{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "c:\\Users\\Lukas\\AppData\\Local\\Programs\\Python\\Python38\\lib\\site-packages\\ignite\\handlers\\checkpoint.py:16: DeprecationWarning: `TorchScript` support for functional optimizers is deprecated and will be removed in a future PyTorch release. Consider using the `torch.compile` optimizer instead.\n", " from torch.distributed.optim import ZeroRedundancyOptimizer\n" ] } ], "source": [ "# Import notwendiger Bibliotheken\n", "import nussl\n", "from common import data, viz\n", "from IPython.display import Audio\n", "import IPython\n", "import tensorflow as tf\n", "from tensorflow.keras import layers, models\n", "import numpy as np\n", "import librosa\n", "import os\n", "from scipy import signal\n", "import matplotlib.pyplot as plt\n", "import stempeg\n", "import pickle\n", "import zipfile\n", "from tensorflow.keras.optimizers import Adam\n", "import tensorflow.signal as tf_signal" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import tensorflow.signal as tf_signal\n", "\n", "# Refactor functions into keras layers.\n", "class InverseSpectrogramLayer(tf.keras.layers.Layer):\n", " def __init__(self, **kwargs):\n", " super(InverseSpectrogramLayer, self).__init__(**kwargs)\n", "\n", " def call(self, spect):\n", " # Convert the input to a tensor if it's not already\n", " magnitude = tf.convert_to_tensor(spect, dtype=tf.float32)\n", "\n", " # Bestimme die Batch-Größe dynamisch\n", " batch_size = tf.shape(magnitude)[0]\n", "\n", " # Zielgröße für das Resizing (None, 169, 257)\n", " target_size = (257, 1723)\n", "\n", " # Resize das Spektrogramm, dabei Batch-Dimension beibehalten\n", " magnitude_resized = tf.image.resize(magnitude, target_size) # (None, 169, 257)\n", "\n", " # Falls notwendig, die Dimensionen noch einmal explizit setzen\n", " magnitude_resized = tf.reshape(magnitude_resized, (batch_size, 257, 1723))\n", "\n", " # Compute complex STFT\n", " stft_complex = tf.complex(magnitude_resized, tf.zeros_like(magnitude_resized))\n", "\n", " # Perform inverse STFT\n", " waveform = tf_signal.inverse_stft(stft_complex, frame_length=512, frame_step=254, fft_length=512, window_fn=tf_signal.hann_window)\n", "\n", " waveform = tf.expand_dims(waveform, axis=-1)\n", " return waveform\n", "\n", "class SpectrogramLayer(tf.keras.layers.Layer):\n", " def __init__(self, **kwargs):\n", " super(SpectrogramLayer, self).__init__(**kwargs)\n", "\n", " def call(self, input_waveform):\n", " wave = input_waveform[:, :, 0]\n", "\n", " stft = tf_signal.stft(wave, frame_length=512, frame_step=254, fft_length=512, window_fn=tf_signal.hann_window)\n", " magnitude = tf.abs(stft) # (Batch, Freq, Time)\n", "\n", " target_size = (512, 128)\n", "\n", " # Umformung für das Resizing: Füge eine Kanal-Dimension hinzu\n", " magnitude = tf.expand_dims(magnitude, axis=-1) # (None, 169, 257, 1)\n", "\n", " # Resize das Spektrogramm\n", " magnitude_resized = tf.image.resize(magnitude, target_size) # (None, 128, 256, 1)\n", "\n", " # Entferne die zusätzliche Dimension\n", " magnitude_resized = tf.squeeze(magnitude_resized, axis=-1) # (None, 128, 256)\n", " # added tf.expand_dims here so it can be done inside a layer.\n", " magnitude_resized = tf.expand_dims(magnitude_resized, axis=-1)\n", "\n", " return magnitude_resized # (None, 128, 256, 1)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input: (None, 512, 128, 1)\n", "conv1: (None, 128, 128, 64)\n", "conv2: (None, 32, 128, 128)\n", "conv3: (None, 8, 128, 256)\n", "conv4: (None, 1, 128, 512)\n", "time_conv1: (None, 16384, 64)\n", "time_conv2: (None, 4096, 128)\n", "time_conv3: (None, 1024, 256)\n", "time_conv4: (None, 128, 512)\n", "x: (None, 1, 128, 512)\n", "dual_conv: (None, 1, 64, 1024)\n", "dual_up: (None, 1, 128, 1024)\n", "dual_up_time Reshape: (None, 128, 1024)\n", "up6: (None, 8, 128, 768)\n", "up7: (None, 32, 128, 384)\n", "up8: (None, 128, 128, 192)\n", "up9: (None, 512, 128, 64)\n", "time_up6: (None, 1024, 768)\n", "time_up7: (None, 4096, 384)\n", "time_up8: (None, 16384, 192)\n", "time_up9: (None, 65536, 64)\n", "wave_9: (None, 65536, 1)\n", "y: (None, 65536, 64)\n", "y_spec: (None, 512, 128, 1)\n", "outputs: (None, 512, 128, 1)\n", "Model: \"model_2\"\n", "__________________________________________________________________________________________________\n", " Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", " input_3 (InputLayer) [(None, 512, 128, 1 0 [] \n", " )] \n", " \n", " inverse_spectrogram_layer_2 (I (None, 65536, 1) 0 ['input_3[0][0]', \n", " nverseSpectrogramLayer) 'dropout_49[0][0]'] \n", " \n", " conv2d_10 (Conv2D) (None, 128, 128, 64 1664 ['input_3[0][0]'] \n", " ) \n", " \n", " conv1d_8 (Conv1D) (None, 16384, 64) 384 ['inverse_spectrogram_layer_2[0][\n", " 0]'] \n", " \n", " activation_36 (Activation) (None, 128, 128, 64 0 ['conv2d_10[0][0]'] \n", " ) \n", " \n", " activation_40 (Activation) (None, 16384, 64) 0 ['conv1d_8[0][0]'] \n", " \n", " dropout_36 (Dropout) (None, 128, 128, 64 0 ['activation_36[0][0]'] \n", " ) \n", " \n", " dropout_40 (Dropout) (None, 16384, 64) 0 ['activation_40[0][0]'] \n", " \n", " conv2d_11 (Conv2D) (None, 32, 128, 128 204928 ['dropout_36[0][0]'] \n", " ) \n", " \n", " conv1d_9 (Conv1D) (None, 4096, 128) 41088 ['dropout_40[0][0]'] \n", " \n", " activation_37 (Activation) (None, 32, 128, 128 0 ['conv2d_11[0][0]'] \n", " ) \n", " \n", " activation_41 (Activation) (None, 4096, 128) 0 ['conv1d_9[0][0]'] \n", " \n", " dropout_37 (Dropout) (None, 32, 128, 128 0 ['activation_37[0][0]'] \n", " ) \n", " \n", " dropout_41 (Dropout) (None, 4096, 128) 0 ['activation_41[0][0]'] \n", " \n", " conv2d_12 (Conv2D) (None, 8, 128, 256) 819456 ['dropout_37[0][0]'] \n", " \n", " conv1d_10 (Conv1D) (None, 1024, 256) 164096 ['dropout_41[0][0]'] \n", " \n", " activation_38 (Activation) (None, 8, 128, 256) 0 ['conv2d_12[0][0]'] \n", " \n", " activation_42 (Activation) (None, 1024, 256) 0 ['conv1d_10[0][0]'] \n", " \n", " dropout_38 (Dropout) (None, 8, 128, 256) 0 ['activation_38[0][0]'] \n", " \n", " dropout_42 (Dropout) (None, 1024, 256) 0 ['activation_42[0][0]'] \n", " \n", " conv2d_13 (Conv2D) (None, 1, 128, 512) 3277312 ['dropout_38[0][0]'] \n", " \n", " conv1d_11 (Conv1D) (None, 128, 512) 655872 ['dropout_42[0][0]'] \n", " \n", " activation_39 (Activation) (None, 1, 128, 512) 0 ['conv2d_13[0][0]'] \n", " \n", " activation_43 (Activation) (None, 128, 512) 0 ['conv1d_11[0][0]'] \n", " \n", " dropout_39 (Dropout) (None, 1, 128, 512) 0 ['activation_39[0][0]'] \n", " \n", " dropout_43 (Dropout) (None, 128, 512) 0 ['activation_43[0][0]'] \n", " \n", " add_4 (Add) (None, 1, 128, 512) 0 ['dropout_39[0][0]', \n", " 'dropout_43[0][0]'] \n", " \n", " conv2d_14 (Conv2D) (None, 1, 64, 1024) 13108224 ['add_4[0][0]'] \n", " \n", " batch_normalization_4 (BatchNo (None, 1, 64, 1024) 4096 ['conv2d_14[0][0]'] \n", " rmalization) \n", " \n", " activation_44 (Activation) (None, 1, 64, 1024) 0 ['batch_normalization_4[0][0]'] \n", " \n", " dropout_44 (Dropout) (None, 1, 64, 1024) 0 ['activation_44[0][0]'] \n", " \n", " conv2d_transpose_12 (Conv2DTra (None, 1, 128, 1024 26215424 ['dropout_44[0][0]'] \n", " nspose) ) \n", " \n", " batch_normalization_5 (BatchNo (None, 1, 128, 1024 4096 ['conv2d_transpose_12[0][0]'] \n", " rmalization) ) \n", " \n", " activation_45 (Activation) (None, 1, 128, 1024 0 ['batch_normalization_5[0][0]'] \n", " ) \n", " \n", " dropout_45 (Dropout) (None, 1, 128, 1024 0 ['activation_45[0][0]'] \n", " ) \n", " \n", " reshape_2 (Reshape) (None, 128, 1024) 0 ['dropout_45[0][0]'] \n", " \n", " conv2d_transpose_13 (Conv2DTra (None, 8, 128, 512) 13107712 ['dropout_45[0][0]'] \n", " nspose) \n", " \n", " conv1d_transpose_8 (Conv1DTran (None, 1024, 512) 2621952 ['reshape_2[0][0]'] \n", " spose) \n", " \n", " activation_46 (Activation) (None, 8, 128, 512) 0 ['conv2d_transpose_13[0][0]'] \n", " \n", " activation_50 (Activation) (None, 1024, 512) 0 ['conv1d_transpose_8[0][0]'] \n", " \n", " dropout_46 (Dropout) (None, 8, 128, 512) 0 ['activation_46[0][0]'] \n", " \n", " dropout_50 (Dropout) (None, 1024, 512) 0 ['activation_50[0][0]'] \n", " \n", " concatenate_12 (Concatenate) (None, 8, 128, 768) 0 ['dropout_46[0][0]', \n", " 'dropout_38[0][0]'] \n", " \n", " concatenate_15 (Concatenate) (None, 1024, 768) 0 ['dropout_50[0][0]', \n", " 'dropout_42[0][0]'] \n", " \n", " conv2d_transpose_14 (Conv2DTra (None, 32, 128, 256 4915456 ['concatenate_12[0][0]'] \n", " nspose) ) \n", " \n", " conv1d_transpose_9 (Conv1DTran (None, 4096, 256) 983296 ['concatenate_15[0][0]'] \n", " spose) \n", " \n", " activation_47 (Activation) (None, 32, 128, 256 0 ['conv2d_transpose_14[0][0]'] \n", " ) \n", " \n", " activation_51 (Activation) (None, 4096, 256) 0 ['conv1d_transpose_9[0][0]'] \n", " \n", " dropout_47 (Dropout) (None, 32, 128, 256 0 ['activation_47[0][0]'] \n", " ) \n", " \n", " dropout_51 (Dropout) (None, 4096, 256) 0 ['activation_51[0][0]'] \n", " \n", " concatenate_13 (Concatenate) (None, 32, 128, 384 0 ['dropout_47[0][0]', \n", " ) 'dropout_37[0][0]'] \n", " \n", " concatenate_16 (Concatenate) (None, 4096, 384) 0 ['dropout_51[0][0]', \n", " 'dropout_41[0][0]'] \n", " \n", " conv2d_transpose_15 (Conv2DTra (None, 128, 128, 12 1228928 ['concatenate_13[0][0]'] \n", " nspose) 8) \n", " \n", " conv1d_transpose_10 (Conv1DTra (None, 16384, 128) 245888 ['concatenate_16[0][0]'] \n", " nspose) \n", " \n", " activation_48 (Activation) (None, 128, 128, 12 0 ['conv2d_transpose_15[0][0]'] \n", " 8) \n", " \n", " activation_52 (Activation) (None, 16384, 128) 0 ['conv1d_transpose_10[0][0]'] \n", " \n", " dropout_48 (Dropout) (None, 128, 128, 12 0 ['activation_48[0][0]'] \n", " 8) \n", " \n", " dropout_52 (Dropout) (None, 16384, 128) 0 ['activation_52[0][0]'] \n", " \n", " concatenate_14 (Concatenate) (None, 128, 128, 19 0 ['dropout_48[0][0]', \n", " 2) 'dropout_36[0][0]'] \n", " \n", " concatenate_17 (Concatenate) (None, 16384, 192) 0 ['dropout_52[0][0]', \n", " 'dropout_40[0][0]'] \n", " \n", " conv2d_transpose_16 (Conv2DTra (None, 512, 128, 64 307264 ['concatenate_14[0][0]'] \n", " nspose) ) \n", " \n", " conv1d_transpose_11 (Conv1DTra (None, 65536, 64) 61504 ['concatenate_17[0][0]'] \n", " nspose) \n", " \n", " activation_49 (Activation) (None, 512, 128, 64 0 ['conv2d_transpose_16[0][0]'] \n", " ) \n", " \n", " activation_53 (Activation) (None, 65536, 64) 0 ['conv1d_transpose_11[0][0]'] \n", " \n", " dropout_49 (Dropout) (None, 512, 128, 64 0 ['activation_49[0][0]'] \n", " ) \n", " \n", " dropout_53 (Dropout) (None, 65536, 64) 0 ['activation_53[0][0]'] \n", " \n", " add_5 (Add) (None, 65536, 64) 0 ['dropout_53[0][0]', \n", " 'inverse_spectrogram_layer_2[1][\n", " 0]'] \n", " \n", " spectrogram_layer_2 (Spectrogr (None, 512, 128, 1) 0 ['add_5[0][0]'] \n", " amLayer) \n", " \n", " conv2d_transpose_17 (Conv2DTra (None, 512, 128, 1) 26 ['spectrogram_layer_2[0][0]'] \n", " nspose) \n", " \n", "==================================================================================================\n", "Total params: 67,968,666\n", "Trainable params: 67,964,570\n", "Non-trainable params: 4,096\n", "__________________________________________________________________________________________________\n" ] } ], "source": [ "drop = 0.45\n", "\n", "def build_dual_freq(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", " print('Input: ', inputs.shape)\n", "\n", " inverse_spectrogram = InverseSpectrogramLayer()\n", " spectrogram = SpectrogramLayer()\n", "\n", " wave = inverse_spectrogram(inputs)\n", "\n", " # Encoder Spec\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(4, 1), padding='same')(inputs)\n", " conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", " print('conv1: ', conv1.shape)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(4, 1), padding='same')(conv1)\n", " conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", " print('conv2: ', conv2.shape)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(4, 1), padding='same')(conv2)\n", " conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", " print('conv3: ', conv3.shape)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(8, 1), padding='same')(conv3)\n", " conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", " print('conv4: ', conv4.shape)\n", "\n", " # Encoder Zeit\n", " time_conv1 = layers.Conv1D(64, 5, strides=4, padding='same')(wave)\n", " time_conv1 = layers.BatchNormalization()(time_conv1)\n", " time_conv1 = layers.ReLU()(time_conv1)\n", " time_conv1 = layers.Dropout(drop)(time_conv1)\n", " print('time_conv1: ', time_conv1.shape)\n", "\n", " time_conv2 = layers.Conv1D(128, 5, strides=4, padding='same')(time_conv1)\n", " time_conv2 = layers.BatchNormalization()(time_conv2)\n", " time_conv2 = layers.ReLU()(time_conv2)\n", " time_conv2 = layers.Dropout(drop)(time_conv2)\n", " print('time_conv2: ', time_conv2.shape)\n", "\n", " time_conv3 = layers.Conv1D(256, 5, strides=4, padding='same')(time_conv2)\n", " time_conv3 = layers.BatchNormalization()(time_conv3)\n", " time_conv3 = layers.ReLU()(time_conv3)\n", " time_conv3 = layers.Dropout(drop)(time_conv3)\n", " print('time_conv3: ', time_conv3.shape)\n", "\n", " time_conv4 = layers.Conv1D(512, 5, strides=8, padding='same')(time_conv3)\n", " time_conv4 = layers.BatchNormalization()(time_conv4)\n", " time_conv4 = layers.ReLU()(time_conv4)\n", " time_conv4 = layers.Dropout(drop)(time_conv4)\n", " print('time_conv4: ', time_conv4.shape)\n", "\n", " # Dual Core\n", " x = layers.Add()([conv4, time_conv4])\n", " print('x: ', x.shape)\n", "\n", " dual_conv = layers.Conv2D(1024, (5, 5), strides=(1, 2), padding='same')(x)\n", " dual_conv = layers.BatchNormalization()(dual_conv)\n", " dual_conv = layers.ReLU()(dual_conv)\n", " dual_conv = layers.Dropout(drop)(dual_conv)\n", " print('dual_conv: ', dual_conv.shape)\n", " #dual_conv = layers.Reshape((64, 1024))(dual_conv) # Entfernt die unnötige Achse\n", " #print('dual_conv Reshape: ', dual_conv.shape)\n", "\n", " dual_up = layers.Conv2DTranspose(1024, (5, 5), strides=(1, 2), padding='same')(dual_conv)\n", " dual_up = layers.BatchNormalization()(dual_up)\n", " dual_up = layers.ReLU()(dual_up)\n", " dual_up = layers.Dropout(drop)(dual_up)\n", " print('dual_up: ', dual_up.shape)\n", " dual_up_time = layers.Reshape((128, 1024))(dual_up) # Entfernt die unnötige Achse\n", " print('dual_up_time Reshape: ', dual_up_time.shape)\n", "\n", " # Decoder Spec\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(8, 1), padding='same')(dual_up)\n", " up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv3])\n", " print('up6: ', up6.shape)\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(4, 1), padding='same')(up6)\n", " up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv2])\n", " print('up7: ', up7.shape)\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(4, 1), padding='same')(up7)\n", " up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv1])\n", " print('up8: ', up8.shape)\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(4, 1), padding='same')(up8)\n", " up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", " print('up9: ', up9.shape)\n", "\n", " # Decoder Spec\n", " time_up6 = layers.Conv1DTranspose(512, 5, strides=8, padding='same')(dual_up_time)\n", " time_up6 = layers.BatchNormalization()(time_up6)\n", " time_up6 = layers.ReLU()(time_up6)\n", " time_up6 = layers.Dropout(drop)(time_up6)\n", " time_up6 = layers.Concatenate()([time_up6, time_conv3])\n", " print('time_up6: ', time_up6.shape)\n", "\n", " time_up7 = layers.Conv1DTranspose(256, 5, strides=4, padding='same')(time_up6)\n", " time_up7 = layers.BatchNormalization()(time_up7)\n", " time_up7 = layers.ReLU()(time_up7)\n", " time_up7 = layers.Dropout(drop)(time_up7)\n", " time_up7 = layers.Concatenate()([time_up7, time_conv2])\n", " print('time_up7: ', time_up7.shape)\n", "\n", " time_up8 = layers.Conv1DTranspose(128, 5, strides=4, padding='same')(time_up7)\n", " time_up8 = layers.BatchNormalization()(time_up8)\n", " time_up8 = layers.ReLU()(time_up8)\n", " time_up8 = layers.Dropout(drop)(time_up8)\n", " time_up8 = layers.Concatenate()([time_up8, time_conv1])\n", " print('time_up8: ', time_up8.shape)\n", "\n", " time_up9 = layers.Conv1DTranspose(64, 5, strides=4, padding='same')(time_up8)\n", " time_up9 = layers.BatchNormalization()(time_up9)\n", " time_up9 = layers.ReLU()(time_up9)\n", " time_up9 = layers.Dropout(drop)(time_up9)\n", " #time_up9 = layers.Concatenate()([time_up9, time_conv1])\n", " print('time_up9: ', time_up9.shape)\n", "\n", " spect = spectrogram(time_up9)\n", " print('spect: ', spect.shape)\n", " #spect = tf.expand_dims(spect, axis=-1)\n", " print('spect expanded: ', spect.shape)\n", "\n", " y = layers.Add()([spect, up9])\n", " print('y: ', y.shape)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(1, 1), padding='same', activation='sigmoid')(y)\n", " #outputs = y\n", " print('outputs: ', outputs.shape)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "def build_dual_freq2(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", " print('Input: ', inputs.shape)\n", "\n", " inverse_spectrogram = InverseSpectrogramLayer()\n", " spectrogram = SpectrogramLayer()\n", "\n", " wave = inverse_spectrogram(inputs)\n", "\n", " # Encoder Spec\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(4, 1), padding='same')(inputs)\n", " #conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", " print('conv1: ', conv1.shape)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(4, 1), padding='same')(conv1)\n", " #conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", " print('conv2: ', conv2.shape)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(4, 1), padding='same')(conv2)\n", " #conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", " print('conv3: ', conv3.shape)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(8, 1), padding='same')(conv3)\n", " #conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", " print('conv4: ', conv4.shape)\n", "\n", " # Encoder Zeit\n", " time_conv1 = layers.Conv1D(64, 5, strides=4, padding='same')(wave)\n", " #time_conv1 = layers.BatchNormalization()(time_conv1)\n", " time_conv1 = layers.ReLU()(time_conv1)\n", " time_conv1 = layers.Dropout(drop)(time_conv1)\n", " print('time_conv1: ', time_conv1.shape)\n", "\n", " time_conv2 = layers.Conv1D(128, 5, strides=4, padding='same')(time_conv1)\n", " #time_conv2 = layers.BatchNormalization()(time_conv2)\n", " time_conv2 = layers.ReLU()(time_conv2)\n", " time_conv2 = layers.Dropout(drop)(time_conv2)\n", " print('time_conv2: ', time_conv2.shape)\n", "\n", " time_conv3 = layers.Conv1D(256, 5, strides=4, padding='same')(time_conv2)\n", " #time_conv3 = layers.BatchNormalization()(time_conv3)\n", " time_conv3 = layers.ReLU()(time_conv3)\n", " time_conv3 = layers.Dropout(drop)(time_conv3)\n", " print('time_conv3: ', time_conv3.shape)\n", "\n", " time_conv4 = layers.Conv1D(512, 5, strides=8, padding='same')(time_conv3)\n", " #time_conv4 = layers.BatchNormalization()(time_conv4)\n", " time_conv4 = layers.ReLU()(time_conv4)\n", " time_conv4 = layers.Dropout(drop)(time_conv4)\n", " print('time_conv4: ', time_conv4.shape)\n", "\n", " # Dual Core\n", " x = layers.Add()([conv4, time_conv4])\n", " print('x: ', x.shape)\n", "\n", " dual_conv = layers.Conv2D(1024, (5, 5), strides=(1, 2), padding='same')(x)\n", " #dual_conv = layers.BatchNormalization()(dual_conv)\n", " dual_conv = layers.ReLU()(dual_conv)\n", " dual_conv = layers.Dropout(drop)(dual_conv)\n", " print('dual_conv: ', dual_conv.shape)\n", " #dual_conv = layers.Reshape((64, 1024))(dual_conv) # Entfernt die unnötige Achse\n", " #print('dual_conv Reshape: ', dual_conv.shape)\n", "\n", " dual_up = layers.Conv2DTranspose(1024, (5, 5), strides=(1, 2), padding='same')(dual_conv)\n", " #dual_up = layers.BatchNormalization()(dual_up)\n", " dual_up = layers.ReLU()(dual_up)\n", " dual_up = layers.Dropout(drop)(dual_up)\n", " print('dual_up: ', dual_up.shape)\n", " dual_up_time = layers.Reshape((128, 1024))(dual_up) # Entfernt die unnötige Achse\n", " print('dual_up_time Reshape: ', dual_up_time.shape)\n", "\n", " # Decoder Spec\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(8, 1), padding='same')(dual_up)\n", " #up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv3])\n", " print('up6: ', up6.shape)\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(4, 1), padding='same')(up6)\n", " #up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv2])\n", " print('up7: ', up7.shape)\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(4, 1), padding='same')(up7)\n", " #up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv1])\n", " print('up8: ', up8.shape)\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(4, 1), padding='same')(up8)\n", " #up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", " print('up9: ', up9.shape)\n", "\n", " # Decoder Spec\n", " time_up6 = layers.Conv1DTranspose(512, 5, strides=8, padding='same')(dual_up_time)\n", " #time_up6 = layers.BatchNormalization()(time_up6)\n", " time_up6 = layers.ReLU()(time_up6)\n", " time_up6 = layers.Dropout(drop)(time_up6)\n", " time_up6 = layers.Concatenate()([time_up6, time_conv3])\n", " print('time_up6: ', time_up6.shape)\n", "\n", " time_up7 = layers.Conv1DTranspose(256, 5, strides=4, padding='same')(time_up6)\n", " #time_up7 = layers.BatchNormalization()(time_up7)\n", " time_up7 = layers.ReLU()(time_up7)\n", " time_up7 = layers.Dropout(drop)(time_up7)\n", " time_up7 = layers.Concatenate()([time_up7, time_conv2])\n", " print('time_up7: ', time_up7.shape)\n", "\n", " time_up8 = layers.Conv1DTranspose(128, 5, strides=4, padding='same')(time_up7)\n", " #time_up8 = layers.BatchNormalization()(time_up8)\n", " time_up8 = layers.ReLU()(time_up8)\n", " time_up8 = layers.Dropout(drop)(time_up8)\n", " time_up8 = layers.Concatenate()([time_up8, time_conv1])\n", " print('time_up8: ', time_up8.shape)\n", "\n", " time_up9 = layers.Conv1DTranspose(64, 5, strides=4, padding='same')(time_up8)\n", " #time_up9 = layers.BatchNormalization()(time_up9)\n", " time_up9 = layers.ReLU()(time_up9)\n", " time_up9 = layers.Dropout(drop)(time_up9)\n", " #time_up9 = layers.Concatenate()([time_up9, time_conv1])\n", " print('time_up9: ', time_up9.shape)\n", "\n", " spect = spectrogram(time_up9)\n", " print('spect: ', spect.shape)\n", " #spect = tf.expand_dims(spect, axis=-1)\n", " print('spect expanded: ', spect.shape)\n", "\n", " y = layers.Add()([spect, up9])\n", " print('y: ', y.shape)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(1, 1), padding='same', activation='sigmoid')(y)\n", " #outputs = y\n", " print('outputs: ', outputs.shape)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "\n", "def build_dual_freq_Gelu_linear2(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", " print('Input: ', inputs.shape)\n", "\n", " inverse_spectrogram = InverseSpectrogramLayer()\n", " spectrogram = SpectrogramLayer()\n", "\n", " wave = inverse_spectrogram(inputs)\n", "\n", " # Encoder Spec\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(4, 1), padding='same')(inputs)\n", " #conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.Activation(\"gelu\")(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", " print('conv1: ', conv1.shape)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(4, 1), padding='same')(conv1)\n", " #conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.Activation(\"gelu\")(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", " print('conv2: ', conv2.shape)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(4, 1), padding='same')(conv2)\n", " #conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.Activation(\"gelu\")(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", " print('conv3: ', conv3.shape)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(8, 1), padding='same')(conv3)\n", " #conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.Activation(\"gelu\")(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", " print('conv4: ', conv4.shape)\n", "\n", " # Encoder Zeit\n", " time_conv1 = layers.Conv1D(64, 5, strides=4, padding='same')(wave)\n", " #time_conv1 = layers.BatchNormalization()(time_conv1)\n", " time_conv1 = layers.Activation(\"gelu\")(time_conv1)\n", " time_conv1 = layers.Dropout(drop)(time_conv1)\n", " print('time_conv1: ', time_conv1.shape)\n", "\n", " time_conv2 = layers.Conv1D(128, 5, strides=4, padding='same')(time_conv1)\n", " #time_conv2 = layers.BatchNormalization()(time_conv2)\n", " time_conv2 = layers.Activation(\"gelu\")(time_conv2)\n", " time_conv2 = layers.Dropout(drop)(time_conv2)\n", " print('time_conv2: ', time_conv2.shape)\n", "\n", " time_conv3 = layers.Conv1D(256, 5, strides=4, padding='same')(time_conv2)\n", " #time_conv3 = layers.BatchNormalization()(time_conv3)\n", " time_conv3 = layers.Activation(\"gelu\")(time_conv3)\n", " time_conv3 = layers.Dropout(drop)(time_conv3)\n", " print('time_conv3: ', time_conv3.shape)\n", "\n", " time_conv4 = layers.Conv1D(512, 5, strides=8, padding='same')(time_conv3)\n", " #time_conv4 = layers.BatchNormalization()(time_conv4)\n", " time_conv4 = layers.Activation(\"gelu\")(time_conv4)\n", " time_conv4 = layers.Dropout(drop)(time_conv4)\n", " print('time_conv4: ', time_conv4.shape)\n", "\n", " # Dual Core\n", " x = layers.Add()([conv4, time_conv4])\n", " print('x: ', x.shape)\n", "\n", " dual_conv = layers.Conv2D(1024, (5, 5), strides=(1, 2), padding='same')(x)\n", " dual_conv = layers.BatchNormalization()(dual_conv)\n", " dual_conv = layers.Activation(\"gelu\")(dual_conv)\n", " dual_conv = layers.Dropout(drop)(dual_conv)\n", " print('dual_conv: ', dual_conv.shape)\n", " #dual_conv = layers.Reshape((64, 1024))(dual_conv) # Entfernt die unnötige Achse\n", " #print('dual_conv Reshape: ', dual_conv.shape)\n", "\n", " dual_up = layers.Conv2DTranspose(1024, (5, 5), strides=(1, 2), padding='same')(dual_conv)\n", " dual_up = layers.BatchNormalization()(dual_up)\n", " dual_up = layers.Activation(\"gelu\")(dual_up)\n", " dual_up = layers.Dropout(drop)(dual_up)\n", " print('dual_up: ', dual_up.shape)\n", " dual_up_time = layers.Reshape((128, 1024))(dual_up) # Entfernt die unnötige Achse\n", " print('dual_up_time Reshape: ', dual_up_time.shape)\n", "\n", " # Decoder Spec\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(8, 1), padding='same')(dual_up)\n", " #up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.Activation(\"gelu\")(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv3])\n", " print('up6: ', up6.shape)\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(4, 1), padding='same')(up6)\n", " #up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.Activation(\"gelu\")(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv2])\n", " print('up7: ', up7.shape)\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(4, 1), padding='same')(up7)\n", " #up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.Activation(\"gelu\")(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv1])\n", " print('up8: ', up8.shape)\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(4, 1), padding='same')(up8)\n", " #up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.Activation(\"gelu\")(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", " print('up9: ', up9.shape)\n", "\n", " # Decoder Spec\n", " time_up6 = layers.Conv1DTranspose(512, 5, strides=8, padding='same')(dual_up_time)\n", " #time_up6 = layers.BatchNormalization()(time_up6)\n", " time_up6 = layers.Activation(\"gelu\")(time_up6)\n", " time_up6 = layers.Dropout(drop)(time_up6)\n", " time_up6 = layers.Concatenate()([time_up6, time_conv3])\n", " print('time_up6: ', time_up6.shape)\n", "\n", " time_up7 = layers.Conv1DTranspose(256, 5, strides=4, padding='same')(time_up6)\n", " #time_up7 = layers.BatchNormalization()(time_up7)\n", " time_up7 = layers.Activation(\"gelu\")(time_up7)\n", " time_up7 = layers.Dropout(drop)(time_up7)\n", " time_up7 = layers.Concatenate()([time_up7, time_conv2])\n", " print('time_up7: ', time_up7.shape)\n", "\n", " time_up8 = layers.Conv1DTranspose(128, 5, strides=4, padding='same')(time_up7)\n", " #time_up8 = layers.BatchNormalization()(time_up8)\n", " time_up8 = layers.Activation(\"gelu\")(time_up8)\n", " time_up8 = layers.Dropout(drop)(time_up8)\n", " time_up8 = layers.Concatenate()([time_up8, time_conv1])\n", " print('time_up8: ', time_up8.shape)\n", "\n", " time_up9 = layers.Conv1DTranspose(64, 5, strides=4, padding='same')(time_up8)\n", " #time_up9 = layers.BatchNormalization()(time_up9)\n", " time_up9 = layers.Activation(\"gelu\")(time_up9)\n", " time_up9 = layers.Dropout(drop)(time_up9)\n", " #time_up9 = layers.Concatenate()([time_up9, time_conv1])\n", " print('time_up9: ', time_up9.shape)\n", "\n", " spect = spectrogram(time_up9)\n", " print('spect: ', spect.shape)\n", " #spect = tf.expand_dims(spect, axis=-1)\n", " print('spect expanded: ', spect.shape)\n", "\n", " y = layers.Add()([spect, up9])\n", " print('y: ', y.shape)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(1, 1), padding='same', activation='linear')(y)\n", " #outputs = y\n", " print('outputs: ', outputs.shape)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "\n", "def build_dual_freq_Gelu2(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", " print('Input: ', inputs.shape)\n", "\n", " inverse_spectrogram = InverseSpectrogramLayer()\n", " spectrogram = SpectrogramLayer()\n", "\n", " wave = inverse_spectrogram(inputs)\n", "\n", " # Encoder Spec\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(4, 1), padding='same')(inputs)\n", " #conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.Activation(\"gelu\")(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", " print('conv1: ', conv1.shape)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(4, 1), padding='same')(conv1)\n", " #conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.Activation(\"gelu\")(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", " print('conv2: ', conv2.shape)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(4, 1), padding='same')(conv2)\n", " #conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.Activation(\"gelu\")(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", " print('conv3: ', conv3.shape)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(8, 1), padding='same')(conv3)\n", " #conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.Activation(\"gelu\")(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", " print('conv4: ', conv4.shape)\n", "\n", " # Encoder Zeit\n", " time_conv1 = layers.Conv1D(64, 5, strides=4, padding='same')(wave)\n", " #time_conv1 = layers.BatchNormalization()(time_conv1)\n", " time_conv1 = layers.Activation(\"gelu\")(time_conv1)\n", " time_conv1 = layers.Dropout(drop)(time_conv1)\n", " print('time_conv1: ', time_conv1.shape)\n", "\n", " time_conv2 = layers.Conv1D(128, 5, strides=4, padding='same')(time_conv1)\n", " #time_conv2 = layers.BatchNormalization()(time_conv2)\n", " time_conv2 = layers.Activation(\"gelu\")(time_conv2)\n", " time_conv2 = layers.Dropout(drop)(time_conv2)\n", " print('time_conv2: ', time_conv2.shape)\n", "\n", " time_conv3 = layers.Conv1D(256, 5, strides=4, padding='same')(time_conv2)\n", " #time_conv3 = layers.BatchNormalization()(time_conv3)\n", " time_conv3 = layers.Activation(\"gelu\")(time_conv3)\n", " time_conv3 = layers.Dropout(drop)(time_conv3)\n", " print('time_conv3: ', time_conv3.shape)\n", "\n", " time_conv4 = layers.Conv1D(512, 5, strides=8, padding='same')(time_conv3)\n", " #time_conv4 = layers.BatchNormalization()(time_conv4)\n", " time_conv4 = layers.Activation(\"gelu\")(time_conv4)\n", " time_conv4 = layers.Dropout(drop)(time_conv4)\n", " print('time_conv4: ', time_conv4.shape)\n", "\n", " # Dual Core\n", " x = layers.Add()([conv4, time_conv4])\n", " print('x: ', x.shape)\n", "\n", " dual_conv = layers.Conv2D(1024, (5, 5), strides=(1, 2), padding='same')(x)\n", " dual_conv = layers.BatchNormalization()(dual_conv)\n", " dual_conv = layers.Activation(\"gelu\")(dual_conv)\n", " dual_conv = layers.Dropout(drop)(dual_conv)\n", " print('dual_conv: ', dual_conv.shape)\n", " #dual_conv = layers.Reshape((64, 1024))(dual_conv) # Entfernt die unnötige Achse\n", " #print('dual_conv Reshape: ', dual_conv.shape)\n", "\n", " dual_up = layers.Conv2DTranspose(1024, (5, 5), strides=(1, 2), padding='same')(dual_conv)\n", " dual_up = layers.BatchNormalization()(dual_up)\n", " dual_up = layers.Activation(\"gelu\")(dual_up)\n", " dual_up = layers.Dropout(drop)(dual_up)\n", " print('dual_up: ', dual_up.shape)\n", " dual_up_time = layers.Reshape((128, 1024))(dual_up) # Entfernt die unnötige Achse\n", " print('dual_up_time Reshape: ', dual_up_time.shape)\n", "\n", " # Decoder Spec\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(8, 1), padding='same')(dual_up)\n", " #up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.Activation(\"gelu\")(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv3])\n", " print('up6: ', up6.shape)\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(4, 1), padding='same')(up6)\n", " #up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.Activation(\"gelu\")(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv2])\n", " print('up7: ', up7.shape)\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(4, 1), padding='same')(up7)\n", " #up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.Activation(\"gelu\")(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv1])\n", " print('up8: ', up8.shape)\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(4, 1), padding='same')(up8)\n", " #up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.Activation(\"gelu\")(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", " print('up9: ', up9.shape)\n", "\n", " # Decoder Spec\n", " time_up6 = layers.Conv1DTranspose(512, 5, strides=8, padding='same')(dual_up_time)\n", " #time_up6 = layers.BatchNormalization()(time_up6)\n", " time_up6 = layers.Activation(\"gelu\")(time_up6)\n", " time_up6 = layers.Dropout(drop)(time_up6)\n", " time_up6 = layers.Concatenate()([time_up6, time_conv3])\n", " print('time_up6: ', time_up6.shape)\n", "\n", " time_up7 = layers.Conv1DTranspose(256, 5, strides=4, padding='same')(time_up6)\n", " #time_up7 = layers.BatchNormalization()(time_up7)\n", " time_up7 = layers.Activation(\"gelu\")(time_up7)\n", " time_up7 = layers.Dropout(drop)(time_up7)\n", " time_up7 = layers.Concatenate()([time_up7, time_conv2])\n", " print('time_up7: ', time_up7.shape)\n", "\n", " time_up8 = layers.Conv1DTranspose(128, 5, strides=4, padding='same')(time_up7)\n", " #time_up8 = layers.BatchNormalization()(time_up8)\n", " time_up8 = layers.Activation(\"gelu\")(time_up8)\n", " time_up8 = layers.Dropout(drop)(time_up8)\n", " time_up8 = layers.Concatenate()([time_up8, time_conv1])\n", " print('time_up8: ', time_up8.shape)\n", "\n", " time_up9 = layers.Conv1DTranspose(64, 5, strides=4, padding='same')(time_up8)\n", " #time_up9 = layers.BatchNormalization()(time_up9)\n", " time_up9 = layers.Activation(\"gelu\")(time_up9)\n", " time_up9 = layers.Dropout(drop)(time_up9)\n", " #time_up9 = layers.Concatenate()([time_up9, time_conv1])\n", " print('time_up9: ', time_up9.shape)\n", "\n", " spect = spectrogram(time_up9)\n", " print('spect: ', spect.shape)\n", " #spect = tf.expand_dims(spect, axis=-1)\n", " print('spect expanded: ', spect.shape)\n", "\n", " y = layers.Add()([spect, up9])\n", " print('y: ', y.shape)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(1, 1), padding='same', activation='sigmoid')(y)\n", " #outputs = y\n", " print('outputs: ', outputs.shape)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "def build_dual_freq_Gelu_linear_time(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", " print('Input: ', inputs.shape)\n", "\n", " inverse_spectrogram = InverseSpectrogramLayer()\n", " spectrogram = SpectrogramLayer()\n", "\n", " wave = inverse_spectrogram(inputs)\n", "\n", " # Encoder Spec\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(4, 1), padding='same')(inputs)\n", " #conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.Activation(\"gelu\")(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", " print('conv1: ', conv1.shape)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(4, 1), padding='same')(conv1)\n", " #conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.Activation(\"gelu\")(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", " print('conv2: ', conv2.shape)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(4, 1), padding='same')(conv2)\n", " #conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.Activation(\"gelu\")(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", " print('conv3: ', conv3.shape)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(8, 1), padding='same')(conv3)\n", " #conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.Activation(\"gelu\")(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", " print('conv4: ', conv4.shape)\n", "\n", " # Encoder Zeit\n", " time_conv1 = layers.Conv1D(64, 5, strides=4, padding='same')(wave)\n", " #time_conv1 = layers.BatchNormalization()(time_conv1)\n", " time_conv1 = layers.Activation(\"gelu\")(time_conv1)\n", " time_conv1 = layers.Dropout(drop)(time_conv1)\n", " print('time_conv1: ', time_conv1.shape)\n", "\n", " time_conv2 = layers.Conv1D(128, 5, strides=4, padding='same')(time_conv1)\n", " #time_conv2 = layers.BatchNormalization()(time_conv2)\n", " time_conv2 = layers.Activation(\"gelu\")(time_conv2)\n", " time_conv2 = layers.Dropout(drop)(time_conv2)\n", " print('time_conv2: ', time_conv2.shape)\n", "\n", " time_conv3 = layers.Conv1D(256, 5, strides=4, padding='same')(time_conv2)\n", " #time_conv3 = layers.BatchNormalization()(time_conv3)\n", " time_conv3 = layers.Activation(\"gelu\")(time_conv3)\n", " time_conv3 = layers.Dropout(drop)(time_conv3)\n", " print('time_conv3: ', time_conv3.shape)\n", "\n", " time_conv4 = layers.Conv1D(512, 5, strides=8, padding='same')(time_conv3)\n", " #time_conv4 = layers.BatchNormalization()(time_conv4)\n", " time_conv4 = layers.Activation(\"gelu\")(time_conv4)\n", " time_conv4 = layers.Dropout(drop)(time_conv4)\n", " print('time_conv4: ', time_conv4.shape)\n", "\n", " # Dual Core\n", " x = layers.Add()([conv4, time_conv4])\n", " print('x: ', x.shape)\n", "\n", " dual_conv = layers.Conv2D(1024, (5, 5), strides=(1, 2), padding='same')(x)\n", " dual_conv = layers.BatchNormalization()(dual_conv)\n", " dual_conv = layers.Activation(\"gelu\")(dual_conv)\n", " dual_conv = layers.Dropout(drop)(dual_conv)\n", " print('dual_conv: ', dual_conv.shape)\n", " #dual_conv = layers.Reshape((64, 1024))(dual_conv) # Entfernt die unnötige Achse\n", " #print('dual_conv Reshape: ', dual_conv.shape)\n", "\n", " dual_up = layers.Conv2DTranspose(1024, (5, 5), strides=(1, 2), padding='same')(dual_conv)\n", " dual_up = layers.BatchNormalization()(dual_up)\n", " dual_up = layers.Activation(\"gelu\")(dual_up)\n", " dual_up = layers.Dropout(drop)(dual_up)\n", " print('dual_up: ', dual_up.shape)\n", " dual_up_time = layers.Reshape((128, 1024))(dual_up) # Entfernt die unnötige Achse\n", " print('dual_up_time Reshape: ', dual_up_time.shape)\n", "\n", " # Decoder Spec\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(8, 1), padding='same')(dual_up)\n", " #up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.Activation(\"gelu\")(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv3])\n", " print('up6: ', up6.shape)\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(4, 1), padding='same')(up6)\n", " #up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.Activation(\"gelu\")(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv2])\n", " print('up7: ', up7.shape)\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(4, 1), padding='same')(up7)\n", " #up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.Activation(\"gelu\")(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv1])\n", " print('up8: ', up8.shape)\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(4, 1), padding='same')(up8)\n", " #up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.Activation(\"gelu\")(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", " print('up9: ', up9.shape)\n", "\n", " # Decoder Spec\n", " time_up6 = layers.Conv1DTranspose(512, 5, strides=8, padding='same')(dual_up_time)\n", " #time_up6 = layers.BatchNormalization()(time_up6)\n", " time_up6 = layers.Activation(\"gelu\")(time_up6)\n", " time_up6 = layers.Dropout(drop)(time_up6)\n", " time_up6 = layers.Concatenate()([time_up6, time_conv3])\n", " print('time_up6: ', time_up6.shape)\n", "\n", " time_up7 = layers.Conv1DTranspose(256, 5, strides=4, padding='same')(time_up6)\n", " #time_up7 = layers.BatchNormalization()(time_up7)\n", " time_up7 = layers.Activation(\"gelu\")(time_up7)\n", " time_up7 = layers.Dropout(drop)(time_up7)\n", " time_up7 = layers.Concatenate()([time_up7, time_conv2])\n", " print('time_up7: ', time_up7.shape)\n", "\n", " time_up8 = layers.Conv1DTranspose(128, 5, strides=4, padding='same')(time_up7)\n", " #time_up8 = layers.BatchNormalization()(time_up8)\n", " time_up8 = layers.Activation(\"gelu\")(time_up8)\n", " time_up8 = layers.Dropout(drop)(time_up8)\n", " time_up8 = layers.Concatenate()([time_up8, time_conv1])\n", " print('time_up8: ', time_up8.shape)\n", "\n", " time_up9 = layers.Conv1DTranspose(64, 5, strides=4, padding='same')(time_up8)\n", " #time_up9 = layers.BatchNormalization()(time_up9)\n", " time_up9 = layers.Activation(\"gelu\")(time_up9)\n", " time_up9 = layers.Dropout(drop)(time_up9)\n", " #time_up9 = layers.Concatenate()([time_up9, time_conv1])\n", " print('time_up9: ', time_up9.shape)\n", "\n", " #spect = spectrogram(time_up9)\n", " #print('spect: ', spect.shape)\n", " #spect = tf.expand_dims(spect, axis=-1)\n", " #print('spect expanded: ', spect.shape)\n", "\n", " wave_9 = inverse_spectrogram(up9)\n", " print('wave_9: ', wave_9.shape)\n", "\n", " y = layers.Add()([time_up9, wave_9])\n", " print('y: ', y.shape)\n", "\n", " y_spec = spectrogram(y)\n", " print('y_spec: ', y_spec.shape)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(1, 1), padding='same', activation='linear')(y_spec)\n", " #outputs = y\n", " print('outputs: ', outputs.shape)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "\n", "# Modell erstellen\n", "model = build_dual_freq_Gelu_linear_time()\n", "model.summary()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model: \"model_1\"\n", "__________________________________________________________________________________________________\n", " Layer (type) Output Shape Param # Connected to \n", "==================================================================================================\n", " input_2 (InputLayer) [(None, 512, 128, 1 0 [] \n", " )] \n", " \n", " conv2d_5 (Conv2D) (None, 256, 64, 64) 1664 ['input_2[0][0]'] \n", " \n", " batch_normalization_18 (BatchN (None, 256, 64, 64) 256 ['conv2d_5[0][0]'] \n", " ormalization) \n", " \n", " re_lu_18 (ReLU) (None, 256, 64, 64) 0 ['batch_normalization_18[0][0]'] \n", " \n", " dropout_18 (Dropout) (None, 256, 64, 64) 0 ['re_lu_18[0][0]'] \n", " \n", " conv2d_6 (Conv2D) (None, 128, 32, 128 204928 ['dropout_18[0][0]'] \n", " ) \n", " \n", " batch_normalization_19 (BatchN (None, 128, 32, 128 512 ['conv2d_6[0][0]'] \n", " ormalization) ) \n", " \n", " re_lu_19 (ReLU) (None, 128, 32, 128 0 ['batch_normalization_19[0][0]'] \n", " ) \n", " \n", " dropout_19 (Dropout) (None, 128, 32, 128 0 ['re_lu_19[0][0]'] \n", " ) \n", " \n", " conv2d_7 (Conv2D) (None, 64, 16, 256) 819456 ['dropout_19[0][0]'] \n", " \n", " batch_normalization_20 (BatchN (None, 64, 16, 256) 1024 ['conv2d_7[0][0]'] \n", " ormalization) \n", " \n", " re_lu_20 (ReLU) (None, 64, 16, 256) 0 ['batch_normalization_20[0][0]'] \n", " \n", " dropout_20 (Dropout) (None, 64, 16, 256) 0 ['re_lu_20[0][0]'] \n", " \n", " conv2d_8 (Conv2D) (None, 32, 8, 512) 3277312 ['dropout_20[0][0]'] \n", " \n", " batch_normalization_21 (BatchN (None, 32, 8, 512) 2048 ['conv2d_8[0][0]'] \n", " ormalization) \n", " \n", " re_lu_21 (ReLU) (None, 32, 8, 512) 0 ['batch_normalization_21[0][0]'] \n", " \n", " dropout_21 (Dropout) (None, 32, 8, 512) 0 ['re_lu_21[0][0]'] \n", " \n", " conv2d_9 (Conv2D) (None, 16, 4, 1024) 13108224 ['dropout_21[0][0]'] \n", " \n", " batch_normalization_22 (BatchN (None, 16, 4, 1024) 4096 ['conv2d_9[0][0]'] \n", " ormalization) \n", " \n", " re_lu_22 (ReLU) (None, 16, 4, 1024) 0 ['batch_normalization_22[0][0]'] \n", " \n", " dropout_22 (Dropout) (None, 16, 4, 1024) 0 ['re_lu_22[0][0]'] \n", " \n", " conv2d_transpose_6 (Conv2DTran (None, 32, 8, 512) 13107712 ['dropout_22[0][0]'] \n", " spose) \n", " \n", " batch_normalization_23 (BatchN (None, 32, 8, 512) 2048 ['conv2d_transpose_6[0][0]'] \n", " ormalization) \n", " \n", " re_lu_23 (ReLU) (None, 32, 8, 512) 0 ['batch_normalization_23[0][0]'] \n", " \n", " dropout_23 (Dropout) (None, 32, 8, 512) 0 ['re_lu_23[0][0]'] \n", " \n", " concatenate_6 (Concatenate) (None, 32, 8, 1024) 0 ['dropout_23[0][0]', \n", " 'dropout_21[0][0]'] \n", " \n", " conv2d_transpose_7 (Conv2DTran (None, 64, 16, 256) 6553856 ['concatenate_6[0][0]'] \n", " spose) \n", " \n", " batch_normalization_24 (BatchN (None, 64, 16, 256) 1024 ['conv2d_transpose_7[0][0]'] \n", " ormalization) \n", " \n", " re_lu_24 (ReLU) (None, 64, 16, 256) 0 ['batch_normalization_24[0][0]'] \n", " \n", " dropout_24 (Dropout) (None, 64, 16, 256) 0 ['re_lu_24[0][0]'] \n", " \n", " concatenate_7 (Concatenate) (None, 64, 16, 512) 0 ['dropout_24[0][0]', \n", " 'dropout_20[0][0]'] \n", " \n", " conv2d_transpose_8 (Conv2DTran (None, 128, 32, 128 1638528 ['concatenate_7[0][0]'] \n", " spose) ) \n", " \n", " batch_normalization_25 (BatchN (None, 128, 32, 128 512 ['conv2d_transpose_8[0][0]'] \n", " ormalization) ) \n", " \n", " re_lu_25 (ReLU) (None, 128, 32, 128 0 ['batch_normalization_25[0][0]'] \n", " ) \n", " \n", " dropout_25 (Dropout) (None, 128, 32, 128 0 ['re_lu_25[0][0]'] \n", " ) \n", " \n", " concatenate_8 (Concatenate) (None, 128, 32, 256 0 ['dropout_25[0][0]', \n", " ) 'dropout_19[0][0]'] \n", " \n", " conv2d_transpose_9 (Conv2DTran (None, 256, 64, 64) 409664 ['concatenate_8[0][0]'] \n", " spose) \n", " \n", " batch_normalization_26 (BatchN (None, 256, 64, 64) 256 ['conv2d_transpose_9[0][0]'] \n", " ormalization) \n", " \n", " re_lu_26 (ReLU) (None, 256, 64, 64) 0 ['batch_normalization_26[0][0]'] \n", " \n", " dropout_26 (Dropout) (None, 256, 64, 64) 0 ['re_lu_26[0][0]'] \n", " \n", " concatenate_9 (Concatenate) (None, 256, 64, 128 0 ['dropout_26[0][0]', \n", " ) 'dropout_18[0][0]'] \n", " \n", " conv2d_transpose_10 (Conv2DTra (None, 512, 128, 1) 3201 ['concatenate_9[0][0]'] \n", " nspose) \n", " \n", "==================================================================================================\n", "Total params: 39,136,321\n", "Trainable params: 39,130,433\n", "Non-trainable params: 5,888\n", "__________________________________________________________________________________________________\n" ] } ], "source": [ "def build_masking_network(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", "\n", " # Encoder\n", " x = layers.Conv2D(64, (5, 5), strides=(2, 2), padding=\"same\")(inputs)\n", " x = layers.BatchNormalization()(x)\n", " x = layers.ReLU()(x)\n", "\n", " x = layers.Conv2D(128, (5, 5), strides=(2, 2), padding=\"same\")(x)\n", " x = layers.BatchNormalization()(x)\n", " x = layers.ReLU()(x)\n", "\n", " x = layers.Conv2D(256, (5, 5), strides=(2, 2), padding=\"same\")(x)\n", " x = layers.BatchNormalization()(x)\n", " x = layers.ReLU()(x)\n", "\n", " # Decoder\n", " x = layers.Conv2DTranspose(128, (5, 5), strides=(2, 2), padding=\"same\")(x)\n", " x = layers.BatchNormalization()(x)\n", " x = layers.ReLU()(x)\n", "\n", " x = layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding=\"same\")(x)\n", " x = layers.BatchNormalization()(x)\n", " x = layers.ReLU()(x)\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', activation='sigmoid')(x) # Maske zwischen 0 und 1\n", " model = models.Model(inputs, outputs)\n", " return model\n", "\n", "def build_unet(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", "\n", " # Encoder\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same')(inputs)\n", " conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " conv1 = layers.Dropout(0.5)(conv1)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same')(conv1)\n", " conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " conv2 = layers.Dropout(0.5)(conv2)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(2, 2), padding='same')(conv2)\n", " conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " conv3 = layers.Dropout(0.5)(conv3)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(2, 2), padding='same')(conv3)\n", " conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", "\n", " conv5 = layers.Conv2D(1024, (5, 5), strides=(2, 2), padding='same')(conv4)\n", " conv5 = layers.BatchNormalization()(conv5)\n", " conv5 = layers.ReLU()(conv5)\n", "\n", " # Decoder\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(2, 2), padding='same')(conv5)\n", " up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " up6 = layers.Concatenate()([up6, conv4])\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(2, 2), padding='same')(up6)\n", " up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " up7 = layers.Concatenate()([up7, conv3])\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(2, 2), padding='same')(up7)\n", " up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " up8 = layers.Concatenate()([up8, conv2])\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same')(up8)\n", " up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " up9 = layers.Concatenate()([up9, conv1])\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', activation='sigmoid')(up9)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "def build_autoencoder(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", "\n", " # Encoder\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same')(inputs)\n", " conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " #conv1 = layers.Dropout(0.5)(conv1)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same')(conv1)\n", " conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " #conv2 = layers.Dropout(0.5)(conv2)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(2, 2), padding='same')(conv2)\n", " conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " #conv3 = layers.Dropout(0.5)(conv3)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(2, 2), padding='same')(conv3)\n", " conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", "\n", " conv5 = layers.Conv2D(1024, (5, 5), strides=(2, 2), padding='same')(conv4)\n", " conv5 = layers.BatchNormalization()(conv5)\n", " conv5 = layers.ReLU()(conv5)\n", "\n", " # Decoder\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(2, 2), padding='same')(conv5)\n", " up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " #up6 = layers.Concatenate()([up6, conv4])\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(2, 2), padding='same')(up6)\n", " up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " #up7 = layers.Concatenate()([up7, conv3])\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(2, 2), padding='same')(up7)\n", " up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " #up8 = layers.Concatenate()([up8, conv2])\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same')(up8)\n", " up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " #up9 = layers.Concatenate()([up9, conv1])\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', activation='sigmoid')(up9)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "def build_unet2(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", "\n", " # Encoder\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same')(inputs)\n", " conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " conv1 = layers.Dropout(0.5)(conv1)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same')(conv1)\n", " conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " conv2 = layers.Dropout(0.5)(conv2)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(2, 2), padding='same')(conv2)\n", " conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " conv3 = layers.Dropout(0.5)(conv3)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(2, 2), padding='same')(conv3)\n", " conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", " conv4 = layers.Dropout(0.5)(conv4)\n", "\n", " conv5 = layers.Conv2D(1024, (5, 5), strides=(2, 2), padding='same')(conv4)\n", " conv5 = layers.BatchNormalization()(conv5)\n", " conv5 = layers.ReLU()(conv5)\n", " conv5 = layers.Dropout(0.5)(conv5)\n", "\n", " # Decoder\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(2, 2), padding='same')(conv5)\n", " up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " up6 = layers.Dropout(0.5)(up6)\n", " up6 = layers.Concatenate()([up6, conv4])\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(2, 2), padding='same')(up6)\n", " up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " up7 = layers.Dropout(0.5)(up7)\n", " up7 = layers.Concatenate()([up7, conv3])\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(2, 2), padding='same')(up7)\n", " up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " up8 = layers.Dropout(0.5)(up8)\n", " up8 = layers.Concatenate()([up8, conv2])\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same')(up8)\n", " up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " up9 = layers.Dropout(0.5)(up9)\n", " up9 = layers.Concatenate()([up9, conv1])\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', activation='sigmoid')(up9)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "drop = 0.45\n", "\n", "def build_unet3(input_shape=(512, 128, 1)):\n", " inputs = tf.keras.Input(shape=input_shape)\n", "\n", " # Encoder\n", " conv1 = layers.Conv2D(64, (5, 5), strides=(2, 2), padding='same')(inputs)\n", " conv1 = layers.BatchNormalization()(conv1)\n", " conv1 = layers.ReLU()(conv1)\n", " conv1 = layers.Dropout(drop)(conv1)\n", "\n", " conv2 = layers.Conv2D(128, (5, 5), strides=(2, 2), padding='same')(conv1)\n", " conv2 = layers.BatchNormalization()(conv2)\n", " conv2 = layers.ReLU()(conv2)\n", " conv2 = layers.Dropout(drop)(conv2)\n", "\n", " conv3 = layers.Conv2D(256, (5, 5), strides=(2, 2), padding='same')(conv2)\n", " conv3 = layers.BatchNormalization()(conv3)\n", " conv3 = layers.ReLU()(conv3)\n", " conv3 = layers.Dropout(drop)(conv3)\n", "\n", " conv4 = layers.Conv2D(512, (5, 5), strides=(2, 2), padding='same')(conv3)\n", " conv4 = layers.BatchNormalization()(conv4)\n", " conv4 = layers.ReLU()(conv4)\n", " conv4 = layers.Dropout(drop)(conv4)\n", "\n", " conv5 = layers.Conv2D(1024, (5, 5), strides=(2, 2), padding='same')(conv4)\n", " conv5 = layers.BatchNormalization()(conv5)\n", " conv5 = layers.ReLU()(conv5)\n", " conv5 = layers.Dropout(drop)(conv5)\n", "\n", " # Decoder\n", " up6 = layers.Conv2DTranspose(512, (5, 5), strides=(2, 2), padding='same')(conv5)\n", " up6 = layers.BatchNormalization()(up6)\n", " up6 = layers.ReLU()(up6)\n", " up6 = layers.Dropout(drop)(up6)\n", " up6 = layers.Concatenate()([up6, conv4])\n", "\n", " up7 = layers.Conv2DTranspose(256, (5, 5), strides=(2, 2), padding='same')(up6)\n", " up7 = layers.BatchNormalization()(up7)\n", " up7 = layers.ReLU()(up7)\n", " up7 = layers.Dropout(drop)(up7)\n", " up7 = layers.Concatenate()([up7, conv3])\n", "\n", " up8 = layers.Conv2DTranspose(128, (5, 5), strides=(2, 2), padding='same')(up7)\n", " up8 = layers.BatchNormalization()(up8)\n", " up8 = layers.ReLU()(up8)\n", " up8 = layers.Dropout(drop)(up8)\n", " up8 = layers.Concatenate()([up8, conv2])\n", "\n", " up9 = layers.Conv2DTranspose(64, (5, 5), strides=(2, 2), padding='same')(up8)\n", " up9 = layers.BatchNormalization()(up9)\n", " up9 = layers.ReLU()(up9)\n", " up9 = layers.Dropout(drop)(up9)\n", " up9 = layers.Concatenate()([up9, conv1])\n", "\n", " outputs = layers.Conv2DTranspose(1, (5, 5), strides=(2, 2), padding='same', activation='sigmoid')(up9)\n", "\n", " model = tf.keras.Model(inputs, outputs)\n", " return model\n", "\n", "\n", "# Modell erstellen\n", "model = build_unet3()\n", "model.summary()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "# Beispiel: Mean Squared Error Loss\n", "def custom_loss(y_true, y_pred):\n", " return tf.reduce_mean(tf.square(y_true - y_pred))\n", "\n", "def mae_loss(y_true, y_pred):\n", " return tf.reduce_mean(tf.abs(y_true - y_pred))\n", "\n", "def snr_metric(vocals, y_pred):\n", " \n", " signal_power = tf.reduce_sum(vocals**2)\n", " noise_power = tf.reduce_sum((vocals - y_pred)**2)\n", " return 10 * tf.math.log(signal_power / (noise_power)) / tf.math.log(10.0)\n", "\n", "def mae_loss_mask(y_true, y_pred, mixture):\n", " after_mask = y_pred * mixture\n", " return tf.reduce_mean(tf.abs(y_true - after_mask))\n", "\n", "def snr_metric_mask(vocals, y_pred, mixture):\n", " after_mask = y_pred * mixture\n", " signal_power = tf.reduce_sum(vocals**2)\n", " noise_power = tf.reduce_sum((vocals - after_mask)**2)\n", " return 10 * tf.math.log(signal_power / (noise_power)) / tf.math.log(10.0)\n", "\n", "def combined_loss(y_true, y_pred, mixture):\n", " # SNR-Berechnung\n", " after_mask = y_pred * mixture\n", " signal_power = tf.reduce_sum(y_true ** 2)\n", " noise_power = tf.reduce_sum((y_true - after_mask) ** 2) \n", "\n", " # Numerische Stabilität hinzufügen\n", " #signal_power += 1e-8\n", " #noise_power += 1e-8\n", "\n", " snr_loss = -10 * tf.math.log(signal_power / noise_power) / tf.math.log(10.0)\n", "\n", " # Zusätzliche MSE-Komponente\n", " mse_loss = tf.reduce_mean(tf.square(y_true - after_mask))\n", "\n", " # Kombinierter Verlust \n", " return snr_loss + 0.1 * mse_loss # Gewichtung anpassen" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "import tensorflow.signal as tf_signal\n", "\n", "def postprocess_simple(after):\n", " n_fft = 512\n", " hop_length = 128\n", " win_length = 512\n", " after_resized = tf.image.resize(after, (257, 1723))\n", "\n", " after_resized = np.squeeze(after_resized, axis=-1)\n", "\n", " #after_resized = after_resized.numpy()\n", "\n", " #after_resized = after_resized * original_max_amplitude\n", "\n", " #complex_spectrogram = after_resized * np.exp(1j * phase)\n", " stft_complex = tf.complex(after_resized, tf.zeros_like(after_resized)) \n", " #print(stft_complex.shape)\n", " #audio_reconstructed = librosa.istft(stft_complex, hop_length=hop_length, win_length=win_length)\n", " waveform = tf_signal.inverse_stft(stft_complex, frame_length=512, frame_step=128, fft_length=512, window_fn=tf_signal.hann_window)\n", " #audio_reconstructed = librosa.griffinlim(complex_spectrogram, hop_length=hop_length, win_length=win_length)\n", " return waveform\n", "\n", "\n", "\n", "def combined_freq_time_loss_mask(y_true, y_pred, mixture):\n", " result = y_pred * mixture\n", "\n", " time_true = postprocess_simple(y_true)\n", " time_result = postprocess_simple(result)\n", " \n", " freq_loss = tf.reduce_mean(tf.abs(y_true - result))\n", " time_loss = tf.reduce_mean(tf.abs(time_true - time_result))\n", " \n", " return freq_loss + time_loss\n", "\n", "def combined_freq_time_metric_mask(y_true, y_pred, mixture):\n", " result = y_pred * mixture\n", "\n", " signal_power = tf.reduce_sum(y_true**2)\n", " noise_power = tf.reduce_sum((y_true - result)**2)\n", "\n", " freq_snr = 10 * tf.math.log(signal_power / (noise_power)) / tf.math.log(10.0)\n", "\n", " time_true = postprocess_simple(y_true)\n", " time_result = postprocess_simple(result)\n", "\n", " time_signal_power = tf.reduce_sum(time_true**2)\n", " time_noise_power = tf.reduce_sum((time_true - time_result)**2)\n", "\n", " time_snr = 10 * tf.math.log(time_signal_power / (time_noise_power)) / tf.math.log(10.0)\n", "\n", "\n", " return (freq_snr + time_snr) / 2\n" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input: (None, 512, 128, 1)\n", "conv1: (None, 128, 128, 64)\n", "conv2: (None, 32, 128, 128)\n", "conv3: (None, 8, 128, 256)\n", "conv4: (None, 1, 128, 512)\n", "time_conv1: (None, 16384, 64)\n", "time_conv2: (None, 4096, 128)\n", "time_conv3: (None, 1024, 256)\n", "time_conv4: (None, 128, 512)\n", "x: (None, 1, 128, 512)\n", "dual_conv: (None, 1, 64, 1024)\n", "dual_up: (None, 1, 128, 1024)\n", "dual_up_time Reshape: (None, 128, 1024)\n", "up6: (None, 8, 128, 768)\n", "up7: (None, 32, 128, 384)\n", "up8: (None, 128, 128, 192)\n", "up9: (None, 512, 128, 64)\n", "time_up6: (None, 1024, 768)\n", "time_up7: (None, 4096, 384)\n", "time_up8: (None, 16384, 192)\n", "time_up9: (None, 65536, 64)\n", "spect: (None, 512, 128, 1)\n", "spect expanded: (None, 512, 128, 1)\n", "y: (None, 512, 128, 64)\n", "outputs: (None, 512, 128, 1)\n" ] } ], "source": [ "# 1\n", "\n", "#model = build_unet()\n", "#model1 = build_unet3()\n", "#model = build_autoencoder()\n", "#model = build_masking_network()\n", "#model1 = build_dual_freq()\n", "#model1 = build_dual_freq_Gelu_linear2()\n", "model1 = build_dual_freq_Gelu2()\n", "\n", "history1 = {\n", " \"train_loss\": [],\n", " \"train_snr\": [],\n", " \"val_loss\": [],\n", " \"val_snr\": []\n", "}\n", "\n", "with zipfile.ZipFile('E:\\\\Projektarbeit\\\\Tests\\\\Mid_Dual_Training_03_21_Epoche=5_SNR=3.1649.zip', 'r') as zipf:\n", " zipf.extractall() # Entpackt alle Dateien\n", "\n", " # Lade die Arrays\n", " train_loss = np.load('train_loss.npy', allow_pickle=True)\n", " train_snr = np.load('train_snr.npy', allow_pickle=True)\n", " val_loss = np.load('val_loss.npy', allow_pickle=True)\n", " val_snr = np.load('val_snr.npy', allow_pickle=True)\n", "\n", " meta_parameter = np.load('meta_parameter.npy', allow_pickle=True)\n", " \n", "history1 = {\n", " \"train_loss\": [],\n", " \"train_snr\": [],\n", " \"val_loss\": [],\n", " \"val_snr\": []\n", "}\n", "\n", "adjusted_learning_rate = meta_parameter[0]\n", "epoch_start = int(meta_parameter[1]) + 1\n", "\n", "for i in range(0, epoch_start):\n", " history1[\"train_loss\"].append(train_loss[i])\n", " history1[\"train_snr\"].append(train_snr[i])\n", " history1[\"val_loss\"].append(val_loss[i])\n", " history1[\"val_snr\"].append(val_snr[i])\n", "\n", "model1.load_weights(\"model_training.h5\")\n", "\n", "os.remove('train_loss.npy')\n", "os.remove('train_snr.npy')\n", "os.remove('val_loss.npy')\n", "os.remove('val_snr.npy')\n", "\n", "os.remove('meta_parameter.npy')\n", "os.remove('model_training.h5')" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Input: (None, 512, 128, 1)\n", "conv1: (None, 128, 128, 64)\n", "conv2: (None, 32, 128, 128)\n", "conv3: (None, 8, 128, 256)\n", "conv4: (None, 1, 128, 512)\n", "time_conv1: (None, 16384, 64)\n", "time_conv2: (None, 4096, 128)\n", "time_conv3: (None, 1024, 256)\n", "time_conv4: (None, 128, 512)\n", "x: (None, 1, 128, 512)\n", "dual_conv: (None, 1, 64, 1024)\n", "dual_up: (None, 1, 128, 1024)\n", "dual_up_time Reshape: (None, 128, 1024)\n", "up6: (None, 8, 128, 768)\n", "up7: (None, 32, 128, 384)\n", "up8: (None, 128, 128, 192)\n", "up9: (None, 512, 128, 64)\n", "time_up6: (None, 1024, 768)\n", "time_up7: (None, 4096, 384)\n", "time_up8: (None, 16384, 192)\n", "time_up9: (None, 65536, 64)\n", "spect: (None, 512, 128, 1)\n", "spect expanded: (None, 512, 128, 1)\n", "y: (None, 512, 128, 64)\n", "outputs: (None, 512, 128, 1)\n" ] } ], "source": [ "# 2\n", "\n", "#model = build_unet()\n", "#model = build_unet3()\n", "#model = build_autoencoder()\n", "#model = build_masking_network()\n", "#model2 = build_dual_freq()\n", "model2 = build_dual_freq()\n", "\n", "history2 = {\n", " \"train_loss\": [],\n", " \"train_snr\": [],\n", " \"val_loss\": [],\n", " \"val_snr\": []\n", "}\n", "\n", "with zipfile.ZipFile('E:\\\\Projektarbeit\\\\Training\\\\Mid_Dual_Training_03_11_Epoche=17_SNR=3.6846.zip', 'r') as zipf:\n", " zipf.extractall() # Entpackt alle Dateien\n", "\n", " # Lade die Arrays\n", " train_loss = np.load('train_loss.npy', allow_pickle=True)\n", " train_snr = np.load('train_snr.npy', allow_pickle=True)\n", " val_loss = np.load('val_loss.npy', allow_pickle=True)\n", " val_snr = np.load('val_snr.npy', allow_pickle=True)\n", "\n", " meta_parameter = np.load('meta_parameter.npy', allow_pickle=True)\n", " \n", "history2 = {\n", " \"train_loss\": [],\n", " \"train_snr\": [],\n", " \"val_loss\": [],\n", " \"val_snr\": []\n", "}\n", "\n", "adjusted_learning_rate = meta_parameter[0]\n", "epoch_start = int(meta_parameter[1]) + 1\n", "\n", "for i in range(0, epoch_start):\n", " history2[\"train_loss\"].append(train_loss[i])\n", " history2[\"train_snr\"].append(train_snr[i])\n", " history2[\"val_loss\"].append(val_loss[i])\n", " history2[\"val_snr\"].append(val_snr[i])\n", "\n", "model2.load_weights(\"model_training.h5\")\n", "\n", "os.remove('train_loss.npy')\n", "os.remove('train_snr.npy')\n", "os.remove('val_loss.npy')\n", "os.remove('val_snr.npy')\n", "\n", "os.remove('meta_parameter.npy')\n", "os.remove('model_training.h5')" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.plot(history1[\"train_snr\"], label=\"Train SNR\")\n", "plt.plot(history1[\"val_snr\"], label=\"Validation SNR\")\n", "plt.xlabel(\"Epoch\")\n", "plt.ylabel(\"SNR (dB)\")\n", "plt.legend()\n", "plt.show()\n", "\n", "plt.plot(history2[\"train_snr\"], label=\"Train SNR\")\n", "plt.plot(history2[\"val_snr\"], label=\"Validation SNR\")\n", "plt.xlabel(\"Epoch\")\n", "plt.ylabel(\"SNR (dB)\")\n", "plt.legend()\n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(2473, 512, 128, 1)\n", "(2473, 512, 128, 1)\n" ] } ], "source": [ "with zipfile.ZipFile('C:\\\\Users\\\\Lukas\\\\Desktop\\\\TH Nürnberg\\\\Projekt\\\\netz\\\\Daten\\\\Test_Vocals_Mix_2473.zip', 'r') as zipf:\n", " zipf.extractall() # Entpackt alle Dateien\n", " \n", " # Lade die Arrays\n", " X_test = np.load('X_train.npy', allow_pickle=True)\n", " y_test = np.load('y_train.npy', allow_pickle=True)\n", "\n", "print(X_test.shape)\n", "print(y_test.shape)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Test Freq Model 1: SNR = 3.1649, Model 2: SNR = 3.6846\n" ] } ], "source": [ "# Evaluierung mit den Testdaten im Frequenzbereich\n", "\n", "test_snr1 = []\n", "test_snr2 = []\n", "for i in range(len(X_test)):\n", " print(i, \"/\", len(X_test), end='\\r')\n", " mask = model1(tf.expand_dims(X_test[i], axis=0), training=False)\n", " snr = snr_metric_mask(y_test[i], mask, X_test[i])\n", " test_snr1.append(snr)\n", "\n", " mask2 = model2(tf.expand_dims(X_test[i], axis=0), training=False)\n", " snr2 = snr_metric_mask(y_test[i], mask2, X_test[i])\n", " test_snr2.append(snr2)\n", "\n", "\n", "avg_test_snr1 = np.mean(test_snr1)\n", "avg_test_snr2 = np.mean(test_snr2)\n", "print(f\"Test Freq Model 1: SNR = {avg_test_snr1:.4f}, Model 2: SNR = {avg_test_snr2:.4f}\")" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model 1: Test SNR = -0.3559, Freq SNR = 2.5548, Time SNR = -3.2667\n", "Model 2: Test SNR = 1.8517, Freq SNR = 3.8063, Time SNR = -0.1028\n" ] } ], "source": [ "# Evaluierung mit den Testdaten\n", "\n", "def combined_freq_time_metric_test(y_true, y_pred, mixture):\n", " result = y_pred * mixture\n", "\n", " signal_power = tf.reduce_sum(y_true**2)\n", " noise_power = tf.reduce_sum((y_true - result)**2)\n", "\n", " freq_snr = 10 * tf.math.log(signal_power / (noise_power)) / tf.math.log(10.0)\n", "\n", " time_true = postprocess_simple(y_true)\n", " time_result = postprocess_simple(result)\n", "\n", " time_signal_power = tf.reduce_sum(time_true**2)\n", " time_noise_power = tf.reduce_sum((time_true - time_result)**2)\n", "\n", " time_snr = 10 * tf.math.log(time_signal_power / (time_noise_power)) / tf.math.log(10.0)\n", "\n", " return freq_snr, time_snr\n", "\n", "test_snr = []\n", "test_freq_snr = []\n", "test_time_snr = []\n", "for i in range(len(X_test)):\n", " print(i, \"/\", len(X_test), end='\\r')\n", " mask = model1(tf.expand_dims(X_test[i], axis=0), training=False)\n", " #snr = snr_metric_mask(y_test[i], mask, X_test[i])\n", "\n", " freq_snr, time_snr = combined_freq_time_metric_test(y_test[i], mask, X_test[i])\n", "\n", " #snr = (freq_snr + time_snr) / 2\n", "\n", " #time_true = postprocess_simple(y_test[i])\n", " #time_result = postprocess_simple(mask)\n", " #print(f\"{i}: {time_snr}, {time_snr}, {time_snr},\")\n", "\n", " #test_snr.append(snr)\n", " #test_freq_snr.append(freq_snr)\n", " #test_time_snr.append(time_snr)\n", "\n", " if tf.math.is_finite(freq_snr) and tf.math.is_finite(time_snr):\n", " snr = (freq_snr + time_snr) / 2\n", " test_snr.append(snr)\n", " test_freq_snr.append(freq_snr)\n", " test_time_snr.append(time_snr)\n", "\n", "avg_test_snr = np.mean(test_snr)\n", "avg_test_freq_snr = np.mean(test_freq_snr)\n", "avg_test_time_snr = np.mean(test_time_snr)\n", "print(f\"Model 1: Test SNR = {avg_test_snr:.4f}, Freq SNR = {avg_test_freq_snr:.4f}, Time SNR = {avg_test_time_snr:.4f}\")\n", "\n", "test_snr = []\n", "test_freq_snr = []\n", "test_time_snr = []\n", "for i in range(len(X_test)):\n", " print(i, \"/\", len(X_test), end='\\r')\n", " mask = model2(tf.expand_dims(X_test[i], axis=0), training=False)\n", " #snr = snr_metric_mask(y_test[i], mask, X_test[i])\n", "\n", " freq_snr, time_snr = combined_freq_time_metric_test(y_test[i], mask, X_test[i])\n", "\n", " #snr = (freq_snr + time_snr) / 2\n", "\n", " #time_true = postprocess_simple(y_test[i])\n", " #time_result = postprocess_simple(mask)\n", " #print(f\"{i}: {time_snr}, {time_snr}, {time_snr},\")\n", "\n", " #test_snr.append(snr)\n", " #test_freq_snr.append(freq_snr)\n", " #test_time_snr.append(time_snr)\n", "\n", " if tf.math.is_finite(freq_snr) and tf.math.is_finite(time_snr):\n", " snr = (freq_snr + time_snr) / 2\n", " test_snr.append(snr)\n", " test_freq_snr.append(freq_snr)\n", " test_time_snr.append(time_snr)\n", "\n", "avg_test_snr = np.mean(test_snr)\n", "avg_test_freq_snr = np.mean(test_freq_snr)\n", "avg_test_time_snr = np.mean(test_time_snr)\n", "print(f\"Model 2: Test SNR = {avg_test_snr:.4f}, Freq SNR = {avg_test_freq_snr:.4f}, Time SNR = {avg_test_time_snr:.4f}\")\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "def preprocess(array, target_size=(512, 128)):\n", " n_fft = 512\n", " hop_length = 128\n", " win_length = 512\n", "\n", " original_max_amplitude = np.max(np.abs(array))\n", " stft = librosa.stft(array, n_fft=n_fft, hop_length=hop_length, win_length=win_length)\n", " stft_magnitude = np.abs(stft)\n", " phase = np.angle(stft)\n", "\n", " stft_magnitude = np.nan_to_num(stft_magnitude, nan=0.0, posinf=0.0, neginf=0.0)\n", " # Prüfen, ob das Array leer oder lautlos ist\n", " if np.max(stft_magnitude) == 0: # Kein hörbares Signal\n", " mag_norm = np.zeros_like(stft_magnitude)\n", " else:\n", " mag_norm = stft_magnitude / np.max(stft_magnitude)\n", " \n", " # Sicherstellen, dass magnitude ein Tensor ist\n", " magnitude = tf.convert_to_tensor(mag_norm)\n", " \n", " # Füge eine Kanaldimension hinzu, falls nicht vorhanden\n", " if len(magnitude.shape) == 2: # Nur Height und Width vorhanden\n", " magnitude = tf.expand_dims(magnitude, axis=-1) # -> (Height, Width, 1)\n", " \n", " # Resize das Spektrogramm\n", " magnitude_resized = tf.image.resize(magnitude, target_size)\n", " return magnitude_resized, phase, original_max_amplitude\n", "\n", "def postprocess(after, original_max_amplitude, phase):\n", " n_fft = 512\n", " hop_length = 128\n", " win_length = 512\n", " after_resized = tf.image.resize(after, (257, 1723))\n", "\n", " after_resized = np.squeeze(after_resized, axis=-1)\n", "\n", " #after_resized = after_resized.numpy()\n", "\n", " after_resized = after_resized * original_max_amplitude\n", "\n", " complex_spectrogram = after_resized * np.exp(1j * phase)\n", " print(complex_spectrogram.shape)\n", " audio_reconstructed = librosa.istft(complex_spectrogram, hop_length=hop_length, win_length=win_length)\n", " #audio_reconstructed = librosa.griffinlim(complex_spectrogram, hop_length=hop_length, win_length=win_length)\n", " return audio_reconstructed" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Funktionen zum Visualizieren der Waveform und Spectrogram\n", "\n", "def show_wav(sources):\n", " if isinstance(sources, list):\n", " sources = {f'Source {i}': s for i, s in enumerate(sources)}\n", " plt.figure(figsize=(10, 5))\n", " plt.plot()\n", " nussl.core.utils.visualize_sources_as_waveform(sources)\n", " plt.show()\n", "\n", "def show_1wav(data):\n", " plt.figure(figsize=(10, 5))\n", " plt.plot()\n", "\n", " librosa.display.waveshow(data.audio_data, sr = data.sample_rate)\n", " \n", " #nussl.core.utils.visualize_waveform(data)\n", " plt.show()\n", "\n", "def show_fre(sources):\n", " if isinstance(sources, list):\n", " sources = {f'Source {i}': s for i, s in enumerate(sources)}\n", " plt.figure(figsize=(10, 5))\n", " plt.plot()\n", " nussl.core.utils.visualize_sources_as_masks(sources, db_cutoff=-80)\n", " plt.tight_layout()\n", " plt.show()\n", "\n", "def show_1fre(data):\n", " plt.figure(figsize=(10, 5))\n", " plt.plot()\n", " nussl.core.utils.visualize_spectrogram(data)\n", " plt.show()" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Abtastrate: 44100, Länge: 200.52678004535147 Sekunden\n", "Model 1:\n", "(257, 1723)\n" ] }, { "data": { "image/png": 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", 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", 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Test mit Trainingsdaten\n", "path = \"C:\\\\Users\\\\Lukas\\\\Desktop\\\\TH Nürnberg\\\\Projekt\\\\musdb18hq\\\\test\\\\Al James - Schoolboy Facination\\\\mixture.wav\"\n", "\n", "# Audio laden\n", "y, sr = librosa.load(path , sr=None) # sr=None behält die Original-Abtastrate\n", "print(f\"Abtastrate: {sr}, Länge: {len(y) / sr} Sekunden\")\n", "#display(Audio(data=y, rate=sr))\n", "\n", "s5 = sr * 5\n", "\n", "x1 = y[0:s5]\n", "x2 = y[s5:2 * s5]\n", "\n", "before = x2 # Ihr Originalsignal\n", "#print(before.shape)\n", "\n", "after, ph, max = preprocess(before)\n", "#print(after.shape)\n", "\n", "print(\"Model 1:\")\n", "mask = model1(tf.expand_dims(after, axis=0), training=False)\n", "#print(mask.shape)\n", "#mask = np.squeeze(mask, axis=-1)\n", "#print(mask.shape)\n", "\n", "neu = mask[0] * after\n", "#neu = mask[0]\n", "\n", "vocals = postprocess(neu, max, ph)\n", "\n", "song = nussl.AudioSignal()\n", "song.audio_data = vocals\n", "show_1fre(song)\n", "show_1wav(song)\n", "display(Audio(data=song.audio_data, rate=sr))\n", "\n", "print(\"Model 2:\")\n", "mask = model2(tf.expand_dims(after, axis=0), training=False)\n", "#print(mask.shape)\n", "#mask = np.squeeze(mask, axis=-1)\n", "#print(mask.shape)\n", "\n", "neu = mask[0] * after\n", "\n", "vocals = postprocess(neu, max, ph)\n", "\n", "song = nussl.AudioSignal()\n", "song.audio_data = vocals\n", "show_1fre(song)\n", "show_1wav(song)\n", "display(Audio(data=song.audio_data, rate=sr))" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "(257, 1723)\n", "(257, 1723)\n", "Mix:\n" ] }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Vocals:\n" ] }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "nach model 1:\n" ] }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "nach model 2:\n" ] }, { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Ziel Amplitudenverlauf:\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Amplitudenverlauf nach Model 1:\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Amplitudenverlauf nach Model 2:\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Ziel Spektogram:\n" ] }, { "data": { "image/png": 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0V2iUj9JyzxPHAzTNRgibOO4BGkkSouslNGEThFsUnYP0h0tplERjtnofK+3H0bQCEBPHHrpexTTKeV3J2hJdr+yKxtvWHEHYRtPsvLzregnLaDDwLufHHWo8RDu4jOutUi/eQpJETBiHeJt5BC+KWQ1cbi5UcQxBFCf0gpglv8M5nuDbSx9gZeDjJREbYosHSgt8wX0KXZjcrb2FgqEhEPzh8FH8uMeHix+iZmkYAja9GDeICZIYW9P4nPtrfHft7/HioElZFHg6epiqMc/a8Hkco85B461ssMRy58+IIpeJynG2uqeolo7Qcc9SKR7mvfZ3Ymkali5o+vK6PAJ6Whc7cfha6z8yX383ftxjs/MMCQmmMcFk6Qjt4SUG3mUmKsdxvXU8f4WCvcDAu0y9dJRh2GboLaPrJfZX38Gl1p+QJCFztQeIidnongSgaO/nFuddrCXnZZTPWycItzha/256bBInAZowCZI+piiiY6ILkzAZsj8+zDPefwOgau/HizokSYyu2eiazUb3WR6ofJyT/u8x8FaBmInyMQRaXleydgmg1XseoTkU7Nm8PQLZ3hWtKQbBFlV7Pw3tAM34En7co+We51DtfSz3n6bu3MR67zS65uAHa0xX78X119CEQW9wAcucYbJ0mK3+S0TxkDgeEMcepcIh4jik5hygH27hBW08fwXLnELTLPxgk9nqvQzDFqZeZrP3XB51y/rhrD4JYWBbMwg0ClaDre6ptCxX88hT1mbeOvEddKIV1tpfxTJn8IM1qqUjBKE7Vub3aq+y79pLAaDrJQy9QpKEsr9LIxXZ79vWHEVrklbvefl5GgktOgcJoyHVwgIbnad3nXcnWZ2V7UUhbzdsc5qBdxlNK2CZDYbe8queK7/HtL3K7o8kumZkd+e/syhvyTlEEPXzd3g9NUbWLgE49jymXsIPu7v6tNFxWNaPjlIpHt4V6c5kzQlJXv+zc1lmdayMy3sfj0hfK8JULiziBS2iqMtE5fhreldj35OWg+zZXE/1YJkzhFF7bCxhGhMIoeXP9VrR+unqvbQHS3ndeK3XleHY8/j++qtGa7PvLxUOoQlz5D0kQES73aZavX6uShUhe5NJEg9Hb6BrFkKYGEY9L/BC2ESxD8gKn8Q+LfcMPe8qvcEFQE40sgJmmTMkSczBxgcoazN0B1eIIhdDL+YVxjQm0sGH/Ls7uIg7uJhX5NFkpUJoclIDlOxpAAr2NHO1ByjaswAYupzI9P1NNK1MtXQEx55nf+W+/DyWOUN3uMSBxvuomPP4wRqG7gDg+Su03DMMvMvoms3Au8xW95SsaEmMrlnoeomhtzw2GdM0mzKThHGfoi1dy9zhZcKwRRgNAbCt2bTzGmCk+zeSdEAOMFk5QZKEOPY8E+WjuN46cRwyU7ufKOqg6yVMo5w3Wr3BS/jBBpZeQiCIk4Chv0mchIRhi+nqvZQKh9jqn+NK/ymGUVN+T/E2Furvwbbm0LQiq+4pNGGiaTaaVkATJvvqD1IqHMIyZ8bKRxx7cvIhTAr2AqYxgWk0qFj7CMJe3rhHUYco6mDolXwgmxAxU7sfd3CRifKdBGEPgIG3ymb3JH6wgR9sEMceUeQShFt03LNMV+/FT/r0Bhexrbm0LBhoWgFTL+IY9fS65eTWsecxjDqd/nkutx6hXlwkSRvO7F1ViofRNYs47Yi8sCvLVeEQ9dLR9H3cyUzl7rx8lguL8nqDZl7WhbApmBMM/RVso4Jjz9MoHyNMPJZbj6bfV0AIk457llb/AlE6QRt4l/H8FQyj/qqTMSE0yvY+otjjSvtPebn5+XwypgmTnneV5uBlaqXbZL3RbPzIxbHmsdJ6IISWT8Ja7hn6wyWyJrRgTeeTMV2v4g6XpIQoiSmliy4gO9F99QdH6tIURecAmmZjmVOstv8MP3IJ4gEaGgJNlvmoixByoF51FkiSMK8DcTwgSWIGfhNHr+Xnnq++nYI1JTu8yMXSS/lAqFI8nA8iusMrBOEWtcJNxIlHyZrFNipompHLAx2rQRS5LNTeyU3Vd2Nbc0TxEEsvMVM6RpwExMR03LMEUR8hjHSyGmKZU1QLi2iazUzxGLc2vo3l3lP4wVpuGe8FbeIkxLZm0IWNrhUQCA7VPsB89T7KhVsQQmeqeje6JutxqXAI26hgmVPphL6IIWwMo069dCuT5eOUC4sYehHHqDFXe4CBdxVdryK0AmVnXzrYlddQdA7KcpTWfzmhhYI1SxQPc2ncvvqD3BrLBYh3FL+PolbnHcb72B8dwI8TemHIo51P88Jwg8uuRxDDdEFnS1vjuysfJE5gxrFIkoSYmJVBwAPmCe4UR3kpXOO/dn6TKEkoaZOU9WmqpkYvSDjZ6tHyQxq2TsnQuali8JHy92Jqgvtqk5wVz/I2/f2UaOAYdW7W70NPDC41H6ZePCwnvbHPZOUEs/ZbmKycYM65g4WSRdXScXSNJj3aYlvuPEmFxcZHuDm5k4o+R610e9quVdGESRj1EUJjq3sKz1+hXFhk4F3GMmfoeVfzQbBtTjKImpQLNyOEwWrnq7j+KnHsUS/dhmPWMRMLgY7rrQIwV7ufyVj2U17coxeu4EcutigzFx/isvsEW/5FAhFwh/Mh5gp3stJ+nGbvNJ3BRTqDJdqDV7il/i3sMyoEYZ+J8lEmy3JQWtIn5fu1F/K6ZOplJip3oWsF+sMlObhK26+Bd5kgHtAfLlHWZ+ixSWv4Cn1/kyO1b+NgfCtV5wAr7ceZrZzANNJFNeQgs2BOyPqa+HhRh8nibVhGlTj2sMwZ4jjE81dZaT9Oxz2b99FCGHjeVUBDxySMfVx/VY4F0r2FjlGnWlhgsnICx57HtmYw9RIFq0HJmEETJkXnYLqgI/tXXbOwzCn6cZNeWi/8YA0hDDruWQbe5Xzh0jKnqBQPy3FLEmIaE2nbbI+1RVldEgiEMPH8lXw8kw3q4ySQ9+Sv4Hqr+YJPo3QEgCj2MY0iPS9b9Lz+MNXzV0jiYS7plG2il08m5ZjBv+45RhFCI4l9bGsuHYOFaHol//nOyefY5AxBf7hEksT0BhcIQtnXhVH3ut8pFxpl/6trFkHkomvW2DGaMIliNx/DDYM25cLi2BgjmwRoWoGCvSAXtDRrZMK7fa0JMWZatvPrMCYgvZ/snYod1yGfkcHAXyUItygXF+kMLo+k/9jj/tLyMko2wcnGEJpWHnvXmmYjENjWHH6wtmth1zTKBMFmfv4ocnHseTRh5pM1gDAevObJ2Oh1ZdecJPH2IuZ17lHXZH/RH14mSSIsc+ZVy+5O1IRMoVAoFAqFQqFQKG4QytTjTUbTSvlGatMoy8+EhaYZDL3lXHIUx34eeh6VNYIMkZasGXTNJoxnWe4+wVTpKEG4RaN8DE2Y9IdL6Hp1THJTKx5ioyP/nYWZM2mRXPky09W4KWkEIQziOCCIB7jDq1ICFgd0BmcRCMrFWxn6m4Rhm7gYM1O7Hz/s0HLPUC8d5VLzYYTQmKndz1r7q7lUJSNf4dIKeWjdNipYeolh0Kbvb+bh6nLhEJf8J2m5Z3DseSyjTBQPcextqUHBalAv3ERz8DKWUaEXufnKhRAaCVEuYfKDzVTqJlc0Jsp3YutVvKjDVu85HHueobeMptm03DOpVHMVP9ggDE0ONR6i5S/hDi4yWTlBFHs0u88BYAibK52vMFM5Qce7IiNWleMYWpFh2MIPu3S8K/SHl3GsuVwKmD0f26xjOvto9k6j6yVK5izDsCUjYjtkg9nqYhYN2+iepFI8zGb3JHO1BxiGrTzKmEsg05C7kZaPhJgrva+ha6U8kuRYc3jBOmE8ZL39NRIS/HhAubBIf3iJJAmplW6n5Z4hij1AxzTK6JrDwLvMlH2Yq/2T9HuXEMIgin3CqE/ZlhE4y5yi6Z5FE/aY/EFKa1ZH6otNq38B05ig2X2OhISht4xrTqXR3SiPigI0SrfiRy6TqbwoIcbSyqx2TzJTOY4XdQhjnyB08YJNDL2CaRQZDK/Q6Z8HoTFRvgOApnuGOPYwjAZDfx1DL9Hsncax5+m4Zyk6B6k5B1huPTom2xiVRiRJiEDQ7Z+T77Kwj5I1y1r7qwD0vVWiqCPlyMKk2TvNVPXu/P51zaFszWJoNhVrnkvNh/HDLnEcEBsBA381l89EUQ/DaOBFXeI0ipo9a8eaJI4DLjUfBmC+/m4GUTOPvPvBBocaDyEqGkV9Ej8Z0CVJc2lFTFXvZr3zBKYxkV97RpLEeTRxY3BWRs+EgWmUafZO07c2KRcWWWt/FS1dFc8QwiAM23TCNppeIiHmsvsEoI3JGCv2POudJ9H1EnbhNhkpJsEUDkEyoGzJVeBh0CIItyjZRzC0Apu9U5hGA5ByzivtPyVJQra6rbF78PwVDjTel8p4J2W0UWjUi7ew0T2ZS/ga5WP4kYs7uLi94qqZqaTGAGL8yKWn93mo9DG+HPweH7Y/yoo3YLFU4pHhKR6w7+CjjX+GEFA1DZ4frvNWfZrZeJ6OH2NogqWBy6nky9yS3AvAs8Er3K4d5CZ9mhnrO7gwbLMSPEfJnMLSoeUn3FkvUzYET28OMIRGy9NwdMGV/pCKYbLSe4a50iKt5AqaMCgnJZ70/xulwiEa5k0sB8/gBZvsr76DYdKhoNeJkoCr/YCYhKVkjQ2xxEJ8hHM8gZ4YaEKjFb5CxZhkqfOn1IuLuYy1P7zMQv2b8jJXsBcwdbnibps1uv1zucTKDzsUzAkatuzn4lSaZBh1gmjIAfsYTzb/01jdKoi38eXW/ynPl8p0kyRks3uSdu1+5orHMUWRS/Fz+JHLZvckBxrv41LzYSyzgWVUmLFvZyt4ma8ZPaZKt1MTsn0yajZFGlSKh3GHl3NJcFGrc6n3p9SLh+kODdmWjrRfWT1oh1dw/TXCqE+SBKyFL+IYJTY7ZygVDrHZfzGPaPf9Dcr2PsK4L9s8YeWysYwg3MBPn4mmFSja+7BTdUtWn/ZX70cIHSE03L6U3Rp6Uao/MCkbM7zU+jz10m1sdU8xRKoStroP55G0qerdbHaeoVy8FXd4mTge5EqEaukIGvvpDpewjDkG3mX8VPlgGmWSJMqjebZZo2BP588jDFtjsjzb3ocmjLG+bFQKl5WbMGwDUCscZLN3SrazSczAu5pHRF6LeU9Ckity9iIIW6/ZCCg7RggNz1/Zlm+OGGVd7zr2YjS6IxUH87mcMo4HtN0XsO19DL3lMWnjaJ+O0PLzOLb8fcOoo2tOfnyleJi+t4oQGkN/hXrpiJSyxmtYZiMfK4B8Z62R9yMQRCNGKkV7lk7YGrt2w6gTR246tpT1tDe4iGVOEgfjEaxRrmfUlpWRaMfzFcIgxhsb04ySbTNJkoCCPY1plFPVCsQj37dT1vlaDfSCcAshjDzKCeyK0u08HuSYoD+89IYMaVSE7E1G14py/44w2Fe4S05A0v0LGftL9zJdviPf71Vx9udSRoCSNUPf32Ct/VW2uqco2/vYTBu+JInpDi/TKB8jijp5yLpeOkpnsJTrhYUw0PWqHGCk4do49mQC01SeKBAUzAl63gpR1MHzV+kNLjBffzcJCY5Rw7EmQRgsNb9I0z1HTEyjfIyWe0Zq4Ssn2EoHMqNkEx55zYGUSOhV2v0LNHunqRduIklC4lT+0PdWGQRNFurvQdcseoML6TWtUXQOSgnMUA7ks/MWnQMjsoKYre6pPEScVZw49mj1X2Kr9ywb7vNowqBRPpqfIztu4F3GsWbTiegilzqP03LPMJ1q9lvumbyx7YUr6FqJq63HCKMhljkjZTLDS3Tcs3JCMbgo5ZTBJlHUo2AvEMVDNM3GHV7E1MuUC4sUrFlcbzV/nrZZxzJnxmQImmYTpfsihDByWULXv0pMjGVOpXLNGCE0dL1CubCIY01ysPEBwmiAY01SKx5ipnY/pcIhSvYMM5W7mSjcSiWV6dnWHL3BBWxrloQEQy9QdA6iazb7Knfn0sKic5BN/yUq9jxCK6DrZUy9yGT5KAkRm92TaJqFZTQwjW0ZQkKMY9THOxw04qgr9yeRyH0FzkFss0EUdSja8xh6PT++M1hi6DdZ7zzJeudJ/Mhlrfcs1cIB/Mhlq3sql9vE8YCKM4+pFWRdSzu07nCZIN23IZ09LeJ4QJTtS0ybxaF3lYLWYKJynHLx1nwhI6tf2TMz0glBxTlIksS0B6/g2PP5xCuTeprmJFPVuxFoWOYUtjVHzTnAMGzR864ywQIztfsJwjZ97ypb3VP5/hJZj0KCcIuu++K4i6bm4IfdvA2pl47SD9ZxvTUmKydy6Ww/btHsnaYXrI5MumIca5owkrJHx5rcVY9navcDMFW9m/5wiWbvNGHUR0ufge+vEqeypaJzYOzeZR0PiJOAMGxxqfmwHEjoTn5fftDE9dcoFxbRhM3m4DxxIu/lyuBpgrhPa/AKvcHLCKGzv/ZOXG893/8zOgFMklDubUzbxUyyva/+IMudJ+QgK2gTxR5b3VM03XM0SkfpuHIRqtk7jWBb2g3gpnszSSIMo07TPYtINBq2wXvtbyNKEvYX5ERkOtrP0rCLEJAkYGgwJ+r0w4SEmH4U0fQDmlqLef0YemJwNexwi1hgpmBQ1HXWadPR2iRJREFrMAjh/179KdwgwdETJm2LfhzwgtsmTqBhWVwK2nzv5D+mQQUv7nGLdi+2MNhfuJubnLezOnyew4X3cqLyPeiYCDTmOcJUsp+aZXC0bjEZN7hb3MuqtsRh7uNq6zH0xKDvb7KevEzJkZLfyepbaZSP7ZJuRfGQMPYxjDq9wcvoeokwbOYutVu959gaviT3g2kFJp3DFKxp3MFFXnIf4Wjj7zBROprXl0zqd2TiuynZ08yU3kK1IOW/ftjBTwacb/4u7eEl+v5GLseW9dTA1ApESYAXdugGy0yLmwF4ofVfWWl9hbOd/45tVJiv3s9t1W9BCA1bVLi59n42uyepOPPYRoW92HJfzCcck+U76A4vE+AzXT7GvsJdzJfupmTNUCzcRN05RJwEDPxmKvNsj51LIFiovze/dpIQL2hxtfVYLkGUNTXmUvNhtLR9ipOAobdMksRc7T7Nua3fZqJ8jJb7ItPVe1lsfIT9hbtlX2DK7Qxb3VMgBO7wci7v09KtFTP27TSsmwE9n9iYupRduoOL9AYXmK7eS5z4BJEr64zYXtPP2nVNK1BJF5UNo54vimaDYMOoI9BolI/lg9b1zpNMlI+x0PjmXJ52rZQOmZQOGPv+nXucM8lxxuhkLJOjFeyF/Blk5S4jk/d13LN4/io7qaYSy6x/G72u7DkIYe+6j2xhVo5bArmHOl2IBFkeMpns6DVn9yoX0v38nkfbv4q1D4gIwxZJEtLsnd5TrifHCaXxLS2agzHyzHqDpR2/I8t7QiRlnGkbGcce1kg9ya599NzX41oywGzCF4Rbrzq56bhn8wmaaUwgEHm9AflMsz4hjgdowszbi1H0dPtKRpKE+Vh69N52/151rD18o+6gakKmUCgUCoVCoVAoFDcINSF7k8k2sQNsBRfoDq7sOqYTLXO19WUa9iEAWu6ZsQhayZDuQDKqVKJszrK/ch+aViCMPTTNysOww2CLsjMrXXmCDUxzWoaVk4A47o+Faw803ke1cJCKKTc+Vou34ug19pXuAkBLV0dsUUYg6Aylg1wSS1ONINyiN7hIyz2DEIbclJ9KOhyjnq/Qm8YElXR1QsogBwThVmpU4SKEwdXWY9SLi5TtfZSdfURRjzDq0vav4AedfOWq6CykEsQ1KbtERyAYeOv0BhcwdIco3nbW2ekYBHLlTktzTm32To1tbN1+bzFJEmPb+6hbBylYU2hagY3u0/k5843LwqTizKPrVSrOfLrJeSp/h9mKj65XU8OFUMo/gg1IVwZb/ZfpDS6kbnTT7Ks/SBh1Gfrr+b1un8PbXqER26tJQ3+djnuWauFgviKTJDFBuMW0czu9/nlavlzlKpuzUtbTe47+4BX6/gat4Ssstx6l455F16tYRoVq6Ui+Otp0z1O0pmj3L3K59Yh0UUoi+sMlhv4mrr9GxdnPXPmElOShEaZlwPOuYhsVDL2Qr/K5g4tcbT2GYdSZqBxPV0jDMfkDyM3v0/YRKeMdLhEnmduVhq4520l3hUGvf4GKs1+6Ngpj16poEA9ouWfkedJVVz9YwwvkKnUce/hhJ392ul4iTo1h4iRgpf8sW91T6MKQhilJQBS5+WrYdPH2fNW+YE4w9K7i+SsUrUmGgZShZivHnr/CRudposTLP+uHW3SHS4RhizO9z9F0zxGlDqqZtGX0fk1jgmLhprF7lE6Ta3jBuow2+5u03DPESYjrr+EOLmLoDmvtr5IkcR6Nze7ZNirExExUjhOlbm95GfOWidLnFkaDfGU5CLfoD5dolI9hWbM4Zg2BxsBfZapwW27yUi8dpVE+Rr10lHrpaF43+sOl7ZX/1CihN7iAEJqMbkYuQmj0BhdYaT+eG4QAXGn/6VjUH7ZXlS1zhoF3GXfwMn6wRhR1qJeO4ohaapJTTNsRKbW2zCqbqdOfaU5SsBfwgpY0HkCkdVrPn0cUtqkWDjGnV1keDlmK5Kbyjh/RsAW32A1CYvw4pmToPNtf54v9X+HL/pOExGgIrsYtinGJalzFQOOq9hLDOOLl3oA/9P6ItrZBi2Xean2YB8230vQi3lf7MXpBzPlOwtG6xm2VEndW65wfNikZGneWJ/DjmAnT4lbxNpzE4Q9a/x9e6vwRAzrUrP102WSVl6gyTY05+qLHLeYkE7YgiMEU0kbmlc6fsGBV+ebaj7ElrvKh0t/HEDZB6HKv8SHm9KO0++dlGzF8GSE0LHOGhfLb8cMuFWc/EFNII+1xPBiRN13AMqfyaEnF2ketdBvzpbsZ0CYhzutGSOqQmdhSghd3aPUvIBDUrYOUtElqxSM4Zo2Ks5+qsyAlv8GGlNb3L/By8/NMO7fT7J3GTCx6bPKO6j9msvpW4njAZvckYeIxE89RN25iyf0zlrqPS3mv0BgEe0utGqVbqdj7ZB0JW9SLt2BiUdAauPEGreAVNrsnKZpTrHafYqPzNF6wjqaXpJOyUc9X6Cerb6XMJOXCYt7GBOEW09V70YSRR6Kvtr4MyPHCaAQXpNyrYEtXwonyMbbcM/hJj63wYt7PyLYikCYF8WDb9CKNXm8F8nlFUSc3HsqMSLL2Iko8aoVDeV83aliUEceDXMEQhi2S3MhMRhfCsMXG4OzYPVjmFAW9gS3Ked+PGI8s6XopV8PkJNGe70c+Ezf/vZ3R3Exelo1ZZBR/Z/7I7eHxzoiHEBru8CqwHW3LInS5IiQJpLJlRMaoabZ0hUWkcsQwjwTn92nUcnfl0e+PIjfPN6dp1p6RpavtrzDaXo2dV7MQiPR5xESRm2+TgG1DuTxCdA3zkkypM+rW23HPjkTMpNtlFHX2NPPIsMwpTGNibHwz+vyyiGD2vTsjWppW2B2JEka6TSMZG1MnJPQGF7b7jSQYccrWpNGTMFKXxJvze9GEmT+n7N72Ioo614yevR7UhOxNJoyazJfupuWeIYiGRFGXgT9ud7rVk/K3XrCaWo9O5QW3XjpKkEituZzEuEQEDOMOjjWNEDpFaxJdLzFZOYFAOlxtdr8OkA82AMqFm/Pv1PUql5oP03TPstT8Iuudp+gMLrLmnsaN5F4uy5CVYtN/iWLhJuLYxwuaucuOJkyqhcVcyw+yMxLCZqv/Uv5ZGDbzfRlTxSOpFMkcuRYp12sPlmi5Z2j2TmOZU0SRS99bxjKrJMQIBMXU9c+25pisnGCz/yIJSd6guoOLmMa2s1y1dGRHQy9llaZRSyUExpiOGrYHuo5Zw9AceuEKcRJKN0e9nrsDRmEbx55no/N0OoiLqBsHCKMOceLnUqnRPS0HGu+j6BzM3arKhYO03PPYZi1vYDruWQbBFo41PTYxEYi8IdiWp2ahczvvmDY6T9PsnZYpB+wFuU/Af4mp6j103LOYeonV7lN0+3Kwrxs1OanylqXDZuq+1e2fY+g38wF59t3Zs9aEmXcu2YDcMqoMIqnPX+08gWPUc8lrwZzYZbMvy0cLL+zmg/ZRl7OCKZ/dhn+OIOxhmZMj+7ViBt7lXG6haTa2NZu/74o+t8v2VhcGM7X784G7lkpwLKOSN/ijjW3BmsXzV3CMmpQhEKPrVbn/DDkpH5VCtP0rbHZPIoTBWvdU3kFsdU/lg6CM7Dqz/SNJEtJxz+bX7Acb2886fb8VZz9ztQfk/jTnoGwT0kFE1nHK9BV1KbkVGmGqeff8FeI4dR11FikXFuUiQloWM5Ikli6HcYg7uEjNPpi6y8kOv9W/QEJCp39+bC+AZU7R7J0mioe0+xdymerV7tP0Bi8B0sGx2TtNz7tKd3gFI3WBbJSPYYzsfcg64WwwHqdSHtOYoF46mstGHKM21q5Z5oyUxJGQJIF0fDXqeTm1zBk6g4usDp6jUT7G0LtKqXCIKHOqi/38u2uFQ8SpRAVkJz5aB5P0vyAesBX1adLhydZ/4vnwCueSS7zUCehHEU/0fxMviegEIVNU+b7JH+BIcpyGVuRitMF+rcFj7U9zOn6E/XaZb3buo25aOJrBZu85bo1v4VLzYXpaDz+OsXRBTMJi1eD2mqBiyHszNfjmqSnWhgFeBJ0gpGBoNESJCcPhB+b+Jd8z8QlCPApag33xIS63HuFM7wucav5feKLPVuDzYkfWjV7iUTJ0PlT9BCt+j4iICpOsRB0GUZMTzrdjCo1XvK9RSCcjUuIsXdC2/Jdy5zzQ8gl29n6TRDrezpTuyN/xMGrS7J3m5ebn2fIvstU7jUBgGhMY2Bypfisv9mRKkc5gCduss9D4ZtaHZxnETSrWPEe0dzGjycVFx56X/YVZz/szgcaBxvvQ0EiSiMfan2bSWGSifCdJErPWeZIL2mmawcsM/RVuqjzIVHJQThCuIVkUaHS8K3Lh0j1L31+nzTrz8SI9f43O4KKUhAmTyfIdefqGMGylcrI4HxCaWoFaMkHF3sehxkO5nHm98ySuv4aVtnWaXpEDxzSp9+gAUEpxN6Xs1j1PFLkMohabvdNMVk5Q3GPilJGdpzdczdthR9Tk/jP3xTw1ihAGveFqvjdc1ol4l5NcJhnLFqalBf8c5cLBfLLVHy7JdjNtw+Ik5FLzYa4Ovk7Rkr+n69Wxe5QO086YXPtae7byrRuI6ybkHpXzZROq3Pn1Os69ckLTSSdWxq6fyf/vXvjNUrgg9Pz8fuoUmD37rHxomj3W18D2xDDbI7/7ukJ27sXa/u7di5+WObVL6onQXzUxuJTybUtnR/8vEPmk7Hp7x0b7O9usj5x79/PbuTcZGBv3bd/j60/inr3LbHLfG1zItyG8Pulh/JplmtdCTcgUCoVCoVAoFAqF4gZxQydkjz76KN/2bd/G/Pw8Qgh+53d+Z+znQog9/3zqU5/Kjzl06NCun//Mz/zM2HmeffZZ3vWud+E4DgcOHOBnf/Znd13LZz/7WW6//XYcx+H48eN8/vN7J3F9LfQiueoi3aSCNAdWNV8dyhydWu4ZwqhFGLaJYhfTmKDnXWXTPZcmLi2hCZNN9ywr7ccRQqNgTtDsnSFKXaUytzDS1QrLnCEItzCNibEEgVlI1bFkbpMkjQB5/gqDYAs/2KA/XJL5p9yzeKmbmTSDuDWXQbbcM2ObV+UKfyeVWqQhbRLKhZvp9S/QC1boDS4wU72Xhfp7ALkC5IedsdWpbPUjjvppHrU1EDrrnScJwjZh1KU7XCaM+lRLR6QMKV09GnrLMnpXOoKpFXKDEcOoEwTr9LwV4tinVlzME/eNUineQhBuyZX8wQX80M3D8vXiYh7pyMLg2QpaFLn04yb10hGisJ26JpnoI3ICN1xj6K/jZomc/U3qpVvxwy5FazKPkmV5rbIVf9iO5uTPKGjlf0+SiIXaO1NTk6k8p9jAu4yllen2z+Vym83u16WbYGqOka2I2dYc673TY+c1dCeNOsqI7WiyR00vjeXmANjoPstm9yS2NUejfJTO8BIlbRJNs+n5a2k53r1q1B8u0R8uMV0+xsC7nLp0zdByz7DZPUnHPSulR/46ReegNEBJ6490K3UBHU0z6A4vS/MRYe5arW32TlPVt6UO1cIhCvYCvf55dF26oGYrnPXS0XzFv+WeyU1loqiTr5SFYWtMCtHtn8Myp9hXewfJyGpaLrsZITuHfMf2NROFlguLVAuL1EtHWWt/lZ6/Rhz1GfirzNTup5gab2QmKI49n9ffKPbzlUX5+Vp+vZlRjpsnUt5+Rp6/ghd2marezdX2n8q2KzMTSVcdR1cLpVxEGmiEYSuXcQ68y0yUbtte5YwHuUTNNMp50tlBsO0A6djzONb4SrBAYBuVMeeqKOrQ7J/H1B2KzsExQ5bRvGph2MqjkTJHYon+cIlO2h67g4sMvMv0B6/kpggAXW+ZOPbxgzUscyp3esyuMXtmUeyzpq2wJdJoGyGe6PMl//fZDPsE4RZbtDA0wR0Nh41hSEzC1WSTvuiiC8Hfnf5/803mhxlGMRf7LsMoomYZfHvtk1wUS5jGBKd7n+Pp+HncIOaWUomml6BrUDVjJmzB73ae4kzL52DJIkoS7ppw8KOEZuJSNeW1r/seEyzQjpaJibmj8fc4Vv4w31T7ESbjWZ5JvsxTyWO4IRywK2z6Ht14iEDDJ2Q1fpFnhr/DINhiRbvIee0ldGFQsfaxUH8P++oP4qd5BVuudBgMo640+jEmmKycYLJygv21d7NQfw9r7a9ytfs0hlFnWtzMtHkkzedoY2iWzNNIQqWwn9nkIJe8p3CsRprjUSo11tzTTDqHMUWR5vBlelqXzeQibf8yQdhj6C0z9KWz40TlOFfcJ9kcnGNNXGSOwzxQ+yE2gvO5VHWx8a3oGNh6NXdgfab7G6z2TjFv3JmXydF+r24cwAtaeaLjhJgr7pMMxQBTd5gs30EljUrpwkgj/duRi+zvjfIxVtpfZUOT/b6XyFyUQkhp+/7iPQyCJkLYGHqRgjXFgcb7aZSOkMTD3FjCNGQdy5yVAXl/SSjdZNO6MRo52i7XZlpvmrk88krvyby9SJKQbv+cdEVN/DzR8UTlOO7gIgV7YSRf2YzM72fNptc1Qb18O56/kpstZZ9nZhajUSB3cDF/L6P5VjMG10nuPHqerN5eK4J2Pa7npLeThAQ/NfzYKSG8likJMGaKYaXmKjsjVVJCN3xd17hTsp+Nkwr2wi5jkmrpyJiZ3Pb36rsSf+99D7sdKzMVTeZkmOU7vV7kyDJnGHpXt79vj+e2M1KV54x8ExktKzuNULI++3pIJ+RXd+K8Hjd0Qua6LnfddRc///M/v+fPr169Ovbnl37plxBC8F3f9V1jx/1v/9v/NnbcJz/5yfxnnU6HD37wg9x000089dRTfOpTn+Lf/Jt/wy/+4i/mx3zlK1/h7/7dv8vHP/5xnnnmGT760Y/y0Y9+lOeee+5135PAZCNtUMYLtZYn+ouizog+Nk06l8SEUQdNWJTsaalpjvrESZDvURl40h3NtmbySYUfbKSa8MyxTLqVlezZXZpbKcEr5I14pgvXtG2Jn5FOArLK1nHPSle1UfvaHRU0a4xH9/B0++ekNj2t8B3vCv1oE02YuVY+lzSkyf+kRCxtSJOQJAmpFA8zUTpKxTmY7wkZeOsE8SBPSirlHCUco84g2Mob9Dj2yBJQxmmS3vn6uxFoY413HAdpgm2bqerd9AYXGPorJEmYO7mBHGTLZItywjRXe4DV7lMMgiaaXkEIDUOz6Kf7lYAxp7wk2d4f4fkrqVudlO1JDbOWOkwNxt5BNhCUMsHL+fPRkJPxojWNadQQQscw6qz1niVJYtzhEuXCIuXiYu7Ql5U7TbPx/BXqxUVKzr70M3lfsgGfZicCjbnKW8c+y6516C3T7ssB7kutzxPHHr2BdFTLyn22h6icyl4Fgo63vcdyZ/JMgcA0J7H0Er3BhV2WxlHUwQvk/o0w6tOL1/bsJK4Ovo5jz0tr/d5pitYUE5W7CMNWuveomE/Cis7B/B1licZ3stONK9v3MVE+mj9H26iM6edlx2Sj6yX8YI2pygl5bNopZx1WtXSEOAnzhPGWOUO3fw7DkImZNzpP55JHmW5giGPU5P7Q0hGiqMNk9a2U0n0eWZJuN1ynXjqaXpOWd2bZvZQLi/hhk43O05jGBNPVe5moHGdf/UGqxVvz57F9P1radmVJPW1K9qy0EffXKBUOSdlZKv1IUkc4gKHfHJvUFswGXrAu/55OZGdrb8/3v8ZI+U42+dvqnsrr2MC7vGsvSrZ4lJHZQus7NP47B2uOUSMhlnt1wzZFR0qQDzY+QMFs5DKiIGxTSRo4lPlI+XtZZIG3m2/hf6h9G5vaJpXiLQyEy6RtcEs54cSkydFqkQer8zxYuJWYhChJuHvK5J2zJk2txaRt8txwlReSC8Qi5q3lv03ZmeVgtEjd1plyNO6eiKkYCafbOk9vDvgm+27COOF8d8BCScfR5XkntTKGBg1b40i1wAFmuYV7qIoi5aTCAWZwxYA/a/0Ck9pNvMf8Jn7h8r/lTHCVLw1/kyXtPC9pp9DQWGk/znzxbgzN5uXm56nFUwyCJjExl1uPcLX12Jh0aOivSzdfvUwQbjEItuj7G1xuPcLm4DxztQeIog5TpaP0RIuIgCgeMlU5wVb3FDO1+zne+H5qxgGcxOGo9c3UrYNMlo9TdQ4wUzjKuwrfy63xHUQEHLHfy9neF+j5a0xat2AaZemYZ1QxjbJMdeKvULX3807zXg5ok1zWznK79k4AHqj9EH7S59ZYLuLNG8dZ917ANuvcV/w7xETb/WTads7X381UtI/DlQ+yr/4g++vvZuivM1M6xlOt/0yr9wK2VmYYtllpP85q2ofsHNhm7frR+ndzofWHWEaZldZX8PwVht4yJWOazeA8FWdeLuqm7sNbw5douueplG7DHV7FNCbyhM47kQuvHp53lenqvXK/WmGRYuEmKaW357cl20mQt8HZgFT2STLlQ8GaRaClCaQ3CGNfJgIfXsq/zw/WaLsv5gmhw7CZ782F7QlDFLtp+gwzly7vXEyT++fGF9mkFHKGnQihjbUpsN22STfB0sixr57tScrh53ZJBnd/7/aiza5JkhDj35vt30r35Gdt1NBb3nXvIBd84+Tak8PRiUvWBu6UZ/a8q3j+mpT670jw3BssEaepGMb2y43cR5YYe/SZXW9ikssX8zFMmO4hvfZExQ/WxidcYu89cCAXRbI9cI49v8vZcifXmxS/HvZKTP0XwQ3NQ/ahD32ID33oQ9f8+dzc+ITid3/3d3nve9/L4uLi2OeVSmXXsRm/8iu/gu/7/NIv/RKWZXHs2DFOnjzJ//F//B/8w3/4DwH4uZ/7Ob7lW76Fn/iJnwDg3/7bf8sXv/hFPv3pT/MLv/ALf55bVCgUCoVCoVAoFIpr8g2zh2x1dZXPfe5zfPzjH9/1s5/5mZ9hcnKSt771rXzqU58iDLdXtR9//HHe/e53Y1nbqwMPPfQQZ8+epdls5se8//3vHzvnQw89xOOPP/66rzMhIEnCPOcBpMn04gFBlCaG1Gwca27X5vpy4WYso4wfueh6lVLhZmm4kBkSpJs8BRoDbxVNmLvyaGS5pKIkxPNXdq0QdNyzTFq3YBh1/GAtT4yZEaSJGrOohpWaaoyyU2pl6k7qLlnNHZUsc0pKGax9zNTuxzFrMlqUBPQGF6iXjubnEcJA16x8FSWLVgH0vWW23Bfp9M9TLx1lonKcSmE/7uAimrBSI4t90rmpexI/7DBdlclWS84Cjr2PSvGwTILonmHDfR4hdOrOtlPdwN8giro41iyb3WfTa6jnK2zZexx4l4liP030bbPSluVjdIWr3b+w7dCT3kP2DirOPPXSUba6p9A0m4ONDzBZvgMhtDzP2Cjy+udzcwMp27Hzd77lX6Riz6NpBkHYpts/l28at8wpkiRkyjlMGA3y55wZIsSxlyYZN+i4ZykVDiGEydBfxdAcgtDNV5+yiOpU+SjRyEpWFgHajvYG6Ybe7YSeM7X708TfiwzDNnHs0feuMF29F9vel8tkHXuecmF843mtdLt0GszcLdMIh0DkzzgMW6y1v4ofbOQOjjtxBxfH3tEg2MJPVxJl5KmTJ3+M08isJkzpLiiMXRviR001sjw7reEreeTK0Et0BhfGNjRnblK14iJztQdy05s4CTCMei5rDkI3N+AIwxZ+IHOJBeEWU9W7aZSPSSlt6ShC6CRJTM+7ypX2V3KJchgNGHirVIqHaaef9f1NgniQy4CyewqCTaqlI9hGdcxcZMs9w8BvstY9SSeVFmaRZ5ArsZZRRROGzPelyaTas85b6A9lQnVNs7DNGmHUzWVR8lmMS3GbvdM0SkcxjDqFVJ62PuIOO/Q30bQCni9NkDIZzHY07W35vfvBBvGOVeI4Td7tBxtjcuXRVV/TmCCMPSZKRyDNnZblXuqFK7TdF+VqdxIzUTrK11r/kbl4H0Es6+yVYZ+CAUPR4xbrHRxKDvCF/p8yiARFAy50PSqmoGAIKqbOuWiF9SF8acXnHeUFfrv727S0NdrJCvujA/RFD13YLOkXaHkRX9lscXmgM2mFTFhwW82hagmO1C3WaDJfiOkGYOupiQYwjMDWoWIYFLCp6CaucFmPu9iJzTfVfoRbOIQQ8FD9/8VK8iKHCu8gIWJ/cpiykJGLTrTMbea7Odj4AG1tgwPl+6np80xX70XXS7kRT8FeoJBK1aLYx7bmUtl+SKlwiHrhJoraJDc3vlVGjrzn2fBeZKJ0hH3a7dRLRxkEW9LEKmkzFEMKic1cskjN2E9Vn+Ny96uc105zMv4jjiZ35e/c1B2W3acZesvSLMRfxvPXWO08jW3NcVDcyao/pGBIY49IhLyl8T3YWLxdv5dL+hJHuI9Tzf+LhnUz/eESW9oaK+FpqoWF/Ht0vcRy61G+1vu/AXCDDSaQ973mnmax8REp0Yt7VJ0DqXTLS9uf8ZV/Xa/S7J3mQv9Rbqq9l97gAqY5ja6XWKi/B0PY3GTcy0bnaQr2AkN/fUz1kiQxRXuWKOpSdA7uiuabxkQevbHtfRiaTVGfJCGmaE7hhx1MrZhfC2zL5+RnpVxKrGk2vbRNi+OeLBfuWUxdGupkueXqpaNj2yd0oyaNf9I6mUdwkhjLqBInAX7YoVo4sK0IQchcisOl3BVyuy4HY3Ky0T56Z+QsSM0ypNx5u03I++U9olL598SeNEvaIQHcyV4Kiu2fxbkrshAaQnOktHtHZF4IY09lB7DruoUw0kjbuARwZ/Rr+/d7uVmFro3fS+YALWWr9i65I8iE5Tvv888TKXotToR7PdNRw5MocnO1zKhaa6/rfyOS1b24nlvkm8k3zITsv/yX/0KlUuE7v/M7xz7/kR/5EX7913+dP/mTP+Ef/aN/xE/91E/xz/7ZP8t/vrKywuzs7NjvZP9eWVm57jHZz/fC8zw6nc7YnwxNmARRn4oj9x1UCwfyCq5pdi61MfVtl7E4Ceh7y/QGF3AHF4miDv3hJQrmBC33bN6wZ85rcTzAsfdRtufy3w9GkgR2++coOgeplW6X16TZ1EtHsa05LrZ+n0K6lyyMBmODpZKz3flk/8+kANnkQAhjbJLWcs9jmTOUrFkSZOWPUlvdDfcFZrRbdzU4fuTmMkXH3kfJ2k7iapt1kiRKXRHNfA9P31+XyVx7p7ctdKM+Q18OfOPYk5Im90UAev3z9IdLuf49c0Tq9s9hiG1r+ijq0CgfY6pwZKQx0AjDNgIx1kD4wRpFa3IsWa9MgCr3QE2OJPyOY092lFmnqFdz56849ljpPUPfX8+fja5X8w5XCCOfSAy8y9LKNW1YG4VFpqp303HPst55Mrcx3t5PMIGhF9H1EhvDc3n2+qKzgDu8nO45s2n2TueSzKG/RcnZx2T5OFHspzbjQbrvTU5WrrYeY7n1aN6hZROOrPxkmvEMXS+x1v5qWmZ0/GAz3fM2SVmfoWhN5uXaDzaJ0kTNGZom5abDVC5bL8nkzKXCzdd0PwrD1og8ppr/XSZI30jvdXVk8tJKO/NJOblKpYWlwiE6gwsYepWSJTv6ne6TulGjXlykUZKJxu10MConPeOdVimVgG51TxEmnpR1pWXYTPeygZz0X249MmaFXDFmpXunVmAYtjCNCYJ4QMHel0qZnPTZSzlwd7gkLYzD7YlQwWxISa93mUrxcF4mEpJ8wj763or2PH7YpFo4BKlF/E7Z0cC7TBD18IM1SvYshxoPcX7rd/P9IUEoEzDLdmv7fY3uW8jakc3uSaKwTct9kaK9P7VOl0jpUyu1525CEuX2+EA+uc4GKrkdc1qWkjS1AkB/8Ep+XtOoU7AXUqcxuadtrf3VXWVrq3sKTS+lEqKAje7TfOfkP8cRBtOOwULJ4s56mUkb3m0fZyaZxNZ0vqPyLgwtQQDvmLFx9AQvSigYGh+eOMAgTHjXrMWznRb3Gt9CLZ7iLt6GR8DbnJs5Jt5JKakzjCNaWpulXsxjGybLA2h6MV6UMONIKfEwFji64FhDsFixsXTBUm/IE1tdvDhmsVTi/9n6FBEBFgZPDf8rnvC5mmzyRHiGP+r+fzmU3EUgPCaTBZ7z/pAoibGtOWb02zATk5XeM7zS/TIb3otccr/KINgiSULCNC2CTAw9TOuAQxBsUnQOEkZdTK3AWvcUrfAV9HQhURcG0/btHBR3YicOt5jvoGbt55L3FINgi3m9jo5ORMhS9zEKSZUPlH8QPxlwRHsXGmBistj4CJZWpuLMc2Tiu1movwfTyCy1ZcLzZ3qf5WXtPH84/H0AmtoGAzo8FXyOU9FL7IsWEGi8vf6PmU0OcrDxAc40f5Ot7qmxfbRCmOyrP8gd1b+FRx9dGFTjqkyaXLydqWS/tOgPWwRRj/nq/bmTbWbvXXQOyoUeezZPN9L0X6ZSPJxONnSa3kVsUeGZ5i8zXb2X2eIxpirSFTKMh+iaQ99bzrcGBGFP7hG35+V+YmOCenFR7q3Vq/hBk6utx1hqfhF3cJGutyz7yoF0j82s7uM4zPugKHIp2TPpgqGsY3JxcCpvA5q903lfJdMENHMnVZkWx8jl2rI/lzL7OAkoaZO5u/NW95RMoWHOYJqT6CMLjzsZlSjLxR4p3d657+daUsJR197rIYQxtli982fXImt3LHNqZA9sfE0HwOtN6kaR7WjmlLg93qyXjo67M49cW5KE+WRt9PmMPsOhtzyWmmIUke4B35lmYfdxr20q8UZcEGH3/jqQ173XPmy5eJ0lpy69KZOp67lFvpncUMni6+GXfumX+Ht/7+/hOM7Y5z/+4z+e//3OO+/Esiz+0T/6R/z0T/80tn39TXh/Hn76p3+a//V//V//ws6vUCgUCoVCoVAo/vrzDREh+/KXv8zZs2f5wR/8wVc99v777ycMQy5evAjIfWirq+PuMtm/s31n1zrmWvvSAP7Fv/gXtNvt/M+lS3Jjq6aVZPheGAyCrTyMXi8dTWVkMspRLiyy1T0lV7SEiWlMUCsu7ogwVNjqPYuul9O8RDKZXXvwCoZRp2hNYYxEFJLU9Uxeh81geImWe4Z66Shx7NHun0sTGccM/TScTzy2+tBxz6bmC3I1q1xYzFeeK/Z8LumKYx/LnJHJfeMBELPW/ioiTUqYrbYYusP5/p/Qdl8ci34MvatE8ZCCNUV/uIQXdakX5d7APIllurqZ4Qcb0pkpiSna+/CDNXRtOy9JlqA0jnvSdIAkl2bFsYfQpGGKaUxwufVInmPIsefZ7J6k5UuXw0zOGSdBuhq1bbxRsBfoptEFANNoYOgVHHseXbPYcs/ijvy8P/L3lc5XGYatXKoahC16gwvoeklGCzWLojVJqXCI/bV3UiocolE+RsFeSHOp1fNV+qIupSWWOUVveJVK8TAamlwVTjy8QIb2R3Nh+UEnX6GK0wTAuSyxcICOe5Z26kBnpN8ljUjSDd4IWR5GklPLTdaN9FpmxqILWe63gXeZMJLGJrpmUbbnZN6h7ikpD4sHJEmUO/tl5ipb3VMYej3NawS94VX8YAMvaOXSDdhtjLG90hcRpZHYKAlHVsq2mz1p1GAQRn2iqIOll2Q+q7BLrXgruu7kUUQvkNG3udoDab6vlswB557BNCYYeJcp2Atj7zy7xpZ7dsy5UjoNylU3z5fywjjazss2muB8qfXH9AYXuNp6LJWA+USxjx/IxJuZbEPKQa/m0hQZLU+TcnurdNPV3qx8Zivh/eEShdSBE8CxpnGHS/n7j+MBrf5LRJErrzNdcbbMqdwww9ALXGz+AcU0V9rAu5yXtczgwzJnEMIY23wfRv3U/KOObtQo2vt3JUodJSGhVLh5LOnrMHVVFMIYi6xlRKnTo66XxiQsYdjGCzalMVLaVmSR9FEMo04YtvLcbLY1RzcKuLni8HyvjS6gZAhKBli6YIMmVUvnZKfJ1YHGhS4MI8FSLyFOYBgm1KyEt00lbHqCO6t1LotLTNHgslilLBxe6neYMQs04gZ/1P+/uRQ+zXxR455GxIwDB0o6awO5sj4vJtDTS44TSBJoezG31xwOl8poCC64Lu+tfpJqUufp4AscKN3PmrjMQW2abrRCEvu0tS0mY2nc8C77OzGFNH+Zied4rP1pbil/M441iWVUGaZqDtuUuTFFmjh96C3L5NzDS9jWrGznI5eWe0Y6qvpNtoILeP4qi8bbMRKT04MvUE6KOEmBXrBKGA2YsG7h2eQMjw1+jY62RdGaxqXJOm3uFQ/wrP95mvQwExOHMlESsNl5BoBesIofrMn+Qa+iaxZh2GR/dBNv096HF/eYiGYoMylNQ+IpmlqTmm5zMfk6V8Q5NDTqpaPM19/NROU4IOVWM2nusi6y/xwETS5pL7JQfw+WKPNi8CjHG9+PrVdwvVW2hhcwhJ23CXHcT914bdzhZaKog61XmLBuyaP2jdKtWHoJN5ZS74SYtcEZNnvPEYQbzBSPpX1fIVUczMhcmPEgj3YE4RbrnSfTvHpabmiTSX51zcIw6lSdA1KaaM9ztfUYs+XjmKmx10TlOGE03gfXnAP4wdquHFCZXDV77hnSdCxE10ppbqpy3n/IfKta7mzbGVyUrqlJyDBsMbyGi57IpOtCy6NGo2OYN8vIITOk2PMarmM8sW2wJs1Qsn7ptZiJvB6yyFew4xp3Rtz2zFdGdM3rkVHM7W0ISTzIZah7PVvbmhszbnlN136Nd/RqkbjrnSfrE7IcstuJyJuv75wjzyVXLKXf82omIn9eviEmZP/5P/9n7rnnHu66665XPfbkyZNomsbMjJwIPfDAAzz66KMEwfZA8Ytf/CJHjhyh0Wjkxzz88MNj5/niF7/IAw88cM3vsW2barU69ge2C3+9cBP94RK+v4oubFruGbmHwTkondxCOYkwNCeVHGzhhd28MmnCTGVqsjGUyQJHMqWjsdF5mvXe6bFwsW1U0PVSalXfYKJyPJf0JEnIVvcUleLhPAS705lI16tESUiW5M4PO1jWLFHUSS3om+n1tNNOIRuca0xWTqDr44k0swTEml7CsbZloY69jyhs5/vJyuYscRIg0j0pEFOwF/LJVqlwCNuaY+BdzvfJmcbEmPWpaUwQxcN8EiOEQX+4lNvtx7GHoRWxzfqYvj6TpHXcs0Sxmw8yQXY0mRTNNuUkeDS0X7KnpaOUv05/uEQYtphIbfdHEQhIYnqDi+gjGeizRiOKh0TxgGbvNI5R53LrEbr9c+iandorR/k7W+89y3L3CQAso0qjdJiKtY+We4Za8VD6LMpj+w0y50TLnEk7Cg1NmIRhS7oVaQU0YeYSAE1Y6f7FbdvdhAQhdKKok090s1QAAHGyLUWTUqX+9r4t73K+t0+MNDtxEqQN+cg+gdijM7jMgcb7mKu8lYI9TaN8jHrxFnnNUQeI88S92SSwWjiQP2tdr2KkZTEI23Tcs/nzyzrZrOF1jBqmXsbQ63hhl9nq/fKagyZhuu8TtvXrHe/K+L6G2MM26xipJFDXS9JxcyRBceZymeGH3e1BWhLQG7ws7b6Lh7f18WnZ2CmhyxKHBuEWQbiV13lNK1AuHMQyynnnmMmkwrBJkA5asjYqqzuN8jGutL6Un98dXCRJAiYrJ+h5V3O5p2PP0+2fy9uhON2nqmk2TfcsU9W7c9fFTH7rBZtUbTlJmirdLiU0Y52otPmO4wFle1/qcLrFIGjmchPTmJDPNP29bJHBMmeIIheBhtAsqsVb86Tv2Z49+eylu+lovXXs+V0Drv5wCduc3nPfgRCGTOBbvJUoGmKi8WfdZe6p13EM8OMEXSRM2oJ9YpKzw02uahdp+QmXXZ+inrCvqHG0LtjwfJ7divnahuCmUsyL3T5vNW9FR3AT+2jS5Zw4yWc3P8Wqtszbnb/Dd1W+g34ovyMBlvsxN1dMWr5goWQRxHCwGLHpgRsmGJrg2ZbL44OXWQ9dpq0CX+r9IgMxIIwGNMNXMIWDLgQFrcFd9e8DoEKJ5waf47z2EoMklPJmBO+v/TgWBW6x3kFneIkDjffRSFNWZLK5vGwHa9IOfMdAaKX9uEw34G+i6xVeiZ/hhdZvsVC6D1PovMRTFMwJvGCTC83fQ6BxuPQ+josjLFh3YwqH04MvcJ5XeJ/zP9ATXeYtWccTYiql2zi79VtUrQUmKsexzKlU7h4yXXsbr2hncXSZSkVDYyA6nPb+gGmtwluM/TyTPM2sdhtTHGQqOYimGUyIA7Tc83KRqHInG+4LrLQf50Lz93il8yhJEtMJl1ngdi40f48oCXm+819pDy6yUH67lH9Hre1yZ80xWTmRSvFleawbB9jyX8qPafcvEsY+V1pf4rj1LTSMmxj6qyTpIujWUB6raRaNws2U7Olryt6G3nLueAmkYwqZAD4MW7T6L+NY03k6l43+WfywgyZMXG89r08g++DVzhP5ebOJRpbuwg9374POfk/TLCYqxzH0IpPlY2jCzCfOAHHs53uDNGGha/YuN9uMPFH7tSSHe0yWRhfwrsdrnTRl7eqoPG47Cbp0h9SEOfZeCq/i2Ph6ydq3IOzln73aPY66e2fuiTvlhtnPsi0jcRJst6Vp25jt44XtfsTQ906iPkrWLxWcA7t+JtMq7L0V4Vr3lV3PqLw1dw3NZJhi+3fzRdzrOEWOvrNsvJu5BWds712cuqZcM09J9Tq4oROyXq/HyZMnOXnyJAAvv/wyJ0+eZGlpe4W50+nw2c9+ds/o2OOPP86/+3f/jq9//etcuHCBX/mVX+HHfuzH+L7v+758svW93/u9WJbFxz/+cU6fPs1v/MZv8HM/93NjUsd/+k//Kb//+7/P//6//++88MIL/Jt/82948skn+eEf/uG/2AegUCgUCoVCoVAo/kYjkiR5c2xI3gCPPPII733ve3d9/rGPfYzPfOYzAPziL/4iP/qjP8rVq1ep1cbD5E8//TQ/9EM/xAsvvIDnedx88818//d/Pz/+4z8+tn/s2Wef5ROf+ARPPPEEU1NTfPKTn+Qnf/Inx8712c9+ln/5L/8lFy9e5PDhw/zsz/4s3/qt3/qa76XT6aTXp1Mq3JxLjrJ8PZXiYWyjguut5SvgWbI+05zMVxkK9sKufEsyweumlHMJk2rxVrrDK8RRl4nKXfmqQnPEmSwzq9iJdPQJ8/9r6QqI3NjexrH3kSQxnr+KlppVZEYkIFcEsiiKY88z9JaZrJzIHdiqpSN03LPSDGNkpXmmdj9r7a/m1yCEmRsORFGHSvEw3f657RUMvUK1cEBGjOz5PIo16vSW31P6OztXtkcNO1q950lIpBnGYGlsM6hcyTClS6CwxyIoplEnjNz8M02zMfRK6rhVJY77FOx5as4BmoOX5TMyKnTcs2PXYhoTYxGS0Wc6+vfsGeuag5/mcBldxc/KU/Y7QmhUiofpuGfzspNJrEbLUqN8jIo5z1Lzi2PvZHTDelaO9NTAQEbI/LEopFxZ0jD0CmHYzMtO5qSYRS+yZ59dQ/Z+R8tKhm3NYZu1/JlJ98IGUTwYu3ddr2Kb9TTX0SB/rmHUyldLbWsOz1/Jy+botexVNuQ9ySSWpcKhvN4WnYN5BCt75lmZyPOyJBEJSSpFjndt/N35zkf/rWmF3M0vqyuaMLGtWZkzZuQ7d777nc9usngbq92TqVNjCcto5NGr0fqaPZvsPBOV47kMFMjbgoyCvYChF6hZ+7nceoQDjfdxqfnwNa7N2HOVPnvvljlDFA/RhJE/g4K9kEuU+mnidMuopCY8BQr27Jh0M5OzlIuLRLHHwFtFCJOCNZUb0WTvNavT2Uo2QBz38uvWtAJJ4uXHZGRleLT8WOYMtcJB1jtP5vfzQO2HSETMuxrT/ElzhfdPzHGhE3J73eQPN9aYETWqpsFCWeOLW8v8jwv7eGw15h0zGitDjRlHtlUtH9aGsDWMOBW+QjEps5Q8y5S2SETAVDyLhmAgPL59ZoaFQsyGr7HkgqlBL0iYcjQ2hjHzRUHbh9/vnON95cP8997XKDNFI55gU1unT5N+3ML1VzlufwvPDj/PUecDVJIKtjDoJH3W9Ss4SZlAeGiJRo9NmsOX2V+4m7NbvyXd7/xNpkq30/Eupw61nV1t2LUYLY8Cwa0TH2WYdJjiII24zpJ+ATfeQKAzKW5iNX6R99vv46y/io7BurjEzfERPAK+7n+ebyt/D6fCV1iLz+f9S7mwyMBfzSNQmjCZqBxnUbuPQ8YEXxz+NwrGJCe4nz9yf5mp0luoiTksCkzGEyzpF7g6+DoFc4Kj4kFe0V7gavcpJktHWO89Kx1GzZk8ujNffzeGsNExKVClk6xwufUI8/V346eOhK3+BcKwlUsQ3cFFGuVjJEnMLeY7uBg9hakVsLQytihzfut3QOhMVu5kq3eGRunIWLtZLixiaPZYBGsvDKOObdbxgw5h2JQytzT3aVYHRuuyNKJooevlXAYoEIg0afdOdrYZGaPtQTYmAJnLsOmeYbH+LbzS+fL2+KggzVAsc4pa4dBY/s+9yOrnay13byaj9zbaj4z2CX8TMY0JmXeOZNc4E3b3X1kEcbfr5O7+ZS9Gy95ofXwzuNY1ZN+Z9dmjY55rkwAR7XY7V9Jd83tv5ITsrxOjE7JG+Q56w6tSTpQOgkAWWMealFI0vZTrnzOywruv/iBXW4/lnzfKx4iScNcgv1xYJIj6aKnLkGmU8wHMaEMlhCbd8rzlvCBJq2orH8Brwhor0FL7vN0oZ4P00fNKaeQincGlPV1wMrLjsj1z2eRS16ty34wQgLZnIwfblWCu9kBuNZ/dkyYMCubEWGcl96po+P4qCUk+QcmuPRuA5/eKwLb3MfSWxzqPne8l+7ttzeySembnbpSPMQiaY88aZEfU6p/DsaYZeFeJYy8fyIdRZ9dgtugczCceo9fr2PP4/nreEF1rIDx+/bJxMYw6hl5k6C2PDTh3Thyy7x/dC5XRKB/DS+V22bPKGqXRSaJAJ05dGjOprhe0XpdbUeYU5kXd/J1kctbRCXVWXrLBBEjZwVT17rEJZ8bYoPBVnt/OhYVRsmTe+cBlx7kce54oGqLrDp6/lg7+t8vdXoOZaz33USrFw1h6iVb/Atk+uVGyNid7fs3++T3rZ/a+DKOeW2j7YRdDd+gPl0YmbauUnVlcb50g2ERohfR5zxDFLlHk7rmQZJkzGLoj2xi9ThS7xLGXl72icxBDL+CHXcKon19jqXAIP+jkZaVaOkLfWyUK22PvIltEupbMRSYhP5SXHU2Y6URfXvNe5X6vdyCElu8NzMra+2s/zpFqibkCfHXd474pm5e7CUVDsDYIKZkak7bG2iDGj2MO10xe7oY0fZ8TE0U6QcKJRsxLPY0pGzqB4Fw7xItjtsIhzyVSDtd0z3Bv9Qf4psYMZQPeOdXngutwrqtxqRdxe11nLp3cNX3BkxshdVunaAj+uHuB55q/wh2Nv0crucLV7hNMlu/gFu6hhMOm1qQcl7mkvchy7xneUfxeNrVNDAw2ucww7lDV51iIbqYnXF7wHqY3uECjfIyauYAbbWJqRVY6TxDHg2suAmbPXkrStdxZdapygoPaXSzFX2dOP8pkPMnT4RfQhUGr9zyOvZ+yPcdt4u18pf3z3Nz4MH7S4yj30MVlRtToxB5Ph1+gbh1kvX+GojWFH7n5fqysnMyW7+JwfCeHiiV+f/Aod/E26qbFuWCdBlWSJOFL7mfYV7kHSxQ5v/W7HG38HS72v8LQX0EIHceaJYp9Joq3sNL6CuXirfT65yk4B/IFhTj2uaPyHTzT/GU0zWamcrfc39Y7jWU2MPVSuodTy9uCe+v/ExeiP8PWq2y6Z7m58h60RCMQHnG653xt+DyOWc/bs0wSPtoOjrYnY30WAk0vUnEO0k33hsr6UaCYyoRHf3+8j6/Kfd7eVSAem/xkx+1uB8cHs6PtcL10lJ53FdusE4R9/GCNWye+AyspcKb1WyRJyETlON3Blby9uF4bPMq16vNfJV7tXrJx1uvh9dz3zrHPn4fRe9l53a9nXLLrGq8xyc++B3YnwM7GeH8Z5IviwoR0H+P1ee0Tsm+IPWQKhUKhUCgUCoVC8dcRNSH7C6A3vErZ2YdjzzNdvD3/PAi3ZA4so04S+2P5EQyjnifwE+gUnYOpI5ImN0GPbDYViNTAQsrJBt5l/GADP9henRydtUvZmzRcyFY0pHmFdOkpWNNj5g3yd8IxyULuYJNH3WQyw5YrV9+v5z4TRW6eNFdGZTQsc4qKsx/LmqXkHKJSvAWQERjblOcqOgdl9Co11TC1Yr55U0rEehh6gc5gPKLgB2tSmqVZWOYMmpD3mW2KZoeLm5SLyefrDi/LnE+pK1z2LDI0rTgiZZrK8xgJYWAYdVq95/Ofj66ENd2z6abl1TyK5Acb+SbrnfSHS5QLB9OEzRpF56BMJBz7GCMOV3ttdt3pEjRqDGOkhiVZxAzIjRjk/aX52fLkmeObnAvGZB49yJw6t10xt00UhCaTZwdhk4I9L5OV77EyJ4TGXO0BTGNizITEMOoyCemOyHAQbu3KPZJJI8OwTZKElNJn1R0u53muNK2QJ9bMVhMz1zzYdmjcSaV0myxDmp1HSka/N6sjmjDZX3vnWLL3obdMEG4x9Jb3dOzK3uPoM842aI9uaDeNiTQhvMAyp3Kzl6I9i21O0thhIpPVddMos9F9es+Vw9Fcbdm9BGkdr9kH8/uQksY1mr0zeP4KMslqRyaTNmtEkcu++oNEsZ+XJ02z01VOP4+0SRc4j3JhkSiSbU1/uETHPYsfNAnDVl6Wh/4Wepqj0bHn6aVyryzanT0zP9jIJbMgV99H64OulSibszuSQcucSplpUsbo8w6jnW1hjBfIZ2ibdTRhMmk5TDsCLxLcXLaxNbhnEppexGrY47fav8LVfsQL/hoFQ6PpJZQMjcPVAm0/QRdQNyOO1yIqRsIt5ZB2EDCIQgrC4B36BxBC48HKP2RDXKFswOFyyOWBzX9a2uD/t/E7NGyd852Y378S0vQF7UBwe92kG8QsuyH7k32YxgS3awe5T3s7+6vv4Bbu4VzyZ7REF48Ba/pV3mHew0eq/wBbGPhiwKXo62hodIaXcOMNruqXCYSPO7yYPlebi80/YLN3mo53mZKzkCc3vxbZirc0anJxrDkSYpZ5AYADyRyb2ibu8DLN3mkSEmkAEmzwWPvTzNXfQSdapqRNMe843GpNMuWYvKVS4X323+KO5AQD7zJN9yx9b9wxWQgDkwL7nSKDMGal8wStpM9LwSZPtv4TTwSfp6iZ/O2Jf8xcskghkWYNxaTCLcVvYrZ6n8zxZdbwgzXWuifR9CJR7OV9x1ztAQ6V30mjdJhiLBM7H699D5ZWJko84nggnYn1ElOVExTtfeh6lZna/RQSh76/Sc9fIwg2ebH5O7wy+DNe6XyZfrxJiEechPiRi65Xma+/W0YCd7SDCcm2WUESUS0dkbkphcA0avT99bHjHWs6b7tlvjJpyjAWBRMGftjLJf2ZWUV2nHQ67Kf5HzOTj/H+1UzbXpCOgFqat8wP1piu3stS9zGaySVqxcNMVe8miIbUi4u7jCReDcusvmkOi3D93FrX6i9ejcyIarSvy9C0Qp5I+vUQhFuv2eEw347xBp7T6Bgvc7HeRk9drmU7miffvt73JElelkbdFa8VHQM5ltwrgvhao2Oj7fzOMetoP3w9c5esfI+anbxZqAnZXwBBuEV3eIUg7NGP5KA1k2qALDyWNY2hO3mBDcMWmi7d0q62vkwQ9qQeN3W8Gd0fZprTshJqVp4MGBgb8O5M3iz3PG1X2lFLdC9oYhrlfAIyOlHU9RK2vS//t6YVmK7emw8wM/vbvTrj7HyjSJnDAD/YoDO4SNVZwAtadNyz0i45aFIwJyg6B3HMWt4xCwRe3CNhZCIR93BTaegoMgG0liYc3rbh1fRKet3erga1P1xionI8TbArbZx3TlKz+8wa03rxltR+fANN2LJREHs3tllDmCTbkxbDqI+9IxhvCNzhZcJomNuP9/oX8IMNimlSb9i7s0pSq2N5Pi13RARS6Yl0RsrcDkffXTZozgbno/pv05hgNZWGymSj2wMC6WqpjQyY5d6cOPbywSw7Jp66XpUW0v5VoqibWzED+STaC8fLVZaIe5R66ShTxSPY1qyUSIY94jiQScO95dzFMY496qUj2xPU9NnK824vNIw6MHXcs+kzkDKFgXd5l/uXphWIk4CmdxHHqO25OJFN6EbJHEUtcwotTcCZlWVDL8pJmNCIoq5sB0gwjXIqf32Zbl8m/R5tG2C7HRj6q7sGR6OpAYSwpeTXmkbTbKJoyEzpGMutR+m4Z3O5qZRopA6vaXnzwy69dM/kaudp/GAtlwVnz2O0k8zKZBT76QBiu/7lE1Uh0v2TFn46eAyjfi51A3DMidz9yzDq+TmLzkFa7pkx964g3GLDfR5LL8nUIuYkmjDknsURx1eQ7WOeIiPx83qZtYVZHYlinzgJ2PSHPLbucqEbUjYFl/rQDQXTBZ2e1uNu69sI4oR5McGlQZ+qBX86eBFDSIX2fAFWPYMNX8ePoWJEzDg2ddNiyrbpxB779GP8mfsr2BTxY8G6b3DR1fnA5CzfZH6YmiWYK2rcN22y7sEfbl3B1hMWSjoNW+e2SoEHS3+fgqHRjXx64Qr7jRqGsNkQSyTEHIoPccHfwkidyA7GN7Go3cdi/BY+VPr7GMLBjTfwGXCs/ne5q/ExZvTbON74ft5S+07q9kHmnbvyRbls0WCn81yGY9awzCnpzjhcpuevUTP2c0msMJfMMFM5kdeNxcZHKKbnmhKLxElARMDFQZdN32PKEbhhTJQk1EyZFP1Q7X0cqX4rE5XjTFXvplQ4hGXIiYYfJ5wMz3Os9t1URZGX46d4V+2THLDu5U+8/0rLD7gqznO29wVurbyfk93PshqdJSaWUu+gDWhpeyz3PWpagb53lZX246wHZ6U1vQgYxh3mk2mmk4Pcpj8onY2DTTa7J1lrf5X+8BJR1MH1V/ly+//EMWr0vWU0vYJlTjHhLOJYk2y6Z7nc/lOG/jpe0MY0ymhpu531/aNuh7JOmyQk1KwFotijYC8w9JYpO/uYqZxIk0fbebs8Vb2b/nBpbECdj0uiDn6whqEX86Tr1eKtI4uV2458SeLtahvrpaOsdp7OB67SwTWm6MhFH9dfww82uNp6jJ53FUercsh+O8Cuwf2rMfBW39T9W9fbx3S9xYdXQ9MrY/uy8881+w1LLl/LnqtRXo8Ff/b8x9vzHYvaSZAuvLnp+c1X/Z6EJJ98XW8S9mYyOma53iTOfIP29nLht/CGFwbUhEyhUCgUCoVCoVAobhBqQvYXgECkOYs6BNEQITRmq/fnyRmz5Kj94RIJCbpeQter1Io3US8exjQnpZQtz2EkVyMm09UtP1jDMqdwBy+PyblGJVEy71Ev/z7LnMFKcynsTL6XJfScLcsEmKNOcFHkjhlYxPGAzd7pXKoXBJtj15ihaTZ+sLZrhXTc0Uw6l2XRvEzeFcUeg+GlPGcayLwVa+2vMvSW85WNJIlzZzmQiSyzVe5R6Vgm6ao4+wnT47OIyCidwSUphYxcNM0giQd7JirM7rU9eCW9R4N6cTGXs2WrX3v9bpbIE+QKTcmaGYty2tZ2VDGK3PxcXiCNPAr2Qu6sJVclZeQiW/XUhCkjhGmC7qG3zNDflvDY5mS+6n+t1bhhIN/D6PVnLoJRJHPUjK4Q6noVL1iXK2RZrqvIzd+LluZlmagcH5OPZeeQyY4D9DR6Kk0dZFTT3cPgYmdZ88IuQSzzhemaNKfpDS6MXKubl7tm7/S2fCYtuwCGXkvPHVIv3QZs5zaRzylO77XEzmbTNmWS7qG/TnekfMJ2hKVo79913UYqy/P8Ferl28fKcpa/L0kd0bJy4A4ustk9iW2OO86CXFGWxgLbyb9HqZaO5M8EUpliKqOOYymLutL+CiDbsG3jEzs/v2VOUSocIgjbmEadUuHQmAxGZJHiPdC0MnESUi8dpWjP5lHBjCxf2ETxcO5kNVrXAYKoLxOJx0M0YSHSstgfLuUr/aNkuf2yZ+gFm/j+aupkub16O1E5nifRDcPWSISuk79DkSZKBqgaFi+Jsxyp6XhRgqlBEEPTi9mXTDGll5gtGtQsg2mrgBvAN5ePMIygYQnCBCbMiHkn4EhlyJ+sWswUBG9p6CQJlDWLRTHPg6W/zwcqR7i74fPWeo9z7ZiXuyGTjkEnSCgZgm4geM+Mx08szmAKWHaj/Fouamd43lvB0Qy+q/IdVC2dBXEHc8nNGNjsLzgcL07RDQNiEpp0GIg+jjAoGBpvSd7KPdr9HEwOEhEQ4NFKllmNXyQi4Gr3Cc5u/RYAZXtf2mdJw4pq6Yg0WEKgCZNS4RBVYx7HkvXFNmvUrP2sDp9nNp5mmPiUtRkK9gJJEtKL1wnjAXdXv48emyzqb6eQVLm5UOXWipR+bnoBR+oWl/0uE84tHIgXsSkQxj5R7BFGQwb+OneJO7i1avBi53P02MQWOu+3P8h58TQPlg7xraW/zVWxwe3JCebKb6WbrBFFHYZhm/bgFcr2HP3hErPV+9hXf5Ba8VaZAzEeUC0colQ4RFGflJIqQvr+Bue0c9ysz9AWso5NVO7azg+YSm1nnTt4S+N7iIllomezjmVU0ITJPeaHeajyg9xf+R/zOuB5V9kaXqDvb+AF7bwe522AIeuTYdRxwzWCsJ9GvwzsVJGgaxbVwmIaEZtho/O03B4gjDy6Ppo/EWQbleUMLJuz+XaHLCoaxwOSJCCKByMqB5PO4GJeFrJjg3ALP+xQMqdyuXzBXmC6fIyIgKHoESVe3v5kie5fjTfLrOLVeL3Ji3dyrehaFPX2/Py18Hrv/fVEpF6LLG+7z5H/z8cBr+N79lIW/WUyunXEDzZec2R2lDh1hn6jkVo1IXuTEUi5QLbno2RO4Vjz+HEvd13Mkz+nL9zQK+iahRd2idKBUTZoz7Kma8Kk1b+Q7wGK0pd+Pe3wdgJFmZQ2G4TsTN4McrDW9bcnXtqII1wmDYJUHpGEBFEv38OxN1rqSDi3Z0WTDbNLtXRk3N0RQcs9kxfoXv98OuBvXbPCSvmVRhyHWHqJhGTElW8KPZVRtdwzaFpxbIA+StaIDL1lht6y1AiP3F+WCDK73szJLklCosSTSS3TSfdC/T3Uy9v7Bycqx+Xv66Wx+231LzD0txOoeqmkcCdx7OVJgzNZnXRgtNE0W06a08G70KyxxkVKNEs49jwD7/KryiKu15gKoaWDie2JY5J4u55nnAS5HDAItygXF2n1L4ztczSNCblHLg3v99P9de7gYj5x27m/Luv8x78rZKX9OF6wSRgNpTzNmMglNtl1Z/UtSQIa5WNpUupqvniwk2FqG589Q5BlbWd5zdwFpXxne9KV7YMrFQ7taY079Ldlx53BJUDu68gmKaYxsWfnr2mFMRe5DD/YoFa46ZodSZRKdcf2II4smERRZ1taS0KSJQZOzxelUuOhv0Uce6nV/NX8GelGLbdAHz139n5No4znr9B2X8AdXqbg7M/3i2YU7AVWO1/Nr2EnllGhUjxMo3IHumZRGpHjtvoX9rh3PX1m8vPRzrJRPgrIxZtm77R0Rs32x6TlJknCNBE5ubNWpXiYl+NV3m7eyayT8FLX55ZywqSdsOZ5/PHgV5gvmSy7ARVTY7Fi8HLP42o/IIgTtrwENxSc7pi0Ap2iEfHeWZ8Pzg3YX4g5GVzESyKqpsHtlQoHS9APNUwtZrGq44YRW56sF2UjYRAlVIyQoh6z5UMQJ1QtwXl/k6nkIJ4YUjIMekHMl73T1JMK+7Q6bVaoWoKGLXA0gznb4TZrGiuxMDWNS16XC9pLREnC0VqBY9otlJMa8xyhqNVZDc9wW/XDTFXvzt/3VPVuDN2Re4H1iuy/NAfTnKRoTuElPRyjLif25hQRAe+yPoouNJ4c/jbN8BUqzn4ONN6HJQrcoX8zM9S5PXkLGhoRAc8NV1kdhFia3L8368ADE3W+t/F2dHSeaf4yfW+V3vAqnr9CtXCAScfA1GCmcgJLFNmMZdv0/Y1v5uvdTUwhqMYVhomPhsZtyVs52PgAtlFhsngbllamVDjEMGzRHl5iyrqNhIRS4RAt9wyLzrsoaVPUS0dpilV0zaYdXsGPY2biOb698ZPUjIWx/S9TpbcQE9BlHceo4wcb9IdLdPvnWOufpqbb/GHvl2hpG5QLBwEpW+4Pl9A1e0xSb1tzOPZ8LvEF2OqeYrZ8PE1ErbPWPcVK+3HcwUVa7pk0wXxIpXiYkjWTLnBe2+EvSUKSJGS196xMHq3Z6VaLYl4/osiViy1pkt9s4bPbP5fvA81+b31Eau35q7jBBqudJ+lGK9yqv4PJVL4a7kgwnt3vqzHaFrzWPVavhdH2883k1VwJ/7qjvQ4Z5ZtJNq7biWk09tx28xeJmpApFAqFQqFQKBQKxQ1CTcjeZIRWoFI8TByHIHQsrYyuWbnLYCbfgu1Vd89fIYxc+sMlKta8lMwEazj2PAV7AT9Yo+Dsx9CLlK1ZKS1I8+iUHCmrul54VZonpJvy02gZjDvgdPvnxpJMjkZH5Gb9MpCuoqcbOGUeMHPPVXy50h4z9Jb33MBacA7kkQUpaTEoOQfzRLtCaNtOcJqDoRfHVpDKBSkRNI0JmWwziWm5Z/J7yGQTfrDBVroSVykepmCNbzre+ZxGDRl2blCO4z5R1B37LPt3b7jKfP3d+Qrjcudx4jgcey9R1NkV2YjSTdMZO6MC2cqNptn572bGJPKaPJLUVS/fIJu6f2WSO5lnTkbRRleCdm48lcftLcfIk2+nEaDsmsuFxT2jjTKKV8j/3XHPEobjeciCcAvBtlvTqGRv4K2OvQtNs3HseRKSXF7j2PNY5hSev5JHdLMInvyeaOT69RGHUJMsoXbBmtp1/VvdU6msNdzlZDb6/DRh5qvD8rzjeVWSJJb5qwav7KqfRecgUdTB0At0+y/lUUl3cDGXA8mI+qwUoI6s8F5PntLqv5RLDHdetzu4mJa3jZFo4bU3g2vCxA828mvLynaUyvhkLrJJsm4kW+HMJEZZRCl7v56/ItsiEuJ4wMC7SpSW3eyZ7HyGO813ev3z9PrnabkvEsVDuv1zuUw5DFtj71K60ZbTBO5e/lkmVTQ0+e7c1AnyWklmx3JFahbd/jmOmvu4rWbQDgTHGzZLfcHKQGPGtvmfZj7O1jDiA/MGd9QTvCjhprKNH8dMORp/4p6lYiYcqwa4oUbbN3m6aeNFGjUz4k7zJm6rFNNcZoIpK2bdl5G+I5WQb91vUtR1vtK7zNl2wh21mOWBTTPQWSzLZ101BR3Roqs1WY3OsuL3sHTBkeQwMQnPc54PFe+n6cU0vYSFkknD1tj0fW7WZ0gSmLcqFJMqK0kTXUDJ1KhRpq1t0IvWKeqTvND6r3hhF8ucotk7zUbnaemMOrhEZ3g5ddSMMfUiYTyg413B9VcJwhZVbR8CnTVabNDkWOFDzOlHuUu8kySJeJsuI16aELSSPi8GjzIZT3NPaZZhFFOzBCUTntiIeLi5TJzAoWKJxcZHCMMW0+U7WKi/h5pxgDAtUu+330MxqbDPqOCGEZd6Ebc6DWISNrVNQiIOxLdxSb/IxuAsg2CLXrBKmHhSYqvZ2EaFQdzk5sa3kiQxBxsfAGA9OMuUfRv74kPcar+TunGAgqHzongKL4mwKbLY+Mh2tDYJEOjcEh9nUruJo42/k8u69xVPsBq3eW/pBxBo+GGX+fI91EtHc6fVUWlwHPtowsjLtiYspqv30g83abpn05yn3q72XQiNIHLpeSt5my6EIXMYlo7mUtNRqXkQbhFH3bzf2Xm+gbc+Uo+0tA5tS77rpduwrTkpCU23QwjNwtAs5qr3owmT54ZfIEnbb6E5qQx/u7/aa0yxk9G6/GbKGXf2CW+ENyKHeyPnHXMOfBMdKN8oo2OCnWTmbX/ZCKHtqRry/BXCsImul9Lcqq/t2l6PYcpO1ITsTSciSGVNSRKy0vs6B523cevEdzBTu5+Ksx9nxLVwqno3k5UTNEpHmCjfSVE08gFG1TlA0Zpiof4e3MFFTL1Ic/ByLtMJwi2ikYH5XoNpaVm/nUl+tMJmAyWZMLgOpIPMPSrNTt1zFHWkDTYJjr1vz0J4rcGeJkwK5gSN8jG6/ZcQmoNtVBgGslLoqSzTMhrY9r7cxr5evCUfpLuDl/HDJkG4hTMie8oGcGHY2p5QJXE+WPfDvfXbICVVo2Fz0yin+++m8v1aO2V8Qits7+sT285ijjVLu3+OJE1l0HLP53t8Rh038/OMVPZM6ikQuaZ/tHMZDbFnVu47EUJj6F2R7odsNzijDU+tdDv10tExZ8PRxKKZoyZc23rYD/fWvWcpG0bLpHRiNMY+2ynl206vMNgx4PDyiUoU+2hakSDsjVnQSttgY9e5sp+PnqvZO4MXtPPv1/XSDndEPf+bptl5GRDCYKJyPN3/VMn3hWbnHZ1cx3GfIOqlE5DxgX42WZNJ4svpNaRld2TSP/Auk5CM3cv15Dp+sLHnHoUg3KJcWATku91r4rFT1iPdDcfLViZfzu4ziob4wVo+ecv2go6eY/Sedzp6jg6sht7VsT1gleLhXZLGhAShWQhh5wOjJIl3XbsQBgkJfrBJFHVy+WQmxQRw/dWxZzEqf9xJJl2JIheBYNnr8/Bak7UhXHIjhiE8sdnngWlZjz8wL/i55RfY8uW/iwbsK1gcrkR8fO4IL7YTTrYMdJGwv+Ty7ftbTNge07bHlKNzqAyHSrCvEFMxIyxN1r8DxQFTdsh8SeO7phd4cDpBE7AV6OxzfEp6zEzBwNQSFjnI/ugAJX2SWbOEowsqhtzTdkK/jWfcdZ7yLnK5P8TUYH0Q8aXBr3Ix2uBPw88TxDFdNrnDmeWx1jr/T/vXOJV8hXIiExRrwiRJQrr9c2OD1KG3nPcPQSjlrb3BBZq907iDi7IvMya4MngaP+7x/PAPOD34Agkxx42baNOjoDVohR4BIQslmzm9yn3mt9LUtvha/wrteEDbT2h6Ce/fJ/j++XkqJhQMwdrweUqFQwzCTe7kPhbiW/CiGC+CaUfjLns/s0WDIIlY94foQjBp6wg0NDQcYTGIm1Tt/dTsg7zVeIi38AB3mg9xu/ZOSsY0neAqq4Pn6A+XaDCPlVjMG3dye3KEp4e/A8CheJEZR+f99nuYtCxm43l68TqgMV9/NxPaTZSZZMoocHNyE5vxK9ysv41J5zC3JW/hYvJ1zopTFJIS+4onKDPFhHULYeTmLqCj/UbJmskXcv1gjc7wMq3+OfbX3iEl2rFHvXw7jj3PXO0BLHOG2fJd7CuewDa2tzFki7Z+5CK0AiVrltKIK6mul6iX35IvnlbTyVqWCier/9milmwzjPzcLffF3LU3P6dWwAu79IN17uJtvM3+TuYMufc7kxm/2r6cnQuoo2T9xJ9nsPxmkLXxb7ZdesbufmZ7MWnn87uerf+N4nrv+LVMYt/I/r7ruS1mWy8yl+PXwp9HevpX740oFAqFQqFQKBQKxd8QbuxywV9D4tgljsv5v/1gja34FVbajwNwZOK7aYbnKNgLGLpcFer2z+VSHddew/PXZE6KqIcQGpuD85jGBNVUgrbcejQ//2DEBGJn9MY0JsZWq8ekN8LIczpt5w+ySZKI5DWG93W9RJRKLXdimTJxpWXObEshEFJK5+xns3syv2ddL9MdXsmTSwZRL12RiEeSMM9Q1ecIC322uq2xqMFG5+n8e6OoQ7mwyMDfwDKqaXLhIN3wPBiLPuzE96WTYbV0hN5gif7wcrqROSYZiRyN5uaKog5R1KHoHKQdSAmmppX3eCbSQU46iMUkyfYz1vWSlFQkSX5sFjnY+S6qpSMyN1YamSna+/c0jDD0OglxLgvdi87gIkb6/oERV0wNIXSZZ04r7ipHGZpW2M7xphVgJIKYfe7Y8/k71DSDoiMjdntdc1Y+QEZidq5cZQl7R6Mq0cjvlgsHGfrNvFxeDylH3I5mZRJgkAYs3cGV/Nxx7OGnK49+PKCvGdLwZSSf1miuLpAroaOJo3d9P3GeIDkKpVtaEg9S0xL5XTK58u5yNxqNEAgsa3ZPCY+MpJZTswr5zA2jnjqi7V7F2yuivfO43e9EJuUOoh5J1BtzZM2uXyAQmkMcD/LnMvqMMjLnudH7i/aQRcnns70SvGcZTyPT49IpKUs09BpRPMQdXMwPt8wpTN1JowubMuntSHl0rEZeXnSjRld0maLBhU6AqQm+MPgj3irehaUlzBYEukj42423oImExUrCkivoBDFuqPFyD94+DXUzpGREvNSt8OSWxT84vILrmzg6XO3DmfYARzOoWjp3Twq6gcmTzQK3V3xWBzF/0LrM354+yNFqgKMJNAH9SONcr48QRaIkJiLifuMeLE1wyfXQhKAfB+x3ihyxpwjjSdb9IS925HNaLL6belxh3riTZ+JnEWh83btCI6kz8Ddwhxc5VLsLgFX3FLY1l5e90ee1F1mdLtgLDP0VKs48FX0O0ykQxh7lpISta5zqfI4w6mNXiiyygBvEzBZNnnSf4G5xL9OOSc0SdPyEWyqCx9ZgdTjgOw/aeJGOqRfYb55AoPGSeJnN8AKV4H34sc6pdp8uLlNelSnbpmppzDjQCeCS/ySOUWet/SRvq32cK9o5pjjIs+HD+JHLQedtOJTQMBn6mxysPIhefBtGbOAJWZebcZ8HnL9NFEeUdZPVQcjX43M8VD5KyzfZ7J6h5Cyw0nmC5XhA0TnIc94y767+UJ5fbBh3eFY8Tlmf4bb4NpbEch6N0/US1dRIBKTUT0uT3W+5Xh4Byt7LZOUEK91nMA05JukMLlEtHGDTPcu+yj1sDM7SHy6x2PgIw7A90lYX8j5sK5Wb53UychkETTTNpuIs4PqyXuxsK7I22DbrOIVDqTvsdK5SmSwdycdFttlg1nkL7fAKF8USZ1q/iRDaWPnayWibCK9NSijSqO6N4s+Tv+zNJkniXe1tRlaXryXjHj3m9ZBJR6933mv/7mtwe/xLymf2F4VIkuSN+TMqxuh0OtRqNUDHsfePNWxJPORA4/1oaGz5F3MHwJ0NihAGk5U7MbUCq52nscwGftCkUTqCH7l4QVu6MQabqQTP2DEILGGbk4TRkJI9zSBoEkVDuVcnn/xUr9ko7BzI7jz/TqSsrTgmidx5fMFeuO6koFI8TLd/bmzQr2mFXZpvKfMrY5t1grC3a4KQOUwJNHTdye87+/5S4VA+ALvWBCMjkz4YepGhv7pDLljKZUuaXqFgTe05ubgWmlZA1wrEifeqk4bs2eQDW6HhWNIp0TQmKNmzdIdLY+fZPtbIG73Rd7LXs70ee02M5J7EcWfFnQ1s9v1Fez7f+yYdPstYRnXPSfzoNZpGDV2zrnvcXjTKxxgG7XzCc633LBCY5uSenZGul8au+42S1TmBzAb8WpJ3ZuVL16vEUXfs915rJ5ado1xYxA97UlK4x+8Kock9bukzzt71aykjo3U9q1vZZO9aewpH3/3O68kWbnbuIbvm9yPQjVpeNrOJfzaAe72Dhez3Jysn2EyTn++FZc6gaxbfVfsYt9b0XEoYJ6AJOLkZEsQJ75s36AWCspkQJYJNTxAncFMpYnWoMW0nDCLBM1sx374QcVPJ5dlWlfunt/i9y1MMIkFBl3LEtSG8tR5yc7nPMDI433NoBRqbHnzzzICXXYdbykMGkcZF1+K/XRkwZdroQjBb1BhGcKE74GDJ4ZLrEZEwTHzmrDKmEHTDkKppECUJf+J/iY53BU2YNOxDLHef4HDlgxjYnGr+XwDc1fgYV+MX8MMOfX/9VQfCowsDGaYxwZ3lv0UoQtaS89yW3MOkUWQz7PNc/CgPGB+kHQ+ISZg1yhR1nZe9NjYmPdHHTEwWnRoVU+PmCgjg5R5M2oJf2zrFMOkwiJq8VXsv05ZNyw+4f9rhspvw+OBlHqotcqET8PXkOfbFhzhSrPOY9wIxEd1oBUsrc0dygq9GX8T116g7N7HSfpyDjQ8wkxzCE0NeHj7GMNgijgfMVe/HFmUsUeTs1m9RKhziXuvb2W+X0YXg/LDJjF7hS95/Iyamau7D0WpseC/yTfa3s5Ss0WadRjJLJalgCympXNGuYv//2fvzMLuu8z4Tfdfa05mnmgdMhZkASIATxEHULIqyZEuWLMuWnbZbsd1O3ElfJ75PknuvH/eT9M1N3EnabTv32m07sRMPkuxIimVNFCVRFGcShAiCAIipUCjUXGee9rTW/WPXOagqFECABEVKOi8fPATOtPc+Z++117e+3/f7iPNC6T+Rik/Q9osMpm6l5s1224UAa+5vnXN/o3t9zBnFkHYkmbYKZM1x5lovkrD7CZV7RZN5iGo7s7FNLNVPRLb3sSGKtWPd++Tl5vGXr9vOfa4z/nauq0jSXKcvtZel2otXjDOJ2GY2Je5mOBylIVocrX/umpKy18JrCSR+ELb1arzafG4j5IpDtQobb9lgp1M+8Fqbar/xaCCkUqmQyWSu+cqeZLFHjx49evTo0aNHjx493iR6AdlNRoh4t1cYRClayxqg2D7LTP0FNtt3dp9bv1qhdYAtUyzUjqJUK+qFpVpoQoSQ5BLbcMx011lRrCtg7MgHPX+BUv04pox1Vw06K/UbuQx2VsqlcNY1ar28f6sbLa9+fvUK3EarL6Hy1hlWyDXmCY6ZRkoHw4h1nZwMGb+igLNjCKB0QNIZYj1tdwaBROmAtjvTPe5Odm51b6tXW0nprPhGBhGXL5FOk2FgRTJZXZMdS8Q2X9OJxzILKNUiZvddNTu2uui4ubKi3Ol7orXCW+nJ4gdFKs1TqLB5+Xszkl3ZV+TE2CK+UvzdpdMD7zqLXzdanQzDKvnk3jXnxPpi6ejcaHQzfJ3HTCNxzaxX1E+utWIIcOONMsv1lwmVh1IBmtUrtuvOJzSOlccyC10TnU6Rcxg2qDfPbHhc18IwkmsMNzorxhp92TRng8Jk2+pfMUEx1zoZWgMr7n/xlfeuM4JZVxjf/byVBvD11rk1zmnrEcLpykAFoivLvZ4MaudazyX3dn+n1S6HiXUGGVoHGDJG25vHMDIkVxwVO3QlrvbodRWbCxnr7q9hJLvZlyCMGoTfyKq0EGb3/aUV9cJ6pIxHpjxWllB5XHCrPL7Y4Fvz0fYCLYgZcLDPZFPKImVo9mQ8jpXgRAW2JkNihiZnhTy75JG3Q7YmPe4dEIRa8PhSjluydUrtGI6EvK2JrfjK7E4r5lyT6WacC40YoRbYElIm1AKTkZiPrwSekpR9gUTQDENMKZhuhLxYLfNU8BWUhoJtM2A7GBgse23ipmBvziZjS0qehylitNqXGHB2Y2CxKX0vaZ0np3IcyP88W/MPEtdxNon9pKzI8TcR24xhJK/qoKZVC89bRAizO/anYiNU5BLn3CfYoW9nQc7RCgN2JjM8GP8goVbUZZ2zPM940qIRhPTJJHszKW5NDNBvJHnUe4Z2qKn5gpMVzeYklFzNDrUdXzUZMw4w7MQoeR6ONJhpapbdgBEdXaO2Ifl47hC3Z/LEDMGp4l9zuvh52kEZpX0qusWQuQeBpOpeopA+QIZB5jhNW9TRqO45PyS24+smxWCSO3KfZnPsbhqiRdnzOepNsd3JsxQ2SFlDVBunSMp+Qu2zz3wPl1SRgIAk+a65SagVPgF51U9eRQ3YvaDOcOogy81XVtxFNwGRjD1urRoHRHTidMyxVt/TE3YfjdYkWiuWa0cp6BHa3jxL1SNRv05hXXEPS9qDLNSOoYkMOzqGRFEf0mDFWOqyuVQithnLzHYNqaSMkzaHcOxh2u4MMbuA0n53HhN3xsmn9jGeeycpZ4SZ9veoiwZlubDh/ef1OvF9PzNWb5XsGNyY2cRqJ/Bg5XoA1hlfvT5Wn5evp9n2ZVflH3x6AdlNRusWzfZFYs4o+VTkEhSqBi1viYTdx4I6031tZPdurch5opOz4k5FDX9XnaBNb5lq4xQLlacxpIO54jaHDq45YWy0J6PtrHIY20hep7UiCJsrjlj1DT/zCnfBVY12NxogO495/sKaQUlrFTlCSgeBiGySlUvbnaHRmoyaRoblq0qzMrFNeKuCmdXuan5QxJAxcsm9V+wrREHZ1Rzq1h+DlDaayJ2xM+lV2l9j/9s5hg7N9tQVA/DqxoLdINFb7FrSr8cyc93PjBpem2sGm9WBXMf5pyNV6TZi9pe7z6+3a43cCJ01v+dg9nD3XN2I9eeDQLBcO4pxFUdDYKXhchzbGlyzrdWypfWf2ZFHdPCD4g03Zoyc9Rbw/IUrXBo3wg+K3YBitVtf53fs3MS6zY87FrgbBA2mkcbz5jfcTqg67pHRfnTOqWR8K56/tDLRWXvD7LgXdps1r5PyrXY0W81GEuGNbsZKtfD8hai5+TonR4FY41rWudY741TnOio3TqA2+OxOoLca15tbccuMUWuevuJ4OvLi1Y8LYXbPX7nSrqCz73LF3j8MGysOmxZatdacM1ebQKw+z9Y4kV1FlmOZWRwrj9Yhnr/ALaksh/IJ3jGYYMBRbE2EbEn4lD2YaQRMtySNwGBLStAKFFVfYgowhOar9T/FV4IzdZsFV3ChabIj6XKulqAZGPgaHpnxCDVM1mEs7lHz4WLL4kJTUrBDtI6cG5WG6ZZFK5R89oIkY8GLPMk9AzZTrQbfdL9Ov5HkkPF+jjWXOOkt0A4VBTNGWdSwDcFsU3GiWuecnGRQbwUh2aQmsEWCajDDC/XPcSz4BhJJxZ/mqfL/j37yTJe/jdYK118ml9jZldF3fq/L58oQhpFGCIsgKOPYw9TbszRViaHYLThYPJDYxbZUnMW2T90PKVEno9JsFbfhKQi1pq48Gr5mstFkIayxXx9ECpiqK4bjktkWhBosYVBsnqXKIi94k1jCYCRh8VTzIk8EjxKunF9/V/8rphshF+oeT9dn2J//FDsLH+Wg+SAZMcyQmWKTHicdGwOidhhlfQmA08XPMxKPaulizih9Kk/Vn2XU2MdZ/wliJDnhPszL4kWG9SAX3RqhCFAri0Sny39LkjxN2eC58v+FRjEXnkCpgPPyBArNGXGEU/oJXgi/jh/UycTHUSg8b56YM0q9dQ7b6qfRnqZYPx4t2ib3YpkFYs4oQ6kDGEayG5gB1NtRzXlnjDgfPouUcRx7mIa7gCZccw8TQlJsvEIYVtHaR+tgxdo+en8QlDGN9Jq61Fb7IoXEdgorjdeVauHqOq43Ryo+QRC2Wa4dpdGeZjh7Dy13mlL9OJcq32Wh8jS15mkmw+cp+huXAtzMIOeNsp//QeFq88eryRNvpny0W+qC+IFpin391vevLbTqBWQ9evTo0aNHjx49evTo8SbRC8jeAJT2cd1Z/DBarY3bQ+zNfBghZJTlWlmFt+0h5EqvDhXWsMwCjpkml9xLJrEjKiA3Mt0VY8ssUG1NUaofj/rnrKxYXY3L7+vv9i2BjdPDq6WNG31mozW5JurvZLo6x5GMb10rd1zf82J1lqZjSIKOejshulJGQya78q7u/q7KRAWqSbM9RS65l7gzfkXmw/MX1jS4Xv09GEamK2la//ka3V0tMowktpleZQJy2TVTqWBVk+TwVSVtoWpjmYU1K3FBUO7uR9QA+/L35vlL6zKKwdpi6XW/3UaStdXvb7QmSSd3dXtQRcdw+TtLxDZ3e9nBxitA688HaUQ9a5recvcx2xpcc46FYbWbgVnPRllKIWPEnREMmVz3fax9/9WysZZZWON42Okft2a/u9K/6Leot84DayWsCWd0w9+0I2Pt9CTZiE5fvo1Yf57GnQGANU5/G75v1UrljTp0rb3mrm4GslGWLco0rjJrWDnmzj6s/l1Wr5p2zrNOdm8jNjon1nM5s3W5/0unIf1G++1YfZHzpfbXuWdu/J1pvfH3IWXiCrklRL9trXl6jcIgUDDThHN1g4stybfnLRKm4KSa4tklj6eXDaYa8Jj7PS42oRkKFlyLTw/+EmfqBlVfsDsdEDc0tSCSmdUDg7FYwN0DNgVLkbag4pskTUibiqQJVV/SZ4fckm6TNkN2p1skDMVYwsAQmnfZ7yBpap5of4aUMchpfZFd6RQHUwO0RROFphy4jIoCxXbI8+4khpDc5+zhrtQof2/wN9gaT7NP7MBXLZR2GXL2cazyWaSwuCP3aSblJJvy7wGiRuDLtaNRv6lVJgaGtDHNHC13mkx8M1r75JJ7yce3EXcGMISFq+u08HimeQkFfKX2x/xd9fdYlvMUZYl5MUWoNINxi5CQb7pPUxdNbs/0UbBt8o5ga1riKk3JVXhKk7IMPpr7+4yr7dxqbaHgRM6Vw3oAT9WZSCaRAj5V+FmqfhA9r+OcrP0dAP1mnKwq8MXyf8QSknLzPKYRjR1pMchC4+WosbH26UsfZFvifl5Q3yRhFrpOiS6tyNRD7UQiuGRcwNAmI+ykL32QnbkPE+Izr8+SS+6lygJb5CHGU3czqrfjCIMtHGBC3kXc7CNm95Ew+liov4iQdldpEPUdbJCKb+02hI8cZEtUvGnClZ6o3ethVQY5l9xLwuwjDOso5XWz06vHv770we7fs4mJSPkgrDX3s/WmLon4Fhr+UtSrTsZJxrcyW34cAMuIE4TNrnHTYv14tzdn3BllNPcAUlhsNw4zZK5VurwR2aw3qh/Y9XKtTMqrZWNuRhNlrYON+9dej2x8ddPp19HT7Hp6zL1VeKP3sxeQ3WTESnNgjcb1y/jBEv2xnVSYY9DeSya5+3Idkg4IwzpSWAxk7yYMaxRrxzCkQ7lxgpidxzQSXRlUR74WWacHVwxQ6yfnnYHX8xdWuT46Vw3iVjcc3ohrTURD5W1ol9+52GPO2JrHOgOhENZKPUikx48kZJcnWoaRIRXfimX1kYpPUGleIJ3YSblxgpY7jWNflietDwqiz18tq6tuOEHr2ozLxMrrGtRXTZRX1zx1Gv120uydmq3usa37TcKw2m2OGj0fnR+Xj1FuuE9i5b8r9nWdlKAjhVs9IK4fHKuNU9Rb5zb8vGZ7imL9xa6URchYN0Bej2EkVxz8Lu9v53g8f6Fr474RqyWaQVhb8/lSWJhGFABHn3P1wGOjATFy2yvRMcHvnKeev4RhZLoTxY4UWCn3qo5TkZQu2LBmsoNtDa65Fq51zWyEFFbXaXU9a3/HV69fE8K8QqK76skb2q9rsf68Wz8WSGFhmYWutf5G7+m87mr44eWawU6Q92qOi53va/1Ci20Nkk7spD99+4bb7kxe1xOG1StqHNf/DoaR5KnmRYQAQ0Cfo7EE3DcQMBJT3OFs5VCfQ9IU1D3FA85Bztd8LtRDjpUFowk4XgoouZoLTZN2KJhINbCk5htzNglTcaqiKNgB21OKUEe/Y0xqUqbGkZqsFTLdsin7JheaMV6qxphrhZQ8QX/M4IUi/M+jn+Y98dt5MDtB0gStNR/ObydpGhwqJNmds9mZNdklN3GC57nYarHUCjjZXuJR9zn6HJOcvZmB1K1Y2sGQcbYZd1GVRZq6xJjeSV9yZ3fCHwRlxMp4IBB4/hL5xA6S8a3IlevNCxvMVZ7E9SssNU9R8aapyBJ7zBFiBuxIvZf9mY8Tap959QpL7mmea11ishEFkgYWrnCpuIqkJaj54CsYjEXyzada58nZBhKwVrr6DCei769g2eww7sUNNf95+SuEGtJmtDA4I89xZ+qTXGo+z1ebn6Eii2zLvosFXYmaLDdOUUgfoKLniNn5SJKnR7hFvp1+NcQueS9Dchffq/wVwcpY3xIuJpKxeIycGuRF/2vkdZadxttIqzzb9BYkEtOIs03tjWqmcEnpBI+2P8ucOE9RzjFT/g4Js8BU6WEKyd3d+t3V0txq41TkcLpS52UaSVJWVGsdc0bXNDYvJLYDMODs4WLpEfblfhrHyhF3xlfqYAe74/pS9QgJZwgpHbygQTI2wlL1CLnkru7vbBiZtbXP7SnqrUmEMLHMLEpdHmfLjVMr9+FG187e9ebQWjEY30vdn+dA7mdpijppnV+zGPtmB09vBNca315t8n+zgoP143TU0PvVnW7XSr1f/fXfD25GkPp6eL2LBr2ArEePHj169OjRo0ePHj3eJHoB2U1GrhhuRGl4k6HMYdqqSoo+FCGGMKMCdBnH85e6BgvtVU42y7UXMYwkrl/B9ebIJvcAl6U+ndVgpdyuRKiTPVu9araRNEgp9xqyquYV8qXrXbFvuzMbroibK45vq40Goj5ZRjezELksXtmfIXKRS1FvnlslGavi+qWV98VxVzXGBnDd2e5K+Ppmva+WcVCrmkZfrZeSQEaSDSPRfXy1ZGNtb6UrHS2Vaq15XK8zZun8/XrS+JEjobvyOdEKVZS5U1eYGXQkohtlvlabQ8TsARxnpPt5q+VbkcnI5SyD5y+sceS7ltNR27ts5hGGjbWmJkJel4ztagTB5UbhhfSBlYMKu86BAomx4lRpGOnIxGJdE+f11Jqnr+oat3pfpbCI2X03JPFYf52s307n353venVmxzRzZJK7u7JPrQNq7Usbbm+NOcZNLka+4lpa9e9rFX53HENh42zyxu/JRZtYdwyr5dydXosdfH+RRmuSpdrlpvGrZcnmiuz2ehArrnXd7co42+UIORvO1KLz/2QlynY1QsFkq0ZMatxQ42uNJWFzysILNaGO3BFvyVvszWq2JnzuyDep+jaW1Cy7IaEW3NEnUURySFcJphpgSU07FJxrGPzZOcmllsSWkWHIRNIjYxtUfUhbItqWAlMKbCkouZqJdNQ8Wgqo+XCpETJVV0yHJbbrWxmNxTiijjHNSe617sCSgnc5dzMi9+ALl1A1OFr/HFnVz23cQb/IkJEj9GcuZyE7v2Fn7Co2XqHRmqTYeAWg24PODyrk4xMMOntI6TR/W/8ryq5mVI1iaZu8HmKh8jT7rfcRU3GEEBgYXKw9wTY5hCkFvoKFls/mhOJSMzqu4+W/ZNkNUUDasMk7Bg8XZ3ix3EAIKMo5vtb+BnfKd1J2Qx7zn+Cl9hyurtMvMrzN+Rg7Y+/gROkzDIWbsLTFtvwHuSP3aWJGngGxjaTVzxi3UJFLBIRckCepyxqXwmNszj7A5tjdDKhBjjY+z85khrIXIJHUmqeZk/O87H+LUAS8yLO0wjLV1jRlWWGudYyp0sM81voLxhJ3MKZ2UgkuYZmFbgPl5fpLlJunCZVLf3JP12TKMgsMZg+jtWIkdx+ev4Qt4lHvSjPLeOru7m9UaV/EMDJUwhkSsc34wsWUzoo5j0HbnUGry2qHULkrRlwWjfb0mmu/4za8PlvS6X/p+Qu0V/oCwuVrWMo46cROwrAa9bxL7UOhSJgFLoXH2KRHgGvPV655zb7JmZI3g5t1zK/WH/V6eD2uia+HzrnyeiSU8Nq/y/XzsRulF5DdZFLOMMn4VoaSBzCNGM2giKfqTLsvUPTPrwxWLbR2scxC9+Tvs7cznL2HVHyiaxnuB5UNU6B+UEQg6EsfpLFSB9MZEEPVJp/at+aEWu/o1zlZO7VsnfqbjSRca5s9Jta8f6OAYz3BSpDTaRQcvW8QpdwVV0SbICivmYx1JmBaq8jOviPzWwlEO40oIZLYXd4/E9se6k54O/ve2U+tgw3rQ6SwIqv4FSni1dA66LrhrW2gvfFl1JHMbfz4ZXfI1RO+V3MbWl2PtpFsTKMjG3Ujtea5zud2GxWvvH798YbKW+OE2HZnu8dnmjnCoHLN/YuO58r6rfWsloXdLCmKlA6VZlTj0wlolWrhB8VukOAHxe6iSYerBQLXZf9O2HUMXP9dCmF2XeeuJpHsSCm7n7cyPqze/uoALgjKtL3lNXWR6/d/o0Dyeic168+pznl6xTmuw+7+d/Y1VJEr6LUcOzuOjFHz6bW/e2fb6xcTwrCOYSSxrIF1j0fHfbmtglpTx7S+5mx1IH4jCwBX1qkukbNNvrPQ5MPjMebbcEcfJE2NLTUfHcsyEg/JO7AjY+IpzV9XHsNVl/fllUrAoiv44kWDqaZDyvJJmSH3DhrMtk3G4j7TLYtztYCCHVBwBDNtc8UuP2Qis2Ixbihsqan6JoMxwUJLkbc1tSDgyfIyx2olAq3ZnJIUbMVUPWQwLllqBSx6Ls0g5HB6kIZoYUvBR7OHSMp+AqUZikPWlkgt2Sd2sC/7CcbTh9lpDfBk8HVqqs2CdwI3iMb4ztjaufalsLqLXEo1sa3B7iJSMjZOQuYpBxcJCHlf/BMUHMGudJJLvMwF9QI7Cx9l0biEL3wm5TlG7ASHkz/HctDkzxZ+Gy/UbE5ZPL0EIyv7en/mHzLllUlbkpxt0vA1hxIjHO5Pcd4tc4+1n0rrAgcLCZKW5AH7XiwsduqDHNFPsS+T4nT7UYayb6PfSKJQbFO7SegE77bfziFnE8NiFxJJUueoyQrNcJk+1cch+S52qH0MqxHmjBlsM0XDVxQck0GRZVv+gyypc+TszRjaZIjt7JL3ciD5YXyioGgkdx+DyX3cwi5c4bJcP0Y+uXNlLJEIYWHIJI6ZxldN+mI7EQiG04coNU7j+hUWakexrUFm6i/g2MPUVsZayyxQSB+g7V4iZhcoN8/SdmeZajxFuXFipR7tckDdqc3tjNXVRtRmReuAausicLkeuBOkrZ+v5JJ7cezB7vND2buj1+iAWvN0dG5on1L9OFOlh6m6l0gYfTzu/y0t0Vxzn7wRflBqkm4mb6VjfrObSL9eCeWb9V32ArIePXr06NGjR48ePXr0eJPoBWQ3mcrKqo+vm7TcGZTyqbYukrZHqLtzNL3FbtFkEJa77wvxKbcv0B+LzASS8a0YMo7WIeXGCfrSB9e406USO1iuHb0ikg/DKg13Hmmku6tLLXe6u5JtW1HBbtwZJwwb2NYgflAkHRu7omfVaoS4bD4hiDI6692VVtNZKbvcQynorjR7/gKmmYsyOhusZEhhrsnqdbbbKQKOPj8VFTGvyi7YZhrXm1sjgUzENq/JSAVh8woThsiZLTqW61kZWS1XjI7tymPobCMMqxvLBJV3efs3kCEKwxqGvLxquDqb0FmV8vylrkS0kz3oHL9hJNe61q073tXfcfc1q4/vOowipExccW6s/s7jznjXWet6uNZ5uWZflbthP7T1rD/GG2W1HGPtd7NW2hY5ZAZRru4qmc9rnW9XdylcwrGyGz4H15fZux6iLNZVeqB1+rShu0Y6HZlSJ2OyEZ1M5fp9lDLePZeDoNzNWhsrLrQdt7iNvpP1GcTV3+nq867Tc+1mEDMEh/IJlj2BIaDoCb487XKqEp2ny56B0nCuGjDZqnGveQ/lwCVjRZfQu4dFZOaRMUgYCi+UTDcdBuyAuh81ee63Q24rGGzP1NiZCrg128ISmloguavgcyjn0QgNDvdXeLEs2ZP2ydqSUMNw3OKT4318YjzP/3Hx91lua87VDQZikpoPZ9Uck/IcA3GTUMMgOfpigj4HfrZvLynLIGeDKeDHB0ZJWwZ9qo97zDvYkjYIlUvBSHDIeD/jziFGcvd1pfThytgWj42h0ZhmDtPIEKr2mntYXGcQSBbEJGf0JWabUdb1bnk/d8v3cJvYw+3yFrZbA+TVIL7SLBlzCCT7sp8g60hOVFpsTkmqvuAbtdMUjAQ2Jo+1T3Kx1STUmsfaJ7Gl5nCujxe8ST6c/kUagaY/JnnFW+RgaoCcEWe7vg0hYDh+gCG5i2LYRAvFglwgIOSiG53Xw7qPs+HTzKqTvFL/GrvFvcwa05SokjQscqbDVrWV7bG3s+S7zLU8JrnEreIAc5UnKbmThCLg+fIfs8nKsiymKaoLbLLv5FbuYb8+xEJY42zwBA+kfxUvqNKXvhWtFQOpfexNPUSpfpxQuyy3TxNzxqj7c6TjYxjSBgxC1SAdG6XtzhC3h5DCIAjL5MwtK9kviecvsSf3MVruNP2Z29mae/+ac1yuk/UKYRKPbcI0c5GBS0eGuKo0QKlI+dO5lkv144Rhm3hsLFIErcwDOtLl9eqdZnuKVljidvMhMir7qvK5q8nKe/R4s7geM66r0QvIbjoKz68yV34Cxx6k6V4iG9+Kp+rk49soJHbiWH1IGV/TiLatqvgrcrD+zO2EykNpl1R8G8PZe0iYfWsmko32FLY12K0Zs8xC90Tw/CVidoGYfVni05mkdKQ6kUPhcPffblBbkfzk6UsfvGKyrLXqSlGU9q86Qe7Y3CrldqVaGxEEZVjX9LiD5y/h+stdfbxhZK5w/usGh6se6zgjRhPz6PmO3KLTRNYPil1nwmtxNalEFJh2nA2jY9toktc5rigAXisfFIiNHeiuw6GnI5vs8GqNGjvb6QR9G93gVtv9X4sgKF9V0raaMKxe8Xiwarstd7rrrHU9dBpgvxqrm5V3UKr5mgbIawWA8irf081ubnkt2UenjnJ1S4Zr8VoCEb0+GL8KqyWuhpFcI0e9WmPv9d+vUq21jbxXFknWB243KoVZP75cq85xNd3WJFfZf09pCjb02Zp2CGkLbi3E8DVU/OjGmrXgHcOS/ZksGdtgezKJIQTn6/BcUVJwNDlbM9m0OFNPMBzziBmKb823MIQmbYYcK4Y0/CgITVk+C67JeNxn0TVJmgFbkg1sI2RvVjES99ichCUXFtsBC+1oW786+g8ZioMbahqBptgOiKk4g+EYw3HI2LArGyNjgS3BV4L9ecGZKkykNRcbmtsKkvv7M4wkDJbbmp/MfIyj+kVGnQQVPUdKDgKd6y8KrJQKiDvjlx0zVQuBZCL/IfqdndjaZtw4QNmb4lJwlEWvzeONKR7zv8yTwZeJGZJS4OErxTn1LOXApalLDFpxBlQ/x6s1+mybyZpitql4f2YnedvirHiRlq6QNRxGEpIfz+7lqwvLDMZgp9jEtozJWAJsKUjqOK/U6uzO2pRkkaV2iKUdFvQZsjKOK1zaos4leZqkcJhs1TkuvseoeYDd3M3B5Md4rvXXGNqkKWrMqwqh1hxR3+agM05CmvQ5FrcYmzGEYCL/IVL2IH0qz0cL/4yUZRAnixQWSZ1EAnnbZruT5xbjXUzKE9xlfZCl6hFMM0fdW6AtGiRim6NaZmERKo9S/ThtP5o/xOwC2cQEaXOI3YWPYxlxlr0zjGUfoOSf55b8JzGlw925X2E+OMlE/kOUm+eoBBfJJHcjhKQvfZBcYgI/KNKXPohp5rrjW7R4a2KY2ZVgbO0YsVoi3pc+iGPlaLanyCa20l553DQSGEZyTW15Z7HFkSnOyeOc5tlXvU6vd/Hph7mm7PXWS/W4ubyeeUDvl+zRo0ePHj169OjRo0ePN4leQPYG4AfFSKohYwxnDtPwFogbeeYqT6JQNNtTKNUiGd+6JmPhWH2k6GepegSlPIyVdPxC7QhztRe66flMcjep+FY8f6Gb4YpWftcWxTdak92s1mqpSBg26EsfxPXmyCR3R26F/jKmmcMPipEUcoOV8dUyNMcZ2TDzoFSr2+z2WlItyyy86upWozXZ7XsVfdZa1zgp42v6CV1N+mcYmTVZseuRCK6WBV6NzrGtlp6uRgprw75a19s8eMNtrnvv9WTVotXBK3/Pzspa1xDmOt2VVmdbrvYeta4v1OrfWkpnVVbuSknh1Xg156aOu1dn5TjqFxZseA5uJHW5VmPz1bxaVnIjbvYKbedaXJ2d6rBR1vJ6M0PrudG+KuvPh6uZZ6w247kWQlivSwKy4Wdu8FusN7jpnEdX2/8zjTo5WxMzNElT0GeH7Eor9mRYaeYMOUuRNBRuqBlNSJ5qXaARaKbrAXuz4IbRDXh/JnK0m2w6XGzZzIlFjpRMljyTKa9K2bXZmmyybbDE9pTLTMsiZmi+u5RguplguRUj1IILjRijsYCUGbk6nqkGKA1aw1OLLnkHTtarnA0WOJzrIy8TJE3I2zC80sfr2aUQU8JiW3BnX4gENiUFpyrR9ZCxBXVfMZKQbFG7eN4/zSi7OV38PABxZ4R0bDOGkcQ0ovsKRP0SlfZJOcMstF/G101mOImlbW43H+LB2IfZlkwwoPr4QPzDvNP+MFU/YEEs8Yq6yG5xLxnTpubN0A4VCWmxI5nijLfMeFKy0PY4X/NYcj1cVWeq9DBfLP8HjpVa1Hy4PdPH1kTAaNLib8ovMNWAkqfZ5KTZmUqy1Nbc4Wyl7odRFk8fwhCCmiiyNdxOH+Ocled5vPFnUe9JbZMWMRI6cjLcpMdJ6Sz9IsOT4bfZI+7hYqtJ2jT5lvsMrlIc06fQKPrFBJfkNMWwyTfaT7NXTiCRTHOSRxr/mTPeMq94S8zIc2QZJtSK3YWPY8gYteZpZt1jCCGxZYpa8/SqOUA9asLtjFGsHaMeLhLiEzf7kMKi7E4xbO0jFAFSmpTkAlKYzLVeJBPfRLF2DKWirHipfpzl2lEARsx93XtTsz1Fw51HIDZUTHSwrX5sq5+8tSXqTWjkWKoeWTlHxgnCNokVqXNX+iht8ql9TJe/zaDeSlL2Xdf1fD28lQwvbjZvlR5gPV4/vYDsDUIIk3rrHBJJ251huRXVli1UngaiiU7bK5KKTyAQLNdPMBF/O8NqaMVGWOIHZRqtSfSKo1kyNr5iY5vbsLFsRwIZrLxPCovEimzRX+WOZ5mFrnTA9Sto7aNU6wpnvqthW4N43mLXdfHq34FccVe8cvLrB0VMM3fVCXmniW9ktX7lhKzjoKdUCykdHHt4jYPi6gDUMlM4Kw5t1zt4Xd2FbWPb+A2P4QbkVa826Vz/HQrESg3eq29jfTDbffw1DORSWF2Xz/X7s36bsPGEPrJQdlbkLq++/51A7Hq/z47DnrHOTXHtPlwOEDvf/bUaUr9ZdBZXbsRtTNwky+HVdZ+vvs0bu5Vcj9So48Z6LQnI1SSF12KjRY319ZSdpu9XY8ROUAsERU9S9TSzLYNFVxLoqFn0poTidN1g3jU4WICCrXl/ditL7ZA7+01eKkVSwJSpeOjp3yZrhfgKTlXgPZnN9Dkw2zIYs9KkrICEGWDHA/K2z3DMpx0KtiQU//Wc5EIzxqa4R8EO8LWgFcKL5TrjSYNAQX8MYtKgHQosTHZYQxgCDBFZx081oOhBqGEobpCxNElTkzAUZ+uChXZkn/8XxSO8sOzyLe9bfK/YJiEsyvoSeTJd+XujNUm1eYYwbNB057vtBZRySca3slR9nkZ7irjMM1t+nJfaX8En4Lxf5OHWs4zHE7zoX+A5/SxzukxKpdlnbiEUARnLJG2P8uXaH5CzLKpeSE2UeGqpzljCJmOZTHIJpQPuy/4ab0//CpYwOFJfYFsKUqbCEHCncYCZhs+xWokLbpWkKVAa2qHG1SEOcSqyhETg6SYnxRFKzHCq+Ncr7RUMlFBUdAuJIGH3odC0RJMFXaHuzjJrTDFlnONz5T8mLrI86v53ZlvfwxAWp+pfoUGJRyv/J3fLO9mRsdii9zPMTkZTdzDNCZqiTowUE2KEZVnE1vFuDV7KGiJm5ii3J7vno2MPk0tMkE7sJC7yxJxRtso7WHBPYgiLdlCmENvOoBrmTOUr2DLFdONZKq1Jmu0pirVjSOkQqDYxZ3SlNY28XKawcp+FFZdjaWOaOTxvvrtAZxjJ7n3K95fx/CXmWsfIJHevuNs6KBV9bio2hLdSa9q57sKwQagDHHuYM/53OV/68g1f2z16/CDTC8h69OjRo0ePHj169OjR402iF5C9QeSSu0kndrLUihpirl9B7qw811vn0Gg2Z+6nygJ10SRjjOL5C91VWq0DDCOGHzYwjEw39b8RYdjoNotW2qfpLa9sb+2KtOuXsa3+lZ5eBoaRxAuqkYHGSsbgalkbpT2U9lccBNe+ZnUmR2u1ssq+dtuWWehKHq6VlbjcT+zaRZIxewjXm1tjJrDaAKXtzqwpHt4IKawr+h9txKs1FH6jWJ/R6brc3UCWq5NNkNLp/gbXYiOJoCaMMlvrsgxXlYRcZf8iKaG6rkzJjRo5dH6jljt9XZmbm23GcbWM7muhI4+8XjmpQKBuQmPPG+X1ymZWZwA7K+7X0yvs9TQU7/Ba+uAV/chJ0BTg68g58SuzNdohLLQFCUOxJx0w1QBHal4saf7d5L/k1ryBAu4b0GxKCk5UJX968F/wvbJN0tTcmtfUfM2R5RAh4O1DBhnbIxtv47VMBhJNMlbIgiupBYKhhEnZN2gryZmGTcpUtEMYsuMkTcHnql+hEYAlBXlb846hJF6oGInDXf02L5UUoY5klu1QEGr48qUGGvjGnMngirI0bcHHc4doq5D93IMlJMNxh636NoqU2Z58JwOZO6Pvc+V6tc0MCbsPKR1yyb2RasNIR/0gdYZ8ah9jiTtYMC5x3HuERrhMoDRbGeNe8zAjMseYleaMP89L7teJmYLF5gkeSP4ihgRfaQ5ZOxh0YphSUPUD7k9OYMk4j1d+j+e8/84F5pAICrbCVYLBGCz5bZbCBlucDLuTWZoh1P2QmCGoUKdP5UmrLHNhlbn698iIYTapXdyd+xV+su+fcZe8i3l9loyIURFVbpXvYUkUkUieKf8B74z9NHv0bs4Uv8im1GGyqo9x+3a2x97OmeIXGU3dwXzjGMn4VvpiBq0Axqw0SR2n6E1SXblXjagxlsIGbdEgxCcM68StPMvNV3CD6pp7mh+UWKw+x3BsP/Ptl9iUPIxEEoQt2mGFZnuaJHleEc8TswdoB2Va7jSev8R47p3kkntRyqXtzqDUinlHYifbU+/GFU1sq79r1AXReBQEZcQqY664PYTWK41xV5qw+2ET20hiGEmUcqm3znUzcp6/hJRO974khEm1cQrXmyNuFbqP9ejxo0IvILvJGEZk5+qHLWrN07TdGQwjiR80cexhDCPTHYBsM5rQCwQBLneIOwgIOV/+atfZqDPpb7sztN0ZpDCvOUE1jAz11rnuvzsTFsceppA+QNwZR2kXpVrdYKxjFx6G1ZUgq9No9fJEtTM5T8Q2r6mhWT+ZvZ4Jth8U11iEv5oDnJTxazYabranSMa3rhm8r9YM+2pEzpFXvqbTNHvD94RXt/deTTqx81VfcyNBQddi+CrnwdXkbY6V7Tbk7dQ5XosNP19fKX+8Vm3X1fZx/ST41erDXiudfb3eGq4bld5t9Lk3SzIYfdaN7U9HrnkjvNbmq6+VSNrkrHNNvRxE6g3qHd9obqRWLpfcy3DMwRJRndijjVNsigfckU8TaMH5WoCrBJbU3JpTnKhI6n7Ir4z9P0lZmqoPM23JuZrmRLnNZMPg3r4WO1JNBh2f2wrwoTHosxW35+v4SjI0USeW8jlezKE0jMdDBpyQ4Th8cbrOTMskJjWPzFn4CrKOQTvUPBh7kFYAZd8jUOCGgqGExYU6HC+F7MhI6p5isQ0FRzMQExzuT/HFhTm2pKLasYqreLg4w1Jbc3shwbATp6kCll2fAZnGwuIWuY26u7adhBdUKTdOoJRLuXECiNz1ABb1ebZad7Mp3Mrtxl6GY/vJmZswpaCuPNKW5FH3v9MMQ060H2YgtoeSG/JTuV9kyI5T9UIWwjpaR8FmzhYcyDvYEvZwmJ8e+Bf8dO7nOOiMc3dmgCHHx5GaczVNRVQ5rr7NY/7TvNCc5VvNExSDNs+4p1mSs1RFg1CEJImxI/VuqnqOvEygUEgEZ9UsrWCZuGGyICb5duX/YKcxzJgeZFP+PWg03+N57sn+A/axh7h2aIs6Wxhmb/4TuLrOSPI2bCNJw4/G4HaoWJbLDDp7uMV5Hyeqf8uL+lFeCr/JhcYTzAXH0TogZ2/G8xcQwqA/fTvD2XvIJHdjmXkA6mqBmJnD1XVqokTSHiRu5DmY+3lOlD4LRLXZ3sr1ZpkFQnyqrXP0Z26PyhH8BfKpfZjSZkyNk1eDhKpFLrn3Civ81WONZcSJ2aPRvRiBEEbk3LxS522aOQYyd65yT05FFvhGbKVpeDQn6EsfBGAkd99NXyzr0eOtTC8g69GjR48ePXr06NGjR483iV5AdpMJw8g8o94615XvhWED04h1myt3HP/a7iWEMBHCpBEscEmVWBaX0Dqg2prqSvo6K9iR69dlp0PDSEb9SFa51ikVudutlg4aRhLXm6PSPEfLnY5Wo1cyB6sbFHdQqnWFVOCyfPC1r16vXhFfvfL1an3BOtm89VkygcAwkqQTO1fMTy5/5nqJ4vXs90ZOdMFK1nAjrleG1nGdfK3cqGxjw15jCGrN06+7abBlXel8daMZmY24GZ9xLa73t1qd3bouueOqz+1ky672HZtm7sYzXt8HB63rlUPeLDpmIVc7ttfiYvl6uR5zmQ6+aqE0xIwol/ePx3dR9A32ZhSLbU3Z82mFEl8JTAH7c4p7B012ZwXLriBuQM7S3NkHfY7NpoTiTMNhrh2j6Jk8u6RphpJBJ+BcPcG5WpJnXhijshwnYShO1WJMNQ0qvsGyC3cWUlR8wYIrSVqw1A7Zl9XsTCsytsTXYAmDS01YcjVPN6a51PQZTRqcr2m2pA1agWa2CZcainaoeUdumIU2lNyAR7xvk9AJvlD/Iq1QM5ExGLAdtIaqcjkdPkU5cGl7c+RT+0jENpOIbUZr/4rsa0dKPl97HoA5OUvckBwQuzkk91D3QzSKp1rnud/+MNtSDu+M/TTnS1+m7Ht8ufl32IagFnrMyHPYhqDPkUw3Qi42QuaaAUtykWWvzVLbJ2YIJlIw27ZY8kxSlmC3PcSoeSv9bMYTHk1dwhASEwdPN5EIdjv9DDoxztS/SZ/Ywilxlqao8Zw6Qo1l9hvvphp4FBhnW/6DvBxOUaSGr5qclqfpZzNLxiyzqsxFeY6p2uM8ET6MgcVS/QRb1V5+LPERkpZAAUc5wkulP6cSXKIil+lL7SVULqX6cUYTt3dNN7aqvRzM/Q+4fommv0SxebZrjpGKTzBfeYbl2lGmSg9zyfsedXcOXzeZ069QSB/AXxmb2t4iEN1bZsuP41gDtP0yQRD1N8xb2yjXTzIn52mJJo7VR7lx4polBqX6cRwzjUAiZGyl12rAcuMUhoyjwgahdgnCyFU0CMr0Z24nYfevMRBarh0lUC7+irFXjx4/KvQCsjeArrzPGSG2Yu3abE/RdmfoSx/sToA6tvCJ2Cb2yncQEgUUm/Lv6Q6McHnC1Jm0rg70Igv9y05k3f+raNDLJfd23x+GjTXNnTv7sBHrpVgdCaDrzUfP38RmhNdbwxGskwhGOnWLAWc3ADFndEP5o231v2ZZ1uuRTHQaFb/eYEPr4HXdmKSwXlMN00ZSzdULAt8PVp+HUsZfVVr2Ws/LzvtWn4taq+sKhjv7eK3vWErnmjbRG3E9NY1vNK+lofSrcT2/4/eD1b/t+t9l9Xm0/ndotS9xwl2g4guaoeCVqsAS4KlIOnf3QJwXivCdBUnSDCn7knYYuRg+sdhivgVbEh4TSZeBmKQdRoFaKxRMNQ2OutOcqAoKjsf9owu8c8c0W7IVlmsJdveV6LPDyBVQCabrAY+UZvCUIGNp2kF0U7clJAyNEDCegFsLDmOJ6O8f7tvE/rzNxXqAFJHd/VdbT2JKqPqKhZbiTNXjM5VvckpP8k7rHeRlgrdbH8QQMNtUfK39NS7pJc6IoxyS7+ab1d9lV/4j5K1tJOx+crGt5JO71wT7nTE45oyilUebBrfIbbzUnifUmkBrloIWrvDYyhj9js0rtRaDMYf9+U8xI+Z5KP5j+EqzN5PkweQd2FKw7CoavkJpmApKzIUnKIkKC7pCw9fYUlOwAxZdyeYkzLkt6ixxqvUIGZWlGSxjIamzzC51gEGRpeIFHPMvsjl9D6Y26Q+HqbFInx5nUI+zxcnQoE1IQFtXaFKhQJrd3EVS53C0w7J/hiVxiSG1mYfSnyZnbqKoLyKEybRxnpQtcQzBN+unmFD7AMiaYywH51ioPN11HPRpIYRkc/adLMnFlW8zasjccZLNxMbpj+1ESJuYMxrdC2Wc8eRd+KqFJRJ4QYMgbK3I+y2SK61zAAxpE7cK3fudTwsh4yzrSab9I7S9+WvKvuVKe4py40TkoukMkXJG8IMiflCMmrxrH1MmcL05bKufRGwzGWOUlDGAY+VIxSfIp6LvoebOsFQ98kNtV9+jx3re1IDsO9/5Dh/+8IcZHR1FCMEXvvCFNc//wi/8AkKINX8+8IEPrHlNsVjkU5/6FJlMhlwux6c//Wnq9fqa17z44ou8/e1vJxaLsWnTJv7tv/23V+zL5z73Ofbs2UMsFuPAgQN8+cs9y9UePXr06NGjR48ePXq8sbypAVmj0eC2227j93//96/6mg984APMzs52//zlX/7lmuc/9alPcfz4cR5++GG+9KUv8Z3vfIdf/uVf7j5frVZ5//vfz5YtW3j++ef57d/+bX7rt36LP/zDP+y+5oknnuBnfuZn+PSnP80LL7zARz7yET7ykY/w0ksvvYajkijtR6590sHzFrurzPnUPpre0hWr7vXWOYpyAVe0iZOh2D57xcqQbQ1GxfDCotPk91qrzJ33r88YdJyNXo31WZ22N0cyvvV1SRfXmx1cbcXtavu3USYtCMoUvbP0pQ+ScoaxzCt7qXn+0hWyrPX9i25mxq9Dp1HxzeD1ZNk65+P10vn+9euUN14Pr/a9r74Oor5z1/4+BcY1n7/qdq6SDbueDOn1rOJefz+vy/sQBOUNe/h9Pwmv07jmRgiC8hrHtjeLa/62ujN+mldIKE0zz77YIMOxqHFy3BRUA8GiKxhwNIttzY6MYL7lkzJDnl4MSVmaJ+Z97uxLYAg4UnZYdC3uG/B5oQh/sXwCrQWNQPOT/ZvJ2YJH5lO8vFSg1bSpth360k1qbYd+x2dHKsSRmi1pk3HZT8HWDDsBGVtwNDhDylT88bkW52tt0hbk7Ki3WMWH+krWyFWKZdfnbNXnlwfu5XTFZ0vKYDAu2Zy0+ZnsuxlQgzTDkJJq8qI+RtXTtALN26334oo2rqozLxdJxDZh6zjnSl9iqXqEmfJ3KDVOIWWcRGwzMWcUQ0ZmLoa0Mc0sSR0ZYI2KApXQJW0ZjDtJXgkf5zveFyk4goJlU/EC3pGaIKdyFD0PW0ryjmCq3mapHfCnc/8bx/RpQq2ZE+fpMyOX4ZiO8Wxwii9Nu5R9kwFHMduK5JvDehteUKUkl/hQ8scYjDn06TEKlkPKMhAChvUgW8Pt2NqhLVoM6QnSOs1L7texDcGgkSamE7SDMhrFRTHHnDHDTHicfpEhYfQx13oRiaQWehhYeCpaLPZ0k78ofZaECe9N7cbFY2/+E2RVP1or0omdaK24O/5T9LOZocxh+nSkUpkOj5F0BhiM7yXpDBKGbTSKQLvszXyEmJlld+J9LNeOcrr4eSrNSZrhMptjd9PySzRak9hmBte/fF5LaRFqd0V1IpkuP0oyNkKlfZGUNRypcNaNc6szx1oH5JK7ScUn0Dqg0ZrsGrnA5fICieyOaUHYZqZ5hIvV72JKh5yzGS9sYJo52u4MttWP+X10Mu7R483mTQ3IHnroIf7Vv/pXfPSjH73qaxzHYXh4uPsnn893nztx4gRf/epX+aM/+iMOHz7M/fffz+/+7u/yV3/1V8zMzADw53/+53iex5/8yZ+wb98+PvnJT/KP/tE/4t//+3/f/Zzf+Z3f4QMf+AC/8Ru/wd69e/mX//Jfcvvtt/N7v/d7r+GookDFtgcihyntE4Y1BAI3qNFypzecCJT1JV6u/DV1ljesOfL8BWwzj9J+NJkR8romeaX68SukZ6/FSrYzyL4e1u/vFQ1aOw2AbzCIqTROUm6eY6l6ZI31/bVYb5f9Wify18ubPbG+kYCu8/2vfs8b6YJ4Mz9bE0bymc5/NxBovxUcvdbvQ0d6/GbxRtb2CRm7qZ93M9tQXG4rceU54fkLGCLyZD1bj8JKAYzFFc0QSm7U5PneQZsF12J31sRTglvyNlVPc99AwO50QCWQVPxo3Pnx7F5m2pJ/f+Ff85ml07xU9KkH8HMv/x3/9ZUxztVSLNcSnKqkeboYZ7olKXqCtCV4aMyizw5pK4nS8EsjkYT7odEUppBoDWlT01aCF0stvlB9gZfLIWMJG0dK8k60D8WwScaC/7T8BfKOwJDwiniex4OHSYsYtXCOlxpF2qHiS9U/YrsYZ9jYy7HSf2Esfjt1ltd8T0q10NrvyvW1DhjOHCYI2zhWHktbHFdnaemAhLBYdqNzbdS8lTvND1J0NSMJgwMFGy/UvK2QI2tZTLeaTDcUMSPa7/35T9EfDtMIQi5Wn+RM5eucaD/MKfEsIT6WlHxpOsRXgqdKJUrUMLTJhzP/E/fGd5C1JdOtJqOiQDtUpC2JRPBo47+QkBbbnTwznCSuY8zLGXbG3sFUs8kjrc9xNniCYWsfvm4ikShC9oh7uMQizXCZ0cQhnm1+lmP6MVIqS6lxCs9foOpN4wU1Xiq5TDU8LsnTKKFoiQa19gyuX2E0dhsGBq+0v0U7KBOIgBCfxepzxM0+8oyyXH0BPyjS9stMl79NUV+k5ZeY8p/jQP7nGcweJhUbQWtFm/qaliCrFxqqjVN4Qcd5MarpqjXP0mxPERPRdbV+nLbNzBq5dqgDmu6l7vOJ2GYgkqpqNGHYoNg8Syq+mUx8M0p79Md3YZlZyo0TzNWPdoPFaD9SKH1zFjR79PhB4C1fQ/btb3+bwcFBdu/eza/+6q+yvHx50H/yySfJ5XLceeed3cfe+973IqXk6aef7r7mgQcewLbt7msefPBBTp06RalU6r7mve9975rtPvjggzz55JNX3S/XdalWq2v+9OjRo0ePHj169OjRo8eN8JYOyD7wgQ/wZ3/2ZzzyyCP8m3/zb3j00Ud56KGHCMMQgLm5OQYH10rPTNOkUCgwNzfXfc3Q0NCa13T+/Wqv6Ty/Ef/6X/9rstls98+mTZu6zxlGpltsC9Eqs0Z3szcbreRqrdie+yBTpYevus3VzoFaq+uW/Ci1tqbu++2qdr285tV4YVzT/el6MoJvVCbgslnEGy//ux5eqzTzjcyW3czvXmsVmeWgkUbi++JS+Ebyw1zUfrOviWuNATebUGtcJdia1GRtTcFWnKpJTlWiXlWDjuJiE9qhJGFofAWbE4otKbCl4kQ1GpMutSSDccmZik/Jg3sz/xMPZXcyGDdZbmvus36MWzIe44kW3ytlmXdNtiZCpICMpWkE0X40Q0kjEKQtjSU0FV8SKhhJWHxn3mfZE3x9tsn2VJxBPU7J85hquBwomNhSsNiG/Zkszy/5/EzuI3ym+DJnKj51b4G75Lt5KvwqI8Y+tFCMJEzem/xFJIIdYixyVtRpLtWfAegaR0WuopHZg20Nkk/upNQ6hx+UGI7tB+Bi+zlS0qKiWzzS/AvipuCSf5RvVv4Dz7sXumYovoLpekjR91Bo/mT2X1ELffpjJtvFOE/V/xOTeo6EM8StmY/RbE9hiQTj4TaaKuC2gsVj85ptTpZbEwOYSE7riyy0fP629jwFyyFjmVRUC1/BXFjlPcm/R8oyqPoBfWIrrvBoU8fH4ynvCyTsAfYY72BEjbFLH0IiaahlFJoXq59FYBBqHylN4kaeyfB5Es4o6cRO3KDGvvhDLOgK33K/wITah9SSFlVuT/4koWpQDCZ5rP4nTMTejmnEcXSMU5W/pT9zOyPsZF6fxTTzDGYP0/LmiTmjzFa+i9YBXthgNjxOqFzq7Vny1hamat9dY8okEF3ZoWMPd/uXKu2RjG+NMprZezhd/PyG5lTN9tSa8SlULpaZ7/YZE0JiW/04q5x5LTNBqFyWqkdIx8aYLn+btjvTlQZbZqE7TwrC9oYu0D16/LDylm6D/slPfrL79wMHDnDrrbeyfft2vv3tb/Oe97znTdwz+Of//J/z67/+691/V6vVblAWhlUarbWTA8NIEoaNrvV9B4FYSff7hNpnf/5TTHtHaHrLa2R1UlggTJRqRYOjchHCvC675tWT0ug9r0+a1Wke+WYhhbU2QJCJV5mMvXmT8psVEHTOk9fLzdifN9qi/vXSOb+/3wsPN+s36vHWRkqHdqg5UzfI27DsRoFXM4BNSYOTZZ+2Mgg1pEyFIwWuEngK+m3FpZbFdEOz1BZsTsFiW5O1TdwQxqw0+7LRNfpCUfLuEYcBp8ay63DXQJGqaxNqyaVWikAJtiU1zVAwkfSYadnYEi61BKZYacGgNVtTFu1QEGpF1VPcluxnruUzHLc4UQ5pBQqF5qye5oC5hQt1l91sJ2ZKDlsfZpkaQ+ZeHB1jRpzlWDVGQlhUQhdHGLw//hN8rfn5lRYuEkPGMM0ctpnBD+pImSUdGyVjDBNLZDC4lVo4xxhbOGB/gCm1yLw4y0Opn6PihYxZB0nlh8mpHFVP4StBwhR8tvxfGY7fyrnyl4g5o4zF4pTckLRp8rbULyKVYNw5hKVt3p39v6GUZtxJ8tnSH/DQ6K9ye7+k6AqKrsYWFnc625ACbnUPAGAbgpwRJ9SamqywJGbJeAUqcolz5a+yPfdBAu1SYY5AtblDvJ1laiyLIlUWuVR/JnITzPqMpO+KJITiJYYyd1FyJ8k5m5HCpN+Y4JL3PU66j/CA83EeSnwMrTULoWS72sNZeZJNmfuZULdwJNagwhwpY4CimEOrNkvVI7iJGraRxA+KLFafjRailIfWCs9fwpAx6u4cbXcGxx7mTPGL3fNXiBWHRjNLEJS7bXE6BEGZMKhgW/24YZXh7D00gyJB2LpqSYCUTrekoSMybHtFwrCK0rnu2BgzcyzXjmJb/bT9Svf9nTE77gx0288Y0iY0kqg3oQ1Gjx5vBm/pDNl6JiYm6O/v58yZMwAMDw+zsLA2MAiCgGKxyPDwcPc18/Pza17T+fervabz/EY4jkMmk1nzp0ePHj169OjRo0ePHj1uhB+ogGx6eprl5WVGRkYAuOeeeyiXyzz//PPd13zzm99EKcXhw4e7r/nOd76D719e1X/44YfZvXt31yDknnvu4ZFHHlmzrYcffph77rnnpu17YqUfWaefl0CQik8gpI0UFg1vgU1qgoRO4Qa1KzJQSvuk4lGRrNZh97H1bCRjFEIiEFE/quvIjl2rON62+glvwGjgmr1LXqPRxfrjDsMq6cTOrpvlekndG23YcbPZqGfajWReOv3PbgZvthPeRrwV9wl+uOWF63kjXEl/UFDKpRWEbE5ocpZmXzYkbcKuDDiGZn/BwlMCL4zkhIbQWFKz6EoUsOxJ7uyD8STEpGZXRrMvLxiIwcE+k7QZ8vCMJu8ImgEYUnPXtlkG+2q8WE4z3YwRM6AeRL3ITlU0c22LSy3JhTr80dLfsdhWJMzIETFlCb6zWKUumgwlJG4IadPk8eZ5Sp7HlrRFn2OxXYzzbHics0yyrBr8XfNvmDTOcig5wC6xjYxOsU/fxpCdoKJbuPh8rfr71HyfcuNE1x2w5U4TtwdotqdW+lCVKDVOcab4RYrts4T4VN1L+ASYGNwWH+EB+14kglm/TpUFxvROtsYyxExB0hLYBtzh/AS3if387OC/4HDs4zSDEE8pxlOSETPNS+E3sYlTkguMOgkGrThCwEdzv8xoLGDYCfjWUpFmoNFa84x7BkvCtrRNLfC51GpTCV2OtxcY0yOcLn6ehE6w4J4km9jB6eLnSdHHmN7J22Kf4IQ4RlPU2cIwm9UO9qZ+DCkd4jLPKLvZlv8g+3M/w7jYz277nZg4xIwsJ0ufo9o4hSEdkoZFn2NQCjwWwld4vP1ZgpUcU0VUud38ABpFin6W3FcYy72DVHyCcecQcSPHjsJPMJC5i1xyL6xck4aRiX4DK08itrk7l+hISTvlDp3GzGDg2MMU0geIOaORGYcwEMKMzEPkJpru/DUNszpGY4aRjLKjVj9xu5/+zO1k4pswzCy55F5q7RnSiZ2Mpu7AMdNrPiMVn6DaOAXAeO6d2EbyprkU9+jxg8Cbelet1+scPXqUo0ePAnD+/HmOHj3K1NQU9Xqd3/iN3+Cpp55icnKSRx55hJ/4iZ9gx44dPPjggwDs3buXD3zgA/zSL/0SzzzzDI8//ji/9mu/xic/+UlGR6MA6Gd/9mexbZtPf/rTHD9+nM985jP8zu/8zhq54T/+x/+Yr371q/y7f/fvOHnyJL/1W7/Fc889x6/92q/d8DEJEU2EHXsYx44ybIaRodY8DdC1mtVo6q1zxJ0RhIwThG0UmvPqeVruNLY1uGbiGXNGu4PV5W2tVZxerQFwp66mE8h0LN8NI9P9jNUT+KvJ/wwjg21mbqhW41qT1E4NyfoA5FqB2tXqwQxhdqUO64POznFfbSL/Vptcvl6p3c20238rBhlvxX16vbzVzsFX4we9Nu/14uqojqsVCsq+gasgZ4WcKiuagcYLIWYIqr5ksmmQMBSbEpFV/WJbEzMUd+Rb3D9Q5n+/9CwVT6A0VH04VrH52W0B+7M+MQNOV5MsLKdYLqYo+wJLajKW4kJd0w4h7whmWpLRuOLOvpCPpT9IwZE8t+RzzJ/mpZLHff0ZDiUHqHqaZhASMwX3JbbR7zj0OfAns/+Kh5t/ycX60wgkJpJ7rA+TVf2EGjKWyYAdJ2fZtIKQqqxw1PsSt2R/kotiDinjK+6T0fhsrBqnlXK7Y1ohth1bJHD9Mg5WFIS12iRNSTFoc5rn8FSdF9tfZsF1SZiCzUnwQpAITupzbE4ZvHswy0W/wsPNP+dSQ3FazTBo7yWnsgyGY3y59d/5hvslxpISSwhCLVhwo316zj2Pi88euZXnGrOcr3kEaCblJD4BjnaYlJPsKPwEQ2YKL6hRqh8HYCk8x7yYoiIrbFK7EEgCrdgaTzOg+jCNNG8zD9JHGl832aSHsbSFox3Ol77MXO0F9uR/ivfl/gkjzgFsQ1DzFb4O0VoRt/Ok6KPiT3NBvcAl4yK+alJhjpiZoxkuE7Ny1FlGoagElyg3zxOsjPcT+Q8xmrmLzfn3cavxHrKxTVhmP7Y1yFjqbiCamwhpk07sJGUMYJkpXG8OP2zTdmdI2oNoHeB6cyRknjrLyKvcd1ffUztjQhCU8fwl6q1zVJqTBMojCMqUGyfw/AVqzdOkGaTcOIFlFhjO3sOh/C+y23kXAH3pgyy3ziCl+ZZoIN+jx/eLN3UW8Nxzz3Ho0CEOHToEwK//+q9z6NAhfvM3fxPDMHjxxRf58R//cXbt2sWnP/1p7rjjDh577DEc5/JF+ud//ufs2bOH97znPXzwgx/k/vvvX9NjLJvN8vWvf53z589zxx138E/+yT/hN3/zN9f0Krv33nv5i7/4C/7wD/+Q2267jb/+67/mC1/4Avv37//+fRk9evTo0aNHjx49evT4kUNorX/4lpvfBKrVKtlsFjBIxbeTsAdQ2mepegTLLGAaCdKxMRYqT6953+b8+0iS50LrKfygznj6bcw2j9J2Z7rmHQDpxE5qzdNYZoEgKK00cFxr0GGZhW6WaDXpxE5a3mK374gQ0cpTGDbWbAMiZ6z1jVBfL50i4ut9Xsr4Ggc2xx4mCJtrMnOdx6QwCcLqW6KH1HqkjKO1+yOfTejR44cJISSHs7/Mp8b6yViKuKFphQJTwFNLBlMNj21pm9lmyFDcYLLm8e4Rm+/OB9w1YHKqonlgUJOzA/bmyzw8M4CnBM8thYwkDC7UAv6H7SE7s1UUMF1LMd1yuCVbp+Ta1AODim8w25YkTShYiraKMhWDjs8/PXuc9ycPcabWYFc6ScqCVgAvVivURYMx0Y8tJfsLFgLN6Upk6vGZ5d9jf+ajbJcjlAOXg7kU040AQwi2pCPZ9/laSNqSXGq2yVg2hoBLbp3Hqv9fssldWEaKcvMsCXuAauscjjVAy52OelFpRcIZQemAtzkf44R4hr36bvakUzQDzWfLf8atsQ9y0n8UL2wwEX87m/Uo7xiO8VJJUfJ88raFYwj2ZAXn67DUDkmaknaomHNbpA2bLxb/DbsLH2ef2MEDQxa21JysCobjMNuEhXZIIwgYidtUvJCpoMT+RD/Pti4CMKYHWaBMRS6xn918N/gGNXcGU8ZourPcl/771GWdF6t/w+bM/WxTUd+3ZVlEItlpDBNozYVwkQI5HGHwdPhNhDCotS/Rcqd5KPdP6XccXvJmeKH0n7gn+w84EXyLmJnDlik0ijG9k0n9PW7hbUzK05T88yv9R6N7Xa19KTK+UC3yyd003AUOxz7OGXGUYXbSR5bnwm9E2T0h2Zp9H21dZbb8GEPZtzFXeZJC+gCj5q1c8o/ihQ0arcmuS6LnV7HMFABKB7Tdme41YBiRUqbzf4juySlnGEvGafhLXVVQ57nVxiHpxE6EkDTasxjSZix1N1vULi4ZF5h3XyZp9eOIFJOlr70BV3CPHt9PNBBSqVRe1WviLe2y+IOIlBmEMFDap+VHwVGkoy+usa3vUGyfZT5sYhkJDqV+iopY7g58nUDJMDI03ch0RKNACND6uoIQgcAx0zTaqy3zA8IwWLONDlcLxqR0kDL+moI1KVPXlDlqrdYEZevtsFcP5B38IOoh57+BVtev1zVv9XG8WlD6g87NcO/s0eMHAa0Vm808CkHaDGmHkpGYh68kGdukUfVJmQ5n/Hn25sYwhU3KVLxzxCBvhfjKoB7CDsfjmYU+PCWYbkDONrClYDBukrXafGO2nz3pNmnLZ5vUZByXlyspqr6k7AteLvncWjBJGoJaINia8NEIPpo9RKjhO83/yll5J9vVHsbjCeaMGX4qfwsAaUvTCsGRcKAgeamk+B+H/hEvNOfRGnKmw8lKm4Rhsill8DfllxgMx+iTSQZjBhPpOCeqdS4akyyrM2STu2i489hmCz8oUwmKaK2697xMfCuWkSJQTSaMt7EolkBHQQykCJTmDucn6JdJLlgFUtYQjo6RMEwuNaHqB1xkHtft5+6+JKcqCksKrBU3yUtunSErSaA1+/OfYi44wXETbnFvAQRbUxoJzDYDZoMa/UaS2ZbHy7yMJWPEjQE8WhhYtHWAhcWmcCuTcp7F6nNA1OjYMrMoNHmV4/3pX2ZRVxiLJTCEIOs5nNOzNMOQuvI44T7MUHw/k6WvoNFsy3+Q3bG7acab2NKg5Plsk0Ns7/vnPOo/TLlxgnRiJ3PNJ5nIf4inK3+EaWSQyXsIcCnVj68sRNZIOKOYRoJQtQnDBpXmJDvT7ydUIQuNl9iVOMQ54yzL5aNI6dCfPsiF6ncIwyrJ+FbmK08xnL2HQLucaz1G0h6kXH+ZbfkPEuCy1DyFY+VI2UP4qsVy7eiaa6BzP7fMy/d2y0igCYnJDHPNJ9cs9q6+h0eW+iFah6iwhm2OYYsER4KvELgtUs4Is+XHuzVvPXr8qPCDVbjQo0ePHj169OjRo0ePHj9E9AKym4xtpmm0p1iqHmFb7D52Fj5KJrmbVHyi+xopHYSQkcQwbOJ6c6SdEUpygVJ48YrPDMPqijwgiWWkruoaGITlNf82jAwaTcNdiPqXbdDQd3VRbselcCOUcl+zlPF6TEBWZ4+S8a049vA1zT2Uct9wB6abaR7xRmfH3mznwV52rMePEqYUNAI4XbcxJXxhOo6rBK1Ac2suScrU9JOn5msWWorplsEXLjY5VTO52NBMNQT/7WKKvdka7x4qckchpB1qkqZmWxraocF43KcVSkItmW3ZnK9kKPuSqQZM1RUHCiamgLIfXfuTTYv5tsmZqsdyW3F/4lMU9AgDdoxTrSJ3mLv46vIsE6mQx+ZdtiZCMpZGa9iVlVhScCgxxJRaZDBuIYXAkAJDwH52M25n6I9F95CnajOcl6dYdE+SNAeRwiKX2M5w/ABDmbsYyz6w4uAX4QY1FipPM2DtxhceF73nGBa7UCheqTUwJEzEM7RVQEoOskXvZ4gC58MFqp7miH6OGst42udU2WckIbm9oHj3CDQCxf5MlhPhNNXAY5+5hQ/EHuJt9m6agaYZaGypudiEYtBGImirkLYK8Gkxobbia1BC0aDEafkiAC1c8ipHX/ogm/LvwfWX2Zl8D+fEC2yKJ/hK+X9nWVxC66hRuCUFfarAkq6yJZ7kJzM/z3a1h3RyF6O5BxjQm2iJNiUxTyP0aauAWugTak25eY6YM0rTnScZ30olmAYUu9MPEaAwiermXW8OQybROkQKExU2EMIkn9xJWc9wUb5Cf/IWXhEvMBZu4VD+F9mX/QQLlae5I/0zxJzRyN1QGHiqzqCxi4Tdz2L1OTSakneei6VH8IIS9dY5Sq3zFOsvbXgN2NYgpox1/11vnaNYO8Zk6Wv0Z27v3p8Tsc1r3tdoTRIqj3rrHBpNy53mVPGv2WO9k1tiD9Lw5rkl/0mSztDNuVh79PgBoSdZvMmEykMpF9saZNo7ghvUCJVH0hno1mc51gCq42K0MlgVm2eZ9R7f0FWoI3cLwwatdQ58nYbTsPGkXwjZdW0MwhqsaajsdPfV8xe69Wdvtvys02ByowCyx8b8MDoP9ujxVqXkeWSsGONxn4pv8ONjbTwl2ZtVPL0kqPlwaz6OIWA8JTlfC7mrL0Uj0IwnBe1QkLE0X5nNcXvOJWmGTKQNhmIKS0A9MJhs2mxJ+Cy0bWKGYtG1OF+D/hj4KnIOjBmaUEHOVhwrS94xGLAUNviW+zA/nf0pnmkVyTsG857D3pyBLg1gCc3BQoz/eGGeT44Okrc1ZT9y+xuISYYokDRhf95hrqmZbSrO6Vn2MEZ/THCk2OC2xAhfb53FMpJcLEUtY0wzx0LwNLbVj+cvrXEObbanyKf2kVJZ0jrNBcDQJoucZ681zmjCINSap7xJ2rrKk7Wvsjn7APu5jR0ZQc69lzNVFyU0tiGQApZcSc7WpC3BfDPgcHwLDV9hSkHJ8ympJr7KsCVl8tySpuR5nJMvs0XtJmmYPBU+wbutt+NrzXTDpapnAcjIEWqywlbGMITAFkkC3WYi+376wwF8wyVmCN6Z/V+YZ4ZGEOKqkKxlURV1JJIT7SXGjTxzcp7bzPdzzP8Gz7We5X2Zf4ipDQIUljA4JV7E1A59yd3UvXny6W30iwnaok42N06DEkJKSv55IGqbYxpxas3TZJK7ycbupO7NE5MZdqkDXJRTxMnSps6UOENLl9BakU/toynqTCQewBcuffkdWNqhxiJe2GAkdx91b4Fy4wT9mdtZqh4BNi4X6OAHS9GcYgXHHsb3lxnN3hc1wk7uxZAO5VW1ZJ05kB/W10gaC+kDPFP+A3LJveyIvYOGKBP2Fvl6/IjRy5D16NGjR48ePXr06NGjx5tELyC7yYSqCURGHk1vkR2JdyGlSduv4Fg5LLNAy53G9eYopA+gdIBtDeJ6c5hmbkMZntYK08wBkQyx01z6VfclrAISISSev9A1mYgkkyZSxpHSIR0bXbe9K1emOpK4q/UBu9kk41s3bHwd7cObf9q+FfahR48ebw6PNP6MLQmPAcdlPO4SM0IUEGqBYwjyjiBUsNTWzDU1Q3HJ0WKT8zWfqg/zLcVwTHEw57LoWqTMkKGY4mxdkrZCAi25Jd3mYtPiWMXmT8/BmbpByhIkTThba7Pc1iQNzfaUz3DM545CyKJr8kBfAa0Vu7OCnxvezEgCNseTlD3YlzfwtWA4rviF8QFiUuNIzbILY0nJtpRmSsyQs8EQgncNK/pikoRKcsafZ6mtuSWbpBUoTOEwbhygL32QgcydbE7fv3KvWYoMkbTq3i/izjjj1u0MUSAuTAzpcEG9QEYMM5o0mW6EaEBqSYFxLDNLxZ8mY5m0QkE7hIOFGPvzMfocA1NofA31IJJUjiZNim7As+Fx3FCRty36ZJKxpMHJssfpVpli2GRQbyUtY6Qtg/vN+/hs6Q8o+i5jCZv9vI0JfYiYTjKoBllWdTwVkpKDWCJB0T/PgpwjpbLUfIUjTAbVMMWwSco0cZUip9PURYUsKY6qlzhe+gvG7TT7zPewJfsujvMcQzJLRjpMi4s0w2XOlb6EJRO0vCVCHVDSF7G0wyY1gSbExMQxInc2L6gyFLsFKSyqjVMs1l+k3jqHLRJMGmdZ8E4w5x+P5JG6RFzkSRvDJM0BQnwG1TASIzJoUQO4qo5tJAl1QLgy9wiVe83yBSnj0e+qNXrVPTrlRP3NmuEyCasf04izXDu6pq+mZaRWFD/R+9KJnQBUmhfYXfg4B8z3csF7hpJ/gYw18n2bb/To8VagN6u8yeSSO7Gt/sgdSdq0RZ2RxEHidp5GazJySSQKbJSKrGSDsLLmM2LO6BUTfqVaSBknDKu0V2QEQpjX1US4I2XsBFVKuZhGhiAoo5VHw1t49QNbcbO6USnjax1QtVbdxtrrWV9b9mZIG7VWWGbhiqbWPXr0+OHnrsQnWHQtqr7FC+UEF5oxip6JAE5VGwzEoOZrym5I0fXxFJR1k0Bp+my4JSfIWiGekgzFPM43HHJWyK3ZgAHHpR5IEmbAwVyD+/ubvGvY5pWKz/5swN2FOnf2x7ktrxiO+XxnweL5UoysFfKVSz6OES0Yzbag7An+13O/y+aUxBCwLRlysipZdgVPL2nm2pKnluVK82cwBPzC8ARlD/oczcWmQSvQ3J7pY5bTSAEvVxp8ofpnSCz6dYF+awfb5B1YIgZIRnL3EY9topA+QH/6IOnETgYSewnx+VrtD1igxJC5BzeskVf9nK95GEJQ9TTjehNFptFaUa6/jCUF31xaoh1oXBXJJxXwcjkkaULOUqQswWTNYyRh8a7YASqBjyUFM7pIO4DdOYv9qRxPN/8SX0TbWnZ9ngie5MfSf5/tqQRuGP2uEoGlbQA84XJKnCShM1wsP8Jt8l1kdI7bEyO84i1yScyyLJf5TvX3sKWkzzEZicWZYDMWknut2/jU4L/gFX8eB4s+PUaf2MIr+jxH9NOMqDEGjV0U0gc4oG/nbam/xyHxdrboqP/ps+4XmFC30BQ15ipPkohtxpAxGmoJIeMU0geI20PsKPwEOTXIpcbzOEaGrDXOorhI1b1EQY9wuvh5WmGZsr5EW7SphJdoixbLcpFBuYNae4bF6vO03VkMI0OleYZsYisDmTu7JRRSOt1F4aiVS0A8tmnNfMBXLTLxrQgMlA6IyQy2NbjmunH9ZSyznzBsYMhkN/jLxDcxWf8uBgYHzPcyYu5juvxt0OEbeBX36PHWoheQ9ejRo0ePHj169OjRo8ebRC8gu8kUa0fJxDcjhKTtzlD0z3O+9GWS5iDGSlbKtgZJxMZJWAPdLFBf+mDXxTDlDGOsSBQ6K1SRq2AkOdQ6WJGErM1WmWaum7HpSA60DrqNHqNm0tFP3jHw0Ohu37PVmaf1rn2v1SVQ66B7LBtxtQxasz111YLiK7KCq7KJjj3cXcl7o/GD4nVlKHv06PHDRV3WOF0zWHAtxuMBeSuk3w54bF6TNmyKrmDZDcjYBl+p/V+cqLTwhEt/zCJva4qu4FTNYmuqQSuUCOBIKcrM1HyLsi95rpTi2VI0nk814I5+k6GYR8IMkALihmaqaTOeBIFm0TXZnbU5VQ746exPETMEodb81sT/zOZEyM60wlUCT8HWZMiDI4qdqYCROGxKwICjuNiUxIzIedGWUcPrsqeIGXC7eBuGgEOFJJ/q+wUecA4SasV2tY0ZTlFTC5hGhlAHuH4ZN6iRMgbxghqLzRMU1QV2Zz5IScwTioBd1gNkRIyxhE3BEUw12kzJC8zVXkBKk735n0ZpGDEztELFhVrAUW+Kc7UW+/MGZ2sw15bYUtAfszhRrRM3BbvScaaaTfY6gyjgxWKbiw2Xh9Kf5s74GG0V8qj7eTbpW3iJUxytL9IKFRJBVVZxtMOsvMQOa4i3Wbeyxxzjk/3/jKzhkNBxqr5ihlPc6Wxjn7mFfzD+/6AZhnym8jmqfkBdeSxRpR0qlr1IBrgol5jWLzGsBzho7mCPvp1z8mX61AD19ixpy6IoF6jrNqEIOFn5PClnhJPieUL8yIGxPYWUJqPsYVfmA+ww7qXZvkhTlZjhFG1vjq3iNiZLX2Oz2sFB+0NcUC+wOf8+Rs0DzFWe5Jnqf6IdlDnrP0GLyP3Y9eawzBwT+Q8yljnMUOZOlqpHaPlFlHIxjCTJ2Obu/KQzF2i2p9bca6uNUzTcReJGDqV9FhovrTH9gEjpY5spbKufULUIwjZ+UKTSeIVNqcOclcd4WT2GQJJJ7n7jLuAePd6C9AKym8xw9j6CsIXnLxF3xokbOfbnP4WvmmjVwjRzmEaMRmuS2coT5OPbMI0sy7WjZJK7kTKO0n538FvdHLqDaeYQ0l6zXcssEATlbtBmGgkAMsndNFqTDGTuRAjzqpb50bYuNzK+ma59Kqxd1ZZ9IwnkjQZUq+vuXG/uNdnzXytovF56jSx79PjRYFlf6Er6YoaiGUoSZsi812Zb2qLqawbjFkpHCzcFy6ZAjkYQTWYtqSNHRal4tugQNzR7MgEawRembXamXHKWQgAPzyd4YNBjd9pjuumw1I4xHFMUPUnSVCRNjSHgUstgU0KzLx/JDJfaij1pxYCjmWwYDDgBJ6oSL4S0GZK3A2qBZG8mGoPn2hJLwr84/zlGE/DvLx1leyrkg2MQNwRfqf4+E+nIQdJXmoW2yyXjIg3tIoRBoF2G04cwhcOO7PsZjR+ipUoMJvchhGRE7mFADVLyz3O2+g1ebHweXyueqy9Q9TVp02JCbWVP+sfIxbYwwWb6YpI7+y12ZKKFuwveM/Q7DgkDhuPgKcFzxQZ9MUHBjNEKNLPNgJKooDWkLUhbFltTMXZlbZbaASVqHLY+zLCRoRbOIbTkgl9EoTlW+SvOixc5U/sG29IG590yX258DtuIGnbf05/m660vYgqHgiMo+x4xI5I6/nzhE8QMA4nA0TZDCZOJdBwDk016mAesd/Jo6y94MngeY2UR8bHK77I39WPMe00MLE7zLEtyluHMYQblDtywylTtSQrxHYzmHqDtzlAgR78aoiQXeDD7jxkS22n6i+zJ/SRTvMxDuX+KgYGDxRZ5iCR5LnjPkE/tI+GMkbZHGXD20NYV+lQf/ZnbySW2Y2mH2drzLDdOAZGNvRAmmfhWWt7ihtdBEJS7i7yRu+YCi82TjFgHVtya/TX3RdvqJ1BthlOHSMbGu+81zSxpXSAmMoybt3Gs9F/I2uM99+AeP1L0ArIePXr06NGjR48ePXr0eJPoBWQ3mbwYQwiJbfWzPfEOkrKfl0p/TtYYQxpJ4vYAMSuLYSTROmC5cQrPX0AISRC2UKpFsXYMoOumaBgZ1ErqP+aMrmTC1mbODCO2UkArySX3olakivaKhLHansa2+hErssTOZ682EFlfgHstbqgRsRA3tNKllNvdp2u5Pb3m/dmAV2tevd5IZCOXRT8o90w+evT4EeBdzn0su4KYAc1A0gwlrVDy3uFImbA5CSNx2JER/L93/7/IOgZ70gnGkwb/7WKbdhiNV3PNOPf3t1ecBCVxI+TWPDQCg0U3yljty4QkjJDTdRtLaiypmEi2aStB1lK0Q8FME27NuggBx0ohW9MGm5KCp5Yl3ysJ9md9moHkbX0+29KQtQJO1GLkrJCxeIvJBjQC2J4K+KWBTzASC/lY7hBVX5IyFV9dnuVn+v4Xyp7ACzUNX/Hl8m+zW2/nojzHxdIjLFSeJiHyuGEVV9c4V3kEd2VcHUvcgdQSAwOtFbelPsZw6hCGkNyZGuRSs81kUCRAs0OMkTaGydsWtoTvzrd5ZrlB1jb46exPMRiX1ALoszUFW/NjownKruaJ8HEytqAYtFkQk/xd8wsstzVxIxqrXyq1eEG/wHarj5g0WQjrLNSOMGJm2GYVOCtOcSjzc2hC7kx+khNlj8O5PtL2CCfaS7RDzemKz8/mf5I8o7gKLCGjbZiSwRg8GTxLvxVjezzLdMPDDTUt0cRH4SvNSOIgTVWmQp2yN8WB/M/zvdKfYiKZDY6zl8NkVT/j7OVE9W/JmKPsSL2b2coTxESGe7L/AF+HlGUZSzuUdeTqfLv5AYbUKDPl7+BrxSXjIo4wyJNhs96MUj5j5kEGY7dQdqdoqRKz5ccxMLo9x6bdF/CDIkoHXaMsrQNK9eNd1YkQZrfMoPP/joTRNqO5SCY2zsny3+B6c1HJxEqDZ9PMoXRAwu6j5E5iCJO4lY+eMxK0aTAWbuFU82Huzv0KzWD5ivtujx4/zPQCspuMLzzy1jbSsXFiOkFa5SmkD+DqGpn4JhwzTbF2rFt7JESklTaNHK32RQQCISSD2cO43jyp+ARhWO0GNJ6/3N1WMr4V1bXZr5BLbEPrgHLjBIa0CcI2Svtsy38QQ9qknGFyiQkATCMa6CJrYmflM4rXf6DCuG5p4bXqzyLr/bWDrmkk6Zya17tPb5S0oRNgrZZzwpUBGkQ3r15NWY8eP/xsSRnsToc8sxjga8HRkqQdSs5UNSkrCtTaoSBraUINtoSsLXip3GJ3Jo4UcKwssaWirST9TsAjsyFV36TPDplpm+xMeUwkXZY9g28uxNma8DnXMLjYjLHo2mxPegg0/3nuHLYBJ2s2FxqCibTJ1mTIpkTIu4cCPjLeQunIkj9hhLgheEpyT1+VLcloXPuJsSa70oq/uRBiCDjfMNibUQgBRc/gp0eG2ZE1SJqamCEYSpjckv8kGctEoyikD1BIH2Cy/l181WKy9DWyiS2U6seZr3+P08XP83z5j6mKOgPOHopilrjI0tQuVU/h6pAxmSdv2ggBfWqItCX5y/ITSCE4KY6igbQl+GL1RWIG+FrgKvjGrMtYUnKQw4QaCmaM/foQQkjmWz4FRzDb9IlJk7fbdzKUMDjLJFPyBHFnhPNqHl9phtRmNssB3mW/gz6ZYm/OJmeLSIJp95GyJFvTJgkTtssRJLA56bA9I9iSMmiHgp/Nvw1faUwJL+gjnGs0uMPZAkAxbDJde4qFytO4wuUB+8dpUOLu3K8QoLjTeC8xYTNEgedrf4lWLWKkqOo5TCPDkNpMKEIcYbLXGKdNnZSIk1c5XHyean+WT/T/cy7JaW5hB3HDJCUtcpbNptidzIbHSdNH3CpQ9+cBuGRcZCL/IZT2aXvLWGaBMKzTl75tzfkuhFyxqw+6i5+ryw06skQp4yxWn2Ms9wBb8w8ihYUftsgl95KNb0UgMYSDY6apNE52mz8321PESKJRjCQOsiguMm7edsV9t0ePH2Z6AVmPHj169OjRo0ePHj16vEn0ArKbzLJ/mmo4g20kWRaX+F79b0iZw0yVv0nC6CNu5Ik5o90VJc9fIlQu/am9SCOBRjOUOUy1fRGlfeqtc93PduxhEs7YZTmfjBOzh5HCIpuYYKHyNOO5d5JP7UPpANebo9I8x/nSl2m2pyjWX6TddUqK+nsIIde4N8actU2ir4bWwWsyz1iPUq0r5H+ev/Sq7oyrWeMO+TobSa5//9UyXr1MWI8eP5pIGUcDmxJtPjAmyVohfQ7MtU12ZwWjcYUjNbfnPXamIml5wRFUfc3mRIyXKw36HM17hzxmWg4zLZPplsXbBk2KvqQWGISalWbRbXamXMYTmmXP5HChxbmGwUsVk6Nlh+NVm3enJ5DA1kTArdmQo8UmjtS0Q8mzRZOKb5K1Qg72lZlv22hgvm1zrp4k1IK5dowT1TgxqeiPWWQskAIShsIQGltqxmIB25MBO1IB+3Oai3WP96Z38rj/AsveWWJGnl3GfexJPohtJNld+DiB8sin9mEaCQrpAxhGhqKYJdQ+w2orI+E4aRFjKCF5Ifw6Kctg1q/jSMkWq4Ap4d3O29iVcbiNO/hy8ztMNwJ+PH0rk3X40qUmoYa9OYearzGF5HzNQ6FXep3tBWAwFrXRXAobOIbgQs1nr5xgp7qV98Z/mj3mCJtTJnNykkuqBMBYwsYQgrPVkIcSh0lbkowlsGTULy1nm4Q6+tzZJgQ66pH2QrGFQlN0Ax6w7mbYiRNqzc5UJGV9KP1LbMt/kJcbXyHvmIyorZzwvsmCnKOtPY6ob3NCHGcwfQDbHiCn+hllNxqFFoqmqFOhzrzf4LB5K0N2DICKLLE78T4W/BZKKOrKpx2GnNTnuOAXMbAYNvZyMTiCLeLU3VnyqX3U1AITahc5cxN+UCTpDJFL7kYIg1R8YlXvMdVVuphmJDOUwupmyzx/iZH4bYxl78W2BlloHGfZPReVTZhJDOnQ8osMpPaTNPowhYNlDWAbSQwjQ8wZZVGf59HK/0lBj3Cp/hyXwmPfh6u5R4+3Dr2A7Cbjh23coEaxeZYQn0x8M45IodEsNF5iUEdp+yC43AxaIJktP04YNjDNHHVvvmtFvxrXm6PeOnfZdtZbxpA2mrBbdwbQcBdpuzMYRgbH6gNgZ+GjCGHRaE0CdBtUG6vcGm1rEM9fZjB7+Lprt24G4iqNnaUwr2j6vFHt1hp3yBtsXH3FvqyqResEZ9+vOrYePXq89VGqxX8rnsRTkrm2pBEYLLtQsBXLrmBT3GNrwmUk7vLwfIy39ze4PedyS1Zzz4Dm9kKSvek2tlQseiZCwFxLkjSi4CfU8FJJUfYtvjGf5UjZ4TMXKygdBUo5W5M0NUpD0tRMN3weGPSQAhqh5N0jcVwl6HcCtiQ15xoW867FcivGdxcFtoQ+x+d8w8BXktF4i5NVgackE2lBxY8aREsBsy3JyapJqAW+FgzFPLYkPN4/ZmEKuN8+hFI+NW+WV8LHuRQeo9qaYtE/RbVxilL9OEl7kLZfYSC1j4IeIcsAp/VTLMlFYobBt8sz/I/9P8lgXLIzkSXrGGxOGTxWm2ZnRrI3q9iddRhlNwNxk6wNFVexJ53AELA5oXmitMxo0iZnm8wHdbYYA4yoMUYSFufrmoRhMBHP4BiCJ8NHeSp8gl3pFMNxi7LvMd0I2Kx24Io2EoEQgql6yGPecwzEJCMJyWQt4ETZ42LD5eXWEoNxgQQU0A5hIC54RbyMrxQxQ/Ko/xStQHGuXaE/Jrg1k0WhGVUT3JJ8iKoXcpbnucv6EC2qPNn8CzSKZe8sNXeWd8R/lpPho9RFhUJyN1VRZlANEtMxXtZPIAT814X/jW9W/gMhPhXmOBp8jYRO8z39XaQQJHSal/1v4egocOuzdpATYwRBmXHrdqruNK/IY9wub+FD+f87aXsUL2xgCJN661x30XV1bbTnLzCcvQel/TWlAq6uU2yfBRQJu4+mG8kiC9YEGXOU4fitOCJFgjwKRX9yDxDVb6edUSreJQwjSUnMszl9Dy3/BkooevT4IaAXkPXo0aNHjx49evTo0aPHm0QvILvJbHLuoN/Zye3xn6QezLFcO8r56rfIJXfTn7yFuqyQjW1iOHsPqfgEYmUlaiR3H4PZwzhWbo1MEaJMjRQWueTeNY97/gL11jlsa7CbxVlovIznLwDRylOzPUUqPoGlHawVqUE6sbObKWu0JtdkdpRy8cM6tvX6+3JdL1eTPkaOT/6ax15Lg+obcT7UhN2/myuSSSHkFZm6jd/b65nSo8ePAu9I7iZmKHakAmKGYl82ylgtthWhFoRasOTaPDjc4lglgSUVptBYQlPxNBXf5Eg5cjnMW4rDfW2+VxJ4SqCAewYESSMkbWoeGinzL/dZbEu6BEoQamiFgq8uz9IO4ZNbBRPpOu0wup1/fbbJKzVJxTd4dkmTtTTNUHC6HudgASwJvhIMOJqEGZC0Auq+Zke6yd6Mz7akps9WCDQxQ3NnwcNVgoQRjb2uEjQCwXQjwBCC9yc+Qa15mlL9BMu1o3j+Eg13kUL6ABP5DxFql0JsglLrPAtikiWm0FqxrCcxheA9+VFmGiElV5OzBSU3ZLoess8a5U+XXgLgpXKLAbJ8tvIVPCXwlKI/Bhfq8MSC4idH+3ilVidUYGFyUk2yIBdImlHD6dv6JL7SeKEm1D53ins4W2+yJSW4qz+BIQR10WDKf45GELLQ8sk7kgcTdzHdUEzWFFNelbRlcF5cYH+in6qnSVrQ8BV5G/I2+LrJ4YEYC24biziDcZPNdoa6r5lvBaRNEwuTgIDPF/8/3Cbuo2DGWHJPYxoJ3KBGzMyxLXYfacNiq3U3GZ0jJQc4Wf4bngu+TEjIFnmIU94892T/AQB1lhlTO7nNfB+7zBE2i1sZidvkdZYx+za2GAMsqDNsCbcx7R1hd+HjaBS3OO9jWE8w7zdQWjOid5C2Ryi1znfP9UxyN2HYWDNPmKs8CVzZezNtj5COjdNwFwnDKpucOxBI6uEClWAaQ1gshmdYrr+Ep+pYMo5tDZI2hqk1T5NwRrlQ/Q4Xqo8Rt75/Kp0ePd4K9AKym4xAMq62UzQWMITDeO6daK0YtvbhhlVOFf+adlDGEBYJewBrlVOhF1S7gdJqDCPFWO4BDls/xtb8g0Ck35bSIRHbjBASy0xhGEmU9og742sGTz9scqr6tzhWlpHcfdSap8kkdyMQpBM7SSd3rbwyuuFWW5Mb7se1MM0cmeTujb+TDWSG18v1yABfrdYsl9hJIX3gura3OuDrODx6/hJK+wjEddfYXS+2NXhdwd616Ekle/T4/pK2IGe7vFy1sITmTF3w5JJBxhI8umhzoWnTDiW+kix7ktm2zYtlydGywe6sYNE1ABiPuxQ9iQTuGwgpWIolV5I0FDNti4ylaIcmVd/CVZJj1Uh6JoBBcvhKkDYDRgYqvGfLDP/9osvf2+pwZyEgbYYcKkgmkm0kULBDtAal4cllm1DD381kmWvG+fT2OinLY6ZlEjM0g07AsYrNWFwx3zZ5pSY5UjJ5oZzglZrNpnhA0XcJtSbU0ULUpty7GMjcxe7Cx8nGt7DFvDO6z63UDLneHBkGKTBOqX4cAwtDCDwF816LdqhYdhWNIKDiRwtxP57Zz/GK5P7BOAfycX4m9xCXGoq7Bkwu1CPh/TuGJW4IE8kkc26LrfEUB8wJJhinEWiOi+9xqQmtQPGV5nfZIe5mImPznqEEWxIhdxXavH1Isssa4mOZj1IJXQZiJgVHsNwOCZQmZgr2JnMMxSUFNUjCFDxZXua55QYVL+BYMcBTgl8ZfDtLbRiJxblN7Gey0aYdKv7j3B9TC3ySlmTQipNSaQazh1FovuV9hR3O/Wit8IIadXc2OjdSJh8bGGen08d0/Rm25z/EPdaHcbDI6BQVuURZLjGcvYeLpUeQCDwCXgzO4AuPb7ePYwnJ/5+9P4+X7Dzre9Hv+66x5mnv2vPu3fOkHtWabcmyLNvybDAG5wCBEMLJSUIgAz6558INIQHfkJCQawKBQwhhOAaMsY2xY8uyrdmSNfc8d+95rrnW/L73j+reVluSJdkCGbu+n0999q5aQ6251rOe3/N7dsstLMVtrhdv5Cl1L4mOCXWXqqoyz2meav8Ja3KN+4M/IxA+i41HCcJFDCODYw/T9i5hWwMbDxxtq8p48U0cKv048krJw9U67kh5eNE6UbyOZZY5UfsYjWSeVjBPJ1wm0RGx8kjZQ6w2n8KSaSwzTS26yPby+xl0dpIkTfZn348r/+YeCvfp851APyDr06dPnz59+vTp06dPn9eJfkD210BXdEmI2CyvpyQm2Fy4k4buyRcts0y9c5KZ2n2stY8xlD1ALr2duneZeufkC+aVTW0h7QzRCucxELSTlY2+IUoFdP1p/GCerj9Nyh4ijut4wSwpd4Jybt+GMUUhvYVm5zSWSPecr6SNZQ1iSpuOv0A5t4/kijlG4UqvsleDUh5Dzp4XHaa1QsrURqbspZo9Pj/TY1sDPamgkX7Z7365ps61zkkK5sRGM+xvFY1+UbOVb4cwWqawkaH81vhelkp+u66affp8K6x4mkQLipbGEJpNGc1tgwnXFRVrvqaTCGY8k3pksjkT88iKIG8JtmY1RUtRj3rTXui4jKUiHlx1aESSow2JLTUFK2F3vkvaUNRCi6frvazbxRZU7F4Wf0fBxTU0gZJcXiwhhOYX9od8YlpRdQJWApOr+X4p4FjDImNqfu70f+AdI12G3Yjd+Z4JUj20+d1zZW4dbHD/Egy6PlsyCY+t9iSUs52Eog2W0Ex3euYhRyoZBl3J19SjjBffxGL7abxoHUObrLWP0WCFBe9Z5hoPMd9+muuLP7Gx/TYV7yYlSwjRy9gNWC6WFDwQPM0cKzS0x1Los9BNeKbeohlBqGC+E3PKX6UTCwZcgR9r5j3J5Xav/1vRdMhZgsvROiuqxWha8CPlW5hu9zJuS+3nkEjG07ASwOWuQagknUSwq2iQMgRZabPix3RizWTWpBMnPNVeZsDtuSxuTxX5s+aXuKlYYSqTZlk3GEiZxApqQU9nMpyWXNJLTKZd/mL9I2xJ385pcYqnuwt8NXmCqpHjZvkmLspzeNE6CoWUJpaRJojWOOxMsuYrHANm/A7vzP09KmqIM+IEZ+RR0tIi1F22MsUBcRv3FP8Fj3X/Hx5t/FcaepF1ZhlLNlHXXSSCGXmajGFxk/E2dtpvYlJtIyttdnM9w9mDVFSFirudZ2u/Tz6zk+HCLSRJhyhuoFRwzXV2OHsAIQyGdQU/mGe4cAv6SmmBIR1sI0Mxs5OR3PWknHGMK9P6wTyNeIYw6SClxWjxdhId0fEuUWsfp5UsMqDH2Fn+AE25zrp/4VWVG/Tp87cdobX+3r2bew1pNpsUCgWmiu+kyhQX1NfYIm9gRcxgCoez639BObePjFllvvlVXHsQ1yzS9KY3pHFSWCgdUckdRJPQ9hfIpyapGjvQKDbrTdR0B4lkTp6lHk6jUHSDJaQwybojrLeOMpA/jCmcjZcl0qxF57BllrSs0EoWaQXz+ME8aXeSKG4jpU0QLgI9V8FX0pBZSgelAqRM4dqDBNEaQljEcR0hzGscD6+O+/z/BQKE8QJnRCHMK8PMV90Y8vnL7tjDJMpnOHuQucZDDOQO0vRnN9bzpRAIhHQxjdxGPd7GeggLIW2kcF5dI+2XoedwufzyI/bp0+d1Z0/ph/jItk1YUnGx4zCeiljwLZqx4HRDc6QCZ5qCQ6WE482ejf35ZsSbR0yakWBLJmbRN/GTnlMiwMmGYE9RU3USTNELpR5ft7mhHHG5a5E2NLtyXUIlea6R4mDRYzTbxhCaUrHLQxdGuWF0mc9fGuW6Ypu5bgqlIWcmnG077M77mEKRNmNSVsz9S2XeMrLKmXoB10g40UyxK+ejAXXFVfFSx2b+yiV4MqPRGma6vcDksdU2AHNyloXwKCV7MxlKRCJAkRDrAE/ViHWA1gohJEHcYq99F896n2EkfZAjxj6UhrNqnikxTKgSvtD6ba7Lv5+55Cjfn3sHKVOw6ilGMxJLCo7VAoq2SSdS7CxalGzNbBe+0DzLoKqyPZMnawnCBDqx6m0DS3Km1eGGSpacpcmYYAjNiBuTM2MWfBsvkVzqCPyk5zKZ6N7fY3WPybSLawjG0tCIBBWnt8/asSBSMOhozjRhMgMnG4qJjMH5ZsxqFFAwbFxDcjyaZ1hX6OqQjuht1ETESC2pUkIgsKQkb5nkbYlr9OrSvERQCzTLXkwriZgRs+ySUzynT7Jf7CbRGkMIiraJFOAYAi/WWBI6kSZlCn5n/t/yfZX/k+lkDYnkkn6GCXEdXdFiKT7JZuNGjnX/iqwzTL17dqOty9Xf03JuH37UoOhOURYTBKJLI5lnJzcyJy/SVisYwiQrq/i6ST2YJk48oqTNRO5WWskia82n2VR6K+1kBa0VtpEhUh6rzacANu6PslRYSc7RDhYJo7WN+4Y+ff52ooGERqNBPv/NZbj9DFmfPn369OnTp0+fPn36vE70A7LXmOnmg1i614Rxyiwz33mKSHcpZfdiCIeZ2n0kSYeOdwmlo2uyY6ZZwjSLjJr7yJrDpO1BbJnFwEIgKdoWLdlgXl5g1T+LZWTwghXiuE4YrRLELYqZ3TS9aRYbj7LmncMROQLdxjHyLDYeZdk/QcooMZo+DMBo+hC2lSdRPlI6ANcs00thW1W0CsmltyOl03tyltmNe8UZSev4WjOP55llXH3ipdEv2jcs406idITxEtLGb+T5Usdiegu59HYss0zK6rlKZuQAW0vvpBXMv2x27OpyKeURRssvkFeaZgnXHtzo4/btIKVDLr2dTGqqnx3r0+dvEdfbW8mYMeuhRdFKWApMjtV77oO2FDy5BicbHvVIkmjoRHCg3Mtyjbq9hsuxhjNNzbZswF2jq7x1JCRUgmYkcaTmbNtGaVgNTB5aisgYirFcm73Dq1yX97FlQjnfJVYSJx1zy+QiLc/h9y83WfRcilZEpASWVKyHgpQR86XlLDPdNF5kUg8FaTek4gRMdx3eNLTOtlKdlJGws1wjbSTcUG7hGoLJjGa6IzhW7/XcOlELSUsLQ0jOtb7IqH2AufbjlFSZllpmIBnBEBbNYI6SuYmGd4mD4k28LfUBPOFRSW1j0XsOQwhcQzKsB9mcs6nrLvnUBIOqwocK72TRi5jKwKacwQO1FRa6vevucX+Zehww3U6QAvYWFHdmt1Mx0zhGL8vVihRznsec36Uba8qWQ8XRPLjkkWiIlaAbS1wjwUskvzB9L3mrlxXzE0gZgsutmM3ZFCVHMNeN+Nxig2fXPRa8nlvl+WbCXKe3P9eChFYsqKYkQ66i5Bgc1Y/gq4Svxse4FD3OSXGUaXmOS+pJTgX3IbUkED7XlVLMiWWGUxZS9JbBNQRDrmIt0NSChE4S8ax+mJIaINGafezmvFrgseQBTqoLXOp2eNA/xbFmg1U/wjEET0Zn6cSK95f/T6ayFi1ZI68zODLLmBhgJTmHwODp5h8jhYklU5QzuzeMsqJ4nZQzzqC1E0P2FDfnul/G0g5HxO0sGNNcqH2GKGmTEiVq8WUi1SWIamScKllnhIu1z7LeOopGsx5eQgoLS6ZIiRKN7iUMI4NpFpkwDzPf/BoBXabk9dzgfj/9W9Q+30v0j/bXmOuzH+Kr7f/JFGOkTYN3536cTWonI9Y+BowtDOQPY1zpTl9rH9+YTumIMFpGIEmIKDHKJvtGymKC+fgoEoPT4RJ1PYdAknNG0CgMwyWX3k4puxc/XKHeOYlppJks3U3GqWLrFMN6C6ZwmSjdRdefoRnOUmCQydLdDKgR8s4YxfQWKtl9GwGIEOYLLOefTxSvYlmDdIMl0s4QaVlirX30Gsv+jdoxBOJ5Daivfodh5DHNIoaRv6b5smWkMIw86kqw9lI1Zxvf87waqoY3Tat7lihep9E5hUASaZ+5zpO4ZmEj6Lz6d2OZviH4lNLBdUZfMF4YLaNUTNoZwjSL35KD5EYAqRVx4r1qR8sXW94+ffr8zSEFdGKTlJFgSU2gBHcNhwDMdUOe6i5wfSXNSiDJW9CNezVnF9oGrqF4qmazLRuyuyiwpMY1Y5SG9UAw50nqkcmwmzCcgkj3grkZz0AIzQe/nGUw5TNZajK3VqBS6CBMje9bxInBT2/LULBiLnZcnq6bXOy4bMkkPLiS4z1jNXJmjCE1tw10aXkOjpFw/xJoLah7Ljk7wrYStpfrREry5mqbRa+3HrdXFaMpWE06ZEwDA8FtmR/lYvch4rhBTa6z2jnFqrFAM1mkktrOTOcxDmS/nzk5y1zcYE1fZqH1FHe4H+RryXE6ccKOXApLwoI8zz3p9zLi9t4XbZO8pXANzcHsINPdLptzNkWdYyqTphnF2LLXULsWJOQtkwstjy92n+OJ8CyGkFjC4IS/QqQ0nRjeOe72ArYYVkKDp+tZlIYfKb2VtSvqOAkEiWYpbvPF7nP8zsonGElb3FktcqCcomiDIzX7y5LdRcFMV3DDgMF/XfpzxtO9gGokDT9WeQvb8g6H5R7uct7DHr2fLBUsmSLnjBCKkIqq8OR6m9sykzzbWWVLTrLkJeQtzammpB0qOnFC0bIZE3sIREA98XhaP81WOcKbnTvZrDexI5flzvRubioXGHAtLAlH7O3c63+BkbSFYwjektnNMR7lOn0IIeBW427WWs+wqXAnQkhcmafevYBS3Y1j3QtmaallusE8jsiyOf0G0jrHeXkRXzUAqLWP45Ilb4wSKW/j/qHeOYlh5Clmd1Et3MSkfYSSMUHOGCZNgSheR+uYlD2IpW325N9LTEBeZ5GIjdq0Pn2+F+gHZH369OnTp0+fPn369OnzOtEPyF5jsiLF3x/+adKGwUWviWtILEx2ySlO1v4UgCTpvMAZ0LYGkDKFlDYnah+jxRpjukpVVXlHPPpMawABAABJREFU+p0k9J4UrXRPkaFErAISFeAH87S6Z6l3TuJYFQC6/jSxDnr9XzDJ6wwr3ZOUGefN+X9C3h7HVSmma/cSiIDV9klyxjBKxyjl9fqYvUwGRmuFIW22FO5CIpntfA0hHDKpqY0MIPTcF69KAK+ilHel2WSTOK4jhYkQJuXcPqqFm/CiGoa0SZImtlV9VcYeV6V/rjPK/tKPknVHWAlO4wWzSGluyCW/sVBYPC8Ld9XZKU66lNLbeo25ZYpMaoqJ0l34wVxveFznWzmFMqnNlHP7UDrCC2Z73/8qe4mZV5p821aVbOpaV0zHHn7Vy3TtvIvf1vR9+ny3c9nr0I4lftJrwDzkxDhSYUvNeT3LgdQIWVOz6mtSBlxf6ZlEjKcVp1oWB4oRiRZUnYTprsOx1QrHmzaOofETwf+aFzy2avDEakLOVHRiGHYVDy1U+Td7HCaqdbqBxd4bV0gSyfJsjrPrRXJugCU1kRLMegZ784pd+S4rocGWbEwx5fNn0y6llMeO6hrlfJdy2uM/vHGGrVvWEAJGy03+4sIYhVKXE800I9kOmzIJl9qapcDANqAgUwgBn63/KhExfrjIaOE2FuLjhNEyS8EJ1junGVc7yTrD7LaHUUJRFGmulzexI/92LshLbFbbyJgGtUBRDzSb1E46ccJ4xkABWUtysik5XVeca3UYdlLkLcHufIbjnXV2FmwWPcmDyxKJIFYaT8fsF7sZU+PMiFnKls2RbBXbkBxdjylZijcMtFnxYTwVkzEUxxuC3XnFqq9wDcGqnzDgQkmmGUzGeGf6fWgNkYKxtOJYLcEQmjE3ZtRN2JrVZE3Nb+54DzlT8WwNurFgKqN5rL5GoBS+SpgW8xyt/QGJjtFacbL1l8QoRp00y17MDblBchbcOSy53AYvhvNBjYJtMhu2aMhV1sUCFTNNPZxmPqnz5fB+tuZcVr0Y14DP1M+SMgVFG4q25B8NvYOhFPz++lco2YJOtMqsWGI96bIpayNlimE1hWsVaMVLRPE6GXdyw1kxk5rCi3vmGlvUVjbrTdTlMrVkhorYxLbyewGYD5/lQu0z1Ltnmcq+YaOnpxCSUXM/eWOYNX2J5fAkBTVAg0UOlX6cI/kfY4tzK3OcICGiE6/QFl3OiCdfr9O7T5/XhX5A9hpzmmfIWoKyazJsZwmVYkWu8enGb3FH4acpmZtIu5NX5G7mRuASRqsM5PZTSG0ik5pCozCFxBEGriGY0pPM6GNsz9zFmr6MISy8qLbR8LiQ3smW1BsZzB8hn9lJO1oiT5UlfR6F5mb3g5zz7yctLQoMk8FlsnQ3WZUljms9F6TWMwzkD1NwJ9DKf9H1e75EzwtmcXWWoj2JQGIaacKoiVIBKmltjGdbA9dIEntuUr0AKOWMYxguUbRCrEKycpC0Xdmw4H+ltVWGkd8IamyritaKrMqRs0YJoga2VaXeOfMCCeJVkqS5IY1UykPKFHFcJ1YeQ/kbUMojiOoUGEajN6x80UlvfZ63fi9H27uAa5Q2tgW8euv6MFpGCEkYLZO/Yuf/ctLOV4roXxb69PmmLMtFfCWpuhHjqZCyHeEaipypud6ZomgLinbvnNbA2Zag6moutAWHiwGrocFjaxZVJ2LekwRKMOwqMmbPjfGu4V6j6DcPCxY8g7cNd9lfbJI2FTsG1/E9i/ONPDIlKY752FbCjoEaZ9eLzHsWJ1spxlIJCiinPO6o1hl0QuLE4AcmfTqhTRQbpHIR690Ua400VrEnnUzlIu6orhNHBhlTsdDOcNNAnb+/rcXunI/SsLvo4BqSe4r/gkdbv0vaHWfVO8OkeYhSdi8D9naK6S1UjRwHxZswpeB884tcFrM0koAONU6vf5zz4jRHo1nytsSLNRnhMOhaXG7HfK51krwlGEvBgYrkUDnDxaDBp9YuYxvw7uEKzQiGXEXeEkzlDIbSvcbL51WvufINzlZG0r3gbl/J4PCAyRcWBK6RsK+o+N3zEXOe5FBJ8dCyYCJj0Io0jiFRGm4bstnqlOgmCdOdgE6skcBQyqAeSY43LRqxZMSNWAkE3USSNhR7ir3r+uWO5PtHK2zN2WRME4HEdUbZyvVs5hDV7H4UCtvo1dL9Uf2TrAWClKEo2IJWpNibKbPgewQiJKXzOKQZTlncZL2TElmuF7dhSJiLGygNb8psJ9G9gPBcyyNlaAoWvD93B4HS3Ol8HwkRR+Mv0ok1d+X/D6pGjqY3w1rrmZ7zctJF65jR4u2U3a10ghWG8jdgIHCkgauzDMjNLKkzXKj/LwbzR6h3TjJZuhspHALdImeNUskdRAqbhIjl4BSdaJWUWWGe0xQZpaJKDJBnWA8yxh6aepFEBbRFg1gFL/tguE+f7yb6d159+vTp06dPnz59+vTp8zrRD8heY241b2KmHXOx7TEftrgQr5LSKSZyt5IRDo1kHq0VKulccRhMMIwMjj2M1glaJ4ynjjCoJ+iqiDVa/M78v+WymGW58RjL6hw17wJluYmiu4miuYlybh+GdAhEl4I5hm1ksGQKX7RpBrM0RZuUMNnivpGLzLOmL3NOHsdLahxXX8GyKlTMLRhGhmFjNyvt4y+ZsbnaTwYgl97OqdZfcbl+H2l7gCBc3CjSvSqpK2Z2k3VHCKPVr88DTSdcxraqBNEKeXeCYnYPzc5pLje/zHrrKEnSIeWMY5llbKv6sts9SZogDLKpLYTRMlFc4+HGR5mp3wcoEuWjVIBlll5gxOE6o1fWLbrSwNoiSZoIIfGiGrbMYlsDxHGdhfg4llmm1j7ek3SInmHJq+lJZppF5usPbGyLq7x6g5De+HX/EsCGtPOVOEl+M17L/mp9+nw3cqOzjXokqYUmT9RcjjXTNCIThWB3QeIYgnYsqKZET9KWg0eWE/YWEqopn3YkeM9YG0tqJtI9+VuiBa0Ibq6alO2YRiSpR5K8pXEMRZAY7Co0qXdSpDMhN00tcPqhIpfPFDEMRa2d4hdOtdmUDtmWCThcbrI543N8vQjAUKZDM7DJ2xEn6wW+tjDI+nKaXbtWsI2EhZNZAObne6qN+ZV8r/m1E9AKLbzY5P4VF0vCZ+qnsSRYwmBr8e2krQEG07uZjp9mq3kroW4zZuyjkQTc3/kfTHsdcu4YJ2of47w8ii3SvKf0YUp6iL3WGBfbHilT8BX/TxhwBVtyJjdaOylYmtFUTKTAlgILk3tKk7iGwDWgEykeXVHEGpY8RcYU1OKQG1MT7ClkWPQD8rbAlhBrQS2Ed40lPLGeZ9CJ+YFJh0+uznKxY7CrICjYGlPAdSXBqXpPcjeeldxatdicdSjagnokqDiw7IMAXKlZDU2OlHxasWQlMGhFECqNIXpujKcaPg9E91NURYJgAQebSERs1QcoijSGAFMK3p15D1VX8yeXIlxDcyycZ74bcMk4z4gscr2ziTsyO5nthFQdh5PiKJ9r/hZerNmZKlMLFKt+jCHAMeC6UorpDpxsaNqRohuDp2NC4XFP+v24hmDYcVlNOkzl7wB6ypdCahMAq51TNMJZxrM3Ysss67Q4rS8xoAZZSc6x2HiUofwRoKeEAShltmMKl26yRjdcZTh7ABOHir0VAD+pMSS2EgqPx+O/4sHwk9zb/A0uJl+jJCbYa97FidrH2CqPYPYbQ/f5HqIfkL3G1OOQWhySliYWJhKJ0JKF7jM40qAiNxElbTQJtjVAknRIO6OE0SorzSfYI25ln9jOgjiHK00q5Pjh6v/FmB5jX+lHCOMmm9Nv4HznKyw1H+NC7TO4Rgk/rhPoNgKJ1oq11jNcbj5I1d2DRGKInntjTfcaVUssVppPkDGrhNEqioSMO05aZ0nZvQvrS9U1FTO7Gcgfpu2dZ2fuHqaKb6VkbdoY3ms23bupr3dOYso0ldzBjWG9ZpMNwmgZrRNM4dC84jR4VaJQzu0jjJskSQtD2j3Hw5eRLxTS26m6eyhmdgNwY/GnGMrfROVKvZppFgnCxZ77o7A2AiApTGxrAK1jXHsQpXqNTLVWpKwSsQ6wzd5NSsufxbZ6/+srdQBCmBtB3UthGHlK2b1YZhmVdDaW8fnB5lXN/St1ULSu1Hr5wcIrGv+V0q8h69Pnm5NozZCTULBihl3FdfkuBSumaCV0E4GX9GqKptIJM12Dh5di3lCVZE3FJ2fz7MmHFJyAIJHUQgNHama7kkYIsx1YCkxsqSlYio/OneOLSzlGcm227l5jsNim27Hpdm123Fxjckud3IDPopfiP+93GE13kaInP7RlbxnPt7KknYi1oCfZHkt5veUtd2ksucw2c9S8FEJoLjbyGFJTDxwG7JhHVkqUUj6GUGzLKkIFf7e6k6wlOFhx2Cd2stp8ku1qP3fa9zBlDLCfG9hpjCIRDGX3k5CQMQe5vvgTZKlgYJG1DPY4w9TDiJsG01RcwY8N/F0uthJmO4pj4TyXOtCNe0Hpr1z4FRxhkjXBizUrvuDOYSg5BhMZSJmCL6/U2FtIo+mNc10xxbKnub81zVQ64U2DATOexYFim0gJHKn5ybExmqFmwFFMt2E90Hx08XFGM5Kj64pm2GsAnbGg6igiBY0QBhwYTSlONiUDdsySb7PsCxIt8BLBlxqzLHkKiWYi4/BG83bW5ArjpTezJtcYpMCMPMP1ld665yzB9rykFgreP2mTMeGNuXFCnXCLdR3LSYsv+L0HeXnLJGNJvr9wIxP5Wzjf7lILIzpxwmjG5GLLJ2tqWhHMdkK6scaWvRq7UddlMBkD4FSrTTUlGTFzTLce5ubi/86u4gfIG7065DBaZrN9M1vUDmId4GibKT2BJQyCpNdmZ1jsYLX1FIXUFEpHjMk95HSZEWMvpdQWSozSZo3V4CyOkaPtL5BWGZbDk1Tsrey17+Km3I+z1nqGYV0lEhG7Sx+kQPZ1Obf79Hm96Adkffr06dOnT58+ffr06fM68boGZA888ADvfve7GR0dRQjBJz/5yY1hURTx4Q9/mH379pHJZBgdHeVHf/RHmZ+fv2YeU1NTCCGueX3kIx+5ZpznnnuON77xjbiuy8TEBP/+3//7FyzLn/3Zn7Fr1y5c12Xfvn189rOf/ZbWyRCSgmHTSAIKhoOjbfIiza3uD9JV8YZhgpQpwmgVw8jQ6p5F65hiZjdnxTOcVfN4SY0ZlpgVS6yFActilVE9RKwCJAY3pz7IdcX/jW3l95KWJZSK6cQrmNpiq3ETufR2DmV/gNXwLIHwaSmflM6QkiU68QoFBhFCUqSX2Wkk8wzY25nnNEIYSGEhjfSG6cjzqbWPY8ssufR25uPnaMbzKJ1sDO/60xQzuynn9pFJTbHceIz11rMbw4SQ2GaJSu4gufRWFhoPkXZGMc0irlWmkjvIeusoSrUxzQJKx/jB/DftiwYQxC3aqteLTamAdbmIH9epiCkAHKvIQP4w1cJNmGZpIyOVqHDDRMS4YvqRz+xECJNuuEYrXCCMmzh2r1m3FyxtZMQss4xtlvCD+Rcu0PNIkib19gniuIaQNl5UuzJ9+gXjvtx6fp3esfT8Hm/w7fUoE4gr7pGvnUlInz7fTTj2MBlLItAYQuMrgZ8YLPk2T64bnG3E7M5rxlIhrVjw7HrCrqJFpAWuVIylNF9csvkvJ8uUnYCMqSjYEdcVIrKWYChFz62xbbAeSnaKKfbmQx5fGuTCqTKWk+A4MVFkECzA8nQWaYBr9K5njhWzKd+iFdqsBA6rgYUre8NSRsJ4qcHZVoZWbLKykkNKjUYwXGxxfL3IVL7FmudSSfmkzYSbBhqkrJiiE5I2FFUn4XhdUXHgXDNmT9GmmN3DMR6hkYTMxQ0sKTmZzNIVHjv0IWxhYQqHEVGhzRpjyQQPRV9jLQiJUKz4mifWOjzamaXkGGg0d+THiZXm0VXBoif536o/R6Bj/j/nf52SA0VbEyqBI8ESvYzYvlyRlCEYTUs2ZXtNus+3PcZ0lf92qcaMZ1OxE9ZDm3nfYtCJGHJjspYgVII7h0LuHFb84+EbSTQMpCQDrqDqKGqBRgFeAjvzmrkufH4+YndeMe1ZKCBSmiVfUHE0P1AdZ2dBoOgtR9YykBgstZ+lQ43P1f8De/R+LrUSKg64JlxqawSa9VASKig7gppoMJKWHMhVeEf6dmKlOR/UiJVmqavYz0F25jNMZmxG0hbP1dvsLbk8shxhS6g4FkVb4hoCxxB0IsWUXeRUvMD2bIZlT9FNYgzpYmmLgi5zbv1TmGYR26pyzr8fhaYZzDIjL9DQHgtikY4/S71zkq5ocWf+nzJk7KQkJlhQp3i2/oecbn9uQ5q/Fp5nm/MGiuYEk7nbOKUeYpdxB75u8HT3k5xWD3JP8V/woPf/sCguUNdzXJKX6OcM+nwv8boe7Z1OhwMHDvAbv/EbLxjW7XZ56qmn+Pmf/3meeuopPvGJT3D69Gne8573vGDcf/Nv/g0LCwsbr3/yT/7JxrBms8lb3/pWNm3axJNPPsmv/uqv8q//9b/mt3/7tzfGeeSRR/jQhz7ET/zET/D000/zvve9j/e9730cO3bsVa/ToGNhSUHRdPh047/yYOP/R40Wy3KZVWokoheUJUlnYxrTLPbcBqWDKRyqeoC8MUqNeS6Hj3NJTJMQU7ZsJt0byeocBgYJEWvhOc6tf4qUXaLWPk6bNZ5u/xlTzs2cSx7pbQNWaMoWI6JCXpUpWZt4pvY/qOQOcrT2BxhGnvXOaXzdpB5MYxkujj30Anv+b5QwdoMlau2T1LtnKesRDCNDJjWF64yiUARx6+uOfaI3bSV3kIwzhBfMoklody8AkoqzhSRp4kfrrLWeAXoyvzBaJQgXX1F9VRjXyMpew2vHHmam/RhN7wKuTmNbA6SsMq7MU5XbiONeQCRl6oqMsdeEuuhclVR2SDmjhNEyhjAZyh4AIFYBKWdoIwCLkzpeMPuiges3YpgFUu4ESdIhCBeR0kEKC9saeFmZ4NVtf3U8KawNB8pvtPB/5QHdC3l+TdtLOVJ+p/Cdvnx9vjsJwkVGUjDgRCz5NudavXNzPTQYTsFNgwZlO+ZSx6ZoKR6KH2M0pUgbGl9JipZiT0Hz07vX2Vyt8fS65GQzzaGBdY6UApqRoB4ZjKV7QdTf2QwrgYkUMFDoYGcS5lfzfG25wlOnRvAiC2tAoDRsGV6nlPPwIovzrQxbcm00gooTIIVmONPFMDRFOybRAik02UqAQBMEJlkz4Wwjz2PrGU7WC6yHFl9aKvJ7Z0b5t8/lOds20VpwoCwJleDWqmQ10HTDNUzhMGg7LMlp0obBTPgEc+IsJ8Xj+DrkTc4N5C2TucZDJCRsVrupODYHS2kutnw8Qo6kxphu+/xl59NYEpSGRS8ia2rSpuArjf/ML2//p0ymEzqxYLYrGU3Dog87Cz1ZYSfWnG7EzHfhUivmkrzEdSWXW0sV1kPB8YbBvGezJRMwmulSsUM2ZRSW1GTNhE4sSTQMOjDswmxH0YwENw1oJlMRJRvShsKLNbcM2kx3DQCGnIi0KZhIK/7ZiV/iXFPzpQWf863ez99aEDGgBnHtCoaweFPhZ+joANfsHT+dCEqO4H+sPsnldq/NQcVWvLk0SqJBa00nUnRjhYNNM0zYlDOYytn8SeOvMCSs+wlnxNN8snGMimMykYG83ZPQPtpa5HTTYy5uMBu2qKgS59tdTgbLtLTPrvTdrMkVZjmFbVWJ4zr5VM/B1xUmJXczF2qfoSkb7DU3cV3+A1xf/AkSIrLSJhBdjtb+gOXmEwiZQgiTzaV3UNW9Eogavd/M5eAUYdKhJDIIDEYyB9gv7yJGM5I+SIVxYhVQS2aIn+fW3KfPdzvm6/nl99xzD/fcc8+LDisUCtx7773XfPbRj36UG2+8kenpaSYnJzc+z+VyDA+/eO+lP/qjPyIMQ/77f//v2LbN3r17eeaZZ/i1X/s1/sE/+AcA/Pqv/zpvf/vb+Zf/8l8C8Eu/9Evce++9fPSjH+W3fuu3XotV7dOnT58+ffr06dOnT58X8LcqH9xoNBBCUCwWr/n8Ix/5CJVKhUOHDvGrv/qrxHG8MezRRx/l9ttvx7a/Lut629vexunTp6nVahvjvOUtb7lmnm9729t49NFHX/UyrgUxkdLESrMz/w4OlP4uhjZoskxO54i0z6b8Gynn9lHK7kUKhziuU3AnqJo7mK7dS4M2oW5jYLHJvpELnQdwtMvR+DKJiHG0TVt0mdITZMxBhDDJmFUG8oeJtc9tmR9lUA0wZh6kYm/FEBYBHqu6SVOu04jn0GjW28eBnpzONvMESRPHzNP2F4iT7oYBx1Wenz0JkiZS2EjpMJjdTyB8CuktZOwhtFb4YY2SM0Wiwt60WmEYGerdC2TMQQwj03Ob1BHohGbcc5+0jOxGQ0opzI2ebVdNMF4MISQCQZJ0iAmoh9OE0TJBuEg1dxhLW1QyOwFoRgscq/0RA/nDwNedCYXoZVuW2s8ymL0Oy8xsLHcnWGKmdt+Ge6Efrm9krK6akHyzDN5VCaEUJl1/euNzpQJKzhRhtLohE3wpNBrTLCJF7zh+fhbsanbvteRqH7aXGnaVl2to/e3IJ18tr96lsk+fbw1HghSwHJhYEr5WcxlyY0IlWA8FX1gwMUQvi/avxm7hyTWY9yT3L1t8YlpxpikIE4OLyyXePhIykQqp+S6XuxbbswmtCP7b3GX25AP2levcNbrCWMpDKUFn3WYg3+HgQA0pNGNjDQB2DK6jleDo/CCbhmu0YsnpRo7rB9ZxjIRG1wUgSQQDTsiSb7DaTbEym8WSCiFg0PXZlOlw20CbqUyHsZRHkMDBYsD3TcKg0/sNGLAVKUNzsS3ImHBj6gdIyxKJhgKDdJOEcfswB7ieqtiGhcnn/S8zH3Sp5g4TiBBbWMz4HRa7iomMw4FciXakOCmO8/bUu8mYgqIteNe4ia8EzVDxv4//PJaEYw1jY18s+bA5o/n4wgorniZINOOZ3nBTCraqzWzNarSGjAkz7Z6r5cOrDn9yucLpVppIwdmWZDWwGE/1rq2uAedami05wW8vP03WVCh6rolSwOacINa9ht+rgeRy1yZSECrBz2z6eaopwY6CS9WFWIFrGKSFxdtT38dwMs4leZIxJ8vHG3+On8CfNP6Sk/WAezLXs9CN6CaCe+cjFjqq931ZgW0IZoIWO7NZBtwrjZtNwV3O2ynagmfic/xg8Y1cx040sBZAO+ptk7pc5vP1/8BZ/VVO6oc5IZ7AFgajokxaONRZwsBinF3ESYtsaguuzGNIh44O6MTLbCm9C0e7zIZNsipHLGIWvGdpqoDr2MlA/jBKRyRJkyhuMKQnCXVE1hoiTYmBZIRusETRmaSje8qOy/X7aIkWy2KVih5jQJfJGlUSFWz8Pvfp873A35o7GN/3+fCHP8yHPvQh8vmvy8N++qd/mo997GN8+ctf5qd+6qf45V/+ZX7u535uY/ji4iJDQ0PXzOvq+8XFxW86ztXhL0YQBDSbzWteALaQ1OOAjGngkOLZ2u9zkadxRJZj+gF83WQ1OEPbX6LWPs5Y7gYAWuECSii2lN7FE43/zg3yZsbVVoZ1lSOpD7DDGuLm1GZusXdhYGBpi6xpUgsugU6YrX+ZEbmLhfrDPJvcS1O0abHMoJ5A6YS0zpHVaarJGLHyEMJEXwmWADJ2lbXWM7T8ecJoFcvM0vWnX2CBLoTEsYdpB4tM5m4BDISQZHSGLcbNxKp7JUBQFMUYUdLemNaQGZKkSTNaIEk61K4EhJY1iCnTjBZvxwtmN+xzDemitSKO69Q7J19yX1ytBbOtAaZr92IIk03Fu8mkpijJCUwMhsUOBBLbyLCt/F4ysgL0ZG9SplCqSz6zkzjpsNY9Q7NzeqMWLpcao5TdSzm3jyCqo5W3IcG8Khe8ugwvxtXgKYxWyaW399oUGHlsa4B1/zwD+cPkrwSM3wylvBc0yr4avL5WZFJTAJhG5pvIKL++ri/b0PqvMUjSz6tbBHDt0ZcNEPv0eS3oJr3mwobQ7M0rdmQj5j2TE7WIs42Y850OO3I+Sgu2ZAJuGdSMphSL3Zjbhix+YvsqBddnpNDGloqVwCJWEltCOxGcbSp+emKSOc/mRK1AogWllM/MeoF2x0Frwehok5IbIC2FsCXVvT6pfMTmQhPTUdw6WONCp1fbVM13mG5l8WODE0sDbB6osa/QZXO1hmUlbB1axzQTlBZ0Y5PpjkszsjnbyrAnH3KmZfPwislaKKg4ETOeZCIVU7Rh2VNYmNg6xZfD+6ioEtN6mQk9gnHlOhkRc6d9B0N2miPyjcQknBLPMOqkyVm9a8SzrRrzYZt3565nc85k2dNcX07wE8HJeszNVYNY9dwtx1JQtjVHygE7c4qZruSDo4M0o97DqVVfMd0JqKYkRdsiVLApC19ZiLh7VFCwEn5wssYPTa1yqNTkpkrv97tkx+StCCmgHcPNA5pEwxFjH81IsuRbLPtw36Kk6igm0gn1ULMjG5E2NJszCSU7oRlqPlO7QKLg08tfv2YvU2chajNwxc79ctDkh0of4HJb84+G3sPNgw6TGdhesChbCe+bNHnjkMCRPZv/SGkuiqOYUnCx7XGxFXO+GWEJwV+uzDGmxjEEpEzJaFpiS8FQSpKzJJPJFo4Uf5IxYx/Xyzf3rOd1wjku85XuHzKptmFiEhHh2oO0vQsIYWDJFI92/5jd8g4uNx/A0Q4700Um7TybGKbibictLKIrD1iFkOQzO0k5Q8yJs8wZlzGERSg8nuh8jJHc9WidoNDs40YGcgcxMBlUFVbFNJFOMIRF8g1S/D59vtt5XSWLr5QoivjgBz+I1prf/M3fvGbYP/tn/2zj//3792PbNj/1Uz/Fr/zKr+A4f301Jr/yK7/CL/7iL/61zb9Pnz59+vTp06dPnz7f/XzHZ8iuBmOXL1/m3nvvvSY79mLcdNNNxHHMpUuXABgeHmZpaemaca6+v1p39lLjvFRdGsC/+lf/ikajsfGamZkBoOxKvtj4NRbCLhVV4s2Fn+WQuI0taiumcJhkD7usOxjP3sjm0juIr6TtO94lAt3C102OFP4eriGJSWjRYUae5lOtP2TRC/mC/wAX5WlMJJ9s/A6H7Xej0eTS2znR+ktK2b1sNW/FF11a8RKB8BlRUwAUTYeng0/jGHnS7jjF7B4yqSmqhZsYMnaypfQu8qlxJkt3EyddhDCv9Ov6etxuGkVSVomsM4ylHZKkyUL9YTqiQ0c06IZrhNEq5fR2jtX+iFJ628a0V7M7eWtk47PB/BGK6c1U5Cb8pMZA/jC2mSOb2kLaHiDr9PbBVPHtG9mbF0OjiZMOrjNK1d5Njip+uM7J2p+yJleQWrLaegpX5jm3/ik0CaZZpJDehlIeWsc0O6fJpiZJWb2m1qXsXkr2ZuqdM3hRjbRRIYrXUToi5YwjZWoji2SZL98zRUoHx8xR75wjSZqE0SrmFWOPZud0b5xvIvF7vnnHVSmp+QrMRF4pQphEcRfgm8oov9FE5JvxasZ9tWgdX2Ps4QdzL5+x69PnNaAZabqxQaB6GaO0qZjKhPzwZsUNgwb/aLvDemjRig1mPJs5T9KOBd0k4c6hOmFscK5WxLFjCnbISmgg0Aw6EZ1YcKQimPMMXKlZC00avkMzcNg2usbw5haOE2PYijiRXLpQQXUSghXNc2eG+Y1TQyzO57l/qcSomzDfztL2baTQaN3L7Ckl2FRskimHWFbC3FqBJxeq1EObmW6KUy2LZmTw6dmEfZUaVVfxxmrM3nxIwYoYdhUaweW2ZsH3sITBFiZ5k/VmcobNpKhSdR2+6P0Jg6rCrDzPxaDOM8kZLjHHce9zpEWJdpQgRE/2d0OxxHX5AicaHZ5e80i0ZjU0SHQvy5YxFLcOak42TapOzFQmpBtLalHPWGQ9EExlLbKW4IxXY1k3mO0k+IniYluw7At+fGtvGx9t2Dy6WuRMI89MN81TtTz7CgkPrab40+kME6mYJQ+WA8mTqyEDrkmiBWU7xjUE4xmJJTUFK+HmSsKAE5G3YhZ9yXTXYEtO8IGBrewsaNI6RdkRHK4Y7HaqDJlZCrZJRY9TNbIYAqayAtfoXb1aseByO6EVGzQjyX+dneF/rS3whXmfLTmTTfo67m9fuGKCYZC3DWxDsMcZZiyV4rH1BhlTkjY0ZVvzpdVVFr2Ic/IYjnZI6RRpaVJRJXbnM2xhknfnfpwJJ8caswxQIu/0+pStdE+SNisMZw8xLU8ylDvIRfEcF7ptDCF4Sj9GiVGe42sEOmGTeYTB/A20umfpeJdwRJatajvtaJG5zpMcyfwQBYbZpg+i0MyJBVaaT7AgzpExLK7jAC3RoqyGv6kqpk+f70a+owOyq8HY2bNn+eIXv0ilUnnZaZ555hmklFSrvYa7t9xyCw888ABR9PWam3vvvZedO3dSKpU2xrnvvvuumc+9997LLbfc8pLf4zgO+Xz+mheALQVvLvwsBcNhSa4wYLmMp3va/TvsO0nrFDW5Si26yJJ3jLnGQxuNlof1Zg5yE5utCp/3/5KqkWNIFtisdjOQ2sm2vMOQ2EqeQQB2Z9+Jg4VA0OqeZTh3iDHrIAAVVaFq7kAiSQsHE4NEa7an7mRM7MEPV2h0zqBUzErzSaqqyrJ/gi3yBpSOyDhDaB2jdLRRoyQQuHYF1yxSMMc5WftTJkp3YZpFfNGmzdqG+2CQNF8gw5PCIuWME6g2pexeANbaxwnjJgJJ3hylE1wJ2pxxRsy9FM0JbKtKI54hTvwX3RdSWD0beh2zPX0Xp9c/ztHaHzB4pRHzoKoSipC0O0lCRNqdxFdN4rhOJ+gF4lI6PVt7s0zWGsIw8tTax4kJGM7fxHjmBiyR3ghgg6hO2hlhOHuQTGoK28zh2C8dwAMUMzuodU7j2oMbDaFTVhnjSsBrmeVvWg/2/PmbRvqavy8m1bvq/GiaxVcmbdTJNZLItDt5zWAhzNdMIvlaSAsNI3NNwPedHoz15ZTfXcx6DgVLobUgbSRoLchZMZvSERkjYTkwiJRg3pNMpBQDtuJndilsI2HJS3F40yKpXMS+PUv8wLZZEi3oxF+vjZrrKBZ9yfasx3ipyf79S2gNUVuSGw4JWiZTE+ukrAhh9Y4tPzH4hzuXMY2EIbcnqTSFIuuG7CzXqBbbnGmlWW1mWGpn6Kzb5IZDhgot5j2LjBkz6ISMpRRZM+H7JyWXm3muK7QYdEKkgFZk8aUFzdm2yU0DmkHb5aw4xV/Vf42ya2Ibkrxl4sWKu9wf5Jw8zja9m8fbf8hhoycdn0rfykQySd4yudwOiFXPUXE4BRXb5bqSS94WnGuCKTWHygZfXRX80vTTHCkHOIambIekTcW+vM9kBrxEM92OOd0IaMh1zkQPsBb6NOOQ8QzcMdilFRs8tuayPRvzlcWEYddnR6FJyujVhx0shuzIgyE0GatXc/amEZtDZYUUmk5ssDUT04k19cjgbNtmLTSoRxZ5K2FTOmHE7dV8VR1FPRT80GQWx9BECiwpWIhbLPg+O6whZtQaAGkTVn2ohz13xW35Xt3cWCri9uwkN2aHqboOltScSL7MLjnJ1myaC82IepBgG4I/XPplDCE4UCiQaIivvN5QrhAqxUEO85T/SXa5A5zVM2zLZQiVZkuu91Ar0hpbpHlSfYlER+TS28k6w+zThzkir6cbr7FVH2CE7XSFR6gUs/WvkNIptumDJFpxPnyEMG5uSPhj7SOB/cZdTGZu5mT8ZSIRsCbXGDFzVFWVydLd3CBvwDUMxtI2d5dH2WZXeHPhZ/9Gz+c+fV5vXlfJYrvd5ty5cxvvL168yDPPPEO5XGZkZIQPfOADPPXUU3zmM58hSZKNmq5yuYxt2zz66KM89thj3HnnneRyOR599FF+9md/lh/+4R/eCLb+zt/5O/ziL/4iP/ETP8GHP/xhjh07xq//+q/zn/7Tf9r43n/6T/8pd9xxB//xP/5H3vnOd/Kxj32MJ5544hpr/D59+vTp06dPnz59+vR5rXldM2RPPPEEhw4d4tChQ0CvHuzQoUP8wi/8AnNzc3z6059mdnaWgwcPMjIysvF65JFefy3HcfjYxz7GHXfcwd69e/l3/+7f8bM/+7PXBFKFQoEvfOELXLx4keuvv55//s//Ob/wC7+wYXkPcOutt/LHf/zH/PZv/zYHDhzg4x//OJ/85Ce57rrrXvU6LXsJRdOhkQRc72ziofhhXEMQ6YSlsNtrHK0qjFj7iBOfbGozkfJYbT6FoU1CnTCUMnhP5r2c4jyOlCg0o3or9UAzogfIqhxN2SKrcgghGCrcjNaKmdp9WNiciR7gNF/Do+e+1aKDJzy+qh6kqAoc7XyKQnoLSkcUU5vYW/xBzsrn2OncybR+jqIY23jCJWVqI9Oi0ZScKQBG1BRHij+JI7IIJAU1wEr3JK4zSja1hba/gBesYEoH40oB81WDh5XmExuOeKXMTjrBEgvRUXzVJGWXyNkjtKMlsjoHQDWzB4C8O/6i21zpiKK7iWr+CENqkCPFn+RQ6ccRQpJyBhFIjtb+ANvI0AzmGE0fwpJpKrmDlNPbKWX3olRAEC7S8GeoBZcwpItAsNR+ltXOCS42vsjF2mfRWtH0Z0iSJq5VBCBtDbyiAuSiuYlCegt5Z4xE+RhGHi9aZ6n5BGl3kihex7aHXnL6qy6PAF4we83fb8wOSWGRJE1Ms0iSNK9xy3wpTLO0sa8EAtO4tjG01vHXs6XfrlmHMF5+nCtczSZe+9kAjnVtxvyV9IJ7PflOz+D1eWUYRh7XgLVQsjkTcKZt04hMLnRsLndc/ERy75LLiBtTtmPuGWlwc3WNITekEZlcamUxpWZxNU9tJU3sS3KlgIlCi/F0wB8sXQDgpgHNRDphOXD4b8cnaC7YFK/TpCc1YUuSrsZYaUWiJNKVhG2TnYNrVIdaZDMBk5kupoQvLWdZbmY4vV7i5NIAk+mARS+FRLNSz+LXDB6aGeHNI6tkrIhjzTRvGlnBEL3jtRGZrAUOp1spLKGpuAG3DUkqtmLYjcjbkq16J2OFN2AISJTGEAJbyl7GRhxEa80bsj9GpDQSyZgaJ2fYnAvXuMA0016vL+cfr5xmLfR5bL3BI+s1xjMw5MRMpBMudDr8XxOHuNy1MYSmFVlMZLokWrAlE7O/mHB4wERpTVUNc8S8h6rjMplOU7QUFzsuYymfD0yucaJp8iNbEopuQBAbDDkRObOXUazYCVLAyXrI5XZPTrnkS860JCeakkAJFroJkYJlv5fBa0SS9dDictegk0jKtiZnKnJWT4JoCXAMqKYEBZEiZ1gIAVutQaoujLoxQkDFgZShWQs0RSthJTAZS0MrUpQdgRRwu/0uvuh/ksyVx+kZS5IoTTG7h4orONf0GU1Lljx4fCUmZQhKtoUtJQdS76IRxpRUGUPATCfgQisgaxkUbclBsQc/qlMwxwiiGhPGAWbEIoOuyRHjLTRlk6OdTzFllvlK9CXuKPw0rnbRKCxhsM+8mxF7H0JIDCPPhNrBQ+GnWJaLrEbnGHR2sU9sp848jSSkYDhM1+5lNqmRMSXn210MIZAItmQyr8v53afP64XQWvfvEl4Dms0mhUKB2/L/iEhCSjvkpEtbhVStFEtRh+2ZPOc6bapWitXIZ9q4QDNZJFZdvLDG1vQdpHUWR9vcUCxyX3MahWJYV3lWP8R+bmPYSfFUdJ4tTHKBaTyarIXnaXZOU8zsZtw+zGJyknawiB/Ms638Xi7UPstQ4Uba4XKv8TEplv0TQE8aaAiLSHVZbDzKLYX/g8fbf8j+/PczmxylG63S9WcRwkCpAIFgsHAjO7kRA4Nnk3sJ4haV1HYGmOTp2u9hmWWGsvuZbzyM1jFCus+zl5dfD/aERTa9hTjxepbwwRylzG5q7eMUs7vwowZ+uMRk4U0AxDqgm6xR75y7xg73qnRtongnoWqzh5uJiDkvesFUOb2dndzAw53/ydb8W1gIjm7UbAG4zuiG1NIw8qikhUYjhYXSEZXcQVr+LHHcQOkI26riWAVa3bOk3clegKUj/LiBEPKaeV9dT02CaRTZk3s3F8Ov4oc1wmiZUnYvpkzR8C6RKO+ahuGvNb2G1+svOdyxh5HC3AjyoBcMhdEyAvG6BRRXf9xfrKat55B55dj6a1jGVzpPKZ2/1nq5Pt855DM7+ZmRHyRScGe1y8WOy46cR6QEJ1spDhQ6LAcOU5kOfmIwku1Q81xONrPctWmeZtdltpUl0YLtpTqFgoeTSYgDwdpqlk9ODzHmxoymAi53XSbTAdsG1vEDi6GxFuk9Ns2nI8yUIuoafPbEJr7/DRewhgwe+Owwe0dXWKln+dpqiWYkaURwU9mn6IR0IhM/MfgvZxTbcik+tKlN3g5phRZD2Q5x0qvZyqUCwsjoWfM38hiidxasBha3jSxzcq3MjNdrwfEbs5dJiLinsB0/gdPNDkXTQQp4Sp1grvMk78z+CGfVPKe79/LW9I9wn/8n3Ol+kMsssJlRNmVt1oIEQwh2FCT1EJphT+b3zrGYtNFzolwJJYO24qEVwY9t6dCKTDJmTKQkfmLwscsWyZVbmpwlEUKQt+BwKaYVS+Y9yfsn1jlaK/DgSu+h0C0DCbvzbZZ8l/XQpBNL1kLBn65c4j3lzWRMjSHgXLM334orNpo410PNqp9w+1DvAdWZpqBg9yzzHQkrgWBHLuZYw2BTRtOJBRdamjU/wZCCB6OHuMt5I/eM9mSOkRKcaPZaKeSs3velDM1XFhIqrkEzVKyEPityjVsyk3y281WWu8fRWvHm9A/jSpNAJVQcm9PBKl3R5npnirwlOd/yuT/4M96Z+RDtOGYy69IMEwZcg/8y/Uv8zKafZ6mbcDZa4Uz0AGmzzFauxxceJV3AlSarusmymCVHhYPOOM8F82RVFoVmXl4gRZ60zjHPaVbaxziU/QFWxRw5KiypM1zHLWQMi9WkQ1o4XJIXSOs8o3qQGm32pQdY8EIsIRlwTX5n/t/+DZ/dffq81mggodFovKwHRj8ge424GpAZRpk3ZH+MHZk8c92AL7R/hwPZ7+do5y+5Kf2DnNQPU+9eII7r5NLbccwcVWMHw2qEiVQa1xDUQ0WiNClT0ol71t5eEjOWdlEanvUWmNHHaPozmNJFSgtLpihZm3qW+sECjlVECotW9yzjxTeRELHcOkraGWLCuZ4uNVb9s+ScEZYajyONDDl3jKK1ifnOUyTKv+YGWAqLraV3UVADSCRPtf+E7bm3YpNinVnWvLPsdu/mmdafkSTNa7ZNJjWFH67jWEX8cOWaYMoyywxkd7PUfAqlPBx7mDjpkiRNMqkpOt6ljb8AldxB1lrPXDP/Su4gKaNISpZIdMR6eB5DOoyYe+lQI9JdNunrOBrfS8dfIEmaGzfatlUlTho41iBh3NxY9qvBmJQpTCNDGK0CvToqyywjhCQIF6+5Yc+lt9PxLl3TI+zq5zl7hGYwSxi3GcjsohUu0OqeBWC0eDurnVMvsLR/pVwNcoUwX7IG7fmBywunNzGNPFG8jmHkr9l/tjWwse5/k0hhYZolonj1BS0Fvtl6fiu8nsFmn799lHP7+Bej76PqKNqx5GCxw1P1DDeVWzy4kmNXPmQlMNmcCVj2LapuhCl6NUjVtMcXFwbYm/dYDy0ODKyRywacXaxwuZNiT6GJnxj4iYktE040M7xr2yyeZzF2oIPyNc88OcSuqRWstMKuSlrnBVoJ8jsVj983RKR6wYElFbZMSLQgZcZcaGXJWwmXOg55S7EcGGzNBEx3Ha4rtMnZEfm0TzewuNjIs63YoOa7/Nl0nnePdlgPLbJmwgMraW4sB1zo2GRMxa/NnOWguY2htEEtUPz+4r/jTYWfYUnOs0tsIdKKkZTN090lhkWJtgp5Kv4cW+1biQh5d2krq74iZQpyliDRmm7cy0xNpCFjahqRoGj3eokdq8Md1QSNYEu2w4V2hq+tG9gSRlPw9LrCkgKlYTwjyVuamyttbJngJwaNyMISmlBJFDCe7mIIzdO1Ao+v9bJNA66kaPeuCZGC1QCGXVj0wZZQC3rB4qc7n+KHCu9jWx5O1jXXlQTjqZ5pCMDJeszuosmip9ldgC8thHxq/f/L+8v/JyXHZFNWULY19y8m3Fw1eXZd8ZYRzUpgsOTDdYWEUAkeWoZlP8ASBiXHRGkwhODR8BRb1BTzYoW55Ci3Gnej0DypH+aN5u3MRA2qRo4dBZvT9ZBAJwQ6xhc+lrY4zeO8N3M3z3ZXOJyt8ufNz7HWPs544Q2kRIFJtYlR1+Wc18DCJCttAt0zG9til5kPuizJeU7W/rR3zF35Pd+pb+CceIaiGONY7Y96qhnvAoP5IyQ64FbzHhb0Gm3ZoKkW2K1vJCGhLTqUdIGAiJxw+Vz9P/SvzX3+lvPKA7LvaFOPPn369OnTp0+fPn369Pluph+QvcaYRppJN0ctSBhOOezLvZ9YxIxmD7FozHKrcTfjuZvIpraQs0dQOuJE7WMsygU+532RCx2PlbCXyTCEoJVEuIZEIJjr+pzsrhOLmIrcRBitkagQpSKGzF2cW/8UOXuUqfwd5J0x/HCNUnYv7WgJL1qnkt3NXvsu2qzhiByx8hljD9LIoJRH1homJmAq+wak6D3hE0JSyu5FSJvZzteY1s9xUT3JkewPoYRCItE6wTRSXEwep5DeRNqd7LkeXkFr1ZMk+tMo5b3AbW6lfRytfErZvUhh4lypzfKCBQD8sCezSznjG82kn28P3w1Xma1/hbPrf4EUBjus2xFCYmFvjPtw46NEcafX1Jmv1/OE0TJohZRmL3N2pTbqapZLK//r2TEEQ/kbyDiDG/VcGo2UKSyzjGPmrsmOXXUkbHXPsth4lI53kXJ6K168Rs4e2ci2LdQfJE4a3+IRBxl36sp2fums0Utlx65OF8Xr2NbAC7Kbr0d2DHrbP4yWX7zh9jc0hP62EX33wz6vHEP0XOkKVkLR6tm/78wG+ImBAv7vc5pICb66luJCx2Q1sCjYITPdFP/j/CAlS9GNDYZdn2dXKxydqyLQ7Cq0uNDOsuC53L+SwZKKih3T6dpcrBfwF2HhdJbr37JKelyDBK00hqWJQoMnvzTIcLZNOzbwE8m5VpovLRXoxiYn6nk2Zbtc6vSkhK5UJFrw+LqLaygsqSjnOjh2TDe0ODy+RKIF0500eatXJ5U1E7aV6mzLJsx6Fku+wBDwA5Vd5G3JbDtmxutSyR3kkjxJLCIClXCcY9SCBBMDQwi+0vjPZKwBJqiylJxmpt2r2QoSzaqveHbd43TToxEonl1PsCXkLIiVoJsI3jUWMuOZGEJz/3IegWbAgaoL66HAixUTGcGmrGDJU8x34QuLOVZ8l3PtNGU7JGvFdBPJrGcx203zbK3Aoi/ZX9Q0wt71xTXgdENzuqHImIJFH7blNAtdRdERpE3BYXk3hoCvLIR04t61qhEZTKUTTtQi8pZkzddsy0Go4Din+Puj/28GXJOMKdAIZrqCd41LTAGHKpJmJMldkUmebBrMdA0sKTgnz3OOy0RKsxaELPg+e8U2XGliapPt4ma6KqKhPN5k3cFS1GHEzLM1ZxMksL1gM2g7pIXFJquMRHC9eCNerLkuNchjnVlWmk+wt/ABRvVWzjW+wL31/8iiHzBkZvGFj9IaRxgEIuCPl3+ZgJAONbaV38to8XbGczczyi4uyzOYwuGC9yCbS+8gjNsAaBRj5kGWdQMlFDlVou5d5hiPbJxf83Ke8+JZjoqn+tmxPt9T9AOy15hSagtngzVOq1kudNus6ItY2mYtuICpLVxD0kmuWN3KEhmzimkWabHCIfFGAAYsl68mjzLne/g65Fy4Rk13OCaeRj5vl+VTWyi4E7S9C8yHz1LK7mW1e5rLzQeBXjDV9C7R6J6m0T3LkNzBLKfQ9C6ESsX4ootKOuwsvJdGOEvNv4itUzhW4YoNu6LpXSJJOoRxDYnEEBaBCDhT+wSXosfxVZNx+xC19klq7eN0/WnSds9wwXVG6frTJM8LCFxnbCMoi+J14rhOOXeAtr9AGNcwrvSWUirAtqobQUIYN9Fosqkt11yo/XCRauEmcunt2DrFmegBwqTD+fARWskieaoYRp4wbiKNDIaRucZCXuloI+jTWmEY+Y1g6vnfI400S42v0uieI5OaQkoH1xlFKY9EdV4gVXx+gKR0RDG7Bz+u0/RmWGg8ghAGlplFo7+t+iM/eum6sFfDNwZf3yk27RumMFd4rX+kXzTo69PnJQiSFjlTkzMTTrcMlIaTLYeiE2JJuGPYYciN2Z2P2F8IMYTmz2fKpIyE/YWYSAmk0Hz0dJrfO6+IlOD3LmTRume33okN3jbc4In1PBrBajfN9oEa0tJUp9poTxE3NY88Pc7yUZc4kJR3h4yXmhxbK9OMTBZ8m00ZnxvKXRZ9h6ypWPMdqk7MvCd5rmHTiWFnLr4i3zP483MTPDtX5ZOzJT5/fpyPnuy1V7ltwGO261KPLKShKdsxO3I+loRHVwSfXV3gL9r3YkjBlxr/CdvIsBZcYDgZ5wn9ADOtR/i893HW5BIX9DyHSj+OH9fJWgZvT72NRGt2FgRBAmt+QtGyGXFdyq7khkGDJ9bgaE2zNRuwFsCJpkPR0iz6PWv4sh3TjsFLYNXX2FLynxc+wb8++28Zz/SuYWOp3jm+JePxtfUcJ5tp0oZiPBVxqdMzCRl1FfVIMJgyKViaBQ/u9R8lbfZklBUH1gJByZFcbsUsdCOGnRRCwAlxikRDLRQ8vS451za4EK8ynhEIAWlDozR8X2E/H2/8Oe1IcarV5dh6RCeGSMNMF7oxzHQF59uCrVnFmUZEO9KkDMERYzcHzC3UwwgpBE3dZS3uspg0Keg8iUh4Vj/AjDzDX3X/nLpsMJa2aEaaZqipBZqUKSjaFn6SUJApDlfSnA9q5G3BpKjy3vKHAVgWs+RTE2wuvWPjjsPQJtNinkVdY1JUMYwMdblKVU8hkFTEJi7WPsuT9d9lUm1jRG1FCpNGPMOm3G1kU1uoGju4HD7O2fghVvRFnm79MWl7gLwxjIFBSRcwsCiKUSxSLzj3+vT5bqYfkPXp06dPnz59+vTp06fP60Q/IHuNMYWNQrOZnmQv1gFnoge4zrqbohrggegrrLaeYZdzFxldZKZ2H3FcxxV5lsUaJdPmRDJNUYyxKtbxhM8Mx9if7dmWrxqL5FWei92H2Ga9gUh5ZFNbyNs9S/gwbmIaaVrBAkPZAyRJB60VufRWMjrDQuspAtVmWj9HJbOdNqtU80dYU5cZsw+QtgeZi5+h48+ScYYQwtxw/kvZQ6x3zzMot3Gqey9aK7RWDBu7SUSMaeQZLtyCZZZZbx29kj3qNWR27cGNbeQFs2TT266RHabNCsX0FrRWdIMlpEwhZYowWsa4ktVKkuaVZtXxNdknw8iy1j7GuHOIE7WPYRoplIrwghV2iltZ05cwjTSlzDbiuI5WIabhbljBCyFJ2QMb8+tJFy2EML8hO2Og0Qhh4ofrKBXgB/NYZhnLLFFvn+rN70UyS7Y1QK19nHrn5MZ6mEaBMG5uDP9WeTH3wVfLN36/bQ28Jpmo1yLL9o3Ok1I6377tfp8+3yKtzhnylqLohBwqRaTNmG3ZEIBN6RhXaiyhSRsJrpGQNRMWPcWjazahkoynA5YDiw9NJfzD7RAoyQ0VuNDOMutZHCg3KLkBm9Ihw67PQLrLqZUyOhGoQHDmayXOHB/gctchUZLc1oSkpVlrpbl18zzbc21ura4x7zl8aTlD3updK/3EwJaKJQ82Z3pmEZESDDgRtdDi+lKbshMwnFLsKrT5vomeqmE1sK6YXlg8tzSAJRXt2GA01ZPuTRkDaJ1wIp7BdUYpiQla3bMsGNNonZB2hogTjz3swMTk6drvMWDvoBMnXPAbGELgSo2XKEbSJiXHINGarbles+j9JXjveIgpNDkLvKSXQRpLRWRNzaxnkzUhb8GWHGzKGfzqlvfxewf+X5yuK8YzbMgym5HFhTYIYFuxgSsVgYL1yOC5umQtgH1Fja8EVRc+WLiVv+w8wIlayCPLHjMdzWgKBlMmFdfElIKHm/O8v7AfQ4BAs7PQu3JutQbpxL2mz0+s9SSL7Qh+svoB/nT9oxQMm6G0yY48fH5OsdRVLPu9LN+peogloOL0lBprQULZNfATRU33rocrxhwAWihGnTQD5NEoNqmdWDLFBEMUbMHlbm8/holmyYtoRjFjaRvXkDRDzYRVYLod8Zw+SqQUHWrMdZ5ACoshPYlA8Im1jzAvL1DXc2R1hkHXYix/K0U1wKngPmIdUFEVhJDk0ttZk2t0ZYe2dwFDOAS6zXb3DiwcKvZWOsEKO/Qhbsz+XUrWJgpqgIvyNHXRosEiBhYl/dItYPr0+W6kf1fzGlNkhLZo0FAeF+RxNnOIsj3FRZ7mPE+ynSOknFGm9XOkVYZsagsA5+v/C58Ol+J11vQlsjpHVVcYFiX26ptINAwwiasznNKPkrJKdEULgG4wx3TtXrLWMEnSxAtm6XgXWeme3Ah6xuwDtEWLYnoLeWMYpSNKYoL59pOMi+uod8/ToUbLn8MQDkp51Dsnrwl82t4FwmiZFXWOIFphpHgbo/YB6nqOef9ZNIrl1tENa/UwXCGMVhFCIsW1PcjjxNuQ+EmZYqZ2H0rHpJyhDYmiIXuShSTpkCQdTLMIQBCtXTuvuE4ps5PF6DgCwWrzKQAK6SkiEVHzLiKFyWrzqd6NvJB4wdLGcqaccdrehWsCRKU8tI43goHnB21CWKikhbwirYzidYJwkbQ7Aby4pO75csC0OwlAJbOdOK4jhUX0LQZV3yjn+1Z5/vJJ6fT222sQTL1cUPdqAqurMlKlgp6r5HeIpLJPj++V/aHR+ImkHVl8bd1kppvmctfmqfU823MtipbClorH112kgLwVceeQYltW04glKaPXn+xcx6Zoh0igHvWCI1dq/NjAdSLSZsKS7/DE8gCbC006dZuvnRylE1lMTazz3l3TDIx1UJ5m7VKKSq7L4mqe+1cKJFpwZHCNA8WIIdcn1jDo+qTNmLeOBKSMhEVPsy3XwboSQNbC3vVvd87Djw1i1fMfXfRN1kMTjaaa8mnHBp+etXh6HWwpOK8WeXfm7aR0mtH0YRIRc2PxpxhJJtklbmHE2ceB1LuoJx7H23/FbYV/zGp4Bong5lKJIwM9O/rdRZO8LejECscQ1EPImRpLwpxnM+vZ2BKqjmJXXuEaik3p6IpsUVO2Ei5eCbZqkaQeSaZyBs+ta2a6Bgu+zReXbG6qJJxuSda9FKdaLhlTkzYU23KaQacXBNpS8+m5FmECe/QRRjM2kVaYUhBrON5soTQ8HcxwU3aUig07CiaREjQjwbKnyFuSR9frTLcTxjOSRQ8U0IrgjuxPcClZ5Uvt01xs93qJ2Ubv/DlcgdGMzaIvKToCU4KfKIJE46sYX3oULYtERzwRfpqjwf+iFcccE89QMjcxaGYYNfcxlrZZ8hRZaVF2BJ/pfIKdRRuJIGNB3jZY9Xv1chLBfrGPZ3iMi/XPMpTZh9IRq3KBVZqMF9/Exdpn2az3cUmepBkmDOpJ1o1lxlKHacbzBIRorRhwtjMbPkWDRbaU3oUXrWNgcdq7j65oYgiLgcwuvtT4T7Rkg7IapiFXmWs/wbR+DgBPNFGiLyXv871FPyDr06dPnz59+vTp06dPn9eJfkD2GiORrCTniFEsd4+TwSUhJi0rTIjruCxPkbLKLDce47HW7zHo7sIwMlSye0nrHM90/pxt+jADIk/VcRhJ2ewvZshagiV9HgAvWmen+UZC0WuobFsVNpfewUztvt4yCIvh4q2UU9swzQLby+/Ho0GXBpZM0U567nWa3hOoq5k2pSOG0ntZax/fyBbZVhXXGd34K6XDYuNRlArIyAGqaphd+jCuWUAKcyO7Vczs3siAdbxLtL0LGxJBw8jgmLmN/00jQ7VwE5HyNvqNOVZlI4Pl2MMUM7t72STpvIiELcVq8ylq7eMM5K8HIOeMcEjeSYEstpkjSnouTwO5w4grGcCrxEkX2xro9R0T1jVP+q9uB60Vbe9Cb/y4jpA2ppG7Zjmubs8XHBNX5nE1G+RaBbaU3sVC/eHeCEJ+y321Xq6R9KvNWphmkWxqimJm99+Iw9WrMdTQOsYwMhvH0XeaA9f3SobopfhO2x9/ndQjQZBIIgXroUGoYD2UJFrQSSSbC01uH+yiNKyHNjkzYW+hw3gqwjUTClbEuyeW+NxCHuuKjDBQAlNAM7KZruVRGlKGYnu+zalakadmh9hZXaMTmahEkJ+KcLfa2FNpLCtBa8HZZo4jpS6mVDR8h7GUh0JwtGGzHjj4icGDKw5+Irl9MOZYI8vnF9P8z4sWi77FY2t5jjXTnGunmL3S+HlnzqdkJww4cKKR5XTLoh0ljGcEZxsRYwwSJpq0TiGFQS2ZYV0u8lDjoz2jBjXAuFGiIFMkqoOJpGRtpuL2Mt5zHjRCTcnuvbKWZKbr89iKz6WOpJv0zquJVMi2bMTmTMClTq+p84WORagEBUvxuXnYW9DEWmMJiDU8s+6zoyAYdhVfWhRMZKBoxfzDXQuUUx4lO6ET987cY3XBgKNINPiJ4P3jOfxE4xHyV51HGE+lyV0RUVStFFlLcGd+kgFXcKkDfqKZ7Sjq4dePk325IsMpg9mOQgIPdM7ymfaDDNopqhQ5Ym/nr1rHsKTAkiAFOFLz1uEQIeB8MyJUcEbNsOJH5EyL/c4o54MapnA4bL+bu9wfJG0YeEmNbWor9ThgmxgjSHo91LKWgZ/AgLMDgK+EnyRI4GSnztH4MlnL4Kg+S8Y0CJImd+R/mjxVuuEategyj9f/G3kxjJQpBowM78ndiCEEsYhxdYbpzleZNA9xWRwD4FLtc9Q7J5lrfY2YgOHUPobVFBPpG/F1E0s7bNcHeW/5wwyoQU5FX+Hc+qdIVAdX5glVm45a3bgv6dPne4V+QPYa02SVW827aMqejXlbdIm1z4iaYoGzDOpJ8uYoKWccKR1aySJaK2LlcbTzKWyz1zhuwLFpRwnTXZ9mpFnqJmgS1vRlusEcnvBoxHN40Tp+ME+g24wUb8O2qmgSFuoPE+uAOOmQ6AiBwZJ/jDGxB1M4rLefw6OBZWZpscJw9hCmcEiIGcjt3wimbDOLZWQIo2X8YH7DDXBf6UfI6CKrcoU5OXslGPn64VTvnLxmu1hmGfeK86IQFvVOT06ZJB0S5bHceKxnj39Fpihl78e6mNlNEC7S8qfJprZsfL9h5LHMcq+B8/OCqwFjC/tKP8IYe/B1yIJYxBDmhsRtpfkEg9m91yxbGK0ipb3x/vk3lqZZ6n2PTCEQ5NLbgZ5sLoxWN2SUArERTH4jGxb6WpHP7ESpmAiPfGbnlYbNr95hUQizFzwKuSGdfDFe7U2yUh7dYOkF++/15PmyzO9kR8TvpYDke52KregmkhvKCRU7JmdqVgOY76Y5Um4w28pSTXdZCWxGUh4Zs/fAJdGCMJG9IKyT4a6hDhUnYH9RcaFt8OS6JFKCRmRxoeOSMhJcM8aRitF0FyHglut7tUPKh6QREV7q4qRjur5N2Y4YzbY5tl7iUieDl5i4RszufMxSYHGm7bI12ztOm7HBzlyXG8oRk1mDeiQZchNO1DVSQKgEX1gw6SYGXiLImT2HxZwF+8om022NcaVlxEPREzzQ+k0yusgRcTtFVeU95Z9jwZhlXpxnJe6woloMZvezJteoRRcRwGcbp7m/tsxjrWVcqamFgqksbM6muK7kMpZWGw6FzzZc/ucFTSs22Z6N+c0zmpP1XoPmQAnu+XqnFdox1EOBJSS2hEVfsqcoGXYSHEOx2kmz1MlQjwzWApjzJJHSlOyElaD3O+ZITTUluXOgzPtztzKWkfgxnGtqJrImabPXLDrRsCsPRQvGMhIvhkaY8Gx3BUPAX7aOMeAKlv2EMT2GQhGpr1/Hzq7/BdcVBbsLgs1ZONOSNCMTrcGREi/WTOpRIqVoxzFnvBp7M2UkBqd5nJPiDEJAogM8HRMR80X/z+nGCY0wpuRIEq25wdjLxWbMLda7CRWcUg/xlvwWEq253txBmGjK1mby0uFE4xOE4RJrrWeo5A6yjU3sKryXtoqY78R0k4QWazRYROkYV6VoBrNA7zqYS29nIncrm9VuBJK2bNHVNRIdYZOiLTqc0RcZMFPsM+9muHALSdLhOn2QrFFlSh+go16flit9+rxe9AOyPn369OnTp0+fPn369Hmd6AdkrzFz7SdZUHVOND/BYHo3HdFhh76eruyw1HoGgWQtPI8XzBLHdfyoTj41xX7jLgYyezhgv4NVucSTwWV81Xuq+rB3hrPRCoe4lXF2cWP+xwnxyBpVSu5mcuntLNQfpCQmyLpDZFNbmSzdjXlFmne5+WWG1RQd7xILnGW2/pXeNJ1n0Vqx2j1NnirtZIWl9lG64cpGVqLtXaDVPctA/jD5zE4AStm9mJic7t7LbPgUZ5p/RdObRUrzGge8q9mutDtJ1h3BC1cAUFdkdldlesUrWacgauBYlQ3plxAS00htjHO1uSSA8byM1mTpbqBnzlHXc5xuf44nG7/LE/5fsJScJlYhhnQp5w4gZYpWuIBh5Deml8LCD+ZJOeMImbom4xRGy9hWvmfygcYP166sW28cy8j2llW6L3o82Fb1mvcSSd4eZ6Z2Hx1/AaU8pLCuWZ5XQs9tMrridBm9/ASvEKWCDdfGq+YjrzfPl2Uq5W1IWb+TeL4hTJ/vDS51LTJmQqgki77kfWMtXCPhifUCZ9spFjtpBJozzSxn2ynOtNKcbJqsBw6WVLhGTDXdpZrvkLMSDpcC9hY1x5ouaSOhbCf4iUGl0GE47TFYaPPk3BBGVuCWElYvpjn3WJH2nMnCYp5s2mck08E2E3aX6kDP9c+LTb62brI73+bO4TW8RFB1I1zZ6z+2GpjUAo2fwHTXZCIjONsyWA8FodJc7Fj4iSRUvQyfIzXnmoonvDm+Gj/Dgl7jUu3zDOWPUFIlLokZ8jrLCc6wU2+lwjhPx5/HxOCQuA1FQsXeRqRgr9zK/vQgb630HPV+d/Ve6mGv4bQtBRdagpShcI1e1m5HweapmkmgBG8bc7l7RPHZhQYrgeTvHfst6pHguXWfryx1OFoLeDS5H0vCsKsYdRPWI4NaaPJcPcds12HEjbl1IGQqk7Cz0PvdGXQUltQ8sQYlW1MLNe1IUw97BiOHKoLZTkI3hnkPEt3LOM57cLmV8JX2JVKmJKvTlBxBQQ1gS4ElBItimdXOCepxQM6yyFiSfzTx8xhCc+HKz9umjObhFcFMF/aWDDKmYFfBZTLrkjVNJu0iQaLZK7ZxHbdyh7uXtCkRGDwTfx4Lk3HnEAOuyXLSZsVL+HjzM3SThKW4zYjrsurF/EDh3VgSLnktOnFCPQ44t/5J1lSHau4gB0s/xkTpLobMXbRVyJge45K8wMVkmTm1jiVcFIpqZi8SiW1mmCq9jW3l99Lxp5lQW5gzLlOLL3Peu5817yyxDni29vu4OoUSipW4w8ONj5KWFUaLt+NIg4IaIC/SxPpb783Zp8/fRvoB2WtMLjVGV7TZVriHSHVZ05eZMy7TFS1sM4+jHUacfdhWFcssE8Ztmt4FPBGQkRWqRpacLnF7dooabRxhMKUnearxP6jpDputMtvsCgFdRtUWptQeXLPA1vJ78GgSxh2ydpUK47gij2MPI4XDOf0448U3sdY9g2WW8cMaQbiIFCZeMMu6nqHRvUQYLVN2t1JMb99wgARIrsjqbKtKwRrntHcfN7sfpGhPkk9NsTl3O+XUNm7J/SRTxbcjhCSfmmIgfxjbyCCEJLlSx2WaJaRMbUi81tvHEEISRss9S3s0XrCAbVU3HBPXWs9QTG/eaOgcRqtE8TquM4JGkU1tYTi9nyBpMp69mdvz/5iB9E5Wmk8w7hyinN7KpHkIpTzixKeS3b2xbkpHvSbYKJKkiWN93aIfuEaKmCRX6u2ubI846QI9GeaLSQdfLHhwRPbKfjFxnVGETDGZfwPwrd3YvxIZ3ytxMxTCvGaf++EKAvFtB2ZSOht1X98qQsgNl8VrPzc3ZKNXx3s9+Mam4H2+u5nzJIaAVmRQtiOuL/kMZTsESvLpmYDjdcFvn3P43LxkxjO50BZcaBsYotf8eSDXJVKSmVYWlQgeW7PYlm9TdSL25AJOt1IINBO5NlFk4McG6WzI9WNLdOcE3prJ0F6Piakay2s5Nu+tk68EbD7SYLGVoZzvMt01udBxSbTkR7escbyRpRNa7Ct0sWXCoi+51HHwlWBTVtCJ4fMLXc42FX9ZO8+pes8p8N4Fj6fW4WJbcLFjYQrNvpLkOnuUQT3BuBzANItUxTZqssaEHqcrPA6I3o18VVfYa95FUzZpap/tYhM3mntphDGtJCJlCEZTCi8RHBC3Md1OONfy+NzaHFUXmpG8IimE+2vLHCzG1CNJ2UpoxZIfmMgz24F7cj/JogcFy2LETVFxLH6k/BYiBcuBJG0qtmUCRlM+I+5Vd8aIVmSwKe0z4iY8tmZRtBRbMzEHSpA1NRNpKNqCiTSMZ8CLoeoatCPNiUaHJ9Y6fHEhIEg0ZVdyvbOJWhCzPZthtqPI6gzdWOOagp1ynIOZ70cimA179dZ5S3CmKThYUnRicKVmR0Gwu6DxE8GOvKbkgGvA9oJFonpS0VApBiwXAfixZsq4niPmPdREg6IaYLYTUjWyzIdtrpO301UxD7f+bxZ8n6P6LA93LvHkehtbWBRtkw4+by3+cyQCKSyqukJalBjTYxzjEXzdK47L6RxZnWGLmuKtqZuYVLs5rR9hr3wTJUYpqir7Cj9EU7bwVaPXGie1n7Q9wHLjMUaKt/GE93FsnaIuG9xW+MeMqc1Msoda4rMsLtHWPt14vf+gq8/3FN/S3cv09DRB8MKnF0oppqenv+2F6tOnT58+ffr06dOnT5/vBb6lgGxqaorDhw9z/vz5az5fWVlh8+bNr8mC/W1lvfUMbXrFqCU5gSkcbJ0ip0pknWEiEbEanSNRHYay+9mafRNahbREjUYyz1k9g6TnuDRulDghTnFJTPOTox9mTp6l4BjUo4hGPEtFZghEyErzCaZbD7PinyJtD7JQf5g6S8y2HyeK1ojidVaaT7DQ+hpCSKbyd1BOb6Wc20fRmaSY6WWLKpmdlLJ7qQWXaHrTdIOFjfVqepdodk73+pD5p9nt3o1GMd34CiPWPjzdoCI2sWzMUY8ug9Y9M5CkQzdco9G9AHzdtOP5RhxaxxuGF1rHOPYwSgUoFW4sG0C9e55CahPQM3qQ0qHrT9MK5/GjdZrxPAKDETWFQDLf/Cq3Ff4x59tfwZV5uqKFECZhtExaFoGeGYcQJlHcM0dxnVG8K8XJL8o3ZGCuZsC0jl7UnOP57om2VWXcPkwtvgz0+qT5wTxJ0sTXDQTiry3T8kqyaM/PYtnWAEp5WFaFIFq7xkHw+RmpV4JSwWsiM3xRJ0qdoJLOxvJ9J5t+9PnuYbajmevCpa6BAH7y9IMEsUkzMqm6DrYBWms25wwcCZdaMbHWDLsKKTRaCfzEZDTT5dHFnqzZkAqN4COnPW4ZqDPvWzyzVqLr27hmQqOWRkpN7jqDzGiMCjVPnRhl854a9WkHZwTipmbeS5HKRdxSaXH5ihvhTz6puHVojfXAoRObfOS4ia8ET6xLPjvnca6pyZhQthzCRHOs9ke4pkABBdPiVLuJbfSMMpYDSdlW3D4Etxaq1BOP2zM/jqlNfNGhaNl4wiNjSVxhEumEM+oRdhqjrBqLZEyDdpRwSl/gAe9jPNOsU48E9UjwoP+nLAcBvg6xtUM9gj+eXcdPBBOphL8zWqVoxUymY9ZCg3YsGHUjBly4bcgmSDQDbm+dI6XJmIJa+P9n78/DLLvq+174s9YezzzUPHb1PLemlloDSGAJCwQ2gzEQY0x8Cb5OTG4cJ4+vYzu+fpzB97Vj5zVJHE+JeUNsA8ZmtgEhEEJTS61Wt3qeq6trHs487HGt949TVerWBAKBMJxPPyVVnbPP2WvvfYb92+v7+34FXiyY80xmPQvXjPGUZG++wROlBCdqBkXXZ9YzKPmalNnJ5jpVFXx+OkABBQeeWA6xpeZSQ7PsxXy+dT9NPPpsl1grHmqdxZKQsgRCwJLX+bwqyzLRqt/PTFSllyyb00nSwsWWsOwp9vfEuFIxlohZ9iVzrY7T4+VGTMpQ+LGg1wFDwHRcphZGDCVshBDUQsXpYJGcztImIBIRaZHglDhLOfY4K55i0E4zYLv8WP7/wkAwEo+xRYzQZyeYF4sc8acZt/M8Ef09DhaGsJiUk5wpfZIZMcM+7mDISmNqi6x0GHVSCASRgrP6cfyojitsni7/OYcqf0pSpSgzywCb6Te30VBLLNcO0587QKwjwqjKudYD5FWOp7y/RSIYknlMJJvVXkbtLBvsW7rKgy4/VHzb+p6dO3dyyy238MADD1xzu9ZdpzFLJAl0iwYr1IJpTpY/RknMEWufc9HDJIw8ppHBFA4r6jKFzB48GpSaZ5iNnmHYyPNMpcFkvExe9bNTbuJko8qbkge40GjhqQjHyHKMYygU+dROelLbUTqiHZZwnWHq8TyGtBEyQcIZxTCyaB0RRg3aqsxi/TBKRUxXHsQ189T8aULVxjLS1FvnyCRGOifkqyfpKXcU6BRCaxK+MzxJLrmFpM4wqDchkcy0nsILqxhmjjBu0vTmCMJF4riJ1mq1B+iFQ4c7yy6jVEcaEUYlgqv6h4JwmUrrEtDpKxLCXO/RiqIKK/UjjJs3cKj9SY7G97Ml9ybm5CS3Jd/DBrWdulpE64iEM8pk+UsASCN5zYm+58++5LF9MUfEqwvMFyObGOWS9wheWMEyktS9WVKJCbYU38pi/dir7tIXRqV1a38p7fWA6DhuXjO26NsMsV7jpVwhX4yrCy2xKvV0nWGkken00nUdDrt8Dyk4gr5VGZkpNT/f3+ljLYeSpCmwpWBz1uJoyeejs7OMpU2eKXk8uSLwlaTuOQg09cBiOOEjBSy1Egy6Hnf1FrjSTDHkRuzOV4mU5DPTRU4uFzFMRbQSsnA2RWPGZHNvGWlDcWdAXNeUp10soXno5BiXmwn+bPl+Sr7Nh/fZfGKyH1NqFnyTf74ddmRCHm5eZCThsuKHHF7unPy24pj/Y+jXKTqdC4Npy6BoJPmTpU/z9eUysYZzdYMFT1Kw4eHGR7gkz9CQVW4yt/FV/8vstUb56MLvMCeWWZLLpMw+PrH82+wVW7ni13maQ2R0gQPuO9mbyZO3NEdXAvoTOzmqH+Fw+PcsG3NMNxQbnTw9jmbB7/S1XWnblAMDX8F0C5qRQaw7Y83agnasGUpKNqQN/BhSpub+pWUeX9RkTMVS22Uk2eb/Pqr5sdEV3rOhxGQ9jS3hXLPGTNtiJTBY9iJsKfFiwVRDsytvc6wMva6k1zV4Z+ZHO/1cSjEtFmhT5XI9ouTFxFpzSl2kEcZUmWeyHrDiRdiYFG0bP4bxpMvJapOTzQpaC/7sosfJmkkrFmzKaNKm5k3DinMNk0BprjQ1K75mg1WkEvl4seZsNEc9DMnrDC3RJikczrW/BoCpLdLSJi9GiJXmdLDIUX2EZ3gSiaC0Krcf1QOc977OdFBj3NrPklwh1iGz3lEAzje+yqCToBwFTHlPUHBMLvs1RpIOn6j8L0aNvTRa5zkcP4CUCVKJiXUL/Cv6OKfKnyAp8xQze8kag9S9GVLuKAmrQECE58/SYyaZUWXKospx/RD1MORKcOh7/bbu0uVV5dsqyIQQ/OEf/iG//uu/zpvf/GY+/OEPX3Nfly5dunTp0qVLly5dunT55nxbBdnaLNi//Jf/kk996lP8xm/8Bh/84AcJguCbPPKHg5nWU+QZIE0PleapjgwwvES5fpxq6yLTlQcJggWa8QoNf460OYivG2TcEYrWJhaiBotykaONvwHAkpKtyRxerJEIvlL9fbbpGxlVm3G0Q6wjSq0L2KvOiJ4/y3LtMH6wgFKd510LbI7jGguNZ5AyQaV5inRiE35co+VdodqeZLF6EMcepFQ/BjwryWt606uPb5JJbuWpyv+g1DpH3tqARNIvcpysf46BxB7a/jRJp+OalXKHrtk3UlirodSd19DVsyVxXMOxB0mtPhag5T3bk2hb/QTh4vrfWgXEyrsmM+tKfJQobmEZaVydol+PkpMJHm3+b2YrD1HM7CVp99KX3b++Pa5zVYDNy0AI82WZSNS92fWQ7LQ9QF9yB1vcuzhf+gwZd6STLbYq6fym636FQ4g7x6UzU2gYKcKoQeolzDyu3u6Xa6Tx7eSura8LgW31AuCaufXXdZcu30tiDSOJmIlkyIJnc3tPi5pv8/ErVT7XfJSDK3X+y9z/JmkYXNHH+VL1ImnTJGsLDpcdztUy9CXb9Kda+LHk6VKbk7Ukl5sJbuvxmG5bJI2YIDao+TZvHS2xJV9FSs2nv7KR6UqWuaUc+YHOzLw5lGT5UpIgMEmZEbdunOXm/hVuN+8ibwfEWnDvYJWPXXb5/HTEVMvh89OSW9yNLHshWnfcAj9T+whzqgLAsXIbSWc2MNSKd+Xexr5snsPLIe1Y04wEc214c/af0lQrZFSBWhiRN8c4GywzkLsFnzZz8Qm26328f/DX6HENzovDmDgMrcrGR1OwEgieVI8T6DYKRb11jl1s47oeyYa0yVQTVnyBITShEvQ6EY4EpWEpMDiy4uPFcKTc6gQel9s8udJirqXodxT3DfSwtyhZ8g2OVFwiJfm96zV+ZNAMLSINfXbE+zZkKNqKjKmZCeuMpixsqcnagoW24sutw3xpZY5PNx5lsR2xELSYjss42qVXj1OKPAaSBkMJGwOLehTiiAxHOEw19hFIzgcrHPVnCBX02S4DZpp/fPQ/kJQW7VhzuRHjSM1IImDGM7Gk5oHyLL2uJG8LJGAISaA0C/oCf1f5XQ5Ff8+5+HEsJHl3AoCcLjLDEgJJMw4ZFAUm1E5G2cFR/RAp4TAfNDghjrLPvo8F40pn37NCXgyTWv2c3Zi5k0fDoxyOHyBjDxEqzfXZPJ9p3s9r3XchtWRP4afpN7dhGilS9gAZ2c9k+Uto3ZF/Tpa/RKl+jIuVLzKeupV2sIRlpDlY/3NG86+jEvkMijyX1dMkjR7OyfNUm6e/h+/oLl1efb5jS7I3velNPProo3zta1/jLW95yysxpn/QWGYPUexxpv0AbarcUPhZhJAY0kGj0TqkkN6NbQ+wVDuEaSQwcVhqHCdnjXKp+pWOY5G5gTtSP8OE0Usp9LnSbtOOFJaQvC73i3jCQ6E5GvwdeWectDNIpXmKeuvc+ljWbNEb/hypxARK+VhmsRPkaHWkiLEK8KM6CJMoqiAQ+MH8NY52/bkDGDKF6wzTk7meeuscttXP9amfYKr2MHPiPL6O2ZK5h0Xv5PrjIuVTa565puh6rib8uSfnfjBP01+4JgwYWO/zWkNKB9Ms0Jfe3XHgWy1Qys3zGNJG6ZAVfZlFMY2vY/rSexjK34FjZFmuHabmPdsnJl/Ave9bYa337cVIOKPP2zbHHqQvu59muIynaig6j6+1L673bX0rxdYrLdG7+rjEcZM4rtFsTz6vX+wFe7W+RzJlISQajR/M4/mz1FbllV26fK8xBFQjyeWWxbmGyUNLSZqRRUM22KtvJCZm3L2F6aDOHcbrmQmPUAp9DAFzbaiGBp+f7uUb831IoTEQSAH1yGDOsygFgt39K6TskI9PZTlfSzPXSHF6uo/Xjs+xd8s8W/asMHmxSGPaRAcxhcEWth1RdHyi0CBWkp/ZpAmV5OlyhiutJJGCHsfi0AqEWlNwBGNpm4GERahjfnHkA+RIszEj+JGhBDkbpIDBhE3Ji/jT+T/GNiR/U3uUB0oLfLL2BVxDUvOucKjyp0gEnu5cJLFEkg16lJ3iDqbFFSpBRDPUjLALlzTLcROJ4OEFj5mOeo7ZykMsVg9iW/0sxnWuNGFzOmbFUzQjTTPq9HYdKtmkTYUpOn1tN/fZ/O3CPBuSCfqNNHnLpt9x2JIV5KyYWAsu1jX1SLA759OKDJa8TlSJFxtYUuMYmmVf0o4FJ2uSNw0UCBR8Y7HN8UqbJ9pX2KZ34WiHpChwRJ/kce8TPFH5YypyEY3iq9X/zPmaTzNS3GBPkLVsbJ2gGS1hCYOksHi88kcM6V5GU5Kv+F/mtJrk/xj6dW7t63xP3t4nWPIlgZK0VtX0t2aGaUeap1fapC1JrBVH4rPkxTDFzF6EkFTbk1yQlxhmO6fFkY60kQVyqshXGv8TS0imjUv0iiwb5U00tY8tLHoY5RJP4+o0GkWSHFvFBkqtC+wtvI/F4BQaRcHagCuztCNFO9Zs5iYAkjrJgjqLS4qe1HYkkpqaw7Z6Waodusa5VymfycbD7Mz8GGHcYDx3J8vts5zkcS4yzT5xFwWGCXWrK0Pv8kPHt1WQ3XXXXdj2szlQu3bt4vHHHyefz3d7yLp06dKlS5cuXbp06dLlW+RlFWS1Wo1arcZnPvMZpJTrf9dqNWzb5nOf+xyVSuW7NNR/GIRRlSBcJIhqFBjmTPsBGt4cK7Wngc6sihdWCaMqAP3ODlpqhd70TiLtk3SGKZgbSJmSkzyGIQUF06bXcii6JvO6zMPNjzDNaSSCXncr7bjMSv3IugxvjbWw4ZY3RawCpHQIoxJxXEPKTr6HaSQwpPPsLJYQ6+OUq7eHcYMoruL5s1Tbk2SSW1E6wNIWw9mbmVC70Frj0aDtzQDQ9pdIWMXVWR//eTNeL4Vlpq8JA14bz9XmGwlnCNNwqfkzaK2QRmb9sY5VYKe4gwE2U9Ad+WNG9jNXeYT56kGkTJB2Btef62pZ5CtJuJq7dnWWShS3MIRFzh5Ba8VcfIJsansnkHm1yfrVvDK4djXTNPNkk1ueZ+DxQmP7no1X6+fIOrsxil2+92RT25ECHNkJUy7Ymi3pmAsNl/2JER70Ps4F8Qy75EbSwmE5bpK3Ou6wy56mFsQYQrMv5zHghFRCi225zmyNayh6nYgt6QjDUNhGzBsHPQZcn0BJ+pItFitp6mUH6cKGDWVye4EwRoWCyZUCl5spGk2Hp5aLVEODlBWRMhWHyyYLnkd/QjDXDjgRXaYaaPpcgWsI3jCcYEtasTeXZCShmG93TEuaIaQtQV/C5J2Ff9Ixf1A7mdRH6De2cVSdYyh5PW8v/gqnxFnG1U4S2mGnvo5JMUVOJtioN1CPAwwJJTFHVc9TlWUORX9H0baZbQb0iA3cUPhZ+rL7GUjvRQvFlUbIvCfZnpOUfcXFWoQCkqamEkr6XfjC8gwzLXhNbpBIwUDSohXHaN2ZjVzyTVY8Tc4WuAZkzIg+16McmORcn5wdUApMTtUspppgyY7jZDMSJA1wpUGsFVPhIb5U+U887X+W/niI2qpxVjqxiZXgPEmdZE/hvVRVm4Jj8GDwOB9f+o8Eok2vtYVZsUCMZjh/Jz2OTTnQpI1+xvQoKVOQsaBgd+Sw/Y7CiyUTqZi5Fjxen0UISJsmD3on6LVclsIznK5+Zr29YHfmrZwpfZKKXKQVrbAQtNimd/FY9Q8ZzdyKr2JSOs8h9Q2qcoUluUigQ6osUWqd42T1b7GwcbTLRT1LEHZm/WIdkaLAVP0xevU4va7JihcxYub4UuU/cSz6CiuN42RVhlhHLDVOUPNncKwCwLpR1Bp+MM9sdAxTJpgsf4kwauBFFVyd5KvV/wzAVOWr35s3c5cu30e8rDOafD5PoVD4pj8/3EQM5e8giirMqdMMJPYwkr6FQmbP+hJtfxqtPHoy15PRRRZrh2gEi0hh4YdlduptuIZgQG4DYDHsfMCfrzfpIcdg+npq4RwrcolSMLkenlz3Z6+RGhrSXv/b82dJOiPYVj+Z5FZqzTNAJ/C52Z6kP70PuFaKppSPEM7679Bx2GsHS+zNvB0HiyvlB/BFgBCCcnAJIW2EkIRRiWp7an39zy2w1sf4AoXaWoG0VlBezVpxk7R6EULirVrzr/USjaUOsMG5hYiYi9Hj2NqhplvMtA+vbl+EUm3q3ktY278M1oKqnzdO6XQkoEKuywENI8tQ5kZiHdIIFyhYG0gaPdSaZ7DMInFc+64HG79YwDJ09m286nBpGknqr1Ch+nKK8ZdEiPXjB2BbP+yfNd8Z32lY9w8rYdTEiyFjKmZbcLSkWQok5xuCgiO4w/1J7rBu57oek02ZBOc4xA1yHxXRCZXfmTdIGopqaGJJxZMlk0v1gHokqIWSViTZ37/Msbk+7p/pZyWw8GKDUEl6ik123bZCMh0gLMGJc/3ooPOZHXoGplTEWhArSd6KMAXMt10uNU3qISQME4HAlQY3ORPUQ8XBpRb7CorPzFQ535BsyXQCiTemNUlDc1tvTNYS9DiC8bTBY7U/pirLJGWek+WPERMyoMepxj7b9Va2JvL0mEm2ZBKMqFEWdZXT4hQjbpJFzydFgT6xkaROM2Jfx2W/xopq0qd6GNK9eFGVRjiPpS1GUxZnqopvLLa5qUeyI2+xO6fpczSO1GxKR/zEwDB5G2wJkdJsTMPGjM11PZK9ec3TJeh14Vw1ZEMyJG2FVAObXfka/+l4P89UsiQNRaAEfzz3+5SDjm3+kqco+Zo5VeGKMUXOGqU3eyObE3exaMxRbXfiSxJWkUgFzBlT3GBPMC0vMNsM2S9u5v2Dv8ZYPE6oPSb9x/F1xI3iVnpcyVP1Tn/Xlyu/x76CoteOGXA1nhJMNg1sqThRNehPCHI6y2K7c5zTOs+FaBGlIoSQuM4wQ9ZeZuJjbCm+lZXgPBuNmzmhHybWintyv8ROvZs+16bKPK+3X8+Z0ie5PbGFtvCxhEsxuRWl2kyGT1CTJQLRJpWYYD4+RaN1kb3mBt6U+VkOVf4UL9aMpS0eiR9if/6DJKwicdykLXzCuIEUJm1/7pr2CSkdipm9nf3ljFJpXaTansQwsmzMvZ4BZzdHGn+NYw9iaZv+7P4X/W7t0uUHlZfVPPO1r31t/XetNffddx9/9md/xsjIyCs+sC5dunTp0qVLly5dunT5QedlFWR33XXXNX8bhsGtt97Kpk2bXuQRP5z0ik04hTSeqtGnx5jUR9hm3MH5rEUQN6k1z5BObiFrDjMZPoHSIaa0CXWLwfQNGEIw3w7Za40hEQw7Sf5w+t9xW+6fEeDTCBfod3ZwsvQxerM34jrDKBXg+bOYZp44qqLRhOEKCXcM20hRa0/ihxVMI8mocwOnWufIp3bS8OfYVLiPK42Ou6JtZoji9no4stY+XljFtvqJlUc+uYmV+hGW9CWQG9mf/yBPVP6YfGonrWDpmpmwIFxczwl7LgKBRpNNTFBunAA6M0imkcQP5kk4o3j+DEKY61JF08wTxw0ss0ipeQqtAoRMQPysIYWlHS60vk4+sYFN5q08VvlDxgtvWA+5NowUcdwkCJe/4+OccEZfNERaKb+zjVfNOBZSW5iuPMho/nVoFOdLn1mfrTIMlzD67gQbO/YgfjAPrD3/C69DExNEZWyrH8+ffcWcHNdeE1cfy28Hxx5ECnN9BjWOvVdkfD+svBJh3T+MeP4MEqhHkpwtGLXgr+cWeW2+n6wFt/Sk+OryMvcl89RDg+3cTKw1jnYwBFgCtmQamIbCkIq/OXOafzl8PZ6CkURIrxNQabsMp1pkrJBKYBNrwUCijWEpJp/K0lNsosOIG25b4A8+sZX37bpMvZGgEVpMty1iXeB8w6QeCgJlULA1WUuQzFoseQrbEFhSsD0nMUSCE1X4D3sNbFnlZDXD9mwDPzaY9xwm0i0smeR03cI1BO/t/2WOB7OYwkUKCwOLRTGNIS1cnabeLhCheLz+DFu5HkMbjOlNHArOkaPYMVtqPEPSGaDX3kpGuLR0yJZMiguNFjvtH2Gn20stiNmShS/NBNw7nMCL4YZCwIZUkyPlLCGCZd+g31Eo3VEWTCoFSJTumH3Mt6E/IbCk5u5hk0akqAQOtdDgr6+keNNwwLJvUo8MFj3NL2/4Vzy0ELAxYzHb8inrJlVjhbTKkaOHpFFgTA+yoEtMpF+DIqYez/Ma+60oBa4heH/vfg4utfB1zM25NEonCL1NjFtbqIs6vbKfqUbIdreH4TDPSG4j854kZcLZGtzaozCE5EtzJgJNO4KGaHG/9zg7OEBVLoHomGZ1DJiahCmf5dphdudeQ1lcJq8znA5LzLsL7LM2MJQ0mG3GbFK7WAjavL34K7QihaUtdostXBY5rEKSfj0BCiIR0fKmCKMGw7k7CFVnpvAthV/msfA4NW+emneF3uQm5sqP0J87QEnOE6lgXeUhZQJDJojiGo7VR6V5Hsss0pfcyVT5frKJ3ewz7iaII1K4BJnbSZDlUPlPuaHws/h2bf17q0uXHwa6TRivMPnUTirMskFt70jTRJUhuYOGqGPJBBJJOrEJL1jhUvnv1ouRWvsKm/QNbFA7WI6bHFJPESnN+WAFrTuW7yVjkQvho9S9GZqqU1As1w7j+bPrBUYUVZ61lDeSRHGLSvMUw9kDneBof5pQdOSHw/Z1KOUzEm8gYRUIoyqx8hFC0pO5HugUFm1/ejXcuUbDn6c/d4CsGOTp8p/jaAchTKrN0ygdYVu91zjzrdnUP0+Kt9qrVm6cwHWGySS3AjFaq46bY2ILjjN0zQl8FFVWw61LxHETpcN1qaIQEscepE2NgeTuawKlpysP0pvpSDLjuPmyg4nXbNafi5QvfT3j6t4qIUzKzTMU0ruZqT60Xnh1evUS3zSQ+jshCBa+peWk7PTuOVauM7bvE5erq2W3a3120C0ourw6COniK5hpG5ypBsQaXpvv566+gEFXM5JQ/D87UowkApY9zc5MjtcO2PzESIE9echaGiE0H5/sZaqW4d9P7MUQcLyseHzF5rGVNMueyyenevjSfJavLjoc2DHDYL7OwnyWSEkOTw5y9lAPURXuG1lmsZzBi0xKgcUN+QazbXP9y/1yPeKJpQBDwJcrU5xr1ng4fBJDwK5swKAb85bhNkrD8WqGoh1xsZGiEloU7ZCybzPdNtmX88lbmnuGNG8sjLGbHWwuvIVQdy6MjMUTjOlBAiLSwuV6DnBJniKBw+Hw7ymqfk6GX6PmT2ObWZreHFIYnJVn2ZHJIIGd2SQTZhEv1qQtg3oI1xU7PaPjyYicFfHwUp5+J2JL2mdTyscU4MWC2RbsLpgcXolZ9mIW24oghr8qHWZLOmLYDVn0DSabDo7UHKmV+eqCTTvuuBr2OoKkqUkaBscrbZKGSV4k17fP0AbDapi8bVGTJRaDU/SoAXLGCNtzCSZSLkNJiSE023MJtqZT1EOB1jBgpUgIk+32ABfUPKfVJA94jxBrzb5snowJn5mpsi0LT5Y6R+5is4lrCOZaEVmdYkjuYEHOMt9+hpZaIWEV6c3eiG31oul8b57Uj2JIh7Ko8sbkuxlUA8z4DS7XI0wp2J1NszmVYlPWYkPaRCKIlKYql9mhr0cJxRn/azxT+ShCWOxO/xjb9A0EStEWLVKmyVA8TjsssTvxJubjUyScUSSSqfoj1FvnCMJletJ72Zp/M0KYjOVfT19yJ6O51xBGJRaaxxgr3M24tZ+SLDMtz/CI9wm26V3skhvZVHgLUkvMbzECpkuXHxS6BVmXLl26dOnSpUuXLl26vEp8xwWZEK9sQO0/dCrNU/QyzoxxmWFjNwAL6izL6iK9YhOWkWLCvY2E00fSHV+XhRVT29ibKZARLsN2hjvMmylHAUmdINaatDtAoFtUm6fZkL2Tmj/zkjM9QkjiuEk20Qn3TchOZtdN+Q/QUuWO8YbwUapNRVaxjBRah6SdIeRVgcdXy9bGCnfz2sRPEUQ1elQfW4tvZ9GYATpBz1FUIQiXiaLK84wcrpbiSems/20YKTx/lnrrHPnk1lWjjlka4QKJl2HacHv2nxFGZbL0sdA6gRCShuw4WSodUmldIpWYIOmO41h93/LzXo2UzqrLX+f/XlC6Zh9d7aZ4NYaRReuIQmo7GWuYvuzN12SfrZlUfDu8mKzw6tu/2UzXmqx0bUzN75Lr5MuVK67NtK6ZTwgE6juQPL5cxOq/l1zmquP4YmYpL3u932Vjly7fGYXUdvxYkzI1Q0mLyw3NXCumEUn6nBDX0GSsEENo3jXu8+ZhnyE3RtIRBuStmLO1LBOpmJN1l4wVsz3T5r0TPj8+0mAsESGF5vq8z0Qq5qcnyhw/P0DfTp+BwRpbbq5wy/ZZerJNqgsuSgtWPJe/vNRLxoxImhGuoZn34GPlQ1yKF9ma67j63ZYap2gkeVvmVnbmBEp3ZvqyVoBtKHrtCNeIyVsREviz8xZzns3urMexqs2S38n18mNNrDUj8QYifBySXJJnSJudWSVXGjjSQKM4yeNk7CGWjflOLmb7Ijl3jJ70TgbiMRb90wSx5nS9QcYSbM1ZtKMYxxAU7c56LKHRCM43XEINZxs2C56NJRVLgeRiPeJco4UXCwYSBgXHIGEKbAP2G3vZlG4wmmwTK1gJOu+vrHBZaseEWnBwKcSSGteAhClYocoxfY6n9SMkydGQVUwMbGHQjGKG4zH2GXfTK7LsYPOqG6WmEXay0rKWoBVpLtRC+hOSVhyzp5AgaUqkljgk6BEbqMY+y15Mjx1zz0COFV+wM9eRKX61+p9pRpoLap6U0flu8WjQm9hOI1ig1DxFOyyRT27GU1WKiS1slDexh9sZEj0EStFju9zek+ekusS871H2FY1QseJpSr4iIkYIMLDQWlNhgbwzTm/mRnrSe7nBHaHXcul1LRbUWYJYIRHUW+c4Fz7MUu0QCbtAQhYIwmVsqx/HHmSpdogLta8QhIukKJCiQCteYUvxrexN/hiNcJ5j1Y/Rp3oZ0lswjQRnxUnmojopCjRkFSGMV+9N3qXLq8DL+uZ/xzvecc2P53n8/M///PNu/2FmZ76TXN9SZQLaJHQKUzgs1g+TV3lWGie47D9Bc9XlL5XYiBAmg8ZO8nbH1tY1BLYhOKof5pI8w5WwStLooRpdYUfhJ5ltHUZrRcodv2bd1xZBnUO7XDtMX3Y/legKE+I6AHJikExyK/FqSPWZ1v0s1Q6hdYQrszTaFyk3zwPXnswnRac3wDQShCJEYjDVeAzoOPc59uA1roovJvVbc24EUHFrVa7YKZyGUzcCUGudX5dzphObSK5u6wudrA7l72DIzKB1jESyMfkahozdzPnH1pexzCTN9uS6bPPlEITLCASmkcEy8yjlo3X07FhWvziMVev959KX3o0U1rrbYt2bodK61gr45coo1xDCfF54M7w8ueGaRDGO653g8OeEdb9aZBNjq7+tyjvRL9pjJ78L8ha9+u+lMK9yAv1O+uOuWe93oY/wW+G7sQ9/ENHEDCYkCUPjx5o+VzKaMrjYNDnXsDGE5kw9xVzb5nLLYSjRJm9F3NVf5vWDK2xMt/jGosnmtEefHbPiW+TsAEtqqoHFrGdSj0xWAhNXKnIJj1t/uolwBKa75qgoSWYCpNS4ZkQjMnj3hhVSZkfSlzVjeh34xeGbeN/wMP1ux8J+c6Zz+SxS8NBC5/NoTzbgfD3F48tZFn2Tyy2HSmiyHJi8e0KjNFxqOiTNTiD2sapNwYGNaYeksNAo7kxuoxJexpaSFeoYQlCOPSbULjLGIANiM3P+MdrBEvnUTlyRY1zs45J4htusHyPWmkW5yFxLsewpPlf5PeqhohUL/nf569gSEkbMWCLgQLHBggeXW5IvzCY5VdHs7zV451jn4mXJU+tZ9VrDqXiafMLDNmLqkaBoK+qRwc29SYZTBiVf8PpBk1AJPjY3S68rmeUMu9jCDeIOkjq9fuwDHXOSsxgY+CKgYFukTIPEaiEnBDyx0qARalxD0OuamBIeCb/AVCNmstliRp/E0CbPVP6CoukynjYItWDQVWQtzXxbUgrgntwv4cWK21KjLKgqg7qHJe80CZEjVgEDmZvocbdiCJOV9nmUDsmRxhUmi7pKr2uxKWMSa83bi9tIys7vf7X0H6mFEV9qPcmx4ItYQlJQvdjCoBJeJiV7WWkco2hOUHAEOdsgiDV3mj/Cp0r/L+3VloeiPcHGwn1EKmCy8uXO/gkXieIWhfRuXKuIECbn6l/mQuNBlmuHCXSLUATsMX5k/XumLBf5EfcdXCr/HU/7n2UuPsGZ0ieZENd3L051+aHiZV3SzeVy1/z90z/906/oYLp06dKlS5cuXbp06dLlhwmhtf7+6Nz/B06tViOXy3Fv/l9xRSwQCh9TWyxEpyjVj7E//0FmOcNy8/S60YWUCcZzd1KPFhg293IgsQEBPNw+y6nyJ9hTeC8CybHyRztmIc1TbCm+lfl2Z+Yn64yy3DyNIW3CuLHurmhb/Qgh8YP5dYe923L/jBQux3mMpOxh0TtJrAJi1WlY7sgNenGswnp+iJQJtPZx7EHy7gaSsgeHJEmd4anK/wA6s1drwY+21b++bWuzY1FU7YQ6P2emwbEHCaMyQjj0pXeTlD0seMdptS8jjeS6M9/Vz381QpgU0jtJGj00oyUmrFtoiTrT7UM025PAs46Ka9uiVLsjKxSyM5smk6sh2YmXlA26zjApu59ae4owKiGF9bxtunpda6QSE0hh0eNsoqUqLFYPApBJbr0mo+Xb5epZt++E79T98LtFJ4cufvYYCgtppJ4XVg2d19sr4Zz57bLmGno1ttVPFFdBq1fkOHX5/sA08/zKhv+LXkez4AkC1ZkNCZWmaEMjEuzJhWxKN1EILKmo+DabeypIoYkiydlSASk0Pa7PZCOFKxUjqSaTjTTvOPT7fOGWX2R3/wpSKppthw37qghLMHs0xaGFXvYWKwSxgVp9yR0p5dlbqHG8kiFndYKnT9Yc6mHHqCJUcL6maEeKLTmTXqcTQDyWiIi1wDE0htAs+yahhn4nZsEz6LFjSqFBLRQ0I8Gxks9oykYI+F8rH+Md2XdxxlshQ4qMYXFEHUcRIrFY9E5SdDczU3v0ms/G7cV3klM99JChTINxs8CFaJFx2cd8XOOGTA+9rmChrbiuAAeXNfcMaq60DVqRINawIaX45FSLm3vSDCY0gerM3gF8ZdZjX9FFaUiZcEM+YDDRRgrNAwt5kobmRFXwUPMcGkVZXeHfjN5DORBMNRQbM4LzNcW851OlQU1U6FF9FI0kKdOgxzEIlKYVaSwpeNA7wrsLN5K3NZcbcKnRJmvZzAcNRpw0zSgm1ppD6hu0ohK15hn+Ud+vsilrYkuNJeEL82V6jRSx1uzvdbl/sURZLhOINq+x93LIv8RmMcoFPU1MSFldwZZp+vQ4gQg64dPxIFVZZkQPYQmJIQT7e22OrkQoNPU4ZF4sUtZXaEZLbDZvZ5YzbNT7WDRmcHSSZXWRotxAQfVyRZ5hv7yJomPy5fZByv4k+6x7edr/LC1vivHCGzoO0cJhoXUCy0xRa55hKH8Hc5VH1o93MbOXPms7bV0lTQ85VUQi2eTmOO+V8WSbQd1DhOb+yu8BsKvwHiQGZ+p/3zVv6vIPHA3EVKtVstnnZ+teTXc++BXGFpJBNcS8d5yF6BRbjNu5rvB+WqLOXOUbBOEi2dR2ACwzR0tVyJgDbGCIx9uXmGp5CCRjhbu55D3CXHyCW/M/j2kkSLrjzDSfotm+xGBiL35cIwgXMY0EUtgI6a6emC5imxluKPwsUVxnV+E9zMtJhBA0ggXmWkdotC8ihCSKm6TdIYbzdxJGJeqtc+vyOa1DtFaEUYM+uYXZ1mHO17/Cipgmm9qOECZKR89at0t7fT+k3SGCcPl5J6K21U/CGWU8fRsJZ4j+zF5q/gwFPYAXlBjI3YoQFqnEBIX0bqR84b4srSOqrYt4qkbC7OHp8p+zGJwijBrry2Tc8askDx2pTyoxsS45XHNoVKrd6RZat+t11l0mk+44SbuHlfoRwqjUKV6I10++1x7zQsHXzfYkabufy5UHCONnx1Vvnbsm9PLFes9eiDV5omGk1vftc+WOL7eXqeP06DzbN/h9IhOJ49o1+1Xp8AWLMeBVLcbghSWiQbiIUn63GPsBQwqbRqSZbMKAq5lIaTamYm7tCbix0Ob1/U125GpsHCphSYVEM5ppoGLRKbACmy2FCqGSBLHkcNnmcMXh4aUC5xo2vzD6KxScgMVaily/R19fnbmTacpnLdIZj309ZU6Wc5ypZujJtPBikwVf0o5M2rEkY0ZcaDj02IqJVMyKDxuSijv6Bft7TUaTmryliDXMeCZbs01qocSLJUt+p6qZapk0I0E9MtiW9uh3OlLCrTmb/oTAEPCe/Lsp+xE73F5a2ifWmoIe4HL5y+ToI2EVmakdJI6b9GSuZ2fhXYwX3kBa5VAoToijnFdPsBx63JweZkPG4r6BHvYVNHtzAa/pUwwnQt40rFgJDLZnQu7obZO3NQlD8c7xJIMJzXQLDi5G1ELB1+cDxtMun6w8w/laSMYCQ2gOrmR5ppLFkvD/TH2GfXnNPZmt3OJs5Sez93CpAQLNlqzAiwWGEBzoTbIr0csmxtmazBEqRdY22JCGsZSgx5WkLcF+Yy/VQJOzNAkTFinjGoKvVz/M9pzBctzksH6cW+Sd3O28HdvqpxXHuIYmVIJaCHvSefK2yQUm+dpihZvznf7prWorC55HSV8hUDGuTrKVjQzJHYyorbREnQYr3GRuoyCTXG9N0NAenoqIdUduWoo82nFEQpiYmNxq3IYpE+x0+rlZ3sYFnsLRSULhd3rBRBsHi3Zc5ivepzjVrGBg0Q6WWDCusD1xN33Z/Zg4zNYeY7p+kJHUTaSsXtKJTVgiyabCW5go3MuW4lvZYtzOhJrgejrtCFmRJC1cMpak38hwKXicc/IcgQ55be6fc1vunzEfneB4+S9etfd4ly6vBt8fZ15dunTp0qVLly5dunTp8kNItyB7hTmvp5kxrjDm3MTb0m8loR1MbbIYnyWZ2LDu2mYYWfxgnk3iBnr1OE+orxMT0tI+BhYmDjmnY2TxdOvTBHGTljeFaSRAGEzWvs5K/Qj9uQOr2R+LWGaObGKc8cIbaAdLSN1xWrRw6NEjnBPHSdsDjKRu4obCzyKFyYHMzwIgkZ3/Sgetw3VZ3lD+Dsazr+F0/Qt4/ixhVGLJO0OjPYkQFi1val3upq8KHC7VO7JKIcz1zDFgfUYv0j6b3Ney0jzHWPIWLkaPM5C5nnL7EvvT78GQDnVvhii+VkporJooZFPbMWSCrDHMfK0jBaw0z1zjwldpnlo3SFCr+WqNVses5Gr3PCkT64YRjj24PqthW/14wRLO6jots4jWEZnkVvpzBzrbfJUBw9UzUwlnlGJmLwurZilrBiVrXB14+a3MoKyNN+kMdNargvX9sdYcveZG6NgvHMb9os8t5Oqs4Vo22qtjKtGlyz8E1mTZ+/KKQTdia9onZ8VsyjRoRAalwKIdmfieyZaJZYTQxFrw0OwAS9U0CStEa4EC9uxY4LW9bXZnA3ZkPG7It9mcgcFsg/GBCqfO9PPE+RGE1DjJiKVSmqeWijhSsyHV4vxyES8yCFVnhidvxdQjEyEgaSgCJRhPQdJU7Mk12ZYJuCHfIGFoXtPb4MfHFmlHJmlT8bUFSdHWVALBgBMzlIg5Whb4SnK+IXnLSMCXqhfZkQnZm+9I+4ZTNufaFR6p/lcOxg+R1Ek0Go8mK41j6yqEWnuKueAY9XAWVycYkUVK3gUEkqS02JiGZyoNMib4SnCuYbEh1eZyy+Zi0yRlKgyhmW7b9DmKffkaW9NtLjdgutGRBKZMzc68zeVGR+Z3XdFiLBFiSYUlIW0qSr7gA71v43PTHpcbAZPtOmVfkbUE002NIeDB5RKjKUkj1KRMQdYyURrG0y7bsrDgwYCrqAWaoiMouib7e9RquLPg5vQwt/UJfm3zb1AOYMBMM8x2hlM2KdPgjemf5YYeB9eAbyxXmGkqnm4u0Y4USZ1hxEnzeHWJmp5nXqyQMEwkkkPqQQpkOcYxLgWPY2Jwg7UFUziUg4ANaYeEKdiZymMJyZ6Cw5lqjCUMQq0YSlq4KkHClKSNfiKlCVRMqNr4okVGFTCFQ1ENkjMcLJkkaw2RFi71eB7XKtJUy5xs/j1LtUMseidRyiebGCOl8yw1TpCwOnLENdnq+dJnGJEFytSZyNhcZ26iplvkTItj9Qqx1lxnvoGJeDP7CzlG7Y4xli3TDOXv+L5Ra3Tp8r3gVX21P/TQQ/zYj/0Yw8PDCCH49Kc/fc39Wmt+4zd+g6GhIRKJBPfccw/nzl3be1MqlXjve99LNpsln8/zgQ98gEajcc0yzzzzDK997WtxXZexsTF+53d+53lj+eu//mt27NiB67rs3buXv/u7v/u2tumydxBf15EYpC2BgcHTtb/ElVlutt/GnsJPY8kElplmS/GtNESdp6r/g7TsYyk+zxV5lmPlj7ISXGChfoSMMYhtZsjZowzn76TH2UQ+tZ3RTKcgaK6G/vZkrqeY3Iwf1WlE8/SlO5b72dR2FIpnmp8hJiJUbXrVEEmVouXPYWJQqh9jpvoQUibpzVxPPrUT0+xIJlaaZ6jH8+vFhhQWQVjrFC2rfVdrH5pXSxbX6BQx6hqJnmW4XK4+QFlfIQgXOVP6JNXWecrti8TKw9UuEkkUVWh5U6QSE5hmftXKv/MFH0ZNUs4AtXh23bVRyuQ1kjbDyHZCK6XTcYDEQKNJJSaukZgp1SbhjAKdQimT3Eq1dR5D2mjlrevh49XtTVsD2OJaR7qO5O9Z6WHbn6bSOI1+gWLrW3Gze15swOp4/bB6zd9r++Pq8YVR9UWf94Vs3L+dAuy5sshXyvL9e0H3S77Ld4IQkn4XKqFECqiEJs2o47S6Md3k1pEFto6skEiFrCykiLXkkYUetmaaLLQTfOryIB85P4jWArtHMN22ebLkYAjN4ysJbiw0KDcS+J7JpuESva7HV6YG+frpMc5XcgRKooCUHTLbdsjYITfkfSypGE54FO2AZgStWDKcCLmtp0otlCTMiK25OoWE1ynenICFZpIz9QT1SJI0Ba6h8WJBnxOSNhU7c5pASe7q8/irSZP/tG2Yx1dMlBbMteBEvcKedJ6xwt3cZtxFTda4Nf/zuKS4O/shJgr3AnBT+l3cbr2FXcbrGbEy7Mzb3GK/lY3yJnodm1DB7myafidiQzJgSzpiwesEOCcNOFaRnGvYXGkZnK1LDNmxwR9OwmjaYCBpUfIFF2sR1xeTtGPFiXLEStBxrDxZFRwqmVxuxPS78NqBBLf12ewv5BhLG1hS48WajKnZlcqz4msGEmBIGEkZjKY6wdGGAAHUI8lAQuJKzUQKztUNDi17NCON1pqUoVhsK85U29zYY3FPcZC/rn6O08Eiva5FM9I0I0FKODSjGICZsM4Z/2tIBAMyx2a9jwkxQMYy2Kz3kTEGKVHBFknemnkHvUaK88EKEoN+16G92tPmx5qsZVPpXLMjKU2S0iJlCobMLIu+T5Y+DsWnOCGOco97H9v1VmY4ybnSpwBYjpuEqoWnalyQ52j6izTaF5mvPErWHWV78Z1knKF1l0VL20hh4sg0vm4worbikmZX4T0oNGmd5Hi1wULQ5qj/eT7f+Asuy9NcZIqvVz9MTTTJWB2XyiviJK7M0i+2EMX17/Xbu0uXV41X9cyk2Wxy3XXX8d/+2397wft/53d+hw9/+MP80R/9EQcPHiSVSnHvvffied76Mu9973s5ceIE999/P5///Od56KGH+Lmf+7n1+2u1Gj/6oz/Khg0beOqpp/jd3/1dfvM3f5M/+ZM/WV/m0Ucf5R/9o3/EBz7wAZ5++mne9ra38ba3vY3jx49/9za+S5cuXbp06dKlS5cuP/R837gsCiH41Kc+xdve9jagMzs2PDzMv/pX/4p//a//NQDVapWBgQE+8pGP8J73vIdTp06xa9cunnzySfbv3w/AF7/4Re677z6mp6cZHh7mv//3/86v/dqvMT8/j213ZnB+5Vd+hU9/+tOcPn0agHe/+900m00+//nPr4/n1ltv5frrr+eP/uiPvqXxr7ksFtL72GTexgIXuFneymLcYNmYx9YJelQPPgFH/c+vuxTNN54mCJe5J/dLHNUPYckkXlzGMbI0gkUsw6XSOM2mwn24Os3x8l9gmUVMI0khsYlQtUgZPSQp0KbGVO3r60YIt+Z/nscrf4SUCZLOEBlnCFO4LDZPYBruuiRSIpmuPIgUFpsK9zHXPrruVLhGMbN3XYZomUVcu4cgqqNUQKya67K5pDtOazVY2DBSOFYPw8kbWPBO0vIXMKRNEC4zmLuN+epj16zDsQcxDZeCM4Et0jTUEjXvCkoFKB2tz35d7YoohGQkdyeztcdw7QFa3hRSOqTcceqtc9hWL6aR7Mg9zTxRVCGVmMALSlhmujMLphV5d4LZykMdcw9pYxqZ5xlFdGatDEwjeY2D5drYr5YhrpFNbafRnrxGViilfc2yz3Xou9ox8JVyUnwhvpPnFsJECOsad8oXcprs0uUHkf+4/d+yIdkJUDaExlOStBkzkGzx+FKB1w0tobTgTDnPobLDRCrGkZqUGRMqwZZMAyE048NllpYyfPZKP1lT0+eE9LsBC55DK5KMJn12jy6ysJKhEVik7ZBGYPF0OcPGlE+f62EIja8MDpcy5CzVCXUWmt39KxiGIghMLleyHCyluLOvxuVmkkeWOrLG1/RFLPoGu7NtLjRcjpYlu/MaXwn67IiVwGBPrk01NNmcrdMILP56Kst4Cg4tK3bkJc+UInK2QTWICZUmZRp4sSJlSU55yzxR+WPe3ferlEKfzGrA8XjaYrbZedylZgtbGGzJumzLahY9yflaxA09Bp+eLbMrlWc8LThZjtldMCjamuFESNqMaUUGfzVpMJA0eKpS4bZinj4XWhGUV2eIxlNgCY2nOkHYc204WFnhvoEevFjQ42h+Z+YrRNrnQwNvoR5q8jZsz0QcXDH56+rjALwnfyvVQLO3ACcrgqmmz4pqcHuhh1jDcluxNSeZbmp25wVHSprBpCC1mt/2uzN/y9szb2ey1eSKMUla53ltZpTZZkTKkix6PkOJjjvk0/4V+nUvG5IJzjcbZKWDLTszsttyFtVA83BjmsnwCfrtnbw5s5Pfv/zveGvx/+YZfYyb5HUcVE+wV9+IIw1aKsJAsECJkpijqIeIRMSw7mM85bLkRdzf/hsG3T2cL3+G0fzr2aR2c0I/jBQWjkwjkASqQdW7QsYdwYsqZK0hpisPsrFwHzEhtkiS0UV2WkNc9msksPEJKRpJAD5f/e/0pHeyXDsMwJ3ZX8ARJo8Gn+FtmXcRKc1s0OCiPEE7LlOqH+uaInX5B84PgMvipUuXmJ+f55577lm/LZfLceDAAR57rHMi/9hjj5HP59eLMYB77rkHKSUHDx5cX+bOO+9cL8YA7r33Xs6cOUO5XF5f5ur1rC2ztp4Xwvd9arXaNT8AfeZ2XJ1guvIgF/UcDVnH0g59qpfz4ggNWccPO0VBoBoE4TKpxAQ10TmRVTpkt3wdsY5otC9Rqh/juvxPc770GU7Xv8D24jtJOQO0/WlC1UIIgzG1jQ16FIEkn9yK6wyzs/AuImKEkOSSm7DNFH5c40r5ASwjScIqMld9mEa4wGLzJKnEBD2Z67hU/QrJFwh0tuWz4ZhhVKLlL+AH88SqjWnkkMJCINaLMeg4D2qtsLSz+neNMFzBNPOEz7GZX5M0NtuTRNpnrnWEZvBsARdFFWyr0xt1dRGgtaIdV1DKp+VNkUluRSmfeuscmeRWgnCZIKohpbNe0HUklw1sM4MUFq6VI1ANbKsXjV6VQHbeGmvrfHZ7fPxgHsNIXVOwvVAxBlBrnlntXzOxrX7CqPS8ZZ/r0GeufnmtvR6ey8txZXwpvpMvOq0jLPPaXMLnFmMvJI/8dniltrdLl1eKS3XNWLLNoysufQkPpWEg2eKBuR7yVszvnRjgSj1D1gq53Ig5tNL5PMmYEdtzdTKujyE1lVKSJxZ76LMV5UDwwILNgufwZMnCU4JGZFCtJjhWylEJbPryDS43kwRKsODZJKyIK80UXmRw9/ASKTNm1rOoRyZxLPnkuTEmKzmakcloIma0UKPXCbl7MODeQZ8eO2A0EXK2nmBPvsGWLGxNt5lrQ86KmWoJDKFoRZKpeppmZLEx3ekW3pTtyDQdQ1ILFY9Gj2FJwdFwilAr/n/z/4F5cZFb8z+PF8ekpcV42mIwYfHx6lc5FU/z0ZX/yY8Mpnj9kEs1UHx1LqLsa5pRzFwLbswW2JAWWAJ2Fwxco2PX34wMjlQSLPgdqfSTlTKjdoaTFZ8zVc2luqYdaZ6uVJFAJRQseSBFZ9n3jxd5dLHNpXrE0ZLi34zew09k7uOLS4vIVVmi0p1i7t7EAe6yb6ERQtYWOFLjGjCeckjhUgs0aVOwIWNwZCXksfYlFjyBFOAagrNVxbIHCbOHC60aA3YCT9e4zhkh1nBGTaM0POR/kuPtJc60S9ybHydn2DzevsTWVJoV1SRQioQpsaTmRK1Bjyqww7iLCTWBELC1+HYu6lkSZPli6+PcKPbT1D5f8f6m47yoI3opIJBMqaNIJBnT4mSjSqw1OXuEC+XPk0tuxxVZLohnaPqLtMMSE2oXK9455quPsTH5GkzhEER1hDCwrV4mK18kSz+L/mnGRT/ngxVCEbIkV3ii/dcsqConOM3G3OuptC6xI/8T3JL7ADExV8Q0Y85NLPo+p6M5mqKNgcly7fD3ZRxLly7fLb5vC7L5+c5J68DAwDW3DwwMrN83Pz9Pf/+1BgamaVIsFq9Z5oWe4+p1vNgya/e/EL/9279NLpdb/xkbG3u5m9ilS5cuXbp06dKlS5cfcr5vC7Lvd/7Nv/k3VKvV9Z8rV64AcLbyt4QiZLzwBiSSlqhxvPwXtOlI1pb1RSCm2Z4kITvGGc32JG3RImEUGJDbaIkWkWqRS24l4YxSFyVel/tFbku9j3J8hbQ1wM7Cu9gmbmVM7OEMTzAtFtist2MbKcKoSoMV5jmHEA5SWJTqxyjVj5FKTKwGQndc9SyZwDRcmu1JwrhJHDdphyWS7jjpxKbnbbeUCRLOKLaZRYiOK6NrFxjI3QLCWF8ulZggm9qOa+Wo6BnGnJtwnWGSiQ0o5bNSPwI8O4viB/Nk3OHOLJJq4wcLNNuT10gn19zN1gw41vCuMvIIomebgC3DZSh/B2OZ27Gtns5tZpFCaiumkafeOkejfYFy4xSuzJJPbl6V3dXWr8yF4dL689lWP6bRmRXqzJZ1lrnasORF0fE1z/VShFED1xl+8Rmml2Go0ZEWfnfe5msN1y82zhfK5nq5dLLunj+TJxDr4eNX860YpnTp8p0ghKTsx9iGImNqbCMm0pKUHeArKAUmNxUV7VgSack/2hCwPQcpM2bJtzm8kqcdWpytZomVZN43OFmTXGpohhIwkmzz2l6fZiQ7OVW+Q68TsjFbJwhMbugt4RqaP7y8jCE0N40ssHtskXZoduSQaY9bhxeoth3evmmG6zfPsa1QYXOmyUI1jSkUx6o2n52xacUGX5ixSJud8GqAVmxgCIGnJAlDUAlsHl4yeXjZ5b+dMRlOREw14bHlJose7CtKTkSX2aD3IIRglzmG1vC+gV9jo9pJhhSu0THemG5E/OH0v+Nu+3WM6UF+buAD/M+lZ7AErPghScOgEigKtkUt1JyqNbnc0PzZ0jM4Rid0e8mXVEPJsg9/O9XJPxsyMzwcHWRvwaXgCHbmBUVHclM+x5IvuFTv5MU1I9FRqSjBeyZs3j6muL1PECq4rgA/M9rL9oxiOKHImDFFK8Y2BP0Jycl6nVYEZ+uShNn5zNucTlINYhqR5sNzf8WWnMUOOU4z0hxtz1HyNSlLMt+OuVHcysZElqXAI0MfC57HpbrHdjlKypK8xnknCkVFLlMNNNf1mPxIZhONULElkWNXwabH6Ugi7xlMM+QmaMg6De1xvNJmMB6lR/Vwsvwxtrp3sRw3ebz9CfZYb2DATKPQKDST1QdIG/1ciY9SCn0WjTkm9Twb9B5259+DbWa5XH8ET9XwglkG3T20RIuWN01v9kYkBrv0foqJLSRFgeH0TezIv5N+1U+teYbPlP4/7Ev2sdPtpSVq9Kd2My8uIZAU1SCj6Vs4Wf4YT7c+jUQQCp+yvoJCM6/PcrTxN0Cn/aFLlx8mvm+t0QYHOye5CwsLDA0Nrd++sLDA9ddfv77M4uLiNY+LoohSqbT++MHBQRYWFq5ZZu3vb7bM2v0vhOM4OI7zvNvH83dTlStILamLEkU1iGGkqMhlethAmVn60vsoyg0UVC/l1E6qrXNoFFPl+/FyB3BlFiksklYPBXsj1WiGkr7YCVjkeiSCGhXSwiWLi5K7mI6PkZIpav4M49m7iAnRdNybSo2OOUkxs5dIBavFV+ekv+7NrhcKCoVt9dJoXwRYL8iEkNT8mc4yqo0XzKK1wjCyxHGNphcSRk0sM78aJF2i2Z5krHA3BiYxEWdqn1uXtJlmHqXaOPYgWkfr0r/l2mHyqZ1UWhfJJrdQaZ7CMotEcQW0RqOxzCJJu5cobq0XGl5QWt//VxcfpfoxpHTIJbdgSJu+7H7KrfNUWheYyN5FJbqCISxaUYnpyoMk3XFU3Opsp+4U0FcXFabhXiPJFMJE6wg/mEdKZ91a/4VcC79ZcWIYqwWuMLHN7PoxuJq151bPkXu+lKxD6+gVLcgss9gJyEasH8/nbptt9RJGlVdEbvJiz6HRBOHy8/rgnrtvunR5pXHsQfKOgSNjBl1F1XfIWyEnVopszwSMJlsIAcPFGg9fHmJvsULaivjsTJqfmih1gpxbSZZ9k7lGihE3YqphUnQkeVvhGhFLfprbe6scKmXJWTZzno0lU6hGCi82uLW3zJ2DgmZoETcENKCYbnN7rkm16ZItegShwZVyFquaRgrNbMtlwPVxzRhDwKaMoBaabMsJNmeaxErQa1sESjKeVIRKcFtPG19J3jzs04olGotzq9e8JALXgGoguOQ9wlDiOu7MXMfJis+mrM1cK6YhmqyIaSaXvsRY4W526Ot538CvcdKfJxABmfYY/7h3H+fqUFVtDuQdtqYjTtctaoHm3uGO22zW3sepiuZMq8yBfIHzoeDLtYsMMchAwiRtCfqD25ltxWzPSZqRoB13pIUFW/P0is/ZukvZj3ln3zjNCObaBr2OQdLQDDgxs57BoBuTMDS2VHxiyuK2PsHj9Vnuyg1zczGDAI6XPV4/5PLESotJeRGJgV/fzNsy78KWgpTV6fVK6xSOAaYAaXf66rK24Do3RbGxkb6ESdmPWQp8EqFkJOGSCSxG04Ocr/lMNhXjSZextEGsIWVC1upIRGdams81/pYfcd+KFuCrmF4jxZyqMFG4F48my3KKN6R+hlArtIZeM9EpylSbLXonX2s9SjN1K5Z2uBw8wZi9HxOTfrmFofQOYiKW9WEW/JNY9g3kklsZNHbSpMzT6gQTxk24cYKzepJBuZFhJ8lN+Q8wQJGveyewtMNM+yluct6Kg8WsnEWhGFEbSRXex4q+zNPhl8jLcQws5sUiKdHLgmoiscg6I9d833bp8oPO9+0M2caNGxkcHOSBBx5Yv61Wq3Hw4EFuu+02AG677TYqlQpPPfXU+jJf/epXUUpx4MCB9WUeeughwvDZk7b777+f7du3UygU1pe5ej1ry6ytp0uXLl26dOnSpUuXLl2+G7yqBVmj0eDIkSMcOXIE6Bh5HDlyhKmpKYQQ/OIv/iL//t//ez772c9y7NgxfuZnfobh4eF1J8adO3fyxje+kQ9+8IM88cQTPPLII3zoQx/iPe95D8PDwwD81E/9FLZt84EPfIATJ07w8Y9/nD/4gz/gl37pl9bH8S/+xb/gi1/8Ir/3e7/H6dOn+c3f/E0OHTrEhz70oZe9TWNqK021TK/uXPXJkWZX9h3MBEdpikrnSlD1MRqscKj9SYbt6xAIZsIjpBObWKx2zEjKzU6A8VTt6+wVr2WjcQsNUSWhHVztYuHQ0j6zYokKCwwbuynLZcKoxUzjEKFusdB4BqXaDGRvJpvaTtHaRKM9xWDuNrRWpJ1BgnCRbcWfoC+7n0brIiDXJXBrszRaK1re1Hoo83rYclynL3sz+eRWcu4YQbjMlsw9pBObSCc2sdw6Q0tVKHuXgGfljGsZaraZIeOO4jrDbCq8BQAvqhLHNSwjRcIZJYxKaK3QaKR0iOM65eYZorhCrALCcOWaLC7Pn13/vS+7n5Q7Tjss4wVLWDJJxh3BMtOEukWpeZZANQijJr3ZG4ni1nqIdRw3r5HimWZ+/WqdbfVjmUUsM79+v1I+hpF93uzYixlSOPbgetaYYWTJuCNEUWXVhKTxgo/5dgObv9Og56slkULITrbbVcYjV2OZRYJw+XvWjP2dGJNI+fwZ7h8kXilTlS7XYkibtNXZtwu+xBCKpysJkkbM5mydnlSbTWMrWHbM/oFljpXylHyb23sDElaEKRS2jNnfU2Xec6lFBoHSZCzNdEtwoZ5hb6FGKzLJWZ1AZAmcqScYSjeJteDri0UWm0lGeqokrBBDaKbKOTK9HovNJHEoWGikGEg3GcrXudRIkTZjYi2Yb7vUQggVWFKzPR0QK0E9tNierVO0Q7ZnWvQ6IQKY9yxKgcmxqs3ubMxsG87XfG7uSfIHM3/Kv7/wW8QqYLPaSslXfN3/LMttxeH4FDmdRaF4d9+v0ss458RxAqXZnxpalTZqSj58uXmcCTfL3lxAxowZScTszClCBfVQsC8fsz0nuLVQoOjAZCNkn7WB3bkk082QB0oLmBKe8M/RigTnaxHTjQjXEFxqwLacy/9Y+hg7c5KyD4Ou4uZiSMbU1EJBqAVPLUdoLWjHglJgcu+QYskX3J4ZRgjwIshYsDHjEitwhMHt9i5uMrfRUhHbcpJaoBlLGVyqByzKeS7XI1oxhEojEZQ8xaV6SM42OFtvcSKcoUqDj5f+mKe8KxhSsOIp9ve63FhMkrEEGavj0rjYhkoAftx5PRyw3swFNceUWuKCvEQ9DrC0RSWYYkiNsEffwGDC5qK8QMKUeCrGkZKdhXdhIbkv838SCJ8e1UPeHqesrzCjTuJol6nwEL5oMZy/k5a/wJT3BK6ZxxctUhTYb9zDiphmyMxQaV3E0TbNKOZC+CjL1CiofpI6gxcssTmRo892SeoMw6JIQzZosMKtxu0kzSLzjacZ07s4Vv4otk5wX+5fsByco/kcl+MuXX7QeVUli4cOHeL1r3/9+t9rRdL73/9+PvKRj/DLv/zLNJtNfu7nfo5KpcJrXvMavvjFL+K67vpj/uIv/oIPfehD3H333Ugp+Ymf+Ak+/OEPr9+fy+X48pe/zC/8wi9w00030dvby2/8xm9ck1V2++2385d/+Zf8+q//Or/6q7/K1q1b+fSnP82ePXte9jZ5ImBM76JHpvG1x6HoiwD02Ju5VP0acVxDCouF5jGy7ignyx8DIG9toCqusKvwHnbJjZzM9jAfneCmzE9zRU5yl7ubL7cPcmdmK5cabQZ1Hz4RS/oS87WDKOWzvfhOgnAR1xkm1hFpd4icdTOR9qk1zzBu7yfhDJAzRlhQT6K1IpPciq0TLNUOIRDrfVovxFrhYxhZxrK3UY8WWGkc5+bM+xBaMpLfhaUtpoVBj7OJZrxCtX2ZMFy5pu/JFC621U8UtxFC4vmztBMbOx/+4RJh1KDUPMVI9nYWUetF1pp1PKsn4Wvjyaa2U29dIOWO0+/uwhAWFyp/R7l1nhvT7yYUActMoXVM3trAfPgMAqNTBKkAKTuOTlIm0FphmnmksJHSJAjLKNVGCrsjtYyb6/vIMovP2z9rxctaQXJ1wbCmiW95U/hBJ2w7lZggCGsM2XupNE8BvOQxANblkS+9TOJlyfcE4gX7tTq3G2gdrTtLphObXtTePoxKL3j7dwuBwDBz1wSCf6t8s334ssfyInLVV4tXoofv+53nRkZ8L7BkAluCFxvcUmyhtOC2ngaG0DQCi0yi87oyLIVpdoqyatuhHZnMNtLsHFpCGhoVCyq+Td4SDLsGhtCEulPoLbVdDldcxhIxSTNiwTe4s6/K8HCN/p4Ge2sulZbLqbk+br9zFgRs1FXCKmTsznu4J+FxpZYlYUZsyTT4+7kCm1IRKTNmXy7io5dCtmdMQi043+g4N15sOuQsxaWmQaQFPbbi307+DT9VeCeG0FRdScYS7Ck4SAHv6/0n+LFmxmtxRhzDaV3P9ea9zPttdhnbeEocZLr8INlCPzlVoFfsIVaaSqCohQFlGvSpPnKqF9cQSGDBt2jFkgt1uKkYIwFfCQYcBUg2piIu1k2kgBsKMTcUJN9Y7CNlCmwStGNN1jawJTyy1CTUMXf0Zvm1sfewO+czkjBRwIZUkz7H5GApzY3FCpBHCI0jNdNtg6Ml2JDu2Nt/3f8sB6w3Y8gEGatz3e61Aw4rfse5MeklqIXgmpCxNFuyNuPxdmqh4kKjRUO32ZYoMOt5hDrmSXWMUb2dzcYQEsE7Nv1THlrwsISg4EjmWorb+xTfWJTcVFQcqxoUHMFUQ+HHHbfFWbHAsr7Ibn2AcfqwLMFyqNlivQalNREaQ0CsQywpWNRVHvUeZa98PU18Bq00raiOQNKrx2mJOpPeozztHyab3IKr03iixmjmAPu4nnNcIsRnsxilL2HhNbdTSBjcmnovKeEQakXaGuBs+BCtYIXR9C0U0zvx485nYknMUdBZxkQ/hjYpRR63yDs5n97AhJlnofAWTpY/RiL/AV5j/Thfa//V9/R93aXLq82rWpC97nWv46Vi0IQQ/NZv/Ra/9Vu/9aLLFItF/vIv//Il17Nv3z6+8Y1vvOQyP/mTP8lP/uRPvvSAu3Tp0qVLly5dunTp0uUV5Pu2h+wfKnVRYUFOEWtFQie5zngDg9ZuNqsdGNJlonAvpllACpOl2iGMVWlePZ4nbQ4yokdoxiFbxQbust5MVa5wu72Lih/zzuyteJHG1xHnxGkcYWKLBMPZ2xgr3M2Z0iexrX6CsMxi9SAT1i0Euk07rjCUv4PT9S/Q9udo6TKDuQOkzD6G3evQKHqzN9KXu+Vb2saMO0KOQYrWRq7PvAdDm1wWxxmgyHH/y8TKx9cd2Z1lJNHE67M12dR2avE8aXeAkdRNKBWSSkwwXz3IcvM0G+xbKKa2MZ69i7I/iW1mgGfdHV/I0bDpTa8GLltYwiXULfKpbexPv4eSnMdVCXbpGwBoqzJtfxpNTMOfwwvKhFEng0ypNlImiKIK2cQolpHCNDIIYRKEi8RxA9vuw1yVKhpGZ6b2atMMraMXlOutycfSzhBSJujN3ogQFgPuHvZk3spMcPRb2veWWbxmZkcKC8PIPk8a+XLNLTqWKR0TGNcZRgiTbGo7CXdsfX1rs2JrUtbnOhquSVqfy5o089vl6pnItedy7EESziipxMYXnR37Ttf7YryYScr30+zYDwuvxixgpXmKaqBZ8lweXk5yrp7imWqKP7+YJlSSetvBa1pMXinSu6XNwfk+ZpopDKERaE7P9dJsOOTGAvaNL5C1O5LD8UwDL5Z8YabzXj5QbDHgBlxspFj0YLhQ49TFPpL9EX5oMtRT49ZbZ0BAsKwxCiaNRRsvMhBCs9J2WfYtrjQTnKllGEnE7OspE2vBVMtkazZBnxMQa0HaVGxI+iSNzhi3pCNuzPtcaAj+48afoOzHKODTV1qkTM3RUpvztYin2jOc81cYsBNIOuNOCgshBIYQrLTPM5p/HeN6mEVjhk2pBD2uwaPRQSq6haUtPtt4lDHZw0hKEmqBJTQSzY+PtIm1wJKa8w2JpwSOhJFEm58c9/nHm5pUQoOiHbEnL5hIKV6fHediLeRP5/6AJ2pLbE0nua0nS9nXTKQiZto2jqHZlmlyqJTjYiPJPQNlYi1JGoo/uVTDloqkodmWk1yoRewpOPxU4Z30Ow55WzCUgBW/86Pp5JVdVwBHdtwam5HAloJLDR+lIS0ttiUKGKty+LPiMI1wnrRIsBQ1GUqa5G3NvSMuQymJJWF/j+Z0zeS+4ZBGJGmGnfw1S4JtCB70jjCmBwniJl+p/j79CZO5sIEhJCmdQKOYFlc43qhQ0APECg5k+rnZuJdxN8OMcRkJZHQBX3gcrn6EQLSRqyqJujfDsfJHma58nQm1k5RpsJWNbFZb6XMtPrr8Z9yQz3G0tYSDxePxF5EITOEw4OxmIL2Xi+XPs0HeQKw1X/I+xwFzHzsySRoqIK1THI3vZ1aXuNHajBCw39jL+wd/jaRO0ufajKRu+p6/t7t0eTXpFmSvMFU9yxtTNxChSWiHhDAZUiM08ZDSZK55lCBcpO1PIxBI4dD2p2n489giiSMMXGmSMU0GkhZ3J3fSn+i4Nt1fm6QaRPgE3Grtw5UGk+UvsdQ6zXT5qwgEu9NvZnP+jUhh4WiHPrGRlfoRIuWTT27izsw/peRdoFdsYrr6EIqYE+W/xBQOtkh8S458BXsjxyp/yXA8xrjsY05Osl/cRok6QdRgOHkDI+yi19hEo30Rsdo/5jrD5O1xYuWzwdzPSLyBRvsilkygdcTGzJ0kdIKU0YMpHAxhkrM7FvdKtYniVqfP6znEqzJC20jh6zqzjacYNHfTL3JE2sPBpkydQLcZFXvYWLiPZe8cAkkUV4ni+rrTY8rtrK9gbkAISRAuImWnX0rriA2p24miCn3Z/Xj+7LcsU1vruVqsHmRD7vXkzTH6M9cDcCU+iheUX7CAWDsea8WPY+WvuV/pENcudv7vdPomv1274DXnzIRVQOuIWvMMflh50eXXir61YtN8gb4yw0g9u9zqtrxc18c1GaRlFrHNAkKYRHELKU2a7Uvr63kuLyar/E4RL9IXaFu93zXb/R+0cOwXK95fKsLh+wlTCh5bcdidDTCEZsCJ+MDmOpeanRDnaj3B1p3LGDmDH9kyzcm6Q6AM/sNJwf0LaYava+KXJdMLeTb2lzlZd7CNGC+W9LiC4zWXM/UEB0sJGpHkpyZKOG7Eddct8LXHxxnfXqHn+hhrPEFrWpDYnSBaCVksZxjOdi6GHa+mO/1nAlqxpNeOmK6nudKymEhFbM6ARpAyYlJGTCs2yFgxaVMhBXhKcveAjyU1rTjGNcASkukmbM8lyNoGhjZZkQv81dJ/ZLvewbyuUKLON9p/hSkEP5Z5H7ebt9HvOtxh7+ZP536XmVbAiN7KZqeARPC29O0c6LPIWppl31xdt2A03SBtKv5qUhHEHcv7Hjtmpt3ZLznHpxZCLTT51EyVRb8jeZxSS+zJvh1LW3yq8VU+X77E9lxHWjiR9OlzAnKuzx39JW7tX+FcPUMtsBl0fX59R4KEofjklSYPLbaYDCoApC3YkpWkzE6xuL8YMZHSpE2YrEf4ShBr2JbRNCNNrDU39zrc0COZ1Atcbjcp+xEzYoa8GKbcOMHB8PMMmGlGU/Dl2QhDdGIPDvRE9DkRt/X4nK7bzHmdIi1vaz7XfIB6GFPUQwwnHd6d+zFel/tFWpHm+myer9b/lM3JLE3R5oCzjQQ2d+WGsQ3BdDNkLOlyJJhis9rKcugTE9FghXRyE9VohlgFQEd+79iDjOReQ0jE2XABUwq2ZRKESvNPhz5IxdfERPTZLgeMeznPZWrRLNV4hgG9ifHCG9jrDiGE4M3JH2ciY+KakDcdfALKjRO8vjDIcEpSCyOmojI9jqQgkyx5AVP1x7rW911+qOgWZF26dOnSpUuXLl26dOnyKtEtyF5hat4ModJcEGfISJcITc5w6JMZXp/4KYrJzSScjrPgaOFH1q/++8EiedXPnF5hTlVoRjGXG20ON5aohzCWNrk9uYEzepJYxASxphp3jDzSziBbim8jldhIhQUcnQRh0hRNFtRZthffSbl1nlLjFDExXlCiziL9mRvxdI2h/GtJyh4C3aYve/NLBh0LYRLho9GsyBWqsU+OPiKtqIkKUVTmQvlzLIpJyuoKhfTudaOIjDNM2Z8kafbg0eSSPMXGwn3UvSmEMIkJ8YWPKVwaahHXzKN1zHjhDQBo1DWOis8bG5KpylcpJrdi4VBTPrv0PjQKX3iYwiEUATONQyTtPiwzjWP1AXI9cy2KO7M59XieWvPMqoHFs+tsqmWEMKn7s/RkrifpjmNb/d/0dRHHzfWrj5OVL9NSZVyZZa51BOgYebzQzMu6o+XqLNNz88mEMNdnT9ZmD7+d7JarZ68iFWBb/Tj24DXb/s0CoP1g/nn3ddwqjWu2RVzluPlSMz/PXV8YlQiiMu7quJrtyfV1f7dmw16IFzIDkTLRyUX7Ljk3fidukt+PvNj7+HvlzvmdIIRJI1RMpBSBknxuWnO5ZTHXdhlyAzamW/QUGxw5NkS01JEBv3F4hd5Em3+7W3HvYB3la7SCzVuWSWRD3rlxjqVWkq2ZJnmrM5uz6EtakWDIDQlig3rNJfJgLN3koSfH8KZidD0gNQG6HdGek5Q8B9uOiCPJgBvSjAxGkm3Gkz45O+R8w+X2vioZM+a6XJM/Oedwqu5w/4JLPTTwYsmZhs1Uy+R8w2TFt3hoAd40YtHvwherv89jzWkSqwYcl9XTSAwMI8WsWKItWizLOQSS4/ElPrH82/hKEahOBtc7i79EqBVTnEQIuCmf4yMrH6MVC8YSITkr5pOXFbsyPo3AwhCaG3tssrZgwInZmG7jSsXr+hpcqmXYX/AYcAN+YUuKViSwDTAw2W4Ms8HJ8nr7LgBShqIdCxZ8iyXfZrGZJGUHrLRdhhMep2oJvNhg2beoRybvGEvxlpEkZ9WjPLRcpmjDdFNjCSgFgjnPZLYtaUTwukGDwysxJys+nhKcqwYU7Y68MNbwE32jDNhJhIBLrYcZ0SMA9Ds7sKRgoQ1Zy+RSQ7DiC76xaFIJTCLdcYN8esXHNmDRg3dk7iFjGUwYvdRDxVTTJyQiUJr/Pvdf+Knef86pVondbj8zXpvLxiVaMZxsL1OPA040S1wOnuBh/5McUV/HwGSD2kbK6mWpdoi2P00muXVV2RDQJzbiiTZPVf4HpcjjciPgSruFJSFQillO04pjWjogp4psMm5FoThc/QieqhFrTdaSHA9meXBlmalGTNYycbDZWLgPL4JPVY8Ta8V1qV5mWp37+12HdxU+SBR7r9K7vEuX7z1Cv5SrRpdvmVqtRi6XAwxuyv8T+ikgEJR1k9Px19ls3s7t2UG+Vp/kWPmjACScURJ2gYa3QBAuUszsxRAOrzHvIW0ZuIbAizuSE9cQLLYjzuhJ+lQ/U/I8mphAt5mvPclI7nZ6Gefp8p9jW/1sTr+OU+VPMJy/k4X6EbT2ySY2Eao2A+4e5tvPUHQ3UQ1mMKVNtXWegex+dupb+Frtv6yfGNlWL7EKrjmBsq1+RtO3MKQmKMgkLRWyIkscq36Czfk3suSfptI8tSpLipHCoS+9h3owR8ufZUvuTZwpfZKh/B2sNM+sh0kbRpaR7AFa8QpeWKHRvohhpBjLvgZLJDlX+tSL7n8hTGyrl02pO5nyniDrjLBF34iFyVnxNEIYuCLLZO3rpN0hyo0T1zy+mNlLOygTq4BcYpyl2qHnrWPNuTDpjtNaLSK1jthafPv6Nr8UrjOM58+yq/AeanoeV+Y643GG8KLqupvky3WO69jthy/aN2YYqW+5YLGtfnKJcSLVft4+eiVxnWG0Vi9YxD2XtfBnxx4kjKoIIa/ZnrXj8HK2E17efrmalzo+r4br3yvFP+Sxv1J8qxLkjYX7+L3Ne5ls2eQtxZAbkLcDxopVALJ9Hu2KTbNpk0oFLFdS1AObI+UM94wsMF3LsLW/RDrvUyu5DNwU0Lqo+Z9PbmZr2mc42Wa2lWDe61yw6LEjxlMtJobKSEORmtDoUGPkTLSn8OYUT50cYd/EPE9eGKbX9WiEFv2pFrGSPL5UYNgN8ZVgKOHxkYsZbu7RVELJkBtjSc2ib5AzFa1Y4hqdYOjRRMBfXba5sUfyyekKN+XzLLcV036TXjPBYXWMDD1IJEmVYsBMU4o8es0EsdakTIOj4RQ7jVESpmSyXecMT3KduIMyda5L9rHQDjGl4PWDJmPJkMstm2YEe3M+lcBkJTCohp1gZEtCrx2TMWNasaQaGtQiwRuHV/jGQpFDKzCakquW/h1b//k2FGxBpDUjCc2GZEiP45M0I54u5xh2A07WXebaUPE1W7KCeiiYSMVMtw0+tXyZMQbYkHaYSMOlOgwnYboFX2+e4a2F7VQCeKQ5yR2pCSZSEGo4uOSzPedwR2/Aw0s2BytlFIor4iQ3y1uZUWUS2mHESXNd0cCL4fBKwPs3waxnYQqoR4L5Nqx4HRlkpDQJU5K1Bc9UGljCwJUGp7lATMg2tY1j4jBb1T5mjCvkVA8NUWWvuQkJfMX/Mg1/nuvdH2fZmMPSDvdktvKN+jRPl/8cw0gxlLmZkneRtj+LZeZx7R5+1H0HgVJsydqs+AqBoOR3LhI9GHyaWvMMPZnrUTokjNvst3+cnOFwkrPcau3CjxXlKOBQ9EXutN9CJW6zIldYiM/w5uQbaceKhCFphDFTcQlDG/xIby+/ffG3f+AuRnX5YUMDMdVqlWz2haX6a3RnyLp06dKlS5cuXbp06dLlVaJbkL3CFDPXY2CySJl+12FbosB287XssPtphJpB3c9w/k62F99JX3InpfoxUk4ft+T/TwzhIIRBS0X4sWLRCykHIbUgphVpcrbJsBqmx0zSp8fo0aPMVh5CSgeBZE6dJp/aybb0Gzhd/mv25z+IKRxuSf80ueQWIuVTdDczoMYZSd7EdOVBht3rGLVupD9zIyPsoiFa5FYlC7bVSxAuo1SLnsz169K8IFykGk1TkotcYYFJeY6zrQfYlXsHGkXeHqc/d4CMO0IcN5HSZrbyEK6ZI46bLIfnuSP3IYbZwWj6VhwrTya5lUJqCwvNY2ySN7PH+VH6cwfoS+9jTG0j1C0Gc7etG1dcLWfLJLeidUQU16noGbxgiWF2UJYlyrJCybtIL+PEOkRKGz+qP++4tYMyGkUUV1mqHWKscDepxARJd3xdztfJI7PIOiNkklsZzB1AIAh160WNKq6Wf67NgF3xn6IVr3C+9BmiqIJtZgmvCoNem6V4MYOD58r84riG8SJmEq4z/C3NAkmZQAgTISTV9hS19pXn3P/KSvGCsPySs2NXH9+1K6R+MI9S7Wu2x7b612dzX+5s13OXt63el/X4F+If8gzTqz327wfjkm9ldkwIk0E1waJvoTQU7Yh2LJluJfj61DCleoqwZZAsBPQONXHTIT25JpsGS7x54wxRbLBjaJlTC73YRU3LswFo1y1uzDfJWSG1wEZrwYakz5s2zmBJTagkvmeyspymOSlAQbQUEZYU05fz3LhtFhULMlZI0g6JteCZlQIPzhfpsSN6XJ9mZHBwJcud/YqCHXOsrJj1DKqhxBTgGopPXmmTNhWaTibYhrTBkifYm8nTCDXNKMYSBl9ofJQJtZXNcgiAK/IMp9Uky3KJ6bhMPQ5YCDwGVB8LYZNZz6PHTLKDA0jgSPNvqAYxoykbUwj6nJhQCXKm4k1DZYp2QN6OVqV7mryl6LVjLrcMBhNtNqWbpE3FjoxPEBsU7ZjhpCRraY6VPY6s+Cy2YXdOkzY7r+1qKDCEZqadoBWZnK5J8k7AWCLkjt6AG4qQNDQHV5pMtw3ylqagChRsi7If04wEGzMdKWG/K9gtN9PvQqw0GxgiUpql1eDpG3tcZpsx7dig4EAoQvakitxi3MpJznNdso8b8jkuBiXKAcRacEOPw1TLphkJpluSvKWwpWA8Lcnbks81PkasNf/fy/8OQ0iS0uRJ9Rg3Gtu4ydhNxrIwMOmzE4zFHUOMTYxTCQN6XYMt4haud38cG5Mb5A72mptohJoR+thTeC/F1E6ksBhM7GNb4W0IYeKaeZaiJqYUzLdjrrRbNMKYtGWwpOrcab+VnYV3MWTuptw4QcHdyLRxiSfVY4zEG9AaHEMyJS9zt/Pj9LsWKeEwood4rXUP/2vxd3kqPkGPK9iQMdli93Bjtgf4wZNqd+nyUnQLslcYW6aIidjlDBIoxQPeI2yyi9TCCC9WaK0pijEMbZKlU+BUmmfoJctmuZ9ItTgpnmYqKnNMn6CsWszHNY4Hs8x4bU6KQwRKUZLzHK78T1xnmCiqsNw+Q8YYpM/ZwdnG/Wwu/jhNUSVLPxW5TBi3ca08XlxFIulRA/Rl95NWOfIqjy3TLIspYiIM6TCUuRkp7VUJT0TOHGU4fQMJp+NCuFI/woXGVzlW/QSBbpBPbOB862tcqn6FqepDGMJ8Nug4WGA0/zpcI8dY4W5sI0VNVpnjHBE+QdQgZfViyQSGtKnKFQ5W/4SdHEChuCxPU48WaEUlxOpL9uqTx7Td3+lBi5vMVx4ljpucCx9mLjrBicYX2JC4lanoaRQhSbsH9QJ9Kl4wiyFt0okJipm9VPwpmu1JlI6u6n0SKB3SikrknXEckaY3exNXag9TbXV6u57r9pewCs9zlGu0LxCt9pNlkluptC69YE/Ni/XTiBcovuLnyBXXjtNaEfjNUKq9Kk/1Vi3+a8+5/5UJUV7bF2sRAy/GCxUHV+9bgVjt23rpEO2Xw1qP3zfj1S5cvp94JaMFvhcnXy/WB/ly0Dpis1PAEJqMqZFAwlDc1L/MnWNz2EZMaSWFtKFecrDSmnrDxU7EmKbCNGK0FuzoX8ZbkuQybYL5GMNU/PTJw/Qn2yx4NidrNlsKFTIFn825Gmk7ZL6SoeHbXJrp4fiTfVw8XqC5ZDE6VmVuJsf0Qp6twyt8da6Xv5hMUAoM8pbiYtPmXC3FiZpB2lQ0Ikkjktw7pNicCqhHkr25BkMJn5/daJM0YvqciFgLkoZmtqVoRZodOYGvYgqmzTvz72dJLiMR9OoijWiemp5nKjjE4eYnuSBP82DjzzmiH+SkfpSj+mFKkceMcZkV6tyVej+R1sy1Qm7pM3GNTk9e3o4o+Q7t2CRpxKRNzXAiwBRwrmEykohZ8FyOVzPc1FuiHhrUAwtfCRqRxovhdYMO1/c4HKwvMu9JxpMRWasjYzxadbCl4uNTGWINF+tJLjQs0mbMMxXBf507zQ2FJF6sWfYF1+cz9LkSiSBSYAiY9yQZSzOcMok1eLGm37UZTkr25hReLNiTC9maMymHne+sIZmnHWm+3PoEy+F5TjYrABja5CuleS7WYibrilNVTTPqSCznPcmJsk8t1Hyq/g1e67yDR4LjvG/g1+i1HMqxx0a9j0oYMB3UCGJFml5SpqRoOQyKPEprJlIuK35MKEJ2JjsxIn0JE601zUgRakVG5dgobyLULS7XHmI5PM9Aai85Y5iHav+VI+o4DwYPk5QWT6mjXPI7ET+uNJjynqBK5wKbicNIvIHXmHewPZ1GoUmagh9N7eSMmsaSAikEOdPCNSSD2QPcZu1hxdM8Ua6Qtw0aoaIZ6e9aT26XLt+PdAuyLl26dOnSpUuXLl26dHmV6BZkrzCamCJ5qkHEQ8GjvDXzWhphjCkF42mDSeP/z96fR8t1nued6O/79lS75qozT5hBAARAgCAozoNESdRky4Oc2LIsO7bl+MZOlp107PjGye1Oum86yXXi7iRedtuOLFtSFFm2RIkSRZGURIqDSAIkQEwEARwcHJx5qLlqz993/yjgCCDBySZFyqrfWmctoGpX7aH29O73+Z7nDNB1Wzpa/QxXl36adGqcaTFHSqe4w/ogZcZ5tvMlDGHRkk0iEXE6eBRfd12PlNacqX6F9aX34gdz2FY/abufQLfIqzLF9EbmvcOcqH6eFTXJef8AI+4eVhrPYEqH56L7ec7/GhvldRxq/iXjdg4vqZJjkDHRT6V5mEY0jx/MrUnZZlrfZdk/ScoqMF68E4AorpGyB5ipfRsApULKmR1sKr6X+dpja0/PhbQJtcf56kO04yUW6k9ypPoXdKJlqsEUY9n9LNSfYKV1gtH0tZysfIE78v+EjHBYqj/JXvZxtbwNL1imz90CQMbdQCm7E9vqp9I5g9YxxcwOEAKBoNE+CXTllTPBs9Q6k4S6a1Tx4q6RbfUjhEXbmyJOPDrhKm1vinRq3do26P62GtMs0mifZKb6TcbUVlrBAlsK72c4fz3wUhlcrX2CJGlcJmkUwqLZ6e4HXrjczTp7HXKti92ri5JGKayXGHqk7f5L1u2Vs50uvh+EC1cMWX61rsLryRVL2eW1eb5aePWL53vpttXo1x1+/Wpc+ju93qy0N4o3ooPz/eT76W75RvBGdjdtqdmc9TGEZizTwTQVHd9GAYmSLJ3NYpqK6kyKc408zaqDaSU8u9xHteliOwnfeX6C/FiIs87CdhOevHMDSx2Xm8cW+fub52kFDpNTfYxP1Fm/vko57XGwUiBRgrTd7SgeOT9IY9XBNmMGCi2OzQxybbHFO4cUJ+qCybbBjX0t0qbiulLEvC/59oLia7OQsxJOtWwMAZGS/K9HBLXIYCmwWA5MNmZ8lnx40H+SIFH024pZscR4xuRQOM2N7nqeVE9hIbnOeC8r3guMOLtJ2X0IJO/IfJSt4kaGjG14UYWmaJLWeSxtcUacZDFuMZS2yJmaqbZNpARTbZsD1TTTHYdF3yYlNSebDk+sdG1nAL4+73BNsUHKiSjZMeuLDbxE8o5yTDsWnGvBiq/5xYkBtuciVkOD/SWPlAEpA2Y8C61hd0FRiwxcE2Y6DsOu4KN9O5hpJxhCsOgpBlNQcuDJ+DheopntdB0Pl3wwBZxpwlhG4ieK+Y5iwZcs+hJDaB5fbrExHdKMYGPOZi7oUEpt5FcGfpT3DJaRwJ39ZVbFLGeCKg8Hz1CwBbWw2+lb8mDItZDAbdbNPNT+825+Z5RQcAwsYRCJiHNihrRw6KiYET3McW+FWGuWdB1TdE1Ono1Os9kawJJwVSZP0RacSGbYlDNZEqvkRZrzHGVYXMUd2V8iZw6RocQutqG1YrJ6LyNs5cnkm7SSJeqygiEsFuMWOXuEQLXoz++jyBAVWaUeR8x2QvxEMdX2+WLzO2yVY8x3ImwpmY6rnA+aDIiNtOOEeztf4/pikZTRDdseTkHW3fCGHa89erzd6RVkbzAFMcqsmMWWkk6yylw7Im+ZxErTjuBM5csUVInt6fd0x5KJDVxjfwCA9W6GR6Kvs0mMsCf9YdYnG+lTZSIRonTEkjHPgOrj4eAvuTH/q7gUkNLBsUqkjT6WOyd4tv7nNP3uOKq+3F4W6k/ghStIDIYLNxEpj4I9hmPmWBGzbCrchZ8oHJkFoKOirmOhkUFKB9PIMVy4gThpM5i6mm3mbczUvs1E6S76ctcw5O4CYKl5CMcqsdw4wOnKPZSyO9fGNZWzOzFFV3qgVIzWMYOFG6h3TtHyzjLdeLhrs24VaSVdCdqSXMC8cFNcVR1m5dm1wsEyywymrqbefgEhTFyrxHjxTpr+LBPFuyjldnUt2y/I7Lpj1xrM1R6hnNv9EhnExVBoAC+Y6wY+S3vNPj5lD2CaRVxnnDiurbnRtWQT03BJ6QwLjSe7wcBXKKyksC6ELmcQCFL20Joc8WIBlHJGXve+JoS15kD4Yvy1wkq+qpX4q76PRgrrZQu71zLu5iIXt0+3UHzl089bERKstUIKC3nhePi+z/+HSA75VhW9bwT7+iVjbsh4tsVVpRq2keA4MWFicK6RY6qRQ2tYqmZ57PwIe9YtcK5S5KmzoxhC87WZAaTUXDe2iApA5mxaNRulumOcAAbWtzCkYrDY4oHn1tNYdSgPtvmRq86zYbhKf6nN2FidTmKw0shgmopn5wcZzbZYDhwm0j7XlRVpEzJmxPmORT0ysAT8j+X/LxlTMp7ucEt/i1sHaphSc1wcYH06xE8kuwotEi2IFPzKwI2YUpAxE651JggUZHSGmY7Pbr2Pr9X+Iw81/oDb3J9hs9rIHvO97Dd2o1AkIqFfDQCghGJVn+OJxh+xWW/j+mKJvSVNye4GUjdjQTOGjZmY1VBysGpStGPmOtCfknxy5SkKVsKNfQlBYqCVQGlBEJm0YoEUsDmbUHIE67OwKeMz55vsK7U42Uwx4YasT0f4ieBsK+C5mmQpkAw5MSmjK8uUAiwpiJRmxY+Z78B0S/OR4u6u3XsCR+stljzF6UZINUgIE9hRNNiYE7gmtGKNJTSWkARK8FB1jowp2J7LkhJ5cpZmwdMYEu6pnOEX+q/j+kIfG9U2ijZ4sWa6FbHoxYxlJN9oTNKOE67JfJgFY45q4vOl5oNUadAUVUqqn4fbn+IFcZwz4iTfrf0hoVKMGkUinVALY8bUOE/Hz5ExBWfabQwBx+qfJ9aaOst0dEBJTHCs9VUaokW/XscNzlVUkg53F/8Xriv+EiOiDy+qdK/zrQfpU0NIBAVjjJIxgdIRJVVkQg+TMUyqqkMziWjoDrdYN1OJfb4dfoV2EpPSKVqyRV7lyZgG18p30klACIiVRgiwXkHW3qPH3zV+cK+IPXr06NGjR48ePXr06PEDTq8ge4OJRcQ2sYHn1TRR4jOrqoxnJVvyNtPtkFsLv87h8Gs81/g8I2wlZUgSkVBngUaYcLv1PgwheKr2RwghaIgWaZVh3N3P1WzhKE+w3/5RFuQUNi4pe4hm5xTT1QfYkn4njj2EY+YYzO1lnXktW8s/zlBuL5Z2KBhjbBU3MlP7Np1wldn2AerJHJN6nuvljWwRY5yRz+OmxlhpPIOULhlngKIYQ+uASHeIiBgv3klalKi0jpEii2HkSZI2w6ldZNwNuM44TX8Wy+x2GSrNI9T8KVxnnDBpY1v9mMLhmuLPsqX0I4zkrifjDDDi7mGh/gTDhZt4ofl1Ap1wW+Efc5KnaCRzZJyuPDLjdKUUY8XbcawCflxno95NIb2ePINUmkcIwgWy1hBZdxN1b4odpb/HYOEGWv4iWoUXnCnFmkRMqYD+/L61blHe3UDW3UTW3YRtZIjjGlHSopzbvdbFmIkPs8G5EV+0USogjusoHWGZ5QuulF3ZoNIRQkhcewiNJopba+6LQpiMFG+5YpjzlToIl3b3tPKxrL4r7od+WLnQdSy87n34Sl0+paO1bfO36Wx44TKGkScIF17SWXtxR+xKnb8XS/pebAzyRnRdlI5eIgvt8cbzejqrbzeGnRhTKBbaaVY9Fy8yefb8EKfqOTYVGpzrOHx+coTNOyvcuXkGlUj6XY+NhQZZM+H9Yys0GykKQz7SAv9Em7lqno5v0+f69K/vENQNDq8WWW1keP+NU/Rv9fGaFk4mZqWaYXapgDQ067NtzrczOE7MtSNLzLWyTGQ61CKLlKHYkI5wrJjhVEwrlqQM+JNr/iXjGUk7tujEBikzJlKSr+69hpwVcUN/FUNoqqHJoAtDKcWuUleGt6PYtVbale4n0gpTSH609Nvsy3+MnGFR1W3KRpoDyRFm5SmO+veRFhYZq58xBhhlGzfkP0GdFjOtmKm24DNnFbVIMt0RvFBXBIngnYM1bhsIiVRXwrcxk/BbY9dzqmVTtGOeqWapdFyuKtWYauRoxYJTLZMXmt3ldCRkzBgN1EKb/eUmz9UdTrcsHKm5ccBhPAM393VYDgw6iaRsQ9HSbMpJzrUSfmTCWAt4TpuajAnHGi3+/roMu0qSO0dsbh2UbMtrEi0oWppzLbi/cZJqZPCxjTaznsX7+sYIL3R93pvZRdHStCOFKQTb5ToyJgSJJiVMGhGUHMED3l9x25DBvcvzvDO7if6UxVX2APVkloLhsF/exqgoc5XYSL+R4f25X+I6uYdd7OQn+v4FacMAYEfB5Zg+jRCCXewk1uAR4CWa31z3W5yuR2zT2+mIDmN6jH2ZnwBgRUzTihI2p/MMpxyOdr4KwIi7h3JuNz9e/BWWxAyBCLG1i61dpLD4TvtTLFJhNe7QJzM8WP/PHIsfIkwU690MP5r9MXKGhS98xhhgwZjhVLDKgO1woLXAsAu7ywZHKgpN8hYd4T16fP/pFWRvMKa28FVMQsQdzo+T1WlO1iLONEO+Uvt95o1pdtvv46r8B5njeebCFseC+9kvridjGjSTEIXGtvqZEeextEVJZNimN9OfMtkg9jAtT9NMFlAoxtLXrd34axQldxOm4bKe3USEpHSWULWo6VlO1+/Dlx6jxdsZyuymnN6MI7Oc8b/DaT3L83qSs9WvoVTMSPEW4rhGJ1xlMT7BhuL7sEWWlqwT64COruI6IwgkWgfcWPxVCqofQzp4wQxJ0iCKW+Qz21A6opzaxNXu3XT8aTZn30WfWI9CUY3PUQ2mqLVP4Og0UlhUOmeQwuY5nqAlWyzVn8SLKmvbuOFNUmeBxdYRBp3tbEzfSiQiUkaJBktkLujOU7LAQGo7N6R/BhuXTrhMFK+AEKwr3IlGk8tctfa9rlECYLhwE0JIoqRDy5uk3n6+u321oh0sk3JGKWV3Um2fYCr4LjNeN0T6YgERxRUqzcOYRrpbFNnDCGGRqBAhTAwjhWuVsK3+bsQAFpZZfsm+5NjD3cJRyG5B54yjdbJWMGk0ppG64n6YJA3CaIlm59TL7qtSOkjpvmTea0VpZtsVl+tKN9IXLfPhlcdBxXHtJQ6OF4vMS6WTQsiXFluXBBdL6eLYw6TsgVddtr8Nrybn/EHhlX6T7+e4tbeDtf3flnxmG43YIGUmNGMTPzZ4arXIRK7Fxmwb14n44KYZfv3OUwgTAt+k1ugWbRIYyXQY7Gsy28hx5PgQQV1Sm00x0V/nicV+WqHFH35zK3Ym4e4d02zcvIpXMQgrguxgiN8yOVEtAhAHAttIeO97zpMuhTQ6KU40XPqyHVJSMeOZfHvJohE4XF1scHXeY3vOZ0vW4ycmVplupxjJdJhvZ6iGJraZcM9slkRLFv0Ui4HJ1fkIS8C4m1CLTE7WNYNu121wXTrNl6v/nkHXoo8Cy3Gbg50vUEk6dNQqo3ozO1LvIUGzT9zKWNomrzOURIYRWWQ8a+In8KFxk+tKHa4rxfzcxoDxdIDSgkpoct6zWPEjynbMcCoib2qO1R0ypmbZS7HScVkNLYZTiiUPbCnIXdjNFvwU+4odUkbCvJfiqmxEwdIMOAn7Sz77Sy36UgGjbsxzNcnyBTPZggWLYQeA8QxsyQsGHc2go/nYhjTVUGBLWPBAIfj2gsIUGl8JspbgF4e38cBc97j67EyFRU/xaGWVdqQ52qizFEh2lSTDrqbkGLTjbtE3kXHImpCz4D9t+XvkTM27y8PUwu55zRCCEbmdtGFQtCw8HVNJOuRME0tIXFPSURGDrsXnV/4d9zb+O7GGnCoxYDtkLYOFTswGu8iZRkQ10KwkbY6KZznSvocqDZ6PHmaQImlK+CqhGsSsBhG2mUMiyOoid6d+hJQh2Ka3M6mfpcYcfao7btA00iyJKQIRUnJMfqz0W/x8+e/RUhGWFDSjhJmkyjmOMOzabFGbWRTTzAYt1hl9nKhp5jvwfLiEH9W/n4d2jx5vKb2CrEePHj169OjRo0ePHj3eInoF2RvMoBrm6/XfZ6+5hW/7X6AhWlhScEbP0J/bi6vzrBjzrCSTLNQeJ0ZRTm3GEAI/UdjC4K9X/0+Gsnsoq25O2ZQ4T9YymO0EONpmh95JpXmEsioxkWwgjFbIuBuo6VlM4VBpHWNJzLCkTlPV53GNEtVgimtzH+V4+z5s4TLbeJJWuMT56kPknBFiAmp6lnxmGwDRhVyqMFoFwBZpoJuZ0goXOV99CC9YRGKwL/9xFsU0B2p/jG1kyGe6rkwFdwNluxuuPNd4kueDhyhmduDTYlG9wInmV4gTj7Y3hdaKJXUay+ojjJYwpE2sAlaYRkqXKG7R9GcZKd6CbfURax9QnK7cQyQCzqgDzNUeYbr6AG1vCoBGssCQXsdZcYSjjS8y4u5Ba0XW3Yyk+wi11ZlcC7yuBdMIYdIIZtdkj9DtRBlGhrQzRBAu4AdzhEmbTGodhjCvLDeUNl4wRxRXSJSP1gleMIPWMUni0/AmKae3IoRkvvk0SseYZhEprDV3Sj+YQ6kArRVaK4JoGa3jy6R8YfTS/LLX2vFQKkApjyiuXPZ6d33zeMHyS957OfQleW2vZkzx4ly2ixlnl8oNpXRf4qKo0WsSQqU8gnDhitv+tfKDbCrxenml3+T7aSTydyXo9b/OnMWSioIVsRzYbMt1OF4tUMp6FIc65PsCgqbBymmXk8t9PLHYj2PFtEKLQ6tFllZzrCvVWfZT1KsuS7Us1abLuzfMYgjNRzbPUl1Is7jcNQdZXM6B1Nz75EZOzA+wp3+VZT+F1oIN19ZoTwleODWAJRXXFNuk0yG7hpe5qa/JdWXFoWqOuXaalJGQMhJOt1wmm1kiLSikfQSash3RDi0+NNphsplhOeieIw2h+d/PH+WZqsGSL3lHP2TMbieqFSXcUvh1IqVZpc5T3l8ylN1NVVboxBUsbXG081Um5RlShsGqn/C8eIaxtMOsqiCBxU7CmZZkuuMw4IScbad4cjXN6WaGZiyZ7cB7Ri1mPYvV0GTUDdcCnjUw03GZbBsESnBtWVF2NLVQdA0i0HzunEszNnGk5vfOLhEogdIQacFTlSzP13M0I4PrywmWhOFUzEQ64sa+HJVQ8kIDvrHQ5HBVcL4jqUWSP10+ynQbHqkuEyrIWpKCpenEsDkb8/hiRKI15zoGEsmwK7l7sJ+UKXg6+BLtWPMvTv472jFIAceqMX8y978TKfATQTWAdiyZ8yW2FAy6kv6UYFtBclNmnDPRKp0k6Tovmxk6SUKiNYnWeITESjOQ388/nfiHTDVDrssMMRd0mA1aTMUVXogWmUmq+ImiIRsUGOZH85/A1Slq7RM8HPwlHg2WdJ1mEnKUw6TMAgrNVmMYQwieC+ZYosp14jYWW4cpGSlWGgfxghlWvVMUyOInmv6USTvWfLP5xyx4IaFSnOMI7WiFuU5ATXfIUOKJzmdpxCGJ1sy0Iw7U/hg/mH9Lj/MePb6fCK31D4+t15tIo9GgUCiwv/ArDIgykVY0RJt5cZo7rBuphCHnxQITepin1bcwhEVa9mFckPA0kwW2sp/NboEzXp2cSDHsOijdPWG3oq6WuuQYVIOELzc/hWuVKFkbOd98nJHcdQzrTUzr51ioP4FjD1NOb+YqfR0viIPM1x5jQ+lu+vQ4B2t/2nUNtAcoORsYU1upGF13w2pynj65nhcaX8c00gThAqZZJGWVafvTGEaW3bkfZ149T8EYY4PawHkxQ03PcbXeT0t0CETAs9VPIhBk01to+9MM52+gFS1iGxmq7dMo1WGi+E5WvJPESbe4CqMVhDAppLfS6Jzmlvyv8p36f6Gc2021dYINxfdytvo1gAvF4grp1Lq1m/KR4i1EysM1SggkG9UOGrJJnWUm1CZqss7h6qeAbqDtRctuIWRX/mYWqHdOorXCMsu4zgB+uLrmwnhxXhelc7Y1iCHtC2HKK6Sc0SuOjQJIOaP4wRxZdxNj7j48XWe6+gCGkWEwtxeBwVztkQvLlkep1svK7y6u+yvRDfRWSOm87lBn2xpcC1zOpbfS8s6+rHTv0sLJMsuvWsC9lmleabmieOWy7XJx/hfX9/Xwcg6Vf1Pe6O/r8cZwqdT1jaCY2cFvjn6Eu0cazHVS1CKTcTfAkpqS49OX67BYz9KMbLYOrBInBkFo8thiP/vKNfpyHYTQVFtpDKn4xuwAP3P1OWoNF8tIaPgOxYzP18+NULQSBpyQa9Ytkt+YUDttYdoJbjlBpsDoswimIvy6SX6bwjunOTE5yFQrzdZ8i5P1LNsKLQyh+OZiGT+BPltzXbnOZ6eKPFFb5b/sNcjaEUsdl0hJEi2Y8xw6iWApkHRizX9b+At+aeDn2FnQSKE51zb47kqLB+v/iWJmB3vNuykZKabVMrZ2OCeOsl1fx1gqjRcrDClYDj3KZoqhtEmQaFxDYEh4oe7zkfU2tUiSMxUHK5INGZhIJwSqO17t0WXBbYOKQSciY8a80Ewz70t+ZKzCqUaOZmxgCM3hqsHGrCZQgpTRDe3OmYpACXbk26wG3VDoTiIZcf2uUyOCnBVyupnl+abFmUbCSFqyOdtd11ok8ZNuoTTbVvxV43/yLyd+mqLd3acmW4JqoBnLSIpWd5zYM6uKdw7BN+Y1/SmDwRQ8vRKSM02Ww4B16RQpQ+An3TF5tbC7vEVLU7YT6pFBLRLkTI0lNc9VJV9qPc7N5g3YUjCQkjzUmOZI/fNsKNxFgQH2OGN8qflXfDj3EzSjhLNqkf3uGIOuZDXQfKtzgnVqPROuy7zns6Pg8peNx9mlr0UgeJbHSYkC69QWWqLNeX0UUzjcYd3KfNghLSy25FM82DzFdrmBYdeiE2sWfZ9ve5/jVvfvMy3PcbLyBTaWPkCfHmOD0c9UssLZ5GmGzO1sExuItKKlQp5TD1E011ONzrLZvJkSeU6K5/j7xRuZaSV0koR7Kv/+DTtue/R4a9BAQr1eJ5/Pv+KUPzyPiHv06NGjR48ePXr06NHjbUavIHuDOVD/Ux6LvsKsnMHRNrdZN1BwJEvUGNdDVGiy0nyGULUo6xEmkg1EusNNxh2khcPXvYcYtXMsUsFPFPUwxjUFedvAlpJqkFCJAt6b/jm2mbfh6SpRXGGm/igtUWeh/gRwIeRXBaSEzSjbyaW3MlW9n3lOkXE3sC53K+udd1ANpiiJDAXVx8nKF8gbwywnp0mSBiOZPZSyOxnI7mQgtZ2NxffRn9nB4dqnaUcrnGk8CEBJ9bOT61mQi3y39occrn2ajaUPUMrtwg9Xu9I4HdFon6QdLKEvOBG6osBY+jpyqdG17pjWMVKabC/+JBYmm0ofQmCQdTey6B0FIOtuIpcax7YG8YN5NpU+RDq1jlgFlMz1eEkVL6kC4GiHdWoLp8QhZpMjbC3/OKPF20k7o2u/mdYKP5ij1j6x1mWJ4gqDznby7ro1I4KLnTjbHiKf2cZ49h30uVuIolVSzihSmGufvyjLuyiH9IM5+nJ7iZXPYnAMjaIvt5dSZht1/zyNYGbNnCVJGq/Y7Xktzn+uM45pFl93dwwgbfd1s+isfpqdU5d1x6R0LjNmuFRW+Fo6X38b18IwWkJrtSbJ7HYSvQvL9frzat7oblavO/b25I2WZBrSwU8EeafbFWtEksdX02zpr9CX63BmpcRQocVMx6E47FMe7DA82mBTxqMV2aw20zw1O8SK52IbCR+cWCTTF1LIeSy2MuRTAVoJ3rd+nm35JjfsneXg1AiHHx+gsCGkWknTWrL47uOjCAlWSVDYqQkXFEvzObaOr7B/cIVHl4ukTcWB1QKWobg657M+nVC2u46K7xn2+Y+7HT4/XeTQaol7ZrNUQovjDRdbKlKGpmRrVnzNj+d+llDBgi/4wnTAZDOmKurcUvh1yvZmHmn8N07rWQo6T1GkKYpRHGGwGoQ8njyGJQQTbhrbEFT8hAUvZMlPMAQMphxyZsKGdEjOVCx2Is534HzHYMCJKNox67OC5xsm9y+kWPBThEow4SoSLYmUYMiJcKQmawkMASOphJypGErFPLwkKVgJf3gqgxCar82n2JhtYxsKL+k6EdZCh4yZsLsQctdw11TjaE3w2JLgdEPzyFIHP9FoNJ8Y+GkMCXkzQQCbsppdJcE9K+c5VNGcbcH6rIGvBHcMSQZT0I4FA6nueXNBLFNyBM80qmzOCaZacLaZMNuBUAmWA4OcmbAxE5PobmfONuCDmZuRwF83PsOS170+7M9/nPnOIYZ1H4nW/Ej2J8hbkpG0xbWpMR7zTjPZiGmFCkXCsJPCTxR9toMQkBJ5LGGwRI12tEKRIRSaaXWYW813slFfw/9c+Y+0RHvtOLrF3cJ4xmKmHTLltbqvpf4eBcMm0E0A+vQYe9NDVGKfQYoY0qFPDbAxZzGecVjvZlhv7u9Oa29hgAISwXvdGzCF4GxUIWeaPZfbHj9U9AqyN5jRwm34YZUWq2xy88wGLZa9mA1GP8vUmRNnKGV3YsssGkVV1pBY1JPujfN7Uu/i4fBbbLGG+HLzc7RUxNmmz8l2nfv9+1mM2tjCINAJDVFbm69SHsern6Mvt7dr1W710wzmCHSMQDKa2oNtDTJXe4R1qXdQ1iO0WGGbfScPB39JU1QZKd5CPZ5lpfEMxcwOOqpGtXWMRjCLr+s0kwUi5bGn+DGKzjp25j7MCXGYA94XeDK6l5PN+9hT+nnWFd9FpDs0vPPk3DGkdAlVC8ss4wUzKOVhGimWo5MkOmLE3NmVFV248R8z9zIfHeGI/g7nm4+TMQdIVLBWEGkUYdImlxqlnNuNrxsMujsYN3ZzpvY1pLAwpcMJnuSF5DGeCv6audojZI0BAt3CEVmCqFuwXXrCf/GYonON7wBgmpdbx6ftPqK4zUzru6x6pylmr8YP5i4bz5QkjQsBwyYpZ5RceiurzUOkzK5N/1L7GGHSptI8QsefxjLcV5UhXrqc3bFmL9/+7vjTJEnrNX3fpVb6tjVI/UIRdnF5Lt0uQpgoHa0Vj6+Vi9v5ohTylaa5fNle6rR4kYtujY49vCY/fel3vj1PcX+TArLH24PV5iGKtqYTWhSsiE4CH9s8z+8dHkdKzeOrGWaqefb1V6nMpfFbJqFnMJZrsWVoFT8x2ZJvdcdt9bX5+swgUUcShiaLftc1VWvQStCMLFpLNjuHVti1d4lTz5bpG2gzt5znmo0LtE/EzB7OcPCBfmoLKfr6W8wtFphp5BhNRRyu2cz7kqqfopNIjtZNjtRtgsQgUBKlYSwNJ5smE2lIG4qsqUibCkNoHl9KGHQFoxnJtzoneL6W0GfbpE1JWqfpkxl2i52YZoGiKrIku8d3XhexpcFzPM0o25gLOjwTTHMsmuWJ+CASwWLY4WjNI9GaqY5F3upK9XaWbK4pavodhZ9IcmbMoKMpO5prSwmnWyYbMwGtRPDNxSLjaZ/FwCJSgkVPEWnBnG9QDQ2akcGHxiLShuIfXdUiVJJ9JcXBSoHn6zn+75Oa+xfSLPo2315yKFgxnUTQjLoBxQOuoBEqtNZ8uXGUr3buo5PAmSZUIoNvLyhWAkHRSrgjP86s79GKNGlDUwkFs56kHQtm2gmrfkzGEry/tI5Ew539ZZ6rJqzLwOa8wUBKMOt1i7fjDYtHl02+POtRiwQlG1qhIlKanc7dPB2fpKRKKBS51BgtHXCfdx+x0jzf7KA1pAxBQy+wGHoshwHvzexiIfCphiGHo2lO1HwkBlXV4bh/P1orSqrIrDzLPnknq3GHvEjx0wP/HF90cA2TyWbAXzfv5en6Kg90PkPZTHGEA/TZKWpxQI5Bdpd+jrpc4WS7TkJChSY7uIGGbPBMrYkXKzKmJKVc0hQwsHiw9d/ZnHU51/GY7yi2pfqItMYyi2/hkd6jx/eXt+fdSo8ePXr06NGjR48ePXr8ENAryN5g5urfYTR7LdvUHj618H8w4eSYjqusxB4DFMjSR6V5hGY4jxKKqegpHNJMyuNEOqEdJxSMMRpRSMub5HlxCF/HeMJn1NhJn5lmkQpzYpHna3/Favvk2rwNI0MQN2h5k13DC7uPjvAwMThVvYcwWqIvtxclFCeCB3ApcLD2J+xw3sNifIK8HAG6xgu19glqnbMAtL0pat45VhoHcS50ZQxMKszQihdI233EicdI7jqO1D5LPZoh1B5J0qLSPIJtlfCjOhqFaRaxrUG0VlRbx8jRxwutBzDMAvnMNgby+zlS/QvGrL30G5uwzCxzzafX1lEgiOIOzc4pGt40QdxkqfUcjsixwjSF9BbSskhRjGEIE6VipOhKH883nqDin2Gq9vW17s+lcjyt1WUdlSiu0AoWXtK5avld56diejN+OHfBPOOlHQ+lo64jY1RF664pS6JjoriFaaRodk6hdLTmSvla6X5f/JI8r4tI6WCaxQvyz1fvxFyUNRpG5oIs8HvbxDAyl8gwv2eE8lq7eXDRYOTKpiCXdsWuNI1+kQxQyNRlEjTLLBOECy+bb/Vmhg//bbpvL3aQ7PGDhRRQSAXk7ZCt2QjbSvid68/x/GIf23IRrhljCM29Z0cJA4MDUyOcqRWoNNJINGk7ZM/mBR56fh0f3XMWM6Ww7ZhaaFLpuCgtmGtkmSg0mV/tnnPjluhmmRkaKWBpKU/oGQgBw/kW+QGf4+eGSJkxKTMhVJLdhZD3jdTpxAafPSsp2ppdhYhYSzblWqwENocrmnMtjZ9AJTQ53ZI0I4MTDYP7O1/kYKVDOwZLO2QtyZHoPCfbdRwsIp1wnBcYzl6LJ3z6VB+rNEnpFO0kItQex7z78AjwRYslfZodejePxfczLU9zbdnl9iEYsBVH6y61SBBrTSMWPFvtGox8ZyWDrwRLPjxbNRhzE742l2J/ucmt/Q1CZTCSClkMDIIEZjsgAFNqZjyJn0jqkUEnNnm6YvF0pXvcxhpuGEgz4sKAE3LnYMB98y4PLypiBXlL0Ag1R+PzeITs0FfxY9kP8PCFa26sBPv6DUZdxdm2yX+Z+b/QWrM1L2jGgpk2nGslFG3NcFpyQD/NPa2HmGzEnG/FKA0pQ7Lof2+/EsBq2LUBcAy4KpcmZcDJumIu6FCLA85zlJFknICQOU6SknmqssI75F2UUwZpaZKxYKYdMlP7No4waOgOxxpNhp0UKWmynhFShsE6tR4Lk+udHyNrD9ISHfr1GC3t80x0H+fEDH6isLAvuCPO029tAeCd7s8wHzfYK97BN7x7WJar1JjD0Sn61BAxCZPyGIEICERIVuU4LQ5hS8GB1hJ1WWFED7NVb+JD+V/hi61vck0xTSWIaEYJidKYRvr7eFT36PHW0ivI3mCKmR0s+ydZlqvsL36CZhzTEk06wqOmO4TCw7GH8cMKNRbJWt0xW8N6IyfEUxxSR9mgNvBY9BXWld5DjgEiYoo6x9HGF2nEIbZ2KKsSfbk9RHEFISSGkSftjOJfCFDOpbeSMkqc5yjPRw+jdIRpFumEK5ysfAEpLJp6CY3G1SmK5noC3aThz5BxhgC6IcoX6HO34DgjzNe+wyn/YTqqxlL7GLEKyVrDdPxpfNUAYVJtHUMiQSdk3A34QbdoieMacVwjjJaIkw5CWJwNv0sYLSGQSCSV9gnSqXVEIkAgKaQmcKwiWWeEvtxeHGcErWMMI0MUV2h2TuHaA5ysfIHz1YfIWsNMVe/nZP0etFbYZp6WN8lKeIq8O0HOGXnJTfql8r8Xv+cHcy/5jaO4QhAtY1wYM1Zrn3jZG+xuQRPQ8iZxnXGanVMkSYM48ddkf432SZLXEUCslPeK42KUCnCs4tq0rwXbGrzEfv57RdKlUsC/qSzwlYqi1xK87NjDa/9+8fpc3P9fbvzW6x2D8HqCi9/MYq/H25svzVWxrIThcpMzLYt6J0UcSyphd/9Z8V2mm1nuHFlhoZZj0beZ8WzufOpZbCNhpZNmZSnL1nwTp5Bw8oUBao002/It+jIeTy32Uwtt6p5DX65Dre1SW3ZZN1BjYS5PpC4UFZFBJhvwwPQwUceglPIxpMKSClsqDtUczjQzLAc2P7NRc03BJ1Yw03H41GSZ1dBkyJWMpCWVEP4/556jGmi+u2rQieGnCj/JrQNpvFhzvPZ5HvGfZ5c50ZUcymVOyzPsFtuIdcCimMQWFnOcxBUmL8gjLNefwgtm8KXHBrWJun8egJw5xGa9DdeAWc9gMZBMt+FcC1Z9zWwHdhc1j6+YvFCPOdeCjRlN1hScbZtsyYMXmxhCUw1NZjwbS8KuksBPYKYD021BwdLMeCaN2OBk02XM1WRMKNkJWnddDo9UNc3YxEsMRlzYVjCZ73QfoE21fTaJUba4BQ7oJ4iU5sOlbSx5EbMefHPeY7pjcO/yPOvyt9LGZ6YNn68eoRkpXFNSC7sujPvF9bzTficlxyBrGZyqR7im4KlKnUjBs6sBz1Y7HK16CGC2nfAni39MJRCsBAEDtssx8SQGFhExHdlmSGxmUG9gnR7lKfUQ1SDhsD7EfFtxiGe4qfCPmBPLFEWaA+GXOREsUU8CTopT5C2TTRmXs/IkFibXcBNNUaUuV4lERMEeo8UqJ9QkI7qf7yYPEgqPzWojEslzPI2NSaAThq2dpFWGHAM42iGtXVqyidYJVeaY5jiT4llG2capdounan/EfHSEFVHh0fArTKtltuh91EPNqmoTK00tDjCNnrS7xw8PvYKsR48ePXr06NGjR48ePd4iehY2bzCj1h6mg6c5Fz5F059mNX8HG9U2ImJO8hQqjpDCpJy5CoAy4yxJn1lxituM27GlJG9LHpyfp9k5g9Yx/fl9SGHx7tyv8BxPYGBREhPoRJFLbyVvjdCI5mm0T5JLb6UZ19A6YbXzAlKYDKevoeFNrXWoLLNMs3MKL1zuGm0IHykMmvECQdj9uzS/yrGHWe48j2WkKRZuZERuB2ApfBIpTM63H2KwcANL9ScxjAxSOjTDeRCCtjfFutJ7WGgdBroZWnHSJIorF7pc3+u61NonAOgkbZbMHOus/WitaHtTa2HPF7lo5GCZZYKojkAwXnoX69QOZsUjKBWsOU4O5PcTJW0a3hQyvXXtOy5mVwlpA8kVf8+Xy/xSKsCLKq+aCXZxGR2ryLC7mzPhAlrHa6HTUliYZoFm59RLlutvgx++tqwvyyyTJE1sM7tmuPFaulaX8mZ3inKp0bXt9WJebVu93nXpOSX2eC38yHCJ55dddo8s866hOsP9DbyOzamWhS1hJCVJGQoJfHaqyMas5lRT8K/G38P5dsjxhsOil6dgw3tjk7Fik+lqgbMtl3Zscev4IvVOihXPpeAGjI/WcEoKa8DAPdPg6ZNj3D9f5L3DNQDes26BMzN9NCOLRd9GCjhat7rByZ5BOxbcPtChERl0EknJTvjwWId6ZGEJEELjJ5J/lLqWRHeNJRqRph0rVgODE50K/9vWf8GCBw+3JomMgJwqsZ4RFpMWA3Ij280xXENS9bfiGibDySaa2aupto6hUDxQ+z22lD/MU9GDjJq70VpzuqG4dVAQKmhG4CeaehgzYdgoDRVf0YhiDCGIteTZepW9+SIPLdU4Ui3wDzYlnPcs+uxkTfoXKxh0BcMphdKwEsC1RQ9LKpQWNOMM//F0jetyA9zcn2CXFAcqNmVHc6YJtuxmh3VizXkxw53praQMcIIsGbNrhJJojSFgd8klb2nuKA6TMkY4Wg2YbnfljeMZA0vCZCMhVIpT+jxbkwlUCIMpAy8WlGzBz6zLEylFLWNzsFknJuFI1WDYtfh/r/8En109zlJ8gpv4AMPiKoZ1H4+EX+B25yMc1N/BECaJuIphYwcSgSXSGBL2so9ZsYJE0tIBI+4eAu2TFeVuV1NpvEQT6BZPhH/NXvtDBKKD1oq8XocnJ9gmx7ENQcaUJI2AanKeBzuPMJi5mnG280x0H0Opq2kkC5jSYb0ep89xOBZ1lSWWSKNJsIXLVPV+dhTewaqsIBAY0mEmOUKkPA7W/pRiZgfnvXXcltrPahDSxu8qbXr0+CGhV5C9wdRZwDHzJCpgKHcdO9nFebmIqU38qEYQ1YniejfNXjqMF24nI/vJ6TLzUYu0cAiVxcbCO1E6IdQt2vEyI9ZOjuinGBRbqDCDL1qsNJ5hIL+f2fqjazeeWicYRoaWN0k5t5uWP0+kO6TsAcK4gUraJEkTyyxjW3mksFgVs6z4p3Ct8lrQrlJBdyySUcA2cwD0OZuYaz1LObuemp7rSiWljWHkyci+ruxNhyRJmyCqdSWDVj/T1QfWts9Fe3sA2yzhBTPA5ZbpUjoUrfU0WGax8fQVi54gXEAgUDrGtYqE0RIpkWfFWMBNja0VcFJYWDLNSvMQoPDj2tp3XLyRv5IUTyCQRpo4rr/sb930Z192HNelRHEFpWNWjdMIYaF1vLYNTLP0EufBN6LAeS3LdXHZAIQwLhsj9mbwNwlOFggqzSMv+35PNtjj+41jD2Mb4BiK6dUCj6505c4nGllyZjeU2DUS0oZippUlawnaMaRNmGoL9pVCrs5DqBw+NFqlmPb5zswwgRJcletwuplmenqEGwdX6cQGrhvyzOkRNhbrjJgtWrUUE7kmWSsia0f4sUEu361G+hNBWClxtu2wPpOQaMFwKuJcx6YRGfzyya/xFzvez3JgMedlGHVjhlMhoZLMJ5J2DBrB6UZM2pQsBB6WTHNHXx+1EDImdKjjqwY5StSVRyQiDlc/xVjxn/NcfI5YRpxSPuejA+wz38dqaT+jegCn+A/pUznOm1lW9TmuT69nU05wugWOFFhSM+hKDlciDjaXGUgNUnI0Z4MOtxZL+EpwS1+RRgjvHy6yLRcx2UojgXnPYMmHTVk43KwyHuRppA3SZleWuBraBImgbMfkTM37BgYpWppqJGlEBpuzCV4i6HMkjbBrn+8lmuPVz7HL+B1MKdjNbmphwmwnYUveRiCYbERUA4OUITCEZn3W5mTDY8xN0Yo0s52I1biDQnNtagOHwmkWghPsCW+nbDl4SbdQt6XgbNPj+twAodI0QsWQK/nK8jwfLOzg4XqBWbFESZU4IY8wmLqaSCn2i9t5Sj2EIU3yOsfz4RKL0XG+GBznJ3I/xarnco6jzBOwVHuGu/K/jhKa1djDklnORMtIJIOpq3ms+l8BmCjdxbJcpaxK+CRMJVXG4jIFaxxH5FBuxIS+mtP6KXbad1HXFUzh0KbKQf0CpXgCC4cznYcpuusZFFtY0qe7Dr6iwbx6ns3lH+V05R5cZxwvmMEwMmy0b2SXPYoXqzVJvpS9W9QePzz0Hj/06NGjR48ePXr06NGjx1tEryB7gzGxafoz1NonuErvY16vMqD6qMsVvGCZrDNMObuDwcINoBXT1Qc4XbmHGos81vx/eDT4AofVKVrJUjc8WKwnZ41yovkVhsRmHJ1aCz0GqLRPsL54F6PF28m6mwjjFtANu6x3um6LtsjS526lP7ODdGoC0yywPn8bHX+afmcrZ6tfo+RsYKXxDEp52Fb/Bee/iDBaotk5Rcs7y1T1fsJoiePVz7HSPo5llknbAyRJg2p4lowzgBQ2plkkvtCJipMmWXfTWkfoUoOGIFzEtvqxzPJlmVrrCney5B9n0TvKQP66l5UEajRJ0sALFwE4VfkiZ5uP0PHOAV25odIRrWiRUnZH11gk8V/yPYaRuWy5ACxroNstehlTiIy7gSRpYJnlV9od1jK+kqRBrXV8zZRC67jrlKh8HHv4TcnLujSz69Xomo1c3h17PQYXr4W/iRxQ6ehvLCN8pZy2K9HLBuvxWkiUz4maZs5zON9JM5pKeHI1z0gqZEs2QAOuoZjqODxVcRlMKQIFrgGuIaiFNkfqDpaAwWKLhWaGUTegEkoWfQdbKuY8yelagU+fNZlaLnG65VL3Ujzz1DDPL/Yx18oSK0k6FTLfSVOtpEk5EXPNHDkrJmMqCpbiL6Zr5MyYspXwfNPmp/IfJlCCBV8ylErIGN0umq8kkYaUAVlT845+gz0l+MBolj1lSTvqmm08Xwv5aHkf+8VNDFCgIF36ybOhdDeHeJKCLtNWqyREjNp7MIRkJj5MTXcAWKbOBsZIiTy1MOZYNWGho9BA3gZDwDP6u5xWT1ELNZGGbekiZ1uaM42EVV8z6Aq2ZiMqocGcb+An3eW2JHxjzmeLWyBjSh5oTLESaCwJnzmrOO8ZfPKMwfmOQNCVJ/qJIG9pHKlZDSUZUxMqzcl6iARuKvwjViKfPscgZUhKjsFS0qQVaZZ9xUjaZH1WkLW6ssuKr3hBHKdoC/pSgj1lCwuTITPLVztfZpscZ8jYxnljmnocMdmIOFUPeWS1QkdHRBpcU+AYkkVPcXthGMcQFHQeX7R5OvwSdzj7uUbspiU6PKMfZaXxDC9Ej/B4+9OMijL7zPdzp/1jhEpRkml2s5+SnOAj5X9KqCPOMMUL4iCPRY8zKspU/EkMYZHPbOPa0j9gtv4409EBTvAkX6v9Z+pyhef0EQQG/ckwAokvPTbL/cQkLMYnMIXD+ebjaJ2Q1jlW9RRBuHjBgCSgHa0QRkuciR4njBskOuLa0j/ANFz6cnsxpMtV5ggLgU+oFJ6OCUVAGL95io0ePd5u9AqyN5h+PU7B3cB48U4W5RxlijyjHmCz2sqW3Luptk+SqIC6d45sehN9ub2UsjuB7rikwdTVrESncWWJLH1MBo9zDdcymrueqegpZjjBSuMZzjUfY1v5IzhWH4Fu0QzniZIOUbxCkjSwrX7EhRvqRjJHoFpEyqPjnydl9+GrOkP5G5hrP8O60ntoRnNsKn2gW9RFK/hhFdMoAt0b20sDGjPuhjXpYVoWSTmjJDqm2jrWdVC8RBZoGgXyzviapDIIF9aWS+mIOK6jdIxt5hHCRAjJfPswKbNInHQwhHlZsXSlm2zjwo10Lr21a9uOxrGHWZ+7DcceJorb1NovrM3/xaik85LX47hb9GrlY14hnFIKC9savExqeSUujsO7FMceJndhLFuSNAjChcukd29UcfZiJ8bXUmBdWsS90eOpXk+B+EbwWmWbF+lZ0fd4LcRxjfVZwXAq4HDNYjkw2JQJWZdrca7jMJpKeGS5e04aTSn67YTJpmJ9WnF1PqIeGWzPhWzPh3x3ZpgDlRwZM6JoKdIXCqRrCiGDrs8vbwlIlOBfTT/ATCeNITX1yMQ1u+fTQp/HxnwTgNnVAo+tZJlup9hTqnOyafJjoyUO19Oc9wx25UPeOxIz51vMeVC2IxItGHI9KqFBLew6FK4EUI9g1hMs+jDVgkakSJmCjGlQsDUNFRDohCVd54B+hEG9gc16DymdYr7+OAAnG19jQSyxXd6Kg80cJ6nJJZrKZxc7GUiZuKZkKQgo2RpTCB5dbrJf3MSNxrtJFKSNbsBxyRGsBiHjGcF8R3HfnEnOVDgStudDOkl3us25FErDkh+yRYxRtCFIwBKS1QB2lS1ShmBXIWJdtvt7Hq0JJtsGf7Vylslm17Z+XdbidCNko1OkIVp8qzWJa0rSJlyb6+Noq8ZnK39OqDStGFKGZsSFc0GDu9x9PFdrs+xrGhFsyKRZiT1+NPNhjquz1PQsW/Um6rSoJB3KzoWizU7zYOc5lIbNeYFrCp6rtZlqxpySz3Fbaju3Ox9BILin8u9ZFNOMyO3cWfgNdpvvYSJ3M7FWHIrvp6MiVsOwu940iUXE8WSaMSdLWue4Ud7GRr0bIeCa1AeYbj7GbvM9TMfPsr3wYdrBMkv1J1E6op7MsRKcopks4GCxXdxEgMcZdYDj/v2EcRtHZNmQvwMhDAI8ruEmthd/kmowxWTnEawL1+hIeTT9aWICUsplwrmO1eYhBjO7eCo+xGgqxWnOscHNYmASRLXv78Hdo8dbSK8g69GjR48ePXr06NGjR4+3iF5B9gbzbPMLVNonWGw9h4mDIwz2yndzIHmQM61vU8xsodo6RhSt0mifZLV5CC+qYgqH4cJNZChxlbyZDCUWkhOY0mZJ13mH3I9lZFlqPQdAX2YrKZ3BNFzma4+hdXKhyyPJZ7Yxnr2RidzNZNwNaK0whcNq8xBKRzTaJ1EoIuXRl74KiSRrDXO6cg9+VEFKhzBaWuv+dHOz2mudG60VA/n9mEaK6do32ZG++4rdlL7cXqQ019wOL+JYfQzk9wPdLkySNAgvdqS0wjZzpM0+wmiFWAWXmV68uOvRXdaupLHZOUU5t3vNbGSm/TSbM3eiUd/L2EKQS28lnVp3oYtootEYRmbtfcPIoy+4Lmr0S8KJu8uZAOpVJYtryyksDLPQDe8OF0hU8BKZ5Pe++80xqngtHa9Xyjf72/JGfLdAvCnyzr8tF6WpPX44CJWg7ATcMdChFYMUmkQLjtcFtlQ4BtzYX+VcpxtuvK0gaSWC1dCgYCUcb9gYQrMp2+I9oyscr+co2zFn2g7HGyYKmGym6SQGhtR8ec+NbC40mCjXuWndAjk7pOAEnJwcYGxDjTAxeGC+yKZMRNmOiZWkGcH5Nnxqfpo+W5OzYibSHYacmJ9Z36ASWmTMmC+cL+IngmPVhG8tNTleDXl4qUUjhLONmM/WvspfNz7Po+1J5sMOfgJ56bAqK7wQPYIhTJqiSiBCHm3/GUP562noBTYV7sLVaZ5sf5qqrLJXvIN57zCT8hgKzYIXsSknuG3QJVTwP6tHUGiuLtnsLqV4ptG9Jky3AxINO4opVgMYciXbCgKloRYJDtdsqiHMdxRLfsJC4FO0LPpSJs0IMqZgW9Fic1Yj0BTt7nlowo15eqV7nj9WjRnXQ+wqCkwBq75iJG3RiGIC4fPu/CZqYYwhYFsBRswcvz3x8wykJMmF09qh1YS0cPimd4jN2TQz7RDXEHzHfx6Ax8JjGFgstY/jq5gCWWIUM16HfcUcEnhnajfnWiGNqCvBbIg2R+PzDOlNmFKwTJ1vBk+SS2+lyBAFVSAtLLali0xW70UKwQ3WBxl0UhRMi294nyMSIWndVZaEiSYQPkLAilykmYQoNBtzd3JCPUzJWs/x6uewzDSDhRsYLtxEv9zIXut97BK38532pyjJNKNqlGrnNFKYtLxJSmqQLWozfXI9C/ExFsQymq5D8nB6N+8w3s1NhX+EFyySS60jJfJUjCVarDJYuIGiGGNUbSJRsE1s4Ki/2L1HeRUFSo8ef5d4+93Z/IAznr8eISwS1cbVaZ4XJ+kIj4I5ThgtEcRdeYkmIZfeiuuME4bLnKp8kRG5nSn/CQaNHC+0HmC5cYBq6xhP1f6IehKSlQPEcY1Sdif9YhNV5uizN2Nb/aTtAaR06M/tpdE+SYRHK1li3N2PIR00CX25vWvLqXREtX2CULXwVYNWtNC1pI9rawXIpRI3pTzQGtcZJ4hWGTK20famcOwhZpIjWNK97KY0l95KK+ha6KdTE2tjyASCRIVUO6fJZ7atTXvRfRDANjIsto4wkN+PF1VesUB5sSRw2NyJlFk6/jReMENNz10W7lzMXk2zc4qOP00YraB1TD6zbU1GaVl9aB2htSLrbsI0i1d0Hmx5kwhhovRLJYlXXE4dYZt5pOhuo4vzfzG9G/tXplsgX3l/+H5LIi/lStLUHn83kdJlspGwGqSQAgYcTScxaIcWOUugEVxf6o5VvaHs04wlu/IhOVOxp9hmxrPJmjDr2QwUWsy3M8x4ElN0L8hX52MSLXihZTHn2Ryq5jCFohXYpHMh6XzIUifNPef7AOhUbbzIYl06xpGa//qCoB7afGSizq0DMb+1YYyhVETGjGhENlkzoZQK2JprkjZjri935ZKJ1rjCpKo6zBrnqQYJR/QpPph+Pz9V+Pvckt6II0zONDQdFdERDa6ybscSaWaCZznY/DRX5d7HgNxCJ1mlTw3RT56bMj/HgOoj0Yq8M0Y/6zjOcZpJyOmG5ndf+Le0Y8G73J2syGVWfc2ipygIl04CgU44WQvxLySTeIlmYyYmVJLrSz7lCwVWX0rgGpKW9jClIG8JwkRzrhUznFKcbQsyJlhC81fTEkNoxjMGm3PQjELfVwUAAQAASURBVCNuGXQxhKYZw3jGwJSCEddmn7OOdqQZSXd/t1rYlT6WbU2iQQCREkxkDQYdB0ukiBQMuxYrgaaezFKVVTSKFqsU3HUsy1VOiiOYSBSa8e7zQDSwqOrcV5ukEWo2Wn0cb/w1fRTwYsV2e5A77Hdwh/PjbDdHMJE0tc+85/Pzw/+StGFwXDyLLSVp0+Bm5ydZZYbp6AACyVPqAMNqiG8FX6Ggy1RljRlOsBSeoN6ZBC5G0/gs1Z9kg9hDVZ9nvZPnu/7nGc5dywH9BAERrj1Ay5tktHg7HdFiQayS0yVGzWvoU2UiEZByRpFYBDohFAH78x/Hi6r0JyOEukM1mGK5cZC5+DkGjSwzQZtEa7I6w4HaH38fj+oePd563vYF2YYNGxBCvOTv137t1wC48847X/Ler/7qr172HdPT03zwgx8knU4zODjIP//n/5w4vjyf6Nvf/jb79u3DcRy2bNnCn/3Zn32/VrFHjx49evTo0aNHjx4/pLztC7Knn36a+fn5tb8HHuhmWv3UT/3U2jSf+MQnLpvmP/yH/7D2XpIkfPCDHyQMQx5//HE+9alP8Wd/9mf863/9r9emOXv2LB/84Ad55zvfyaFDh/iN3/gNfvmXf5n777//dS+vLXLk3QmUClAocrrMrDiFr7tSu4uBvVorWp3TSGlimgUce5gTnftpeZNIBNdkPsxAfj/p1DoMI89J8RyabtcmSjyq+jyDegMDeoIwWsGLKigV0G9sopzbTaQ65IxhFoNjSCR9YgO1C0/AAGIdrD3VX6g/ccGQ4/KOzYslbhpNlLRIkjaRCBgu3IQXzBAkTfy4flmXoBPMkUuNMpS/gSjpfC+gVwiiuIJlZJFIpHTI2oOIS3ZFKUwcq0CiAzrB/Ov+DdLO0Joc8KLE03XGAWh4U6ScUSZKdwEXjEDi5lpXME7aKOWRTq2j5U2iVEAxs+OK8wnChdeV26V1V4JxsVt4pdDit7LTIl7GUfKl0709Txsa3esw9njTUcpjJCPJWhEHqy4bMz62VKTMhK3ZhEeXTeZ9i+freQZcn61Zj2ZsMOREPFfPsBQIJtIROVMRhiYzHYeb+jo8vmrTiLoGE3OeydZsTMpQDDoRT6wUmGpn6DRttBYMpjt8eGKVbywUWKllWPUdri42ONmy+Y3tivFci1AZHG9YxBoWfItECyIlKDkhx6sFjtfzlFyftJFwumXQnzIZTDkcjr/BTfZ2no/nibRPI0z4fO2zPNteZlKeoRMnPFj/T5xtfIsVMUuWPoKoSpK0mdDjlFWJG433MWoUmRZzZIXDC/IIDe2zUH+CYd2HIuIx73/wlfa9/G9b/xWG6IZCX2OtxzUFeVuwvZCi3xGsT7uYUqA1NELd7R5FkqIdc96zacaCM42IF+ohx/1lpsRhvty+h4O1OomGQdfgcBWqgSZraqY7gv39BqdaFq1IEym4vj9NwdJ8ayFmwlVsziYkGs6026zPGgy6kj5H0I4FrRiKlubAqmaqGVMJNEMphRRwIDzFrPcMUkDeFqx4MQpFURVQOkGToHRMRMAmdTVn5Qm+Wf/PRAquLhkoDSOyyE5zPe1IkzIEP1r4x0zKM/SnJCOZrgnKQ53P4pqSc8ZZ0sKhaNlESnMymWOf2E81jEiZglBHLLaPkDKLZHSGLWoXx8STZMwBAhFwNvwuoWrR8M5TymzjTPWrhNEKlpHGdcaZ0oeJlEekNaPpfZyvPsQIW1mVy2xybqY/v4+0LPFC634GdR+nk8c5Xv9rOsKjrVZYn7mZCI9VWSEW3evdUGY3JgYpsjhmDnRCO1gmUAn9pounY2aMs0BPMdLjhwuhtX7zBo28CfzGb/wG9957L6dOnUIIwZ133snevXv5/d///StOf9999/GhD32Iubk5hoaGAPjDP/xDfvu3f5vl5WVs2+a3f/u3+epXv8rRo0fXPvfTP/3T1Go1vv71r7+m5Wo0GhQKBYRIM1G8gxKjHK5+CsceZk/6w1TkAq1kiUrn1BWlav35fXTCFTa5t7FdrmM2rjNmFpAC/ERxmnNYOBRVgUl5jPnmQcqZbfTJ9Zz3D5C1hxBCdq3ddcCEsYeIkFU9RUb2c6b6FUyjiBAmfZmtzNceo5jZQa19AiEkjj2MUiGWmcUPl1+x0CjndrNT3sk5+TwFhlnRkyzUHqec20OleXhtrJBh5EnZZdreFLbVT6JCkqTRlWpaZVaahy4rQLq2/Q3CaAUpHUqZHXhRhY4//arbX0qXlD3ABvdmTjW/gW3lGXH3sBqepuXPk3PHqLVPo5SHYeQxjTSGtIniFim7jzjx8IIZbGsQy0wDkKiQMKrCJWPQoFu4XCymXk+Ysm0NIoQknxqnHS7hh4tr33sxkPuV6Jo1v3mHq2HkLxujJ4TEtgav6Ez5yt/z5gRMC2FeCAP/nqT2jXaC7NHjtfAPx36Xf7pzmccW+2nGkp15j0HX418dyjKWtnlHn2I4FZKzImY9l0Yk8ZWgbCXs6aux3HEZybY5uFwmZyWEqvuQY9E36SRizco9a2o2ZXzOdRz2FJtsGK6SG49IPBAStIKV8xlWW2nG++ucnO+jGVkMpHzmPJdDNYfrSz6G0Ay5Hq4Vo4CZZtdisB6ZtGODz5zz2ZxNkzZgyes6Kn6p9TW8qML19o/xnHoIx8gzKLYwqPs5mHyDormeyeq9a+fzQbmFa6z1tOMEQwieUc/ygcw7mGr5ZE2T6bjKrDjFNrWHp+Kv0mif5JdHf5dzHY9bBjL8l4Uv89Hij+AnGksKmpEibQrKjqQRaQZSgnascaSgGmquykPOVDxXk7iG4OnVFn12ikeih8nLEXaLraQMSTtO2Ntn4UhY8uEnJlqca7soDc24u92LVsKDC92A5/EMKA2NCAzRnVfRBlsK0oamZGu8RPBCAzIW5C14dMnjGAe42byJAdfkTxb/mH8w+AlsCYteQi0KmZJTnGs/jh/MIYTJcOEGbjJuo+yY3NivWfAlloS0oVkOJOdaCSWnu3xfbR7lenMHhhCc99uUzRSLcYu8SBFpxbZ8hiDRPOmdIxQew8kow3aW5+LT5HSJvM5QE000ikXOkBfD1PQco3SHDcxxEqWjbsFcuImqdxYhJK5VYtjayQ3OVTwRPs8tznbOdBpUZJWyKlGRVU53voVj5thu3UFau0TEKDSBCFgVs8y2nuL29MeJiHm4/n+zpfxh6vEsGsWEsYdnq59kV+lnOVr9DO8o/kMGRYFZlomJOVb/Qs/9tscPOBpIqNfr5POvHMXz9nzU/TKEYcinP/1pfvEXfxEhvjde5DOf+Qz9/f3s2rWL3/md36HT6ay998QTT7B79+61Ygzg7rvvptFocOzYsbVp3v3ud182r7vvvpsnnrjcjKJHjx49evTo0aNHjx493kh+oAqyL33pS9RqNX7hF35h7bWPfvSjfPrTn+Zb3/oWv/M7v8Nf/MVf8LGPfWzt/YWFhcuKMWDt/wsLC684TaPRwPOu/HQmCAIajcZlfwDFzBYi3aFPlSlldzKY2clTtT9i3jt8IRzxe90x2+pf+3efuYmsM8KwGuKR+JtcX+hjOW7jmpIT4gX2WZtZ1edYMOaItY9SAbHqMO0/RSeYZ7HxJLEKWG2fZKXxDFXmmIufI1IeKZ1Fa0XOHUMIiSlSADT9WaArpfODOcJohbY3dcUnUpZZRkqXcm43GXOQhmywS+8lFB6DYgs7Sx8lUt5aB0cgcKwibW8KgDBaWeu+NDunWG2dQKmAidJd2NYghpFHSgvHKmGZZZQKWG0eouNPv6pswXXGyaTGMaTD8erneFf2F7nD+Slm2wfZYL2DQnrDSwImg3CBjj9NFFdodk7hBTMXlnOJjj9N25vCD+ZQyrusi9XdXt+TGr5aJ+iivM+2BgmjJYYyu8kZw3T8aZQKEMLEMPKv6Sngpd2x1xt6/FoQQuI645espyKKq6/yqZfyZnTHXGecdGr8so7YlSSfPXp8P6gGCbGSFK0YS2gyZkTFd/hnO0L29ylqkcQxFJGS7CpX2ZFvc2NfnaFUiG0kSKEp5Dy25LrHii0VxxsW7UQwd+F5oilgW67beatFkvWDNXzPQkhYPpfF6pcICf1jbbZuWqHTsUkZCUU75J7ZIgNOQMbU1CMDgHZsUfUdWoFNLbKQAuZ8i1MtgyoNKn7MdCtmLuhwruPR8GbIO2McCL/MkNmVbR9tfIFn1beotU8zWb2X/vw+mp1TDMmrKKgST8XHGM/YxErzU8V3oIDBlINjSEZkET+pUxV1MlY/28ofAeBDY2liBb819iMsejFFRxAqzUhacnVRMJZWeLFmJKXwY7imGLGj0D0X1iLJXDsm0ZpdxQxaa67hJtI6x0k1QzOO2Vqw8BPBpmzMxqwmZcRUI8mWXJsBJ+ZEXTDnm4ykJWVHUA3hXEvzRKXGfEfRjhQrvubh5RpfX2hSDQULPpQdwZKnyJmwSp3b7ZspOQZFW1ByN/LV9uPMtCPCRPFo8AWkligVsqX8YYby17NJX0vKkIgL6zGUUvTZirKtOFmPubYsWfEUM62Y3WIb1TDkvN/m2/XfZz5ukBYOp+QpBuwU51shy37EDe56yskg27N5EqUZU+NkdZqMYbHO6ONg7U/xkhoL8TFM4RAIn4P1T5KWJareWaR0aYbzlNyNSGFS75xmXE9wOJjlx4s7sA1BjGKvvY6arHO09j8YSO9Yu8495v0PvlP/LyQipiK6ww3CaIWGaDMpjyGly062c7W4mZK5HoBdpZ9lp7meWwq/zoqY5au1/x/L+iwm5lrGaI8ePwz8QBVkf/qnf8r73/9+RkdH1177lV/5Fe6++252797Nz/7sz/Lnf/7nfPGLX+TMmTNv6rL8u3/37ygUCmt/ExMTAAhh4YoS08YkGXOASHVYV3oPA6ltaJ2sjWXqIhFCYpllTla+wITYhUJzp/Uuvtx8ioqsMuf7rE82UosiYh0Q6g4CA6U8BAauVUYpj0xqA0IYZJxuYVmPZiiYEyQqoMESWXcTtXbXprYZdl0HXbtbEF60fL9Y+FzJxS6KKyjl0fDOk+iIMT3I0+pbnKx8gQbLrKhJvGB5bXqNxg8X1/6fdTfh2MNrTnjF9CYA/KROGC2RJA38cJVm5xRJ0rysCHu1cVVeMEPbm8ILl9lf/AQviOM82P4kAKvMdMfreZNrRU+SNNbW+UpordYuMJeGQl/8/Gsda3XxuwAS1aac240t0sx1nlkb46Z1jP4bSDKuZMX/t6WY3oQXzFxWHL7V7oFSWBhGfu03vpQ3U77Z483n7ToW8dUQCDblTQ6tlhhN+6xPh7zQzDCY6dCOTRqRZMyNmMg3WA1tXCsmZ0dUAodF3+ZEpUSf63NmsUzWCRlIBfhJd1u8UNcECqohZE3FX59P8/+cKvNTm7vn7HzZxyiZlAY6eOc0518oEnUk9ZUUXmRiScX/nM5xc5/PVDvNfAcsqWknBqZUGEIz1c4w75s8VXE5UtVdGaB2mI2aSAEt0aHfcviZvk+wQe+h5U2S0QWCpEHKHmCnuJXNxfcxkN/PSuMZBgs3kBBxwPsC++TVzLUjXNPgwdoMf7rw3zjiz1MPYxaSBimjQChC+sUm0jqH0vBf54+SszSLHgy5Juszmj2lrlwwbSheaAgGXUEtEtRCxemWSdrQ+Ak0IsG+PpO5tmKuHaMunBIGdR8bGeXigIyirQkSwVMrmlrosD4dcraV5p7zBkJ0i9/5jmLRU7gXgqhvLBcZSUvWZw2ylmCDm+NQfD+GhD9duY9KoCk5klbMWvEhhGA10HwgfReDegMZ06CSdBh1r+Wc910AAt3ClSUGjSxngxozHZ916ZiptsFU2+BUy2R3yWA5ECwEHn0pA1MIXMOkYDi8u/BPGTRy5AyL05V7uN//Cv0pi3sq/55VP+aJ+h+w5MUcVIc5Z5xlSS5xSp/jgDrIaPF2CuY4aaOPQb2Bqj7PjflfoaOqhNESmdQ4HX+GREd0/Gk2FN6D1pqbs+PcV53mkfYp+o0M877HZPA4u4o/QydZpdo6Rlu0KbkbybgbaIs2DmmKDGEYGfrJs13vpT93DYnWPBPdR6wDSqpIIDoshh0kAkuk2Fv8ecbZzuHap7HM7Pf34O7R4y3kB+aKeO7cOR588EF++Zd/+RWnu+GGGwA4ffo0AMPDwywuLl42zcX/Dw8Pv+I0+Xwe173yE5rf+Z3foV6vr/2dP3/+9a9Ujx49evTo0aNHjx49fqj5gSnIPvnJTzI4OMgHP/jBV5zu0KFDAIyMjABw0003ceTIEZaWvhcu/MADD5DP57n66qvXpnnooYcu+54HHniAm2666WXn4zgO+Xz+sj+AYWM7aQoEusU421moP0ErXiDWAS1vkiD6XhcpjqvdrpEwSafWEYqQqqwxnjEpMMwuc4KstMgZNo/H91GW6zlXe4Dl1lEGCzew2jxEK+jKLi3DZan+JLX2CQC8qIpA0g6W6SSr9Ke2Us7uIIiWkdLEMDKEcYOMuwHH6kMI+YrdEMPIIKWLIVOstI+TsyyUjrmj8E+Yaz/DavvkS0IcL0ryTLOIH1UIwgU0Gscepul3DTTq3hRZdxPFzA4cq9RdF6sPpYK1nLLXgtYxSVxnQvaxRe8gjFZYl7mR6eoDVNsnX9LVejVZ3cVOptYRttWPbQ1e0i17/cHNSdJm1LwGgJwzimMV1t77GxlT6HhNWvhGYcvu08g3Qw75N0XpiLQz9OoTvsW8lRloP6hcup9dmnn4dkejsaVgOBXgxSYDKZ/9/VUsqThcS7EpE5I2FE8uDjDvm0xWC6z6KQyh2ZjtsKNcJW1HVEKbbCqkFVkcb1ikjG6WVp8jmEh3uzbrsvDxTQ2qre6x7o5oZM7GHdXEoWTDnhoHT49yYqmPp5fLHKwUuLEvZiU0yZkJdw0FzHoWaSNhup3muVqOvBlTthIiBR8YjdhVUFxfLBGJiO1Fi7pcZVvRZNbz2J/v4xdHfpd1Rh9h3Ga38z4ywsFTVcaN3ZRzu6m2T/FC8+vsSX+Y0YxJpBVjaYOSKvKB/CdYJwcoOxbPJw8Ta5/z4QEm/e/Qr8u0Y8XH+nYBsOwrCrbgz2eWeWpFM5ZWHKxIBroKezKm5oYBQagEfiI4UlGsSyfEGvpdSdYyaCYRVZo8EX2Fp/WjpAzJ+VaCJcEQmh+fiFkJLNqxwXN1kw05g4kMPDgfsD4rMKTg+VrE8VqAIwWLnuJQxedE3UMg+IX+j/BcRfH/GvwAZ1oe1UDx2JLHR8v7WJc1yFvgx5qMKdifGeEva59kWp6mrVYBMI00flKnyBBPq+8ybOQZT6fImzGW7A7/77MVloRT9Ygx1+U7ndM8Gj/GU8l3mVc10tJiUs9xVi1yY/FX2WTcSCtKuK3wj/li5f9kT+nnOagPcqt9LaPJBALJqeY3uErtxhYuZT1CoFqYGLTjZRbkFLZwybqbLxiDxdQ6k+Qz2xhS64hRDKQEjk5xi7uFlaTNSXmYorOOM97DWNJlpHgLCRGuLHFV6p1sEqNkdIHnOw+wN/fT3Ff/z5zgILXOWQ6o73CD9SOsU1uIiJlpP82KXCYnUpyq3tMNhCZiU+kDGD2XxR4/RPxAFGRKKT75yU/y8z//85jm926sz5w5w7/9t/+WgwcPMjU1xZe//GU+/vGPc/vtt3PNNd2b3/e+971cffXV/NzP/RyHDx/m/vvv53d/93f5tV/7NRyne7D/6q/+KpOTk/zWb/0Wzz//PH/wB3/A5z//eX7zN3/zdS+rrW0Wk5MIJBER1xV/iZRRIlAtoDsOSUr3QqhwdGHs1hJaK+biI2yUQ0y1Iu7Kr8M1JZYUtFREEDc5Xv0c/fl9DGWvIVbdgQZR3EIKi3rn9GXLEUbdC0A2NUTa6GOqej9aK6R0qXcmcaw+lI4RSJSO107GL0eStDGki9YxV2XvBuAG4z2sylWCcIFsauSKn9M6Jo5rJHF97bWL45IGM1djmVm8cJGUWaTZOQWAUiH5zDYa7ZNYZvkVt7cQEsPIYJolrir/5IULlsm7Cr/JcnQSgJQ9wMUi6rUWG7aRWQuFDqMVLDO9JuW7KEN8PZKrdGodM+EzlNUwBXOMIKq/+odeAaWjN8V9ynXGL3NafKsxzSJ+uEo6te5Fct+3F6ZZeqsX4QeOOK6t/fsHzS0zZWg0ghMNl8O1HKteitO1AhPphK/P21hSMecb/PSuKdYXGgSJZDjTQQhQWnCulidnxtQ7KUYybQYczWgq4aqcIlSaT88tMOdLzrdh1XcQQmOYir+6fwOkTIySRXa9ojVj8mzNZSzbZku2w/Z8B19JlgODA1WHA1WHvKU41kgRKcFIKsJXkkAJjlRiJts21UhythmywSzjJZqxZAJDaG7s7z6gsSTMJTVM6WBpi7G0w0a9G4Vii3EzG/J3kLLKbDDLrPqKbQWHWqi5ppglZ5q0VEQliCha60l0zG7z3eSdMXKGRSMKWfTg6eWYnCVJm5pbC4Pd8VxWwq6ixjUgZXQt5x9ZSFjyNKuh4I5heGq1ew4+UfeIlMZAkNVptlt3EquAE8kM/SmD2Q5IARrB/sEVlAbX6IZMP7EUceOAgyO7xVSsNeuzDk+vdlAalnSdp5P7mfbanG4EDKQkOUuzOevimpI+2+HxlSaJhtONCC9R2AY8217mlwZ/ibZaZaO+hm3uXWxz7yJlFJiKnmKj3s15tcpIursO/Y7i6nxM0VK0Y8GAa/KA/x22yw3s5HqksAiET0MFtFjl2eonWRTTRCIEYNzOcUvh1zna+AI79B6qYUTZSCORXJv9KSwhqUczzHKcKGnz3dofUrTWc67+Laaq99PsnMKUNgAahdaKc+IoWWnTjDR3lYdox91rX5FROvEqQ+4uHJElUh5NlmkmCygU99b/Kwdqf0zRXU9L1smlN7OT/fxo/pe4mhtpiDYGBg3ZYDxzPQJJqBNuyf8qCoWB2Y0J0Mn3+cju0eOt4weiIHvwwQeZnp7mF3/xFy973bZtHnzwQd773veyfft2/tk/+2f85E/+JF/5ylfWpjEMg3vvvRfDMLjpppv42Mc+xsc//nH+zb/5N2vTbNy4ka9+9as88MAD7Nmzh9/7vd/jT/7kT7j77ru/b+vYo0ePHj169OjRo0ePHz5+4HLI3q5czCEDAylTgKQ/dw2bxLXURYWT9XtIO2O0vO+FM6ecUYJwibHCrUzoqxk0coQqYVvBxYs193WeZJfey3mxQCg85vzDNDunyLqb6ASzoBWGkXuJVPAiF7tM0M0Oa/nzFzK+XArpTQRxE9NwKdrrWOocww/mXnb9yrndaK1wjDxp2UdLLbODG3g2vh+losvW6yKX5ma9OJvKMDJoHaNUQMoZfcm8hws30QhmiROfMFri5TCMPAPZnQRJg3FrH2VV4pQ4RFqWOFv/FlpHaOW/xADi0iyxK3FpLtjLTfvi3K4rYVv9GDKFlCbj7n6mWo/iWiXqnZNXNE/5fnJpjlfW3UTLm8R1xtccJ98OWGYZ28q/xNDj7chryZLr8YOPEJL/46p/yZZszIATMuc5bM11FRCVwCHRghNNh/2lNo6RcLCao2QpNmXbjBWb/Isnh9mYMzEEbMok3DS0wrMrZQ7VTPwEhlOQtTTjbsSOUo1sOiCKDYLQZPNdHU4/mKGY71DcGDJ/PEvTdzjVyNGKJeNuwFfm0iQKdhU1vhKcrMO2AhRMxYwnGXcVR+qSkg3fXmxTE02uywwx1fbZkEnxbHuZ/dlBptsBOdPk6eQY7zB30o4TTulz3OxuWcu7Kql+qnKFDWoDG7NdWeWJZp3N6TytKCHWmlocUJU1TnoPkbIK9Flb0ChGknVMODnGMga27Ip+P1V5jB/N3szZps+PTjg8OJeQtw12lQQLHvxl7SAJEdeKfXxo3CTRgmcrMJERHKkmaK1ZiXxmjfOEusO18ho+MGYw5oacaTvcOlClFjg830yzEnQ/s6NocqaR8HD4FAN6HbGI2WmNUQ27nScFdHRXzm9gsD2XY74TckZ3z5MlVWazW+C4v0xeZ/h2+79TTG/iXfbd9KdMplo+p+RpzjUfI1FthnLXkRJ53p+9FkvCVTnNmZbg+nLMuY5JyoDjNc1zrQrDRp7TehYTk+n4WcbNPRyufoqR4i14UQUvqmIZaTanbmNJn6ZPbMAXLVI6S5sq42ozVVlhOjzAVutWBinR0D6RiEiIack6Z5vfxjKzrEu9g1PNbxDHNa4t/QPOJ4fZKm7ExeGqXJZ2pGhFCaf1LFXdHTMf64CFejceaKJ0F0vtY6zL3kSkOyTE5BjghebXGc7uJSULCCRz3rOMuteS1UUO1z/XvUbrmInSXVytr0WhOawfxRYuFX/yNeWQ9ujx9uXvaA7ZDwJSZihldrCt8CPYwiWlU9T0LNfmP0bHP08pu3Nt2m4Qc5FWtEifzNJRMR0dcrLu8Wx7ea0YS4g42/z22uf8qIJlljCMHFLaXdt3dwOuM45tDa5N12ifXJN51TvniJMmAIZ0sYwsWWcEpSKmqw8gkPTl9gIwkN//kvUasLYxbO2kHa3QTBbYJK7lqHqEor3uisWYlA4aTcoZpZTdiWP10Z/ft7b+SdJeG7OWtvsu+Vz3oh6qFh1/mlzqe46aLydf7JebaAfLLCQnOC8nGRKbmW0fxLX7UZdY8V+KEMZl88y4GxCIte116Y31lYoxKZ3XJO2zzTxCSMKowbn242SdYYK4+ZYXY3C5TKzlTWKZ5ddcjL3ZDnkX94MorhBEtVd0xXy70HU+7Y0l+7uOYeQ5tBqTMRJSRsxE2iNSkqwTsiHfxDEUe4setcjif07nGUnF7CzWqYU2QWiyr8/g+nLAB0brXF1oYhkJk22TOwd87hwM6XMUMx1BJTSRQpMrB8zWcqRTIYtPGKzfWSNdiJg8XCRf9Jhtp1EaapHBM7U0t/RH3DYY81xNMNOB8Qy0YzhUk+QsWAklm7OaqZYmZ9gUdY7nWw0GHQc/0cxxkhU/xhKSmbDJdr0NQwgcKelTAziGYKscYzgZ5VTyXbbpzQQ6puLHnGt5nJeTTHc6nImXqMUBq7JCRIhtZChbmzhTvZdqdI6UsGlFCaYQDDiaoq35lYGb0RosKTmwCoOuyY6iYN7rSg779Bi/0HcT2wpdad1KILhjMOFkXbG7ZLC3zyQh4fbUdm4091J2TBqxJNaCrKH59mKZSmhxqCqoBJAxJbGCed/jI/kbeVdplJ3WGGlTsq8vzWDKYU/J5fpikauzBUadNAASwV5rAwLJgjFD2RGMGyWW5SofH/h17nLeR6Q0odKEOqFPDREnda7P/Rwb9TWU9QjVIKHfgcNV2J5XPLhgUAsFS76gESocbBSao7XPEBOz0bievMpzW+Efs0XvY6d5V/faErc4Fz7FGFezkJzA1i6RCBBITotnOOs/xlbrVo5591GybZaMWSSCki4wnIySS41zvf1jZHRh7brUEjUmjD340sMQklaoWA1CApVwxnuYufpjzDefYbHxNOXcbgby+7Fw6UtfhaktEmKy9HXllrkPA3Cm+hVOV75E25tiItmAQlHKbGNj8X1cV/wlCgyTMyxmxSy3m+8iI/tRvWiTHj9E9AqyHj169OjRo0ePHj169HiL6BVkbzBKtemEK0Qi6OZzyCp9YgN1ucK64ruIku91XsILQdFNf5oHO5+mowOeDr7EIZ5gWBSZFl0ZX5NlhDBp+9MIBHFcI06a2FYeQ9o4Zg7PnyXjDK51m0yziGMPkyiffGYbSdJAqQApHTLOECvNQ7TDRVreJKXsTtJ2P+1wiXRqHavNwy9Zr8nGN5lsP0Lbn6HuTXE8+hY5c4jp6gOXZXVdROsI0ywSxXU64eolr6u15bv4uUrzyCXbr7t9au0XuuvuzyClg2Hkia/QkUqSBkernyGMllhuHGC+c4hZdZyiu54gqr3C7xSsdTNsq0Tbm8KyBgii1Zf9zIs//1poeZNrAdR+MEe1fQIpX3uO2feTl5O+Xok3u8N3aYcyjmtvStj0m0EvG+3vPgPZnWwtWNQjgxONLJXQ5kA1RxgbzLSyxEoQKYElNP/k6nlsqVj1U5xspjhTK1ALu92vWEn8xOBcvcCEm1B0QpaDrpTREILpjsH/8nSJbx5Zx1ixyZmVEofmBll4IUtj1WFooMnZ2TKukWBJTaTAlrAamniJ4Ma+bvcpUpAxod+BUEE1FMx6EqUh0Zqy5TBgZlgJAmY9j33iBu5tfQZfxWSFw0lxinnf40v1P8XBwpHQTCKW5RJKR9xb+08syjm+UPlPnBTPM6TWMStnGBF9SAR5laeiz9P0p2klS2wufYicOcSE69JREedbCYHqdsAi1Q2Fzpkmu0uCP5j5t/zl/BJBAn4CH+gfQeluZliiu+fvqY7JQEqSaDhcSbi5r0g9THg+nuernW8x24EF3+Jk00ABiRaMp6ERaT6z+ic8s+oREPG5+sMsdBQjaQM/1pxuxAy63e+NNTzXqhArjRcrhIB2nDCuh9iqtnCi7vGl6v/FgOoj0ZrFsMOga9KOFDnDxtE2ewofJRABTzT+iGebn2U5DPjq4ip+ojlUlfSnuuvjxd1zSEDIQfUktjWIo1MUdQ4Hi0CERCKiIFwy9iCmkWKjfSOno0cZM3ZTUefoT4ZZ8o+zWH+KjalbiEXMSHovWkNa5xmRRaqijoHBLnk788YMZ+LHGct3Y4MW/KOcDb+LpW2O8l2ejk+SMgweDv6StN2PYw+tSQ2b3izLjQNMNx/tGnxc6M4JJM0kwtQmKVlgrHA71xV/mcHCDRzR32EuOUbOHGKq/gAVMc+qnqKTxKzX48zGddpqhSj+25lf9ejxg0RvDNkbxKVjyAyjgGVmGUzvZLr6AOnUOjr+9BXHSl3ENItsyN+BrV2mvMfpc7ey1D5Gxhmg0jxCKbuTausY6dQ6iqkNLDYPkkmN0/bn16RzhpEnlxqj6U+TJO21+Tr2MEG4sDavjLsBP6yQJI3XNWbIMstIaSOFiRfMrI2h6lrlvvQGXSCwrD4S5WHIDGG0tDZtyhklSXzipPaSz1pm+XUVBz169Ojx/WK0eDu/PXYHOVOxHEg2ZmLmfZNxN8ISmoGUTzu2ONNKcdvwCovtDKdbKVJSc6xhsDnb/dxoSrG3XOO/nynz7qEQxf+fvT+Pkuu8zzvxz/vetfal90Z3o9HYCYIEQXATKZISRVKyKEuyJEeOJTse23HiJT/bE9uTjJPjk5mTnMxJjpPJOHEy8VhObMWWHcuyVoqiuIk7wQ3EDjQave+1V931fX9/VHcT4CaJoiRKuh+cPgCqbt2luuq+93vf5/s88PUlG627MkMp4Lm1mLuHIWVo9uTr1AObWEvmOw4T2RbPVXLsyPj4SvLoqs115Yin101u7AlZ9U2m25JWpGmGmvs7z/Ke1GFCBTvz3Z6sWEPRhjVPk7O6BcFcO6bfNXiwOcWwHmBGzDLBGJ6KyBgWPY7F095FjlX+O/2FG1iuPbn1vqy1z5Bzh1mtP8vu8ofxdbe3brpyH7bVj2uXMKXNYXkn/Y7LRb/O4XzXoXRnDuY6UPU1riHYnoXJBjRCRSUIcaVB0elKzXfnBYboOkC+sK4xBHyt8ywHuJKRjMP97ZfojYcIhE9B53nPYLZbrPqCdV/RjrqhzoGCZqBoxzH9KYsLzQ47sykaoeK0v8pV6T78WPNiMMs1zijmxi1sWwqebM4TiICrrTEeDp8iSw9tKvTqMbbJMq04JCTqugmKJnOcYKn+LEp16MkdotI8zp2F/x8Ggpru0CMzLOsa260yDwT3Y4sUg+xGInG0jYFBSMS0PIlFil69jaaocbLyF1xX/PvU5BrluJ8VYw5Ldx2ka3qRtCwR6DYTqtsusCpX6Ff9LMoFqnoeTUwnXEdKE4HBeuOFrXiaKzLvIyTgRPUzSCND1hnaur4A6C/cgCkc6v7sVuuClA492YOkjBI71H7qssFU+BQps4cBsZO2aDDTfoq2N005dxBTpikYw4zG45wRzyGFxXTlPvKZvTRaZ5KbXAk/4CQ9ZAkJCQkJCQkJCQkJCW97koLsLcY0SjhWET9YZrH5XNcowiqTdsewzRy21U/aHUO+IvCwkBpnsvpVKnqGtjfNcus4frC4JeezjCyZ1DhKRzSCBeK4RbMzhdrIN4OufC+IW8Rxi3Lu4NbsWHdm6mWZXMeb25jZMrdmx14ZMuzYg686No3CDxa3XrM5M/d68jWNJghXiePWljFGLr2blDOC588TRuuv+drXmx37dg0TBALDyFxmdPLt8MrfUcLbm1eGfyckfLcIFCx7kkYoqIWSRxYjClbEkt/9DA5nmxzpqfHcaplV3+JkTSIF7Mp2pXaHix59TshCO82hksI1YtaD7muXvZiXKoqXKoo9BZO0oUgZMdPNLA+vZDndSBEqwVcX87iGxpKash2wJ9c9l27P6K3ZsYW2IlZwsd3hg/lr2ZaRLHkehoCnG8v86dqf8dDaGrUgRgHHam1ipVnqRMSErFIhEB1e4gUe8/+Kx6L7qfgRFT1Df+EGItXeMvhxRBbTcMkZg+QzezF1d6ZjunJfVxGhPLxgjVp7kkl5hhm/waF8if8w83+QtwVPrcZsz2h25ASxhkeWAqpBzLTXoNex6U2ZlB1BI1QcXY14ZClgzRfEWjOQkny0eC0jGYe0AcPxKG3ZYkZ3c7ReqsRMt+DhtXXqgULrbvD2cicka0tcQ6K1Zsh1ebw1i9YQioC5tkfaFFxhbuOofxFbCkwpeKq5yNWpIUb0ACuBTzPqKlD69TihCJjSi3QIKBopstLmpH8fy41jKNXBtnoBKGT20NQeC2KVWEQ8Gt3LvDjP1/2vkpV9XG/cSEan6Ig258SzTMtztGWLpeYLdHQFhWJdXWSo+E5WxAyGNrnAc9g6hYHFtPcU89WHuVh/hOnKfbykH2bWuEAofF7iMSQGlc4kC9VHGbIPMmgeIGUUSbmjAOTcYV6o/imTnUc2ci99qq2TpOwB+gs3kEmNo3VMO1zBNrumS9nUBEr5tIJlqsE0LdEhr3LsM26jE63RFFXqaoG2N00mNY4p0yzXnmSydj8v8Rjz9cdxRJah4s0EUSOZHUv4kSK5gnmLyae30wnWyLhjeGG3sKh1pi4LQQ2jyyV+llmmFSyjVIe1DZv6KG5fJgVcrj1JPrOXVmcKj66dehCuvmr7sepa9VaaJxHCvESq+HKY8aa73qXugVp5l63ntazmLz2Gb8allvfdY17HNIu0/aXXXI9pFr/p+t/o5PzK7W0uH28UqG+Gb7VPLOHtwRvFGCQkvFXU/VkaoWBfLkQjWA0MPjymOdVwGXIj/NjgfC1PqARLvsFc22BXTrPgGZRtRaQga0U8X+1exE42BNUwxVSzW+gd7jGQAsbTIY6MWPAsVnzBRCYibcKgG1ILDQZczV9dDLi6nGbA1bxY0fSnTIIYzjcCarHPrkyWQGmGXRcvhuWOZoUakOKO8gB38AkirZltxjxWW8bSFg/V/4Sb0n+XQYaIiUnHaUIRMuTspCQy1GKf2dqDQFcmL4SFEJKF9vNEcZtF9SJ+sMQcbMnlpTDpye5nufYk1xZ/nqaokRYOp+stfnnkn3GuHnFlyWChIzi27hPqmKpuY8bGlhujJQ28eKPvV0q8WHGxGTPZqTPXsbiikOH55gqHs31UZY2iKnBL/i4MAUudGK3BwaIWhoQoqqHBFyr/F78w/Lss+x7LPmxLpUirDAVHEoYBtjRY7IS04pCrnTHm2gFtFTGtX2QseBcRmvPiNAfk7fSKDDXlIxFM6udYbbxIb+4qWsESQ6mrCdw2Bha+blIWo2R1jnkxST2a50p5K2uN5xkv/jwzok5Ih+P6HP0MMRs+i9aKrNOP0grLzFLzZuhP7SJWIWnZQyW8gLB2dC3oC7BUfxqtIwYLN5E1+plpPkm1PYnMWGgdE6kOdblMMbWdjj9LQy8T6A6RauMFKzj2IKv1ZwFIWWUcM0esI+qt08QqYLXxfLfw2ogjcexBRoq3M1d9CMPIYBopmu1JrPwdTMtzNONlau1JpLBYazyPQJCzhygY2+ik17GNDK1gCdvqoamWWag+SiY1/r39YickfJ9JZsgSEhISEhISEhISEhK+TyQF2VvMeuN5ss4gjpnHsYrdWZpXOAVdOjsmEFsOfNB1XpTCIuduQ2t1mWzOukRWGISrr5nLtTkjpnV02YzBpqPh68kLhbS3/t2VIly+3LcrB3ut2awoqr7uLNi3Mvv2RllU32z27Fvlu52vlZCQ8INNszOJ0nCqYdGOBY7UnKx3z4+hEnxtKcvphsPXFm0soan4Gim6ErmCFVMPBafqafbnOvQ7MdVA88xqjCVhqR1SthWh6rolTncsqmH3/LW84cD45XmLhY5B2Y75ye02gdIMuhG39Gv6XUibgh/bZrEvl+Mh7zinm01WvICnm/P8x9n/gzGjhwsNzYmqzx8s/QXn6yHPxme4Kt3H3nSRd6Q/wc50nrS0uChPc0o/zqpcYEacwNMRIRG21U8+sxfHKnYda4WF58+j4hamkULpkKw1gBQmplmk7E4QRHV2lz/Ms7U/ZrbzDPNiiTPyGM82VwiVwosFFxoRJ8QpfB2zIM8TEWPSlSWWHMHpeoeUIflG+AzjOZt6EFOSaY70ZLiioJmwy8y1A2oskhHdsfN0vUMjDDlWb/CCeoCybTMn5lBa84vDv0vBFgy5Kfodl0f8FziYK1HxY0qqTNowaMUhc3KWx8IXeMD/G55TD3AVN/OMOkqNJoqQUITMqDVOiaOUyTEhrqGU2cty7Uk6/gIXag+w2HyOmJC6P4sv2pxTTzFV/Sp+VOfF+H7uLv5j6nKd/dyAr5qkdY60cOi399P0F+iNhzje+BytzhRCSC4ET7BSf4bJyheoNI/TiBcpZvazWHucYmYvE6V7qHoXMbA4nPoJxvO34UVV/LhBELdox2usNI9zsPRJrjduROuYIGphGhn8YHFr3Ky0TlNpHscxcvTmD+OHawhhbuWWSmERBEt4qo400lhmgXrrNEqHnFaPMN96lpX6MyjVobYxo2aYBULV4Xz9azTaZ0kZxa3rm3DDYbfjL3yvvtIJCW8LkqvPt5hiZj8Dxl52GNe9PJ3vDAHgOsNb+nHoyg5fq5BQOqS5cTLSOkYKa0OSF28VVkKY35YTYRRVyaTGKWUPkM/s3XpcIDb2q2uX35s/vFWMGcbLjjCvJQe79PnvtJDZPK5L+72ksLb+dp1hDPnmwoG/HR362yGwOSEh4e2LbfVzdK3Nl1YXiLXgfFMwmlbkTMVnZwQnqgHTLTAEFC3F/qJAadiZ9SnbIe8ZqHF9b5XthTon6hb9qW7PlBSwq2BxdL1rSf/ECpypd23rJxuaWgiPLceMZgQ9Tvc8NdPp9qaV7ZCHlwR9dszZekQjErRCxZ3pKymbLkusM0CZe0q/zXrk8Vf1z1KLfbbb15MxDa4195C3BFPtFjVZY7HjM5FziIkYMQ7SUqs0wyUm5Qk6wqOY3oEhTNreNLbV3+1JRuDYA7hmgZQzgiEsOv4sUVSlE1epd6ZYC8+Rdscouzu54D3KhDrADqtMxjR4bq3DBb9KUfXzaOd/cCVXs8stkTJM9hYtbCm4upTi2h74R0PXszunuaHPImMa7MspBHBF0WA1btGrxwhR+LGmYFo8EX+FXjOFIR1sQ3C1OYFG88X2wzRDTSuKeT6cJEOJehDzYPANJIKpoMr99X9HkzUifEbsa1itP0tVNJhvPM1T1f9MNZimXxQ44Pbz3tStjGddXvS+xA7jOgYLN+FYfdhmnv7MlSw2XyCI6pxd/ywtf5mUM0yzM4lrFjkvzxLqNuuyQo/cTl7l8HRAVhWwzTw1uU4cN8ln9tLvXkG9dRoh5NbYawiLWusUAJXmcarRRUYzN5BVBfqNHOPxTq4272K3dQs73JvZLq+hlN7F1dYYgVLskNfS7EzSn7mSbGoChNi4Edv9rK3Wj7K64RIJBpXmcaB7vaLRrNafJY5bpKwSo6U72FX+IOuNY5c5PJtGN1g7iqoMmPs4mPswtxd+nX36MCmr3HVglnmkTJFxx743X+iEhLcJSUGWkJCQkJCQkJCQkJDwfSIpyN5iqq2TvFT5M+Y5zWDhJqBr0AFgSvcyI474kvDbVxLHG+6JOt4y4VhvHCPnbus+/CYMDFqdKSrN49Q3jEOgO3ukVESwEYhc78zS9qY39uHVQcyX7+PLz3+nM0ubkkXTcF9+cOPOn9Ihnj//mkYjCQkJCd9LgnCZiVyK67ODfHama4Z0ril4bEVyTdmgzzUZTsG2dDeE2I/hVF1wtOJyvJ7i4ZUC/9/5MuvtFLf0tqkGcDTuzjY4UnBNqTunH2vNxWbXpClldsOmHw4fohMLfCXoxAJLwI6M5r6lFJ/c0SFnxQykDDQw6dW40OzgSEmZIi3ts6aaPOF9hp3mO6jJGtc625n2Gtiym1d2Q0+Od+ZGONyTwhQwU7mfbfSxUH2UAecAvm5yIX6avDGIY+QxjAw5dxiAQmYfHX+WlfozdPxZZqsPkEmNI6VDK1jGtfswhEOrM0UnrjDmXs8pnmQ9DHgiPMFoxiEUIUWdYzx7CxXV5vHwJSwpaYTdIOdYQ6i7GWTnm4KMqTnca2AIzZ9O11j1oS1bbJNlJjIpSo7gfLTMj6V+nFYcYgqHWGsej47S6ziMsJ8/Xf9T9hZsLBwGVB/Lvsd2fSUB3TF2Z+kDLLeOM1d/jKqeZ7h4K+tigQO5D2KZZWwzz7P6SU56q7zQWeBss81HCp8kqzP4cZ1YBaiN8Xo4ew3bstdvORw7Zg7HHmSh+iiR9oiJKKsSJyuf4YI8yTean2KAMgOpKwmFj9YRtpFhqvLlrc9jemMmqe7PXaYGaXoLrPinWOI8s2qVF3mUZWOBjmixGJ9kgDK9xgSx1nyl8V9YFXOk3TFcWcAPu/mgrj2I3jAK0+iuWkdItPZROrxMbbNJpXmctc5Z5lpHX/3dCVa2/r2uLnI+eIxJeZw1WSEr+wnDNSyRZjh/A/vtd1+mwklI+GEnKcjeYgyjwGjpDvrEDnLGIKZZRAob0yzih9Wt5Syz/Lruf5v9WlI6OM4Q2dQE5dzVCGESXPKaV1rVfys27ZuyyU2Zg0AQhMso5ePYg4TR5c6Nm7LB7xWbxSu87HL47drdJyQkvDHJd+rN4zrDWLIrSby6lOKJ9SqG6IYFrwcwkRMYEqoh/Ovpsyx70O/CyWrEsQoMuxE/MdJkyXOpBCYjaXiXe5A1T/OfV75ErKEdCTqR4rHofp5dC9mX1zQjzT/oezezrZhqIOjEkgMFn+3pgGtLEbMdBy+WaA1eDP1GlotiltGswfU9GfbnCtTkOodSP04oAhpinbwt+LtjeW4d0OwvCG7o8clbgquKIXY3g5n9RYef6vuntNQqjsjyHvfHKKtB6v4chszQ8LoxKKHqkM/sJZfeTT6zl97cYQSy6zjsz+OHVdrhKmOlO1mtP8s2vY2CsY1pMU1B9RJr8IVHC4+2rlCRqxxgH5YQrHoxse6+j14Mp2tQsuHLc/6Grb9BVjjECk617+MU53mutcLXK/N0RIt6GPGQ9xmG2E3Fj7g7fR1pUzDPaT6Y+7us+4orzG0MuSk6BCzJaU6rR8iKFJH2KKd3Ukzvpk/swBFZJitf4IXKnxBG60gkJTFKvyhgYHJVMU3GkjzhfYarjDvIp0ZwrAILjWeJibhQ+RLuRqxMrXWGnvQeenKHCHSHmcr9NEWL2wu/zoQ6wFX5j+DpCENYWNohm5ogijtsL92FaRbRWtHqTNFfuAEvWMKxB7GtXnpyhzCNNFKajOor6KXEkNwHgEF3TD8pjnO69jkWgjZZZwhDWKSsMufWP4djFQHwgnk0eqtfXemQjDuOaRQ2+t9fvh7ZbDsAaHvT+OHKq65JNm8uAyw3nqXf2Ycjsvh0aKk1enJX01Jr+KpJTa5tSRwTEn4USAqyhISEhISEhISEhISE7xNJQfYWk3OHWWq+wOn2fQCouEUUVVDKv8yE4/UMOQwjs+WQqFWA58/T8qaptE4D3bthm7NW6hWSR9PIveG+ZVMTG9K/VcSGA9Wl7op+sPgq6eGld7S+m2zO2IWv4baYhEO+PkkYcsKbIflOvXn8YJkzta5UsR7CzlSBVgglR/BSxWOuDcsenKmFHDJ34Riw6kOPY5C1BPOeyeNrWbQWrAUmOQuaoSJlCj6Wfx9SgB9ranHATnmEsazF+aZgRxb6HM07+gQDruJMXbAemNy76HCsZrHoGSz5JiVH8O8Xv0hbRdya2c22NORMTdqAU7XPERJyhbmNjC6StwS9TsSKL8lbislWdzyoBAaxhl8Z/Wc8VFlGCNipr2JU7eHF6Bwn/PvoSe2mJ7ObKKpRzOxHILFkih5nglj55IxBoo0w6JQzQj41ylDqaibUAW4r/CNMBEPxCGfqX2RYlDnZqpLRGc7qJwCY6jyGIyWmFHhxTNqE59diFtpgSqgEcEqcZMWHx5Y9FsUa32jO8qH8z7AWTVKTa5z2H2AX2wG4M/1TjMk+KqrNTMunGihG2IchRNeZMQzJ25KarBDoJofkeyhbDpZI0ysmaHjzHKt+mqnqVzhY+iTQNfGyZJrtDDGSceglz9drs3iR5kDqfZwVz1NrT+EFazhWEUdkGS3dQRB15f5pd5Q+sYOytQOJ5PriLzEZPcGyXOQl/TAhAefkS9TjRZbjM9hmhkj5FBikkBrH2Zhpa/oLKOXTnzlArDrYRoa2N811xt08Uf8vzIkFFIqWWuV0816CuMWFypfYXriDo+EXiXXEZO1+1hrPk0mN0wmWgJdbEWwrv6XIaXsz3fYBYdDxZxFCvmZmmGsPbDhwdseoS2flhZBkU+PMtY7SiBe56D2BRBLGLbyoSq0zxXTrCYxLrk8SEn7YSQqyt5hae5Kd2XdTSu1gxT/VTbjX4auKJ7j8YnrzZBXHrS15wNZFk44xjRxSZgGwrB6EkK+ygX+toOhL19/sTFLKHgAuKeb0y4HR3w6bWvJX7v/rbv+brF9rhUB8S7LLb4Zt9b5Kzvmt7scPGkkYckLC9xatI8azLgeKmnONFmVHEGrIWxpTSGaaIWue5t1DJncMCS7UI2IFebsrs/NiuK2/TsaMCBVoDe04puLHrHoROVNhG7A7myZHhrwlcI3ucq6h2Z72yRiKm/tCtBbc3h8wlFLct9CiHsK2lOJ2624OFFIYAgyh+fxihTVf8U93/BY/3jfMSuAxrPvQwMm6Rc7UrPiSz83VMCU8stS10I81XOH20QxjHq79Bx5t/BeUUOSdEdKixFL9WYrZfcQ6ohMsESufqcq9eME6k5UvYEqXWLUwpI1lZBmPd3JGPEtH+DS1T0qY7M1/gFDHjNh5zqmn2C6voeJd4O/1/izNKOIbwTF25mxerHSYyJsoulb2rVCTpsBTlSozYpEXqn9KRISvFNuMg8SEHLTfyyPhF7ClJGMa9LomezMFxrIueUsyJIt0IsUXKv8XGs18K6SgSszXHqVgOFwI11gLz7EYn+Ta9Ed5Z/4f8qHSbzMhhhkq3syofYQsPbzEC0w3Pfpdh33mEHNeh+dq/42DXE8+NUYQrhJEdXzdZKl5DNhoSTDztEWd4XgUKSw6os1u8xZKqpdBYz8tKqx75xmS+8gafdTak7T9OVqiSrV9llh5pJwRiu44R4q/SDNcpD93iLXWWUrZA5wQz3FD4RdossoF71Fmqw8ShMs025O4zjC1aAbbyNBon0XFDYqZ/aSsV7dThFEbUNhWLyl3G1JYW2PP9uKdpKwyw7nrLovi2exFlzJNMbMfjd6SVG4WevvSd2LLLHlnGyvtrkNko32eMFpHCEkUe9/dL3NCwtuIH66r04SEhISEhISEhISEhB8gkoLsLUbrmIudJwhVh4Y3jUBsuSC9etmXZzeEfNldUGl/ayYrl96NRhNG61hmFtMsEgRLaK1e1xRkk2Jmf3fddPNEHHuQavPEZctsShK/XZdEpcPLXvPNJFCvXP9rhTxr9Dc9pm+FIFx9zRnJ19qP1yORAiYkJLwesdaECq4uZWjHsNqJmGxAyTEZSlsMpCT7ch6mgN0Fi5Ij+Nr6In+2cpo+R7PccbnYdom1YD0QSAQlx+AFdZZjNYO/qBzliqLmp7e7ZExNO4KTNY3S4CnJwysmsRZEGrxYUrZifm7CZaENcx3JjrxJvwt9bje4+o6+MjtyBpVAoxG08BhJu+QtzUIH6qEgUHD3YIEX1wMm8gbtCJqBYtnzWVENbi38Gh8q/QYl1UuP2M5aNIlSnW7WVFgjjlsY0sEyyxTTE5RzB8k5Q/TnDtPsTOJFVSqiRo/YTkUuU5Apvlz9N/SrQWbFEseji9xq3cU7C8P82tAnKNiCk+I4Q/EY9VDT7zg8vtpgvhWSMUxOtWrskaNMyRMM6wHGiu+mRYWzag6J5CD7sTH58eyHWIqaHI3OECjNfNtntuXzROciM2qNlCn5RP//zpWlFL6KWTbmeHf+1zilJ9kmSzhGnj5jFyYGPWaarGVgCMF+fT2OdsnpEnv1QVrapx3FAMyKGfrzR1ijxlrjeQYLN5Gy+2hFy/Rm9qG1z8HCx7vSwfoDRCj69TgxIXmd4dHa/4Mv2oyonVzp3MWSOsNU5V7G8rexs/hjLHReII5bSGHT8Wc5wHX4wsMyuioa03AxZQqtY5bFLLVwFtvMkEvvBrrjt2VkMGWaeqc7k6XRRMq/bIx8WVGiSDlDWyYbSoc49iCWWUZg0PKXqfhTW60YmwoV2+oljuukrT6uLv0s5fTOLSVPGLVY0RdoRSs0/AWkMAlVh57cVWitUDr6oVO0JCS8Ecmn/S3GtnpwzBx+1CCOW2j01tQ9vL5roVKdS2R/Bp2wQtodQwjJcPFWpEwTRk1sM49GU8oeoJjZj2HkyaYmyKV3X1b42VY/TX+BlDPStbbXYbdH7C3qHdmUJmxq2F+JYeTfUMa46aD43WBz29+Jk1wiBUxISHg9UmbXev50zeeh1mlSpsQ1YKrToOx0zzvLXvdcvzsXM5xSfLB/kBucPbxUFfzltMmZhuTomqIaaGKtWfW6F/N/WznLx0tHmGtLptoGrai7vjUvpmxH9DoBeQu+umBwbbnG52YFZTvCkpq9BbgiH3JTT0DG1OzIRJTtmCMlnx5bcXNvRCvS3NbTgyW7692X1/S7CqXhQkNjScl8W/HIcotq+HIP8aQ8Ts4yEFoSiA79xh768ke2nHr78kdYazwPgBdVWW8coyRG6ZO7uLnwq5jSpi7XuRg8RUut4akIw8hzgsdZiI+zW4ySt0w6kUaKrs399eYh0sJhpu1xwl+kKdqkTMkZNcNEKs9K1KIRzFOhQb8eZ6H9POfaD+DRYj1uUzRSLHvdseZs9fP0upIex2ZH1uFqa4zbioPkLEnBkfgxXFV2eX/uSoqmw/XObnYXLN5p3kpeFxl387TiCNcQnFST5AybeU4zy0nmxAJFI4UpBathd3slOcop/34ss0xJjnZ7wRsvsdo6wUD+CHVWMISJ1oq8cElpl7TOYQjJB8u/w7Z4O2tyhQJZynI715R+jgwlJAaH7HvIZ/Zim90CrEGLC96jrDVfwhJpothDo1hpnyLCp9o6jdaKHmcCKVO4zjBh3GKteZIwWse2+rHMMs3OJK3g5XiZrR4yM0/GHqDsThDF3tYNY9NIdwOzM9dhb9xklTJFPjVOJjVOEK6Sz+zFEBaeaCEw6M0fxrb6CaI6s9UHWWs8T8ubouPPolREy+9uX268NwkJPyokBVlCQkJCQkJCQkJCQsL3iaQge4uxzSy11hm0jnGd4Vc9/0auhZuzV4Z06U8foOCO4ppFNDHlzB7iuI5rFQCoNk/Q8pfoyx6g191Nr7MbQzqUcwexrf4Np0ZFENW3whVtqx94a4wthDCRMoUhbaSwkDJ12YxUHNfRaAwjQyl74FUzad/NGShD2phm6XVnA19pHGKZ5cuakRMSEhLeiFBB2tA0lEdNL6I1DKRgzM2xPRNzdTHElDCS9lkPJGU7xpZwbQ9YEpZ9n1hDjys5UWsxkLJYCTr8RPEKfm5wN5HWBEpzvh5zuhbR48AtAyanGjaGUNzW5/MLuxqESvLRMYVjKHJmRCME11Ccatjc0ldlT67F9kyLZ6sOw6mIkh1xc2/A/nzM/oKmGghiLZhuGxgCxrKCnCUZTEl6bJcFvcZw2mHFmMOLa8x7HotyCl836FeD5IxBXGcbKWeEjNHTfW+idVqdqa4BhM5wqvFF2rJF2Zrg7PpnKdgjzFcf5oR4hmtyf4e7nPdwo/EeFuM6eVuw0A65b20JrSFUiht601hCsk30crTxP1j0OxRUiSDWGBi8y/kgeZ0hJuKI+2Hel/0Ee8SOrWDntg6Ykie4I/+rVHzNgaIkZUJ/SvJStcNCO8QQECgIYphvRVxZthjNGDyyvoYpBUOyyFl/DUcYhAq2qREMIbhCH+EKfYR1PYMjJS+GF4m1ol8NcqH9DQZTBymkx2noZUwjRyGzj0JqnFhHrAXnqbW6RhauNLEwkUjG0i6WkPRbKQwsJDAbPMecOsEBczvvdPcxYGa5yfoAVzp30V+4gY7oMOoeYXv+XdSDWfZm7yZt9HBN+kM0o0XGi3cRxh3q0TxKdQjCCnHsYW3MsFlmupupJizi1zDSsIwU7WAFhSLnDpO1BrE2cs68uMZ6eIGM2QfAtsI76HP2UXC6ip1eezczlfs5vf5XRNqn0jrNYPZqiumJrfWnnBFMs0jHn6Xjd3PtMnZ/4rKY8CNFUpC9xWgdo3SIF67j+fNv2Iv0Wn1UAEG4TKR9FqqPUm2fZ6H6KCv1Zxgs3ER6Y9DrzV+L0hElOUo9mme6/g0AlOoOQmG0ThzXieM6SnXDlqO4sbGF7/zXHsU1tPZpe9MoHWIaORxnaOv5zeLMsXpo+UuXBT5/twnC1ctiBWyr97LnXymXdO2e140hSEhISHglC+2QUAvSwuZ2+xbuDx5k1YeSI5nrGHx5XuJKhR9LCpYiUiAFrAWSXTnN3cMpeh0YdCFCYRuCG3pyFCxNn62o+t0etUhpDAFna4oeOyZnavzYQAGRkjy1nmfJNynaPkU7oBmBKxXbUl3547lGhqVOij3Z7o3AZyou64HJ1xYEtVAw04xpRl2HyGfXQk5UYj69/t94YrVJ3pIYmKz7EUrHNPx5PB0AIDA4weNdJ0UjRdrupa2qGEaesdKdZFLjXJX5MCc697I39z6eq/wxnqoxUboHA5P+wg0c5Hr6KJAyBYYQ7HJLvFhrUHYstskSCtiWtgiU5hn1CL2uxd/p+VUUGguTpaBDVtr0uCbjmTT9lPBFQJ9r4kjJlHiBRhxwkidZaZ9kNNXta1oL4LO1l1hox9zUl+aKkk3GFASxJmUKBlImRUuz1FFcV+ghUpr+lEm/KJAyDT61+H/SZ7ssRU2W5Ap9tssefRgvVuRUgbpockw9gGVkmGsdpekvAiClTc4exhAWWsfUW6cB2J6/lbaKsISBLzwutNo8ET/eLfjMUVxpYgiTfrmLjClphYpOHFGjyZw4y0r9aWaiZwmFj0ZRbZ2kwTIaRUd06LP2cqHyJWIVUGm8hECgVIcoqiCF2e1T35AGZtMTrxoLbasfKSyy9gDz1YdZrT+LF9cQwiBWAQ1/nrK1g4o/xUjxdrL0MFn7KqutU2RSXRnpZmi0I7MM5a6jEc5v9a4BeMEKcdy8bLux9jGN13ZLTkj4YSQpyBISEhISEhISEhISEr5PJAXZW0zLmwIg2gg4fiNp3ms1rEph0ZM7BEAmNY5ppEm7Y5SyB1isPY4l0gwVb6YVLBPHdWb95yia2xnN30SjfZZq62Q3tPGS9W3uw6bz4FshF1TKxzJ7t2bCoqiC58+/fGwbcsG2N41r9xDH9e94m98KAoFhZC6bFYtfx3Fxk0b77Hd7txISEn5IkMJiPGtRD8GWXce9PfpavlqdphlqGqFmV15y76JNIzLYm2vzNzOQMTSnqxGxhnYEp2ua6RasyhWW2hGR1jy+ErAaSDKW4L7GaRxDMpIxGMlK1kOD/XmPSEtMoWlHBsNuyIATEWtBNbD50EgdT0n+ejpmxXPZke3wUr0r0V7wTFwD6qEkUF13xYIj+dTqi3xursZsXMEQghudj9Bnu/zJyh9y3L+Xh4KvENFVFZzmKWrRDBcqX2K59iSWWSZWPkHcomAMs6twFwUGKTnjrIsFDrk/znz0IrvKH6QWzOGQplePMSquJC1NIjRnWnUkgqItmTMu8rD/PAuqSskWKOC/rT/EPZk7mGw3mfe7SotpeY7n4q9ynin8+GVpekxEI1T4SnGduIWHmn/EFdzEDe5HWfVCbEPQCuE6cz/bcwZKw4lKgCXBNgSWhM83n+JMHfK2YNWLWQibnG22WNY1WlHEwdInaUQRBZGiwTKroU9N1phhmScbf8wp/34EBo32WfxwhSBcoxkuIZD4qsli7XHWWyfJpiY2Pk8GrjQoWjaDuo+y5ZAXgwgBR+PjZEyDm8wfYyk+zYnOKllLcn/rU9TEOrOVr5NyRlhvHMPVWTxdI5uaQGCw1jnLpP8YZ6ufB6Djz5JyR0EYCCFxnW1k7H60jreMx2Llv6q9IAiXyZkD1LwZyrmDCCEpmNtotM+yI30LpdQOoDuOduIqANvy7yCKKrS9aYKoQhRV6ckdIlRtXFmg0jxOPtWVNBpGBqU6aB11jcw2xvBa+yJB1CAh4UeFpCD7LrLZs/V6XGrNLqXTPTHpkFpnisX6k7Q6Uygd4QUreGGNYmY/tkiTlf1knSFcZ5hG+yyTlS8wXf068OqA5mJ231t/YBsE4fJW4aV0iG31U8oewDDymGZxS67ZbE++5uu/G31bm9b5l4Zkx3HrMtfFt6OV7nfiCJmQkPC9Y7MP2IsF+4s2hhDcUC5wXWqUHlfwYHWec3WFIWA822amneLdQwaNSHBFycCSkDa71vklR7BHjvLXlX+HH0MrDpltw44s/Mq2PRwoCTImnKtFBAqWPJu/uOhyoeUQKsl02yZrxvztXImhdBuJZr5j8YkdghXfphZYDLoxx2oWsRY8uxqzLRXyzgGJJaFoC26xD7Im1+gljyGhJur4SnFD+qewZIoBcx9ZeuhPH8AWKbywtuGU17t10W0Ik7XwHMvBSWosMlt9EENYzIgTDJj7aalVbCODR5NYRPjCwxCCgmFzUZ7mafUEF5sBF+oPsBqcZYdVJm1qVjoRXlzhYrvD3myWBWOWi/IMO/Vebrbez5geY8Zr8cX2A91esfgoX/cfIGMaZEyDu3O/RK+ZomykEQKmmx6B0mgNi23N06tthtIWRVvT6wjO1WJ+PHc9C+0QKWDOb1KVVXxCHG3jqYjTzXvpd22KtsVheQ2nxYtILZlTJxgr3ErRGcPZ6Ns2jQKuPUCkfDr+LMu1Jxkt3cFY/jZSVpm+wvWs+mf43Pq/5vn4DI94n2EubOCQ4tPL/5LxeCeGhKxpskfcyJR+gbm2z/7s+5n2nkIIEz9cY7BwE2N6mGrnIv3uFcSEDKau6gY+K39rfNnsQc+448TKY6X+DM3Oy+NzqzNFECxhGPlucPVGcdYN+15kvXGMlDPCufXPMVi4CRMHA4vJ2lcpZvaz1nieU9W/ph7MookRwtqKsrFkin3cQDNexjDyNLx5DCPTte/f6OsWQqLRaBVs9bclJPyo8Pa7Mk1ISEhISEhISEhISPgRQWit35pgqh9x6vU6hUKBlDNOFLe7jkXS+bbztoQw0bqbz2JImyBc7YYvChPbzBLGbfxgkZQzQsEdZbH2+Le1filTrxua/J1gW72XzUp1t/XGx/9m3p83w/dqOwkJCT8a/L3B32UkI+nEmlqgKdiCpypVbiwXEUDOgj5HI4BYw0xbkrM0RUsz3RaMpTVPrUInVqwFHgrNzkzX5GlHTlAJoGTDxabmP8/9n/zi8O+yIyeoh10jENfQ5MxudphrKEYzHU7XM3RiyWgqQAFTLZvPzra4tpylHUGPI/BiTZ8Lix34H9WH+OX+23AMeGGtK59/MjpBQfWyLKYYVXtRKIbMPNPxGjW5yoX6A4zm3sFU5csMFG7Ej+uEcYdmZ5Ld5Q/j6TquyOPpOmlRQmpJRhfwRBtftMmrMmmd5pHaf2B/6ScJhU+g22xTu/FkB0c7CC3JizRDrosfKx6PjrJd7eWaYoELjYC2ilgQi+RUAYnkPEd5l/0upoIq5zlKWhaZqtyLaRb5RO+vcr5TA6AgUxzVj3KT8U5cQzKRM5ECKr4m1GDLrtNijyM4WwtZCJs87f1P0nYPfdZebJ1it9zGZ9f/DR8p/xbrkceKXOVi8BQ3Wx+grQMMDJ6Lv4ofNWh70/TmD+NHDRrts/QXbkDrmPXWSYZy11H1p4mUx2D6IJ6q0yd3EYgOBdU17tpp9TAfNIlQnOcoNxm38YR6BEdkmarcC3THc61DLLPM4cxPcCp8CEM6pM0eLFKkKbCuZ5ivPgxsqnYUIEnbPZhGinpndqvNQcoU6Kjr0ryhftlUukjpIIWDaaTpSe1itvogUjoU0ruwjCx1bwbPn8cyy5cZg5SyB2j5SwhhknUGcYw8C7XHkDJNKbOL9ebxy8bnzfG6J3cIP6pfNoOXkPCDhwZiarUa+Xz+DZdMZsjeYmIVEEbrCGG+qSLg5X6vNoZ0Mc0ipcxuorhBszOJH3Qdmzr+LFXv4hu6OG4ihNySLHw3ijHgVcVYd1tvfPzfqyIpKcYSEhLeSobSklqgOVcPCJXmoeoifWZmyz49b4HS4CnBhZZgOKWYbGheqHQfz5iKPQWB1pqrihksYbDQCQiUZtWDb6yv0Y4Ey52Ie0q/zVc6j/PkSsAzay0aESx5gk78ciD0XDvFote1ZF/yLeqhyVxHEBJhCoEj4aury0gB5+qaE9UOt5g3UwuhFQmeD6doxzG1eJ6izjFbfZDtTh5Pdoi1piVqVKKLHMx9mCw9CGGyWHucemeKtN21O1/xT6F1zFz7KJH2WIsmmfWf43TwIAYm1WiGilgiIua2wj+irLqS/nowy5w8y3OVP2ZAFmjKBm3tE2tN2TX4QPZ6XGFzpuYxrZeZyKTYpodYNRYwkVwtbuZYdJHzHEUiGVV76M0fZk/uvRz1L1KQKZ4LvsjXO39OM1hmLWozlDY4VQ05VQ35QvMopxoNPtt4jMdb0yx1FEIILohjDKcPU2m8xEp4Gk80eVGf5K7Cr/PF5n/n67XfZy56HtcsUtVtBJIX9UNssw6htWKsdCdaK5qd89hWL8u1J7vOhHGL+dqjmNLB8+eZqtxL3Z9jyn+CUHucDL5OL3lmgwbPBH/Lseg+CsY2ZtQaRbGNi9X7tyR+SnUoZvbiWAWeqP4hOXuYtcbz3cIvOM+aniItS912B6ufKK4BEstMI4Qka/Rd3nMuHZQOkUZ66zG9UaDFcQuNIm33Ml97dKP3y6fWOsNy7cmtHvJXujRWWydxrBJBsES1PUnVm6KcvZI4rtP0F1HKJ+2ObTkxgkQIiRQmQhjfnS9wQsLbkKQgS0hISEhISEhISEhI+D6RFGRvMUG4BHznhhVaR3T8WaKoShg3STkDwOWGFGm7h678gI3nXj1b1pVAqtcNSf5eIYX1fd3+pSQGGgkJCW8Ww8jgGFByBEd6bSZykp8YGOSGPovJekTWFDRCaMddiaEjBfMdyeEyXNejuboYs9Ax6HMUodKs+5oHWp/irJhkKC3JWoLD+R46sSbccOJdbZ9Ga1iTFR5f9mhFMN02aMcSRyoMoRnZyB4LVff8Vg9AIuhzNRM5za2lPv793B+zPSswhGQubPD0eoPT1YgJRqhHAe+y7yBv2ny877cAGBcDNOKAnYxzp/NedsgBtjPEh8r/K+8s/BqHch8nUm2EkPhRg9nqg2itWKg+uiXVa/vznGx+kZwxSI4eluQ0F+RJ+o0sq/4ZjpjvQ+mQ3vxhluMGtrZZMKY5668R667b4ZXFFKMZhyOpbYQKno7vZTgeZd6Y4Yw4gaNdYuWzg2tYNGYJ4hazwXOUVQlLSFJWmbY3TaszxYycRGsYSpvkbYMRtZNRN4Mr8hywtuEYgpWgwyFxPYfklewv/R3qnRliHeLqLA91Ps0h98cZK92JY+QZkvuYlad5rP1p9op3UFJliqntKB0Sqg6DhZsIwlUmSvfQ9Be6HyJhkrJevkbwghUa7bMsdl7ElDaejnCFzXDqGvZYtzLTfoqUdllTF8m4Y1xd+LsUM/sRQlJtnqDRPktP7hAr7ZMMFm7CV03K9k4Wqo9ybv1z5O0RDGlTyuwnCJfp+Et0wsqW9HGTl92hX+0ADRDHdaQw6c8fIe0Mk0mNb5nclLIHgK7sUQhza8zXWtFon0WjMaSNEJK02UN/4QY8f558Zi9tb3pr213HRUWs/belAVdCwneL5NP+FiNlhvHS3Qxnr8GxB7+p0+K3QqV5nI6/gGFkSLtjW4+3/BU2f4UC8So7+66+PEIK6xKHwW8ucXyzvFGhs3nSfi0uDcjelGJ8N/l+F6cJCQk/uJQz+1nxNHlLUw+hE0M7Eix04PH4KWqBJmt2+7wABlOK8YziqVUYckNm2gZ3DlW5rqfKx7YLDpUFf6f8S9yV2U89gMdWmnQizWwr5gQnGEzZvCv1UyzqKtPRc5Rtm4qvmW4qZjoWj66miLWgaEWkDE0rFqz4Bv0pwfXlAtVAcKYuSJsCy8yQtzSDKZslY4YTdHuQDdE9dy8GTY7rcwDUwwhfdYs8X8c8E59EbsacKM158QJpneaAvB2BgZQmg4Wb2JV+F/2FG5hw3gF0XW5tM49DmrzK01ZrFBikrSJy9jBpaVHxpzggbsHBpqDzHGAf/aJAzY8JlWbVU7RCTd4WjGUlP1P+ELszecbVBAN6jIvqOcbMa2jLFuNqgputD3DQvJML8iT3+59lvXUG1xnGsnq4UP0KD9XmqfjdwO60cOhPSQbjEdaCgJqvGHRSrKkma1GbtM5xQ+YTTFa+wKnGF+lL72eHU8QRWRyRRSLZra7ipvTH2e7kGXVy5OUQs9UHKdgjuKLAUPFm5tvPbgUdu3YfdX/uMukhdGNi/KjB12u/T6wVWV1kUJTIO9uoyHVGxZUUnTGmwqcAKKT3Ylk9FDP7KZgjxLGHK/Os1J/p9vM5w/TljzCq9pJx+ilZ2zHNInJDLrkZDyOExDDyuM7wZfvzSrRWrNSfoe7PYRkueWdb93ic4Utuuip6cldhWT3YVi+GkcE0i+QzexHCJIq97rEGK+wo/RjN9iRXlD7OaOmOrcifTeKk3SDhR4ikIEtISEhISEhISEhISPg+kRRkbzHl7H5G1R5M4RJGtY0m2jePFBYpZwTb6iGOW7Q6U1t3tfxg8eVZMfHq2amMOwJszE4Jg5QzwkD+uq1Zu7daDvCtzDx1m3Wty8In47iFZZbJpMbJb4Rlvl0xjDd2yUlISPjhZqX+DBIwBRiia+BRDzV5S/D3+97BtjT0OxF7sh4ZExypMYTm5v7u37f11+nLtbAMxTPrJs0IelzJQAoKtuBwOYNtCA73GPxU+TAAz+iHGRRFdhjX0YgiLCkYyUhcqRlwFacbFquByaov+bP5rrlCK9L8VfUo9VAznIKFtuJf7vgYc+2uLHLVP8OHs3diG4KJvMV4Js2iMY+rM3wjfJqvNP4LZdtmUS4Qa4WpLZ6IH6epAv628q8ZEDt5pPYf6AgPpUNanSlM4dARdQrGMHVW6M0fRkqHIKpzsvIZAFKyxHx0DEcYuCLPJLMcsX+cHjPNgXyOKwtZxjI2tpSESpMx4WBJcsuAYH++K6WzJWQtQVqaFMjSb+xBaskoAzRoUdVtmrKB0iFXm3exPX8rSgX4wSIjxdvYbnSNSJ7zZ5gTCyx3FONunlUqtOOYahAyaOTpMzPU5ColmeaD5d/hY6Vf5r2pm1gLAnapnVyhr0JqiSUMxlM5BlMGWkOoPWyrn7nqw0xVv8pi7UlGMtfRaJ8FuuOgY+a2DKcMI4PrDJNL70YIydWln+W5+Kss6fO8xAsIIamzTE2ukhddp8JQdZDSREqbg+Z7mG58g1h1mKl/A4C0LLE3fSc3GO+mJNP0mBNsi7dTTE/Qm9mPYWSwze54prUi527bMua4VLXySgwjQ9ubZr1xjIXqoxuzXm3WGs8DXROt1fqz+MEiUtqM5m9hJHcDbX+JWHn4wSJZerja/jGuEge5vvDzFFSZmcr9hJfMzPlR43WlkwkJP4y8rQuy3/u930MIcdnPvn0vBx17nsev/Mqv0NPTQzab5SMf+QhLS0uXrWN6epr3v//9pNNp+vv7+a3f+i2i6HJp34MPPsjhw4dxHIddu3bxqU996k3vcxS3OKEeoRrNoFRn64T7ZqV4SocEUR3LyFwiN+y6Jr4cpmhunbg2izWARvssAoFpFrd60ur+HI5VQAiJaw9vLfudFGdvdPJ+JVqr7jFdarNL15mp1Zmi2jr5pvfjtdhc/7fKN+svi+P6d7I7CQkJPwRkLLClZluqexPqqqLiXL07rvQ6ipwVIwVMZAJ2ZT1GUgG1UGJKzULH5ZmFPibrOY6UI9ImuAa8uB4Rac3FZsxNvTGxhtPVkHOtJh/L30WkFdekBxjJ2JgS/nr9DFMtwZFyg22pmOl2N3w6qzMULYUpBB8vHWGyHpC1NO8aiAmUYDTdtcv/eOmjzLUDJnKShXbMcidkHzsZ1n1sU7t5f/6XmPfbVPU8k/IEOV3iWnkDaWEhhcUaswA83/zLrfcl0j4ttUolukhHVQDozx1mV/Y97C5/mBPqEVa8U7SDVVZUgwm1k0PWOKd5mmrkY0lohppG2H1f3zFgUgvgVE2z5AlO1iXLna6cc1saLCGZF0t0qJPWaTwVYWiTtmwRE3Gz1ZVNpingWCWuLv0sZUYYy1qUXcmEGGJQDTDl1TnpL2NhYUnJWXmOBVXltJrlSvZiS8ly3GAl8FjqhIxnXM7Ks8Ro9tuDxFqx4gXMtiLmgyYlPcD23M3054+gdYRj91NQvaTdMbKpCfa477qsr1rrCM+fp9E+S97ZRkqnuMJ4F7ZIUY/mMYWLI7KcX/9bANZap9nv3LnRjiCZlecZz9/G9sK7ALiy9NOcW/8cdVaoqDYPen/FTLsrc8wafQzJfVyV/8nL+tjSVh9SOgjEVpjzazGcv3HrOsMyyxsujOFWD9lQ8WaKmf0A+MEyMRESiyiqknO3cbD0Sap6jqfbf86sWuV09AirRre3zjWL9OQOYRh5bCOD/W1cWyQk/KDzti7IAA4cOMDCwsLWzze+8Y2t537jN36Dz3/+8/zlX/4lDz30EPPz8/zET/zE1vNxHPP+97+fIAh47LHH+JM/+RM+9alP8c//+T/fWubChQu8//3v513vehfPP/88v/7rv84v/MIvcO+9lze7JiQkJCQkJCQkJCQkvNW8rYOhf+/3fo+/+Zu/4fnnn3/Vc7Vajb6+Pj796U/z0Y9+FIBTp06xf/9+Hn/8cW688Ua+/OUvc8899zA/P8/AQNel8A//8A/5nd/5HVZWVrBtm9/5nd/hi1/8Ii+99NLWuj/+8Y9TrVb5yle+8i3v62Yw9FjxLhAGO9R+5oyLTFa/imP1IKVJqzP1bR2/ZZa3QhiXWycIw5VLwholWitcZ3hLZiCESSm7n2rrHEp1sK1esu4QhnAwpYMf12l6S+zN3s3Z9v2krBJSWNQ70xtB1t9+aLRt9aN1RBRXL5MXbAZcvx5SOghhYpkFUlaJlr9CFDcopCeoNI9vLWcY+Tc9K2WaxS3npjeLlA5otXUsGv0d7VNCQsIPNo49yD8e/fscyIccq1nszMYset17m0VbE2tBzlTEGq4sNBECRss1mm0Hy4ipdFJINL35Fsv1LCeqOR5alnyt8zTvtI+wI2dgy+55fqED29LwwnpM3pK0IsVEziRnaQbdmL35Fosdl0XPItKQNjQvViW9DuzPhzxbsXENzXg6ptcJ+adnVvlAzyiT9ZjtG9sZdDUvVQVfbD5Hr95GvyiQt0wypuTZ9gJ77QEmg3XqosrZxld5R+YTrMsKgegQEzJZ+RI7S/dwof4AWivSzgBtfx7bLNHxZ+nLHyFj9BDoDov1JxnIHyHWEfu5gUE7y1LQ5vHOn/OR4v+CLSWrfsD2rEPOgl4HhtyYWigJlKAdw8GCz1TL5mxD0ON0ZaMnqjESQaw1WUvyeOcCALvFKF/t/DnX2R+iZLisbsz83DVQ5NnVkMW4Tp/MEeoYgWBX3uXp2hp7UiVOe2tcme6lYAu8GJqhYs0PaSiP3Zk8odIUbIkfa4bSkmqgqfiKvCU50+gwLaYZ02M8FX2ZSvM4jj1I3h2h1plmJHs9i50XiWIPQ9rEyiNt91Fvn+NA8eMctEZ5MbyIJ5oYWMx2nqHs7mS3uoqKrFJjhZ16L8+rh2iHq/S4u+nTY6R1GoXGoqumCYk4qR7iTvcDSOClaIYVdY7dHMHAQCJ4wv+fpO1eLJlCYDBfffiyMc62erdyRl1nmFJqB15UpdI8vhXiPFS8GT+us944Rtodo+1NAzBYuIn19lkcq4Rj5hg1rsZVKbaZBZaiJm3RJqdz9FsplsIWD9X+bzKpcUZSR1gNzyGFyUr9me/Zdzsh4a3nhygY+uzZswwPDzMxMcFP//RPMz3d/aIfPXqUMAx5z3ves7Xsvn37GBsb4/HHu85Rjz/+OAcPHtwqxgDuvvtu6vU6x48f31rm0nVsLrO5jtfD933q9fplPwCB9mjHa6zIZTxVQ+tw62QHr5b3bVrEZi/pnbpUxielSaA79GR2bxVjKWeEocItACgVYFu99OWPkEvvZL1xbKuoCsJVqq1zrNSfQWtFO1gjCJfxRBNTukhh0Qm7IdaDhZu2es6EMC+T7plmkUxqfGvfDSO/JbcIwmXCaB3TKF52XBl37A2t7pXyieMWnj9PrKONXjtFtXUS2+rdCol07W8eH/B6fV1RVMUwMpcdi231v6aM8fUkm0r5mGYJvfEHEtliQsKPMn6wSN7SrAQmGVOz7EtakaBgaVZ9idYw05Y8X5G0I5OHlvO0OzYvrZdwnAgvMljxXGYreY5V8nx5HtKm4BbrCIu+hyE0aRMmG5p1L8aWECpFxhLsLRiseIoeu3vz63wjw0SuyeFSnZypKFgxHx1tcmUhoB1JbuzxOFT0yZgx55oOQ7qXNV8zlJGcqAR0YnihIujEmgm1h22yxHmmqIfdG1BXp4awpWS308OoHuG2zN/jvHiRYT2ApR1cnaU/fwRP1xnP30YhvZ0wblFIT9DxZzGMPO1wlanKvQyzl3L2AKZwycgehu0sz8dnsITBwfQHiDUc8xZY1XXubb3IyWrAl+abtGOBFLDiC2INgZJ4SjCWgR5H0+to9hcNUqZACKj4MROMIJDsLlj8b6OfZCKdpdc1GXVy7E4XyJhwY7/FbT09PKMfx5UmV5ZcBlNwZaaMJQXv7esnbQpO13xO11uc6VT4avP/Y96Y4X/WP4vSEClY7IQINJ1I48WauXaIryOqeg5PB7hmkWxqgjCq0AnXMQ2X9eA8bW+a/swV5NxtBOEqoepQyh4gpdPEGg5Z4wBILbnO/hD9ehyJYFD3sE/v5wX9DVbqz9DqTKFRHK3+EU+2/4KL4iUerP07LsozrMtlKs2TaK1pxzE7GOYW83YsTEacDBOZDNc5H2LIOEBKlFhqHOXK0k9zRf6D3Fj8B/TmD+PaPfTmu72Mnj9PRvYybl0PdMfHidI9jHIl641jAGSdIYaKN3fDsBvPEoSrNNpnu31ldHiy/v/SiEMMDOb0CSqyQqg0VVkjl97NhPtOsqrAgLkPS6ZJSPhR4W1dkN1www186lOf4itf+Qr/6T/9Jy5cuMA73/lOGo0Gi4uL2LZNsVi87DUDAwMsLi4CsLi4eFkxtvn85nNvtEy9XqfTef3Zon/1r/4VhUJh62d0dPQ7PdyEhISEhISEhISEhB8x3tYF2fve9z4+9rGPcdVVV3H33XfzpS99iWq1ymc+85nv967xT/7JP6FWq239zMzMALBYe5Rae4rl+AyrnTNoHTFg7qPaOolh5Ek7w5etR6kOllkmVsFljwHk0rtpdabIG4NYonunKO2O0ZPaxXz1YaA7CxaEq1Ta56i3Tr8qZ2xzXYu1x7ekjZXoIm1/YUv2GITL9MldW+GSPbmryKR2YJllhJBbsr/NRl9D2lu5YilnBClTRFHlsu02O5Ovyh671HDkUuqt0yjlo5SP1oowWieKqjj2IEH48mzUK2fcNo/19WasurOOxtbMlm31E4TLrynLfCM3p00DktfiByW4MgnDTkh46/BieGgxZNmDZ1cjnl9v04oEDy7X+ZOFWS40NLGGtcCmx1ZcrOeZ7Vj8sydHmOukaMcGsZb0OSGHewwqfncG7NpymuOViHYERVvgxYolD+pRwEI75ulVnzsGYzwlmGkbXFGoozTEWiCBPsfnTCNNLTRYDw1MoQlVd4YpZ2oO96ToRJqdWc37RwwG3a5ByZoX0We7rMdttqkRGsrjC+0HcA3BS94SZ/017q3+G54MP89s9UGO8RSzwbMIJDVvhpnK/Zxb/xzrjWP4/gLtYA0pU+TcbbS9afaXfpKW6DoOz1YfwNdNfKWYUOPcX/u/WRNzfKH5adbELBW5yoXa1+hxLLa5aZ5ZE8y2JV6sOV/XLHgmfbYia2pm24L/PDvHkKu4qU+zK2+yt2gxlLbYb4yQt6Df0diGIGUK5vwmlnz5widUMMJ+RjIWthQ8uxox3fY43aoRKQgUlGyLvGmTF2n2Z9/PLrWTIesg016DY40qc2qdx1Y6TLY61MMAL45piw4pUeIkT7JUe4qWN002NY5rFSm7E8Q6Yrx0NxV/imr7AleXfhZDOuw2bqQil8lZkkApFjvHKKt++q0UgQg4L0/h65iKblEyRpEyhWkW8VVzo0VhgIXGs+wuf5hGvMjJymcoZffzcPggWoMpu+PANjfNRb9OpGDMzbHfGMEQFu/P/yotKuyW2/CFT8oo0e/sox10JYtjpTtJ6TxNUUUIyVDx5u7vlK4Zl0BQbV/AwCKMqmRT493HhYnrDHOh/Q1K2QO8oB/lRXU/6+3zHG98jmOcJCbCNjKM6kGOVv+IHtWHJv6efacTEr7f/GBcTW5QLBbZs2cP586dY3BwkCAIqFarly2ztLTE4GDXUn1wcPBVroub//9my+TzeVKp13focxyHfD5/2c8m+dQYftTA8+dJu2NU9Ay21YtlZul1dnePJbOftDuGECZKB8TKu2z9/YUbaLTPMlS8menG4xhY5NK7KbrjuLKwFaC4Kb8TSDKp8VeHQ79GEePKPEJYKB3S8We3HJFsqx/byJAzBml2JunJ7CXtjuHYg6St3q0CaFNPDtDxZxFCIqQNdIvITUv7S4uVrtX+t/Zx2yyOgnCVrDu09fimi9OmzNMyy1thk69FszMJl5zQN/fHMr+5DPKt4O1UBCVh2AkJbw0CgRcLIqUp2oKSY7C3kGK6BftyOcZFV3Ex2/L57LTgXFOy5Nk4UvPh0QCBRmkIlaQdS6QASwq2ZwWGENzYb9LrdEOQQ62IFUzKM5Qcgxv7us66Xiy4ubfN/5wpEylJNbAp2xFFJ2As3XX2daXmpbqLKcCRirTZLWIqfsRsW3KhZXCypqn6mim9RN6WXF0oULYctjlZYh1hG3BNeoDtVpnbCv+Id9of4qbCL+OKPGV7J03W6PizW+9Nb/4w2fQupDApZnaRtvooZQ9wsvIZ1tRFbJllT+knKItRnlZP843gc2wr3sqqf7bbN+SdRWrJcP5GXuwsYQiBKQWnqiGtCFb9gLFUyEogmWoJ9udjfnP7EI7svqc5S2NJsKWgL2VStDUFK6YTKT7fOIqFyUI7ZKrVLca8GI5k+8laAl9pDvWY5AyLrHBY9zW5jeGzEYfEWlFjEUNI5oMX6Aifi/IULVHja43/xOP+Z2lqn7Rhcj5+EoDl2pPsLN3DoeIncYwcUljMVR9i1LmWFAViFRCEy5ja5AbrHpqiwRXsYbkTojS80/kJtjt5GlGIJ5q4ZJmUJ+iTOQqqB6U6RFGVTrhOGK4BoFSTjqqw3jxJMbMfP2rw3tQdNFXAStSiFgccDc4zYGbpT3WL9bRpMKF2YgjBAa4kZxn06jKduMK59c/hBUtkUxM0o0VW9SShbtOTO8Qw+5DCwBTdnnAhXcJwhfnaowhhUbbHu9coOsbz5+n4s0hh4kVVqq1zFNM7MKTLtng7TVbJm8N4OuLq0s/SlM3LbPATEn7Y+YEqyJrNJufPn2doaIhrr70Wy7K4//77t54/ffo009PT3HTTTQDcdNNNHDt2jOXll2c47rvvPvL5PFdcccXWMpeuY3OZzXUkJCQkJCQkJCQkJCR8t3hbF2T/+B//Yx566CGmpqZ47LHH+PCHP4xhGPzUT/0UhUKBn//5n+c3f/M3eeCBBzh69Cg/93M/x0033cSNN94IwF133cUVV1zBJz/5SV544QXuvfdefvd3f5df+ZVfwXG6dxr/wT/4B0xOTvLbv/3bnDp1iv/4H/8jn/nMZ/iN3/iNN73fldZJep3djBRvJ2P348d1CqlxfH+BHr2Ncu4g8UYumBAGKm7hWCXg5VmVgjHMaOkOsrKfjNOHp2vssW8lI3toxsvkzWHS7hhKdTCMzFaO1ytROsQw8phmkVL2AFpHlMQohrQZNQ9Tzh1kn3UbEkk5vZO6P8eI2slI8XYWa4/T6kzhB4t4UQ0hDOBl6WEmNY6UDnHcojd3iJQzQqN9Fj9Y7Bp/XGKeEYTLbyj922TTzCOX3k1P7qotx0XXGaZgjtCbP9yVHOqYIFzekGkar1pPZkMqsekAVczs39ivbp7bWyE17GawdGfzDCNDJjV+2Xpfb1bq0pmzbzcn7fV45SzhK2dGLw3iTkhIePP0Fa5HChjN2kw3FYYUnKv7pEwIYs2MWmPJ8xjJOKRMyWxT8cCSZLIp+OqCw1zHItaCo5U0sRYULcUt/ZoeW5MxddcpsSIYdBUfHLW4vifi5/quYWcOWpHgTMPkmmKb3lSH9ww0aYQ2h7Yts7NQ58vzZSIl8GLJ3lybHlsx3bE42XC52DZZD+DqHptAdbO+duUFgdKMiwGyliBjCmwp6U8ZXMXNBDHYhsASgjnjImXbZodTpF+PENKhoyqk3bGt9yZWPsPu1RTdcfYYNzPMXraZh+gv3MCVvIM9+jBSSy54jzJTuZ/99ruZqdxP0Rljp9pB0RlDCUUrWmZZTDGW7ZqkTORNripqPjDSVWL0OzHXlkJGUj6hFjQiyYFCkxvKTTKmRgEzzYDplqAaGigN92SvZU8uwzsHbby4m/32zr6IIz2KAVczlIJaCANpE0sYPNVcZLYZs+h7NGjRFG1SFKipDvus23i+9VkAcrrEodzH6QRL1GWdUCsOG3dQj+cpZQ/QGw8xqHu4WtyK1vHWuLAaTzKcPoxpFpnTJygYNhOM0Oda+DpmR95kdz6FLSUK2KV2UtVzjKv9PBz8LRXZHU/T7hiN9lk0mr3ynYwX38tOfRW35n6JW+0f5zbnY1gSxlIZJlJ5tqdTvDe/m71Fi4W2YtnzGc9JDpfTzKg1vlz/A1qhYlpepNqe5ObCr5Jyhmh5UwAsVB+lxDBDxgEuxE9RUL204zUss9xtwbB6UDpEqQ5TlXs3HuvbGqO8qLYR+hyy2niRIFymKVoMqZ306G1YwiAm4mL0DMEb5KElJPyw8bYuyGZnZ/mpn/op9u7dy0/+5E/S09PDE088QV9fHwC///u/zz333MNHPvIRbr31VgYHB/nrv/7rrdcbhsEXvvAFDMPgpptu4hOf+AQ/8zM/w7/4F/9ia5kdO3bwxS9+kfvuu4+rr76af/tv/y3/9b/+V+6+++43vd9aBUzXH6JP7KBojtIJKghhYFk9TMZPsN441j2BatXtndJhN8T5Eunfin+Kmcr9rIcXqDZP0PAX6IgWjXgRISQXKl+i7U2TckbeMMTRtnoppLeTdgbohBWKmf3EhBzOfJSTzS+yx+hqwBWKtOyh4IyxYEwzX3t0ax2WWabRPntJyHV3H9ve9NZjtc7Fy/rg4rj+hvu1ySsLhyiqUsoewJQ2WqstOaXWitXgLJXWue7/Lyl2NvfhUrxgZeN1ETVvBi+qbexXiyiuvWHP2LeCvSHh3Cyo4rhFGLW/pfVevu9vjSTjUqmqlCkMI7ch7ZQbz39nx5uQkNDFlXlsqTlQ0Fzo1BlKwTeCz7Mz27U/P+D2M5ZxAUiZAkPCn1c+zXOVNp+ufh4hYMk3qYeCyZZJNZTMdyS/fuZTxBq+NBuytwA5U2EJ8GKJFwsWOzDbihl0FY+vpZluZJlqpTjfdKk3XSqew5FSm5mOzUNLislWipm25ES1W/S1I3ih0uFMLcKWgm3prmTvJW+R/pRJzhIcr/hkbUms4HA5QytSjKZhOCN5X+YqSo4kZ0lOR4/QiSuU5Cj73TuxrV6kdBi3rqetK/SJHZwIH6AmV1lR53BklmljkoZoMOM9ww73ZoaKN9NDjoOlT3I113JeXiDSPh1do2huJ9RtcpYmUBpLCjKmItQw71nsyrYZcH0sqbpSTSvmuUqOWmjhxfCl5lGaG+PRoifpcSW9LjzemqURCoJYs+TBxbaJFwtWfcFcG75QPc29rRcZzdo8U/1/MaWgQYuaWEeh6VUDPBt8nosc40D2/ay0T5LWqW6gtFkgrTK8qI/hCIO94h3sNm/Bkx2WqXBOHmel/gyGkeds46vsEzfRiBe3PlfT8TovcZzFTsBpcYyKr4kULHs+vo54oPNpruRGluUiUprMtLqySC/otlyknBF6ZJYLlS+REQ6rcoVFXaVs27zUWmdHTrAjZ2BKgQJircnbkgHX5VwtZtVTlMizN/8BTqgLnK9/jThu4mB1nRy1Ioi6Y3qFeWJC+qy9nAkept6ZJgiXkdK5rKVh88ZoEC6jdUQmNU6vsxs/XEPKNBPFuwCIRMSYXWRU9iCBXtWHwMAPa9/Nr3JCwtuK126+eZvw53/+52/4vOu6/MEf/AF/8Ad/8LrLbN++nS996UtvuJ7bb7+d55577k3tY0JCQkJCQkJCQkJCwpvlbR0M/YPEZjC0a49RTG0nVB00MeuNY9hWL72ZK5ivPkxv/jBrjefRWmEYeWwzjxcsdqWLr5jpeaOg5m8nnFgIk7Q7Qo+7m1a0Qqg69Dv7OLf+OUZLd7DUPEYQLjNauoPV9ml603tZbh3HDxY3tpVBCAuBJIzWX3MbmwGRbxYpLBDmq463lD2wJVtMOSM4Zo5q6+Sb3k5CQkLCd0I5d5DfHPoQu7IRj62a7MzBv5j+PP+w/8dxDc1kQ5O1BJGCoTScqytaoeKUmmZUD7Eo1vhg7ygvrgfkLZOH/ec5LA/S4xpkTMFIBgadiJXAZLYNKUOw6mkyFmRMQa+jCJTgxXXNeE6yIxMhgZlOV5o3nFL80VSN9w6UuNDQ/Mny7/PLw7/JsXqDfbkchoCVTsTn6n/Mx4o/zxUlSahAClhow1TTY0fO5WS9Sc6w2ZmzsQ14cd3DFJJe1+Jx7wznGl9jW+46HJFjtvPMliPuQPYqVtqnKKV20I7WabTOUM5dzXrzRaRMbSknPlz+35jUC1xhbmMhaDORzvKcN8eK7oY6b9dXMmbnUcBEzmRfPuJMw2QsrWjFgidXYnbnTW7q8Xhy3eWKfEjaUMx7Fg8sKrZnDcYzmq/MhVzXZ3OiElMNA1xpMpC2+OvGV7nLeQ9f8b5M1ujj3e51zHQ6nBMnydNHSqcYkkWO6qM0o0WK5nZW/NMMuFewHk5uje39mSuRwuKAvhqB4Gn1AJZM0yd2kFYZZuVpasEsI/Y1OKRoiio9aoBFcYGL1fvpzR2i0j5HHDfZVriF5dYJdmXfTVYXOOHfR9ruI4yb1FpnGChcTydc33JtjuM6llnGMrO0vWluKvwyz7T+nGuyH2NRTHKjcQRDdAOzV0OPGWOKq8U+MpbkEf8F3pu5hrPNNsOuS8qUPNmapcYK1egig+YBUjrDtHqBteZxHKuHjj9LT+4Qtc4USvmknAEsmSJrDeCr5mUhzlI6OFbfZaYv8LK8flvhFkzhMF39OtuLdyKQTFa+AMB7Cr/Jo95n8MOV7+i6IiHh+88PUTD0DxpeMEelc4G1xvO0gzWGijcznL2WRrCAlClW689uycfiuI4fLKF1hFL+q/qaLi1OLu01EkISx/VX9R+9MnQaNvucIjr+AtOV++iE69Rbp1nyTmCaRVbaJ+nPXMGVpZ9G65gwbrLUfAFjQ5bY3c8WUVR9VTF26faU8l/lKvh6gc2vxabmvHusDlI62Fb/ZVK7jj9LtXXybeVe+Hbm7fg+/aDEBCQkvB7rjWNooGhFmAJ67Zh/veP93NzbYcBVeLGiFiiqQcwLaxEjGYOUKelX/SjgtvwIXqzZkbPI24IcPbiGpB1pPl39GmVL8fCKybGKZiytKdvdnqiVjqYeaE5UBU8sRxwoCdZ9TSOSNCJJOxKkzW4o9Tt7SpysxlT8iP917Dd5srFMv5VioR3gSIi05u/1/QKx1tgSTlVjWhE0QsW2tMNKJ2LYSSMRLHcUjRCWWOeEOIUXK3rVAIO5a6gG0yz5x+lz9yKEpJiewBZZ8u4ItswikVs9u8XMforp3eTSuzGMPArNuBjEEIJ9uRxDacmKvsB2fSXD7EWh2J4zmA3qVILucQpgqiVxpeYjY5qriwGzHRvX0LxQtXim4lANBI0w5MHKMlMtwVXlbr+4Ato6oMc1eb65wgczdzLjN9gtbkSheNg/RlZa7NFXkFd5HG1jCMF2tY+sOYhDGj+sUI8XcY0SE6V7sM08694kjXAeQ0jOynOs1J9hvvowCkUKh+XWcZqdKZqs0RRVqtEMISGeqlNI72a18SxRVKU3d4jZ6oO4doml6BSLYpIgqqN0SL+9n+3FO4mUjx81GC3dgd4YL6O4ShDVGSrejBaq646sU8zVH+NsvMhK4HEyniUtLW53D2BIwYoX8O7UIRTg6YCpToNnm8vkVQ5DWNxovJfT9S8RiABHZlGqgx+87EYthYkhU7Q6U1RbJ4m0jyOzlzzfbUVI26+Ouill9wMKT9UJdAelQyrBBRQh1xd/iXcWfo0luULa7k2KsYQfKZKro4SEhISEhISEhISEhO8TSUH2FiNlHj9YRMoUnj9P3Z8j0v6WacelFDP76c0fJuWMAGAaxa3nNqf1pXQ2/t99rW31by2nVGfLlVAgXtNEI4rr9OQOkXa2kU1N0PamAWi0zxJFVTx/ntnqg6yqSdY65zCkSxitby136T68msvdDTfNKjb3NY7r35K73yuNPTZDooHXlCcmmVrfGm/H9+lHyVzk7ThDmfCd4zrDlGxN1oq4qTckZcRYUtOIzK18sh5Hkja7GWN/tHofJ/1l0tJiUp5nuhnyJ+tf50IjZKUT42iXi36dTqTYzREiDXcMhBwsCeY7krkOrHYiMpagGmiWOxFXlCwMAT1ON28sZyquLgbkTUXRhn4XduVN+lMmu3OKO8oDCCG4oc/mXD3giqLNTMsnZUoCBSNZg1hDyZFYsputNpCWGKJrSuLHmiHRg6UdJoN1nmz/BQUGKds7sYwMU5V7ybpDxLp73nZklgwlcvYwvfnDrNafpdY6g2PkSVlltA6JtSbWmpQp6EQKpaEWzLFqLDKln+eMeoweB+7qL9HvCubakkqgqYeah5YUz6ybnGpYvFgVhApaUTeLbNGDK0suHxvqJ9ZgSU09hMejpznN07QjRYksF1ptVuQys/I0R+S13O4e5ATnOCGew8AgIxwWogYn9aPMVB8AYCx3MxPiGtY75+jXI1zh3IkfVum391NTHSztMFS8mb78EWJC1uQ6puGilI9GUYvnyRmDGJgEqrnhNqiwzDKdcJ1MahzXLGLJFIN6AtNIM2h0jbjWgvMUzG30pfez0j6J0iHl3EFGiu+ikBpnofooZXIApITJu7K/RL/u4aJxAVvbvMhzPNG5SCeKeUY/TCNU/HXjq+SEy0mexNE2j9T/E9vi7UghuCr/EWJC1r1JoKtiAbpyRR0RRutdAy6zSN2foyRGKWUPdMd8YTKYv4Fq++xl3x3DyOAYeXpzh4mVz3z1YQA6YYWl9nGOdb6IRHCq8UUqSWtCwo8YSUH2FiM3LNhLmb049iBh1MRT9S17+O4y3QJks9jwNmziL5UEbrrmbRYmQlj05A5hmWlcuwcpHQYLN6E21qnRuM7wZfsiEF2Xwc4UGkXLm8YwMpRzB7fkhkJI0u4Y8UZItB8sorXasjJ2nWFsq2dr2Uu5tIdNILYklC9bweeJ4kb3mN/A3n3zRP9KNl/7WnyrdvFCyA0J5FtjL//d4PUL3oQfZN6OBXHCd47nz+NKjS1jzje75/L/eTEmZcQ0IoEXb5z/BLTjmJ1ci4nBJNOcXf8sC1Gdu9zb8eKYgmPQFs1uEHHkkRYOltRMtixeWNc4BpRsqEY+Qaz5mvckRcfg8ytznG9APewWHANuwFDKpxlJXqpoBp2XXVcF0Ik1oVKUbc2KamBJzTv6XfbkBTlT40jBQkvhx5qUCRW/67qn0LRCxblWk+f1U8x4z9AvCrwn87O8VPkzLlS/gmsUyKV3s944hiEcKuEF5moPd8OgO2cJojrZ1ASuM0TVm6JgDNOTPUC/a7Mn71B0BL2uJFAax8zh6gw3ytu5Ut7KQhsCJZhvq+4YZ8CZRhtLCOohzLW7FzF/svocjgFps1uULXUU003IW933CGBU7WVMXMWnl/8lbR0wlk5zT3E3Hy++g6F09/e4j538ePYdjLoZXMOgJNP4UYOUM4wSih1qF8MbN0QdbfNc8y+5MfszDMUj5ITLhfY32KuvoxOusxSdwtI2YdQGoMAgEolGsSgm2WYewjK747DSPs3OJO3ORcK4iRCSHnLcnf67DOlBUjrPDdY99KohGuE817kf6b5ORaRFiQFzHwCPR18iLXt4IvoyAJPyPD1qgKaskaefmJC68llrvkQnirndejdLrDMk9+EKm2sKP4MlDJ7VT3AheIJQ+JfdnIXu+F7O7GWwcBOV5nGyzhBZZ4iUThPELfxgEdsqYYqXr3kyqfGtm8aLtcdxZJaGN7flopy2ewii7vXEvDGDbeUTuWLCjxxJQZaQkJCQkJCQkJCQkPB9IinI3mKiuIJA0PDmybndGau1+nMo5WNb/QgEKXcbUqbIZ/bS8ObQOkLrN74b5FhFoHt3yjFzGDJDpXPhdWeXAKyNma04bm7kiETEcQuBsXXnSmuF5y+w3jpz2WuDqN7N2RImnj+/tezrodGvckhUqrm1nVc+960YfrxhRtcluVtvxFbW21uU9/XdILkTmJDwg0PaHcNTAksqDhZ8ep2Af7hHMd+xyVuakYxN1hIcLsM9IzbvHyxxXj3D9c4ujhR/kSP5Hla8gLJt80D7JHvkKLvzKXZmMvQ7Dr12xNUFjytLAi/WLHbgonGBUMGgnmBfQfCRgWF2ZKEZarxY8rm5FI3QJGMqbu7TmBJC1c1Ba8WSi42QRhxyoiYYMvM8ueLhxYJmJHixAo+tNuhNSbZnBc9UalxVNik5kjNqBteQHCrm+DvFd/K/9P0083qd8/IC46W7Gchfh0WKKO505WoyS8bsY2fpA1xZ+mmK7jhpq4+sPUDBHaXgjuLpetdVWEMj1DRCWPUUa57mSnErRVXgsfg+ikaKM3Wfh1crPNm5yGJbM9+KOVLOUHYlrVBxslHjq62T3JW5hoqvmW5BoOBzjb/meL1JPYSFdsxT6zV6jQyLYpIjxV+kbKTJWoIvVSep+hoJpE3BA/7f0Ik0J/xFLCmpqDZKhxTdcZb844Q6phNHjGSuY864iBCSrHDRKL4R/i1CSB5r/ynX2vegdMgcJ9iffR/7Sz9JVucoy+3UohmG9U7mo2O0/a5RRjmzn5Hi7QwUbsSPGkTK5yXxHMtxk0CHBKJDjSbPtf8Gy8jSlE0MI4MhHea9FwhEd3zrt/czWfkC26xDPOp9hpnWkzxR/UP64yG26SEAHqr9e67Mf5Qv1P4dZ+NFDEzqrHCSo8zpE7S1v2VKcnb9s68aq6UwaQVLtDcUPaaRotq+QEo7FJwxRoq34/nzrHvn6csfQcoUrlmkJ38Njj1Ixh1ntvogUVTtmnQJSRh3KKYn8MM1puoP0epMUcoewLb6v3df7ISE7zOJ7f1bxKbtfdqdwPMX6M8foebNYJkZWt4CWnf7ogwjjyFdoriGEM6rZH9CmEgjQxRVL1v/SPF2xIYcUiCpBl0ZQbMzvVVsmGYRKUyktAmCla1izTAyW4WRYeRJ2b10glXSzgDN9jk0+g0t9r8ZAkEus4e2v7S136ZZfE2bfMssI6W9Zan/3UYgMMwCcVxHYHSLXzS21XtZgGVCQkLCt4JjD/Kvdv0i7+qv4CuDyUaaoVTAbNvBMTTPVSxu6+vw5LrLrmwMwGTLYLkDloSBVPfvNV+QMTXn6pu9VJIeR5AyNNcUfSZbNkueZKYVM5SWFC3IWppACV6qaGxDkDHhJ0Ya9KQ8Vjsp/FgSa8HphsuurM/RikvWhJIdE2vBeiC5b6HDR8ccWpHEi6Fka6TouhjmTIUrNfOeQdlWTDYNDAGzLcV4TiLQTDYUi57PGjWm9YuYwiEn+2nrCv16nHWxQExIhhJKKGbaT3GFezd5nWVBzpHRBQAmzF5GMiZ5W/D/LH2Be9I/Rn9K8EKlgyUkectkJfDJGRYZ06AZxizHTa7OlfhK6zludw9R8SP2Fi1WPc25VpMbe3LMtRSPBM8wqvZgYLAk57nB2UPRESy0Y/5i5V/y0Z5/wqEeE9eATgx+LMhZmk8tneYDxb0sdzT+hvQ0a3XvW3uxRgo416lRkxXSOsuKmOEgBwl1TNGyibUmaxl8pfMwe/RhFoxZTq//FbcXfh1PeDRFA0XMYnR8wza/H8cq4IcVBrJXE2kPgF4xwc2ZcSp+TD0MiNBYSGbEIo528YVHSqdpiyaeaHJu/XMMF28lI3uYaT3JaOYGGvEiflyn195DS62RkT1sj3cwKc/Qr0doigbHq3/B9uIdeKpOWvYw33524yZmgGMVsc0MWXOQ6cp9ABvuxz3sTd/Jmr5IoDuUjNGtYzymHsQx8oSqjSEsVprHmSjcwaL3El6wRhitb429mdQ4rc5U93g3+gx784eptE5jyBQ5d4ROuP4qyWRCwg8Wie19QkJCQkJCQkJCQkLC256kIHuL0VpxoPhxGsECpdQEabOMYxUZL9y50cAaE0brKOVjmdnLXiukSz69a0vCZhgZBIJMapyV9il6GSNLD/2668RkSpu005UhSJkiiqoE4WpXYigkufRugMvcF/uyB2h5U5hGmmbnPKZZYqx057d1jJsOkFvHjMYPa0RRlZ7cIWyrnyiqEkWVLQfJTcJonbTd8ypnxe4xOJet2zLL39Z+vRYa3ZV7ak0xu2/LaGFzduzbdcL7bhlwJMYeCQk/GPjBIkVL0ZtvUXR89haaDGVaDLgBg67HDT0+27IttqcVKSPmZN2kaGkKtqDXhRPV7izU2VpIztTcNqC433sUCaQMza5sxLmWQysSDLiKlNkNbu51FM+ugSU0t/Zrbu6Nua0v4HQjgxcZ2DJmd2+F56opBtyuyUifo/kvC2eJtWDRk1gSfnaHRTuWpIyutPGPZlZIG5prim28WKDozuCFSnBd2Wd7Jub6XvBjmGlpXvTnmZTnWRZTXMk7OCxuZC2apMAgF+KnSJEnUE1yusTp9b9C6QhLW0zJswyoYWIRsd/pZz30MSVsS8V8JPdj9LiCfhfWqPECR9mWMTgvTjOetXAMwXrcZlI8x5+s/Xd26r2seiE39FkYQtCOFFlps9BWzHltjsjD5ITLqJvhgNzJsudjbJzqryh9HE/FTDU1se4af/Q6mkDBtdZuDCHw4+77/kDwAGdadRY6Aa4h6HEku1IFbkrtoCbXWAvOA5AzLU5EcxRsg4WOxy3mzZQMlxvtvXyi/3/HJ2BOnOWlyp/RZI2iuZ1d5Q9imWkG3Cs4nPkooeqafwyKPaR0moV2QK9rsCObYsB2aeuQlE6T1RnOdx5iQZzD1Wks7fDOwq8xxhWcXf8seXeU+c5z9MldpMwermAPu/UhSqqfc/I4A2qMlmixTQ+RccewRJqs0Y+n62Ts/u7nOz1BENWptS9i0nWOBMinJlAq4sXKfyMlS+zmOqSWlLIHkAjGjWtJyxJKR7TCVRyryHA8Sp+zl72597Gr/EGCcJV8Zi9KRWRS4wA0vHl6cofohOtMFO6iJ7MXP6pjGm9fM66EhLca85svkvDt4Ic1UjpN2d1JmRGW9BmG09dwvvJ5ytmrKGf2s9Z4AcMsYkh7S+7nhzX8YJFq62R3Sl91GM3fwnzzOSbcdxKIDpGOmGw9zM7M7QyJfczpY5jSIZfeTRi3kKIP00hhGxlSRglfNQnswa4Nv7AwzRJZo5+aPUysAiyzF9vMstI+STm7n9X6swBbkgLTLL5KOgldB0ghTLSOSLtjKB1t9Zk1/UWk3LDsN9J0/FmKmf00vLmNMGsHKSwce4AobhNG61tyyVf2UglhknbHtiQLQphYZpkgXP6WfheuM0wUt+n4C2g0TW8B0yziWEU6/sKGFbF+1XEaRgatgtfuz3uDPjopnTfdD5b0kX3nCETibJjwXWeoeDMSkFKz0Mqws6fCWiPNnt4K59ZKNEID14zYV/j/s/ffUZJd53kv/Nv75MrVOU1PT8JgEjAYDAAiEABJkGAURQWKohgkSxZpSdYn0fZV8L13SU66V7aW/fleW7IlW5Jt8RMpikpMIkgQJEHkDEzCpJ7uns7dlevkvb8/TncTAwxAgASTVL+1es10d4VTp8+p2u95n/d52mgNR4A+O2ZvUdLnhOwv5QhSydsmBAu+4Jqqz88Nvxal4YpigiE0ewsB9dhkPTK4ogTH65rFQDKRF4y4EQNOzNm2y95qnanEZL6TYyW0yNsxbxqpseR7WFLx2pFVDpRHWfBTioWUnKF4rO6wK59wsmWxq5DwkZ19GEJhScWwm7IUGJRMRclSWFLTTTNvwIPlhAXHYCUYIlD9jLgOy0GILSWrtccIcy2S1EebisXG/ZgVh77iIfLmELYyKdJPTligyoSpYjKXI29mLpB7y4Ljdc2VJc0t5REsOcKAA+/rP0Le1HQSmHSL3FZ8A6uB5nx7IxRZw0w7ZcA1sKVkd0ngJy4Fy+BkMMOktROt4d7kXk40qhjC4nXeIfZVBM1YUI9g2NWcbUHegtcOC041NX2uQb8j+FHzDlaDFNsQaEAI2JY3uNBOGUnH8O0Gn2v/N27I/ThTxggVR6BxUZosQNuVzHdSqiLPs8kaN5d/gZx2WBarmMpEeNcw7z+O6xaodc9ze+59uMJgNG9zf2eGEbWNi92IvGlSkDaeNqk6Ntfxg6xTY5AyU3KAgJRZmlxb+Wkeb36UQ+V3U1VVJsQwg67FtL/ImB5kVBxmSTSY0MNMixlGvEPEuosjiuzSV1M36+yoXMeSOEfXLJCECywFzyCFRd6bomrvYNC5knn/cVrpIiXRh0+DUesQjjboihbj6XaG5TYumqeZbz9Ov5nDTveitaZDmdX8PgadK1mTZzCEQ8efxrHKaFL84CJV505W4pOY0sE1KzRf4lzs0ePvEr0OWY8ePXr06NGjR48ePXp8l+gVZK8ytllkVVykFpznVPcuYuUT6S6V/D6GzSvZIa+lkNuJUj4df5pKYT/NzinipLblZpSzB5mo3I4pXIby+2mxTFn1M6KH2Jm/FYAWa/xg4a3cmXsXeWuAKF5jxLuKAXsPq83HWGo/zUrz0S3zDI1mKL8fAwvT8EjSBgBt/xxhtEQ7XMQy+5isvpGJwmu2ZIfAVmbZc9E6wTL7EEISRovs7nsnlfw+wmiRIJwn703x+uKHub38S7SCGQYLBxit3MxA8TBrrSfww7ktw49NM5Hn56gpHV0y0FvO7cGQ9iWuT8/PRoOvyxDjpI1lFNhefgMFb2cmnTEKTHhHuab0PlxnjEp+H2PF6xCIrUyUywVsQyYLfTFXS9saeMVdLtcZu0TS6dgjVAsHXtFjvBwut4++FUr5vVtSk+8lNHpLCvu9mDv3ckLSvxv0AqxfGVHaQQhNnBicanlEscGFTh7HTihZEXtLbVa7HvNdl8F8l8XA4mQrh9KCc+0CFStmwIkpWymHKwEnmjkGHcX1fT5n2iZzvkVx4zZ5UzFop4SppmjBwXLMoBORN2P2lTqcb5QouiFHdyxw3eA6p+olto3UuX73RaYG6qx2Pf71Mwb7qw0WA5N/c6pLyYJOKhl0FIuBwVdXTKp2wslmDlsq9hRCpjsGnpHylRWH3fmQs23B11YMiqbm6j6HXQWPWGmaOqCVxlhmH91wHj+cwyX7vDjAURyjRC04j4XJfnMcjWbYznExzjIm2wmcbRsM2ilXlgUroeTexiKxglacmZ7ctdAh1TCel3xs/TimhKv7PN42YXGsllKxJRVbcPtwllN2oGqyGsTcnNtBJ1ZMFCQf6LsDQ1i8JX8VkwXB2RZcUYi5ZSBgWy7mipLmSDUhUIL3TtX50W0dnlgLOVDRHBkwyJuSibxk2Vd8fm2JSGm2OUWu4hreUvxpuqKL1lAwoZso2nHKbNjidCOi6hjsq7iZnE84zIlZxvUQVV3G2nAmnNRjvCH3fiqWTd40WA8SfmxoktGcZCKfydnfPmHzjgkX15BUDI8bvO0sijWm01U+VfttuqLJRX2c4dIRcirP0+oebGngGIIT7c9So81ZPUdMzDI1htQIHbXK1eIwr7H3UhQueZ0nFhHjeg8dfxqlQsrOJKa0SdKAZjJPrLvcaP8QezjKEmfZpw9xIXiA3UWPST1JREJbtqgyxg9XfobH1OPcVf8dvtL9HzTkOjvs13Ch9TVco8qIsY+8N0WzcwpbFthbeRdd0caPa9hmifQlXKR79Pi7Rs9l8VVi02URDN5a+d/QaOo604QvyRm2qZ1UDI/T+gIjapRZY5pEh9TjC1hGgZIxwlJwnFb3NFPVO5lt3kvJmyJvDrIenGPI20egmqQ6ZrX5KB8Y+XVWggiAGMUzPIApXNaDsyiVUPV2Eqk2UlgsNx7EtgYouKPsla+lIddpscJS+2kquR0YwmS9e5bR/NX06wnOxvcxah/i2ebntlwg+4uHqXdPbxUrBW8nnWB6K0R6yNvHanA6C6D2p7m5/AscT7/ElHU9dZY4X/sMBW8nbf/c1r8j5RtZaR/beo6Jyu1UxDiL6QnW28dQKmSkfCPJRiRAJ1ym7G5jsXH/1n5/vmvjcx0lAWxriJzdjxCSWvsYRyv/kDVxkTG1k2XjIo7Osa5nWe2cJO8M0ug8i2X1E0aLl5XA9RUP0Q6WMA13q1jMuZNESZM0bWNbA6/IQfL5MsfNRfvlHuNyTphSOuSccbrhRZQKL7vNQki0VkhhvWRMwjfCdcYQG9dwlE4u2cbN57jc6xPCfNEi99XGMEqXOJd+L/GtSFpfLj3Z5rcfxx7hd/f9NDcNrXGsVqFoZjLDWEkcQxErgS0VkZIcmVokjgwaLQ8hNGFisuK77B9dpdO1MU3FTK1EvxegtKAZ2ty7WuSOkTpfXa5wrK75oW0hD657eIbmhr4OU30Nlpt55roeVTuhFpkcGVller3MroEa+WJIu+liGIoH54YBONRf49GVfgadiCA1eKbp8NWlkNtGHMbclLyZ0ooNdhR82rFJpCSJhlnfJkjh2qrPmbbLlxYVV/cZ9Nma+1c0036LiuGxoOq0RYOcLjIiqizoNXI6x73N36Xg7eAG6x1cMM6znyswhGDEszjb9rm66jGV1zRjwUwHFBClmruDh/nN7dfSSiSPrELREkwW4Mb+NgUr4lyrwOm2zc58zKxvUTIVq6HEMyFvKE40JXlT8MRayOtHbVZCwfFaxNX9NiuB5kI75JYhB9uAIIV6BPtLikPVJicbRQSaLy8bHO3XfPZiynoS8K6JIn4CJxqKsi3JmbAWaEq24HwrZj6t8+bBIQqm5nwbXCP7/cGq4FwLUq0xhKAVK5bDzD1yOl3lRHgXH+x/P+fbPrY0sISklcYcrHgsdFMMIVgIfK7py2NLQaw0j6y3KRo2gUqxhKSrYgwhaWsfLRQ57SERCCG4opjDNeBcM8YQgk4aU6PNTruPKNUM50yeaNYYNYvEWvGQupdx9rMspglUE4lkUlzFgjjDbO2L7Ky+PZOfqjwSSSB8XlMcI2fCiXqIJSQPqvtYaNzHm8u/RF13iUXMMf+zvK3wfjppzP3xpynZE9zh3kCqNQJBO045reYZ0gNIBHnD5Jg+w6n1T3x3T/gePb4lei6LPXr06NGjR48ePXr06PE9T68ge5WZqLyOGTFPybLplwVKIkeZQdZljaf006ykZ2iKNgCTajdCSAxhEunuVibHdO1vua74fobsfQyKHVzlvpUhPcVBbsSRBa6r/Cx+ooh0ikbzxcZ/JEyz7lmctMk7Q/jJGq4sMSB3ADCUPwjARXmaKb0NrVP2Fu6kZIxwhb6WG733sBae47HGH9PonsYlz3jpBvZX30POnUQImYVKb8jf2v45xsu3UvB20u/twRI5PKtv6zU0ZI1x6zBSSzQpQpi0/XPY1hBR0qSY20MzzIw++ouHM/OOdA0AS3qMlG5gqnonrWiBtdYTrDYfww/nsGQOKSz6i4cZKB3BsSooFW3t/81OTF/xEEPlGyi4w5TsiQ1TkwqB6NKvx5mRJzi9/hec6X4JgChepulPI6RHnNQQQm4Fazv2yJYErtE9RyW3g24wQyW/D8+ZoBvMkCR1BALHKl9W4vl8LLMP2xqikr/ikvDLMFokSbuXvc9md+y5EjOlQpROyLuTAFvdESmdre3QWiGERLxMGZ8Q8rIumGG0iB/OEUTzxEntkt+9WGi4UiGG9F7gzHnJ872Kkjn9nA7iSz3nd4PvhHFLrzv27UdrxXqUvQ+O53yC1ECK7DroMw0PS2oudF2GPJ+FlRKnFvsRQtMIHApOiEaQJBLXiVlu5rnQ8TjdKHG6UaQe2dwxUsc1E3549xwfvqKBLRVVWzPhpbQSk5bvoBBcP77E7oF1rhtbplgKGMp3CUILK6eQUpGm2TY2Y5O5VhGlYSmwyZsJE17Kz+wWdBKx0TWT3LsiWQ9tHlx3UcBF32JnPiTV0IhNzrUFthRcWYwYcWNqYcKkW+QL/seIRcR2PcFTnb/gLNMscJqCcLip9GFusN6BK0326j1M5G0SpZnrRBQNi082nqIeC1ZCsm5VohnLSX5+5HpONA3uW1aM5yVDHmzzEmIlsQxFnx2zPZews9hhOYvu4tOLdXbkIpZDyWQexjzFj243GPdiFrqKw/0WYQp7ivCBnQbjXsqEl7C7kFCxoWilBEkm1azaCWfbXVZCSZ9jclW5yJkmtBLBRN7AMSBKwZICreGqPptbq4Ms+pqiqdmWg8drbZ4ML7IawmqQULAEQsCgK5HAjpKJRlF2Jln0Y0Y9l6ptMeSZXNPn4RqC7QWTWhTz+pGsO5Y3MzdIhea0voBCo7TGFSYFaVEQHn0UmfTyLMolBm2HZqTIm4IDVZu8Jdlf8TiUG2B/xWAsb/KHK3/MA+0/ZCxvkmrN23Ovo6Dz7FYHyct+BuVuHq7/VyD7XL1S72NMD+Lh8Hj414yKfhKlWego7ks+SyPNgqX7Cgd5kodYNRYAiJImnTTmnJxmn/k6xvQuYqVxDUHREhQsg11ylG2ex0PJZ1lK2kjdW6L2+PtD72h/lSkxzLqe5avxvbRUgCMMRnQ/gWhzvvYZisYIi5xmIB0lLxxea70VRxQyqaGOKeb20Fc8hKFNbO0xpPtJSFkW07RFlyv0NRwP7+Kh9DHqooUlDI6UfxKBwUr7GQby++mEy9Tax1j1n+V47U/Z2/cjBKqJIRwW24/zsPoSRTFEQoirC9zf/SgA25xrubLyQ1Tye4mJGNSTOHhs916DH2fzXlorHHsE06xgiwJ97i7Wg7O00kXK5vjWTNSp1meZiR4hEhGNeA6tkw1rd0UUrxLGNUzDo5Lfx1rrCXL2AForTrY+TaoTTOHQTldwzCLF3B4K3k4MI89K9wRTlTsZMw9hCmdDKth6wd/BMUpESZN2sMBM7S76rB0kSZ1j9Y8xo58iSBsMlo6Ss/u37pOmHbSOM/dFrbacJsNocasYStMOy40HMwln5wSOWcyKHQRKxwTRGkV3EtsauGxRA9mHWpysk6oO9c6z2M+JPzDNCvobyAqfOysF0A1maHVPb30vEC9Y/GutXpaUTyBA68tKGzeLLq0VhvzGRecmUbyK1smL/j4LJncumQ38ZtncboF4yef8bvBix8PfV16Nv/d3g5HC1ZgCotSgFtrUYoNnWx62VOwtBsRKMO5FpFoyWGkzWujQjmyk0Mw1i7hGylorx2ozz+cXy9w8ukzBTBnLBdy76jIx0GDbZB3HTdAaIiVJdebUeNG3WfNdJqoNbCfFNBUX1ivU1nOMDDVJleT82X6iyCRJJGUrIVSCbmLQZycUTMW877AaGQSp5EApQmnBfGByx0jCepSFJQcbtviLgcXFLpxoWuTNrACZ6dr85pllthdsTodrvLf6Pgxtckae5cbceznT+gJKxxwTTzJkFMgbFqFOcaXB+VaAZxocFyepOAZvL15FqjPZIEDOFPip5pmaYiqvGXANRlzF0WrA5+YNZroO9y71sxbZ2FLxyFqZ2wYD9pU6/OPdBZZDk2sqAdf3Nbmuv8FELuRY02ayIBl0NI4BFUtxomnSTSW1yMBPBXsKMec7Fs80CqxHJt3UYH85z0wnmwlLFKyFKfevtvjU+gU+V59m2VfMdSKqDjQjTd6EuU7IkzVBIxbsKxV4fXmCubZiwDW5uzFHojTT7ZjrBnJ0E3C1xyGux5IS2xCcDFbZUYTVQBOp7OLK/orDgysRrTj73k80c8Z59ssdnBWn+GL3f/IUD/PV5POMOC5P8TDdJOUKuY3F0OeB+Di/u/wZ2ommZGURCrHK5veakeYfjXyQd1V+kflOwo6Cw5AneSj8JJYwqMcXqKgKN1Q+RDdZY9w8zMPqS9nMtelwtfN2TopTnG53aCUJd7rvoCna2NYQYdJkh76KRIdcUI9zW+GnAeioVWbFccaMCheDLl/pPsun24+zFASYQuAniputtzFqFjHovWf2+PtDryDr0aNHjx49evTo0aNHj+8SPVOPV4lNU4/JypvwZBZo3EgvcoNxK/XUZ1aewyHHUnICQziMGQc47X+Ja5138tXG/8PB6k/wTO1PMgmjUeLm/Adwhc1X/D9lV+42BJJ+1c9JHmRYXsGg6mdezlPX8yw27t/qDPQXDyOFSZx2CJMWhrSpujsYYJILySMYwmG19QSWWaHgjhIlHUa9q6mqIdqigcTgmdqfMFg6ynrnBFI4DBQy98Gaf54ozuR846Wb6KZrFIxBVoJTdIMZtFZU8vuIlc+Ydw1L4XHipIMfzm3tJyHMS4wvqoUDFKwROskyAoMwadIJZhgp38Ba5zRFdwzPqBCqNmvtYyjlY5oViu44tfYx4FKzC8PIYxpFbLOIYxZJVUitfQzTrJBzhum3d7EcHMc1K6y3nkQaxUs6R883BRFCIoSD1jFCGGidZt2+jVyWbriU3U/aRPHqNzSVcJ0xgnD+WzbYeDnY1hBJ2nhVpXKb+XM9evx9ZaR8I/9q++u5stTlswtF9hRSvrYi+NHJgFhJUi24otJACM1q12P3yDoLa0XydkyqJKaRkqQGx2tlylZC2Y54ql7iqkqT+1fLHKm2SbXg8XoBP4Hbhpp8canEtlxKqgVv2zOLUoKVeoHRwQZJbPDVC2O0E8nNw6v4sYlnJZxvlDjddthdCHm27TLmxiyFJn8522Uyl8NPFPurBqOuYiGQVG2NBAadhIu+xZCTsBiajLkJ0x0T24CLXXj9UEiqBfevOXQSTTfR/MH8v+JQ9f3sYIxYp8yKBXaJCRppyCnxMFWxjRYr3G6/Bj9RrCY+h0pF6pFiJJddF77QSrh1xMAS8Ng6DLhZV2vQSQmVwJUKjeBM26CdwLgH65Fg0FEcqbaZ7uSY7Ro8vp5yx6jAlppYCZZDyUwHEqWZKggiJRhxFTNdQaphe15zvi3YVdBIAauhYDWEtUDxSHSaO0t7URoutCP2lm2+UlvB0Cav7a+y2M1MPSAz8aiFmliBFNDvZmLsJV+xEkQ40uDqfptn1mMmCyaLfkqiNH/Z+H1+YewfkWjod+B8S1NxBPc2Fnlj3ygX2glVx6AdK+pRwrP6PCFddqorAGiLLifjL9MOFzhUfBfjDDLLEjfmJ3mwM0dVVSgbDk9zglvsQywHIVIIJIKdJRuAp+ptusKnTIEhx+FL4dcYZhenwi9RdEbZTqbaMZFckKdYj6aZtI/iaJdEJIzpQfKGxTF1ljZrtONFEhVRsIe4Xt7CjF6mLeqEus1OdYCy4RCrTHER6ISLxiwttcwR8RpirZgXS0zoYY6JJ5mp3fUdP8d79Hj1ePmmHr2C7FVisyAbKt1IlLbZZh9lWA1yVp6kX48zrR7Fj9fpc3cRqjZKx1jSoyq2cbz2pwDsq74bA4sGixwRR+mqBK01ITESQYIiED6+6JDTRdbFAudrn0ajcTYCoDcp5vYQxg3ieAUhXWyriildOv55dvf9IKFuM1O7i8nqGzGwcClwvnsvUbyGVtElj5n3prZmwyBzWATY5b6WNX2BULVJdYhrVLNAULNMf34vrXCBKGkSxauX7CvTrGRFi9ZbMy+Za+MMWidUCweotY9dEij9fDYDoz1nIpstM/tIlY/WMf3FqygaIwS6gYFFJ1nBMgq0wwVcq0w3WiNJu5cNvYZv7FSXyQoVWocI4Vx2+6T00CpAoy95vGx2LDspg2gFpcLMfS/tvurzP5bZtxUt8HIxjPxLbsvzC9Yef3e4nItnjxcyUDrCr0+8jVsH6yz5HhU7wk9NBlyfp2tldha65K0Y20yp+S6zXY96bNBnpww5WTHTiE0cqdldaXD/0gCuoRh0IhYDh24quHl4jdzGjNlsN0feSBn0AlqRxd6RNWw3wbQVcWCQJpIoMjBNxVKtwEy7QC02AEi1YHsu4HOLOa7vi/mDswlvH3dZjwTLAUwVYNGHIRceWI55xzaDxUCyzUsZ9SLWIwtbKs51bM63smDkWwYT2onk8XVJ2RZ8du0iu61hDAF+ojitZ9mmR7GEkbkKptmMb05a5E1jaz+Wnez/JQuKFnx5qcMPbcvRSjLHxdl2hGcanI/X+PD2AQAu+pKSBZGCUw3NDQOaj88E7CnkGMvBgg9hqhn2MsnlqYbiYFXiyCxE+r7lmHdvzwooKaAWGThSEypBPRZszyU807C4d7XJ4UqR/zj779hf/iGG1BAV08GSkihVeKZEIjgZLVOlxH3hn/Ou4k9QdiSJ0lQdwQNrLXbnC7Rihdx4vVprPt99jDvz16K15k/WP8oPFN+DLTNbfdfI3nnrG2PRniGY7ypsQ9CJFU9Fc5RUCQeLr/ofZbJwI4FuIpAM6SlOhHex272NY62/Yk/xTezQ2/l8+/d5XeGncYRBqFNGHJdEZeHXjVDx8drvY5k5Ov40Y5Vb6cYrHDHfzN2Nf89U9U6G9BRd0SanCygU/ZRRaLTWnJUncSmwT+6klcacESfwVY3Fxv14zgRR0uSWwk9SlC6nxTkMbRKLkLP1z3FD8ad4Vt2H0jED9hXsUbs5Lc8wlm7jsfizDDp78XWNhfrXvjMndo8e3xZ6Los9evTo0aNHjx49evTo8T1PryB7lYlVQMEapl/1E5PQTpeZ0U8xahxgp/taasF5lhsPstp8jIIcosUKAJX8PpRQFHSR1e4p5tQqd9V/h0W5xCke4rH4s1yUp3ms8cfsFVP0UwZgsHw9xdweRvNX01c8hGlWsu1IO0TxMhqNUj5FZ4wgXkejsywz/xSV/D4W24/TTOZp6EX6vN2Uc7sxzSrwdROHjj+9NYBfLRyg5EzQ9s+xoE4yV7+HtdaT1DvPMl//CtXCAQ4U3kFVbCNKmrh2P3lvityGCyBAktSzDtNGF8a2BgjjOsXcLgDSDUmcaXikaRPHHsEwSltOh4aRJ4wzR0Y/nEMIk8HCQXLOKFonrLePUY8vsFD/GovtJ2h0nqXePc947loq5nYEEtssIRBYZiYvdZ2xrcd/fndo87Vvuva5Vh9a+SgVvqg8USl/63E2ZZoAcbJOx5+m409vmIgk2b/fBne8OFl/xUYS32hbvtnu2KsdTt3j1eeVdse+VZOS79dAalsWyBkaIUAKTTO2SJRgLXC56Buca+c42yrSjSz81KSVSLqp4IuLBvXYYj2yGHAixnJdbDNl2I2Y9U2C1MCSGkvAM+tV7pkd4XijSNFMyJkJ/YUufmpwYbXCnz29g1bN4a9PbOfMYh9ztRJnl/sYKHWYLLSZ8EJ25H32l9sUrZgriopjTRtLSGItaMbQiTUlUzOV1yz48MYxk5yhyJtZZ+2/n7X5R89+lsXAYmc+YiKfdaYaseR0y2B7AVIN0+mjDHsGUap5XD9OSsxpeZpQp5zS0+SkxTHxIBdY5Gy8xpeiL1F1stvf2zmHFKA0TOZyWzLCMNXcn36RC/E6b+ofZrpjYAlNLcy6YJaA+W5II5a8e9Ll6Vad002Fn2hypuBMM+FUQ7GjaPDXC7UNaWPKwarNamTwaM3k4XWTT8z6zPqSe5c111R82okkUpqbB0qM5+Bnx/4pR50dGEJST0KeTRawDYmfKE5Ei3jaZU8hx4eG3k/JzrpjYzlBlML+YpEg0fQ7ButxxJlWh0c7S9xoHWbVT3iqvc6UeyOWFBwPVlgNNcdqKWshPFP3OdeMWQkUp7sN+h3BYhgwpgfZkyvTb7vsz7+FM+t/iYXHTO0uNApDOqwzx2TxFgCe4EFMI8cZcYJYK57W92FJwRPJGRKlaSUJt+R+AkM6DJVvoF9sZ8y+mq90/hDXGSMlYVxWOdn6NG3R4LHGH/EV/095LP0ii3KJQDc4ZOxCa9BaYwqHnOzn5vIvcLP7bnLOME8md7Gqm3R1jaXkJOcaX2RP5W1cEM9wpbyFXeZNTKmd5AwTX9WYlefY7lxPVQ8TvIiKpUePv4v0JIuvEs+dIXNkmTO1v+KqyvuRSE5272J37nWZvC9tkqqQeufEJRKhwdJRisYI52qfAuA1lQ8zJMrUVJeccFijgaUtLohnOMT1/G393zFYOsp+cROPxZ/Fj1bw7EGCaO0SmdpU9U6ayTxB3KDgjGbOg+ECtlnCtcoIDErmGI1kFscosd49i1IRBXeUbrS2JYOUwkKTZnb1nVMAjFVuJS/7WYvP4BpV5utfYbB0FD9ep+2fwzBKbCvdyHTtb7dmpzK5YhutEwQCz91GN5hBSg9DeqRpi1JuN2HSIojmMY3KJa/ncjI8w8ijVXTJTJZtDTBWuJZ6NEOfvYuF7hMM5vZt6dFHKzez1jmFY1UJ4waQWd8/l815qecG+j43AHlzW15JGG9W1KnMhSpazKSa/vlLirdXY0brWwkhvtzrfrV4sQDp5yOFhdZJz8b924gQJoZRIE0a39R+/maPj+/38GrPmeD39n2AA+UWFzp5HlyzeO1gth92lZskqUHOjuhGNt3EpOSENEOHzkbg8m+eavFfjxgoDauBhyE0X1rOc6QaMuIFPFEr0ogFuwsxD6xZ/MTUOpahOF4rc7xpcX1fwEShw0C5g+PFrK/lqVR8nrgwwu7+GidX+vjyise7J9c5386TaMm457MWOty3ZnOiHvFj2yVfXja4ZVAx4MTcu+rR72QzZJ6hMYRm2I2xhMYxFK3Y5A/PCnYULV43HPLAmosls9v+5cIa/bJATXVZNRZpqgWm9NUMyiJ9joWfKiq25FS7zc5cgXPdNvuLReY6EXkzkzXurUj6bU2qoZMIHlyJKVgGRwcyV8C1UFC0st8rDRrBkKMIVBZVvx4JzrdSDlYlSz4s+ikV20AIeKA1zwfGx1j0BXOdlKMDkkE7wZQgyObMZn2TCS9lzjeY68DNgwknWxb3Lre5opinFqacjle40h7iM/5fc0S+kWv68nSTTFopBEzmbZ5o1vlq4//hI9v/D9ZCRSfO5I1hqhj2TM62AmbFIikxZdVHvyzwqdpvM1G5nR8ovJYBV9COs6Iy0ZogzRwoXQOebQRcP+jxsdWTjKpxusLngfrvIYRJzp2g6kxxiKMcE09yjTjCF/0/41bnh4lRNGjjaJths8BcWqNK5uzb1AFd2aErWuzRO1nQa6yJOdbCcxTsISpiHIHkRO1jaDSvL/8yEoErTZZ1g5LO0xQdPO0waOY5ps6ynDxL3hzEE2Vs7eFol1QkNFhhVE0hESwYMxR1djF0QZ3ElgXG9C5y2uM4D1APLtDn7cZP1rZmxXv0+P6kJ1ns0aNHjx49evTo0aNHj+95egXZq0yefnaqXby5/BGerP0xO+QwO3K3YGIyX/8Ko+YBctYgkEmE8t4UhpEnb/RTTy6wt+9HsMw+ctpjWTcoCIdQJyyLabqygykcntRfY2f17ay2nmDMLjDiHmQgv4+KM7mVyWWaFaqFA0isTGJjDxAlTSr2JK7Vh2uVMWWOVjCHSwGtFZbIEUaLDBT20fRnv94dkx62PYjWirY/jWOPAFCUQ+R0CT/KQoIde4SV5iME8TquM4ZSXQb0JI49QhDOA5tyxYScO0m1eJABby8DpSP0FfYxXLiKycrrqXdOMJo7zGj5FkpeJnXMrubnL5G+bf7fNIqXdMcMo8Rk8WYSHdLsnqGVZoHG862HcZ0xbGsIRxQwpMugs5fxwtEXdMcy444EIUyEcLZ+XvB2bQUum0YOyCSOm1LRb4QQFuPlW7GMHEKY+NHSJd2CTdnmt4ppFL8pmWDm8pldPb1c9yPLkmPrGPiG2/Ey98vzUTr+prsom3+f77Vg6G/Ed1rWqXWSnY+vcD9vbuc32z39fu6OARTdcSQQK8meUosf2tbkymodrQXt0OZMs8BXFoYQQjOU75BzYsbKLXb11zk4vMqf3RqybbzGSF+LAddnotjirWMNtuW7+InJEzXBny8uU4sMduQ1iZI8vNLHlZUm79q2zp/POgxV2wAICetdjzgyGHB9FptZjtaPTNZoRDZ7yi12Fdvcu1pkPrBwDcHbJ0zOdUwGXYlrKE61XPKmZsLLOvNXFH1mugYDTkjZjghTSSM2uHbA4mhfwlKQSVVn2orH1lIO5Pt4TD/AfY3/RFUNcA03MS2epM+x6HMEeVPiGIJRO4drCBqyQS1MeZxHGM0ZHKxKmjHYUvPHF5d4pqa4bcTi5iFB3lAMOim7Cim2hF35hL3FhIqlcQ2NKzV5U/HgapfrBzIJbKzg7vBLLPsJhoD3jI7x8Ipie14x6ErKpmItMlgKDDSCVmJQtjSn2yZ5U/Nwa4W8mQWj7S/n6SbZ8apRBKniiHwjtw/nEYAl4TVDNjcO2pRtwS39Vf7vK/8PTjYC9pQkozmT4+Eig55JM1Z8JfxzLiZPkNNFJu0KA47NnZV/yjC7ECLbpzsKGj/VGELQjDTNKOWrjXnuTz5D3tTkdJGy4eALn9HKzdxQ/hl2uDdzs3UTtjSyTpNhMOpdzYyYp2hY5LTHCf01BjyTZTHHkOtgS4MBI8/p4MtMqSlSrXi0/t+QWBTsIUpylNngEfrVIH3Fqxmr3MqA5WZSRZXwcOP3mZfzNGQ2PhColDsKe7nFuhOJRJFyuvtFlsQ5GqwwrnbQlA0GjDxX6r0M6X52yGFuMm/jenmUmlwlJy328xpe6/04Y+wlTnsmQz3+/tAryF5lCqrErJijYtkUvJ08oh5lJ5MkJExW38hieoKaf25roaq1ouhOkuiQEfMAZdXPePE6dubzhCLklDjJNjfPDrWPi+nTlBlhQO7EEi5vKf8yZcdgKB3HFA6dZBlp5DHNCkcKP8Yu8yYG9Dg7uAZTOFxh3Uo9mmGPexsFcwRHFujP76Ws+6hY26lHMwyWjrLUfAzHyrYv506ilM+AdwWeM0ElfwVD+QNMVt/IpNqO4uvys4IzghAmadrGlC4TldsYl30kaZdibs/W7XZU38o+942st57GE2VWm49R65xiofUY07W/RUqPc7VP0QznaAVzG/spQSmfVEVbjyNlAcvs25LAFXN7MIw8Y6XrsLTDCHsYKh0l1ZmToWNVcM0yUbzMkJ5CCMmi/xSmcHCdsa3Hnay+kZK3jf7iYRx7CL0hK3XsEcK4gb0xY+eYRQyjhGX2vahj4/OxrSr1cAbL8LDMPuRzij0pLPrtXVtFz/PZnLkxzcqLzu9szrtljpPfWBr4fArerufIM19Y0CgVZhcMnhOovbV9lykonr9fvplteiUIBGnawbaGvu/s+b/d++bV4vtlO79dREkTS2qUFowONnhkvYhlpcz4Fhc6ObYXurxtzyxjww1mGiWC0CJJJPWOy0K9SBBanJvNwptdM2XN9zjdzJMqwVdWclRtwRv7h5nzDeqx4EyrQMVOaIQOQWLwO286S73p4eZj7JJi97ZVwsjk2WaJRd+lz07YuW2Nnf112pFFyQnZmc8uWN3U3+WJmuTmgS7v3bnM/mqDw5UOI67i8Vo2K/b5xTwHyzFfWy3xn58t8GTDZTE00MB8YPJ/zT1DpDT3BE+wHodc7AbM17/Cuwd/jVurgwy5Dh/sez19juC+xgr1KCFRkGrNg+15EhK+Gt/HDxRu4nwrppsKOjEESvCTE8PcMiwY8xKmOwJHap5pGMz5BjvyMSdbFsWNYmkxkIy4MV9Y0Lx93AVgLYSyLXBlCUMKEgVVS/GaIcFKKNhb0mzPB+wrBVgS5n2TM22B0jDiKk40BD8/1cfOUovJXMpcJyZnZu+7b6iOcbDP4oM7XE41suBqgDE3k052E825VkLe1JwUJ/iTlVPYBgzTx2w74o8X/zWT7vVorRikTKwUFwOfo/053jYwzq4iTOQla5FkV0ETpJpn/BVKtsGo6OcfDPwQ27yEq71RyraJqU2u4SYmjCqv8XagteaKsk1Oe+wsmdxsH+Cos4OVpMOA6bFP3MyzrTaTanc2Py0yp8i3Fd7DOXmWGm0GSkeQwuBacTOKlEn3euqyzlHjDrbrgyzHPiNqmKbo0F88TJfsYuyXG/+Rqm3x6fbjnOQsRYboqDW0VhwRR3lj7jBVmUOThWS3VMCiWOHe5EusJV08U1JQZb7Q/V9s83K06HA2uQ/N3+/3mh5/v+gVZD169OjRo0ePHj169OjxXaJn6vEqsWnq8d6hXyVKLcbyJpaEdqyZ7YQssY5A8ljzf6GUv5U5dqz+MYq5XRww30AkQk6GX+TDw+9HCljoKOpxTM4wKNkGsdLcFx2nqoaoUiTWKdf2FXBk5kx1qhHxsHqYudrd3FH5COvU6aMCwKpYZ1QPEOmUUdejGScsqDqjskI99VmXNU60/oahwlWstJ8hTtbpKx5ivfU0ALv73sm5+ucxjTypinjf4D+mHiWc0/OUVBkHi1ljmlC3yZN1kM51vsKd+Q9SsAwuhm0eDv8SP5xnX+VH8HSeJc7SL7YjkZRVmZZokdM5XGHTooNCsyjO0YozU5LNgGnHHiFJW6RpByEkI+UbWWkfo+CMcqv9A7iGpJHEzIgZKipzN2zIdeajJ8lZgyw2H+b1xX+EJSSWMDClINWax/VjzNa/xL7Kj3CmfTcAfbldhGmTgjVCqmNi1WXMOECTFdrpMrXumS2Tkk2ea1yxKZ9L0w6Hqu+noIqc0Q8RJA2qzhQaRajaLDcexHMm2JG7hbLq47R+gNXmY5ccY8XcHlrd01Ty+4jSDn44j7fR2Ss544RpEyEkSiUo1Jb5ysvBsUcYzh9iLThNFDcxDBfbLF7yGJth1kKYDBQPY0pnKyPmcmYkhlFC6xitYzxnjCQNXiANfTlU8vtQKFrd05d0Zy5nEOI5E0Dm0CmExA9XLpvFdrlg7m8lh+v5WX0vxmZn/KU6qt/p8O3vREj53yXy3hT/48B7uGlyAceLuXCxj10712iuORxfGuDQ2ArTKxUO7F2iueJSqET4LQvbTfD6su5OGoKZB6MoWXzCZb3tUQ8d1iKbXcUWiZKEqYEhNY5MOd4osb/c5MBt65iTJdLlDqqREK5qnEEBGlrTBtJQNBseQ1MdnCtyaKVJVwJWjzmsNfOYRspcq0DOTMmbMUFq0IotHlz32JlPGXQiVkIbWyq+tmpxoKz47MWU14+aLPiSWGmervlM5Fye6axzMN9HO1Y8mZzjkLmTO8cErUSSMxRBKjjZFCx0Y/ock+0FQSeBM40s6HjAlYSpZjIPJ5twoKx5sgavG1acbmcmG312ghSwLd9F60wmWrCzY3XV97Blyl1LJQyhacaQbrwdCAGDDjTizBzjQEnx6Lrk569cIUoN1gOHnJkghSbRkqfrBSa8iLuXXQ6WU24eydyP718c5FjT4Kn1gNeNurhSM+ImPFqzOFxJmPNNhp2UViKpWCnNJMubA4iVYCU0WAkF96+2eEp/mTe5b6aTpDyrz7OHHfQ5FpaEH9se4KeSIJUshSaREpRMRaQET9Uz4xLPhJsGYnJGyoWuw0OrcKpb52ChQsESzG4ESC/7CRN5C29D4OAnMOxl8spmLJhpp1QdSaJgNUhYjQMGLJdumm7lxhWkzaKuM8szVMQ47xnYy1qYhWMPuhaeIVgOUuajFmN2kaeTc1zv7KbfFRStrDPZjDVPNhqsyxpvKk9RCzVnu00OFMvEKgu/DlMwBZTszOqnEUEn0TzaWaJKiUeSz/VMPXp8n9MLhv6Os1mQHS3/LKnUDOl++m2be+OHeZ1zPStBRNmymI/anBVPYYsCk2o3Z+XTDOudNOQqU2on467HoCc4VY84wwWm/fsY8vaxRx9EIhhxHfodSc4UrIaa/7b4n/gHwz+HKTNZxZ81P48tPG62bmIuavKsfoA47XDYvJOarKFQ2NrGwOSh+n/hjvJHyEmLeb2OpS0iEZLTOU7xECVjhGa6iCtLmDgsB8eZcm9kSA0hEczLeY7X/pTdfe8EYDSdpCw9coaBZ0pWgogvdP6YNxd+CteQTCfrPFT/L1xf+RCOtolFzMn4y/TZu4jxCVWbsjGGqwvMJ08zah5gOrgfIQxMaW+4QJ4GIFURldxOhJA0/TkOFN5GQRUoS48FvUZNLHGu9immqneSkjCsdzJImZJlE6TZB6JA4uAhtWSYPhra52uN/5erqx+kyQoCycXOI5S97aQqpBut4odzjFZuxsDCFA5dVceP12l1T28FaW8uuqWwieJlDCPPcPFaBsUOLqZPX1JoGUae/sJBTOGw2jlJFC9zdfWDWNrmbHIf9c4pQKG1YrRyM0FS3/qAem5Ic8HbSds/t+VWmXeGNwKwG5ed9bGtoa3iSEqPoeJh2tESbf8c8PVixzQrlLxtmDJHXvaTErMenKUTTFPM7SFOOvjhHAVvJ3HaJWf3X/YDdPP5nh9g/lJI6eFY/Vhm/iWLSykd8huxCm3/LEI4W/OZlvRodE+jdbK1v0yz8rIlpi+HFwvLzuYQYyyzfEkQuWGUMKRNkjS+rYXQy3W0NIzSi8Y3vFhx+GIOiy/3Ob8R38tOjH3FQ/znPW/nmoF1LCMll4t4aGaU1x+5wPETQ+zetsqZ2QGuuXOdeCmhNuNydqXKNfsXULHgxLkh9kysYliayDfIVWOECQ8/Pka/F7Dc9ZgoZjNiz9bLVO2Y/duXcPsV9rhFvBCzdCa70DNTK7FvYgVpaPJjKeaQjchZqEZI2kgwhxx0mFJ7UnDvuTFOtmzuHK1zoZ0jUpIBJ+ZT8x79Tjaf5RqKma5NyVLcvQC7ywYn6gl3jApmuwZ9tmbeh04Cq0FKyZIYG589RQsmcnCqATuKsNCFv2k9wxFjH2fiJSbkAKM5mwFHMOYp+uyUpdDk6ZrmtUOKWAmaieTOsVU6kUWqBd3E5N7VHEerIafbDrbU7C4EhEripwZ9dkyYSsZyXU40ikRKshRKVsMs7Fpp2JFPCFPB7mKHgh1ztlnkK8s2CjhcUfTZCUNewHChg9bQiWz+fGaAn9i5yFInzxeXCpxrKa7pkyQaBp2UnKF4YM1ixANbgiE0tUjQiqHPzuSXsYK8qSlZmuN1kc20ScF4zuBiN+XqPoNFH64saWypuehLXAPuXvTJSZM9ZYuSlUkpB5yEVmzw2Xn4kcmUVAv+45kOFiY39BeZbadMFQ2eroVcUbb5z4v/kx+vvg/PEFxoR+ws2Qw48P9d/CzvLr+FkiUIU81aqMibkgFX8Im1Z7nW3kW6sSQMUsVC0mSv18dEXjLdSvl47fc5nH8X59TD/ED+rRQswaALhoAvLXUpGzaTBRPbAFMITtZjYq24us8hSDOXzKWuYjH0Gfc8lAbHyLalaEk+1XmA91Zfw2qgsaXgru4znF7/i+/Ked6jx6tDz2WxR48ePXr06NGjR48ePb7n6XXIXiU2O2S/MPlr7C64xBrCFAomtJOsRq6FMNNOOKsWWdJnmWQ/Q6LMA+oehuUVDKoBHk8/T9maYFztYVZmXYFxtYcjpX6iVNOOFefjdV5THsRPNnJbYsVqHLIollnV52iGF7nD+zEARjyLMM0GqvOWJGdk29uKNbYh8BNNvyu42EnJmZKVIKaTxtwXfoKCM0pBDpKnylz8GE1/msnSbVxsP0TeGaZojbEenOU19g+SNyxOcpbV+AwAR4w3kJMmqda0VMBDwSfp93az1H6Km/Lvo2J4VGyTVGVX4gwpqNgSpbOw0WzbFEGqCdKUBVWnIdeopbPUu+eZLN5IPZkl2XBh8qw+1jqnSJIGrjOK1grXKnOtcScxCfPGLI10nmvFa7GEweM8wpCeoiaWGNITzHESS+SY7zzG/vxbiIkY16N0dUgsYoSWFISHhSTSKYaQGAg6OkShmZbHiVWXpcYDCOlimWW0VsTJ+iUdBtsaAhRS2mzP30RKTEetkqiQbrzKhHeUhfBpmp1T2NYAUby6dd+R8o24soQjiihSQt1mUGedoVAEzESPEEQ19hXegkSyxhx5qiwlJ2j5Fy8r3dvk+Z2NTZlg25/ZkvEJBDuqb+Ni5xGK7hitYJ4k7ZKmTWxrgKI7QdmcoJUukigfQzoUjEFC3cYU2dC9iUM9vkCqE6IkcwTddOB8uZLBzS6gEPKS/TNYOspa+xiuPUgQrSCEddnOTzG3ByHklgTStgYyMxoVoLXKuldp55uWLz6Xzfy9Un4vSeojhbnVhbwcAoFtDwNfN8/YPIak9DYkoC8uZ3wlHarN7pdAYFn9l+zLTZ7bPXtu18ow8ijlI6W31R3cNKN5tbPrXi7fya7aH1z1z3nLzosYhuLuc+O8ae8s7bZDveMy0tciTSXDt2jkcAGURocJwjJAaVQrRPbnIFHoRCFsA90I8I91aa04JInE9WI6HYevXRzmqr464yN1GrUc9a7L+FCDp2eHyJkJhtAcOrKMsKFxzqbe9NhxYwvVUdTP21xcK2MIRSe2uNDxKJiKvJlwruOyt9jlE7MFbuhP8YyUVmJQtVIeWne4qhKzHhmMuTGJBj81+NDJP+VXt/0Eic5MMGqhZjlIeTZZ4I2VCc40YxaSJjucCn6iqDomDwRn0CiG1AhvHytTNDUXOln48oGyYtiJcQzFsabHvqJPPbbYlusSK8lUXwPXi6nVc+TciFJfgOFpoqZESJCGZn05j+vGNNsuT671YUvFuY5NztAMOTEFM+X+NY8xTyGASGXdvO25iMlimzAxiJWkEdl0UoNrBldZamfdxxPNAgVT8eCayWw7YdgzOdqfMuTE5M0EpQUagS1TmrGFJTWekRAriRTZcai0YD2yeLZlE6gsK20tjHnNoMNsR6M0bDQYMYQgVtn9RnOSqysRjdigmwpMAa7UxBqmOwYPrXUIdMR2p0SqNXvKJiOuYrojsKSgaGrqMezIawqmQqDpphJHap5qGOwrKSQw60vijW7eaqD4y/bneKP7JmpRRFuH9Bk5HtePoVGs+adJ0oAPDP4sI55kvquQAlaCmKMDNrUwk4pGKSwHKc04oqsjrsiX2FvOZIwDjiLVAj8V2FJTNBXxxvGkyV5jK8n6BK1E8L+Wpnm69j+/I+d0jx7fHl5+h+z7yxf6+4BuAonO3J5sKVgMNE+u++wpeaz4KY+ox5BY1PxzrKrj7C7cQb/cDkBDNNlpvoZnOp9m3NtDLZwmiNaoFsdY8cuUN+bIiuRZ9RW2ITjXbVOQNoGOGGGIYT2I4UiKpsmJaBErGCJQKSXLpB0p+osGJ+oR4zmLWqgoO5IT9ZCneJyj6bU00pCn1BfpBjOE8RrLaQfPmcA0soXXTPPLVDYcEzvJCp1gmjW3hkorbGMSwzRx8NBKE6mUp3mEihznkPc2YhGxK38VAAuqznQYYGmbPdYgjTim6rh04hSJoB4lrCVdluUiZd1HTS4z23mQIJzHMEpMN79MktQpeDsRwvj6LBMC28hjmyUa/gVW8muY2mQgHaUj1qjrLrMcpyq20ZTrBKpJQ6yTbCwiJws34iiH6eQhlJViCQeJBAG2MrGEQ1t0sbTFqlziZP3PGCxfz1rzxNbCVSufMMoW89ki+usL6E2ZoGX2UUtnMYSJgcV6cJa+3C6WoxOEcQPPmUBt3E8KC88dRwjJfPtRhgtX46c1TOEQyQiJZFmdoWJP0pEeAKeDL9P2zzFQOrI1B/hSPH8R78c1tFYUvEnCuIFpuLhmhdnWfXjO4CWyS9sawjRc1lpPUDfOkaZN+oqH8ON1SsYYrXCBgj2MEJJaeJ4oaRIn65cs5oGXXQAp5aOU/wIXyJXmIxhGCT+c39jnG4XkRpGyWYC0/fNb0QthXM/+LtFSVpQkq6j01VvYbxabL3ueTwjCaJFSfi/NzikMI49hFEiSOlI6JMmlr+n5vBK54NZxKYzLFmPAJQXtc/dJmna2tnGTb7UQyyImrFdUCD9XUimkjf4OFIOmWaFspXj5iMXlEmNeyNp6nvEdDf7gC+P86pVroABlEx9fx6haCNckXeogijaECTpIsoGnRHHxbyK8XMyZ+WHmuy7DbsjpVp6pvI8lNVoL/vtju3jPFbMoBI9dGMGSinnfY2ehTWvewvZSShMR5nLK+jMmhqlwcgl9vs9fXxglVrCvGCKF5rF6DlvCfz+b55YhxZxvsL+UMN0xGB+IKJgaWyo+NZfy1nGbTipIFXxk/H08sBJwb/Q3vL/vR/jj9Y9zo/UOpuQwX6zN89ryGE63gtbZBcB2nKJRnKh9nAP9v8Z0G66paoZdzXQHnqhJHMPhmkrCtdU2Ak3OTBkpdphtFPnq3Ajbcj57htdZqhUolEPSpuDcXD97dqwStC0eXhrk6v51ZltFnm2ZzHY0QgAIXMNmxIUxT2HLLPT6yZqk6ggGHINa4GwVQ7EW5I2UZ1b7GXQD7l0tUbUUS4HBqAeHypJAadYig6KZ8ni9wJXFKCtIQpdtXkSsBJ4BQWoQKMm8b9FJBbaEe5dD8qbJXJSdT/NdByEEcx0fBWzLuYSpxpKw4EfkLYf1yMCVmrUwK1DGPc3ZtiRvavaVcqQ6R5hqthckF7uauQ6c6tZ411iVuS7sLmrWIsGomzmAmgIcNFUb6nF28fNsU1Nx4NF6nbL0WG09wedR7BM3U5d12rrNteJavhx/mtc4P8zD8adYCWIMYVGxBWeaEb5OeHpdMlU0qYXZhd4h12DY84iUhy0hUvDAcsSRgUy6OJXXrIaCiqUJlGAtlFRsTT0WPLii2Vky6CQ6++zt0ePvCd/TR/tv/dZvcd1111EsFhkaGuIHf/AHOXXq0oXN7bffjhDikq8Pf/jDl9xmZmaGt73tbeRyOYaGhvhn/+yfkSSXXmW+5557OHLkCI7jsHv3bv7oj/7o2/3yevTo0aNHjx49evTo8fec72nJ4pvf/Gbe8573cN1115EkCb/+67/OM888w/Hjx8nnM1nB7bffzhVXXMG/+Bf/Yut+uVxuqzWYpimHDx9mZGSEf/tv/y0LCwt84AMf4B/+w3/Iv/k3/waA8+fPc/DgQT784Q/zMz/zM3zxi1/kl37pl/j0pz/NnXfe+bK2dVOy+ONDv8pE3qMZaRxDULIEcx2FKWG60+Xu1n8Cvp7n5FgV2v65LbODofIN9MvtLERPM2Ef4Zz/VW5z380FMUcqEnK6yJDuR6E5LZ5hXO3h8fCv6QYzVAsHmLCOkBLz2txuznV8tNbsLuZ5ttWmYmaSIteQrEURQ47DahjSbzsci+cZ1QOcFCc4V/sUcOngvudMbLkcVvL7aAUXSdMmY5VbMYWDn9aI0w6t4CKjxSMIYbDUfpIbcj/OnDzL+dpnGCgdoWAMcod3HRe6PoGOGDDyhCpFo2nqAA8bIQR9lkM9joh1yhn5DN107QWug89nM3tqU5q3u++d1JNZ6t1zWEaB4dwBUhK6yRpVaztna58GYLB0LfXuWYQwOZR7B1VKHONhgrTGXvla5jako6FqMyyvQCJJSSjoItP6SaSwWKh/9RV1VRx7hDipXdJVcOwRTMMliNZJ0+aWWUTB24lt5hk293ExepIoabEtfwML/pMoneBaZXJGP814AdvIY0kPgcFS6wlyzjCtDSOUl8vlpF+bjonw9UDz57oKbqu+gaX201sdwIK3k1RFaBQCSaoicnY/hnSod8+hVPc74iS4KYN8vvGGEBLbGrqswci34rb4Uphm5etd1I1O1nPNVb6+bZcaaWzKBi9321eDzdd7eefJy5t3AK+6Oco3wyt1iHyp1/NKnvOhWz/MVbeukdQU509W2XFlje6qSXFHinAl5kQR7cckc1200hhFA60ApUkbCpkXCFuC0siyTXAqYO5chSfWqjy8bvKOsQ4nWzmGnJiV0OKvZkM+sk/zbMulm2byr5UQfnx7nXZs0e8FFL2Qlu+gtaBa6PLE4iCzXZvH1iFnCu4YjhBCM+/bFExF0Uy5b83mQCmlHkvGvZjTbZsxN8XYkNzFOnMK7CSw4MOJVoOcsDkhnmZU7WJRTnONvIpPNf+AKF7lLZV/StW2uT9+glvsa/hCeA9VsY2SrmDorKN9qFhlqRtz3aDFkKO4stTlfNvDNRQ3jC3T6Losdz1cI8WQmrFyi+Vmnm5isq3c4ivzQ9w6tpy5LqYGrdBmNXB5pOZyvJ4SpVmXJko1UsBY3uTLzTneXN3GlaWEi77BVC5hMTRpxpl0rmRpJr2YbippJRJXap5uGLiG4PdW/pZfGnkT+0sRI17AfNellWTaf1NA3kyJlaCbSlKdZaeVrIRgwzXxXMfgk6szrDPHqN7NQ/X/wo3ln0MiiUXMhJG5Ej+lT/A69xCdRLG7ZNKMNX6iMaXANTK3REPAnzY+y6S8mgVO84G+2zBF5iTZTWBnAeZ9qNiQMyBUWXfqEyszvLN/ezbikGg8I2sNWhLONBPuix8l0SHzzQep5HfTDha2uuYTlduJtE/V2EZX19ijriIlRSD5Wud/8PbSzxJrxfaCQyNUdNOUtaSLgcGyXObnxneQajjbFhgik2j225kDZub8qIkV9DuCkqWpR9m2TbdSHk5OcWr9E9/S+dqjx3eXvyOSxc997nOXfP9Hf/RHDA0N8eijj3Lrrbdu/TyXyzEyMnLZx/j85z/P8ePH+cIXvsDw8DCHDx/mX/7Lf8mv/Mqv8Bu/8RvYts3v/d7vsWPHDn7nd34HgH379nHvvffy7//9v3/ZBdkmnpnJOwqWIEihFmUfbMt+TFt06S8cot49B0hMI7cVfBhGiwghmRKHCQm4znorBWGxJ/deAIbSETQKheZRfTeN7jRKJ+wuHKAbzFDJ72PI3kdH13iDd5j7uhdIRUyBMu3IoyBtTCEIUsVaGtHUXVSoSbViPYoYoI/T8gyByhaMz1/8bRZjABV7kqI9hitKlNUAdbFMIkOEMBgvTXCxeR9p2sncCLXBxfZD2NYQqQoZklO0YkWDNovyHDl1NYGOsIWFh02CItUpK5FiRa6ihSLW3Y199tKOcEP5/TSiiwwWDqJ0jKdLJMYgbqGEn9aZbd6LVlEmbcqlG+58E9S751E6QSIxMfhC499jGCVyzjCREVJmBAsbKSRdWsQiROmUWIa4usR8+9FvWIzZ1hBxsorAwHVGydkDrLcbWwtK2xogjBYx3MmtwmezgFA6IW8OcaL2cVxnjDhp01bL5OxBEtXFj2pggyltLOkRK58k9XHtPtr+2Vd0/AJIo7jx/F/fz8/f5x1/+pLCpRHNkaSN7P7SQ5PN8IVJCyGygizVCR1/iXTDnv+bwTBKqLQFQrwseZ4QFuBjGsXnOSFKpDAv6yL47SjGgI14hEu3eXOfPRetk0sKjc19/+0oxuDr++iVFDYCkckohQVCftfmxl6pS+WrsZ2VwpU0IhtZNEkWInZfV6dxdiOoXcMn/2qSd/9yk5P/P0GlkDKwL0TkLejEYEqsCQvtJyAFOoF0OaS14uDHJs80LG4eyKSFX1pU3DZs0UoEu0su61HC0b4mj6yXONEW7C6BKRWWVJxtFnHbeXJmwmzX49ZClyCVbM9FnGk5mBICJTnezIqg9UjSTiQDDoQqmzlaDCwqVibL8wyNITTtRDLfBduAP1r5b9zmvZevhp/kdvdHCEVKO11mXQWUvSneOfhhyrZAa3indy22hLfI11ELE57gKXbovQCsBwmLaRNL9rOrEKA0zAcG2zxNLh/x9NLA1gzWoB0QRiYVL6ACtAKHm0dWaPgOlqFoRTaLvkusBMsBLIY+jjBYSSKassX1uXFqoWKPMcKIl80n7S4kFM3snO+zJDlTEaaCpxo2Cz4kSnPbkKIRafI5eIt3ByNudt5KNDNdG9fIioiiqekkRnYJS4utea3Zbib1dKUmUoK9xhjrcT/HxSMcrfxDHG3TkA3aos4NuSFKtuCguBpbalzDQKNZC2HYkwSp5qvra6wby7wpv4+V5iO8buCNDCVVJnKaexYSKo5BouCiL3im5nN1X+ZgmGhBK9a8vW87scqKsTDNCrLVQG1Y1GvWo2nG7aszWXn72MZ7QnbxYZhdVClDChVzD54tacYJhhC8o/yznFDnyOkiR5zxTGIYgiULLEVdhtQQOUPzt/PZSscSgr2V7L0/Z2pSLeh3MjfMSGXunYnW1EJNJ0kJdetbPl979Ph+4Xtasvh8Go1s8dLX13fJz//kT/6EgYEBDh48yK/92q/R7Xa3fnf//fdz6NAhhoeHt35255130mw2OXbs2NZt7rjjjkse88477+T+++9/0W0Jw5Bms3nJV48ePXr06NGjR48ePXq8Er6nO2TPRSnFL/3SL3HzzTdz8ODBrZ+/973vZfv27YyNjfHUU0/xK7/yK5w6dYpPfvKTACwuLl5SjAFb3y8uLr7kbZrNJr7v43neC7bnt37rt/jN3/zNF/w8SjWLSRYMaUmBZ0pm/A4V0yFJU9rhIlLapKpDknaJw0xe1188jCW9jStna5xhBTQIJG21wnLjQXZU38qY2slrjDtYLjTop8hn6/+OofIN2MJjPN1GxXRINbw2P0UtTGklCZFStFXEigqxMbGFRSpSHow/xRXWrfjaoi1bmNqiHkxnryNevuQqfc6d3JJFKhRztbtxnXFWrTK19jEMo0Q5tx1D9jNUPMx69yz9Yop76v+Ba6o/RVvU2Z7uoChtKrZkKCmTUwdwpEFTJwgt6QqflAQDE6U188nT5Mx+muFF0jTL5Xl+p2bT3KC/eJhI+8RpZ0s+uGIc27q950ywo3wHHbVKM7yIIRyK7iRCSAbyV7LQuI99lR+noHK8pfxPmBazBLTx6dDUizTjBZLUp+xuw8TFxGElPoUf1V7UEOG5FNxh6p0sE6wbzNANZi75fZJ2tvaxZfahdUgxtwelYtr+OYa8fVxT/SnOhPeiVEKsfNrhIkolSGmSqIhm5xRCSBx7BKUi4JWZPGzyYh3ITTbltVI6uPYgrlWmYm7HNvJ0o1WSNCCM6/jBRUyzShQvZx3AuEa60X16ed0t+QLjj61texlKayEkadrMujgv+J1BGC29KrLJl+tseLnnerGOzSvt/HwrDoNKtS/5/lJ3z8tfs9NoBCLbTv3tk3l+L7LeeppU30k8H2HmoDsnqOxL+ZtPT/KDb6zxoz+5BPkq+368QzIXI0yDeC7AHLTQ3ZRoPkFuHpISUBAEFhc6ebblFGc7NuuRyQd2xMRa0IoNjlZD9gzUiGKDnaHDjjyESnLfSpXFQDLuKa6pNjGk5ujgGufXKiwGJkLAaA62eVlX6HBFsRqaSJFlZ+UMWAwNLPF1edupumJPWTLiZj9LNKx0FNvzN/FYcg+vd3+ULwYf47D9djyjyj21/8CdlX9KzhRcaCX0uwZn210mczkeDy4yqgeI6dIVPpa2WI9DHmr/MW9OPsJSYNNOJFLA4YEa0lAcGFqj3nEJUhPHTPBji1hJFrsefU7IeuBgSUVOJzy4VuJAyed8x6HPEZQNhysrNiuBy8Wuzcl2k9cOVGhEWXDzg6sGn2wFjDgen6j9Abfm3sdNgwWm8il7izFFy6Joav7v6XkOWRNcXYkpWzZlK6YemUzkNLsKIeuRiSsFQmiKZkqgJKnWNONMtmgIqEeZ46HSsBoHTMvT9LOd88nDjJoHGFCDBLKDn2rSEJqRYi0KGc+5nOm0yQmLMHUYdCW39fcjGOB3Zn+PHx/8dVpJwsGqRyeBw/0mqYZGBALwDBNbChb8zFjFNQR+ApHS9DmCc60IIRwudkP6HZvH1UnCuMGJzsezQ1I67Km8g9nuQ4TxGkVdJEFxT+M/cFv5F5lRZ0iJ2ZbuZcDIs4spPt34d7yx758TKU3Blnylc5qWXOFnBm7Ckik3D0tmOoK8mXXDWmm2X5px5hRtCLCkxrbhQiulZEuEgE6y9t06zXv0+I7zfVOQ/fzP/zzPPPMM99577yU//9mf/dmt/x86dIjR0VHe8IY3cPbsWXbt2vVt255f+7Vf4yMf+cjW981mk23btqE0TOQNIpW9yawFmpiEp/U0UhoM5w6w2H2akdINJDpkufEgY5VbUTqmHlxgNleiEc1xo/lWNBpfJ5yTIQerP8HZ7pepWxeoNY7hORP8WPUn+dD4/75la+8Ygse7CxANsp4ETMsTXMVhHEMyaebxUy/bpihih9WP5HWMygoXVY0ONea7jxFFK1+fDRGSzTWeaWRFaa19jBrH2Fd9NwYWa3qawdJRNIrV5mOskzn6GUaeETXM4aF/Tqo1ilE6OmFWrWGFA7RVxJKcp8AUg7KIrxP6KWJLA63hvJinKIdppyukKkIgkBtyxUtli9kb91rrCQDy3hQ7qm/D1zXq/gUMewApLZqdU5zZkF0OlW/gIDehzOzFaa0YK+/FUQ5n5UkC3WCx/iBTlTdRVQP0M0jb3oFCYWmbhljF0g4dmSOMTr7kcbK5LzedDou5PbT9sy9YwCvlo7ViR/WtaFJayRJKx0SqRcHbSStZYjk+QTeYYbB0FNcoU8qN4esaAJ14dUtmKoWJkJIoeWVd28vNtV2OqrcDO3+IRIeEaZO11hO0rQUAongV06xQcEZJVIhjloiscmZRn7RwjdwLitEXQ2t12cDll2KgdIRUhWitSFRInHZJVUAULW3dRgoLIUyUfnVkdi+36O0rHiJMWnT8aYSQWwHWr8o2fAuukFIWkMLcmr187gUGrYIXv6MQW4XxN+uM+M0ihLnlPvnt5vnF7mjlZip2hDVqITwLW2mEa/LO9y2hlmPSWoLlmkQnmwgTrKkC9qDM/MCrEmMwRSudfQ90T8asdz225zsMOiZBanCqlc1Q9VsJEpd6bLHe9lgLXF5z5UUAklCSxJJ6M4cQmmfrZbQWTEnFcL5LZ7XAqJeyPZfwZN2hnZhcWcysyjtJ5nAHULUUGvC0QArNRVvSZ2cLZSkgUdliXpGySx5FCBjzriGnHG42r2NbeS9N3eWpRsKA6SGEoN92GXAFb8tto5toruS1LPops2ELhWawcBVBKmjEBm+cWEQIyBdCum2bu2dH2JEP6CYGY+UWOTciCC1SJXDNlKobIoSmFrjsyEUca2aFiSs1O4oWRUvTiERWmGiDYVfxbCNlOTSZzMPbxiyOtwxuGfpZ1iNBLdJ8Zk5xy3BWJW/PBfyHfQN0kxhLKhINZ9oWuwsxjcimHpmc75jsL8XYUqGAvJHNVOVNTaIlYSrwE4FlCy60E/pMFyPdS5/lsJ1RntAPcdTbQSPM8wX/YX5+5HpascHVlkc3AUEB2xA80axxoevQosN7xgb5t1d8iEgBZKHSsYJTDYVjCIJEM1GQ7C5ZxApGPfBtA0OwYSsviJTmlDiN61/JoGtz0fep6QsM5Q/QcQZJVETZniDS3Y1Ikw41WWNID3Bb+Rdpyhbb1RWYSKaNs1zUAf16Aq0V455mKp8V8VP5PbjGHmypqcWScy3BxW7K9oLBmAegCRUMutk1iXam4KUVC4SAr3XPE4ouyd+Tizw9esD3iWTxF37hF/jUpz7Fl770JSYmJl7ytjfccAMAZ85keVgjIyMsLS1dcpvN7zfnzl7sNqVS6bLdMQDHcSiVSpd89ejRo0ePHj169OjRo8cr4Xu6Q6a15h//43/MX/zFX3DPPfewY8eOb3ifJ554AoDR0VEAbrzxRv71v/7XLC8vMzQ0BMBdd91FqVRi//79W7f5zGc+c8nj3HXXXdx4442vfJuBc82EJ/VJXusc4GvRMfYbV5Ckozza/cTWYP5S0sA2q4xVbmWt+yx5Z5CduVsZ1+NI8xCuYdBMIlJSPFGmqZeZyF+HRlGsjrFdXcl6mMmazjFHWVW5KE9zR+46TClotiKu4jBDnsVKEHOMkwym41yUp4l0mz3RUdaMJcqqQEOukdNlPKtKEM6jNq46KxViWwOAxA9XsK0hyt4keaOfnC6SiAQDi1p4niCcJ+9N4YdLWGaZ4fwhlNIsRQFPqC+TN/pxRJHrrL1005RpeYIbzWsJUsVy2kYiWJVLGNqiX/VzvP1X7Ci/jqq5/evuiumlJgdb+3yjQyGlR9mZJEcZQ1o0xCxR0t6QzGWmGpX8Ptbaz9AuHuZs+iB5c5BItSnKEWba9/P63Pt4RN3DteWfoqpLnJEnuND4EqaRpy+3h0i1abQuUM5tZ7319AuymJ7Pc6/gS+mgdfoCGd4mYbzCQvcJgnCegreTtn+O0crN+PE6o+YBZtQjTFRux5NVlsLjtLpnqeT3EqUdOv40A6UjrG4cX34494qNM5SKMI0yCa2X7Hi0ooUtJ0jIOj+QSbkssw+Noh0ukCR12rw6HZGXSztc3Mr+eq6UcFNmCWBZ/Rsh0K+s+/at8tw8OK0VWl+6j79dLorfiDRtooV1WcdC2x4mildfYDTyrbgVvtixIMjc1b5Rt2/zePp2dseee8xubs/m8VSSo0x38lzrtQmf7WIUBWlHY+QEwhEYZQPhWayczjHxIy66FZJcaCELJt1TCdLSJIFkabHE9kN1OnWHvpzPZ2dGmPCy0GFDwMdnPPocydWVmDEvYLS/xTa7jmErVCyQhiLq2ESpwd2Lfdw00GDez8wcFtp58qbGFFmo84irmPAi7l31uHWwSysxCVLJSmhgiCy7K1GCeiwZ9TSNWJBowdlmStHK0qCOGvvoyxtcaIcshs9wyNuLELA3V+Gr4TH2qN000ogrHYtmlDn9dRMwJcx1sm7glFtiOQzZpa/lwbUWtwxY1HwPPzERzQJXTq6wM5+dF0cnFwlDk7OrVUypcY2EbmJy30qVqystvrBU4upyxKCdcKph8snWF3hn4Q2YkeBs2yfUCXcMF3m2CXvKFttzMa7MgomVhrVIcKquONQnGfWypVDVTlmLbASZ4cR84FC2sn1Xi0yw4DMX4UN72mgEsRIoLVgJLcKN/Te/kQFmSrClph7FfKb+b7m6+kHMeJBQp9zu3MzJYJUrrFEmCxMYAlxjI3RdQCdRPNtpc6hYZaYdsMPqYykQOAb87fIqB/N9TBY2AqONrPN1dEBuyU4FmtmOJtWa9TBhPQnY5uZ5KD7Fa6z9PBKd5qjeQ7/tUk23c7b2qS15eZL6dIOZzBW5cC3bGSFvGaTaxk1s2gQsyWXKaoAlzqKE4vbyL5FqwVJX0E70lpvixY7i9SOCLzcW+MGhMUZdRS2WLGwYxTy1HrBOi47o8ObKFH/dOM6N9pVcY0/xtehJ0u/Q50aPHt8LfE/b3v/cz/0cH/3oR/mrv/or9u7du/XzcrmM53mcPXuWj370o7z1rW+lv7+fp556il/+5V9mYmKCL3/5y8DXbe/Hxsb47d/+bRYXF3n/+9/Pz/zMz7zA9v7nf/7n+Qf/4B9w991384u/+IvflO39R6Z+HUe61CLNepDgmZlL0lzU5KS6l7XWE1uL+GrhQBa+aw1TFdvoU1USFE/Ff8uYezWn1j/BUPkGgqROENUwpL3ldri/+h4ArpRT1JMQQ0gsJMvUebL957yz/CFcQ7KzZGzZyiZKE6SaxSBkUayQU3lWjQUKukJBFTjFQyw3Hrzs68t7U1jSw5AOZXOC8/XPgNZbi5XnLyZz7iSuVeYG406aOsDBYsY4h6UddjGFRLC9YG/Y8GaL5iDVxErxrJrF1ZkDZU0scaH5pcsWMEKYuPYIUpp0/Gly7iR+OLcladRabS0in7uY3LTql0gkFm21gitL+GkNz6gyqCextcOUXaGVJIQ6JdWKrvBRaBpyjY5apZuuIYX1knb8r9SWu5jbg23kafjTJEl9q5CwrSGG8vsZZhdlXaIm68RE1PVFhDDoJNnMX5L6SGlS7zxLJue0vuFM2CtBCBN0SiG3m04ws7UoL3g7idMue/JvIBRdYt3NJI2qnf0dO2cukcV9p3muzHVb9Q1ondKMFwiiGqAyi34db3x9exYBl7OJ37Tjz7mT5O0h1tpPX1LoPFea92JzYq+GlXu2LS90MH3uHN/mOW4YeUyjuCFp+u6aGb2U6+q3i/7iYX6o+HZ+9/9zgXgpxihK0oYi9cHqE8iCgU40RtVB7BnJVqZ+mGn/AMIY3QlRaz46UgSzKXMXKpyslYmU5ELX5KpywGSxjSkVhVxIFJloDafWqxhC82TD48b+NvO+iysVJStmLbLps2OqTkDZC7l/YZCVyGTCi7GEJtaCpcBkX8mnaGUzpku+lxUogCMV3dSgm0gsqbnQNTleVxztF8x2BbPtlG6asq9ib839nGsm7CpZ/OHaXby7fAdPNhrsyZe4zz/DGwp7uK81z6jo557gE7yr9ONcDLrsKxVINeRN2FdS3DK8xprvEqQGg17AeuDw1dU8Hzo8jVuKCZoWUmoC3ySOTbqRRSuykWjWQ4czHYfVUPIbp/8FHxr/3wFY6MZM5G0KFkzlNUVTESrB784s8tryGLaE2XZKrLLz6axa5M3VbewspDy4KrhjJKURG6Qa5v1sf/TZmql8RKQk2/MdcnZMkhooDX5iEitJNzFZCS1WIoNWnL3GexZD7vb/lDfn38tK0sHCJCRmf76CJQVlW3DX+gJXecPUwoSCZbAQ+AzaLk8kZ7gYPcmb3B/CNSS7ywatWG/I+8BPFLYUjOclO/IJ9TiLKBj3UhYDg5yR/d07CVzsQqqySAA/0ZRswUI35WMr/4Zt1TcwW/si26pvwMBkSE9xMr6Hij3JAX01tjR4XD+GgUWo2+RlPzldYiZ+hFr7GG+v/m/cMuTQiAXroaITa0q2xDOhamcXql0DduZjUi1oJxJDZK6XkRI0Y8HFjiJvCWIF51sBNd1hTp5itvbF7+j53aPHq8vLt73/npYs/u7v/i6NRoPbb7+d0dHRra+PfexjANi2zRe+8AXe9KY3ceWVV/JP/sk/4Yd/+If5m7/5m63HMAyDT33qUxiGwY033sj73vc+PvCBD1ySW7Zjxw4+/elPc9ddd3H11VfzO7/zO/zBH/zBK7a879GjR48ePXr06NGjR49Xwvd0h+z7ic0O2QdHfpV6lIVGrqYd9ucrPNtpckxn3TGtFYOlo6Q6xDWqBGmNMfMqHO1iYNKQa1zJLuqpz5pco8Ei9XCGAWcPpnAIdZtWPI/Wilvsd9BWERfkswS6wXYO0RR1CrrMspimq+rkZIXtKusuzsgztNJFpuS1xCLiZOdvGc8fRQoDgeT0+l8A2VXxvsJVrLWewHXGMKWLlBbdcAnX6iNnD1I1ttFSy6x2TuJYZQxhEiQNwmhxSyZ2feVDGNrg/sZ/ZqxyKxUxRlMvUhHjhKLLUDqOh01NNBigymPqHgxhEak2B+TtfK31X+kvHGKl+ciL7ve8N4VSCX44x1jlVmzh0VV1DGGy3Hoa2yyRpF2StInWCQJBztvOoLuXepSZS5TsCVa6J6h6O4lUm1rnDGna5GD1Jzje+ATDpaOsdU4TxcuMVm5mof41dlbfzkzrXmyz9JImFVI6oBVKxxRze9A6pe2f29rPzzWEkNLD3pCNZvlOJs6GvM4yC0RxE8NwCcJ5BALHGSWKa1hm+RIzjmrhALX2sZc8Xp/virfZqXk58kLDKOFYlUte9+b9h8o3EKdtau1j9BUPXSLT+0byzsshhERgvGLXwcttM7ARsDyA1uq71q27HAIBwviWunOvtBv7gvtvdNq+m46JL8ct0rYGiJN1tFbf0OHy5TpgvhImKrfzwf5b+Y2fPEv3rMKuaFrzFk4uQUhorTsMXh3xxc+N84a3zhPOpQgJVlUQLEISSZLIIIoM8sUQrQVPTY/w0HoOreFon8+JpsuRapucmWBIzb3LVa6qdDiwY4k0lrSaLqkSPLXax2S+i2cl1AMHx0gJUpNECZqxxccvmPzQZELZSlgKbJZDk/VIIEUmpzMEbM8lPNOwGPEUiRLMdEABIy48tpaQaM16ErC3UGChG3PtgA1AM4alrqJkSyKlKVmCYQ9SDZHK/pJnmopUa1aikKmch2cKipagGWmaseJd27JtW48sglSyt9TiqXqJspUy6ITkzEymOFro8GytgmMoFnyb9djgtqF17l7qY8GHZqSZ7gQcKHs0Y83H6h/jPZUfwzMFR6qK1UhSNDVjXsS8b/NkLctxUzrLvuokmcRyoQvX9CnWIkk9EuwppJxsSc41EybyJmM5CFIomHCuDXuKmj5b0U4kg07MA2s2Q272eJaEegQX2inzUQsLkxHHwxACP1EMeSatWNGOU24YtOimWXdorpOyGAZsz2Xz680o5Vyyym2VEWIFf9a8m1ut22jFMSmax9Q9/GDhzVQcQcmC8y3NkCd4aj1g0LVZDEJWqbHLHGJnyeTjtce51TnMQ+EZrjZ38tnuX1C1d7BdXZHJzUWHIaosUyMSEXXmeYNzI+f9Jl9u/EemqncyoCcBmNFPYQuPvBzgpwb30U4EJ+sxBcvYOo+HPcnvr3yS6823cNOgR5BmRiq7i/C1pRghwDUks2GL2waqfHW1zsPhX3KV+1bW5NLWuqRHj+9PXn6HrFeQvUpsFmQ/NfqrDHserpF9IFkSvrzkE+iI8/IEc417KXlTtIIZPHuYHe7N1JmnyCA5XWSQMjXaPNz6KIZ0KXuT+PH61iLesUcQQrIjdws2HjPxI1hGgU60xKC7F0cU6ahVSmKEpl5kH9diIUnR9Fk2iqwt6hgSP1UYAppxwgUWmE+eJkyahHEd2yrR8aexrSEquR1Z4CNgywIlhjjZ+vQL5FdCyC0ZYyW/j6q9g2Yyz5B5BTPBQ5SdSRxRICVmPThL0RllSl8NQFXkSdEUDQtDCiwheDqeYzZ5jCBuEMZrG7KpzJLbcybwwzlsawjTcPGsPhyjRD3IArM354jg0kXe5v2eK3Uq5ffS9qc3JJCDOGaRRvcCJW8bo9YhNAoTh5QYT+cxMCnpPBeM8yyFx1+yyNiUdxnSJkqapEnjGy44nzvvtImUHqBQKqSS34dl5Ld+Z8kcpnBQOmale5Kd+VtZTp6l1jn1kgvrb3W268VmnqSw8NxxlErw7CoFcwQ/rVEwhpht3fcdccaDl17cG0YerROUCjGMElqHWGb1Bfv9Ozn/9lw25w2/G8/97WazeH85PP9v+N36ezwXz5ngv+1/P++86TxrMzlsO8mcXhs5BvvazzWfxPZS7D6NtAUYYFTtbKgKEG42t5QudXnq7j4+PlPhdUMBiRb4aTbbNVXo0IlNKk7EWuBSsUOGKm3OrlRpxRYLgcVHL3R531SOTpLN4B2ptlkJHR5edyiamgEnc1Y81pCM58ASGlvC2bagYsP2XEqiYciJCZUkUhKBps/OZJD3rmS26lGaSd9Xw0zueHTA5d7lNrYwuCiWKakSbxup0EoE/Y5mPRTMdRQXA58x12U5CMkbFgXLwDUFQ65gTyFhWy7geDPHgJPiGSnrkcl0x2DcUxysZEWp0qC1wDZTSrkArQWOkzC7UubxWolH1yWjHjgS/nDlBDvVFIf7cuwtpqxsFGN9dkqYCk62TJqR5mI3ZsSz6CaaZpxwdMDCllAwNRc6kifXfa4fzGbyglTzxdo8t1fGsCR4Boy4mliDJcA1FFUr249lK6GbGsz7Nhd9yXxXcaHr09Y+eVwuGOf5gdJB1oJMejiWk/ip5v+d/33eXPggAPXU55w8xqjejaENRowSozmLjzc/zevtO1mOfXbnC5zo1FmXywyrMXLCYsRzWA4idhYdLAmDDgRKYEtNKxaM5xS/8My/4v/c/X/SSTTLvuJ4uEhDrjKYjrNqLFBVQ/iiy/HmX3Fb4afpM106acwZeTaLxtEXaYYXty6IGNKhz57iztx1nGq3qRouf1n7bQ5XPsgV5iieIdFoLvo+u4t5KjYYQuAZGscAW2YRDInKfva5iwmraYe2bBPQ4UTt49/hM7xHj1eTvyOSxR49evTo0aNHjx49evT4u0yvQ/Yqsdkhe0vlnyKwKFoWnSShalsYQjDtZ+YGF40LJDpguva3DJVvYFJcRSoSnmp+nG2lWwh1m34xxRVyG1pDVyUoNKfFM9SjGaQ0MYTDSvMRJqtvZKZ2F3v7foRIdykxSIs15toPYBo5UhWRdwYxZY5xuZ+WyCRau9SezTxSHlV381rzTbRVzHl5BoFkJTxJ059GKZ+R8o0kOst1Wm8/BcBw6QYmxEFSkRAT0WaVZf8EcdImSetbEqHNbtRQ+QYkklj51DonLpHWNTrPsr/ybgLRpqj7cLTDRXGaPiboiiahbrMWnEaphCTtbnXuBktHWW09QTm3h3rnBJB1ukxps908SkusE+kus7UvII0cSoVbV9aFMLHMylbeUjG3ByEyJ0mNuqSDY5oVHKtCkgbESY2cM85e53W0ZQNbe6zpCzTCGTr+9CXHg2OP4FjlS7pnpllhIL+PTrxKlLRe0I3ZJO9NveDxLodtDZGqgKI7jml4RBtdB9vIozdkkrX2sZcdGrwpebuc+cQLbisdtIq+4eNK6SCESd7Nsmo6wdw3ZZzxrQQfv1y+GwYR3w42ZXrf6j77Zu7/vdDB+nbw3H0xWX0j/2HXEY6MrFIsBTw9PcyVo6usNfL4sUmYGpScCEsqCrmA6bUqOwZqrDTyTE1muYHSUhgObDa6/QVJfS3HybUqRSvBMxNSJUi14Fw7z7mOwY39PruqdaLEIExMDKmYbha5d9XlnRMN/vBsEaXhx7YHTJUbLLXz1COb+9Zc+p1s2yuW4mzbYC3UdGLFrpJBydJIYNBJyZspc77FsJPQiA2qdsrploVnwpkmXOzGWFJiiawbV7AlqdJYUmBK2FWER1YVkwWDhW4mVyxZmbFV0RI4huD+tSZlw2F/xaHf0VQshSmglQhWwqxbNORmUspTLZO9xYRYCUpWgmcouolB3syOsfUoyw4rmikPrHusBRoFzHdithUsDpQ1fXbCJ2ckU0WTPkdzsBSwHlmshAahyswuilbWRZrraK7pg8VAojT0OZpWnOVk1UPN091V3tA/RCvWPNRc4VBugNXg/8/ef0dbdt33neBn733yzfflUK8yCoVCAYXADBKkKAZTojUKTWva1nLbXp7xaOxuu73stqfHa023e3W7xzMedbvt8bjdHodxaFuSRcsKlEyRFAMIBqRCoVCo/OrldPM9ce89f5z3HlAgSIIWJVPt913rrbteOneffcLdv/P9/r7fgo/MO4y1oOaUrNkwFxyLNPfGisQI1sel0cWX8+d50D5E0/U4UXP4xt6IUDi8e9qjvp8L188F/bzMMP18coV3uw/x6eHP82PVn+JqusWFYJpACbbiguv2Hg3TYigHrJtXKcyYC/KDSAQTTsRIF8wGPq4sc8oaviQuLKPidXVMxXHYzRJesJ9HCpf3qQ+xpYfc5JuM8h0edj/Cw5U2d8Yxmc2Z96pcz7cZiwELdoEb4iqx6fCoeB815RIoyV6W0fY8RoXm3ya/wDnvg7jWRQvNbfNNPhF9jLgwzEalWY2hZJW1tbR8wY1eGTD+lfFdLnf+8e/NRX6EI/yu4O0zZD/Qtve/H2GwPNIKqDiCQJa9ZC3PcknX2Ejgq7sneVH/JgCP8D7ajs+/3P3rHG9+GImLL6o85p3AlYLVOGFZLHPCLuGLGlI6HHMeZ8K0MY2neM0+x5PNP8mGuY4rIvps0y/WyPIdpJzn0ejHSEUZ7OpbH9/OMS0atAIHJQTaWn5cfoJACaqux/niETbGBV/zxnRHV5mqP8mSeIRUJmzZG7jOJAvVJ1kdfoOn6h/kjt5hWT+Pkj51f4Gh2GSx9m4AYtNhb3ydc+2fYq+4Q2bHjLNdQn+OvBiyUH0nFs1i83EshoptEpkKDRFyxn03QsBEIMk07KgnWc0HLMurbA7LnqTj8jHCZgtjc3RUMBhfpz+6xhPNP0HVVJBCssarBP4CQkjGyTKLzQ8S6y57w5eo+KWdtxCSUbKM67TIiz08dxopXKrRKZKsQ+C1iJw2QkgC0SCkTmBClHGYpM55Z5Et+zi3gitsDF8ky7cI/UW0yUjz3n3yrFZ0hqqaZqP3TBkS/IaCTAhnvzemQ6G/fRhv4M/fJ8f03SaeU6ciJ0CBI3y0zakxQdXU6LQuspx87VDy+p0wUXuUfrLyloXimxfn383VTwhJ6C+SZNtE/jwVd5LCpDQbSzj4dPO79ON79xVA384tUMoQbIH9HfaRvdUYrTW4ThvXqQLgBHO4MqQ7vvVti7O3kpT+buIgSsBREVm2DUJ+2/l/Y8/U2y2mXKf9lv10Fnv4UOXNcJwmWg/x3EnSbONwjFI4mN9lS/oDfD/67t4u3jiXmRkSKUN/HGC0YKE2ZLtbpeJl3OrXeKDZI9OK2fk+yjM8MrGBUJb2qQSbgaoJVNNFVDzwHUTVxzuX4b/YpVJNWd5s8uCFbXQs2FqrMlMd8VjhUA0yKrWUyqIm2ZRsrNX51XWfSy3NZ9br/OkHd/GUxlWalX6NW8MIJSwP1cvCJjdgrGQ6sAgEniwFMpmGpaig7RX4yjDpZyhhmLeCVphwvOIyyD0aTsAD9bLwCBRMeQVbqeTOSLAVa1bTISeqDc7UJTOBYZALfnV4mY86j7BYEVhKJ70Pz9To51BxyvDp9URSc0rb98xYHm5ociMIpOFd7Zi6l1MYiRKGqpfTiBKkNDiOIWpl6FTS64R082lkHdZih/MNhweqMW0/ZTMO2clzzkqHRxsxkaMprODGUDEswBEQKsvJimYmkOykgoXQsJsJtpJyfhIN/dxwLphgyrfMBpbZcIpIgSMdcisIlCVShsUoxVhwpeFiK2NtFPENETAqJOf3LjAb+jw5Adup5XgUcmW0x0P1GtcGHhXH0s9hOihDkk+Z00wEkp+tfIrXejkfas2yHVsGuSExBa7w+Nron/IzUz9LoJZYH+ekRuNLRd11CJRkPlI0PYsvyyK65RliLak5BnC4NVI8v+uRxgMG4+ssHvsoalzDFI/xqvwCmUjxlOB0NWJznNPLc0Ib0JM7tB2fd3OJbp6RWs2yHpCaBJ+AnQwWVYtT/nuZtk3aflmgPeB9jIYnmYskoSplpoEqexoBpvycC3XJbib4yvh3/dI+whF+YHAkWTzCEY5whCMc4QhHOMIRjnCEf084kix+n3AgWfxg/T9jMWhS9SSdVDPhK2bC0nVJW/hydxtlHe6Kl/lo+BS5sYwKzWYxBGDOqXFH7/BYNIOnBNtxmUsiBbw03mZPbpDaIdP2BAqHE04bRwq20oQNucl6cYUZ50EShvhEXB/8Bu3KOc7xTjpyj8BGzIoWqdWsiw00OeflKZqew0ac4krJZXuFO73PcrHxKXps4IiAzI4xNmcnfo1WeJJBus7D/keJbIjBsqJuc2Pv04fsQb1yjrwY8VBYRgfcNc8T53vkxZBasEic75Fkm9TDUxzznmStuMyi8ygTps0deZ0lc4aG8oGywfmevMXa+DlCt0VneIV3N/8UQzFgJXuOlneS2HTY6D1Dq3qBh9UPUaBxUAzlkG17m5Xu5xHCwfem8ZwadXeOljhGJmKqpsGqfYXt4UuAwtr00FAh9BeR0kEKF0d6+KpOQy1g0NRNm6qtsKHWuLb384eGIwduglGwRJJt46gKSgak+S4PNn6MAdtYq+mmy2TFkLzYOWQ15prvIzfxd8w2g/sZq4PMt1wnJZPnNLFWE6gGw3zjPsfFAyOOt3KfE0KiVB1XVfeNTa5/W/Yh8OdJs61v+/sD2aNAEAbHSLJtKsEi2qQEboNxtkuWbd/nCui5k2iTYfTgPkbijcxZNTzFKL4NQnxb97yDv3870kt4Xap5cO5+t317O9v6d8Xb/f+364T4vWaUvdX7v3kbB+eelP5bGqH8Tufgu+Hg3P1ezEG+nzjW+jD/4MFLWAQXF7b45deO8dHj66z1anRTj8kgITeSq/0q75/dJgozlDIMRz61aooXFoQzBllTJHcNlccjbGG48+sOE1MjNjfqnP7gkMErhn/ywin+40dvU5nXIOH6N9ucubiH8KDogdMAW0DvrsdXl+dYi10eaw04MdVFa8Fmr8aLnTq+tPyzOwVn6j4VR9D0LM/vak7WHDJjeaJVMCwkDVfjS8tK7PJku8+tYYUT1TGv9KrsZpIbfcv5hmA7FTzazFmLHZIy85mrPcNkIPnITMK/WPb5kYWCREt2MkVFGWIt2NtnnbSFuls6G7oStIHQKUONB7mg4lh2U4gcwSfmuvzNazX+d8c0E15Gw8vYS32moxhXGnIj8ZTml+9NsxQVfHWndEO0wNNTPXZTn1hLImVIjMQVlrafspf6rCcuFrg5LE1BImXIjeBkJWUz8XilL3m1m3Gs6tHyBDXX8s83V3gyXGCYG3wlmY0EgRI4wjLpWyrKcKWvWIosx6IMbQWf3fBYiODljuGpGUFhYVQIdtPShfHRtmI+MFQczXbqECjL9UHpVLg+NtTd0snyeFWgBKyM4Ep/yJQX4grBqNCMTcE9sUImYjwb8tH6WW70UyqOw/mmw82+5kxdYvevYG1L85VRAdd6hlFuuG7W+GT7ODf7BXeyLrOqzkTgcHccM+MF9POCc02Pa92My1wmtUOO24eZVXVcKZgKHXwJe2lplPKqucMT3mm+kV2na1fJ9IhH5Yc4EVW4Pu7xjmaTqitQwnKtp1mqlvO2m5Ux8X976wusdX/79/waP8IRvn/gTBFMAACGd0lEQVQ4cln8PcdBQfaRxn9O26sSKEHLl2hT6u4DJWn5isJYxoVlORnwQKVOoi0vZ2scY5qPL7gEyuIKy1hLElPa4Ma6DIG8N9R084y7YoWYPo7wmdWLpKJ0vdoRq0zbRQwWgyERY24nX2YU3+Fi62dwcEgY0TbT+Lj8Vu//xY+2/iK3WCYXKeftA3hSku8vdLW1pFaT2Zw92eG90XHavsSVZdZpqmEvNYwLy0aasCV2SMSIzI7ZzW7S8BZRODSY5WbyRbJiyMnaB5BWEtNjUGwyznao+NNMqTPkIiWwVRbsHGOb4uPSET0CG+LiIBE0lE9qNJvsEdmISPgsi2U+Vj9HqMqFYm5KmclOohkUBTu2T0fusDz6KtpkNKOTAHTHN8nyHeaa7wNgvftlphvvYpiu46kKo3STvNijEp5AChdPVfBVHWNzAllnbLoMklUWK+/AYnCtj4PPgC1GepcZdY5XB7/CJ+t/ioqjEKKc02Gu2TUjttQqie0zyNbQtpRdHvSFHcjlDha/305WFvqL+E6NfnznMAS6XbtIZ3gVKX3q4QkKk+GpSrlP+Q5p3qMdnWZneJXJ6nlO2ccIKa2sU3K21Dojs3NYMIIhL7rfUqAcLLzfjrW4505jbUFe7CGEg6Pq+68BFW+acb5DnKwS+HNok5Hnu5xr/jgeIaENGYoBiRgy1FskRZfcxGR5/7Bn8Xdqb17GDLwuBZQy3Hc6zL+l/1AgynPAn2cqOo/CwWDopHfQ+/8fp2u/q1I6KVysLfYLoxBrEoT0ynELB21ijIlpVS/cFz3w3fDmefxee8LeTpEkZchE9QLjfOdbeiXLIOoq1sRvWdQpVUfJAG1GGD3+XekrPHDdPBCQKBlibIG1KcakPNT6af7GA8eougUL9QGDxMdRmqxQNMKUIMjxgnLONrdrjDOXZpjguZqikFRrKZWpHKHAmVCYkUZIAQJMbBEOyIoEA3pgyLqC2h+YhkoAtQiyogyaBuiNsL0EvR0zvAF56vCN5VlON/r8P69M8jMnRyRa8bmtiBMVw3pSOiierxfspIrFMEcIy+e3fJYqEEjLSAtm/YKWV/BLKz4/Mp/jSUNmJMNCcmvkUFjBU5NjBJaV2OfJyQ6hWx6vrHDwnAJjBWnhoI1kkLlspz7drOyScKXlt7ckU4Hkm7tjfmQxYD2WvHciKT/7tCQ1gm4uaXuGtlegRPnZOBkkFFbSz1zmKmNe2G1ypjbCU4aql+EqzTD1uTOoUndz2kHK3FQPv1YgXTCpoLcT0B2FpIVikHusxT53x4pTlfK41RzNeuLy1R2BJwWnauXn8EJoSLRgrAU7KQRqv5fOsfjS0s0Fx0LDUAsyI6goS9UxFLaURRYGxloiBQTSEDmG860uShq0kRRGEucOvcy7L6agk1o8Vfa6AWwn+w/jnLK3TVu4OS5t6Z9u/Kd8M/s3fKr5HwOlbf5k6BCVHRRs7MtLZ70qNVfyYEOwHkOoSlfMgwLzZl/z9Az40hIow6BQDApJbqCbCe4MNIEj2EsLHCF4Rn+NRXOOKVmjsAZN2Zt4th6S6nK8rwx7VIXPhtjlUX+BuidwRNlD1vJAW0GsLRv7cQp/Z+1/+N9EX+8R/kPGkcviEY5whCMc4QhHOMIRjnCEI/zA44gh+z7hgCF7uPkznBJL1F0HJWEjSakpl8Rovpz/Cu93f5S5yKXqClZGmporKQx8aLbMMXGloZM5PN91WB5qWr7i7jBmaFO+2PubnGv/FI+rB+jlOWfqAduxZjOL6Yk+YzGga1dZ734ZgcB1J5isPMR694ucbP0IOTEL9iwGy4Js8Yz+Ao+K9zG0pYlET3Z4ufNPaNcu8rT7I3zdfBWDoS2O8WPt09QcS+iUOTYvdmA7KXjevIQSLtrmbCWvYK1hJnyYgCpnOUnHjFmRN9lJr5PrEUm6duhmN9/8AGvd36Zdu4iv6lTkJALJpJ7jmvkiUrg0nWPs5beoO/Pc6XyGJ5t/knnRZtsMaIkKPRvz/okWdbd8urCdwq1+Tm4NX8p+mcidIhB1ttNrzAQPYazmnH2wlGzKVYwwjG2HRPdIih6D8XXg/nDseuUcad6j6s+S6RFKOAROk5qaZWX0dZrhcRwRsNr7Cg81foI+Wyx3fpN65Rw/Ev0k7UCVIaGp5XKyTl/usZG8zGB8ncCfx5gCbRKmqhdIdZ9RunnoAPmdUAlPlGxS0QNUmXW2/38H4dBSuDSrD9IZvMxC82m2x6+SFx3q4Skedz5OTXn4UpIby3V7jzvJM99iABL6i6T59qEMcKp6ga3B5UNp4ffixnfA9B1IJyvhCeJ0E9+d2M+VK2Wf72n8LBUClJCsiU1uJV8ky/vfMcy5XbtIYbLvOXwaOHzft8JbsW8HQec+IdJKrqWfu2/evleHwrcrr3w7mKo/iS9Lk5Kt0ctv61z6fuG7yRWblfPUvUU8EbGTvnbokPq7OqbvUbb53dCsnOefXPgkNTdnsT7gVrfJdBjTTT2UsNwdhTzU7JNoh8gp8J0CawVJoZisj/CDAr+iKVKBci1u3TLecqid1Lz2tRbn3ttFBBKMRV2cg3YDahUIfBjHmM++hIk1NjHsXPXJMocoyvjszQU+/tBdrBVUFjXDZYfh0Kc7CvjCVpumq5GUuVQPN4asxSFKWHq5ouoYak7BP7jl8fSMRArLbiq50EjZTl3aXkEgDb4yfHazwrsmEhr7jNiJdo9gn2nb3qvyD25M8VPHegxyl1HhMCwkN0cOuyk80dKsJYop33BnpBgVlmMR/MP1FT7WWuRExfLPlvucrzVoeaU8byYwhKp0SxwUitPVmGHusJZ4nKuN+NX1OnXX8kgjYVgonpzZ4fL2BLdGHk9NdTkx16F2UiMjie5pvvHVOYa5wyuDgIqy/MvlMaerEe+YsJyopMxEY272a2ynDqNC8o/X1niyMkfDE9Rc6KSwVIGNpAyI3kvLaLlAlVLLplsyZV/cTHnvtM83dnKennXJDDzaiHmxFzLraxajlOONHtVayvW1CVbjELF/z7g7drncMRgLS1XF6arGFZZuLrnaE4eB0hu6zw37NdrOCd7tnSPTlmeLl3iH8wj/ZvhPedL7g5yt1EkKSzuQpNqSaEs/0yybbT7aXuDWoGAuUsSFxZOClVHO+2ddjkc5TTfHlYZrgwhtBTup4KW9gq/rFzlpzrEUVqi5gm5mmA4l/cyyMk4Y2pRI+LhCMjY5MSlNEeEKxdftl3hCvI+a4zAVqkOXRV/CbmpoeJJ7w5zQkfxW+jk2es98367dIxzh9x5HksXfcxwUZIG3xA9Ff5hlsUbLtLlUb7KVlIVVoOAL/RV6bPPB4BIvxuu8ozqPEnCyCssjqLsCbdkPdTQEytJwyxvzTqbYScub3t/b+Rf8SPST1D1JNzNYa0mN4Qvpv6Y3vsax5odJTJ8l8Qi5yNi1d9mNb6BNwiOVH6dqK6yquyzo46RkzDl1AiUJlOTzyQtIoZjSC2ihaVFjKQpYHif07ZgFp0HVLfXtZ+oSd19ysDKCnaRgL0/5t72/wSeaf4GxzdmVu3jWoyd3uLH36cMg5lPNj6Nw6Zt1dkfXEUKSZhsstT7CGfMwzxW/zpx3kQWzyIiE2zzP1uAFPlj7U8SkSCQLbo3IUTyf3sOxDue8GUaFJlKK0/X94FULm7FhI0751e5f58nmn+Ra9nlmgofwbEjXlq6Fw3yTYXxn33GxtLgHsJhDaVUULDFOlllqfYRhsUHVmcUXVXbzG3SHr1KNTuGpCtPqAXxCpu0EHQYMRAeBxGJYsksshAFKQG5gM0kY24yvJb9IKzyFsTmp7t/X+wWvL/Lf6A5YFJ3DfqoDeVktOss43aRVObMfV/DyoezswMZ/IjiLL6rkdsydzmeAsn9tlO/wpPMJXKFIbMaqusvI7LA1eOFQiuY6bRrRCbRJ6Y1vva1eJnjdIfJAlmlNjOO0Dp0pD9z8Dhbty53fxHXaVPwZeqNXaVYf4pzzfsz+okVTsMlNYt1ld/DC4fbfKO/8dlLPt8KB3O67FRWljf8Sad4lL/YOF/yeO8l05WEyG7MzeOHbFgEHvXJvlOIcnFf/rpioXWKUbe3P7+Shg+hBIflmd863wvcyV2+Ft1NUVsITJFlZ3Evpl/MtQyZrj1CYMaN0G22S77qdwJ8nL4a/K3ImxymdS8voiAIpHJJs7XAuz7c+xZ9dfIAnJ3poI3hmt8ETrSF1L+PesELkaDqZw8nqCM8pG6z6qUcjSLFWIIQl8nMcpXEcQ5Y5SGl4ZXOSByY7zD40woxBpxCe85EzVcz2CFHzSS/3cKcU6kQTfBfmJ8FxIMuxr95Drw75rV9f4MmT69xZb7EZh5yoD+gmPv3cZVA4NN2c9cQjN4KnZnZ5tdvgVG3IIHNR0rIRB9ScgmuDkEEheGpygCsNt4YVrg0czlQ1NUeTW0HTzam5OS91a7S9gumgdGg0ViCFpe5n+E5BGOQ4jqE/CNgaRdwdhawmpfOjK2HCM/RzSTcvw4G1hRNRwaSfc20QHFry93OH45WyIFuojtgcR8xEY2phytXtNuuJx0ONIUmhyIyk7adM1sYoaRDCcne3yUJzwOxD5b3MZpB1BYOOz+WNKa70Az4w1aOfe7zcC3mtD6vjjNfsbX6i/SCBstwdWi61YSeVhMrScC3dTHC1ZzhZK2MEvrJZMBc51D3B6armM2uWuND8R8cVX9qWPD2taXkFgTLcHgXMB2VMQqA0FTdnojbGWsHuIGI3DbjSD/Gl3S+gS2HTP95YZsFO03Bdnim+yR9uv4t+ZnltEPNYO2RjbCmM5cV8mZ+cPInA0vTg9rBcb1ztwRPt0v7+mW3BblowF7loCw/UOfx8KuWVlo1EcizSzAc5SljuxR69XHKtV8YBzKsms6HLq4Mht+U13u2U7osrYpMdewtXRDwpnyBQkrgwdHRC2wn4xd2/xrubf4oZ2eBcw6OTWuqeINFwpT/g872f+75f40c4wu8djiSLRzjCEY5whCMc4QhHOMIRjvADjyOG7PuEA4bshxt/joWwzlqS4AtFzXG4ne8xIxtEquyqTbQhNZqxzTkVVbk1HrLoV7g0IVkbl/KH6QAarkEAddeQasFIS1bGkoZn2U7gVNUigH4hGOSCF3ZTcqsZ24y2imj5DsvjMsijI3oIJNM0yTE4CGJbsK5W+FB0nhuD8olh3fHYK0oJ47paIbAVJkybvhjygDfFdKh4rZcwFXg0PMl8WEpgQmW5NSglD5mx7Caa4zWHUAl2UsvVQY/XxDcJRANH+MzrY/TlgJyMHhusdH6Lpxv/GSkZ22qVOb2EwSIR5CInFSnb9jZT4iQGQ9XU2FT3yOyYCRZ5qf8LHKu/h0e4ROgoaq5kPiqdqQSCncSgLewkOW3fpe0LuplFCVBSsDYqXaNi02FOPohrPV4cfxolPRrBMda7X0apCsfrH+JW598w23gPU/IMt5IvkuZdmtEpBJKKmmBjfBklPWreHHvj60xUzmGtoS2P0zKTLHr1Q6mqxdJJC3bNiEj4NFQ5/5ftF8n1iMKkDONbVMNTVL0ZkqLLMF1H6z5K1WmEJ4icCbbHV/Gc2qFc72TrE+xmN8mKAdYaKv4UAL3xXZT0DrOiWtULLLlPcjP5IjV/jrqcY8kcJ9tniFbVXTwbkjCkk9+m5s5z0pzHYNlQK9zuf47Qm2KULOO5EyTp2n3MTLNyntzEjOI7CASNyoOHBiYHjErgz5Om6/dJ/EJ/kcnoHJvDF/GcOsYWzEePMWnmiEWMRCKtpCM26RZ3CVQLX1SpM8WWvUFTLBDTO2T/DvDd5GtSuAgZHjIv3y0s2vdmyfItpAwJvCmmgnMkpk83uXvIBgohaUenESgsmu3hFaw1aN3/FtbzbYd4v2E/DhwXS1+y+zOzDrb35jyxSngCgcRzyhDx3vgG1ur7AtP/XfG9GIEoVacSzOGpCuNshzTvHn6/N7yCED5CyLcl5/xOstPvBVGwhLEFSnoIJFnRJ893D+d1uvEu/sriR3j/dIdMK76y0+CDM3u82iuffqb798NQaU43+rjSkOwHOdfClKiaUWSKbj+kEqY4jqEoJM+szPLIRIcoyGhMx+RjxepGk3Pv2cM5UUevDMCAWqohGiE4CuanIE3B9+HKHQBsrhHHp6A7xPZi9PqI/jXJ7l6FxbM9xjsOq1sNAkfjuwXD1OPX1yZ4qJYihcWThsgpGBcO26nH2foQVxpWRxFNL+NLO3WWh/DBmZz1xMERcGckOFmxPNbq0808ZqOYQeay0BxQFJJGIyYee6SZw844JNEOrjTUvYyqn/LyzgR7mUNqBLuZ4O9tPc+fnnuMpyZ7fGWnwbRfcKY2Ylw4nJro8os3F3j3ZJ+FZp/1bo1WmLAyqNHyE6p+xtW9Fq6wzFfG3BtWeGhyj+44wHM0czM9wpl9CbKBvC8Y7PkoZRgMA6Zmh0jXsL7c4GqnybiQaCvYyxUbseAPzA3IjeSf3w1p+oIzVUvD1dwdO7gSXtwzBErsyw0FdbcMPc4tVJTlzkhwomL5wqbhU8cNiZbMBimRU+BKQzNM8L0CISx7gwpro4jIKWjus43b44grvQqdTNDNwRGCExXNjWGZ6/WFrSE/PFvltZ7lRE3iScuxUPO5TclXkxv87MIZVsaCB2qlo2S/EKQaClveP272NbtphiMkj7R9mp5FivLp/dlqirYCTxo2U5dOpshtyaQdjzRjXYaZ72WC1XGpTnlxsMt7WxO82CnXGO+erPJP9r7BafMgDzcrBAqaLuxmsBUbPClYHiecb4QsD3N+cfev/Y6v6SMc4d8fjiSLv+c4KMj+b2f+MokJeK2X40qJJwVTQUlEvtpL2GPApKjjCokrBbmxDE3O6WpEzYWb/ZwJ3yEuLI4UXI+7SATvbDXpZ+WNcVxYKq5kOhCcrRa40pJoSXdf8jHIy0O6FRtWkzH31B0e5hxnGi5JUbo+FsaihEAImA1dEm0xFtaTBAls0WGSFj2GzMgGY1NQlS5KCFZ0h1Vx/dBRKVCSXxn9Mz4W/TTbxYhc5NSoMOX5nKk7eLIMu+ykllFRat9zq9kQu9zJv8aEd4Yn1AW2s5hJN2C56DASI86rRcZac4WX8UREy0xyl8ss8BC5yHi5//M8UP8RJs0MBstt8RIVOcFa/DzHg3fTsfe4xHvoMCSyIX0xpGJDMgqerE8QOqUcQ4nyOGzGhk5akFrNhtjmZvJFRskdnmj8CSyGhq0Tk3K1+BwAZ9ynGIsBr/b+FZG/QNNfYnv8Ko3wONZqHFna9rsiYrX/LMfrH2Bl+FWKooex+eHCrx4cQyLxZJX3OO+g5kq6qWaniNFoCjRWGAo0r6afLUOns02m60/iyohpe4Jr6edoB6fZHl89dK2M6aEpWO3+NmGwgDYZAkmhxzgqwnUqKOHgyBAlXDZ6zyCEpBqexndqxPkedX+BzX0LfiEktWCJtneas/ZBFILb4i4AIzoM8rWyb22/WKhFZ0nzHpOVB9kcfBNrCyrBEkLIb+nzOijOlKrjOlWU9LDWvKWM76CnzVpN4M2S6yFKBhiTcbz+fppmGi0KXOuxI1YZ6A20TRGo++SbUBYEjopIs43Dcb8x+FmpClL4GFsghMRR0X3Sv7fbn1QJT1D3F3BFhC+qDPQGe+ObGJshhUOhB4DEmPiwePpe+sqq4SkshjhZfdu2+QCBN4WnKgzTdSJ/BuDw2Bz0+X0n/E7dLb/TNh2nWcoG9QAhPazJ8P25b4lLOMBB36QQDkKo+6ISDvr73m5cwHfCDzX+HH/+nMuZZo8re026uUM3l3xoukOiFb3MI1CaiTCh4mWMMo+0UDjS0E19BoWDtYKpICFQmtAtiHMHz9E0KjHbvSp7qc+lkxt09iKW3jVCRgrdKbCFZf2VKu3pEddvT3LxvTuIQDK4BvXzkG1onKbAPdOEc8cgzaA3hN0hphNjU83Gsy7VRsqtexNM14fMPJGRb2lG2y6rWw3mJvokqUtzIiYZOixvN2kEKf/95SnONwUt1zAsJP96dcilZpWnpjI2EpeNRHKqotnLJdrCQlDgK8ufufEV/ofT78UiqDvltXd37ONLy7n6kGPtHtYKBrHP+rDCqHC4OvA4FhZspQ43B/DxuZSml7HQHHBjt8X5mR3S1MFxDK6rubI+RctPuTeKWIzGCAFy39r9Nzaa/PSpdbZGFTItuTaI8KTldDVmL/WYDcvzYVw4VN2cydqYyWNl8TDY9EkzhzxXGCuIcwcp4Ea/ym7mYKwgt9ByDZcmOtzq17g28LGUYdILoWFUCL6xa3nPlODeWFJ3LTXH8i/uDflPTlQAWIklgSrDsYe5YCOBTmp4urwkMRZOVxMWawNcV7M7jOimHnuZiyste5nDXiZZ3jc4nQqgn8P7Jkvb/c3EoeIYRoUkM4JeDufrBbkRXB861F3Li3uGYxVFaixXuyl112GxothLyyBqVwguTUhe7VlSbXm4Jelk0M9gVBjeOyWYCXJcYTHAbuqymZbnwvq4LEjrLjy3N2LCC1iqKs5ULeuJ5Je3V/nJmXmMhbZnWY0lKyNNbiz/dOu//R1dr0c4wr9fHEkWj3CEIxzhCEc4whGOcIQjHOEHHkcM2fcJBwzZX33gLzPh+XxmLWfdlOzWktNiJizlDN3McnW8x57a4pheoun49HRGTbk0PYeKU7JW7r5rkyvBEaVYRgC/sL3Cir7Me9SHOdf0DjO3xkV5GMeFZlDk/Fr3/8FHmn+esU15tNbic6Nr/KHJB/Gk5bWe5ZnsVdp6mivFZ/l4+BNc02tc8hcBSLTltWIdaSUuLlUbsRhGbCYJHYZMiwZDk9F0fCqOIlCCuLBspDEv8wwbvWe42PoZLnlLh0xcog3bRfn4bk3dw7cRO+YWD/Me7qrbvN+/AFA+Edv5m8zULvGQfZKUHINlQlbYNSO+3PufONb6MIvmHE0RIRCMbU5HdpgyE7hCklqNLxRN1zvcZmI0vz74u8zVnuBBe4kOfSo2ZFtusWNuc0o8xq7cxGLYSl/FkR5N5zhz5gRr8haPyUfIjMGTkt+Mf6E07nAe4Pb4SxyvvJeqafDy+FcwJsPYgonqeRzho4SLg09AFY+QAbs0mMK3/mF4tcHyte7/h/nmB8psOXuKgegwsFsIobBWMyq2D00+6pVzTHpnWR58icerfwhNwfX8S0ROm+3hS0xUH0YJh/Xul5lrvo9ANLjd+VWEcJAyQgqHWriAIyN68V0KPWCu9g62x69SC+YJZB1H+GgK1gffvI+l8dxpKv4Uo3STico5Buk6AKPkDlJWD+V9jtOkFZ2h6RwjNh1Wup/Hcyep+DNkesQovnNonnDAglXCE/hODSlchukGedGjHp4g0yOMKSVkodsGoNhnOcbZ7hvYrPphftXBOHvjW4eZUgfMmJThfvh3aYRyINPz3EkKPcJRFbJ8B6XqGDPG2uI+tkgKl0p4gsH4+n3yPMdp4qiovIbStbctP3yzLLJZOU9vfA3Xmfy2DNUBi3QgsXRUtG+KswWYt81aHYSBH7CTbyXPPGAM38zYvZX5yduRK347VtF12jgqOpRWlsdj8LYdEj13mjzf/pY5fzuGJm9EuH8fFKJ8XqlNRqHH+0xmlx9v/0X+03MZx5t9/urzs/zBxZxxIWl7BdupS8PVGGA2TJiujJDKIoXFWIE1gkJLhLDEuYsUpVHD1jikFaS0qmP+zstL/Cdn11kbVNlJPSJleOLEOrXjBbYA6Qtk3UG4ElH1SvrEWLIbI/7Lf3WW//rj13EnBegyz8wWFptZRssC6cDeVsS1vRbvOLlOdalASEHes3z1hUUuHd9g0A8Q0uI6Gs8v2NqtUQtTPK+g2494pdNgO3VpeZpX+i6jwrIYwWKYYyxYBKku5W9tr9iXJuZkWuIpw7V+hU6meLgR0/RS7o4q1JwyZ2wz8bg1cujn8GDdcHOoeGoy5h0n1ylyiRcUKNfy9WsLPDi9Q28UEro5K/0a87UhvSRgN/Fpehme0lT9jDDIGY59CiMx+7K8ZiXGWoHWkiDI+Y1bC1greLAxpBUkpIVDP/PoZS41N2dcOORWEGuFJw2/dM/lQ7OGl7qKP7TUwyCoeRndxOfX1uvspZYPzhT81qbD+yY1d8eKmcCwmZSMUcUBR0Bq4GSloJ9Lqo5BCUukDDU3JzeSQGk+vVojLuDDs9lhFttu5tLJJdbC8liwFFmWx4LjlfLcL4xg2i9NUWpuTqId7o4CAK4PFSsjzTsmBXbfQKywcHsomPJBSThdydjLHF7pSZ7p7vKu5gQLUZk92vbK9zDAa31BP7OcqQs+s9ll3qvhCkHDl8SF5dG2YHkE13plQPVhbpsrefeERgnLauKgTSlZ9KWg6li2EnioYfjKtuDvr/83b/vaPcIRfvDw9hky5/dmQP/hoJcLVseCh5o+9dEkF5olxd/PDYm2hEoyJWvkpiw0cmuYdH3WszGLlRpxYdlKcno6JREJkQ1pOj5X7A3e4z1IyzS5Y2IqvmIhBCEgM5AbwcoIMiNouh5/dPa/5G484rhfp58ZLqrT3OxrUm2ouor3eA9SGEuFH8GTkom8TVwYcmNJjcYIg4uHsJKCUmbY8jzSNGTbDnim97d5rPXH2MmWmWQJ13r4eHj7dtux6DMRSJSAUQGjsUYg2ZW7TOo5ADZsSiwyGmaSblbwqrnDGY5TCxZ42n2Kf7b933Kx9TNYDN8c/yKz0UUebf1R1vQVxmqEYxQFmkyk1E0dg+Xr5rfwZJWanCYrxgz1FjU1y6RdQOs+kWgx6fg8EMySacuDog6cYZAb8iwnFQkPuB/g1fSz9FjBOobYdPh0/2+zUH8X8/o0k/5ZJuwC1hqq/izb+TViZxbPqaFNSpp398Ojp4htB19WKcjZLm7QHd/CmJRm5QxJ3kObjFowj+/NMiNOM2snSK1GWcWOvYUvq2hyqu4stdY8se4Qqhbb6TWmqhd4cfxpLkafJHLa5eJahrTUMca2gxAOqe6jZbFvr5+VhYY7jSerZS+eP4uxE/SyVdJs47C4gXKBbN4Q8isQ1MNFFtRFfCco3TuLawjhMFG7RJJ3GcZ9xH7AsiN97g6+SGVfCteMTpMUXZJsDylDiqKLFN7h9pNsD2MK4nSFeuUcSnqM0u37ipI3W/IfSO8AWpWyADxwsxRIHBmWxZ0e4jl14nQFY+IyWBlTFgf7BUTFn6EzvEK2X+y93kdWuW8MQoYk2e5hwXBQgBRF976C5Y2FgeM0aYQnGGVbWGuoBfMUOibOO9/S95QUPaQMD9/zoMh5Y8F0UHAZmxM6M/f1h70dHDpKyir18BhxViUrym373iyFHhy6ajoqIAUcFd23f28sxjx3kvxtyiutyd7y53mxR17sHe5nXuzhOpOgTOn+aO39/XFvKv6KooNUtcMA5wO88Zx+O/h2c6n3X/eKhMgxDBKfj89rmm6OEg67mctGqkiNYDHM8KUuZW6JS1I4aFMuRg2CQBV00oBhoRgVitwIbg0jom6Dx1oZmVZsJAF1p+C9F1YIFgQmhfWrVTyvwJiyWKzWRwz7AVElw/Elf+zMLqoC7kOT5XttDzGbCaNlgRMaMIJeHPCBJ+9hMvjcF47xxPENRkOf9//QKuk6zM4Pufb8BOffvcftbzRICodk4CCxTNZHVAea3czBEYaLjQxXWCpOweVehAG+slnwsQXBl7bgbN1HCmh7AcaWPUVCwM0BXGxYan7Gw37GrV4dbQWZkZypFkgBm4ni/ZMxM2FMEjvc3W0yKhzOtrvcHvmcs4IrnSbHojGuNNzpNZiJxtS9nM0kQALtwqFtElylybTi8l6D1cThsWbMsFD40lBzCxqu5is7HqeqkmY9xvE09X5AZ2uCG8MIX1rEvgQyVJaTNcH5+pAZ3+fWsMKtkcOJqGAvV3xoesRa7LOXKSIFvaLcp83Uoe1ZXhsIdhJ4oG7ZjAWLoSBSZS/ZqwPJAzXDSCs2E8XVnmA6FIwKy6nakExLCivJrWBYeGxngsUIpnxNahwajuF/uT3mjxyvcC92cGUZ3D3l52wkkqen+7w6qPOHT6Q81wkZFoLFyJAZwaWmZjVWLAQF2graXoGnPB6rTfBjC2Ou9kM8KThZSVmNPTYSyYkqgKDuGP7MmSrf2FO8eyKj7mq2Epe9XPHB6YwfndcMC4iUpu2n9LJSbrkYxUROSGYk7/IzjIVX+iHvntTMBgm/sRZ8T9fuEY7w+xlHksUjHOEIRzjCEY5whCMc4QhH+PeEI8ni9wkHksX/4tT/hVz7zEclcxUp2E4Fs4Eht2W2xq9sdLhmv8I75YdZFztM2wl8objLBgN2WTJnWPQr5LZ0LQTo5wULkUeiLbfGQwAeqtXopJp2oOhnhlQbOkXGDXGV8/YCjpDcZYMHnQWUgKanUAI8Bb3M0vIF3dTiKcFOojlTd+hmZQbMb4+uM2Gm6Mg9NDm5SMnsGIXLVvIKH/B/imviVebMCSSCVGS0qJHYjDV1r8zb0qfIKZhzq6TG8Lx9jgotCpEzNOXT/xP2Ue6JV3jQPk5H9JgTE/RMzJxb5U6xxwQ1JjyfUaExWH65+3NE/gKz4UVc65OLlJHZYaP3LNYWHGt9mDl7BihzqjpiEyVcGmaSLXGHWHeoqmnmzSlcHFIyPBwi4XFHLHN7/CVmo4tEtNjWN5hSZ8hEzJI+xVCMGYoeLTOJi0NOwY7a4KI4S0+X836n82tIFRH58zT9JcbFLoNk7ZDtiIIlmsEJlHDpJLfxnTqhaiJE6cA5yNY45j3JgC1GeheLoR+vIIQkdFukxQBtEiYq50iKLr6qE8kJIhpsmRtMypMklOfHQG9wWj5JX3S5PviNw4ypgxytN7NNB4zPgblEJTyBkj6jZOWQLYGSQXFVhKtC+vEdIn+eNO/gOXWG8S2mG++iO76JsQXGxET+Ao70kdIhzjq4ToUZ/yH28tso6bPVe3Z/XN/eIOKADXmzDFAIiRDuYa6VEKWRipIekTdFP75D6M8c5sgdyO8OZGxS+jiqAUDgtUr3R9WkHi6V7pDJCqC+73lXjtMkcNvfcgy+3d8WRfc+F0HPnaYoOoc5bm/EG+fojXN68PPvZkTyRiburUww3kqqeOj0KCSOan7HPDOBQEhv/39SrEmoRmfuO4feLt6cnVaeA/v5g/vn7AEbCK8bf7xdvJXs9NHWH+V/vtggdAvuDKpM+imjwqXq5nx9t0bFsZyvD5mtjXDdAsfZn38BeS4xRlIUkqxwiIKMQVyes1mh2E0D5iojVocVFqojtschZ6f3eG1rgguLWwTVfXls1ZL3BcKxeE0oBqAq0F/2UI4haBV40xKkwAw02Z5g7V6Dm706Slhqbo6SlkcubeJMlPceWdkXzBhbspGZoehoZCiQgSRd0wgJn/3acV7ue0jgVLWgkyle6grO1koXPlcadlKXmSBjrBW7qcugEMwGZe6WtoJg36VvNVZ8aLqPEPDcXo2RFgTS8umVMX/oeEhuBFLAQpjhCMsTxzfQhaQzCFnu1/i7NxT/1aU+z263uNAYMi4cBoVDIM2hHHQj8ak5mr9w8yZ/69wJdlKX2SDlxV6Fh+tjpsKE3STgaj9keSx4eirZlzwatuOA7dSlV0iGuWAtLh0Tn5zQtFxN5GhCVTJKuZHkRjIbjRnlLtupT9XRLFaHbI1Dfv5elUeahl9Z0RyrujzSNBRWMNaCtmuY8nP2Moez9RGf36zz1NSQ5zsVZgJNP5fMBDm/ueHzR070eHa3zolKxtf3Ao5Fmhm/4P97U/CReYeGa1hLFE9P9WiFCUJYxplHN/XIjeTaIORUJWUvc3Ak/O0bMT86X+NSM2Z57DMfZGymLr60rCUO/VzwyYUOmS4ln640/OJKg9NVQ0UZBoXCl5aKo7kXu8zsZ8blRtDLFTNBzola6dQZ+DlGC7SR7MYhFTc/ZI6D/cy+Z7fbdDLFeyd7/HcvR/yrvSOXxSP8fsaRy+LvOQ4Ksk+2/gKu9Km5imvJLhejSbSFUzWBr6CXCf5550Xm9BJjMWZRTlJzHC7nK0yYNqvqHk84D1Bx5GEoY24sW2lKTbmcqjtYSsfCK6M9Hqm26WeGiitp+4JhXvaAddICVwp8JennBSOdU2A4HlbYTXPusMqSnWeHPpqCRTnJUsVDCNgYF3xDX2ZsdtnoPcP51qdomklW5XW2x1cRQnI++AgztMkxrIsNaqbBnFPHlZJMl6GPz8T/nI9X/yivcpMlc5yqdNnSQ6oiYEvsMmcn6dmYvuyxrq/wiHial+wXaDnHiWydFzv/kB9u/Of0xQjXumhR8NXu36FVvYC1BiV9Jt0zjMwOK93P4zptHqv+RxgMuShlUfeK55hxznPCLgHQYchzo5/neO39+DZCINk2N5iSZ5i10wwYsSPXqdk2ORl79h7DfJM07+E5NSruJEJIchOz03+Ok61PcNo8SF+MWOEqa93fBqAWnaXqTdON7x5KoNq1i7TdU3Tyu0jhMEw3SLI1Trc+SdvM8s3BP2Op/hR3e5/jdPPj5XiLuwSyjhCKbrpMxZ0klC0GeoOd/nOHDnJzzfex0XuWydolxvkOSvpYa1j0H2NH32Kc7xwWJUrVifwZrNUUJjnsr3GdNr7bPAzCVqpOq1IWt3G+hxQug/F16vs2/uN0k9CbJM42Cb2ZfalmSj08cRgY3apeoDt8hcBfoNBj8mKPwJ+n4k2TFv37QrffuPh940K7DAHu3VcUHqAMWY7RenQYeh2nm7hOg7zoEHgzjJPlQxmekqX88M1BzG/uBasFC/TjO2UxY4v7CpC3Kkg8d5pC975jGDRwWFC9VfH5VuHQb2Vvf4CDnrXv1B/17VwFv53NvudOHkYivPFnWb5zn/vkfe/xhvl4s73+G4uhN25PmwzQhN4MxhaMk+VDV8VGdJzu6EYpLZU+9fAU/fgOSoYUunvfvL1x/2Yb7zmMG/h2mG686/ABwL8rZhvv4W+f/QCPTO7xP74yy/unclpeQcXJeW1Qoe0V3Br5WAsfnNnDVYZOEpBqScPLcKShMJL1OMSXplzUOwWro4j1xOWJdo9GkLLcr3Fhfhu73/e01484ttQlOC5J7mncOkhPkGyA0YJo0SI8wd7LpYtjWMsJF/cLc0+CsXSuODROZOQ9yMcSXUjSxCFJXa53mpxq9PEcjZCWL6/O8MTkHrPzfcI5CwrMyPLs1+aJtWKhMmaiPmK9U+Njz32Rn7/4YYaFwlpBxSnIjWQt8Zj0iv2HkaUg50RlTMXN+fpukys9yVwIH53t4DmapHC43Kmzk0kWw4IpPyPRitwKfGl4dq+UKL+rHTMXjdlNAjIjmQ1jfu7VBg81JesxVBxxGDj9ZHvAs7t1AmV5sDam6ad00gBtBYUR+MrQ8hPiwmEv9dlOXc7Vh6RaUdvvfRsXzqHd+2occLwS08lcrBUYyhp2O3VZTySLoUZbwfJY8tRkzHSYkBvJ13drJEawPCzlip6Eb+zCOycta7HkoXpOoAxrscfVvuCd7fJ+dFDE/usVxaeO53x9Lzh8wDvjF+xliq1UcrGR8WLX41Iz5au7HpeapQNz28v5zEbEdADDQvCvdu7yh6aX+IXNNf7M8VkKC9oKEiPoZtBw4foAUm0ZF4a1dMwfPl6h5hi2U4Un4eawtPNvepZ+LpDAdgo3+hnvn/G4NYDFChwLNVf6ijPV0plzIcz5+zcLfvqEx3qsGBSCudAw4xeMivLBwN2xpO1ZjkU5/+iWOLK9P8Lvcxy5LB7hCEc4whGOcIQjHOEIRzjCDzyOTD2+zzhZd6goD20tnpwkdAQTPnxha8yxMKSb5dztf5FedIqqnOa0nAZgy95gQbyXG71f42z9FJHjsZWkTAWl6cFSFKAtPLvX43RU59Z4SIWAQV6yY0lh6UtBoODOMKVnY8Z2xHvDRW4lI04FpSxrlBtya5iwE0yFHp1Y8VA4hSPhK4M1ZmjziniJu53f4ETrD7DU+ggLZpENuYmDjzYJSga4uKyLHSJTYcJO0FYR180qU8Uku3IPXwTMVx5nxezwoDyNqySZMcw5Nb5hnuNO5zMs1y6xO3iBE62PcUE8xVCMOSPeyZq9yaSZ48fbf4lV06FBlZvyGp38Nu3aRfYGlznZ+gSrw2/Qdk+iyRFCMlN9hBWu4omwzHuyEafUu6mYkK/b3+KYepRV8wpZvoNjXRIxZD1+kYv+x6nZChLBXS6T5SN6YpUpVbJDZ92nwIVCFBgMQ3bJiXmi+SeITMRddZub3V9nsvbI4XkQOA1yEyOlc5/U7Fb3N2hXz1NTs/hhlXr0FFc7/4LN8DSuUyW1Q842f4Sx7TBtTxCpOuvmVQbxKoUe46kKnqyS6RHTjXcxTNc52/5xdrLXqEWn9/OXChr+Er6ospI+v+8G+PqzF99tYmx+yEwdQOsBCQYpnH1m4hg7/efuc9cTwsGVYclu2ZTAbRK6bbb739j/vaQzvEKzcp5+fIvO8Aqu0yZwGwz1eN/8oUfu1IizzfvYE6miw+8P2DEp3G9hPKQMcVQNz6neJ28rii6eU8dzWxR6TCVYYhTfYbL+ODv7WWoH2x8ny4csnFJ1mtEpdgcvUAlPMIrvMEzkfZI3YV5nkd4qA+u75XW92bjDWvMtbNKbGTMpfSJ/oZR+2oIs38X3ZoHSqELr4b474reyUFAyjt8uc+vgvcpQ6pIdlNKn4s8wSrfv+1vfbZVmMNJ7q03hOI1DN8Q3G2IE3hSjeHQoEX3jtSCEc3j8BOLwHOsOXz2cY2NS+uMb+N4M2mSHLJ0QPpVgkcH4+uH+FzbFka+bAAjhlHNgc1ynTaG77Axeest9+F7wMO/hha7PpSnL//54HyUsiVa83Kvy3uk9RpnLXBhjrKDi5TjKELo5nleQpC6eq1HKMNca4DiG8dgjKxRqHPJYq88vrbQA+OMPrLGxV8NawZ9/3uVvPJ7xwrVZHujtElQtozWJXytQPnihZXhXIZXFCwqsFURLgCORoQJr0Z2C21stLrQ2cWrw0tVpLj26gdM3TEwknJhLSG7lODXI9gQ/ceYWSLAF3P5mk1c6DRIteann0HRhKkjIMofQLfjz85/ktcGBQ6Bme98dsu0V7GUOdbdku4aFop+79HOXh+oj5gOP3AqqfobvFXQ7PrdGimFuqTmKQDk03ZxB4bCZePz0iS1u92vU3Zxbg+qhqyWETPiS633Lgw1B09VIAWeqY3IjGRTwuY2cW40KE36FH13cYXlQRQlLqiV/61qLJyZKBulMNWMtDjnf6qKNpOLmiBTiwmEj8bk3Vkz5ikk/ZT0OsAhcYTlZSXhyIqWbeqzEPhfqmmGh6PWreNLQ9gz3xgohoO4arBUsVcvs0FEBd8cuTkmG8pGZlC/u+CghOBaV7ot1T2Kt4NFmaX5RnncSA3jS8q+WFe+fMXx6xeFjcwW3RuXybiZQ7CSW01Voe4YfmzjOr210+JNLc2wkpatzzbFc68FjbUOkLAbFqBC83IGfOlbF3Zd/nqpkJEYSa5eLjTGRU7CZBPTy0mRsNvSoOZbH2pbBvvPoEy3DXJhSGEFhJf/94zFJkTHt+8xFY6SAUe6QaAdjYcJXJFrySt9jNnzLS/AIR/jfJI4ki98nHEgW/6+n/zKBCoi1oJNarg/H/IH5iEyXwYgCSLQgNZZxAd8cbBOLmA/Xl1gZFQghCJTgZE1RdSyFKXu+DhyqSgljGbS4VAVXcBiC2csF90Zl35mSpR3+6jij6ZW2sotVyU5S/n4nKXjOvMI7nQtIBGcbpdTD2tKmPjOWfqZZLjrEIua0nGOvSOjIDpqCOTvLg7UIJWHfyZbclFa+iYaNOGep6qJNaaOb6LIYvJX0mFZVDJZVs8eSmqBfZLRdn6/rF7kkHmHVdOjILd7vX+BeHLMj9sjJmLOzSATaGq6IZ1nvfhkog1pX1T1u9X+Lh2s/xpydpOa6VByJ3t+fblYQKMlqOmTCiWj7DoUBR0JhoDCWzSwp98NqNJqu7OLgsMMy0/YENVsjp2AoB/TZpm3nWJST5MawyR4CiW991uUdbnX+DQAnW58AIDYdkqLLA+4HaFHDYImkg7aW1JZB2QBV6WGsZWRTurLHtr3NHGcZiwECyVr2Iq6qUFXT7GY3yYoBi5V3kNkxmRmyNXiOydoltEl5WH6ANXWPgd7Ak1UcfHrFCp3RtcMesUInVPwpusNXqUdnOOY9iYODtJKe3MG1PgJJLlJyO0bi0mCKwIQMZI8hO6yPXqQWzJPp0WGocLt2EWMKchNT9xfY6D1L6M+jpM+Ef4qR3qUX3yHPd5msP8Ew3bhvMV8NT+FIn1G6CUCrcrYMsRYBhU1wRVQGIesOrgwpTIoQiml5hkQMCW2dLmuMii32BpepV87RH107lLi9MRD6jbJKbTJ8t0H6BvfDN0sUBQKEohIsUUagln8jhESblLwoHR1dFZbBxhiUcJDCRUkfR/jsxTfeFDAd3ieN9NxJ6uESO/3ncJ022owI/TniZJVqdIpRsn7Y5/Xmwu5g/oRQDMbXgdcDsK0tDguwwJvAU2UwbT9eLl053yRJfOM4Dh6GHMzBG/vRXKeN1gOkqnyL3PGtrOtr0Vms1QzjW6j9MZSujz6+O0WcrhwWb1K4BP5cKRUuxt/aM7e/P743S+RNfEuPmEAQ+Atv24ky8OcRvG55b2xWFrbWYGzOnzn2V3isbXi4MWA7CdhMXU5VYi73IiY8jUUwKCSFhQ9Md/bv3ZJO6jMTjZHC4kiDqzRrgxoAjjRoI+hmHjNhzAudOicrCU0/Y3GyR202oxgL8kRSO1f2e4lGgHAkOBKbFJBrbKaxoxw5EUJhsNm+N2SuyVZzVCSQNUW6XLC3FjF7KcHuR6bIqsIMNCjIdyz5WKJcS3jWIV3O2VuJaE7F6FyQjFy+sjzHTJASqIJndhoEyjLlF4f9YY80+whhaYQpWaFo1mM6vYhqlBAnHkJYAj8nyxyGqY8Qls1xRCdzWEtcfmh2l2/utDhVHRMojSsN90YVzrW6fH59ik+cXGUU+8S5w1+7Uudj82VvGsBaUsbMXKjHfHU35IPTQ7YSj0GhePf0Ls16jDECYwR5oUizUuaZaUWrOkYbiTWC3VHIyjgikIaZMGZcOIe9ThLLS906JysxgdK0woTdOEQbwfVBBSHK8GlHGiKn4NagykyQ8Nvbdfq5YCs2PNAQ7KZwpmo4WUlw9/8237fo7+cuc9GY9XFEy8+oeRnrowrTYczdYQVHlMfu5sin5Rqm/Iy7Y5+2p9lOHQTQzQVnqjnriUM3ExyLNFup4mw1Yyd18KWl6RVsJi5zQc526jLl5yRGsp06jLUoewP3ew8zo/jsZoWPzw1oBQnP7bSYCTJuDAPanma4Hz69lwkaruXR5ghty961s9WYhlfa91/t1ThZHZNoh0AV5dwqzfPdKi3X4ErLV3Ycfu7uX31b1+0RjvCDiSPJ4hGOcIQjHOEIRzjCEY5whCP8wONIsvh9RsuzpAYCZVkf53x0LuLTqz0+NttgdVyySVMBBPus19cH/5QH6h9neViQW8OOHrHk1elnlme3Y87UQq70h/zQTJWvbWdcaPlUHMvxall3T/tlZouxUHMkNVcyyOFGv3xytml62LSBwbKIz2QgWBmWWWQf4CI7SflE/lpP0fQUz47WWZJTzEQuVVcxqeu8wgqvmQJXeuzauxy3D7Mnunxl0KUv9zimT6DRXOPrnOYJGiLkWMVnJzY83JIEqmQHe5lisdJmfWz4l73/Hx8Nf5qv6a8SqAZT4gIXeBglBC1qLIk2y+MxbdfnttmjrzfIVcqsnqchQ/rJKlAaG6yqe9zo/RrvqP0MHbHDPQq83ONW/FU+6H2SW3YdxzosmEmO+TVGRfmEcyIQaFseE09K5m3EvaHmdr6HsGWW1ap5hQX5EOe8GX5t/Gne7/4oL6Wf4V3uJ/li/E/ZrlxkllPsiXWUcFnQx2nZmUMZVSe7TaZHhG6bwGnSk7ts23vEpsNu/xpnaj/Mq72f56n6/xmFYtL3cCSk2mPBVkn0HLEuMLbFa+IVpHRQwmV9/AKz0UW29FVqts0ro2dZqDxJs/IAC/Ih7uivsabu4VofKVxGxTaT7hkaziK2otkbXCbJtqmHJw5ZjzjvcHn0j0uJoTeBIz16o9dwnAbVYI60GDARnEVaSUtUaNoIwxwL4VnuipfZHbyE67SZqj7MWve3mW28B9dW6MS3sbbgRPherg9+g7HbZpCukeU7hP4ioWrhhKXTXJrvYkyMq0I6wyuH7M9W79lDA5N27SLrgy8fzvFk/XH68TKz1cfQ5LRNyaTO2EfpqB4LrUskonSeHCUr+N4sQkiSdI2p+pOHcsuZ6AJ3Op9BCHnIjh0YoOR6hLUGz6mR5r39bZUGHG8VhGxswTiNcVQD321QcaeoyEmUddCiIIjqdNwWvXEp2asEi+R6RJZ3qIZLWGvojG4AIKVHXuzR8k8cykyNHhy+V5pt0qpeINcxw/jWoRTwQN4IZabaG50iPXeSON1GuymB0yTypqh58wy9icNgbmsLmtFpdocvM7EvL65XzpEVA4zJsNYcBjkH3gSD8R7qTc/4ZqqPsjF4nkZ05j7m6oAdK/dlfGgscsCkHTCaAPXozP48OPhOjb19huzNBiRCSPrxHTx3mmowQ2EyJJJRuomxxXd08XwjvluIdNUVzAUZr/Rq1FzNvbHkM2sB/9WlHV7tNmi4BS0/oV2NqdYT3MggJAinlP8hQflgDcw5Q3QM8Z7DXqeCFGU21+lqgrFQcXOiVsa91xpYK+gkPguDAZPHx9x4pcpUc0h9LkUoGG06hO0Cf8lFhC7MthCeC4WG3gi/PcJ2Yq5+pkq7NuZz92aZ2cp56tI9sqFEF+AG+66+eyG+XzDe9chWFOPMZS/1eaye4ISGoidpujmFEYRBwdlqSuQUJFqxEvs83Bjw7G6Td010+RuX5/jAdI7faRIoTdqrU3VKxquS5Jw5u8OsPyQfCqaHQwZDnwta8UvLU/zQTJ9bg4hTtTEr44j3nV3hKzcWeLQ1YJx4xHm5hPFkeUyu9APO19LDkOVhoTgWaV7tRyRG0M8Ff/e1aT45P6KbuwSydAlsezmB0iRa4SnN3EIPFVom0hHHRwpdSOLYY0IZbu3noa3EHokRvDaIyIzgnROW39yo85HZPq60hErzua0qT7YSthOftpeRG0nDtUx4htxIRoVgNijljl/ZjbjYyOjlLl/fC/jVnXX++OIMgTK0/AxHGCYaIxqVmFHs80CzR5w7bMUhyyNBrQFf2wu5NbB8aEayEGZc7vk8PTXg19brnKsVTHplltrpSkbDLZDAWEuqjmZPOjS8nJ3MoZcrvrHnsJ0YzjcFd8ce3UzQyQKeaBWcqWq2Eo8rvQpTfs5XdiOmfcOkn7MYaXIjSbVkL3NYiwMiZWi6mv/lps/DrYhRIbhQz3mxW+N4lNLJAgaFYilKOVNJCZTmxV4Fc6TfOsJ/QDiSLH6fcCBZ/PQ7/hyOCBlrSS9XLIYZmZEMCsXlnqKbQS/VpMZwuu6Savg76/9v/tTc/4kH6+WhmAkKpvzyA07tSxIcVS4kCi3pZR793OXlvoe2UHEgkJbElAXGgUwwkJY7I8HpqmU+LAuvcSG5FztUHEthBI60NJzSxWk7k7zcMWgDFVewm2i+VHyeGfkAp8QcixW3lEcKeLBuqTuamqtxRbmcKqygmznkVpAZwec2DNZaWr4qnZSBfqbxpORYVRFryyi3PNAQ1B1LrAW9HLYSmA3Zd8GCf7T3DNP2BPOiTd+kRMLlnthgrbjM7uAFPtj4s7hC0VAelyYcqg4YoOkaJCD253A3U4wKuNm3FMaSW0ugBIm2SGAzizkWRmgDjhQsxyMerFVp+YLVkaHuCRwBy8OC6dCh4kJSwOX+gC25gYtPIkZ4NuTq4JfxnDrT4XmOm3MEwmMpCpgOJTWnHE+gOHToygzcGlg+n1zmrDkLwNf0v+Vx9WH26LIgJoltgS8Uq2xzWs4yHTrkxhIXlnvpgCmnwnYxYsKJqDgKa2EzS3jBfIFJdYqEIf1ijd3BCwghaUTnqHuL1JnmFItUXUXdU1ScskiVopS99vNSOhtrQzfPWBObFKRUbINvdP9nzrc+xYgOEyzSYxspFIv6JNNuSKINu2bEXfEyJ+1FqsIntgWf7/0cUMrtfKdWhiELB20y0myDaniKyJuipY5xypwgkA4VR+Hsx0DI/fFBKYUdFZpXxKsYq0vnRrPLdv+bLDafLt0kbYrB4AifndGrzFYfpcEsE2aCV3iGXnyXs5UP49uATGRc7vxjpHCZrj/J1uA5HNV4yz4xz53mZO0DzOlFIuHiS4XBkhhNhwF7coOKbXI3+xrd0VVCf5GKP00g62yNXiEvdmhVL9Ab36UZnSqLZjPBntygrzfojm/SjsrzobApO/3nONX6UQZ647CQbFbO0x1d/ZaxtaoXWHAvEdiIui1lwgMxQOEwFD02iiskeQ9ji8Mi5MCpMsn2sDZFyQoTlXOkuk/gNNkeXqEoupxp/xi9YrWURSarVPxpMj2i7s6x2vvtw8In9BdxVEiad4Cyl65ZOU9hUqreDJ6sonBxhE/DTJKLjLHoMzRbbPSewVpz6D4pEFTCk4eFXBnubXGdNlm+ReDPE3kT7A0u065dZJztUvVn6cevO1cWRQ8hw+8YYyBlSCM6hbYFjvTIihFZMaQoOhib8xdP/hV+5tQur/XqtL0cT2pGhUOiFa40xFrSzZ0yOLg6IgxzlGNIE4cgzHG8cm50LnF8gzWQxQ7jscfGoELVyxnlLltxwHSYMN8YMPt4gnOqCbMtaNQgDMBzsdUqOM7BziG6XdjYwTx3BzPUZFsG4ZSW+O6ZOqIZgTboOx30bo732BTUwrJoywtI8lLDDdhRBqGLkILsWpf+HZfx2KPRihn2fBzHcGurxd1RyBNTe9SrCRMXcmRVYTODqLgcXKyyEUCw/32SYzox+XLC8isNbnQb+MpQcXKOtXu4rkFISzSRM9zyCKoFTlDOU387wA8KhLRsb9dwlKYSZfQGIUmhUNLiSsN/8c0Gn1x0qLuG3AiemNyj1RhTmcrwJiWy5iCCct5spkEb8s2cZFvyyu1pMqOouRmD3OO1QciFxoj6fkE10xgwin324oCZ6ohKJcOvFHg1w3DLJUsV17YmOD3RJfBzbmxOkGjFNzshjzQSBoXDbJCwmfgsRjFVL+fYYhepLE7VIgPAgAwltrDY3BJvSr746jFSU4ZIB6p0cqy5OUJA00/ZiUMSrThWG3C7V+eh6V08r0AI6A8C4tzFd4oyDkAajBX4XsFvLc/RcDXXhx6PN8fsZh4vdV2qjmXCNwTS8nCzTzNKGKYe063h4flsLcSJx5W9FptJKXUsrKSXl1/Ho5xurrg5lGgLjzULXh24PD01ouFlfHmnyaSnmQ1SPr0a8fR0zk7qcKExYnkU8OUdh79170iyeITfzziSLB7hCEc4whGOcIQjHOEIRzjCDzyOJIvfZ2wmHjuZz8VGSqQM26nLbqaYDwvuDjQNX2GAp2ZclIDVMfyFpZ/Fk5bcCtqupqL0YWPv2Ehqbl7myrg5WpY1tCsN75kopVKe1Ehh0VbiSIO1YKwg0QoIiZQlMxJPGu7FDkpAZgTrMSxGgoqj+fKOx4mKJdGWbp4xGYY8OuFgdp+m6TlUnJJJmgwkkVM2bxsLg1zhSGh7OcJwGAY6LiQ/uiDQVhKoUiJo9k1JjDVkBgaF4EpPMOEZPrcBT0wIlCjZsW4Gp6uG5/bgCfEEO2bEXbGBKzwerM7SGzRYA060PkZD+HR1TMUNsEBqStcobUsGyheQW0HNMbhC8NiEINFlTs3BmAJp0baCoWQZu5nAlRXafmnAUhjLhC/49a1dHqm22YhzHotcXu7E1KXPi/llmu5x5vUpFr06Re2jKNySgbFf4f3OD9P0BbkpzVfaviW35fvmlPs9H0l+wn+EaN9q6138QQAKU9k3H/HZjA1BOkvdU4wKQ92VdFJNQ4Z0i5TL5nMcM4/zlLfE54bXOSdPsN39Bs32MSq2xaI8zeVKSss7iSN8JIqGblEIQ8v3sBaGucWRgsgpDWWmlCTWlppRtPyQueI4AJEjeGf1r2AoTVGSwvJiXrBRXOUJ/wKXi1vMm3laMsIxj/B88Rk+Hv4EnWJ4mAdV6DFxusKjrT/KS51/RBQeJwWa/hJ1MYtrfQr2jVnynJbnooR4w7kEFVfiSMGl4iHGpsAREiR47R9CSUFu9tllY+mYMVPVk2zb2xxjll/t/XUutn6GicpxrnT/V56u/2lW5d398zVnkK0zWbvEVu9ZPHf6kInROsFREa3wFCOzgy9O0LEjWqZCpBx8R+LrJpOmztjmNJ2PsNd6ktBGNKgCcDoqXTlHImZUP896dpm2nuaueBnPhngipBYskuo+jgwZZzucb32Ke8k3EEIRBUvE6RpJ0TuUdlbCE4zju1gsgdPEoNGiwFiLg6RNk9xqJALlXEI7JXOuKwUtM7k/nhEykBgM6/oKveQeSnpYa6j6czjRKZYHX2ax+u5D85o4XeFE62Pc6XzmvvuhNsn+XBb7uWIhrqpQmBRH+ChcQupkxFgMrvUIqDKwG0TBEmnepRmcoO4vIEXJsARuE1eGVOQkhU3oZstk+Rbt8Azr3S/Srl1kmKwfyk6zfIfZxnsYF3v08x3Q3+qS+UZ4botcl7JZgaIwSSlLFRIsDPNSqfBcx+PpqYJO5tPyCmpuwmQUM3eqj/LBXfQRkYto1MEtM5Zw1P6XBLWvWx8l2LUu21/IUMOIk2f2yIaSs/v5Y25gEJ7CpgWiEkIlxPo+Ik0RwyHW97H1OrguOA7CdZHtBjLwcaQEY8qv/c8ORmOUsWw9O2Du3S72zg5mlKNOtLj7v2bMPzpCRpIv/dosT/+JEQQuwhXUFnNq5NgCgqmYvA8Xm5tEtyYI/Zz6XMqBktakBseTiFZpLmJ2x4iqh6h4EHnIwMXzFKeXUs445XGyhUFEbinv0Aaza+mtS6SyFIkknLfUbIJbhd49j6VzXWQEa5erzC302NuqkBWK0M/5uXfvsj2MuDWskJrSrENIi1MpxyZrYOMcXFUyZcbiTEG1ZXhipjS2kWF5H3lvsf9BAiBBDyz1YcrdV2o80IpJxi6NGcPW1YhaM8Fowclmj8DP2e1VWBkHKGGpOJZB4bAQxuRGYhG0w4RKmOI1DCaHYgwyB7chQO4brYw1fsvwoUvlfUl6pdy1nOjyxRqYHvdZWW/Rao7pJAHVekKeOqzv1qgHKUoafml5mh87ts3Xtyb40Mk17u40sVbwlR2Px1sFg8JhXEjOVDUvdCXDQrEYlfJKx9FMR6WkNAxyHMcglaHQiifmtsjz0kHyYP0hhSUrHJQ0fFga+onPMC9dNRtexjf2GpyMsjJjThkebxk2E4fz9ZgvbVcJFEcui0f4DwpHksXvEw4ki3/r4b/ElO9ytjbg06tt3t2O2U5deoUk0YJuJoh1OeWd1DIdCl7ci/nJJZ+5IMdXBk8eFDClTaygtJzt5i7jQpIYyaCQRMrgCvD2naUixzDIFWMt2U4Fr3YNH5kv5XjaCm6NFKerBW2v4NrAp+Ea1mJJ5MBuCk0XNhL4erfD4/UWndRwNdvg4WCW41VF3bX40lJzLIWFaD+wMreCUVG+Lo8gVGUI9l5qiRxYjEp5ZL7fr6UEDHK4N7KcrAqu9gy5sTw+oXAEfG4jY7Hi4UsY5JbdtOAle5Ube5/mg40/y4wXsZenJDZjVd7mo5XHqLlloKWvSskmQGHBlRBrwbiwdFKLkgJrLbuJpuWrw/DtiiMIHejncGMw4mWe4aebP8woL4vQW4OCxYpiKzZMBaXV8G5iyIzl3ya/yqLzKAbDlJlkXa7SMfdYEA9xxp1hMlC4spwXKK3GtS3ljkpCXJQFx81hTNv1aAeKwlhSXRY9joTr/ZgVscm8naHtehig5koEsDJOOFULudYfsRRFSAEbcUbPxETC55vmt5hV53Hx2LQ36aXLtPwTHLcP4+LQdgIcUYaIu7Isdgpj0dYy1porvMqMPsaWWqVqm9RNjQLDpKow0Bm+UKRWE5MikVwpPouSPj8cfIK40ARKclWvcErMs6fHdGWXW8kXGSfLWGuQwmWm8U4yPUIIye7gBR5s/hTTZpaK8HFl6ZZprMViUULSMzE+Lik5Bsue3EIg6dh7AAzSdZ7wfhQXh5ry6OmUXbnHi51/yMOtP0yPDVZ7X+Ij9T+DwfKi/RJneQeb6h69YvVQDni4kN/vZ4JSIjhM15mqXmBanCG0IQaLROBal6EcMhB77KSv4e47CFbUBGPTxZdVakzh4uPbgI7cIrVDVrqfR0gPR9WIvAkmvDO41mereI3cxIzTTY7V3ktie2z2vobjtA4llAfOkQJBNTrDON1kpnaJhpilEDkWg7GaodlmlG0SOE2SoktejIm8iVJSWAyouJMUNqUfrxz2YPVH15huvIus6OM5dfrJPZJ0jdnGeyhs2e+103+OqfqTxPneYcjzAaQMCbwpxskygT+PFA5p3mWiep5A1ulnKxQmpRWcpJPcRgh1X3/Zgc194M/jyIA420EISTM6RSDrrHQ/j5Q+1mSEwbFS2vgGG/9W5TxJ0aXQCe3oNOvdL98XOv6dIIQDmG/pO/vx9l/iLz88pu5n9FOPipejhGVyouxTrMwWOBOKX/qlY/zkz3YxnRjZCkvJXuiB50BvDNNNGIzLe/3yHntfKQgbOf6s5Nd//RgffuddnJrAmQ8RM7VSWgilXLHQ5ZejymIrL7DLu2Q3hriLAXKqAr4LgVf+HcAghkYEu0OsseiVAa9+scWFn84RzYji8hbOQ5PY3RFmkCEnI3Z/c0wSu0SVjGdvzbNUG5IWir3U5+7Y5xOnVmktJTgtiZoIwFMIVx3KHe0oQ0iBLcyhxlhvJuRdy95KRL2d4EQGHQvSsUPzfCmzlPv1az4UXL89ydmTO7hVy3MvzPGeT/VY+7eWIMyJJgt0LNhcrfH3r8/yR05to40kdHNyI/m7r00hgT92ZhdrBa3qmKiaUWSlpDvLHOK0LPRvdBs092WJc9URU1MD8rR8Zj0aeUwulMc37no8f2+GB6f2qNUT8lSxvltnujkkrGQEE4bxlkM8dtFG0hmWx62b+SzWBrzWaaKE5Su7IT/76B2iVobJJW7VYLKyoBEC0oGDMYI0cRgnZeSEkoZGIyZNHCr1jGTkMhp79JKAm4MqT59cZX23Rj/z+LX1Gg83Cp5eWsMPCv75yyf4sVNrvLbTppc7HK+M6GY+hRH80mrAA3V4qJbw6iCg7hqm/Jy5MMZThlqQsjcOUcLQCFOGqVeGYlvoZx6f26ryeCslNwJflusVXxmO1fsMEp/bwwqO2LfqN5JX+i4fmh7SyVxqTsFifcAv3Jnl0UbCbuaSGsFuJqk7lv/j5f/mu16rRzjCDy6OJItHOMIRjnCEIxzhCEc4whGO8AOPI4bs+4QDhuwLT/0s5+djNndrzE726XYjAr+UHO4OIjbikK3U5UJjQOTlFFohhKVZifGDAuW8/jTWaIG1gjxTZJmD6xYYIxknHqPcJSkUmVEI7KFk8fREhzDKUI4hSxz+3uXj/MTxMuj1aqfJw+0Oe3FAI0i52atzutHnbr/GbBiTaMXtYYQry8DJubAMoMyNpO2nhE5x2DQNpVqi0IrRvtOVEKCNIDeSWCvGWjEsJL605ZMzZTldG1L3UzKtWB9V8GTptvXaoMKZ6phbw4iT1Zibw5AZP0cKy2ZSulmNtWR1DA/UDL60SMEhUxcpg79vfCL2HdvGWjEqFK60CCyDQjHYz0jRtsxNc+XrrN2ogPdMjAlUQS/zeHUQsBRldPMyiyVSlppT5gyVTKUgVIZurrg7LNkugMWozIwztjQWKcf2xmDh0tkqMwLBQbacYDcTdDLw5evuj8eicp8ariZShvXE5YublqdmBGNdBpL28pKR9CSsx9DyoJ8LWp5lVMCtgUFQSjSnQ7lvsGKpOiWjWLKsZaKWtewznvvGHpQS0NwICltm56W6lLZWHMmoMJxvSFqeJTPw7LZlMpRMB7AygrkIXu5oHm4pdlP2DWNgJykljoOioKdTzlSq+EpQ7NtqVRyBr8ShuciBPDHRlrjg0FxGUh7H3EIn1eTG7O+DwZMSa2E6dJiPxP4xFtwaFNRcSd0V/Fr/GtNmlkcbDfYSU+bDOZKtOGfDdnGty+Q+y6WEwBHlPNRcRehIXHGosHpdurnPgCfakukyiF1bw9CmFGhCfDSaCSfiRNUlNbA5LtgshpwK6zyXLnPJW+JG0uGE12Q56zPn1Bjrgsxqasojt4YN20GLgl1WOGXKPMGYlKaIaHkeSoiSBTAlA20oWU9tyzF1xQAHRV90sRgKkeNYlwfFKSqOQknYSFIu8zWeFO/hJV7grH0YXyi2bI+6rexf94IeQ3KRMWFa3FPL9PQqg2ydufBResUqVTXNZvwy7eAUZ+wlXKFwkWT7+XsxGRKBRFBg2FT3WBs/j7EFSnpEbimnTIoeSjicdt/LDG1yDFf5JsN8kwfdp7ljX6SmZglslY69R2ZjJuVJMhGjbU5Byubw8rcN8nacJs3oFJGaOMyYS3SPpOjtu2Du8sdn/wJ/4+M32VytcexiH1mRyJaPCBzEyenXZYmT7ZKdWtvCXi9lcMVajAgl8W1DeEwwuCloXFLovZx7L1SpVVMmf8hDb45J1wyVHz+BffAMdnYWfH//BmIgz8vXJEHoorw48gySFNEfQKdfjiHJSj1btYI9sYhtthBpgrh9l5t/5San/+8PwepGybpVQri5Cs1q+b+eA8tbsDgFG3vYXkx+a8DW1Yj5p3JEI8AOM+Rjx2F64vWb28EYD16tLV/j5PWJLjRsdcuLWAiIM/RyD/UHLu3TQxl0+6+Pa3kTJuqQZNjrG4iLS3BrAxYnYKcPhcZsDOg+b6mfNYhIIfZvHqaX07nqMPFOENWSadKb4/KC3ZeH28SQrIPOBf/1l07zf3hgm6UzXYqxJDolcJbq5Xy0KuU+bvYwnTJ0XVQ97DjHDHLURFCyg0JgU43wJLpfsP2yT7WZ4UQGtymw2iJ9iVqqHZqLvD53FjvKSgmnFNhMozsZZmTRMRgNRSypPSSRE2HJSGqD2RyRb2pUTXDv+SrH3zfmt391lqd+aI3bX2tw8oke6Y5F+ZAPJdZAMGG4e6VJNUrojwPa9TGuX16TYVujqgLh7s9RbktmdQQ65ZDF1KkgixVZ6pCmDkKAs5/VFkY59bMGm1v00LJ5q8rE7AgnsuzdC2hMJwx3ffrDgIXTPTZu15icGTHqeaSpwze2pvjUN/+7t7xWj3CE3x94+wzZUQ/Z9xlTtRF55jLVLJ2IGo0YIWxZrOhyxf7sXshi6FH18rIXBkF/HNDd8wkcTaYl2sr9cEhItGInc5gLMqD8DBsXigk/ZVwotBUoYYn2b4K6kBgtKQrJD8/20UYSOAUPNnukhUPFLdBGshiNkcBUkOA5GkcZFqOEceGwmTpMmQNHO0sv89hMAowFV1pirchNKVm4M1aEqiw+3P3iS1tBw9V0MkWgLBVlCJVGYtGmnIeKk6OtRAg4Vx+hjWA+THGkYSlKD/er5mr8/f/ZSwVh0+4XiuX4tlOHQVEWTGMt8GX5WdvPBRuxZToQeLL8sIu1IFSWwpY9cbkppaNn6oK6W45doJDCMh+WPXqTXkFhwSIYFpKqY6g4GqUlvrK4osCtKXYzwVb5GX342drNJSuxOnTBLEx5eXYzyzA3VN1SMipgvzfK0s8tgSolmFJYjBXkRpCIcg4uTUgKa6mocpuBKgtLgNmgfD2Qlzqu4HhVsbVfAL0RnX15TKJLV8l0fz60NdyJByz4VSQCRwoKY0i0oeJKqq6kHxcIBJOBLAsSW8piT9UlriyPz2KlLJbO1B2MtdTdMnA8UIKpoHy/SuGyPN7CkzUyfWB+Dhuxpp8XVByHuNDl3GAZ6IxduUfTlFEOVeGjhGTL9piTTTKj6doxIT6vils8Lh/aDzoXhwHm00G5kigsfKR2jv36iYYvSbUlcgTToUuYT/BasY4va6Tm9QclEkEnLdhOTCmYtPawoOjKLpqchmkzlAOqpsZYjohsha4se2U8M4u7f+vN90PJQ0dyTNUwFh73l9AGjrkNhIBFr44SYFD4tiwEAyvJ8wZ9M2Y3u85x70FA4VPKWa/m6yjrkIuMjJghu7iEKOEyMBu05XE69h51OUfDTHA1+y0W/cdo2DYIyK1Fa/CF4iHzJDmah3gEKQSelCzSYq8oF9iOlVSJMDbEE4pjeolAVtiIn0GEj6GEi0Ufzt8deRVf1Ojoe0SyiaZgZ3wNJT1q/hwCRV6M9+3058mLMUOzgetU8J0ajvDJRMbY5DhItMhxVEiBZkqeQdscB4e6mMUKQ9U26IiUgCpGRExUzrLefeuCrCi67PSfe0OAeBmtcHjshctDTYF0LcffOURNRVhjERUPMVEtC4g8LwuOm/egEoDWiKkqGIvopNjEEMyCNZb6eYFoBjiRy/FajHAE25/NmHhcEp5RkOSIjS1EmpaFymhcFjZxWn4Q7PYhzcv3ObjpVIKyoOoMSpmk64LnlsVaPIY4hiTj9KckDIZlwaNUOeZ2rZQ5Glv2zM1P/P/bu/cwuaoy0f/ftS916arq6nuncycQAggEBIIBFLk/owfld36O/hzFiD561MADw+NoHGfIOIzCyJx5HBWdGXQczxwElJFxDhNRfggoF7kkREK45n7vpO9dl31d6/yxqisENBAM3SZ5Pzz90Nm1q/rdb3XXrrf2Wu+yt7cVMf3j+LML9OgqOnBROsCdVrTDLgfHwBjMnoqdHzfxCYo2mChFOYpkZx2n6KJ8B1XMEG+o4M8rku6s4XRmcWeXIYptrI4DrS/rIDm3z97mKNSCPvv4s7sbf9BtUA9RowHGRDhl385FcxQmSFCZxgLQu0JMEpHWYfumNtuCviUgm01QjsPabT0c1THC50/bwpod3cyoj5LvMzgFv/FpUGy/HGXnwXl2ErJJNE45h1POYeIUVcqiSlm7WLcxuG5I14KA8c0eflHbT5Eafw7JpjF03aDDxpII2Pq5NmwLx3xrjE4VStmlEtJQkcYKL9uYRJtoTKIxQYKu2nloTmzo6q2iq4bFZ2zHhDDr2BF0BF4OVAYyrt0XB3qnjaFTxUt7Omkv1TFaoRxDOOoQ7fJQjiGo22GdShm2DJWppx59hSpZL2E8yKJRlHMBuypFMk5KR4s9ERbLIbquUb7CyUHntCpO1oADHbMCdAq5Qky+ZOd1dk+rYIyi1BHijenmdAwhjgQyZFEIIYQQQgghpogMWTxIJoYsPvKOT/HSWA9v7RyhkImoxz57anl8R9OatVe4xsIMg2GWnJuyuZZlKLJDq3IubK3BKW0pffmIvJuQ81KCxCXWDmmjc+LExNhHBjKc2x2Sde0imL6j2VLN4SgYilxSA0ORYkEpoc1PGuuDOXRmIjzH7NORsT/I2sUxvZRq7FFNPMYTl/7Q5cUxaMuAQvHA4AB9XisX9nmkBrqzKRlHE6S2a9Ro7DCe2OYlBc9wfGtMi5uijaKauvQHLuOJ7XL47HDMGd0e03IpRU9z3y6fc7oTcq4mahxvf+gyPWcXvw5T++9tNXhkdDdZkyGnMryl3EJ/LSXWhhPafQqNNc3yrh1GB3ZY3u4A1o1FlDMep3U6xI1hhS2uIeNANVUMhootlRTfsVdUWjOKjKOoJoaxyNCWVcwt2GF8WQf6AzuErezTvNJSTWDNcJ11znrmpEfR5mX5yeg/cWn5kywoZyh4hmpihxBWYoPbGDZ544bruWbOX9KVtVfygtQwEGjKGYdEw7ZqxJgOGXaGOSM/i7yr2FyJOK7NDk/zHXv1cjyGnKvor2u6cg71xBCk9meMRJp1wTCPjn6Ls8tXkqqEJ8Z/wDnFj9LpteApRUfOduJMDdQTzXicUk0Tdqh+dqZrOcM5n6OKedsEJTL012MGdZUxZ5Q23UbFqXCc10fWdXg+GOCtRftJ9nCYUvAdBoMEVylyrr26pg1sDapsdl5k4/AKOkun0O7PYcv4o3QW5nO8WQRAl58jSDWhSfGVQ6ATWhwfjWE7e3h67Ie8u/XKxtA8TU8uS5AagjRlmx6gpsZJVExqYloo02emUXLtJ7++4zASRxRcj8GkRk5lcIA9jGLQ1FWVvCmQqIQ9ZiMD1WfxvSKO8unKzqfTzKDNlIhJCJX9O1+nHyeIR2jJdLN79DHeXr4KH4+c8ohMSoLmWR4lTisMV9biugVOKf1/dNDGyvTnnOScR4vKkGDIKpddZhgHh7qq0abbKKosFROyTq2i4HQRmRrVZA+D46sB21BjTvk8chTJUWCEfqp6kEq4k9bsDPZUnm4urD3LXUhO54lVzGb9FGE6Ti3sB2gsiN1KV8sCKvEuCl43vmohISSnWmnXPQw5dkjeYLSOzswxjKW7CJIRypmZDAXrqQfbyWX7qAVb6Gp9KwNjqwCY2fZOaukg4/XtlPIzMEbbBiOZHkZqG/C9Ih25eSQmRCkHF7vIed7rZCTYRJxUcBx7NcFRHt0txzMYvEQt2EIhN5eu3HyyqkRVD5B32hlNd6BN3Pz5v81E8xFjNKkOUMoj1YFdtNok/MMJn+cT717HjjVFZp9nLzOrQgZVztlGGhkPqiGmFkE9hpxnF/RzFHgOynft9xkPUwlRLY3GG4m2V9vKeWjJQjYDjQXTcRw7jM9R0FqCNLVX47SGah3C0A5PdJy9QxXjBKIEwhgzWLUNN7Ieeo+94ufMaYeOVmhv3TukUDnQ0rjM7vv2cav1vUMfW4uNzpB1GKlgxgPS7RVGnnMpzYzJzCugprfZq3alvN03Se1Vuwlh3IxLbx/F6S1CZwl8D6qBvR0wlZD6k6NkpjmY0NC/Nk/HzBot7+yFKCF4YpDM3ByqxcfUYtLBkN1rcpR76kQVj0xLips3pHVFpsuga3ZEgNEQDHvUqhme39PBo4N5glTxp6dvpDgtbjYoSfcEhLs0OlYEFZ9sISEOHCrjOQaredaOljije4ha5HPUjCFKRxviIU044lA60UVXEsKd4OYNXkkRDxvqIx5eRlMdy7BntIjrGGLtcPyJe9ApeCVQriIeaQwtHFMo12AM/OypuZzSNUT3tApeTjOyK4frGsLIY7iSZ0OlyFmzd+L5KUnsUuoOqY94uJ4m36tJq+BkwaQ0uyGObM/RPjsgGnXo31nCd1Pi1OXeHd1sqSqm5e1w9nN7hyhmo2bDkVwuJgh8XFdTCzIM1PN0t9RwHY3naXwvbXZhHBwqUol8tFFsq9kGJ8e1j+Iqw9qhNo5rH6WjtUaaOgyO2cWgc55dXPql0RL//cm/fd3vw4T4wyNDFt+wm2++mZtuuoldu3axcOFCvvGNb7Bo0aIDeoyOTELej6nHPjurBXrydX4zVObsUgXHNVRjn+5cgFIwTxlKXoaByCVI7ZiqvnxEqx+hUdQTj4yT4jqGIHFp8VKCxqLTx7XaQiznps15U7052yWq7CfUUpfR2GdusUZrNmSonmcozDQXZDy7a4THBtt4e+8gI1EGRxlasyH1xMN3NNNyCTnXRxufRIPrGC7p6eLF0QQNdGZSHAXVxG3MP7LDBlMDuzWUlR3GNp54KAwFN2VG3hZvkXZocT1aXENHJiHWijlFm7sN1SwFT1PyUp4dcVg4J8JRMBD61FOXo4oQpD1kHBiNND05WDsassXZzMz4eIIUSr7NR8ax84YCA2B4hrW8Q52Cqwz5xhh4RxnCxpC2vGs4utWlmhjuGPk1V5XfRncmJTEwEDoMRVD0NJtGHY5rNXRkod3X5F3DntBlIFSUfMP81jyt9eOJlWY0jShke5nZWCi1mihyrqGeQt6zrfBrCSyZ9kUyDs2W/L6jyLsuBoi1YV5rhs3jirzuZmbBodU3DIYubRlbiD3UH3FWT4bh0HB8m23dr4DZBdhQse/lprU4uKqDSH2cMvbkeFZxCXuc3cxw51HwHFJtSIDxWJNzFa2+h4NiWtpD5NVp9zIoZYvJvKeYXsjQkfgkusz/3v1ljmp/F+3ZmXauWNhKawaqMYzEETOLedZVAxZ3tuI7dp7V8yMRXV4eJ1lArr1IhjztaTtuyWd7fRWj2TH6VCdDcUjB9Sk4HkGaklEudZMQmRhfZegoHI+rbM58ZfOaakPOdenS7VS0Pd6HR7/JaW0fpzeTIzaGjKOoJ5pRKszKdvG83s07CvNJtYGa/SAi0K1oDD4uWXLUs4Mo5VAN97At+jWzCx9m0BmmVZcoUSAyMbPchexxNrJz3L759/FwlcOwqVJUefJ4zOJEEj/BFDR5v4M5bjf1NKHoTaPXLRBrO0yzYiJQMMNpZyDNUFcB0/0SOoZONZcWXSQlodObybi/gyjeTT7by3i6i9hpZUBXKLidtLrTKOa72VFbBdg/gLzbTkLCqDNE0ZSZ6Z5E7EboTMrm4NfESY3O/DFsG7mfOW0XUaIHD48R+olNjazJMBit40T3fHw/y9FmLoPM4NHqt5iTWUSSDZidW8SedB0Zt0DebQegmJ/HYH0dAN3FE3EaAzbCZJzB8d+gjX1jrpRL0ekBYNPYg3QX30JZTaPQ0tlYBHyAnSMPM628GBcf38mjVJYZ+bdS0u08F9zLzPzpRKbG7tHHOKr9XQzs5/Vb64Qg3kEuOx3fK5KkAUkysvd2FMpRzP1wHpyWvZ0TC/lGkWTnTCmwRU6U2CrAbbzgZPzm98pRe4fleS7K9xuTIx37pbUdqlcP7GM3FoRGa1voaG0LGa1tAaW1LdbKdmkF4hiCCFXI2oJvqGLbz5fzttjLZvY+/rYB6G61xRZAZ9key54RWyAW8jbWbMYOa/RclOvgArWVKR0zXVRPyRaCE0MWfc8WqRPqYfNbM1pn18MO7TOHyL/Dhzl9e4dLao0qhezZmjJrXoiakadjeAy/Q9niLqkxvCVH38IcyaYxvNOm48xM6I53Ud/pUDq60am4CpnpLirrkuwKqfc7JJEd0j/U6H7YloGSlxKFLiaNUZ4tnHWoCcc9WnoS/NYINGTKmmypQqkSMK1tnK1DZdvCXivwwO9w8EoGU0sZfcmj0B2jXHC7MrjtGn84Ia0ZMq0BhdaIymiWTCbFyTVWJdCgE4NXAl2zxVwa2jljp/UM4HkapeyQv7bpAWldkTcx5fY6wSaXUm/IeH+WfCkmM91FxylprHDyis1rysw9dYTqNpeWnhQ3r9i9tkj3SRG13Q5dXRXyHSnhqEOyrYeTyiktjTnto2GWjJtSLtVJEodqLYPrGCpBhrEwy7rxFrrydTJ+iuNoHMegHDtVo621Rkujm+WGSoFpuZD2kp3KcZxRdHdU8HOaod0txI3pFQB93WM8P7L/N7BCHE5kyOLL3HHHHVx77bUsX76cVatWsXDhQi655BJ27/7t8w2EEEIIIYQQ4vchQxZf5swzz+SMM87gm9/8JgBaa2bNmsVVV13FsmXL9nvfiSGL3z5xGZ1Zn1grBiKXegIFz9CRsVezaqnDL/sVBkN71nZ621bV9OYdNo0ntGacRqOMOr8xD3GOdx4bdT8nZ6fzdLiDhAQPj+P9PnryLvXEsLMWU9MxdSKOL7RRS7S9uuI59OWhxaPZ0MBVtolDi2sXos44hsFQ0Z015BpXt0Zih111yDiKodB+Qra9Zte1qquA4zI9/CL6FaerxWxkBzNNL4OMs8msZrY6mVVj/5tTW/+Eo9we7hr5OrNaz8HBp0/PZU7WfuKVaLv4sO8oWn3Hdjt0IExth72JoXytfmNdLGOIUnh+NCDruHTmPBT2KtJ4rNkUjDE9U2JbNIaHw8robmblTqdXT2fA2UNZt7MmuZeF3sW0qCwF16OeJuQcj9E0pOhk2KPHWRPdw9G5t5OSUGOU8/On4CrbfCHn2jXBHhnbRZuxa3HNzBbQGKpJysPJvRzjLKJLtbKdPbToAjWnSr9ZT6eaQ4duZ5e7g7LuZIt5Gt9pYaZewEaeYrY6mVFnkBnpLHY62wmpMUMfRRafHc4ONtUfIUkDzi1cTtHxybm2GcpgFDHMOK2mQHcmR2oML6W7cIzDTKeLVt9jQzDKo+PfZUH5Ujp0D4Gq4+Ix6gzSYkpoNOMMAlCik5gQB5eUvQvoVhikRbUTmnFm6PkMOwPUGaONXlzjMeoM2E59JqDMNKYZu/7PJrUFjyzbk9VUgn6ieDfv6/wCA0kdDwelFJucDfSkM/DxqKk6z4b3Mj93LgBZk2VMjRCrEN9kCaiQpYVYheRMkRqjtFBu/LtAUZfY7ryERhObWvPKSta0UDQlNrPGDkUzMW3eLLKmhZxpYbN+isHKWrSu8662P2M3I6Qqod+sp1cdTUAVjywJIS2mxEvxQ7T6fXSqOcSEVBgko1qa+UpNTEqMNjGeyuKrFgIzhotHiv0EeChYz5zc23AaV6pSYnZGawiSUTryxwCwc+RXnNz+EQC2JqswRnO0d1ZzeGRdhaxPH6PLP4bYBNT0IHPVQgadfjzjE1LDVT6hqWDQeGQJTQVX+QTpKJ6TpV3NYkvwOMVML2V3BrEJSAhx8XGVjzYpvsqxvb6K2blFuPgkhCQqxsFlZ7iGIBom65cBKGdmsKuymiQZoa/tbFqdPjaOP4DvFYmTGm0tR5F1iigcPLJoYlISFA5ZVWQ03dFc9yzRNRzlU3S7cfAZjjfiu0WyTpFY14h1nWq0mzQNmFl6G2PJDnwnT95pJzQVHByUcinRjUEzqDeTdYrsqT2HwiHVAa5jh9Npk5D1y7jKI9ERXmMx7ESHKGWfo4Lfxc3zz+XU7gFmvzOk8qxdtDeuQKYNwgGFVzAYDTpU9sJY1p5ijYa45uDlNV4LKK/RyEHb792Sg1Oyq7Hr0YhwW0oS2IWRB/sLjNZzlHIhzw21U/ISHGWHu/UHGRZ2jnDXli5Obw/ozgfM7BolW0gwGqK6HbY2PpbjoR09LGitMB77diRFJiJMXVq8hBkdYwDUA598LubHL83k/L5B8n7MUC3PSJSlr1BlxoxRHNdQH/PZuLud1myIMYrernFWbZrGjGKVR3d3cGrHGDe/UGZ6i8M7umvUUpf+wGe8MULAV/DuedvYM1rk6HmDBBWPaiVLW2cN5dgGEpWRLFHksWu8wNF9Q6SJQ6HDXmVTCga2F2lpicgVYxzfENccquNZNg62oY1icy3HiW3jGAN7ghz//JJtitPXYp/Pn49u4oLWueyup1w2y/CP6wKuP8mwvZ5nVkuNPUGOzTWfNt92ynWVoc2PG9MC7LqgeyKXs7rGyDopWT8h5yVUowyVyKfg29EyrqMZred4ZqQVR0F31o76eHo0z5yWmOHIZWfgMBjaxkxrR+x0ghPbHSqJougZ5hYSdgUeuUbzKm1gQSlkKPLoycaU/ISuvL26OdEBOW00vrJXnlJSrSjlQlLtYIwi4yVooxiq5dkT5Chn7Gv+tlqOXYFHqO37hcEQunPw1GDMMa0+Px3ZRJtu44RimVjDC7UR/t8Z7fzbzm24xmOu20XBd5je4jK3oCl6mkpipwkkWtGTTfAc8JSdnlD2E0LtUGs2zUrwHc2GSgsf/c2X9/veS4g/bK9/yKIUZA1RFNHS0sKdd97JZZdd1ty+ZMkSRkZG+MlPfrLP/mEYEoZ7h1+MjY0xa9Ysrp375+yp+6yOtrBHr6PXOZaYkP7ked7qXsAa8wjneO9EN4YY9rX4OMCasXFmZgsUfMULlQpFJ8NRxSyrxoY5odDG89VR5uZaMQbasw5Pjg1yemsn68bruMqhzffxHMXG+hhvKZXJe3bUyHMjITUdU1N1Til2s7tuX3DXmnUsMEezmV2ckp3JE+F6suR5euyHnFf8H/Tl8jjKdv5rHmOU0plz2VQNWNCaZ1ctIes61BNNa8bFUXafou9STzTlrF3gWDcaQrkKtlZDip5HR85jOEyZXbQnRk+pxvBHw9MjFUpuhvaMj6NgU61K2c3SmfPQBtu6W4PGNNqMa7pyPkFqC9F6oilnXILUEKaavOcQpYai7zAYJviOQ951mosfZ1xF1JgAVs66pNq21A9Sw3icNuObGD52bKmAxs6vqsaatqzbPMZqrNGA38ib60CUGgq+0yyUg9QOk6PxGDnXITaGUmMfu9wzjblQtjCemCM2cUwZx0FjaM/uXUQ6NXauQcFXjEU2DrfxHL7yr3wid66yj51xVTOvsbGLiStlC94otcVzauzix6mxDcEzjW2JNrR49nkMU207gil7W861izr7js1fkBqMMc2GcBP72JjAGBtT3HgOXKWajxc17pRq+3gv779ljCHUmpzrNh8jNQY18Two2x1xYu4E0Dyml8c30XY/SHXzd18pmseusY898Ry5jmosvG4a+6rm70+sTfPnpcbmMEhTso6L33j+M44trCeOLePY1v8T91MKqomdM2fzbvdzUMSN9vWBicgpO48qNAntbo6JP9uJmH/bq3xFx41W81AzEWUnT8axz0XGtb8XlTgl1DbmUKf4jtPMY6RtO/9Mo/913My/feyKqVMg18iZY593DEUnQ03HZJTbfDyNwW90EY2NpprGhMSEKiJrMvi2fG8+Vl7ZYX6J0QwwRkpCuylTJSBLpnm7xnYNzSgXg6FiQnIqwxAjaKXRaDzT2FdpcjpPhon7msaXxrGlHQ6KLx6fYST2uXr9L3n0nON4caCdOa3j3PRMN588ZozuYo0w9tg4VmI88TiuPEbej6mEGR4bbOOYYsDMYoWsnxAlLs8Nt7G15vNHs/opl+tkCylJqHhhSzdbay2c2DHMjzd3s7AtpCsb0h/kyDr2Tevmap6sa5iRr/PkcIlf7Iz4wokBz48WWdw7gDGK964c4F/fMqOxmHOGowohQ5HPcOxQdA1tjSHj1cRlIHLoyGge2q14R4+hMxszGPpsqLpE2vC2zghfGY4qjzEWZrn5hSJnditm5mNKXsJFj32Tb7/lz4gNzM7H/K8NDvNaPTqzML8Y8dCeDEVfsWYoYl6rz1vbUx4ZcPnvM2tsrOboyiaU/YT2bMDWaoFq4rJy2KPVh4umjZFoh/HYoycfkPMS/s/WLn6ya5DPzm+lIxOjMDwz1oIxtvPs5qqDq2B6XhMbxV9v+T8s7X0PY7GhJwf399c4rtTCxkrI3cNf5fpj/5L2jOF/bdvDqYVu+loctlU1RV9xSpvmq1vWsyh7DMe32SVKNo6nnNvrUPC0LXAczf+/y+Xu2r3MUidy+fTpKAUdfsqOwOXBXQGXzMjx5IDmh8Pf5avzP8FvhgwntCn+585f8OH283l6uM7C9jwtnmL9WMoxrQ7LX7qem47/S/7suev5b+2f47+Gb+I9HZ/jwj6fL276EX3Zk/h/2o5nbmGiU67i7u1V/nh2C4ORoiNjaPVSIu3w/LjDb4bqXDYrR3c2ZijyWFdx2F7VLOqyLxzf3Pk8lxSPZ1s15sT2DF/f+SO+MOt9rBpMWVD22DCW0ppxuK/2HG/LLKAn7xCmsKdu5wkr4N/Hf8J7Cu+lPwgITcouZyfv6zyWgcDgKvv83DP2EruStZzpXsIg42RNhrKTp6IjQiKWzO7gU7IwtDikyRyyAzYwMECapvT29u6zvbe3l+eff/5V+99www186UtfetX2UIeNNyoR2iSkJiIlQpuUxIRokxDrsPnGKtIpDpCYkEh7+Np+HxtDpE1je9D4f9hYV0g1t8cmROMQafsGfGK7oxvrW5mIxMQkRHZ/bT+dT4mJTUhKRKTDRpz2zax9DKdZRE2Itf00KzEhoVbEOkUpp7ndvgm138fa2H1fUZDFJiLWKZFOiLUmbLSzTxsFWdg4Znv8aWOtsZDYQKSTRkFm130yjaIiNppI26YeBtWMIdI2HrcZj40ZHFxlW9DrxrveWE88H07zDbW9vy3IjFLExpCYiEjbOXORNs2fNXGMdr0nuz/YWTp7f/ZEfAZQzZw6yraxn9hHNW4zjYIM7Pw2A81jAgfD3hxH2ubFGPD13ji0srl95RvyidxppUiVArU3r8nLCrKJeDW2Jb9q/H9ixTfdKMiixvM4UYSkjRb+jrJrqtl5cPb2fQoyDK7etyDTLyvIdKMgS1/2HKWN/L2yIIuNxtVu8zFeXpBpZeeCvbwgs2/W7e+AwRZCEwVZbDSNWUAoY+OcKAi0US8rmvdTkBmDahx7agxGK2KT4hjXBgSALcgmjg3s/V9ekMUmBeOQ8uqCLDGaxEQkje2Jsc17lGk+ui3IeLXE2IJMAYmJiI2DajwXqvF7EZu0GfNEHA728SfWV1PGbebM1XbOY2JiEhOSNH/+3oLM/h3FKNzm42kMmMbvELrxmmWvMibGoEhfdiwOcaNveGI0KREpSePnhbiY5u029xqFLcjsPsa+Jjf+U2ZiXUVNYhycxn1/V0FWTQy1VKNNwngcUU1CKol9fa0kIbk4Iko01SSklqZUkpBEJVQTQz0N9u5PQpy61NKQepoynkQ4cUQYpSSxatzfpZJEBGlALY0a2+wyFJBQT+3vRTUJCVKf2MRUk5B66lNJIoxRpI1ttRTqqaaaRNRSTT1VuEAmtQVZPbXzmOupfT2pp1BLY+qpfZ2OtKGWxvjKUEkiqglE2m/sl+CQ2CUg0oDY2G2xdgh1QtB4rFBrfK2ITUyoU2qpff20MStqaYKnEnw3pJZ61FK3ef9qEpJoh2rSyCkpQWrPjbU0JJvYgqye2iZZiYFQ24KsnmoSo9AmJdQBobaNjibOdbGJAEOQBtRTQ2rs82nnO2tCrV6xXTXWZ7R5dJTBGEViJs4HCSn2eVMK6o3GV7EJCVJ77jBGE6QBkTYEqUKbhLBxrg+1wkkVkdaNueU2NjDEJsQ0/l9PU4xJSU1MqG3ssbaNuhITUk+d5nPqKd14PlTjvvY5qqcpobYfeNUb7fgnHi/WCaHWGGNzbc/ZCZHWjfU8YyJt453Ix8T6msakzfcoiUlJTUSo7fHaZTwgNRHGpM33IokxxMZpvKZF1BvHLMShqzFC4nVc+5IrZA07duxgxowZPPLIIyxevLi5/XOf+xwPPvggjz322D77v/IK2caNGznllFMmK1whhBBCCCHEH7itW7cyc+bM/e4jV8gaurq6cF2X/v7+fbb39/czbdq0V+2fzWbJZrPNf8+ZMweALVu2UC6X39xgBbB3mOjWrVtf81KwODgk55NPcj75JOeTT3I++STnk09yPvmmMufGGMbHx5k+ffpr7isFWUMmk+G0007jvvvua84h01pz3333ceWVV77m/Z3G3ItyuSx/ZJOstbVVcj7JJOeTT3I++STnk09yPvkk55NPcj75pirnr/cijRRkL3PttdeyZMkSTj/9dBYtWsTXvvY1qtUqV1xxxVSHJoQQQgghhDgMSUH2Mh/4wAfYs2cP1113Hbt27eKUU07hnnvueVWjDyGEEEIIIYQ4GKQge4Urr7zydQ1RfKVsNsvy5cv3mVcm3lyS88knOZ98kvPJJzmffJLzySc5n3yS88l3qORcuiwKIYQQQgghxBRxpjoAIYQQQgghhDhSSUEmhBBCCCGEEFNECjIhhBBCCCGEmCJSkAkhhBBCCCHEFJGC7CC5+eabmTt3LrlcjjPPPJPHH398qkM6LBxoXkdGRli6dCl9fX1ks1mOPfZYVqxYMUnRHvp++ctfcumllzJ9+nSUUvzHf/zHfvf/8Y9/zEUXXUR3dzetra0sXryYn/3sZ5MT7GHiQHMOcOutt7Jw4UJaWlro6+vjYx/7GIODg29+sIeBG264gTPOOINSqURPTw+XXXYZL7zwwuu+/+23345Sissuu+zNC/II8u1vf5uTTz65uWjr4sWL+elPfzrVYR3y3khe5fx5cN14440opbjmmmt+5z633HILb3/722lvb6e9vZ0LL7xQ3j++Qa8n3wBf+9rXWLBgAfl8nlmzZvGnf/qnBEEwOUHuhxRkB8Edd9zBtddey/Lly1m1ahULFy7kkksuYffu3VMd2iHtQPMaRREXXXQRmzZt4s477+SFF17glltuYcaMGZMc+aGrWq2ycOFCbr755te1/y9/+UsuuugiVqxYwcqVKznvvPO49NJLeeqpp97kSA8fB5rzhx9+mI985CN8/OMfZ+3atfzoRz/i8ccf5xOf+MSbHOnh4cEHH2Tp0qX8+te/5t577yWOYy6++GKq1epr3nfTpk189rOf5e1vf/skRHpkmDlzJjfeeCMrV67kySef5Pzzz+e9730va9eunerQDmkHmlc5fx5cTzzxBP/0T//EySefvN/9HnjgAT74wQ9y//338+ijjzJr1iwuvvhitm/fPkmRHh5eb75/8IMfsGzZMpYvX85zzz3Hd7/7Xe644w7+/M//fJIi3Q8jfm+LFi0yS5cubf47TVMzffp0c8MNN0xhVIe+A83rt7/9bTNv3jwTRdFkhXhYA8xdd911wPc74YQTzJe+9KWDH9AR4PXk/KabbjLz5s3bZ9vXv/51M2PGjDcxssPX7t27DWAefPDB/e6XJIk566yzzHe+8x2zZMkS8973vndyAjwCtbe3m+985ztTHcZhZ395lfPnwTM+Pm7mz59v7r33XnPuueeaq6+++nXfN0kSUyqVzPe///03L8DDzIHke+nSpeb888/fZ9u1115rzj777Dc5ytcmV8h+T1EUsXLlSi688MLmNsdxuPDCC3n00UenMLJD2xvJ63/+53+yePFili5dSm9vLyeeeCJf+cpXSNN0ssI+4mmtGR8fp6OjY6pDOWwtXryYrVu3smLFCowx9Pf3c+edd/Kud71rqkM7JI2OjgK85u/sX//1X9PT08PHP/7xyQjriJSmKbfffjvVapXFixdPdTiHjdeTVzl/HjxLly7l3e9+9z7vX16vWq1GHMdyDj0AB5Lvs846i5UrVzaHhW7YsIEVK1b8QZw/vakO4FA3MDBAmqb09vbus723t5fnn39+iqI69L2RvG7YsIFf/OIXfOhDH2LFihWsW7eOz3zmM8RxzPLlyycj7CPe3/3d31GpVHj/+98/1aEcts4++2xuvfVWPvCBDxAEAUmScOmll77uIY9iL60111xzDWeffTYnnnji79zvoYce4rvf/S6rV6+evOCOIGvWrGHx4sUEQUCxWOSuu+7ihBNOmOqwDnkHklc5fx4ct99+O6tWreKJJ554Q/f//Oc/z/Tp099QMXckOtB8/8mf/AkDAwOcc845GGNIkoRPfepTfxBDFuUKmThsaK3p6enhn//5nznttNP4wAc+wBe/+EX+8R//capDOyL84Ac/4Etf+hI//OEP6enpmepwDlvPPvssV199Nddddx0rV67knnvuYdOmTXzqU5+a6tAOOUuXLuWZZ57h9ttv/537jI+Pc/nll3PLLbfQ1dU1idEdORYsWMDq1at57LHH+PSnP82SJUt49tlnpzqsQ96B5FXOn7+/rVu3cvXVV3PrrbeSy+UO+P433ngjt99+O3fdddcbuv+R5o3k+4EHHuArX/kK3/rWt1i1ahU//vGP+a//+i+uv/76Nzna12Gqx0we6sIwNK7rvmrex0c+8hHznve8Z2qCOgy8kby+4x3vMBdccME+21asWGEAE4bhmxXqYYsDmEN22223mXw+b+6+++43N6jD3OvJ+Yc//GHzvve9b59tv/rVrwxgduzY8SZGd3hZunSpmTlzptmwYcN+93vqqacMYFzXbX4ppYxSyriua9atWzdJER85LrjgAvPJT35yqsM47Owvr3L+/P3dddddr3qtAJqvFUmS/M773nTTTaZcLpsnnnhiEiM+tL2RfJ9zzjnms5/97D7b/u3f/s3k83mTpulkhf5byRWy31Mmk+G0007jvvvua27TWnPffffJGPjfwxvJ69lnn826devQWje3vfjii/T19ZHJZN70mI9Ut912G1dccQW33XYb7373u6c6nMNerVbDcfZ96XZdFwBjzFSEdEgxxnDllVdy11138Ytf/IKjjjpqv/sfd9xxrFmzhtWrVze/3vOe93DeeeexevVqZs2aNUmRHzm01oRhONVhHHb2l1c5f/7+Lrjggle9Vpx++ul86EMfYvXq1c3X6Vf66le/yvXXX88999zD6aefPslRH7reSL7/oM+fU1oOHiZuv/12k81mzb/+67+aZ5991nzyk580bW1tZteuXVMd2iHttfJ6+eWXm2XLljX337JliymVSubKK680L7zwgrn77rtNT0+P+Zu/+ZupOoRDzvj4uHnqqaeaVwX+/u//3jz11FNm8+bNxhhjli1bZi6//PLm/rfeeqvxPM/cfPPNZufOnc2vkZGRqTqEQ86B5vx73/ue8TzPfOtb3zLr1683Dz30kDn99NPNokWLpuoQDimf/vSnTblcNg888MA+v7O1Wq25zytfW15JuiwePMuWLTMPPvig2bhxo3n66afNsmXLjFLK/PznP5/q0A5pr5VXOX9Ojld2/Xtl3m+88UaTyWTMnXfeuc/r0fj4+BREe+h7rXwvX77clEolc9ttt5kNGzaYn//85+boo48273//+6cg2n1JQXaQfOMb3zCzZ882mUzGLFq0yPz617+e6pAOC/vL67nnnmuWLFmyz/6PPPKIOfPMM002mzXz5s0zX/7yl/c7TEDs6/777zfAq74m8rxkyRJz7rnnNvc/99xz97u/eG0HmnNjbJv7E044weTzedPX12c+9KEPmW3btk1+8Ieg35ZrwHzve99r7vPbXlteTgqyg+djH/uYmTNnjslkMqa7u9tccMEFUowdBK+VVzl/To5XFgivzPucOXN+6+vR8uXLJz3Ww8Fr5TuOY/NXf/VX5uijjza5XM7MmjXLfOYznzHDw8OTHusrKWOm+hqdEEIIIYQQQhyZZA6ZEEIIIYQQQkwRKciEEEIIIYQQYopIQSaEEEIIIYQQU0QKMiGEEEIIIYSYIlKQCSGEEEIIIcQUkYJMCCGEEEIIIaaIFGRCCCGEEEIIMUWkIBNCCCEO0Ec/+lEuu+yyqQ5DCCHEYcCb6gCEEEKIPyRKqf3evnz5cv7hH/4BY8wkRSSEEOJwJgWZEEII8TI7d+5sfn/HHXdw3XXX8cILLzS3FYtFisXiVIQmhBDiMCRDFoUQQoiXmTZtWvOrXC6jlNpnW7FYfNWQxXe+851cddVVXHPNNbS3t9Pb28stt9xCtVrliiuuoFQqccwxx/DTn/50n5/1zDPP8Ed/9EcUi0V6e3u5/PLLGRgYmOQjFkIIMZWkIBNCCCEOgu9///t0dXXx+OOPc9VVV/HpT3+aP/7jP+ass85i1apVXHzxxVx++eXUajUARkZGOP/88zn11FN58sknueeee+jv7+f973//FB+JEEKIySQFmRBCCHEQLFy4kL/4i79g/vz5fOELXyCXy9HV1cUnPvEJ5s+fz3XXXcfg4CBPP/00AN/85jc59dRT+cpXvsJxxx3Hqaeeyr/8y79w//338+KLL07x0QghhJgsModMCCGEOAhOPvnk5veu69LZ2clJJ53U3Nbb2wvA7t27AfjNb37D/fff/1vno61fv55jjz32TY5YCCHEHwIpyIQQQoiDwPf9ff6tlNpn20T3Rq01AJVKhUsvvZS//du/fdVj9fX1vYmRCiGE+EMiBZkQQggxBd761rfy7//+78ydOxfPk9OxEEIcqWQOmRBCCDEFli5dytDQEB/84Ad54oknWL9+PT/72c+44oorSNN0qsMTQggxSaQgE0IIIabA9OnTefjhh0nTlIsvvpiTTjqJa665hra2NhxHTs9CCHGkUMYYM9VBCCGEEEIIIcSRSD6CE0IIIYQQQogpIgWZEEIIIYQQQkwRKciEEEIIIYQQYopIQSaEEEIIIYQQU0QKMiGEEEIIIYSYIlKQCSGEEEIIIcQUkYJMCCGEEEIIIaaIFGRCCCGEEEIIMUWkIBNCCCGEEEKIKSIFmRBCCCGEEEJMESnIhBBCCCGEEGKKSEEmhBBCCCGEEFPk/wKZDETC/+W5OAAAAABJRU5ErkJggg==", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Spektogram nach Model 1:\n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Spektogram nach Model 2:\n" ] }, { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "song_id = 15 # 15 20 30\n", "\n", "# STFT Parameter setzen\n", "stft_params = nussl.STFTParams(window_length=512, hop_length=128, window_type='sqrt_hann')\n", "#stft_params = nussl.STFTParams(window_length=1024, hop_length=256, window_type='sqrt_hann')\n", "\n", "# Pfad zu den Trainingsdaten festlegen\n", "fg_path = \"C:\\\\Users\\\\Lukas\\\\nussl_tutorial\\\\train\"\n", "\n", "# Trainingsdaten mit `nussl` laden\n", "train_data = data.on_the_fly(stft_params, transform=None, fg_path=fg_path, num_mixtures=2000, coherent_prob=0.1)\n", "\n", "# Testdaten laden\n", "test_path = \"C:\\\\Users\\\\Lukas\\\\nussl_tutorial\\\\test\"\n", "test_data = data.on_the_fly(stft_params, transform=None, fg_path=test_path, num_mixtures=100)\n", "\n", "#song_id = 15\n", "# 15 20 30\n", "\n", "test_item = test_data[song_id]\n", "mix = test_item['mix']\n", "mix_array = mix.audio_data[0]\n", "#print(mix_array.shape)\n", "vocals = test_item['sources']['vocals']\n", "\n", "mix_mag, ph, max = preprocess(mix_array)\n", "\n", "mask1 = model1(tf.expand_dims(mix_mag, axis=0), training=False)\n", "neu1 = mask1[0] * mix_mag\n", "#neu1 = mask1[0]\n", "audi1 = postprocess(neu1, max, ph)\n", "audio_vocal1 = nussl.AudioSignal()\n", "audio_vocal1.audio_data = audi1\n", "\n", "mask2 = model2(tf.expand_dims(mix_mag, axis=0), training=False)\n", "neu2 = mask2[0] * mix_mag\n", "audi2 = postprocess(neu2, max, ph)\n", "audio_vocal2 = nussl.AudioSignal()\n", "audio_vocal2.audio_data = audi2\n", "\n", "item = test_data[song_id]\n", "\n", "# Orginaldaten\n", "print('Mix:')\n", "display(Audio(data=item['mix'].audio_data, rate=item['mix'].sample_rate))\n", "#print(item.keys())\n", "#show_wav(item['sources'])\n", "#show_fre(item['sources'])\n", "\n", "print('Vocals:')\n", "display(Audio(data=item['sources']['vocals'].audio_data, rate=item['mix'].sample_rate))\n", "\n", "# Audio nach Model\n", "print('nach model 1:')\n", "display(Audio(data=audio_vocal1.audio_data, rate=item['mix'].sample_rate))\n", "\n", "print('nach model 2:')\n", "display(Audio(data=audio_vocal2.audio_data, rate=item['mix'].sample_rate))\n", "\n", "print('Ziel Amplitudenverlauf:')\n", "show_1wav(data=item['sources']['vocals'])\n", "print('Amplitudenverlauf nach Model 1:')\n", "show_1wav(audio_vocal1)\n", "\n", "print('Amplitudenverlauf nach Model 2:')\n", "show_1wav(audio_vocal2)\n", "\n", "print('Ziel Spektogram:')\n", "show_1fre(data=item['sources']['vocals'])\n", "print('Spektogram nach Model 1:')\n", "show_1fre(audio_vocal1)\n", "\n", "print('Spektogram nach Model 2:')\n", "show_1fre(audio_vocal2)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 2 }