{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# VGG16 and ImageNet" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "[ImageNet](http://www.image-net.org/challenges/LSVRC/) is an image classification and localization competition. [VGG16](http://www.robots.ox.ac.uk/~vgg/research/very_deep/) is a 16-layer network architecture and weights trained on the competition dataset by the Visual Geometry Group (VGG).\n", "\n", "In this notebook we explore testing the network on samples images.\n", "\n", "## Constructing the Network\n", "\n", "First, we import the ConX library:" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Using TensorFlow backend.\n", "ConX, version 3.6.8\n" ] } ], "source": [ "import conx as cx" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can load in a number of predefined networks, including \"VGG16\" and \"VGG19\":" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "WARNING: no such history file '/home/dblank/.keras/models/history.pickle'\n" ] } ], "source": [ "net = cx.Network.get(\"vgg16\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We get a warning letting us know that this is a trained model, but no training history exists. That is because this model was trained outside of ConX." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's see what this network looks like:" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "application/javascript": [ "\n", "require(['base/js/namespace'], function(Jupyter) {\n", " Jupyter.notebook.kernel.comm_manager.register_target('conx_svg_control', function(comm, msg) {\n", " comm.on_msg(function(msg) {\n", " var data = msg[\"content\"][\"data\"];\n", " var images = document.getElementsByClassName(data[\"class\"]);\n", " for (var i = 0; i < images.length; i++) {\n", " if (data[\"href\"]) {\n", " images[i].setAttributeNS(null, \"href\", data[\"href\"]);\n", " }\n", " if (data[\"src\"]) {\n", " images[i].setAttributeNS(null, \"src\", data[\"src\"]);\n", " }\n", " }\n", " });\n", " });\n", "});\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " Layer: predictions (output)\n", " output range: (0, 1)\n", " shape = (1000,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = softmax\n", " use_bias = TruepredictionsWeights from fc2 to predictions\n", " predictions/kernel:0 has shape (4096, 1000)\n", " predictions/bias:0 has shape (1000,)Layer: fc2 (hidden)\n", " output range: (0, +Infinity)\n", " shape = (4096,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = relu\n", " use_bias = Truefc2Weights from fc1 to fc2\n", " fc2/kernel:0 has shape (4096, 4096)\n", " fc2/bias:0 has shape (4096,)Layer: fc1 (hidden)\n", " output range: (0, +Infinity)\n", " shape = (4096,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = relu\n", " use_bias = Truefc1Weights from flatten to fc1\n", " fc1/kernel:0 has shape (25088, 4096)\n", " fc1/bias:0 has shape (4096,)Layer: flatten (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = Flatten\n", " trainable = TrueflattenWeights from block5_pool to flattenLayer: block5_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock5_pool5120Weights from block5_conv3 to block5_poolLayer: block5_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv35120Weights from block5_conv2 to block5_conv3\n", " block5_conv3/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv3/bias:0 has shape (512,)Layer: block5_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv25120Weights from block5_conv1 to block5_conv2\n", " block5_conv2/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv2/bias:0 has shape (512,)Layer: block5_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv15120Weights from block4_pool to block5_conv1\n", " block5_conv1/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv1/bias:0 has shape (512,)Layer: block4_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock4_pool5120Weights from block4_conv3 to block4_poolLayer: block4_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv35120Weights from block4_conv2 to block4_conv3\n", " block4_conv3/kernel:0 has shape (3, 3, 512, 512)\n", " block4_conv3/bias:0 has shape (512,)Layer: block4_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv25120Weights from block4_conv1 to block4_conv2\n", " block4_conv2/kernel:0 has shape (3, 3, 512, 512)\n", " block4_conv2/bias:0 has shape (512,)Layer: block4_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv15120Weights from block3_pool to block4_conv1\n", " block4_conv1/kernel:0 has shape (3, 3, 256, 512)\n", " block4_conv1/bias:0 has shape (512,)Layer: block3_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock3_pool2560Weights from block3_conv3 to block3_poolLayer: block3_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv32560Weights from block3_conv2 to block3_conv3\n", " block3_conv3/kernel:0 has shape (3, 3, 256, 256)\n", " block3_conv3/bias:0 has shape (256,)Layer: block3_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv22560Weights from block3_conv1 to block3_conv2\n", " block3_conv2/kernel:0 has shape (3, 3, 256, 256)\n", " block3_conv2/bias:0 has shape (256,)Layer: block3_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv12560Weights from block2_pool to block3_conv1\n", " block3_conv1/kernel:0 has shape (3, 3, 128, 256)\n", " block3_conv1/bias:0 has shape (256,)Layer: block2_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock2_pool1280Weights from block2_conv2 to block2_poolLayer: block2_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 128\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock2_conv21280Weights from block2_conv1 to block2_conv2\n", " block2_conv2/kernel:0 has shape (3, 3, 128, 128)\n", " block2_conv2/bias:0 has shape (128,)Layer: block2_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 128\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock2_conv11280Weights from block1_pool to block2_conv1\n", " block2_conv1/kernel:0 has shape (3, 3, 64, 128)\n", " block2_conv1/bias:0 has shape (128,)Layer: block1_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock1_pool640Weights from block1_conv2 to block1_poolLayer: block1_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 64\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock1_conv2640Weights from block1_conv1 to block1_conv2\n", " block1_conv2/kernel:0 has shape (3, 3, 64, 64)\n", " block1_conv2/bias:0 has shape (64,)Layer: block1_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 64\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock1_conv1640Weights from input_1 to block1_conv1\n", " block1_conv1/kernel:0 has shape (3, 3, 3, 64)\n", " block1_conv1/bias:0 has shape (64,)Layer: input_1 (input)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = Input\n", " batch_shape = (None, 224, 224, 3)input_130VGG16" ], "text/plain": [ "" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.picture(rotate=True)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Predefined networks have an info method describing the network:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/markdown": [ "**Network**: VGG16\n", "\n", " * **Status**: compiled \n", " * **Layers**: 23 \n", "\n", "This network architecture comes from the paper:\n", "\n", "Very Deep Convolutional Networks for Large-Scale Image Recognition\n", "by Karen Simonyan and Andrew Zisserman.\n", "\n", "Their network was trained on the ImageNet challenge dataset.\n", "The dataset contains 32,326 images broken down into 1,000 categories.\n", "\n", "The network was trained for 74 epochs on the training data. This typically\n", "took 3 to 4 weeks time on a computer with 4 GPUs. This network's weights were\n", "converted from the original Caffe model into Keras.\n", "\n", "Sources:\n", " * https://arxiv.org/pdf/1409.1556.pdf \n", " * http://www.robots.ox.ac.uk/~vgg/research/very_deep/ \n", " * http://www.image-net.org/challenges/LSVRC/ \n", " * http://image-net.org/challenges/LSVRC/2014/ \n", " * http://image-net.org/challenges/LSVRC/2014/browse-synsets \n", "\n" ], "text/plain": [ "**Network**: VGG16\n", "\n", " * **Status**: compiled \n", " * **Layers**: 23 \n", "\n", "This network architecture comes from the paper:\n", "\n", "Very Deep Convolutional Networks for Large-Scale Image Recognition\n", "by Karen Simonyan and Andrew Zisserman.\n", "\n", "Their network was trained on the ImageNet challenge dataset.\n", "The dataset contains 32,326 images broken down into 1,000 categories.\n", "\n", "The network was trained for 74 epochs on the training data. This typically\n", "took 3 to 4 weeks time on a computer with 4 GPUs. This network's weights were\n", "converted from the original Caffe model into Keras.\n", "\n", "Sources:\n", " * https://arxiv.org/pdf/1409.1556.pdf \n", " * http://www.robots.ox.ac.uk/~vgg/research/very_deep/ \n", " * http://www.image-net.org/challenges/LSVRC/ \n", " * http://image-net.org/challenges/LSVRC/2014/ \n", " * http://image-net.org/challenges/LSVRC/2014/browse-synsets \n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "net.info()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see a complete summary of each layer:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", "input_1 (InputLayer) (None, 224, 224, 3) 0 \n", "_________________________________________________________________\n", "block1_conv1 (Conv2D) (None, 224, 224, 64) 1792 \n", "_________________________________________________________________\n", "block1_conv2 (Conv2D) (None, 224, 224, 64) 36928 \n", "_________________________________________________________________\n", "block1_pool (MaxPooling2D) (None, 112, 112, 64) 0 \n", "_________________________________________________________________\n", "block2_conv1 (Conv2D) (None, 112, 112, 128) 73856 \n", "_________________________________________________________________\n", "block2_conv2 (Conv2D) (None, 112, 112, 128) 147584 \n", "_________________________________________________________________\n", "block2_pool (MaxPooling2D) (None, 56, 56, 128) 0 \n", "_________________________________________________________________\n", "block3_conv1 (Conv2D) (None, 56, 56, 256) 295168 \n", "_________________________________________________________________\n", "block3_conv2 (Conv2D) (None, 56, 56, 256) 590080 \n", "_________________________________________________________________\n", "block3_conv3 (Conv2D) (None, 56, 56, 256) 590080 \n", "_________________________________________________________________\n", "block3_pool (MaxPooling2D) (None, 28, 28, 256) 0 \n", "_________________________________________________________________\n", "block4_conv1 (Conv2D) (None, 28, 28, 512) 1180160 \n", "_________________________________________________________________\n", "block4_conv2 (Conv2D) (None, 28, 28, 512) 2359808 \n", "_________________________________________________________________\n", "block4_conv3 (Conv2D) (None, 28, 28, 512) 2359808 \n", "_________________________________________________________________\n", "block4_pool (MaxPooling2D) (None, 14, 14, 512) 0 \n", "_________________________________________________________________\n", "block5_conv1 (Conv2D) (None, 14, 14, 512) 2359808 \n", "_________________________________________________________________\n", "block5_conv2 (Conv2D) (None, 14, 14, 512) 2359808 \n", "_________________________________________________________________\n", "block5_conv3 (Conv2D) (None, 14, 14, 512) 2359808 \n", "_________________________________________________________________\n", "block5_pool (MaxPooling2D) (None, 7, 7, 512) 0 \n", "_________________________________________________________________\n", "flatten (Flatten) (None, 25088) 0 \n", "_________________________________________________________________\n", "fc1 (Dense) (None, 4096) 102764544 \n", "_________________________________________________________________\n", "fc2 (Dense) (None, 4096) 16781312 \n", "_________________________________________________________________\n", "predictions (Dense) (None, 1000) 4097000 \n", "=================================================================\n", "Total params: 138,357,544\n", "Trainable params: 138,357,544\n", "Non-trainable params: 0\n", "_________________________________________________________________\n" ] } ], "source": [ "net.summary()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This network is huge! 138 million weights! \n", "\n", "But why does this have 23 layers when it is described as having 16? The original description only counted layers that have trainable weights. So, that doesn't include the input layer (1) nor the pooling layers (5) or the flatten layer (1). So:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "16" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "23 - 1 - 5 - 1 " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Testing" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's see what the network can do. Let's grab an image and propagate it through the network (I'll show you where this image came from in just a moment).\n", "\n", "We download the picture:" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using cached http://farm4.static.flickr.com/3426/3817878004_7dec9cdfbd.jpg as './geyser-1.jpg'.\n" ] } ], "source": [ "cx.download(\"http://farm4.static.flickr.com/3426/3817878004_7dec9cdfbd.jpg\", filename=\"geyser-1.jpg\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In order to propagate it through the network, it needs to be resized to 224 x 224, so we can do that as we open it:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img = cx.image(\"geyser-1.jpg\", resize=(224, 224))\n", "img" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To propagate it through the network it should be a 3D matrix:" ] }, { "cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [], "source": [ "array = cx.image_to_array(img)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This network comes with a special preprocess() method for getting the image values into the proper range:" ] }, { "cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": [ "array2 = net.preprocess(array)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And now, we are ready to propagate the array through the network:" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [], "source": [ "output = net.propagate(array2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What is this output?" ] }, { "cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1000" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(output)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can pretty-format the output to see condensed view of the values:" ] }, { "cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 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0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.03,0.00,0.09,0.00,0.76, 0.00,0.00,0.00,0.00,0.03,0.01,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00, 0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00,0.00]\n" ] } ], "source": [ "print(net.pf(output))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This network comes with a special method postprocess() that will take this values and look them up, giving us the category ID, and a nice human-readable label:" ] }, { "cell_type": "code", "execution_count": 34, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('n09288635', 'geyser', 0.7626754641532898),\n", " ('n09246464', 'cliff', 0.08688867092132568),\n", " ('n09193705', 'alp', 0.03189372643828392),\n", " ('n09468604', 'valley', 0.027246791869401932),\n", " ('n03160309', 'dam', 0.01493859849870205)]" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.postprocess(output)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Indeed, this is a picture of a geyser!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see a picture of the entire network, with activations:" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/html": [ "\n", " \n", " \n", " \n", " \n", " \n", " \n", " Layer: predictions (output)\n", " output range: (0, 1)\n", " shape = (1000,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = softmax\n", " use_bias = TruepredictionsWeights from fc2 to predictions\n", " predictions/kernel:0 has shape (4096, 1000)\n", " predictions/bias:0 has shape (1000,)Layer: fc2 (hidden)\n", " output range: (0, +Infinity)\n", " shape = (4096,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = relu\n", " use_bias = Truefc2Weights from fc1 to fc2\n", " fc2/kernel:0 has shape (4096, 4096)\n", " fc2/bias:0 has shape (4096,)Layer: fc1 (hidden)\n", " output range: (0, +Infinity)\n", " shape = (4096,)\n", " Keras class = Dense\n", " trainable = True\n", " activation = relu\n", " use_bias = Truefc1Weights from flatten to fc1\n", " fc1/kernel:0 has shape (25088, 4096)\n", " fc1/bias:0 has shape (4096,)Layer: flatten (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = Flatten\n", " trainable = TrueflattenWeights from block5_pool to flattenLayer: block5_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock5_pool5120Weights from block5_conv3 to block5_poolLayer: block5_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv35120Weights from block5_conv2 to block5_conv3\n", " block5_conv3/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv3/bias:0 has shape (512,)Layer: block5_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv25120Weights from block5_conv1 to block5_conv2\n", " block5_conv2/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv2/bias:0 has shape (512,)Layer: block5_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock5_conv15120Weights from block4_pool to block5_conv1\n", " block5_conv1/kernel:0 has shape (3, 3, 512, 512)\n", " block5_conv1/bias:0 has shape (512,)Layer: block4_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock4_pool5120Weights from block4_conv3 to block4_poolLayer: block4_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv35120Weights from block4_conv2 to block4_conv3\n", " block4_conv3/kernel:0 has shape (3, 3, 512, 512)\n", " block4_conv3/bias:0 has shape (512,)Layer: block4_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv25120Weights from block4_conv1 to block4_conv2\n", " block4_conv2/kernel:0 has shape (3, 3, 512, 512)\n", " block4_conv2/bias:0 has shape (512,)Layer: block4_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 512\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock4_conv15120Weights from block3_pool to block4_conv1\n", " block4_conv1/kernel:0 has shape (3, 3, 256, 512)\n", " block4_conv1/bias:0 has shape (512,)Layer: block3_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock3_pool2560Weights from block3_conv3 to block3_poolLayer: block3_conv3 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv32560Weights from block3_conv2 to block3_conv3\n", " block3_conv3/kernel:0 has shape (3, 3, 256, 256)\n", " block3_conv3/bias:0 has shape (256,)Layer: block3_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv22560Weights from block3_conv1 to block3_conv2\n", " block3_conv2/kernel:0 has shape (3, 3, 256, 256)\n", " block3_conv2/bias:0 has shape (256,)Layer: block3_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 256\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock3_conv12560Weights from block2_pool to block3_conv1\n", " block3_conv1/kernel:0 has shape (3, 3, 128, 256)\n", " block3_conv1/bias:0 has shape (256,)Layer: block2_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock2_pool1280Weights from block2_conv2 to block2_poolLayer: block2_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 128\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock2_conv21280Weights from block2_conv1 to block2_conv2\n", " block2_conv2/kernel:0 has shape (3, 3, 128, 128)\n", " block2_conv2/bias:0 has shape (128,)Layer: block2_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 128\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock2_conv11280Weights from block1_pool to block2_conv1\n", " block2_conv1/kernel:0 has shape (3, 3, 64, 128)\n", " block2_conv1/bias:0 has shape (128,)Layer: block1_pool (hidden)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = MaxPooling2D\n", " trainable = True\n", " pool_size = (2, 2)\n", " padding = valid\n", " strides = (2, 2)\n", " data_format = channels_lastblock1_pool640Weights from block1_conv2 to block1_poolLayer: block1_conv2 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 64\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock1_conv2640Weights from block1_conv1 to block1_conv2\n", " block1_conv2/kernel:0 has shape (3, 3, 64, 64)\n", " block1_conv2/bias:0 has shape (64,)Layer: block1_conv1 (hidden)\n", " output range: (0, +Infinity)\n", " Keras class = Conv2D\n", " trainable = True\n", " filters = 64\n", " kernel_size = (3, 3)\n", " strides = (1, 1)\n", " padding = same\n", " data_format = channels_last\n", " dilation_rate = (1, 1)\n", " activation = relu\n", " use_bias = Trueblock1_conv1640Weights from input_1 to block1_conv1\n", " block1_conv1/kernel:0 has shape (3, 3, 3, 64)\n", " block1_conv1/bias:0 has shape (64,)Layer: input_1 (input)\n", " output range: (-Infinity, +Infinity)\n", " Keras class = Input\n", " batch_shape = (None, 224, 224, 3)input_130VGG16" ], "text/plain": [ "" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.picture(array2, scale=0.25)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Why is the first layer gray? Because it is a regular input layer, with 3 channels, and it is showing the first channel. \n", "\n", "How does the network represent a picture? It re-represents the picture at every layer. Many layers are composed of features. For example, we can look at the first layer, `input_1`:" ] }, { "cell_type": "code", "execution_count": 36, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

Feature 0

Feature 1

Feature 2
" ], "text/plain": [ "" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.propagate_to_features(\"input_1\", array2)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "In this example, a feature is a color channel. So feature 0 is Red, feature 1 is Green, and feature 2 is Blue." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can view all channels together by propagating to the input layer, and then viewing the output as an image:" ] }, { "cell_type": "code", "execution_count": 37, "metadata": {}, "outputs": [ { "data": { "image/png": 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VlbXCVtYQbMv5OI3RBdSceSPyXBOmogLOEOQmRXJlQaImvutVoe87MpaUhvHw9PoUuugtNS6VGC28fX0qpYihraTTu3dPP/1ku7ilZEN4/vp0d3cX+jjnOXo/z1cFZ9XO1ysRWYNNBQoaF0qrzqiNXgBIeL1sw2E0wdtpuG2rMzFfZmgNgv/569fvP3/y3tvT6JwNXWg1s0BrzISqOl+vxmLi7MeBUkpbSt92QkSiTAYb19pa5ny9Xmut1nhR2coWOu86V7iVUgw5MoaZn17ftlQut5mZ1/nW+TDPN0Q0xnCTYRj3lqiUTAAGURCWZd6b+nVdEdF7P4xDraXrBmNM4xxjx9yIyADurWvJJcZunpfYRa4VWLyxDlBattbOt1vatuB88NZ5Z4zZSjHe7c3d2I8xRkRclwUR9zF+Tnld5pZLzqkpL2lW5n2gkXOajpNzXhFbbU9PX4nIOI9Iqtrvc+nbjUt13gFAS8UHT4DWWhU05K2z1tl9ZheCN5ZCjMa5mjMppGXToau1VuZgbNlycI6IQgzG2P2O2lvJrutC7JwxpWzG29JaZbbB55SlNlQ1iNwqOWuDZ2YSsT7olmpO0zSFoU/bmlM2ZLhVUrZE3vi2leQMGkMs6FzwruTMuW6vbw+PDy7ExlxrXefZeleFr6+XzvdrriFEIpy3xRJt12WcjmlZ0YH3TrQty6zavj79ogzWekcGVWOMD3dnYTbW1FpuT18H5376889fvnwZhuH69vr8/NwqD13XWlVlZs7bysyWjDOGamXm5pxvpRIRku7Z2zkahqHrAyJuKZ2P98xsLHV9GKeBCOLQq6Aieu9fLzc1bpnXGPz15fnh/rytVxFRtE3ler22nLuutwZUtZQMKPulcHc8365XZgZBLmyNT1uqrZS6hRiYeR8vlJKNNY05dtH7wNycMSSSt9UhAYCIAgCg1FpFBABs8IfTaZ7nWisizvNNRG3w+2p0/+IigiDedUAmxg6kWkfLPO/DqTUv4zTZ4E/nO0DctlVqtWhUlbkBi7V2XVZu3PVdrVVVlQEAQFF1X6iCqmpNHmkcpyaiwmlbQcTEcLld7x8fvLVdCMJKZJqIAogIKRBSK6UxE1Hw1jnP3L5NLg1ZZ5EAFLlUEE6lWOuMMT7YMPQEQD7UnJXAGjLWpLR1Xd+FuK0rsa6Xeb5duxj2ugiasKh1ziD++U9/Gk9H632Mse867/26rtIYFIfx4K01xhARggGR58ubd9QN3bLMLOJ9dNbsLdey5fV2/frl59aacK05Oeecd7otZV5KStYYq1BzIUBVzWkzyhbVWutdl9fV7fst5pZzBtUQutaaCnrvK5fKXGvd13rWWiH0LvZDH0J0xjVga/xl3Z5eX0spnz9/Xpa5qqQt/ea3P64pPTw+VGFC01o7TpMy57SltAXrowvWOkLDXK/XCyIKMyJaa2stVRjI9MOY0mZQt23bj5SqMjM5u+/0UVVVLZltXrYlW+ONIS61ltpqU8FhHEvKwZucFmPREqkKAoHBbhqKSjyM1+ttXZd9+k1Ezvmckw9+HA4KjIipZu8DSxNS54OzVFtWFQGYDgcXg+u7vWRcUmrCxiIRNS4pJRdsP00ist7m68uLQbTWOedKZkR0TR4+fLi+vJbWasotlxgj7aFARK3V4Bxag2heX19UmyUUEYNUc7YKAKCqxrsQfSCzbCs5p4Rq0U8jWreua87JWhtCDM7V1lwIKee3t7dx6I6K6bawgiVy3vvg15LRmDHGy+WSczbGdLFfUyKiYRh9jFtaU15aawAgwoh4GKcQwvPTkwvucDwcj3evz6/jOLRSjscjKBlrc2ultG1emXk8naIPTiF6Z5FKziDqjPGeakvCfLvNzrnT6SQC3tjW2t+6+L/FX3XQtm2qWltlbsxSSkMw1pKCtFYJwCIxswWcxlEFbsvttizOeyXMOQsCqqCy80aA+kM/z3PlBvyt+tzXTvsgkxFLyc45Iuy6npn3Ncy6bvt/IINdN0jDvSYWkb7rjDHef7tWdiALMJfWAKDVFvqOmUHVOceFvXEGDChut1k4Rx9yyTVnBfbBKYgihq4XxPPd/edf/dB1PbPUWgCgtUpoHbl1XdK8jONkjL1dryVX59w4jgqszPtqd8sJvR+PR3Rm2bbpeNhKTnllqYDy7v3DMIzC4JzvosdWt9uqjRnBBCcM8zyv6+qck9ZUEdFs60IGiEhESs4IBlhKKYjoQ9xziRRRbq2kmhIaY4MHdGvaypycMTknEUnrOm8bihAigCKSCLfWciuX9YrE02Fk4a3U0HeqytLQmjj0d58/2cNYcwneS2vzPOdtG4YBRde0bGmV1gBAVfbGtGrzRLmw5qoq67JuOVv0t+sqwku6CeHp/k4QlnWNMYLxb/Pydl3Xden7fltmFB37HgDm5QoiwuCMRzRNxBg7zzfvPfnY55xVdUsJiNKWS8mxi4bIWruvQGMI3vtxGpk5b8X6uNZyW9c49N771r6Vfc654/19Shsa//r6wlz7ELkUFpyOpxCdtRYM1VJyTpXVOFtLNdaGEIxFhfbttrVOBVXVWdtaa7XuMyMiAgAQ2VcgCAYM5lL273O+LqoISt/qgVpRtJQ8jQfm1loT4WVZ+2FQQ4Lwcrs2EQEwhkKIRORCb5Baq6A8DYflei0l98PArcYYc97Slsh9+/pFxTh3W2ZV9V1szB8eH4ZxAlBE5Fq3bc2teGvJ2XnZuq4ziE0kTpMzRqNv68bMnoxw5dpU1VtXShbmVluIXc01pc17z63G2NVanXdSCzYmb5ct7w+VIe+sRWus64jl+vwy9dEDMDdjsdZCZFQViAQAnenGDp3hu8O1FgAAIuYirRVuTNpa265XaTIM4+12cyGE6FkaABBByqXvB0TItRwe7vKarXXeR2N8CPH69tYNU+XmvFtLSrUWgcPh8PDwYBCt99PxGMbhcDptZSOAtK6lZAGYpkOMcV6X4/l+n0ICUSlNVenydqmNt3VjZkAF3MdPxlp7d3c+DuM09kP0Pphh6vqha5XnbTYhbpyrNAAw5Fpr1kYp/NNPf9k/HQBaa42riohIFU5pAwBSyCXbEGrj8XgUBEQkCwrAIIhYWlPgNW8xdrfL8h+pVFgMUcsFUPbSnhuX1ABAgbu+c84BiGgTbQBCiHvjn1NpVUIIqhpDeHp5ybUej6e+71WwtaaqeVtLyaWxCDtjQ4jbbUFGi9Ygdl2/3mYRIW8AYIfYxa5vzI+P76LzqFpKnm+3WisASmnLMqc1G2OW+VoA3334sOaU07osSz8MrTXJxRnjjFFmkW+vK8KEiIgxdmnLRHS+e4eIvOXlclOk0PX7G4LGHMaxteatA8DY90QEwoT28fMHKWVZZmuttNYPXW3ijQ0hUtPORa4lp/z9D9+JSD9Nto8uRmeprHPv/DzPIcTWWirFG3u93rZlMUjHaRKB8XAQbbHzZJHQpFw7H6a707ouINj3vUj94ccf1y29e/fucDyN46FsiVtR4dZabeV8PotIFRjHiZmlNmttWlaDaAy4Lrw8/fKXX34ma/vY3243+vL8lHMWERFJ2zoOw373O+8OwyHE8PB4f/9w3/lAoCJio+/6iESi2lrbti1Xvi2rEhqi+8d3rQqXxizM7KyNLjjnWmveOGkthGhDICJrXc6ptZZTVlXnLasacsYYJN337865ltoOWwSAlqoxxhjDpRokYSZEZkYF4WasU1Ui9N7uANJuGl8urzH2XRwAHSCy1Lv7U64VANYlERFLYSnRhVrYWNv5CAB5WY0xO3RLRKKLiAhS91O+g5J2TNMvP/0lr1urZer7l6evlSWGQRWliLW2teadVWNiPyC5GLvD4aCqJSWbMiJKbYXZGLtn5ZxT1/XMrbbGLNZ4a+1Pf/6LJbLOnu4f1BAAhM4nbq0yKQDAEPs5baW11tp12wrhervZvt8xU2va0JjWpOY0xC6n9Pb2Ok2HP/y//t9BgYJfU+Kav/7lp2Ds/PLy8fOnLoQd0dx1HRHlnKS22+WGxggCAGzLTAbnt2U8Hq6vr5mrNW7bVuFiQ0BjiKg18V1Mpbac1/XS6rYtN2Pw7e21pOxCzFt2ZIfpSMaqIFmnBm7bNZfinHPOgchxnP7WJP0t/qqDrA/zlkspwhJ9tETGmKrMCq3V0+k4jof37+6P0+iAWmsk4Fy/l9/Cam0cz13XRwOIiNe3V63ctgspBMDb61MVbTURYZOsgrd5k8I15ZbnuibnnGhrpdYsLVeBYqA1huPd6SoCrbCDnJrrg4ukWKExgffBKwiAOGcsGbKmtgLI3EBEawYgJCJA6wS5NAYl70LoffCS8xAcq/pgQRswKPO8bq02RC4lEzZCAUDy9vb6Bopvb69QCqiRhtZ1jUlVVFEKa+IYHAraoT+/fw8AQtwfBhMDOgLr0UVS/vr0E9b2Ns8GUbFN7+8K17en55TyMs81Jx/jvlYFBhERbiKSUkJmAkDCBvV6e6vzm+96Zg7ouVRWLHXNZYvDYAQR0QNCUYh9JMMshdk6wznbPnIujK6WZkxPmatW6uO6bIdxqkX6rjtNp7c5XZfr9eXl/PjQR/fy/KUPMbjoYhectdaOYeCmhLZVdjGIiLE235bH7z+T97WJC9Pl+QuhydcXADlOExFpEqVvkMwA0rBBKW7ojCVVXea51dZys2Cc4H/5x//e+bAtSzj0z8+/0LIsCNRaE4Y9tfrgDZDUiojruhgFFTDGKOLepqzruiyzMaZx7bpQarXOGWNqa873AGCNIesVCdAqiHM2pURg99rUWgcAhAgAZJFbQ8RlXpy3Utv+IXbxcD5V5mgCAozjQQXYOAFqJZWSQogAkFLywTcRQ5ZLDdHv8//W2t72xrHf0mId1patJVbd1o1L5lpLSlwqKhjnYuxi11lrAaW0lmsFi+1bD2H62OVUtpK4ZUJGaCyNlEvaULWW1sWwMyIM4Hq9zbdb9KHzHXJdl8UYDwBcizP49vJS1wwicRyJqOv6YegVsdYS4iiApZR9xDtNh1rLfL31fQdEOXPJNfbDXjQDkapa64yxtVQRASJEHPqOgje1bagqMk4jigJALdlbW0uy1pVlfvn6dDyejTGtNi615LKVVlXef/pUFQVAa7u9XWLsvn79Yq0FgC3nmrfn56eck6r6OHjvc605p8Ph8PXL0zQM3ofL24uIqKLzblnT9Xr1xlpyqtr3wzJv87pEF7Zts9Zyk5wTcwOAnFNrwqp/+rc/X69XAJgOZxEia7xzDgCZRXfCUatcZScrWuNTzvO25crLuoEiAihzCFFBAGVeLzv+fFlmREXnm+g3tJ/xqTQlaa0ZciqESP3QO+eUW8lFRLjx0HXA4pxLKQmzlHY6H9ecuhC6h0fnQ5yGIvJyW99//9stV2XxwZM1vgshhHVZRcQ7exhiKck6qyD7/glEvA+H47Clxdu9prQ+xLzkNM9cSi05OO+cbyKh6/K2VubWauiHkrMlcmRbayktrbZxnBSxtQbC3lgpzRvX9V1rreRiwQzjkNNmrDGA2zynZWmpGGusj8N4dM73wZ+m4e3L17wmdG46HJirDxHJobGlVQVjLAKA94FrG8Z+S3M/TmxoHMau6wtXaAJNRNvejO4cvbRttAPqRIBFWewYyUJOGzN7H6Q1YDFIPtgI2MUYh4EFh3EUkWHsybu11IcPj84FcmG53a63a2vt7u7+7e1NagWA4H0/dIbUOc+q13kmALIuhHA8Hm+3q6oexsFZp6pl49GHOHTobEobEdWc9nGeMBNA3ra+742xIYR+GAzZh4fHw929IbJEwzA8v77FYaQ936Clfui2Le3ARxXpui7n7MiUkpdlTikZY0utZGjog3MOBaZp8t6jMbHv+65H0VKKH/t521gVjOn7DkRaq4dhMsbuS9R1u6VSyJHzTlRTrYxARJ0PwoLOLGnTUl+/Pp2/+9zf39th0K7/8e//voLuKVyUcq0ECKjT1BPAcr0dpsP9u0dujMaAEgC0nJdlhm99t1nXRVprTQUgp3YYT2S8oCiAtZZbLqWActd3XAUAEMxOVWu1GWOY1fm+ibTCW8lh6OfbrdW2sz1z2vK6GktkoD+MggJK1pH3YV43BarMKW3buh7GodYChLfbrbWaaiGCEB0A5Fr386SqtdaUtpJyztmE/u7xsVYupQEKIgmAKpeSEYxzPsSYa3HOg3PXn3+hzlkFFslb2QHOSM77sC3XlLamjTzVJmtK1ruSS63l8d2H27K8Xa8xRiXUxr/+/sfGervdjqeTtW5Zlm1b87buSIZ9mFBrJaJ//eMflVmkqVQCEWERSake7u+1saR8PJ9LqetW+3Hq+glVpVVn/Y7E2CEH3HhetpRrrbW1ymUH5BOJsIKUWtdlVYV127ZtRcQudqfTGRFvl3nZ0rwtqVRV5cYWkIS6OLw8v+7PcUqp1trShmAO5wc3DoIgWmPfGfKo2lrLeau11Jac833fW2tZWQBMF3wf1WApBRCtc8Zaa60wvF6vPvjYddPpoIitbtYbZkbjgIUMKtcYQ/T20+dPv/79b733ZL3zrokS0XqbAYCcNcZu62bQtVR83/muU1VWERHmts/bmFvnozVOKjtrrHNcq4/2dH8gQ02ZW3OxI7Q2emtcFfa9r1JLa6W1aRgABcGQ20eSVhC+AQJDEEOu92BQCdOW+n4QkfP5DACq0louaVXloQ/rsrRW9xVlY0bRdVlcDPM8xxi9DwRAhiwRM4s2BNNabZxjF4io5Twa23Udb2kYDjEONYki3j8+NmVylkXC8VBBg+9Od3chhGEciWhL6+E4ASICTKfTcBgvlwuDWmtLa0R0d3fnyNdSQwzrsgzD8HB31/f9eDz0Xd9y2QdkKW9dHLu+G7vu5z/+a0ppbfW2bePpHLqghD7GlLahG5ZlqaUsy9J1XS5b6PtUszEmxjiOkyiDyK9+9f3fuvi/xV912CYNTWedS7XsXA5m9sHv5cLbvKaUAg45bwYrRcMiQohIzHo6nSuXVoq1fl1uFkhElm1rCmgAAFXEkhWit8uzMSa6zqAgQejHX/78kzOmmwZG0lJD8LWpiKIxzpoCUFLpRamyBXz9+YtsKXbBEoh3yvV8Pj0cJ344e+/Px/PQ9//6538zhlS01s2RNUan0/ntdpvnxRCFENOWCSAEL4QPIeScjXNpTcNw2LbVgGiru7qGIQeEilhLIclx6HmZW6ultFqrsxENIJKL0fuQ0jc4i7dxHKZ5uYmIc06dJZTrbemCG/oBxGzzdWfktSpbWUM3dF2/bStYLDkbYuuiDR4Run6QpsMwLltGVa5ZRIyg9zHprTG46O3YNVFVba36aKVVUQKWqnp7eXn89OnLn38uW4pd34/99Xqd180F2/eDElqVebmehkPOOed0e5s/fD+ggiHiraizpZQYu9GMFvTtevFqsLXQdXmd9+ORt+32dh2GoYAaRNFvnNVaC6lVZeedGbp1XU+Hw1t5I6KUcjaqqQ3O5brF0BEQc7vdrkgKaN99+Aiqt/l66HoT49eX5//1L/9CoRtEgdAA2OsybynnrfjgVHW+Luu6vP/03fn+fpzGbgjMbIzp+vHh7sRc87oRYslNagOkJqJSLZExHsEaImOMQRj7jgD6flBo1hprrXGun0YbfK4VGzNzrrUfelYtpUBrNdXxcIjWKPM09HfHkyN9/fJLLdXF+OvvPnbO9H14d3//w3efP31+f3d/RMRStuDo/uEUA+Wcr5eLtdh1fez6bVsJIMZ+vlyCc6+vr865UkoXO2Y2aAygQTQusqBoy9ss2gAgLUmNWkfOGGUJzoE0EUHhljNaE8axOxyut1fv/fXttbV6e337Ri1KpY/BKN8ur1++frHW7+OFt5cXaA1Ua63CzE1jjPscZj/rSGCtJSJvrXXWIViiWra9+WNFVHXOA6hoc8HkZXNkl23jQOP9aVu35+dnkeqjVZW8JeYSnHXO7Ss9bs0BXi8vqrquW+/D/PqyXl+3edm2rbWS1uV2u5G1XJuIKAEA5JzJWAUjIpfnF2st1/ot0e2ti+o4TtY6Zl6X9fb0bA08Xy/TNKV1Hcfxw+P7d+8eBIBon+fsMjAgquQ9i5QttdZCdFzbaTqUWsjZAACpttoEwexb75S2kmspxRizz57I2daaiu4s5HWdmbm21Frtu67kHGMsDIhIgISGue0r4L7zQ9d1XVdLi7Hrgm8iZKwgxH4QEUsktQ3DWFodxymn/PXPf5EtSWvLsjSCrbWlbi8vLyEGH7xz7t3d8bvPHx7v7x8e7qdp9MEi6dB3g3fB04f7u9PhgIZ2bLIg1FpDiFKLqpa8SePDMLXW+hi3Zc7pmw6MiLzNS4jRB3c8T74P0+lsyLKwqjrnVApoayUTAbEQABFSsLU1AKipWKS0bCGG+e2yn7A9qxjE6By3ZoxpmR0Zh7TzNGqpRLZVdtZvuTjnc8rGmHW7pZZqyeu2pG3NORlj9xmTAKRlvVyv+o2ILNbZxqXror07oTVxmLhwjEFBkCTlxVkHAMp6mE5ty8TCbVe8CdN46PrOWROsBZHYBW3MtRljFICZD4ejqtScRLTzkYjO9w+HqfsGijAGAJSFm5Axxpjr7bqsC5J+/uGzI2MA87aVtKVl/fLll2VZWBo6yjmL8LalaTqgNTYGEUnb1vX9vK615dB1fdcToJAJJbfC0kC6aTLkaoZlXkLn1y1fb6/WWhRtrXAtzG2br4TWACpaAKylhTBsWw6jl5yX+Y0MEmKtJXrrwcUu9N30/Yf7Hz99jD6GEBqX0LvLdYl+rNJc55e6mO40nE/GGmMMOgJp0ce01evL7RC7cDyAIQV7N4xF2t39g5LZatm3f2mr93d37x/f/aff/NoC3p1HHwicOucsAirlVMfToXK1LjTQMAZr0FlCEWet0da2DUBHo84bsP5tZUOh1oIhcBUQyTmJsEGvQBbJGCO1zq+vTiC/Xe4e3jNWBplOx1qatfb561c/jmvN0ppxjhGt88Jw9/HRjYMol7RN08ENQZjJ+NZaF93tdgtDt63JkB+6Y7VWVWvlzvciXNPMwYfOAhpS1CoIbUlpvHuQrNF6B/jl9SWMnbSMRCIAACzQWjXO3T885m15+PiBQQnAGPP2+iSkIGKsN8OwzhfbRePD48eP0zQBN993pOh9PN8/OGdLKa215XZbt9q4OOdEuCgDinEAINfbFj2N53P/8dOltlb1dByT8Hi6A6LR+7Kud3ePWrgBbltCbq3V/ngXrZ+39Xh/R6LbvBkfv7y+ne7u/9Yk/S3+qoNAaUtFyayl1MJEdDidQoyAuKYCZJnBEMUwDNOkqtPhAACt5WkYgjOBDKAaAmNMzjX2U/B9S1VVvXFdCIYwBueMkQa+64x3yzKzgjX+N9/98LvvvnNkUMASHcchrfm7736wwR/H6ePjI4hMx0N/mF4ul4d374GltnI6H2Lsfv7l53lZnp6en59e5+u6ExTv7+8+f/70/Q/f/e53v304nQgUCVVxPEwxRuec7zskTSnlnEOMt/nWT4dSsqqKqLD4rt/WVRD6riMFAlDhOI4U/N4EqKp1dgf7GGvJ0NPXr9e0vb6+TOOJAGotYMgENwyDtfZ0/8hV65oCeVJJpYSus47A2Oe3S1MxgD7EWosPLq1rFzwzi1QQJoAYQ9fF4EMrVVpT1ej9sqzOGlUlQ4ZssC6V4vtuXRYB+PT5c611GIdWGQRFhAAfHh5ba8ttfXr68vL0JQTPW/7l+enw8IC1tdryuqGqIQKWvusKNyAqpdac5+W6q54YY2indBhjvZ2mw8vz0zcFFCJQ4ibRmcpMNmy5GGP90H15ejmfz4hwPBzSuiHjtm2qcn6464ZOVYNzOed1Xadp2iHCh8OhlXI8HL58+ULLmnKrQnbJJfS9j72QYTSuG8n408N9rvV6vV4uF0ScTiciGodp6nsQuZsmZd5VQq3Bw3T39fVtTUma7qUtiDRsxpgpdofDdJyOtdbf/vrXTvBumH7z/Q/v7++mfmLm3oX3p7MBvF2X0PcPp8P9NL27v6+13a5veVtFAJHSllLatpSfvj7N60LWfvn6pKq3261w6wZ//3g+3I3D1H3+7mOrrbGIyM8//4UM5FaN9+SsD9Z3sQo3lVR56PpauJ8mtFaEjXciLK2qyjaved2M9d14LI0ZtIkY73bKURPp+ul8d//4/n2Mw7ps3rq0lRCi9QFJSilbq8eH+8o8jqOoEUNrSjmnME3nD++LiAtd4RpClMZSmyPjfQAAJM1527eaXQh1nVG05QIs3iI39sE3lVYbALTWjDEgrRuHZVmMMaUUEOyc58zW2i+/fCWimvMQozDfLlfswqf3Hy5PT2EcQwykxE1V8O3rEzNb4wDAOZdzdsbt8kHzckGLwzDO63K8f7jdrg+Pdzv7plXZ6dqGRMmGrldmIGJD7z99UsHnl2dE9K4bpynnFGO3bVtlRmPW+eK9N851PsQu1tqkNeccCDtDFPqY0rbOVxDJpd2WBQwZGxSNkJm33ABqS9N0GIbR+5By67tx58hvKXlj4xjRYD8M1vvD+Q7JTNPECMuWui4+3t1bNMcpDl1HBmtr33/49I+//vX/8Q//Wermo//h++9DCMfDwZFBYETs+z44d5ym6TDlWi5fn7S25XJtRT5//NSPnbUudgOheX1+E5aXyzW1qqrbugHh/qynUvp+sCFs8zYOw+X6ltcVVLGy0Z27Vw7TeWcj+RBUEBGBDACISKtt2xbnHbCgqiKGEEkRVYEFRfvDKLDLpraS1lrL7bqgMcZQa/V2uczzrMxd1yVQ2/dZmBEOp8OWU9f1a0rj6YiGKvNO+yslO4s7VARFrXWtNbI2hLjlvN93pTREdN6hAVUFIali0aLqMl8tUb3OvGuttGqt1dYU2DlPZAyYsm3GmGEYY99Vlev1NadshvHt9UrOXq8XY8ztemulkDG5FOu9QXIWfQg7NrK0mvISQiyNYz8sy5zXNVivqt51qpK2jMZW5i7469tbHHphLevWO/t2eSZj19uNWbdtTestdh4MEBECrOt6u93ysg3DMM+36/Wy3a7TMNjW2jAMx9jdbnNVdc49vV6HYSJxvbcs7Ajv709d17+8vh0OBzIeWAXo7uFhXZfWSs7JBq8Ch/Hw69/99qc//Vm4WgADSETjOBkWb+Du4/vX57e/++3vPNGHX39/mKZgXejjWnIf46ePHx2FvC0/fP6eLEzjFLv48od/27atHzsw4Jwr0n741XcW2nQ4/fMf/5BzLrXmUqxFBenH8T/95rfrsnaxb62tqZjQBwXWTbkehlG5tW0DkXS7oXfjdMi5tFKqLMfusG0rotmnv0poo5UKzgdv6fL8TN4PIUrOqtpKBREwxKBbSTs+NYTu3YfzfHl2zq3zAiwhOKkpLcgIMcZaM3PztpOSrbVYcs55PBxaytyyCBtSzgwkjGQQa81F2JJVgNs8v3/37vL1yRqTUyaLwDCX9e78kHRBxJaztgbC9XYzzlPw4nzjQig+7HByW3MiAtZdeho7YzPo51//cH29Prx/fL28DR/fty05Q//rX/7w/vvvAAAB9twJFPp+EA2VKzR20W+1YqshRFFN29ZadcYaZ1nN44f3v/zlpzH6aP1yvQ2hk1IMUQhhyzl4JyrB9x5lu82qOqcELy/D8agitZRtWfp+sGRut+t2m6lx6aLLKb2/v/PBrSkByrrO1lrmJswxdqra9RERrTHee+dtP06Jq1pTmiIY55wKLtt2uVyWkofjMfSDcSGEYMF45w5T9/7h/tPHj+MwEGA/Dcab9+8eemss0n/9x398/+Gx78M0HZDgdDgbY0ouxmgfXBZG5xrzb37767St4zCuKb1/92FO2y48Jiwl1RBiZdlybVXGbjrfncM0smofu1orAez8GwAgFktmXRZvnfchOp/LisDSChFxU1Iwxoa+L60KgDNm7PptmWHn9YsYa76NhLv++nqxRMuyXC8vVZiIui4SUfCOAMp6cwotbzG4sq3e+2EYaq2WTIxxW+daq/eh1krorLMqyjU3LjlvxhjnfCnZOdtAxe7SerbkAoZOd3fLugJAjCE4szP065Z3tZi0pVpLleZ9QJLb7XZbVvIWlK6XuesPTaSfprQtxDXnVFubDgewjoi+//x5n2GP42itNcY4b0GkleytV9V+HL33PkbnvYggwk7nzzkZ665vL8GbdV2YK6m+fPkZlINz0pr3PsbQDSMzR98tl7mL/fn+fuj6XeMkretOH9pyqqW+vb39rYv/W/xVBzljLq8vAPByuQxdZ7wLIfrgGmdU7UJsuTrrW2ufP31UVeeNAhMaBOIm0+mAiK3ytycgJVH4+nZtVRTp3fldH62I3J1PFu00DSGG+8d7YzGGbu8HPzzcfXr34Mm01n71/feISGiMQiml86FuqxGVUgC47+PnT5/7bnh5eT4cjt/WB1y3bau1zrf5X//059v1tk+PDSFY3dpKzhzP901ESRURvCVnS8nKTbTt8g21VAAw1ohIiLHVJrWmtImIckNjt2375hiBqgRkbd8Pqrpt6/F4QO+mwwiowboYOzTm/HCvQK01BOCaass7QG5b1prLzuzbSi4paUp5Xb1zzA2AmogxRhB88LVl5RZj13V9E4mxc95tudy/e6eCtZbD+aTKl8tr2ZIL0Q2d7SN5f1vTeDizMnqXalbVfuyGqSOiEL2z8PL8Bay9vL5ut9vtel0u17vj6XK5GGd856y10zC0VrjWlLMAWDK7Isbl7U0Fvzw9revqu5hzDWGn3fpaq7UWCaRkQWXra60WDUhr3HKt25aklpxTjHGcDmvaQgwG8XK5bsu8LMv17bUPcYi7PgP003j//h093t199+kHa23K+fXtKeXl4e6ODD7eP0z9GL3rfJdzK6UAS3T+m26Htd4HH4KIHMbJAJKiRRJW6yKjsdb+7te/zaX8+lc/fP/DD33XA+Btnh/fv1/y9ni8q6W44F0/PN4/BOO6sIuQ9dY4bnq9XZd1fff48PHx8f35fnDucRwPxwlQhXVd1nXbbrfrX37+c1NBxFzKtm65bErKUqW1d+fTy+UlDDGVtbZGJjBz4TaczzszzfuwbSsZEJHgHSG0UtZ1KyUDEIiQAjd2zvXHsZRMqIIgAGqwcNu2Zcf+1VKrsKpKbco8z7eSy7wuTaU0doZCiDa4jdt4GPddpYj4GLz3x+ngjVXWVndWmNjojTEhBAbddaJ39m039jknADBE6/5dlsrMSui8ayKl5KLSHY82BhcikPEuNGYVUNVdviHVPF/ehLkLrt42Fjg8PIS+G7v+9eUrt9Z1nar+/MtPr6+vADDPs3NeBa+XSz9Ea523npmdcw/39znnlMs835ZlVmYAIDI5J9XqrL97/6FxK1tSZRMjc+tDZ0hut3nZtpxzLm0aj8ttttbV2sZx3NV7/x235eM4ltbIa2cpdv0hdtM4PhD7p+c3ZXq7zN3YPzye1YiiSNPMrbVmFaZxQCN9DNZYAArRd50ng4Vb5qrAKKWU8v15ZGzT6fTd54f33/3Yje7+cByd++HT56bQ9T0A9F1kqdM4Dn3/+HjuvCOiUmvhZhV65+8fTz/8+Pk//d3f3Z3vXi+LFC4pne8Ov/zyl+DcGKKqfFvPrisCzWsuTUQx2PD37z+7zMTYOztEa8B0xhsFQQxDX5mdsd4aEUDySBR7P8agrRKI1MaNa04EsFzmEENuGaWAYm97hwCFpYgjsd7EOKCit7bkAsLGGsgZSiu5xel8LaU1sGirJUHxwVWpYJBAMzeNTlEFtNUWnNntKFoVEeycX7T5PuRWr5dbKbWpREe8bJ23vbWXtxfvoyPrp065QSpSRWvrusgtjdNIRKJKoPP12lr1xpngDvd3jcV7PN3dXb8+ezQpr/E4vb8/t5SHu3d394+DMVTyMAzGmNhHMmRdZG4hxH6cjOo8zwjknR29J7tLv4gwcCvznLhWq+KMN94SEXHr+omBUxFr3PLyVMoag3u6fI2xN8YcP36sW/bWsrEGdF1nVlWFlis1aa3VfddMiodhGvseVZ0xZct//tPPt2Xect3xs8aYaRoJ4DAM3to+RoMuxm4Yxg/v3hMhACDtOcmwQmV5fn5BxKHvnXOnu0M/9Pf3D12IYz+Mw2CNGYbhfH+U2tbbfDhN7989EtHn9x9ZauxD8MEA9iGejqfOh3lZDufT1I+n4/nx4eG//Jf/LYb+8cN7Va2t5ZzTuhBRUx7G4Xg8lZqtgcZlT/yNKzM/Pr4jopQ21l0GmxUaANRaEQEA9ns/5eyszevGXJibdxEArDOFc6kNrRERQ25Za86riGQWa523FgAQSFWPx0Na10M/Ruu0tuB8CCGlZIyRymnZgCEt686pQMQmwqUCgKpa49ZUDsdT8B0zH/r+0HWaq+4OOs4gYnAWUHKp3nesaoO/XV7WnF7fnvuhe3l5brWSqiqQoXXNtdSSWxMdjqdW29B1b1+f19sNrWfB55eL9z7GqM6mlAy5UgoCiIB1dLlcnO9TXrjW2+1GANM0GedSzcyMpI2LQkPET58+bdv69vzy4cMHFwMYm69Lay3VFpCMQedsK6mWDRGFQFW99/O6hhC8tY1ZBBDRAH7jaf0t/hZ/tUHGO7IOje1i7GIcYjz1Yxd7VH04n4nodlvm+UZEwmyt6bv+44dPj+fH+8PBG+ut7UN3HKcQwjiOiOjIROeNxXnbrPHbmvq+X9bVGSeqXR9FZJoma+04jIh4vjsToXXkg+9CPB0OzNkg/u7Xv3HORedP08TM58P0m1/98OHjO+a2Lte+Hz58+DTG/lfffR98t/77yKmLw9PT82W+orV9303ToeZ0Pp1K3ZiZrCVjXl5eQHVHGzGL9YaliTZWBgBjTRNBY7rgLBGKOkAEMOSQtXFBhCqybalInZf1Nz/+3XJdUtpC7FSVFIeu7/pOAMahswahldcvXzXXbU0tN1A035B7fheFBNVpmHY/Ie/DjmZS1fF49iGiMcG62+srp7wLPQCRGkJEi1S3TN52XRdjF7peVYdhAJHb2xs5a9F0vjfGOBuj96AkDEh+y8U6++f/9a+9s84YCuH+8ZFZ5nmprYzjqKqNZVfGzFvy1u3bKVQRrXuperm+sVQfuxi7VLKPHaA6H7789ItFaml5+tOfOGVofLg7l1JOxyNLQ0Jooqqt5K6LoYsAoATDNAhKLmmYDpUbM6e8jeNEjdWQBUVjQ/Ax+Oicuz+dPpwf+jg83L1rVUqqIrKvv+bbbV8jjeP0/vHhu08fhxCjC1wrsKLiNEzB++MwAsAQY+W2Lul4OOwiCMH7nTja971z7jAdnHXOuRjj/fF8GvvOWlQhgONhRGXv7OE09X2Mwe/S8bteOoGMfQRUEf765cs4ToCmliq1gaKSXudbDMGROR2Ows15FzuPiKLcuKQtxdiJSOW2X8eE1ruApMaYfhiRkBRqrYT4Hyo61lnnHKB0XeynoeuiIWtsjHFgltZyiH6Zl5enr2/Xmwnuj//6r845FbHGeN8RWUSchmHXRnXBl1JciOgcM5dtcZZaqyFGIjJEqeZlnYUrArx9fa615lpZ1QSnqlU4p4yIRLhLYzC3u7v7ZVmiD6A6ne6ttaXkXGvJWVVDjO/evXPOnQ5HS+QU0JrXeUZL13lG0Sl2b5fL9vbahEMIqDLPM7Cyqvd+hwcASylZRKSVtCy369XbUMquTV2Z2/F0AlVDVPMKIkbwbZ1JdP7ylUkJwFhTUyYi5raULABkbdd1oevW201EuhBBeVvm03GyRAaN92rJ0LLOhAoAzPU4jtzEkP3Hf/gHUjgMfl7WktrpfI6+u6QrMzvnmxQC28UwjoPxoe+HLdVguzF0hHo8DCLSD6O1lsDsbg3TdCBS1zlV3c0V5vWyzLcY+vPx4Mj8w9/9vguRiKy1w2iZ2XtvrVVmNGZ49+7x4WHZ1uM0vT4/N66lFG99A315egLWhw/vnp4vwYen56dlmb11KW+lVSJTckr1pR/GtG4xduuyHKapcSY0goqC27r5YeTWLJGK+C5KbahYS7HWqgju1iXW55SdtwBwvV6n42lZ3tK6uKFHS4EwV4nD+D7El9fXGIOxrrTm+66UDNYSgFpkaammMXZ26H76X3+KSNq4qaCxIhJjx85Ka2lZjCIYROdIdZfiDsaVunlrjXfrtgXvW221lnnLYmwrhNzGGK6t9b7nWtAq5wZODuH4y9evWItlJiI/xOMwBO8Tawzu7flr7Psvf/mp7zp79q1m5yw35QbruipXUE05VzQRNK3L8XBc12VZ5of7d68vLz46BVDVbUsgcnz/jpx33SCSum7QtDKAirKy824nBo7H+7evT49dZNF5WX3wW1qis6pSc/3DH/5A3netsO5iocaIKgB450KIft8TAIUYp8P5fP9wPN+FEFIqXdcZY7gWRHTGGMSSC7IYwOi9I1JWURRmNJ65MfOOZt3nKbuJ4C6FHEKYhqP34e58mvrh8f7u++8/3T+ep8OUcw7Wh+ClNQJtrbaSb2+v59PRWTgdh1/9+H3Xd7mU1GrayrZt949367p8eX7++csvOedWynGatm2ttZKSIRyG0Tm3S76Hzm+3+ZuTbRMRdV0wZFW0Nt5l9xSoVvXeg7ZaqjYBJVUttW7LWrmOU//3//BffIhj3+Wc42ECi+M4qIHD4dB1QxwG6wNZN69X691/qPqUUkIIAMCqrTXrTYPm/Tdvp1KyaHPG9HFYtnR+uANLDLqlpJXrsgbraq055dra9XazQ3De9X0/9IMztj8eU0o2BHKkqlwqIgLRsiwlbcFbBrXRp1ZTqyltxqJIQ2WrHIdwPIwvL8+7YFs/dF3X1VpabYoY+g4MGWO4iIiE2OUtWWv7YUCwwjzPt3EcfAzWWktUSvJkS6tm6K2CqhpjBXAYJml6Ot0dH+5fvj6VVFQ1dB2RqbXc5mvXdXcPD39rkv4Wf9VBzJxLrrWsOccQdt0tR4aImkoIUQVSLm+XW96aNf717a211sU49T2owC6YY13atuMQYvSWIMbYdR0YAiXn3FbydV289x/efdrVLHY9ZUS0zjrvuq7/3a9/8/2nj8M0He/OD/cP0zR2fd930zR2D6dT3/l1XmKMy7y8f//+7XLxzg5918cYfAzBvXv3CEifP/1wu96u8xz78evz6/l81/cDi6hA3w8tF0v0TStP2BhLREAqtYgygFprnQ05ZWdM1/e11OPjQ2pVtOVaQck6a41HJERwaJ21MZh//dd/+Z//83+EvqtNrbV3j++Mc/Oa1nVJKRmkWisF72K0hGgJAIJzIrJv5NO6lpTuH+6MczZGVvWxA0RGEMW05VYldrHrBwAghcNhQsKdzeK7qKqeLAY73t2Jodu6EEDKSQAsUT+Ot+XaWvHBn8/HVhuoTlPPzBStIKJ3IThENDaQ9caYy8tll3qMQz/PNwF9e3vxhJbI+KDGNkWy7rYtp7s7FiHrx8Oh1FRKBmRjjA/94XhXi2zX6+35uet6ZwyrllZ3k0gwZL2/zev7958AwFp/PJ5KSofzaaslxgiIwQcByakQog5j34/9+e4UY7REzpJ1Nre6rCs3bqDknAAq0pZL8L0CgcjYx/cPj87iPpgjIkMyxOC8dQaXbXEhlFSNtURUcmVma23f9/9O/6vW2loqIhLa+4f7boiuC0BkDJWalmUZ+n46TCj6+eOn//IP//nv//4//+qHH969exym8YcffrDWDsM0DkM/9M77H3/zG+eccWStXbfMzH/+058e7+9VdRhGVd1NaiwaETkcD7urSXCOLCKpaBPhtCUAqKXOt5t11oXYjRMF/LbdJUgpgVLZkqqiqjAj8N352PXT+e69CmZW56N3AZWX+eatzTm1ypfbxTuDiClty/Vac3bGomrLeZ1v27Y2aKnV/9CpbKzjdNy2rIDv3r2/3a6cKwHUlHfpBIVvlCBLpM5u3MIwTIdzF8LUTWSssuzTXyRstd1u1xDjfLsBS5wmG/x0Ot09PGptXRy/LTtyc8Fvb69iSLTtG04f7OvTl9aacYGMif0QQjyfztZ7RaPWNNBtW/uha1xRte/7nPPxfBKBtSSKYdtFs5jF+V0x3flwOt//8vPPZExTSVvyxq5zCl1XmUtp57vHf/ekM0gA83U+nk7CeTqOwJq4Oedayr7zuomUlpidNXvnK7K7nAgaMw1HAEhli7673paHx3MtxXde2N3Hbktbzjnl2odvnwgAzrta6062AgBEtJ7AkO4mmEilVGfjP/35/3cc75j5/uO7vJaP7x4Lt+E//Q4AlOvH9x9KrqnVP//5jwJoyG9pi4cpr5dxOjy/3UT48rY0Qjby9nKL3oNBIMqtNUlGjLfEpSGiAgGYmovt2SJVZgMGQWsu2zzPUoL10VLJG6EBa7lUslakKFLozu/ef5qvcynlv/23//qHP8SfXn95GO/W9BItxq6b55tznpSNtOpjZwwoR0Nvt6uzBNZLEhetApAYVVJpfQwNNC834IfT3Wl+eXl9a8YbylFrUSOo6hCqaErZWmpkOHEX3Koq3n19eh48XX95GQ+H3roQQpsTOhVE5Eygux2HCDiTv/z088O7M7Ngk8YKhiTV+w+/Uk+tNX84bbcLOTN13VtObZtzk7v7d07x+uWXkufoewBAqWTsvnknwlqSgFyX7TyNn3/161by9uUXCl5KA4LoTG6Q14Vt4pLWtHaxJ9Wn+fbh86fXp6+gygCsWssW+okAoOTS9f00TeM4IlIIYRqG1prz3rsQQwCAlPOegbz3xhhCrK3l3W5wt4Ty/jAdbvPmrK2l3T+cnXd936nq09NzrYX/3eSFG+8ZtJSi33Y5qqoq0loz1mxp26Wv1227vF1EuO96a23sYt/3Mcbf/P533oXz3TmG8PHDxw8PD+MUnTEpbeM05VbJ2mWZmXlZZgA8jBMpkHX7YtrbPpUsIsy8rRs3NoghBiIiQ0iwOyjshhvn6TgMIzd11oeu90RVWUvpgi+1fvr8+Z/+5Z+cc7///e9fX1+zyv3dA8XoEOZ53rYNVI3C7XrV1hzZVIrr+gb47t2HUllV0SjXCk2AJW9ptwmttR7u71LJ67qmlBERVUU5t7Y7n+yUjH4abPDj+dRaYWYCsaT3d/fMfHc8DV3HpeZ53Vvmw+EoACEG6yMgWsS1pK1VFcyVm0gMvpTqpp6DBe9Dtw9QAzMvaeVayflpmm5vF2V+/PBhHEbvv5mlcKv7r7iqrOuyrYttwiJfvny5vL6SoR3zb6xhUON2gdUSvEeRvK2F23CY+mEIIZSSnbXL7bbMiQDIez+OU9d1aVm3NX0jttamjXdvtRCCJQreA1EqueyS261ZcsHa6MyOKue271ExV/axe35+2a8qZlYBIsol73r1Oy7mP4SvSqnMvKOQSqkpZRaptZ4PJ2etApSUrbUMuv+Ezjtr7e5w7L3/b//1H/+P//0f//t/+Yf59hZjJ0DGubRtoRtaq97aLg7CMI5TCH1lJmf78fD+82drgkGcDpNxuxGK1sxISoZEmL55xgkw79rvtznVWnLZXBeMw1Zb6LqffvlL7Pzr6+sf/vCHt8tVkLyL5J1KTSm1xs55XheDyFvmWnd6MTPHOB0O90BkvEVEJGy5eEDSZkiNMS7267oOw3B6vGucAYBVrTffPE+MYYV13frDoQgDwLJs1pi6bt57MkYFOJftej0dj/uZXpYZCErjlJKzPhzOjPa//d/+94agiM76Lac+BmMMg0ht87Jcrlc0xli/G4D7vl/XW3SWEIBIAVgleu+tNYigJEqG7C7aUVr++vTFEjqkxmKMsc6qamvqQiSiPSu9/PILAsQYP3/+nNKWcrbOGEQCHIZhXde/dfF/i7/qIN4lUpVba7WwCuw5Msa4o6kNQuiCsabre2sdEbVaAQgAdlmHvfWZDoeS6j7lKlUQEckE34lIF2NK6bYuO6t6x8Crak5ZRLY1z8uybdu6LI1r2jZnLbB0fdf3PTPH2BuLoYsiEmOcxpP3vu97Iupj/Pzx0+Ewdn13vj8HMl3XfXsJAGPdMi+ltN/93d89Pz1tKdvguz7ene+Wbeu6PljHzKBtXxn4GFoRrQyArTGQAdT58gaqh8NxmkZRBmuPd6cqSs4qYm31eJhKya1yZbFkU6mt1K7rj8fDcTqKiNSWc+bWuLBTkFK08ZYLIu4rJWuNivrgUbVsG6sab8j76XhcU7IxElEppbQMsGvAgI2eDBmiJa3vPnzaxdiWt7e6LLnVbc3btq7rYqzZltmirSnvgEZrbYix7wc2dB6n//n/+f+C4t3d3W53VqUyszUQvM8pDX1vibZt7cfp9vqmiGSQpKlqynnZCiIKV6nNGMuNQ4iy5eijjaG/O/d9V1Ji5th1u6frlkttktKmui9rMd8WruX1+enrz7/UUhHgdrl472pKzK2VQqSwpRUACMU5l1MCgN31ez+g+x+sdbvT2a4jsK5rrayqZHCIvvPBEqpq13cA0IXQ9yOga6zTMBHRbsS2pbwvk3YFqP2KB4Atbdba220uqazzTAr7Em8/kSK8TwD2O9c7Z4wFYxAxhNCHaK37+edf3r97b40xgEPXq1QGpeD9GBvC2/Vyfnw43d8DQUrrXgGHOJRc/qNdE5HWGvM3H87d9n1ndyjXebmoKjfBqc85xeNhK+Xx3fttydLab3787TAMKW1aa+yiZVGAvh+WZXl5fS21djEwgSO3byisj1taVXUYJiJPRLgDwRARUQnV2q1kY0xr9bbcECCG4DtfWtn9LWqt0CStG5FBVWU+Hk7ed96aZVl8F7zvEJGIjPXjOE3j0HL2zjnnvfOvry/z6+vXP/+Fanv95cvTzz8NY99E4jieP7xfLtdSa3Auz8vLly997HNtzPx6vZwfHp6enkrNVdjHaL2/vr3VUlXFGhIRMpRz8j4cj0cEqLUsyxUMici2bjEG61zwvfehlhq7SCzX25VEt/m23q6DD58+fSo5lVrXdTMWaX90pFUizGWz3u5HfhdMJAIE2AVmrXX7Ip6IkAhxrz6Lc27o4zR0h2kcup4Uxj5wa0SExhhj1i1XZlAEUOeIDCCisOwndcep1ypr2tZtVdUY4jiN1loEeHi4Dz7sD4Z1DsCIaq0lpa2pgCHyNsZuz+WNCyFu82ytVQDbd4e7u62kt3l+9/HzPM+wu8Ld5l0RUgh2s4Q9g357YJRYtYCiNarKjVEVRLZtCX3nYiTFMA5754GG5nX5859/ZmYQ8YZE+euXL5fLJcSeuT0+vl+Zz48Px8cH59xtW9VZNiaXbZmvuwEQM4OhlIsSuBjAOyS7pfRNwWuccs5lLcwCANwUALiwtBaC+/D503KbjTHW+of7x53daoxlaAoARCHEl7dXItPHbwiPnBMhDs70h358uP/Vjz+u82qJFLjWMr+9RMDXLz9Lq+t88cGJyG2ejTHjMDYFNM459/hw9/Hjx9ryEGOIobUm2kDr27awilb56V//zVl/f/8Q+p6I5tut76KwoO679DYO/ct1ITLffffJAjhj0rJKK32Iu/D08TSpKjnnLFLsQm0lerf78O1NjPcWUWP04zTsDdMwjgIQQtg/tN6P0xg6HzsfvT+dDsrt7jDVlO+PB2dxW697JUD4zYPLGAOqe07NOe82SKWU//kv//x//o9/+tO//VS4/XvilM+fPz8+PB5PRyLi1nLOe7P17ZcKsM9fT+cTM6/rogAAcDqfbHDkzNYqW3P37kTe/fFPf/7Vd995G8Y41Vw/vn/XGlvvW2376vI/ip7aMiL207ifTnIWVaWIMc74kOZFma/Prznl6+Xy6bvvGpphGAF1W5en5+c//emPcey70N9ut1LSdZkfP3235C2hzvNtZzkXKWMcQ+i4ZmOwpJXzNzNwIEMuClEfXFrXUooK1Nq0cYzBku4Dy85YIjre3TVty7IAwNOXrym3YTio6q7Svc8EU9rAWRZYthURz4cjlyqpKDdjDTr6+vVLP4S3t1dvLKrIsq6vNy+8LYs1prX6dr2sqXTTaInmXN9//Lhu21/+/Jfnt9e7u7taKrNaH3YZnN22XVVDHwvrly9fove1lr6LznzzuZrnpWauWw5dyLW+vL09Pj7O14uzuG3rP//zH6zxr69v+xX6tybpb/FXHZTSpiDbtnUxikjXR2NMbpX2raDyf2SXvu8BoLX2drsiEO8i0MJ9P0zDiATBW+/cNA3HwzSN469++O7x/tEYMw6DqqroPjMD0P8oQJk55WSMaU22VL68PM3zstWMxh8Ox2maDKC0b0kdEddl3XXERTDl3Frz3kvj6IxBiENvjemH4ePnz3urYaxVkNIaGeecFxHnwscPn//yl58+ffq0zMu+ZeEqteyXI5G1olxBGQCtaSokRIaApYISiwhr4SHGZVms9z/8/ve7wP779+8puONhTNx+86sfS6tA+uHdxziNZJ2NERHrtnkygahsuaasqmRIv70t4JxrIuiccd4g7ijEmsv5cNxSut1mi7TD77lWIqpQ//KXv9zf3xtjTsfz2+0KRN77HY3aatl9YIVwKUkJQ+xqLd7aGJ2pZfv559uffuI1df1Qay45SankXCEUlvfv3zvnu653wX/48AEADGI3jMuWfIx9F2qtKaXYxX13nVPWxl5BKtsuhmmyXReCv7687pi1bd32g+S9Q0IVQbLe+4eHhz/96d+6ro99T4ZOh+PX56fjadytFEhQay07LRMRuYkxBlXIoHVB1QDQLs0jyqlU5/s4dApS8haDvZ+GLlpv6XTozlM8Tl30dOj93SFGS44ItIo06ywZstap0i6AyyKlNWutsS63SmSP5/u78wOhBVBrcRyOCtCUc1n3ByOvBUleX59LKT5Y/XdSJhJ0Mfz9b3/XOYsEaU1WzP/2u9+TU9vZjRlQYrBfnp5//NWvr2+X0930+vXPf/yXf7bBWyRABovoDCHa6L0zBKLbEgGNaKSQW5amKoCNve8Q7DCMIAKc3375y+VPf8k1X25va7o5ROfG+9P5315f0IEjq9Zobs6Y3ngf/Ja2LWcXIrZSWLo4vL28uWmIwYOyoDhRiwaJkFyrDCLCtRiMx75zqKrWgIiAtWARWX78/kdVPhwe3i7PiqUJ59bIhWBBBKBwKS0Yh2DAGmWtWpuIc66wsg/9452fhsRtHCeDCGrImUMI/eN7ICLjEExw3sbu5e1t/vK0PT8pwNBPwuiNzYxKoKRIlkWMsWLpcB6X29VDOBxOIBqnYx+6WkUJRZqiadsmtai3FkEcgfXeIHaRGArXhq33fjifDdoujiQifT/snWzswt4hEuIur1pr3bc8e92JCM6gATQWT6dDDE7km+FpF7txnM53R+99F0Pfj2tKQBRDUNW2e1E6BwB7E72llNJWav3GcvS+68LxcPDBf+ujpTIXESUyuzSpAi/LuizLtm63yyIMoLTOqeT6+O5xGIfpMHnvD9P0dr2gsdb5liukGoy/vL6iwVrq+3fv//mf//kf/vN/Hw/H3//+90zVGQvacs0VoRnaavXBI5gtpZSzSGNm40gJd/2jbV1q3i7LBkTr7XZ7eVqW5ePHDwAwjuPd8dhSGqMFkVxbCCEO3dvter1eEfFwviutlrSJVu8prevpdEpbrY2ts0hojKmt8JZIxJIprdkYlnW5e/eRfOecq7UCqnEUY7zO29Pzy7zcLpfLYRx3Y7jgXCslpVRSZlVVrnUXpKg5Jwv2eDzfbmvsh8PpWFsrUi3Rusx5q9uWnp9e+vN5GHoRyTnvZApvDQBUldvlNg7D89cv0iqDHk+H6/UmDLXWGIOLseu6ZZkNAoFu220YxhDCuqb+MFnr0BmQRiDWWQEouaBC3bLx4TbPPsbaWl7LvG6llHHsuFay1pVSAGB3Zt/RwV0XdotiAEgp7YBFQjN0Xez9Pg0ZOtvH6JzfBx8xxr6P3oeuD8fztJUsDLU1Z8yOIfLef9PCJVLBkmvJjRmYW8mFiIJ149CFELyN+4QF/n3ysitnM3PKeV3TPG8vz68ggIi7qf3peOr6uN+Y19sNALatRN+D4P10fn86dyGQtawwThMA/PL0LKr/45//SUSksaqIxfe/+vH+3QfjXW0KAGjMMPQqiuS2vCGCtbb9e/FzOB6G8dSYp0PMef7l559ijNfr2/OXZ+H6r3/4F1UlY79+/Xq9Xp21quKMCV3X9/0wjArcalKut8vFOQsAW8oAICKAsr6+SpXgXN/3ZJyxdi15GE77422M2bb0/Pp2//Cw5fTx80dmPh4PeduOxyOySM6GnPXGR7eLRwkXFEUhUvP89aUbD0VlSRu31oeOS9nBZX3fKVASvl0ul8slhOBCuLt/fPnySwydIXq8v0fEGEIXgjG4bZuxzjq729zk+m1sx61xK46gtmy9M9aDUi11R51bZ1JODCqqXKu19MvTV29tfzpAVefs5++/qymJcONMym1dFgCwe/8FwtKYmbn++5pVALC1dr3ciIgUogtD7Axi8J6s60PYz6i1duzj6XgwlhARQMbeW2tD52Pw0zDscyUR2SWJm34zNELElFJKuwnO/995O4QQQrevg/cjfjoevQ8xhOPhUGrea1lhIDKt1dYaIuac7+9O6zKvy+q8G3yvAiJSUlJVQBzH4XQ/xbGLcWBGcAYJgJDB5sJoHXpnrIkxbHlDA0DUDbExL2k1zpdSraP+MJ4e7g9396KGCNO6btvGrVk065LuHs7IcDzf7eZgCmSQ9pUjKAXfVQZnwziOHz9+3JGN/1HMOWcDmeU670SO5br4EBtr38fcquv8rk0e+/70cDdN07KujetPP/0MAG9vbyUvMcTd3dT6gNZ6Z51zyoyIbaeGiNRSOx+8sesyc2sgsqyrqn781Y/ruraSgnOtNQS63W7M1fuAiOuyWCJjKeVVWjME5/t7E4InQwBb2gAAWHyw23rjXK5vbyptH2UaY1prvotzzq7riGin/fzxf/7T/ePj+XD807/96Xg4gCgQEZltXRHxb1383+KvOmgYxtjFPUUh4u7fBQDMXOu3S1ZErLUiYNHkbdsfCCKKsetCtwtssKrztuu6vutUdehC1/mPH993Q4zeh+D3v99jWRdE9Oab0QKhsdYejyMRWWMBdvNF632MvvcxcFPnnQ9eVT98eH++vzvdHa2jUtIuKZNzbrUex0NLZRj7GMKhG1Tkcrvdlq3Wsvua7So9XTcikIq++/ipMqy1NIS+G9fb8t2HD85FG6MgGO8AoLXS9V2qWY0qEgA9vntXuM3z5TrPfpiOD48//ub7d+/eqerUT02lGye0cZkXF4Il6vv+4eG9M0ZYUXUax6eX52G8867bcr3Ot+C7xpxT7oe+VFluVx+D7/u3t7eaM7SmityKcvaxb7WFGB7uH3/88deNJaX0+vTivfcuOnLRh91Bytrdcrhu20KEpKCquazbtoZocy1IWLYkuUz9eD7f7Ti1UqrrokOsJe+DhZTXl7fn4/HE3CwSIt6Wpda65rXVlLdtLa2bJpIKAA5pH4KWLQHq9fXyf7H3Xz2WJ1meIHZMm/3V1S5CZUSqkl3T0xwOerm7WAwFuLsgv+U8kgAfSIAfgAAxisPp3qpW1VlVmZER4eqqvzJ5jA/m7pnDT1APaUhERoS7X/e499xjR/xEpeX3330bY0BEpRUhJBO2WO9MszBVvVyvUkovrq6qqpqGYex7kjMjhLJHYT1CCC1LmhjCuT+EEMZx1Eo93rOEpFyMaWJwhUBIpZSMESEoozxFTCllQgAgxhgiloBumlYquVota620VIwxKdUjeJaQnHNRsKyq2nlXwFCS83mauaCEPhrW11VbIPeEEK01AUYpbdtFYRQhYt3UMUbKSNFlaOpGUlI3daV1TnHd1imEWumQkgvx+sUVFExfSre3txgpARp8YIYKozKw9Wo7z/P7b7/bbrfdeiMVt8EJIymjMXkAWC6XgisuJQBIU2WM2qjDYY+U92PfrZaV0iynVds557gym83mfD5zQjmlzrnx3Ifg3Wz3+71pmkQol4+qzRiD9z5mgExZbZxzwKjSgjAGiHVTKWM4ZYeH+9M4BwDvvNb6m3/6p3/8+7/f7rbOupvbT89baGOq4gOWUppmW8qq6DzJmTBWdzWT3NppsVgWtCQV3DqHiIJSxTnJWElVSFGMscViqYUoj1AKqqaqqqrSpqEZxuHEOZ+9A4Bxttpo5/wjep2x5WKdcm67qnjn2XEyUhPGKRNMSMi5QDqP+/3t3e3d/c2ybjISROyPJzuOQgpCgDrnGON1W1dVTSkFgqVVopQWeqFSqvg5GCUYAaOUFExySrmIOREKZXMNAGVxRymtjKmMqUztQiSMCSG1UmWQGWMEgBJhgnPvfabkPI5SybauC2URCFJOlVaUQSZICOFS0EdbUfmIChACgMUYGeX9MJQ3T2WkFCw6X1Wm7dpl1ZKYFWMMsnNOMS4oLww+N3tEzISuNxcXl6++/vmvHw7HblmN4+h8pIRfv3rBJXPeMckhJ0a58w4Qg3PH44FSapQ5HfbvPn89Dqf9/uHm5pOb54TxcN4LIbTUOSXr7PmwJ5incZZccqaUUsG6xlTr7RpjwOj70/n4cNBaa61CQkdgXS/2x+MjT4HzcepjjFSKaXSyNplQBDgc9inE3W43j1ZLZYxKKVHCOKGZkphSiJFS6lIsC1tW8ChaZUpyzotl672vCt/QWVO3lElCck7hu29+fzrvTVV7H3LO03jOGKNPJCcqOGf0tD/0x9MwDkJrrY3kHP1MucicAaOSsRhSRkIJH4Prx3m13BFACkkbBZjiPEbv93f3x+Px/YcP3XZ5Ph3Wq/Xrd++iD5OdCc2HwwPBnDOkhBQyKRTNEpfGGCl517Zl/FnGT5TS/njIgNM0OW91Laq6EvqRZl6g8sXGvuCVcs6cc8IYAEghtFKcc8qeTIgplU/uyKWuqIxhjFEGggutZInRTJAyBjRJqaSUUigpVRHESynlDJTSGDDn7ILNGauqevXy+mp70XYt+hhj7JoFiTlFD4gUYJxmAOBMNXW93bbbzYoS5hwILoezNXV99/CRCZ5znqbpw/ffxxir5mnHa4z1lmbCgTnr+v58Og6Cwmn/wCnZXly23WLRNNaNAFEr0e8P1s6r5Upr/fBwv+qWq9U6hEA5M8bc39/dPXzKGAhArTQjRClJCEkx6a4L1kujvXVF05Rybip1/eq1lJVSdWFaBh84IZJxO82Ciq5pGGOZEMFYCKGsvwFAawWZ5IA5ES74PE8hpNm5tu0mO6aYuBCECWstpY+Kpy0XhDGh1XK5JGUeFIJgTAi6vb4mIQFiSklxwbhExGmaKGYfQ9W1zvsYIuMsZgzBL3ebl6/eHI69c1NMIcXophlTiMErztaLJWNssrap64fjIaSohADOOOd1XXFKnfPWup+apJ/On/WhQpHiekEJ10oA5nmeY4wxegBAxGEeCSG7iwtIyBgLETXjWnAtBACEkABgthZjLDiGkndLHqVPLErvAyYAgIQ5ZyCcKaUREyGEYN6uFhQSZKqEBihC7wRjZlQKVmREuVCSMkYIyZASBmsHgEQYhugFM96HGEPddOvNgpJ87Id932utGWMCZC1knLyq9DCOKbvBTj6k0+GUU9ws1372iEiYaLs1MHDzrCRbrXeMU4wxphBomiFJY1yaZn+WQkrOq0Z7QJ8RCUQbMmLwllEphJnGWQtBKZ36KRNo2yYDXuyurD2llBBd1bbRTuM4EMFl26AiXBDrA62aYX8LkmmltZSEkBisIBk8HPen69dvXmx3hjOC5DwN7W573B+SYsfjHQAQTkTVEAGMQAheEMqYVFwIKYSRQeCckMQsKKkkP97dp5i7q4tUKVXXmONx6FnTOm8hJyPEcByMrjJQZx0VIlCUTAzeUUnDeBacLBebNNscIyOJMY6c5eglI5LSjMiAMMaGw7lcmIkBARp9ylRG4CSjm2ez3K4Wi+xjVKapl2GwiVEY5kyI4MrHWHc1kky9D8aYoiAAADnnpmlCjIuu45SEEDilCT2huYyIAcA7H1Ny3hcMpXUu5+y8TymN08QYm6YppRScAwAhOXlquWj5HyEMiBSi/PQAIKWq6kdjBkqpEKJoOuSMz+8kQghnDABiDJgSAHjvrXWciZTiMA7WOiFECH61XC2aGkL0s9+u1847nyJlMM/z5eXlOE4k56quY0qmUtpIwaWWMqUkheKEc84TklM/Mi4TEJ8w+qxEY1RHqFK6zgCZAue8LPdDCM4FLkS77Oq2xZgIITGlebZGqnme1utNSOlhv2dSnY9HTFlQtl6tLzY7Tqh106JbphAyoBKCA/UpRu+stRRAcMWkHI6HHNyHj+9v7m6BYs55e7Xhta5Wi0XbrjYbQDwej4CYEHJGKRXl8okHlkqCUEpJJb3zdrYhpv/T//g/ButWy9Xs55DS559/3jRNu1xM03x7/7DZbI/HY3HbhgTB2gJKtLOVlIZTn4ZpnqcYQkpRMCYoI5gxRmCUUCKlTIic0mHoF8s22dnPVhkpjNJCZMxVZY63NxdvXrhpfPHiusCcgpt415zOfUpxdDbn/PbdOxoDhhAqY2qjlJRSynEcq0oTQuq6XnYt5sApZ4wVnisACKGKYqPz3vtHDDIhpEhElsoSAMroqnxJGQsgImZETPA0vUICJUYfcWghlJqv2Hw+w+oKTqAsXXNptkIch1Fxzaiwbkop+RgKZqCpdNtWTVUZpRgVVPB+mlwIWqsP778TlDHGTqeT1iqFeD4eKCGH/T75oKW01o7zHGPkwqhqwasGudBahjgzTrUylHIEpIzEnPqhd84665tFRyk9D+PhcKAMZjtNbhacC87Xq+3x2C+WC+fc5fbF5XaTkVjrTg+Hh4f7GKNzfp5nAKi1TsHlgM1yI4S01kXnEJFxlVO8+fBhsVg6N1nrgCDlrFq0vZ3seTz3Q4yRAjRN3fc9kzJFjDE452OMjPGYsapMoSjmlCijdV399r/8zel4jDkWaexPdx8JY+163dTN7uLaB4c5kgwZCQAIpiilSqnl9QuklAvuvCWY/ewIZmsnO4zR+bJ2AUbL/encxBm5/fjRCEEoZIKME8BIOQQfjsNw//GTbKrT6bBaLZyfGGVgRNs2iLjerRFxnmfaNg2mNI79NM/WOUrpxW7nvO/H3ihBSW7rtmnrJ5wypJRSTMVnt9DickbOmNFaKyWEdM4lxJhSCa8YSjg+JkLOWEF8PvPmtNKcc8H5olsopcqEokDtydOXUUJoIYtBKkMoxhkAJESSyXq5KmBK5xylTBt9sd5WWmdCUob1erVer1RlOGNKKSmElnKz2UQfUohaKc4ZoRQosz5qZaQSLgZEWK93ddMxrkCKzLl1ox3PY3+stGZAMUY/OU1VjjE6H2O01gql+tPJGLVYLwqF4+HhHlO+/fixXdRam/ubGyWEoGyz2TLGlRLr1UoIkUL2sw3eaaGi97N3WhVNsjjZ2YYYrHN2ooInJN6nYRpTzrNznLKmW1DCGWOn/YPzrqDETVVrrYqHZZHTkZzHGHdXV0opY6rj4bxYLJyzlILQ0sV4PB7++N1703XLzTYiIsaq1jFESliMIaTEKW12m8Tp7J3zEwOyaBtAdNPMyvTQo/WPs/N5tnXdCMa1YClkpbTzaTieMiER0XlPpKAxXb16PRzOQipOKGZs6k4ImVIypjoeT+fziVIKxqiubRkhWikpBBe8rqqmroXkWkshxDzZnLDokBtjKKMlLz6GYIzlfi+DpEdt2IgxYggpIAIAAikVAmPMPxOOGQWAmBIlBADKsjRnKpXkTALAE2oE09Mj/1A7U1pyLSL2w7mpm+CTD5kSzqhICRfLRUoJCEkpHc99VXf3Dw8AME7Tou2GoQ8xrlYr733EZL1vu24YRyZk0zRSSkCYR1tX3XqzE3p5ef1md3FRV4pgcuOsqJRcLpo6Bh+cL5Sjsoxlki82q8na/fEUgn/x4qXSct01D/e3D3e3mJIQommaeZ6VUt77kuoKZSfEEELIIUpjaKaAWQi5XKwuX7wkhPSn02Z7tbu8Eqqu24Xtx6vtpZ0mU1d933ddF0JYtp1Q6nA4jHYihOSUvHcppRSxKKkIrUZnd5cXojKEMECUVMSQpBCbza5u20DAxVC3bdctTqdjZYwxVZF9OhwOh/3hcV8dQnkVOOdSSSaokCLlzCj1PsQQ1+v16K21c3IhJAQqUko008wIoXSxXiy6JRXq97//ZlnVzrroE2ES3ONghzOxWq4I0J+6+J/On/XhkNM8DafTkTGGAN77JjSUkKdakCrOZV2P1ofghRAUIENKiYTgy+gUAB71/Rkr4e9DApJijIQxtBFFNgCMUkRMkAHAeVeQEM+kPAAoGyapJCKhoizNMMZUvMUJIYxSjLkk75QSF7xtGsyJMc4YM8YgJucD53y29jyPk7UIOQY/z3PbNm3bBuuFVtbOWlU550+fPiktZu+7riskdHBpnPquWwWfGCGAIJlSuzrlaO183O8pACP0fBqoYJTwcZyM0VVtrra7/nDfz76q69vbGyBse3WJGRhjJOVzfzaV7vthtdw8PNy2i/X5PFg77bZbay3LMI2TaWqfYvSJAigh4jxOLk7e66bp5+mXf/HrP/3dPwzDsF5thDBRIIZUVVWAEFxknDwOSUJIjNEMkgkX5hwiJCScc0qds4SQ29ubypi7u/thmkJwQPJExtnZ3eVV8th0Xc4kpGT7UQASQrx3mDJlpGrqMAzW+9XuSspDjI4gAGV2GAglQGnxUeCCJ+dFpbx3hFIhJSWBVaaqa5aDtWmOsW6MUqrtVv3tXWOq0/7Im0YwFoJPsx36M6V8nmct1bnvqZLcGG1MlVK++fSpANhma4+nU9knaaMoI5xTKWXOuVBAyRNlttzaRaWj9DDW+Zyzi352trDbpmkcpymE4GKKKRV+UtnyEcwU4Km5J0qpR5P7p6Vo6bQE54QQApBShCfIGWOMcYI5IqLgqu/7MsHOOS8XCwDgDPb7vRLy888/t9ZVVXVxuSOEROdvb2/97Ky1BbkzzzMByIguBCaEtXaaRyGE4IoQGr09n853d/eZyLpdDzYCE/MYvA1CCt00MeP3N9/P3hNCbu5vCWMpBOtd07aU0tm63eYCU15ttzElQqFujA/JmLppGsiEFIPajMfTud1u+qGf+36eZkqpUjK6uN1c3Hy8I0wsN+u74+GhH7wLUlf393sk4McppcS1FEoBAAE0Rk7TWKgQRZsthvhINeNkmufgXELgXJJMhmF6+eJN348fvnvfD5P33oVHiee6bpbLFWPMe+dSFpznlDIlRKt6uaZcWO+FVpxzzBExSsFLDATrUkptXQPjommBQWmnx2gZpV3bDkM/jP16vWqkchjH45FywTL0U18ZzRjLMe/3e6kkjxi7tv10u6eMd4tFSWaVMTElxti577va1I3xKVGkp/M5Y8BNi8iklN77DFhclJ4SaizFYsqZEJIgI1AMKcUheiGULj4ynHMkwBiDDCFGbUypKSmjpUkq7dHzJLXk8tJ4AeTHbUoIlJJC1MJHjwQnJLfBCcE5587Z/ny82u6Oh4PWehhGx2jXLeI0Ky3nYZRSIiSl1H5/5AQqrXRVxTQaaXLO4zRQp3RleBKXq5etbJUSfp6VakGy4f6QAUN2s59yTpIxJWTCbExVwANhzlxKKQUT8vbuPqKfg7+4uACSj+fz1dWV4PTDh+8Xi8V5/4CInDOhFXBW1Y0htI9JaZWcs9PULLrlcjlmEqNHSExw05jZWh88Imoph3lIMcWUtZDjNDIgi8VynsbCrkl2LsI+CAAJFePnw1Ev1l1dnY+H9Waz3+8z4uXlpV40BMBGJ4F8+ONNXVdEkLqp8oBcSUyhpfzw6RPTMgzDI5iD0mmctOYUIMcElCglOaVIiJ+ti76u65DS1J84y5Wpc0jH/YOdZ8z5tmun998td2tOeUQfnYuc5jlEpNZPzaLux4mejqfjMLdtqwRByJRTADgP5xjmfhjcfKSIEEOrZQhOCta1TUYo8jUxRm9DGdDP1nvvZusLBqq8fRlmzDF4Rwix3ueUCEIKPqVEMHNCORdF+gEASo9VFNrLHwGAc1GeBUSMORJKU8KSbgHAOW9MZbSZrdVaA+URiLMpA2t00+rqerP98OGDdQ4gv7q8UkIdDoeUMwdCKWOM13UbZr9cr2up3GT9eF6oDkNq6xoSrlftPPWUE0HpZnHJuBHVgujaZ1DLzeLqxXLzArPyITfNgjDGedbK8AQxJ1NXs3c3d/cRrTZGaKVlPfZnwniYLGN+HI855+hd0xrI0c+ubZtpmkCQOSYlzTCdnfcEgk+oO4PgJ9sLxttWk8xnOzbdojL1ONlMJYYY7ERNY88OmLB2xJwoEYxxQPTOxxgl4SxLTNCuVwRRCFkv17JutJEQLLA43d04F2imPuWrd58jk1zx2Q4ZAglYL7rvv/tnmqOWMqXAAFIIEKMRNCFBylPOoAQkBCmycyllrWpPYDrsKc1MqIRhtd1wDBFzU3WJsLZrgVHrp4pL4Ey7iCFWhisJyLmU4qcm6afzZ33ol199QQiZfQQqMzDr0v39PgTPmBiHiTP5cDy6EFJKdW20ErvddhzHUiD+8CiUOuuGYS7Slc655IOUSle1EKKUkjlnBBCca20opSFGzh9NyR/BU2WTVAQqKIVnRCCl8LRJSk+w8EfYVF2VR6irarlYQkI/25SSj5Fy6WdX6WrRLihlOQMhZLla1UprJankTAjBtJud1IZmwjkXQkzT+LDfE0LsNGEKp/1h0y1IzsNwdnHGiBzosl00pl0tVpCAc3F9/eLy6nIYBkqpC2GaplL/lZWSqkyKOcYolBrHMaU0O9culofDPqV0fX2dUnrYn4Hwuq6m8yAFN7r23vngiTKr3VXIkDNOg/346VNMORMo9kXr1ZZS5r03xrRdg4hSsGk6m0qWSTUABO9ijJiwWJechvM8zUDZNI3Bzsbo27ubvj+5eaaUnQ+H/nhUUnrnjNaUEK219z5izoRiTuO5f/XlV8rUUz8SoBQTRPQ+WZ8AoMiDsQwIMAfvMno3aa1X69Xm1ctsKmrqgAAA1sXlajU72ylNdBUmSzPO6EkIiQLJGRFdjJxzbx3drJbH8+l3f/ePh9Pwzbfv/+Zvf7ffH1NEzlhVNc4HADj3van1ZtleXWw4heVqiQkBQEr52MgjMiZSSi6kGBETEkIQU845Oi+VLEIMRTJOSSnEI7GpCNo8t/Plc0pcPm8+2aN9YE6pCNSEcbDO+TJ3lEpqo+vWdItutVi+efUqpBAyhpg+e/NZJmy92TDKnQ1DPwTn/DyTnNt22XZLrfRqse3PQwqpMdootehWzs/D2CuhvPf96ZRcgIiZ4em8TzEyJgBoq1rvguCybRZ2dg/3DwXYRYAWuCoF4JQipsPpJJQmnFo3X+52XCpKOOVcKcUYG8dRKbm7emkx708nkhMjJEcUQmJObbdEIK9evQ7OpZS211cxJOec0OLm5ta7YIxx3jeLzkg1DieaIWMMMTLG22aJKQMnZe8KkLlgujI+Jak0F0xI8Z//43/8i9/80hjFKUnBN1VruEzOSgp3n27cMGqth3Fw0+Rn66YhQAZVSVPnlNebCz9PhALjTGojJAOChDGaEDhdLFdN21LI/XA83D9EIM16dfHymmHGlKXRm4vdGOPx5q7qWp6h74fVxYWSIubctA0kbLoWgzNScIJ52S1uzOFv/+53lWkoQN/3i0V7PA9KVxe7q2HsGYXgg2CsqusQvHNOKgkABSRbUqnkfI4JY4oJBedFUKkIF2qtIZOM+SkpQunKy4iqDAF+/MeSMp8TZ/kqxIyYASCkaENk/hE0bqQa7cwYwwR1U3vnK2NuD/sY6Xq9HWM6D+OrV69Op1Py6eFw1FLe3z+suWybihDhnPvyi68/vH//cPtQdQ3nXGujlChc09VqNU4TQhzRS6FDcM65TJimnGQglFBKU4hKqZyinSafCOeCUhYJciEJkDL6kFJKyvrTmWnGOZ/mgVBqdG3n2U5WaFp3TQbkhM7jWWWCiIyBH4fT0ZoX27qup3G+uLp+/+FGSDlNU22aw+FwdXVFGbl9uDOC0QxAQDCSOJ29pcAwIWFAQxKCISIGFFyauqqqapoz+rC92n768OE8j43UKWdGyOy8G87jPIWYFYW+Py8Wy+l45IT7fnjx5uenfhr6oW4ba61uKhezCyHnLIEApSE6mmkm0Lbt+7t7LRlg7vd7Soio2vH+KEM+7h/KHuv6+oUfxr7vm7oGJTAkG5IQvJ9niolx6m2olKSIua4M4/Tzd2+im+0wKqXO56E/D865lFJT15RSCpkxGr2lAFLKsj1DxGJTTgghNGMqyOZiC5wLvbhpWqV0jFFphTnmjCXmysaysOee/4Yy+qM7nVL6qJcUU8L8GMS5sNTgMY5jxkKJVloAZ4ioBa+Vjt4d+2NmVEo5W7tcrdrFomqa0pB9ev/daf/w/v0fuWBKm/VqpbX2zmmp67rGlOZ51lrHGGc7jeMIGQWX1o3Ac8IAlJpKKS374aSNMko1dV1VVV3XyYfZWpoBSE4hMEIE5RTwdDoZo4UQSIAKlnMehn6eJ6UUZudSqNrlcZgopRQgxhAxuqnvmvrTw/1sx5iC876t6+1qa53FGNu2DtFbNykl/GwJITF46yYm5atXrx8eHuq21UYyzjAh5zyEmAGlVA/H/TiNOWdCIUTX1s00T8U+hgk+n09hnhVjp/sHmhPNmT9VX7fff/DHw2rR+eSdHQcfqeBCciaAMBZ8EEIgQAjx4e4OQwQAyNkwXnOhCEXvc0IGzI0TRt80tU9x7ofz6XR5/Wqc3GpzAZQVHEZOiVEyTzPth36apuj8p/ffU4DL6wvT1JlQ5z1nDKM3lRGcK60QUQhZUDylBEwpCSEAIAXMOcunvDjNVipZIpUClKJQSlla8mdmUhmj/jh9/qjuZM+3/FMGxfKh6GNOyXsvhS6PxrkgmLXSdd0QSi92u8vNqjKGM/DOaqMWXTcMg9Rit9sRzoxWl+sVxLDsGiGYD67uFoyrsssVhBJgSvD1ehVSiimsVovG1EJwIMm7iXNGOMzW2uCnaSQUHvb3NzefyuSLEII5YnEhUkWRL0VI7WIRaXzY3zFGCM2UCyZl03YRop9nQkhIcXt1mQmbppEmjITMPtTLRbtZF2mqjIQz4pwDzCSjn63gVEvFBSvzYyGkZJJSmgmpKgOc5JwzJQXE1NV1RpjtEF3QlQFGCKXWzm6ajKkAYLlcmq6brTVK5hjatks+hBBiiIGSSMDuj8P+cDrvU4rROyW19z4mzxkRQoQYldKZEq1VmGdjdMAEiBzgfDpnDPM4UM3tOM/WRmc/fPfdYtEBYiBw9/Fj3XY5pRATZbSYvZfX/acu/qfzZ33o4XD+8OEjYzwjUUb6GKfZDf3EKBeCNbWehr42phA7CSE5QwnqkjBCCN4nH2MCBMDCxwgxIoEf7zA555WpNH9UFim/JkTB+XMy9t4X+Xr40W7p8X5HTOgRE6OirAP6oS94KCEkYip9vRFMKqmUIgBXl2utxavtGkLEGJbLbppHRKzrZrNeFxnY836f7CylxJzX200MKXqXU3LzvNss/WSLrMDd3d3N+/duHhJGzphSzAXnU5zGSSlVpE+lVPMwBesyIqUshKDK+CLnmJOPMVNGFG2aeprH0/k02IkrHnOklBYw7ziNSinKRcbIKGWRVG3NtVq2KwJst1nN09SfTufTiREmBeuapj/2MUbvgp0LrIzEkIRSx/OZMkg5p5iLlYqQIqVUetOmaaxz/TBOdhRCpJC8d0qq8/l8fz50ywVhrF50XKrSaSAAIm4urzGTbtWdDofsHGN87IfkI8GcUprnWSk52kkpBTk75zMlBPM8WyFkYsTaWVA6Om+M7LpWcxbn4e7j+6Yx0mgCaTgejseHnJO3LlMSYp5GGyPST/v7777/+Kdv30+TR8RMST87YFRKSUkO0QGAqYwQAoAwxktcM8YL7q6A9h5BTNNUbnwA8N4/K/EVIdzZ2hKUz4P3Ep1FbaFE5FP//kN7lFIKwZeCqRxjasE5ASimDjHFUs7GlHJMWmtTGVPVlORVU6ucd5v1qq0hhuViUanq7du3796+JoKtN5uurj9++10IjnJudHV5cU0pnYdxuVjdfP/BCEUyEJKVUuvVmrAkOY/OY0gpJS5NxEwYn8b5iSaVEZFCVkp1XednCwCZ5Eyziy5RMgcXUxCSUUaUlPcP9+M0xhgJk9vVVnE5jUPdtDmnEELs5+3msj8Pd3/6vqqrf/ynf4ghaSUwxO16A4DOOa11XbcFfliwsJTw2XpCAQGZEFKq0hd45wExp8g5985qaZSS2hjvYkqpaVrJ+dT3hJCQwQUXgp/sLLVBjKquKGIEotqaaLVaLUnAnPPFeqUoLWQ9AkwIEQNiiCmluq4yoxSgauphHKvKoHOKEkEQGI0pTONEMjIAIuXknDR6uL1xKXVadHUdESOiFIIzRqfB1lW3Wmhp2Okc3RwTeu9CDAEy8SEXPaDy5osxRkxAaQh+6IeIGBN6b2O0mII0KgUnJOMCSmxxLnwMvmySZjv7wJ7klZ/FSOCpxCwzI855zlgK05xzmQYQQjDllBwhyDjRRtInF3hGac5YSpVEgHNCad5tVwxI2yzbzZoTYiq9u7iqlXi1q16u65eXW6PU7F3Vtlcvr5N3lGRghBvx8tVb3XTzdJbdChg59/3QD0opwuU0zW4YJ9vHYG3wkmQtBa2kkhQzCTFIKRRgyjCPU87ZjZPPhDNBm5ZHcNGzTJr1GrSRQgjARkmjtdB1vexEowWnicC533NRccEqYx72t8M4Xr+6dqN/9eItgM9Ada0/3d0WmfMImTFWack4TxgpBQSqgNjTCQg6586nHkIs072ImNDnnFXVZsnMZiulEk1T101M/nDYBwKYo6D42dufecI5l+M4BEJtsIQx2w9V3UEkggvkJMV0GsdEqNIKiQAgkGklOTqPmJMPEDNS3i26xMDHJHWNhDCmTdOMs005S8Ki9TZ6ZfSI2F6/XCxWvU2ZcJopSYEXzYTzNI+zY4+Ta3rYn3IUztrJWsaY+YEjT2OMCMAYjzF475VWKYTogtG6EHkLADE6D5kAwNAPBUQSYxz6oTh/znYuw87nHqhMBJ9T7zNApAwESmKIMTzPTVNKSqtFtyhhXYYJiIiYCieEc660WiyWITgfAhDiXYjef/Hm+l//q7/67M2r9XZFGIsJEYhpakRMIeaUGlNJrT57+0VVL3LOjBJKCOfCWuvmMbtU6K/j1ANJx9CbRkRrU85+7HeLFSfEOjtNo9LGWqur2hiTUnLWPSnz59knIEQ1XeQiSyG0BkqP/bmUKABQVTVhjFDqY1RcdnX1D//wD/1wP45Do1ujFAWo6+pm/wCUaa2dcxjQBs85TykrpQghxlR12wEU74HEOGOcl4wAANE7SCAqEzPmlG5P+3EcuGaMU0WJ9f582n/xxRcQggDS1Q0DknOmjNh5pBQEl8ZUCIAAxbgDEUnKIQQfkAoOQLlUKaV5tjc3N6pr15ut0PJRmlhVSqocMeWcCLRtxxhbmGqx6JqqBkLO/dF5XwIg5vRTk/TT+bM+NKQ0zTMBNk2+lInOeaDUOV/Kf6WVlJJSSjkPwQNAuaAzICsm94SEkCilbp4fAR+zLRL059OpwBSEFAljStGFiE9tUAEu/eCg9XTKhD+lWLofAMAnGfny+Jzzqq600eV9VnIPYoopkSfanVYqIjJKtZF11zFOry+30bv1eik5X6/WXbcAgPOpL9CyaZrmeSaMEcpevnmHCEKI6+sXxhg7T+PUCy5TRJIz5KQVm9I02JN1IxO8MfVwfIgxupC22135qcZpOp/PIQSSkFGuuFDScK0zZ0lwuViAUMfzQCnlXHrvq6pSSnEuCSdMygjonO26ZrVaee8oA+dnNznvvdb6xatXwzxpbQrd4urli1Kkk5y994XOsFpvaq2ruioLDiGEC0kISQCVUoTSY3+WWjfrFQjGmsaSxJUMiPv97X/5m/9sKkMFm5wFzmZv27YFgGE4HY+H2bmU8+7i8pnVyBnFhEgg5QzwKCHvffzss8+2L68321VICSjVTfXwcM+AVXWVABmlMcbLi939h4+3dx8fPn1ijOvKaCUCYgHE0VprRvI4DIJzpZTWguScMPbjOEyWUppTYoxHRM6Fc66wBBNGSqnSijE2zg4BhnEs+0wASthjt36eRkJIiql8fqlivXfPQ83SP3HBKaVc/FCPlpv9WRwKHrFOtIQpeaKIAEC5HEvBWnDTAOC9X6zalFJM6dGcKqIWjDE2T3MIXhpNOMuEKlOVmWtbNzlnDGmYJkLI5eUlIZQTap3jXCilBZOVMVpImpOU5KIywc9IkzIysyyNIZQuFsux7yFnAFBaUsxaCKOUUqqpK++9nXxKyWGaM5Gm3l1cWO+ZUlLK8zB4a5Uo2EVbL1of0jj21y8vu2o5Dv1s+5SzeGLDNk1bMKPjONrJWzszKaSUiEkazZlYdCvM8XQ6S2FSTPM0FwgiZQQAGOFC6tXV5XK9lt2CdY1oupNzVV1Rkpd108+TS7HdrprNJgO+/+5PjNAYk/eBMrG7upz8nHzATCEhIUQwLijLOXNKMxJM6asvv0REO86znRinCMmNRVe6eA7GnPH0sL//eCMIRe/mYEkmAMD4I+iCC04FJZyBMcpHrwTTtcwklE16fz4/weoCISQEn2Ii5JGQBJkUK1jOubPe+Xh/ODAh+mkahsE5h4hG65KGOefee0R01hVW3TMQpPBaClajNPXlQ8UM/bFVypESUgzg4L/GiT5P/hERIJfv652300wA//a//OfTcR/cvFgs9udRCDHNM+VSShVCaJomIipjCqLUmJoQopW4v7+JMSIm51xdt5gzpiykOj8cBWFGqvN+nwd3uVy3SmklmsWKEj70Q/CRZphOJ8NkihG9VYyGcSKZphC6btG0JvlAGcMMhHFnvX8sH1PRTx3OZ8gREBMkwbmdpmmwTd1eXV4JoQNkY4xkguS83W3L0ya5mOd5sVgCgPfWWmdnP83+fOoRaFWZnCKhpFssUsQikhVC8OexW21O52k8D9v1Vlftotss1jupDRdcSdk0rRD0/v6+7/vL6wutFWOs67rFcplzHoahbPljiIzTEFOxQ8mYIeEwjD//+uuua7/97jtw8/7hvq3qYhK03qx89NbOxuhYAO3nwbSV5qJqm+DcPNsYIueccBYT0qbWUtKE0bsxxujnqeuUUEybR3hHSVSEkKJzG2NIKaWAzjr+iAt23odxHIZpijFaO8cUx9GmlDCG8gnnY3/YH6y1OeeAidHHU/yB/qs4I1D6KjvbEMJjuxrjcz/0iDRl7HmAVaqO4m/ivZunuaTqm9ub3/zFrwggIynaGVPmSumqBi4Wy+7iYtf3fdM0RalVKYWImOI8jwA49L0Qsm4bKdTFxVW7WJ1Op9evX2kh52GWTLiQh9uTChQDvnv9+Wa5WzRrJhQD1lS1txYSrpbLw/6uqcw8z3acx2GkmRZ5eUF4DpCQdM2CAcOYAKDEaLHIqevm3E8xp+Px+P2nPzrnIPH1ek0pPTzchxBK7aSUlFo94mwyeOeKlcBut0OMmdGUM6U0x4iIQoiE6XQanLPRuZASpRR9uP/2w3B7UFxYH0fnI5APHz7kEKLzLAM415+HSpuQYkqZK8mVEIwmH+pGC6M4pcAp4ywTorQCDtcvr/70pz/9l7/9m+VyaSiz43Q47DHGFMI4nC53O655xCw4b02lOD+fBwxpe/Uy59w0NSFEcE4Zdd7zcXJC8Jj8ojUEKJWMYKYZIGE/nKd5ruqKc2HtXFplay0mLH269+l4PudMKKVNs5imsR+GlFLwYdl2KaWIMUWMkGkGJVUMkTFGgD6r5z0PO8slniBTICmmGGNhGJdatnzrH29ESx1csuljI0lIijFjds6V4vjl1RVjrFssbu/uddW+fvkihjiM4/l8EpS9efVqu9r8/ve/V7ry3iultNYAkDIOfY+I/fl88eJ1P5wRUTBBciaM3z7cQ0qV3iwWu/lwJEAykd+9//D68ur2U0QfmBTRW+dsTgyIwATBTkqp1bqb5uzO0+Xu+hRtxRWTBLjK0fV9H91EBadSNFIxIcHjOA5NU2utP/zh/fpqMdux1svjw54zqKr6PA5Vs3TOcQIJIGMAIEII5ybGpNTaBs+AUCbt2EvFAOBwfGiaTQj2zbu3qqmPD3tCyaeP35kQuVAYcTychK44g/M0bbbbkPPs/bITrJIpeGct4cqlFKwVnFJCj4dDbSQmSMnZSCRnmGKKmTG4Od7jHHavXvKcRucqrYEIqas4BkAyzxMlHClNQKZ5ak3DU3A+jeMoK8m5iNanlBnP7CdW50/nz/zQw9AjAS3lbruzzjWmkVzEGErdWRmdYioiKkXWLPgQUgopYSb7wyHGR3/E89AHH6a+55SmlEqhyRlLBGKMRTUuhlSMY+BHC8+ngfzjKbd5qS4QkbJHeGi53J9T6fMXwo/0HdKTu9c4jj745WpZ2PG77frzVy8YSfM43N/dBR+cnx8eHgDgyy+/3Gw2Wuu+mOhx3tTtYrEhOd/c3p7P5/Vq0zbdZrNbLRb9OHaLNeUqpnw+9aRqu+21Eo1uFt98+ABaU8aVMe1isVxvlKyklMvVpti1uMkWn+3d5lLrSgoefcqUUC60Uk1d6crM8zwHjzkj4ulwvLx+pSvz5c9+5h0iRhdHSSH5QAh58+adlLIIalhrBWUpJWut1qaQbyGTYRheffa2bhoAiBgYAMYghLx/OHz4+HG0Y12pViop2TxNTaW5kvV66WPu1lsutcW4vNghZ0QIH2NGknPeXV0pY7SWh/1eEEoprdo2IxolQoiyquq2DTktVov1bttdrLz3SAnjmksFAIVVFkIgjCEBoSTl3MUoCKFSXl1dUi1KsCXE4FFwTi+32/44WUyc5d1u0fcnRDRaIuLp3J/6aRgGRByHcbauyIxBJjklXgR8vR3HgZEsOe0aJRTPOVVG5pwQveBUMqoFh4Scc58C4zQF70Mo93WJPEJIDDGGiAm98zEjIgafMpIYYvChxN//H9K+LBhjjDkDpSwiMkKkkiVMU8yr5apIN764fiGNsiFRQhgh2YfbuwdAPOxvBKd/+fMv/1e/+fqv/sWv7m7eBzsRiqvV6uLi9Ys3b25vP03jyDlnnC66tTCqWa82L1+JLEKK/TD040gyFdR03S5ESpniUnJdJ0rquo4ZEgUbQ6I4nec8D23dkpigt4qz2iijKkCWCXcR7Oy65fJ8OrthopQyoYKbx8PIGLu8uEREdEEIlplwKTEppmnCiELIEJ21llEqhZjmabHaDtOUouWCBheDd4QCJQSYUqZiXGol0M3JhTQGLaXznnEOLlVcUJ8VoYEACpIheRdo8MPDgURQgqXk+4dbezoNo9NaAZBpsGN/ypSOs6OCBoggGb+8Jm9fi8v17fsPExDwAfwYbB8gS5YxAeMyp5RDpIwYKTjFCdPuy7f781kRQXIWjDLAqjI2Bp5zXq5W5+MDwZSJIEB9jMBK9MDHT7evXl0h4jCOjLF5noypMDsfAgE0WoU+UIJC6EZLjNHUjfNxHAdKafAxGyoEcy6IoiDORIkYRCyTv+ADyB9QyaW7d84Vd9CUUunuETEBlIiEH0FJSsYtxWh5hAxgjBFSMCqc80+ET5Ixc84Jl91iMX38gIjWzpvN9u7u9nQepGDDafzqy6/7YcScAThX9O36i6baK83neTTGUCU2ametkwvpvb+9vx+sG+i4aB6HX1XTpJQoz/NsQ0aqBM/FgIJJwaRRwzDUhmMMF9ttipEJGlI2izV3ciYwu8FPYb1ZHz99kMbMs42QQYrb+4emVuv1zo5TjMg5l0JOZZvqXFNVxhgMsUi21FWbc27bNkQ3jfZ8vqeQ52kWUtTNIvjAtQJCxtlerrbzOCJirbtop+l0GKdzvdu2jTm76OaBc+GDU1wRKkyl7fk4O1drTaQ69v3Lq8txnAnGfpqapu3WOjq/n06SC60lWDen5CmrErk9HBeVwhjdMCmtJSEYY6QQQsqAKUYGgAA0w3l/gGCj82htJhStr6SiSugvv/yy61aYSdO0KaXtxWVBCgPAw/3JzrbIUxX8cpmc68qU9rBt6rqpjVGcMaGEVsooUWkDANM0YsoE6Dg7F+OP4CMQMIZYfDpDseYu36707EXaqR96AOCcM85STM+Js8Ri6dNL9oWnSX7OmeQslXw0Ca+r8sCn0wkAqrqSRrvoXry+RESM+R//8R/7fsiEAmEhhIeHB6mUMaY/n5RS02wr07TVYrVapZQ2q4UgzM926CcG5PXVtdE6ejcMw+xdJsC4ZEoFSnS3VPUiMYoMZCVNV6u6GoNnRvo4S0mH89na+XA6MCUT4223IJy23Qoo895LKTnnTd34aWaEaGNm5whj5U1lg5+mKThHKcSUxnFkwAhhIcZyewJATH62U8Iw90dGMxc8pei9M8aQnFNKr16+DtEJIa6urrSqhGSbzUpktMe78XzarTbbzYWuqrZdzjaYpnYhIIGm0sFZb+eu6+plJyqTfKzrKqYIhDCaayURAMe5iXE4HV7/xa/Ndr1oFylnAqxp6uV2kwHdNFHGiBIxZskYo1zVJlgX7bhoW0ZFkWCKwWKMPzVJP50/60MxR2NM3XYXly+Ct5yBnSZKafFhBgDr/cP+gVJ67h/trAvro6lrY1St1XqxqGrDCEgpgWQhxGLRdm2rdD1O03mcnbP9uU8A3vvngtKnUPDnAFCSKCE0hOC8n6bRRT+OY1Gxe86RzygTeLJ3L5UoPA2bcs4xxOKLJaUSRWj0aX4UZpcBD/tD8BEIm5yvm2XT1PPQz1Ovjbm6utrf34+n427VujkqrYHh8TgFHytTn4epq+uXL15w+qhlvlstBOeHw4Oz0zhOzse26bioQPDMuK5aQvk8e485AnCtqZL92PfjmXE6OY+QY44+hdG72/N+ihYona03dXeaRt0148MD804IppSZrWdSAGNGV0KIEF0ZjSGmnFBrnTOp2oYxUbYeiGiMGU89xgiUIiIn7Hw8BOdphnEcU0humqZ+iOjOdurHQTBCMZ0e7obDHRecURlTBkaPw8k5m2JkjI3j5JzjUt4+7LmU3nlFeQjh7uHm1J8Rc+j7aei/e//terO8/eaPLqPYLimlHnEKwWSiFSc0z7P97N27AtVLKVVVnZzHhHd3d4/sCUCATCjQi4vL7z9+qLvOJbRuYhSKLEdBW+acp9HOoy0Oa8/AIkxACCnOcYxTbXTdPEo0lqqxMIkppc65YRgL6TbGyDiTUlHCvXv0soGnjj7lHFMCgFJFcM4LkwEAuOBF0+b5lCgvH6U/OuXeh9LaM1Z3HeNMKCW0UlqdD0fB5d/9/e//8O23QITUOiWoJOE5RtcfHm5eXV0savPu9SvBedcuV6sFZcT5OM+BMTWMozHmX/zlb15cX3IuOecvL3edqaydQrB2nqZ5VlISQtbbC0gkhqyqOuWcMgRMiQAlHCEzI0DQBHg+HSG50U/dZkk5DSmslpvMBVBFOY8Zx+NhPO3P/dE5J4SQQkspGSFDP67WqyKRN45DWdcVEUZrbXCuxGhdV4wx7zwX3HsXQwzThBiVUt4HRtm5P94fbncvXibKbIouhox4Pn368O13GUjXLparVVNXSLNpGztboSTh7OF8pEIqpZSRyVpG6aJbIIE5hMjoar1Z1O383Yf5/q652jmKXOvd1ZWk7O7jx5xzpCQjjsNYXi8A4ECm87k2WmjJOKMMAEBW2qfEr19c/unDhxCwabttV7///vuUkhSKUOGCC/iI1cCUY4gUeEoJSAFRT5vVknFetp0ZSEiJEAKZ5Jx99M5ZSqvSxITg2qblnNd1o5WyZZsiZMmLJdoSxgIyqKo654w0Fkbej2dJRfO3nB+z6UlpzymllHrnuRD9cOyWOyoopXSaRs45p2Ts+74fv/nD+9PhGBwmTNvN8n/313+5WHXWhcP5CDFvtq/Pp4GxcPPp03rXvXi1e9if7+/vI4KR/Nz35743WnbLpZ2GcRy/fPvun7/71juXUvbWisoAj4xzLY3ibE6OEUkoqEoCySCwahfH8UwokUomF7wdshIRMWNmnFxcXP7un/7h6vLyeLx79fXn3/7+D3WITddkoIQQ56dECcn5YncRfcKcYoyU02maAGCaJgogGBntLLT0LlhnjVRc8Bid0qxpKh8mLsQ4D1zQmDwTdL3bCF1R5bgAGgMXmVDMADGGqq37hwPktN1d3H/8XjDKOQ85NcvFar26+/ApxIgRM4EoaAhxc3HBEzmeB7VsKSOZMlYL0Wgaws3Nx+A9JWSe5hRz1Zm725sUo6wqSHg+HAgTBDNwYqdZ8yyVmqwTTFA/DV3bzNY676tuWdUtl0qadnv15t2XP0+IRSQMALyPIabSLeaUtNR2tm27kEYrLghnpjJKKy64kKKuKsLZ8XCY5r50387PgCiEKBlPCJlyzhmegSMl4TvrCNCcEQlgetQkK00SIhYM/3Or9EMSfRKRkEoyXhZVBSNFjVGlW0LEbrGa5wkRteIphsoIwWi3bLWUXV198erVqxcXV9u1MfzVq4uE4Z/+6Z8/3TwYpTar1d3tw/k8xUQOh9M8hZxCXVVVVXEp3r56dbFe0ZyAYAg2Ax7399Y5Kcw4zDlDDIkRbkf79rO3D/uHnDL62JmWUToOx0YZb/1qscQQpuH8+ovP5qmvTD268O6rr5artXM25xydN1IVyLpzbppnwfk0D3XXSsmrqsLoC762cG5NXUfMACCFYpw563yMVPCAoTDZCSExIGXSWqtrM05TyshVlYErww/93fsPf0LE4Kxzruk6oCzGyBlbrpbjuV8ul6KSiSRGyHDqpVA0UxsDZzIPY5z91bvP9r//A1+vTv05IDqIkSRdN1opHyM6J6WcZxuiT5hiTIKz4LwUzDrnrKNACSGUZDRSvXv7RlJ2d/9w/fLl68/ehpCVqqRUP/v1r5umYUK4EHYXFwDwDBCmlNZd24+DEFIIqbVRSpU+nRBi59l7j/SxvhyGMyHEF4xSeixDn1PgE14O6RPePsZYqIbPOk0xxhKd5QHjk4XNoxzzEzaK/khsLKXkQ4gpheAf4c8pZUIZI3/5q1/8+mdf/eyrL19cXUzWYko5egb4+dtXba1XiwWj/NWL69effYZeHY77/nxqq5pyYa0XUkupAODc98rUmImWar1ZrpcL7/08zyF6a+3sphDCarFsmoVSen9/UMr88f2fYojuPF9dXPnZVto0TeXmyQgdfVJc9MdDghR96LolzwQySYRh9F3Xaa0LBUpKGUKSUq7WK855P5wYYzlhgS5M0/ToZhE9JlrVi+LbKZVUSkdEJAA0c84IIUbX+4fTcb8fh6OUElMenGWiGcdBabpctVpXSppx6lPOddNqxQPi3e0dI/RwOKimoYITSiRjlZD3n26idVrKODqi5FQbsO64f6ApUsXlolVccKmcCxfXL5V8FB+gGSghMfkYIgeWUjJaewwkZ8Z/0mb66fx5H8qE3K7bVvFlV1eNub1/+OZP382TPQ6Tc67S8uLqxebyAogIiUhTcaFTFISQiBBDyjnHGCY3F0dhApRy7jMKKQWjBNHGgH7ymFgiAfI4zd6FMoFnBFKKBIAAuBiKfC5jLGEghNRKP+42EwJA2XyW3Fl8GnLOjPFcREPJI2SkCB8UlGBOkRHAEHNMQLLPWOuKcf32859HKhmnaCc7ng+HI2ZYb7abi0vKRYJsXbj/+PDx40dVy6uXetUtL9bbq5erivPkIqX8PJ+7rru8umBUJBIJo4orLdRXbz6rNLPD3Brt5gkoFZnH0XOkjZDMI51xV9U0J+4DTYg+ATJGSKeqh7s9+tzP0/03f0JK7h/2UrGQYqOlUsr2Bx+yS1kq3ixaIRjmdD73ZROhtfbBSiGqqgrRc84JlbUxV6/enCYbWRZckpwpiYJxTaUEZr2dZjtNvZa8FpDuzlPK2UejGELIkEKMIWfnZqUUBYBM5tmGmGttBAbnhtV2xTkXSmXgEUkEooUAnKfjIcWE5wn//vfj7cH+7T+TmDSvBOac+EO/N41xhJp2HQOSmGmiAbNMZPIzpUAohEwok0wIN40UEUnO3s0X2/XPv3h7dbkRFIRgEP12tb7Ybtar7sXlZcTUDwMXKmWSIPXTxClgiIKxMjNPT9YIknNBmanMPM0ppRQiJYxz9fH+/nzq7/Z7AEBEwbmN4TngyvTqfD4V+PCP4Uv5SXvs+V1VatPi3v5cjT6XCpTSMo723uWcQ/DOuv7c98eTdTMBXK8XBPF0PsUYr6+uurrWSnaLTmmBiOM4HY6ndt15TGGcRKZcMdAiOhdIqBcVZ+Lv/uYf/x//9//nv/93/2Hoj3/1m7+ojKJAukV77k9V1XBCMSWteMoxYGrbVgq+2+xyjE3TCCGbbhEQCWeUUW+ts67v+6qqmqZZdqvVers/ndvVYpjs/niMBHa7C845BWA0m0rv7++DdW3bzdMkOe/qtqAzAWAcR0SMOYXg7DQhIudi1S1TSj5EG5z37vBwGIY+h7RaLr0PpqkexjloUXMqFKeUZ8ojZYSxlBJlxAcHDCY7qkoDgJTyPI4Ph9Ph/sAY88FlTFQwygiVFABiiDElIcX5YZ9DWjYd5EwB+hT4brm7uOxjoJSeh6PqDBM0Q1rttrLVVWXGeSxFmlISOCWFOIc5cQrGyDdXu198+e5qu153leJ00WgScbHolm3HOT8M4/7UD+OYcy6Wh1ILSiknLOfsg4vhB7wmJWy9u7A+MEJma9vlakaIKTHCE4IQIuEjZq+IrkDKGQETWjuXARb8aHVUtqDP66IYY4yPqiTwBMJ/ni6VShQgez+H4J2bMMdgXQjh/uH+6mqnpCDo728/ns7nz9++ubq6qqqKcUIIwZxVZR5OPWOsqvTp1I/DkMLs5vM8z926k1J2Xfsv/+W/XG12+/3x73/3d/+3/8v/dbleXl1ftG317u3bSqnddru/v6uNfLi/9yEyTijhw2m4XG+8mzKSebSZEqoUE3KxWGKK0qi6rc7jMI5jyuTzzz/vzz0iBgTCpQsppJyixxABkTFW13VKSQt5uL9njMXgAeBwPMboqXiEMQfrCufzeDikmEL0iIlzjjEm5zmlNEPXmBCCXmy61y/zbL1gPiQQ0ixXmClQAgBIUBtNKM7RB0yEkNev3+52l5vNJoQwzxZzqqt2tuPs3bOzcAxRMSaATOMQjgNh7NXFSz+fMyEvv/icYIacVNdEQCoF1zogxhDqqko5A4BzIcXEBeeV0vM4cEq2q04reXWxvbm9V2K83K4WjTKGd0019qPWJvq7EaDZrBmncQ4hxrZuOGd1VcWcpmlilCOilIrTeJqmlNJiuZ7GvmoXAcnFxQWNth9HeX//6tWLEIIQImIGljPi7ENKKRMyjNOCtVKqBBkROXmcdMYYf0ihP9p5lkHaj0dRZRaLMSJijC5nZIxyQRkSCnm3Wd/eP1xfbtfr1TiMSvKL3YZSWhSlYwj98QQA+4+3p1PPFfv9d3/4N3/9v7b98B3jLHGpWT+chVa//sUvx6nnnP/hm3/+t//2327X28Vi8fOf//LFxcuE8XQ4+GHOGUY7uGgloV1dN3Xt0px8mMYxU1ItlufTOVM4DafVYvHx46d1097f3oBiFKkS7OE8tvVqmibnRvRuUXX9MNjBCqVTACYkIP7qV7/+pz99I6Xy3i0WCymlaavJTQwJZUIqfr+/owAZoKqrOYY8zdvlYrDzue+nKW7W3ThNzfaSeJcxU6qaZjVS0i6qRlTncRxtX0nhnY3eA2VaiPuH+7eLrwDj8XgkgMroHNG6iUJWVZWc5aKAVIERIipJgPVSpHnux8lgQkZTCHM/bTfrj+NZCO6iJ9PkUlCEzN4rKbngJKFznhH+U5P00/mzPtx5KyRr24ZRCoS6abrYLAGjdeH1iwutuOSctW1T14yAoqQ/n6WkXbdYLRpKH1lBXdUgonfBWVfWSCkl56JS2kabKWWEQCZV083jOLkwDH0hxyAhKQFiDiE4Z621jHLrfURk/BFIn3OGTMv6qBSaZT723DM9T+szJEQoZFGSEmOlmlHTOEkh7OxNpUjGaehfXm3Pg+WUrhfLwuzJEIFkgrkyZt013357Qyifz4d3L66uNh3frY5//42b3Hq56k/eRai5YUJQxr74+mefvXvzD3/3j/uH47//D/9ByzrmuLvYaSn38zQ6a2cnjeGcY85u8l9+/mW1WJyGYbITkswEW65XkLE2khCyWLWM0f3d7W69+eUXX37zx4+6MtpUc0TnPVfSKJ4R6tqkEEjOwKj1viK8bTvCyDDNOCbnXEioiZjtFGNQSCgnAAARKcHxfGSV/uzzd6eHY1vXp4/98dvvNMmiaXfrq4mSptbzNFWEK2lwmn1ImOKyW7mUIUcG5Pvv31sXXr+4dtETRqfJ1ppSQsIUAJDSWPA9lNJpmqU2F5vd/TwvVBX6KTN6+/33WuqPD3u+WlLOQkw6ekIJpzxkpIzOw8ylkJQ9wtkypKbSs53q2GVCqrrawPpw/9AuaspoTuBCuL+//frdZ0Kp79+/l0K1VZVzFpwvV8sYohBCC0WwVIeRMaaNhoz9+UylHCdLICCQFKt5OMfoV60xpuKMUUpdSBij926cZp9Qk2xna0xVBq4xxOcmCQu9JmdMUGgh8Fin0kKkpBmQpNLKC8agsJ4o40KklDKkShttzJefv4vRZUIZY1RQzoVWykfImJRSCfJXX37+n3/3zy76v/7L37zcrQEyCPqrty9P49B2bQzz77/fE5U4Vxnw44dPv/7VL15cvTwejz6G6PMwT5O1isN2sXQ3n4oJnTf69v5EgYYQckxtVU1nL5W0ycpKYYgiRO+tNHIcxgyopTzcPWwXy7pS39/fFsOJpmmO53Nd1wCwXi9Px/3f/va33WrhT8P5fOqWCyGE9xYAJGFt256mXgtBU44pEkkoQEgppGg0P59PnIuxP0vBvXOJcsPFffKaG0Ip4yzaGDDFFBdNd/fpvaCCcRWz54wxIa+uXo6ng8OIAEorIJlkmkMgAsrUJaQQLTIhUkpna2lwtqryaiGAvXv77vhwcKccp7lW1dkGktBonSZHKC2EpJyQUIqYKeHMWjtOY0pJSgYAdnacyfVmnSJGnyijU0jb1frnP/uia/Rnb9/EGENwldFaawDCBe8WnRSiAHtjCjHGD9+9Z4zjo1H7NM3zZKdpHCcX5skyIQlQzDmmZO3snJ2dK1Cx8KR18xyaP0bRl7SPiCnGMpd+vgtKk0Qz5JzTk09N0UTRWnPOpZRN01SVaRqDOSvBr68upnE2WkspJeeMcSbFerXebRf/h//hryuev373+mLVLhZtCOH6Yv32s+vNov7Vz95BipiSd3NG/+b6ahrHaZwYg8qYTOJqtXr54pX18XC/X1WL6+0OMEnJu+V6d3W9PxwO/elwPvXnvu/PBPPk/eF0GIeTVCJaxymtq3qx6N69+ezrr77o+/NnL19cXVyFEKZ+kJzP8zyM/cfbT8D5YtmRnFfrJRccEYukAAMmubTeTsOJICBQIUWwTjDOkAqpok8Pt/efvX5ldN3UC0ScKN3v97JVXBEbZyYJIbDZbljh3Gp5Gs4ppUy5S5Fw8unT9x8/faAMmBBAefTpWR6m3GZSCCkFAMSYOlUzyVmGbrNxzu2H3nvHCBEu9v2wWK9ixtFa5z1kEnwsfFEkT8NFxliMMYRICCilhFKUcka59z4i5gSIeHmxSdGvNqtu2SQEknNVVUUiwRhT9My1EkVfpUCWKKUZce7HEmS+8EhCAIBC7rZ2tnZ+5GpiLr42hJCCcCkk0ifM/OOuqOBLyu9jiCmm9Dw3oBR+1NQ/P1PFl7Y49j0T8Lu27Zo2xQiU5ielUkEo4yIixhi+frH7xRevAYKotBRi3S5YpXab7arrNst22ekQo3OuNVpSPI/jqT8QQpjixqhhOI+zXW+3lar6Q//xwwfI+e7mJviUckYAU9X9uVfGZEjn87Hc3T54b230XkpJBP/w8a5qm2+/f2/autZ6vVhmTNbOnFCjpWAkc2KDbbs2+2CtDdY657z3nCtExBgDpsqYGCIAYIIQQsE1A0BG8vLq5acPHx/u7hartXBYU8YEcX/8g516zEFpnjCcTofa1OM4dm23WK99dMIYbUxE3FxslRYxpc3u0vqgajPONqEXjJfnk3D2+GLFNM4TxHQ+77//9nstJSrWDz3BrIEQoJP1LgSmZFVVxbbAh4CIVddJY35qkn46f9aHEkKUrJRQjDHvgpAi5+yinawFACUE5qQ4NaZiQjTGQAzbhVmsOsGFVIpyTjgjlDZts9tdvry8fvniZdWYmJEyUEaYSq67FnJUjCwbvemauqkR0ccwjLN1Yf+wv3/YO+shk+DQ+8QYI4BGycedcog5Z3xa3AMhFGjGxyYpF0BJGZeW2RNGDphzZo+0ZuRPB56GUEorAPDeaaOFkJRnLoTQlWCMFHFJyf+3/+2/1kprY+qmvrjarroFQBbG5Jw/e3GJKV1suv/+X/78X/zFF4RxpmREHPppvVp99uZVV5EYY8iwubx88+Kzdb243O2G/nh3f1frCkJSdW0Yp5Esl+tGKcLY9bu3zkfRLA77fV3XkeM333+3vtpVdfPzt1/87h9+V2mjhLE+JuC66YhPKcDxNHGj53lmQLVSlVYlb01uwhyQkHq9sugDZsIYMEI4wwSQya5dfvf+A+sW7z99G6qGaYYF5zpPIsNwOLGaRQDrZlA8S71+87JpW6aoadfatBno5eUrTsWnP/3pYrMoJRMixoRj8EIrO3jvYvQ+JTyfexwiz7CuW8ZYdvH6zWcZ+ACoosPTSQB9dfVKmG4cp4TIc/bBFQAGN1oPPjDBMOQQAlCqpOz7c1FoL6RKzjnJGUjmnF/sLsQLAQA5peBD1bSUEsKpEDLFoLSevVt0i8ViWYCoPliAIARv6jr40HZtXdfOOqXVk2BJKjae57730VFPHadSNy7E5omo6bwX/JFeB4SQ/zrvP0NEETLLQAhBAvA0GS2fzbngPBbyUPm16drZea01YzQDe3xkQkrVlXN2zDVNU3QQyt+kJMZxmq3drlcZ8PXLyyKuid55BkwSrauH/V6btuuWSscYknehqSqo1XF/a6QqZIxpmgDyerMFyJ8e7mQtKcHz/hwCRhspAmMsev/h+w9FMKL3VlARc6aUMMFTSs47o3RIWUnOKGhd9dbFlEo3yTjT2jg7C6VjCpgjFYIRVizdy5P27e2H/81/+9cfPt0cpvT5m913d99hzKwWIoRwODJGKa2lYIExJaVZtNZ7rvVquRiPk64rwVhyFhEtAAGKKWGIwCihpNY658w4EUX7jgTFRU4JlPQxmIQ1F4f+rJXyKYGA5bo7jcebu1tJZIgxI3RcGF3N8xRDpDlnSmkI4RmSXMBa8zCmlL0NKaYMKJWQUiqtVuvVar1q2kZKWdXVc13IOaeMCyEFl5QwRiBhLADQ+4d7rUUJNSGoVup2//DMdEMCicDsY0i5qJB6TCngYX94QuJBSgn/64VnhkfB2ALGexxIIUGgCDQhAQAEeI5lwXnh+jxKi2mtlFouFo/LqkxzzgDp6d8iKCVa67qpS+1flHsFZZRSwfn+7uHqYrtbNoMdo3cVZwyI9xEA5nm+u7vr+55QuLjcKS2dc4qr9Wp7fXHR1E1T14vFAmJKIVRSKcpuP35iSDjl282mNkYJGb1/s9395ouv1lL/1S9+/e/+/X94+eKVNrULPiSs65oCxBgJZj9N0zAwKagUzjlKCGNscnNCnKc5ZxKTo4zEnGJOVFIbgk9JGz0m97C/70/H1Xp3e/uRS0UoU6ayw0Cc9eM5TlO36Ezb9MfTNNphmmzwNx8+Ptzc5hB///vfj7MLIVxevNifjjyD0ooQwimNKaaYaHEWxlxVBmJEgO3l5f7mBiFHH9arZT8MNCWb8DScKSNV08zef/H115TSTAgifPb6HS1CZFyKBDlTYq0tLYhS6uLiAgCGeS6qMsVOpaDlS8+RcwZKU4o555gx56ykZJQW3uaiacZxmO0YQ3r16sVi2c7WEgDrppR8pevJWQAIPsSAQz/1Q2+dI08KoLf7h2GywzyXNX2GGJ8mTYiIOZalZ+lbAX4AlT4m06elaPHvooRSSqWQZeTJGCdESKmYFMZUT7RPgvhIGeWMSSG7tquqmlJqtNFKaaULhcTUJue8aJvr7VZKSYAymgsgwc3jerVsuyZjPO73bh5Xm1W3XA7zVNd1CIHEFEIATEoImnAeJpLy1eqCEcaI9BlvDnuC+fbmZhjGum2ruv79N9+sVss/fPPHly9fXlxdMUbnYSxe84wQN80xpP3+oYBfoagAMZ4gdl1LMAMjKaaUEElOkIERpfhnbz4rNvcPh+PpcCAIDsFIPk+9TTHn7EM4Hw798dBsVqZuDvvT2E9t0xFC+r7v+1O7aL23kFM/HKVWQvKUEuci/+gF8D6E8Cg250O4+f5TVbdMCI+J5FxvFyFlJjUAxBBrYzhjIUyV4AFxd3n54cP3OWdKgBKgSmml1Oy9dwERq6pmQuQnS+PS+RbwJSFESNE0bdu1iMgYfwwVAoSQRCDnrLSinBS1oxiwbRfDedztLpRWdd0wxiLiPM3707m02wkxhDDP08P9w8PDQ9+PjIrJugJKCskTQmIMTzf5Iz/pOQYJJZgQy0w05x9sRHLOGQEel6KMMcGF4BzyD361TV0/JvLnpQAApY/Gc1prxgV9cmySQiqlKJBuuUg+UUJWy83+7v7zrz5PKTFCY/R//Oaf3TzO46C1xJzcNEgllstumibG1WKxqJQ+Ho+NNiklLcTdp9uUklGGUvb9h++7ZVtV1bJrnHPf/OmP42gxQ1tVP//VL5KdpRTXlxfTNDn7OOJYr9eMMclERgQAzJkyYYwRWscYCWfWOaFEyhh8opwDyUDp6Oa3V6+k0OvtduqHhGTRLTNijJZybp1jlHKavfeeQBY8evf5Z5+t2y6kxBUnki3XC+vmnJN1s66rlJJzPlg3T54gcMGVkuXJLPce51xJ+erlq+xTs1oSxtBoi6lqmsYYY5o//eGPlRTvv/1jxsAEm4Mvq5yfuvifzp/1oZTSmHMGCpnIojPBGDDqvE/pUfRGCJFiKgVcWSQCQNW0ABBjyBkJoZBJJpQRRimVUtZ1zRiXVAghjocjAKxXK8ZFjNGH0I/T7d1DcVI0RlbGrFbr0kIppe3sDoe9MdXpNISUCpDvuQDNORNgOecixlKyJD4dAMCnf9tzki1fBYRQKgAY51woGfGxbikP8VzRAuRn4miZ9Zd0WwQBlVSU0uMwDn1PCDG6ury+uLn5RJjIOXNCpZIEIKU0z3Nwbhj7UgVevbj2MUTElNJnb95IJdarFRP6Fz//1XKxcqO11r757PXheLy9vV10q7ZqOBOKsa++/BIxE05/+7u/wZhubm61lItuBQABgw0eETljhBCXQsCUcu7HAQCqugnB100bc2ZSCCWcDUw8iqr62fXnYbe7GI7n9cUFp4RQKplgCVlCjJkx5q11yatl03VN8vH9t9+ud9vr16/ef/wQfOi6rhR7jPJ5tKXAEJwrJdGnQq/lnBBChKBa8nbRlnY4Z3IaB7loNu9eI8s3Dw+8aRerpQ+27tpE6epi52OY53m1WtGISIBmhISAKTPOgfKc6f3+UFeP4q6UsKJ4E0IoscgoJYRI+TgJyviIiIspYU5AsrX2eDhobaa5n6ZRKvmnP/4BAKZxmkbbn88Ph5O1wYUEAMbIGN1y1TV1veja3W5b4Ev9MMzOxSeGMTxr2eVcxkwp5vy0bcqYE+aUH//LT0UqPitDYJk6QXnatFJK6ZQSeZQkSaUYeI7p0jD9WLak3PVKq/vjqWnb2TmSURo59gMhJOVIKWNCZgBpdFEbvb/9RFIgGG9vPkopEYj3PvlAM+wPB8553bZ1XUNChnkcTyTG168/O/fjFNL/97/8be/sb3//T68+e7c/7JEQ721OCREPh+Pl1WXK2SOauk4pCSmX2x1SSjmrqjqlZL1Dguf+zIVglMacmWApZo/pu4/fvXn35t27t7Wuvvz654QQb63pOs51USAEROe9pCznTKVwGPvJmboeh0nXzdc//0UMqT8PARNl4rg/csFjzoQKQnnwIaYUC72RE+e99Z5muP308difM5djP3HOfYx8VW9fX//8X/8r2rQg+HGYqm6tF2uPebneEkrbbkWtc/HRj5Bb73Mms7XTNNV1AwDeu6K6EVLinHsbcsb0tH8UQjrrniURix50gbUv15v1etv3Z1NXp/PZezfOQ4whJZimMRPWto21dn849GN/7vsCC7BuHMfR+Xm5WjDGrI/BxRixkDl/CFDMAATxB5DoY8qEnHJGyJn8wJR/zqz5STI351x6c63UY9xDAgACjPxIyax8SRHqKf+usubPKZ2HkTJQRmdExvNmsbDWaq11ZSjlXGohVIxxsWjP57PWUnGWc04pCCnP5xNjrDgv+hgZ458+fWKUtnWN3l50m1//8tfjZGtj3rx9q6j46vMv/l//7j/GEN/97Ovbm08hOApgpLq7vbt8cUUYBYDtdns8HrhRy/WqKLjE6I2pCAEqOFJACkAyABBKCCF1bcyq+/nPvoqT/frrnz/sbyEFILyfA+Fgc6CMCc7nvnfOTdauLzfCqARZcDX2UwhBMrlZbjIwxqTkys1WCB4pIYQgEsH5I5QiJyEoq5T3nkVctt1E8m61Op2OWkqb0nK9GTCtX13xSr/78ismK9F2x2GcBtc07eFwoBjjIxQDQ8zpOAxFoCEEP/vIpJyKUV9I52GgghNCGYGImIECecyv5VUHigDAmTCm2qyWGTADQkzTYDHn3W6LEZWUSgvnPSJu1mtCyOlwwhAopSHGabAxROcskMw4qVvtMUzDbH1OMWOmkCkmKN08QI4Y8mN/k1NCkklGIBkwpIjPinkpRl8Ez3PBQFGCKQNATIlznp/iPuUfNvuEkJJyHwcBJY4T5IxA6WWnr5dLTljEgDE/nE6dIH/xxeuLzerl9VuPeZ78HOL9/vj1L/6FlFwoLhmoFHKMrTGMQgbedksKcDzcVUyP43hz+7HT6wzp7//+7xWhq/Xu6uqyW1b//Ol7irjZbIfDyCmBnDmnppbBp6EfpmGeTkN/OmKO8+m4vztvF53rj5ywwTtpaqOqWigXk+EiAEjNfvOrv0oZc4Df/eNvvzl9+P0//S//zb/6b/p+dMFTkjinnaoToo22qTcU8zyfcQ4VFXawjVRA0zROfd+fT/sYY6ZcKKVWC0YIDc7FmdKcU6qlYDT7QH1KQnHz4rLulBVSMT4Ox6v1dpwmhox39Uz9nz5+S6T+7JdfdJtlEJnqKjO6qC8Y+wkP+tP58z405ZwBc86UssL0Hc4n52wBdhhjKKW+CH3FyBhLZXD/1LUUp5z8I5xR+Y3WelE3Wpsy98aUCCEZ8Hg4fvp0s1wu9/vDx08fnbNSyQR5nidG6WazSynFgEM/9P15nqx1Dijth6FUpYVGXL5diJECe/6Oz31SzrkswPIPRkoZ8g+6jc+fzBljjCGBZ3BJeajnWz4/w1BKO8kgpRhjXC667fXWRX88HUPwY3/+q7/8xc+/ePPrz3fXa+Nt6m2KAe3sMGXnxWDx4sWLm9Mn4voUJpd9oWhzqTCzQGK7aDnli3pxPN/f39//9//d/yAZd7O11r3/wx9/8YtfnPvzdrvdXl5Sxqy158OREpzHSUsuJR/HgVEqGV9W4nb/4DIVqqKCcyW9d16qhvEZEw2JEtL3wy9/+cvT6XjYnzhT693lP/7+n16/ei2lTAE5r2ywxghItZQyzKNCMU+2Mc3XX399DvMwzzHGi+urlDPnfLVbAYBsuiCkT4krHnMGRkJKSCBD6lZdRk9JipkRb5umAy4cJsZF0zbffPN7ZcyrFy+MMb/9X347TNNms9Vts7rcfRqOzXZDA0afAhUcGOWcS8mqRtd1U1V10ZqbvZutrauqqevyspVtISIWaBIAlBH3D/0ygFL64vLy83dvvHeVlsM4jsNoZ0ue1uhVXceQxmFUSnMuCsRutpM2mjF2c3PrbJztnCI653yKo52L61yMEZ93SIiQaUw/bJUAIGMukMTn6EwJCoEu51xu+RJzj+uGp6CEp9Xoj0tb8nSeIpgIIb/8/N2fvv2j895aSwn75S9/9suv3m6W5ouXF7/66lpRVFpTwqQwjPLTOY0j+fbD6d1XfyWaRYjxD//wd9N4Ukosl0tTtcM4LherZdd98/t/utq9md10Oj6sVovPP/88uvji8vL+9qY1NSFkmuzu6nq53mJKnBJAlJznnIUyEOB8OCnDhZC7F1ceMhNimkYpjOIqccGUVkpCpqZWk7W7q5dt011fv2Jc55zO53OMcXd1ObvEqLTO7XZva7PIk51Pw2K5GKfxYf9QbxabFxfjPO+Px6qttZE3H78P0Zu2A22a1YJSKhUPiIlk6yKhsNiuuSCnfr9Yb4mfjw8PhLGma7tu2Z/7YklwfXExnI5N26ha9adxebE7jr1cVjZHSigFgHmeysvHGDNSM8YY4/gokhUKYLI4cgOlLoSyQCKECKmfszE+iSADAKZca93U3eVu27VtXVUAMNlxGMe6qqZ57har4+mEiPd3+xQzowIShGg/fHz/8LBftMtz3ytZTdPYz9NysZhmW7ijKcWYHwdI6eng05KptFA5Q8aMmMtn55yttWWfUsK6lPDPkVdWnelHPg3pqU+ilJbmCQDKyIITenm5ub7cnk7H7e7Kefzy3RujhNY6M922+v/43/0rRkkGdCFEhNNwRiKA1O/fD55uLl///NXlZ7WSwc4p+BdXV69evP3jN98aYy5fbHLMb796+937P/72t7/9T//pP1nvFaXfv3/PKc0pcanP0xRSElzpuvLejcM8TbboKgouDtPY6urm421keRr6HAMigg9RCt22hNGmXtwdj+fJ3t49vHzxelG3X7x7K43mnDNg8+SA0ojZ+cwIpBkbuawk7fvBR59ZPpwONMPFdjuMZ+99358F44KTYN2Lq6uQQsIYc+aKB4yq4lww630/BQoYQgAkWsryVt8u1hCiUhJz/vTpptDQwzjnlA79UbQKMVJATgAw59LIFyO9gClHzACMSSFYfvJ8KRFZ8KSM8Uerg5wJhUKwxBwZFQCQUkoxCSGy919+/fXd/YEIdj733PPoA6Hsw83NYpqmeV52ramr8/ncNDXlfNj3UrIY86ebm4uLi48fPzZVZa1lTChGnXNcSUopf7ReiIxxH4IkrPxsCTHDI+UDUyLlWieEUhp8CJg4EiQEUy6aU+UqKO+ux3V+ena6wfy4oIeCI8k5FzxJSbjLejE7O07+//3v/j//5//p32itgTJKlUJ891IQQmpjgkyUiQgJsyeZ1+3isD83Vd6+fDcePmhlTuOZU/qXv/yLV1cvD6fb779///rl4rC/3yy2lTaU05BSTvk3v/mNda6qqrv+6GZffkAKdLO+yBlohhQtFzw6NyfiCVxcbKZgvY+C0RRhDr5qDGeCCM2V6ec5QOoqIrjsqup3f/ufy4rbz05qTQTs7+6/+OJX+8NDzRdSaan56KMLHiQhMUXnUghcynk4GqlTjJyL8bhnOWSIlDFOSM6RCpoBOSMhIahGcrz78P1y/UqwKDX7+OGjeTjGEIaBUq1Op6PgLDnvx4FKtVx2Nx9vW67vz8dHNQTOeQxYXrNn7HqZzFdV9ePRYPCBAAvBh+gRsQiJuRDck7wMIQQxJYzL1XKz3bRd+/LlS855DFFK6YOLMa7Xmz/+4U9t29ZNQylTWseEMUapZM55mqaiR9DUdbGTm6bpNA6nYZpHOw1zmW0xxjMlmZKYCSZI8Tl5g3fReZ9i/kHx/qkqLUOrkinTE/ynOH5jjgnLXuCHpUApXktchhhijD5FZ50Soq7q4+EwTJNWKiSkVBICOWcXgtYtADZNm4I3slq2KyP1bEcm8u766jjHYYrdYtW1i+jD4f6ma6rry8/+5W/++nTsu3aRUmKCL5dL55xSer/fKyn3+30uQ76ISOmpHwmhdpwAYJgnwVhdN5tuvbzcDMPg9w8kRjdPUmuqZGTUT1P14qJZbihn43kul8PDw/3d7c3pdCxEnWN/UlpLJUlmSihTc855dAQjMpL7w0kTEW1YLFZGyRIqTVUTwhojD3efbPTFFNTHWFWmRMLt7e311evlctc1ilUVIp73h2VVT/Pctq330U7OWZdjmofxfDhQyCEEzqioFUj2Uxf/0/mzPpRSSoA6FzNADJhS8sEn9CF4SqmzQQohhLDBW+9dCIyz6N0jyo6RGGMK6G2YR+tj2eQ9JieldFV3SukvPv9iuVwuNmsCbL1ecy2urq+vX71sqhZzAAAuFWGcUMooL1du4YQIKYSQlWljSErqkNGF4GNExMnaBDnGUBahLkUbQ4o5Bixq5TFgCCH4VAYQSKCsbUMIIXjvXYwxPiGhyu2en5Aoj3Im+EMv/5RQATERAlwIoQWhWWuxXXZSCSElEDSaU4A5ePSjEkIwqrXOiXkXY0yISCX57rvvXly/RtZIszbVYrlcS8U5I97O1xdX//t/8z83qtvv78/n4+lhj5j7vv/mm2+GYfh08xFC7PcHiEEqXtemPx0JICbXdZ2zjlJKST6c9/PUZ+dJzoIrh14JJromEOBCC1nVdX19cfX9+2/3h8NsA1N6vdhc7i5SCEYbTGTR7U6n03pz+e3Hb1NOlWwUV9GnzWoNKRthGJDoPRNymsbZhX4Yh+FMBY1AEHHy7vHCCSmm9NnrV9bNNgCGKBUPKXg7C2Dd5YYowbmqlay0CtYNwyC5lFIKJpqu68fh1bu33BXvUURCyTgOpZJjDJz1uc3OWedl4pQzUUhCRGkiMuRUSr0UU0bIlHjvmSSRYk6Jkh8GTwDAOAOAEPzu4sL56e5wVjF+8cUXYRiqSoSATd2klACxqRcAYFTTtK3zTghJKVVK1U1zPu9lUpElxXg0KWEEAEIhxlhXHFPKOROWfQic8VKlxJjKYp1S+mx7Ck8FK3nyYIj4tAnL/z/2/uNZsjQ97wQ/fbRrdfWNuDciMiK1zqzMqkIByIIugiCJZrMBjM0YF22zmLGZxWznL5jFmM2OZm3TJKjQ5BANSQCEqipUZaXWGfrq69r96HM+PYubVcSfgEW9Kzc3X7i7uX/nvO/7PL/HXu2hALhKBvvqn/aTZv/q9QAACKEBhlDc6zSffPIJ1/UQwj6jQtaeQ6UxPQ/mGpVlGYQNDSrFS2MhhIBZJ2hFy0UsrPvhp3e3t0cOQUaDLI21FLxGWZ4+9eSzo9HmbH5KXJTlxY0bN7Z3dqaTsVKqKopuq6WtRoQAXlGMEbR1kVtKqeuUVVYLaKx2KcMW1kJgD1PG8jwXyPobfVaJ1KSB7x9sHXx59wvGmN9shGG4Xi3Gl2MIYaffW04XHgqFFpPpjDmBkrbM4yDyLMGqksqAbLUOwzBLE4dRA4FQijquNdpS0PbaquTWWqO0xggC7PlkOZ80mj2hMGa0qOKW3+RlrrUWEAlu/XZk6gIIK7kqq7LhR3XNkcsE1y5Bi+kEGQW50ErbquQa4ayuk6LKSw4A0FpT5kihOZecKyFNWfKsrLO8kNpIbbhU2KHMdxFGrucabZW0SsOyUBgRay2CFkPq+e5wMGLEb/c6hdTNdudqaOcHLoKkljyO49VqeXp5aYxh1G21OovljNccQeg51A+Y4NxYLVUNMdQYXM7neV4BY6ABWpm6rhBCAFpudFYUwqiaV1f6OwNBraQ0WghRl9xoa7Vm5KvUWgih0loro4GV2kL71fMAQGuBtUZKabQWWlkDLQBXDRJCyGjje14YhFEUHR7uXgl1DYAYMUAJtnK40bXYYIyzLFNSU8qARRjZVov6LrVWUmC0RFrDXrfnt1pB1JbKiKr0GFmu181Ga2OwP9rY8TxvsVjEi2UzinxCoQVCCcJYWVdSGWC1NZB6LrHYKoO9wENka2tH19x3PcdxNNCyKlm7wSgxWb7Mc8C067iffvLeoNNt+AG25t6ju91294qWA0phVNUdDhpud2/zWhQ5zCHayiDw20EouR51N12C25GHAUQAM0xAyKADaCuS0loNEIWIEL8ZIYQAQ7JSUvI4nmOMw9Ze4IZC1oSQoirBeO0jWy7XVVEu83VZrQ2XwKUAamC01VZoTL0AZWlWVVxIqaxZLNbSWKntOk3zuhJaZWWeF3le5DXnWZZKpSBCwoC6qousKotSclWVlVa6LgVXKsnjokwxNtZaCyHClDJCKWtEUZmnH396v8i5qJUS3HGZFwQWgNl4Op1OtYVeEFZ1pYA9no4pcSFimVBrLmfT5fnZ2Wqx1toAa8u8TJI4LYs0y7mUNRer5UoIrpSsqvIKhn3FblZao6+w5aooy7worq7d4seYcP3jFFD7Y1uB/XtljJFSSKWM+sm9gfyqfaSYfBUO7TiUkR9rRq21gqvA840Sd/a3w8AhhALw1WRAK0kpLasSQ9hqtfu9DoT64vIcaFAU1fbmHnVcIaXLCK8qhJDSwABQlsXZ2VlZFlErskDzuhBCEEStUXEWayPN1afQhhJGMFtOp67nEt/LgEEIC8EtQaKumefG8aJOi1m8doPwKmJlPB4/8cQT1prN4ZBSenF5AYx+fHwPM/vRZ28TCj3fbfejxWJ5OR6HzfBydhE0giRNgyjymFsKbgGgLhMVdwiFEFqMgqhJHEdaoIWUFnKurNZJGUe9Ni8rY3WSL+N4oYCtqsqlzHGd/mhgjKEuKavKIjCdzrzAxQyZn+pBf1r/wAsJbbS1Gtii5AYAAAkixPF8YWxSFHFelFIs4qyWQlkjjYrTrBQSWhLnRa1Mnld5UQuhpVJ1LaTUSZomSSy1rqv66j7PpbTbaf/Ob//OL7z11vPPPBv6gTGGc76K0/liOdwZtbudZqPNkBNETYzoYDDQrtsY9APPHzY6iDrtbqfbHVwddYyxRhCtlvE6yeI4U8ZKY7iUFiAjNcaY85orUUuujJU/PiCVVFfwb3A1ptXamK/Urtbaqw7J/vdR/9VI1FgAADRcCKF4XZec86vtwNV3hzG+yidGPwke0QpC6FC6t7u1t9XdG3aLZOEQlmUpIUBpUZWF5zCPkTxbV0VupAqCIF4neVqulutWs1PXNQamqiuljdTKGDPa2jq8ecsAeHJy8uOod8jLympNHaYNUFJjAmtRM8dPk1RLYa29XM43965prZxGgyNYLZbFOtnY3PIDv8yKbqdvIcAYN8JwfHFx/+GDNM2wRbyorDIUYsao6+OyKIyx08nU97zVeoUwVIYv47WQRkhdFIXrB2WVl3kma04RVUrxsp7PZg5ysbUQwlqp/saWBSYI3IJnkddYrVcY4263ayAMgwBaW5VCY6SldIKgrgsuhNJcW6UR0EATz/cvZ1Mu1GAwrGseT2dBEDgugwhOZyvHc6fLtctolueEkqSojDFB2MjzQgEgtW1HQV2XGligNIBXAG8oAFRSBa1QSun7Lq9r33E6nebtJ5+6Ehp+9513u93+8fFxniYPPvvIdYOL+ay3MVJSllmW55Wl4DzPtra2KsOZ61tGeFnVJWdUAAAgwK12OytTSDAxQBmZrNNWp2k14IIHQaiNBBZyXkMJAAAEU2sthvBK7KitBT8OBWUMAAAgAlprgJHWEl3hnxAyxgCtq7qy1iII67rWSl/ZS6y1VxRwjDGECH6Vy6gQslYZx3W2t4bAWoeQoqzOZrnnewCAQb+LtbFaFXnuuo7rAkqQlZoxp8hqSp1aVN1OO15OMfO1koRAq5QSHGO8t3tQluXJ8bG1VimFMVAKUOYBCQI3UFZ3er2iKFw/gqDyPC+XOl2ujTE2cLnRg/4gj2PYaNVVtTsanZ+fu4zxVifPU4iglDUAoCiK7Z2tJF6P+sOqFIPuJsa4LkXkt4s4HXZ7DOIyz5tRe3Nz6+LyFAGbyNKjDGtNESnyDDHiOX5VZmEYreaXhDEMddTuLOYTWlfIKGGoiwNAKq0ho6QuSkNIu9+tsWG+Tz3Xt5Yr7blhwWvquxhRkuQlACCKGoyxsqxc35daXzw6iqIIYmKwbjVaWokkLzDGWVFEYTNJc0wpl2qtE49uCKlrLn3XRdYYAFZJtr+9aa1VgjPmVBXHCEqlHj1++OB8UpdFluWTdXpxMW21Wjt7+9945dVC6f/8B//l1u3bH7zzrhM24rTAxNna2srzHKCwzHOGoJLC9T3BJcaEMaS0DvyG0UBZJbWcl8uvdO8US63SJKOUAQAIhhjj8iuwD8vzHBNswFerr5+A7plDfzKZN1/N5621Flp7NbtAEP5EUAIx/Mmu/yd2pa/2/AhprR1KAcKIIFWLp5+4dnzxI2MIhtahFCDLGGYOrcoCEggAdjyq8ooyjDHABC3nC0rxer1wHMY5n08vRJ23h5uLxeqVl7526+bte/fvf3n3i6gdMEKU1RAiLkvm+FVeI0QhJrIyeVIqqVVZEQsAAE3G4vEcKzU9PWtFbROobq9Vcx4nK2DtwcFhmeVK6MD3tVHKyNPT035/R0ngh8gY1W71cpBoI9M0u7Z9TWu7mi+roggY9hgTWcGYz5VUSgWBLyHobm0WylTGUKMJxJU0o73rSJpHd+/fvPMa4GVV8UUcb21vpmlCw0YtBMeINaJSawwhxswSLIz1HZcghNI8p5RSAieTCWNsNBp5nre9tcMrDhGtuLy4nHChJvNFmpU1l3lR5mU5X8fzVYwoW6XZbLnIi2q6WK3zVEEwXS+m64XU0EJ4NdqpamGt5TV//4OP/suf/Nmn9x4mSbJery8uz959+0f/+c///NMvPn/rzW+8eP36d/7xb5AwePb113pbu/ePTqRQvBCO43ApqOtS4mJCHdet6q8WIUopRh2tDbBIKAMhxASXZSmEKIuyKivBhf5xVySlLKtSCqmk0vq/s8f+O0vn76FGfzIB/ao9UgohdGUPpZQSSq6CIcGPU5qubhWstYRiY5TrOhBCJ3ChkQd72xTDZjNQWmqltNbD4dBxaeA78MqjCnQjCvzQzbOk3Qonk7HWar2cG1G3GpGW4uLiQkh+djam1Hv5pdd++Vd/DUGaFBlmGDtIWl4LbrR1KIXGKq2Z44z6A8dza87L+ZKUwg/D/nAjxIQgpCCEiLmERlE0HA6yLLtz+zaEMAzDPM8IRSzAXsRqXq7jleDlaj6lnqsh4EojA0XNO6224txxmZXKdwIlJHX8wXBkjPGYGzUihJAXuJgQTFAQBp3uBgLUoU7gukk8N1Z3us26qKWQeVFwxfO6gr5bS828AGBU18ICY63hUpAkSXJk66Lcu3aQpwkmxHMZt2a4MSSu9+kXdwm0jDGubYSg7wVlXXueTxGxBOVlmSYrBKD07Wy1JMxZrb5YLxdHjx71e4Pv/NLPhZgqWSOEDQCNZhOj08FguF4nvX63KkuU21GvbQBK49V7lxetRhP6bl5Wu1veb7z1C6cXZ1yrs9Nzo+r5ZI6aWFR1EIZSGy8MsywVAjqOu1wvMUYYU2WsgaAoay6EtdYaaKyCMDCgZg67QpQTQq7i7a6UyZTRK5nBV/plYzDCV+p6CwywkNdSyq+2EpT+ZAkMIURaK0Kp47gIIQgAQvAKC2mRhdYihBlEKESCy3bTZQ6DEPJaBK4jpRqPx4EfMA8pqbIsc13mek5dloHnLhaL4WgrcN2Hjx4w5vR6vWS97nWG2ijmkOl87jhOs939xbd+7WJ8+vD0YZbE2BplRej5abLyXQ8SXAmukMGu3+r11lm6mM2gttrhDgRaa4xIUdfFct5xfQtMmpdu09ne3mEOvv/oLnUYF9V4euG6fl3JXqedxWkUhucXx91Wu8hSodV0xrvtflUWFMCSF9KA6xt7Z+dHBoAQ07Ojo43hlkdQKS03Wku9Wi+t1Nhhs4tz6vnper6x08vSvBE1OALAWg9gYVWz3Vot1oRggiECUBuphPhpF//T+gddaDKZEAAxxo8fPoRWLxfzLElbzSDP4/l8PhwOd/auLdcxZrQq65+ozob9vkMpgkRaEEaNLC8QczQMs9I0m33PCU8vxsen53lecqlryZVSFsIb+zuEgM3NYZFneZpk68Vf/sWf+q4juGh3+4hQXtW3rl1nUk8uT7ut4GBj+K3XXn7mqWf/D7/1O6+88vqdp59ijHFer9ZxkuVuFKVFtoqTuqq11kVRZHkOIazrGkFSFAVGlDGWJJnggtdcA4sQ/smw8yeKz59cnQEABgKjv7q+AwCMNj9JpTfGWAu0MlcaRGsspQxjbOFXAlNrLboKdkJIa4URciCNGhHBSMmaYuj7vtEaE+w6LgTWWE0o8X0fWgCMJQwx5gwGg/39fWvt3v7+YDRECHf7g8DzPN/N8pgyAjGtSp7n8vru7Tdf/7nXXv6m73eqqlJKeo6TxwvquJDAvMrTNI3zDGBEm41Rs91ttUmjMRxtNJ1AlXx7extjJIRYr9eO40BjIcC+7yHkh14zCCJETafdNdJorfPlYn9jo+n5WZlroIzVZVnG6wRa3Ox0NAHGAqkUo1QZEDZb5sfeWuZ7VZI1/ZA5Dtc6mY0hpLt7B9k6N8BiShzHIQgyC1zPC6IGdV3sMAqRldxqZZUkjCjXYRTRtY6n03mzEUrGLPPTpKgpKtcJsaA5GCKMpNJSa8dxcq4enR4RDAOHMQA8DEpGeM0RVZubXd/1GkGjvZhEndE4Lna7HaCV4gIRIqVcrlYnj46fvH1LQcgana///K/FWRH4vuAVpTTyPMJYLURdlUarDEKptOP708Xk4NrerVu3EMR5Wc6n48l0OhmfCS48x0+zzPEDjBFGNMsrziXB0vcC16VxmQV+WBZVGIacC+sbLgRzXWAMwvgq4xrArzSkCACtNYbwam9koLFAW/NVuo0xV3tTK7gw1vq+hyEBFkFwheWx1tpKcHC107fKaAgIoZa0mw2PUQs4r2tGHGu0MQoRx2GsqkvXoVIaY6+kcbXvR2maXsxnLz73/HQ6Zq5rlV0sJpv7B3lWpOuk06NCCwDR2WTMqNduj771rY0vPnp/MjnPk4XbjCgiALrGdSolmSDdzeH4wVHdjlwn9LRLISyrvN1uM4wNACKvN/t9a22eZfnswmtEVQW7nUGar2phnBDkeaYknyerjV6/5Lzd7bnMkVpNi8tG6EsrkcSh6ysuqbJciMAHlHoMoUUuAYFQAwRto9UkhBLftVyWaSaqrNXylusYoQBAK7mSDBHiSAgMwVibquY+cU1VKq6I54aL5aKqBcKQUSfLc2PMD//ukij9+fjyxuZ2p91UQnz8xRd7e3sEwSuoGAYmSTPabnbbbQAAwVDyqu0Fea2/+PxTxcWo3/v000+Go43L86NRp3nn4JrRohI1kvy5p+68+/Gn/W4X53kz8But1mKx8Fw3TpKNrS2ZplEUcWN8x03S1HV9l5CyKD7//PMgijzXb3V6BwcHN2/ckprHcfz551/e++KLRw+P9q/tQIjquvT9AELoMFqUJaFYSs4Yk1IijAEAeZ65nlcrdQVm4lw4vgesNdpoA4DRFiOrNIAGWHQFxfnv81GtAdAAWIzJTyLwwN8THlgLtDZX+Y4OJQAii3AUeBAAY0EzagghMIEQ0isAqkMZAFYrZTHSQjOG1+slpWxrOEqShDlOq91VXDQ67UWSWgMoI3EcE+a2u8PAx2VRFEVJCH7+5VeWy4PTk8cP798TatXqdPOq7LbbaZLVCPGai7nsIcZgOJ3OIjfc2+4/eHi/2Ww0GlGlpFEqyxLHZzYzUdCpqqzhNnWZGmPCMFzxqtlsnl2cu54LZZlwgz1GCQy9Zq246/sOwlXFNUAYYuK5vkRG1thhgsvhaDCdzQj0Ou2eKGNCdBB6l6ePAcFB2FwuFp1utyxy0420MUZLGgUgLYSSiEMsubUW/rNfeKM36OQ5hwh4rq8k91w3K6q9ra3/+PYPbm/t7Q77giupTVFVkvNut7t7/fDy7KgRBrxMtzY20zRdZ1lV1YHn3rt779WvfU0ZJau6LEovaHSG3bufff7Mjeuvv/xiVZWrVZwJ9eEX9wLHQxg0w4gQprUOw6Cq6qDZugpTNFJZYLRWUbNNNe+023ldWQixJcLYdivCxGk0Go0o8j0PQvjpJ5+cX55n8Wq5WvGq3BiNKKVKcYiAEApZEPi+NJpABIwZbm5iBFzP83xPK33FNIIQllWttCQIQWOVNYQQApExRlkDrb5i71tjEILMdcMgcJwAQIMQAAZoo6010AAuSwAAglcYKCaV/ODjzz66NwXYiIq7ngchvJqrSCEwhQQhrRXEFBjlem6eJJ3eYL1aIQA0MIy5WZa5jnM5m2OEPN8va9FqD6SyCCGKkYVQKW1trZXd2tzOk+X3fvDf1smKRZ7faGDixFp6tUjWi9BviESQhrO/tcMws0YTQghCEEIhq7PjU4iAohjDCBNAoZuLImo0FtMxUBJdZUwigB1kFJRG6rI0xmhkg6BB/dBznPV6HkQhCX3HkPH5MXCwkarRbs+n025z6FAvq3POE4ZYESeO73KpO512XhbA94qIEs8zFmFKYF7ItAKqJkpb8NNV50/rH3ahVrs1m02vRi1ffvklAKDMC4bg0XquEFzySijtMIoxYoxFURSG4aP7Dyihk8kkDBtVVVVV6VDiMVqX5e3DG6HrZPGSl2UU+p1249bBExtbe9/94NP/17/6/1Zl3W21jBKqrLeH/Waz+cN33rY/dlr6YUCp4zhenCTz1TLJMguhVMpxnDTLfOYgAKTiEMKTs3NGyP2Hjy7H4zyJHzx+eP3w8Jd+8Zd/45/95huvv/nk089QypZxUpRlkmQWAAuxhRgjWnJZCPX49EQqU3MuhSSUXDHLpZCz6cRou1ivuJJVXQshhFZX0VXawqs+SV/R8s0VRoVf7UyV1krJr1Dl5iuY41frVK0bYeBSSDH1XEcpaZT4yulGoUMpQohigiFgzLmaeaVpQhmLGo2q4iWvhxubBkDfDz3fz/PSag2t8l3GCIZAacW1Vj//zTeLdDW9OCcUv/Wt73zrjV9psHaWlEaIg43N/b1rN/cO9ze3Pd9XynieTyltho00zcq6LtN8Op1tbA73rx9kSZEXCcOh7wfEQFELQkjghwShwWAw7PcZdaJWs6orTFC329va3JKK+x6TUlKHVFW1Gs+BhRhRRggXIkmLrc2dyfQIE9Vttwl0sjwbbW4FjbbnB1VZC86xBT5jRBtkFAZGAev4/nA45EkpsgL+9j/+FqVEcpsVpe8xh2IlTeSyHMBlxVkQ7o9GVkguleO4V+LZZ557DgGbJUmzEYWRf3F22u12ijTDjHYbbQCt49I4XmdZde3wxpNPPUup+3fvvn12drq8PPudf/6boqwgplrro/OLdVE2/ajbawulKWVpKYosYw62WlujW62mMWB71O82oyLLpdau4x5NZkLIUa8rjO00ms0wWCSxQx2MwMbWzvnJyRtff6Moik8+/jBP4rIszqdTxWVV5H4UJml2pa66tr3huKwVNhzHoRgLIRBCZ+dnlmCl1MZgUJUlIYT8ONfbWgutvnrAKAUQOq7jOA4hBGFotb2iDOIfT/shhBbCq6V/lubff/dTCSgvy1WSdLotoyxz3CswhOvQPM0tgr4fAGizOCaY1lK2Gg2ptUVYCA4JuTgfa8kbYUsb4/u+FwTGAPgV+wdSwINGgwtVc0UBo4wayE/nY54uC8X3R9ttN0zS9OTsfDgaMOqkaYoAyMoyaDas0g8eP9wc9f3Av1jERVFgGBFoCCHKqk6vubycWGgrzgPfzarajxoGCJ6umkEvF3lRZoPNzapQyAVlVkR+w2916jSWuo7rvOV3eu3uYnE2vpyMNvfqqrDKtJrdUnCjpZQi8PwKaNAJhNGAEKON0LLBQlVkvsar1QRVVVEVeVWVhFDXda+IS4VQQRBcpOnlZNJsNo0x3W4XAbteLrY2RtAardVoc9MPQqUtc72y5hqAPC/TLF7PF0ePT65sx9vb2+dnx1WxDikKGO4Ntv7d/+9/P55M9/b2et1uFIaff3EXYHR8en7/3sOLyfRqRkMdN07TrEjH0+nJ6SnzQ4tgEIWO61VcxXHGPM/xvF632+50LIJ1xbu9XrPdfXR0jCn96ONPT07PhUVPP/fim9/8uXa/j5i7f3CrqgViXl5zYexqlVZlzbUyEHApjTFJmkppHj86Wq3WQsqv7PM/Pt3h31t1Gmu1slp+lbnzE4fTlZBPfSU00UKINEmvRmA7230jasd1h4MeIxQhC4BVSlKMq6pkLvtqF6W15/uQYABAWVUVr6+gm9RxAEKMMUxIo9FwPaeuCgJRELXCMGo1Ai9oCmGUtr4bYcdYrK21N7aubW5sdlttYtHleNzqdHb3dtaLWZIkBgClZCOKZF27njMYDNIsOz09IwQbC4UqCSGtRjsIgsV0WpQlhBAYo7W+trtLHYdR11o7Xy4wxoJfUUCN0cBzg8ANIMZZkRdZGkSNoszn84U1rN3qVnVhjUAI1TVfr9etVktotUpiCLSo67quDZeyKBuOl6cpgrCU3ECAAIBKatf1XAdryTHGnPON7c2OF/Q7HUZoulphTOqqGI/Hw+GQEBKvl7yqk/WKc44RIZgiTCsuGGNaS4MMc5y8qMqyGF9Mbj91R8pK8tohbrvZvrZ/84ujs7/4/g+9ZqvV6377538uLUoNoB81MXFWSSyNni0WheRpXq7X6zQvTk5OlNBpWX/y5T0vjIq6ggYYANZxPF8tDcJ5VX/4yad37z/IiyKv6oePj47Pz05Pz/7LH/3x2+99eHw6fv6Fl6/duNUZjLr93jrOLi4vfc8virKuaylUkmTz5Sot6ovpvNlqI4ivVFHk73k+rbXKQmv+e8bI1ZNaayW/yhr5+96Rq1/zVbRIFEWHu9suJVprrb86X68AZhYYxhxjNMGIEkQpvXKwIAgRRpTRoiiEqKfjMcEgCkOErTZKCLG5sWUhWsWVUgBYwxgDkGJMy6rMiyotuZamyKqL88vhYJgVRan15WKxWkxLJeMi0xAUVTmdTgPfe/TgQeh7T9y4WWTJej1uhs1GGHBeCSkW05mU0g88x3EajQaGyGWIV6XnMoyoH/mQ0p3d64t5ompFIesPN7iS88k0CAIFAPNcgwyiaHfnRqc78L2QEKprbo2IQj9LEgwRIQQaC4XE2kAuHAnS2dyBCAPY8HxdcuIwP/T86WTSHrQj10+yzPd9awBrtN5s9v7qnXcQgADBPM1uHB4cHx8rpVqtllIKISfPc4QhwkQD02i2QFXxurIQFrXGOWDUefqp5999+/08j2fLddQZMYJkLW/feWY6n/zu7/1vBINBf4My7yrTCCC8Xs7TLPN9vyxraDQ01gtDzeVyGdfWnE7HYaO1ubENgZmv1mWeS6F83ytKyRyaFZXrMUrpZDrtw+HzL77yF3/2p8zxhpubqyQTdb1Yrgghv/Irv/K9732POKzRbDx+9KgRRb4fVlVdS7WOE0JIr9tCCDmMXa3vrzh+4CpuAkIIsDHmysRiNADgakRqIADQWAu1MfYnFm3XcxFCxtiySA73dz97dGqNVTXHjPx4+y8JoQhdWWKk1koqDQG6orkIKV3XK6uyKnJKGAIAUewwOhhsnJ+OlcVSUaWqva1mXZbpOm60IkQFlO50tmoE1BDQH4we3z+6ubOrjB0vF03HbbTaeVlrIb1Gw5VC1rwVBbwsPj5+ZLWsSk5QEQRhnq4I9QC0nsvSJM3zzGEsDMOLi2OhYFUALTXysOO5CNCtzV0HkLjKeC2kMRv9/mR8HnY6i8Vy0OnkSWYAyIqcEocYTwEBjAqCYD1dOI3Idd1lPIMCO1GoykoWtSW4qBbCcepmo3frxk+7+J/WP+hC3WZrtpxHjYblIOd1I4oMwqzZFUKsVdUJnKZDKLHNKHr44O7+7q7n+c12y/NcbRQmsMwLa63r+JR5bmcQZ/r0ZFyXRRqvfc/76LPPPvjk/byqt7b3KaVKcEoA1EIJ2dvYXqT18eWl5LziohYSATBdLCHGVZ1rrdZpmpUFRXBjY8gcgiH8zV/6xVdfeIpXKcJwY7hz/2TSag+5dra3t1fLNTRAKDBdxgqgJM4+eP/jGzcP0zSuyipJ13GRH509XiWxUeBf/p/+ZX9rFzDPbfTe/uReXYuqqqoi7zRbdV1Za4XgopJCKG0N51IqJaQ0BkgjpeLGfmWcl0JaA428suRDYbTS1hprrELQQGsRANYIILnjBnu7A49Bz2EQQS5kWZQGAoKZ1hogVBbF1QHd7/UEtsz3EEYIYimV0XaWxCz0GKXtqLm7fa1IRc0JoREmEFjNa5MX4Oh8dXy2PrssiiqhPq6VMQIQ6EdB4+RyXHIOjRWEeS4LGa7rikGMEeV1vbO9Pb6YSAvcwAccZdkkW+cKkTxbX+nFgEV+4NdVVfPSD1uOQXVRS2UXVcyBzfPSCYM4ixFCktcwz5K6bLfDQklTlg5kBKFHFw+AsUURp1VCqV8KkyVxqzdcrqZJFlNKkbV1UXiEYAuYkp3tTUdqY0yJEInz7CoyhhBCEFnG6cbODpXS7zRdgO8CBBCuoQ0hunnjie3d3bLmQoi8qKDR1HM9ShGjGMI8z8NGY//g+njsSlGtqyqv+I2961s7W59//kVVa2NRv9dyHPdiumBemK7T7f7gweOHRupmq7sqq36/32q3J+NLRtF6tWq2mkEQVFqdnJ1tbWwEUfSnf/ZnQRjce3x6eHgopX7qxg7WZeCjNF/fuHk4ny02+700z6G1SinI6iI3/f6Q+aGo642N3tGje2HYqCr+xedf3rp5UDQam5ubz7/40l/9+Z9pWWd5sb97bbGaGGPyskQh1lemOWIJoFVdNIIGxlhbgCDSWmNGIUK1EAhiCwyyACILETRGX4FSEbZXpB2CkVXK9RxeV9T106JgnscohRgRQoC2teBBGBpjKGV5WfrMU1JQyoRUGMMkjTtRwyo92t7w/IhzXlSV5zvzxbTVakIMi7woakUIns3mQtWm32s0m24QSimPTh/vbPXSLJ5OJu1WqyxL33FHo5HfaM9mM14WlNG7Dx8rjJjnAQAsp9jUUdNDtZGV2tranE4uMMZamUazBSEo89L1PWMhdRxbLTjnrgGzk7NWoyEhKIvCWFPN5p2W1/YDQ0hZ151OTypTJmkyz1pBBABwXdZoNKYXs2eefAEAeHpxpIwiSgOiDYWOggCA3CEhpQhCpABUSgVBYCBglO7t7kWt7mBvkyu1nExrzv/mow//6wfvMUy+vHf/4cOHjsPu3b13BUspiiJJUqXkerXkdXXt2rU4Tnd29za29t5481vf/oVfPrhx88b1W7/yS79yeO1aM4rqupbKag0nl3MAaVZU3W4PMwKRDUL/cjzWXPTa3eFgo9VsFUW5jNdFWRQ1D6JoPp8//8Lz8/nyqaee9hyHi/ra1lYzdI+P7s2nkyJLet12tppRBDY2NkbDjW6rQSl9+PBhmeftZvP+/fv7e4edZmc0GF2/dshrcXF6Hq9WvCi/9da3hYbUD6fLlVZGSlNUvDYqK3MhRMUFxCQvqnWcVFyWteBSS23Ej/t3ZTX4sY3kSmlqr6IbjTXaWGO10lprwfmw10UAuJ5XVLW1WgthtYIQuq4ntUKEKGMghJzXCGHBOcFYKDGfTR8/eGCVaUatLKs4V4SQNItHw66DYDMKa6kqXlNK9/f3W42mUFBLvVyssrI2yLv/8NTzQq11nsbT6bTiIi2Ey9ww9CmjhDDmeA5DaTxfLRaR32w0+ot4Rih2XFaUOYTQ9zytTF3XWZY2ggakjBCCHNxt95KTcwWN0pJXZVUWWshm2HRcd7KY59OF60Vu6EtlkiShlB7euBX4ESYIU3o5nXzja2/KnO9vXg9ogBG0xkgpG512jaGSsre/W0ihlCTGmEYYXpyfH9666VKn2e4QL/zd//L7rzz59NFqUfL6dDZtbg0MJYy5GOO6roeDjTD08rJohP5yGXsq8Dx3uDG6f/++G/gQsde+9kJdlHGSQYwbYTgc9Pb39xfz5eX4wlqYZZko6XQ1QxR3giBJY14vMHW44FIJxlhVlt1ed/VoDSW3Sn6Zlc8+9WTgO7UQzz73LPWaCGiA6Of3Hxzs7b744svT8Wxzc1QX5cbG8MO795gbNFqdu4/ud7uDV199tSjyxXzx4MvPf+07v0wJu7i8WC4XfuD6Yfjhhx9ijF985eX+aOT73sHete/9zV9NFwtrLfUcoDTFWCullDIGXM7XHaExwYRAz2FMOlHgQQh5XQeur4G12gKjMILKWoq+ih3DANZ1bSGG1jqMEIyCMHz7gw+/9tJLCEMIoZTcQqSVgVAhhLK80NZqpQPXm62W0qh+v18X1a1bt9dpSR23ruuqqvvdNgCA+jTN8lpLlzlOz62K3HdwKSGC1mhlAADY3d6/iWGlhM6TRbvVWiyX0+Vqd++aAcgAKLVK05QXORIKGNRut7UVZ5cnjucja09OjrvNdl7nVV0TgppRmGS502wki6V1IFRy49qO32pXs4RAXFUlMNpC6FKcGuM3GkmWd3tdTHBR5FEj0tJigLK6AooETnh5eQmh/cHffW/v+s7F+0d+r8OVYtY625tQqrIogLGqrn/aJP20/kEX4bWcl/PDw8OyqEc3tqGBGxsbJ3k2XK/Hk8vI853AH7hhUlUbGxtZniMMAUZ5XpwsJk/s7LQHPaABJGS1jhkmgRvcuXOnrgRjrK4Fo1hKGccxF5Ux5oWnn2k0ord+5puTxfLtD97/4fvvzaYLYxXnfGN7C2LLucjyhBHqBX631cnjlQvR5sbo+OjEddB4NoMAKzPpthvNRuvatQNtTBGnvh+Isri+s/Hd7/510Gi5fugyEjU7L7z0yvn56ebmqNXY39vfdRmVytZ1uVqtEIFVWd544lZd8e9973tlUbz5tTfSPH3pldfG44sPP/nECxoMWYi073llhbOyLrnms7nv+9Da4bADCUnT3Pc8oRQGtTZKG+PgK0i3lQogeBU6Cq98ntrIMPCNhdki8X2fYuKFviwrx3HLuuJcUNdVWhFK0iRtNSJe15zz8WzSbbZ+67d/JyuFMqpIsiIvlFKux1zXLZIszzM3bCJghOCuR4HCk8U6YDoKG7NVDLC3WGWdhgexaxBJi2I4HALqHp1Pb+xv9Nqj2WLS4eL9o6PNjWGZpqtkQSk9vPkMhLrOU4dhXktCMZLQD30hK4T8+cV5N2piSvI0qz3qZgWHwHA+Gg3zOC7rGhkFpS4JaTJ/OV87iLSajbqu6oqLqnaYVwv+W//if/z93//9xXocha3QD5587jmu9PHlWVqWwfamXsRIWAfAOs/R9s5OfziqhWq0Ou1OvzcYTBbTa53BPE1Ox+P7k/Ovv/BiMZtvjTY0sHXNeS1Hm5udfj+Vld9sJHHS7PcgxhCiJ5988vXXXqvK2mhb1WUQBM1mO4oiSmlRlL1eH0Io6xromhL47Tfe+J//xW89c+cJYBGj7moZp2kKISQEl1WRJakxxkglyrKu+dHJsZJmZ2c7CAKtNZeq6bPJ7OLR44dVmsZxfPz44f/yr/6V74VC6fl8PpvNbtx++t69e9tbW81m0/VYr9OOAo8RLCTfv7br+77reV9+ec9Ym2WZ1LooCs/zaiFGo83nnnnu7PScUE9r6/nBeDxbrlcVF2XNk6yolXHdsCz4Yh1nRaWU4kJUQqRZLo2WSgEAtdbyx+xSDKEFWggx6Pfb7cZqMfNdRxldFLlSkvNaW0tdVteV4Bxhcj6bYEwmi3lVVRTSV15+TSijLbzaeEWNqNfvIITyPGcOa3f7EKB+t4Mxrqqq1YiakWsNTLNk1I367Wae5XFSKcN6o92Ki9liuVgsoqhZCRAXnLiNawdPvPLyy6vVglJTlHPmuh4L8qzotTuMOZRSzmvXdauqTJIUITRsd621sqqw1Ol4fnT/ke+FQRiWZamUeOnOk7mWQSN0CeGcu4wZqdIkrYpScoEoUcZQRP/4j/94lq17mwPqUqF0uztEAENMWptbgosaoYoL1wu8RhtFrWbB5WBze2NrSyk1Wywmi8XXn3/RSrE5GDENbC0G3V6yXDPGuv3B4c1b0qhMSzfwV6J68dnnlbWNVvv1V762t7sPCal5hQn6wd/90A9DA8Ddu3eV1ggRo21Z89k6jvOKMHZ0dCSr4nd++7d/5ptvIoQhQKI2DvMQQq1Wi1AMjGm3u9pazjmmZLpYxOssCHyl1Phi/L/+7u+eHp8laTpP1u+99946yfauH9x7dHzv3qMsy9qt1uZo8OQzT/7RH/3Rv/sP/+mDDz9drNZnp+cWmP39fQBRVZaM0sPDw+Pj062tnUane3Z5cff+A631cr3q9vo/99ZbaVVOlnHQ6G5s71PHE1WppHJ9v6iq+XKxXCdJKZZpVlSV+Xvhd9papbW2Rit7BZxSUsqaM0aNVd1Wq+n7t5+4XZbVVUgfBNhaUBQlxriq6ziO0zSbzGaj0RBj/LM/+/OEuDXXVcExQFIJLmohBISwETXzslZKU+pIbSBEjaDpOEG/10LM29vdazcaZbp4/uk7GqKk4LNlYTQhxM3zvKrr5TKbLJJ5XJ2Nk42t/SfuvCCFwQAoLkVV9VvtPC06rbbvB2HUaDabgR81G22jBFSSEBKvYmBgs92+8cyzOOfGmCzL4jj+4P0PKaXM85vIoRgTTBGESZzXOaeIUsdRSmKCTifnwEXTddzqjoqSX87mi2zdHw0LUYcIO5FvrQFK+60GIoSMNjceHx2PJ9M0zYSSP/zRD0Jt3rzzzKqq2s12vFi++frrWmvXdbIsFULce3BvmcYQouPx7OTBw4KL/euHo+7g4aNH9+/f39jaMgD83LffMgB+9sWXzVanFkop8+Xd+2eXlxeTaVLUn3zyubAgFeLe/btP33ny13/913v9DZf6R0cnVVHVZWmvUmmkCKMmprgoyorXvBbrdayBKYr69vMvA0DKSv7g3Xf39/cbnc7p5YT5kReEjDqirr/7N3/Fq/L1r735yitv/tEf/dd//a9/96OPPlmvV+/86EfvvvOeqOuiKDaGw2effXayWKVl3R9tdAcD3/d3d/Y450meWYxe/do34qS4GE+bzebW1rDkHCBMmGMBApSs86zk/Ks0UWscx6WEIES01sBCqa6Qzlc2ZgutdV3XGHn92j7DhGBcVxVCSCiptUEQAwC01q7rSqPTLPZ9//at2wjiuhJlUQEAJOeU0iuSWRAElFIv8I2FGKNaGddxtZCzVYwBrGrz0aefnp6dRi55ePdT3/Oo4xtDwrBjARn2+6IstDIKEEQj6rW+fDAfbj352td+OYw2RS2FKLMkKYpitVpVdR0EweXFmFGHUaeq8nQ5L8vSYyxRsigLwWWFEEYEEuz7Xo7AjeEwXi1rKa3SLnXKPLu2f+AQprisOddWA2i90HUb/vbeQTMaDEYbCCHWDGNeYGuN5NgonxG+XDFj0bWt7U6jeev6tZYfxGURz5c2jP7wsx8hQn7zm996+cadb3/jmyFzvFbUDEO/1VzM1h+f3D+J5xoGbxy+Gm0Mnrp5+5l+//2zx5eLNdfmkw8/Dqizv3dd1VW6jqWop9OpH4ZRFK2WSRLnR0cn1qAvvrj/5Rf3Z7PVD3/0rovBGy+/8Pqbb2yOtqOoW3MptCEUI2ha7SaGVEkdhA2/GSoLVC0azRYyuNWOWt3Wiy+9GDjh4eGNF1997fr+rgFAQbBcZw8eHv/1X719cj5ZrZdv/cKvDUb7v/f7f/yvf/f3krT84IOPEKUVL2eLhVKq1+7KqoDWMIDiLJ2tFpWolnG8t7t/dnpa8qrf6WLobG3vP3PnpqzyeD1XVrSiSHGZlXKyrqaruKhEzUshJcWQC865YsxBwNayFgBII8uiBMpGUbg1apV5qiEijssBwIwBAC5nEwiRUNJhLlUGA2wUGvSGEOCiqiFARinmORBjiDFAiFCn4hIhEgQ+Ydj33aARWUJ2dnYYCUKiqzQzQApeU5flq5nPPCcKpCmsMrN5QagPEcEA5EVa1LUbhY9OTguJNrdu3bzxpBKmyNaYQAydukh4UW31ukYKowpU26DTYw4NWo2g2Wi22pwXskqJQ+Plygka3XZ0MV43aEsLUWZFWRVep1UrGS/XrusGDsYIeVGkiwrUgCDvcnwhRblcLaiDLABK8IorXgofMyVtpuRPu/if1j/oQnldd9utL0+OAaHXdvf9qIm0EYQlWd4Ngp3Da0EQGGvDRqMddfqDrhsxSFnbCVaTcdBErW63SFY5UoEQT99+AiOwubP92f17d+8/uP/g0c7OThg1b918whpQVjwvSqXUBx9+fHJ21hsM+oNRnKZKKT+IHMdJ4/Wtmzf29651u30pJWVu0GxRxxVaCVFLKauiTJPYDwJlNa+rbqtxeX7+2aef57Icn578tz//s4dHJ4vlfBUvXd/f3t4uiiLP84cPH3788Sc7Ozvf+c53nn322Tu3n3zyyScRAp12R4i6rgpG8WZ/cHJ8enR6bowpy8Jx3LOzs9Vqtb29/f4HH9Zacy0n81kuzGSxev7557728svL1dJYVVRFnGXzxfpiPLOQVFKts4pQ3yCc1aLiClOnqrhUGiKACXBcp9VsOpT6gVcURRCEaZpqY8bjMXMchJDWynHcZ55+djgczpaLdZr8BCRhreVVhQBoRlFdFVpLhBDCEAGYJKkypjfoz5ZpWta1sqPRbpamDLmDRq8ucwA4MpC5bcKcH6tbjOs6V54WjLHfCLOiktpq6N959vXNvWdKnmIHYI/WmmsIK8HrWgNi43jpegwgFHoBRcT3Q+o6vCxvHBwUSawkN0peveHhcJhVld9tE4f4rUhBQL3AELxM1o1GQ5Tl+dGxMUYZQDHUXDUcX5c14LWRXCjVarZMxdF8sfy9v/7rrz3/Igf69OR8luWj5kCn1dtffNHs9ygEZVFQh03G048ePGgzRggedHfLXL18887v/c2feCz6m/c++J//P//vs8nq7OwsXifz+RxCOJnPb968WUuxsb11cnaxTrKsqMKwuYrTbrfPuawq/vjxcVlUEML/9V//bl3Xt28cLBaLk+NTYHBZ5sZCpe18uSyqyli7iuP1Om612pfjC4RBsxXVefI//NN/Mh6P56vl45PjV179Wm8wmi/mDx8+nC1WShmE4f17D4QQeZH+yZ/+cbvd1gZ88tlnzzz7PPkxIhQhVNf5aNQ3xmDCrLWRH8ZJsl4u260WRIi5nuu7o9HIdb0giF544eWj4/M//q9/Or68TLJ8sVqlRZ5VvKiVkHaxSLOiXqVFWaskrTRiFQe1MFwYTB1jpTEGU3Tj8JrRynFYlmf6qywRfHx8/PDR0aNHj771rW91Or3jk2MAMcIUYlxV1RWqN/IDgqDS0loLjHEoNlwwiikllFLHcSChVaXiuLoczw/3no/zpUV8b2fH6hobC2GQlxWmNM3Wq/WyKFLfZb5Doyiw1mpjqopjBg2GWweHT7/wswaE7Wbb8AIz4nluM2oQAtqNiAEIrU3W66ootNZB2EAWeK7nMzdP10pLIXiSJsvl0mdMrJKiTINGSCltt7sMI5cSAwy2OvL9qihPjk95VQ5a3XyVYA1MnjFjATSmLFyh0ObGRqXVH373b5qtZrPZBAh/561fzFfrsNlM88IyMpvPpdK+H3oe/dsPPtzburZcK8v8k3Xy7NaNqpB3bj719b2n7ly/4YSB4Ork+DyLs/HFJE5z3wsfPTw6Pz+/f+/Bark+O7+0ADHHr7kEEDPXVQa4jved7/z62dlZnqbPPvPkcNCnBG72Brwu/TC4ckH4vq+UYo5zcnoadlrzZFnVNUHgv/3XP3r1xRd0JdKKH52PP/nsM1ULl7Avv/ySEHJ6evzEE09YoLe2tm7evPlv/+2/vTi/GI+nH3zwEWM+Yz5CbLVOGGO8rDdHI6lEuo7j1WJjNNzc2EjWq3i9eun55wed7uxyjCAsixJatLGxZYhXcJ1mhbWWc24sIMxZZ+WqqC8XcVKKySpZlTKt9f3ji2XK14XIK0kIYRQxQtuNcL1ecyGzLKeOM18uDw4Oep0eQrjX63tusFqugzDM8zxN0yRea6MwxgghpaXWej6ZWmA8hwFjoiCo8gIC4zp0Pl9YrVrt5saw34qanz94bDC9uJg5vtPwwlbD93wWRq1er7cx2traGNZliaC2Rs3ni8jzO502gmS9WEJrCXXavWs//+1/bBVtN4bj8dhhmBIQOuHLzz4XYCLrEgG7nM0VF5fTCXXcsqyk1q1mFxiNEeqEDULxZn8ki1JWNbJAcm6tYgACq4SWg+HAWIkwsMC0m11syPbGVhj4QGuqTZkX0He/Must03V3c/Q377wtFb++u3Py+NFbv/jti/H56fn58cllURQuYVlW3Ds9Or64/N0//IPdXuM3Xn5jJfJ//OYvvPzsbYxRk+CT+dn56dgCHEbNrOLMde4/fJjneS0lRKSs+SpOkiSpyrosyqIoTk9PMSJXV+GPPvoIAHB5eblYLLZ3tlyPWiVnk0mWpNAaCGFZ11GrOV8uw3YLIFRWlQLo6PTs+9/93u3D/dnlhRJiMhkHnieqChhz8+bN2Wx2586dxWzmOn4cJ8aYN974utJWa315Mf67t9+7++Co5toC5HjRZDY31gaeo4SYjidHjx41fK8qimQVW2unk+lgMBBSzebzVbyuhT68cef2k88d3nhCSZ2tV5PZbLFeZ0WhAVzGCVe6qPl8nT86HSvIpmm1ruwy5VIBqbXiAlnt+0Ge5xCT2Wx+cnLieV6r3f32t7/9/HMvXHF40jitqopRjIzFBFlgtFFXC+vBYIAsQAhpJbmoXIcQYMo8NYJjpJBVDNt+J2o3eo5p37xx4/j4ZGOwUxYJY1YbIIVqNlpc1KHvXJyfVUUROBRYrZWKwqDVahglkvVquRifTy5e+uZbvWu3Pa9xcjaGBEOA0qSIGhFC0ALthx5jLPS9uCwwJt3hQFoALKryssoyiOwsXkPfLdYZryrN64dffGqsUlxoLcfrmdcM967ttZtRr9FaL1aY0rTOtzf3XOp2g9Y6TRAAP22Sflr/oIt88uCLnd1d16B7VQ4QquL1cHvrT//qPc/zesNRmhTGgrgqq7K8WK2ENf/057/5Bz/6QWCMUUWF7H/6z/+2ik3UaqJVwqXuD3YeHT+SVm36I2ChECLNijxNMSKVFFZqhBDn/ApQI6UE0CLPK4sSISQl96SMwuYH770XUuowApRM0rXjNypRNzotbvSw2fz0k8+SfO0cun/7/U9efPHlRsN78uknX3nhucfnlxU3ebpSWtdl/sUXX7z00kvMoXGWdTptKWXo+1mWDEeb9+/fb/f773/w8cHBdWtUEHpRoxXHMXNoMwybYdDs9T/95KPtrS3quNPFChHWbsJlnj26ODWIdFud2cXMjZrbW7ubw+FiMX98crJeryEwnh9praRSjLFksgRRKFRdcCEM5LVwKByoJsZ4sVwihLr9weVkkpXF9esHruNDgBB28qpyXT/PyyudlDHKcR3X84QQjDECEcbY87wsi7VRCCEtJXMcwWvJdRQ6lFJZy8Wy3N3bOD67+KW3XrdgXdbZ+fnFxXi8s7sZhZ5UYrFYIWRcz93aGCoNXdetuVTK+oErFG+3WxZBhKmSquD14RN3Dvd2L8anX376we5oMyuKoNOAlBS8oqFflqVRqtHvKinjIleCW61cRiCymKA8jh2XRl5gpVRCEIw1BBjjNI237zxBCTs7P+l1WoQwBOFytWh2ulnNDUQ+osNmuxEE6AcffMSE+nIyy6qKa3l47dpfvvd2XGSk4peTi9Pl7Ojs9MsH9/d3d5XjXtvYeu/9d1fj9X9490eYsA/uf/Teyenhnac2eqNVUi6L3EDQ63V3tofL5bLMc8ElIeTatWtB6I+Gg26vLZXI8oxzURSl67qEEN/3XY9hSqUCZVlenJ397M+8dXx2vpgu1vFacCWlRJjMlwsLzN27dx1KA+I8uHf3mWdfrhQEiMyX8XS6rMvy5PTo5s0nPM/zA8+PgizLIYSe403G07Ks8jxvNptlWR4cHLz3/ofdbu/evftSKKMBZa7SVnAZtdrYoR999NGzz71wMZ5ejKdHx+eLOHl0dDqbTLQyrutiTLUxVZEtZ4vlMu60u88+88LBwSEAYDIZe77H6wpjbDSXRlZcEEKqWo6ny0cn47PpsqhNkhV5VddcQUxHG5ubm5v9fp9Saq0FFtYV55w3m51lvDw6e+z7vlW6GUbIgitLY11VhGDXdbVRhGIhOcLQcbHnOcZqC4zrsuns0nPoh+/+4LP3HxTpgjLS728x6hkgjZUIocAPEUIWGK3EdDqDGBur86JI4vryYgKF1HXR9NBm0wlsfnr04KXnnv7lb79FHNhsN8qyIBiHYeS6gTT62dtPlVkptY6T+IpNiRiExBoAru3sRpRRhsNWC1NqtNXKKKmdqJGuMl7UjND1fFmWZZLGRgOEcW9jwxIc+kF7Y5iUNWkNB5dJPAgGawO3traRBu9++fnz1w7f+PmX/+2f/sHBtcP1ev2Lv/DW8dEZrMSKFOt4+erBmz/45IPXb+3/L//tD3/rG/+s3XDjVFdGcodczMdNQqwS0NooirTWruslSRKGYZZldV1jCKN2q6qqPFdVXRJCrmKNIKaYUqMEAZhg9pu/+S/+7kffr4tSCuX6PiQehNBxnDIr8rywUif1sj/aBQb87r/7jzfuvPrgYrpeza5fvz6+nDLXPTk92traajYaVVUAwFqtluOyMs8pxefnF6Otrdu3bzNKrl+/vphPTk8eAYx2NrfqqkizbGtrI2w23n3/A8/zPvnkixu3n/ze3/3dnYP9eL0oypqXtXRDrqQtMsdxpJQ1l1UtECR7u/vz+Xy9XBFC8jyD1lRFDiz2fR9YzFyf+P5skZyfT0fDYV4esSD0gwBYzRhzHc+lblzkmEDJ+WAwSNM0y7LlcvnkrWcQBmVZBkGACZRCIoQc14/jnFIKEcKEaAKPj4+2t3eiqJHq1HUdC4EFdP9wEwFroF7n2vGaZVZUKqcOY5goa3zX0VoHQSC0rUUlhS7KghKwef1a07cbvUAp5TMLAL51fSNdXvaa4RuvvpgXNSFuVmYPL8ezZN3wW3mWRUEwXS1bUQNa67jUSEF8JwzcuCwEBNR38jS/CtWwUjDXC4ZdpFGS5IN2f5EkJZ84vltpXSdS6xliNM1ySJDvh8QiWlX8qJ60Gm2AULpav/7Esx/eu5fldWGsKsqDrZE16vfe+/71ZrPM091Rf1acP39jdJGm3cbo+/e+27k32n5i+73xxUbkvfj84cnpg82t/QhRgjHUer5eUkxWl5fdTsvCgDEGIbg6LeJ10mq1Li/HnuuJusTYMwBNFlMvCPwgevKZV7744v3k4mzDv7ZeL+NFJXnFa+l7jUqXyXoqyxgQunfjWYPskzduv/39CyPVzcP9R48f104wjReB36gqkVfLvZ3rRVFwqXr9tjdfYgBa7eZ0vhhPx3UWZ2X+6qtfn1ye9zs9N/A//eLxzcNDx1VpEne6bUKd27dvW2O8IJitFvfvfb6/f4M4bqvRyLLlaDSaTNfLeBl4LhdOELY8x5svpsv1suJSQ9RrtherFXM9q7WDLGEgDINcaup4Dx89Pji47gCnLjW06VInod8AFlBKlTGUMFHXgedxUfbaXd91CYLEpVbrshLrJJZSQIQ67XZdlJAQCzSmkELdabnaetqCxSSeXi6SLFG87LY2+iSaJuD+Jx90O9Goe60W0DIVeLAseFkmCOP9nev9fvNa3+l2mkopwcX5IiFQllnKKFsuZ1ZxA4nhhXG0leqF6we14DkXy0VyNp0Ao7I8hVK0+11RyhA2knkSNButfnN+uZCcb1/fGz844Uo7DiulGEYbVuOT40c7e3tHjx4OBgOTJKEXnUzO20FkW03EASEALeNFKwhsltk4fnR+Aqz+Zz/3s//yO7+6d22rlOJksbh39Pi9D+/u9UfKc2qEcy6ns8k7X36OXUdmCTXsxv7O5fn4t1795sFwJ5vPkyzvtztB4Mfxej6f1WUlpWKMcaGsVkkSF3kKAKhr3u12lVJRFI4nlxBCY/Vo2G+1GlrKusgaUdjvbzbavfVi6TBMKdHKXj84GA6HzWZz79pBzeVyuWSMWcEf3v8syfLf/8//+fNP7/qN5jJNZpfjqsh7vW63Pfjkk09chxrFLy/GO1tbQsgPP/zRr771ZttjCMOXX359Pp8boy6n48vLy1ardXx8HDYaQilt7aeffgqB1kZi6j39zAvaIKVtXfMv792bzBZFUUgpKXGNBm//4N0v7z7kyrR7A6VRrXQp+OOL8zhfX07PizrPRaGNVRoqqQlEu1s7q/kqzXMh6jjLpJTaqKIoHJchABzHQQg9cetOq9GIwiAKQt/zjJIYYwIhI7Tf70Vh0IzCRiNsN4OyKt7+0Q8LqqjKgAAATqdJREFUzhElWmtoLARqwYW0YLYyRxcrIeqmYzda3XSduK4LjMgrEWecUfv1l+78H/+Hb//qz9x689nOcDSqyspxHGNMkaQAAN8PCKUQEgipUZwQIoQA0KzjWAiBoB0Neq++8Nydg2tvvvTCZrelrCLMTdaJ5pW2drGKoyDQdb2azoMgQAwjo6lQWquAOUKpq4x4znkURdKojWv7kecDgwyG1sCfdvE/rX/QhRrdDmQUeLTE9i+/+7ej6ztiMTXUUms7CW/SMK7qtCpu7x+kRY6ooywoyzQK/MVySUM2XcS8KnpRazy79Ih3upy+8uJr2GF1za/Cbn3fz/J8tVpJKRljvU6nKIosy5rNBuc8jmNtba/X6Q96RZ7OZpNOp3N1LFVZ1usMm+1hoxkCcMXVRuvVmhDSbre3tve9IBr0NxBCLsWvvfxCu9v+jX/8T1vdntFgMZsCpRijFxcXVclv3749nY5dRihCq9UKIfTSi8/e/+IzZORzz7/MsOM5zi//8i+HjUZR8jiOkyT54Q9/GARBXdfdXgdosJovAHaStNza3k/STCvj+WG7M7iczBBFnXYHE+fOnacODm9O58nJ2Wxv7+ZotFFXhTQSIuS6zuXkcrGOF8tkNp3Pl6udra1RtzccDDAm2iiIYBzHWRE7LuWcCyHiZP3csy/cPDxst9sOpVLUrsswJsvl0lrrudQa2Yw8BDVBgDEPIWIh/PzeXS5l4HnAmNGg0w6i0cb29s52MwrzMqu5euHpF5p+kxe5Qyyx4o1Xn/9Hv/DNX/zWKxElRVzJ2hF14YY+gJYyOtocBr5jjEqS2FhsjLZWGaurqoYQXqX0GMFFXTrAHOxsPHPr8Bff+lYnjLSQCGIWRbzkriHAWsl1vl4XZVpVdZnF2Wz6+PFRuloHUdTqNDHGdcUhQtoKRkimRKvRiCjJl2t47aWbTBlMaG8wurecfuvw4OXtvUdV9vZnn7965yUu9Hd/9D2Pke2t6+fZ2PGbmper9ep6fwd5Tk1NtSwOuqPADf7qy3e++cTXX3v9mWyeKcsvL8aMUsYoQqgsSwhhFPpamawoNkejsqiWqyUhGGNc8zr0ncdHj7qdnlIqK6qbBzeWq8X21g71/IePH5XVqsiT6XTa7fbyPN8cbFVcSA2v7e07jJR1QbQY9HvG6slsmRay2wrffvsHu3sHzXaXEmdjMKx4wUU5vri4eeNWVlTGwuX8Ym9vy0IKkGek6fba/+3P/+T2088FAatKvl4upZEfvf/BcHOj2ewhAIyWXIPNjY3lctnrdCzQ2HEVl56HG42GlGAxmzHmZEXR6XaTJOl2Or6DXA++//EnXGle18NeP8vr0PeMFpvDkbbQdTxjDFeyrivX9dbrtee5GKDBYIAxLct8tDFUtWi1I6NU5AcXFxfEczEkF5eX3U4TQ4AQ8hhDGF0si/l6MRtfNsJw1O+2ooaDGUD63sPTGzcPuVRHR6dbm9vTSTabn/T7HVmL1159ctTvMKgwxtPl/Ox87Lhh2GlFjABIreFlWf7t3717eH2XImwhns3X3W6zKGOttVIYWMmYW5UVABoglpVlOwxklQWNqMyrdc1/8N47TuRby1zmp1lCtZKKb27snJ2fVHUZOO7u4dPpalXK2vUcZHCa561BM9V5ZU0jbEJlmthFAJH/5//5/zo9O//oy7vE92gYXeTFK63mowePms3B5yenhzu7yIJRv7tYLIhLjDFpWmolT89PnYB6Uefp3a0ffPz58zfuWKOS9SKZzo7Hi9X4dDDa8n0vTdOrzI3D69fjZF2UAlNSVPVivkAYCiHrOh0MBpSgvd3rYeiXZV1W46KsqRt8/sXdVrs1GgweHq+jVlNbwAVvNBqz+URr0h0M4zj2PZcw5AXRn//1d3/+zZejKPADhoH2PY86HqGuH/jrZOn4znvvvv+zP/MzWmvPc7QCzAmGw8Hl5fTTz7+8fv26k8HhaKMoqvHlebfX6/b78Tp5/sWXszRHCNe11FIoa9frlZQCIFRVJVLad4PZfHF2Ph70R9paRGDgefPFLPCjJM5xJxC8fOHJZ1Z5Nr64wBAGnieE2NzojyeXfqOZl5XreRihsspd13NdhzoYSGi1hoTUdV2XpcvcJEmqqlrjdVnXyWK5vb3NfM/xnDzNtRQoDClh1loG4FM3bzUDjyLoB35ZcUSd89Xka/0Xux557an9ZtMt4zouDwPXoRhLCLQUcZJaoE9Px+12kzBsZAW9dpUXQlRJmg66Hd/3rbV5VjbbjfV6QSgBlpxeXO7vbZZljhHNi8oSzLUVBlI3rLnxg7A96JdV9vnx436rxRDhdUEJwZikeWak6fVGSVE0g+Ds/ETXHBjtMR9aOx5f9nYGWbImriTYSauyHTaQyMo//dM/u/v46O0PP4HSaKHe/vATacDNrd2tZvvx3XtP33ni8nyskEauy63Z2NnWNfcDZ7meO9r84IffM1bOFlNQ6M1bO9PlIvBoq9NVnN+7d08p3e60+t3uYjmva66UIBhfXl4qJXu9ruOwwWDged4VqIhzvrW91+r0EELGwBtP3HIcBqweX06qgmPsUMxc10WUNNtt33OlEvPFxGijrd3c3hmPx9945RUh6vc//qjVHx3eeKLRiJRSl5PJ5599+dIrr81ms7quF4sFF3UhqjxeUaOMqcuqsNa2olBUFQJAa3F6eooxObh+2BuMAAD7+/uu73/rG9+IoqjX683ns0ePHkkujDGdTs8CCCHUWhsDm83G9tamklwpeTqenF/OlLbDbudb3/xGFPgH+1tpHkdRNBz0PJcFgT+bTpfzWZIkq9XSAm2tDaNAWT2ZTMqyXK0W6/U6LwoLwHK9Zo6TpunDx4+FUkmaV5wTxoTWju8TIA42e7u91vbm8MaNg3a7dfPGdUbJz3/tNVEkgRs4rvMf/+PvKQcm8RpAVGnF8yQp6r/6uw+TlD/xxBOuG0Th8L137te8LoscIdyKoltP3MrSQkoLIJS85rXk3AipszRVyhqAsppTx1UWTNexALBQFliccZkl+dOHN9964fXp+HyerBm0RRYDxX2Hbo5GWV0//dzzSbL2G5HvedAArTUCIPLCuqgZQEqZMs59xwPG/rRJ+mn9gy74f/+//V9aUVRy/v5Hn9x9dP/ms0+9eus2MvYv3nvXIe7zBzff+ehH1iNc206/WyOQruL12Wnk+xUvru0fni3Hh8Pd2XRJwmYJy9uD6y1KEHaqIg+CkBKKKA48z6F0tVo0u/31KmbMgcY6LpNKSCkppYHnOI53fn46GG0uV0mW5ZHvGwgwRtDa2XpGMAYQS11KwY3UQdDp91pam2azeXp6ujsaFVK89PSdk+PHn9496g1GcZYPeoOj40eB5+1s72ZFmSXxaNAqytoPPME1osiDcrVcQqfBpamqcnPYXccphERoPhxuh54zmc0Wy5gx5vp+GscI2M2drcl4aq3FGPuulxV5WVcO9bmoPNc1Rl9N3RGmxuCSF3tbo/fef+flF19YrNbb29sMm8fHJ1HgdRuNZqPx5cMj5odVmVWcF1lKKRVCttq9drPpOl6crH2P8kq6oTfo9uI4jvMUAQIQyqtSl0UQBKPRgGFCCF2u5s/cOuw0WogQaG2aZRjjrMhH7XZWZw3XgYRqrbEfeBAJyaFDTFH9+9//Y4vdX//VXzx+dN8LI+L7j0/HG93IARpALOrKQMo5X8Y5QijLYoSRAYhCoy3gNRcWUsaglrmyl9Px9nBDCmGlAIx2Ah8p7Qbe6fjS9VjosKgREcymk/njo2PS6kGCPvv0k+3d/WQywwgBiJN45XiO224UsnKi0CZ14Pqu5yBp4f1HR5/fe9hqd4aH+y6lb//oR9Knj8fnEXOSomg3OtajjLnVdM7XMYPYdRyEYBQ0zs+Pm4Peero6T+YiiSnWt/YPNDD9ZtgIfEKw53nayPl8UZa55zgX5yfNRmi1Yg6N41gIUXMOoBGSz2Yzz3ellHEaNxphXRfT6WS+WNaVaDXa7aizubGlpOn1+5xzpdTuzsbmaFjlBYGo12lCoP/ib/+2EHK0tVnlVbvRLcuyN+i+8/YPaiEJZo1WO8/TJEkmkwkvi6N7jxTA58s0K9XGxshayxgJfOb7HkLo5OQkSdY3b94cbgyHw+F6NXddL2y0rrCJdc0hRBcX54SQTqeLEG63OwBCzwu4UO+99561VlmNARhfTNuN9p//+d/UFbh//2y1yg/2r/W6PULIejbvtVtX8QwEoU6n0+l08jy/0u9laRYEgZRCaSmEmM9mSkqkLbgCOiultV3Gq8vxOGxGD48exWnRbHcmi+X5+NxxWb/TdinZ2tq8jOd3799vb46kAY1G0zFIAkNdR1dinRa/+ktv/U///B+9++47n997yIvagWiz0ylK7jhOWddfJTtagDHh2rTbPeaEVVUDa61SBMFVnKV5oY3RSlzb3S+KQtQVDnyXuXFRp0InaXm4t7/ZaVMjl/NJ4JBRJxqORryqZheX7W6vLvKsLBBCdV17ngesqYoqjFpYQuaGyHUARfA7v/Gd+TL2fC9eL1vt9nQ2Pdi/kVcFo3R/tJWl6Ueff8r6nijk89dvcgg+PzqmGANo6jwLNhoAoNnF2bWDW/HZ+uD5rx0wuFhNsbGV1EWZ7u3tJatYGTAa9JJ4df3gRiU4BLgsy/HlZGNj48UXnvnf/tPvXds/HI0Gk/nMIU4lDSEEQxMneRAFZV0qWUVBy3fdRbIosuL84qI36gYQOox6UTdL4kajkWUZAuD6tb28rg729o+OJ2cXF5SRi4uLXn/oMgcj0O93BK8WyzXG+OToUavTS7Li5o1bl5eX+/ub56fHTz311GS6BIhEUaQlXywWyoCtra3zi0lRFMxxRsNhlmVXCE+MAABAKuP6fpYknucx5sbJ0vMdXulG2Du7fAwhdB1Ha5WmWRA0GMPSiCBwro1621s7RZ4+OjmH0M7XGefiiWs7VlWrjJfGNqJWlZf9XqvIMkacpMp91+Wcc86VMdR1ijiBEAae1+v1JpPLn//ZbzrWnJ2d3XziVq/XNUJ0fff+6WlV1tSlne7AxWS1mvuR5yDqBl6yTktFWk2q6+qdLx4POk2Zl0G7QTFxAhavUs5F5JB7jy8cP4DWVMD6EFmIpss5scDzqDW61iBOs7iopIXDTqSkPp1cjnpDhgkhxHUcJTiw0iM4bPiMUZcyoCQkeBmXj84uP3n4sKiqdtDe296ZXpwoC7MyMZoPdq4DSIzmLiK15PBXf+1XtbUIofl87riu1GpzYytNkiAMxyfHt5588u6Du36/maRF1w+Mseez6eD6XhPT+XoV64pbbebLX3r2Z72OZzB88YnnqqrSSqxWqzhZAQAuzsej0SiM/On5RXfQQ4RCgN9+++1r1w8BAFm8iFpNq1EYBev1entzc5UUjUYoOffDaLlereOlUuXtG09VVRU2w/HlzPe9k8vTfisSdb27e2M5n+7t78Zx/Ojh4163ra2FRoWN3ubG9ny5wBBqCOuyNFqOxxfPPv30F3fvb29vnp+fb29v5xVfL9eEEEyBluLk6OiFF1/mXCmjN0ejJEk6/c58Pn/++ef/9z/447oSCMFOp1NVlef5zXZDVuLs4txCAKxJ07TZaIW+n5cJwcxo2+r2Wu02AjaO4yyNN7evHz1+wJhXVlmdxC+/8mxdxN3+sN9pvffJ5xAxqzkAttPpjecrx3GyLN8YDoqiEErv7e0tZ3MDAec1ogRjnK5jKWW33UYA9PvdOwfXTo8ebW9vdbs9oKTre4ZgUFfvfHnv+tZ2rxUxQtZprhDc3do+Oz3d6XXjmhd5rq1dxkWWJvfuf/mb/+SfjC/ODDRa2pqX7dCbrvKL+bouK+y4LsaUUeJQaG1dZhSjSgMD4Of37mPm9RrBVQ6MMaYdRoHvO4wRSmVdQWAcBwFlgtA1gt97/HB3+4AyNp1evvfZA4PY00898eDxWeB5DMHjh/e8VitqNpVSuaxc1/1pk/TT+gddiGJspK6KKvB9XvN2o7VaLo3Q+Trt9XqTxTRqNa1BXqMd9LuL9Xo4GgJRLy7PlbWd5obhtt0NZuv5+5+/d/ej9x5PTufrlR8279x+8sk7Tx8e3HzjjTdqIU9Pznf29harNWPMQPPGG28899xzCOF2f3R9/0ar1cIYX9s7ABYWRZbGCaNOVVXQgtlsoqWMk8T1giqrd7e2Nze2tQTSGmHAp1986rgsTdOz0/OXXn2FC7W5sbWxuc08dnxxUUo1z3IIIaUUApQm6en5+fbu7ng6dxzv/PwyzzIhhOM4WoIiL1944YX5bOI4DEGS5jkiZLFY9Dvdu3e/lKJ66sknHJcBaFutVrPVklwJJXd2dlutVqfT2draoow8ePCAYLZezo+O7iVpHMersio67aYfuLPZ2Pf9dqvlUqogu/vwtN0fHRwcAAAO9vfKPC+rCjNHSuX5DiEEEzCejc+mF5Xk4+kUUzeJM6W063jMdQFGbuALIVrdFsIwyVJIidSKENQd9KyQX3xxd52X739x7/j8stEIaiGySn7/nQ++/96H9x4+WsepVTXQdhVXnutKo48n0/lq5QUhgmSxTMYXFx9/+rGFinNRCkkcr5a2FiLJMm2AFzQMIlXJZ/PF7s4uQigvq7Kur6IjiMOUUnlR1JxT10PMNZBC5lZcJ0mZpjmEpsiyjXbzW6+99PSN/W7DG3TaVV4w18WuE8dxXmRZmXeabQwQwhhfsQAQxK7nlZwrqxHDSZ4sVqta8HUcR26UldXFbK4RhJhkZ5eu706LGHPrVdIQfG9+/PD+/d2bz33v4x+l+Wo+X8RxrLVutFqO57366iu/9Eu/1OkN+r2h50ee58VxfHx8jBkpivz49PwqIYBzTh3n8PCwP+gaqxnBjNGdzb3x5TTw/aIoAQBpmq7XqyItKs4rIQgj8/VMat3ude/fv1+Uued5ZcW11kirbqvpYLScL+J1iikdjobdbvfy8hIAAAGizFVSD4ej5WoRx/H29m5d1+1Wa7VaQAhX60QK1e909/Z3l/Pkmaef29joXNvbo5RyzhtRRBlttzuc17vbO67jdTrdw8PDb/zMz0CA9vf3oygyxnQ6ndu37xRlNj6/OD4+DsMgy+ejUWe4tSkgu/fo9O9++M5ffe+dzz79/ObNw729PT/wg8CrqirLskGvm6xXggup9Ww2Yw7e3t0ljGmtJZcQYgghpvTy8nI8ncZFgShuer4oq/vHR47nE4vyWnfa/cGgf3J8GkSt6XI1mS3yvDjYux5zPkvzrKqPLy/G83kYNl5//fXTx0dpURgLOt2eRXAyndz78ovQI9ubG0Ual1VVcmU0gsRRFlHmu4GXpbnve4FDAQBZUUEIEQBFUdRcEkqVUjXnSVoIDpK8roVtdYc/+81vQ4DPJ5N1pbZ3R28+fztbrg53t+7cPvBccvvOE6+98vKt63tQ6UcPjoyG8K1f+LYB0BijlAQYAQCKPI1aDWihrqTEWhvrh62KIIJg1w/WeVbML0nHKxyPjesmtUer6QsvvvjeO++Ptg5933zz6ReGve3VclbUxebGtjaGYMy5oAj3h8Msy/zAOzk6anU6zHGTJJVSLBfzwbA3HS9nsxljtChz1yGB32g028vlajI52RztAkg9FzcaDWNMXldlVT54/KjfaaVF/uSNG5eXl47ntxs+MtgPGxDCQad9//jE8zyMiJLacVlZJHUtCaMY4zzJlDGMOVmeMMYaURMCZVR9cnrebHUgpo4beJ5LoK7K3PM7EIEkWy6XqxdeeOHBwyMlNYTQ84Ig8KqqLssyDMPFYu4FvlGGEYwwRMQtinw+mXzzW284hH5+73GRZ2+8/sJyPpunvK51Hs9akffg8Wld5k/cvrW7PSrLmhH48OSsFKobusxxhbGXs0UUBIPBSHBeVRUA4KqRJ4QQCP3Amc4mha7azcYzhze/8eQzJ7MJMGCRl8t1zvPy+v5wa7RR1OLuw8eY0ufu3F5NLlgj+I9/+Gf/9Jd/eZVni9UqctytzcHi/EIwx4NovFi5WJ9fHCvOv/7GNybzZbPR+ZO/+Judg5tC1ACg0HMQQRgBxtjl5NJ13XWSXC4WBAIHko2tnSRJuoOurrkxptloKWW4qDECmteU0kG//ejkrNdu9rqRC6Afdb/76afbww0IDAKAIFAsl4R6l+v88fERfPmN1zvNVlXXUmtCiZKKUMRlWVeSWAwJDFpNKYykhLrM12Cax5Uumy2viEs8La2tl0r9o1/8lX4z/E9/9he/8Su/borqSkJvgUaQVGV9tY6Poujjjz85PDyYz+eH169PZnNKSRCFk8mk0265rms0wBjlZaGUXC2mVclXi/hK9S2F2rt2sFrO0jTZv7YHCU1WWVGUAOrj83Nry1dffPn47NR33Ns3Du49PO20uwDWq5RLKbaHm0VRKKUEL3q9Xi2U1prXMo7XjsuklN1em9fKKE6wdRwvS3NhQLPVEUK6FPieYwGquEQAWKAeH5/s7V5Ls8JxXGtBt9teLldRFM1mM98P0jJzyJXinSCEpDSDXut73/9uGIajzZ1Ws6VkdXL0iJDg1s3riNhG6AZhZ75KIVTt0CsrXtd5WpQXl9Mb17am03mz3b+YzhyXKaV8398abh+dHjHGsiLDEDfDZpbHrseOx+dOw9Va/9wLr1zv9yAiq0rMl9lup1mL3AsiaeF8udrZGDkIOg4VQnz66OzO/i6k4OR80ooipAUj5MvLy9DxDYDnZ8cNn21tbLajgHNutR6v8tNZ6jA3zfPQ9xGGBNtOpyVEnSSxNHayWnWjKPT9mmupdavXNWWhlDo4uPHw0RFlxChFMMyLwqWk1+6qOrEYWw2pg//ynQ+fvH1bcGWMub7ZDSkJw1Zelk4YwK/93DeqvOp1uovFFCPa7fZqXmsjaqFdwjRQzPXzovTCMOMZLARoRvN43HU8lZVUqu39/fc/fqfZ2V3OTu8889JrL77ebLY2e11CSJanSmrf96uq8jyvKMog8DnnSZJkSbK5uZkWWeCHjuOcnJxsbW298867P/utbwRRdHp21mk2McYQoPV6XRSF1nq5XjuOW9dVHMeu6xkNG5Erq7xQ8HJytrkxRAiNL6eH1zdLbiGCP/P6K3/9/XeF4Lu7u2en54Nery5jALGF+OpWIYoizgVCCGGkpLJaOBRjQjjnec09vwEBYhQNus0kXQVhazaeRq2G7wUbWzuffPopgtAAjBGEEGKM0zRvNqMkzaUU1hiEUF1XlDndVtMAYLWuhRWivLyYDgdt33WV5kmSdFohgJgFbasVxcAPmp1OKHmVF9n9e/fSJHODSGrjeW5d15BgnwWdbiuOY4RgnGY3D24eHT/yo4BpW4ii1OJyufh//E+/HYSN8fnlyWLx1M0bdV1+fvd+s9ubTuevPP+Mi1FRZUIY3/UFr8IoWq5jzIiq8jgv0lpijCeTGVdiORl//c1vdKIwz+Pp6eOf+YVf/L0/+EtrKXUcSqk1SmuNEAg8ijCYzJca4s1B5/T4xI/a6/U6DEMEQKfVMAYopcIwVEphAJVVUnKrTMdntUWI0rLI0rxijJ1cjKNW+9p2z9QCEEIIcT3/p138T+sfdMGvf/tbBEDBOUQQIwdIG4Seg0ll1CpZQ2S0AhYh3/OMlQ6mS1mHQGVZrbVermdb3cHk4vFg+2kJ1MHejYvpWbvT+cYzLwSNRrPRkFKVVdmIIoRQUZRHx48Orh8GQVCkebfXWa4WjusLIaRUlNLZbPnw3qdRs9XrdaeT+cHhtWvX95rNZp6LRiM6Oz/NM/7JJx/983/+m//+3/8HDdTB9nA2Pq8Am8/XjShstVpJkhNa1wqKurZA1xq3223HAAiwUbIq1p4fukEkOHddVykNMALaQIBqXmJom1EEERiPx47rsyBCEDdCv87TskpGww3iYKPQdLbI83K0uck5F9IURdFqNWteh0FICFEKQKiXy6WUEkIYNVsUWS6M6zpxXAheEdcBWvaaftDqn52fbw7avu/fu/8YIoApVYAxKzeHTd9jXCqtretFH3/2KcPEQFCWJaOu5zuKC67EcGOnzsuszBGxVV5ubA7OZ1Mp+DeffTqtxbXuwO00P/jww8NrB7N4NVuuPTfY7ndagZ+X2bqWh1sDw/z33/twEa+fvXGYJgsBIQIsq8o0L5jrUggwcRuhf/z4wTdfetpg+O6nj+KEN1sdiAAhpKoFo9hq2Yq8WojHZ5dbg25aF0rYVqvlMjZfpb12BADwXbcoiit+vEOgRdBaGAa+VJJaABhJksRljCAymS/azUajEV1O5+1211qLmONLbY0GWmMIIQ1drlUtOAQoipqEuNZqz3Ek51oYP2huNPuZkACAhssCzOq6bg52pKg6UXO5mm22+oebe7WS69UaYRgnK8cjDx48WC9XF2cPn3/2WaWUEKLdab377rtcamA1htDzXMboYNB57Y2vK22vXT/8xje+jhD+N//m31xcXJRFmqVxu9kKGvhnfu5rs+Xlm2++8uKzt9er8cVkWuRxv9tniNmquL67dTlZllXe3doEtKGhAdoIqahDXN9lYQQJdpnLqMtFtbW1GXoeJDhqNrUyvuNmeVpUVRA2eFVRbPMkKcosbDRuHt6GiNy7/+iLe19ckZLOz8+DIMjzDCFYFpnv+ZTSoiwrXmoNEaaIYOZQoFRdltvbm8vlAgCJCFzMl0VeXcxWP3z/wzyrvrx7+od/8heTWWyQU+TCCjmdpSeXq6OLJF+VFDtvv/ujw1s3eoNRkRaQEIBJklWlUBpYAMBitep0uqHba7V7dam7YbsZtN//4v4n9+//1Wcff/+9d+dZMVktl4t1IwgdTAopuqMNBdlnX3xpFE5Xie+6zzz5zGQxX2YVBhhBezKeNbzIZxQYAK3N85K5AaTeh+++v7e5NZue1VUx7DTj+UIqoZUBFsepWCdZ6Hp5kSEBotAFVgkh0mQpheK1WC/XhDoYEYgxpj5BTrfb5VxIqbmxshYudSBAnuvs72xQghwClFJptnZdTIBV1moADWFYWwu0rIoq8nwKrTbGcRyAcVmWGEIIQFXXdV170DHMAKg7gxHnPM2SG4d7l+Mpow5FZD6bXd/dwwQtF2uMyScffXZt/3qeZ0cnp8wJwqglhORVdePWLQCANaDVahVV5bqu7/tlWT777DMIoTTP969d37u2X5al63hZlgml4kV6eHgYx+uzk4skW959eOwxx7cyzpYvPffi97//l+3R8Pbt2wihxWrdjYJGg50/Pt0abUWRv5jNtFGl0BalBBHBVZ7n6/W62+0mSdLv97N0BRCSQiGEECFSyl6vx1wMABhPL5vN9p3bT3FRpUlOMPEDv6zywPes+SrXME0zAKDne0VeN5uNNEulqKEBg3737Oy83Wxiyi4vp81mEwGACfCkwRgzSnq9oe/7y9nc9/2qLCCyWV7UNceDXjpfHeztUWW2Rq297Vc///xeIRWwRmldVrnvrsMoiJOlQwMLrFYqCF2tVRANji7OZ5fzU1U9cfPmFR5stlww5GQ1OfbP8rJUxizTRFizubGRF0WSZMPNjaPT093dXVVm1NsnCBX5YrSxcXJ06jB2dDZWmJ3Ppq1G470fvcvQc42mqzRVwEILkDFCWtdpImD8BkAEQYCKoup2u1fMM4RQVVUuY37U4EXpu4xzySjNy5oQZK31Ix9ZUFWV6zBKSFkJrbVWihCKasnD0Ge+a63WQArFEcVcibyqIIQWAKAtxTgMG14Q1HXpODTyQsd1hTLdwTCtZCOKxpeXjUbTAmCg5UouptMizwEAwMLDgxsGmCBqHP7/23uzXs2y+7xvDXvvtefh3e943jPWqapzqqqrq3okezJni5QFi5EUxLYkC0YAJ8pNchUggQMkQC4CxMllgBgG4lgyQCFIbMWRaFOkyDTZA9nsuWuuM593HvY8ryEXJeQz8ILPV9h7/YHn+a/1e64dmobdanlJEjcN/f+Lay8nk7quR6PxarUiRG21WgCATz79PE7SJM6qii5Wq+U6PD+7MFzzcjKqaNPutw9u3W4Y4lW1no4YzV98/vDb3/pGEK8FREePTzzTPXl0n6WpQRQkmsnosqjLNMvSsq4Yo7yuqirPc1PX1+s1Y6yitaKpWFGeIbgc28nTlDZVXZRpmq6DlRBsuViFq7DT6ShEcVzb0FSIhNdyCFHCMILPzBZrdIOUVVWWhSwpluPMl0uMgOu65+fnDeNMwGWYLpYhYAJCQBlLktQwNUII443Xsh3H1lRDkuXlbJ1nBZSVKEvHF+cnT590250b169c3d/xWw5CshCieBYXYMA513Rim6brmpbdMlXn4Oqh63hFXs6WC05pkmUNEHXDZ/NVQ7mkqKP5wnK9jz/7TAjRHWycXUxW67huxI2r1wSgMhLtdns2nUqShKAUZpXt989mEwmjnb2hrCrdTmtnawA5AxCVFJiugxQsq8rxycl6FaxWqyJPXdfLqxJKWEDIIagp5xSohsUErKsGSYrjOIRoAMIiLwHCWFEoBIqq1xy2PM93vCxOf22Sfq1faSFFkfIqF5ADBMq6BJgjBRZNASXBBVNk2bFNIJgi42frRwCApuiaZkAkMQZ6vb5jOr7fZYx6HV9glFVFFMVRFHHO67rK8yxJEoFAvzcgmjaZTK5euaLq2mKxGo8nSJKePn3aNI2ua7IsI4SSJMnz/LnbNxmliqKs18HJyanrOISQy/kozjO/0/7Fx7947923RdUAgVq97p2ru//mz/60iII4jaezJef86NEDRSbjs3NLI1mS9Pt9AQAhpKrLOIt1097d23ddlwMgq2pW50mWYowB5d1uV1EUTSWOaQIA6qYCAHX7gyzLOu1Wv98/OjqSZJzlSV3mW8OBLMtJngIAmrrhjCdJIkkSY9QwjYbR2WzW7/c7vvvhhx8ahg0BrsqaaDqHWFGU09PTo6Mjw7Jms1kQRLbpAM6rKk/TDCM5TRIg0L0Hj4uGMiE9fHI8ms6OnjzGQjiOc23/uuCgqqosz6Mkpk2JBAiCIAgSJJEr+1c1VT+8cpCXJdTVOE1nsxmSSc040Y2kKE3DOh9PT88uGw4Wi/WT05OaUt/zMOOKZq/Xa1OBjDEAgOXYWVUyCCeLwDTMVRS6vhumyb/7wQ9c36qzOA0jTHQEJN3QAaJXrt8wLa/T6emGVpYlxjhNE0LIKggkRanqpqGMAywTUpU1a3hVU1kmjIM0K54B0zmACEmtVgtCSIiChBAQYw4AFQzLoCxKxmoqGggBVnBcxOtoBSVY1EXTVKZlNZQyCVVVs7m5DYQwVU3VdBlJvW6fCeC5rqqqcZFQzghRLMsCAGimnhdFVhSe53mOM5lM0jzHEuacf/DBB36rJUkSIYQQEoZBXddCCF3VCFHmi4Xf8q5eu7ZcrheLBUF40OtmSVIWxeH1Xc6owHJKxdG9z1fL+S9/+cv5fJFEUcf3F8v5wc3nf/M3f8u17Tdee5Mx3vJ9AEARx1kcE0kZTyen5+c1ZUma1IKneZ4muYwwozUQTNWIZdsIgaZpJEkSHLquu1hO7z14cPPmTcMwiCTLMj4/Pc7T2NC0VssDQOR5SmSSxDGta1UmQgjLsherNQfo7t27hmGapoUxppTKsrqYr1vtjmZYo8lMJTrCSpqW777/8y+++KLI6zzLLM+ezqf72/usoJphYVk5vHltuLGRJNF6sTw9OsZYGmxsRmEGACiKIoyCMAx9f8AEJJrm+h7j6MretdlkfuPGDdt1F4uFEHC6Wq7WkeCwoSCKiyBJKyCILB9cu4YA4IxzzrOi1FSd1rVhagKJ8WK+jtZE1zq+b3dbNeBpXbvd7vf//b+XJXjtyk6ZBVXeBPPlw3sPRqN5XVOEUNk0p6enMiF5VS7WK1VVyyqv67oo8jRJy7LWdf0Z3L+oKlVVNU3DkoKQDCCGAMdxDDGmjCOClZbtAQZEw1VZNTTzWYGBAKysiqosK8ooRvNwXda5JKOGsbjMMcaU1lWRISA0orumvbe9O+wPBGWEEKLpkqLUdQMAaLfbskSKuuSc1XVFCNnb2+OCuZ5j247jOI7jUkoxxkmSmKYJIaSUrlbr99551zb0pmmKovBaniRJj+59evr43v1PPnjthbuOpgFFDtLi8nz63N2XoCxfLuYa0TVCNjc3/5M//s+eu/28rJppXja08WxnMZ1rRHvuxiEBYKPXy/McIRTF67wsn23RiqLI83K9ChhjdV1neQkhrFkNoRBCJEmi67rneYvFIgiCuq7ni0W73dYNzW97QLCW7wIAGGOmaTDGmoYCLvI8K4r85OQkSlMsw6pMsyIDgjeUIoQwkm3L2du9QikTAkAsCYHrmjVNE6zWiuCioeejc8p5HIa3btwkChYcbG1u7u3suJ4TRVFdlu1Wi9E6WC0JIUwACiAhZBkGHAAKIGJ8w+/eu3//lVdeIYrUNE1RlpZlCw5MwwICWrYbJvFWu+tYVlqWkkbqKtMUbRwkNaVEUsL1yjC0pi4no4soirCiEl0DkuL6bU23ZdOO8vWXXzqEoHzphVtf/+pXoRC6rq7DMEqKXq8bxzEXAmNc1SWEcB2s0jTFsgwQppRS2jyr4QQcNnVdFEUcx3VVQQgRxllRCACQpRmAcpNom70hQaTnDzCSiarWVaPKxHQcTdcN1Xg24YqqAhhxVmEJ5VUpq4pMpJbr+i1fUFEmmUXUPMuiNK4ZjaLw7OwsSqPTy/OHDx8qqrRaLLCEJtOxqmsIoSgKe71eGAZEU9dBgAA4Pj4uy6ooawFBb9DPirKhFEK4mM8Rhqau/fjHf5Xm4TvvvfNv/+KHdV2naTqfrb949HSxXBdFIyjDAqRR0ulsaIpcVvTg8ObP3nvHMPW9nW3GWBAEnmV88P5PizKXZPTsl4IAYCyZjrdzZY8jWQApSQtJktIiN00ziCNd17lg1w8PEUJVWUMI0yJXZHJ2draYTaoi57SOwlW746sqCcPIcRzGmGE864eVIZLW6yBL03bH67bajDVlmvt+izHOAMyLIo6yV7706pOjo3ZnoJvWredvP3hw/+P3f7GYjHrddlbERVWlcbGYrSQZzxdTSYb9nn91b9tQlb7ffvnuHQDA6enp/v7+bDYpsqRIkyzLiqpI4lCREZbJ559+evf556uqAABQTgkhUIJ1XUEIO66HMf7s83uGZc9W60UQ6ZrBsUIp5ZxXeVYksaYQSuk6SxSiRUHYNDXEWLetvOFHx2ePHj3UVHB6/nAdTFst0zZVxpjrtgVjWZJoqmpqehzHGCOIRFmWy9XiWVADAEAIlXne0Cb7m7fpthCiYbWmGZZpYIyQa3uubduGLWNsa3YSpIZm84Z7tocQkiWl67gKkF3doIJyzlRZoVXZNI3t2lCWGsh3d7f/43/0Ry+9cEcG+OzomDYNhHA0GjHGdF2/HI0gxkEY/uQnfx3FYRhFQohnrpZS+mwaPaOGTyYT09AppQAA23G9ll9WdV5WZVkVRVHXteX0vvK1b42nq2VYOX6fIAlxur23e3Z+Ga0jDHFVF7PJyDCMn/70PVplCKOr1278/j/8/clk0m61KGsGg8Ef/uE/IARrsnJtf1/G6NnBExB2+73d/Wvf/s7fef2Nt/avHbTb3c3NzYvxJSbyO+/+VAhx//4DRdVs28ZIskzH8ztvvPFGu91uaNXQGkIUxQFCSNe1pqFFUTRNzQVL41iSlbIsZUXWiRKs5xIUjmMnaYqwLGMZIWTaVpQlVw+uvfLKy2999asc8sFwqLn2Yr1qO9atvZ3FOq4ojKIaY5xmeVWXnms2VWHqqq6RJAq++fWvv/DCC5ejqQD87OyYyMpivsRAVFURJLHn+xvDjSyMsIRkWa7KmtY1xtjQNcvUDVXRXS+vqW15WZJgzdYVXcYoybM8jVum7mi6oZqGYYRZGq4jwTitai7oPFpMx+ONjd2aS5PL2XQ6Kau823YErxUsA4F0XceSRBS1aRrf9WQFqxrBEiyKMk0TTdMZY4qsPINot1otQggAoOFcJXLTNKZppWn2axf/a/1KC/7R7/89DnGWZVmWKBpRMKk5B7TmAquGjiWAOBMcVDWXTCVPSlmWp8HEtT3OaJSGuqrt97b+4R/8AWDcanX+13/2zxijlxenrtORJXx4++bx5UXPsUcnp36nxyUsUej3uxCB89GlIsst142jxLJdDGG0Whu2yRhL09RxPYwxBFLT1BghohGiylEc/uLnH1y/dsAZ2Nu9+s57fykztXv9yvFnv4jmk/F0eePOi5bb3tzY2Bhud3vtJE5pU3320fv379/f3dt7+bWvjMcnCoKffvJJuzMsy9hu9ZKKNowh2iCBbt960eu2yix3HLMumd/xfvz//vV8Mbl98+aPf/h9RbPuvvil1TKIwvXedrumTIIoTVPTNBUiQyzRhlcNfAaVpZRGaYYxNk2tKopWq1WVtWCMI/Lg6aXraFmaZ1lu2UYQhPtbu1GWDXY2VaLIWE7S1DDMRw8+O35ynKxX7a5zcP3m2fnMMIhpIAXD/b1dSSFpmli+Gc9zrCBJxrRhpuPHacqBuJyMXNdbTGcaQRttm2h6Vdcn51OB1HbXj4KlImuA11iWDVWybC8MI1lRkiRngmqakceJQNV4srhx7cr+9tbZ0VmQV36/9+jooYRkCPg6DITg+3vX6pJxSjVNe3T0MEmSf/C7v6Orcp7nUZZyLsWrRVQ2QgjbMDVCyqaaL5eDwSBYrnXLdA2dIoyhZKgS55xSCgGiDZVkKSsKVVGKqnJsE/72b3yt5lDVTAFYFKyv7x/kdV3WhWU5k9lMN1SdqJRS2/EUVV7MVxDjJ6dPbcu2LEOS5bqsWZEf3rylSNpzB9d7/aFg9Oj46U9++rONbi8q88VqefvgMIwiw7bWs1VQZ1ueD3R9uVxapmkqJK9LTSamaQrO1kFY142mqbppzmbzve2dlteeTqeSrqzmi8eP77/25dcxkoYbWxJSv/+X3/u93/5703j5r//0ny9ms9/8nT+qaElUTZFlz++tl1NZlpfz2cH1K+PJ6NH9h5rpCkgvTo5rSrnAsgQ2hjter385HrVsi9X84OBmVha+22rqWtebp8cnL999ax1Fjqu//97PBJBsy779/J28yBazURiGMsKc8+livtnvSDKGAO3sbD15er5Yx5KkSTLgjE9n49Vssrm5ubm9W2Y1QGK+SBAGsu5eji4BEBDCjm2FcfLcndvj8aXrdxSFAAHLsnjy6FHPs7M8hQClZUMwGp1f6LpuO16338dAaCY2dVzUGa8hgnAdJf2NjX63e/T0JE6TMAqKMt3eGggBJIg2BoMnx6cMSADyIqt7/W6cJqamCAF0ywpWIQDAsEwMsQxF1WSzZdjv+YO2z5kIopwBHsTh5WhkW5ZMJEnCrBGaqtOGm6YpK/j0/LTrOU1TD7q9oq7v3H5xOrlYBHHDqQRxmaRQkUfjy26nN+j2vnhw3zZM3TIN0yQIYow55w3lCCEhRJqmOiGQKJBR+OW7h5vbV2rKfN9HnBFFPT0/t/2Wqsh5niNZqqvGNM1Op3N8dOp6dpwkQZYKxgb9PhMiizPLVPuDLVUzdRlvb16pm3J7ZzPPyo8//lhAMZlMT0+PX3/rzcly5WrmL774gDVsuLULAEBclGGSNmXLdjq+//T4WNWI5bimbqi6ul4Hnu0M+8Mwjs6n4ySMNrrt+XyRxOntOy+s58vF4ujlF1+bjE/vf/yh6W+99dXvVE3y5PHjbrfTam9EwTov8qYuN7eHo8vLneHG51/c54INBgOiqHlZnZ0e3b59e7EOy7ra29mJwrjfH9R1pRJDkqWTowe+7/vtnq5rhmkRomZZSpu6KCuZEEp5t+1PpxME4Wq9xojKkI/H4yZPsGrlDWganiaR22oxWj9/eDXL09lsoege56UsG/fuPULEpbThvLl9+7nR6ZO8rBRFGWz0gyQzLYcJEK8jRZbHF6cyQjJRs7Iso8QgOM1rhIjnuRJBOrFsB+RVbpk2RjwvsqzgjmnPlvMgSVRNBnUqQ+XFl+5EwWJ/d+/0cnI6mkqyyhtW86pumGNqWVF2O4PlYimQgBAOe30o2GI5N11vHaw6LV8IgJFSVlmcpnGREUmKs9SyDIIVoqh1RYUQdV3bjjlbzFzX5Q2wTBVJsiJDiImmyGEYpVFs2Fae57yhm1vDy4sRwETCkMiYEGKY+rN+e0JIXldRGPbanSTPCJbhK89df+XVL9eU2oaFZDyfz8MwJIQoEri4uNjb21+tgqyqvVZHV1WiSvP5XFE1jSiEkHUUAyp0g3CBb968DSTQ8gbjyQgjvrO1ZZutdbCglC5Xi8vJpNXpQsr+9P/4l3u3bl0Z7MRRRCQpWq40Yk7m89/45tcULE3DxWQ2p5ReubZ/dHTkW57vep1B7/s/+qGnmbah+532vfsPoyR3TFLWSbiOFJo3dfaP/4v/7sGjJ4aCg/UqCJYHt+7O5+tO2+92/cvRaHO4Mbq4cJ2W41qW4zAGgyAwDDVYrTRDf/tnP/3KW18BEDacWrq5XARUcNdqZ3kaJCskccdscQ5pXXuOxSFnAlZZo5uKaZrn5+ftdrvMEwVxiSgQye++87aqqk3TFBXDGEsIt1w9XC9d17XcLhe0rmgUlY9OJp7rYgk5js1pjpEkGFWIEud5UVWEGEVeuo4TLueqosRZmeUZaFi0Gpu2M9zcXS0WXq+znq2vX7vy4MnpjVt7B1d3KKMIqydPHz88PSohtwXp9Z2Kln1LJzJeh0l7eDWK1wDKCOLPH3xsmw4EVNfMsm4gwIZhxEmoqQZgFWdCNkwA+LNa9bqsmKhpLRSDlFkuEJAkqe15k8lECLi1vR0sA4hEXqW6ZuqqLQDN87zle3VBEeRJloGGIlmSZVmCkmHJVUnzUjR1YVuaLClN0yRJMhgMOOeKpj5+/NjzvDTPPcf5tUn6tX6lJf3W3/2dv/rhDyxDX8qqRCCjnAtmanaVJxIQq/nM9/22omlOa2dr+PP33m377mK+ohW8CEO/3fNbrSenJ912+913f7p9ZV9R7NPTs+VibJr2YhHbjomJ5nr+6dmlToxOz/rjP/7P0yR5+uAhZEySFc/z0or197cfX15stlppURRVxSnVFLWumgjGLce9PD+lVVUh+SxYKYYuhNjYGNw8uBEnwXK5jMancTT58IP3B1tXqiTu9bqqKkuStHf1Sp2XjuOoqhqGkeU4w+3harVyEDo5v7Qs84svHliWxoQQjFcVJYQ826watlnVdZKFDHBds8No6XmoySmW5aJiSR4Zui7JSrCOirzq9wYIANXxzy9Ou33n03sP7rz0moTAw4cPen1vtVoDKM5GYxlxHqyyLLty5erbP3/n9p1XZQwFa6I0Y7T0/VaSxFCIJE8xhrqqZkWKEC6LuNf1syxL0kQhikpUKG0G66Cs6o1h7+Rk/rVvfumdn73ntPvrKHl8dNbUzcbGYLmY3bh+5c+//387Xsc1LAiEu9WbTEeT+WoWUctSwzg3dWPQ9oMwafsO5yxPE9M06yoDnNVNmaeJ63pN01BKs6JCCDHOmoaWVaM7BiGkqKssL3jTaJoWhHESx4aphVHQMEYURZakZbBCkhSsY13VmoYhhASEQghFUZIkMW1PMAYANC0dcNY0DQOCUjqfzyVJSsZZXmRVVRGirNcUqYb+5ptvLhdr07L6frvf7w77vTiOgzCcTGdhGC3m8+l02vXbYRSYlg4Yf/3VL9Vl/uLdO7IEDV396je/QTlXNeXhp59dnjwhGH7tra+kSdJuuWEYrVchkpTXX3+DNzROUlOxrg63TVUvkvTm4WHTNFSUxFQX4azhFS3rPMsA4+PzMUKoqKogCE3TlCDaHA43NjZpzQSCkiSdX5xP58skSV768hsHt16VJENBuLu5M9y+JqlWXjHPNveubN+7fz8IwuFwo9Xy58sVACCMo+GgWzfNcLjFGF+tlm+++VYURUVRRmECJVkIoamqbiBVQ6oED67sqpIMAZVlJCkybRgAoGkq0zaIKnPB8jyrGnpweLuk4Pr+VdtuFQzdvPPKcGvn4PqNF1948cUXX93ePfC7G71e7/zkiNclq+J2y2nqYm97x9QMjoCiEMO2ZKLappXlcV0WRR7nWSQERRA4llHleVVVQZj4Xms+GWMIZQk/uP9UVjXTI/2NDcpEQ+H7nzxU9c7lyfStl97iRc0h08z2vccXAFkvvvz65qCn624Uxa7XCpZL2zTXy0W4XuZlMl9Mx+NxUxeX40tJktM8D9dBkiSACSgEIaSqa8e2IYdEVi3TcQyT1U2WZbqmpWleVoWiKFAIXtUQ0LIsn4WagjGEEAB/00qQZRlCKE4z2lSCU8BZWdcIobquO/1+XdeqqiIEu357o99rt1q0rtGw1/39v//333jrLSyTyXQ2Gk0e3n8ShLFE9C+/8ZWr12+WDb1xePP06BFq6oMr+9/+jd/4vf/wu8PB5sHBQV3XkiR9+vFHX3rl5ddee+3q1avT6SRL46LIfd8HgG4N+5zzyXgaRInv+5JhYiFG08WXvvT6a6+9VRZVy2tved1iMtu0/d2NrdVqRbC00e3XRZ4XRctv6YaapumdW7frhjacjWcTCStQCMarvM66nfbZaDTcvfHya2+YpkkUZRWlltPyWq12uzOdLjaH2wDgo6OzpuGqojmuV5W1hPFwo18U+c7u7mBjI8sqy7IhgoIKRhlCiFJKa4gh5oJiJH7+/rtZGulEhqyWJaSpqqKpruM8mwqN4AChVbDeHm50Wi0A0NZwxzBcWdP7w4Fje1vD3eHW7u7eoUKsi8ni4dHpchXZli5JUp7nRNd0hVBWT2cjVVfysqCC1bSqypw1zf379zzH8ltux29BCF3T0BRMJPGDH/zA8LSaIdN26qIJ14FtW5RzQ7c0y5vOol5396Xbb1y5tk0klsRpnJWffPZQwnJV0q7nV1neanUQQnt7e4SoHAAkSxyCLK90nRBC4iSqygxDBIFYLVYYIkWSGGNN02RZBjh3HE/T9GdoYsMwxuOpLCme06qapqoqTZGwgLSpWFMlUcA5L8syTVMIQVHkRVFohDBaPkPHVXWJMV6vV4qiMMY6vu+7NobC1ImhafCHf/5nMtGOTi4uLmZlFRHTWM2X3/nOt3/0o7/udQe0akxLOzw8/LPv/cvNwYZhmK9++cuWbQZBBAD46PPPfvD9Hzz//PMv3LlT1dSw/acnTybzues4SMDzo8d3XvpSlnEGmKZpEGHe1FhGSV4CxjzX5YKZhhFFsaYoAKMHT5/qGGZ5ngRrz2lFtMBE5nlRFtVGf+Ph8ZGiqnleDfuDOAxYU0GivfzcbVnTgij0HSOrGEHCbfVWy2mWZZ1OB0JptVxJqnb16tVgtfQ9bzwe9/rtQb9/MbrIktLxzKZqKAUPnzy689ztNM2KporCsNvtCoBWYWDrxnR8/tEnH92+cXj1+g1dU5uGciABWdKIsg4Cx7arolCIhiGsq6xp0MXl2fnl5eHhjZ29fYLhYjaxbZtyAbHsmqRs6tOToyKtyqoaTxZBFCuq2vXdvIjLquAQcCYKWgvOMeNN2WwM+p1OO01K23K/+OKLVVJpGAjRQKK2/E6SpztbXUvdRDiJk5iolsiLMI4pp5w1L9+98W//8u1XXnl+Z9D/9P4jBhDGIo6yXtvpdjtCVHGaPn1yHytywWkSp0TRaNMQGRvEBBjKsiJhRZbloijiJGz7XYAQhFCRpFUQuK6bpRFACGHMmEizRFWUzY2NMI4xBEVRCI4Yr33PWywWHGHEOMDQMIy8KokkmzJehSGSJct0mqZpGJcRxhJijCkSIopS1bUiy0VZw3/63/+TTmdwdHwuILz93PMYAUprjDGE8PLysmnYdDb66te//t/8k/9qZ3Nrvpj9T//0f+ScF0XZafmYKA8en3Ranc+/+OTp0WMhlMMbt8az8YMH96I4fuv1r8ZZolu+LMtJEsuKstnrzhfrhglD0yjneRpZlm05GhKobqosjiGEAIq6rLIsy6vycj7DknRtu2eqzpOj0zCJvFYvjFYKVjQFZ3lh2ebWcFMgbJuWRrQsLbAsbW10f/D2j3Y3d4nuYAnTohhsbpyen3c6nWC+cBwHYbBYBZ7nJUna6bRpVV9OxpubmxeXY89rQSHyNFZdF1RcNlC8jhAXm9vDqqqCIHAcB8tEkqQ0zQWWNRUuJitJUTzPnY7HG8PBMsyPj562O64i6xvDHq/qoiwNQxMAGQTnDUMA6LrKOV8s16zh5+eXq3DBaW3Z1joKOADno1NVNjBUmjrf7u0wVmEu8iJVdTOK682+53vWp48uLUPb2N70HFNwFieprmtJFj++/zRcBbuDboWAoYKiVvevbCfJyrOd8/GEaIYskTxZd30/yiqERVEk+1e267ISZX6xXJ1Mxppptom2zBJN08os3xzuTGaXHCBalRubW5xSwBmDSNfMqsxMzURY5FkhEBAImppRF2UUh8+IvpqmyRguw4RyKGMAOKMQpWl8sLtTVUWwDpGk2oaeFRETkqRqnHMEgKrIgteGYXAGKaW/dvG/1q+04DfeeOW7v/27qm4ChKbjcb/bNh1LkYmmaYZhPHjwQNM0v9s5enhv/8p1hOFyOb93756qkbfe/Fu24/yLf/W9r7z+2tHRURRFk9ms0+vP5ishhGZIbW+DqFqWZQLw4fZ2w/jHH/zy8PCmpOoSlBpBaVlphIwnl47jKKoWRWG34xdFtlwuh71BlEQXo5FpWZ999OHB9UOFaOv1SiZaliVCQCCaa9euTWYzSune3p7n+nVNFQkZplMXBdQkRFmc1Y5tCCHW6zVEsqIolqEnSdo0NVFJleee562DZZqmDWOW5TRC9PyOrmkff/hhf3NTU3QKK0Mz6ryUVGU2HbOmGQw2iKavVivGWKvdBYgpSMYYK4ry4S9/cfPw1mQV9Tqtjz77yPd6uqHNJpNXXn65KAqEJCwoVuRnV5yasnpGzvF9fx2F773/7nh8iTGO8midBowCGcgSQr/3W787ujhdLMP33/vpzYObeSV6bfvk+Mn+zZcpazzf5qzKknhzcyvPq8ePH3e6/vj88vruxuV80fHafn9nsZwRBe3tbP/4J29vbe3GcYQg03W9zKlCcF5kLddpWN5que/+/NP+5pBWRRDHMpHjMIZQDHub8+nY9/0qzy3XDdK8LjPXaxNVXi+XmqZJCEKAJEnqDHpFXhRZmmSZLMsaIUVRyAperWOIFdaUnDOBsGUZfc9dr5dxljcUtF0nzSKi6VwgCBHnHEOgSEhRlL+Bp37n278FOCqKggpxeLCvqQpCUhBEn33yiaKqFW0Or11HAr340iuu6yqy/PbbP9F09fz88sMPP/zW3/7bZ6enj3z3u9/97ny6MCw9TOLReK5IWq/TEZh9/sWnt2/cEYBHSfLk6PjG4XWikiRLmACW48gSKvNUJ6qElTzLJUU5Pj61XctynSAKhBDRav3aSy8Pe4NOuz2ZTpumKYvatTwGeLfjZXmOEJKIQgWP8zhOMgkIl3JVJjxrEGT9Qffi+MT12+sgsm1bJ3oQFwJARTW2Nrof/vKXQbAsy6q70XtydCxJkqTqaRqXRbm9twsAELxBkhSuQ7/dCsNQNXTf8qqqVhTFsm0iIYhRy/eqvOSCcVYlUUhp5bec+WyiacpqvWy5+622zxjLstz32xgQTZWrpsmrQlOUPM/W4aphpSKTl194obp58733312sp3meIyQZlsnK6vTs6dnxU471m7efUyGSZPnk5KRqGlWR84qVWSbLcGOjkwZBlKQb/WGwXrRs85t/661//i/+1aQJ1mnjuBqUjZOz87t3705HM0s3iyaL09TTLYCgqhhpWuuqWqQVBsgjxrXbt/78Rz+83u/dS3MmagGYpmkAIFlRmqqiVQWRnOTZcp26lqPrepalMsKA8/l4qqpqFEVYlmVZ5gCUdZ2mdcM4EpwLARDM8xwAriuSadqLMCKaFaepQIgxWtUcQlgUhWGaqqanaS5LSAgBv/e//29lVtqePZ1OLVMfDgfL5frZY0WAIcS45Xiz2cy1Td1Uf/7+e0+PHnMhtjevfOMb33r09BGAcpEEtu3dunEzigPDMtp+75NP721tdo+PjxeLlSRJGxt9t9X+4IMPjs/Hg/5QQMl1nSCKEQDL5WzQ66d5QTRdCFEVeZymlJaAcwnj2WTqul6r1cEy2BgMP/74kzKrGlZiRTk4OHh0/x4hRNaU5WoFMXb9NuAszyvLcquy8lu2Yzr3Pv90a/eq47iKouZZgSQpy9JWu8Xrgii4KvLlcllxdnlxcXVvH6uESLJttdIs7vd8U3fGywXiUNEURZIorZuK1lVt2GYcR7ZpxGnmOqZgHMuSoelVXUoQY9V48ujB8fmxrlpbw43RfLm9tY0w0VX5/Pyy3fK6/V5d14gzVVUlGTFOgYCMsW63izEuG/Yn3/uT45OTKI5VCStAarXc3nCHYJgHyZMnTw8Orhu27XrtVRhJWLz66gujy/MHn31uu56sGJN1qCDRssyz0XwxX964eQPhRpaVOssc1+McBcF6PJ8ZBrk63FR0/fGTEwEkW9cGQ5tzbptkOZs9uTz/o//g7/7rH3+Ql5Eqa1XZNIIH66WE0NagH2aVphNLV7KkLOpSlmXX8kaji+6gT6s6TkKGZRljTmmeZ7qu50VTM44w5LSuaAM4azmWoWlJURVFJUkIQmEZRsMBEDCOIoTQ/s722dmZY1m6riLbsVq+KziFgO7u7jZNQxS1qirOuW3buq4zTne2NyUZx3F8dnaexNl8vuh2+9Pp1DCMrY3hl19/y3KcdbhyXVclyvnFiesYdV12O527z985ODgwTTsMQ8drtRxne2vLd5wsjuoyWy9n7XY7KzNKa1pmvms0TYO5ePnO3Vs3Dl3X3T+4bjjWbDULouDp06e6rqVZIstymqaj6RwhfHD1ytfffM0x9a3hkBCiGbpAvGK5quGsyL548MWtW7eKpqrrCgCuG5osoZbnsrqqG1aU5WK1FBAwxvIse/zoUb/dMXXDazndfj+I4ouLS0PXbduSEMqLQjAmS1Jvo885VzU9CNcnx09lWeacCw5q2shEqet6tZxPxuPVYlGWyeeffPzS3eeJIpdVnmcpBhBivA4CKAQVvOGsprwoKSHkWUx9dnYWh/Hf+da3/9N/9I//8D/6Awhwq9OjEMfRKoqikoqNwYDoWppnnFOiYCDEu+/8PEuqyXjqe+7msNv2/LoRl5Mlw+r1GzfqhsmyggEkhJS0mS3mHEh+b3BycjKejEeTiet3GRef3Dv+5P7JbJ3UFLZ7vW+89ZV3332fluXo7Gxzc3h2eYYxlGR869bNq7sD29IVRXFN68njh7vb2zcODtI0rqrqYjRy/RaSFA4BwliCyDAMTdMbWnHOsyx7FmCrRKuqajpbqqqqKArnPM/L2XwtYZKmOWegrKqqrCFAq3WYF82vTdKv9Sst+N/+1/9lr9NRVcVxHCGgSshivrRs27LNOI5lQiQI66ZSZDyZrN5592e9bns0nn7rW9/Ky/K5m4dpmlc1xQjrukxrtrk9uLg4z4tSQcTvtCACYZyrqkobNl+uO12/zJqyKuM45gAIIdZhGKeJZZhlnutEPh1Nad3oinT35TsNg188fCTJGAlQlqVl2kSRfvLXP7t+cDVNk6JqAGsckzx98sjpdmzb7Qw2u4PBBx++zznf3dwaj2au2/Ism0LQaXUNQ8/KSoJICLFazPKiUnX55Ojpiy++lMTJ6fExr5vB1uagvykQZELMFiOCVaITU7MghKamTWdjJCm6blRVmZelY5m//OD9l1961bHNtKgEYwAKQ9MEgMdHT0/OT1zbadn2lYNDoqhFzaPV1LZb48WcUe5YdrvTapoGI8kwjDh8dhVffwYfNUytKktVd4gq/cX/8+8eHj3J4pXvdyxiazIK4mhnf08woBtktVppxJrN5ld3+uPJyO90EEdcIFPX1lkTJyFGClEhZyWGUGCZMTCaLGzXxrwxFXwxmQFJcW1vb3d7dHLcMN72/NHs6ObNm0Vd2rpTVPF0vpwtl5aqtNutYX+ws+n9yf/5VwLhq5uDuq4Blk1LWy8CCmB70KuLaj5bRlWGuTBkybTtqqqfHh8rmvHsc5uqylkjGG2327PVEiJFkQDnXAgoSUSSpcV83mq5G+3O2eWFRiwBOPxf/uf/odvurdfrjWF/tQ4dx0EAciA45wih6Xy+PRxS1mAIawY5a2zTggg/69gkBJqGsVjGlmlB0AAhKGO24xBVSdMUCGyaJufUsqwgSmjDGlpzABUsrYKIA6BgWTMMSZK+uHdvdHGmSKg/3Fmv15zS5XrOOLT9NkIoS1LLtCEUQbyWkdKwxlDUIAocxzl6/MjU1TBPNM1o9TaqslxGSw7AVmewWq8lhbi2m5e5Y9sylsM4adktyzazLLMtd7WcJEVGVFIX7O6tW4osR0kEBJJUJYyDIA6Hva3ZfOyZFtFMVSUXZyetdq+oSllWoihUFanVbiVBdDm67Ha6ruthCVdl6fm+a5kMsCgIL87Orl0/FIw1AI9PH02mSyST6zdurlcr07Q0XVMkRdO0sioAAOt14Di2jKEAXJaUhglNlYhs1Kw5vzj56MOP+/5gNpt2+2235ZR5g+EzsK1pGPb4/CmC/OrVq6soUYkqQxBXjFNe1ZQQbJikzgtZ06qSUsajMG77LdeQ13EaxEm/13vtxeH+xtXv/V//JqmbuhGMMUTUtml6vhmuI8s2miJvaAE4d23jL97+tGrq73zjTV0hH396f7jZs23nZ+//orsxuLZ/7aMPPykgK8Lgm2++NZ3PBQef3/9C0swoSfx2WwIgXC873TYSIK/qPC8NVQmCACK53++naTqaXDq2vdnrt9rdIi8n0/H/B10mV+Xgc3S2AAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" } ], "source": [ "features = net.propagate_to(\"input_1\", array2) ## this should be identical to array2\n", "cx.array_to_image(features) " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice that it looks different from the original:" ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Why the difference? Remember that the image was preprocessed." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also look at the first Convolutional layer, `block1_conv1`:" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

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" ], "text/plain": [ "" ] }, "execution_count": 58, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.propagate_to_features(\"block1_conv1\", array2, scale=0.5, cols=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We don't know what each of the 64 features represents here because it was learned. You might be able to see some patterns though. " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can also look at the last Convolutional layer, `block5_pool`:" ] }, { "cell_type": "code", "execution_count": 61, "metadata": {}, "outputs": [ { "data": { "text/html": [ "

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" ], "text/plain": [ "" ] }, "execution_count": 61, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.propagate_to_features(\"block5_pool\", array2, scale=0.25, cols=10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Again, these 512 features were learned.\n", "\n", "Now, let's examine the output and the categories. We recall that the output of the network was:" ] }, { "cell_type": "code", "execution_count": 62, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('n09288635', 'geyser', 0.7626754641532898),\n", " ('n09246464', 'cliff', 0.08688867092132568),\n", " ('n09193705', 'alp', 0.03189372643828392),\n", " ('n09468604', 'valley', 0.027246791869401932),\n", " ('n03160309', 'dam', 0.01493859849870205)]" ] }, "execution_count": 62, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.postprocess(output)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see that the label \"geyser\" is category ID \"n09288635\". We can see all of the images in this set with the following:" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [], "source": [ "from IPython.display import IFrame\n", "\n", "def show_category(category):\n", " return IFrame(src=\"http://imagenet.stanford.edu/synset?wnid=%s\" % category, width=\"100%\", height=\"500px\")" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "show_category('n09288635')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's try another image, this time, a picture of a dog. First, I select one from the dog set:" ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using cached http://farm4.static.flickr.com/3657/3415738992_fecc303889.jpg as './dog.jpg'.\n" ] } ], "source": [ "cx.download(\"http://farm4.static.flickr.com/3657/3415738992_fecc303889.jpg\", filename=\"dog.jpg\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Open it up as an image in the proper size:" ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "image/png": 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09xL3gUG+DnD7xTI2VDSjPt/vEVCzPnfe3lr9DSOiRISMiOiMWckTqyH7YJZUxVCJlNHl7cUFiKx2hVaRASigEZmZxRSJ2WTDMpTcqlamqqjObe+BfnGud7Z3YSaCRCpgygQOzIfgoCxTqFJTR6lz0pyNCKyEwFTXMVQ+C4JCSNEcm7Bpp6gGnSmxllnUu0olpTamNrVN07S5a6k3iX6dXEqROAOAKqSu7aE+1UxEAARKSKCqfVgKDGbJrGEKjhA1iha9OSKiQUTssybIOUvqrqEE4yGDQm+IzGaAqGiARDnn/k6JMQbvjAtAJCJw5lJk4axioRSNIKJXRCsSiapDx8TOYU5kkJzD1hAE1l3jC885DmIKlHJSg+C4AEU1FIWUUTXnlFwO6kKKidg7KqIGEUVmAkMCEak7Ccqa2+ygBBVQRKRi4E1FKYOgz07xGosBlNTVljvNiUAde+JBFqKCW2k9qml/aWpQyewyMqacC2FkRSNGAtxmJITomIgKP6BcF4iFY+8ghFIQQU0zOSwieRLOyQmY8wiohoyQSQwoiZlXBipCyMGVNJSQXU5q5q2rFWrISKkEtP4w/Fu4z9WDADOkNkjsrEMPLrAfDklSrTVZQ+cNqaXUGmHUTIbEiKKGq1EsxJcGyVNMLooOBDwjNvE54HBlXpLOl5uz87qO5fls0zYy2tvxo4oDs5HrTXOL4KcImLvUGSQ1DFQ5CBQ8QI/+w5UDMDMFNQEhzKJxG5wxXTN12x8SueZFEcC++oH7QOJLhsmurvr+OjUAIGZFdOYAFTozRWRDREDMKRE6DmyobZcRwDnKqSt9mM2zd8XFbD6dTufL490dHY+m7IPkhBwQpAcE2jYCgCLN1uusokCjESZURM65A1B2iIgl8Dq2BDAEUZOqDADWtWvjMoRAqlkbxGHvdXoYCxFyjho7BENPqC2SA0GGPgh3ACqqzlAUxAQcmKqRIREa2NU6IaJDCiEMBmVOWFgKzjnnARl6kIXQ1HovAGRgaEAqYGZAaCA9G4FoAErI3hceyXMROXUZnUO1lqCCq9zo+kK/3qfrDVIVVenxy2zinGPvKBS+KCkUiUAYEwkqA1DuQAOrwzZ2iF2B4pJhwhhVTImrmMXMK+WYQrdJl6v1qoHlqk1Jk4ALngK7sqLgHKCqaootaFZtu67LlttuiVxwILIo6h2XzI6ZrY/KUcyo61oARGwZPQAYAjlENmC3vaaZNUtKqSiK/sPTFY4j2QxgG7EBpJSI0DmnX7kEiQjIo1mWaCYhFMzbi1jMimJoonWzNpICOeX66RfPy7I8fXE0HA5fHB8Vk93TixkAzJYnyGej0Wh/d88DKMIqtnkFq3p1uZlXkz2LOh6PwfP6/KQoqq5L3vN0unv88sixH4+namios1hTKHjeQmoDWGpPJzsT78rJdFe5sy1TaaY5d1Fjis3GTBLHEEZcltqBIvdkJzvqGcisopZ72sB6fG7L/wERoWkRwtRGBSKqFTYiFOfIkMDUcnaeKXYojhI5RsYyikP0IGqiwMmAEQBIvPcAOhruUO46iSF3LlmM2XNLYARGX7HIa6P8MgAFjCqiKeWNqhKqEfqisCxD2BWEdj5vFmuzkUgW6xJDE5NjZiZGUFsLNEMIXQvAWXWOQHWqIkjXuUVcz2e42GDTONA8muyPRoPRaFSWpePg0BRMGE0s5ZhEuiTZFHtciQwdhC8PEyIYEpGKGgACG2TRPvNgQ0dErNizqte/dR3NXP8XwPQrmMp1/ouILnCfMPVWqgqOg1qkntBEMEQGMgTn2WFYrRYvLo4A9PTsxeVsE4hnq7WIrWbnyFMQbVLc39+/mK3qur2zf7ism05zG222XMaYANfDaqCSJHcZTJSm0531ZrGuF0miD4EcOOBN08SUfU8DKpxt1ti0Tez2dneqCoVG3hVEjKQ5JgTNOXZd6uUx3kXNwOiZit4QTEB7nggZTfpjCWao2jPj/YVGgIEdOKWiNFUvgo7NxLEHTYhJpUP0SEVWr1xkUaNomNHA8EuDg22C6xDRiHNmYAesYIldfyq2mML1/X69a9tgA9Uki0iGDhBEEjOT8+K8L8pRNZoPR3mxSQZqxgiK0OuKNGOKgFBkJyqi1miWFElRl5tVRJfSYK1wuVzXbejZNwqOCqbCk/fgvEPJmjOCgiYzEYwIEVS8Kxy5Pg5lAgLUK6glJ3GezXodQ6tZERiIWdWRExN0AL3E5ArpBDOzbQCPiGhCDIQs24BMmF3O2XsWkd7RImKPBwEAoVOJppLNyAU1AKnPT14088vZ7OLx6VkbMcbMQ+dSqvPau6JpYjGkg4O9xWxelqX3Htl/fvS8KKpQDMoCdsa75PxqtXj3vQ8ePnx4MZ+Fsrh54/DXjz+bTAYEXFXDrm3Pu+58dnn78MC5qsvtZDLZrOrBaDrrVvUMPn70YVG2P/rdH43HuyklowgpdnUjIuzdYn45HO00ccOaghZlCFEiAIAyOWcmKQsqRmosBz/spWjeCM1QNW/FjYEK9qLJ2ZCwMDQUBesgWEodU6Ncumps7dx0xQmExkSQrAs6MFRGMuReR+YdRUXvC2eBWvGO2GXCAggR2QwZQa726PoqExHUqBZzztFay8iaiYiRw2gMLVTE9cHNzWbTnM0ESY0AnZggSc4GaAqCHtbrdTLL2W+6dtOlVYfg9jxh9oMwvlGMw3otPnA5qIpB5asylCWwc5kcs6qC4RBRAgzEOTRyjom945KICJ15jwDYi5sopyyUlQDQSKwDbcxKNVAVUCldqSr6lWCUNSkHMusxcCDX08aIcg2MExEAAmQkQmAzMQ3ksuWkSkjKgb2r6vWs2cznFy9n5y+fH89ahZi56brSh8ujmSurpk6TiR+MJmquqdP+3q2uq1NKk+mAqWg3LQhgKMUUVDebrvAlB79q1yXa+XyxmK+CL5G6y/ni1t6BA2zq5ekZBs+j4U6z6VSNvA6Hu6fLZ6eLS1qL1hdNQexLyFG72iCiQVuvPLG2dZIWyiqBOnDsUVXBSC0xMOVW0VJKRSHWpY79gFV6Yt+TZHMupNSxDyREilvZIZEqqUZy2dhDGFFiZidNSa4jHjCjMzIQ4NJEwYANADBlcM56UNE5zjmquRC2roQZtU/VLfdCll7TyIidEqvzqeNOCVkMUxIiQIAQymxaDKtQTVQuWQJAY4aOxMygF6IgdALWrNtMM6nTxjSHtgMqJI0cWjke3zBD04WBozIYoQusVAXnHCKSC2hGrnLOmYGI4FCNLPiBCrJDMjJ2TB4AABWAyISgX2sTMVVDjUrqJRRhIAJECIDe+y2KBCKSALb4FDvs+XEjR1/Rd5kZI5potuzJmE1VjXzKNajGbNQ9P/r8k6OnLzdJ2yyXc910KZSuqrwqCtLF2Rn7coDD0/OzOwf3psORYFMNfFlMzk5Ww/FoMBo1Tbu4fLm7u1uWYW9v5+Ti/Gw2b9qIFCTPV6tVVVVHx89CKC0qizTaEfBZUx/s697eLqCW5WT39j4BD6qdJ0++eOezk73p4tbNAx9CSS7nXK8u23qdYsvM3hUDIELX6LqAysyADDVldFklW2x1mbL5wjxqq0WvykVzqEqIvhiKZHAMW9xoiwSpklmBlsxUyzp3TSjGZqbAimYcmLlHDAFIUAEM2FSAkXoWFcy8C6bIzP1FZ30Ihw4Q+oCqB6pBVVVFkylkywAAmJkLxwRKnnRnd1BvhiZ7p2ebkguHXa+6Dp6IlAhztkW21UbmDW+E46YTo90bk8Ld2Nk73Nk/6HOVqBaKwhdDw+C9BzCHiICEAGikxsGHHiYkIgNiz4gGBj1fDwBmmiUjInOPGRFkVkgBMElUzarqHAHotcq4z9evcXoAAMm9yFOJEcREv8wf1YgAmc2kXxiHIJrR0PLmxYtHxy9PEmiyPF/XTc7Ou6qq1qsZoh8NJwokSow0meycXV4MJ6P9nWHbtrnpUPTl0fPg/O3Du7cGt2azWVEUIbgmdrhxAKSqy81SVefzedelFK0bdIGwrRsXytFwcn5+PpkORdJoOJ3NZnsHB6vVyswev7hoNzwIPBoOQzXYbOpm02aJOecebc45Q9cNh6HXBgEiGokIspkmTpExgYuWnDIjMiCSByAAIwDbqskIr0zzy7U1C2Bm/UlHb9BDmIbIjsYmESirRARvqCYi0DB6M+gJCURDMoItTYiIX2bw1NPaIFsxl6hZltS/fTIyZ6oKqoxYFqPJeLSZFVVYeYCAhM4CIRE4T6oqCKKU1DrVTsgIx6PD8c7tcufmaLxTDoYUYxlbS7mqBuSY2ffqp229BAKbAbvK+UCcVbY5CRgBKiIS8pUYFEU5iIGZNwTDxKzmVJQJc+oclz3UcsV29gK8fkHFjGGrjMArROlLa5atkFtFxBGllIixjVk1zS7Pl5cvzk+Olsu01nbdxSYKe9qs1k3TOFIkWq3ng/EodjnGvFzPfKj+q7/563v7e/v7+wcHhz/7xc8OD2++/vrrL4+e37n7imaZz+e7+3vVYJBSykkX7QoR67ruui74MsY0n8/ffP2N5WZZ1/VkuouIy+VyOh177wkhm1SDYnd3+vTFZnfknh2df/2eW3ap61KoBu182YNp1lNyLpuJSDIzFDNyRM4kiXTOAmAn0oEwZUb2CnaVKYIB9GZznbV8iXJsGVE0KzA4S8FMkK7lyUY9UI+oCmBGDCb+aoGzIVy7ZIZeykLXYOCWNtg+yQJRRMykx3F6WYJDD0DMjMFVlR8UtFtyW2dySsTsjFCd45SAAdSgSRYFNVpRDMrBQSjH1WhcVEVRDYCYm6LwnoNn9oSu50Scd0XPZIBaKIZG6MmLJpCMoCIZAAHMOd8jI4jkuOgwExCXPuZE6L0CWiJVsNy2c9HKe09YXPHXVwgMXKFIztMV32pMiLRdHnYMCAZIKWdmsKbeSKxn8+MPP/l4tlzNLpcpmiCp2nK+unFjP3YWrWGAye6gEzt6/PTO7XuXs0XTrg5vT7/z29+9uLhYZ3v5yaM33377/uHhL371d/v7N9rYtbG7MZ7Ozud7u7tPnz13rjg/f5lV7t6+s9msl8vNeDx+dnRE3l1cXD54+PD999//1re+dXE+m052V6vlZDJZLBa3Du9UoXj29PjTF+v9nWEI9cHIHDnRzKHIOQqSI/CeiaDtaujqXjTtnAMtXMAKsLO1Qc4iPreAKUI0ZEAHSMgFs+81N9eSgOtV7bW7fdBExuI9giPsBIlFwANLEFEGy6YgSqTiokgiTMasCoSBrCAGYlAgNXKg8BUOqdf3o1mkbFi7nusFYJc1S4bknBPLnmFnQrZfQtusCZiIRDhQ4dmARMUAUK1Tjp0pFKG4u3Pj7mTvxnB/rxoNy2qcDAaTSdNGEWFVtayaAWBb0bE9rywKvL3cyaskAO5LK/4tPKhXsW+fMJCznDMhNk3ryiKmBhHLosQrYM+uJBdb5OLflDDDtkjIxJR61TOZGSyX89V68cWz38wu5s+PZuaqplOC/PTzl4c39yGner2KOSnbcrk8Oj+7vGx39vaa2K3Wa7V4cnLS1XE4KFPdHkz321W9GGx+/Zt3/uK/9e9/8skng3KwcIssFkLhOWyamsgxkJnlnGOX3a6bTqdn5+fMXNd1b5E3b966uLi898rtxWJhiOtVszPdn44n89Stm+7T50fVw+mwKE1bFXCh8N6rKiIwYCfinOu6znsPKJ4LNPDgkjQEDjn51DooFEiQrGBTBDTADPZlOcP1/c7sr9kP55xlYceqaqDAiGgKCuQASK0jI0OEBOQQwANVYllVAdi5sN0aBESka0G5bZ2pmYH2GpnMvWYLzTlo2k4T0qAiTGZE6MaD8XLoYxISQAEwAoOcBdGRZhBLYgBAwfmyKsuyHJauCFU5IvJ9OgSEvJVYgCEomCMMSGIIhh6JPDOAMTIAGCCQgOTr89SHU2YGvc82AGBCBRArioxWRjYzy6ZOU0pEfMUiQYyJiIDY2IEAoJiyagYUZgYDQSiAtUevGovp4snzzz/64NO/feejpo1I3WQ4PD+b+cDjwXAVUzEIi7ZZLBbL1WbVxNFoMhhNVvMVCJShqAaT4/m8znL25GLC1c7e7oPXXj05O/2Hf/oXTz57/uD+vdl8+fTF8/v372vu0MPyZOnIE8lyue66fOvwxnK5HI1GOSszp5RT0xwe3p4vLpyjx188e2V/d7VcNs6dq379zVdfHB89fXn04lwrWPtw/srehAveLSequRwVkjIAWs51jKo5ZgqplLDsvSmYdHlO2KkNhBRxiMCQAbEkTsjDjGtFQPVCwGZK5F0BWLu+RoSM2GMgBHDmBb0TUSQCNRBCdFyKCIAaZ7IyQ1RVhl32AEC+KE2ZGQ0UQL8MzK6pP0KkNE4Z1TJRwUaatcFFt8pZ26b2nnerjQ8MQ75xcJCa56kTIE6gdQYBVYM2wyYyJCt8KAbTcjIo9ibldKccDJ2vuq5TAVHSLETEvgBRyjUyuT7FRkQ16cs7rwPHPkC8/krOufcHW21vXxdmZgjIjsAYxNicWcdbxdRXX63/P5iQ0RXUpwBgWTIIKADhqm6cL2JqK6bL2cnnj5/N10JUMkHXNS13O3u7Rek3y5pVzy8vxuPJYrk+PZ/df/iw65In3sT0ysMHjz76+P7+q25dP3959OqrD1+5ddvMBuUwr9YXp2e3bt0CgNVqtVhvvvP9H8yOzwZl5Qu3WTYucCiKlBI7l1JS1Tp2tyY3cs6Dsjo/PweU27dvxU4++fQREe3t7DpmR3h4eDhbrYHiFyfHk0HaqyjgKKtJSktNJBaoIiZJbUwdRKDB1iEyezMDVJMmQUIDDFnRefJgYuyVs7EhskoHZIKm4gnEIJiKQ0cI+brkDgS3zgUQaCu0vQoP+m8RFqDqUK6/1cP62826utvwinLdCvBUCQUKyZYdo4BCFs05WSKaqIKRMVFRFFVVaa5FxJRiVmAg3JIyDJhT9t5XVeWLyjnnXLhGW6/Ek+DQoUhHiopORIBN1a4lSFfpYf9cr58TUYyRiEIIqtqra5hZwYwLVCHN4JRT0hAs5Z6Fv66Q7GVEKSVWAKeIbKAEqtYrLQQNiSi2q7Pz559/+snxPL7z7tNnpy8mk4m0cXdvCpZms1UI1DUx51xW4TfvfNBFK4fTZ0+PdyfTThfj6eTTx1/cfHDvo0efA+FoOLlz9+Ev3n3nwb1XLjfPHuzvPXjwtZcnx48fn928c5cGo3/5l3/1xr0HOzs7F7NZVjg/PwcmJDo6OpKc2bmc84vjo9s3byHS2dnZcDg4OjpKKXXRLs7OysLfvnnrwd07ylhW1eMnTy9nC++6k5OLe4cH33w1HuztE2NVumzaNE1db2LqVDXnXBRFWZbehd4ychTvi647ps6DhQ7RkWHYERwwM7tSBFBUGNgVkB1SyD4kYocOBXttIhIjeg8E3JcZfgm5E/mtQgoVyRAU3RaU3aa/atex3LW9XiubnEsDp5UKMYrliNFzvdpgl9O6TZRtHDio+FAOh0NJ2jSNCoI68j5nlJS0y4Xzviir4WAwGpajCRdlEYYA0HVdF5uUOtWMFAjQNKOImTikvpRLEQTAX4eJfQx+ZaxqBn2+b1vZjjh3JboDRmZkNCGVBA7IyNiLKQEbEJCC9JVfRgi9rLmX6oIBEYlkJEOztllfXJ588eTzs9nq3Y+PHj853qTleDxsu9ps2DZN08bBcJfZx7brUhwMp6tm0cwWO9NxXyqdc6aifPLs6d1X7k+nEyZ6+sUX33zzrfFwlFMajIbvfvD+7/7e3//lcpmS7O3tZZViODi7uNjf37+YLeq6nk6nknPTNM57VV3NF4d370wnE1IZ0fDp06e3Dm+IdOtVQtFuU5+enJRV2Ds4mE6nNw9uvTw+SrkNiE2MfVzlfdF/2BijaM45i4j3vl9M8drnTGZGBhlU2tasQ8SMiTM6VnNkkpiIzJkkAlHwxIKoBizslFANAYjRAxCgcF+j4ZgIeid9haX0mJV9mbz+/5cvfbX+WMyEAQWkohC1I4KMUgTwrE3UlOtOioFxL7ggIu99velEclkOREn7MgREz4BlGUIoisJx6ImAa7eIiADUx6BmkHQDoE4kgYCZEWCG2JclXb1pBVRVMRC7UiVvMyqGnJP3HhGMPaMzSMQiwmK5MgeOkNkMiZyIIAoRqXW9Ro7AqRGiolnKKcU6SitN89kXn5xcrj94cr68bMqd2zv77c1qR5KOqvHz50e3Dneqihfz+ubNyY3bh4PB4NHnL6zYW8+PPJtjG1STL774YnLrIJTFzs50uVzeunnwJ7/3O7/5+NHk4GC2nsVYdCYff/HZaDSanZ3fvXXoD2+fXlzef/XBZ599vlqt9vf3vfe39g8Ws/njZ0/v3bv34N4rPa/9s1/+3f379w8PD733l+s5e09gRyenOsNW24cq3hevfuNrH7z3zhefnJy4YF3z/bfuI6IZmkFMWVPOOXddl3NW1aIomJmo9sRG6Jzb0NJx5RwZiWVVMGgvnDsJGJAcFgWCJ+8CT5KVYLXLzqAAYlMAdmRkltpQKvb1ZUPJxESm3jnqEVna9j3A65z1mtL86v1uZr0SHdEYNSMgApMKACOqySiQhjKPV6KgFFZNdJKRkwccVmVXp1CMcp6bJaC+MpyqKlhCNxpO93dGg6oMwXsWUTONqU2p6zkd5xxAFiEVAZO+TJFyTuwABZSMDAEYkM0QxRCpz5UA4Mujr4wgRCzoGRFQqS9iRUB1WRWNPTJz35TGDBkkAXiTpEhU9EEqAntnkA1d0kXbvDyZn83i+cnF0+ML0acnZ6eTyRgNtWtGo9HzZ6fBhdt37j0/ebzbLtpGnj2/fPu73w4PDusmzi4vPvj0U1e4nb39tokptoeHty/OT56h/dZbX2+61GKgmENR7ezs5C5W40kYD+dnZ9WoqDerp0+eH9y8cXT0YjAom7ZdN/Xe3p6ImGdSyTkWVdWs1oPR6OLy7PHnz+/cuXP64hNfDM8uZuNR9dnnj9/+1jebdfvga2989vho2ebLOSCyZABoMiggAIN120Ouql3XMTMzp6uGEQDKpKHwiCiqHlixU6XIETEFTEQByCVJDocgFReloppiyuazS+QioUt1h+g5JEpmlUoAEwJnwEZihMyMJEiE4HrtX59I9OW7VzUtvXyEzMwIzQC84zAwW0JGTmxgHsiF4AeSksckKcLM5x1Xq3nAAjEDehXXsz2lyIbjgMccho5LLobIzFyAYUp9ubUACpEjcoSYuhapAwCXcwYUwC0Y4nqZEqKigmh/2q5A422LJdyi8CQK0BfaEoB5QOj9pXNf6rpNEQHIg4CQGjjvgjdF77foRswS1+3y7OSL46c//ejJ7GSxWNtgdLBcz27dvnt5eTksyuFoslytbu3vA+gnn36wvzesN93J6ToUg/PT07ZbKcBoNP3zP/+Ld959f3a5LIqwabvm+Pjli+epqZPRerO5/cqDp0+feO9zTKJ6fn6+Xq9VVVTLYvBbv/Vbl4vLtm7M8GI+u3nnUFU36w0RFEXx7NmzajieLy8uH60e3Lv30cdHJ0dHQKPLs+Nh4eIdqbuzX/7ylw/vvvrd3/ntzuT485fPn30YY9w0m8mwBKQsMeZIvOUV27a9vpH6NCUUPoRgmmOMagKIkmNfileWpSM/tMp7JSqMxDoBW+fsmYIjXxibqKkWoTLD0gWHQQEQG0CuGTX1LtSBOSVPRH3LLc/cd2dRFERzRArbS9K2BqsA4FwwHdHwFU01h2y5Ueuca4dd7QvZNN3acLNeBLW6IYcZmAQJ2bkQSkfJEEsfhJH2q+l+OZoW5SiEEoH78mq12JNZ5KiqqizCgeu28947EXHeck7OBQJQVUdsIKjUx6DXtwB8CcUJEV3TJFdwMfZdVAD65j49QUeIRIRq2RCZ0Dm35U2Zc1Ji6GLdtMuTi7OPHz+fLVKtAF7E4vOjZ4NBtV63ucuL1B4c7GflJ0/OvSubAlabS3TFerNyDm/fvr2zf/Dy5fOf//Lv/uE//PMvnjw+Oz/abGoRmS8W40HVdt3J+UUndn5+NhqNptNpSmlQVXduHYrIzsH+6cmJY9yZjJt18/5HH47H467rjo+P93amO5Od999973d/9/d++Zt36y5r0tn55cOvHZ7NLpvluk6AFTx5/DIMfOEDkZF0X394b3ZyVgyL88v5dDxCZNV8XTjQQznXt6qZeRcAgGnbjkA0G2rbdmCWLBeuyCKFL4komw9I7DywqCWIUSEKXYnEVU0ToidVg2hIqpSZyTwRAznJicgbiiIKKxGCMpEQkQIxs/Solem1aYJBX2YIFMCPCRyqGBamDXNV4sBZNqrbxoA7FWnyJkA2JYZq5BGYjY1FidGkK8uBcwVR5XzV20xfg7XVrBH1sQigqSmRY/YOEVOKiBBjW5aOga4rbr8Sul7XTxH2/NtWxKjB9WWZhFsW+EuDvg5kicAUnXNohkbMHomJKBTUrFebzdlvPn33ow9ffPJy/fjJ5+crya0gyO7uzvnZIna280q1v7+7XK9Wzcx5Org1Gg8npxc1Eb/yyj3pNpt2073sUtTj06OPPnvkfPHNt7//l//Vj73H23fvPDs64qpKMZ6eHDvv3/vgg6OjowcPHhLgvdt3Ch8+/vjjb37zm6enZ4e3byzn6+9/57tPXzyP6/rerdur9aLZNPfv33/y5MmzZ8/2928cHT2fjqaLTXtxEn0RispyTCen6gZ1VbpHVFAdxzcO/viP//DHf5W+eH76W288IMcePSLG1ChQUVQppeFwmNM2Xgoh9EWFOUcDdRTabmUgWfI6deu6YaSSi67ryqJg5ypXhEHRY6hMQkYIPlsiMermwj5wAHKAxH6g6hywAhkwUlAg7woBFQ6GqMiGhOyAB0yF954ZnesVwNctYIBdaQ5zJnIVmDIomak0VJoT07Kd0DEOb+By3XSXbX0RZbVJ607jfghsaOxB8tCV4oCDKytXlOy9B6ScU88Yee89uyIUzjlEtb7VE7MDMGafc4uIOUfFbQOj6/TqKxVtfVkGGrJZ335LTDNyuU35DXT79es2Nb28EFTVRADR+ppjsxijak65Oz89e/5ytlyl5WK9mMvudIJjy1kXiwUxOI+xy+ft+c3DW8+fxW984+56Ua8WOYvtTJCoK0clhjA7n02ne3duv7JeLwFZJX377e/84pc/2dmd3nnl3tHJKWQZhNClfH4+/853vtOJ7o5H8+VqMh2vVqu2be/fv39+cXJwsPerX/9mMpk8+vCj733/+48+/6y8X07G47btRtUgpeZb3/72O7985/lp+8ZrN54/PSMcJoFOk1MIRJrWQhkwlhzffOPrR49+EUWHfUMAw+ALZcg5MisCUWDnHCL3NDIREYWc++ZeTCSICMimmlQgtUgGJs4XYJY2mZmdc8EXzMwuSs87CWTLKKoMbtsfyhMzAooxQQBwkCOCMVTWYywA5gozJgZkzUA9HI70pWNCIoHgCKGoTLJKVFX07AJazAG9L+qKBmql+BJ4QG6lbi6bkHQtOQZfMHlLiYqKuWIaMJV4ZVcAwMxOHIIWzjtiI0BExhFCgcd/83/MORtk1QgAzjkA512hasxeLPesJiIyErITJFUVSbhlmMAXxdZ+VU3RiA3AAfYtu1DYuMtZ02LR5XVZFmKhnIziBjs7Pzua/fXf/uWHn80+efS+atkAd106OVseHh44zVmxa+agflKh92FYOXLJJNRtXrV1WYzbxez3/t5vPz+bHdy8ta4bLoKIHB2dTMZ7l5eX5PjZkxc3D8vd3d3lck0q9SblzJNpeff+K/fv3nOMd24fEvP55WVZFq+/+jUB+uu/+qvBYJjFHj16VI2GMafpcDAajZCLDz9831BHw4PZxeVHH77wFW82EgqILTy8Pwy6uXfv9luvf3Nvb+fmzTvi4O9+9jev3ix/9IMHBe+bWVvPs+lVoQsRAQObIyRyznlDI4y522w2bWyjxCRx08WcNdWtZq2cK8rSO+ec8yE4Zu+R2QO6qihVlRiZMYRA6NkRY2LyJZUKAsZi6JwDV6QIRpzBAQVAZybAlTrP5YRcWZYT45IIDKJDJqKkAkaoCKg5ZyDKFtnUELNERsm5a+suxTamGjto6iW2kptVzlHbOuuG02UX6xw7P9ib7N3Fnf2wcxDKPSJKKXWx2WwWKbcmMB1N0AdAUc0A5F24rnEjANfHxbjtPgBmciXE2hayEV6fKCLwZrJtJAmgZmx9pwsFACHCvhRLJEnrncsSj559nJL4UL3y6jcGxbhZN5v52brjZrPyvvjs5bLtOKX06mv363q9abrROKS2KirPnJhpOByKpkQ2O17EKFLO3nzra8T+7v27akRt9+zZsxiz80XdbjpI50fnXYbzk7xanDnnYiM+qAIJWFEUddcWnp+/eHF4eIiIl5ezD9oOmN966xsvXx6fz88ELMb41ltv/fSnP3n48KFz8Prrbz578fT4+Pj0+Gx3t1rViR2YesdADLmj9WbhgLh0i7OT8vZ+ORqfzGbsSs8hxkguUM5GgojOBVX1xBmNmJ1zaGCqiKigisqeWjEi8kypcIqpU9GmsaLob19zzgwQhcip5C0CCF2lJaEPBQd0LhRKKNGAFYli7ggQibJEg860AHQAqjoCmxq2jChxw4UxMBRBeyE7kfQkI5hzpGgshIYGyFSSmWPnPDMHdoXwBnhkIXGhPu9YU1te51xB7IJmKAY42IFQac/ob03LiAKhARlyQdQn5VtJDZ785P/UE005J7UWAPquygDgiNmR2lWTCVEXir5fg4iQgZmY5us4tZc7GZBzLvf8rpqKRGuxq3PdtnH2+dPzjz//OEU4vL0/GAweP3/5H/+zHyeFbK5u8t27OxRyu8nIMK6q+WVTlK2HYlg4QDnYH1+c11E2oj7n/L1vvXE5O3ntza9tOndxuZhdLsY7u3/3s49GkwEFq5u4nksnMA4ckxABGNy7f7DZrES7Bw/v3L/3Soxxb7pzcX76u7/393cP9j947zdVUR4cHBwdnaScJ5PJ6cU5EXUptm27mC1v3bz9k5/+bVYcjXeXl7MXRytfgsaSoZtO+eE9vrP/GpfCRfjuG2+j88D04Xs//aMfvHFn70Y1HKilHJNBwm1nEvPEQqBmPSDXxRhjXNazLtVN7JBps25MIDiXupybLoRARKZKRIjmPYcQejDoKkggM+lbB42KsgolF2VwBaA657wf9t3BYtuZiGSTPpDzxH7Pl7vVYJyrKbiC2AceATEgMRJREFX0JqpgBkaGgKAqPTykIgKisdOoG7UsIpYTWs5dS6kzydolBmycsAtUjkIxIHJmlrpWNLax6Vt+hFACAKmYQ0Iuy4G7ZrR6p9kTnn17CcOtnvo6ULhGRrbmn/oGYypw3baP+oLt/hXADFRUIsR6Prt4cfL8xXmj5C6W63V8VhbFp88fL1dgDsphSXEd29qZm+yMVeXiZOW8spWT6dAjZOnm8yiWugYwaDGCUOCNg4PKTxarBQAMxqN6E28f3n784qiomICI0Sw3UZihp4mX8xUAjMaD1EUiGgwG73/04Xe+9bYvi1//+tcxxj/8/d//5JNHzrnUxfl8vq43L168+P73v//Be+8fHBy8ePlsf//G0cnpB+8/dQTVsNrUjVk7LqDrpCymZ7PTajo+mEyfnby4e+vWwe5hFnz64vz+zdvOc+oSEQH4L1WIoIhwzeT05YY5x6RCjlNKTGRqJFaQ42BI5L2nvt2VZhFZr9dFUV13OmAKasmMzVLfxjugqSTnGEBNHfu+DwqbgUjM1ncQAmcXSJYcOSrJkBQValMm9gqsJkpE5g0UEAwyopmErZgaDYAVkZQKG2VNzKpkaCskBu/ZSEMkNXEJKPhQOhcQPACoA1D0piLXysy+4QpJr5OHqzZAiMhcIhqiERIygvNAjjRtKQfpT89VySURKoNYhLwFUZlzzttCFgPVjKJ9D9a0ma/r1XJxcXR69uT5SUrJlcPFWfNytm49mEC9rBlpYwDzerXIy3W8dQMZiti1w3Ly6cenN2+XojQajrp2vZjH12/voZeyHB6dLpLJ3mTn+OTi5OS03rTDQbXa5I0kZkoKiJxBNkkPCNmhCS0W9eHtg8ViUVXVZDKZr1c/+clPvve973nvHz9+/I1vvPXJJ49OzbqcpuPJ/R/cffTJR//eP/qz49NTBF+Wg7atnfnjs3VdNw6xcBgc+UL+9ldzH6hpLjI+/u037/3BD9s7Dx/c//pbP/3VL7777d8qAZ0L7AFUrgg5QRMkyCKEpjmDSkwbRgWV1EZgAtHC+5zBOQqOGalvjtn7iG3/JhEzzTmbIUAG0K7riCBll5I4pOGgJHREHHwXQiUiCrnNK1UVMVMCcJw66QRFLDeuGoIbmA0QWdGBC0yFKAAz5SCMyuiQ+r6/RqZgzMDkqedujc00JwYYeAXVaIZokc2GW1dvwILqVCEgG5TODzXLlibABKklUCVgEXelJKCrQQXinLtGi0SVrtJwsOtaViAiQMyEIHr1Neitc9tFm1CuGpsrmEjaNHXdweWi3rR49Hw13gkvnhzFQF0CQwcoN6dhIckLOs5370wKJrXO+Srn/Mor+9navRujTz88PrwzKgbFN994M8ZuOJmsu8vgitzFo2fPB6NJCP7xs1k2rwaW1SMJiBEAcJfqTJAb2L/hN5tNSqmu6/v37w+Hw8VisVqt9vb2qqrquq5p6uOLs+l0allOj45fuXe3aZqzk9Nvf/vb77//4a2be6vLx+NJgWvu2g6QIHsa5KgyNB92aLVJv/ro2Zv3q/qN1e3Dvb9Td345H1blqCwATXMPJxMAaZa+qFdkmzwhmsq2BgYNtrk9IvfdgMy899dZQY+KqFhZlr32SjIYGBiKmXSWnQqIa5nZHIpDahVRtYG66RoClEyAyBQh+5gj08qZKWQuzdSIPLkS1RjRA2LOyJ0agZEKgPNmQQ3JgYkj6lsQEQOrZVA2ElZUANOsSh7BDDtRZgfg0QlkVAcIzGaeQ0/6A4KpOBBDM7XtBIJeeaSqhETotsUqoAYm1mf9qIgGBFuOYQuXOnZsABjhSk0CAEQoRkbmC5/rbmDy2bOjJy+ev/f0xcsX7fOXL7pMi+Pjcm/SXW4cQiY1sdN5mgxpZ2+M2C0ulw/u7TWJJwV3bc6QJHbHL9q7d6eb2Hz9wWGJ+uTZ83Kyk0TbZn6wvx8K2h0w4UBjl1WevoQNYTb1AJjRsymyExhOy7puzs4uBoPBjRv777777ve+972qqmaz2WQyWSza58+fv/nmm2+++eajzz57+uT5cDw6Oj5abzYHBwddvfztt9/85DNm5vffe9bAZjiY1O1yWGm9Bl+GpXI735Dn4e7wL3/+6Ic/+mFT51fv3/rFx5/vDYf+kAt05BgNGCAjKvbbIQhAzP3iZlEzQ9GyGPUDJND3G0TXYqPrDENVndOUUlmWIoIl9mIUM1OAet2ww6Zpgx8URdGaESqgdd2m67q++AyR1dAxOkdDGVoc+K7wYYC+KMLYFRNAkjAyREHnoDBCIDZkyBmw81SQuAyZWM0sozMUJXQFgBmhU0UFb1aa5mxaegQwRMoJHJORmSVHgIhZPVkTIyBiTqlXtznty1wRiRyaktvSG31YQ9wXxYCZoTEamGTo1TG9d7QrPZ6q975v/KUq5FzOWUQlN7PFyenp8ZPTi4tZvZyvBoOBps4Snl8sWRxAX1JHWfXG3n7TNSppd89bxsm0XJwtYxNvH+62KI6GzNS27e17d5vNphwO6roGoNFwOJ/PHzx4UA79v/rLd3kcVps4HvrNJjkEh0CECJxy8t7VbQOq49Gobdqua27dunFxcVHX9Z07d5xzq9WyqqqUEjN771er1Y2vPVitKhHNOd+7d2+9Xnvihw8ffvrRk+Go3GzSznQIFsH8P/kP//Gsrj5896fvffB+mTarRHW7uXvrtfnl+fOjZyfnq50b+0ocHOeYMgD2cwUk92KeXn5JfcGYOlcwIhY+bPXzhEyhx7TV5Bqo7u+9fgeuvYxdPYhcf+/lrIjROYesCAhAXerjTwWQKNk7F4QNIZglayuIwcq2q8vccREgR/SBMahl9k7JO/aKYkCCYuoSmGJCREkOPDE6QAYQQI+oZAmYyJEHktyZAQIzXzdI82oKoGgGRsysue9obkjmRBsAUiFml0kdFuQYJW+1rqbbYk4gJLEejY+wXSlVRgIAx4WRIXlkZwDIHhGJESCi65599smjl8dH55vUudFo9NmzM0Rk9qMCj8+61DcVzfLaK3cWlyfZrChpWefgm5HsD8J6f7pbBrqYRSAdjStWLsit1WUonA9VWXzxxRdfe/jqh++/P57u3r49bcUzNJdnGwRQ50yNAFLOA+96WksMV6vNeBJOTs6bpnvzzTe/853vzGazv/qrv/oHf/j7z58/n06nInJjf//Vr91v22Y6na7Xm8Fg+Jd/+ePXX3/9u995++nTp68+vP3sxSVTRO6atb39Ow9enM7/vb/44X/4F7/3j/97/6PlmiaB/upf/+2f/9EIRZeL5uVsfWvRVQM/Kq0sAhqLJTV0zonJNWTtXTUaYs6xbz5V+IqImNE51zfJF5Gcc1+9KVetr7bQ3tYjbqu9AcCMmdl7JvTEaIrZ8jZAAO4p15xzjHm9rp1zw0pWy/l4OqQ5h7KoXBhsLkIIzo8xBOKAUCCR96WGAXBADMCVGLILYIREzgeLQMCsFL0ZJiJy5DIoAIEJQkAkRDNot81BVckoqyCxx5DF+sJr1ayIzkAlK8J2Whc5RmBkRFGR6JxTFSJPBGDa5+k5d72qs6dqAQzRmakiMbCZASoZKCKqns8vF6v12WKTWumSPX1+frlMN24U88XmxiQIMYCoSCAQ7WKUajyIsd7ZG80X62koRtUwpk2jkDOMpj7FfOtg/8WLl7N1B84NBoNPHn16987tzz/91LtCGhSMAhhjpLLwTUw5RyDvSRFSymXpO0kAqGoiOt2ZHhzsdV1X1/WTJ092dnacc3fv3jWz+Xw+Ho9Xq9Xu7u5sNuslsLu7u2+88cYHH3xQluXNm4cvXh6XXjed3bg1wDx49vSz0+Pjn/7qXz0Y+sdtSkkdV4+ffHpj77Cu62y6XG3YFZFpUJZmZhnQ6KqlUA8VMaIQsaMetmfnHAB4H/o8QbVvjIMiSa/M+prT74HDvk/qNVBAyN4HMDRQ51yWbcobQkgx9q+gBv18tTZGJuvaDKDAXiVplgFCyCsXA/igvgUAkwDSgB8aF64fa5ETYSDkpmuQvScP4CwZOTCFztSY0YC9IzPbku995xg0TGRqSAZo2tdAI7FHViPEz3/8HxMFQu9ccMWQ0YhAkUSSpeicAzDiIICMfRyfsy5Veg7DMzs0QwhC0Pexu8qugA26+dGHH/z0X7/38W/ee3J2ufjkWRrtFXdv3vn4ky+Mih998+Y//+lLNFCQ/f2hpA1Hqlu9ue9N871X9tv5YjwqJ9UwadeJLc7mw8nO61+/W3fw7rvv3751a9PUuwc7qvDyyUsDujEdL6D69SdnYNEDCWhmMHCFZUA3xczFoGmaVm2nCl0XpzvFYGSvv/46M//Jn/zJ2dnZ7Ozk1q1b8/n8jTfeQMSU0unp6XK53Gw2Xdf98Ic/7C0AES/Ol48+/OTnv/plNR7Vm8vXHt7b3f/mp4/focujeyP9z973AOmNO+6/82d/eGN//+mLk8rHW7v7r7/xcDFf3T08uLE3zDmCpJyjQDaAnDMCpJz7fLSvzkFE5xxT4V2Zcm2Qui5Jti5urlnlbTLgXB96bm+2Ky0wAHjPfb+nEMoYtx2rtyUWhilHkdRlWTe1mTkkBimKAkSZOVQl+1AGXxEpWk+DF94jh0E1AXTIhS8cYEAuiJxHl10lUDKFxNFhCRwQjcihYkeI5Mh5BULeKuNEBLNS3/0dopkZSN9SQPsc3UwADEANkhEqUl8O198+eJW7o1i/GpDFrjrxOXDOFewdMzMgmDPrO4qCk9TZ5vlycT6v101+fpImQ6yIco5M8LXbk89PzkZegAwA1psWtdy0NB5R2+ThaLSZt3t7e8OqqOs6Z7m8nFeV29mtVK1r2ps3bgPh3s7+7OJkdra8c/8BYZ7cHP76sxcOkjlUskxACCTSN9yJCG1TT6e8PwmdZDNY1JmwREQyml9cPn78+XQ6VdWzs7Pd3d2qqr72ta+Fsrh7927btm+//fbl5eXFxcWmXjlX/M7f+/5wupPNpcyrtU5LWL78zfr50U2vB3cKxATez5b56MXxvXv3JDeC5EPZdtmVg6OzZZuTifajeDyFHrwDRMdYFkUfAZuZd0URKuccoDgXmCpmJoZ+elhvhT1cj+AI2bF3zhVF0cuT++eIjGghlGZSFL4IpXMu9KgVYwjB+6JwfhTKgQsOCdHnDEklqbRtm7o2JVnnru1yG2PMeVnXXYxNu8jdPHVnXXMm7Ry6hWzmsV1pt0JZW96EJCBrkka0i7E2TdlqlS53NUpMXUTDvlCPAQ3JQE3AIBGgc0SAhMFBFvAeANG+JO8JEdH10Q0i9vYraIZAgJZ7MZb5QALmEBUBDCJisJwE1Q0KTE+e/Pyd3/zqb379aVR4/mR+Y3/guVDi06PTG7vjnQk9fdzGK5AqtoIso2FPcGmKkSifnq7v3b0pIilmRhiOh3cOb4DZoy++ONi9Gari6eMnB7duPHoxa7Ps3bz5kw9OfaYM+MbdB6uzeRtnF2JEHHNOBkV2d+4PZxcLIhy6YhZbAZlftvP5fDzaPb24vH3n/un5ce66f+cf/IMXL14eHh5eXFy8+cbX3/n1B9PpDhG13fqN139rOBz0cM8f/4MfrZr1hx89MocfvPfs937v/uGeu1va/CiBFT966zXCzd+8+35R6g/+3u9++snHwHQ5X7/yyiuXF/PVpjvYHUqMoF4hM28bfwM46ocJOQshEJZgVJRb7ygivafcelZHTA7QVIy8A/B9J2W46jC/daX9iBFD7eFDNGaWjFXle1faW3MfufYvnlKKcQsGEGmMOedIBD57kbooqi5tNgmcYXCemYUWHj2jC47IBXYFFQVC4XisvlRAJG9u6Jkc5OwwiXkkAZcNAKklIwMTBTK2Us2TY/OZwBHav1EeBV/R16mhIfXWCgAqAGqqakjkHBGpZQS9Zuc9FQqOnYGujOLjJ5/8zbsfn1/OY7LJTjWdFk2zBslMgKCeidkn6f8uAQApmahnHAwGlq0oCud4va6R6fDwcFSNdnZ2z8/PLy/marxq12fnF4g4u1xanVzlb+/eO7nsDJQr/g/+u//4f/lP/+kNtbBVuGIBwE5PTxfeByTzpR+PK4uQs5Zleffe7efPn5+dnUnK9+/f/9U7v0SEe/fu3rt3bz5bvvXWW2+99dbl5eXJ8fzk5Hi5Op+MbgwH41cePvijP/4DYqyXsrM/2Jm8eXjw6o39qhwpQv5v/8WfrVfL4SCsVqsyVF2X6qZRgc1mMxqNYiQRZ0QIzgxBEY2YPCqZYj/1QQWcc3SV7V7lPXa9YtcP50LvLxEZgcC+lEoi4nULbETqpZ5m5pxDoN7jbpV7zCEE51xVVcPhsKqG3hf9BJy2bVUhpVS3TdO1ddt0KXZt7LpYt+2mabqua7tN7FZNu07tKqVluznPzSx289xeUFpBXkleQrciaSxH09SBJk0MxppdUoqCoqBIGh0Dk2EmzIhPf/y/Blc4Ds55LoJzJfSDF/vZDn3fym2HOsjSppSQ9Gr4DDou0PdEBYHU2VWUm2Z+9s57//r//i9+NltHEfv009N7t/fEMhflalW3dTMYjnfG5Ycfv/hiRV2KRA4hj50DhcEgjwbDonQl6IP7d+4c3nj+4vFiMR8OJs6FJjYgcL6JQtpuknZtTlhUxTfuv/bPf/ruTcPXv/Xa3Te+fXGyXEp98bd/G1mfKkwMbh/sjHd1udH1sgHDmHPbwXjAg2E13SXn3I0b+wRw9/BwPB3t7e2MhtXJyckP//4frFf1t7719s9/9tPL2eyV+3cH1bQsw87ODlK5aTdVVZyfnP8n/+l/Mntx/Nobu7enu3dH/F/8l4/+7D/6H/zqZ7+ittuvqiZvvve973/x+aMQwmQ42N/bmUx357Ozw5vj8SQ4Ve1Upc05p3RdTId9zgqgfWkyM6eUclbRJsbYdd1VSWMPlbrrhElVzaTv4LD1jhSQVLJesfa9jfZZV8arfk8pb3OmPv4zs5xzSqk3g5xENGqKiOh9QQTeF0ao0E8sRiTzQMhU+MDcBxje+8IFdlyiEYXA4HEwViy9r9BKIBYzIWDLBqTOgfOERTQmIrSswIRcMHlyztiZsQqAOUZH286meE2+i4EBGRAYoRGhIw7G28OHyEo7nONmffTL3/z1b947rhMS8PHpxXhn4F3pfZE6Wa/qum2YoEuiqDHFHlAgAh845uw9h4JFuxjbP//zP7+4OPuzP/vTouTZbDYYlCJyPrucjIfz+aLr0mC0I+SpKD569BQIhmgh6MF+tWou9w6qkvXVQIyws7fXqc0Xy4vT9WotzrkYwTmngOv1ejrdvXXrliNKXXd0fJxzfP+d37x88mJcDtbzi0GBR0cvd3d3v//974vI7cO7b7z5W4PRUFHLMrx49uTWzd0nTz8tQnV52R6fXX5yvPmP/mf/8w9+9X5um9u3bkVNh3fu9BhQzB0h5i4DQF3HxaJJnQertnAmWT9JRyTZ1QgoETHb+s4eRboipa9mLgL3Y8R6L4jbststfX3tYrewqMEVgHq9rbyFwBH56uGc659cV6SYmfOMyL6syJcCGEXb1MbY5tjl2KWUYpIu5raJmy42XZdj7Lqu65pms9nUi65ZpHYhspL1TDaXsbkUXWhemK7R2qySQFVBkkBqMbeYW0gCoq4oh4hMzMro2DEVZj1AZrQdBLalOpHRXdV89mJk9oUpI5ohmRKTfvT+//df/+2j95++fHJ8NiJ/sZgX5WA6nTI6TLhcL6bT6fOzJoSy3A38fAI4B0NEKwDrphuUMJr40g+PTpb/6Pe/d3B777e++dY//8//+aZZ7+/fnF/OEuTdvRvHF6fDyWhzlh59fjka+AevvfaXT37xLYVXbo2qsPl//l/+z1l8Ge/9vVfgxSW7Tl9cbg73B3v7d1I6X69i2wmXIG1I0oyLcLB7sKlng/Fod3dnZzK9ODnaHVeLi7Mc26Zrx+MRkt25c+etN16N9cXs/IuPP/zF3YevDapxzGl3d/fo6Oh/97/5Z598+MHPf/K3l+cnuzcP/vrv/l/L1bpif3h7L+0MCjdIqNLVr7/+W7Pz1Wyxmu5NN3W92swE09cO75hZlEYTg0Z0DIhErGo9i62amYucFUk0ZXZsV8Pgvuo1+ycxtr3tqgKSERFhTz6b94zIzrm+A2E/VOjajhGRjXt49atydURs27ZXWYQQJCuRFkVhZppiAhURZ5i7nDT1fT2obQrPrffBeedcCF5My1BgbMkxADryxIUvC2Ym9EwF48h5B+iNGJBKKhTEiBl5K/swYgK+gtOgh3/hK3XGWzNFAKae7eiHrhIDkSNAdqD54tEXn3/05Pn5y7lG6lprOiuHIwEEwuV67ZxbbtaD0QgR2RfrtjUAQjCDoigAcDj0pv7oxdGdm6Pz89MPP/7ov/5Xf73arKY747IsclZPrJq8qy6P103KnmFV2y/fex+c3Z76m7e6m0PYdZgaWq4e705hien2dCIAf/X/+F+VlV+vogtu3SYDFqiTWJfyer22nEH09PT45MXz/emEiC5Xi6qqRmV1eXHx9VdfPzs5/T/8p//ss08ePf3ic0a4OD3q4noyGlRVNd3dReQ/+KM//G/8/g/3Du9cLk7XdfHGa689eOX+86dPB9UIGUKxMxpPC1eJiCHUdT0aTZomzi5X89UqAzJ7VRWwvrdFzplI+xk6V2pbM7PeAq7FdV9NGK4TI9tWiW3JJNiOSoMrXyg9kt+PC74aqXMtmIRrZ+y9v24kc22vPV+1TabZETrvCvKBvCuKIm+nccUmdimltkttl9rYaZYYY47RRE005dy2bdM0bdvG2GZpc150zXmOF7m7TGkZ80olamw0Ntu+5QDkgIgIAfvZRXjVmw8AvPeSza7Aedj2wyGHhn3XBbKuPn304d+88+GzJy/PoZXlfKHENw5vjUcT59xsNgPnyGi+2Nw8vDFfrwY7o9miBQADBYK6bvui7W5ZH+wVhzd2njx9/sOUJ7vjonBdbC7mMxN3cXFRDUbO+cnUHx2n3Z3BvImzOgHQzbdgfze9djhfvm7flHiTQ5n5nUWCqiuo+9//s//tR++cGNO6zkURMiY13pmUi/kmWx4X3KxXl7OLwZ1wfnlZePreb383qz59+vS33/72/+e/+JejwWBvd+eLzz+/e/cumLWX55v15e5kn4vBjcPbwZcXs7ME8b/5H/zF5fHZu+/9ckQVMpbTYr1eDyZ7Kce6cyDNcDhsUlxvmtu3Xjk/P18sm5enixs394Zu7EKdYieiqtuJ8873k0V7cV0HqCltHeQ1Pt8/uR5YSOT6Do9qIiLBF84FMgAmADXUfrqTmSFSFt1OxANE3PZN6A1dsir1Eky7nlupqgYZwDnnEdmxB7SccxHKNjdIxt4lybFNKli3mZwECNE4EFJKaFDlbEgZ2BBC2pZAMbP3hZn1f6Ug50MBVIEL20Fr2M8z0XwV4jDR9tT+G1cA+T4uYfZ97GJmVyCj5LiZzeeff3E8LceXm00XydSNwsSTZ2BJyTNH0RCCCTCjRwJE7zz0al2C4Klp0njsAzsA5ZLXy9VmuVqv1wh+Mt4/m10OBjvG3lgXK0Sl+SqaKDhmpN98nIowzNb9wbeL375djPb03cdWFKluumkJ/9n/7e+SJlUdjkPMsW2tLJW4+dY3Xm2azXw+X67mBoBMwmxGH7//4WpTT2/c/PGPf/zKK/fG08nF+RyQmfzR8alzLm46j0Qq52dH89mpaXbOPf3i88NbO3/yR//o7PxkNBoZwmA0HE8GjOnnv/iZxJaZ27aNkrvUTadTybZuuyyEEEyBDPpQ0LvCudK0h34SwHZ45DXGfv3criRjX/1K/08mB1c1xF/WN1+l/z1mQ1ezYvt9V7HtDxOYgoqBoWQ1S6pRNfbZQp82+eACu22oSgZEmcC7oqqqshxU5QjUuqaNbbdpuqZLMScxiznFnHLOsUsp5pxVRNqmk6yxS03drmO7ajfLOK/ry7aeOTPTru1RIs0ZAYmV0BlI/7evWjo5M4N+ANcVfNETv0QgefPy2WdfPHtZa/nFp09Wbb45LdhjqLhNsV6tuzZNJ5OT82NwfrFaVgNu61rBNAsioEHBpG3euTsiUjDJHb721jekjc6FnJu2ac4u68F4hApIdPRyfjq3G/tFIN+07bjuUjl8r8nPfrz5n357MqpoFVfL1v/Vsp3y5OBAl3VLRg8ejD57fAnROoGdvf368kLaIq6fv/ZgtMmr737/d372i1/evX3n4uxs79at2WLx5ptvPn/67MHDV2ezeRJZLpY/+J3vPnv2rCgKiWln/+DXv/71vVcejHanL1488264WCzqdfv0889ef/WVf/cf/cP3PvxcPY/H49PjZ/UmnS66l+fHo9FNJhCRxWJx//7DR4/SbF6XxUqm1bjwbCUjMnMIZQglEcSYvfc5Z9Ve7tmzKpqSXPV6gCuIcGu4/T8db1vLqiox9QJnNfHeKyRCEOmne2aEa6UwIzKA5NzTOaaWkFStDzm2P5ZzDoGcI6CUHbD3quarctNuQsGg4LNLSQBgOBz2vKuIdF0X+/G4Cty3TQhDSCbKkj1SjIlEJMbWtX1zSQTXt3LucQdU0SyaAdRM1PJ19nedCfa9FOkrbT77Nw2odbNcrZanJ4vz2XKDwsw74xtFMSRf+SK0KQLAar0ej8erzToMqlVTG/btI1VNnXM5KxhcztaVH2+a9uL0fFAM6rpWhOBLEWEmBCrLMBwUq7kFFxYr7eo6Zrt9s3rr4eT2dNiC+79+sv6bJ5snDX1at0FgQcsEkXhYb+JmKQAQu4yAl5eXh7d3prspaiSD6XQaY7x7585qdnn2/Ojp8+ePnj0lIhYrimKz7sjoG9988/T09OTk5PDwsK2b4+PjW4d33v7OdyWjGZ6fX8SYwMHRycsnj558+P6nf/qn/87x6cmqXn3t4RtR4svj1XJzeV2/2dQtAo2GYwCMOdcxxaxuW3TbX9+9UVqvHL1ac71e+etcvt8RMzNQJADcDnxn5m2fVYBeYqKqOUfRmLTLOZmpWFYTtaQmIukKpTLV3J+E3h76uLNHSXuaCgDEJINmFCUUEKJ+qIuxg7IMPrhreUDh+oDW56RZRaRvThF76lz7SYu5j61d1DapdDmllLqudUlW13E000Rp7Z0zToi8HR+/vSNERdih9gOSQFPKPefWdqkk9+Lo5YefrRCCJBgXrsM4GQ26uEGmEnnNcrm8HIwmzQr4hhZhCDntD/B4acBobQwDX6Ddvj8qCnz7ldcfffbpfD4Pk3h5sVpcbu7cnWYL5xdnN15787PPnwJi4ZKaVYMqRKs7k4uLg73BzkjWdfd+RjfHxRymO2Wbm9deu3txvmjq0cXlYrrDyG5+oT/47u3FYuEoDCpMub51+41333/vtddeG452Bjv1zu6Nnb3dn/z0pyNf7IwnRFDX9ZMXL+er+a39g0ePPn3l4T3LEAr369/8ogj++z/44Xy2/OzTT2LsRuMbg4Mbda5//C//xZ/+/p/8+Mf/8uzk5N7hrb0bo0dfPLt/75vQ68YZn718fnh4u4kdI56fzcubw7EDNaiqwhdVP8qPKOfcWwyYCWI/QRQQ4dpf9nhUlgQAOQm7bd2wqvYp0JVXVXYgEHPuYawadDvGmHjgt9Ooe9PcZvA9FHqF9mOPQJVlSURiWYFAU9ZM3olEDpQlEaCAgSkyIZJnL2LGRibOEQb0PQSBJhkVBSBfwULGzESaW2XO18os0iySsomCSk6t5Ki6dctX90JWzSBqkK7ONKhFdkamlhMHPnn52RcvL1ZN2qzWB7du5tQpUlGVhracz4W0zSmqtbEjIiTHRCE4QEMAE/MOuy45j8cv55ra+XxZr/hHP/rRz/728bDy43G1Wbezi8sbBzefv3y8WDW3bk3feO3edFA1m5awM+n29/c3m1VWvXHjwHtXDUe3DvdWdTMej5o27u1PmIvbtw9zFhA3GOjDe7fn54vL8+buvYO9/Z3PP39cFFXXdZ999tnx8XHbds45BdvZ2WPyX3z2uK7r5XrNLpyeX2SFd9/7YL5cvvvubwZVGWNMKb715ps3bty6devWjZt3vvOD33v1jbcfvzx98OCBQwJz4+lkf1A8P9r0mDEA9Xrhtm2qquo7Xs1Wa/IFcUB2KXX9+PAvbzDbpi/Xcaduhy9SHxFe+9TrP3EtHMk5i2Y1SZJTzpJNxFLqFHpBqClIkqgac445R5HUn6I+K3cu9K/fg6N99saOzBSYFCVDjeQBmYiyxR7Qdb4fckCI2yY4W2Ersw9b4BYRY4zXrftFUs8s9HQrkVNVkgw5Wc4SY1ZtVGLOGU3RBFVAFE1Vs4CZYd+/pU/9VEEAgUljevz80YvTLoI2XVv4MKgGi/mK2ffUaJOiGQ6qETCZWVIhdD1dd1VbAmaQJFe+ODy8OZtdfPd7r/3mnV/89g++9fjpfLWOUXQ0Gg3K0eUs3757czDkRx8/i6nJ2ZgqRDt+cXRjf3rrxv5kVI6HlWZZLhfj6cB7/+GHL37zzmPnVSR/8xvfajbt61/f+69//HPv+Wtv3MnS7O3t1XX9+uuvHRzsnZ1d7O4ftG27Wq3quv75L3/x8vT0xq3Dlyen8/ny88dfzFbr8/ni1u17k9Ho9ddeXy3Xh7fv3NnfffHs5bfe/u3bd7727e+8zUX5oz/8d7/zvd999Ojj/+H/+H9ytlxGlf3x8PikTqnbbDZmuLOz0xNCw+Fws9kURRGTXqzqUBa9xP1qWfAqmwnXQM910PWlm7mqZbiOyvpUyRS3BiqSc+47yKXc5RxVQcRSNsnU3+PEW5ipr0Jpu7qfVtp7paturx6RtzDOtuWjKaRoOaWUcwQ2QzTcDsPtf7F/IDKgGgiTR2S9GpPVq8OuIAhD5BizbbvGgstpoQoAaqAm3rwpGJg59siiqpAAHCVRVEcMIh0RSTTHAVBTyj//yX/+//7rx6eLNqXutTffyBupdm9oFmfsXThpTluBgsr1ehW9JIOL2fzB4d113fmiUOsEIBkwYZfx6/cGH3/+vGv544+frFbtjbsD5WLdWqigTk0V10z+2dPT8aicTJm48Dug1g5t4CxVjlPbusGgKsKqvtjf31+v14vV4uHrNyaD4uxopZDOL58/fG1vPDzYudl4Bzd2R++884nP+Oqrr15eXq4Wy+FkPBgNVOXi7LKN3f0Hr/3q4w+HZXnn/sMP333va19/9eT09Pbh3V+98+u7Ozdv37493Bs/fPW1T1++mM0uBtP9clj+3jf+eLlcfP7FJ6++8Y1hUW5EvvXW2w9ffXO4M3l8aU9fHlXVWKM10IzH47Zt+9lUi8WyKP06Ut1GR+C9F8kqslX79AYHnlAMt9vZy/5794kICOSYe7PcNlk2E00iyUBjrD1xnRqQBADEAGiq2msvRYCIRNVzAICiqNq2JUJVcZ5SlMFgQETeF33LMedYU3aOOk1ElHOOtkID6RpD8t6DIprkmIP3RORcP2G711xjzr2abnvM6rqtqqonwspiGGMsArZtKxoBlBC9CqWIOaECETqiviQJtmVyBKCKkkw6kGySLAtIltSYdATpxfHlbAOgNh3vFMhZkkkmVsdY1/VmtY4aV826TbGqhn1xKGgufQDR0OOqaoXzqdOzy/Xlot201mR38+7g8qw27RDUFBG5bmJsW09VjC2Tj11d+DCq9obDQVlV6yYtc/rsyYu6bnfGExHZ29uZTCam9MVnxwcHN7O6O7fuN3X7xdMnXdxMR9OPfv3ZnZuT2XKRc9ys6uWiuXP77sHBQZbWQMbj8cnR8e1bh+PJZF1vdvb2Hn/2ORP97Gc/Y+aHb3z9w88/HgwGH737/nRycO/ON7r64u7tG8vZ/PLycjQaFT6QK3Z2D771vR+Ug91//5/8E8nW1MLOGWjfpVpENptNCAER1bBuk4Ejwhg7U1XNKXUpdTlHtRZxOx6y39frDCmEsM0WgAi/2t5163dS6vrZk56JMaA5UyYsmIvgB74fb47I7Hta1QyZfQhF3zbM+6L/fq9cuUr5URV6pVGPpcYYVYGIELj32Yg9J95Hz8jsAUj1S8y/67oY41d9vKoSow+uKENVDUMonXME5Lx5VHRFYNcjW2yihgYEOWUFURECBgmGKpCAyCXUcfjis7/7yS8vXh4/P5jcHDCA4+y5SYaWZvN58L7y4cnxcnc8jiYjoclOCIQxxtUK9verF2cJgAh03ca7+wUW7JNljs0mP1nod96+9+T5mQ1ym3HsIJkkQcBuEKqmaZwvB0NaLaNz3G6yKz0CT3YmUOjz58vXvvZK3axyaqrRcPdg99mLx+Pp/oeffAAgr9y7h2m9WV3ef3jDad65f/f09NSy3L5xo2lrVzsFYxygGVhiwqOj+fH5xdj7nZ1ydzIVkdFo8PNf/93e3sGnn3z2Rz/64WcffVAVGMrR508+2tu5W5aj1KyRHe+Grkv3vv564Kpu4z/9X/z3P//iE0m61k1RVd77LLFt28PDWy9fHnmk5Xy+HPDNg0q62ImKdDG1KgCoReFjlF4MqqpErjfr7aaiI3dd/Oius94YlclhQMgIKkU1UM1ikYhAkbnAayiKyIxNHYv1ghVEMmXHxow5Z2bvfZFzdOGq+EIdiiKCQ+gkA1gGo5yMzEzFzGHouyES9ZWofUBCff5dNw0A/P+4+tMYW9PkPBCLiHf7lnNOntwz71p1a+m1qrvZXJpsiRI3kRJpasYcA5JmZMgj2/AP/7AFA/ICGBjLwBg24BnAY83YGhvwWLA4Hkiy3CI5oijuS5NNdjerq6prr7vnnifP8m3vEuEf78msGicuLrJu5XLuzfeLN+KJZ+GUVcTr7jlEn3vQTI6xtiBUBSmrTAYDcoutSRnlDCIS0Cc9BGXqHQCgBs0jkRAev//+6cUpkk4gEWQYwsVyTsCTySTGGGJkkBAEkqTeO6WdNjGlvu/Lsqyqyuq84QAB6LphtUiaDHiIyK5UH3zw/OpqaFfCCX2QVbMEAEL03ldVWRQcQlisFvPlAjXu7e7MLpfGjp48aUJKoLAajQDV86MjEelD8N6/8OLtBw8eNKs+MozGk9PTcx9js1idn18AwNnFqdb68aNHm+PNs7Ozq4uFIbNaNs+OnvVD3Nzc0MqenZ1Zaw+2dkpX1HVtyuIP//RPq6pwZe2KSqvq6urK+9aHPonMLi6b1WI1mzfL5Wc/9/lf+lt/W2yxWF5lEK/v+7xR9N6Px+M8GVwu2xhYk8p7E+acGMTMrM16RZ7P0808lE8tEeRLk67jlG42n0SgNWUGNAo4UxBpRKPIKuWUMlpbpYw1RbblxnWyAF7zRT6JqtHaCkMIAYRAhAAVILHoCCqJZlSiciOcX9j1PJfFgCYXY1mnwxBc7x3o+r7HtSfFGtNlZl0UU+YkIkiilUPSRJrJIEREn2mywiDrJFNWGglqhsYk/dYbv/Evfus7ZV1YLnzfMNHb7354cOtWoREAiqKYLZYDK0nQNh4RL87OV6uurO1kvMXI88t54WDFCAAopAgEUuCBiAht59Orn3vw1tvvg1jfD1q5KFS4agir8ca4a5eHO+X5+aoawdAxEB89fa4dXMzOhyF+5tW9d9/72BoYj8cbdRWG9tbtg74bZufL7c2JkhBjUEUxrsY7u5urfrh1+9ZkPA59V5alVebZw2d1WY7qSRj6YWi2t/fmqwsh9fzo+WhjVGt6/vBxub3TdsOt27dj8qumk5UkXoaQxpNyubg6PT1vh/Tqq68+e/LxeDy+fXiPeddNd/7+P/iP/rP/+H9b54eflNYkjCGEonBN0xRudLVsr1q/VTuJHpBFkgjkIqc15cBoonWNRMxiOvHeZ6vEm2p0A0JpTYCCbECCUxQ5CaEhRHaK9HrAIiCi4BlQ0Bbe9yxJa0N0gyHktkG6rsvfgpkJyKKOIZTkeghaYxIuRCkB0lau/Rbya4gx4VogtR7pkg85xcG6Itfs/Bzma+Hm9VN2BFFKaWXRWFBERhtlCDUaK4pu3q7BMUIBrXVh9MOjExa6mq2Ws6uNehS7wEDt1SIB9n1/NZv5ELp2MEY1IQSQIfjJqLLGDMPAzE3T4fUEkJuqFMUU4yERUC+CTx89QXYp9YDc913T8nLZKAVd37I3qS27RoUGqtJpbZsucFK+l51tlwJKgtFonMLAMQXfa1BlVTSL+fn5OTOXVZGzOi9Oz56eHjPR0Pvo+eGHH61Wq6fPj8fj0eXsvB7XMfnlxcVnX355Mh2Pp+OiKl599eU79+6eXZxbbcIQ7926d3k5CyGsmoUx5smjx0fPz4wub9269c477wxDZ61+/PgjjqFdrhDVX/ipn79qm2xygdecjhCC1pqZrXZDTPIpiyEiyi24tYU2n7rQbvgg69GesuFW/ve82f0AQLb6JtKkwCitlMo3e/7iWmujbWYuZwAov3HKwGQmNdv87YxRkKLEgUMEyZEMlFIaqcIkKlgbXWpttdbAeIM55DY6hKFpV977/GihVkRUlKVxVl2n2WZgi6+V0wCAl3/2/84HBBFRueulbbbEiQm8+AiSJDEqElbaUExYlPiv/7//j3/262+8d3wUg9nf33/48LgPQ12UhHKws60UNqtV48Oy80Tq6qrb3x7NF8utra2Lq8uqKqZOPXy2KDfcByceWQDgcIRVVbR9V9VmtUhEpgIoqjAMnCXiVwsJKUwq16fBKnBGU0l+6XVRCtNy2WhNSmM3pP3tUWTsh0GAp/WkGNtlExfL2Yt37lxdLapybExvjHn/vWeff+l2R+rhw8e39zb3NjeW7XBwcHA5u+ibdmt3xzl3fHSyt7975/b945NnlXEXlycMaTSZ7h/cCSGMx+PRaDSdTk9OTqeTzavFbFRPl027s3cgkra3d4+fPx2G7ms/+oPLVVLgD+7c3dq9Mzu/+Oav/xOjnbUWAGezWV3XiCrGASWQS68ebI8LOwydD20uRVpra+2N8MNae5NUmz1F8lyMiNYW+QfsvV/z34gQxWoVQ8cJ2FBKCSUz8YwxBkRLnuZT6HvvvQ+xz+tTay0zaGWy0IzZc4gAMMSQj3hKKXEY4tovVok2VuWxKbcZN8AtAN2o9m5g/5xDKrze3Ob/K2sirBARJcCMpoLKubHKkE0SEQmAsjnodZkHQRAgRr44fvb95096bka4W1ajq3b1+HylR9UwDGJUGOIQQ1EUGetikeAjJYkhtW3LnNouO1uA1hrkOuVJ4XLhQTTkdgLDcpkE2CqXIoCoyIkUpCScVFHVTLoN3rmtrh9Wq8YoRLKb092dzTvnlytb2ARC2iya1dHRCZLe29/nIEdHs6Pjp003PDs5vvPC7ab1p8cX41FlrTk/P16sliLywgsvfOYzny2KQmnTDX5nf//9j75/cX65nF1iikbpejzpum5zc7Mej0irq/nl4f7Bs8fPUOjhw4eI+Pjxw/Pz84cPHz4/PnaufPbs2Wx+VRS2Xc1I+r39+973eRWilMqQZEqJWRrv+86nhIRr1lLGzJXCGyj+hv9xTf3MUNR/I146/37dOJKIgKCigrQRJkXmJh2YExDpjG7mn9cN9QQRMxAW156mkARAkRCi0pBYYtJaI6ja1QWUDqwxjtP6u+dHiIjy1yfSKa5Tl5i5tE4jGa2dsdm179Pr/tyJMrOGFFNuukkECIB9GgCAIeR4JFBaUkStEqBGFFQK+Fd+45f/8I/OA6SWl2ERes8Hm0W/mO9u76UIHz99/uDBrZiSK+1i2dSTyXgcLpq2HaAcs4+AAcqpbocw8rFAPXAUwq5lAnDT0rfdqDDCaqnCfAlbG7I9guOr7nAXTy+AnNQRulVT1FV7AVAtJJkwoBubyMujo2NjwTnd923TJGOCUvpgb495eP54trkxfvnluxezs2EYdjZ2x8oNI6nJdk07GlcXfTvdmAjww4cPJfg7d+6U1ej27cMnjz8ERqusLdzRo2PUqOvxqBoPw2CtXSxXKbEfxFVuvlys2s4tl65yy2UzHk8nk+l333hjd3v71p17OxtVu1iePD5+8bMv3b7zua6d9/1CAuZsOxGxVnNMs9VysdPsbtRVVXWdCLFR2uhSIIikLP8Yhq4oCkQVwpAra0opBQ+K0rXyPf+kRSRGRlSBkyZUoBAwxsiQQowg6JykhADgQ5+xnpiGXPxC8ETUrFpj9dpphoVIefaaMCRBRBSs640UWdciUDD7EPLhVgA+k11S8lpngZ4XQaOtKbUp3M21vrZTuH6i1HXmGwBQil5S5BhSiMkPIQ6Jg0AQCCzXriyEQjnVA1niRx//0be+80Hfe05qY7SxvbkzGo3GVTXdqIfBn1/OjLNJMsjXKaXi4J1zzFwUiIiKqDDUtn1uhUjWuSKJgQMoK7fvHcY+WMWCECKIJEWmHKFfqhSBjJ7URYoQgt/adiFxTIOA7/olEU42islkrMgAwGS0ac1IMDVdf3nRVIU2xs6X88lkdHBwcHJ8/PCDR13wmZV4dHw8nkzruk4pTceT+Xx2a38vDOHNN94ajzc2NzfHo/Lx06MQ0t7O1jAMq9Uqg39t28UYz8/PQwjHR6e7u7shhPfff59ILZfLi4vLra3druvOz0+/+91vn56eNsPq4cMPf+5nf7HrOudMPkkhxnVPGSWk2A6DIBCBVmVhDSmjyAIqpUxuVXHNLCYBViovj0mTUkply+E8MGXm/A39PMU8D0tOUKabQG9INyYfcsOxFLxRmzDHvm9TSojr7Kvcv+YZn9Oa0YJA+fnJ/GsAythnnuRijBnKVUqpaxHVDZ8zv5Nf7Xo9JsAhapbACRBJgWA2dTYG1hQsSSkZckLELIpNp5oNnPzTb/zziwvlnJpubgxxCAFt4Xxoz2fpsvVDCBsjxX6IATToqDilxAiJ0+a4JjSaguhE9YRlNr/qBDImghFwY9997fXXfuNXvvX51+89+uBxUcCkhrIorlaNNeCt3rWRhyEUsjF2iy4EzykxiTE2pQgIdjEfplPXd6K5b5ZdUVBZaatssmlruz4+uihLVVJ19ehyb2viOwDGy8uLyqjdrW0i7YriyePHVVX8zE/+1NXl7M7dwwcv3X/++NHW5s752RIg7myPj58/3zi4u7M19t6fnp7t7R08PzrZ3t4+n13u7x8+f3qklKpc5f1wfHy8u7tzfn46dMutren7737w/tvvTafF1mQ0orS7s9l1PsZBW9P2Q7dcIkDTLAN79uzTalRuKeVjVCJJUc8sUSSEYK22uAZxtNYgoAkDomjSyhARGhSRLMG7megRyadASiTmAwEpRgBiDhljz5B74nRzw4okIogcEyuRNAwdWQeKiCCtRyiNoJUyIikzoGm9xswHHXOMDDOm5EWSABijAYMPUcDl/iE3D33f47WHT15rgdYAQInXxoqSw0cFgFlSAI6Skr520iciIY+iVu3x0XEkk73QVYgCIjEMPARlqOk6rW1VjK02iBhCEIEhhjyTOeeMMYCcAIOAc9D3IrRGE4LI0Un/lS9/7pVXXnjvw8eRwTldFQo5lXUxqeurK29NkTo21hpjQmJmKEtti+gK0Fq37VDXZduumOPGxni6WWhDhXXPn57FyF0Xbt0+dNo1q84Y03VdEn91cem02d/ZTSkVRWGM2d7ezpFwJycnHz98bAo3Hm0dH58+PzkmgrbvtLVFUYzH47ZpDg8P27Ydj+vF4ir4/tmTp0ZRUdih6x8//KgozGJxNXRLBP7Wn3xzczwpCpifP//zP/2jb/zKL6+aq2tQkLJRckzJx4CozDoSjhAl0z4irBXruWqklGJIedBmwOwCorShNUlZ5TH3hn6/XitBRiWjXyva1pl311olDnHITBH5lNopL3vWeylJSmFeluZ1OVwnyuM6MWv9Zq29aYVv+lrC9XFkjn3fhxCGYRCRYVg7LOdamz8x74m0UdfYqUCMkQA5JqA+BlZUCpIuSAAIxStXtEf/7F/9s25ldLmhQK1i1wmuVq1x+mS1bOdSVHWhZXvquq6fN20A8CFkqXUIoQnNuJggadUPV2lRWLMaQllR6CBh8gT/9s986X//H/0XWoM1uq6Sl3T39hc/evi9/VuHi9V8c4yrZWAD4Up66ohIaxn6SKiDj96zsbbrPbMMPVzMl6sl7E4nZ2fLW7d2rubnpRlZrWYh9X2/uz8aLujW5vaHV89efvAqeW/MaGtvZ3Z5Wbni5S/cfvL8ibbmnfcfPz4+3ZyOKMaNUX1+MR9NNrb3dsaT8uLi4u7+4cXZWRvD5dlZYXQa+nnTE+4u50lEUujnp8Fa++Thw1sHByNXfvT+G2EY+mYGASL1pf6Tr3zpa4jISbyPgrBsVpLYc4wgyCVLp8gyLkRpT7V1fRx813VFUSjSxriQPJLWSAli7epPbxGJSOtrlpMiiYmIrM4An/jgQ+iIdOJo0bLnbPZ0vdnPNggZuzLGaERJiZVSQwygiJmddkIQozdGhdjfwAU3O4L1I8HxpihmaQcAxxiZQSkMISBK2y7ygU4p3uDzKSUGH6LXN2c2Py4pxRgSkjALoWhtgJICowxEHz94/83f/fZHVIxJo++7vh1Gm9vz+Tythm4eWBnsmbZtGAIDWaMIdRCxmTelVGhTq7q+HRRCXCVTiALM0dKEipn/9A/fq6fYXykzMaUr45z74SoCXC4v2hVGTjHC1naxmIfxuAIfDKW2DdalelTJshWOKXKKNBrJ+TlWlcwu2u39Se/nRNo41zR9P/iuS4tlu7u7eXxxObKFImcrgiTvf/BuCiw+yjCQkbbpbWEO7mymQXO36EJz76X9kHB3Z1+R2xiVF7MZAJ6fnqHC+XxpVeqG+NGjo83SdGJGJbTN1dHR6s7hCwEWZycnY8dHF8XxMWztOd37O7fudgOD2Bj7DDF77w2BItJaF9aACCBoUugsoyUfkNYSiySgmIk0ICYJSIKKCIg53viHgVAONMyhVrnuEsHgfQiBJQLrvH7kFCR7Pcd4U/C0oRjXZz3GqJQTWY9fxpgYfMguHtKvE8UFUeSGwRRj1FqLhGtFRqYFpmt0jIZhUCpLRjHPc1rrECTEpAgBQBhTSgTaobFoLGjDgpk2n5LkZwBRgJUWE7w8effb/7f/6p9dnbar1Xx2cTEMQwjpyZMnpMyyGSKm+bwllWLw7bIdFyNW+uhiVhjr+2F+eeXbAZxBrZhh0SEWttqoQcHh7S0FzBIBSExqzgQR/RCvFm2E/vnlc2FgDyLBObO1o1YL2dw280UTBpYh3L81MUqvVm2+OhTZemSbJexMS6tH+3eqwc9n5+HBiy8fH58uFjNhs7U1nphpezXcvb2vWT985+1333tLLJMyGtKL928f3jtgqPooq8VwdUznV1ee8Nb93e9+93Rrd1LXkw8/ejsOC7+anz5/TGlozp7Ozy6ePr6Afqn6xcXsKF4+vrg4q0vHPlxdPjp//vjg4OCskTefdgOq+SIypN/57X8JILYwGWzKpWvVLZ1zMXL0HkiiRjPZGk1uV9XUuCLj7TEy5gQLkbwtxOyzRZA5KFprBXgzA91sF5k5X6k3A/66VkkQ4K7r8hSf/zwzVq+HG7w5Z9779XxNuQNhkbRaLdq+HdIniRrZly/f48ycpaq5SwGAlEKMfdMsUwo3fJEM5SpKMfYgKQ5+VFREyihtSRkkrZ3VWjtj806WiDDDbzamYfH443cuFm1VlKtVEwP7yKYsMvI/DH5UVqOajEWNUBRF07UatSbILgDWGqWwLMu+751TzOKcbbo2slilFeRFHcboixHZQjjGzY2xpCSiSMOqYwGuapsSjKfQt4jEzjIjPHu6QIrGgFJUVZUrqOt6Y2U171erlbAmhN296dX8wpVFSsIpbG9vb2/U2kDXN+OR3doauaJ6+PAhgh+NRs+ePbs8Pw+xb5pGa2r75vwkAJm+i5MpCbTAYo2SlC4uLsLg2+WKE4bQA+Px0XC5ksEDm1IRHB0ddV2/Wg51WYUQPn7CCSGkVI0E0dy/9yoqCiHd0DpFJP/ARMTHKAiknbG10aUxBrUzxt0cu5QSxzUD6HppjvmeJYFcxm7KYX4A5FNhIFrZmwn6hkl0s5y8USrffJ1rsP0T4Z58YmvKAKCI5PoL3nzMNWfF591hvvfzn3vv8ynPblOJA7KE2LFEH3oWrw1Yp4hAo9C1/zwxKUEiZa0pUSkfkwTsg3324Xe/+e032l7Pl4vghYw+Prl4cnLCzM3VYlqN2IdJVU7HY0wRtaK6SD6Oy+riaoaKEoIpCxiCYmCG0QRQQgqsxZ2fzepC5RTF+/d3tWNivns4efrsqi5GvvNNp4paE5vz005pjoGV7UZFaQ3aca1GlhnLyobA3sfFvPc9xij1WJyBk+NLQ5tA3dMnZ8+fNJyUK+DRo4dHJ88ZYb4I1ageb0729vZKa55+eB6TvP7F106PzojAD3hyel5WdPtO3TXLvu1LXf/ef/10fnZCvnn2/GE7rI5Ony+WVykOc6/fOPEfdMU7V+liBrOmSz4oRQ8e3N/arkNIEP0sJBKIDNqIwur05PHnvvD5G8/KXLpCGNpuiD4EkihUl1uVm4CKShNQQUTK6HzUmCHFzOlkH/puaEMYcH09q3xTAUAuXf7aCuzmyCIquoYC8o2cy1j+yHxMu64bhqFpGma+XsdDCKFpmlXX5kYihBBCEEmUUnE9jeGaiZwX2k3TNH3f5+J98ymkPumYAZMm4eSjX7btEhVqjXVdr7GsT3a+IjmNk4iQtKBCpREY0/DoycPj844DzJdtH5rkQ0rJakMATd90XYuIyMLMRVElZvEx+wEowLIsEbEsS104QVJKEepuCMwiEBjIOQVCAmF+1UFAAjo/m9vSBO5AlCLenY61EutkaF3XJqM2BAaOMnQpei/AwaNxKrHPmjOlwVjIsWshtm3jd3amk/FWVdvpdKuqiq2trcLieARKwXJ+2S3x8OD+ZFpuTMffe+vNAHxyftI0y6rQW5MxEUkyfd/FGH7whx8sl7OiKKqiHI1G1hSEGjgdn8eIFjACqdkAG8ZWVTUe18MwSEw7Ozuxj4QKKSjAGGW5mrOEKNG4Iv9QjTF930e+cbFTxhgg5CyvRWWV1sZ8wovgbIENa2oFMqjrHRJh7gWv61nK0g9EIQFIjCzGuHwL36hD5ZonlUtprso3l29+VflQ3rx/c5SZWZBFfbLbvCmWMa4H9uwHwcxr5ykyeYG0Bg2YmEUhGTKaECWhRIKkea3G55wjJyKolSAoLpESCPV+MX/+7r/+w+8fX65WbVC6VCk2y35U1UppW5eReVKNr+arZmh1wNIardTlfB4jaK1N4cDHoihWwzA0TV2XQGhR94MoA0XJfeqcsgCJ0J0+X+1uu42aTucAiowzfduOqnG/WHCykw2OEqnFpp3XdblVV49PZoUjInJlGdNV4crgCaBHAk4qDLGqU+XskPTR6fxgdzL04XKxHFk4OjoOAQ5vj87PZ31cQeiFx0McHj58uD3Z8tJfXvogPNFmMbtaDGgNLTu8ddv1fZNSqqvBD91ovF1V1fnFBZI1xkNMpAAYWoKPr+SAFyzV0IEbK764OLx3K73ZEBNBoE6pDX7x/kurdi5DVxTFcrEyxhBR0yw3N24NQ+eMKpwF4IRaMQCQ1iYMiVNet6y14CBilPbRMyMkRTa5skgphRRlLdQkQIYEMQUEjQCESlmVUwO9X29N8108DINVOue13lzWwzAgoiI2Fm426fng5iVWPuhDDFEYMYeKA6f1WJYH/LwsyOXZGJPSGrtcN9+CwIzEhE5Dy6iYeegXIkIAaX1ffELLo0IZXNsvcmnpybP3Pn7+aLFYxcgxxrqul0OHirQ17dCHEKy1RFBZV1djbdzAkgsxMzttAiellPceCIcQ296LiDLaD8GHxBGUQqOAJZlSBxkC0TDE6ZZTSglTiE1Zliz9aplmpzElEVbNMl2ctYi6LKtmFZfL5WisQwhIUekkArkGWL1hlPVdKJ1Zrdpm0Rpdbm5MN6b1ZFI8e9x470u9vbs37QYe+kIknZyf+V6DxC984ZXI5CPtb+HmGJxSiLK7t12PSiK0Tl3Ojhm68URNNkZ9BI05ViaCAAcmgshcVoUkqsYjEQSMiLICgHK8N5aNnYPFVdd0AyJqo7Lt/3pMtqTIiAAIaxABQAWBo/c+V9DMAf0k5Q0Acc3VTSGGEBRmVZqKMQuMVSbXpbxoYuAkwoBAwpkMz1kbtGyb6ws65OK6hl1TCCFkW2Tvfe+H/Cl5xs/nNYSQ24QQe4F4k6zpnMsH9OZQ5hsjl1sAMGq9WAJOMbBGIli3vJrFp5TXoMAc862vQEWMwNw2J9/+s9/5xje+6cPGEC/H49Hx0cX2Fu3sbcfIqJSFoq7hYnbeDkNtSwBQruiGNokalWXqW2b2KYrnvg1FQSmJiETmq6smCjitIKFzRqchQMREWuFqGaqpOjtZFACkYGd/enrRjifF1by9/+KoD+S7wfuh7WgQbppojCFUF6e9KzDzrXxPA1llG22HxaI1NPZhCQA7uxsBBu9XyccXHxxubHDTLNvmcrmS0zO4/4rdnGzOrvz5ZfPgwe7Z8dHR8WpzdypJKkcX3fyFyp6cPX/w8qvz583V8sr3onRlTdWzrx21fUJFkhhBcVJ1kazWOzuTd998KAwvvXgfEgtoA3B63B780A9M97+ws1FczZYY12zDYRiyql3phMCQGDimSIDEKfl+pciiVcG3CnFNO48DAIWhd46yzCilpEn1Png/5HE7e9mRcsKI6EHrfKoAwFqd55Wb32NKy+WyLEu6ZrbnECYA8P66heUUYgCWqqo+jRKEEJAkDSGfabl2PdFa551WPpeZjZX52rlhiJx86BWjjwMKLFdzREwhigh9AqlKyPxUFul91E5r6WYXzz949Ozh8UV+RkOSGIGILBBEHrpuGIayLAGgKGzve1LgfS8ihpTWOvlAAqu+YwTnVEyMKNZapRQIaISUBAADJ6sVIAyJm0EHQE4qRNBaKQXz1VyQjcGNjSoGmV2uLmdD15nlkuvaacPaJFQ+L5P8EEPgEGNZS/JYlnU3yHjqFClXFJcXCyJLUBLqq8t4dXUVPLqivn37gBBCJyfHV6umm0zBD9A1/Rc+t/Pi/Uk39MywMdEnJ2ddN8TIqGxdu+RFQ1rMlgAqZmPYNc0MhKMGgJi6pi0rMoTL+dWP//BXXrhV//t/4ydefbDxH/yff3m56K3SXdfJdegPXrsscYgKAREYKHCCmFLvgdcUYGOcQI6zIk6ETAoJZW1nl1JKPmikvHJERKVQGzDaZfeEm70OXnPejDEZbLnpIOUmPpjohuKet/CQOIagAG+K6w2EBACcPnFCzpz8GzNHuN5s3XS9uXIzcxTxnLroo3CA6GOMDH1MrQ86n04A5iTAPqubESh07Udv/9G33vjgj771mHnn4vRp4WoSmE7LEKMMfdP1063NxWoFQClwPRqddmfGmMX5TAhLW5yenYlIYd0AUCmNjDFA6Yr5VbO3NyU1MEtZlsaErue6oPkqUcLkVYpDRKkqY7SqJvXFxULbqJbkJZZqw6fm4Nbe5dVFbRwn03UDMo8mSmvXdcN4wymtrE1lGZSCs/NTJjVfzcvStV0oR2a5XNhJRQpWzUXbpnpkqnJ8djx/8YXNy0uuSp6OQVv97Onx9s50sVjKVctJn17Otqf7021Iffr+994b1zh0aVJOunaYlNV335vPPGRqYuXUqIRDp0sHCPq9j06rqZmSNE3zd37hFz54fPjBo/f+8X/5n7S+2Z5MkO2XvvzF997+sCzLGOPGxubRkUrsq9IiKmAA9iIQIkgQq21C9L4XIOfqlFIYvNY6xgiiFTlClXtErXVMERGrqgohgGhjlNGlSEKP1hSIWJUYY4zJa629d1W5NnCMbRNi5KbJp/YGFmWOCJSS17gGAoy1KaVsznhD/GP+xIFHaXSFyaVUrq35Pr1nIqJhGIjIx4HzQecUfFvXNZFGjH4IlJsGZkA0QJi1nBIHiGm1WiQwq25hdecZOKWu60ajEQAoa7rgGSBDBllBWxX12elFnkYBIKyDaLiqnDD6IVpjY2RF0HQtswDB4H1KYfDBGg2ogsAgg2fRBro2tm0fwtAuIUXVtyqxrJoZsDs7O51dpSHI5UUzHlXVCKraNKuhKKHrhhjAWLDOOOfqEWqT2hVaE7a26r6luhovFkPwWI9Kgrpdie/6IXQnp4tqbBfzZYjt+Vmzf7C7Wq3KeuP5Sdv6QZWGari8vDw/P5/NFleLRdP5BKwUtF17NRCATsAEUjs9KvXh7qhp/cVsWY3Gs0UwxvY+vPv2n+3t3H/1ldes218eHS2XS1PIrYOdG6MlZlZkY4xFaZWxSilMEYY+n7kbo9rs5E1EeS3OHI0p8/owT8q5Hufp2zmnVYlgRBBJrqWbkhIqZYx2+RK31jrn8js38GdG6W8G/BhjYkG9HrBuECv5FC9JromqOR9GKVKKshlJPpR5HZCPTa7NMcYUo/eRmRXqFJGI2nY19IFIa+BosjcfQ965MSQESwAi3dtvPxYudFHd2tXLtmubJiyWg/cFUIwxDMMQPLYrq6xSuiq0H2LXdLNFYFmMR1XftGgV9Jw4msJorUbjihS3zYAEWukEAUhzF4NLmikS6yRV7bSGJvnxpJQwbG2D0Y45Aqmmp73D8dGF11aS5+lUogylheBlul1673c2HVCYz81F6hB0CgBSuAKWS9C2USaSIEceb248e3yuC6lqLMa0mOPmhrp3v/7zq/NmXk230vHRKRLHeHm4O7nqexS8PJ+9fP/w8mxB/fyLX/iLv/n7v//9pytdmraDBIQQa0WV8P19vb89WSxaSzjZsX/87vJwk1ZdaxX3ftYsjn7gB370N3/1V9//4O0yzWz1uY4nRWG7bgCAYehc6Srtb+9vEyoGST7mLRMSMfvsp+zcmkWPirIbN6JSqogxIt7cyCGlpA3lWVvrfLM7U9LNmUNEZh2jV8R1Pc43JyA1pPgaY9daZ54RALAkickjIyJZGyMTQVEUiKiUIRLmeL3SFABwhdOaFBSBOQa5KbeLxQIRk7CktSQwxgAAIbD3jUCazWZE2tk6JSaIkIYY+8QhMmc/p4iQjOGHz44/enhWjid+6FKMTT8o6zofIgszj0Yj770ztiiKvu8J0JqCs2mJhW4I/RCUNctmlUd4IkocWIJSaIwmgBijUSBJgLILbogsWiuA2PuBWZZNZ5weOrVatXUtbSPTbVwuGwV6Mq6ZYxKylar0GAD6viNnZOg4pUXjY1JdE0bjSsCvlgPpwAmqwiqQW/s7Xedv3d41xiCVi4V3VVlY9ezJc6U1kfZ9u7OzU1X1gwf3z04W3vuuG4qiFAp7hztR5K33vvW5F7deuLO96JJSoCBuOKqQtzbLjdqOzChEQa1YkojmwERklF4tF7P56Rvf+qPZ+VG4PP7wvXcfvPy56d6d1WqV+fO2tJW2VsPYrE1ZeJ3VTXxtCo55V68KpUwWIRGRobWWKPL6dLJEwEzrzFL09Zrq5srOObREJKIyqJSNwZxzVVlaa3MpTZGF81dav2UznDxY3xR+RGWMWy/lr/dDyujC2tLYGxUAYiaIYEgx96+Z/sHMKXHuqhUZBKNVgaAJrY6yYhAWBmYUREaQJNgu5ss//s7H442R99E5d3J5umr7zc0N0roqCu99nnUwpbIsl/O5dePZclm70ve+MJqZ+9CX1vU+AIBSDgC8j4SKE3mfEEGjBokxpZGzHCASWNBhiM6R79AVojW1fdKFGXyaz8PGxB4/jbfujoahW12GaW2GxKm1z5pl7aAgM58NXqTcUHWBW6UaHU7e/2BRVjyZamHTtT1ISWa46ufTrY0nT072b1fLJe/vTU+en3BCQ2Y6UnUZjNletAtJ1bNnz7Z36/OusbZCrP/0m5df+xq+/NLBo4fHo8O7XxyFl27tPnz0dLy9Efr+pbsHG5vbR8fPnp0/G5OsVtHaIkGoR8TMg+dK0gcfvvXaZ+xvfuu3/gd/+9/dO/ylp89X1ZibxA4Go7VTozZ0r96/U442knDsAhoFURjbQURTTUqUUpijaEEhqcSBSCckQiJjSVIYPCAjSM6wRERAnxKnJFrbHCKfkuRsDwCoqqLvgYg8EQBpbRWhtTaEwVo9n8+tU03XZiYICAGqwXsiMpryPI6I2Vcf8RO1sbFqWo+NphgjRJ8F/jfjV25VCSXGYIwKIQpjCN7ZUcZWAUgkWGsocUwpZhITcxKJzIlQOQ3LBQH1q0UTIqOxHCAMAxE1TQMAKJKdqbuum0wmwUc/DMtmqbXmkL26oek773kymQy+SylZWwQvXedz/+Rj3NgYA4DW1HaBAZKwCMQAhFoEYuQYGZUXgch66FlpXiwW4t3h/gZR8IP03QqMRUDngsbCFIhIkNiaMHTRGFUUbrWIMfbViFarVtvKlbasaHt7XLqdk6Pu6uKqqp1x1cWpdHNfV1MAKit3dnY5mWyy9M5ojvLkyfOdHXZOX50vmxkcXTxVkx0y/t69O/u39r781a/u3Lo7u1wtl1eAoV101pVrVwXionBN056en6HAm99/I6b+6nI+mm6Px7eraqceTYxRfd+jaB+b2wcHEdYDODOjcGKfWUcx+U+P2DfIIhHEa6IaIhJqpcz6toWUUsgeODHGm9/hWjPEHJVSuXQZY3L9M8ZoTQDZH0+0XsuhGCSknOPG2V/pmt0cAfimeTXGFEVhtVmbHohk0PRmPMpNKq0N5tdbq1y/SbFSSMRVVRWl1dhFoaiIUEwSw4jKqsLW337jDxddE4K6mi89y6IN2ppVOxSFu+maZ7MZGls6d3k5r4rKcrKTycXpORodGZXR3nvn1DXoIHk5q5RKPBiLzGgKsJ3GilaXPQBEYa11s4rTTdc0IQU4uK2bJmDQRQXGQlmRIiV2ODnyISk2nBJUjleDaFvrsqkVtissS3V2zl1YOctdS8yglLNu4ABCvUBx9OxKcEjB379dtqtAWhWVv/OgMiWs2ovCbiznvXXw8YdHr7z60unZ8uNHp1/72r3Hj86GzkmqNrYbCWH+/GkIgbXvLtwwnylhwNBeXWGfaETEnUIVkt4ZoW+Hwjpm4FUaVD8aFZ957Qt3X3ztdH4yLe+eHz3ZGE+VwnKEleU7t14BNCyiQHyMMQoZIgHGnjmhQYVIihWgRLTWcooQg0JCliTrEEQAAMx6oHRd4YQlppSEUSkl2Bd2PAzBGAPg82fE6BEl63O01tZGZu773omIiI/pBsI0Rkli63Tbd9ZaAoyRtc5xvWSdNkazQiWU+p6ZvfeZgZThXmstafTDMB6Pm2alyBJppCS8VoqKpLUMOnBCAWAkAiBRhrQhlMXx86dkCgXJFSYAE6pMuxqGoetiURStD54ZJQHpwMk5V4+2JAI53a2S1loTWq1E5OpqocjkbBQiItSCUJZ1UeJktGGMGRVVEgRENNAPup5g03ZG6+l26bs4qSnGWDgXI/s+MXLX0+amme6m1AMRhBS3tiazeRs9pSQCcXtrTKSrMdmqtCUUYzeZJGfHxYTaFoZu2XVDWY99kLKG6da0bQdLslosm5X3QxyNnXVy63C7rFQQ1rb7O//eL77+2muk4uHhxua0qurNSV0xpHpikdNidvb08cnZ+fOnR0c+JF0TJlZOMZrShBT9eGK7Ns1mQ+BeYjw5W7zxrT9556M3qnLjnbff3d7eJlHKGuF4uDFBHTGREuVThMSJ+zD4fljG6EEYhJgZRAOAELIkRGS1DkiwpLU12hplCImtIrcejzDGOPh1RjVLJMzFEogysTIK5NhAle+0QlkSJo3GmLp01lqWvB31WusQUkgxSSQiRJWL6DB0GdKPMRpSLJBSYoX/jcZUmRs41hZWhK21RVE45xQZ54xzBjGH4ZJSirRRpAwrI7YoXeVMaXRxdnnx3Y9OlqteylHvGWM29IfguSjKqiryeir0ULnJ+dF5Ma5PlpcfnTx/fnE22dpClfks2WG/zMzTvOsiohCHQo+Xi15rvVxdVbVdNUsBQUQOAOBXS8EAXiJGv+zl+JK2XnD9EHxQgjC7iKXDRRdmc9w8sNVYtytEbAgkRRam6YZ5/uiqKgYdpSSApRqVarVIlxfdqy8e9il0NL57b79vWleKeHu5OLembDpWhe6b7vg0HF3Mz47TslmkQKvZ+f0HhycnD3033D88bP3wQ3/phw0uz04Xe7ub1nBV6/HEbh2ao9NoSJeFJcSygLalNgwcQZP2A7KQQDFfJpZya6tYyvL1z/7As2cfPn/09offf1SPtAIMwb/82Re1npDhvm/Xuz2SmFoWD5hSCjF5liiSCK0CRUqDIJJOAKgNkjO6KMu6LGtnJoWbODuuypE1RT0eVbVVCo1VuV9kZiKd81pz+QRkgaiUQrCswNpiXEycc2TLoijqUuWD1fd9xtj7LvqQhqHJidGZ/ZR3nj5FP/QhDH3fzy4XMXDGs6pqtLGxXRRVbVylbKEMsuT7fTwe57NbVZXWOvEQgicBzOsPRIVKkTKIqrk6bntfELXLhbOlMQ6JlDLG6JuX2Pf91taYmTPLQZsCCLRxKUnea2m9ZtfeaBEz91EpFUJi5qK0xnwSdy7ZRlApQFdUtnQIiGVZIMef++kfWS58WUy0ga09W0/LlLAwFkLCyFWpuoZcZZxTSLxq0mQncTKKUnPFX3z9Nkg7mYyVcL+clSUM3XI+nyGlrk2jcXG4vzX47oUX7i7n0UfY2C52drdjgM3NnXIkhLppurrUHz188+OPnjz8+Nl3vvO9YjRazOX88qHWBaKpqw1iBwxdw6RgY2OCoLS2AGIJCqMRgTEJ8nxhq3rSrmR/+zOz+bEpNj7zypev5ueLxaKqRlVV3zm842yZUac88H4SKpc4b6tlLbzMlnEKNWaJB5FBBUCIpAB1UVQAhDrHI1mlFCqytlBknCtzvkJKwfs1ipQHg+s3QSIEUqi1tprWbYPW16kJa+08MLOPIXKKnPJsvl4OxZh8CCHFwHmtLyKGjFLKaGuMy7jpzQoNr21O8sm5icLRuhwJM4Jy2okp8rJziO3FqvPktFYg0LYYgwfEsqj7zrNE78NoVCzbZeVKU9mYRKOTuBpif3nGlbVZFRXj2mfQORNCGI1Gq9UqRpiMLJTonLk8m+3v7XvfAyQQRtRdCuMKPeO+reax2S0rDf0/+oe/qx2kk8vRuFw1sQ2dqV3ru8Ucqgr2psWyDWhT7NlWZXMRjKs3duJqZscH/v33TtBuJB8+/2rtgzk5be/vjzY2x0+fnIwn1g8c0zAuiocfPtKGOg8q8OKyI53mV0ttNp4ez9ogmyP74v0Hl1f+5fsvv/m9727d3v7F//aXLk4v7t27d3J61KyGo8fv1ZaWC65qf3HpyxIHn3ameuqIbHV6tOh8Cp6tKy4uT//W3/zvTLfHfW9Ojt559OHjp0fHD179zC7S1na9O92NobOog4pK2dVqpZRSZBA/WVGKJFKWFEAiZhAAYwgBBFNCIlTalAgqyGDKwnuvgwaAJInUIInUOl8mxRhJeaVUSmC0y/MuoSFJjImTIIHWpiJkPTStGDMS8XkyzhUUEVIipHV0CGk1BL9aray1q1XjSMfUdWFNMCrL0rlSCIOPRMAgMUUvKREU6xO5zm1arVZKY2UqIiKFOhvmZsVVLmbIWpIPKcZ+xczaGABwzlmn+74Xkbouc7A5Iy6XSxFp21VRFGVZDoP3yQ/D4JxzzmS0IjMG+r4XAWNoGHxGQKqyUEoNwQMAIILEn/9rXwut7O1UTddo0VfzZT/ApLbjkVLWCPiiiKFJhSbxUDhlFDSrHiFoUaNqvLgM2giBtIs81cpy0S9Xc+9D18PlZV/X9vy0Oz8/YiY/pCS9s3L3hfH+nbG1Y4hmc2v0vbeeMxJqszWdvPDC1sZmsmb3vXePQjd885t/gpbu33nw8cdPZlfnv/f7v9MuMfGgTPzKj7423TTDoPqIbaMXq95po5V0HQ+BohS9FyZvrCCq2tl3P3rrR3/kZyoNtjBomJMYU47HVQhpiD7GrKygG6Na/JSKHAAQFKFGVFo7MgbJoLKkHWojqBjRoEMho6wyVluntVHktNaoiIiy3VJKwumTXDmt7HUFVXq9RierrdJWuyLv1ImIrvUkIhxjzOcH1ZpICtfmUPn1r3dLGgGAgEREabjJekQWlE+G+nxAlUalsmsYEZHSWitjmBQCIAmDbOzu/61f/PENZCx1H9qitqPRiAQQVO8lhKi1Wcy9NcVy0QqjhCgpIBMpKErDmMrKZXF9XqB1faOUslZrjdNJra0pimIYhunmBkhKSQAZRF68vffN3/jm9kbdr1pdAodYOMeenE21KTDGvkt7O/uTSvtVu1WRHhKJS4lLW1ba+dXKmLi9Oa0LNart5oYaV1svvbq9NYHxuDo5X4KyqJFFHezcwhinEzUM3Wi85UN/Oe/Lzb2v/PDB2eni8HadNC+XQ7v0x8/OVzO4mB8/fPz8J3/mJ158+cUvfvZL7WL5/PllZASx3/rWd95/56O/+ld/bvfwwNT4wisHSruTU0wIx94LcosrP6im7fsIm5uT2wcvfvjBx2b6YuXcP/yP/3dXV4tnp7Pz8w9Pri6UTiEOpISUzpEaGsHSmkyUUmIGQBFWoIgRlFKGCq0Ko2tVjkyxYUxtTK2008Zp56iodFE6WxNqra0xVmmjjbGFIQKlTOFGWtuyrJVyhZtYW1lTKFOAYDbsUEoXprDFuK4mo3o8qmujtTUmk/CvOaPIzCnEPEJ577uu64chBM+CiXE6nTpbElEXh9wchpAScBRGrYyxRIScBIElAseiKAQZKRgrRFoRKWChHEATE4RUjra3xxtM6Ns2JWnbFgACx1XbIEJKkFJCAh96bbAo1m5VoCjG2HWBU442XLsBxhi1sm3b5qVZ2/fp2pm87/vBR45CpLR2z05OGw+oeqvsuCqcU007GCvep8urBlD7gJez895LPSpTElOQ98NkujmdblYjJhBOMJvN2y4OPQzDADjMZjPriIQ0UunSdDwaTfz8arW9V0wmd4YhGot37twejYtnT98/ebYi0ZcXzf07r/Q+XMwXixUItI8+fri/d+f54yePnzz7o+9+/+TkVCk1v2r/0k/+xVG9+fnPf75tu+hTu/JdP/trP/+zWwdRIoTBRkhdG43B3Z2i0Law+q33Pkg8PHz7z/a2Dnf3d28d7t6+ffjxB8/9sOKkkyApnQUW+Z9UCNeuCsyalIgIJAKm9WRMQEqu+aC5Dl1nCcl1uWUiynVOKYNIGULNhHZmztGJSqG1WmlcK9+BDGrrHGiViSP597Is89Rxo1HG6zjarHoTEUBGAtRARM7YPLeklIZhyNSnGH22W1BKa2VFhBFQQDFAjBrRaFg75+eqnlHglAJHH3yvqNqeTDv0yq+1fIgChMyRDBBC3/fOYUqglMry+xDWJmyE4IyN0edoqaIo8t8k/w1T4hg5B0fAWjHDJkcchDQkAG1YUt/1fZcQRasCQJQxg4cADARdHxmkHVoREUYidXIyS+xXy9YVSmsdUuxCz6nVWkvE4LEut2aXs+m0iD5dnc0nI+d9XK3wrbc/+NznXgaA589OkGU80men87pOQw+r1Qo1RpUObu3fOrw/tJbxytnyL//s154eLR59dGytnS/a737nzd3Dya07h6cn57ubW/fv7j16vz09fW6tRoA+dCEop3cWi5YgTTfNqpnde7Dxxc9/9oW7B0ePn4pPZycnz5+dbW1uSwopBWYBtR5BmBkIgeSm+8xgeKZNZTyI8viSSRlEgJJ/IUE+noLrxi5DPPkwCVy7yKq1ZQN9kjmotbZVVZXWaa1tWZmqyJvPzDu+0WnAtaIjhACoFLm8wwwpAgCwaK0VgcZrTYjITYpI/tmBUI4cuf7bgSEFnCAOShhQQvRaSJEyBlE4pZRAJDFjivXW4euvTL75zcV4VETG2cobYzr2RIhMfmAirQj9EI1BrTUSpxRREgegkrtVr6xTGm9ELVU1ys8NEKaUBAJROQxhGOYAXBnTM2vQI4eJqayw93EyqmarIQHExFppa2AYBNlwkKg5DGBJVyVvT83TZxfTbdW2aXerqILcubMd+xQjxNTsHI4vZ1fKwGrFzVW3fzBtlsv9w/L4tLt//+6qez6Z3GueXUbhu/uHy/piMQ/7O26xPJnP+SuvvapgNhpNNrdGr33uB37jj//g+FH7b/38a5zMO2++1TUB2FcVzBeXm1sb77/z7avL+b//d//WP/8X/6+Nac1RLvrKVH3jz+/cLa9m3Xhsq9HG65/7/N7Bg4NXXvvjP/yDvd2di6vY9vbZ2fLOXVj1nbBCMM46Dn0WugsoVCiSjLGISEICkbBCuBYnkXwyfgOxxJyziiQgjAIxeaVMSokT5FAh5oQAwzBoa7KPUp5lkTlbagNwksgx5ZqdUsp2V8bZdtUQqhBj13U3+uO+HwAgm0UahUY751xBgEYFYYUKrrWdSqPWOrOosp4zb54EIYWYfW4AFSI6rThjYEIKKCdvIxChIo8edfnaC7ehpDS0hdXZqzQ/DYjonGubEENiBqWUVjaHLRijcvRXVZbIKec2G2OUMvlOJ6LSFVpTfgqJaG2TGTMNO/retw0nSWVZto0nI0LgKqVtYonGgsSkMAoDc0FKqrqoKhhX4/llUsqVriisjX03u7pIKWjlTo4WxihmIBWsVf0wB50uL5b37rx4dPTk7Hk8On6qC9W23dn5SdtxYgohaYd1NX7zjTdnlyff/rPvbWza3//93x2auLNVnZ62z44/PNg52N03Tx5dfuaVV8uyFJGPH39Qjcrf/f1fM0YNrbt164ADL1eDIjWEeHhn/8WX958+uTA4+tVf+8bZ6fnrX/0RLPDXf/W/Xq1Wb79/fLmcrZZDYtDGgdLGlNloKZvYwKccFRHx0yYi+Ckt5c2HiQhwAhYCQFhrjpXOeo8EyLz2DUUkMtoSKkXaaKtIIykW0rbQ1hFpra3W1hhntMvv52yD3E7IWkDniVBrnbPtEgdNrAiUQq3XVk03HUi+7p02VmlrbfYmjz6kTF4SjpxYkBDN+nsACDoNKrAQJ620RokcXnrx5dfvPH94eqFzXDiaGEJhbNcMALy5NVouVkqTD711NSrTD31Z1Uop4TC0QRQNfej7tS8KIi2X/WhUrbUmmuaLRVWWIXFqPQgikmBqWU/qaFFLSrNFKCaQwLSdxwjGgrNIVoyiZomm6uuJbZcrrGzfNhsboI1Aare3xkS0temOny9J8faoWi3b+/enl+ehnjSF3nTOoU4xXnz21b2trclb75wFHlzpkPT8ylf1JoZZaMuhX9mKZiu6d/eQpCzLdtkNaL3R/MUHr83bITymv/7v/fi7b7336OGHtw7v7+wd+L49O13u7x1enK+CzA8PeLkq2deDv2ja83S6+OJru9/80z/5O3/7b+1s3+K4ePzO8539LYCTIOMPPvhot9xuvXf1mGNiPyRJlC1RY/C+zZoxBkQQTkLEKaY1/JKiUkoAUAgkpsQiQsDAgqgTA2Qzz7QWCjPHfAUjolJrSlTeFNrCAQAZ7ZRCi13bA4CxVjEDSQgBWYvI3t4egywWi4z8uEIBJImClIh4MnJFAdpYrQ0INjxkDR0iirAxxqBRqG3hQgg+eRHhEPsUBkgELMEXVilSCLkiZok+ISkDSgOJNbWzo+39vbv3JrUjABgCM2YOR0oMxtIwDIAgIjGQ74eYPDD6MDClEASFvE+ArDRqbUNMDKxUJn2xiMSQHy8LwKStc1qIRUBIoofCKWZfOWga8AxdxLomrQG5LEodAkcixuLsNDpnLs+H7c3xztZoOsF6ZLc2x08fXy6Xna2wmrj5ZZhswvGTZlxaa8bjaX16fnZydHV0cgaqB0n7e1scY9cOzClE6odVjFGQQxBm6IM/vXjE3GqsktBrX3ixb9vNg6033njj3XcePnnyyDl3996Lxtl7t+/NLpd7+xv7+7df/exdwfLVVw9XlzD4lkm6lZDYjz86u3/v1r/5rd+0Vfytf/3b33njj1566X47QN9e9b5BSMsg1xYFYJw1xlhSGklrbUiJKFQCSKgicwSSzNIA9pkAGpLnwJzFjWFIIXBM10sQzBS+rA9Jca3N+BQBL1diQQSndWJOLNoa0mrtXay0M0VR2LJ01piiKOt6VBSFWouTfUoBhWJCjiExEyBCIk6AKEjKkCBoq1mEUAprFZNCnTH8BEIobdsGgYRMAAQEkrQwEmqGqJTRYEQ0iyZMgPXhrS9+9Qeff/To6uIqKM0iUWlInivrYoCh90oR4bXSmSHGhKidU5iYUSpnQVhAiJNGKTQqdCF4ZjZGpSTKrCMdIEqBRAkEcUg81mBHo264EAFtIIVQW1x0XI/M5awdRaqcKiA5SuVmeT5rbu8UXX8lS+gH2Nv3H38cmi5FbOZzKCtzeFj6FAavPnq+3N5QKZ0qpfZ2tk9OTnhQj56c/dlbq+m4qiYJ9BTj8Xjkrga9YUcb+5y4Q542Tf9nbz7emiqN6Zu/+9HrX7nz8IP3v/qlH/u95vfefvPjF1849N5/781vGTX64hc/3zTN6dmj6XT7yQcnb37r5Cs/fPf77x6dX5r/1f/ib//LX/mnt/bu/uiP/OR777/9j/7j/+TugxeIm1//jW9YWy6GYVjxxeL05NmG/rJNpEk5lsioQURxcFwrJGKJIHrt0XUdlBhT8j2iIgLPiRA5REZRgIiktebEgJxiiClA4uwYD8iItSRQ61ybdfOWEYM10gpwM6oTUUEFaUhJymIjxjipW6MCgwrBpMjDMEQnKQ5Za2qQkEOIumGxEQkNaS0KRREqbYBQKWYgjRDWUfUIyugCAzrrFBkAKxKy46ghXDcHqLTSltASkSunt27duXdnux+WVq/X8aAQlco+T8ysNMXInAQArKUQAl17k2YfdUUGFZE2PkVj1A325H0iVHJthiaUs2iAAZnh9PyiMKMXXtjpu2yhJTk13ZUw3Sk8p/GkTIGbptUG2rYfj8vZOexs7vSdgA6FKzlajAUinJwsj5+mahwJLQAJ+sS+9/PxhJbL5vK83T90L7xSdo2MJ7y5g7GXne162V2++sU9wGK8bRSBLaAoqgLrGFXi9vtvv/dr//IPX//iq9/+4+fvvPVse3v3YP9W0zRa66IoDg42Oaad3eLFVzff/+DUFnH/EH77d/7N7t70+OTJo8cflGXxF/7ijz1/+vijR0f37t7qhpZIrZZ+3qzOr5ZEZHWBZBQZVBaNATKoDJLNG1RF5rrpJ0SFLAR5tc4IwiECCLIAco6bu+Eb3+AAmSaS7WRv/uQarr8JOV43uOra/zZLPAiVMcY4W7i6MK5QrrT1qK4mk8m4HpXFpCo3tCoUOCJKINdOIISIVhunnSJNxpA2SAqUzk12Jqc658hoIsVAoEUoZUIeZJL2GkUjjXqsiEjX9+9+9a/85A/t7E4qVQFEVyhrtY8+hEFrIIVN4xHR++i7GAdmLyGEuq6t0gAQhLvoUZlVE7SymTKSUijLWmTNebFoyWhXAiABCQC0AXxLdRk+/Oh8VFtAkgiTSrP3HODJk3bZ0axrFiuoRmBRFaU5O+l+5OvbF6fnnNTVBTH6oedi1C9nodjUYKCZmxKGQpcbo9tDRxtT2tqaeO8Pbk0n1qZVenC72q23ml5eePHearWabus/+K1HP/FXvvzW9y8O9/YxwtHTHnRfT+L3vjtTuHfnJTvEk7/wl28/fvZ8Y2PcNIMtJEa+PJ8d7O19/Ud/9AuvfX65WK0Ww/bG2Ehor65uH9ybbBRb29N79x98+803CPVXv/61OOceRAs2HSSALnHwrQJrTab9OFKmKOuiHClTKFeSsoTGswiSICWFiAoIJecfp6w6Wm/Jr2emLJyUdSOotHPlJ7bwvN4g8rWRWGIf0xCHbmjb5D3ET0yQIwdbWkQsrKvGxfb21vbW9N7B3tbm/u72rb3tW/fu3dvd3trYnBa2ZFNaPalMhdapstRVRUVJlVOFQasEiYzVymnl8qiUX5IrK12M0ZQRZOBIqEhpTUrfeNgqpaJEEEKji3rz9q3Pf+GzGzH1lXUcIuVou5SUUn0ntI7rhhyMl6E1q3QffIzRe4hJUkpaQTaLynSVxWLhnLbWtm1bFAVwdAaUcI5DTwBloY1TZPQweEQURO8jIOWCUhTsPVQjp7UWVhdn4cVXitPTi9HIVqPRquOuB1S2Xdh6hDESOqg3/Ws/cGCr5vz8fDyaBM+2cPW4QqT5bGU1nh638/lxVdLx8TNO1M2Hu7d2H380f+n+3vuPHu3tT8DEq4UsV7y9Mw6w+OD9NkZ+7/vHr7585623v+ecMcY8fXJECjY2psvl8smjh1XtrILzk2VZ0Ze+/Con2t2ZXlyc/O7v/fb25tZ0Z+OjDx4ToLIGJA2Bl4tGaypKky2FEbO3d6bAaSCFikBR3r6gIlQkREAqY6LXvWZOPoY8UN+sRmG9Ls+TsUbIbrdMRAgCwvlXnsqvSc3X5RbW+EAWdWitjXFWG2OsNYVyrihsUdjRuFaoq6rK/vNKOUStyNz4gittlV7PZGpt0gtKqcxyVsqUZe1MobKOniqFI4qZtI2CSjFkk0cxRnFGN7TZvPPK3/j5vxGZFJMT2rC1rRyRVhpGI5sYmMHavMyAFMAgNH2ryLRtP65M4VTXL5wjrXWMUpY1INtSEetu8K7Qo0oCq5J1TQACQIIAn7s/VtVWYEUC1uqspu8jc0KtbbtCIZVEza9CUeGt2yb1emd3XE0mj48GBL3qUht9uen7IN77voXBq++98ezyVG1MR9qGqqrOz8+tnRrtdvbc8bNZXVYn58vdrf3Ls+7OrXsh8dHx2Xe/831Xwle/9uXHD9vxpv3aj31tul08eOX2xvbW176+G5O7fWc3puHPv/PeaDSabuwMvvvpn/n6B4+ePnjlc4e3XnzxwdZnP7e3f7s+vLvddH1tBqs3ho5efOGVjdHmr/zqP/fdJZVGYhCUxPT48bmfdZdXMwsFghFEQm1VochqZbWyCTUgRmStNWgFhgCV6LVG3mpTFAVkedJNnOF1OjUiGpcnLmULV5gi3+b5WhdJwAmFCVChlpCu3ZYZMHHyOSkmxCQMKQmIdXZki4mrN63bmIy362paFiNrSmsrA5Wrxs6W1lRWV0ZZFEStRBPC2gBVG0WU+z1VFIU2rqpGRVEVRVE4Z8yaF3/tx/SpaHJEZE4Asu6USe0cvna4E1EsOhHNVW21zr4rogiMJWZGALqONcn3hb6m0llrbmjea9G0ECnoO0kCKQoSu5JJQGkNIJ95YfxDP/a1Rw9PvR+0M9EHAGi9J9QhsMTAItrgMHTC2Ha4d0stls1b312eX84jcx99URVDL8Hrza1CWNe18V2oato5gMvLi8lUx8CjcfX+u8/fefPct6IqAGu7lbm6HJjocnmOyoBCJHj8+Oxbf/peMTKnp8MffPsPuzb+7u9/cHbyfHNzs7AqsT85OfNdYa195dUXJrbY337wQ5/77MP3vvvGH79//lGvxE03ak72gw/fccXkK1/6/OGtvX5Y/f7v/iur6M7dfVsoAECBJDCE2IU+SRTFoCjH8+RrTQREJMdlI1LkvPVZsze0IWs1EBKCRjRaKUVK6et20+QdEoBcC4KBkXK063qBRBpVXjWtA76E1wfjhhEnwgACKLj+hYq0VkYpg2CMdggqd6dEGpUlZQEJCLTWedGVPWDUdUQiXktEiKjI9vDXaO5Nf0IZZs2e+XAdQQ7Xpw0AnNpQG+P/9f/075bVKSfBrm+Gq41phQTWgUK4uUe8ZwTyPgbPSikyOqWkkVJaa6WZebFYaK1DL03fF65YLnovKYkYG4rCAAsKzs6X//D//iutRyRYLAIRMUOIMMQ0qoxRoBGGNhILg04SFxf4Uz/zYwf39r3HYUgRcDbvCwcicbkcmMH3UtVKgKM3O7uj87N575Ox1cGdrde/ehCFn53B87MrNIPCri7d1dkCFAXELiJqYoGIiRPcOjz44a99cTRSxhQv3nuwas7v3N09PNydTGm+OPdhsXNn//j4ne++8cZ/+v/8V390vPidD05PL7phdTUqq7u370xG++ezK+/D7LIB4N2dnaJK4+m+BgCgliX0+Ojo0Wq1GlKTu0aAG9U5CAQAFlFKVaSVUg5yhJxSjJaxIDMyqnJ2pLBwurjZnpMYjU6RU0obXRpdKu0SIwCltbyYBDA7kyi9liW5cqSUS9fRYSgMKYIkjiGfzsylIrSKnDGlUg5RWWvLelSNNpUdk5mI1qKIichYYUAmpUyKDJKzSDiro6xx+alwzmmVA2tCjB4ASBIDAHBCBGRAzm5icrOQUIyI8uDF13/uJ7+kCVXpKEBKqSjIGI0IwUuWaOXGPC8/rNYaCQGKokg+Zi02XC9/sz1kbpV88jFAUTpjlXASkCR1AtV2g9ElEDGgCCgCpURZrbQmo4xR1qphCNbAaKL+5f/nm9/79nlRFJwkRTSkhpaNsYJinSAmjiLRGRcuzlfb2/vTzZ35VTu03fvvPTo6C5WuLTkGen7WLVYiCJdnKQa0uohehyGu5n5coFOLP/7jt5U044l59uzp7VsvnZycTLfM7u64byIkd7Bz8Dv/5s9+89e+/+EskdEbO9PlctnO/XSzOHo260LzwoP7R0fP7xzuHZ19dHx8VNhNErdZEiligDjw7PyyXTUpJYKMBeI6pAAlIx6ICICAWdsJwggA2lllDSgCQkbIXTsBgjCwCDJDItKKHCgiYxVlTVx2ZoT8MNA6KMyQ0qTNjSFoPgZpbY5MiCpbSKz36euE7bVuTimFcp2wSUCABJTb2/yWNcoikoPhsuI597W5hOWamqukUkqLJBItzCl5vI5/zOqTfBd0aYEixebh3/zr/72r+f/1G7/5to1qdbUCDcMwCIFGDCHECEQQAlhHRDSEoDQOPo1GGhGUoRAHROW9t460oaZLRH1R6NAPpbOhG4YeCCAB+NASCDAuho40tA1rBVpDWbmLy65wuvVJATBBad3Y8POnjbP6hZfh5LztOs4GQrYEUgGj8yEpLW2TPvMDn0EZrLl6/PCkqC9jIDKDk2Jvz1TFeOjPuy61g5luhhRxY2fj6PSi950xsLN5cH55vLkx7a6gWbU/8fUXFOo3/vyt7Z3NF168Pd0sY/84RfP0yceXZdq7fWc6Kr//mx9FL/NF04Ww6ezl+XB+cvXn3/091PozL7/y7T//TVL80z/1Vwnq88tnP/b6i7/2Rx8S4Iqp62V2dYpWowgICAKDIDMpIWU4kVaESIhahLOBPQOQcCRGxCgICbTRAl7QMAelVCKN6x21RkQCTNlMPs8/QGvgUBX5CGpFCYNVHPyQcX5aG4kZpUg4+d7HGAWiMIpEIvY+ed+zxDUfHhWRisnnyBgAkRQTR2YwpFBRXtb4MOS0RQFKERAxq/xSQqWUAApfW9srhQCcXRuyluDm0WGC4Jm0LscbP/qFlw9rq50uCpebSedcZsZold1Q18rXlBIggspRvjaEMJlMcttgjEGEKGCdEUm+l8pR6cyoshrQgSK0koAT7O3XidFqbQhtYZDFaGx9RFKENtMQx5ViECRpljD0yaABkKJQKaKw7Yeh7+N4tPn51++dnn/89MlHAP7e/Wm/qPYPps4WxoXlfPXs6DkjjMrNewe1FX24t3N2efHivc3xSAnqIV4YA0j+R378cy/cmewd7t2/u1EWk9nVGRGfnS5EUKtyfu7DWfntjwbdXEXUItj4sFNNV4twcrSqal1WpjL1Bx98tLm5+cLt10hMVRXG1LcPdyoLBmDAvNrxpNeS9jyq3+CIImv60qf27wpRJVaEBaEhVQjaJITgMnrKoHNod05XRiJBla9RrbW1RaZfIKrrw7qWf/C1I7jgJ0b3N1dr/q8879+UWCJK17kL696AY0ohRZ84rkmAzKHvmHnwfU6YTTykFNbr1mtbvJsmk1ACxxh9L2kQSPkXxJSdP2KMmEQgSuAI5de+9tf+9i/9qNOQes8JupZFUlGSUpBdOYkgxtS2fYyslFIgTdtqpRJD265IJUQQRu/T5khzTM1KOAGmuLlvNsdxw0hpzfaeQQAgAd9sT4FjNCUJx671LEKATqHW0WgIUapN+aGv3Fusoo+p72WQoBlCmwCkHG2++NKtzfHmbDZ/+ugsDrxaCcTy7Kzpo3/reyfR27KYTMfVRkWxEx+6q9lVXdenp+f3bpWXZ3M/yLjC2Tz8xR/7ocdHzTtvvX950XzzD9753htPf+Knv3KwO3329MnH7z09Pr4UY9963PzW+7Nv/vnHb5/qL9/ZKoEVm+erq6//xJevZhckMXCYXT7qlrOjp0cH+/eWTZNPydbO5mdf2I4o0culH57PL7phkZslBsBsNS+EYDJFQ60TFyjLJDRl4oZWyjBHpMQKAUkZjcaRtUrrDNysTzZJIinLkpRWawmoVWRyIgJc50/nE5NSkhTzqUUgDRQGn1IIcej7PiYfo/fe932bcwldYXJCUuLA6zfI8kkRBE7e9977rm+Hoev7dvDtcrmA6Dn0g/cSooiE6HN2KAAQcpI4SAzA4eYR+ZQOH1h83pSWyrAZ3bt16NSARiI6zdaUERHzTZRNghAw+DXp31obAlyDXhqAEQGQFUBRWAAwBKNRKSSzq9aVDEgl4agwdW12NnT01csP9urKSkxb25PCGWCoS5tVNaAERW7tT52qNzddAE5ExtpEEjSMN8YppQ/fPe6b2cbIkPKihp1dp8ww9KFZdds7oyEuBt8OvedYxj5h8puT+upqOfQ8u+xGY8OBFegNq//8jfe29tz332kEAUB/9gu3nj46K2sqzAiJXrz/yhtvnJ0z9EilcR9dBLc864FBB23cv/zt7yrN81PwTVBQpSRN0w2x39ycZiY4KXN4a8coAASJpmtak2sYfBILm8k0+Wh+GtfEaxOvPPkSEeT3EYQwt3FEmhmYIcs8AACQQBuyjrQjnaUjn4JxSBCFGRCIOeajlmcaQMkNa4xRKCQJjH5IcxafR/vrVjXbIIS1h9S1WCWlNMSQ1gARtG07DB3muBLQ3oec+XZDgiYi8jH0fmj7ph98HHrv+5QCUgIWYCYB5LxMiz4OidvPf+7H/95//8cPdpRwxMJ3DQy9KCRNSgR8SCzZA9JIAkIY1+Uw9IUzIQSWtLm52fe9Z/AAIabI0PshRA6tfeXWBAL3/XB+1uiCukVchfbbf3rScyRnmsUSCCYbqu9DiqQNsMDOLjx7eHLVNc+Phqsr1TO03h8c7I9G45Pz5dXlBRAzAyaKXeoXpm3h0ceryUblXLlc+K6BsiwnNY3G3pTQeDi7aBSFUaljgKEXBOhWPlGaLxdxkVJoN8YK+PI7f/beN77xpnjnV8/np6vf+oM/f/vyFNBGHNrUPF3NAN0hwLaYV287RKwt37q/gRFu3dm6e29/Z+vwvXc/UEr3frDWKuVe++yD1x/sk8DqKpycnIFfI+TZ6SBftTdo/M1tC5+KhEPEzJkHFFIqBwQYW5AyCEaR06oAoJs8OFRGmYqUs7a4JjLTNYwTmZNwGHyLqBCUUkprK5L6vs3lM/mhW7QQWAkYAE1i9RpIEpFhGIahi9Ezs0ayas23TyBAkLGFrmuGYej6ZtVcAEYASCnmPhMRr6cuoMjRxz6k4GPg5Ak4Z+0xMwGSQkKlyQikyJEQIvrPPHj9l37hFfFrZD74vArL/ywUQiJl/BAEkoi0XXczv8NN2wAqpKS1juvWWJ2e+M1xqa0lkHq0cXo6oAEfgUG1PSuFywUnSG2bnLORIxGmqFD0com/9ztPlNEJUtIw3d86ny/Or5YGoWmlMKaqi/mqE4TgoVlGVLBsu+WV9K2M6tHpUStqWFyqtlGozK37RdsoYRiNcDyySBRTGlhMaRMpJdDOYXu6bVXx4kuEYIIftUNxGgAAMMUUDQBotI98MIiVhPkqgOiuTyKr0Zi/9kM/d7V4Pl/MBNdxFTkeUqH6zMt3DEASWK0aDZ80fPgJPi2fPpo3h/Wa55E5y2qN4Kyn8ryIQhFgFkT81GxOSKSUzuXzZuT4VKO5vuuNKRGVMNw4fWZFKGLDsgxhllJjtckiqrwvjdGH6GOMa0vkJBozvTqpG5EJCUMiAsIkaUAKITY5hCmEIZMyAJm65WkzP+6XF6G96tpFGAa4lg7mg6wIiUiB1TpGESG3dfuFf+fr/+7/6e9/4aU75WBAFTqihBQUYM5FjjGkhCHEIQRrKfnEzAo500eMMTEkES6cLSxtjkdkUZd23l1ubQZN6uT4rCqRSrCEHlJpYHGZqik6W3ECkGF3W3M0rkohxp17uLkFCqFN8ML21uLk0vdeIxilrEYGnM8GSRqV6yFYCwRKQ0F6EIghDAJh0VoselcFpeOjjyNYuGpDt9TPn68EkQk2xxvhanDKTzYLXVGAGfHCsX3nvZP3j+HN+XIQ48QkjII9MgXwswbmiLv7m9tb0LV+XGx89bWDv/e/+Q9+/1u/zNH9wi/+W3du3+cE2QQZVDRF+ZlX9l56cBgizBcLzInonB3d1mdxvStn/hQktF6FXN+JlK1j8jisdWFNgaCMsca4G2/l9XFUCghFI6K6Zo1AHpLyFwMgFCqK4hrh0ogYQgohdF3nhx7EKDLW1NaMFSIBkmQk5zqzi66TQxDzipuZrdXaqBijc7Yo3WSjnm6OjWWlemViHnyVQh+6GENKkULXxuHK95e+u0JUAglAsShABgACvaZdISE6LQmiN2BTab74yk/9D/+dL7+0YyCIY+QBIjDFZJCVg5hEaYWAfcfOGY00JBl6D8hGO0DSUUjFPnLHOvTh4sqHCGMrrgAfwZAAlG1Ei4ioWFKzkGEIZW2d0V2IWnutXIqpbzkkCZ4qgscX55osciq0ipi00ymlogAqQAZxZPsmJfanl92kHlldLFahCSQqiBr1gYZBkU3M2phqiGE6nWigyaYtCxwbfO0zh/uTcZ1iPbJ3bm9XI0yueOd0RQAWQiVhS2DKUAEXogOmnuHbRzNsR/cOa9Hzzz3YffDqX3jzT+cP7r8wDGv43VptjDFktEKti9df3cqX3LILIfZ5AsiDRrbggrUAPb+RiGQvDBHMZkYAiATqWrCQp34iXEtCQOWsuswRIUAt/38zOxARoUVE0Br1GjFQZPNRAxVyZgiS0gattUqRdUiGUJF2hTFOrsPAFaC2Do0WpRmQmZ1zmc7nnAEkkE5TNKhLV1nUtRqPJmVRaw1oSBFES6JT7GIYYoxUYeLBacUyKE7AJmoEpSihUEzcEQCQEeIEqRhPbT352YN7L2698n/5tV/51d++YpeYUSdhVCYkQUo9F06hjsqaMMTa6IHQWj30cTyx1sBq6Y0FLUIA7PH4mDenxbPLRGCaJvVtBwjaAKJMJoXve/YBLQ6RtHaQfFgN9+6VzcrPG0qWUwMOdAIPSnXM45GalshoS07DysNErVZqc7uYXfXaqnbw2nFcwngLe5ary5U1lXWEiE0bfBxqU8Sh3d4ZnZ4tbr3SnScpVCq4/ZEfv/v86cnVBf/xm22rlUAqCSYJSgWIJMmOoB84DgAeeFPB+8+vDmtQl/TXf+avGNrau3V7NNkTBGNV3/f5SiEiAVKgX//8Z58+vdoc9RH90Ieqshm7kTXbKAHg9QiPLEOKQbLLYAqEBkCLRERSVGQ5YS6GDIKEAAhCmEwMkZQhCrw+lSDXUTI3WDoRqSSkTIpBKQJIgNkK2aeUyGhndKHHzhpl1sIPRlKEzHCt+QzMjASSCx2AlvW3yJhsxbWhXWOCVYSQdGF0CCH1ThWs/RD7wa8+8cNdS6KMIQKRABhBEuWIO4XX6hMAISTS1sYoztoA1e1XP/83/9qP/Hf/W9sbBUEgXRIAeAWkIEaJMZtPJBFBFuecsTpxcAUBQAzsjAL0pdPWiUTFqS8M2/wAI4AAiB4GbtseGErLAglItBEAKAts237o02jiVl0qrQXgzC1zRqoN8T7NZ+H4Mk4KSGdpqqIJfZmgsuriwmtV7OxscYi3b0+rCgR6H9uqqkejUVngIvWIRmJrFL/2+YOd3akzQ0y0PSlG5cEbb688SkyxArVJGgm0s1GYobcKplZvIYxIjwsgEXD4sz+2e8mOqnEQKOoNjilvUPI1zcwirJGUxq//8JdvHx40TXuzcL65lPM2XK5TBmOMMYUQ1pQOkbw2/MTd7uYTP9mdXyOpue9cX+vyiZn3uk+AdDPUI2K+dq+nMaWUcs5lmafWVimTAEFpRfqGCpw/MvvtKGWylWz+4Hx8EZUxxmqDjChApNajucQMgXsfhH2MvTa6yJ11WdTOlvmFJYnA6JIzKICgUFtbMUcwlKKOaVCl7pOHkarMrc+W//YrL//gz//E9+bz+f/yP/zNi4gBVOSECNklOsZIoEKIIUUHhUaIPiBiXdeJ/WC6DdC7+3F56W+/RHcObfekazw50ppiTLEsqe/ZFUCkUJJzerUcDEqMwAyDh0WzYoZqJH0v2GqjoyK4OOXY8+v36EGBJcBHA8yRf/DW9pONi9NLfx70+UmLOiHW7751Nd10F+esGJfLZduFqtT392LT8sml+ss/uvPeH8x/7i9tbu/4H/6LP/B//A+/cWsL6xKbBsal67vQAW8wqCFualWo1AQVfNytqJa4c+fwcjmfP2//R/+THyn3vgSWbt3dV6YK7bKqqqH3eXEikDSRCCiEvb1qWn25bZuiXGlDhav5kxwWBoAcTQQgIJSzYPoQrCucY2ZRWiMBp5h5cTeoe4YCiYWMAQDvB7jeiCYSA/Tp8hnCEGPglIzSWcatCGJMSimtx1oNgEyoM0MuSqys5kTZxFkrhaBYr/NnmSORztgTXceFGTKJIwlrU4WYhJlEI5EhBqMhpS4uQ+w5aQDQymhUhIjaOhRhjihKUlZOM0pCouuvjkDK2kIx+BC1sTEGBQPCUJrt2/deu7UK/7O/+53/7L/sPp6BBkEUpUgkkYBP3hjDKWqtA4BzZUqh7/uUGAfc0aGooa5xY3Pv+PTYaAUqGU0S0DhBAmOwHmmthEh3jXcFKNbWqsEP2zvVyqdCD20bjNOoxFpsW0GECPTyobvNQRL52/LwPYJu8SN37PcTifcDGDEmeJlMJiGstFGIyfukNHRdNKPy1q3pffJ3pvee99/96Puj76+efeO3/w+//I9/fZxsf9nfHvMgQZE0UQBAG96slUZl+iQGbt2Zjoy/aE5our0DKS3GXCsAJ8IhBOec1jZpyfd73kMmAcrIpTVD6HNpJMJstr0eXDChrFHPlJIkTimk4JPRIZDSlG9VRC0iCCDCiGtpSB621q0CfpK2IdfRmvl0xuS9HwQSXX88CApwZgADkNZJICmypBWIRsGUIggCZAtIFPE3JfmaRbV+uvKclAki+ZFQqEEiCAGL1U4wBd93Q0hR4uDJaK2rqWFBFCGkGCBAwA6EIEaGpLHUXFmrENFailH5FAy6wjoAKB2lKKNxi/1AtO1t94t//R/s3/nnv/dHb/wX//TMGAXAAGSYV0KOiIR8l5IYWCtdyDpBqqhuN2jSyqJbNTsHVZta5nK5GFqRMRmG4AqcjN3FrBGiqlRPT1JNUYRVoTS04pUCxQbDPDJCrQ04ZXA49bIzAmv2nz989uBg+gfvrnZ37YONqXr5fHdqPj6Ox1EM8tGVNpqnWy4uhoFrW6SqGF3OZq++Wv367x2tzuTzn9t7+Pbp//zv/9LDU/WHf/atV/Zf39ytNqzmIY72x8NKeX/lnDhtnMLtA7tRVvVGjV5++B5Ltfobf+Uv9XdeSTy9Ont/c2t/NpttTLeUMpMNPfRhzbpIIBIJLYpcrnxR6MKtjNVlWROomDijfqi0UkBE0QciipzSapEkiSIhJUwsgRmN0oIEKNluhFMCIhZESTEN2ggwc5JPLvGYdZ8hJR9jikMvIqRRg+UkRBFZWWUBOBIpVWazCAQlHDkyokrcZ2YTImidd/qM12lxCJ4oM6NLrVB08KH3qQ2JJSZLEELUzmpFyz62zSCsu2Wb+cxUWmeMsdo5bW7qPJIkDiiQ7Ua87zP5Dtd9zHrblFJiiUSgDRljrBkJpC998Wd+9Me+/NM/bc2msIhSIkDE4v2gkbQhrUlrXVWV9wEAxHPtbIKhKq33PvmhHtnZvFMKNWJoA4kBFoEIAOMKm2UcOSmnJkRlC+4aGE/FWEAfGUBrYIYkwRjlEK3pS1e0c7JmeWeKLN2yvbqz/4Lvh60teun+9HB/9LWX6rEUw6DITDbG6Nve6VhW8Jvf+nC3JBcuF2cnlUqr81kF8vDJk5/5az81O2/7005Z068uR5O2cFQ5O/SdsI+Bd7b3J/V0b+t+36y+8vnR86Fxet85/NM3v01Gk1ZE1K6WQ9cTESBzCoSiFPjQx+hj5MVilU2OYowx0zEVkVZ5Lw+fSsTKXy2lFMKQfTcAgDmyxPUZFCHKiYYhxyFzuh6DlBJY04w+gbHSWp2Mci2xR2Jk1ArU2gRu3aFiTCkkHgbfMfP19CaZ/nzjqEO05psCUH4ZvI4XM0SaE3gfvffZs8n7GFMKIQmpGCB40VmjhOtMCUgkIYr4HkEl7pUVa0Usg+ebhp0TEzEiIEWFKCBMAko0gaJKW/XDX/2lr37pF/7RL/+Df/KPF0UtA9A4hR5VitFyAuQQBh9SCFCPlPY8NS7G+eUFjCy1nQoMm1PddwJRtNKYwmRcdk3a3tKzVdyYEIh+fOynUzm/oJdfsBuKli0wpn4IGyhlpeZtMJu6W7JRm240qqYwDJuvvTBEkenuAUd5cM+8+0FYNt3nv1idXl781U1z/95eVZZ/8sZs87Pp61+9v+wuh6vm+49bTur4Kt3a7P/Ff/XbP/0//nvbc/MP/8l//vd/9sf71I5hR03K5aq7NMu+97tTu1GZl155VQW+tXdrgOHDh+ePvn/5M69/vXdb09D92n/+z9H2TquTs/PdrU2jrA+JTARMKXFMHiD6JIqLK5+K8pw0VWVdV5tAQKgTs1IIQAQgiBo0JwdFzb5lSJQGDSUIsAhjQhRCFqEYE7MQEbBXGENMLAmBRGJW0SvEJMzXVk6+75AEQbKWDRVFzgIoUTk0g9cXtO/axD6EgChOja7rsUH0eUEKAFrZGJOICOfDIyyBmfu+9b2PIcUoCOhQ+eg5Sd9wNyQQpcjokghTdm2gABARWa3ZhKQtGc3MKXAIIQ7ryLqb9VpKibOvvyQRFFLKOGdrRiC02mlX17/49V/4yZ9Q1oQYU0zIzMKYkhCuU6DLkpi5aXpgHo9HqxX0rVJKhSEiJCJIAJ4TgW0Wne+9A40KFKTAUKDURRm8tH1swzB0Q6EVAAwelI4WTezjg319er4s1e7tWwedn1VliVivvC+KYmtjcv++xZD6ZfPqvi506NLT0M9eveX3JmboQVX3D++8vr0xqW1Vu7Cz77Twpp62Tj9/8sHZ+0/2Rzt3b9062N25u7Oxvb3Z923iUI3qvh2KwqJWL77+gyfP69lcPnr3Q3Tl+VV49Pzt2exCRLITSS5jRmthHIYhpZRDWVNIiGo+n7dtF3x3cxFnQGetalSktVHKkLakC9R54c5ZwQEAGZhKHBKH/x9bfxqtaXadh2F7OOe87/tNd6q5qrt6ntBozADBAZxEGhwiWbJkRoOdZcWO44jKSuwkSrxiO1n548iWY8VKVuwoWpZlmTIjiiIlkqIJkIQAkpiJBhroubu65rrzN73DOWfvnR/nu9Vwlu/qP33r3qrv3u+8++z97Gcoc7+ZpDSoRJOsEmnjUSA5Dmo55UFzkpweJsCecU+BmYOrGF1OUVJkBFCTlEVExc6qIxRhMBgjolpGLUxTKASXs6ZTEHET4WWSc445ppSSaE7SxxSTKADZRvoLoM652szYbX4wb+ScFWsUhHI9F10+AMTSMNFZh14mxOCCYQAnKkK+VknszIBf+MhP/WJ94Q+++dt/57/5zr0BTDVUfhg6cnXXDT6UnlojQQZt19mD7w3YhkmDQyYwxk48YzfEqsJKq6HvLo8RzMuKZg2v5h0AicKTVyd3HyzUMiMMQKet7m3zYkWXJnx/PuzP38uAd/fF1ccEfOHiBV6vTg+HK+f23ItH9+5VWJ3fvnjaGBwNR5I8Qv7KH3/7Ux//4OzaBz/2onzuD1++tHutmvrH1A4Pv0z1Cztc/6ff/fYv/9t/dVRVVT3Cc9vu/mHFyKPqIy++tLh7H8n81oW/9V9//mQ/vvj407vjj/Nhnj11aWtrC0RPj09wjwFUSZswil1mZGYnkguuxkxRsnbp4MHh+Z1mNN7epL8BgoEaEJEhA1nwjQDWWIllRkI0FUUXsLRqYIgZwIBMsqJqHNpCU2f2oNkMTbKZ5JjKza6aDcQUQzMqF33pHwpIpZqcoxQzETlGMCcGHrwZMnkzZkZNQ8przQMBFi8lM0P0iAqYVdV0U+PaodU0qBggnixaRRFJbS+G5pICaF2HpmmI0BVBFrFnV/nQeF87X/lQs/chFPvnDVoBZ4ZmcMayYWYwMnAGhDgSa8mNDBgs9GqXLn3gox98bneivlYHARF8cAaS88YrlYjMETpu28E01WPX96DZskjOceS5JiLmnN0Q+yvX6xmOzRLEDtiq4Nhp10ofu5HHypQYEuhqbef2qgh0HKEXPFivjhZabc1u3Lb56XB0kh4c360mSqYeaFTNbXlntVi+9e764EbtyLHTu7fte6+9tj659//+rZf/7h+uq91JXY0mV7a+9we/bd1iUEp2inmoDfeuXhWu96Y7Tz7+dDPZOzo9HTcTJr+9d+krX/3ieJaafGHr2lW/PaHRuZQGSZmZY4xRFACKCbWZIcLZJrAuZCIwWq/Xfd/23XqjCjrbyxeOppmxLy6zwblQOjw6yw8ungMiIhvPjzzETnJUERXRMnZt8t1SyjHnqJqJYWNRa0BEOeeUBtUs1qfclfZxozzTTFTSfrmAEgAgYlnalHsRMRGDTQkrm/0yt5xdpOX6LSojHVLsY05JhhgNy7zP7ExyS4hkVsROo1BPXFX7ZuSrSainvhpzmLh6Uo9mREQUCGvvxo6b8lsofKqUUVUdj4Em3u0qRUBB0BzFjfTa5R/+q//Gp0gRfU4pV77qujibVFniaIKEVVprQ/6Ry9cy0enxIM56cipYBxaVQTMRZUkQ8M3X5XsPuvmaJ+d5NPYqbAbrhRttPxrVxuxGlQHAacL7B6uf+NCFPg4nyX/uy/fOXzl/fJpfepIfu771B394cmhxPH7k9vFJu+p/+oc+8+yl6x/78A/9+A++ePWp6vqjF3an5y4/6tNk76/89T88PcYffJJ+47976+//yre3xuHm79/1IwWcV4vhz/71v5X13hd++7dkOj7/0rOPXHr0E08/6WIcT6ffuH387/31//Onrpy7dM6HC7xyD2qfVdbHp3cMIaPNF0exa5eLtYI57xG5qkYA7LiSXKhuuh5svu6Pl+vYnebUlRzlYuMqkhiJvVfCOlSOPQIjq4DhWb58mXhSjibZUtYcQQWSkAEZFP8jzTENbde13XrV933xwGGqAGDZnSwWp10/z9IbCAIRY13XG697RDMUETR2LjjnDJLKsls9WK2XsV323aIdltL3arEQQM9YJggAKQ8FNB2yCFIE7VOKMbV9CiE48MiOHZomh0SAjOQQPCKzC8SeyRd7aSbPzAzs0HnyJR7KuUBckfPEzvmAQIZGBAoCrjcEtBHZDIFz7pOYOffolRdGIyPQFM1xCIyKhXVvIpEJujQoMAE+ONJRcDGmZJZUGEEBYs7s/XqNJ0sU8OsomtQzdUNkDznbYjlsbdVIueGi4KHVALM9P5pNt7amQ8Iv/vHb5x7be/WdLNKt+gHDeHvr0nLt6un2fDU0M4FBZls7Yze7On3qwqWnn350cufufgv5mSfW/VoeuVJ/4Hn+rd/+8gnApI6UTyVyf7o8V43v7b/1B7/2j+JiuVx1h4tUTff+wa//1s13v/4DF6tf/Nd/7t/43/yv+dGPZDEZzxgnnC+2q+74cH8TJQNQyDtIZGf5BA91OSIpi6xWbduuY+pyzgpgWARjwoDlzS7TPREjMuKZA16RYiKY5JQHlcFERaxw440QyJELipCtLMlzKZ8AapAMEpL6wJ6paMCcc6ZQ+NFFd188VLxnRBNJmocsbZZu6FcxxkIXsTNelVnKEh+ubcujVv43yvthtUTERHImXypYgSNXn/GyWACAAdUc8llvTnbG8mIsyWXIVU1SKWiOySMpITmPxTXdi2inkiADe0ZiZ7sXHvv0D730m1965SjFvGznhJZS8p7jIJNRNXOeXLXoDnKUeaxqjtCM2iF1Q6orErAJebGcoo4ncTGHcxd5e1rdOmnHE9/3KZF+45u39/ZqQDnX8PHSWuY22Te/ff+dO8JxfX57JG7y3/7+rYuT5ntfS43nL//z/omfujvZvnxz/+2qur2zd24qyy+98vLQiwf6j//pDbHAa3xyhnffsuuP8bNPzh7ZeyqH6m/9zW89+dI/+fSf+JHah/n9d85tb/1nf/C1d7765i//h//+8888UuX8pa9/4zMf/eDO9sefe+6R4f7xlT/5p2wyDXgJ//kvnZx77P/w1/4f/8f/y5+bzXYLGu69R2SATI4rHwyR1BtkR76gnus4vPnGja1R3Uy3qjCpqhkiSkpUPJqAEFHNyLHTkM5kiSZqquRJcxI5jX1HaqaeKbBnZE+hcq4iQkZC6hnQNDJ5MPG+QmAATTlmEdCUMwKYAw4h9ENXBCjFUjRGQTQkQEQZVn1cd21MKeacQ10BqyF03bpMSMU6T6QMXmpmhXifs09pqGHTmYQQFNDnpNCVrYJD5LLJICIxBQAx4zN9JpyxAgEATIGQELMW/zVgZiYuG10iMsyEDNAY1Kot2qACQJYRP/rha3/0neNNmi5RViWivk+KcGWHKyZV2d5iObbV2lQGjRICSafE4CinQUF5vRZCXg/y7u22qTEPWFc4dDZEbNfx/G4zXw9qCjr0CmmQAOHOcX7hyV2KxwouJDukvBTYX4mM6Z3X3t0J/q27d5uDB5O9na6b3enrt7743oOlXoP+6Ser7YtQDVCJtvO+r5b17uhf+henv/dr/92nfuwTC784fXDnyX/pZ1f7R9d+5OOP/dq1Dzx9/vxzP/KBj//Q3Te+eWHvkb1Hnxqenw4rHDmF/u3l+sG9bv/WW/dO5gsAtzebnd2SRiQion7DB3HeqfQPFy3L1XrddYX829imWCBuXJcQQR/GHJXoArNgrAQGqpbj0ObYoyKCGBv7MfvALhAzkWNnoom8CzZGREZyhMzeQNTEUMvKnp1DgJTS2Rp9Q5hHNEArXPshJ01adMxApIjkKmSXhy6l5INDQpWNUBMIAc25oJqdc2VugzMidl3VZlll8xm3mVTMzBQRVNQQiqxTRIjMaKMNRWZQUxVkQhWnqOwUEUxVBKH434IhusBIU9WxxVY0Bdn6zKd/5nNf+NYrbwVlFy1VRGLineu74YMfGy1PhnaQ7T3obsR378CzT1GzhB4VCXxFiEYCCmIA45pzjzEpTmg68qeHMpnh0LFSPjnpAkIDYABbrp5eGH3wXPXN1+7dev3u7gX5S/+jjxzdf8u/Ze+eDM9NJv/JL71XS95nvjybLOfLC9srnNNtd/LDj/HzY3328Wbv0XDyYPHEM1fuv3Gv6w+gvvz4tWvH9/f5ykk+uLNa3ZGJ3Hzzu4++sNfdefPn/s2/Rjkuzl089/F/4Vr814bJePXy53cf+cDxVz9/+tTF+ee/d3v1h4/+zP/1Y0+PDv6Dvz2d9vN2deHCBQUyhbbtmVlkXfSQdpZlmKIhggm89s7bOzu7O7Ol6TkFK++FgoGpiAIAOkeiiAZIxKiiyNT3rcShX7cmNvRdFWrnYTw+T2HEnhAZlKvKGShCZtegaSB0TAqGLmMUn8sFzUyBCJSFIJR9zYYegGeGTUmGoRcRRBqNRkajUE1DqFNcGUCSJH323hdWSmlgvPdMrgxwAHUpn5tLP/YewMxiikkiPZzHVUvmDvBGVadFXV1aWzMDVcSNAhWZzBERgimAEm+WFiWZz8yUAQnQN8BN9jDbffJjHz4/cARr1Y3MjLwzzUhwZffxwogZN1IpmcGJWjLx2bLCuoVla85jTuDIicYUwY2oGbk2reuZH9rchIwD9h0kB7UDVljkftzUT169+MTlMXi9tDfrs7jp7vkrux+8OM0Ut0N/CLDHiOsuqj+/i7ydU0pG9Jkfv3bpknMZ6zGeLHyYhlDVt268t+oWFy9fn+HFr373C8v9Ozsrm4ziYX9sp/P47S8/0GGUelrur9b3J91y9dpX073bJ+9+a3KyuvSBp1/8y7/09d/8m3/wm//1z332pyFLl2lQZaQEIghDkoKN9CkOUYEYQJ1XAuyynCwkDzGdKcY2wPOZm82Gk0HIrva+0VCjpwxGRqI9YBz6JQKVtQ0wMCKir8IYyatg5bcQZuArqqaZxwnrDBXiCHxjYQyh9qFxXKtVnraMakWHFIgrBI/gTCEnAQBj7+pJGE19vTsej4NjR+xd48yBUjmaTTMux4zREXoET+idC0SBuSr2TIhYsRs0Shwgmfjmfbo/AEDeHK8C3wORmTKhZnlY2wHAI6EB2EYQY5uzXch7gKoIpCYhBCAwdozO8fhP/ql/6x//s//gaOUdrxlx3ZtD2j/QRyG8ZR2xMtQRhpXy5T7PtjkNNN7C/cNkRqenOhlTzhmQxlNRsOUqE1C36H0VuhhpBMzkVHfOAR7RSdJnPvD0F7/wh5/+2Ae/8Aev9HF1/OD0zu0HP/qTP3jrzTffeP22OPzzP/Opr//Rd7NLLzb2yk1bxuFPfmTc1LPbtx4gZR/o8EAOJu/uTMARNDtbX/vmNwi2L1579Ot/fHB48Z3+9Gs/+KOfnu2kxf3v6s03A6z72Vjfebf58f/x0fLWPl5+53tf//at/qXZLZw89jE4fPyDP7V+8PK/+ud/5hf/vd/fzaIpu2Zipl0chhQ1lw0wZTNErIN3jqaj2YKOFqcHh4eHW1vNzs7V0MxUFYAQNnaeJdCyMDu9AaRs5AvxE0kMPaCwYyBjRrRURBcxRiICBERAYoB6c8kCqApkCjACQJSkuRcwJ2JgBsbokMhEfFXHSOzqkUfNKfhJzpnIETskLXAkKXHwNSEzO7cBmzYbWiJ1auZyJjDMSejMQtLUclLHlZo5Du8T+Oz73M7Lq92wsnEjwtOHdn5Somffb30AFBDUFI0QmAihwFkAyEDgBeTcuet753iRnGSXsUVnrDhiFjDnXM1R1wkAesB+BdSYaEJF52HdaQiQk6kieUUCUkcu16GS2BnG0ZgcMZgqQUXAwaaC//l/9YVPPY23Dx6cvzgKDpfzxQdefPTg4HjdnqKOc9/+09/68rYHYZpH3RqNd7Z27jw4vXYx7O3t3d9/AOgQZL227Rn4eroYstckMR11/c7FJ9+8/b0Pf/hD+zfiUL1uuP3ut79xYb606eze3ePh4B/emx//2q/++odffP7TP/ojH/jxP3V7//Sf/OqvHLxx4yNPNqvFrWEOcC6aWZKiD0ZFSCLOFStgU0VVJcecPLMHgMOT02vDBc1JFYp0DtEBqG0ERuW9J2QK5qMIAjAHpsa7aDV4Ds459oFcEDAUIXSqaBtfUSjM5rP5GpCYwESyaTbTjFYVCR6RZQFAJAYAKtsdLUYitgm1QYZNWpcrLuO0OSpmZs65nPWM6MRmljM5F7yPoiZFNYTgyKkZcGQ29/55RKSNqaQiFnAezRT+h4Ra33eO4eEfqeYiOz77xQEQemJVdS4Ev/fcs1ffu3c4xEEBo+SK+NLInAsIhGinIoyQwZYtIGpTQ0rmHBEaOxw6m4yqNg5xCMyxqlk0EQF4NDVDj9hLop3zOCT0YF2PW9vVrdv3d3d3Qqi7YfX2W2/OZtcvXdk9uH/AzkYe89zvbMeoPNN1BLj+9OX+dLluF6oK0E+3qW5mi9P5MQ4++J0wu3w5fOkbN8L0emv1Mkxf/867H+C0DO1rc9r6xjsHAd5dtw3d/rEf/8mPffIHnn7pA7Pz1//u//3vjmepvX/n3LVHjnuH67uf+ckPvvv2jZxzVlFFVTPNDlnECs1TBc0MyZynKoyW69MH+8dxyFq8ijYEe0TcuAGe3fUEwOgJLaOBoDoee68I3qFjZvLeuSDIqpl4Y7wI//0PRERi0WwAQIKIUKJkhDMYIDCXBJyNcF5LxUMwAOcdIhI6VVUFIlKOYOQcMXkDUSnhypvNLVGxOyYRYUeWqaQaFc6oiHgfKlf9/yn6ysvUmIEIHWz42HTGNi2vqaz9yz+jYAy+CDg3eRSY1RJTY2YMJJpMiVmHBL/wp/7lr3/lPz4Cd3gCnt1hlP/if/kzOl+AH295OVku0QhQOmGO4lyovVsu25IWXjfQdUOYVqBDiiwi4y2PAQBMDbL1HiG2Ol/AiIGn3jJ+9dvdpz40vvHWYbvNFbvJaBLznXu3xucuNAeHfc1+MYJ1qj78wjN1TT0s7916d9K4GOH8+dHyCKm2tk8VhXUbJ773OzOt9/YuPDg4/NZ79/3B6R+d39r93v6y6xajy89kL93h6sVd/p2vfN1++/MXn33ilW++9q1vvXH+YnPt/HOf/NGf+Orv//b8zptPv4D/2T/48k8/sRevZBt672tVyDmRB6AgBiJDFWpTdsGR2WQyWXSTuwdHd4+On2xXWK/relIyLctBef/tAwJkBWQfKKuxOZqNOKCWIomqIlryvyRL7zwSOTPGTVXebKEQ0XmvqmSNFY28CWhCAgFzBlqgHsmF8uyCNxXiUaGiPrxpU0pAWNcj2ziIV9Ei2MYPf9OMMqsqouWch6EzM+bSETrmETI7CA6o0EMIAdKQcONzwptZRw3IkM8oXlRYsEZYnH0ADdQKRlH4JFr4qWePNRoiKBXjv6euPfXRl3Z/96vqXOtI7rb20gvPf/uPvghMhJgGMGAmTSqG0HY59lFzyV5XM/AVrNp0bloJxpx4uc6YgZmcV0CIvfqKAgKPXX+SyJmt4d3b3eOP7x4vUtstZ1vszXum2XS2tzv+wEsfXi3j3cMbhwerEE+PHyyaHeqHxACf+vQLv//5b5/c9M98pDlXb53sn+7tXv7WyzeffkGBR3dvnS77tLV7/WR10u5HHODo9M24Wn780z/+8ivvXTl/sZpWezsXTeCJRx+fXH70Rz75qa+/+jIsj4/mbzxlT33zq1/dvnqh7fvZZCxnTi/ZNOdcuRBCLdmUFQSJyHtm5ih5sV7FofMmhauGQGBnlIkN+Q0BGexMUO8dqCBWrE50EDNgY+az+1DAPECJaQWFoQQmbyaRvElcNFAwFe0d+qIcAcAyz2GhmhKYGQIBiJkCUDH0VBViM0NAJjJELrcrGBFZqZGlgsKGe5RU1eGGLue9BxVjAjOnhAQIRDEnBIlpAACibOIRAxGKGYgaUYE/iF02yWClyIsqEwGgqjAgOkcqGTcYsqoyu0wiamBJwvjf+V/8r77+x//+jVw1K/uHf+Nncw61USJHEupZUIgoKGAEsLPj1wNVIVVFt+B4vkYchq7PIBYCrZYyrmBUMxnmLN6DISnIiKPf4xm5/obdPob1yfr5F0ankeqJ79ddM+oPDk9mW9Xnf/c3BYUBtkZOetjeEjJ45Jknb77z3h++cvD51/zHHqu7B/zV/f3RlF555x3v+brgsqMrT+9Ux92t925vb5PC3nj3ytXpRfbu0ceuniyGFmRQGuIKPb599J6/88Z3fufvdJlGQf7yX/13p7Pd3/7cP76/WDy1u51S3FyFqlkkea2K/Bchq3KWqvZV1TRNU4Xx4cFy3c+r5UqNhcG72ghVlIGTdOWKR0SVDADIyIDOjTNkpQSKqIbgCmMypcRERfGsoswuZzLMgFY09cyoqgaGRKbmwZmoQ+xTqwYiWS2bmunGpoGIShpezoKoZ/0GZekds2Y9A6eyKSNJYR3AmZq0fBARuUC+yhJ9YAdomktBpfdbybNu0gwNsplXVecDFvlcaUm/LzAKzTxzMUBDpGwGqgSEm3YBEVHVTJSBDBkc72w98/M//dh3/z83fvozT3706R+/8c7LxBUiCsF0khHAwAApmaZo7WqIqq05ZkaWrssAELN4hnVfHj7IOSMTsjdJjFJVFUAfvAnoANlh2O+GT+yMTfzJwWIycdXI6sGPvTUX/KDAzOuT6BjGo/DRD3/kD7/2lTtH8J3v3p0TPPboVsjuIy9cP82w7m/Pl/HGOwdVoxd2PnL/7luTsZzf3V307eHRu5cuvKi5/fKXf9dktEorDM3r3717fm+7m594yO3yqJr4S489e2HL1Rcfe+uNXy4j7UNVe2mt7KzLMtNs5ohTNufcuB41lZ8vVm27mk7bLCMzNOudcyYgm4AEKYxgAAA1LZXKzDkXNxomeHggStnLOTJ7QFMTJFQ1kQ3RCM5weAMkAxUAhJwHFSEAFYlxKPuhgoEDwhklEMvtLTkV9gn7WhXMUpmkiyN+qaCb+1alWJeUKzp4T2iI6BTQnKpulKCFSqiqllNpJZix/Aw5RSICwixSpi8zRTNHJOkhrUmJHBITMAKiKRMbqog4IkegWUwSxRDFfubHfvrDT7391HOferA8Gk5v71pY74zquyf1yBxAJKeg8xU0Lo2CG9aUIQ+SVcEhIAKR8zWmPpkCet8OmbxUQceN6ztbr/qhhZ1d86xP7vCtXty4/uofHP/8z3zo/oNXhqN09eLzjPdEVrHvGX1WrBuvqotV/P0vfvN333DrbA3Ic1tbj16qf+LDP/23/qu/P94en9uRD35wZ34ctvdocbxer45iVx3ykboO3fjdN784m1zq1i0RtJ22gz56fefWjYPl6dyT/dzP/0QIzeHxYnnYjh95ctRs4bIYrGTvXRkLRFREhI2MzAARc87Jc3BhVI/H4/H8dDmfz3dmp9w0TT2VlMo7XJp+RAMzBEbDvEk8MpGESGCkpiJSzMOgECeGbM4V8ZDBhtmLiAqbFsI5R6qlkUC1mPphaCUJcEHEDdSYQVJ0zqlkBSyW+ETcd+ucunKoNhwXLK51G+ncJpkJhJEIwRFXVVOqnmNfVVVMSfrektDD5b2IMCKamCrI2VYXRDUbJNGhUPlVM6jiWSrU2VJ/g0+5h0Mh0VkYlW6EBJoVQSwOJuPdJx5/5qeYzqXYj7vpDECRMaXGzQIjAARVIgBC5w0pDxHMqiiQDZghBDcMaTKpiTBlXfcGiClDFhgygrmYIEXLWcZNxqhXfPoL/9rP/KPPvbw8djyh89sXh9gmpUEMXKxqaGMa1E57uH8ifbTJSCqi64/2MjT/+Hd/u5nZeFqL6cnBenCrg2X/vRtvvPChF5Ztt16He7dgfcJsbn0iQ0d39hduWrmxf+vN+4sHx49eOvfxj3xy/+4BqHbt/rnHnmhG7d6FRzyHQtp9+LaVxfRG1CBJRLKKmTlm7/2omdR1k7OaltR4Y2ak0g+UkiQx9ikPSdcGPeCg1iEJ4CaD5uEAtBliTExFRUyLQWIHOYFmLNCSqGYBRVDDje92KuR0PfNkLBZiD2dlkyy5lxxT7GLsAWAYupLEoJrPEo43rmPfz9gsl3vpPpkZCTb8PU+uAoPeldOJZpI3jGsAUDAAT6SGg2lGoHLIEJnp/QGoPA1qEVUMPaOxr8gFcIxZRQbVDECqmZlFYgg1SsLZtbVvTw7uvPbOGx+lgJXFeQzj6PyVR6rVq61473LSo2Osdysfsmd/2g6eiZCQckx9CLw47Z1D8kQikt1yJWmafQNDR66G1drNdvTaIxc63Bfv/9P/528hwOrC+X/lL/3pb/7xtx977gOvf/urIOOul/W6P+3p1l1dDmBMAFIHiII7YXZ7fndnsuvW4/3V0d1D9+GPPXHn1pvPPffRP/PnXvzSb7/52Z+/OJ3O7t053T+4f3h4WDcji/sTpFHdbM8a3mkef/rx1WIxO8/kR8nbn/nZP03+wo0/fm1vdqjOFaIic3hoGs/MyJRzBlXFDFDFGGvnQ11Nx1MZkmQzGRSMXSA2lQRFbsOYoqhqSsOGUV4GBjTauH6eiSCKLAIUTSCX9VUJ7k4VVTIokipiVY0JkRXE1AAk5SIETUPvmgYRicDO7O5Lse/a1caSKaXCxAMAsxg5mgmCV8si4l1lsHH+AjImdIbe+zpUQGi0ofGjGVQudSnmREkyIhWeFSJmUVNA0k24DmRW1Jhs6DQOqWuH9tSwVevL3+OQAVRARDuhrJbFYk4KltXMsoAOjJazBj+m4LPz4EIalkfL+f7JSsQmZlmB6gsmfeVDAKwgZ8JIAryejBukNKkJQYlzyckZeq2rwIyILAkMOdRG6pwQNt6YzUHOevNgvrsz7U77i02zNeGvvHX3l/7Zl//m3/vCaOvaQcc3H6zv3M8LbL53Uw8HGACSZnYw9Hx+Boe58wHMp5N2OFl7Rv/tr7z+5/78//Qv/sWfffvtB+/dfvnO/m0mPDo+uH371eOjA18Pbd9VtKPtMfTrPsWvffmbN+/ef+XlV4dF+Mrnf+OpZ39suv3shceuf/5L33z6xSdhg7aUM5PFZFNdTDeRrFHFNGoiAh8IakjE5mrPAUxQAMmbEmEDxoYgOYPEnHoEcaiWBx2SbNJkSoa7ZesZBEUZUVKvOUpqU25zjjm1poOZoChpLKdzw9NAIiLJGzleQdlVN8S88h8AxBhFLMsQUxdTl3I/pC7JoKAxr2Pq1IasnUHOcR3TMverPLQpr7KsDXrywM4bgBoEEgcAHh2xc4AIJmZEUHpzIFQl8gRAOcXi1xPjkNJSRIiD4bQKYyNBZEUpeduOSLMYJSMSHRAFAJBM1RTMOc45EzpTRrST+dEbb333zXfuf/ri5JFz9YXQYF5KTLOt6BaqgCPvuiirhefxsInLVVTdhEKMx03XrxAh534y5fW6NwPvbbUgoOgd55z7VVitu+kkXjw/mrj2dAEXrtaf+2df+xd+8Af/T3/jHz/52PTu4RwhNye5Yo6bzHJzCmwAFG7eiRdmO5/70r2rT/r798Knnp/9m3/lF69fuP7ST/yV3/kv//1/+iuff+xJ3L87n87yxQvnTk+P985NV4tU1ytyvu+sqtPTzz3RzPwff/3Vv/ipJ378Jz9+Z/llj4/cuXvjoy99QtneevO1krWKKKPRCA1yzhwCEYooqIFDVeu6gUf1KEz3thwCgyKaEhsQsiH5KqUBCcCUQHQDrmjKmxoGyW90pICSJMeYVZhZTUQ0xgimCEqI2Yy55AYQmH+Iw4sIkhSIoGmah/NxKcklp6HgRGayWi8lQ85RTZyj2tcaEzKmorgy9b5CNMuimsEASJRURHxgzhmpci4gChAJJNOeOJ9ZPgOWHVpRuDoXzuJIXGkUYowAqKoiqVgAlBe5sUkRAS3kK1VVRvv+Yf+hJ76IIXLf9+vV6f5qjZ3c7E+996MkCRSYggcHYIqNUw+YDUTAQNnZqCFELXromLqcwblqNJqs1+KY68plU1EAwj5lRRgopgHXp5IX/aipRzPc3+/3ZvDlP/xa40BWw86IZ2P03iuxbeIzkNAY6WTe9S18+9WTLtLO9sUPffDx+0eLv/v/+v/+8i/9sx95/tLf/ju/5K09fnD0W//086pyenz4kQ8/u//geL44On/hymg8A0x1tfXRj32AoHr2+acf3L39u7/zpZvv3K6dH41Gb7x+487tB+t1q1k0G9r7tobFx6Gs1wEAkFUhpZTUHPmctY9Djr1JLld5ITgDFFvZZJIIFDSDZkmDSZIcQTOopTSAZhIzSZpjOX+l8QU1RiouzA/7DTijHZV8edsE3ELxwi2n/+GOgByfjV8EoOwohDCux55dUdhxHpwlp5EtOpEAVCODGhoUJgeTJyLJ/RCXzpfc5Q2g5M5In06iGHEx0UckBEZE9l5zbzJUVZUjV6FGho2KzwiIymLTV43maFmBRVMiSogskhgN2RO5ElkOTH3f5hzfvXf35jsn99uTo2OVxy49bfZ5cjs1em9j9NHSbGxDZzyC1Vx9gBA4ZwFgU81iOQkzdu3QdwMhDIOE4IbBRrVUNaeIhDZ0GtF2Lvg1JB76poKdGVhojgCaBAPEdqW+qk+Gvs8QEMfBQkUTGp8sFtOtOmXLUDu/evlbhx9+Fh6/9EHQuyenX/6JH9lezOu9R55/6zvf/bl/8am+x63Z+Gt/9M6HPvns0dHJdGt2+t6tlNK5S3t37+/3w+IjH/3ocy8+/ZFPb1975rn10hLkJ5974vO/97lf+IVf+LVf/XVPPlfeBa8KOStWNAzDtB55DiEE0cFSVgF0RqTAftUlnp9k6UaTHTDnfAWYEZDUillIqQg5Z0nZGNkRqEEWMkvDWsSI4GEzSkShqhCRgNiHM8xLDCVLLtObajIQRPLea04ppVIsDSTnWFWVgiG5EGoicuxj6pi9A9ZsohERRYTriaYUKlYkICBgk+zIVARMmT27ylXBul7ieug6H4zRArsBkyt9EAEwB5JoG5R1Y+gDqMVJehMkxezYMbrySTJUJEQWEWSvRfAPZCaq4gissGmNkNisyOHbo6ODm3f25yfH/boNWztktGfQKZDH0ZirSlIPltAHa7vkPYnZMIj3DohEyhugSMYERBwHYS7mg5DJJ9JkGhyOKgoVrdbSK+54JNOLl5qbt7utEYyw2tp99nsnr87bPoJjFm+ABt7zet3tnpsu5ktSfhBbEry846ZNevmVr3/4pdGTV59vUQ7efGuwqcq4dpOvfOtbn/zUkzu7ERG3Z1vO+SvnH7mTX3vhhRfOXXx0fvLAT5q33z765EefaiOf37GTN5f/+d/52wBwcnx8cfdcURac7ZDBDHMSa8CQAcB7L2oCAoTeuRStS4nWK7LBu4Z9rcZleUgGBfosYysRlWQYdkBGkA1JRLIZ5Lwxn2dm772AAiABFi04Aj4smTlHAASwM6Ag44YJQKIJwUrJZPIK6HzlnEMcAMh7j2rAFtPGcgyQtPh5IxChYyarhl6kzzkPLnjnHLvGBY+izAwYibDcus6SEBb6DBVMjohMN/NUoc+wd2bWhEbZGAkCMaOaIrFpSbhBM3TBYwYhQRUD0FzcVhCADBJYlVLaP7jz9o1X3n33wf7R6ZDT1dGuCTy/NXEP2tbFnZ10cQb9APM5ntvh/ZX0iA6gnlC7zMSQEziHiJiT1Y1XzXXjzSzFjAjjRrYCNtvT0/UCR9AtVDNSZYM31rqS7pln6uW8Xx7bF199ZQTARsh5Iv7c+ebwYK2dBV93aTkfXMMIlkzoJ3/o0bvv3Xni2SdODvbfvvPebLrz1DPProfuiceuhPH8xeevPnL58QcHr1U1XX1k9tJHn2M63pt9dmtnO1Sz071HiAixHV8878O5B3eOvvqVb/zYj/3YnTsHt995Y/LI+PT0GJINqxbrGoLbuPpvSJ8wMjZyPjhC55iGJAdHaT6/101qNpvtXQzcdKCcIqQcnFPNIBylt2xoUES5wdVmlgVDPc05OirlQx2PmJwSIpGTDABlrSUKklPsO2YWsZx7JEFonCM1ZUaiyoOPqW3qBsGrkgvsfeWIgx9lNcltAZKYGjBmtEQQzvzxRqNJOf2eaSGuTy0jAVNdTUaj6pTbyjuIWXSdu7nk7EQyMyNCkaIWDRTTyIyKrvihF5SQZlAkUiPIhT6iCIyUARjA1BQBtRj2l6UFc4EhiMCxG2I3n8/vPzhq21Y0MXMfhzQMo+A9Jkc+ZZhMKj0eRLQODkhJxXlOgzhPOSkRsAPUM1syor5LiAjAodLz588f3buvmmNEImsqssrnPJhhP+g6+XGyqhpX59aPJRgWlEl9qOuQknZc2zqm6QgCVhMn5tNuNapC++De6nC/v3KVt/a0qS84qp98+krW6u23371+7cXl6Xe7tq+aWNXuR3/sB69dvt7G6cH+gwuXr7frJHmYbm8fHt6aTXejcNXIvXsHX/zCV8fj6XgyOTk9Hfo+VE1KEkJwRGfCHY8IqmxkIQTEpLiZqYfUr9thiO3u9tR3XcWZvaFjSGyQDZnYccYMYmflrexA1YiRESuThO+7hqNzzgDKelI1l7TBAlIOw7DZPIGaRqJND1AQxhBCsWIsWHcpZyJCyIbOyDbNsXPEAGQPAVTaeENjFGHnnXOOQ+NGlRsbAisiogFIigY5y+A096LIzCpQzCeYWXVVWKXIhIOqaYwRITGzKmCm5NR7j1BUCmd8PATF4swMJkL28OexHIf5+vB4fnj77q33bh7cP9hXVWS0Sf2N2+988PKlj5Dcys45mI7y5d363Qd9VUPb2fnzfjWkOrjUZnNIBFVNRDwMEQBMqSSFAgg5euv1B9NZfTzvvIPQVNMa5utIDDHCss2HR3quqZ96zN27A9euVCfOhGPX990aRlvSEFSeRoDe28rydj2aTKbrk/SpDz/6B60+8WR1fKd++tkn33zje9/8Rnfu0uyTn/iBd95+77Of/dnvvvLqX/zM/2yI1daW69P67p2Vs/zGN7+4c+X6ZFo9uHnj+lMfy2nok/uVf/jLd+69cTo/Pn9h+71bB1cfuTZO48PDw1HTLFVDTqPJWES6rgvekUIGj4jMEGMWNudC1/XLVTxYrKfb+9e9b6hyo0YJwUDVEaMYBe8QUdEzB+/qMs8CMQEpGxNp7lWVA2PRh216TU3FhiRL2QEQQUxtSkNVNcRqJoWESuTNDMEj+MIHTaIlDNw5BwJRRO3MlbwORBBoXCaecjRFxEwGTmFUqY2Dq5Kb1KOZaIyYfLYUY9ctT07v931PiqCac44mSVM2ESv2O0KmLLk0JYoIyVKSOMh6yEvLlpKoguT3ia6b/ZNZSWwq3WcxFEgprtuT45PDk5OT05MFbOK8cD6078UVKj6FVa9KRnWD4BIBtL0Scdsmx2yWQwjeIxEwu/UqqsDDvEcimExqM2TmgsECGYAYKDPGDGqcs1JwQ9RTxSWECvHaed4KcH23efxytc3uyrY7P9GcowiYAnheHB78hT//M/dPT09Pl0cPVtPp1iuvvPozn/2Xu7i89uijq/ViNHJ3br/74Q9/dDTZm2zNAGO3Xg1xuVrNX3/zj7t2GdcnB4c3EgwnRwfewbNPPf2Vr3znwuXtO7duNU3z+uuvj6aT2WzWdkPJGygbF1WQrLkwRsVQKeZUJn3nAjsZOjw4Xq7bvhtazXLGZyNiZ4gl3ZWdI8doBADFHwGYEBGZmL0j3mwB1RBARFIe1LKdkaEAIEssG5aH7+/DvVGRHZdjLSKgCloyX1PZOQEAiJoZEAIhYXE5cwjFurYi2pioYdG3G6ARG7CIZUGwGHMXU87q+r4nUgJAwS4uiSAnYvIIzqEXMBOJaZ1zdFlyHJTREgyjZfCVhhGHqljgIhZjFkNEEzUwIyAiNSRyfdvdvf32d1698e7t26v2RKJwYEK83y0en43Wfffx2cV/eveNamevioeV2rWd8dEiViGvO/JiTe1NErCp4HIxgCF7FFNEmI5ABIaUEWW67fpOFCEDkmNDcJy3ptXxaXYIi5g7gMPX0THkO/31c3z1Cg1tv7plFy9TCOH4OE9m4+PjfPk89Ev8wEvP/qPf+PxnPn7x+Q/sfPRjL73zysGHPnTx5e981ft6vVwCnAydPv749TffevXCY1eDG6vy8vaN4eTOhavnVS/LcFfo6uPXH5/WW7ff+87f+N/9uzS5wGHaDevgG4dY+Wr/wfHp8fFsNum6jogCbbbwAAS57NN9J72vPKh4Xznn6lAtIb5zezWpjpPpxSTj3e2Jr9SREjpWzTWhgYpzxbaYhMCIENE70myQ1TFbUZSbEojooCpohgqahclKBSmHuLDimbyZlZTshyBUERAXWygzS7kr7QEWCIkR1BAZKG1ofmBFSOxcYHCEPrgtdJ6no0RiZkI+DcvYnQ4a54vlJllHRGKMw9DlXHxTBxHIUSWDZDhLftJsWcEGyQKYhlTcTVA2cG4Jxfn+alqKPJPPOXdd13Xdql2nnM1SiSwREQW8PNpaL5Z1E0aMtR8PyYSBLC7Wqa4oK+Wsi3kaT0fMxTuAqjoAa914AKirMBl7VyMhxiETQV27UGHfpXU7BHYqCRGrQEDMjJGHweJxHt0/pK1ZMw50/alpVetoIqMxzRoEHYDrRbd86rHm8oXtt9872dqefO2rX7/74LWvffXbH3jxuY989IU33vxO20aR5Lg5d37qaYsRGs+HJ/du3Xp7fTK33pyrwdxo1Lzx+svLw8P1HP7RP/niv/5v/el7d04//omPOOLYD+vlcjKZLNu1915FNtvqTcDwQ24viWnZ2pPjEOq6ru4+OH5wcLRq133f52Hj21EiOhSK9TEjoqgKWFI5K2+iquUMSUwxnsVi4fvGmoi4KX5nOuDChSqfyfmMGrcxxkml9ovYGTi6wfD5TKAhIgAOwJmxGZtJzrHQr7yrQj12zhOwDENad/1qGOJaLWaVbuiHYXAiCUpTnNeQEzkE5ZSPcTSWDMyuJELHfkCNTOhFUu4guagKao6cd1Rcy1SkXA/GBGIxDqFigiGl7uadt7/z9t39o+Oh79s2Whe5cmOE+223x7hy+DiHn6wn36zBjXB7DPeXtgDYA5iOc+pgzbB/f331anO87MD8ej0gsvr01OOTpx47987dJS2GpbDk6D0jYt9lyk2YdQgS2F08R++8108qfzJI2DzK8XjFv/S59c/+yNVnH9/bnW0x5TzEr7/yvWfradfKJz7xoT/6o2/uTPfaOLx1Y39vu/nMD3306Rc+ND89bNfxJ3/4xy6cu9wOcHBytHfueYeLweRkcfTIM08++cGXHrT5A9eeeHC4fnex+J3f+8qn/8RPfWBZn7TDX/izP//Pf+/rP/pjH/u9P/w6xW62M0tofbdGh8fdqmka3xmqNeORqVZV1VMachrVjpMYF2pFHjs3jKuqqj7/jVfmKa6vyxVp7cLlyXhGxsSbbYtmSxJJxQYjyooIQCknNFTNWfoi27D8MAeQCsUdwbJlIhdT7733riIMZptVQvFfLASMgmd57wdZAwQAUCmm74SIRXFV7FJKl0GEqhZjJqKS9KWYDEQVc5+iHudBk64hJ65nTvT8xUdODu6+r/ovr5KRwAw8i234K+VxCRwYiokqlThDRFPLcOaia2YPOxgiIgJVzRJzjDl28/npwcFBSmkYhmE9ELoE6oiy6mkX132XozyztYsG09FoVFsVcg3QdTitHROQwKC4XOdQQeVsVAN7IRdu3uq+9fLJe7dO7t1Zdd2Qs0qmFAHRIUXnMVTUR1it+nFTt0MiADQDQk14DEMGOH+uduiD4/vHh72kZ596DOKSOd1589VZDYt26fL49Hh59/Z7VVXJ4vja+es0Oqi29vy42d69ev2ZJ85fu8DM7925f+vuu9NzF+Zwsc3TXF+CybmD3hYXzt2rdBzqm3duT5vpN77+xvMvPt0P663dnZQkxtg0TRkvUhoK02fDZ4NN1cw5JzFVHYYhqwgYInpmzfDuuw/uPThdLruuW0aJqhtHjXKXEkBJXi3eCiKieVMaVXKJYnhISXt44ylsOErMZfbFgpaUxRWcUZBKMU5pk1xYNk1lrQgAipvEJZVNYPjDbyz2tjnHnPMwDOWM5dRJTCm2cRiAkAwIfYm4dWjiqgCqxIBMjlgMBDdWabAxOAfynovO2DGBoDjnK2JCsrOVgxaLdfw+Em7frbr16uj04PW33z7cP8rSd6sOEiBZJiXAVdLPn9z/WJWpuv54bk7uHTwy3bKLcv84XnLwIKpb6YVzHO/LwHbvOI8bvrIHOY/m6zamtAI7OJg7ASIEc8jS9gMjOUcZhRLcn+fd80EkrPt+awzzjhzBOitoYtfErP/lb7zzZ3/6+ts3bl95ZOvc9rXf/coXV25y5/bgR/rIud1qZc88Nrp9Vx57+unf+oM/Ojoe/8AP7X7rq7f/xE/U33319Pnnty7sPvrdV371dHX/rbduffKTT/3wT/7ZrckjN19+/d3bd30YLSezyZWLT9ZbH+7c3mjyK7/8Kxns7bfvPffUR+7deT3nVDte6KIaVZoiMA3DEMmFIXJNZTdcVXXMGQRQzDlJ89PZ3t7e1uyR87GN3Xt39p27ZWh1hUgwbnarUYPEBsWCHsCyGaABE4GJARJgViOi2HfMvngplBP20ES7sCsAzZSc2xzKEEIRK5f39+EqRzcy6A2jlMkX1Kr0rESuZCiGEEqbARvzMOvTOg69cy6LMHPf9+tumYd4uG63xtJU450d1BhL5FNxM3foqAhACmRExCVRVzQkUSA1VTF1XBkx4vtBeqVnAmA4SzAp90VMOeVhPj85Xa4MJIsNfULkKMkEBKDtY41hFtlkABtIYvKOHG03ftHEak3rTCQ2bggG7QjXna7W9WTsxiNKgrCWmokn1XrVGSZTQISsKkkDQQ8QGkgClk0FYgJUy2gMkD1IGpC1k7B/q7t0nkBmx/1h4/0J92D+3q1uftrpgL7qX3m9/a1vf/tqDdDEW0eHk9GVX//i23/8R3f+wuzFGzcPv/fyzWbSSQYi/vbrX/uhn//YN19+A8HOTc+/dfLAmma07l0ejVzoaDGt6cbbNz784Rdu3/zexYsXY7tmZiqeGIhGG3PXnDOlxAzeq/chaVTDGONsWsU4zGaz2uO4qidNfe/O/vlzW8tVP2lah4EYfDNCQLEiT0BEUsslPfBhq6p5w5m0AlVSkUWSagYmHc5WR2gAwb4/HPt9sHYDJKkqoTMQMyUiOSu373e0Z0pUOosLAwCRlFNENdUsGtt2rWqr5ZwMkgAagcJ4NM3bO84RM3sAISBFYmZCU1XJiVxlHCx33tUGkFElqeMANirxaOQ2yeNlKYroHr4URBDREGqx46Ojo+P5ynJKMZJ3cYBoPHUVQWpj+wO7T34CddEfpxZ/YXb17x8ezMZua7vdnePBSkzd8tRmI+0HQrUB7e5J90QNlAEdUSWm0K07E4CKAcwHBKCcxQBT5GUXpxbXJ1xPYZGKngQ9GCcaUEEZLH7ulePre/jR68cv7f7AJz746V//3d8NYbj0uPvOW7lG/tqtYT6IALwXPfarwxP19JY4m03hH/y3bzxyfvbnfuHTr736yvVrW12sf/2f/ObP/6X/ZLH6lSvV7L39e9218xfBPZct53W0FLLmqHfeu9k4AOS7d++NfUAmj4wCMSUK3hyCKIimlESgqiDG5JwbxCilxep02lxcdPPxzG8NO+dUj+4ef/U7bwWU+dWTx69d2VpPp+cvsg8hODNgagC0KEwQMaVkpkQoAL4KzB7JKxkjgTkwIAxZeyLIklQh5w6B63pyRvS0GCMUQW7PyQAAc9xJREFUIz5X5RyJCMEjun44DSGUPadIIvTO1d8X2oRlFvfeFy/9lBJIZLMhZwAb+jYnOzo62BpPQjP2rg51xXWYjB4pZZ2BRxBqYIc+ZGDjQNUYHSMo+pqIGL2BY1creaq8sWdXEfr3nyrlGGOOycyyeXA1hcYAVKM6oqRGjINaBjOZOmRVw1Bl6jy0fgvy5GZaX5nVM5WBUxiPUBlr6AHbrMNgydSDGXCP0Lc0iE6CO1+PxiM3Cs4BWBQUZYPcJwfqyC9WsZ66VQSayrIHFOeZklqPGNEQsJhLqM/tWt68O4SGw7nKjxsTW6Uxo4z2xvPTTjETuQqlBq0cBm81MAKd36a37h7e34+AebY1FQ7r5coGCPWeKv7+vbfalLfT6aNCy+Hk7nyOyoBMwb717beGVUyo3NQIHHPqUowxQhaQjSQXk4Di5veZMyOoICgt+1VKYjKaoN8Lk+DQK715OD+ex5PD05N2sV4cuThAHtAMSRDRqMkWjGoOE+SRw5rJKVdUjSlU5F0GBFQkA8wbKTA0mwYURLQrlVItig5q0cxUnOMRYfGtTcHPwAIzM/ngZ84Fs4SICA7JA3uxbIYpdwYCRmTE6JImzZ5pBKBq6fzuVVex5JjLIgywWC+SQQLMpQvGswho5xyRq0LDzMbOORd8HXztXeVdtfHhpRIXmcgx+oLFMnvnw+ZvcC6kGI8OT40wiyhCHHLOUtehCs5770b1V47nlKu1rn717Xdm9e5nx757t7+8Pa7rvAvjlhKSgdRNTeca35hUgPuLNfBo3XZd2+a19H0mohAqdo5d8J6ZvWjvPc1P8qgJpn48HqHPyngWa1FQOUNE6/H+Wl65Q6u+xQzLSKfob99ZiNHJ8ZFoyXXNJjquEAHquq5qMGVF2jsP9+7fevbpj3ZDcNX5IU9Q89PXrv+tV774tfOzp5v2L+3DiCevvvn2fG1FsYqKe3u1ETK7tuvQuRhjEWFklWip73tVzWAppbZf931nZkNOQ+zmi/b4aHF6skhpqKpqNpleOH/eEd28dfDFr732+p35uzfnBycnh/sPlienOQ7Bj0IzIiJfV+Qdeee8Z+9CNR5NR6Guq3pWVxfqsOO4BlCRrKql+G0WoUXqdPZhiggllJDf/wLEEkco2VQ3/h3O1czeDIFQwLJK369SGmKMxax5w1bRzIx934/H452dndn2zvbWLrNHcmAEAEU0p3BmF/Hwg0tkmG42B1piSsGI8AwyOJP6c8mhMmKHTGKGqogG5sxsaLu+j1mTmeUkiOgImBlEk2aquIt4t1/xCCPhQrpzo9F4vNhqGqkAXdoagACWeajUgBEBKjIROJ63164RDZY6qOsw9DHGIQHwkJlBozgHoooI7Vq6TqZbYgaahQEMcGOHZsXcXNmTaP36e/fGbms+H/oWVYiJFTIBGgAikEEd/HIZRYS9pASjsYMBiNOtO7f7AXMcDo576PvOQWzcM830xdP+BazXun7j9kkGg4xKkJMCQN00nbTgYD6f185lTQAQc/a62fEoGKiY4cPRHk1TzIxgBqHeco7rOtTeTZvmzt3jpdJbtx4AhdHcnCg4InKOG08BmMAMiQtfl9ghEqAnYkJSSEBmchZIJ0VvvOkKCB3iBoQCgaJue7i7KjC+nmXhFfevcngKilDSxAAsZzUo2TRU9n9mxuwBkpkwe0Q2xMZPVFJet4pkOSORY2Y5c7JBlSKsVtScsQpjIhZNm5Q758pv6uGrVzA1JRcQMbCdjUeZGVQh9evT0/07Bwf7R4emURVErG9la7tKpqO6ElWRPDPad8PtxfK5ve3vvXfn+cuXf/a8/dbi+PKUMaW18LKXQNYpdKp1TeMaj+aWM9+7ncfempnELOMpq9owgJnxmWSvqijnzIzNyIk5Xw9eKEbNyG3OCICAgGjGkjJB/rXffG/yU6ODo3i8NrHsGKwYvoCigXeABETgPFZ14Jxjv96awM7W7snp+vCw/cDHPubtEM7Zp1761Ft//z9c3njjf3L+0W7vQr0avvG91xG4Y3GA3ZADsEJPyALmEIOvNFqUTGp9l3svlCMzjMnHnDkJGoLDGIc6BAVkamKMIYTgaXdndnJykruYRniw6IbXbx4N4+s7y0sX2vO7e5fJNTAJTUPMWU1SRkIFIOeQSwadElKmaJDMUNWQ0HtvoDWMcBMVVwZipuzsTC1dnqKHh/VhXSMi7ysVIyKDTGXzLVGz5BxFzLkC4EPf94BKBG3bj0aT0WjkXQDCFIeT02XsIhFozoXVwohsZgaiklTSw6d28zreF3CeyZrOADM7yxknKl64iGdkGTDpunUbh67rNKczbKJ8OStYzCk4f9ovCPC7p+sLgT+3f9jJ/Ork3EXFulYHVtfqGJy6toBcESBC7VVBhLkTiMiITjIMvakqAuQsxEhcxIeGyDFlRCRA51HVYs4EiIAAgAYEBoQNYUA6OjpetUNWKStH3HBrAAAIwFBDKAwYzlHr2tUOLEs/JO+r1159dbozbuf7s9DE/Qfhnbfurt60tGq7+f7BUgOZFUtLOMNoNmtu3biDgIpp0pglqsWYU0oIzMCl3gByHLIpZhUFQ7RQOeepGVVVFdqhzYCI7t69+YPj9eFyfXJ6uu4WWWIehk1Vs4c+OfB9oOZmb2miugnwhNKrleBuZqYzeUXJG3mINH3/gv7htunsjzboOBoUmaiqSv6+2BqinDTnrKre+6YeOeccVqaAiDFGzZZjciJCtrGrFbCU14icE4a6MhACEQBFSKYAjguFH9wmPJcoOCurr/KiC6OxwMLeMyGs1+u277SPi2Ue1to0HDEEkyTkiBXwsBvmrn5vefKLF576jbePwrCsAT4+3V2k1U0Hux6pglVW82AJW1Xqebrt80naHlei4MENMqiCc2BGkqmqiAhEkgxIBICxrkBS78klgTCCVRs8xBHgHMGrCSph9eiW5+2hGudJBWsIliIVkhgQgjH50YjRlDhXHqZBeYfEhlHgo+VK0Ivi4vjw3sniwc3vXnns8rX7N37ubTe6egcvPq/r49+/f1jWdSKChpkBiwW4bpaYqBCK75pqGZZD7fsueYIq1GpUu4COG6LxqBbTvl0TGLMPXO9t7W1tNZIhxtiydx184+DmgwfLp568gCCny/nW1qXxqJo0kwqYgiVkU0AgkfKSIhmpkWGunDdDs0xEZGRIwA4A1YyRm3o25A7ZpVzCOTd59HhWwIplCKIBlnjPBACqEGMc4hpQjIQsOHbgaxEBAQ84YCpbidG4SVGT5BDCerWkxobcuo1ivxg+5UFEEIHQbTqhs9RRomKCWp4SekgoBFDnuACfYIVdbwDmvU9dv+5Wqhunq5S0XP2oWnoGIIwxJqYjyc+c32l4fB4p4Pkx1RM43HXVua10/wS8o/E4uxUhKDIOInkuiEAMbZfrBp1jcKgqiLToshoQoZl5Dx4DmDgHmBEAnUcURMubbQcAIBISyjBtbG9ntr296/k0sBtSX8iRCAZEoilnbEacM7nK5aSeGMxCPRqP6tN7iajyYxut3cHx/XOXl1vgnxQDrEwHMe6igIEhJDFGS0kco6oCgZmJKZ1xiMpDroMSQcMh5yyUyQUACCFU7BGBiUFykYMSsZkE56NI5UNFboABRE+O5w9mYXc2UmSEY4LGoVgYa/Lg2CGVS3IDZGrpIFlEShIXEoGcBXobkGNTK2HxjBvgvJh+lXvg4Sr/bDG5eYs3wqYseNa0AijQJsERHSMandlLlS/OOeWcHbGKILB7eMUUlh6RA3POYTmjJU6ZiOp6JKaMJQ/kv1fVDdLDobg0KIhoUeeLg9PF0cGDg+B88FVVCxlXYdqlSETOUTLLKidE92Kq1utwYfrERTtnq8Vwcp4mP3Tu8tvx3qOL/jACreFi1EXCJKyQK3S+0tz2Tv3+vTQaIbMROaQcKkLEOMh0Ol7GVnqbjIOKDUMiwunWZP/+sBXYedeuY40kprXBkxfhY5+86lwYjXYfuXpy+9VTAwNCUnBgohYAUpt4DGqWbQBsghdi2z5/fr1KN/YffPjZp+yILu3Qd77xpetXPnWNd648/YDFHE7uteulFWU3JjBDJIEYjRmTgJkaDHVVEWLO2QeXhugMM2GueFzXsKEOIbvKVz44EJGkKYkmyYwwmVZ7W7OD4zXEzB56iwTURr132K2621cuTB651E4O3cWdvd3d3VEdmqo2dh2QZ2cADojLBEyIyCqQz4xGihuPmkHW4g7H5ExUTXIaNjr1qKrqXRNCKJd16UTL0kgkFbp6GQaccwZqyBy8z7USGigl732VJS2XablcrlanXjIRiOImcO5hq4uIiFwy7dhtUPeHDROCoLpNM1aerTNHANu4CwkCbpgHIlnSYjlHNZAch4GZGNzZRmHzjVmVLR3NTyc87iBdCI0pv3N4GLZbCFsveH86ijV7SCC1ZUgaM1Ex/wHPMJu54SCZWV3XfR8JyBQUxHkUjX1nBDAaT44Oj03B1ZTjUEBjsAQAHrRhCt6uXZtMtmcEPBtNd2cj1WMiKqFoDglMHRARphLvly00zNxPJjDEPB5fXq3eW8wPQMUH1XZlqp7D1NBPZ4GqW6sDAAIQBDbMqqYEkouYk4gRmFLODbly1ahqzmZm2XQYBqwqVLKSHQBESOaYcyZGVS3hx9N6dOojA/YpInux7EJAcvNlhzqQ491xIDUf2GQEQOiBvTdJRSZU4LZNMPEmcUs3cXUb33cuCXHFX6zEGBNv8rgeGk+c7dw3BnoFRi0WfJvdTc6IJTfHE5GvatVcLKHK1dF1a9RyuiDl3teN2/CyRIjIuTEAgvMApTf2AGBKZ9R/RjUiMGIzBdAsG4rdw76YsDJlAxrS8sH+reXpWiWbJgSuazKjFPN6vd7e3vaVW56sQYExHx2f7j52/R/df2sWYF+H/2hf168Nf+0T+z94biv2yy+fDidzXojMGtiZ8GKF65TBsOutbrpHr/DBXJL2k5kf+gIycEqWs05qVrSD4+Pd3Um37ovxL0CsnG5Nqjj0lUE942mdnnn28WmztTxZXnh0ZzYyAkZN7CAABqG6wph0PB2xS9OR1EjM6+nI702a7e1L61THlThcwVgrF5aLE83y5PlRt3boH41x8U9efc9BFuQCLgpAMqtDGGL0jGbCnupQB+CBBNRSFmaMkjEOlfNt1zkVZ+iq4DkQCpM38DnHFOOoYSDenU1XCu2q68m65SAg2x6ZOSXcP+lvvPfdnd36xeceX8V4cTIaj5vRaDQaz5qmqeuRGQoAIlgJFLYIgICSYioDNDOqZATnnBPNICY5M3PXtw8H4uLezcxEzjGnHItg/az6bZAfEBXTImyvx6NS2hIH1ZxyXC3XKQ1OJKP54MfjGXjeyI5L/8HIhgDI9n0W6GdB9aVhUzAp7CXAjbflQ5V0oVqrGgAayND1bdsXfMp730Fi8r2k2WzCPgxDV/pdYa7J1Q7fjsNnajyiYd0Og4M35nRpZ/Ti1s5NXkGni1ivut6PLGcxBkVDaNbrgc0QAZhTlGbEKVLXDgA09OIDGID33Pe9cw4ZulWPBBVjjikEhiRJ04VJvbdzjp3M+3UVnA+MYASsKshFuIND1miJwWpPDrwPMh6PmcJ4PHv1lbdGszCuUHWC2h4eH/TtaivgRCTW1ZT8/rL3gIZOLZatsBokKZk/GRBSSplcMgVX3OcIwAq+3XVdCKEkQ/Z9z0RUeWYjQs2WkjANoXJ1XbvQAWE06dqBJySairY4C4COD/bnr/vbTahIuctadcOeAICJyKiZqUJRYsCZIKLQqYq3NxHnnD2BiCChc2TGKaWH47yquk05ZxVDRsmqZsWGxIqfIzAapDRgyd1JiXwol62IPPTn8YGh1xAq33jNyRSdUjEBBOKgJVwR0VFALBbgBmAbxEkJkQEYQEWSpCSSWKQA/KLqXBAiBlx3q2F9tFgtUxIg06QtQYWjlBUQERlU1m1WNWaoCVPlvvPO6x+7cPmQYjPgD145/uzl0f/tW+1PXqGdqv4pWfzBHhwex9FFONqHTCRirRlDRxG893XQMY+N+8UqRoB6hHVdgaKoX6xWKQkqRemdg5xhNuVQhb7vx7XrTCa1e+aZc3vbIzX7zKc+Nq6b6Vi3Q0bmUT0+mvejChS1qWDSgIGgsZiG4PKgj7300ps3b3zhq3c+8mQ2noWmbudL37WH99946uJWdYt396btQN9546AiEB1kg/CgAMSsjGDKKYpzEDG6EJyRmMYkIwyUSJzk4EA21nAjQlMVCXVd16DO+WSSRCqoqxFehC0ZdH78oB3aQKy+JuIKQ5eGlXXOh/vH7cuv376yN9vZ2hpX3J52s3PTncmsH3XNeAIAIbhNw6aScwbikiw6DMNGoGyogIRkCM45O+OROLcB88upzZKQUFNWi6bM1JghQ581RgWPygpOWUSY2RTratL3rWMZjZucvasJbECDZjQa4rosLAufpdRLen8aIwRCKxJoM8CkNqgNZhuUVDUrbIavgpeWz2eJ/boFgKyp7/sYo4qUwMYQ6o3VqioRVSEgIge/7Pvtrd379xekdtHzU25n5inRqUe4zNMnZhjGxsHtbKvzlmljzs4IaUiAbrFqK89N5UCoWxfkDYahS0mQoJlMyEGMgATNyM1P+5gVAHZmBAJ148fjMSJfuHCBGUZufGkH9nYn40kQFGOtfGVmdVVVVRNzMpA6VCHUSvzK6/ej2c7uVFJEpB50XFec194BN0Cz3cMMC5PCx8GzOgEIESzZxpY4JckGuWyPzj76vi8WSMXkv3w8vLLKBRpCKOo056mpeVwzGoAqaNl+8SBZTAv5EgBizLcPTu4eL+6czO/P5/ePjo8Wp0eL03V7OuS+T9EMjTaqzjODEy2QMCGzd+WaRGQgZvJVVTEzGJXu+aHD/DB0ZyhpIeRnM1OBkqBcOJwFZi4HJ1QuhFCFuqlH3ntPXC7tlMSdpUZskKbNzLSJbkAFsAIamCDJZmoHNhCQXMZLVWV2G+A3J3FZUlQZRHIfowqoGhiZlgUjpJQQQURCqIioCY6ZsfZdTDeWa2vyo+aWxM/uOgcmTAmrR6vl9i6tsm55OF4xu3y4RAMwBlWbn+bdPejWbtIwAoyq0bJdL9qcBVKGekx93zkHaEAEfZ9i0q2JT208txOOjuJ0PNnamrELTT2OXVdV1d42HKyzc6HQffu+HzeByUseRqPR+mQ9qndU7VuvfPfOzeWzz1yq/VBV3PUxEokO1K9CHcZ1A+Nz7yzvDACoVgEMgIKFpQIGlgHZ1BuaogpkEXbO6MyiuOS/M5UR0PH7u28REe8cEG+WzNrUVYa8NW3GTXMKSzISwH4YxJSYmblofcEoGdw9OGrqMPLbeQWIOBr62kED4JFEFLAkGZOoBe8IzoIwmRWViaFsQgEYK2ZE4I1cMebyjSkNZpZzNEjMXlSL+WkBtgYVAOWKi19plvgw95qIym6UyStmM6sq74qlhKEAKJgjIituvwBiVlLnCq/wbH5XAGWwlAeLQ0JxbvMPiKlp7rse4xD7tm3bGGOfYtd1Wdj7uh9SVfm6ruPQIpr3XjQ5VwEAkPu9b738w9evvBOXH5pB18pjO747Ogk7O0yLqV3805fvvjWvv7zO25dzerve4n4Ofp3TNCCosed23c9XbjrL6/U6CQBoqFgA2rXungvrRdoa1zlD36ZRDd4MHTxyca/r7tVuevHipb3MlqKqXrl66eojFw+/+6Dr2jItSspN7URTe7qazHhr2xFDP7Tv3d3/03/yh4Z2gfnAMUfSYSENp5xOJ9Vkd+9T7dbO33vthjiroipCbRIBYvnlYkFwOKsgGcYEyM45JmK1KFlyHrlmwBRCYARVFduk/3jvib1nJyJVVTE57/2Ex5xxeT7fuvmg72IY2sLnUCx0TCBiAAJLKeWuTV+4dWt3Z+uRqxfPb4+GVT/barYnW5NAoRq7KjjnPHkACM6LiJqIqfNVKWRV5UWSKRFzcJWkXDyXRZLqxnDeBy5OkjFGVe36ru9bJEVXJRU2jV1XshVTLgJ8YPZm2ZB1YABBgpTSRtVe2s2yhDNEYBBQhg3qwUBn/iephICriOUEOcEG0d9oBhQETApnKWcZhpRS6dZx6FNM0XuuKpcHLCWhdDAKhhmWAp+4uPXoSb9cGs6WjRt1Xb+VDdyYaXLJCLbTrVZOEGDUVwNM2NoW2mjbI+47qUd+fZqMEQxGjc9rBRMQCMG3y8ETS4T5og8V1IGawOokxrg1g0sXzzM16KEblqIdATL78zvjm3fWpiApl6oPYFVwkrIitG0bqH76qUvTyWR5cCPU4DlgWiij88YQLev43GN3u+5ut5CNBsZGSckgltwpAwAoTgkOyNRQLafEzjssBLaQc3ZVWHUrqMfsq7KiKxZuKSUCrEMAyMSAwCEwNLY1nXHg1Emhb5b35SF6BQAyFEckQq5PT3vRQ7Adx5id5YQyCZXCBAGRsVJPQbQ4ZKNZsZJhBEQyVUR2gCUhiwAg5yySfWBAZbdh2m98a7UIoQZUE7GqqsCw9ANltCoLzzOUysTUzCRFVXDesyqoGoErgxsRlt8CKqBaIBYRMdCYVSLgYEgcKQ6rKD2IJwzoYBPxKRpz7FPX9av58mTIrVjuDdEoi/YxAXGJJWVPKfXBIzrWLk+pri65f3Z//1997Mo/PnzlR8YfOrz1+qWaafWgZkvj1cRX103+zCP4sYP8GwQ3jt2eukPMce0qx1WF/UKjAPQWDThrhbwcbBQwavLOD13qMs62Ku8GiUSYtvbqftV94OntF198YchLh7VvaLweP4CjOzfuSxg1O54XyZJrtrNY8izL3l54fAKYAvP2ufOT2aXXX/1S5WHMO8hKMPKzYTbaRsqrYaE0fNcO671Jw5gVPOhW7XFISbFjBFGgQkdFEU3IAxm7jEpVYETXZ/HItJYqkIH02mLvnWrChllC7cU0qwIxCQ+SJmHmJv4y6aOXLr3x3i3psPUxNIU7iWYkhst1W7FzFBQtU5Asi5P+ldWt+bXzV1ezabNs6mpru3lkb2drNAtWgVfPFQIG7wFIwcCgcIbKqSrUDGYw8H3fGkhBcMtRY2bLAgBDWuWcRWFKJKZsVDYCBhnQcgZEfsjcy1lXfasaA7sqbFOhP5X0GbMzkBUyaBKNuKFIqZkAaM7FGThladWiWsrSG0KZe4CwkC3ZO1Xt4lDsnzdtk5VnRYe+H2KXUmKHzOyB2NQBcoI/fK3tPdzPpMRJ8oR0XF2owwQH59PYUvRSfbypn3B00fMF35/bAgVLq4EyIUmOcO367mhEechqg/MokKuqHjpB5GYiKQ2iVc5ZxJoGmxERQQiBgFTz0Es9GploHzNTTVgjgpo0deUYCUHERqNmNpsxcxWa+/cf5ByDr8lxwaNrcu3q+PTg3qJbPzg9OrG4O93a3pmUCNOUUsVYEeIZ6F0CD4psCABUytajaNa4LP36opWTAs6IbtRqklTS2YCfczaQuq6bqj6/O21ql02yREk5xljO1jAMYhpVomyi3AGgHwbJdrC/ePfW4f3j1fEiHp4sjxfL0/VytVj3bV8AclFSYxOH9DBm430NXRKJMRZLGTvji5ytyt83Ey29LLlQzuKGGX1GP3r4vbSJNj6zX9QzVyczUS1qQEQq9FAFA0POEkWSyhpJUlRyKqKmnBMSe2Ym9sAOIGNER05M+75/cHBfBPs25mTAIQ5q4CTLbDbbOETk3NQOPJ8u1k2oUqYbJ/lzNxeXt2b/8MZb99Q+6KDqb0zq3akOaxnQ8K1byT8qP/VUePqo/9IhpOTOvaBvP3DtAEiwVbnvvH78zPXmyqXp3TsHTmCeIQ06ngSRIWfY2vHLeTaBdonPPXl9b2uchmXKkYGypgwkMjRVjaF5+ZV9IwjsPOp8nsYNTAhpFx3bpB5Xnk+XR/sPDlaruL0bKx9EZH56mgkedO1LXl8ROalWLufHr1197d0bqe/SSuqKNRsqiMES3v8Qg5jEAIC4slS8a8yyGUZN42acCcjRMAyYpCZExBCCEUbJTklBkLDvuxD8eDy9fmV3NVx++ZWbzgMrgOd+3QI5VW0teZdq55m49uO1tW4chpwhQn/cPzjpZuPl7u6oH/J0tNgZj+tQXTq/O5uM61FF5HxoTH152MCoZH+lOCBC0Z2XkwlnDrflpAJZYOK6ihFNsvfBVXVZYfowLl9ZcKSyTIoxBl8BBkQj7+hshM9IppZNczHgK6BG8esB0M0kL3JWYxEKk5o9ktOzAuzIEzo0GVIahkGzgJEKEPF8tTYzx6E8lA9JpWLax6GVyN5PxvaFN29fujj5/K3F9xY6JReqMQIFQqe9N3xtkX71Tdnq+NKYPr4DYzL1ypIdRxAwyM41Q0yLxalzDCaVd8RpvepN3WzLSzYEmkwpqwaGR69fuXLp6ub3qGY55Zx94JQSe5cTqGbvfYyao01G9aj2xVsByJkJMCSDmMUkqWXMenX7Qmxh4kbJwkkGBA5NGNVVVWGx60BvjqEpysQzUMmQFBGMchJVy1mKAeJZqgIUM55SOy2LiPR9HIah9PdJNhw8EUnZpqPxxe2dK+d3c87DkPouErkice6GNMScFUR1SJG8E8OsMIhaRh10vmwPDuf7J93hcrg/Xz04XRwdHy+Xy3be9e2QY3rIqETgh6Xt+1IV6fvWihsjUjQ4c9kFcgHdRm1hZqpAZ96itDEV44cFlcgROVegKbUMoKgCZsrO+0KuUYFkggAGWZgqK0ADdYBKbAGAHBJQgeUAyIfKAFami8XCKayX3TBEVdIo09Gkaepu3ZlhHaryoh0yJNEEJ938sStXHpu5g+PhlQf04efP/+6bxz4jOyfERDuBSPPqs9fpP3rgaq9XcvPInr64BW/vp/9my26vrTIFhXbV3WUIAKMKUZFN1TWU2529Zkjx+DCOPFQ1V01wrn7qyefSupesBtnx+OjgjUt7jyDRrPFZ+4IJ9ymqYOVZc56MK++rpml2z+299957h/MuGty6Z+PQk+OnHn/uyqOP3nrzLlTViVDoZafGc13YCtP1eM4DQlJAQpWJYRRs1RIiAOSNqYA1gt1gnonBjGAYBmYchsHAITsiBKdx6MCj975weT1pBouK0CdH7WQ0qkbjiztby0fWx68uTtvWOQfEqmpZu2Edmjrmrqq59mFok3Mupdz30UJovGezxbx7ZX5rPB35Udib1ceLxezw9NxWM5uMLuzujEMbKs+FvA0gSUFBVIgcgcs54xn97eGtTWDOVWbo2Q0mTdMUZ+eq8qrgXSMihGJqIYSu66qqEkkAFIIreTFaYveKU0M5rymDKGXBnDYPMm2yOje4KSETOCZfus9NcUUwBGTuh9QNPailGBHZe59zLjyXEEJKqTj3pSTOuShJwZJCAh2NsuPxF165+cxW84naKh+4hgyrmBOiVQiDaXeM52TWeEd95xx94EL+xI5MB2iAfUNk0HVMBLGnbq3rpRq2k1m9/2ABAFng/MUqDmTE53avBjer/HaBjiXpYn6U+qFq6uAYwPAMFS4j6tbOdnAOiYhczpnZJ9Mhu+PTdt12hnj9+pNUCHSQhrbrunVNDsd15ZoQAqAmlVJOaseNkt+gypt0OVWQbCo49DFFSylvaBJpw/XemDikWKb4YliUTZEpq+WsOWc0qUJTN2EyqZum6eIw5NT2XcwyaBZEjSIppX5Y92si0qiOWFLX5j5Z1hQ1C5FPSdsuHx0vDxer/fni9vHi/tH8+HQ9PzlcLk/adhHjYLKhrj7sLwsH6OEVv2FpnkXMMHPV1A+JmgYPOXRYCnNZRBX2ifc+hJqZXWqXRGTIgOSci0OC1BMzO0FTMgSJdpb0lcVUU/FDAzNGj4ZDGvLQeyYUdgoxd/PD+7fv3k/geiXzofH1qjvdGe1GiV2O45HTnMCjas4qmpJ35MSd3D9Fpno3zffh6+/c/Z9/6CnDXtW7FAc4dlBTbs+zf4Dype74Rxy1fu+1+VGl+LNX8E9cxT9e+j96d3j5BKhjCVI3VDcURR0E11R1RYf7/fkLfnWa2qzXZnL1sQtII3ErUstDVj2+culxJLt3tGyCTQmjw3lSZNhGMIRh+aBuxk09qSqv0ofKnr2098qNo7bnb765rOz0s5/9M7fv32+TrNYatU4SAYdxTXt71f4BsxMkMDFjcJWNzCAzZ1kU2jmgAgxmMRmzaY6k5AB9TQg89GKapiMcutiMRjpIpGgmIfi26xwz1sZCg8dFF3Zm1Xhybms0PPNovnN/3q0VQAETAhupOVj3yXlGxNmYIAkTEVfDEAd2HOooPRL0QxwJzVfp+Og+AGxvNU8+dvXweLE18eNRPQ2hqerxdFaHpvIEmJln5ZCIChAyGJqa5GwSXGDyPlRg1jHWzcSHmqEZ8jrHQVMEUlASEREoOggiV7ACRHQiGQzYVUSkogUzKzjCwypdnmDnXPFlUEMQEBFgBpGhXSJZb+q9Jz8F6Zddu1zNUxIr3iNYZP+aJBIDs/ehoAOGiJoyknMIq7ZvJpwBnIffecs+c23xnK/a3DUQZVi7EToc177fGtPfezf5K/TCuPujY5gv8F95CkDhRddXl/2bh9BJXqyaijsIdVqnHPrAtur7GGE6ro9XiRh2pvV0OkVXzLFIU14sFgZS16Pbd97LFDXgQFRlFYHIsKNQT6aVqwFc7UdR+tjlUUWzqZNID5ZZB7i/3y3XrQimpEldw5BSkgyjOnjvvafkJSVkRgCpCTNDzCX78SxiC4ERs6CBAgkxgXI79HVd541rDcYYmQg8O7eJs6YSTlyFM4cwJcKmaSaNH9X+qIuQlQg4oAoJoBqkqCG4tm09O+ecqYJASqlDNINV14ZQq0W1zMwxxpPT7rW333vsyd11qqet9pU1tbRdGjXVqPHjuvJOxFQ1i0jgoKQgmjWJiQtj5IqCdxy8DwCAVJG5SiORRouasnFhIxWwCB7eWojo2u7UO8cSna8chSySZahCUxDUM2oyPqy9ZpayKK8JUGGIMeZ22bYtM9fTBmdXDvffu72/3/U9mG/qZkiDZAyhZmeUqWAPftSkfg0ABsJIh0eLnMh50A7Hs3o2606W+m9/6f7v/fTHqL6Dss1up+tuNaNq9yTvenx3Dv/7b+FPPeVuLLDNuljSq3P59Hn34gX7y8/YF95xLy+7/eN6d68XgSFbv1bTcOW6pWWcjmsMw0svfujwcLW7PVRVYzL0fd92qxiHVZc+98VXxg29dHH75ZtzYA+1XK3hiV0eg0oFISSjtF4vRFMe8M6tPNsKw5wE4K//zf/Ck/v5H8jvzfvx2G3VOymlro2Vo3O7/ugozPvEkEmwdkC19a34jQs8FJUpGQSEmAQy1A3FwYjMBey6fjwe9130dZVNU86yajWn8XQsIv0wNETDMPim1izrdlFV1WRcb42nT12b9d3BvCXJhprJOFLyDsxssYhNTaNah2GYjibBhZw0SgxEPrgUZYXOABVFBLzR6ljun96fjm13MtudNltb3gdqnNuZjC+Mpxcvd3U9YipO9UjkgNxstIVV5fwIwasvADubqnchy6DsySFXNMyPWRTpoYwIh2F4SDJ2KfdgQVVNFAIVXCqm3nF1xr8qClH3ftuLzhDVJEvs+3XM66iD48blLHlYLE4XiwWgOvRxI1Zm5zwimqhzLoSKyaeUvKtUKGXJGbI5zCkm9T4aEAbpV/hKf/ysH5MXR6TYp2Xa3tq6fDT/gUfhW3fllf22V/zoJTtM4Tf3U7D8gsLFnfELF/pXliDQdyti7wghJey6YXvHtV3e3fOrtSH4927ceeqx66Ippr7ve8cBK3z73btHpxpXOnvU0wMGSzsVOLRrk2bpck7R1cGM23Vc993B3TiPCG10RAFtvnaIVWQ96aJXRsS6HvWdAACTInDMucKiGxREqENY9HGzmS/INoADQIJskJISUMpqCI5YRJRd2iSnbTQ3mlXZCgsJEFMSRDQoXT7WdT2u/O5WPe9aRDIts646YlV17Ls+heAda58iAyYVSYpVgAiKoE6hzCdoKWUxZuDjbuhW8+PT1dbcnT+3vTWdCPY1VM1qLRnrGn3ApmnAyIVKFRQZKDgfFK041jChaMyaCMGRI+LkGpX2+2C3DTOk9LVOY2eALjjnEwRLKbOzlGKKUlUjRDRKYCaCZe4uLlCotRqYxlFTYR6wgiZUXE3mx/feuXPr5s0bqupciMsWmR1WYTRKuUPEygdAXveniCZifYt9pCpUx4vh/NTboGnI7KonzzWOVr/4Gzf+tz9+9ae2Aztx9Y7k+Umaf6SBT1bww0/V/87L/cjgz07gtVW/VeN3FmA190P/gzsanx599Wi4N0g2wf9fU+8ZZ1t6lXeu8IYdTqh0U/ftrFZGoSUQSWQGI0Q2BkYDIiOiTbIxwjbRyBiN8dgjwMNgxjA2HhtsPEY2eGSMMVESQgjRUtOtDre7b6pw0g5vWms+7OqG+tWX+lD1qzq1zxue9Tz/J4FqefCBo7haV7M6xLg4tH/+xIettS970dWD5eFu2ImAIfvAAw/8yv/7R3WHTw3yxk++48Pvu1nX9t5lOlzQK+9s/+R0YCrSraQ52qzW6zF/5EYYEXJHdx3p6155+KEPr0roLh6+AEI9q/Hi4WFdzU6pB4l1NZ+1HfGYAyuCb8F7T1kSgjwnNyEAAbLR1tmhL30SIkhRakVyEMLozWyIiRWsMSSiYiYyQslIRkUgSHG2HsbknQFB5/Xy0ZWSqXLdox8567MKABHEKM6ZnJMU2G4iNOi8IpGqZpUUhoqssbbEJCIFwDnnCiAqkJKYEGDIeRfh9NZNsDcv3Tnf7a9X4eCw3c7mzcH+vPENuxqgMlbAG2BSUNEsRdN5IYICiLGNRavWqNjd8RPTu05UptTwxHZEREK0oiXmkJBSDoAlhAG0AOYiY5EeY9A4KkTgjDwtogiOkI2xNaBDb5v5nmkaZ/zZttv2Q4p9yRhKTohk26wBQJJCmtz51hDWWcDZNsA4hLLtizFmMzDYkgugFDWy56T1+jPvu57LmHTD9kgrzvX8Tmc2Fp/chIHgUsv3A4wEt7A6WkBO5ZEN76G+cNHvWfSI21QgliuXm5OTVRq1ZI2pLJrDMNDxrZt//PAjfTemlKzFS5fvKbpoQeYg+wBdtwaGiz5drturtRzNDyQXAUSb2VIyed2XoGCVBWXGerR36fWve8VrX3vnpUsPJIPAYqZ7KGCShGItQhczQDFainLJUlJiQNJJIyQAMASLmpsq2RYtooCSGkCNUiJgSpLGgohdGpSYJzVHAbRIzsIqjLHkkiSEECU5V82WzXJZH7WxbsUwAmpSLKIpFVALAKXomCAWTElLQQYuEWPBLNQHSMQZsA8lkKZCQy6jUhLRKDJKAu4CPfP07vGb/fWz1Y11WI+5H4YYOkVVT8xsBUwMlNQUAgBGgpJL38X1aYkDWeNpwa4yxqSUFMqk8kqBqf4BAIxxFeQCjCLZoIXn9NYCJedRVT0RKWhOWZRIMhCzwaLETOCYLVdLYxxnKTKu1+uPPPp4LmyMyVEMVznnFEtdMWeqjC2lVNYNKezND85OTpVoOwwnawkZQLPuGWekrrDS0V5wRPbhk/HL/9uzb//Mly3kZOGPIPm75tf++KT9AxhexvIVdwghf2RVtiU/1FYPr8cX7stBjfVWj7Hc7/gOk58UuPZ4bOaZW+I4Hl1YfuBPbvgWlmpvtv/juJnf8YIrtjpcnxxf3C88HL/0EC6t/fD04y9o4DMfNAD9vUd3Xq4XiHZMW4fVk9evh766ebPz5CxGUX7piy8u55cPjxZML0lpTHFg6521xhhjTMlsHV28dAAPr1SzCCCIJSSLZYTnGqtFAZICANx9CEC42tCNE13lnLOpkoKkgWDu674fm6aKcZy6gkxNGbOpqpTFIETOJYDNWnmTIM+a+uLFI2R5qJ5ff/b44euZowJSLqIoiKAKWbQUjSUbwwgGAFJK4zjW3g99nrppxowghZkZjSEhVMkSlD1yEnr0qZNNFy7uj1fHzXYzr6uqQZhhb/2ByGRxWpeScxpIipCVnBQSOU6qjXMVtreeGhgxSyEmKQlJQSWlYIwzcE7X0OeHAdZ6yFFLOcfrl0IKKEoeAQgJi0QAUIQsCqjWWwAghBSh63Z9v2NrEE0WmWAEk8Q1DQkmvLTzZmp5IqXJJFuKOst9KgYoxjRUXClCTheWePsUfuOR61/3QFtKj2JnTfvos/LBk/LSfX6gBit0I2IOYHN8MsOLAvmY49BiDL7KFphWRbyZ2WxG8VV1cOlQHtvNoNQN3dVgvP4EXrq42jzdzA7DelwSjwj7Tpqe7p3r1aVsMyya2hizCdE2wGyuXTvZdkhEzAKIqcj+/v7e3p5zrmSJaQTIVVXhc0liA3aXNqVkzYKGpxbT6bpa9C8hDxCyahRtLFY1zbwI4Nl1EZQIghlywhECOxtCclwAwDAbYxjPh9cCmksR0TIpzSjOVcaYpmlyznCpPh3W/QaSQEiYBafpakqCKFObYY7JGJIpmpSzMS7GNLVgWiJUiBoLozOAoBIEWYiYbbXaxsmG52g82XSZALVIhd7UCjJNIgnQEAthIlWBOA6N2y9F0disgqrIRspf0O+ZmQiM836ioxdQg46IVbWQghKpOLIRM6iQAhBkjVQm0BnAdMoFiDkb5pLS0B8/c/t6vxvm8wWSP1vdsm5ujZ8CqSXHuq5t3XjrVEvKgwKvtv0QoGkNlBSyMmAIZQfE3jZDtvssN/ISzC/+0Vnd0JfdcyUPj0kufyKltuZTLqA6NWq6MUbMD1yedae72SxvbPMzT3Vf/sLFM0O6KwRb0/vj+EoDrzmwv7caN7euHSzlBZYfuigHJymFD/75rUfvfPErzV788w/92X69owPHHF94WBmMl21V3/0SD3uXj65+4OHffc1D+MTx+MzttJh550VRJdHly+Zw/16yYm1bpE+xFCkXLi1CjM65w8PDx598Fhna+dwazCKOCQDBIDMYKKg0QfYAURW2UdlXi0VdcbU4eDaCefa2RIEgbGOM6AxmIuoH0tpgGGNK3tfIgE0lRDqF1cduHHA2rxHTrGkNYVVVR0ezuy9cu70Z1htZrcuNM1jvJGQRgBhJDKAUAEh6jgaZ6DQiWgQBKMRijDg7EWhUiBl0W3Jja1NSKbTO8MHd2dN7x7c2/aVle//lg4sHuwuHR23tjXPG1JMNpsRdzKmkDGerZnZFSgAVQCslgmQVRPoL+3zO+TwwOl0DSynGWFUlWxcdAG0UAQFRZVUt530mViEbnsBMJRViFslQStetT1frnAuhSzmTYeecFHXOjeOYc0aECe9MSmPoh1CAOOaEyAKQRMwIyUMkPT0e6n2yNHc+DhEOG/w/f3/90KJ56dHd3eraNsVXtXR1Zjyb2OU1l0UxpdudRNzP/OjtjHO4v4E/eHZ4w93mEamOpL/DywVv9w7TNsA+69FS7/PG9GnMoCkMT37ggi7n/eNmhIUBP4O5H02GvfbuxhymIkN3tkvgvX32WskFGm+GkHKByuvRXg2kMegOummUYYwpKYthUqiqyntHhi145qKKgiCKAoUIGZVB02TWAQCAMWoCIYPGNjNX3XsFUPPNMxlyAcAsCkmY8wgma6eVJ1eVHCWkbCxyITIpjiUlVWQ7IQrFGQJokap2hrPF2WbVHVcdEDCkTQ9jwam0W9gUzZpkWvqpiDEMIKKacwHkjIXSZFlCZXHGiECvqamZpxr4Aput3DjurXV7Xe99NZuNzOzgnPMzeZwYoYBISUkGBwZAkW0e+4mqmEuS54LIE1BpCrXYycOh5xFp6x2KJgYvBSUlJVIAkYLGcYhq2SCL0VJyDDvIKafx1tM3HnvySTZsqdrGofJLQqMUjaXcRWYahhGRuIVu1w9xCKLbdYwBJSdCJIWQsXLQWhA013bRjdsZw+zQHq+HZYvf85tPfdwLL3/1R7/wG/KfLHs5KDoC1hU5YyFz5ZRMcTP6d8fySTU8kMN6BC1wNu5et6w+bT+9J8alZy/lzgN4zZ4hjuIhBqgay0PIj/1mu8lNB7O2XLzCkKRy2tiWZ8YEN0qsj4AWh9eu37p61aHm5azKSRSKd603vFpvQzjeW862u/Xh/kHOY+MXY4rO2sWePd20GYo30AmMg1gSY8El9RY0PFdNJKoABWC1gov7wTQway4f7NkH7i5P3z599NHd07cyQaoMaSwUU1XrKkdtOISQJVXD4Js6hOQdQoEAGbow6daNdVXDR3uzS81FQ3j75ImT1e7Cjeur7WbX09lKb9zm2+siUIihCGhiIMiphFGqmlNUVWDSOIKoIkEq4pDVpck0su2SY3LeAkBO9om4PjndbHeLk1Xoou7X5tLh5Xbe+WpBmM79yCBx7HS37Rqq67ptF+v1rabZjzkQGZE4eQ6ttefqJp6DmQuzAQBiUEUQEpUsKqACULIwndPxz2URBTjHamuMedtv+13ZW6q1lLbJ2jYnybkAaIwDoKhqVXPKgwjkEQhyzkqgCXCbVCzWSUqGrge2sW5814UEkGUEBlSEGbz3Qzc7v/7Bhx4YnzmN8aRt7hiGW4mtTzvExdr2x5pOjuUzXuhAtGNaY0ZXLzCxp30nJZaDhq9W3pAgKgOJCoHGKLVvQIfGQbMoDt3Boomhj5qabApBQ3zvCy7dWNkocLS3GMcRIqAhVV3uHRSRruvm87kiOl8T25xlmsG0betdM1XxHuzZ3a0kClLAs6srOPPZRRj+UlYOAIZQxggC4pxzrqo9qYFYxjHCSQdTq5siDj3UtemGHarBiQkfyYEaaxlRU1E2zw/xmUmhWOvqtrpk7/F11yeu3O1NPTgXCQdrYLNDw1WHQ1FRwZjQGBNCQgJBkKmQAdUgMEMSyQkZ0ZIrMaFXTdkQZpn6M80zN3eSvWHVgz1bcya7z+jJIClgYVPGoQvDpqkXk9wOxFLAGT9BnJ/LJ9F5Ofg0/gSQXMK530mJ2YiI5cpCZYhVoUxN5RgmghgwgSgDi+bN7uz6qhuiXm0uhVJiKGgUEdu2FRTrUAuT4fVqG8aUIYZRGm9OsYDVvbkxW9yMiRDB6vKCJ8GuG3OCQQAIU1KAIgE6B+9699iFZ9/y2rteOVzZDNeWYGQHVyqoWGPJf7zl+++El7o4emgJbmT/p+vhU+7hyuEDUh6IcDQ3KYYkYNmklFtroM+eELpQdnrvATnG6Q8vUthzQj5q9t9/41m2d/+r3/ojSzyv7JhGazAP44XLl2az2Vk3GO+qqhJNiHh8enp0cMDn9hqqqsY5l8Z88cLBtZs3hTGDqhasynzO2guUv3g6DeJ6zMOIw9DN57OLy6Vz1cWj+dX53uXF09fX2yefGvoeI+SSQYddwKqZwxAB10KDrWetr+aEbNlMfMOc86x2lNOlC3uuqV3VzOaHBwf5YP9ouz3u+vFs29/eboZuE2Uc0pj7i9fP+lurvltDP6RcTA6SHIQkjFAUtGAuAKDGKCDEMSgUAC4ChYCs6ginQ9n0eu3WjfUwrHfxbLe6crgMF1b7Bxcqro2yQuVM3/enbrZERGvZGJdSYuGJ8EV0HmE1zFZEVCcII4hERBZBQjdt9wjnJvspbHiOfIXnHKlw7l0d4m4XsjFgqB3CEJJO/+nKmZgG7+s85umHFEkCCVWMqWbzMhxnKIIElYccKUEZQriw3Js17qnrG1FWVRkJAMBiHGXu/e//WRC8/dWvOvgof7XcLkfuI5crXgFdIdOP+XWXrfcJxBgrGQtaU0QNkwnANSYS9ExZrXWqoCpQmRBzZUWNbUid9eTqNJ4RA5s5so9i37PefOjR64Koqt7VTRuHXjxUi+WciFxd1ZZu3LjR1mYyRhFRyX/h6PHe9Riqqpq4WwLqiySCqqjLNKL85SHKBCEoKWtW46q6rl3VODBDHpuZbav1s7d2jz4NpJSioJVut3NtO6ZiSXjgklo0ZJAmT0UIwaBUVbXd7oZ9N2+MsViIq9qpzqypjWujlIox5zYrhEW/XPqrXTOM212nZ2dp6HSTzGaQMWCYWJwCiCCFE05SFUgUEVBDLGCZs0pKhck+8fSpjL3FK8xsnXGVNw06O9OibBsFjmlk4xmBDEPB581Qz3NxDaFD0im1RAyqmktiMhP84vzORDR9g7V2cqFCAQ0BDQMTKqeUtkN//fjGrEU2ulunPo6ubpLGbgSL3K9We4d7x6cnxL7vogjUs2q92iJwAIXeWoqe8QSKK7w5LWW72tt3TWVyl5umNiXdXucWfCUBObOWP3j/yR++f/UJL539L684+sHPvHP29LUbMix9TqP9uCXWpdrl8cDAaVru06ol1awzZwvl543C4zgYY0RIc5l7YtHhdrx0COq1tkctLNUGdI2p7T/8f9/54x94OiUEFQEawshZocjhxSNR7btuNm+2q4EA57M940xVzwh13fW+4nG004er/GzREoIhiAlvJ7ACawWwAPkvVtACUjGUUoRyn7Zx3O3P91xr9+ezw+VsN/Q3NtvV2ebeq7fe/8HVjVsImhnsjmJ0Tjdd20q9cVXTCik7m1OZyB1j5Fsn3WKxYBrmqI2zB/sXhtqPQ7dIcX/OOZWcc4llLGHd9atuNY7VNoTxjpD6vNr1YaDVVo53METsRsgJJBVRIrRjKRZURXPO1sCoyRhGpC6F0ckzmsa4vnzW3D47fHDUKxfi4T4a44CrnHMJfRRgEBAtkCxWgGLQPG9XMoiECMwwVYMSG5FciiKWCVuqCAow7VbPm6VRdBJHUdRYy8n2/bjtdsTnRAXVQgylCJGBLCWHrt8g8G47qpiUEpuwWM5Wq3LoQwqxWdqzs0QEMw+C6CzFmKuq2Wx3OaamRjtAlKAMUKkLzmFEoP/28PrZkb7n4+943dVXHJ398Sftw5OdtWVIhJbRMt7SHkVnNYGopYKqrJJAQKadAEpWYswqqFyK8Sb2Ebihbb+59/I96PYfe2b8qfdeE0YCmVrHCxQdS2Vs0zRT6nwcRyuyv79fijZVVVXNZrMC0en8N53arbVZs7eQgwDakLIJkIkNl7/8gIpA5QyiDDnMlABFQiqW9mb7kchaS5WZO4k5pJfC7ePTlKlAwQwZkmUaSxrHEZG4qpjBOaeac85IIKLr7dBW7GpvUC0hsnW+JbZMPpaQc6airhTHrWcT3HY29GtEYHK1k5QXy2GxKbuAt0+LJFbF1SpHCTPPKYugIEDKwAwpFUcmSmISRG8kjn24dmMz37/Q+FDVcd5WBJpSxJIFo4iGEJCBtCD9BV9cVc8RdmwNApgiOafJVaL6HGMBaRIyRVMuGUAsmcRaHE9WZ4RRc5GQus2JgyaktBt2ZCpUcMZ46wrkZjE/Od4qGe8rr3RWwvqEvA9HC2oY5vXisVsbY6AKtAtl/5LlgERydtrNZo1l7frh6IA3W41JTITaijoSUOngmWubr/uFswcfdG968ZXXvmL2htu3+mEsSQYHH38B/ss2qYWWxHl24Iv2AkIFRgPWIrlkK+gVKmFBvbmll9RQSWXw6OrlK3nuf+bd73n7bz0RASrRXoFQi0K/7ReLhVjvvPfeE1HFvuRxjKEfdnuHByEMwzA0zbz2hgEtSgYYx76qGgICq1rSdgBh7lMywKpCgIpggQBkNtPZDBa1a/wiJyALlTFJUrvcm+0tD0Lu55cO9m/fcfN4zy3f9TtPHp+x9akfYt1Y0bxjIygApbGz1jkRU6BozjKEW7c2m+7swurW/UdH9sJysdwrWXPOM6ScCqDmHEMIoQ3L0I55HLtuHMcxhKM45pC6ELswhhBSKoXE8N6qS089fdMbyFn7AWKi1U42vZOcR59AYJnBxXKxxYOWb6X8wYefzP3VFPGOozjf2ycwMWYjYwoRABgN0rkoqarIAKrm/AqPAKoT7xkQVVAgPn8qgnOPdJ6ynRNtAoh1qkcSimOMMZYMhnQIYz8OSg2ck0e5aCa0TT3v0w5KAIDl0qSBYx/2jvaH4YwIrAH2ZrPLuYf9jF0vvskqtDmJiz1XVdzH0lROUiRUAEEQVGUCggJgH30k/tPbz7zxoStfcZmP9l9weu06dls12u/wjhaNYkmQF1CyVwhU2GcskmMC56DOpmgOyNs4erJ+/16p6hWV33zs+Oc/8FiYazWAZNAp/go0DOnowKr3Uy6RiNhZi2CZAGbyHBA4x1BSVqGYk2XjnDM5Ws+7TUKGItjHQhWexz4AphfZGmiqUhmeNXVleNa08FyEkoistczKzqPB1OerR90L7jf9n0UpZGjCaWuM0Rc3hr6ua1VkZ8MQmYhJQxyGEAzI1q339tuUEpNjNgTCjgFAUSpkVSWaOagsu8qPQxhmZTaOI2w3hmxCU2wZzcjGmwpRnEURNHHEEGU12GvPyskJpliMshJIwcorcqyKPvlMbmcntUdvaleHyVEPAOPYP+85njZ3kRxTtNaa5+ZsaIzBIlPOk5hBRCRO621RISKFRjTmHIDUshchj6ZoKr6EEG6vTrsezCIPu5DTjE0R0JxkxNAPmxhzTMkYI6lY70+2w9EhrU5BYF3PbQ7dYg5o2fdyKhCGjEaS0GyB0dPpST9fuKayvYwXD3wCPNuMhsFYnFWcixpIqdDZCn7+v978957twepL7l1cODr8+Kp+xeWTvGOVcJJlmQUhlwLZaFVbTJWzbT+eCeeR4fQWUA2Hd7/4Gt/xR9ce+de/d+2J0dx1dPGwG858Nw45dJIBFWUzQNM0nejEO6/rmojYekRtnbXEwzBYQmSzHYK1sNuOEkoI4eqlK5cvP358eowCfYR5Y3LOKAVxogowU37xZX/HkVy9cPlgubdcLpumaduWyEwwARQEy+zc/t5FttlVTevpvsu3f+MPbq47dgpAZTumfLzaWyy2vG2tderaZj6lJYcxEqZrwwYA9vaPrElNa5w1UIxlqwhEIfNgNJFQrbb1837YHMDeEFPOcT6bDbttlP0CNYrmEmKJl2oPIN63uZQujhL7Z+/ePXtz/JM/h9O1rgscDNhU2razaHe/+whc21xbrde3V/3L8+H+fHmo+3a+KKVMxTqlFGttCAFAGuedc+YvK3BFZaL4qCIRlaIimdioik7VjQIMrCgF1FgWEUIuRYKkkIqAAtZdJyH0++0SlHLOMe6ISQqwhSGktm36mBEYuTjHiOS9C2kghhwC1bQwtuSoYJ0HBNo7oKGn7TqrErELQ8DKOwclIwKXkggJDNlCLTE4cQpnt/M7jk+Plv7995rX3elfuk/tIE2Kxs82w7FhKCpNzsM4liDGQrBiClUXCof62jr8xjM3/8X7Hu88tw2zd476piMoZHspAgo6BkEmw+cn8r7vEYkVmtqdk6xSJNAcUwjBuqo8x1L01tWNeQ5sSF3KZDlrmcQN0Lz0cLRXFm0zmzWz2aytZ01VG2POOVkiZEhEjWVmctX+Yr/cMe5nLC+4dfqBhyVFAIKYwRJttj0ZTjlMgbBJSQTkkvpU8jMnq27YVaNnawANYwYyhMxslQuXSGocGFVXStKS5ot2HDrNyoAJVcBa4VHaFLbzyhgEJpekJJmP45jAeT7ddDsMcn20pRRjAFVmhAbw+EQecwP7m3sLzELe12TP0UnTWjnpoIjTa2zOkceKUEphouc043PgvEgu1JdYAMCjYgCDJmk2pWgZlIyAgWFcb1ent1fd1tV16oZoq5oIAVhEJWsImcjkPG52sOr7PNDcibFNtUiqOF+0IYTGO4v2JG9Fw7AGqUsMUNd5u8PZQuaHsLolRezM0xjT0AFbQERfmWkMK1xMyAH8WQwzqToaN7fDO2/f/Pd/7Od1iHv04n1/tQ53NWZPzZ5tD9B09Yn6Mt87onn75PHT/+Y/DU9s89/58CMHjTtofGMiKOZ+Xdc1NDwMqxkRiGaDwzpCEVdXE8NimgsOKQ4pLFo/jCM7a62FGEFyDN0gctJ3UFlrzN7BItGtAIKlUAEIBQEYALUsG3jZvdXBgVy+eP/+8nBvr1nM5lP8NWcRKao6xKFtW5VEVb1HjTf3LJu9ankce3PnwbXfef92dQu6PoU+mZqHkqzl/T1smsqxYWYCMGa/xABDfOTJ21eSznfreeuPlhcWrmHyCIaVXcMioFpCir6ZEyqIEljDjQ09axYBML6EHS4q8radLSSHcQiI3I3r+f5sczLbb/vHL569+0/WrLA6Q3MhDysMAFLg4Wv50Rur7TY8cMcohS7GsJwv6rqd6GjMWNe1McZ6Z60152QcULTMxFNUT1Un3ljKETJNg5AiCgg5d4gIYDExGFDMuY/bob+9GcMoMXqm0U1XsAwgUjTHEhm4ZC4lG3JiUt8DU3RO5o3zbKqq2u06tlgvsCo0jqVPYsAiF1QJCVpyRaOrSrbCAMZxjmWXo68scc4JjOGqpX4bGoN7bpQdWGfXKdUp5uTLGN//VHh0Vsy+1iAXlieXPT706vseuOfu++++n6Cljzz+xL/6j75OswFaVe9dH8tsZlbjsJg2VlCw5EQ0gzFYMKuIMTaEcfISAYAq5JwJFRFBokguqKoYEsQujBjbql7MFsCShRGKBUbUooJITHK4j/N5ONo7nNXG12Ct5XNaKwNk1SICiFOVj8khW+eMK0yLg1m883LbjXsvfXD8w1vclTQTTIhBNecc40jMfuGZMWcwjIpWaXzq9ml2fEHmkMvebEwpiSNQUUgAgI5I2KlKyYiKjFYApeQixlQpFiIwTc3MzjlCgrqaV1Wfs6+gsfWKKw9PSmmO79xaoUlIf3zjCgcWZAFT6MMfyak8cfnCDCk5Y6vaHrT7AKSk1rqpxQYVTJSCKgTAGZTlObMTqCoiE07MtwIABbCUhKSlZMiZmaVAltINZ8/evrnuAhvJOfu6iiG44gaJBTkKiJIhm1QAcLvJAtowqC2+Md0uLxbSOEt1G2MOgyLhpQsudnirLxC4MGjC4y47hjCKj3bWKtfaW5ACYcy+skSZGFSLEchFL1zky5fNtduBBAKooTBmXlSFEywCJyjUuSsXL33aR/+VOy7e18yOoowUzEP3mxvP6OE9zfHpNkZEa7Zd55y7eXpWkfHWr3NQZMulaQgwWkMp4xRlAQCRPHR9YxcppbZtALVPSQTPdmHXjVklh1BX7s4rl/f2682tAQEMFFUgAod69yW6+xJdOfD7y73KN5WtiEgJVUuMGUAUSoyjc9WUHAcAyDg1UB4cXkwlts3iymVz+crwb3/5md4QjmIs3Li9UyizggDUNNW8ckXibNbmwoLmmad32y3sDmjmZ5KOsTKz2azKVfGtOuM1I+KELC2gnh0QHrYzESGaAPtlmgZYa3OWEgbQAYWIcztHxbtdfcPILSyZCHMqfZYDgEFUAZLo7duyOeWhf+TFL6SP01dfuXBnadF7Q6YSAWtZNU1E8EKaCVCEpjZEAEASeK7KEhGQIGc5Z1bnOHXUFy1FRQrsuvVut5nsOAjMzg9hmzWhsiAx2247gjoBAyWpcBERhlxoGDOyhhBijEgIIJZxCCXH7JAMYoiSQeq6CjE4x9W8hFXqRsAaQYmNNsYWiVKQ0ABJu8Btr5tUZlXFnAQINROCZbAWQx9b34qkg7YpZBXYz+fQeBQit3/nnXunt0/mjd0NQAbZ2CHlnHNRGWMCJGZOAATcNFJXc+v82TiUIiQwFalPTBhmq6oASmRKxjHIMAxIjIhjTnVdz+cebg0AU5UYgWjb6sFM2wrrup2Ivs+DahWFYLoPFCZJKSA6Y8gYN43IWYGtWSwWDMFV94x8+qoXXn/vwwUdp1xSybtxILVVVaWUCiNbWySQYUmKiEMfxkVzvO4ESq0tGUOsjisCVSFky1ZyzqBJVa21pARUmBlZRCLoRIxKuSQJg7ocRaxYEVN7yJW50MxS3BWF07FoKhc8RAsFQYnGiADwkcdi08I9l8+WB/vb0aKZe8OqkHIUkZyjwZwLhKwImK26SfJQCFnyhHmxuQCAQVDAnDMSS86iA4GUnHOSs9Nb/W4DRQCMKjJVRXa7FBpbh5Bs5aNsZBhV1VpDSZEwCnUnMq+1vUiAPJs1pSgz94Pu7ddaJMThQOl2KRyhpFxA11GpgyuXPRboYgIAZkqxMJsw5JSCcxRGqRu7C7Lu+zDAJueFQcNkTNkNsH/I7b4fbuc7Lh0dHz/jrbHVvrollW29qF730Ise/eB7msZdgrlideN021atEsaYxyI5lT5BEJ2T2z+EZravwpq2KjLlEcM4GEXHZsoXpVRiHEPlN8NIQNbalHmXw2K2uPPC/LEnVqqAAgTgnd57tz3ak8WsNVyjaN/3jFpKarxzlXVoE4IxFOJgLY9hRJwzewAxaNAQAOzv3zmfHbXb7d7BDZ+bC/d/+J3vPDbgtlhyQtkbkc9Krivad+R9U/fh1NOBhZCTPHNt2O26g0Wzvzw4XHR37O3vu7aQdQrEjgVyljBsmaqqqlQF0KiqYVMKxXEzISQkbUGl9AFPtqsluAhBAkg5XC4UUooFmvJ6D/oSCAJDglhEE5tKXMu3b5ePfORRGLuX3vdiDbQ8pJI1xKHvd7kkUzRPB3D8iyGrIipNyDWF51FKz2t1KoBoQPPURxtSFCAprKV4Zwy7MKbZvElZhAiJyfiUc2382PVsMBctUNhhNePZrIoh7M33hmFAa3JMCWEi86gpraFtkpwUChCD9+b4OOwfegWrGkuRUkhVvXe5RCJg71IsviEt4jxXpRijSqWtqzGPjeOZn53F1Xy2t97cnm61zOzMPDb1fLavRqTEHJOZzciaJKWk4r0fw3CevQZBynXdDKFHqIwxUIrAOerSMcN5GwtZ61erEZ0iVYpDSokVDCACz7ypDMQEhGAQZjXMbJlXdVPVTXUO3hDJRLaUlDM6a0tJbOzUNJBS8X4SpC0iEbAQohpjoWkp8uk9F+enu0sve3n/4T/thcGS3/XRWvbO9LGYCq5d//Db/tHf+8c/+kvT1SJL2myk5IE4MKSWuZ63TAthYjClFC1BRJAI2eP5I1Amcn6Wst1uc0nOEYaE1rrLR3/67j987QP3GjJ1sxdtAeGYV9qnCw2pgiTpBykExqAAqOWLCz7eaYJwY3WsjFE7JlNSzDEggxHJ5xUfjGkcsQiSIYIkRUQEhOS5BnNEJC1FvLVhTFlSzl0pOaUxJ+hDiAG897t+cNYi8DjGgrje7MgaMJxzbvZm4zhyhjDmkOHWWfHSveDugzFmAg6Y2oN6sw5Ihrh4V0s9SGlH6C0gkRaVgni6iiWTdWQMqWjM2RKwBQFFzQrSB3aGFvtuuV+gxMbt3zg7W874/rvuO109c9+9V2bzQ19dY7bIhEQK0i6v1rOLly4bY2m5aNf9AITj2MegzIhsYUxRpSjOKmnbuZLsup6tkZTGlEoploz3JmqKIZQQ61mdctDstpvx7OxUVQ/mDahxlZ/NZt5ACkAW6kr3F3Aw94eHF2pPDorlyhBZY0oM9bz11iky89T1k2MGCxTj6Ll2lc85O2cwA7qMapq6An5JdVfFfuawWHziAx8aU0prSRpSEXr8yUfe/lPf8rKXfd3ZcOKqCjUWxiHgdtP323x89vTRRZdTIYL2YFs3R84ZlHEU9FCBJ2qY1eeQSlHllWcndVUPJipWzstgHvyszyRsLyyXx7eGBjr02wbv7NI6xYM7rMJQCeZ+7IY89LmE26cf//Vff/u//cquuJN8kscGeLvp6aWf/TGP/pf3N4aNM6koqZ47RXIWZCRmQlVCYwwyTcOS51lQRMRkY86Kvegm5W3RXYyxHztmAoKUZQgByQKQc64UHWIKIeScC2A3jCHkGHJBIwKW3TpAH2OI2VosSbx1qsJIu22xjpHUVoOxhKqI0M5qY4gYREsuJcZUSjYGY8yajWQtSSbQqYjAKAtf79ct15gTWGu9kXGI+wdLkeidRUTgc30RiMi4/f0LJau1DkkIixQUlH6cMJxqiQn46NDv7132vm7bdhzHFGOOIcZordFc8hBijGjQWuNsJVn7Xbfb7AyzN9Y5g8jOcF2xQbQKraHG4XxZOc+Nr6qq8d475xz7pmkM24n8ZowzU2H1REwGVMKUioiM45hyyDmmFFLujcnOVU3rjg4P77q0D7kKMWGBdXYo3Td8++evuvbv/uA/e9nLX77XeMt7ahprvfdWMeect6vdU2e3bnbr3W6jeeuyjqoeslQJqwXDoVEj3oBBW5w41mS4WrSLC4fzC1c/5WPMAt7+jn85jGZxgaoj5+u9qp61i/22PspotWVqF2IOilssZpfe+N3f83M/837f3uFqc1dz8a4FP9DS1RfOX/rQ6y9fYvIWuBFuzys+nKus9cA8jTonFC0RTYTzvzA1T149RhGJcez67XbTdV0XY0wZjGUB7IZQpp7GLKJqDDEgAAlSyQpIKYMClqglS1TYhjSWEFI2SCDZMCIpM/d97703VhgQAHPW3a6bGFRVVTGDtWytqSs3dZmpEJGdWrxKgbNVUNWU0hgHRLh4tM+qu02cNa7rN40xIllUAUVAkdn5dj5bqmrV1LPGtbW17JBgor8SAYga0AsHdV0ts3Bdt5qLpFhS0pRmbW2MIcByXupMRBRC6roOAGKMVVVNf9e8bQyVCKoIxqDzUFkyrM4555y3tvZNVVXe197X1vimmXlXM1smS0RaZOK0TfCwEIZh6FJKKfcxdSXvBAwjtK6699Ke4wwKO3RLir//WH/Xgy/9+jf/0N/7ka/9a5//vUPflywA4jywHXOWHLthi5v1brdNq9P16vaNAlpXCyH11dXWLtGwuoqSqSwIGhpTZdzSH1RoRrKmnu1fOLr28CN2b2ZMdeCa5exQ7ZEzh3ZeWZ07MxfQQGhL9eiff+TCC1/72Pv+a8zZcGXcQT2fn/Xls97wVT/8lr+Te2wW1tfF+kjOeMuO0ZAa7+bgW25m7Cv2la0bY50x5nwd1YwgJY9j7MLYD0Pf9/1ut1ttzrphTBHYlDiOIFlSViERyFkYsK1qJpsBwaISOmdLSLbCBILZDp3044A0C9KPJbbzKqRonYQBiLBpGsQ8b7iuWMWEqLkgUqrrKufCBlOKTUvLfWssxpyGsVS1RbZQkFUO9/bHs3jYQAwbnjeOYd7Oco4vuOdqUlC2ItlaHxV8s7+3f7GqadetZ/W+AzrcayVbAUHBAjCKtA6uXrlDTb5+8/hstRKEPozGW5IS+i4MfQIxlqrKoyo3/tnrN4Ywnq6P69YJ2W2IfegXs8XesqkUnCFny4Fny5W3lfd+f3+/bVtrrff1fLZf+ZlzFbOt67apZ97X5zcB1XEccwwpDpv1cdedbFerOPTdZn12+6TvBmvme/Pq0oF/4IW5T7DZxS/97i/7mNe8+G0/9OMve/DSF3zStx+IP95uAXV7nJh0u12AYcczRfnT9z77OV/5aa/98jfIhRflnJHR15cv3OfN4qBGzKL1rM5aOYu+2gumymBS2xpj4frJL/zUu376h/+mZyB0Z1QNvBTCIdnl/R/16q//9p/+1T++voYQ5k+c9V/zvW/7ok/8ijd96Sc8fZr6TUsoqHuv+6q/u7Xyshcd7F2sLpAcLfyFeUOAxKYittY7JEZiYIPI1tTT8F5VJ7d/zjHlMcUhjLsYh+e5e6J5KkU1hnOS58GFIlJSJgUiUigghQCrqgoxGUOpnBPzpHA/4GpzLMVMu7P3Tgp3u3xOcFUoRVMoOeQwpJwkxjIOCQCsNU3lJgCtq6GuDSNMvGxTU5bUzFtGcURF2DbGWHTGA8r+/j7yNOZVeW6W1izb5XJJcO6WVUgGuSRgIlVQQkdKJGB8SWMYx4lrDog5R50Yjueg7kzGkvMCOp/Picg5pwpJi4g0VWsNIBGxslcyBGoJjYiElM5xQwjnZDUR1XJ+aJmqMlUVgABVS44BtOQcScEgkUJKZRh3ORWypq7rOy/NZ5V91Wte+TEf9eJ3v+cj737/8ORTtxcX4PjsRr8bPvz4ta/7zi/e7eSzv+g18/1KUcaUf+Adf+PZdby41/zoD/9EGKIzzlbNwYtf/uvv/G01/t5PebC7nZiRGLfj6Z0PveDSiy9UCaluD1/+gv/0a/95vXlGbQohvPqLP+fl/9MnG8G8aI5e8aq3fMG3fu6nfEJjqicf+bNv/wc/9v/88n+YD3bMvO7ksRtP/dEHHv7or/y+h9/7xz/wbW9/+VGfdrtkFMmQcQSGhSiBFCoFAZlQFNDkrCIQ4ojIKaWcY07jsD0O/UnoOhEArSwvrZtnTUNfkCAobocYUp44Kta52jpWyCGqqreWyMQYrecA4oktUA/l9nbc9qkborFUOZ9CrlzlPB1etH2nu+3oHSyW2s7o4MAtZk5FQLnvi8iEzAwLZyxKHMu8VVaALE5hf8lS4sntm2sFNzsYx01rFsu96vrTz9x998Hy4HC2dzCOMeWB0eSUAMC1XpEYUKBTiLt18KYs6ir02SLYoi94sW+bgy6Kp30qiqKTSDlVLarqcra0QEnLkyc3rz31zNHBgZR84eBKU7WGuMjo2Ow3s8uHFba6aOmwIeMNog7DkFIZhtANw3q7Wm83q9Vq13e73W6z2azX667rprdBIciopCBCqlz5mTW1MO7its/bmDaoSXBnzGzeVC+42L7m5aadyQ/84D//9E993d/6/jc/sfpXly8/tO5PHn3y+j/+2W/+uZ/7w5/8pb/5yW94+X/+tQ8aC9/2t7/ie//6P73r8OpvvPN9b37TZ5yub89ecPd9n3Tv13/hd37FF3/C/EXwA9/6M5cfmJPkIey973bfjSfVHS/89d99z7A5ft8ffeTtb/2OuNv1ReuHPuOHv/T7Oo03zrYv+sRX/v23vuNbv+KTZrN5e3Rp9rJP+Ilv/ZE3f+93f803ftaDr/jo4XjzxLVn37+6761f+Xmf/MWffrVdv+ePHr118zh1mlPvuJCCMLNhOxGXEVEBaRoaIRr2ExSPCElCzpKlMBsUsNbUdd34mURkC2yhjBMFnFS1qetSSl177+oyLQa5lFJiTESmcVa5FBHNasgqUkrq6xY4albjDKEZh0w0lVrB2CsraRTno3VKBFVlc0RSSBG2XTbGVNaMgzKCKixrbiEadr5eIGjreehNVbmSCd1w0PjFfM9wU0KHSlnKJJy0zTKlhGiH3ThvjzSNORYyxAhCPALtz49M67vdushuwm9HUWMJEQnQuco2zlZ1TnJ2tt1sNqrKxrJFQE4lGazC2IOnhptD0suNeqvsaAix7/vtdj10677vASCMacJ7rDZnq83Zrt/2ocs5pxREMgEXKKpqDMU4AoCmEQpqAYMGUUsQzOKNX7TNstb3/u6f/eF7H/2t3/ztv/8jP/ft3/kvfuInv/Lk1vaX3vmj2zW8/jOPPv+NPybqX/zKO5949NmP/dSPvX2z74bd+9/zVN/FlPt3/Og/A95/wys/3r3wantw33hruzsZBfH+z3tVuX1msf6JH3r7533mJ1186Mo/f8cvo9zIOd3/mpd86xd841t/8q+/65d+rwxB08HnvvGzUGw/Hn/cF33OH/3+7973wMF/+oV/d/vRD7/2DW/67x964i1/6weu/9nTl68c/KPv+b8xnr3ph7//kdvPpBiNY4VIhmsRQrQgHiSlFGOMY9gSp5T7rGOSIgIl55wIQTRvNe+MZ1+72WJW1dZzhQrjDpxzzMYab609Wa9EhIkUpfGVomSCibO824btJuVECEQCo2oOUiyFbjf0mdHsTlcpj6XoMGZrrUGXs27HXNVOA3vGMQgzNzOIJZI1arlLZUilqJIh1/hC5Nq6acpizgywf6nNZGPcAHbW+3Z2dLB/RZLWVVViISwAsN50ojSfHSz3j8aQV9uNa9qktNn0iDTEYlHuuHCoyVTWj9swzRurqtIiqaBxViRjliGmW6frsYubs9sKRTTNZrNJzQY1/VAyKHu8+woe7dP+oi5Zb96+fWN1ejL065AMyTj2MfXr7eb6zWdv3r7xkScee/ypR2/evL7eHqeSihZFEdCYdtOPHcNu22/HNIQQxhR3Q7/p1yebZ1e7HZv9dlFedZcsgS3AQU2rm/FWzM+elf/1x371yj3Lr37zTx3a+Na/+X9dtPo3//7XLvBTf/33fvzipfpXf/m/fPhDx0L8ZV/9mu/48u+6+jmvfN+/ec/7//jPf/D7vy0w7N138e9+xXd84htec+dd+xdN062Ob9y8+B3f9AWbZ8+Ob2/t8u6f+Y//5Nu+5Rdectc9B5fv3x4/+XGf+Iprj/aXX/2a3/zP737jX33jF3/Tm1/z6vv/NF767i/90rd813f+/of+/PO/6X/6G3//H7zxzQ81L/urn/zabz6cXXxmffuZW6vtEEg1EQliUUiqOjkTLRLkAgIlSUoBVXKOgBkkaS6GHAMbZSrq2JKhXIAMTXP8yaLvjU1SQsmCkGK0QIamMj9GBgWcwIJTJZwoS8GUhdmGFBWNFGxn1juXUhrH6JxBhfWqByyMpmkx59FXNiVAVMWpLxQBAFVKKdttyNk4W3WbUTIwynYzdOv1om2b2vnKWl8DYImBCKYYy9T5wsb5qvF1k8bkfR1jJgBQEgBvgBljKMiseRptoGODWhTKeeggFwFCNsx2s96FEKw5p/FPIYVJCREp84ab1kwQ2nHMZYyYUs38XLyWpiP+drsdQ9f3fdcNMY4xhJJjTnEcuhDCdrvdbrfDMOx2u9V6ve27s/XqbL1Zb7bd0KsUtrqoawtqrQLhOJT/+c0f/dM/+UsX9vEz/8rLvvs7fu4LP+/ln/TJr/u3/+o3H374+qe/8fNrA//ml96dUprND556+try5S++dM8Lfvyfv+3n3/aLD7zEv/dd79uun1g2bv++y7nLd1++BNw89DEPpnjjf/zGu1qzoWbpDvZ+8f/4Dz/99/7pX/mUjyrHTyzqA312Bx5P4+mfvvO3Hv39d7//V/9A28tv/da3X6T153/aa3/nF371yd/809/7578uy8Pv+5p3PPVb7/nGL/mkSmcEFtSNPZg8BjYuSUHUHHosAVMZNU/1TwyaSxpCLyVIhByixDFjzyM459haAIql241ATrFwylpKmDpG0dtxTPN2VsZBQykSUyoKXDcUijBCUPGeGucTxjxob2FvuQzxdBg1DHph4barTEbZcEh50boi0neFrTIRoWw3kZBKKQgc+owEBIjEY8rzyt4+3b7shQ/2274lLGNhxe7s7M47Lt99ee/S5av14mBMQyzRUatihz50/XYMnbKrmyo++RQjGYLKmt0gRIgGXvbg8srV+5595uz69ZsZdbvdppS8M57JWtv3fdMsupCfvfVsCOnk9s2UxFetM77rNkQE1oUQqqYehtAa3yMkKbEPwogVtjM3n7vlws/aJZGJISPmYdyGEIaxK0UQuK7rkiEwDsPgXTOMuevjEIeUg0GIqJt+B6IhBBGpqsY4fOzxZ976o9/1zV/1tl2SEcyHH/vZv/aGH/nI9acuVuazPveNf/07/sGh2/vyX/6+d/7HX3nTm774NS/7ym/9nrf891//1c/47Jd/63d/7q//hz/4w3//Wx/7tm/45jd+11t/4M10992v/Qz6nUefukSzF92Zv/t/+3F/R/91n/s93/Vln7D/2leEP/iPFz/58/7Wl/7E2//F3/5/vv4n3/j5H/3iF7+ou3R/fO8f3vP61/7QW37mzV/6SWen2cFQf9T+W7/q73znN71xc/MYLb3hjZ+ekb/m+77qqz/1G7756z8FOk0sMXQoBjEDIeU0lpxFcpGIJaQ8xDI8dxtNKRUQJeAYY5EgJRVJWZNSSRKyxrGMOQsIGLQ5Zzj3g1GSkrMQmVKK6FRvU6rK77YRgJgBEUOCnGSM2ZANJSOiQeMsoRRizVnZJEQoWUQgaa4bA4xjEElkjLeWneeccAwFLLFxUXSSbxWhaXF/f//s7MSwWnaqmso4a9pZs5zP9riqjKtiLlnOrRgla07SLto+DE3T1O0shCFrTqolqxa4dGkZozCoxNS29bTCGSQtYthlwACy2qxDSJPYfnjhAjNb56ZSqylyGENWxVSKNWStdYYt0bzhWeNmdcNkDU9psIKIzrmUJtdITjmknGMuKZcQczf03dCvu7Oz9em6251u12frVd+Nm1W3WZ/ttutuuxl38au+8St/7Tdv3LjOr331nf/+l3/gu7/5p/7kkUdtKaL0lm/8sdjb//a+n/+Sv/IPH3nk+PWf8Kpf/JXve/vbfppNLmF07cUPfODPn338fT/7j379rX/7r22PT+vFuFmHp3738dd98qsPLt/x/V//vUrNPYeXu/Xu4PDwa3/wb/yNL/+Rr/viN/Tx1pd83es+8fPeODYX3/Yd/4SbvUceHyoOu/UKEc5ON/fd/2m3nn6aiOjSAavJrfPOXn7RQzPPNgzNfuWo8maxmFXGzosaM/S3yFRQkIWK9lkzyhSYg4lePik9qgrYiw4gapyF2bwiP45jF9a7YVsES1JvWZ3ru4GZQxnTOBHvTdRCZFJJTAiM3S7P5n69CpWjlGS7SYzoG+q7cblXNdbrXFerceiDseh91Y85psxJBwlCiopjkf4sG4+1hab1q+0YBskxtnuUd2JqFk0p0dn1U1Pb++5onr5x7C1kdXddbi5durBcXCB21cwMJzeRDREgm5DGuq5V9U8/+KEX3XPvjVvvZuuFxiK5ADLB/RfvzSHfunXLIw4xIBBoaRez7e5szhaNDf1Qz+cxlCefetx7E3Msqs7a2WwmUqZ+oJxLF0aFzJYQdHG4rH11OJ8vq6qZz2ZVrQAQp1KsLAXqxuLQ5hK0FFX0rg2pL5LibshZ4rjbDF0pmsIYcyhT3yCA8Yx5zDn/7P/+S3bx4N2vetX/99/f/SVf/EMtpQaghPJEV37gB7/s1a+8Mqu/4GNfacqYbwzx0z/2La9/1REH+rHv/ReXj/Y+5bUvfO0nf9RBjMdP3eYjfte/fPdHf8wrjj7zY3j/8v/8hm9+xw+/5R99/z/72v/l4x5/5A9//3c+tBzSt3zNZ+Tt8fGty7/2r9/3wd9+/A2f/an/+H/9+m/7np/4/q960xd+1sehgTx2977oge/6q2/5O9/5lbtdtzAKBzNE3azWb/3Sr/66r/wikETGWsoiGQCMbUopRlMqigCUC+hzWJFJ4JyiApMd3xgTklX26Ji991R5V6Nvy4CWDBVNoJKjcx5VpRQgcpXTUshw6vMYxRhDBp2zQXKM2RjMqoRUELsQnYNIMG67JIJIpUz0PZpQ+cwFAEpRAHCMJeeq4Qw6pjKr3fn0S3KJyGwUIReoCU7WWzCYzTDkcHjRzBqwvnXtskw96ClPDSkTH14mjoWxIlJXzRhj086wZIcwAtQOiKCPsU9hs+0m4Grbtt12m4axuWsRS1HVGPPJyUkppfJtn3JJyVpeLBanpydE5L3P/ThNlYnLcrGo29YZP2/mbe2c985WqppCRwTMFnGUAtbaXMK0Rjxv5yOCUgYVnBoTC2oqGRAQwTmHBJLLkEOO9PQj70tb/ai73bXTuNmBASxF77776rd8yzt+7d/9j3vucuMpHh25T/+Yb/+oV7VpGCmYygRrsID+9n/9H5/38a9GN9S6uP/C5d31WzW6f/uOn/3hv/Wm7ZMnf/7ws+tXXqTmys2H/3Rx911pJU0z+/kf+ydf+6Yvmy2rs9VJVPtNX/TZBSNS6fvBWXt889Y3f9OXnB0/a1xD6AERUQn9F33h5/abdV3X1npEBrCqyGQQ0aR+S86LwHnaGC0ATSj8SRxWAgJytmLTqMulpGo2c1Vj2XrAxu2DmyEMICoo1kDtPQA4siFLynm97YzzVmUyjCpEJBwHAUIkLQBAkgqMifeaauqcNsbMZrVCATXD0FvrPGtKYA2KdRLzonLkcZQ8dgCpaCmlgHEsxUgJFTti3ps1693qyuX9bRziZrh4z/zSnVcv7V+4cvVF1sycs+vVdgLqxpzX263z9eOPfQStve+B+2/cPr7j6t03n3l2UZuSSxfTvVd4KEPKkAELKKs2beXqKuVw4eLhdux33TiMI5QsmveP9lDSfD4fxyHGsNls2rZ13qNiSLGUUrJcurC8+9KVxXxurEe2nmkiMaFSjskYs8vB+7pti6pOQA0lTCVXVTMOJlNf1zUTsLNr7EETWCtlojraUoKoxFRqxxf2tW/p5u3C2VpICH6H42N/8H+86P7PrhC2JxHmYGP9wvsijFq0LUVnlYZx5yq78Muz076aVWbWGpPEsjj86Je+SFOBS/Zr/+qnWlMvD/tZe0UtuqwB0hvf8Pr19samB1cvh7OHF3t3QI5kbNNg33dQ8tn1p42riyhQCGNkpLri3e5UckrJeEAlSyCGLRGQMBUoIMoIz8eR/lIX3Xnn0hSncoanF9EY48Ege2qW4OdDKQlRRKwlybFuPBFozJaJAKeiEGstqhpiVLDEIiAFSoGpSEQEiFhEC7Ok89IwkTJRr6xlRmhaZgMxhlTKLsaUs6TSVgQlM4IhUCnWIRkjIiEXAJjN3frWWV3jvKV5WxatafZm1LRipl48sNaKiJYSQkDDZ9vtrRs3lsvl008/PaubGGPKBZkswNH+os8x9aPGjKJT+BCZ2sUcvS1ZLBAwEeP0C4c4ElHbtrvdbgrWAFGOUYBVdYxh1h7MZnuzelnXrbeW2TJP5nxhtoym8v68L8icIzJDCDGOOWdm9t4b44z1jp03tqoqtqZt26pqrPFT35oxTjE7b2vghZXKJQCwCCjwlm/4h3EAVlsKRLWpEIiPI6EbikpOUyRJRHHIstt0se84JywMCUspM+foYP7AfUeKpTEzmrW28mhNZeYOGTNwshQoKbIMZAnUIFhrXSnFuFZEpEzEx4KoopmmukTSJJmnsg9EBEvoDJMlMlLUVh7PjRHnUIfng3aEiNadP74iJeoIwdUepVjVXTekVIjIGDZEqGIcMfNqGFzlJGvOk3ukMFd7i9nqdKwa3u6KBy4lJwFPZruNjSMzlNbWiBxCnM2r1dnITIgZkQgKWawL1K1f9YFJLCER9lqcNxiLiuY0SmGKpW5w1ljFbhzDxeVlvtk7ggfuuGvRXJhVC8zIzEVELHvvN/3u7OyMyRCZR/7sT179yodWq9ULHnxQFOeLWX9zaxDnfr7bRQ0joDjnENF4W1msPGeBbrdbHZ8NKV66cEjOFYEYtFFlJBFZLvdQ4Wy72zPVru9St1ss5kez2f7+fuvrDDI5bj2wEhFh27aq6kJgFGc5pgJAm24T4zg6B/2mrlsmy40lIgJMKmSp8o2IWOaYYb1NwzCIRF95jZLnsU7gO4StDqpj/jcz8yYDkEAMwhhSz8lZ9t46aqoKiYhArfVkaTWs97JJRckzEhsqWfn22cnITXXyjLWX0EGlsyLR1UmkOHMgfJZLVh04Yle6mW+NxRCytTZaBxh06qwHm6NKLiKJAJHZsvPGTc/e9LAhIlnrQdFVdVIFwud39udPn3jeQUGARGycr9g6Danf7kIZskmMBFEQGZhSSpO3KOaEhmPJxrgssus7NBxjZDYpTSlYEBEEMAhZdAjQdRrHlEV2XWftOTvKWisCCETIUCwBx22YeV85y1NazWBKWUQtswggsmQgVNE0hjQ/mIddX3L2dT07Okpohcx0DUREZjbEotoNPREZpLaudtv+6Oho8lJZlJkHY0xVNSBYt+1UPT1tMoZRYzaAZ+uzDLo3XywX+5WfqVLdzJ4/QBtjphlviclaLqWcbTZ7M+8dEQHB+YqhqozTkkneW+9901bW2qlra8o2hhBSDimF50swnHN14/eq5qBeXJgvm9pZQsNIBMaiIW69qdXXhHOvNWOA8pVf9X8uQCwYxsLG2cpUpgU2TJ6wsCiSeMtohFH6LoRoJMmkXqFibfy83vvFd/yKyVVQFcCIiawR9WJnWCdjDi3MuASRjKyr4WQcdhNowViHQoZrYwxqIRXVAqxA6JyrqgaR9Txjdw7AMcjGWEdEXgUQEVm1IE75eARQMIQg5hyCpwBquSl1TaXvt7u0Ox7G7GrcxjhuYX/uhz5QXWtWKcUgD6E3xpTduINMoMu5nS14TMSmMHCO2RjKuQjibszdDbh8MOzV7Bq7OhuWS1d5yoUBcBxHdrDtyqz13RgygE4OCSjeu3HICsU5k1IEAEu2qecg5vqTZy995QHw7f1m/4X3PLiNwloEbUrJV2yqFpB3u351fHPd746OLg5X73rXu37tc97wBf/6X/7ry1eOrj11q6rtxbrcXp3eeenqpuuggKrWde0IS0zt/l5MZVEv6oN6122eePIjL335K5547CPzRd2NYRzH/cODKFqkYJZiQVW7cdX3XbusKjtXLcaIgSkTjJNk4tzEt6dSkjdVkQjjYIm3uUgYES2ha9uKFSpnBVyDzfmFEjTG8ZR3QxxEEVEnma9mb0zo8PSD1/CxR3/+5S/4CkRWzU6hpFwpKSUGZqNknKAym6xis2SjApjHbcozJgAAA3BzdQwX7/iaL3z9KF0NVmDh6Zw9SKDs5lyUjBVpioScklEbQ0JEIq7rNrPJJcVoyRBTVCFA46xa65VYNUvOpQgRTKIHITEykWE21hhn2BljmCwCIzChAWJlmhCphAYARAugokKFbAUBxRiTChSFUlQVQ0hJi4AmKc+d9lhEcpKJkKGqjGCtIAGAsCFVDakwueNVOR1zAcvGqJj1agCALDKbtSVrVZGCNK21npGhZM0JU0rGUAxwTkAQMIbGFJGNNdDMm/nCHB4uja2rqgFVY0khWWuZHACJyKbbbbdbRpotFn0/tPNZO/OzWWst1bUnFUmxSCxZJ32DiCyAM3a73V6/dXOz2dy6devmzZuVb4Zdl0sMIZyjFojLecmqikzMSxEt1tppCZzm+AT4vOl2OlwhTku8pb/0EXPKUibeDqIys7XWe9/Ws6aZVVUzuUgr5yZTqXNVXbd1XTcHy0vz+mUvqT7+dd/eGFdIEJAInv9UmhhHfwGCVFUUnSCSrKg5p5RSoVe+/rU/9bafYu1SGEspKDr92kiETESG2JHxyI5MRcQAUzPyVEnKbB2xYWOtcc7XZNhaT6Zi6xGxFMk5l1Keq0UUY623pmbGlIOUyWlbP38GnRhIZBCHAkgiOZeYc5ACliUVYms0cykhFmhaWxSAqZSkBR27kFMWYRVjbN+PTVOv1sP+3gxkdJ4ro5ZMP2ZFNMRSZNVFY2h3E/nmZrEARnZsd9tB0eXYGYulQFXZkJOEomQKaUhqLIkUtlxK8cZkyb5iYwxiXCytd/Vy0ewvD2bLyzR2CsRMKRlrLaAVjeuT49PV2Wa1fs1HvdpgufPSpT/4vd/92I/92Pe+973jICntHnzwjmEYbh2fEjvn3N7e3mJ/7/T4eo5FVbOI8zyO/dGlw6O9i7vdbrFYROmcMa6qhpBqY1U1SQkhFIIYEzNNuzaA4HQ2smYyN07phudx7NZaDyIyZ+b+5DipJik63R3Oz17sjJsYZspIBG1Ih8vFru+tr6zxiGhyvS67zs9mL7r/t9/1a4+cZItGISMxG/UMIpKz5kzGUC7TlzkgCuOYy1DmMcZB8gzl6ife99av+wff95YvOr1+HFPPQyeIKM77OSJOj6ISFAAlZrKkICbmFAUKKqgioTOMzBaBPUMYE1IBUVFMJYWcNOeJEZZSAoD/H6nuARRwdh/uAAAAAElFTkSuQmCC\n", "text/plain": [ "" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "img = cx.image(\"dog.jpg\", resize=(224,224))\n", "img" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Convert to array, and preprocess the array:" ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [], "source": [ "array = net.preprocess(cx.image_to_array(img))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And finally, propagate, and postprocess it:" ] }, { "cell_type": "code", "execution_count": 68, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "[('n02100236', 'German_short-haired_pointer', 0.6061604619026184),\n", " ('n02099712', 'Labrador_retriever', 0.17321829497814178),\n", " ('n02109047', 'Great_Dane', 0.1112799122929573),\n", " ('n02100583', 'vizsla', 0.013886826112866402),\n", " ('n02099849', 'Chesapeake_Bay_retriever', 0.011956770904362202)]" ] }, "execution_count": 68, "metadata": {}, "output_type": "execute_result" } ], "source": [ "net.postprocess(net.propagate(array))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Is that a German_short-haired_pointer? Let's compare:" ] }, { "cell_type": "code", "execution_count": 69, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 69, "metadata": {}, "output_type": "execute_result" } ], "source": [ "show_category(\"n02100236\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That could be correct. To know for certain, we'd have to know what the target is for that image (or find it in the above pictures). You can download the training set of target categories and image URLs here:\n", "\n", "http://image-net.org/download-imageurls\n", "\n", "The fall 2011 dataset is 350 MB compressed, and 1.1 GB uncompressed. Searching through this file, we find that this image is actually 'n00015388_34057'. What is that? Let's see." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To explore all of the categories, we can download the JSON file describing them:" ] }, { "cell_type": "code", "execution_count": 70, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Using cached https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json as './imagenet_class_index.json'.\n" ] } ], "source": [ "cx.download(\"https://s3.amazonaws.com/deep-learning-models/image-models/imagenet_class_index.json\")" ] }, { "cell_type": "code", "execution_count": 71, "metadata": {}, "outputs": [], "source": [ "import json" ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [], "source": [ "data = json.load(open(\"imagenet_class_index.json\"))" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "1000" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(data)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And here is all 1,000 labels:" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Afghan_hound', 'African_chameleon', 'African_crocodile', 'African_elephant', 'African_grey', 'African_hunting_dog', 'Airedale', 'American_Staffordshire_terrier', 'American_alligator', 'American_black_bear', 'American_chameleon', 'American_coot', 'American_egret', 'American_lobster', 'Angora', 'Appenzeller', 'Arabian_camel', 'Arctic_fox', 'Australian_terrier', 'Band_Aid', 'Bedlington_terrier', 'Bernese_mountain_dog', 'Blenheim_spaniel', 'Border_collie', 'Border_terrier', 'Boston_bull', 'Bouvier_des_Flandres', 'Brabancon_griffon', 'Brittany_spaniel', 'CD_player', 'Cardigan', 'Chesapeake_Bay_retriever', 'Chihuahua', 'Christmas_stocking', 'Crock_Pot', 'Dandie_Dinmont', 'Doberman', 'Dungeness_crab', 'Dutch_oven', 'Egyptian_cat', 'English_foxhound', 'English_setter', 'English_springer', 'EntleBucher', 'Eskimo_dog', 'European_fire_salamander', 'European_gallinule', 'French_bulldog', 'French_horn', 'French_loaf', 'German_shepherd', 'German_short-haired_pointer', 'Gila_monster', 'Gordon_setter', 'Granny_Smith', 'Great_Dane', 'Great_Pyrenees', 'Greater_Swiss_Mountain_dog', 'Ibizan_hound', 'Indian_cobra', 'Indian_elephant', 'Irish_setter', 'Irish_terrier', 'Irish_water_spaniel', 'Irish_wolfhound', 'Italian_greyhound', 'Japanese_spaniel', 'Kerry_blue_terrier', 'Komodo_dragon', 'Labrador_retriever', 'Lakeland_terrier', 'Leonberg', 'Lhasa', 'Loafer', 'Madagascar_cat', 'Maltese_dog', 'Mexican_hairless', 'Model_T', 'Newfoundland', 'Norfolk_terrier', 'Norwegian_elkhound', 'Norwich_terrier', 'Old_English_sheepdog', 'Pekinese', 'Pembroke', 'Persian_cat', 'Petri_dish', 'Polaroid_camera', 'Pomeranian', 'Rhodesian_ridgeback', 'Rottweiler', 'Saint_Bernard', 'Saluki', 'Samoyed', 'Scotch_terrier', 'Scottish_deerhound', 'Sealyham_terrier', 'Shetland_sheepdog', 'Shih-Tzu', 'Siamese_cat', 'Siberian_husky', 'Staffordshire_bullterrier', 'Sussex_spaniel', 'Tibetan_mastiff', 'Tibetan_terrier', 'Walker_hound', 'Weimaraner', 'Welsh_springer_spaniel', 'West_Highland_white_terrier', 'Windsor_tie', 'Yorkshire_terrier', 'abacus', 'abaya', 'academic_gown', 'accordion', 'acorn', 'acorn_squash', 'acoustic_guitar', 'admiral', 'affenpinscher', 'agama', 'agaric', 'aircraft_carrier', 'airliner', 'airship', 'albatross', 'alligator_lizard', 'alp', 'altar', 'ambulance', 'amphibian', 'analog_clock', 'anemone_fish', 'ant', 'apiary', 'apron', 'armadillo', 'artichoke', 'ashcan', 'assault_rifle', 'axolotl', 'baboon', 'backpack', 'badger', 'bagel', 'bakery', 'balance_beam', 'bald_eagle', 'balloon', 'ballplayer', 'ballpoint', 'banana', 'banded_gecko', 'banjo', 'bannister', 'barbell', 'barber_chair', 'barbershop', 'barn', 'barn_spider', 'barometer', 'barracouta', 'barrel', 'barrow', 'baseball', 'basenji', 'basketball', 'basset', 'bassinet', 'bassoon', 'bath_towel', 'bathing_cap', 'bathtub', 'beach_wagon', 'beacon', 'beagle', 'beaker', 'bearskin', 'beaver', 'bee', 'bee_eater', 'beer_bottle', 'beer_glass', 'bell_cote', 'bell_pepper', 'bib', 'bicycle-built-for-two', 'bighorn', 'bikini', 'binder', 'binoculars', 'birdhouse', 'bison', 'bittern', 'black-and-tan_coonhound', 'black-footed_ferret', 'black_and_gold_garden_spider', 'black_grouse', 'black_stork', 'black_swan', 'black_widow', 'bloodhound', 'bluetick', 'boa_constrictor', 'boathouse', 'bobsled', 'bolete', 'bolo_tie', 'bonnet', 'book_jacket', 'bookcase', 'bookshop', 'borzoi', 'bottlecap', 'bow', 'bow_tie', 'box_turtle', 'boxer', 'brain_coral', 'brambling', 'brass', 'brassiere', 'breakwater', 'breastplate', 'briard', 'broccoli', 'broom', 'brown_bear', 'bubble', 'bucket', 'buckeye', 'buckle', 'bulbul', 'bull_mastiff', 'bullet_train', 'bulletproof_vest', 'bullfrog', 'burrito', 'bustard', 'butcher_shop', 'butternut_squash', 'cab', 'cabbage_butterfly', 'cairn', 'caldron', 'can_opener', 'candle', 'cannon', 'canoe', 'capuchin', 'car_mirror', 'car_wheel', 'carbonara', 'cardigan', 'cardoon', 'carousel', \"carpenter's_kit\", 'carton', 'cash_machine', 'cassette', 'cassette_player', 'castle', 'catamaran', 'cauliflower', 'cello', 'cellular_telephone', 'centipede', 'chain', 'chain_mail', 'chain_saw', 'chainlink_fence', 'chambered_nautilus', 'cheeseburger', 'cheetah', 'chest', 'chickadee', 'chiffonier', 'chime', 'chimpanzee', 'china_cabinet', 'chiton', 'chocolate_sauce', 'chow', 'church', 'cicada', 'cinema', 'cleaver', 'cliff', 'cliff_dwelling', 'cloak', 'clog', 'clumber', 'cock', 'cocker_spaniel', 'cockroach', 'cocktail_shaker', 'coffee_mug', 'coffeepot', 'coho', 'coil', 'collie', 'colobus', 'combination_lock', 'comic_book', 'common_iguana', 'common_newt', 'computer_keyboard', 'conch', 'confectionery', 'consomme', 'container_ship', 'convertible', 'coral_fungus', 'coral_reef', 'corkscrew', 'corn', 'cornet', 'coucal', 'cougar', 'cowboy_boot', 'cowboy_hat', 'coyote', 'cradle', 'crane', 'crane', 'crash_helmet', 'crate', 'crayfish', 'crib', 'cricket', 'croquet_ball', 'crossword_puzzle', 'crutch', 'cucumber', 'cuirass', 'cup', 'curly-coated_retriever', 'custard_apple', 'daisy', 'dalmatian', 'dam', 'damselfly', 'desk', 'desktop_computer', 'dhole', 'dial_telephone', 'diamondback', 'diaper', 'digital_clock', 'digital_watch', 'dingo', 'dining_table', 'dishrag', 'dishwasher', 'disk_brake', 'dock', 'dogsled', 'dome', 'doormat', 'dough', 'dowitcher', 'dragonfly', 'drake', 'drilling_platform', 'drum', 'drumstick', 'dugong', 'dumbbell', 'dung_beetle', 'ear', 'earthstar', 'echidna', 'eel', 'eft', 'eggnog', 'electric_fan', 'electric_guitar', 'electric_locomotive', 'electric_ray', 'entertainment_center', 'envelope', 'espresso', 'espresso_maker', 'face_powder', 'feather_boa', 'fiddler_crab', 'fig', 'file', 'fire_engine', 'fire_screen', 'fireboat', 'flagpole', 'flamingo', 'flat-coated_retriever', 'flatworm', 'flute', 'fly', 'folding_chair', 'football_helmet', 'forklift', 'fountain', 'fountain_pen', 'four-poster', 'fox_squirrel', 'freight_car', 'frilled_lizard', 'frying_pan', 'fur_coat', 'gar', 'garbage_truck', 'garden_spider', 'garter_snake', 'gas_pump', 'gasmask', 'gazelle', 'geyser', 'giant_panda', 'giant_schnauzer', 'gibbon', 'go-kart', 'goblet', 'golden_retriever', 'goldfinch', 'goldfish', 'golf_ball', 'golfcart', 'gondola', 'gong', 'goose', 'gorilla', 'gown', 'grand_piano', 'grasshopper', 'great_grey_owl', 'great_white_shark', 'green_lizard', 'green_mamba', 'green_snake', 'greenhouse', 'grey_fox', 'grey_whale', 'grille', 'grocery_store', 'groenendael', 'groom', 'ground_beetle', 'guacamole', 'guenon', 'guillotine', 'guinea_pig', 'gyromitra', 'hair_slide', 'hair_spray', 'half_track', 'hammer', 'hammerhead', 'hamper', 'hamster', 'hand-held_computer', 'hand_blower', 'handkerchief', 'hard_disc', 'hare', 'harmonica', 'harp', 'hartebeest', 'harvester', 'harvestman', 'hatchet', 'hay', 'head_cabbage', 'hen', 'hen-of-the-woods', 'hermit_crab', 'hip', 'hippopotamus', 'hog', 'hognose_snake', 'holster', 'home_theater', 'honeycomb', 'hook', 'hoopskirt', 'horizontal_bar', 'hornbill', 'horned_viper', 'horse_cart', 'hot_pot', 'hotdog', 'hourglass', 'house_finch', 'howler_monkey', 'hummingbird', 'hyena', 'iPod', 'ibex', 'ice_bear', 'ice_cream', 'ice_lolly', 'impala', 'indigo_bunting', 'indri', 'iron', 'isopod', 'jacamar', \"jack-o'-lantern\", 'jackfruit', 'jaguar', 'jay', 'jean', 'jeep', 'jellyfish', 'jersey', 'jigsaw_puzzle', 'jinrikisha', 'joystick', 'junco', 'keeshond', 'kelpie', 'killer_whale', 'kimono', 'king_crab', 'king_penguin', 'king_snake', 'kit_fox', 'kite', 'knee_pad', 'knot', 'koala', 'komondor', 'kuvasz', 'lab_coat', 'lacewing', 'ladle', 'ladybug', 'lakeside', 'lampshade', 'langur', 'laptop', 'lawn_mower', 'leaf_beetle', 'leafhopper', 'leatherback_turtle', 'lemon', 'lens_cap', 'leopard', 'lesser_panda', 'letter_opener', 'library', 'lifeboat', 'lighter', 'limousine', 'limpkin', 'liner', 'lion', 'lionfish', 'lipstick', 'little_blue_heron', 'llama', 'loggerhead', 'long-horned_beetle', 'lorikeet', 'lotion', 'loudspeaker', 'loupe', 'lumbermill', 'lycaenid', 'lynx', 'macaque', 'macaw', 'magnetic_compass', 'magpie', 'mailbag', 'mailbox', 'maillot', 'maillot', 'malamute', 'malinois', 'manhole_cover', 'mantis', 'maraca', 'marimba', 'marmoset', 'marmot', 'mashed_potato', 'mask', 'matchstick', 'maypole', 'maze', 'measuring_cup', 'meat_loaf', 'medicine_chest', 'meerkat', 'megalith', 'menu', 'microphone', 'microwave', 'military_uniform', 'milk_can', 'miniature_pinscher', 'miniature_poodle', 'miniature_schnauzer', 'minibus', 'miniskirt', 'minivan', 'mink', 'missile', 'mitten', 'mixing_bowl', 'mobile_home', 'modem', 'monarch', 'monastery', 'mongoose', 'monitor', 'moped', 'mortar', 'mortarboard', 'mosque', 'mosquito_net', 'motor_scooter', 'mountain_bike', 'mountain_tent', 'mouse', 'mousetrap', 'moving_van', 'mud_turtle', 'mushroom', 'muzzle', 'nail', 'neck_brace', 'necklace', 'nematode', 'night_snake', 'nipple', 'notebook', 'obelisk', 'oboe', 'ocarina', 'odometer', 'oil_filter', 'orange', 'orangutan', 'organ', 'oscilloscope', 'ostrich', 'otter', 'otterhound', 'overskirt', 'ox', 'oxcart', 'oxygen_mask', 'oystercatcher', 'packet', 'paddle', 'paddlewheel', 'padlock', 'paintbrush', 'pajama', 'palace', 'panpipe', 'paper_towel', 'papillon', 'parachute', 'parallel_bars', 'park_bench', 'parking_meter', 'partridge', 'passenger_car', 'patas', 'patio', 'pay-phone', 'peacock', 'pedestal', 'pelican', 'pencil_box', 'pencil_sharpener', 'perfume', 'photocopier', 'pick', 'pickelhaube', 'picket_fence', 'pickup', 'pier', 'piggy_bank', 'pill_bottle', 'pillow', 'pineapple', 'ping-pong_ball', 'pinwheel', 'pirate', 'pitcher', 'pizza', 'plane', 'planetarium', 'plastic_bag', 'plate', 'plate_rack', 'platypus', 'plow', 'plunger', 'pole', 'polecat', 'police_van', 'pomegranate', 'poncho', 'pool_table', 'pop_bottle', 'porcupine', 'pot', 'potpie', \"potter's_wheel\", 'power_drill', 'prairie_chicken', 'prayer_rug', 'pretzel', 'printer', 'prison', 'proboscis_monkey', 'projectile', 'projector', 'promontory', 'ptarmigan', 'puck', 'puffer', 'pug', 'punching_bag', 'purse', 'quail', 'quill', 'quilt', 'racer', 'racket', 'radiator', 'radio', 'radio_telescope', 'rain_barrel', 'ram', 'rapeseed', 'recreational_vehicle', 'red-backed_sandpiper', 'red-breasted_merganser', 'red_fox', 'red_wine', 'red_wolf', 'redbone', 'redshank', 'reel', 'reflex_camera', 'refrigerator', 'remote_control', 'restaurant', 'revolver', 'rhinoceros_beetle', 'rifle', 'ringlet', 'ringneck_snake', 'robin', 'rock_beauty', 'rock_crab', 'rock_python', 'rocking_chair', 'rotisserie', 'rubber_eraser', 'ruddy_turnstone', 'ruffed_grouse', 'rugby_ball', 'rule', 'running_shoe', 'safe', 'safety_pin', 'saltshaker', 'sandal', 'sandbar', 'sarong', 'sax', 'scabbard', 'scale', 'schipperke', 'school_bus', 'schooner', 'scoreboard', 'scorpion', 'screen', 'screw', 'screwdriver', 'scuba_diver', 'sea_anemone', 'sea_cucumber', 'sea_lion', 'sea_slug', 'sea_snake', 'sea_urchin', 'seashore', 'seat_belt', 'sewing_machine', 'shield', 'shoe_shop', 'shoji', 'shopping_basket', 'shopping_cart', 'shovel', 'shower_cap', 'shower_curtain', 'siamang', 'sidewinder', 'silky_terrier', 'ski', 'ski_mask', 'skunk', 'sleeping_bag', 'slide_rule', 'sliding_door', 'slot', 'sloth_bear', 'slug', 'snail', 'snorkel', 'snow_leopard', 'snowmobile', 'snowplow', 'soap_dispenser', 'soccer_ball', 'sock', 'soft-coated_wheaten_terrier', 'solar_dish', 'sombrero', 'sorrel', 'soup_bowl', 'space_bar', 'space_heater', 'space_shuttle', 'spaghetti_squash', 'spatula', 'speedboat', 'spider_monkey', 'spider_web', 'spindle', 'spiny_lobster', 'spoonbill', 'sports_car', 'spotlight', 'spotted_salamander', 'squirrel_monkey', 'stage', 'standard_poodle', 'standard_schnauzer', 'starfish', 'steam_locomotive', 'steel_arch_bridge', 'steel_drum', 'stethoscope', 'stingray', 'stinkhorn', 'stole', 'stone_wall', 'stopwatch', 'stove', 'strainer', 'strawberry', 'street_sign', 'streetcar', 'stretcher', 'studio_couch', 'stupa', 'sturgeon', 'submarine', 'suit', 'sulphur-crested_cockatoo', 'sulphur_butterfly', 'sundial', 'sunglass', 'sunglasses', 'sunscreen', 'suspension_bridge', 'swab', 'sweatshirt', 'swimming_trunks', 'swing', 'switch', 'syringe', 'tabby', 'table_lamp', 'tailed_frog', 'tank', 'tape_player', 'tarantula', 'teapot', 'teddy', 'television', 'tench', 'tennis_ball', 'terrapin', 'thatch', 'theater_curtain', 'thimble', 'three-toed_sloth', 'thresher', 'throne', 'thunder_snake', 'tick', 'tiger', 'tiger_beetle', 'tiger_cat', 'tiger_shark', 'tile_roof', 'timber_wolf', 'titi', 'toaster', 'tobacco_shop', 'toilet_seat', 'toilet_tissue', 'torch', 'totem_pole', 'toucan', 'tow_truck', 'toy_poodle', 'toy_terrier', 'toyshop', 'tractor', 'traffic_light', 'trailer_truck', 'tray', 'tree_frog', 'trench_coat', 'triceratops', 'tricycle', 'trifle', 'trilobite', 'trimaran', 'tripod', 'triumphal_arch', 'trolleybus', 'trombone', 'tub', 'turnstile', 'tusker', 'typewriter_keyboard', 'umbrella', 'unicycle', 'upright', 'vacuum', 'valley', 'vase', 'vault', 'velvet', 'vending_machine', 'vestment', 'viaduct', 'vine_snake', 'violin', 'vizsla', 'volcano', 'volleyball', 'vulture', 'waffle_iron', 'walking_stick', 'wall_clock', 'wallaby', 'wallet', 'wardrobe', 'warplane', 'warthog', 'washbasin', 'washer', 'water_bottle', 'water_buffalo', 'water_jug', 'water_ouzel', 'water_snake', 'water_tower', 'weasel', 'web_site', 'weevil', 'whippet', 'whiptail', 'whiskey_jug', 'whistle', 'white_stork', 'white_wolf', 'wig', 'wild_boar', 'window_screen', 'window_shade', 'wine_bottle', 'wing', 'wire-haired_fox_terrier', 'wok', 'wolf_spider', 'wombat', 'wood_rabbit', 'wooden_spoon', 'wool', 'worm_fence', 'wreck', 'yawl', \"yellow_lady's_slipper\", 'yurt', 'zebra', 'zucchini']\n" ] } ], "source": [ "print(sorted([label for (category,label) in data.values()]))" ] }, { "cell_type": "code", "execution_count": 75, "metadata": {}, "outputs": [], "source": [ "labels = {label: category for (category,label) in data.values()}\n", "categories = {category:label for (category,label) in data.values()}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you don't recognize a label, you can look at the images in that dataset:" ] }, { "cell_type": "code", "execution_count": 76, "metadata": {}, "outputs": [], "source": [ "category = labels['rock_beauty']" ] }, { "cell_type": "code", "execution_count": 77, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", " \n", " " ], "text/plain": [ "" ] }, "execution_count": 77, "metadata": {}, "output_type": "execute_result" } ], "source": [ "show_category(category)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Thus, \"rock_beauty\" is a fish!" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we look up the dog picture's ID, we see that it is actually classified as \"Animal, animate being, beast, brute, creature, fauna\". However, it is not one of the 1,000 categories trained on. So, the network did very well on a novel image. " ] } ], "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": "3.6.3" } }, "nbformat": 4, "nbformat_minor": 2 }