05_1013_PAMAP2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 384,
   "id": "fb742a8f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from scipy.interpolate import interp1d\n",
    "from scipy.stats import mode\n",
    "\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.metrics import classification_report, confusion_matrix, ConfusionMatrixDisplay\n",
    "\n",
    "from sklearn.metrics import confusion_matrix,classification_report,accuracy_score\n",
    "import seaborn as sns\n",
    "\n",
    "import tensorflow as tf\n",
    "import keras\n",
    "from tensorflow import stack\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "from tensorflow.keras.optimizers import Adam\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, GlobalAveragePooling1D, BatchNormalization, MaxPool1D, Reshape, Activation, Flatten\n",
    "from keras.layers import Conv1D, LSTM, Dropout, Bidirectional,LayerNormalization\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 385,
   "id": "abcdd503",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv('./data/pamap2.csv', index_col=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 386,
   "id": "12fa1845",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['timestamp', 'activityID', 'heartrate', 'handTemperature',\n",
       "       'handAcc16_1', 'handAcc16_2', 'handAcc16_3', 'handAcc6_1', 'handAcc6_2',\n",
       "       'handAcc6_3', 'handGyro1', 'handGyro2', 'handGyro3', 'handMagne1',\n",
       "       'handMagne2', 'handMagne3', 'handOrientation1', 'handOrientation2',\n",
       "       'handOrientation3', 'handOrientation4', 'chestTemperature',\n",
       "       'chestAcc16_1', 'chestAcc16_2', 'chestAcc16_3', 'chestAcc6_1',\n",
       "       'chestAcc6_2', 'chestAcc6_3', 'chestGyro1', 'chestGyro2', 'chestGyro3',\n",
       "       'chestMagne1', 'chestMagne2', 'chestMagne3', 'chestOrientation1',\n",
       "       'chestOrientation2', 'chestOrientation3', 'chestOrientation4',\n",
       "       'ankleTemperature', 'ankleAcc16_1', 'ankleAcc16_2', 'ankleAcc16_3',\n",
       "       'ankleAcc6_1', 'ankleAcc6_2', 'ankleAcc6_3', 'ankleGyro1', 'ankleGyro2',\n",
       "       'ankleGyro3', 'ankleMagne1', 'ankleMagne2', 'ankleMagne3',\n",
       "       'ankleOrientation1', 'ankleOrientation2', 'ankleOrientation3',\n",
       "       'ankleOrientation4', 'subject_id'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 386,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "id": "93b8b00b",
   "metadata": {},
   "outputs": [],
   "source": [
    "hand = ['handAcc16_1', 'handAcc16_2', 'handAcc16_3', 'handAcc6_1', 'handAcc6_2',\n",
    "       'handAcc6_3', 'handGyro1', 'handGyro2', 'handGyro3', 'handMagne1',\n",
    "       'handMagne2', 'handMagne3','activityID'];\n",
    "h_features = df[hand]\n",
    "\n",
    "\n",
    "chest = ['chestAcc16_1', 'chestAcc16_2', 'chestAcc16_3', 'chestAcc6_1',\n",
    "       'chestAcc6_2', 'chestAcc6_3', 'chestGyro1', 'chestGyro2', 'chestGyro3',\n",
    "       'chestMagne1', 'chestMagne2', 'chestMagne3','activityID']\n",
    "c_features = df[chest]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 388,
   "id": "b40bac78",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Counter({1: 17575,\n",
       "         2: 16881,\n",
       "         3: 17256,\n",
       "         12: 10699,\n",
       "         13: 9585,\n",
       "         4: 20998,\n",
       "         7: 16857,\n",
       "         5: 8665})"
      ]
     },
     "execution_count": 388,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from collections import Counter\n",
    "\n",
    "Counter(h_features['activityID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 389,
   "id": "978d7b3d",
   "metadata": {},
   "outputs": [],
   "source": [
    "label_encode = LabelEncoder()\n",
    "h_features['activityID'] = label_encode.fit_transform(h_features['activityID'])\n",
    "c_features['activityID'] = label_encode.fit_transform(c_features['activityID'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "id": "c79a709e",
   "metadata": {},
   "outputs": [
    {
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       "      <th>handAcc16_1</th>\n",
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       "<p>118516 rows × 13 columns</p>\n",
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      "text/plain": [
       "         handAcc16_1  handAcc16_2  handAcc16_3  handAcc6_1  handAcc6_2  \\\n",
       "2932        2.301060      7.25857      6.09259    2.207200     7.24042   \n",
       "2943        2.246150      7.48180      5.55219    2.251300     7.40595   \n",
       "2954        2.300000      7.10681      6.09309    2.346130     7.46611   \n",
       "2965        2.494550      7.52335      6.17157    2.591060     7.76653   \n",
       "2976        2.716540      8.30596      4.78671    2.595960     7.94641   \n",
       "...              ...          ...          ...         ...         ...   \n",
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       "2818435     0.530504      2.67279      9.35297    0.540382     2.87591   \n",
       "2818445     0.644139      2.70986      9.35454    0.630675     2.81489   \n",
       "\n",
       "         handAcc6_3  handGyro1  handGyro2  handGyro3  handMagne1  handMagne2  \\\n",
       "2932        5.95555  -0.069961  -0.018328   0.004582     9.15626   -67.18250   \n",
       "2943        5.65313  -0.431227   0.002685  -0.062964     9.14612   -67.39360   \n",
       "2954        6.12103   0.075692  -0.030792   0.005246     9.69163   -67.08980   \n",
       "2965        6.27112  -0.259058  -0.267895  -0.038533     9.58694   -67.08820   \n",
       "2976        4.86635   0.377115  -0.023688  -0.020670     8.59622   -67.14860   \n",
       "...             ...        ...        ...        ...         ...         ...   \n",
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       "2818413     9.47051   0.011127   0.038150   0.059271    18.33580    -5.21004   \n",
       "2818423     9.40988   0.000674   0.034051   0.008866    17.71400    -4.92892   \n",
       "2818435     9.30409  -0.048145   0.034565  -0.001782    18.08540    -4.82465   \n",
       "2818445     9.34943  -0.004483  -0.001148   0.039415    17.95720    -4.94146   \n",
       "\n",
       "         handMagne3  activityID  \n",
       "2932       -20.0857           0  \n",
       "2943       -20.5508           0  \n",
       "2954       -21.2481           0  \n",
       "2965       -20.8997           0  \n",
       "2976       -20.1947           0  \n",
       "...             ...         ...  \n",
       "2818402    -41.8342           4  \n",
       "2818413    -41.4393           4  \n",
       "2818423    -41.8335           4  \n",
       "2818435    -41.8349           4  \n",
       "2818445    -41.1777           4  \n",
       "\n",
       "[118516 rows x 13 columns]"
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     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "h_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "id": "5e0e84ff",
   "metadata": {},
   "outputs": [
    {
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       "      <td>0.428255</td>\n",
       "      <td>9.64882</td>\n",
       "      <td>-1.685030</td>\n",
       "      <td>0.218926</td>\n",
       "      <td>9.60427</td>\n",
       "      <td>-1.398660</td>\n",
       "      <td>0.007856</td>\n",
       "      <td>0.001881</td>\n",
       "      <td>-0.058687</td>\n",
       "      <td>2.177730</td>\n",
       "      <td>-51.2222</td>\n",
       "      <td>43.68360</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818402</th>\n",
       "      <td>-2.176960</td>\n",
       "      <td>9.63375</td>\n",
       "      <td>0.397475</td>\n",
       "      <td>-2.399840</td>\n",
       "      <td>9.77329</td>\n",
       "      <td>0.703170</td>\n",
       "      <td>0.019680</td>\n",
       "      <td>0.018043</td>\n",
       "      <td>-0.013087</td>\n",
       "      <td>21.723400</td>\n",
       "      <td>-30.6849</td>\n",
       "      <td>8.91800</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818413</th>\n",
       "      <td>-2.145710</td>\n",
       "      <td>9.63208</td>\n",
       "      <td>0.165721</td>\n",
       "      <td>-2.266810</td>\n",
       "      <td>9.53169</td>\n",
       "      <td>0.565652</td>\n",
       "      <td>0.056830</td>\n",
       "      <td>-0.038897</td>\n",
       "      <td>0.005755</td>\n",
       "      <td>21.973900</td>\n",
       "      <td>-29.9201</td>\n",
       "      <td>8.63339</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818423</th>\n",
       "      <td>-1.882640</td>\n",
       "      <td>9.51751</td>\n",
       "      <td>0.054697</td>\n",
       "      <td>-2.161590</td>\n",
       "      <td>9.57682</td>\n",
       "      <td>0.504698</td>\n",
       "      <td>-0.060698</td>\n",
       "      <td>-0.026238</td>\n",
       "      <td>0.049355</td>\n",
       "      <td>21.971700</td>\n",
       "      <td>-30.6947</td>\n",
       "      <td>9.48380</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818435</th>\n",
       "      <td>-1.867470</td>\n",
       "      <td>9.63384</td>\n",
       "      <td>0.557966</td>\n",
       "      <td>-2.128490</td>\n",
       "      <td>9.69697</td>\n",
       "      <td>0.882662</td>\n",
       "      <td>-0.025373</td>\n",
       "      <td>0.022089</td>\n",
       "      <td>0.019818</td>\n",
       "      <td>21.863500</td>\n",
       "      <td>-30.8185</td>\n",
       "      <td>8.35572</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2818445</th>\n",
       "      <td>-1.948720</td>\n",
       "      <td>9.89635</td>\n",
       "      <td>0.362036</td>\n",
       "      <td>-2.039800</td>\n",
       "      <td>9.84828</td>\n",
       "      <td>0.459413</td>\n",
       "      <td>0.131878</td>\n",
       "      <td>-0.028070</td>\n",
       "      <td>0.005272</td>\n",
       "      <td>21.216700</td>\n",
       "      <td>-30.9238</td>\n",
       "      <td>8.63383</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>118516 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         chestAcc16_1  chestAcc16_2  chestAcc16_3  chestAcc6_1  chestAcc6_2  \\\n",
       "2932         0.352225       9.72437     -1.686650     0.173568      9.69512   \n",
       "2943         0.125825       9.72560     -1.613310     0.143761      9.71023   \n",
       "2954         0.199567       9.64954     -1.689170     0.083704      9.75569   \n",
       "2965         0.279626       9.80069     -1.572050     0.114698      9.78564   \n",
       "2976         0.428255       9.64882     -1.685030     0.218926      9.60427   \n",
       "...               ...           ...           ...          ...          ...   \n",
       "2818402     -2.176960       9.63375      0.397475    -2.399840      9.77329   \n",
       "2818413     -2.145710       9.63208      0.165721    -2.266810      9.53169   \n",
       "2818423     -1.882640       9.51751      0.054697    -2.161590      9.57682   \n",
       "2818435     -1.867470       9.63384      0.557966    -2.128490      9.69697   \n",
       "2818445     -1.948720       9.89635      0.362036    -2.039800      9.84828   \n",
       "\n",
       "         chestAcc6_3  chestGyro1  chestGyro2  chestGyro3  chestMagne1  \\\n",
       "2932       -1.534140    0.000275   -0.013352   -0.039315     0.462317   \n",
       "2943       -1.503690   -0.029411   -0.037321   -0.033805     1.113440   \n",
       "2954       -1.533420   -0.009560   -0.055878   -0.044714     1.032800   \n",
       "2965       -1.412620   -0.067753    0.020297   -0.012148     0.671351   \n",
       "2976       -1.398660    0.007856    0.001881   -0.058687     2.177730   \n",
       "...              ...         ...         ...         ...          ...   \n",
       "2818402     0.703170    0.019680    0.018043   -0.013087    21.723400   \n",
       "2818413     0.565652    0.056830   -0.038897    0.005755    21.973900   \n",
       "2818423     0.504698   -0.060698   -0.026238    0.049355    21.971700   \n",
       "2818435     0.882662   -0.025373    0.022089    0.019818    21.863500   \n",
       "2818445     0.459413    0.131878   -0.028070    0.005272    21.216700   \n",
       "\n",
       "         chestMagne2  chestMagne3  activityID  \n",
       "2932        -50.7110     42.92280           0  \n",
       "2943        -50.1898     44.64950           0  \n",
       "2954        -50.8441     43.17650           0  \n",
       "2965        -50.2744     43.29430           0  \n",
       "2976        -51.2222     43.68360           0  \n",
       "...              ...          ...         ...  \n",
       "2818402     -30.6849      8.91800           4  \n",
       "2818413     -29.9201      8.63339           4  \n",
       "2818423     -30.6947      9.48380           4  \n",
       "2818435     -30.8185      8.35572           4  \n",
       "2818445     -30.9238      8.63383           4  \n",
       "\n",
       "[118516 rows x 13 columns]"
      ]
     },
     "execution_count": 391,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c_features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 392,
   "id": "4877dafe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4     20998\n",
       "1     17575\n",
       "3     17256\n",
       "2     16881\n",
       "7     16857\n",
       "12    10699\n",
       "13     9585\n",
       "5      8665\n",
       "Name: activityID, dtype: int64"
      ]
     },
     "execution_count": 392,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['activityID'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 393,
   "id": "013d3e78",
   "metadata": {},
   "outputs": [],
   "source": [
    "def split_sequences(sequences, time_steps, steps=1):\n",
    "    X, y = list(), list()\n",
    "    for i in range(0, len(sequences), steps):\n",
    "\n",
    "        end_ix = i + time_steps\n",
    "\n",
    "        if end_ix > len(sequences):\n",
    "            break\n",
    "\n",
    "        seq_x, seq_y = sequences[i:end_ix, :-1], sequences[end_ix-1, -1]\n",
    "        X.append(seq_x)\n",
    "        y.append(seq_y)\n",
    "    return np.array(X), np.array(y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 394,
   "id": "4521e341",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "hand_train, hand_test = train_test_split(h_features, test_size = 0.2, shuffle = True, random_state = 42)\n",
    "chest_train, chest_test = train_test_split(c_features, test_size = 0.2, shuffle = True, random_state = 42)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 395,
   "id": "eb6d8082",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_hand_set = np.array(hand_train)\n",
    "test_hand_set = np.array(hand_test)\n",
    "train_chest_set = np.array(chest_train)\n",
    "test_chest_set = np.array(chest_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 396,
   "id": "3916e999",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "scaler = StandardScaler()\n",
    "train_hand_set[:,:-1] = scaler.fit_transform(train_hand_set[:,:-1])\n",
    "test_hand_set[:,:-1] = scaler.transform(test_hand_set[:,:-1])\n",
    "scaler = StandardScaler()\n",
    "train_chest_set[:,:-1] = scaler.fit_transform(train_chest_set[:,:-1])\n",
    "test_chest_set[:,:-1] = scaler.transform(test_chest_set[:,:-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 397,
   "id": "312a5563",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.54092897,  0.10380076, -0.73884228, ..., -0.5560904 ,\n",
       "         1.27176936,  2.        ],\n",
       "       [-0.86312543, -0.31053269, -0.87322845, ..., -0.50051732,\n",
       "        -0.58507136,  3.        ],\n",
       "       [ 0.48784377, -0.02397468,  1.58600692, ...,  0.11276476,\n",
       "        -0.42953786,  1.        ],\n",
       "       ...,\n",
       "       [ 1.63993141, -0.75149615,  1.02667317, ...,  0.21844729,\n",
       "         0.31023801,  0.        ],\n",
       "       [ 0.78554211,  0.28854086,  1.31489252, ...,  1.23330375,\n",
       "        -0.99850321,  0.        ],\n",
       "       [ 1.70721208, -0.04603599,  0.82085369, ...,  0.51458017,\n",
       "        -1.31209267,  0.        ]])"
      ]
     },
     "execution_count": 397,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_hand_set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 398,
   "id": "13d0b74c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(18960, 15, 12) (18960,)\n",
      "(4738, 15, 12) (4738,)\n",
      "(18960, 15, 12) (18960,)\n",
      "(4738, 15, 12) (4738,)\n"
     ]
    }
   ],
   "source": [
    "TIMESTEPS = 15;\n",
    "STEPS = 5;\n",
    "\n",
    "X_train_h, y_train_h = split_sequences(train_hand_set, TIMESTEPS, STEPS)\n",
    "print(X_train_h.shape, y_train_h.shape)\n",
    "\n",
    "X_test_h, y_test_h = split_sequences(test_hand_set, TIMESTEPS, STEPS)\n",
    "print(X_test_h.shape, y_test_h.shape)\n",
    "\n",
    "X_train_c, y_train_c = split_sequences(train_chest_set, TIMESTEPS, STEPS)\n",
    "print(X_train_c.shape, y_train_c.shape)\n",
    "\n",
    "X_test_c, y_test_c = split_sequences(test_chest_set, TIMESTEPS, STEPS)\n",
    "print(X_test_c.shape, y_test_c.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 399,
   "id": "8a024732",
   "metadata": {},
   "outputs": [],
   "source": [
    "y_train_h = to_categorical(y_train_h)\n",
    "y_test_h = to_categorical(y_test_h)\n",
    "y_train_c = to_categorical(y_train_c)\n",
    "y_test_c = to_categorical(y_test_c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 400,
   "id": "30b35309",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((18960, 8), (4738, 8), (18960, 8), (18960, 8))"
      ]
     },
     "execution_count": 400,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train_h.shape,y_test_h.shape,y_train_c.shape,y_train_c.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 401,
   "id": "12c2fac6",
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size = 64\n",
    "validation_split = 0.2\n",
    "epochs = 30"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 402,
   "id": "9e4ecc74",
   "metadata": {},
   "outputs": [],
   "source": [
    "def display_results(testy,predictions,classNames):\n",
    "    y_test=np.argmax(testy, axis=1)\n",
    "    y_scores=np.argmax(predictions, axis=1)\n",
    "    classes = len(classNames)\n",
    "    cm = confusion_matrix(y_testh, y_scores)\n",
    "    print(\"**** Confusion Matrix ****\")\n",
    "    print(cm)\n",
    "    print(\"**** Classification Report ****\")\n",
    "    print(classification_report(y_testh, y_scores, target_names=classNames))\n",
    "    con = np.zeros((classes,classes))\n",
    "    for x in range(classes):\n",
    "        for y in range(classes):\n",
    "            con[x,y] = cm[x,y] #/np.sum(cm[x,:])\n",
    "\n",
    "    plt.figure(figsize=(10,8))\n",
    "    df = sns.heatmap(con, annot=True, fmt='g', cmap='Blues',xticklabels= classNames , yticklabels= classNames)\n",
    "    plt.xlabel('Predicted')\n",
    "    plt.ylabel('Actual')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fe71b8f",
   "metadata": {},
   "source": [
    "## Train set: Hand / Test set: Hand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 403,
   "id": "8fafa57f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15 12 8\n"
     ]
    }
   ],
   "source": [
    "n_timesteps, n_features, n_outputs = X_train_h.shape[1], X_train_h.shape[2], y_train_h.shape[1]\n",
    "print(n_timesteps, n_features, n_outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "id": "78d3a816",
   "metadata": {},
   "outputs": [],
   "source": [
    "model1 = Sequential()\n",
    "model1.add(LSTM(64, input_shape = [n_timesteps, n_features], return_sequences=True))\n",
    "model1.add(LSTM(32))\n",
    "model1.add(Dropout(0.3))\n",
    "\n",
    "model1.add(Dense(16, activation=\"relu\"))\n",
    "model1.add(Dropout(0.3))\n",
    "model1.add(Dense(n_outputs, activation = \"softmax\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "id": "b479942e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_33\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " lstm_23 (LSTM)              (None, 15, 64)            19712     \n",
      "                                                                 \n",
      " lstm_24 (LSTM)              (None, 32)                12416     \n",
      "                                                                 \n",
      " dropout_37 (Dropout)        (None, 32)                0         \n",
      "                                                                 \n",
      " dense_70 (Dense)            (None, 16)                528       \n",
      "                                                                 \n",
      " dropout_38 (Dropout)        (None, 16)                0         \n",
      "                                                                 \n",
      " dense_71 (Dense)            (None, 8)                 136       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 32792 (128.09 KB)\n",
      "Trainable params: 32792 (128.09 KB)\n",
      "Non-trainable params: 0 (0.00 Byte)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model1.compile(loss = \"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])\n",
    "model1.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 406,
   "id": "76f8740b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/30\n",
      "237/237 [==============================] - 12s 29ms/step - loss: 1.5726 - accuracy: 0.4236 - val_loss: 1.2234 - val_accuracy: 0.5414\n",
      "Epoch 2/30\n",
      "237/237 [==============================] - 5s 22ms/step - loss: 1.2085 - accuracy: 0.5907 - val_loss: 0.9680 - val_accuracy: 0.6912\n",
      "Epoch 3/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 1.0127 - accuracy: 0.6702 - val_loss: 0.8704 - val_accuracy: 0.7091\n",
      "Epoch 4/30\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.9228 - accuracy: 0.6970 - val_loss: 0.8254 - val_accuracy: 0.7292\n",
      "Epoch 5/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.8553 - accuracy: 0.7194 - val_loss: 0.8345 - val_accuracy: 0.7329\n",
      "Epoch 6/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.8024 - accuracy: 0.7358 - val_loss: 0.8015 - val_accuracy: 0.7447\n",
      "Epoch 7/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.7631 - accuracy: 0.7446 - val_loss: 0.8096 - val_accuracy: 0.7445\n",
      "Epoch 8/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.7338 - accuracy: 0.7492 - val_loss: 0.7959 - val_accuracy: 0.7508\n",
      "Epoch 9/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.6947 - accuracy: 0.7618 - val_loss: 0.8230 - val_accuracy: 0.7479\n",
      "Epoch 10/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.6783 - accuracy: 0.7685 - val_loss: 0.8361 - val_accuracy: 0.7524\n",
      "Epoch 11/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.6549 - accuracy: 0.7722 - val_loss: 0.8080 - val_accuracy: 0.7484\n",
      "Epoch 12/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.6309 - accuracy: 0.7795 - val_loss: 0.8490 - val_accuracy: 0.7400\n",
      "Epoch 13/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.6192 - accuracy: 0.7814 - val_loss: 0.8649 - val_accuracy: 0.7429\n",
      "Epoch 14/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.5988 - accuracy: 0.7891 - val_loss: 0.8980 - val_accuracy: 0.7545\n",
      "Epoch 15/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.5882 - accuracy: 0.7898 - val_loss: 0.8906 - val_accuracy: 0.7458\n",
      "Epoch 16/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.5640 - accuracy: 0.7977 - val_loss: 0.9034 - val_accuracy: 0.7511\n",
      "Epoch 17/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.5440 - accuracy: 0.8081 - val_loss: 0.9618 - val_accuracy: 0.7455\n",
      "Epoch 18/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.5425 - accuracy: 0.8101 - val_loss: 0.9470 - val_accuracy: 0.7487\n",
      "Epoch 19/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.5494 - accuracy: 0.8071 - val_loss: 1.0056 - val_accuracy: 0.7460\n",
      "Epoch 20/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.5264 - accuracy: 0.8118 - val_loss: 0.9942 - val_accuracy: 0.7474\n",
      "Epoch 21/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.5131 - accuracy: 0.8161 - val_loss: 0.9867 - val_accuracy: 0.7487\n",
      "Epoch 22/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.4997 - accuracy: 0.8200 - val_loss: 1.0048 - val_accuracy: 0.7582\n",
      "Epoch 23/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.4940 - accuracy: 0.8252 - val_loss: 1.0721 - val_accuracy: 0.7400\n",
      "Epoch 24/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.4928 - accuracy: 0.8242 - val_loss: 1.0570 - val_accuracy: 0.7402\n",
      "Epoch 25/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.4897 - accuracy: 0.8265 - val_loss: 1.0659 - val_accuracy: 0.7453\n",
      "Epoch 26/30\n",
      "237/237 [==============================] - 5s 23ms/step - loss: 0.4931 - accuracy: 0.8223 - val_loss: 1.0895 - val_accuracy: 0.7532\n",
      "Epoch 27/30\n",
      "237/237 [==============================] - 6s 23ms/step - loss: 0.4567 - accuracy: 0.8395 - val_loss: 1.1141 - val_accuracy: 0.7437\n",
      "Epoch 28/30\n",
      "237/237 [==============================] - 7s 27ms/step - loss: 0.4484 - accuracy: 0.8401 - val_loss: 1.1719 - val_accuracy: 0.7418\n",
      "Epoch 29/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.4416 - accuracy: 0.8393 - val_loss: 1.1258 - val_accuracy: 0.7534\n",
      "Epoch 30/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.4555 - accuracy: 0.8395 - val_loss: 1.1759 - val_accuracy: 0.7453\n"
     ]
    }
   ],
   "source": [
    "history = model1.fit(X_train_h, y_train_h, batch_size= batch_size, epochs=epochs, validation_split=validation_split)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 407,
   "id": "32763964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e2cf9d6290>"
      ]
     },
     "execution_count": 407,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 408,
   "id": "ad6aaa08",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e29ce42c50>"
      ]
     },
     "execution_count": 408,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['accuracy'])\n",
    "plt.plot(history.history['val_accuracy'])\n",
    "plt.title('Training and validation accuracy')\n",
    "plt.ylabel('accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 409,
   "id": "4886238a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 2s 8ms/step\n",
      "[[654   8   9   6   1   2   7  23]\n",
      " [  2 596  31   7   0  12   6  21]\n",
      " [  5  27 546  23   1  17  19  43]\n",
      " [  2  11  15 723   1  45  52  36]\n",
      " [  1   9  10  15 277  21   4  13]\n",
      " [  0  22  14  68  20 474  19  18]\n",
      " [  3  16  17 148  12  31 119  91]\n",
      " [  7  14  29  71  12  24  47 161]]\n",
      "0.7492612916842549\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.92      0.95       710\n",
      "           1       0.85      0.88      0.87       675\n",
      "           2       0.81      0.80      0.81       681\n",
      "           3       0.68      0.82      0.74       885\n",
      "           4       0.85      0.79      0.82       350\n",
      "           5       0.76      0.75      0.75       635\n",
      "           6       0.44      0.27      0.34       437\n",
      "           7       0.40      0.44      0.42       365\n",
      "\n",
      "    accuracy                           0.75      4738\n",
      "   macro avg       0.72      0.71      0.71      4738\n",
      "weighted avg       0.75      0.75      0.74      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 409,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=model1.predict(X_test_h)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_h, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e4aafa4",
   "metadata": {},
   "source": [
    "## Train set: Hand / Test set: Chest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 410,
   "id": "eaabc2f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 1s 7ms/step\n",
      "[[361   9  24  53   6   5  29 223]\n",
      " [ 89  78 173  17   5  10  27 276]\n",
      " [  9 147 170  38   4  84  47 182]\n",
      " [  6  70  53 142  84 284  98 148]\n",
      " [  4  11   4  49 164  84  10  24]\n",
      " [  4  43  30 116  78 243  62  59]\n",
      " [  6  39  15  96  51 108  47  75]\n",
      " [  9  36  14  84  57  64  45  56]]\n",
      "0.26614605318699874\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.74      0.51      0.60       710\n",
      "           1       0.18      0.12      0.14       675\n",
      "           2       0.35      0.25      0.29       681\n",
      "           3       0.24      0.16      0.19       885\n",
      "           4       0.37      0.47      0.41       350\n",
      "           5       0.28      0.38      0.32       635\n",
      "           6       0.13      0.11      0.12       437\n",
      "           7       0.05      0.15      0.08       365\n",
      "\n",
      "    accuracy                           0.27      4738\n",
      "   macro avg       0.29      0.27      0.27      4738\n",
      "weighted avg       0.31      0.27      0.28      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 410,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=model1.predict(X_test_c)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_h, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 411,
   "id": "3376d404",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: pamap2_hand.pth\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: pamap2_hand.pth\\assets\n"
     ]
    }
   ],
   "source": [
    "pth_file1 = 'pamap2_hand.pth'\n",
    "tf.keras.models.save_model(model1, pth_file1, include_optimizer=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04ffedd4",
   "metadata": {},
   "source": [
    "## Fine tuning pretrained model with hands for chest model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 412,
   "id": "aeaa351e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
     ]
    }
   ],
   "source": [
    "base_model = keras.models.load_model(pth_file1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 413,
   "id": "85cfcfd7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of layers in the base model:  6\n",
      "Model: \"sequential_34\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " lstm_23 (LSTM)              (None, 15, 64)            19712     \n",
      "                                                                 \n",
      " lstm_24 (LSTM)              (None, 32)                12416     \n",
      "                                                                 \n",
      " dropout_37 (Dropout)        (None, 32)                0         \n",
      "                                                                 \n",
      " dense_70 (Dense)            (None, 16)                528       \n",
      "                                                                 \n",
      " dropout_38 (Dropout)        (None, 16)                0         \n",
      "                                                                 \n",
      " dense_72 (Dense)            (None, 8)                 136       \n",
      "                                                                 \n",
      " dense_73 (Dense)            (None, 8)                 72        \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 32864 (128.38 KB)\n",
      "Trainable params: 736 (2.88 KB)\n",
      "Non-trainable params: 32128 (125.50 KB)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of layers in the base model: \", len(base_model.layers))\n",
    "fine_tune_at = 2\n",
    "\n",
    "for layer in base_model.layers[:fine_tune_at]:\n",
    "    layer.trainable = False\n",
    "\n",
    "new_model1 = Sequential(base_model.layers[:-1])\n",
    "new_model1.add(Dense(8, activation=\"sigmoid\"))\n",
    "new_model1.add(Dense(n_outputs, activation=\"sigmoid\"))\n",
    "\n",
    "new_model1.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 414,
   "id": "59e35101",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_model1.compile(loss =\"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 415,
   "id": "716096fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Layer Type</th>\n",
       "      <th>Layer Name</th>\n",
       "      <th>Layer Trainable</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_23</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_24</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_37</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_70</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_38</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_71</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Layer Type  Layer Name  \\\n",
       "0  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_23   \n",
       "1  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_24   \n",
       "2  <keras.src.layers.regularization.dropout.Dropo...  dropout_37   \n",
       "3  <keras.src.layers.core.dense.Dense object at 0...    dense_70   \n",
       "4  <keras.src.layers.regularization.dropout.Dropo...  dropout_38   \n",
       "5  <keras.src.layers.core.dense.Dense object at 0...    dense_71   \n",
       "\n",
       "   Layer Trainable  \n",
       "0            False  \n",
       "1            False  \n",
       "2             True  \n",
       "3             True  \n",
       "4             True  \n",
       "5             True  "
      ]
     },
     "execution_count": 415,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display_layers = [(layer, layer.name, layer.trainable) for layer in base_model.layers]\n",
    "pd.DataFrame(display_layers, columns=['Layer Type', 'Layer Name', 'Layer Trainable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "id": "f8b93f59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "237/237 [==============================] - 10s 22ms/step - loss: 1.7225 - accuracy: 0.3372 - val_loss: 1.5243 - val_accuracy: 0.3985\n",
      "Epoch 2/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.5770 - accuracy: 0.3844 - val_loss: 1.4790 - val_accuracy: 0.4372\n",
      "Epoch 3/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.5444 - accuracy: 0.4047 - val_loss: 1.4533 - val_accuracy: 0.4346\n",
      "Epoch 4/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.5263 - accuracy: 0.4052 - val_loss: 1.4444 - val_accuracy: 0.4544\n",
      "Epoch 5/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.5103 - accuracy: 0.4132 - val_loss: 1.4357 - val_accuracy: 0.4451\n",
      "Epoch 6/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.5118 - accuracy: 0.4141 - val_loss: 1.4289 - val_accuracy: 0.4586\n",
      "Epoch 7/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.5079 - accuracy: 0.4162 - val_loss: 1.4224 - val_accuracy: 0.4623\n",
      "Epoch 8/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.5035 - accuracy: 0.4204 - val_loss: 1.4180 - val_accuracy: 0.4523\n",
      "Epoch 9/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.5056 - accuracy: 0.4160 - val_loss: 1.4151 - val_accuracy: 0.4562\n",
      "Epoch 10/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4995 - accuracy: 0.4164 - val_loss: 1.4150 - val_accuracy: 0.4491\n",
      "Epoch 11/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4978 - accuracy: 0.4179 - val_loss: 1.4149 - val_accuracy: 0.4486\n",
      "Epoch 12/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.5003 - accuracy: 0.4150 - val_loss: 1.4079 - val_accuracy: 0.4594\n",
      "Epoch 13/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4947 - accuracy: 0.4152 - val_loss: 1.4145 - val_accuracy: 0.4209\n",
      "Epoch 14/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4899 - accuracy: 0.4184 - val_loss: 1.4014 - val_accuracy: 0.4578\n",
      "Epoch 15/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4915 - accuracy: 0.4175 - val_loss: 1.4009 - val_accuracy: 0.4678\n",
      "Epoch 16/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4839 - accuracy: 0.4217 - val_loss: 1.3936 - val_accuracy: 0.4586\n",
      "Epoch 17/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4843 - accuracy: 0.4209 - val_loss: 1.4003 - val_accuracy: 0.4615\n",
      "Epoch 18/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4870 - accuracy: 0.4206 - val_loss: 1.3983 - val_accuracy: 0.4702\n",
      "Epoch 19/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4806 - accuracy: 0.4191 - val_loss: 1.3981 - val_accuracy: 0.4668\n",
      "Epoch 20/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.4853 - accuracy: 0.4186 - val_loss: 1.3970 - val_accuracy: 0.4623\n"
     ]
    }
   ],
   "source": [
    "history1 = new_model1.fit(X_train_c, y_train_c, batch_size= batch_size, epochs=20, validation_split=validation_split)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 417,
   "id": "c0321cff",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model.trainable = True\n",
    "new_model1.compile(loss =\"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 418,
   "id": "cb6d0ad4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Layer Type</th>\n",
       "      <th>Layer Name</th>\n",
       "      <th>Layer Trainable</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_23</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_24</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_37</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_70</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_38</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_71</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Layer Type  Layer Name  \\\n",
       "0  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_23   \n",
       "1  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_24   \n",
       "2  <keras.src.layers.regularization.dropout.Dropo...  dropout_37   \n",
       "3  <keras.src.layers.core.dense.Dense object at 0...    dense_70   \n",
       "4  <keras.src.layers.regularization.dropout.Dropo...  dropout_38   \n",
       "5  <keras.src.layers.core.dense.Dense object at 0...    dense_71   \n",
       "\n",
       "   Layer Trainable  \n",
       "0             True  \n",
       "1             True  \n",
       "2             True  \n",
       "3             True  \n",
       "4             True  \n",
       "5             True  "
      ]
     },
     "execution_count": 418,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display_layers = [(layer, layer.name, layer.trainable) for layer in base_model.layers]\n",
    "pd.DataFrame(display_layers, columns=['Layer Type', 'Layer Name', 'Layer Trainable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 419,
   "id": "f93c980c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "237/237 [==============================] - 14s 30ms/step - loss: 1.3132 - accuracy: 0.4889 - val_loss: 1.1396 - val_accuracy: 0.5775\n",
      "Epoch 2/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 1.1400 - accuracy: 0.5690 - val_loss: 1.0378 - val_accuracy: 0.6134\n",
      "Epoch 3/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 1.0331 - accuracy: 0.6098 - val_loss: 0.9531 - val_accuracy: 0.6400\n",
      "Epoch 4/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.9695 - accuracy: 0.6276 - val_loss: 0.9148 - val_accuracy: 0.6548\n",
      "Epoch 5/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.9308 - accuracy: 0.6437 - val_loss: 0.8877 - val_accuracy: 0.6624\n",
      "Epoch 6/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.9021 - accuracy: 0.6506 - val_loss: 0.8702 - val_accuracy: 0.6669\n",
      "Epoch 7/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8844 - accuracy: 0.6582 - val_loss: 0.8778 - val_accuracy: 0.6653\n",
      "Epoch 8/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8517 - accuracy: 0.6717 - val_loss: 0.8566 - val_accuracy: 0.6799\n",
      "Epoch 9/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8343 - accuracy: 0.6795 - val_loss: 0.8578 - val_accuracy: 0.6714\n",
      "Epoch 10/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.8104 - accuracy: 0.6874 - val_loss: 0.8366 - val_accuracy: 0.6770\n",
      "Epoch 11/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7952 - accuracy: 0.6911 - val_loss: 0.8494 - val_accuracy: 0.6772\n",
      "Epoch 12/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7865 - accuracy: 0.6941 - val_loss: 0.8395 - val_accuracy: 0.6796\n",
      "Epoch 13/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7741 - accuracy: 0.6982 - val_loss: 0.8074 - val_accuracy: 0.6912\n",
      "Epoch 14/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7571 - accuracy: 0.7042 - val_loss: 0.8154 - val_accuracy: 0.6867\n",
      "Epoch 15/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7450 - accuracy: 0.7055 - val_loss: 0.7901 - val_accuracy: 0.6996\n",
      "Epoch 16/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7315 - accuracy: 0.7140 - val_loss: 0.7926 - val_accuracy: 0.6917\n",
      "Epoch 17/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7270 - accuracy: 0.7149 - val_loss: 0.8119 - val_accuracy: 0.6920\n",
      "Epoch 18/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7189 - accuracy: 0.7201 - val_loss: 0.8141 - val_accuracy: 0.6946\n",
      "Epoch 19/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7066 - accuracy: 0.7214 - val_loss: 0.8100 - val_accuracy: 0.7031\n",
      "Epoch 20/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6965 - accuracy: 0.7280 - val_loss: 0.7992 - val_accuracy: 0.7002\n"
     ]
    }
   ],
   "source": [
    "history2 = new_model1.fit(X_train_c, y_train_c, epochs=20, batch_size = batch_size, validation_split = validation_split, shuffle = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 420,
   "id": "231e9991",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e32235e290>"
      ]
     },
     "execution_count": 420,
     "metadata": {},
     "output_type": "execute_result"
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    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history2.history['loss'])\n",
    "plt.plot(history2.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 421,
   "id": "53e999ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e2a055d810>"
      ]
     },
     "execution_count": 421,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history2.history['accuracy'])\n",
    "plt.plot(history2.history['val_accuracy'])\n",
    "plt.title('Training and validation accuracy')\n",
    "plt.ylabel('accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 422,
   "id": "c7922dd5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 2s 8ms/step\n",
      "[[681   0   1  13   0   2   3  10]\n",
      " [  4 626  24   6   2   5   3   5]\n",
      " [  4   6 631  28   0   1   4   7]\n",
      " [  7   1   8 604   7 171  38  49]\n",
      " [  2   0   3  26 269  13  17  20]\n",
      " [  4   5   8 371  10 158  48  31]\n",
      " [  2   1  15  93   6  59 203  58]\n",
      " [  3   9  11  64  28  40  36 174]]\n",
      "0.7062051498522584\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.96      0.96      0.96       710\n",
      "           1       0.97      0.93      0.95       675\n",
      "           2       0.90      0.93      0.91       681\n",
      "           3       0.50      0.68      0.58       885\n",
      "           4       0.84      0.77      0.80       350\n",
      "           5       0.35      0.25      0.29       635\n",
      "           6       0.58      0.46      0.51       437\n",
      "           7       0.49      0.48      0.48       365\n",
      "\n",
      "    accuracy                           0.71      4738\n",
      "   macro avg       0.70      0.68      0.69      4738\n",
      "weighted avg       0.70      0.71      0.70      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 422,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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bbhdvpkgBLu+f97PWH6AvvviCP/74g99++42BAwe+UVmtWrXCwsKCfv36cfr0aYKCglQXT+Q0kqerq0vp0qXVFoVCC4Aly3dT19GS0f/rSLUq5fmsowsDezVn2Zq9ADx4+IS/jpxj5sTeNKpfgypmZfm8a2N6d2nMjt/TO5Xly+pjV7MKFuZpHwq1bcywq1kFQ/0SqpjdGycytF9r1ePFy3cxoEcz+nZvirVlBeZM6oNZBWOWr9uvivlhxW+M/l9HOrRxpmb1Svh6f8mTp8lsDky/rUJeDRjQCX//ffj77yMi4iYzZ/oSFRVDjx6fAODt7ceYMfNV8T16fExk5F28vJYTEXETf/99BATsY+DAzqqYvn07EBQUgo+PPxERN/Hx8efIkTD69euQ7/rl1aNHTzh//grnz18B0k6yPn/+iuoWG+9iHml1vsr581df1Pku589fJTIyhsePn7Jg/jpCQy9w+/Zdzp6N4LvvfiA6Oo42H6df+Tt27CLme69Lr3OfdgQHheLru5UrV27h67uVI0dO07df+khyv/7tCfA/QEDAASIibuHltZKoqFg+65F+HL4JTTimpk79iR07DuLtPYoSJYoTExNPTEw8T5+mn77xrucxf/4aTp48y61bd7hw4RoLFqzl+PFw2rdvoqr/2DELsqj/CiIibhLgv4+AgP1q9e/Ttz1BQSH4+gRwJeIWvj4BBV7/zO3ijqpdKBQK+vZth88yf/btO8rFi9eZMH4JxYrp0q5dY1UZae1irepx9u2ivSqmX/8OBPjvJyBgPxERN19pF20KLDeRf3KO3XvCysoKFxcX4uLiqFev3huVpaWlRWBgIF988QUfffQR1apVY+7cubRv355ixfJ/XzeAf05f4bMh85k2tgcTvnXj2s0YRk9dy6ZXOk59v1rMtLE9WL34KwwNSnLjVgxT5mzG95UO2Beft+S74V1Vj/f7TwFg8IifWOefdml+tcrlMSqTfqWd/86jlDEoxYRv3TApZ8DZizfp1G82N27HqmK8f9pJsWJFWeg5EMPSJTgRGkG73jN5+Cj7e2xlp23bRsTH3+fHHzdx9+49qlevgo/PZCpWLAdATMw9oqLST0o2MzPBx2cyXl7LWb9+F+XKlWHixCG0aZN+q5U6dWowf/4YFi5cy+LF6zEzM2HBgjHY22e+0XJBCQ+/TN++E1SPvbxWANC5c3NmzRr+TuZxNjyCfv0mqR7PnrUKgE6dmjFlqjtXrt4m8JuDxMffx8CgFLa2lqxbPwMrq/Tzo6IiYynyyhSLYx0bvL1HsGjRRpYs3oSZWXm854/E3j79ium2bRuSkPCAH3/YQkxMPFZWlfl52UTVa/6mNOGYenlrlj59Jqit9/L6Fje3lu9FHnGxCYwZs4CYu/coVaoE1tbm+C6frLryNSYmnshX6l/JzIRlPpOZ5bWcDar6D6ZNm/QvEnXq1MB7/mgWLVynqv/8BaMLtP5p7eJ71eNX24XXrG/44ovOJD1NZto0H+4nPsTOzorlKyZTomRx1TZRkTEUeeWLfVq7GMmiRRtYsnhjPtrFdwXWLl7X+zqFWlAUyoxnlIt3klKpxMbGBnd3d0aMGFHg5QcFBdGwYUMuX76MhYVFnrcrXrlngdelMDy5MbWwqyBeSFVmP236Pimi0Mk9SPwnlGjGx5xSmVLYVXhjRRQ13/o+KtT+PvegPIoMn15gZf1XZMTuPXD37l3Wrl3L7du3GTBgQIGUuW3bNkqWLImVlRWXL1/m22+/xdXVNV+dOiGEEEK8W6Rj9x4oX748xsbG+Pj4YGhoWCBlPnjwgDFjxnDz5k2MjY1p2bJlrrdQEUIIId51ig/88gHp2L0H3sZsed++fenbt2+BlyuEEEIUpg/9HLsPO3shhBBCCA0iI3ZCCCGE0BiF/csXhU06dkIIIYTQGDIVK4QQQgghNIKM2AkhhBBCY8hVsUIIIYQQGuJDn4qVjp0QQgghNMaH3rH7sLMXQgghhNAg0rETQgghhMZQUKTAlvy4ffs2n3/+OUZGRujp6eHg4MA///yjel6pVDJlyhQqVKhA8eLFadq0KWfPnlUrIykpia+//hpjY2NKlChBhw4duHXrVr7qIR07IYQQQmgORZGCW/IoPj4eV1dXdHR0+O233zh37hze3t4YGBioYubMmcP8+fNZunQpJ06cwMTEhFatWvHgwQNVjIeHB9u2bWPTpk0cPnyYhw8f0q5dO1JSUvKevvJt/F6V+GAUr9yzsKtQIJ7cmFrYVRAvpCqfFXYVCkQRhU5hV0G8oEQzPuaUyrx/uL+riihqvvV9VKszv8DKunJqRJ7ixo0bR1BQEH///XeWzyuVSipUqICHhwdjx44F0kbnypcvz+zZs3F3dycxMZGyZcuydu1aPvvsMwAiIyMxMzNj9+7dtGnTJk91kRE7IYQQQmgMhaJIgS15tWPHDpydnenWrRvlypXD0dERX19f1fNXr14lOjqa1q1bq9bp6urSpEkTgoODAfjnn3949uyZWkyFChWoXbu2KiYvpGMnhBBCCI2hUCgKbElKSuL+/ftqS1JSUqZ9XrlyhZ9++gkrKyv27NnD0KFD+eabb1izZg0A0dHRAJQvX15tu/Lly6uei46OpmjRohgaGmYbkxfSsRNCCCGEyIKXlxf6+vpqi5eXV6a41NRU6tSpw8yZM3F0dMTd3Z3Bgwfz008/qcVl/B1bpVKZ62/b5iXmVdKxE0IIIYTGKMirYsePH09iYqLaMn78+Ez7NDU1pWZN9fMHa9SowY0bNwAwMTEByDTydvfuXdUonomJCcnJycTHx2cbkxdyg2LxRh7fmFLYVSgQFWuvL+wqFIhrpzsVdhXemHaRYoVdBfGCplx0oCkUCq3CrsJ7oSBvUKyrq4uurm6uca6urly4cEFt3cWLF6lSpQoAVatWxcTEhH379uHo6AhAcnIyhw4dYvbs2QA4OTmho6PDvn376N69OwBRUVGEh4czZ86cPNdZOnZCCCGEEG9g+PDhuLi4MHPmTLp3787x48fx8fHBx8cHSJuC9fDwYObMmVhZWWFlZcXMmTPR09OjV69eAOjr6zNo0CBGjhyJkZERZcqUYdSoUdja2tKyZcs810U6dkIIIYTQHPk4H62gfPTRR2zbto3x48czbdo0qlatysKFC+ndu7cqZsyYMTx58oRhw4YRHx9PvXr12Lt3L6VKlVLFLFiwAG1tbbp3786TJ09o0aIFq1evRksr76O1ch878UaUXMg96D1QqfaGwq5CgZCp2HeHgvd/2kymYkVBU2D91vdRvf6PBVbWxaPDCqys/4qM2AkhhBBCcxTCiN27RK6KFUIIIYTQEDJiJ4QQQgjN8YGP2EnHTgghhBCa4wOfi/zA0xdCCCGE0BwyYieEEEIIjaGUqVghhBBCCA3xYffrZCpWCCGEEEJTyIidEEIIITRHkQ97yE46dkIIIYTQHB/4OXYyFSuEEEIIoSFkxE4IIYQQmuPDHrCTEbt3Sf/+/enUqdNrbdu0aVM8PDwKtD5CCCHEe6eIouCW95B07N4hixYtYvXq1arHWXXWDh48iEKhICEhQW391q1bmT59+tuvZAFZtuwXbKw7MNPTN8e448fDcXMbjp1tF1q2GMymjb9litmzJ5hP2/4P29pufNr2f+zbd+S162VSrhSLZ7kRfngsl09MZK//UGxrmgKgrV2ECcNbsX/rMC4dn8g/f4xk0czOlC9bKlM5TvaV2LKiH5eOT+Rc8Dh+WdWfYro5D5D3++wjjvzuQcQ/3/HbZnfq1qmcKWbEsKb888dILp/8jl9W9ae6Rdk85eXrE8hn3SZQ16k/jV2H8M1X87h6NTLb+KmTfaldowdr/XbnWva+vcfo0G4kjnaf06HdSPbvO54pZtOGvbRp+TV17PvQvct4/jl5Pk/1zos7d+IYPWoB9er1wcG+O506ehAefjnHbdKOqxHY2XajZQt3Nm38PVNM2nH1Fba1u/Jp26/Yt+9ogdX5VcuW/UKXLsNxdOxOgwafM2zYDK5cuZXrdsePn8HNzQNbWzdatPiCjVm2jSDath1G7dqdadt22Bu1jdwsWbIBG+sOaktD1745bvNft+/cbNywmw7tv8apzmc41fmMzz4bzV+H/slxm3ctB9CM1+KNKBQFt7yHpGP3DtHX18fAwOC1ti1TpgylSmXuYLyLzpy+xJbNe7C2Ns8x7tbNaNyHTMXZqSbbAhfiPrQbnp6+7NkTrIoJCfmXEcPn0KFjU7ZvX0yHjk0Z7jGHsLAL+a6XfuliBK4dxPNnqXw+dB1NO/7AtLl7uP/gKQDFi+lgW9OURcsO8XH3nxnssZlqVYxYtbSnWjlO9pVY93MfDgVH8GlPHz7t4cPqDcdJTVVmu+8OH9diyriPWez7F226/czxU9dZ9/PnVDDRV8UMG9iQIX0b8N3M3Xzaw4eY2Ids9O1LCb2iueZ28sR5evZqzYZN0/FZMZHnz1MYMmgmjx8/zRR7YP8JTp++TLlyhrmWGxpykVEjFtG+QyMCAmfTvkMjRo1YxOmwS6qY33YHM2uWH4PdO/PL1lnUcbJhqPssoiJjcy0/N4mJD+nZcxzaOlr4+n7Pr7uWMHbcAEqXLpHtNrdu3sF9yPQXx9V83Id2xdNzeRbH1bwXx9XCF8fVXMLCLr5xnTM6fjyc3r0/ZcuWuaxaNZ2UlBQGDZqU5Wvz0s2b0QwZMhUnp1oEBi5i6NBueHr6sGdPkFoOw4fPoWPHZmzfvpiOHZvh4TH7tdpGXllZVebvw36qZcfOJdnG/tftOy/KmxgzclQ//APm4x8wn/r17fjf/zy5dOnGe5PDS+/7ayFen3TsCoG/vz+2trYUL14cIyMjWrZsyaNHj9SmYvv378+hQ4dYtGgRCoUChULBtWvXaNasGQCGhoYoFAr69+8PZB7dMzc3Z+bMmQwcOJBSpUpRuXJlfHx81OoRHByMg4MDxYoVw9nZmcDAQBQKBaGhoW8t90ePnjBqtDfTZ3xFaf2SOcZu2vQ7pqZlmTBxMBYWZnTr1ho3t5asXLlNFbPGbwcuLg64u3ejmkUl3N27Ub++HX5+O/Jdt2EDGxIZfZ8R3wcSGn6bW5EJHD52les34wF48DCJnoPXsHPPWSKuxXHq9C2+89qNfa2Kah2wKWM+ZuX6Y/yw4jAXI2K4euMeu/adI/lZSrb7HtzXhU1bQ9gYcIrLV2KZPPt3IqPv07fHR6qYL/rUZ7HP3/y2/zwXLt/FY8I2ihfTofOndrnmtsx3PJ06N8XSygwbmyrMmPklUVGxnDt7VS3uzp17zJyxitlzvkJbWyvXcteu2U0DF1sGD+lEtWoVGTykE/Xq12btmvRv+2v8duHm1oyu3ZpjYVGRcRP6YWJixKZN+3ItPzfLfbdiamKMl9c32NlVp1Kl8jRoYE/lyqbZbpN+XH3x4rhqhZtbC1au3P5KnXe+OK66vjiuur44rna+cZ0zWrFiKm5uLbGyqoKNTVW8vDyIjIzh7NnsRx1f5jBR1TbaZGobfn7bVW3DwsLsRduwf622kVdaWlqULWuoWsqU0c829r9u33nRvHldmjRxpmrVilStWpHhw/ugp1eMsNB/35scXnrfX4s3oijA5T0kHbv/WFRUFD179mTgwIGcP3+egwcP4ubmhlKpPpqzaNEiGjRowODBg4mKiiIqKgozMzMCAgIAuHDhAlFRUSxatCjbfXl7e+Ps7ExISAjDhg3jyy+/5N9/096gHjx4QPv27bG1teXUqVNMnz6dsWPHvr3EX5g27WeaNnHGxcUh19jQ0H9xdXVUW9ewkSNnwy/z7Nnz9JiGGWPqEBqS9RtxTlo3s+b02UiWeXcn7NBo9vwylF5dnHLcpnTJYqSmpqpG9YzKlKCOvRmx9x6xfd0gQg+Nxn/VAD5yzDyt+pKOthZ2NU05FKz+QX4oOAJnezMAKlcypHzZUmoxyc9SOHryOs4OZvnO9eGDxwDov9K5Tk1NZfzYH+g/sB2WVnkrMyzsEi4u6h1LV1c7QkPSRraeJT/n3NmruLiqx7i42hEW8uajX3/8cZzatS359ps5uDToR+dOw9myZW+O24SGXsDV1UFtXebj6gKuDTPHvM5xlV8PHjwCQF8/+xH4rNpGo0Z1CM/QNho2zBjjSEhIwU2DZ3T9eiSNGvanRfMvGDF8LjdvRmcb+1+37/xKSUlh166/ePz4KQ6ONlnGvMs5aNJrkW9yjp34L0VFRfH8+XPc3NwwNzfH1taWYcOGUbKk+uiVvr4+RYsWRU9PDxMTE0xMTNDS0qJMmTIAlCtXDhMTE/T1s/8W1rZtW4YNG4alpSVjx47F2NiYgwcPArB+/XoUCgW+vr7UrFmTTz75hNGjR7+1vAF27fqLc+euMGJkzud6vBQTm4CRsXp+RkYGPH+eQnz8fQBiYxMwMjLIFBMTE5/v+lWuZEifz5y5eiOOXu5rWbvlJNPGf0LXDvZZxusW1Wb88JZs232Gh4+SAKhSKW36cuSwpqz3/4fe7msJPx/F5hX9qFq5TJbllDHUQ1tbi9i4R2rrY+MeUs447bh4+W/GmJi4h5Q1znnkMyOlUsmc2Wup42SNVfX0DtyK5TvQ0irC530+yXNZsVm9Rsb6xMYmABCfcJ+UlNQsXsf0mDdx8+YdNm78nSrmpixfMZnPenyM54zlBAb+me02eT+uMtf5dY6r/FAqlXh5rcDJqSbVq1fJNi42Nh5jY4MM9Xt7bSMv7O2smTV7OMtXTGH6jK+IiY2nZ48xqvpk9F+377y6cOEadRy7Y2fbhSmTf2LpDxOwtMz6i9m7moOmvBbi9cjtTv5j9vb2tGjRAltbW9q0aUPr1q3p2rUrhoa5n8+UX3Z26aMkCoUCExMT7t69C6SN+NnZ2VGsWDFVTN26dXMsLykpiaSkJLV1RXWT0dXN/RyvqKgYZnr6smLltDzFv1pvNS9GNl9dn+n8VqUy83Z5UKSIgtNnI5m16AAAZ/+NprplWfp2/wj/HWFqsdraRfhxbleKKBRMmL5LrQyAdb+cZEtg6Ityfse1flU+c6vDrIX7s91/xlFbhUKRaV1eYnLjOX0VFy9cZ836qap1Z89eYd3a3/glwCvff7uM8Upl5nUKco95HUqlklq1LRgxog8ANWtW4/LlG2zc+DudOjXLc52zPq4yxhRMnXMybdrPXLx4jQ0bZucam/nvnnsOBfV3z0rjJuqj2w4ONrRuNYTAwD8YMKBTltv8l+07r6pWrci2wIXcv/+IvXuDGTd2IWvXzcy2c/cu5qApr8Vrewer9F+SEbv/mJaWFvv27eO3336jZs2aLFmyBGtra65evZr7xvmko6Oj9lihUJCamgqkfQhk98GQHS8vL/T19dUWL69learL2bMRxMUl0sVtOLVqdqJWzU6cOB7O2rW/UqtmJ1JSMp9/VtbYgNiYBLV1cfcS0dbWwsAgbZrK2Ngg08hP3L3ETKMZeXE35iEXI2LU1l2+EksFU/VvstraRfjZuzuVKxnSc/Aa1WgdwJ2YBwBZllPRRL2cl+7FP+b585RMI29GZUoQ82KE7m7sQ4BMMcZlSmQaxcvJzBmr+PPPk6z0m4SJiZFq/amT/3Iv7j6tmn+Ffe1e2NfuRWRkLHPnrKV1i6+yLc84i9foXlyiarTL0KA0WlpFMr1G9+4lZhoRex1lyxpiaaE+bWxRrRJRkTHZbPHfH1d5NX36Mv744zh+fp6YmBjnGGtsbJhppOReljlkjEl4qzm8Sk+vGNWrV+H6tayvvn5XX4eiRXWoUqUCtrZWjBzZDxubqqxZk/W5le9qDhm9r6/F61IqFAW2vI+kY1cIFAoFrq6uTJ06lZCQEIoWLcq2bdsyxRUtWjRTh6do0bTRrqw6QvlhY2PD6dOn1UbgTp48meM248ePJzExUW0ZP949T/urX9+OHTuXsC1wkWqpXduS9u2bsC1wEVpamU/Ud3CwITg4VG1d0OEQatW2REdHOz0mKHNMdufE5OREyA0szNU/UKtVMeJ2VILq8ctOXdXKZfjsCz/iE5+oxd+8nUDUnfu5lvOqZ89TOH0uisYNLNTWN25QjZNhNwG4cSueOzEP1GJ0tLWo71yFk6E3c81NqVTiOX0l+/cdZ+Wq76lUqZza8+07NGJr4Bz8t85WLeXKGTJgYHuWLZ+Qbbn29lYcCT6jti44+DQOjtXT6lhUm5q1qmaKORJ8BvsXMW/CsY4NV6/eVlt37VokFSpmfxsYBwfrLI6r0AzHlXUWx1Xoax1XuVEqlUyb9jN79wbj5+eJmZlJrttk1TYOHw6hdoa2ERSUOcbRsUZBVT1HycnPiIi4RdmyWZ+C8F+379elVCpJTn6W5XPvSw6a8lqIvJGO3X/s2LFjzJw5k5MnT3Ljxg22bt1KTEwMNWpkfrM1Nzfn2LFjXLt2jdjYWFJTU6lSpQoKhYJff/2VmJgYHj58+Fr16NWrF6mpqQwZMoTz58+zZ88e5s2bB2Q/VaOrq0vp0qXVlrxOq5YsqUf16lXUluJ6xTAwKKU6l8jb24+xYxaotunR42MiI+/i5bWCiIibBPjvIyBgPwMHdlbF9OnbnqCgEHx9ArgScQtfnwCOHAmjX78O+f6b+K49Qh27Snw9uBHmZmXo1NaW3l2dWL0x7b5sWlpF8Jn/Gfa1KvD1uAC0ihShrFFJyhqVROeVK0h/XhXEwN71+LRVTczNyjD6q+ZYVDVm49ZTqpjNy/vRv2f61LfvmmB6dqnDZ50dsaxmzJQxH1PRVJ+1m0+oYpavPcrXgxvxcQsbrC3LscCzE0+ePmPbrtO55jZj2kp+3XmY2XO/pkSJ4sTGJBAbk8DTp8kAGBiWwqq6mdqira2FsbEBVatWUJUzfuwPLJi/UfX4876fEBx8mhW+27ly5TYrfLdz9Eg4ffqmn6fXt9+nBAT8wdaAP4mIuM1sLz+iomL57LOW+Xl5stS/XwfCwi7y88+/cP16FDt3HmLLlr307tVWFePtvZaxYxaqHqcdVzF4ea18cVztf3FcdVTFpB1Xofj6bH1xXG19cVy1f+M6ZzR16k/s2HEQb+9RlChRnJiYeGJi4nn6NP1Ll7e3H2PGzM+Qw128vJYTEXETf/99BATsU2sbfft2ICgoBB8ffyIibuLj4//abSMvZs9eyfHj4dy6GU1Y2AW++WYWDx8+plPn5qocCrN958X8+Ws4efIst27d4cKFayxYsJbjx8Np377Je5MDaMZr8UY+8Isn5By7/1jp0qX566+/WLhwIffv36dKlSp4e3vzySefsHnzZrXYUaNG0a9fP2rWrMmTJ0+4evUq5ubmTJ06lXHjxjFgwAD69u2rdlPj/NRj586dfPnllzg4OGBra8ukSZPo1auX2nl3/6WYmHgio9Kn0CqZmbDMZzKzvJazYf0uypUrw8SJg2nTxkUVU6dODbznj2bRwnUsXrweMzMT5i8Yjb29db73HxYeyRcemxj3bUs8hjbh5u0EJs/+nW270kabTMuXpk3ztG+n+wKGqW3bdcAqjpy4BsDydUfR1dVmytiPMShdnHMXo+k5eI3qtikAVcwMKWOop3q84/ezGOrrMXxoE8qVLcWFS3fp8+V6bkclqmJ+XHmYYsW0mfldO/RLFyPk9G16DVnLo8fJuea2+cWtRQb0m6a2fsbMoXTq3DTPf6OoqFjVeYQAjo7WzPX+hiWLtrBkyRbMzMoz1/tb7OytVDGftHUhMeEhP/8YQExMAlZWZvz087gcR9XyytbOiiVLxzF//lp+/GELlSqVZ/yEQbTv0EQVExNzL8NxVZ5lPt8zy2slG9bvfnFcfZHhuLLBe/4oFi1cz+LFG14cV6Owt3/zUcaMXt5YuE8f9ZFRL69vcXNrqcoh6pUczMxM8PGZjJfXctar2sYQ2rRxfSWHGsyfP4aFC9eq2saCBWNeq23kxZ3oOEaOmEdCwn0MDUtj72DN5i1zqVix3IscCrd950VcbAJjxiwg5u49SpUqgbW1Ob7LJ6uuGH0fcgDNeC3eyPvZHyswCmV+z7wWGmv9+vUMGDCAxMREihcvnqdtlGjGzSkr1d5Q2FUoENdOdyrsKrwx7SKF88WioCnI/T6A7zol8vEgCpaCt98RtGy/usDKuryzf4GV9V+REbsP2Jo1a6hWrRoVK1YkLCyMsWPH0r179zx36oQQQoh3znt60UNBkY7dByw6OppJkyYRHR2Nqakp3bp1w9PTs7CrJYQQQry+9/TcuIIiHbsP2JgxYxgzZkxhV0MIIYQoOB92v06uihVCCCGE0BQyYieEEEIIzSHn2AkhhBBCaIgPvGMnU7FCCCGEEBpCRuyEEEIIoTk+8CEr6dgJIYQQQnPIVKwQQgghhNAEMmInhBBCCM3xYQ/YScdOCCGEEJpD+YH/8oRMxQohhBBCaAgZsRNCCCGE5vjAL56Qjp0QQgghNMeH3a+Tjp0QQgghNIicYyeEEEIIITSBjNgJIYQQQnPIOXZCiFvhPQq7CgWiQq11hV2FN3b9jFthV6FAFC1SqrCr8MYUGnKykhJlYVehgKQWdgXeD5px2L42mYoVQgghhNAQ0rETQgghhOYooii4JY+mTJmCQqFQW0xMTFTPK5VKpkyZQoUKFShevDhNmzbl7NmzamUkJSXx9ddfY2xsTIkSJejQoQO3bt3Kf/r53kIIIYQQ4l1VCB07gFq1ahEVFaVazpw5o3puzpw5zJ8/n6VLl3LixAlMTExo1aoVDx48UMV4eHiwbds2Nm3axOHDh3n48CHt2rUjJSUlX/WQc+yEEEIIId6Qtra22ijdS0qlkoULFzJx4kTc3NLOIfbz86N8+fJs2LABd3d3EhMTWbFiBWvXrqVly5YArFu3DjMzM/bv30+bNm3yXA8ZsRNCCCGExlAqCm5JSkri/v37aktSUlKW+7106RIVKlSgatWq9OjRgytXrgBw9epVoqOjad26tSpWV1eXJk2aEBwcDMA///zDs2fP1GIqVKhA7dq1VTF5JR07IYQQQmiOApyK9fLyQl9fX23x8vLKtMt69eqxZs0a9uzZg6+vL9HR0bi4uBAXF0d0dDQA5cuXV9umfPnyqueio6MpWrQohoaG2cbklUzFCiGEEEJkYfz48YwYMUJtna6ubqa4Tz75RPX/tra2NGjQAAsLC/z8/Khfvz4Aigz311MqlZnWZZSXmIxkxE4IIYQQmkOhKLBFV1eX0qVLqy1ZdewyKlGiBLa2tly6dEl13l3Gkbe7d++qRvFMTExITk4mPj4+25i8ko6dEEIIITRHIV0V+6qkpCTOnz+PqakpVatWxcTEhH379qmeT05O5tChQ7i4uADg5OSEjo6OWkxUVBTh4eGqmLySqVghhBBCaI5CGLIaNWoU7du3p3Llyty9e5cZM2Zw//59+vXrh0KhwMPDg5kzZ2JlZYWVlRUzZ85ET0+PXr16AaCvr8+gQYMYOXIkRkZGlClThlGjRmFra6u6SjavpGMnhBBCCPEGbt26Rc+ePYmNjaVs2bLUr1+fo0ePUqVKFQDGjBnDkydPGDZsGPHx8dSrV4+9e/dSqlT6Tw8uWLAAbW1tunfvzpMnT2jRogWrV69GS0srX3VRKJVKTfkRPVEIlFwo7CoUEM34DUb5rdh3hyb8VqymkN+KfXcoqPHW91Htq20FVtaVpZ0LrKz/iozYCSGEEEJzvMG5cZpALp4QQgghhNAQMmInhBBCCI2hzOd93zSNjNi9p5o2bYqHh4fqsbm5OQsXLiy0+gghhBDvhCIFuLyHZMSugPTv35+EhAQCAwMLZf8nTpygRIkShbJvIYQQQrwb3tP+qMiobNmy6OnpFXY18mzZsl+wse7ATE/fHOOOHw/HzW04drZdaNliMJs2/pYpZs+eYD5t+z9sa7vxadv/sW/fkbdVbQDu3Ilj9KgF1KvXBwf77nTq6EF4+OUct0nLYwR2tt1o2cKdTRt/zxSTlsdX2Nbuyqdtv2LfvqOvXUeTcqVZOqsbZ4MmcuXkZPYFfIVdzQqq50cOa87fOz2IODGZ88HfsXn5ABxtK6mV8Xm3jwhYNYiLx74n6qwnpUsVy9O++/Wox7E9I7l6agp7tgyjXp0qmWJGDmtOyJ9jufLPFAJWDaK6Rblcy13us50e3b6jntNAmrgO5ZuvvLl6NVIt5vGjp3hOX0WLpl/h7NCPDp+OYvPGfdmUmG7f3uN0bDeaOnZ96dhuNAf2ncgUs2nDPj5u+S1O9v3o3mUC/5z8N9dy82P9+l00bz4IW1s33Nw8OHnybI7xx4+fwc3NA1tbN1q0+IKNWbaNINq2HUbt2p1p23bYW20bJ06EM3ToNBo27Ie1dXv27899X+9aDhm9r+9TzZsPxsa6U6Zl2tRlueTw371HvVXvwA2KC5N07PLJ398fW1tbihcvjpGRES1btmT06NH4+fmxfft2FAoFCoWCgwcPAjB27FiqV6+Onp4e1apV4/vvv+fZs2eq8qZMmYKDgwNr167F3NwcfX19evTowYMHD1Qxjx49om/fvpQsWRJTU1O8vb0z1SvjVKxCoWD58uV07twZPT09rKys2LFjh9o2O3bswMrKiuLFi9OsWTP8/PxQKBQkJCQU6N8sozOnL7Fl8x6src1zjLt1Mxr3IVNxdqrJtsCFuA/thqenL3v2BKtiQkL+ZcTwOXTo2JTt2xfToWNThnvMISzs7dyGJTHxIT17jkNbRwtf3+/5ddcSxo4bQOnS2Y+W3rp5B/ch01/kMR/3oV3x9FyeRR7zXuSx8EUecwkLu5jvOuqXLsaOdUN49jyF3kP9aNxhEVPn7CbxwVNVzJXrsUzw3Emzzovp2MeHm7cT2OQ7ACPD9C8HxYvp8GfQJRb7Hsrzvjt8bMu0cW1Z5HOI1l1/4Nipa6xf1o+KpvqqmP8NaoR7P1cmeu7kk89+5G7sQzYvH0AJvaI5ln3yxHl69GrF+k3T8FkxnpTnqbgPmsXjx+l5zZm1lqDDp5k1Zxjbd82jT79P8PL0448DJ7MtNzTkIqNHLKZ9h4b4B3rRvkNDRo1YzOmw9M7677uPMHvWGga7d+KXrTNxcrLhS/fZREXG5vlvk5Pdu//Gy2s5X37ZncDARTg51WLw4ClERt7NMv7mzWiGDJmKk1MtAgMXMXRoNzw9fdizJ0gVExLyL8OHz6Fjx2Zs376Yjh2b4eEx+621jcePn2JtXZVJk9zzFP8u5vCq9/l9yt9/Hn8fXqVaVq6aCkCbj7P+BYP/+j3qrSvAnxR7H0nHLh+ioqLo2bMnAwcO5Pz58xw8eBA3NzcmT55M9+7d+fjjj4mKiiIqKkr1EyClSpVi9erVnDt3jkWLFuHr68uCBQvUyo2IiCAwMJBff/2VX3/9lUOHDjFr1izV86NHj+bPP/9k27Zt7N27l4MHD/LPP//kWt+pU6fSvXt3Tp8+Tdu2benduzf37t0D4Nq1a3Tt2pVOnToRGhqKu7s7EydOLMC/VtYePXrCqNHeTJ/xFaX1S+YYu2nT75ialmXCxMFYWJjRrVtr3NxasnJl+j2K1vjtwMXFAXf3blSzqIS7ezfq17fDz29HDiW/vuW+WzE1McbL6xvs7KpTqVJ5GjSwp3Jl0zzk8cWLPFrh5taClSu3v5LHzhd5dH2RR9cXeezMdx3/N6gxkdGJDP9uK6FnbnErMoHDx65w/eY9Vcy2Xaf5+2gEN27FczHiLlPm7KZ0qWLUqG6iivFdG8zS5X/xT9jNPO/bvZ8rGwP+YUPASS5diWHSrN1ERiXS77N6qpjBfVxZ5HOQ3fvPceHyXb6d4E/xYjq4fWqfY9k/+46jU+cmWFpVwtqmCtNnuhMVFcu5s1dVMWGhl+jQsREf1a1JxYpl6da9BdWtK3M2/Eq25a5b8zv1XWz5YkhHqlWryBdDOlKvfi3WrUkfdVnjtxs3t6Z06daMahYVGTuhLyYmRmzetD/Pf5ucrFoVSJcurejWrQ0WFmZMnDgYExPjLEewIP2YmqhqG20ytQ0/v+2qtmFhYfaibdi/tbbRpIkzw4f3oXXrvP380buYw0vv+/tUmTL6lC1rqFoO/nmCypVNqFu3di45/DfvUeLtko5dPkRFRfH8+XPc3NwwNzfH1taWYcOGUbJkSYoXL46uri4mJiaYmJhQtGja6MN3332Hi4sL5ubmtG/fnpEjR7Jlyxa1clNTU1m9ejW1a9emUaNG9OnThwMHDgDw8OFDVqxYwbx582jVqhW2trb4+fmRkpKSa3379+9Pz549sbS0ZObMmTx69Ijjx48D8PPPP2Ntbc3cuXOxtramR48e9O/fv2D/YFmYNu1nmjZxxsXFIdfY0NB/cXV1VFvXsJEjZ8Mv8+zZ8/SYhhlj6hAaUrDTZC/98cdxate25Ntv5uDSoB+dOw1ny5a9OW4TGnoBV1eHDHXMmMcFXBtmjnmdPNo0q0HY2dv4zO/Bmb/Gs9f/f/Tu6pxtvI6OFp93+4jE+084dyE627jc6OhoYVezAoeC1aelDwVfxtmhMgCVKxlSvmwpDgWlxyQ/S+HIyWs4O1bO1/4ePngMgP4rH7yOTtYc/PMUd+7cQ6lUcvzYWa5fi8a1oV225YSFXcLFxVZtnYurHaEhlwB4lvycc2ev4uJqlyHGltCQNx+tSE5+xtmzl2mY4Th2dXUkJOR8lttk1TYaNapDeIa2kbHMRo2yL/O/9i7n8L6/T70qOfkZO3Ycwq1LCxTZjED91+9Rb90HPhUrF0/kg729PS1atMDW1pY2bdrQunVrunbtiqGhYbbb+Pv7s3DhQi5fvszDhw95/vw5pUuXVosxNzdX+1kRU1NT7t5Nm4KJiIggOTmZBg0aqJ4vU6YM1tbWudbXzi79g6hEiRKUKlVKVe6FCxf46KOP1OLr1q2bY3lJSUkkJSWprSuqm4yubs5TaC/t2vUX585dwd8/81RyVmJiE2horK+2zsjIgOfPU4iPv0+5cmWIjU3AyMggU0xMTHye9pFfN2/eYePG3+k/oAPuQ7ty+vQlPGcsp2hRHTp1avaGeWSM0X+tPCpXMqTvZ3Xx8Qtisc8hHG0rMX18O5KTn/PLjlBVXMsm1vw87zOKF9PhTsxDPhu8insJj/O9v5fKGOihra1FTNxDtfUxcQ8pa5zW+SpnXEq17lWxcQ+pVMEgz/tSKpXMnb2OOk7WWFU3U60fP6EfUyb50rLpV2hra6FQKJg6fTB1nGyyLSs2NgGjjK+PsT6xsQkAxCc8ICUlNXOMkT5xsYl5rnN24uPvp5Wf4Tg2NjYgJiYhmzrHY2ysHl/YbSO/3tUcNOF96lUH9h/jwYNHdO7cItuY//o96q17P/tjBUZG7PJBS0uLffv28dtvv1GzZk2WLFmCtbU1V69ezTL+6NGj9OjRg08++YRff/2VkJAQJk6cSHJyslqcjo6O2mOFQkFqatpPx7zJL77lVm7Gb2+57cvLywt9fX21xcsr+5NxXxUVFcNMT1/mzh2R547gyzpnqGSm9Zm+hGaRW0FRKpXUrFWNESP6ULNmNXr0aEO37q3YmMWJxq/KWx4ZY7JYlwdFiig4cy4Sr0X7CP83irW/nGC9/wn6vjIdChB0/AotuyylfW8f/jx8ER/vHhiVefMrqzMeRwqFgoy/6JTxUFMo8nese05fzcULN5g97yu19evX/c7psMss+XEkm/w9GTW2NzOmreJI8Jkcy8uqLeT2t1cqKdAPkKzrkL/4jOszx7zeMfW2vGs5aMr71Kv8A/bTqHEdypcvk2Pcf/ke9bYpiygKbHkfyYhdPikUClxdXXF1dWXSpElUqVKFbdu2UbRo0UzTo0FBQVSpUkXt3LXr16/na3+Wlpbo6Ohw9OhRKldOm6qKj4/n4sWLNGnS5LXzsLGxYffu3WrrTp7M/gRzgPHjxzNixAi1dUV185bP2bMRxMUl0sVtuGpdSkoqJ0+cZf36XZw+E5Dph47LGhsQm2HEIu5eItraWhgYpI38GBsbqEZWXo3JOBJQUMqWNcTSwkxtnUW1Suzdk/0Vbv91HndjHnAxIkZt3aUrMXzaSv38midPnnHtxj2u3bjHqdM3Cdo9nF5uTixZ/le+9wlwL+Exz5+nqEblXjIuU0I1Qnc3Nu2ioHLGJVX/D2BUpmSmUbzszJyxmoN//sPqtZMwMTFSrX/6NJlFCzezaPEIGjdNm/aytq7MhfPX8Vu1iwYZpltV9cvi9bkXd181OmFoUAotrSKZRufu3UvMNILxOgwNS6OlVYTYWPWRj7i47F9/Y2PDTCMl97I8pjLGJLy1tpFf72IOmvI+9dLt23c5EnyaJUvG5hj3Lucg8k9G7PLh2LFjzJw5k5MnT3Ljxg22bt1KTEwMNWrUwNzcnNOnT3PhwgViY2N59uwZlpaW3Lhxg02bNhEREcHixYvZti1/P05csmRJBg0axOjRozlw4ADh4eH079+fIkXe7KVzd3fn33//ZezYsVy8eJEtW7awevVqIPtvYLq6upQuXVptyeu32vr17dixcwnbAhepltq1LWnfvgnbAhdlerMEcHCwITg4VG1d0OEQatW2REdHOz0mKHOMg2P2U29vwrGODVev3lZbd+1aJBUqls12GwcH6yzyCM2Qh3UWeYS+Vh7HQ25gWdVYbZ2FuTG3InOeMlEoFBQt+vrf9Z49S+H0uUgau1iqrW/sYsnJ0BsA3LgVz52YB2oxOjpaNHA252TIjRzLVyqVeE5fxYF9J1ixaiKVKqnfIuX58+c8f5aCIsO37CJaRUhNzX400N7eKtOIXnDwGRwcrdLqV1SbmrWqZoo5EhyOg2P1HOucF0WL6lCrliVBQSEZ6hCKo2PWP5ieVds4fDiE2hnaRlBQ5pjsyvyvvYs5aMr71Etbtx7AyEifJk2zP8cW/vv3qLfuAz/HTjp2+VC6dGn++usv2rZtS/Xq1fnuu+/w9vbmk08+YfDgwVhbW+Ps7EzZsmUJCgqiY8eODB8+nK+++goHBweCg4P5/vvv873fuXPn0rhxYzp06EDLli1p2LAhTk5Ob5RL1apV8ff3Z+vWrdjZ2fHTTz+pRhZ1dXXfqOyslCypR/XqVdSW4nrFMDAoRfXqafc58/b2Y+yY9CuGe/T4mMjIu3h5rSAi4iYB/vsICNjPwIGdVTF9+rYnKCgEX58ArkTcwtcngCNHwujXr0OB5wDQv18HwsIu8vPPv3D9ehQ7dx5iy5a99O7VVhXj7b2WsWMWZsgjBi+vlS/y2P8ij44Z8gjF12frizy2vsijfb7r6LMmiDp2ZnwzuAnmlcvQ+VM7Pu/6Eas3HgOgeHEdxn/bijp2ZlQyNcC2RgXmTe2MafnS7NwTriqnrHFJatmYUrVy2qhYDavy1LIxxUC/uCpmy4qBDOhVX/V4mV8Qvbo40aOzE1bVyjJ1bFsqmuqzZvNxVYzv2iC+GdyET1rUxNqyHAs9u/Dk6TO27grLMS/PaavYtTOIWXO/okSJ4sTGJBAbk8DTp2mnNpQsqYfzRzWYP3cDJ46f49atuwRuO8TO7X/TomX6B9uEsT+ycP4m1ePP+37MkeAzrPDdwZUrt1nhu4NjR8L5vO8nqpi+/doSEPAn2wIOciXiNrO91hIVFUv3z7I/byk/BgzohL//Pvz99xERcZOZM32JioqhR4+0Onh7+zFmzHxVfHrbWE5ExE38/fcRELBPrW307duBoKAQfHz8iYi4iY+P/1ttG48ePeH8+SucP592BfKtW3c4f/6K6pYt70MOmvI+BWkX5W3b+gedOjVDW1u9Q1rY71Fv3Qd+uxOF8k1O4hIaxdPTk59//pmbN/N+ewslr38fpj59JlDDpioTJg4GYNy4hdy+fZe1a2eqYo4fD2eW13IuXbpBuXJlGDy4Cz16fqJWzu+/B7Fo4Tpu3bqDmZkJHsM/z/MtF9Kl5jnyzz9PMH/+Wq5fi6JSpfL0H9CB7t1bq54fN27Rizw8M+Sx8pU83OjR8+MMeQSzaOH6V/LoTevWDciPCrXWAWkXRkzwaE3VKkbcvBXPsjVBrPdPm2rXLarNj3O642hnRhlDPeITHhMafpuFy/4kLDx9NHLksOaM+l/mjsu3E/3ZEpg2unR87yg2B57C+8c/VM/361GP/w1sRLmypbhw6Q6TZ+/m6D/X1MoYOaw5fbrXRb90MUJO32L8jB1cuJzWAbh+xi3L3Gxr9Mpy/fSZ7nTqnHZaQmxMAgsXbOJI0BkSEx9iWsGYrt2b07dfW9VI9IC+06lQsSyeXkNVZezdc4wli7Zw69ZdzMzK88233WnZWv1iok0b9rFqxU5iYhKwtKrEmHF9cP4o+5GjokVKZftcVtav38WKFVu5e/ce1atXYfz4L/joo7Tp83HjFrw4prxU8cePn8FLrW10pWcWbWPhwrWqYyo/tyPJr2PHztC374RM6zt3bs6sWcMLNQdlxpM88+F9fZ86fDiELwZN5bfff6Bq1YpqzxXme5SCtz9ibP5d1rcJeh3XZnySe9A7Rjp2H7Aff/yRjz76CCMjI4KCgvj666/56quvmDFjRp7LeJOO3bsl72+Y77KXHbv3WXYdu/dNfjt24u15k47du+X9f5/6Tzp2kwqwYzft/evYycUTH7BLly4xY8YM7t27R+XKlRk5ciTjx48v7GoJIYQQr+89nUItKNKx+4AtWLAg069gCCGEEOL9JR07IYQQQmiO9/Rq1oIiHTshhBBCaI4PvGMntzsRQgghhNAQMmInhBBCCI2hlIsnhBBCCCE0xAc+FykdOyGEEEJojg98xO4D79cKIYQQQmgOGbETQgghhOb4wK+KlY6dEEIIITTHB96xk6lYIYQQQggNISN2QgghhNAcH/aAnXTshBBCCKE5lDIVK4QQQgghNIGM2AkhhBBCc3zg97GTjp0QQgghNIdMxQohhBBCCE0gI3biDaUWdgUKhAKtwq5Cgbgd3ruwq/DGLJ1+L+wqFIiIU58UdhXe2NG7Vwq7CgXC0ciosKtQIFKVzwq7Cm9M77/odXzYA3bSsRNCCCGE5ijygc9FSsdOCCGEEBrjA792Qs6xE0IIIYTQFDJiJ4QQQgiN8aGP2EnHTgghhBAaQ/GB9+xkKlYIIYQQQkPIiJ0QQgghNMYHPmAnHTshhBBCaI4PvWMnU7FCCCGEEAXIy8sLhUKBh4eHap1SqWTKlClUqFCB4sWL07RpU86ePau2XVJSEl9//TXGxsaUKFGCDh06cOvWrXztWzp2QgghhNAYiiIFt7yOEydO4OPjg52dndr6OXPmMH/+fJYuXcqJEycwMTGhVatWPHjwQBXj4eHBtm3b2LRpE4cPH+bhw4e0a9eOlJSUPO9fOnZCCCGE0BgKRcEt+fXw4UN69+6Nr68vhoaGqvVKpZKFCxcyceJE3NzcqF27Nn5+fjx+/JgNGzYAkJiYyIoVK/D29qZly5Y4Ojqybt06zpw5w/79+/NcB+nYCSGEEEJkISkpifv376stSUlJ2cb/73//49NPP6Vly5Zq669evUp0dDStW7dWrdPV1aVJkyYEBwcD8M8///Ds2TO1mAoVKlC7dm1VTF5Ix04IIYQQGqOIouAWLy8v9PX11RYvL68s97tp0yZOnTqV5fPR0dEAlC9fXm19+fLlVc9FR0dTtGhRtZG+jDF5IVfFCiGEEEJjFORVsePHj2fEiBFq63R1dTPF3bx5k2+//Za9e/dSrFixHOqmXjmlUpnrDZXzEvMqGbETQgghhMYoyHPsdHV1KV26tNqSVcfun3/+4e7duzg5OaGtrY22tjaHDh1i8eLFaGtrq0bqMo683b17V/WciYkJycnJxMfHZxuTF9Kxe0c1bdpU7TJpc3NzFi5cmOd4IYQQQvw3WrRowZkzZwgNDVUtzs7O9O7dm9DQUKpVq4aJiQn79u1TbZOcnMyhQ4dwcXEBwMnJCR0dHbWYqKgowsPDVTF5IVOxGmLr1q3o6OgUdjVy1Lz5YCJvx2Ra36vXJ0ya7J7lNsePhzNr1kouX7pJuXJl+OKLzvTo+bFazJ49wSxetIEbN6KpXNkEj+Gf06pV/beSA8CJE+GsWLGV8PAIYmLu8cMPE2jZskGO2xw/foZZs1Zw6dKNF3l0oWfPTzLkEcSiReu5cSOKypVNGT68D61a5Vzu63r+PIWlSzfx686/iI1NoGxZQzp1bsaXX3ajSJHsv+8dPx7O7FmruHw57fUY9EUnevRQfz327jnC4sXpr8e3Hr1f+/UoX7YkY79tRBMXc4rpanP1Rjzjpu0l/PxdVcy37g3o4WaLfqlihIZHMXnWH1y6EpdleSuXdKapa1XcR2xn38GIHPf9eTd7Bvd1ppxxCS5eiWPGvIOcCLmtFpOffWfnfWgXF0Ij2L3xT65fuEVC3H2+9hyAU2Nb1fP9G43IcrvuX7ajba/mABzccYQj+05x/eItnj5O4ofdnpQoVTzXfR/YFsRvG/8kIe4+Fc1N6PVNJ6ztq6meVyqVBK7aw6EdR3n04DHValah74guVKxqkmvZWzYdYMumP4i8HQuAhWVF3L/sSMPG9gA8fvSUhQu28OeBUyQmPKRCRWN6fd6K7j1a5Fju/r0n+GHxVm7evIuZWTm+8uhCi5bOajGbNx5g9crdxMYkYmFZgTHjelPH2TrXOudmhe9uli7cSq/PWzJ6fA8A4mITWTQ/gCPBZ3n44Al1nKwYM7EXVarkPAq0f+8//LgkkFs3Y6hkVpavvu1M85Z11GK2bPwTv1V7iI1JwMKyAqPG9aCOU/U3zuNNFMZvxZYqVYratWurrStRogRGRkaq9R4eHsycORMrKyusrKyYOXMmenp69OrVCwB9fX0GDRrEyJEjMTIyokyZMowaNQpbW9tMF2PkREbsNESZMmUoVapUYVcjR/7+8/j78CrVsnLVVADafJz1N5FbN+/gPmQ6zk412RY4H/ehXfH0XM6ePelXB4WE/MuI4fPo0LEp27cvpEPHpgz3mEtY2MW3lsfjx0+xtq7KpElZf+hmdPNmNEOGTMXJqRaBgYsYOrQbnp4+7NkTpIoJCfmX4cPn0LFjM7ZvX0zHjs3w8JhNWNiFt5LD8uVb2bxpD999P5hdu5YwalRfVq4IZN26Xdluc+vWHYa6z8DJuSZbt3kzxL0LMz1XsHfPEbU8RoyYR4cOTQncvoAOHZoyYvi813o9SpfS5ZdVn/H8eQoDvt5G665+zFxwiPsP0q9Ic+/3EQN712HK7D/o1Gc9MXGPWPNTF0roZf6SM7B3HVDmbd+ftq7Od6Oa8sOKY7TrtY6TIbdZuaQzFUzS21h+9p2T96FdJD1NprJlBT4f7pbl8wsDp6gtg8b1QKFQ4NzUXq0M23o2tOuT9w+oYwdC2LA4kPZ9WjJtxUiq21dl/mgf4u6kT1Xt3vAHezYf4vPhbkz2HY5+mVLMHf4zTx4/zbX8cuXL8O3w7mz4ZSobfplK3Xo1+farRVy+lHZD2LmzNxD89xlmznZn269efN63DbM81/HngVPZlhkWepkxI3+kXQcXftk2nXYdXBgz4kdOh6V/kfj9t2PM8VrPYPf2bA6YRh0na4a5exMVmb8vBRmdPXOVrb/8hVX1Sqp1SqWS4d/8wK1bMSxc8hUb/SdhWsGIoYO8efI4+6s7w0IjGDdqGZ92aMDmrZP5tEMDxo5cxpnTV1Qxe347ztxZmxg0pC0b/SfhWKc6X7kveuM83lRh38cuO2PGjMHDw4Nhw4bh7OzM7du32bt3r9pn94IFC+jUqRPdu3fH1dUVPT09du7ciZaWVp73Ix27ArJz504MDAxITU0FIDQ0FIVCwejRo1Ux7u7u9OzZk7i4OHr27EmlSpXQ09PD1taWjRs35mt/q1atQl9fXzVkm9XU7cyZMxk4cCClSpWicuXK+Pj4qJURHByMg4MDxYoVw9nZmcDAQBQKBaGhoa/3R8hFmTL6lC1rqFoO/nmCypVNqFu3dpbxmzb9jqlpWSZM/AILCzO6dWuFm1sLVq7cropZ47cTFxcH3N27Us2iEu7uXalf3w4/v51vJQeAJk2cGT68D61b521o/GUeEycOfpFHG9zcWrJy5TZVjJ/f9hd5dMPCwgx3927Ur2+Pn9+Ot5JDaMgFmreoS9OmzlSsVI42H7vg6upAeHj2o1ibNu3B1NSYCRMGvfJ6NGflykBVzJo1v+LiYs8Q9y5Uq1aJIe5dqF/fjjWv8XoM7f8RUXceMGbKXk6fjeZ21H2Cj9/kxq1EVcyAXo78uOI4e/64zMWIOEZP2kPxYtp0+MRGrSwbK2MG9nZizNQ9edr3oN5O/BIYzpbAcCKu3mP6vINE3XlA767pHZW87js370O7sKtfgy6D2+LcxC7L5w2MSqstpw6HY+NoSbkKRqqYNt2b0O7zFljUqpLn/e7ZfIjGn9ajSfv6VDAvT+9vOlOmnAF/bEv7UqRUKtm75S/a922JcxM7KlUzZfDEXiQlJXN0X/adr5eaNnOkURN7zM1NMDc34WuPrujpFeP06bR2EBZ6mfadGvJR3RpUrFiWrt2bUd3ajLNnr2Zb5ro1e6jfoBaDhrSnarUKDBrSnrr1a7J+bfqxt3b173Tu0hi3rk2pZlGBMeN7Y2Jahi2bDuT5b5PR40dPmTB2Od9P7UtpfT3V+hvX73Am7AoTJ31OLduqmFc1Yfz3n/PkcRK/7T6WbXkb1u6jXoOaDBrclqrVTBk0uC1169mwfk36/dTW+e2jU5eGuHVtTDWLCowe3wMTU0N+2XzwtfPQJAcPHlQ7hUqhUDBlyhSioqJ4+vQphw4dyjTKV6xYMZYsWUJcXByPHz9m586dmJmZ5Wu/0rErII0bN+bBgweEhIQAcOjQIYyNjTl06JAq5uDBgzRp0oSnT5/i5OTEr7/+Snh4OEOGDKFPnz4cO5Z9I3vVvHnzGDVqFHv27KFVq1bZxnl7e+Ps7ExISAjDhg3jyy+/5N9//wXgwYMHtG/fHltbW06dOsX06dMZO3bsG/wF8ic5+Rk7dhzCrUuLbIfNQ0Mv4OrqoLauYSNHzoZf5tmz5+kxDTPHhIb8+zaq/VpCQ//F1dVRbV2jRnUIV8vjXxo2zBjjSEjI+bdSJyenGhw9cpqrV9OmFv/99yqnTp2nSWOnbLfJ6vVwbejI2bMRqjzCQi/gkinGgZDQ/I88tmhiwZlzd1g6ux3H9w9l54bP+axz+vSfWUV9ypUtyd9Hr6nWJT9L4dg/t6hjV0G1rlgxbRZ5fcqU2X8QG/c41/3qaBehdo3y/H30utr6v49cp459hXztO780oV0k3nvA6SPnaNyu7huV8/zZc65dvEXtuurTerU/suZy+DUAYqLukXjvAbU/Sp/C1CmqjY2DhSomr1JSUvlt91GePEnC3t4SAMc61Tn0Zwh37txDqVRy/Nh5rl+7g4urbbblnA69TANX9Q9rF9fahIVcBuBZ8nPOn7uWKaaBS23CQi/nq86v8pqxnkaNbanfoKba+uTktGOiaNH0kWQtrSLo6GgTeir7/Z0OvUIDF/WyGrjWUtUxLY/rNHCppRZT36UWYaE5n+bwthXmDYrfBXKOXQHR19fHwcGBgwcP4uTkxMGDBxk+fDhTp07lwYMHPHr0iIsXL9K0aVMqVqzIqFGjVNt+/fXX/P777/zyyy/Uq1cvx/2MHz8ePz8/Dh48iK1t9m8uAG3btmXYsGEAjB07lgULFnDw4EFsbGxYv349CoUCX19fihUrRs2aNbl9+zaDBw9+8z9GHhzYf4wHDx7RuXP256rExCbQ0FhfbZ2RkQHPn6cQH3+fcuXKEBubgJFRxhh9YmLUryoqTLGx8RgbG6ityzqPzDFvK48vBrvx4MFjPm37NVpaRUhJScXDozeftmuU7TaxMfEYZeh8GmeRh3GGPIyNDIh9jTwqV9Snd1d7Vqz/hx9XHsO+tgmTRzcjOfk523adp6xR2qhExs5a7L3HVDQtrXr83cimnAqLZP+hvH3YGBoUR1u7CLFxj9TWx917rNpnXvedX5rQLoJ+O0ExPV2cGmc9updXDxIfkZqSSmlD9VNMShuWIvFe2k8wJcbdT1tXJnNMXHTecr108SZ9ek4nOfkZenrFWLD4GywsKwIwbsLnTJ28ktbNhqOtrYVCoWDy9IE5nkMWG5uY5d8+NjZtpDk+4QEpKak5xuTX77uP8+/5G6zb/F2m58yrmmBawYglC7fy3eQ+FC+uy1q/vcTGJhIbk/3+sssjLvb+izwekpKSShmj0hliShP3mnkUlPe1Q1ZQpGNXgJo2bcrBgwcZMWIEf//9NzNmzCAgIIDDhw+TkJBA+fLlsbGxISUlhVmzZrF582Zu375NUlISSUlJlChRIsfyvb29efToESdPnqRatWo5xgJqv1OnUCgwMTHh7t20k84vXLiAnZ2d2v126tbN+Rv2y3q+qqhuMrq6RXOtS0b+Aftp1LgO5cuXyTEu06iFUplpfeaYwjl5NidZ3bso4/rMMW8vj927D7Nz5yHmzhuOlWVlzv97Fa+ZKyhXzpBOnZtnu12mOpKHPMjfPZhU5RRRcObcHeYtTZt2O3chBqtqxvTuZs+2XekjmRlPm1OgeHmY0KJxNVw+MqNdz3X53n+m0/EUqsMvT/t+HZrQLv7afZz6rZwoqlswF3NlecxlWKcgi/aVx1TNzU3ZsnU6Dx48Zv/eE3w/wZcVfuOxsKzIhnV7OR0WwaIfPKhQwYh/Tl5g5rQ1lDU2oH6GkSr1Oqs/zuo+ZK9zP7OsREfdY+6sjfzoMwLdLP7mOjrazFv4JVO/96OJy7doaRWhXv0auDbKeqpfvZIZ8kCZKbeCykMUHJmKLUBNmzbl77//JiwsjCJFilCzZk2aNGnCoUOHVNOwkNZBW7BgAWPGjOGPP/4gNDSUNm3akJycnGP5jRo1IiUlhS1btuSpPhmvklUoFKpzALNqfMpcPpGyvgO3T47bZOX27bscCT5Nt67ZTyMDlDU2IDYmQW1d3L1EtLW1MDBI+4ZubGxAbGzmmIwjZIXJ2Ngw00jJvSzzyBiT8NbymDfXjy8Gu/Hpp42obl2Fjh2b0q9/B3x8tma7jXFZw0x1jIvLnEdMFjFGr5FHTOwjLme4wjTiahwVTNJGCGJejJa9HD17yahMcdVom0vdylSuZEDoof9x8bgHF497APDj3PZs8OmW5X7jE57w/HkqZY3Uv2gZGeoRe+9xnvedX5rQLi6EXSH6xl2atM955iEvSumXoIhWERLv3Vdb/yD+IfqGJQHQfzFalCkm4SH6ZfJ2MZlOUW0qVylPrdpV+XZEd6pbm7F+7V6ePk1m8UJ/Ro3tSdNmjlS3rkzP3q1o80ld/Fb/lm15xsaZR97u3buP0Yu6GhqUQkurSKbX59WY/Dh/7jr34h7Qu/t0nO2G4Gw3hH9OXGTj+gM42w0hJSWVmrXM2bx1Mn8dXczeg9784DOcxIRHVKxYNsc8Mo683Yu7rxqhMzQoiZZWkcwx9x5kGsX7r33oU7HSsStAL8+zW7hwIU2aNEGhUNCkSRMOHjyo1rH7+++/6dixI59//jn29vZUq1aNS5cu5Vp+3bp1+f3335k5cyZz5859o7ra2Nhw+vRptRG4kydP5rjN+PHjSUxMVFvGjx+S731v3XoAIyN9mjR1zjHOwcGa4OBQtXVBh0OpVdsSHR3t9JigzDEOjvk7gf1tcnCwyZTH4cMh1FbLw4agoMwxjo413kqdnjxJynRbE60iRVQd/6ykvR5hauuCgkKpVctClYd9FjHBQaE4OuT/Ng7/hEZSzVz9p3WqVjHkdlTah/jN24ncjXlIw/rpJ+PraBehnlMlTp2OBOCnVcdp+9ka2vVcq1oAZngfYsyUrC+kePY8lfDzd2hYr7La+ob1q3AqLDLP+84vTWgXf/16DHPrSlR+MZX5JrR1tDGvXomzJ9Sv5D174iKWtc0BKGtaBv0ypdRinj97zr+hEaqY/FIq4dmz5zx/nsLz5ykUyfDpXiSXdmLnYMnR4LNq644EhWPvmHbenk5RbWrUNM8UczT4LPYOlvmub936NfglcCqbAiarlpq1zGnbrh6bAiajpZXezkuV0qNMmVJcv36Hc2ev0bS5Qw55VOPokXPqeQSfU9UxLY8qHA1WjzkafA57B4t851GQCvInxd5H0rErQC/Ps1u3bh1NmzYF0jp7p06dUp1fB2Bpacm+ffsIDg7m/PnzuLu75/l34Bo0aMBvv/3GtGnTWLBgwWvXtVevXqSmpjJkyBDOnz/Pnj17mDdvHpD9dE3Wd+DO3zRsamoq27b+QadOzdDWVr9829t7LWPHLFQ97tHjYyIjY/DyWklExE0C/PcTELCfgQM7qmL69G1PUFAovj5buRJxC1+frRw5Eka/fu3zVa/8ePToCefPX+H8+bTL/m/dusP581eIjLz7Ig8/xoyZnyGPu3h5LSci4ib+/vsICNjHwIGdVTF9+3YgKCgEHx9/IiJu4uPj/yKPDm8lh2bNPmLZz/4cPHiS27fusm/fUVav3kHLV+5zNt97LWPHLnoljzZERsYw6+XrEbCfrQEHGDiwU3oefdoRHBSKr+9Wrly5ha/vVo4cOU3f13g9Vq7/B4fapgwbWJcqZgZ0+NiGHm52rNsSqopZtSGEYQPr0rqZJdUtjJg79WOePH3Ojt/SLhKIjXvMxYg4tQUgMvo+tyLTR3nW/dyVPp85qB6vWP8P3Tvb0q1jLSyqluG7kU2oYFKK9QFhed53frzr7eLp4ySuX7rN9UtpF9vERt3j+qXbarcdefLoKScOhtG4Xdb3ykuIu8/1S7e5eyvtnnG3rkRx/dJtHt5PH+Gc/e1P7A/4W/W4zWdNOPTrMf7adYzIa3fYsDiQuLvxNOuUdkW6QqGgdffG7Fy3n3/+Os2tK1Esn7kRXd2i1G+lfr+1rCxe8AunTl7g9u0YLl28yZKF/pw8cZ627RpQsmRxnD+yYf68zZw4fp5bt2LYvu1vft0RRIuW6RcZTRy3jEXz02dRevdpzZHgcFYu38XVK5GsXL6LY0fP0btPG1VMn/4fs9X/ENsC/uJKRCRzZ60nKiqObp9lfxpEdkqUKIalVUW1pbheUfT1S2JpldbB3rfnJCeP/8utmzH8+UcIX34xn6bNHWngmj6d/N34FSxeEKB63PPzlhwNPseq5b9x9UoUq5b/xvGj5+ndN/12NZ/3a8W2gL8J3HqYKxGRzJu1ieioe3T9rGm+8xAFR86xK2DNmjXj1KlTqk6coaEhNWvWJDIykho10kZfvv/+e65evUqbNm3Q09NjyJAhdOrUicTEvJ1w6urqyq5du2jbti1aWlp88803+a5n6dKl2blzJ19++SUODg7Y2toyadIkevXqlePv3L2p4OAwIiNjcOuS+eTwmJh7REal36i1kll5lvl8zyyvlWxYv5ty5cowceIXtGmTfpuROnVs8J4/ikUL17N48QbMzEyYv2AU9vZv7waZ4eGX6dt3guqxl9cKADp3bs6sWcOJiblH1Ct5mJmZ4OMzGS+v5axfv+tFHkNo08b1lTxqMH/+GBYuXMvixesxMzNhwYIx2Nu/+Q1Ls/Ldd4NZtHgD06b5cC8ukXLlDOn+WWuGDeuuiomJiScq8pXXo1J5fl72HbNmrWLDht8oV64MEyYOonWb9JsoO9axwdt7JIsWbWDJ4o2YmZXHe/7I13o9Tp+7w5ejdjD6q0Z8Pbg+NyMTmT7vINtf6Tgt8ztBsWLaTBvXHP3SxQgNj6bfsAAePX6Wr31VrqRPGYP0m+Xu2nsRQ/3ifD24PmWNS3AxIo6B32wjMupBge8b3v12cfXCTWZ/86Pq8calabdWcf34IwZP7Amk3XMOpZL6LR2zLOPP7cFsX7VX9djrq6UADBrfg0Zt087vvRsZy4PE9I5evRaOPLz/mO2r95IYd5+KVU0ZMWcwxibp5yC27dWc5KRnrPEO4NHDJ1jUqMyo+e4U18v9fSwu7j4Tx/kQE5NAyVLFqV7djB99RtHAJe38s9nzvmTRgl8YP+Zn7ic+wrSCMV9921WtAxYddU9t9NvB0YrZ84axdHEAPywOwKxyOWZ7D8POPn0U6+NP6pGY8BCfn7YTE5OApVVFflg2ggoVjXOt8+uIiUnAe85m4mLvY1xWn3YdXBgytJ1aTHRUnNropIOjJV5zh/DjkkB+XBKIWeWyzJo3BFu79PO723xSl8SER/j8tJPYmEQsrSqw5OdvqfDKbW4Kw/s6hVpQFMrcTqwSH4z169czYMAAEhMTKV489zvCAyh5O7fj+K8pyPvNH99lqcrnhV2FN2bp9HthV6FARJz6JPegd9zRu1dyD3oPOBoVbkejoKQq8/+l4V2jp539lfcFxXnT37kH5dHJHm+/vgVNRuw+YGvWrKFatWpUrFiRsLAwxo4dS/fu3fPcqRNCCCHeNYr39eS4AiIduw9YdHQ0kyZNIjo6GlNTU7p164anp2dhV0sIIYQQr0k6dh+wMWPGMGbMmMKuhhBCCFFgPvRz7KRjJ4QQQgiN8aF37OR2J0IIIYQQGkJG7IQQQgihMT70ETvp2AkhhBBCY3zgF8XKVKwQQgghhKaQETshhBBCaAyZihVCCCGE0BCKD3wu8gNPXwghhBBCc8iInRBCCCE0hkzFCiGEEEJoCMUH3rOTjp0QQgghNMYH3q+Tc+yEEEIIITSFjNgJIYQQQmN86CN20rETQgghhMb40Dt2MhUrhBBCCKEhZMROvBEFWoVdBfEKheL9fz0unGxW2FUoEGOPRxV2Fd7YrI/MC7sKBUJJSmFXoUAolcrCrsJ74UP/rVjp2AkhhBBCY3zoHTuZihVCCCGE0BAyYieEEEIIjVFE8WFPWUvHTgghhBAaQ6ZihRBCCCGERpAROyGEEEJojA99xEo6dkIIIYTQGHKOnRBCCCGEhpBz7IQQQgghhEaQETshhBBCaIwPfcRKOnZCCCGE0BgyFSuEEEIIITSCjNgJIYQQQmMo5KpYIYQQQgjNIFOxQgghhBBCI0jHTgM0bdoUDw+Pwq6GEEIIUeiKFODyPpKpWA2wdetWdHR0CrsauVq27Bf27g3mypXbFCtWFEdHG0aN6k+1apVy3O748TPMmrWCS5duUK5cGb74ogs9e36iFrNnTxCLFq3nxo0oKlc2ZfjwPrRq1eCt5bJ+/S5WrNhKTEw8VlaVmTBhMM7Otd6bHDZu2M3Gjb9x+/ZdACytKvO/YT1o3MQphxzCmTVrBZdVObjRI1MOwSx+JQeP4Z8XWA6+PoHs33ecq1ciKVasKA6O1Rk+shdVq1ZQi4uIuM0C7w2cPHGO1FQllpaV8F7ggWkF42zL3rf3GEsWb+HmjTuYVS7PN99+RstWddViNm3Yy6qVO4mJScDSshJjx/fFyblGjnW+uON3ok6G8iAqGi0dHcpYWVCzRydKmZqoxT24HcW5zduI/fcSSqWS0hVNcf5qMHrGZQB4dCeG8I0B3LsYQeqz55Szq4lt388opl86x/1f3X+Iy7v28TQxkVIVTbH9vBtG1laq55VKJRe27eLan4d59ugxhhbm2PXrQelKFXIoNc2JE2dZuWI7Z89GEBMTz5KlY2nZsp7q+aVLNrF7dxDR0bHo6GhTs5YFHh69sLevnmO5e/ccYfHijdy4EU3lyiZ869GLVq3qq8Vs2PAbK1dsJyYmHktLM8ZPGIizc81c65zRyRPnWLliB2fPXiEmJp7FS0fTsmX6617TpluW240c/TmDBnXMIYejLF68SXU8eXj0pGWremoxGzfseZFD2vE0bsIAnHM5nrLj67ONffuOc/XFe6uDY3VGjPxcrW0olUp+/OEXftlygPv3H2JnZ8V33w/C0sosx7L37j3KksWbVbl8+23PTG1j44Y9rFq5Iz2X8f1zbRtvU2H88sRPP/3ETz/9xLVr1wCoVasWkyZN4pNP0t4jlUolU6dOxcfHh/j4eOrVq8cPP/xArVrpnxtJSUmMGjWKjRs38uTJE1q0aMGPP/5IpUo5f0Zm9L52SN95ycnJ/9m+ypQpQ6lSpf6z/b2u48fD6d37U7ZsmcuqVdNJSUlh0KBJPH78NNttbt6MZsiQqTg51SIwcBFDh3bD09OHPXuCVDEhIf8yfPgcOnZsxvbti+nYsRkeHrMJC7vwVvLYvftvvLyW8+WX3QkMXISTUy0GD55CZOTd9yaH8ibGjBzVD/+A+fgHzKd+fTv+9z9PLl26kWX8rZvRuA+ZirNTTbYFLsR9aDc8PX3ZsydYLYcRw+fQoWNTtm9fTIeOTRnuMafAcjh54jw9e7Vmw6bp+KyYyPPnKQwZNFPt+LlxI5q+vSdTtWoFVvlNIiBwNu5fulFUN/svPqEhFxk1YhHtOzQiIHA27Ts0YtSIRZwOu6SK+W13MLNm+THYvTO/bJ1FHScbhrrPIioyNsc6x/17iaotm9B48hhcxn6LMjWFI7OX8Pxpkirm0Z0Y/p7hTUlTE1wnjKCZ50Sqd2qLlk7a9+7nT5MInrMYhUKB63gPGk0aRerzFI7N/xFlamq2+7599CRn1v1C9Y4f03T6BIysLTky9wcex95TxVzetZeI3w5g1/czmkwdSzH90gTPXsyzJ9m3yZeePEnC2sac774fnOXz5uYV+O77L9i+YwHr1ntSsWJZvhg0jXv3ErMtMyTkAiNGeNOhQxMCt8+nQ4cmjBjuTVjYRVXM7t2HmeW1CvehXdi6zRsn5xq4D5lBZGRMrnXO6PGTJKxtqvDd94OyfP7Q3z5qywzPYSgUClq3rp9lPEBoyAVGjlhAhw5N2LZ93oscFhCmdjwF4fUih4Btc17k4PlaOQCcOHGOnr3asHGTJ74rviPleSqDB81Qaxsrlm/Hb/UuJn43kM1bvDA2NuCLQTN49OhJDrlcZNSIhXTo0JitgXPp0KExI0csyKJtrGaIuxv+W2dTx6kG7u4zicylbbxNRRQFt+RVpUqVmDVrFidPnuTkyZM0b96cjh07cvbsWQDmzJnD/PnzWbp0KSdOnMDExIRWrVrx4MEDVRkeHh5s27aNTZs2cfjwYR4+fEi7du1ISUnJX/75ihbZatq0KV999RUjRozA2NgYKysrFAoFoaGhqpiEhAQUCgUHDx4E4ODBgygUCg4cOICzszN6enq4uLhw4UL6B+GUKVNwcHBg7dq1mJubo6+vT48ePdQOhoxTsebm5sycOZOBAwdSqlQpKleujI+Pj1p9g4ODcXBwoFixYjg7OxMYGJipvgVtxYqpuLm1xMqqCjY2VfHy8iAyMoazZy9nu82mTb9jalqWiRMHY2FhRrdubXBza8nKldtUMX5+23FxccDdvRsWFma4u3ejfn17/Px2vJU8Vq0KpEuXVnTr1gYLCzMmThyMiYkxGzf+9t7k0Lx5XZo0caZq1YpUrVqR4cP7oKdXjLDQf3PMYYIqh9aZcljjt0OVQzWLSi9ysCuwHJb5jqdT56ZYWplhY1OFGTO/JCoqlnNnr6piFi/cTKPGDowc3ZsaNatiZlaeJk3rYGSkn225a9fspoGLLYOHdKJatYoMHtKJevVrs3ZN+uu5xm8Xbm7N6NqtORYWFRk3oR8mJkZs2rQvxzo3GPM1lRs3oHSlCuhXqYTj4L48ibtHwrX0DvT5X7ZT3r4WtXq6YWBuRolyZTFxsEX3xWjcvUsRPI6Jw3FIX0qbVaS0WUUch/Qh4cp1Ys5l32m+/NsBqjRxoUrThi9G67pT3MiQawf+AtJGECJ+/4PqHT+mwkeOaeW69yMlOZnbR07kmBdA48Z18PDolW0np137xri42GNmZoKVVWXGjRvAw4ePuXDherZlrlmzExcXe4a4d6FatUoMce9C/fq2rPH7VRXjt3onbl1a0K1bKywsKjFhwqC012LjnlzrnDkHR7716Emr1vWyfL5sWUO15Y8/TlC3Xi3MzMrnkMMuGrjYMcS9M9WqVWSIe2fq16/NWr9dqpjVq3+lS5fmdO3WAguLSoyfMABTE2M2bdyb7xwAfHwn0rnzy7ZhzoyZw160jStA2mu9ds1uhrh3plXrelhVr8zMWf/j6dMkdv16ONty177IZfCQzi/aRmfq1a/NmjXpufj5/UoXt1dz6Y+piTGbN71eLu+r9u3b07ZtW6pXr0716tXx9PSkZMmSHD16FKVSycKFC5k4cSJubm7Url0bPz8/Hj9+zIYNGwBITExkxYoVeHt707JlSxwdHVm3bh1nzpxh//79+aqLdOwKkJ+fH9ra2gQFBbFnT97fZCZOnIi3tzcnT55EW1ubgQMHqj0fERFBYGAgv/76K7/++iuHDh1i1qxZOZbp7e2Ns7MzISEhDBs2jC+//JJ//0370H7w4AHt27fH1taWU6dOMX36dMaOHZv/hN/QgwePANDXz360MTT0X1xdHdXWNWpUh/Dwyzx79lwV07BhxhhHQkLOF3CNITn5GWfPXs60P1fX7Pf3ruWQUUpKCrt2/cXjx09xcLTJMiarHBo2cuRshhxcG2aMqUNoSNadxTf18MFjAPT1SwKQmprKX4dCMDc3ZcgXM2nsOoSen03kwP6cOylhYZdwcbFTW+fqakdoSNoo0bPk55w7exUXV/UYF1c7wkIukh/PnqSNjhQtoQeAMjWV6LBwSpqUJ3jOYn4bNppDk2cTdTJUtU3qs+coFAqKaKefOaOlowMKBfcuRmS5n9Tnz0m8doOyturTk+Vq1+DepbQP+8cxsSQl3qds7fQYLR0djG2suHcp63JfV3LyM7Zs3kupUnrY2JhnGxcWehEXVwe1da4NHQl58YUjrf1F4Opqrx7j6kDIWzrOXoqNTeCvQ6fo0qV5jnGhoRcz16+hAyGhaZ3w5ORnnDt7JVOMi6sdoSEFM7r9IEPbuHXrLrGxCWr7LFpUB+ePahKSwz5Dwy5m0TbsVW0jOfk5585eweUt5vI6Cvscu5SUFDZt2sSjR49o0KABV69eJTo6mtatW6tidHV1adKkCcHBabMe//zzD8+ePVOLqVChArVr11bF5JV07AqQpaUlc+bMwdrammLFiuV5O09PT5o0aULNmjUZN24cwcHBPH2aPoSemprK6tWrqV27No0aNaJPnz4cOHAgxzLbtm3LsGHDsLS0ZOzYsRgbG6tGCtevX49CocDX15eaNWvyySefMHr06NfK+XUplUq8vFbg5FST6tWrZBsXGxuPsbGB2jojIwOeP08hPv7+i5gEjIwyx8TExBd0tYmPv09KSmqm/RkbGxATk5DlNu9aDi9duHCNOo7dsbPtwpTJP7H0hwlYWlbOMjYmNgEjY/VRr8LMQalUMmf2Wuo4WWNVPe0coXtx93n8+Ckrlu+gYUN7fJZPoEXLunh8M58Tx89lW1ZsVrkZ6xMbmwBAfMKL1zxT/ukxea3z2fX+lKluQWmzigAk3X9AytMkLu3cQ3nbWriM/QZTZweOL/Yh9nzah6ehZVW0dItybvM2nicl8/xpEmc3bgWlkqcJWU9rJj14iDI1lWKl1b806eqX4mli2jZJCfdV69RiSpfmaeL9POeVkz//PIlTnV442PfAz+9XVqycjKFh9ucFxsYmYJxhdNXYSJ/YF20rIf4BKSmpGGc6zvL3WryO7YGH0CtRLNvRvZfS2kEWx0qGHLJqKwWRQ1rb8KOOkw1W1Sur6gRkcwxnPzWe1jYy1NM4vZ4JBdQ2ClpBTsUmJSVx//59tSUpKSnL/Z45c4aSJUuiq6vL0KFD2bZtGzVr1iQ6OhqA8uXVR3rLly+vei46OpqiRYtiaGiYbUye889XtMiRs7Pza21nZ5f+jcjU1BSAu3fTz9cyNzdXO4fO1NRU7fncylQoFJiYmKi2uXDhAnZ2dmqdz7p162YqI6OsD/DXO5dw2rSfuXjxGvPn596hVCjUT3RQKpWZ1meOybyuIGVVp5x29y7mULVqRbYFLmTT5rn06Pkx48Yu5PLlrM+xy6p+ZJkDmWLeRg6e01dx8cJ15sz7RrUuVZl2vlmz5k707f8pNjXM+WJwR5o0rcOWzTlPZeTlb6/gzV6f036bSLx5G+f/pZ/P9fI4MHGyw+KTFuhXMaN6+zaYONTm2h9/A6BbuhQffT2Y6JAz7BrswW73ETx78gR9czMURXJ5C89LXplftEy5vq569WqzdZs3GzbOpGEjR4Z7eBMXl5DjNpleC7I4hjLFvN22ArA14A/atWuErm7RXGMz55DV350MMQXTVmZMX8HFCzeYO+/bzPXKdAzn/L4FeWvTb9o23mVeXl7o6+urLV5eXlnGWltbExoaytGjR/nyyy/p168f586lf6nM+nMj579TXmIyko5dASpRooTq/4u8eMN9+cYN8OzZsyy3e/WK1pcvYOorJ0VnvOJVoVCoPZ9bmRm3yepAebWe2cn6AF+W63YZTZ++jD/+OI6fnycmJtlfqQhgbGyYacTn3r1EtLW1MDAo9SLGgNjYjDEJmUbJCoKhYWm0tIpk2l9cXGK2+3vXcnipaFEdqlSpgK2tFSNH9sPGpipr1uzMMrassYFqxOGluCxzyBxT0DnMnLGKP/88yUq/SZiYGKnWGxqURltbCwsL9SvIqlWrQFRU9idyG2eR2724RNWoi6HBy9c8Q8y9xBzP3XvV6TWbiQ45g+v44RQvk/6NXLdUSRRaRShVwVQtvmQFU57EpV/kUM62Jq28p/PxD3P45Me5OA0dwNP4RPTKGpEV3VIlURQpkmnkLfn+A3RLp42Y6Rqk/fs0QT0m6f6DTKN4r0tPrxhVqpji4GCNp+f/0NLWIsA/+9kGY2MDYjIeQ3H3VSNCBoalsmx/r75eb8PJk+e5ejWSrt1a5BqbVTu4F5eYRQ5ZxLxhDp4zVnLwz39Y5TdZrW28bIOZj+H7Oe4zq7YR90o9DQqgbbwNRRTKAlvGjx9PYmKi2jJ+/Pgs91u0aFEsLS1xdnbGy8sLe3t7Fi1ahIlJ2lXwGUfe7t69qxrFMzExITk5mfj4+Gxj8px/vqJFnpUtWxaAqKgo1bq3eWFCftjY2HD69Gm14eSTJ0/mul3WB7h7nverVCqZNu1n9u4Nxs/PEzMzk1y3cXCwITg4VG3d4cMh1K5tic6LqwYdHGwICsoc4+hY8JfbFy2qQ61algQFhaitDw4OzXZ/71oO2VEqlSQnZ/3lI6scgg6HUCtDDsFBmWOyO2/vdernOX0l+/cdZ+Wq76lUqZza8zpFtalVuxpXr0aqrb92LZoKOdzqxN7eiiPBZ9TWBQefxsGxuqrcmrWqZoo5EnwGe8ecb92hVCo57beJqJMhuI73oEQ59XoU0dbGoKo5D6PvqK1/GH2H4i9udfIq3VIl0SmhR8zZf0m6/wCTOnaZYl6Wq29emZhw9XM074afp4xVNQD0yhqjq19aLSb1+XNi/71EGSuLHPN6bTkcYwD2DtUJDg5TWxccFIqjQ9oxlNb+LDLHBIfhWEDHWVa2+h+gVq1qOZ4f+JKDQ3WCg0+rrQsKCsPRwRpIy6FmrWqZYtKOOevXqp9SqWTG9BXs33eMlasmZWoblSqVw9jYQG2fycnPOXniHI457NPBvnqObaNoUe0Cz6UgFORUrK6uLqVLl1ZbdHV181QPpVJJUlISVatWxcTEhH370i+2Sk5O5tChQ7i4uADg5OSEjo6OWkxUVBTh4eGqmDznn69okWfFixenfv36zJo1i3PnzvHXX3/x3XffFXa1AOjVqxepqakMGTKE8+fPs2fPHubNmwfkPHye9QGe+7TES1On/sSOHQfx9h5FiRLFiYmJJyYmnqev3PrB29uPMWPmqx736PExkZF38fJaTkTETfz99xEQsI+BAzurYvr27UBQUAg+Pv5ERNzEx8efI0fC6NevQ37+LHk2YEAn/P334e+/j4iIm8yc6UtUVAw9enzy3uQwf/4aTp48y61bd7hw4RoLFqzl+PFw2rdvosph7JgFWeSwgoiImwT47yMgYL9aDn36ticoKARfnwCuRNzC1yegQHOYMW0lv+48zOy5X1OiRHFiYxKIjUng6dP00wEGDGzP778fwX/LAW5cj2bD+t85dPAfevRMPyF5/NgfWDB/o+rx530/ITj4NCt8t3Plym1W+G7n6JFw+vRNv0df336fEhDwB1sD/iQi4jazvfyIiorls89a5ljn036buBl8HKcvB6JdTJenCYk8TUgk5ZXbIVl+2orbR//h2p+HeXjnLlf2HeROyBmqtmiiirn+VzD3Ll/h0Z0YbgYd48TS5Vh83FztfnhBXgu5su9germftOD6wSCuHwrmwe0ozqz7hSdx8Zi3aASktXWLj5tzcefvRJ4M5f7N25zy8UOraFEqNvgo19fj0aMnnD9/lfPn065KvnXrLufPXyUyMobHj5+yYP46QkMvcPv2Xc6ejeC7734gOjqONh+nf0iNHbuI+d7r0v/OfdoRHBSKr+9Wrly5ha/vVo4cOU3ffu1UMf36tyfA/wABAQeIiLiFl9fKtNeiR/prnFcZc7j9Sg4vPXz4mD17jtIlm9G6cWOXMN97vepxnz6fEhwUxnLfQK5cuc1y30COHjlDn36fqmL692+Hv/8BAgL+ICLiFrO8Vr92DgDTp63g151/M2fut+iVKE5MTAIxr7QNhUJBn75t8fXZxv59x7l08QYTJ/xAsWK6fNquoaqc8WOXsmD+BtXjz/u2JTg4cy59+6bn0q9fOwICDrA1Yy6ftXqtXN5XEyZM4O+//+batWucOXOGiRMncvDgQXr37o1CocDDw4OZM2eybds2wsPD6d+/P3p6evTq1QsAfX19Bg0axMiRIzlw4AAhISF8/vnn2Nra0rJlzu8zGckNit+ilStXMnDgQJydnbG2tmbOnDlqV7wUltKlS7Nz506+/PJLHBwcsLW1ZdKkSfTq1StfF33k18vbgfTpM0FtvZfXt7i5pR24MTH3iIpKf1M1MzPBx2cyXl7LWb9+F+XKlWHixCG0aeOqiqlTpwbz549h4cK1LF68HjMzExYsGIO9/dv5xti2bSPi4+/z44+buHv3HtWrV8HHZzIVK5Z7b3KIi01gzJgFxNy9R6lSJbC2Nsd3+WTVla8xMfFEvpJDJTMTlvlMZpbXcjaochhMmzbpH9J16tTAe/5oFi1cp8ph/oLRBZbD5he3FhnQb5ra+hkzh9Kpc1MAWraqy6TJX7DcZzteM1djXrUCCxaNoI5T+mhOVFQsRV65QZWjozVzvb9hyaItLFmyBTOz8sz1/hY7+/Qb+X7S1oXEhIf8/GMAMTEJWFmZ8dPP46hQsWyOdX55a5GgmQvU1jsO7kvlxmk3bq7g7ID9gF5c2vk7Z9ZuoaRpeT76ZghG1paq+IdRdzi/ZTvJDx+hV9aI6h0+xuJj9Y7Go7sxJD94qHpcsb4zyQ8fcSFwF0kJ9ylVyZT6o/6HnnH6FJ3lp61JSX7G6dUbefb4MYbVquIy5mt0iuf+PnA2PIJ+/SapHs+etQqATp2aMWWqO1eu3ibwm4PEx9/HwKAUtraWrFs/Ayur9At0oiJjKaJIH19wrGODt/cIFi3ayJLFmzAzK4/3/JFqNzVu27YhCQkP+PGHLaobhP+8bKKq/eXH2fAr9O835ZUc/F7k0ISZs74CYPeuIJRKJZ9+6ppVES9yeOV4qmPNPG8PFi/axOLFm6hsZoL3/OHYqx1PriQkPOSnH/xf5GDGsmUTqJjL8ZSdl7cWeTUXgBkzh9G5c1MABn3RkaSkZKZPW879+4+ws7PEd/lESpQonp5LVCyKTG3DgyWLNrFkyWYqm5kwz9sjU9tISHjATz8GqHL5+efxubaNt6kwRqzu3LlDnz59iIqKQl9fHzs7O37//XdatUrr4I4ZM4YnT54wbNgw1Q2K9+7dq3b+/IIFC9DW1qZ79+6qGxSvXr0aLS2tfNVFoczLyVVC461fv54BAwaQmJhI8eLFc99AJX+3exBvl5L3vzk/T31c2FUoEBNPvr0rmv8rsz7K37k97yol+bvB67tKEz6utYvY5x70hoYG/VlgZf3s2qzAyvqvyIjdB2rNmjVUq1aNihUrEhYWxtixY+nevXs+O3VCCCGEeJdIx+4DFR0dzaRJk4iOjsbU1JRu3brh6elZ2NUSQggh3kh+fgpME0nH7gM1ZswYxowZU9jVEEIIIQqUdOyEEEIIITTEh367jw89fyGEEEIIjSEjdkIIIYTQGEUU7//Vw29COnZCCCGE0Bgf+jl2MhUrhBBCCKEhZMROCCGEEBrjQx+xko6dEEIIITSGTMUKIYQQQgiNICN2QgghhNAYCrkqVgghhBBCM8hUrBBCCCGE0AgyYieEEEIIjfGhj1hJx04IIYQQGkN+eUIIIYQQQkPIOXZCCCGEEEIjyIideCNKPuwh73eNUplS2FV4Yy7+jwq7CgXiWDeTwq7CGwuNu1rYVSgQNgalC7sKBUK7SPHCrsJ74UMfsZOOnRBCCCE0hlZhV6CQyVSsEEIIIYSGkBE7IYQQQmgMuSpWCCGEEEJDfOjn2MlUrBBCCCGEhpAROyGEEEJojA99xE46dkIIIYTQGFofeMdOpmKFEEIIITSEjNgJIYQQQmPIVKwQQgghhIaQ250IIYQQQmiID33ETs6xE0IIIYTQEDJiJ4QQQgiN8aH/Vqx07IQQQgihMWQqVgghhBBCaIQPqmO3evVqDAwMVI+nTJmCg4NDodUnJwqFgsDAQACuXbuGQqEgNDQ0T/FCCCHEh6qIQllgy/uoUKdi+/fvj5+fH15eXowbN061PjAwkM6dO6NUvt0/6qhRo/j666/f6j7+K1FRURgaGhZ2NfJs2bJfWDB/LX37tmfCxMHZxh0/Hs6sWSu4fOkG5cqV4Ysv3OjR8xO1mD17glm8aD03bkRRubIpHsM/p1WrBm+l3kuWbOCHpZvU1hkbG3A4aM17kwPA8+cpLF26iV93/kVsbAJlyxrSqXMzvvyyG0WKZP997/jxcGbPWsXlyzcpV64Mg77oRI8eH6vF7N1zhMWLN3DjRjSVK5vwrUdvWrWqn+86drEwoYuFKaYldAG4kviYFeduEhwdD8CJ7g2z3G5R2FXWXbgNQOdq5WlTuRzWhiUoqaNNs21HePgsJdd9d7Uw4XPrShgXL8qVxMfMD71CaOx9tZjBtSrTuVp5Suloc/beQ+aciuDK/ce5ln3ixFlWrgjk7NkIYmLiWbJ0HC1b1lM9r1Qq+WHpZrZs2cv9+4+ws7Pi+0lDsLKqnGO5efm7b9jwGytXBBITE4+lpRnjJwzC2blmrnU+HxrBrxv+5Mq/t0iIu88IrwF81NhW9fxPMzby128n1LaxrFmZ6b4eqscJcfdZ/8NOzpy4yNPHSZhWLkunvi2p18w+57y2BvHrhj9JiLtPpaom9P2mEzYO1VTPK5VKAlbu4cD2ozx68BjLWlUYMKILZtVMcs0roxW+u1m6cCu9Pm/J6PE9AHj86CmLFwTw5x+hJCY8pEJFI3r0bkH3Hs1yLGv/3n/4cUkgt27GUMmsLF9925nmLeuoxWzZ+Cd+q/YQG5OAhWUFRo3rQR2n6vmu9+aN+9m8aT+Rt2MAsLCsxNBhnWnU2OFFXU7wy5YDnDt7lYSEh/yy1RObGua5lrtv73GWLv6FmzfuYla5HN98250WrT5Si9m0YR+rV+4iJiYBC8uKjB3fBydnm3znUJDklycKWbFixZg9ezbx8fEFVmZycnKe4kqWLImRkVGB7bcwmZiYoKurW9jVyJMzpy+xZfMerK3Nc4y7dTMa9yFTcXaqybbAhbgP7Yanpy979gSrYkJC/mXE8Dl06NiU7dsX06FjU4Z7zCEs7MJbq7+VVWX+PuynWnbsXPLe5bB8+VY2b9rDd98PZteuJYwa1ZeVKwJZt25X9rncusNQ9xk4Oddk6zZvhrh3YabnCvbuOaKey4h5dOjQlMDtC+jQoSkjhs8jLOxivut493EyS09fo9++UPrtC+Xk3UTmudagWmk9AD7ecUxtmXb8IqlKJX/eilWVUUxLiyPR8aw+fyvP+21lZswIh2qsOn+Tz/eGEBqbyKJGtSivl96++tpUpFf1Csw9dYX++8OIe5rM0ia10NPO/bTtJ0+eYm1jznffZ/2FZvnybaxevYPvvh/Mll/mYFzWkEEDp/Do4ZNsy8zL33337sPM8lqJ+9CubN3mjZNzTdyHTCcyMibXOic9SaayZQUGjHDLNsa+vg0/7ZiiWsZ6q+f3w7QNRN24y6jZA5m9ZjQfNbFj0aQ1XL2Y/WtzZH8IaxYF0qlvS7xWjcTariqzRvkQG53+ebFz/R/s3nSIASPc8FwxHIMypZjp8TNPHj3NNa9XnT1zla2//IVV9Upq6+fN3kzw4XA8Zw1i687p9O7TijkzN/LnHyHZlhUWGsG4Ucv4tEMDNm+dzKcdGjB25DLOnL6iitnz23HmztrEoCFt2eg/Ccc61fnKfRFRkXH5qjdAeZMyeIzowaZfZrDplxnUq1+Lb76az+VLaX/bJ0+e4uBYHY8RPfJcZmjIJUaPWEL7Dg3xD/SifYeGjBqxhNNhl1Uxv+8+wuxZaxns3pFftnri5GTDl+5ziIqMzaFk8bYVeseuZcuWmJiY4OXllW1MQEAAtWrVQldXF3Nzc7y9vdWeNzc3Z8aMGfTv3x99fX0GD057Q1m9ejWVK1dGT0+Pzp07Exen3mCymopduXKlal+mpqZ89dVXueYwcuRI2rdvr3q8cOFCFAoFu3alf0haW1uzbNkyAE6cOEGrVq0wNjZGX1+fJk2acOrUqVz381JqaiqDBw+mevXqXL9+Hch66nbr1q00a9YMPT097O3tOXLkiFo5vr6+mJmZqf4+8+fPV5uqfhsePXrCqNHeTJ/xFaX1S+YYu2nT75ialmXCxMFYWJjRrVtr3NxasnLlNlXMGr8duLg44O7ejWoWlXB370b9+nb4+e14azloaWlRtqyhailTRv+9yyE05ALNW9SlaVNnKlYqR5uPXXB1dSA8PCKHXPZgamrMhAmDXuTSCje35qxcGZiey5pfcXGxZ4h7F6pVq8QQ9y7Ur2/HGr+d+a7j31H3CI6O58bDp9x4+JSfwq/z+HkKtY1KARD39Jna0riiEf/cTeT2oyRVGRsvReL37y3OxD3I8357Va/I9qt32H71DtcePGF+6FXuPEmiq0X6CFBPq4qsOn+TP2/HEXH/MVOOX6SYlhZtKpfNtfzGjZ3w8OhN69aZR2SVSiVr1vyK+9CutG7dgOrVqzBr1jc8fZrEr7/+lW2Zefm7+63egVuXFnTr1goLCzMmTBiEiYkRmzb+nmudHRrU4LMhbanb1C7bGB0dbQyMSquWkqVLqD1/6ew12nRthGXNKpSvaIRb/1aUKFmcaxey79jt2nyIZu3q0bxDfSqal6efR2eMyhmwb1uQ6u/125a/6NSvJXWb2mFWzZQvv+tFclIyQfvy/p76+NFTJoxdzvdT+1JaX0/tudNhEbTr6IJzXRsqVDSmS/cmVLeuxLnw69mWt2HtPuo1qMmgwW2pWs2UQYPbUreeDevX/J+9uw6LMmsDOPwbGpRGCUEBAQMRsGPF7tbP3LXX7u4OLAzUtdu1sdcODLAFLOzAAKUxyfn+QAdHGtEBPLfXXJdz5sw7z5l3gGdOvSdldbZsPEGL1n/Q6n8uWBc1Y+TY9piY6rNrh2eG4/6qRs0yuFR3wtLKFEsrUwYNaYuWloYsCWvavBp9+7eiUpVSGT7mlk1HqFSlFH/3ao61tRl/92pOxUr2bNmU9HnZtPEIrVrVoHWbmlgXLcTocZ0wMTFkx/aTaRz551OSZN8tN1J4YqesrMysWbNYsmQJL18m/wG/fv06bdu2pX379ty6dYspU6YwceJENmzYIFdv3rx5lCpViuvXrzNx4kQuX75M9+7d6devH76+vtSsWZMZM2akGcvy5cvp378/vXr14tatWxw4cAAbG5t021CjRg3Onz9PQkICAGfPnsXIyIizZ88CEBQUxIMHD6hevToA7969o0uXLpw/f55Lly5ha2tLo0aNePcu/T8+MTExtG3blmvXrnHhwgWKFCmSat3x48czYsQIfH19sbOzo0OHDsTFxQHg5eVFnz59GDx4ML6+vtStW5eZM2em+/o/atq0FdSoXo4qVZzSrevre4+qVZ3lyv6o5syd24+IjY1LqvPH93XK4OtzL9ti/t7z56+p9kdXatf6m2FD5/HiRVCqdXNqG8qWLcGlizd5+jRxyPLevafcuOFPdZeyqT7H1/c+Vas6yZVV/cOZO3cey9ri53ufKsnqOOHj+2O9j0qSxJ40TRVlboVGJXvcQF2VP0z12f/0zQ+9joqShOL6+bn8JkKu/HJQBKUNdQAolE8dI001LgUl1YlNkHIjOJLSRto/9PovX74hJDhc7n1WU1OlfHl7fNL4PKT3vsfExHLnzuPk56+qU5rHzYy7Po/o3XgSQ9u7smr2DiLD5X+fFSttxcVTvryP+kBCQgLeJ32IjY2jpHPKv2PjYuN4ev8lpSvID02WrlCMB7efAfD2dRgRoe9wqFBM9riqmgolnIry4NazDMfuOuNfqrk4UKly8mFppzK2nD3jx9s34UilUq5evsfzZ2+oUtU+1ePd9H1C5Sryx6pc1R4/38REKzYmDv+7z6lcRf4YlarY4+eb+perjIiPT+DIfxf59DEaR6f0/36lxs/vEVWqyCfyVaqWxtcnsRc4NiaOu3eeUqWqw3d1HPD1eZjl180Ov3tilyO2O2nZsiVOTk5MnjyZtWvXyj22YMECateuzcSJEwGws7Pj7t27zJs3j65du8rq1apVixEjRsjuT5o0ifr168vm7tnZ2eHt7c3Ro6l/O50xYwbDhw9n8ODBsrLy5cunWv8rFxcX3r17h4+PD2XKlOH8+fOMGDGCPXv2AHDmzBmMjY0pXry4LNZvrVy5En19fc6ePUuTJk1SfZ3379/TuHFjPn36hKenJ7q6qfcUQeIcwsaNGwMwdepU7O3tefToEcWLF2fJkiU0bNhQ9p59fX8OHTqUbnuz6r//znH37hN273ZLvzIQHBLBH0bybTQ01CMuLp7w8CgKFjQgJCQCQ0O9ZHWCg7NvaP9bjqWLMXvOUCwtzQgNjWD58p10aD+Kg4eWoq+vkyvaAPB3z1a8e/eRxo0GoqysRHx8AkOG/EnjJtVSfU5IcDiG3yWgRim0xei7thgZ6hGSxbYU1dViXS1H1JSV+BQXz0gvf55GJR+SbGxZkA+x8XLDsFmhp6aKipKEsM/y0zlCo2Mw1NADwFBDDYCwz7FydcI+x2KS78emQ4QERwAkew8NDfXSHDJN732PCH9HfHxCiscNCYn4oZgBnCoVp2ItRwqY6PP2dRi7Vh9hxsDlzFo3DFW1xD8zg6d1ZvGkTfRsOBFlZSXUNNQYNqsbxuZGKR4zKuIDCfEJ6BrIJ8u6+tpEfumBjQyLkpXJ1THQlhuuTcvRw1e45x/Alh0TUnx89NgOTJu8kfq1RqKiooxEImHStC44l7VN9ZghIZEYGn7/c69L6Jd5muER74mPT8DAUOe7OjqEhkRmKO7vPXgQwF8dphATHYuWlgaLlgylqI15+k9MRUhIBIZG38VnpEPIl/jCIxI/U4bJfr/pZrkNQvZQeI/dV3PmzGHjxo3cvXtXrtzf35+qVavKlVWtWpWHDx8SH580CbpcuXLJnle5svxQx/f3v/X27Vtev35N7dq1Mx27rq4uTk5OeHp6cuvWLZSUlOjduzd+fn68e/cOT09PWW/d19fq06cPdnZ26Orqoqury/v37wkICEjzdTp06MD79+85fvx4ukkdQOnSSd+2TE1NZa8NcP/+fSpUqCBX//v734uOjiYqKkruFh2dsfmMgYHBzJq5mnnzhqGurpah50DiELOcLwtqvi3/vgpSafLnZROX6mWpX78KxYpZUqWKEytXTgJg377TqT4np7UBEudbHTx4lnnzh+Lh4Ybr7EGsW7ePfXtTb0dinPIxSUmpLcnrZLUtz9994s8TPnQ/5YfH40CmVLDDSkczWb1mVsYcDQgmJiF7Flx9fxRJCmXS70okKVXKqu8/Mhl4DzP0vmfhuBlRuY4zZaqUxMLalLJ/2DParReBL4Lx8U76fb5j1RE+vPvE+MV9mLl2KI3aV2fxxI0EPH6d9sEz0K5kbZdKk7U1JUGBYcybvY0Zs/9GXV01xTrb/j3FrZtPWLR0AP/unMCwkW1xnb6FSxfvplg/KSj5u4lxf1clhbizej6sLM3YvWcW/26fStv2tZkwdgWPH2V8bmlKkseXwu8zsvbe/0y/e49djknsXFxcqF+/PuPGjZMrT+mDntJq2Xz58qVbJy2amsn/WGRGjRo18PT05OzZs1SvXh19fX3s7e3x8vLC09OTGjVqyOp27dqV69evs2jRIry9vfH19cXQ0DDdRR+NGjXi5s2bXLp0KUMxqaom/aL6+h5+HS7O6Pv6LVdXV1ki+vXm6royQ7HcufOY0NBIWrcain3JFtiXbMHVK7fZvPkQ9iVbyCXpXxUw0pP1YHwVGhaJiooyenqJ39CNjJL3OISGRWJkpJehuH6UlpYGdnZFeP4s5T9OObUN8+dt5O+erWjcuBp2xYrQvHkNunRtxqpVe1J9jlEBfUJC5HtBQkOTtyU4hTqGWWxLXIKUl+8/4x/+nmW3nvMw8gPtbc3k6jgZ6WCpo8X+Jz82DAsQERNLXIJU1iv3lYG6mqyHLvRLb973dfTVVQnN4Bed1BgV0ANI9nkIC03eAyT3vHTedz19bZSVlTJ93KzSN9KhgIk+QS8TexnfvAzhuMcFeo9tT6lydhSxLcT/utfHurgFxz28UjyGjl4+lJSViPxu6D0q/D06Bonzc3UNEnuUIsKS1/m+Fy8l/nefExb6jj/bTqdc6V6UK92L61cfsO3fU5Qr3YtPH6NZsmgPw0e1o3pNJ+yKWdD+z1rUa1iezeuPpXpcI6PkvVZhoVGyHjp9vfwoKyslrxP2LlkvXkapqqlQuIgJ9qWsGTKsPXbFCrNlc+oxpsfISI+Q4ORtMJS1QftLGyLk64RF/ZTPVGYoS6TZdsuNckxiBzB79mwOHjyIt3fSisGSJUty4cIFuXre3t7Y2dmhrJz6CrSSJUsmS4DSSoi0tbWxtLTk1KlTWYr96zy706dPy5K46tWrs337drn5dQDnz59n0KBBNGrUSLZQIyQk/SGkvn37Mnv2bJo1ayabv5dVxYsX58qVK3Jl165dS/M5Y8eOJTIyUu42dmzvDL1epUqlOXBwCXv3LZbdSpWyoWnT6uzdtzjFc+nkVBxvb1+5Mq8LPtiXskFVVSWpjlfyOk7Ov2a5fUxMLI8fv6RAAYMUH8+pbfj0KTrZtibKSkqyxD8lTk7F8Pb2kyvz8vLF3r6orC2OKdTx9vLF2akY2UECqH0Xd3MrY+6GveNh5IcfPn5cgpR74e+paKwnV17BWI+bXxKMVx+iCfkUI1dHRUlCmQK63AzJ+CKNlJibG2NUQF/uPYyJieXq1Ts4p/F5SO99V1NTxd6+aPI63n5pHjer3kV+IPRtBHpfkoCvPftK33WBKCkppfqFUkVVBati5ty8Kr+i+tbVB9iVsgSgoJkBeoba3PqmTlxsHP6+j7FzsEw3zgqVSrBr31S2e0yW3UraW9KoSUW2e0wmPiGBuLh4JN/FraykREIaX4RLO1kn69G76H1XNudNVU2FEiWLcMlbvs4l77s4OhVNN+6MiomJTb9SKhwdbbjofUuuzNv7Jk7OiXMeVdVUKGlvxUXv23J1Lnrfwsk59WHqX0EpG2+5UY6K28HBgT///JMlS5K2jxg+fDinTp1i+vTpPHjwgI0bN7J06VK5+XQpGTRoEEePHmXu3Lk8ePCApUuXpjm/DhJXybq5ueHu7s7Dhw+5ceOGXCxp+TrP7uDBg7LErkaNGmzZsoUCBQpQsmTSRFobGxs2b96Mv78/ly9f5s8//8xwj+HAgQOZMWMGTZo0SZbwZsbAgQM5fPgwCxYs4OHDh6xcuZIjR46kOQygrq6Ojo6O3C2jw6r582thZ1dE7qappYGenjZ2dokLQNzcNjJ61ELZc9q3b8Dr129xdV3L48cv8Nh9Ag+Pk3Tv3lJWp1Pnpnh5+bB6lQdPHr9k9SoPLl70o0uXZll8Z9I2Z846rly5zcsXQfj53WfQoNm8f/+RFi1r5Zo2ANSsWZ6VK3bj6XmNVy/fcuLEJTZsOECdb/Y9W+C2mdGjF3/Tlvq8fh3MbNd1iW3xOMkej1N0795CVqdzpyZ4e/myevUenjx5yerVe7h48SaduzQls/o5FMHJSAdTLXWK6mrRt1QRyhTQ5UhA0lyzfCrK1LYwSnXRhKGGKnZ6+bDIrwGAjW4+7PTyoaOWNL34n+qlaGNjKru/9cErmlsZ09TKGEttTYY6WWGipY7H46RFMtsevqJbCQtqFDKkqI4Wk8vb8jk+nmMB6W8d8uHDJ/z9n+Lv/xRIXDDh7/+U16+DkUgkdO7chFUrd3PixCUePHjOuLFL0NBQp0kTF9kxRo9ezAK3zbL7GXnfu3Rthsfuk3h4nOTx4xe4uq4jMDCEdu3rpxvz54/RPHvwimcPEhfbBL8O49mDV4QEhfP5YzRblh7gwe1nBAeGcffGI+aNWou2bj7ZXndmRYwxMTdizdxdPLr7nDcvQzi0zZNbVx9QrlrSSs0Zg5ZzbPd52f3G7apz5uBlzhy6zKtnb9i0eB8hb8Kp07IKkDgS0bCtC/s3neTq2Zu8eBLI8pnbUFNXo2pd+T3jUpIvnwY2toXkbppaaujq5sfGthD582tStrwdi+bv4tqVe7x6GcyBvV4cOnCRmrWT5ptOGLsW94Uesvsd/qrDJe+7rF9zhKdPAlm/5ghXLvnzZ+c6sjp/danLXo/z7NtzgSePXzN/9naCAsP4X7sa6cb9vcULd3D92j1evQrmwYMA3Bft5OqVuzRukjiNKTLiPff8n/H4UeL5e/Y0kHv+z+RGE8aNXs6iBUl7dP7VuQEXvW+xdvVBnjx5zdrVB7l88Q5/dU7at7Jzl4Z4eJxhr4cnTx6/Yo7rZgIDQ2nbLvNTmoTskyMWT3xr+vTp7Ny5U3a/TJky7Ny5k0mTJjF9+nRMTU2ZNm2a3MKJlFSqVIk1a9YwefJkpkyZQp06dZgwYQLTp09P9TldunTh8+fPLFy4kBEjRmBkZMT//ve/DMWtq6uLs7MzAQEBsiSuWrVqJCQkyPXWQeKWKr169cLZ2ZnChQsza9asdBPVbw0ZMoSEhAQaNWrE0aNHqVKlSoaf+1XVqlVZsWIFU6dOZcKECdSvX5+hQ4eydOnSTB8ruwQHh/M6MOkPo7mFCStXTWa26xq2/vsfBQsaMH58T+rXT2pvmTIlcFswksWLtuDu/i8WFiYsWDgSR8fs6SH63pugUIYPm09ERBT6+jo4OhVjx855FCpUMNe0AWDChJ4sdt/KtGmrCAuNpGBBfdq2q0e/fm1ldYKDwwn8ZsK+ubkxK1ZOYPbs9WzdeoSCBQ0YN74H9eonzV11LlMcN7fhLF68lSXu27CwMMZtwXAcHTO/6aqBuipTK9phpKHG+9g4HkV+ZND5O1z5ZsVqvcJGSCDVhKpVUVN62Sdt7Lu6VuK806lXHnDoWeJ800L5NdD7Zn7ViRch6Kqp8HdJC4w01Hgc+ZEh5+8Q9DFpG5VN916hrqzM6DJF0VZT4U7oOwaevcPHuPQ3P75z+zFdukyU3Z8zez0ALVrUxHX2IP7+uyXRn2OYNm0VUZHvKV3aljVrJ5Mvf9KXv8DXwSh98yUsI+97o0Z/EBHxjn+W7SQ4OBxb28KsWDlB9tlNy5N7L5g+8B/Z/c1L9gPg0rA8PUa25sXjQM4fucaH95/QN9ShZBkbBk/rhGa+xIRaRUWZUfN7sn35IeaNWkv0pxiMzQ3pO6EDzt+sHn3zKoR33/S8Vq7jzLuoj+xZf5yI0CgsrE0ZPb8nBUySesib/lmLmOhY1rl58OHdJ4qWLMy4Rb1lr/2jZs/rzZJFHowbvYaoyA+YmhnSf1BL2nyTgAUFhsqdDydnG1zn9eKfJfv4Z8k+LAoXYPb8XjiUTtpYuX7DCkRGfGDV8oOEBEdiY2vGkhWDMTPL/N6qoSGRjBu9nODgCLS1tbC1s2D5qtGyFatnzlxn4rhVsvojhyf+nu/bvxX9BrQGIDAwVK5n0snZjrluA1iyeBdLl+zCwsKYeW4DKe2YtNK2QaPKRES8Z8U/ewkOjsDG1px/VozErFD62/78TIqYG+fq6sqePXu4d+8empqaVKlShTlz5lCsWNLvcalUytSpU1m1ahXh4eFUrFiRZcuWYW+ftDo6OjqaESNGsG3bNj59+kTt2rX5559/MDfP+EIYifRnX95ByDV69uzJvXv3OH/+fPqVv5Dy8zbRFTJPKk0/scjpKu4KU3QI2eJym5SH53MT39Cnig4hWxTXy9q8tZxGRenH5oLnBGpK5dKv9IN2P01/b8aM+p9Vg/QrAQ0aNKB9+/aUL1+euLg4xo8fz61bt7h7965sDcCcOXOYOXMmGzZswM7OjhkzZnDu3Dnu37+PtnbinNC+ffty8OBBNmzYgKGhIcOHDycsLIzr16+nOf3sWzmux074debPn0/dunXJly8fR44cYePGjfzzzz/pP1EQBEEQBJnvp3qtX7+eggULcv36dVxcXJBKpSxatIjx48fTqlXiFVw2btyIsbExW7dupXfv3kRGRrJ27Vo2b95MnTqJw/ZbtmzBwsKCkydPUr9++tMmIIfNscup/v33X/Lnz5/i7dsu1NzmypUr1K1bFwcHB1asWIG7uzt///23osMSBEEQhCzLzlWxKW/zFZ1uDJGRiSuKDQwSe+6fPn1KUFAQ9erVk9VRV1enevXqsgWj169fJzY2Vq6OmZkZpUqVkltUmh7RY5cBzZo1o2LFiik+9u2WIrnNt3MZBUEQBCEvyM45dq6urkydOlWu7Ovc/dRIpVKGDRvGH3/8QalSiYuDgoISF18ZGxvL1TU2NpZdGjQoKAg1NTX09fWT1fn6/IwQiV0GaGtry8a/BUEQBEH4PYwdO5Zhw4bJlamrp32FmQEDBnDz5s0Ud67IyqbUmd24WgzFCoIgCIKQZ2TnlSdS3uYr9cRu4MCBHDhwgDNnzsitZDUxMQFI1vP29u1bWS+eiYkJMTExhIeHp1onQ+3PcE1BEARBEIQcThGXFJNKpQwYMIA9e/Zw+vRprKys5B63srLCxMSEEydOyMpiYmI4e/asbMuysmXLoqqqKlcnMDCQ27dvZ2pbMzEUKwiCIAiC8AP69+/P1q1b2b9/P9ra2rKeOV1dXTQ1NZFIJAwZMoRZs2Zha2uLra0ts2bNQktLi44dO8rq9ujRg+HDh2NoaIiBgQEjRozAwcFBtko2I0RiJwiCIAhCnqGsgA2Kly9fDiB3XXhI3Pbk6wUVRo0axadPn+jXr59sg+Ljx4/LzeFfuHAhKioqtG3bVrZB8YYNGzK8hx2IDYqFHyQ2KM5ZxAbFOYfYoDjnEBsU5xy/YoPi468OZ9ux6hVqlG3H+lVEj50gCIIgCHnG77544HdvvyAIgiAIQp4heuwEQRAEQcgzsnOD4txIJHaCIAiCIOQZilg8kZOIoVhBEARBEIQ8QvTYCYIgCIKQZyhJfu/NPkRiJwiCIAhCnvG7z7ETQ7GCIAiCIAh5hOixEwRBEAQhz/jde+xEYif8EAm/+U9QDpNAgqJD+GGHm+WNK09IJIaKDuGH2enm/isdABx+8UHRIWSLBua5/8oyar9gnPB3H4r83dsvCIIgCIKQZ4geO0EQBEEQ8gzJbz6QJBI7QRAEQRDyjN88rxOJnSAIgiAIecfv3mMn5tgJgiAIgiDkEaLHThAEQRCEPON377ESiZ0gCIIgCHmG5De/pNjvntgKgiAIgiDkGaLHThAEQRCEPOM3XzshEjtBEARBEPIOsSpWEARBEARByBNEj50gCIIgCHnGb95hJxI7QRAEQRDyDqXfPLMTQ7GCIAiCIAh5hOixEwRBEAQhz/jNO+xEjx3As2fPkEgk+Pr6AuDp6YlEIiEiIkKhcf2oKVOm4OTkpOgwBEEQBOGXkUiy75YbiR67FFSpUoXAwEB0dXUVHQoAXbt2JSIign379mXqeSNGjGDgwIE/J6gsWLlyF8ePe/PkySs0NNRwdi7OiBFdsbY2T/N5V67cYvbstTx8GEDBggb8/XdrOnRoKFfn2DEvFi/+l4CAQAoXNmXo0E7UrVv5p7Tj6tXbrF27h9u3HxMcHMayZeOoUyft11J0G65dvcO6tfu5c+cJwcHhuC8dRZ06FWWPjxuzhH37POWeU9rRlu07Zqd53OPHLuLuvp0XAUFYFDZhyJCO1KlbUa7Otq1HWbd2P8HB4djYWDBmXDfKlSuZpXZ8/PCZ1cuOce70bcLD3mNXvBCDRzWnRCkLANYuP86po768DYpARVWFYiUL0WtAQ+xLF07zuJ4nb7Jm2TFevQilkIUhPQc0oHptB7k6e3Z4s22DJ6Eh77AsaszgUc1wLGOdpXZ8782bUObP28S58zeI/hyNpaUZM2YOoFQpm1Sfc+XKbWbPXsejhy++fKZa0r5DA7k6x4554754KwEBQRQubMKQoX9Rt26lH4535bJDrFr+n1yZoaEOx8/OASA0JAr3hXu55O3Pu3cfKVPWllHj2lG4SME0j3vqxA2WLznIyxchmFsY0W9Qc2rVcZKrs3P7WTavP0FIcCTWNqaMGN0G57K26cZ8dvsJ7nj5EfzyLapqqhQuaUX97k0pYGEsqyOVSjm95ShXj3jz6f0nLIoVoWn//2FsaSqrs2/xDh773icqNAo1TTUKl7CiQY9mcsdJyaWD57mw+zTvwqIoWMSExn1aYVmqaKZeOzUrlx1k1fJDcmWJ52MeAB8/fmbJwr14nvYlMuIDpmaGtP+zFm3aV0/zuInn4wAvXwRjblHgy/lwlquzc7snm9cf/3I+zBgxum2GzsfPlEvzsWwjeuxSoKamhomJCZLcmq5/kT9/fgwNDVN9PCYm5hdGk/iH6M8/G7Nz5zzWr59OfHw8PXpM4uPHz6k+58WLIHr1mkrZsvbs27eYPn3aMHPmKo4d85LV8fG5x9Chc2nevCb797vTvHlNhgyZg5/f/Z/Sjo8fP1OsmBWTJvXOUP2c0IaPn6IpVtySCRP/TrXOH9WcOXt+jey2YuX4NI/p63Of4cMW0KxZdfbud6NZs+oMG+qGn98DWZ0jh71wdV1P7z6t8dg7n7LlStC710xevw7OUjtmT9nN1YsPmTizA5t2D6d8ZTuG9F5F8JtIACyKFGDo2BZs9BjOPxv6YWpmwLC+qwkPe5/qMW/7PWPyqH+p36QsG3YNo36TskwatYU7NwNkdU4d9cV97gE696zNuh1DcCxjxYh+awkKDM9SO74VGfmeDh3GoKKqzOrVEzn03xJGj+mGjk6+VJ/z8sUbeveaTrmyJdm7bwG9+/yPmTPXcOyYt6yOj889hg2dT7PmNdi/fxHNmtdg6JB5cufnRxS1MeWY52zZbcfeCUBigjJ88ApevQxhgXsftu4ah6mZAX3/Xsynj9GpHu+m7xPGjlhLo6YV2eYxnkZNKzJmxGpu3Xwqq3P8yDXcZu+ie88GbN01DucyNgzss4zAwLB043166xGVmlajz8KhdHPtR0J8PBvGLyfmc1JM53edwmvvGZr2+x/93IeR30Cb9eP+Ifqb31Fmtha0GtaRIavG0nVGX5DC+nH/kBCfkHrbzt7g8Mq9VG9fj/7LRmJZqigbJ6wg4m1S3Bl57bQUtTHjmOdc2W3H3kmyx9zm7ML7wh2mu3Zn94Ep/Nm5NvNct+N52jf1mH0fM3bE6i/nY+KX87Hqu/NxFbfZO+nesxFbd034cj6WZOh8CD/PT0nsjh49yh9//IGenh6GhoY0adKEx48fA4nJxIABAzA1NUVDQwNLS0tcXV1lz42IiKBXr14YGxujoaFBqVKlOHQo6ZuIt7c3Li4uaGpqYmFhwaBBg/jw4YPscUtLS2bNmkX37t3R1tamcOHCrFq1Si6+K1eu4OzsjIaGBuXKlcPHx0fu8e+HYjds2ICenh7Hjh2jRIkS5M+fnwYNGhAYGCh7TlxcHIMGDZK1efTo0XTp0oUWLVpk6D3bvXs3Dg4OaGpqYmhoSJ06dfjw4QNTpkxh48aN7N+/H4lEgkQiwdPTE4DRo0djZ2eHlpYW1tbWTJw4kdjYWNkxvx+K7dq1Ky1atMDV1RUzMzPs7OwA+Oeff7C1tUVDQwNjY2P+97//ZSjmzFq7diqtWtXB1rYIxYtb4eo6hNevg7lz51Gqz9m+/SimpgUYP74nRYta0KZNfVq1qsO6dXtldTZu3E+VKk707t2GokUt6N27DZUqObJx44Gf0o7q1csxdGgn6tWrkqH6OaENLi5lGDykI3Xrpd5bo6amQoEC+rKbnp52msfctOkQlas40qt3K6ytzenVuxWVKjmweWPSz+uGDQdp3boW/2tTh6JFzRk7rjumJoZs33Ys022I/hzL2VO36De0MU5lrTEvbESPvvUwLaTP3l0XAajXyJnylewoZG6ItY0JA0c05cP7zzx+GJjqcXduuUC5SrZ06lGLIlYF6dSjFmUr2LDz3/OyOts3n6NJy/I0bVURS2tjBo9qTkETPfbtvJjpdnxvzeo9mJoY4eo6iNKl7TA3N6ZyZUcKF069p+brZ2rc+L+/fKbq0qpVbdat2y+rs2njwS+fqf9hXdSc3r3/R6VKpdm48eAPxwygrKyMkZGu7KZvkPh5CXj+llt+Txk7sQP2DpZYWpkwZkIHPn2M5ujhq6keb+vm01SsXJzuPRtgZW1C954NqFCxONs2n5bV2bLpFM1bVaHl//7AqqgpI8a0xdhEn93bz6Ubb9eZfSlTryLGlqaYWhei9bA/iXgbzquHL4DEhNRr71lqtK+H/R+OGFua8b/hfxEbHYvfmeuy41RoVAUrBxv0TQwpZGtB3S6NiAyOIPxN6smM1x5PytavRPmGlSlYOLG3TreAPpcPeWXqtdOirKyU4vkAuOX3hCbNK1OuQjHMChnRqo0LtsXMuXvnearH27r5FBUrl6B7z4ZfzkfDL+fjlKzOlk0nad6q6jfno92X83E2QzH/LJJsvOVGPyWx+/DhA8OGDePq1aucOnUKJSUlWrZsSUJCAu7u7hw4cICdO3dy//59tmzZgqWlJQAJCQk0bNgQb29vtmzZwt27d5k9ezbKysoA3Lp1i/r169OqVStu3rzJjh07uHDhAgMGDJB7fTc3N1nC1q9fP/r27cu9e/dksTVp0oRixYpx/fp1pkyZwogRI9Jt08ePH5k/fz6bN2/m3LlzBAQEyD1vzpw5/Pvvv6xfvx4vLy+ioqIyPHQaGBhIhw4d6N69O/7+/nh6etKqVSukUikjRoygbdu2skQyMDCQKlUSEwptbW02bNjA3bt3Wbx4MatXr2bhwoVpvtapU6fw9/fnxIkTHDp0iGvXrjFo0CCmTZvG/fv3OXr0KC4uLhmK+0e9e5eYkOvqpp5A+Preo2pV+a7/atXKcPv2I2Jj42R1/vjj+zrO+Pj4Z3PEWZNb2nD1yh3+qNKNhvUHMGnickJDI9Os7+v7gKpVHeXKqv7hhI9vYi9jTEwsd+88pmpVJ7k6Vao64uuT+Z7I+Ph44uMTUFOXn0Girq7KTZ+nyerHxsax3+MS+bU1sLEzS/W4t28+p0JlO7myilWKcdvvmew4D/xfUf67OuUr23HbL/U/jBl1+vQVSpWyYfCguVSp3IWWLYayc+fxNJ/j63s/2fv6RzVn7sh9pu5T9Y/kdXx97v1wzAABAW+pX3MMTetPYOyINbx8kdgLGxOT+PpqaqqyusrKSqioKuPr8zjV4930e0KlKvJD9JWrlsTP9wmQeB7u3Q1IVqdSlRLc9HuS6fg/f/wEgJa2FgDhQaG8D4/CpkxxWR0VNRUsHYoS4J/88wUQ8zma6ycuo29iiG4BvRTrxMXG8frhC2zKFJMrtylTTHbcrLz29xLPxyia1h/H2BGrZecDwMnZhnNn/Hj7JhypVMrVK/cJePaGylXtUz1eyufDHj/fxHOY+vkoyU2/1M/zr6Akyb5bbvRT5ti1bt1a7v7atWspWLAgd+/eJSAgAFtbW/744w8kEglFihSR1Tt58iRXrlzB399f1ptkbZ00h2XevHl07NiRIUOGAGBra4u7uzvVq1dn+fLlaGhoANCoUSP69esHJPZqLVy4EE9PT4oXL86///5LfHw869atQ0tLC3t7e16+fEnfvn3TbFNsbCwrVqygaNHEOREDBgxg2rRpsseXLFnC2LFjadmyJQBLly7l8OHDGXq/AgMDiYuLo1WrVrL3w8EhaX6PpqYm0dHRmJiYyD1vwoQJsv9bWloyfPhwduzYwahRo1J9rXz58rFmzRrU1NQA2LNnD/ny5aNJkyZoa2tTpEgRnJ2dU31+dpFKpbi6rqVs2ZLY2RVJtV5ISDhGRnpyZYaGesTFxRMeHkXBggaEhERgaJi8TnDwjw+TZYfc0IZqLmWo36AKZmYFePnyDe7u2+nWdTK7PebJ/YH+VmoxhwRHABAR/o74+AQMDXWT1wmJyHSMWvk0KOVYhA2rTmJpVRB9Q21OHvHh7q0XmBc2ktXzOnuXKaP/5fPnWAyNtFm4ohd6+qkPa4aFvEPfUP7Lhb6hNmEh7wCIDP9AfHwCBt/VMTDMT+iXOj/ixYs3bNt2lK7dmtG7z/+4efMhM2esQU1NlRYtaqb4nOCQCP4wSv6+Jv9MfV9HN1s+U6VKWzJtVhcKFzEmLDSKtSuP0P2v+ezcPxFLKxNMzQxYungf4yd1RFNLnS0bTxEaEkVIcOpfFkJDolJ4j7UJDYkCICL8/ZfPk3wdQ0NtQkPS/hLyPalUyuGV+yhib42xZWLS/y488Vzm15c/fn59bSLeyL9nlw6e59jaA8R8jqGAhTHdZvVDRTXlP6cfoz6QkJBAfn2dZMd9H/Yu06+dklKlrZg2q9s35+Mw3f+ay879k9HTy8/Ice2YPnkzDWuPQVlFCSWJEhOndsK5TOpzOBPPh3zMBoY6KZwP+TqG35wzQTF+SmL3+PFjJk6cyKVLlwgJCSEhIXHuQUBAAF27dqVu3boUK1aMBg0a0KRJE+rVqweAr68v5ubmsqTue9evX+fRo0f8+++/sjKpVEpCQgJPnz6lRIkSAJQuXVr2uEQiwcTEhLdv3wLg7++Po6MjWlpasjqVK6c/QV1LS0uW1AGYmprKjhkZGcmbN2+oUKGC7HFlZWXKli0ra3taHB0dqV27Ng4ODtSvX5969erxv//9D319/TSft3v3bhYtWsSjR494//49cXFx6OjopPkcBwcHWVIHULduXYoUKYK1tTUNGjSgQYMGtGzZUu79+So6OproaPk5MurqMairqyWrm55p01bw4MEztm6dk27d7+c6SqXSZOXJ6yQvU6Sc3oaGjarK/m9rV5hSpWyoXbsPZz2vpzl8+314UqTJYk7WLqRZXm02cWZ7XCfvokXdGSgrK2FXvBB1Gzrx4N4rWZ0y5W1Yv3MoEREfOOhxmUkjN7NqyyD0DfNnuB1IU2pHsirZsmpOKpViX6oow4Z1AqBkSWsePQpg27ajqSZ2ifGkEBBpf6bIps9U1WqlvrlXiNKO1jRvOIlD+y/xV5c6zFvYi2mTtlCz6giUlZWoUKk4Vaul3juUWrwpvccp1cnsiTi4bDdBT1/Ty21w+pVTiMGpVjlsyhTjXVgUF3afYfus9fRaMATVVL4EQfJhvcS4M//aKUn5fEzg0P6L/NWlLtu2nOb2zacsXNoPU1NDblx/yOwZWzEqoEvFyiVSjznZRyz5z26KH0MF/+rNOb/5FeOnDMU2bdqU0NBQVq9ezeXLl7l8+TKQOL+uTJkyPH36lOnTp/Pp0yfatm0rm9OlqamZ5nETEhLo3bs3vr6+spufnx8PHz6US7pUVeV/uCQSiSzB+voHNbNSOub3x0rtj3d6lJWVOXHiBEeOHKFkyZIsWbKEYsWK8fRp6l3wly5don379jRs2JBDhw7h4+PD+PHj010QkS+ffM+FtrY2N27cYNu2bZiamjJp0iQcHR1T3OrF1dUVXV1duZur68oMtfFb06ev5PTpK2zcOBMTE6M06xoZ6SfrYQgLi0RFRVk2B8zISI+QkO/rRCTrJVOU3NiGAgX1MTMz4vnz1OemJcYcIVcWFhqJ4ZeeJD19bZSVlVKu811PX0YVsjBi6bq+nLg4E49j41m9dRBxcQmYFjKQ1dHUUsO8sBGlShdh7NS2KKsoc2jflVSPaWCU1Dv3VXjYe1kiqKufD2VlpWS9c+Fh75P1MGVFgQL62BS1kCsram1OYBoLTAoYJfWMfhWa4mcqeZ2f8ZnS1FLHxtaMgOeJX3ZL2Bdhm8d4PC8u4NiZ2SxdOZCIiA+YFUp9MZehkU6ynp7wsHeyXiM9/fxfPk/ydcLC3iXrNUrLwX92c+/SbXrMHSA3fKr9pbfsfbj8eX4f8S5ZT5pGPk2MChXEysGGDhO6EfziLXe9bqb4elo6+VBSUuJduHzcH745bmZeOyMSz0chAp6/5fPnGJYt3sfQkW1wqeGIbTFz2nWsSd0G5di8IfUh/191Pn4GiUSabbfcKNsTu9DQUPz9/ZkwYQK1a9emRIkShIfL/8HS0dGhXbt2rF69mh07duDh4UFYWBilS5fm5cuXPHiQ8qqtMmXKcOfOHWxsbJLdvu2FSkvJkiXx8/Pj06dPsrJLly5lvcGArq4uxsbGXLmS9McjPj4+2aKMtEgkEqpWrcrUqVPx8fFBTU2NvXsTJ9erqakRHx8vV9/Ly4siRYowfvx4ypUrh62tLc+fZ22+j4qKCnXq1GHu3LncvHmTZ8+ecfr06WT1xo4dS2RkpNxt7NiMrQyFxER32rQVHD/uzcaNM7GwMEn3OU5OxfH29pUru3DBh1KlbFD9MvTh5FQcL6/kdZydU/8m+ivlxjZEhL8jKDCUAgVS7zV2crLD29tPrszLyw9np8S5RGpqqpS0L5qsjrf3TZyc5ecbZZamlhpGBXSIivrIlYv3+aNG6r1BUqlUNu8rJaVKF+HqpYdyZVcuPqCUoyUAqqoq2JUolKzOtUsPKOWY+jSCjHIuU5ynT1/JlT179hqzQgVSfY6TU7FknymvC77Yy32miuHtlbyOk3NxsltMTCxPnwZhVEB+6FdbWxN9A20Cnr/F/85zqtd0TOUIUNrRmssX5eeUXvK+i6NT4nQcVVUVipcsnKzO5Yv+lHZMf9sZqVTKgWW7ueN1k+5z+mNgIp9k6psYkl9fh0ffzP+Mi43j2a3HFC5hld7RiY9N+TOmoqqCma2F3HEBHvnclx33x147ucTzEYhRAV3i4uKJi4tH6bsJY8rKSiQkpJ64pH4+EjtR0j4fRREUJ9sTO319fQwNDVm1ahWPHj3i9OnTDBs2TPb4woUL2b59O/fu3ePBgwfs2rULExMT9PT0qF69Oi4uLrRu3ZoTJ07w9OlTjhw5wtGjR4HE+XIXL16kf//++Pr68vDhQw4cOJCpvdo6duyIkpISPXr04O7duxw+fJj58+f/cLsHDhyIq6sr+/fv5/79+wwePJjw8PAMDXtcvnyZWbNmce3aNQICAtizZw/BwcGyoWVLS0tu3rzJ/fv3CQkJITY2FhsbGwICAti+fTuPHz/G3d1dlghmxqFDh3B3d8fX15fnz5+zadMmEhISKFYs+R9edXV1dHR05G6ZGYadOnU5Bw544uY2gnz5NAkODic4OJzP32w34Oa2kVGjFsjut2/fgNev3+LquobHj1+we/cJPDxO0L17S1mdzp2b4eXlw6pVu3n8+AWrVu3m4kU/unRplun3IyM+fPiEv/8T/P0TJ2y/fPkGf/8nvH79Nse2ITHmp/h/mYj96uVb/P2f8vp1MB8+fGLunI34+tzn1cu3XLl8m359XdHX15bb627MaHcWuG2R3e/UqTHeXn6sWb2XJ09esmb1Xi5dvEmnLk1kdbp2bcru3afw8DjF48cvme26nsDAENq1r5eldlz2us8lr3u8fhnG1YsPGPT3CiyKFKBx8/J8+hjDSvcj3L75nKDX4dz3f8nsKbsIfhNJzbpJ0zOmj9/GisVJ81/b/PkHVy8+YMu6Mzx/+pYt685w7fJD2v5ZTVanfScXDu25wqG9V3j25A3u8w7wJjCCFm1+fJ/Brl2a4ef3gBUrdvH8eSAHD55l587j/NmxkayOm9tmRo9alBRP+wa8fh2Mq+s6Hj9+gcfuk3h4nKR79+ayOp06N8XLy5fVq/bw5PFLVq/a8+Uz1fSHY144z4PrVx/w6mUIt24+ZdTQ1Xx4/5mmzROH7U8cu861Kw94+SIYz9N+9Ou5mBq1HKlcNWmi/aSxG1iycJ/sfoe/anLJ258Na4/x9EkQG9Ye4/Kle3ToVEtW56/Otdnn4cX+Pd48fRyI25xdBAWG8792SecqNQeW7cLv9DXaje6MuqYG78KieBcWRWx04iiHRCKhasvqsv3u3jx7jYfbv6iqq+JYsywAYYEhnN1+glcPXxDxNoyAu0/ZPmsDKmqq2FVIatvaMUu5eCBppW7VVjW4fvQS145d4m1AEP+t3EPk23AqNK6a4ddO+3zs/u58rPxyPiqTP78mZcvZsdjNg2tX7vPqZQgH9nnz34FL1KydNJ960tj1LFmY9Dekw1+1ueR9lw1rj345H0e5fMmfDp1qf3M+6rDP4wL793h9OR87CQoM43/tfs0CvNT87qtis32OnZKSEtu3b2fQoEGUKlWKYsWK4e7uTo0aNYDEvdXmzJnDw4cPUVZWpnz58hw+fBglpcQc08PDgxEjRtChQwc+fPiAjY0Ns2cnbpJaunRpzp49y/jx46lWrRpSqZSiRYvSrl27DMeXP39+Dh48SJ8+fXB2dqZkyZLMmTMn2YKPzBo9ejRBQUF07twZZWVlevXqRf369WUretOio6PDuXPnWLRoEVFRURQpUgQ3NzcaNkzcwLZnz554enpSrlw53r9/z5kzZ2jevDlDhw5lwIABREdH07hxYyZOnMiUKVMyFbeenh579uxhypQpfP78GVtbW7Zt24a9ffrzYTJr27YjAHTqNE6u3NV1MK1a1QEgODiMwMCkISgLCxNWrZqMq+sa/v33PwoWNGD8+F7Ur580J6xMmRIsWDCKRYs24+7+LxYWJixcOApHxx/rFUrN7duP6Nw5qQ2urmsBaNmyFrNnD82Rbbhz+zFdu0yW3Z8zewMALVrUYNKUXjx88JwD+z2JeveRAgX0qFihFG4Lh5Evf9L0iMDXISh980XFuUxx5rsNw33xVtzdt1PYwhi3BcNwdEyaI9uwUVUiIt6xfNkugoPDsbUtzMqV4yhUKO2NalPz/v1nVrofJvhNJDq6WlSv7UCvgQ1QUVUmPiGB50/fcuTANSIjPqCjl48S9uYsW98Pa5uk3uE3QRFyvRcOTpZMmfMnq5ceZc2yYxSyMGTanL/kNjWu3cCJyMiPbFh1ktDgKKxsTJi3rAcmZmnPg80Ih9K2LFk6hgULNvPPsp2YmxszdlwPmjZL2jw2ODiM1998pswtjFm5aiKzXdex9d/DXz5Tf1O/ftIWPGXKFMdtwQgWL/oXd/etWFiYsGDhCLnzk1Vv34QzbtQ6IsLfo2+QH4fSVmzYOgpTs8ResJDgSBbO9SA0NAqjAro0blaRnn0ayR0jKDAMyTfnwdG5KLPm9eCfJQdYvuQg5hYFmD3vbxxKJ/VY1WtYjojID6xe8R8hwVEUtTXFfXl/2eum5cqXrUXWjFoiV956WEfK1Ev8AlOtTW1io2M5sHQ3n99/xLx4EbrN6ou6VuLCPBU1VZ7deYzXPk8+v/9Efj1tLB2K0nvBEPJ/sz1Q2OtQPkYmbcNVunoZPkZ94My/x3gXHolxEVM6T++NvnHSFIL0XjstiedjzZfzof3lfIyWvS+z5v/N0kV7mTBmHVGRHzAxM6DfoOZyCVjK5+Nv/lmyn+VLDnw5Hz2/Ox/lvzkfkRS1NcN9+YAMnY+fKQdNr1YIiTSrk86ENCUkJFCiRAnatm3L9OnTFR3OT5Q9m50K2SNe+ms3nf4ZwqIzv3VFTmSkodjd97PDh9jU51jmJkdf5v6fC4AG5ukneTldftUaP/01nrzLnr0aAay1f7yH+1cTlxTLJs+fP+f48eNUr16d6Oholi5dytOnT+nYsaOiQxMEQRCE38bvfkktkdhlEyUlJTZs2MCIESOQSqWUKlWKkydPUqJECQICAihZMvVrY969e5fChdO+lqUgCIIgCOn73YdiRWKXTSwsLPDy8krxMTMzM3x9fVN9rplZ6rviC4IgCIKQcb95XicSu19BRUUFG5vUd/gWBEEQBEHIDiKxEwRBEAQhzxBDsYIgCIIgCHnEb57X/faLRwRBEARBEH7YuXPnaNq0KWZmZkgkEvbt2yf3uFQqZcqUKZiZmaGpqUmNGjW4c+eOXJ3o6GgGDhyIkZER+fLlo1mzZrx8+TJTcYjEThAEQRCEPENJkn23zPjw4QOOjo4sXbo0xcfnzp3LggULWLp0KVevXsXExIS6devy7l3SNYKHDBnC3r172b59OxcuXOD9+/c0adIk2WVF0yKGYgVBEARByDMUNRTbsGFD2RWjvieVSlm0aBHjx4+nVatWAGzcuBFjY2O2bt1K7969iYyMZO3atWzevJk6dRKvxrRlyxYsLCw4efIk9evXz1AcosdOEARBEAQhBdHR0URFRcndoqOj03/id54+fUpQUBD16iVdJ1tdXZ3q1avj7e0NwPXr14mNjZWrY2ZmRqlSpWR1MkIkdoIgCIIg5BkSiTTbbq6urujq6srdXF1dMx1TUFAQAMbGxnLlxsbGsseCgoJQU1NDX18/1ToZIYZiBUEQBEHIM7JzKHbs2LEMGzZMrkxdXT3Lx5N8txeLVCpNVva9jNT5luixEwRBEARBSIG6ujo6Ojpyt6wkdiYmJgDJet7evn0r68UzMTEhJiaG8PDwVOtkhEjsBEEQBEHIMySS7LtlFysrK0xMTDhx4oSsLCYmhrNnz1KlShUAypYti6qqqlydwMBAbt++LauTEWIoVhAEQRCEPENRq2Lfv3/Po0ePZPefPn2Kr68vBgYGFC5cmCFDhjBr1ixsbW2xtbVl1qxZaGlp0bFjRwB0dXXp0aMHw4cPx9DQEAMDA0aMGIGDg4NslWxGiMROEARBEIQ8Q1FDkdeuXaNmzZqy+1/n5nXp0oUNGzYwatQoPn36RL9+/QgPD6dixYocP34cbW1t2XMWLlyIiooKbdu25dOnT9SuXZsNGzagrKyc4TgkUqlUmn3NEn4/DxQdgPCNeGmMokP4YWHRTxQdQrYw0rBVdAg/7ENsoKJDyBZHX+b+nwuABuYaig7hh+VXrfHTXyP084FsO5ahRrNsO9avInrsBEEQBEHIM7JzblxuJBI74YdIyRsdvlJpxi/XkpNJ8sDlr9WVtRQdQraITfio6BB+mIqSpqJDyBZNC+dXdAjZ4lpIsKJD+GFVM7648wfk/t+DP0KsihUEQRAEQcgjRI+dIAiCIAh5Rl4YufgRIrETBEEQBCHPkEh+78HI37v1giAIgiAIeYjosRMEQRAEIQ8RQ7GCIAiCIAh5wu8+x04MxQqCIAiCIOQRosdOEARBEIQ85PfusROJnSAIgiAIecbvvipWJHaCIAiCIOQhv3eP3e+d1gqCIAiCIOQhosdOEARBEIQ843dfFSsSO0EQBEEQ8ozfPbETQ7GCIAiCIAh5hOixEwRBEAQhD/m9+6xEYicIgiAIQp4hkfzeQ7HZktjVqFEDJycnFi1alB2H++U2bNjAkCFDiIiIAGDKlCns27cPX19fhcb1o3Laedm29TDbth3h1au3ANjYFqZ/v/a4VC+b6nOuXLnN7NlrefQwgIIFDfj771a079BQrs6xY964L/6XgIBAChc2ZcjQv6hbt/JPa8eH959Y7L6VkycvExYaSYkSVowb3wMHB9s02zFn9noePXpBwYIG9Pi7Be3bN5Crc/zYRdzdtxIQEEThwiYMHvIndetWypaYr169w7q1+7lz5zHBweEsWTqaOnUqJr328Uvs3HGcO3ceExHxjj173ShRwird4ybGvO2bmDsmi3nr1iOsW7uf4OBwbGwsGDuuO+XKlcxSO96+iWDJgn1cvHCXz9ExFC5SkInT/qKEfeFkdWdN3creXV4MHd2ajp1qpXnc0yd8WLHkEC9fhGBuYUTfQU2pWcdJrs6u7efYsv4kIcGRWNuYMmz0/3Aua5PpNqxZtZ+TJ67y9MlrNDTUcHS2ZejwDlhZmcnqfPzwmYULtnH61HUiI95hVqgAf/5Vn3Yd6qZ57BPHr7DUfRcvAt5gUdiYQYPbUrtuebk627eeYMO6QwQHR1DUphCjx3ambLnimW7Ht9auOoT7ot382akuo8b+CYBUKmXFsn147DpLVNQHHEpbM3ZCZ2xsC6V5rJPHr7LMfS8vXrzFwqIgA4a0pnYd+d8RO7adYsO6I4R8acOoMR0pU65YpuPesf0kO7ef5vWrYACK2pjTu28Lqrk4yuo8efyKhQt2cP3qPRISpBS1KcT8BQMwNTNK9bgnjl9lmftuWRsGDmlD7Trl5Ops33aSDev+IyQ48ksb/qJsBttw3/cxR7ef4dn9l0SGRjFgZjfKVHOQPd7dZViKz2vTtwkNO8j/LEilUhaOWs3ty/eSHSclp/d6cXTbGSLCoihkaUKHgS2wc7SWO97+9cc4e/ASH999xLpkEf4a2ppCViYZapvw437v/spUjBgxglOnTik6DBlLS8ssJWd79uxh+vTp2R9QFhmbGDF8RBd2eyxgt8cCKlUqTf/+M3n4MCDF+i9fBNG711TKlS3J3n2L6N2nDTNnrubYMW9ZHR+fewwbOpdmzWuwf787zZrXYOiQufj53f9p7ZgwcRne3n7MmTOY/QcWUbWqE927TeHNm9CU2/HyDX16z6BsuZLs2etGr96tmTVzLcePXZRvx7D5NGtWg337F9KsWQ2GDZ2Pn9+DbIn506doihW3ZMLEnqk8/hnnMsUZNvyvDB/Tx+c+w4a50axZdfbtX0CzZtUZNtRNLubDhy8w23U9vfu0Zs9eN8qWK0HvXjN4/To4022IivzI353cUFFVZvGKfuzcP5EhI1uhra2ZrK7nKT9u33xGgYK66R73pu8Txo1YR8OmFdjqMZaGTSswdsRabt98Kqtz/Mh1FszeTbee9dmyayxOZWwY3GcZQYFhmW7Htav+tO9Yl3+3T2PV2rHExyXQu8dsPn78LKszd/ZmvC7cZPbcfuz/bz6dujTEdeZGTp+6lupxfX0eMHKYO02b/cHufa40bfYHI4a5c9PvkazO0cMXmTN7Ez17t2DXnlmULVucvr3nEPg6JNPt+Or2rSfs3uWJXTELufL1aw+zeeMxxkz4i393TsbQSJc+f8/jw4dPqR7Lz/cRo4Yvp0mzKuzaO40mzaowatg/3PR7nNSGI5eZ67qVnr2bssNjGmXK2tGv9wICX6f885cWY2MDhgxty7Zd09i2axoVKpZk8ICFPHr4EoAXAW/o8tcMrKxMWbthHLv3zqR33xaoqaum0YaHjBq+lCbNqrJ770yaNKvKyGFL5c/DkUvMdd1Cz97N2ekxnTJli9Gv97wMn4fozzFYFDXjryGtUnx84d4pcrduY9ojkUgoW90xWd0Tu85leKnBlVM+bFuyjyad6zBlzXBsS1uxcNQqQt+Ey+oc2Xqa4zvP8teQVkxcNRRdA23mD1vBp28+3z+fJBtvuY9I7FKQP39+DA0NFR3GDzMwMEBbWzvVx2NiYn5hNFCrVgWqVy+HlVUhrKwKMXRoJ7S0NPDzvZdi/e3bj2JqWoBx43tStKgFbdrUo1WrOqxbt1dWZ9PGA1Sp4kTv3m2wLmpO795tqFSpNBs3Hvgpbfj8OZoTxy8yYkRnype3p0gRUwYMbI+5eUG2bTuaSjuOYWpqxLhxPb60oy6tWtVi3bp9Se3YdIgqVRzp1bs11tbm9OrdmkqVSrNp48FsidvFpQxDhnSkXr2UewCbN69B//5tqVI5+S/+1GzadDCFmB3YtPGQrM7GDQdp1bo2bdrUpWhRc8aN64GJiSHbtx3LdBs2rjuOsYk+k2d0wt7BErNChlSoVBzzwgXk6r19E8G8WTuZPqcrKirK6R532+YzVKhcnG4962NpbUK3nvUpX7EY2zafkdXZuukUzVtVpsX/qmJV1IThY/6HsYk+u7efz3Q7VqweQ4uW1bGxNadY8SJMn9WbwMAQ7t5JSiT9fB/SrHk1ylcoSaFCBWjTtjZ2xQpz5/aTVI+7ZdNRKlVx4O9ezbG2LsTfvZpTsZI9WzYdkdXZtPEwrVrVoHWbmlgXLcTocZ0xMTFkx/aTmW4HJPYsjh21kslTu6GjoyUrl0ql/LvpOH/3bkqduuWwtTVnhmtPPn+O5vChS2m04TiVKtvTo1cTrKzN6NGrCRUqleDfzcdldTZvOEbL1i60+l91rIuaMWrsn5iYGrBz++lMx1+jZhmqVXfC0tIUS0tTBg1pg5aWBjdvJiZhSxbvopqLI8NGdKBESUvMLQriUt0JQ8PUvzBs2XSMSpVL8XevZlhZm/F3r2ZUqFSSLZuTPvObNhyhZevqtP5fjcTzMPYvTEwN2bk9Yx0KpSuVoFXPRpStXjrFx3UNdeRuvhduU9zZhoJm8n/XAh694tiOs3Qf0z5Dr3ts51mqNa6IS5NKmFka03FQSwwK6HFmnxeQeN5P7DpHk051KFu9NObWpvQY15GY6Bgun7iRodfIDpJs/JcbZTqx+/DhA507dyZ//vyYmpri5uYm93hMTAyjRo2iUKFC5MuXj4oVK+Lp6Sl7/Pnz5zRt2hR9fX3y5cuHvb09hw8flj1+584dGjdujI6ODtra2lSrVo3Hj5O+ra1fv54SJUqgoaFB8eLF+eeff2SPPXv2DIlEwp49e6hZsyZaWlo4Ojpy8WJSzwgkDr0WLlwYLS0tWrZsSWio/De9KVOm4OTkJLvftWtXWrRowfz58zE1NcXQ0JD+/fsTGxsrqxMYGEjjxo3R1NTEysqKrVu3ZqqnbcqUKRQuXBh1dXXMzMwYNGgQkDic+vz5c4YOHYpEIpHNHQgNDaVDhw6Ym5ujpaWFg4MD27ZtkztmjRo1GDJkiOy+paUlM2bMoGvXrujq6tKzZ09iYmIYMGAApqamaGhoYGlpiaura4Zi/hHx8fH89985Pn78jJNzysNAvr73qFrVWa7sj2rO3Ln9iNjYuKQ6f3xfpwy+Pikniz8cd1wC8fEJqKuryZWrq6tx47p/is/x9b1P1apOcmVV/3Dmzp3Hsnb4+d6nSrI6Tvj4/ryexx/l5/sghZid8fmSqMfExHLnzmOqVpVPFqtWdcInC+fn/JlblLAvzJhha6jnMpo//+fK3t1ecnUSEhKYPHYjf3WtQ1Ebs1SOJO+W31MqVSkhV1a5aklu+iYmUbGxcdy7+4KK39WpWKUEN/1ST7Qy6v27jwDo6uaXlTmXLYbnmRu8eROGVCrlyuU7PH8WRNU/Uv5DDuDn95AqVeSH0apULY2vz8PEdsTEcffOU6pULf1dHQd8fbLWMzxrxmZcqjtSqYq9XPmrl8GEhERSuUopWZmamiplyxXHz/fR94eRuen7iMpVS8mVVanqgJ/PI1kb/O8+S1ancpVSaR43I+LjEzhy+CKfPkXj6GhLQkIC5876UcTShD4951L9j350bDeZ0ydT7zWFxF7HKt/FV7WqA37fnAf/u8+oUlX+XFWuUgpf34c/1IaURIa94+bFu1RrXEGuPPpzDCunbuGvIa3QNdRJ9zhxsXE8f/AS+/J2cuX25Yvx6PYzAIIDw4gMe4d9+aQhZVU1FYo5FpXVEX6+TM+xGzlyJGfOnGHv3r2YmJgwbtw4rl+/LkuEunXrxrNnz9i+fTtmZmbs3buXBg0acOvWLWxtbenfvz8xMTGcO3eOfPnycffuXfLnT/yF9urVK1xcXKhRowanT59GR0cHLy8v4uIS//itXr2ayZMns3TpUpydnfHx8aFnz57ky5ePLl26yGIcP3488+fPx9bWlvHjx9OhQwcePXqEiooKly9fpnv37syaNYtWrVpx9OhRJk+enG67z5w5g6mpKWfOnOHRo0e0a9cOJycnevZMHNrq3LkzISEheHp6oqqqyrBhw3j79m2G3tPdu3ezcOFCtm/fjr29PUFBQfj5+QGJw6mOjo706tVL9loAnz9/pmzZsowePRodHR3+++8/OnXqhLW1NRUrVkztpZg3bx4TJ05kwoQJALi7u3PgwAF27txJ4cKFefHiBS9evMhQ3Flx//4zOrQfRXR0DFpamixdNg4bm+TzowCCQyL4w0j+m7GhoR5xcfGEh0dRsKABISERGBrqJasTHBzOz5AvvyZOTsVY/s9OilqbY2iky3//nefmzYcUKWKa4nNCgsMx/C75NEqhHUbftcPIUI+Qn9SO7JAYs/z5MTLUJSQ4AoCI8HfExycka5ehoS4hIRGZfr1XL0Pw2HGejp1r0a1nfe7ceoab6y7UVFVo3DzxM79x7QmUlZVo/1eNDB83NCQKA0P5nm0DQ21CQ959acd74uMTMPjuj5+hoTahIVGZbse3pFIp8+ZsoUzZYtjaJQ1ljh3XhSmTVlOnxgBUVJSRSCRMnd6TMmVTnwsXEhKB4fc/L0ZJ73V4ROL5SFbHUJfQkMhMx37k8CX87z5n685JKcQS+eX1v3vPjHR4ncaQaUhIJIbJ3mcd2fFkbUijTmY9ePCCTh2mEhMTi5aWBovcB1PUphAhwRF8/PiZtWsOMnDQ/xgyrB1eF24ydLA7azeMpVz5EikeLyQkAoPvfi4MDHUz0AbdLLchLd5Hr6KhpU5ZF/mEfvuSfdiUssS5WqlUninvXeQHEuIT0NWX/1nRMdAmMizxZyUqNEpW9n2d0KBf+bvs9x6MzFRi9/79e9auXcumTZuoWzdxEu/GjRsxNzcH4PHjx2zbto2XL19iZpb4bXnEiBEcPXqU9evXM2vWLAICAmjdujUODonfVqytkyZdLlu2DF1dXbZv346qauIcBju7pG8H06dPx83NjVatEucVWFlZcffuXVauXCmX2I0YMYLGjRsDMHXqVOzt7Xn06BHFixdn8eLF1K9fnzFjxsiO7+3tzdGjKQ+jfaWvr8/SpUtRVlamePHiNG7cmFOnTtGzZ0/u3bvHyZMnuXr1KuXKJU6QXbNmDba2qU+m/1ZAQAAmJibUqVMHVVVVChcuTIUKid+uDAwMUFZWRltbGxOTpMmnhQoVYsSIEbL7AwcO5OjRo+zatSvNxK5WrVpyzwsICMDW1pY//vgDiURCkSJFUn1udHQ00dHRcmVq6jHJeq/SYmVViL37FhEV9YHjx70ZM3oRm7fMSjW5S7a6SSpNVp5sAZRU+lNXRc2ZO5jx45ZSvXoPlJWVKFnSmiZNqnH3buq9N9/HIyWldiSvk9NXd2Uo5mR1srZqLSFBSgn7wvQf0hyAYiUsePIoEI+d52ncvCL+dwLYvuUMW3aNyfTxk7VDKk32uUrpo/ij52fm9A08uB/Axn/lv1z+u+UoN/0eseSf4ZiaFeD6NX9mTFuPUQE9KldJfXJ7yu1IO0aplExPJQoKDGWu61ZWrB6R5s9/Rt7XrDwnK8dNjZWlKbv2zOTduw+cPH6VCeNWsW7jeLS/DC3XrFWWTl0SF2wVL1EEX9+H7NxxOtXELqX4UvqdlJVzlRXnD1+hUt2yqH4zL9Dnwm38bzxiytrhmT9gBuJONoT5A+cnK3LrEGp2yVRi9/jxY2JiYqhcOWnFoYGBAcWKJXa73rhxA6lUKpeMQWJC8HXO2qBBg+jbty/Hjx+nTp06tG7dmtKlE79J+Pr6Uq1aNVlS963g4GBevHhBjx495Hqu4uLi0NWV/3b09XgApqaJvShv376lePHi+Pv707JlS7n6lStXTjexs7e3R1k5ab6Oqakpt27dAuD+/fuoqKhQpkwZ2eM2Njbo6+unecyv2rRpw6JFi7C2tqZBgwY0atSIpk2boqKS+umJj49n9uzZ7Nixg1evXsmSrnz58qX5Wl8Tz6+6du1K3bp1KVasGA0aNKBJkybUq1cvxee6uroydepUubJJk/szZcrADLUTEodjihRJTPodHGy5fesRmzYdZNq0/snqFjDSk/X+fBUaFomKijJ6eonfCI2M9JL1/oSGRWJkpJfhmDKrcGFTNm+ZycePn3n//iMFCxowdOh8Cpkbp1jfqIA+ISHy31ZDQ5O3IziFOoY/sR0/KjHmCLmy0NAoWY+Qnr42yspKydoeFhqZ5hylVF+vgA7WReV7RS2tTTh90hcAnxuPCA97T9O6E2WPx8cnsHjeHrZvPsOB4ykvJDI00knW8xYe9l7Wi6ennx9lZaVkdcLC3iXr6cuMWTM24HnmOhs2T8LEJGnu0+fPMSxetIPF7sNwqZHY01usWGHu+z9n4/r/Uk3sjFL4eQkLjZK91/p62l/aId8rFBaW+fNx984zwkKj6NBmiqwsPj6B69cesH3rKfb/NxuAkOBIChTQ+yaed2m+lpFR8l6rsLB3ydqQVp3MUlVToXCRxJ9d+1LW3L79lH83H2Ps+M6oqChTtKj8kL61tRk+N1IfujYy0iP0u5+LsLAoWQ9d6m2IStaL96Me+D0hKOAtfaZ0kiv3v/GQ4NehDGg8Xq582cQN2JW2ZrR78t/H2rr5UFJWIjJM/ufgXfh7dPQTR910vsQfGRaF3je9tVHh79HRz/rPSmbl9C/EP1um+iulX3pLUpOQkICysjLXr1/H19dXdvP392fx4sUA/P333zx58oROnTpx69YtypUrx5IlSwDQ1Ey+uu3bY0PicOy3x759+zaXLslPxv02Mfx6gr8+P702pOb7ZFMikaR7zIy+loWFBffv32fZsmVoamrSr18/XFxc5Obwfc/NzY2FCxcyatQoTp8+ja+vL/Xr1093QcT3iV+ZMmV4+vQp06dP59OnT7Rt25b//e9/KT537NixREZGyt3Gju2doTamRiqVEhOTcjudnIrj7e0rV+Z1wQf7Ujaoqqok1fFKXie1eXvZSUtLg4IFDYiMfI/XBR9q16qQYj0np2J4e/vJx+jli719UVk7HFOo4+3li7NT5rdw+FUcnexSiTnxvVdTU8XevmjyOt5+OGfh/Dg6F+X5szdyZQHP32JiagBAo6YV2LpnHFt2j5XdChTU5a9udXBfOSDV4zo4WnH5ovz8yEve/pR2ShxNUFVVoXhJCy5flJ8XeOXiPUp/s81DRkmlUmZOX8+pE1dZu3485uYF5R6Pi4sjLjYeiZL8HyclZSUSElL/neLoaMtF71tyZd7et3ByThw5UFVToaS9VbI6F71v4+Qs/2U8PRUrl2T3/hns2DNNdrMvZUWjJpXYsWca5hYFMDLS5dLFO7LnxMbEcf3aPRydUt8iprSTDZe878iVXfS6jaOzjawNJUpaJqtzyftOmsfNDKlUSkxsLKpqKtiXsuLZ0yC5x58/C0pzqxNHJxsuet+WK/P2uo3jN+ehREnLZHUued/GySljozwZdf6/yxQpZk5hG/ktZhr/WZup60cwZe1w2Q2g/YDmqS6kUFFVoYidOXevySe1d649wKaUJQAFTA3QNdCWqxMXG8d9v8eyOsLPl6nEzsbGBlVVVblEKjw8nAcPEk+is7Mz8fHxvH37FhsbG7nbt8OIFhYW9OnThz179jB8+HBWr14NJPa0nT9/PsWExtjYmEKFCvHkyZNkx7aySn+/ra9KliyZLBH8/n5mFS9enLi4OHx8fGRljx49ku2LlxGampo0a9YMd3d3PD09uXjxoqxHUE1Njfj4eLn658+fp3nz5vz11184OjpibW3Nw4dZm3iro6NDu3btWL16NTt27MDDw4OwsOTbOKirq6OjoyN3y8ww7IIFm7h27Q4vX77h/v1nLFy4mStXbtO0aXUA3Nw2MnrUQln99u0b8Pr1W1xd1/L48Qs8dp/Aw+Mk3bsn9bh26twULy8fVq/y4Mnjl6xe5cHFi3506dIsS+9FRlw478P58zd4+fINXl6+dO0yESurQrRslbg/1AK3zYwevfibdtTn9etgZruuS2yHx0n2eJyie/cWsjqdOzXB28uX1av38OTJS1av3sPFizfp3KVptsT84cMn/P2f4u+fuPLy5cu3+Ps/lW07EhHxDn//pzx6nDi/8unTV/j7P5Wbqzh69GIWuG3JQMxNZHW6dG2Kx+5TeHic4vHjl7i6riMwMIR27VPuFU5Lh061uHXzKetXHeVFwFuO/neVvbu9aNPBBQA9vfzY2JrJ3VRUlDE00sHSKqk3dfLYjSxduF92v/1fNbnsfY+Na4/z7EkQG9ce58qle3ToVFNWp2Pn2uz38ObAHm+ePg5iwZzdBAWG0brdH5lux8xp6/nvoBez5w0gXz5NQoIjCAmO4PPnxC9l+fNrUa58CRbM28rVK3d5+fIt+/ae5eD+83J7oY0b/Q+LFmyX3f+rcwMuet9i7eoDPHnyirWrD3D54m3+6py072PnLo3w8DjDXg9Pnjx+xRzXzQQGhtC2Xe1MtSFfPk1sbc3lbpqaaujp5cfW1hyJRMKfneuxdtVBTp28zsOHL5k4fg0aGuo0apK0Mnv8mFUsXrBLdv/PTnW56H2bdWv+4+mT16xb8x+XL93lz05Jn5dOXeuzZ/dZ9nqc48nj18ybvZXAwFDatKtJZi1euJPr1+7z6lUwDx68wH3RLq5d9adxkyoAdO3emKNHLrF71xkCnr9h278nOOvpQ7v2Se/XuDErWLxgxzdtqPelDYe+tOEQly/d4a9O9WV1OndtyJ7dnuz1OMuTx6+YO3vLlzZk7Dx8/hhNwMNXBDx8BUBIYBgBD1/JbTvy6cNnrnr64dIk+Up4XUMdzK1N5W4Ahsb6FPhm5ey8Ics55ZG08rt+2+qcO3SZ8/9d5vWzN2xbso+wt+HUaJ74fkkkEuq2ceHQlpNcP3eTl08CWeu6DTV1NSrWLcOv83tvd5Kpodj8+fPTo0cPRo4ciaGhIcbGxowfPx4lpcT80M7Ojj///JPOnTvj5uaGs7MzISEhnD59GgcHBxo1asSQIUNo2LAhdnZ2hIeHc/r0aUqUSJyrMGDAAJYsWUL79u0ZO3Ysurq6XLp0iQoVKlCsWDGmTJnCoEGD0NHRoWHDhkRHR3Pt2jXCw8MZNizlDRm/N2jQIKpUqcLcuXNp0aIFx48fT3cYNj3FixenTp069OrVi+XLl6Oqqsrw4cPR1NTMUJfwhg0biI+Pp2LFimhpabF582Y0NTVl890sLS05d+4c7du3R11dHSMjI2xsbPDw8MDb2xt9fX0WLFhAUFCQ7L3MqIULF2JqaoqTkxNKSkrs2rULExMT9PT0svJWpCk0JIJRoxYS/DYMbe18FCtmyeo1k2UrX4ODw3kdmLS/mbmFCStXTWa26xq2/vsfBQsaMH58T+rXryKrU6ZMCdwWjGTxoi24u/+LhYUJCxaOxNHx5/V0vXv/kYULNhMUFIqunjb16lZiyNA/Zb1vwcHhBH6zT5u5uTErVk5g9uz1bN16hIIFDRg3vgf16idNaXAuUxw3t+EsXryVJe7bsLAwxm3BcBwdM9eTkpo7tx/TpUvSJPc5s9cD0KJFTVxnD+TM6auMG7dU9vjwYQsA6N+/LQMGJn6DD3wdgpIk6btgYszDWLx4G0vct6cYc6NGfxAR8Y5/lu0kODgcW9vCrFg5nkKF5HupMsLeoQjzFvVi2eIDrFlxBLNChgwb/T8aNkm5pzQ1QYHhcr1hjs7WzJzXjeVLDrFiySHMLYyYNa8HpUonfWGs17AskZEfWLPiCCHBURS1NWXR8n6YmmV+W6SvW4t07yI/NDx9Vm9atEz8kjPPbSCLFm5nzMhlREa+x9TMiIFD2tK2fR1Z/cDAUCRKSefDydmOuW4DWbJ4J0uX7MLCwph5bgMp7ZjUk9WgUWUiIt6z4p89BAdHYGNrzj8rRmFWSH7LmOzQrUcjoj/HMGvapi8bFBdl+ZoR5MuXNDITFBiK0jfnwsnZljnz+7LU3YNl7nuwKFyQOW59Ke1YNKkNDSsSGfGeVcv3ExwciY1tIZatHIZZodR70VITFhrJ+DErCA6OIL+2JnZ2hVm+aqRsuLt2nXJMnNyNtasPMmfWZiwtTVmwaBBlyib9fkneBjvmzO/PUvfdLHXfjUVhY+a69Zc/Dw0rERHxnpXL98nOw7KVIzLchmf3XzB3cNKOENuXJn5RqdqgPD3GdQDg8ikfkEqpWNs5xWNkxNvXIbyL/CC7X6G2M++jPnJg43EiQ6MoZGXKkDk9MTIxkNVp2LEWMdGxbFngwYf3n7AuUZjhbr3R1NLIchyZJfnNF09IpJkcm3z//j19+/Zlz549aGtrM3z4cP777z/ZFQ5iY2OZMWMGmzZt4tWrVxgaGlK5cmWmTp2Kg4MDAwcO5MiRI7x8+RIdHR0aNGjAwoULZXPwbt68yciRI7lw4QLKyso4OTmxYcMG2SKLrVu3Mm/ePO7evUu+fPlwcHBgyJAhtGzZkmfPnmFlZYWPj49slW5ERAT6+vqcOXOGGjVqALBu3TomT55MaGgoderUoXr16kyfPj3VK0907dqViIgI9u3bJ3sfhgwZgq+vr2wrl8DAQHr06MHp06cxMTHB1dWVIUOGMG3aNHr3Tnu4ct++fcyePRt/f3/i4+NxcHBgxowZ1K6d+O3t0qVL9O7dm/v37xMdHY1UKiUsLIzu3btz6tQptLS06NWrFwEBAURGRsri/P7KE5aWlgwZMkRuC5TVq1fzzz//8PDhQ5SVlSlfvjzz5s3D2Tljvwyk5NztODJDKo1Pv1KukLWpBjnJ+7hARYeQLTSUMzbHNidLkP7avS5/Fgnp72eYG1wLyfzG3jlNVePGP/01ouOvZNux1JUz98UxJ8h0YidkzMuXL7GwsODkyZOyBC0vEoldTpP7f5xFYpdziMQuZxGJXcZEx1/NtmOpK5dPv1IOky3XihXg9OnTvH//HgcHBwIDAxk1ahSWlpa4uLgoOjRBEARB+G2IVbFCtoiNjWXcuHHY29vTsmVLChQoINus+N9//yV//vwp3uzt7dM/uCAIgiAIQgaIodhf4N27d7x58ybFx1RVVdPcFDinE0OxOU3u/3EWQ7E5hxiKzVnEUGzGxCRcz7ZjqSmVzbZj/SpiKPYX0NbWRlv7123OKAiCIAi/q999Vezv3XpBEARBEIQ8RPTYCYIgCIKQh/zeiydEYicIgiAIQp4hEYmdIAiCIAhC3iC2OxEEQRAEQRDyBNFjJwiCIAhCHvJ791mJxE4QBEEQhDzjd59j93untYIgCIIgCHmI6LETBEEQBCEPET12giAIgiAIeYJEIsm2W2b9888/WFlZoaGhQdmyZTl//vxPaGHaRGInCIIgCILwg3bs2MGQIUMYP348Pj4+VKtWjYYNGxIQEPBL45BIpdLcf9VwQWGk3Fd0CNlCKo1XdAjZJPf/OL+PC1R0CNlCQ1lf0SH8sARpjKJDyBYSlBUdQra4FhKs6BB+WFXjxj/9NbLz75KEYhmuW7FiRcqUKcPy5ctlZSVKlKBFixa4urpmW0zpET12giAIgiDkGZJs/JdRMTExXL9+nXr16smV16tXD29v7+xuYprE4glBEARBEIQUREdHEx0dLVemrq6Ourq6XFlISAjx8fEYGxvLlRsbGxMUFPTT45QjFYQc7PPnz9LJkydLP3/+rOhQfkheaEdeaINUKtqRk+SFNkileaMdeaENP8PkyZOlJM5xkd0mT56crN6rV6+kgNTb21uufMaMGdJixYr9omgTiTl2Qo4WFRWFrq4ukZGR6OjoKDqcLMsL7cgLbQDRjpwkL7QB8kY78kIbfoaM9tjFxMSgpaXFrl27aNmypax88ODB+Pr6cvbs2V8SL4g5doIgCIIgCClSV1dHR0dH7vZ9UgegpqZG2bJlOXHihFz5iRMnqFKlyq8KFxBz7ARBEARBEH7YsGHD6NSpE+XKlaNy5cqsWrWKgIAA+vTp80vjEImdIAiCIAjCD2rXrh2hoaFMmzaNwMBASpUqxeHDhylSpMgvjUMkdkKOpq6uzuTJk1Ps+s5N8kI78kIbQLQjJ8kLbYC80Y680IacoF+/fvTr10+hMYjFE4IgCIIgCHmEWDwhCIIgCIKQR4jEThAEQRAEIY8QiZ0gCIIgCEIeIRI7QRAEQRCEPEIkdoIgCILwg6Kioti3bx/+/v6KDuWHREREKDoE4QeJVbGC8JPcvHkzxXKJRIKGhgaFCxfO8VsLREVFpVgukUhQV1dHTU3tF0eUNXnhXAg5S9u2bXFxcWHAgAF8+vQJR0dHnj17hlQqZfv27bRu3VrRIaZrzpw5WFpa0q5dOyCxTR4eHpiYmHD48GEcHR0VHKGQFSKxE3KkAwcOpFj+9Q+xjY0NVlZWvziqzFFSUkIikaT6uKqqKu3atWPlypVoaGj8wsgyLr02mJub07VrVyZPnoySUs4dAMgL5wJEgpqTmJiYcOzYMRwdHdm6dSuTJ0/Gz8+PjRs3smrVKnx8fBQdYrqsra3ZsmULVapU4cSJE7Rt25YdO3awc+dOAgICOH78uKJDFLJCKgg5kEQikSopKUklEonc7WuZkpKS1MXFRRoWFqboUFO1b98+abFixaRr1qyR3rx5U+rn5ydds2aNtESJEtLt27dLt2zZIjU3N5cOHz5c0aGmauPGjVJzc3PphAkTpAcOHJDu379fOmHCBKmFhYV05cqV0hkzZkj19PSkM2fOVHSoacoL50IqTfq5SO2mrq4u7dy5s/TTp0+KDjVNenp6Un19/WQ3AwMDqZmZmdTFxUW6bt06RYeZJg0NDWlAQIBUKpVKO3XqJB09erRUKpVKnz9/Ls2XL58iQ8uwb9swaNAgaa9evaRSqVR6//59qZ6eniJDE36ASOyEHOnkyZPSihUrSk+ePCmNioqSRkVFSU+ePCmtVKmS9L///pNeuHBBam9vL+3evbuiQ01V+fLlpUePHk1WfvToUWn58uWlUqlUunfvXqm1tfWvDi3DatWqJd2xY0ey8h07dkhr1aollUql0k2bNkmLFSv2q0PLlLxwLqTSvJOgLliwQGpoaCj966+/pO7u7tLFixdL//rrL6mRkZF05syZ0r///luqrq4uXbVqlaJDTZWtra10x44d0vfv30sLFCggPXXqlFQqlUp9fX2lhoaGCo4uY0xNTaVeXl5SqVQqtbOzk+7cuVMqlUql9+7dk2praysyNOEHiMROyJHs7e1lv3C+deHCBWnJkiWlUqlUeuLECamFhcWvDi3DNDQ0pP7+/snK/f39pRoaGlKpVCp9+vSpVFNT81eHlmGamprSBw8eJCt/8OCBLO4nT57k6DZIpXnjXEileSdBbdWqlXT58uXJylesWCFt1aqVVCqVSt3d3aWlSpX61aFl2LJly6QqKipSPT09qaOjozQ+Pl4qlSbGXaNGDQVHlzH9+/eXFilSRFqnTh2poaGh9N27d1KpVCrdvn271NnZWcHRCVmVcyfFCL+1x48fo6Ojk6xcR0eHJ0+eAGBra0tISMivDi3DihcvzuzZs4mJiZGVxcbGMnv2bIoXLw7Aq1evMDY2VlSI6TI3N2ft2rXJyteuXYuFhQUAoaGh6Ovr/+rQMiUvnAuAW7dupXhB8SJFinDr1i0AnJycCAwM/NWhZcqxY8eoU6dOsvLatWtz7NgxABo1aiT7Wc+J+vXrx6VLl1i3bh0XLlyQzTG1trZmxowZCo4uYxYuXMjAgQMpWbIkJ06cIH/+/AAEBgYq/HqnQtapKDoAQUhJ2bJlGTlyJJs2baJAgQIABAcHM2rUKMqXLw/Aw4cPMTc3V2SYaVq2bBnNmjXD3Nyc0qVLI5FIuHnzJvHx8Rw6dAiAJ0+e5OhfoPPnz6dNmzYcOXKE8uXLI5FIuHr1Kvfu3WP37t0AXL16VbaqLqfKC+cCkhLUVatWyVYk58YE1cDAgIMHDzJ06FC58oMHD2JgYADAhw8f0NbWVkR46YqNjaVYsWIcOnSIli1byj3WuHFjBUWVObGxsfTq1YuJEydibW0t99iQIUMUE5SQLcSqWCFHun//Ps2bN+fp06dYWFggkUgICAjA2tqa/fv3Y2dnx759+3j37h2dOnVSdLipev/+PVu2bOHBgwdIpVKKFy9Ox44dc+wfrJQ8e/aMFStWyLWhd+/eWFpaKjq0TMkL58Lb25tmzZqhpKSUYoJaqVIlNm/eTFBQECNHjlR0uKlavXo1ffv2pVGjRlSoUAGJRMKVK1c4fPgwK1asoEePHri5uXHlyhV27Nih6HBTVKhQIU6ePEmJEiUUHUqW6enpcePGjWSJnZC7icROyLGkUinHjh2T+0Nct27dHL2thiD8bHkhQQXw8vJi6dKl3L9/X9aOgQMHUqVKFUWHliGzZ8/m3r17rFmzBhWV3Dn41a1bNxwcHBg2bJiiQxGykUjsBOEnevDgAZ6enrx9+5aEhAS5xyZNmqSgqDInIiKCK1eupNiGzp07KyiqzMsL50LIOVq2bMmpU6fInz8/Dg4O5MuXT+7xPXv2KCiyjJs5cybz58+ndu3alC1bNlkbBg0apKDIhB8hEjshxzp16hSnTp1K8Q/xunXrFBRVxn0dbjIyMsLExERug1yJRMKNGzcUGF3GHDx4kD///FM23+n7NoSFhSkwuozLC+fiq7ySoCYkJPDo0aMU2+Hi4qKgqDKuW7duaT6+fv36XxRJ1qW1ybtEIsnRi1eE1InETsiRpk6dyrRp0yhXrhympqbJrhqwd+9eBUWWcUWKFKFfv36MHj1a0aFkmZ2dHY0aNWLWrFloaWkpOpwsywvnAvJOgnrp0iU6duzI8+fP+f5PkEQiIT4+XkGRCULuJxI7IUcyNTVl7ty5OXphRHp0dHTw9fXN1ROT8+XLx61bt3J1GyBvnAvIOwmqk5MTdnZ2TJ06NcUvbrq6ugqKTBByv9w541PI82JiYnLNJOrUtGnThuPHj9OnTx9Fh5Jl9evX59q1a7k+IcoL5wIgPDycNm3aKDqMH/bw4UN2796NjY2NokPJlDJlynDq1Cn09fVxdnZO8/rDObX3dNiwYUyfPp18+fKlu2hiwYIFvygqITuJxE7Ikf7++2+2bt3KxIkTFR1KltnY2DBx4kQuXbqEg4MDqqqqco/nhonJjRs3ZuTIkdy9ezfFNjRr1kxBkWVOXjgXkHcS1IoVK/Lo0aNcl9g1b94cdXV1AFq0aKHYYLLIx8eH2NhY2f9Tk1bSKuRsYihWyJEGDx7Mpk2bKF26NKVLl072hzg3fJPMCxOT09paJjfNhcoL5wLA1dWVBQsW0Lhx41ydoO7du5cJEyYwcuTIFNtRunRpBUUmCLmfSOyEHKlmzZqpPiaRSDh9+vQvjEYQcoa8kqCm9IVBIpEglUpz1RcGQciJRGInCIIg/FLPnz9P8/GUroeb08THx7Nw4UJ27txJQECA3HWIgVyzFdDVq1fZtWtXim3IDXvxCcmJOXaCkI3ywsRkd3d3evXqhYaGBu7u7mnWzclDf3nhXORVuSFxS8/UqVNZs2YNw4YNY+LEiYwfP55nz56xb9++XLOf4Pbt2+ncuTP16tXjxIkT1KtXj4cPHxIUFJTsGrhC7iF67IQco1WrVmzYsAEdHR1atWqVZt2c+k2yZs2a7N27Fz09vTSHkwHOnDnzi6LKHCsrK65du4ahoWGuHvrLC+cC8k6CeuDAARo2bIiqqioHDhxIs25uWJRTtGhR3N3dady4Mdra2vj6+srKLl26xNatWxUdYrpKly5N79696d+/P9ra2vj5+WFlZUXv3r0xNTVl6tSpig5RyALRYyfkGLq6urKVWLl1H6tvE4ScnCyk5enTpyn+P7fJC+cC8s4qxhYtWhAUFETBggXTXFGaW+bYBQUF4eDgAED+/PmJjIwEoEmTJrlmNf/jx49p3LgxAOrq6nz48AGJRMLQoUOpVauWSOxyKZHYCTnGt5fgyQ2X40lP9+7dWbx4cbKLs3/48IGBAwfmisui5RWnTp2idu3aKT62dOlSBgwY8Isjyri8kqB+e9mw7y8hlhuZm5sTGBhI4cKFsbGx4fjx45QpU4arV6/KtkTJ6QwMDHj37h0AhQoV4vbt2zg4OBAREcHHjx8VHJ2QVWIoVsiRpkyZQrdu3XL1XBxlZWUCAwMpWLCgXHlISAgmJibExcUpKLK0pTfc962cPPT3LT09PU6cOEH58uXlyhctWsSkSZOIiopSUGS/pxcvXmBhYZHiY5cuXaJSpUq/OKLMGzNmDDo6OowbN47du3fToUMHLC0tCQgIYOjQocyePVvRIaarY8eOlCtXjmHDhjFz5kwWL15M8+bNOXHiBGXKlMmxU16EtInETsiRypYti5+fH9WrV6dHjx60atUKDQ0NRYeVIVFRUUilUvT19Xn48CEFChSQPRYfH8/BgwcZM2YMr1+/VmCUqft+Ptr169eJj4+nWLFiQOJF6JWVlSlbtmyu2XZm/fr1jBo1irNnz1KyZEkA5s+fz/Tp0zl06BDVqlVTcIQZ8+HDB2bPns2pU6d4+/Ztsp6vnDzn8VvFixfHy8sLQ0NDuXIvLy8aN25MRESEYgL7AZcvX8bLywsbG5tcMUcQElfufv78GTMzMxISEpg/fz4XLlyQbeitr6+v6BCFLBCJnZBj3bx5k/Xr17N161ZiYmJo37493bt3T9brktMoKSmlOd9JIpEwdepUxo8f/wujypoFCxbg6enJxo0bZb/kw8PD6datG9WqVWP48OEKjjDj5s+fz6JFi7hw4QI7duxg1qxZHDlyJFdduq5Dhw6cPXuWTp06pXiN1cGDBysosszp2bMnN27cwNPTUzZV4dy5czRt2pQpU6YwdOhQBUeYvnPnzlGlShVUVORnNMXFxeHt7Y2Li4uCIhN+dyKxE3K8uLg4Dh48yPr16zl69CjFihXj77//pmvXrjlykcXZs2eRSqXUqlULDw8PDAwMZI+pqalRpEgRzMzMFBhhxhUqVIjjx49jb28vV3779m3q1auXY3sdUzN27FhWr15NfHw8R48epWLFiooOKVP09PT477//qFq1qqJD+SFSqZQ2bdrw9u1bjh8/zsWLF2nWrBkzZszINclpalMtQkNDKViwYK5YAJIX2iAkJxZPCDleQkICMTExREdHI5VKMTAwYPny5UycOJHVq1fTrl07RYcop3r16kDiitLChQun2HsXEBBA4cKFf3VomRYVFcWbN2+SJXZv376VTbrOqVLag8/U1BQtLS1cXFy4fPkyly9fBnL2fnzf0tfXl/uikFtJJBK2bdtG48aNqV27Njdv3sTV1TVHL2L53terZHwvNDSUfPnyKSCizEutXyc6Oho1NbVfHI2QXUSPnZBjXb9+nfXr17Nt2zbU1dXp3Lkzf//9t+zC4W5ubsydO5c3b94oONKU5YVvw507d+bs2bO4ubnJJrRfunSJkSNH4uLiwsaNGxUcYerS2oPvWzl9P75vbdmyhf3797Nx40a0tLQUHU6m3Lx5M1nZu3fv6NChA40bN6Zv376y8px8rdive2zu37+fBg0ayK2AjY+P5+bNmxQrVoyjR48qKsR0ff3SM3ToUKZPn07+/Pllj8XHx3Pu3DmePXuW5vY6Qs4lEjshRypdujR3796lfv369OzZk6ZNm6KsrCxXJzg4GGNj4xy7dYKSkpJs365vPX/+nJIlS/LhwwcFRZZxHz9+ZMSIEaxbt062l5qKigo9evRg3rx5uaZnIq9wdnbm8ePHSKVSLC0tUVVVlXv8xo0bCoosfV/nnn77J+fb+7nlWrHdunUDYOPGjbRt2xZNTU3ZY2pqalhaWtKzZ0+MjIwUFWK6vn7pef78Oebm5nK/W7+2Ydq0abluqoKQSAzFCjlSmzZt6N69O4UKFUq1ToECBXJkUvd1uxCJRMKkSZPkelbi4+O5fPkyTk5OCoouc7S0tPjnn3+YN2+eLKGwsbERCZ2CpLWxb06Xmze7/tbXPTYtLS0ZMWJErvxZ+HouatasyZ49e8Tq1zxG9NgJOUZe2T/t63YhZ8+epXLlynJzVb5+Gx4xYgS2traKCvG3kFc+T0LO9OnTJ6RSqeyL2/Pnz9m7dy8lS5akXr16Co4ua+Lj47l16xZFihQRyV4uJnrshBwjo/M5cvqlk75eHaBbt24sXrwYHR0dBUeUdbl537S88nlKSUxMTIrnIycvyEnv+rDfyg37wDVv3pxWrVrRp08fIiIiqFChAmpqaoSEhLBgwQK5OYM51ZAhQ3BwcKBHjx7Ex8fj4uLCxYsX0dLS4tChQ9SoUUPRIQpZIHrsBEFIVV7ZNy2vePDgAT169MDb21uuPDfMTVNSUspQvZzejq+MjIw4e/Ys9vb2rFmzhiVLluDj44OHhweTJk3C399f0SGmq1ChQuzfv59y5cqxb98++vfvz5kzZ9i0aRNnzpzBy8tL0SEKWSB67AQhG7Vq1YoNGzago6MjWz2XmtxwuZ4jR47kiX3T8opu3bqhoqLCoUOHUky0c7KcOB/2R3z8+FG2ufLx48dp1aoVSkpKVKpUiefPnys4uowJDQ3FxMQEgMOHD9OmTRvs7Ozo0aNHitsFCbmDSOwEIRvp6urK/tjq6Ojkqj+8Kckr+6YBXL16lV27dhEQEEBMTIzcY7khyQbw9fXl+vXrFC9eXNGh/PZsbGzYt28fLVu25NixY7KrZbx9+zbXTL8wNjbm7t27mJqacvToUf755x8gMWn9fhcCIfcQiZ0gZKOvK+YAli9fTkJCgmzV3LNnz9i3bx8lSpSgfv36igoxU6ZPn86kSZNy5b5p39q+fTudO3emXr16nDhxgnr16vHw4UOCgoJo2bKlosPLsJIlSxISEqLoMLLFhw8fOHv2bIqJdm7YMHrSpEl07NiRoUOHUrt2bSpXrgwk9t45OzsrOLqM6datG23btpX1/tatWxdIvO6t+PKQe4k5doLwk9SrV09ucnXx4sVRVVXNVZOrc/O+ad8qXbo0vXv3pn///mhra+Pn54eVlRW9e/fG1NSUqVOnKjrEDDl9+jQTJkxg1qxZODg4JDsfuaWnyMfHh0aNGvHx40c+fPiAgYEBISEhaGlpUbBgwRy9KOdbQUFBBAYG4ujoKJtDeOXKFXR0dGSJ0cuXLzEzM8vwHMNfbffu3bx48YI2bdpgbm4OJO7Rp6enR/PmzRUcnZAVIrEThJ8kL0yuTi/hmTx58i+K5Mfky5ePO3fuYGlpiZGREWfOnMHBwQF/f39q1apFYGCgokPMkK/JwfdD/Llh8cS3atSogZ2dHcuXL0dPTw8/Pz9UVVX566+/GDx4cLrzU3MTHR0dfH19sba2VnQoWebg4MDhw4exsLBQdChCBoihWEH4SfLC5Orckrilx8DAQHZt20KFCnH79m0cHByIiIjg48ePCo4u475upZPb+fr6snLlSpSVlVFWViY6Ohpra2vmzp1Lly5d8lRilxf6Tp49eya78oyQ84nEThB+krwwuTqvqFatGidOnMDBwYG2bdsyePBgTp8+zYkTJ6hdu7aiw8uw6tWrKzqEbKGqqirrdTQ2NiYgIIASJUqgq6tLQECAgqMThNxNJHaC8JPkhcnV8fHxLFy4kJ07d6Y4yT0sLExBkWXO0qVL+fz5MwBjx45FVVWVCxcu0KpVKyZOnKjg6DLu3LlzaT7u4uLyiyL5Mc7Ozly7dg07Oztq1qzJpEmTCAkJYfPmzTg4OCg6PEHI1cQcO0H4iTIyuTonmzRpEmvWrGHYsGFMnDiR8ePHy1b3Tpo0KVesXgT4888/qVGjBtWrV8fOzk7R4WRZShPwv51vl1vm2F27do13795Rs2ZNgoOD6dKlCxcuXMDGxob169fj6Oio6BCzzdfFOrl5jl1eaMPvRCR2giCkqmjRori7u9O4cWO0tbXx9fWVlV26dImtW7cqOsQM6d27N2fPnuXBgweYmJhQvXp1qlevTo0aNXJFgv1VZGSk3P3Y2Fh8fHyYOHEiM2fOzFXDyr+LvLB4QiR2uYtI7ARBSFW+fPnw9/encOHCmJqa8t9//1GmTBmePHmCs7NzskQjpwsKCsLT0xNPT09ZolewYMFcsyo2NefOnWPo0KFcv35d0aFkyOrVq6lRowa2traKDuWnywtJUV5ow+8kZ26sIwhCjmBubi5LemxsbDh+/DiQeBUHdXV1RYaWJdra2ujr66Ovr4+enh4qKiqySyrlZgUKFOD+/fuKDiPD3NzcKF68OGZmZnTo0IGVK1dy7949RYf1U9y9e5ciRYooOowfsnLlSoyNjRUdhpBBosdOEIRUjRkzBh0dHcaNG8fu3bvp0KEDlpaWBAQEMHToUGbPnq3oEDNk9OjRnD17Fj8/P0qVKoWLiwvVq1fHxcUFPT09RYeXYTdv3pS7L5VKCQwMZPbs2cTGxuaqi7YHBQVx5swZzp49i6enJw8fPqRAgQLUqFGD7du3Kzq8dLVs2TLFSwZKJBI0NDSwsbGhY8eOFCtWTAHRZUxq14P9tg0uLi7i8mK5jEjsBEHIsMuXL+Pl5YWNjQ3NmjVTdDgZpqSkRIECBRg6dCjNmzenRIkSig4pS5SUlJBIJMn2RqtUqRLr1q3LVfMFf8P58AAAFItJREFUv/rw4QMXLlxg+/btbNmyBalUSlxcnKLDSlfXrl3Zt28fenp6lC1bFqlUio+PDxEREdSrVw8/Pz+ePXvGqVOnqFq1qqLDTZGVlRXBwcF8/PgRfX19pFIpERERaGlpkT9/ft6+fYu1tTVnzpwRmxPnIiKxEwQhVefOnaNKlSqoqMjvjBQXF4e3t3eu2V7Dz89P1jN0/vx5lJWVZYsnatSokSsSvdjYWGxtbTl27BgaGhpAUsL69X5uceTIEdn58PPzw97eHhcXF2rUqEG1atXQ19dXdIjpGjNmDFFRUSxdulS2WjkhIYHBgwejra3NzJkz6dOnD3fu3OHChQsKjjZl27ZtY9WqVaxZs4aiRYsC8OjRI3r37k2vXr2oWrUq7du3x8TEhN27dys4WiGjRGInCEKqlJWVCQwMpGDBgnLloaGhFCxYMNdsr/E9Pz8/Fi1axJYtW0hISMg17ShQoAAXL17ExsZG0aH8kK8J6fDhw+nduze6urqKDinTChQogJeXV7Ltcx48eECVKlUICQnh1q1bVKtWjYiICMUEmY6iRYvi4eGBk5OTXLmPjw+tW7fmyZMneHt707p161y/wOh3IhZPCIKQqq/XIP1eaGgo+fLlU0BEWefj48PChQtp3rw5NWvWZPPmzTg6OjJs2DBFh5ZhnTt3Zs2aNYoO44ctWLCAqlWrMm/ePIoVK0a7du1Yvnx5rrh+8ldxcXEpLvi4d++e7IuChoZGij8/OUVgYGCKw95xcXEEBQUBYGZmJrscn5A7iCtPCIKQzNdrdUokErp27Sq3AjY+Pp6bN29SpUoVRYWXafr6+rx//x5HR0dq1KhBz549cXFxyXWXdouJiWHNmjWcOHGCcuXKJUuuFyxYoKDIMmfIkCEMGTIEgFu3bnH27FlOnjzJ4MGDMTQ0zBW9Q506daJHjx6MGzeO8uXLI5FIuHLlCrNmzaJz584AnD17Fnt7ewVHmrqaNWvSu3dv1qxZI7sajo+PD3379qVWrVpA4vmxsrJSZJhCJonEThCEZL4OjUmlUrS1tdHU1JQ9pqamRqVKlejZs6eiwsu0zZs358pE7nu3b9+mTJkyQOKQ37dycs9Qanx8fPD09OTMmTOcP3+ehIQEzM3NFR1WhixcuBBjY2Pmzp3LmzdvgMTr3g4dOpTRo0cDUK9ePRo0aKDIMNO0du1aOnXqRNmyZVFVVQUSe+tq167N2rVrAcifPz9ubm6KDFPIJDHHThCEVI0aNYopU6agpaUFILucWIkSJahfv76CoxNyq2bNmnHhwgWioqJwcnKSLWLJrcl3VFQUQK6MHRKHjx88eIBUKqV48eI5eosWIX0isRMEIVV169aldevW9OnTh4iICIoXL46qqiohISEsWLCAvn37KjpEIRcaMWJErk7kBCEnE4mdIAipMjIyks0TWrNmDUuWLMHHxwcPDw8mTZqUqya7C7mPg4MDhw8fzpF7qL1584YRI0Zw6tQp3r59m2xvwdyw0jo+Pp4NGzbI2pCQkCD3+OnTpxUUmfAjxBw7QRBS9fHjR7S1tQE4fvw4rVq1QklJiUqVKvH8+XMFRyfkdc+ePSM2NlbRYaSoa9euBAQEMHHiRExNTXPlHMfBgwezYcMGGjduTKlSpXJlG4TkRGInCEKqbGxs2LdvHy1btuTYsWMMHToUgLdv34ohNOG3duHCBc6fP59sD7jcZPv27ezcuZNGjRopOhQhG4l97ARBSNWkSZMYMWIElpaWVKxYkcqVKwOJvXdft0cQhN+RhYVFsuHX3EZNTS3Xb3YtJCfm2AmCkKagoCACAwNxdHSUXTrpypUr6Ojo5Mprkwq5h7a2Nn5+flhbWys6lGSOHz+Om5sbK1euxNLSUtHhZImbmxtPnjxh6dKlYhg2DxGJnSAIgpAj5eTETl9fn48fPxIXF4eWlpZsH7ivwsLCFBRZxrVs2ZIzZ85gYGCAvb19sjbs2bNHQZEJP0LMsRMEQRCETFq0aJGiQ/hhenp6tGzZUtFhCNlM9NgJgiAIOdLWrVtp3rx5rrsusSAokkjsBEEQhF9q0KBB2NjYMGjQILnypUuX8ujRoxzbGxYVFSVbDf71ahOpEavGBUURiZ0gCILwSxUqVIgDBw5QtmxZufIbN27QrFkzXr58qaDI0qasrExgYCAFCxZESUkpxQUHUqkUiUSSYzcoLlOmDKdOnUJfXx9nZ+c0F03cuHHjF0YmZBcxx04QBEH4pUJDQ9HV1U1WrqOjQ0hIiAIiypjTp09jYGAAwJkzZxQcTdY0b94cdXV1AFq0aKHYYISfQvTYCYIgCL9UqVKl6NOnDwMGDJArX7JkCcuXL+fu3bsKikwQcj/RYycIgiD8UsOGDWPAgAEEBwdTq1YtAE6dOoWbm1uOnV8HcPPmzQzXLV269E+MRBBSJ3rsBEEQhF9u+fLlzJw5k9evXwNgaWnJlClT6Ny5s4IjS93XeXVf59GlJafOsdPX18/wZsS5YS8+ITmR2AmCIAgKExwcjKamJvnz51d0KOl6/vy57P8+Pj6MGDGCkSNHyi61d/HiRdzc3Jg7d26Onb+2ceNG2f9DQ0OZMWMG9evXl2vDsWPHmDhxouza0ELuIhI7QRAEQcikChUqMGXKFBo1aiRXfvjwYSZOnMj169cVFFnGtW7dmpo1ayab67h06VJOnjzJvn37FBOY8ENEYicIgiD8dHltmw1NTU1u3LhBiRIl5Mr9/f0pU6YMnz59UlBkGZc/f358fX2xsbGRK3/48CHOzs68f/9eQZEJP0IsnhAEQRB+ury2zUaJEiWYMWMGa9euRUNDA4Do6GhmzJiRLNnLqQwNDdm7dy8jR46UK9+3bx+GhoYKikr4UaLHThAEQRAy6cqVKzRt2pSEhAQcHR0B8PPzQyKRcOjQISpUqKDgCNO3YcMGevToQYMGDWRz7C5dusTRo0dZs2YNXbt2VWyAQpaIxE4QBEEQsuDjx49s2bKFe/fuIZVKKVmyJB07dsxV17a9fPky7u7u+Pv7y9owaNAgKlasqOjQhCwSiZ0gCILw04ltNgTh1xBz7ARBEISf7tuNh9PbZiO3ePDgAZ6enrx9+5aEhAS5xyZNmqSgqDInISGBR48epdgGFxcXBUUl/AjRYycIgiD8Unlhm43Vq1fTt29fjIyMMDExkeuNlEgkuWJl76VLl+jYsSPPnz/n+1RAIpHk2E2WhbSJxE4QBEH4pfLCNhtFihShX79+jB49WtGhZJmTkxN2dnZMnToVU1PTZEPlurq6CopM+BFiKFYQBEH4pfLCNhvh4eG0adNG0WH8kIcPH7J79+5kCbaQu4nEThAEQfilpk6dSo8ePfD09Exxm43coE2bNhw/fpw+ffooOpQsq1ixIo8ePRKJXR4jEjtBEAThl+ratSslSpTA3d2dPXv2yLbZ8PLyyjXbbNjY2DBx4kQuXbqEg4MDqqqqco8PGjRIQZFl3MCBAxk+fDhBQUEptqF06dIKikz4EWKOnSAIgvDLxMbG0qtXLyZOnIi1tbWiw8kyKyurVB+TSCQ8efLkF0aTNUpKSsnKJBIJUqlULJ7IxURiJwiCIPxSenp63LhxI1cndnnB8+fP03y8SJEivygSITuJxE4QBEH4pbp164aDgwPDhg1TdCg/LCYmhqdPn1K0aFFUVMTsJkHxxKdQEARB+KVsbGyYPn063t7elC1bNtkluHLD/LSPHz8ycOBANm7cCCRuVmxtbc2gQYMwMzNjzJgxCo4wYzZv3syKFSt4+vQpFy9epEiRIixatAgrKyuaN2+u6PCELEg+wC4IgiAIP9GaNWvQ09Pj+vXrrFq1ioULF8pu316hIicbO3Ysfn5+eHp6oqGhISuvU6cOO3bsUGBkGbd8+XKGDRtGo0aNiIiIkM2p09PTyzXnQUhODMUKgiAIQiYVKVKEHTt2UKlSJbS1tfHz88Pa2ppHjx5RpkwZoqKiFB1iukqWLMmsWbNo0aKFXBtu375NjRo1CAkJUXSIQhaIHjtBEARBYaRSabLLWeUGwcHBFCxYMFn5hw8fkl3BIad6+vQpzs7OycrV1dX58OGDAiISsoNI7ARBEIRfbtOmTTg4OKCpqYmmpialS5dm8+bNig4rw8qXL89///0nu/81mVu9erVs0+WczsrKCl9f32TlR44coWTJkr8+ICFbiMUTgiAIwi+1YMECJk6cyIABA6hatSpSqRQvLy/69OlDSEgIQ4cOVXSI6XJ1daVBgwbcvXuXuLg4Fi9ezJ07d7h48SJnz55VdHgZMnLkSPr378/nz5+RSqVcuXKFbdu24erqmmuuACIkJ+bYCYIgCL+UlZUVU6dOpXPnznLlGzduZMqUKTx9+lRBkWXOrVu3mD9/PtevXychIYEyZcowevRoHBwcFB1ahq1evZoZM2bw4sULAAoVKsSUKVPo0aOHgiMTskokdoIgCMIvpaGhwe3bt5Ndo/Thw4c4ODjw+fNnBUX2+woJCSEhISHFeYNC7iLm2AmCIAi/lI2NDTt37kxWvmPHDmxtbRUQUeYdPnyYY8eOJSs/duwYR44cUUBEmff06VMePnwIgJGRkSype/jwIc+ePVNgZMKPEHPsBEEQhF9q6tSptGvXjnPnzlG1alUkEgkXLlzg1KlTKSZ8OdGYMWOYPXt2snKpVMqYMWNo2LChAqLKnK5du9K9e/dkyfTly5dZs2YNnp6eiglM+CFiKFYQBEH45a5fv86CBQu4d+8eUqmUkiVLMnz48BS338iJNDU18ff3x9LSUq782bNn2Nvb54rtQnR0dLhx40ayIfFHjx5Rrlw5IiIiFBOY8ENEj50gCILwy5UtW5Z///1X0WFkma6uLk+ePEmW2D169CjZJdJyKolEwrt375KVR0ZGyq5CIeQ+Yo6dIAiC8EsoKSmhrKyc5k1FJXf0NzRr1owhQ4bw+PFjWdmjR48YPnw4zZo1U2BkGVetWjVcXV3lkrj4+HhcXV35448/FBiZ8CPEUKwgCILwS+zfvz/Vx7y9vVmyZAlSqZRPnz79wqiyJjIykgYNGnDt2jXMzc0BePnyJdWqVWPPnj3o6ekpNsAMuHv3Li4uLujp6VGtWjUAzp8/T1RUFKdPn6ZUqVIKjlDICpHYCYIgCApz7949xo4dy8GDB/nzzz+ZPn06hQsXVnRYGSKVSjlx4gR+fn6yq2e4uLgoOqxMef36NUuXLpVrw4ABAzAwMFB0aEIWicROEARB+OVev37N5MmT2bhxI/Xr18fV1TXX9xBFRETkip46IW8Tc+wEQRCEXyYyMpLRo0djY2PDnTt3OHXqFAcPHsx1Sd2cOXPYsWOH7H7btm0xNDSkUKFC+Pn5KTCyjDt69CgXLlyQ3V+2bBlOTk507NiR8PBwBUYm/AiR2AmCIAi/xNy5c7G2tubQoUNs27YNb29v2dyu3GblypVYWFgAcOLECU6cOMGRI0do2LAhI0eOVHB0GTNy5EiioqKAxMujDRs2jEaNGvHkyROGDRum4OiErBJDsYIgCMIvoaSkhKamJnXq1EFZWTnVenv27PmFUWWNpqYmDx48wMLCgsGDB/P582dWrlzJgwcPqFixYq7o8cqfPz+3b9/G0tKSKVOmcPv2bXbv3s2NGzdo1KgRQUFBig5RyILcsa5cEARByPU6d+6MRCJRdBjZQl9fnxcvXmBhYcHRo0eZMWMGkLigIrfsAaempsb/27uXUGjfOIzjF6ZZvCiEjeSQSTksRFlgYSPbmSUlspOoaYqFUlKKIlLKwmFnMVkilENJlEMGRY2iiaFQTguH8V+8NSX1NoP3/7wz8/2sZu6exbW8eu7fc99PT0+SpMXFRdXV1UmSkpKS/G/yEHoodgCA/8XExITREX6MzWZTTU2NLBaLrq+v/VeI7e7ufrrJ4V9VXl4uu92usrIybW5u+mcGj4+P/Ue4IPQwYwcAQJAGBgbU3NysvLw8LSwsKC4uTpJ0cXGhpqYmg9MFZnh4WCaTSU6nUyMjI0pLS5Mkzc7Oqrq62uB0+Cpm7AAA+KLDw0OdnZ3p+fn5w3qo3D6B8MNWLAAAQTo5OZHNZpPL5ZL0e7ZOkn+GMFTm7Nxut8bHx+V2uzU4OKjU1FTNzc0pPT1d+fn5RsfDF7AVCwBAkFpbW5WZmSmv16tfv37p4OBAq6urKikp0fLystHxArKysqLCwkJtbGxoenpaDw8PkqS9vT11dnYanA5fRbEDACBI6+vr6urqUkpKiqKjoxUdHa3y8nL19PSopaXF6HgBaW9vV3d3txYWFmQ2m/3rlZWVWl9fNzAZvoNiBwBAkN7e3vwfTCQnJ+v8/FySlJGRoaOjIyOjBczlcslqtX5aT0lJ0fX1tQGJ8BOYsQMAIEgFBQXa29tTdna2SktL1dvbK7PZrNHRUWVnZxsdLyAJCQm6uLhQVlbWh/WdnR3/F7IIPbyxAwAgSB0dHfL5fJKk7u5unZ6eqqKiQjMzMxoaGjI4XWBqamrU1tYmr9erqKgo+Xw+ra2tyeFw+A8rRujhuBMAAH7Azc2NEhMTQ+Z2jZeXF9XX12tqakrv7+8ymUx6fX1VbW2tJiYm/njtG/5dFDsAACLYycmJtre35fP5VFRUJIvFYnQkfAPFDgCACGG32wN+tr+//y8mwd/CxxMAAESInZ2dD/+3trb09vam3NxcSb/viY2JiVFxcbER8fADKHYAAESIpaUl/+/+/n7Fx8drcnJSiYmJkqTb21s1NDSooqLCqIj4JrZiAQCIQGlpaZqfn/90ddj+/r6qqqr8Z/MhtHDcCQAAEeju7k6Xl5ef1q+urnR/f29AIvwEih0AABHIarWqoaFBTqdTHo9HHo9HTqdTjY2NstlsRsfDF7EVCwBABHp6epLD4dDY2JheXl4kSSaTSY2Njerr61NsbKzBCfEVFDsAACLY4+Oj3G633t/flZOTQ6ELcRQ7AACAMMGMHQAAQJig2AEAAIQJih0AAECYoNgBAACECYodAABAmKDYAQAAhAmKHQAAQJig2AEAAISJ/wBQOTSjjc5/eAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=new_model1.predict(X_test_c)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_c, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0730327a",
   "metadata": {},
   "source": [
    "## Train set: Chest / Test set: Chest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 423,
   "id": "2abb3769",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "15 12 8\n"
     ]
    }
   ],
   "source": [
    "n_timesteps, n_features, n_outputs = X_train_c.shape[1], X_train_c.shape[2], y_train_c.shape[1]\n",
    "print(n_timesteps, n_features, n_outputs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 424,
   "id": "821aa5b6",
   "metadata": {},
   "outputs": [],
   "source": [
    "model2 = Sequential()\n",
    "model2.add(LSTM(64, input_shape = [n_timesteps, n_features], return_sequences=True))\n",
    "model2.add(LSTM(32))\n",
    "model2.add(Dropout(0.3))\n",
    "\n",
    "model2.add(Dense(16, activation=\"relu\"))\n",
    "model2.add(Dropout(0.4))\n",
    "model2.add(Dense(n_outputs, activation = \"softmax\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 425,
   "id": "92f8e7a9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_35\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " lstm_25 (LSTM)              (None, 15, 64)            19712     \n",
      "                                                                 \n",
      " lstm_26 (LSTM)              (None, 32)                12416     \n",
      "                                                                 \n",
      " dropout_39 (Dropout)        (None, 32)                0         \n",
      "                                                                 \n",
      " dense_74 (Dense)            (None, 16)                528       \n",
      "                                                                 \n",
      " dropout_40 (Dropout)        (None, 16)                0         \n",
      "                                                                 \n",
      " dense_75 (Dense)            (None, 8)                 136       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 32792 (128.09 KB)\n",
      "Trainable params: 32792 (128.09 KB)\n",
      "Non-trainable params: 0 (0.00 Byte)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model2.compile(loss = \"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])\n",
    "model2.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 426,
   "id": "a6d30c85",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/30\n",
      "237/237 [==============================] - 13s 33ms/step - loss: 1.6225 - accuracy: 0.3511 - val_loss: 1.2754 - val_accuracy: 0.4834\n",
      "Epoch 2/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 1.2458 - accuracy: 0.5203 - val_loss: 1.0034 - val_accuracy: 0.6324\n",
      "Epoch 3/30\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 1.0780 - accuracy: 0.5970 - val_loss: 0.9331 - val_accuracy: 0.6495\n",
      "Epoch 4/30\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 1.0032 - accuracy: 0.6244 - val_loss: 0.8409 - val_accuracy: 0.6685\n",
      "Epoch 5/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.9338 - accuracy: 0.6452 - val_loss: 0.8112 - val_accuracy: 0.6801\n",
      "Epoch 6/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8995 - accuracy: 0.6593 - val_loss: 0.8005 - val_accuracy: 0.6862\n",
      "Epoch 7/30\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.8601 - accuracy: 0.6652 - val_loss: 0.7626 - val_accuracy: 0.6994\n",
      "Epoch 8/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8306 - accuracy: 0.6810 - val_loss: 0.7639 - val_accuracy: 0.7046\n",
      "Epoch 9/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8110 - accuracy: 0.6901 - val_loss: 0.7602 - val_accuracy: 0.7004\n",
      "Epoch 10/30\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.8018 - accuracy: 0.6879 - val_loss: 0.7445 - val_accuracy: 0.7144\n",
      "Epoch 11/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7552 - accuracy: 0.7048 - val_loss: 0.7601 - val_accuracy: 0.7091\n",
      "Epoch 12/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7482 - accuracy: 0.7069 - val_loss: 0.7666 - val_accuracy: 0.7028\n",
      "Epoch 13/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7479 - accuracy: 0.7085 - val_loss: 0.7681 - val_accuracy: 0.7041\n",
      "Epoch 14/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7151 - accuracy: 0.7151 - val_loss: 0.7458 - val_accuracy: 0.7197\n",
      "Epoch 15/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7122 - accuracy: 0.7205 - val_loss: 0.7544 - val_accuracy: 0.7078\n",
      "Epoch 16/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6933 - accuracy: 0.7255 - val_loss: 0.7797 - val_accuracy: 0.7123\n",
      "Epoch 17/30\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.6884 - accuracy: 0.7257 - val_loss: 0.7872 - val_accuracy: 0.7128\n",
      "Epoch 18/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6872 - accuracy: 0.7304 - val_loss: 0.7719 - val_accuracy: 0.7110\n",
      "Epoch 19/30\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.6667 - accuracy: 0.7325 - val_loss: 0.7957 - val_accuracy: 0.7168\n",
      "Epoch 20/30\n",
      "237/237 [==============================] - 7s 28ms/step - loss: 0.6651 - accuracy: 0.7364 - val_loss: 0.8157 - val_accuracy: 0.7110\n",
      "Epoch 21/30\n",
      "237/237 [==============================] - 7s 28ms/step - loss: 0.6419 - accuracy: 0.7420 - val_loss: 0.7981 - val_accuracy: 0.7115\n",
      "Epoch 22/30\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.6302 - accuracy: 0.7435 - val_loss: 0.8410 - val_accuracy: 0.7017\n",
      "Epoch 23/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6407 - accuracy: 0.7390 - val_loss: 0.8487 - val_accuracy: 0.7052\n",
      "Epoch 24/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6309 - accuracy: 0.7460 - val_loss: 0.8565 - val_accuracy: 0.7133\n",
      "Epoch 25/30\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.6125 - accuracy: 0.7497 - val_loss: 0.8414 - val_accuracy: 0.7078\n",
      "Epoch 26/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6054 - accuracy: 0.7553 - val_loss: 0.8801 - val_accuracy: 0.7094\n",
      "Epoch 27/30\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6024 - accuracy: 0.7564 - val_loss: 0.8724 - val_accuracy: 0.7157\n",
      "Epoch 28/30\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6039 - accuracy: 0.7565 - val_loss: 0.8608 - val_accuracy: 0.7194\n",
      "Epoch 29/30\n",
      "237/237 [==============================] - 7s 28ms/step - loss: 0.5948 - accuracy: 0.7607 - val_loss: 0.8837 - val_accuracy: 0.7141\n",
      "Epoch 30/30\n",
      "237/237 [==============================] - 7s 28ms/step - loss: 0.5993 - accuracy: 0.7560 - val_loss: 0.8486 - val_accuracy: 0.7099\n"
     ]
    }
   ],
   "source": [
    "history = model2.fit(X_train_c, y_train_c, batch_size= batch_size, epochs=epochs, validation_split=validation_split)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 427,
   "id": "f2a11cea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e2feeb9390>"
      ]
     },
     "execution_count": 427,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cvHlzJk+efNpjLBYLM2fOrPW5nfU8IiIix1PIcQF7vxw3DSMfPnw4F1544Ul/9/vvv2OxWFi1alW1nnP58uXcdtttzijP7qmnnqJ79+5VtmdkZFRroVYRERFHKOS4gLsX6vzrX//K3Llz2bNnT5Xfvffee3Tv3r3ai3DGxcUREhLirBJPq3Hjxm6blVpERBoOhRwXKO987K4RVsOGDSM+Pr7KkPuCggI+//xzRo4cybXXXktycjIhISF06dKFzz777LTPeeLlqm3btnHuuecSFBREx44dTzqM/x//+Adt27YlJCSEli1b8vjjj1NaWgqY0wE8/fTTrF27FovFgsVisdd74uWqdevWcf755xMcHExMTAy33XZbpVmux40bx8iRI3n55ZdJTEwkJiaGu+66y34uERERqGdrV3mEYUBpQbUOCbCWYCktpLSwBEJr0fnYPwQcWMncz8+PsWPHMm3aNJ544gn76udffvklJSUl3HLLLXz22Wf84x//ICIigtmzZ3PDDTfQsmVL+vXrd8bnt9lsXHnllcTGxrJ06VJycnIq9d8pFx4ezrRp00hKSmLdunXceuuthIeH8/DDDzN69GjWr1/PTz/9xK+//gpQaQ2ycgUFBVxyySWcddZZLF++nMzMTG655RbuvvvuSiFu3rx5JCYmMm/ePLZv387o0aPp3r07t9566xlfj4iINAwKOWdSWgAvJFXrkOhjt1p7NB0CQh3a9eabb+all15i/vz5DB48GDAvVV155ZU0adKEBx980L7vPffcw08//cSXX37pUMj59ddf2bRpE7t377avEfbCCy9U6Ufzz3/+036/efPmPPDAA3z++ec8/PDDBAcHExYWhp+fH40bNz7luT755BMKCwv58MMPCQ01X/uUKVMYPnw4//d//0dCQgIAjRo1YsqUKfj6+tK+fXsuu+wy/ve//ynkiIiInUKOl2jfvj0DBgzgvffeY/DgwezYsYNFixbxyy+/YLVaefHFF/n888/Zt28fxcXFFBcX20PEmWzatImmTZtWWgS1f//+Vfb76quvmDx5Mtu3bycvL4+ysjIiIiKq9To2bdpEt27dKtU2cOBAbDYbW7ZssYecTp064evra98nMTGRdevWVetcIiLi3RRyzsQ/xGxRqQbDMNiQnouBQfvG4fYh5TU6dzX89a9/5e677+aNN97g/fffp1mzZlxwwQW89NJLvPbaa0yePJkuXboQGhrKfffdR0lJiUPPe7JJDS0nXEZbunQp11xzDU8//TQXX3wxkZGRTJ8+nVdeeaVar8EwjCrPfbJz+vv7V/mdzVZ/huyLiIjrKeScicXi8CUj+yGAX5CNEquNEp9g/APc8zaPGjWKe++9l08//ZQPPviAW2+9FYvFwqJFixgxYgTXX389YPax2bZtGx06dHDoeTt27Ehqairp6ekkJZmX7n7//fdK+yxevJhmzZrx2GOP2bedONorICAAq9V6xnN98MEH5Ofn21tzFi9ejI+PD23btnWoXhEREdDoKpc5fnkHdwkLC2P06NE8+uijpKenM27cOABat27NnDlzWLJkCZs2beL2229n//79Dj/vhRdeSLt27Rg7dixr165l0aJFlcJM+TlSU1OZPn06O3bs4PXXX2fGjBmV9mnevDm7du1izZo1HDp0iOLi4irnuu666wgKCuLGG29k/fr1zJs3j3vuuYcbbrjBfqlKRETEEQo5LuKphTr/+te/cvToUS688EKaNm0KwOOPP07Pnj25+OKLGTRoEI0bN2bkyJEOP6ePjw8zZsyguLiYvn37csstt/D8889X2mfEiBHcf//93H333XTv3p0lS5bw+OOPV9rnqquu4pJLLmHw4MHExcWddBh7SEgIP//8M0eOHKFPnz5cffXVXHDBBUyZMqX6b4aIiDRoFqOBrSKZk5NDZGQk2dnZVTrFFhUVsWvXLlq0aEFQUFCtznMgp4gDOUVEhwaQ3Mg9k+rJqTnzz1ZERNzvdN/fp6KWHBfxVEuOiIiImBRyXMTfzUs7iIiISGUKOS5S3pJTajVOOgRbREREXEshx0X8fS1YsGAYBqVWhRwRERF3U8g5CWe0vFgsFvz9zMnr3DmMXE5OrWkiIg2PQs5xymfRLSio3oKcp6LOx3VH+Z/piTMli4iI99KMx8fx9fUlKiqKzMxMwJyz5VRLDDjCx1qKUVZKfqGFYF8FHU8wDIOCggIyMzOJioqqtN6ViIh4N4WcE5SvkF0edGojp6iUnMIy8gN9yQ0JqPXzSc1FRUWddvVzERHxPgo5J7BYLCQmJhIfH09paWmtnmvOxv28OG8z3ZOjeGV0OydVKNXl7++vFhwRkQZIIecUfH19a/3F2Dg6gn25VnwOFGiWXRERETdTx2MXSjm2nENGVhFlGmElIiLiVgo5LhQfHoi/r4Uym8H+nCJPlyMiItKgKOS4kI+PhSZRwQDsPVro4WpEREQaFoUcF0uJNi9ZKeSIiIi4l0KOiyU3Mlty0o44Z4JBERERcYxCjoslN1JLjoiIiCco5LhYeUvO3qNqyREREXEnhRwXU0uOiIiIZyjkuFjKsZacjOxCrUYuIiLiRgo5LhYXHkignw82A/Zna64cERERd1HIcTGLxUITjbASERFxO4UcN1C/HBEREfdTyHGDFI2wEhERcTuFHDcob8lJU0uOiIiI2yjkuIHmyhEREXE/hRw30PpVIiIi7qeQ4wblLTn7c4ooKdNcOSIiIu6gkOMGMaEBBPv7YhiQnqXWHBEREXdQyHEDi8VyXL8chRwRERF3UMhxE3U+FhERcS+FHDepGEaukCMiIuIOCjlukhKty1UiIiLupJDjJlraQURExL0UctwkWYt0ioiIuJVCjpukHGvJycwtpqjU6uFqREREvJ9CjptEhfgTGuALaK4cERERd1DIcRNzrhwt1CkiIuIuCjluVDHCSv1yREREXE0hx400wkpERMR9PBpyFi5cyPDhw0lKSsJisTBz5kyHj128eDF+fn50797dZfU5m0ZYiYiIuI9HQ05+fj7dunVjypQp1TouOzubsWPHcsEFF7ioMtfQ+lUiIiLu4+fJkw8dOpShQ4dW+7jbb7+dMWPG4OvrW63WH0/T5SoRERH3qXd9ct5//3127NjBk08+6elSqq18rpxDecUUlmiuHBEREVfyaEtOdW3bto1HHnmERYsW4efnWOnFxcUUFxfbH+fk5LiqvDOKCPYjPNCP3OIy9mUV0Do+3GO1iIiIeLt605JjtVoZM2YMTz/9NG3btnX4uIkTJxIZGWm/paSkuLDK07NYLCRHa64cERERd6g3ISc3N5cVK1Zw99134+fnh5+fH8888wxr167Fz8+PuXPnnvS4CRMmkJ2dbb+lpaW5ufLK7J2PNcJKRETEperN5aqIiAjWrVtXadvUqVOZO3cuX331FS1atDjpcYGBgQQGBrqjRIdohJWIiIh7eDTk5OXlsX37dvvjXbt2sWbNGqKjo2natCkTJkxg3759fPjhh/j4+NC5c+dKx8fHxxMUFFRle12WohFWIiIibuHRkLNixQoGDx5sfzx+/HgAbrzxRqZNm0ZGRgapqameKs8lKlpydLlKRETElSyGYRieLsKdcnJyiIyMJDs7m4iICLeff2N6Dpe+vojo0ABWPT7E7ecXERGpj2ry/V1vOh57i+Rji3QeyS8hv7jMw9WIiIh4L4UcN4sI8icy2B+AfVnqlyMiIuIqCjkeoIU6RUREXE8hxwM0wkpERMT1FHI8QCOsREREXE8hxwMqLlepJUdERMRVFHI8IOXY+lV7s9SSIyIi4ioKOR6QrD45IiIiLqeQ4wHll6uyCkrJLSr1cDUiIiLeSSHHA0ID/YgODQDUmiMiIuIqCjkeotXIRUREXEshx0M0IaCIiIhrKeR4iCYEFBERcS2FHA/RhIAiIiKupZDjIeXDyNPUkiMiIuISCjkekhKtlhwRERFXUsjxkCZRZktOblEZ2YWaK0dERMTZFHI8JDjAl9gwc64cjbASERFxPoUcD9LyDiIiIq6jkONBGmElIiLiOgo5HqSWHBEREddRyPEgjbASERFxHYUcD1JLjoiIiOso5HjQ8Yt0Gobh4WpERES8i0KOBzWJMkNOXnEZWQWaK0dERMSZFHI8KMjfl/jwQECXrERERJxNIcfDNIxcRETENRRyPKxioU6FHBEREWdSyPGwimHkulwlIiLiTAo5HqZh5CIiIq6hkONh5X1ytEiniIiIcynkeFjKcS05mitHRETEeRRyPCwxKgiLBQpLrRzJL/F0OSIiIl5DIcdZctJh9gPw9S3VOizQz5eE8CAA0tQvR0RExGkUcpzF4gPL34F1X0Fp9cKKFuoUERFxPoUcZwlLgOBowICDm6t1qEZYiYiIOJ9CjrNYLJDQybx/YGO1DtUIKxEREedTyHGm+I7mz8zqhZwUteSIiIg4nUKOM8V3MH9WM+Ro/SoRERHnU8hxphpfrtJcOSIiIs6mkONM5S05efuh4IjDhyVGBeFjgeIyGwfzil1UnIiISMOikONMgeEQ1dS8X41LVv6+PiRGaqFOERERZ1LIcbbyzsfVvGTVpJFCjoiIiDMp5DibfYTVhmodVj7CSsPIRUREnEMhx9lq2Pm4TUIYAKv2HHV2RSIiIg2SQo6z2VtyNkE1Rkqd2yYOgCU7DlNcZnVFZSIiIg2KQo6zxbQGHz8oyYXsNIcP65AYTnx4IIWlVpbvUmuOiIhIbSnkOJtfAMS2Ne9X45KVxWLhvLZma86CrZmuqExERKRBUchxhRp2Ph7ULh6A+VsOOrsiERGRBkchxxUSjuuXUw1nt47FxwLbMvPYl6Wh5CIiIrWhkOMKNZwrJzLEn55NGwGwQK05IiIitaKQ4wrlIefQVrCWVuvQ8n4587eoX46IiEhtKOS4QlRTCAgHWykc2latQ8v75SzZcZiSMpsrqhMREWkQFHJcwWKpWKyzGmtYAXRKiiA2LIC84jJWamJAERGRGlPIcRV75+PqhRwfH4t9YsAFW9UvR0REpKY8GnIWLlzI8OHDSUpKwmKxMHPmzNPu/8033zBkyBDi4uKIiIigf//+/Pzzz+4ptrpq2PkY4Lx26pcjIiJSWx4NOfn5+XTr1o0pU6Y4tP/ChQsZMmQIP/zwAytXrmTw4MEMHz6c1atXu7jSGqjhXDkA57SJw2KBzftzOZBT5OTCREREGgY/T5586NChDB061OH9J0+eXOnxCy+8wLfffst3331Hjx49nFxdLZUv1JmVCsW5EBju8KHRoQF0TY5ibVoWC7YcZFSfFBcVKSIi4r3qdZ8cm81Gbm4u0dHRp9ynuLiYnJycSje3CImGsMbm/czN1T58UPlQci3xICIiUiP1OuS88sor5OfnM2rUqFPuM3HiRCIjI+23lBQ3torYR1hV/5LVoGP9chZtO0SZVUPJRUREqqvehpzPPvuMp556is8//5z4+PhT7jdhwgSys7Ptt7Q0x1cGr7XyS1Y16HzcNTmKRiH+5BaVsToty7l1iYiINAD1MuR8/vnn/PWvf+WLL77gwgsvPO2+gYGBREREVLq5TXzNhpED+PpYOKd8KLmWeBAREam2ehdyPvvsM8aNG8enn37KZZdd5ulyTu/4uXIMo9qHn6d+OSIiIjXm0dFVeXl5bN++3f54165drFmzhujoaJo2bcqECRPYt28fH374IWAGnLFjx/Kvf/2Ls846i/379wMQHBxMZGSkR17DacW2AyxQcBjyMiE8oVqHn3ss5Kzfl8PB3GLiwgNdUKSIiIh38mhLzooVK+jRo4d9+Pf48ePp0aMHTzzxBAAZGRmkpqba93/77bcpKyvjrrvuIjEx0X679957PVL/GQWEQHRL834NOh/HhQfSuYl5eW2hZj8WERGpFo+25AwaNAjjNJdxpk2bVunx/PnzXVuQKyR0hCM7IHMTtDq/2ocPahvP+n05LNh6kKt6JbugQBEREe9U7/rk1DvxNR9hBRVLPCzcdhCrrfr9ekRERBoqhRxXq8VcOQA9UqIID/Ijq6CUtXuznFeXiIiIl1PIcbXyuXIyN4Ot+pP6+fn6cE6bWEBDyUVERKpDIcfVoluCXxCUFcLRXTV6ikFtzckO56vzsYiIiMMUclzNxxfi2pn3azApIFQMJf9zbxZH8kucVZmIiIhXU8hxh/KZj2vY+bhxZBDtG4djGLBom1pzREREHKGQ4w61WN6h3KB25iUr9csRERFxjEKOOyTUPuSUL/GwYOtBbBpKLiIickYKOe5QPlfO4R1QWlSjp+jVrBFhgX4czi9hQ3qOE4sTERHxTgo57hDeGIKiwLDCoS01eooAPx8GtIoBYP4WLdgpIiJyJgo57mCxHDdfzqYaP015vxwNJRcRETkzhRx3sY+wqtnMx1CxxMPq1KNkF5Q6oyoRERGvpZDjLk7ofNwkKpg28WHYDFi0Xa05IiIip1OjkPPBBx8we/Zs++OHH36YqKgoBgwYwJ49e5xWnFep5Vw55eyjrDSUXERE5LRqFHJeeOEFgoODAfj999+ZMmUKkyZNIjY2lvvvv9+pBXqN8oU6c9Oh8GiNn8Y+X87WgxiGhpKLiIicSo1CTlpaGq1btwZg5syZXH311dx2221MnDiRRYsWObVArxEUCZEp5v1adD7u06IRwf6+ZOYWsykj10nFiYiIeJ8ahZywsDAOHz4MwC+//MKFF14IQFBQEIWFhc6rzts4ofNxoJ9vxVDyrRpKLiIicio1CjlDhgzhlltu4ZZbbmHr1q1cdtllAGzYsIHmzZs7sz7vUn7Jqhadj6FilNV89csRERE5pRqFnDfeeIP+/ftz8OBBvv76a2JizJaFlStXcu211zq1QK/ihLlyAAa1NfvlrNpzlJwiDSUXERE5Gb+aHBQVFcWUKVOqbH/66adrXZBXO36ElWGYkwTWQNOYEFrGhrLzUD5Lth/iks6JTixSRETEO9SoJeenn37it99+sz9+44036N69O2PGjOHo0ZqPHPJ6sW3Bxw+KsyFnX62e6tzjFuwUERGRqmoUch566CFycsxFItetW8cDDzzApZdeys6dOxk/frxTC/QqfgEQY45Kq+18OYOO65ejoeQiIiJV1Sjk7Nq1i44dzUsvX3/9NcOGDeOFF15g6tSp/Pjjj04t0OvE137mY4CzWsYQ6OdDRnYR2zLznFCYiIiId6lRyAkICKCgoACAX3/9lYsuugiA6OhoewuPnIITlncACPL35ayWWpVcRETkVGoUcs4++2zGjx/Ps88+y7Jly+xDyLdu3UpycrJTC/Q68cdGWNXychUct8SD+uWIiIhUUaOQM2XKFPz8/Pjqq6948803adKkCQA//vgjl1xyiVML9Drlc+Uc2gLW2g3/Lu+Xs3zXUfKLy2pbmYiIiFep0RDypk2b8v3331fZ/tprr9W6IK8X1Qz8Q6E0H47shLh2NX6qFrGhpEQHk3akkCU7DjOkY4ITCxUREanfahRyAKxWKzNnzmTTpk1YLBY6dOjAiBEj8PX1dWZ93sfHx2zN2bfCXN6hFiHHYrEwqG08Hy3dw4KtmQo5IiIix6lRyNm+fTuXXnop+/bto127dhiGwdatW0lJSWH27Nm0atXK2XV6l4SOZsjJ3AhcWaunOq9tHB8t3WMfSm6p4QSDIiIi3qZGfXL+/ve/06pVK9LS0li1ahWrV68mNTWVFi1a8Pe//93ZNXqf42c+rqX+rWII8PVh79FCdh7Kr/XziYiIeIsateQsWLCApUuXEh0dbd8WExPDiy++yMCBA51WnNdy0lw5AKGBfvRp0YjF2w8zf8tBWsWF1fo5RUREvEGNWnICAwPJzc2tsj0vL4+AgIBaF+X1yhfqPLobSmrf+lK+YKeGkouIiFSoUcgZNmwYt912G3/88QeGYWAYBkuXLuWOO+7g8ssvd3aN3ic0FkLjAQMyN9f66cqHki/deZjDecW1fj4RERFvUKOQ8/rrr9OqVSv69+9PUFAQQUFBDBgwgNatWzN58mQnl+ilyufLydxQ66dqHR9Gx8QISspsPDd7U62fT0RExBvUqE9OVFQU3377Ldu3b2fTpk0YhkHHjh1p3bq1s+vzXgmdYNcCyKx9KLFYLDx/RWeufHMJM1bvY2SPJvbZkEVERBoqh0POmVYXnz9/vv3+q6++WuOCGgz7CKvat+QA9GjaiBv7N2fakt08NmMdv9x/LiEBNZ4GSUREpN5z+Ftw9erVDu2neVoc5KSFOo/34MXt+GXDfvYeLWTyr9t49NIOTntuERGR+sbhkDNv3jxX1tHwxLUHLJB/EPIOQljtLy+FBfrx3BWduXnaCt5ZtJPLuyXRuUlk7WsVERGph2rU8VicICAUGjU37zuxNef89glc1jURmwH/+PpPyqw2pz23iIhIfaKQ40nl8+U4MeQAPDm8IxFBfmxIz+G9xbuc+twiIiL1hUKOJzm587H9acODeOwysz/Oq3O2knakwKnPLyIiUh8o5HiSfa4c589tM6p3Cme1jKao1MajM9ZhGIbTzyEiIlKXKeR4kv1y1SawObfvjMVi4YUruhDg58OibYeYuWafU59fRESkrlPI8aToVuAbCKX5kLXH6U/fMi6Mv59vTtD47PebOJJf4vRziIiI1FUKOZ7k6wdxbc37Tu58XO62c1vRLiGcI/klPPe9a84hIiJSFynkeFq88ycFPF6Anw8vXtUFiwW+Wb2PhVqpXEREGgiFHE+zj7ByXStL+ZIPAI/NXEdhidVl5xIREakrFHI8zUVz5ZzowYvbkRgZRNqRQib/utWl5xIREakLFHI8rbwl59A2KCt22WnCAv14dkRnAN75bRfr92W77FwiIiJ1gUKOp0UkQVAkGFYz6LjQhR0TuKxLIlabwSPfaMkHERHxbgo5nmaxuLzz8fGevNxc8mH9vhzeX7zb5ecTERHxFIWcusBFyzuc9FThQTx6qZZ8EBER76eQUxckuK8lB8wlH/q2iKaw1MpjM9dryQcREfFKCjl1Qfxxyzu4gY+PhYlXmks+LNx6kG/XpLvlvCIiIu7k0ZCzcOFChg8fTlJSEhaLhZkzZ57xmAULFtCrVy+CgoJo2bIlb731lusLdbX49ubP7DQocs+op1ZxYdwz2Fzy4ZnvN2rJBxER8ToeDTn5+fl069aNKVOmOLT/rl27uPTSSznnnHNYvXo1jz76KH//+9/5+uuvXVypiwU3gogm5n03teYA3H7ecUs+zNaSDyIi4l38PHnyoUOHMnToUIf3f+utt2jatCmTJ08GoEOHDqxYsYKXX36Zq666ykVVukl8R8jZZ3Y+bnqWW04Z4OfDC1d24eq3lvDNqn1c0aMJ57SJc8u5RUREXK1e9cn5/fffueiiiyptu/jii1mxYgWlpaUnPaa4uJicnJxKtzopqbv5c9l/XTop4Il6NWvEDWc1A+CRr9eRU3Ty91FERKS+qVchZ//+/SQkJFTalpCQQFlZGYcOHTrpMRMnTiQyMtJ+S0lJcUep1dfvDgiNg4ObYN4Lbj31w5e0JyU6mH1ZhTz7nS5biYiId6hXIQfAYrFUelw+/PnE7eUmTJhAdna2/ZaWlubyGmskNBaGTTbvL3kd0pa57dRhgX688pfuWCzw5cq9/LrxgNvOLSIi4ir1KuQ0btyY/fv3V9qWmZmJn58fMTExJz0mMDCQiIiISrc6q8Mw6DoaDBvMuANK3DdRX98W0dx6TksAHvnmTw7nue+SmYiIiCvUq5DTv39/5syZU2nbL7/8Qu/evfH39/dQVU429P8gPBGO7ID/PePWU48f0pa2CWEcyivhn5okUERE6jmPhpy8vDzWrFnDmjVrAHOI+Jo1a0hNTQXMS01jx46173/HHXewZ88exo8fz6ZNm3jvvfd49913efDBBz1RvmsEN4LLjw2p/+NN2P2b204d5O/Lq6O64+dj4cf1+zVJoIiI1GseDTkrVqygR48e9OjRA4Dx48fTo0cPnnjiCQAyMjLsgQegRYsW/PDDD8yfP5/u3bvz7LPP8vrrr9f/4eMnanMh9DwW7mbeCcW5bjt15yaR3HN+GwCe+HY9GdmFbju3iIiIM1mMBnZNIicnh8jISLKzs+t2/5yiHHhzIGSnQq+bYPhkt5261Grj6jeXsHZvNue0ieXDm/uesmO3iIiIO9Tk+7te9clpUIIiYOQb5v2V78P2/7nt1P6+PrwyqjuBfj4s2naIj/9IPfNBIiIidYxCTl3W4lzoe5t5f9Y9UJjltlO3jg/j4UvMNbVemL2J3Yfy3XZuERERZ1DIqesufAqiW5pLPvw0wa2nvmlAc85qGU1hqZUHvlyL1dagrmyKiEg9p5BT1wWEwsg3AQus/RQ2/+C2U/v4WHj5L90IC/Rj5Z6j/GfhTredW0REpLYUcuqDpmfBgLvN+9/dCwVH3Hbq5EYhPDGsIwCvzdnK5v11dO0vERGREyjk1BeD/wmx7SA/E2Y/4NZT/6V3Mhe0j6fEauP+z9dSUmZz6/lFRERqQiGnvvAPgiveAosvbPgGNsxw26ktFgsTr+pCoxB/NmXk8Pr/trnt3CIiIjWlkFOfNOkJ54w3738/HvIy3Xbq+PAgnr+iCwBT529nVepRt51bRESkJhRy6ptzH4aELlB4BL6/H9w4l+OlXRIZ0T0JmwEPfrGWwhKr284tIiJSXQo59Y1fgHnZyscfNn8Pf37u1tM/c3lnEiIC2Xkon//7abNbzy0iIlIdCjn1UePOMOgR8/4PD0OO+xbSjAzxZ9LV3QCYtmQ3i7cfctu5RUREqkMhp74aeB806QXF2eZsyG68bHVe2ziu69cUgIe+XEtOUanbzi0iIuIohZz6ytfPnCTQNxC2/wqrPnDr6R+9tANNo0NIzy7i6Vkb3XpuERERRyjk1Gdx7eCCJ8z7Pz8GR/e47dShgX68OqobFgt8vWovP2/Y77Zzi4iIOEIhp74762/QtD+U5MG3d7n1slXv5tHcdm5LACZ8s46Ve9w3E7OIiMiZKOTUdz6+MHIq+IfA7kWwxX1rWwGMH9KWjokRHMkvYdTbS3n9f9u0kKeIiNQJCjneILql2aIDMPd5sLlv2YVAP1+m334WI7onYbUZvDpnK9f+Zyn7sgrdVoOIiMjJKOR4iwH3QGAkZG6Aje5b8gEgIsiff13Tg9dGdyM0wJdlu48wdPJCfliX4dY6REREjqeQ4y2CG1WsVD7vBbCWub2EK3ok88O959AtJYqcojLu/GQVj3z9JwUl7q9FREREIceb9LsDgqPh8Ha3z4RcrllMKF/d0Z+7BrfCYoHpy9MY9vpvrN+X7ZF6RESk4VLI8SZBEXD2feb9BS9CWYlHyvD39eGhi9vzyS39aBwRxM5D+VwxdTHvLNqJTZ2SRUTETRRyvE2fWyEsAbJSYfVHHi1lQKtYfrz3HC7qmECp1eC52Zu48f1lZOYWebQuERFpGBRyvE1ACJzzoHl/4UtQ6tlRTo1CA3j7hl48f0Vngvx9WLTtEEMnL2Le5kyP1iUiIt5PIccb9boRIpIhNwNWvO/parBYLFzXrxnf3X027RuHczi/hJumLeepWRsoKrV6ujwREfFSCjneyC8QznvYvP/bq1Cc59l6jmmTEM7MuwZy08DmgLmK+cg3FrPtQK5nCxMREa+kkOOtuo+BRi0g/yAs+4+nq7EL8vflyeGdeH9cH2JCA9i8P5dh//6NL5anebo0ERHxMgo53srXHwZNMO8v/hcU1a0h3IPbx/PjfedwTptYistsPPz1nzz7/UbKrO6brVlERLybQo4363I1xLaDoiz4faqnq6kiPjyID27qy/0XtgXg3d928dcPVpBTVOrhykRExBso5HgzH18Y/Kh5//c3oKDurRLu42Ph3gvbMPW6ngT5+7Bg60GueGMxuw/le7o0ERGp5xRyvF2Hy6FxFyjJhcWTPV3NKV3aJZGv7hhAYmQQOw7mM+KNxSzZfsjTZYmISD2mkOPtfHxg8D/N+3/8B3IPeLae0+jcJJJv7xpI95QosgtLGfveMj5eusfTZYmINByGAdvmwMKXoTDL09XUmkJOQ9D2YmjSG8oKzSHldVh8RBDTbzuLkd2TKLMZ/HPmep74dj2l6pAsIvWJtcwMC9v/B9l7zfBQl9lssGEmvH0ufHI1zH0W3joH0pZ7urJasRhGXX/nnSsnJ4fIyEiys7OJiIjwdDnus2MefDQSfAPg76shMtnTFZ2WYRi8uWAHL/28BcOAga1jmDqmF5Eh/p4uTUTk9AqOwJc3wq6FFdsCwiC2LcS1q/gZ1x6imoGvn+dqtZbB+q9g0atwaIu5zT8UgqMgZx9YfOGCx2HAveaVAQ+qyfe3Qk5DYRgwbRjs+Q16jYPh//J0RQ75ZcN+7vt8DQUlVlrEhvLfsb1pHR/m6bJERE7uwEaYfi0c3W2GhcgmcHgHGKeY3d03AGJaHws+7SGurTkqNqY1+Ae5rs6yYljzqdlX8+huc1tQJPS9Hc76mzlw5bv7YMM35u9anQ9XvA1h8a6r6QwUchzQYEMOwJ4l8P5Q8PGDu5dDdEtPV+SQTRk53PLBCvZlFRIe5McbY3pybts4T5clIlLZpu/gm9uhNN9sobn2M0joBGUlcGSn2VJycOuxn5vh0HazG8HJWHwguhU06w/NzobmA53TAl9SACunwZJ/Q266uS0kFvrfBX1ugaDjvhcNA1Z9CD/+w6wzLAGu/A+0HFT7OmpAIccBDTrkAHx0Jez4H3S7Fq54y9PVOOxQXjF3fLSSFXuO4mOBx4d1ZNyA5lgsFk+XJiINnc0GCyfB/Inm4xbnwl8+gJDoMx+XnVo5+JTfP9kErlHNoPnZ0GwANBsIjZqDo/8GFuXA8v+ac6YVHBu5Gp4EA/8OPW80F3c+lcxN8OVNcHATYIFzHjAnm3XzZTaFHAc0+JCzbxX8d7D5v4Q7l5rXheuJ4jIrj81Yz1cr9wJwbd8Unr68MwF+6j8vIh5SnAcz7zBbcQD6/Q0ueq52AcAwIC8T0lebXQx2L4aMtVUveUU0McNO84Fma09Mq6qhp+AILH0T/ngbio8Fp6hmcPb95vI/foGO1VRSAD9PMFuBAFLOgqvegaiUmr/OalLIcUCDDzkA06+Dzd9DpyvgL9M8XU21GIbBO4t28cKPmzAM6Ncimjev70V0aICnSxORhubILpg+BjI3mn1rhr0GPa53zbmKcyH1DzP07Fli/ofVdsLs8GEJFa08ST1g40xY/p55+QzMvj7nPACdr6p5CFv/tdlXpzgHgqJg5FRof1ktXpjjFHIcoJADHNgAbw4EDLh9ESR29XRF1TZvcyb3fLaavOIyUqKDmXRVN/q3ivF0WSLSUOxcYI6gKjxqhovRH0NKX/edv6QA9i4zW3n2LIa9K8BafPJ9G3eFcx+E9sOdM0LqyC746mZIX2U+7ns7XPSs461CNaSQ4wCFnGO+utlM5G2Hwpjpnq6mRrYeyOWWD1aQeqQAgCt7NuGxSzsQE+bav2giUoeVFsKhbXDwWB+X7DRI6mm2Njjj0ophwLL/wE8TzMtHST3hmk8gIqn2z10bpUWwb0VF6ElfbXZ6Pns8tBnieN8dR5WVwNxnzA7MYAapq9+H2NbOPc9xFHIcoJBzzKFt8EZfMGxwy/8gubenK6qR7MJSXvp5M5/8kYphQFSIPxOGtucvvVLw8VGnZBGvVZIPh7ZWhJnyn0d3m/+unUxid+gwzFzupib9EcuKYfZ4WP2x+bjrNeZ0HK4c6l3Xbf3F7JNUcNicC+iyV6HbaJecSiHHAQo5x5l5J6z5BFoOhrEzPV1NraxOPcqjM9azKSMHgD7NG/H8FV1omxDu4cpEpFaKc80RRwc3V75lpZ76mKAoiO9gBpmwxuakfKm/A8d93cW0MQNP++Fm/5UzXcbJ3Q+fXw97l5sDN4Y8aw671ghPyEmHb26D3YvMx93GwKUvQaBz5zRTyHGAQs5xju6Gf/cCWxmMm20OTazHyqw2pi3ZzatztlJQYsXPx8Jt57bknvPbEBzg6+nyROR08g9XHkZ9cLPZUpOz79THhMSaE+jFtz82kd6xWYRD46qGj7yDsOUHcxTUrgVgLan4XXiSeTmrwzCz067vCTOr71sJ068355UJioSr34PWFzrvtXsDm9Vc72rBi2ZLWkwbGPc9hDd22ikUchygkHOC7++HFe9B0wFw0w9e8b+SfVmFPDVrA3M2mouRpkQH8+yIzgxq57mZOkUEsz9LbkbVIHNwS8XcLScTlnAsxBwXZOLaQWhszeooyoFtv5ijTLfNgZK8it8FNzL7KnYYZs7yu3EWzLrH7NQb286c4C+mVc3O2xDs/g2+vtX887n+G6cuBaGQ4wCFnBNk74PXe5h/gUd/DB2Ge7oip/llw36emrWB9OwiAC7rmsgTwzqSENGAr5+LuNuhbbDkdXO5g0NbzaHHpxLV1AwSce0qwkxsGzN4uEppEeycD5u/gy0/mn1LyvkFV8xI3HaoOdtvkL43zij/sNmaE+bcmekVchygkHMSP02ApVMBC/S+GS580myS9QL5xWW8Nmcr7y/ZjdVmEB7ox4MXt+P6s5rhq47JIq6VuhQ+HQ1FWRXbLL7mkjLlQaY81MS2gYBQj5UKmItVpi2FTd+brTzZaeb2cx6EwY95fIHKhk4hxwEKOSdRkg+zH4S1n5qPwxJg6P9Bx5FecfkKYEN6No/OWM/atCwAuiVH8vwVXejcxDvCnEids/kH+OomKCuC5D7Q/24zzES3Ar96MHmnYVTMMtykl6erERRyHKKQcxq7FpozWR7ZYT5ucxFc+jI0aubRspzFajP4dFkqk37aTG5RGT4WGDegBfcPaUN4kP+Zn0BEHLPyA/j+PvOSRZuLzZnVT7c2kogDFHIcoJBzBqVF8NursOhVc8pw/xAY9AicdWfVEQf1VGZuEc9+v4nv1por8IYF+nFVzyZcf1Yz2mjIuUjNGYY5wmbec+bj7tfD8Mle82+HeJZCjgMUchx0cKv5P7E9i83HCZ3NSa/q6aSBJ7Ng60Ge+W4DOw7m27f1bRHNDWc14+JOjbXwp0h12Kzw48Ow/B3z8TkPwPmPe80lb/E8hRwHKORUg2GYkwX+8k9zfRYs0OcWuOBxr+mYbLMZLNlxmI+X7mHOpgNYbeZfh9iwQEb3SWZMv2Y0iQr2cJUidVxpEXxzK2yaBVjMPn39bvd0VeJlFHIcoJBTA/mHzKCz9jPzcVjjYx2TR3jV/9L2Zxfx2bJUPluWSmauudCdjwXObx/P9Wc149w2cVoqQuRERdnw2RhzdWzfALjibeh8paerEi+kkOMAhZxa2LnAnDzQ3jH5YrjsZXNuCy9SarXx68YDfPzHHhZvr5gzo2l0CGP6NWVU7xSiQ+vB6BCRcvmHzYn3mvQEfye2TOZkwCdXw4H1EBAO134KLc513vOLHEchxwEKObVUWgSLXoHfXqvomDz4Uej3N/D183R1TrfjYB6fLE3lq5Vp5BSVARDg58NlXRK5/qxm9GwahcWLWrPEy+xdCcv/C+u/MSf8DIwwW2C7j4Gm/WvXEntoG3x0JWSnmtNOXPcVJHZ1Xu0iJ1DIcYBCjpMc3GION09dYj6ObgUtB0FKP0jpC42ae9WlrMISK9+tTefjP/bw595s+/a2CWH0aR5Np6RIOjeJoG1COEH+WidLPKi0CDZ8A8v+A+mrK7YHRZqXlspFNYNu10K3ayC6RfXOsXcFfPIXKDxi/t2/4Rvz77yIC9XLkDN16lReeuklMjIy6NSpE5MnT+acc8455f6ffPIJkyZNYtu2bURGRnLJJZfw8ssvExMT49D5FHKcyGaDNR/DL49XntEUzAXyygNPcl9I6u7cZnIPWpuWxcdL9zBrbTrFZbZKv/PzsdA6PsweejolRdIxKYKwQO9r5ZI65ugeWPEurPrIDB8AvoFm/5g+t5orbacuMfvWbfgWSnIrjm3a3ww8nUaeeVDBtjnwxVgoLYCknnDdlzVfQ0qkGupdyPn888+54YYbmDp1KgMHDuTtt9/mnXfeYePGjTRtWrWfx2+//cZ5553Ha6+9xvDhw9m3bx933HEHbdq0YcaMGQ6dUyHHBQqPmv110pZB2h/mLKG20sr7+PibTdnHB5/IJp6p10myCkpYuO0QG9Kz2Ziew/p92RwtKK2yn8UCzWNC6ZQUUSn8qF+P1JrNBjvnwbL/wtafgGP/nEemmEu09Bx78gBSUgCbZ5uznO+YV3GcX5C5Gne3MWbL7ImXoNd8Ct/ebc4C3OoCGPUhBIa58AWKVKh3Iadfv3707NmTN998076tQ4cOjBw5kokTJ1bZ/+WXX+bNN99kx44d9m3//ve/mTRpEmlpaQ6dUyHHDUqLIGNNRehJWwb5mVX3i0iGlD5m8Ol8tdMXc3M3wzDIyC5i/b5sNqTnsCHd/JlxbIHQEyVGBnFlzyY8MKSdRm1J9RRmmYFj+TsVAwEAWg6GvrdC20vAx8HLpjnp8OcXZgvPwc0V28MaQ9e/mIEnvgMsngy/PmX+rus1MGKKJvkTt6pXIaekpISQkBC+/PJLrrjiCvv2e++9lzVr1rBgwYIqxyxZsoTBgwczY8YMhg4dSmZmJqNGjaJDhw689dZbJz1PcXExxcXF9sc5OTmkpKQo5LiTYUDWnmOh51jwObDenPK9XGi8+b/CZv09V6eLHM4rPhZ6clh/rNVn16GKCQiv7pXM/13VVQuGypntX292JP7zC/NyEZidibuPMeewim1T8+c2DLMPz9rpsO7LikteYPa3ObrbvD/g73Dh01qsUtyuXoWc9PR0mjRpwuLFixkwYIB9+wsvvMAHH3zAli1bTnrcV199xU033URRURFlZWVcfvnlfPXVV/j7n/x/FE899RRPP/10le0KOR5WnAfpq8zA8+eXcGgL+PjBJS+a/1h7Uaflk8ktKmX2nxk8NnM9VpvBFT2a8NLVXfHz1ReHnMAwYOd8WPhSxQzkAPEdzb8rXUc7/5JRWQls+8Vs3dn6c8Xl54tfgP53OfdcIg6qlyFnyZIl9O9f8b/3559/no8++ojNmzdXOWbjxo1ceOGF3H///Vx88cVkZGTw0EMP0adPH959992TnkctOfVASb55nX/DN+bj7tfDZa+Af5Bn63KD2X9mcO/01ZTZDIZ3S+K1Ud0UdMRUHm7mvwhpS81tFl/oMNy8JNVsoHv+M5B/GDZ/Z86H1ep8159P5BRqEnI8NuQjNjYWX19f9u/fX2l7ZmYmCQkJJz1m4sSJDBw4kIceegiArl27EhoayjnnnMNzzz1HYmJilWMCAwMJDAx0/gsQ5wkIhavfM0d//PqkOWIrcwOM/hgikz1dnUtd1jURXx8L93y2iu/WplNmtfH6tT3wV9CpmwzD9cHiZOHGNxB632ReKnJ3h/3QGOg1zr3nFHESj/1LGhAQQK9evZgzZ06l7XPmzKl0+ep4BQUF+JxwHdjX1+xc18Cm+/E+FgsM/Dtc/w0ER5t9A94+D3Yt8nRlLndJ58a8dX0vAnx9+HH9fu78ZBXFZVZPl9WwFWWbc8Gs+RTmPGkuW/DvXvBsLLzRD+Y+Bxl/moHEWQzDHOn03iXw0Ugz4PgGQr874N615lIq9XxEooi71Ykh5G+99Rb9+/fnP//5D//973/ZsGEDzZo1Y8KECezbt48PP/wQgGnTpnHrrbfy+uuv2y9X3Xffffj4+PDHH384dE6NrqoHju6Bz6+D/evM5vmLnzf/offyfjrzt2Ry20crKSmzcX77eKZe11MTC7qSYZgjiw5trbgd3GLO5Ju3/8zHgzmhXofh5izCTXrXrDPu6VpuBt4HEVVbqEUaonrVJ6fc1KlTmTRpEhkZGXTu3JnXXnuNc8811z4ZN24cu3fvZv78+fb9//3vf/PWW2+xa9cuoqKiOP/88/m///s/mjRx7H84Cjn1REkBfHcvrPvCfNxlFAz/FwSEeLYuF/tt2yFu+XA5RaU2zmkTy3/H9lbQcRabDTbOgK2/mB3dD22DkrxT7x+eaI5Wim0HsW0hrq3ZL2XvCtj4LWz/H5QVVuwf1hg6DIMOl5v9Zc60zInCjUi11MuQ424KOfWIYcAfb8HPj5mTjzXuAqM/gUbNPF2ZS/2+4zB//WA5BSVWBraO4Z2xfQgOUNCpMcOA7b/Cr0/DgXWVf2fxheiWFSEmtu2xUNP6zDP/luSbQWfTLHMEUnFOxe+Co6HdpdDxcnNSPb/j+gUq3IjUiEKOAxRy6qFdi+DLcVBwyPzyuPo9aDXY01W51PLdRxj33jLyS6z0axHNe+P6EKqlIaov9Q/439MVQ68DI6DPX83lCOLaQaMW4OeEmafLimHXQrOFZ8sPUFCxej0B4dD2IrOFJyDMHAqucCNSbQo5DlDIqaey98Ln15sdki0+cOFT5kgTL+6ns3LPUca9t4zc4jJ6N2vE+zf1ITxIM8w65MBGmPusGTjgWAfe2+Ds8RAS7dpzW8sg9XezhWfTd5CbUXUfhRuRalPIcYBCTj1WWgSzx8OaT8zHna6AEW+YQ9C91Nq0LG549w9yisro0TSKaTf1JTK4FkHHMCD/EBzdZa45VlZktkLYfxafZNtJfoLZ/6T7dXVr4dWje2D+RHPWXgwzEPe4Hs77h2emI7DZYN/KY4FnFuQdhJ43KNyI1IBCjgMUcuo5wzDX6/npEbCVQXwnuOZjc0HCsmKwlpi3smKwloL12LaykpPcLzUf+4dASIz5P/yQGPOSWB2aiHD9vmyuf/cPsgpK6ZocyYc39yUq5DSXWKxlkLMXjuwyw4z9527z5+k621ZXaJw58q3PLRAc5bznra68g7DoZVj+bsXsvB1HwOB/mn1t6oLyf2q9uPVRxJUUchygkOMl9vwOX4w9+cKfzuAfelzwORZ+ygOQ/XE0hCeZI3Bc/MW1MT2H69/9gyP5JXRMjOCTv/ahUcEuOLKzapjJSjUD4ClZIKKJuSCqX7DZKdZ+Czr5T98TtuVnwh//gexU8ykDwszLL2fd5d4WiqIc+H0KLJkCpcfWA2s5CC54Apr0cl8dIuJyCjkOUMjxIjnp8OVNFZ047SwVX8y+/sfuB5g3v2M/fQPN+z7+5kKHBYeP3Y6YI7mqo1ELs9Wg4whz1mYXBZ4t6Vm88u40BhQvZpj/CmKNI6fe2TfQHIXWqAVEt6j8M6qpc1qqrKWwYQb8NtmcoRrM97braBh4b+0WizyT0iJY8S4sfLliIcmkHnDBk17fKV2koVLIcYBCjpcp72Pi41sRbHx8ax40bDZzKHB54Ck8UjkAHX+/8Ii5MnN5HxUwA0THEdDxCmjSs/aBx1oGe34zR+1s+g7yD9p/VUgQ+REtMaKaExjfirDENvhEtzTDTHiS+1aJNgzYNgd+ew1SlxzbaDH77Ay8H5Kd1KJiGJCdBjvmwoKXzEtyADFt4ILHzdFLuhQk4rUUchygkCNOVZxnrta8caY5ydzxk8NFphwLPCMhubfjX8DWUti14Fiw+b6ipQIgKIrcFhfzxLbWzM5rSwkVnZAD/XxoHhNKi9hQmseG0jI2lBZx5uOY0AAs7ggAqX/A4skVo5oAmp8DZ99vLu7oaA0l+eYIqQPr4cCGip/Hz0UTngSDJ0C3MWeeeE9E6j2FHAco5IjLlOSbLRobvzUnhyvvIwIQkWxODNdxJCT3qdrKUlZsThC38VvYPBuKsip+FxID7YeZganFueDrT3pWIR/+voftmXnsOpRH6pECSq2n/qscHuRHy2Php8WxW2xYIBYL+FgsWAAfHws+FrCUP7ZYzN9ZsO9n3iDI35fkRsGnDk6Zm2Hxv8wZq8v7BzXuCmffBx1GVIQSmw2y9hwLMhvMyfoObDD7F3GS1+PjD3HtoesocyXuujSyS0RcSiHHAQo54hYlBbDjf7BhJmz9qfKIpvAkM/B0uNwMMxu/hS0/Vm6lCI2vWBPJgSUCyqw20rOK2Hkoj12H8u23nQfzSc8udOo6kuUGtYtj0lVdiY84Tf+erDRYOhVWTjP7PgE0am6GtYNbzNaaktyTHxvWGBI6QePOkNDZvB/b1uxnJSINjkKOAxRyxO1KiyoCz5YfT/2lHp5oBp+OI6DpWWbfIicoKrWy53DBceHHDEI5hWUYGNgMsBkGHPtpMzC328A4/rFhPjYMyC4spcxmEBXiz3MjOzOsa9Lpiyg4Asv+ay7TcfzlNzA7K8e1N5ftSOh07NYZQmOd8vpFxDso5DhAIUc8qqzY7Dhb3noTGF4RbE52GauO2nYgl/FfrGXdvmwALu+WxDMjOp1+/h4wL+mtnW6OjIvvYIaZmNbqUyMiZ6SQ4wCFHBHnKLXa+Pfc7bwxbztWm0FCRCCTru7GeW3jPF2aiHihmnx/14//NopInePv68P4IW35+m8DaBkbyoGcYm58bxn/nLmOgpLTTUYoIuIeCjkiUivdU6KY/fdzGDegOQAfL03l0n8tYuWeo54tTEQaPIUcEam14ABfnrq8Ex//tR+JkUHsPlzAX95awks/b6akzObp8kSkgVLIERGnObtNLD/ddy5X9miCzYA35u1gxBuL2bw/58wHi4g4mUKOiDhVZLA/r47uzpvX9aRRiD+bMnK4/N+LeXvBDqy2BjXOQUQ8TCFHRFxiaJdEfr7/XC5oH0+J1cbEHzdzzX9+J/VwgadLE5EGQkPIRcSlDMPgixVpPPPdRvJLrIQE+HLbuS1pEhVMRLA/EUH+hAf5EXnsfliQH74+WmhTRCrTPDkOUMgR8YzUwwU8+OValu0+csZ9wwL9iAjyIyLYDEARQf7HApEZhs5pG0fvZo3cs+ioiNQJCjkOUMgR8RyrzeDTZan8sfMwuUVl5BSVmj8LS8kpKqWo1PGRWK3jw7i2b1Ou6tnkzDMti0i9p5DjAIUckbqrpMxGblEpOccFn+NDUE5hGfuyCvlp/X4KS60ABPj5cGnnxlzbtyl9W0SrdUfESynkOEAhR6T+yy0q5ds16Xz6RyobMyqGp7eKC+Xavk25smcy0aFq3RHxJgo5DlDIEfEehmGwbl82ny1L5ds16RSUHGvd8fXhkmOtO2e1VOuOiDdQyHGAQo6Id8orLmPWmnQ+XbaH9fsqWndaxpqtO1f1UuuOSH2mkOMAhRwR77dubzafLktl1pp95B/XunNx58Zc3i2JlOhgGkcEERnsr1YekXpCIccBCjkiDUdecRnfrU3ns2Wp/Lk3u8rvA/x8SIgIJCE8iITIIPNnRCAJEUHHbub90EA/D1QvIsdTyHGAQo5Iw7T+WN+dlXuOkplbzJH8EoePDQv0I/5YGAoN9CPAz4K/rw/+vj4E+PkQ4OuDv+8ptvkd2+brQ0xYAP1bxuDnq8nmRapLIccBCjkiAlBcZiUzp5jM3CIO5BRzIKeI/TlFZB67b96KySsuc+p5kyKDuKF/c67tm6L5fUSqQSHHAQo5IlIdecVlZB4LPJm5RRSWWCm12iixGpSU2Si12o49tlU8LjOqbrMabMrI4fCxFqQgfx+u6JHMuAHNadc43MOvUqTuU8hxgEKOiHhKUamV79am8/7i3ZXm9xnYOoabBrTg/Pbx+GjdLpGTUshxgEKOiHiaYRgs332U9xfv4ucN+7Ed+1e4WUwIY/s3Z1TvZMKD/D1bpEgdo5DjAIUcEalL9h4t4KOle5i+LI3swlIAQgN8+UvvFG4c0JwWsaEerlCkblDIcYBCjojURQUlZcxYvY9pi3ezLTPPvn1wuzhuGtiCc9rEak4fadAUchygkCMidZlhGPy2/RDTFu9m7pZMyv+Fbh0fxlktowny8yXQ34dAP1+CTvHzZL+PCPYnQpfApB5TyHGAQo6I1Be7D+Uzbcluvlq5t9ZD2S0WuLRLIvec35r2jfVvn9Q/CjkOUMgRkfomt6iU2X9mkJFdRHGZjaJSK8VlNopLrRSVWSkutZ36Z6mVojJzKHu5izomcM/5beiSHOnBVyVSPQo5DlDIEZGGaGN6Dm/M284P6zPsl8AGtYvjnvPb0KtZI88WJ+IAhRwHKOSISEO2PTOXN+bt4Ns1++xD1we0iuGe89twVstodW6WOkshxwEKOSIiZn+fqfO3882qfZQdSzt9mjfinvPbaCSX1EkKOQ5QyBERqbD3aAFvLdjBF8v3UmI1++10S4ninsGtuaBDvMKO1BkKOQ5QyBERqepAThFvL9jJp8v2UFRqhp2OiRHcc35rLu7UWMtNiMcp5DhAIUdE5NQO5RXzzqJdfPT7bvJLrAC0iQ9jbP9m9G8VQ6u4MLe27hSVWjEMCA7wdds5pW5SyHGAQo6IyJkdzS/h/SW7eX/xLnKLKuboiQ0LoG+LaPq1iKFfy2jaxoc7rZXHMAx2Hy5gdepRVqUeZXVqFpv352IYBq3jw+iaHEXX5Ei6JkfRvnE4Qf4KPg2JQo4DFHJERByXU1TKZ3+kMn/LQValHqX4uPl2ABqF+NOneTT9WsbQr0U0HRIj8HUw9OQWlbI2LdseatakZXG0oNShY/19LbRrHE6XJlF0S46kS3IkbRPC8ff1qfZrlPpBIccBCjkiIjVTXGblz73Z/LHzMH/sOsKK3UcpLLVW2ic8yM8MPS3M4NM5KQI/Xx9sNoMdB/PsLTSrU7PYmpnLid9AAX4+dGkSSY+UKHo2a0SPplH4Wiys25fN2r3Z/Lk3iz/3ZnMkv6RKfYF+PnRMiqBbchRdmkTSNTmSlnFhDocuqdsUchygkCMi4hylVhvr9mXzx84j/LHrMCt2H62y/ERogC9tEsLZkZlH7kmWpkiJDqZHihlmejZtRIfECAL8Tt8aYxgG+7IKWbfXDD7r9pnB5/jLauXCAv24qGMCo/qk0K+F5gGqzxRyHKCQIyLiGmVWGxszcuyhZ9muI+QcFzyC/X3plhJJj6aN6JESRfemUcSHBznl3DabwZ4jBfaWnj/3ZrF+X06llqbmMSH8pXcKV/dKJiHCOecV91HIcYBCjoiIe1htBpv357A9M4/W8WG0SwjHz419Zqw2gzVpWXy1Mo1Za9Lto8V8fSwMahvHqD4pnN8+Xv146gmFHAco5IiINDwFJWXM/jODz5ensWLPUfv22LBArurVhFG9U2gVF+bBCuVMFHIcoJAjItKwbc/M48sVaXy9ai+H8io6MPdp3ohRvVO4rGsiIQF+HqxQTkYhxwEKOSIiAmbH6bmbM/l8eRrzt2TaFywNC/RjeLdERvdpSrfkSHVWriMUchygkCMiIifan13E16v28sWKNPYcLrBvT24UTNuEcFrGhtIiLpSWsWG0jAslPjxQ4cfN6mXImTp1Ki+99BIZGRl06tSJyZMnc84555xy/+LiYp555hk+/vhj9u/fT3JyMo899hg333yzQ+dTyBERkVOx2Qz+2HWEL1ak8cO6jCqTH5YLDfC1h54WsaG0LL8fF0pYoC51uUK9Czmff/45N9xwA1OnTmXgwIG8/fbbvPPOO2zcuJGmTZue9JgRI0Zw4MABnnvuOVq3bk1mZiZlZWUMGDDAoXMq5IiIiCNyikpZvy+bnQfz2XUon50H89h1KJ+0o4VYbaf+6owPD7QHn9iwQCKC/IkI9jv209/+ODzIn/AgP6eN7jIMg1KrQXGZleIyG1HB/m4dzeZq9S7k9OvXj549e/Lmm2/at3Xo0IGRI0cyceLEKvv/9NNPXHPNNezcuZPo6OganVMhR0REaqOkzEbqkYJKwWfnwXx2HsrnUF5xtZ8vJMD3JEHIj0A/X0qsNorLrBSVmj+LS20Ul9koKjWDTHmgKX98/Dd6oJ8P7RMj6JRUfous12t+1eT722NtaiUlJaxcuZJHHnmk0vaLLrqIJUuWnPSYWbNm0bt3byZNmsRHH31EaGgol19+Oc8++yzBwcEnPaa4uJji4ooPXU5OjvNehIiINDgBfj60jg+jdXwYkFDpdzlFpew61vKz61A+WQUl5BSVkVNYSk5RKTmFZeQWlZJTVGafHbqgxEpBiZX9Tv56Ki6zsTYti7VpWfZtvj4WWsWF0ikpkk5JEXRMiqBTYiSRIf7Vfn6bzeBIQQkHc4srbnnmT39fHx4Z2t6Jr6ZmPBZyDh06hNVqJSGh8gckISGB/fv3n/SYnTt38ttvvxEUFMSMGTM4dOgQd955J0eOHOG999476TETJ07k6aefdnr9IiIiJ4oI8qdbShTdUqLOuG+Z1UZecRk5hWXHAlBFEMopKqWo1EqQvy+Bfj4E+vkS6H/8T/N+UPk2Px/774P8ffDz8WHP4Xw2pOccu2WzMT2Hw/klbD2Qx9YDecxYvc9eS3KjYHtrT6ekCJpGh3C0oPRYeCmyh5fM4wLN4fySU162iw0LbNghp9yJvdMNwzhlj3WbzYbFYuGTTz4hMjISgFdffZWrr76aN95446StORMmTGD8+PH2xzk5OaSkpDjxFYiIiFSfn68PUSEBRIUEuOT5W8aF0TIujOHdkgDz+/VATjEb0rPtwWdDeg57jxbabz9vOFDt88SEBhAXHmjewsyfdWXZDI+FnNjYWHx9fau02mRmZlZp3SmXmJhIkyZN7AEHzD48hmGwd+9e2rRpU+WYwMBAAgMDnVu8iIhIPWOxWGgcGUTjyCAu6FDxPZtdUMqGDLOlpzz8ZGQVERNWNbzEhQcSHx5kvx8dGlCnl8XwWMgJCAigV69ezJkzhyuuuMK+fc6cOYwYMeKkxwwcOJAvv/ySvLw8wsLM6be3bt2Kj48PycnJbqlbRETEm0SG+DOgVSwDWsV6uhSn82j8Gj9+PO+88w7vvfcemzZt4v777yc1NZU77rgDMC81jR071r7/mDFjiImJ4aabbmLjxo0sXLiQhx56iJtvvvmUHY9FRESkYfJon5zRo0dz+PBhnnnmGTIyMujcuTM//PADzZo1AyAjI4PU1FT7/mFhYcyZM4d77rmH3r17ExMTw6hRo3juuec89RJERESkjvL4jMfupnlyRERE6p+afH/X3d5CIiIiIrWgkCMiIiJeSSFHREREvJJCjoiIiHglhRwRERHxSgo5IiIi4pUUckRERMQrKeSIiIiIV1LIEREREa+kkCMiIiJeSSFHREREvJJHF+j0hPKlunJycjxciYiIiDiq/Hu7OktuNriQk5ubC0BKSoqHKxEREZHqys3NJTIy0qF9G9wq5DabjfT0dMLDw7FYLE597pycHFJSUkhLS9MK59Wg96369J7VjN63mtH7VjN636rvdO+ZYRjk5uaSlJSEj49jvW0aXEuOj48PycnJLj1HRESEPtA1oPet+vSe1Yzet5rR+1Yzet+q71TvmaMtOOXU8VhERES8kkKOiIiIeCWFHCcKDAzkySefJDAw0NOl1Ct636pP71nN6H2rGb1vNaP3rfqc/Z41uI7HIiIi0jCoJUdERES8kkKOiIiIeCWFHBEREfFKCjkiIiLilRRynGTq1Km0aNGCoKAgevXqxaJFizxdUp321FNPYbFYKt0aN27s6bLqnIULFzJ8+HCSkpKwWCzMnDmz0u8Nw+Cpp54iKSmJ4OBgBg0axIYNGzxTbB1ypvdt3LhxVT5/Z511lmeKrSMmTpxInz59CA8PJz4+npEjR7Jly5ZK++jzVpUj75s+b1W9+eabdO3a1T7pX//+/fnxxx/tv3fWZ00hxwk+//xz7rvvPh577DFWr17NOeecw9ChQ0lNTfV0aXVap06dyMjIsN/WrVvn6ZLqnPz8fLp168aUKVNO+vtJkybx6quvMmXKFJYvX07jxo0ZMmSIfY22hupM7xvAJZdcUunz98MPP7ixwrpnwYIF3HXXXSxdupQ5c+ZQVlbGRRddRH5+vn0ffd6qcuR9A33eTpScnMyLL77IihUrWLFiBeeffz4jRoywBxmnfdYMqbW+ffsad9xxR6Vt7du3Nx555BEPVVT3Pfnkk0a3bt08XUa9AhgzZsywP7bZbEbjxo2NF1980b6tqKjIiIyMNN566y0PVFg3nfi+GYZh3HjjjcaIESM8Uk99kZmZaQDGggULDMPQ581RJ75vhqHPm6MaNWpkvPPOO079rKklp5ZKSkpYuXIlF110UaXtF110EUuWLPFQVfXDtm3bSEpKokWLFlxzzTXs3LnT0yXVK7t27WL//v2VPnuBgYGcd955+uw5YP78+cTHx9O2bVtuvfVWMjMzPV1SnZKdnQ1AdHQ0oM+bo05838rp83ZqVquV6dOnk5+fT//+/Z36WVPIqaVDhw5htVpJSEiotD0hIYH9+/d7qKq6r1+/fnz44Yf8/PPP/Pe//2X//v0MGDCAw4cPe7q0eqP886XPXvUNHTqUTz75hLlz5/LKK6+wfPlyzj//fIqLiz1dWp1gGAbjx4/n7LPPpnPnzoA+b4442fsG+rydyrp16wgLCyMwMJA77riDGTNm0LFjR6d+1hrcKuSuYrFYKj02DKPKNqkwdOhQ+/0uXbrQv39/WrVqxQcffMD48eM9WFn9o89e9Y0ePdp+v3PnzvTu3ZtmzZoxe/ZsrrzySg9WVjfcfffd/Pnnn/z2229VfqfP26md6n3T5+3k2rVrx5o1a8jKyuLrr7/mxhtvZMGCBfbfO+OzppacWoqNjcXX17dKuszMzKySQuXUQkND6dKlC9u2bfN0KfVG+Wg0ffZqLzExkWbNmunzB9xzzz3MmjWLefPmkZycbN+uz9vpnep9Oxl93kwBAQG0bt2a3r17M3HiRLp168a//vUvp37WFHJqKSAggF69ejFnzpxK2+fMmcOAAQM8VFX9U1xczKZNm0hMTPR0KfVGixYtaNy4caXPXklJCQsWLNBnr5oOHz5MWlpag/78GYbB3XffzTfffMPcuXNp0aJFpd/r83ZyZ3rfTkaft5MzDIPi4mLnftac1Cm6QZs+fbrh7+9vvPvuu8bGjRuN++67zwgNDTV2797t6dLqrAceeMCYP3++sXPnTmPp0qXGsGHDjPDwcL1nJ8jNzTVWr15trF692gCMV1991Vi9erWxZ88ewzAM48UXXzQiIyONb775xli3bp1x7bXXGomJiUZOTo6HK/es071vubm5xgMPPGAsWbLE2LVrlzFv3jyjf//+RpMmTRr0+/a3v/3NiIyMNObPn29kZGTYbwUFBfZ99Hmr6kzvmz5vJzdhwgRj4cKFxq5du4w///zTePTRRw0fHx/jl19+MQzDeZ81hRwneeONN4xmzZoZAQEBRs+ePSsNH5SqRo8ebSQmJhr+/v5GUlKSceWVVxobNmzwdFl1zrx58wygyu3GG280DMMc1vvkk08ajRs3NgIDA41zzz3XWLdunWeLrgNO974VFBQYF110kREXF2f4+/sbTZs2NW688UYjNTXV02V71MneL8B4//337fvo81bVmd43fd5O7uabb7Z/Z8bFxRkXXHCBPeAYhvM+axbDMIwatiyJiIiI1FnqkyMiIiJeSSFHREREvJJCjoiIiHglhRwRERHxSgo5IiIi4pUUckRERMQrKeSIiIiIV1LIEZEGb/78+VgsFrKysjxdiog4kUKOiIiIeCWFHBEREfFKCjki4nGGYTBp0iRatmxJcHAw3bp146uvvgIqLiXNnj2bbt26ERQURL9+/Vi3bl2l5/j666/p1KkTgYGBNG/enFdeeaXS74uLi3n44YdJSUkhMDCQNm3a8O6771baZ+XKlfTu3ZuQkBAGDBjAli1bXPvCRcSlFHJExOP++c9/8v777/Pmm2+yYcMG7r//fq6//noWLFhg3+ehhx7i5ZdfZvny5cTHx3P55ZdTWloKmOFk1KhRXHPNNaxbt46nnnqKxx9/nGnTptmPHzt2LNOnT+f1119n06ZNvPXWW4SFhVWq47HHHuOVV15hxYoV+Pn5cfPNN7vl9YuIa2iBThHxqPz8fGJjY5k7dy79+/e3b7/lllsoKCjgtttuY/DgwUyfPp3Ro0cDcOTIEZKTk5k2bRqjRo3iuuuu4+DBg/zyyy/24x9++GFmz57Nhg0b2Lp1K+3atWPOnDlceOGFVWqYP38+gwcP5tdff+WCCy4A4IcffuCyyy6jsLCQoKAgF78LIuIKaskREY/auHEjRUVFDBkyhLCwMPvtww8/ZMeOHfb9jg9A0dHRtGvXjk2bNgGwadMmBg4cWOl5Bw4cyLZt27BaraxZswZfX1/OO++809bStWtX+/3ExEQAMjMza/0aRcQz/DxdgIg0bDabDYDZs2fTpEmTSr8LDAysFHROZLFYALNPT/n9csc3UgcHBztUi7+/f5XnLq9PROofteSIiEd17NiRwMBAUlNTad26daVbSkqKfb+lS5fa7x89epStW7fSvn17+3P89ttvlZ53yZIltG3bFl9fX7p06YLNZqvUx0dEvJ9ackTEo8LDw3nwwQe5//77sdlsnH322eTk5LBkyRLCwsJo1qwZAM888wwxMTEkJCTw2GOPERsby8iRIwF44IEH6NOnD88++yyjR4/m999/Z8qUKUydOhWA5s2bc+ONN3LzzTfz+uuv061bN/bs2UNmZiajRo3y1EsXERdTyBERj3v22WeJj49n4sSJ7Ny5k6ioKHr27Mmjjz5qv1z04osvcu+997Jt2za6devGrFmzCAgIAKBnz5588cUXPPHEEzz77LMkJibyzDPPMG7cOPs53nzzTR599FHuvPNODh8+TNOmTXn00Uc98XJFxE00ukpE6rTykU9Hjx4lKirK0+WISD2iPjkiIiLilRRyRERExCvpcpWIiIh4JbXkiIiIiFdSyBERERGvpJAjIiIiXkkhR0RERLySQo6IiIh4JYUcERER8UoKOSIiIuKVFHJERETEKynkiIiIiFf6fxDHyOo/o1+bAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 428,
   "id": "330f79f5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e29eb95810>"
      ]
     },
     "execution_count": 428,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['accuracy'])\n",
    "plt.plot(history.history['val_accuracy'])\n",
    "plt.title('Training and validation accuracy')\n",
    "plt.ylabel('accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 429,
   "id": "ec6bfb84",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 2s 7ms/step\n",
      "[[676   0   5  19   0   2   5   3]\n",
      " [  5 621  23  13   0   4   2   7]\n",
      " [  0   4 632  22   0   2  12   9]\n",
      " [  4   3  16 662   3 141  32  24]\n",
      " [  2   0   2  36 256  13  21  20]\n",
      " [  2   3  15 417   6 123  41  28]\n",
      " [  2   3  16 157   5  21 210  23]\n",
      " [  3  11   8  77  27  44  34 161]]\n",
      "0.7051498522583368\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.97      0.95      0.96       710\n",
      "           1       0.96      0.92      0.94       675\n",
      "           2       0.88      0.93      0.90       681\n",
      "           3       0.47      0.75      0.58       885\n",
      "           4       0.86      0.73      0.79       350\n",
      "           5       0.35      0.19      0.25       635\n",
      "           6       0.59      0.48      0.53       437\n",
      "           7       0.59      0.44      0.50       365\n",
      "\n",
      "    accuracy                           0.71      4738\n",
      "   macro avg       0.71      0.67      0.68      4738\n",
      "weighted avg       0.71      0.71      0.70      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 429,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=model2.predict(X_test_c)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_c, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "59975e2b",
   "metadata": {},
   "source": [
    "## Train set: Chest / Test set: Hand"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "c6d992dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 1s 8ms/step\n",
      "[[141 148  94 137   1  59  29 101]\n",
      " [ 31  18 175 291  29  59  18  54]\n",
      " [ 14  19  47 400   4  89  22  86]\n",
      " [ 73  22   8 316  37 115 136 178]\n",
      " [  4   7   4  52 119  46  59  59]\n",
      " [ 17  11  10 317  25 118  53  84]\n",
      " [ 30  19  11 162   4  74  72  65]\n",
      " [ 36  19  23 123   8  66  33  57]]\n",
      "0.18742085268045588\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.41      0.20      0.27       710\n",
      "           1       0.07      0.03      0.04       675\n",
      "           2       0.13      0.07      0.09       681\n",
      "           3       0.18      0.36      0.24       885\n",
      "           4       0.52      0.34      0.41       350\n",
      "           5       0.19      0.19      0.19       635\n",
      "           6       0.17      0.16      0.17       437\n",
      "           7       0.08      0.16      0.11       365\n",
      "\n",
      "    accuracy                           0.19      4738\n",
      "   macro avg       0.22      0.19      0.19      4738\n",
      "weighted avg       0.21      0.19      0.18      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 430,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=model2.predict(X_test_h)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_h, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 431,
   "id": "ad916acf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: pamap2_chest.pth\\assets\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Assets written to: pamap2_chest.pth\\assets\n"
     ]
    }
   ],
   "source": [
    "pth_file2 = 'pamap2_chest.pth'\n",
    "tf.keras.models.save_model(model2, pth_file2, include_optimizer=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f063d411",
   "metadata": {},
   "source": [
    "## Fine tuning pretrained model with chest for hands model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 432,
   "id": "bb4e392b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:No training configuration found in save file, so the model was *not* compiled. Compile it manually.\n"
     ]
    }
   ],
   "source": [
    "base_model1 = keras.models.load_model(pth_file2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 433,
   "id": "6ec17a75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of layers in the base model:  6\n",
      "Model: \"sequential_36\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " lstm_25 (LSTM)              (None, 15, 64)            19712     \n",
      "                                                                 \n",
      " lstm_26 (LSTM)              (None, 32)                12416     \n",
      "                                                                 \n",
      " dropout_39 (Dropout)        (None, 32)                0         \n",
      "                                                                 \n",
      " dense_74 (Dense)            (None, 16)                528       \n",
      "                                                                 \n",
      " dropout_40 (Dropout)        (None, 16)                0         \n",
      "                                                                 \n",
      " dense_76 (Dense)            (None, 16)                272       \n",
      "                                                                 \n",
      " dropout_41 (Dropout)        (None, 16)                0         \n",
      "                                                                 \n",
      " dense_77 (Dense)            (None, 8)                 136       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 33064 (129.16 KB)\n",
      "Trainable params: 936 (3.66 KB)\n",
      "Non-trainable params: 32128 (125.50 KB)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "print(\"Number of layers in the base model: \", len(base_model1.layers))\n",
    "fine_tune_at = 2\n",
    "\n",
    "for layer in base_model1.layers[:fine_tune_at]:\n",
    "    layer.trainable = False\n",
    "\n",
    "new_model2 = Sequential(base_model1.layers[:-1])\n",
    "new_model2.add(Dense(16, activation=\"sigmoid\"))\n",
    "new_model2.add(Dropout(0.3))\n",
    "new_model2.add(Dense(n_outputs, activation=\"sigmoid\"))\n",
    "\n",
    "new_model2.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 434,
   "id": "bb18c748",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_model2.compile(loss =\"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 435,
   "id": "facb98a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Layer Type</th>\n",
       "      <th>Layer Name</th>\n",
       "      <th>Layer Trainable</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_25</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_26</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_39</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_74</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
       "      <td>dropout_40</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_75</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "                                          Layer Type  Layer Name  \\\n",
       "0  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_25   \n",
       "1  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_26   \n",
       "2  <keras.src.layers.regularization.dropout.Dropo...  dropout_39   \n",
       "3  <keras.src.layers.core.dense.Dense object at 0...    dense_74   \n",
       "4  <keras.src.layers.regularization.dropout.Dropo...  dropout_40   \n",
       "5  <keras.src.layers.core.dense.Dense object at 0...    dense_75   \n",
       "\n",
       "   Layer Trainable  \n",
       "0            False  \n",
       "1            False  \n",
       "2             True  \n",
       "3             True  \n",
       "4             True  \n",
       "5             True  "
      ]
     },
     "execution_count": 435,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display_layers = [(layer, layer.name, layer.trainable) for layer in base_model1.layers]\n",
    "pd.DataFrame(display_layers, columns=['Layer Type', 'Layer Name', 'Layer Trainable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 436,
   "id": "f06a9864",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "237/237 [==============================] - 9s 20ms/step - loss: 1.9528 - accuracy: 0.2485 - val_loss: 1.8005 - val_accuracy: 0.3352\n",
      "Epoch 2/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.8455 - accuracy: 0.3076 - val_loss: 1.7390 - val_accuracy: 0.3826\n",
      "Epoch 3/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7998 - accuracy: 0.3317 - val_loss: 1.6921 - val_accuracy: 0.4040\n",
      "Epoch 4/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7744 - accuracy: 0.3497 - val_loss: 1.6632 - val_accuracy: 0.4235\n",
      "Epoch 5/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7566 - accuracy: 0.3551 - val_loss: 1.6469 - val_accuracy: 0.4188\n",
      "Epoch 6/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7516 - accuracy: 0.3570 - val_loss: 1.6391 - val_accuracy: 0.4320\n",
      "Epoch 7/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7548 - accuracy: 0.3602 - val_loss: 1.6297 - val_accuracy: 0.4386\n",
      "Epoch 8/20\n",
      "237/237 [==============================] - 3s 15ms/step - loss: 1.7485 - accuracy: 0.3647 - val_loss: 1.6311 - val_accuracy: 0.4335\n",
      "Epoch 9/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.7366 - accuracy: 0.3680 - val_loss: 1.6091 - val_accuracy: 0.4459\n",
      "Epoch 10/20\n",
      "237/237 [==============================] - 4s 16ms/step - loss: 1.7248 - accuracy: 0.3759 - val_loss: 1.6050 - val_accuracy: 0.4473\n",
      "Epoch 11/20\n",
      "237/237 [==============================] - 4s 17ms/step - loss: 1.7274 - accuracy: 0.3793 - val_loss: 1.5997 - val_accuracy: 0.4451\n",
      "Epoch 12/20\n",
      "237/237 [==============================] - 5s 19ms/step - loss: 1.7252 - accuracy: 0.3780 - val_loss: 1.6021 - val_accuracy: 0.4449\n",
      "Epoch 13/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7262 - accuracy: 0.3778 - val_loss: 1.5928 - val_accuracy: 0.4570\n",
      "Epoch 14/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7238 - accuracy: 0.3756 - val_loss: 1.6024 - val_accuracy: 0.4436\n",
      "Epoch 15/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.7278 - accuracy: 0.3790 - val_loss: 1.5880 - val_accuracy: 0.4517\n",
      "Epoch 16/20\n",
      "237/237 [==============================] - 4s 16ms/step - loss: 1.7207 - accuracy: 0.3830 - val_loss: 1.5842 - val_accuracy: 0.4491\n",
      "Epoch 17/20\n",
      "237/237 [==============================] - 3s 14ms/step - loss: 1.7195 - accuracy: 0.3809 - val_loss: 1.5837 - val_accuracy: 0.4560\n",
      "Epoch 18/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.7116 - accuracy: 0.3844 - val_loss: 1.5765 - val_accuracy: 0.4509\n",
      "Epoch 19/20\n",
      "237/237 [==============================] - 4s 16ms/step - loss: 1.7235 - accuracy: 0.3800 - val_loss: 1.5795 - val_accuracy: 0.4525\n",
      "Epoch 20/20\n",
      "237/237 [==============================] - 4s 15ms/step - loss: 1.7151 - accuracy: 0.3807 - val_loss: 1.5758 - val_accuracy: 0.4570\n"
     ]
    }
   ],
   "source": [
    "history3 = new_model2.fit(X_train_h, y_train_h, batch_size= batch_size, epochs=20, validation_split=validation_split)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 437,
   "id": "8deaaaa2",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model1.trainable = True\n",
    "new_model2.compile(loss =\"categorical_crossentropy\", optimizer = Adam(learning_rate=0.01), metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 438,
   "id": "5f826bc8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Layer Type</th>\n",
       "      <th>Layer Name</th>\n",
       "      <th>Layer Trainable</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_25</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>&lt;keras.src.layers.rnn.lstm.LSTM object at 0x00...</td>\n",
       "      <td>lstm_26</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>&lt;keras.src.layers.regularization.dropout.Dropo...</td>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_74</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
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       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>&lt;keras.src.layers.core.dense.Dense object at 0...</td>\n",
       "      <td>dense_75</td>\n",
       "      <td>True</td>\n",
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      ],
      "text/plain": [
       "                                          Layer Type  Layer Name  \\\n",
       "0  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_25   \n",
       "1  <keras.src.layers.rnn.lstm.LSTM object at 0x00...     lstm_26   \n",
       "2  <keras.src.layers.regularization.dropout.Dropo...  dropout_39   \n",
       "3  <keras.src.layers.core.dense.Dense object at 0...    dense_74   \n",
       "4  <keras.src.layers.regularization.dropout.Dropo...  dropout_40   \n",
       "5  <keras.src.layers.core.dense.Dense object at 0...    dense_75   \n",
       "\n",
       "   Layer Trainable  \n",
       "0             True  \n",
       "1             True  \n",
       "2             True  \n",
       "3             True  \n",
       "4             True  \n",
       "5             True  "
      ]
     },
     "execution_count": 438,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "display_layers = [(layer, layer.name, layer.trainable) for layer in base_model1.layers]\n",
    "pd.DataFrame(display_layers, columns=['Layer Type', 'Layer Name', 'Layer Trainable'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 439,
   "id": "2f062e54",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 1.4781 - accuracy: 0.4802 - val_loss: 1.1507 - val_accuracy: 0.6239\n",
      "Epoch 2/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 1.1245 - accuracy: 0.6122 - val_loss: 0.9940 - val_accuracy: 0.6896\n",
      "Epoch 3/20\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.9981 - accuracy: 0.6665 - val_loss: 0.9438 - val_accuracy: 0.7089\n",
      "Epoch 4/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.9217 - accuracy: 0.6924 - val_loss: 0.8956 - val_accuracy: 0.7199\n",
      "Epoch 5/20\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.8732 - accuracy: 0.7089 - val_loss: 0.8772 - val_accuracy: 0.7321\n",
      "Epoch 6/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.8205 - accuracy: 0.7273 - val_loss: 0.8648 - val_accuracy: 0.7355\n",
      "Epoch 7/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.7997 - accuracy: 0.7346 - val_loss: 0.8298 - val_accuracy: 0.7424\n",
      "Epoch 8/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7623 - accuracy: 0.7497 - val_loss: 0.8226 - val_accuracy: 0.7429\n",
      "Epoch 9/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.7307 - accuracy: 0.7576 - val_loss: 0.8385 - val_accuracy: 0.7445\n",
      "Epoch 10/20\n",
      "237/237 [==============================] - 6s 27ms/step - loss: 0.7135 - accuracy: 0.7625 - val_loss: 0.8353 - val_accuracy: 0.7487\n",
      "Epoch 11/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6772 - accuracy: 0.7768 - val_loss: 0.8223 - val_accuracy: 0.7516\n",
      "Epoch 12/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6750 - accuracy: 0.7764 - val_loss: 0.8180 - val_accuracy: 0.7500\n",
      "Epoch 13/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6742 - accuracy: 0.7793 - val_loss: 0.8040 - val_accuracy: 0.7569\n",
      "Epoch 14/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6553 - accuracy: 0.7853 - val_loss: 0.8007 - val_accuracy: 0.7616\n",
      "Epoch 15/20\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.6288 - accuracy: 0.7947 - val_loss: 0.8427 - val_accuracy: 0.7534\n",
      "Epoch 16/20\n",
      "237/237 [==============================] - 6s 24ms/step - loss: 0.6326 - accuracy: 0.7927 - val_loss: 0.8148 - val_accuracy: 0.7529\n",
      "Epoch 17/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.6156 - accuracy: 0.8012 - val_loss: 0.8460 - val_accuracy: 0.7513\n",
      "Epoch 18/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.5987 - accuracy: 0.8035 - val_loss: 0.8269 - val_accuracy: 0.7561\n",
      "Epoch 19/20\n",
      "237/237 [==============================] - 6s 25ms/step - loss: 0.6042 - accuracy: 0.8003 - val_loss: 0.8448 - val_accuracy: 0.7516\n",
      "Epoch 20/20\n",
      "237/237 [==============================] - 6s 26ms/step - loss: 0.5939 - accuracy: 0.8066 - val_loss: 0.8209 - val_accuracy: 0.7569\n"
     ]
    }
   ],
   "source": [
    "history4 = new_model1.fit(X_train_h, y_train_h, epochs=20, batch_size = batch_size, validation_split = validation_split, shuffle = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 440,
   "id": "d9bbf7a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<matplotlib.legend.Legend at 0x1e2c6596290>"
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     "execution_count": 440,
     "metadata": {},
     "output_type": "execute_result"
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history4.history['loss'])\n",
    "plt.plot(history4.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 441,
   "id": "801b0d56",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x1e2f4cf5810>"
      ]
     },
     "execution_count": 441,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history4.history['accuracy'])\n",
    "plt.plot(history4.history['val_accuracy'])\n",
    "plt.title('Training and validation accuracy')\n",
    "plt.ylabel('accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'Validation'], loc='upper left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 442,
   "id": "b1d4f93d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "149/149 [==============================] - 2s 8ms/step\n",
      "[[610  15  16  60   0   9   0   0]\n",
      " [ 65 339  61 104  10  96   0   0]\n",
      " [ 35  54 356 162   4  70   0   0]\n",
      " [ 46  16 118 586  43  76   0   0]\n",
      " [  8  14  19 137 145  27   0   0]\n",
      " [ 34  30  99 267  25 180   0   0]\n",
      " [ 35  18  82 245   9  48   0   0]\n",
      " [ 52  43  46 168  12  44   0   0]]\n",
      "0.4677078936260025\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.69      0.86      0.76       710\n",
      "           1       0.64      0.50      0.56       675\n",
      "           2       0.45      0.52      0.48       681\n",
      "           3       0.34      0.66      0.45       885\n",
      "           4       0.58      0.41      0.48       350\n",
      "           5       0.33      0.28      0.30       635\n",
      "           6       0.00      0.00      0.00       437\n",
      "           7       0.00      0.00      0.00       365\n",
      "\n",
      "    accuracy                           0.47      4738\n",
      "   macro avg       0.38      0.41      0.38      4738\n",
      "weighted avg       0.41      0.47      0.42      4738\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 442,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "y_pred=new_model2.predict(X_test_h)\n",
    "y_pred = np.argmax(y_pred, axis=-1)\n",
    "y_test2 = np.argmax(y_test_h, axis=-1)\n",
    "\n",
    "LABELS = ['lying','sitting','standing','walking','running','Nordic_walking','ascending_stairs','descending_stairs']\n",
    "cm=confusion_matrix(y_test2,y_pred)\n",
    "\n",
    "print(cm)\n",
    "print(accuracy_score(y_test2,y_pred))\n",
    "print(classification_report(y_test2,y_pred))\n",
    "sns.heatmap(cm, cmap=\"YlGnBu\", xticklabels=LABELS, yticklabels=LABELS, annot=True, fmt = '.2f')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9abf45c3",
   "metadata": {},
   "source": [
    "### Predict hand Data\n",
    "#### Training data: hand -> Testing data: hand\n",
    "Accuaracy: 74.92\n",
    "\n",
    "#### Training data: chest -> Testing data: hand\n",
    "Accuaracy: 18.74\n",
    "#### Finetuning with hand data with pretrained_model by chest\n",
    "Accuaracy: 46.77\n",
    "\n",
    "-----------------------------------------------------------------------\n",
    "### Predict chest Data\n",
    "#### Training data: chest -> Testing data: chest\n",
    "Accuaracy: 70.51\n",
    "\n",
    "#### Training data: hand -> Testing data: chest\n",
    "Accuaracy: 26.61\n",
    "#### Finetuning with chest data with pretrained_model by hand\n",
    "Accuaracy: 70.62\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85cbbba2",
   "metadata": {},
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}