4pZS2cxrmYcd7x0By9ufpGhFUO57cXbaOts49U3X2X2stldn7lk2xIqSyq58+U7AXh+4/PMWTGna/vKnSsxjLsW3EVpqpQn1z3JnOVzuGL8Fdwy7xbWN6ynuaOZ6YumM6B0AA+tfIiHVz3c9f4tjVuob6lnxisz8vqYfvfa77q2n8jHNH3hdCaNmhTUMYWYU2+PacXOFZQUlQR1TCHm1NtjWtuwlvmb5wd1TCHm1Jtj2tu2l2ffeDaoYwoxp94e0/RF01lVvyqoYwoxp94e092L7+a9494b1DH1ZU6bGtcwuLKU+1+bwcDyCl7Z/izPbX6UD519AX/Z+ktOG9nMO06rYk3zQ0y9YCLFVQsprlrEv1z+Pta13selZ6R49xnl7C16gs9fcg716WfY2Tmftw0/s1+Oae3utTS1N/U4pwd/9uDWurq6u7qrITWMOWHrG9YzrmZc0s2QHFC2YVO+YVO+4VK2YVO+YVO+YettvkcaAra5/AAAC71JREFUxnzk6eryy0vA6WZ2qpmVAlOBuQm36bjNeGVG0k2QHFG2YVO+YVO+4VK2YVO+YVO+YctFvgVzz667d5rZjcBjRI8e+oW7L0u4Wcft/FHnJ90EyRFlGzblGzblGy5lGzblGzblG7Zc5FswxS6Auz8CPHLUHUVEREREROSEVkjDmIO0YOuCpJsgOaJsw6Z8w6Z8w6Vsw6Z8w6Z8w5aLfAtmgqre0ARVkiRlGzblGzblGy5lGzblGzblG7YTfYKqIP1myW+SboLkiLINm/INm/INl7INm/INm/INWy7yVbGbsLJU2dF3koKkbMOmfMOmfMOlbMOmfMOmfMOWi3xV7CbsqolXJd0EyRFlGzblGzblGy5lGzblGzblG7Zc5KtiN2Gzls5KugmSI8o2bMo3bMo3XMo2bMo3bMo3bLnIV8Vuwi4ec3HSTZAcUbZhU75hU77hUrZhU75hU75hy0W+KnYT1tTelHQTJEeUbdiUb9iUb7iUbdiUb9iUb9hyka+K3YQt2b4k6SZIjijbsCnfsCnfcCnbsCnfsCnfsOUiXz1nN2FbGrdw0oCTkm6G5ICyDZvyDZvyDZeyDZvyDZvyDVtv89VzdvPYXQvuSroJkiPKNmzKN2zKN1zKNmzKN2zKN2y5yFfFbsKGVgxNugmSI8o2bMo3bMo3XMo2bMo3bMo3bLnIV8VuwiaPm5x0EyRHlG3YlG/YlG+4lG3YlG/YlG/YcpGvit2EzVkxJ+kmSI4o27Ap37Ap33Ap27Ap37Ap37DlIt+gJ6gysx3AhqTbcRS1wM6kGyE5oWzDpnzDpnzDpWzDpnzDpnzD1tt8T3H3Yd1tCLrYLQRm9vLhZg+TwqZsw6Z8w6Z8w6Vsw6Z8w6Z8w5aLfDWMWURERERERIKjYldERERERESCo2I3eXpgWLiUbdiUb9iUb7iUbdiUb9iUb9j6PF/dsysiIiIiIiLB0ZVdERERERERCY6K3YSY2RQzW2lmq83sW0m3R3rOzMaa2dNmttzMlpnZV+P1Q8zscTN7PX4dHK83M/vfOPPFZjYp2SOQozGzlJktMrOH4+VTzWx+nOF9ZlYary+Ll1fH28cl2W45OjOrMbP7zew1M1thZher74bDzL4W/15eamazzKxc/bdwmdkvzGy7mS3NWtfj/mpm18b7v25m1yZxLHKgw2T7w/h382Iz+62Z1WRtuynOdqWZXZm1XufVeai7fLO2fcPM3Mxq4+Wc9F0VuwkwsxRwO/AB4Czg783srGRbJb3QCXzD3c8CLgK+FOf4LeBJdz8deDJehijv0+N/NwB39n+TpYe+CqzIWv4B8BN3nwDsBq6P118P7I7X/yTeT/LbT4E/uPuZwLlEOavvBsDMRgNfAS5w97OBFDAV9d9CNgOYctC6HvVXMxsC3AxcCLwTuHl/gSyJmsGh2T4OnO3u5wCrgJsA4nOsqcDb4vfcEX8prfPq/DWDQ/PFzMYC7wfeyFqdk76rYjcZ7wRWu/tad28H7gWuTrhN0kPuvtXdF8Y/NxKdLI8mynJmvNtM4Jr456uBX3nkBaDGzEb1c7PlGJnZGOCDwM/jZQMuA+6Pdzk42/2Z3w9cHu8vecjMBgHvAaYDuHu7uzegvhuSYqDCzIqBSmAr6r8Fy93/DOw6aHVP++uVwOPuvsvddxMVVIechEv/6i5bd/+ju3fGiy8AY+Kfrwbudfc2d18HrCY6p9Z5dZ46TN+F6IvFfwWyJ4/KSd9VsZuM0cDGrOVN8TopUPGwt/OA+cAId98ab3oTGBH/rNwLy61Ev4gz8fJQoCHrD3B2fl3Zxtv3xPtLfjoV2AH8Mh6m/nMzq0J9Nwjuvhn4EdEVg61E/XEB6r+h6Wl/VT8uTNcBj8Y/K9sAmNnVwGZ3f/WgTTnJV8WuyHEys2pgDvDP7r43e5tH051ryvMCY2ZXAdvdfUHSbZGcKAYmAXe6+3nAPt4aAgmo7xayeHjb1URfapwEVKEreEFTfw2TmX2H6Jaxe5Jui/QNM6sEvg38e3/9N1XsJmMzMDZreUy8TgqMmZUQFbr3uPsD8ept+4c4xq/b4/XKvXBcCnzIzNYTDYe6jOgez5p4WCQcmF9XtvH2QUB9fzZYemQTsMnd58fL9xMVv+q7YfhrYJ2773D3DuABoj6t/huWnvZX9eMCYmafBa4CPulvPSdV2Ra+8URfRL4an2ONARaa2UhylK+K3WS8BJwezwxZSnSz/dyE2yQ9FN/TNR1Y4e4/zto0F9g/U9y1wINZ6z8TzzZ3EbAnawiW5BF3v8ndx7j7OKL++ZS7fxJ4GvhovNvB2e7P/KPx/rrKkKfc/U1go5mdEa+6HFiO+m4o3gAuMrPK+Pf0/nzVf8PS0/76GPB+MxscX/1/f7xO8oyZTSG6jehD7t6ctWkuMNWiGdRPJZrI6EV0Xl0w3H2Juw9393HxOdYmYFL8dzknfbf46LtIX3P3TjO7kSioFPALd1+WcLOk5y4FPg0sMbNX4nXfBr4PzDaz64ENwMfjbY8Af0M0oUIz8Ln+ba70gW8C95rZ94BFxBMcxa93m9lqookYpibUPjl2XwbuiU+M1hL1xyLUdwueu883s/uBhURDIBcBdwG/R/23IJnZLGAyUGtmm4hmZu3R31p332Vm3yUqjAD+w927mzhH+tFhsr0JKAMej+eKe8Hd/8Hdl5nZbKIvrzqBL7l7Ov4cnVfnoe7ydffph9k9J33X9OWliIiIiIiIhEbDmEVERERERCQ4KnZFREREREQkOCp2RUREREREJDgqdkVERERERCQ4KnZFREREREQkOCp2RUREREREJDgqdkVERBJkZpPNzLP+pc1st5ktNbOZZjbF4odN9vLz325mdWY2ru9aLSIikv+Kk26AiIiIADALeAQwYABwBnAN8BngCTP7mLs39OJz3w7cDDwDrO+TloqIiBQAFbsiIiL5YaG7/zp7hZl9Hfgf4OtExfAHkmiYiIhIIdIwZhERkTzl7ml3/wbwLDDFzN4FYGYnmdktZvZKPOS51cyWm9k3zSy1//1mVgf8Ml58Omuo9IysfcrM7Ntmtiz+nAYze8jMzuu/IxUREel7urIrIiKS/6YD7wI+SFT4ngN8GPgtsAYoAaYA3wdOA74Yv+8BYBRwA/BfwIp4/RoAMysB/gBcAtwN3AYMAr4APGdm73H3l3N8bCIiIjmhYldERCT/LY5fJ8avfwJOc3fP2udWM7sb+LyZ1bn7VndfbGbziIrdx939mYM+90ZgMjDF3R/bv9LM7gCWAj+Kt4uIiBQcDWMWERHJf3vj14EA7t6yv9A1s1IzG2JmtcBjRH/bLzjGz/0U8BqwwMxq9/8DSoHHgXeZWUVfHoiIiEh/0ZVdERGR/Dcwft0LYGbFwLeIZmqeQDSDc7bBx/i5fwVUADuOsE8tsPGYWyoiIpInVOyKiIjkv3Pi15Xx64+BLwP3Af8JbAc6gEnADzj2kVsGLCGa7flwjlQIi4iI5C0VuyIiIvnv+vj19/Hrp4E/u/vU7J3MbEI37/Vu1u33OjAMeMrdM8fdShERkTyie3ZFRETylJmlzOxHRDMxP+Luz8Wb0hw0dNnMqoCvdfMxTfHrkG62/QoYyWGu7JrZiN60W0REJB/oyq6IiEh+mGRmn4p/HgCcAVwDnAL8EfhE1r73A180s/uAJ4ARwHVAfTef+xKQAb5jZoOBfcA6d58P/BS4AvihmV0GPEV0X/DJwOVAK/C+vjxIERGR/mIHPrVARERE+pOZTQaezlqVIboauwl4GZjl7n846D2VwDTg40SF7kaiZ/G+RFT8fs7dZ2Ttfy3wTaLJrEqAme7+2XhbMfBPREOjz4rfsgV4Md7vj312sCIiIv1Ixa6IiIiIiIgER/fsioiIiIiISHBU7IqIiIiIiEhwVOyKiIiIiIhIcFTsioiIiIiISHBU7IqIiIiIiEhwVOyKiIiIiIhIcFTsioiIiIiISHBU7IqIiIiIiEhwVOyKiIiIiIhIcFTsioiIiIiISHD+H4Gdcr+JVcwUAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 1152x576 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":265},"id":"-qARJjMOhHnk","executionInfo":{"status":"ok","timestamp":1630408965231,"user_tz":-330,"elapsed":540,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"fe7aa6dd-63cb-4b51-805b-b58f83615572"},"source":["data_change = df['Change%']\n","plt.plot(data_change, label = 'Changing Evolution')\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAAYAAAAD4CAYAAADlwTGnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO2dd5gUVdaHf2cCQ5QhDAjMwAyIICrJkSSKAgKKgrrsCmvEgK64mP1A1MVVFLOyRsQcUEQFFJQkIIiAQ0biMOQ4Q44T7/dHVXVXV1dVV3dXd1d3nfd55pnuirdv3brnnnDPJSEEGIZhGPeRFOsCMAzDMLGBBQDDMIxLYQHAMAzjUlgAMAzDuBQWAAzDMC4lJdYFUFO3bl2RnZ0d62IwDMPEFcuWLSsSQmQEe56jBEB2djby8vJiXQyGYZi4goi2h3Iem4AYhmFcCgsAhmEYl8ICgGEYxqWwAGAYhnEpLAAYhmFcCgsAhmEYl8ICgGEYxqWwAIgAf2w5iC2FJ2JdDIZhGFMcNREsURj0wWIAwLYxfWNcEoZhGGNYA2AYhnEpLAAYhmFcCgsAhmEYl8ICgGEYxqWwAGAYhnEpLAAYhmFcCgsAhmEYl8ICgGEYxqWwAGAYhnEpLAAYhmFcCgsAhmEYl8ICgGEYxkZ6vT4f/d5aGOtiWIKTwTEMw9jIpv3xkwnYFg2AiNKJaBIRbSCi9UTUmYhqE9EsItos/69lx70YhmEYe7DLBPQmgF+EEC0BtAGwHsBwAHOEEM0BzJG/MwzDMA4hbAFARDUBXAbgQwAQQpQIIY4A6A/gU/mwTwFcF+69GIZhGPuwQwPIAVAI4GMiWkFE44moGoD6Qoi98jH7ANS34V4MwzCMTdghAFIAtAfwrhCiHYCT0Jh7hBACgNA7mYiGEFEeEeUVFhbaUByGYRjGCnYIgF0AdgkhlsjfJ0ESCPuJqAEAyP8P6J0shBgnhMgVQuRmZGTYUByGYRjGCmELACHEPgA7iaiFvKkHgHUApgK4Td52G4Ap4d6LYRiGsQ+75gH8G8CXRFQJQAGAwZCEy0QiuhPAdgD/sOleDMMwjA3YIgCEECsB5Ors6mHH9RmGYRj74VQQDMMwLoUFAMMwjEthAcAwDONSWAAwDMO4FBYADMMwLoUFAMMwjEthAcAwDONSWAAwDMO4FBYADMMwLoUFAMMwjEthAcAwDONSWAAwDMO4FBYADMMwLoUFAMMwjEthAcAwDGMT0uq38QMLAIZhGJfCAoBhGMalsABgGIaxiTizALEAYBiGcSssABiGYWwizhQAFgAMwzBuhQUAwzCMTXAYKMMwDBMXsABgGIaxCfX4//np65E9fFrMymIFFgAMwzARYNxvBbEuQkBYADAMw9hEnLkA7BMARJRMRCuI6Cf5ew4RLSGifCL6hogq2XUvhmGYeMHJjmE7NYAHAKxXfX8RwOtCiHMAHAZwp433YhiGcRxCZyaAg/t/ewQAEWUC6AtgvPydAHQHMEk+5FMA19lxL4ZhmHjCwf2/bRrAGwAeB1Ahf68D4IgQokz+vgtAI70TiWgIEeURUV5hYaFNxWEYhok+eqP9CgerAGELACK6BsABIcSyUM4XQowTQuQKIXIzMjLCLQ7DMIyjcLIASLHhGpcA6EdEVwOoDOAsAG8CSCeiFFkLyASw24Z7MQzDxBUO7v/D1wCEECOEEJlCiGwAAwH8KoS4CcBcAAPkw24DMCXcezEMw8QbTtYAIjkP4P8APExE+ZB8Ah9G8F4MwzCOxMH9vy0mIA9CiHkA5smfCwB0sPP6DMMwTsZ1TmCGYRjGmArn9v8sABiGYexCfyKYcyUAC4AI8tHCrRj61fJYF4NhmBjCGoBL+e9P6zBt9d5YF4NhmCihN9hnDYBhGMZlEEn/WQNgGIZxAeq+npRtrAEwDMO4C5JVANYAHMzcjQew9+jpWBeDYZgEQD3aVzQAngfgYAZ//Cf6jl0Y62IwDJOgOLf7ZwEAADh0siTWRWAYJgHw8QEoTuAKgW/+3IF9R8/EpExmsABgGIaJACQbgYpOFOP/vluD2z9eGuMS+cMCgGEYxiaEThhQmewFLjpRHP0CBYAFAMMwTARQnMDvztsCwJlZQVkAMAzD2IWqk1d8AL9uOADAmdFALAAYhmGiQLkDJwSwAGAYhrEJdTZQ8hiBJBzY/7tbADh5ijbDMPEN+fb/rAE4De7/GYbRo/2zs9D/7d/Duoam/0e5AzscW5eEjDec9zgYhnECh06WhDRBVPg4gTUmINYAnAWbgBiGiRYcBeQwnPc4GIaJZ/RSQSg4UAFwuQBw4ANhGCYxSEnSegGch7sFAOsADMOEwLEzpSgpq/DbrjYrJ7MAcDbR0gDY18AwiUXrUTNx92d5psewAGAAONP2xzCJzrLth/Ft3s6IXX/+pkK/bb9vOej5nJLk/O7V+SWMIHYNzK94ZR5embHRcP/w71bbcyOGYSzzt3cX4bFJ0Xv38g8cx7AJKzzf46D/D18AEFEWEc0lonVE9BcRPSBvr01Es4hos/y/VvjFtRe7fABbi07irbn5yB4+DRP/9B9xfLtsly33YRjGuRw9Xebz3S0aQBmAR4QQrQB0AjCUiFoBGA5gjhCiOYA58ndHEQnT/DcRVDkZhokfXOEDEELsFUIslz8fB7AeQCMA/QF8Kh/2KYDrwr2X3bBpnklUjp7Wj1JhIolvj+K6MFAiygbQDsASAPWFEHvlXfsA1Dc4ZwgR5RFRXmGhv1MlkrgpOuf4mVJHrknKRIY2z8zE4E+ctwShm0jSzgRzILYJACKqDuA7AA8KIY6p9wmpp9XtbYUQ44QQuUKI3IyMDLuKYwn3dP9AnzcWoNMLc2JdDEO2Fp3EQQcumRfP/J5/MPBBTMRISXa+ALAlGRwRpULq/L8UQnwvb95PRA2EEHuJqAGAA3bcy05cpABg95HTsS6CLgdPFOOuz/KwYscRVE9Lwdpnese6SAxjC67wAZCU8u5DAOuFEK+pdk0FcJv8+TYAU8K9l+24SAA4lUnLdmHFjiMAgBPFZQGOZhjnoh1QJrvEBHQJgFsAdCeilfLf1QDGALiSiDYD6Cl/dxTqMNCfVu+JYUncSxy8I4xLEELgvz+uw4Z9xwIfbIF48AGEbQISQiyE/9oHCj3CvX4kUUvsV2ZsxDWtG/rsX7b9MAaO+wN/jOiButXTwrpXcVk50lKSw7oGwzCRY/+xYnz0+1ZMX7PX9Dij4BG/rc7v/10+E1j1Wbt4AwCMX1CA0nKBpVsPhX2v3q//FvY1GIaJHGUVUthsINu91dQucdD/u3xFsABeYEWFC2Yhh2XbD+tu33bwlPWCMUwYOHHlqXhAWbPXTACs3HkEZeX68yu0Z8WBBcjlAiDQAfID5PcpclBcjJPii0isPPW/OZvx6qxN2Damr+3Xdgpl8otuNoHrOpN1grW1Hg9t290mIPX6nTr7lW3Hz5SioPBENIrEMGETicXHX521yfZrOo2y8sAaQKLhCgFwqqQMx8+U+m1XRwHpvTKKX2DkD2vR/dX5kSqeq4kHNTkWLNxchM37j4d0brj9f8/X5uPFXzYYXDvx1OGTxWV4bdYmnCktB2CfAIiHtu0KAdBh9BxcOGqm/44AbVnbDsrKK3D3Z3nIHj7NvsIxjA43f7gEV1oMHCg8XozOL8zxCIzyMG2W+QdO4N15W3T3Od0cWl4hcLqkPKhz3pyzGWPnbMbXcibf1GR7ukU9AbDnyGn8uc03qGTX4VM4cqrElnsGiysEgNEEI58oIJ392jjekyXlmLVuv30FixJ2xTUzsWf1riPIP+Brjpy9fj/2Hj2DDxduBRAZH4BCJK9tBw99sxLnPf1LUOecKpH6h5NyP5EUogagrRq9VBxXvjYff3/vD59tXV+ci8temhvSPcPFFQLAiECNWdsMTsbpTNU+byyIdRHCorisHLsOuyeKasZf+zyfizT5kfq99Tt6vqZvjlSac0UEk4A6XQBMXRX6hM5SObonUlk8L2xUEycNtJNjZ2LTt7haAARqy9q5Ae/P11eLnUy45oBIsPdocHmJHpm4Cl1fnIvisuBU+3jlns+XeT6rTQNW7e+RcAJ7yxCp6wq89MuGkP0e4d1b+q9EAUUqhYP6XVSe5S0fLonIvaySUALgurd/x5SVuy0d+/KMDVi584h3g84z1w4EPv1jexiliw2KeusUflm7F51f+BW/yeup6k3A0zJnvZRHUInSiDTHzpR6HILRRjviV3Om1NrQXj1K19rDtxSeQJ7GBv3cT+vwyMRVlq4dKQFw+FQp3pm3BYM+CL1DtOK4zj9wHNnDp2GV+t3XHhdi/x9IQKufy60fSam6F2wuCu1mNpFQAmDlziN44OuVAY+rqBB4e+4W3PflctPjrAwEnB4VEaxDLNKskF+8tXuOWj7HyOxQWl6h21GXllcElVhu56FTGL+gwPO99aiZ6Ds2fLOZEAJDPsvDwiBe8qkrjU0YZRrbzpnScjw1eS1OaMwH6olgD37jXaO2rLwCPV6djwEaG/T4hVvx3XJry5ZaMQHtOXIaf3t3EQ6ftO7YVAZbpQaTrKygdlxX+Iy2vcfM2ygNPKao6lnZHa6yHOh8dd0t2FyEK16ZF94NbSBhBEAwsx9LdBqZ/jyAwBIg0haWo6dL8fbc/JBndxrZHGOFUqfKu7D/WOBFapRfrjVtDHh3EVo+5e/wu/3jpbjgPzMsl+nWj5biuWnrfUbfWwpPWj7fiOKyCsxctx93fPqn4TEb9x33ebb+gw7vBq1tf2LeTny+eDvGztkMwBvWrG4qiwu8o/2xv+YHVf7np69H7nOzfbZZEQDvz9+CZdsPY7IFbVwIgQ37jnk0wVDb+RbNPB11W1FfUUnrohY0Ht+J/EHvrZ+9bj/mbjDPaB9oMLhpv28ZtxaF38bCJWEEQDB2z2ITVbqiQmDmX/sghDDVABYXSB7+cDUAIQSmrtpjOPJ59qd1eHnGRvwaoPEZEStThhW2FZ3EuN8KAh8oV7HQVNGqXfpaRLALoRw7Lc0RsVuZU55pqoFTce3uo+j9xm94V+Vb8j/SWyitBqCUt1SzXfsuTPxzJ6at3uvXSQZi3G8FKDpRjKOnvHNorPTPVsx6nrLl7USfNxZ4TIJGAmbZ9sPYZtBhVlQI9NDM01FfR/15phzF51uX/oJTy12f5WHwJ8aCPND5TiVxBEAQtW/mTPz6z50Y8vkyTMzbadqQB45bDCD8JQXmrD+AYRNW4M3Zm3X3n5Y78NMhduROdAIr7DpszRmsvMCRdG4C9k/cKZV9FidLyrFih3+OKGWRHmU9BAAY9eM6w+tpn6UiV7SPWDuKfvy71Rj61fKQByvF5d62F8w1rBy6drcUolwga1xGzfVv7y7C5QYmEz2hoe7fX5+1yS8ZY6mOP0n5bUtCSP74w4pduDnGDt1QcKUA0HOmKZ39PtkksffoGT8nsB7h9EkHjp/B/RMkP0RB0QlsLTrpN2NZCUkL9PuW7ziMeRu9WkLetkP4cdUexwkApZPdcfAU1u+1Nj/BYwKK8G+xO8RRvSj79e8sCukaQgC9Xp+Pj3/f6olSUVDarLZTNvododaf+jy7H4GAtbKboTcwUG97Z94WbNREF5WZmIDUWEkBc6qkDA99Y82J7jQSRwAEYwIy0QDUoyorI8JwOo0x0zd4hNGJ4nJc8co8j2ahoExL1778Wm54ZxFu/9irog547w/8e8IKv3oJx8kWDr/nF+HxSd6X5Ju8nRg9fb2lc5U6Nsq0Gi52CZhJy3bhyyXeSLFZ661NGjRrZxVCsh0/8+M6HQ3A15+i/NcLN5S2WyqOH+roqxHfr8YBC34bwJp2rK1y7et0/ExpwPBfvecW6L3U0wD05k9st5DF96898TvRMmEEgBXn0c5Dp/DG7E1YZzDyXLfnGIrlUdvYOZv9oisiyQl55K9tTF4NwPrbO2yCN/JDWy/NR/4cNa3g27ydyB4+DadKynDT+CWYmLcrpAg75V2+94tluvuLy8ptEWzh1suj367CyB/Wer4/NXmtydHWtMcKnw7cyAQkbZ+ycg+yh0/Dz2v3QY9QByvq+874az9G/fiX6fHBmNI8wstjh/ct44WjZmLAu39oT/Nw7EypvgAI8Cz12stOvcmGhIBzE6pVit+kygkjALSNoPB4sd+Du+XDJXhj9mbdUNHjZ0px9dgFPqFkk01C8hSCfacmr9iNZk9Ml5yzqhfFaISfnJRkul8P9WxIvZdDafyLCw7inx8sNsxvHi5vzZWiTg4cM45tDxX1BKkWT/6Ca/+3MORrKaPk8gqBHRZGfBUVwse8EzrSfc3Si4ye5tWStG3Au16F9F2Jbnt5xkbNHSTUnV4wwk7rfC46UYKN+wJP2LLiL7Bivlqz28jZX4TWo2ZivuxAVrPniL+WovhcAK8zWCqD9F/PJ0VAwLkJaanx243Gb8k1KKYOZfTR9cVf/ZJpHT7lnxFUYX+InZTWhmnGU5PX4sFvVqK8QmBr0UmfMFM9lRTwagCKsyxY9Exjykv24NcrsWjLQRSaTD6qqBBhLzCiPttsohMghUU++PWKgELpxV82+nzfYKFDCkRZhcBlL8/12y6EwBeLt3tSgQz7egXOffLnsO+n5tyR+tdbmO+dQ6DttIN1WqsnHR04bs2MA/gLnqVbD6H3G/ascKdtnhVC8l8ZCY8Dx854opLytkkmwfkb/QXAfV/6a4vbNVFEa3YdxQcWotACtVmHTwUyJWEEgDJIUd6JYp0RWiQmbQXT8Xy+2Gsffn76ep8XWM/OefBEMQqPS41vwtIdAKQXd+hXyy1PdNKzHCkdidrfkT18Gp6RVfsHvl7hyXh69dgFuGCUcUz9ml1Hsf2geTyzut4n5plPOBo2YQUmr9yD/ADON736CleTMRJ0S7cewpOT1+LpKVL9/LTafM3YQBSdKEb28Gm49wvvRMSS8oqA7VM7Ere06LjBJbu+KAk6tVDJHj7Nx4ehME+ngzXD6kIoQgiPVqL+6QPe+wOTV+7WDfvs8PwcdH3xV59t3y7zb1N674e2Kq59ayFGT19vOogLFNJaVl5hmJspHkgYAaCMdLUvxc5DXpXe7u5/2IQVuCHE6I4Fm4t8XpMCnYlHHZ+fg1/+8rXn/m9OPqat3ovvLc7cLDzhP9JTtAmlcSupAT7+fRuEED6zJDfsO45TJpPJrn1rIbq9PM/TeZ0qKcPEvJ3SPAr5GLvrvaDwBL5f7j/J6H8mE50OnyxB9vBpeHLyGr99SvkKNB2OMotaaVu7j5zSnVdxqqTMMEZdD6Pw10DORG1nbSXw4bjBQEFJm/zzWl9hpvZhKIz5WT/FghX2HDntMZfd+cmfeO4nb5jrR79vw/crpOf45hzfMOilWw8bhn0qv8msby464T8L2ai6zMyrgUSZ3kAznkgcAVDuawJSuFSVZtVuBSCczIMAsEwnNhyAJ92vXsOsUikZAEw7ZTUva0wlADDog8WYsnI3ZPeCj09E3QkFM5t2/IKtOFVShqcm/4XHJ61GzojpnpBa7SQdM5RwvUMnSnQnLuVtO+RjFlGz89Ap3ZHfDyt2od2zswAAXyzegS8Wb0fb/86EEAL5B07giGxSUCdhA4A3Zm/Cws1FqJIq1fnp0gp8odLiFI3j9o/+9OmsjEwGx86UYuZf+g5aALgmgB9DawIKt/M57+lfPGYUO1HewVMl5egy5lc8+u0qfLpoG+ZsOIDxC7fiH+//gdW7jmDyCuOZworGa0awM2mNnOBmE0MDKVlOz44aiPh1X2vw+ABMZLbT8vbojfoBaUWmguev9tteXiE8ndGpknJsP3gSL83YiMz0Kp5jtCq80S82ypmk7oS0nembszdj/MICrBnV2++80dPX+4V1Wk1epsc/x0uOtxkPXuazfcB7fxjOz1iy9RB6aoTN0K+WY5rGZPOkHJ3zwYICv+n5at7/rQDv/1aAqfdfAgA4XVLm46spKa/AwZMlWKpJrpb73GzMfMi33IDkc/l1wwG8ObCt4T3N8PMBhHQVX35aHfog5tDJEtSuVslwv6ItTV21x2ewtHTrIdzz+TLsPWrdD6Flw75j+MFEgOhh1FmbTbIMZM5y2jybYEkcDUB5ECbPK54eld4o90RxmUcDOFNajm4vz8O01XvxvsqRpVXhw3nJ1Dz67Sq8PnsTjp8pw4niMrw5e3PEoofU6Dkbjd653UdOe7QOQBL42s5fzaszN6FJ7aoBy6BoYlqBVlom8PBEfUH6m05kijJiDTVu/LFJq32+/ximBgrom0qs0ut1Sdj+ue2Qz0xn5RWcYaLthNsu7/wkL+hzjDrrgyZJ64jMtYC2/50VdDmcRMJoAEqERklZBUZN1Y9Tjid1TUkXq+buz/I8yayineZ5ksrRNnraekxYugPN6lWLahmCJdDgrLiswtJi50rHUVZe4ZO8rri83DAcVM88owgAS/mPdNCaPEJJWWAnivBQVrjaNqavz347EuoBUgesfXXVIZ1WMRoM6KWG9txb/oufniM4Iq4BEFEfItpIRPlENDxS91Enavpk0TbdY8IxSTiBpaoX/ujp2OX5V1bnshILHkvsEvgvyKatsgrh07Y+XLAV1dP0x1Dx7hy0iloLVHwfdudUql+jsi3X+T5IkxEgzWWJcyuPKREVAESUDOBtAFcBaAVgEBG1isS9DgWRezwRKDpu/+Qqy/eWR35mUTdOwK6Z3MvlZG0HNHX+/m8FqF45VfecxVuCy0gar6idtQ99E3gtjlDYZzH1RCRYlODPMdImoA4A8oUQBQBARF8D6A/AOOVhCISiDsY7fxTErmFaTeIWa5TIn0hiZIfXOoYTld2qGbcLNhd55o8wwbPr8Clk1grsk7KTSJuAGgHYqfq+S95mK1ttsjUyDBMc78XhOtlO5YvFgUNf7SbmUUBENISI8ogor7AwuBmHCiXlzl30JJpUSon542QYJkSspJ+3/Z4Rvv5uAFmq75nyNg9CiHFCiFwhRG5GRkZIN+nesr5fBIIb6demYayLYJmmGc6OIGLsIzU5Bj1bHJIcAwkQaQHwJ4DmRJRDRJUADAQwNcL3tIVLm9e17Vq9z69vy3WuDdDBJ9sQflEp2f4mcUULf8FuNAnOiPaN0+0qTtwz8urzYl0EP7LrSLbrb+/t7Lfv0V4tol2csOiQXTsm9w1mKU27iKgAEEKUAbgfwAwA6wFMFEKYJxN3CPXPsif0DABSkpKw4PEr0KROYAfP2EHtdLf/ObInXv17G9NzAy2cYYVNo68y3Z/bpBamDesa1DXtaNiP9m6Bv57pjR/u6xL2tSJJvRpptlznylbGg4Zww1uzantnjnc9J/yBzqO9zvXEyZ+lExWVGoFBRSR5pv/5YV+jmjxhMxgS0QQEIcR0IcS5QohmQojRkb6fXaTY+TQIyKpdFc3r1fDbNfGezhh8Sbbne4OalVGziv9LlFEjLaCN31J2yCC4oV0jPKt5GT68/eKgVNVPBl8cdMqCJ/vqj3CrpaWgXeNaQV2rc9M6qGEQq2/Gw1eeG/Q5ANDr/Pro3LROwOPqVjdOoQAAz19/oeE+s7h0tXBupEoRoiY1yduOvriro2k5AnFd24a4v3tzvH5jW3Q7N8PPtNc2Kx03dWqMhf93Bd64MbQUGNHGjveofs3gB5DHYjC3J75EcxSx0x6nXElPqHTIqY3/XHu+z7GhjvCeMOg4rbDq6V5Y9XQvAMD393XBnEe64bUb2+KWztlY9mRPz3E1q6R6fkdV1SjnknP8O70Nz/bB5S3q+c2ibHm2vyBUoyfosgzC40Zc1RKtGpyle+07u+ZgwpBO+OOJHqb306NmlVSffD5jbvB2yOfUq254XklZBXKzAwuphgads4JZ3iqz9lEjzTt4+GGovraUYqNNfq2c1qJ941r49I4OSE1Owv8GtUMDuQN8tFcLpKUkI7NWVXQ7V9/H19hCOg4117VtaGiqPE/VFqygp3FrX9P7rzgnqGsCoc1BUS9yFC1YABhgpgHUkRNgqUfuVtAOLJrrdCREFNS884n3eG2udaun4fE++vZWtdqvUFm1klHNqqmoWVXqPNo3roVmGd6y1amehjRVp6yMkDJqpOH1G9vgh/u6IC3FX+WtLCeu02Y1zQrwwuuZDPTO2TamL+7p1gzTH7jUs+3nBy7F8KtaAvAK8eppKXj2ugt8zu3ftiHyR1+FKUMvwbAezf2unZxEOLe+V5ikV/WO2F8e0Nrz+YZ2jdAmy+ufKC0XyK4T2ME9/rZc8wNM+uje55/t8/1D1bWqpXmfQ1qy9/P5Dc/ydJpDLXZo/+zYOOAxSuZaNde2aegxd6pfIz3Bc3Onxvjx38GZFO/vfg5aZ9bU3Verqv7EPCPOre//DiZp3v1IpZC5q2uOz/dEdALHBD1HVLAkJxlXjbL03n2Xm79InZpKziTSLN6toKdqJpF5g9OaJjrk1MbiET3wvWwbN1JfU3R+zwe3BuiEVCwe0QNL5JG08nuSiHB9u0y0a1zLkxLhsd7+AkibNI5gni4gkCP6q7s74vUb9f0hRKRa8MZ7E+3tnr6mFVKSk9AmKx03qzq6G3OloDXtACBd1bG0yfR2+IMvyUFXlfYz+JJs3NC+Ee6+1PflBoDR13uFUD2T9AY9WtYz3a/VQC5s5O0Mq1f2mrvUmtR3/+qCTaOvwrYxfU2jxf6rMvmlWQgrNjJleZqwWgCo2qDSXs5rcJauydOMOtXSfDrp+y5v5vkczNKpgP5gQ/sOhZIKwuyUpnWlAcI/Ls7yeRZ2amZWSUgBkFnLXL22gtHDaJpRzZM/vKqJo6djTm0M6iB1LMqVtB27XidIRKYNbliP5tg2pi9W/cdrsjm7ZmW0l23jRk1Ib3BxaXPrYbe1qlXyOMaFJ/W2l2f7X4Cnr2mFe7s18ztXbwFus4il1AAdT5dmdXF9u0yfbU9f0wpThkppm5WVvdTvtvalrlPd66xVj7wyZCeuNs1xpZQkjLz6PLTJrOnT+aQkE5Sf91jvFmidmQ4iwsi+rfxCkxWh8o9c37JruUenDhUuaCSZOLo08wqdCgH0kbUCtSamDr9UtDHA3ymvHjXf2jnbtGw5dYML31WnU1bXszaizUjj1nuXa4AIZqEAABXWSURBVFZJ9WnPd6pG0tqMn1VUv3tYd/8Bm95gQ1uUUPyBZkqDkro+NTnJRxuz24dnhYQUAPVrVMbU+y/B2md64wWV7TbbQhSOwsCLs3S3j7vlInSTwxrVjUtvVKWYAi5qInXO2o5dLzqGAPSUI0BGyKYMPWpW8Zps1CiN6G/tM3W3A8B7N1+EWTr56q3iGdypil+zairu6Jqjq8Zq1zsOlGI3NYQX7o6uOR5TjPKCqbU49Xs+55FuPucqI1MiScC+ObCtXxROMhHuvqwpptzva65ITSaPYA+kwht1Cs+pzFOXNq+LDjn6YYjP9DvfY/L7ePDFnhG6gMDYQe08vppfHrwU4265CCkWo2/KDNaj1pKcRH4dt9GIW6+NKAIpt0ktaMfIt3Ru4neNb4Z0wrR/e817z113ARaP6IGkJMJNHb3Hq+u9UXoVH8E3/7HLPZ8f7tXCY771limwBhBKv6xdFKitykyotJckAlqofFYsAGwiKYnQOjMd1dNSfEY3VmyaCmZhoP8b1A4LHr/CZyT4TD/faBkBoE1WOuY/djlu9TRu6cF3lF9wvcedk1ENr/y9NRYN7246EjSifROpoWnnMagbV58LzkZz2b49dlA7vHfzRUHdw6MBWGyw2rVsAfOFNrQ22GBRRoHqkZv6fjkaG70iJwjSSL9/20ae31ZDNqkYvZypyUkejcOs2Gonsva3q00gH99+sd+5datXwsR7OuO2LtmoWkkqT1pKMsbflos2mTVRt7oUIaZoNS3PPgu9NH4CM0r1Fo7WQQjhJ8UMF0TRWZ6DiDBtWFd8PNj7G5W60GsPHZvW8RnkdGpaB2fLzmW1IFK3w+dvuBCbR3sXU6pbPQ03tGuEz+7o4HNtpW3otU1t+7Nj0Re1OU25ZSxs/loSUgD44lvJb/+zvaWzjF74BjWroHJqsp9TspZ2ZSS5zTSpU83PB9BRDhPUmuWrVkrGWZVTkZaSHDBKxIiLmtTG2md6e7QIb/n07az92jREnwusdxaA5JBtllENo661Fi99XVsp/ZMyMiOQqX053AltykpU6ntc3bqB57P2BfdqADr3VToygyKlJCfpahxaaqji47WLkCuRSyOuaqk7ah9wUZauVnBp8wxMub9r2HH2Lw8wnl/yYE+vg7xC+GuxFYYagP728xvW9KkLBW39qjvHc+pVR8uzaxhGX6kfpzY9d1IS4bUb2+IyTQTSJ4M74KaOjdGwpv97pu2XG9euitf+4a2jULIOqP0x5RXWNMZokFAC4Lt/dcEjGiepumEJAdQ7y/pEHW142rYxfVHNJKZczwGqpkJjO1cLmUXDu2PR8O6Wy2ZG9bQUv0b8SoBJZMGQlpKMOY9cjq4WZ0vf2TUHG5/rgzcHSiF3RMA7N7c3nG2dHKYzTFkvWe2jqZ6Wgtu7ZKPvhQ38jrfyImqPUWzHqUnk9TmYXMZMpjWvXwMLHr8Cd1/aVHf/I71Cm5OgYBR+qWA2w/zBnud6lsQE/P1YFzTSj8YRHsGp/8P9AyJ8v5/f0BvOOfvhbvjlQWOTZSimkxZn18Do6y/U1Ta117vx4qywJ4amJBGe7Hsevr23s2fAoL2PkdCMJAmzIhgg2doVe7uC9vFabSoCAtMfuBRFx4t9Fvw2o1WAGGQ/H4Dqc6gjfiO0jcts7dZIQ0RIS0lWdQrS6PXS5hkY+uVyTFvju1JTbTnk8oJGZ+HGixsjI8CkKS2nPQLAt3mP6qevsSid+5Xn+c++VR6Ztj6rV06R1qAg78g/kPPaGxgjXevebs08i8SbhcaGMylxw7N9gj6/74UNfJ6JWvh1Pacu3pknZQC9qEktfBAgnDVQ36zsVwuKejXS8OngDgZnBH+PYBjW/Ry/6xFR2KP15KQk3CULeEXD9RMAMVh4JqEEgB7qEbtA4Mby94sykZxEqJKaDCJC9bQULH2ihyXJcUXLeqp7+T9Nofkfydwf2kvHwsGkRVHhu57jHZG+fVN7TNPkkFc0r8vPrYdbOvk7BwNxUl4u0yxKS01yEmHR8O6ooyNohMe847v98d4tMPz7NTircioevLI5kggYcJF5dI+W4Ve19MxZMCOcdqKO/rFKu8bphgKgiyp1RLusdN3UD4Ba2AVP52Z1/E2qOjRKr2LLWiDf39cFN7yzCABwect6Pv6Ie7pJnXa4mQHU539+ZwdMXrk74GzwaJBQJiA9ujSr42MXbJOZjkEdGmPuo5frHt+2cTrG/K2174jkrMqGcdkXW5j1qXCtbIduJk+Xj2SfbEckQ6jUrJKq23G3OLsGlj3ZE4M66EdYKdSqVgnLn7oSD4WYjuH2LlJYYG4QSb0aplfRncxmJKwHdmiMbWP6onKq5Ld58ppWuucrpCYneboVq8/ih/u66E5SizZan8z/9QkstLyBAkb7fb9frHpWVn2uXw/phGf7n++n6QVL+8a1fCbzKX117WqVMOIqaXa9IgRDfY/UQrR5/Rp4rHdLvzYVi5UnE14DICLc1LEx3v+tAEJITjt1aKiWYB3+X9zVUXetYT117u+5Wbi+XSPsPCyNWtplBZfXJhj8BEBIY7HQWPWfXob71PH3CrMf7oaer8332RaOyapzszq2pQdXnmO4jukeLeuhpLwCy3ccDugrUmjXuFbQuY8igb/TXA5qMDnHO+nLvN6UvVe2qo9R17bCqB/XWZ55m1W7Km4JMG8hWAjed0ddDuX3BDLzGnGThQhENgFFiiDeXbMcLHqkpSSbjvy0pCQnIaduNUwb1tUn1YARy5+6MqTOR6uxOiDgwBCz3DqxRjHlhWtCS0oiVE5KxksmETdORdv+rFTF6wPb4qOFW9Euy3oa7wxZyzaKLAqGQR2yUFxmLbxVi/L71OVQ0qaYBYGY0cWGrKuRIOFNQGq0dvmlI/2ThNklhQNd5vyGNS2F79WuVkl3wlcgtOplLHKNJxImEZ4JhzIJTvFphOIAbZReBU9d0yqoOR3KoXbk3nnhhtZ47R/+2UetvAaesG3VtnPqVceTfc/DWzrJ49oGIeT08KYI4SigiGBk/tCz69sx6cOJOFkDiAec4ESPNIrzvUmdaj4mNKNO3O4kaeQxvdh6WR9anF0DRfkHTfNNKY9a/fOIyBPFo8VKziQzlP6JTUARxkoFRyrzX6xhDSA0lOaQ6AJg43N9DH+j1gSkaK52D5YUTSNYMywgOYStrIn97s0XYe2uo6ZatSIczmsQ2EQLSClflmw9ZK2gOsSyablKAFghXGmuEEojZpyHZx5AiM3i0zs6oLJNbcpOkgi4RGWXNvNjaX+7ohEEm3lTTVU5bXWaKiW5knajrk6gQCA6WViEB5BWLNOzx3dpVgerdh5B3eppqJyajG+GdEJLiw7fUf3Ox5bCE8jbfjioMmthDSBCmElY9aSXh3qei4EdrOcLMsMJ3f+aUb2w58gZHNQkpmKCIEwNINAs3FhR8IL1KCmtBqBEAZVbTCKnx6O9WqBW1Uq4trV3FnLHnNp49e9tcNWFwaUmsYNHe7XAwIuzPBPyOloUKABQpVIy+rVt6CMABl6chTZZ6Rjx/ZqA5yu1G4uZwM4bmkQZtX3zgZ7Nw86r8pJqsZBYU6NyKlqcXcOxEQjxgPJShhsGGs9oncApNmgA1dJSMKxHc5/cR0SEv12UGXZcfygkJxGaWFjIxyq1qlXypIMPhNLnWDFh2Y07NACTfXavwaCspMUWoMTALT4AM/zmAcgvTbnFLKJuJJj3v1/bhth84ATuuyL47L/h4goBoKBnlw839bAWF/cTCY2bwkC1aLUfJfdRaYJGzNlBMMEkqclJllKCRAJXNGuzTtnNqj0TGKNkcG7CyAQUjg8g0dD293ZMZosGrhAACnpCOVI5uePj8TOBULRGNwsA7W9PtsEHkCj859pWAPytC/FSM64QAGZ5cMLN8+1/Lxl2AoTE+CAWqo8mrjYBGWkA7APA4EtydLfHy3wiVzVrvUdyv85C0eHAE67CQ7uSWaxhE5D/LPLOzeqgc9M6eOLq82JToDhA6f/nPno5JtzdKbaFMcEVTmDTBcjDDPs0wony/9z61YPOWe927MoGGs9oBzVVK6VgwhDndmqxpOs5dbEwvwjXyKnfc+pWQ05d+8JL7SYsAUBELwO4FkAJgC0ABgshjsj7RgC4E0A5gGFCiBlhljVs4kQrixgzH+oW6yLEHe/d3B7jF2zl6C7GFKVraZZRDV/c1TGmZQmGcIe/swBcIIRoDWATgBEAQEStAAwEcD6APgDeIaLglyayCX53mVDpc0EDTPpXFzbtwbt4PeNPoDWQnUpYGoAQYqbq62IAA+TP/QF8LYQoBrCViPIBdADwRzj3C5doTLX2TOt2ubbBJBazH74M9WwOmGBij50G8DsA/Cx/bgRgp2rfLnmbH0Q0hIjyiCivsLDQxuJ4ublTE7TJSsc/bcrzY0acDQAYxhLn1KthuP4vE78E1ACIaDYAvexMI4UQU+RjRgIoA/BlsAUQQowDMA4AcnNzIzJurndWZUwZekkkLm1ILBI7MQwTHX4f3j0hJsIFFABCiJ5m+4nodgDXAOghvLMhdgNQr/ydKW9LeGK5uAPDMNGhUXoVn+/x+rqHZQIioj4AHgfQTwhxSrVrKoCBRJRGRDkAmgNYGs694gU2ATGMe4m39z/ceQBvAUgDMEv2fi8WQtwrhPiLiCYCWAfJNDRUCFEe5r0YhmEcSbwuABVuFJDhNFohxGgAo8O5fjwTp+2BYZgwMEs740RclQoiGjSUbYM845ZhGKfjilQQ0aR2tUooeP7quLMFMgzjPlgARAC7F5lhGIaJBGwCYhiGsYl40/xZADAMw4RJvAZ9sABgGIaxiThTAFgAMAzDuBUWAAzDMGESr7m/WAAwDMPYBDuBGYZhmLiABQDDMEyYcBQQwzCMy4m3JSFZADAMw4RJnCoALAAYhmHsIr7G/ywAGIZhXAsLAIZhGJfCAoBhGCZMUuQMwCnJ8WUE4nTQDMMwYXJzpybYf+wMhl5huEiiI2EBIJMaZ5KbYRjnUDk1GSP7top1MYKGBQCA34d3R5XU5FgXg2EYJqqwAADQSF7Hl2EYxk2wE5hhGMalsABgGIZxKSwAGIZhXAoLAIZhGJfCAoBhGMal2CIAiOgRIhJEVFf+TkQ0lojyiWg1EbW34z4MwzCMfYQtAIgoC0AvADtUm68C0Fz+GwLg3XDvwzAMw9iLHRrA6wAeh29K7P4APhMSiwGkE1EDG+7FMAzD2ERYAoCI+gPYLYRYpdnVCMBO1fdd8ja9awwhojwiyissLAynOAzDMEwQBJwJTESzAZyts2skgCcgmX9CRggxDsA4AMjNzY3XhXUYhmHijoACQAjRU287EV0IIAfAKnkdzEwAy4moA4DdALJUh2fK2xiGYRiHELIJSAixRghRTwiRLYTIhmTmaS+E2AdgKoBb5WigTgCOCiH22lNkhmEYxg4ilQxuOoCrAeQDOAVgcITuwzAMw4SIbQJA1gKUzwLAULuuzTAMw9gPzwRmGIZxKbweAOMIvrq7I/YfOxPrYjCMq2ABwDiCLs3qxroIDOM62ATEMAzjUlgAMAzDuBQWAAzDMC6FBQDDMIxLYQHAMAzjUlgAMAzDuBQWAAzDMC6FBQDDMIxLISltjzMgokIA20M8vS6AIhuLEw24zNGByxwduMzRQa/MTYQQGcFeyFECIByIKE8IkRvrcgQDlzk6cJmjA5c5OthZZjYBMQzDuBQWAAzDMC4lkQTAuFgXIAS4zNGByxwduMzRwbYyJ4wPgGEYhgmORNIAGIZhmCBgAcAwDONSEkIAEFEfItpIRPlENDzW5VEgoiwimktE64joLyJ6QN5em4hmEdFm+X8teTsR0Vj5d6wmovYxKncyEa0gop/k7zlEtEQu1zdEVEneniZ/z5f3Z8eovOlENImINhDReiLqHAd1/JDcJtYS0QQiquy0eiaij4joABGtVW0Lul6J6Db5+M1EdFsMyvyy3DZWE9EPRJSu2jdCLvNGIuqt2h61PkWvzKp9jxCRIKK68nd761kIEdd/AJIBbAHQFEAlAKsAtIp1ueSyNQDQXv5cA8AmAK0AvARguLx9OIAX5c9XA/gZAAHoBGBJjMr9MICvAPwkf58IYKD8+T0A/5I/3wfgPfnzQADfxKi8nwK4S/5cCUC6k+sYQCMAWwFUUdXv7U6rZwCXAWgPYK1qW1D1CqA2gAL5fy35c60ol7kXgBT584uqMreS+4s0ADlyP5Ic7T5Fr8zy9iwAMyBNjq0biXqOasOPUOV1BjBD9X0EgBGxLpdBWacAuBLARgAN5G0NAGyUP78PYJDqeM9xUSxjJoA5ALoD+EluaEWqF8hT33Lj7Cx/TpGPoyiXt6bcmZJmu5PruBGAnfLLmiLXc28n1jOAbE1nGlS9AhgE4H3Vdp/jolFmzb7rAXwpf/bpK5R6jkWfoldmAJMAtAGwDV4BYGs9J4IJSHmZFHbJ2xyFrLa3A7AEQH0hxF551z4A9eXPTvgtbwB4HECF/L0OgCNCiDKdMnnKK+8/Kh8fTXIAFAL4WDZbjSeianBwHQshdgN4BcAOAHsh1dsyOLueFYKt15jXt4Y7II2gAQeXmYj6A9gthFil2WVrmRNBADgeIqoO4DsADwohjqn3CUlcOyIWl4iuAXBACLEs1mUJghRI6vO7Qoh2AE5CMk14cFIdA4BsN+8PSXg1BFANQJ+YFioEnFavgSCikQDKAHwZ67KYQURVATwB4OlI3ysRBMBuSLYyhUx5myMgolRInf+XQojv5c37iaiBvL8BgAPy9lj/lksA9COibQC+hmQGehNAOhGl6JTJU155f00AB6NYXkAa6ewSQiyRv0+CJBCcWscA0BPAViFEoRCiFMD3kOreyfWsEGy9OqG+QUS3A7gGwE2y4AKcW+ZmkAYHq+R3MRPAciI626RsIZU5EQTAnwCayxEUlSA5yabGuEwAJI89gA8BrBdCvKbaNRWA4qW/DZJvQNl+q+zp7wTgqErdjjhCiBFCiEwhRDakevxVCHETgLkABhiUV/kdA+TjozoiFELsA7CTiFrIm3oAWAeH1rHMDgCdiKiq3EaUMju2nlUEW68zAPQiolqy5tNL3hY1iKgPJLNmPyHEKdWuqQAGylFWOQCaA1iKGPcpQog1Qoh6Qohs+V3cBSmYZB/srudIOjai9QfJM74Jkud+ZKzLoypXV0gq8moAK+W/qyHZb+cA2AxgNoDa8vEE4G35d6wBkBvDsl8ObxRQU0gvRj6AbwGkydsry9/z5f1NY1TWtgDy5HqeDCkKwtF1DOAZABsArAXwOaRIFEfVM4AJkHwUpXIndGco9QrJ7p4v/w2OQZnzIdnHlXfwPdXxI+UybwRwlWp71PoUvTJr9m+D1wlsaz1zKgiGYRiXkggmIIZhGCYEWAAwDMO4FBYADMMwLoUFAMMwjEthAcAwDONSWAAwDMO4FBYADMMwLuX/Ab5ab97rYd15AAAAAElFTkSuQmCC\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"9zdADU2kHB41","executionInfo":{"status":"ok","timestamp":1630393982505,"user_tz":-330,"elapsed":2,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"9fb91cce-e3ca-43e6-a3a9-0b6346b270b6"},"source":["#create new dataframe with 'Open column'\n","data = df.filter(['Open'])\n","\n","#converting the dataframe into numpy arrays\n","dataset = data.values\n","\n","#Getting the number of rows to train the model\n","#taking 70 percent of the data(since we multiplied by 0.7) [training data set]\n","training_data_len = math.ceil(len(dataset)* .7)\n","training_data_len"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["950"]},"metadata":{},"execution_count":13}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"TB3c1KPCHDf-","executionInfo":{"status":"ok","timestamp":1630393984002,"user_tz":-330,"elapsed":2,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"7da14b09-6194-4e82-ed46-134cab69adff"},"source":["#scale the data\n","scaler = MinMaxScaler(feature_range=(0,1))\n","scaled_data = scaler.fit_transform(dataset)\n","scaled_data"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([[4.48781789e-01],\n","       [4.46247555e-01],\n","       [4.46173454e-01],\n","       ...,\n","       [3.26041852e-04],\n","       [7.41004209e-04],\n","       [7.41004209e-04]])"]},"metadata":{},"execution_count":14}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Xel5BEZaHFgN","executionInfo":{"status":"ok","timestamp":1630393985370,"user_tz":-330,"elapsed":2,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"b434cb53-44c0-4de8-9687-26ae85c45588"},"source":["#creating training data set\n","#creating the scaled training data set\n","train_data = scaled_data[0:training_data_len , :]\n","#split the data into x_train and y_train\n","x_train = []\n","y_train = []\n","\n","for i in range(60 , len(train_data)):\n","    x_train.append(train_data[i-60:i , 0])\n","    y_train.append(train_data[i,0])\n","    if i<=61:\n","        print(x_train)\n","        print(y_train)\n","        print()"],"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[array([0.44878179, 0.44624755, 0.44617345, 0.44077894, 0.4327761 ,\n","       0.43213883, 0.38991641, 0.41346553, 0.44559547, 0.44289822,\n","       0.44666252, 0.4655433 , 0.45645859, 0.45567313, 0.46632877,\n","       0.47486514, 0.46621021, 0.46724761, 0.45798506, 0.48337187,\n","       0.47204932, 0.44537317, 0.45407256, 0.44128283, 0.42367657,\n","       0.42407671, 0.44719604, 0.44221649, 0.42735195, 0.4288636 ,\n","       0.41193906, 0.41445847, 0.45509514, 0.43665896, 0.38529255,\n","       0.40061652, 0.50032604, 0.49300492, 0.49679886, 0.5204369 ,\n","       0.51225621, 0.54134803, 0.54625348, 0.53995495, 0.50650602,\n","       0.5099591 , 0.51865849, 0.55433043, 0.52025906, 0.52842492,\n","       0.58056198, 0.57590847, 0.57678286, 0.63278795, 0.59226984,\n","       0.53485684, 0.52187444, 0.48033375, 0.44952279, 0.485832  ])]\n","[0.5458237002786176]\n","\n","[array([0.44878179, 0.44624755, 0.44617345, 0.44077894, 0.4327761 ,\n","       0.43213883, 0.38991641, 0.41346553, 0.44559547, 0.44289822,\n","       0.44666252, 0.4655433 , 0.45645859, 0.45567313, 0.46632877,\n","       0.47486514, 0.46621021, 0.46724761, 0.45798506, 0.48337187,\n","       0.47204932, 0.44537317, 0.45407256, 0.44128283, 0.42367657,\n","       0.42407671, 0.44719604, 0.44221649, 0.42735195, 0.4288636 ,\n","       0.41193906, 0.41445847, 0.45509514, 0.43665896, 0.38529255,\n","       0.40061652, 0.50032604, 0.49300492, 0.49679886, 0.5204369 ,\n","       0.51225621, 0.54134803, 0.54625348, 0.53995495, 0.50650602,\n","       0.5099591 , 0.51865849, 0.55433043, 0.52025906, 0.52842492,\n","       0.58056198, 0.57590847, 0.57678286, 0.63278795, 0.59226984,\n","       0.53485684, 0.52187444, 0.48033375, 0.44952279, 0.485832  ]), array([0.44624755, 0.44617345, 0.44077894, 0.4327761 , 0.43213883,\n","       0.38991641, 0.41346553, 0.44559547, 0.44289822, 0.44666252,\n","       0.4655433 , 0.45645859, 0.45567313, 0.46632877, 0.47486514,\n","       0.46621021, 0.46724761, 0.45798506, 0.48337187, 0.47204932,\n","       0.44537317, 0.45407256, 0.44128283, 0.42367657, 0.42407671,\n","       0.44719604, 0.44221649, 0.42735195, 0.4288636 , 0.41193906,\n","       0.41445847, 0.45509514, 0.43665896, 0.38529255, 0.40061652,\n","       0.50032604, 0.49300492, 0.49679886, 0.5204369 , 0.51225621,\n","       0.54134803, 0.54625348, 0.53995495, 0.50650602, 0.5099591 ,\n","       0.51865849, 0.55433043, 0.52025906, 0.52842492, 0.58056198,\n","       0.57590847, 0.57678286, 0.63278795, 0.59226984, 0.53485684,\n","       0.52187444, 0.48033375, 0.44952279, 0.485832  , 0.5458237 ])]\n","[0.5458237002786176, 0.5597693994901891]\n","\n"]}]},{"cell_type":"code","metadata":{"id":"tuLQpGZlHHbZ"},"source":["#convert the x_train and y_train to numpy arrays\n","x_train, y_train = np.array(x_train), np.array(y_train)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3r1mCsHIICdw","executionInfo":{"status":"ok","timestamp":1630400172858,"user_tz":-330,"elapsed":577,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"2fdfab27-1a4c-4b4a-bbaf-9e13694ca6be"},"source":["#Reshape the data since lsdm models expects input to be 3 dimensional\n","x_train = np.reshape(x_train , (x_train.shape[0] , x_train.shape[1] , 1)) \n","x_train.shape"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(890, 60, 1)"]},"metadata":{},"execution_count":45}]},{"cell_type":"code","metadata":{"id":"TrcDyxkDIFHD"},"source":["#Build the LSTM(Long Short Term Model) model\n","model = Sequential()\n","model.add(LSTM(units=50, return_sequences=True, input_shape=(x_train.shape[1], 1))) #adding a lstm layer\n","model.add(LSTM(units=50, return_sequences=True)) #adding another lstm layer\n","model.add(LSTM(units=50,  return_sequences=False)) #returning sequence as false because we dont want to create any more layers\n","model.add(Dense(units=25))  #making another layer having 25 neurons\n","model.add(Dense(units=1))   #prediction of the next closing value"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"Hjes4LDfIIiN"},"source":[""],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EsznX_YbILJw","executionInfo":{"status":"ok","timestamp":1630403769373,"user_tz":-330,"elapsed":45078,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"88a1f422-ac00-4d3d-d0c2-54735d9bccb1"},"source":["#compile the model\n","model.compile(optimizer= 'adam' , loss='mean_squared_error')\n","\n","#train the model\n","model.fit(x_train , y_train , batch_size=2 , epochs=2)"],"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/2\n","445/445 [==============================] - 24s 46ms/step - loss: 3.9442e-04\n","Epoch 2/2\n","445/445 [==============================] - 21s 47ms/step - loss: 3.4654e-04\n"]},{"output_type":"execute_result","data":{"text/plain":["<keras.callbacks.History at 0x7f1c102c0850>"]},"metadata":{},"execution_count":95}]},{"cell_type":"code","metadata":{"id":"zNZPCJ6wIXXI"},"source":["#create the training data set\n","test_data = scaled_data[training_data_len - 60: , :]\n","#create the data sets x_tests and y_tests\n","x_test = []\n","y_test = dataset[training_data_len:, :] # we want our model to predict the values of y_test\n","for i in range(60, len(test_data)):  \n","    x_test.append(test_data[i-60:i, 0])\n","   "],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"xE-y25-DIbgR"},"source":["#convert the data to a numpy aray\n","x_test = np.array(x_test)"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"nz-k2PqWIuw9"},"source":["#reshape the data since we want 3-dimensional inputs\n","x_test = np.reshape(x_test, (x_test.shape[0] , x_test.shape[1] , 1))"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"id":"xlQoHNggK5DQ"},"source":["#get the models predicted price values\n","predictions = model.predict(x_test)\n","predictions = scaler.inverse_transform(predictions) # here we are unscaling the values"],"execution_count":null,"outputs":[]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Q_4PO4XhLfa1","executionInfo":{"status":"ok","timestamp":1630403787302,"user_tz":-330,"elapsed":5,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"3d40cea3-df2f-458a-ed54-b5f9fc97b4ae"},"source":["#get the root mean squared error(RMSE)\n","rmse = np.sqrt(np.mean(predictions - y_test)**2)\n","rmse"],"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1.0933326439541153"]},"metadata":{},"execution_count":100}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":622},"id":"EdOr3156LycM","executionInfo":{"status":"ok","timestamp":1630403791006,"user_tz":-330,"elapsed":1612,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"c42f1f0a-470c-4d3c-8b2f-c41d571b4b1f"},"source":["#Plot the data\n","train = data[:training_data_len]\n","valid = data[training_data_len:]\n","valid['Predictions'] = predictions\n","\n","#Visualize the data\n","plt.figure(figsize=(16,8))\n","plt.title('Model')\n","plt.xlabel('Date' , fontsize=18)\n","plt.ylabel('Opening Price USD($)' , fontsize=18)\n","plt.plot(train['Open'])\n","plt.plot([valid[\"Open\"],valid[\"Predictions\"]])\n","plt.legend(['Train' , 'Val' , 'Predicitons'], loc='upper right')\n","plt.show()"],"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:4: SettingWithCopyWarning: \n","A value is trying to be set on a copy of a slice from a DataFrame.\n","Try using .loc[row_indexer,col_indexer] = value instead\n","\n","See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n","  after removing the cwd from sys.path.\n"]},{"output_type":"display_data","data":{"image/png":"iVBORw0KGgoAAAANSUhEUgAAA7sAAAH4CAYAAACLyfodAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nOzdeZjkZXnv//fT1dXr9KzMsMwwzqDsggOOLBIRxBUJ2wEDmggRNZoYjUlUNEcjOZqQ7WjwnKgoETQ/RcSgJIg7HFCiMMo+7DAwC8wMs8/0Vsvz+6O+VV3d09Nd1V3dVd39fl1XX131rW9VPzP0H3zmvp/7CTFGJEmSJEmaTprqvQBJkiRJkmrNsCtJkiRJmnYMu5IkSZKkacewK0mSJEmadgy7kiRJkqRpx7ArSZIkSZp2DLuSJE1TIYRlIYQYQmiu4N5LQwi/mIx1SZI0GQy7kiQ1iBDCmhBCfwhhvyHX701C67L6rEySpKnHsCtJUmN5Bri4+CSEcAzQUb/lSJI0NRl2JUlqLN8A3ln2/BLg68UnIYQ5IYSvhxA2hxCeDSH8zxBCU/JaKoTwTyGEF0MITwNvLf/g5L3XhBCeDyGsDyF8JoSQmow/lCRJk82wK0lSY/kVMDuEcGQSRC8C/r3s9S8Ac4BDgNdSCMZ/mLz2HuAs4DhgJXDBkM++FsgCL0vueSPw7gn5U0iSVGeGXUmSGk+xuvsG4BFgfXK9GH4/HmPcFWNcA/wz8AfJ628DPh9jXBtj3Ar8XfEDQwj7A2cCfxZj3BNj3AR8Lvk8SZKmnVGnM0qSpEn3DeAOYDllLczAfkAaeLbs2rPA4uTxQcDaIa8VvSR57/MhhOK1piH3S5I0bRh2JUlqMDHGZ0MIz1CoxF5W9tKLQIZCcF2dXFvKQOX3eeDgsvuXlj1eC/QB+8UYsxOxbkmSGoltzJIkNabLgNfFGPeUXcsBNwCfDSF0hRBeAvw5A3t6bwA+GEJYEkKYB1xefGOM8Xngx8A/hxBmhxCaQggvDSG8dlL+NJIkTTLDriRJDSjG+FSMcdUwL/0psAd4GvgF8E3g35LXvgL8CLgf+C3wH0Pe+06ghUJVeBtwI3BgzRcvSVIDCDHGeq9BkiRJkqSasrIrSZIkSZp2DLuSJEmSpGnHsCtJkiRJmnYMu5IkSZKkacewK0mSJEmadprrvYCJtN9++8Vly5bVexmSJEmSpAnwm9/85sUY48LhXpvWYXfZsmWsWjXcEYWSJEmSpKkuhPDsvl6rWxtzCOHwEMJ9ZV87Qwh/FkKYH0L4SQjhieT7vOT+EEK4KoTwZAjhgRDC8fVauyRJkiSpsdUt7MYYH4sxrogxrgBeCXQDNwGXAz+LMR4K/Cx5DvAW4NDk673AFyd/1ZIkSZKkqaBRBlSdATwVY3wWOAe4Lrl+HXBu8vgc4Oux4FfA3BDCgZO/VEmSJElSo2uUPbsXAd9KHu8fY3w+efwCsH/yeDGwtuw965JrzyNJkiRJdZDJZFi3bh29vb31Xsq01tbWxpIlS0in0xW/p+5hN4TQApwNfHzoazHGGEKIVX7eeym0ObN06dKarFGSJEmShrNu3Tq6urpYtmwZIYR6L2daijGyZcsW1q1bx/Llyyt+XyO0Mb8F+G2McWPyfGOxPTn5vim5vh44uOx9S5Jrg8QYr44xrowxrly4cNgJ1JIkSZJUE729vSxYsMCgO4FCCCxYsKDq6nkjhN2LGWhhBrgZuCR5fAnw/bLr70ymMp8E7Chrd5YkSZKkujDoTryx/B3XNeyGEDqBNwD/UXb5SuANIYQngNcnzwF+ADwNPAl8BfjjSVyqJEmSJDWcLVu2sGLFClasWMEBBxzA4sWLS8/7+/tHfO+qVav44Ac/OEkrnXx13bMbY9wDLBhybQuF6cxD743An0zS0iRJkiSp4S1YsID77rsPgE9/+tPMmjWLv/zLvyy9ns1maW4ePvatXLmSlStXTso666ER2pglSZIkSTVy6aWX8r73vY8TTzyRj370o9x9992cfPLJHHfccbz61a/mscceA+D222/nrLPOAgpB+V3vehennXYahxxyCFdddVU9/wg1UfdpzJIkSZI0HVzxnw+zesPOmn7mUQfN5q9/9+iq37du3TruuusuUqkUO3fu5M4776S5uZmf/vSnfOITn+C73/3uXu959NFHue2229i1axeHH34473//+6s66qfRGHYlSZIkaZq58MILSaVSAOzYsYNLLrmEJ554ghACmUxm2Pe89a1vpbW1ldbWVhYtWsTGjRtZsmTJZC67pgy7kiRJklQDY6nATpTOzs7S409+8pOcfvrp3HTTTaxZs4bTTjtt2Pe0traWHqdSKbLZ7EQvc0K5Z1eSJEmSprEdO3awePFiAK699tr6LmYSGXYlSZIkaRr76Ec/ysc//nGOO+64KV+trUYonOgzPa1cuTKuWrWq3suQJEmSNE098sgjHHnkkfVexoww3N91COE3McZhz0+ysitJkiRJmnYMu2pIa17cwzGf/hHPbtlT76VIkiRJmoIMu2pIz23tZldvlue2dtd7KZIkSZKmIMOu6uqh9Tvoy+b2ut6fzQ/6LkmSJEnVMOyqbtZv7+GsL/yCT9/88F6v9ecMu5IkSZLGzrCrutndWxh7vmrNtr1eK1V2c4ZdSZIkSdUz7KpumlMBgGx+7+OvrOxKkiRJozv99NP50Y9+NOja5z//ed7//vcPe/9pp53GTDme1bCrugnJ98ww1Vsru5IkSdLoLr74Yq6//vpB166//nouvvjiOq2ocRh2VTfFim42N0xl1wFVkiRJ0qguuOACbrnlFvr7+wFYs2YNGzZs4Fvf+hYrV67k6KOP5q//+q/rvMr6aK73AjRzFUPu1u5+brp3Hecdt6T0mm3MkiRJmnJuvRxeeLC2n3nAMfCWK/f58vz58znhhBO49dZbOeecc7j++ut529vexic+8Qnmz59PLpfjjDPO4IEHHuDYY4+t7doanJVd1U0uqez2Z/N8+Nv3c//a7aXXMlZ2JUmSpIqUtzIXW5hvuOEGjj/+eI477jgefvhhVq9eXedVTj4ru6qbTH5wkN2yp6/0uFTZdc+uJEmSpooRKrAT6ZxzzuHDH/4wv/3tb+nu7mb+/Pn80z/9E/fccw/z5s3j0ksvpbe3ty5rqycru6qb3JApzLv7cqXH7tmVJEmSKjNr1ixOP/103vWud3HxxRezc+dOOjs7mTNnDhs3buTWW2+t9xLrwsqu6mboYKqtuwcqu31JyO0z7EqSJEmjuvjiiznvvPO4/vrrOeKIIzjuuOM44ogjOPjggznllFPqvby6MOyqbrJD2pg3l4XdjG3MkiRJUsXOPfdcYhwoJl177bXD3nf77bdPzoIagG3MqpvskDbmzbsKYbenP0dPptDSnLGyK0mSJGkMrOyqbnK5vcNujJEjP/XD0jUru5IkSZLGwsqu6ma4Nubu/tygaw6okiRJkjQWhl3VzXBtzFt29w+6ZtiVJEmSNBaGXdXN0KOHXtzdP2hIFdjGLEmSJGlsDLuqm8yQPbu5fGTt1u5B1zx6SJIkSdJYGHZVN7myPbuppgDAU5t3D7rHNmZJkiRpZKlUihUrVvDyl7+cCy+8kO7u7tHftA+XXnopN954IwDvfve7Wb169T7vvfnmm7nyyisB+N73vjfivfVg2FXdlO/ZndfRAhh2JUmSpGq1t7dz33338dBDD9HS0sKXvvSlQa9ns9kxfe5Xv/pVjjrqqH2+fvbZZ3P55ZcDhl1pkGxZG/P8zjQAT2/eM+ge9+xKkiRJlXvNa17Dk08+ye23385rXvMazj77bI466ihyuRwf+chHeNWrXsWxxx7Ll7/8ZQBijHzgAx/g8MMP5/Wvfz2bNm0qfdZpp53GqlWrAPjhD3/I8ccfzyte8QrOOOMMAK699lo+8IEPcNddd3HzzTfzkY98hBUrVvDUU09x3333cdJJJ3Hsscdy3nnnsW3bttJnfuxjH+OEE07gsMMO48477wTg4Ycf5oQTTmDFihUce+yxPPHEE+P+u/CcXdVNeWV3fmehsrtX2LWyK0mSpCni7+/+ex7d+mhNP/OI+UfwsRM+VtG92WyWW2+9lTe/+c0A/Pa3v+Whhx5i+fLlXH311cyZM4d77rmHvr4+TjnlFN74xjdy77338thjj7F69Wo2btzIUUcdxbve9a5Bn7t582be8573cMcdd7B8+XK2bt066PVXv/rVnH322Zx11llccMEFABx77LF84Qtf4LWvfS2f+tSnuOKKK/j85z9fWufdd9/ND37wA6644gp++tOf8qUvfYkPfehDvOMd76C/v59cbvCRpGNh2FXdlO/ZLbYxD63kZqzsSpIkSSPq6elhxYoVQKGye9lll3HXXXdxwgknsHz5cgB+/OMf88ADD5T24+7YsYMnnniCO+64g4svvphUKsVBBx3E6173ur0+/1e/+hWnnnpq6bPmz58/4np27NjB9u3bee1rXwvAJZdcwoUXXlh6/fzzzwfgla98JWvWrAHg5JNP5rOf/Szr1q3j/PPP59BDDx3H30iBYVd1Uz6NeV5S2R3Kyq4kSZKmikorsLVW3LM7VGdnZ+lxjJEvfOELvOlNbxp0zw9+8IMJX99Qra2tQGGwVnE/8dvf/nZOPPFEbrnlFs4880y+/OUvDxu8q+GeXdVN+Tm7S+a1lx63Ng/8Whp2JUmSpPF705vexBe/+EUymQwAjz/+OHv27OHUU0/l29/+Nrlcjueff57bbrttr/eedNJJ3HHHHTzzzDMAe7UxA3R1dbFr1y4A5syZw7x580r7cb/xjW+Uqrz78vTTT3PIIYfwwQ9+kHPOOYcHHnhgXH9esLKrOsomLcr/861H8s6Tl/EPP3wMgGOXzOGeNYUN7H22MUuSJEnj9u53v5s1a9Zw/PHHE2Nk4cKFfO973+O8887j5z//OUcddRRLly7l5JNP3uu9Cxcu5Oqrr+b8888nn8+zaNEifvKTnwy656KLLuI973kPV111FTfeeCPXXXcd73vf++ju7uaQQw7ha1/72ojru+GGG/jGN75BOp3mgAMO4BOf+MS4/8whxjj6XVPUypUrY3F6mBrPP/zwUa6+42me/NszAVh2+S0A/OEpy/jaL9eU7nvm784khFCPJUqSJEkjeuSRRzjyyCPrvYwZYbi/6xDCb2KMK4e73zZm1U0uH2lO7R1ijzpw9qDn5Xt7JUmSJKkShl3VTSYXaW7a+1dw0ey2Qc89a1eSJElStdyzq7rJ5fOkmgYqu393/jGseXEP6abB1d4//Nrd7DerlS/+/isne4mSJEmSpijDruomm4+ky9qYLz5hKQD3rBk83a04rEqSJElqRDFGZ8xMsLHMmrKNWXWTzcVBld2iow6czcKuVr526atoafZXVJIkSY2rra2NLVu2jCmMqTIxRrZs2UJbW9voN5exsqu6yeaH37Pb2drMPX/1egB+8dHT+cA37+U3z23zX8wkSZLUcJYsWcK6devYvHlzvZcyrbW1tbFkyZKq3mPYVd3k8vlhpzGXWzS7jdcftYi712yluz9HZ6u/spIkSWoc6XSa5cuX13sZGoY9oqqbTH74NuahZrelAdjZm5noJUmSJEmaJgy7qptcLtJcSdhtT8JuT3ailyRJkiRpmjDsqm72tWd3KCu7kiRJkqpl2FXdZCvYswswu72wT3dnj2FXkiRJUmUMu6qbnHt2JUmSJE0Qw67qJpuLpCtpY3bPriRJkqQq1TXshhDmhhBuDCE8GkJ4JIRwcghhfgjhJyGEJ5Lv85J7QwjhqhDCkyGEB0IIx9dz7Rq/bD5fUWW3q802ZkmSJEnVqXdl91+AH8YYjwBeATwCXA78LMZ4KPCz5DnAW4BDk6/3Al+c/OWqFm66dx1X/eyJwoCqCvbsplNNdLSkbGOWJEmSVLG6hd0QwhzgVOAagBhjf4xxO3AOcF1y23XAucnjc4Cvx4JfAXNDCAdO8rJVA7c++ALf+c1acvnKjh6Cwr5d25glSZIkVaqeld3lwGbgayGEe0MIXw0hdAL7xxifT+55Adg/ebwYWFv2/nXJtUFCCO8NIawKIazavHnzBC5fY9WTydHdlyOTi6Qq2LMLhVZmK7uSJEmSKlXPsNsMHA98McZ4HLCHgZZlAGKMEYjVfGiM8eoY48oY48qFCxfWbLGqnb5Mnj39WXL5fMWV3Y6WFD2ZXNU/K5+P/PLJF6t+nyRJkqSprZ5hdx2wLsb46+T5jRTC78Zie3LyfVPy+nrg4LL3L0muaYrpyeTozeTpy1Z2zi5AWzpFT3/1YfeaXzzDO776a366emPV75UkSZI0ddUt7MYYXwDWhhAOTy6dAawGbgYuSa5dAnw/eXwz8M5kKvNJwI6ydmdNIb1JhXZnT6biym57S6r0vmo8tXk3AJt29VX9XkmSJElTV3Odf/6fAv9fCKEFeBr4QwoB/IYQwmXAs8Dbknt/AJwJPAl0J/dqCiq2I+/szVa8Z7c9nWLDGMJuLl/ogk/Ve+64JEmSpElV17AbY7wPWDnMS2cMc28E/mTCF6UJ15vJA4Ugmq6wjbm9JUX3GNqYk6xLU6js50iSJEmaHqx3adL1lVVoU5W2MafH1sacj4W0a9iVJEmSZhbDriZd+VTldIX9xe0jDKjatKuXZZffwg8f2nsL90Abs2FXkiRJmkkMu5pUmVyebH7gNKmKK7vJ0UMx7n0S1cMbdgLwzbvX7vVaLrnfwq4kSZI0sxh2NamGtiLP60hX9L62dIp8hP5cfq/XcrlCoB1usnMxHA+TkSVJkiRNY4ZdTaricKqi/We3VfS+9nQKYNhW5uwIrcrFNubMMCFZkiRJ0vRl2NWkGlrZPWBOhWG3JQm7wwypKgba4Sq7xYxb3jotSZIkafoz7GpS7RV2K6zsdrTsu7Jb3Jc7XGW3OI05a2VXkiRJmlEMu5pUQyuz+1dY2W1Lj1TZLQTZkcJuf87KriRJkjSTGHY1qYbu2e1qba7ofcU9u8OdtZvNjb5n18quJEmSNLMYdjWphobVUOGZQMU9u90jDKgabs9uqY3ZPbuSJEnSjGLY1aQarg25EiNNY+5LPjPVtPevs9OYJUmSpJmpsh5SqUaKld0Pv/4wXnHwnIrfV9yzu6s3u/dnZgtBdrjKbiZn2JUkSZJmIsOuJlUx7F6wcgmL57ZX/L5iG/NffOd+Wpqb+N1XHFR6rS+z7wFVfdnCz8s6oEqSJEmaUWxj1qQqDqhqa67uV68jqewC3PXUlsGfmQTaGPcOtMUgnDHsSpIkSTOKYVeTqrhnt1iprVT5/QfPH1wRLgba4YZQ9WWLr9nGLEmSJM0khl1NmgfX7eDKWx8FoK25urDbWlYJ7h0ypKp3hFblYhuze3YlSZKkmcWwq0nz0IYdAKw4eC5Nw+yvHUkIgb8680gA9gwJu5VUdm1jliRJkmYWw64mTX8SPK+5ZOWY3v+eUw9hv1mte521W6rsDtOqXArCVnYlSZKkGcWwq0lTDLstVQ6nKtfZmqK7f/DxQ/uq7MYYB9qYh6n6SpIkSZq+DLuaNMXg2Vrlft1y7ekUe/qGtDEnn5sb0qqczUeKGTeTtbIrSZIkzSSGXU2aYmU3napuv265ztZmejL7quwODrR9ZQF3uP28kiRJkqYvw64mTV8uT0tzEyGMPex2tOy7sjs00PZlBu5zGrMkSZI0sxh2NWn6s3laU+P7letoSdEzdEBVaQjV4LDbW17ZdRqzJEmSNKMYdjVp+rJ5WtPj+5XrbGlmz9ABVcNMY87nI3/0jVWl51Z2JUmSpJmlud4L0MzRn83TMs7KbnuFld01W/bw0PqdXPrqZTy+cddeZ/NKkiRJmt6s7GrS9Gfz4zp2CAoDqvZd2R0Iuw+u3wHAhSuX0J5Oec6uJEmSNMMYdjVpahF229MpejN5cmXBtneYacwPb9hJS3MTh+3fRTrVZBuzJEmSNMMYdjVp+rK5cZ2xC9DZWnh/TzJpOcY4UNkta2N+cN0OjjygEHSbU8EBVZIkSdIMY9jVpOnPjb+y29FS2Gbe3ZctfWaxyFvexvzc1m4OWTgLoFDZzVvZlSRJkmYSw64mTS0GVHW0FCq73cnAqd7+gRBb3trck8mVqsDNTVZ2JUmSpJnGsKtJU4s9u8XKbnFIVW92YMpy+b7c7v5s6d50s3t2JUmSpJnGsKtJ05fN0zrusJvs2U0qu8Xv6VQoVXbz+UhvJk97unBvuimQsbIrSZIkzSiGXU2a2hw9VAiwxXNzi4OqZrU2lwJt8VoxGDenmjx6SJIkSZphDLuaNH01bGMuDqgqhd22ZnLJEKrift6BsBvI5K3sSpIkSTOJYVeTpj9XuzbmgQFVhe9drenSEKpia3N7EoxbPGdXkiRJmnEMu5o0fZnxn7NbquwOGVA1q625dPRQdyab3FucxtxEjIOnNUuSJEma3gy7mjS1OWd3oLK7aVcvT27aDUBXazPZIW3M7WVtzIDVXUmSJGkGaa73AjRz1OKc3eKE5T39OU747M9K18sru8U25o7iNOaysNuWHl9lWZIkSdLUYGVXkyKby5OPjLuy29QU6GhJlQZUFXW1NZdalQcGVCXn7CYB2+OHJEmSpJnDsKtJ0ZcttBCPd0AVFFqZu5MpzEWzWtMAZPP50n7eYhtzMWD3Z21jliRJkmYKw64mRTFojreyC4WK7XCVXYBsLg60MRfDbqmya9iVJEmSZgrDriZFf66WYTdValUuKlaMs4PamAdXdvus7EqSJEkzhmFXk6JU2R3ngCoYPuwW9+Xm8pGezOBpzK22MUuSJEkzjmFXk6IvOQ+3tQbTkDtamtnVmxl0LdVUmLh873PbuPqOp0k1hVKwLu3ZtY1ZkiRJmjEMu5oUfTWu7G7e1TfoWvF4ocuuW8WOnkIQDiEkP7MQsK3sSpIkSTOHYVeTopbTmDtbm9m8e3DYTTUN/txcfuCYIacxS5IkSTOPYVeT4q4nXwRg2X6d4/6s9pbUXmfmFiu7C7ta97p/oI05t9drkiRJkqYnw64mXC4f+eavn+OUly1geQ3CbmfL3vt+i3t208n3csXWaSu7kiRJ0sxh2NWE29bdz4Ydvbz+yP1r8nntLc17XWtO2ph39hbO3/3QGYeWXvPoIUmSJGnmqWvYDSGsCSE8GEK4L4SwKrk2P4TwkxDCE8n3ecn1EEK4KoTwZAjhgRDC8fVcuyqXT/bPpmswnAqGr+w2JxXd3X1ZzjhiER9+w2Gl1zx6SJIkSZp5GqGye3qMcUWMcWXy/HLgZzHGQ4GfJc8B3gIcmny9F/jipK9UY1KcFdUU9m4xHovZ7enS4z869RCu/cNX0Zwa+Oz2IWG4GLI9ekiSJEmaOcYUdkMIrSGEllovJnEOcF3y+Drg3LLrX48FvwLmhhAOnKA1qIbysZB2h9lOOyZHHzS79Piy1yzntMMX0dU20NrcMSTsOo1ZkiRJmnkqCrshhBUhhL8NIdwVQtgBdAM9IYQdIYRfhhA+G0I4bgw/PwI/DiH8JoTw3uTa/jHG55PHLwDFjZ6LgbVl712XXFODK4XdGqXdIw4YCLuzWgshd05ZtbdjyJ5ew64kSZI08+w96adMCOEs4JPASiAAa4C7gS3J8/nAy4CPA5cn+27/JsZ4S4U//3dijOtDCIuAn4QQHi1/McYYQwhxH+/d15rfS6HNmaVLl1bzVk2QWOM25pays3rb04Uq7uy28rA7pLLrNGZJkiRpxtlnZTeE8HPg+8Bu4DLgwBjjITHGN8QYL4ox/l7yeDlwIPAeYA9wcwjhp5X88Bjj+uT7JuAm4ARgY7E9Ofm+Kbl9PXBw2duXJNeGfubVMcaVMcaVCxcurGQZmmC1bmMGOPWwwn/bkATo2e37DrvFM3gz7tmVJEmSZoyR2pi3A8fFGM+IMV4bY9y4rxtjjBtjjP8WY3wd8Epg12g/OITQGULoKj4G3gg8BNwMXJLcdgmFwE1y/Z3JVOaTgB1l7c5qYLl8MezWLu1+9Z0ruf+v31h63pYeCLhDjyYKIdDS3ESfYVeSJEmaMfbZxhxjPH8sHxhjvA84r4Jb9wduSipzzcA3Y4w/DCHcA9wQQrgMeBZ4W3L/D4AzgScp7Bn+w7GsT5OvOI25hlmXluamQe3M5YZWdgFaU022MUuSJEkzyIh7didSjPFp4BXDXN8CnDHM9Qj8ySQsTTUWY+0ru8NpCoVgPVzYbWk27EqSJEkzybjP2Q0hdIQQ0qPfqZmqWNlN1XLT7jCK5+m2pw27kiRJ0kxXzdFDvzvkWlcI4SZgJ7ArhHBNCKF1IhapqW0iBlQNpxh2hx49BEnYdc+uJEmSNGNU2sb8f4BtwH+WXfsscDbwDaCFwh7ap5PrUkkx7IYJbmNuTqYutw/XxuyeXUmSJGlGqbSN+TjgR8UnIYQU8E7gSzHGS2OMbweuAd5e+yVqqqv1Obv7MlDZtY1ZkiRJmun2WdkNIZyaPGxPvmaXXVsGzAaeKbu2FlhW9nxNjPG52i9ZU83A0UMT+3PSyQ8Ybs9uOmUbsyRJkjSTjNTGXDzapzh86lTg0OTxkUAeODr5AlgEtAKXAgG4CTDsqmzP7sSm3SXzOtiwo3fYQVgtzU30WdmVJEmSZoyRztktnWMbQjgP+FmM8R+T518B5gy5583AK2OM75rA9WoKKk5jbprg0u6//v7x/HT1Rg6e37HXa63NTezqzU7oz5ckSZLUOCodUHUn8LEQwgZgFoW9uZ8fcs9K4Jkark3TRJykacz7zWrlohOWDvuaA6okSZKkmaXSsPuXwI8pTF4GuB/4xyH3vB34Vo3WpWkkP0kDqkbi0UOSJEnSzFJR2I0xPhRCOBJ4NdAP/CLG2Fd8PYQwF/h7yiY2S0UDRw/Vbw1OY5YkSZJmlkoru8QYdwC37uO17cB1tVqUppd8fnIGVI2kJdVExsquJEmSNGNUes6uNGaN0Mbcmm6iN5Or28+XJEmSNLn2GXZDCJeFEKoOwyGEVAjh3eNblqaT/CQNqBrJnPY0O3uzpSqzJEmSpOltpDD7z8CjIYQPhBD2G+2DQgj7hxA+DDzG3sOrNIOVwm4d0+78zlZy+ciOnkzd1iBJkiRp8s/OLc8AACAASURBVIy0Z/dQ4LPA54B/DiGsAu4GngK2AgGYn9x3ErAied81wKcmasGaemIDtDEv6GwBYGt3P/OSx5IkSZKmr32G3RjjZuC9IYQrgPcBFwAf2sftDwOfAb4SY3y+5qvUlNYIbczzi2F3Tz8vXVi/dUiSJEmaHKNOY44xrgc+CXwyhLAIOApYCERgM/BwjPHFCV2lprRcA0xjLobdLbv767YGSZIkSZOn4qOHAGKMm4BNE7QWTVPFmVD1PGe3GHa3dRt2JUmSpJnAo4c04WJsnMru1j2GXUmSJGkmqCjshhDmhBA+EUL4ZQhhcwihL/n+ixDC5SGE2RO9UE1dxcpuqo6bdtvSKTpbUrYxS5IkSTPEqG3MIYRjgR8AB1KYwLyLQivzbODVydcfhxDeHGNcPYFr1RTVCAOqAObPamHrnr76LkKSJEnSpBixshtCaAO+S2Eg1d8Cy2OMc2KMB8cY5wDLk+v7A/8RQmid6AVr6imG3VDPTbsUztrd2u05u5IkSdJMMFob80XAS4G3xxg/GWN8tvzFGOOzMcb/Cfw+cFhyvzRIvgH27ALMbU+zwwFVkiRJ0owwWtg9G7g7xvjdkW6KMX4HuBs4p1YL0/SRzxe+17uNuaMlRU8mV99FSJIkSZoUo4XdVwA/rvCzfpzcLw3SKJXd9nSK7n7DriRJkjQTjBZ2FwLPVfhZzyX3S4MkWZemOpd221tS9Bh2JUmSpBlhtLDbCXRX+Fk9yf3SII0yjdk2ZkmSJGnmGC3s1jmeaDoonrPbCG3MPZkcsVhqliRJkjRtjXrOLvAXIYRKpiwvHu9iND0NHD1U33W0tzQTI/Rm8rS3pOq7GEmSJEkTqpKwe1zyVQlLZtpLowyo6kgCbk8mZ9iVJEmSprkRw26McbQ2Z2lU+XxjhN32dCHgdvdnmd/ZUte1SJIkSZpYhllNuOKe3VS9w26xsutEZkmSJGnaG1fYDSEcFEJ4VQhhbq0WpOmntGe3zv+0Umxj9qxdSZIkafobMX6EEFaEEP48hLBgyPX9Qgi3AmuBXwEbQwifmsB1agqLDTSNGfD4IUmSJGkGGK3W9j7gz2KMW4Zc/yrwJuAZ4CZgG/DXIYRza79ETXWNcs6ubcySJEnSzDFa2D0ZuLX8QgjhJcDZwP3A0THGC4BjgPXAeyZikZracg0zjbkwj802ZkmSJGn6Gy3sHgQ8PuTa65Lv/xpj7AOIMW4G/h04vrbLU6P59M0P89lbVlf1nmIbc93P2bWNWZIkSZoxRgu7s4DtQ66dQOE83duGXH8KmF+jdalBXXvXGr5y5zNVvad49FDjTGPO1nUdkiRJkibeaGF3HfCyIddeDWyPMT455HozsLtWC9P0kW+QAVVOY5YkSZJmjtHC7irgnSGEAwFCCCdT2J/702HuPQrYUNvlaTooHT1U5zbmNtuYJUmSpBljtLB7JbAIeDSEcDeFkJsH/mWYe88Cfl3b5Wk6iDESAoQ6p91UU6C1uclpzJIkSdIMMGLYjTHeD5wHPEehovsM8HsxxrvK7wshvIlCKL51rw/RtBSLU6cqkIux7i3MRR0tKduYJUmSpBmgebQbYoz/BfzXKPf8COiq1aLUmMoDbl82X2oLHk0+1v+M3aL2tGFXkiRJmglGa2OWSjK5gbC7q7fyicb5GOvewlzUlk7RlzXsSpIkSdPdiJXdEMKpI7wcgR7gmRjjlpquSg2pfLDT7r4sC7taK3pfjPU/dqioNZ2iN5Ov9zIkSZIkTbDR2phvpxBqRxRC+CXwp8keX01TvWVhd09fFZXdfGyYNua2dJOVXUmSJGkGGC3s/g0jh91OCkcOvR74fyGElcOcv6tponyKcXVtzPU/Y7eotbmJPiu7kiRJ0rQ3YtiNMX66kg8JIRwD/DfwceCy8S9LjWhoG3Ol8snRQ42gLZ1i657+ei9DkiRJ0gSryYCqGOODwDUUKryapnrG2sYcI00N0sfc1pwa1I4tSZIkaXqq5TTm1cABNfw8NZje8jbmasNug5R2W9NN9GVtY5YkSZKmu1qG3blAb7VvCiGkQgj3hhD+K3m+PITw6xDCkyGEb4cQWpLrrcnzJ5PXl9Vw7arAoDbmKbpn18quJEmSNDPUJOyGwiGqvws8PIa3fwh4pOz53wOfizG+DNjGwB7gy4BtyfXPJfdpEpUf2VNNG3OMjTWNeUdPhg9+617Wb++p93IkSZIkTZBxhd0QQlsI4TjgOuBk4Noq378EeCvw1eR5AF4H3Jjcch1wbvL4nOQ5yetnJPdrkox5QFW+cSq7xXN2b75/A79+2uOhJUmSpOlqxGnMIYQ8FZyzCwTgmzHGq6v8+Z8HPgp0Jc8XANtjjMUktQ5YnDxeDKwFiDFmQwg7kvtfrPJnaoyKYbe5KdDdX+2e3YlaVXXamgf+fafHdmZJkiRp2hrtnN07GDns9gDPAN+LMf6kmh8cQjgL2BRj/E0I4bRq3jvK574XeC/A0qVLa/WxYmBA1bzOFnqqOKs2FyONUoRvTadKj8vPDZYkSZI0vYx2zu5pE/izTwHODiGcCbQBs4F/AeaGEJqT6u4SYH1y/3rgYGBdCKEZmAPs1YeaVJevBli5cmUlVWlVqFgJndeRrmrIU4zQVMtRaOPQWlbZ7TbsSpIkSdNW3SJIjPHjMcYlMcZlwEXAz2OM7wBuAy5IbrsE+H7y+ObkOcnrP48xGmYnQT4fWbu1m55MjnQq0NnaXFXYzcdIqkEqu23llV3bmCVJkqRpa7Q25nr4GHB9COEzwL3ANcn1a4BvhBCeBLZSCMiaBD9e/QLv+/ffsnhuO23pFO3pVFUtwA119JBtzJIkSdKM0BBhN8Z4O3B78vhp4IRh7ukFLpzUhQmAzbv7AVi/vYdFXa20pVPs7M1U9N6P/8eD/Of9G3jpws6JXGLFytuYDbuSJEnS9NUgOynV0Mq6xc89bnFVld37124HGrOy220bsyRJkjRtGXY1quIgp3s/+QY+ceaRtCVn1VYikyvc1zhht7yyW/nxSZIkSZKmFsOuRlUMu3Pa00AhMFY6oKoYdhsk69La7IAqSZIkaSYw7GpUvZkcbekmmpoKibU9nao4KGZyhRboVFNjpN3yyq5HD0mSJEnTV1VhN4TQFUL4VAjhFyGEJ0IIJyfX90uuHzExy1Q9dffnaC/b69qWhN1KTn5qvDZmpzFLkiRJM0HF05hDCAuBXwCHAE8m39sBYowvhhAuAeYCfz4B61Qddffn6GgZ+FVpb0kRI/Tn8oPagoczEHYndIkVGzSN2TZmSZIkadqqprL7GeAA4ETgNcDQ+PJ94IwarUsNpDeTo71lcGUXoLd/8JCqoz71Q/7xR48OulZsYw4NWNm1jVmSJEmavqoJu2cB/xpj/C0wXP/q08DBNVmVGkp3f3ZIG3Ph16a8MrqrN0N3f47/e9tTg97b32CV3baySnSvYVeSJEmatipuYwb2o9C+vC95oG18y1Ej+dT3H+KVL5lX2LNbVtktBt/yicxPb94DDB4ABZBtsD27reUDqpJ9x41SdZYkSZJUO9VUdl8AXjrC68cBz41vOWokN927ntse3URvJkfHMGG3vLL71ObdABw0p710LZeP5JMegKYGKe22pVNc/pYjOHfFQeTysdRmLUmSJGl6qSbs/gC4LIRw4NAXQggnAu+ksG9X00A+H9ndl2VHT2bYacwwfNjdr6u1dK04nAoap40Z4H2vfSkvXzwHcCKzJEmSNF1VE3avALLAvcDfUdi3e0kI4VvAHcAG4O9rvkJNiu7+LJ+++WE27uwFYHd/lhhhZ292rzbmtmHamJ/aVGhjzpYF3P6yxxWcUjSpitOluzPZOq9EkiRJ0kSoOOzGGF8ATgJ+DbyLwjTmPwDeBvwYeE2McetELFIT7/q713LtXWv49189C8DOnkzpe29mcGW3GHzLw+7zO3qAwROOs2Utwtl8Y6XdYlu2lV1JkiRpeqqmskuMcW2M8RxgPoUjiE4CFsYYfzfGuG4iFqiJF2Pk2rvWAPCf928gxsiu3kLFs9jG3NEyzDTmsqOHii3N5QG4vI25vOLbCIqB3eOHJEmSpOmpmmnMJTHGncA9NV6L6mRHT4bntnZz6KJZPLFpN09t3lOq7G7vydCfzdPeMvCrMtw05t5MIcyWh8f+bFnYbbDK7tz2NADbuvvrvBJJkiRJE6Hiym4I4fdCCF8f4fXrQggX1GZZmkzbugvB9hUHzwVgy+6+UmW3GFgHtTEPM6CqGHzL24LLK7u5Bgu7C2a1ALB1j2FXkiRJmo6qaWP+AIWzdPclB/zp+JajeihWN18yvwMoVHp39mYG3TPo6KHk8e6+geFOpbA7qI05lj1urDbmeR2GXUmSJGk6qybsHklhEvO+3AscNb7lqB62F8Pufp1AYQJzsbJbVD6NuastzYLOFp7ZvKd0rdjGnM3HUjW4kSu7cztaCMGwK0mSJE1X1YTdTgrV232JQNf4lqN62LanUMUdVNntGVzZLW9jBjh0/1k8vmkXUAiy/bk8s9sK+3qL1d3ysFte5W0EqabAvI4Wthh2JUmSpGmpmrD7DPA7I7z+O8Bz41uO6qHYxrw0Cbs7ezLs6htc2T1gTtug54cu6uLJjbuJMdKXLYTbeZ2F1uDivt3MoKOHGquNGWB+ZwvbDLuSJEnStFRN2L0JuDCEcNnQF0II7wIuBP6jVgvT5NnW3U9TgDntabramoet7L5iydxBzw/bfxa7+rJs3NlXamEu7oMdrrLbaG3MAPOt7EqSJEnTVjVh90rgEeDqEMJDIYR/T74eBL4CPAb87UQsUhNn9Yad/OLJLcztaKGpKTC7Lc3O3gy7erN0tQ0cN9TSPPhX5WWLCh3rT2zaVQq385PKbnd/oSo86JzdRgy7nS3u2ZUkSZKmqYrDboxxF3AK8GXgQODtyddBwBeBVyfn72oKOfOqO7l/7XbmdhTOnZ3TnmZnMo35JQsKbc0fPOPQvd63sKsQbLd1Z0qTmIuV3d7MMG3MDbZnF2D+LNuYJUmSpOmqefRbBsQYdwB/HEL4E2C/5PKLMcbGSzKqSl/SijynPc2OngzPvNjN77xsAd/741NINYW97u9sLfzq7OnLloXdQmDu7t+7jbkh9+x2tLCtu598PtI0zJ9RkiRJ0tRVTRtzSSzYnHwZdKeB9dt7AJjd3sx9a7fz4u4+TjxkAc2pJkLYd9jd3Zsd2LNbamMeJuw2YGV3bkeafGSvM4UlSZIkTX37rOyGEJYCxBifK38+muL9anzFqckAK18yDyhUdovtxycdsmCf7+1sScLuoMpuIew+/sIu3njU/qXzdqEx9+wW9yTv7ssyN1m7JEmSpOlhpDbmNUA+hNARY+xPnleSWFKj36JG8OLuPgA+8qbDueTVywCY1VpoRV48t51lyZ7d4aSaAh0tqUFtzPM7C+/95588zomHLGjIgFuu+Gfd0zfS8dGSJEmSpqKRwu7fUAi32SHPNU1s2lUIu0cdNJtZSVtysfX4L9542LDty+U6W5uTym7hPYtmD5zFu627f1AbcyPqbC38u8zuPtuYJUmSpOlmn2E3xvjpkZ5r6itWdhfOai1d++PTX8rRB83mvOMWj/r+WaWwW6iMLuhs4eo/eCXv/cZvyOfjoDbmRlRsY97Vmx3lTkmSJElTTUUDqkIIs0II/xZCuHCiF6SJ15vJ8c1fP8emnb0ALOwaCLsHzmnnohOWjlrVhULY3dOXLZ2z25ZOccjCTqCwRzfTgEOpyhXbmB97YRdrt3bXeTWSJEmSaqmisBtj3A1cBMye2OVoMnxn1Vo+cdOD/MOPHgNgfufYhjN1tqYGVXbb0ilSTYVfqWw+T3aKtDH/3a2P8pp/uK3Oq5EkSZJUS9UcPbQaWDZB69Ak6morVDR39WbZb1YL6dSYTqBK2phz9CXtym3pJpqT82qzuUgml6eRj6/tSiq7RU9u2lWnlUiSJEmqtWpSzj8A7w8hHDZRi9Hke9vKg8f83mIbc28mRwjQkmqiOVVIt7l8pD8XaU6C9OH7d9VkvbVUrOwW3frgC3VaiSRJkqRaG2ka81BHAGuBB0MI/wU8AQzd6BhjjP+rVovTxOhP2otfsqCDPz79ZWP+nM6yAVVtzSlCCKSSUm4mX6jstqSa+NGfncqCWY13jm1zqol0KpT2Fj+1eXedV1Rw1c+e4IDZbbztVWP/hwhJkiRppqsm7H667PF5+7gnAobdBpdNwt0Nf3Ry6cihsShOY+7J5GhLFyq46WTPbi6XJ5PLk04Flu/XOf5FT5DyIVrd/Y1x3u7//snjAIZdSZIkaRyqSTrLJ2wVmlTF82+bx7mhdlZrM/3ZPLt7s7SlCy3BqaSNuTiNeaz7geuhUcKuJEmSpPGrOOzGGJ+dyIWoep/7yeMcPL+DC165pKr3FcNuunl8QbQzqQpv3NlXepwuTWOOSWV3aoTd1uYm9vR73q4kSZI0XYyaREIIF4UQHgwh9IQQ1oYQPhNCmBoJZpr7l589wV9+5/6q31ds3W0ZZxAttkC/sLOXrrbC41RpGnOe/myhjXkqWDq/gx4ru5IkSdK0MWLaCSG8FfgmcDSwGzgQ+Dhw5cQvTSOJcWCvaS4fR7hzb7VqYy4G3PXbe0rHGZWOHspHuvuzpYpvo1s6v8PKriRJkjSNjFba+xCwBVgZY1wIHAD8N4UjiFonenEaLJvLc/P9G8jlIzt7BoLZMy9WN0U4m8sTwkAVdqzmdBQCbn82z+wk+DY1BZpCYQjWrt6pE3YXzW6zsitJkiRNI6OF3VcCX44x/hYgxvgi8AmgAzhygtemIW596AU++K17+dkjG3lxT1/p+sMbdlb1Of25SLqpiRDGF3bntg8cJ1Ss7ELhSJ9sPrKnP0tXg4fdd5y4lHQqMKs1xZ4+w64kSZI0XYwWducCjw+59hgQktc0ie56agsAv3p6K1t295euP7Gx+spuLfbSzu0YCLjFyi4UWpmzucKU5lltjR12P3veMTzx2TNpb2mmJ5MjX2VLuCRJkqTGNFoSCcDQjYzF5w6pmmS/eroQdv/tl8+QL9uzu6WsyluJTC5Pcw2mJJeH3a6yUJtqCmTzkd192XGd4zuZOlsKRyf1ZHJTpvVakiRJ0r5V8n/1y0IIx5c9n5N8PzSEsH3ozcWWZ9XG9+5dz6ZdvZy7YjHPvLiHhV2tbN7Vx7V3rQFgXkd6UJW3Epl8bc6/bU+naEk10Z/LM7t9IPimU03k8oU9u1Ml7HYk69xT56Fa5YPHJEmSJI1dJf9X/7+Sr6H+dR/3p8a+HA31Z9++D4Cl8zsB+IcLjuU7q9bygwdfAODQRV1s664y7NboSKAQAnM60mze1bdXZbc3k6Mvm586YTdd+LXt7stBV/3WUe1kbUmSJEnDGy2JXDEpq9Cobli1lqYAJy1fwIolc0thd+HsVh55vroBVdkaVXYB5rYnYbe1rLLbFNjekwFo+D27RZ2thbB779ptLJ3fQdM4J1WPVdawK0mSJNXEiEkkxmjYraPyYUk/f3QTRxzQRXtLivaWgeL5gs4Wtu6prrLbX6MBVTCwb3dQZTcV2J5Um6dMZbelsM4Pf/t+dvfl+IOTXlKXdRTPQJYkSZI0PlMjicxQL+4ePHjq5YvnlB7/n7cfx67eLC/s6GV7d4Znt+zhJQs69/lZtz+2if5snjcefUAyjbk2ld05yfFDg/bsNjWxvTup7E6ZsDvwDwjrtnXXbR3ZnJVdSZIkqRamRhKZoTbs6AXgr848ki17+jn7FQeVXjvr2MLjr//3GgBe+4+38+33nsSJhywY9rMu/do9AKy58q1kcjVsYx6usjsF25iLlV2ARV1tdVuHbcySJElSbdTt+KAQQlsI4e4Qwv0hhIdDCFck15eHEH4dQngyhPDtEEJLcr01ef5k8vqyeq29Vh5av2PEgUQbtvcAcMrL9uPytxzBUQfN3uue+Z0tpcerK9y7Wzh6qEZtzO3FsDtQ2W1ONbFjilV2i3t2gbqetZvN28YsSZIk1UI9z8rtA14XY3wFsAJ4cwjhJODvgc/FGF8GbAMuS+6/DNiWXP9cct+U9fjGXZzzf3/JZ25ZXQqGQxXD7kFz911pLA+7z24ptN/e+cRmVm8YPvju7M2QqWEb81EHzWbp/A66ykJtc1OgP9l72jVFKrvl+6C7+3N1W4dtzJIkSVJt1C3sxoLdydN08hWB1wE3JtevA85NHp+TPCd5/YwQQn1G5tbAYft38fsnLuVrv1zDq/72p6zdOrBPdMP2Hs79v7/ke/etZ057mjll+2GHKp+C/PjGXQD8wTV3c+ZVdw57ZuuG7T1JG3Nt/urOP34Jd3z09EHTi8urxvU8s7YanWVtzD2Z+oVdB1RJkiRJtVHPyi4hhFQI4T5gE/AT4Clge4wxm9yyDlicPF4MrAVIXt8BDL9BdYr41O8ezWfPezn92TzX3/Nc6frDG3Zy39rtPLR+J3/02kMYKdMfcWAXl5z8Ek552QIe37h7UMC966kte92/YXtPTQdUDae5LPhOnTbmZv7XOUcD0FvHsOs5u5IkSVJt1DXsxhhzMcYVwBLgBOCI8X5mCOG9IYRVIYRVmzdvHvcaJ1KqKfCOE1/C649cxA2r1pX2iu5Mhju9+egDeNcpy0f8jHSqiSvOeTmnHbaIF3f3lVqZAW57dBMA2bJq4frtvfTnIs1NE/efPlUWdssrpo3uD05exgGz2+ipYxtzxjZmSZIkqSYqTiIhhHeOcksEeoDngN+WVWdHFWPcHkK4DTgZmBtCaE7evwRYn9y2HjgYWBdCaAbmAHuVLmOMVwNXA6xcuXJKJIe3HnsgP31kE6uf38nLF89hRxJ2r/wfx9CWTo3y7oKD53cAcO/abaVra7bsAWBP30B4K1Z2W5onrgO8WDVuSzcNam+eCtpbUnTXsbLrgCpJkiSpNqopu11LIdAWFVPM0GsR2BJC+KsY41f29WEhhIVAJgm67cAbKAydug24ALgeuAT4fvKWm5Pn/528/vM43KbUKeiUl+0HwJ1PvDgo7JZPOB7NknntANz73HagcCTQMy8Wwu6uvoEBWBt39NZ0QNVwipXd9gqDeiNpS6es7EqSJEnTQDWJ5w3Ab4E1wOUUBkedC3w8ubYKOB/4KLAb+FII4X+M8HkHAreFEB4A7gF+EmP8L+BjwJ+HEJ6ksCf3muT+a4AFyfU/T9YwLSzqauOIA7r45t3P8t9PbWFHT4autuZB7cCjKYbd+9YWwu4Jy+bz3NZusrk8u/sGiuzd/TkyE9zGXPzsqRh2O1pS496zm89Hrr/7Ofqz1VVpv3rn0/yPL941rp8tSZIkqaCayu4pQCtwTIyxu+z6zSGEf6VQcX15jPEzIYQvA/dTCKXfHe7DYowPAMcNc/1pCvt3h17vBS6sYr1TykfedDiXXbeKr975NLNHmcA8nDntaTpbUjywbgcAJyyfz49Xb+Sup7YMOkO2O5MjM8FtzMUBVW0tUy/stqdTdPdX3IE/rO/8Zi2X/8eD7OjJ8EevfWnF7/vMLY+M6+dKkiRJGlBNee8y4LohQReA5Aiha4F3lz3/OnBMDdY4I5xx5P6csHw+u/qy7OjJMLejurAbQmBxUt1tbW7imMVzAHjnv93NPWsK+3jb0k309GfJ5ie4spua4m3MmbHvm/27Wx/ha79cA1B1ZVeSJElS7VSTeBYBI6WXZmD/sucbqK5yPOPNam1mTxJ2q63sAiyZVxhStbCrlWOWzGHZgmRo1XPbSte7+3NkspNz9NBUDLvt42xj/vL/e5pHXyicd1ztP1hIkiRJqp1qEs/jwGUhhNlDXwghzKFQ+X2s7PJyCufnqkKdSdjd3t0/prD70oWdAByycBYdLc3c8sHXAJTC18JZrfRkcmTyedKpCWxjToJ0+xRsY+4YRxtz+RFPAK1TMOxLkiRJ00U1lde/AW4AHgshfI1C+AU4HLiUQuX3bQAhhCbgIuCXNVvpDDCrNcXu5JigsYTdD73+MN5yzIEcdWDh3yM6W5tZ0NlSOnt3UVcbz+/oJZOLk1LZrfTYpEbS3jL2aczlRzyBbcySJElSPVUcdmOM3w0hvB343+w9Cfl54PdjjMVhVCngLcDmmqxyhuhsKVR2c/nI7DGE3VmtzRy/dN6ga0vmtbNlTz8A+3W1lD6/eUIru1O3jbktnaJ3jHt2y494AsOuJEmSVE9V7amNMX47hHAj8EoKbcqQHDsUY8yV3ZdhcEuzKtDZ2kxPsl90bntLTT5zyfwO7l+3g46WFLNa0+zsLbToTmxld2ofPdSfy5PN5Uvt2JUqP+IJoD9n2JUkSZLqpeoBUkmovTv5Ug3Nah34zzGWNubhLOgshObD9u8aFD5bJmNA1RTcs1v8O+rJ5OiqNuz2Dgm746zs5vORpirOWpYkSZI0YEyJJ4TQEUI4OISwdOhXrRc4k8xqGwi7+82qTWX3DUftz9EHzeYLFx9HR1n4nMg25lTy2a3piQvUE6V4NnDPGCYy7xpa2a0i7GaGqQLnYqx6DZIkSZIKKq7sJkOnPgr8KXDACLdOvXJeg+gsq+zu19Vak898zaELec2hC4HBldaJbGNuClN3z25Hsube/uqqsk9t3s3PHtkIwJuO3p8fPbyxqjbmPX17T4DOG3YlSZKkMaumjflK4C+Bh4HvAlsmZEUz2KzWgXC4cFZtwm65jkFhd+Iqu7l8IaRNxWnMxb+jnb2ZUe4c7H//+HFuefB5AK44++X86umtVVV2d/UOE3bd8itJkiSNWTVh9/eBH8YYz5yoxcx0nS0D/zkW1qiyW6680jqRld1iyJvInzFRDt2/C4CHN+zg5YvnVPy+57Z2lx7PamumpbmJvmzlrdBDh1uBbcySJEnSeFSTRuYB35+ohWhwG/NEVEUnq405m5QkWyawejxRXrqwk3kdae5Zs62q963bNhB2O9IpWlJN9FVR2R0u7NrGJJh1jAAAIABJREFULEmSJI1dNYnnQeDAiVqIBk9jnggdZZXjg+a2TdjPyWQLIa3ao3saQQiBlcvmc+Nv1vHte57b5329mRynXPlzfvzwC+zuy7Kte6Dtuakp0JpuqrKNee+26XzesCtJkiSNVTVp5ArgfSGEgydqMTNd54SH3YHK7rIFnRP2czL5qdvGDHDa4YWBXh/77oP7vOfJTbtZv72Hv/mv1azf1rPX6y2pasPuMG3Mhl1JkiRpzKpJV68EngVWhxBuAp4Bhm5KjDHG/5+9+46Ts6z3Pv65ps9sb9nd7G56QhISEkJCQhOkSECRomJHEcUj6rGXx/PoweOD7VgQ9aBY4dhFFBBEkRKQHkjvPZvtbbZNn7meP2Z22fTsJpuZ3Xzfr9e+Zua+75n5zebO7Hznal85UcWdaka7ZXdo1+jSvBOztNGhJJLpkDaak2CNpnecPYnGYJgfPrGDUCyxX4v4gO2tfUD6C4ShXZgHeF2OYc7GfPD4Xo3ZFREREREZueGkq1uHXH/XYY6xgMLuCPlGeV3aoS27xoxeEE2M8ZZdYwxTy/MBaO2JMqU8/d/kkfXN3PrABi6eMwGvK/3aXA4HDcFDtOy6hteye6h1fZV1RURERERGbjhhd+qoVSFAOmTddu08zppcMiqPPzTsjqbYwJhdx9hs2QWoLEzPht3SE2FKebrL99Pb2mjuifDbF/cOBtHmngh7OkL43c79AqvH5SASH0bYjakbs4iIiIjIiXTMYddau2c0C5G0dy6dPGqPPTAb82mZ5XVGy9TyAAATCkdvEqzRVpmpvaU3OrhtV3s/Z04q5u1LJvHZP60FoLM/xobGbqaU5/GL9y7BkWnM9jgd9IQPDrCHE44ncTkMiSEBV2FXRERERGTkRneQqOQUr8vJ3e87m/nDWD92JD5z+WwunDWBhXXFo/o8o6myIB12W3sig9t2tfdzzvQyrl9SBwZ2tvXzoxU7eH5nJ1fOr6Kq6NVwP9xuzKFYEr/bSe+QJYjUjVlEREREZOQOG3aNMV8iPQb3NmttKnP7aDRBVY67cFbFqD+Hx+Xg/Jnlo/48o6nQ78LrctCSCbuhWIKm7ghTM7NYX7+4jtX1QX60YgcAU8v3n93a43IOa4KqSDyJ37N/2NUEVSIiIiIiI3eklt1bSYfdbwAx9p+g6nA0QZWMC8YYKgt9tPRESaYstz20CYCpFa+G2nkTCwevH7iUk/cILbvW2oMmCAvFkoPdzAeoG7OIiIiIyMgdabrcqcA0a21syO2j/UwbvVJFTq7KQi+tvRFe2NnBr1/YC8CsIeOdXU7HYFftutLAfvf1uBxEDxF2/7Cynqn/5+HB7tHxZIoP/+YVVtcH8bv3D7spteyKiIiIiIzYYVt2D5yQShNUyammOOChvjPEqvogAL9475L9wi7A/7xzET9esYMzJ+0/PtnjdBBLHLyc0N3P7gagqTvChEIfDV1hHlrbBMCZk4r57QeW8esX9vDXtU0KuyIiIiIix2FsLoQqchIU+910h+Osrg8yrTyP186ecNAxE4v9fPnqeXhd+7fKeg/TstsTiQPgcqa7MQfD8cF9AY+Tc6aXcdWCiYC6MYuIiIiIHI9hzcZsjMkD3gHMBMqAAxdStdbam05QbSJZVRxw0xWKsbo+yAUzhjfhlsflIJZMHTQ+d2A5ooE1eIOh2OC+gW7MzszxqWOf30pERERERA5wzGHXGHM28FfgSJ/6LaCwK+NCkd9NJJ4iEo8yd8hkVMfC43RgLSRSFrdzSNjNtOxGM12cu4e07PoyYXdgrV51YxYRERERGbnhdGP+DuABrgfKrbWOQ/w4j/IYImNGUcAzeH3oGrrHwuNK/9c6cEbmgfw60MU5GNq/GzOAI9Oyq6WHRERERERGbjhh9yzg29bae621naNVkEiuKPa7B69XFp6YsDsgGk+37A4Nu4PdmB0D3ZgVdkVERERERmo4YbcH6BitQkRyTXHg1bA7ocA7rPsOTFgVS74adiPxV2dnHmjZ7Ro6ZteTHlUw2LKrsCsiIiIiMmLDCbv3AZePViEiuabIPzTsjqxl9+F16WWF4skUb//J84P7o5kJqoaO2R1o2R0Iu8q6IiIiIiIjN5yw+zlggjHm+8aY6WboFLMi41Cx/9Uxu37P8IajL51ayswJ+fzXXzcSTSTZ1d7Pqr3Bwf2RxEA35ldbdgfG7A52Y9aYXRERERGRERtO2A0CZwO3AFuBhDEmecBPYlSqFMmCoiHdmIerrjTAB14zDWuhtSfK3o4QAJ9+3Szg1ZbdoevsOjIh15n5X6luzCIiIiIiIzecdXbvIb20kMgpocA7rGWoD1KVmdSqqTvC3s502L1+cR3f+sfWwfG73UMmqEpkxvcao5ZdEREREZHjdcyf5q217x3FOkRyzkBL60gNLFfU3JMOu/leFxUFXhxmyNJDQ1p245mw61TYFRERERE5bsfXdCUyzt35zkVMKc8b0X0Hlitq6Y5Q3xmirjSAMQaf20k0kSQST9LZH8OY9Pq7sWQ63A6M2U0eetUiERERERE5BsMZs4sxxmmMucEY8ytjzKPGmDMz20sy22tGp0yR7LhifjVzqgtHdN9Cnwu/2znYsjup1A+A1+UgEk/RGAwD8MlLZ1FT7OctZ9UCWnpIREREROREOOaWXWNMAPgHcC7QDwSAkszuHuDrwM+B/3uCaxQZk4wxVBX52NLcy672fl53eiWQXoM3mkiyrysddpdOK+Ojl8wcvJ8j8xWUVTdmEREREZERG07L7q3AYuBaYBowOKDRWptE6/CKHKSy0Mu/treTSFmunF8NgM/tIJpIUd+VnrSqtsS/330GxuwmFXZFREREREZsOGH3LcBd1tr7gUONJtwOTDkRRYmMFwvr0p0fplXkMTfTHdrrcnL/6kb+48/rcTvN4NjeAQ6HujGLiIiIiByv4UxQNRFYc4T9IaDg+MoRGV8+/bpZLJlSQm1JYHBJIa/71e+Y4kk7OCHVgIExu2rYFREREREZueGE3Q7gSBNQnQ40Hl85IuOLy+ngkjmV+23zuZxHvI9TE1SJiIiIiBy34XRjfgy4MTNR1X6MMVOB9wGPnKjCRMargZbdKWUB/vLh8w7aPzBBlcbsioiIiIiM3HDC7pdJz778EvAhwALLjTFfA14BosDXTniFIuPMQDfl6xbVsrCu+KD9A92aU2rZFREREREZsWMOu9ba7cAlQAL4L9KzMX8a+BxQD1xira0fjSJFxpPeSByAigLvIfcPhGFlXRERERGRkRvOmF2stS8DC4wx84A5pAPvNmvtqtEoTmQ86okkAKjIP3LYVTdmEREREZGRG1bYHWCtXQ+sP8G1iJwSjtayq27MIiIiIiLHb9hh1xgzEbgKmJbZtBP4q7W24UQWJjJe9YQzLbuHC7uajVlERERE5LgNK+waY74I/F/AfcCu7xtjbrPWfvmEVSYyThX4XITjScoP043ZZEbSp9SNWURERERkxI457BpjPkJ6RuaXgO8CGzO7Tgc+AXzJGNNhrf3BCa9SZBz5/QfP4aXdnXhch54fzjk4QZXCroiIiIjISA2nZfejwIvA+dbaxJDta40x9wLPZI5R2BU5gqnleUwtzzvs/oExu8nUyapIRERERGT8Gc46u5OA3x4QdAGw1saBX2eOOSbGmDpjzBPGmI3GmA3GmI9ltpcaYx41xmzLXJZkthtjzB3GmO3GmLXGmEXDqF1kzMg07KplV0RERETkOAwn7O4FCo6wvyBzzLFKAJ+y1s4FlgEfNsbMBT4PPGatnQk8lrkNcAUwM/NzM3DnMJ5LZMwY7MasCapEREREREZsOGH3B8AHjTHVB+4wxtQA/wZ8/1gfzFrbZK19JXO9F9gE1ABXA3dnDrsbuCZz/WrgHpv2PFB8qFpExrrBbsxq2RURERERGbHhjNntBlqAzcaYXwGbM9vnAO8EtgI9xpgbht7JWnvP0R7YGDMFOBN4Aai01jZldjUDlZnrNUD9kLvty2xrQmQcMcZgjFp2RURERESOx3DC7i+HXP/QIfafdcAxABY4Ytg1xuQDfwI+bq3tMQMDFgFrrTXGDOsTvzHmZtLdnJk06ZiHEIvkFIcxKOuKiIiIiIzccMLua0/0kxtj3KSD7q+ttfdlNrcYY6qttU2Zbsqtme0NQN2Qu9dmtu3HWnsXcBfA4sWLFRdkTHIao27MIiIiIiLH4ZjDrrV2xYl8YpNuwv0ZsMla+50hux4A3gN8PXN5/5DtHzHG/A5YCnQP6e4sMq64nYZ4QmsPiYiIiIiM1HBadgEwxgSAItJhM3Qcz30e8G5gnTFmdWbbF0iH3D8YY24C9gDXZ/Y9DFwJbAdCwI3H8dwiOS3gddEfS2a7DBERERGRMeuYwq4xpgL4DPAmYMqQ7btJd0P+lrW29ZB3Pgxr7b8Ac5jdlxzieAt8eDjPITJW5XmchGIHLWktIiIiIiLH6Khh1xizDPgLMAGIA+uBHqAQmA18Gni3MeYaa+0Lo1iryCkj4HHRH1XLroiIiIjISB1xnV1jzATgQcBLulW12Fq7wFp7gbV2AVAM3JLZ/2DmeBE5TvleF/1RteyKiIiIiIzUEcMu6VbbQuASa+2d1trw0J3W2rC19kfApZnjPjU6ZYqcWgJedWMWERERETkeRwu7rwf+11r7ypEOyuz/FXDViSpM5FSW59EEVSIiIiIix+NoYXcK8PwxPtYLwOTjqkZEAMjzOtWNWURERETkOBwt7CYB9zE+litzvIgcp/QEVQq7IiIiIiIjdbSwuw147TE+1kWk18AVkeOU53USiiVJr7glIiIiIiLDdbSw+xfgOmPM8iMdZIy5HLgOuO9EFSZyKsvzukikLNFEKtuliIiIiIiMSUcLu7cD9cBfjDFfM8ZMG7rTGDPNGPNV4H5gH/C90SlT5NSS50kvgR3SJFUiIiIiIiNyxLBrre0FLgf2AJ8DthljgsaYPcaYLtLdnD8P7AWuyBwvIscp4HECaNyuiIiIiMgIHa1lF2vtVmAh8DHgX0ACqCY9GdXTwMeBhdbazaNYp8gpJc+bbtnt11q7IiIiIiIj4jqWg6y1YeD7mR8RGWWDYTeqbswiIiIiIiNx1JZdETn58jLdmENq2RURERERGRGFXZEcFPCoZVdERERE5Hgo7IrkoPzBbsxq2RURERERGQmFXZEc5B/oxhxXy66IiIiIyEgo7IrkoIGlh8IasysiIiIiMiIKuyI5yOcemKBKLbsiIiIiIiOhsCuSg5wOg9flIKxuzCIiIiIiI6KwK5Kj/B4nYbXsioiIiIiMiMKuSI4KuBV2RURERERGSmFXJEf5PU7NxiwiIiIiMkIKuyI5yu9xElHLroiIiIjIiCjsiuSogNul2ZhFREREREZIYVckR/nUjVlEREREZMQUdkVyVMCtbswiIiIiIiOlsCuSowIeJ6F4IttliIiIiIiMSQq7IjnK53ESjqWyXYaIiIiIyJiksCuSo9Lr7KplV0RERERkJBR2RXLUwDq71tpslyIiIiIiMuYo7IrkKL/HibUQTagrs4iIiIjIcLmyXYCIHFrA7QRgS3MvDcEwj29uZXZVAe+/YFqWKxMRERERyX0KuyI5yu9Jh93337OStt7o4HaFXRERERGRo1M3ZpEc5fekv4saGnTzvfp+SkRERETkWCjsiuQof6YbM8DZU0sp9LmIJpKkUpqwSkRERETkaBR2RXJUge/VVtxbrzqdT19+GvGkZeWeLhJJTVolIiIiInIkCrsiOeqsySV89dr5fO26+cypLmBikR+A63/8HPc8tyfL1YmIiIiI5DYNABTJUW6ng3csnTR4u7rYN3i9MRjORkkiIiIiImOGWnZFxoiaYv/gda9b/3VFRERERI5En5hFxogiv5tZlfkABEPxLFcjIiIiIpLbFHZFxghjDP/4xIVMK88jGFbYFRERERE5EoVdkTGm0O+mR2FXREREROSIFHZFxpjigFvdmEVEREREjkJhV2SMKfa7CYZj2S5DRERERCSnKeyKjDFFfjfdatkVERERETkihV2RMaYo4KEnkiCZstkuRUREREQkZynsiowxxX43gCapEhERERE5AoVdkTGmOJAOu90KuyIiIiIih6WwKzLGFGVadrtCmqRKRERERORwFHZFxpgCXzrs9kUTWa5ERERERCR3ZS3sGmN+boxpNcasH7Kt1BjzqDFmW+ayJLPdGGPuMMZsN8asNcYsylbdItmW73UB0K+wKyIiIiJyWNls2f0lsPyAbZ8HHrPWzgQey9wGuAKYmfm5GbjzJNUoknMGwm5vRGFXRERERORwshZ2rbVPAZ0HbL4auDtz/W7gmiHb77FpzwPFxpjqk1OpSG7J96llV0RERETkaHJtzG6ltbYpc70ZqMxcrwHqhxy3L7PtIMaYm40xK40xK9va2kavUpEsyfM6AeiPJbNciYiIiIhI7sq1sDvIWmsBO4L73WWtXWytXVxRUTEKlYlkl9flxON0qBuziIiIiMgR5FrYbRnonpy5bM1sbwDqhhxXm9kmckrK8zrVjVlERERE5AhyLew+ALwnc/09wP1Dtt+QmZV5GdA9pLuzyCknz+vS0kMiIiIiIkfgytYTG2N+C1wElBtj9gH/CXwd+IMx5iZgD3B95vCHgSuB7UAIuPGkFyySQ/IVdkVEREREjihrYdda+/bD7LrkEMda4MOjW5HI2JHvdakbs4iIiIjIEeRaN2YROQb5PrXsioiIiIgcicKuyBikMbsiIiIiIkemsCsyBhWoG7OIiIiIyBEp7IqMQXleF31aZ1dERERE5LAUdkXGoHyvi/5YklTKZrsUEREREZGcpLArMgble9MTqYfiySxXIiIiIiKSmxR2Rcag4oAbgI6+aJYrERERERHJTQq7ImNQbUkAgH1d4SxXIiIiIiKSmxR2RcagulI/APWdoSxXIiIiIiKSmxR2Rcag6iI/LofhgTWNPLO9PdvliIiIiIjkHIVdkTHI6TBMLPbz7I4OPva71ZqVWURERETkAAq7ImNUODMTc3tflI1NPVmuRkREREQktyjsioxRPver/32f3NKaxUpERERERHKPK9sFiMjI/Pw9S1jX0M2PVuxgdX0w2+WIiIiIiOQUteyKjFEzKwu4blEtdSUBLUEkIiIiInIAhV2RMa6mxE9DUGFXRERERGQohV2RMa6m2E9vJEFPJJ7tUkREREREcobCrsgYV1PiB6BRrbsiIiIiIoMUdkXGuJridNht0LhdEREREZFBCrsiY9xAy67G7YqIiIiIvEphV2SMK8/zUuR388KuzmyXIiIiIiKSMxR2RcY4h8Pw5rNq+fv6Zlp6ItkuR0REREQkJyjsiowD7142GWPg8tuf4tLvrCAUS2S7JBERERGRrFLYFRkHppTn8ev3LyMST7K9tY91+7qzXZKIiIiISFYp7IqME2dPLeWpz74WgHUNCrsiIiIicmpzZbsAETlxJhT4qC7ysao+SDJlcTrMEY8PhmL88IntOB0OPn/F7JNUpYiIiIjI6FPYFRlnzqgt4qG1Tezp6OePHzwXv8d52GP/84EN3L+6EYDXzCzn3Bnl++1fsbUNh4FkyrKgtpiSPM+o1i4iIiIicqIo7IqMM+87byrBUJwXdnVy5R1P87nls/G5HfRHk1QX+1g0qYTucJwP3LOSF3d1cuN5U3hkfTO3PbyJT19+GosmlVDkd/PwuiY+/JtXsDb9uNMq8vjUZadx2dxK3E6DMUduNRYRERERySZjBz7JjkOLFy+2K1euzHYZIlnx4JpGfvD4dra09O63fXZVAV6XgzX7url0TiXfvn4Bz2xv55ZfvwLA4skl/OYDy7j2f54hmbJMLc+jJM/DPza00N4XxWFgfk0R991y3lG7SYuIiIiIjCZjzMvW2sWH3KewKzJ+dYfjfO+f21g2rZTJZXk8trmF+1c1sqWll9I8D6988bLBY3+0YgeNwTD3PLeHxZNLWLmniy++YS43nT8VSHdlfmprGz9+agfP7+zke29byNULa/jHhmYeXNvEbdfOo9DnztZLFRERGddCsQR/XdvE0qnpv+kikqawKyKDOvqivOXHz3HLRTN481m1B+3/+t8286MVO3A6DM987mKqinz77U+mLMtvf4ptrX3UFPtpCIYB+Ozy07jlohkn5TWIiIicKv6yqoH7VjWwvqGbzv4YtSV+7v/weZTle7NdmkhOUNgVkWNmreWVvUG8LgfzaooOeUxbb5T7Vzfw7I4Olk4t5fHNrexs7+eJT19EvldTAYiIiIzUn1ftIxxLUV3k4zP3rqW9L0pdqZ85VYVcOqeSL96/ngW1xfz43WcNThyZSln+9Mo+aksCnDO9bETPu7o+SLHfzZRytRrL2KKwKyKj6pW9Xbzpzme5YGYFl82t5Ip5VXhcDh7d0MLW1l5W7w1y27XzmDGh4IQ955bmXu55bjefXT6bIr+6T4uIyNhQ3xli7b5uFk8pYUKBl53t/dQU+4nEk6zaG+TGX740eOzMCfm8dUkdN5wzBY/LAcD9qxv4+O9X43U5eM+5U/jc5bN5aF0TH/3tKgB+/O6zuPz0qkM+dzAU4/mdHVQU+JhekcevX9hLbUm6l9Z3/rEVh8Nw5zsXccmcytH/RYicIAq7IjLqvvvoVu56aifheBKvy0E0kdpvf22Jn0c/ceERl0I6nHAsmflmOwCkW5+vu/NZVu0NsmxaKb9+/7ITPllWOJZkW2svc6oLcTsdRzy2qz9God896hN2JVOWzv4Y5fkezYYtInKCRTJ/v0b6/jrwmfrA+zd1h3lobRMXzKxgXUM3//HndYN/Iwf+Xhb53QQ8Tpq6IwB88Q1zcRi4asFEyg/RXXlrSy93PrmDP69qoMDrojeaoK7Uj8MYGrrCfPnq05lfU0RjMMLpEwupLfETTaS48o6n2dnWD0Chz0VPJDH4mNMr8nA5HPTHEnxu+WweWd/Mt69fgM89/L/bIieTwq6InBTWWra29HHbw5t4amsbVYU+zppcwvVL6njPz19k0aRiJhT4uHxeJXkeF5fOqcRxQEBs74tS3xnC7XRw+z+34nU52d7ax462Pr563XzeclYtz+7o4J0/fYG51YVsbOqhptjPxy6dyfWL607Ia3hwbRPff2wb21r7qCr0Mae6gPa+GJ7Mt+gLaou447Ht9EcTFPhc/PHlfRT4XJTne7lgZjlffuPpoxJGP/a7Vdy/upFrz6zhu29deMIfX0TkVLKmPsjf1jdT6HdRXeTjP/68nivmVfPfbz7joL9NR/LTp3dy78v7CIbizKoq4JfvXTJ4/3gyxSXfXsHezhCleR46+2OcO72Mj186izX1QVp6IkwuC/Di7i42NHazdGoZ+V4n//H6uUd9XmstP3h8O5uaeyjye3jL4lqaghE+/cc1hOPJ/Y6dUOBl0aQSHtnQzPfetpDWnijfeGQzn7hsFhfOqqAs30N5vpfnd3bw7p+9OHi/r183n7edPemYfxci2aCwKyInVSKZ4rmdHZwzrQxXplX0Ny/s5UcrdtAbidMVigOwoK6Y266Zx4RCLxsbe3hgTSP3vdIw+Dh+t5OyfA+hWJK60gBr6oOcO72MV/Z2URLw8MSnL+Ijv1nFk1taSaQst1w0nekV+ezrCnPJnAn43A62tfQxqSxAbyRBS0+EaDyF02G49+V9XDm/inefM4VkynL/6gY2NPawp6Off25qZWKRjw9eOJ0/r2ogGIoxtTyPfV1htrX24XIYPC4HJQEPjd1hrjpjIoV+F/WdYVZsbePaM2uYWp7HxbMnUFcSYMW2Nv7wUj3VRT4++bpZPLO9g6/8dSOvm1vJV6+bf8SW44H36H1dYS7+9pPEk+nbv795GUunjWxclojIqSKVsvx5VQNr9gV597LJTK/IZ2NTD1uae/nUH9fgdprB99XyfA/tfTHee+4U3rVsMrUlfl7Z28Vjm1pZMqWUy0+vJGWhpSfC9/65jR1tfXSH42xr7WN2VQENwTC9kQRzqgv594tnMGNCPp/901pW7Q3ytiV1/O6les6eWsqvblo62CV5tF7zx36/mo6+KJ+8bBabm3u566md7O0M8d5zp3DrG08H0i3Zh2q1fWJLK//Y0MJTW9toCIaZVp7HZ5efxvJ51aNWs8jxUNgVkZzRF02wam8XrT1Rvva3TXT0xxj6NnT94lounVPJyj1dXDx7AsumlWGtJZmy3PPcHn60YgetvVG+8ab5vHXJJKy1RBMpvnDfOu5b1XD4Jz6Aw0DKwgUzy2nrjbK5uRef24HL4eADF0zjoxfPOOib/WTK8stnd/PSrk6+eNVcaor9xJOpwbBqreXjv1/NI+ubD+rGPbU8j4ZgGJN5HGMgnrRcs3Ai779gGrOrCga/GADY2dbHVx/exJNb2ijL99DSEwXgTx86hw/96hVmTMjnNx9YNszfvkjuicSTNATDOI3BYQyTygLZLknGqGTKsq8rRFtvlIfWNdHSE6GpO8KqvcHB93y/2znY6jm7qoB7P3QuHX1RmrojLKwr5vN/WstfVjcC4HIYEpn3a2thyZQSWnuj7OkI4XIYlkwpxeU0vO70Kt559iSMgR8+sZ37VzeyrbWPSaUB9naGeM2sCu6+cQnP7uhgfm1RVpbpq+8M8eSWVt6xdPIxD7nZ09HPb1+s59GNzXSHE3zzzfPZ0tzHTedPHdWwLjJcCrsikpO6Q3F+9swuvC4Hp08spL0vxnVn1hyx+5i1lmAoTnHAfVBX4frOEP2xBKV5Hp7d3kEyZZlWkcfOtn7KC7zUFPtwORzUd4WoKfbzt/XN/HFlPV6Xk49cPIM3nFF9wrofB0Mx/ra+mXAsSWWhj+XzqmgMhvnp0zvxup3cctF0fvHMbu54fBvWwrJppXzhyjnMrykikbJc9N9P0huJc9WCidR3hZlaFsAYw39eNZefPr2L2x7exNevm8/5M8upLdk/HEQqku6/AAAdWElEQVTiSZ7e1k5tiZ851YUn5PWIjAZrLTfdvZLHN7fiMGCBq86YyEcvnsHMyhM3oZ2Mf1uae7nxFy/SmBnz6nE5mJSZ5+HG86Zw2dxKHljdSGMwQl2pn8c2tfLZ5adxRm3xfo8TiiX4y6pGYokkTT0RFk8u5eyppfzp5X387qW9lOZ5uGxuFUunlh52xYJIPMkV33uaXe39fPTiGXzqdaeN7osfZc/uaOcdP3lh8PbXrpvP209Q1+ZUyrJiWxslAQ8L64qPfgeRQ1DYzVEd/XsodBfj9hz6zVJExr9d7f08tqmFrz68iZSFs6eW8uKuTgB+esNiLp178IyYfdEEb7/redY1dGMMfG75bOZWFzK5LMDksjy+/9g2vv3oVpwOM9ilekpZeimJS+ZMwOUwWMDtdBCOJVlV30VdSYAH1zayq62fWZUFVBf7uHROJT63k1TK0h9LsKcjxMRi/+Baj284o3q/1miRQ7HWsq8rTE2xH4fD0B2Kc9PdLxHwunAYeHJLenz/lfOr8bgc3PPcbiLxJL+6aSnnzijPdvmSZcmUpS+SoNDvoiecIOB1Ek2kCMeSVBSkJ26KxJO86c5naemJ8MnLTqM838PSqWUUBbI3U/+KrW3837+s4w8fPIfqIn/W6jgRrLX89sV6yvM93PH4NrY09/KVq+cdcizvrvZ+tjT38NC6ZgzwmctPo640wK72fqKJJO29MSYUemntibK6vovfvlhPQzAMwK1XzeW95009ya9OxgOF3Ry0dcd91O/5DHHXa1j+ml9kuxwRybL6zhDf/PsWHlzTSL7XlW55/tgFh23lTqYsL+zq4J5n9/DIhmYAFtQW8av3L+VNdz5LJJ6iJOBmS0svkfirXaonlwXwOB0Ew3GqCn0090Ro640O7q8o8A7eXlBXzBsXTOR3L+5lW2vfQTVUF/l4/fxqJpfncc600hO6tJTkvmAoxsbGHs6aUoLXdejZWrtDcW74xYusqQ9SU+zH7TR09sfoiSQoCbhxOhy87/wpfOjC6YO9Kjr7Y1zzw2fY2xninUsn8YUr55Cn9bsPaW9HiC0tvUyvyGNaRX62yzlmnf0xXtrdyeamXp7d0c5VCybyjrMn0ROJ0xiMUOBzsacjxLcf3cLGxp7B2Yp7I3EmFPho64uSsul5GnZ3hNjY2MOu9n5+csNiLjvEF4Ry4ry0u5PP/HENuztC/OYDSzlnWhnGGKy13P7PbXz/8W2kLBQH3MQz/26nVRXw/M7OgybNgvRQoqsX1vDAmkZe3t3JY5+6iKoiXxZemYxlCrs5aPNLq1jfeDM/cb6f/1p2DUvL9eYscqqLJ1Nsa+ljxoR8EqkUAc/RP+Bba1mxtY0fPL6dlXu6Brd/+Y2n846lk0hZS0t3lHA8SWMwzG0Pb6KtN8oZtUUkU5Yiv5vzZ5bTE06wfF4VU8vzaO6O8PzODv7fQ5to74tS4HVx0wVTqS0JUN8ZYn5NEfFkivtWNfDoxhYAPE4HVy2YSG2Jn4DHSXm+l2gixcK6YuZOVFfq8WZvR4i33vUcTd0RigNu3rhgIpWFPi6ZM4GSgIciv5tEyvKR37zCM9vbueWiGWxu7sHjcpLvdbJ8XjUXzqo47OM/tbWNL92/nvquMAtqi/jFjWdrPe2Mlbs7+c2Le+mLJHh8c3pyPoCFdcXkeZ289rQJvLK3i5d2dw1OQLSgtojigIeJRT76okke39zC0qllvP+CqcyYkH/SljKLJVJ86x9b+OUzu4kl01/CVRf5aOqOUJrnoSccH3w9kF6ybvnpVVQV+djS3Eu+z8XGxh7m1RTR1B3m4XXNBDxOZlcVcP3iOs0afJL0RRO89ltP0tYb5TWzKnj9/Cq++cgWOvpjXHtmDe9aNplZlflsbOzhG49spieSoDzfw5XzqynP99LRF6W6yI/TYbjotAqMMezp6Oey7z7F7KoCPn7pTGpLAkws9pN/iC+6QrEETd0R6koCdPRHqe8Mc/bU0iz8JiRXKOzmoNU79/K/q+/k1yVv5Vv7nudd7/63bJckImNYZ3+MRV95lLpSP2fWlfBfV59OccBz0HHJlCWaSB5zkG7ri+JzOw87ocrm5h6i8RS/e2kvf13TRG80cdAx82uKuObMGpZMKaGjL8aMCfnUlQaIJ1Os3N3Fk1tb6QknuHBWOZfMqTzqusYnQiSeJJWZ+CwYitMdjlPkd5PndbG3M0RFgZdoPMnksrxRWz85lbLEkik8TgfGHLw2Zy77/J/W8udVDXz12vk8ubWNv29oJnbApGwDk/p89dr5vGPpyELI39Y18e+/W0VdaYAz60pwGMj3uQZD3JyqQiaVBZhdVTB4vu9s62Plni4WTSqhosDLy3s6cRjDWZNL8LmdJ+X8Gg3/2NDM/z6/h39tb6fQ56Y838OyaWW86axaXtjZyQNrGgnHEuzuCFHkd3PZ3EryvS6CoRgbGnvoCsVp74viMHDmpBLWN3QTTaSoKvTxzqWTuPnCafzq+b10h+Pp8dMWGoNhJpUGaAiGiSctp08s5F3LJhNLpmgMhplRkT+sJXp+8tRObnt4E9cvruWtSyYxqzKfPI+LB9c28vS2dqoKfcydWEhfJIHbZbhkTuURJ3NqDIbxu52U5B38Xieja09HP39Z1cgPnthGPGmZXVXA25bUccM5U4Z1Tgx1+z+3cvs/tw3eLvS5uGxuFRedVsGmph4cxvD09nbW1AcByPM4cToMvdEEt791IW84Y+Kor3cvuUlhNwf945d/5r9L4tQXlHNHw2pe9+5PZrskERnjWnoilAQ8WZ0lM5myROJJmnsiOI3hyS2t/H7lPjY19Qwe43YayvK89ETihGJJ3E5DwOOiOxwnz+OkrjRATzjOJXMqeeuSusFJYA4V1Lv6Y7T1RdNrMbf2Mbk8j8oCL/2xBH3RJH2RBP3RBH3R9GXSWna39/PElrZjej2VhV6qi/wsn1dFvtdFWZ6Hne39hGLpUP/3DS0U+d1cOqeSBbVFFPjSXcdnVxUwuyq9PvOX7l/PlpZeJpUGqC7ysbWlj9aeCG19UZIpS4HPTUnAzZsW1RLwptf7rCryUVXoo7LQh9NheGFnBy/s6uS6RTXUFPuzEoyf3tbGH1fuw+Ny8OCaRq5bVMvXrpsPQDiWJBiOcd8rDQQ8TnojCXrCcWZVFnD9kuNb//q5HR185t41xJMpHMbQF0ngdBpC0eRg6yDArMp8HMawpaWXQ320MQZqiv388B2LWJDFiXBSKUvSWlwOM/jvGE+m2NLci9vpwONyUJqXbh1v7o6wqamHp7a18YtndlNT7OdNi2q4+cLph2zxstbS0R8j3+s65JIyQ7X1Rvnb+iYe3djC09vamVIWYHdHaL9jigNugqE4BT4X+V4XTd0Rppbn0d4XpTeSYPnpVdzy2unMm1hEKJ7EYaC9N0YilaLA56YszzP4hc6KbW2875cvsXhyCX/8t3NP3C9UsmpbSy/3rWrgxnOnMKHw+Lofp1KWDY099McSNHdH+OemFv61vZ1gKD4410RJwM0N50yhqsjH6vogrT1RGoNhNjb1UJ7v5ZLZE3C7DIU+Nxb417Z2Lp49gU9cNuug52rsDlNV6NPcE+OAwm4OuuMTX+I7l7+eWb3redemV7jhSz/MdkkiIqNmX1eINfXd+NwOnt/ZQXc4TsDj4pzpZZw3oxy/28kTm1t5cmsru9r7yfO4eGpbG5F4ijyPk6oiH539MbrDcSYWp7u/5XlcbBwSoo8m4HFiLSRSKd533lRK8zw4jKEo4KbQl578pjscH1wzOd/nYt2+bna19x/0PE6HIZmyXDCznNaeKFtaeg96vqrMB7/eSJyLZk9g7b4gXf1xFtYVM6HQS2Vmf1tvlOd2dAxO0jJUeb6HOdWFPL2tfXBbTbGf8gIvyVSKt589iWsW1vDyni7+sLKeAp+Lzv4Y155Zy/J5Vcf8uzkWl31nBdta+yjP9zC5LI/b37qQutLsLRPUHYoTDMfY3trHhsYeVtcHcToMsyrzecMZE3l6WxvJFCyoK2J7ax8NXWEeWtdEV3+MaRX5TKvIoyzPy4K6Il7a3UkyBW9bUscZtUX7fZmQTFl6wvFjbj3si6a7Fzd3h2noCuNwGNr7Yry4q4OuUHywBbym2E9pnoeUtWxv7dtvuTKPy0FdiZ/W3nSoBHjfeVP5wpWzT/gH82TKcttDm3hhVwfvOXcK1y+uw1qLteBwpLuXVhR4CXhcPLaphf95cgdFfjczJuRz11M7AfC5HfvNDTCgyO/O/F93Eoqlx2ve8fYzeeOCiSf0Ncj4FYoleH5nB0umlOJ2OnA6zEG9M8KxJP/c1MLf1jfx9NZ2XE5DbyRBylq8rvRSUxfOqmDRpBKe2NLK9tY+wvEkyVS6Rfr0iUV09EdxOx28bUkdAY+LrlCMJ7e0csHMCl4/v3rErdVycijs5qBvfvHj/PCMN2Ne7uaavHXc/sXPZ7skEZGc0hOJ85sX9tLcHaGpO0yR301FgZfGYIREytLeG2XptFJmTMinpji9zNKGxh4i8SR5Xhf5Xmfm0kXA48LpMCSSKaKJ1LAnPOrsjxGJJ2nqDjO5LA+f20lXf2ww7AVDMdbu66apO8zCuhI2N/fwl1UNJFKWj186k7Mml+4XIA6USKaIJ23mOSK09ERo7A6zYksb29v6uGJeFdeeWcPfN7Twp1f20RtJUJbnYXNzL16Xg3gyRVm+l1gilf5Jpga7hJ49Jb1EyuyqAkryPCSSKVZsbaMhGOaNCyZS6HMP1nS4GvujCebf+nc+cvFMPnlAC8lY0hgM85W/bqQ7HGdPR4i2viixRIp8rwsD9EYT5HtdzK9Jj2nf0dZHd2Yc6bTyPM6aXEJ5gZfm7ggd/TF2tPYxrSIPa9OtswsnFfPg6sbB5W8KfS5SNh36zppcQnWxD7/bicMY1jV0E0uksMCsCfksqCumK5Red7whGGZfVwiD4cLTKsj3urhyfnVWf3eHsqGxm3X7ulnf2E1dSYCUhbI8D163g/rOELvaQ0wuC9DaG+GsySVMLsvjzLriMdVlX8amcCxJJJ4k4HXyhfvW89LuTvZ2hphdVcCyaWXkeZ0U+Nz8cWU9kXiKAp+LxmCYnsirQ3E8LgexRIqLZ0/gJzcsVhfpHKawm4O++I2bWFc0ne1FC5jduoF7P/bZbJckIiJjQCKZIpGyeF0OXtkb5G/rmvC6Hdxy0QzyvC56I3HueGwbrb1RVtcH2ZPpmmoMLJ1ayit7gvt1/3UYuGBmBVuae4kmkhT63fzllvMGWzJDsQR/XdPEZ/+09rDLYY1Vnf0xWnvTXXOjiRT3r2pge2sfT25tw2EM50wvo9jvpsDn5vmdHWxq6qGjP0Z5vofSPC91JX4au8O4HA5CsQRbW/qoLfHzzTedwczKgsGlcUQku5Ipy56OfqaW5x32y5buUJztbb2DvSzOmlzC3c/u5qsPb2bZtFKK/G6mlOXx/gum7fd/u6s/Rm8kQZ7XSWtvlNMqC9QSfJIp7Oag737uQzy4cAldGz2c59/CD77wlWyXJCIi41BLT4StLb08va2dXz2/h+WnV/GaWRVMLPazpj7Iro5+fvviXs6fUY7H6eCxza0U+d2cN6OM9Q099ETiBENxAF74wiWD3a9PVdbaQ35YttbyxJZWFtaVUKoJk0TGBWstn/rjGh5e10RVoY+GYJhCn5sr5lcxqTTAhsYeHlrbtN8s4tPK8/jQRdOZVVlAPJliVlUB+zrDbGnpwetysqCumIlFPvVwOIEUdnPQF772GXaXVLLXX8dF4dX8v3/7WrZLEhGRcS6VsodscejLdN8FeHJLK/evbuSvaxuZW13IpLI8HtvUgtNhWHfr5Se7ZBGRnLG5uYdv/2Mrz2xvJxRLUp7vYfm8Ks6oKaa9P0ppwMNdT+9kZ1v/ER+nstDL6+enx66fPbWU182tVGvwcVDYzUE/+/jnWFfQzKRICX2+Nr70lV9nuyQREZFB3eE4BV4XDochHEvSE4mf8q26IiIA0USSUDR5yInrUinL5uZeGoNhktaytbmXKeV5zK4qIBxPsro+yD83tfLU1rbByd3K8jwU+t1MKQswr6aIPK+LZMpy78v7CMeS1Jb4qSnx4zTpWakH8pvDYagrCTB9Qj5OY6gq8hJLWLrDMfZ1hVm5u4uKAi+leR6qi3zk+1w4jMn8pCdbLMv3Ek+mmDexiJ5InPUN3QRDcSYUeplekU9XKMbpE4tO8m94eI4Udoc3Q0eWGWOWA98DnMBPrbVfz3JJIxati3NaYzUtBT5qegqzXY6IiMh+ivyvrm/q9zjxe468lI2IyKnC63LidR36PdHhMMydWMjcienP95efvv/M+GfUFnPDOVOIJVI4HYa/rW9ixZY2QrEkW1p691sab3ZVAYsmlVDfFWLV3iCWdMg1GIyBWCLFn3saDrncGsCUsgD/2h6jL5o49AFD6zaQOszjbPyvy/db9m8sGTNVG2OcwA+By4B9wEvGmAestRuzW9nI7GwxTPeU4rUxik8rzXY5IiIiIiJyknhc6SWU3nDGRN5wxqvLcSWS6Rn1kymbnin+KGN7I/Ekuzv6SSTTy5gV+d1UFvrwuAwzJhSQSqUjcmMwTCSeJGXTE3alrCWRsrT2RAjFkqxv6GZSWYDqIj8zJuTTFAyzva2PCQVeHGN4fPGYCbvA2cB2a+1OAGPM74CrgTEZdie6LG3uMBPDAd7ywVuyXY6IiIiIiGSZy+kY1nraPreT2VXpVuR5NQd3Nx4YC3y0ddGvObNmv9tTy/M4d0b5MdeRq07syuSjqwaoH3J7X2bbmBQwTmr6vMTDTdkuRUREREREZNwZSy27x8QYczNwM8CkSZOyXM3h/dtt/53tEkRERERERMatsdSy2wDUDbldm9m2H2vtXdbaxdbaxRUVFSetOBEREREREckdYynsvgTMNMZMNcZ4gLcBD2S5JhEREREREclBY6Ybs7U2YYz5CPB30ksP/dxauyHLZYmIiIiIiEgOGjNhF8Ba+zDwcLbrEBERERERkdw2lroxi4iIiIiIiBwThV0REREREREZdxR2RUREREREZNxR2BUREREREZFxR2FXRERERERExh2FXRERERERERl3FHZFRERERERk3FHYFRERERERkXFHYVdERERERETGHYVdERERERERGXcUdkVERERERGTcUdgVERERERGRcUdhV0RERERERMYdhV0REREREREZd4y1Nts1jBpjTBuwJ9t1HEU50J7tIkSOgc5VGSt0rspYoXNVxgqdq5LLJltrKw61Y1yH3bHAGLPSWrs423WIHI3OVRkrdK7KWKFzVcYKnasyVqkbs4iIiIiIiIw7CrsiIiIiIiIy7ijsZt9d2S5A5BjpXJWxQueqjBU6V2Ws0LkqY5LG7IqIiIiIiMi4o5ZdERERERERGXcUdrPEGLPcGLPFGLPdGPP5bNcjpzZjTJ0x5gljzEZjzAZjzMcy20uNMY8aY7ZlLksy240x5o7M+bvWGLMou69ATjXGGKcxZpUx5q+Z21ONMS9kzsnfG2M8me3ezO3tmf1Tslm3nFqMMcXGmHuNMZuNMZuMMefofVVykTHmE5m//+uNMb81xvj0virjgcJuFhhjnMAPgSuAucDbjTFzs1uVnOISwKestXOBZcCHM+fk54HHrLUzgccytyF97s7M/NwM3HnyS5ZT3MeATUNufwP4rrV2BtAF3JTZfhPQldn+3cxxIifL94BHrLWzgQWkz1m9r0pOMcbUAP8OLLbWzgOcwNvQ+6qMAwq72XE2sN1au9NaGwN+B1yd5ZrkFGatbbLWvpK53kv6A1kN6fPy7sxhdwPXZK5fDdxj054Hio0x1Se5bDlFGWNqgdcDP83cNsDFwL2ZQw48VwfO4XuBSzLHi4wqY0wR8BrgZwDW2pi1NojeVyU3uQC/McYFBIAm9L4q44DCbnbUAPVDbu/LbBPJukx3pDOBF4BKa21TZlczUJm5rnNYsul24LNAKnO7DAhaaxOZ20PPx8FzNbO/O3O8yGibCrQBv8h0uf+pMSYPva9KjrHWNgDfAvaSDrndwMvofVXGAYVdERlkjMkH/gR83FrbM3SfTU/drunbJauMMW8AWq21L2e7FpGjcAGLgDuttWcC/bzaZRnQ+6rkhsy48atJf0EzEcgDlme1KJETRGE3OxqAuiG3azPbRLLGGOMmHXR/ba29L7O5ZaAbXeayNbNd57Bky3nAG40xu0kPAbmY9LjI4kz3O9j/fBw8VzP7i4COk1mwnLL2AfustS9kbt9LOvzqfVVyzaXALmttm7U2DtxH+r1W76sy5insZsdLwMzMLHce0pMAPJDlmuQUlhlr8zNgk7X2O0N2PQC8J3P9PcD9Q7bfkJk9dBnQPaRbnsiosdb+H2ttrbV2Cun3zsette8EngDenDnswHN14Bx+c+Z4taTJqLPWNgP1xpjTMpsuATai91XJPXuBZcaYQObzwMC5qvdVGfOMzs3sMMZcSXrcmRP4ubX2tiyXJKcwY8z5wNPAOl4dB/kF0uN2/wBMAvYA11trOzN/DH9AuptTCLjRWrvypBcupzRjzEXAp621bzDGTCPd0lsKrALeZa2NGmN8wP+SHofeCbzNWrszWzXLqcUYs5D0RGoeYCdwI+mGBr2vSk4xxnwZeCvp1RlWAe8nPTZX76sypinsioiIiIiIyLijbswiIiIiIiIy7ijsioiIiIiIyLijsCsiIiIiIiLjjsKuiIiIiIiIjDsKuyIiIiIiIjLuKOyKiIiIiIjIuKOwKyIikkXGmIuMMXbIT9IY02WMWW+MudsYszyzButIH3+hMeZWY8yUE1e1iIhI7nNluwAREREB4LfAw4ABCoDTgGuAG4B/GmPeYq0NjuBxFwL/CTwJ7D4hlYqIiIwBCrsiIiK54RVr7a+GbjDGfBL4JvBJ0mH4imwUJiIiMhapG7OIiEiOstYmrbWfAv4FLDfGnA9gjJlojPm2MWZ1pstzxBiz0RjzOWOMc+D+xphbgV9kbj4xpKv0L4cc4zXGfMEYsyHzOEFjzIPGmDNP3isVERE58dSyKyIikvt+BpwPvJ508D0DuA74M7ADcAPLga8D04APZu53H1AN3Ax8FdiU2b4DwBjjBh4BzgX+F/gBUAR8AHjGGPMaa+3KUX5tIiIio0JhV0REJPetzVzOylyuAKZZa+2QY243xvwv8H5jzK3W2iZr7VpjzHOkw+6j1tonD3jcjwAXAcuttX8f2GiM+R9gPfCtzH4REZExR92YRUREcl9P5rIQwFobHgi6xhiPMabUGFMO/J303/bFx/i47wI2Ay8bY8oHfgAP8ChwvjHGfyJfiIiIyMmill0REZHcV5i57AEwxriAz5OeqXkG6Rmchyo5xsedA/iBtiMcUw7UH3OlIiIiOUJhV0REJPedkbnckrn8DvBR4PfAbUArEAcWAd/g2HtuGWAd6dmeD+dIQVhERCRnKeyKiIjkvpsylw9lLt8NPGWtfdvQg4wxMw5xX3uIbQO2ARXA49ba1HFXKSIikkM0ZldERCRHGWOcxphvkZ6J+WFr7TOZXUkO6LpsjMkDPnGIh+nLXJYeYt898P/bu1tVK6IwjsO/BVoEg+mYNApGr8AP7CaDCH4UwRswmMwm70CTCF6AHESzHu/BoNiMguksw+ywFS1y2ByG50nDzLuGteKfd9aszvaPzu4YY+9/5g0Ax4HOLgAcD5fGGLc316erC9WN6ny1X93aqn1dPRhjvKreVnvV/er7X957UB1Wj8cYZ6of1ec554fqWXW9ejrGuFq9a9kXfK66Vv2srhzlIgFgV8bvpxYAALs0xrhcvd+6ddjSjf1afapezjnf/DHmVPWkutkSdL+0nMV70BJ+7805n2/V36ketfzM6mT1Ys55d/PsRPWw5dPoi5sh36qPm7r9I1ssAOyQsAsAAMDq2LMLAADA6gi7AAAArI6wCwAAwOoIuwAAAKyOsAsAAMDqCLsAAACsjrALAADA6gi7AAAArI6wCwAAwOoIuwAAAKzOL9XqNa7eCRhuAAAAAElFTkSuQmCC\n","text/plain":["<Figure size 1152x576 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":417},"id":"Uk3XDChTNdMO","executionInfo":{"status":"ok","timestamp":1630403794529,"user_tz":-330,"elapsed":676,"user":{"displayName":"Swapnil.Biswas Btech2020","photoUrl":"","userId":"10581545405833579740"}},"outputId":"89f754b6-15c0-4298-ae7a-a1495d07ced3"},"source":["#Show the valid and predicted prices\n","valid"],"execution_count":null,"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>Open</th>\n","      <th>Predictions</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>950</th>\n","      <td>5.36</td>\n","      <td>8.239012</td>\n","    </tr>\n","    <tr>\n","      <th>951</th>\n","      <td>5.54</td>\n","      <td>7.910715</td>\n","    </tr>\n","    <tr>\n","      <th>952</th>\n","      <td>5.05</td>\n","      <td>8.169835</td>\n","    </tr>\n","    <tr>\n","      <th>953</th>\n","      <td>4.62</td>\n","      <td>7.704402</td>\n","    </tr>\n","    <tr>\n","      <th>954</th>\n","      <td>4.55</td>\n","      <td>7.519466</td>\n","    </tr>\n","    <tr>\n","      <th>...</th>\n","      <td>...</td>\n","      <td>...</td>\n","    </tr>\n","    <tr>\n","      <th>1352</th>\n","      <td>1.49</td>\n","      <td>5.501567</td>\n","    </tr>\n","    <tr>\n","      <th>1353</th>\n","      <td>1.66</td>\n","      <td>5.364160</td>\n","    </tr>\n","    <tr>\n","      <th>1354</th>\n","      <td>1.71</td>\n","      <td>5.510063</td>\n","    </tr>\n","    <tr>\n","      <th>1355</th>\n","      <td>1.99</td>\n","      <td>5.504855</td>\n","    </tr>\n","    <tr>\n","      <th>1356</th>\n","      <td>1.99</td>\n","      <td>5.747606</td>\n","    </tr>\n","  </tbody>\n","</table>\n","<p>407 rows × 2 columns</p>\n","</div>"],"text/plain":["      Open  Predictions\n","950   5.36     8.239012\n","951   5.54     7.910715\n","952   5.05     8.169835\n","953   4.62     7.704402\n","954   4.55     7.519466\n","...    ...          ...\n","1352  1.49     5.501567\n","1353  1.66     5.364160\n","1354  1.71     5.510063\n","1355  1.99     5.504855\n","1356  1.99     5.747606\n","\n","[407 rows x 2 columns]"]},"metadata":{},"execution_count":102}]}]}